ML-Explainability/CV/CNN_attribution_maps.ipynb

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        "# Introduction to saliency mapping with CNNs\n",
        "\n",
        "<a href=\"https://colab.research.google.com/drive/1yTeHor5uYuC7O8ZxsfUIIH_1VefEMeOB\" target=\"_blank\">\n",
        "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\">\n",
        "</a>\n",
        "\n",
        "Return to the [castle](https://github.com/Nkluge-correa/TeenyTinyCastle).\n",
        "\n",
        "Convolutional Neural Networks are the cornerstone for numerous contemporary AI applications, particularly those centered around visual data processing. CNNs excel in extracting hierarchical patterns and features from visual data, making them essential in tasks that require vision, such as autonomous vehicles, medical imaging diagnostics, facial recognition systems, and much more. Hence, understanding the workings of models like CNNs becomes paramount, especially in high-risk domains, due to the critical consequences of malfunction or misuse.\n",
        "\n",
        "To help us achieve this, we have Explainable AI (**XAI**) on our side. XAI (specifically in CV applications) has formed two major exploration threads when interpreting CNNs: **feature visualization** and **saliency mapping**. This notebook focuses on **saliency mapping** techniques.\n",
        "\n",
        "![image](https://raw.githubusercontent.com/jacobgil/keras-cam/master/examples/dog.jpg)\n",
        "\n",
        "[Source](https://github.com/jacobgil/keras-cam).\n",
        "\n",
        "In this notebook, we will interpret a CNN trained on the [`CIFAR-10`](https://www.cs.toronto.edu/~kriz/cifar.html) dataset, a collection of labeled images from the [80 million tiny images dataset](https://groups.csail.mit.edu/vision/TinyImages/) (currently taken down). CIFAR-10 is one of the most widely used datasets for machine learning research, containing 60,000 32x32 color images in 10 different classes. These classes are airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks (6,000 images of each class).\n",
        "\n",
        "Training the CNN we will be exploring is outside the scope of this notebook. So, we are just going to upload a pre-trained model. You can find a tutorial on how to train a CNN in this [notebook](https://github.com/Nkluge-correa/TeenyTinyCastle/blob/master/ML-Explainability/CV/CNN_model_maker.ipynb). Our pre-trained model is available on the Hub. 🤗\n",
        "\n",
        "> **Note: For a comprehensive explanation of the limitations and difficulties related to saliency mapping techniques, we recommend \"[Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study](https://arxiv.org/abs/2002.00772)\". For a complete guide on ML Explainability, we recommend \"[Interpretable Machine Learning: A Guide for Making Black Box Models Explainable](https://christophm.github.io/interpretable-ml-book/)\".**\n",
        "\n"
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            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
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          "text": [
            "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
          ]
        },
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          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 32, 32, 32)        896       \n",
            "                                                                 \n",
            " batch_normalization (Batch  (None, 32, 32, 32)        128       \n",
            " Normalization)                                                  \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 32, 32, 32)        9248      \n",
            "                                                                 \n",
            " batch_normalization_1 (Bat  (None, 32, 32, 32)        128       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2  (None, 16, 16, 32)        0         \n",
            " D)                                                              \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 16, 16, 32)        0         \n",
            "                                                                 \n",
            " conv2d_2 (Conv2D)           (None, 16, 16, 64)        18496     \n",
            "                                                                 \n",
            " batch_normalization_2 (Bat  (None, 16, 16, 64)        256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_3 (Conv2D)           (None, 16, 16, 64)        36928     \n",
            "                                                                 \n",
            " batch_normalization_3 (Bat  (None, 16, 16, 64)        256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPoolin  (None, 8, 8, 64)          0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 8, 8, 64)          0         \n",
            "                                                                 \n",
            " conv2d_4 (Conv2D)           (None, 8, 8, 128)         73856     \n",
            "                                                                 \n",
            " batch_normalization_4 (Bat  (None, 8, 8, 128)         512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " conv2d_5 (Conv2D)           (None, 8, 8, 128)         147584    \n",
            "                                                                 \n",
            " batch_normalization_5 (Bat  (None, 8, 8, 128)         512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " max_pooling2d_2 (MaxPoolin  (None, 4, 4, 128)         0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 4, 4, 128)         0         \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 2048)              0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 128)               262272    \n",
            "                                                                 \n",
            " batch_normalization_6 (Bat  (None, 128)               512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dropout_3 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 10)                1290      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 552874 (2.11 MB)\n",
            "Trainable params: 0 (0.00 Byte)\n",
            "Non-trainable params: 552874 (2.11 MB)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "!pip install huggingface_hub[\"tensorflow\"] -q\n",
        "\n",
        "# We are loading our Keras model from the Hub via the `huggingface_hub.from_pretrained_keras`\n",
        "from huggingface_hub import from_pretrained_keras\n",
        "import tensorflow as tf\n",
        "\n",
        "model = from_pretrained_keras(\"AiresPucrs/Cifar-CNN\")\n",
        "model.trainable = False\n",
        "model.summary()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WSvKspakoQZR"
      },
      "source": [
        "Now, let us quickly test our CNN against the test set of CIFAR-10."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 862
        },
        "id": "i9xFe4eCl6Vj",
        "outputId": "cdab4a93-8f3d-4666-d964-5c25a8019a65"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz\n",
            "170498071/170498071 [==============================] - 4s 0us/step\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x1000 with 25 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Load the CIFAR-10 dataset from the Keras API\n",
        "(_, _), (x_test, y_test) = tf.keras.datasets.cifar10.load_data()\n",
        "\n",
        "# These are the classes names\n",
        "class_names = ['Airplane', 'Automobile', 'Bird', 'Cat', 'Deer',\n",
        "               'Dog', 'Frog', 'Horse', 'Ship', 'Truck']\n",
        "\n",
        "# Preprocess the images in the test set\n",
        "x_test = x_test.astype('float32')\n",
        "x_test = x_test / 255.\n",
        "y_test = tf.keras.utils.to_categorical(y_test, 10)\n",
        "\n",
        "# Make predictions and get classes for the first 25 images\n",
        "# `np.expand_dims` is to add the batch dimension\n",
        "# `np.argmax` is to get the class number from the softmax distribution\n",
        "predictions = [np.argmax(model.predict(np.expand_dims(x_test[i], axis=0), verbose=0)) for i in range (25)]\n",
        "\n",
        "# Plot the predictions\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(x_test[i], cmap=plt.cm.binary)\n",
        "    plt.xlabel(class_names[predictions[i]])\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8Ve8QlbwE8or"
      },
      "source": [
        "Great! Everything seems to be working fine. Now, let us do some Ssaliency mapping. Saliency maps, also referred to as **Class Activation Maps** (CAM), provide a straightforward way to pinpoint the key areas in an image that a CNN focuses on when recognizing a particular object or class within the image. Essentially, a saliency map highlights which parts of the image are most influential in the network's decision-making process for that specific class.\n",
        "\n",
        "The underlying idea behind this technique can be simplified as follows:\n",
        "\n",
        "> **The stronger the activation of specific channels in response to the input image and the greater their relevance to the target class, the more prominently these areas contribute to the network's classification decision.**\n",
        "\n",
        "The technique we are using in this notebook is **Gradient-weighted Class Activation Mapping** (Grad-CAM), proposed in \"[Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://arxiv.org/abs/1610.02391)\". Grad-CAM uses the gradients of any target concept, flowing into the final convolutional layer to produce a coarse localization map highlighting important regions in the image for predicting the concept. If you wish to better understand the ideas that led to Grad-CAM, we recommend this [video made by the paper's authors](https://www.youtube.com/watch?v=COjUB9Izk6E). For the rest of the tutorial, we will only worry about implementing it.\n",
        "\n",
        "> **Note: You can find the original implementation of Grad-CAM in [this GitHub repository](https://github.com/ramprs/grad-cam/).**\n",
        "\n",
        "To start, we need to get the final layer of our CNN before the input is flattened and passed through the classification MLP. In Keras, you can get the name of every layer of your model by calling the `layers` method."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G6BdharaE8or",
        "outputId": "e4a86f70-1eff-4b58-eb6a-b76592f3c238"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "conv2d\n",
            "batch_normalization\n",
            "conv2d_1\n",
            "batch_normalization_1\n",
            "max_pooling2d\n",
            "dropout\n",
            "conv2d_2\n",
            "batch_normalization_2\n",
            "conv2d_3\n",
            "batch_normalization_3\n",
            "max_pooling2d_1\n",
            "dropout_1\n",
            "conv2d_4\n",
            "batch_normalization_4\n",
            "conv2d_5\n",
            "batch_normalization_5\n",
            "max_pooling2d_2\n",
            "dropout_2\n",
            "flatten\n",
            "dense\n",
            "batch_normalization_6\n",
            "dropout_3\n",
            "dense_1\n"
          ]
        }
      ],
      "source": [
        "for layer in model.layers:\n",
        "    print(layer.name)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xeyQbiJNE8os"
      },
      "source": [
        "We will use `batch_normalization_5` as the last convolutional layer from this CNN, given that all spatial features are flattened right after. Also, let us randomly choose an image we can use as the subject of our exploration."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "1gz91eBNAWkr",
        "outputId": "0840b81a-9929-4bb0-93e6-4134a4b0aa67"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Pick up a ramdom sample index\n",
        "sample = np.random.randint(0, 9999) # 2657 is the index of our Horse image!\n",
        "\n",
        "# create the image tensor by adding the batch dimension\n",
        "img_tensor = np.expand_dims(x_test[sample], axis=0)\n",
        "\n",
        "# Generate the prediciton\n",
        "predictions = [num for num in list(model.predict(img_tensor, verbose=0)[0])]\n",
        "\n",
        "# Plot the image and the prediciton\n",
        "plt.figure()\n",
        "plt.imshow(x_test[sample])\n",
        "plt.title(\n",
        "    f'''Prediction: {class_names[np.array(predictions).argmax()]}\n",
        "    ({max(predictions) * 100:.2f} % confidence)''')\n",
        "plt.xticks([])\n",
        "plt.yticks([])\n",
        "plt.grid(False)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4j2lCwmWsphH"
      },
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SgkoWqH9E8os"
      },
      "source": [
        "Below, we create two functions: one to generate the array of values that represent our saliency map (`create_saliency_map`), and another to generate this map as a plotly heatmap (`create_saliency_map`)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "qN43IGXpE8os",
        "outputId": "45ff7445-327a-4aba-e1a6-c5d3fcda1c28"
      },
      "outputs": [
        {
          "data": {
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      ],
      "source": [
        "import plotly.express as px\n",
        "\n",
        "def MakeGradcamMap(image, model, last_conv_layer_name=\"batch_normalization_5\", pred_index=None):\n",
        "    \"\"\"\n",
        "    Returns a Grad-CAM (Gradient-weighted Class Activation Map) heatmap for a\n",
        "    given input image, generated using a pre-trained model and a specific\n",
        "    convolutional layer.\n",
        "\n",
        "    Args:\n",
        "        - image: A numpy array representing the input image.\n",
        "        - model: A pre-trained Keras model to be used in the Grad-CAM algorithm.\n",
        "        - last_conv_layer_name: A string representing the name of the convolutional\n",
        "            layer used in the Grad-CAM algorithm.\n",
        "        - pred_index: An integer representing the predicted index of the model's\n",
        "            output, used in the Grad-CAM algorithm. Defaults to None.\n",
        "\n",
        "    Returns:\n",
        "        - A numpy array representing the Grad-CAM heatmap of the input image.\n",
        "    \"\"\"\n",
        "    # Define a new Keras model with the same input as 'model' but with two outputs:\n",
        "    # the output of the specified last convolutional layer ('last_conv_layer_name')\n",
        "    # and the final output of the model.\n",
        "    grad_model = tf.keras.models.Model(\n",
        "        [model.inputs], [model.get_layer(last_conv_layer_name).output, model.output]\n",
        "    )\n",
        "\n",
        "    # Create a batch of images with a single image by adding an extra dimension at the beginning.\n",
        "    img_array = np.expand_dims(image, axis=0)\n",
        "\n",
        "    # Use TensorFlow's GradientTape to record operations for automatic differentiation.\n",
        "    # Compute the output of 'grad_model' and select the prediction corresponding to 'pred_index' if provided,\n",
        "    # otherwise select the prediction with the highest confidence.\n",
        "    with tf.GradientTape() as tape:\n",
        "        last_conv_layer_output, preds = grad_model(img_array)\n",
        "        if pred_index is None:\n",
        "            pred_index = np.argmax(preds[0])\n",
        "        class_channel = preds[:, pred_index]\n",
        "\n",
        "    # Compute the gradients of the selected class channel with respect to the model's last convolutional layer output\n",
        "    # using automatic differentiation.\n",
        "    grads = tape.gradient(class_channel, last_conv_layer_output)\n",
        "\n",
        "    # Calculate the mean of gradients across the spatial dimensions (width, height)\n",
        "    # and the channel dimension of the gradients computed in the previous step.\n",
        "    pooled_grads = tf.reduce_mean(grads, axis=(0, 1, 2))\n",
        "\n",
        "    # Compute the heatmap by performing a dot product between the output of the last convolutional layer\n",
        "    # and the pooled gradients. Remove any singleton dimensions to make the heatmap compatible with visualization.\n",
        "    last_conv_layer_output = last_conv_layer_output[0]\n",
        "    heatmap = last_conv_layer_output @ pooled_grads[..., tf.newaxis]\n",
        "    heatmap = tf.squeeze(heatmap)\n",
        "\n",
        "    # Normalize the heatmap values by scaling them between 0 and 1.\n",
        "    heatmap = tf.maximum(heatmap, 0) / tf.math.reduce_max(heatmap)\n",
        "\n",
        "    # Return the computed heatmap as a NumPy array.\n",
        "    return heatmap.numpy()\n",
        "\n",
        "\n",
        "def CreateSaliencyMap(heatmap):\n",
        "    \"\"\"\n",
        "    Create a saliency map from a given heatmap.\n",
        "\n",
        "    Args:\n",
        "        heatmap (numpy.ndarray): The heatmap to create the saliency map from.\n",
        "\n",
        "    Returns:\n",
        "        None.\n",
        "    \"\"\"\n",
        "\n",
        "    # Ensure all values in the heatmap are non-negative.\n",
        "    saliency_map = np.maximum(heatmap, 0)\n",
        "\n",
        "    # Normalize the saliency map values by scaling them between 0 and 1.\n",
        "    saliency_map /= np.max(saliency_map)\n",
        "\n",
        "    # Create a Plotly figure to display the saliency map.\n",
        "    fig = px.imshow(saliency_map,\n",
        "                    title=f'Saliency Map',\n",
        "                    text_auto=True)\n",
        "\n",
        "    fig.update_layout(\n",
        "        {\n",
        "        'template': 'plotly_dark',\n",
        "        'plot_bgcolor': 'rgba(0, 0, 0, 0)',\n",
        "        'paper_bgcolor': 'rgba(0, 0, 0, 0)',\n",
        "        'title_x': 0.5,\n",
        "        'coloraxis_showscale': False,\n",
        "        }\n",
        "      )\n",
        "\n",
        "    # Show the Plotly figure.\n",
        "    return fig.show()\n",
        "\n",
        "# Set the activation function of the last layer in the model to None.\n",
        "model.layers[-1].activation = None\n",
        "\n",
        "CreateSaliencyMap(MakeGradcamMap(x_test[sample], model))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wd27OToyE8ot"
      },
      "source": [
        "With this saliency map, we can combine the original image with the map to generate an **\"attention map\"**, i.e. which areas of the image does the model assign more weight to generate its classification."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        },
        "id": "8R6xjT0xE8ot",
