{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d_ta3S5pv26v"
      },
      "source": [
        "<center><h1>A Comprehensive Analysis of Convolutional Neural Networks</h1>\n",
        "<h2>Matthias Bartolo</h2>\n",
        "\n",
        "</center>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DSPCom-KmApV"
      },
      "source": [
        "# Convolutional Neural Network (CNN)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qLGkt5qiyz4E"
      },
      "source": [
        "This assignment is an _edited_ version of Tensorflow's official [CNN tutorial](https://www.tensorflow.org/tutorials/images/cnn). The goal of this assignment is to go through the notebook and fill in the empty code cells when prompted. Moreover, you will be asked to write down short comments on any notable observations in the _Comments_ section under each question.\n",
        "\n",
        "As a precursor to starting this assignment, you can optionally go through the original notebook and read through any extra comments that might have been removed in this version.\n",
        "\n",
        "This notebook can be run locally, or can be run from <b>Google Colab</b> which can be found [here](https://colab.research.google.com/drive/1PztXT1Xe7AMkNpy-O4tUAkn2wDfeI41H?usp=sharing)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "m7KBpffWzlxH"
      },
      "source": [
        "### Import TensorFlow"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<font size=\"0.7\">\n",
        "\n",
        "```python\n",
        "conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0\n",
        "# Anything above 2.10 is not supported on the GPU on Windows Native\n",
        "python -m pip install \"tensorflow<2.11\"\n",
        "# Verify the installation:\n",
        "python -c \"import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))\"\n",
        "```\n",
        "\n",
        "</font>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T21:12:16.101447Z",
          "start_time": "2023-11-20T21:12:11.728762Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "hidden": true,
        "id": "iAve6DCL4JH4",
        "outputId": "53ccdfee-552a-49d6-a200-2e9d5b1e7758"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "2.10.1\n",
            "[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]\n"
          ]
        }
      ],
      "source": [
        "from time import time\n",
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "import keras\n",
        "import matplotlib.pyplot as plt\n",
        "from tensorflow.keras import datasets, layers, models\n",
        "from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau\n",
        "from tensorflow.keras.optimizers import SGD, RMSprop, Adagrad, Adadelta, Adam, Adamax, Nadam\n",
        "from sklearn.metrics import confusion_matrix, precision_score, recall_score, f1_score\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "print(tf.__version__)\n",
        "print(tf.config.list_physical_devices('GPU'))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "jRFxccghyMVo"
      },
      "source": [
        "### Download and prepare the CIFAR10 dataset\n",
        "\n",
        "\n",
        "The CIFAR10 dataset contains 60,000 color images in 10 classes, with 6,000 images in each class. The dataset is divided into 50,000 training images and 10,000 testing images. The classes are mutually exclusive and there is no overlap between them."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T21:12:17.697163Z",
          "start_time": "2023-11-20T21:12:16.104451Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 861
        },
        "execution": {
          "iopub.execute_input": "2023-10-27T06:01:17.356811Z",
          "iopub.status.busy": "2023-10-27T06:01:17.356346Z",
          "iopub.status.idle": "2023-10-27T06:01:23.459377Z",
          "shell.execute_reply": "2023-10-27T06:01:23.458566Z"
        },
        "hidden": true,
        "id": "JWoEqyMuXFF4",
        "outputId": "91dcfd10-0be9-461a-846a-b934cb34287c"
      },
      "outputs": [
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1000x1000 with 25 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Loading and splitting the dataset\n",
        "(train_images, train_labels), (test_images, test_labels) = datasets.cifar10.load_data()\n",
        "\n",
        "# Normalizing pixel values to be between 0 and 1\n",
        "train_images, test_images = train_images / 255.0, test_images / 255.0\n",
        "\n",
        "# Declaring the class names\n",
        "class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer',\n",
        "               'dog', 'frog', 'horse', 'ship', 'truck']\n",
        "\n",
        "# Plotting the first 25 images from the training set and displaying the class name below each image\n",
        "plt.figure(figsize=(10,10))\n",
        "for i in range(25):\n",
        "    plt.subplot(5,5,i+1)\n",
        "    plt.xticks([])\n",
        "    plt.yticks([])\n",
        "    plt.grid(False)\n",
        "    plt.imshow(train_images[i])\n",
        "    plt.xlabel(class_names[train_labels[i][0]])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Oewp-wYg31t9"
      },
      "source": [
        "### Creating the model's architecture"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T21:12:17.712163Z",
          "start_time": "2023-11-20T21:12:17.699166Z"
        },
        "code_folding": [],
        "id": "VRr5QWmnv267"
      },
      "outputs": [],
      "source": [
        "def fit(model, epochs:int=100, optimizer=Adam(clipnorm=1.0), verbose:int=1, batch_size:int=256, callbacks=EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True), colors:tuple=('blue','purple','green','cyan'), do_display:bool=False, do_save:bool=False, save_name:str='model'):\n",
        "    \"\"\"Function which fits a model to the training data and plots the training process.\n",
        "\n",
        "    Args:\n",
        "        model (keras.model): Model to fit\n",
        "        epochs (int, optional): Number of epochs to train for. Defaults to 10.\n",
        "        optimizer (str, optional): Optimizer to use. Defaults to 'adam'.\n",
        "        verbose (int, optional): Verbosity of training. Defaults to 1.\n",
        "        batch_size (int, optional): Batch size. Defaults to 32.\n",
        "        callbacks (list, optional): List of callbacks. Defaults to [EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)].\n",
        "        colors (tuple, optional): Colors to use for plotting. Defaults to ('blue','purple','green','cyan').`\n",
        "        do_save (bool, optional): Whether to save the model. Defaults to False.\n",
        "        save_name (str, optional): Name of the model to save. Defaults to 'model'.\n",
        "    \"\"\"\n",
        "\n",
        "    # Loading the model\n",
        "    model.compile(optimizer=optimizer,\n",
        "                    loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
        "                    metrics=['accuracy'])\n",
        "\n",
        "    # Printing the model summary\n",
        "    print(model.summary())\n",
        "\n",
        "    # Setting the start time\n",
        "    s=time()\n",
        "\n",
        "    # Training Model\n",
        "    history = model.fit(train_images, train_labels, epochs=epochs, verbose=verbose,\n",
        "                        validation_data=(test_images, test_labels), batch_size=batch_size, callbacks=callbacks)\n",
        "\n",
        "    # Printing the training time\n",
        "    print(f'\\033[36mTraining Time: {round(time()-s,2)}s\\033[0m')\n",
        "    print('*'*50)\n",
        "\n",
        "    # Plotting Training process\n",
        "    plt.plot(history.history['accuracy'], label='Train Accuracy', color = colors[0])\n",
        "    plt.plot(history.history['loss'], label = 'Train Loss', color = colors[1], linestyle='dashed')\n",
        "    plt.plot(history.history['val_accuracy'], label = 'Validation Accuracy', color = colors[2])\n",
        "    plt.plot(history.history['val_loss'], label = 'Validation Loss', color = colors[3], linestyle='dashed')\n",
        "    plt.xlabel('Epoch')\n",
        "    plt.ylabel('Accuracy')\n",
        "    plt.legend(loc='upper right')\n",
        "    plt.grid(True)\n",
        "    plt.show()\n",
        "\n",
        "    # Testing the model\n",
        "    test_loss, test_acc = model.evaluate(test_images,  test_labels, verbose=2)\n",
        "\n",
        "    # Calculating the Precision, Recall and F1 Score\n",
        "    y_pred = model.predict(test_images)\n",
        "    y_pred = [np.argmax(i) for i in y_pred]\n",
        "    \n",
        "    # Printing the test results\n",
        "    print(f'\\033[35mTest Accuracy: {round(test_acc,2)}\\033[0m')\n",
        "    print(f'\\033[34mTest Loss: {round(test_loss,2)}\\033[0m')\n",
        "    print(f'\\033[33mTest Precision: {round(precision_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "    print(f'\\033[32mTest Recall: {round(recall_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "    print(f'\\033[31mTest F1 Score: {round(f1_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "\n",
        "    # Plotting the confusion matrix\n",
        "    if do_display:\n",
        "        cm = confusion_matrix(test_labels, y_pred)\n",
        "        plt.figure(figsize=(10,7))\n",
        "        sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=class_names, yticklabels=class_names)\n",
        "        plt.ylabel('Actual')\n",
        "        plt.xlabel('Predicted')\n",
        "        plt.show()\n",
        "\n",
        "    # Saving the model\n",
        "    if do_save:\n",
        "        model.save(f'{save_name}.h5')\n",
        "\n",
        "    return test_acc"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3hQvqXpNyN3x"
      },
      "source": [
        "In the original notebook, the below model configuration was used. 3 Convolution Layers were used to extract visual features from the image. Then these features are passed to a normal Neural Network which will learn to classify the different class labels."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T21:13:42.961391Z",
          "start_time": "2023-11-20T21:12:42.562650Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 993
        },
        "execution": {
          "iopub.execute_input": "2023-10-27T06:01:24.118814Z",
          "iopub.status.busy": "2023-10-27T06:01:24.118571Z",
          "iopub.status.idle": "2023-10-27T06:01:26.532957Z",
          "shell.execute_reply": "2023-10-27T06:01:26.532276Z"
        },
        "id": "L9YmGQBQPrdn",
        "outputId": "7860ed4a-aa11-462f-e2a3-018ddeb23b09"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_3 (Conv2D)           (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_2 (MaxPooling  (None, 15, 15, 32)       0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_4 (Conv2D)           (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_3 (MaxPooling  (None, 6, 6, 64)         0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_5 (Conv2D)           (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_1 (Flatten)         (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 34.47s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.8409 - accuracy: 0.7204 - 363ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 756us/step\n",
            "\u001b[35mTest Accuracy: 0.72\u001b[0m\n",
            "\u001b[34mTest Loss: 0.84\u001b[0m\n",
            "\u001b[33mTest Precision: 0.72\u001b[0m\n",
            "\u001b[32mTest Recall: 0.72\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.72\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Creating the model\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7nY2bRtvv26-"
      },
      "source": [
        "### Q.1\n",
        "Create a model architecture that has only one (Conv2D+MaxPooling2D) layer. Then. pass this model to the predefined <code>fit</code> function, which will train the model, display the training progress, and evaluate on the test set.  \n",
        "\n",
        "Write down what differences you note between this model and the original one in the _Comments_ section."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:23:36.829059Z",
          "start_time": "2023-11-20T22:23:36.825059Z"
        },
        "code_folding": [],
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 871
        },
        "id": "rlK6RlTxv26_",
        "outputId": "017a2457-5e7c-432c-d46c-6065e9d4bd7e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_6 (Conv2D)           (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_4 (MaxPooling  (None, 15, 15, 32)       0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " flatten_2 (Flatten)         (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_5 (Dense)             (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 14.44s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0474 - accuracy: 0.6445 - 298ms/epoch - 952us/step\n",
            "313/313 [==============================] - 0s 614us/step\n",
            "\u001b[35mTest Accuracy: 0.64\u001b[0m\n",
            "\u001b[34mTest Loss: 1.05\u001b[0m\n",
            "\u001b[33mTest Precision: 0.65\u001b[0m\n",
            "\u001b[32mTest Recall: 0.64\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.64\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Creating the model\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8LvEshsJv26_"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qffkBruYv26_"
      },
      "source": [
        "* The model in the original notebook has 3 Convolutional Layers, while the model in this question has only 1 Convolutional Layer, thus the model in the original notebook is more complex and will take longer to train.\n",
        "* This model has a lower accuracy than the original model, this is because the model in the original notebook has more layers and thus can learn more complex features. Similarly, the same can said about the Precision, Recall and F1-Score metrics.\n",
        "* The model in the original notebook has a lower loss than the model in this question, this is because the model in the original notebook has more layers and thus can learn more complex features.\n",
        "* From the training and validation accuracy and loss curves, it was noted that the model in the original notebook has a higher training accuracy and a lower training loss than the model in this question."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "_-W2-7tJv26_"
      },
      "source": [
        "### Q.2\n",
        "The original CNN architecture used 32,64,64 output channels for each of the Convolution Layers respectively. Does increasing the output channels (eg. 128,256,256) boost performance on our small dataset? What happens when you decrease the output channels (eg. 8,16,16)?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:23:37.933408Z",
          "start_time": "2023-11-20T22:23:37.924065Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 993
        },
        "id": "fEg3KOHCv27A",
        "outputId": "0036db3d-3abf-47d9-85db-aa7e66e93dc8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_3\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_7 (Conv2D)           (None, 30, 30, 128)       3584      \n",
            "                                                                 \n",
            " max_pooling2d_5 (MaxPooling  (None, 15, 15, 128)      0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_8 (Conv2D)           (None, 13, 13, 256)       295168    \n",
            "                                                                 \n",
            " max_pooling2d_6 (MaxPooling  (None, 6, 6, 256)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_9 (Conv2D)           (None, 4, 4, 256)         590080    \n",
            "                                                                 \n",
            " flatten_3 (Flatten)         (None, 4096)              0         \n",
            "                                                                 \n",
            " dense_6 (Dense)             (None, 64)                262208    \n",
            "                                                                 \n",
            " dense_7 (Dense)             (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 1,151,690\n",
            "Trainable params: 1,151,690\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 74.87s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9280 - accuracy: 0.6736 - 436ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 884us/step\n",
            "\u001b[35mTest Accuracy: 0.67\u001b[0m\n",
            "\u001b[34mTest Loss: 0.93\u001b[0m\n",
            "\u001b[33mTest Precision: 0.67\u001b[0m\n",
            "\u001b[32mTest Recall: 0.67\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.67\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Creating the model\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(128, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(256, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(256, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "fit(model,verbose=0)\n",
        "\n",
        "del model\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:23:41.333291Z",
          "start_time": "2023-11-20T22:23:41.323100Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 993
        },
        "id": "e27915gEv27A",
        "outputId": "cdcc3888-93db-43e3-f4af-575ec9c5d860"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_4\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_10 (Conv2D)          (None, 30, 30, 8)         224       \n",
            "                                                                 \n",
            " max_pooling2d_7 (MaxPooling  (None, 15, 15, 8)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_11 (Conv2D)          (None, 13, 13, 16)        1168      \n",
            "                                                                 \n",
            " max_pooling2d_8 (MaxPooling  (None, 6, 6, 16)         0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_12 (Conv2D)          (None, 4, 4, 16)          2320      \n",
            "                                                                 \n",
            " flatten_4 (Flatten)         (None, 256)               0         \n",
            "                                                                 \n",
            " dense_8 (Dense)             (None, 64)                16448     \n",
            "                                                                 \n",
            " dense_9 (Dense)             (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 20,810\n",
            "Trainable params: 20,810\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 17.13s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0664 - accuracy: 0.6290 - 334ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 759us/step\n",
            "\u001b[35mTest Accuracy: 0.63\u001b[0m\n",
            "\u001b[34mTest Loss: 1.07\u001b[0m\n",
            "\u001b[33mTest Precision: 0.62\u001b[0m\n",
            "\u001b[32mTest Recall: 0.63\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.62\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "#Define Model with lower CNN output channels\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(8, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(16, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(16, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zBjZ4hGav27B"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tTOZVkvwv27B"
      },
      "source": [
        "* Increasing the output channels to 128,256,256 boosted the performance of the model, this is because the model can learn more complex features.\n",
        "* Decreasing the output channels to 8,16,16 decreased the performance of the model, this is because the model cannot learn complex features.\n",
        "* The model with 128,256,256 output channels has a higher accuracy, precision, recall and F1-Score than the model with 8,16,16 output channels, whilst respectively incurring a lower loss."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "VDedLLuXv27B"
      },
      "source": [
        "### Q.3\n",
        "The Convolution Layers apply the _convolution_ operation on the image. Max-Pooling slides (in this case) a <code>2x2</code> window across the resulting convolution and takes only the maximum value. Max-Pooling adds translation invariance to the model - meaning translating the image by a small amount does not significnatly hinder performance.\n",
        "\n",
        "Max-Pooling also helps reduce the size of the visual features, but having too large of a window might ignore more finer details of the object in the image. Show this empirically, by increasing the size of the <code>MaxPooling2D</code> sliding window and noting any changes in performance and time-efficiency. By looking at the original model's summary, we can see that the final <code>Conv2D</code> layer was outputting features in <code>4x4</code> matrices. Try and make the third <code>Conv2D</code> layer output <code>1x1</code> matrices of features instead, by editing some parameters of the <code>MaxPooling2D</code> layers.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:23:45.913606Z",
          "start_time": "2023-11-20T22:23:45.903607Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 993
        },
        "id": "WOWJXE5_v27B",
        "outputId": "2b6d8233-4c57-4e7d-d8b7-a9b101cf802f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_5\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_13 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_9 (MaxPooling  (None, 15, 15, 32)       0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_14 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_10 (MaxPoolin  (None, 13, 13, 64)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_15 (Conv2D)          (None, 11, 11, 64)        36928     \n",
            "                                                                 \n",
            " flatten_5 (Flatten)         (None, 7744)              0         \n",
            "                                                                 \n",
            " dense_10 (Dense)            (None, 64)                495680    \n",
            "                                                                 \n",
            " dense_11 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 552,650\n",
            "Trainable params: 552,650\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 32.36s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9403 - accuracy: 0.6682 - 348ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 833us/step\n",
            "\u001b[35mTest Accuracy: 0.67\u001b[0m\n",
            "\u001b[34mTest Loss: 0.94\u001b[0m\n",
            "\u001b[33mTest Precision: 0.67\u001b[0m\n",
            "\u001b[32mTest Recall: 0.67\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.67\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "#Define Model with bigger MaxPooling Window.\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((1, 1)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_7\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_19 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_13 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_20 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_14 (MaxPoolin  (None, 3, 4, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_21 (Conv2D)          (None, 1, 2, 64)          36928     \n",
            "                                                                 \n",
            " flatten_7 (Flatten)         (None, 128)               0         \n",
            "                                                                 \n",
            " dense_14 (Dense)            (None, 64)                8256      \n",
            "                                                                 \n",
            " dense_15 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 65,226\n",
            "Trainable params: 65,226\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 39.48s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACSQElEQVR4nOzdd3gU1frA8e/upvdeCSmQ0HsTkCa9RBG8IL0I6r1gQ34qFgSsV1ERRb0qRVTEBgpKMdJ7D9IJIfQE0nvZ7O7vj0k2WRIggSSb8n6eZ57dmTkzc/aQsG9OVRkMBgNCCCGEELWE2twZEEIIIYSoSBLcCCGEEKJWkeBGCCGEELWKBDdCCCGEqFUkuBFCCCFErSLBjRBCCCFqFQluhBBCCFGrWJg7A1VNr9dz7do1HB0dUalU5s6OEEIIIcrAYDCQnp6On58favXt62bqXHBz7do1AgICzJ0NIYQQQtyFy5cvU69evdumqXPBjaOjI6AUjpOTU4XeW6vV8tdff9GvXz8sLS0r9N41iZRDESkLhZSDQspBIeVQRMpCUZZySEtLIyAgwPg9fjt1LrgpbIpycnKqlODGzs4OJyenOv9DKuWgkLJQSDkopBwUUg5FpCwU5SmHsnQpkQ7FQgghhKhVJLgRQgghRK0iwY0QQgghapU61+dGCCFqMr1eT15enrmzcU+0Wi0WFhbk5OSg0+nMnR2zkrJQFJaDXq+vkPtJcCOEEDVEXl4eMTExFfYFYC4GgwEfHx8uX75c5+cbk7JQFJZDTEwMISEhWFlZ3dP9JLgRQogawGAwEBsbi0ajISAg4I6TmFVner2ejIwMHBwcavTnqAhSFgq9Xk96ejppaWnExsZSv379ewr2JLgRQogaID8/n6ysLPz8/LCzszN3du5JYdOajY1Nnf5CBymLQoXl4OnpSWxsLPn5+fc0NL7ulqQQQtQghf0x7rW6XojqrDCgudf+RxLcCCFEDVKX+2WI2q+ifr4luBFCCCFErSLBjRBCCCFqFQluhBBC1ChBQUEsWLDA3NkQ1ZgEN0IIISqFSqUqddNoNLi6ujJ37ty7uu+BAwd4/PHHKySPP/zwAxqNhmnTplXI/UT1IMFNBcrPzSfncg4Gg8HcWRFCCLOLjY01bgsWLMDJyYnY2FiuXr3K6dOnef75541pDQYD+fn5Zbqvp6dnhQ2HX7x4MS+88AI//PADOTk5FXLPu1XTZ56uTiS4qSC6PB3z3eZz+qnTZN7INHd2hBC1nMEAmZnm2cr695uPj49xc3Z2RqVSGfejoqJwdnZm/fr1tGvXDmtra3bu3El0dDQPPfQQ3t7eODg40KFDB/7++2+T+97cLKVSqfj66695+OGHsbOzIzQ0lDVr1twxfzExMezevZuXXnqJsLAwVq1aVSLNkiVLaNasGdbW1vj6+jJ9+nTjuZSUFJ544gm8vb2xsbGhefPm/PHHHwDMmTOH1q1bm9xrwYIFBAUFGfcnTpzIww8/zPz586lXrx6NGjUC4Ntvv6V9+/Y4Ojri4+PD6NGjuXHjhsm9Tpw4wZAhQ3BycsLR0ZFu3boRHR3N9u3bsbS0JC4uziT9s88+S7du3e5YJrWFBDcVRGOlwSnACYDEM4lmzo0QorbLygIHB/NsWVkV9zleeukl3n33XU6dOkXLli3JyMhg0KBBbNq0iSNHjjBgwADCw8O5dOnSbe8zd+5cRowYwT///MOgQYMYM2YMSUlJt71m6dKlDB48GGdnZ8aOHcvixYtNzn/++edMmzaNxx9/nGPHjrFmzRoaNmwIKJPODRw4kF27dvHdd99x8uRJ3n33XTQaTbk+/+bNmzl37hwbN240BkZarZY33niDo0eP8ttvv3HhwgUmTpxovObq1at0794da2trNm/ezKFDh5g8eTL5+fl0796dkJAQvv32W2N6rVbL999/z+TJk8uVt5pMZiiuQO6N3Ek5n0LimUQa9m5o7uwIIUS1N2/ePPr27Wvcd3Nzo1WrVsb9N954g9WrV7NmzRqTWpObTZw4kVGjRgHw9ttvs3DhQvbv38+AAQNKTa/X61m2bBmffPIJAI8++ijPP/88MTExBAcHA/Dmm2/y/PPP88wzzxiv69ChAwB///03+/fv59SpU4SFhQEQEhJS7s9vb2/PwoUL8fDwMM5QXDwICQkJYeHChXTo0MG4TMOiRYtwdnZm5cqVxknvCvMA8Nhjj7F06VL+7//+D4C1a9eSk5PDiBEjyp2/mkpqbiqQeyN3QGpuhBCVz84OMjLMs1Xk6g/t27c32c/IyGDmzJk0adIEFxcXHBwcOHXq1B1rblq2bGl8b29vj5OTU4mmnOIiIiLIzMxk0KBBAHh4eNC3b1+WLFkCwI0bN7h27Rq9e/cu9frIyEjq1atnElTcjebNm5eYdfrQoUOEh4dTv359HB0d6dGjB4CxDCIjI+nWrdstlyeYOHEi586dY+/evQAsW7aMESNGYG9vf095rUmk5qYCSXAjhKgqKhXUhu+qm79wZ86cSUREBPPnz6dhw4bY2tryyCOP3LGz7c1f9CqV6rarpy9evJikpCRsbW2Nx/R6Pf/88w9z5841OV6aO51Xq9UlBpdotdoS6W7+/JmZmfTv35/+/fvz/fff4+npyaVLl+jfv7+xDO70bC8vL8LDw1m6dCnBwcGsX7+erVu33vaa2kaCmwokwY0QQtybXbt2GTvaglKTc+HChQp9RmJiIr///jsrV66kWbNmxuM6nY7777+fv/76iwEDBhAUFMSmTZvo1atXiXu0bNmSK1eucPbs2VJrbzw9PYmLi8NgMBiXFIiMjLxj3k6fPk1iYiLvvvsuAQEBABw8eLDEs7/55hu0Wu0ta2+mTJnCqFGjqFevHg0aNKBr1653fHZtIs1SFagwuEm9mIo2u2SELoQQ4vZCQ0NZtWoVkZGRHD16lNGjR9+2BuZufPvtt7i7uzNixAiaN29u3Fq1asWgQYOMHYvnzJnDBx98wMKFC4mKiuLw4cPGPjo9evSge/fuDB8+nIiICGJiYli/fj0bNmwAoGfPnsTHx/Pee+8RHR3NokWLWL9+/R3zVr9+faysrPjkk084f/48a9as4Y033jBJM336dNLS0nj00Uc5ePAgUVFRfPvtt5w5c8aYpn///jg5OfHmm28yadKkiiq6GkOCmwpk52GHe193eszpgV5bsb+MQghRF3z44Ye4urrSpUsXwsPD6d+/P23btq3QZyxZsoSHH3641EUahw8fzpo1a0hISGDChAksWLCAzz77jGbNmjFkyBCioqKMaX/99Vc6dOjAqFGjaNq0KS+88IJxNesmTZrw2WefsWjRIlq1asX+/fuZOXPmHfPm6enJsmXL+Pnnn2natCnvvvsu8+fPN0nj7u7O5s2bycjIoEePHrRr146vvvrKpBZHrVYzceJEdDod48ePv9uiqrFUhjo241xaWhrOzs6kpqbi5ORUoffWarWsW7eOQYMG3bKqsC6QcigiZaGQclDcSznk5OQYR/LY2NhUUg6rhl6vJy0tDScnJ+MIobqqMsviscceIz4+vkxz/phbYTlYWVlx8eLFUn/Oy/P9LX1uhBBCiFokNTWVY8eOsWLFihoR2FQGCW4qmEFnIPFsIvocPX7t/MydHSGEEHXMQw89xP79+3nyySdN5hCqSyS4qWBph9L43/D/4dPGhycOP2Hu7AghhKhj6tqw79LU7cbOSmDtbw0ow8EN+jrVnUkIIYSoFiS4qWDW3taoLdVos7SkXU0zd3aEEEKIOkeCmwqmslDhGuIKQMLpBDPnRgghhKh7JLipBIWT+UlwI4QQQlQ9CW4qgQQ3QgghhPlIcFMJjGtMnZY1poQQoqIFBQWxYMECc2dDVGMS3FQC//v86fF6Dzo928ncWRFCCLNRqVSlbhqNBldXV+bOnXtX9z1w4ACPP/74PeWtZ8+ePPvss/d0D1F9yTw3lcA9zJ2ec3qaOxtCCGFWsbGxxvc//vgjs2fP5syZM+j1etLT0/H19TWeNxgM6HQ6LCzu/LXk6elZKfkVtYfU3AghhKgUPj4+xs3Z2RmVSmXcj4qKwtnZmfXr19OuXTusra3ZuXMn0dHRPPTQQ3h7e+Pg4ECHDh34+++/Te57c7OUSqXi66+/5uGHH8bOzo7Q0NB7Xnbg119/pVmzZlhbWxMUFMQHH3xgcv6zzz4jNDQUGxsbvL29eeSRR4znfvnlF1q0aIGtrS3u7u706dOHzMzMe8qPKB8JbipJ2tU0otZHEX8q3txZEULUYnmZebfc8nPyy5xWm60tU9qK9tJLL/Huu+9y6tQpWrZsSUZGBoMGDWLTpk0cOXKEAQMGEB4ezqVLl257n7lz5zJixAj++ecfBg0axJgxY0hKSrqrPB06dIgRI0bw6KOPcuzYMebMmcNrr73GsmXLADh48CBPP/008+bN48yZM2zYsIHu3bsDSm3VqFGjmDx5MqdOnWLr1q0MGzaMOrZGtdmZtVlq+/btvP/++xw6dIjY2FhWr17N0KFDb3tNbm4u8+bN47vvviMuLg5fX19mz57N5MmTqybTZbT9je0c+t8hur3SjQfefMDc2RFC1FLvOLxzy3Ohg0IZ/edo4/58r/los7Slpg3sEcjErRON+x8HfUxWQlaJdK8bXr/7zJZi3rx5Jusfubm50apVK+P+G2+8werVq1mzZg3Tp0+/5X0mTpzIqFGjAHj77bdZuHAh+/fvZ8CAAeXO04cffkjv3r157bXXAAgLC+PkyZO8//77TJw4kUuXLmFvb8+QIUNwdHQkMDCQNm3aAEpwk5+fz7BhwwgMDASgRYsW5c6DuDdmrbnJzMykVatWLFq0qMzXjBgxgk2bNrF48WLOnDnDDz/8QKNGjSoxl3fHo7EHIMPBhRDidtq3b2+yn5GRwcyZM2nSpAkuLi44ODhw6tSpO9bctGzZ0vje3t4eJycnbty4cVd5OnXqFF27djU51rVrV6KiotDpdPTt25fAwEBCQkIYN24c33//PVlZSiDYqlUrevfuTYsWLfjXv/7FV199RXJy8l3lQ9w9s9bcDBw4kIEDB5Y5/YYNG9i2bRvnz5/Hzc0NUNpebyc3N5fc3FzjflqasiSCVqtFqy39L5i7VXg/rVaLS0MXAOJPxVf4c6q74uVQ10lZKKQcFPdSDlqtFoPBgF6vR6/XG4+/mPbiLa9Ra9QmaWfEzbhlWpVaZZL2qfNPlZqueJryKLxOr9ebNNHY2tqa3PP555/n77//5r333qNhw4bY2toyYsQIcnNzTdIVlkUhjUZjsq9SqcjPz79tfm++x+3OFc+/vb09Bw8eZOvWrURERDB79mzmzJnDvn37cHFxYePGjezevZuIiAg++eQTXnnlFfbs2UNwcHCpz7lTXuqC4uVgMBjQarVoNBqTNOX5valRo6XWrFlD+/btee+99/j222+xt7fnwQcf5I033sDW1rbUa955551Shxv+9ddf2NnZVUo+IyIiyL2uBFSJZxP5c+2fqDSqSnlWdRYREWHuLFQbUhYKKQfF3ZSDhYUFPj4+ZGRkkJdXxr4vOqCs3WR0kK3NvmOynLScMt7wputycjAYDMY/MAulp6ejVhc1IuzYsYNHH32U3r17A0pNTkxMDJ07dzZeq9frycnJMblXdna2yb7BYCiRprj8/Hzy8vJKPd+gQQO2b99ucm7Lli00aNDApGNwx44d6dixI88++yxBQUH8+eefhIeHA0pTVIsWLXjmmWdo2bIlK1euZNq0abcsn/T09Fueq0syMzPJzs5m+/bt5Oeb9hkrrB0rixoV3Jw/f56dO3diY2PD6tWrSUhI4D//+Q+JiYksXbq01GtmzZrFjBlFf62kpaUREBBAv379cHJyqtD8abVaIiIi6Nu3LxYaC6KeiSI/J5/OTTrj1tCtQp9VnRUvB0tLS3Nnx6ykLBRSDop7KYecnBwuX76Mg4MDNjY2lZTDymNjY4NKpcLJycmk5sbR0dHk/+JGjRqxbt06hg8fjkqlYvbs2RgMBqysrIzp1Go1NjY2JtfZ2tqa7KtUqhJpirOwsCA1NZXz58+bHPf19eXFF1+kU6dOLFy4kBEjRrBnzx6+/vprPv30U5ycnPjjjz+IiYmhW7duuLq6sm7dOvR6Pa1bt+bUqVNs3ryZvn374uXlxb59+0hISKB169al5sVgMJCeno6joyMqVd37I7hQYTnY29tja2tL9+7dS/yc3ypQLU2NCm70ej0qlYrvv/8eZ2dnQOn49cgjj/DZZ5+VWntjbW2NtbV1ieOWlpaV9p9s4b3dG7lz/eh1UqNT8W7iXSnPqs4qs4xrGikLhZSD4m7KQafToVKpUKvVJjUdNUVhntVq06aymz/PRx99xOTJk7n//vvx8PDgxRdfJD093fjZC928X1q53KmsfvjhB3744QeTY2+88QavvvoqP/30E7Nnz+bNN9/E19eXefPmGQeuuLm58eGHHzJ37lxycnIIDQ3lhx9+oEWLFpw6dYodO3bw8ccfk5aWRmBgIB988AGDBw8uNQ+FZXHz56lripeDSqUq9XekPL8zNSq48fX1xd/f3xjYADRp0gSDwcCVK1cIDQ01Y+5K8mjswfWj10k4nUDYkDBzZ0cIIcxm4sSJTJw40bh///33o9PpSnyhBwUFsXnzZpNjNzfnXLhwwWS/tGHWKSkpt83P1q1bb3t++PDhDB8+vNRz999//y2vb9KkCRs2bLjtvUXlq1FhYteuXbl27RoZGRnGY2fPnkWtVlOvXj0z5qx0bae2ZejyoTR+uLG5syKEEELUGWYNbjIyMoiMjCQyMhKAmJgYIiMjjUP+Zs2axfjx443pR48ejbu7O5MmTeLkyZNs376d//u//2Py5Mm37FBsTiG9Q2g1rhVuDepOfxshhBDC3Mwa3Bw8eJA2bdoYJz+aMWMGbdq0Yfbs2YAyGVLxuQ0cHByIiIggJSWF9u3bM2bMGMLDw1m4cKFZ8i+EEEKI6sesfW569ux52ympC6e6Lq5x48Y1ajjp+U3nSTiVQMuxLbFxqXkjHIQQQoiapkZ1KK6J1jy2htSLqfi09qH+/fXNnR0hhBCi1qtRHYprIuMyDGdkGQYhhBCiKkhwU8ncG7kDssaUEEIIUVUkuKlkhTU3iacTzZwTIYQQom6Q4KaSyergQgghRNWS4KaSFQY3yeeTyc/Nv0NqIYQQN+vZsyfPPvuscT8oKIgFCxbc9hqVSsVvv/12z8+uqPuIqiXBTSVz8HHAytEKg95AcnSyubMjhBBVJjw8nAEDBpR6bvfu3Wg0Gv75559y3/fAgQM8/vjj95o9E3PmzKF169YljsfGxjJw4MAKfdatZGdn4+bmhoeHB7m5uVXyzNpKgptKplKpePjbh5m8azIuwS7mzo4QQlSZxx57jIiICK5cuVLi3IoVK2jfvj0tW7Ys9309PT2xs7OriCzekY+PT6mLL1eGX3/9lWbNmtG4cWOz1xYZDAby82tua4MEN1Wg8UONCegSgKWtrIYshKg7hgwZgqenZ4kJWTMyMvj999+ZNGkSiYmJjBo1Cn9/f+zs7GjRokWJlbpvdnOzVFRUFN27d8fGxoamTZuWOtHriy++SFhYGHZ2doSEhPDaa6+h1WoBZcLYuXPncvToUeOq1IV5vrlZ6tixYzzwwAPY2tri7u7O448/brLe4cSJExk6dCjz58/H19cXd3d3pk2bZnzW7SxevJixY8cyduxYFi9eXOL8iRMnGDJkCE5OTjg6OtKtWzeio6ON55csWUKzZs2wtrbG19eX6dOnA8pCoyqVyrjUESgLi6pUKuMCoFu3bkWlUrF+/XratWuHtbU1O3fuJDo6moceeghvb28cHBzo0KEDf//9t0m+cnNzefHFFwkICMDa2pqGDRuyePFiDAYDDRs2ZP78+SbpIyMjUalUnDt37o5lcrdkEj8hhKiBDAYDWdosszzbztIOlUp1x3QWFhaMHz+eZcuW8corrxiv+fnnn9HpdIwaNYqsrCzatWvHiy++iJOTE3/++Sfjxo2jQYMGdOzY8Y7P0Ov1DBs2DG9vb/bt20dqaqpJ/5xCjo6OLFu2DD8/P44dO8bUqVNxdHTkhRdeYOTIkRw/fpwNGzYYv7idnZ1L3CMzM5P+/fvTuXNnDhw4wI0bN5gyZQrTp083CeC2bNmCr68vW7Zs4dy5c4wcOZLWrVszderUW36O6Oho9uzZw6pVqzAYDDz33HNcvHiRwMBAAK5evUr37t3p2bMnmzdvxsnJiV27dhlrVz7//HNmzJjBu+++y8CBA0lNTWXXrl13LL+bvfTSS8yfP5+QkBBcXV25fPkygwYN4q233sLa2prly5cTHh7OmTNnqF9fmZh2/Pjx7Nmzh4ULF9KqVStiYmJISEhApVIxefJkli5dysyZM43PWLp0Kd27d6dhw4blzl9ZSXBTBTLjMzm16hR5GXl0eb6LubMjhKgFsrRZOLzjYJZnZ8zKwN7KvkxpJ0+ezPvvv8+2bdvo2bMnAN988w3h4eE4Ozvj6upq8sX31FNPsXHjRn766acyBTd///03p0+fZuPGjfj5+QHw9ttvl+gn8+qrrxrfBwUFMXPmTFauXMkLL7yAra0tDg4OWFhY4OPjc8tnrVixgpycHJYvX469vfL5P/30U8LDw/nvf/+Lt7c3AK6urnz66adoNBoaN27M4MGD2bRp022Dm6VLlzJw4EBcXV0B6N+/P0uXLmXOnDkALFq0CGdnZ1auXImlpdIKEBYWZrz+zTff5Pnnn+eZZ54xHuvQocMdy+9m8+bNo2/fvsZ9Nzc3WrVqZdx/4403WL16NWvWrGH69OmcPXuWn376iYiICPr06QNASEiIMf3EiROZPXs2+/fvp2PHjmi1WlasWFGiNqeiSbNUFciKz+LPJ/9k29xtt11LSwghapvGjRvTpUsXlixZAsC5c+fYsWMH48aNA0Cn0/HGG2/QokUL3NzccHBwYOPGjSaLJt/OqVOnCAgIMAY2AJ07dy6R7scff6Rr1674+Pjg4ODAq6++WuZnFH9Wq1atjIENQNeuXdHr9Zw5c8Z4rFmzZmg0GuO+r68vN27cuOV9dTody5cvZ+zYscZjY8eOZdmyZej1ekBpyunWrZsxsCnuxo0bXLt2jd69e5fr85Smffv2JvsZGRnMnDmTJk2a4OLigoODA6dOnTKWXWRkJBqNhh49epR6Pz8/PwYPHmz891+7di25ubn861//uue83o7U3FQB1wauqDQq8tLzyIjNwNHP0dxZEkLUcHaWdmTMyrhzwkp6dnk89thjPPXUUyxatIilS5fSoEEDunbtCsD777/Pxx9/zIIFC2jRogX29vY8++yz5OXlVVh+9+zZw5gxY5g7dy79+/c31oB88MEHFfaM4m4OQFQqlTFIKc2mTZu4evUqI0eONDmu0+nYtGkTffv2xdbW9pbX3+4cgFqt1GMU/+P6Vn2AigduADNnziQiIoL58+fTsGFDbG1teeSRR4z/Pnd6NsCUKVMYN24cH330EUuXLmXkyJGV3iFcam6qgIW1Ba4hSlWjTOYnhKgIKpUKeyt7s2xl6W9T3IgRI1Cr1axYsYLly5czadIk4z127drFQw89xNixY2nVqhUhISGcPXu2zPdu0qQJly9fJjY21nhs7969Jml2795NYGAgr7zyCu3btyc0NJSLFy+apLGyskKn093xWUePHiUzM9N4bNeuXajVaho1alTmPN/su+++Y+TIkURGRppsjz76qLFjccuWLdmxY0epQYmjoyNBQUFs2rSp1Pt7enoCmJRR8c7Ft7Nr1y4mTpzIww8/TIsWLfDx8eHChQvG8y1atECv17Nt27Zb3mPQoEHY29vz+eefs2HDBiZPnlymZ98LCW6qiMxULISoqxwcHBg5ciSzZs0iNjaWCRMmGM+FhoYSERHB7t27OXXqFE888QTXr18v87379OlDWFgYEyZM4OjRo+zYsYNXXnnFJE1oaCiXLl1i5cqVREdHs3DhQlavXm2SJigoiJiYGCIjI0lISCh1npkxY8ZgY2PDhAkTOH78OFu2bOGpp55i3Lhxxv425RUfH8+GDRsYP348zZs3N9nGjx/Pb7/9RlJSEtOnTyctLY1HH32UgwcPEhUVxbfffmtsDpszZw4ffPABCxcuJCoqisOHD/PJJ58ASu3Kfffdx7vvvsupU6fYtm2bSR+k2wkNDWXVqlVERkZy9OhRRo8ebVILFRQUxIQJE5g8eTK//fYbMTExbN26lZ9++smYRqPRMHHiRGbNmkVoaGipzYYVTYKbKmJcQFNWBxdC1EGPPfYYycnJ9O/f36R/zKuvvkrbtm3p378/PXv2xMfHh6FDh5b5vmq1mtWrV5OdnU3Hjh2ZMmUKb731lkmaBx98kOeee47p06fTunVrdu/ezWuvvWaSZvjw4QwYMIBevXrh6elZ6nB0Ozs7Nm7cSFJSEh06dOCRRx6hd+/efPrpp+UrjGK+/fZb7OzsSu0v07t3b2xtbfnuu+9wd3dn8+bNZGRk0KNHD9q1a8dXX31lbAKbMGECCxYs4LPPPqNZs2YMGTKEqKgo472WLFlCfn4+7dq149lnn+XNN98sU/4+/PBDXF1d6dKlC+Hh4fTv35+2bduapPn888955JFH+M9//kPjxo2ZOnWqSe0WKP/+eXl5TJo0qbxFdFdUhjrWwzUtLQ1nZ2dSU1NxcnKq0HtrtVrWrVvHoEGDSrS5Hl58mLVT1tKgXwPGbhx7izvUDrcrh7pGykIh5aC4l3LIyckhJiaG4OBgbGxsKimHVUOv15OWloaTk5OxP0hdVVfKYseOHfTu3ZvLly+XWstVWA5WVlZcvHix1J/z8nx/S4fiKiLNUkIIIeqa3Nxc4uPjmTNnDv/617/uuvmuvGpvmFjN+LT2YcLWCUzZN8XcWRFCCCGqxA8//EBgYCApKSm89957VfZcqbmpIlb2VgT1CDJ3NoQQQogqM3HiRCZOnFjlz5WaGyGEEELUKlJzU4Uu7bzEmTVn8GnjQ4tRLcydHSGEEKJWkpqbKnRl3xV2v7+bM7+duXNiIYQQQtwVCW6qkIyYEkIIISqfBDdVqDC4STybiF5363VGhBBCCHH3JLipQi5BLmisNOTn5JN6KdXc2RFCCCFqJQluqpBao8Y9rGAZBmmaEkKIMunZsyfPPvuscT8oKIgFCxbc9hqVSsVvv/12z8+uqPuIqiXBTRUzNk2dSTRzToQQonKFh4czYMCAUs/t3r0bjUbDP//8U+77HjhwgMcff/xes2dizpw5tG7dusTx2NhYBg4cWKHPutmKFStwc3Or1GfUNRLcVDH3xkrNTWKUBDdCiNrtscceIyIigitXrpQ4t2LFCtq3b0/Lli3LfV9PT0/s7OwqIot35OPjg7W1dZU8S1QcCW6qWMdpHXnu8nMM+nSQubMihBCVasiQIXh6erJs2TKT4xkZGfz+++9MmjSJxMRERo0ahb+/P3Z2drRo0aLUFbmLu7lZKioqiu7du2NjY0PTpk2JiIgocc2LL75IWFgYdnZ2hISE8Nprr6HVagFYtmwZc+fO5ejRo6hUKlQqlTHPNzdLHTt2jAceeABbW1vc3d15/PHHycjIMJ6fOHEiQ4cOZf78+fj6+uLu7s60adOMz7obly5d4qGHHsLBwQEnJydGjBjB9evXjeePHj1Kr169cHR0xMnJiXbt2nHw4EEALl68SHh4OK6urtjb29OsWTPWrVt313mpKWQSvyrm4ONg7iwIIWqRzNuc0wDF11W+XVo1YFuGtPZlzBeAhYUF48ePZ9myZbzyyiuoVCoAfv75Z3Q6HaNGjSIrK4t27drx4osv4uTkxJ9//sm4ceNo0KABHTt2vOMz9Ho9w4YNw9vbm3379pGammrSP6eQo6Mjy5Ytw8/Pj2PHjjF16lQcHR154YUXGDlyJMePH2fDhg38/fffADg7O5e4R2ZmJv3796dz584cOHCAGzduMGXKFKZPn24SwG3ZsgVfX1+2bNnCuXPnGDlyJK1bt2bq1KnlKL2iz1cY2Gzbto38/HymTZvGyJEj2bp1KwBjxoyhTZs2fP7552g0GiIjI42rzk+bNo28vDy2b9+Ovb09J0+exMGh9n8PSXAjhBA12O2+pgYBfxbb9wKybpG2B7C12H4QUNqwB0M58gYwefJk3n//fbZt20bPnj0B+OabbwgPD8fZ2RlXV1dmzpxpTP/UU0+xceNGfvrppzIFN3///TenT59m48aN+Pn5AfD222+X6Cfz6quvFn22oCBmzpzJypUreeGFF7C1tcXBwQELCwt8fHxu+awVK1aQk5PD8uXLsbdXwrxPP/2U8PBw/vvf/xpXvHZ1deXTTz9Fo9HQuHFjBg8ezKZNm+4quNm0aRPHjh0jJiaGgIAAAJYvX06zZs04cOAAHTp04NKlS/zf//0fjRs3BiA0NNR4/aVLlxg+fDgtWiiz4oeEhJQ7DzWRNEuZwe75u/lp+E/EHY0zd1aEEKJSNW7cmC5durBkyRIAzp07x44dOxg3bhwAOp2ON954gxYtWuDm5oaDgwMbN27k0qVLZbr/qVOnCAgIMAY2AJ07dy6R7scff6Rr1674+Pjg4ODAq6++WuZnFH9Wq1atjIENQNeuXdHr9Zw5UzTzfLNmzdBoNMZ9X19fbty4Ua5nFX9mQECAMbABaNq0KS4uLpw6dQqAGTNmMGXKFPr06cO7775LdHS0Me3TTz/Nm2++SdeuXXn99dfvqgN3TSTBTQXLtrhzZdi5Dec4teoUcUckuBFC3JuM22y/3pT2xm3Srr8p7YVbpLsbjz32GL/++ivp6eksXbqUBg0a0LVrVwDef/99Pv74Y1588UW2bNlCZGQk/fv3Jy8v7y6fVtKePXsYM2YMgwYN4o8//uDIkSO88sorFfqM4gqbhAqpVCr0+sqbuHXOnDmcOHGCwYMHs3nzZpo2bcrq1asBmDJlCufPn2fcuHEcO3aM9u3b88knn1RaXqoLCW4qiAF4Rq1mYv/+HLlDWuMyDGdkrhshxL2xv81mU460tmVMezdGjBiBWq1mxYoVLF++nEmTJhn73+zatYuHHnqIsWPH0qpVK0JCQjh79myZ792kSRMuX75MbGys8djevXtN0uzevZvAwEBeeeUV2rdvT2hoKBcvXjRJY2VlhU6nu+Ozjh49SmZmUY+kXbt2oVaradSoUZnzXB6Fn+/y5cvGYydPniQlJYWmTZsaj4WFhfHcc8/x119/MWzYMJYuXWo8FxAQwJNPPsmqVat4/vnn+eqrryolr9WJBDcVRAUkq1TkWljwebHqyNK4NyoYDn5ahoMLIWo/BwcHRo4cyaxZs4iNjWXChAnGc6GhoURERLB7925OnTrFE088YTIS6E769OlDWFgYEyZM4OjRo+zYsYNXXnnFJE1oaCiXLl1i5cqVREdHs3DhQmPNRqGgoCBiYmKIjIwkISGB3NzcEs8aM2YMNjY2TJgwgePHj7Nlyxaeeuopxo0bZ+xvc7d0Oh2RkZEm26lTp+jTpw8tWrRgzJgxHD58mP379zN+/Hh69OhB+/btyc7OZvr06WzdupWLFy+ya9cuDhw4QJMmTQB49tln2bhxIzExMRw+fJgtW7YYz9VmEtxUoCcLqh1XqlQk3yadLKAphKhrHnvsMZKTk+nfv79J/5hXX32Vtm3b0r9/f3r27ImPjw9Dhw4t833VajWrV68mOzubjh07MmXKFN566y2TNA8++CDPPfcc06dPp3Xr1uzevZvXXnvNJM3w4cMZMGAAvXr1wtPTs9Th6HZ2dmzcuJGkpCQ6dOjAI488Qu/evfn000/LVxilyMjIoE2bNiZbeHg4KpWK33//HVdXV7p3706fPn0ICQnhxx9/BECj0ZCYmMj48eMJCwtjxIgRDBw4kLlz5wJK0DRt2jSaNGnCgAEDCAsL47PPPrvn/FZ3KoPBUN7O7zVaWloazs7OpKam4uTkVKH3ztNqaZSVxQVnZz4AZtwiXerlVBbUX4DaQs3LWS+jsbx9TU9No9VqWbduHYMGDSrR9lzXSFkopBwU91IOOTk5xMTEEBwcjI3NzQ1ONYteryctLQ0nJyfU6rr9N7aUhaKwHKysrLh48WKpP+fl+f6uuyVZCVTAwJgYAD4DbtV9zMnfCUt7S/T5epLP366ORwghhBDlZdbgZvv27YSHh+Pn51fuxcl27dqFhYVFqWuBmFOPK1dwMhiIBkrOkalQqVV4NPLAwsaCtCtpVZk9IYQQotYza3CTmZlJq1atWLRoUbmuS0lJYfz48fTu3buScnb3bHQ6xhf0vfn8NunGbhzLrIxZhPSuGxMqCSGEEFXFrDMUDxw48K5WW33yyScZPXo0Go2mWi5F/6Rej7tGw+3morTzqJpF34QQQoi6psYtv7B06VLOnz/Pd999x5tvvnnH9Lm5uSZD+tLSlGYgrVZ7TwuZlabwfsFaLYUDESv2CTVDYTlUdPnWRFIWCikHxb2UQ35+PgaDAZ1OV6kTwlWFwnEsBoOhxn+WeyVloSgsB71ej8FgID8/v8TvSXl+b2pUcBMVFcVLL73Ejh07sCjDTMAA77zzjnFIXHF//fUXdnaVU3tS2oq0N8tPzefKV1fQJmpp+HZD44RWtUlZyqGukLJQSDko7qYc1Go1vr6+pKam1pogMT093dxZqDakLBRpaWlkZWWxZcuWEsFeVtatVkYrqcYENzqdjtGjRzN37lzCwsLKfN2sWbOYMaNoUHZaWhoBAQH069evwoeCa7VaIiIi6Nu3L5aWlmxSqfhQrWaMXs/om0bca7O1vD/xfTBAzw49sfe627k/q5+by6Euk7JQSDko7qUcDAYDV69eJTMzs8YPGzYYDGRmZmJvb18r/7ArDykLhcFgICMjg8zMTNzd3WnZsmWJ8ihseSmLGhPcpKenc/DgQY4cOcL06dOBouorCwsL/vrrLx544IES11lbW2NtbV3iuKWlZaX9J1t474MoI6bS1WomlJLGJciFlJgUUqNTcfF3qZS8mFNllnFNI2WhkHJQ3G05+Pv7ExMTYzIVf01kMBjIzs7G1ta2Tn+hg5RFocJysLe3JzAwECsrqxJpyvM7U2OCGycnJ44dO2Zy7LPPPmPz5s388ssvBAcHmylntzYFmAfsBQ4DbW8679HYg5SYFBJOJxDYPbDK8yeEqFmsrKwIDQ2ttAUfq4pWq2X79u107969zge7UhYKrVbLtm3b6Nu3b6mBTXmZNbjJyMjg3Llzxv3CdT3c3NyoX78+s2bN4urVqyxfvhy1Wk3z5s1Nrvfy8sLGxqbE8erCBxgOrESZ1O/rm857NPbg3PpzsgyDEKLM1Gp1jZ+hWKPRkJ+fj42NTZ3+Qgcpi0IajQadTldhza1mbbQ9ePCgcQ0NgBkzZtCmTRtmz54NQGxsLJcuXTJnFu/ZtILXFVBivSlZY0oIIYSoeGatuenZsye3W9pq2bJlt71+zpw5zJkzp2IzVcG6Ai2Bf4BlwHPFzklwI4QQQlS8mtvdvoZQAf8peH/zelMejT1QW6qxtFPWmRJCCCHEvasxHYprsjHAj8A4lOCmMKK087Tj5czatyq4EEIIYU4S3FQBB2BzKcdVKpUENkIIIUQFk2apaiL+ZDwZcRnmzoYQQghR40lwU4VSgYXApzcd3zZvG581/4yd/91phlwJIYQQtYsEN1VoM/AMysR+ucWO17uvHhjg0P8OkXkj0zyZE0IIIWoJCW6qUDhQD4gHfil2PKRvCP4d/cnPzmfPh3vMkzkhhBCilpDgpgpZAE8UvF9U7LhKpaLbq90AOLDoANlJ2VWdNSGEEKLWkOCmik0BLIE9wJFix8OGhOHdypu8jDz2frzXPJkTQgghagEJbqpY4XpToEzqV0ilUtH91e4A7F+4n5zUnKrOmhBCCFErSHBjBoXrTX2P6XpTTYY1waOJB2oLNfEn482QMyGEEKLmk0n8zKAr0BYIAtIA14LjKrWKEb+OwLm+M1b2977kuxBCCFEXSXBjBipgL0rfm5t5NvGs4twIIYQQtYs0S5lJaYFNcQa9gTNrzqDN1lZJfoQQQojaQoIbMzsHLCnl+MqHVrLyoZUcWXyklLNCCCGEuBUJbszoChAGTAWO33Su4aCGAOz67y50eboqzpkQQghRc0lwY0b1gMGAHngISCh2rs2kNjj4OpB2JY3IbyLNkT0hhBCiRpLgxsyWAiHAeWAYRWtOWdhY0PWFrgDsfGcn+ny9eTIohBBC1DAS3JiZB7AWcAJ2AE8ChoJz7R5vh52nHSkxKRz74Zi5siiEEELUKBLcVANNgZ9Q/jGWAe8XHLe0s6Tz850B2PHWDvQ6qb0RQggh7kSCm2qiP/BxwfutKP1wADr8pwM2rjZY2lmSEZdhlrwJIYQQNYlM4leNTAO8gYcpijqtHa2ZemAqriGuqFQq82VOCCGEqCEkuKlGVMC/iu0bgEzArYGbeTIkhBBC1EDSLFVNaYEngN5AdsGx3PRcDn99GIPBcOsLhRBCiDpOam6qqWvAr0ASMAn4Tqvjs2afkXY5DUd/R0IHhpo3g0IIIUQ1JTU31VQgsAplDaofgTctNTQb0QyA7W9sl9obIYQQ4hYkuKnGegBfFLyfC1x5pRsaaw1X9lzhwpYL5suYEEIIUY1JcFPNTQZmFrz/j6stdm8+AMD2N7ebLU9CCCFEdSbBTQ3wLvAgytIM85+9D52jFRe2XODSzktmzpkQQghR/UhwUwNogO+BbsBiCzUdHm0OwJ///pP8nHxzZk0IIYSodmS0VA3hAGxDmQsn860HOPP7Gfw7+cuCmkIIIcRNJLipQQrnJ7b3tGfoqWmcdbPFyqw5EkIIIaofCW5qoH+A+9xssQCiAQ+DAV2eDgtr+ecUQgghpM9NDdQcaAKkA69k5PH9wO9Z//R6M+dKCCGEqB4kuKmB1MD8gvdL7CzZF5PC4S8PE7U+ypzZEkIIIaoFCW5qqF7AEECnVnHoZ2W5zTWPrSE7Kfu21wkhhBC1nQQ3Ndh7KMPE97T0JnlMCzJiM1g3bZ25syWEEEKYlQQ3NVgTYGrB+61fDMFgoeL4yuOc+OmEObMlhBBCmJUENzXcHMAD6O9gRedXuwPK5H7psenmzJYQQghhNjJ2uIbzBi4CdoBuVjcu/H4GbaaW7MRsHH0dzZw7IYQQouqZteZm+/bthIeH4+fnh0ql4rfffrtt+lWrVtG3b188PT1xcnKic+fObNy4sWoyW43ZFbxqrDQ8+tujPHHkCbyae5k1T0IIIYS5mDW4yczMpFWrVixatKhM6bdv307fvn1Zt24dhw4dolevXoSHh3PkyJFKzmnNsA8YU9+ZNDtL4zGDwWC+DAkhhBBmYNZmqYEDBzJw4MAyp1+wYIHJ/ttvv83vv//O2rVradOmTanX5Obmkpuba9xPS0sDQKvVotVqy5/p2yi8X0XftywMwBMWFhxVqZin0/GeNp8DCw8QsymGkWtGolKr7niPimLOcqhupCwUUg4KKQeFlEMRKQtFWcqhPGWkMlSTP+1VKhWrV69m6NChZb5Gr9cTFBTECy+8wPTp00tNM2fOHObOnVvi+IoVK7CzsyvliprrqKcnr3fpgoVez4e/bCBlwiH0OXr8Jvnh9ZA0UwkhhKi5srKyGD16NKmpqTg5Od02bY0Obt577z3effddTp8+jZdX6V/epdXcBAQEkJCQcMfCKS+tVktERAR9+/bF0tLyzhdUggc1Gjao1QzT63nxfwdZ/5/1aKw1TN43Gc+mnlWSh+pQDtWFlIVCykEh5aCQcigiZaEoSzmkpaXh4eFRpuCmxo6WWrFiBXPnzuX333+/ZWADYG1tjbW1dYnjlpaWlfaDVJn3vpP3gb+AVWo1zz/ZgYZrozi3/hx/TP6Dx/Y+hsZSU2V5MWc5VDdSFgopB4WUg0LKoYiUheJ25VCe8qmR89ysXLmSKVOm8NNPP9GnTx9zZ6daaQ5MLng/U6Ui/OsHsXG1IfZwLDve2mHOrAkhhBBVosYFNz/88AOTJk3ihx9+YPDgwebOTrU0D2V4+B5gu58jgz9Tymn7m9u5euCqObMmhBBCVDqzNktlZGRw7tw5435MTAyRkZG4ublRv359Zs2axdWrV1m+fDmgNEVNmDCBjz/+mE6dOhEXFweAra0tzs7OZvkM1ZEv8C5KgDMQ0DzanNO/nebUqlPkJOeYN3NCCCFEJTNrzc3Bgwdp06aNcRj3jBkzaNOmDbNnzwYgNjaWS5cuGdN/+eWX5OfnM23aNHx9fY3bM888Y5b8V2dPAY+hLKwJMPizwYxcNZIG/RqYMVdCCCFE5TNrzU3Pnj1vO8ncsmXLTPa3bt1auRmqpbIBnZstYUPCjMcSzyaSfD6ZhgMami9jQgghRCWocX1uRPn8CTRCWWCzUEZcBt/2+5Yfwn/g2Ipj5smYEEIIUUkkuKnl1MBl4BMgpuCYrbst9e+vjz5fz6oxq9j3yT7zZVAIIYSoYBLc1HIDgD5AHvBywTGNpYaHlz9Mx6c6ArDh6Q1seX2LrEMlhBCiVpDgppZToUzspwJWAvsLj6tVDPh4AD3n9QRg+7ztrJu+DoNeAhwhhBA1mwQ3dUBrYELB+3BgGaBHWfKix2s9GPTZIFDBwc8Osv3N7WbKpRBCCFExJLipI94BmgA3gEnA4WLnOvy7A8N/GI5PGx86Tu9olvwJIYQQFaXcwU1QUBDz5s0zmX9GVH8+QCRKE9UTQPti5/KA5iObM/XAVGzdbI3H83PyqzKLQgghRIUod3Dz7LPPsmrVKkJCQujbty8rV640WXVbVF9WwEzgi2LHLgKBwAJApyn6cTjw2QG+bP8laVfTqjKLQgghxD27q+AmMjKS/fv306RJE5566il8fX2ZPn06hw8fvvMNRLXyGRAHPAe0ATYDeZl57Hx3J/En4lnSdQmJZxPNmkchhBCiPO66z03btm1ZuHAh165d4/XXX+frr7+mQ4cOtG7dmiVLlsiw4hribeB/gDtwAugNjLG3oveuybiFupF6MZWvO33N0W+Pyr+pEEKIGuGugxutVstPP/3Egw8+yPPPP0/79u35+uuvGT58OC+//DJjxoypyHyKSqIBHgeigOkoPxC/APcFOJNy+An8O/qTk5LDb+N/Y+WDK6WZSgghRLVX7rWlDh8+zNKlS/nhhx9Qq9WMHz+ejz76iMaNGxvTPPzww3To0KFCMyoqlyvKLMZTgaeBbUCegxWTdk5i13u72DZvO2f/OMu1Dtd4OvppLG0tzZrfQrGAG2Bt7owIIYSoNsod3HTo0IG+ffvy+eefM3ToUCwtS37JBQcH8+ijj1ZIBkXVaglsAVahzG6ssdTQ/ZXu7JnUhi+Ss+mZlst+W0s6YeZVV4EPUDpIdwW2I/MaCCGEUJT7++n8+fMEBgbeNo29vT1Lly6960wJ81IBw286tsPPkQt+jixDmQTQGeiSmEW74zeY2j2Q+ipVlebRgDK0HWBXQZ4mV2kOhBBCVFfl/mP3xo0b7NtXcqHFffv2cfDgwQrJlKh+vgSWAiNRmoFSgfXudrzZI4iQfD1XL6YY01ZFt2MVsAS4r2B/FiC9gYQQQsBdBDfTpk3j8uXLJY5fvXqVadOmVUimRPXjB0xEWZ/qBrBbp2fK7ssE7L1C4NYLfNPsM/Yv2o9Bb+ABjYa3OnbkeAXnIQWYC+gK9i1R+gaFFeTpzQp+nhBCiJqp3MHNyZMnadu2bYnjbdq04eTJkxWSKVG9aYDOGjVfdQngiLstL7+1A22mlvXT1/PJwyvZpVZzwNeXjhYWvAxkV8AzLwP3A3OAF4sdtwI+Kni/AGXUlxBCiLqt3MGNtbU1169fL3E8NjYWCwtzdzEVVc091J3Jmycw8JOBWNpZkrTmLE91/IoO0VfIV6l4B2gO/HUPzzgOdEaZh8cPGH/T+UHAQECLMimhEEKIuq3cwU2/fv2YNWsWqampxmMpKSm8/PLL9O3bt0IzJ2oGlVpFx+kd+fexfxPcK4gObja8fOwgv+TnUw84D/QHxgDJ5bz3NpQam6soC3/uQRnRdbMPUfoFzb/rTyGEEKK2KHdVy/z58+nevTuBgYG0adMGgMjISLy9vfn2228rPIOi5nANcWX83+PJTM5k085NPGgw0C05m2lRiazq4M9elapc89H8BIxDWdizG/AbSmfm0jQu2IQQQohyBzf+/v78888/fP/99xw9ehRbW1smTZrEqFGjSp3zRtQtKrUKa6eiEGbvCxE0//oIwcOa0OHVbti18QWUTsHngdBb3OcGytDuPJRh6d8BNmXMQxZwDOh0V59ACCFETXdXnWTs7e15/PHHKzovohZqOKAhUX9EwapTnFx1irVT29L3vb587WLDDJTOwa9QMnDxAn4ANqFM1qcp4/OigQdQhoVHAR4V8imEEELUJHfdA/jkyZNcunSJvLw8k+MPPvjgPWdK1B5NhzclpHcIES9GcPjLwxz+6jBn155l697H0Aa68CbwI/AFykzDlyiqzQkv2MojCHApuM/rwKKK+BBCCCFqlLuaofjhhx/m2LFjqFQq40rRqoIZanU63e0uF3WQjYsN4f8Lp+WYlqx9fC2JZxJpF/QxXf4YxSeDw4hCWY08CGXY+B4g+C6fpQE+BnqhBExPAi3u/SMIIYSoQco9WuqZZ54hODiYGzduYGdnx4kTJ9i+fTvt27dn69atlZBFUVsEdg/kycgn6f5ad5z8HHnmvnqcQlmNXAVcADJRal3uRU/gEUAPPEPVzJgshBCi+ih3cLNnzx7mzZuHh4cHarUatVrN/fffzzvvvMPTTz9dGXkUtYiFjQW95vXiqainsHO3wxlYaDCw8LMDTE7MYhfQowKe8z7KSuFbUEZZCSGEqDvKHdzodDocHR0B8PDw4Nq1awAEBgZy5syZis2dqLUs7YpG1p38+SSJ09YR5PsBV59eT3ps+j3fPwj4v4L3zwM593xHIYQQNUW5g5vmzZtz9OhRADp16sR7773Hrl27mDdvHiEhIRWeQVH7BXQJoNGDjdBr9ez/ZD8LQxay8fmNZFzPuKf7vogyo3Fr4N7DJSGEEDVFuYObV199Fb1eD8C8efOIiYmhW7durFu3joULF1Z4BkXt51TPiZG/jWRcxDjqda5Hfk4+ez/cy8KQhUS8GIE2W3tX93UAjgKrAM+KzLAQQohqrdyjpfr3729837BhQ06fPk1SUhKurq7GEVNClJdKpSKkTwjBvYOJ3hjNltlbuHbgGlF/RtHnnT53fV+Z50YIIeqectXcaLVaLCwsOH78uMlxNzc3CWxEhVCpVDQc0JAp+6Ywau0oBnw8AJVa+dnSZmnZ8c4OclLK34PmGjAB2F+x2b2jDGS0lhBCVLVyBTeWlpbUr19f5rIRlU6lUhE2JIyQ3kX9uA5+cZDNL2/m4+CP2f7mdnLTcst8v9eB5VTt0PAXATdLS6Y/8AAL1WqSqui5QghR15W7z80rr7zCyy+/TFKS/FctqpZ7I3c8m3mSk5LDlte28HHwx+z8707yMvLueO1cwB7YC6yopPzpUSYhLDSg4PWqoyMzNRr8gYkFeZDaHCGEqDzlDm4+/fRTtm/fjp+fH40aNaJt27YmmxCVJWxwGE8efZLhPwzHvZE72UnZbHppEx/4fcCGZzcYZ8sujR/KGlYAL6A0F1UULfAt0BwliCrUEzih1fLk0aO0NBjIAb4BOgNtKzgPeiRgEkKIQuXuUDx06NBKyIYQZaPWqGn+aHOa/qspx384zvY3tpN4NpGM2AyTfl86rQ6Npelym88BXwExKM1UbwB295CXHGAp8B7K7MqgBCxvovxiqVDWyRpw4QIfN23KYUtLvkBZS8sJZTRXoctAQBmeaQCuo6x6frzY6wmUAO5HlMBJCCHqsnIHN6+//npl5EOIclFr1LQc25IWo1sQsyUGe09747mE0wks7baU1pNa0+7xdrg1dAOUlcc/AIYBHwK/UhSUABwA6gE+KIHJraSjrFv1IRBXcMwTmAH8h9J/qVTAfQXbh8CNYufigYYoQcmTwAjAFkhFCVraA1YFaZ/i1ouBZgLet8n3vTKgrNvVBehYic8RQoh7dderggtRHajUKpNOxwDHVhwjKyGL3e/vZvf7uwnpG0L7f7enUXgjhlqoeQlYjNKMVNwQlKDDE2iFMvlfq4KtMVA4p/LrwEcF7wNQmrkmU/ZaILeCrdBulGalvQXbc4AjRWtsHQVaFrxvgBIoNURZELR5wWsQSkDkX8Y8lFc6ymf8BaiPUmPkVEnPEkKIe1Xu4EatVt922LeMpBLm1uP1Hvh39Ofg5weJWh/F+YjznI84j6OfI22mtGHO811428napPNvOuAOJKDUpPxdsBXqXWz/GeAvYCYwmqJalbv1EEqz1FLgf8BFILngnH9BngpNQandsb3DPX8C1qPUMFnfY/5OAMOBMygB3v+hBF8AfwCByMrrQojqpdzBzerVq032tVotR44c4ZtvvmHu3Lm3uEqIqqPWqAkbEkbYkDBSLqRw6MtDHFl8hPRr6RxYdIBus7qhQqlpMRgMqFQqHIGTKKOdjqPUlkQWvB7FtJYnEKXmoiJndvIBZqHUAu0quHdzwPWmdI7cWQLwGEr/n/MoMzS732W+fkAJqLJQAq2fUTpEg1I+IwAN8B1KkCaEENVBuYObhx4q+V/YI488QrNmzfjxxx957LHHynyv7du38/7773Po0CFiY2NZvXr1HTssb926lRkzZnDixAkCAgJ49dVXmThxYjk/hagrXIJc6P12b3rO6cnp306Tk5qDhY3yY2/QG/hfm//h286XlmNbEtgjEFuNmg5Ah2L30FNy4c3KmrJSA3S/x3t4oAQhI4DtKP18/gTCynEPLUofok8L9nujBDrFl7Goj9L/ZhMwFHgLJUCT6TyFEOZW7qHgt3LfffexadOmcl2TmZlJq1atWLToVl0kTcXExDB48GB69epFZGQkzz77LFOmTGHjxo13k2VRh2isNDQb0Yx2U9sZj13ec5nr/1wncmkky3svZ0H9Bfz1f38RdzTOZFi5mnsbVWUOA1D68gQC51ACnK3luF6D0jwGyhD6jZRcn8sNpelrWrF0YzCd60cIIcyhQjoUZ2dns3DhQvz9y9edceDAgQwcOLDM6b/44guCg4P54IMPAGjSpAk7d+7ko48+MlnzSoiyCOgcwMTtE/nnu384+fNJ0q+ls2f+HvbM34NnM0/6fdCPhv0bmjubd605sA+luWgf0A+lT8+k21xjQKl5UaPMybOPoskIS2OJUrvTApiOUrsTBfxG5XVuFkKIOyl3cHPzApkGg4H09HTs7Oz47rvvKjRzN9uzZw99+pguoti/f3+effbZW16Tm5tLbm7RNP1paWmA0ldIq7271aZvpfB+FX3fmqYmlYPffX743edHnw/6EL0hmuMrjnNu3TniT8SjtlYbP0NGbAYaGw22rnfqymvK3GXhhtL5+TGNhl/Uao7rdGj1+hLp9MB/1WrOqVR8rdOhQpmHpzdKE9WdTAYaqFSM1Gg4qFLxP52O14o9x9zlUF1IOSikHIpIWSjKUg7lKSOV4XbTupZi2bJlJsGNWq3G09OTTp064ep6c/fHslOpVHfscxMWFsakSZOYNWuW8di6desYPHgwWVlZ2NqW/OKZM2dOqR2dV6xYgZ1dTWtsEFUhPyOftANpuPZwNS7aefmLyyT9nYRdIzuc2jjh2NoR2xBb4/nqTg/sqFePbleulGiLzrC0ZEHbthz08QHgjV27aJGQUOIeZRFnZ8cfISFMOn4czZ2TCyFEmWVlZTF69GhSU1Nxcrr9ZBTlrrmpaZ13Z82axYwZM4z7aWlpBAQE0K9fvzsWTnlptVoiIiLo27cvlpaWd76glqoV5TDCdPe7j74jMT+RzBOZZJ7IJPa7WGw9bAnuHUxI3xBajGtR6hQJ1akshgC0VGbMyQVeUKsZZDDwqkbDBZUKa4OBhTodkzre2xR9kwHq1zc+5xu1mgm5uWyqJuVgTtXp58GcpByKSFkoylIOhS0vZVHu4Gbp0qU4ODjwr3/9y+T4zz//TFZWFhMmTCjvLcvMx8eH69evmxy7fv06Tk5OpdbaAFhbW2NtXXKmD0tLy0r7QarMe9cktakcJm2dRFJ0EtEbo4n+K5qYzTFkJ2Rz8seTXI+8TrvHijoqxx6OxaOJB5a2RZ+9upXFs8DnBRtAMPCrSkUbi4qd1/PfKBMmbrCxYYyFRbUrB3ORclBIORSRslDcrhzKUz7l/p/snXfe4X//+1+J415eXjz++OOVGtx07tyZdevWmRyLiIigc+fOt7hCiIrj1sANt/+40eE/HdBpdVzZe4Xov6Kxcy9q3tTl6VjafSn6fD2B3QMJ6h1EjuPNA8nN7zmUSQnPotToLKfknDoVoSfKHDh/qNX83b8//1Or6YIyeqszyrD1uiQOiLexMXc2hKj1yh3cXLp0ieDg4BLHAwMDuXTpUilX3FpGRgbnzp0z7sfExBAZGYmbmxv169dn1qxZXL16leXLlwPw5JNP8umnn/LCCy8wefJkNm/ezE8//cSff/5Z3o8hxD3RWGoI7BZIYLdAk+MpF1KwdbUl7UqacWZkgC8//ZImw5rQfFRzvJp5mSPLJhoCh1EmI+xIBc4JcZOxKIuHjjAYuGRhwVaKhqQ/gDJHTqETQCNq35ow54HVKJMp7rGwwNC/Pzv0euZTcni9EKJilPv/ES8vL/755x+CgoJMjh89ehR39/LNg3rw4EF69epl3C/sGzNhwgSWLVtGbGysScAUHBzMn3/+yXPPPcfHH39MvXr1+Prrr2UYuKg23MPcefbSsyScTiD6r2jO/nmWmM0xJJxKYMdbO7CwsTAGNzqtDpVahVpTWaHF7dmj1KBUtk7Amfx8vtyxA6vu3TlgYcEeoGuxNAkoQ9ftUYKtwpqd5igLnjpT8+YagqLJFI0K+mUtV6tZC+wAmlV9toSo9cod3IwaNYqnn34aR0dHundX5lLdtm0bzzzzDI8++mi57tWzZ09uN1hr2bJlpV5z5MiRcj1HiKqkUqnwbOKJZxNP2v2nHWt+WkNIfghRa6JoMqyJMd3p1adZ/9R6Gj3UiCbDmhD8QDAaq9o5xkgDBKanM8hg4MmCY8V/88+hLC2RDmwp2Ir7L8rSFACHUGZGtirYrIu9twIGF6SvSnpgP0rtTCuUyQwBehTk6X7gYWCwVsvPe/bwfbduWKpUNK7ifApRV5Q7uHnjjTe4cOECvXv3xqKg86Fer2f8+PG8/fbbFZ5BIWo6CwcLmg9qTpsJbUyOR62LIvNGJoe/Oszhrw5j7WRN2JAwGj/cmIYDGmLlcK9LclZvxceW3YeyWOgpYE+x7QLKiKviJZEL5BVspXmy2PtLKJ2nB6FMRljv3rNtpAW2oTQ5rQZiC473oCi48UJZiNWp2DWNkpPZm59PsqWlcbh8NvAhyqKsDhWYRyHqqnIHN1ZWVvz444+8+eabREZGYmtrS4sWLQgMDLzzxUIIo/CvwmkxpgWnV5/m9OrTZMRlcGzFMY6tOIaFjQUzrs7A1q18kwbWZBqUZqjmwNSbzhWv5WmPsop68SAnr9h+8RByPUXBBygzKQ9ECXa6oMywfCfJKIFL02LHBgGbC55ZyBGlc/YjN11f2oQTFoBfsf13gDdQZpD+BFmEVIh7ddd990JDQwkNDa3IvAhRp2gsNTTo24AGfRsw6NNBXNl3hVOrTnF61Wmsna1NApt1T63DxtmGsCFh+Hf0rzGTB1aU4p/WirLXwPQE5qIEOftQOlAfA95DCTrWowQ5oDSNnUAZQXam2BYPeKOMdCqkQwlsPFECkWEoHaRLTjpRNp2BIJSaqqEF91yIsjjp3foNaIASLNatnxYh7iK4GT58OB07duTFF180Of7ee+9x4MABfv755wrLnBB1hUqtIqBzAAGdA+j7Xl9yUoqGj+em53L4y8Po8nTseGsH9l72hA4OJWxIGCF9Q7B2vNuv1NqvETC7YEtEWYpiHcpCoEmY1sY8Tsm+PoUsgCyKOjUvQAlkAqFCZmIeiBJYvQm8D/wORKAEZs9Qeg2THmUk1nGUgC0TeLfY+dcKzjVA6e8zDKVzt3m6r9ccF1AC2g5mzoe4N+X+Od++fTuDBg0qcXzgwIFs3769QjIlRF2mUqlM1rBSW6h5cPGDNBvRDGsnazJvZBK5NJKfhv/E+x7vs+nlTbe5myjkDowCvkWphTkGuBQ737ZgexR4HViB0nk5HbiC6WitJkAIFRPYFLID3gYigW4owdT/Ac8XS/MNygzQHVCawUJRApfZKDU9umJpB6EEYNHAfJQaqnooEytursB8V6U3UfpQXa2Ee2eh/Ls3Qekzdas+XXVFCsoEnJOB71GC6Zqk3DU3GRkZWFmV7OhoaWlZrqmRhRBlY2lrScuxLWk5tiW6PB2Xdl7izNoznF17luToZOy97Y1p40/Gs3bqWrxbe+PTygef1j54NffC0k5mPi1OjfIlVtx8c2SkFM1QOiovQ/myfa7Yud8KtkLWKLVPzVH6E+UBhWHxf1Fqbzag9Dn6A6Xv0BcowcEDxe6TgzLkvro5CvigNAuCUjbDUD7DVOAl7n31eQPwC0oQebngWD2Umj0flFq0bSg1arVzLGORXJSaze+APynqU7YUJch/8hbXVUflDm5atGjBjz/+yOzZs02Or1y5kqZNm97iKiFERdBYaQh+IJjgB4Lp/2F/Es8kYudRVKcQeziWy7svc3n3ZeMxlVqFe5g7Pq196PhURwK6BJgj66IcVMAklEkQi4elI1GGmhcGMw24/X/iDigdnB9BCXw2owQ6fYuliSm4X3+UWqBuKKO8zDWvUBbwE0oAsw+YgxLkAbRGGVa/E/gU+JKiIOduRsIdA56maGLJ+iij1oah/BvEo/wbZABRKLV5jnfxnJrgENAHpcamUDOgO0r5jC92PJ/qP9lmufP32muvMWzYMKKjo3ngASX237RpEytWrOCXX36p8AwKIUqnUqnwaGy6gEHwA8EMWzGMuMg4rkdeJy4yjswbmSScTiDhdAItxrQwpj238Rx7P9pLUK8gGvRtgE9rnzrXUbm6u7m+rXwziZmyQhkOP+Cm4xtQAorio8pACW48gc9QmrhA6Rf0Z8Fxr4JXT5SalXsNhk6gjBZbDqQWHLNAqUEpFAxsR/mynVPwfhHwFUrfpPfK8bzjKMGSHqXW6iWUZsDin8MTWILyxf4HSuC3FqioPw+OAp+p1bRwrPqQ6RhwA+hdsN8UpVnTH6X5dizQEiXI01FUa6VHmYCzE0pzaHVdQqXcwU14eDi//fYbb7/9Nr/88gu2tra0atWKzZs34+bmVhl5FEKUkaOfIy1GtaDFqKIgJiMug7jIOOKOxuHXoWgA8pU9V5SFQDdGs+mlTdi62xLSO4TgPsE06NsAlyAXM3wCUdWeRJlnaDVKE8xplFqeLOAipl8Se4EXb75BAQ/ga4qGsV9CqQ0IRKkRcaf0UVsGlA7VG4sdC0bp4D2JoiapQiqgV8G2FaVWZzvl7xPSDKUGyxGlSfJWk5n8qyD/D6EEIx1RApz25XxecdEogcEPQIBaTf+MDOO5dCqvdugySu3T9yjBTSOUuaVUKM2Z+1H6cd3c/FZ8f1NBuv0ogegrwFNUv2bNu6pZGjx4MIMHDwaUJch/+OEHZs6cyaFDh9DpdHe4WghRlRx8HGg4oCENBzQ0Od58VHNs3Ww5//d5Lmy5QHZiNid+OsGJn04A8O/j/zYuFWHQG6RWp5ZSocwN1AaYhxJspKM0ydzAtG9SMDCu4Hh8sTS5KEtoFJ+AMAKYUmzfHiVICATqqdU0d3IyPj8A5Qv0QeAJlKCjLKNdeqL0h9l6Uz53o/QbmUVRLcsOlEDoJ5RATIXSf6ksX8qdUJrIwlGCgu4F9x9WhmuLi0WZz+grlKYdgAf1emNgpkVpImwJzCx4zr3+1l1AmTl7FbCr2HErlNqaDIqCqbLMmN0XZdHd51GCvRdQavfeRVlqpLr8L3HXzWbbt29n8eLF/Prrr/j5+TFs2DAWLVpUkXkTQlQij0YeeDTyoNPTndBpdVzdf1VZ7PPv86RcSMGzSdGyjr9P/p34k/GE9A0hpE8I9bvWr7VLRdR1KpQ5gJxQ+vQU9wCmHZFBCYZSUGoFQoodd0AJCi6ijE7LRKklOAWg0TC32MCU2SjD3otPbFgePW/an4MSXH0NPIbSzPVDwbk3gI8L3pentiEQpa/PoyjzI22j7MFNKkoH7wUos1GD0jz4FtBCr2ddwTJEu1DK8RJKM1gHlCBnGOX7sjZQFGS8iTLqqVAPlCan4YBrOe5ZXG+UWrlvUWpuLqCUy0cF+a4OTVXlCm7i4uJYtmwZixcvJi0tjREjRpCbm8tvv/0mnYmFqME0lhrqd61P/a716TmnJ7o8nbGmxmAwEP1XNBmxGVw7cI2db+/E2rlgqYihdWOpCHFrKpQvyZu/KEcWbKCMxrqMEuhcBGJ0OgLS041pK7qL+ysotSBbUTomF+ZzKvDqPdzXCViDEiw8Vo7rMikKbDqjzEjdo+Cctli6nijNgh+iDPs/gFKGQSij5iZT+vIcBpQpBFYBv6KMtOtYcO4RlGaw4SgTRFbUEiQaYCJKs92HFK3nVr7lsytPmee5CQ8Pp1GjRvzzzz8sWLCAa9eu8cknn1Rm3oQQZlK8VkalUjH1wFQeWvYQLce2xN7LntzUXI59f4yf//UzS7stNWNORU1gg9KXow9KUPC6Xo9bbu7tL7oHPVAmZNyKMgqsL3AQpcOy560vKxMLlKazwpqBPJR+SMU7PmtRajAK+VE0OeMuigKb0oShBGQXUZrR3FFqRp5BCXwK6VHWX/s/oCHKHE1votSM/Vos3QCUsphOxa6tVsgeZcqBKJQh4zWuWWr9+vU8/fTT/Pvf/5ZlF4SoY5z8nWg9oTWtJ7RGr9Nzdd9VTq0+xenVp2k4qKgvjzZby8oHV9JwYEMaP9wY1+C7rfgW4t714PaBREWYibIeWOFcQodQvuyjUZqxuhakm1bO+3qhNK+9gNJxdz9FnZh1KE1Va4qlt0HpmD0MZY2zquZbsFUXZQ5udu7cyeLFi2nXrh1NmjRh3LhxPProvQxMFELURGqNmoAuAQR0UZaK0GuLxqmc//u8cfvr+b/wbumtrHI+uCEGg+E2dxWiZpqKUiMThdKpufC3wQuls/W9skMZ0VZ8Ar3CpUQKF2sdhhLY2Je4uu4qc7PUfffdx1dffUVsbCxPPPEEK1euxM/PD71eT0REBOnF2k+FEHWDSqUyacLy7+DPgI8HENQrCJVGxfV/rrNt7jYWd1zM8fHHidkUY0ybk5pjsoaWEDVRC5SRVB1RAhsnlOahaJRJEStDPkqtzQ2Uod2PIIHNzco9Wsre3p7JkyczefJkzpw5w+LFi3n33Xd56aWX6Nu3L2vWrLnzTYQQtZKDjwOdnu5Ep6c7kZWYxdk/znLmtzOc23iO/PR8k6Uijiw+wl/P/4VTPSe8Wnjh1bxga+GFR2MPLG1lyQhRM/ig9O+JQGmGquxOtX7c/ciyuuKeZlBu1KgR7733Hu+88w5r165lyZIlFZUvIUQNZ+duZ+ynk52ezW9f/4Z7o6L/9tOupBlf066kcW79OeM5lVrFE0eewLulMoXb9WPXyU7Mxi3UDUc/R1Sq6tJtUQiFLco8PaJ6qJDlITQaDUOHDmXo0KEVcTshRC1jYWOBXYgdGsuiJqz+H/anx+we3DhxgxvHC7ZjypadnI1rg6LOyAc+O8ChLw4p97K1wK2hG+6h7rg2dMU91J3mjzaX4ehCCKPqvvaVEKIWs3GxMc6vU8hgMJAVn4WVfVGwYutqi2sDV1IupJCfnW8Mggo1G9HM+H7Xe7tIOJ2AXwc//Dv449XCCwtr+a9OiLpEfuOFENWKSqXC3su0e2Tvt3vT++3e6LQ6Ui6kkHQuiaSoJBKjEsm6kYW1k7Ux7fm/z3M+4jyRSyMBZc4e75be+HXww6+DH63GtUJtUeaxFEKIGkiCGyFEjaGx1OAe6o57qLsy9rUUXV/oin8nf64duMa1A9fITsrm2sFrXDt4DdufbGk9sbUxbeSySDTWGvw7+uMa4ip9eYSoJSS4EULUKiF9lPWvQGniSolJ4eqBq1w7cA2VWmUSwGx9fSupl1IBsHa2xqe1Dz5tfPBt64tfez+T9bWEEDWHBDdCiFpLpVLhGuKKa4grzUc2Nzmnz9cTFh7GtQPXiIuMIzc1l4vbLnJx20UA/Dv5M2Vv0brWx388jmuIK94tvLGwkf86hajO5DdUCFEnqS3UDPp0EAC6PB3xp+KJOxJH7OFY4o7E4X+fvzGtNkvLqtGrMOgNqDQqPJt44tPGB48mHjgHOOPd0ts4bF0IYX4S3Agh6jyNlQafVj74tPIx6ZNTKDs5m5A+IcQeiSUrPss4dL1QmyltePArZZaTvMw8lnVfhlM9JxzrOeIc4IxTPSecApyw87YzWa5CCFE5JLgRQog7cPJ3YuzGsRgMBtKvphN7RKndST6fTNrlNHzbFC0ZmHYljdjDscQeji31Xi7dXOAh5b1Bb+D6set4NfOSEVxCVCAJboQQooxUKpVSC1PPiUbhjUpN4+jnyKi1o0i7kkbq5VTSr6STejlVmYn5chp2DeyMaZPOJfG/1v/DwtYC3za++Lb3xb+DP34d/HAPdUelltFbQtwNCW6EEKICWTtaEzYkrNRzeXl5rFu7zrifeikVaydrctNyubz7Mpd3Xy66j5M1/T7oR9spbQGlA7RKrZKAR4gykOBGCCGqiEqlQmVRFJyE9AnhxeQXSYxKVOblOajMzRN7JJbctFzsPIpqeaLWR/HrqF/xbuGNV0svvFt649PKB68WXtg425jj4whRbUlwI4QQZqRSq/Bo5IFHIw9ajm0JKLU0N07cwDW4aH2tG8duoM3UcmXvFa7svWJyD+dAZ4YuG0pQzyAA8nPyUVuqUWukH4+omyS4EUKIakZtocanlY/Jsa4vdKXxw425/s91ZTuqvKZdTiP1Yiq27rbGtAe/OMimlzfhEuiCo58jjn6OOPg6GN+H9A3B1tX25scKUWtIcCOEEDWA2kKNZxNPPJt4mkxImJ2czY1jN/Bo7GE8duPEDfKz80k4nUDC6YQS9/r3sX8bg5u9C/Zy+KvDxsDHOcgZr+ZeeDX3wq2hm8lK7kLUFBLcCCFEDWbraktg90CTY0O+GELXF7qSdiWNjNgM0q+lm2yOfo7GtEnnkog/GU/8yfgS99ZYaZh6cCreLZQJClMupKDX6XENdpWOzaJak+BGCCFqGbVGXbTA6B0UNnelX0sn/Wo6iVGJxJ+IJ/5EPHkZebiGFPX72fXeLg5+fhALWws8m3ri1dwLz2aeeDb1xK2hG24N3aSfj6gWJLgRQog6zLm+M871nUscN+gNpF1Nw8reynhMl6dDY60hPzuf2EOxxB4ynajwpbSXsHa0BuCf7/8h9VIqbg3ccG3gilsDN2xcZFSXqBoS3AghhChBpVbhHGAa9Dz49YMM+WIIyeeTjUtQxJ+IJ/6UUstTGNgAHP3mKOcjzptcb+tmi2sDV5yDnLEaWRQ0Xd1/FW22FltXW2xcbbBxscHKwcpkBXchykOCGyGEEGWmtlDjHuaOe5g7TYY1uWW6Rg81wsHHgeToZJKik8i8nkl2UjbZSdkkxyTTaEzRDM9/v/Q3F7ZcKPEcGxcb7Dzt+M+J/xgDndO/nSY7ORuPxsrweVs3GfUlSpLgRgghRIXrOK0jTCvaz8vII/m8Euhkp2RzmaLZmJ3rO+PeyJ2c5Byyk7PRa/Xo8/VkJWRhMBhManD2LdxnEgjZedrh0dgD90bueDT2oPNznaWzs5DgRgghROWzcrDCu6U33i290Wq1XF5XFNwMXTbU+N5gMJCfnU92cjY5yTlos7Um96l/f33UGjUJpxNIu5JGVnwWl+IvcWnHJRx8HOjyfBdj2rVPrCU7IRv3xkrg49nEE/dG7ibNZ6J2qhbBzaJFi3j//feJi4ujVatWfPLJJ3Ts2PGW6RcsWMDnn3/OpUuX8PDw4JFHHuGdd97BxkY6qwkhRE2mUqmwtLPE0s4SJ3+nEud7zetlfJ+XkUfi2URlPp8zCSVqbKI3RJN6KbXEPZzqOVGvcz3+9dO/jMdyUnKwdraWfj61hNmDmx9//JEZM2bwxRdf0KlTJxYsWED//v05c+YMXl5eJdKvWLGCl156iSVLltClSxfOnj3LxIkTUalUfPjhh2b4BEIIIczBysEK37a++Lb1LfV8+FfhxJ+MN05mmHA6gczrmaRdSSP9arpJ2i/bf0lWQpaxhsctzA2XQBecApxwDXbFqV7JQEtUX2YPbj788EOmTp3KpEmTAPjiiy/4888/WbJkCS+99FKJ9Lt376Zr166MHj0agKCgIEaNGsW+ffuqNN9CCCGqtwb9GtCgXwOTY9lJ2SScScCgMxiP6fJ0pF5KRa/Vc3XfVa7uu2pyTUDXACbvnGzc/+Pff2BpZ4lzgDNOAU7KcPoAZ+y97KW/TzVh1uAmLy+PQ4cOMWvWLOMxtVpNnz592LNnT6nXdOnShe+++479+/fTsWNHzp8/z7p16xg3blyp6XNzc8nNzTXup6WlAaDVatFqtaVec7cK71fR961ppByKSFkopBwUUg4Kc5aDhaMFPu19TJ+vgplJM0mKSiLxTCKJpxNJOpek1PBcScclxMWYVp+v5/BXh02Co0JqSzVh4WEMWznMeGzdv9ehsdJg46IMcS8c6m7jaoODrwNOwU6meamjyvIzUZ4yUhkMhpL/QlXk2rVr+Pv7s3v3bjp37mw8/sILL7Bt27Zb1sYsXLiQmTNnKh3P8vN58skn+fzzz0tNO2fOHObOnVvi+IoVK7Czs6uYDyKEEKJO0OfpSdyYSF5CHtp4LXmJeWgTtGiTtaAH5y7OBL8QDCgTIR4dfhRu8S3r0NKBhvMaGvev/3IdS09L7BraYe1rLbVAN8nKymL06NGkpqbi5HT7ZkKzN0uV19atW3n77bf57LPP6NSpE+fOneOZZ57hjTfe4LXXXiuRftasWcyYMcO4n5aWRkBAAP369btj4ZSXVqslIiKCvn37YmlpWaH3rkmkHIpIWSikHBRSDooaXw5DSx7SaXVkxmWCCmP/HJ1Wh8d/PchJziEnpdiWrGwBHQLo27cvERER9OjSg4XDFmLQK5GQtbM1Pm198Gvnh297X/w6+tXqfj9l+ZkobHkpC7MGNx4eHmg0Gq5fv25y/Pr16/j4+JR6zWuvvca4ceOYMmUKAC1atCAzM5PHH3+cV155BbXadF0Ta2trrK1LDvuztLSstF+qyrx3TSLlUETKQiHloJByUNSmcrC0tMQmxKbEsfv/7/7bXmdsatFCh+kduHbgGnFH4shNzeXilotc3HIRgJZjW/Lwtw8DoNfpOfvHWTwaeeAa4orGqvas3H67n4ny/KyYNbixsrKiXbt2bNq0iaFDhwKg1+vZtGkT06dPL/WarKysEgGMRqP8w5qxhU0IIYS4a/ae9gz8eCCg1PjEn4jn2sFrXD1wlWsHrlGvSz1j2oRTCfw49EcAVBoVrsGuuIe54xbmhnuYO4HdA/FqVnK0cV1i9mapGTNmMGHCBNq3b0/Hjh1ZsGABmZmZxtFT48ePx9/fn3feeQeA8PBwPvzwQ9q0aWNslnrttdcIDw83BjlCCCFETaWx1ODT2gef1j60ndK2xPns5Gx82/qSeDaRvIw8ks4lkXQuCdYp53u/09sY3CRFJ7Fp1ibcw9xxCXbBwtoClUaF2kKN2kKNT2sfXINdjfe9ceyG8ZzaQo3GSoNzoHONm/jQ7MHNyJEjiY+PZ/bs2cTFxdG6dWs2bNiAt7c3AJcuXTKpqXn11VdRqVS8+uqrXL16FU9PT8LDw3nrrbfM9RGEEEKIKhPYLZDHDz2OwWAgIzaDxLOJymSGZxJIOpuEb7uieX9uHLvByZ9P3vJegz8fTPsn2wMQeziWb/t8W2o65/rOdH+tuzHY0uXpyM/Jx9qpegY9Zg9uAKZPn37LZqitW7ea7FtYWPD666/z+uuvV0HOhBBCiOpJpVLh6OeIo58jQT2DSk3j1dyLfh/0I/FsImmX09Dn6002B18HY1oLGwvcG7mbnM/Pzic7KZvUS6moLYoqGi7vucw3Pb/BKcAJz6aeeDbzxLOpJ17NvPBo4oGNs3lXDKgWwY0QQgghKp5bQzc6z+h854RA/a71mX66ZEVDVmIW8SfjcQ91Nx5Ljk4GIO1yGmmX04jeGG08Z+VoxUupL5l1KQsJboQQQghxS3budgR2CzQ51mZyGxo/3Jj4k/HKdiLe+N6pnpPZ1+iS4EYIIYQQ5Wbrakv9rvWp37W+yfH83Hwz5aiI+s5JhBBCCCHKxsLa/PUmEtwIIYQQolaR4EYIIYQQtYoEN0IIIYSoVSS4EUIIIUStYv5eP0IIIYSoUfR6yMyE1FRlS0szfW9hAQWrKJmFBDdCCCFEDWAwQHIy3LihvGZkKFtmZtne5+SAWq1sGk3ZNpWq9CAmLU3Jz634+0twI4QQQtQ5BgPk5kJSkg2RkZCUpAQu168rW+H74q/55p9CxoRGA87ORZuTk/Lq42PefElwI4QQolbT65UgoixbTo7ympenbFpt0fuy7N98n9u9z80FsAT6l+vzuLiAmxs4OCibvb3pa2nH7O3BxkYJqHS6sm96vXJ98cCl+HtbW6V2p7qR4EYIIUSNk5Wl1GbExRXVdNy8X/g+I8Pcub09tdqApyd4e6vw8gJvb2UrfF/8mKcnWFfPhbirFQluhBBC3BWtFtLTS24ZGaUfL9o0XLlyP+++qzH+1V9a/42bjxkMStNNXNy9BSzW1mXbrKyKNkvLW+8Xvre0VGpHCq8vy3u1WsuOHesIDx+EpaXl3X8oYUKCGyGEqEMMBqVpJDUVUlJKbqmpZQ1QCptV7oYacL9jqjuxsVH6dhTWatzqvatrUTBhaVm9mlG0WqXfiqhYEtwIIUQNpNUqI2YSE5UtKank+9KCl5QUpW9IRbKxAUdHpW+Go2PpW/Fztrb5nDlzmA4d2mJhUfQ1VFrQcfMxF5eiwMXRsXoFKqL6kOBGCCHMKDtbCUaSk5Wt8P3Nx24OXNLS7u25KpXSIdTFxXRzcrp1gOLoWPK8g4NSG1IeWq2BdetiGTTIUO5rhSgLCW6EEOIu6XRK80zhHCClTWhWfEtJ0RATcz+zZlmQkqIEKnfftKNwcQF3d2X0jLt70fvC7ebgxcVFCWocHZX5ToSojSS4EULUKYV9TtLSSm7p6eV7X/5OraX3NVGrlX4hbm6lv7q6FgUuxQMZV1fpryFEaSS4EULUWDqdMtT38mVlu3IFYmOLak+Kb8WPVfREaFZWphOZlTapmbMzODjkEx19hN692+DlZWEMXKQWRYiKJcGNEKLaMRiKOswWBi6FwUvx/WvX7i1QKd6HpDAQKTxW/P2tjhUGLWWdd0Tpa3KNBx5oLX1NagGDwUB0cjRbL2xly4UtHIk9gputG/Wd6xPoHEigSyCBzoHKvksgDlYO5bp/ni6Pa+nXuJp2lStpV4q29Cvk6/Pxc/DD38kfP0c//Bz98HdU3rvYuKAyQ09rg8FAQlYC19KvkaXNonNA5yrPQyEJboQQFSotDa5eVbYrV5TXy5fVnD7dlm++0RhnaS1ty84uen+7dWuKU6vBzw8CApTNz0+pDSkMRm61OThIbUlly9ZmE5sRS2x6rMnr1bSrnL14lr1b93J/4P10qtcJDzuPCn9+Rl4Gx64fI1eXS4hrCP6O/mjUd9+OZzAYiEmJYUvMFrZe3MrWC1u5knalRLpdl3eVer2brVtRsFMQ/Pja+7IvaR/Hdx8nNjPWJIi5nnn9rvJpa2FbFPA4+ePnoLz3cfDBwcoBO0s742ZvZW+yb62xLjUwytZmK4FW+lWupl0tel+wfzVdOZanU4biBbkEEfNMzF3lvyJIcCOEKBOtFuLjlWafm4OX4u/T00u7WgMElPuZKhX4+ipBS716RQFM8X0fH2UFYlG5DAYDGXkZJOckk5KTQnJ2wWtOMglZCcSmxxKXGWcSyKTmpt72nnt374XdyvtQt1A6B3TmPv/76BzQmeZezbFQl/0fNj4zniNxRzgSe4TI65EciT3C2cSzGCiKkq00VgS5BBHiGkKIS4jyWmxztHYscd8LKReMwcyWmC1cTrtsct5Sbcl99e6jV1Av7qt3Hxl5GVxMvcjFlItcSrvExZSLXEy9SEpOCknZSSRlJ3Ek7kjJD3Cp9M9lpbHC39Gfek71jJu/oz8WagslUCwIKgpreJJzksnOzyY6OZro5Ogyl18htUpdItiJz4onKTupzPfwsvfCx8EHg8FglhokkOBGiDqt+Iyvd9oSEsp+XycnJfjw91defXx0xMWdok2bJtjba7C1VeZGKb7dfMzWVlkPRwKXipenyyM+M574rHhuZN4gPrPgNSuexKxEUnKV4OXmQEZn0JX7WTYWNvg6+OLr6Ku8OvjiZefFxXMX0bpr2Xd1H2cSzxCVFEVUUhTLjy4HwN7Sng7+HehcrzP31buPzvU642nvicFg4ELKBWMgcyTuCJFxkVxNv1rq830dfLG3sudiykXydHmcTTzL2cSzpab1sPOggWsDQlxDsFBbsP3idi6mXjRJY6m2pKN/R3oF9aJnUE86B3TGztLujuWQlpvGpdSiYKd48JOZkknL4JbUd65vEsTUc6qHh51HuQKEwtqywmDHGPikX+VG5g2ytFlkajPJ0maZbIU1LnqDnoy8DDLySvaWt7Wwxd/JH39Hf+NrYXNY4b6voy9WGqsy57eyyH8bQtRCOTlFQUlsrOlr8ffXrys1MmWl0Sjr3Pj7F22FQUzx9w43dS3QavWsWxfNoEGNsLSsHsN79AY9qTmpJGYnkpydjIXaAltLW2wtbLGztDO+v5dmjPLS6rTEpMQQlah80Re+Xk67jIXaAhsLm9I3jQ3WFtYmx6w0VqTlphmDluJBzJ1qVG7HSmOFq40rLjYuuNq64mrjiqutqzFwMQYxBa9O1k4lvpy1Wi3rUtcxaJCy5EBSdhL7ruxjz5U97Lmyh31X9pGel87WC0rTT6EglyBSclJIyUkpNW+hbqG08W1DGx9la+3TGm8HbwB0eh1X068SnRTN+eTzypaivEYnRZOYnUhCVgIJWQnsu7rPeE8LtQUd/DoYg5kuAV2wt7Ivd7k5WTvR3Ks5zb2alyyLdUVlca9sLW2NNVHlodVpyc7PNgY7mXlKAJSTn4O7nTv+jv5m68tzNyS4EaIG0euVpqHCjrVXrhRt164VBS0pKeW7r5ub0rxzp83dvXr1U8nNzzX+lVm4peWmkZSdRGJ2ovKalVj0vtix5Jxk9Ab9HZ9hpbHC1sIWW8uCoKfYewcrB1xsXHCxdsHZxhkXGxecrQteC/aLH9MYNOgMOs4nn+dC2gWikqI4m3jWGMhcSLlwV7Ujd0Oj0uBp74mnnSde9l7G9+627iZBi4uNi8l7WwvbCv+Cc7N1Y2DoQAaGDgSUQORUwin2XtnLnstKwHMq4RQXUi4ASu1Jc6/mShBTEMy09G5ZarOS8fOqNdR3rk995/r0Cu5V4nxqTioxKTHGwCcjL4PO9TrTtX7XcncEroksNZZYaixxsnYyd1YqhAQ3QlQjSUlw/jxculQUtBQPYq5eLXtNi5WV0l/Fx+fWr4XT2FuZqRZZp9eRmJ1obCK5+TU5J9kkcEnPTTfZ1+rLUe10C/aW9rjauqI36MnSZpGtzSZXVzSzXp4ujzxd3j3VdhSyVFtiMBjIP3rrIV52lnY0dGtIqFsooW6hhLmHEegSiMFgICc/x2TL1eWWOJaTn0Nufi45uhycrJyMgYuXvReedp7G9y42LqhV1ShSLUaj1hhrOaa0nQJASk6KcTRSE88mFd704WzjTGuf1rT2aV2h9xXmIcGNEFVIr1dqWKKji7Zz54rel6XGRaVSgpLCTrWFm5+fErQUBi4uLtVj3Z0raVdY8c8KNl3exNJflpKYUxTMJGcnm3T4vFs2FjY4WDngaOWIg5UDbrZuuNu542ajvLrbuhcds3Uz7rvZumFtUXIct96gJyc/xxjsZOdnk61VquyLv8/IyzA2k6TmppZ4n5qTatzXG/TGYMxaY00DtwbG4CXULZRQdyWY8XP0qzFV/1XJxcal1BoXIUojwY0QFSQnR+l0W3yLjVWzeXNzvvxSQ0wMxMQo6W7H1xeCgkwDl+Kbr2/51/K52dnEs/xx9g+iEqPoFtiNgQ0H4mrrem83LSYzL5PVp1fzzdFv2HR+U1EAk1h6ejdbN2Otgqedp/G9m62bMWBxtFZeC7fC4/ZW9uUaVVMWxUeMVITCkUbxGfFs3ryZsQ+OxcbapkLuLYQoSYIbIW4jMxMuXFCaiq5cKRm8FG6JiUrakjRAA9MjGiV4adCgaGvYUHkNCQG7ivk+NaHVadl1eRd/nP2DtWfXmowW+eLQF2hUGroFduPBsAcJbxROQ7eG5X6G3qBn+8XtfHP0G345+YvJaItuAd3wy/OjS6su+Dj5mAQy7nbuFR6cVDcqlQpHa0ds1DZ4WnlWaSdlIeqi2v0/ihB3kJ+v9Gk5fx5jzUpMTNH+jRvlu5+FhdLp1sND2dzc9Oj15+nTJ5iwMA0NGkD9+vde81IWydnJrD+3nj/O/sH6c+tNRphYqi3pEdSD5p7N+Tvmb47fOG4cmTLjrxk08WjCg40eJDwsnPvq3XfbL+OoRGX47rf/fGsybDbENYQJrSYwtuVYAhwClBEh7StmRIgQQtyOBDeiTsjOhuPH4cgRiIyE06eV4OXyZWV9ottxdlZqVOrXV4ZBFwYuxYOYws3JybSfi1arY926EwwaFHjLIdBanZbIuEh2Xd7Frsu72HdlH3qDHl9HX3wcfPB1UF6Lvy88Z2Nh2rRxJuEMa8+u5Y+zf7Dz0k6TkTfutu4MDhtMeFg4/Rr0MxkVEZMcw9qza1lzZg3bLm7jVMIpTiWc4r+7/ouHnQeDQwfzYKMH6degHw5WDqTkpPDj8R9Z/s9ydl/ebbyPk7UTI5uNZHyr8XQN6GrsO6Itz3hzIYS4RxLciFonMVEJYCIjTYMZJYgxQNNfwO8ghOqhkQ6NhR5HZx1OTnocnHQ4Oumxd9Bh76jHzl6HhaUenUGHpdoSH5cg4yRfIa4h+Dr6lnvESUpOCnsu7zEGM/uv7idLm1Ui3a0mJSvOxcbFGPhcTbtKVFKUyflmns0IDwtnSNiQ29bABLsG83Snp3m609Ok5KSw8dxG1pxdw7qodSRkJfDN0W/45ug3WGmsaOfbjsOxh40jitQqNf0b9Gd8q/E81OghbC1ty1UeQghR0SS4ETWWTqcMmT56tCiIOXJEqY0pjWvIeVQPPk6SyybT+wApBRsA+TcfuDVrjTXBrsElpnNv4NaAYJdgLLEkLjeO7459x75r+9h1eRcnbpwoMULI1caVLgFd6BrQla71u2JnaadMZ58RR2zGTa8Fx3N1ucbROacTTgNKc1PPoJ7GgCbYNbhshVmMi40LI5uPZGTzkWh1WnZe2mms1YlOjmbPlT0ANPdqzoRWExjTYgy+jr7lfo4QQlQWCW5EtWYwKLPoRkXB2bOm27lzkJdX+nUhIdC6NbRpAy1a6Ths+THvH3qV7PxsbCxsmNhqIo7WjqhVajQqjfKqVl5LO6ZRacjOzyYmOcY4q+nFlIvk6nI5nXDaGFzczMHKQelYe8r0eEO3hkogUxDMNPZoXK4aIIPBQGpuqkkAZGdpxwPBD1ToJFyWGkt6BfeiV3AvPuj3AacSTrHn8h7a+raltU9rGbIshKiWJLgR1YJWC//8A2fOlAxiSl+IUWFpCU2bFgUyrVsrm7Ozcv6f6/8wZc0UDlw7AECvoF58Gf7lXY0Gulm+Pp/LqZeLpnJPPk90ctHU7oUT0FmoLGjr25b769/P/fXvp0tAF+OU8HdLpVIZZ79t4tnknj9LWZ/Z1LMpTT2bVsnzhBDibklwI8wiPx8OHYItW5Rt507IKtntBFA66AYGQliY6RYaqhzXlNKNJDc/lze3v8m7u94lX5+Ps7Uz8/vN57E2j1VYbYOF2oJg12CCXYPpTe8S55Ozk7mYfJGz+87y8JCHZZSQEEJUEQluRJXIz1f6w2zdqgQz23cYyLS4CP77wH8/jNyPyiMK1+x2NNGE0913CB0b1SMsTGlisinHfGe7Lu1iytopxqaihxs/zKeDPsXP0a9yPtwtuNq64mDhwEX1xTsnFkIIUWEkuBGVQqdTgpkdOwqCmQNJpDvtVwIZ//3w7/1gH29yjQFIsl/HLtaxK+fftL7emnDncMKdw2nn1+6OfVLSctOY9fcsPjv4GQDe9t4sGrSI4U2HV9bHFEIIUQ1JcCMqhMGg9I/5K0LPn5uT2XbMjRz3z5RAJmQ/dDhX4hpLtSWtfFrR0a8jHf070tCtITsu7WDt2bXsubyHyLhIIuMieWP7G/g4+DA4dDBDwobQN6Qv9lb2Jvf68+yfPPnnk1xJuwLA5NaTmd9vfoUuKSCEEKJmqBbBzaJFi3j//feJi4ujVatWfPLJJ3Ts2PGW6VNSUnjllVdYtWoVSUlJBAYGsmDBAgYNGlSFua5bcvJzTIYhx2XEcTYulsioOM7FxXE9KxatVRw4XIdWWmhV8h6hbqF09O9IJ/9OdPTvSCufViUmoetavysv3f8S8ZnxrD+3nrVn17Lx3EbiMuJYfGQxi48sxlpjzQPBDzAkbAj317+f/+76LyuOrQCUWXG/HPIlvUNK9oERQghRN5g9uPnxxx+ZMWMGX3zxBZ06dWLBggX079+fM2fO4OXlVSJ9Xl4effv2xcvLi19++QV/f38uXryIi4tL1We+FsrMy+To9aMciT3C4djDHIk7QkxKjMnU/SXYF2zFOOLG/Q3uo3PAfXSq14n2fu1xs3Urcz487T0Z32o841uNJ0+Xx/aL21l7Zi1rz64lJiWG9efWs/7cemN6tUrNs52eZV6veSVqdYQQQtQtZg9uPvzwQ6ZOncqkSZMA+OKLL/jzzz9ZsmQJL730Uon0S5YsISkpid27dxtHnwQFBd3y/rm5ueTm5hr309LSAGU6+IqeEr7wfjVlqvnErEQir0cqW1wkR+KOEJUUVWKCOaN8a8jwgXRf5TXDB19HH1oE+dC5pTc92nkT5O6Dq5Ur2zZvo2/fviYjhO62XFSo6BHQgx4BPXi/9/ucSjjFn+f+5M+oP9l7dS8tvFrw+cDPae/X/p6eUxlq2s9EZZFyUEg5KKQcikhZKMpSDuUpI5XBYLjFN1nly8vLw87Ojl9++YWhQ4caj0+YMIGUlBR+//33EtcMGjQINzc37Ozs+P333/H09GT06NG8+OKLaEoZEzxnzhzmzp1b4viKFSuwq4zll6spg8HAPxn/cDrzNNFZ0cRkxxCvjS81rbPKHbu05qSd6URmdCdIaKwENDku+Phk0qpVPK1axdO8eQJOTub9hcw35GOhMnuMLoQQopJlZWUxevRoUlNTcXK6/WSlZv1WSEhIQKfT4e1tOqGZt7c3p0+XPuPr+fPn2bx5M2PGjGHdunWcO3eO//znP2i1Wl5//fUS6WfNmsWMGTOM+2lpaQQEBNCvX787Fk55abVaIiIiStRYmFtKTgpP/PkEq6NXlzjXwLUBrbxbEWzdhoTjbdi/ph2nDviQWnDe3t7AwIEG+vbV06tXPkFB1kC9gq101bUczEHKQiHloJByUEg5FJGyUJSlHApbXsqixv3Jq9fr8fLy4ssvv0Sj0dCuXTuuXr3K+++/X2pwY21tjbW1dYnjlpaWlfaDVJn3Lq/9V/cz8peRXEi5gKXakpHNR9LOtx1tfNoQYNmajWucWfEprNpZdI2lJQwcCKNHQ3i4Cjs7FVC+xSGV+1SfcjA3KQuFlINCykEh5VBEykJxu3IoT/mYNbjx8PBAo9Fw/fp1k+PXr1/Hx8en1Gt8fX2xtLQ0aYJq0qQJcXFx5OXlYWVlVal5rin0Bj0f7fmIlza9RL4+n2CXYFY+spKmzh35/Xd47w346y9lcj1QZgHu0UMJaIYPB7ey9/0VQgghqpXy/zlegaysrGjXrh2bNhWt0qzX69m0aROdO3cu9ZquXbty7tw59Hq98djZs2fx9fWVwKZAQlYC4T+EMzNiJvn6fP7V9F/8NvAIn7zUEW9vGDsW1q1TApu2bWH+fGV17S1bYOpUCWyEEELUbGZvlpoxYwYTJkygffv2dOzYkQULFpCZmWkcPTV+/Hj8/f155513APj3v//Np59+yjPPPMNTTz1FVFQUb7/9Nk8//bQ5P0a1se3CNkavGs219GtYa6z5qN/HZO98nM4TVca1mxo2VGpoRo2Cxo3Nm18hhBCiopk9uBk5ciTx8fHMnj2buLg4WrduzYYNG4ydjC9duoRaXVTBFBAQwMaNG3nuuedo2bIl/v7+PPPMM7z44ovm+gjVgk6v460dbzF321z0Bj2NPRozr8WPvD+9JQeUBbHp3h3eew86dlSaoYQQQojayOzBDcD06dOZPn16qee2bt1a4ljnzp3Zu3dvJeeq5ohNj2XMqjFsubAFgLHNJ+B96FNGP+tAfj44OytBzZQpoDZrQ6QQQghR+apFcCPu3sZzGxm3ehzxWfHYW9rzdIPP+WXWOKKilPPDhsEnn4Bf1S6ILYQQQpiNBDc1lFanZfaW2by7610Amnm0pMnxn3jnlUYA+PrCokXw8MPmzKUQQghR9SS4qYGik6IZt3oce67sAaC/63848vYHnLimLEL55JPw7rtKc5QQQghR10hwU4Nk5mXy9o63mb9nPnm6PBwtnWh0ZjEblz8CQKNG8NVX0K2bmTMqhBBCmJEENzWAwWDgxxM/MvOvmVxNvwpAY8u+XP7sfxy8GoylJbz0Erz8MtjYmDmzQgghhJlJcFPN/XP9H55e/zTbLm4DoL5TEB4HP+LwiocAFZ06wddfQ/Pm5s2nEEIIUV1IcFNNJWcnM3vLbD47+Bl6gx4bCxsmNpjF+tf+j8PnbLGxgf/+F6ZNg1IWQxdCCCHqLAluqhmdXseSI0t4efPLJGQlAPBI00e4L20+r04KJCcHQkLg11+hdWvz5lUIIYSojmRKt2pkz+U9dPq6E4//8TgJWQk09WzKukf/xnPLz8ycogQ2gwbBwYMS2AghhBC3IjU31UBcRhwv/v0iy48uB8DJ2om5PefykN80Ro2wZN8+ZbmE11+H116TWYaFEEKI25Hgxsy+PPQlM/+aSXpeOgCTW0/mnT7vcPKAF/d1gBs3wMUFvv9eqbURQgghxO1JcGMmeoOe//vr//hw74cAdPDrwKeDPqWDX0c++EAZ2q3TQatWsGqV0s9GCCGEEHcmwY0ZZGuzGbt6LKtOrQLgzV5vMqvbLDIz1IwcCT//rKQbNw6++ALs7MyYWSGEEKKGkeCmisVnxvPgygfZe2UvVhorlj20jFEtRnH6tLLI5alTYGkJCxbAv/+t9LURQgghRNlJcFOFziaeZeD3AzmffB5XG1d+e/Q3ugd2Z9UqmDgR0tOV1bt/+QU6dzZ3boUQQoiaScbdVJGdl3bSeXFnziefJ9glmN2P7aZ7YHc++ACGD1cCmx494PBhCWyEEEKIeyHBTRX48fiP9Fneh6TsJDr6d2TvlL009mhMaqoytBvguefg77/B29u8eRVCCCFqOgluKpHBYOC/O//Lo78+Sq4ul6GNh7Jlwha87L0AWLECsrOhaVP44AOwkEZCIYQQ4p7J12klydfnM33ddP536H8APNPpGT7o9wEaddFCUF9/rbxOnSodh4UQQoiKIsFNJUjPTWfs72NZf249KlR81P8jnrnvGZM0hw8rm5WVMuRbCCGEEBVDgpsKlqRNovd3vYm8HomthS0rhq9gaOOhJdJ99ZXyOnw4uLtXbR6FEEKI2kyCmwp07MYxXjj7AgnaBLzsvVg7ai0d/TuWSJeZqSynADBlShVnUgghhKjlJLipIPuu7KPfd/1I06YR5hbG+rHrCXEtfc2En35Shn43aAA9e1ZtPoUQQojaToKbCtLIoxH+jv4EWASwacImvJ1uPaa7sCPxlCmywrcQQghR0SS4qSAuNi5sGL2B/Vv342brdst0J07A7t3KsO+JE6suf0IIIURdIfUGFcjXwRdLteVt0xTW2oSHg49PFWRKCCGEqGMkuKlCOTmwfLnyXjoSCyGEEJVDgpsqtHo1JCVBQAD072/u3AghhBC1kwQ3VaiwSWryZNBobp9WCCGEEHdHgpsqEh0NmzcryyxMnmzu3AghhBC1lwQ3VaSw1qZ/f6hf37x5EUIIIWozCW6qgFYLS5cq76dONW9ehBBCiNpOgpsq8OefcP06eHsrQ8CFEEIIUXkkuKkChYtkTpwIlrefBkcIIYQQ90iCm0p2+TJs2KC8f+wx8+ZFCCGEqAskuKlkS5aAXq8skBkaau7cCCGEELWfBDeVSKeDxYuV99KRWAghhKgaEtxUoogIpVnKzQ2GDTN3boQQQoi6QYKbSlTYkXjcOLCxMW9ehBBCiLqiWgQ3ixYtIigoCBsbGzp16sT+/fvLdN3KlStRqVQMHTq0cjN4F65fhzVrlPeySKYQQghRdcwe3Pz444/MmDGD119/ncOHD9OqVSv69+/PjRs3bnvdhQsXmDlzJt26dauinJbPsmWQnw/33QfNm5s7N0IIIUTdYfbg5sMPP2Tq1KlMmjSJpk2b8sUXX2BnZ8eSJUtueY1Op2PMmDHMnTuXkJCQKsxt2RgMRcstSEdiIYQQompZmPPheXl5HDp0iFmzZhmPqdVq+vTpw549e2553bx58/Dy8uKxxx5jx44dt31Gbm4uubm5xv20tDQAtFotWq32Hj+BqcL7bd6s49w5SxwdDQwblk8FP6baKyyHii7fmkjKQiHloJByUEg5FJGyUJSlHMpTRmYNbhISEtDpdHh7e5sc9/b25vTp06Ves3PnThYvXkxkZGSZnvHOO+8wd+7cEsf/+usv7Ozsyp3nsj0zHgigS5cLbNv2T6U8oyaIiIgwdxaqDSkLhZSDQspBIeVQRMpCcbtyyMrKKvN9zBrclFd6ejrjxo3jq6++wsPDo0zXzJo1ixkzZhj309LSCAgIoF+/fjg5OVVo/rRaLatWbWXfvnoAzJkTQLt29Sr0GTWBVqslIiKCvn37YlnH15uQslBIOSikHBRSDkWkLBRlKYfClpeyMGtw4+HhgUaj4fr16ybHr1+/jo+PT4n00dHRXLhwgfBiq0/q9XoALCwsOHPmDA0aNDC5xtraGmtr6xL3srS0rJQfpK1bA8jNVdG6NXTqZIFKVeGPqDEqq4xrIikLhZSDQspBIeVQRMpCcbtyKE/5mLVDsZWVFe3atWPTpk3GY3q9nk2bNtG5c+cS6Rs3bsyxY8eIjIw0bg8++CC9evUiMjKSgICAqsx+CQYDREQEAkpH4roc2AghhBDmYvZmqRkzZjBhwgTat29Px44dWbBgAZmZmUyaNAmA8ePH4+/vzzvvvIONjQ3NbxpX7eLiAlDiuDns36/i0iUnbG0NjBkjkY0QQghhDmYPbkaOHEl8fDyzZ88mLi6O1q1bs2HDBmMn40uXLqFWm33EepksXqzk85FHDDg7S3AjhBBCmIPZgxuA6dOnM3369FLPbd269bbXLlu2rOIzdBfS0uCnn5SAZvJkPdVgCiEhhBCiTqoWwU1tcP48+PhAXl46XbrIQlJCCCGEuUhwU0Fat4aTJ/P5/vvdqFQPmDs7QgghRJ0lbScVSK0Gd/ccc2dDCCGEqNMkuBFCCCFErSLBjRBCCCFqFQluhBBCCFGrSHAjhBBCiFpFghshhBBC1CoS3AghhBCiVpHgRgghhBC1igQ3QgghhKhVJLgRQgghRK0iwY0QQgghahUJboQQQghRq0hwI4QQQohaRYIbIYQQQtQqFubOQFUzGAwApKWlVfi9tVotWVlZpKWlYWlpWeH3rymkHIpIWSikHBRSDgophyJSFoqylEPh93bh9/jt1LngJj09HYCAgAAz50QIIYQQ5ZWeno6zs/Nt06gMZQmBahG9Xs+1a9dwdHREpVJV6L3T0tIICAjg8uXLODk5Vei9axIphyJSFgopB4WUg0LKocj/t3f/MVHXfxzAnwdyFyAKeAJ3MRDETlFhi/R2s6yECbQ1VFq6WDtXk4Hg7Ict+2FgW8PZZqvmaK3SfxwULtRq9kMUWgw0CAQLmbBbrAmSNokfoo57ff9gnDtFsa9398bPPR/bZ7vPD+T5efn64+Xn80ZYi3F3UwcRweDgIMxmMwIC7ryqxu+e3AQEBCA2Ntar32PWrFl+3aQTWIcbWItxrMM41mEc63ADazFuqjpM9cRmAhcUExERkaZwuCEiIiJN4XDjQQaDASUlJTAYDKqjKMU63MBajGMdxrEO41iHG1iLcZ6ug98tKCYiIiJt45MbIiIi0hQON0RERKQpHG6IiIhIUzjcEBERkaZwuPGQvXv3Yt68eXjggQdgtVpx6tQp1ZF8rrS0FDqdzm1buHCh6lhe9/PPP+Ppp5+G2WyGTqfDoUOH3M6LCN555x2YTCYEBwcjIyMD586dUxPWy6aqxcaNG2/pkaysLDVhvaSsrAzLli1DWFgYoqKisGbNGnR2drpdMzo6iqKiIsyZMwczZ85Ebm4uLly4oCix99xNLZ544olbeqKgoEBRYu8oLy9HSkqK6z+os9lsOHr0qOu8v/TDVHXwZC9wuPGAL7/8Eq+88gpKSkrw22+/ITU1FZmZmejv71cdzecWL16M3t5e1/bLL7+ojuR1w8PDSE1Nxd69eyc9v3v3bnz00Uf45JNPcPLkSYSGhiIzMxOjo6M+Tup9U9UCALKystx6pKKiwocJva+urg5FRUVobGzETz/9hOvXr2P16tUYHh52XfPyyy/jm2++QVVVFerq6nD+/HmsW7dOYWrvuJtaAMCmTZvcemL37t2KEntHbGwsdu3ahebmZjQ1NWHVqlXIycnB77//DsB/+mGqOgAe7AWhe7Z8+XIpKipy7Y+NjYnZbJaysjKFqXyvpKREUlNTVcdQCoBUV1e79p1Op8TExMj777/vOnb58mUxGAxSUVGhIKHv3FwLERG73S45OTlK8qjS398vAKSurk5Exv/+g4KCpKqqynVNR0eHAJCGhgZVMX3i5lqIiDz++OOydetWdaEUiYiIkM8++8yv+0HkRh1EPNsLfHJzj65du4bm5mZkZGS4jgUEBCAjIwMNDQ0Kk6lx7tw5mM1mJCYmIi8vDz09PaojKeVwONDX1+fWH7Nnz4bVavXL/gCA2tpaREVFwWKxoLCwEJcuXVIdyasGBgYAAJGRkQCA5uZmXL9+3a0nFi5ciLi4OM33xM21mHDgwAEYjUYsWbIEb7zxBkZGRlTE84mxsTFUVlZieHgYNpvNb/vh5jpM8FQv+N0vzvS0ixcvYmxsDNHR0W7Ho6OjcfbsWUWp1LBardi/fz8sFgt6e3uxc+dOPPbYYzhz5gzCwsJUx1Oir68PACbtj4lz/iQrKwvr1q1DQkICuru78eabbyI7OxsNDQ0IDAxUHc/jnE4nXnrpJaxYsQJLliwBMN4Ter0e4eHhbtdqvScmqwUAPPfcc4iPj4fZbEZbWxtef/11dHZ24uuvv1aY1vPa29ths9kwOjqKmTNnorq6GsnJyWhtbfWrfrhdHQDP9gKHG/KY7Oxs1+eUlBRYrVbEx8fjq6++wosvvqgwGU0XGzZscH1eunQpUlJSMH/+fNTW1iI9PV1hMu8oKirCmTNn/GLt2VRuV4v8/HzX56VLl8JkMiE9PR3d3d2YP3++r2N6jcViQWtrKwYGBnDw4EHY7XbU1dWpjuVzt6tDcnKyR3uBr6XukdFoRGBg4C0r2y9cuICYmBhFqaaH8PBwPPTQQ+jq6lIdRZmJHmB/TC4xMRFGo1GTPVJcXIxvv/0WJ06cQGxsrOt4TEwMrl27hsuXL7tdr+WeuF0tJmO1WgFAcz2h1+uRlJSEtLQ0lJWVITU1FR9++KHf9cPt6jCZe+kFDjf3SK/XIy0tDTU1Na5jTqcTNTU1bu8R/dHQ0BC6u7thMplUR1EmISEBMTExbv3x77//4uTJk37fHwDw119/4dKlS5rqERFBcXExqqurcfz4cSQkJLidT0tLQ1BQkFtPdHZ2oqenR3M9MVUtJtPa2goAmuqJyTidTly9etWv+mEyE3WYzD31gkeWJfu5yspKMRgMsn//fvnjjz8kPz9fwsPDpa+vT3U0n3r11VeltrZWHA6H1NfXS0ZGhhiNRunv71cdzasGBwelpaVFWlpaBIDs2bNHWlpa5M8//xQRkV27dkl4eLgcPnxY2traJCcnRxISEuTKlSuKk3venWoxODgo27Ztk4aGBnE4HHLs2DF5+OGHZcGCBTI6Oqo6uscUFhbK7Nmzpba2Vnp7e13byMiI65qCggKJi4uT48ePS1NTk9hsNrHZbApTe8dUtejq6pJ3331XmpqaxOFwyOHDhyUxMVFWrlypOLlnbd++Xerq6sThcEhbW5ts375ddDqd/PjjjyLiP/1wpzp4uhc43HjIxx9/LHFxcaLX62X58uXS2NioOpLPrV+/Xkwmk+j1ennwwQdl/fr10tXVpTqW1504cUIA3LLZ7XYRGf9x8B07dkh0dLQYDAZJT0+Xzs5OtaG95E61GBkZkdWrV8vcuXMlKChI4uPjZdOmTZr7R8Bk9w9A9u3b57rmypUrsnnzZomIiJCQkBBZu3at9Pb2qgvtJVPVoqenR1auXCmRkZFiMBgkKSlJXnvtNRkYGFAb3MNeeOEFiY+PF71eL3PnzpX09HTXYCPiP/1wpzp4uhd0IiL//XkPERER0fTENTdERESkKRxuiIiISFM43BAREZGmcLghIiIiTeFwQ0RERJrC4YaIiIg0hcMNERERaQqHGyIiItIUDjdERAB0Oh0OHTqkOgYReQCHGyJSbuPGjdDpdLdsWVlZqqMR0X1ohuoAREQAkJWVhX379rkdMxgMitIQ0f2MT26IaFowGAyIiYlx2yIiIgCMvzIqLy9HdnY2goODkZiYiIMHD7p9fXt7O1atWoXg4GDMmTMH+fn5GBoacrvmiy++wOLFi2EwGGAymVBcXOx2/uLFi1i7di1CQkKwYMECHDlyxLs3TUReweGGiO4LO3bsQG5uLk6fPo28vDxs2LABHR0dAIDh4WFkZmYiIiICv/76K6qqqnDs2DG34aW8vBxFRUXIz89He3s7jhw5gqSkJLfvsXPnTjz77LNoa2vDU089hby8PPzzzz8+vU8i8gDP/TJzIqL/j91ul8DAQAkNDXXb3nvvPRERASAFBQVuX2O1WqWwsFBERD799FOJiIiQoaEh1/nvvvtOAgICpK+vT0REzGazvPXWW7fNAEDefvtt1/7Q0JAAkKNHj3rsPonIN7jmhoimhSeffBLl5eVuxyIjI12fbTab2zmbzYbW1lYAQEdHB1JTUxEaGuo6v2LFCjidTnR2dkKn0+H8+fNIT0+/Y4aUlBTX59DQUMyaNQv9/f3/7y0RkSIcbohoWggNDb3lNZGnBAcH39V1QUFBbvs6nQ5Op9MbkYjIi7jmhojuC42NjbfsL1q0CACwaNEinD59GsPDw67z9fX1CAgIgMViQVhYGObNm4eamhqfZiYiNfjkhoimhatXr6Kvr8/t2IwZM2A0GgEAVVVVeOSRR/Doo4/iwIEDOHXqFD7//HMAQF5eHkpKSmC321FaWoq///4bW7ZswfPPP4/o6GgAQGlpKQoKChAVFYXs7GwMDg6ivr4eW7Zs8e2NEpHXcbghomnh+++/h8lkcjtmsVhw9uxZAOM/yVRZWYnNmzfDZDKhoqICycnJAICQkBD88MMP2Lp1K5YtW4aQkBDk5uZiz549rj/LbrdjdHQUH3zwAbZt2waj0YhnnnnGdzdIRD6jExFRHYKI6E50Oh2qq6uxZs0a1VGI6D7ANTdERESkKRxuiIiISFO45oaIpj2+PSei/4JPboiIiEhTONwQERGRpnC4ISIiIk3hcENERESawuGGiIiINIXDDREREWkKhxsiIiLSFA43REREpCn/A3IvCpLCQyb4AAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9115 - accuracy: 0.6868 - 374ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 834us/step\n",
            "\u001b[35mTest Accuracy: 0.69\u001b[0m\n",
            "\u001b[34mTest Loss: 0.91\u001b[0m\n",
            "\u001b[33mTest Precision: 0.69\u001b[0m\n",
            "\u001b[32mTest Recall: 0.69\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.69\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "#Define Model with bigger MaxPooling Window.\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((4, 3)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GYdJllUdv27C"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oQa6eO6_v27C"
      },
      "source": [
        "* Decreasing the size of the MaxPooling2D sliding window to 1x1 decreased the performance of the model, this is because the model is underfitting and cannot learn complex features.\n",
        "* On the other hand, increasing the size of the MaxPooling2D sliding window to 4x3 presented better results then the 1x1 sliding window, but not as good as the original 2x2 sliding window. This is because the model can learn more complex features, but at the same time, it is ignoring finer details of the object in the image.\n",
        "* Additionally, when the size of the kernel is increased, the training time is decreased, as there would be less iterations to perform."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "-zFufal1v27C"
      },
      "source": [
        "### Q.4\n",
        "Activation Functions are applied to the output of a neuron in a Neural Network. ReLU (Rectified Linear Unit) is one of the most popular activation functions used in Machine Learning. Experiment with another activation function of your choice and note any differences."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:23:54.292009Z",
          "start_time": "2023-11-20T22:23:54.278118Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 876
        },
        "id": "UsXqTg_Dv27C",
        "outputId": "62525d86-d6cc-42ab-df4e-1a1da812512e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[36mTesting relu activation function\u001b[0m\n",
            "Model: \"sequential_34\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_68 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_51 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_69 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_52 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_70 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_34 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_70 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_71 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "None\n",
            "\u001b[36mTraining Time: 44.19s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9281 - accuracy: 0.6805 - 381ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 865us/step\n",
            "\u001b[35mTest Accuracy: 0.68\u001b[0m\n",
            "\u001b[34mTest Loss: 0.93\u001b[0m\n",
            "\u001b[33mTest Precision: 0.68\u001b[0m\n",
            "\u001b[32mTest Recall: 0.68\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.68\u001b[0m\n",
            "\u001b[36mTesting sigmoid activation function\u001b[0m\n",
            "Model: \"sequential_35\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_71 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_53 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_72 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_54 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_73 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_35 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_72 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_73 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 14.66s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 2.3030 - accuracy: 0.1000 - 406ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 811us/step\n",
            "\u001b[35mTest Accuracy: 0.1\u001b[0m\n",
            "\u001b[34mTest Loss: 2.3\u001b[0m\n",
            "\u001b[33mTest Precision: 0.01\u001b[0m\n",
            "\u001b[32mTest Recall: 0.1\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.02\u001b[0m\n",
            "\u001b[36mTesting softmax activation function\u001b[0m\n",
            "Model: \"sequential_36\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_74 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_55 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_75 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_56 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_76 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_36 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_74 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_75 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 142.61s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 1s - loss: 1.2930 - accuracy: 0.5310 - 788ms/epoch - 3ms/step\n",
            "313/313 [==============================] - 1s 1ms/step\n",
            "\u001b[35mTest Accuracy: 0.53\u001b[0m\n",
            "\u001b[34mTest Loss: 1.29\u001b[0m\n",
            "\u001b[33mTest Precision: 0.52\u001b[0m\n",
            "\u001b[32mTest Recall: 0.53\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.52\u001b[0m\n",
            "\u001b[36mTesting elu activation function\u001b[0m\n",
            "Model: \"sequential_37\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_77 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_57 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_78 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_58 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_79 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_37 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_76 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_77 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 20.28s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.8600 - accuracy: 0.7104 - 354ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 700us/step\n",
            "\u001b[35mTest Accuracy: 0.71\u001b[0m\n",
            "\u001b[34mTest Loss: 0.86\u001b[0m\n",
            "\u001b[33mTest Precision: 0.71\u001b[0m\n",
            "\u001b[32mTest Recall: 0.71\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.71\u001b[0m\n",
            "\u001b[36mTesting selu activation function\u001b[0m\n",
            "Model: \"sequential_38\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_80 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_59 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_81 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_60 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_82 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_38 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_78 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_79 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 17.09s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9473 - accuracy: 0.6791 - 352ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 773us/step\n",
            "\u001b[35mTest Accuracy: 0.68\u001b[0m\n",
            "\u001b[34mTest Loss: 0.95\u001b[0m\n",
            "\u001b[33mTest Precision: 0.68\u001b[0m\n",
            "\u001b[32mTest Recall: 0.68\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.67\u001b[0m\n",
            "\u001b[36mTesting tanh activation function\u001b[0m\n",
            "Model: \"sequential_39\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_83 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_61 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_84 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_62 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_85 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_39 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_80 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_81 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 17.76s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9331 - accuracy: 0.6803 - 336ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 750us/step\n",
            "\u001b[35mTest Accuracy: 0.68\u001b[0m\n",
            "\u001b[34mTest Loss: 0.93\u001b[0m\n",
            "\u001b[33mTest Precision: 0.68\u001b[0m\n",
            "\u001b[32mTest Recall: 0.68\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.68\u001b[0m\n",
            "\u001b[36mTesting hard_sigmoid activation function\u001b[0m\n",
            "Model: \"sequential_40\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_86 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_63 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_87 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_64 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_88 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_40 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_82 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_83 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 34.04s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 2.3031 - accuracy: 0.1000 - 365ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 882us/step\n",
            "\u001b[35mTest Accuracy: 0.1\u001b[0m\n",
            "\u001b[34mTest Loss: 2.3\u001b[0m\n",
            "\u001b[33mTest Precision: 0.01\u001b[0m\n",
            "\u001b[32mTest Recall: 0.1\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.02\u001b[0m\n",
            "\u001b[36mTesting softplus activation function\u001b[0m\n",
            "Model: \"sequential_41\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_89 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_65 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_90 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_66 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_91 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_41 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_84 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_85 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 61.09s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.3201 - accuracy: 0.5310 - 339ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 722us/step\n",
            "\u001b[35mTest Accuracy: 0.53\u001b[0m\n",
            "\u001b[34mTest Loss: 1.32\u001b[0m\n",
            "\u001b[33mTest Precision: 0.53\u001b[0m\n",
            "\u001b[32mTest Recall: 0.53\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.52\u001b[0m\n",
            "\u001b[36mTesting softsign activation function\u001b[0m\n",
            "Model: \"sequential_42\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_92 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_67 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_93 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_68 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_94 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_42 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_86 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_87 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 24.33s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.8650 - accuracy: 0.7073 - 353ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 750us/step\n",
            "\u001b[35mTest Accuracy: 0.71\u001b[0m\n",
            "\u001b[34mTest Loss: 0.87\u001b[0m\n",
            "\u001b[33mTest Precision: 0.71\u001b[0m\n",
            "\u001b[32mTest Recall: 0.71\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.71\u001b[0m\n",
            "\u001b[36mTesting swish activation function\u001b[0m\n",
            "Model: \"sequential_43\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_95 (Conv2D)          (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_69 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_96 (Conv2D)          (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_70 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_97 (Conv2D)          (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_43 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_88 (Dense)            (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_89 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 122,570\n",
            "Trainable params: 122,570\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 21.4s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACQhElEQVR4nOzdeVhU5dvA8e8M+w4qICAKKCqa4m5quSsu4Vra5pLaqm1mlplbi5ZL9cvMeiu1zdJyadE03Pdd1BRRBEUFFBdA9mFm3j+ODMuAggLDwP25rnMx58xzztzzODI3z3kWlV6v1yOEEEIIUUWoTR2AEEIIIURZkuRGCCGEEFWKJDdCCCGEqFIkuRFCCCFElSLJjRBCCCGqFEluhBBCCFGlSHIjhBBCiCrF0tQBVDSdTkdcXBxOTk6oVCpThyOEEEKIEtDr9dy6dQtvb2/U6ju3zVS75CYuLg5fX19ThyGEEEKIe3Dx4kXq1KlzxzLVLrlxcnIClMpxdnYu02trNBr+/fdfevfujZWVVZle21xJnRRN6sWY1IkxqZOiSb0Yqw51kpKSgq+vr+F7/E6qXXKTeyvK2dm5XJIbe3t7nJ2dq+yHq7SkToom9WJM6sSY1EnRpF6MVac6KUmXEulQLIQQQogqRZIbIYQQQlQpktwIIYQQokqpdn1uhBDCnOl0OrKzs00dhklpNBosLS3JzMxEq9WaOpxKoarUibW19V2HeZeEJDdCCGEmsrOziYmJQafTmToUk9Lr9dSuXZuLFy/KfGW3VZU6UavV+Pv7Y21tfV/XkeRGCCHMgF6vJz4+HgsLC3x9fcvkr1tzpdPpSE1NxdHRsVrXQ35VoU5yJ9mNj4+nbt2695WkSXIjhBBmICcnh/T0dLy9vbG3tzd1OCaVe2vO1tbWbL/Iy1pVqRN3d3fi4uLIycm5ryHt5lsDQghRjeT2o7jf5nohKrPcz/f99huS5EYIIcyIOfenEOJuyurzbdLkZseOHYSGhuLt7Y1KpWLt2rV3PScrK4upU6dSr149bGxs8PPzY8mSJeUfrBBCCCHMgkn73KSlpREcHMyYMWMYMmRIic4ZNmwYV65c4bvvvqNBgwbEx8dX+5EDQgghhMhj0uSmb9++9O3bt8TlN2zYwPbt24mOjqZGjRoA+Pn5lVN0QgghKqOAgACef/553nrrLVOHIiopsxot9eeff9KmTRvmzp3Ljz/+iIODAwMGDOD999/Hzs6uyHOysrLIysoy7KekpADKhEcajaZM48u9Xllf15xJnRRN6sWY1Imx/HWi1WrR6/XodDqzaa22sLC44/PTp09nxowZpb7uvn370Ol0hvq4H7/88gsjR47k+eef54svvriva5mSXq83/DSXz0dRcv9dNRqN0eenNL8bVPrcGjExlUrFmjVrGDRoULFl+vTpw7Zt2+jZsyfTp0/n2rVrvPTSS3Tr1o2lS5cWec7MmTOZNWuW0fHly5eX+XBKvVZP6qlUHJs6olJLpz8hRNmxtLSkdu3a+Pr6ms2IqStXrhger1mzhtmzZ3Pw4EHDMQcHBxwdHQHlS1mr1WJpWbF/cw8aNIiWLVuybNkyIiIisLW1rdDXzy87O9ts/m3LS3Z2NhcvXiQhIYGcnJwCz6Wnp/Pkk0+SnJyMs7PzHa9jVi03Op0OlUrFzz//jIuLCwCffPIJjz76KF9++WWRrTdTpkxh4sSJhv2UlBR8fX3p3bv3XSunNPR6PYuDFpMUncSTm5/E72G/Mru2OdNoNISFhdGrV6/7mrOgqpF6MSZ1Yix/nWi1Wi5evIijoyO2trbo9ZCebpq47O2hJINa8v+O9fDwQK1WExgYCMC2bdvo0aMHf//9N9OnT+fEiRNs2LABX19f3njjDfbv309aWhpBQUF8+OGH9OzZ03Ct3NtSkydPRqVSYWFhwddff8369ev5999/8fHxYd68eQwYMOCO8cXExHDgwAHWrFnD3r172bRpE08++WSBMkuWLOHTTz8lKiqKGjVqMGTIEBYuXAhAUlISb7/9Nn/88QfJyck0aNCA2bNn88gjjzBr1iz++OMPjhw5YrjW//73P/73v/8RHR0NwDPPPENSUhJt27blyy+/xMbGhnPnzvHjjz+ycOFCIiMjcXBwoFu3bnz66ad4eHgYrnXy5Enefvttdu7ciV6vJzg4mIULF5KUlETv3r25cOECtWvXNpR//fXXOXLkCNu3b7/7P5wJZWZmYmdnR+fOnY0Szdw7LyVhVsmNl5cXPj4+hsQGICgoCL1ez6VLlwz/afKzsbHBxsbG6LiVlVWZ/wL1ae9DUnQSUX9FEdjdOJbqrDzquyqQejEmdWLMysoKtVqNSqVCrVajVqtJS4My/PusVFJTwcGhdOfkTixX+Oc777zD/PnzCQgIwM3NjYsXL9K/f39mz56NjY0NP/zwAwMHDiQyMpK6desWuGZufQC8//77zJ07l/nz57Nw4UJGjBjBhQsXDP0zi/L999/Tv39/3NzcePrpp1m6dClPP/204fnFixczceJEPvroI/r27UtycjK7d+9GrVaj0+no378/t27d4qeffqJ+/fqcOnUKCwsLw79V/veZG2/+YyqVii1btuDi4kJYWJjhOa1Wy/vvv0+jRo24evUqEydOZMyYMaxfvx6Ay5cv07VrV7p27cqWLVtwdnZm586d5OTk0KVLFwICAvj555958803ASVJXr58OXPnzq30E/zl1l1RvwdK9XtBX0kA+jVr1tyxzNdff623s7PT37p1y3Bs7dq1erVarU9PTy/R6yQnJ+sBfXJy8v2EW6QTK0/oZzJT/2m9T/U6na7Mr2+OsrOz9WvXrtVnZ2ebOpRKRerFmNSJsfx1kpGRoT916pQ+IyNDr9fr9ampej2YZktNLf17Wbp0qd7FxcWwv3XrVj2gX7t27V3Pbdq0qX7hwoWG/Xr16ulnz56t12q1er1e+f549913Dc+npqbqAf0///xT7DW1Wq3e19fX8PqJiYl6a2trfXR0tKGMt7e3furUqUWev3HjRr1ardZHRkYW+fyMGTP0wcHBBY59+umn+nr16hn2R40apff09NRnZWUVG6der9cfPHhQDxi++6ZMmaL39/cv8H9Fq9Xqb968qddqtfqPP/5YHxQUZHhu1apVekdHR33qvfzDVbDCn/P8SvP9bdIULjU1lfDwcMLDwwGliTA8PJzY2FhAuaU0cuRIQ/knn3ySmjVr8swzz3Dq1Cl27NjBm2++yZgxY4rtUFyRAnoHoLZRk3whmfgj8aYORwhRhdnbKy0optjKsrtimzZtCuynpqYyadIkgoKCcHV1xdHRkYiICMP3QnGaN29ueOzg4ICzszNXr14ttnxYWBhpaWn069cPgFq1atGrVy/DvGlXr14lLi6OHj16FHl+eHg4derUoWHDhiV6n8Vp1qyZUT+bw4cPExoaSt26dXFycqJLly4AhjoIDw/n4YcfLrYlY/To0URFRbFv3z4Ali1bxrBhw3AobXObGTPpbalDhw7RrVs3w35u35hRo0axbNky4uPjC3ygHR0dCQsL4+WXX6ZNmzbUrFmTYcOG8cEHH1R47EWxsrfCqbUTyXuSiVgVgXdrb1OHJISoolSq0t8aqowKf+FOmjSJsLAw5s+fT4MGDbCzs+PRRx8lOzv7jtcp/EWvUqnuOGrou+++48aNGwX+MNbpdBw/fpxZs2bd9Q/muz2vVqsNI5hyFTXap/D7T0tLIyQkhJCQEH7++Wfc3d2JjY0lJCTEUAd3e20PDw9CQ0NZunQp/v7+/PPPP2zbtu2O51Q1Jk1uunbtavSPn9+yZcuMjjVu3Nhwb7Iycu3gakhuun/YXaZKF0KIUti9ezejR49m8ODBgNKSc/78+TJ9jevXr/PHH3/w66+/0rRpU8NxrVbLQw89xL///kufPn3w8/Nj8+bNBf4Iz9W8eXMuXbrEmTNnimy9cXd3JyEhAb1eb/geyL1LcSenT5/m+vXrfPTRR/j6+gJKQ0Dh1/7+++/RaDTFtt6MGzeOJ554gjp16lC/fn06dep019euSip3zyIz5NzGGQsbC66fuc61iGumDkcIIcxKYGAgq1evJjw8nGPHjvHkk0+W+bwtP/74o6Hl/4EHHjBswcHB9OvXj++++w5QphJZsGABn3/+OWfPnuXIkSOGkVJdunShc+fODB06lLCwMGJiYvjnn3/YsGEDoPzxnpiYyNy5czl37hyLFi3in3/+uWtsdevWxdramoULFxIdHc2ff/7J+++/X6DMhAkTSElJ4fHHH+fQoUOcPXuWH3/8kbNnzxrKhISE4OzszAcffMAzzzxTVlVnNiS5KWMWdhb0XdSX5w4/R62gWqYORwghzMonn3yCm5sbHTt2JDQ0lJCQEFq1alWmr7FkyRIGDx5cZMv60KFD+fPPP7l27RqjRo3is88+48svv6Rp06Y88sgjBRKIVatW0bZtW5544gmaNGnC5MmTDatZBwUF8eWXX7Jo0SKCg4M5cOAAkyZNumts7u7uLFu2jN9++40mTZrw0UcfMX/+/AJlatasyZYtW0hNTaVLly60bt2a7777rkArjlqtZvTo0Wi12gJ9V6uLSjOJX0VJSUnBxcWlRJMAlZZGo2H9+vX069dPhrLeJnVSNKkXY1InxvLXiVarJSYmBn9/f5NONFcZ6HQ6UlJScHZ2rvRDmytKUXUyduxYEhMT+fPPP00cXcllZmYW+zkvzfe3Wc1zI4QQQog7S05O5sSJEyxfvtysEpuyJClvObm49yJrR6/lwKIDpg5FCCFENTJw4EB69+7NCy+8QK9evUwdjklIy005uXriKse+P0biyUTajW9n6nCEEEJUE9Vt2HdRpOWmnDQa2AhUEHcojqQLSaYORwghhKg2JLkpJ46ejtR7uB4Ap9ecNnE0QgghRPUhyU05ChoaBEDEqggTRyKEEEJUH5LclKOgIUpyE7s7ltSEVBNHI4QQQlQPktyUI+c6zvi09wE9RKyR1hshhBCiIkhyU86Chgbh3sQdawfruxcWQghxVwEBASxevNjUYYhKTJKbctZhYgdeOvkSwSODTR2KEEJUKJVKdcdt5syZ93Td/fv3M2rUqPuKrWvXrrz22mv3dQ1Reck8N+VMbSH5oxCieoqPjzc8XrFiBdOnTycyMtJwzNHR0fBYr9ej1WqxtLz715K7uzspKSllG6yoUuSbt4JoMjRc3HPR1GEIIUSFqV27tmFzcXFBpVIZ9k+fPo2TkxP//PMPrVu3xsbGhl27dnHu3DkGDhyIp6cnjo6OtG3blk2bNhW4buHbUiqVim+//ZbBgwdjb29PYGDgfS87sGrVKpo2bYqNjQ1+fn4sWLCgwPNffvklgYGB2Nra4unpyaOPPmp47vfff6dZs2bY2dlRs2ZNevbsSVpa2n3FI0pHkpsKcCvuFvPc57Gs6zIykzNNHY4QogrJTssudsvJzClxWU2GpkRly9rbb7/NRx99REREBM2bNyc1NZV+/fqxefNmjh49Sp8+fQgNDSU2NvaO15k1axbDhg3j+PHj9OvXj6eeeoobN27cU0yHDx9m2LBhPP7445w4cYKZM2cybdo0li1bBsChQ4d45ZVXeO+994iMjGTDhg107twZUFqrnnjiCcaMGUNERATbtm1jyJAhVLM1qk1ObktVACdvJ1x8Xbh2+hpn/j5D86eamzokIUQVMcdxTrHPBfYL5Ml1Txr253vMR5OuKbJsvS71GL1ttGH/f37/I/1aulG5GfoZ9x5sEd57770C6x/VqFGD4OC8Porvv/8+a9as4c8//2TChAnFXmf06NE88cQTAMyePZvPP/+cAwcO0KdPn1LH9Mknn9CjRw+mTZsGQMOGDTl16hTz5s1j9OjRxMbG4uDgwCOPPIKTkxP16tWjZcuWgJLc5OTkMGTIEOrVUyZybdasWaljEPdHWm4qiEzoJ4QQxtq0aVNgPzU1lUmTJhEUFISrqyuOjo5ERETcteWmefO8PxodHBxwdnbm6tWr9xRTREQEnTp1KnCsU6dOnD17Fq1WS69evahXrx4BAQGMGDGCn3/+mfR0JREMDg6mR48eNGvWjMcee4xvvvmGmzdv3lMc4t5Jy00FCRoaxM4PdxK1IYrstGwZGi6EKBNTUqcU+1zhAQ2Trk4qtqxKrSqw/+r5V+8vsBJycHAosD9p0iTCwsKYP38+DRo0wM7OjkcffZTs7DvfErOysiqwr1Kp0Ol0ZR4vgJOTE0eOHGHbtm38+++/TJ8+nZkzZ3Lw4EFcXV0JCwtjz549/PvvvyxcuJCpU6eyf/9+/P39yyUeYUxabipI7Ra1cfV3JScjh6gNUaYORwhRRVg7WBe7WdpalrislZ1VicqWt927dzN69GgGDx5Ms2bNqF27NufPny/3180vKCiI3bt3G8XVsGFDLCwsALC0tKRnz57MnTuX48ePc/78ebZs2QIoiVWnTp2YNWsWR48exdramjVr1lToe6jupOWmgqhUKoKGBrF3/l4iVkXQZGgTU4ckhBCVTmBgIKtXryY0NBSVSsW0adPKrQUmMTGR8PDwAse8vLx44403aNu2Le+//z7Dhw9n7969fPHFF3z55ZcA/P3330RHR9O5c2fc3NxYv349Op2ORo0asX//fjZv3kzv3r3x8PBg//79JCYmEhQUVC7vQRRNWm4qUG5Cc+bvM2iztSaORgghKp9PPvkENzc3OnbsSGhoKCEhIbRq1apcXmv58uW0bNmywPbNN9/QqlUrVq5cya+//soDDzzA9OnTee+99xg9ejQArq6urF69mu7duxMUFMRXX33FL7/8QtOmTXF2dmbHjh3069ePhg0b8u6777JgwQL69u1bLu9BFE1abiqQTzsfQj4NIbB/IBbWFqYORwghKszo0aMNyQEoMwQXNTzaz8/PcHsn1/jx4wvsR0dHF5jEr6jrJCUl3TGebdu23fH5oUOHMnTo0CKfe+ihh4o9PygoiA0bNtzx2qL8SXJTgVRqFQ++9qCpwxBCCCGqNLktJYQQQogqRZIbEzj9x2lWDFlBzNYYU4cihBBCVDmS3JjA2fVnOb3mNCdXnDR1KEIIIUSVI8mNCeSOmjq95jQ6bfkMcRRCCCGqK0luTMCvqx+2rrakXU3j4m5ZKVwIIYQoS5LcmICFtQWNBjQC4NSqUyaORgghhKhaJLkxkdyFNE+vPl3kHA1CCCGEuDeS3JhI/d71sXa0JuVSCnEH40wdjhBCCFFlSHJjIpa2ljR8pCF1HqyDJkNj6nCEEKLS6tq1K6+99pphPyAggMWLF9/xHJVKxdq1a+/7tcvqOqJiyQzFJjT4x8GoLSW/FEJUTaGhoWg0miKXI9i5cyedO3fm2LFjNG/evFTX3b9/P1pt2a7PN3PmTNauXWu0kGZ8fDxubm5l+lrFycjIwMfHB7VazeXLl7GxsamQ162K5JvVhCSxEUJUZWPHjiUsLIxLly4ZPbd06VLatGlT6sQGwN3dHXt7+7II8a5q165dYUnGqlWraNq0KY0bNzZ5a5FerycnJ8ekMdwP+XatBDJuZpBwLMHUYQghRJl65JFHcHd3Z9myZQWOp6am8ttvvzF27FiuX7/OE088gY+PD/b29jRr1oxffvnljtctfFvq7NmzdO7cGVtbW5o0aUJYWJjROW+99RYNGzbE3t6egIAApk2bhkajdAlYtmwZs2bN4tixY6hUKlQqlSHmwrelTpw4Qffu3bGzs6NmzZo899xzpKamGp4fPXo0gwYNYv78+Xh5eVGzZk3Gjx9veK07+e6773j66ad5+umn+e6774yeP3nyJI888gjOzs44OTnx8MMPc+7cOcPzP/30E82aNcPGxgYvLy8mTJgAwPnz51GpVAVapZKSklCpVIYFQLdt24ZKpeKff/6hdevW2NjYsGvXLs6dO8fAgQPx9PTE0dGRtm3bsmnTpgJxZWVl8dZbb+Hr64uNjQ0NGjTgu+++Q6/X06BBA+bPn1+gfHh4OCqViqioqLvWyb2S21Imdi7sHMv7Ladmw5q8dPIlU4cjhDATer2edE26SV7b3soelUp113KWlpaMHDmSZcuWMXXqVMM5v/32G1qtlieeeILU1FRat27NW2+9hbOzM+vWrWPEiBHUr1+fdu3a3fU1dDodQ4YMwdPTk/3795OcnFygf04uJycnli1bhre3NydOnODZZ5/FycmJyZMnM3z4cP777z82bNhg+OJ2cXExukZaWhohISF06NCBgwcPcvXqVcaNG8eECRMKJHBbt27Fy8uLrVu3EhUVxfDhw2nRogXPPvtsse/j3Llz7N27l9WrV6PX63n99de5cOEC9erVA+Dy5ct07tyZrl27smXLFpydndm9e7ehdWXx4sW8+eabzJkzh379+pGcnMzu3bvvWn+Fvf3228yfP5+AgADc3Ny4ePEi/fr148MPP8TGxoYffviB0NBQIiMjqVu3LgAjR45k7969fP755wQHBxMTE8O1a9dQqVSMGTOGpUuXMmnSJMNrLF26lM6dO9OgQYNSx1dSktyYmE9bH1BB4qlErp2+Rq3GtUwdkhDCDKRr0nGc42iS106dkoqDtUOJyo4ZM4Z58+axfft2unbtCihfbkOHDsXFxQUXF5cCX3wvv/wyGzduZOXKlSVKbjZt2sTp06fZuHEj3t7eAMyePZu+ffsWKPfuu+8aHvv5+TFp0iR+/fVXJk+ejJ2dHY6OjlhaWlK7du1iX2v58uVkZmbyww8/4OCgvP8vvviC0NBQPv74Yzw9PQFwc3Pjiy++wMLCgsaNG9O/f382b958x+RmyZIl9O3b19C/JyQkhKVLlzJz5kwAFi1ahIuLC7/++itWVlYANGzY0HD+7NmzGT9+PK+88gpqtXJTpm3btnetv8Lee+89evXqZdivUaMGwcHBhv3333+fNWvW8OeffzJhwgTOnDnDypUrCQsLo2fPnoDSspZr9OjRTJ8+nQMHDtCuXTs0Gg3Lly83as0pa3JbysRsXW0J6KF8EGRCPyFEVdO4cWM6duzIkiVLAIiKimLnzp2MHTsWAK1Wy/vvv0+zZs2oUaMGjo6ObNy4kdjY2BJdPyIiAl9fX0NiA9ChQwejcitWrKBTp07Url0bR0dH3n333RK/Rv7XCg4ONiQ2AJ06dUKn0xEZGWk41rRpUywsLAz7Xl5eXL16tdjrarVavv/+e55++mnDsaeffpply5ah0ylL9ISHh/Pwww8bEpv8rl69SlxcHF26dCnV+ylKmzZtCuynpqYyadIkgoKCcHV1xdHRkYiICEPdhYeHY2FhUexre3t7079/f8O//19//UVWVhaPPfbYfcd6J9JyUwkEDQ0iakMUEasi6Dy1s6nDEUKYAXsre1KnpN69YDm9dmmMHTuWl19+mUWLFrF06VLq169v+DKcN28e//vf//jss89o1qwZDg4OvPbaa2RnZ5dZvHv37uWpp55i1qxZhISEGFpAFixYUGavkV/hBESlUhmSlKJs3LiRy5cvM3z48ALHtVotmzdvplevXtjZ2RV7/p2eAwwtOfknjC2uD1D+xA1g0qRJhIWFMX/+fBo0aICdnR2PPvqo4d/nbq8NMG7cOEaMGMGnn37K0qVLGT58eLl3CJeWm0qg0cBGqNQqEo4mcDP6pqnDEUKYAZVKhYO1g0m2kvS3yW/YsGGo1WqWL1/ODz/8wJgxYwzX2L17NwMHDuTpp58mODiYgIAAzpw5U+JrBwUFcfHiReLj4w3H9u3bV6DMnj17qFevHlOnTqVNmzYEBgZy4cKFAmWsra3vOrw8KCiIY8eOkZaWZji2e/du1Go1jRo1KnHMhX333Xc8/vjjhIeHF9gef/xxQ8fi5s2bs3PnziKTEicnJ/z8/Ni+fXuR13d3dwcoUEeFh7wXZ/fu3YwePZrBgwfTrFkzateuzfnz5w3PN2vWDJ1OV+xrA/Tr1w8HBwcWL17Mhg0bGDNmTIle+35IclMJOLg7UK+z0mksYk2EiaMRQoiy5ejoyPDhw5kyZQrx8fGMHj3a8FxgYCBhYWHs2bOHiIgInn/+ea5cuVLia/fs2ZOGDRsyatQojh07xs6dO5k6dWqBMoGBgcTGxvLrr79y7tw5Pv/8c9asWVOgjJ+fHzExMYSHh3Pt2jWysrKMXuupp57C1taWUaNG8d9//7F161ZefvllRowYYehvU1qJiYn89ddfjBo1igceeKDANnLkSNauXcuNGzeYMGECKSkpPP744xw6dIizZ8/y448/Gm6HTZ8+nUWLFrFw4ULOnj3LkSNHWLhwIaC0rjz44IN89NFHREREsH379gJ9kO4kMDCQ1atXEx4ezrFjx3jyyScLtEL5+fkxatQoxowZw9q1a4mJiWHbtm2sXLnSUMbCwoLRo0czZcoUAgMDi7xtWNYkuakk8q81JYQQVc3YsWO5efMmISEhBfrHvPvuu7Rq1YqQkBC6du1K7dq1GTRoUImvq1arWbNmDRkZGbRr145x48bx4YcfFigzYMAAXn/9dSZMmECLFi3Ys2cP06ZNK1Bm6NCh9OnTh27duuHu7l7kcHR7e3s2btzIjRs3aNu2LY8++ig9evTgiy++KF1l5JPbOblHjx5Gz/Xo0QM7Ozt++uknatasyZYtW0hNTaVLly60bt2ab775xnALbNSoUcyePZvFixfTtGlTHnnkEc6ePWu41pIlS8jJyaF169a89tprfPDBByWK75NPPsHNzY2OHTsSGhpKSEgIrVq1KlBm8eLFPProo7z00ks0btyYZ599tkDrFij//tnZ2TzzzDOlraJ7otJXs1UbU1JScHFxITk5GWdn5zK9tkajYf369fTr16/ITl93civ+FqfXnqbxoMY4eTmVaVymdD91UpVJvRiTOjGWv060Wi0xMTH4+/tja2tr6tBMSqfTkZKSgrOzs6E/SXVX2etk586d9OjRg4sXL96xlSszM7PYz3lpvr+lQ3El4eTlRNsXSz9sTwghhKissrKySExMZObMmTz22GP3fPuutCpfeieEEEKIKuGXX36hXr16JCUlMXfu3Ap7XZMmNzt27CA0NBRvb+9Sr7y6e/duLC0tadGiRbnFV9H0ej2HvjrEj71/JO1q2t1PEEIIISqx0aNHo9VqOXz4MD4+PhX2uiZNbtLS0ggODmbRokWlOi8pKYmRI0cW2QHLnKlUKo58c4TosGhO/yEdi4UQQoh7YdI+N3379jWaIrskXnjhBZ588kksLCxMvnJqWQsaGkT8kXgiVkXQ+tnWpg5HCCGEMDtm16F46dKlREdH89NPP5VoKFtWVlaB+QpSUlIAZRRCSVZpLY3c693PdQMHBLJl6hZiNseQcjUFO7e7z/5YmZVFnVRFUi/GpE6M5a8TrVaLXq9Hp9Pdcbbb6iB3kG9ufYiqUyc6nQ69Xo9GoymwhAWU7neDWSU3Z8+e5e2332bnzp1YWpYs9Dlz5jBr1iyj4//++2+5Tf8cFhZ2X+fb1rUlMzaTVbNXUaNbjTKKyrTut06qKqkXY1InxsLCwgyLOqamppbp0gTm7NatW6YOodIx9zrJzs4mIyODHTt2GFY8z5Wenl7i65hNcqPVannyySeZNWtWgZVQ72bKlClMnDjRsJ+SkoKvry+9e/cul3luwsLC6NWr133N0+F40JFdH+7C5pwN/eb1K8MIK15Z1UlVI/ViTOrEWP460Wq1XLx4EUdHx2o/z41er+fWrVs4OTmVeimIqqqq1ElmZiZ2dnZ07ty5yHluSspskptbt25x6NAhjh49yoQJE4C85itLS0v+/fdfunfvbnSejY0NNjY2RsetrKzK7Rfo/V77gWEPsOvDXUSHRaPL1GHjZBy/uSnP+jZnUi/GpE6MWVlZoVarUalUqNXqSjlJW0XKve2SWx+i6tRJ7ue8qN8Dpfm9YDY14OzszIkTJwosKvbCCy/QqFEjwsPDad++valDLDMezTyoFVQLvy5+pCeWvBlOCCGqoq5du/Laa68Z9gMCAli8ePEdzynt9CLlfR1RsUzacpOamkpUVJRhP3fRsho1alC3bl2mTJnC5cuX+eGHH1Cr1TzwwAMFzvfw8MDW1tbouLlTqVS8cOwFLKws7l5YCCEqqdDQUDQaDRs2bDB6bufOnXTu3Jljx47RvHnzUl13//79d13Bu7RmzpzJ2rVrjVbLjo+Px83NrUxfq7Bly5bx2muvkZSUVK6vU52YtOXm0KFDtGzZkpYtWwIwceJEWrZsyfTp0wHlQxUbG2vKEE1GEhshhLkbO3YsYWFhXLp0yei5pUuX0qZNm1InNgDu7u7lNiCksNq1axfZtUFUbiZNbrp27Yperzfali1bBijZ7LZt24o9f+bMmUZZdlWTcjmFm9E3TR2GEEKU2iOPPIK7u7vhd3qu1NRUfvvtN8aOHcv169d54okn8PHxwd7enmbNmhW5Ind+hW9LnT171tABtUmTJkWOuHvrrbdo2LAh9vb2BAQEMG3aNMPQ4mXLljFr1iyOHTuGSqVCpVIZYi58W+rEiRN0794dOzs7atasyXPPPUdqaqrh+dGjRzNo0CDmz5+Pl5cXNWvWZPz48fc1xUFsbCwDBw7E0dERZ2dnhg0bxpUrVwzPHzt2jB49euDr64urqyutW7fm0KFDAFy4cIHQ0FDc3NxwcHCgadOmrF+//p5jMRdm06G4Otr7yV7+feNfgkcGM+j7QaYORwhRCd1poRYLIP94kzuVVQP5Z9UqrqxDCeMCsLS0ZOTIkSxbtoypU6caRvH89ttvaLVannjiCVJTU2ndujVvvfUWzs7OrFu3jhEjRlC/fn3atWt319fQ6XQMGTIET09P9u/fT3JycoH+ObmcnJxYtmwZ3t7enDhxgmeffRYnJycmT57M8OHD+e+//9iwYQObNm0CwMXFxegaaWlphISE0KFDBw4ePMjVq1cZN24cEyZMKJDAbd26FS8vL7Zu3UpUVBTDhw+nRYsWPPvss6Wovbz3l5vYbN++nZycHMaPH8/w4cMNf/w/9dRTtGjRgo8//hgXFxeOHz9u6Hw7fvx4srOz2bFjBw4ODpw6dQpHR8dSx2FuJLmpxLzbegMQ+Wck2mwtFtZyq0oIUdCdvqb6Aevy7XsAxQ1R6AJsy7fvB1wropy+FLEBjBkzhnnz5rF9+3a6du0KKLekhg4diouLCy4uLkyaNMlQ/uWXX2bjxo2sXLmyRMnNpk2bOH36NBs3bsTbW/mdOXv2bKPZ799999289+bnx6RJk/j111+ZPHkydnZ2ODo6GuYSKs7y5cvJzMzkhx9+wMFBSfO++OILQkND+fjjjw0rXru5ufHFF19gYWFB48aN6d+/P5s3b76n5Gbz5s2cOHGCmJgYfH19Afjhhx9o2rQpBw8epG3btsTGxvLGG2/QsGFDnJ2dadSokeH82NhYhg4dSrNmzQCl1as6MJvRUtWRb0dfHDwdyEzKJGZrjKnDEUKIUmvcuDEdO3ZkyZIlAERFRbFz507Gjh0LKHOYvf/++zRr1owaNWrg6OjIxo0bS9zfMiIiAl9fX0NiA9ChQwejcitWrKBTp07Url0bR0dH3n333VL36YyIiCA4ONiQ2AB06tQJnU5HZGSk4VjTpk0LzK7r5eXF1atXS/Va+V/T19fXkNgANGnSBFdXVyIiIgClv+pzzz3HoEGD+Pjjjzl37pyh7CuvvMIHH3xAp06dmDFjBsePH7+nOMyNJDeVmNpCTePBjQGIWBVh4miEEJVR6h22VYXKXr1D2X8KlT1fTLl7MXbsWFatWsWtW7dYunQp9evXp0uXLgDMmzeP//3vf7z11lts3bqV8PBwQkJCynQW5r179/LUU0/Rr18//v77b44ePcrUqVPLbabnwvOxqFSqcl0SYebMmZw4cYLevXuzZcsWmjRpwpo1awAYN24c0dHRjBgxghMnTtCmTRsWLlxYbrFUFpLcVHJNhjYB4PTa0+i05rteiBCifDjcYSs8j/GdyhZexa64cvdi2LBhqNVqli9fzg8//MCYMWMM/W92797NwIEDefrppwkODiYgIIAzZ86U+NpBQUFcvHiR+Ph4w7F9+/YVKLNnzx7q1avH1KlTadOmDYGBgVy4cKFAGWtr67sOLw8KCuLYsWOkpeX1SNq9ezdqtbrAraCylPv+Ll68aDh26tQpkpKSaNKkieFYw4YNeemll9i4cSNDhgxh6dKlhud8fX154YUXWL16NW+88QbffPNNucRamUhyU8nV61IPuxp2pCemE7uzeg6LF0KYN0dHR4YPH86UKVOIj49n9OjRhucCAwMJCwtjz549RERE8PzzzxcYCXQ3PXv2pGHDhowaNYpjx46xc+dOpk6dWqBMYGAgsbGx/Prrr5w7d47PP//c0LKRy8/PzzDX2rVr1wosuJzrqaeewtbWllGjRvHff/+xdetWXn75ZUaMGGHob3OvtFptgUlqw8PDiYiIoGfPnjRr1oynnnqKI0eOcODAAUaOHEmXLl1o06YNGRkZTJgwgW3bthEbG8vu3bs5ePAgQUFBALz22mts3LiRmJgYjhw5wtatWw3PVWWS3FRyFlYWNBqg/EUQsVpuTQkhzNPYsWO5efMmISEhBfrHvPvuu7Rq1YqQkBC6du1K7dq1GTRoUImvq1arWbNmDRkZGbRr145x48bx4YcfFigzYMAAXn/9dSZMmECLFi3Ys2cP06ZNK1Bm6NCh9OnTh27duuHu7l7kcHR7e3s2btzIjRs3aNu2LY8++ig9evTgiy++KF1lFCE1NdUw71vuFhoaikql4o8//sDNzY3OnTvTs2dPAgICWLFiBQAWFhZcv36d0aNH07ZtWx5//HH69u1rWDBaq9Uyfvx4goKC6NOnDw0bNuTLL7+873grO5U+d530aiIlJQUXFxeSk5PLZeHM9evX069fvzJdG+fywctcj7xOw0caYutqXgvmlVedmDupF2NSJ8by14lWqyUmJgZ/f/9qv3CmTqcjJSUFZ2dns15HqSxVlTrJzMws9nNemu9vGQpuBnza+uDT1sfUYQghhBBmwXzTOyGEEEKIIkhyYyayUrLY9fEuVgxZQTW7kyiEEEKUityWMhMqCxXbZ20nJyOHhPAEvFp6mTokIYQQolKSlhszYe1gTWDfQEAm9BOiOpOWW1GVldXnW5IbMxI0VJmbQJIbIaqf3On8y2tWXSEqg9zPd/7lK+6F3JYyIw0faYiFtQXXTl8j8VQi7k3cTR2SEKKCWFpaYm9vT2JiIlZWVmY93Pd+6XQ6srOzyczMrNb1kF9VqBOdTkdiYiL29vZYWt5feiLJjRmxcbYhoFcAZ9ed5dSqU3Rp0sXUIQkhKohKpcLLy4uYmBijpQOqG71eT0ZGBnZ2doZlHKq7qlInarWaunXr3vd7kOTGzAQNDeLsurNErIqgyzRJboSoTqytrQkMDKz2t6Y0Gg07duygc+fOMuHjbVWlTqytrcuk5UmSmzL2X82a9ALK66PVaEAjbJxtqNGgBjlZOVjayD+hENWJWq2u9jMUW1hYkJOTg62trVl/kZclqZOC5JuxDH2lVjOtUyfO6vUsBcqjYdC+pj1vJr6JhfX9dbYSQgghqirz7HVUSfnq9aiA79Vq3ivH15HERgghhCieJDdlqL9ez/PHjgEwE1hazq937fQ10q+nl/OrCCGEEOZFkpsyFnLhApO1WgCeA/4tp9dZO2oti4IWceLnE+X0CkIIIYR5kuSmHLyv0/EUkAMMBcLL4TVqt6wNyIR+QgghRGGS3JQDFbAE6AakAn+Ww2sEDVFmK76w8wKpV1LL4RWEEEII8yTJTTmxBlaj9LuZXg7Xd6nrgndbb9DD6bWny+EVhBBCCPMkyU05cgVG59vPBrLK8Pqy1pQQQghhTJKbCpIM9AXGALoyumaToU0AOL/1PBk3MsroqkIIIYR5k+SmghwDdgDLgalldM0aDWrg2dwTXY6OyD8jy+iqQgghhHmTGYorSGfgW5TbVB8B9YAXyuC6Xd/rikqlon7v+mVwNSGEEML8SXJTgUYBsSgdjMcDPkDofV6z8cDG9xuWEEIIUaXIbakK9i4wDqXfzePAQdOGI4QQQlQ5ktxUMBXwJdAHSAfDZH/3Izk2mc1TN/Pvm+U1H7IQQghhPiS5MQErYCUwAGUunPu9N5iWmMau2bs49OUhNOma+45PCCGEMGeS3JiIE/AH8EAZXMurlReufq5o0jVEbYwqgysKIYQQ5kuSm0piBzAW0N7DuSqVisZDlI7FMqGfEEKI6k6Sm0rgJsqoqSXAG/d4jdwJ/c78dYacrPvtxSOEEEKYL0luKgE34Ovbj/8HfHoP16jzYB2cvJ3ISskiZnNM2QUnhBBCmBlJbiqJx4G5tx+/AfxeyvNVahWNByu3pk6tOlWGkQkhhBDmRZKbSmQSyuR+euBpYFcpzw8aGoRdTTvs3OzKPDYhhBDCXMgMxZWICuW21CWUkVQDgQNASRdW8Ovix6SESagtJWcVQghRfUlyU8lYoCyu2R3wB+qU4lyVWoVKrSqXuIQQQghzIX/iV0L2wL/Az4DNPZyv1+uJOxSHXqcv28CEEEIIMyDJTSXlTN4/jg5lmHhJBnjr9Xq+Cv6Kb9p+w8U9F8stPiGEEKKykuTGDIxDmeBvAkpn4ztRqVR4NvcEIPz78PINTAghhKiEJLkxAwNQOht/DXxUgvItnmkBwNFvj3J67enyC0wIIYSohCS5MQODgM9vP34HpS/OnQT0CODB1x8EYO2otdyIulF+wQkhhBCVjCQ3ZmICyjw4AM8AW+5SvufHPfHt5EtWShYrh66U1cKFEEJUGyZNbnbs2EFoaCje3t6oVCrWrl17x/KrV6+mV69euLu74+zsTIcOHdi4cWPFBFsJfAwMBzTAYOC/O5S1sLLgsZWP4eDhwJXjVwh7K6xCYhRCCCFMzaTJTVpaGsHBwSxatKhE5Xfs2EGvXr1Yv349hw8fplu3boSGhnL06NFyjrRyUAPLgM5AJnDuLuWdvJ0Y+utQ6jxYh46TOpZ3eEIIIUSlYNJJ/Pr27Uvfvn1LXP6zzz4rsD979mz++OMP/vrrL1q2bFnkOVlZWWRlZRn2U1JSANBoNGg0ZXurJvd6ZX3d/CyAlcAZlYoH9Xru9kp1HqrDiO0jUKlU5RpXcSqiTsyR1IsxqRNjUidFk3oxVh3qpDTvzaxnKNbpdNy6dYsaNWoUW2bOnDnMmjXL6Pi///6Lvb19ucQVFlYxt4DW3/55w8YGp+xsrPR3n7Qv5UgK9oH2WDpV7D99RdWJuZF6MSZ1YkzqpGhSL8aqcp2kp6eXuKxZJzfz588nNTWVYcOGFVtmypQpTJw40bCfkpKCr68vvXv3xtnZuUzj0Wg0hIWF0atXL6ysrMr02sU5AYy3tKSbXs93Wi13WnzhwMIDhL8XToN+DXhs9WMVslSDKerEHEi9GJM6MSZ1UjSpF2PVoU5y77yUhNkmN8uXL2fWrFn88ccfeHh4FFvOxsYGGxvjRQysrKzK7QNQntcu7AqQAPykUuGnVvP+HcoGdAvAwsaCqPVR7F+wn4ffebhCYoSKrRNzIvViTOrEmNRJ0aRejFXlOinN+zLLoeC//vor48aNY+XKlfTs2dPU4ZhUX+Cr248/AL65Q1mvll70W9QPgK3TthK9ObqcoxNCCCEqntklN7/88gvPPPMMv/zyC/379zd1OJXCOODd249fBP65Q9lWY1vR4pkW6HV6Vj2xipTLJW/mE0IIIcyBSZOb1NRUwsPDCQ8PByAmJobw8HBiY2MBpb/MyJEjDeWXL1/OyJEjWbBgAe3btychIYGEhASSk5NNEX6l8h4wEtACjwGH71C236J+eAZ7kp6Yzu/Dfker0VZIjEIIIURFMGlyc+jQIVq2bGkYxj1x4kRatmzJ9OnTAYiPjzckOgD/93//R05ODuPHj8fLy8uwvfrqqyaJvzJRodyS6gmkoSzTUBwrOyuG/T4MGxcbLu65KOtPCSGEqFJM2qG4a9eu6O8wfHnZsmUF9rdt21a+AZk5a+B3lMRm9l3K1mhQg8E/DCYzOZOmjzUt/+CEEEKICmK2o6VE0VyAwvM96yi6ia7RgEblH5AQQghRwcyuQ7EonQXAECDnLuXSrqbx9wt/k52aXQFRCSGEEOVHWm6qsBiUUVSZwEvA11DkJH96vZ7ljywn7mAc2beyGfzTYFSq8p/gTwghhCgP0nJThfkDy1H+kb9BGVFVFJVKRe8FvVFZqDix/ASHFh+qsBiFEEKIsibJTRU3mLw+ODOB/yumXL2H69HzI2VCxA2vbeDygcvlH5wQQghRDiS5qQZeoOAkf38WU67DGx0IGhKETqPjt8d+I/16yRcpE0IIISoLSW6qifeAMSgjpx4HYosoo1KpGLBkADUa1CA5NpnVT61Gp9VVaJxCCCHE/ZLkpppQoaxBFQrMBeoWU87WxZZhq4ZhaWfJzeibpF1Jq7AYhRBCiLIgo6WqESvgD4oeMZWfZ3NPnlz3JF6tvLB1sa2AyIQQQoiyIy031Uz+xOYm8DxQ1Mpc/t38CyQ2el3xM0kLIYQQlYkkN9XYoyijpwYDWcWU0ev17P98P8u6LCMn625TAQohhBCmJ8lNNTYPcAS2AqNQOhsXlnY1jW0ztxG7K5Z/3/i3QuMTQggh7oUkN9VYK2A1SserFcCkIso4ejoy+MfBABxcdJATy09UXIBCCCHEPZDkpprrBSy7/fhTlLWoCmvYvyEPT30YgL+e/YurJ69WTHBCCCHEPZDkRvAUyi0qUFpvfi2iTNdZXfHv4Y8mXcPKoSvJulVcLx0hhBDCtCS5EQC8AbyGMv9NiyKeV1uoGbp8KE4+TlyPvM5f4/5Cr5cRVEIIISofSW4EoAwRXwAcBhoXU8bBw4HHfnsMSztLvNt6V1xwQgghRCnIJH7CQA3Uyre/BWVlcf98x3w7+PJqzKs4ejpWaGxCCCFESUnLjSjS30AfIAS4Vui5/IlNdmq2LLAphBCiUil1cuPn58d7771HbGxRSy+KqqIV4AWcBR4Bilph6trpa3zT7ht+H/67LLAphBCi0ih1cvPaa6+xevVqAgIC6NWrF7/++itZWTJypqrxBjYCNYD9wHCg8PzEOq2O5AvJxGyOYduMbRUcoRBCCFG0e0puwsPDOXDgAEFBQbz88st4eXkxYcIEjhw5Uh4xChNpjHJ7yg5Yh7IOVf7xUR5NPQj9JhSAnR/u5My6MxUeoxBCCFHYPfe5adWqFZ9//jlxcXHMmDGDb7/9lrZt29KiRQuWLFkiw4SriA4o896ogSXAjELPN3uyGW3HtwVgzYg1JJ1PqtD4hBBCiMLuObnRaDSsXLmSAQMG8MYbb9CmTRu+/fZbhg4dyjvvvMNTTz1VlnEKExoAfHX78XmM16DqvaA3Pu18yLyZycpHV5KTKQtsCiGEMJ1SDwU/cuQIS5cu5ZdffkGtVjNy5Eg+/fRTGjfOmx1l8ODBtG3btkwDFab1LMqQ8B4oc+LkZ2ljyWO/PcbXrb4m/nA8W6Ztofe83hUfpBBCCME9JDdt27alV69eLF68mEGDBmFlZWVUxt/fn8cff7xMAhSVR898j7XAOaDh7X2Xui4M+XkIuz/eTYeJHSo+OCGEEOK2Uic30dHR1KtX745lHBwcWLp06T0HJSq3TJT1qLYCu4Amt483CGlA/d71UakKt+0IIYQQFafUfW6uXr3K/v37jY7v37+fQ4cOlUlQonLTAfHATZSJ/i7ney5/YnN67WkykzMrNjghhBDVXqmTm/Hjx3Px4kWj45cvX2b8+PFlEpSo3OyBv4BGwEWgL5BUqMyOD3ewYvAK1j27TkbOCSGEqFClTm5OnTpFq1atjI63bNmSU6dOlUlQovKrCWwAagMngEEot6ty1e9VH7WVmsi1kST+kWiCCIUQQlRXpU5ubGxsuHLlitHx+Ph4LC1lHc7qxA/4B3ACtgMjyRsm7tPOhz6f9QEg7oc4Tq44aYoQhRBCVEOlTm569+7NlClTSE5ONhxLSkrinXfeoVevXmUanKj8WgBrASuUW1Un8j3X5sU2NHu6GejgjxF/sHXGVvQ6uUUlhBCifJW6qWX+/Pl07tyZevXq0bJlSwDCw8Px9PTkxx9/LPMAReXXHfgZ8AGC8x1XqVT0/6Y/CakJJK5NZMd7O7h57iaDfxwsI6qEEEKUm1InNz4+Phw/fpyff/6ZY8eOYWdnxzPPPMMTTzxR5Jw3onp4rNB+FmADqC3U+Iz2oV3/dvzz0j/49/CXxEYIIUS5uqdOMg4ODjz33HNlHYuoIo4CA4FvUFp1AIJHBVO/R33c/N0M5XQ5OtSW97wCiBBCCFGke+4BfOrUKWJjY8nOzi5wfMCAAfcdlDBvX6EMER8KbM53PH9ik5aYxrIuy+gyvQsPPP5ABUcohBCiKrunGYoHDx7MiRMnUKlUhjlMcm81aLXaso1QmJ2FQDSwCRhgackse3ujMvs/38+1iGusemIViacS6TqzKyq13K4SQghx/0p9T+DVV1/F39+fq1evYm9vz8mTJ9mxYwdt2rRh27Zt5RCiMDfWwCqUkVRXVSpmdejAgUL9bLrO7ErHNzsCsOP9Hfw27Dey07ILX0oIIYQotVInN3v37uW9996jVq1aqNVq1Go1Dz30EHPmzOGVV14pjxiFGXJGmQPHT68nwdGRhywtCSVvHhy1hZpec3sxcOlA1FZqIlZFsKzzMlIupZguaCGEEFVCqZMbrVaLk5MTALVq1SIuLg6AevXqERkZWbbRCbNWG9iSk0P32Fgs9Ho8MP7AtRjdglFbR2Hvbk/8kXi+afsNV04YTxIphBBClFSpk5sHHniAY8eOAdC+fXvmzp3L7t27ee+99wgICCjzAIV5qwO8cvQo/+XkMCvf8RNAL2AnULdTXZ498CwezTywdrLGuY6zSWIVQghRNZS6Q/G7775LWloaAO+99x6PPPIIDz/8MDVr1mTFihVlHqCoGuqjzGKc60OUDsebUIaLz/BzZczuMaRfS8fOzc5QTq/Xy7w4QgghSqXUyU1ISIjhcYMGDTh9+jQ3btzAzc1NvoREiX0EuABLgS23t65ONsxwsqHr7TIHFx8kZnMMg74fhLWDtYkiFUIIYW5KdVtKo9FgaWnJf//9V+B4jRo1JLERpeIHfA1EAS+gtOpsA7qhzHaclphG2KQwIlZFsPThpdLRWAghRImVKrmxsrKibt26MpeNKDN1gcXAOeAllGHk7QAHdwee/vdp7NztiT+awDdtv+HS/kumDFUIIYSZKHWH4qlTp/LOO+9w48aN8ohHVFO+wCLykhxQOhp7/fcSPx55jmMPeLC0yzJO/HKi+IsIIYQQ3ENy88UXX7Bjxw68vb1p1KgRrVq1KrCVxo4dOwgNDcXb2xuVSsXatWvves62bdto1aoVNjY2NGjQgGXLlpX2LYhKrA7gkG//Sw8Holt68WPYCP5vyyjmLjvGlhlbTRWeEEIIM1DqDsWDBg0qsxdPS0sjODiYMWPGMGTIkLuWj4mJoX///rzwwgv8/PPPbN68mXHjxuHl5VWgo7OoOlYBc4Gv9XoudfTlp41PcyTuFvOBPoD09BJCCFFYqZObGTNmlNmL9+3bl759+5a4/FdffYW/vz8LFiwAICgoiF27dvHpp59KclNFeQOfAW+pVMwDFmt1nPJ2oh8wFvjWlMEJIYSolO55VXBT2Lt3Lz179ixwLCQkhNdee63Yc7KyssjKyjLsp6Qoo240Gg0ajaZM48u9Xllf15yVVZ3UAj4GJgKfoOcrtZreqZn8MOQ3Os/sjEc7Hywxn5Yc+awYkzoxJnVSNKkXY9WhTkrz3kqd3KjV6jsO+y7PkVQJCQl4enoWOObp6UlKSgoZGRnY2dkZnTNnzhxmzZpldPzff//FvojVqstCWFhYuVzXnJVlnXQBWlhbk/hVDNc2JXJ++3mOr+nP0U71GR4ZSbuEBLNJcuSzYkzqxJjUSdGkXoxV5TpJT08vcdlSJzdr1qwpsK/RaDh69Cjff/99kUmEqU2ZMoWJEyca9lNSUvD19aV37944O5ftNP8ajYawsDB69eqFlZXV3U+oBsqzTrIfzObPUX9yet1ZNjWtT7KrK3PatydYr2eqVssAvb70PeYriHxWjEmdGJM6KZrUi7HqUCe5d15KotTJzcCBA42OPfroozRt2pQVK1YwduzY0l6yxGrXrs2VKwUXVbxy5QrOzs5FttoA2NjYYGNjY3Tcysqq3D4A5Xltc1UedWLlZsXjax9n89TNZLT5P/a+0ZFDr7XnmJ0VwywtaQ7MAAZxD8MCK4h8VoxJnRiTOima1IuxqlwnpXlfZfY7/8EHH2Tz5s1ldbkidejQweg1wsLC6NChQ7m+rqi8VGoVPef05KlPQwiZuY1X6nxKn2+P4KTTcxwYCrxj6iCFEEJUqDJJbjIyMvj888/x8fEp1XmpqamEh4cTHh4OKEO9w8PDiY2NBZRbSiNHjjSUf+GFF4iOjmby5MmcPn2aL7/8kpUrV/L666+XxdsQZix4RDCjto7C3VJNrxnbOHEllXcBV2B0vnKngQumCFAIIUSFKfVtqcILZOr1em7duoW9vT0//fRTqa516NAhunXrZtjP7RszatQoli1bRnx8vCHRAfD392fdunW8/vrr/O9//6NOnTp8++23MgxcAODb0ZdxB8aReTOT2l5OvI/SapP/huVUYDXK2lZdUTond729L4QQomoodXLz6aefFkhu1Go17u7utG/fHjc3t1Jdq2vXruj1+mKfL2r24a5du3L06NFSvY6oPlzruUK9vP3olSdJOJZA9/e7o1KryAIsgPPAstsbKKf0Av4P8xlOLoQQomilTm5Gjx5dDmEIUfZuxd1i7ei15GTkcC3iGoN/GMzfjtbcAvagrEK+HTiIcqvqFAUTm+koLTpdgAAk6RFCCHNR6j43S5cu5bfffjM6/ttvv/H999+XSVBClAUnbyce+foRLKwtOL3mNEseWkJybDJOQAgwByXJuQlsRBlZlSsZ+BBlFuQGKKuXj0CZETkKKL69UQghhKmVOrmZM2cOtWrVMjru4eHB7NmzyyQoIcpK8IhgRm0bhYOHA1eOXeH/Wv8fkX9FFijjCPS+veXSAFOAToAVcAn4CXgWCARezFdWjyQ7QghRmZQ6uYmNjcXf39/oeL169Qp0/hWisvDtoHQ0rt2iNunX0vl1wK+sn7D+jv29agEfALuAJGAT8C7wEEqy0zJf2QiU1cyfQumzcwZJdoQQwpRKndx4eHhw/Phxo+PHjh2jZs2aZRKUEGXNtZ4rY/eNpcMbypxIdjXs7riMSH72QA/gfWAnSrLzdL7ntwNxwHLgeaAR4AM8AXwNxJfJOxBCCFFSpe5Q/MQTT/DKK6/g5ORE586dAdi+fTuvvvoqjz/+eJkHKERZsbSxpPf83gQNCcK7rbfheOqVVOxr2aO2KFmuX3hFstFAEEoH5W3AXpSE5tfbW13A63bZC0AGSgdlIYSoClKAvwEHwHgNA9ModXLz/vvvc/78eXr06IGlpXK6Tqdj5MiR0udGmAXfjr6Gx9psLT/3/RlrR2sG/zhYGUpeSnYoc+V0vb2fAexHadHZjtJvJ9dilNXNPS0t8XnwQTar1TQBGt/ePJFRWUKIyu8m8CewCmVARjbQDjNObqytrVmxYgUffPAB4eHh2NnZ0axZM+rVq3f3k4WoZBKOJXDj7A2yU7P5qvlX9PuyH82fan5f1yyc7OSXDtgCV1Qqrnh6cqTQ8/FA7duPt6L8AmmMMmLL+r6iEkKI+/cT8DNKP8ScfMcboQzK0FE51vIrdXKTKzAwkMDAwLKMRYgK59PWh+fDn2fN02u4tO8Sa55ew9l1Z+n/ZX9sXW3L/PU+B+YB+3NyWHniBNbNm3PGwoLTKH15PPOV/R/wx+3HFoA/eS08jYBRKJ2bhRCivCQC7vn21wAbbj9+AHj09taEytXqXOoEa+jQoXz88cdGx+fOnctjjz1WJkEJUZFq1K/BMzufocvMLqgsVPz3y398FfwV57efL5fXswE66PX0io3lY52Ov1Hmzomn4C+HIKAt4ARob5f5G5gPvEbBv0ymoczJMw/4CzhLwb+qhBCipC6h/CHWGeUPrjP5nnseZQ6w08AJlPnBmlK5Ehu4h5abHTt2MHPmTKPjffv2ZcGCBWURkxAVTm2ppuuMrjQIacDqp1ZzM/omW97ZwjO7ninxqKr7VbgVZs7tn3qUxCcS5RfKaZRkJ39Ua4CTRVyvAdACZSRXriyUBEsIIXKdR+k/swplUER+O4GGtx8XnhOssip1cpOamoq1tfHdfysrK1JSUsokKCFMpc6DdXg+/Hk2vbWJDm90qLDE5k5UgPftrVsxZWYB/5GX/ESidGyOwPg/+YNAAnm3t5qgdHpugXL7SwhRvWxBme4ilwroiHK7aQjKiE9zU+rkplmzZqxYsYLp06cXOP7rr7/SpEmTMgtMCFOxcbKh/5f9CxzbOn0rTt5OtH6+daVIeAobenvLpUNpWj5NwdtTOpQm5nSUBGdbvudcgMHA0vIMVAhhUhHA74AHyi0mgA4o//9boiQ0g1H+mDJnpU5upk2bxpAhQzh37hzdu3cHYPPmzSxfvpzff/+9zAMUwtTiDsWx44MdoIez688y4NsBOHg4mDqsO1Kj/LVV+C8uNca3uI4Cu1HW00rLV1aPMhFhMMrioW2QEVtCmBs9St+Y31FuOZ26fTyIvOTGDuWPIccKj678lDq5CQ0NZe3atcyePZvff/8dOzs7goOD2bJlCzVq1CiPGIUwKa9WXoR8EsKmtzZx5q8zLG62mIFLBxLYzzxHCzqjdFRum++YFgin4G2pM8CK2xsokxd2QEl0ugDtkb47QlRmHwPfoQwwyGUF9EJpock/bLsqJTZwj8PR+/fvz+7du0lLSyM6Opphw4YxadIkgoODyzo+IUxOpVbx4GsP8uzBZ/F4wIO0q2ks77+cdePXoUnXmDq8MmEBtEbpd5OrBspw9CEoa22lA5uB6SjJzbR8ZTUofXyEEKaRA5xxdS2wrt1plMTGBmVyvR+Bq8A64Bkqx3w05eWe39uOHTsYNWoU3t7eLFiwgO7du7Nv376yjE2ISsWzuSfPHnyW9q+1B+DQl4f4vvv3d1yA05y5A6+gNGVfQWna/gJ4DOV+fed8ZbcCrsDDKAuMhlHwFpcQonTSgVjgMMryBrm2A88Cg1AW8m2E8oeIvZUVk7t04Ui+PoHjUZaASQTWoqyJ51rukVcOpbotlZCQwLJly/juu+9ISUlh2LBhZGVlsXbtWulMLKoFS1tL+nzah8C+gawdvZa249tWyg7GZU2NMmHXAyi/MPUoTdq5DqBMv77r9vYhyi+XNiitPC8AfhUXrhCVig6lT1vi7e0aygjFWrefX4fyh0Puc4koyU2uf1FuJYHSEvNtMa9jp9FwVqXiwdv7bW5v1VGJk5vQ0FB27NhB//79+eyzz+jTpw8WFhZ89dVX5RmfEJVS/d71mXB6AtZOeV1sL+27hJOPEy6+LiaMrGKoKNg/ZyrwOHnraW1H+atz3+0t/yrq+1F+eT9E9fkrUlQ9epROuFEoLZvXUEYZ+dx+/hdgNnkJi7bQ+RvJmy/mCnmz/uZnhdKCmv/md3vgPZTEyD3f5qLRsH/9ekL79buv91VVlDi5+eeff3jllVd48cUXZdkFIQAb57zutOnX0lkxZAU5GTn0/6o/Dwx/wISRVTwVyoSBDVBmSgZlUrDtKMlM/nbdz1EmFVSh9PHJ7aD8IEJUbltRWk1y55IqfOs1kLzkJgNl7qn8nMlLSvKPPOwMLLl9PH/S4oTxzL/Nbm+FaZB5qvIrcXKza9cuvvvuO1q3bk1QUBAjRozg8ccfL8/YhDAb2WnZuPi6cPnAZVY9voqz687Sd2FfbF3Kfn0qc+F3extVxPFAlOb1o7e3zwCsrAjo0oX8f3f+CNxCmQI+/1bUL30h7sc18qZHyL99S94iuBcpONu3JRAAeKEkJW75ngtB6XuWm7DUovjRhbl/GIiyU+Lk5sEHH+TBBx/ks88+Y8WKFSxZsoSJEyei0+kICwvD19cXJyen8oxViErLtZ4rz+x6hh3v72Dnhzs5/uNxLuy4wJCfhlD3IXOc37P8fHh7iwN2kHcbKwLItij4t+cC4FgR17BDmWE5/6rqy4BUjBMhFyQRul/xKJM73iLvizp3c0fpYG4OQ4m1KC2KrkDN28f+Qhk5dL2Yc06Sl9x0RFkWJQjl8xdA8YvX+pDXiiMqXqnnuXFwcGDMmDGMGTOGyMhIvvvuOz766CPefvttevXqxZ9//lkecQpR6VlYWdDtvW406NOA1U+vJikmiWVdltHp7U50f787KrV8xebnjdJPJ7f997JGw+8HD8LDDxvK9EFZDf1Kvi0Npck/s9D1PkEZ0VWYNcqXUXi+Y0soukXIjao9PLYoeuAyyrxGkfm2gSgdwUEZrTP1Dtd4AVh8+3EySt+T/C0W+bcGKP+m5SkTJSkp3ApzBqXj+9fAc7fL1iAvsamHkrTk35rnu24D4O1yjl2UjVInN/k1atSIuXPnMmfOHP766y+WLFlSVnEJYbZ8O/ryQvgL/PPyPxz74RjJ55MlsSkBD8Dv1q0Cxz4qolwaSpJTeF6dR1AW98ufCKWgfJkVno3oU4z7Q4DyCzEIOJ7v2A+3Xyt3fS+v27He1y9PE0hFeR/ut/cvA6EoX/hFDdv3IC+5CQBGorR4XEe5hZN/c8933hWUvinFeRH48vbjmyhT/ue2ABVOhFqgdKAFJQnTklfvepTWvyiUxKU1ef229lH8Omy2QFK+/ZYot0YDgco977gojTL5/2lhYcGgQYMYNGhQWVxOCLNn42zDoO8H0WhQI/y75f2dqsnQYGlrbl+LlYsDypdtYbOLOJaBMmlZ4URoIEoSkz8RSkKZCK3wqJZ5GCdCapSWnqYo/SpyrUP50s1NhNyp2E6eOpTbLoVbYSJRkpkxKDPWgpI8hN+O1wKoj5IcNrq95R9CbAV8f5fXzeWB0i8lf/KTmO9x/n+7RODC7a0oL5GX3Nwgr19LDUtL4vr1I8Mq76bQW+QlN41vx1G4FaYxSutM/tY5ewpOXimqBvktK0Q5ChocZHis1+tZ9fgqUEHfxX1NGFX1YYfyZVbYB0Ucy0JJhNILHe+L8oUcj9JSkICSAMWT128j11sot0NyWQC1UVp7mlAwQdiP0sHUCyUJKs3tsJsoCcsZlBE4g24fz0RJUoqTkO+xDcrw43rcue9ISeSP3RVlTbKS8EVpZSncEpSbDLXKV/ba7Z83gZsqFVhZYaHXU1+lojEFR+TVRklYRfUlyY0QFeTqf1eJ2hCFNlvLpf2X8BjjATIlRaVhg/JlW9jcQvtalC/fOIxvdwXfvk4cSqKkRWkxuYxyeyy/MeQtYmiJ8oWc2+LTGKXjKigtKwvUaqLIa4VJzHedLuQlN/YorS/WFGyFaXR7v/Dqf70xLTvyWmbuJhClTq8BCTk5nNyxg9EPP4yj1f2kZaKqkuRGiAri2cyTcfvHserJVVyLuEbM7BhWhq+k7+d9qVFfFp01F7mtMbWLeO7nfI9zUL6M425vhVtmPFD6r1y9XfbS7Q2UJCk3uVEBn6vVxBc63wclaSk8P9BpquboMDV587800OtJuXVLFm4VxZLkRogKVLtFbZ47/Bxbp29l32f7iFofxZebv6TT5E48/M7D0h+nCrEkryWmKLmdbjUot1Byk6B4lBaY/J7T6cDCokArTHFDr6tiYiNEaclvUiEqmJWdFd1md+Om300y12RyfvN5/vv1Px6e+vDdTxZVjhVQ5/ZWnKk6HVYWMv+sECUlyY0QJmJbx5bB6wcT9WcUdjXtsLRR/jtqNVpSLqbgFuB2lysIIYQoSnWbr0qISkWlUtHk0SYFhosf+OIAi4IWsWXaFjTphbusCiGEuBtJboSoZC7tvYQ2W8vOD3ayqMkiTq89jV6vN3VYQghhNiS5EaKSeXTFowxbNQyXui4kX0hmxeAVLO+3nOtni1v9RgghRH6S3AhRyahUKoKGBPHSqZd46J2HsLC2IGpDFIsfWEz4snBThyeEEJWeJDdCVFLWDtb0+LAHL/73IvVD6qPT6vBuU9zAYiGEELlktJQQlVzNwJo89c9TJJ5MxOMBD8Pxw98cxq+LHzUbFl4EQAghqjdJboQwAyqVqkBik3AsgXUvrENtqabDGx14eOrDWDtYmzBCIYSoPCS5EcIM2TjbUD+kPlH/RLFrzi6O/3SckE9DCBoShEolc9QKIcpHTg5cuwZXr0JiovKzqM3ZGTZuNF2cktwIYYbc/N14ct2TRP4ZycbXNpJ0PonfHv2NgF4B9F3Yl1qNapk6RCGEGdDrISnp7slK7nbjhnLO3dQ08d1ySW6EMFMqlYrGAxtTv3d9dn20i90f7yY6LJqlDy/l9djXZZ0qIaqp9PS8ZORuCUtiImhKOVeoWg21aoG7O3h4FL+Zkvz2E8LMWdlZ0W1WN4JHBrPhlQ3U71O/QGKj1+vlVpUQZk6rVRKR+Piit7g4C86f70lqqiVpaaW/vrPznROV/FuNGlDZlzqT5EaIKqJG/Ro88fcTBY6dXX+WfZ/uU25VNZZbVUJUNllZkJBQfNISH688f+UK6HR3upIacDDs2diUPFlxd1fKVyWS3AhRheRvodHr9Wx6axNX/7vK4uaLefD1B+kyrQvWjjKqSojypNdDauqdE5bc7ebNkl9XrVaSES8vqF1b+Zm7ubvnEBOzh4EDO+DtbYWTE1TnBltJboSoolQqFcPXDmfjaxs58/cZ9szdw4mfTxDySQhNHmsit6qEuAcaDcTFQWyssl26pOwXTlrS00t+TWvrgolK4cQlL4EBy2K+tTUaPevX36R+fbCyKpv3as4kuRGiCqtRvwZP/PUEkX9FsuHVDSTFJPH78N/x/z9/+n3RT25VCZGPXq+MBoqNhYsX8xKY3O3iRSWRufPtoTxOTsYJSlGJi5tb9W5lKQ+VIrlZtGgR8+bNIyEhgeDgYBYuXEi7du2KLf/ZZ5+xePFiYmNjqVWrFo8++ihz5szB1ta2AqMWwnw0Cm1EQM8Ads/dze6PdhOzOYbrZ65LciOqlcxMpaWlqKQl93FJWlysrcHXF+rWVX56exedtDg43P1aonyYPLlZsWIFEydO5KuvvqJ9+/Z89tlnhISEEBkZiUcRY8mWL1/O22+/zZIlS+jYsSNnzpxh9OjRqFQqPvnkExO8AyHMg5WdFV1ndCV4ZDAnlp+gYWhDw3NRG6Pwbu2NfS17E0YoxL3T6ZShzcUlLbGxyvMl4emZl7jUrVtw8/VV+r2oZWXGSs3kyc0nn3zCs88+yzPPPAPAV199xbp161iyZAlvv/22Ufk9e/bQqVMnnnzySQD8/Px44okn2L9/f4XGLYS5cvN3o/PUzob9zORMVg5ZiU6r44HhD9B2fFt82vmYMEIhjGm1SqvLuXNw9qyKzZsb8/vvFoaWmEuXIDv77textzdOWPInMnXqgNwEMH8mTW6ys7M5fPgwU6ZMMRxTq9X07NmTvXv3FnlOx44d+emnnzhw4ADt2rUjOjqa9evXM2LEiCLLZ2VlkZWVZdhPSUkBQKPRoCntzEV3kXu9sr6uOZM6KVplqpcb529Qs1FNEo4mcOyHYxz74Rherb1o9UIrmgxrgpVdxfROrEx1UllUtzpJT4foaIiJUREdrSI6GqKjVZw7p+LCBdBocjumWAKNjM5Xq/V4e4Ovrx5f38I/9dStW7L+LeZY3dXhs1Ka96bS60sykXL5iIuLw8fHhz179tChQwfD8cmTJ7N9+/ZiW2M+//xzJk2ahF6vJycnhxdeeIHFixcXWXbmzJnMmjXL6Pjy5cuxt5cmeCFAGTaefjada+uvkbQrCX2O8mvBwsmCehPr4dzS2cQRiqpAr4eUFGsSEhxub/b5Hjtw8+adm0wsLXV4eKRTu3YaHh7puLtnUKuW8tPdPQM3t0wsLU32lSbKWXp6Ok8++STJyck4O9/5d5LJb0uV1rZt25g9ezZffvkl7du3JyoqildffZX333+fadOmGZWfMmUKEydONOynpKTg6+tL796971o5paXRaAgLC6NXr15YyVg8QOqkOJW2Xl6DtMQ0ji87zpH/O0LKpRT6j+6Pk48ToDxnV8MOtUXZdziotHViQuZYJzk5Sl8XpeVFxblzBVtibt26c7OJq6uegAA9/v4QEKCnfn09AQHKYx8fsLCwQaNRExa2z6zqpbyZ42eltHLvvJSESZObWrVqYWFhwZUrVwocv3LlCrVr1y7ynGnTpjFixAjGjRsHQLNmzUhLS+O5555j6tSpqAv18rKxscGmiKkXraysyu0DUJ7XNldSJ0WrjPXi6u1K53c689BbDxF/JJ4afjUMz/095m+un7lOmxfb0HJMS+xrln3rZ2WsE1OrbHWSlqbcPjp3ruAWHQ3nzysJzp3UqQP160NAgPIz/1ajhgoo2bjoylYvlUFVrpPSvC+TJjfW1ta0bt2azZs3M2jQIAB0Oh2bN29mwoQJRZ6Tnp5ulMBY3F7kwoR32ISoctQWanza5nUszkzKJO5gHBk3Mtg0eRNbp23lgcdvd0BuKx2Qqwq9Hq5dU1pfLl5UOurmPj5/XkliCv09asTGBvz98xKW/EmMv7902BXlz+S3pSZOnMioUaNo06YN7dq147PPPiMtLc0wemrkyJH4+PgwZ84cAEJDQ/nkk09o2bKl4bbUtGnTCA0NNSQ5QoiyZ+tqy+sXX+fELyc4uOig0gH5+2Mc+/4Y3m296TqzK4H9Ak0dprgDvV6Z7r+oxCV3/9IlZT6Yu3FzM251yU1kfHxkqLQwLZMnN8OHDycxMZHp06eTkJBAixYt2LBhA56engDExsYWaKl59913UalUvPvuu1y+fBl3d3dCQ0P58MMPTfUWhKg2rOytaDW2FS3HtOTy/sscXHSQkytPEncwjlvxt0wdXrWXnFx84pJ7rKTLAnh6cnukUd5Wt25eAuPmVr7vRYj7YfLkBmDChAnF3obatm1bgX1LS0tmzJjBjBkzKiAyIURRVCoVdR6sQ50H69B7QW/Cl4XT7IlmhucPfnmQs+vO0nZ8Wxr0aYBKLXPL36/UVONEpfD+rRLml7VqFUxa6tQpuO/jo8zCK4S5qhTJjRDCfDl4ONBpcifDvl6v5+CigySeSuTs+rO4BbgZOiDb1bAzYaSVm04Hly/D2bMQFaX8jIy04PjxrowebUlSUsmu4+ZWfNKSm7jYyT+DqOIkuRFClCmVSsXwNcM5uPgg4UvDuRl9k7A3w5QOyE8oHZC9W3ubOkyT0OmUFpbc5CX/z3PniurrogZcDHvOzsUnLbnHZD0jISS5EUKUg5oNa9Ln0z50/6A7//3yn9IBOTyB8KXhZCZlMnz1cFOHWG5yE5jCycvZs0oCk2/CdCOWlspoogYNIDAQ/P213LhxgCFD2hAQYEUZT80lRJUlyY0QotxYO1jTalwrWo5tyaV9lzi46CAtx7Y0PH/j3A0O/99h2rzQBsc6jiaMtHTKIoEJDMxLYnJ/1qunPJ9Lo9Gxfv1VmjaFKjp1iRDlQpIbIUS5U6lU+HbwxbeDb4HjhxYfYu+CveyZt4cGfRuga6ND37dyzFeVP4Ep6hbS3RKYgADj5KVBA+MERghR9uS/mBDCZAJ6BnDl+BWiw6KJWh8F6+Gb376hw8QONH+6OZa25f8rKikJIiPh9OmCP0uawBTVAlO3riQwQpiS/PcTQphMgz4NaNCnAdcir3Fg0QEOf3uYaxHX+OvZv9j98W7Gnx5fJutYabXK7LpFJTF3mm1XEhghzJP81xRCmFytRrXotaAXmQ9m4nHZg0NfHKLhgIaGxEav13Mj6gY1A2ve8TrJyUrCUjiJiYq6cyuMtzc0agSNGys/GzWChg0lgRHCXMl/WyFEpWHhYEH719rT8fWOaDI0huMXtl/g+27f06BvA9q92gGLQH8iI1VGSUxCQvHXtrFREpb8SUzjxsoxGYUkRNUiyY0QotJRW6rJxoYTh5Sk5czSS6iBqH+iiPoniit4sJcOnOABtIV+jXl55bW+5E9i6tYFWX5OiOpBkhshhMloNBATo4xCOn1azaZNzfnsMwvOnIG4uPwlH8KNJjzIflpyFE+uMog/6G+7GXX7ttQf0ZEmzS1p2BBcXIp7NSFEdSHJjRCiXOXkwIULeUOq82/nzyudfRUWgH+Bcz0987e+1KBRo774e3Xl2obDHPziALfiblEj7hgjn3kYlaxCLYS4TZIbIcR902qVxRuLSmBiYpQWmuLY2yujj+rX16FSRdGvXwBNm1rSqBG4uhZ1hh20fIiOb3Tg5G8nsbKzMizMmZOZw5/j/qTVuFbU61IPlUoW7BSiOpLkRghRIvkXdiy8nTsH2dnFn2trmzeEuvDm5QUqFWg0Wtavj6BfP/8SzcZrYW1B86eaFzh2/KfjnPj5BCd+PoFXKy8enPggTYc1xcJKOtsIUZ1IciOEMNDrIT6+6AQmKqqohR3zWFtD/fpFJzA+PqCugNtG9brUo82LbQhfFk78kXjWPL2GTW9tot3L7Wj9XGvs3GQ5bCGqA0luhKiG9HqIjYUDB+Do0YIJTFpa8efln9Su8Obra/rRSDUDa9L/y/50e68bh74+xMEvDnLr8i02v72ZnR/s5JXoV3Bwl2WzhajqJLkRohpISoJDh2D/fmU7cKD4mXktLMDPr+gExlzWRbKvZU/nqZ3pOKkj//36H/s+2Yejl2OBxOb62evUaFBD+uUIUQWZwa8pIURpZGfD8eNKApObyJw+bVzO0hKCg6FNG2VEUm4C4+en3GKqCixtLGkxqgXBI4PJSs6bojjlcgpfNvnS0C+nydAmqC1luFVlk6PL4UbGDa6lX+N6+nWupV/jWvo1rqZeJepqFHFH46hhXwNnG2dcbF2UnzYuuNi64GjtiLqKDKHT6rSkZKWQnJVMcmYySZlJhse5P2+k3+DMpTMc2H4AVztXnG2ccbJxUn5aOxnt21raVunEXpIbIcyYXg/R0XlJzP79ym2mopYaCAiAdu2gfXvlZ8uWYFdNuqCoVCpsXW0N+5f3X0ZloeLygcusenwVm+puov2r7Wk5tiW2LrZ3uFLZ0Ol13Mi4wZXUKySkJnAl7QpXUq9wJa3QfuoVrqVdw/WMK652rrja5ttsCu3buuJm52Z0zNay/N9PSej0Om5m3DQkKLnb9YzrRsdyt5uZN+94zWVxy4p9ToXK8GWem/DkPi72mK3xc/dbfzq9jtTs1GKTksLHiipzK/tWiV/v72t/l6icpdqy2MQn/8+7JUnONs7YWNrca/WUG0luhDAj168rSUz+Vpnr143LubnlJTLt20PbtuDuXvHxVlZBQ4J4PfZ1Di4+yMFFB0mOTebfN/5l28xttBrXioffeRj7WvalumZxCYvhcb79xPREcnQ5Jb721fSrXE2/Wtq3CYCNhY1RwuNq64qbrXEiVNRW1BeXXq8nOSu52KTkevp1rmUUPHYj4wY6ve6e3kMNuxrUsq9FTbua1LKvhZutG7EXY3Fyd+JW9i2SM5MLtGxodBr06EnJSiElK4VLXLqn1wWwtrC+Y4LkYO1AanZqsYlLSlYKevT3/Pr52Vra4mLjgqutKy62LoaYXG1ccbJ2IjYmFg9fD9Jy0kjJSuFW1i3lZ/Ytw35uopTbKnYj48Z9x2WltjJKhLwcvVj52Mr7vva9kuRGiEoqMxPCwwu2ypw7Z1zO2hpatMhLZNq1U4ZdV+EW5zLh4OFA1xldeeithzj+83H2fbKPxFOJHP76MJ3f7QzkJSwJqQmGlpWySlhA+dL2dPCktmNtPB098XTwLLBf06Ym4fvCadupLak5yhdoaTY9erK0WYZY74WdpZ0h0VGpVFxPv871jOulfq+5XGxcqGVfq8CWm7QUtbnZuWGpLvhVpdFoWL9+Pf369cOq0LwBer3yngsnPEU9LvZYvtaSbG22IUG7H1ZqK0NCUlRyUmDf1tXwOH95a4vi7xcb6iTEuE7yy21JKirxKWo/Jbv459I0yugDjU7D9Qzlc5HLx8nnvurrfklyI0QloNMpo5Xyd/g9dqzoye8aNix4eyk4WFkU0tzp9XqyddmkZKWARvlSuZdNo9OU/jzrbLLfzCblegqZmZn8uuJXpW9H2lW0eu3dg8/nbglL7mN3B/c7flmB8oWVYJNAM49md/zCKkrul9jNjJt3ToKyij6enJmMHj0ZORlkpGYQnxpv9BqO1o7GCYldvqTFvmDSUsOuxl3f8/1SqVTYWtpi62iLp6PnPV9Hq9Mqt5OKSX5yH6dlp+Fo7XjX5KSy9HFRq9SGVhYf7i8Bya0jo4QoK8Xk71WSGyFM4OpVOHDAk3371Bw+DAcPKiOaCqtVq2CLTNu2UKNGhYd73/R6PTczb3Ix+SIXUy5yKeUSF5MvcunW7Z8pl7iUcomMnAw4bupogUJ3gOzS7XBMc8TDzgO/en7Ur1+f2o617ylhqSj5v8TqUa/U5+v0OlKyUgokPFqdtkDiUln685QHC7WFkpzYuoCsV1akAnVUyUhyI0QFuHEDtm+HLVuU7dQpK+DBAmVsbaFVq4LJjJ9f5b+9lJu4GBKWlEt5CUy+RCYjJ6NU17VQWWBtYV2izcrCyvi4uhRlC5dRW1HDrgY1LWqS+E8iJ745wcU9Fw2xufq70urZVrQc0xJHT8eyrtJKQa1SG25HCWFuJLkRohzcugU7d+YlM+Hhysim/OrUuUX37g506KCmXTto1owSLTtQkfR6PUmZSUaJSv4Wl4spF0nXpJfoeu727vi6+FLHuQ6+znk/fV188bTz5MiuI4T2DcXe1r7SDOP1G+1H29FtuXLiCke+OcKxH46RFJPElne24NHUg0YDGpk6RCFEIZLcCFEGMjJg7968ZObAgfyrXSuCgqBbN+jeHTp21HDgwJbbHSJN8yWerc3mZsZNEtMT79jikttp8G5q2dfKS1ZyE5d8iYyPs88db2NoNBpOW5zGxtKm0iQ2+Xk286Tv533p+VFPTv52ktNrThPYL9Dw/IFFB8hKyaLlMy1xrF01W3OEMBeS3AhxDzQapZ9MbjKzZ4/x3DL+/koi0727ktR4eRU8v6zk6HK4mXGT6xnXuZFxg+vpt3/e3s//OP9zqdmpJX6NmnY185IVp4JJi6+LLz5OPthZVY9Jc6zsrWgxqgUtRrUwHNPl6Ng1exe34m6xbfo2Gg9qTKvnWhHQI8CwYrkQouJIciNECWi1yq2l3GRm507jNZi8vKBHDyWR6dZNSW5K9Ro6LUmZSaVOUlKyUu75falQ4WbnRh3nOsW2utRxroO9VenmfKlu9Ho93T/szuGvD3Np3yVO/X6KU7+fwi3AjVbPtqLFMy2qbN8cISojSW6EKIJeD6dO5SUz27YZj2aqWTPvNlP37soQ7cKdfzNzMom/FU/crTjibsVx+dZl4m7FcSn5EpGxkXyw9ANuZiqtLkmZhV6glFxsXKhpX1PpCGun/Mz/OPe5/MdcbV2xUJt4tcsqwMLKghajW9BidAuuHL/C4f87zPEfj3Mz+iabp2wm6XwSj3z1iKnDFKLakORGCJRk5tw52Lo1L6G5Wmg4sLMzdO6sJDKdu+bgGXCV+FQlWdmSEsdPW/OSl9wt/6RWRSpiVnVnG+dSJSg17WviautqNNGZMA3P5p70+6IfPT/uyckVJzn89WFaP9fa8Hz80Xiiw6JpMboFDh6yQrkQ5UF+G4pq69KlvERmyxa4eBFAD/bXwSkO6yZxNGh5Ge/GcTh7x6GxjSMu9TLzbsUx6a8rJZ5K3tbSFm8nb7ydvPFx8sHbyRsPew/io+Lp2r4rHo4ehqTFzdYNK4tKNmRK3BNrB2tajmlJyzEtCxw/8PkBwpeFs+XdLQQNDqL1863x6+onfXOEKEOS3Ihq42JCBqvCYtl88DIHT8dxJT0OnOLA6TL0igPnOFTOcejV2QBkA6eAU1rgovH1LFQW1HasjY+zkrB4O95OYHL3byczudPW56fRaFh/Yz39Au88Vbqoevx7+JN4KpHLBy5zcuVJTq48SY0GNWj1XCulNcddWnOEuF+S3IgqKTU7lWMJx9hw/DD/HDtMRNIR0u0jQK2FmkCnos/LnYrG3d7dqLXFsH87eXG3d5f+KqLUmj/dnOZPNychPEHpm/PTcW5E3WDT5E0c+eYIEyInmHzqeiHMnSQ3wuylZKUQnhDO4bjDHI4/wu7ow5xPPQ2qfLPm3R6ootY446r2wdfVm8Z1vPGrYZy8eDl5VZop9EXVVbtFbfp/2Z9ec3vx36//cfj/DtNoQCNDYqPVaDn4xUFyat3bApVCVGeS3AizkpSZxNH4oxyOP8yR+CMcjj/MmetnjAuqgFteqOJb42fTmp5NWzG2b2vaBXnLX8WiUrF2tKbVuFa0GtcKXU5eP67IPyMJmxiGylJFxi8ZNH20KY0GNMK+lgzLF+JuJLkRldaNjBtKAhN3mCMJys9zN88VXTjZF+JbQVxrbJNa0bNpKx7v70W/qeDmVrFxC3Gv1JZ5MzNb2VtRu1VtEo4kcO6fc5z75xwqCxV+XfxoPKQxzZ5shp1b9Zg4UYjSkuRGVAqJaYmGlpjcn+eTzhdZ1jbTj6yYVujjWisJTXwrvJw9GDAABo5Uhmrb2FRs/EKUtcC+gfj19GP116vxuO7BmT/OkHA0gZgtMcRsiaFBnwaG5CYnKwdLG/l1LkQu+d8gKlxCaoKhRSY3mbmYUsRwJMDXoT7Oaa24eao1cYeURCYzoyYATZrAwMdg4EBo2xbUlW85IiHum62vLQ89/xDdZnTjZvRNItZEcPXEVWrUr2Eos+rxVSSdTyJoaBBBQ4KoFVRLbr+Kak2SG1GuUrNTOZB8gEM7DnHs6jEOxx8m7lZckWUb1mxIS89WuGa0JvF4aw7+1ZKLZ1wNz6tU0KmTkswMHAiBgUVeRogqyy3AjY5vdCxwLCcrh+hN0WSnZpMQnsDWaVup2aimIdHxauUliY6odiS5EeXiatpVFu5fyKKDi7iZeRNi8p5ToaJxrca09m5Nq9qtCHJrTeLxFoT97cy6dXDjRl5ZW1vo3VtJZh55BDw8Kv69CFGZWdpY8mrMq0T+GUnE6giiw6K5HnmdXbN3sWv2LoKGBDFs1TBThylEhZLkRpSpczfOsWDvApaGLyUzJxMAD2sPejfqTVuftrT2ak1w7WBSbzjy11/wx3cwZVPBFbVr1oTQUCWh6dULHGROMyHuyL6WvWE25KyULM6sO8Pp1ac5u/4sdTrWMZTLuJGhzIw8JIh6XephYSXzNImqSZIbUSYOxx1m7p65/H7qd8OyBG292/LGg29gdc6K0P6hREdbsfYXePMP2LdPWc8pV0AADBqkJDQdO4KlfDKFuCc2zjY0e6IZzZ5ohiZdg06bb3j5X5EcWnyIQ4sPYVfDjkYDGtF4SGPq96qPpa38pxNVh3yaxT3T6/Vsit7Ex7s/ZnPMZsPxPg368Fant+hSrwv//ZfDjB/OM+UtS84Umo6mTZu8hKZpU+MVtYUQ98fKvuDSHh5NPWj1bCtOrz1NemI64cvCCV8WjrWjNYH9A+n+YfcCHZWFMFeS3IhSy9Hl8Pup35m7ey5HE44CyjpLjz/wOJM7Taa5Z3OOH4fHH4fffrNEr1d6/lpZQbduSjIzYADUqXOnVxFClDXvNt54t/Gm/+L+xO6KJWJ1BKdXnyblUgonV56kz2d9DGWvRV7DwcNB5tIRZkmSG1Fi6Zp0lh5dyoK9C4hJUnoI21vZM67lOCZ2mEg913ocOgSDnoc//sg9S0WbNgm8+motQkMtcXExWfhCiNvUFmr8uvjh18WPPp/1Ie5gHHGH4nCs7Wgos+7FdcTujMWvmx9BQ4NoPLBxgeeFqMwkuRF3dT39OosOLmLhgYVcS78GQC37Wrzc7mXGtx1PTfua7N4NL3wAGzYo56hU8NhjMHmyhkuX9tOvXz9k8WshKh+VSoVPOx982vkYjmk1WjJvZqLL0REdFk10WDTrXlxH3Yfq0nRYU4KGBuHk5WTCqIW4M0luRLEuJF3gk72f8O3Rb0nXpAPg7+rPGx3e4JmWz2Bnac/WrfDBB7B1q3KOhQU8+SS88w40bgwaDVy6ZMI3IYQoNQsrC54/+jzXz1wnYk0EEasiiDsYR+zOWGJ3xnLmrzM8vfFpU4cpRLEqxZyuixYtws/PD1tbW9q3b8+BAwfuWD4pKYnx48fj5eWFjY0NDRs2ZP369RUUbdV3LOEYT69+mvqf1+fzA5+TrkmnZe2W/DL0F868fIaX2o5nx2Z7HnoIevRQEhsrKxg3DiIj4YcflMRGCGHeajasyUNvPcSzB57ltQuv0fuT3tTpUIemw5sayqRcTuH77t9z6KtDpF1NM2G0QuQxecvNihUrmDhxIl999RXt27fns88+IyQkhMjISDyKmLEtOzubXr164eHhwe+//46Pjw8XLlzA1dW14oOvQvR6PdvOb2PunrlsiNpgON4zoCeTO06mZ0BP9HoVf/2ltNQcOqQ8b2OjJDWTJ0PduiYKXghR7lzqutDh9Q50eL0D+nzzOJz6/RTnt57n/NbzrB+/Hr9ufjQd1pTGgxvj4C6TVAnTMHly88knn/Dss8/yzDPPAPDVV1+xbt06lixZwttvv21UfsmSJdy4cYM9e/ZgdbsTh5+fX7HXz8rKIivfDHEpKSkAaDQaNBpNGb4TDNcr6+uWJ61Oy9rItSzYt4BD8UrGolapGdp4KG88+AatvFqh1cIvv2iZM8eC//5Txmvb2+t57jkdr7+uw8tLuVZRb9sc66QiSL0YkzoxZg51EhgaiCZDQ8TvEcQfjidmcwwxm2NY99I6/Lr5EfJ5CDUalO3wcnOol4pWHeqkNO9Npc+fglew7Oxs7O3t+f333xk0aJDh+KhRo0hKSuKPvCE3Bv369aNGjRrY29vzxx9/4O7uzpNPPslbb72FhYXxbJszZ85k1qxZRseXL1+Ovb19mb4fc5Kty2brja2svbqW+Ox4AKxV1vSo2YMB7gPwsvFCq1WxY4cPq1Y15NIlpfOgnZ2Gfv1iGDDgHC4u2aZ8C0KISiYrIYukPUkk7UoiIzoDlaWKB75/AAsH5XdzxoUMrGpYYelk8r+rhRlKT0/nySefJDk5GWdn5zuWNekn7Nq1a2i1Wjw9PQsc9/T05PTp00WeEx0dzZYtW3jqqadYv349UVFRvPTSS2g0GmbMmGFUfsqUKUycONGwn5KSgq+vL717975r5ZSWRqMhLCyMXr16GVqVKpukzCS+PvI1Xxz8gitpVwBws3XjxdYv8lKbl/Bw8CA7G376ScXcuRZERystNa6uel5+WceECeDm5g/4l+j1zKFOTEHqxZjUiTGzrJMxyo8bUTdIOJpAk8eaGJ5a2mEpV45dwb+nP0GPBhEYGnhP8+iYZb2Us+pQJ7l3XkrC7NJnnU6Hh4cH//d//4eFhQWtW7fm8uXLzJs3r8jkxsbGBhsbG6PjVlZW5fYBKM9r36tLKZf4bN9nfH34a1KzUwHwdfbljQ5vMLbVWBytHcnMhP/7P/j4Y7h4UTmvVi144w146SUVzs4WwL2tRVMZ66QykHoxJnVizBzrxDPIE8+gvD9cs9Oy0eXo0OXoOLfhHOc2nENtpaZ+7/o0HdaURgMaYetqW6rXMMd6KW9VuU5K875MmtzUqlULCwsLrly5UuD4lStXqF27dpHneHl5YWVlVeAWVFBQEAkJCWRnZ2NtbV2uMZubU4mnmLdnHj8f/xmNTrlf2cyjGZM7TWZ40+FYWViRlgaffAHz5kFCgnKelxe8+SY895wsXCmEuH/WDta8EP4C105f4+RvJzm18hRX/7vK2XVnObvuLE2HNeXRFY+aOkxRRZg0ubG2tqZ169Zs3rzZ0OdGp9OxefNmJkyYUOQ5nTp1Yvny5eh0OtRqZST7mTNn8PLyksQmn92xu/l498f8deYvw7Gufl2Z3HEyfRr0QaVSkZIC8xfBJ5/ANWVuPnx94e23YcwYsC3dH1FCCHFXtRrXosu0LnSZ1oXEU4mc/O0kJ1ecJOjRIEOZa5HX2PTWJpoOa0rD0IbYOBm3vgtxJya/LTVx4kRGjRpFmzZtaNeuHZ999hlpaWmG0VMjR47Ex8eHOXPmAPDiiy/yxRdf8Oqrr/Lyyy9z9uxZZs+ezSuvvGLKt1Ep6PQ6/jj9B/P2zGPvpb0AqFAxJGgIb3Z8k/Z12gNw4wZ8/jn873+QlKScW78+TJkCI0aA5IhCiIrg3sSdrjO60nVGV/S6vLEtJ1eeJPKPSCL/iMTCxoLAfoFKovNIQ6wd5ReUuDuTJzfDhw8nMTGR6dOnk5CQQIsWLdiwYYOhk3FsbKyhhQbA19eXjRs38vrrr9O8eXN8fHx49dVXeeutt0z1FkwuMyeTH479wIK9CzhzXVl629rCmlHBo5jUcRINazYE4OpV+PRTWLQIbt1Szm3cGKZOVRa5tDT5p0EIUV2p1CrD46aPNUWn0XFyxUmun7nO6TWnOb3mNJa2lgT2D6Tngp4mjFSYg0rxdTZhwoRib0Nt27bN6FiHDh3Yt29fOUdV+d3IuMHig4tZeGChYeSTq60rL7V5iZfbv0xtR6XfUny80p/mq68gI0M5t3lzePddGDJEWTJBCCEqi1qNa9HtvW50ndWVqyeucnKlcuvqRtQNzv17jtAaoYay8UficfV3ldXLRQGVIrkRpXMh6QKf7vuUb498S5pGme68rktdXn/wdca2HIuTjTInTWysMvLpu+8gdx7DNm1g2jQIDVUWtxRCiMpKpVLh2dwTz+aedHu/GwnhCVw/cx1LW+WrS6/X8/vw30k6n6SsXj4kiMaDZPVyIcmNWQlPCGfennms+G8FWr0WgGDPYN7s+CbDmg7DykIZJpecDJMmwbJlkJOjnNupk5LU9O4tSY0QwvyoVCq8Wnrh1dLLMFNt5s1MLO0sC65e/tI6fDv6EjQkiKAhQbj6uZo2cGESktxUcnq9nk3Rm5i3Zx5h0WGG4z0DevJmxzfpFdALVb5sRaOBoUNh82Zlv0cP5fZTly6S1Aghqha7Gna8ePxFrp9V+uVErI7g8v7LXNx9kYu7L5IYkciAbwYAGNbDUskvwmpBkptKSqPV8Nup35i3Zx7hCeEAWKgsGNZ0GG92fJOWXi2NztHr4cUXlcTGwQH++gu6davgwIUQooLVDKxJp8md6DS5EymXUji9Vkl0mj6Wt3r55f2XWTt6raFFx6u1lyQ6VZgkN5VManYq3x35jk/2fUJsciwA9lb2jGs5jtc7vI6fq1+x5+b2r1GrYcUKSWyEENWPcx1n2k1oR7sJ7Qocj1gTwfXI6+yas4tdc3bh7OtsSHR8O/mitlAXc0VhjiS5qSSupF5h4YGFfHnwS25m3gTAw8GDl9u9zIttXqSmfc07nv/bb8o8NaDMX9O/f3lHLIQQ5qPz1M54tfQiYnUEZ9efJeViCvv/t5/9/9uPvbs9Y/eMLfPVy4XpSHJjYpHXIlmwdwE/HPuBLK0ypCmwRiBvdHiDkcEjsbO6+/DGffuUyfcAXn0VihlVL4QQ1ZaNsw0PPP4ADzz+AJoMDdFh0USsjiDyz0hUKhWu/q6GsuHLwrF2sqZBnwZYO8ikgeZIkhsT2XtxL3P3zOWP03+gR+no9mCdB5nccTIDGg3AQl2yyWdiYmDAAGWod2goLFhQnlELIYT5s7KzotGARjQa0AitRsvNczcNt6X0Oj2b39lManwqlnaWNOjTgKAhQTR8pGGpF/YUpiPJTQXS6XX8feZv5u6ey+6Luw3HQxuGMrnTZDr5dipVB7ebN6FfP0hMhJYtYflymZBPCCFKw8LKglqNaxn2NRkamj3VjIhVESTFJBlmR1ZbqvHv7k/LsS1pOqzpHa4oKgNJbipAVk4WPx3/ifl753P62mlAWR7h6WZPM6njJILcg+5yBWPZ2fDoo3D6NNSpA3//DY4yb5UQQtwXawdres/rTa+5vbhy7AoRqyOIWB1B4slEzv17DvcH3A3JjVaj5dblWzKXTiUkyU05uplxk68OfcXnBz4nITUBABcbF15o8wKvtH8Fbyfve7pu7pDvLVuUhObvv8H73i4lhBCiCCqVitotalO7RW26vdeNa5HXOL3mNA36NDCUOb/1PD+F/IRHMw8a9G1AYL9AfDv6YmElTeimJslNOYhNjmXR4UV8c+QbUrNTAajjXIfXH3ydca3G4WzjfF/X/+gjWLIkb8h3cHBZRC2EEKI4tRrV4qG3Hypw7MqJK6jUKq6euMrVE1fZM3cPNs42BPQKILBfII0HN5Y1r0xEkpsydPzqcT698Cm7j+8mR6ese/CAxwNM7jiZ4Q8Mx9ri/nvdr1wJ77yjPP78c6XPjRBCiIrX8Y2OtBjdgnP/niNqfRRRG6JIv5ZOxKoIIlZF4NPex5DcpF9Lx9bVFrWlzKdTESS5KSM7Luygy7Iuhv1uft2Y3GkyIfVDymwWzL17YeRI5fFrr8H48WVyWSGEEPfIvqY9zZ5oRrMnmqHT6og/HM/Z9WeJPxKPexN3Q7l/Xv6HqA1R1A+pT4O+DWjQpwGOntJRsrxIclNGOvl2omGNhrjr3Jk/eD4P1n2wTK8fHZ035HvAAJg/v0wvL4QQ4j6pLdT4tPPBp51PgeN6vZ64Q3FkJmVycsVJTq44CYB3G2+lr07/QOq0r2OKkKssSW7KiIXagkPjDrHl3y209mpdpte+eVOZcfjaNWjVSoZ8CyGEOVGpVIyPGM/lA5c5+89ZotZHEX8knrhDccQdiiPqnyiePfisoXzWrSxsnGxMGLH5k+SmDNlalv0ET9nZyirfuUO+//pLWRRTCCGE+VBbqvHt6ItvR1+6v9+d1IRUojZEcXb9Wbzb5g13zbqVxTz3edRuUZvAfoE06NsA79beqNSyyGdpSHJTien18MILsHWrMuR73ToZ8i2EEFWBY21HWoxuQYvRLQocv7TvEtosLZf3X+by/stsm7ENe3d7AvsqiU79kPoyAqsEpNt2JTZnDixdqgz5XrkSmjc3dURCCCHKU/1e9Xn90uuEfhNK0JAgrJ2sSU9M59gPx1j1xCpO/HzCUFar0aLX600YbeUlLTeV1IoVMHWq8viLL6BvX9PGI4QQomI4+zjTalwrWo1rhTZbS+zuWKL+UW5hNeibN4ng0SVH2T5rOw36NMC/l79hChIhyU2ltGcPjBqlPH79dWU2YiGEENWPhbUF/t388e/mT6+5vQo8F7M5htT4VMKXhhO+NBzUcHPhTQJ6BhDQMwDfTtV3tmS5LVXJnDsHAwcqQ74HDoR580wdkRBCiMpo8I+DGRE2ggcnPkjNRjVBB5f3X2bnhzv5oecP5GTkteSkXklFr6s+t7Ck5aYSyT/ku3Vr+PlnGfIthBCiaJY2loZWmu4fdWft92vxx5/YbbFkp2Zj45w3nPzXgb9yI+oG/t39Dee4BbiZMPryJclNJZGdDUOGQGQk+PrCn3/KkG8hhBAlZ+1uTXC/YNqMa1PgeE5mDtcjr5OZlMmp305x6rdTALj6ueLf059GAxrRKLSRKUIuN5LcVAJ6PTz3HGzbBk5Ossq3EEKIsmNpa8mkq5O4fOAyMZtjiN4UzaV9l0g6n8TRb4+SlZxlSG70ej3Rm6Lx7eiLtcP9r4doKpLcVAKzZ8P33yu3oGTItxBCiLJmYWVB3U51qdupLl2mdyE7NZsLOy8QvSmaug/VNZS7fuY6P/X+CbWVGt8Ovvj3UG5jebf1NqvOyZLcmNgvv8C77yqPFy6EPn1MG48QQoiqz9rRmsC+gQT2DSxw/NblW7jUcyH5QjIXdlzgwo4LbJuxDWsna/y6+NFhUgf8uviZJuhSkOTGhHbvhmeeUR5PnChDvoUQQpiWf3d/Xo15lZvRN4neFE3M5hhiNseQcSODM3+fofULeWsnXjlxhbhDcQT0DMDF18WEURuT5MZEzp2DQYOUId+DBsHcuaaOSAghhFAW+qxRvwY16tegzfNt0Ov0JIQnEL0pmnqd6xnK/ffLf+yaswuAmg1r4t/Tn4AeAfh18zP5EhGS3JjAjRsFh3z/9JMM+RZCCFE5qdQqvFp54dXKq8BxVz9XfNr7EHcwjutnrnP9zHUOfXkIS1tL3rr5Fpa2pksxJLmpYIWHfMsq30IIIcxR6+da0/q51mQmZXJ++3nDbSwHdweTJjYgyU2F0uvh2Wdh+3ZlyPe6deDldffzhBBCiMrK1tWWxgMb03hgYwA0GRoTRyTLL1SoDz+EH35QbkH99hs0a2bqiIQQQoiyZWVnZeoQJLmpKL/8AtOmKY8XLYKQENPGI4QQQlRVktxUgF27YPRo5fEbb8Dzz5s0HCGEEKJKk+SmnEVFKUO9s7Nh8GAZ8i2EEEKUN0luylHukO/r16FtW2XIt1pqXAghhChX8lVbTrKylJaaM2egbl1llW97e1NHJYQQQlR9ktyUg9wh3zt2gLOzMuS7dm1TRyWEEEJUD5LclIPZs9X8+GPekO8HHjB1REIIIUT1IZP4lbHt2+vw6afKWgpffgm9e5s4ICGEEKKakZabMrRrl4qFC1sA8Oab8Nxzpo1HCCGEqI4kuSkjZ8/CY49ZkJNjwaBBOj76yNQRCSGEENWT3JYqI2o11KwJNWrcZNkyR9Qy5lsIIYQwCUluykj9+rBzZw7//LMfe/sepg5HCCGEqLakeaEMubmBq2uWqcMQQgghqrVKkdwsWrQIPz8/bG1tad++PQcOHCjReb/++isqlYpBgwaVb4BCCCGEMBsmT25WrFjBxIkTmTFjBkeOHCE4OJiQkBCuXr16x/POnz/PpEmTePjhhysoUiGEEEKYA5MnN5988gnPPvsszzzzDE2aNOGrr77C3t6eJUuWFHuOVqvlqaeeYtasWQQEBFRgtEIIIYSo7EzaoTg7O5vDhw8zZcoUwzG1Wk3Pnj3Zu3dvsee99957eHh4MHbsWHbu3HnH18jKyiIrK68fTEpKCgAajQaNRnOf76Cg3OuV9XXNmdRJ0aRejEmdGJM6KZrUi7HqUCeleW8mTW6uXbuGVqvF09OzwHFPT09Onz5d5Dm7du3iu+++Izw8vESvMWfOHGbNmmV0/N9//8W+nFayDAsLK5frmjOpk6JJvRiTOjEmdVI0qRdjVblO0tPTS1zWrIaC37p1ixEjRvDNN99Qq1atEp0zZcoUJk6caNhPSUnB19eX3r174+zsXKbxaTQawsLC6NWrF1ZWVmV6bXMldVI0qRdjUifGpE6KJvVirDrUSe6dl5IwaXJTq1YtLCwsuHLlSoHjV65coXYRy2ifO3eO8+fPExoaajim0+kAsLS0JDIykvr16xc4x8bGBhsbG6NrWVlZldsHoDyvba6kToom9WJM6sSY1EnRpF6MVeU6Kc37MmmHYmtra1q3bs3mzZsNx3Q6HZs3b6ZDhw5G5Rs3bsyJEycIDw83bAMGDKBbt26Eh4fj6+tbkeELIYQQohIy+W2piRMnMmrUKNq0aUO7du347LPPSEtL45lnngFg5MiR+Pj4MGfOHGxtbXnggQcKnO/q6gpgdFwIIYQQ1ZPJk5vhw4eTmJjI9OnTSUhIoEWLFmzYsMHQyTg2NlbWaRJCCCFEiZk8uQGYMGECEyZMKPK5bdu23fHcZcuWlX1AQgghhDBb0iQihBBCiCpFkhshhBBCVCmV4rZURdLr9UDpxsuXlEajIT09nZSUlCo7FK+0pE6KJvViTOrEmNRJ0aRejFWHOsn93s79Hr+Tapfc3Lp1C0CGjQshhBBm6NatW7i4uNyxjEpfkhSoCtHpdMTFxeHk5IRKpSrTa+fOfnzx4sUyn/3YXEmdFE3qxZjUiTGpk6JJvRirDnWi1+u5desW3t7edx1FXe1abtRqNXXq1CnX13B2dq6yH657JXVSNKkXY1InxqROiib1Yqyq18ndWmxySYdiIYQQQlQpktwIIYQQokqR5KYM2djYMGPGjCIX6qyupE6KJvViTOrEmNRJ0aRejEmdFFTtOhQLIYQQomqTlhshhBBCVCmS3AghhBCiSpHkRgghhBBViiQ3QgghhKhSJLkpI4sWLcLPzw9bW1vat2/PgQMHTB2SSc2ZM4e2bdvi5OSEh4cHgwYNIjIy0tRhVSofffQRKpWK1157zdShmNzly5d5+umnqVmzJnZ2djRr1oxDhw6ZOiyT0Wq1TJs2DX9/f+zs7Khfvz7vv/9+idbUqUp27NhBaGgo3t7eqFQq1q5dW+B5vV7P9OnT8fLyws7Ojp49e3L27FnTBFtB7lQnGo2Gt956i2bNmuHg4IC3tzcjR44kLi7OdAGbiCQ3ZWDFihVMnDiRGTNmcOTIEYKDgwkJCeHq1aumDs1ktm/fzvjx49m3bx9hYWFoNBp69+5NWlqaqUOrFA4ePMjXX39N8+bNTR2Kyd28eZNOnTphZWXFP//8w6lTp1iwYAFubm6mDs1kPv74YxYvXswXX3xBREQEH3/8MXPnzmXhwoWmDq1CpaWlERwczKJFi4p8fu7cuXz++ed89dVX7N+/HwcHB0JCQsjMzKzgSCvOneokPT2dI0eOMG3aNI4cOcLq1auJjIzk/9u735Amuz4O4N8525zDyim6jVgZif/6g7UMU4gyKIui0qQYsuqFWNPUKIxMKkh9EVTUi8WietUf6gbLigo1EYpK0WYGlUViQUyTyH9hxXbuF9F49tQdz/2kO2t+P3DBzrk2/V4XevhxnXPtWrt2rYSkkgn6bWlpacJms3nbbrdbGI1GUVNTIzFVYOnr6xMARHNzs+wo0g0NDYn4+HhRX18vlixZIkpKSmRHkqq8vFxkZmbKjhFQVq9eLbZt2+bTt2HDBmGxWCQlkg+AqK2t9bY9Ho/Q6/XiyJEj3r6PHz8KtVotLl68KCGh//33OfmZlpYWAUD09PT4J1SA4JWb3/Tlyxe0tbVh+fLl3r6QkBAsX74cDx48kJgssAwMDAAAdDqd5CTy2Ww2rF692udvZiKrq6uD2WzGxo0bERMTg9TUVJw+fVp2LKkWL16MxsZGdHV1AQA6Ojpw7949ZGdnS04WOLq7u+FyuXz+j6ZMmYJFixZx7P0PAwMDUCgUmDp1quwofjXhHpw51vr7++F2uxEbG+vTHxsbi+fPn0tKFVg8Hg9KS0uRkZGB2bNny44j1aVLl9De3o7W1lbZUQLG69evYbfbsWvXLuzbtw+tra3YuXMnVCoVrFar7HhS7N27F4ODg0hMTIRSqYTb7UZVVRUsFovsaAHD5XIBwE/H3u/7JrrR0VGUl5dj8+bNQf0wzZ9hcUPjzmaz4enTp7h3757sKFK9ffsWJSUlqK+vR1hYmOw4AcPj8cBsNqO6uhoAkJqaiqdPn+LUqVMTtri5fPkyzp8/jwsXLiAlJQVOpxOlpaUwGo0T9pzQv/P161fk5eVBCAG73S47jt9xWuo3RUdHQ6lUore316e/t7cXer1eUqrAUVRUhBs3bqCpqQnTpk2THUeqtrY29PX1Yf78+QgNDUVoaCiam5tx4sQJhIaGwu12y44ohcFgQHJysk9fUlIS3rx5IymRfHv27MHevXuxadMmzJkzB/n5+SgrK0NNTY3saAHj+/jKsfdH3wubnp4e1NfXT7irNgCLm9+mUqmwYMECNDY2evs8Hg8aGxuRnp4uMZlcQggUFRWhtrYWd+/eRVxcnOxI0mVlZaGzsxNOp9O7mc1mWCwWOJ1OKJVK2RGlyMjI+OFrArq6ujB9+nRJieT79OkTQkJ8h2elUgmPxyMpUeCJi4uDXq/3GXsHBwfx6NGjCT32fi9sXr58iYaGBkRFRcmOJAWnpcbArl27YLVaYTabkZaWhuPHj2NkZARbt26VHU0am82GCxcu4Nq1a4iIiPDOgU+ZMgUajUZyOjkiIiJ+WHOk1WoRFRU1odcilZWVYfHixaiurkZeXh5aWlrgcDjgcDhkR5NmzZo1qKqqgslkQkpKCh4/foyjR49i27ZtsqP51fDwMF69euVtd3d3w+l0QqfTwWQyobS0FIcPH0Z8fDzi4uJQWVkJo9GIdevWyQs9zn51TgwGA3Jzc9He3o4bN27A7XZ7x16dTgeVSiUrtv/Jvl0rWJw8eVKYTCahUqlEWlqaePjwoexIUgH46Xbu3DnZ0QIKbwX/5vr162L27NlCrVaLxMRE4XA4ZEeSanBwUJSUlAiTySTCwsLEzJkzRUVFhfj8+bPsaH7V1NT003HEarUKIb7dDl5ZWSliY2OFWq0WWVlZ4sWLF3JDj7NfnZPu7u5/HHubmppkR/crhRAT7CsviYiIKKhxzQ0REREFFRY3REREFFRY3BAREVFQYXFDREREQYXFDREREQUVFjdEREQUVFjcEBERUVBhcUNERERBhcUNEREAhUKBq1evyo5BRGOAxQ0RSbdlyxYoFIoftpUrV8qORkR/ID44k4gCwsqVK3Hu3DmfPrVaLSkNEf3JeOWGiAKCWq2GXq/32SIjIwF8mzKy2+3Izs6GRqPBzJkz8ddff/l8vrOzE8uWLYNGo0FUVBQKCgowPDzs856zZ88iJSUFarUaBoMBRUVFPvv7+/uxfv16hIeHIz4+HnV1deN70EQ0LljcENEfobKyEjk5Oejo6IDFYsGmTZvw7NkzAMDIyAhWrFiByMhItLa24sqVK2hoaPApXux2O2w2GwoKCtDZ2Ym6ujrMmjXL53ccOnQIeXl5ePLkCVatWgWLxYIPHz749TiJaAzIfiw5EZHVahVKpVJotVqfraqqSgghBABRWFjo85lFixaJ7du3CyGEcDgcIjIyUgwPD3v337x5U4SEhAiXyyWEEMJoNIqKiop/zABA7N+/39seHh4WAMStW7fG7DiJyD+45oaIAsLSpUtht9t9+nQ6nfd1enq6z7709HQ4nU4AwLNnzzBv3jxotVrv/oyMDHg8Hrx48QIKhQLv3r1DVlbWLzPMnTvX+1qr1WLy5Mno6+v7fw+JiCRhcUNEAUGr1f4wTTRWNBrN//S+SZMm+bQVCgU8Hs94RCKiccQ1N0T0R3j48OEP7aSkJABAUlISOjo6MDIy4t1///59hISEICEhAREREZgxYwYaGxv9mpmI5OCVGyIKCJ8/f4bL5fLpCw0NRXR0NADgypUrMJvNyMzMxPnz59HS0oIzZ84AACwWCw4cOACr1YqDBw/i/fv3KC4uRn5+PmJjYwEABw8eRGFhIWJiYpCdnY2hoSHcv38fxcXF/j1QIhp3LG6IKCDcvn0bBoPBpy8hIQHPnz8H8O1OpkuXLmHHjh0wGAy4ePEikpOTAQDh4eG4c+cOSkpKsHDhQoSHhyMnJwdHjx71/iyr1YrR0VEcO3YMu3fvRnR0NHJzc/13gETkNwohhJAdgojoVxQKBWpra7Fu3TrZUYjoD8A1N0RERBRUWNwQERFRUOGaGyIKeJw9J6J/g1duiIiIKKiwuCEiIqKgwuKGiIiIggqLGyIiIgoqLG6IiIgoqLC4ISIioqDC4oaIiIiCCosbIiIiCip/A4j4/aQ4cSyxAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.8773 - accuracy: 0.7088 - 395ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 786us/step\n",
            "\u001b[35mTest Accuracy: 0.71\u001b[0m\n",
            "\u001b[34mTest Loss: 0.88\u001b[0m\n",
            "\u001b[33mTest Precision: 0.71\u001b[0m\n",
            "\u001b[32mTest Recall: 0.71\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.71\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Defining the activation functions to test\n",
        "activation_functions = ['relu', 'sigmoid', 'softmax', 'elu', 'selu', 'tanh', 'hard_sigmoid', 'softplus', 'softsign', 'swish']\n",
        "best_activation_function = None\n",
        "best_activation_function_acc = 0\n",
        "\n",
        "for activation_function in activation_functions:\n",
        "  print(f'\\033[36mTesting {activation_function} activation function\\033[0m')\n",