        "outputId": "6affcd64-cd75-4abb-eec4-61862a302d32"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "<ipython-input-16-4215d104c10a>:19: MatplotlibDeprecationWarning:\n",
            "\n",
            "The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.\n",
            "\n"
          ]
        },
        {
          "data": {
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lOSqVNtO9qQOTym0NtMcRErGyzrrVa0qqPAWaO37QuKYxhSrBp91+Jn0m+C3pWU7P93cXPSwpYluk+wkur9T2zTRaIKu2scdiVZlcyoQsk3fbQmmDQTmtUwW99/nWAP48LvCW8IaGbAfDKA7r6hjtNECiaEc5R/lI86aNcSfXR/Gq/77SzvHpMLhX9jZ2n2k6qcAeaPeydm4s040GB+N2feM+xs66/ETifN99pA1/gK+lO4K+fQA3iwFwrBz9JhLqCRBaGIgAVIZxBtcmIyqtecbEFA4IotXdNMRUaRX6BwCMc/0dnHQw+3su+6p7/ps0ldT2xbGa5TJMv8cJzTafB9of+mQpgHEZgXBfPaC/FWhu2vfq+dVhx5WP38dSTKFNCTNm8BjBL+v4tHS0mlUC/t6uo6Id1XkqU59PqefHX9Mm4L1hRlFO7Ebr9BqnrzyO4UhAHwLQgZ7QoLQDK488auAWMrZ62EEKoX0ixu/6wRe8Yycw/HtjMOokSg///awcVORYbOkTXob475VZm++CbthzfkbgJ5Dwo0AzRmeW6KacKZ81DoBwKWZqBQUIKfjvHClH91Rr6Pw7tu92K1o9LfGCHuCTdgOBLfL+ARgmcOjLjnRCm1X8jDHsyAC9uOs0xU5acZW0qwaVx7MZrKpRfzK3gMXYFbZjBy3sGaqf90yfPcGK5SBfPLpYHmj+cPsx/dGGD0NEh1Fc+wNNXkpZVQnI2yPTlnJOIaC8fuBxJ72ViUx235/Lq7x32lH22/QgLavfulsVO/cDNKTOELql4qG6R7kqBw03WmWjwMN76pNiIom3zAo9H71Gx8f7ziNY+1xBcD5w6+QvaXZTvvwBn6yrcLYJi/9Q4Lg9uaMBYoLRZ210Ht93H2m+dt7AIY+kMZQBb3nWZK2CDsBFCHdjNc17i5Qdw001/xDmplhygEA/E3l0DILWwvk33z/Bod7TcuO4eGinz5C7hLmSKHQ50K3aWNva+WyO7BIyRkENyUfAYjC1gEG9sYPJ0T/nwjRhvFrkt457D6DAPDXwNNLK9VNMYZjiJ3M+DOjjNXeNc2rYTzPK63510wFY1YQNBFzz0oHmo3gcN2hhNwBJHfcsp8l+R5lGyz4Z8EkgeJdV61fYlZZC434/kzQGjk1cmipUWxGc7Ye3vx/Kbg5biNlVpDMg6Gfa/nkT7p8AQqf/ZFzejmcQ6NiaIuBJe8iLltVZKJEr4y/7Sbsnlga8A7LvHz+IKTy/SkUDEExUwPCUyaEJu9zqVcZCEzCAd6wJSOuF6cqlyjx0sArNj2B1AUYAxC3fr0Dh1jbvoP08rCXB7XgCUJP2lvpUNU8Q7vzd1ozxkAZJp3kMYU/Q5LBRSZJpKljc6ebcTKbTvN+5lJ7KoTQ9Dsl6o9lxT7N9LzwVDOpaGL7WTg65wL7IPJLXasZX3bI5cB5rc2gdWjZzcF1QXLOMep33No5nMcM2WvUh33SCB4vhs4mJVRTCdPUWULyhTSkWQr+Ws1Rmvb8PC7JIk3IoAjx0f1sknwjG78jQt2P5C2A4A3kmwPBUlHey27sLANkaSnLa+V43x/b/IffRzUOhL616e6W9r3AFqOG+y18BomjZGnUW+rAOPIQktbhebJaFc5v58l07h5IK+/MdT2WCNsAJDPf7s52SadRf/ZCu2o8yxVHWwchPHkvldHqQKEQkeftqH97/5nhX3BvxHLT4giUrmUoMHUx3KWr14DcqcHzIo54tTJtuorCu+tdn0HOv13OdT/j77Cjhbny2Ga49gBMEcIBEN5ePjG/ejNuLv8HILeO6fkd+9kTT92dGpuW8yVefetNgg8/73N7++CQx8z6B3M6EXx+RxT39s+C397lLW59AEM/cn/1+KZ+P78cU+EIRDDffqFy6d4e3EHvQhVLKhrC3FPJ34V/pXHbapUbPIDF4bnfJGIoyxVL3PqJ0dJnAocDCQVfnYYXoe/m+4+rUJv3s2uNwG94SaoVV3spWRVmIjl48G8I0tFof6SewqKgySWeZ5yn+zvTH78eFZk/pP8vvs/fp8YW4PqXweL2P1DDvdjLy94m4qBCNvqJujLL0Go3Zql8PWfaqjzMKwHRLGU9+cmvF6c6TKNrjCmQ80Hj9tMW2HbQU9vZAY7pyNel93tMZy45oYCprNUVY7tt8z60ezE5m6Z288wwaX4lWAYpbOo1yCLMU6UBMHcelJD68kkd3K64clyELewIIQGOKsu2T/D45fmApTJOEC8lu4J73ohI68NQH2s/07qp3EBjAsP2g+YgBsIwttGmoTUHUvnFJR5rPMnQ6yb/qwksBuhyoQ1h3o8Q9Jb7VGu69eXbwiN1kW9eTt0BzxyT6HVZ17hE81nZ3m90EvC5KU4A7Bf4bzX/8PZRptMVJO++d5GzXQyV7XEQqwJAiaNAk5bhSGdNi3+/NAPWrdxt8a9Z4SVjgHGjR5bPs/Y4gencpRkLD4wygLp6J0PVcf6E03NdkpLC3811Cq7Lsbj9DCv91CPDtuZOmVsKApWsnjjIdMvfsqOHG03S3H18Aw8OU0rviJDSde38rpJQP1sD6cEwrPcZkLU3JMjkslEJLef0NNns6vg0KXSBlbb/xHGXM5LvmPOU3wPM7DWIBeOy2Cmf8wBsEylLI+6fvvwCBJVIBdt/Hh6tua3jV+zHTVJ1cnu9aK4DcW4qkYHAKn0+6//7sw311JWlMH0AuVktgKnBoiGxDRQSUxgxugd+n8qqA/0zonwYuz9+JHzzRdDzl/Uc8abqd2cljwQIuVfaRxg9rYRpWOfDMH8vQs++s3qW0s0K9hsGrGNOVJa2cF+UW5D+iYNVxXNsD7XYmT3Ow+sN9Cv5sghu9pjPPtEVjG5bpLw3CeES9j2VgjOuhTNqqp0V9sO8NmCvJnd9Gosp/3lFgUEBoUaHgoHnYuGVnPWCdtOSqlUXQ61os1/mpvPqz42ezj2601okpbIqX3LvzjtkTJeAB+N4l6GtH3KS559fdTtoACgEFWK9QrtFrsDPgCQOFUjdij+itzMkaluDXljgl0WeHFTB0i3727Ndd2jOQOqcupub/ILxLu9ABwrZYUs4jSJ20mS9wf9cTIOj10+Z3t2XJN9rQfg5QiJ8KEqZscP8DngW60MpddHaVxfDX92seFWQ0uWZr1+hvYdVDXwmywK7ee0y5zrSVUoBhJjoekKreQEGuH7emuLmUrF1A8gEc0gYo2BMtyj5CRzmOa0azy3uV9gQKCmhg/vP4nHYHkbeAkO9ySVcz9iq7fvY+iW6OvpMV9YrydScA7AIFK5Z171lM7/SCr44fgEIPb6LWFDM+5Z0UpO57nO8uo1PIu7iM4jc35FNA2MmA7WKldmFdsHgK917u9x+kOx1IDeUEBBEMeu8TwV9OrS+w5ISf94e/fZOCEKehnpMsn2hUM8y0FCrUHrhOqnxiSN9qgVXOSC20P/TTXXX6dLLULUSitAcMcwptskyl875/vKMFv3X5RpmzhhrLOVZv2a1uM0JUTXJvkU+OOSKL9tSNLJkK2PMxDnT+YPxtPaRb857ptTbLSeNMo3NMCLi25s1771vlNgZAfjnufAYKD+mfcp93xONAZYA05vfmcfb8k6o1GZ/dEIJ/GWrGpMmU1p9tanE/fgwKz/f6QuY/VDNxeio/vqOWwt67BPxOeruHPC0FL4DYChAKCqUxZNOqpWB0IS2hOyrwDAww6ZlL7w4VaDoQPz+K575KKrz5ZTH0PI47WD2V8rnkT9NF2ZbedJMcKkg7pGY8w8FZ7WqIcJlKXBxqlOaPTmfo557cR0Zhjdy3Hd3ta6aLV3r9rt0DFmaR+FfPZzmWyz3pNANgslaHaxYUGKxdStUTdh/OT8sz7sqLAPttseB87iZsKMCflCPeY75MJ/dL2/f5+y3tsB648A3AHaBYzKJ1ez6WBX2724LZHO2hfETSEN6fgMLDoCQguKTzUsi67LM/W6ADj+zZ6VjlfPdCxhQ2A83xzM42JZ4/NM+Xx49AQUVMs16HvHoM+yhINQ21fLCCXoDQMQPvoLJrmjvtMdB8fMA0ArGr9rbpUd5uifqgTuXxoDYNTvV+hw7qGyMJK5acFEb9DBzO7D9J93g9ytRnr1Kd9zI9Z0I8mAGmdR0VU0B4WAWr7xy0o5y3CGj25/A55DvKTSSgYZYAkPWoM2IBlJ1/ItRZP7PhLnq2MlzKRHq/S2njE7OjXj544Uw/yHe2Krcng861YvqtQMPE18oIU/hLOlreNa4/AYVvAwOkyyjFVm+JYRzCK9/PNj1prMgJIrxdNPLzvU3u7X/SHtrxMdDcb+mm6a0uPPNv2vHSfK9KpQkM7SJu+Wn1HSvP2YqGXM7hXc5zhH/n+EGg2c62h6yNBVmzjxObbNJZcNlCwYtGAY37NNEHWj1b2ffgmMCEe+u43rAj0ROtryfPkNbpp+Yh9x40wnEcPP9ZGi3HvTjW50pn4yF7yMjmz76mzEv6aNshI2XgZl8MQYQnu/MJpPgIJUakK7eW2ay8OWwlTYDBXrgLbFm7cOoJwzpgUQaoWKc/acIuRktFrAInSD102rNLA0e65oqekXK02833KfmdL1VAuAGD5X3R5IB7TOEdIJxxBsm/LAWz2hF1eCu3VN4DOEINFpoyoAKN50WB4FO7ftL+b7U1YWQfVFD4k7sNKEuB13EeT9WzwDtLQfIoYLBqHqP7yON5WgpM/yfHj0ABOEG5PdIPzY7Ra9qJZYoKs+kaBZJ124ljTcKgFaDo+6QI2vHfrOd7mgrTOWKfAUEEss10j2X5tIAnJ6LzPh99YnC7l7NvnWU/spDr8+nTixPE7osx3/9efPl9dppL5j7KBuCuVpmUVYR2WQlPo46yw9DuIzuA4XgHTjdTWihaMSPNpMxlhShN0p9tcmc7+SHAYAfMvhEGp6Cpq7eg8CDscfw+AWELTXdD4X3GFDSdTVq18/k+Pc4yJa3r81NQuPfJ8cT9/XqvXicupOItO4p0H3dko8l2853lKhSZOZregUU5mk8XkDxV6c3xfVDQ+fhV3ONqTFTWEaVaTP3Tab5Fk2fZwnABBH1vXuvePqU9qOQ4y0onx3kPde98bmjfOIXrlK7qw/w5MLxHt2eLV6Q3Zjnilt3SsXzzbP0omfZ0cVDQQVrsEGgn9zTXdKJjCEhl8rqCtPwNnO4jW5l+ZXrSKMwP1tRAsoulMATE+LN+95OlgElTZSCas/vi3k4P7app6nYhQSnE3VR+y+c8BudlVsZrfUXmV19PI+3cqsIx53JQ2J9bapAGRJ9ourP6VWfh+yealtfOWzLuzjb40nV0ewRnm43XD+vfsnvaOhjxi6fy1dga7Hl7J4Gh3WzW4Mf7ftDeVefN8QNL4ZOPr7PHvRf/ZJEwP2j7xE2rrm3QAKogZtzBknkkMDzaR2zSuxPZHmjzb1UO0aHSPQ8jlEFVBQZe3y0DG0JhunJmzlR5zs68dawUyR5otycGc9qkKckU0FYDQT3a/tJOH8mLS4SmZbvV5w23Btk7Ufnx1X3UZSiW0XjC6numLCHvLQ+m5KUT2EYlKj85M+1ZWUO4jw7a4IMnIaFySes32smPRDp/rK9M/n13PMYSANCt+x1LQS2E/vPW/PdzOqN6axJTYDqKiQoqCwKyICoApWx8dDTTIzCMhsJo/0+A9emOH0DAa2Dyxuk+ilfF9ZLXS8ST1ar6LI8g81o9fb50o2wPy/TalN89fuw+6uN8nQlZxZlJOms0k3w41/58E8fETG/1XI3c2/2SbpnU7gJa/0x6S7X6yvHIT3wFNvJFX5vS7IEm1yoIhuo2j0c+PYum+T26JE6pcy/HBIWov0nZC9CEVt/K4H2br38qUo+Ph3LeHgTahdRt9NAl/SduHhu0OUjnesfT1M/yGTBnGDWtNHVtR3ugYf5+6v97+jPdaTG+Xwpp8u9byeAPz2oDiID5FBx4nPEDPXN31VnAfsfCYWEQ4B9oODM5KGczfQYKms2z2f38DqmaaXpTcOgB2nxyz+U+IWHcvYnbiMWgLS7ya4ItVznzkfc1uR//BihIj9afQbY8zPtT64frNtBybY76bKTtxBZaD0GLbLiej3l2MXy8rz/iYrVLqFoKiz0Z6QZYRKOWJRAFkHqfwjStChPmG0J09T0RvMfYlh9+b/F3zS/P3pncHp+bpuzBjKXh2wAHtQZM0jCrZfWzAUTbg3Qc75sjd1LO+lhXa5YZAgpaiEyjwvzQ3nvrKxtanAKFY+Z5Pz9ZCvZQTgoGu9dt9AmT32mdmSoPB+1su9shffIGKCKVPQaVH0GBM4MKFKw/pbnRs4cO66GsPkdbFlWOvhf95o3gftT1sDC0mT6d1jHa9+zD98kHLftJwcEQPFH9HeQs/hy8p5VtI4XN9zpqyqlpewI5d8Ja1Fb9/2OWwpP7KN96UxfIJQoMMx23+wUOwc+KJeQt61QgeJgyhtcby90jAj4EGL9D3LQJEMAEhUmbPvQ7LZjigSb37jSmk2x5MtZovPJ+HHnMYj4Ih0dhcwpplNuDoGCgr540ZBsErSb8mJblKWBtx2tnpe5t8SAoH+o9QOHT4LP1oCQLmXDkIbx5vzIZeUAA5p7vAAWp4D2d1OWpT04B1Zk90x4u78chcj4Bhi/BgH/jW8oHbZ+0PHMLAwoySxrrXRaLyzXLIO+Cpj/qQ1B4JxWPNp+0h+TvxuGZjzKn8F9Xa/bx2dX2VAC2FVB7TQWm9mwj0uuRn6BBHv+GpcBS2v13kQgG+6FTUoxzcLqkN3akAAcFkTeQKArPcrKlVwi0Eu4NBM8gMCONuhCrhVj3Ymu9LTSGJjzAoOMMxgRsqpvAu89XfwQG5eODBwfxSbBUOWYBDEgjKstn7TpqEJC6ZtVFPsqfth2rPGld1Dkob3LuaKvOI0fGWLPIUTYHJOzU6K2U2sipXzwWHmWbsBA+KxRBRi0wCyp6lGX+zVI26lJsdd4r2myLcT6vP6M93fSHpKeAfQIHWTxaWvx4TjR7HM8y5iPBaHug3YLK5zjg9SmKBu1TW0HeZQ+05/R2/J4r38k70t+kiWL0BP6GexXJp9q2dB9V4qS5z3RDtnzz+AEovI7fp2WgKgMezn0dO6wa9OtR4T7CoMWq0LYsCAYLEdCOjRSVo62YMFw2MaIIBq21M+iMBgIFCvUdHFr+oJE7TIGHyVr427hGp6MgkBZqefPGUngaEIcQbeFpt3QqsE7mZNUGeK3UTNic2Rak8fHxl/cUKNiGT1bNzag56vOexkVsPuvANBTkqwdkCX0IDSjugiWXHS/zapgJCv5UoRM8Mpd3VkJdGwb/DP649SHmjc/444vjlmwMbfvcQvAcg1emSatg0C6U1WApwHx7u5SShsuncC9gwXRj8azfcXoQhLWlyhNgHFWMhMqUDwm1q4/7p/CPIdZTkOv5k19skkQsPBQ003kK/wVZIa5TVe/P/OT4Ny0FfbNwpR+/q9dlkBhupg1pyhNjpokbzHYzFu+7vqJH103gn24knkvwr5kH0JKvyqIjFwU0nwWa6YJRWgGEMoW05y0IKYutzoGvvPapoDgY9PaO1Umq7ClYl+yRR41fcFesiP69VHuHplPN+qn+Z326njearFrudNN6IAv2SuWeS95eiUlTgQ5YgUKxR9JmG3Yhmo2epMe9Hl0flvcuNJ6AwUz313mT78OtT4+bULFPLYWba+n0Fi9Jb5Go1nE8BZDtM9rD+dFK8NHW7+otxkQmfOif8/cUAbN82XdlELUmdeeJUxn75PUlUgkMZgEIYx8qu/UFST85/o2YwtOrnlSKhxUsVXA7ntFnY2h50iyBgaZqNKB8iQqQEQUoAFSg1xY0AA2IdQB2oPYuBFiAfwsUDtoTKHQ9fDIqgPp6zsPgN6ZnGzwJhUdhc6QVxuyyRYI1AOCJFv2VTd0gcuSpAu4ch12HbgfySLfbQRvdxXZTOsF0bl9x57YGBrUUdDO2SicdNzdr68o97pB5pnsSckc/Da10smYJGHvK6x3tO8cPQYF75dW7HDDuKOMIS8FwWAX4fhBb6671UVD5A41Yivt5+x2/bT2k0X4r/pWOOu7PASBJzrHAJN6GU+1txMKHFlPsXn1y1vGbx3/T7CMR/C4l00CzrmhmMQf8nee4toMWQWPv1wywiJYfbiKTQLO6kaBWA+T6TrtP4/wi0CyC08xqu4Mz0Dww7CZbfN47aDiLRLXgSdBos1u/n12j71DB3fGE5z/OOGrrwNI68Btg8B0DGDDvPdOSD46tLiatBX/X249BGDRd+fssh0w415IehXZpqNoeWQqseVvRMGifavV1ffDHTfAcfXimefeOnxxa0HcCu2a/BJ+UKzcXVdkFcQUDgrSpG7r8TtnBQPM6aOt4Nw/VlIcY4bv8c6los2hVVj3L9Q2keVb+S74LLd1mny2hSX5k1fO1o6gHQFuyPriFNpt6S1No87/J9zx+sKL52VLob3VlUDjtFYp0FomFLIYYLqbM8anUXERTb9XqccM7zYoL0BYoqI0fqc/Ac2hXPSX1Lvx79A1BznsnzR7SycBda/U9ZRDMgd8ywScBiB05D5oyJS2pG2e9ERxDy9Zq5ZllKMGvMQWZ9TsAIssZQCjTVIXp4x1z0zwdT9UmRcv+H/WxWx49QiQTMlyWowJ/yJgWODFaB0zWW2jFcedotSbK54qqMpM207/tH20E6ZNnYJDGOtOc5X0nad4dQ9C2ICoakTOnooaSJi/Z3it5V9NYDudkBhUM1Y9Jc6ENdD3KaQ9n8PlTPjxUU3jw9o43/WQPtP5LnrAj0GxCQ6d7qxweBZV9O1vuScjWzHp7kXxGm+67LPDHgWbVuXRotWDv9QrRJxFANuc3ZlcUlt9idaB2Ua3Nj6hJnBwpQrAqPnvIVscRFi2E1XGGmol0CPQ5rTXy+xEwcCAYxCJ4ch/pfYis8Aeme6B9el8GVv4UQ+qsXtNkVfAACByuopV68gCF6Jf1snp+jRiF5HcOgBQKWvQ6V3sYdD+lSTPA5DuPZyVtNfckqTeTo3XgMb6O/WR4TA60PltbF0enNM3wTHsjcKZ18/7vZi28y/ez66fjVM7eWQoaU7jQwldno5OWf540g2jnmr/SlpzPspx1Ob3UdfNzS2GU45ttWJMYz/ePvrsDwgC8ZvAvrQVtMzh6nQI3EHYc7qV+8NYk3zj++HsK5vc+tKoOYSB+F8WB86P3JfvVlcRI+sNhlcpKgJ5WSfySmEIKCDvjDADKmsBhKRzWw48sBR20aEtBabUFwhHARQo6kSNZjtay7mfVPo6GYpbA3BK6VPvWpM/ZRDC1AEh3LK5jEBpnAZG2TALNK7jBbnUVMON7H2haB7bPoMlAizt9n4kqPkXajcFSy6rRNfn9rog+jN4DEM50g/YkeEz/7IF2T/dVvz8U7evjlEi11QTuaiddFT0wAaSVoD5/Q20sUNr5U73e1eFGs9kpkGtDWxmz4W9HJdc9tM52OHnwYWxVn936KWmPK99FBkjy89AqwpDfubYJvl8c3+l2Hn9oKTzpUF7/BXUjtjFd4FqD/tI0ZCfUXMbmlt9RsLpZX+pSu0k0yqkxcLilJbAW6Dpai64kxhbUpZS/FRROMJH8GyyyEIa3FkIktyhLvasZw4DSMCQ7nDONmvbMuKa0TwbUu+8EuLXmH+Vrd00Hjl0sBTYbaYaV7q316nRlKeiZwowqg2WfWl/fmhuZvtQia9oQsLRftYG8poK2TGs714UXdZud4urkvVBEW8F5lkStPJlc62nQzn66rco+7h3pHjXWd/2v5/P6s+O0Dk5g0OpTVdV1BgvAh6R/sjpkOVOlGzOTvqiXlvVWnm8c797x9Jt1eqLZ+Zc3K6YoNJURxyw9LdLgMu/05TxhwtsnUvH9+h/HH84+uoOCY2f5osTcUM5TuDMQEpUz9Ed1MpsMWIULKfW60ti87pXLIFeLqJWgsQECgK0ABdLKMhCA4LPWPXfLr44ClR7cb11DzHetwRA3t1EXQ17fwBA0H7THAf5u4PB5ttfBvPyUajRPbzhnOTip+Zt5uuAgFgODypa0yFPdTcNiyGejaAI+5QI76s2qjHod3vqakRS0Ftps2FZVgrd6llHwlIAD3UdeqoxYtz3a3Bsg9G7LIgUQljNpn/XdOwvh+Dv7cPT9+fzTu87jiXYCgl6rtCqB5PNZ/r2E9jRdVd1EnKmUvFcuqpO3T+1/KIiYnXHriId6n/mf7fcV7REUgAnwNs/ofnwCBK1K0aXtZI/ImfDfBIY/DDQzsESNa8PEIgiFwQoMgLnSjnEDWgU1SHtz+KrQ/FpDt0CKLREY6iYyLFsVV1gEgwIHuo96plL005yK06CAfv87ALhZCyghwPdCaHzn15aCP9D0fNCfBn5q8bprOIvvCQIBCtm25Q5CfXKSwAALqyHak896B5VfqPwaSCBWBi2BPlfddaGiDpruYiG2Z78bjr9SaUguce6yKzQ2KUFgmAdACf1k9G5UJ7C6TGyxKuM5PrsbeuaRSXkf++tPhJJOY35KJ3n7ScNDOjahVui8Bu4LyBzBb7ymtl+aP9Vdv01aLF5+aotTuOmcS03rfTloT/XVd57v+6w/tF3FaiigPi0JQ/thz00VgS8sBYndnu2v7UuQUMZL0PgpLvz5iubcgmIMB9egchYaG9tXDlT55GaqS7usA4w/gHGF+2fleYwZPCnELVXVtRIYzGDrlS6OVfdtpctoqfAXa0HyZBe1y8iqs2uAL+bBRxloIgjZoCkTDYuBzSkDpIXkMWgoCG+AYXPwnems2w7LK00J5cVAs5cQD/dR/Kbmv8SyIFCQVjEF6/zaLeUVrIbSJJYyLAi2J3zerKpFIwbLSWNm8p0STgPCOwEirNa0aHPyQ+9J7zVhhhavw7GoDBEgsizF++iZTXrUAH0nsB+Fidw7hVLR/E7T/Oo9bxSIzw4WWAWRAgI1eQaakcJ+H9KZ5XR5BoiGJWCczggFFMgzmic74Ak4vnO864uzDc++eKJpn50gwtlWh4vQJL8e+1qM9prULXUVJbD+nwk0+yxt/aIAzwqopkVtzXJAdXwAgGhoLm6jfl9kfr633n20oK4zCOGuVsHTX89CugWay630EGimUAckWGuD1tgRtAo014yovqffDi5NQaakjrn45KKRDgdNylllO9INULi/f/j+y/XTU02jzB1PoFtJA810RUGuy3VkHBMCRjVevAcL00i1aCVUFUULNCCdmMWEKGtVFr05LLcHkKFiBt+4CfW5MXWCi7BkKUCq5sk95dFbsnfCKP+qdN8JgjLdV0JOweFLUJB6v7t9vouAUPXwUadH2lPZz/zP93KzIZV4Wtwvij7S6/VTnc6yPtHOOg7anAhSimQz+W34RtHJ5zbDqqtZot7zRcD5y66W49+bklob1qFcSb05FmRs0gRYdW/zs3FMmnGGerRUKmbyVL1oWQon0BqAdRxBYgrr9UoBbekPF5cSUEDRWn/3sGr4BQBiMSjNBiNYbyBXPph+VoOFphqICsxoYK2ySERir6oSJr+9NJFKN/LxOpdrJ60C0EUETyuLsYe0Dijci4Z0H2FYChpfAGciGd+Rur1aDNIGjXFH/caVMUX/Kwul3KMg2zcYMt6ptLjzu7ae4TCDfpPYyJeU0t1c2LQGjPT+ZvmY3GR9urHxO6HyJCxV8PJMOle8P1kUZ34n7e3hXeDTQlBBfJt+6l3Zs54sJ/NbAF4uax7k7JjB53PoP+V/FP/TOp7tqe+pdpU0T320jvPD303xO/qnFLCjHsovylO1UE0thDNWAzn/8PjzbS7oPsqSxnX2bPuA8nL3ImdqVhVslumnpI0a9X1xIICtWq6ZvF+af56XLaxyH70q/ZL4wshHtX61FqoTRcALGCjtnH20Rt6arqrxwCyHtoWTxmZoITqn1Vk/q+/AkU5dR3QRSfpT818L6XLzqBe8rIdKdz7zwswz38cv6kU7iSXBqlXcAcdxjnZn75dCEXd3CXl6KdyDtsCB5VjpQjJ+QH5MPwLoSoqRaTUQqwQeo7PcRZ8Io8xC+um4OQTfU38//T1p43h49o02/tXxBAx6Zh7nNN91PpPv15lFJrTHMss7nmg4aOf9Ub6HOj/1xVdt+cY9dOsjsbhr/OmzmOPiVqaHailflph4AoN/Axj+jdlHhjlnrAHBWYXUtMpVRPO7MWOcqZG9W6MQuVLgzl4pa0F6IIDhdCMpaABzRlLURcGBs1ymqwjPtCoDUJZC5Y3O0/R+FXcOcpgMYuHuMWiEdq54LkvBOk9DBl0lXbmCrOdLry5TWAoGe6n7qAPMTFfxA7UUXpnfqwU+LY+ebYQDENo60PUaD96Zx6N2U3GR4+6h2T8Nlm1lmhoEFHa0v++op9duoR3grtlLNlfs1zbKMpqVpW9VOe7fBONJO4XPZwKr0vnzs48FkuMUNGdFbp/hPMrimLEBjR/UXGDJT4LPX9YbmO/DQTsB4UnwPrXDd9ua5X24b3rviDfYU37yft6/iUGtl/bFZ7Rvjhs9/sB99KQiRM0cnJHhsTUuHHAJNKcfNyyELVaCBJpBoNAW0st3vRk9URbCetUMpJWq6rJXuYtq6wmdkTRcO5Hn06K0siQeZxLM9O3ayntnOhHAN4HOwfy22l5nX+p2OZ91ELimlZD3ym20sw29XEgBmjH9tBamcdVyMvha4iJiGqW9uA6iXUarQOGgAQUYvI9u3jjUwaq8Arowkx89lZQdotzcsJO2GXjeQTMHcKUVux3bPGc+bzgMa3u5PBkba+tXJtxI0ep4GpjvBNF5vBE6dY+/Xw+07zz7rnw8nkBBd8XfmO6jsy4KFMhynm3EPF/HM2fw+at1DD85ntr9DCA/AcB57zPau99Pf2cdnurz1Bdf0f7g+NmKZnlJaNDSS2ITe64n4OA0iKAvy0AGsvcCtnqfouK8jDzrdSpRbf4uTb9nFZ0WQbuNcGj5ExSmZm+zHG9oYxqqab55jS4yK1mCnQJb3FPQe0LzI484y7MVU3AMcOO9fFcD1cOUVK5PWD4tCbNwO9VMI0g6l3QuoMDnxYVU3daxhQIF6+LW8YbxQ/jnROb8KHy4NimbPPafSeHuK9xGjA1UvAPtDjK2Me1dz3Lm/eLVbHbYpGV3S1EfgJ53TkGBA8glv6Kd10/Cxgy3ac1Pwug7h2rzFHqn7/+rcn1a1qNcn51VMBxDpY53GvMx7kq/eFP2W5sXz35WF/adjDtR0sjnt4Lb/fJTa/O/8fjjFc0xLjiDKK7DhyujIv1Ae3NK6i6z3n11/MDxYCnMo/qV/zigX1KLgxx69tqhxloEmBUkeq+kvJ/PMgiNw1UUNEyauJYURDj9lSsb6x7wPPsoZ/IAlu84tXupcr7e+Q1beX8xZN4zszEt9WRqe7FMq106Bxi0xdDTT21ZBZqXggNpsspZp6fSOmi3kbiVcsDMGANk5EJGSVSgrFQJIofGuSKOIK7L4D8D9o5v6aZC4h51WTt4c3N7aJA5s84O7AQTCnw7+PbJYDiK3Nd6HlV8YynqH90yT9cjbfCEAb3s6OCl26HgqxaCgoKmMcT01CW0pBsOZc8kP2BaCi+09fDkojotjTyPqnBI2JF+tKWMk7NNgU+tAtPrdxbDyMNbjqxD4XvghbPYxQotWkfQuRLv+zM/OX6weO0130BtLGcV9Qrk3VNQGXQGB+g6gIEgQB2uaY8V0laiJk+BUAlOqWm3tCX4B0BAaNwjCW8siXz/7TU27/HSFHD6/mngTKYUIf8oEDjS4mwG+QqYaic+p52S25gH6SlMOtBsZQEQHGqrC3EfrXz2tBB60VoGmnM9xGk1UCuva9FmFSyaBbJdBm8QFKzjBg5YuiiNZoIj+c/q+8DLInyAjXIHGSV8KjuOLL8DcLEsltcCuHdyh4dE2hLXmkca52Z/u/RTsX3+44PfcBdYyx4EVAgiXcQ4+OqsQ/6oDSq1klqgp4/tnLOJ+IzwmrsVD9pZ1i1nk7wK6Ge5T0AdO7aSdvyuSp5tMsbhA82QQh09dtfT8y5jntfeXwDUscb+h/w2Nrk34Cl/H79Hn/wBGPD4g0CzQD8LjBiAIfQJECtnfSzg8MUGKPQU1g42+wAGDoCqpwMwDsDJxXT3dBjw/rsGknLT8N1IT6QAvc0oGtZA/+5s5HmTfIuZpELCeCF4pKnr2Wamem7JvSzv+5lHNoPQw1LIPFa2K7WXAgdL6yECzXy3vbJtyrWEDiZnoFkthbhHoEhBn6AQlkLscLqsgSPAIDtYAs7FGadwyt7Gzj53g+9VAt6TF3cK/YgZeFqxbJ4cfDsCzAAaDHZPlig31+5psO4Y4NXu1h4r8zgXt81Fmn7Ss8/UVejZdz2RAdWXzxaD8NGfWgoKDob7XBOtxA0UrIMvJeSTpiDC++dq6YcxVjR51s4y+kMVa4xa7f01XHdP8ZjvxA+KJoCwCDx00bp4DTDHNuRZ7QD9efaJCX1oD5j98c3jDwPN55tjw5LYBC8tCudXvQHs7LENhIsJFQTkwscxCzAHU9eH6wiAmtrh1at5f/aMFyAY/PgMZ/syzr92KfUg0plDD2eWCw+0ZLqxxP2JmTngOTNhMKQwEWnqtoJPZjZ9lullZAymP5hztQVQ5XrltNMXyjJYSstmi1i+i5vJ2710gEJMbY3Ru2y3tVAxiLYOOqbgzfysZA0OAgFyXUH+UUhtJG0HL7oXzfaGETxyCmsI34hN7PpEa4AAr+NLV0kzxCpnLmwjQAiQHCvebsdTtUafSZ8WMJwuo5V9XX2Xz72AyQtowfWmPLNguAttCiQNNPO93L9In8/vNdu2mISypDtzptdNgBkmjSDyJOjkK3BDaKp8PfOWMcr9v2osvXXBvbn3LfcRYkIIwVktFJzv+USaax/YpJn3o5/N4vzs+De/0dy1cXCeuAESaI5+lY6k71Zg/B5onnO+SzPydJN4++Q7Fx09fJUdFEuaDVqBwiAd9KLhSGt6atpNSAsNKXjQaQgi1Y+q0aPL0DSXvA7OJ1MNC8MmTZ4tJhUm1imnZHAGlU9sPd1QOsW0zxpoduiaCN1e4wYKBQ64Cw6/nzmFNISY1zqF7hovgR+/c8pp5l/NYhp8piAObhuBZRO+ZXMbKhhdYGAFD8IUSiPlpLXgPmXAmFpc5UHzKG+rsBv9Jc9LNufGMgaLGER/IqXZ0lCaPttL+RmSruJZBC73Sucyzs7nzjpGPWU8+XFPG7CyfaiolMnwiQvpXdvhpCnIar/r2OM7dexlFca4PeqDySd2u/jvO34ACkx6hykyaEIBgLAaUtSjVzLHczEddeX1Aqeyas56OFpexZs6htDvZdrJlc1scwDRrzd9mfLsWK57Pi8MKQPv6R5gz9qDTZoO2rJMTu1+5GG4C3wpB4PV494DbVkKaD6T+VNAvwKAexpqbI/NtlNLAYZaqKaxhfUSUFghUV7DUtj1DEacQTisRnq2ywCEtg4WY1Z7wXdo/nshpqNuw8r9/7e9AhguALZqIVu4gXZZpZYjtlYi6HqGlcFtjynYRv4TBg4lBsfhs/i8Lgzxh5T5OwVYC6Pov9l38mcA0spr49rgBHfyohyWI1cLaI6wvIB2E52Wgs5AetrKGfKc0gRshgQ8p6RmWmPw+aCflkJfP0hOaYvpUsUcp0/BeradjttPLQoZc2WZB83LXap5PCh5ylMtSqf1Brm+8dz3j++DQm3ifZYyStbDlQI6hTVbjYO3ns9BANklFWpBzKPyJ/AePdD58jeHsUkDW+dVgjfPA/kVDCDXneY2tbPylPSzSEJ7YEJJO2Ifb5lONJCqg9xTECiAQD8jexUFo2MwO2cY1eZ4Ekwek7k4HVXv1XYYTOcl8CteoS4lw7AkdBvtqIZKJmEIXupA2FLHZFOzWKsQTRqB5hDkVovpNLBZALVlZlG2a2nDWZ7i+RT+FKeclFDfLdby3qvwZix7/tvU0Gi9gYFKmGidd6GEcg0Wf9UMN0kv77cEwNLlOEQqAIh5bHT8hbc1psDKJV+UUN1CW53mq79yn0Ge6UaqQPN0HR2Clu2nbpxznC15rMZWg+rnlsUMKk+lLGh0WZm+L/m3vCHk49lBk2mkff/nQIEtUJtuICwAE64piZJB5+CUfDbzKG6hDbo4mgTVhVnl9XUugalCcw6IEDTW6W/X8lvzHXnYbTFaAQKrwaZBPwe9Vua9MRgehP3D37v8qvwnyJD58roCzQctwcAorAUIqGnq+oOiHb7qGWjOwbJa8Hc6H7utEgDWCD6ze5LGti2eEwlQ0tUxt6KIJHQTVTyiFrF5TIyAwUsSIdY1LIABazpoDSiT39C0QoyhTrPDxK0kgrJkapaTLE8FqZKfjmHvdPEoVZ4GCQfbPst+xrA4PA1tKSiPQUdfvndLsz/NQuLByYkydOkgYBObKy3bfN3T1TXkfDQzy1Zll3cU+Hy2SdzRLiWKHscYntvwafyqtl+xPOsYTgWaMeQNxeJwIfH9elaBTyXIhH6Cxh8cP599VCCAaHVnb2dBaKcWMJDGEk8wcFOb86jR2SAAcAp3oF0955kC/AYEkDzkOjvK1BSvPO7XLNcwRM7rrxjskaF+kK7axCdNrQMCh9JWOt5KyzeZamptAXDfIgUJuoh0phEDzeo+ojXwauHfgeaccaRTU+tbC+lOgpjWJhzu82wObN8hGK9ktQ0syympaP7k9NReMNeuKs8AtCFmJoV+Q83fa4YXYxC6wK0AIfPvGXXWY9Nb3J4Kd28tmQKfiU5hYL3pHlmKt29TVAn8ryxfuZQc6jatNQsl0MU2KWHr7Sg4NsSz43nPQHMJaE2/EdOBVbGgC+r8uKPJWeRrVVzlwlOg+RAj4/iDsXi6itQl9+huojI23Hs+0pVLDzZovTvyQ9lPADhpx/j46fED95H1iywvPOmeM3bog+XAU40+MomB6/F8LAyzUfbox6NB9NJkUVjme65MrmcUOIo2SS00cX+Wt/R99fxz+R5Bge11oz2ly5d+mc6OfO3hXdkXlV5nPqCY+aTRyhqb45UWM89j6mkyMwHlpJUQrvdKoLnypXWQtDGqveqhQkNXKMfCgxCAPSMphL0bg8rs2wYk8iTbz0rIC6uYCMZB60SVT76b46TGq2RwH9fe56rf8ULVwVzlX0NUDdGi9cSM6TLy++yXevV876CdPInOw6U/z3T3QK5PmuZ542k548jHj3uz0Oejx3u6j2/le2on+aP4u7046xrXfoxDfa/KOZc2Osb2ZwfH9tEG/87xfVDgNwGo8ZcW47AYgVm+vLZX7TpZ6kaan8bpe/CctiwaVF7pSk62IUBhBXANQQmwXJH8qm2y44M6tqyCpRqAUyHXFsGkmd6j0XMwBqRsb4X4TbN/8yfleLwHPGowd8B4Ttezh4RJJR4wNrWjUBerYLHd+HfSDLlQDTUtFZyamuCx0j1TAelyHwG21EJIWvlWs7wP7qNepQzg2rBl2BtYFusTds5/XLZjiukG7NVrEYrV1AXBG/WxGAUJVcVCKo1Py8IQQeteFU182Pns2C7IkuNLOInUJ79I1rYRjbeT7/ltCNdZgDFGshHvfCh8PfgXPR61oGFF+ay6NJMvjm3rdhhrEnImIstQO9KKpXJ+thNylvLcAs2On1kKb8bio0tIxv1jUPnRQjhotBRGOtL83j9KYxm1rqS9WyD41Ec/OL4NCkYXxCglEaotBVBgI1cK17YXmd4WxlbaN2shhcEB8QQGggDLxL9V2zE0jT5yPsz7T4LUjmuTgNCDwfOoDRnu+eI7tDNGQD//7Vm7P/fuHTbzIwjY8GmiBDjzKy2eoKDndzQFWVoOGZcoV9KaLosRVE6gqOmsaCCovkDWQZ3xrHup4UZ1HLXG2I2x5Xu/5W/t6zJGNEjId42YQb763OQoaYor1IdI0O8/J37U2bNvXD9UUwvosv8yVBdA0+PLOMyg8wCjAoVnyuvaH48CyFvoINPrlgOZh7M8O9pofhekn3M/3rNkAoDwILZ1vZ/4+c34qx+GnoYsqvywfo5niz/euY2YldCqvYvuszw6Zgn6YxxzwsDxXNJ80B6OqtuD9L+z5bcx4geWAkDm42BjzS0DfeYGy/iB5W/4gtkLvZiNGk1OHcyS33yqPLJit52rDQMUaDXEdxIQUygJFOUXT4aSBT4tEL197hKEjXpTaBwILsxfPHljipnuBg437Y0uG5vPfqWdjDLZHFDUdk7rCDbdP/y+MgX6shE3KLCQuEHTGD/odlUa8+hAc6fj7qiLLiZkO0AG/yeWQikYNVtGnCke/Vnjw61iBRHW6gHaLjS+o4PUuq5mvBwoqwA+2Zz7Ju3dAn+nsNrwoS+5Nd/XjCXWW7S/YMGozSpLofd1WqWKxxj0ZEzOVjpdgDUehgARhaTminsFNdUFBkdbWOwe1ku12GxeX1nhd4FmID+6k+m48I7venDrjS7x0X3vJeFtzOB5jI0xq53AdN5nzeN8dh35VJvHteezJrRRVlbHIIsFvQF0Sxo+M7vp28cPQEEKWZ0QG91Zrk42LFhub1E0R1oMqfvnZOf2w645GIDbrpCUkTjOZTGsaTEACQ5pKcQcexsa8dBMiiZgoB1Ot0uh+hTY33IfnbSnPxXaj8z0TLOnd42gcr5+gEJwDdcXvAs029ugMtrN9GU6DTTzftIkrmAJwG9dRzxuwOA9FRUo4cVVxaW5otNSs2W8o6aaVv/JFM9zRFGxqTNKE64PR+3I3z20/vC+BChEcloL3gZO1psrfktoZBA25Xv0TwrY+NIgop6IvZ9WrfrNWEsxCtAWM/PC7fPrHWhuQOLOs1TjxjRgAYIxD4WOgtVpbCUY3gLNdmyIlwLvcB/ZlnvS/fwx3EfntfLQ0zj99E8Uhhpj7Cd/HuPvaJVfgrbE7gaNfSbVABpEHUi3nTWwatWt0/3k+AP3EVuTqkHfN5rt5uDHdaz+gGDSAAHj4rWg5jU7WoSAjlXrM0CcEovA8hoUVm1BUHg++euH+0AZAHx2AsLctO0o1ztm+y7tSdAnsxTzPTDdU73aukGV+7H+a95j2w2NSAWJpksNu9vYp6uJf6vvn4No7ozK9uxBqH3+dHg9g2nWj7bxuWo2m0cWI3/2inzRGJpJSlqOQH5WVuMc7p77QMYit7AYxDIwn9bCcB9129T6gp2apAO+w/9SM8VzE0DkmDuVaj1ubtGjbvO6ed61T5SP0e0Pk3cLD9UuA8KXU+i+o/W97k+WnS9yKQoLdohEezgL7zyNz+KTDjbB6v1Ne37eqy1GR3Bs5jscQO/DJPWxWw2i360fZAxqejbtgfa94/uWArdVzkJpDVfOOiorAYhrAOaGlRwbaXRLRQ6M0kvy8NmofJud5wSAYhRqhRJPAMp6IHi0z1zAYHkJxxHwLZdTAgKaUWl2K+0rYX+7f3Mf9aCCvp9l/crEPd1ivAaGJaKaImkr+3gEi7lSeTVtTjXN9PziGs9LgsljlTOvZfxn/dpCaEa7ge45QkRLLT3FANtUTDy0KYTSUsCgpvfRhlNIHqpmCvNg6Zh27TusgBDS4S7a27GvAIQrz9s9t9tOi4HWQtZ701JY6O0XaDU4QktehoXgg2WrhezFDwXJN8cTHFxXZtNSqD+ZtUfhyDpX/CBBjQHwbI6aaSVD2qntG2pqML0MDov6yGx1uLf7qqw97+b2Llvkm/2q7CD93+LEibLPqvLDWKwppsDNpUQQmDQR9u9cuby3jnxPEARkAeJUivuH5ME6Fj+/qecfHN+3FKoTIVaD0JILLK/Ng3mNgAHktdiSxX5aaWrl9bIug81zJGsrAUAKPgpS63SH2XxOFeuAj93ud34+8ptm36E9PTDdW9pgKEMFmk3KdIKYvBcpJFj/DipLOwnj852nFl/pMs5wp0Hqy/zu2lwtfpPnb4Fmk0CzdP+wPLTskHeTTdiO4k+twe3srwo5d3udg+cmXUiaPF4PpvuKVgBp4TZyiSv0rKS9XX47tu/hQoK1pUCgaEvGy/oxxHYdhtjgb+/4BrjnluA8cxZQKbLlcus20b4c1jSB4GYlPGjdTwFfe7YSxj3l97LEZ36uSprP9LXFSMkJqV404NmDo9hnmXsiwlm/Bop4zmd66b93Y/wWMB5nbsYXxFoLA+C2FX5WVRJMftbCNyvfHv3q+HGg2WapROh7AUFYwAkKMCzGHgDA9wEq3OhCDu1oeDV+32N75gDWzmQ5D6HSHUpGo8skb5bQctTcTNIg6YqhU8MBWtjV+yHM4T8KNE8rYZa3BtCpdYy9VaSMahkYHu+NgG8K+FUB5BkDoMDX7yXobKNaj3BYFBUsFCAaIMI+VUtB+u6p/1uQZ712ywxPxeW2yVoJFcOtHw5+LI7U8ej6x+Ay4wfpMtq0Fhw7P++5r3AbbXdcOyal7r3DYijB1bNTfPM624PTLXPV8MqYAq6FtQzbIthsQO742ntBhYBsBo1XpFsVPQZmv1BTp0UEeM4UIj8TcJx8SmGc02XJY75530rbtmVzZfPLxCVmpVmbe1geGXQuoPdIzxmKA+/qL9/J+0+KgPLGjU+e/rz4OPjuAQyEp09X2ni23ukV37ttq38oxYV1/GHellTSbsaRj9O3ju9bChWMigpEmQMMhqKbHbGwsOBxdm9QAMdkF9PhWndpkK7OzaQ3E2Ei6Ue647kltBoMFHYIEBg0vscq0Kx+dasVi027M5g37R04CMNYPWOTpqZoCTfJVxmW9TF5Fj5pOqvIYrDVqmR1LVGwq4VB4S7fWKj7mQdeAlCyFxLbhDwwQAvJF9qvcq/aTq+ZfMng1wG4rfzvEwysB6r1YDu4suWLc8Sltr+tA8mMGQgo+OXx516gcO2N67AUHkHBDlCQelrWIwLEG8hAs11plW+v7bz7C3QpIB1oyzrX8xgwrGi2AsfUppCRMlE5ZZvT0gGFYbezJWA7rd0V5QlrLh9SJYcdkGAQU2+7V2xb8FY2iiMBckv/F753vUc4SPlIz6cLSMfzw2y+r1y5Y8Xzu3zHeE/mlbYkQ2tswPWcIFlzC/Am3Q+OH7iPTLKPawaP41+r+pFqkq7uZ6WrjtaI34NfEFJPKhAAtHtIgjPH4DZl8LaNofP1W/jk/eU32pOpfV4//R5gdWMGHAyV73pgzplvlvOJ0U5X0K28rLMP2szfbzTjs4e74Jz3P+v4dE+l271NKNNvNO17Xntf66ripzyZwU1u4Hnw+MMo48wizaRmG9V1goK4jsKlJNfgb1olKfgWAnQsgAELucbCa7YUILOeNuA7Fus1ekXZzZtmqmIyCI09rQU2m836kocNCVapoVIaWLVvt3f539mR1e/2qVup+JcZLwkmW+fDMekr4kSsVhXdpL7ZvlOplHS8tPcCvLITBa/rLa49eWYElk3yP9+vcgI2x0W+qECRjY4E2bruxw8R/T8YaMa8LvdRXav7KCwGS6uh9jNtZ2c1fGfqR0OpoPB8i6a3zs+e/Yi8V8/QGrCeoVSB43JzqNVg1bnsyPWwEG4I1+Nddzp6IMDE4rAKMHMwmOzndF8d2elq8zktk1gDRePGdXa4fsQtBLkHcQuhdjxNQZYrl4tmwG26nsk1y44ezBQspjTWAw+DXg5OJ3WOvF2yb2iI39WYKkyQ//j5p1NNr4wj5J5L+8q/7dgfO2k7fm8Pt5E7Lr8KFDbfZqgAc+wnyThVC+2efmjx7pVa4o4UvjdwpeusVmwvMM6wanzGaAxWm8HnagdzgK6s7ZENhbCgabmYHCXUnX28rYLKDktXEfKb4tmZtGz2MUA24C+rdulZOSjeLf/DZQfCN4A/hZGYh14/BpprXPvtu9ZK+9Qq+My9PKp8V4bLejjL7MezpJ31+6mZgD8JNI9ynGDgR11PWsckQktpoR80YCIm7ylwSE2fBEXmm6wrNTgRONNSMJZF0NMzT027zg8B3LfTQwF8Cgo3q8CeA80mtJv1YajFM0J/LucxffTQ/odf+cbg93fUfvBSt7FHfLb9oB3n4Ra17uHqaZvXdRh6FGeCkAvj5Y+mNXDIEFj9acFcElPI3GMLb6ah8rzFMij3U88+AnYr8u7glNRaS5E+e24z3VaBgbOLTtr82zUTqUZi0tqCxwEKnp6JaJUKeEdvdtPP4ThcR81HNvjjUXCykzP+UJYA+ZpBVd3byi3XPVi1UVlwlDWGGXDXQ8pTfHbyV/E5i+mTdjx7Wggnr9/qf9BMQeDp2cMS0PZ/m+6Hx3+LpaA/nvr71v/AWAtXzz5lTndP/eMzCWmj15t5+bsfUsHWM5doKYzfZj2N1QwDFES7OgV7lWtUWoWsdf2GX9KqcToA3rQeXLyHe563WAKmO0q+mdBxCGr5OY1n7f69IjBqSXOe8+/p+k7TAROj9pyR4V3cwevPPD0f1ogV5cKG5WeelAZsj7Q1i7KCsiJTEgD6Gp2G540RP9iXiaWQVsFHxxRoJdBSqD947YeElc4kz+vSARS0TT5qE9e2rawCO2ixfqj/llgMC/Gb1sOUUylQEwXdejxp33nyUlkLGWjWwCpde+5W8R1f2WdubT28ZhSWMRGWwynhaQGgsaJcKBPpD6B4YiOrMXvT9IERh/RD8SJPx72DhqBRZowxgPkeO62HUb6Ddiu//HC5Znv8wfEjUHhXXrV4zja9M1t7RjSjmxb5dE8BQWnqiqrzE20WqqdDmiy4YgDb5LcdAlYDc/ZpoPn0ubvcGxpUDqCx1fcIKpu8y1qwAzeanWVS9w3PT7SHP09rgucbDbiBAn3KGjglGLBtqh3k2HfSA0DcGaXHfQDBSZt/LeS320hHa8BhBxjYEHp738+caeRX0i7OPhJwSBcSrwEGmpk5+bGBAVf2HxvHHMaZVlwJvJE0yzUD1sBglt+WTgAocFgJDMAL6xizMmasYx4qc9h/+plOz1ertTBcewvAyvbMM2nkbU/pXmsaFjf5y/yPFc1V6IsgksXONnQJNDNpzVYCWnbkmJ7jU9Itn0IdqHikpyzgs4NGOYADGFS2cchDaJPF+6hKHPfZOeVvRQ+cHx4/cB+JQM436Va651a7fX8+l/IWqGvNgwldzvmut8BQXNDXIFtNWj0/OsVKMN6v0dNOUzhTyHIWxymgn1DfTtcOINPQhE4XVn0WtGnNPfJOZZ7iqq6D/lW7671hvVAAxNlEkHMejpeWL0LeStRW2uoB+sdxP/jEOfYejxoAT6OFgl65jYK9QWBDhLyKPXG/NDCgtdSS12JRyN/eORMpAaOmp+o0VXUhJSiAU1rRbV7mCnnGs/JPLF5DxHuYpAC03DgvZiMBsagUaS2s1Am8rISVmVHH6XETjRaxGQUFb1DIvuEiOgUFpyu3xhMDzQ43y32Qevy4RdA8ZhQlICy2gYyzMgukEMu6/arokY+6j8r6GiyUQGRyT1itLYh2gaolxHRmdgeGTOcg7YiHGjDWP0HkjabTQwHBTYZ/Ki+FQmig+8HxfUvhv1g+v537Wn/HH431IaCH1ngKfdzuj0asfA/asBYUEOS9vB6goH/RmLWFNCBrEaw62woAgnBb/FX5HwK66mmP09/qu9FVIHRATmh395EdwerzPuS3H+9Eaf0EA7d2Ea1US70my2+47b4Hj5W4xhlLof3WmoNs77M4FDFnESHnYPh83hOEXabn0S1BDqT2nwL6SsF+lUBfeT8WgNFa2Nvg27D3ynsrrknbEkC+LFxFG9gfwPWRlsJHCJzrw9uF9JGrmHlOSwGuK5oz1GzoeI+OrdzuwjawMvBchtyFmAiw43qRRla5whJY18Jrxb5gtBZeO2m0HqQveszkyxzomUeA7k1WsRAKRHUXrQZSSga8oq0ZQE40aHDeEUAH2l0X74nV21EWq/2SPNcw7G0lNsYX74rW1amyt2R9ZsLz+un3LfjcbUJLoUHInvNI4ad636dHtgMVU42DFaiA46zP3z1+GGhu4X+7f2jkVjQeDRKdCQFBkRIYoIDj3lCThHaAwnhWN19nutV1KStANPr22GQzSwyhzbuFnp2E8Wxp+HynMsWDJt/aFN9lpWklOqGD78zX6tkGR86YmgzYvsxz+inuriHIGagz31uWA/ODHy3eUxaZnhrnOFycEoegj+rRj5z3KSBcHigtv7Kc1oAn16mrSGnlLhIhNH7jIQ2Oa79bChREx6Z4Ne9fLIVquSxwdIW3DmUEgwMU0OlG+vqj8MCIK1TXS3wBaJ1Bx2b3aIKBN6B7siD7w7Lnddtxbi3SnwxdeX8l38buhIb0CD0J4Jyqe9Ko9fOdwRu0Dt4Emp0nmbFI8tP7WcdDsCvN5NlyETEprSPr9mo5AHkJKt9ThA+hXkPf+rrS0RKzAnAFhu8e3weF/5qFHCUcPyc8d1gPDRx0OZiml4xPUBg18qKNcpi8N2kNSnsyuqGFOV+52rVpxx/Q1kDttgrIFNbu5AIMauy81sarv/mcF8NooJk0auySr7i4vCwFeec63p91aOsAbd6OWMKe1+A5LYj0hGsodxUt293FQqzB6+GqcO8mIfB5MLNanRQ02mx6FyXAkS6c/isL4DxT8y/rQK2GNdJXviNtWAt+qfUQFkNYD2ENXJfjYiwhLYXbLCSV4sjxUe5LB9I6ANIaSKuAFsPaO+YE7KTDsWg9XBb3zGJh2zKsbXjtUG5evvFKQHilFTattlYA5hlV3mEljOv+o+VQ12tl225UoDldZWst4SBLAFq5mSBuloJb9Iu55TThCQg1JbUKLufj53QLDeFS9+OeV+IxDTXZstxGOu4syqpWxPlMlYHyRts7X1tAA3RcJF9mPkcOr1zO3z3+ONDcL1b3UXanUzCwWodLaQjwTwDBjvMQ+GjaEYOYVou+M5OVu6NrscYnJZlOfqfQHcFoCTr3Wf9s/u7XPd6nz5EEKyFOLut3VOBOXE4+0OyzsswZQQbSNICcbo0Egt71bId7SPpv5z1DCL9FF1LxRHfFlUUhUOwEg/i/0+pAptEVWqmkoJtCAGGnINh0Je3j7CjBvweQrAwcd7pd10ybYHIxuJzpr9z8bnOm0RFo5nYXCgqDn1EgPHerzbHkHrsCbGBZXrsHOOw4xyevvQDCDHnW2UfAyr2Slm8sLLzc8AKDz2xrdWO1RajaKgWUS1c4BAySRwdtWWyXke1ds5FIWz2yh2UWnBX5UOCnchbtaXOdQg19AoTyTfJeqjCkDitWLXsZswMYYCPQDEk+LAvKBmCMucpWxj5GNga2hoLBYBm+64Y09+MnwPCDbS5EqD5kXzTpkNOlpL02gSHzEEakkKiWkHt3TPwcGOyWp/i8U0LVls+YYFAAoZZCDVqrB0bnihvoPShQ0qHlmzXDkwucs4n4DO40P3dSvYECpbDSut0HMKDjCuVSKg1WtsM8RqDOUdmgkhT3Nlqosxs9mbldI+zJnmnCpqK20wNYB3i7duAoIbITGCLOkCVNmg/aBIv7rKOmFTCUZpqziSS4XDOR6ErySOfcHZSf91RgYNwsG47uo3kOS4AgEX87aZj0XOPAQPPalrOLJdDsHsDgK2IKluseq5+0X/tcvWooP71b98kNCABsxgOAcBsh3Eme31lxi0WtBAVaCQZgrw2DxSdV+XIKdU93lAToJ2sm9+i9ukyrgnxmzWeDUaW+JZhz7LqhZ/tZt0X8nGMw3FU61prBTa9HQZXPhdQFxQw0cxxZpRtj6T1mjOPfDDTH31KtsKwEL2Cgm6H+SvMUMBlxhbwntI4LUOj3UQCjzxb3CIiI28psy/soS3kv62LiUpJZSD0ziQShqSA+glDeXHUI6CxxMZZ1+jklRHo/CsdYhK9chiSbarkGnYFjTcQsm0pmt53g5IjIJRA6foNDWBWRbsHrv9ZuPJdEhGas7gkgtRvzI7xi977NLm8fqtQnl5PqDKKdW1n7Nlw5FfMqF9DK9QQZfBa3ELa6jxb8WmEpMKh8mQSaAU+X0f4dIHD9RruKrtNSQIFIncnK0vblRrP8INFuC+HlbSG8fOe9DdsB3utK6+HaYU0YsDL4vC7DawGvl+HlC2sDr73wK7/Y9iuBglsKcSz3eEP1bvGy89xgQB7ey3IlswArrALMYdmtfMsqq8Hh8czVQG9I3t6OvVcqFJaxGisDdq9VriMtOt0utRIbvN+WAjnOkEIdfpegNU45Th7cQaZ59BhTjwRGepVvCgEqyk9SCpmBG7Mg+roIxTyp8e+Pf2tKapUpaWxPAKXdjDz4LDUjBRh5uCwGU9DgfZfnmLEK/k5XAJDvmqBAGuq5sh5Wg0JbAHzOxnWoXQcN+Hxajfgl+/4DrdL1vdpzHRGsK+2j6v1EI8hoox3lkzYH7oHm4Lt72zcUiKk7rsnPXppl8fQjp9q89OPeGHVx3YqiuIfoY/UGjQ4wH7S0KOa1oXWbJ0sCcj//jkCzsmt8+B5TtzkbIEEU1PiNLCC0une3Gtpi2DX+go2sAs+krfwd01KTjcFnvGTNAIXsD2JZND9H1wLg2GZYDDTntja7THD2P4PPfGG8b6uQPMZMTYYgbQXwczLC44rmnLk1AtJOWlrl4FnYCzaEl40yzbGkWr5X/ZQ948GyRAYoHLxelzXqii8qjT88oJl0x4xk9vaZ+/EHgebh9atX0RdJ/G+Tt+XjWItV1RAUIU1iCN1uflTwKMt4pkHB5F5otvGupjWYlCuDAh7hw2XhS4sqq4EEoY3tb20wC4wMJ41QTC+twWsDaqpfni1p8c6dAaz241o5lB8a+xGoJG19Z5bBZQdqemq7k2Dc2zPSMfTMPgbKEzL4uRanuRo0HIYGzq6BPMMUs+e10VJQ7zUCzpsa/26XUQebgetqS6EshrQKGDPwa1oKnJpaQeYPDTb7uO+yotmvEFgMNIvkonTOvvOaZGYZI3hJTIF/L98p/K+0FhyvnVbbvjLG4Hjl/IqXG14OvHZMRV0GvDzjCZ7WAz63FJA93byavOzsiljt4BZbecNQQeXt4T4KyyG0/fgs6QrOeb1yeL/aqkD2l60U/jk7yVGxhbU39k7X024gJ7jyNycvSUWSDyllVaKggGYc9gfnd/fO+/+XHT8MNB/oCQpSAYcEhIcp8Tc5NbrCOj9gvgsPNHUJ4bjuMvX1KGcF9CYQKTCcNIICWP7DbTSvFfUmMDQoyD103gq51PgLGMB3ogJ36r7SQDMtHJdCN00749DOysTzvpb4D9cr6CrnVtxlRg0aBFS80PjZpb3Fy/kpV+UluiboOjJrmjZqLR7zDipX3KAAYloGlY5bYDPwPGioe3NbC8wVzXQP1QK1TtMWRILAPuwDNlJqupbuIlvEiwkI/CuLYG8s2wEO7lh+zeCzIXctyfUJvnNtguMFgkLsmPpCx4LIhRjnB4ql+mU5/cAsP4tgETdAaPN7rZwx5MXb25ArnNGW2V61BQb7emMBtnN9mnUBDFgrPz9KRhuA4M1D0ugMPpcPTICBJFoRdXwl4J9op+B/Svd/4fF9S+GXaOKkoS9ocioQ1CaaxsUxHPgUvicat5cP9uAJs7NdpwAv+iGbb7LaJo0WiQJSxRVKe5Y8pMMt1V6rynf5k/NEfhl64Y8BIlDbUvA6n8Fnr7ySttrnWu+S1dBxv8tU+7PwfZU/rwnOOiVVg890v3kNmdQd5SqFX/lXUO6dckP53Ypomh28ZTKgj173bLMU8AASCDLgWzOGWjj3VFSlRZX3AxDMrSwervNbCX4JGOR1RbMFEHTJzOBnb6NhoeN07drx8RfKV8TrIticoLA3bG0BlByHG7nFxUqX0a4Vza8KPqM/G0Bn/IOlUPzq5WiKyccm0cN0D1EJ6vUKBBHk7CFJtwy0OTeiTO6xSNJ3THpuVHLAV0+KE1CoNQpbOFTdRf5Ag6f/PXmKY3vwXTNmjaHJmvP3WwCxO/0BeM8fftw7pOM90WOCr4/vWwr/S4QuCAJRgkW3C9pKiD1VAhBeKeoJDnGtIqAyTVqjN/1rNx8fpN2tu01dQGMx8Hmu6wYCxibUtVSWgwSNNK4AoAPOiHtdOIMqNg0MXQEKZ5fW4KCJZ4SWeehMDxgHYLba0oLme5a6nrK9xB1V5a3Fe+o+ygHE4DOlmwF+rFTXQHNtv4AMNPM1+Qpa7v16DkHl5GfXUXFiaZeoeepbNf/cD+cqt1DQoNp9uoFQ2r1FoPMj0l8f6W76aHfR9RGC//rwdiH9zmmnH7vcRwwqM0bPuELJBeoOoQjHd7BTML9SqL8yfvDyCDYbdrmPll8wv8JaSAvhta90IQGvHQASbqNwH/3asbL51zb8SvfRL48pqa8CBec3peSQ3smyK2/uZK5NfoRhr1fQPGHME8LcAtp2QFy4kjht0zpW5sEw0a/eQeWd0mfHxALzdB9RQfDVMZ17FZJv/Lilyset8rcsqhmek50s+/7eF8eTXP+WrP9DQAD+ONAsdBW8PtuB7oD2sNghjEXoi4QgWt/vTffCaHMR+AFUz2BQk3nGPYKA1CXfuTK/eoaAIPnAbLRPA0ILw9KQsj1cnmcttz5/NrQ2ON/P/ZNGY1CId30UENplM+sLqWcDwqSVu0jaqywfiOVAlculrt73a8CPCk6trC6roVAjcIzdDCjTQmj3kO531DS6dGq66tY0yGmjk9buKYzVyj2jyOsehX8FlqsMTuyU6uWUXOlC9dhN9yutA7kGarbfcio1jDfQkmiArq2y5Vy7pLq1pUK+HV3S486l/LXqPku0sEpBX6n1B3+tpGUMqgRGfuzHka7JQMaSD4eCFhp8MJDnDC2Ck6k7yCyUEUExp9WZQGOuLqIc4961UV48uVPH0FvBLays4FHpj/FtRwKXn+/w7cuj8vomCuEnoPC/5JqCN1+1rK2DshLM8IJjmeFXwsPKQG8IZ1oK6Uig26U0dbUYkhHAhnP57SLcOO/d8h0+aMs6PZ+ZcWFhQA46DUgbmVMf4j3SkplEOA8FhTWw2dkhj3jP6l6nE9uMGtry+u2JMF7vbYtErYJyv6oloRKp6kAJQVpaB1ztfGNZCr1oJw5I46PSZPDj98O5sn4AhOE+SqG9uQeOBoszmHzRKvgIGrbFXkVpPfiHhfXwGwEKH4D/Bri/kV/A9ZvTT8MqqEAzaR8+0nccwXv9X2mohlofg5itEyuOHWuFlUD//q9sk1/g95O83EURR4i/tS8Y4rzWhdd2/NrBUa8N/PL4e+2FlwG/tnWgeVu9V11Y746+E6UBci0Cz07r9RWBZwk0b7yySTLQbLkW3g1mr7AabMNWBJ1xcZEbEmQTyGHA3gLemc43+AHolTEklrViDYh1Gi6BZkMoFre6Ku0rSaz3vwKEN4+fovt8/e036690GYrfKfZ5/EFMIX+baDC8tnOGUTD8SsRfJZg7DXA0hHX+k6RWwpPFYCWw412tia0bjcJdy9EgMFxIOICBacz05andUKh3W6kbKMX1TeDz7fRvMnZAd2nof90WnloPYxj1nPVMJEYnvGIcExBoCZV8lXo8gsMRcI64Auo9cPRzQ9WZfFPg5F1G7ePHgaWjqgAzKsQN0aY1IHGDjCPsmm1EWghvlBsp3UakF7CgnvFBO+IIBIGLs40c9d1gxhSyLpYAaoba0XTlzL3687uixbFFl1JbBQ0QL7qT1o5tMMr1hBlohmWgGeXefck7grXeSxUv5tmDdzv+tRIDc9roMvhOt1CCoq/cILA20Qumj0VtG9yvau+F5amUeAKqI7+3sxtsS2qSppzVINDbXzggtJtAziHSsYYDJJSplV/11gMg3LLQ/B/yvYFBsteJEEXXZ3+KCPiTj+xQwRzaNIawXwi/5auAIJluaPHahlYCx6gZAgME+l90OijAhIha624VrAKoNo1DfgdojXoBRyziBISuP1/eZe7evVsIFPizk/t3Dy0CSAy5aiGU1946HZCe/Syr5yZ9zsJW+U3GSeskFWMoeoLaEzAUkHTpCQy8lh6NFPmquUFZCorqxRkArMO7U8rCKotBAYG+ZJSrZzsqvjC/f9C0chXlNwmm8LcOPh/7HGk6DTTDkQHmbPY6sxLezZqujLW8Z+o50o3jBQyvpL/geCUHcWXz8gaGlRWIVcpXnnfOVkKtaF7pJopVzr1LagWkHZnvYJPHw9MqoEIWgJ+L0ZC75+a9jYXaSj1N1gguRz+PVfzZbpyeCtsRO0hV3naucvYFrkEdoPAkfcUqQIJBetxSn0lO9koxAIFCuNy9gvP1ALTB5uylzwDhfPJte/v9+Sfa+5d97/i+pfD/yDO8hGX45zPQbCjtY5njl1m4kAz4tQgKq1w6K+filZg0YM4/4ft4tnHNexTwDU6R5yIYWAMEaUCn620uZn5V1zzjBgpauAlmEwzyr4ABVCIrLRWdq0RktELIFwp+FKhsWiQgeFjTciC6yZTQYZLZoA2fqABBgweBYHeaEwDxcJCYdaOGSNXF3LpNUWh15KaDqlUEh4IBxH3U1kCtPKaVIKuRw32UoJJBZbqNsMOd5B/57AcAuoo+JjjomgUX6wH5vWZc3WSeAn8oMZYgkNtSvNLPHW4dz8kaAQK/GHSmVWAbq74vd2FlJZZ/YPlHuI881iz82gEuv9zwawfv/3JLl1JcE4DKSuGW3bMbRr+US9PCLQSk+8gigHyl6rftBcfGXgs7/fkXHL4XlnvE4T0teHfs5Tl1N/qSW3OQxnOAaM9SqrHlwSU7V7wPAX77IpDnbGCbrCeCleCBApAJGnMQOE7z4LsyWiDrqRijPDjefSvHUybfPH4caC6GJt341xq4AbJxXDD8SrCo4FpWv8R7CppuTgWBTtdikAJ7Bq/bKhC3Ud5fBA1rn6kCSr3PDkAAgcJHulqphRZwKigVEABxB4l2wLzTii7Bp0F21phss+CD7+q58rnJgJYyqeVQ5Rzp9N68LpCwh3QKkHmDWmHbAvzXHmsFuT+Oh1hCWw0obbKAApPmmq7O/YfbeaZHPYfSFvVcZrz83YLK3k2mYFnWgTaldw3P++TJ2qFEA8opubheISyI3c8606cl4ilUwUCzrC0qnjgCzoDwUCsaUeZwIy3QQgg3VUxuiADywm6ffqXLXqoxd7hvSy4IjWs6ku4pnYewzgEQU2HZvjqqALq64EzXwWfly1NQd0fKeGNKRylmig8uyR5tap/vUaP5SabfweiZVu90Le/nxw8CzYcQBQO5KA38Za2NvxbwK4Xwr5Wf/bN1c9/0XkUkNq3o0MC0goUI7yzXa9FSaBB65fy6l6n7yBIo/MhL4wk+BkjX37UAdS/5oFLzesu5rkVucGgw4NYTP60shAIUm/nx+WidnomxUSF8YUzPMppcQ/kyziaMW26Bvjc6hrIh26K9AE8MyJacjqPzvpaFdBEf7HFULzkwdzy1XqdQH8rpnVGRtPigS5xxieXA+MOFjDWgd0L95I9xiOpo7SCIcDb0JzXlmq6ejgHEAF0eFsMv0H0kAWan2yiWYa/9gWUXXnvH9FSLlc2/NgPOtAoMvwD8l3Oaar+T01LLKLx1JfuOm9uVUyusggws71zQtu3F1RSw1ZbC8oXtr8zLMiCfIGct2DcM8IzfFPhbgzCyX7N9m3Xv4pTgvBL41f+iwWfOTiKQ8F20+qLQzsEyxr0kbx5Py7jdn58cbwT9qYRokPlUVFye9SPPr44fB5qVSUqQpjVgQFoIeSYYrNbYX3RbABUHKCELO2g238M0B02F/MsUqEJzocXwShrQgBbAoPXRsp3X3bJzsz68BYQW2ARSDL9lAcdBY3qT6wAK0YQggWm0sPestytN+q7ekW1GGnOM+k1gKCLOeifNbAJDNRQeD6/2tBv9vC7XkaXWDpuxhTr3VtenVaBbXdTfZmNMa6EtBpPpqUnLgLLnNfTMht0tbDQ2r0cBggib0NZ9XEd8wXs3DMYSGNNLl1JYBR1T4DqGiik4xCKI1csvZPA5xxTdRw1ePb7ODq3FlNkXVF4MgFu6bizbLV21BAaH5ZYX0Va1cZ5l3CElmztil1RfKT8YfLaKUdVHhszbzZPMY5jqR9Cs+skorAkG6tosWta6hC4lrvWL+AZl57wuoU5AEGBQHq+R9TAAzriBgkATHmiQ9595f3L8ABTyDBzuFeQHalIYr7YUXnleFVNAae9LolgUTCcQUPQBwchBl/cm5R5U5rv6T2kKBGM2FPO+AYKX1jHB4BCQuPVTCSxgKo+c/tZav+cmbi3MNxxcMraF5kVjeg7KvkdaAweGKTvMWlN+4TuiowtOCBI1i0rqfcxmegYFJfpsP94WYGySTj5GopXVDCbUPUFno/ZKAbay3KHRNjxnr3PHTm9OyH2cUUqICARLADHf4m828Tu7dH4DxDiK1VPAMx/Vlr2vudV1gUL9JSDsDVsaYGbAGQIMJtZAWgzIj+w4p7xyppOMAZwHR2cLecu+2Rbf1CBouaRtXoxcN+Jlsao5YIOCkSC93JBBhOpvBta5cI20SLSqT6guVFAbaCk5+sYqXUncs9/20Qrmdxq7VgGBWUu34831yO0U6i7FkQe/HWj+JiAAP9oQTwVlNHgJ2OXlPnopKBAYXulGGkL5Iaj8RKs/iSHkvZUtvqpMDC7newUMSLuBgj6brTeBr2G4gIoC7RCsdY3urPiLLn8HCuTDjEuONOdElr5W4e/lhNv1rl5vTJqCQQW6HwCNYBP37Z5OwKCfTf4ohzfkeBg8DGbr4T04Chhovhc0kBv6/bWy2xMAmD7BYaCVtSBDgQRn0SQQeNAsK9sme2um6jogUHjRcQgYqRC0cnr22LPIOFvIYdZbV6y9I9C8Y0Uz9sayC2YXbF+wFRHvV65yfuUqZ26OtzzcR7U5np5hvQMBJigsPB0HKJhh5zTQba9cs2C4cr4UrYRlDAobrk1FzisvmGGL/yNWP6P6JSwSC1BGbITXoMAAclgWgKfVIP0HHKAgf7D5e/ukEQQ0zUpa4pYeLhffldH0INwA4V1+mvH5kj8EBOCPA81Z+Ar8hAZtBlh+oc1eNQaxXtb3QV8/B3jqGVZDPd/De3HUGgPSDJWHro3QGUca8yiXEqKsZPY5lbZpBQ5VHoRQOACB10994mRKtNCs+nnVvAS+CkW6ieygedbZj98zBH/0nQCCOuF6LHCQd51ay8Y4j+sBCtak0WjzfrfOE1DgxsC1CrUhGcUdyQi1NiP7/v4FutW/sbKMK91n6eumZWGWygl/q2LS7cmz1oLcGX12jGgd1UCAokawh5CKC1oKwWL0tUf6dh3R0sgVct5rFzrQ3PEB8lS4pDL+lgDYayEaMrXeZydlKTu1hXCO9QMhtDmuLbV9w0p8jmmlVSfMb65Uzoa2AmhRGboNqDLkQIm+pKsG4Id0wrJk8aVvzFKgaydRwNUDoRxw3BMvMpDej/mNppO2u/eTpoP+LJqyz4NQfw4qC5B1Aea7vnF8GxTW/6Iu2rN9Xinc13pwG70Mv5bjteJsZvi1WntvP75YBxVoJlPUMDuuDxqFPSJmEVZBz0T6ZfF+DTSXvmg9ACYonIKAZ2WoeyPfQdvRLiKy/oOlAA0+B2PFJyXznrRKWxINDmUpmEl+lu+ggD+HHIquZW8QU+B4Aj8btNFQIkrOVhIZP2TlVHysBjnlZNF8jYEewj0HYwacbcWfI87bqRXksyu10LVysRSA9cpxtRI0UH+28jOjy2N7dPeMT23sdJXAQsCW/ZYd7xljUNHgoDDMP3fYK23AFZvaGTx3Qc3zjrjBK11FttNS8DgDF177gtlvLOtA86/ttaL5DDT/csMv7LF6Wjfke4Du6l+646K2HVTOUHi0Qd7bWPFdBQ9hipXAhdg2e9PF42mzOHLiBYDs7+CDBY8wtcQQCM+elshKQE0bmfyStOiClaBsKPNWP9GXs5KQi+PiNTZdOLnK2hGL8+qGGzxjHNFOXudWwFSA3wcI2/1toBn9O4qc73VxF1c6gtv3jh9+jrOFcGkd5gMUVipl6xUWwjIvS2EtG+6bdgxkh0ogU3Ux9QSLnni4fhi3YFDbEoC8aBMU0GcJqHW9UOVgN05HBuG9e/UOCM07tAoWXAJzHYR2V7dQCLr4pKQCQZwjWD1pbTVE4WOKq9U7ahBbP6M9MAFB76EtjBsoxLtufF0WhI020XY6rzX4Hk+aDIjU+kijpF7R/LENtyG0/ASBpbSFVdaEAZLW836EE5ZYGks0gVZa0oFRTGK2gmZdXrMAAkuhZqzDU0uotbBpCbAj2lqwTNNWgIPfaY6tSGR18975fWdOT2VcwdIfnxMwgLw2cRs1MKjFIJ2bXcK7rZVX8N+8c0hhz226aott9DO5J2pAhyGFaqxivrKTS51JcHW0pdRtmVKDApnax3AZefdFdUnS+KGe2l2VLkmR0pWl5JHvYJ20LKoG8IWt8LSwrllNR7HAIk+uuQeQXWnyfqE9WRxPxw9nH1FDr3FVQFDntAbWr7xehtcr90DKgDS3u0A1SQLOoFGMUZjajd5bcpPG+AFXU6f1kn31WnMrAeDuPqq68XoAgZZ3MoryHVB9IkLRa4op8GQp9NfCuKJ5ozWoaSkkzft3xw/aGvjMUuj9TVV/neDAZ856NW+dZjGBY46gw936DJ5jAEi+bBNqazmTCI6aGVTz0cxgnLaYHe/R8UHbyQyw0OxgsXI5PgAAtxew2v3kBm6jA5incIj7bl7TLkNJ9KRlsNTIpTIwczTrnDFOPgYQs5rgwIuf2Zzn+vyme31HwXI+bKSj9cBtL65wFRUwoLe2yJjCLzzFFLymao89kGRySFSnYwrwnOePF1ysopoinWp97Ys08kkQwC6Aj+tc5OqdbiNiBlzzUOMzYwq0FOKl2ej8XdI0Fs61MCcoZ1RxQUAFKM0/+ZltIbUEdxcoPq3H1To45ITimbSss6kP3jkthR6sEwRGGsn/u8f33Uecklqzh8JVZCAYJO2V4/FXB5t/veLer1f79RsU2NTW7S20thB0KmqCwQ0UrNYpvGA5PdXKzTUC3VkvAobSGijoUposPMVaUr8EBVlrIOlO9xFgFc/aCRQQUNhoUKi9Yd7QFERYixvNmlZ1sO6Bm/CGSd2egQW3Z1XI31vxfs8KNOtDKwzkwmA566P2MhL3kW3LQRXp+DEi9wQEPvtKcbdWmv6W245n+nQHFDCsdBOtBawrTHKCx7IQJNsz+7LnRJC4dHIDA6/hAQYAgGsjvn63YVdONV3yQZ0U/PW3GzzGdtr7CgVt97TUCCw3GLwQG1aG+8gbFJBjvWbbNb93v7fWb7nlRUxweGHl9uuchln2SGrZoWi/AIsV3BuhLCaiIqZdrBsoxKSAcEf1YjjP4HNbVQ4vsOcmeY6cShyMgp5hxqmuPoRsaejsziwKY1kt9qeLqK3nAxCUz0/BnnRDs8p5jy/v61lWzU+ti+9aCDx+Hmg2mX5YaxMszNWFCjCvFQtilBZTV63dNUYtL2oztfF2GwFTox8uJatQYdCoJCJN43QbdaBZPaGnpcBy+aB1mXicovIOCsXfaKaxuu4+VZopLQOsHdRE1ZIDYB+0ztdGvqveaXL/DhSnEH8U8GIJTIZ/ApIH0MiLXm9xZ97t+fUuMGgLLH6MxWNfLTiwzWAr0o8v4a3kSdLWAnZYlrQAyj20kjHNMs4QaazSIYRa7inFrZ75Lqs4WHMtqDVqHYVlmuMz2LwdXt8Y9pYA9TufoxM9JYauZO57ST96ZASa86/XL2CCAVQZEmAArQEKQKTvvDX/SB8Cl3LCfNdY5zeSI8C8a9wa62N0bq5Bg9QFlmdHutus3W5ge3R5vHohB6W1AB8uH7EGXNPlOyjoQ+hPq4D9ybjDQR1jhWUZwV9Xq1KEhyTR8xD6PA+A8AYXzfcbx7dB4fVf6YW2dh+9GD9Yuc/RigBznD2DzcB//ZpBaGrvKIaIo4vcweQMER2gEH8vm+mClmUDLRJPV1JO9xN6CP12uMzgM2nRwEOUP4T+3X1SxNdeQtP4m+Zma/RqDTjSWnD5zXuOYTXQ7dTuozWegaTj36TdgUHFyd1amM/h9iyaJn5Vl/I3bdL5nnKjueRBzU00JW54t8xwmQHbcDngV1oKvyzcQ6+2okKVN/gr63UZ/JWqB91MaVE4AH+lcF8b9nK45+ci3eHrApZh01KgYDGEVZHByvIX76hUWQYplpzz8K8r891hLUDdRxdw5YyiRUshtsvWQHOsTYj1Cq9cp/Dy3im1p6KuXMCm7qMeHy/pHYrPPpKH6I40A7eHuMwjsGv5/WUPrVBBijuoVpDZGONoVSX6K60H0MkW1oOlSmFISwCY6xWybW2nSseAXSRIxku1ZOcod2Q/JJ9wOqxFOioIAYTZBok1BANtIg0qD1rxs0MEwhwUWczzXo2fUxSxDKC1c4y1AVJfHz8MNKMAoZSt1NYsZxitF8/AekVwua0H0cxXA8IdFFR7j5afQeU4SGPA7A4KD0CRAr82yat0ah3gFnwu8XUDBAZw5rBpwD+EqvoirevsII+ldp8axwxIW/pZFSjkgzJofXXLM3S83S2FKdA5gfEMQp/AMAHmDSj4d2gdSBeFuDYo6xhs1oqzPxIYliP26HdUIHlZ0LBQrqO1LLa5WGEt+BJrYKlVsEYg2q0/BmO5Rcu2DjTTUiiLIWkV8EaP+5M5GChlJ/vyjJhXpd/+jampJQT14zr7CEyTx6cSdVoIM9jMHh6rVopLI85/VzYWYs+OWKFvQLbXQjQG90WyFO4s01R1SJt//MATtf9uB4yBxO0pgkFScktsaCbuMRnjNZ9hOtN0PWjdD5q0DdA0hcKiKTBwxIqAr1wOQBiHDiKmcXnwFmg+f7w/fgQK2ga9C2nOKlqxx9D6ZR1ofgXt9csOS8HTUlCh+3xeyQwDCNBCvtLA21UEZXTPmEJbDJFffoBkWAo73zGtB4rgOPaA6+oD6aGqWTZWDRoKm7wt7M6cAfgxrbTe2jQ9u05JVVqDQMcUTgBQIW0FCl2mHuxDuI+/BglovsPKYRtN4R9DwkYdwbIzfVaMMQUTi2FnI6yVGl+CQQUrGUuwmI20uLI5gYN783vOWGJ8oDUXyy7zjCkgwGGF22fzq2EHKLBeyABsM0avTaDf23daBnnPdZ9v23DfQZsfkM77DuT2Fu2OaWG+Rk9xTDQgNDjYAQq6VnmqCOSCk2cWEoSzf/kOzcUSSGINQwr/3O1Vp7CWdcL6lFvp+Cu3WZbPpZyGyWibgl4Z0CZY5MD05TGNuCR0AoF1/ekmYmsUqIgAv8ljvXcKdBwK4pmJt16gGd9o5zUerr84vh9opqUggWZOP31xSurKQPMCXr+sr/9LZx8JoJRYOa2EoOlcaQ0QN42Cu+nlKuKfyT70tpPeA0aZfw4iAscXoJCoMMZ+VYjaR5aOgRVzlGPKKIBlVbIAxjtQAPLTv34ChaGDzZkfILXCcT6vZ69Ma4D5NWBU6/hMp7Rd5bQRU2C6imVmugaKFOAJBjsHcg8EAbCVAFJmbAv5aUFk+9A6qKByMHQobwZfrSz68sxuI8ITIUxW7tWz1sLOXe0aIDQaJJyRhXdvzbhmHaWg9x1A4DbBgdfYEYg2frxBrAPLfLl6oAEAD4L/3e87KJxS5aY4GAqAQ1EPWyB48SqhZ9jpxo03RPw2wsb1+c4EiLImKg758OdixTiyLdK2UVAY0pWDJQU/LYolg4sWfQobT4AoGiU3x++J/6OdhOa4AYKyBnGngCHvq9toAMuo40O+96778vi+pUDN3m7jLgbDoszLDhSgqE4lkMDD3QQUWymbAVMcKShMy0CtggYIM00nuq0A0fy7e9jnKgApozty3iPalO1yN+Jb/xKpVx+XSVp9MCcHSGgnkqvIlPEm8rY1rf31b/yZVTt86w/Hmc9yHyp6dhU4UkeuIR3MrfU4RaV1S1EIuzFWm22VZ5angogEXTJhUlM417uSWWe6Lnt7sknj2TM587FqWQI/aeMYGk63YLdr5uFe