        "  # Defining the model\n",
        "  model = models.Sequential()\n",
        "\n",
        "  # Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "  # These extract the most important visual features from the image.\n",
        "  model.add(layers.Conv2D(32, (3, 3), activation=activation_function, input_shape=(32, 32, 3)))\n",
        "  model.add(layers.MaxPooling2D((2, 2)))\n",
        "  model.add(layers.Conv2D(64, (3, 3), activation=activation_function))\n",
        "  model.add(layers.MaxPooling2D((2, 2)))\n",
        "  model.add(layers.Conv2D(64, (3, 3), activation=activation_function))\n",
        "\n",
        "  # Adding Dense/Fully-Connected Layers.\n",
        "  # These contian the 'classification' part of the model.\n",
        "  model.add(layers.Flatten())\n",
        "  model.add(layers.Dense(64, activation=activation_function))\n",
        "  model.add(layers.Dense(10))\n",
        "\n",
        "  # Fitting the model\n",
        "  test_acc = fit(model,verbose=0)\n",
        "\n",
        "  # Saving the best activation function\n",
        "  if best_activation_function_acc < test_acc:\n",
        "    best_activation_function_acc = test_acc\n",
        "    best_activation_function = activation_function\n",
        "  del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[36mBest Activation Function: elu\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "print(f'\\033[36mBest Activation Function: {best_activation_function}\\033[0m')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OQ5OrhtGv27D"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bLa7sHSYv27D"
      },
      "source": [
        "* The best models were the ones with  the ELU, SoftSign, ReLU and Tanh activation functions, this is because these activation functions are non-linear and thus can learn complex features.\n",
        "* On the other hand, the models with the Sigmoid and Softmax activation functions or a variant of them performed poorly, this is because these activation functions are linear and thus cannot learn complex features.\n",
        "* It was also noted that the SoftSign activation function performed better than the SoftPlus activation function, this is because the SoftSign activation function is non-linear and thus can learn complex features, whilst the SoftPlus activation function is linear and thus cannot learn complex features."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "y4n9fB7Cv27D"
      },
      "source": [
        "### Q.5\n",
        "We have explored with improving the feautre detection process. Now let's turn our attention to the _classifier_ part; the final fully-connected layer. After flattening the features into a 1-D vector, can you modify the final dense layer (change number of neurons, add more layers, etc.) and describe how this affects the performance of the model?\n",
        "\n",
        "Note: The final output of the dense layer must still be 10, as this is the number of classes in our _CIFAR10_ dataset."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:24:22.586262Z",
          "start_time": "2023-11-20T22:24:22.569213Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 871
        },
        "id": "sxcfMVZgv27E",
        "outputId": "33b984f2-0545-4b8f-a2cb-55e62a975683",
        "scrolled": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_49\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_111 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_80 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_112 (Conv2D)         (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_81 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_113 (Conv2D)         (None, 4, 4, 64)          36928     \n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "                                                                 \n",
            " flatten_49 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_103 (Dense)           (None, 32)                32800     \n",
            "                                                                 \n",
            " dense_104 (Dense)           (None, 10)                330       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 89,450\n",
            "Trainable params: 89,450\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 47.54s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9547 - accuracy: 0.6696 - 410ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 833us/step\n",
            "\u001b[35mTest Accuracy: 0.67\u001b[0m\n",
            "\u001b[34mTest Loss: 0.95\u001b[0m\n",
            "\u001b[33mTest Precision: 0.67\u001b[0m\n",
            "\u001b[32mTest Recall: 0.67\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.67\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Defining Model with modified dense layers (Reducing the number of neurons)\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(32, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 871
        },
        "id": "WSnPaxBPzH-X",
        "outputId": "9fe31d52-84a3-430e-a517-a2727d4b8d25"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_46\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_102 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_74 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_103 (Conv2D)         (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_75 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_104 (Conv2D)         (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_46 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_94 (Dense)            (None, 128)               131200    \n",
            "                                                                 \n",
            " dense_95 (Dense)            (None, 10)                1290      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 188,810\n",
            "Trainable params: 188,810\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 28.5s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACMPElEQVR4nOzdd3gU5drA4d9seq+kQUiBhE7oiEiRKu1QVFCQIqhHBRvyqQhSRIWjqBys5yjlWBBUig2BSJEq0kKvoQRIAoSSXja78/0xySZLQkhgk0157uuaKzsz78w82UmyT955i6KqqooQQgghRDWhs3YAQgghhBCWJMmNEEIIIaoVSW6EEEIIUa1IciOEEEKIakWSGyGEEEJUK5LcCCGEEKJakeRGCCGEENWKrbUDqGhGo5H4+Hjc3NxQFMXa4QghhBCiFFRVJTU1laCgIHS6kutmalxyEx8fT3BwsLXDEEIIIcQdOH/+PHXq1CmxTI1Lbtzc3ADtzXF3d7foufV6PevWraNXr17Y2dlZ9Nyi9OQ+VA5yHyoHuQ+Vg9yHu5eSkkJwcLDpc7wkNS65yX8U5e7uXi7JjbOzM+7u7vLDa0VyHyoHuQ+Vg9yHykHug+WUpkmJNCgWQgghRLUiyY0QQgghqhVJboQQQghRrdS4NjdCCFGVGY1GcnJySl1er9dja2tLVlYWBoOhHCMTJZH7UDr29va37eZdGpLcCCFEFZGTk8OZM2cwGo2lPkZVVQICAjh//ryM7WVFch9KR6fTERYWhr29/V2dR5IbIYSoAlRVJSEhARsbG4KDg0v9363RaCQtLQ1XV1eL/Ecs7ozch9vLH2Q3ISGBunXr3lUSKMmNEEJUAbm5uWRkZBAUFISzs3Opj8t/jOXo6CgfqlYk96F0atWqRXx8PLm5uXfVZV7eYSGEqALy22ncbXW9EJVZ/s/33bZLkuRGCCGqEGmvIaozS/18S3IjhBBCiGpFkhshhBBCVCuS3AghhKhSQkNDmTdvnrXDEJWYJDdCCCHKhaIoJS4zZsy4o/Pu2rWLp556yiIxfvfdd9jY2DB+/HiLnE9UDpLcWJAhx0DG6QxUVbV2KEIIYXUJCQmmZd68ebi7u5ttmzRpkqmsqqrk5uaW6ry1atUqU3f4kixYsIBXXnmF7777jqysLIuc806VZeRpUTJJbizEmGvkw4APOTHxBMnnkq0djhCimlNVSE+3zlLa/98CAgJMi4eHB4qimNaPHTuGm5sbv//+O61bt8bBwYGtW7cSGxvLwIED8ff3x9XVlbZt2/LHH3+Ynffmx1KKovDll18yePBgnJ2diYiI4Oeff75tfGfOnGH79u289tprREZGsmLFiiJlFi5cSJMmTXBwcCAwMJAJEyaY9t24cYN//vOf+Pv74+joSNOmTfn1118BmDFjBi1atDA712effUZ4eLhpfcyYMQwaNIi3336boKAgGjRoAMDXX39NmzZtcHNzIyAggOHDh3P58mWzcx0+fJj+/fvj7u6Om5sbnTp1IjY2ls2bN2NnZ0diYqJZ+RdffJFOnTrd9j2pLiS5sRCdrQ6v+l4AJO5NvE1pIYS4OxkZ4Op6+8XdXUedOp64u+tKVb40S0aG5b6P1157jTlz5nD06FGaN29OWloaffv2Zf369ezbt48HHniAAQMGEBcXV+J5Zs6cydChQzlw4AB9+/ZlxIgRXLt2rcRjFi1aRL9+/fDw8OCxxx5jwYIFZvs/++wzxo8fz1NPPcXBgwf5+eefqV+/PqANytenTx+2bdvGN998w5EjR5gzZw42NjZl+v7Xr1/P8ePHiY6ONiVGer2eWbNmsX//flatWsXZs2cZM2aM6ZiLFy/SuXNnHBwc2LBhA3v27GHs2LHk5ubSuXNnwsPD+frrr03l9Xo93377LWPHji1TbFWaWsMkJyergJqcnGzxc68au0qdwQx13SvrLH5uUXo5OTnqqlWr1JycHGuHUqPJfbCszMxM9ciRI2pmZqaqqqqalqaqWh1KxS9paWWPf9GiRaqHh4dpfePGjSqgrlq16rbHNmnSRP3oo49M6yEhIeqHH35oWgfUqVOnmtbT0tJUQP39999veU6DwaAGBwebrn/lyhXV3t5ePX36tKlMUFCQOmXKlGKPX7t2rarT6dTjx48Xu3/69OlqVFSU2fXeeecdNSQkxLRt9OjRqr+/v5qdnX3LOFVVVXft2qUCampqqqqqqjp58mQ1LCzslr9b//rXv9RGjRqZ1pcvX666urqqaXdy4yrYzT/nhZXl81tqbiwooFUAAAn7EqwciRCiunN2hrS02y8pKUYuXLhBSoqxVOVLs1iouQsAbdq0MVtPS0tj0qRJNGrUCE9PT1xdXTl69Ohta26aN29ueu3i4oK7u3uRRzmFRUdHk56eTt++fQHw9fWlZ8+eLFy4EIDLly8THx9P9+7diz0+JiaGOnXqEBkZWarv81aaNWtWZNTpPXv2MGDAAOrWrYubmxtdunQBML0HMTExdOrU6ZbTE4wZM4ZTp07x119/AbB48WKGDh2Ki4vLXcValcjcUhaUn9wk7k1EVVUZSVQIUW4UBUrzWWU0gsGgla2MUxrd/IE7adIkoqOjmTt3LvXr18fJyYmHHnroto1tb/6gVxSlxNnTFyxYwLVr13BycjJtMxqNHDhwgJkzZ5ptL87t9ut0uiKdS/R6fZFyN3//6enp9O7dm969e/Ptt99Sq1Yt4uLi6N27t+k9uN21/fz8GDBgAIsWLSIsLIzff/+dTZs2lXhMdSPJjQX5NfNDsVXIvJpJclwyniGe1g5JCCGqlG3btjFmzBgGDx4MaDU5Z8+eteg1rl69yk8//cTSpUtp0qSJabvBYOC+++5j3bp1PPDAA4SGhrJ+/Xruv//+Iudo3rw5Fy5c4MSJE8XW3tSqVYvERPN/dA8ePHjb2I4dO8bVq1eZM2cOwcHBAOzevbvItf/3v/+h1+tvWXvzxBNP8Oijj1KnTh3q1atHx44db3vt6qQS5vFVl62DLY51HQFI2COPpoQQoqwiIiJYsWIFMTEx7N+/n+HDh5dYA3Mnvv76a3x8fBg6dChNmzY1LVFRUfTt29fUsHjGjBm8//77zJ8/n5MnT7J3714++ugjALp06ULnzp158MEHiY6O5syZM/z++++sWbMGgK5du3LlyhXeffddYmNj+fTTT4v0+ipO3bp1sbe356OPPuL06dP8/PPPzJo1y6zMhAkTSElJ4ZFHHmH37t2cPHmSr7/+muPHj5vK9O7dG3d3d9566y0ef/xxS711VYYkNxbm09uHrrO64tfUz9qhCCFElfPBBx/g5eXFvffey4ABA+jduzetWrWy6DUWLlzI4MGDi2068OCDD/Lzzz+TlJTE6NGjmTdvHp9++ilNmjShf//+nDx50lR2+fLltG3blkcffZTGjRvzyiuvmGazbtSoEZ9++imffPIJUVFR/P3332bdyG+lVq1aLF68mB9++IHGjRszZ84c5s6da1bGx8eHDRs2kJaWRpcuXWjdujVffPGFWS2OTqdjzJgxGAwGRo0adadvVZWlqDc/FKzmUlJS8PDwIDk5GXd3d4ueW6/Xs3r1avr27XvLqkJR/uQ+VA5yHywrKyuLM2fOEBYWhqOjY6mPMxqNpKSk4O7ujq4yNrqpIaxxH8aNG8eVK1dKNeZPZVHSz3lZPr+lzY0QQghRjSQnJ3Pw4EGWLFlSpRIbS5I0vhzcOHODwz8cJiPJgiNdCSGEEKUwcOBAevXqxdNPP03Pnj2tHY5VSM1NOVg+dDmX9l9i6PKhNBrSyNrhCCGEqEFqWrfv4kjNTTkwDea3V3pMCSGEEBVNkptyYEpupDu4EEIIUeGsmtxs3ryZAQMGEBQUhKIorFq16rbHZGdnM2XKFEJCQnBwcCA0NNQ0XHZlEdgqEID4PfFFRqgUQgghRPmyapub9PR0oqKiGDt2LEOGDCnVMUOHDuXSpUssWLCA+vXrk5CQYPEBnu6WXzM/FBuFjCsZpFxIwSPYw9ohCSGEEDWGVZObPn360KdPn1KXX7NmDX/++SenT5/G29sbgNDQ0BKPyc7OJjs727SekpICaGNwFDfPx93IP59qo1KrcS0uH7zM+Z3ncQ6w4Cxz4rby74Ol768oG7kPlqXX61FVFaPRWKZ/6PJrj/OPFdYh96F0jEYjqqqi1+uxsbEx21eWvyVVqrfUzz//TJs2bXj33Xf5+uuvcXFx4R//+AezZs265URis2fPZubMmUW2r1u3DmdLTm1bSHR0NLl+uQBs/X4rsXax5XIdUbLo6GhrhyCQ+2Aptra2BAQEkJaWdttJJIuTmppaDlFZR/PmzXnmmWd45plnrB1KmVWn+1AecnJyyMzMZPPmzeTm5prty8go/fAqVSq5OX36NFu3bsXR0ZGVK1eSlJTEs88+y9WrV1m0aFGxx0yePJmJEyea1lNSUggODqZXr17lMkJxdHQ0PXv25JL3JVLHpVKnQx3cartZ9DqiZIXvg4yMaz1yHywrKyuL8+fP4+rqWqYRilVVJTU1FTc3t2KnGyhPN//nfbNp06Yxffr0Mp93165duLi43NU/qN26dSMqKooPP/zwjs9RFta8D1VJVlYWTk5OdO7cudgRikurSiU3RqMRRVH49ttv8fDQ2rF88MEHPPTQQ3z66afF1t44ODjg4OBQZLudnV25/cG1s7MjrFNYuZxblF553mNRenIfLMNgMKAoCjqdrkzD9+c/Ask/tiIlJBT0GF22bBnTpk0zm9zR1dXVFJOqqhgMBmxtb/+x5O/vb5H4KvI9seZ9qEp0Oh2KohT7d6Msf0eq1DscGBhI7dq1TYkNaJOTqarKhQsXrBiZEEKImwUEBJgWDw8PFEUxrR87dgw3Nzd+//13WrdujYODA1u3biU2NpaBAwfi7++Pq6srbdu2LTKbdmhoKPPmzTOtK4rCl19+yeDBg3F2diYiIuKupx1Yvnw5TZo0MfXKff/99832f/rpp0RERODo6Ii/vz8PPfSQad+PP/5Is2bNcHJywsfHhx49epCenn5X8YiyqVLJTceOHYmPjyctLc207cSJE+h0OurUqWPFyIp34a8LbJ2zlYt/X7R2KEKIaionPeeWS25WbqnL6jP1pSpraa+99hpz5szh6NGjNG/enLS0NPr27cv69evZt28fDzzwAAMGDCAuLq7E88ycOZOhQ4dy4MAB+vbty4gRI7h27dodxbRnzx6GDh3KI488wsGDB5kxYwZvvPEGixcvBmD37t08//zzvPnmmxw/fpw1a9bQuXNnQKutevTRRxk7dixHjx5l06ZNDBkyRIYFqWBWfSyVlpbGqVOnTOtnzpwhJiYGb29v6taty+TJk7l48SJfffUVAMOHD2fWrFk8/vjjzJw5k6SkJP7v//6PsWPH3rJBsTXt+e8eYhbF0PmNztRuV9va4QghqqHZrrNvuS+ibwSP/PKIaX2u31z0GcX3OAnpEsKYTWNM6/8O/Xex8+NNV8veRqYkb775ptn8R97e3kRFRZnWZ82axcqVK/n555+ZMGHCLc8zZswYHn30UQDeeecd5s+fz99//80DDzxQ5pg++OADunfvzhtvvAFAZGQkR44c4b333mPMmDHExcXh4uJC//79cXNzIyQkhJYtWwJacpObm8uQIUMICQkBoFmzZqZZwUXFsGrNze7du2nZsqXph2LixIm0bNmSadOmAdoPSeFs3dXVlejoaG7cuEGbNm0YMWIEAwYMYP78+VaJ/3YCW2uD+clIxUIIUbw2bdqYraelpTFp0iQaNWqEp6cnrq6uHD169LY1N82bNze9dnFxwd3dncuXL99RTEePHqVjx45m2zp27MjJkycxGAz07NmTkJAQwsPDGTlyJN9++62pJ09UVBTdu3enWbNmPPzww3zxxRdcv379juIQd86qNTddu3YtsaouvwqwsIYNG1aZrqVBrYOAgpGKpYW8EMLSJqdNvuU+nY35/6+TLk+6ZVlFZ/736YWzL9xdYKXk4uJitj5p0iSio6OZO3cu9evXx8nJiYceeui23d9vbmyqKEq5jSfj5ubG3r172bRpE+vWrWPatGnMmDGDXbt24enpSXR0NNu3b2fdunV89NFHTJkyhR07duDj41Mu8YiiqlSbm6rGP8ofxUYh/VI6qRdlbAMhhOXZu9jfcrF1tC11WTsnu1KVLW/btm1jzJgxDB48mGbNmhEQEMDZs2fL/bqFNWrUiG3bthWJKzIy0tS93dbWlh49evDuu+9y4MABzp49y4YNGwAtserYsSMzZ85k37592Nvbl2p6IWE5VaoreFVj52RnGqk4fk887nUsO66OEEJUNxEREaxYsYIBAwagKApvvPFGudXAXLlyhZiYGLNtgYGBvPzyy7Rt25ZZs2YxbNgwduzYwccff8ynn34KwK+//srp06fp3LkzXl5erF69GqPRSIMGDdi5cyfr16+nV69e+Pn5sXPnTq5cuULDhg3L5XsQxZOam3KW/2hK2t0IIcTtffDBB3h5eXHvvfcyYMAAevfuTatWrcrlWkuWLDG1+8xfvvjiC1q1asX333/P0qVLadq0KdOmTePNN99kzJgxAHh6erJixQq6detGo0aN+Pzzz/nuu+9o0qQJ7u7ubN68mb59+xIZGcnUqVN5//33yzTVkLh7UnNTzgJbBxKzOIbEmERrhyKEEFYzZswYU3IAt25zGRoaanq8k2/8+PFm6zc/piruPDdu3Cgxnk2bNpW4/8EHH+TBBx8sdt999913y+MbNWrEmjVrimyX+aQqliQ35azxQ40JvjcYv6Z+1g5FCCGEqBEkuSlnrgGuuAa4WjsMIYQQosaQNjdCCCGEqFYkuakAZzac4ecnfmbPf/dYOxQhhBCi2pPkpgJcPnSZfQv2ceKXE9YORQghhKj2JLmpAPnTMMTvibdyJEIIIUT1J8lNBQhoEYCiU0hLSCM1QUYqFkIIIcqTJDcVwN7FHt9GvoAM5ieEEEKUN0luKkjhSTSFEEIIUX4kuakg+e1upOZGCCHKpmvXrrz44oum9dDQUObNm1fiMYqiWGSySkudR1QsSW4qSH5yk3Ujy8qRCCFExRgwYAAPPPBAsfu2bNmCoigcOHCgzOfdtWsXTz311N2GZ2bGjBm0aNGiyPaEhIQKmxcqMzMTb29vfH19yc7OrpBrVleS3FSQ2u1q8+r1V3l88+PWDkUIISrEuHHjiI6O5sKFC0X2LVq0iDZt2tC8efMyn7dWrVo4OztbIsTbCggIwMHBoUKutXz5cpo0aULDhg2tXlukqiq5ublWjeFuSHJTQWzsbHD0dLR2GEIIUWH69+9PrVq1WLx4sdn2tLQ0fvjhB8aNG8fVq1d59NFHqV27Ns7OzjRr1ozvvvuuxPPe/Fjq5MmTdO7cGUdHRxo3bkx0dHSRY1599VUiIyNxdnYmPDycN954A71eD8DixYuZOXMm+/fvR1EUFEUxxXzzY6mDBw/SrVs3nJyc8PHx4amnniItLc20f8yYMQwaNIi5c+cSGBiIj48P48ePN12rJAsWLOCxxx7jscceY8GCBUX2Hz58mP79++Pu7o6bmxudOnUiNjbWtH/hwoU0adIEBwcHAgMDmTBhAqBNNKooCjExMaayN27cQFEU0wSgmzZtQlEUfv/9d1q3bo2DgwNbt24lNjaWgQMH4u/vj6urK23btuWPP/4wiys7O5tXX32V4OBgHBwcqF+/PgsWLEBVVerXr8/cuXPNysfExKAoCqdOnbrte3KnZG4pIYSoglRVJUOfcdtyRqORdH06Njk26HSW+X/W2c4ZRVFuW87W1pZRo0axePFipkyZYjrmhx9+wGAw8Oijj5KWlkbr1q159dVXcXd357fffmPkyJHUq1ePdu3a3fYaRqORIUOG4O/vz86dO0lOTjZrn5PPzc2NxYsXExQUxMGDB3nyySdxc3PjlVdeYdiwYRw6dIg1a9aYPrg9PDyKnCM9PZ3evXvToUMHdu3axeXLl3niiSeYMGGCWQK3ceNGAgMD2bhxI6dOnWLYsGE0b96cYcOG3fL7iI2NZceOHaxYsQJVVXnppZc4d+4cISEhAFy8eJHOnTvTtWtXNmzYgLu7O9u2bTPVrnz22WdMnDiROXPm0KdPH5KTk9m2bdtt37+bvfbaa8ydO5fw8HC8vLw4f/48ffv25e2338bBwYGvvvqKAQMGcPz4cerWrQvAqFGj2LFjB/PnzycqKoozZ86QlJSEoiiMHTuWRYsWMWnSJNM1Fi1aROfOnalfv36Z4ystSW4q0Lkt59j4xkbc67gz5Jsh1g5HCFGFZegzcJ1tnUl50yan4WLvUqqyY8eO5b333uPPP/+ka9eugPbh9uCDD+Lh4YGHh4fZB99zzz3H2rVr+f7770uV3Pzxxx8cO3aMtWvXEhSk9Up95513irSTmTp1qul1aGgokyZNYunSpbzyyis4OTnh6uqKra0tAQEBt7zWkiVLyMrK4quvvsLFRfv+P/74YwYMGMC//vUv/P39AfDy8uLjjz/GxsaGhg0b0q9fPzZs2FBicrNw4UL69OmDl5cXAL1792bRokXMmDEDgE8++QQPDw+WLl2KnZ0dAJGRkabj33rrLV5++WVeeOEF07a2bdve9v272ZtvvknPnj1N697e3kRFRZnWZ82axcqVK/n555+ZMGECJ06c4Pvvvyc6OpoePXoAEB4ebio/ZswYpk2bxt9//027du3Q6/UsWbKkSG2OpcljqQqkKArn/jzH2Y1nrR2KEEJUiIYNG3LvvfeycOFCAE6dOsWWLVsYN24cAAaDgVmzZtGsWTO8vb1xdXVl7dq1xMXFler8R48eJTg42JTYAHTo0KFIuWXLltGxY0cCAgJwdXVl6tSppb5G4WtFRUWZEhuAjh07YjQaOX78uGlbkyZNsLGxMa0HBgZy5cqVW57XYDDwv//9j8cee8y07bHHHmPx4sUYjUZAe5TTqVMnU2JT2OXLl4mPj6d79+5l+n6K06ZNG7P1tLQ0Jk2aRKNGjfD09MTV1ZWjR4+a3ruYmBhsbGzo0qVLsecLCgqiX79+pvv/yy+/kJ2dzcMPP3zXsZZEam4qUECLAFAgNT6VtMQ0XAOs81+XEKLqc7ZzJm1y2m3LGY1GUlJTcHdzt+hjqbIYN24czz33HJ988gmLFi2iXr16pg/D9957j3//+9/MmzePZs2a4eLiwosvvkhOTo5FYgXYsWMHI0aMYObMmfTu3dtUA/L+++9b7BqF3ZyAKIpiSlKKs3btWi5evFikZsdgMLB+/Xp69uyJk5PTLY8vaR9guu+qqpq23aoNUOHEDWDSpElER0czd+5c6tevj5OTEw899JDp/tzu2gBPPPEEI0eO5MMPP2TRokUMGzas3BuES81NBbJ3tce3oTZSsQzmJ4S4G4qi4GLvUrrFrpTlSrmUpr1NYUOHDkWn07FkyRK++uorxo4dazrHtm3bGDhwII899hhRUVGEh4dz4kTpJxlu1KgR58+fJyGhYAyxv/76y6zM9u3bCQkJYcqUKbRp04aIiAjOnTtnVsbe3h6DwXDba+3fv5/09HTTtm3btqHT6WjQoEGpY77ZggULeOSRR4iJiTFbHnnkEVPD4ubNm7Nly5ZikxI3NzdCQ0NZv359seevVasWgNl7VLhxcUm2bdvGmDFjGDx4MM2aNSMgIICzZ8+a9jdr1gyj0ciff/55y3P07dsXFxcXPvvsM9asWcPYsWNLde27IclNBcsfqVgG8xNC1BSurq4MGzaMyZMnk5CQwJgxY0z7IiIiiI6OZvv27Rw9epR//vOfXLp0qdTn7tGjB5GRkYwePZr9+/ezZcsWpkyZYlYmIiKCuLg4li5dSmxsLPPnz2flypVmZUJDQzlz5gwxMTEkJSUVO87MiBEjcHR0ZPTo0Rw6dIiNGzfy3HPPMXLkSFN7m7K6cuUKv/zyC6NHj6Zp06Zmy6hRo1i1ahXXrl1jwoQJpKSk8Mgjj7B7925OnjzJ119/bXocNmPGDN5//33mz5/PyZMn2bt3Lx999BGg1a7cc889zJkzh6NHj/Lnn3+atUEqSUREBCtWrCAmJob9+/czfPhws1qo0NBQRo8ezdixY1m1ahVnzpxh06ZNfP/996YyNjY2jBkzhsmTJxMREVHsY0NLk+SmgslIxUKImmjcuHFcv36d3r17m7WPmTp1Kq1ataJ379507dqVgIAABg0aVOrz6nQ6Vq5cSWZmJu3ateOJJ57g7bffNivzj3/8g5deeokJEybQokULtm/fzhtvvGFW5sEHH+SBBx7g/vvvp1atWsV2R3d2dmbt2rVcu3aNtm3b8tBDD9G9e3c+/vjjsr0ZheQ3Ti6uvUz37t1xcnLim2++wcfHhw0bNpCWlkaXLl1o3bo1X3zxhekR2OjRo5k3bx6ffvopTZo0oX///pw8edJ0roULF5Kbm0vr1q158cUXeeutt0oV3wcffICXlxf33nsvAwYMoHfv3rRq1cqszGeffcZDDz3Es88+S8OGDXnyySfNardAu/85OTk8/njFjPWmqIUfwtUAKSkpeHh4kJycjLu7u0XPrdfrWb16NX379i220RdoPaYWd16MW203Jl6YaNHrC01p7oMof3IfLCsrK4szZ84QFhaGo2Ppx8wyGo2kpKTg7m65Njei7Gr6fdiyZQvdu3fn/PnzJdZylfRzXpbPb2lQXMECWwbiGuCKfzN/crNysXWUWyCEEKJ6ys7O5sqVK8yYMYOHH374jh/flZV8slYwe1d7Xk542dphCCGEEOXuu+++Y9y4cbRo0YKvvvqqwq5b8+rGhBBCCFEhxowZg8FgYM+ePdSuXbvCrivJjRVlp8qsr0IIIYSlSXJjBVeOXOGDOh/waZNPrR2KEEIIUe1ImxsrcA92JzU+FVRIv5yOi1/p5mgRQgghxO1JzY0VOLg54BPpA8hIxUIIIYSlSXJjJTJSsRBCCFE+JLmxEhmpWAghhCgfktxYSX5yI4+lhBCiZF27duXFF180rYeGhjJv3rwSj1EUhVWrVt31tS11HlGxJLmxksCWWnKTcj6F9CvptykthBBVz4ABA3jggQeK3bdlyxYUReHAgQNlPu+uXbt46qmn7jY8MzNmzKBFixZFtickJNCnTx+LXutmixcvxtPTs1yvUdNIbykrcXB3oMmwJjjXcsaoN97+ACGEqGLGjRvHgw8+yIULF6hTp47ZvkWLFtGmTRuaN29e5vPWqlXLUiHeVkBAQIVdS1iO1NxY0UNLH6LvR31xC3KzdihCCGFx/fv3p1atWixevNhse1paGj/88APjxo3j6tWrPProo9SuXRtnZ2eaNWtW7Izchd38WOrkyZN07twZR0dHGjduTHR0dJFjXn31VSIjI3F2diY8PJw33ngDvV4PaDUnM2fOZP/+/SiKgqIopphvfix18OBBunXrhpOTEz4+Pjz11FOkpaWZ9o8ZM4ZBgwYxd+5cAgMD8fHxYfz48aZr3Ym4uDgGDhyIq6sr7u7uDB06lEuXLpn279+/n/vvvx83Nzfc3d1p3bo1u3fvBuDcuXMMGDAALy8vXFxcaNKkCatXr77jWKoKqbkRQogqrKSH2jaAfSnL6gCnUpQty6hctra2jBo1isWLFzNlyhQURQHghx9+wGAw8Oijj5KWlkbr1q159dVXcXd357fffmPkyJHUq1ePdu3a3fYaRqORIUOG4O/vz86dO0lOTjZrn5PPzc2NxYsXExQUxMGDB3nyySdxc3PjlVdeYdiwYRw6dIg1a9bwxx9/AODh4VHkHOnp6fTu3ZsOHTqwa9cuLl++zBNPPMGECRPMEriNGzcSGBjIxo0bOXXqFMOGDaN58+YMGzasDO9ewfeXn9j8+eef5ObmMn78eIYNG8amTZsAGDFiBC1btuSzzz7DxsaGmJgY7OzsABg/fjw5OTls3rwZFxcXjhw5gqura5njqHLUGiY5OVkF1OTkZIufOycnR121apWak5NT6mOy07LVCzsvWDyWmuxO7oOwPLkPlpWZmakeOXJEzczMNNtOCUtfVVUNBoN6/fp11WAwqM4llO1y0/V8b1GurI4ePaoC6saNG03bOnXqpD722GO3PKZfv37qyy+/bFrv0qWL+sILL5jWQ0JC1A8//FBVVVVdu3atamtrq168eNG0//fff1cBdeXKlbe8xnvvvae2bt3atD59+nQ1KiqqSLnC5/nvf/+renl5qWlpaab9v/32m6rT6dTExERVVVV19OjRakhIiJqbm2sq8/DDD6tDhw413YebLVq0SPXw8Cg2znXr1qk2NjZqXFycadvhw4dVQP37779VVVVVNzc3dfHixcUe36xZM3XGjBnFvwmV0K1+zlW1bJ/f8ljKinLSc5jjMYcv239JRlKGtcMRQgiLa9iwIffeey8LFy4E4NSpU2zZsoVx48YBYDAYmDVrFs2aNcPb2xtXV1fWrl1LXFxcqc5/9OhRgoODCQoKMm3r0KFDkXLLli2jY8eOBAQE4OrqytSpU0t9jcLXioqKwsWloP6qY8eOGI1Gjh8/btrWpEkTbGxsTOuBgYFcuXKlTNcqfM3g4GCCg4NN2xo3boynpydHjx4FYOLEiTzxxBP06NGDOXPmEBsbayr7/PPP89Zbb9GxY0emT59+Rw24qyKrJjebN29mwIABBAUFlbm73bZt27C1tS22dXtVYe9ij1e4FyBdwoUQdyathGX5TWUvl1D295vKnr1FuTsxbtw4li9fTmpqKosWLaJevXp06dIFgPfee49///vfvPrqq2zcuJGYmBh69+5NTk7OHV6tqB07djBixAj69u3Lr7/+yr59+5gyZYpFr1FY/iOhfIqiYDSWX8eRGTNmcPjwYfr168eGDRto3LgxK1euBOCJJ57g9OnTjBw5koMHD9KmTRs++uijcoulsrBqcpOenk5UVBSffPJJmY67ceMGo0aNonv37uUUWcWRkYqFEHfDpYTFsQxlnUpZ9k4MHToUnU7HkiVL+Oqrrxg7dqyp/c22bdsYOHAgjz32GFFRUYSHh3PixIlSn7tRo0acP3+ehISCv6F//fWXWZnt27cTEhLClClTaNOmDREREZw7d86sjL29PQaD4bbX2r9/P+npBS2Stm3bhk6no0GDBqWOuSzyv7/z58+bth05coQbN27QuHFj07bIyEheeukl1q1bx5AhQ1i0aJFpX3BwME8//TQrVqzg5Zdf5osvviiXWCsTqyY3ffr04a233mLw4MFlOu7pp59m+PDhxVY9VjUyUrEQorpzdXVl2LBhTJ48mYSEBMaMGWPaFxERQXR0NNu3b+fo0aP885//NOsJdDs9evQgMjKS0aNHs3//frZs2cKUKVPMykRERBAXF8fSpUuJjY1l/vz5ppqNfKGhoZw5c4aYmBiSkpLIzs4ucq0RI0bg6OjI6NGjOXToEBs3buS5555j5MiR+Pv7l+1NuYnBYCAmJsZsOXr0KD169KBZs2aMGDGCvXv38vfffzNq1Ci6dOlCmzZtyMzMZMKECWzatIlz586xbds2du3aRaNGjQB48cUXWbt2LWfOnGHv3r1s3LjRtK86q3K9pRYtWsTp06f55ptveOutt25bPjs72+yHNCUlBQC9Xn9XXfOKk3++spy3VpQ2XkP8nniLx1NT3cl9EJYn98Gy9Ho9qqpiNBrL9IhDVVXT1/J8NHI7jz/+OAsWLKBPnz4EBASYYnn99deJjY2ld+/eODs78+STTzJw4ECSk5PN4r05/sLry5cv58knn6Rdu3ambuJ9+/Y1vVf9+/fnxRdfZMKECWRnZ9O3b1+mTp3KzJkzTecYPHgwy5cv5/777+fGjRssWLDAlITln8fR0ZHff/+dl156ibZt2+Ls7MyQIUN4//33TedR89pe3xxrSffBaDSSlpZGy5YtzbbXq1ePEydOsHLlSp5//nk6d+6MTqejd+/ezJ8/H6PRiKIoJCUlMWrUKC5duoSvry+DBw9m+vTpGI1GU++qCxcu4O7uTu/evfnggw+s+rNQEqPRiKqq6PV6s3ZLULa/JYqa/45bmaIorFy5kkGDBt2yzMmTJ7nvvvvYsmULkZGRzJgxg1WrVhETE3PLY2bMmMHMmTOLbF+yZAnOzs4WiPzuGNINHBxxEICmXzXF1r3K5ZtCiApga2tLQEAAwcHB2Nvb3/4AIaqgnJwczp8/T2JiIrm5uWb7MjIyGD58OMnJybi7u5d4nirzSWowGBg+fDgzZ84kMjKy1MdNnjyZiRMnmtZTUlIIDg6mV69et31zyipTr2fasWNMa9gQt5salJXkwvQLXD91naY+TQnvGW7RmGoivV5PdHQ0PXv2LNKwT1QcuQ+WlZWVxfnz53F1dcXR8ebWNLemqiqpqam4ubmZ2rmIiif3oXSysrJwcnIyDcpYWP6Tl9KoMslNamoqu3fvZt++fUyYMAEoqL6ytbVl3bp1dOvWrchxDg4OODg4FNluZ2dn8T+4fWxsWN+qFcEGAy/fVJ1Wkg4vdcCgNxDQNEA+BCyoPO6xKDu5D5ZhMBhQFAWdTodOV/rmkvmPH/KPFdYh96F0dDodiqIU+3ejLH9Hqkxy4+7uzsGDB822ffrpp2zYsIEff/yRsLAwK0VW4CGjkfU6HXN0Op4CSjupQttn25ZnWEIIIUSNYtXkJi0tjVOnTpnW81uqe3t7U7duXSZPnszFixf56quv0Ol0NG3a1Ox4Pz8/HB0di2y3ltGqyqy0NOJdXfkQmGbtgIQQQogayKp1Y7t376Zly5amFuITJ06kZcuWTJumpQUJCQllHkHSmmyB4XkjRs4Fkspw7OXDl4n5XwxZyVnlEZoQopqoJH1AhCgXlvr5tmrNTdeuXUv8Rm6eSfZmM2bMYMaMGZYN6i7dGx9PC1UlRlGYg5bklMbSgUu5Hnsdt3Vu1OtZrzxDFEJUQfndYnNycnByunnIPSGqh/xRo2/uBl5WVabNTVWhA2YZDAywteVj4EWgTimOC2odxPXY6yTsSZDkRghRhK2tLc7Ozly5cgU7O7tSN0o1Go3k5OSQlZUlDVmtSO7D7RmNRq5cuYKzszO2tneXnkhyUw56qSqdAQVIv13hPIGtAzn8/WEZqVgIUSxFUQgMDOTMmTNFpg4oiaqqZGZm4uTkJF2QrUjuQ+nodDrq1q171++RJDflQAF+QestVdrbkz8Ng0ygKYS4FXt7eyIiIso04aNer2fz5s107txZuuRbkdyH0rG3t7dIzZYkN+WkrMMDBrbSkpsbZ26QeS0TJ295pi6EKEqn05VpED8bGxtyc3NxdHSUD1UrkvtQseTBXzm7CrwC7L1NOScvJ7zqeQGQsFceTQkhhBB3SpKbcvYK8B4w5XYF0RoVgzyaEkIIIe6GPJYqZ68DXwFrgM1A5xLKtnu+Hc1HNadO+9L0rxJCCCFEcSS5KWf1gCeAz4HJwFZu3ci4bse6FRWWEEIIUW3JY6kK8AbgBGwHfrNyLEIIIUR1J8lNBQgCnst7PQUwllD2zIYzbJy2kcSYxPIPTAghhKiGJLmpIK8CHsABYGkJ5XZ/tpvNszYTuy62YgITQgghqhlJbiqIN1qtzT+BLiWUyx/MT0YqFkIIIe6MNCiuQP9XijIyUrEQQghxd6TmxoqKmw89f6Ti67HXybqRVbEBCSGEENWAJDdWcBj4B/BuMfucfZzxDPUEZKRiIYQQ4k5IcmMFe9Am1vwXcKOY/fJoSgghhLhzktxYwQigCXAdbWqGm+UnN5cPXK7AqIQQQojqQRoUW4EN8BYwGJiHNgZOQKH9Lca0oNHgRvhE+lghOiGEEKJqk5obKxkItAcygLdv2ucW6IZvQ18U3a0mahBCCCHErUhyYyUK8E7e6/8AZ6wYixBCCFGdSHJjRd2AHoAe+PCmfSd+PcHy4cvZt3BfxQcmhBBCVGHS5sbK5gCbgWdu2n71xFUOfXeIizsv0vTRptg52VkhOiGEEKLqkZobK2sNvAQ43rS91ZOtcKvtxvXT19nyzhYrRCaEEEJUTZLcVCIGIL/zt4ObA33m9wFg27+2kXQsyWpxCSGEEFWJJDeVxC6gGfAIBdMyNBzckIh+ERj1Rn575jdUtbgJG4QQQghRmCQ3lYQfEAtsBP7I26YoCn0+6oOtky1nN53lwDcHrBegEEIIUUVIclNJhABP571+nYLaG68wL7pM6wLAwW8PWiEyIYQQomqR3lKVyBRgAbAbWAE8mLe9w8QOuPi5EDUqymqxCSGEEFWF1NxUIn7AxLzXU4HcvNc29ja0HNsSna3cLiGEEOJ25NOyknkZ8AaOAV8Xsz83K5ed83di0BsqNjAhhBCiipDkppLxACbnvf7jpn2qqvK/+//HmhfWsHP+zgqOTAghhKgaJLmphMYDa4BvbtquKAqtnmwFwKbpm0iOS67o0IQQQohKT5KbSsgJ6I02uebNWoxpQd376qJP17PmhTUVHJkQQghR+UlyU8ldAx4FzuWtKzqFfp/1Q2er49iqYxz/+bgVoxNCCCEqH0luKrmngKXAYCAjb5tfUz86vNwBgN+f+52c9BwrRSeEEEJUPpLcVHIfAL7APrREJ39wv85vdMYjxIPkuGQ2z9pstfiEEEKIykaSm0quLvADYAN8C8zL227vYk/fj/tSv099Wj/V2lrhCSGEEJWOjFBcBXQF3gdeBP4PiAK6AZH9I4noF4GiFNf0WAghhKiZpOamingeGAUYgKHA2bzthRObzGuZFR6XEEIIUdlIclNFKMDnQGvAHUgvtC8nLYefn/iZjyI/Iv1KerHHCyGEEDWFJDdViBPwE7ALaFJou62jLfG748m8mskfr9w8rrEQQghRs0hyU8XUBnwKrV8GdLY6+n/eHxSIWRzD2T/PWic4IYQQohKwanKzefNmBgwYQFBQEIqisGrVqhLLr1ixgp49e1KrVi3c3d3p0KEDa9eurZhgK6H/AqFoc1DVuaeOqdfUb8/8hiFHJtYUQghRM1k1uUlPTycqKopPPvmkVOU3b95Mz549Wb16NXv27OH+++9nwIAB7Nu3r5wjrXxUYAeQCQwDzgDdZ3fHuZYzSUeT2P7+dqvGJ4QQQliLVbuC9+nThz59+pS6/Lx588zW33nnHX766Sd++eUXWrZsaeHoKjcF+Aw4BOxGG8F4u5cTvT/ozcqRK9n85maaDmuKV7iXVeMUQgghKlqVHufGaDSSmpqKt7f3LctkZ2eTnZ1tWk9JSQFAr9ej1+stGk/++Sx93luxAZYBHWxt2a8oPG408tXQhoQsCOHK4StcOXkF12DXComlMqno+yCKJ/ehcpD7UDnIfbh7ZXnvFFVV1dsXK3+KorBy5UoGDRpU6mPeffdd5syZw7Fjx/Dz8yu2zIwZM5g5c2aR7UuWLMHZ2flOw61UDvv4MO3eezHodIw5dIi+fx1F56jD1q1K565CCCGESUZGBsOHDyc5ORl3d/cSy1bZ5GbJkiU8+eST/PTTT/To0eOW5YqruQkODiYpKem2b05Z6fV6oqOj6dmzJ3Z2dhY99+18qtPxoo0NOlVlR24uNeshnTlr3gdRQO5D5SD3oXKQ+3D3UlJS8PX1LVVyUyX/tV+6dClPPPEEP/zwQ4mJDYCDgwMODg5FttvZ2ZXbD1h5nvtWngcOAuGKQls7OxRAVVUOf3+Yayev0Xlq5wqNpzKwxn0QRcl9qBzkPlQOch/uXFnetyqX3Hz33XeMHTuWpUuX0q9fP2uHU2kowBd5X/PF74pn+SPLUXQKEf0iCGwZaKXohBBCiIpj1a7gaWlpxMTEEBMTA8CZM2eIiYkhLi4OgMmTJzNq1ChT+SVLljBq1Cjef/992rdvT2JiIomJiSQnJ1sj/EqncGKTDqxsV5vGw5qgGlV+/eevGA1Ga4UmhBBCVBirJje7d++mZcuWpm7cEydOpGXLlkybNg2AhIQEU6ID8N///pfc3FzGjx9PYGCgaXnhhResEn9lZUCbSfw54Ph/+uPg7kD8rnj2/HePdQMTQgghKoBVH0t17dqVktozL1682Gx906ZN5RtQNWEDPI42/s10D0c+/N8gsgcvY/3k9UT0jcAzxNO6AQohhBDlSOaWqqaeAcYCRmDGwAbYDW5IdnI2ywYvQ58h4ywIIYSoviS5qaYU4BOgHXBdUfh26UPYhniQGJPI6T9OWzk6IYQQovxUud5SovQcgRVAa+CIvQ07dj3J+7viadA3wsqRCSGEEOVHam6qudrAj2hZ7P5aLnhKYiOEEKKak+SmBrgPWAJsAPzztl0/c53FXRZz9eRV6wUmhBBClANJbmqIh4HCdTYffbqL2B3nWTZoGdmp2bc6TAghhKhyJLmpgX4H3nq3J8tXjyA+9horR65ENVaKKcaEEEKIuybJTQ1kA9gqCkd7hLP0t+EcjD7Nn2/+ae2whBBCCIuQ5KYG6oVWe+MCxHYP55vfR7Du/R0cXXnUypEJIYQQd0+SmxqqCxANuANxnUP4Knok3z33O5cPXbZyZEIIIcTdKXNyExoayptvvmk255Oomjqg9aDyVlUu3lOHxX+MItvb0dphCSGEEHelzMnNiy++yIoVKwgPD6dnz54sXbqU7GzpbVNVtQY2KQp+RpUuEd7UDnK3dkhCCCHEXbmj5CYmJoa///6bRo0a8dxzzxEYGMiECRPYu3dvecQoylkzYJdOYZGNzvQDIY+nhBBCVFV33OamVatWzJ8/n/j4eKZPn86XX35J27ZtadGiBQsXLixxtm9R+dRFG8VYVVWip21g0JpTrPnpmLXDEkIIIcrsjueW0uv1rFy5kkWLFhEdHc0999zDuHHjuHDhAq+//jp//PEHS5YssWSsogIoisLibmHs6BrGI+eT+fXQJe5r6n/7A4UQQohKoszJzd69e1m0aBHfffcdOp2OUaNG8eGHH9KwYUNTmcGDB9O2bVuLBioqzr86hbDpfDLxwR70dbBlw9UM2vg4WzssIYQQolTKnNy0bduWnj178tlnnzFo0CDs7OyKlAkLC+ORRx6xSICi4tWx0bHDw4EOx5OIb+DL/Tey2KQ30NrOxtqhCSGEELdV5uTm9OnThISElFjGxcWFRYsW3XFQwvrqujuyMTGdbvsSuNgykC4Zejba2SD1cUIIISq7Mjcovnz5Mjt37iyyfefOnezevdsiQYnKITLSh58upVNn+3nSne3om2Mg3dpBCSGEELdR5uRm/PjxnD9/vsj2ixcvMn78eIsEJSqP1g/UZ+HfF+kQn8r/7G1wsXZAQgghxG2U+bHUkSNHaNWqVZHtLVu25MiRIxYJSlQuPV+8hx6AUmhbNuBgpXiEEEKIkpS55sbBwYFLly4V2Z6QkICt7R33LBeVXH5ik3YpjS9nbKKBqvIpkGHNoIQQQohilDm56dWrF5MnTyY5Odm07caNG7z++uv07NnTosGJykU1qnzT+xu+9HLinKIwHggCXgBkPnEhhBCVRZmrWubOnUvnzp0JCQmhZcuWAMTExODv78/XX39t8QBF5aHoFHrN7UVC32/xOHeDg1M7k+DtxHxgPtAVeBp4kLsYHVIIIYS4S2X+DKpduzYHDhzg22+/Zf/+/Tg5OfH444/z6KOPFjvmjahewnuE0+fdnuheWss98/7i+jNtOPFWN6K9nNgEHAOGWDlGIYQQNdsd/YPt4uLCU089ZelYRBXR/oX22LvZEz0pGt2nu7n38z0Mn9KJk9O74GOjIz/FNQDjgIeAPoAMASiEEKIi3PHTgyNHjhAXF0dOTo7Z9n/84x93HZSo3BRFodW4VkT2j2Tdy+s4+O1BbPck8KZOMetRtRr4X94SAjwFjAUCrBCzEEKImuOORigePHgwBw8eRFEU0+zfiqJ9rBkMBstGKCotV39XhnwzhKjRUfhE+Jh+BjKvZZKdmk3TEE8mAouAc8AUYDraY6tngC6Ydy8XQgghLKHMvaVeeOEFwsLCuHz5Ms7Ozhw+fJjNmzfTpk0bNm3aVA4hisquXs96eIZ6mtbX/d86Pm38KQnvb+e9XCMX0Wpv7gFyge+B+4G91ghWCCFEtVfm5GbHjh28+eab+Pr6otPp0Ol03HfffcyePZvnn3++PGIUVYghx8D1U9fRZ+iJnhTNF22/4NrfFxkF7AD2Af8EOgGFh4JcBHwM/AFcANSKDlwIIUS1UebkxmAw4ObmBoCvry/x8fEAhISEcPz4cctGJ6ocG3sbRm8czYAvB+Do5UhiTCJf3vMlq59bTVZyFi2Az4E/KXgklQI8l7f0BIIBd6AN8BjwRYV/F0IIIaqyMic3TZs2Zf/+/QC0b9+ed999l23btvHmm28SHh5u8QBF1aPotAbHE45NoPljzUGFXR/v4pNGn3Bx10WtTKHyqcAEYCDQAK1XVRqwB/gWWFuorAo0B/oCE4H/ApuBy0htjxBCCE2ZGxRPnTqV9HRtbug333yT/v3706lTJ3x8fFi2bJnFAxRVl4ufC4O/HkzU6Ch+e+Y3spKz8K7nXaRcbWBOofUc4DTamDnHgIhC++KBg3nL7zedxxN4EnjbYt+BEEKIqqjMyU3v3r1Nr+vXr8+xY8e4du0aXl5ept4yQhQW3iOcZw4+Q9KxJJy8nQBQVZXD3x+m0ZBG2NiZj4BjDzTMW27mA2wCjlOQ/BwDzgI3MK8RUoFEpOu5EELUNGV6LKXX67G1teXQoUNm2729vSWxESWydbQloEVBmnH4+8Msf2Q5X7T9ggs7L5T6PI5oXcifAj5AG0vnNJAOHECb/iHfYkUhEvgSeWQlhBA1SZmSGzs7O+rWrStj2QiLcPJ24tL+SyzosIDfxv9Gdmr2nZ8LaAaE5a2rwAqdjlS0R1UPAHF3G7AQQogqocwNiqdMmcLrr7/OtWvXyiMeUUM0HdaU8cfGEzUqClTY/eluPo/6nLitlklBFGCVwcBctNqedUBTtJ5XUosjhBDVW5mTm48//pjNmzcTFBREgwYNaNWqldkiRGm51HJh0P8GMfKPkXiEeHDjzA0WdV7E9ve3W+T8NsDLQAzQAa1X1lNAb6QWRwghqrMyNygeNGhQOYQharLw7uE8c+AZ1rywhpjFMQS2DLTo+RsAW4B5wFS0gQIvAnUtehUhhBCVRZmTm+nTp5dHHKKGc3B3YOCigdwz8R78m/mbtl86eAm/Jn4ourtrsJ5fi9Mf2IhWk5MvC+3RlRBCiOqhzI+lhChPhROb66evs/DehXzV/SuS45Itcv4GmPeoOo42Y7n0qBJCiOqjzMmNTqfDxsbmlosQlnL50GVUo8rZTWf5rNln7P96v2kWekv5CG1045reoyoVeA1oCWy1cixCCHG3ypzcrFy5khUrVpiWZcuW8dprrxEYGMh///vfMp1r8+bNDBgwgKCgIBRFYdWqVbc9ZtOmTbRq1QoHBwfq16/P4sWLy/otiCqiwT8a8PT+p6lzTx2yU7JZNWoVPw79kYyrGRa7xr+hRveoUoFv0Gq0/gUkA42sGpEQQty9Mre5GThwYJFtDz30EE2aNGHZsmWMGzeu1OdKT08nKiqKsWPHMmTIkNuWP3PmDP369ePpp5/m22+/Zf369TzxxBMEBgaajZwsqg/v+t48vuVxts7Zyp8z/+TIj0eI2xbHwIUDqf9A/bs+f+G2OI+jzVz+FPAjWpJTnRsd70ObrHRb3npdYDLaKND5DGjvkRBCVCVlTm5u5Z577uGpp54q0zF9+vShT58+pS7/+eefExYWxvvvvw9Ao0aN2Lp1Kx9++OEtk5vs7GyyswsGh0tJSQG00Zb1en2Z4r2d/PNZ+rwCOrzagdCeofw8+meuHr/KmY1nCOkeUmzZO7kP4cAGYL5Ox3SdjnWKwlcGA68ajRaIvnJJA17T6fhCp0NVFJxVldeMRl40GnEE8t+1BYrCdzodSw0GfO/gOvL7UDnIfagc5D7cvbK8dxZJbjIzM5k/fz61a9e2xOluaceOHfTo0cNsW+/evXnxxRdveczs2bOZOXNmke3r1q3D2dnZ0iECEB0dXS7nFVD7zdrY/2ZPWts0Vq9eDYBqUFFsivamupP70AB439WVn+rVo9GBA6zOa+OzNSgIF70e76wsfLKycNHrqaoTjhgUhTVdu6K6u9PpwgVGHz6Mb1YWGwqVybS15ZUePUi1taVlZiZTd+4kODX1jq4nvw+Vg9yHykHuw53LyCh9k4QyJzc3T5Cpqiqpqak4OzvzzTfflPV0ZZKYmIi/v7/ZNn9/f1JSUsjMzMTJyanIMZMnT2bixImm9ZSUFIKDg+nVqxfu7u4WjU+v1xMdHU3Pnj2xs7Oz6LlFIYMLXhr0Br7p/g1hPcLoOLkjNnY2FrkPTwLkJesqMNTWlpxCP/dOqkoQEKiqdFFVpheq4dmpKPjk7S+f9LnsdigKrVQVh7z1WopCTm4unf394abfqXyNgCGqymkXF6bcfz/fGAw8UIYG3fL7UDnIfagc5D7cvfwnL6VR5uTmww8/NEtudDodtWrVon379nh5eZX1dOXOwcEBBweHItvt7OzK7QesPM8tzJ1YdYKLf13k4l8XOb32NIO/HoxHuAdgufuQDtyPNvBfPHANyFQUYoFYRcEfsMvrKagC3Sh4tOMJBOUttdHG1/nnXUdUeheB/wO+A95Ba1MD0KkUx0YBO4EHgc2KwiBbW94HXoAy1VrJ70PlIPehcpD7cOfK8r6VObkZM2ZMWQ+xmICAAC5dumS27dKlS7i7uxdbayOqvyYPN0H9TuW3Z34jflc8/2n5H7r/qztqsOX6O7kAawqtZ6ElOfmLX6F9qWjj5lwEMoEbecuRvP3pFCQ3KvAS0AYtIQqyWMSQDXwIvJV3TQVIuoPz+ALRwLPAArR4jwGfUbYERwghKlKZk5tFixbh6urKww8/bLb9hx9+ICMjg9GjR1ssuJt16NDB1M4iX3R0NB06dLjFEaImaPpIU+reV5efxv7E6ejTrH1+La7NXEkISKDuPZbv7+SI1gA5vJh97sBJtMQlhYLanvi81xGFyp5E64qeryHQPW/pAnjfYXy/AS8Cp/LWO6KN59PyDs9nj9ZzrAlaz7K6SGIjhKjcyjzOzezZs/H1Ldp3ws/Pj3feeadM50pLSyMmJoaYmBhA6+odExNDXJw2lNrkyZMZNWqUqfzTTz/N6dOneeWVVzh27Biffvop33//PS+99FJZvw1RzbjXceexNY/xwPwHsHW0Je1gGpvf3Gy1eBTAA2gM9ABGoT0SeqhQGUe0R0at88ofAz4BhqDVmLx3B9edhdat/RQQCHyNNq/WnSY2+RS0WpvdFDzagpozHpAQomopc3ITFxdHWFhYke0hISGmpKS0du/eTcuWLWnZUvvTO3HiRFq2bMm0adMASEhIMDtnWFgYv/32G9HR0URFRfH+++/z5Zdfyhg3AgBFp9D+ufY8tf8pvO73osuMLqZ9aZfSuHbqmhWjK6ou8C5awpAErADGozXkVdFqcvL9idZOZgawGci5xTmHAa7AK2hTSzyGZWtZWhU6X35bpDW3Li6EEFZR5sdSfn5+HDhwgNDQULPt+/fvx8fHp/iDbqFr164lDqdf3OjDXbt2Zd++fWW6jqhZPMM8CXkhhICWAaZtm2dtZvfnu2nxeAu6TOuCR7CHFSMsyhutE1h+R7B4oHDz/HVo0yJsBWai9cK6D629joLWtgYgEm0KiYpo2v8uWtKVP+P6BORxlRCicihzzc2jjz7K888/z8aNGzEYDBgMBjZs2MALL7zAI488Uh4xCnFXVFUl9WIqqkFl35f7+Kj+R/z+wu+kXUqzdmi3FAQUbiL/T+C/wCNoDZgz0BKed/KWvYXKVlSfxdfRRnU2As8Dz1DQS0wIIaypzDU3s2bN4uzZs3Tv3h1bW+1wo9HIqFGjytzmRoiKoCgKw1YOI25rHBumbuDcn+f4e/7f7PtyH+1faM+9/3cvTl6Vu7ddXbSxd55Ee2R1GFiP1lW7BVrbnormgNaDqjHaY7D/oDWS/oE7bwwthBCWUObkxt7enmXLlvHWW28RExODk5MTzZo1IySk+KHwhags6t5Xl9EbR3P6j9NsmLKB+F3xbJ29FdWo0mNOj9ufoJJQ0Cb4bGrtQNBimYTWPuhRtCks2qP12CraMk8IISrGHU+/EBERQURExO0LClGJKIpCvZ71CO8RzvGfj7PtX9vo8HLBUAIpF1Jw8nHCzkkG2SqL/sB2YADaWD+Vux7MMlS0tlH7gaNoQwP0BYoOGSqEqGhlbnPz4IMP8q9//avI9nfffbfI2DdCVFaKotBwYEPGbR+HSy0X0/ZVY1bxUcRH7P7Pbgx6gxUjrHqaAX+j9Z4Kztt2ycmJzYpC6QdNr5wygIRC69fQuuvXAfqh1V4NQet+/yxaDzghhPWUObnZvHkzffv2LbK9T58+bN5svXFFhLhb6VfSuXriKqkXU/nt6d/4pOEn7P96P0ZD9ZsZvLz4obUByre1Th162NrigfboagTayMmb0Wp4KhsVOAf8gtYDbSha3G7A04XKeaE9krNBa3M0BK0R+HW00ZsXV1jEQojilDm5SUtLw97evsh2Ozu7Mk1qJURl41LLhedOPscD8x/Axd+F66evs2rUKj5r9hkHvzuIMVeSnLKyMRqpmzfcw3FgCTARbQRmD7SG0fkuARXZfy0diC20rqLVOIUC/wDeQGscfRytR9jFQmUVYAdavIeB5Whd8NehjS00plDZLUBXYCFU+RosIaqKMic3zZo1Y9myZUW2L126lMaNrdFnQwjLsXWwpf1z7Xk+9nm6z+mOo5cjSUeTWDF8BUeWH7n9CYSZQbGxnMrN5TLwO9oIyoPQHufYYT4dxRS06Ssao43o/G9gG1oSUhIDcBWtp9ZOtLGACnsbGIn2+KgD0ACohVYbM6BQOaVQXM3RkpT3gLVoj6R23XTeCLRRpvPZAD3RRoVuU2j7V2jjAY0DAtBqr9bmxS0qryS0HomVd8AIUZIyNyh+4403GDJkCLGxsXTr1g2A9evXs2TJEn788UeLByiENdi72HPfq/fR5uk27Jy/k+M/HafRkEam/Yn7E/Gu5429a9FaTFFULeCBvCXfdbR5q/KdR6s9OZq3fJ23XYc2avMeChrrPgjEoLV9uXHTtUKAs4XWf0ZrC1ScVCCXgj+EK9Da0ljyrr6B1tj4fxTUXi1Ba58zgoJBGUXlcBl4H20qlHTAB23qkQlotY2iaihzcjNgwABWrVrFO++8w48//oiTkxNRUVFs2LABb28Z3UJUL44ejnR5owudp3ZGUbTxdw16A0sHLiUnNYf2L7Sn3YR2OHnXhP5BlnXzYINrgUS0JGYPWqPcPWg9knIw74V0ETh90/FuaOPr3DxV6jPAw3n7Ci8BaIlMYZacmT1fXbT5uF5D+56+Ar5Dqw1aDhTunpFJzehpVll9hjY5bGbeuhtareBUtMljY9Fq6Gq6NOAI2j8o19H+wbheaHkQ839krOGOuoL369ePfv36AZCSksJ3333HpEmT2LNnDwaDVLaK6ic/sQFIPpeMjZ0Nmdcy2TR9E9vf206bZ9pwz0v34BboZsUoq74AtMdH/QptS8C8pxJoj6wMFCQqXmiPk4ozxrIh3jEFaJu3vA+sBrIpaBuQgzY2UBu0hsyuaCM+69Fql1qhPS4D7f34qtD+wuX0aB8s/fPKXgA+b96c8zodLdF6tbmX1zdZxYWgJTZtgOlo7+P3aI82H6QgsVHRag3LNuFQ5aNSMGXKGeAbiiYq+ct0tEeroP3T0bWE84ZSRZMb0HpNLViwgOXLlxMUFMSQIUP45JNPLBmbEJWSd31vxh8bz5Efj7D1na1cOnCJ7e9tZ+f8nbR4vAWdJnfCo65UYFtKYN5SWHtrBGJB9mhtjwrbitao+re85WbvYJ7cvFbC+T0pSG7SgTVhYWYTnIYCUXnn6wvcU+rIq48LaPOj1UEbYRugD7ARrcF7/of+cLRpTwpPVhuNdv/+Cfwf5VPjZynX0GqcYoFThV7HorWBG5tXLg6YVsJ5Egu99kWrkfTKWzwLvfai5MSnopQpuUlMTGTx4sUsWLCAlJQUhg4dSnZ2NqtWrZLGxKJG0dnoaDqsKU2GNuHk6pNsfWcr57efZ8/ne2gxuoUkN6LMugHH0NoabUT7cLXLW2zR2u3k80WrkbK7abHN+9qlUFl/4METJ8ioX5+DOh0X0NoknQV+QmsUnZ/cxKF94DUvtFTUXGUVJQ6YgzZ1SA7a9/csWk2ZQvEfzDrMG4+vRKvhmYf2KGsc8CpFH4lWBCNaspufuEQBrfP2bUT7ubqVU4VehwBPYJ6kFF5CC5VtgjZkQmVW6uRmwIABbN68mX79+jFv3jweeOABbGxs+Pzzz8szPiEqNUVRiOwXSUTfCOK2xHHy95PUuaeOaf++hfvwa+pH7Xa1rRilqCoaUDDDe0nqAotKeU5PYOTRo/QNC8NOp+MacBBtZOUDQOdCZfcAX950fDAFic4jFNQeVTVn0Wq/FlMwwWsXtNoKl+IPuaVP0WpuZqH16PsUrU3OaLQatXp3G2wJ4vOutQ+th+BpIKvQ/ikUJDf5CXFgXkz1877mL5GFjgvNO291Uerk5vfff+f555/nmWeekWkXhLiJoiiEdA4hpHPBHGvpl9NZPWE1uZm5hHUP477J9xHWLcys/Y4QFc0b7UO9SzH7ItF6dx3IW86g9WI7j/aorAUFyc1W4GO0/+Kb5n2tR+VscLsQ7RFSbt56N7Skprj3oDQUoDfQC9iEluRsREsMd6IljnfzW54/tUd+4/rmaG1+QKsxmnFTeRu05KQe5jV8wWiPJWtib7xSJzdbt25lwYIFtG7dmkaNGjFy5EgeeeSR8oxNiCrNmGuk6SNNOfD1Ac6sP8OZ9Weo3a42HV/rSIMBDdDZlnmYKSHKVRPgzULrycAhCpKdtoX27QBuHvHMAa3bfhO0GgxrTu5qpKCx9n15673Qkrf7LHQNBbg/b9mGluSMpCCxyUR7VHS79yEHrYF5fjKzF639Vb6HKUhuwoEn0d7jRmgJTV2Kb1Cvo2YmNlCG5Oaee+7hnnvuYd68eSxbtoyFCxcyceJEjEYj0dHRBAcH4+YmPUWEyOcW5MbAhQPpOqMr2+duZ+8Xe7n490W+H/I9bkFuPLTsIereZ42n9EKUjgfQMW+5WU+0buyH85YjaB/mMXnLxEJlvwD+g/aBnL80RftQtnQ95jG03k06tLGFQKuROkH5Pi7qiDavmlpo2xfAC8BgtGQvf3qPA2jf9+C8cipaDzl9oWPzp/ZoBfQotF0B/mv58KudMveWcnFxYezYsYwdO5bjx4+zYMEC5syZw2uvvUbPnj35+eefyyNOIaosj7oe9Jnfh85TO/PXv/9i73/3kn45He+IgnGhUi6m4OLngo1dZazUF6KoFpjPI2ZAa9dyGK22p1GhfXsKLYW5onV/30hBt+q5wI9oyYlSzNdvKeidtCCvbP7+zLxzqXnr7wD5rd3KM7EprHCydipvfSWw0s4O1z59SLPT6lhaUpDcOAAPoTVabp23NKfm1rpYwh13BQdo0KAB7777LrNnz+aXX35h4cKFlopLiGrHxc+F7m93p8u0LsTvjsfV39W0b8WIFVw9fpUWj7eg1ROt8Aqvbn1URHVnQ0FD1X/ctG8y2iOhw4WW42iDwR3EfCqKM2jtVm4lu9DrY2DWxT3fILTHT9Zuxj8fbcLVt4GlqkqavT22qkozRaED5uPMLLFWkNXUXSU3+WxsbBg0aBCDBg2yxOmEqNZsHWyp27HgcVTWjSySjiWRfimdrbO3snX2VsJ7htP6qdY0+EcDbOylNkdUbSF5y5BC2/RovX0uoPXoyvc02gBwxrxFvemrX6Gyj6ANSli4bLu8bZVFY7Taplm5uazato2nOnbE1e5WQ04KS7FIciOEuHOOno68FPcSx385zt4v9hK7LpbT0ac5HX0a51rOdHu7G62fbH37EwlRhdihffDfPEJaM0qfnOQ/wqkKgoF6yclm04iI8iPJjRCVgI29DY0fbEzjBxtz4+wN9i7Yy74F+0hLSMPOueC/PH2GHsVGwdZBfnWFEOJW5C+kEJWMZ6gn3WZ1o+v0rpz47QT1e9c37dv16S62ztlK1OgoWj/ZGt+GN0/9KIQQQpIbISopna2OhgMbmm079fspMq9m8tcHf/HXB39Rt1NdWoxpQcPBDXHykvmkhRACCsY4EkJUAY+te4xHf32UBv9ogKJTiNsSx8/jfmau/1yWP7rc2uEJIUSlIDU3QlQhOhsdkf0iiewXScrFFPb/bz+Hlh7i8sHLKLqCETZUVeX4T8cJ6x6Gg5s0YRRC1CyS3AhRRbnXdqfT653o9Honrhy5YjZ62JXDV1g2eBm2jrZE9IugybAmRPaLNGucLIQQ1ZUkN0JUA7Ua1zJbT0tMw7u+N9dOXePo8qMcXX4UO2c7IgdE0mRYEyL6RGDrKL/+QojqSdrcCFENhfcIZ8KJCTy19yk6vtoRz1BP9Bl6Di87zPdDvuf0+tPWDlEIIcqN/OsmRDWlKAqBLQMJbBlI99ndid8Vz+HvD3P6j9PU61kw086Wd7Zw9cRVmgxrQniPcJnfSghR5UlyI0QNoCgKtdvVpnY789l2VFVl7xd7uXH2Bvv/tx8nbyci+kXQYGAD6veuj72rvZUiFkKIOyfJjRA13KCvBnF42WGO/HiE9EvpHPj6AAe+PoCNgw3NRjRj4IKB1g5RCCHKRJIbIWowRVEI6RRCSKcQHvj3A5zfdp5jPx3j+KrjXD993ewRldFgZOe/d1K/T318G/qiKEoJZxZCCOuR5EYIAWhj6IR0DiGkcwi95vbiyuEr2DgUJDcX/rrAupfXse7ldXhHeNNgYAMaDmxInQ510NlI3wQhROUhyY0QoghFUfBr6me2TWejo36f+pxZf4ZrJ6+xY+4OdszdgXMtZyL7R9Lh5Q74NfG7xRmFEKLiSHIjhCiVOvfUYcTqEWSnZnNqzSmO/3Sck7+dJONKBjGLYmj1ZCtT2eTzyag2qhWjFULUZJLcCCHKxMHNgSYPN6HJw00w6A3EbYkjdl0sddrXMZXZPGsze7/ci0tDF7Yf2k6jgY2o1aSWtNMRQlQISW6EEHfMxs6GsG5hhHULM9ueejEVVEg/ms6mqZvYNHUTHnU9iOgfQWT/SOo/UF8SHSFEuZHkRghhccN/G05SbBI/vfcTDnEOnNt4juS4ZHZ/upszf5wh4niEqWxWchaOHo5WjFYIUd1IciOEKBcedT3w7eNL3759QQ9nNpzhxK8n8AjxMJXJzc7lw+AP8YnwMdXqBLUOMpvhXAghykqSGyFEubNztiOyfySR/SPNtifuSyQnLYeEvQkk7E1g85ubcfF3IaKfluiE9wjHwc3BSlELIaoqGZxCCGE1de6pw6TESQxcPJDGDzXG3s2e9EvpxCyM4fsh3/P3x3+byqqq9L4SQpROpUhuPvnkE0JDQ3F0dKR9+/b8/fffJZafN28eDRo0wMnJieDgYF566SWysrIqKFohhCW5+LnQYnQLHv7hYV5JeoWRf4yk/Yvt8arnZVbTc3jZYf7T6j9se3cbN87dsF7AQohKz+qPpZYtW8bEiRP5/PPPad++PfPmzaN3794cP34cP7+iA4ItWbKE1157jYULF3Lvvfdy4sQJxowZg6IofPDBB1b4DoQQlmJjb0N493DCu4fT+4PeZvtO/HqCxH2JJO5L5I9X/6BOhzo0faQpjR9ujFugm5UiFkJURlZPbj744AOefPJJHn/8cQA+//xzfvvtNxYuXMhrr71WpPz27dvp2LEjw4cPByA0NJRHH32UnTt3Fnv+7OxssrOzTespKSkA6PV69Hq9Rb+X/PNZ+ryibOQ+VA6Wvg/d3+tOnY51OPL9Ec79eY4LOy5wYccF1ry4hrqd6zLsp2HYOdtZ5FrVifw+VA5yH+5eWd47RbXig+ycnBycnZ358ccfGTRokGn76NGjuXHjBj/99FORY5YsWcKzzz7LunXraNeuHadPn6Zfv36MHDmS119/vUj5GTNmMHPmzGLP4+zsbNHvRwhRMfTX9NzYfoPrW66TcTwDp3pONHi/gWl/6oFUnOs5Y+NiU8JZhBBVSUZGBsOHDyc5ORl3d/cSy1q15iYpKQmDwYC/v7/Zdn9/f44dO1bsMcOHDycpKYn77rsPVVXJzc3l6aefLjaxAZg8eTITJ040raekpBAcHEyvXr1u++aUlV6vJzo6mp49e2JnJ/9BWovch8qh3O/DY9qX5HPJpF9JJ6hNEKCNm/PvYf8GFeo9UI/GQxtTv1997F3sLR9DFSC/D5VDdbgP2dlw/TpcuwY3bihcv66t37ih5G2D69e17W5u8PXXBoteP//JS2lY/bFUWW3atIl33nmHTz/9lPbt23Pq1CleeOEFZs2axRtvvFGkvIODAw4ORbuS2tnZldsPWHmeW5Se3IfKobzvg299X3zr+5rWr8VfwyvMi6RjSZz4+QQnfj6BnYsdDf7RgKaPNKVe73rYOlS5P313TX4fKofKcB9ycyEpCS5fhitXtCUpSUta8hOW/KXwtszM0l+jVi2ws7Nsn6WyvG9W/Q339fXFxsaGS5cumW2/dOkSAQEBxR7zxhtvMHLkSJ544gkAmjVrRnp6Ok899RRTpkxBp6sUHcCEEFbi39yfZ488y+WDlzm09BCHlh7ixpkbHPruEIe+O0TvD3tzz4v3WDtMISxGr9eSk/xEpXDSUtzr69fv/FqKAp6e4O0NXl7mS+Ftvr63PVW5smpyY29vT+vWrVm/fr2pzY3RaGT9+vVMmDCh2GMyMjKKJDA2NtpzdRkHQwgBoCgK/s398W/uT7e3uxG/O55DSw9x5IcjNH64sancni/2cOSHI9TrVY96vevh19RP5rwSFUpVIT0dUlLMl+Tkottu3p+ftNxJsqIoWgJSq5a2+PoWJCclJS7u7lAV6hCsXjc7ceJERo8eTZs2bWjXrh3z5s0jPT3d1Htq1KhR1K5dm9mzZwMwYMAAPvjgA1q2bGl6LPXGG28wYMAAU5IjhBD5FEWhdtva1G5bm15ze5klLyd+OcHp6NOcjj5N9P9F4xrgSr1e9QjvFU54j3Bc/V2tGLmoijIzISEB4uPNlwsXbDh+/B7+9S8bUlMLkpfUVDAa7/66igI+PuDnV5Cw5L8ubpu3N1Tnj0yrJzfDhg3jypUrTJs2jcTERFq0aMGaNWtMjYzj4uLMamqmTp2KoihMnTqVixcvUqtWLQYMGMDbb79trW9BCFFF3Fwr0/PdnoR1D+P0utOc3XSWtMQ09n+1n/1f7cfG3oZXr79q6l6uqqrU6tRgOTmQmFg0abl5uXUtig7wv9VOdDqtVsTDQ/tamiW/5sXPr/onK2Vl9eQGYMKECbd8DLVp0yazdVtbW6ZPn8706dMrIDIhRHXm29AX34a+3PPCPeRm53J++3li18Vyet1pHNwdzMbNWdxlMfYu9oT3Cqder3rUalxLkp0qLP9xUHFtUwpvy09arlwp/bkdHSEoyHzx9zcQH7+fTp2a4+1tWyRRcXbWal+EZVSK5EYIIazN1sGWsPvDCLs/DGaDIaegG2tGUgZxW+NAhVNrTgHgFuRmaqsT3iMcZ18ZN8taVFWrWcnI0Hr3FJeoFJfElHXWHju7oklLYGDRbZ6eRRMVvd7I6tXn6du3GdJprfxJciOEEMWwsS+o43fyceLp/U+banXObT5HanwqMYtjiFkcQ9NHmvLgdw8CYDQYSY5LxjPUU2p2iqGq2qOb/BqRpCQtKcnM1L4Wfl3ctlu9vtP+JI6O5m1SCi9+fuZJi7d31WhMKyS5EUKI21IUBf9m/vg38+fel+9Fn6knbmucKdmp17ueqezlQ5f5T4v/4BroSt2OdQnuGExwx2ACWgRgY1d9G0XkJy2FG9MW9zohQRsMrry4uBSfpBSXvNSqpZWXHLT6keRGCCHKyM7Jjno961GvZz14z3wYiqsnrqKz1ZGWkMaRH49w5McjANg62VK7XW06v9GZ8O7h1gq91PR6rUdP4SUlRRuFtnDD2sIJTFmSFh8frTYkP8FwdgYnJ/OvZX3t5IQ88hGAJDdCCHHXCj9+avJwEyL7RRK/O564bXGc33ae89vPk3U9i3N/nkOdUpAIndlwhkNLDxHcMZi6HeviVc/LYo+yjEa4ehXOnYP9+33JzlZITy+asOQnLTdvK8totIV5exdti3Jzu5SAAChm4HghLEaSGyGEsDA7ZztCOocQ0jkEANWoknQsifPbz1Pnnjqmcid/P8neL/ay94u9ALj4uZgeY0X2i8S3YdFhXlVVSz7ya0suXiy+S3JCglb7AnZAxzv+Xpydte7JhZeAgKIJS2Cgtjg63vGlhLAYSW6EEKKcKTqFWo1rUatxLbPtDf6hzWR+YfsF4nfHk345nWMrj3Fs5TGiJ0XjNOlZEg21iiQuZalV8fNTcXRMpXZtVzw9daYEJX9MlZIWd3ewlU8JUQXJj60QQpSzjIziR61NSAghPj6E+KtwyT4Xt5x46nKeMM7gyQ0+nltQc/MAa2hKNnY0IJZ6uHrZmWpNatcu2h1ZG1sFFCWX1as30rdvX4tPZChEZSXJjRBC3CG9XktaLly49Yi1CQlaI9zbs+UGdbnhVpcrgR2pHWhkRB1Fe+TjbyBt+n6M6Vm0JAZbR1vC7wunwcAGRPaPLHGaCO3RlBA1iyQ3QghRjMxMrT3LhQvaUvh1/nLpUunHV3F2Lr52pXCD28BAcHPLP6KglsVoUDjXcijHfz7O8Z+Oc+PsDU78coITv5wABVo83oKBCwZa/D0QoqqS5EYIUeOkpJSctFy4oI10Wxr29iU/Gspf3NzufDwVnY2OsG5hhHULo/eHvbl88LIp0YnfHY9HsIepbE5aDptmbqLBPxoQfG/wnV1QiCpOkhshRLWhqlr351slLPnbU1NLdz5nZwgO1hKXOnXMl/xtvr4VO2qtoij4N/fHv7k/nad2JuViCjrbggBi18WyY+4OdszdgZOPE/X71ifFN4XLdS8T0LR6DyQoRD5JboQQVYLBoM0LVFKNy8WLpZ8vyNOzaMJSOGmpU0frMVTZR691r+1uvl7HneaPNefEbyfIvJrJwa8PAvDlh1+is9Mx/Nfh1Ouljaicfjmd3Oxc3Ou4y1QRolqR5EYIUSmkp8P589qgc3FxBV/zX1+4ALm5pTuXn1/xyUrhbS4u5fv9WEvtdrUZ/PVgDHoD57ed5+iqoxxac4jc+FxyUnPwDPM0ld27YC8bXt+Ag4cDfk398Gvmh38zf9NXR08ZtEZUTZLcCCHKnapqtS7FJS35X69evf15dDqt0W1JtS1BQTL6LYCNnQ2hXUOp3bE2Offn0KdPHzLiM3APLqjpybyWic5WR3ZytjaS8rbzZud45uAz+DX1AyDpWBK52bn4NvTF1kE+OkTlJj+hQoi7kpNT/FxDFy7YEBNzL5Mm2XL+fOnmHXJzg5AQqFu36Ne6dbXERgaVuzOKouAZ6mm2rdd7vej+dneSjiVx6eAlLh+8zOWDl7l08BJpCWl4R3ibym57bxsxC2PQ2eoIvjeYiP4RRPbXRlGWR1qispE/E0KIYun15knLrWZ5Tkq61Rl0QMGIvIqiJSfFJS75Xz09K+AbE2Zs7G1MDZQLy07NNquhsbGzwcHDgezkbM5tPse5zef445U/8AzzJLJ/JL3m9sLGXhori8pBkhshaqjMTDh9GmJj4dQp7euZMwXJy5UrpT+XnZ35WC3a6LgGkpL2M2BAc8LDbalTR+s2LaoGBzfzZ3v9P+9Pv8/6cf30dU79fooTv57g7Maz3Dhzg9h1sWaJTWx0LH5N/XALdLv5tEJUCEluhKjGUlIKEpfCX0+d0noW3U5xScvNg84FBWkzQd/cHVqvN7J69Xm6dGmGnV35fH+iYimKgnc9b9pNaEe7Ce3IScvh9PrTGHIMpjK5WbksG7wMfbqewNaBRPaPJLJ/JIGtAlF0NevxlaqqJGUkcSzpGIcvHWbn5Z1c3HsRDycPXOxdcLV3xdXeFRe7Qq/tXXCydZJHfXdJkhshqjBV1R4LFZfAxMbevvbFwwPq19eWevUgPFxrlFtS0iJEPntXexoObGi2LTUhFb8mflz8+yIJexJI2JPAnzP/xMXfhYh+EUSNisLnHh+SMpK4mnmV5Kxkco25GFQDucbcIovBWHR7SWU9HT2p416HOu51CPYIprZbbVzsy7drnMFo4MyNMxxLOma2HE06yrVM89EgF8cvvu35FBRTopOf9BRJguxc0Ck6VFRUVUVFGyq7uNdq3jDaRV4XWtcpOhxtHXG0dcTJ1gknOyfTa0dbR5zsnG75+uZjbHXWTy2sH4EQ4pYMBu0R0c09iwp/vd2AdH5+BclL4a/162vJi/yDKO6UqqqkZKdwNfMqSRlJWsKScZXUeamkX0nn9MnTXLh4gcvJl0l3SCfDOYOsTVnkbipln34L8XL0Kkh43INNrwsnQa72t56fK19aThonrp7QEpcrRzl2VUtiTlw9QY4hp9hjFBRCPENo4N2ArOtZeNTyICM3g/ScdNJy0kjLSSNdr73O0GcAWuKRmpNKak4pR5usZGx1ttRxr8OZF85YLwarXVkIQXp6yd2jL1zQEpzbCQ42T1oKJzJu0uyhylJVFaNqxKgaUSl4bVSNZvtK2p+tzyYhO4FDlw9hUAxk6jPJys0yLZm5Besl7st7nanP5FrmNVPNS67xNomKR95yE0dbRzzwwBhvxFa1xd7BHgdHBxydHXF0ccTJzQlHJ60WwEZng63O1myxUYpu0yk6rmVe40LKBS6kXOB8ynnSctK4nnWd61nXOXj54K3DdPAwT3jcg/F09OT09dMcTTrKsaRjnE85f8vjHW0daeDTgIa+DU1LI99GRPhE4GznjF6vZ/Xq1Xmzsxf/nNaoGsnQZxQkPcUkQIX35dfQKCgoioKC9p9Kca/zH3MV91pBwaAazH4OTPe70H0v6XXh5C6/Fs2aJLkRopzl5MCxY3DgABw8CCdOFCQwpRnbxdZWS15u1T06JAScnMr/+xCWZVSNxCXHceLqCbPl+NXjnE8+j0G18IfDUcuerjBnO2d8nHzwdfbF19kXH2cffJ3yvuZvy9ufv83ZzpnNb21my8It5GYVnyA9tu4x6vXURlO+evIqaYlp+DXxw8m79D/wyVnJpmSncNJTeD05O1lbriRz+MrhEs9Xy7kWjWo1oqFPQ7NEJsQzBJ1yd89wdYrO9NipqjGqRrPk6LZJbzmT5EYIC1FVbYTd/CTm4EHt9fHjJY+s6+FRNFkp/DUgAGykh22xbtfWoKTXNooN9jb25dpwU1VVrmZe1ZKWpONaAnNNS2JOXj1JtqEUg/+UkYKCTtGZFkVRwAhujm6mNhGF21aYrds54Whz03ox5b2cvMySFie7O8uuO0/tzH2T7+N67HUuH7pcsBy8zNWTV00DCALELI5h6ztbAXALcsOvqR+1mtbSRlZu6kdAVECxXdE9HD3wcPSgiV+TW8aRmp1aJAG6kHKBa1nXCPMMMyUwDXwa4OPsc0ffa3WnU3Q42znjbOcMleCfLUluhLgDyckFCUx+EnPokLa9OJ6e0KyZtjRuDKGhBcmMRzFV9tVBhj6D+Ox4Yi7FkG3MNlWxp+vTb/06r+q9uP0Z+gzT4xdLsdXZ4mbvhpuDG672rkVfl7Sv0GtXe1cS0xLNal/yX1/Pun7L69vp7KjvXZ9In0izJcwzDAdbh4IEpZiExWw9b39xiVppHodYk85Gh0+kDz6RPjQa0si0PTcrFxuHgmTFzskOjxAPks8lkxqfSmp8KrHrYk37nz/9PF5hXgCc33GerBtZBLYKxNX/9rUgbg5uNKrViEa1Gt22rKgaJLkRogR6vVbzUjiJOXhQe6RUHDs7aNhQS2KaNy9IaOrUqRkNd9Nz0vnt5G8sO7yM1SdXk5WbVa6PQ+5WrjHX1B6jPAW7BxPpE0kDnwZmSUyIZ0il6FlSGdk6mr8vnad2pvPUzmSnZHPlyBWzWp7rZ67jGeJpKrtz3k4Of689XnILciOwVSABrQIIbBVIUOsg3Gq7SVfrak5+q4TIc+0a7N9vvhw+rLWZKU5wcEHykp/INGhQ8waqy9Rn8vup3/n+8Pf8cuIXU48PAEedI17OXqYurfldWV3sXQpe27mUvD/vtYu9CzaK9p/87RpPlua13qg3Nc5MzdZ6pqRmp2rrxbxOzbn1vnR9Ol6OXjTwzUtevCNNr+t719eq6oVFOLg7UOeeOtS5p84ty3iEeODbyJekY0mmWp4Tv54AQGenY3LqZNPoy/F74nHycsIzzFMSnmpEkhtR4xgMcPKkeRJz4IDWM6k4rq7mtTDNm0PTpuDlVbFx58tvxxF7LZazN87i6+xLq8BWeDlVXEDZudmsjV3L94e/56fjP5GWk2baF+YZxrAmwxjcYDDxe+Lp169fpXwcAuDp6GmR8xhV4103JhWW0/PdnvR8tyc5aTlcOnCJhL0J2rInARsHG7NpJX596lcS9ibg6OlIQEutdid/8Y7wRmcj97UqkuRGVGvJyVriUjiROXRIm3qgOGFhEBVlvoSGVvxAdgajgQspF4i9HkvstVjta6HXKdkpRY4J9wqndWBrbQlqTavAVng7eRdz9juTY8jhj9N/8P3h71l1bBXJ2QUNjILdgxnaZCjDmgyjTVAbFEVBr9eToCRY7PqVmSQ2lZO9qz3B9wYTfG+waZtqLGizpaoqto622NjbkHUji7Mbz3J241nTfp9IHyYcn2BWXmp3qgZJbkS1kZUFf/8NGzfqWL26HS++aMvZs8WXdXbWamHyE5jmzbXF3b0C483N4sz1M8UmMGdunLnloGD5arvVJtQzlPjUeM7cOMPp66c5ff00Pxz5wVQm1DPULOFpHdi6TL09co25bDizgWWHlrHy2EqztilBbkE83PhhhjUZRvs67eUDXlQJhaeAUBSFsdvGYsgxcOXIlYIanr0JJMYkEtg60FRWVVU+ivgI3wa+hN4fSmjXUAJaBkjNTiUlyY2osjIy4K+/4M8/teWvvyA7G8AGKPijFBxctDamXj3Ld682qkaSs5K5mnmVqxlXuZZ5jauZeV8zrppex6fGE3s9lospF0vs+WOnsyPMK4x6XvW0xbvga5hnmFn322uZ19ibsJc98XvYk6Atp6+f5uyNs5y9cZblR5ebyoZ4hJgSnfykx9fZ17TfYDTw57k/WXZoGSuOrSApo2Dab38Xfx5q/BDDmgyjY92OktCIasHG3oaAFgEEtAig5diWABgNRnJSC/7BuHL4Ctdjr3M99jonV58EwMHDgZDOIYR2DSWibwS+DX2LPb+oeJLciCojLQ22by9IZv7+W+vNVJi/P3TqZMTD4zCPPNKIVq1s8b6LJzPJWcnsTdjL5fTLxScthbZdz7qOUTWW6fxu9m4FSctNCUywezA2utJlYN5O3vQI70GP8B6mbdczr7MvcZ9ZwnPq2inOJZ/jXPI5VhxdYSob7B6sJTlOvvxy4hcupV8y7fN19uXBRg8yrMkwOod0LnVMQlRlOhsdjp6OpnXfRr48tfcp06Orc5vPkZ2czYlfTnDilxOkX0mnx2zt90+foefaqWv4NfWrcZOFVhaS3IhKKyUFtm4tSGZ27y46FUHt2tClS8ESGQm5uQZWrz5Nly4NyzwbdUJqAlvjtrIlbgtb4rZw4NKBMicsrvaueDt54+Pko3119sHbUfvq4+SDn4ufKYnxdfYtt2f4Xk5edAvrRrewbqZtN7JusC9hnynZ2ZuwlxNXT3A+5bzZ0PJejl4MaTSEYU2GcX/Y/dJdWdR4OhsdgS0DCWwZSIeJHTAajCTuS+TsJi3Zqdernqns2U1nWdJvCU4+ToR2CSX0/lDq3FfHNEmlKH/yF0tUGtevw5YtBcnMvn1gvCmvCAkxT2bCw+98/BhVVTl17ZQpkdlybgux12OLlAvzDKOuR11TclIkcclb93H2wcvRCwdbhzsLqAJ4Onpyf9j93B92v2lbSnaKKeG5mHKR7uHd6RHeA3ubGtanXYgy0NnoCGoTRFCbIO6ddK/ZvtT4VOxc7Mi8msnRFUc5ukIb7EnnrONy48v0/7w/Qa2DAMhJy0FnpzPrwSXunrybwipUFU6d0trJ/PUXbNum9Wq6+R+bevXMk5mQkDu/psFo4MClA6ZkZmvcVhLTEs3KKCg0929Op7qd6BTSifvq3keQW9CdX7QKcHdwp0toF7qEdrF2KEJUC62eaEXU6Cjid8ebHmPFbYsjNyOXhN0J2DkXVCn//cnfbHh9A55hnvg28MWnoQ++DXzxbeiLTwMfXPxcpIfWHZDkRlSIlBTYtQt27ChIaIqbNLJBg4JEpnNnbWTfO5WVm8Vf8X+Zkpnt57cX6UJtb2NPu9rtuC/4PjqFdOLe4HstNvaJEKLmsrGzIbhDMMEdgun0eiey0rNYtXAVTfya4F2voCHg9dPXUY1qkcbK+Z7e/zT+zf0BuPj3RVIupuDbwBfv+t7FzqUlNJLcCIszGrUpCwonMocOFa2VsXPKIqLbdlybrSfXdz9e3iqODgoJio5lisL3Wwvmyyk8d07+XDqFXxcup6oqO0/tJPZgbJHu1G72bnSs21Grmanbiba12+Jo64gQQpQnG3sbnOo60bBvQ2zsCpKS/p/3p+uMrlw9fpWkY0kkHU/i6rGrJB1PIjkuGe+IgkRozxd72PflPgAUGwW/Jn4EtQuidtva1G5XG79mftI1PY8kN+KuXb8OO3dqScyOHdrr4iaQrBtqoEGXfTg0+oNLLus5mLyVI7lZ2s60vMXC/F386RTSyZTMNPdvLr19hBCVhqIouAW64RboRmjXULN9udm5Zm1xPEM9CWoTRNLxJHJStdGXLx24ZEp4Xrn6Ck7e2hARifsTsXe1xyvcq0Y+1pLkRpRZZiYsW1YwtsyxY0XLODlBm7YqDTqcRKn3Bxft17MjcSPRWdchC20BAlwD6BHeg3vr3IujraNp1mdVVe/4tT5Xz5XTV3i639M08mtUI3+xhRBV382NjDtP6UznKZ1RVZXUi6nE747n4q6LxP8dT9aNLFNiA7D2pbWc3XgWJ28ngtoGUbudVrsT1DaoVDOlV3WS3IhSS06GTz+FefPg8mXzffXrwz33QON2CRhC1nPSsJ4NZ/9gS8oFiC8o5+7gTtfQrvQI60H38O408rV88qHX61mdvJoI7whJbIQQ1Y6iKLjXcce9jjsNBzUstozOVoeNvQ2Z1zKJXRtL7NqCnqCBrQJ5as9TpnVDjqHatd+R5Ebc1uXLWkLzySdaw2DQei2NGAHN2yWTE/gnu67+wfoz6/nmyhG4VnCsvY09HYM70j2sO93Du9MmqI2MmSKEEOVs5LqRGHIMXDpwyVS7c/Hvi1w5egXnWuaz1H/c4GPsnO0IbB1IUJsgAlsHEtAiAHuXqjscRKX4lPnkk0947733SExMJCoqio8++oh27drdsvyNGzeYMmUKK1as4Nq1a4SEhDBv3jz69u1bgVFXf+fOwdy58OWX2rxNAA2bZTJowg4I28CGuPX8a/8uDDEFI+spKLQKbEX3MG2slI51O+Js53yLKwghhCgvNvY2prF4eEbblp2STea1gpmD06+kc+PsDQCuHLnCga8PANocXL4NfWn6aFM6T+1c0aHfNasnN8uWLWPixIl8/vnntG/fnnnz5tG7d2+OHz+On59fkfI5OTn07NkTPz8/fvzxR2rXrs25c+fw9PSs+OCrqaNHYc4cWLIEctUcCNpF7U4b8Gq1gZOZO5iTkA2FJnuO8I6gR3gPuod15/6w+y06E7UQQgjLcXB3wMG9YKBRl1ouvJzwMvG744nfE0/C7gTi98STlpDGlSNXSEss6Omhz9Dz5T1fEtAiQKvlaR2k1fC4Vr4aHqsnNx988AFPPvkkjz/+OACff/45v/32GwsXLuS1114rUn7hwoVcu3aN7du3Y5c3tn5oaGhFhlxt7doF78w2sOrvvRC6AR7ZiC5sC0abDC4CF/N+xoPcgrRh/UO70T28O3U96lo1biGEEHfONcCVyP6RRPaPNG1LTUglYU8CbrXdTNsS9ydy+eBlLh+8bKrhQYFajWoR2DqQZiOaUb93/YoOv1hWTW5ycnLYs2cPkydPNm3T6XT06NGDHTt2FHvMzz//TIcOHRg/fjw//fQTtWrVYvjw4bz66qvYFDPNc3Z2NtnaVNEApOQ1GtHr9ehvnnXxLuWfz9LnLU8Go5HFqw/zwco/OZm7ERpshqiCftxGwNfJly4hXbg/9H66hnQt0lC3sn2/VfE+VEdyHyoHuQ+VQ1W7D46+joT1DgMKYvaK9GLoqqEk7E0gcU8iCfsSSIvXaniuHLmCX3M/QrrdxTDyt1GW986qyU1SUhIGgwF/f3+z7f7+/hwrrn8xcPr0aTZs2MCIESNYvXo1p06d4tlnn0Wv1zN9+vQi5WfPns3MmTOLbF+3bh3OzuXTFiQ6OrpczmsJqqpyMfsiB1IPsjnuJCf0MRgdr0HBnG84KS40c2tCM7dmNHNtRl3HuugUHSTCqcRTnOKU9b6BMqjM96EmkftQOch9qByqxX1oBS6tXKhPffTX9WTEZpAZm8l5u/MkrU4qt8tmZGSUuqzVH0uVldFoxM/Pj//+97/Y2NjQunVrLl68yHvvvVdscjN58mQmTpxoWk9JSSE4OJhevXrh7u5u0dj0ej3R0dH07NnT9MisMlBVldWnVvP9ke/ZeHYTiel5DWZs8pYcF4LV+3i0fVcGt+xKC/8WVXqgu8p6H2oauQ+Vg9yHykHuw93Lf/JSGlZNbnx9fbGxseHSpUtm2y9dukRAQECxxwQGBmJnZ2f2CKpRo0YkJiaSk5ODvb15wyYHBwccHIrO0mxnZ1duP2Dlee6y2n5+O69Ev8K289sKNuY6wPl7cYjvxtC29/P2+LYEB1W+BmF3qzLdh5pM7kPlIPehcpD7cOfK8r5ZdRIKe3t7Wrduzfr1603bjEYj69evp0OHDsUe07FjR06dOoXRaDRtO3HiBIGBgUUSm5rsWNIxBi8bTMeFHdl2fhtKrhPseAkWb8D3yxu802ADl36Yyldvd6yWiY0QQoiay+ozbE2cOJEvvviC//3vfxw9epRnnnmG9PR0U++pUaNGmTU4fuaZZ7h27RovvPACJ06c4LfffuOdd95h/Pjx1voWKpX41Hj++cs/afppU1YdW4Wi6mDPE6j/Pkmdwx/w0cv3cy7WkcmTwcPD2tEKIYQQlmf1NjfDhg3jypUrTJs2jcTERFq0aMGaNWtMjYzj4uLQ6QpysODgYNauXctLL71E8+bNqV27Ni+88AKvvvqqtb6FSiElO4V3t73LBzs+IDNXG6DJ8ew/yPptNlxpzPjxMHs2uLnd5kRCCCFEFWf15AZgwoQJTJgwodh9mzZtKrKtQ4cO/PXXX+UcVdWQnZvN57s/560tb5GUobVS983sQNJ375IVdx/168OCH6Fz1RtgUgghhLgjlSK5EWVnVI0sO7SMKRumcObGGQCC7BuQ/tNsknYOQqdTePn/YOZMbYZuIYQQoqaQ5KYK+uP0H7z6x6vsTdgLgJ9zALVPzGTfwrFgtKVJE1i4EEqYnksIIYSotiS5qUJiEmN49Y9XWRe7DgA3ezd6ubzK+rdeZN8VF2xt4fWp8PrrUEzvdyGEEKJGkOSmCjh74yxTN0zl24PfAmCns+Oxhs9w7uupLP+lFgCtWmm1NVFR1oxUCCGEsD5JbiqxqxlXeXvL23yy6xNyDDkAPNLkUZpceot3x4WTmqrV0MyYAZMmga3cTSGEEEKSm8rIYDTw2e7PmLphKsnZ2iSWPcJ7MKHBv/j3a61YulEr16GDVlvTsKEVgxVCCCEqGUluKpkDlw7w1C9PsfPiTgBaBLTgnfv/xfHVvXi0K2RmgrMzvPMOTJgAxUyELoQQQtRoktxUEpn6TGZtnsV7298j15iLu4M7c7rPobPLP3lyjI4dO7Ry3brBF19AeLh14xVCCCEqK0luKoH1p9fzz1//Sez1WACGNBrCvF4f8c1nQbSaATk52sjC778PTzwBimLVcIUQQohKTZIbK0rKSGLSukn8b///AKjtVptP+n7CwIYDmTULpk3TyvXtC//5D9SpY8VghRBCiCpCkhsrUFWVbw9+y0trXyIpIwkFhfFtx/N297dxd3Dn6lV47z2t7IcfwgsvSG2NEEIIUVqS3FSw09dP8/SvTxN9OhqApn5N+WLAF9xT5x5TmblzITUVmjeH55+XxEYIIYQoC0luKojeoOfDvz5kxqYZZOZm4mDjwPQu05l07yTsbOxM5S5fhvnztdezZkGhCdGFEEIIUQqS3FSAXRd38eQvT7L/0n4AuoV14/N+nxPhE1Gk7Jw5kJEBbdvCgAEVHakQQghR9UlyU45Ss1N5Y+MbfPT3RxhVIz5OPnzQ+wNGNh+JUsyzposX4bPPtNezZsnjKCGEEOJOSHJTTn498SvP/vYs51POAzCy+Uje7/U+tVxq3fKYd96BrCzo2BF69aqoSIUQQojqRZIbC7umv8ajKx5l+bHlAIR7hfN5v8/pWa9nicedO6cNzgfw1ltSayOEEELcKUluLMSoGvly35dMOjqJDGMGNooNk+6dxLQu03C2c77t8W+9BXq9NgJx167lH68QQghRXUlyYyEbz2zk2d+fBaBNYBu++McXtAhoUapjT52CRYu017NmlVOAQgghRA0hyY2FdAvrxvCmw3G67sTHIz/G0cGx1Me++SYYDNCnD9x7bzkGKYQQQtQAMoqKhSiKwuJ/LGZArQHY6Eo/VffRo/DNN9rrN98sp+CEEEKIGkSSGyubMQNUFQYNgjZtrB2NEEIIUfVJcmNFBw7A999rr2fOtG4sQgghRHUhyY0V5c/6PWyYNo+UEEIIIe6eJDdWsns3/PSTNnfUjBnWjkYIIYSoPiS5sZI33tC+PvYYNGxo3ViEEEKI6kSSGyvYtg3WrAEbm4JHU0IIIYSwDElurCC/1ubxx6FePevGIoQQQlQ3ktxUsI0btcXeviDJEUIIIYTlSHJTgVS1IKF58kmoW9e68QghhBDVkSQ3FWjtWq29jaMjvP66taMRQgghqidJbipI4VqbZ5+FoCDrxiOEEEJUV5LcVJCff9bGtnFxgVdftXY0QgghRPUlyU0FMBoLunw//zz4+Vk3HiGEEKI6k+SmAixfrs0j5e4OkyZZOxohhBCiepPkppwZDDB9uvZ64kTw9rZuPEIIIUR1J8lNOfvuOzh6VEtqXnzR2tEIIYQQ1Z8kN+VIry+YFPP//g88PKwajhBCCFEjSHJTjr76CmJjoVYtmDDB2tEIIYQQNYMkN+UkOxvefFN7PXkyuLpaNx4hhBCippDkppwsWABxcdpgfU8/be1ohBBCiJpDkptykJkJb7+tvZ4yBZycrBuPEEIIUZNUiuTmk08+ITQ0FEdHR9q3b8/ff/9dquOWLl2KoigMGjSofAMso//+V0d8vDYx5rhx1o5GCCGEqFmsntwsW7aMiRMnMn36dPbu3UtUVBS9e/fm8uXLJR539uxZJk2aRKdOnSoo0tLJzLThvfe0t3XaNHBwsHJAQgghRA1j9eTmgw8+4Mknn+Txxx+ncePGfP755zg7O7Nw4cJbHmMwGBgxYgQzZ84kPDy8AqO9vdWrw7l8WaFePRg1ytrRCCGEEDWPrTUvnpOTw549e5g8ebJpm06no0ePHuzYseOWx7355pv4+fkxbtw4tmzZUuI1srOzyc7ONq2npKQAoNfr0ev1d/kdmLt6Vc+qVfUBmDo1F1Cx8CVEKeTfV0vfX1E2ch8qB7kPlYPch7tXlvfOqslNUlISBoMBf39/s+3+/v4cO3as2GO2bt3KggULiImJKdU1Zs+ezcyZM4tsX7duHc7OzmWOuSTLlkWSmtqIOnVScXffwOrVFj29KKPo6GhrhyCQ+1BZyH2oHOQ+3LmMjIxSl7VqclNWqampjBw5ki+++AJfX99SHTN58mQmTpxoWk9JSSE4OJhevXrh7u5usdiuXYNRo7S385137BkwoK/Fzi3KRq/XEx0dTc+ePbGzs7N2ODWW3IfKQe5D5SD34e7lP3kpDasmN76+vtjY2HDp0iWz7ZcuXSIgIKBI+djYWM6ePcuAAQNM24xGIwC2trYcP36cevXqmR3j4OCAQzGteu3s7Cz6A5aQAH5+Kt7eyQwd6iw/vJWApe+xuDNyHyoHuQ+Vg9yHO1eW982qDYrt7e1p3bo169evN20zGo2sX7+eDh06FCnfsGFDDh48SExMjGn5xz/+wf33309MTAzBwcEVGb6ZFi3gwIFcpkzZic7qzbSFEEKImsvqj6UmTpzI6NGjadOmDe3atWPevHmkp6fz+OOPAzBq1Chq167N7NmzcXR0pGnTpmbHe3p6AhTZbg22tlCrVqa1wxBCCCFqNKsnN8OGDePKlStMmzaNxMREWrRowZo1a0yNjOPi4tBJVYgQQgghSsnqyQ3AhAkTmHCLabM3bdpU4rGLFy+2fEBCCCGEqLKkSkQIIYQQ1YokN0IIIYSoViS5EUIIIUS1IsmNEEIIIaoVSW6EEEIIUa1IciOEEEKIakWSGyGEEEJUK5LcCCGEEKJakeRGCCGEENWKJDdCCCGEqFYkuRFCCCFEtVIp5paqSKqqApCSkmLxc+v1ejIyMkhJScHOzs7i5xelI/ehcpD7UDnIfagc5D7cvfzP7fzP8ZLUuOQmNTUVgODgYCtHIoQQQoiySk1NxcPDo8QyilqaFKgaMRqNxMfH4+bmhqIoFj13SkoKwcHBnD9/Hnd3d4ueW5Se3IfKQe5D5SD3oXKQ+3D3VFUlNTWVoKAgdLqSW9XUuJobnU5HnTp1yvUa7u7u8sNbCch9qBzkPlQOch8qB7kPd+d2NTb5pEGxEEIIIaoVSW6EEEIIUa1IcmNBDg4OTJ8+HQcHB2uHUqPJfagc5D5UDnIfKge5DxWrxjUoFkIIIUT1JjU3QgghhKhWJLkRQgghRLUiyY0QQgghqhVJboQQQghRrUhyYyGffPIJoaGhODo60r59e/7++29rh1TjzJgxA0VRzJaGDRtaO6xqb/PmzQwYMICgoCAURWHVqlVm+1VVZdq0aQQGBuLk5ESPHj04efKkdYKtxm53H8aMGVPk9+OBBx6wTrDV1OzZs2nbti1ubm74+fkxaNAgjh8/blYmKyuL8ePH4+Pjg6urKw8++CCXLl2yUsTVlyQ3FrBs2TImTpzI9OnT2bt3L1FRUfTu3ZvLly9bO7Qap0mTJiQkJJiWrVu3Wjukai89PZ2oqCg++eSTYve/++67zJ8/n88//5ydO3fi4uJC7969ycrKquBIq7fb3QeABx54wOz347vvvqvACKu/P//8k/Hjx/PXX38RHR2NXq+nV69epKenm8q89NJL/PLLL/zwww/8+eefxMfHM2TIECtGXU2p4q61a9dOHT9+vGndYDCoQUFB6uzZs60YVc0zffp0NSoqytph1GiAunLlStO60WhUAwIC1Pfee8+07caNG6qDg4P63XffWSHCmuHm+6Cqqjp69Gh14MCBVomnprp8+bIKqH/++aeqqtrPvp2dnfrDDz+Yyhw9elQF1B07dlgrzGpJam7uUk5ODnv27KFHjx6mbTqdjh49erBjxw4rRlYznTx5kqCgIMLDwxkxYgRxcXHWDqlGO3PmDImJiWa/Hx4eHrRv315+P6xg06ZN+Pn50aBBA5555hmuXr1q7ZCqteTkZAC8vb0B2LNnD3q93uz3oWHDhtStW1d+HyxMkpu7lJSUhMFgwN/f32y7v78/iYmJVoqqZmrfvj2LFy9mzZo1fPbZZ5w5c4ZOnTqRmppq7dBqrPzfAfn9sL4HHniAr776ivXr1/Ovf/2LP//8kz59+mAwGKwdWrVkNBp58cUX6dixI02bNgW03wd7e3s8PT3Nysrvg+XVuFnBRfXVp08f0+vmzZvTvn17QkJC+P777xk3bpwVIxPC+h555BHT62bNmtG8eXPq1avHpk2b6N69uxUjq57Gjx/PoUOHpN2flUjNzV3y9fXFxsamSGv3S5cuERAQYKWoBICnpyeRkZGcOnXK2qHUWPm/A/L7UfmEh4fj6+srvx/lYMKECfz6669s3LiROnXqmLYHBASQk5PDjRs3zMrL74PlSXJzl+zt7WndujXr1683bTMajaxfv54OHTpYMTKRlpZGbGwsgYGB1g6lxgoLCyMgIMDs9yMlJYWdO3fK74eVXbhwgav/397dhES1BmAcf442DjODykyWjoFmKGJBLTJrqE0JqUGgTGQxxBSRmDoUIm1qUKG2FbQYCMpVH2BgCVFBHytBaqO5sIEiaGFDdds008fG9y6CgUP3xr0X9ei5/x8cmHPeM/q8Dgcezwfzxx8cHwvIGKO+vj6NjY3p6dOnqqmpsY1v3bpVHo/Hdjyk02m9e/eO42GBcVlqAfT39ysej6uxsVFNTU26fPmycrmcjh075nS0/5WBgQHt379f1dXVmpub0+DgoAoLC3X48GGno7laNpu1/ff/9u1bTU1NKRQKqaqqSqdPn9b58+dVV1enmpoaJZNJVVZWqr293bnQLvS7zyEUCml4eFjRaFQVFRV68+aNzpw5o9raWrW0tDiY2l16e3t18+ZN3bt3T8XFxfn7aEpLS+Xz+VRaWqrjx4+rv79foVBIJSUlSiQSikQi2rFjh8PpXcbpx7Xc4sqVK6aqqsoUFRWZpqYmMzk56XSk/53Ozk4TDodNUVGRWbdunens7DSvX792OpbrPXv2zEj6ZYnH48aYn4+DJ5NJU15ebrxer2lubjbpdNrZ0C70u8/h69evZu/evWbNmjXG4/GY6upqc+LECZPJZJyO7Sp/9feXZEZGRvL7fPv2zfT09JhgMGj8fr/p6Ogw79+/dy60S1nGGLP0lQoAAGBxcM8NAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAEiyLEt37951OgaABUC5AeC4o0ePyrKsX5bW1lanowFYgfjiTADLQmtrq0ZGRmzbvF6vQ2kArGScuQGwLHi9XlVUVNiWYDAo6eclo1Qqpba2Nvl8Pm3YsEF37tyxvX9mZkZ79uyRz+fT6tWr1dXVpWw2a9vn+vXr2rRpk7xer8LhsPr6+mzjnz59UkdHh/x+v+rq6jQ+Pr64kwawKCg3AFaEZDKpaDSq6elpxWIxHTp0SLOzs5KkXC6nlpYWBYNBvXjxQqOjo3r8+LGtvKRSKfX29qqrq0szMzMaHx9XbW2t7XcMDw/r4MGDevnypfbt26dYLKbPnz8v6TwBLACnv5YcAOLxuCksLDSBQMC2XLhwwRhjjCTT3d1te8/27dvNyZMnjTHGXL161QSDQZPNZvPj9+/fNwUFBSaTyRhjjKmsrDRnz5792wySzLlz5/Lr2WzWSDIPHjxYsHkCWBrccwNgWdi9e7dSqZRtWygUyr+ORCK2sUgkoqmpKUnS7OystmzZokAgkB/fuXOn5ufnlU6nZVmW5ubm1Nzc/NsMmzdvzr8OBAIqKSnRhw8f/uuUADiEcgNgWQgEAr9cJlooPp/vH+3n8Xhs65ZlaX5+fjEiAVhE3HMDYEWYnJz8Zb2hoUGS1NDQoOnpaeVyufz4xMSECgoKVF9fr+LiYq1fv15PnjxZ0swAnMGZGwDLwo8fP5TJZGzbVq1apbKyMknS6OioGhsbtWvXLt24cUPPnz/XtWvXJEmxWEyDg4OKx+MaGhrSx48flUgkdOTIEZWXl0uShoaG1N3drbVr16qtrU1fvnzRxMSEEonE0k4UwKKj3ABYFh4+fKhwOGzbVl9fr1evXkn6+STT7du31dPTo3A4rFu3bmnjxo2SJL/fr0ePHunUqVPatm2b/H6/otGoLl68mP9Z8Xhc379/16VLlzQwMKCysjIdOHBg6SYIYMlYxhjjdAgA+B3LsjQ2Nqb29nanowBYAbjnBgAAuArlBgAAuAr33ABY9rh6DuDf4MwNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwFcoNAABwlT8B6LPcmH9/RvIAAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.9017 - accuracy: 0.6924 - 335ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 771us/step\n",
            "\u001b[35mTest Accuracy: 0.69\u001b[0m\n",
            "\u001b[34mTest Loss: 0.9\u001b[0m\n",
            "\u001b[33mTest Precision: 0.7\u001b[0m\n",
            "\u001b[32mTest Recall: 0.69\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.69\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "#Define Model with modified dense layers (Adding the number of neurons)\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(128, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 941
        },
        "id": "evHmqALyznab",
        "outputId": "2e1b21c6-5704-4ebd-e918-a78b20a4b7a2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_50\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_114 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_82 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_115 (Conv2D)         (None, 13, 13, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_83 (MaxPoolin  (None, 6, 6, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " conv2d_116 (Conv2D)         (None, 4, 4, 64)          36928     \n",
            "                                                                 \n",
            " flatten_50 (Flatten)        (None, 1024)              0         \n",
            "                                                                 \n",
            " dense_105 (Dense)           (None, 64)                65600     \n",
            "                                                                 \n",
            " dense_106 (Dense)           (None, 32)                2080      \n",
            "                                                                 \n",
            " dense_107 (Dense)           (None, 16)                528       \n",
            "                                                                 \n",
            " dense_108 (Dense)           (None, 10)                170       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 124,698\n",
            "Trainable params: 124,698\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 34.24s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 0.8742 - accuracy: 0.6984 - 378ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 844us/step\n",
            "\u001b[35mTest Accuracy: 0.7\u001b[0m\n",
            "\u001b[34mTest Loss: 0.87\u001b[0m\n",
            "\u001b[33mTest Precision: 0.7\u001b[0m\n",
            "\u001b[32mTest Recall: 0.7\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.7\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Defining Model with modified dense layers (Adding extra layers)\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "# These contian the 'classification' part of the model.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.Dense(32, activation='relu'))\n",
        "model.add(layers.Dense(16, activation='relu'))\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0)\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YaW0c6hev27E"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BNmce5z7v27E"
      },
      "source": [
        "* The best model was the one with 3 Dense Layers, this is because the model can learn more complex features.\n",
        "* The model with 3 Dense Layers has a higher accuracy, precision, recall and F1-Score than the model with 1 Dense Layer, whilst respectively incurring a lower loss.\n",
        "* Increasing the number of neurons in the Dense Layer from 64 to 128, reduced the performance of the model, this is because the model is overfitting.\n",
        "* Decreasing the number of neurons in the Dense Layer from 64 to 32, decreased the performance of the model, ensuring that the model is not overfitting."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "gtB_8yxMv27F"
      },
      "source": [
        "### Q.6\n",
        "In a Neural Network, the optimizer is the heuristic function used to 'push' the model down the right path. Compare two versions of an architecture of your choice that use different optimizers. This can be done by setting the <code>optimizer</code> parameter in the <code>fit</code> function (eg. <code>optimizer='sgd'</code>)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "id": "UireQmR8v27F"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.gradient_descent.SGD object at 0x000001E7EB22E5B0> optimizer\u001b[0m\n",
            "Model: \"sequential_51\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_117 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_84 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_51 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_109 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_110 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "None\n",
            "\u001b[36mTraining Time: 60.43s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.1301 - accuracy: 0.6051 - 305ms/epoch - 975us/step\n",
            "313/313 [==============================] - 0s 655us/step\n",
            "\u001b[35mTest Accuracy: 0.61\u001b[0m\n",
            "\u001b[34mTest Loss: 1.13\u001b[0m\n",
            "\u001b[33mTest Precision: 0.6\u001b[0m\n",
            "\u001b[32mTest Recall: 0.61\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.6\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.rmsprop.RMSprop object at 0x000001E7EB22E040> optimizer\u001b[0m\n",
            "Model: \"sequential_52\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_118 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_85 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_52 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_111 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_112 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 13.82s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0309 - accuracy: 0.6442 - 302ms/epoch - 966us/step\n",
            "313/313 [==============================] - 0s 635us/step\n",
            "\u001b[35mTest Accuracy: 0.64\u001b[0m\n",
            "\u001b[34mTest Loss: 1.03\u001b[0m\n",
            "\u001b[33mTest Precision: 0.65\u001b[0m\n",
            "\u001b[32mTest Recall: 0.64\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.64\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.adagrad.Adagrad object at 0x000001E7EB22EBB0> optimizer\u001b[0m\n",
            "Model: \"sequential_53\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_119 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_86 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_53 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_113 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_114 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 72.77s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.4720 - accuracy: 0.4850 - 309ms/epoch - 988us/step\n",
            "313/313 [==============================] - 0s 664us/step\n",
            "\u001b[35mTest Accuracy: 0.49\u001b[0m\n",
            "\u001b[34mTest Loss: 1.47\u001b[0m\n",
            "\u001b[33mTest Precision: 0.48\u001b[0m\n",
            "\u001b[32mTest Recall: 0.48\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.48\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.adadelta.Adadelta object at 0x000001E4B6F1C4C0> optimizer\u001b[0m\n",
            "Model: \"sequential_54\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_120 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_87 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_54 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_115 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_116 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 74.46s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.8289 - accuracy: 0.3752 - 318ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 703us/step\n",
            "\u001b[35mTest Accuracy: 0.38\u001b[0m\n",
            "\u001b[34mTest Loss: 1.83\u001b[0m\n",
            "\u001b[33mTest Precision: 0.37\u001b[0m\n",
            "\u001b[32mTest Recall: 0.38\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.36\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.adam.Adam object at 0x000001E4B6F1C640> optimizer\u001b[0m\n",
            "Model: \"sequential_55\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_121 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_88 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_55 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_117 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_118 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 13.84s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0079 - accuracy: 0.6520 - 316ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 674us/step\n",
            "\u001b[35mTest Accuracy: 0.65\u001b[0m\n",
            "\u001b[34mTest Loss: 1.01\u001b[0m\n",
            "\u001b[33mTest Precision: 0.65\u001b[0m\n",
            "\u001b[32mTest Recall: 0.65\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.65\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.adamax.Adamax object at 0x000001E4B6F1C5B0> optimizer\u001b[0m\n",
            "Model: \"sequential_56\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_122 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_89 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_56 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_119 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_120 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 19.2s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0212 - accuracy: 0.6442 - 306ms/epoch - 979us/step\n",
            "313/313 [==============================] - 0s 641us/step\n",
            "\u001b[35mTest Accuracy: 0.64\u001b[0m\n",
            "\u001b[34mTest Loss: 1.02\u001b[0m\n",
            "\u001b[33mTest Precision: 0.64\u001b[0m\n",
            "\u001b[32mTest Recall: 0.64\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.64\u001b[0m\n",
            "\u001b[36mTesting <keras.optimizers.optimizer_v2.nadam.Nadam object at 0x000001E4B6F1CFA0> optimizer\u001b[0m\n",
            "Model: \"sequential_57\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_123 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " max_pooling2d_90 (MaxPoolin  (None, 15, 15, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten_57 (Flatten)        (None, 7200)              0         \n",
            "                                                                 \n",
            " dense_121 (Dense)           (None, 64)                460864    \n",
            "                                                                 \n",
            " dense_122 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 462,410\n",
            "Trainable params: 462,410\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 26.56s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACW6ElEQVR4nOzdd1gUV9vA4d8uvQuIFEVAwY5gb7EXrIlJjCaaqFFT3miaSUyMSdT0zyRqenlfS5rRFDUmscTYu7FgbyCKSlFUelt25/tjZGEBEXRhKc99XXOxM3Nm9uxhYZ89VaMoioIQQgghRA2htXQGhBBCCCHMSYIbIYQQQtQoEtwIIYQQokaR4EYIIYQQNYoEN0IIIYSoUSS4EUIIIUSNIsGNEEIIIWoUa0tnoLIZDAbi4uJwcXFBo9FYOjtCCCGEKANFUUhLS8PPzw+ttvS6mVoX3MTFxeHv72/pbAghhBDiNly4cIEGDRqUmqbWBTcuLi6AWjiurq5mvbdOp+Pvv/9mwIAB2NjYmPXetY2UpXlJeZqPlKV5SXmaT00vy9TUVPz9/Y2f46WpdcFNflOUq6trhQQ3jo6OuLq61sg3VmWSsjQvKU/zkbI0LylP86ktZVmWLiXSoVgIIYQQNYoEN0IIIYSoUSS4EUIIIUSNUuv63AghRHVmMBjIzc21dDbMRqfTYW1tTXZ2Nnq93tLZqdZqQlna2trecph3WUhwI4QQ1URubi4xMTEYDAZLZ8VsFEXBx8eHCxcuyNxjd6gmlKVWqyUoKAhbW9s7uo8EN0IIUQ0oikJ8fDxWVlb4+/ub5dttVWAwGEhPT8fZ2bnGvCZLqe5lmT/Jbnx8PA0bNryjAE2CGyGEqAby8vLIzMzEz88PR0dHS2fHbPKb2ezt7avlB3JVUhPK0svLi7i4OPLy8u5oOHv1fPVCCFHL5PehuNPqeiGqsvz39532GZLgRgghqpHq2pdCiLIw1/tbghshhBBC1CgS3AghhBCiRpHgRgghRLUSGBjI/PnzLZ0NUYVJcCOEEKJCaDSaUrdZs2bd1n3//fdfHn/8cbPk8aeffsLKyorJkyeb5X6iapDgxoz0Oj2Z0ZkoimLprAghhMXFx8cbt/nz5+Pq6mpy7MUXXzSmVRSFvLy8Mt3Xy8vLbMPhFyxYwLRp0/jpp5/Izs42yz1vV02aedrSJLgxE0Oegfl+8zn9wmmSY5ItnR0hRA2nKJCRYZmtrN/ffHx8jJubmxsajca4f/LkSVxcXFizZg29evXCwcGB7du3Ex0dzT333IO3tzfOzs506NCBf/75x+S+RZulNBoN//vf/7j33ntxdHQkJCSEVatW3TJ/MTEx7Ny5k1deeYUmTZqwfPnyYmkWLlxIy5YtsbOzw9fXlylTphjPJScn88QTT+Dt7Y29vT2tWrXizz//BGDWrFmEh4eb3Gv+/PkEBgYa98ePH8/w4cN555138PPzo2nTpgB8//33tG/fHhcXF3x8fBg9ejSXL182udexY8cYOnQorq6uuLi40L17d6Kjo9mxYwd2dnYkJCSYpH/uuefo3r37LcukppDgxky01lo8m3gCEPdvnIVzI4So6TIzwdnZMltmpvlex6uvvsrMmTM5duwYrVu3Jj09ncGDB7NhwwYOHjzIwIEDGTZsGLGxsaXeZ/bs2YwcOZLDhw8zePBgxowZw7Vr10q9ZtGiRQwZMgQ3NzcefvhhFixYYHL+yy+/ZPLkyTz++OMcOXKEVatWERwcDKgT5g0aNIgdO3bwww8/cPz4cd5//32srKzK9fo3bNjAqVOnWL9+vTEw0ul0vPXWWxw6dIiVK1dy7tw5xo8fb7zm0qVL9OjRAzs7OzZu3Mj+/fuZMGECeXl5dOvWjUaNGvH9998b0+t0On788UcmTJhQrrxVa0otk5KSogBKSkqK2e/9x3/+UGYxS1n97Gqz37u2yc3NVVauXKnk5uZaOis1gpSn+ViqLLOyspTjx48rWVlZiqIoSnq6oqh1KJW/paeXP/+LFi1S3NzcjPubNm1SAGX58uXK9evXFb1ef9NrW7ZsqXz66afG/YCAAGXevHnGfUB57bXXjPvp6ekKoKxZs+am99Tr9Yq/v7+ycuVKRVEU5cqVK4qtra1y9uxZYxo/Pz9lxowZJV6/bt06RavVKqdOnSrx/MyZM5WwsDCTY/PmzVMCAgKM++PGjVO8vb2VnJycm+ZTURTl33//VQAlLS1NURRFmT59uhIUFFTsPajX65Xr168r77//vtK8eXPj8d9++01xdnZW0m/nF1fJir7PCyvP57fU3JiRX3s/AOL2Sc2NEKJiOTpCerplNnOu/tC+fXuT/fT0dF588UWaN29OnTp1cHZ25sSJE7esuWndurXxsZOTE66ursWacgpbv349GRkZDB48GIC6devSv39/Fi5cCMDly5eJi4ujb9++JV4fGRlJgwYNaNKkSZle582EhoYWm3V6//79DBs2jIYNG+Li4kLPnj0BjGUQGRlJ9+7db7o8wbhx44iKimL37t0ALF68mJEjR+Lk5HRHea1OZG0pM/Lt4AtAwoEEDHkGtNYSOwohKoZGAzXhs6roB+6LL77I+vXr+fDDDwkODsbBwYERI0bcsrNt0Q96jUZT6urpCxYs4Nq1azg4OBiPGQwGDh8+zOzZs02Ol+RW57VabbHBJTqdrli6oq8/IyODiIgIIiIi+PHHH/Hy8iI2NpaIiAhjGdzquevVq8ewYcNYtGgRQUFBrFmzhs2bN5d6TU0jwY0ZeTbxROuoJS8zj8vHLuMT5mPpLAkhRLWyY8cOxo8fz7333guoNTnnzp0z63NcvXqV33//naVLl9KyZUvjcb1ez1133cXff//NwIEDCQwMZMOGDfTu3bvYPVq3bs3Fixc5ffp0ibU3Xl5eJCQkoCiKcUmByMjIW+bt5MmTXL16lffffx9/f38A9u3bV+y5v/32W3Q63U1rbyZNmsRDDz1EgwYNaNy4Md26dbvlc9ckUrVgRhqtBsfGan2tdCoWQojyCwkJYfny5URGRnLo0CFGjx5dag3M7fj+++/x9PRk5MiRtGrVyriFhYUxePBgY8fiWbNm8dFHH/HJJ59w5swZDhw4wKeffgpAz5496dGjB/fffz/r168nJiaGNWvWsHbtWgB69erFlStXmDNnDtHR0Xz++eesWbPmlnlr2LAhtra2fPrpp5w9e5ZVq1bx1ltvmaSZMmUKqampPPjgg+zbt48zZ87w/fffc+rUKWOaiIgIXF1defvtt3n00UfNVXTVhgQ3ZubRz4Neb/WiQZcGls6KEEJUO3PnzsXd3Z2uXbsybNgwIiIiaNu2rVmfY+HChdx7770lLtJ4//33s2rVKpKSkhg3bhzz58/niy++oGXLlgwdOpQzZ84Y0/7222906NCBhx56iBYtWjBt2jTjatbNmzfniy++4PPPPycsLIy9e/eazOtzM15eXixevJhffvmFFi1a8P777/Phhx+apPH09GTjxo2kp6fTs2dP2rVrx3//+1+TWhytVsv48ePR6/WMHTv2douq2tIoRRsFa7jU1FTc3NxISUnB1dXVrPfW6XSsXr2awYMH37SqUJSNlKV5SXmaj6XKMjs7m5iYGIKCgrC3t6+0561oBoOB1NRUXF1d0Wrl+/adKFqWEydO5MqVK2Wa86eqKO19Xp7Pb+lzI4QQQtQgKSkpHDt2jCVLllSrwMacJLipACmxKSTuT8SvvR/ujdwtnR0hhBC1yL333svevXt58skn6d+/v6WzYxES3FSAv5/7mzN/nmHA3AF0eb6LpbMjhBCiFtm4cWOtb+Kr3a++gvh1uDGZn4yYEkIIISqdBDcVID+4ubT3koVzIoQQQtQ+EtxUAJ926uR916Ovk3nVjCvMCSGEEOKWJLipAA7uDrJCuBBCCGEhEtxUEGmaEkIIISxDgpsKUr9jfUCCGyGEMLfAwEDmz59v6WyIKkyGgleQJsOa4OzjTP1O9S2dFSGEsIiSljcobObMmbzxxhvlvu+///5bbDXt8urVqxfh4eESJNVQEtxUEPcgd9yDZAI/IUTtFR8fb3y8bNky3njjDZPFHZ2dnY2PFUUhLy8Pa+tbfyx5eXmZN6OixpFmKSGEEBXCx8fHuLm5uaHRaIz7J0+exMXFhTVr1tCrVy8cHBzYvn070dHR3HPPPXh7e+Ps7EyHDh34559/TO5btFlKo9Hwv//9j3vvvRdHR0dCQkLueNmB3377jZYtW2JnZ0dgYCAfffSRyfkvvviCkJAQ7O3t8fb2ZsSIEcZzv/76K6GhoTg4OODp6Um/fv3IyMi4o/yI8rFocLN161aGDRuGn58fGo2GlStX3vKanJwcZsyYQUBAgPFNt3DhworP7G24cuIK29/fzqHvDlk6K0KIGio3I/emW152XpnT6rJ0ZUprbq+++iozZ87k2LFjtG7dmvT0dAYPHsyGDRs4ePAgAwcOZNiwYcTGxpZ6n9mzZzNy5EgOHz7M4MGDGTNmDNeuXbutPO3fv5+RI0fy4IMPcuTIEWbNmsXrr7/O4sWLAdi3bx/PPPMMb775JqdOnWLt2rX06NEDUGurHnroISZMmMCJEyfYvHkz9913H7VsjWqLs2izVEZGBmFhYUyYMIH77ruvTNeMHDmSxMREFixYQHBwMPHx8RgMhgrO6e25uPsiG6ZvIKBnAGFjwyydHSFEDfSe83s3PRcyOITRf4027n9Y70N0mboS0wb0DGD85vHG/Y8DPyYzqfg8XTOVmbef2RLMmjWL3r17G1ey9vDwICys4P/lW2+9xYoVK1i1ahVTpky56X3Gjx/PQw89BMC7777LJ598wt69exk4cGC58zR37lz69u3L66+/DkCTJk04fvw4H3zwAePHjyc2NhYnJyeGDh2Ki4sLAQEBtGnTBlCDm7y8PO677z4CAgIACA0NLXcexJ2xaHAzaNAgBg0aVOb0a9euZcuWLZw9exYPDw9ArZ6squp3UDsTx+2Lw6A3oLWSVkAhhCisffv2Jvvp6enMmjWLv/76yxgoZGVl3bLmpnXr1sbHTk5OuLq6cvny5dvK04kTJ7jnnntMjnXr1o358+ej1+vp378/AQEBNGrUiIEDBzJw4EBjk1hYWBh9+/YlNDSUiIgIBgwYwIgRI3B3lz6YlaladShetWoV7du3Z86cOXz//fc4OTlx991389Zbb+Hg4FDiNTk5OeTk5Bj3U1NTAdDpdOh0JX+DuV3598v/6Rbsho2TDboMHQlHEvBqKZ3gyqpoWYo7I+VpPpYqS51Oh6IoGAwGk9rql1Nfvuk1WiutSdqpCVNvmlaj1Zikffrs0yWmu92a8vzriv50dHQEML62F154gX/++Yc5c+YQHByMg4MDI0eOJCcnx+S589Pns7KyMtnXaDTk5eWVmt+i9yjtXOF8Ozk5sW/fPjZv3sz69et54403mDVrFnv27KFOnTqsW7eOnTt3sn79ej799FNmzJjBrl27CAoKKleZlVd+01dpr6uqMxgMKIqCTqfDysrK5Fx5/uaqVXBz9uxZtm/fjr29PStWrCApKYmnnnqKq1evsmjRohKvee+995g9e3ax43///bfxj8rc1q9fb3xsG2iL7piOtQvX4tnXs0KeryYrXJbizkl5mk9ll6W1tTU+Pj6kp6eTm1vGvi96oKzdZPSQpcu6ZbLs1Owy3rDIddnZKIpi/IKZmak2eaWnp+Pm5kZaWhoA27Zt48EHH6Rv377G8zExMXTp0sV4rcFgIDs727gPkJWVZbKvKEqxNIXl5eWRm5tb4vnGjRuzdetWk3ObNm2icePGJh2DO3bsSMeOHXnuuecIDAzkr7/+YtiwYYDaFBUaGsqzzz5L69atWbp0KZMnTy5/wd2G/LKsjnJzc8nKymLr1q3k5Zn2Gct/z5RFtQpuDAYDGo2GH3/8ETc3N0BtGx0xYgRffPFFibU306dPZ+rUgm8rqamp+Pv7M2DAAFxdXc2aP51Ox/r16+nfvz82NjYAbNi6gT3H9lA3py6DBpe9Ca62K6ksxe2T8jQfS5VldnY2Fy5cwNnZGXt7+0p7XnOxt7dHo9EY/+/mf7nMHw7u4uKCRqOhadOmrF69mvvvvx+NRsMbb7yBoijY2toar9Vqtdjb25v8D3dwcDDZ12g0xdIUZm1tTUpKCmfPnjU57uvry8svv0ynTp345JNPGDlyJLt27eJ///sfn332Ga6urvz555/ExMTQvXt33N3dWb16NQaDgfDwcE6cOMHGjRvp378/9erVY8+ePSQlJREeHm72z5yiFEUhLS3NWJbVUXZ2Ng4ODvTo0aPY+/xmgWpJqlVw4+vrS/369Y2BDUDz5s1RFIWLFy8SEhJS7Bo7Ozvs7OyKHbexsamwf0yF7+3f2Z897CFhf4J8qNyGivw91UZSnuZT2WWp1+vRaDRotVq02urXfy8/z0V/5n8I57+2efPmMWHCBO666y7q1q3Lyy+/TFpamvF8vqL7JZXLrcrqp59+4qeffjI59tZbb/Haa6/x888/88Ybb/D222/j6+vLm2++yYQJEwDw8PBg7ty5zJ49m+zsbEJCQvjpp58IDQ3lxIkTbNu2jY8//pjU1FQCAgL46KOPGDJkyO0WXZnlN0UVLZvqRKvVotFoSvz7Ks/fW7UKbrp168Yvv/xCenq6Mdo/ffo0Wq2WBg0aWDh3JctfhuHq6avodXqsbKxucYUQQtQ848ePZ/z48cb9Xr16GfuGFP5GHhgYyMaNG02uLdqcc+7cOZP9koZZJycnl5qfzZs3l3r+/vvv5/777y/x3F133XXT65s3b87atWtLvbeoeBYN7dLT04mMjCQyMhKAmJgYIiMjjb3ip0+fztixY43pR48ejaenJ48++ijHjx9n69atvPTSS0yYMOGmHYotza2hG48feJxpV6dJYCOEEEJUAosGN/v27aNNmzbG+QGmTp1KmzZtjGuNxMfHmwz/c3Z2Zv369SQnJ9O+fXvGjBnDsGHD+OSTTyyS/7LQaDT4tvGVwEYIIYSoJBZtlsqvlryZ/NkgC2vWrJmM+BBCCCHETVXPHkfVTOrFVFZNWsVPd/9068RCCCGEuCPVqkNxdWXtYM3BBQcByLqehYN71ewfJIQQQtQEUnNTCRw9HXFvrE69HbcvzsK5EUIIIWo2CW4qSf46U5f2XrJwToQQQoiaTYKbSuLX0Q+AuH+l5kYIIYSoSBLcVJL8yfwu7blU6ggxIYQQQtwZCW4qiW8bXzRWGtIT0km7VH0XNRNCiMrWq1cvnnvuOeN+YGAg8+fPL/UajUbDypUr7/i5zXUfUbkkuKkkNo42eId649nEk/SEdEtnRwghKtywYcMYOHBgiee2bduGRqPh8OHD5b7vv//+y+OPP36n2TMxa9YswsPDix2Pj49n0KDKWfQ4KysLDw8P6tatS05OTqU8Z00lQ8HNLNvq5jMRT9w9EWs7KXIhRO0wceJE7r//fi5evFhs/b9FixbRvn17WrduXa7VngG8vLzMmc1S+fj4VNpz/fbbb7Rs2RJFUVi5ciWjRo2qtOcuSlEU9Ho91tbV8zNLam7M6DWtlkcjIth/k6XmJbARQtQmQ4cOxcvLq9hs8+np6fzyyy9MnDiRq1evMnHiRPz9/XF0dCQ0NLTYSt1FFW2WOnPmDD169MDe3p4WLVqUOIv9yy+/TJMmTXB0dKRRo0a8/vrr6HQ6QJ0Nf/bs2Rw6dAiNRoNGozHmuWiz1JEjR+jTpw8ODg54enry+OOPk55eUBs/fvx4hg8fzocffoivry+enp5MnjzZ+FylWbBgAQ8//DAPP/wwCxYsKHb+2LFjDB06FFdXV1xcXOjevTvR0dHG8wsXLqRLly44ODjg6+vLlClTAHWhUY1GY1zHEdSFRTUajXEB0M2bN6PRaFizZg3t2rXDzs6O7du3Ex0dzT333IO3tzfOzs506NCBf/75xyRfOTk5vPzyy/j7+2NnZ0dwcDALFixAURSCg4P58MMPTdJHRkai0WiIioq6ZZncLvm0NaNLGg1ZNjZ8ZDDwSynpDHoDGq36BySEELdDURQydZkWeW5HG8cy/f+ytrZm7NixLF68mBkzZhiv+eWXX9Dr9Tz00EOkpqYSHh7OjBkzqFOnDn/99RePPPIIjRs3pmPHjrd8DoPBwH333Ye3tzd79uwhJSXFpH9OPhcXFxYvXoyfnx9Hjhzhsccew8XFhWnTpjFq1CiOHj3K2rVrjR/cbm5uxe6RkZFBREQEXbp04d9//+Xy5ctMmjSJKVOmmARwmzZtwtfXl02bNhEVFcWoUaMIDw/nscceu+nriI6OZteuXSxfvhxFUXj++ec5f/48AQEBAFy6dIkePXrQq1cvNm7ciKurKzt27CAvLw+AL7/8kqlTpzJz5kyGDx9OWloaO3bsuGX5FfXKK6/w4Ycf0qhRI9zd3blw4QKDBw/mnXfewc7Oju+++45hw4Zx6tQpGjZsCMDYsWPZtWsXn3zyCWFhYcTExJCUlIRGo2HChAksWrSIF1980fgcixYtokePHgQHB5c7f2UlwY0ZPa/X86NWy3KNhrNAoxLSLBmyhPNbz/PYv49Rt1ndys6iEKKGyNRl4vyes0WeO316Ok62TmVKO2HCBD744AO2bNlCr169APXD7f7778fNzQ0XFxeefvppXF1d0Wq1PP3006xbt46ff/65TMHNP//8w8mTJ1m3bh1+fuqUG++++26xfjKvvfaa8XFgYCAvvvgiS5cuZdq0aTg4OODs7Iy1tXWpzVBLliwhOzub7777Dicn9fV/9tlnDBs2jP/7v//D29sbAHd3dz777DOsrKxo1qwZQ4YMYcOGDaUGNwsXLmTQoEG4u6sTvkZERLBo0SJmzZoFwOeff46bmxtLly7FxsYGgCZNmhivf/vtt5k6dSpPPvmksSw7dOhwy/Ir6s0336R///7GfQ8PD8LCwoz7b731FitWrGDVqlVMmTKF06dP8/PPP7N+/Xr69esHQKNGBZ9+48eP54033mDv3r107NgRnU7HkiVLitXmmJs0S5lRa6BNYiIGjYb5N0mTk5pDbnquTOYnhKgVmjVrRteuXVm4cCEAUVFRbNu2jYkTJwKg1+v54IMPCAsLw8PDA2dnZ9atW0dsbGyZ7n/ixAn8/f2NgQ1Aly5diqVbtmwZ3bp1w8fHB2dnZ1577bUyP0fh5woLCzMGNgDdunXDYDBw6tQp47GWLVtiVaj/pa+vL5cvX77pffV6Pd9++y0PP/yw8djDDz/M4sWLMRgMgNqU0717d2NgU9jly5eJi4ujT58+5Xo9JWnfvr3Jfnp6Oi+++CLNmzenTp06ODs7c+LECWPZRUZGYmVlRc+ePUu8n5+fH0OGDDH+/v/44w9ycnJ44IEH7jivpZGaGzMbHhXFQW9vFgAzAc8i5/06+hG7PZZLey8RNjashDsIIcStOdo4kj7dMiMvHW0cy5V+4sSJPP3003z++ecsWrSIxo0bGz8MP/zwQ7766ivmzZtnDByee+45cnNzzZbfXbt2MWbMGGbPnk1ERISxBuSjjz4y23MUVjQA0Wg0xiClJOvWrePSpUvFOhDr9Xo2bNhA//79cXC4+ZqEpZ0D0GrVeozCc6zdrA9Q4cAN4MUXX2T9+vV8+OGHBAcH4+DgwIgRI4y/n1s9N8CkSZN45JFHmDdvHosWLWLUqFE4OpbvPVReUnNjZq2TkghTFDKBL0s4L8swCCHMQaPR4GTrZJGtvP0FR44ciVarZcmSJXz33XdMmDDBeI8dO3YwePBgHn74YcLCwmjUqBGnT58u872bN2/OhQsXiI+PNx7bvXu3SZqdO3cSEBDAjBkzaN++PSEhIZw/f94kja2tLXq9/pbPdejQITIyMozHduzYgVarpWnTpmXOc1ELFizgwQcfJDIy0mR78MEHjR2LW7duzbZt20oMSlxcXAgMDGTjxo0l3j9/dFnhMircubg0O3bsYPz48dx7772Ehobi4+PDuXPnjOdDQ0MxGAxs2bLlpvcYPHgwTk5OfPnll6xdu5YJEyaU6bnvhAQ3ZqYBpt74A/kSKPqnkj9TceKhRPJy8io1b0IIYQnOzs6MGjWK6dOnEx8fz/jx443nQkJC2LRpEzt37uTEiRM88cQTJCYmlvne/fr1o0mTJowbN45Dhw6xbds2ZsyYYZImJCSE2NhYli5dSnR0NJ988gkrVqwwSRMYGEhMTAyRkZEkJSWVOM/MmDFjsLe3Z9y4cRw9epRNmzbx9NNP88gjjxj725TXlStX+OOPPxg3bhytWrUy2caOHcvKlSu5du0aU6ZMITU1lQcffJB9+/Zx5swZvv/+e2Nz2KxZs5g7dy5ff/01Z86c4cCBA3z66aeAWrvSuXNn3n//fU6cOMGWLVtM+iCVJiQkhOXLlxMZGcmhQ4cYPXq0SS1UYGAg48aNY8KECaxcuZKYmBg2b97Mzz//bExjZWXF+PHjmT59OiEhISU2G5qbBDcVYISi8BqwAyg6602doDo4eDqgz9WTeLjsf8BCCFGdTZw4kevXrxMREWHSP2bGjBmEhYUxaNAgevXqhY+PD8OHDy/zfbVaLStWrCArK4uOHTsyadIk3nnnHZM0d999N88//zxTpkwhPDycnTt38vrrr5ukuf/++xk4cCC9e/fGy8urxOHojo6OrFu3jmvXrtGhQwdGjBhB3759+eyzz8pXGIXkd07u27dvsXN9+/bFwcGBH374AU9PTzZu3Eh6ejo9e/akXbt2/Pe//zU2gY0bN465c+eyYMECQkNDGTp0KGfOnDHea+HCheTl5dGuXTuee+453n777TLlb+7cubi7u9O1a1eGDRtGREQEbdu2NUnz5ZdfMmLECJ566imaNWvGY489ZlK7BervPzc3l0cffbS8RXRbNEotW+goNTUVNzc3UlJScHV1Neu9dTodq1evZvDgwSV2+sr34+AfiVoTxaDPBtFx8q1HA9RGZS1LUTZSnuZjqbLMzs4mJiaGoKAg7O3tK+15K5rBYCA1NdU4wkfcvqpcltu2baNv375cuHCh1Fqu0t7n5fn8lg7FlSAXsC2036ifOkzOxc/FIvkRQgghKkNOTg5Xrlxh1qxZPPDAA7fdfFdeVSu0q2GigXuAfkWOd5nahTGrx9D83uYWyJUQQghROX766ScCAgJITk5mzpw5lfa8EtxUIEdgLbAN2GXhvAghhBCVbfz48ej1evbv30/9+vUr7XkluKlAvkD+lEwlzcWYnpBOxpWMEs4IIYQQ4nZJcFPBXrjxcwVwptDxP5/8k498P+LggoMWyJUQQghRc0lwU8FaAEMABZhb6LhHsAcAcf/GWSBXQgghRM0lwU0lyF8LdTFw5cbj/Mn8ZKZiIYQQwrwkuKkEPYH2QDbw9Y1jvm190Wg1pF5MJS0+zXKZE0IIIWoYCW4qgQZ4E/gMeP7GMVtnW7xaqOt9SNOUEEIIYT4S3FSSQcBkoPB6q34d1SnIpWlKCCFurlevXjz33HPG/cDAQObPn1/qNRqNhpUrV97xc5vrPqJySXBjAYYbm6wQLoSoyYYNG8bAgQNLPLdt2zY0Gg2HDx8u933//fdfHn/88TvNnolZs2YRHh5e7Hh8fDyDBg0y63MVtXjxYurUqVOhz1HbSHBTyZYBoahDwwN6BtBhSgfaPd7OwrkSQgjzmzhxIuvXr+fixYvFzi1atIj27dvTunXrct/Xy8sLR0dHc2Txlnx8fLCzs6uU5xLmI8FNJTsCHAc+AOo292Lwp4NpMaKFhXMlhBDmN3ToULy8vFi8eLHJ8fT0dH755RcmTpzI1atXmThxIv7+/jg6OhIaGlriityFFW2WOnPmDD169MDe3p4WLVqwfv36Yte8/PLLNGnSBEdHRxo1asTrr7+OTqcD1JqT2bNnc+jQITQaDRqNxpjnos1SR44coU+fPjg4OODp6cnjjz9Oenq68fz48eMZPnw4H374Ib6+vnh6ejJ58mTjc92O2NhY7rnnHpydnXF1dWXkyJEkJiYazx86dIjevXvj5uZGw4YN6dChA/v27QPg/PnzDBs2DHd3d5ycnGjZsiWrV6++7bxUF7JwZiV7GnW24j3ADuAuy2ZHCFHNlTbHuRVQeF3l0tJqAYcypHW6yfGSWFtbM3bsWBYvXsyMGTPQaDQA/PLLL+j1eh566CFSU1MJDw9nxowZ1KlTh7/++otHHnmExo0b07Fjx1s+h8Fg4L777sPb25s9e/aQkpJi0j8nn4uLC4sXL8bPz48jR47w2GOP4eLiwrRp0xg1ahRHjx5l7dq1/PPPPwC4ubkVu0dGRgYRERF06dKFf//9l8uXLzNp0iSmTJliEsBt2rQJX19fNm3aRFRUFKNGjSI8PJzHHnusHKVX8PryA5stW7aQl5fH5MmTGTVqFJs3bwZgzJgxtGnThs8//5ysrCyioqKMK9ZPnjyZ3Nxctm7dipOTE8ePH8fZ2bnc+ah2lFomJSVFAZSUlBSz3zs3N1dZuXKlkpubW2q6xxRFQVGUuxVFyc3IVc5vP6/EbIoxe36qs7KWpSgbKU/zsVRZZmVlKcePH1eysrJMjlPKNrjIPRxLSduzSNq6N0lXXidOnFAAZdOmTcZj3bt3Vx5++GFFURRFr9cr169fV/R6vfH8kCFDlBdeeMG437NnT+XZZ5817gcEBCjz5s1TFEVR1q1bp1hbWyuXLl0ynl+zZo0CKCtWrLhpvj744AOlXbt2xv2ZM2cqYWFhxdIVvs8333yjuLu7K+np6cbzf/31l6LVapWEhARFURRl3LhxSkBAgJKXl2dM88ADDyijRo26aV4WLVqkuLm5lXju77//VqysrJTY2FjjsWPHjimAsnfvXkVRFMXFxUVZvHhxiWUZGhqqzJo166bPXdXc7H2uKOX7/JZmKQvIX5JhFbB6w1kW3bWIDa9usGSWhBCiQjRr1oyuXbuycOFCAKKioti2bRsTJ04EQK/X88EHHxAWFoaHhwfOzs6sW7eO2NjYMt3/xIkT+Pv74+fnZzzWpUuXYumWLVtGt27d8PHxwdnZmddee63Mz1H4ucLCwnByKqi/6tatGwaDgVOnThmPtWzZEisrK+O+r68vly9fLtdzFX5Of39//P39jcdatGhBnTp1OHHiBABTp05l0qRJDBgwgHnz5hEdHW1M+8wzz/D222/TrVs3Zs6ceVsduKsjCW4soClw943Hv/UIACD+QDx6nd5ieRJCVE/ppWy/FUl7uZS0a4qkPXeTdLdj4sSJ/Pbbb6SlpbFo0SIaN25Mz549Afjwww/56quveOmll9i0aRORkZFERESQm5t7m89W3K5duxgzZgyDBw/mzz//5ODBg8yYMcOsz1FYfpNQPo1Gg8FgqJDnAnWk17Fjxxg8eDDbtm2jVatWrFixAoBJkyZx9uxZHnnkEY4cOUL79u359NNPKywvVYUENxby0o2fP7vakRfsgT5Hz+UjtxfZCyFqL6dSNvtypHUoY9rbMXLkSLRaLUuWLOG7775jwoQJxv43O3bsYPDgwTz88MOEhYXRqFEjTp8+XeZ7N2/enAsXLhAfH288tnv3bpM0O3fuJCAggBkzZtC+fXtCQkI4f/68SRpbW1v0+tK/YDZv3pxDhw6RkVHQI2nHjh1otVqaNm1a5jyXR/7ru3DhgvHY8ePHSU5OpkWLgsEoTZo04bnnnmP58uXce++9LFq0yHjO39+fJ598kuXLl/PCCy/w3//+t0LyWpVIcGMh3YDngFUaDSFBdQC49K/MdyOEqHmcnZ0ZNWoU06dPJz4+nvHjxxvPhYSEsGnTJnbu3MmJEyd44oknTEYC3Uq/fv1o0qQJ48aN49ChQ2zbto0ZM2aYpAkJCSE2NpalS5cSHR3NJ598YqzZyBcYGEhMTAyRkZEkJSWRk5NT7LnGjBmDvb0948aN4+jRo2zatImnn36aRx55BG9v7/IVShF6vZ7IyEiT7cSJE/Tr14/Q0FDGjBnDgQMH2Lt3L2PHjqVnz560b9+erKwspkyZwubNmzl//jy7d+9m3759NG/eHIDnnnuOdevWERMTw4EDB9i0aZPxXE0mwY2FaIB5wACggSyiKYSo4SZOnMj169eJiIgw6R8zY8YMwsLCGDRoEL169cLHx4fhw4eX+b5arZYVK1aQlZVFx44dmTRpEu+8845Jmrvvvpvnn3+eKVOmEB4ezs6dO3n99ddN0tx///0MHDiQ3r174+XlVeJwdEdHR9atW8e1a9fo0KEDI0aMoG/fvnz22WflK4wSpKen06ZNG5Nt2LBhaDQafv/9d9zd3enRowf9+vWjUaNGLFu2DAArKyuuXr3K2LFjadasGRMmTGDgwIHMnj0bUIOmyZMn07x5cwYOHEiTJk344osv7ji/VZ1GURTF0pmoTKmpqbi5uZGSkoKrq6tZ763T6Vi9ejWDBw8u1uZamlOrTvHTPUvxblWP/xz5j1nzVF3dblmKkkl5mo+lyjI7O5uYmBiCgoKwty/a4FR9GQwGUlNTcXV1RauV79t3oiaUZWnv8/J8flfPV1+DpAL/7RPIN/seI/7kFXLSileFCiGEEKLsZBI/C7MBvnW2I6mdH95Hn8LaXn4lQgghxJ2waM3N1q1bGTZsGH5+fuVeeXXHjh1YW1uXuNBZdeIATLnxeFHTumhtrEpLLoQQQohbsGhwk5GRQVhYGJ9//nm5rktOTmbs2LH07du3gnJWuZ5CHbK5H9hi4bwIIYQQ1Z1F20AGDRp0W0vJP/nkk4wePRorK6ty1fZUVV7AWJ2eb2ysePlUEnua1rV0loQQVVQtGwMiahlzvb+rXQePRYsWcfbsWX744QfefvvtW6bPyckxma8gNTUVUEc83MkqrSXJv9/t3PfJtBy+qePE3qZ12ZWYSnuPolNq1S53UpaiOClP87FUWSo3lnfKycnBzs6uUp+7IuV/mCmKUqGz+NYGNaEsc3JyjO/1on9j5fmbq1bBzZkzZ3jllVfYtm0b1tZly/p7771nHO9f2N9//42jo6O5swjA+vXrb+u6ljbNODa4KR8ejWZsevnWPKmpbrcsRcmkPM3HEmXp4eGBwWDAy8vLOMNvTXH16lVLZ6HGqK5lqSgKV65c4dq1a5w5c6bY+czMzDLfq9oEN3q9ntGjRzN79myaNGlS5uumT5/O1KlTjfupqan4+/szYMCACpnnZv369fTv3/+25r+IeX0z7wR5MG5nCoNeGQzAdaAO6qR/tcmdlqUwJeVpPpYsS51OR2xsbLX98CqJoihkZ2djb29f4wK2ylYTytLa2pr27duX+LeV3/JSpvuYM1MVKS0tjX379nHw4EGmTFHHFxkMBhRFwdramr///ps+ffoUu87Ozq7EKlwbG5sK+8d0u/fuFlCHp1p+wcUWXli92gONlZahqJ2N3wG6mzuj1UBF/p5qIylP87FEWdrY2NCkSZMKW/DREnQ6HVu3bqVHjx7y3rxDNaEsbW1tbzoBYXleU7UJblxdXTly5IjJsS+++IKNGzfy66+/EhQUZKGcmU+rB1ux8dWNXDl2hSNLjmD9SBiHgRygBzAIeBtoa9FcCiEsSavV1qgZiq2srMjLy8Pe3r7afiBXFVKWBSw6FDw9Pd24QBhgXLQsNlbtbzJ9+nTGjh0LqH/QrVq1Mtnq1auHvb09rVq1wsnpdterrToc3B24a/pdAGx+YzNNc/KIAp5AjULXAO2AkcBJi+VSCCGEqNosGtzs27fPuEAYwNSpU2nTpg1vvPEGAPHx8cZAp7boOKUjLn4ueLf2Jjs5mwbAV8AJYAxq35tfgJbAHgvmUwghhKiqLNos1atXr1LHtC9evLjU62fNmsWsWbPMmykLs3G04cnDT+LoaTqSKxj4AXgFeB2IAToUOq9DXcpBCCGEqO1k4cwqqGhgU1grYAWwg4JfXgbQDJgOXKvozAkhhBBVnAQ3VVhaXBqrp6wm43JGsXOFexj9DJwF3geCgHcBfaXkUAghhKh6qs1oqdro1wd/JXZbLFprLQPnD7xpuvFAXWAGcOTGT2tgWmVkUgghhKhipOamCuvxeg8A9n25j+RzyTdNpwGGAZHA/9049j5w8yuEEEKImkuCmyqscf/GBPUNQp+rZ/PMzbdMrwVeAFqgzmz8UcVmTwghhKiSJLip4vq+1xeAQ98fIvFI4i3TW6FO9Adqp2NZP1gIIURtI8FNFVe/Q31ajGgBCmycsbFM1wwH1gEbqH1rUgkhhBAS3FQDvd/ujcZKw+k/ThO749aTGmqAAUhgI4QQonaS0VLVQN2mdekwuQPWdtZ4Nfcq17WpwCbgngrJmRBCCFH1SHBTTQz6eFC5r0kCmqNO7HcMdaI/IYQQoqaTZqlqSFGUUpetyFcX6AYYgDcqOlNCCCFEFSHBTTVzcc9Fvu31LUd+PFKm9G9RsNjmgYrMmBBCCFFFSHBTzcRsjOH81vNsen0T+txbL7IQCoy+8XhGheZMCCGEqBokuKlmOj3TCWcfZ5LPJbPv631lumY2aueqtcDWisycEEIIUQVIcFPN2DrZ0nNmTwC2vrWVnLScW17TGJh04/EMZGI/IYQQNZsEN9VQm4lt8Aj2IPNKJrvn7y7TNa8BjkAgkFWBeRNCCCEsTYKbasjKxoreb/cGYOcHO8m4knHLa+oD54DvUYMcIYQQoqaS4KaaavlAS3za+JCblsv+r/eX6ZryTf8nhBBCVE8yiV81pdFqiJgbwbXoa4SPCy/XtWeAL4APkDeAEEKImkc+26qxwF6BBPYKLNc1OqAnEA+0pKCjsRBCCFFTSLNUDZGXk0fG5Vv3vbEBpt14PBvIrshMCSGEEBYgwU0NcG7zOT5r8hl/PP5HmdI/CTQALgJfVmTGhBBCCAuQ4KYGcPZxJvViKqd+P8WFXRdumd4emHnj8btAWkVmTgghhKhkEtzUAHWb1SX80XAANryyoUyLao4HQlBXDp9fcVkTQgghKp0ENzVEr1m9sLKz4vzW80StjbplemvURTUBPgSuVmTmhBBCiEokwU0N4drAlY5PdwRgw/QNKIZb1948APRC7WBsX5GZE0IIISqRBDc1yF2v3IWdqx2JhxLZ+dHOW6bXAhtR15tyqujMCSGEEJVEgpsaxNHTkT7v9AEgLa5s3YQ1FZkhIYQQwgJkEr8apsPkDni18CKoT1C5rlsHzAJ+QF1FXAghhKiupOamhtFoNCaBjT5XT0psyi2vmwfspmCIuBBCCFFdSXBTg2WnZPPjoB9Z3Gsx6YnppaZ958bPJcCRCs+ZEEIIUXEkuKnB9Ll6ks8nkxyTzE9DfyI3I/emadsBIwAFeK2yMiiEEEJUAAluajAnLyfGrBmDg6cDcfvi+O3B3zDkGW6a/k3UN8Qq1CYqIYQQojqS4KaG8wzx5KE/HsLa3prTf55m9dOrbzqDcXNg3I3HjwIJlZVJIYQQwowkuKkF/Lv4c9+S+0AD+7/az47/23HTtDMBW+AUahNVvuQi+0IIIURVJcFNLdH83uYMnD8QgB3/t4OMKxklpgsANqBO7Odb6PgIoAnwKhCJBDpCCCGqLpnnphbp9EwnctNzaXp3U5y8bj4n8V03tnwZwB4gHXjvxhYMjERdwiEMmQxQCCFE1SE1N7VM91e7U69VPeN+WdagcgLigZ+A+1DXoYoC3gXaoPbPEUIIIaoKCW5qsfNbz/N126/LtFSDM/Ag8BtwGTXQuRc10OlWKF0capPWIaTpSgghhGVIcFNLKQaFNU+vIfFQIkuGLCEnLafM17qgBjrLUQOd0YXO/YpaoxOOGvTcevlOIYQQwrwkuKmlNFoNo1aOwqmeEwmRCfwy4hf0On257+OC6YriLVFrdOyAXagBzgOozVhCCCFEZbBocLN161aGDRuGn58fGo2GlStXlpp++fLl9O/fHy8vL1xdXenSpQvr1q2rnMzWQO5B7oz+azQ2jjZE/x3Nn0/+edM5cMqqL2qNzllgEuob7FegBTAVaaoSQghR8Swa3GRkZBAWFsbnn39epvRbt26lf//+rF69mv3799O7d2+GDRvGwYMHKzinNZdfez9GLBuBRqshcmEkW9/aap77Av9FHTY+ENABV5BRVUIIISqeRYeCDxo0iEGDBpU5/fz580323333XX7//Xf++OMP2rRpY+bc1R5NhjZh8OeD+es/f7F55mZ82/rSZGgTs9w7FFgDrAeaFjp+FvgXdTi5BDxCCCHMqVrPc2MwGEhLS8PDw+OmaXJycsjJKegsm5qaCoBOp0On05k1P/n3M/d9K0PYxDCunb1GyvkU/Hv5m/019LrxM/+u06ys+E2rZa7BwByDga5FmsOqc1lWRVKe5iNlaV5SnuZT08uyPK9Lo9xpJwsz0Wg0rFixguHDh5f5mjlz5vD+++9z8uRJ6tWrV2KaWbNmMXv27GLHlyxZgqOj4+1mt0bKn/NGo63YuhQF+LlJE1aEhJBtrcbXXeLiGHv8OL4ZJc+cLIQQonbLzMxk9OjRpKSk4OrqWmraahvcLFmyhMcee4zff/+dfv363TRdSTU3/v7+JCUl3bJwykun07F+/Xr69++PjY2NWe9d2RSDwrpn1xE8OJjgQcEV8hwJwJtaLQu1WgwaDTaKwpMGA68aDLjWoLK8U+s1GnZpNLxoMHC74XhNem9ampSleUl5mk9NL8vU1FTq1q1bpuCmWjZLLV26lEmTJvHLL7+UGtgA2NnZYWdnV+y4jY1Nhf3yK/LeleXAggMc+PoAkQsiue/H+2g5sqXZn8MftdPxc8A0YLVGw6dWVvhYWfHSjTT5ZakHUoCrwLUbmwEYUuh+04AjRdLkd2zuYvbcV45M1JXak4BcKyv+7w7vVxPem1WFlKV5SXmaT00ty/K8pmo3z81PP/3Eo48+yk8//cSQIUNufYG4LWFjwwgdHYohz8BvD/3GwYUVNyKtJfAXaqfjQcCzhc4NtbLCA7ABPFEX7+wMDAaeLHKfHcBa1I7K0cB14BjQE/iywnJfsRyB6TcezwVOWDAvQghRXVi05iY9PZ2oqILp3WJiYoiMjMTDw4OGDRsyffp0Ll26xHfffQeoTVHjxo3j448/plOnTiQkJADg4OCAm5ubRV5DTWVlY8Xw74Zj42zDgW8OsGriKnJSc+j8XOcKe85+NzYo6Hichhqk5HMBPG5sDYpc/yJq7Y7njfOuwJuo8+xUt0kE01BfK6jzA20BVgFTgH+QEWZCCFEai9bc7Nu3jzZt2hiHcU+dOpU2bdrwxhtvABAfH09sbKwx/TfffENeXh6TJ0/G19fXuD377LMl3l/cGa2VlqFfDaXLi2qjzrrn17HlrS13PNFfeXyp13MctX9ODpAKnAMOoH7YF3YvMB4YhjozcijwM/AD3HFzTmXaBAQCfxc6Nh91Ha+NqK9JCCHEzVm05qZXr16lflAuXrzYZH/z5s0VmyFRjEajof+c/ti52rH5jc1sfXMrLUa0wKu5V6U8fwvUJqnbpQHGFNrPBUYAT6FOLljV7EANzjJQ+woNuHE8CHgVeAO1JmcwBTU7QgghTFXLDsWicmk0Gnq+3hM7VztcfF0qLbCpCJ8CfwB/ojZZvUrV6Xj2L2qfowzUoOb7IudfAr5F7U/0O/BwpeZOCCGqDwluRJl1fta0v03qxVScvJ2wsrGyUI7KbwpwGvgGeB3YC3wH1LFgnkBdpiICta9NL2AFajNUYfbAAtRRYr0rMW9CCFHdVJUvraKaSbmQwsJuC/n5/p/Jy86zdHbKzA74GjVIsEOtxekAHLVgno4B/VE7Tne9kaebzWfTEwlshBDiViS4Ebfl6umrZFzO4PQfp1kyZAm56bmWzlK5TAC2Aw1RR1J1Qm2qsoTPUeexaQ+sBpzLeN0FYFtFZUoIIaqxcgc3gYGBvPnmmyajmETt06hvI8asHYOtsy0xG2P4vv/3ZF3PsnS2yqU9sB91+LkVEGKhfHyC2lF4HVDWCQ12Ac2AUagjyIQQQhQod3Dz3HPPsXz5cho1akT//v1ZunSpyfIGovYI7BnI2A1jsXe35+Lui3zb+1syLlevtaHqok78txPTVcsr+h2dhNp3BtSOb7NR5+Ypq7aosy/H37hWCCFEgdsKbiIjI9m7dy/Nmzfn6aefxtfXlylTpnDgwIGKyKOowup3rM/4LeNx8nYi8VAii7ovIvVi9apLsAJaFdrfiFqLs7OCni8edTmIxwD9bd7DDnXkF8DHWLbPkBBCVDW33eembdu2fPLJJ8TFxTFz5kz+97//0aFDB8LDw1m4cGGlTvQmLMs71JtHtz2KW0M3rGytsHaovoPwFOAt1P4svYAvbhwzl8tAX9R+PhtR18G6XQOB+1ADpMmYN59CCFGd3fankE6nY8WKFSxatIj169fTuXNnJk6cyMWLF3n11Vf5559/WLJkiTnzKqowzxBPHt3+KFprLY6et7t2teVpUEcrTQB+QQ0afkSd8bgDcBfge5v3voY6KuoE6tIRG4F6d5jfecAaYOuNfMrcN0IIcRvBzYEDB1i0aBE//fQTWq2WsWPHMm/ePJo1a2ZMc++999KhQwezZlRUfW7+pt1ht769FQdPB9o/2R6NpvqshuQMLEMdQfUyavNUfhPV28CMG4+vArtRg55bBSkpqBPzHQZ8gA2osw7fqYao8/W8irq21jDK3ilZCCFqqnIHNx06dKB///58+eWXDB8+vMQlyIOCgnjwwQfNkkFRPcUfjGfTG5tAgag1Udz9v7txqudk6WyVmQZ4ARgObEadPfhf1BXJ821GXcoB1CCjA9Dxxs92qAt3gjox3yDUkVl1URe+bGLGvE4FlgBDkVk5hRACbuN/4dmzZwkICCg1jZOTE4sWLbrtTInqzyfMh4i5Efzz8j+c/uM0X7b+kuGLhxM8MNjSWSuXxje2iSWc06MOxz4FxN7YfrtxToO6RMIwYN+NrQ6wHmhp5jzaoS4keidrcAkhRE1S7g7Fly9fZs+ePcWO79mzh3379pklU6L602g1dH6uM4/9+xheLb3ISMzgx0E/subZNdVqRuPSjETtP5OM2n/m/4D7UWtxFNRFP0GdUXgF6irf4RWUl8KBjQHpXCyEqN3KHdxMnjyZCxcuFDt+6dIlJk+ebJZMiZrDu7U3j/37GB2f6QjA3k/2srjXYhRDzfn4dUUNYKYBvwLngQSgUaE0Q1CbqyraftQlHIouuilESQ4CmZbOhBAVoNzBzfHjx2nbtm2x423atOH48eNmyZSoWWwcbBj08SBGrx6Nk7cTbR9ri0ZbfToY3w5v1KapyvYPsAd1BfFkCzy/qLryUDvAF/5aMQdojboUiRCgfkH6AXVpl4sUTDZa3ZQ7uLGzsyMxMbHY8fj4eKytpTujuLmQQSFMOTmFNhPaGI/FH4gnLT7NgrmqWZ5HnWn5MuqSDqJ2u4i6SOxIwAt18sj8r6AKan+yaKAHagf66rWASvVnQA0sfy1y/AfUubAqUwbQHXVZmkdQ3xP+gAPq/5QniqQ/gbrYb1VV7uBmwIABTJ8+nZSUFOOx5ORkXn31Vfr372/WzImax76OvXFYeNb1LJYOX8qXoV9y8veTFs5ZzWALfHbj8edApOWyUmVdA9ItnYkKdBJ1WoBQ1A+nSahzNiUD7sDZG+k0qDV8j6IGOnOBNqg1f6Li6FFHWk5Bne+qO/A0BbOVx6POs9UEuOdG2opqxC88Q7oT6mztNqjzeTVGHXGUC5xGndi0sG6oS8bUQV0O5n7U99MXVI2awHIHNx9++CEXLlwgICCA3r1707t3b4KCgkhISOCjjz6qiDyKGio7ORtHT0eyrmaxbPgy/nzyT3Izqtfq4lVRP9Rv6gbUSQira7WyOaUD36HODl0XcEFtOuyCOvHh5kJp9VSvMotCHamX7zzwEeqSHBrU6QtmoS62egV1BF8+N2Ah6sSVvqgj/7oC06n49dVqmx2otR++qH30PkcNZNxQJ/fMX7Qm7ca+Aqy6kbYd6vvXXP8dLwMzgUDU90S+z4FzqE1SUag1eTGoAyZeK5QuA/WLFKhzeB0ElgMfov7PecdM+bwT5Q5u6tevz+HDh5kzZw4tWrSgXbt2fPzxxxw5cgR/f/+KyKOoodyD3Jm4eyJdX+oKwP6v9/NNu2+IPxBv4ZxVfx+hfhPbifpPsbbbBIxD/Sed/y34MmoflB+BS4XSrkctuxaocwc9i7p+15+oTTrZlZPlUqWgfktujLoO2qeFzvVA/ea/FPWDaxfqB1ln1G/mJRmKGgyNQQ3s5lJQwyNuTy6mNSMrgG9QfyceqL+j1ajvw+9Qa9VArbH5C7XZ50nUZqGDqO/fANQg6XadBB5HHdH5Jmqz5beFzrdEXZA3nzVqANQbNejN54Q6aCId9X3zB+rfyHPA3ai1UZZ2W51knJycePzxx82dF1ELWdtZ039OfxpHNGbluJVcPXWV/3X+Hz1n9URpXnNGVFW2BqgfaNOAn1E/tGqLKNQPC0/UwATUdbi6ok6m+Ajqt+WzhbZOha4/ixrAnLixFbVQoynXCu7mthn1gy6/tsaGgm/9oH4YLriN+3qg9vW4H/WDq3mhcwqW6SBf3WSjTvnwK2qty8+oM5MDPIRaKzMCdd26W81L1Qz4EnVW9G9Qm5uv3zhe+Pnsb3EfBdiC+oXnz0LHO6IGyPfe4vrSOKEGROaeu8scbrsH8PHjx4mNjSU317Si7O67777jTInap1HfRvzn8H/44/E/OPHbCeL3x2PXws7S2arWnkWtAn+I6tXMcjtSUPuVfEtBe78/al8GLeoHSdFvvG1vbEU9hhoMRVMQ/EQX+tmIgpFoh1EnUWxqnpdRqmzUpT/moX5gBQEfABGoS4aYS9EPu72oTQ0LUEdWieKSUZdA+R7T/lxrKAhu2gFf38a9PVGbCV9A7UPnWehcf9Tf/fM3HpfkKur7OQc1QL3nxr26UbMD1tuaofjee+/lyJEjaDQa4+rf+Z1E9Xp9aZcLcVMOHg488MsDHPnxCIH9A9m0exMAukwd1g7W1Wp9qqrAloKFNKtCcJOBGhy4ofZ7ceTO/7luRv1Wu4KC5iIt6j/6caivu7xt7zaoAUyjEs4pgE5RWIPa7PAwamfLN1C/BVfkLNFvoTYXgRqAfYTad6iivYA6w3Z71NrAl5FlPgpbh9pp++KN/QaotTMjUPt0mYstam1LvmjUgF0B1qLWnjyt0WBva8vPGo2xtrYualOUDjUIMufSL1VZufvcPPvsswQFBXH58mUcHR05duwYW7dupX379mzevLkCsihqE41GQ+uHW+Pg4QCAoiisGLuCHwf+SMqFlFtcLW4mE/i6dWte0mr5HXXEUGVajtqnIAy1Dd8ZtfmkAeqszT8WSpsAfHLj2DrUeTfOoX4jLtpQuRT4CTWwaY46S3Qs6j/7hzD/h7CGgoAs7Ub+c1BrVDqgBgEVZRrqh9sfqAFdZQQ2oNaI3YP64fgaavNeSc11tVEu8BRqYNMYtb/WedTatW7cxgdsOTRGbYJ9FvXv6RjwpLU14wcN4mFraw4WSvsJahNXbQls4DbKfteuXbz55pvUrVsXrVaLVqvlrrvu4r333uOZZ56piDyKWux61HXO/HWG6L+j+bLVlxxYcMBYWyjKxgD0t7JiTVAQH1tZMRz121wY8AzqeljJZngeBfUf7CeonQoLz5LcEvXD0Z2CURY5qB15D2FalX8C9R/2w6jV6e1Rm2Bcbly7s1DaiahNJntvPPc0oL4ZXktZeKJ2/Pz+xuNDqH13pmGeWX/PAK9QENC5oXaAHmqGe5eHD2rN2Hc38vAv6pDxDzDtMFsb2aKONpuC+vvvR8UGNEU1AuajBlcfAg1v/G9sqii1fhLPcv8e9Ho9Li7qd4a6desSFxcHQEBAAKdOnTJv7kSt5xHiwRORT9CgcwNyUnP4Y9IfLBm8hNSLqbe+WADqH/kqvZ6p+/bxmF5PM9QPzMOoo2xGoAYH+eJQa0/K4gKwGLWTrh/QCjUw+ePGlq8J6rfMq6i1LGmoQ0z3odayDCqU1g11KHsf1D4e9VH7tYA6y27h0R0dUDtadsAy/Qc0qEHYcQr6Nn2Amu9LpVxXGgX1W3Y4ak3U/4o8nyVoUH/Hx1B/VzmoQdzyQmn01Pw1zTJQA5kvCh3rifp35GSRHKncUJsPT+bl8c3ff3MoL4/eFsxPVVDuWttWrVpx6NAhgoKC6NSpE3PmzMHW1pZvvvmGRo1KaqUW4s7UbVqXR7c/yu55u9n42kai1kbxRasviJgXQfj4cOmLUwaeQI9LlxgcFoaNlRWJwFbUURTbMR3mOQ/1W2AT1H/c+VsD1OAi/59GGmoTU+H+PPaow0D7oXZ0zadBrUbP53xjCywhr22BZUWOKagfLEmo/8irmnrAEmA08B/UgMz3Nu4ThzpEeN2N/T6YlqOl1UetrVqIOox5RKFznqgdu21ubNaFHndGrf3JF4E68scasLaywjY8HGuNhgFU3dXttwHjUTuWOwGjMO3cWxVYA/Wysiq19qiqKndw89prr5GRkQHAm2++ydChQ+nevTuenp4sW1b0X5IQ5qG10tL1xa6EDAnh90d/59KeS2yZvYWWI1ti62R76xsIE97AAze2ohJQg5HTN7b/3jjuh1oNvu3Gvgvqh5YedXK8fqgdKG81NPV2aCgIiKqyoajzzKRSUC2ehtrxedhNrsm3DDUwuo5ahu9TMNqrKtGgNgdOLHJcV+inrsi5on28DlJo8jitFgIC2IDaXDoR9bVXFVmofarmowbZ/qgjx6paYCNMlTu4iYgo+B4RHBzMyZMnuXbtGu7u7vINWlQ4r+ZeTNg+gV1zd+HbztcY2BQdtSdu3/eo/Wa2odbsbEH9MIoDElE/rPM7s25BRs4U5XpjyzcDtdniftQmNJ8SrnkFtQkK1CHD32M6z0x1cIGCwEaHWsuX/9ihSNqlqEGDDsjIy+PHCxfYFxjIFY2GpELpFApGalniL3s36qi70zf2J6COWKuKtYfCVLn+L+l0OhwcHIiMjKRVq1bG4x4elpzSStQ2Wmst3aZ1Mzm2/5v9nPnrDEO/HoqLb2WNI6m53FE7BefPWpWC2mGyMaajdCSwKZ2C+kFohdpxewPqh+N4TD+s70FtDnwFdURSVW2aKU15PgX6FHqsUxScDx/mtwYN2G5jYxL8/YvaSTsAtRnoQdS+SJUR6CSgTraXg1pr+V9gcCU8rzCPctV42tjY0LBhQ5nLRlQpukwdG2ds5PQfp/mi5Rcc/vGwjKgyMzfU5pbKGolUU2hQ56fZh9qXKBn12/9dwKJC6bqgDnefTfUMbMzBGnV+otBCx86gNkWeB+aglmFT1HmFjhe9gZn5oHaafgR1iQEJbKqXcjfnzpgxg1dffZVr1yp7pgwhSmbjaMP4zePxbedL9vVsVjy8gmX3LiM9oSav/Syqk3DU1bbnoPan2Yka5BSeL+Z2OiDXdGNQ1176FbV/mD1qwPMW6vQChacFuNOvM7moQdORQsdmY7ruk6g+yl2r/NlnnxEVFYWfnx8BAQE4OZkOgDtw4IDZMidEWdVrVY+JuyayY84OtszewqnfTxG7LZaBnwwkdHSo9MURFmdNwVo+U1CHwstXxFtzQO2vdD9qf68/UDtf588rlK8nagBpjzp1QOGfHqj9w/K9gxpYFk7zD+r0CH+iTo1gTc1enqCmK3dwM3z48ArIhhB3zsrGih4zetB0WFNWjl9JwsEEfh//Ow3vakidgDqWzp4QAASjzu0jys8Fdbj9aNTOyIVXOc9GrX3JLeG6oiOb/kEdwVZUXdR1nKQvWfVX7t/hzJkzKyIfQpiNd2tvJu2ZxI45O8hOzjYJbK5FXcMjWDrAC1HdFe2btBZ1LqQc1EAnu9Djok1WT6N2li+czhF4EnXOIlH9SYAqaqT8WpzCEg8n8lX4VzQZ2oQ+b/fBu7W3hXInhDA3D8o+Yuu+isyIqBLK3aFYq9ViZWV1002Iqip2eywarYbTf5zmq/CvWD5mOdeipNeDEELUNOWuuVmxYoXJvk6n4+DBg3z77bfMnj3bbBkTwtw6PNWBoL5BbH5jM8d+PsaRJUc49vMx2kxsQ4/Xe+Ba3/XWNxFCCFHllTu4ueeee4odGzFiBC1btmTZsmVMnFh0Um4hqo66TesyYtkIur3SjU2vbeLM6jPs/3o/UWuieObsM2itqtpk90IIIcrLbP/JO3fuzIYNG8x1OyEqlG8bX0b/NZrxW8fT8K6GdH6+szGwURSFnLQcC+dQCCHE7TJLcJOVlcUnn3xC/foyf6moXgK6BzB+63g6Pt3ReOzEbyf4pNEn7Jq7C11W0SUAhRBCVHXlbpYqukCmoiikpaXh6OjIDz/8YNbMCVEZNBoNGquC9/Th7w+TmZTJ3y/8za65u+j+anfCxoXJ6uNCCFFNlDu4mTdvnklwo9Vq8fLyolOnTri7l2+S6q1bt/LBBx+wf/9+4uPjWbFixS0nCdy8eTNTp07l2LFj+Pv789prrzF+/PjyvgwhbmrkbyM59N0hNs/aTOqFVFZPXs3G1zbS/sn2dJjcQToeCyFEFVfu4MacgURGRgZhYWFMmDCB++679cwDMTExDBkyhCeffJIff/yRDRs2MGnSJHx9fYmIiDBbvkTtprXW0mZCG0LHhHLgfwfYPW8316Ovs/297Vzac4mxG8ZaOotCCCFKUe7gZtGiRTg7O/PAAw+YHP/ll1/IzMxk3LhxZb7XoEGDGDRoUJnTf/XVVwQFBfHRRx8B0Lx5c7Zv3868efNuGtzk5OSQk1PQOTQ1NRVQh7DrdObtT5F/P3PftzaqEmWphTaPtyFsYhhn/jzD3o/30u6pdsY8ZVzJ4NKuSwQPCa7yo6yqRHnWEFKW5iXlaT41vSzL87o0iqKUazHVJk2a8PXXX9O7d2+T41u2bOHxxx/n1KlT5bldQUY0mls2S/Xo0YO2bdsyf/5847FFixbx3HPPkZKSUuI1s2bNKnH+nSVLluDo6HhbeRW1l6IoxmbZhGUJJPyUgK2vLV5DvfDo44GVg0xkKYQQFSEzM5PRo0eTkpKCq2vp3QPKXXMTGxtLUFBQseMBAQHExsaW93blkpCQgLe36ZT53t7epKamkpWVhYODQ7Frpk+fztSpU437qamp+Pv7M2DAgFsWTnnpdDrWr19P//79sbEpuvKJKI/qUJa7ju8ieU0y2fHZXPrvJa7+cpU2k9rQ7ql2uDaoWv1yqkN5VhdSluYl5Wk+Nb0s81teyqLcwU29evU4fPgwgYGBJscPHTqEp2fRtVctz87ODjs7u2LHbWxsKuyXX5H3rm2qcln2mN6Dzk93JvLbSPbM38O1qGvs+nAXe+bvofUjrbl7wd0mne+rgqpcntWNlKV5SXmaT00ty/K8pnJ3FHjooYd45pln2LRpE3q9Hr1ez8aNG3n22Wd58MEHy3u7cvHx8SExMdHkWGJiIq6uriXW2ghR0Wydbek4uSOTT07mwd8fJKBnAIY8A2goNmWCEEKIylHumpu33nqLc+fO0bdvX6yt1csNBgNjx47l3XffNXsGC+vSpQurV682ObZ+/Xq6dOlSoc8rxK1orbQ0vbspTe9uSvyBeOzr2BvPXTl+hRWPrKDPO31oHNG4ytXmCCFETVPu4MbW1pZly5bx9ttvExkZiYODA6GhoQQEBJT7ydPT04mKijLux8TEEBkZiYeHBw0bNmT69OlcunSJ7777DoAnn3ySzz77jGnTpjFhwgQ2btzIzz//zF9//VXu5xaiovi29TXZ3/r2VuIPxPPjoB8J6hNEvzn98GvnZ6HcCSFEzVfu4CZfSEgIISEhd/Tk+/btMxl1ld/xd9y4cSxevJj4+HiTTspBQUH89ddfPP/883z88cc0aNCA//3vfzLHjajSBn06CBc/F/Z+upeYjTH8t/1/afVgK/q80wf3RuWb+FIIIcStlTu4uf/+++nYsSMvv/yyyfE5c+bw77//8ssvv5T5Xr169Sq1L8LixYtLvObgwYNlfg4hLM3R05EBHw6g49Md2fT6Jg7/cJijS49y/Lfj3PXKXfR+s/etbyKEEKLMyt2heOvWrQwePLjY8UGDBrF161azZEqImqhOQB3u/e5enjjwBI0jGmPQGbB1kfWqhBDC3Mpdc5Oeno6tbfF/yDY2NuUagy5EbeUT7sPDax8mZmMM/l39jcfP/nOW62ev02ZCG7TWVXvGYyGEqMrK/R80NDSUZcuWFTu+dOlSWrRoYZZMCVEbBPUJwtr+xojDPANrn13Ln0/8yZehX3Jy5UkZPi6EELep3DU3r7/+Ovfddx/R0dH06dMHgA0bNrBkyRJ+/fVXs2dQiNpAURTaPt6WrW9tJelkEsvuXYZ/N3/6z+lvUrsjhBDi1spdczNs2DBWrlxJVFQUTz31FC+88AKXLl1i48aNBAcHV0QehajxrGys6PxsZ56JfobuM7pj7WDNhR0XWNhtIcvuXcbV01ctnUUhhKg2bqthf8iQIezYsYOMjAzOnj3LyJEjefHFFwkLCzN3/oSoVezd7Onzdh+eiXqGto+1RaPVcHLlSZJOJlk6a0IIUW3cdq/FrVu3Mm7cOPz8/Pjoo4/o06cPu3fvNmfehKi1XPxcGPbNMP5z9D/c9epdNBnWxHhu4+sb+fM/f3Lp30vSL0cIIUpQrj43CQkJLF68mAULFpCamsrIkSPJyclh5cqV0plYiArg1dyLvu/0Ne7n5eSx74t9ZF3LYv9X+6nXqh7hj4bT+uHWONVzsmBOhRCi6ihzzc2wYcNo2rQphw8fZv78+cTFxfHpp59WZN6EEEVY2VgxYtkIQkeHYmVnxeWjl/n7hb+ZW38uy+5dxtl/zlo6i0IIYXFlrrlZs2YNzzzzDP/5z3/ueNkFIcTt0Wg1NOrXiEb9GjHos0EcXXqUyEWRxP0bx8mVJ/EI8aBRv0aWzqYQQlhUmWtutm/fTlpaGu3ataNTp0589tlnJCVJJ0chLMXB3YEO/+nAY3sf4z9H/kPnqZ1pM6GN8XzUuigWdF3A/v/uJyc1x4I5FUKIylXm4KZz587897//JT4+nieeeIKlS5fi5+eHwWBg/fr1pKWlVWQ+hRClqNeqHhEfRVC3WV3jschFkVzcdZE/H/+Tj/0/5vzH57m0RzohCyFqvnKPlnJycmLChAls376dI0eO8MILL/D+++9Tr1497r777orIoxDiNkTMi6DfnH7UbVaXvKw8rm+6zrfdv+Wbtt+w/5v9GPIMls6iEEJUiDtawKZp06bMmTOHixcv8tNPP5krT0IIM3DxdaHbS9146vhTjN06Fvfe7ljZWZEQmcDu+bvRWGksnUUhhKgQ5V5+oSRWVlYMHz6c4cOHm+N2Qggz0mg0NOjcgIBnA+i1pBfHlxzH2ccZjUYNbnSZOn4e8TOhY0JpMaIF1nZm+bcghBAWI//FhKhFHD0d6TK1i8mxo8uOErUmiqg1Uax7bh3hE8Jp/0R73Bu5WyiXQghxZ+6oWUoIUf0FRwTTa3YvXOq7kJmUyc45O/mk8Sf8MPAHTv5+UvrmCCGqHQluhKjlXPxc6PlGT5479xyjVoyicURjAKLXRbNs+DKSzydbNoNCCFFO0iwlhABAa62l2fBmNBvejGvR19j/9X7SLqXh0djDmGbbu9vwauFFyOAQrGytLJhbIYS4OQluhBDFeDT2oP+c/ibH0hPS2fTGJhS9gmNdR0LHhBL+aDg+YT4WyqUQQpRMmqWEEGWjgS5Tu+Ds40xmUiZ7Pt7D1+Ff83Wbr9k9fzcZVzIsnUMhhACk5kYIUUbO3s70n9Ofvu/2JfrvaCIXR3Lq91MkRCaQEJmAlZ0VHf7TwdLZFEIICW6EEOWjtdYSMjiEkMEhZF3L4ujSoxxZcoRWD7Yypjn8w2Hi9scRPl6arYQQlU+CGyHEbXPwcKDDUx3o8JRpjc3eT/dyae8l9szfg0+4D2Hjw2g9pjWOdR0tlFMhRG0ifW6EEGalKAo9Z/akxYgWWNmqyz2se24dH/l9xLL7lhG1NsrSWRRC1HBScyOEMCuNRmNstsq8msnRpUc5tPgQcfviOLniJHnZeQQPDLZ0NoUQNZgEN0KICuPo6UjHyR3pOLkjl49e5uDCgzQe0Nh4PiU2hTVPr6Ht420JHhiM1koqk4UQd06CGyFEpajXqh4RcyNMjh1YcIBTq05xatUpXP1daTupLW0mtsG1vquFcimEqAnka5IQwmJCHwql8/OdcfBwIPVCKptnbmZ+w/ksvWcpp/86jUEv61oJIcpPghshhMXUbVaXiLkRTL00lXt/uJeAHgEoBoVTq07x66hf0WXqLJ1FIUQ1JM1SQgiLs7a3pvWY1rQe05qkk0ns/+9+tNZa7FzsAHUE1rrn19GofyPpmyOEuCUJboQQVUrdZnWJ+Mi0b07cv3Hs+XgPez7eg4ufCy1GtqDVqFbU71QfjUZjoZwKIaoq+fojhKjynH2c6TxV7ZuTFpfGnvl7WNBlAR8Hfcz6l9dzLfqapbMohKhCJLgRQlR5bg3diPgogqlxU3lw1YOEjg7FxsmGlPMp7Jyzk+tnrxvT6nP1FsypEKIqkGYpIUS1YW1nTdNhTWk6rCm6TB1nVp/hzF9nCOodZEzzz/R/iF4XTctRLWk1qhWeTTwtmGMhhCVIcCOEqJZsHG1oMaIFLUa0MB5TFIVTv5/ievR1Nr+xmc1vbManjY8x0KkTWMdyGRZCVBpplhJC1BgajYbH9z3OPYvuIXhgMBorDQkHE9jwygY+DvqYpcOXWjqLQohKIDU3Qogaxb6OPeHjwwkfH05mUiYnlp/g2LJjnNt8DreGbsZ0hjwDO+bsIGRICN6tvWXUlRA1iAQ3Qogay7GuI+0eb0e7x9uRnpBuMuNx7I5YNs7YyMYZG3ELcKPZ8GY0vacpAd0D0FpLpbYQ1ZkEN0KIWsHZx9lk39remqZ3NyX672hSzqcY59Gxd7enydAmdJvWjXqt6lkot0KIO1Elvp58/vnnBAYGYm9vT6dOndi7d2+p6efPn0/Tpk1xcHDA39+f559/nuzs7ErKrRCiJmjQqQEP/v4gLyW9xKgVowgfH46DpwPZ17M5/P1h8rLzjGmTzyWTnphuwdwKIcrD4jU3y5YtY+rUqXz11Vd06tSJ+fPnExERwalTp6hXr/i3piVLlvDKK6+wcOFCunbtyunTpxk/fjwajYa5c+da4BUIIaozWydbmg1vRrPhzTDkGbiw8wLR66PxbedrTLNl9hYiv43Ev4s/wUODyXaTL1NCVGUWD27mzp3LY489xqOPPgrAV199xV9//cXChQt55ZVXiqXfuXMn3bp1Y/To0QAEBgby0EMPsWfPnkrNtxCi5tFaawnoEUBAjwCT4+kJ6aDAhZ0XuLDzAgALvllA6OhQWj3YyqSjshDC8iwa3OTm5rJ//36mT59uPKbVaunXrx+7du0q8ZquXbvyww8/sHfvXjp27MjZs2dZvXo1jzzySInpc3JyyMnJMe6npqYCoNPp0OnMu+Jw/v3Mfd/aSMrSvKQ878zIVSNJvZjKmT/PcHLlSc5vOU/ioUQSDyVy4H8HeOLoEzLa6jbJe9N8LFWWGRkQHw+JiRri4yEhQYNWC089Zbj1xeVQntdl0eAmKSkJvV6Pt7e3yXFvb29OnjxZ4jWjR48mKSmJu+66C0VRyMvL48knn+TVV18tMf17773H7Nmzix3/+++/cXR0vPMXUYL169dXyH1rIylL85LyvEMNwf0Zd1zGu5C8K5nrW69jG2rLmjVrADDkGjg/9zxundxw6+yGlYOVhTNcfch703zMUZaKAmlptly7Zkdysj3Xr9tz/bpdkZ/q46wsm2LXe3hkERj49x3no7DMzMwyp7V4s1R5bd68mXfffZcvvviCTp06ERUVxbPPPstbb73F66+/Xiz99OnTmTp1qnE/NTUVf39/BgwYgKurq1nzptPpWL9+Pf3798fGpvgvW5SdlKV5SXmaT35ZPvThQ9jY2KAoirHW5tTKUxzefZiU3SlYf21N8JBgWo5qSeOBjbG2r3b/biuFvDfNp2hZqgEKJCerW0qKptjjlBRITjZ9fPUqJCSATlf22khHRwVfX/DxUfD2Bn9/WwYPHmzW15ff8lIWFv1rq1u3LlZWViQmJpocT0xMxMfHp8RrXn/9dR555BEmTZoEQGhoKBkZGTz++OPMmDEDrdZ0AJidnR12dnbF7mNjY1Nhf0gVee/aRsrSvKQ8zaeksmzQsQG9ZvfiyJIjXD11lZO/neTkbyexc7Oj+X3NuWv6XXiGyFpXJZH3ZukUBVJT4coVdbt8ufjjy5etiI7uiaI4kJysISUFDHfYMlS3Lvj4gK8vN4KXkh87O2tQY/zCAZF5ay7L8/6waHBja2tLu3bt2LBhA8OHDwfAYDCwYcMGpkyZUuI1mZmZxQIYKyu1ABVFqdD8CiFEaeoE1KHnGz3p8XoPEiITOLLkCMeWHiP1YiqRiyLpNq2bMW1mUib27vZorarEjByiEikKZGXBtWum29WrkJRUcuBy5Qrk5t7qzlqgTrGjtrbg7g516tx6c3dXN19f8PZWr62OLF5POnXqVMaNG0f79u3p2LEj8+fPJyMjwzh6auzYsdSvX5/33nsPgGHDhjF37lzatGljbJZ6/fXXGTZsmDHIEUIIS9JoNPi28cW3jS/9/68/sdtjOb/1PHWb1TWmWTVpFbHbYmk8oDHBg4JpHNEYZ2/nUu4qqqrsbDh7FuLiigcsN9sKjXMpFycnqFcPvLwKtvx9d/c8zp3bx4AB7alb19oYsNjbQ23r727x4GbUqFFcuXKFN954g4SEBMLDw1m7dq2xk3FsbKxJTc1rr72GRqPhtdde49KlS3h5eTFs2DDeeecdS70EIYS4KY1WU2x4uWJQiD8QT9a1LI4uPcrRpUcB8G3nS/CgYJoMaUKDzg0slWVRgsxMNYA5cwaiotQt//HFi2ptTHnZ2ICHh+lWt+7NgxcvL3BwuPn9dDqF1asT6dxZoba38Fk8uAGYMmXKTZuhNm/ebLJvbW3NzJkzmTlzZiXkTAghzE+j1fDs2We5uOciZ1afIWpNFAkHE4jfH0/8/njObz7Po9seNabPup6Fg3spn2rCLDIyIDraNHDJf3zpUunXurpCw4bg6Vk8YLnZ5uRU+2pUKkuVCG6EEKK20VpraditIQ27NaTvO31JT0gnam0UUWui8L/L35gu82omH3p/iE+4D8GDggkZFEL9TvWlr045ZGWpo39K2tR5WdTal/j40u/j5gYhIeoWHKxu+Y/r1pVApSqR4EYIIaoAZx9nwseHEz4+3OT4pT2XUPSKsVZn29vbsHe3JzgimMYDGxMyKASnek6WybQFGAyQnq4OW05NVbfkZLXjbdGAJX9LSSn7/T08TIOWwkGMh4cEMNWFBDdCCFGFhQwO4YX4F4haF0XU6iii/44m+3q2sa/O3Qvups2ENgDoMnVobbRY2VTdwRWKogYbly+rW1ychq1bG3L6tJaMjIKApXDwUng/Le32ntfOrmD4cuGt8JDmxo3VAEZUfxLcCCFEFefs40z4uHDCx4VjyDNwcc9FotaoTViNIxob0+3/Zj+bZ26mUb9GNB7YmOCBwbj5V/y6V1lZBcFK/vDl0jbTWfStgTblfk4bG7WZyNVV3erVKx6wFN7c3KTWpTaR4EYIIaqRwn11+rzdx+TchZ0XyEnN4cTyE5xYfgIArxZeBA8KJnhgMAE9A267VufaNTh9Gk6dMv0ZE6M2E5VXfkDi5WVAp7tMcHA93N21xmDF1dU0eCm6b2cnwYq4OQluhBCihhixdATx0+I5s+YM0Wujubj7IleOX+HK8Svs/XQv065NMwY32SnZ2LvZm1yfk6OOFiocwOQ/Tkoq/bltbdVgpSybl5c69wqATqdn9eo9DB48GBsb6SQtzEOCGyGEqCE0Wg1+7f3wa+9Hz9d7knU9i7P/nCVqTRR5OQaSM2y5ck4NVHaP/5bc9BwyGzYj2rY5+xMbcO68ptTp+uvXh6ZNoUkT9WfTptCokdrs4+oqNSmi6pDgRgghqqGMDLX/SlKS2s+lpJ9JSQ5cudKSpKSWXL8OyhL1WnuyeInLWGHAPmkXLdmFPy4cpznnHFrg3MKfps20xiCmSRN1tJCzTKAsqgkJboQQoorIzS0Y0pyYePO5WRISbq+fC6ijgby8HNhSZxpBylkapJ7A9twpXLPT6MxeOmftJTwsnHsW3GPeFydEJZLgRgghKkFeHpw7VzDj7fnzxQOWq1fLd097+4Jp+evWVbf8xyX9dHcHa+N/fTugOdCcvOw8otdHc+K3E5z6/RTBEcHG50g6lcTOD3bSYkQLgvoEYWVbdYeZC5FPghshhDATvR5iY9XgpegWE6MGOLdiba2uxlx0KHPRzdsbXFzMk29re2uaDmtK02FN0efqTc4d+/kYBxcc5OCCg9jXsafp3U1pPqI5jfs3xtpePkJE1STvTCGEKIecHEhMdGDDBg0xMaYBzNmzRedwMWVvXzDjbaNGJc/H4uEBWgsOGipaM9N4QGPS49M5sfwEGYkZHPruEIe+O4Stiy1NhjYhYm4Ezj7SGUdULRLcCCFqNUVRZ71NTFT7u5T2MzERUlJsgAE3vZ+trTrTbf4aRIW3+vUtG7jcjgadGtCgUwMGfTqICzsvcPzX45z47QRpl9I4/edp7llU0Dfn2M/HsLKzIqBHgCz0KSxKghshRI2l06kLIp4/X7DFxhZ02M2fMTc7u3z3tbY20KiRhiZNNMUCmAYNwKoGdkvRWmkJ6B5AQPcABs4byMU9F7l+9jrWdgUfIxtf28i1M9dAAz7hPgT2CiSwVyABPQKwr2Nfyt2FMC8JboQQ1VZGhhqsFA5eCm9xcZQ6b0thzs5qP5Z69Ur/6e6uY9eu1QwZMhgbG5uKfYFVlEarwb+LP/5dClYv1+v0NOrXCK2VlqSTSSQcTCDhYAK75+0GDbS4vwUP/PKABXMtahMJboQQVZKiqHO15AcvJQUxZRldZGcHDRtCQEDB5udnGrTUqweOjmXLl04nk9WVxMrGiiFfDAEgPSGdc1vOcW7TOc5tPsfVU1dx8CxoptLr9HzX5zvqd6qPf3d/9Jn6m91WiNsiwY0QwiJ0Orh0yTRwKfwzNhYyM299H1dX08Cl6FavXvXr51LdOfs402pUK1qNagVAWnyaySisuH1xxG6PJXZ7LLs+2gVauDrvKkF9ggjqE4R/N39snWwtlX1RA0hwI4SoEDk5aoASE6PO75K/5QcvZW0y8vFRg5T82peitTB16lTs6xB3zsXXdMx63WZ1ue/H+4jZFMO5Tee4Hn2duH/jiPs3jh3/t4Peb/emx4weAOTlqOPnC/ftEeJW5N0ihLgtOp0apOQHLYWDmJgYiI9Xm5ZKY2urBitFA5f8nw0aFCywKGoOB3cHQkeHEjo6FJ1Ox8pvV9JY25jYrbHEbIwhqHeQMe3JlSf5ffzv+HfzJ6hPEIG9A/Fr73fbq5uL2kGCGyHETSkKXLgABw9CZKQ6j0t+EHPp0q1rXhwdITBQ3YKCpMlIlMzWy5bQwaG0ndAWpUhEfGnPJfKy84jZEEPMhhg1vbMtDbs3JKhPEOHjw3GsW8YOU6LWkOBGCAGogcrZs3DggOlWWqdde3vT4CX/cf5+3brS+VaUj6bIG2bARwNo+1hbYjaqTVjnNp0j61oWUWuiiFoTRasHWxnTxh+Mx8rWCq8WXsXuI2oXCW6EqIXy8uDUKdMg5uBBdTK7oqytoWVLaNNGXR26cBDj7S3Bi6hYGo0Gr+ZeeDX3ouPkjigGhcQjicRsjCHpRBKuDVyNaTe9tokzq8/gVM9JbcLqE0hQnyDcG7lLsFPLSHAjRA1mMKgT1kVHa1i/viFr1miJjITDhyErq3h6OzsIC4O2bdVgpm1baNVK+r2IqkOj1eAT5oNPmE+xc9b21lg7WJNxOYOjS49ydOlRANwauhEyJMQ4VF3UfBLcCFGNpaerfWLyh04XHUp98WL+WkfWQBuTa52dCwKY/J/NmkEtnZdO1AAjfxtJXk4el/Zc4uyGs5zbeI6Luy+SEpvC1VOm7atb3tqCVwsvAnsF4ugpfXZqGgluhKjCdDo4eRKOHzcNYPK3a9dufQ8rK6hfX6FOnST69/egfXsr2rZVF2+UzryiprG2syagRwABPQJgNuSm5xK7IxatdcGbPeNyBpvf2KzuaMAnzIegvkE0v685DTo3QKOVJqzqToIbIaqI7Gw4csS0D8zhw+p8MaWpU6dgOHVJm68vKEoeq1fvZPDgwdjIEFpRi9g62xIcEWxyTK/T0/HpjsRsjOHKsSskRCaQEJnAro924drAlV5v9qLNo21uckdRHUhwI4QFpKWpQ6vzg5gDB9TaGX0Js9C7ukJoqNqBt6TgxdW1+DVFqU1TQggA1/quDPpkEKAuFRGzKYYzf53h1KpTpF5MNZlDJz0hnZTYFPw6+Emn5GpEghshKtjVq6ZBzMGDcOZMyRPc1a2r9n3J39q0gUaNpPlIiIri7ONM6EOhhD4USl52HlHrokwmETz03SH+efkf6gTWocUDLWg5siW+7Xwl0KniJLgRwkwMBnWCu8hI0+3ixZLTN2hgGsS0bQv168vQaiEsxdremmb3NDM5lpuRi42TDcnnktn5wU52frCTOkF1aDmyJS1HtsSnjY8EOlWQBDdC3IbsbDh2zDSIOXSo5HliQO28WziIadMGvLwqMcNCiNvSe3Zv7nr5LqLWRnHs52Oc/uM0yTHJ7Pi/Hez5ZA8vXXlJFvmsgiS4EeIWkpKK18acPFly/xg7O3VemPDwgq1167L1ixFClF9OXg6X0i4BYGtli62VLXZWdupPazu0mjtv07VxtKH5fc1pfl9zdJk6zqw+w7Gfj2HjaGMS2Pww8AdsHGzwbeeLbztf/Nr54VTP6Y6fX5SfBDdCoE5oFx2t9oU5cwZOny74mZBQ8jWenqZBTHg4NG0q88QIYU56g55LaZeIuR5DTHIMMddjOJdyzrh/KfUSCjdfodVKY2UMdEoKfvKPOdo44u3kjY+zD77OvupPF1/jY1c7VzQaDTaONrQY0YIWI1qYPM+VE1eIXhcNqIt95nNt4IpvO1+a39+csEfCKqaQgOTsZA7FHWLb9W3Ui6tHmF8Yjja1d/4eCW5ErZGbq/aJKRrAnDmjToRX2grWjRsXD2Skf4wQas1JfnChoeAPIr8fSv6xwv1SCh8zKAaSdcnsvbSXC+kXCoKYG4FMbEosOkPpw/3sre2x0liRq88tllav6MnKyyIrr4QpucvBwdrBGPCYBEDOvvi6+FLXvi6D1g0i50gOVw5cIW5/HFdPXyX1YiqpF1OpE1jHGNzkpuey/OHl+LYtqOFx9nEuUz5Sc1I5fuU4xy4f49gVdTt6+ShxaXHGNB8t/gitRkuIRwhhPmG0rtea1t6tCfMJw9/V36x9hAyKgQspF4i6FkXUtSjOXDtD1LUo7K3tWTpiqdmep7wkuBE1jqKoC0Bu3ao2IeUHMefOldyUlM/VVV07KSSkYGvSRJ21V5qVhDnp9DoydZm42btZOiu3JVefyy/HfmH+nvnsi9tnnpseu/kpa601AW4BBLkHEVTnxuYeRGCdQILqBFHPqZ7xA1tRFHL1ucYtR59T8Dgv56bHM3QZJKQnkJCeQHx6vPozLZ749HhSc1LJyssyBl2l0aDBq40XPt198Lb3xjXHFYdrDhgCDCQfTcbX2Rf9ST2H1h7i5O8njYGei58Lvu18adi9Ic2GN8M+wJ4TSSc4evmoSSATmxJ70+f2d/XHSe/EVeUqVzKvcOrqKU5dPcXPx342pqljX4fW3q1pXU8Ndlp7t6ZVvVal1vLoDXoupl40Bi5nrp4h6rr68+z1s+Toi0/G5WbnhqIoFutsLcGNqPYMBrVz79atsG2b+jM+vuS0jo6mgUvhQMbLS2piRMW4nHGZXRd2seviLnZe2Mm+uH1k5WXhbu9OI/dGxbbG7o3xd/PHWlu1/kUnZSbxzf5v+Pzfz01qCu6UBg31XeqbBCzGQMY9iPou9bHSlm3ySY1Gg521HXbWdmbLX6YusyDwuRHw5D9OyCg4djnjMgbFwOWMy1zOuGx6kzM3tnzTwdZgi0umCw7XHXBOd8Ypw4m0g2mkZ6UTr8TftLnN19mXVvVa0dKrJS3rtaRVvVa08GqBg9aB1atXM2jQIK7lXuNw4mEOJRzi8GX154mkEyRnJ7P1/Fa2nt9aUGZoCPEMUWt3vMPwcPAg+lq0MZi5WQCTz0ZrQyP3RgR7BBPiEaL+9AxBQTGpzatMVesvR4gy0Olg/341kNm2DbZvh+vXTdPY2kKHDtC5s9oPJj+Y8fWVAKY8rmRcYfO5zWyI2cCui7uw0lhRx74O7g7u1LGrQx37OgX79oX27Qv2HW0ca9VQWb1Bz9HLR9l5YacxmIm+Hl1i2uvZ19kfv5/98fuLnbPSWBFQJ0ANeOoUCX48GlPHvk4Fv5ICJ66cYP7u+Xx3+Duy87IB9QN2cofJjA8fj4udC6DWmgAmH8pKofbeko7n6nLZsXEH9wy9B5sq2mHN0cbRWPal0Rv0JGUmFasBKrrl1wblanO56nwVirZI3Simek71CMgLQLNVQ7BtMO2atqNXr16E9grFxqF4WeluzNap0WjwcfbBx9mHAY0HGM/n6nM5mXRSDXgSD3MoUf2ZmJHI6aunOX31NL8e/7XE15YfwIR4hhDsrgYv+cFMVQzEq1ZuhChBZibs3l1QK7N7t3qsMCcn6NoVevSA7t2hY0dwcLBMfquz1JxUtpzbwsaYjWw8t5HDiYfv+J42WhtjoONq54qNlQ02WhvjT2uttckxa621+vgm57wcvWjr25Ywn6rRYfJ61nV2X9xtDGb2XNpDem56sXQtvFrQtUFXuvh3oat/Vxq4NuBc8jnOXj9r3KKvR3P2+llirseQo88xHi+Ju7074T7h9ArsRa/AXnSq38mstRWKovB39N/M3zOftVFrjcfb+LTh+c7PM6rVKGyt7nwItE6nw0ZbNYOa8rLSWuHt7I23szdhlN55OFOXSWJ6oknAk5ieSD2nerSs15KWXi3xcvJiw4wNbF+7HRRII40/5vzBGvs1NOzekMYDGtNmQhscPMr2z87WylZtkvJubXI8MT2Rw4mHjQFPSk4Kjd0bm9TENHRrWObas6pAghtR5WRnw6ZNGr79tgXvvWfFgQPFlw/w9IS77ioIZtq0AWt5N5dbli6LHRd2qMFMzEb2xe1Dr5h2TAqtF0rfoL70DOyJnZUdydnJJGcncz37uvFxiftZ19ErenQGHVcyr3Al84pZ867VaGletzltfdvSzrcdbX3bEu4TbqxFMDeDYiAuLY6opCjWX13P73/9zu5LuzmRdKJYWhdbFzo16GQMZjrV74S7g3uxdK3qtaJVvVYlPld8WnyxoCd/S8xI5Hr2dTad28Smc5sAtVNtV/+u9ApQg52O9TveVrCTpcvi+8Pf8/Gejzl+5TigNlsMbzac5zo/R/eG3WtVTVxFcbRxVJve3INKTdf3nb50eb4LZzecJfrvaM7+fZbUi6mcXX+Ws/+cJXx8uDHt5aOX0V0v/1or3s7e9HfuT//G/ct9bVUlHwfC4hRFnTdm3Tp127IFsrKsgRBjmvr11UAmP5hp3lyWJLgdOr2OvfF7jTUzOy/sJFefa5ImxCOEPkF96BPUh16BvajnVO+2nktRFDJ0GSYBT0p2CjqDjjxDHjq9Dp1Bh05/Y//G41udj02NZX/cfhIzEo2dLL8//D2gfgg38WxiEvC08W1TpiYcRVG4mnXVZMhx4VE751POm5bVhYKHwR7BdPXvSpcGaq1MS6+Wd/QtV6vRUt+1PvVd69M9oHux8xm5GURdi2LXxV1sPreZzec2k5iRaAxSQR3d09W/q7Fmp2P9jqXWtMSnxfP5v5/z1b6vuJp1FQBnW2cmtpnIM52euWWTjKg4jnUdaTWqFa1GtUJRFJJOJhH9dzTXz17HsW5B7eXfz/9N7JZYLs6+iF87P/za+xlHY5W1dqem0ChKaQNga57U1FTc3NxISUnB1cxDYHQ6HatXr76x8nLNqGatKMnJsGEDrF0Lf/8NsUUGAPj5KTRrdoExY/zo3duawEDpK3O7cvW5/Hfff1m4YyGnsk+RocswOV/fpT59G/WlT2Afegf1pqFbQwvltHzi0uI4EH+A/XH7OZBwgAPxB7iYWvJaF43dG9PWt60a7Pi0IUefUyx4iUmOKbE5qTArjRX+rv646F2ICI2ge0B3OjfofNsBoLkoisLJpJNqoHNeDXaKdmh1sHagW8NuxpqdDvU7YGtly4H4A8zbPY9lR5cZh1EH1gnkmY7PMKHNhAof0SX/N81DMSgs6LqAS3sulXi+QZcGTNw50bivy9KV2G+nKivP57cEN2Ykf6Q3p9fDvn0FtTN79pgOy7azU2tlIiLUrUkTHWvWSFneCUVRWH5iOS//87JJh1ZPB09jzUyfoD6EeITUmGaGxPREDiYcVIOe+P0ciD/AueRz5bqHr7NvsSHHQXXUUTz+bv4oeqXK/50risKJpBPGWp3N5zYXaxZ0tHEkqE4Qx64UjMG+q+FdPN/5ee5ueneldRCV/5vmo9PpWPXzKlrXa83lyMvE748nbl8c16Ov02RoEx764yFj2rn152LtYF1Qu9PeD9+2vti72VvwFZSuPJ/fVaJZ6vPPP+eDDz4gISGBsLAwPv30Uzp27HjT9MnJycyYMYPly5dz7do1AgICmD9/PoMHD67EXItbuXSpIJj55x+4ds30fLNmaiAzcKAa2DgW6htatI9NVWJQDCRnJ3MlQ+1HkpSZZPo48wpXMgoeZ+RmMLTJUF7q+hIt67WslDzuubiHF/5+gR0XdgDg7eRNhGsETw9+mrb125plSvqqyNvZm4HBAxkYPNB47GrmVZOA53DiYeMHe9EhxwFuATjYlF59r9NX4TfnDRqNhhZeLWjh1YKnOjxlDHY2xWwy1uwkZSZx7MoxrLXWjGw5kuc7P097v/aWzrq4Q9bO1gT2CiSkf0GzfnZyNtnJ2cb99MR00uLUhfCuR1/n2LKCANcjxIOWI1vS5+0+lZfpCmDx4GbZsmVMnTqVr776ik6dOjF//nwiIiI4deoU9eoVr+rNzc2lf//+1KtXj19//ZX69etz/vx56tSpU/mZF8VERcHSpfDLL3C4yEAbNzfo16+gdqZhFW79UBSFA/EH+OX4L0RfjzYJVq5mXi3W6fZWvj30Ld8e+pahTYYyres07mp4V4XUlsRcj2H6huksO7YMUJsiXur6Es91fI6t/2wlzDusxgY2N+Pp6Em/Rv3o16ifpbNiMYWDnckdJ6MoCsevHOfo5aPc1fAu6rvWt3QWRQWyr2OPfZ2CGhlnb2emXZ1G3P44Y+1O/P54ks8lc+3MNXSZBQF8Xk4eW9/eSuMBjfHv4o/Wunr8/7B4cDN37lwee+wxHn30UQC++uor/vrrLxYuXMgrr7xSLP3ChQu5du0aO3fuNFZhBgYGVmaWRREXL8LPP8NPP6lNT/k0GnVIdn4w07Fj1R/RFHUtiiVHlrDkyBJOXT1ValpXO1fqOtbFy9ELLyevgseONx7fOJadl81nez9j+Ynl/Hn6T/48/SedG3RmWtdp3NPsHrMEG8nZybyz9R0+2fsJufpcNGgYHz6et3q/RX3X+sb5L4QANdhpWa9lpdUkiqrHwcOBxv0b07h/Y+OxzKRM4vbHUSewjvFY7PZYtr29jW1vb8POzY5G/RoRPDCYxhGNcfOvujNsW/SjJjc3l/379zN9+nTjMa1WS79+/di1a1eJ16xatYouXbowefJkfv/9d7y8vBg9ejQvv/wyVlbFRyfk5OSQk1Mws2Jqaiqgtk2a+x9+/v1qwwfJlSuwfLmWn3/WsH27BkVRayGsrBT69FEYNcrAkCEKnp4F1yhK2ZubKrMsE9IT+OX4Lyw9vpR/4/41Hre3tmdoyFC6NehGXce6xs3L0QtPB89yDbPtdm83zvQ8w7zd8/j+yPfsvrib+36+jxCPEF7o/AJjWo25rWG7ufpcvjnwDW9vf5trWWq7X5/APrzf933CvcMB0/d6bXhvVjQpS/OS8jSfOy1LGzcbAvoEmNzD2smaFqNaEPNPDFlXszjx2wlO/KZOf1C3RV0GzBtAYO/AO898GZTndVm0Q3FcXBz169dn586ddOnSxXh82rRpbNmyhT179hS7plmzZpw7d44xY8bw1FNPERUVxVNPPcUzzzzDzJkzi6WfNWsWs2fPLnZ8yZIlODpafgKw6iQ93Zo9e3zZvr0+hw55YTAU1Di0aJFE9+6X6NIljjp1cku5S9WQqc9kV/IutiZv5UjaEQwYANCiJcwljB7uPejk1glHK/O/R67rrvNX0l+sSVpDhl4dueRu7c4wr2EM8ByAs/WtF9BTFIU9KXv4Lv474nLUafD97f0Z5zeOdi7takwHYSFE1aDoFTKjM0k7mEbqgVQyz2SCAZrOa4pDkNpPLe1IGtmx2bi2dcXO13wTSubLzMxk9OjRVX+01O0EN02aNCE7O5uYmBhjTc3cuXP54IMPiC9hQaGSam78/f1JSkqqkNFS69evp3///jWm139mJvz5p4aff9aydq2G3NyCD8127QyMHKkwYoQBf3/zPm9iaiJf/vUlPTv1pEGdBvg6++JsW7ZVc28mJy+HtdFr+enYT6yOWm2cRh6go19HHmr5ECOaj8Db2ftOs18maTlpLDy0kI/3fMzFNHUIs4utC4+1eYynOz5NfZeS+0Hsi9vHtA3T2H5hOwD1HOsxs8dMHg1/9KYjXGrie9NSpCzNS8rTfCqzLLOuZXF+83ma3tvU+GVq1fhVHF1yFCtbK6ZenoqNo3nzkJqaSt26dav+aKm6detiZWVFYmKiyfHExER8fHxKvMbX1xcbGxuTJqjmzZuTkJBAbm4utramk1TZ2dlhZ1c8grSxsamwX35F3rsy5OaqI5x++glWrYKMQtOitGgBDz0Eo0ZBSEh+zY15puRWFIXdF3fz1f6vWHZ0GTn6HN6Nedd43tnWGV9nX3xdfPF19sXH2cdkP/+nh4OH8Y/NoBjYcm4LS44s4dcTv5KcnWy8X1PPpowJHcPo0NE09mhcNDsVzsPGgxe7vcgznZ9h6dGlzNkxh2NXjjF3z1w+/fdTxrQew0tdX6KFVwsAzief59WNr7LkyBJAbTZ7ocsLvNzt5TLPylvd35tViZSleUl5mk9llKWNtw2ho0JNjgV0DyA9Ph0bRxsc3cxf612e12TR4MbW1pZ27dqxYcMGhg8fDoDBYGDDhg1MmTKlxGu6devGkiVLMBgMaG9MUXv69Gl8fX2LBTaifI4cgQUL4Icf4OrVguNBQWpA8+CD0KqV+SfTS8tJ48cjP/LVvq84lHjIeNzPzg9HJ0cS0hNIz00nPTedM9fOcObamVLupq6fkh/4XEy9yKW0gkmt/Fz8eKjVQ4wJHUO4T3iVaL6xtbJlbNhYHmn9CKvPrGbOzjlsPb+VxZGLWRy5mGFNhhHsEcwX/35Bjj4HDRoeCXuEd/q8QwPXBpbOvhBCAND+yfa0f7I9isHy0+dZfOzK1KlTGTduHO3bt6djx47Mnz+fjIwM4+ipsWPHUr9+fd577z0A/vOf//DZZ5/x7LPP8vTTT3PmzBneffddnnnmGUu+jGorJUWtoVm4EP4t6EuLr69aO/PQQ+rq2hURA0QmRPLVvq/48ciPxplh7a3tebDVg0wKm8SVyCsMGTIEGxsb0nPTiU+LJz49vvjPQo+vZV0jV59LbEossSnqtMd17OswovkIRoeOpkdAjyq7+JtGo2FIkyEMaTKE3Rd388HOD1hxYgV/nP7DmKZ3YG8+HPAhbX3bWjCnQghxcxqt5b80Wjy4GTVqFFeuXOGNN94gISGB8PBw1q5di7e32u8hNjbWWEMD4O/vz7p163j++edp3bo19evX59lnn+Xll1+21EuodhRFXV17wQL49VfIylKP29jA3XfDxIkwYACUMPjsjmXpsvj52M98tf8rdl/cbTze1LMpT7Z/knFh43B3cFdnLT202nje2daZEM8QQjxDSrqtUU5ejnGF3fi0eOys7egb1NesqyVXhs4NOvPbyN84ffU0H+38iJNXT/JS15cYEjKkStQ2CSFEVWbx4AZgypQpN22G2rx5c7FjXbp0Yffu3cUTi1LFxcG336q1NFFRBcdbtFADmkceAS+vinnuU0mn+Hr/1yyOXMz17OsA2GhtuK/5fTzZ/kl6BvQ0y4e2nbUdAXUCCKgTcMf3qgqaeDbh62FfWzobQghRrVSJ4EZUHJ0O/vxTraVZswYM6ohnnJ3VPjQTJ0KnThXT7JSrz+X3k7/z5b4v2XRuk/F4gFsAT7R7ggltJlTayCQhhBC1hwQ3NdTJk2pA8913cLnQ4sB33aUGNCNGqAFOeSiKQo4+h/TcdNJy0kjLTbvp48T0RJYdW0ZihjoSTqvRMiRkCE+2f5KIxhFVtt+LEEKI6k+Cmxrmn39g5kzYubPgmLc3jBsHEyZA06alX5+dl83/bf8/tl/YXmLQkmfIK1d+fJx9mNRmEo+1e4yGblV4MSkhhBA1hgQ3NUR2NkyfDvPnq/tWVjB4sFpLM3iw2ln4Vo5dPsbo5aM5nHj4lmkdrB1wsXPB2dYZF1sX08c39u9qeBf3NL0HGyuZu0IIIUTlkeCmBjh6FEaPVuepAfjPf+D119Xh3GWhKAqf7f2Ml9a/RI4+By9HL2b1mkV9l/olBjDOts43nQlXCCGEsDT5hKrGFAU+/RSmTYOcHKhXTx0JNWRI2e+RkJ7AhN8nsCZqDQADgwey6J5F+DiXPEO0EEIIUdVJcFNNJSTAo4/C2rXq/uDBamDjXY7BR3+e/pMJv0/gSuYV7Kzs+HDAh0zuMFnmURFCCFGtSXBTDa1apfalSUoCe3v46CO1KaqsMUmmLpMX/36RL/d9CUBr79YsuW8JLeu1rMBcCyGEEJVDgptqJDMTXngBvvpK3Q8LgyVL1En4yupg/EFGLx/NyaSTADzf+Xne7fsu9tb2FZBjIYQQovJJcFNNHDigdho+dUrdf/FFePttKGHB8xIZFANzd83l1Q2vojPo8HX25dvh39K/cf+Ky7QQQghhARLcVHF6vdrs9Npr6mzDfn7qEgr9+pX9HhdTLzJu5Tg2xmwE4N5m9/LNsG+o61i3gnIthBBCWI4EN1XYhQswdizkL691//3w9dfg6Vn2e/x2/Dce++Mxrmdfx9HGkY8HfszENhOl07AQQogaS4KbKurnn+GJJyA5GZyc4JNP1NFRZY1J0nPTeXbNsyyMXAhAe7/2/HjfjzTxbFJxmRZCCCGqAAluqpjUVHjmGbXpCaBjR/jxRwgOLvs99lzcw5jlY4i+Ho0GDdPvms6sXrNkpmAhhBC1ggQ3Vcj589CnD5w9C1otzJihzjRclqUTEtITWBe1jjVRa/j1+K/oFT0N3Rry/b3f0yOgR8VnXgghhKgiJLipQp57Tg1sAgLghx/UFbxvRqfXseviLtacWcPa6LVEJkSanH+w1YN8OeRL6tjXqcgsCyGEEFWOBDdVxObNsHKluuDlmjXQvHnxNLEpsayNWsvaqLX8c/Yf0nLTTM6392vPwMYDGdJkCJ3qd5JOw0IIIWolCW6qAIMBpk5VHz/5ZEFgk52Xzbbz29SAJnotx68cN7murmNdIhpHMDB4IAMaD6CeU71KzrkQQghR9UhwUwV89x0cPAhubjDuubN8tnc1a6LWsClmE1l5WcZ0Wo2Wzg06Myh4EAODB9LWty1ajdaCORdCCCGqHgluLCwjA159FUCh47Q36fjjLJPzfi5+DGw8kIHBA+nXqB/uDu6WyKYQQghRbUhwY2EffADxV7JwGjuR9bqfAOgZ0JPBIYMZGDyQ0Hqh0ndGCCGEKAcJbizo0iX4v88SYdxwMvx3Y6215sshXzKp7SRLZ00IIYSotiS4saCnZh0h+5GhUCcWd3t3fhv5G72Dels6W0IIIUS1JsGNhXy8+i9WeT0Idun4O4bwz4Q/ZWkEIYQQwgxkqE0lUxSFebvm89zeu8EuHe/M3kRO2S2BjRBCCGEmUnNTiXR6HU+veZqv938NGrCKnMTO+V/g4SBrPgkhhBDmIsFNJbmedZ0HfnmADTEbQNHA3x/ySt/naRQgI6GEEEIIc5LgphJEXYtiyJIhnL56GlucyP3pJ3xSh/HKy5bOmRBCCFHzSHBTwbac28J9P9/Htaxr1Hf2J/WrP8iNCuPt/4Gzs6VzJ4QQQtQ80qG4Ai08uJD+3/fnWtY1OtbvyMALe0mLCqN1axg/3tK5E0IIIWomqbmpAAbFwLT10/hg5wcAjGw5klebL6b9fxwA+OgjdfVvIYQQQpifBDdmlqXP4oHfHuCP038A8EaPN5jZayb3DteSlwdDh0K/fhbOpBBCCFGDSXBjRhdTL/Jq1KvEZMVgZ2XHgrsXMKb1GDZuhFWrwNoaPvzQ0rkUQgghajYJbszkUMIhBv04iPiseLwcvVj54Eq6+ndFr4cXXlDT/Oc/0LSpZfMphBBC1HQS3JiJt7M31lprGto35J/x/xDiFQLAd99BZCTUqQMzZ1o0i0IIIUStIMGNmfg4+7D6odUc2XmEwDqBAKSnw4wZ6vnXXwdPT8vlTwghhKgtZCi4GTX1bIqjlaNx/4MPID4eGjeGyZMtmDEhhBCiFpHgpoJcvKgGNwBz5oCdnWXzI4QQQtQWEtxUkFdfhaws6NED7r3X0rkRQgghag8JbirA/v0avv/+/9u7+5imzjYM4FeLUCkDpFZo6wcCOvALloB0xOnmYAImbijLcCNaiYGgQFSiW9ymyDJD4hJnthjMFj/2h6Jjmc5t79wYEzYNyKJBNBGiRMMWKIiL8jWhL33eP4x904GI89DTHq5fcpL2Oee017l5Em5OTzkPHu/dC6h4b0wiIiKXYXMjMSGAbdselHXtWiA2VuZARERE44xbNDf79+/HzJkzMXHiRJjNZtTV1Y1qv+PHj0OlUiEtLW1sAz6B2lojzp1Tw9cX2L1b7jRERETjj+zNzYkTJ1BYWIiioiJcunQJMTExSE5ORkdHx4j73bp1C1u3bsXixYtdlPTx+vuBL76YCwDYtg2YNk3mQEREROOQ7M3N3r17kZ2djaysLMydOxcHDhyAVqvFoUOHHrnP4OAgMjMzUVxcjPDwcBemHVlpqRpW6zMwGgW2bZM7DRER0fgk6z/xGxgYwMWLF7F9+3bHmFqtRlJSEmpqah653wcffIDg4GCsX78ev/3224jv0d/fj/7+fsfzrq4uAIDNZoPNZnvKI/i/zk5g9+4H5dy5cwAajRoSvvy48/BnI+XPaDxjPaXDWkqL9ZSO0mv5JMcla3PT2dmJwcFBhISEOI2HhISgsbFx2H3OnTuHgwcPor6+flTvUVJSguLi4iHjP/30E7Ra7TB7/Ds3bwbAz28hdLr/Iji4Gv/5j2QvPa5VVFTIHUFRWE/psJbSYj2lo9Ra9vX1jXpbj7r9Qnd3N9asWYPPP/8cer1+VPts374dhYWFjuddXV2YPn06li1bhoCAAEnzZWXZUF5eh5SUV+Dt7S3pa483NpsNFRUVeOUV1lIKrKd0WEtpsZ7SUXotH37yMhqyNjd6vR5eXl5ob293Gm9vb4fBYBiyfXNzM27duoUVK1Y4xux2OwBgwoQJaGpqQkREhNM+Go0GmmH+PbC3t7fkP3ytFpgy5e8xee3xirWUFuspHdZSWqyndJRayyc5JlkvKPbx8UFsbCwqKysdY3a7HZWVlUhISBiyfVRUFK5cuYL6+nrH8uqrr2Lp0qWor6/H9OnTXRmfiIiI3JDsH0sVFhbCYrEgLi4O8fHx2LdvH3p7e5GVlQUAWLt2LaZOnYqSkhJMnDgR8+fPd9p/0qRJADBknIiIiMYn2ZubjIwM3L59Gzt37oTVasVzzz2HM2fOOC4ybmlpgVot+zfWiYiIyEPI3twAQH5+PvLz84ddV1VVNeK+R44ckT4QEREReSyeEiEiIiJFYXNDREREisLmhoiIiBSFzQ0REREpCpsbIiIiUhQ2N0RERKQobG6IiIhIUdjcEBERkaKwuSEiIiJFcYv/UOxKQggAT3br9NGy2Wzo6+tDV1eXIu/I6kqspbRYT+mwltJiPaWj9Fo+/L398Pf4SMZdc9Pd3Q0AvIM4ERGRB+ru7kZgYOCI26jEaFogBbHb7WhtbYW/vz9UKpWkr93V1YXp06fjjz/+QEBAgKSvPd6wltJiPaXDWkqL9ZSO0msphEB3dzdMJtNjb6g97s7cqNVqTJs2bUzfIyAgQJETSw6spbRYT+mwltJiPaWj5Fo+7ozNQ7ygmIiIiBSFzQ0REREpCpsbCWk0GhQVFUGj0cgdxeOxltJiPaXDWkqL9ZQOa/l/4+6CYiIiIlI2nrkhIiIiRWFzQ0RERIrC5oaIiIgUhc0NERERKQqbG4ns378fM2fOxMSJE2E2m1FXVyd3JI+0a9cuqFQqpyUqKkruWB7j119/xYoVK2AymaBSqXDq1Cmn9UII7Ny5E0ajEb6+vkhKSsL169flCevmHlfLdevWDZmrKSkp8oR1cyUlJVi4cCH8/f0RHByMtLQ0NDU1OW1z//595OXlYfLkyXjmmWeQnp6O9vZ2mRK7t9HU86WXXhoyP3Nzc2VK7HpsbiRw4sQJFBYWoqioCJcuXUJMTAySk5PR0dEhdzSPNG/ePLS1tTmWc+fOyR3JY/T29iImJgb79+8fdv2ePXvwySef4MCBA7hw4QL8/PyQnJyM+/fvuzip+3tcLQEgJSXFaa6WlZW5MKHnqK6uRl5eHmpra1FRUQGbzYZly5aht7fXsc2WLVvw7bffory8HNXV1WhtbcWqVatkTO2+RlNPAMjOznaan3v27JEpsQwEPbX4+HiRl5fneD44OChMJpMoKSmRMZVnKioqEjExMXLHUAQA4uTJk47ndrtdGAwG8dFHHznG7t69KzQajSgrK5Mhoef4Zy2FEMJisYjXXntNljyerqOjQwAQ1dXVQogH89Db21uUl5c7trl27ZoAIGpqauSK6TH+WU8hhHjxxRfFpk2b5AslM565eUoDAwO4ePEikpKSHGNqtRpJSUmoqamRMZnnun79OkwmE8LDw5GZmYmWlha5IynCzZs3YbVaneZqYGAgzGYz5+q/VFVVheDgYERGRmLDhg24c+eO3JE8wr179wAAOp0OAHDx4kXYbDanuRkVFYUZM2Zwbo7CP+v50NGjR6HX6zF//nxs374dfX19csSTxbi7cabUOjs7MTg4iJCQEKfxkJAQNDY2ypTKc5nNZhw5cgSRkZFoa2tDcXExFi9ejKtXr8Lf31/ueB7NarUCwLBz9eE6Gr2UlBSsWrUKYWFhaG5uxrvvvovU1FTU1NTAy8tL7nhuy263Y/PmzVi0aBHmz58P4MHc9PHxwaRJk5y25dx8vOHqCQBvvfUWQkNDYTKZ0NDQgHfeeQdNTU34+uuvZUzrOmxuyK2kpqY6HkdHR8NsNiM0NBRffvkl1q9fL2MyImerV692PF6wYAGio6MRERGBqqoqJCYmypjMveXl5eHq1au8lk4ij6pnTk6O4/GCBQtgNBqRmJiI5uZmREREuDqmy/Fjqaek1+vh5eU15Kr+9vZ2GAwGmVIpx6RJk/Dss8/ixo0bckfxeA/nI+fq2AgPD4der+dcHUF+fj6+++47nD17FtOmTXOMGwwGDAwM4O7du07bc26O7FH1HI7ZbAaAcTM/2dw8JR8fH8TGxqKystIxZrfbUVlZiYSEBBmTKUNPTw+am5thNBrljuLxwsLCYDAYnOZqV1cXLly4wLkqgT///BN37tzhXB2GEAL5+fk4efIkfvnlF4SFhTmtj42Nhbe3t9PcbGpqQktLC+fmMB5Xz+HU19cDwLiZn/xYSgKFhYWwWCyIi4tDfHw89u3bh97eXmRlZckdzeNs3boVK1asQGhoKFpbW1FUVAQvLy+8+eabckfzCD09PU5/md28eRP19fXQ6XSYMWMGNm/ejA8//BCzZ89GWFgYduzYAZPJhLS0NPlCu6mRaqnT6VBcXIz09HQYDAY0Nzfj7bffxqxZs5CcnCxjaveUl5eHY8eO4ZtvvoG/v7/jOprAwED4+voiMDAQ69evR2FhIXQ6HQICAlBQUICEhAQ8//zzMqd3P4+rZ3NzM44dO4bly5dj8uTJaGhowJYtW7BkyRJER0fLnN5F5P66llJ8+umnYsaMGcLHx0fEx8eL2tpauSN5pIyMDGE0GoWPj4+YOnWqyMjIEDdu3JA7lsc4e/asADBksVgsQogHXwffsWOHCAkJERqNRiQmJoqmpiZ5Q7upkWrZ19cnli1bJqZMmSK8vb1FaGioyM7OFlarVe7Ybmm4OgIQhw8fdmzz999/i40bN4qgoCCh1WrFypUrRVtbm3yh3djj6tnS0iKWLFkidDqd0Gg0YtasWWLbtm3i3r178gZ3IZUQQriymSIiIiIaS7zmhoiIiBSFzQ0REREpCpsbIiIiUhQ2N0RERKQobG6IiIhIUdjcEBERkaKwuSEiIiJFYXNDREREisLmhogIgEqlwqlTp+SOQUQSYHNDRLJbt24dVCrVkCUlJUXuaETkgXjjTCJyCykpKTh8+LDTmEajkSkNEXkynrkhIreg0WhgMBiclqCgIAAPPjIqLS1FamoqfH19ER4ejq+++spp/ytXruDll1+Gr68vJk+ejJycHPT09Dhtc+jQIcybNw8ajQZGoxH5+flO6zs7O7Fy5UpotVrMnj0bp0+fHtuDJqIxweaGiDzCjh07kJ6ejsuXLyMzMxOrV6/GtWvXAAC9vb1ITk5GUFAQfv/9d5SXl+Pnn392al5KS0uRl5eHnJwcXLlyBadPn8asWbOc3qO4uBhvvPEGGhoasHz5cmRmZuKvv/5y6XESkQTkvi05EZHFYhFeXl7Cz8/Padm9e7cQQggAIjc312kfs9ksNmzYIIQQ4rPPPhNBQUGip6fHsf77778XarVaWK1WIYQQJpNJvPfee4/MAEC8//77juc9PT0CgPjhhx8kO04icg1ec0NEbmHp0qUoLS11GtPpdI7HCQkJTusSEhJQX18PALh27RpiYmLg5+fnWL9o0SLY7XY0NTVBpVKhtbUViYmJI2aIjo52PPbz80NAQAA6Ojr+7SERkUzY3BCRW/Dz8xvyMZFUfH19R7Wdt7e303OVSgW73T4WkYhoDPGaGyLyCLW1tUOez5kzBwAwZ84cXL58Gb29vY7158+fh1qtRmRkJPz9/TFz5kxUVla6NDMRyYNnbojILfT398NqtTqNTZgwAXq9HgBQXl6OuLg4vPDCCzh69Cjq6upw8OBBAEBmZiaKiopgsViwa9cu3L59GwUFBVizZg1CQkIAALt27UJubi6Cg4ORmpqK7u5unD9/HgUFBa49UCIac2xuiMgtnDlzBkaj0WksMjISjY2NAB58k+n48ePYuHEjjEYjysrKMHfuXACAVqvFjz/+iE2bNmHhwoXQarVIT0/H3r17Ha9lsVhw//59fPzxx9i6dSv0ej1ef/111x0gEbmMSggh5A5BRDQSlUqFkydPIi0tTe4oROQBeM0NERERKQqbGyIiIlIUXnNDRG6Pn54T0ZPgmRsiIiJSFDY3REREpChsboiIiEhR2NwQERGRorC5ISIiIkVhc0NERESKwuaGiIiIFIXNDRERESnK/wCAoCe3wBsHXgAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 0s - loss: 1.0456 - accuracy: 0.6484 - 331ms/epoch - 1ms/step\n",
            "313/313 [==============================] - 0s 673us/step\n",
            "\u001b[35mTest Accuracy: 0.65\u001b[0m\n",
            "\u001b[34mTest Loss: 1.05\u001b[0m\n",
            "\u001b[33mTest Precision: 0.65\u001b[0m\n",
            "\u001b[32mTest Recall: 0.65\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.65\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "# Defining Model with modified dense layers (Adding extra layers)\n",
        "optimizers = [SGD(clipnorm=1.0), RMSprop(clipnorm=1.0), Adagrad(clipnorm=1.0), Adadelta(clipnorm=1.0), Adam(clipnorm=1.0), Adamax(clipnorm=1.0), Nadam(clipnorm=1.0)]\n",
        "best_optimizer = None\n",
        "best_optimizer_acc = 0\n",
        "\n",
        "for optimizer in optimizers:\n",
        "  print(f'\\033[36mTesting {optimizer} optimizer\\033[0m')\n",
        "  # Defining the model\n",
        "  model = models.Sequential()\n",
        "\n",
        "  # Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "  # These extract the most important visual features from the image.\n",
        "  model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))\n",
        "  model.add(layers.MaxPooling2D((2, 2)))\n",
        "\n",
        "  # Adding Dense/Fully-Connected Layers.\n",
        "  # These contian the 'classification' part of the model.\n",
        "  model.add(layers.Flatten())\n",
        "  model.add(layers.Dense(64, activation='relu'))\n",
        "  model.add(layers.Dense(10))\n",
        "\n",
        "  # Fitting the model\n",
        "  test_acc = fit(model,verbose=0, optimizer=optimizer)\n",
        "\n",
        "  # Saving the best optimizer\n",
        "  if best_optimizer_acc < test_acc:\n",
        "    best_optimizer_acc = test_acc\n",
        "    best_optimizer = optimizer\n",
        "    \n",
        "  del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[36mBest Optimizer: <keras.optimizers.optimizer_v2.adam.Adam object at 0x000001E4B6F1C640>\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "print(f'\\033[36mBest Optimizer: {best_optimizer}\\033[0m')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mcD19CCdv27G"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mjR_gy0Pv27G"
      },
      "source": [
        "* The best model was the one with the Adam optimizer, this is because the Adam optimizer is an adaptive learning rate optimization algorithm that's been designed specifically for training deep neural networks.\n",
        "* The model with the Adam optimizer has a higher accuracy, precision, recall and F1-Score than the model with the SGD optimizer, whilst respectively incurring a lower loss.\n",
        "* The model with the AdaGrad and AdaDelta optimizers performed the worst, this is because the AdaGrad and AdaDelta optimizers are adaptive learning rate optimization algorithms that have been designed specifically for training deep neural networks, but are not as good as the Adam optimizer in terms of CNNs.\n",
        "* Surprisingly, the model with SGD optimizer performed better than the model with the AdaGrad and AdaDelta optimizers, this is because the SGD optimizer is a stochastic gradient descent optimizer that is not adaptive and thus was not overfitting in this case."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T20:18:47.087381Z",
          "start_time": "2023-11-20T20:18:47.070380Z"
        },
        "id": "KWQ600Wsv27G"
      },
      "source": [
        "### Q.7\n",
        "The original CNN architecture managed to achieve ~70% accuracy on the test set using 122,570 model parameters. Can you define your own CNN architecture and try to improve on the original model? Improvements include: achieving higher performance on the test set, comparable performance using significantly fewer model parameters, faster training time, different model architecture, etc...\n",
        "\n",
        "Note down which factors of your CNN architecture you found to be the most responsible for contributing to model performance."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "ExecuteTime": {
          "end_time": "2023-11-20T22:24:28.593470Z",
          "start_time": "2023-11-20T22:24:28.585471Z"
        },
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "7eKhayShv27G",
        "outputId": "35e69434-0615-441c-ed6a-32740f286d35"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_26\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_157 (Conv2D)         (None, 30, 30, 32)        896       \n",
            "                                                                 \n",
            " batch_normalization_242 (Ba  (None, 30, 30, 32)       128       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " conv2d_158 (Conv2D)         (None, 28, 28, 32)        9248      \n",
            "                                                                 \n",
            " batch_normalization_243 (Ba  (None, 28, 28, 32)       128       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " max_pooling2d_52 (MaxPoolin  (None, 14, 14, 32)       0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_167 (Dropout)       (None, 14, 14, 32)        0         \n",
            "                                                                 \n",
            " conv2d_159 (Conv2D)         (None, 12, 12, 64)        18496     \n",
            "                                                                 \n",
            " batch_normalization_244 (Ba  (None, 12, 12, 64)       256       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " conv2d_160 (Conv2D)         (None, 10, 10, 64)        36928     \n",
            "                                                                 \n",
            " batch_normalization_245 (Ba  (None, 10, 10, 64)       256       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " max_pooling2d_53 (MaxPoolin  (None, 5, 5, 64)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_168 (Dropout)       (None, 5, 5, 64)          0         \n",
            "                                                                 \n",
            " conv2d_161 (Conv2D)         (None, 3, 3, 128)         73856     \n",
            "                                                                 \n",
            " batch_normalization_246 (Ba  (None, 3, 3, 128)        512       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " conv2d_162 (Conv2D)         (None, 1, 1, 128)         147584    \n",
            "                                                                 \n",
            " batch_normalization_247 (Ba  (None, 1, 1, 128)        512       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dropout_169 (Dropout)       (None, 1, 1, 128)         0         \n",
            "                                                                 \n",
            " flatten_25 (Flatten)        (None, 128)               0         \n",
            "                                                                 \n",
            " dense_114 (Dense)           (None, 512)               66048     \n",
            "                                                                 \n",
            " batch_normalization_248 (Ba  (None, 512)              2048      \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dropout_170 (Dropout)       (None, 512)               0         \n",
            "                                                                 \n",
            " dense_115 (Dense)           (None, 256)               131328    \n",
            "                                                                 \n",
            " batch_normalization_249 (Ba  (None, 256)              1024      \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dropout_171 (Dropout)       (None, 256)               0         \n",
            "                                                                 \n",
            " dense_116 (Dense)           (None, 128)               32896     \n",
            "                                                                 \n",
            " batch_normalization_250 (Ba  (None, 128)              512       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dropout_172 (Dropout)       (None, 128)               0         \n",
            "                                                                 \n",
            " dense_117 (Dense)           (None, 64)                8256      \n",
            "                                                                 \n",
            " batch_normalization_251 (Ba  (None, 64)               256       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dropout_173 (Dropout)       (None, 64)                0         \n",
            "                                                                 \n",
            " dense_118 (Dense)           (None, 10)                650       \n",
            "                                                                 \n",
            " activation_7 (Activation)   (None, 10)                0         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 531,818\n",
            "Trainable params: 529,002\n",
            "Non-trainable params: 2,816\n",
            "_________________________________________________________________\n",
            "None\n",
            "\u001b[36mTraining Time: 129.79s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 1s - loss: 0.6929 - accuracy: 0.8155 - 595ms/epoch - 2ms/step\n",
            "313/313 [==============================] - 1s 1ms/step\n",
            "\u001b[35mTest Accuracy: 0.82\u001b[0m\n",
            "\u001b[34mTest Loss: 0.69\u001b[0m\n",
            "\u001b[33mTest Precision: 0.81\u001b[0m\n",
            "\u001b[32mTest Recall: 0.82\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.81\u001b[0m\n"
          ]
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1EAAAKaCAYAAADf3dNpAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAADiLElEQVR4nOzdd3gU1dvG8W8SQkgHQkmoCRBCDVUh9CpNuoqKgopIEelVOgKh9957ExCQpggKP5TehVAFQgmQhJpe3z/yGlwJkUCym3J/vPa63JnZ2XuybDnznHPGLDY2NhYRERERERF5JeamDiAiIiIiIpKWqBElIiIiIiKSBGpEiYiIiIiIJIEaUSIiIiIiIkmgRpSIiIiIiEgSqBElIiIiIiKSBGpEiYiIiIiIJIEaUSIiIiIiIkmQydQBJGVY1xlj6ggmEbj7W1NHMInomIx5zWwLCzNTRzAJMzLocWfMwyYmg76/M6rwqBhTRzCJTBn089zeKvXWM6zLdTPK84SemmWU50luqfeVExERERERSYVUiRIREREREUNmqrUkRn8dERERERGRJFAlSkREREREDGXUgaivSJUoERERERGRJFAjSkREREREJAnUnU9ERERERAxpYolE6a8jIiIiIiKSBKpEiYiIiIiIIU0skShVokRERERERJJAlSgRERERETGkMVGJ0l9HREREREQkCVSJEhERERERQxoTlShVokRERERERJJAlSgRERERETGkMVGJ0l9HREREREQkCVSJEhERERERQxoTlShVokRERERERJJAlSgRERERETGkMVGJ0l9HREREREQkCTJcI+rGjRuYmZlx+vTpN97XZ599RosWLd54PyIiIiIiqYqZmXFuaVSGa0Tlz58fPz8/SpUqZeooaYa5uRnDPq+Jz+qvebirP+dXdWXgJ9UMtlnQ/11C9w02uG0d96HBNmXdndk+4SP8tvXh9g+9mNW7MbZZLI15KG/kxPFj9OjWmfp1qlOudDF+3fuLwfq9v/xMl6++oFa1SpQrXYxLF31MlDR5LV28gHYfv08NrwrUr1WVPj27cePG9fj1d+/coWKZ4gnefvl5twmTJ7/g4CAmjhtLo/p1qFyhDO3bfsj5c+dMHSvFNXqnDmVLebxwGzt6pKmjpagTx4/xTdfO1KtVjTIlPdj3r/d8epBRP9cy6nH/24olC6lcrgRTJ3rHLwsPD2ei93e8U8uL2lUqMLBPDwIDA0yY8s0tXbSAdh+9T43KFahfsyp9enTjxvXrCW4bGxtL9y5fUdGzOL/tS3/veUk+Ga4RZWFhgbOzM5kyJTwcLDY2lqioKCOnSt36fOhFx2bl6TXjJ8p+Np8hC/bR+8PKdG1Z0WC7n45cw7X1tPhb+9Fb4te5ONmxY+LHXLv7iBpfL6X5wHWUcM3BwgFNjXw0ry80NJSiRYsxaPCwl64vW64C3Xv1NXKylHXy+DHeb/MxS1euY/b8xURFRdKtcwdCQ0IAyO3szO69Bwxunbp0w8bGhirVqps4ffIaNWwohw/9wWjv8Wz4YRteVarSuePnPLh/39TRUtTqdRv55beD8bd5C5cCUP+dhiZOlrJCQ0Pw8PBg0JDhpo6SYjLq51pGPe5/unD+HD9s2kARdw+D5dMmjePggV8ZO2EqcxetIMD/AQP79DBRyuRx8vgx3v/wY5auWsfsBS9+j/3TmlXLIe0WR5KXmblxbmlU2k2eiN27d1OtWjWyZs2Kk5MT7777LteuXQNe7M7322+/YWZmxq5du6hQoQJWVlYcPHiQESNGULZsWebPn0/+/PmxsbHhgw8+4MmTJ6/1vP987s2bN1O7dm1sbGwoU6YMhw4dMtjPwYMHqV69OtbW1uTPn5/u3bsTHByc/H+oV1S5ZD62/36Z3Ueu4nv/CT8cuMje49epWCyPwXYRkVHcfxQcf3scFBa/rlFldyKjouk5fTdXbj3kxCU/vpm6i5Y1i1MoTzZjH9JrqVa9Bl9370mduvUTXP9u0+Z06vI1lSt7GTlZypo5dyFNm7ekcBF3inoUY8Qob+75+eHjcx6IOzGRI0dOg9uv+/ZS752G2NjYmjh98gkLC2PvLz/Ts3dfKlR8iwIFCtL562/IX6AA369fa+p4KSp79uwGr++B/b+SP38BKr71tqmjpahq1WvSrUcv6tZL+D2fHmTUz7WMetx/CwkJZvi3/Rk0dCT2Dg7xy4OePePHLZvo0XsAFd+uTLESJRkycgznzpziz7NnTJj4zcyc96/vse/+/3vswnmD7S5d9GH18mUMGzXGREklLUmXjajg4GB69+7N8ePH2bt3L+bm5rRs2ZKYmJiXPmbgwIGMGzcOHx8fPD09Abh69SobNmzgxx9/ZPfu3Zw6dYquXbu+8fMOHjyYvn37cvr0aYoWLcpHH30UX/26du0aDRs2pHXr1pw9e5b169dz8OBBunXrlgx/mddz+Pxtapd3pUi+7ACULpQLr1L5+PnoNYPtqpctyM1NPTmzvDPTezYku4N1/DqrzBZERsUQG/t8+9DwuGOuUjp/yh+EJJugoGcAODg4Jrje58J5Ll/yoXnL94wZK8VFR0cRHR1NZisrg+VWVlk4dfKEiVIZX2RkBDu3b6N5y9aYpeG+7CIZ2STv0VStXpO3K1cxWH7R5zxRUVG89Y/Go6tbIZydXTh39rSRU6ac+O8xx+ffY2GhoQwZ2I/+g4eSI0dOU0VLXTQmKlHpcorz1q1bG9xfsmQJOXPm5MKFC9jZ2SX4mFGjRlG/vuEZqbCwMFasWEHevHkBmDlzJk2aNGHy5Mk4Ozsn6Xn/OQarb9++NGnSBICRI0dSsmRJrl69SrFixfD29qZt27b07NkTAHd3d2bMmEHNmjWZO3cuWbJkeeF5w8PDCQ8PN1gWGxOFmXnyvLyT1v6Bg60VZ5Z1JjomBgtzc4Yv/o11e5+fwdlz7C+2HrzEDb/HFMqTjZEdarF13IfU7LaMmJhYfjt1g/Fd6tGrTWVmbTqKbZbMjO5YGwDn7Am/JpL6xMTEMHmCN2XKlqeIe9EEt9n6w0bcChWmTNlyRk6Xsmxt7fAsU5aF8+bgVqgQTk452L1zB2fPnCZ/gQKmjmc0+/b+wrNnz2jWoqWpo4jIa9izeyeXLl5gyaoNL6wLDAzA0tISe3sHg+XZnXKk+XFRf4v/Hitn+D02eeI4PMuUpVbtuiZMJ2lJuqxEXblyhY8++ohChQrh4OCAq6srAL6+vi99TMWKFV9YVqBAgfgGFICXlxcxMTFcunTpjZ7370oXgIuLCwAPHjwA4MyZMyxbtgw7O7v4W4MGDYiJieH6SwZBent74+joaHCLurn/pceaVO/VKsGHdUvx2ZgteHVazJfjt9Hzg0q0fad0/Dbf/3qBHX9c4fx1f378/TKtBm+gYrE81ChTEACfGwF0HPcj3d+vxMNdA7ixsQc37j3m3sMgYv9ZnpJUbfzYUVy7doWxEyYnuD4sLIzdu3bQvEXrBNendaO9JxBLLA3q1KRSeU/Wrl5Jw0ZNME/DfbqTasvmTVStVoNcuXKbOoqIJNH9e35MmejNiDETsPpXVT2jGD9mFNeuXmHs+OffY/t/3cfxo4fpM2CQCZNJWpMuK1FNmzalYMGCLFy4kDx58hATE0OpUqWIiIh46WNsbd987MarPq+l5fMZ6f7uDvN3l7+goCA6depE9+7dX9h/gZec7R40aBC9e/c2WJar2dQ3OpZ/GtupLpPW/sH3v14A4Px1fwrkdqTfx1VY/XPCM5Pd8HuM/+NgCufNxm+nbgCwft951u87T65stgSHRhALdH+vEtf9HiVbVkk548d+x8ED+1mwZCW5c79YiQXYu+cnwkLDaNK0uZHTGUf+AgVYvGwVoSEhBAUHkTNnLgb06UXefBmjS+rdu3c4cvgPJk+baeooIvIaLvqc59HDQD77+Hl36+joaE6fPM7G9WuYNnsBkZGRPHv21KAa9TAwACenHKaInKziv8eWriT3P3oUHT96mNu3blG7aiWD7fv37kHZ8hVYsGSFsaOmDhnoBOHrSHeNqMDAQC5dusTChQupXj1uZrCDBw++1r58fX25e/cuefLETaBw+PBhzM3N8fDweGHb5Hre8uXLc+HCBYoUKfLKj7GysnrhjFJydeUDsLbKRMy/qkXR0bGYJ9KPNW8Oe5wcbLj3MOiFdQ8exU2S0a5hGcIioth7POEKm6QOsbGxTPAezW/7fmH+4uXkzZfvpdtu3bKJGrVqky17diMmND5rGxusbWx4+uQJf/xxkJ690+8MXv+09YfNZM/uRPUatUwdRUReQ8W3vVj9/VaDZaOHD6agmxuffvYluXPHzV587Mhh6tR7B4CbN65z754fpT3LmiBx8viv77H2HTrSvJXhON4PWzend7+BVK9Z25hRJQ1Jd42obNmy4eTkxIIFC3BxccHX15eBAwe+1r6yZMlC+/btmTRpEk+fPqV79+588MEHCY6HSq7nHTBgAJUrV6Zbt258+eWX2NracuHCBfbs2cOsWbNe6zje1M5DVxjQtiq37j/lwg1/yro70/39t1mxK26mHtsslgxuX50tBy5y72EwhfJkY0ynOly785A9x/6K30/nFhU5fP42QaER1K3gxthOdRm6cB9PgsNf9tSpSkhIMLf+0TXzzp3bXLrog4OjIy4ueXjy5DH3/Pziu2b+fS0lpxw50vQg1fFjR7F71w4mT5uFja0tAQH+ANjZ2RuM0bvle5NTJ44zffZ8U0VNcX/8/j9iY8HV1Y1bvjeZOnkibm6FaNailamjpbiYmBi2bdlM0+YtXnqJiPQmJDjYoDv2ndu3uejjg6OjIy558iTyyLQjo36uZdTjtrW1pXARd4NlWaytcXTMGr+8aYvWzJg8HkdHR2xt7Zg8fgylPctSyrOMKSIni/Fj/v97bHrC32N/zzz6b84uLomeOEz3VIlKVLr7JjQ3N2fdunV0796dUqVK4eHhwYwZM6hVq1aS91WkSBFatWpF48aNefjwIe+++y5z5sxJ0ef19PRk//79DB48mOrVqxMbG0vhwoVp06ZNkvMnl94zf2b4FzWZ3rMhObPa4BcYxOLtpxi74n8ARMfEUqpQLtq+40lWuyz4BT7jl+PXGbV0PxGR0fH7qVjMhSHtq2NnnZlLtwLpNnUna/f8aarDSrIL5/+k4xft4+9PnjgOgKbNWjBqzDj2/7qP4UO/jV8/sF9cF8tOXb6mc9dvjBs2GW3csA6ATh3aGywfPmosTZs/n1xg25bN5MrtTGWvqkbNZ0xBz4KYOW0K9+/fw9ExK3Xr1+fr7r0MuuimV4cP/YGf311atEyf490Scv78n3z5ebv4+5MmxF2QtFnzlnw3dpypYiWrjPq5llGP+1X07DsQc3NzBvXtQUREJJWqVKX/oKGmjvVG4r/HvvjX99h3ht9jIklhFqtR/QkaMWIEW7Zsib+eVFpjXSdjXuMgcPe3/71ROhQdkzHfxhYWaXdq1DdhlkGvBJmGZ8J9IzEZ9P2dUYVHvfxyLOlZpgz6eW5vlXqrPda1vzPK84T+mjYb6an3lRMREREREUmF0l13PhEREREReUMaE5Uo/XVeYsSIEWm2K5+IiIiIiKQcVaJERERERMRQRh2I+opUiRIREREREUkCVaJERERERMSQxkQlSn8dERERERGRJFAlSkREREREDGlMVKJUiRIREREREUkCVaJERERERMSQxkQlSn8dERERERGRJFAlSkREREREDGlMVKJUiRIREREREUkCNaJERERERESSQN35RERERETEkCaWSJT+OiIiIiIiIkmgSpSIiIiIiBjSxBKJUiVKREREREQkCVSJEhERERERQxoTlSj9dURERERERJJAlSgRERERETGkMVGJUiMqnXr402BTRzCJ7G93M3UEk3h0bJapI4hICjE31w+ZjMQqU8bsJBQaGW3qCKZhlTFf7/RAjSgRERERETGkMVGJ0l9HREREREQkCVSJEhERERERQ6pEJUp/HRERERERkSRQJUpERERERAxpdr5EqRIlIiIiIiKSBKpEiYiIiIiIIY2JSpT+OiIiIiIiIkmgSpSIiIiIiBjSmKhEqRIlIiIiIiKSBKpEiYiIiIiIIY2JSpT+OiIiIiIikupFR0czdOhQ3NzcsLa2pnDhwnz33XfExsbGbxMbG8uwYcNwcXHB2tqaevXqceXKFYP9PHz4kLZt2+Lg4EDWrFnp0KEDQUFBScqiRpSIiIiIiKR648ePZ+7cucyaNQsfHx/Gjx/PhAkTmDlzZvw2EyZMYMaMGcybN48jR45ga2tLgwYNCAsLi9+mbdu2nD9/nj179rB9+3YOHDjAV199laQsZrH/bLpJuhEaaeoEppH97W6mjmASj47NMnUEERFJBjExGfNnWWhktKkjmISTbeodWWPdarFRnid0c4dX3vbdd98ld+7cLF78PFvr1q2xtrZm1apVxMbGkidPHvr06UPfvn0BePLkCblz52bZsmV8+OGH+Pj4UKJECY4dO0bFihUB2L17N40bN+b27dvkyZPnlbKoEiUiIiIiIiYRHh7O06dPDW7h4eEJblulShX27t3L5cuXAThz5gwHDx6kUaNGAFy/fp179+5Rr169+Mc4OjpSqVIlDh06BMChQ4fImjVrfAMKoF69epibm3PkyJFXzq1GlIiIiIiIGDAzMzPKzdvbG0dHR4Obt7d3gpkGDhzIhx9+SLFixbC0tKRcuXL07NmTtm3bAnDv3j0AcufObfC43Llzx6+7d+8euXLlMlifKVMmsmfPHr/Nq0i9NUQREREREUnXBg0aRO/evQ2WWVlZJbjthg0bWL16NWvWrKFkyZKcPn2anj17kidPHtq3b2+MuPHUiBIREREREQNmRrrYrpWV1UsbTf/Wr1+/+GoUQOnSpbl58ybe3t60b98eZ2dnAO7fv4+Li0v84+7fv0/ZsmUBcHZ25sGDBwb7jYqK4uHDh/GPfxXqziciIiIiIqleSEgI5uaGzRcLCwtiYmIAcHNzw9nZmb1798avf/r0KUeOHMHLywsALy8vHj9+zIkTJ+K32bdvHzExMVSqVOmVs6gSJSIiIiIihoxTiEqSpk2bMmbMGAoUKEDJkiU5deoUU6ZM4YsvvgDiqmc9e/Zk9OjRuLu74+bmxtChQ8mTJw8tWrQAoHjx4jRs2JCOHTsyb948IiMj6datGx9++OErz8wHqkQlq2XLlpE1a9ZEtxkxYkR8ORHgs88+i39RRUREREQkYTNnzuS9996ja9euFC9enL59+9KpUye+++67+G369+/PN998w1dffcVbb71FUFAQu3fvJkuWLPHbrF69mmLFilG3bl0aN25MtWrVWLBgQZKypOnrRC1btoyePXvy+PFjU0cBXi1PUFAQ4eHhODk5AXGNqMePH7Nly5ZkzWLs60Q1eqcOfnfvvLD8gw8/5tshw42WIzmvE2VnY8Xwru/SrE4Zcmaz48yl2/SdsJETF3wBaF6nDF++V41yxQvglNWWSm28OXvZ8G+Q28mesT1bUqdyMextrbh84wETFv/Elr2nky0nmOY6UevWrGb50sUEBPhT1KMYA78dSmlPT6PnMJbFC+ezd8/PXL/+F1ZZslC2bDl69u6Lq1shU0dLURn1uAFOHD/GsiWL8bnwJ/7+/kydMZs6dev99wPTsA3r1rBh/Vru3on7LCtcxJ1OXbpSrXpNEydLWanpuFP6OlEnjh9jxbLFXLhwngB/f6ZMm0Xt//93HRkZyZyZ0zn4v/3cvnMbOzs7KlWuQveevcmVK/d/7PnNpOR1ohbNm82SBXMMlhVwdWPd5u08ffKYRfNmc/TwH9y750e2bNmoXqsuX3X5Bjt7+xTL9LfUfJ0ouw+WGeV5gjZ8ZpTnSW6p95VLp+zs7LCzszN1jGS3et1GYmKefwBevXKFzh0/p/47DU2Y6s3MHfYxJYrk4Yshy/Hzf8JHjd9mx7xvKN96NHf9n2BjnZk/Tl9j056TzB3WNsF9LPquHVntrXm/53wCHgfRplFFVo3/gqptJ3Dm0m0jH1Hy2b1rJ5MmeDNk+EhKly7D6pXL6dKpA1u3744/QZDeHD92lDYftaVk6dJER0Uzc/oUOnfswOZtO7CxsTF1vBSTUY8bIDQ0BA8PD1q0ak3vHhnjQt65cjvTo1dfChQsSGxsLD9u3UKPbl+zftMPFCnibup4KSYjHXdoaChFixajecvW9On5jcG6sLAwfHwu0LFTV4p6ePD06VMmjh9Lz2+6smb9JhMlTh5uhYswY+6i+PsWFnE/gf39/Qnwf0C3nn1xLVSYe353mTh2FAH+Dxg7cZqJ0kpaYNLufLt376ZatWpkzZoVJycn3n33Xa5duwbAb7/9hpmZmUFV5/Tp05iZmXHjxg1+++03Pv/8c548eRI/z/yIESMAePToEe3atSNbtmzY2NjQqFEjrly5Er+fv7vdbd++HQ8PD2xsbHjvvfcICQlh+fLluLq6ki1bNrp370509POGwX/t929btmzB3d2dLFmy0KBBA27duhW/7t/d+f4tJiYGb29v3NzcsLa2pkyZMmzcuPE1/8LGkz17dnLkyBl/O7D/V/LnL0DFt942dbTXksXKkhZ1yzJ42hZ+P3mNv24FMGb+Tq7d8qfj+9UBWLvjGN4LdrPv8KWX7qdymULMWbef4+dvcuNOIOMX/cTjZ6GUK5HfWIeSIlYuX0qr9z6gRcvWFC5ShCHDR5IlSxa2bE7bX7KJmbtgMc1btqJIEXc8ihVj1Jhx+PndxefCeVNHS1EZ9bgBqlWvSbcevahbr76poxhNrdp1qF6jJgULuuLq6sY3PXphY2PD2TOnTR0tRWWk465WvQZfd+9Jnbov/ru2t7dn3sIlvNOwEa5uhfAsU5aB3w7F58J5/PzumiBt8slkYYFTjpzxt6zZsgFxVcexk6ZTrWZt8uUvQMW3K9Pp6x78fuA3oqKiTJzatIx1nai0yqSNqODgYHr37s3x48fZu3cv5ubmtGzZMn6GjcRUqVKFadOm4eDggJ+fH35+fvTt2xeI6yJ3/Phxtm3bxqFDh4iNjaVx48ZERj7v4xYSEsKMGTNYt24du3fv5rfffqNly5bs3LmTnTt3snLlSubPn2/QgHnV/Y4ZM4YVK1bw+++/8/jx4/hpGF+Ft7c3K1asYN68eZw/f55evXrxySefsH///lfeh6lFRkawc/s2mrdsnWbfHJkszMmUyYKwCMN+kWHhkVQpV/iV93P4zF+8904FsjnYYGZmxvsNKpDFKhMHjr/Y+E4rIiMi8LlwnspeVeKXmZubU7lyFc6eOWXCZMYV9OwZAA6OjiZOYlwZ9bgzoujoaHbt3EFoaAhlypQzdRyjyajH/TLPnj3DzMwMe3sHU0d5I7d8fWn2Ti3ea9qAEYP7cy+RRmFQ0DNsbe3IlEkdtuTlTPqvo3Xr1gb3lyxZQs6cOblw4cJ/PjZz5sw4OjpiZmZmMKf7lStX2LZtG7///jtVqsT9yFu9ejX58+dny5YtvP/++0Bcv9+5c+dSuHDcD+L33nuPlStXcv/+fezs7ChRogS1a9fm119/pU2bNkna76xZs+KnSFy+fDnFixfn6NGjvP124lWZ8PBwxo4dyy+//BI/DWOhQoU4ePAg8+fPp2bNhPtmh4eHEx4ebrAsxvzV59xPbvv2/sKzZ89o1qKlSZ4/OQSFhHP4zF8M6tiIS9fvcz/wKR80rEglTzeu3fJ/5f180n8JK8d/wd39E4iMjCYkLII2vRfy162AFEyfsh49fkR0dPQL3facnJy4fv0vE6UyrpiYGCaMH0vZcuVxdy9q6jhGk1GPO6O5cvkSn378IRER4djY2DB1xmwKFyli6lgpLqMed2LCw8OZMXUSDRs1SdNDEUqW9mTIyDEUKOhKQIA/SxbMpUuHdqz6fiu2trYG2z5+9IilC+fRrNX7JkqbeqTVE+HGYtJK1JUrV/joo48oVKgQDg4OuLq6AuDr6/va+/Tx8SFTpkwG87w7OTnh4eGBj49P/DIbG5v4BhRA7ty5cXV1NfiQyJ07d/zFuF51v5kyZeKtt96Kv1+sWDGyZs1qsM3LXL16lZCQEOrXrx8/dsrOzo4VK1bEd3NMiLe3N46Ojga3ieO9//P5UsqWzZuoWq1Gig9CTWlfDFmBmRn89fMYnhyZxtcf1WTD7uNJGvQ7/Ot3yWpvTaNOM6j6yQRmrNrHqglfULLIq0+hKanP2NEjuXblChMmTTV1FKPKqMed0bi6urFh0xZWrd3A+20+Yui3A7h29aqpY6W4jHrcLxMZGUn/vj2JBb4dOsLUcd6IV9Xq1KnfgCJFPahcpRqTZ84lKOgZ+/bsNtguOCiIvj264FaoMF926mqitJJWmLQS1bRpUwoWLMjChQvJkycPMTExlCpVioiIiPjGzD8nD/xnt7k3ZWlpaXDfzMwswWWv0rUwuQQFBQGwY8cO8ubNa7AusarSoEGD6N27t8GyGHPTVKHu3r3DkcN/MHnaTJM8f3K6fjuAd76cjk2WzDjYZeFewFNWjvuc63derYrkli8HXT6sSfnWo/H56x4A5y7foWr5wnRqU4PuY9alZPwUky1rNiwsLAgMDDRYHhgYSI4cOUyUynjGjh7Fgf2/sWT5KnIn4crmaV1GPe6MyDJzZgoULAhAiZKlOP/nOVavWsGwEaNMnCxlZdTjTkhkZCQD+vbC7+5dFixelqarUAmxt3cgf4GC3L71/KR9cHAwvbp1wsbGFu/JM8j0r9+EGZEqUYkzWSUqMDCQS5cuMWTIEOrWrUvx4sV59OhR/PqcOXMC4OfnF7/s9OnTBvvInDmzwcQPEHcBraioKI4cOfLCc5UoUeK1877qfqOiojh+/Hj8/UuXLvH48WOKFy/+n89RokQJrKys8PX1pUiRIga3/PlfPhGBlZUVDg4OBjdTdeXb+sNmsmd3onqNWiZ5/pQQEhbBvYCnZLW3pl6V4mz/7dwrPc4mS2YAYv51FYHo6FjM0/AHk2XmzBQvUZIjhw/FL4uJieHIkUN4puPxA7GxsYwdPYp9e/ewcMly8uVL25ODvKqMetzyXExMDJEREaaOYXQZ9bj/bkD5+t5k3sKlZM2azdSRkl1ISDB3bt/CKUfcb83goCB6du2IpaUlE6bOMtlvKElbTFaJypYtG05OTixYsAAXFxd8fX0ZOHBg/Pq/Gw4jRoxgzJgxXL58mcmTJxvsw9XVlaCgIPbu3UuZMmWwsbHB3d2d5s2b07FjR+bPn4+9vT0DBw4kb968NG/e/LXzvup+LS0t+eabb5gxYwaZMmWiW7duVK5c+T/HQ0HcrDh9+/alV69exMTEUK1aNZ48ecLvv/+Og4MD7du3f+38xhATE8O2LZtp2rxFuhiMWc+rOGZmcPnGAwrnz8nYXi24fP0+K7bFNR6yOdiQ3zkbLrniBtgXdY3rvng/8Cn3A59x6cY9rvo+YNaQjxg05QcCnwTTrLYndSt70KrHPJMdV3L4tP3nDP12ACVLlqJUaU9WrVxOaGgoLVq2MnW0FDP2u5Hs2rmdaTPnYGtjS4B/3Ng4O3t7gwv4pTcZ9bgBQoKDDbqX37l9m4s+Pjg6OuKShKvapyXTp06mWvUaOLu4EBIczM4d2zl+7ChzFyw2dbQUlZGOOyQkmFv//Hd95zaXLvrg4OhIjhw56de7Bxd9LjB99jxiYqIJCIh7zzs6OmJpmdlUsd/IzKkTqVajFs4ueQjwf8CiebOxMLegfsPG8Q2osLAwho8eR3BwEMHBcT2DsmbLjoWFhYnTm1DaPd9rFCb7pWtubs66devo3r07pUqVwsPDgxkzZlCrVi0grjGydu1aunTpgqenJ2+99RajR4+On8AB4mbo69y5M23atCEwMJDhw4czYsQIli5dSo8ePXj33XeJiIigRo0a7Ny584Xuekn1Kvu1sbFhwIABfPzxx9y5c4fq1auzePGrfwh/99135MyZE29vb/766y+yZs1K+fLl+fbbb98ouzEcPvQHfn53adGy9X9vnAY42mVh1DfNyJs7Kw+fhLB172mGz/6RqKi4Lp5NapZm4ahP47dfOf4LAEbP28mY+TuJioqhxTdzGd29ORund8LOxoprt/z5cthKfjr435OnpGYNGzXm0cOHzJk1g4AAfzyKFWfO/EU4pePufBvWrwWgw2efGiwfNdqb5um48ZhRjxvg/Pk/+fLzdvH3J02IG2varHlLvhs7zlSxUtTDh4EMGTQAf/8H2NnbU7SoB3MXLMarSlVTR0tRGem4L5z/k45fPD8pO3li3L/lps1a0LlrN/b/tg+AD99rYfC4hUuWU/GtSqRFD+7fZ/igfjx58pis2bLjWbY8C5avIVu27Jw8fpTzf54F4IPmjQwet2n7z7jkyZvQLkUwi42NTdlLY4tJhCbf8LE0JfvbGeOCmP/26NgsU0cQEZFkkJTJi9KT0Mjo/94oHXKyTb09dxw/XmmU53my5tP/3igVSr2vnIiIiIiImIQmlkicSac4FxERERERSWtUiRIREREREQOqRCVOlSgREREREZEkUCVKREREREQMqBKVOFWiREREREREkkCVKBERERERMaBKVOJUiRIREREREUkCVaJERERERMSQClGJUiVKREREREQkCVSJEhERERERAxoTlThVokRERERERJJAlSgRERERETGgSlTiVIkSERERERFJAlWiRERERETEgCpRiVMlSkREREREJAlUiRIREREREUMqRCVKlSgREREREZEkUCVKREREREQMaExU4lSJEhERERERSQI1okRERERERJJA3fnSqZCIKFNHMIlHx2aZOoJJlBq4y9QRTOLU6AamjmASEdExpo4gRhQemTFfb+vMFqaOYBJZLDPmcdtk1k/S1Ebd+RKnSpSIiIiIiEgSqNkvIiIiIiIGVIlKnCpRIiIiIiIiSaBKlIiIiIiIGFAlKnGqRImIiIiIiCSBKlEiIiIiImJIhahEqRIlIiIiIiKSBKpEiYiIiIiIAY2JSpwqUSIiIiIiIkmgSpSIiIiIiBhQJSpxqkSJiIiIiIgkgSpRIiIiIiJiQJWoxKkSJSIiIiIikgSqRImIiIiIiCEVohKlSpSIiIiIiEgSqBIlIiIiIiIGNCYqcapEiYiIiIiIJIEaUSIiIiIiIkmg7nwiIiIiImJA3fkSp0qUiIiIiIhIEqgRlUxq1apFz549X7re1dWVadOmJXm/I0aMoGzZsq+dS0REREQkqczMzIxyS6vUnc9Ijh07hq2traljJItF82azZMEcg2UFXN1Yt3k7AFs2bWDP7p1cuniBkOBgftp/CHt7B1NENYp1a1azfOliAgL8KepRjIHfDqW0p6epY7223A5W9G/iQY1iObHObMHNgBAGrD/Ln7efAmCT2YJ+TTyoXzI3WW0tuf0wlOUHb7D20K34fbSplJ9m5V0omdcRuyyZKDdkD8/Cokx1SK9l6eIF/Lp3Dzeu/4WVVRY8y5bjm559cHV1A+DunTs0a1wvwceOmziVeu80NGbcZJNR39+JHffTJ49ZNG82Rw//wb17fmTLlo3qteryVZdvsLO3N1Hi5BEdHc3yhXPYs3sHDx8GkCNHTho0ac6nX3Qy+HFz8/pfLJg9lTMnjxMdHU1Bt0KMHDeV3M4uJkyffFYsWcicmVNp8/Gn9Oo3CIBxo4dz7MhhAvwfYG1tQ+kyZfm6Rx9c3QqZOG3ymTt7JvPnzjJY5urmxpYfd5sokWksWbSAGdMm8/En7eg/cLCp40gaoUaUkeTMmTPR9ZGRkVhaWhopzZtzK1yEGXMXxd+3sHj+Tyk8LIxKVapSqUpV5s2cZoJ0xrN7104mTfBmyPCRlC5dhtUrl9OlUwe2bt+Nk5OTqeMlmYN1JtZ3q8zhaw/psOg4D4MjcM1hy9PQ5w2gb5sVw6uIE33WnuH2w1CqFc3ByFYlePAknL0XHgBgndmCAxcDOHAxgH5NPEx1OG/k5PFjvN/mY0qULEV0dDSzZ06lW+cOfL95O9Y2NuR2dmb33gMGj/lh4wZWLl9ClWrVTZQ6eWTU9/fLjtvf358A/wd069kX10KFued3l4ljRxHg/4CxE6eZKG3yWLtyCVs3b2DgsDG4FSrMJZ/zjB89FFs7e1q3aQvAndu36P5VOxo1a8VnHbtiY2vHjb+ukjlzZhOnTx4Xzp/jh00bKOJu+FlVrHhJGjRqSm4XF54+ecKiebPp0fVLNm/fg4WFhYnSJr/CRdyZv2hp/P30dGyv4s9zZ9n4/TqKFk2b31UpKS1XiYxBjahkFBUVRbdu3Vi5ciWWlpZ06dKFUaNGYWZmhqurKz179ozv8mdmZsacOXPYtWsXe/fupV+/fowYMYJx48YxdepUQkJC+OCDD/6z8WUqmSwscMqRcLY2bdsBcPL4UWNGMomVy5fS6r0PaNGyNQBDho/kwIHf2LJ5Ex06fmXidEnXqXYh/B6HMXD9ufhltx+GGmxT3jUbm4/f4ci1hwCsP3KLj7zy41nAMb4Rtex/NwCoVDi7cYKngJlzFxrcHzHKm/q1q+Ljc57yFd7CwsKCHP96D/y6by/13mmIjU3arjpn1Pf3y467cBF3xk6aHn8/X/4CdPq6ByOHDCAqKopMmdLuV+n5s6epWqM2XtVqAOCcJy97f97FxQvPPwMWz51BpSrV6fxN7/hlefPlN3rWlBASEszwb/szaOhIli6ab7CuResP4v8/T568dPq6O5+2aYnf3Tvky1/A2FFTTEKfZRlFSEgw3w7sx7ARo1k4f66p40gaozFRyWj58uVkypSJo0ePMn36dKZMmcKiRYteuv2IESNo2bIl586d44svvmDDhg2MGDGCsWPHcvz4cVxcXJgzZ85LH29Kt3x9afZOLd5r2oARg/tzz++uqSMZXWREBD4XzlPZq0r8MnNzcypXrsLZM6dMmOz11S2Zmz9vP2Hmp2U5MqIO23pVpU2lfAbbnLzxiLolc5HbwQqAyoWz45rDloOXA0wR2WiCgp4B4ODgmOB6nwvnuXzJh+Yt3zNmrBSRUd/fSTnuoKBn2NrapekGFEBJz7KcPH6EW743ALh6+RJ/njnJ217VAIiJieHwHwfIV6Ag/bp3omXDmnT54mMO7t9rwtTJZ5L3aKpWr8nblaskul1oaAg7tv1Anrz5yO3sbKR0xuHre5P6tavRpGFdBg3og18Geb8DjB09iuo1ahp8j8s/mBnplkal7U//VCZ//vxMnToVMzMzPDw8OHfuHFOnTqVjx44Jbv/xxx/z+eefx9//8MMP6dChAx06dABg9OjR/PLLL4SFhSX6vOHh4YSHhxsui7LAysrqDY8oYSVLezJk5BgKFHQlIMCfJQvm0qVDO1Z9vzXdjPt6FY8ePyI6OvqFbntOTk5cv/6XiVK9mfzZrfnYqwBLDtxg7t6/KJ3fkaEtShARHcsPx+8AMOoHH0a/X5Lfh9UhMjqG2Fj49vtzHPvrkYnTp5yYmBgmT/CmTNnyFHEvmuA2W3/YiFuhwpQpW87I6ZJXRn1/J+W4Hz96xNKF82jW6n0TpU0+H7frQEhwEO0/aIa5uQUxMdF06Nyd+g3fBeDxo4eEhoSwdsUSvujcjU7denH00EGGDejFlDmLKVv+LRMfwev7e2zfklUbXrrNxg1rmT1tEqGhoRR0dWPG3EVYWqaPbowApT09GTXaG1dXNwIC/Jk3ZzZftGvLxi0/YmtrZ+p4KWr3zh1c9LnA6nUbTR1F0ig1opJR5cqVDfqPenl5MXnyZKKjoxPcvmLFigb3fXx86Ny5s8EyLy8vfv3110Sf19vbm5EjRxos6zdoKAMGD0tK/FfmVfX5eI8iRT0oWdqTVk3qs2/Pbpq2aJ0izynGYWZmxp+3nzB512UALtx9SlFnOz6unD++EfVptYKULZCVr5ac4M6jUN4ulI0RLUvy4Gk4f1wJNGX8FDN+7CiuXbvComWrE1wfFhbG7l07+LJjFyMnS34Z9f39qscdHBRE3x5dcCtUmC87dTVF1GT12y8/8cvuHQwZNR7XQoW5evkSs6eOxylnTho2aU5MTAwAVWrU4v2P4rpyFilajPPnzvDj5u/TbCPq/j0/pkz0ZsbcRYmecGzY6F3eruRFYEAAq1csZfCA3ixYujrFTlIaW7XqNeP/v6hHMUqVLkPjd2rz8+5dtGyd9k8SvMw9Pz8mjBvDvIVL0s1rmRI0JipxakSZUHKd1R00aBC9e/c2WBYUZbyBofb2DuQvUJDbt3yN9pypQbas2bCwsCAw0LDhEBgYSI4cOUyU6s34Pwvn6v0gg2XXHgTTwDOu+4pVJnP6NCpK1+Un+c3HH4BLfs8onseBL2u6pctG1Pix33HwwH4WLFlJ7twJd+PZu+cnwkLDaNK0uZHTpbyM+v5O6LiDg4Pp1a0TNja2eE+eQaY0NBnQy8ybOZmP2nWgzjuNAChUpCj3791lzfJFNGzSHMes2bCwyISrW2GDxxVwdeNcGu22DHDR5zyPHgby2cfPu99GR0dz+uRxNq5fw4Ejp7GwsMDO3h47e3sKFHSllKcn9Wt4sX/fL7zTqIkJ06ccBwcHChR05ZZv+n6/X7hwnocPA/nog1bxy6Kjozl54hjr167m6MlzGW6CDUk6NaKS0ZEjRwzuHz58GHd391d+IxYvXpwjR47Qrl07g338FysrqxfOpEQGG2866ZCQYO7cvkXDJs2M9pypgWXmzBQvUZIjhw9Rp27cVNcxMTEcOXKIDz/6xMTpXs+J649wy2nYuHfLacPdR3GTS1hamJM5kzkxsbEG20THxGKezs5YxcbGMsF7NL/t+4X5i5eTN1++l267dcsmatSqTbbsaXcijZfJqO/vfx93cFAQPb/+isyZMzNh6qx0c/Y6PCwMc3PD4dHm5hbExsS9xy0tLSlWoiS3bt4w2Oa27800Pb15xbe9WP39VoNlo4cPpqCbG59+9mWC39uxsRBLLBGREcaKaXQhIcHcvnWLHE3T90QTlSpXZuMPPxosGzZkEG5uhfi8Q0c1oP6fKlGJUyMqGfn6+tK7d286derEyZMnmTlzJpMnT37lx/fo0YPPPvuMihUrUrVqVVavXs358+cpVCh1XZNi5tSJVKtRC2eXPAT4P2DRvNlYmFtQv2FjAAID/AkMDIg/g3vtyhVsbG1wdnbBwTGrCZMnv0/bf87QbwdQsmQpSpX2ZNXK5YSGhtKiZav/fnAqtPR/N9jQrTJd6hRi55l7eBZwpE3l/Az5/jwAQeFRHLkWyMB3ixEeeeH/u/Nlp2XFvIzddjF+PznsM5PT3oqCTjYAeLjYExwexd1HYTwJjTTJsSXV+LGj2L1rB5OnzcLG1paAgLjKm52dPVmyZInf7pbvTU6dOM702fNftqs0JaO+vxM77uCgIHp27UhYWBjDR48jODiI4OC4im3WbNnT9A8ur+o1WbV0Ablyu+BWqDBXLl/k+7UraNS0Rfw2bT75nFGD++JZrgLlKrzN0cMH+ePgfqbNWWK64G/I1taWwkXcDZZlsbbG0TErhYu4c+f2LX75aReVvKqSNVs2Hty/z4qlcV3/qvz/TIbpwZSJ46lRqzYuefLg/+ABc2fPxMLCnIaN3zV1tBRla2v3wvhWa2sbHLNmfem4V5F/UyMqGbVr147Q0FDefvttLCws6NGjB1999erTXLdp04Zr167Rv39/wsLCaN26NV26dOGnn35KwdRJ9+D+fYYP6seTJ4/Jmi07nmXLs2D5GrJlizsL/8PGDQYXrez6ZVxlbfCI0TRp1tIkmVNKw0aNefTwIXNmzSAgwB+PYsWZM38RTmm0O9+5W0/ouuwkfRt70K1+EW49DGXMVh+2nXo+W1OPVafp29iDyR+XIauNJXcehTJl12XWHHre/eNjrwJ0f+f5D5R1X1cGoP+6s2z+/7FVqd3GDesA6NShvcHy4aPG0rT583/H27ZsJlduZyp7VTVqvpSSUd/fiR33yeNHOf/nWQA+aN7I4HGbtv+MS568poicLLr3+ZYl82cxfeJoHj16SI4cOWna8j3adXg+vq96rbr0GjCMNcsXMXPKOPIXcGWk9xRKly1vwuQpK3NmK06fOsG6NSt59vQJ2Z1yULZ8BRYuW0P27GnvGoAvc//+PQb1783jx4/Jlj075cpVYMXqDWRPh1V1SToVohJnFhv7r345ki4EGrE7X2pia5UxzwuUGrjL1BFM4tToBqaOYBIR0TGmjiBGFB6ZMV9v68xpt8L3JrJYZszjzqisU/HQyiJ9jfPb4uqkRv+9USqUMX9xioiIiIjIS2lMVOJ0sV0REREREZEkUCVKREREREQMqBCVOFWiREREREREkkCVKBERERERMaAxUYlTJUpERERERCQJ1IgSERERERFJAnXnExERERERA+rNlzhVokRERERERJJAlSgRERERETFgbq5SVGJUiRIREREREUkCVaJERERERMSAxkQlTpUoERERERGRJFAlSkREREREDOhiu4lTJUpERERERCQJVIkSEREREREDKkQlTpUoERERERGRJFAlSkREREREDGhMVOJUiRIREREREUkCVaJERERERMSAKlGJUyVKREREREQkCVSJSqesMlmYOoIY0eER9U0dwSRqjP/N1BFMYl+/mqaOYBKPQyJNHcEkrC0z5ue5eQY9Cx5LrKkjiFGl3n/nGfQt+MpUiRIREREREUkCVaJERERERMSAxkQlTpUoERERERGRJFAjSkREREREJAnUnU9ERERERAyoN1/iVIkSERERERFJAlWiRERERETEgCaWSJwqUSIiIiIiIkmgSpSIiIiIiBhQISpxqkSJiIiIiIgkgSpRIiIiIiJiQGOiEqdKlIiIiIiISBKoEiUiIiIiIgZUiEqcKlEiIiIiIiJJoEqUiIiIiIgY0JioxKkSJSIiIiIikgSqRImIiIiIiAEVohKnSpSIiIiIiEgSqBIlIiIiIiIGNCYqcapEiYiIiIiIJIEaUSIiIiIiYsDMzDi3pLpz5w6ffPIJTk5OWFtbU7p0aY4fPx6/PjY2lmHDhuHi4oK1tTX16tXjypUrBvt4+PAhbdu2xcHBgaxZs9KhQweCgoKSlEPd+VKxESNGsGXLFk6fPm3qKAaWLJrPr3v3cOP6X1hZZcGzbDm69+yDq1uh+G3Cw8OZOmk8P+/eQUREJF5VqjJwyHCcnHKYMHny2rBuDRvWr+XunTsAFC7iTqcuXalWvaaJkyWvxfNns2TBHINlBQq6sXbzdgC6ffUZp04cM1jfvPUH9P92uNEyJpec9pnpUa8IVYs4kcXSnFsPQxmx1YcLfs8A6FTTjQalcuHskIXI6Bh8/J4xa99f/HnnqcF+qrk78VUNV9xz2xERFcOJm4/pvf6cKQ7pja1YspA5M6fS5uNP6dVvEABbNm3gp107uHTxAiHBwew5cBh7ewcTJ02ac6dPsHHNMq5c9OFhoD/DvKdSpUad+PUHf/uFnVu+58olH549fcLspespXLTYC/u58OcZls+fycUL57Awt6CQuwdjps7FyiqLMQ/ntbVp/g73/O6+sLzFex/Sq/8QAP48e5pFc2fgc/4c5hbmFHEvxqQZ87HKkjaOMSEbN6xl8/fr8Lsb9/ntVrgIX37VlSrVagDQuUM7Tv7rc63le20YNGSEsaMmuxPHj7Fi6WIuXDhPgL8/U6bPonbdevHrY2NjmTt7Jj9s/J5nz55Splx5vh06nIIFXU0XOplFR0czb84sdm7fRmBAADlz5qJpi5Z07NRFXdhSuUePHlG1alVq167Nrl27yJkzJ1euXCFbtmzx20yYMIEZM2awfPly3NzcGDp0KA0aNODChQtk+f/PrbZt2+Ln58eePXuIjIzk888/56uvvmLNmjWvnEWNKEmyk8eP8f6HH1OyZGmio6OZNWMqX3f+ko0/bMfaxgaAyRO8Ofi//YybNB17ezvGj/2Ofr2+YcmKtSZOn3xy5XamR6++FChYkNjYWH7cuoUe3b5m/aYfKFLE3dTxkpVb4SJMn7Mo/r6FheFHR7OW7/Fl527x97NksTZatuRinyUTy76owLHrj+m2+jSPQiIpkN2Gp2FR8dvcDAxh/M7L3H4UipWlBZ9Uzs+cT8rSfOYhHoVEAlC3eE6GNi3GrL3XOHr9EZnMzSicy85Uh/VGLpw/xw+bNlDE3cNgeVhYGF5VquFVpRpzZk41Ubo3ExYailsRD95p0oLvvu394vqwUEp6lqN6nQZMHz8ywX1c+PMMQ3p3pc2nX9Cl10AsLDJx/eolzMzSTieP+cvWER0dE3//+l9X6NOtI7XqvgPENaD69+hM28++pEffb7HIZMHVy5cwM087x5iQ3Lmd+bp7b/IXKEgssezYtpW+Pbuxct0mCv//53eLVu/zVddv4h+TFj/XEhIaGkpRj2I0b9maPj2/eWH9siWLWLt6JaPGjCNv3nzMmTWdrzt9yaatO7CysjJB4uS3bPFCNq5fy6gx4yhcpAjnz//JiCHfYmdnx8eftDN1PEnE+PHjyZ8/P0uXLo1f5ubmFv//sbGxTJs2jSFDhtC8eXMAVqxYQe7cudmyZQsffvghPj4+7N69m2PHjlGxYkUAZs6cSePGjZk0aRJ58uR5pSxqRKWwmJgYJk2axIIFC7h16xa5c+emU6dODB48mAEDBvDDDz9w+/ZtnJ2dadu2LcOGDcPS0pJly5YxcmTcF/ffZ0WWLl3KZ599ZsKjiTNr3iKD+yO/86ZerSr4XDhP+Ypv8ezZM7b+sIkx4ybydqXKAAz/zpv3mjfm3JnTlC5T1gSpk1+t2nUM7n/Toxcb1q3l7JnT6a4RZWFhgVOOnC9db5UlS6Lr04LPqxbk3pNwRmzziV9293GYwTa7/7xvcH/yT1doWT4P7rntOHr9ERZmZvRr6M60PVfZcsovfru/AkJSNnwKCAkJZvi3/Rk0dCRLF803WPdh27gfGSeOHzVFtGTxllc13vKq9tL19Ro2BeCe352XbrNg+kSav/cRbT7tEL8sfxo7W581W3aD+2tWLCJvvvyULf8WALOnTaB1m7a0bf9l/DYFCrqR1lWvWdvgftdverL5+3X8ee5MfCMqS5Ys5Ejjn2sJqVa9BtWq10hwXWxsLGtWrqDjV52pXacuAN+NHU+9mlX5de8vNGzcxJhRU8yZ06eoWbsu1WvWAiBP3nzs3rmD8+fSZo+BlGKsqlx4eDjh4eEGy6ysrBJstG/bto0GDRrw/vvvs3//fvLmzUvXrl3p2LEjANevX+fevXvUq/e8uuro6EilSpU4dOgQH374IYcOHSJr1qzxDSiAevXqYW5uzpEjR2jZsuUr5U7bp5LSgEGDBjFu3DiGDh3KhQsXWLNmDblz5wbA3t6eZcuWceHCBaZPn87ChQuZOjXurG6bNm3o06cPJUuWxM/PDz8/P9q0aWPKQ3mpoKC4rk4Ojo4A+Fw4T1RUJJUqV4nfxs2tEM4ueTh79rQpIqa46Ohodu3cQWhoCGXKlDN1nGR329eXZg1q8X6zBowY3P+F7j97du2gcZ2qfPJBc+bOnEpYaKiJkr6+mh45uOD3lAnvlWJv32qs/eotWpZ/+dmoTOZmtKqQh2dhkVy+F9ePupiLHbkdshATC2u/eoufe1dl1sdlKJzT1liHkWwmeY+mavWavP2P97E89/hRIBcvnCNrtuz06tSOD9+tTb+vv+DPMydNHe21RUZGsmfXdho1bYmZmRmPHgZy4c+zZM2Wna4d2tKiYQ26d/qMs6fT7jEmJDo6mp93x31+l/YsG798967t1K/lxYetmzJ7xpQ0+bmWVHdu3yYgwJ9KXs/f9/b29pTy9OTsmdOmC5bMypQtx9Ejh7h54zoAly5e5PTJk1R9SeNSUpa3tzeOjo4GN29v7wS3/euvv5g7dy7u7u789NNPdOnShe7du7N8+XIA7t27BxD/W/tvuXPnjl937949cuXKZbA+U6ZMZM+ePX6bV6FKVAp69uwZ06dPZ9asWbRv3x6AwoULU61a3NnPIUOGxG/r6upK3759WbduHf3798fa2ho7OzsyZcqEs7Nzos+TUAs+ksxGKbvHxMQwacJYypQrTxH3ogAEBvhjaWmJvYPhGAknJycCAwJSPJMxXbl8iU8//pCIiHBsbGyYOmM2hYsUMXWsZFWilCeDR4yhgKsrgf7+LFk4l65ftmPlhq3Y2tpSv2FjnJ3zkCNnLq5euczcmVPwvXkD70nTTR09SfJmy8L7FfOy6tAtFh+8Qck8DvRv6E5UdAw/nnn+oVrd3Ylx75Uki6UFAc8i6LzyNI9D47ry5csW192nc003Jv98hbuPw/jUKz8LPytHi5mHDboGpmZ7du/k0sULLFm1wdRRUi2//x8LuWrJPDp2600hdw/27trOoB5fMW/lJvLmL2jihEn3v9/2EhT0jEbvtgDg7p3bACxbOIcuPfpSpGgxft6xjd5fd2DZ2i3kK5D2jvGfrl65TId2HxEREY61tQ0TpsykUOG4z+8Gjd7FOU8ecubMxdXLl5g1fTI3b1xnwpSZJk6dsgIC/AHI7uRksNzJKUe6+v7+/MuvCAoOpmXTxlhYWBAdHc3X3XvS+N2mpo6WqhhreNigQYPo3duwW/XLfsPGxMRQsWJFxo4dC0C5cuX4888/mTdvXvxvbWNRIyoF+fj4EB4eTt26dRNcv379embMmMG1a9cICgoiKioKB4ekD8729vaO7/r3t0GDh/Ht0BGvEztJxo0ZxbWrV1i87NUH4qUnrq5ubNi0haCgZ+z5+SeGfjuAxctWpauGlFfV6vH/X8TdgxKlPWndpD779uymaYvWNG/1Qfz6wu5FyZEjB927dOD2LV/y5S9gisivxdzMjAt34yaKALh0L4giuWx5r0Jeg0bUsRuP+HDeMbLaWNKqQh4mvFeKTxcd51FIZHzXh0X/u8Fen7gfI8O3+vBTr6rUL5mLTSdeHMCf2ty/58eUid7MmLso3Yx/SAmxsXHjiBo3f493mrQAoEjR4pw6cYSftm/hiy49TJju9ezctpm3vaqRI2fcGdq/j7Fpq/dp3DSue0tRj+KcOH6YnT9u5quve5ksa3Io6OrKqvWbCQoKYt8vPzFy2CDmLVpBocJFaPne88+1Iu5FccqZk6+/+jzNfa5Jwn7evYtd239k7PhJFC5ShEsXLzJp/Fhy5spFs+av1pVLks/Luu4lxMXFhRIlShgsK168OJs2bQKILzzcv38fFxeX+G3u379P2bJl47d58OCBwT6ioqJ4+PDhfxYu/knd+VKQtfXLB6EeOnSItm3b0rhxY7Zv386pU6cYPHgwERERSX6eQYMG8eTJE4Nbn/6D3iT6Kxk/dhQHD/zG/EUryP2Pf3ROOXISGRnJs6eGM5YFBgbilCP9zM4HYJk5MwUKFqREyVL06NWHoh7FWL1qhaljpSh7ewfyFyzI7Vu+Ca4vUdoTgDsvWZ9aBTyL4C//YINl1wNCcHY0nIEsLDKGW49COXfnKSO3XSQ6Jja+219AUFxF+J/7iYyO5faj0Bf2k1pd9DnPo4eBfPbxe1StWJqqFUtz6sQxNqxdRdWKcZPJCGT//5lGC/xjVlKIGy/kf//Vu4OkFvf87nLi2GHebd46fpmTU9x4IFe3wgbbFnQtxP0kdHlJrSwtM5O/QEGKlyjJ1917417Ug/VrVia4ban//1y7lcY+15Lq7zFgDwMDDZYHBgakq+/vaZMn8vmXHWnYuAnuRT14t1lz2rb7jKWLFpg6WqpiZmZmlFtSVK1alUuXLhksu3z5MgULxlXG3dzccHZ2Zu/evfHrnz59ypEjR/Dy8gLAy8uLx48fc+LEifht9u3bR0xMDJUqVXrlLGpEpSB3d3esra0NXsi//fHHHxQsWJDBgwdTsWJF3N3duXnzpsE2mTNnfqUfLFZWVjg4OBjcUvIMcmxsLOPHjuLXfb8wb9Ey8ubLZ7C+eImSZMpkydEjh+KX3bj+F/f87uL5j/7m6VFMTAyRr9EQTktCQoK5c/vWSwdcX7l0EQCnnGlrQPbpW48p6GRjsKyAkzV+T8Je8og4ZmZmWFrEfZT63H1GeFQ0rjme7yeTuRl5slrj9zjx/aQWFd/2YvX3W1mxbnP8rXiJUjRo/C4r1m3GwsLC1BFThdwueXHKkZPbN28YLL9z6ya5nF0SflAqtuvHH8iaLTuVqz4fE+KcJy85cubi1r+O8ZbvTXK7pL1j/C8xMbEvPZF5+WLc51p6nGjin/Lmy0eOHDk5cvj593dQUBB/nj2LZzqZFAriZt/89yya5ubmxMTEvOQRklr06tWLw4cPM3bsWK5evcqaNWtYsGABX3/9NRD3ndyzZ09Gjx7Ntm3bOHfuHO3atSNPnjy0aNECiKtcNWzYkI4dO3L06FF+//13unXrxocffvjKM/OBuvOlqCxZsjBgwAD69+9P5syZqVq1Kv7+/pw/fx53d3d8fX1Zt24db731Fjt27OCHH34weLyrqyvXr1/n9OnT5MuXD3t7+1TRvWbcmFHs3rWdKdNnY2NrG9+H2s7OnixZsmBvb0/zlq2ZMmk8Do6O2NnZMcF7NJ5lyqabmfkApk+dTLXqNXB2cSEkOJidO7Zz/NhR5i5YbOpoyWrW1IlUrVELZ5c8BPg/YNH82ViYW1CvYWNu3/Jlz+4deFWrgaNjVq5eucSMyRMoW77iC9Nip3arDt9i2RcV+KJaQfacf0DJvA60Lp+X77bH/XjKYmnOl9Vd2X8pgICgCLLaWPLBW3nJ5ZCZPRfiugUER0Sz8fhdOtdy496TcPyehNG+SlzXn7+3Se1sbW3jZyf7WxZraxwds8YvDwzwJzAwgNu+cWflr125jI2tLbmdXXB0zGrsyK8lNCSEu7efVxXu3b3DtcsXsXdwJJezC8+ePuHBPT8C///z7bbvDQCyOeUgu1MOzMzMeO/jz1i5eC6F3D0o7O7Bnp3buHXzBoNHTzbFIb22mJgYdm3fQsMmzcmU6fnPAjMzMz785HOWLphNYXcPihQtxk87tuJ78zqjxk0xYeI3N3vGFLyqVsfZOQ8hIcH8tGs7J48fZcachdy+5ctPu7ZTpVrN+M+1qZPGUa5CRdyLpq3PtYSEhARzy/f5v/07d25z6aIPDo6OuLjk4eNP27FowTwKFHQlb968zJk1g5y5chlcSyqtq1GrNosXzsPFxYXCRYpw0ceHVSuW0aJl6/9+cAaSGq+Z9dZbb/HDDz8waNAgRo0ahZubG9OmTaNt27bx2/Tv35/g4GC++uorHj9+TLVq1di9e3f8NaIAVq9eTbdu3ahbty7m5ua0bt2aGTNmJCmLWWxsbGyyHZm8ICYmBm9vbxYuXMjdu3dxcXGhc+fODBo0iP79+7NkyRLCw8Np0qQJlStXZsSIETx+/BiImzCibdu27N27l8ePHydpivOg8JR7WSt4vnjBSYDh342lWfNWwPOL7f60awcRERF4Va3GwMHDUvwsXiYL473hhw/9lqOHD+Pv/wA7e3uKFvXg8w4d8apS1WgZ/haUghMWDBvUl9Mnj/P0yWOyZsuOZ9nyfNW1O/nyF+D+PT9GDR3IX9euEBYaSq7cztSoXZfPOnTG1i7lr41Uf/KBZN1fdXcnvqlbmAJO1tx5FMaqw7f44WTcOKbMFuaMbV2C0nkdyWpjyZPQSM7fecrC/93gwt1n8fvIZG7GN3UL08TTGStLc/68/ZSJP115oavgm9jXz7gXdO7yZXuKehSLv9juwnmzWDx/zgvbDRk5hnebpdx4gsf/fy2u5HDm5DEGfPPlC8vrNWpG3yHf8fOOrUwZO+yF9W2/6MynHbrE31+/cjE/bl7Ps6dPKFTEgw5de1KqTPlkywlgbZmy1b9jh3+nb/dOrPp+e4JTtK9evogfvl/Ls6dPKexelM7f9MGzbPIeY0KsM6fccX83YjDHjxwmIMAfOzt7ihQtSrvPvqSSV1Xu3/Nj2OD+XLsa97mWO7czNevU44uOXbAzwueaZaaU/R47fvQIHb94cQB+0+YtGDVmXPzFdjd/v4Fnz55StnwFvh0yjIKuaX9q+78FBwcxZ+YM9u39hUcPA8mZMxcNGzfhqy5dsbTMbNQsNpapr6HytxpTfjfK8xzobfzfTclBjah0KiUbUamZMRtRqUlKNqJSs+RuRKUVxm5EpRbJ2YhKS1K6EZVapWQjKjVL6UaUpC6puRFVc6pxGlH7e6XNRpTGRImIiIiIiCSBxkSJiIiIiIiB1DgmKjVRJUpERERERCQJVIkSEREREREDKkQlTpUoERERERGRJFAlSkREREREDGhMVOJUiRIREREREUkCVaJERERERMSAClGJUyVKREREREQkCVSJEhERERERA+YqRSVKlSgREREREZEkUCNKREREREQkCdSdT0REREREDKg3X+JUiRIREREREUkCVaJERERERMSALrabOFWiREREREREkkCVKBERERERMWCuQlSiVIkSERERERFJAlWiRERERETEgMZEJU6VKBERERERkSRQJUpERERERAyoEJU4NaLSKQ0GlIzg1/41TR3BJPJ/tsrUEUzi/qp2po5gEqER0aaOYBIxsbGmjmASZhm0k5B+sEtao0aUiIiIiIgYMEMt28RkzNMdIiIiIiIir0mVKBERERERMaChIYlTJUpERERERCQJVIkSEREREREDuk5U4lSJEhERERERSQJVokRERERExIAKUYlTJUpERERERCQJ1IgSERERERFJAnXnExERERERA+bqz5coVaJERERERESSQJUoERERERExoEJU4lSJEhERERERSQJVokRERERExIAutps4VaJERERERESSQJUoERERERExoEJU4lSJEhERERERSQJVokRERERExICuE5U4VaJERERERESSQJUoERERERExoDpU4lSJSka1atWiZ8+epo4hIiIiIiIpSJUoSbITx4+xYtliLlw4T4C/P1OmzaJ23Xrx6/f+8jMbN6zD58J5njx5wrrvf8CjWHETJk45J44fY9mSxfhc+BN/f3+mzphNnX/8LdKDxfNns2TBHINlBQq6sXbzdgC6ffUZp04cM1jfvPUH9P92uNEypoRNG9ax+ft13L17B4BChYvQ4asuVKlWA4Dbt3yZMWUiZ06fJCIiAq8q1egzcDBOTjlMGTvJ/pzZmoK57F5YvuCni/RZcoRcjlkY/UlF6njmwS5LJq74PWXi5rNsO+qb6D6GrznBlK1/pnj+lBQcHMScmTPYt/cXHj0MxKNYcfoPHEzJ0qVNHS3ZLJqXwPvb1Y11///+Hj96BMeOHibA/wE21jaUKlOWrt174+pWyBRxU8yKJQuZM3MqbT7+lF79BgGwZdMGftq1g0sXLxASHMyeA4ext3cwcdLkNXf2TObPnWWwzNXNjS0/7jZRIuPJCN/fb0rXiUqcGlFpSEREBJkzZzZ1DEJDQylatBjNW7amT89vElxftlwF6jdoxHcjhpogofGEhobg4eFBi1at6d2jm6njpBi3wkWYPmdR/H0LC8OPjmYt3+PLzs+PP0sWa6NlSym5cuema/de5C9QEIAd27bQr2c3Vq7bhEvevHTv0hH3oh7MXrAUgPmzZ9C3+9csXrkWc/O0U+Sv9e12zM2ff1GWKJCNH4e8ww+HbwCw4OvqONpmps2EfQQ+C+P9aoVY0asmNQbt4OyNh/GP+279KZbtvRx/PygsymjHkFJGDRvK1atXGO09npy5crHzx2107vg5m7buIFfu3KaOl2zcChdhxtyE398exUvwTqN3cXZx4emTJyyeP5teX3dk448/Y2FhYYq4ye7C+XP8sGkDRdw9DJaHhYXhVaUaXlWqMWfmVBOlS3mFi7gzf9HS+Pvp5XX9Lxnl+1tSjhpRryk4OJguXbqwefNm7O3t6du3r8H68PBwBg8ezNq1a3n8+DGlSpVi/Pjx1KpVK36bgwcPMmjQII4fP06OHDlo2bIl3t7e2NraAuDq6kqHDh24cuUKW7ZsoVWrVixbtsyIR5mwatVrUK16jZeuf7dpcwDu3rltrEgmU616TapVr2nqGCnOwsICpxw5X7reKkuWRNenRdVr1ja43+Wbnmz+fh1/njvLgwcP8Lt7hxXrNmFnF1eBGf6dN/VqVOb40cO8XbmKKSK/loBn4Qb3e5fPx7V7Tzl44T4AlTxy0mvRYU5cCwBg4uazdGtcnHKFnAwaUUFhkTx4Ema84CksLCyMvb/8zNQZs6lQ8S0AOn/9DQf2/8r369fydfeepg2YjDIl8v5u0fqD+P93yZOXr7p2p92HrfC7e4d8+QsYK2KKCQkJZvi3/Rk0dCRLF803WPdh23YAnDh+1BTRjMbCwoIc6ezz+1VklO/vN2GuQlSi0s7p0lSmX79+7N+/n61bt/Lzzz/z22+/cfLkyfj13bp149ChQ6xbt46zZ8/y/vvv07BhQ65cuQLAtWvXaNiwIa1bt+bs2bOsX7+egwcP0q2b4dmQSZMmUaZMGU6dOsXQoem7qiOp121fX5o1qMX7zRowYnB/7vndNVi/Z9cOGtepyicfNGfuzKmEhYaaKGnKiI6O5ufdOwkNDaWUZxkiIyMwMzMzqAxntrLC3NycM6dOJrKn1M3SwpwPqxVi1a9X45cdueRPay9XstlmxswMWldxxcrSgv+dv2fw2N7NS3NzURsOjnuXHk1LYpHGv32jo6OIjo4ms5WVwXIrqyycOnnCRKlSxi1fX5q9U4v3mib8/v5baGgIO7b9QJ68+cjt7GzklCljkvdoqlavmaZOfCQ3X9+b1K9djSYN6zJoQB/8XvL6i4ghVaJeQ1BQEIsXL2bVqlXUrVsXgOXLl5MvXz4AfH19Wbp0Kb6+vuTJkweAvn37snv3bpYuXcrYsWPx9vambdu28RNRuLu7M2PGDGrWrMncuXPJkiULAHXq1KFPnz6J5gkPDyc83PBscrRZZqz+9eUv8jpKlPJk8IgxFHB1JdDfnyUL59L1y3as3LAVW1tb6jdsjLNzHnLkzMXVK5eZO3MKvjdv4D1puqmjv7GrVy7zZbuPiIiIwNrahvFTZlCocBGyZctOFmtrZk2bTNdvehJLLLOnTyE6OpqAAH9Tx35t776VH0fbzKza/7wR1X7abyzrWRPfJR8RGRVDSEQUH0/+jb/uP4vfZt5uH05fD+RRUASViuZkxEflcc5qzaCVx01xGMnC1tYOzzJlWThvDm6FCuHklIPdO3dw9sxp8hdI+xWYv5Us7cmQkWMoUNCVgAB/liyYS5cO7Vj1/db4XhGbNqxlzvTJhIaGUsDVjWlzFmJpafqu5W9qz+6dXLp4gSWrNpg6ismU9vRk1GhvXF3dCAjwZ96c2XzRri0bt/yIre2LYyUlY9GYqMSpEfUarl27RkREBJUqVYpflj17djw84vpTnzt3jujoaIoWLWrwuPDwcJycnAA4c+YMZ8+eZfXq1fHrY2NjiYmJ4fr16xQvHjcRQ8WKFf8zj7e3NyNHjjRY9u2QYQweOuK1jk/kn7yqVo///yLuHpQo7UnrJvXZt2c3TVu0pnmr5919CrsXJUeOHHTv0oHbt3zTfHefgq6urFy/maCgIPb98hOjhn3L3EXLKVS4CGMnTGXC2FFsWLsKc3Nz6jdsjEfxEmlqPNS/tavjzp7Td7j36HklcUibcjjaZObd734i8Fk4775VgOU9a9Jg+C4u3HoMwKwdF+K3P+/7iMioGKZ39GL42pNERMUY+zCSzWjvCYwY9i0N6tTEwsKCYsVL0LBRE3wunDd1tGRj8P4u6kHJ0p60+sf7G6BBo3d5u3IVAvz9WbtyKUMH9GHe0lVp+kTd/Xt+TJnozYy5i9L0cbypf3ZnK+pRjFKly9D4ndr8vHsXLVu/b8JkIqmfGlEpICgoCAsLC06cOPHCAM2/x08EBQXRqVMnunfv/sLjC/zjLOffZwITM2jQIHr37m2wLNos7Z8llNTJ3t6B/AULcvuWb4LrS5T2BOBOOmhEWVpmjp9YoniJkvic/5P1a1YyaOhIKlepyubtP/H40SMsLCywd3CgUd3q5MnbyMSpX0/+HLbULu1C28m/xS9zy21P54bFeavPVi7efgzAnzcfUaVYLr5qUIyeiw4nuK9jVwOwzGROwZx2XPF7aoT0KSN/gQIsXraK0JAQgoKDyJkzFwP69CJvvvymjpZi7O0dyF/A8P1tZ2+Pnb09+QsUpJSnJw1qVmH/r7/wTsMmJkz6Zi76nOfRw0A++/i9+GXR0dGcPnmcjevXcODI6QwzwcI/OTg4UKCgK7d8E/58l4xFhajEqRH1GgoXLoylpSVHjhyJb/A8evSIy5cvU7NmTcqVK0d0dDQPHjygevXqCe6jfPnyXLhwgSJFirxxHisrqxfOpIVExL7xfkUSEhISzJ3bt2jYuFmC669cugiAU870N1A5JiaWyIhIg2VZs2UD4PjRwzx6+JAateqYItob+6RWEfyfhLH75PMJYawzx/2IjI01/DyJjonFPJFvV0/XbETHxOD/NH1MNGFtY4O1jQ1Pnzzhjz8O0rN33/9+UBoV//5ukvD7OzYWYoklMiLCyMmSV8W3vVj9/VaDZaOHD6agmxuffvZlhmxAQdzrf/vWLXI0TX+f3yLJTY2o12BnZ0eHDh3o168fTk5O5MqVi8GDB8d34ylatCht27alXbt2TJ48mXLlyuHv78/evXvx9PSkSZMmDBgwgMqVK9OtWze+/PJLbG1tuXDhAnv27GHWrFn/kcC0QkKCDc5S3blzm0sXfXBwdMTFJQ9Pnjzmnp8fDx48AODGjesAOOXIke5mAAoJDsb3n3+L27e56OODo6MjLv8/Hi6tmzV1IlVr1MLZJQ8B/g9YNH82FuYW1GvYmNu3fNmzewde1Wrg6JiVq1cuMWPyBMqWr/jCdMFpzewZU6hStQa5nV0ICQnmp13bOXn8KNPnLATgxy2bcS1UmGzZsnHu7GmmTPDmo0/aUdDVzcTJk87MLK4RtWb/NaJjnjeYLt99wlW/p0zv6MXglcd5GBTOu2/lp07pPLw/fi8Ab7vnpKJ7Dg6cv0dQaCRvF83JuHZvsf5/f/E4OG3/0P7j9/8RGwuurm7c8r3J1MkTcXMrRLMWrUwdLdnMnDqRav98f8+Le3/Xb9iYO7dvsffn3bxduQpZs2XD/8F9Vi6N6/7mVe3lM7SmBba2thQu4m6wLIu1NY6OWeOXBwb4ExgYwO3//4y/duUyNra25HZ2wdExq7Ejp4gpE8dTo1ZtXPLkwf/BA+bOnomFhTkNG79r6mgpLiN8f0vKUiPqNU2cOJGgoCCaNm2Kvb09ffr04cmTJ/Hrly5dyujRo+nTpw937twhR44cVK5cmXffjftg8vT0ZP/+/QwePJjq1asTGxtL4cKFadOmjakO6ZVdOP8nHb9oH39/8sRxADRt1oJRY8ax/9d9DB/6bfz6gf3iuhp26vI1nbu+eF2ptOz8+T/58vN28fcnTfAGoFnzlnw3dpypYiWrBw/uM/zbfjx98pis2bLjWbY885etIVu27ESEh3P86GE2rF1JWGgouXI7U6tuPT7r0NnUsd/Yo4cPGTlkIAEB/tjZ2VOkaFGmz1lIJa+4Wbx8b95gzsypPH3yBJc8efn8y0589En7/9hr6lS7dB4K5LRj5W9XDZZHRcfy3rhfGPlxBTb0r4Ntlkz8df8ZneYc5OfTcRchDo+K5r0qbgx6ryxWlubcfBDE7J0XmLn9QkJPlaYEPQti5rQp3L9/D0fHrNStX5+vu/fC0tLS1NGSzYP79xk+qB9P/vH+XrA87v0dFRXFmVMnWL9mJc+ePiG7Uw7Klq/A/KWryZ7dydTRU9zmjetZPP/5hYg7d4j7rB8ycgzvNmtpqljJ6v79ewzq35vHjx+TLXt2ypWrwIrVG8iePbupo6W4jPD9/aY0sUTizGL/3U9D0oWM2p3PPI1Pq/y60sOFTV9HJouM+Xrn/2yVqSOYxP1V7f57o3QoNCLa1BFMIrEuo+lZFsuM2ZUwg77cZEnF5Yx2a84a5XlWfOxplOdJbqn4pRMREREREVPIoOelX1nanYtXRERERETEBF6pErVt27ZX3mGzZgnP6CMiIiIiImmDxkQl7pUaUS1atHilnZmZmREdnTH7bouIiIiISMbwSo2omJi0e8V5ERERERFJGtWhEqcxUSIiIiIiIknwWrPzBQcHs3//fnx9fYn411XLu3fvnizBRERERETENDLqZQZeVZIbUadOnaJx48aEhIQQHBxM9uzZCQgIwMbGhly5cqkRJSIiIiIi6VqSu/P16tWLpk2b8ujRI6ytrTl8+DA3b96kQoUKTJo0KSUyioiIiIiIEZmZGeeWViW5EXX69Gn69OmDubk5FhYWhIeHkz9/fiZMmMC3336bEhlFRERERERSjSQ3oiwtLTE3j3tYrly58PX1BcDR0ZFbt24lbzoRERERETE6MzMzo9zSqiSPiSpXrhzHjh3D3d2dmjVrMmzYMAICAli5ciWlSpVKiYwiIiIiIiKpRpIrUWPHjsXFxQWAMWPGkC1bNrp06YK/vz8LFixI9oAiIiIiImJcGhOVuCRXoipWrBj//7ly5WL37t3JGkhERERERCQ1e63rRImIiIiISPql60QlLsmNKDc3t0QHgf31119vFEhERERERCQ1S3IjqmfPngb3IyMjOXXqFLt376Zfv37JlUtERERERCRVSnIjqkePHgkunz17NsePH3/jQCIiIiIiYlrqzZe4JM/O9zKNGjVi06ZNybU7ERERERGRVCnZJpbYuHEj2bNnT67diYiIiIiIiaTlC+Eaw2tdbPeff9TY2Fju3buHv78/c+bMSdZwIiIiIiIiqU2SG1HNmzc3aESZm5uTM2dOatWqRbFixZI1nLwBnTzIUKwyJVvP3DTlwdNwU0cwiTvLPzV1BJMo1vtHU0cwibMTmpg6gklERsWaOoJJmGU2dQKROBnzl8WrS3IjasSIESkQQ0REREREJG1IciPTwsKCBw8evLA8MDAQCwuLZAklIiIiIiKmY2ZmZpRbWpXkRlRsbMLl9fDwcDJnVg1aRERERETSt1fuzjdjxgwgrlW6aNEi7Ozs4tdFR0dz4MABjYkSEREREUkHzNNukcgoXrkRNXXqVCCuEjVv3jyDrnuZM2fG1dWVefPmJX9CERERERGRVOSVG1HXr18HoHbt2mzevJls2bKlWCgRERERETEdVaISl+TZ+X799deUyCEiIiIiIpImJHliidatWzN+/PgXlk+YMIH3338/WUKJiIiIiIjpaHa+xCW5EXXgwAEaN278wvJGjRpx4MCBZAklIiIiIiKSWiW5O19QUFCCU5lbWlry9OnTZAklIiIiIiKmozFRiUtyJap06dKsX7/+heXr1q2jRIkSyRJKREREREQktUpyJWro0KG0atWKa9euUadOHQD27t3LmjVr2LhxY7IHFBERERER40rDw5WMIsmNqKZNm7JlyxbGjh3Lxo0bsba2pkyZMuzbt4/s2bOnREYREREREZFUI8mNKIAmTZrQpEkTAJ4+fcratWvp27cvJ06cIDo6OlkDioiIiIiIcZmrFJWoJI+J+tuBAwdo3749efLkYfLkydSpU4fDhw8nZzYREREREZFUJ0mVqHv37rFs2TIWL17M06dP+eCDDwgPD2fLli2aVEJERERERDKEV65ENW3aFA8PD86ePcu0adO4e/cuM2fOTMlsIiIiIiJiAuZGuqVVr1yJ2rVrF927d6dLly64u7unZCYREREREZFU65UbgAcPHuTZs2dUqFCBSpUqMWvWLAICAlIym4iIiIiImICZmXFuadUrN6IqV67MwoUL8fPzo1OnTqxbt448efIQExPDnj17ePbsWUrmTNNq1apFz549TR1DRERERESSQZKnOLe1teWLL77giy++4NKlSyxevJhx48YxcOBA6tevz7Zt21Iip6RywcFBzJk5g317f+HRw0A8ihWn/8DBlCxd2tTRUty6NatZvnQxAQH+FPUoxsBvh1La09PUsZLN0sUL+HXvHm5c/wsrqyx4li3HNz374OrqBsDdO3do1rhego8dN3Eq9d5paMy4r+3c6RNsWrucq5d8eBjoz5AxU6hSI+6C4lFRkaxYOJtjhw9y7+5tbG3tKVuxEp937o5TjlwAnD11jIHdOya472kLVlG0eCmjHcub2LhhLZs2rMPv7h0AChUuQodOXalarQYAmzdu4Kdd27nkc4Hg4GD2/e8I9g4Opoz8Wn4fUY/8TjYvLF9+4DpDvz+HVSZzhrQsSbMKecmcyZz9Pg8YsuEcAc/CAchqY8mM9hUonteBrDaWBAZF8PO5e0z40YegsChjH85r27RhHZu/X8fdf77eX3WhSrUa3L1zh5ZN6if4uLETplA3jby3X8b/wX3mzpzC4T/+R1hYGPnyFeDb4aMpVqIUUVGRLJgzg8O//4+7d25ja2dHxbe96PJNL3LkzGXq6Mlm8cL57N3zM9ev/4VVliyULVuOnr374upWyNTRUlRGPe6k0hTniXut60T9zcPDgwkTJuDt7c2PP/7IkiVLkiuXpDGjhg3l6tUrjPYeT85cudj54zY6d/ycTVt3kCt3blPHSzG7d+1k0gRvhgwfSenSZVi9cjldOnVg6/bdODk5mTpesjh5/Bjvt/mYEiVLER0dzeyZU+nWuQPfb96OtY0NuZ2d2b33gMFjfti4gZXLl1ClWnUTpU66sLBQ3IoU5Z0mLRg9uLfBuvCwMK5e9uGj9h0pVMSDoGdPmTd9AiMH9mTGojUAFC9VllVbfjF43MpFszlz4ijuxUoa7TjeVK5cznTr0Zv8BQoSGxvLjh+30rdHN1at30ThIu6EhYXiVaU6XlWqM3vGFFPHfW1NJx3A4h8/EDzy2LOmWxV2nLoLwLBWpahTMhddlhznWWgko94vzYIv36LV1IMAxMbCz+fuMWm7D4FBEbjmtOW7D0qT1caT7stPmuSYXkeu3Lnp2r0X+QsUBGDHti3069mNles2UdCtEDt/2W+w/Q+bvmf18iV4paH3dkKePn1Clw6fUL7i20yaPo+s2bJz+9bN+BMCYWFhXL7oQ/svO+Pu7sHTZ0+ZPsmbAb27sXjlBhOnTz7Hjx2lzUdtKVm6NNFR0cycPoXOHTuwedsObGxePMmQXmTU45bkZRYbGxtr6hDpSXBwMF26dGHz5s3Y29vTt29ffvzxR8qWLcu0adN49OgRPXr04McffyQ8PJyaNWsyY8YMg8k6Fi5cyKhRowgMDKRBgwZUr16dUaNG8fjx41fOERJpvJc1LCyMapUqMHXGbKrXrBW//OMPWlG1Wg2+7t7TaFmMfdak7YfvU7JUab4dMgyAmJgY3qlbk48+/pQOHb8yWo7IqBijPdejhw+pX7sqC5asoHyFtxLc5uMPWlGseHGGjRyTolkePA1Pkf02rl7WoBKVkMs+f9Lzq09YtnEXuXK7vLA+KiqST1u+Q9PWH/HxZ8n7byGng1Wy7u+/1K1eme69+tK81Xvxy04cO0rnL9sbtRJVqt/2FNv38FYlqVvKmRqj9mKfJROnvBvSffkJdp72A6Bwbjt+HVKH5pP/x6kbjxLcx+c13ehUtwiVh+1J1mxnJzRJ1v39l/o1KvNNr340a9n6hXWftmmFR/ESDBkxOsVzREal3PfY3JlTOHfmFHMWrXzlx/icP0fH9h+ycfsenJ3zpFg2e+s3Or/9Rh4+fEjt6l4sWb6KChUT/nxPj0x53FlM93L/p2E/XTHK84xqkDYnrEvLMwumSv369WP//v1s3bqVn3/+md9++42TJ5+flfzss884fvw427Zt49ChQ8TGxtK4cWMiIyMB+P333+ncuTM9evTg9OnT1K9fnzFjUvaH6JuKjo4iOjqazFaGP+ysrLJw6uQJE6VKeZEREfhcOE9lryrxy8zNzalcuQpnz5wyYbKUFRQUN/7RwcExwfU+F85z+ZIPzVu+l+D69CI4OAgzMzPs7OwTXH/44H6ePX3CO42bGzlZ8omOjubnXTsIDQ2hdJmypo6TYiwtzGj5Vj7WH/YFoHSBrGTOZM7BS/7x21y7H8TthyGUd8uW4D5yO1jRsIwLh68GGiVzSoiOjubn3TsJDQ2llGeZF9bHvbcv0qzFi42rtOb3A79SrHhJhgzoxbv1q/P5x63Z9sP3iT4mKCjuPW9vl/a6r76qoP8f3+7gmPDne3qVUY9b3kwqbv+mPUFBQSxevJhVq1ZRt25dAJYvX06+fPkAuHLlCtu2beP333+nSpW4H96rV68mf/78bNmyhffff5+ZM2fSqFEj+vbtC0DRokX5448/2L495c7AvilbWzs8y5Rl4bw5uBUqhJNTDnbv3MHZM6fJX6CAqeOlmEePHxEdHf1Ctz0nJyeuX//LRKlSVkxMDJMneFOmbHmKuBdNcJutP2zErVBhypQtZ+R0xhMRHs7SudOpWa8hNrZ2CW7z844fKP+2Fzlypb3urFevXOaLTz8iIiIcaxsbJk6dSaHCRUwdK8U08HTBwdqSjf/fiMppb0V4ZDRPQw3HNgU8CyeXveHJopmfleed0s5YZ87EnnP3GLDmtLFiJ5urVy7zZbuPiIiIwNrahvFTZiT4ev/4wyZcCxXCMx28t+/euc2WTetp07Y97T7/Cp8L55g2yRtLS0savdvihe3Dw8OZO3MK9Ro0xtYu4fd8WhcTE8OE8WMpW6487i/5fE+PMupxvwpzDYlKlCpRyejatWtERERQqVKl+GXZs2fHw8MDAB8fHzJlymSw3snJCQ8PD3x8fAC4dOkSb7/9tsF+/33/38LDw3n69KnBLTw8Zbo5vcxo7wnEEkuDOjWpVN6TtatX0rBRE8zN9E8sPRk/dhTXrl1h7ITJCa4PCwtj964dNE8HZ6pfJioqEu/h/YmNjaVbn8EJbhPw4D4njx7inSYtjZwueRR0dWX1hs0sXbWe1u9/yIihg/jr2lVTx0oxbbwK8NuFB9x/je6hozadp/GEA3SYf4SCOWwY2irtjH/7W0FXV1au38zileto9UEbRg379oXXOywsjJ927UgXVSiI++FctFgJOn3dk6LFitO81Qc0a/EeWza9ON4pKiqSYQN7Q2wsfQcOM0Fa4xg7eiTXrlxhwqSppo5iVBn1uOXN6RduOuDt7Y2jo6PBbdJ4b6NmyF+gAIuXreKPoyfZ9cuvrFr3PVFRUeTNl9+oOYwpW9ZsWFhYEBho2H0nMDCQHDlymChVyhk/9jsOHtjPvIXLyZ3bOcFt9u75ibDQMJo0Tbtd2BITFRWJ97D+PLjnx5ip815ehdq5FXsHRypXq2nkhMnD0jIz+QsUpHiJknTr0Rv3oh6sW/3qY0fSkrzZrKnmkZO1h3zjl/k/C8fK0gKHf41NyWFvxYNnhg0t/2fhXLsfxJ4/7zNo3VnaVXcjl5HHrL2pf77eX3ePe73XrzF8vff98jNhYaE0fjd9vLedcuTE1a2wwbKCboW4f8/PYFlUVCRDB/bh3r27TJ29KN1WocaOHsWB/b+xcOlycjsn/PmeHmXU435V5mZmRrmlVWpEJaPChQtjaWnJkSNH4pc9evSIy5cvA1C8eHGioqIM1gcGBnLp0iVKlCgBxM14eOzYMYP9/vv+vw0aNIgnT54Y3PoOGJRch5Uk1jY25MyZi6dPnvDHHwepVeflA/PTOsvMmSleoiRHDh+KXxYTE8ORI4fwLJP2u7v8LTY2lvFjv+O3fb8wd+FS8v5/99SEbN2yiRq1apMte3YjJjSOvxtQd2/7MnbqPBwcsya4XWxsLL/s3Erdhk3JlMnSuCFTSGxMLBGREaaOkSI+qFyAwGfh7Dt/P37ZOd/HRETFULVozvhlhXLZki+7DSevJzypBDy/aGTmTGn7qzUmJpbIiEiDZT/+sInqteqkm/d26TLl8L153WDZrZs3cHZ5PmHE3w2o2743mTZnMY5Zsxo5ZcqLjY1l7OhR7Nu7h4VLlpMvHZ/4/KeMetySvDQmKhnZ2dnRoUMH+vXrh5OTE7ly5WLw4MGYm8d9obq7u9O8eXM6duzI/Pnzsbe3Z+DAgeTNm5fmzePO7n3zzTfUqFGDKVOm0LRpU/bt28euXbswS6SlbmVlhdW/JnUw5ux8AH/8/j9iY8HV1Y1bvjeZOnkibm6FaNailVFzGNun7T9n6LcDKFmyFKVKe7Jq5XJCQ0Np0TL9HPf4saPYvWsHk6fNwsbWloCAuMH2dnb2ZMmSJX67W743OXXiONNnzzdV1DcSGhLC3TvPqxH3/e5w7cpF7B0cye6Ug7FD+3H1sg8jxs8gOiaGh4EBANg7OGJp+byxdObEUe753aHBu2mzK9+s6VOoUq06zs55CAkJZvfO7Zw4fpSZcxcCEBDgT2BAALdu3QTg6tXL2NjY4uziguNLGpaplZkZvF85PxuP3iI65vln5rOwKNYf8mVoq5I8DokgKCyKke+V5vhfD+Nn5qtdIhc57K044/uYkPAoirrYM7h5SY5dC+T2w1BTHVKSzZ4xhSpVa5Db2YWQkGB+2rWdk8ePMn3Owvhtbvne5NTJ40ydNc+ESZNXm4/b0fmLT1ixZAF16jfgwvlzbPthI/0HjwDiGlBD+vfi8iUfxk+dTUx0NIH//9nn4OiIpWVmE6ZPPmO/G8munduZNnMOtja2BPj//+e7veHne3qTUY87qdJwkcgoNMV5MgsKCjKY4rxPnz7s2LHjhSnOt23bRkREBDVq1GDmzJkvTHE+cuRIHj58SIMGDahYsSKzZs3Cz88vkWc2ZOxG1M+7dzFz2hTu37+Ho2NW6tavz9fde2Fvn/DMZSnFFGXhtatXxV9s16NYcQZ8OwTPBGa2SkkpOcV5xTLFE1w+fNRYmjZ/3lCYPWMqO3f8yI+7fok/cZDSknOK85ddLLdew6a0/aIzn3+Q8DTT42YsxLPc8ylxx48cyIN7fkyeuzzZsv1bSk5x/t3wwRw7epgAf3/s7OwpUrQo7T//kkpeVQFYMHcWC+fNfuFxw/717yElJPcU59WL5WT1117UHLWX6/7BBuv+vthu878vtnvRnyHrz+L//935vNyd6Pducdyd7bHKZM7dx6HsPuPHnD1XXpiQ4k2l5BTno0cM4fiRwwQEPH+9P/3sSyr9Y9bROTOmsnvnj2zZabz3NqTsFOcAv//vN+bPmsbtWzdxyZOPNm3b0azl+wD43b3D+83eSfBxM+YtpXzFxMcqvwljTnFepqRHgstHjfameTo6Gfhvqem4U/MU59/9YpyxsEPrpc2Ji9SISgM6duzIxYsX+d///vfKjzF2Iyq1SMt9a9+EMa8TlZqk1HWiUjtjXycqtUjJ60SlZsa+TlRqkdKNqNTKlNeJEuNLzY2oMXuN04gaXPf1G1Hjxo1j0KBB9OjRg2nTpgFxE+H06dOHdevWER4eToMGDZgzZw65cz+fLdfX15cuXbrw66+/YmdnR/v27fH29iZTpld/QdJ2x+10atKkSZw5c4arV68yc+ZMli9fTvv27U0dS0REREQkVTh27Bjz58/H09PTYHmvXr348ccf+f7779m/fz93796lVavnFcbo6GiaNGlCREQEf/zxB8uXL2fZsmUMG5a02TfViEqFjh49Sv369SldujTz5s1jxowZfPnll6aOJSIiIiIZhJmR/nudS/UEBQXRtm1bFi5cSLZszy+C/uTJExYvXsyUKVOoU6cOFSpUYOnSpfzxxx8cPnwYgJ9//pkLFy6watUqypYtS6NGjfjuu++YPXs2ERGvPomSGlGp0IYNG3jw4AGhoaGcP3+ezp07mzqSiIiIiEiyS+hSPd7eiV+q5+uvv6ZJkybUq1fPYPmJEyeIjIw0WF6sWDEKFCjAoUNxsykfOnSI0qVLG3Tva9CgAU+fPuX8+fOvnDsV98QUEREREZH0bNCgQfTu3dtg2b9nnf6ndevWcfLkyQQvAXTv3j0yZ85M1n9dkiB37tzcu3cvfpt/NqD+Xv/3ulelRpSIiIiIiBgwN9JcXQldqudlbt26RY8ePdizZ4/Jp6NXdz4REREREUn1Tpw4wYMHDyhfvjyZMmUiU6ZM7N+/nxkzZpApUyZy585NREQEjx8/Nnjc/fv3cXZ2BsDZ2Zn79++/sP7vda9KjSgRERERETFgbmacW1LUrVuXc+fOcfr06fhbxYoVadu2bfz/W1pasnfv3vjHXLp0CV9fX7y8vADw8vLi3LlzPHjwIH6bPXv24ODgQIkSJV45i7rziYiIiIhIqmdvb0+pUqUMltna2uLk5BS/vEOHDvTu3Zvs2bPj4ODAN998g5eXF5UrVwbgnXfeoUSJEnz66adMmDCBe/fuMWTIEL7++utX7lYIakSJiIiIiMi/mJkZaVBUMps6dSrm5ua0bt3a4GK7f7OwsGD79u106dIFLy8vbG1tad++PaNGjUrS85jFxsZmzEuCp3MhkRnzZTVPo2/4NxUZFWPqCCbx4Gni15FIr3I6vPqZsvSkVL/tpo5gEmcnNDF1BJOIjMqY32P21jq/nZFkScUv98Tf/jLK8/SrVcgoz5PcUvFLJyIiIiIipmCs2fnSKk0sISIiIiIikgSqRImIiIiIiIEMOkLilakSJSIiIiIikgSqRImIiIiIiIGMOlnXq1IlSkREREREJAlUiRIREREREQOanS9xqkSJiIiIiIgkgSpRIiIiIiJiQEOiEqdKlIiIiIiISBKoEiUiIiIiIgbMUSkqMapEiYiIiIiIJIEqUemUmc4eZChmGbTjck4HK1NHMIlMGXTKpEtTmpk6gklkf7ubqSOYxMOjs0wdQSRDy6A/LV6ZKlEiIiIiIiJJoEaUiIiIiIhIEqg7n4iIiIiIGMigPcdfmSpRIiIiIiIiSaBKlIiIiIiIGDDXzBKJUiVKREREREQkCVSJEhERERERAypEJU6VKBERERERkSRQJUpERERERAxoTFTiVIkSERERERFJAlWiRERERETEgApRiVMlSkREREREJAlUiRIREREREQOqtCROfx8REREREZEkUCVKREREREQMmGlQVKJUiRIREREREUkCVaJERERERMSA6lCJUyVKREREREQkCVSJEhERERERA+YaE5UoVaKSSWxsLF999RXZs2fHzMyM06dPmzqSiIiIiIikADWiksnu3btZtmwZ27dvx8/Pj1KlSpk6klE1eqcOZUt5vHAbO3qkqaOluHVrVtOofh3eKleath++z7mzZ00dKVmdPH6Mnt0606BudSp4FuPXfb8YrA8MDGD4kIE0qFudKm+XpVvnL/G9ecM0YZPRxg1r+ei95tSqUpFaVSryxacf8vvBA/Hrw8PDGT92FPVqVKZG5Qr0792dwMAAEyZOPieOH6NHt87Ur1OdcqWL8eveX1667ehRwylXuhirVy43YkLjuH//Pt8O6EvNqpWoVMGT91o25fyf50wd643Y2VgxsW9rLu0cxcNDU/h1WW8qlCgQv755nTL8OOdrbv86ntBTs/AsmjfB/VTydGPX/G8I+GMy9/83kT2Le5LFytJYh5Hs5s6e+cL3V4umDU0dK8UtXjifjz9ojddb5ahV3Yue33TlxvW/TB3LKE4cP8Y3XTtTr1Y1ypT0YF8in3MiCVEjKplcu3YNFxcXqlSpgrOzM5kyGfaUjIiIMFEy41i9biO//HYw/jZv4VIA6r+Tvr+Edu/ayaQJ3nTq+jXrvv8BD49idOnUgcDAQFNHSzahoaEU9SjGgG+HvbAuNjaWPj2+5s7t20yZPoc16zfjkicPXb76gtCQEBOkTT65cjnTrUdvVqzdyPI131Px7cr07dGNa1evADB1ojf/2/8b3hOnMX/JCgL8H9C/d3cTp04eoaGhFC1ajEGDX3zN/2nf3j2cO3uGnLlyGSmZ8Tx98oTPPv2ITJaWzJq3kM1bd9C77wAcHBxNHe2NzB32MXUqF+OLIcup+MFYfjl0kR3zviFPzrjjsrHOzB+nrzFkxpaX7qOSpxtbZ3Vl7+GLVP9kItU+mci8dfuJiYk10lGkjMJF3A2+x5auWGPqSCnu+LGjtPmoLSvXbmD+wqVERUXRuWMHQtL45/erCA0NwcPDg0FDhps6SqplZqRbWqUxUcngs88+Y/nyuLOwZmZmFCxYEFdXV0qVKkWmTJlYtWoVpUuX5tdff2X//v3069ePM2fOkD17dtq3b8/o0aPjG13Pnj2jc+fObNmyBQcHB/r378/WrVspW7Ys06ZNM+FRJi579uwG95csWkD+/AWo+NbbJkpkHCuXL6XVex/QomVrAIYMH8mBA7+xZfMmOnT8ysTpkkfV6jWoWr1Ggut8b97g3NkzbNj8I4WLuAMwaMgI3qldjd27dtCy9fvGjJqsatSqbXC/6zc92bRhHX+ePUPu3M5s/WEzo8dN5K1KlQEYNmos77dowrmzpyntWdYEiZNPteo1qPaS1/xvD+7fZ/zY0cyZv4hvvu5kpGTGs3TJQpydnRk12jt+Wd58+U2Y6M1lsbKkRd2yvN9rAb+fvAbAmPk7aVyjFB3fr87IOdtZu+MYAAVcsr90PxP6tGLOut+YtHRP/LIrNx+kbHgjsLCwIEeOnKaOYVRzFyw2uD9qzDhqV/fC58J5KlR8y0SpjKNa9ZpUq17T1DEkDVMlKhlMnz6dUaNGkS9fPvz8/Dh2LO5LaPny5WTOnJnff/+defPmcefOHRo3bsxbb73FmTNnmDt3LosXL2b06NHx++rduze///4727ZtY8+ePfzvf//j5MmTpjq01xIZGcHO7dto3rJ1ur5QW2REBD4XzlPZq0r8MnNzcypXrsLZM6dMmMx4/q6wZrayil9mbm5O5syZOX3qhKliJbvo6Gh+3rWD0NAQSpcpi8+F80RFRfJ2Ja/4bVzdCuHs4sK5M6dNF9RIYmJiGPJtf9p/3iG+8Zze7P91HyVKlqJv7+7UruFFm/dasGnjBlPHeiOZLMzJlMmCsIhIg+Vh4ZFUKVf4lfaRM5sdb3u64f8wiF+X9ebGL2P5eVEPqpQtlBKRjcrX9yb1a1ejScO6DBrQBz+/u6aOZHRBz54B4OCYtiuukjzMzIxzS6tUiUoGjo6O2NvbY2FhgbOzc/xyd3d3JkyYEH9/8ODB5M+fn1mzZmFmZkaxYsW4e/cuAwYMYNiwYQQHB7N8+XLWrFlD3bp1AVi6dCl58uQx+jG9iX17f+HZs2c0a9HS1FFS1KPHj4iOjsbJyclguZOTE9czSJ/yuIZDHmZNn8LgYSOxtrZm9crl3L9/j4AAf1PHe2NXr1zmi08/IiIiHGsbGyZOnUmhwkW4fOkilpaW2Ds4GGyfPXsOAgPSx7ioxCxdshALCws+avupqaOkmNu3b/H9+rV80u5zvuzYmT//PMcE79FYWlrSrHna/GwLCgnn8Jm/GNSxEZeu3+d+4FM+aFiRSp5uXLv1au9Xt3w5ABjcqTGDpv7A2Uu3afvu2+yc/w0V3h/LNd+0+b4v7enJqNHeuLq6ERDgz7w5s/miXVs2bvkRW1s7U8czipiYGCaMH0vZcuVxdy9q6jgiqZ4aUSmoQoUKBvd9fHzw8vIyqM5UrVqVoKAgbt++zaNHj4iMjOTtt593gXN0dMTDwyPR5wkPDyc8PNxgWYy5FVb/qA4Y05bNm6harQa5cuU2yfOL8VhaWjJp6gxGDR9C7WqVsLCw4O1KXlStVoPY2LQ9PgKgoKsrqzdsJigoiL17fmLE0EHMX7zC1LFM6sL5P1m7aiVrNmxK15XmmJhYSpQsRfeevQEoVrwE165cYeOGdWm2EQXwxZAVzB/Rlr9+HkNUVDSnL95iw+7jlCte4L8fDJibx73mizcdZOW2wwCcuXSbWm970L65F8Nmbkux7Cnpn926inoUo1TpMjR+pzY/796VprslJ8XY0SO5duUKy1am/7Fg8mrS82d8clB3vhRka2trlOfx9vbG0dHR4DZxvPd/PzAF3L17hyOH/6Bl6/dM8vzGlC1rNiwsLF6YRCIwMJAcOXKYKJXxFS9RirXfb+G334/x097/MWveIh4/fpzmx48AWFpmJn+BghQvUZJuPXrjXtSDdatX4uSUg8jISJ49fWqw/cOHATil89f+1MkTPHwYSON36lCxbEkqli2J3927TJk0nsYN6pg6XrLJmTMnhQsbdnFzK1QozXfxun47gHe+nI6TV2/cGw2l+qeTsMxkwfU7r1ZB9fOP+zfv89c9g+WXrt8jv3O2ZM9rKg4ODhQo6MotX19TRzGKsaNHcWD/byxcupzc/+hRIyIvp0aUERUvXpxDhw4ZnKH//fffsbe3J1++fBQqVAhLS8v4MVUAT5484fLly4nud9CgQTx58sTg1m/AoBQ7jsRs/WEz2bM7Ub1GLZM8vzFZZs5M8RIlOXL4UPyymJgYjhw5hGeZciZMZhr29vZky54d35s38LnwJzVrp58f1H+LjYklIjKC4iVKkimTJceOHo5fd+PGde75+VG6TFnTBTSCJk2bsWHTVtZ9/0P8LWeuXLT7rANz5i0ydbxkU6ZceW7cuG6w7ObNG7i4JDzld1oTEhbBvYCnZLW3pl6V4mz/7dWmbr95N5C7Dx5T1NVwRsYiBXPh6/cwJaKaREhIMLdv3SJHzvQ90URsbCxjR49i3949LFyynHzp4OSXJB9zI93SKnXnM6KuXbsybdo0vvnmG7p168alS5cYPnw4vXv3xtzcHHt7e9q3b0+/fv3Inj07uXLlYvjw4ZibmydaUrWyerHrXmjkSzZOQTExMWzbspmmzVu8MMV7evVp+88Z+u0ASpYsRanSnqxauZzQ0FBatGxl6mjJJiQk2OBs7N07t7l00QcHR0dcXPKw5+fdZMuWDWeXPFy9cplJ48dQq3ZdvKpUM2HqNzdr+hSqVKuOs3MeQkKC2b1zOyeOH2Xm3IXY2dvTvGUrpk4ah4ODI7Z2dkwcN5rSZcqm+Zn54MXX/M6/XvOsWQ0rDpkyZSJHjhy4uqX9yQX+9smn7fns049YtGAe7zRsxJ/nzrJp4waGDh9l6mhvpJ5XcczM4PKNBxTOn5OxvVpw+fp9VmyLOxmUzcGG/M7ZcMkVN7FAUde4btn3A59yPzBu0oGpy39hSOcmnLt8hzOXbvNJ00p4uObm436LE37SNGDKxPHUqFUblzx58H/wgLmzZ2JhYU7Dxu+aOlqKGvvdSHbt3M60mXOw/b/27jusqfNvA/gdkCFTQFBUNoqAgChWcSvWLSi2dW9t3SjuX504UFy4ce+tVeseqLg3bkRxFAcKiosNSd4/eE1NQRQhOZLcn15cV3NyEu5HCMlzvs/Q08frhOw5bQaGhtDV1RU4nWKlJCcj9vO/c8+e4V5UFIyNjWFZxOaikzDU45PuD6Js2bI4cOAARowYAQ8PD5iamqJXr14YO3as7Jw5c+agb9++aNmypWyJ86dPnxaJP2YXzp9DXNwL2XLf6qBps+Z4m5iIxQvn4/XrBDhVdMbipStUakjX3Tu38UevbrLbc2ZOBwC09G2NSVOm43VCPObOnJ49jNHcHC1a+aHPH/2Eilto3ia+wcSxo/E6IQEGBoZwrFABC5YsR3XvWgCAoSPGQKShgVHDApCRkYEaNWth1Ff2VSoq7t65jT49//2Zz/7/n3kr39YImjpdqFhKVcnNHXNCF2L+vDlYFrYIZcuWw4hR/0OLlr5CRysQYwNdBA3yRdlSJZD4PgV7wq9jwqK9yMqSAABa1HPD8qB/FwxZP6MnAGBK2AFMXXoAALBw00no6mghZFhbmBjr4db952jZbyEePyu6i6q8evUSY0YG4t27dzAxNYWnZ1Ws27gtx/Ydqmbb1s0AgF7d5ReJCZoSDD8VuhiYmzt3bqN3j66y27NCsqdB+Pq1weRp6vF37ms4JypvIqkqzP5WYcnJyShbtixmz56NXr16ffPjhKhE/QjU9fWeJVbPl7FETf98FdNQz190dX1DN/1poNARBJF4aaHQEQShpr/makv3By5nbLuunDmgv1UumpW/H/hHp54iIyNx7949/PTTT3j//j2CgrKHjvj5+QmcjIiIiIjUBfvzeWMn6gc0a9YsREdHQ1tbG1WrVsXp06fVarU3IiIiIqIfGTtRPxhPT09cvXpV6BhEREREpMbUdQj1tyrKKwsSEREREREpHStRREREREQkh5WWvPHfh4iIiIiIKB9YiSIiIiIiIjmcE5U3VqKIiIiIiIjygZUoIiIiIiKSwzpU3liJIiIiIiIiygd2ooiIiIiIiPKBw/mIiIiIiEgO15XIGytRRERERERE+cBKFBERERERydHg0hJ5YiWKiIiIiIgoH1iJIiIiIiIiOZwTlTdWooiIiIiIiPKBlSgiIiIiIpIj4pyoPLESRURERERElA+sRBERERERkRzOicobK1FERERERET5wEoUERERERHJ4T5ReWMnSkVJIRU6giDUdRKkhno2G1DTn3eGWCJ0BEEU01DPwRNvLi4QOoIgTOuOFjqCIN6eni50BCL6BuxEERERERGRHM6Jypt6XtYjIiIiIiL6TqxEERERERGRHFai8sZKFBERERERUT6wEkVERERERHLUdbGub8VKFBERERERUT6wE0VERERERJQPHM5HRERERERy1HcPym/DShQREREREVE+sBJFRERERERyuLBE3liJIiIiIiIiygdWooiIiIiISA43280bK1FERERERET5wEoUERERERHJ4ZyovLESRURERERElA+sRBERERERkRzuE5U3VqKIiIiIiIjygZUoIiIiIiKSwzlReWMlioiIiIiIKB/YicpD/fr1MWTIEKFjEBEREREplUiknK+iisP5qFAkJydh8YL5OB5+DG8T38CpojNGjv4Trm5uQkdTuC2bNmLt6pV4/ToBFZwqYvT/xsHN3V3oWIXq6pXLWLdmJe7evYPXCQmYE7oQDXwaye4PW7wAhw8ewMtXL6FVTAvOLq4YOHgI3Nw9BExdMNf+v81RUdltnhW6EA0a/tvmlJRkLAidjZPHw/H+/TuUKVsO7Tt2wS+/tRcwdcHt3LYFf23fghcvngMA7B0c0ev3fqhZuy5ePH+ONi1+zvVx00LmwKdxU2VGLVSrVizFifCjePL4EXR0dOFe2RODhwyDrZ297Jz09HTMnTUDRw7tR0ZGJrxr1sLosRNgZlZSwOQFp+qvbw0NEcb2boQOTTxRyswQcQkfsP7AVUxffVx2jn5xbUzp3xSt6rrC1FgPT14kYvH2c1ix66Lcc1WvZI2JfzRBNVcriCUS3Lwfh1ZDVyItPUvZzSoU27Zswratm/Hiefbr3cGxPP7o1x+169QTOJniXb1yGWtWrUTU3dtISEjA3PmL0PCz33uir2ElSokyMjKEjqAwQePH4cL5c5gSPAPbdv0N75q10LdPD8S/eiV0NIU6dPAAZoUE44/+A7Bl+y44OVVEvz964c2bN0JHK1SpqamoUKEixvw5Ptf7bWxsMep/47B9599YvW4jypQti/5/9EJiYqKSkxae1NRUVHCqiFH/y73Nc2ZOx7mzZzA5OAQ7du9Hx85dERI8GREnjud6flFhUaoU+g8eirWbtmPtpu3wqlYdI4YMxKOYByhVujQOHIuQ++rTbyD09PTgXbuO0NEL5NqVy/i1fUes2bAVi5etQlZWFgb07Y3UlBTZObNDgnEq4gSmz5qH5avXISEhHiOGDhIwdeFQ9df3sC710KdNDQydvQeV28/B2MUHEdipHvr/WlN2zozBLfBzjQroMXErKrefg4Vbz2JuoC9a1HaWnVO9kjX2zO2J8Ev3UafXQtTuuRBhO89BIpEK0axCYVGqNAKGDsfm7X9h07ad+Kl6DQQMHICYmAdCR1O41NQUODk5YczYCUJH+WGJlPRVVLET9RUSiQQjR46EqakpSpcujYkTJ8rui42NhZ+fHwwMDGBkZITffvsNrz7rNEycOBGVK1fGihUrYGdnB11dXQDAjh074ObmhuLFi8PMzAyNGjVCcnKy7HErVqyAs7MzdHV1UbFiRSxevFhp7f0eaWlpCD92BEMCh6OqVzVYW9ug74BBsLK2xvatm4WOp1Dr166G/y+/oXWbtnBwdMTYCZOgq6uL3X/tFDpaoapdpy4GDB6Chj65VyGatWiFGt41Uc7KCg6O5TFsxGgkJSXhwf1oJSctPLXq1EX/QV9u883r19HStzW8qlVHmbLl4P9LO5Sv4IQ7t28qOWnhqlOvAWrVqQdrG1tY29ii36Ah0NPTw+1bN6GpqQmzkuZyXxHHj8GncVPo6ekLHb1AFoatgK+fPxwcy6OCU0VMmhyMl3EvEHX3DgDg48eP2LNrJwKHj8JP1WvA2aUSJkwOxo3rkbh147qw4QtI1V/fNdxssO/0XRw6F43Yl2+x68RthF96AC8XK7lzNhy4htORjxD78i1W7bmEmzFxcueEBLTE4u1nMWt9BKIex+NB7GvsDL+FjEyxEM0qFPUbNESduvVgY2MLW1s7DAoYCj09Pdws4r/T36J2nXoYGDAUPo1y/70n+hp2or5i7dq10NfXx8WLFxESEoKgoCAcPXoUEokEfn5+SExMREREBI4ePYpHjx6hXbt2co+PiYnBzp078ddff+H69euIi4tDhw4d0LNnT0RFReHkyZPw9/eHVJp9JWvjxo0YP348pk6diqioKEybNg3jxo3D2rVrhWj+NxGLsyAWi6GtoyN3XEdHF5HXrgqUSvEyMzIQdfcOanj/ezVTQ0MDNWrUxM0bkQImE1ZmZgb+2rEVBoaGqOBUUeg4CuNeuTJOnTyO+FevIJVKcfnSBcT+8wQ1vGsJHa3QiMViHDl0AKmpqaiUy9CtqLt3cD/6HnxbtxUgnWIlJX0EABgZGwPIbmtWViaq1/j39W5nZ4/SlmVw8+Z1ISIKoii+vi/c+gcNvBzhaJU97NLN0RLeHjY4cj5a7pyWtZ1RxtwIAFC3ij3KW5nj2KXsioy5iT5+qmSNhMRknFjWD0/2/4kji39HTXcb5TdIQcRiMQ4e2I/U1BR4eHgKHYd+ABoikVK+iirOifoKd3d3TJiQXeotX748Fi5ciPDwcADArVu38PjxY1hZZV+pWrduHVxdXXH58mVUq1YNQPYQvnXr1sHc3BwAcO3aNWRlZcHf3x82Ntl/fN0+mzc0YcIEzJ49G/7+/gAAOzs73L17F0uXLkW3bt1yzZieno709HS5Y2INbej8p1OjKPr6BnD3qIzlYYthZ28PM7OSOHRgP27euA4ra2ulZBDC23dvIRaLYWZmJnfczMwMjx8/EiiVcE5FnMDoEcOQlpaKkubmCFu2CiYmJkLHUpiRY8ZhyqRxaPZzPWgWKwYNkQhjJ0xGFa9qQkcrsJgH99G7awdkZGSgeHE9zJgzH/YOjjnO27trJ2zt7eFeWbU+cEkkEswKmQYPzypwLF8BAPDmdQK0tLRgaGQkd66ZmRnevH4tREylKsqv71nrImCkp4sbWwIhlkihqSHChKVHsOXIddk5gXP+xqLR/nj49/+QmSWGRCJF/+l/4ez1xwAAuzKmAIA/e/tgzIIDuPkgDp2aVcGBBX1QtdNcPHxWdIdwP7gfjS4d2yMjIx16enqYO38RHBxzvt6JSB4rUV/h/p8FAiwtLREfH4+oqChYWVnJOlAA4OLighIlSiAqKkp2zMbGRtaBAgAPDw/4+PjAzc0Nv/76K5YvX463b98CAJKTk/Hw4UP06tULBgYGsq8pU6bg4cOHX8wYHBwMY2Njua9ZM4IL65/gm0wJDoEUUjRpWA/Vq7hj88b1aNqsBTRE/BVTF9WqVceWHbuwZv1m1KxVByOHD0Giis0N+9yWTetx++YNzJ2/GBu37MTQ4aMwY1oQLl44J3S0ArOxtcX6rX9h5fot8P+tHYLG/w+PHsbInZOWlobDB/erZBVq+tQgPIx5gOAZc4SO8sMoyq/vX3zc0L5JZXSfsAXe3eej9+TtGNKxDjo1ryI7p/+vNfGTqzXajliLmt0XYPSC/Qgd5ocG1bI7Exoa2VfLV+6+hPX7r+LG/RcYOW8f7scmoFsrL0HaVVhsbe2wbedubNi8Db+264Bx/xuFhzExX38gqTzOicobK1FfoaWlJXdbJBJBIpF88+P19eXnCWhqauLo0aM4d+4cjhw5ggULFuDPP//ExYsXoaenBwBYvnw5qlevnuNxXzJmzBgEBgbKHRNraH9zxsJgZW2NlWs2IDUlBUnJSTA3t8CoYUNRtpzV1x9cRJmUMIGmpmaORSTevHmDkiWL9mpd36O4nh6srW1gbW0Dd4/K8G3RBLt27UCv3n8IHa3QpaWlYdH8UMwKXYA6desDAMpXcEL0vXtYv2aV3JCvokhLSxtW1tmVcmcXV0TduY2tm9ZjzLhJsnOOHzuCtLRUNG/pJ1RMhZgxLQhnTp3E8tUbUKp0adlxs5LmyMzMxMcPH+SqUW/evIGZGrzei/Lre9rA5pi1/iS2H8uer3jn4StYlzbBiK71sfHANejqFMOkvk3QbvR6HDqXPcTv9sOXcC9fBkM61sGJyzGIe509vDPqsfxiSdFP4mFVqoQym1PotLS1Yf3/I2NcXCvhzu1b2LhhHcZPDBI4GdGPjWWC7+Ts7IynT5/i6dOnsmN3797Fu3fv4OLikudjRSIRatWqhUmTJiEyMhLa2trYtWsXSpUqhTJlyuDRo0dwdHSU+7Kzs/vi8+no6MDIyEjuS1lD+f6ruJ4ezM0t8OH9e5w7dwb1GzYUJIcyaGlrw9nFFRcvnJcdk0gkuHjxPNw5nhxSiQSZKroiZVZWFrKyMnNUWjU1NSCRfvtFlqJCIpEiMyNT7tjeXTtRp35DmJiaCpSqcEmlUsyYFoQTx48hbMUalC1XTu5+ZxdXFCumhUsX/329P3n8CC/jXsDdvbKS0wqvKL2+i+tq5VhBTyyRyOZiaGlqQlurWJ7n/BP3Fi8S3qOCjbncOY7W5oh9+U5x4QUgKUI/WyIhsRL1nRo1agQ3Nzd06tQJoaGhyMrKQv/+/VGvXj14eX25tH/x4kWEh4ejcePGsLCwwMWLF5GQkABn5+xlVCdNmoTBgwfD2NgYTZs2RXp6Oq5cuYK3b9/mqDb9SM6dPQ2pNHtYwNPYfzB39kzY2dnDt7W/0NEUqku3Hhj3v1Fwda2ESm7u2LB+LVJTU9G6jWq1OyUlGU9jY2W3nz9/huh7UTAyNkYJ4xJYsTwM9eo3RElzc7x7+xbbtmxCfPwr/FyE9w36b5tffNZmS8syqOpVDfPmzISOrg4sLcvi6tVL2L93D4YOHy1g6oJbNH8Oataqi1KlLZGSkozDB/fh2pVLmLd4ueycp7H/IPLaFcxdGCZg0sI1fWoQDh3chznzFkFPXx+vXycAAAwMDKGrqwtDQ0P4tWmLObNmwMjYGAYGBggJngJ3j8pw86gsbPgCUvXX94Ez9zCqe0M8ffUOdx/Fo7JTGQxuXxvr9l0BAHxMScepa48wbWBzpKZnIfblW9TxtEenZlUwat4+2fPM3XgKY3v/jFsP4nDjQRw6N68CJxtzdPzfBqGaVmDz5s5G7Tp1UdrSEinJyTiwfx+uXL6EJctWCh1N4VKSkxH7+e/9s2e4FxUFY2NjWJYpI2CyH0hRHmunBOxEfSeRSIQ9e/Zg0KBBqFu3LjQ0NNC0aVMsWLAgz8cZGRnh1KlTCA0NxYcPH2BjY4PZs2ejWbNmAIDevXtDT08PM2fOxIgRI6Cvrw83NzcMGTJECa36fkkfk7AgdA5evXoJY+MS8Pn5ZwwYPDTHcEhV07RZc7xNTMTihfPx+nUCnCo6Y/HSFSo3vOfundvo0/PfhU1mz5wOAGjl2xp/jp+EJ48fY+/fg/Hu7VsYlygBV1c3rFq7EQ6O5YWKXGB379zGH73+bfOc/29zS9/WmDRlOqaFzMHCeXMwdswIfHj/HqUty6D/oCFFfrPdt4mJmDR2NF6/ToCBgSEcK1TAvMXLUf2zVSj37v4LFqVKoboKrUS4Y1v2dgy/9+wqd3zC5Gnw9cu+KDJs5BhoaGhgZGAAMjIy4F2rNkZ/YW+lokTVX9+Bc/Zgwu+NMW94a5ibGiAu4QNW7r6EaavCZed0HbcJQf2aYs2kdjAx0kPsy7eYGHYYyz/bbHfh1rPQ1S6GkICWMDHSw62YOLQcvAKPnxeN/bJyk5j4BmPHjEJCQnz2iosVnLBk2Up411Sd1/aX3LlzG717/Pt6nxWSPZfc168NJk+bLlQsKkJE0k9ra5NKSclUzx9rUV4qsyCK8maPBaGmzUZWPuZlqpJiGuo5Al1DPf+swazeGKEjCOLtaX6AVye6P3A54+LD90r5PtUdjJXyfQqber4jERERERERfacfuP9LRERERERCUNPBPd+MlSgiIiIiIqJ8YCWKiIiIiIjksBCVN1aiiIiIiIiI8oGVKCIiIiIiksdSVJ5YiSIiIiIiIsoHVqKIiIiIiEiOiKWoPLESRUREREREP7zg4GBUq1YNhoaGsLCwQOvWrREdHS13TlpaGgYMGAAzMzMYGBigbdu2ePXqldw5sbGxaNGiBfT09GBhYYERI0YgKysrX1nYiSIiIiIiIjkikXK+8iMiIgIDBgzAhQsXcPToUWRmZqJx48ZITk6WnTN06FDs3bsX27dvR0REBF68eAF/f3/Z/WKxGC1atEBGRgbOnTuHtWvXYs2aNRg/fnz+/n2kUqk0f/GpKEjJVM8fq4aa7gwnkajnz1tNm40siUToCIIopqGe1/001PPPGszqjRE6giDenp4udARSIt0feGLN1ScflPJ9qtoaffdjExISYGFhgYiICNStWxfv37+Hubk5Nm3ahF9++QUAcO/ePTg7O+P8+fOoUaMGDh48iJYtW+LFixcoVaoUACAsLAyjRo1CQkICtLW1v+l7q+c7EhERERERfZFISV/p6en48OGD3Fd6evo3ZXz//j0AwNTUFABw9epVZGZmolGjRrJzKlasCGtra5w/fx4AcP78ebi5uck6UADQpEkTfPjwAXfu3Pnmfx92ooiIiIiISBDBwcEwNjaW+woODv7q4yQSCYYMGYJatWqhUqVKAICXL19CW1sbJUqUkDu3VKlSePnypeyczztQn+7/dN+3+oGLiEREREREJAglDSUeM2YMAgMD5Y7p6Oh89XEDBgzA7du3cebMGUVFyxM7UUREREREJAgdHZ1v6jR9buDAgdi3bx9OnTqFcuXKyY6XLl0aGRkZePfunVw16tWrVyhdurTsnEuXLsk936fV+z6d8y04nI+IiIiIiH54UqkUAwcOxK5du3D8+HHY2dnJ3V+1alVoaWkhPDxcdiw6OhqxsbHw9vYGAHh7e+PWrVuIj4+XnXP06FEYGRnBxcXlm7OwEkVERERERHJ+xM12BwwYgE2bNmHPnj0wNDSUzWEyNjZG8eLFYWxsjF69eiEwMBCmpqYwMjLCoEGD4O3tjRo1agAAGjduDBcXF3Tp0gUhISF4+fIlxo4diwEDBuSrIsZOFBERERER/fCWLFkCAKhfv77c8dWrV6N79+4AgLlz50JDQwNt27ZFeno6mjRpgsWLF8vO1dTUxL59+9CvXz94e3tDX18f3bp1Q1BQUL6ycJ8oFcV9otQL94lSL9wnSr1wnyj1wn2i1MuPvE/U9diPSvk+la0NlfJ9Cpt6viMRERERERF9px+4/0tEREREREJQ0yL4N2MnSkWlZajncB8dLfUsrmqq6Xgf9fxpA8U0NYWOQEqkroPuE0+p57A2k5rDhY4giNdnZgodQSDq+f6tCtiJIiIiIiIieezf5UldL+QSERERERF9F1aiiIiIiIhIzo+4T9SPhJUoIiIiIiKifGAlioiIiIiI5Kjp1pvfjJUoIiIiIiKifGAlioiIiIiI5LAQlTdWooiIiIiIiPKBlSgiIiIiIpLHUlSeWIkiIiIiIiLKB1aiiIiIiIhIDveJyhsrUURERERERPnAShQREREREcnhPlF5YyWKiIiIiIgoH9iJIiIiIiIiygcO5yMiIiIiIjkczZc3VqKIiIiIiIjygZUoIiIiIiKSx1JUnliJIiIiIiIiygdWooiIiIiISA43280bK1EK1L17d7Ru3TrPc2xtbREaGqqUPEREREREVHCsRAns8uXL0NfXFzpGgaxbvRxLFszFbx26YOiIMYh78Rz+LX/O9dwpM+bA5+emSk5YOK5euYx1a1Yi6u4dvE5IwOzQhWjg00junEePHmL+3Fm4duUyssRi2Ns7YObc+bC0LCNQ6sK3bcsmbNu6GS+ePwcAODiWxx/9+qN2nXoCJ1OslcuXIvzoETx+/Ag6urqoXNkTQwKHw9bOXuhoCsV2q1e7AaBZ44aIe/E8x/Hf2nfE/8ZOECCR4i1ZtABLlyyUO2ZrZ4fdew8JlKjgNDREGNunMTo0q4pSpoaIe/0e6/ddwfRVx2TnWJgaYMrAFmhUvQKMDYvjTOQjBM7ajYdPX8vOsStrhukBLeHtYQcdrWI4eiEagbN2IT4xSYhmfbevvYdXcauY6+MCAkegW49eyor5Q+Fmu3ljJ0pg5ubmQkcokLt3bmH3zm1wLO8kO2ZRqjT2HYmQO2/3X9uxad0qeNeqo+yIhSYtNRUVKlSEX5u2GD5kUI77nz6NRa+uHeHn/wv69h8EfQMDPIqJgY62jgBpFceiVGkEDB0OaxsbSKVS7N2zGwEDB2Drzl1wdCwvdDyFuXL5Etp16ARXNzeIs8RYMG8O+vbphb/+3g89PT2h4ykM261e7QaAjVt2QCIRy27HPHiAvn164OfGRfMC2LdycCyPpStWy25ramoKmKbghnVtgD5ta6LPpC24++glqjpbYem43/AhKQ2Lt50BAGyb2R2ZWRL8OnwNPiSnYXDHujiw8A94tpuJlLQM6OlqY9+CPrj1IA7N+ocBACb0bYqds3uibs8FkEqlQjYxX772Hn7kxGm522dPn0LQhLHwadRYWRGpiGEnqhDs2LEDkyZNQkxMDPT09ODp6Yk9e/bI7p81axZmz56NjIwMtG/fHqGhodDS0gKQPZxvyJAhGDJkCABAJBJh8eLF+Pvvv3Hy5ElYWloiJCQEv/zyixBNy1NKSjIm/jkSo8dNwpoVS2XHNTU1YVZSvnMYceIYGv7cFHp6RbfqVqtOXdSqU/eL9y+aH4padephSOAI2TErK2tlRFOq+g0ayt0eFDAU27Zsxs0b11W6E7Vk2Uq520FTp6NBHW9E3b2Dql7VBEqleGx3NnVpNwCYmprK3V61YhmsrKzhVe0ngRIph6amJkqWLNoXNj9Xw90W+07dxqGzUQCA2Li3+K1xZXi5WgEAHK1LorqbLaq0n4moR68AAINn/IUnByfgtyaVsWbPJXh72MLG0hQ1uszFx+R0AEDviVsQFx6E+l6OOHH5gTCN+w5few//788+4sRxeP1UHeWsrBQd7YfFQlTeOCeqgOLi4tChQwf07NkTUVFROHnyJPz9/WVXZ06cOIGHDx/ixIkTWLt2LdasWYM1a9bk+Zzjxo1D27ZtcePGDXTq1Ant27dHVFSUElqTP7OmT0HN2vXwU/WaeZ537+4dPIi+h1at2yopmfJJJBKcOXUSNja26P9HL/jUq4muHX/DifBjX39wESYWi3HwwH6kpqbAw8NT6DhKlfTxIwDAyNhY4CTKxXarV7szMzNwYN/f8GvTFiIVH9sTG/sPfm5QGy2a+mDMqGGIi3shdKQCuXDzCRp4lYejdUkAgFt5S3h72OHIuXsAAB2t7OvoaelZssdIpVJkZGahpoed7BypVIr0jH/PScvIhEQiRc3KdspqitK9ef0aZ05HoHUb1f3cQgXHSlQBxcXFISsrC/7+/rCxsQEAuLm5ye43MTHBwoULoampiYoVK6JFixYIDw9Hnz59vvicv/76K3r37g0AmDx5Mo4ePYoFCxZg8eLFuZ6fnp6O9PR0+WNZxaCjo7hhZEcPH0D0vbtYtX7bV8/du2cnbO3s4a7CH7ITE98gJSUFq1ctR/+BAQgYOhznzpzG8KGDsGzlWlRVsSu4D+5Ho0vH9sjISIeenh7mzl8EB0dHoWMpjUQiQciMaajsWQXly1cQOo7SsN3q1W4AOB5+DB8/foRv6zZCR1EoN3d3BE0Jhq2tHV6/TkDY4kXo2bUTduzeC319A6HjfZdZa0/ASF8XN7aNhFgihaaGCBOWHMKWw5EAgOgn8YiNe4vJA5pjYPAOJKdmYHDHuihXqgRKlzQCAFy6/Q+S0zIwdWALjF98ECKRCFMGNkexYpoobWYoZPMUau/fu6Gnp4+G6j6UT7WvmxQYK1EF5OHhAR8fH7i5ueHXX3/F8uXL8fbtW9n9rq6ucuOqLS0tER8fn+dzent757idVyUqODgYxsbGcl+hs6Z/Z4u+7tXLOMydGYxJU0K+2lFLS0vDkYP7VboKBQBSiQQAUL9+Q3Tu2h1OFZ3Ro/fvqFOvPnZs3yJwusJna2uHbTt3Y8Pmbfi1XQeM+98oPIyJETqW0kybMgkPHzxAyKy5QkdRKrZbvdoNALv/2olatevCwqKU0FEUqnademjcpBkqOFVEzVp1sHDJMnz8+AFHDh0UOtp3+6WRB9o3rYLu4zbBu8tc9J60BUM610OnFl4AgCyxBO1HrYGjdUnEhU9G4qlpqFvVAYfORkEiyR5N8/pdMjqNWY/mdVzwOmIqXh2fDGOD4rgW9QySIjQfKr/+3rUTzVq0VOjFaCr6WIkqIE1NTRw9ehTnzp3DkSNHsGDBAvz555+4ePEiAMjmPn0iEokg+f8P3IVlzJgxCAwMlDuWnKW4H+29qDt4m/gG3Tv9O09LLBbj+rUr2LltEyIuXJd1HE8cO4K0tFQ0a+mnsDw/ghImJihWrBjsHeSrMXZ2DrgeeVWgVIqjpa0N6/+vvLq4VsKd27ewccM6jJ8YJHAyxZs2JQinIk5i1doNKFW6tNBxlIbtVq92A8CLF89x8cI5zA5dIHQUpTMyMoK1jS2exsYKHeW7TRvcErPWHsf2o9cBAHcevoS1pQlGdGuIjfuvAAAi7z1Hjc5zYaSvC20tTbx+l4xTqwbjatRT2fOEX7wPV//pMDPWQ5ZYgvdJaXh8cDyeHE0UolkKd+3qFTx58hjT1fCiyX9xn6i8sRNVCEQiEWrVqoVatWph/PjxsLGxwa5du777+S5cuICuXbvK3fb0/PJQOB0dnRxXS7KSxV84u+C8fvLGhm175I5NnfgnbGzt0Ll7b7nK2949O1GnXkOYmJj+92lUipaWNlxcK+HJk8dyx2P/eaJSy5t/iUQiQWZGhtAxFEoqlSJ46mQcDz+KlWvWo1w59ZhszHarV7s/t2fXXzA1NUOduvWFjqJ0KSnJePb0KUq2KroLTRTX1cpRLRKLpdDQyPnB+ENyGgDAwaokqjiXw6SlOZd2f/M+BQBQz8sRFiYG2HfqjgJSC2/PXzvg7OKKCk65L3lO9Ak7UQV08eJFhIeHo3HjxrCwsMDFixeRkJAAZ2dn3Lx587uec/v27fDy8kLt2rWxceNGXLp0CStXrvz6A5VEX18fDv9ZhU23eHEYGZeQO/409h9cv3YFs+eHKTuiQqSkJMtdlXz+/Bmi70XByNgYlpZl0LVHL4weHogqVb3g9VN1nDtzGqciTmDZqnUCpi588+bORu06dVHa0hIpyck4sH8frly+lGM1M1UzbfIkHDywD6ELFkNfTx+vExIAAAaGhtDV1RU4neKw3erV7k8kEgn+3v0XWvm1RrFiqv9RYc7MGahbvwEsy5RBQnw8lixaAE1NDTRt3lLoaN/twOm7GNXdB09fvsPdRy9R2aksBnesi3V7L8vO8fdxR8LbZDx9+RaVHC0xK9APeyNuI/zifdk5XVpWQ/STV0h4m4zqbjaYNcwPCzafxoPYBCGa9d2+9h4OAElJSTh69DACh48SKuYPRcXXkikw1f/LqGBGRkY4deoUQkND8eHDB9jY2GD27Nlo1qwZtm7d+l3POWnSJGzZsgX9+/eHpaUlNm/eDBcXl0JOrnj79vwFi1KlUN27ltBRCsXdO7fxe89usttzZmbPO2vl2xqTpk5HQ5+f8b/xE7F6xTLMnD4VNrZ2mDlnPjyrVBUqskIkJr7B2DGjkJAQDwNDQ1So4IQly1bCu6Zq/Jy/ZNvWzQCAXt27yB0PmhIMvzb+QkRSCrZbvdr9yYXz5xAX90JtVid79eolxowMxLt372BiagpPz6pYt3FbjuXei5LAWbsx4Y8mmDfSH+YmBoh7/R4rd13AtBVHZeeUNjPCjCG+sDA1wMvXH7HxwBUEr5RfVbaCjTmCBjSDqZEe/ol7i5DV4Zi/6ZSym1NgX3sPB4DDB/cDUimaNGshSEYqWkTSorRTmhoQiUTYtWsXWrduXaDnSVTgcL4fmY6Weq6VopnL8AwiUg18l1YvprWGCx1BEK/PzBQ6giD0tX/c9++H8alK+T4OFsWV8n0Km3p+4iQiIiIiIvpO7EQRERERERHlA+dE/WA4upKIiIiIBPfjjjT8IbASRURERERElA+sRBERERERkRxutps3VqKIiIiIiIjygZUoIiIiIiKSw81288ZKFBERERERUT6wEkVERERERHJYiMobK1FERERERET5wEoUERERERHJYykqT6xEERERERER5QMrUUREREREJIf7ROWNlSgiIiIiIqJ8YCWKiIiIiIjkcJ+ovLESRURERERElA+sRBERERERkRwWovLGShQREREREVE+sBJFRERERERyOCcqb6xEERERERER5QMrUURERERE9B8sReVFJJVKpUKHoML3MV0idARBZGSpZ7v1ddTzeoi6/vXiEAv1IlHXX3Q1JZao58/botFEoSMIIvV0kNARvujZ2wylfJ9yJtpK+T6FjcP5iIiIiIiI8kE9L18TEREREdEXcdRD3liJIiIiIiIiygdWooiIiIiISA4LUXljJYqIiIiIiCgfWIkiIiIiIiI5nBOVN1aiiIiIiIiI8oGVKCIiIiIikiPirKg8sRJFRERERESUD6xEERERERGRPBai8sRKFBERERERUT6wEkVERERERHJYiMobK1FERERERET5wEoUERERERHJ4T5ReWMlioiIiIiIKB9YiSIiIiIiIjncJypvrEQRERERERHlAytRREREREQkj4WoPLESRURERERElA/sRBEREREREeUDO1E/mCdPnkAkEuH69etCRyEiIiIiNSVS0ldRxTlR36h+/fqoXLkyQkNDhY4iuNUrluFE+FE8efwIOjq6cK/siUFDhsHWzk52ztSgCbh04TxeJ8SjuJ4e3D08MXjoMNja2QuYvGBWhC3CqmWL5Y5Z29phy1/7AAC7d27D0UMHEH3vLlKSk3E44jwMDY2EiKpwV69cxppVKxF19zYSEhIwd/4iNPRpJHQshXv16hXmzZmJs2dOIy0tFVbWNpg0eRpcK7kJHU1htm3ZhG1bN+PF8+cAAAfH8vijX3/UrlNP4GSKtXL5UoQfPYLHjx9BR1cXlSt7Ykjg8CL9N+xbJScnYfGC+TgefgxvE9/AqaIzRo7+E65uqvt7DqhHu7/l/fsTqVSKgP5/4NzZ05gVugD1Gxadv/EaGiKM7dEAHRp7oJSZAeJef8T6g5GYvjZCdk7q6aBcH/u/xYcxd/NZWJcugTHd6qF+FXvZc2w+cgMz1p1CZpZYWU2hHxg7UYVEKpVCLBajWDHV/ye9duUyfm3fES6ulSAWi7Fo/lwM7NsL23ftQ3E9PQCAs4srmjVvidKWZfDh/TssXbIIA/7ojb8PHoWmpqbALfh+dg6OmL9khey2pua/P+/0tDRUr1kL1WvWQtiCUAHSKU9qagqcnJzQ2r8tAgMGCh1HKT68f4/uXTqg2k/VsTBsOUxNTPDPP//AyMhY6GgKZVGqNAKGDoe1jQ2kUin27tmNgIEDsHXnLjg6lhc6nsJcuXwJ7Tp0gqubG8RZYiyYNwd9+/TCX3/vh97//51TVUHjxyEm5gGmBM+AuYUFDuz9G3379MDOPfthUaqU0PEURh3a/S3v359s2rC2yJYJhnWqgz6tq6HPtF24+zgeVSuWwdIxbfAhKQ2Ld14EANj6hcg9pnGN8ggb5YddJ+8CAJysS0JDQ4SBs/7Gw2eJcLW3wKKRftDX1caYxYeV3iYhcLPdvHE43zfo3r07IiIiMG/ePIhEIohEIqxZswYikQgHDx5E1apVoaOjgzNnzqB79+5o3bq13OOHDBmC+vXry25LJBKEhITA0dEROjo6sLa2xtSpU3P93mKxGD179kTFihURGxurwFZ+uwVhy9HKrw0cHMujglNFTJwcjJdxcYi6e0d2jv8vv6GKVzWUKVsWFV1c0X9QAF69jEPci+cCJi+4YpqaMCtpLvsqYWIiu69dp67o2qMPKrl5CJhQOWrXqYeBAUPh0+hnoaMozepVy1G6dGkETQmGm5s7ypazQs1atWFlbS10NIWq36Ah6tStBxsbW9ja2mFQwFDo6enh5o3rQkdTqCXLVsKvjT8cHcvDqWJFBE2djri4F3J/51RRWloawo8dwZDA4ajqVQ3W1jboO2AQrKytsX3rZqHjKYy6tPtb3r8BIPpeFDauXYPxQbl/NvnR1ahkhX1n7uHQ+fuIffkOu07eRfilGHi5lJOd8yoxSe6rVe2KiIh8gidxbwEARy/F4I/g3Qi//BBP4t5i/9lozNtyFn71nIVqFv1gVL9sUgjmzZuH+/fvo1KlSggKyi7/3rmT/Qdn9OjRmDVrFuzt7WHy2QfqvIwZMwbLly/H3LlzUbt2bcTFxeHevXs5zktPT0eHDh3w5MkTnD59Gubm5oXXqEKUlPQRAGBknPsV+dSUFPy9+y+ULVsOpUqXVma0Qvc0Nha+jetDW0cHldw90HfgEJS2LCN0LFKCiBPH4V2rNoYHDsbVK5dhYVEKv7XviLa//CZ0NKURi8U4cvgQUlNT4OHhKXQcpUr6mPffOVUhFmdBLBZDW0dH7riOji4ir10VKJXiqWu7c3v/TktNxdjRIzDyz3EoWfLH/NzxNRduP0WvVlXhaGWGmKdv4OZQCt7uNhi98FCu51uY6KOpdwX0mfpXns9rpK+LxA+pioj8Q+Jmu3ljJ+obGBsbQ1tbG3p6eij9/52AT52eoKAg/Pzzt1+N//jxI+bNm4eFCxeiW7duAAAHBwfUrl1b7rykpCS0aNEC6enpOHHiBIzzeONOT09Henq63LEMaEHnP28GiiCRSDA7JBgenlXgWL6C3H3bt2zC/LmzkZqaAhtbOyxathJaWtoKz6Qorm7uGDtpKqxtbPH6dQJWLVuCfr26YsP2PdDX1xc6HinYs2dPsX3rZnTu2gO9+/TF7du3EBI8BVpaWvD1ayN0PIV6cD8aXTq2R0ZGOvT09DB3/iI4ODoKHUtpJBIJQmZMQ2XPKij/n79zqkZf3wDuHpWxPGwx7OztYWZWEocO7MfNG9dVuuqqju3+0vv37JnT4e5RGfUb+AiYrmBmbTgNIz0d3NgwCGKJFJoaIkxYHo4tR2/men7nZp74mJKO3aeivvic9mVN0a9tdbUZykdfx+F8BeTl5ZWv86OiopCeng4fn7z/OHXo0AHJyck4cuRInh0oAAgODoaxsbHc1+yQ6fnK9b1mTA3Cw5gHmDZjdo77mrVohY3bdmLZqnWwtrHF6OFDc3T2ihLvWnXQ8OcmcKzghBo1a2P2giVISvqI40dzv7JFqkUikaKisysGDwlERWcX/PJrO/i3/Q07tm0ROprC2draYdvO3diweRt+bdcB4/43Cg9jYoSOpTTTpkzCwwcPEDJrrtBRlGJKcAikkKJJw3qoXsUdmzeuR9NmLaAhUu2PDOrW7tzevyNOHMeVSxcwbNQYAZMV3C8NXdH+Z3d0D9oB715L0HvaLgxpXwudmlbO9fyuzT2x9ehNpGdk5Xp/mZKG+HtWF/x18g5W71XdyuR/iUTK+SqqWIkqoP9WIDQ0NCCVSuWOZWZmyv6/ePHi3/S8zZs3x4YNG3D+/Hk0bNgwz3PHjBmDwMBAuWMZ0Pqm71MQM6ZNxplTEVi2en2uw/QMDA1hYGgIaxtbuHl4oEGtGjgRfgxNm7dQeDZlMDQ0gpW1DZ49/THmqpFimZubw8HBQe6Ynb09jh1T/auSWtrasLaxAQC4uFbCndu3sHHDOoyfmPvqVqpk2pQgnIo4iVVrNxT54cjfysraGivXbEBqSgqSkpNgbm6BUcOGomw5K6GjKZQ6tftL799XLl3As6dP0aBWdbnzRwYGoHKVqli2ap2yo36Xaf2aYNbG09gefhsAcOdRPKxLlcCIznWw8dB1uXNrudvAycYcXSZsy/W5LM0McWh+D1y4/RQDQv5WdHQqQtiJ+kba2toQi7++pKW5uTlu374td+z69evQ0sru1JQvXx7FixdHeHg4evfu/cXn6devHypVqgRfX1/s378f9ep9eTlhHR2dHEP3PqZLvpr1e0mlUoQET8HJ48ewdOValC1X7hseA0ghRWZmhsJyKVtKSjKeP3uKpi18hY5CSuDhWQVPnjyWO/bPP09gaVlWoETCkUgkyMxQnddybqRSKYKnTsbx8KNYuWY9yqngB+mvKa6nh+J6evjw/j3OnTuDIYHDhY6kFKrc7q+9f3fr1Qd+/r/IHWvf1g+BI0ajTr0GyoxaIMV1tSD5zwVtsUQCDY2cZY9uLavg6r3nuPXwVY77ypTM7kBFRr/A78G7clwkJ/XGTtQ3srW1xcWLF/HkyRMYGBhAIsm9k9KwYUPMnDkT69atg7e3NzZs2IDbt2/D0zN7Erauri5GjRqFkSNHQltbG7Vq1UJCQgLu3LmDXr16yT3XoEGDIBaL0bJlSxw8eDDHvCmhzJgahEMH92P2vIXQ09fH69cJAAADA0Po6uri2bOnOHroIGrUrAUTExO8evUKa1Yuh66ODmrVritw+u+3YO5M1K5bH6Uty+B1QjxWhC2CpoYmfm7aHADw5nUC3rx5LatMPXzwAHr6eihd2hJGxiUETF74UpKT5VaLfP7sGe5FRcHY2BiWZVRzoY3OXbqhe5cOWLEsDI2bNsPtWzexc8c2jJug2tWYeXNno3aduihtaYmU5GQc2L8PVy5fwpJlK4WOplDTJk/CwQP7ELpgMfT19PE64f//zhlm/51TZefOnoZUmj2M82nsP5g7eybs7Ozh29pf6GgKpQ7t/tr7d8mS5rkuJlHa0vKbLpj+KA6ci8aoLnXx9NV73H0cj8rlLTG4XU2s239N7jxDPR3413fF6EU5h+WXKWmIw/N7IvbVO4xZdBjmJf4defQqMUnhbaAfHztR32j48OHo1q0bXFxckJqaitWrV+d6XpMmTTBu3DiMHDkSaWlp6NmzJ7p27Ypbt27Jzhk3bhyKFSuG8ePH48WLF7C0tETfvn1zfb4hQ4ZAIpGgefPmOHToEGrWrKmQ9uXHpzkgf/TsJnd8wuRpaOXXBjraOoi8dgWbN6zDhw8fYGZmBs+qXli5bjNMzcyEiFwo4l+9woQxI/D+/TuUMDGFe+UqWLZ2E0xMTAEAu3Zsk9uMt3/vrgCAPydOQQtf1Vp44M6d2+jdo6vs9qyQYACAr18bTJ6mnPl4ylbJzR1zQhdi/rw5WBa2CGXLlsOIUf9Di5aqXYlMTHyDsWNGISEhHgaGhqhQwQlLlq2Ed81aQkdTqG3/v6x1r+5d5I4HTQmGXxvV+VCdm6SPSVgQOgevXr2EsXEJ+Pz8MwYMHiobUaGq1KHdX3v/VhWBc/djQm8fzAtsCXMTfcS9/oiVe65g2pqTcuf96lMJIhGw7ditHM/RsJoDHK3M4Ghlhoe7RsjdV7zOeEXG/2EU5flKyiCSsjapkhQ5nO9HlpGlnu3W11HP6yHq+teLb2zq5b/Dkki1iSXq+fO2aDRR6AiCSD39445meJf69WkshaFEcU2lfJ/Cpp6fvIiIiIiI6Iu4T1TeVHPdTiIiIiIiIgVhJYqIiIiIiORw6HjeWIkiIiIiIiLKB1aiiIiIiIhIDgtReWMlioiIiIiIKB9YiSIiIiIiInksReWJlSgiIiIiIqJ8YCeKiIiIiIgoHzicj4iIiIiI5HCz3byxEkVERERERJQPrEQREREREZEcbrabN1aiiIiIiIiI8oGVKCIiIiIiksNCVN5YiSIiIiIiIsoHVqKIiIiIiEgeS1F5YiWKiIiIiIgoH9iJIiIiIiIiOSIl/fc9Fi1aBFtbW+jq6qJ69eq4dOlSIbf+69iJIiIiIiKiImHr1q0IDAzEhAkTcO3aNXh4eKBJkyaIj49Xag52ooiIiIiISI5IpJyv/JozZw769OmDHj16wMXFBWFhYdDT08OqVasK/x8hD+xEERERERGRINLT0/Hhwwe5r/T09FzPzcjIwNWrV9GoUSPZMQ0NDTRq1Ajnz59XVuRsUqJClJaWJp0wYYI0LS1N6ChKxXaz3eqA7Wa71QHbzXaTck2YMEEKQO5rwoQJuZ77/PlzKQDpuXPn5I6PGDFC+tNPPykh7b9EUqlUqtxuG6myDx8+wNjYGO/fv4eRkZHQcZSG7Wa71QHbzXarA7ab7SblSk9Pz1F50tHRgY6OTo5zX7x4gbJly+LcuXPw9vaWHR85ciQiIiJw8eJFhef9hPtEERERERGRIL7UYcpNyZIloampiVevXskdf/XqFUqXLq2IeF/EOVFERERERPTD09bWRtWqVREeHi47JpFIEB4eLleZUgZWooiIiIiIqEgIDAxEt27d4OXlhZ9++gmhoaFITk5Gjx49lJqDnSgqVDo6OpgwYcI3l2VVBdvNdqsDtpvtVgdsN9tNP7Z27dohISEB48ePx8uXL1G5cmUcOnQIpUqVUmoOLixBRERERESUD5wTRURERERElA/sRBEREREREeUDO1FERERERET5wE4UERERERFRPrATRURERERElA/sRBERfYN169YhPT09x/GMjAysW7dOgESKl5mZiZ49e+Lx48dCRyEiKhTPnj374n0XLlxQYhIq6tiJokKTkZGB6OhoZGVlCR1FaU6fPo3OnTvD29sbz58/BwCsX78eZ86cETgZFbYePXrg/fv3OY5//PhR6Rv8KYuWlhZ27twpdAwiUpDo6GgMHDgQPj4+8PHxwcCBAxEdHS10LIVq3LgxEhMTcxw/e/YsmjZtKkAiKqq42S4VWEpKCgYNGoS1a9cCAO7fvw97e3sMGjQIZcuWxejRowVOqBg7d+5Ely5d0KlTJ0RGRsqqFO/fv8e0adNw4MABgRNSYZJKpRCJRDmOP3v2DMbGxgIkUo7WrVtj9+7dGDp0qNBRlMrExCTXn7dIJIKuri4cHR3RvXt3lepABwYG5nr88zb7+fnB1NRUycmUY/369QgLC8Pjx49x/vx52NjYIDQ0FHZ2dvDz8xM6XqHbuXMn2rdvDy8vL3h7ewPIrsRUqlQJW7ZsQdu2bQVOqBg1atRA48aNceLECRgaGgIATp06hVatWmHixInChqMihZvtUoEFBATg7NmzCA0NRdOmTXHz5k3Y29tjz549mDhxIiIjI4WOqBCenp4YOnQounbtCkNDQ9y4cQP29vaIjIxEs2bN8PLlS6EjFhpPT89cP1Dm5tq1awpOo1yf2n7jxg24urqiWLF/rz2JxWI8fvwYTZs2xbZt2wRMqThTpkzB7Nmz4ePjg6pVq0JfX1/u/sGDBwuUTLHmzp2LqVOnolmzZvjpp58AAJcuXcKhQ4cwdOhQPH78GOvXr8eCBQvQp08fgdMWjgYNGuDatWsQi8VwcnICkH1RTFNTExUrVkR0dDREIhHOnDkDFxcXgdMWriVLlmD8+PEYMmQIpk6ditu3b8Pe3h5r1qzB2rVrceLECaEjFjoHBwd06tQJQUFBcscnTJiADRs24OHDhwIlUyyJRIJffvkFiYmJOHz4MM6dOwdfX19MmTIFAQEBQsejIoSdKCowGxsbbN26FTVq1JDrTMTExKBKlSr48OGD0BEVQk9PD3fv3oWtra1cux89egQXFxekpaUJHbHQTJo0Sfb/aWlpWLx4MVxcXOSuXt65cwf9+/dHcHCwUDEV4lPbJ02ahGHDhsHAwEB2n7a2NmxtbdG2bVtoa2sLFVGh7OzsvnifSCTCo0ePlJhGedq2bYuff/4Zffv2lTu+dOlSHDlyBDt37sSCBQuwbNky3Lp1S6CUhSs0NBSnT5/G6tWrYWRkBCC7st67d2/Url0bffr0QceOHZGamorDhw8LnLZwubi4YNq0aWjdurXc3/Pbt2+jfv36eP36tdARC52enh5u3rwJR0dHueMPHjyAh4cHUlJSBEqmeBkZGWjRogVSUlJw8+ZNBAcHY+DAgULHoiKGw/mowBISEmBhYZHjeHJy8jdXL4qi0qVLIyYmBra2tnLHz5w5A3t7e2FCKciECRNk/9+7d28MHjwYkydPznHO06dPlR1N4T613dbWFu3atYOurq7AiZRLXReVOHz4MGbMmJHjuI+PD4YNGwYAaN68uUoNV545cyaOHj0q60ABgLGxMSZOnIjGjRsjICAA48ePR+PGjQVMqRiPHz+Gp6dnjuM6OjpITk4WIJHi1a9fH6dPn87RiTpz5gzq1KkjUCrFuHnzZo5jEydORIcOHdC5c2fUrVtXdo67u7uy41ERxU4UFZiXlxf279+PQYMGAYCs47RixQpZpUIV9enTBwEBAVi1ahVEIhFevHiB8+fPY/jw4Rg3bpzQ8RRm+/btuHLlSo7jnTt3hpeXF1atWiVAKsXr1q2b0BEElZGRgcePH8PBwUFuSKOqMjU1xd69e3PMBdu7d69sTlBycrJsToUqeP/+PeLj43MM1UtISJCNKChRogQyMjKEiKdQdnZ2uH79OmxsbOSOHzp0CM7OzgKlUixfX1+MGjUKV69eRY0aNQBkjyrYvn07Jk2ahL///lvu3KKscuXKEIlE+Hzw1afbS5cuxbJly2TzXsVisYBJqShR/XdCUrhp06ahWbNmuHv3LrKysjBv3jzcvXsX586dQ0REhNDxFGb06NGQSCTw8fFBSkoK6tatCx0dHQwfPlzWoVRFxYsXx9mzZ1G+fHm542fPnlXpKo1YLMbcuXOxbds2xMbG5vggmdtqT6pAXReOGTduHPr164cTJ07I5kRdvnwZBw4cQFhYGADg6NGjqFevnpAxC5Wfnx969uyJ2bNno1q1agCy2zx8+HC0bt0aQPa8sAoVKgiYUjECAwMxYMAApKWlQSqV4tKlS9i8eTOCg4OxYsUKoeMpRP/+/QEAixcvxuLFi3O9D4BKdCzUtaJOCiYlKgQxMTHS3r17S6tVqyZ1dnaWdurUSXrz5k2hYylFenq69M6dO9KLFy9KP378KHQchQsODpbq6upKBw0aJF2/fr10/fr10oEDB0r19PSkwcHBQsdTmHHjxkktLS2ls2bNkurq6konT54s7dWrl9TMzEw6b948oeMpzODBg6VVq1aVnj59Wqqvry99+PChVCqVSnfv3i2tXLmywOkU68yZM9L27dtLPT09pZ6entL27dtLz549K3Qshfn48aO0d+/eUm1tbamGhoZUQ0NDqq2tLe3Tp480KSlJKpVKpZGRkdLIyEhhgyrIhg0bpI6OjlKRSCQViUTSsmXLSlesWCF0LCL6QXFhCSLKt23btmHevHmIiooCADg7OyMgIAC//fabwMkUx8HBAfPnz0eLFi1gaGiI69evy45duHABmzZtEjqiQqjrwjHqLCkpSbZgiL29vdxiKuogJSUFSUlJuc71paIvODgYpUqVQs+ePeWOr1q1CgkJCRg1apRAyaio4XA+KhQSiQQxMTGIj4+HRCKRu69u3boCpSp8/v7+33zuX3/9pcAkwsjKysK0adPQs2dPle4w5ebly5dwc3MDABgYGMg23m3ZsqVKz4FT14VjgOwhnLt375ZdLHB1dYWvry80NTUFTqZYBgYGsnlf6tKBSk1NhVQqhZ6eHvT09JCQkIDQ0FC4uLio1EIa8+fPx++//w5dXV3Mnz8/z3NVdfuCpUuX5nrRy9XVFe3bt2cnir4ZO1FUYBcuXEDHjh3xzz//4L+FTVUYS/05Vd5U9VsUK1YMISEh6Nq1q9BRlK5cuXKIi4uDtbU1HBwccOTIEVSpUgWXL1+Gjo6O0PEURl0XjomJiUHz5s3x/Plz2Z5JwcHBsLKywv79++Hg4CBwwsInkUhk+4IlJSUBAAwNDTFs2DD8+eef0NDQEDih4vj5+cHf3x99+/bFu3fv8NNPP0FbWxuvX7/GnDlz0K9fP6EjFoq5c+eiU6dO0NXVxdy5c794nkgkUtlO1MuXL2FpaZnjuLm5OeLi4gRIREUVO1FUYH379pV90LK0tFTpq9OrV68WOoLgfHx8EBERkWNpd1XXpk0bhIeHo3r16hg0aBA6d+6MlStXIjY2NscKbqpEXReOGTx4MBwcHHDhwgVZVebNmzfo3LkzBg8ejP379wucsPD9+eefWLlyJaZPn45atWoByF7ueuLEiUhLS8PUqVMFTqg4165dk3UqduzYgdKlSyMyMhI7d+7E+PHjVaYT9fkCC+q62IKVlRXOnj2bYw+8s2fPokyZMgKloqKIc6KowPT19XHjxo0ce02QagoLC8OkSZPQqVMnVK1aFfr6+nL3F/WlcL/VhQsXcO7cOZQvXx6tWrUSOo5CPXz4ENOnT8eNGzeQlJSEKlWqYNSoUbLhjapIX18fFy5cyNHGGzduoFatWrJKjSopU6YMwsLCcryG9+zZg/79++P58+cCJVM8PT093Lt3D9bW1vjtt9/g6uoq2/vOyclJpTeeVTchISEICQnBzJkz0bBhQwBAeHg4Ro4ciWHDhmHMmDECJ6SigpUoKrDq1asjJiZGLTpRVapUQXh4OExMTODp6Zln1e3atWtKTKY8n5a+nTNnTo77VG345uf+Oxm5Ro0aqFGjBlatWoUZM2ao9Dh6BwcHLF++XOgYSqWjo4OPHz/mOJ6UlARtbW0BEileYmIiKlasmON4xYoVVXYJ/08cHR2xe/dutGnTBocPH5ZVl+Pj4+U2H1YlYrEYa9asQXh4eK7zmY8fPy5QMsUaMWIE3rx5g/79+8u2qtDV1cWoUaPYgaJ8YSeKCmzQoEEYNmyYbOK9lpaW3P2qtPu3n5+fbP7Lp31T1M1/32jVhTpPRn748CFWr16NR48eITQ0FBYWFjh48CCsra3h6uoqdDyFaNmyJX7//XesXLlStk/UxYsX0bdvX5Wttnp4eGDhwoU5FhxYuHAhPDw8BEqlHOPHj0fHjh0xdOhQ+Pj4yOb7HTlyBJ6engKnU4yAgACsWbMGLVq0QKVKlVR6KP7nRCIRZsyYgXHjxiEqKgrFixdH+fLlVXpuKykGh/NRgeU22fjTTuCqXJkg9aKrq4uoqKgc4+gfPXoEFxcXpKWlCZRMsSIiItCsWTPUqlULp06dQlRUFOzt7TF9+nRcuXIFO3bsEDqiQrx79w7dunXD3r17ZReGMjMz4efnh9WrV6NEiRLCBlSAiIgItGjRAtbW1rJOxPnz5/H06VMcOHAAderUETihYr18+RJxcXHw8PCQva9dunQJRkZGuVboirqSJUti3bp1aN68udBRiIokVqKowNR1cuonV65ckS2B7OLigqpVqwqcqPBxWVz1nYw8evRoTJkyBYGBgTA0NJQdb9iwIRYuXChgMsUqUaIE9uzZg5iYGLn90FR52HK9evVw//59LFq0CPfu3QOQva1D//79Vfp3PDMzE8WLF8f169dzVJ0+VSFVkba2tkr/Pn9JgwYN8qy6qeowRip87ERRgdnY2AgdQRDPnj1Dhw4dcPbsWdlV6Xfv3qFmzZrYsmULypUrJ2zAQsRlcYE+ffpgyJAhyMzMzHUysqq6detWrsMYLSws8Pr1awESKU5gYGCe9584cUL2/7nNCSzKMjMz0bRpU4SFhan0Kny50dLSgrW1tdqNmhg2bBjmzZuHhQsXqs1QPgCoXLmy3O3MzExcv34dt2/fRrdu3YQJRUUSO1FUaO7evYvY2FjZRM1PVHX+QO/evZGZmYmoqCjZPjLR0dHo0aMHevfujUOHDgmcsPB8aVncT6OB1eENWF0nI5coUQJxcXE5KnCRkZEoW7asQKkUIzIyUu72tWvXkJWVJXt9379/H5qamipZbdbS0sLNmzeFjiGYP//8E//73/+wfv162ZL2qui/G8YfP34cBw8ehKura475zKq4YTyAL14InDhxokquukmKwzlRVGCPHj1CmzZtcOvWLdlcKODfD9aqenWvePHiOHfuXI7hH1evXkWdOnVUeknclStXYu7cuXjw4AEAoHz58hgyZAh69+4tcDLFS0pKUqvJyMOHD8fFixexfft2VKhQAdeuXcOrV6/QtWtXdO3aFRMmTBA6okLMmTMHJ0+exNq1a2FiYgIAePv2LXr06IE6deqoZPVx6NCh0NHRwfTp04WOonSenp6IiYlBZmYmbGxscmzdoCqrrfbo0eObz1W3fRFjYmLw008/qfxKlFR4WImiAgsICICdnR3Cw8NhZ2eHS5cu4c2bNxg2bBhmzZoldDyFsbKyQmZmZo7jYrFYpecPjB8/HnPmzMGgQYPkJp8PHToUsbGxCAoKEjihYhkYGKBatWpCx1CaadOmYcCAAbCysoJYLIaLiwuysrLQqVMnjB07Vuh4CjN79mwcOXJE1oECABMTE0yZMgWNGzdWyU5UVlYWVq1ahWPHjuW6B5yqDWH8nLqstvp5xyg1NRUSiUT2c37y5Al2794NZ2dnNGnSRKiIgjl//jx0dXWFjkFFCCtRVGAlS5bE8ePH4e7uDmNjY1y6dAlOTk44fvw4hg0blmOIjKrYs2cPpk2bhkWLFsHLywtA9iITgwYNwqhRo1T2Tdnc3Bzz589Hhw4d5I5v3rwZgwYNUrl5MpTt6dOnuHXrFpKSkuDp6Yny5csLHUmhDA0NsXfvXtSvX1/u+IkTJ+Dr65vrHlJF0c2bN1GpUiVoaGigQYMGXzxPJBJxwr2Kady4Mfz9/dG3b1+8e/cOFStWhJaWFl6/fo05c+agX79+QkdUiP8OaZRKpYiLi8OVK1cwbtw4la2uU+FjJYoKTCwWy1btKlmyJF68eAEnJyfY2NggOjpa4HSFy8TERG7+T3JyMqpXr45ixbJfSllZWShWrBh69uypsp2ozMxMWafxc1WrVkVWVpYAiaiwfW2BhQsXLsj+X1WrE23atEGPHj0we/ZsuX2iRowYkeNDWFHm6emJuLg4WFhY4J9//sHly5dhZmYmdCzBXL16VbYao6urq8ruEQVkD1H8ND9ox44dKFWqFCIjI7Fz506MHz9eZTtRxsbGcrc1NDTg5OSEoKAgNG7cWKBUVBSxE0UFVqlSJdy4cQN2dnaoXr06QkJCoK2tjWXLlsHe3l7oeIUqNDRU6AiC69KlC5YsWZLjw/OyZcvQqVMngVJRYVLnBRY+CQsLw/Dhw9GxY0fZsN1ixYqhV69emDlzpsDpCk+JEiXw+PFjWFhY4MmTJ2q7mXZ8fDzat2+PkydPyq222qBBA2zZsgXm5ubCBlSAlJQU2QXQI0eOwN/fHxoaGqhRowb++ecfgdMphlgsRo8ePeDm5iY3VJfoe3A4HxXY4cOHkZycDH9/f8TExKBly5a4f/8+zMzMsHXrVtly0FR0fV6ZyMrKwpo1a2BtbY0aNWoAyL5CHxsbi65du2LBggVCxSQFUMcFFj6XnJyMhw8fAgAcHBxyzBMq6n7//XesW7cOlpaWiI2NRbly5aCpqZnruY8ePVJyOuVp164dHj16hHXr1sHZ2RlA9oqz3bp1g6OjIzZv3ixwwsLn7u6O3r17o02bNqhUqRIOHToEb29vXL16FS1atMDLly+FjqgQX9o4nSi/2IkihUhMTMwx9E0VicVi7N69W274h6+v7xc/hBRVec2V+BznTaiesmXL4siRI3B1dZU7fvv2bTRu3BgvXrwQKBkVlkOHDiEmJgaDBw9GUFCQ3KbKnwsICFByMuUxNjbGsWPHciwac+nSJTRu3Bjv3r0TJpgC7dixAx07doRYLIaPjw+OHDkCAAgODsapU6dw8OBBgRMqhpeXF2bMmAEfHx+ho1ARx+F8pBCqvM/GJzExMWjevDmeP38uG+YUHBwMKysr7N+/Hw4ODgInLDyfbzJK6uXDhw9ISEjIcTwhIUFlFldQd02bNgWQPR8oICDgi50oVSaRSHLskwRk75+lqkMcf/nlF9SuXRtxcXHw8PCQHffx8UGbNm0ETKZYU6ZMwfDhwzF58uRcV6E0MjISKBkVNaxE0XfJz8RqVd2wr3nz5pBKpdi4caOs0/jmzRt07twZGhoa2L9/v8AJiQqua9euOH36dK4LLNSpUwdr164VOCFRwfn5+eHdu3fYvHmzbIuK58+fo1OnTjAxMcGuXbsETkiFRUNDQ/b/n4+WkUqlEIlEKru3JRU+VqLou/x3dRt1FBERgQsXLshV3czMzDB9+nTUqlVLwGREhUddFlgg9bZw4UL4+vrC1tYWVlZWAIDY2Fi4ublhw4YNAqejwrR69WpYWVnlGHYvkUgQGxsrUCoqiliJIvpOpqam2LdvH2rWrCl3/OzZs2jVqhV3PSeVouoLLBBJpVKEh4fL5rg6OzujUaNGAqeiwqapqSlb1v9zb968gYWFBStR9M3YiaJCEx8fL9sXysnJKccfKFXTtWtXXLt2DStXrpQb5tSnTx9UrVoVa9asETYgERF9s/DwcISHhyM+Pj7HPKhVq1YJlIoKm4aGBl69epVj2fp//vkHLi4uSE5OFigZFTUczkcF9uHDBwwYMABbtmyRXcHR1NREu3btsGjRIpUd+jd//nx069YN3t7esgnJWVlZ8PX1xbx58wROR0RE32rSpEkICgqCl5cXLC0tVX5lWXX0aasOkUiEcePGQU9PT3afWCzGxYsXUblyZYHSUVHEShQVWLt27RAZGYkFCxbA29sbAHD+/HkEBASgcuXK2LJli8AJFevBgwe4d+8egOzhH46OjgInIiKi/LC0tERISAi6dOkidBRSkE9bdURERMDb2xva2tqy+7S1tWFra4vhw4ejfPnyQkWkIoadKCowfX19HD58GLVr15Y7fvr0aTRt2pSlcSIi+qGZmZnh0qVLKrU1BeWuR48emDdvHpcypwLjcD4qMDMzs1yH7BkbG8PExESARMohlUqxY8cOnDhxItcx9Kq6tDsRkarp3bs3Nm3ahHHjxgkdhRRs9erVQkcgFcFOFBXY2LFjERgYiPXr16N06dIAgJcvX2LEiBEq/YY0ZMgQLF26FA0aNECpUqU4hp6IqAj5NEcGyF7eetmyZTh27Bjc3d1zbLw7Z84cZccjoh8ch/NRgXl6eiImJgbp6emwtrYGkL2/ho6OTo6xxdeuXRMiokKYmppiw4YNaN68udBRiIgonz7NkfkakUiE48ePKzgNERU1rERRgbVu3VroCIIwNjaGvb290DGIiOg7nDhxQugIRFSEsRJFBSIWi3H27Fm4u7ujRIkSQsdRqrVr1+LQoUNYtWoVihcvLnQcIiIiIlISdqKowHR1dREVFQU7OzuhoyhVamoq2rRpg7Nnz8LW1jbHGHpVGrpIRERERP/icD4qsEqVKuHRo0dq14nq1q0brl69is6dO3NhCSIiIiI1wkoUFdihQ4cwZswYTJ48GVWrVoW+vr7c/aq6F8OX9sciIiIiItXGThQVmIaGhuz/P6/GSKVSiEQiiMViIWIpXMWKFbFt2za4u7sLHYWIiIiIlIjD+ajA1HWFo9mzZ2PkyJEICwuDra2t0HGIiIiISElYiSL6TiYmJkhJSUFWVhb09PRyLCyRmJgoUDIiIiIiUiRWoui73Lx5E5UqVYKGhgZu3ryZ57mqOtwtNDRU6AhEREREJABWoui7aGho4OXLl7CwsICGhgZEIhFy+1VS5TlRRERERKSeWImi7/L48WOYm5vL/l9dicVi7N69G1FRUQAAV1dX+Pr6QlNTU+BkRERERKQorERRobl79y5iY2ORkZEhOyYSidCqVSsBUylOTEwMmjdvjufPn8PJyQkAEB0dDSsrK+zfvx8ODg4CJyQiIiIiRWAnigrs0aNHaNOmDW7duiU3rO/TcueqOpyvefPmkEql2LhxI0xNTQEAb968QefOnaGhoYH9+/cLnJCIiIiIFEHj66cQ5S0gIAB2dnaIj4+Hnp4ebt++jVOnTsHLywsnT54UOp7CREREICQkRNaBAgAzMzNMnz4dERERAiYjIiIiIkXinCgqsPPnz+P48eMoWbIkNDQ0oKmpidq1ayM4OBiDBw9GZGSk0BEVQkdHBx8/fsxxPCkpCdra2gIkIiIiIiJlYCWKCkwsFsPQ0BAAULJkSbx48QIAYGNjg+joaCGjKVTLli3x+++/4+LFi5BKpZBKpbhw4QL69u0LX19foeMRERERkYKwEkUFVqlSJdy4cQN2dnaoXr06QkJCoK2tjWXLlsHe3l7oeAozf/58dOvWDd7e3rKNdrOysuDr68s9pIiIiIhUGBeWoAI7fPgwkpOT4e/vj5iYGLRs2RL379+HmZkZtm7dioYNGwodUaFiYmJkS5w7OzvD0dFR4EREREREpEjsRJFCJCYmwsTERLZCnyoKCgrC8OHDoaenJ3c8NTUVM2fOxPjx4wVKRkRERESKxE4U0XfS1NREXFwcLCws5I6/efMGFhYWKru0OxEREZG648ISRN9JKpXmWmm7ceOG3LLnRERERKRauLAEUT59GqYoEolQoUIFuY6UWCxGUlIS+vbtK2BCIiIiIlIkDucjyqe1a9dCKpWiZ8+eCA0NhbGxsew+bW1t2NrawtvbW8CERERERKRI7EQRfaeIiAjUrFlTtrw5EREREakHdqKIvlNsbGye91tbWyspCREREREpEztRRN9JQ0MjzyXcuTofERERkWriwhJE3ykyMlLudmZmJiIjIzFnzhxMnTpVoFREREREpGisRBEVsv3792PmzJk4efKk0FGIiIiISAG4TxRRIXNycsLly5eFjkFERERECsLhfETf6cOHD3K3pVIp4uLiMHHiRJQvX16gVERERESkaOxEEX2nEiVK5FhYQiqVwsrKClu2bBEoFREREREpGudEEX2niIgIudsaGhowNzeHo6MjihXj9QkiIiIiVcVOFFEB3b17F7GxscjIyJA77uvrK1AiIiIiIlIkXi4n+k6PHj2Cv78/bt68CZFIhE/XIz4N8eM+UURERESqiavzEX2ngIAA2NraIj4+Hnp6erh9+zZOnToFLy8vLm9OREREpMI4nI/oO5UsWRLHjx+Hu7s7jI2NcenSJTg5OeH48eMYNmxYjs14iYiIiEg1sBJF9J3EYjEMDQ0BZHeoXrx4AQCwsbFBdHS0kNGIiIiISIE4J4roO1WqVAk3btyAnZ0dqlevjpCQEGhra2PZsmWwt7cXOh4RERERKQiH8xF9p8OHDyM5ORn+/v6IiYlBy5Ytcf/+fZiZmWHr1q1o2LCh0BGJiIiISAHYiSIqRImJiTAxMcmxCS8RERERqQ52ooiIiIiIiPKBC0sQERERERHlAztRRERERERE+cBOFBERERERUT6wE0VERERERJQP7EQREdEPpXv37mjdurXsdv369TFkyBCl5zh58iREIhHevXun9O9NREQ/NnaiiIjom3Tv3h0ikQgikQja2tpwdHREUFAQsrKyFPp9//rrL0yePPmbzmXHh4iIlKGY0AGIiKjoaNq0KVavXo309HQcOHAAAwYMgJaWFsaMGSN3XkZGBrS1tQvle5qamhbK8xARERUWVqKIiOib6ejooHTp0rCxsUG/fv3QqFEj/P3337IheFOnTkWZMmXg5OQEAHj69Cl+++03lChRAqampvDz88OTJ09kzycWixEYGIgSJUrAzMwMI0eOxH+3L/zvcL709HSMGjUKVlZW0NHRgaOjI1auXIknT56gQYMGACDb9Lp79+4AAIlEguDgYNjZ2aF48eLw8PDAjh075L7PgQMHUKFCBRQvXhwNGjSQy0lERPQ5dqKIiOi7FS9eHBkZGQCA8PBwREdH4+jRo9i3bx8yMzPRpEkTGBoa4vTp0zh79iwMDAzQtGlT2WNmz56NNWvWYNWqVThz5gwSExOxa9euPL9n165dsXnzZsyfPx9RUVFYunQpDAwMYGVlhZ07dwIAoqOjERcXh3nz5gEAgoODsW7dOoSFheHOnTsYOnQoOnfujIiICADZnT1/f3+0atUK169fR+/evTF69GhF/bMREVERx+F8RESUb1KpFOHh4Th8+DAGDRqEhIQE6OvrY8WKFbJhfBs2bIBEIsGKFSsgEokAAKtXr0aJEiVw8uRJNG7cGKGhoRgzZgz8/f0BAGFhYTh8+PAXv+/9+/exbds2HD16FI0aNQIA2Nvby+7/NPTPwsICJUqUAJBduZo2bRqOHTsGb29v2WPOnDmDpUuXol69eliyZAkcHBwwe/ZsAICTkxNu3bqFGTNmFOK/GhERqQp2ooiI6Jvt27cPBgYGyMzMhEQiQceOHTFx4kQMGDAAbm5ucvOgbty4gZiYGBgaGso9R1paGh4+fIj3798jLi4O1atXl91XrFgxeHl55RjS98n169ehqamJevXqfXPmmJgYpKSk4Oeff5Y7npGRAU9PTwBAVFSUXA4Asg4XERHRf7ETRURE36xBgwZYsmQJtLW1UaZMGRQr9u/biL6+vty5SUlJqFq1KjZu3JjjeczNzb/r+xcvXjzfj0lKSgIA7N+/H2XLlpW7T0dH57tyEBGRemMnioiIvpm+vj4cHR2/6dwqVapg69atsLCwgJGRUa7nWFpa4uLFi6hbty4AICsrC1evXkWVKlVyPd/NzQ0SiQQRERGy4Xyf+1QJE4vFsmMuLi7Q0dFBbGzsFytYzs7O+Pvvv+WOXbhw4euNJCIitcSFJYiISCE6deqEkiVLws/PD6dPn8bjx49x8uRJDB48GM+ePQMABAQEYPr06di9ezfu3buH/v3757nHk62tLbp164aePXti9+7dsufctm0bAMDGxgYikQj79u1DQkICkpKSYGhoiOHDh2Po0KFYu3YtHj58iGvXrmHBggVYu3YtAKBv37548OABRowYgejoaGzatAlr1qxR9D8REREVUexEERGRQujp6eHUqVOwtraGv78/nJ2d0atXL6SlpckqU8OGDUOXLl3QrVs3eHt7w9DQEG3atMnzeZcsWYJffvkF/fv3R8WKFdGnTx8kJycDAMqWLYtJkyZh9OjRKFWqFAYOHAgAmDx5MsaNG4fg4GA4OzujadOm2L9/P+zs7AAA1tbW2LlzJ3bv3g0PDw+EhYVh2rRpCvzXISKiokwk/dLsXSIiIiIiIsqBlSgiIiIiIqJ8YCeKiIiIiIgoH9iJIiIiIiIiygd2ooiIiIiIiPKBnSgiIiIiIqJ8YCeKiIiIiIgoH9iJIiIiIiIiygd2ooiIiIiIiPKBnSgiIiIiIqJ8YCeKiIiIiIgoH9iJIiIiIiIiyof/A6IHxbWXwXN6AAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 1000x700 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Defining Custom CNN Model\n",
        "model = models.Sequential()\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "# These extract the most important visual features from the image.\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='elu', input_shape=(32, 32, 3)))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Conv2D(32, (3, 3), activation='elu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25)) # Adding Dropout for regularization\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='elu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='elu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25)) # Adding Dropout for regularization\n",
        "\n",
        "# Performing 2D Convolution + MaxPooling on the image, reducing its size.\n",
        "model.add(layers.Conv2D(128, (3, 3), activation='elu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Conv2D(128, (3, 3), activation='elu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.25)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(512, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(256, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(128, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Final Dense Layer (Output Layer having 10 neurons for 10 classes)\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Adding Softmax Activation to the output layer\n",
        "model.add(layers.Activation('softmax'))\n",
        "\n",
        "# Fitting the model\n",
        "fit(model,verbose=0, epochs=1000, optimizer=Adam(clipnorm=3.0, learning_rate=0.007), batch_size=512, callbacks=EarlyStopping(monitor='val_loss', patience=15, restore_best_weights=True), colors=('blue','purple','green','cyan'), do_display=True, do_save=True, save_name='model')\n",
        "del model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MgLq6tp5v27h"
      },
      "source": [
        "##### Comments"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eUgcRvXDv27h"
      },
      "source": [
        "* The above architecture managed to achieve an improved `Accuracy`, `Precision`, `Recall` and `F1-Score` of 82% on the test set using 531,818 model parameters.\n",
        "* Moreover, the `Precision`, `Recall` and `F1-Score` metrics were also improved, whilst incurring a lower `Loss`.\n",
        "* To facilitate best results the following factors were considered:\n",
        "    1. Utilised an `increasing the number of Convolutional Layers`, to ensure that the model can learn complex features.\n",
        "    2. Utilised a `large number of neurons and layers in the Dense Layer`, to ensure that the model can learn complex features.\n",
        "    3. Added the `softmax activation function` to the final Dense Layer, to ensure that the model would not overfit.\n",
        "    4. Utilised the `Adam optimizer` with `gradient clipping` and an `appropriate learning rate`, to ensure that the model would not overfit.\n",
        "    5. Utilised the `ELU` and `ReLU` activation functions as they were the best performing activation functions, to ensure that the model would not overfit.\n",
        "    6. Utilised an `Early Stopping callback`, to ensure that the model would not overfit.\n",
        "    7. Utilised several `Dropout layers`, to curb overfitting.\n",
        "    8. Utilised several `Batch Normalization layers`, to ensure that the model would not overfit.\n",
        "    9. Utilised a `large batch size`, to ensure that the model would not overfit.\n",
        "    10. Utilised a `large number of epochs`, to ensure that the model would not overfit.\n",
        "* From the above `training and validation accuracy and loss curves`, it can be noted that the model is not overfitting, as the curves are gradually converging.\n",
        "* From the above `confusion matrix`, it was noted that the model is generally performing well, however, it is struggling to classify the `cat` and `dog` classes correctly.\n",
        "* From the above `distinct diagonal line` in the `confusion matrix`, it was noted that the model is performing well, as the model is correctly classifying the majority of the classes."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "**<h3>CIFAR DecaLuminarNet: An Enhanced CNN Architecture for the CIFAR-10 Dataset</h3>**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "def fit_updated(model, epochs:int=100, optimizer=Adam(clipnorm=1.0), verbose:int=1, batch_size:int=256, callbacks=[EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True), ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=5, min_lr=0.00001)], colors:tuple=('blue','purple','green','cyan'), do_display:bool=False, do_save:bool=False, save_name:str='model'):\n",
        "    \"\"\"Function which fits a model to the training data and plots the training process.\n",
        "\n",
        "    Args:\n",
        "        model (keras.model): Model to fit\n",
        "        epochs (int, optional): Number of epochs to train for. Defaults to 10.\n",
        "        optimizer (str, optional): Optimizer to use. Defaults to 'adam'.\n",
        "        verbose (int, optional): Verbosity of training. Defaults to 1.\n",
        "        batch_size (int, optional): Batch size. Defaults to 32.\n",
        "        callbacks (list, optional): List of callbacks. Defaults to [EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)].\n",
        "        colors (tuple, optional): Colors to use for plotting. Defaults to ('blue','purple','green','cyan').`\n",
        "        do_save (bool, optional): Whether to save the model. Defaults to False.\n",
        "        save_name (str, optional): Name of the model to save. Defaults to 'model'.\n",
        "    \"\"\"\n",
        "\n",
        "    # Loading the model\n",
        "    model.compile(optimizer=optimizer,\n",
        "                    loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
        "                    metrics=['accuracy'])\n",
        "\n",
        "    # Printing the model summary\n",
        "    print(model.summary())\n",
        "\n",
        "    # Setting the start time\n",
        "    s=time()\n",
        "\n",
        "    # Training Model\n",
        "    history = model.fit(\n",
        "        train_images,\n",
        "        train_labels,\n",
        "        verbose=verbose,\n",
        "        steps_per_epoch=train_images.shape[0] // 128,\n",
        "        epochs=epochs,\n",
        "        validation_data=(test_images, test_labels),\n",
        "        callbacks=callbacks,\n",
        "        batch_size=batch_size,\n",
        "    )\n",
        "\n",
        "    # Printing the training time\n",
        "    print(f'\\033[36mTraining Time: {round(time()-s,2)}s\\033[0m')\n",
        "    print('*'*50)\n",
        "\n",
        "    # Plotting Training process\n",
        "    plt.figure(figsize=(10,7))\n",
        "    plt.style.use('seaborn-v0_8')\n",
        "    plt.plot(history.history['accuracy'], label='Train Accuracy', color = colors[0])\n",
        "    plt.plot(history.history['loss'], label = 'Train Loss', color = colors[1], linestyle='dashed')\n",
        "    plt.plot(history.history['val_accuracy'], label = 'Validation Accuracy', color = colors[2])\n",
        "    plt.plot(history.history['val_loss'], label = 'Validation Loss', color = colors[3], linestyle='dashed')\n",
        "    plt.title('Training Curves', fontsize=17)\n",
        "    plt.xlabel('Epoch', fontsize=14)\n",
        "    plt.ylabel('Accuracy', fontsize=14)\n",
        "    plt.legend(loc='upper right')\n",
        "    plt.grid(True)\n",
        "    plt.show()\n",
        "\n",
        "    # Testing the model\n",
        "    test_loss, test_acc = model.evaluate(test_images,  test_labels, verbose=2)\n",
        "\n",
        "    # Calculating the Precision, Recall and F1 Score\n",
        "    y_pred = model.predict(test_images)\n",
        "    y_pred = [np.argmax(i) for i in y_pred]\n",
        "    \n",
        "    # Printing the test results\n",
        "    print(f'\\033[35mTest Accuracy: {round(test_acc,2)}\\033[0m')\n",
        "    print(f'\\033[34mTest Loss: {round(test_loss,2)}\\033[0m')\n",
        "    print(f'\\033[33mTest Precision: {round(precision_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "    print(f'\\033[32mTest Recall: {round(recall_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "    print(f'\\033[31mTest F1 Score: {round(f1_score(test_labels, y_pred, average=\"weighted\"),2)}\\033[0m')\n",
        "\n",
        "    # Plotting the confusion matrix\n",
        "    if do_display:\n",
        "        cm = confusion_matrix(test_labels, y_pred)\n",
        "        plt.figure(figsize=(10,7))\n",
        "        plt.title('Confusion Matrix', fontsize=17)\n",
        "        sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=class_names, yticklabels=class_names)\n",
        "        plt.xticks(fontsize=12, rotation=45)\n",
        "        plt.yticks(fontsize=12)\n",
        "        plt.ylabel('Actual', fontsize=14)\n",
        "        plt.xlabel('Predicted', fontsize=14)\n",
        "        plt.show()\n",
        "\n",
        "    # Saving the model\n",
        "    if do_save:\n",
        "        model.save(f'{save_name}.h5')\n",
        "\n",
        "    return test_acc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d_20 (Conv2D)          (None, 32, 32, 64)        1792      \n",
            "                                                                 \n",
            " batch_normalization_30 (Bat  (None, 32, 32, 64)       256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_21 (Conv2D)          (None, 32, 32, 64)        36928     \n",
            "                                                                 \n",
            " batch_normalization_31 (Bat  (None, 32, 32, 64)       256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_8 (MaxPooling  (None, 16, 16, 64)       0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " dropout_18 (Dropout)        (None, 16, 16, 64)        0         \n",
            "                                                                 \n",
            " conv2d_22 (Conv2D)          (None, 16, 16, 128)       73856     \n",
            "                                                                 \n",
            " batch_normalization_32 (Bat  (None, 16, 16, 128)      512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_23 (Conv2D)          (None, 16, 16, 128)       147584    \n",
            "                                                                 \n",
            " batch_normalization_33 (Bat  (None, 16, 16, 128)      512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_9 (MaxPooling  (None, 8, 8, 128)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " dropout_19 (Dropout)        (None, 8, 8, 128)         0         \n",
            "                                                                 \n",
            " conv2d_24 (Conv2D)          (None, 8, 8, 256)         295168    \n",
            "                                                                 \n",
            " batch_normalization_34 (Bat  (None, 8, 8, 256)        1024      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_25 (Conv2D)          (None, 8, 8, 256)         590080    \n",
            "                                                                 \n",
            " batch_normalization_35 (Bat  (None, 8, 8, 256)        1024      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_26 (Conv2D)          (None, 8, 8, 256)         590080    \n",
            "                                                                 \n",
            " batch_normalization_36 (Bat  (None, 8, 8, 256)        1024      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_10 (MaxPoolin  (None, 4, 4, 256)        0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_20 (Dropout)        (None, 4, 4, 256)         0         \n",
            "                                                                 \n",
            " conv2d_27 (Conv2D)          (None, 4, 4, 512)         1180160   \n",
            "                                                                 \n",
            " batch_normalization_37 (Bat  (None, 4, 4, 512)        2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_28 (Conv2D)          (None, 4, 4, 512)         2359808   \n",
            "                                                                 \n",
            " batch_normalization_38 (Bat  (None, 4, 4, 512)        2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_29 (Conv2D)          (None, 4, 4, 512)         2359808   \n",
            "                                                                 \n",
            " batch_normalization_39 (Bat  (None, 4, 4, 512)        2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_11 (MaxPoolin  (None, 2, 2, 512)        0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_21 (Dropout)        (None, 2, 2, 512)         0         \n",
            "                                                                 \n",
            " flatten_2 (Flatten)         (None, 2048)              0         \n",
            "                                                                 \n",
            " dense_12 (Dense)            (None, 512)               1049088   \n",
            "                                                                 \n",
            " batch_normalization_40 (Bat  (None, 512)              2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_22 (Dropout)        (None, 512)               0         \n",
            "                                                                 \n",
            " dense_13 (Dense)            (None, 512)               262656    \n",
            "                                                                 \n",
            " batch_normalization_41 (Bat  (None, 512)              2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_23 (Dropout)        (None, 512)               0         \n",
            "                                                                 \n",
            " dense_14 (Dense)            (None, 256)               131328    \n",
            "                                                                 \n",
            " batch_normalization_42 (Bat  (None, 256)              1024      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_24 (Dropout)        (None, 256)               0         \n",
            "                                                                 \n",
            " dense_15 (Dense)            (None, 128)               32896     \n",
            "                                                                 \n",
            " batch_normalization_43 (Bat  (None, 128)              512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_25 (Dropout)        (None, 128)               0         \n",
            "                                                                 \n",
            " dense_16 (Dense)            (None, 64)                8256      \n",
            "                                                                 \n",
            " batch_normalization_44 (Bat  (None, 64)               256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_26 (Dropout)        (None, 64)                0         \n",
            "                                                                 \n",
            " dense_17 (Dense)            (None, 10)                650       \n",
            "                                                                 \n",
            " activation_2 (Activation)   (None, 10)                0         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 9,136,778\n",
            "Trainable params: 9,128,458\n",
            "Non-trainable params: 8,320\n",
            "_________________________________________________________________\n",
            "None\n",
            "WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 58500 batches). You may need to use the repeat() function when building your dataset.\n",
            "\u001b[36mTraining Time: 1394.31s\u001b[0m\n",
            "**************************************************\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1000x700 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "313/313 - 2s - loss: 0.8806 - accuracy: 0.8669 - 2s/epoch - 5ms/step\n",
            "313/313 [==============================] - 2s 5ms/step\n",
            "\u001b[35mTest Accuracy: 0.87\u001b[0m\n",
            "\u001b[34mTest Loss: 0.88\u001b[0m\n",
            "\u001b[33mTest Precision: 0.87\u001b[0m\n",
            "\u001b[32mTest Recall: 0.87\u001b[0m\n",
            "\u001b[31mTest F1 Score: 0.87\u001b[0m\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1000x700 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "model = models.Sequential()\n",
        "\n",
        "# Block 1: Convolutional layers with MaxPooling\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='elu', padding='same', input_shape=(32, 32, 3)))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(64, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25))\n",
        "\n",
        "# Block 2: Convolutional layers with MaxPooling\n",
        "model.add(layers.Conv2D(128, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(128, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25))\n",
        "\n",
        "# Block 3: Convolutional layers with MaxPooling\n",
        "model.add(layers.Conv2D(256, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(256, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(256, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25))\n",
        "\n",
        "# Block 4: Convolutional layers with MaxPooling\n",
        "model.add(layers.Conv2D(512, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(512, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Conv2D(512, (3, 3), activation='elu', padding='same'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.MaxPooling2D((2, 2)))\n",
        "model.add(layers.Dropout(0.25))\n",
        "\n",
        "# Flatten and add Dense layers\n",
        "model.add(layers.Flatten())\n",
        "model.add(layers.Dense(512, activation='relu'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Dropout(0.5))\n",
        "\n",
        "model.add(layers.Dense(512, activation='relu'))\n",
        "model.add(layers.BatchNormalization())\n",
        "model.add(layers.Dropout(0.5))\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(256, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(128, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Adding Dense/Fully-Connected Layers.\n",
        "model.add(layers.Dense(64, activation='relu'))\n",
        "model.add(layers.BatchNormalization()) # Adding BatchNormalization for regularization\n",
        "model.add(layers.Dropout(0.5)) # Adding Dropout for regularization\n",
        "\n",
        "# Final Dense Layer (Output Layer having 10 neurons for 10 classes)\n",
        "model.add(layers.Dense(10))\n",
        "\n",
        "# Adding Softmax Activation to the output layer\n",
        "model.add(layers.Activation('softmax'))\n",
        "\n",
        "# Fitting the model\n",
        "fit_updated(\n",
        "    model,\n",
        "    verbose=0,\n",
        "    epochs=150,  # Increased epochs for more training\n",
        "    optimizer=Adam(clipnorm=3.0, learning_rate=0.0007),  # Lowered learning rate\n",
        "    batch_size=512,\n",
        "    callbacks=EarlyStopping(monitor='val_accuracy', patience=15, restore_best_weights=True),  # Use accuracy for stopping\n",
        "    colors=('blue', 'purple', 'orange', 'cyan'),\n",
        "    do_display=True,\n",
        "    do_save=True,\n",
        "    save_name='cifar_decaluminar_net_model',\n",
        ")\n",
        "del model\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### **CIFAR DecaLuminarNet:** A Further Enhanced CNN Architecture for CIFAR10\n",
        "\n",
        "The proposed architecture was further refined to achieve a more efficient model. The adapted architecture, named `CIFAR DecaLuminarNet`, achieved an impressive **87%** `Accuracy`, `Precision`, `Recall`, and `F1-Score` on the CIFAR10 test set, utilizing **9,136,778** parameters. This model was trained for **150** epochs with a batch size of **512**. The `DecaLuminarNet` conveys deep and illuminating insights into the model's architecture, with `Deca` representing the 10 classes in CIFAR10 and `LuminarNet` signifying the model's illuminating performance over the first proposed architecture.\n",
        "<p align=\"center\">\n",
        "\n",
        "| No.   | Layer Type           | Details                |\n",
        "|-------|----------------------|------------------------|\n",
        "| 1     | `Conv2D`             | (3, 3), 64 filters, `ELU`, `padding='same'` |\n",
        "| 2     | `BatchNormalization` | -                      |\n",
        "| 3     | `Conv2D`             | (3, 3), 64 filters, `ELU`, `padding='same'` |\n",
        "| 4     | `BatchNormalization` | -                      |\n",
        "| 5     | `MaxPooling2D`       | (2, 2)                 |\n",
        "| 6     | `Dropout`            | 25%                    |\n",
        "| 7     | `Conv2D`             | (3, 3), 128 filters, `ELU`, `padding='same'` |\n",
        "| 8     | `BatchNormalization` | -                      |\n",
        "| 9     | `Conv2D`             | (3, 3), 128 filters, `ELU`, `padding='same'` |\n",
        "| 10    | `BatchNormalization` | -                      |\n",
        "| 11    | `MaxPooling2D`       | (2, 2)                 |\n",
        "| 12    | `Dropout`            | 25%                    |\n",
        "| 13    | `Conv2D`             | (3, 3), 256 filters, `ELU`, `padding='same'` |\n",
        "| 14    | `BatchNormalization` | -                      |\n",
        "| 15    | `Conv2D`             | (3, 3), 256 filters, `ELU`, `padding='same'` |\n",
        "| 16    | `BatchNormalization` | -                      |\n",
        "| 17    | `Conv2D`             | (3, 3), 256 filters, `ELU`, `padding='same'` |\n",
        "| 18    | `BatchNormalization` | -                      |\n",
        "| 19    | `MaxPooling2D`       | (2, 2)                 |\n",
        "| 20    | `Dropout`            | 25%                    |\n",
        "| 21    | `Flatten`            | -                      |\n",
        "| 22    | `Dense`              | 512 neurons, `ReLU`    |\n",
        "| 23    | `BatchNormalization` | -                      |\n",
        "| 24    | `Dropout`            | 50%                    |\n",
        "| 25    | `Dense`              | 512 neurons, `ReLU`    |\n",
        "| 26    | `BatchNormalization` | -                      |\n",
        "| 27    | `Dropout`            | 50%                    |\n",
        "| 28    | `Dense`              | 256 neurons, `ReLU`    |\n",
        "| 29    | `BatchNormalization` | -                      |\n",
        "| 30    | `Dropout`            | 50%                    |\n",
        "| 31    | `Dense`              | 128 neurons, `ReLU`    |\n",
        "| 32    | `BatchNormalization` | -                      |\n",
        "| 33    | `Dropout`            | 50%                    |\n",
        "| 34    | `Dense`              | 64 neurons, `ReLU`     |\n",
        "| 35    | `BatchNormalization` | -                      |\n",
        "| 36    | `Dropout`            | 50%                    |\n",
        "| 37    | `Dense`              | 10 neurons, `Softmax`  |\n",
        "\n",
        "</p>\n",
        "\n",
        "The refined architecture focused on expanding convolutional layers, incorporating renowned optimal activation functions like softmax and ELU, and employing optimization techniques such as the Adam optimizer with gradient clipping. Additional strategies included integrating dropout and batch normalization layers, utilizing a larger batch size and epochs, and incorporating an early stopping and reduce learning rate on plateau callbacks. \n",
        "\n",
        "Observations from the enhanced model revealed notable outcomes: training and validation curves displayed gradual convergence, indicating minimized overfitting. However, challenges in accurately classifying specific classes, notably `cat` and `dog` persisted. Despite this, a distinct diagonal line in the matrix highlighted the model's generally accurate classification across most classes."
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.16"
    },
    "toc": {
      "base_numbering": 1,
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": false
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}