2mf9N1S/tB6UdsQkTjVRx1M1gWHUqqchnMWe40XpKlnI483rkPShwYeAc2lr5Ty+/xSdPt51K489vS+rmAyk77BRUJ98qAynY6w69+c0PNE+O85BhgkMSntK95jfCRAPz351fD/Q/NJAswh4y7UI6UJar10rmtfLIvB8CzS7bHUxxdQ7vfVVmsIuF9Cr3D0NCq+8F9ZAWwZx76rrhQttDSQtt7scNAUHR2ttACBaVM9b4PADOCIXHV38KpoZItBCYOgVm5GrD7AA9CM7uRGeq3lOt1FsRtaQ9g4Mel8k5SPVCU+YPq0MVAuRkQkUDQS0WGpmVE5F5PNAWkLpcuFOsSHr8tmcadSz1OrRcleUdu4U0tkT1A4SbunSCewwegVSG5RpreICMrjQWtBSKSqha7NsueqslIdqWaerKLR895jEGTuv7v7bV87sudJyuOIPV1kKrq4j9hQnUJj8gWt2wmJX62H+3cfkKk6CnOOgE0hgEx2t0qst71D7ta0CZ5uJhUAOj471W0xBBlpKSZPkDs57N952xNfbqEicQpSWQrmU0APD5F0nIv7J8dSk36H5w/U7gf8HgAD8N1kKEWz2+dsQn8Y0zL+lz57Oiq4N6YwlWAl7CA1CO4HkiXY3PfU3p/Y9WQ4qOmv5PERrK+gWt4FRK9Opi6jBS2HITxnybfyIjtohnPW+eb+EtY+gMmmQ/Ob0z2lFPPHVfbromUf8acC7g9oUA3xBau4iDlB5tSgJgS6aUkrZkKsU5JFftzRGXeaobVopcAUCks4w7o+sSvLnG2Wufr9KSvD0+vw9Y0557d6/JNJI60AthLAiNq+CJ8uB7fqqBij5XfjIhtYqSiueGriqASzr7LspcXo81QvHGGc+ffaZRn0mI+0o1HjGyTtCV4u6+1gSFpgceVrjS3W7oScMPKWDpJfnfnR8FyTOe/p7POsz3Q/K9P2YgomlkEy2ONWbsQJaC8ZzzApZ1jGI3pxuunNO5jsFeAeIO/irQeN2H7XWf9P26wsoDguPPDpMy/uO9nhnUI8t7qHpuV/Z7jvxIO5pu9Ov7BmYBFaCYFgN5d4wgDt7+jf+6KwoLRdTWPO+0tbIgy4gv+W98mm1QCiS1MUygtr5rnLForXsDUszu91OTLeqt02erdaTAZ5t9CAbivQZw5+DzDFHs58378lRwgqydgExfx15NqCsgyxgi3wR7ODG5MGbO/lze/yZz+trX4A5Xjto2GEh7IpJpGJCJSutJo5F3Qvw9jfaHOhxmHUuhO6Gap5zoWiPnVw1af3cu3TnvfjdwyXfegAfz3Vt4GxSenthNe4ORaCUhZkRFRE2gytNXvyEB0oDMP3/5/FToa9TWT9N90n+nxw/shRqJgasg8UWgBE7k+YU1ASCYE5voCgw6Smhp89efYq6buAWGDYBANKwhRZmdfy+UgsJIR/vTFoBQtPK+SKBvBJ78THe1OS4/3tqdaNvOBFvA/4KEem/atDW7JTDJ93iIn550Zin+qYPWvaPcyFMpZ0CHmiB3mKA4qpbpQWZyTkZ3ru8BVDeZWq+zbpkIk43Za9b0rgDMTnBOOpydIVm1pbWjc9PGTMayTGdwDbvjyFttZ0FROhT8AKe21m08CdATPyZYKCtSZ7ydB9txFqEDQGFXJ/QQHFh7w3Yhc0vrkmPqbBsa10nhIjVDrG8ChyeAGGORx5T4L2TQHfpdHvHSHeo4tqJ2e7hypMYVHZRbY+ePFY9LW4gIwtUxVF8VcYDAYDZHZUua8SkWAoaeKbdmPUdCHzWhJXubKfZVLd3/BAQgJ+CArrSqmmUKyg77EkbCUGO3JrCZ34itpQJh7XwbkqaPGfjeQp/mS1EIa8WQJ69wGJeh983xRiBYF8xvDlrhOb+aK+YvlIWAyxniATzGvdjobksfa1aPFlrskLQyPOMD4DusPxZdFDs19AawpV0uhGmO4o0a6mfo6zKlIKefcrfkYyuhBiVDKxa5ld+/JKxKiCmsDDvHWfjNsvU6bum3Sak9f5JdwCnGJcqHVcNsVIgEfTx+7QWqhimkJxpC/0y5+KjjDOAcQahi2vJy1GO8WcpLTum0oJOy2Vvagloq+Pshi9lnJ8PVOsdKc2P+0dumoXhzBIliLSMKd1pvI22EfYlIPghZMstVA3H9LMAT6Oy031+vAULpWkZHsHiuKfPPwHCD8Dh+4FmC5fJo/vIuC21Ydmq65e4jiLIbB1oHoIfopWgBHK7g9IaAd1HeW1qKXBOMwPIudoTG4aPzI8f1HXAgwZ1GfE603i5lhCBQWfgL1ee7n0M0G77ZQu2Fszi61DGbSIREYIwY5fMiGAEpaemRq0YvyDcdehPZ8+0J7cDeNzGeVdEomGzoxR0xkW5+qyAQeFtcKd+2swdM/vuAobXKwdfTzjEqJVO3vSsOantf88UjgrhsBTRF439/Bs0KZCzuB5AQVq/qN9cUJBB0LAitt6JP9ISFHy1ReGW00rzj4WzEv6MFVzYSKvAL9h2XPnt5WtfWPuCW6xUhtP1lOLWUNuF42XBe7nNt60NLMQO0YwwS091m0/5z3ZSV8072aJNj2qdbkMM+sxpcpOm+cFRgt4KGMgvtTgRKOthxATKN2XdAANRUHEFk6nX9WpDTXq4F+r+i7pAAcOT0P/q3rt0573z+hvHvxdohlyTLhbAo8VQyosLncKS8H5q/iki31gLld4zjZMms+FdpQQHZrIsLQOd9ieDNoqboJBzyPEFKHh6juJjcjsk52IZAPgsO6fwUWOvdj/6QZ04/HcqVK2BK3QcvSk0P2iqUs1nSD+1efZhrTwmjYK80tlIV+XzUwg8004XXaxZcJRrqLvvFoMYv32ccnBGu53CbUwp1SBoMbRjWAaApCNgiLtJ3twxiRaizX9J4RnNZw1WLn5wUX/pV7Gc+pyK3Hg/BZmIaILAHRxSgio4OMt914yf29rvSrRLAiV9rWzPNBroQYKAHwnVouCdkU7TnwUQpcWa1tzelPtU1anw6PUDSzwPvf8O2g+A4fuBZpk7YrCxJXVMe+PHwD3vcV9Ek83pUOsIuDVvC7Xp+abQr1XGh6WA40y9mh8wjzjClQI5LYCdvxGfLgzXTwSfPQPIDo/th8ttFM/65mBtS2Ff4lI6hdh6hQtp0VLIjTheDvgrNZr4GAiWuFiiRdHMFKsC6AoKrKHQj1rrhgF0l8TOM/1la2DCaUNztzzndXXYHpVHu23ar7851dNN5GJP/6RWxdlFDmpTJclauvBwBCAUM9tNWpXnj1q+LGirj61zSuwtXdbbm+tETelyVduwIJuFQ2j9cW6XUV5zu4qV1kI9k/cWXZcSVygrIu0G84gvwCvOcPnOKdgRe6C9FltxoAYit/aIWR3od6rctK6bY87CHE3tCEApiPBCi0qXwNBbnD8DzPybIx1yjz/cNP972j4/C/An4d7TZO9gdpPlPXe6UxRN+TfSnpp/q2SZXbLADYRGxeVt79Jp+vP3md8fAALwQ1CgEsKhTwFfQh/o7yUQEExmIIEir7XLbt6TXdDC3lTw699+OCcw5MAzT7eQJwBQ+PtHCp9wN3kG88wd2HQtbTjy2R1icW8FBQILgQFVG6ydu3O+8sMhvcWCAcCOabz98e+4wdkRDKjRoVOOFt/gnjMtnnv16KQRIBoITK5DU6S7KY5Iz20HkuZNY7/QVRVlauvFMo+KJWSZuPe9WjBvGZiDSiRPBbEJDEMqUfokKKoFMaSLC9dNi6XjCnSktJiowLJRiOcIF4E/AQACFDu3TaAbSZ7zXUFsJxBkwLm+WZZKzsbGlci3s5ECPFCuDa7QRgEDAhQMUZYlTZLl7PUw3Yw7++HmEWHwx/kcwZ4gICqeq+CXLGSkd3eb3G/hOruux0X34QkAJ0D0vSn07bjbAnwCjeTp57MP7/I3IHCARN07niVBjNNnAHgCkidwwEO6bxw/n5IKdFwBqvlzJ9NcwM4ZSAAWaSDPen1PYUnpR0zB4tx7DzU4DBrUohAwwAkMMQhDuOfUPjhsp4toWBS5MIhWRQp9uGNzIZF772rJ+3UYtntu2Ab4tSIPeyGsEtQnIG3tHGxECzkjG1cFus/fc4C0dk66xh00rVGSFJ0l1+eE5m/ex3T1NZrikjm6a3DZQxq7MXTHB1ronzGDdh8xXwp67/dpprcBTpo9pOMIJS3FpQLCalAYf2UtdBfaKkzqfMeCm9kcdDm1piwxCniDQP1lmXmdbiOn4Df2pxcQ0EHqjtxpN/pqidVLYW/VDrNdHxy6Q/CPP1c6HtNWnmNKENvGmp0KjGafBjsQ+boS7ifNGsSc+UknDOEr7/hMUOO4ng11u2cPtEdh/pmA/wwcnvL4xvFtUPiFDwAqinr30V+I773GBztiRfMvrPgGrBle+XWqX9ab2E3RMltnskkGmjHdR2ohcAUy4FgZQLb9EesOfLfmvz/KheQ7LQW6lPwC9ke4jPgc1yQkoHim39fVACH3kKUHgLUWYqvYhe0OsxVb1/yKvXIcKSlWAgMjgRr0wvkXoKvC/qS1ZFn1Wy0FAsI+8hU4h72hRQ0733YsLNSXr1LHBQdmnTHedQeJ6v78pnH89tzCusJAid+e9wLPTYLKFtbXNqHLuz4ri56reVK4r50xIU8XUJ7zz/KTmPGhnLhv3PVUdhimG3L4GxRMzOFrx7egLTbdw3K8VlgGMMeV5cpqwnheBrcVishy7LUzyOpBp6sJjosc5IaLPZYgS1dcKAOir3wKCCth8zYxHNxb4LDn5S+nivikO1ZshGjne07wIRg0P9FtSFArfhK3Yha43YpznvZ/7k/4+S3IQNLhId15fgKHp+tvHP9+oJl/1pZr0HZNUdVJD21heI69u1fxrmdkOv9cJ2FPVzpvmjidkaoRykKgBbHFoihQ6KAyzxVgvnIezgMoRAnS0L/SdN/5PKxo7b7Z3UBYpaHGwjaXllYPcNPoLGr1UWgKCFior4aJcI+39cylNun30dMP7/em1Rp0Z49Se6ebwmaZ3PtdwuTadcUdD4zvFKzQgf8wRj4ZGHXLPrsrwhvHuf6AmAo66ZyA4QQYNinzHgOpaY1h6d6RNFWqA3vLMshMXC2GzKkFaVsMq8BAHbgUtA/t4ziENXqk6gwdz3IcoxnjGp0H/atk5SqnlkulQj6raYaiYZ3HwQPq7pqNjiMhip8H7bh/49snMIgXo5W3ex6dP5nfDjruZXzKA1P3+O7xA0shp6QixYZ1oPmX8fN+YSG8LCyEX7C4Z6sthQSC83OcExR6UmYHk1tPaF0hF5t5upTyu7Qh9ON7tfANXDy3pYD9OwTS9ZHuoivuu+e9XXR35HMuMQUUOJR7ieLVDL4u+HrB14JdYTlcF4Brw9cLdiFA87Vhi6ucGXdYqIF0G3iyd2xNKZGdbLx76dE/oT6NO7TXe8/rSWut8NQUxwTh4S7gdx+CtnO/p9AOUfeLlhbC3nnvCo+MC3bzIzt7W+0svfcqK6ICzdsGrWMULcBm06l2k8J+tesoLDuPvks3o73ivu1uhfZYurhMM4h+RWUjDpeikWb0C2FdLI+P/Czk2bFXhqEW6trM8rsPwLb4ZsE2xIeHgLYK0N9ovoiyjgg35B5T9TW2nYoebKxBIv6y7ep74k5tv60C0i4sbH+JxbByF7K5Q5kzD9J81Yd8Bq8N62EJIDQ4bPIHkpfSGhg06oBX8mnpghY08oxYoylm6tyTHkSEfQYKjchoP5g9p8ObfGg9bLk+0lAyeF5/phSdxx8Gmnu2kQaaX4itq/trTk2rtQzA2AyvjxYfLUZU5JAtZKUz5nbBNn0LLUG2BIvzt5N2xTxw3wEK7p7gsHsjsgQZ372/va5TqNbPIz4J+QqzfS0sNyDPewNYnp+QXDkgY6T52JPgYecmCQw/0W7++q/+BjBEr857qNZWkDjst+ee8tmLWzRQDvw4k8+5xbbVtxO2J1Bkuw0jzm2eyw3gKQQAdRUQGOhLbkBA1YNceDeFAwzA6cUJCnQb2fL4CFWCAr1D4VKKezVNmgIBgCVY8JUEhXD/IL8NjVzzQABIkCgAiJ0E9iIoZFsaKgh95bjbxi3JUS6jyy29Yl5aJdut7Q0rQaPrADzp1Z8uG9D7Ktptg3qhPe1JUELeUpArEBxKElheAQStg/LAVp4oRQHNKyLglTbcmTyL++cz2jMgkPZNQHh69t09HCCgNHzv+PniNQSTLKhiQ+Evn/Yzq98vSa/bXYMaktbKh1EIjSkAwPL9FhTgG7azZyjoxS3kV0xFBem+4R8JEPuKa9/DemD8ALpgrdYn7EL9coJQo1qOtV7YKxePLcflq9YrXAkK6xVpgQCOaJQF2BahL4J4DIr779KAa7ChBJ7CqW4Kd9P2bz5coAfwc7rQChG+a7R/OAT+3SronWFlt1X0oCUwlLVR3Sga3k7QYPwg06OeXQUEWtcTQKt9Ch/ZtoC6hdo1lBMhVs4oSmAACBBZy9yRc6U2l9sYlYfIV06S5Otf8W57cbAQHEwAIgUjZxItYC/LaanWlgJ6YttGfK7U3PGR4/WjhJFnOMOIc/mNc59gwHJW0FkVA7EUsNJaIDCo9SARwQIQiT9kHspDBRjW4LCtAaB4h0qIgshu3hlg8ERzCn8Dvcoq6BUcniwFjXlBwKUsgo2SbzcgIEDICU6GBPip0dY7ZRqI8LfBG4yy7zRPcvxXx7dB4X/hdxWHY4eg8F+g68jwX+k++i8Y/hes3EgrXza/lsbjhL4SHSnsW5wt77ULaiGUlbDTBXR9wHcK94+kfXy0wL9+h2D//TusgesD+/oNbMf++KdnGZX10LOQAhQQoCIdWpoUDGtdWOuFtVYHl18Of+24/hV7Qvm6sPV7pQMcDL1ZXg5AxhwQmt8ADKC1YLuDwhToXJPQELwl36G5oeZzBS0F+sXB6p3ukgHN3aUuyeOiu0E0xQYPCpi2LK4U8nujLYgNwA2XmPU7gWFf/Xtf+WwOwu0LvYJZzo0G0U5pKTiqqQMAVvbzK+M/qWzEgskN7Nx+fW1s2+mnTy/+QrqEgl38srASiT3UBbJ7/ZV9/SuUCP9l8beA/TL4K7an3zk/4TKDL8eHkW8gM1Nbgw7rwLNdwo20M7zF8yutEOM5+bpXvZyWY/fn5eEaco/roLXr6EJcX/4rzy/sokk6ezXIYGHbwhaaw8oFVUpJ8twmYCQqhvJg5T4C0s1IYLiCn2p+iQMyv6RAwnenUwCodASHuiYgOMaXs06RxxiDuoJ4CK3DWBGnO0NcLueRj+b3jeP7geYSfD6Agd5vrlOQZVTFNjEltZ0T3M+9SlyCVf7OoLJz+O4yxZcTHLyDyuLjtxyUxkCx+iDSQe17R8BYzvvaNcvIr3QR0bKoYLGjbPFsGwfAze7afQG47Rxwse4hvil8Ye8FrJ0YsBrh43uSObi9Wj2OVTTYtKmGS8QYZO7e46YI8axLj1I4Jk1Aoeum1sF8f7y3pzq21cJ8XJ6lpYIue9HRz9HvX64BaU9+MWsLLcGj3ENUpFIARrtszEnQfXTwu3pyqlZpJehaBCOtrAmE1eBpOSyAU1OLf3WVmBoohvxuuak5PcNFKfgp8J20rvqkwUc7bwA7JUZch2ChErtFwNT49Zwswja04EE4Dis2YznDxy/X4vevZx7ulZvIVS08+KP4Ve7tM08U6KsbiTTyDihERXworYS+0p7SfUmTDuf1YEAybIJuycQu52Bc/UsZyk/VajrDyOpbx7dB4b9oKXivUXh5Wwq/IJaCA/+Fhf8SGi2FBpEhhvDUqqelEECQloLTUkAElSnoU7O366PcR/77dwDDx0fcvzb2x29gb+zfv7Gvj/hLq+H6/Ru+P7CvjX19xDTCjCmAAMOD/mEAsFibEZbCCmvBFvDLI4j8a2O/fsVnHH9dsY5j/Yrpq7lXEoVtqY5rWgpICyBfiDEwAKgVMQeOCuAzSJxCw1qjp6C+LQ+01NRMNfx13D8tgFpF0oFDvss674v3XLQ9p2aXVgK1PReaBAZDA7TU+NZwI7laCuI+KgCIyGqr2NmcBoSVsLI1dwh9T8UlVueHwgCL6aQr9z5CTkvdL8T3U8tSQA3aGE+G2kGXW14vWgcL/mtHHsuwfy34cqyXRywj03Kr7FhxjXBPZvlSviHWIRiwN65gTfhOa8PDk/lyw68MNNfOBHwO4Tw2yza0jCWUVUB3keHa1OhfTcML7gsX2lK48Avb24rYaj3EHglpLail0Lub+cEvRZOgMi2FK5d/bwaS3eBX8seVvKHuyEGbfYcNLmNq64H0p/P480RwniHCXECDtMc85O8IOJeLErgvlPvi+H5MwS+Uv9zbzDRwe4tgphcYaPaMI/Q1LegYeweksgoDGHIQ0mpQ68H7T6aeVFDZd8YXKpCc11eeGT/4+MD++MC+Llz//IbvjYtAsTf2R7uPfLfa4AoG4OA2uOVmd+lv9rVgOzYKvHYIF85IcjPYy7EtN87jp+wYAF7v1y64XEfLCQg8xQvKqlC4FVCgu0nTlQtKgIEBcAGNLe9QMOj7nEXSwLTtABaCjebHeIJYDu0DJgjofQuLpYLKG2Fp5LTYYTVI71HtLkFn1bR1i5o7BBCWY72AnUABS57MlcvLvb71bFfOPspilMWABAT46Prw+3gMsuUZVzD4C9ipK/iKdrS1M9Ds2Ga4cofeF8LNFbOPAHhY9O6eMYVoD1kiMbTShbS80kW4PEq6bJgv2WevEs4aRwgf/0tomW64i17Z1y+c8Qd1Ibnwnyo1pUQcFgdnHfXEBTTvvJu4IHGDW6B5i3hSN5HSVHyN2EKfe9HaAzCAfKFg4fKek2aVp1PJaPEpPPb94/ugQO2cWg0yPuAJCAQHz72PPIPMbkFDulQtTGnOQPLMF0hBy8EMBQTk4ihgeRrCjgkK5d7J+MJ1dWD5IwPLH0HzK4PKe2P/zuvrA/v3R4DCP2k5XBeujEc4YwpbW1zM7NTcF7cPWCsGz3Ls14qA5BWN4LaAV2pyL490ZrmrqjUQyDVjFRVToBkPDIAoi+FwyfBZ/Q0IQAzgAdTVE/QWBBXnGCAl8YtjhkgNbut3VfqyPLI+FURcBQhAD+b2kaB/p6+3BhiFFYV/me7HX3VcXwcImFxH1Z2uIENo5zvPVFT2zsEYvL1B3vTkd+TU1By0KVRqlQiBCGEplMXyIhgY8MIIPBMcdgafa4pqsg/jNwUKthDblRDfAiDMOaGKM5Gi4jvLs50WcNv5oYL21OntocWXT987cLx9ZXxBQeFVIKHpenmqngUYXGY4YZWFUBMUmA8VCNLHjLTgJ8amxpTlwxrQuAHjArQekNH8YR0IOKgLqgS+avSHdl9/PAS0Kz9MWgEKjrxw5PWD48/dR95a/3+5rmiOedC/YEHPP0OYqtyKhcHi2hPeAZ3NgwKEqNlSWoJHxRGujhcYA8MfH+EuSveRb4f/pvvoClfRtbH/+Qf74wPX7w9c/0SA+eOff+G6PrA/AhR895YWtBR03e8yE1AIgb1shQvJFvAK95G/NnbS/BX2+esVG+fFmoUYZPytwWer75iuEsbcJ4nCvIS4qXBWEGjB0wIfDQS0FFRYVtpV74hYx2mFTBrdRSX0ec1nD4ujrAcp2wCWrQM94wIFCiaBvNX0mn2UESynYANGDMekHQzhttkhmO2VGhgHW6jc5UqCAeuKGnN/o70dK9c1uHvufQTYhVqf4Lkow7L/oqaxJiDM6pyBltsG+CuBYQH+KwT2fhmuVwDEesVW2Us2vzNb+V3mWKKWalW16gXHLzf49gCXBIVf2cYBciunnYeQNxgs9/EiYhaIewSXyx1Il9KmW6itho/9C5yp9JG+BLUcLvzKPNp9dAlAMP8CjS2z3hIorgoqPwWara2BDDTv/DCju4VbCBjuo1I+aqaRdXqdfUQB/s59hOP3E43HppLTPPgUaH4EmD88fhBo3ijmpcYP6g40QdPENMA8dwd1g3lvhtdBrKzFLcrTNAWF0sgEFKiF0QYM33/Ceq1J2AEaSXOlMbg8Asx5vuK8P3r1Mgq0AE5BNcQUwNCkvASqp0DYlnsrWTJganiGC2aWQedwD7BtxhTVrQ3Hd4ilkEJeXUwO0sCHsxNPbZk0TY+htVakU4Lbw6UF9G+fwBOVPssRNE+NnH5peArDSkf/Cp/ZrRHlQsEn5idvBDmtUdsRhEuBbobsE2sBynwyWzbLrfgrBHp0MzWcXq0cpCxAVsHS7dTgQp6uV0oFMMpVrqtsr2rmle1nVhho8jtmV3q56FbyRXyDwYqt6AUBJPCcgn2l5h1bOUVB0oGU7BAArIK6XDdjnUJbfzXtVGhctDbcPyPN8x/8no4WYoiQVChOGkWGi1AvMfSG5pOGB1q7bJ5oD+c3NFMa3uTxJPyfQOYPjp9bCpApqVmBX6ld8Lx2BKpq3cLubbP5GU5unY3yz0sAVwCirYLcradAwdFLYEPImzv29QHsDCp/XOFGSrfQ/viNnS6k/c/vOl8fH7h+/8bH/45A88e//inX0cfvdh/RUqidCEym61kG32hSp783PraTlkJOUzUz7NeVmlxYFBFgfKXMbTcSg89We4gkHUhhDIjDu9MUUEB+A62bHi4gC82S9ZrWSFoqYDC0r73eOWkmQGXpKlK3WL9rgYv2qIGG6rGK3wDLmRUx6OOrde0e6q/ZWerDsWcTbMOdUylpkeQ8IwLuopRF+O850GHlo6X2Z8maAfAEc2SAOfn4I5WNlwMrZ64th18ei9iuXOnMYKWM3MKCEvrotQnpRtppFYRb0sO6TAvUXx71ymXJ14r6rhUKBWet0enDWWFAQ/CFsPbdV47tlWN9YZWl8EouikghNXUgtffsq4vTRHcElytw7GEBXGk5XPiVtF/p/nlVgLktBdIMDrqqVrmthqVQq+ETsLZMSx4xBZtxhEvcRyO2gHATleZvfT5pChxqIXzmKnoHEF+l/4z2bwDDnwWaMXRIrsgvS2GldhHmjdW0tpqXbahppUgh7/CaQjqthgYCG3RPU9zTIvCOG7g3IFxXBZvxccE/YvZRny/s3x/Yv68IKl8RZ7gy+Lx/y46oexeKczEPZ40gtwJAamwxzzsa4VohQKhRrrWACxmQfIUmuxbW8gSH0GLry21msasqUnBbarlcFWULKM33AAAzEfINCdSUq0fNIu5BoU0aGNNIS9GoDqewzveb0JifId+b9yIIWwxQoGWe1wugtRGuGbq4UugDqCmlnmV3gM48T640cIJpq/cOFi915Kqrd7utCFJHENjbSosZE3GEVygG2ypmKN40ONZ27Msr3fLo932lw44mg8Sm2DemF4aczeEFDhXfSA0rvGQBGNlMUewht6J/zDZ29h/tfkPLLvLGReveQrCvNE88QWGV+6jjTDPQnDONXALNsritLAkNKh+0ns6qtPyd55oE4fOPwrknJDTYj0DzCCC/o2me6Gtdd1DuIyuZNcDhu8IcaItV7o3ZQ98FhP8RUMBHFNB0qBW/xgLM9EkuWAWvFgx2WSuTWUp+dcxzcnStKSCtLAU0SFQg2hsUgJxRlG6ejwwI/46YgO8dVsHeEUjOWMH+J62Hfz4SFD6w/xUzjq5/YkbS9XHh+v1RoMD3R8dZzhbNIFxaCgSH1qg93dcxE8lXzMRZK9ZzcNqqmcEZU3itet5eqZ2tDjhTyK9FAW5DC1dwMKqew2oIfdGAWgAHizhIu79SyFo6ylauQCkfdbsqgA3kzq9L3uNYqYiH4I2FUKECr5Uzgla4w3pNB4U4XUsNDE4wA8r1lNwTrpWsh6/8/oOHheULkl+CBqcCJbDQPWbmoAvC5FaNM0vjgrTtOS8iFRrL3+TvVHiiiQIcLPWXOdILTgUUrDSviiesvLYIMNsLwVMr86/9krynxi5gJ1/uXGuxCtl6LHOxYYzalctwVgaaY7WReYIC3X7VVxTsspCMtN1TUisg7RpojjjDzaLI9A00c0oqYxIOi5hTWQWYQLExroEHC8FxX6AGE4vBWttnoHmAwwESCSzVvVxePoS2PNMsoyzRwABw/k3LoPMd+v4zjx8cP9gQj4HmVrA4QeKXh7XwAvBKV9HrSmXG+fEd5AegGN4kGHBTOaBiCZuLzoIWckdAYes5THMFBXcPAPi4YlrpPxEs3r9/5/TTHdNPr43rX/9g/85A8//+Hff+lS6lj6vcR1tBgTqrCGhORXXLxXu2sGqrit0uplyg9Eq30Gs1AKwU/GtlunXQCAqcurpopTRgYJ0ggVrrcLp2POvg+hcVq99mr+RfBSXSLDdi46AMl2EDl6yeZjkXXRYR1LYdwiv8wXE2eK1jsAwqW2mIIbg500SD1ZltaHfZFthoUICJATrBcwzSzBOe4yvPAUQeq12RtB3AYPkhHXt5zDK6HCbuo72DT53bb29uSfAwcgvIXSyGADsQFBbgr5iw4K+43nQpceO8tSMIvZiXgxvzXYxSZhPsbJNQY0LYGwiOAQTlPtpiKWRcYafVsMV9FJsTNgB4rnaGrwaFXLOg6XSa6n5yH7kAhlgZPRGB709JozOPGBbUDe9iB5/6nIoGlQsUyhpAC+Uz+AwyBQ6B/WQ1TJB4BARgCP3b6mW1Wj8LNP+nQKFWD+cgKSXG5Q8oV1Fr1FJwA+ws9bnymEAwrALEIILDNhpE6D66cpXxFo0+g8UzqJwrlK8L/iGrmPn30YHmrfTNQHNWIt0d1a8LqC9zGX37uwQPv4XLPe9rlkm6mCzjDkj30V7hG16Wg9wsLfUcwa/UHAocHNxhtSKTFiAAGNx3ar0mZ7EcTusCEG2VbqadWj7ClSQWY2ia/bW2pvHLYJ7KRLoBDaE9h9RP91HyxpFulzZbYj8ZqX+3Jk+3UyQJb9QhXJcX/7rWE8c5PXJNs3q2eHKxPBylLGchT7ibFooWY0PcSHqWV9V7R0A5+tVXWoDLJdCcfGKQv+7vAjV4xVUqKI20frKUdOlEMcI6KL+VIeI1QuOMsACFthTGzqkuFsWgrRbizqCzuoXkN2mwfo407mk03EgCBtQp1ZXkqGvU9RPNyp1k2afO/nVhJD9pGDTKxTqGItK8jKd0LJvm+SbdU74/AYYfWAr/AMDdUoCHlbCBjHnlhlrhS12Gdt/KAC9bqIK34jZSV5HsOhkNk+a5xhSu1MJ8p8vIIxaQwv1KV9H1O+MEH2EN+N74+N//RED5nw98/O9/sK+Nj3/9E1NSf4el4NTynI6M9GEv0YitP2jC+9sibX9nOgczLLc1TksB4eZ4rZD26/XK1c4LrxdjCq+0HtpqCCsCwIqA9HApLQapkZYFlRMKCAZ/xUpYqYmXpbDSBx15LuNiqVyPvvL70Ga4Vqxat7V622ZLf/TmjJcMiCIsBGrem5q/c7ZMzPMvIY/4EMzCqvsAF9O1UIDFrBoKi52V3k6uswSjhBi6p8pPhLi3rOeiZwTWX6h57P7qYHFtuZW8aDXhwTvQ/IqFlHu3mxNXx89cpRGPBAa3xAdaCoackhquI/uVrqJc5LZeyAA04C9OXW2lY6dsr/U0CYCbIIKYfuppKeyM3dBKgIelGEdbCtTeW7inlu/A3r/Qm+N1oJlrGS66lPavAo4rpcvev9CuorQaMqjSaxLoqkJZCA4GlUlL0EvdTj/ApGsSnEL/2Pwu0DO5kdaBCuEn99BJe7oWmp20Mz9Nc/6dbiw85PPN44eB5rgmMMSkBge3eWmLITXDXKwD0fLKUsj4ASq4jJxOGmd1KdVin2qAtCgGKIj7aDv8Y1dMwbnW4OPK2Ue5O2oFmoO+P66chsrfG/u3fFBnt8AvNw4AXxtc8BQ1ddA9Y/nbQP890o2Tbp6KLayyFGKBWwr/16toBALPBSK+sn3Thxzuo1VaZOXnGXilO6m0ZyuNP1atpqvKCQooTZVuJmrQXi4jj3jC3pnHLhcEPz+/EiBjI1GxoJBTJH0PF5ClGGDg2Kn1K82p3eYgj2oG75nnzK+U6wzUotOXxre8hJ1qYwavgVY08/YUFI1g20oD19RQzsfK5uTTfDbGCGfedX6dMfoFOWU5Y/45WyMawBl4VgshZx15BpXdMv6Q10DKq2SHmvWcPBLtwS/siRsJyVsVYO6XM6ag0073oL0GbftLZgy1tdFTVtUtRItC7x3TWDWoXG4jtJVw0m5BZQGFolndK6HMuIS4f8oT8mAhmKRzodezB+0p0Ky7J/gJRuPP5rPHWW3tz44fB5oBtRQ8NYsMNm/OCUCZ/3QFRKU4wuTMXbg2ChR8yz2aalvAoaaBJah8NCjs3/kxnN/hDtqXxhS479GF/a/f2Ntx/Su3ufgnA83Xxv7XlQvXNq5/Mr90H6XeFM1LoZt7FFmCQdSVkYdyJpS3IUAlrsJ6CI2aFsDrtTJAGqZXgEJq/iuvE5Sc9150JaXvf22h2QEIgImlQG3ZuG//4iK27Cd5V2z2ln2yYlsFbI8guqeWaaxs76wZwBABzBDKIeDNUfEDpNAPAOWMIdJW8b6BLpDVgAAkeMQ0VFsxI993ThtN4cSBGZ5ATwsDJAQ/FQBmf4rA4D5Bw1LwaIuafsrflt/jNm83UsYU1mKAmoNe0EeBITV4GLJ/DPsV/LO4vfbLUlFAbqOCiC9Y9NVO5SFoUQ5utT29h3QdrlZaEhx2KkLs3LiWQPOmpdBuohL2u62CAQqMM/hr0mhRIC0Q5wym2GO578mKZpl+qkCQekjKkWkpFBgwRsR0jth9QMTUtBQOwQxrmQRJP9Ic1zjowN119PSse87oRIHXvH9nI0Bo3zh+AApcp0BroCYH9j5H7uUyWh4amyECblYl8x5dQAeQNwFCabyOZ+ux2pAqaR+tyXOxWWxfsbEvx/4nA86/KewvXP/K2Uf/+gfX7ysDzTn76H/nzCPOPkr3UYOCl9/XqD1TITBaB33O3RFC5Ml4BxBAALqPcq1Duo/8tYCyFDLo/Io/3ico+CsDDQSC12qrocABbRksAlsHpH2tdBWvvN5YO8EgacvSzZMC1BJwzD29MfF5R9seFoQj3BMJAJZWhgEFADHh56ABEvzmveA4WhG5V20ARKrJO9+5POcpWbw71r7t5FSWPzXtmpOZCLOb5hlHuO+LA+wX6emu8Qgwb7o2X56glMHn7VgfAR6bAWf3ClWUVihWgpegRllqHWhOMHihNuzbrwQPupEMub123s/u5kd5iiesOZbaOAgGVIScPZPqDUEh3UdtMawCAZQbqdcsMDBNqyJmHbVryV32Qxog0ekwLIyYRgtgWAxc9lQBZFoIwNjAbmyTfSqeCgp5bne2aCMqnCHP4cgHD+koD74FCv1nw3uSyVTEQmg/OH4eaIbyrLe7CDzLXwJDWQNgAHmCQsUTBABuoLBjKOOSQXyhAMXzD0eguQLLGSwefztAQ2l7BJ8zllCBZrZGDNydMzli2+i46Tf7D6NjUxyVYoodQ3HxQyqWzLvaH0pXC5sFKUTjfQ1BMbJ3WyuOBAHPIGlqv3wxj1IVN+Cxf1O4g2JGS/R/0PZa9fEYS4EW5Yhne4vzFMyZjr+RUyJDKGceluCeDUWdvnjdkL+FxjKxvbLtyYvb+YVqBvOTtVKTN4I4UrZxcMNrVwx440TC1OhLxqJrRHMs7IQeuu1Wjw3kV9gMzds1FZvvqzwhloKXic5JB3QdlQJflgX/2mVU+16J9dEyLZUXAYeYuiugUO4kkxdmoDnBYIAC5owkFwEegN7gMdcZaFA6F52dQeWs4O03BX9eo84oMFAN3m+CfwrVYrbq8+RZWgzHOyx5uhlrXj8K/geaJS+puPkMID5L5zjSfOP4fqDZ21JgwSkQXjkY41OcO1cv79z0zmHGj+GwdLTbBAgSFLiJmBcNDRDsJKJ87iOzr3Qh0VLYjut3ziBKF1DQMshcloLj+t+/4/c/H7j+94Xr2rj+RUshg9SOAoWyFACZGZJCFxRM1kwAVL1rzUW2H0D3Ufrs6eZ5XaGpv6xiCvbrFZr/Ky0IM+zXK8DktXIOcFzHhmqr3UwvBqStV0aXprhKI8UOS8F3Wwq2XvmujHPsjWu9Un7GHPKwFKjV5k6dK3V7S3cFwsIwCsoEthlURgoMFG2leyK63/Md1GIjTQSbGZjcFQPZKbwqLuiEGqvgcgWpncIOoW2ufIiuon0IGA9vp5GVM/hsaRHstBBsO3ztAFJOWMipq+Tt9kl7Kwt5sE3pQoIh+x9pDQQfxoec8ndaD+uFchfRx7tz5tK10F90S6Ugt1mKeAyyX9MqMAgoCAAQhVxcOvBD4O8XdEYSPNYulPXgrxjHsk6hrQwCy6vfsedMJg0unzvoglai9BmAsg5CjiSNIE0Zk6KqhW1bI1Ts3sYTIM+dNPyAdgBAvB8FXOWClHKW3p3Pu+b3jeMHlsJV16LElAa09OwJBHQheYOCrmQebiNHBpgBXAzCoe897GEeZw9TXTT6sBg28EFtf8/g8wf3NvKMMaSbiVNSP/Kaz7sM5pxHQ5fJAuArPqJjsPR1tzVQVkENfr3nrZ0tqzUJ2xHxipznTV9VaLnpkqGqS5cGr3nmBBFaDQaEJt/5DctCYw4phn2FRHQAi4HktSIwjAwq7wSgwvbU8n3BmQ47pzFmzAhWbpJQLlKbRQMmlXdOSaU4T+iNMlHp82x3RwoyR+wpFfdtMR7F+EI3gW+IpZA0NHuSBqDmh2cRQNzwzeBzjgHyQMpMSxSMMZA0oGMN+i5A1Q4daA0MlMWr/3p1s2egGWIV6J9VHTdjFRn5ienD5PCekkpViFNSwSmpqe2zUHQjTashenNMSfUH60FpYgF0Hp/Qxj1UULlBv4XnEJpDkDogwF9/b2MFCRAnMOBMj0k775ekl/JpOs1Dk7vP92UdOhCdI0XK+V1k+EFMYYJCuwkEEFIgDCCA7LhfvSGjILV9K3DwshSMgebsHGPn5rduPbcS8I/MZzvwe8fzv3fHGn5fIdQzzuAfG/5Pzj765+rfv9NtlM/uD8f+JwVZ7llDgWRAbEeBFIqcN5+L11IOROod7dQfR+cZuRo6tV3OKnp5+OO5u6ZZBjgtdldNS8H3q59rZ3Folxl7gBnwqy0FcBpr7MoXwesXZ5WkRvoS8IkgSZj7a5Wq5alZbixYfbcgdsiNj5xEwLc3VmtgqJ1Rk4HdgO0NNnyfFQRYjs/QWil0d/p5zHaUly48twYM0HVk4PctAugSyBZZ0cEIelgV0h6ZLoCf2Gbwi55Rx9oULB5f2ctAL1Jx2EegOUA/37HTfUStT4YveYkY7mkh0FLw2k47aTUjKfdJIngY8vvNAD/ik+pNAGkqBAFWGUgGv50AQC2FmoyeYCDWw06TZAjvERjWOEPSZBYSGDyWGUltKQjNAU5zhQO9i27wLIU+ZUeBgXoc8lyzicgHp6VQnTIBYQht0kjXZ5V2yuVkNsqLM72ClDpaos6ewfR0v3ooW71mAxwB38UDAD+akvoBQKyE4TveMOud0EODzh1KnDuhID56M6Aa6Gmo3lNMNY6QmpTOCrC0FLi5GA5Q8A3g95X0FPjbCwD2h8xIElDY/1xhPfyTgPKx4f/QUsiiw0uT6xk9XlNLY2BFJxh71WMIQSwlBuu39XRPT9eO59xzXxYW0LKoW84+cn7r9/KajeQp5P2K9QwoUEABBummtPwmABIMuKjNk+nshaFdWgmO1DIXcuWo5bbYwSXl60WfI76wwK1/yayxjUKCTb0IdSYo8L4znRGoEQLfkxYMGv5oZ2CcALBzAO/WLCvzBLfcAwlAKihWmmS1TQIFEgyC5u3y3Blv2jnBYANrR7NzJpJnWit/N2TwWtU3mxS1QC33QxrfWCBQCCj4iiIvxg8SKLjiPNg1eVaC2uUqsrYYejYFQQEpsNOaJcjmWoIKPpcFQEGvFkW47sYsJaR7SKwCYFoWnE9bH9bJfBzoyQACAHM6+8M9yhZJU27r4g0BBBXw7wDBj2s96yHp6Fm4AQJm+cpKoORPa6hYuMYXn+WA+t7x40Az0AWnrsDdSMIaaAuhvMHZA4+WQvnxKDQhFgMEFQUcaHLnNFWrIDMHpWfwOdw/BBwGkMEgcvl56XJC/ka6nYShcpYJG9eiUZIn0myDN390j5RV0Ps7oSVRan+NtmhwjIfknL6O3Ao6CmX9nLWwG51V93LT5JyzjhQytWq59j5KzXWFOyiqmuDIqmW9VnJyONY83UfdfYZWIJaHqh0rQz2LRx6xmtPNacz0p4f2PqEBSJcStfoEiVox7dyyIS1XcAylQKXmLaxY/bHRFgSDvDv3awLSUc8yZF0L/GVccK+jtBQB9mV3TfW9CqVZHNB64h/3kqLgDwsigZuAoLQzqJyWWgNGl9rNCjS4TqE/ptRWA39zN1sv62GuJ2iBHoXrGIF1Ogam0SCgn1DVoDJ8nn3cQwlI9mmdT8FP4T9+U9j6BIAbMJBR9J7QgId7HDeYh/AN2eNMrHVpS4jKitxHAgTBorJJpeabx/cthesMNKsB2fsWvtJS4FdWw1qIrbYWzeSyBrwQmVP74Ijpe9mR7V7Kil+ofUvwIZbCRwT18HtH2t87/q4N/1d8+OS0FPbltSZh/7Pj79piKTj8d7x3X17mYMhBClWElmoIC8IoAMSa2vp7jnpLIdzBX8uPWXtYBh8I+pXntWFXWgB0I70sXURWriJPS8HNYP+V914SfP6V+yvtiF0wLtDTcsKFVFYMp+2tBW5zsXzHBmSwErAw+tdDeyuNNAduBJpFC3YftBaDQeOCuoRc1BfZMkUIMl3DgOJMCjlOYY09kTLhWjKwKG2z3ouDDjXIepZLG7IVvEyB4nk2D75d6T7aFoHm2A8paFzrUC5RBYQavxxhTkZJwR+gtn5ZTC1dgP3i2gULl1JZFMB+tfUQW6qgJh34aiDYJyCkotCAcFgK4kYaoIAW7DgsBLr8dloRESTmWocGj9qdlFaD5jcsiewTWZzG2EBrz7TkMJS8Ev7V/ibAgHmPY/YQ9N+6p8ftXg2YmV544fZHt1G6ijblp7iPgIzHOdpS+CYu/LmlALUU2l30HEvYNfhv1kIhNFIQoXytjx23DW1dMJ2ntdBWA/c9qg/vvLEUaguLOqMBiqalnkuDp6vEUTOQ0Pw0rAHRFGt1omdLJrDcLYV8flgKmebaYEA4MoqZQixTyXUgXEYXmgiEQMgZFDFdMxt4cVbF7CPLLjJPS8DpA009kcxolqt5mT6nbfrO9Q3hOopqe7XfSSutOnnL0UBbo0+qUzS3+kj9uGU9g0emAby1FHoGdfwwIzD4sHKYP12BbKuyeFfeWyiL5/Yn+ZS3gsFBLRRPubqZ1gGtAk4W8KKjrQLeTwCNV7TFQG2fsS1DggfvqaXggALEBIa2FEK7P6wH0eo16HwGkcPlZGB0fAAA5u8zqBzjVGkJ/GdQmbKk+sIz6G/ND2c/fQEKftLOaypDko58/e7Z5ju+f/IiXUlKgzfn9P1vIgJ+us3FqFprwr1/pVgF2BFrIM0xwIEjgNYBfbE1S4RAQAHJ2UeXlbC29N3yM4e2HfhISyEDytBZRFzl/JHB5B2B5LAI0jK4wjrwC/APlKUwXEkp9T0FDYWUSePo+o1YnOT5fWmXFvRWvgzlljAPaWor3SpcD7IMdlnusY/8kAVy6/CV1yt9zKumrjrjB78W+GHfkBNWAo2zkvrbCwliOevIMmIZfZii2gmMGeiFY6VAe/kqrH8lmLDaHU9ILc8QAh2i+WVjWv4bpWm4KAEEgNtf1Cpn6SaKVofFdiTOQDMFDBOGZcS+KxZdmMIFXoJjU9tPXnWgAs22IiC+0zq2jZgFlbupxufMktcrpiDWSo20hsPstFpHwU90uiH2N6KlIHEFrLAm1kpLoFa355mTDzCthLIQTkvBgg+C/9u1U8CQrqAJGOVchrqFespqpN9lCSTPZvygXU8NEp2uLYSauLBTMO5sNCp4SJmS4KFgUOm8+x+UQYfANr/Tbufz+qTlufnPBBnkvlo55MPat+m0FLI6Wddd7/Dnsrw5/mDxWrKrCys4ASF2Qud10RQMCH+MIeSAMPryq5MQAWX6AkVjt8saDDZgl2cA2mG5TgEfO9xLHzn7aHvsd/Q7aPs3gYJuot2g8BH5+QeAj2zsD7SkIY7BObUd3C0hxE+rsb1viY9rIkgpYVzrQIHMMbjTKkigCGGSL+O8ywo6o3YkjC2V6XB+oT8C4LXC3FLjDLe51cZ5RjUfOwalJXMSnDhLKOcURZvkPkcedXDfeDn9xEiBF525LfflF5MmtsCIKASbwxJp27UUaQgOvYOqAAM60NwupFQyDOCsqOgb0gjUGnyOXE/DFqABG4DKeRI9YJFB5VYIEjf7+z6Oil+p4On3pHBTBYJNlTIZFsI+trGw+BrbjZbWQLqIdm7HTjDgBocdR+gv+sU+RwIGOuOIs7TSiiDAx9Cg60gsgaHhf0LbHcCm4AdnGonLqPc2ImhMUADbUAQnqG2fcYQCCIfGEwoYCCbfAYR3tM/u1dh4AAQBJxX6zskP5XK3cI8jz3QlofP5yfGH7qNsOLhoxLvAoc5JK1XI+dur8dtiiOue89udwviCBpoJKAUs1bEuweYNXe1cK5Qz+DzdR8iBKu+ofJvBxuwDNnphQLsmuq0aGDjE626p6UC5dzKoaWAQON1LDKrXc8bMwdk00S0xmOiFh63QGN36Xb5iKgxWut5y27rtGjktgWmQtiVeJEBwjUEscwpArH2vwHlaUnbeJw+lqk2+IX9ZicTkExmNoud3J9R8Po4oaU9vV1EAsY++6IgF3UwKApF+18C1qr+nRQCIwJdyMW4QW53LSM+mByDReAwBwYHsUkoq6tHFIdh9oXa1bReSWHyGiLkULRWFmlRwuIcIBLn/UVsKAgzeBaF1NayF+uvYQ81Aw13wlwsJ8rtAATdaCf/jq2glN2qWmAr6TjcsAeVpAeSiodMUe3nyzFdgkPwzyJLOJb97Ht4ykPKjRGe4g/S6XESsA4SH/lOg8LrUfZRMn2+LBWtHUBlXWQgrYW55pJtgkIFGR68slL1ISjjXgjWrdQoV/E33ES6PoPP2+Bznb7EW6D7iGoR/GHxO99LvHVbDzuDyBfiHxZ8jXEkJStrxFFMcNjzuYbnZ/6L81mA3fo7TPS2ABL6cwcKAs/3KMXmlFFqWUxL1bLlHTmroy+D7BfMMKgORPxJjXoDZla4ly8VvOfef0yctLYO1Y+At0b5SG9f95WKqsiF3Q0JrkyIICoekJVMGRqAZ7dO3EDBLLAoGkyk8y541EUopsWkFxHtybhI1VmQ7ZZmERQu8oryO8q0vlEamWlzNkLMAiwUP4X0RnJJXR9ATAxAISITJPlmtSuZnOJ2r2tnv+SU2WgWWLiTItuf6dUC6ila5kVZzrbqPvGmj3QoE0MK92pv93r9buKcVcFgDoFsoBf90KZGGsgYAu08xBdMl41TcMvszNe+a0AK0AnoKav2DnPE92pDJh6BmDOBM6Ml46j7am2fvLxDnZn68N3RwxbIfAMO3QUGDa6qh9bz700qYgWVLQNCP53gONi09O+RmMbyhleYlwWr+RYN6Ww4u1sHu+zqQm7kmQ3nRkIHjs+89W8aFdj+o5co/jR4Eii1tzHSO0t5LuwTaSknpzn1yaqdPGPzK6Z7L6MDvdmLbUKMelpzXIFHNnhpUbd+RQFa7qGp1HOGDt7YiyEN0tNU3mm/8ZuWea77T9k0ripq+WbebZzuAzjzvdJB03TEo112XIvONOpSlwHcpH/OJBHcgeKrlqzcAMOs1+7L6s9xH/VjzApV0AYRhJbRVoDRaEASEM4BsCbhqKcRBF2TSJIZA8I1i6qywSavFbA+07MU6Ny0rTItB0jSAotLXdbGIH3LC0NYAeRnVd/1sOys/B4MHiT8EvsmPg9tGui6uElXLr0AzlAYySwELLYeq+5HPd48/AAVtNGqaOsuog84942jXAGphlJ3BqamO0IIB1GKStALG4rUtf/TLEhRqhhHaVZRbVuyd54/exmJvx/7t2B+JuBnD2B9xzbNvGz5gIrHI8JulAEwLIc7ddi48M2cfsTdVGiZnUmbx5fyQxYb4/pFWQWpb+eGczY/vwHL3zJXz7qklI/ZVSiHflkwGllfUyCzcTVgJNM7+X9UGiU9dJeROoDLgaisUAFxR0HoxK85vuc1WnCPxDc02ev8KlopSWmlHu8NmR47XRgeYnr3rG9k2b9uLSsmboibjlOwpoTUFhhezRdl27n4bO9dGAHmXVbDKMqj4QW7NHlNOX8lv8h1we0GDy20pGHqvjgCGWOGdYAOCl1oM3ZPtPuI9mVUkfEdLoQBHXUTlRjppOS6zbcdU0xFUFrp/8hvHb+2js98eQSJPLoQCuJYWNyHtHWvkO7zQLKyCSGMdvxoWA11J1gDChXwsxlnWL45vgwLcoXhXGp83C+i0U25hZp5ztKmFwodW34Fm1IBgpz3TfALD+ZvxgpxmWrueJij45fmpTcYXEgAuD2DYSIHqoVXnTqzlvhJmUt4Ycr2LC4ogssYISTDhAlr9VrVRaR6aPhhIRZu/Fu1QfnO6CxzxUR76ny16ZfkC1gX3FTNyUqr5lVtWlEWxwy61mMLqy4G9YybSBix3Uo3gc7uiOAV0LNpTWtZR9E08g4Jq9KrhNx/eaZb94eCur9VHpXEoLXuvLIvumu4jozrZZfK0jjxhi/wsJativdAHGaKHQCUfvI4c7JD3A9WXDCrD8sNL3NiQ/T0shI4PbBOgQNwz5KaLGVzmN5qjwfQraymYK9AsGn794Uar9vYH2lQlsg1E+BdIoGkEBG2zmysOd8H/jvbVHx5+47jH06ANNRDqaqwsKt8GggYOr/t7tyUwjXkGnenejLeOyRQ/PH5sKfRwegAGb9kGx52GDiZWA+Tz3Th8VhpZOmOu4uuBV64gR/oV724h36joPBs50JYR+36+FocoA6q10lV6q1hShFf1RbC4SeoNcNWpwdsnyg18IOWKBq+X0HddU8izfJZoEd+ujgS+d1oUUeeF3fe3x/1QRQMMJPhcbrj073cZvAY4xXHwQwt+vcdre2gpBYUOsHoFdiF0gg+qfX3wJn9VUNmLaw8a0+kQbmBxz/T1vuzzBJN2GEof9zzfg94N4sf1Tf548kQ9b3U265Yifbp0KNyt0swAc59Ng8oy08gKSCiYM8hcFkMUvHvshHZei2A/e0niDU1sAJmNYlNGQK5Fvky695CjrAAmDZ2uZMlNcnd+Ncb0rK8eNOVPAfnxapd8vW7ww0tDrnnQ4zvY/M18rer4PxZoLkVWu9z7HGNAYwrJXmIhrDLFWpg/AUJ3DNNAzEMHSoiloJTFZ/sKgbfVdcRdUC9v1xF/y59/JFjQlXRZzyOvucFZBqAAgYziuLuM9JofTI/vMCTz11jmPa27I/y8+dOSKYAKYsZ4pZBErBMwzwVYPS/d+PUt9tNCapfsw7ymG8K990LiF9+o4OVXrpwxDt9hSaQM4fqH8Gzxw5ymSnLhaltSzVsKGpzdVACBmPqqLWv5Hs2Jwu3sA76Z86J6gZaDX3eLbTfi2dppNfslnlpCs/la98kEXJOA7M+VPJtytq6twl6ycTABmJlH227LIHtNNV31be6dgeOdriEYsO0VG9uJpeD2amAot1G4kcLSeyXf5aZKjCsA8d3uIx5AR+Acxq0SgFrssAIyTbWhAkKnm7OF0IfSTjfPAAEBbsoUUDE4BL2m9+f8Tsmuz9+sAD0PWgv/ch8xWoymKSj014qtJ1fq96hhHXCuItl/HhTiNXe6+pApLN+lU0C/dbTmcTb06FlIK8uMjTfA0qaWaN2DjuPPoFPamqHFZQAKij4fVbj9rjEuagu1QpEAZRYWzQEn+iszZps6tXMns7P8yYC7GaysKC46o7bCymfM4KFRJocTCQsatQXIkqfF0Cmr/GL5MKE4geqgBVEuM77frO6N91KDysz7EQWVs+xxbSb5ZR3DYjAUAkdDD75XAKv+NYRCMGVky0aTZrXpD450+iAxItMRIBLgakrqKZCLRuFtYnWsCtjTeuj9jmgdEBjQz2OWra0F7TGp8KCx8qN3Bq3HAubhT0R0sw9ZlBMBjvTRdcPb3zID5IpJa15QmdT5ThCwFvZ63VkIMPBGv+wEjRp+kKFY/GnyzEGDvuN7xw9iCqzeOax7RkkI8rNTlUHnMQSD5lqtpn9e11OgH79T099b/9p6KEtiRwyhzvkMP6YyVw62KwnSOTX+IQDGTqhbNwdD3OeAp6YoYBP7/lvdAwXKSsuFgiQ1Us+FUrC2Irb1pJdtGQe4Upt/OfBhOb/9CqfBTutlbTDOHBZFbk3B6a+GcDMtg+4907U+JB9yJgy4UI8rZtNKENZgew6h30MIJT2rsU0Q2foMR3zLYQaVXcrZwU9GfnC869ZjkZ7AUL0qtrM1Bwxll38EBzh1jbAQNJ1LrQ0RmGXr0G1kPZ3UYflRnIX+dCb3o3olX+R9W4Dl513tBX7AyIzWABej5be0SQMBQdxHsOyOKN8uN9ZsRQWF+H0X+nX24/foEkc1WqU//s7uOntIBXxeUKG6Pbu1FujOGWVqmgrryL7L2e4dcTKUhZK86ghhECZ+A9LeJRvakkxLwa0CzfElOxQ9xoC2//eP74PCyFpEuDToFAfUakxoZ0oFlwkSN86qUZRkn38TLBwdoUcuA6d/jsIf7RoqQGl3Uc/7teqU+WGL01fNmnUtmi1mJ2n6+s06QOoD+gVtaDsus1bKNXFOgdrepOTECLoDCytWNbuBH2exFwPNBrvaQbOunAG0M33NhhABVp0wmS+VT5hoqgY2YQqa21P5LNtVWQVezzSx+6Mj7ewDrrzWRlYtV/PR/E4Jc6gvZTFonlEGF0VNvSKDjcFh75N21Nnduq1ITEsAZui5W01zC3BYEhPgNhOxYoIrk1fGGSSonCuZ+74BdB/x3c58SAtBr0BWfIwJAqfFM68FGB4FvPSPjsMz3aMAmW/TWXBlD45BqUKGWZyA4CO5n4/lM0MR0RlC9WzHDfhgxRO86Rpo3s64AvMMxXN7K6C6onnw7jeOH1gKGirswRN+TzHfB9qz8/i3MbhGwaVaU155Jw2hCef7U/CXEO+JSbQkdJHz+O2SDuEbVXZyUDNsGo+aXTMbqgYJma2MVAoRNsubqlcd7U7rMXP4QjX4DAOnyiPbxnLm1sqPyGPnx4C2Ye10jSTNrp07qLKxwlow+sezIB0km77kbqCpCpBGS8E1nX2PYbuZCRDC8O7yOr5A/ck22y7TeUkFl0elg0wFf2WW/1oL9/rzI40UW8+i55xt6Mi+PixvxkKU1kCXf0ZXTt9zWZnsksYKLICxolm3tTj+Ol/WxY4aT144AWSW/bzSETUFOuXFedfuSfDc6pp7u44IEjRCz/6LS2+x1RJ9AEEl8/FInqOzd8ktpm3B76WhIq6BsBSgloKXwC95B4lLMCAv/PnT4weWwoSD2V/0Yzw0pjRwTx/M3+86T7LhgGPgVIU4LQDZ0QLXcBvlXnFv/jRYc23vb/xsG4ABvh8tVNQG6Po9gYQI8RTqMS00EuaEngYCtPDn+9dBKy3ae5jCRSZmfsvQu8fm9b4c5ju/nWwZP45AM+e+hxfBsfDCuuL7uXZt1EZqjEfsCNBuiw3vArASJO5yC+XDJlgYYPaU8IujAEFbOFtZXUrFQ92Hdw6d4ouCmoH/FtgEBhca3v7Ft6eBO2DkrEhReFshmWcVtlrajg7E6vOwDELTD1jvqag9JZWB5nAfbYT7SAGgrQKlKRD0thXaciyrtqujhWvXwbp7P1UCnkYR5C3n9cNxU/+f3tHnGDvay0eyUzaBAvocu21Ft6so+9IVKJjOBwCUtbBZLoICanvwi0FlWgujNqzBnx/fBgVqLB3QQwmlFvhMTE35rhW8Lawf97zzHf3BRtXBycYWNJ8dMF1A476zQ60Ea1sHs4FdyjS1lVlbHSxdqxYizXydLy2Au46kwsfk2SNWcYyjGhNqkVTFCS5xzQ/ocPbYStTd2ThjlXN3QPaHuEFkEFQ7lHYo2mXJfpPSziH+POQf4NalxejXLjOrG2UG+kRXrGWtzdPx6F0w+dHINbhv6eS6m+tBwCuPTW7xMqUkWHsLIKMCzVWuYQGg0s7gc9N4TZjRaaz9HsOYOppln3U6rYVj7JgmNhb1JnQZdxqtdfyU2j4fj9bCfXzdW/2Z1vKnaa40Ff6UQ5IuZJQoByNdxxYwZFifa9JJySXlzz4Xn5zC4IfHD0ChtQOrhuhmWikaXOjxe1cDWulAkm91weFnA8pcgly3C4g7Arq4hhYuD/fItTeubdiX4dry5xaWQvriLt/1wbayFJI1dpYYmDPe7sNb73QKT0HlKTjLIkAELGtqKZoea/A6WMg1vacwiDZXXW7eJVvEpnVRAVsOS21j7Yhi29oxXdF3xhkcdsVWy2YWMQVHfozHY/8ezymbaeacFlVYNO3C6D+M38BXwp8CCTehXV1wGgwy3GlaNxKdvWSNK/QdACEA5XW3P3846x8gCojdnxU/sHvs+3p3wWhgtoV0bWyXQp1nrimf7T1dQH7EFCLfXqewxnbZB3cxnmDad0jBpe3lVU5OwX4S6qO3tbsfhDnktp4/zfTh/iyGuI+AXosiz53p6+oAhFPQl+WnNNDNHYmbfzzXB6n7iO4gdS2NmfAoHhe+ORrnj49vg8Le80PqbQs4BBJQqIcp6KNiq0dNpoAMnn7GBG0NapJxcG1kYMWnO6ndS8HEvdCDFkX/3rsXguxb/mdsQSHQ6tSaBdHaRjsh3Soq+HWwpLwWBjyFKGkNGqT4eOehN6SMsy5qKvo+9nwJl1Lvkqq0tWLBW7ieNvh9ZW7SV/3MtrN20dz/pjBpgadt3PUeNzQA8R1F6OQv7T/v99YMJ/fWzAVVzzqMsisbn3V1rY8f98UFVXm8E3MEgwn7MWNoAu2db2ZMgbOJ7jSuUWCsQcCA8QVK/Ao0i9Ug/UAliMz2uYPHx/O3lJlNM/OkcVYwTPL67D2QscFXWI4eQxmLZxD6nlvzfDPFXT7NXUxTrhVI6KNUpmc5ByAo1dm33U74/xP3touSo7qyYAivvvf9H3dOpdH8UIQUOHNVrep99oyrV9uJMcYgFPoC+p1n2uPyx8dfmY/UXGJIzpgWNpnbapJZ2KjdtkhG3pI5AxYQEgokqhE300b9imb88sILFEraLxCoBVNHM9i5sLPqcueecC6MVjBgcA7wY05MM6ds6hpTUgKw71FaCODSwhHJLBhqqrK5VFFLfgjYFonV8uGDo1LqrQ++qXxO1gMdqCgjLydBM1FwwiE6Wgub+wLsMTF1HOXO2h7SJCT1yQG0B6M8mdeGMZkPed7Tp0+6b3B+K55pOc/3swIIBwQN2Difz+OZx7UPfjddMaMYaT/Efvg0YF04mBRj0jH9qOUq3nXGSjs1BGfmo0E8zUbxfGe31/z+7D9A0bqzsFPUPpm4STFPS1XYPRLm+zwpgkUciVOh1DssLYAW0MRz+jUBY8yfQCbxvMtR/YFOzFREHqkpk/koz0Tp4yn/JqeJbkK1nfdYGK0djfJ30PBjULhzFnAZK6c+ZmMk5N3VTIjBRNul2/T0tKEJAJim33cmo4UqrZzEtXTsK8t89NqJ1y6m/9qJW2mZBQ4ZuHPZb+DO1QBzozSG3twNBgpsz320azYh+RIeag1lVUzHDppgCAo7gF4MjkS6xZsC6AXpInALEKJU9NX9HCTwLNAg1btmMBIPTrpIklJGTybs1U8399Lmed3Vp+tOLuVNnwN2e70V7guEzbtwDQ50sL+bkzxtW/r81ZeIqvLx9ymNtbPr57PO7KyBck7flXtKgw4KDg7vSxGM70OL/53sV9dVhdHDW+/UXA8EoEXteo0idxgLEGrH9AEFpV9sz8V5CosO5ycQfAaFt7ZTW0zlMZw+n8W8YV3tWW2MzkFBkW7KB3AJ+ergIGB8Ap8ItLP2eG8f2c/0PM2jkHzmxrDthpUf0qLMPE+LyAkKTzBoJsMxruVwRKSzc6L1DZmIh/T810DhDI173ONCBrpGN8KYbCzz0Yo9S1jJ+c35mUbw2Jh4XWkArWK1+ehMm84IK/fBjOLsbGcWnZQ21nHS5kEoWVE67UwOMEQwu1y9s6SZYJy7S2XRkUtQvh58OPv9MaZnV7hzQHd9NXZZXEc46Sbt3+dWqhpJoxZ3P/6uP73/wk0d5/Em1QNHW+hDJdw9TVP1YxqlmdmHtERM+wkY8nz31GkS61vCTAmkZbUNMPc6lniMfZ9GlKS9gOjBuKjN9VBfRnNQa5NPTmXEWVanDS0M03+r1ds9ac1n+4ipzfcPcT0aUwTnDYoBhKMWIeDIucfn4xkX/omwP9zPzLFKNi/WeLQP6+feIeMwj9srD1pXyaKHx/Pz8nwUBPZtqmbs/7Ovhpa+Q158uP798WNQeO3JemKQ5BBZ4YWJG7VPc12XRHrup4AEtGNaJrhM7GgFZfMvKfRmyPxrS3tI/NqBvBOvHaUpUEO4M/GLmsIrgVde2LrGwo3Ei6vl3MhaFTuAO+ijICNtF4jTLuseKJPVDMlqk3W0T9q9Ct10IggkbudVMt9yQtm16jpYFy6EqUUy+3f95YSYB+Q/nEEWQKslPap0JlElqNUFWgjbzHFnS2brytr2k5PcUpVJ1K52iJ4EiMVZlwsN0q0VpMx4p6awSU3ATNB6s5WngHI0Ddj9w/YqO3ie+YbRTXnv+Urf20bhmj16CBk9Ez5cNaIkN0uDj2YWHDvDXJL0V0JhvX/3xjbdiehNcThTuVY3vXjfw0rPENPT0exgUt/4WPwcDkk94o2RSjsQHvqRXoyY8kJPwAwujhWo6DeQ3twkNKsqzxjyfNDYst+axJ5p98K+gdfLHMsjjDnKpTDeGHzdbH9jwqwaoo2pjtKSz9SnPISNo42C3z+w75XPpT4pRpFYpI/TZ9Q0Y53i4PWn46/MR08wmHNJ3aUvaFtONQDx7CFdHsDAa/3bhwqe6KgjS9tZy2KPP2ExksimgKM2j9/0d+xcpcpldudt4FxmINC+BvC30mvAWvN2fw2LyU7hfIQZ8vUv+qrBQEtS6FrMfRh+dN51MHkHhDiey4DzEQMDfASH4CjuNawcFCJLbTefgn7PJIrsxkobHTOo4shWfNMZvJuS1K6isAEE3Wwt4yH5O0CoA8W8O+npLFXZj+dPIMKZ1uWyjk3HME1BBDJtE6SIEHHhwQSo+S2+Yx2orvtctNCcxOCchUMyeABfWNp5r+5m12Lqk/5ua++DqTUy2ONpZ+CQ6EfiT9MM8jz3dTaAANlCZe0jbu+Po1ZsyxlnfiO9TpVtqnv8UJ9PydX3BigQ7ZpPDaKTHE0SZkIKr5DVF2jt4KnXFcgVHRd4L+wcD64mIaLvDw17+T85/oVP4V2Jv9xdmwuuKVQaPzTzXVMwE8SpKWQz/0xUqCnPL95/8Xn5ECrUNPvvtbVLZ2kKN2qNzRsTbroZGloMmWi/DBQMy6AlpAOHKdPBcovQkdAqoYchZETF6jobo1zU8vQdislTU5B5Wmli/Is7xPtSNUeEIZ/Taqf+1zt18cE2UhwAIZ8DGKUUxfi5xSQufpdsT8uZ5JzbrEdGunEy8wEHrsj5xqzjLT9wahQ4ysTxsa4BzHl1vpH+w8qt8o4w2yZj0xSAt20hK3F1+9VfCUmLBCbqGX1CzBin1Nd9VACgrTSrt9YwBiMeNzE82xBkNKCGIvOEDoM1o/CpzltiPyyGzVadJZaHETf9Z2u5QYIIrfoLIGK3L6sXH4zkxnDizM6Nc7bXZNnp9ST5lyCYR1oO9x0QiGmBthjwIXI3AwFQQyC9sJFKCCqm4fOfusEiuw5v8B3WsKnd7Urji6xJiNXcV/fvfjib3/ruD8ePQeEXzUfnMKtrLY8cSU0BQOKuqmdi4678m01n2kKDwlb0EbjOxwkKAoJbTuUNvHZg33Iqb+wM/OLzvxL4RQfzr6wOfGHjxsYdWcAQ6PMO4F5BAArrbByMrTpnJIx4tMWKYTtqpwbQ2NBMWdigGIbN/Ivaw0Itix3AdY0W8TQjBQFDg05pvr0uAC2JX+/ra+tRmSd6rEQ3QmsKVM0iibjIGrh3oUAP3p0dujVLIQdmikO9r7TCmIgrAkITuKU9Gdum3j+D8hMo2Gbxb6YTQIu7Hc9mPN7vviozFfhZ90UnXN4dGVwuZMCgMHOGqq7ELvwbl/pHWlXQfNRnAgOdz9HO5WqzYi9jRhpQML5OQPDjWzDwij75Wwr1+GTwTXIMrzGhBQYAxDuO/VlyehF7egMUUKbijc4DClAy89c0nKoi9xVfQG0Zwk/XmHRUTLtZb5IFYEZ4WxyoQXVEY7pAY6ARRntsy2bfvF4RvbT+kgWgBy3NlwhkrgIFmMCS6xBk6uLvgOHn8xRYoU+goCZbGFSe9e2rsxM0pTQgCOU3fCJPm3bahERjCxG4eFOcZ12nn8d0dJoBSn3flCC0pPHZcRhnr/rDpaBGePioIoNK5vKYgmH8fd1peb6DALV0j5SyyfBXX2NsskdaHKajCVbI4x3zPcE0I9YI9Gq3HOcaGaPp6TqPCKbOb+PLAdUhszWH/nNqMom5m1l9MoPqydDf0xwkYOYPDfY40zBpU20x/A8mI/0eImpzqMKrj6gF55m8NkHaGHScfeKgLbNRny1Pn/3bWQdjQPpO5+tg+zSTtJznk6z0E1li7hl51Sm6JftDZSLqnieN11at1YZBp1bEZhmjibfqdTSeNyhZeRjjZ9lq5v5Oq2daUT0+jgbJ9v/kkTp/1S4BraqbMW3o7uni98NPpLnForYQCh0PyBSq1W03Aotp0UsmeyhCdN+/fcJvjr/QFP6xD8nj3C6sTJqSgC9c7Wi+cbH/6KIxUNAezbNaIM1IWyGpu8NOy9G8S1O4y9G8b+B1b85YZlom/idvvOhn+EVD1is2XqgA2pvE8orEpqnj1tnBwXvv6HVnNzaoOCBIjpNHoz/OtCSjX32/HMxbALAq/7pOzSCYzzWFAoWHpqCKCggWwca0hzErBXo3LjmzJOVvSiw0GSGBaE0hOdM5mMb3a39tWR4ZTlhO2YepJuUgK2nndCC/awpDeXV/pKNnTL6ePfPPcgGUrChgjA+CDmaBA9uiot3Oe72EMdDzM3Yvu561RpRMI+Qka4aA8BYj0b1rPJ1mPgOBQl1ffd3mo0MC4FkmCGlZyYlrGdyg6YSAOH49DgcGZaFWYNIEw05Le+zrK6k4S3uwL40Cg3q8tOszjWUIFNzAv2XGHmGyblVdGdfSW3XHtmvTKE6cjWk+YACB7dem54TRLdCCbgyXyGNQ8krC3VqtJVyLRsEwvxL7dTSFMh/VZy/ScLTWkv4RP0UE/I1PYV8sPj+cx5Uqp/INEXRRTamEITEKLVLRPNSdCE1OAyecycGsv9Vpd5/LTCRfgjSFm2WVNkE/QnABN70taF88Oh21/y1NHemE39KevszHhUn90Er9Yy7KSDqVXTuoNMjsQ5AaEMGYmJYBA+sT6+F8Jj9YjzKMJ0DSU3pajcZRb01K9S4jR+k5DVic2OaCWwJrn7+rIDVWtMmoJe0YBthMCzPIANjZrkflsedV95OhnoBggISpx2cHMgegmxUP0xEsH46/fkBb6pHIxMu6lVOtXZ0Sga6nOnwsze5IdmAwAPA+bGlSLH6+nwEvh9QcrGYH4zgmSArvzOgPaYZ9aBH1uzWEsF5aOYEMIOOn/0BpWHtMkl2OnWNPPVBjLNbwFDVsrJyta/E42/epPRwMRIeTJm0iurHkQM5uTBcsi0ukGq6dyey1wGgEjDbsZWZiWbBBS3AAxneQPohFt7DwhbdO/P3x85DUPH0K82rJXzIfPXwKTANQmoI6SpoC1/vIRGsNE5Ia/EPPRC5NobSBPmfgtWvNoxeBQlrCjYUXjUgvyJeQ2KsmwN1kygUEAiN26GJ7OvdX9dnBTlNi/mJdxBUSPJpLHvki3wBADuQkkJRTORHyNXC859X01zSh/VLy0BRyQKHLPa/BrR3rgyiVP/fp1Uc2tQeX5EZvtbq4ZkcBxYS2guGpHqHUpCDG5cw6jKknpf2Wxtgx8cEfcAABfQku/aeXCUtzpk5qdlrYFk7rGgLzP5dcKXpmWR2JFdxgHe0MbW0BYtbob28QSNQoU2eb5jMEMKMxwtozRTBV30UQ3eJNIu3hn7I0HXz/+8M/4Il2No83TdoPtH+xTKKVb61qwPIzFF+IpKMZvI7iI6Bm0RXvSXBk/siZaQ/RXwkzzfhJ6kGm2ZrCUtWD/w3jrodojtEA57PTBxiQNIFHbTttWox/tswdTWFduh5Q0KZKi36wGNUfkasFGZkB0t7kdPan4z8yHy07a3iOo9nNR/vdfETO2qCw5W9QFFJi58a9d5uNiukHXhl0JgfnJqy+/2vr3rY5CTQZxW4QeJH53pQq9poBvSHV30heHiXY+ZBJ1Thi9nPfAcBBoIgkzX/ANO2nHLX/QUkO0iTGqSzz0XJHM9O2O5op3TkIbKZtpiFihI1ecvnBnA9kGaKPPEEhqD0sDZjN6CaBA0QCVt4bMzcJKPwe81Pb0L0z+ugs49hYptMETmGaALtaQJE1+x0A9l4NGApEGCAw89HmZybeNmqqGzHAehxhV/MdAXHoUzvQyBvT0NxvDWNPOynkuCI5CQ45zOrwM39EgzMxPK21hxxgIGG07hfsnUVTEe+txd7LyVvXTGsA2J0m1A0CRzcoJbhkXXoSJWk+1GQJ7ivCiK81wkDzfW7OHQjkDpp4RPdh7caCtxi3+iJbeGlHsbWnACYIAIHAdcl0tHBdnIFCoKjl0EdDKFBYBQaQEIDyLbT2PCL8fwUUJjRuXuU281NG67HftRFvegeFylP2N4V91VoJWr10I2tZCtiKqHDz0e45CGMqotmJQEUSshDUcTS/m49irmlv7A/TdX/3eYwjmczWzpsDZikt5v2Lkg1AP0Jwgs0jzR3MbWayKESFrZ4+hXlXx/cbOEhD6HNtttC9+tmsNMzBrQVAUFiMo9kOM1IzfJGOmNc0qxh+/5b062YtA4IDND5dt7bg9/EOEnCggJ3RjN/T23y0q6xjaQ8CRNrCi50m3gb/43epo8PScNYbKBp9E+udLJkeUHtO1mKc1E1i+u/NlPQoWjWZrhxmPAU4X2A2mXw49uu3SfyC9hhQqOcYtBwKIs9xONPf0GCk+oTqc6YlhqR6sidOBi0G3oa2QPlBZlmA1i6SPjKZ+9qUFAUZ4bzica7uNZMRwP1NSnNY8ims51yVAnjNWVBASLB+SdBST6kpHJD+dPwYFP6f+x/7JjebZGsKC8AXo8w3ds9fuIT+bT6q58oJJ/OR/dGpvDc1hfQw1NsczZrFvNt89GuXY/pXlqnozsQvlBR+R2kLe9GpLJABGSRq8DRIiIaBj5rCe1tojMo8I21AafQrgDZ/yMlMYGjpqYhWmkIx+1NTCJTzuX+b01lnTfhRBWfz+DKfCRykKedFhnNRS1hBgKApqQsncWLOixIKq1uaAhl/7wJHU1O3YZuU7FqN2G29SOx8b1Zd6jgXfTuB4H1BuMxJ6xBCA4BbjH5/SMvRHu/WCsZ8dO8BAzkzb9LMTMbEaB4CE1KQhJEirOjrAYgwgCYBJIGhzX5oSTgCbSoxjGness9HWM8BhD/xkJPpG+K341dMWdxTYCBrwTD4YKi2LAljUkqsYNhH7HmW64Zh7dIkDADSTLS5NtuYoLCnb6qZqR1K64T5ctg/iGK8u/sAwM1FPtfi5ybNN9LE1BrGIVrjrjEU3Pp0rdEGrrVwuabg5iPbKtU1BW0BIEFKKxII9LuXTmT/7fHXk9dMTjHCGSexD0dAk69rxCxxWhFRThhq7btQacfqp6hGnz0PXEPgQnapRe2kKVQoak1SU/gpfQkRULioJOVvHc1G3z2CbMSkdb26PJkgDaDbqdPoZ4kz3yJoIFwryCJ8S3sLSdXZTEnSFH4LCvIrQI5ujIYUAgOlnaYkcRaBghZVl9lDZ0ktPQgxXa92dLvrIcq5pqDB9Zb2STNYb2n5TMs5m4FjpHc3B/F3CSlnWu32JyAxUEgvy/IDD00hGg/FjYfxqy1izGTGqQfwHsdG01a7HporTP7W7mJAZHKdZz9UBQ+41o0W+Fx7aIbdjhU0GMj8I+0gRltACCAkSBoowM6HlOHvwxCXCM/Ip7UD0OTD81rVpyFz0EItwyH6yphF/DL5iuBy8moDld1vaFD3d+mvncoEiLc0mo0mSmzMoEHGVe83H17by36I8nb83KeQ0hScEdZ1T14rFsOoNJ+85o7mw6jcYOCbV2vznHvvWsqiJ6yd6xz92otO5V0rp/K6nMqMPgLauXyTKR++hKSmAIxNGSbFidakMj5gd0xp0wcg0++JbASH8h+Mkzdk6yQwXCTiZaCQDO0Z7QEdwnZRU9gPUIDyyFHu5iOYkxlpPgWUZsCzAGFfJGjGzaYcGHxZz6oNLb0gaaU0hRrfwQEphxzavtiKB2ImOUmsNVt4NgIWtwulNRDMdfXAaA5vPgVJW2LWrQ2Iic+cl9YAGGK6E0wTKKC3fT3LGP9CgwMMMDhYN8TsSUkt9Y9mQF40aWT24wMS3eEwJRZTJUwumkSoQhQthgLI2gLj2Nwah/EBB4nozPVRKQEQ8o/JvLM1qt7TpCFEQusUl6aga4Wk3vUHIOJmBQQKBgSrOqXIZ7eQl0CbU2sMj9DiAoW2vJT5FLs0gKj48Hp2JxlyttAj3rCM5rboURJalN2kGPyMmeuqLVK/1sIVpT18NTiUb6GlPzAkWkKFrqm1TnDHCDrCxDcB4pvjP56nEHiCQp0vXJ/NR+BI4Xnvuwhqj09h02Qk85HMRmMq2thZzuRZBK/SbuwOV9Vs5RdhqcNRY/x9m2akMh9lD9gGBRNERgAaKWnkz2G0fU27ZactiyaSaYnMvtL23GPapqbg+XrZCqV9cDT7jGb3bXgYLiCfAv0KHDRboLBiri+aca4YUOAibFpqQVKR/i1JUQSGCLT5KPweQSIYWhUCBgwo+KCQ/qlQq3RO2OLK70HBfQLNyJvJD8O/7wGF3vebab7P932Tnp4aA2lIA5RGkyahagYTscj8BxTqd/t7MJ8qm/Y8pwKrgWU+yv5qIHdW2xKcxdhbAdPxG+lybp3WAsCBgbbCzPNMyT/iHoeypcHTwLQDFBLuZ8ADFAKb9F5jKDnGcs/3FNhFmwnHfFSDprQHbgcQFQav/UcSRZ87F1aW5QIwjbJbWvMJJLEVjSbPAoUVq0ABgS+ajK6oa/kUpGk0/TMSDhlcXiWQvd5/kLXGdAsA3zzoT8d/YD6aaxHDAiONuv1P81FJIhRBeC7EO30Km2kb2iQn2zxUaxnJlIS+d/MZzqtqLaHMR2QAMLNJqA05eW3npHU0AsbRzPY+IXewtweKqa5tPtLAXMWEBwQARSNpUTvZRIuxlzRX9JrD8Jl/NIQc6fABCiNFivmTeclUFWbyahAZM9I2rWHCVpcxL9lIBwzUDMmGkU8h1Dx5njXg9FzlEwWJEw7oOPPv8NlOG/H5ufXk+BVg4IABCBjzzujJlE9QaMbvGkL7G9DP3Kz3aAd2JkH5ZCcSUMccV5ra3643Jk30J3GfRy+iSHqNTVpqJoHRgrs+ehjn4fQegz3T0dPB0RqDCtc9RQqNlPX0L7TmAPMVNEBs9I4nYVpHq5yyQOwmLglePTgP8CuGW6aioo9F8sksjbgeyV7FtViWDGelLeBDO3Z/qiE5TtLo1TXsdVGIuspU5GGq+g0MeCl6TNdI0JJB5zZHiTQ9geBPjx+Dwv/c/7evn5qCls6uLTyqSe7Yk5bT+ec8hdIGoLWOdhlyeu/lWyGpiV/3VXsv3zajWWl7m6YwvoWbnfpCMUM5lxPAvhR9VMDSQJE4BoxrCnlejLQU8zsMCBoQ6ECuyWfUAAgOaymMXJFGp/loHM0FEm1ukUlpoctRvqY9qcvDaVubcRNSX5P22q8QpjWYGUnOZ1BrCJqUfLXOwLLICL5+z6DstIixmJDZVQie7tW7YvMdCAQ1hJrFu+xvQKEmEvE6HRACcgjq3Oage7SDzdDm1gruZDrw6rTa8CktrbUNXgPGBh0QBEjR5FTte2BeDINekyYwKM0zignKf3BVP8dim0XZxNcqoegiDUlhX0Cb9NZF3sd6ITu4xujdj2H6AwIz8kAT0KwOuEfa/5QWNzr0VI5mvDjG7jEpYUxLMkcpIilpPkoASSIT4MlclAByT6z/iqv6f9VS1LXYHIFifxVPytVBCWvL3DyWBc1d8QD93WajC4irhJP4KnrGhVqvKnCtWrfqWhcu0vwXx9gVI2gpxPXWnJkNrLveu0i7saNjN9osiENe+OPxv6IpaOc1NhVWk0VAphOwQ05uezqaN6r2t2kMrgEU0zcNwc4CgJtILtNRShrOuj9OZdZWKmYzSfRv7OzlIBoLKDFIiuhDI4blncBQPZNLu66Vb+FIQ3KSjpzK2RpARIFYaxQU1JW2FrUGlDnsz6AA0xryAQYnKMjPIEBAoIg9ANcSJMnIP8DXHXxNpqJxhuF9NrQkun62yl6qYPsVBACn2ciBQWJLTUTTb/ocCAqHudD+9n74GbYx/F00uQUemYem4JrEsE3+5TmKGiSa2cf7J+nC+kmkqDkm1WgBhb9UlyUqdLHG0iIT0/eXHyAOibJpWWk4r6OHgMY+R3nkCHxvfxNO2n9i6LnPfKE0MfzREnxvRGkKlR8Y53NibJR7Kv0cqCS2hdWRRcVQa5KstKrFKD0RRgG5aQmYNvL+bH+QztJo15hA5VN4OpUrO/XumEURi7mPprAhnor2eTbJPPr1LxSFv9AU9qeQ1CKMK2aTnS8SyZXlU6g9FrgXg2kKSUOrQlJ3llMZma0d3EzbCbzyLkey/AzyKWRyH4UCkrvYHO6QOaCuc7nPYAZopxEoALQNGDQr6ZjOn3bo6x6zHJRUXQUI0hTadMRZmnslrQXjb4gGBfREtlgOClWmTPvbTUsCBTMpjU8BAwwPcADQM7hHa4gCGRAcltL4sVJz1ry4F2lr1TaacKUpBGCagiJRoya+KS1rkDYAppzYq8JfITASB/UNZeq90hR6Yps55uRcvukwdtNPbfla5qP7BjWBxH0X83+9EnsH7lcSBAKvO6eM7Q7lk3HIsusj6Aw/hTXS49odzMgGaVhfN05myayIxBX071Ri0U0mtGrrc07Jg/u/HQHp2+ZHbECQBiDzjiR7MW2Jiy8ENlYkFpn8ihciN1bs1gpWvMj8x6eAeEG+hTAAmHpV2tYCU+xrSBAAkLGaHoIqaoVpL9MAFnbe0Oz2m6bHtbP5hrTAWQJFviCuzhvSFORTkB/uAnB1KOosabGwArgYnr1iovva5HkTsDYmWECagrAorevSAP8Hx19HH4kodK4BW3HFTSCoiKPdoKCZiIX6SWSvytYo2jvbwXzvG1ome+dEHdWMZpmKgF8EilugkrUcRq+0SuZ2PxxOzfw0aKVuas0UNmoBQ743aNsVmTXm3F0nxtwCbjFf1xCkDRxLWcSARCzPN4xeSwWkAYGAQuBQTMJFh2zga6YPahYwoHBJtH0LAgmc5qP2N5izA2P3PyV/OZyr7PUAhQCwtktHTGsw4MQemoIEEAMMD/ORzgKHLB3WZy8rwkjSf//dug6ajAoc9Pd6VdrrFdh3AYOblFrbcEkSwLkaK9sOpiE8QQD6nOhPS8ynZom0xsD1wihBC5smuOqI1n4xOFIRKycY6H73XYy06WCgXyFGfGgKZUYKSQMpJ7OkfAJFSAtIBEGhQQAbK15AFkg4KMBAod8BNBAhErFnnKbaF9IKF82JixoU7fC4UEvzUMNSfgArK6RGPs1k+wEWQNDvigIedzSbGUnLnq9YBQpgOCo0q9lHEuutvyj61LLa3X/bzMtMS/Zv87MfHP9ik513UADNR+VoVtUlCRXZSBapQZ1NuEkiFlNvZ3FHFBXo9FIVku7kP7B0kaKfE5glHfRaGFMkMy6mMfDaksUBubCbdtggDkb4tAQH9KzkbEczamINaPppDWE3ELlPIQOHpoDFHrgwgHGxTy5W5QkKH/wJAqzPaQMKwJiler5CMzD9Xj3oDnI2Z5i0BydWNn0TLpiGjVm9spqE2oKeoXNblZZ+3B+BwxH4nIHsM5HfTEUHSBSDaAfzzgaMEmR0xpiMNulPM6AfowZKi1NTeNMQPtBXgQHPzdUtH1lbiAkuMq5NWmK7H74zNB60Ddpp3vczDssPAHGMhQGM05BCBq5BFZthqHtAAEkQ0HIWSt/N/JfMSSFfxPgeoglod+02hadDUyDdHOZCkIaRaFN4m9oYAGNt0XvAPDhtjxnxPhtT6s8UI+fYWTS/9pyFvj5HknPbyJgu1/WiqVBRVg9A/8TGvjv+Ykbz/+2qeRUDoLpX7hXNaC5Hc5mVvoSjvaAQzUdI5NY8hY19S0MYzWHLVLRXSWw5TuVfWaqeQlGLJHwnB9CnQOiSpDWYNNoB7a7FqTEEsfE4hgq6Y5on0YkXg9gyEQEYU9ChHexJk0+BxLwisS8aP6QJ0HzUZiPx476PQ1OQyQhAX5/aAN61h+MeHoBhPoYGBQwouM2fPgAxkvYd7GH8a1FriDK9EPNG7r9rAPV8zhVYe+ZEwM79Tp7bj6AZyns1ANz3nE8H82gEui6TkdIDr1/b0pLmoxJepGX4WkqnyYijJywt5txtuEhh7l+Qf2vZZ5qCFIHaAW8HN7QBnfe0gQd64tXa06+bAKzF4A7BCFlMFOIzYvTKQGQ9xDGZi0YrCEjyr1DUFTdW3sU78kZE4ooXzdA3NYPEyl+Q5rDWC8hErBd6Qhtu0pcvy1/WiIvzFAYUhrFm0vFLHoKGJu63wgbeOfaPm5rCSgWzCDByhNAYDpFLpqR1/BUwleawwjWE1dJ/B1uYELFootoRvQjlaArR1gWP0hW/+5vjX2+yA9Bm2UcRyA3YxxRsdRqZr0hLQNt7MLP55VzWjOZz6WyRXLYWcbehKnk+O0gq10htxvhgUoDglAMGBI3345HGARqw/Ppgjsy6N2nZK8ipV9OerbTNqKIEOgpJ4nUGTi1iSWIY5q9lI6bcbGbUvoJPad52nc//ogGitQUXVw9gKGlGzLv8osWkpeZKovGziBrPfNlC0FxH497xAS0Fp8xIkkniOL9NXjMtQSBS0XFhZ3zQFEyjYLlTpQcwGBCIYXdDL6DXoTBBBdIQXHjZRlMoZlGq1HCnT1pB/x7i77xHn3QiGhisFPiyNWfa+Rf4kEbn9Exgm0XvVhRz77RDK7DZzt9oCtV0WpyTYyNMUJDwGOCM5foG/TPigfSHwtMSFBc57p7unO7qvlX0nPU3zUK6d/6Bwo5krGDZ7EuqayUIKo1UpTRpCph6/e3xc0dzfnY0B4AbG1cWxu6g8ymlPexxNO8L5VMYR/Pm8qSlFdChs29GdGzcd+X/lQu1L/NoCuV8BnbudjDLVOSIvcUcfZCI6XPAQ2eg5yZIUno7bLyGGmVNv1mwfY1dagYVB00QIigs9y0szoHk71jZ4OFLX2hzkX3N+55rH8loLKBroJB/RUy/GQpmuQuQ+PXckT/6W92MdFwbMBxmpCw/AJJrJG35qWkWYhGHphD6lGyLWO2DHeNUV7s/uF6ykxXgItOObP8+GW1v4H65phAzKW0D92uVVnAH7nvzXqXdO/B6lXQqreOTpnCy1HUAQ92OFkpGOziJTXTb9BxWbDT7q+S7ipRgoe9dwPjWyEd1Hd1+TxDQDcvAQSIzTwHCRAHJJKS/xb+gc7l+37hATSFvLDmad2kFF276IWoRfCTDVM28hDTzlGyC0Hiuwe4LIZbGcIn9Y4zeswHRxkamdpmXZlBpSwtwmrYw+7NoLbFsDbyFpMAhSAETddQggRMcgAEHDcIAKghDX7RBDXGAXMP9wOwfHn+9n0K9MOfFSFyZSEnDnLKeyJ7RnO1ovg0U2Jg1c4w+BTH+hey5B+5o3r2hjvZRqI5ZbTYiOQwzQ5wb5bwBAigNKC2PQeGt2QAA4BDuVnQ/V7oYMU1E7VBGA8bm9oK1wxrNSWsYfiDLTmigUWkGDLwGzUeHaf8wH+k6u20aGGLaq53z1oZ5pKHLc3/Du+Yw1KG/8StUk64dZQrKiTpay4ACxhNDadOOszFL9zLfUR3d/ZpBo3oMKOxvQOEe57KiinY7muu6AGOdzmcChMJUXfsYQBjicUfzMAvL0n82wp+goPMjfFV0mZIo4zQPuUaEHHAoDYNl8F7XvO0QmA7Md+n/AIQGi4lMDAqJpQlsizSqtKvB48biYncLN2LfWOuu69yIfAHYiDWahZumD3UnQXrQ1yyCgkOcpthqbQb+45I5smIIALCTwzgZvSUxasb/m9kVaMbf4wToVVF7Tg4GEAYWTmB404rbRJvdb4fGN7d+dPwvOZoTCe4cGjFhpxUFTJYg8WZBPoUyESkaRGvQ1EY5ifotU9IrZdcLvPhsm5GQuFkTOYtbaIw4G8Pu6dqdSj4o9GXMagNX6ih/LrTzN4wRa1/aMRVZD2lF0DXaVWkPyS04CxBA53MDg3wPgXFIr2yz0QghadEqrMd3mgJ/b/52AGhpysCw7wkM2CYuFSmtAQEibAUbjCTT12JeZFxl9xawNv0XaEY0owHMlEmmkF1paQo08dAENCGn41M4IpCOP3cq43E9QCPT02Gi6pEighHRELjE+MX0xfDlP9gYoJUpTyYjMyk1zqidltGwtXMaMA/jEJKgmUgzGR3NWU52enAfgUWOs7lBIiw9Bhi0PlrEbtYsX2Rg44pdM/v35sqpG2tVg8dWqCoOUOj11STepLW7QIJxkbRrsKnHfFQAoMAG6hJZ5uor0FqJPr+aeywVEv6ab/gfHr+XSGKAYWx3zOxMjP6mIK20sIjoCaAIo43O97PjL+Yp/B+r4jkQL2Q7mm9qDF/taE7cZNmxOcUsE0mRqpbG1sJ3DDHdV89buPdoDz57OTPxi93YKA4yOYlJsLYUE1OiDxjCqMxHsLR+vPsqevCN/a/QXkDgJqRE9gSY1gSQWB+YvRb60iblZULaZIIcXLUm9fGeME3BnZEefdRmpD6T4ccAw2gK3wCDt6XuqZ0NMDnu0A3VwPCMmojWDFrJSJqKEpQs67uu3DXJZ5Vmitic6LNRE4HMc4q5LmtC/c7eNxnY9xrG/nAqj6ZQzuRM4HWHmZdIi6+gozlxv4r56DmgAKjI6cEJnBbt1qEtyH/wdDR7H1/GcNBFt0N/lm0w4LrndzUTI1ZQEmyIdgQeepehyaxMqkLOCCKYyUiagkxFK2qhzCtuXFnL619RpqQrK21lOaGD9yJvrHj1PIYOXY2NWPdoCnj4M54Eqw9ruBJdV0hzMfTNmststCmwzqrMtdZa9nsz0ebrAGwDKwphEhQ5Ttzl1nzkoIcPHPyBvbDs1TVhZeaR5wCUHxz/K5vsBBlxzWosL/gNtBRhsiMbUZ1Br30qZoGOZiQylzmUbZYzRIry+D9AwUUnouT4+94bW/XA29mkJ0yRYx4pMChaC4AmJLfjKwpJ5iMRSLRzl34DjUBKY9FlJKX8QC8g1NpD0PkcDNPPk+Dcqd0ihXpMhBvUDBTVoO83w4DyPYCiznEQu56FX6OgIAkMktpWFhNaiI6qtCYoiY+DOYTxmdyvVwzLJNKuXBpiVedvBpUntQM5hDNzpH1P03U7mTE78UnjSIUtugN7/qoqQ2w5BPRIe6dH/9U8riV/Y3Y0/fiDbUe289t1N1XYDzuz/Q+mQklfY8KtBZ2pJXWNe/2RDQfPOXxj+k8CwFj35XAOUOiMMUO1xkEfRWy9c5+NARgnHi+stARgtAOZvdVLLRiSpjYdzIHs2eGbRR7fzGZ15o9v0t7I4nn+dDxkjOFrGkhxZHV8+Mnx147mqdN0NoO7IJ9+ZOJrlfN3SQUstgP5GMZ8RIfNvlsruLfSTk2h5jDsMh9BUUcDCgggc0/DqDVkq4Oli1408J5nG51q90Z2AYAQfkWtAwS0NDcgACgEtUU4ZDuatyb9hSQw+mf0m04CXyJYGsdu/wKOyWtNLBYJ5ZqCHGIn45c/RnnOe/lIBwQEYaDr4AADUEWuBf9fZsGe4Sxa5u8OyArQtEBtNGmXzjJJLvly1EcCAtCESdUntZXm3ryW7T8mhHSXNiB/gyT+m5rCTF6LQ7MY3wQjkmzyWrro3yOTo+ehKRwWjm6QAp4e2SrDR7kAg2XZBmGzD7QUJ4JZ7NKauuHkT/CzM38xvTBbeozPIFDb7s551kJzB/MCN96KjQt3aQmokPUVG1/JPFlaQ2Dj2pr5zDDV3KMxrPI3BFAadQPOE+nibGBEm5UTgQx5IjcUGiP/wovC6E2BJBPAtt9Bn0J2PBP9q0EhK3v5+9A1xAuAEfxgzDzhjF39fQgdHiiQQF6YAayvlABwShp/PP7C0ew+BTQ4BUqSV3QISDDIAoOaRWoL4tGDL1ConYM2/QfyKQTnJ9DXsJMT1mqXBi2PvTk7QTun1QBaBy00IBzAULezaceYoBtfVUwDQjHAdgxxkTjQp6BraQcCh9EOnCDGIV9hAwMGrQtxHYtoCT/NdJTtYG6wiuRq1iI4Y9L9LgiWzX9g3w9MWuMn83k7fQcEMIY3nYBmjN38E6KqqIk2ndtvTejNoKO5waEAY3V7Ab2cBjhjK2U2ApKTVGpeTJl9ZFI5lsTuWcyWlqdj+vAncJD6tQAhv2soCibtNNYt0Q1NAa7hvYHBd+c9v5t5kNkrCksk19rH87fKIVcZfyCaubm/APqdDhTvaWf0Uf0JGCITV9TvFQUMkRvX4jyGxWdzMyLJJ8DxHQ4IHL826iGJrQCBcxhCHETasHwKRfeRFSIvUNwZFaW36/5F/teRTjI8CQQ+WglSUswQvX6LPo7OlpA1fdUYZxFkHBTWV/OKvwGHf+doFn9yRKbeerc0UbVeJOyJDpHaDcxS15zakmMq2pDzGXQkV9qNPYvfoQbOjnquJWK2RDMfCWrudBb68kdhgQCBBOFZ5QxaAe2HqZVDcY1PwR3IhzRgYFDninKoddtXDba4Maar6Lxpja7d2AqcRGh6X9g8BZiDmd/YQBCcsCPG/wSFqkMCnb8A9xm1gUf5H4h4KL77JB0gUoAdbSHLQAsYtdUhINOXhm4ANfEQGvw8G2cOxoTmnfRjDWPcnAJfPgXS5D2L24nxF8OPYfwPMKitYwUAky5EdRPS0RZ2THsKEOyrJKSsxwPOM56dkmfa1Amn89Gv1Xabgg1NPDKdtE8rzXyDU1t4B4aZDibNoYEdp6N5xe610hoosGvV5ShH80VH80UtOrZmOSdmox4zc1m7a95U2ze4X0Kd3Qhd4zGkNRg9LXLfFbtWPMYyp/puOu3GN2CQlSDtvqwI6u/xK2j8kWc+AOJJC+FprgE+aeSd9D4e/2LnNda7mxdQIJeCuURANeGDnZnZEQKlJcgcxDkJeZumYPewCAqLXSb9oBzYYlytqgEThSNoInOSU0dtpPx1+TQj8TvVT5oHEGW2yBUIbjwT1+K+xgMep6P3HRRkyc9e/ncjo2MYisnFzRdrBEtL4EA4ZjmDdcG807QEfW1vtNNS/7tGMPemhY6p/t16+JD2DgyzlrufCdmS7m0cL2vvRea0kdwTAFi70hbndRzxTbSTVJNxZNyljZZPYTUoiNHr+n4l5CwuDaHWN6p7mFVR5bSVj0K/p5tOe/3zuzVAU22UsnpVS0a0NDnpR7OdjZXn/eYDC2MOEgC4j1jl3Vn5bjCKRX/DYNt2DzLkYIRQzByEAo3TXLRizEYyGS1sfMXdaV90Pitt4cYXrQo9d4Hp5Xy29ZC0llKOhnJSoTecGovQJLqPnuWEWbWNmsQux3PsQOJGZJmXkMDGzcUZK7S+ukxzNkCBDzUoe+zTVEVbqZaICQC9/0OQhwkYpFJ6lJi+jJglpfKgkaf09sPjx6DQi3kFK4IgCNTgzQQyKtY3wHMCO9RYQlxAlsY2Y2gySFvlggtOafKIvBET11DBJYQhtpfQVVLWDKCRVJtRKg/E0KLPSns6jIrpL85LiNEYOg2PuHEDhZDkoFdQY9Dh4IGC1AEEY78BC9fZQ+uPeHUnDjfvHNeWNjDlbxvp/2/ScFw/+uAYrlYZk2wKm+uHtOKyliWpi1ll4vAyRWNJhpYjbedxLW316TBOcypb2tOhjMnzdjgYHMBgXLsZuQZ7I0Q3RCLn53cD+/H5D6R+ZwxHx/fAGfKSZmB94n4Fl8Y9zBR4mIw6HyY9dM2WiDSyzUlLOnST90OO5nlfR6bZ31GHj401qpELSAoJF/eRcAv/jpj6a0xG999bw864bWF17k1ouGkCLRAUDUzZMWbGg27sjzQVnm7ZniTyp+PnPgVlzRnfMh8lbbsrE0kQAGpbvEqjM6g7pOT9kvYDQucX794cEHdsyDV9o6SnOzZuqnxbqt+STQ99ViVLa5hp7sc4RX9SvTknpdte+eUrWIsmpEBeqyR0agqHEZw2f2BsiiFpAZT2AQRuphEEkAA4jTZ2RylBoZaRBUDIBqJZU2muBTLFZ7LJsr6/zCRmiEGZ8NQOZJSIaRs5PT0NIvMhuYMHHQzxcU1m9HYnTVNIWuMIWmtFqfAxA7LnK/Ctvu5LCWxZzZloUw8yTVOYCWe3NIbblsD2zXM4X0FrKakBWlKzT9bMHJuho045RumBCQdzZ888mbqu9Xudvx/Wiyat0RiYUTPaYtfuUysRd9GzgkYAamOB9gUEEteiWShGU9BE1UUJf+XGF+99QdrCjYuawxe1hi/c+If7uf8Tdf/if0FazgAA575JREFULOcVG9eu2cxXPCa0fdAUkN+BwnDQGgPyIVSbixcFXvb0TU61miYXJTCfd1VDW1JZ9vOZFzJedcY913H3OGq65jOr/Z+w4IGTXvpQPE2ef4fi+KSZHx5/5VM4nOOQlkD0S0AbbURw1ZEs84jy62sG1z3EFLQgKk37KhNnA9gpO2AxKDmDRtXOo/GqfiGxpPIQJLydioE5qzvbcTQAgoH2EPhaHY4K8y8cKP4GCKudydG9pimlx1ub+fqo9w1zxm8Rk3ZFm4so3vE5lRDdnlOq4rLRUnD5D860lEoIyWSf2yvt9SdDPK+bnRvB6hWKRNJ4CDH1iP5kqHn5VYEy52gz9ZaEU2CAlvrbD73NjMR852qoKJDc86xrDN24PEtaEylKFnz7fo4XIB7AkCfAqAGeA9zGYoOA/Tal0/Ko4ng4mpN7V+QBpkGhzjWAFWXf99nJ8hHIjCTAeEYi1fyE8TOMD6HKHUfz7Ot+xZ6lL+RnCPNbhExHd4MW4PxmROekw60czSUC7QaAGgUb48HcAZat5SdormyeFmosaBG+5mZBk6Wc2rrOTXKhtzgEJTOWuqslEH6IROq/D8ECooMwOnwDld8cPzcfoQbD1I+fkYqOyalXjjM8c7Wzsjqqd1hguYumIDJ4/YsYZtSMn44hSsRN6MgGBNcUxmJBpiln8DdfqIHVBqh+3p5dC3Ep+qhAIa66VrgqIs5Ncci5QtsJSjePHMIKwexwm6mLcSDO9koEl9oOOp/JMI1jTvSK8QWppN2nD/9BAyYZINOqqXndwACMjP4BHJpU3gEBsE9q1abS3n2qeUhBOwYMjv7M86k4mm7MRY50pUGwHXa2NrHvAY5yPkc7nAU0Gpnh3zBN3oBwAt+g2cibw/nL9AqjjScqPBHiPFSjWmcqWmmF9l5wgNAEEfc3JLjCqpl7YhzDDQACiENTGLBwRu7O43Isb2oEtSmXNum6yPAvcC21ULj7gEgvrx2jlUCgxXqpfaZ1KTaQ1qOBQe0lKf+aPskXOmqDYFp0sikgLNJHCVS1GoNgixs5xd3nmwtQZdzGyzQD+UbtAReoABTvbedZop0Y3yW7kK6JY0azhn9+Ty4fj59PXtNQNWBoO6D0Z0oGCsdqWTPZQUmZNEV/WZpA0j3TNj4ypRWl2sn+y52RCmWpU5jYduDsB83gAIVuaKH0PHuYd5VPGsBaZS6q7ZFGS2inM0EhklMM0hzCjDISfFLi6U1INDIT/LabddswDtp10g5cLjmUSSnhpog3P0KMFUFal3oLbP8i4Oadx58Ko8ush6C1/hsPPH/Q/PJg6O4eEF2lmYiKqY2pzAWlRaYvP0IR2IfKi5YsokirnNbii8H9mIOmpKrrppPafQxDagFuGFrLJSf7iV2q3b7Oo9r7ZPv1/6Jwtc9PgCGmzQRS3YY1ZyOy9haWkz7uFguMLqMjj2ZOSFIBloRO85Gk+maD3D0tazMcmYtCpiJGF/1DsPiH5qU2H0Xin9gNHprlLNOTFtCLUAhrXa+c6COpmLPMDoG/abOkdkBrpslBLqijl1RjrXfjKpVR8zxqjw2tsGBzrbJKK9Fv0yi2cYd8pLusDLh6pnrEojC3gSXcjgo6CZenxgTe5iI0261jn6OsWYZd/+T4K03BX6DKuuAhaV9oW/neZaFsQ71+wwZAfXg9bxKkwkkFi4C32PtBrhHP/MbofSB2Q/JGWDH9zoVe0uL4416r8jXonbE00KQtyHREuz/JtBf8IZvLXGSICi63Yd6awIikaqYglfSGIa1+6k1kQ5L4IbOfw2Ldl6moy8russoTll9PN9BYW3Z/nBcDJDHEwRt5fl7nF435MWYa5s3v06YglZd2L3gtjUJ/YWaj0+8U/S3ms8KUdaqaj3r3U8bwNQaaGTxAIKbdDyK2Ro7+/0Hqb74GHACas6ERG7pnHevcAEItQb/h5qPT5LRIHfI3fpqxLGezWHLPGAYn70NL6ExAn/K4s1uVdwH1EFGaKBWWusmnzHSrtT9aCEv0XBdGtRUd0FSUu69zyyzu8x7kE2U+lHkTsblrHgGpNe+yeBwCHcRDbVAF+1jjXn3t0sBJOR8o8PvjrzWFIfMiamGvjsWIoZWKCFwkBNq6OQBr/1LJpiUR1gw9fkJq0Ihpq/EmgkA7KKkDXR4radJUexWleQR9Gjh1yU1ldKNfVMXXKlMRQ1L7LPMRz7V9cQ10Oet87fe+Rk1F7CHUBBdIhuvOt9vRPoqAopA6JLYdzJXVWqVaO94lh25GYDSE7/J9c32+y575YD4aGD7YYg3XpHagAaBxHsWkd4yJcrqzGuBgtbJLPitvCDPzF8aHsDlruWY8j8+hGEMBtQZl00uoA8hAACp9Y3L6ZGKr6/pQUXDHr4MCVGOnNcjjsKDcInNEr7/I5bK4XDmZ/DZbOcKnz2CtxOIkyDbjRGkICzxHYkU5gMeXsKkl3AjOUNb5inIe/8MQ06+rtIAvbDqaN/7BaApfKqM1hUqX51G7tq2ekaezgjTES2Taqb7YuWgJqGeiuZcm+DAsNYvn7Tux88LeVy2Zngv7tXHnwuu+mVbrIe288cLmLpEXdaer9otfZZ6aXQoTWF/UfEBtLaj6Vmsu+h9rOZ1h7UGaav6v6+38+SOZ/Oj4uaYQM9je7j3+zrSnkswqi6G3xNriEQcYgGB0j9Afu5gylMY3CTkfoGB2rgaGEBex2wMI2aHAk6kyBrWE02x0mcYggBB46L1JbYKMrjUFXU8nl0QRUEzkOE3XQwywdmrmgTEbhSouqWOcxt05xvgnzcAnHvmAQ4J3y0wX+3Dg48O9KfwBDA8BuCLaRCPDXD1k++Ohir6pFPFGnC1MtkkJ5lCG+RFKOgTnz4jsVF8N1f5TvRfGdKQ0iNbi7WoEIH4vaaZnx3unGBmMgPMwHekv0VqBHMnlyM85c/j1M4H2GbQUvwkQOSuZysykSWauRSgi6eIM5QU+S7BxH4IczheZ/qUypGWEl2taAmiCdek+KHHzX/uiaEqr1U+3NR2BBJf10UU6WIw4Q/kPclsUGmkkF/b9wp2z+HfV6MaO8inslO9UPoUCobWAyIvgvbnlrMZHtkQU3dnoSDL1WQuAgd5xT9Yc57oPzvbt8WNQAI5x8GD0YtCyk45U5Pa8Jn9JUyFmwTi4PQQfK2sg9mIuqyNQAJAo1MnO8njfgUCM3c+PdurlKHDeczCRJrAumou+ill/0hQkcZXWICBIc+IFOrQSmxovVU+uz7OiiESMTguJdE806OV8UzOL7+T4xLPrrFPPtA+HgP5Tup/Pe2eDn1Ky3+FvI+hvC+0nHtdhLDqnUYZmz4ExZqI8zrPoXTTIzFIGYtIs2QBbe0aPdjC8qh336eNjDo8/E7gfprj36tvvd0DQHIDRGLImAC4guJRr7/Gr7yGA9PwAEAhW1srHkVyriIDB9YgubrMZkK2//AiKIJJPwcFBvy86jcefsPFFAND2vgKNdjA3AHUMIlupkL1NMUjuUc3vI48pxkm4YEhppoLi614BApB5lcZwF7DU2dMW7q2VVEFPSjLodmOvwM3xviuGHdo0JJHAvRDrQmzykwTGYKaxPiMsyI+ULBCPlR2152z5bxWGv/Yp6BdrCjF5AKdUSg2gBvfARCNejARVB+3tJE4tb9DDOuoFkrgBYHF/5xH70I0329th+IWWtwasYDs/9K2QHyGAxYlqqwGgQCEaFCoiaV0CEcysXOp12mUNyFnACwHQqZz0H+x7c3r9hXUzPG6P3yGtDSGAEQUsPI6HPP87EPgdBT3yfwc572+Pt+vvXvEECL0H0Z9ud8PyxtvVFBLnz6NOOScJF4mRDBNc/jqasVc5BH6CetEazau2f2lLnXn+AWnXLcbIzTlKjYECDCRbG7R7beqMudVggNTiutzQRlFJ0WNMMRixaT7Kmj1eIaLAV278s4o5f0naj9r8RgvWFWWWo7mXvQZnL0f9/ofRQ//gxtfa+No3/gk6mrVIHp3QMhmN+ag6YSaxcfNdagYWvoJabJP8YRcwrIxaRh3AsSBUspWSfoBMbkS0GLJc5qMyJZVJce8b9/1VS6fnqlnweeOVidoC6MYLNB+tYPDMRd/11XulrPWFjCigW7RI5IWdFzffWsP5xS+anxkosO/EAiSM/EDOezv+ynxU9Dcq77wSNLuc5hcBgwi6QsFY22YykhyzmRzCJDsxPpYqDSAtHys2B/O0BNStFjN4Hs+k5+tyRruQA7n3U11zhqV1vqW6osJYpaIvFS2A4ktNIsUKhNbiXxNaWC2Mj9/81H7UpsPLiwuNX6eeKWarNBctfsfq0QAqhnbmjbfsT20BMIb3LJb1irf7TzAYGOj+TPYF4sR4Y7BmVXzU2x8w2s5pHzlTu+fC/khYovMwYPC++NEAjWnZAQYTmqwUh0LFIbjPryOQ1D7I9tO0i85NSFEaRQS4tMiYaSLAZSfIlOVUTtr5YSunYpzKve5RfghrxTii27HczupxQr85taERQdOv+o2IOyaipCaejahVD0A+onqUTmjaEasYmXSjr/O459cYbR+Y876RUf6EveXvuBC5sfPGyloRWo7r3g9YPS3zEXlnR+Mxy6EtxNBO08/Br/98/Nx8ZPbiJ/KcyzAHHYBpv8WghxulYoWF3AjGYwW45RYJnJ9F6KtdmMjMtCBaupN5WqgHv4CAvoFuLcx118/TO5KoNAU3HyECi5rCuhY3gClNoTSL+qvrIkDfj7m/qxsRyLyLADdtkPsC7ppYs2hSSjpTT3TQCOc52mXJ2y3iGiFRc4tsKbw3YVf0Rsyzp8noSVxHZf6jo7EpzreEncX0NQrqHyV1gSgCPXfgeJiXfaspt/9OSte7OGEpgquMJIMJ0P0NOMgPr9n0gR4aAwXUMUnB9rOQL4ggrhwtPzzan1r10U5Jc1EqmjrobM7RJgKMbRcA0KpxJ64rsVbiKxPXQkn1qxj2P6sk+7U04zixgltkxgsTklqy8td61ezk2OVojsQXXlVmllN5xalRfMWEs/paSnIuzyY+9L8xcqjGEGcNb535l9FhpYkLwSi/kGm2HVZJW97ipkS14VctrLiwX8Deq1ZyvhN3awqL5qNyUt85juY7ksAApHyla2NdX4i1sNaFey/EBmrb+qu+CzO/PMT19y46xISWH1pDSM4r4PgZFMzxl47mljn7//XqMD9eckwobai1WWB7QZySo8sbcSgmlA4mES6aUoyHvT0bAhRdaxAY83JmIU70ZCANJvOHp3NZDugOUSX4MBIoTFNYK1CDZ6T/wCLxBpsvsLgWlL6/NRk19CceLClhGq3McMZ8QozeGL52amotTtJwTp+KUQ6BZb/y9C99qNO/OFRF7w9f/lySuU98k308Ig5SqAYYWhhFdaTjpoHju04gPNfBKXBo4I+w+jH00CONg0DAN2i9nRFl6DE6BKwRViZOb9LORh4BowFCJJ2o+QkruIWljQeA36R2lUls9xpEI+lvkjn9AvsxkUyaQo67tVY45czktVvLWLlri01PYzlvq6nimQYy82m9AE1IFBB3Vj3AfBV1FdOw0p4QQMofciHyxmgFCeTFSFWmbRTY0PEsAOo5LLjL7IS6Lqgq/0RGOZ2rP28RNXLX6g1VlrYVODWV4lsar/RvsQ+NPQ7rbDpBP/fT4y8dzQIGvY2RRSam9JByrYBpE/6pkRkzy9K+qHlaLKpToK22ED8ZEqjdjyhbzcf3QI9+3aSd946RdIAEs7Q5aHwG42hm2pKmgJntfGgKVdhqR7P7T4ah7ShCRdRSCwoCbqe8C7SwszM0c0hlM/dHGszu2IxJURp0znWPz5OszcH+s9Oiz/iQ42+OYfNnWvXJ+Irk/F/VonVvR+ebjkSDisDVwUDXkva3fgMzB4TvV/BZALiuAvnV2sP0J6MbGwCKYezaBS7KtDEbvjvLT2re7AHvTwL+E5j7rSIBffKe7yjHrNUz0TNg10oCHAWXnIifWoIC5Wi+FDk0PoWL6x8truFVmoJmOb8KFOLuPRIWNYWFWsuogi9vAkuFoQbze6jr8muGoUYz/o3cm226kbtMMkmfY26CQpa2tClsZq56d2rS2g11XuxVQQP7nsitHRbFRRNcp5kEQF6VLDejxnYmHc216QkDZ4CdvxB5IfeFWUblQvaaSnhweZqQkuMBE5otN4nYWwtXfzEG/8J8pLqN01iM/pws5dcTEnlIOZi086deIg6IjuaQ+QhhqvLD1stEnuMAAiW1xLksTe9/6ODjaK7lshHlaF5yKsvRbBrC09G8IrAuSjjmZwjOFgoZdSkNZAYkRHQECkUBgcLuZpvv98NkTfvDcf0EBT9reo8/5yT16Dmm/Q4Yfn4c7zmYt9vwhxGviAEFUKKiX6b4anPrN8FAMsmOMQMJHCzoreUXDb7rEjiETW4nnaoHZKpObS9bDP62ZeRTAPAAh4qVfwDAQ1tQvyRIthQcuLxW+xDE5EXyS4BGALjCQaE0gWsnLi1TnrVRfTmFCyi+toHC0tITXMJlvYB2NNPVuorJl2ZAgACXxHagSN5zBzbm3Nc0FTkoYCty7yYYbNrpE+suYFhZIaQLKAcyxEu4JF2+1NTU2hdiv4C8ZmHBXCV4yMSUTEuCQQ9a03VkKsfGjkAtiY+mlX2v8i/sa9beIijkc79VPaj+XgI6jLBn1pB8DtQfHH/pUzi1hLlnWoSN6lF/f1Os8h4pDj3zW6+dHbY+lK16minoqSlAphuvn4HHpA8odEjq8dvOMhmRaQ0zy6N8zU/o9x+639S3HdLCKYabtZkB8gU8Gb79fVQtnlQieC9WpDo9fTTxoK5nszsgODC40VHQ8uzZs8y6E/aC6Tb5CtBtvjptfAlnx/fDpMd3gPDf6h9ZKLsL+WwxzwKha0lTcJ/CNNuWP4aTMjeZamlwXP83pRmoFaXNSWtgX6O0voFaAUI2zcc0Kj9pnLH9DXv6VvTZeyakmchAUGBbtPN4gZK/5jBo0prs+xuxPC3n2lZVxTa/QBRIgvlkKhgn8j5+FyDQLEQ676XSN39vto1MSrQqaJ4C7Fm1+ZGm8gjgaP+D3h9Wv3lGIbHVRfKXjvOZo6yEgqQPhF5XmY+q0+95NuUw76iAGiPGh6UxJI5A1ien/tHxc1B4EP2Dh35gzs5UPlTrgQbB2G0xyWx7X33+7gYGrrw6b3YhDlKmLbDuoW8Qn1jR9Y5QPf03JoSVDF8agyaotcbQmkJJkYGHo5lpkioRM3dB1RX9Np5tA9Wk4BLKt/uBIuYWY9rhJplfhT5l0RM+ktEyQNvZ6Yje/USX2FGvItF863xPf4f7M18+8hE0EbQzD/MvyTxwXQsrAl9rYQX/2LmxOahoJ5KWhUAHQWBXn2RU2Oa1q293hsWxF/NQSGqr6SvwRZPR1zJgWDYm2JebEy/vu6TWHZuLpNUGUklmpkE/fTO04RskiUY73zhHZpKDepcMPaDoHTTDX5CvgHmC9vxVWsG6ytF8ReK6gSsSX1fin4uOZpmRlnZDS6xVMf5YYz4K1xSY99qvetem+Sg21iXHdTmkK72erTJoYqKmIJ9FmX448WyXe1fT0ldubK57HrfMR0BQU9g7GywX2eiiVF8Oec4V2lHhobtoJXNhZdCJn50WpNggv2qtIXuDASA0gY1puYH8wr4D8l3se2Ovu/wVWAxI2MCiKR2BYtsCBobKi08l180i7/RR9tPjx6DwlNzert/5wiPjh0pRsom+NMNUoLliO1X0ofH+7IGJLiHy3FKhJn1YWjQ6zO/D1CTGbhrAoSkcZiEOPpuncJS38nx/QtxYAS40YdCsQMlyRdaCgPtgGWd3Z727wEI7UeSRz3dQC4ixEwAClJaKkezuhzEnqRlHYvXuHL+RawJPXaGfzfN+9xX4HTIZdXtx6EkzEyBDA6JGRzDKZFC/+r2F6iXQJQCtQDtbOcCUv9sq0CYrBp/huspsFJYm2SK3gf2WL2mAXH4DeXCmBU4zUX3ChzT1uwMDhYbupzRNQd/XYZpMD2otFASOrTYJLDXPStqDHM7ZK6GWtnHz+8onIL9J8Kx9lnvXQC5TobTo/BRqghK50sdW08DQ6AtpAlnrOG1qDjpn9rIeOHwCiovcrR1X2QujIUiLGYNryM9Z8FLtyXCycIRWZAE2tDx3awx5l/M6AhP+OppCO7AZkVjKk4h61m0KSo8SbAkTM8C/Gau/O/7ap/AdIMTj93umD0Wq0jnXGoXilVUESThPFkL6H1bzhlwSu3H8HYwak/Z+PxoYmsEv8y/I0ekA8DxTApM0NmlqA33wycB3qjOLsGmeLgZBe2irylIxI4vYODhbAu2zS/1WvppBmkIOWAzUvssau++pGWX4GHA475xwovefMFP5yLvbb3CJIV9Bk83CdZXmEFi4pAa6lhDgACsGr/WSsEF/DyD1K6IckGsXON6iDapoQZPRWms0hSuOBXMbOLOWQdhRjs6Fu37jRuSrmNei7dtAAchm6t0h1v7eE9OPyTGABgiB7yIqfZovUPMCGEmkCCOGnJYDnb83FwG+Sluo+6YpaBJmyNF8A20+Klq8LtMKNp3Ke0AidoEIFp9th3UCvQnVDYSWozCfAia+P+Rb2HMdh6aQskyRPSyCAAGIzDZS22wuLj2B8ndomZMs3WLlTW9EgS11VTq0RcfNooepS3ug4Lf3wsKFzQimmjzJOdx7Md8tBkC6WCw7KDwV86qlYYyxcUx90ua/O/4KFD7xeklxR+Izw4fbx9Gd9CETY4fV+JXtZCx1/lRBAwWAdo9spg2M7bolSAOI0QzGXyAgKClVafNcXY9TeT1AYWLcBwAk8RwhoVvSJKUdFBgguR912y/L/JDaTd5MR4f5KNVyzmJMl5DA2RLTkJLauC2aLZG6pqGnjm61lCnxCRj+hIZRMTWXzj+Yj65VkV8Y89GE7BIUdmBfJrQpS0LL3dQ3r/qKvc0fpLKyQEmayT+XzEdjEvxy8yoH9l4VbbSwse+Nm+aOnQmsFzbBfLdK4r3zaBqMVCx46N40sJdw0dJ+ApowpvWGdB3gekMKMV1mRroIBnfNU7hoUhpQQINC+RKpHSyCAzYgZzFDT6/YWDc3w/m6S3taBQoRibgIDnEXQKhc7AIGXrtWIht+cNLY7Iy0ETclfc5TqLZg0yp8OYuhFztXVCOvE2XmArB2YFGSL6e32HLt0LaweNbuDNyBMpd146pujMWuzBIMdsVqzZ7fG/sORKcVodZaWJyQwL0fZBNfcU2vhwIeRtJ9CnS/O/7CfDTFHk5IvrsIw14dw1ymVRJP1q7beeQzBnUMjO+ZTjyynGAZdg0DBbStWO0bwMPsU6DSjmZdM1+X11qAfavS2Q5nvgcoNIsuIJn9Y6u0MR+VKu9ImnmyCnkC3JPQDswcqSGOHO4jMPORNeOyPMLg2utoDETvfTVA8Mm89Mx/tJV1n8w3DhZi0oo+AlRB1icDSVNRhz7HlAfuNLZWcGVWOoyzWEQ1SrD94wAoaS0ChdX0XogTICNa1ZdYBdybDLg2bjfgjiS9P4ZvN+OMr01m7xDvoK+ggEUzxkp3zM61ZiXPfsoyC/Fb9F3SKvA0H+WEh4qJM6y07HPaDe2mqYgSeSTipoTeDmaOgZDxfkxIAwonjcNNSHLImfmo7X9KA2aDQ2unwLR9QO30zfmbezVeZOqiBsLfh/NZNmKahWoi3c2hrHkKgdOkRPMRRlMp8qRuEk34HGEaOSaKnYz0t8fPNYUL3YA6D8PIZhJjjzTg6M6cDtE5Hne86uNIrjvKKxx8RwRAY7m1BMDO2dwmBAAxTA7G7E8fAczp7GnOsOoVHevdGgJ66WwtOVx2bEpYGBW412cHQYFSZk+dz43UWuxJlTq5fWBLTTfcVl2DRnbM03yk88DHMOtNkttHmrP6afhtRDizHcLSRbDq8ScgoO9UJBElrqjQybVKUr8W8HWV2WZFSezX1S4+dgDVZwJDa0A0C+EGenmiIQdKh5w1ftEn0UuPoM1XpSng1BTAEE9ED/59cy/xvbHyhX1vvPBC5C9OrHqVeWnXqvvN2FNmtidtJ/8bKNgQ8wM6rDVHs5S0GzSjrKy5ApGca5DJ3c+40F3ILAR8XQxF/aKj+Qs0H2HmK6wkbecw7SVQKCk/ws1HicVn45L5SBoCgMvMSNQ8wJ3b6/eLtMQ0zh2usdMbcePYWBsJ3MloJzFXtKZQLuKbFHRDgeIzF0KmIqZl4qL5ZyXZYiYuagoclSUeJMtnvUKTCNo/Qe1nJ8pUBOS9kevmp1x0R9wArjKL9T7uC4FrxLGZLTtTA0IgQUL6IS78paP5XQlp6fDTCz8x7Y9lnHfjcd3D5PmO+HAdI+2+vd/Ez2bsTFYaaBZSmpj9m9NYxT00hEnL414vk20awiydfbJoUGLJoKnokZanYbRB5NQKKIUytZe1QL61scleABRd9K4p+B8wC7gp7ZMmMCB+vrcby3If74iHxhCSxtFmvQqPjMnHJUB6nw0STZsGW05ILgsQUDhVZjJ0VLpbTMMIoFpTAEH+3Hwv5IxRe1O7W9QUam/jCuPcKBv7DjpryfC7zvhwxEMrJADUp7IMzcSFpHhqCpuzjndJpQKKCQtF1e2hKYQczVFpvQ5SZAMN7SzV93kbQFhIKjWFdjRbWtt19JwcQOZw/qgpOPVuaQbTB/N7NAX1p6T8EW+yNQX1XyjdNASwrcvsJHHERaCwdDqBc5M2wW8BSjohnab6zh3NnsZ8AhOZpELiG30KnKRyKAVB7vlDQAD+RUjqt8fvQMGum2E/rvEh7dCkPwGMkOLTe8LK7mfzAIS+Zn7Icfy8/3hm9b2T6QfQ65nHsc6Rawz1W+shAaMxiPmnBjwZfA/+timPLwGgWYmaQjJ6Q9pF5wcwOsFTU6B0hJG/SiWW1DPNKHZVpZ4Goyq9CMVNTXrn9K2DwZQpEpPMs6IkMTFd/7OVRaCIJATaiqAJpv3b+MfpPyGtUHJsi4b5EwKmKQTwz1Xt8w/DNoNSdlW+XrCxEftV/oLrhY0bWC/kepWNeL2w9wDDvBxHm3jrFvdPi0DbMxdib/LGzdmNSWaUWLdMRlyrKDkBTZpC3mxj7m+wgK9FX8JN4LsT1xc14Gt8D2s5AKCdxWLytbje3YAQrSkw8mglcEtj2O1oHp+CawrmX4D9aQJbawqU8gkUsUsjKwY/okoFGCiyaTUozLpKdDQD0JpL2U7kTU9WaeGLjubxKezWOhpcSOGzUGJCcyDmT3SwgLyMkOUUk8eNfdw8MFH2bGkTAbOR25j78/HX0Uc/uveBSf/u0afk2szDGHzfG1Hy/R3He1mK32PaG6MH4BFGw/Q/5TMQCDzKU4TRRBq5o7kBgRKZ+xNKQtpNqEBJS7X3cA6z6kUACQy7BsnuUD4zM8nm6tEtxsZd7gIES3H0Cx55xOJl+KuhU70mHUX3BDLRaThKcogJUNVuRl+AcAXNM37uvzBg6E4WL5+VB7L4hCK+xHt1psBVICfg2Kxd1iD2935dci4zrp/MtBoxWdaN2HfNql037iznacrBvF7lHOVSD76zXpHVExYGyRIjJOxCgl7SYXUY5h5tgKCw9gkKkbUMtja5+QrtsJatBVXYbTmaa+ltOZwp5Gg5eAOH2X5WkUajJZS2VIyaW8EVGIQ6qdLafHScJaI8gKHRn4DA79c1GHkkRlw9a+KQACw3EKspeeZDcGnrrHDVAohFIDijj+R7SZqjJi4IkDYh01JrRQ4KItCtuGlpB6V1AIs+BdNc2gZO30G4D6EHx4+P/280hfic/NQSzjxvQ8IAQZm+Awaq1J+AAcbkndl75JH7G+KR/wECZ5pMQsmOsXTo92gLY6gw4jY1WeaEAA6zUa+HE2NOkvM5+Z4yK+y3tE/mncQMFZmXgNOHMN0/GxgGijnWFHsvzTvkhJQZkAM7PXBiulfamg+0SVOUR45JCei6a42jzTYKAojWNAKizUlPwKvxF109bdRTYbFoP0dpfprVG133XtTeTEOxbqy8sbnEAxieKedzhk8RHIBzwKzL0RAA0DchgBghwWPzkQz/pPnouu8GCDmKe8G5UGgqShvYlEv3tG/xHNL3yjb/FGNHS+0Bag9tKhqp/EhbRfueBjmqD7PSmJIyJL4QCExImj+MPZTAUNdDp24y0vpi7UCOpKVitPXDWY+ijciChXI07x5DHd769m/mRmgNt/HKVWTVsXBW/w6M3n4PjWhdE5qloveBr46LZnI/R4a/djR/e/wFKPyboxijf1/MjQ9n5QccO4bJumbVjJtp5xpFSsu+VqMvEm1AjB/tQFbMt7SFCIX8bTMfJTRTE6kwvBoAkXet40L1WNL/rMPsDugbuRjDnYx/DzqcNZBaEj2dzX697TcV0WbdAcbvp9iDGb4icBuDdSV8WPUTGur/ju9i8GL+YyrK0hqA3qpxtm/0t0WP+R3gWlLV174QnvwNmfWhHcTCVWp9dV6BgjQVhWIGytEsUGiHIgWCW+ai2Mj7V/3OF3D9KpPP/lWO5o5AAiskmUAhk9ZDZFKbjE+hyLkT+boHFBiCuehwXa/SGg5N4d61eimkKQD/BxVq+k8kvhSSepnGYOYjmUMrLDsRFxm4TEIMN0XnI4hcZaqKi0CwTFNwbaP9Eq8eE/Mn09JGM8rt4GCmpONs9CbEiGLUpQXSPh/jfG7zUKLmKaBmOV9IXFmBoeVonlijiyPm4psuJKeuBSO+AtpxYeZGLGjpjNJSynQUjEQqLQWiNEx0UxF4CahXAa9i5YNhq5K4fnj8pflopLvP979J+2N9TqnxeSSzdBX8+pt3lcSYnTYOcZPInPHHhzSc59NZXGWFgUK9aqSPQ1OQJNR2yzyum6WSsbQWYtpBOyJD8iI1ANcimLY5aEoalmGnWiaYs+6NX0BN6P4Ab1YxbNcUQC2hZlJPP6Y9+04zEzjQEqjeEQ4Q2ZpCxOQ7NllJ6wN7Xw0G6j+saJVNoKOjmRYD57nNlAHyHdBMBfNjEKw8FDX6gRxfAehcJgBUZJVmAhMUOk5yeiJYoSV1hvTWZhJRQM5fgcJd9nOajw5NYZumcFNTACOSIE2BAlC3OeSKszFAAYngdKRJVKBU3U5lGK0rrZd6oZah8ZEEBpaj1WHVtm1Cnc5qP0o9wvtK22jAdWYyY4/3l49F0dHQGjhm4jhPngUc+ZfpDq45yGE8gGDf36C2yaqY1j4UtXHAxDLyovInKBq02jOmI394/AvzkcuOPBujhWf7dP0x4zdA811ZT7Cx8zvzVwOdDD0eJiLEe5r7Dp6g0NFDIi6mtfbAv/UECWQzidYUKPGEaQk1IaE0h3Oto3Gu5arz1uQ1lIag8wbXbufgLFv0tMVAEQ06bLL7aOaYcWQLzhUpatpPQqxaX0X5i++Z/hXlNNhiGHVrChgG3I5mUDOgw69W8Lw7UmaF6qrY7do6MfmyRBUqi6IiPwoQwhujtYMw0hlwqsleAU0fKga+GgVv2tNuLDqVr/Wr+jRe2OtX9cf6Vb4FTOBA8UZKtFttTmZ7T48lpePcpincr6KPF2f07kQIAFxTuKvNrlctL32l9k0uDWEh8bWAf6I0ZvlP1gUsagpBTaHMRyhmqrQrgYu0zv1A11UAsFaFpPY8BfnaTGton4JAgZPhel5HZIErhR5NPFC0TmsFyPOcGGBo/hCQbb4njpppdwSWouzFGclXVsC2JgMCpSkAqzVaoDStRFCjkIYAbJn/oBnmpWsuBlbX+y5UCGv0NwTDpkOT6wTEQe0hVv0tjYGL3yhQ+Bky/Eufwgdg6IZ+HL+rR5w/JMH+Nt9TdLW0Q4KHQ03OPTwZPdOecxOOfGl5h+GHlfvUBrQYmdJmS0NKiq01MKo5dgGEbKpi/mskh3LEkfnn2KQXB0otdUFzkqRTlifpyYR554NHRE5af/CLrY+GbA8JGQqN01bqnnZqI9W+Y4dX2sXzR0dzZkfL9CYtKSegQvJEQ4yACrSpaCM4SFH2YwJDm4lgaRhAOK4pua/+0lNilE8oI8uPEL/K3xO/Kn29cK1XmXfWq6F1Zp6rLmifR5Ec6YySI3pdHPb53sjNcm+Bwka8HBQS1z2awter7PdX1u5ngcQ/BNcrgK8YMLhWneMmEFxoUMBFGv/imY52mWOVFgKKfQJAxK5lKCJrZcJ2NJf0m+uGHMHStGAAMdoThZ+PgOA85cEHxC8k9C2T/lvI5BhGOX5nmRA6mnPMTAMK0TMJLgo19ayoajMPsPCCpmBq3EX+AgQMEJ16fJOEKTrGC5GNLw0QHE7nHxx/AQo/kOj7vQ8u3mkOJJb2h7pOkWkJaBD0NKlOKRRttjf3BmFzgPQAAzsfZpxh/g40J0iQJTqgNKrrTzL2gAhSm5Cbs03MRsTPBfE0EHrTlQ5rlESVlEI5cHJTGFZYax35+PvQWoSxfJxXX4ssyE+hoNQi+bCnjt4sjQqYiCM8nMsxGkLJYGLGyZBAjDNVKnN/gRm/Yhi4ajHagpg90wkSDXQJaI3Lan7VGd0K1QXZjDuhxeBqA3sE9xqIGxk3VtwVQsz1gXrdKhitiYSq+qTZ3ZVuTSHvAoQsUKgopLtCPPeeqKP7RtxlPvq6b8QGz1z6grR30XxUeyywDxK1ThTJrsCKDWfXM8SztZvWHtqpPIIRrgKq3luXdIqVXBVUmsJoB/I5tKPZNQV1qBzvIkqRRPMedFunlgZGQkvmRm+ClGz7qfPY+wsQyvQjcChX8ziay3yUIZpaZR1ITrSk9774zO52Wh2xJB8CLQeQn8PSMgp2IjG+BvFECUkjLP3vg8KfHM16aY84Y/5h10flvgGZT3WPD9dv2CPKZaeLAJWGuTfOYljnnBrEMHW0/fNQLUlQPqFnyabcfxjnclg4asiOy+WAY2NxpmbE3XbEXjVSGgNNR0fkisBg7bIpBx3N8SKzpr1Z/5qR91BqVuqS/eloXow0mggluc3uCEC7V1kZgQGVOQQrJTOV5F3AoEXlmiEB+GIbfoFO0UQ5S2Nhxd3muUUzUDmUB7iaFmRCapqRRDZ1PWe51rHIUHoxNbvWPICyXdPRG/dobEFH8/pFW/ENXC+Gjr4oW46mIG1AsmQBA9NkMkEi88XQ1xdBgOajncDrhdoweGO9ypR1vW6sOxH3xkVfghzNKzcuxvBfKBC81oT+fqkvvqI1BGbsv1hAfPH6Gk1iXQAisb4KEOSkBmRGklP64WiOAs26pgl0ldaQAVxKk9ZgVDzBF2WWE0WCDL4JIOavLQDyT/X4XHQ+Uz7Xdd5IrNICSD0XBREFQwBRYcoZ+IraHvRmWiL4jmLoi2LLFTV7+uL4WNpHusGooo1kPuql5cHNvrBZZpk9xnLi2sKfj/+deQrf5IvHxY+r5VrBp/f3iLEk1x4knTZATHlh5Y4WYL9VxjPNAeGR1lILDDhco+i/faZZedFMYb/da0nq4BhoB3M7mttElD0bOpKzFGIGThAQAuO6UrMG7+yWeCRjCAjVhmMUWgku0jdpDS1HXwomwsqyM69dU1hWrwkJVH1G1Yds72IA/Ob5gha5jZxGSykzVKXNO1ueMI0A/V217y+ZFyE1CeQdVRbKw3STcpeZRYrWdDb66/YU7WhSopkRc1NrSGCX9hB716SxnQWi7WiW9mAhqQYKwf70/SEiijcDMWbWkbWA1iBGsHKGG7d8ABofAORoVnQQtYw2H8mZrpDX3Gh9VWmi+66EaQlNdoIFagMHf3INFmMKPHiFj0MbB2n3mFeh08+0MUW583kdfGL4wwZkEqLXbpYKp9/EHM1qp+EZugfSXRz87CfH/7KmMJ0+DTuD6Jnvr44PmoI7K11DkMrXQGDRHWIQqwHhZHZt0zatYfKPhtCydPiAlYTBNCi2/oy+KI2hVMFDU9Aetb2hSK0PA0WSgANm0Y4su2vUxhyK4U6UqWKTASkOvv0KkLqtOAjXFKpFA2PhTP5fJOraQ2kKFde5W2MAS1u8Ul9vDga0z0U+g4gz7FOC6Bf7oTQG+hTkS9jRJgkx9ACQsbqOQFS9EJQso2knMO/ua8y7i6xIM5wAVQ5hLWN8t58n9006eSFT0UavYuDr1T4grHII7+s14cJmKhDvPIMa2HaKPMoqA/er6nJv5OtVdblv4HUXI/4f+RRKU1j3xkVfwtdLoJAEBTPVhZbtmCU94qqtZqNEWeDQGEIrLJRVxDSFNiNxFnT7Fnp2/+5r1xRkNvIlM8DFBdPz9dje6jAcgsFABEZTEPhEgwta0DTAUfsTlBY/ctFFXOG8nzSFIqovVPhIBUjIKEShKMY7V+YkuZtFh/JIaARKo5ZWwAmEdC7rHHFNuH2Hpv7/qSk0EBvDf5huzuOHwBCPMwwQIi3tlIjnfh7vd5+Al9MM38Cg77XkP6g8k26sPKU1+j/TBBjjaK4OL3vzTI5x5J/3zWDIBoRyZkpDmDkNS2DA3b607aOikByaBzYFnYecJHbRDCo5uDqOImqp4IzaC8LjjtbRz7Rbsw/HzFaDqDUFyKdgjFpMLGXPDQSdfNrLu+NLWeskAPVywpJe9QcDJXtX+J8k2EzGw9OBn3cxqL0R8aqv7UXb7gIIpvUaR3Q0R9w0+YnRm9YjqdvCHUfLEyjwTM0A+1dpCneZj+K1EferNAR3NL/c0QyakHLamD3f/h1tLrWB3sxaLpttHZXg/tgk09YcMOY2MtceS70W0sn421lPAAhFHWmm9CVhaBg4TNwZynM+NPSHYD0VEssoqWl7lfsYBSmhr6T8otsTKBY2rpJMoMBTOZuVVsxlD1uLm2P8QuCmSYhp7nzu2RA3emta5Yv7YQqXhuAS9M+A4X9vRrOOT+990xImOe224fh7EQcwOMM3YDDGPSWezFxnEZKYRGsRLTU4QAzYvIOACMWv8QACpRlIYH/+HbbvbU6aR0oMINR5NyB8SINUbK6dmhwubBNt5qPuPUEhOq/cx7S0jgzWz2urzmk/mag0XN3dNTAjU5EcybUq55I01PlkexXzFLN5CB3umDeaqQHfUksvedEmqjCG2EORLdAaApkWN8fB2sh7QoCrJbTC50YEt4PE3fMSyuFcQN1OU/mhXOiAaE/aAzWF3IgnKORuP0PsSitH88xJiL1r/aI2JWUDwuJs39aU2B9FbtGaQmCNCV9jBIyMIaMNMiI1/+GXa6Gpviv2Q1PQuk0Nlmn+hrqfkR1iLVBJjQtRmq4VVOG8I2LMVD1znUQcyfdzJBA4pj8c3M50rZE6C+TR0Yzof0VrRNQozbpneQMlGCKMH5CPtPN5HM1FZwtyUleIe3T7w5zLvgzGT47/ZfMR/ggKz9ufQOBj2oH0dX6CgjuVXVo8tZXpSABjRmpWiFnUzqSFZvxxEoMG85iLlGbLZIcIZ5tkLIc0NyLBxsWlgC/tRRs3Fu4uL9zhvHbZVpE9TyEX5y4orTUFgYKc0qgoJtAqmTPO1VIizWG3Q97TuiPDJJ7+hNWljflodA6ZKq7YHXgnU5HCTo98sAXHst6xOlpoobdMjJHAarvNNWYjOkWBExQujpmv1hwU1ErJFug1prA38uKcgPxVC9xhY+8KMW3nspZ6XolYLwIk9xRGOU1brE75GRwMxHiGOWhma4HBbgAox/Kv0hDcfEStIF6MPjLz0XrRbJQ5/BcY6V5/q5jMuqOAgaaiCCA2nc+L/piF6pMdjFiqBl2KPIrEujneGGpafzffpXWOCAyBQyuQ2Sg1e/oA/zontelDa3BQWGTKLjzk0KfeHcznjNYXyePOr9SdNxRqqvk0dT3y/ZiZ0qT8RC/6/jAfaeMoiWBVkpbU0DloNrqwuFNdXaNAQZNn/nvmo2HTYYP8Le0AgDMtHvkTczvtvgki846wtAaDuf/uVJ4/T2vGZYQ0Zh2T1HpgeNoJKANMH9LC8req6KaAR1pM/caJynrmlHU0Dt+zojbjqeWaQXNSOX8DozGsfDifWZSPGcSMs/Oe2kjMfxzJkWfawIQ0hHdQCC8zBDj23sjzt8p5Ogul6jetSGLEpAX6o3xs1CAKA/7ndw84DMMQIzGzByU7IBlLT8cy6BwVo1G+g6EpL/OlOysT2os4eqmDNHBQaOK2PwLPTkSWVtCrpWpuh0xG+jNz/PH9BN8gIUYuStJCz6QJr/pF/uGgb6H9nDYWsF3QerTps41ZCZmN0p4Z8xLHBKbyHu02EXHQTd0Y4Dgkouz7MxYGYJpnyNEcTu8zPoLve6dj/d6Yxets7Lc29eAFxjfe+AQeAushJOON7v90/IWmMEwENvDrmIqeknielT0+Tg2H/n00vN0Ts+pDTODQANQIXsYw3Od728xjGoO+6d0JLclezz2/ayanjQYw6Zq9PHvlykREX4JpCsf9uOl8VscPw5FTuSZFlRRVG/PUvZ0My+MkJ0DbQzKsLsg4SfQK2VZL0liA2zwCoydM7yWKQZAvIPPiHcGO5jQMUATAWcEjWdVKo5zCE5SUQppClgQaNZhKoqWmENpnV8OOltzI1hBizTkoDkv609pK7j+VNjfMmJL9Lh9C7l/ASuz9C9o6cq1ftSlSvKgl1PyElGkpEmvdtbS1ykOidyrTO0PzH+h8zpu4USYh7PEVxP2rHMtMK1/ChKQG5yKUf2HXJDH6F9ZNBt0OdEq94vmySWtzKa7zX6YhpQX9DAIPaXKlUVwJagx8T4BLbaPNaYHsXdt697Y1jB/MfziaW1MAzUyY33rOeEFGUFtIZG0lRxPUpDfPMABPRZ1AO6lpnasbyfDRajMu3Q4u0khDnGsMPaGNAhA0u74Fk8Q6tIUXljQAALUisPjDi2bX2oaznpW2hZ7dH9r46b+lKYQav49hxM7cnflWhg/o9SgjrYy5nnwftZDWDDwf3tK6XjF1OiVUR3uTarq+Z74TpR+I3szb5i54vkNzGAfzpOlZzdZlOTkg46uoul8hObFNfoVYBARfhZNOvrJ+UlKi0Lc5CUmbzAQSOxzm5VXc1styKm/OHq75zJvDwmOdFLNU32x2/BhH8xl5pDRpEVlmZJSUNn6gkRRPuskedI0VLbVaaCUUxeE+BdIDzTdVVu0T0PNAQKYfNxI3Nl581wuBGxvlP9Cz0iBibU5A1GY0ZI5J4cFt1cgSCjJNMyizUch8lAKLX8Xct0xLm76F7Ils2NkT2rSZPRLo/YuBgX0BA8RQKDovYzKK5CIItGmJIL5M0i58TsxcANOaOMsZ3IQIG6ejWZM2pTHQHKXFRB0QBghGSnZwKG1O30gAkh9hIiRKOycNjDDJyWjyG8i8F27YGV/C4l7MWs03SeO784th0S8gvhDB64KU1RGJ4z9Y7nuMElZXm6UI3tSC1Xc/xYV/FX30bj4aCbAZ74NZPp8bU5E/96ncx/vD0w55FWKUZ3n5yDeA8Kb+Bbq+Djqj9tUzS/HkGriPkNOn9uDOZ2kIYeeKnlE+SokYH8Q4n6fORdxF1IosQiQ2wTtpKgI1fnBwSlNAjGKdHO/FX7NrV4x9dy0Dmrk57F5s9HA0dyQGLO9EbUga1/nqUibWewDhzO8aagHCRi8C1of6rh+g1Av6FLIjNXw/hqaNnl2eJakHHcJ5oxx8dPTGDeCF2jeAZhy8gNDmOfIz3L0/cfas3QKZmpF9G1Nga1OjmP2V6Tze5WguCf9FvwIB4q40BwUQFOQoD27GU/fBdAFrkH+Yc7IXBCtNodcfj2E8VR7bb5fUXGAUDfwzvqShb47L3ZpSz2J2DSELRDWnobWAjY4aGkDQmZRNBl8m1aAZNQwkjGSCQLI3o6lM2IjNfdmdjxQYjDko2X+k+yAd0eFbM5mzpXgEQ6XD+EFsagu6PoGifIxqw00NQU5qOZrZ/mEG2fg5IAD/IvroGJBsoDlcGn5K0Oefg0daOSOD+jswH2Xmoadm4OUe5b1J+N8z/aL/MS29f8s7AMgJPOYjDJJHYtm9nonYGsI9aWRAWkVzpZmUzAR2zHLeNB1Rotn0Go7paP42atnlBKOTwCh5mk+0/DVoIhC5qUeiv06tL7lSTjlKYan2F0ywP0OgOg7kmqlc1352RzPwAIWW4mjAlp2dmkxJRex3agWQlrCy1fUImyfR/cO+a5vxi1LjC8mlKxK/am5I/E8BRNxY+EUtrcxHEaMpzI5hMkOR6e3SHGILFEZrbFrhHBUtaIe9se5XSfr3qxzL90bcvxB3ljmJy1qUaSlpTkok9yrG1nXSz82xoOU+jOmPnWP3tZgPSB/VzDVvRNKqnLARcjSr/aV5FQ3XuUwks9vagILm4nDt6nql9m5YaSFTxh+CDF+gsAQMYPRdlC9ixYwPSdSMchpJgt+4CQy5agE/LI7Povs7JNdnm1yvqJeOQ5obUhmHDo6riIUrbvTGUSxlEQhqPw/yh3Ux36LZaMxH2nyqgeCh1f3k+Is9mo1BfwCEjyYeMe7w3yeoZLyX54DQ5wPVH8AUnt/rdT57vD/m3glWOAHB3nVqGV5efmifAcMm9AMQk8wmD+A6wEsaTlpd2nRytoUqXlLKSFCB2ef5qDsHwcykRvcVeSmLrt44tSUdDg2JNvN0m1Ye1wZdsnLJ//u087kBIn1+wgWFo2/ZPmrfUaf5fW80wHO3ibSzcRhr29NxGpuDOakR0bzU6xXF8yzR2jXGuW7pMCkogJqCOYxlUpKjWZpFO6GRNDmNXynkX1KIbRaTnObLbvHp4pym9WsAcCezaEWfhzDwFpAn1xayfjNTYKu0bdKp67R7Mgmm8L8J16ue+q8AIkNiycEaUo4we2wW0mN5aXwmSU85NDXjQ3Q/pk456Susd8bKMb7bKvEQoONx/eAppyUGR1nB8T/n92793fEXmsI70x0G+72jGY9rZ3r17Mlk6v/59o5+d0y+Y/A30xhZ9vnuJxN35q93SVI8NYmR9r2cd1MQERtC+s+awmgIpink81mZj0oSqDXvZX8mM+KKjr1/85ZvAdy3OTnWqCkkF2veiTsmmiM4d6EGkLN6Z8nT0s7y1SoXry97yg1M2U+NBlDfqlDTdYSfXpStFs6+KXNRVbQdnmTkfd0gwAEbePwlNNmznNwYZouSYnvtKa5HBbz4dwPxi/d+dVpwJdRF01KHpSJxbArTwMAlMOiQbmmP2sHaVYdrUyvYd803uHcvcFcOZ5mVyqQkxzPupPkIjyW2Ny1JtNMzaGmGXzCUV+deErUFDTlkiulQU1g103bd8hfl+I2A8SXIj0C61kS/s53y0BQ6yuhiQISA5akpsH6pUMyl33VfmkLRJmmZmnNhg7Qh8gzSU2kdG71OltbIOjSAGicVsFBlaxHGK4Crd/Bj3eSP4VPjaL4/awoIC0Sp+QylKcjPcEGmo6Kn0RRG6/vZ8a8dzU9JXsz6kISbgZ8S97MMPIBhypi0foWeNab9uU4mEnx4f0uF4feMcbk2YKh8SPKHlJfHs94O0axzz+8cQJFpwctYSceklSmThqQVnaUZtIqs3wt0ahJoNWiYJzUAg54DMgWFYW6z1U8MEp9LtVXQn6DpbUpzWEicjuboceyTxALjU1DZOsvxBwECnYZh0l10nYxmHmAgs1H/HX0sR++ElHImB4JzSIqBVVRRQD6GWpIkNWHN9xUmGPTaNUFJvcsdU1HPT2Hayo1LGsLWWWmJyBc1hF0b6WQCHaKaBU7UDnLvFg76b2fzv/Rg/hxgKI6zCmjICXvpj8TY4Hf2LGbQqtcm/0RNkDu072kDwHwF2OjZ4w0OIyzK3FxaG1p6twFc39OfE8MLWOkkDYHC06EBydncaVlMNZ9pSTqkLb//jW2/tSSA0X6mUYR2GwmcPscaPcvTIlpQLfCYP9cOzt/oc2szP8SFf+FonkHXgsODob2rNw/twK6fqv9oFP4uq4Yz98Bc9/kJMHrH5/efpiAxiPO7jm9tRo4jTaGoZ1t8dkD3VP9PIJPoQfMJcJ4aGThuO1pDkhEHRl9rDII+hJA+lse318BdxmA/tI+laS3S97Rh7PMegcH4DI79lg0Ujlh9I8Du49R1WJ3EAL5pv0A7mJ+a4oBBlqmmzT8DBomKLFJa9vUN+R4qn3wKoxWUVG3RY6HJW1ouObHyxfMNbRS/8sXz3dqDACDy5q5qZUaqaCJqCmYqUngydl0XNlGgEG0w6kxhpxIDZHKqkNS0aJ9EzajVz6SPYnYMEG2WcuHCWfaYFBCURL6HWNvRPAwYtP0HKPiseY+E0BzVhBUYsQRB7hCS/lUFY/YITKNUWs9JSBsDrfmM8NLOXucNka1ZFDiMv2KHQEVMvYImlqX5shoTRj/my6ejWb4GBN8lh/PPFYV/Yz76xER/Awqf7v0QFFyr0PE7jeMEhW3535npR43g+T1W956ngPe09SHtk634XPXwMf8gJ6JABFcmpSn3qYWEDwZzqpUENHQt32+sGtQCykS2mWmBgJKAIo60cYhgcPas9S8b5r77PMBQcLDJ+vUtz+gjzRNwoFDbiJqr9OqufDAM4Jjg5zQYmndCM1Gr26Idb9dZlkJmPXwyH4Hmo3gVUHQU0kY5nqUV3Gz/MRW1L0FzF8x8dKEA4Mq7Q1EvB4U0PwP3YA5LK6ZNTWELFICbWoIikIp/5yGsCxCqdbXGVSCzzCXjumnOSp/Faod1RHBFVAkVRXuLfgv3wcx6GaXplBbgG+coIsn6mibCFO3z9SBAFPFQGmr6MN2RvCDbYUYhoitb76s5FeQL1KpGcMAAQo4w4WAgLVkUvwgMWibe1dRomsw2B1X00OwbrdV1ZSry32M+KrPqJ/NRBwz88PhfcTQ7c7VMzWgR89wwXz4fU85Tyj/f9V6Xz8DwLE/M81O+KS9wfldL64/vPgCtnxlmNPnwlvfUgvT5kpyYUOLZOOK8nsd752wWUn1Q30z7+bh1pHXJGifhdteRfJ69IUlJjz7/gHbxHe3xbKM3CYtPTX9GM4XjWznw+xrAbHavZ9WPcaSPai3J0PvR/2TqSWiGR0u4Iedz8v57GfHhOvT8B4FhBBcXIty5bM8wbZziAmLVh9+aJ43KBHg0k1o6z+AACIgPiRpoKaKBIi3N5T1/19Bq+kuP8e7vsnc/32/1fn9/HFU/nOhpadqFr/FBpqw5fCw6fTovOfmaLuR0jqa/g+YJgMc9S3v3e54C65jjYPmNF7T5KN7582+Of+1ofjJReMXVYBx0Xtl3ZunMT+eNk0jO4+lg9nwnYJ2MvfOkdagBgqedA/gs7/z+D9/djETp2877cV+imtoh5zoTcJUaaOal75E0lmyQ5o8r2mlc634FJSTK3Dpbu2o87TDhSW1+/Hl7evx23ZdW7uf3Msan4CYjn6egNpNPQQNXe0fU6/XB/Pj2mqqtKVLOV+I8vE+0HpE0AmkKOs+1JiBO3roXh89hynUQmDTzKchUhP1mPlrUFEYr2DT/lPYAlPOxDn2Dm/A4eZFpzYw7Vb8OCEaitIQmGkl4B4HEEFN3bjwkg8eYDNJ9yMttY0HmtQ/2+6YB8ZZllYW/S/WL6WLd11+TRDLaCfXMpoAjfscgDIFvKiSX/7Q/gvwDC7MknjTtiFobKjHzBw6fAkYDmN2ax1S0WJYWvSuNQ3OYNEbGfDVmI0JNjHj1k+NfaQo+sE4z0FNiHablYaH9yEEkXraT6p+A4UnSVq6X8Y12ETi/7WlWmrI/S/2nVOp5H/k+PPv2Z8CQxgT7qTzLfUr7Gg89dswpmymJgmGENm4m/FRtoHzfgcKkZaflh7TzGIHiXSv4nabgEmuy/pqdWk13srZTWn+2uSd5+z/B2gD78TcagafbM4cz2QWDef4Ia/V7pgXI2dymReTbNezsdVCbNQAcNvxKe+7XDYwztGmtNTFj1AYbU6QRn6SNnH5rpvuk909jYFl+5WnGboDgUo1XbScnoD26/hhPqvvkk2ky/FsdiJBjvoSFlmKOU/gFzjBtx8z55h/5ZB9aQ2sHfr/57JPvso4/xIX/aEG8wxTw+FB97DD9p3S+rVzrgLo4yj+qYVrFO4N8aCAq49P7cxquv0F1/5T2RmG/S3ve93q+f5PfL3qbITqDRVmyT6LzDrVQQPIjBjM8DWhphf/xmylLRHZXi4idecydD59nd99B4WT8E3l0agsOEjNAVVgMQ87pdQeNicFPVPTNom09SIoxzdh0KMfsLH8dWdtm9oJzkFRLxzJmBzTZyrUNJzLtfiJaei9fkqdprkEcaTd8obtZDE9zFhx0noCg8GLbjDIqbUc1w9Y15rf4efdhOL9Uf6idqRbkMoa/jeZWNdebVGH1lO+gadvyckkLsNgikhkDUjQGeB5n0eueIdHDSu/S1q1KD0DrITUdkVC06F9/SmL8Ck3D4jfRvPAjOGDoO+lnchDAM+0ADEUnSTvYlkYtAeNobsAKiVc/O/4aFN4BAZjdj050e6Lgk3iHYbOj+vxk7N/Xo2jJ01wJxgCTgwJEv/nhWQOs47l3APhkqvoJQLy3Bcsg5YphIU9Fv3mzjSdrGDUG0wkIjDcHqLqu4JiOeUzMWkUoBM9Kfiep+PhLrz9trhaOB18e2MPL8w0set0ZCaWFBFVeYDSGwwlZgyOboQIVprnI+Km0C1zFvHM3KETeSIaC6txLXKT+xOBN0o99/saADJquaEqSYxh7rmke0nt6eQv3JfB+tdkAQpuHhNdi6qtW0PW/tPs7cZjhyS/HrNhYkIYaGnvy9PIhGOoYQdRaRaRhdzQfmgO6DwE2Zxg4vLOFj2kf2McjTQig9BE8mnZzLADRbRtH2gg4D+YfOYrOxz8+26Gs4pEKQV+dprlKFaKqkFOZkRbnMRAsXGtQnQjKzg9/cvxHjuaTyT5eaj4GZ+T+p4dHGvQynj1rH2fc8TBL2XmuJ8953/IdPorv870Nin728e354Ud+vq2xOIMPBIYZ4Hq1JORqLnZ9cwEVLGmNuCK9NZ00MRIRsoDjqA3ldBOzus7HgjHPbx3JXS1qMw0wUtT5xFGzJotEay/kOWM2sufN0TzmZ6O91LwKpw8CbzPqbXk3ZvZvGlOQdH7+zf1T8PnkcIbVqd8t04+ZgMbn9a4FqIHeJwZaDgcGSsQDBgktejjzVdjNPRkQ46LpDhm478b+4GjOLFMl+W3nLX6vttEx39NjwIEB77TSj324/9YAlhxGw2F5szPw3jc09jQTx7PukLUkyPseQRL2dgeIoZuHE9rLPwRbTJqbkpjWwl1JVeNofvKo3xx/DQoHEDTBWMQEHSgHaj2cuQco6ONFEADc0dzvf7LSGAx5SvtHWjzTPr1/yn17z4c8R73/6sgPV/yd0CrEbRrSonbOsrmqMALoxR010/I0yDgT4awi096qDTUA1ZBplXv21HoAiwHMca2Ud4W1Q8jDNQTTGuj30MqoECMhlxpgyGFKAdBWQca2CQxR4ZerVuzMTKyt2PDEWgIGl95fdCze2AwFRdK53Cad0Q5kIjoDCNLuifOMNtL7O+8XxXRpIYnRHk5NQaaw0yEr6GG/aQmoxb+Mtu7cC9gXXeS72vHe5uGQRioTG6LnczQGOHPLB92gXlzNWVq2NBEkLT3izKK9Ja3H0jCv0PiOXtOdjK0Z/pg5m2YP6SqO6vV1W77IiPX6Da68WhVo/pEf0uw8oyNNOxhT0ZhFR0Pe9qwDwDNtNAHS7EOjGEezTE1okxPCTFrxDCn5/fEfhqSiP97ta/CKqqHezEjOxNM61ZnZow4HEaKlmk77lO9D/T/ne1LYG9v+WCfkh7T3TP2sxsbz7uE31V9M8Sc54h1HfTQh0fbdtpOKQOLhxA4rKLqo9EGFloXOStu9Zy2eNWqp3554hxK7N97yfmGIJxzOTwKAMYmkZNcmN6JsMb49eaA5FOQK8kM8tIKg6STbSWw0rOiUs+cwIaFWhn6r7HxoCmln1ekxZqbp860B5QPYjBzQyqBlNgpu0UodJORjYFp3mrTEeVcHeEFGQOl+atQ47nn3HNnUj6H+GDocjd8eeEvz0Mpg++P9ME2hx5uVN2mJdK0iQS3tSdP2vcfX6vqZt8aZ6qx0H1/V1MN/xqphI/1hgtezVb5fK5/Kzh46hyXlOdi+OX7uU+gPe368V/gEg6r046OAbkw1yMEpH5Ekn949nYO3tI8M/mm7tPLiKOsnDP79jfEhbUhALYVjSL2laUZpGHtJTRqrvAvA1uxIDsaSqO0PlEkyASz06o/NKGzAR6L3WuhCbaDQ20iS6/q+ma4G+h+t4TKTS1GWW1V7pIng66XZ7QJPc64DhQ6WVJTNYANl/w+kln1GYm/ZbcdhvPdsjTrLRcjRLB8Dl6wwyf3QCg7G8bjH58oMuPs+rLzTx3ECTIPK2cTUDsjsubRJLmkKgXvV9+616joTexnkqGGJT1rvv7o40JvUOO30l2Z3R+pMkNlW1dWChzO9Rxe+MS1nxM/M3/G4EyVHpHjPr7Qg/+k35PArjddh3MO/2nQjPgenb5mQhvonjwHL4WBm+YdzeerxSZOw0Wh1yq5Tt8ghYP3++LmmwE48K3ky/bcQqQ8f6B9xMuqTqcvm2+/u40+A8Ej7AAjHN/22jJ8fnwEi8Km851e7vFASKSU8lhjmBSzNMA5Q8H9c8AhSF4eVJBIXgWBhFgcLVOTM5FO1ndw+/SW+I7J3i+pAwjelHeAg8xFbxzQeaQDyicj5PFFZkuwLEDIDcjRngmv8l/mo6lcb4vSKo6Bzmb6FcSorAul+AENCzsoTGAYQIgd4OtIJ8lvwPcj2ZUhbGWDJjuRRiKE2UxKj3gSALfMRlFbmo1xlKnpxBrvuNZwaQWpZ7BVP4wazCCCmdoB1Q6aZjPjVRVZpVPkQxA5ScnHqe2B4p774cP09I3QxBx1hxHcfTuXhdV4vHwWnYOOAEMez83KjlQ888j3tWRfjvQ0oj/wNMt82wcfj35mPHv4FGCDAG6cR652V9LOpBgI6giT9fY93CSxckvyUz64dJB19n/msmI/HZ2njnUDVLRPhYhDYttFhHX4fQDsIOVwrLe0t1lziCsH7pzzyLF/Dsq3RXQcfQzLXjw/Bye3BIB5k+j4wJ+2EBcslbLJGdgcyaNd1J2Az4aNTJFBwsGWamaC0BTX8Rync0tpZ7Y5qd2AfneC012z2UU8x3qnbwYkx7z7KZzeE5XQulMiW5DuiSP4FyQhM2wTRRDRwGJ52VzUbiwd99DvPLn77EvqGeqgK35/PijJD3ThfKQfpOG0tzTr9J/yuYcTwJ+18fs648D3tk0np+Zau3hHZ4vmGdgG07f8o1wRq51nWE4ff4Kzj5Ok6saB4q8v3x987mmOaTOygt1AMzFo9kb2ByeLCVXIu1uCqSjvXe0pax31dUDL8DAh+/X3a3x4+ZiZNpDLkpS4J5PAAZ6ApqWpW9eG8RawuE2XqgGb1KgKHCmcGtMpoUj1eWcx+1N6zprSiN8vhAtpkItpZrSRPbcLlZFhy7KmsJjQN65MO+M74vQX1VZ7rBIRuUoiruD+hB647XI4ds+hFlcloz1tBxqlVO9tcA4Wk1jkx5qMCh3L+jpbA97Qvwv7Uood/IDFzHez3h7kGowFUHVVnDaLkd+4VyIslSTu4bHocX39f6vfEnaGlkc7oo8RDolTowsyIbwGPC0dt+h9WKM84UqGqN2MbxlW0PR3vDNDIZKJ5unJpoPW9nvp2pMGIY7PVCxAgPBh3p83YUtqT4k8+MVrCfNaUpGVkXKp/+j07nW1ROwTmeb/rNW0Gq9N8y49b6z/VFKZSp1PZ/jwNnzpUEtKgeUfHFIe0WliadeqUo7R3EDhB4s+HJHpvTnUp8NQCaoQ9y5a0/ymtmSBEbkd8B2BpnZVRRrL51/U7Ccz5JItzTVO71idMYw2L0mSvg/yn/M9DM3579SnfMyWs4bulEyjfAm9SuGhTY1XYfqt3XPgQE6r79c+YsrSFXs8IlvbUFPSOhLVeO7Yd146ABKufaF/JotOmBRHKA2e1qNublhAzSU2WRK1Z99Qe3E8QwEw5mC+v2sjPFZOm7TrluGbXMB+OFmkrZdq7urdtXIpRnA01TlsyUYTS/jyem1Gn2hLzXNOKU+lnreD0TnxzhPHGOL/tU22bpxqxn8K3AYYxvLD7Z3kfq9T1/inv+xchqYCcMgo9dS2hN0EPbnXIc21GrUE2dvJmnJmz8byr1kd0Tz7OeLs3LOyZ9icCGsJTecOkBWdiRj5wTmobE8+8tdf6zFkjJVNMuXJU+aujVKpkX9wl20S0ug6rbezaNNOdZNWsess+5tjSis3gyZr7Omdne6em4Eu4zd+5GPZQRfzmb9rdPCLF/x4dNQB89lanNdMV14uetpsLFTHN9Xm0XWgyrFPrFBXTv9kqnLAmcKDE3yGUbY46weEAC6V9YyY6PsKaxRl8OYvJYRXPmEDWptbYO7i9KnBTVN87pSS1NnBvaQrATYO/VtlGjH6ueWXbqlXeKdMWAItyqR8zp4GcPwQmA2wLA0IBWMgrpeYIlpuTIdCrpGoLVfTZ6vEc2Jb2iZW7iSgszfvpTPe+033+Zj3a5KMPxHeaQti72F7POn/jC3g3NE/au2H3/at/evyFoxkNBqpMxZzn9F+UqaiAIGhCCnz1ptcxlVa8pcYN0Ms99xg/IpJEaPnAhLOB/Nz1Bh6d87uvdO1AMDDljZTObh/+y7ONiC5DjIjSf0cJAZrDuFPLaAEchnPNSKJaOG1MRVV6lZAGCDG2K4xRbkhxVt/JAwie64A+1+ys5993OvjefPSTPzsECIODlsjWbOl/Hi+hXwHoFI25bHQ5m4Ggo1mLuY3gYdE+MiMpYsgdyg0SSjf4NLAYYv4AEs+PRR5TP5q5RnBBQzJLOoonqIz9ZA7kvQUAvBdMWzQjgaGpmWeoc6Cd9WE8SnvNCCDQpiK1Gpr/hcxHYt7IsQxYFxsOTO/zew8buWUQw3UAwTP/UTi+PUStkvvFVdwc5CadeuY0FcGeVYRP2gtmBAwhn9VS/TFPfoqONMex6qHnPwPW4x1vR+K3jWPHX2kKXWSbioYFLHagNo5eK7m2d2KtM0xrBjtaekvpt6EPyCNfMb0PH/yW9rieSp/f0/8/ONAbcVTiYHGr9wnPUVd5dpkihA7mKXMMQz3F/hcGcDQBXn4Gva/Tc0hFE9e0R9rCaCAa+ZslbTI1WdIFAJIsE3vCCbsXoh3fde+pJQwoaFS+UYfNUThGbtOp9Y11x/iZh+hzEqerp/uGMSeOczuajWm7k7kZvjNxlnU4miXIsK4dDeV0+EGzOY4GgSczRJuFEJiw0rRnBA4gw19j2qnQ1MRWGLFWyr08LRWlW3UUczr5S8teAgBpArpWL+7I0SRCfCJO83EUIK3QUIqeHwHe77BXwIDAXmRprbHzHW+87hve52N1WGR0mkb0yWIHDLphDrp5lK46v731Q8U+1v0d7D59znvaB+EjrU5vdfn++DEoXP3R09EyEFxrTEZfvP66Al+r9u79WqD5SMxTf9GbvEjjT+QIecoLsTRvgO8+82cfPscHYEgHhncc1nO7pXkAZMa9wUaWzDnMnd+LYIgiiTP1ZinqYrELOyWXR832ha+romcLGLjiD3bPjhUXKbNIppzfgZ0bbSiJ1drCzdDUY0Uf8tEdgZ1BabOMYPsAicU2eSxz10xfaQ+Rro3MMcR7Gp4fXWWE3/MO7NxezjVoR4OyHPMKxy0mI+0goTWK0ucMaJ8CaghyHpcj2cHCHM7q77eB6gDQA4nSFErNFv1T8dkXqUg7pe2qu5zFG5VXDuQ7gZtMP3lvJ/vxrr3iYPewwS0p0eaj9ayqsC5sOXSCiaxabUUgw/e0XCUcSusJZGk7UYIjLgoNj2nuYSQTlnZ0uZPbUekZAs3Pe9T5Md61Y1YynfxBH9Y4guUk/sCEH+W+84wBs6nT1Pc7MPv741mnT3X5/viXjmYb2k/vOKUfaQwRij6avXmdCcuavmVTbDinqBI5gGeDa1Dfvhv2bN87UXKaxkCAzFOSAvAEBkVo+NOT763EHJMRMBENUwZ/9wB0qRtYVucJTa3yZG4CqDkQGFbXQ6LlEMLsgyYNYX6XdrCoQUjqNHbWEuPUEX6O06rZ7dlt4iP47IF3YIABw9FFAwiPfNpScqyKaRVXv6H5RSujMVpT2peNYGBfcTia7R1Ky6kmBCDwNPsGkQWimVunG0iMxhCtHXi+dhh3+GlMmprANIrGq05rCuakPq9+NqlLSxE9SFMQ82TLWCQSpX6MJtCzphXp1N9RaUUfSblgvrs77S0tTmBQS9szb+TT7a5xPtefvIc+fnyRuXnXs3Ot/7sufzg+DYnf5fv0Hk/J96wnvf+5SsBfgMKso1G/iwCqwdYKXFEO5dYUFjWFBfyzyLjMTp6Mfdw7erAxIIQbjKOdzhHoAVzNkT3Av2mfc0D/qYOaUj8UJWxqGWnyO9tFS//Fsms2J+39OdCycoiyJNBASAsyEGnZn6CwELW2fpMnZXOWvdP8NtTCZuN20xSyNBxpZXdqilXiJlhIAq15vFWtc5uYYlptkjj8DNpUMyBOFqQe+2qeXTziPe+uY/yZ7dZaX36d1GwpOZUTRWMrKl6znzDmhGRI7u7rZn30GfSSF838KbG7Kck0hkFTw2YMsDfU9EDiulSM604kcq1xJl+FeLWoqDSE7KjbjWL6N0pTePFz86bStCdPT1gTiHyjKXQm9oG3v65NbDH/QtW1Ak+YP4ArksAgzAvE4j7hgf7WZv5LIIADDGNNk4G85wQNtSt5hkDDQSIGBlhpdocRXuSAjlOdpclv0sAUosdpQh3P3374HJTzCXy6cd4HDO0ft/RS+/afHn81o9nNZaMZKOooysksR/PSX+C6tDF7WdAhomQ/7tbZZgxtmkuk6j+btjv5A/x9CA79mPrpK+c1ktJN4kj/lZBUPmCggSQCmbkDdR7XnSKNkgw/tKTzkCt816f5ikmr37uBwfeQbSYLgYEU3gKam2mKPtoQGGebliaCfhZp3og2G22KX58m3E8UkmSvGTBn2ME5kNrn9LkLe+x3i0g6UDym1t3XvIVeZVBAgZYaQ9pC8AuzOKO0B7DvxOyr3dGA0FLYAQqs2XdiWTOeKNqRKs2lKSKJYeuqd19ltkiBQtBxHATvLDPezW8bH1FUhJGAIMYU2EuqmJkKBJoQiBAEW1jDmFiGxip9RQkPvppnhiKV0pTEwF6bPgY6W+VEF8kAb0AQyJobIQa8jImrgg4MOIGhU8LOTWbZ/hK3DEyVs30/Pb5blpGTGpN+kGxaSYa3Vq/nE38GhOcbeGXjQspXDyPxip9oL/gbTcFMMh0jrNBUOZQjxtF8AINs69zMWrbRKmQkO2to7fAHV9nBweYNoHtqHQ429M+APQ59RDF5bySVceaPPDsWkMT4RgFdeAJYWQB4vCe1JQYHDvPJR4AcL0bIBa35DxmdJoALpdHG3VqCMTI5SttYJJ6p34BpBs0OMfKzekRM5WFGejqfnzaRGUGq9XTCW4c8cNc7LcSczmvP2kJCGjds0MgGhunugaQarGnvTctXZUSXo8GXw/yt3M/mI/92frI5mrXG0ETW5JiDUJJ1ctJYrqr5XjVZTVL/BiYNgX2hNIU1wLstYKrnOgCn30C0A2m88piV+bGq7B8s+B/muZA9oW1Iwr8Bhwks2P7dJgvG9FnBZZ3Pc+gFZt7GwXRzaOToCzL87pPstn+O7TdtwXv3IHEDKuNOH179fq0EPp8IRJd1HgO9H3iQkaNIv1ng2QjfHv/KfKR+UCiqzEbXejiaL6Zd0bOeA8mIo0TK4UkHmaQVrCzVHxtb0sfTVqTk59cefUFySDX0bwC450tg/ATeiMb0NwRMYqEjUa5+52yJqKipSJmFBugK4cMk/2yQUGRRoJZ/ll+mjUicbVRbNC57RqNe5qOYcweiBgf5xo2k1mBAwU9u81EMX90WJSUgyG7jh6OZ1MMW6POw4zPtScjv7T82/JIEswdPIouLiXFs2Rus56mhApJgE3hs/KI+TciPkFYNgfceE1LPDJtReSi37RfCfJjqzF2yIIkZpbGN6Jf8HJYrSX5Xn2wCwsvTONN5F6ctoLjrHTsAzd/oNf3YyaEYhRzGr+9YSAY7EEyVxr92LrfXynp8bfoOEvcqsWgvSf+JtTY1JoFhlEkrgIx9gAqAnlHdZhuRG45uHmCIOY1L7x1YWgs3XnxoDwIM94Ogjdnzou8Or49dPx3iujAe/4dCP4ADZhz9oGbH8S8mr0kaGHDoEDQILE6NoX0PGvT9HYOG3RHhbEKdos8fYOg0YxbdOerZD81RUtEjraW9kSna0Wxpc/9MO1OLc+Yprsz18W7lUz2oZbxRDDrfsH8fJzXCK41zGLRCKD6EpKa2FJc2oF9izmm/hzAPCYXSTGsJ5kg26ugvmdmwYX1maTjTqhsfgoAfosf0bqs2CgLg0X99P4ckaDrqSCQMYx8tYj5czNKr9CZ95Zl43o7ztxhRUMOjs9jt4SmGxyY9nMwB5IoJKV6YMFTUdfkMYpSlpXpbXU6vsQFcmaDafMTv2rl7vA7NbIufq/QNWe5i6h187zI+wHkXuh/yKyCdyRxD2c1Hh1lnyOBIi3j0RT939skfNYV+16c0v/4zG35yp2O8vT0ej+v38p0zhafld2V+Pv4jTeHi9RU1Se1aiS/6Fi77m5BUhWxSXs6k1lB/yyJCNiZGRvJtfaTAaT76I9MQMDRc5seOko31ZBzogRXdmjNQ1OwlMaV1RrSEtbFmXkUOq0SOpuD+gZI89YXuNK6Sy+8gM1ywDeRPyAY6pYlwpCEAMh1JQ+A5727pmyT57lMYW3W9oY7dXwH7ogGE80/v/nR+//t4pF0kyqSi9I1mJtpgp4Pj9+JMLLaLBnRUfyj2nIhy1iDfLtA22g984WN1336rnYwmyRARtabR4nyCSNS2z1d9c2lqRYo7o8NP7yzGf6PChnPHOJoj6KcIxR8UUKhT1SRLTSAfWL07MOMygNaeEokrtbaWpkQGLtE10jQ5juP+xgLimoBHZ7v+3NEs4c4Y/tt1PNKf+T72zPOmeoeatvkR0mnm2+fPu/m4/o6uf18SPtz9DAbP8t6A4bfvOI+/mtEchsoL0Wa/Jd8Coh3N7VcIOp95P5BjQ8zodVlWTLzwNnbhwPCwAH44pmPr5wMQHq1jfsF+NI8e5dfmPFhXst1P6wggXEyZmcdjJpq5CJiBV+KcQQ2wmKZ8YD4tFtJpKfb6G0czcDqasdupzNq1UUlg8AkUvmPoYnINCC3izp87mj+DgZf36Kqjsy1H83h9RRy8PVVxOZ9TfaliHrV4AwT+Nht7vzatjg8a6kc/1Lp7uOWQmGtrur1qbsJY4AK4DBR2zCJ4wdnLybkkgDma2a43Orijw1GNcaqtYuv7CAwLLfgMjc8ZKB9Emzz5McmxW07lKlzbvm6Cwop9OJqzv9XrJoYs8Myj3h8BwY9n3qNHxD7r5vkrp2/CR//n4xPj/w4EvgOIPx+fAeE7EPi3wPD3juZHVEHgNBNRIOnIo7W09pFskFEEzfEr31FX2kxTzsYERvlozu7IfKSQoNKAIXg/u6yYZ82sc5T3YPTHkR8am2salfQuR7P0I3SaZh4PjSedemahbNAw3wNqY5gamMFytw1W1YdRXpmtgYzpW9I+NQZu+HLzE7blHa1AQ109EdNs7nzuuMGJLpohxXM/c7Zld4UlHSYcuyP6UAtAAov4OF+kCKMp2LmgCzr+Hrz9fgJB/37SxfH+91tdXtMbvyGGUQ+mxjDLNeU2o78UIgzkFYxGUsgwfT9MywDyrrHXGNcryHZjV/cdmoIEvuyIwF5fK0eLH1CYfSBq8iUq7DdIPyFmsOlPSeQiYCyaMdupDA49Se+savOihBzlytsfE+wgzDNvnMPBhs8MMDQS4KDUQ1J57/x34cZNsfHILbOpp89Y0b4WT/PsvJ3XornUZxCe1c8aiz9Eor+Y0awqlTooR7MWwpP56FpxmI0uzlcoUFBQJiu5S31E1iC4GGbnEQzTpDJeGCPWIH0M1m61Pjq+B48u7un+ntjCpEapMRQB1/garNSkhI9i/vXsSE9B6bkkL+WbtBGUahhGqqWAcVAPCLTMrhU9aYbSh/XSzSkX8lLwaTGKTGRWQGpmYuemWWIG0IDCO3H37zaCq4c+iXIPhh/Tb/7nko0yn1KatMYZ84HE7rWbvdDkIDHvhPjFMbjtMiztIJQ5Zz5ozj/gyH4KE05PXSNFziSXikj65wgGrbxcZBBBQ405lfcG7iiGfyPK0UyzkRzNeQedz5XWG8pt1OBOtKO5eG29eLEdT0dz0d+FAtxeKrFVs6E2GUMRpSHvuGnR0yznPMJmtXlQzRmZjkpv1ZM/WiMNUTgI5BDKR0fzgyDY/gM8bT4KfwcBu8fFCQijcZ9a8VPz/jhODAzMyw430UaX48JXleMu0hOGfnb8i/0UTkdzVUNp43BenRf9J0ezFtVCCGRyym/G52Yj9XseAxJ4Ds5qqgMP3MPUI3j0Dm/EQ1vI8zzZiWCYlpeq2Sqng8lRbsz1Byf0ufYR4PMg1tG9IgxuUk8AEbHI0TrSeNWlgCAejuZsp6Mc0tP6By/8FhTwlGRiAmuHyc8zGlvPstXebwDxtPGxBTQyEgolrDs9eQ91TjK5ljhVRh684PmKSZpXQZLdaCkfHs3ofpsPfKdNp5n+VvMxnOdq14oaCiqflPojMGsfrUnrSXzRoa2d5prax44u9JP22pNHe+wpbVtZ/H+KumbuTs2cB2rXv2p4gQCCo7zNWtnfnY/m0I+2Ijy0Aej5R1p6GttTGw55ufOsp38ginj2JelU9X5aHqzIJzWHjY1jnAhQDBimzDCqmXH4TqfllzwB6PfHXzua29wXHpKauMDQ1JD5KPr315I1XaoymmdKwEuUxrFjQGHiwk929ImxzK/Hh+czj5Jj7hkTr99i0lZsl6WuqoE/jIHNntJoouvtfk2ByJh+gFbDdc9iOBoecuSOaK2JYa+2jLO7gYGZ0VyvqU1iSiuQprAEDaUpAASEJygkPjTHtKXa3aOM2McCtGb4AVuFcxYI72gVK1sX8QEYdEhLCzAOvzfboYSnazMFNiDkCOvTSd6rPvTe3voGenq26eqgP7V5TL4cNV+mWWhuApm3zgBNr1eYUznoU199vgkcm073BpJbEw+BvAUYYLwxTFM4fQdlzRlN4aIwUvSlLUdLY7i1claOj2qBE9bkuQppDNlgVnyBdBom+Ybayds6p5uGQIw2soNXqrwceezBmK1rhijCf7OX40E01s/Pv/343aRAMuwbR13iw9+kjwmpzm6aTUx7qazv6fbPx1/6FE4tQdpAz3JEtE9h/iwsFbWw25aUkDhkU//DR+Vrmm9YlH86W9zstd1IPc5NYiCCOqrT+Hki/cHUT2AYKVZSn2YqM40SVp01r0D+BfNuWNrgupi/tKUBCr1/WJMGshOtEa7V6d3RXN+hiLCplf4c9tCAfrbmMMaIIVA5F6Vg9eCAgCbsGsf1Md7nJSffDrWNt4Sogkx3skJBBzOk5oFzOD6H1HOwqi0nLd/yi+Si/Rqt+xrHOAdw0OHMcsUgNekLMRofJG3X0usZ5k/YivCjGKHII6UFZs2j4sg1U3iTSuRXaIDg25NCS5tFVwNAmZm4UGTuDovoeTXym0BmI/YzTUbNfNWuYf02ON1EcYopYuBGKDiB4K2jvVvfulkA8Lj/YWz0N8GsDjB6fzyu9OIzfmtEwfn9qOxDazg1hgGHsHsPtvfH4+/2U0AeZqFZyMAmp0U+tuccB3QAba/TwA6VeXySgUMzwk/sacwBpwmoWS3PeXA0kydoZsFRhgulLbHkAe5z/XhfUJ3WAKp8q8FjVkgVQKDzPkmh8s+XDmiOI6TbqDUJAeNuDlz8iGaiNDBk2k7NVvB2yXFgTSsex/sQBJmYGLcxxniCARgN83uN5GkqVJ6wm8XT+O2qc7ebMZbut8MC+8YXziM+dHqcFfPvl0RvNJf9JjQdiKJPONFoEiCgQvcSkJ5d5EoTEWzTo2u1k1lLkWz2t4ODGNesfRS9Q2jP4aN2gNRaXTn0y8ZdyPZlATk0lDdHwSrNVMwS2vYVs+ZRjGM5kO0HqA2QRsDreRzWBWfbDSA4lbamQCKRs7s79I3Zf08FnT+mXJV20q/9NgB4z+cM/IlSM5K7zDgpNo+851j87Gj++fHvzUcYhl/mo8AlQAg6n5l2RcsUDQwIRiew0ZYYozY2IWPrNWmMKIchuw3ffjdiKze68ZRWnSZJ/0T43dRknXUM8CpnJCiT89qWPdxpGHX0dWsBln9iEcTsF05TkWtRGHCQg6+1DIHCJijQ0ZybfgPagXlvM9+m6ct3vnNmPccJDwMIc5KT62gh8tJNG7IDgr7qNB95Xz9fZlwfDyGRyTvnnqvtnwTFU/76dMR5abThTL9rZzbS9nUJFA20yiziYFACw2oNYUABUcxda0/dsbj7WuBevI7AvcrMdNOpfMuMdAH7VeWVCSqOGc0ip3dQAC7TeC9sznnZ7WwO3IxO4toaTWv0O/SfAAJtJhIQDCio520xyYzZAwJJhveJ3TJP+xIcHLyTSVnuaP6OKPB45njraLtPs9Hzd/1pJL/TjYuFwwVMZPZoJKa9OZpzeFk7mhMtoP3k+HeO5q4S7/WnnfcmDfaZz3Z2E5G9L8/ObhBIHOaZaQH9HlbSDN/K7Xue1gN0qMcbecp/HG9pOfXw+23WcTEj+p0jeHzouGd+XhebWZ0iwMlj95QhMkmWcjTPLGZJkSxPbevN2u3xqRHOTz0A4QEMIHNuqS9Gej4HxiHPtT257cp2030BquvMaJ66jaN5EoMIcbZ6vF/2O+LwB0ymT4CQb2n5Ie2tVc1JP17WkCRV/RUU0eRgxkLG6ol77UfgtOdOS3B2szQGo1O1aaNWnTc12G3j1AGt/U8591SEs83TOEz6UyTUg+E9jxarjMm1dvEY3e/HgMOMoYQczW9iwCfe+U3aJx6iNswH7ZQ5zAsKHPQIy4fgtwZZhiFUTL5Pz56UOcJGZnz+jg/Hv9AUVO1oDFvYHW5aSzx7WiBy0adAsnBHFh2i0hBGU/DNTQwgHD+Ocwwx280h0MqTjzSX2ur3hwEDlX8SQiAeEqoViil4nM6AHM3qoVNT0HwGsy5mTBkAXJ4eVlQT3Q5SoaZQVdHS2bPVZNKpUzOapVH4oNfHfhp0z7PxFONjInGF2m4LFZs5ZVp6OTqufTdbPM2DT2A4aFxMPlmJ1MhkP4T6QO2Jt/MHFt05TvYRx998pdzmu0eJWqEZI+sndnnUgmtCb40uxaUi6t5e1BTKVHTDNQSmxWKY6jiaR1MI7JvaRpuNAjZBhaA6wC3zkWsKCkOVRlDpFx3NG5G10PqdL5QnrTTe1ZFKNB9hP0xMGrNk9qRZGMgf49nqeTqahwzOrsxisMbQfXg/iOFMU5n29yktE7Mabbzf6wmECchfVAzbQZP05OGoMcApOmkwDWP+nyr+l8ffL3Px9jcDtxl+jOwUqXQfXiQBSR/5QdFKMcrnb/GqT5A8aacEEc3o8pH2Dgo4QQEwgPggxTx5iKrCd/Qqq1mtON+kh9fxncf8A/hqMut4QRztpckeTqqCbA2u0a4UgaS03a3K3cTePuSZpr/PhFdRR7yv0D22Q/NraPArbRiDvj6mlCf77KqEdb/nDb0z4i3tAIbHZ8R517+qB96Z82T+cxZgGCNLlSN/Tdh3BW3n8ZAMtUhQaQI7A3tzZsBaZLKLNvxo0CjLkO7LET3+ha2Q1Z5OEyOI0nw0glvSFFfmJJkbQ+CVicTdfVibP82au11KAuc+ZyC9SeOdcVZjJmsVErXh0niquk2YKd/wgRzfzEekubdudALw5x9lzNvEh97T9SkDDMb5CAyDTG4+eoIN2yHOyhaeDBg4bfo4eab9FCj+aj8FFet+BW0qX79FYSS2NdfVqJT+966/3Mgt27f5DmzSlTtMe+Q3IFgFD5BwAntnbU+bbhebZ+fB0tSJJ9SoUM9jFKE2a/vynmc/plm5ANu12nTYi1vdDTAfJNXhvM2AkkxDUiyZMhmJmPa01FursW6f7unXgPZ8w0jJYvL9J0nqAIQBht3lnKT9dvgL35vi/O3PAD8cJ+8A8V6gf/mnur63jN8rsq2BHrlMGhyNIXNAoMEgV2kJPYWsNIeKRFqUXBdnNZd2AQD7XpRJAvmNphDACG6ks2J6XCEW4/PbpPmNG72pbIrGAIk4vttddUPWd/mZ79BU7hRAbTE6NpUP1M/N+l898tu/eJyHwT+ZflXzFDAaCMxsaDsLHXlheRNxzIKeQ3adnx1/DQpHpFAyCkkzbzOM2aEiG4Cy/wXQe+Duu/7yrjV9d4FDpQ9gnEDxGGj54brT4i3t4BMqEsOTx64+WsLYj6Nff4BCF+hiRA1+N1kpwqiIvECud242LeQTKZ3t/w3HS7FQfrtAge/KHf2uBgABhRgPvIwneZ+NHB+vJ9fJ3tkGmNDEHcEQRowuFGhp1ENufU2dPwLDp7R4/P5NEZ+PJzP/JGI+z5/uPyvjehDzBJ3KQWZoIljGBSQjjELnq0Chr3lPzueondX3zTxZJiUkZg6DhDfAQCGbtheXgM/UnnpFbzX+ORcGiZWak1Cz5gObe3nX7PmlhRezKKE1CPk6NOdB45LP5k3taZMKUn5Fb/IPnfpfAITfjMAfAoPA0QHilPZH7F52bcwfJjDEMlr5kP8o7+cN8nNQMKZ8qGlvrUMJIBmauaPWOUmgqU5LMGyaMI5Nzw0EXBIAr2V/qJrglMxHO4A/6kU8mLyu85F/8jlAPMjvKF/vzkf5JOJHHbPrPc8NA/Uj7P/PQ2Uox9kGCtH0b5gQXBHrmnb3j1KZfc/rfy454pULjEN3HM2JnoQERW1FhwgWEJNuwrWW7CZQH50tchoJvcXe0p0+fosM73laKkVffHxb90DM93SuGBNm59TsPpt1/9ykSMDgjCMbKOZ3OZ9pFuJ1O5VlZtpKI7PKYUxImBI6jT0as61czCVcNAFRjmbRUxcR9H/lNm2A9aWz+XCEH4xxGGFJwI/mDo6h+EOvfsBr0eh/BBxpQ9dfbhFVc/NpBhqACD7T/e1RUKrjoTGg8z2rP7PhJ6x5xuJ/AxQ6hLKr23+1cwcrcVeMsfbwvVdtoFPfyljm+8Z9v5B74379wr5v7NeNvGvG7ZbmkBu55XTC+Qd0gx/A8IioODqsGbIYZRyKiNI2fDBoMNuzKu0JFE6VAhaq4TPISA7HoOPQbHPPxw/FjAhJ9O3CxdOsFEebkH1moHdxb+1hnHo910EmA9Vd93k9lnXlQxPGpM99+aNkuErObl1kShsJRGKHAmbrWe1dVxoptZuD4f5Oe6jv793RHo5mx8+Pv/trYi4bGGbwNW9nmgBBaQKwwe2YYhsQNNgv5l1A6PqLrUhNAYGdphXkhZtawUZg3wv3Kh/CLcf0Nk1BC+Lt1bSdWp2Sf9IUAhN9tHI3Kz99gUwn01951wxmJEO7E1cGAnflIS1u3t+4OfY45sHZ7jQbJwKxpx+IA9ZfLsT84TiY1qPDv+37GeMu9VditONYYaZbw0z3oLUFfDruCYACjAKENRoAf7/9LU/Xs1xEiGkFpCM8/A0C/oWmsAeovAMk5bQUL3titDtgWBYXy6KpSMx/CwDMx9DaQzOsx3tP79H7gH/y06YdQ+sHGHQaAido6J6BQAOOA4MxYj4beifbxzWUAbPmOAYeVt5xKO15fh4q/9l+z/RxBQIGTDDzT+cXZE4obMbUYRi0fc+jak0qMCNTN08xVDnnGshYfknseZb/zaFeybcKPNpLnx6PevN6cocBi7+o+u94kqGrgyO8foDTiVNx/CUH+MAqB3+a/2C9+xn2Kj/DkRZM20PbKqOEddLlY56Clq4A0Ay+BIV6utZFejiVySDLnOS+ApGbJnLq3vANpUFWBlkaYrI4i+7hzjb8tESREUP3egO0yviDFD3aCx80hi9BZfIZK0wcDNlwFxIUDnm/HccDQkqfM//efAt6vsqOGLDBs5w/HD8GBeOC51oxJu3kRq3GGOCMStRG4EtSokCBmkIm9v0qTeG+selTaGDYyW05u5VGanfm8NAOvMp+HvwYM8ow/Flq2M1Jh+nFmwGY9+K9XsNMRfCBDhHtZyttwAT9nDr35H0nQ3NXRvNgZ279rjWVbClvGmyciYKwp0UU/bv0BJd5vJzoyDNnptvyDtxE+xZWTtSKBndZngtoVlQZy8DkBKH34/eQ8bE57RlqJvYNJ/7G8ZzSZtcuagpwTSHLCajxQs1HAHIMcEqBPf8AC4mrGGoDQyD3ZVqDaw8Cg4t0rXs0LyFGU1gkQQKEtMNegBJJcFj9W2GoCiUHdQNkOZrbBU0aKzOTNIIyPyUUQALI1JzrrnfUzjt1by3MbHUCJqOmxNe/lRGsm563/yRWvDmGB0mGD5ipqH2S8T56+rrBRJrjaAztbBZIuaYA/+1pQysSIOK4fgLIz46fg0L6Plt19PIgJKqMvix1qb9HJpSKX967QCBz4369sPfGfd/YAorN8DYu6t8SvTPJZmrPtO4FXov5WsM0MQ4j9iUgtl2P5sBHnxoK0Pf8fh51kFNZjubo+qc5n/NRxpH2qUvY1vVtjFKyeO3w78cJCGFpc0/hr7v7WUuBa8e4YXUP8KBaJEgcEBlAkWBQqyusBoMCiCpxZ/PMCmKIoAmDNWsGMdAwrfPg8A+mfzTkg3SOp4+LAw1wAkRMJ7AfRpmQtKZ8HPjcxeZcH19/0gg4sINgAEr9MhHlVVFG7WheD5MS5yysC5mBW+ajpXBWmPkozuXjE8c8hd5ljcxcZqNtoJBI3JTyLyxscJyT7nePq0XtQmtv6f0UG3aBWK5kwEkA14sBKxQrNgM3TB78qCFMl/z2+AwOb4jPttCwtYUFRbcNhGFp6PSn2ai/x6KFxpzkAPD8e4BD0wrpjeXpuk1K/w1Q8Ekih+e/eYq4JpM22VTYHgmaPCXzUWZrBuVDkDr5PAMehtosr4EBwAdm/Qks2jTU1Q0DBH0LzjTMQHdJP+HlWlX4gCJ9urGU1g+cadnlev2Sac6YklJGTrtgZNK5Pr8/AJo1KNV7B5KMh+VLJpepSA7pCaF945d8v8+e9EGnt/SXuaQk7cgG2+e0+f4BnZPg533hn/d2tH36SGS7hgB2+jYi7I2kQjMpTU+34W3apX0h1jfB/ohhCJLsfEVMtDVfpiSbvNTp/Iv1nnY4mmnXV1paO3Wd6McBME7lotnyKbD/minKAHn+mwG1ejxrh0GlZZuZUOfMkiZLIihAaMdpN1/LOgcg/IbvyXWjbIYrjwLeC9HkMt3vsR72W5UiIDhvqJPKmN891uz7xtFs7/zgaJ40fYuDwGgfn2ZD/+n4C/PRbR+ZR4PK/L8jcWeR7L1qxGnTDKBAQf4CaQOlKST23tQekr4GSSfV2IY5Azzq2u+AoBl6vIOB0o6o18qzlQa/d767zzC+f6SRWbSokm/vrwvXQvTO6ey59hY/B8j8SNRmJkp5Z8fDfjbmLWTmR7Cczsp3M01zJ2oiU0baRKLRGPo9mUBohZZaD2dFSZHBN94oE4FF5s+6RVEz5DOGCc0S49MO+tYxaFVb945m86nnYSA/KDGw2JDTXEV/sy7V2RnBt5/MrIAmgdxj4iNjafMRncuIC1gXpB3U5LRLLl3sLO1h5xduzVXYY0a6aT66k5qCtAnOdK6x8HA0H22RtvYR+ySLPnaKJmo8d/BIn8vnsaB9yqXp1zd0SOoGgSE41iUYckzeG8gbO69aQA9rgGThmMDcMsin/lXXqWc+8/0HSUxf58Ho36X+XmwwZSkZ05mWI3GQfi5OWOs+EMxDoairhYHay/gqmoirpP5VgQgZa8xFsRC4powIKHAB8EmXfz7+WlNoRmJwW/RD2WhzYavNZQ3CTQwCBRIBAeAEgeLAillugQNikHl0ftPGExjsuWdavqU9tQV13AMU+OD297u5qNOyyx3KhaVVS8rJ5oDXE7n4UVoWoH5Zx/Yqb5bkt/n/lmiN0UXQRtxvfZ79T2maNS0zldo9gHiEqHq7N5MdmKkmTi5qFuaU42fBmDm/3/Mhnu2R8JGe+T4A3oAhrb368WgoSGu7efTT4BouE5ZvStBYYXkRRismCdp1moSYBJckEBXz0dk0BXdK675mPqMmuE1IKl3FEVwhhRK6MJaMXGcAvVii9mNebGfpk+rTvqavLJFlFmI7F3MHtNhd7zVqaS3AbTOVsP+fpiNEk8N3mPDWW0MCn+jkc9qMBgMFjWk5nRtM0P0sum0xKU0LbGqKt7I/agofHM3uj/B9FsLKmeufHX/naPZrkyrq3cU1dzAcrde12CUpJtA+hRxz0b7LjFSaAhdpuxnN0BK7RTA0w0QzS0AdMNXsDsMAgadtXve+xdvSpPnk+exHjcGvn2kHX3VGb2l8KO0bOp9/l0X86Ju73dXhCcRq8jQJaYxPI1E/hkYkGByKthVHmREq7YbMS9Ptm6Giq1lDIA+Haw0aRbP7QnyLce/6XcGN4PNaj39DzutiUtI5/FuOoS7JzsC6++GBc/lIq28KOjb5O2awTzueUDt18Lr4IPwuTWcPHZSkOI5mmYyKuQevNWOZM5pjMbiDaVjY9ClIK9jXap/C1mJ50lRsPCcMEFKagrZypXAHYKNW2K0NdEgDoT7eyNSKqfFg/puKJ5mkNIWbzmfSIuImoCTyupHyze1SFYJ7P6s/wzm+NfGDcx3Hact34WWd95JpLTAGDlNdzjyRjcVVZBcFmdUr26q9O7qRfRvPCWgt8X92Kg84WF6Wpx1uzrkK/w1QyGmyt+ZluGqxhRuI7NhzEUiQ2waKADZB4d6jMbS2QFH8ZMSnOOC1ePNnPJn5p7TH3yYw5CdQyNEOnlqD0vzc152PUnqnhaUZ8zq+xwHBW1uUn2jOP6caSzEWaj0x253q6fmtnhNDns17x6RUdYx+shnyk+NKr9fgjyipMZRDarPmJIwZRoaqlm+ioth6dWNwX1+2WUmsw6id7PNBD59AISzNb/UihRzAh8ZAkDyH2JPZf9ImvPX98OULVpsR8htgaHAwk5IAoOL+5YSmmakdvKYx5DCmMqFafbsbjeLYgCs3wxm0tAXnm3Cc7wMUEkAtdneAwq6eq/gKaQRcvSBuYki5rBEAdm0gnXkhF0HBJGf39atjDjnp8Wl1dsnZASGO3w4Oo6UZKCcdyw0G0iAqX+d5lheTr4GxecITEOwvHmnH/bPurjHg+N4/H/9qRrM3rzqkoxSoMSSZvzMcieS9GNvxR2bYAzlPpkpgmFmYqkX2QE0c/zsle9j1ExS23h9dj47p3vZeM/dkv3fe1dXpdwzj9PfC6lMX4a30AIqDBVvbU3zOiXgpYPjAspguW3b09ZQnVn0wrXSXmaTYbSMtZkCKNfP7QyMzUYO4i433b3qUlxr4ajc+0ytM9vNu7MFR3hu1OtdnlfP4PRqouMpoVc5hxixUZXxi9AO1J0jkmSc8/wnjhxkBw8jmj2mSPIG5Nj+FO/MFAnCzk/pHqP2goaOt7VOzEdXu9WcJVEGT8dXFRhT9BG4AF4l8sUOkTYgBJtpe7ia1w5RirUtA+GA9NJ4RlhaPPM82fgJEdJt1XaxtO29YWwMtXIxJdN71NPc8werQEPq3f7+oNMgLHsCQlvdJpt8cf6UpPJt3mO9YFjVBbXdAVqLn8n3jU6g9g9OYs84z6HYaATYIvKd1vj32+J6Cn9ybGPOOvcM0g2datrawm9kbMBkAeBNNPrun/A/QIqJiGKKAQc8tnueu28K1fEI0/XGgiHZAmgLliVDsv91vFmManfpqy5cQ6MijFISddIAE9trDFNRLVPc3dC9oZgxo00aQcmZYaM9fBWpGv220AjHnAef2Onq1NhQVfM6vAXzVPSPt4i6ZgSWbRHPEYDnSIvSumHP395l2Ho/BX73SLXBGG0k6NbMRBOPSHuh8poYgM0ZPXsP4FwA699u8Ue/v1QpkQgIYQjr9HKnQ4vIZFiAkENQOguZiJBl/IvJVb8wbsVfR1g4gX4i9uIb6rs6hHyEjEXsh96u6M2/k+kLuwApqEVxGI6M29VI3zaoL2TWv8wmy722ta/2Jg5mWZgsQ7lSaaQ/dT2Aa+Ay1isV3bfl+6EBvif9CaUnzu/4WIi6OletI979MOp9Zpw6QiE80+Pn4MShkDoaJRU3Djz35YAaPszhsM2py/gk7BSTOj4T/wcRiIt48ZmmW72mrH4AwrSD9t+WTvRPxyKchk8O8jdkMAOSZxu8+03AAx3zP59YWhkwfi80Ok3H/FJ86QEO/CxTyHCbZr6n3YPtdEvBuJ7FoIKEQTpO49fL+WEmqCQ+N9e4PvkuUM+3i1MW2P7h5PF9q7advOc+TYSTOtDQtrdFvyXhozMNQj3c3qsfZd2+HPzu94NJi02oLeg/p1aX/tPRPf5IiTaqtIotxDMlFN5yUPIl8EWktn60xdDO0FJuko43Iy6KFLoa7Xm2WQl58iWkKexFsFnIVo1MsviR0EXkvT68+jKHJRxd3G8Paw/vjXZMwzcyk7knDOJqnEdR8bHdVSu08/eDWAqR9F+ZdNWZPE9Gb45nlyWpQVYjjvT89/srRPEPPOeAAgv5VXtoJkUiGs/Yy2dCa7DhCT11DEAf4xGAPKCJzEmPZzLe3tAJqIbyniWk3y6wVJasONzWG+67QuM37Yz4asEC/u5thWuoDUHQLMjGfN49WJfDEfOvB9jnmFHwaURJt0cmclzQEroJZ26RWOd9pCqUW3aj1lLVqpVpbzEJLFajGnBZr/K1JMFEzULtL9cZxMCe0NsyyX1Wu5rpU3Sr1xugiw4uGZT4P9ZMYU4PfVAqAScUH3zewtfrPPeotGnQ5z3l/9qveyn6aJoZhjclhGL5Phtqe9ma7nnv9bEqzwFve5qYYunC689E9IDANFqsAI+gArr3aFbr6QmRpCiujQlnvKLDYqwMLGoWAyhMBXMWicr2Axeu4SrvYFxA3EsAKabEfCECAKtDy724tYDQC+Wuq/fwsXwLzaaIgnn/eT6C2Fj2BsPs1ApmftAVpAw//wuFoftcQEHOOA6Ce4Pf74y9AoVq8gcE5t8ilp6/TAcW0jY1zff/xK+x2KpvJaJ8DqAUKoJnUqVzk3PM/cNEt/pYJaPO9Yvw1NyHHjHRPfr8vKXjKf9TvAzAMkaZdfgKEfKRgtAXnQT1wozo+ChwWpai1mBaeRnBowAAulrn6FWTGmQBeZfJZdy9IuGNb/W1dKgLHePyAWATOsDq3xLlmldQuQbFV0kvK+Vwzn+VoLn9GcmAH+3eBv0FgeAKSXkwJqn0e4me7q4f11i3e/oQEOQWzviu6n2R+UT+6+EQW+9R4O99ncHgDhv5DA8KMCUmexogez4yBUGYkGHOM7sMGW9nAu67ZGkuEawcArmpcAcPSGYmFC5E3/wgKC8BeBQrkE4EbuMVfbiACuX6VJnB9AfdVdVmlZeTa7YiW6VG0PFqQj6gB3BMcBhRg4PDJfDfXxdDHfCezEh37PaIMHBDIPZFI5Z8UKATg54fpqMCgzErxBASCG3SWNpKLAqQPij8ff2U+UrOKgYURUI8kG3QuGQ+XP7UCla20ocIh0KOYN2Zshqtm2AYwj/LHLEQi32L+qDjunDQ3Fz1NS0/n9rdmJFims0Hn+ilkYpiKmGpr5NGyKYIT1QoAigAaCB4AoXtzPYJTvWkTZPL43lqWoez+0gZHKm6uf3xImbeMHsw8I+rRMg/dfnEy0nPSHoNlgxPZUBUXiIgZJMbRzUzeoAdtemP3fAnru1LD04BYzsDscyGNgwWabiE6YTu5MNNt1U10jli1j4Ptk7kfYCBhRfdkhviQdpolp7zm7k0PZ/tPw0z1nRf1UjaLWgPsnGy9DMTWlrv3BEasL0TeQFyIpUgk+g3WQuaFaAmZooCFYYL0cDRg08UAm0vM35nXTr/OEzTsOtc84wDe5cTZP9beopsyRxatB6wP7C+qce1bq9GDzN87IXvr1mie8W7e/PPxF45mnZzr5ZmWWmq3Zj5qCeZaMRHNVdufgHHuNiMCZnVVZ+yzftaD2Vf0vMw7kuzvfJiP0jQEgJpCmZH2YTYC7h29xLDMTXsrmm6Yx2E+OtrI0h7tp6PH1hstz8BMSqjdrTL9kFhWLJqEFtaqCI1rBWLVuYFiGVAEeO2gIC52sw8vJG4kXmVSC4UVR3dGmweTRBlmPSevrD1jAm0OCv0vkMFwVcjUWOshSWoEam2kG5L8AJmcgJkN/RxG3b5NLHOjw9+jsA4PcNzSqFIhyHKBMw0o4Nz85l2LvMWOBgOPRgoXbB70MaA3TGhANbipjOYlnExrzEeSWMWQ1jAmyMxxAsJcn4xuOmj+EqCjPQ45QH+MXKjuv3i5OOE2EldsXAGsfOGio/naVy3DfS+s/QtrXdUHm7OjbzL8TGC/gPtXvf++gfUqBrr+aQEmgkEsdGrrq9Bf4IeDwin1ozUBhfmO2UjzQVJrTeHCjsXZ5Fed99XzREpjAM11Nss5yulffUlzT8iHUkujSzsIfPH6C8AXAhf/Ho7mLE3iAMocjWckzp8Dw19rCvwFkX6vT2MdUWr6MP5sLikgSf5ngDBFNOM33HmAAbrcQ9uwtCk3BlC2gY9rDDmmI08bs9EAVPMsqw+sTviU9ji67T6QredqiS0mZaZu8XcEIhYWpCkspkUBBXBoEWvJp2CTwiLPD4iauLalqkaxx5HLjTNwcB5hHzIXpcpuyqhnLVwVkJO62rzjqtXXUyt0NBl/z4Iekyf8ws9dSMw1y1S+Q2Ng3dsh3t/syC/ueFa2JUAj6GOWtb9bfdzQLElvXpdkyhOOLRBR2mgGZ7lWtW/TRnIG6WmuWTc5UimUDG6ECbDRQmsQFIJhpdras8jjApL+BJhWsIDWFPaNc7E3OprByBr4hC/39Uy3dJ/pOEhF7f2ED2tLP38y5aWV4X4fc+oOzT7AVg7nnHPab+WLx/koI0knz7TjcFHpvwIKKnogIDp9uLScdZvAMNrDcOsy24iJj6liN7Hab6ZptnFfw7UMRtgnpX64UzlxP7SDneg0OZf3Bm75Euikbme1lYud3fjfgcLxGziY+tF2sH61TjsiiaAxt5pExPivggJcsXC1prCoKZT2sIKaAgoQZF66WLCzI3A9qr0CiRd2RgFEbiRexo5v9v0aZtgB4hv2IeSbBDHZqGfclM9A9BILN1tnKQ2rG7pmyUqqLQ3DhwVQNCdTm/piQi2lrg8f2wTLWr2jGKH7OMrJzR1uSWtLGsAGghOw1u4PGgFnD510Ezcdi4l/ME3g9ytrjsnokwZgzMoZkt8fMb/f+2Q6kPYQEgqiGX/QERXUSmspHpolr+A+MIm4xqewsLH2jbVXbfEZoJO5+jf2C7HvBkRsLpS3/ocSQGkKZS//RazihDfkmKLovxy6duJAf9fpHzi1gjrXirQ300or+KLUb2nQyrUzo/zGwo3RFNSfrSlENNhlrA5PrSgsaQ31F60VfPHaNAXlTz4PhfOaGekYHT87/pWjGcDEMhvzS+forSXUYlrOQV2SHwb/AINHUYfJCMoXh6ZRkr3nF3NX/nEuN0BsPZfjYFYZ2x3N5zcek+gcEAwo2FL1/wBkj1bW+NBXDQNBJsa0xQk+1AkQCFxxYQVBIQQGF8Gg0mVScsdzpXntxLVqgO6llW2BHTcyblSMdLHLsp9TTU1CnFYp2wFE1ixZlyg1E5kMOyk6KjKjWWEoCon/JyO/MQt7D2xK12r9AtFpOEAhEB0g1aCBQoBNRuf9uLfyVWZ5VUCtMsT0eVY9tQ93BdOEgVOaZKjXfJAiaQJyqfWYoPbG8EWTj7QP+Tzscd572qqfaUEts5kM/yIAEBR0DoFDC/l604XAjbXumsaQuxj6Tb1XmsF+VT1XIter+mz9g9iJjC8gvlitr6KduBDxBe3voOCE+cIY31ZT+xOAy2Q05jafLR495yPzwsz1uDgz/Jz/cUQePUxH4k8pUNAKsMsczbtCcd2M1HMUCAYh85CZiuRUzh6H7CdNCvxvgUJqEJGcHtakOT+ulXekpezy3hi+RR05QDzzb5bv5qRZw8gAQoDRTuWJNmoTkdL2e9o+TEl6pyQ8Sa/ePt4G7AguOfGMAOgNV4zB8c5bZBEwZiMHhdX/AgtXAYXOAooALowZyZ3Owz6sX0JOvvqQ2og9+227CTSh6Al9pyTfaYRi2JKKQ8QgjUHg0GnRbdrOOTNm145eMEA2Y1pgNAAjTQmQmZRwrZ8yaTPPYBRSmWmWf4aZurZ+kk6DAkWQKFOVII2Erz7a9Cv6n/526d/T+mvyzKNvB0wzEM19MFeA/oZxBgg6DQRC+lCdKzZ+AELCxPyhAGPxeln6Ckx4ahujUGYj+g7iq9bpyg2si5/9Vc6bdQPxxarWirFaJVRzFxAXgivIgnVRd9XSJwMMJzXU71NTeF4/0lK+gJmoNtrc6nNZLMarIVPk0XdB89GmaWyToW8JAxK22Fe5EC2Amc8gx4zmDudeP4tkO/d+fvwcFNoqEFDkhWsLGnyKDglKU/oD78/gqKRP6wsdaftzPgePw8wkp3Ga6ael/QlRPUNR63xTuru3AcOO41096DHfkP0/O3ev2ElmFMSo4AdjY1rOoBQoXA0FZM8R+IoyIF0oACjt4Or7rSmYQ7o1haNq7BiulikJ547AjpLRty2drq1TtdEKkg7X4oTW8WwK2l7a+xRFIJLkNpkH5GimRpKNulrCmUw1pzzpD5JmF81YGhtQVcJYQjD8NGrArpRPA/1cSOCqtxZrTNAEZUx/M22fgAAIFEKEM/SDAYU0xjsmHZtV66ufigmI8RyMgfc7nNEiVo40LacsCdQYP+815UWUhhiBoPYpv1SZJVddr0BcDF64okxIkTN3oYwpFWGEQG/YFHz/phnoYljBAvKiEW/9n2orgUUuYP2CNNNatJG0iY0Vu83Vo8v7UX2yvY2pKdz4Ki0gF26aiu68cMfCnQs3Ltwok9ItM1HofHHJyKBZiUEsoLma/oY2H4m540LenMW8v+oveR1XmZL2P7z+ImF+Vbp8LqgIrfFv/H9kPhrJhoAgItcLNWiVRX94nGnnb4aa59+kTURRfpf2plm8h47KDORlIMHoDhxOZZhGkT3A86jn09l4YABMEtVBtDY9oPorQelstII+H/9OXWF0Ax+40WmLaZ6vzUadwvKCjJw9V47e3Y69oFYgu/pzZqWkv5p7oMlraoMpFynmN7TzgKNuxGQrNckcwKt6Ks2QTQIFbAiIOQ9fPukUmHkHQCs7h1Yr8pbE1aoqX5aPNNJIiKaaSCrfaD44Jcjjb9og7TvPswQT1xi8rn4Ujbkmov7LjnuXaCK6Io1JkDBaa9+CCRk+aXKusyXCUGeG+yrMTHKsczRO5YyaoPZpwpYAMeXUVt8ptMz9W/bd1Yan/6bLkonHNIVx5j/mLkQB87d9ePAuu5dR5qM2J46Zr30+pikc53Zks98lSLh/KeLte/8GGP4FKGhganAn2o6aUWuZYCN2mFTFZ3sBIUn3AxCaK4B0raAkeyTXIEJ03sr37l9QtNBtcw3uLIa39/qcxrz3zc9pH4Q5BmULTjK0J/MXA+oEDbCHhmDMHYlm4mA+6QWdUyYgOpLLBFTXX9QfLlylFaDSSuZbrV20+eiAE68rJdlml8M+Nr5QmgLtvRG4wPUxE0jcyLw5CDQTLDmjkhOQZO9rY36Q5pO+lmIymwxFK6gWnciOU+UvrOIt0lKx2W7bADUVJTuAgBI2pbUuCdGkUdcUMoZ3LVu6oxjb6VRWOOqSf4HcIEi3LQ40yvHUmsInpmImiXCJ9smYhmFVHU9mqUXUIscuvbS9J00vMxGqtAKdg8z5oqZwrQpmWAF8XdREr2hNYbQHgUKaT+EuWlg325D7sMeq/R3WjdgXUsw/AKxaejvWr7K9xwbixVDOXwQQdehFTXHXmlq9dbCDggQR1xTE9L8IDl/tZH5ltU9pBKUdvOhneKU0hlVpEXixz15Q/tIU6m8czrm4t0QUGO4YTSFv/X0h91cBorQHXecC8osawlV5+jsGrEi9wAEQPzv+Yp6CK2OUeqBBRusdGWcY0skGHyZlu4N4mxTfM4/l6AVaih8TkUcrRV8rfR8MfaKI5GDue0rTwnmbvgdPk1bB+w1uTWA4wOHQBvAAgrbRcnjmpB3/It6ltCBjN1BYoPmIvy+Y+Yj3BS3yMyx7z3V2bn9IGWWuTr/xhcCNO76gWepSt0FgiH5ObSJJbQ2dwCRczoYVILQgvXiPw1m0VW+qL7hzV9uxvHL+AqPRcBxoPoL9yUFczuwBDKUJt+Z56TQKEaAGYI5m0Xpq7+BkftWdQkTA6MfGzGFrxswtwId7kzZAUg1nEqNpcopXD41PgUAEkDQ/aFkEBIq5Sksop+aKCVyo+TAxv9f5Jw0BAtWQi1VIG2y4G1j/oBlIvOob26lcABArkPEPmf8/yPYz/MMmvOsvj9kA9d4c0+I5Zj9J/TQf5ReB4MKGgOKxVDn9BrenZzmf765BtEDZC3CqhnIEb84viIXc9Jfsq3wLmxFIcY3jedOURNOTQB14CAk+zg5Q+PnxY1DYh0r6TuCu7mRKUwCQUl1Brj/MuRkwKL3Lf2ARRO0/oGmngaDTJh8ECkhK/3IYCzDCwGdMS4pAckczrI6zZPZoCd4aw/71f5jU+vnfRSnOI4JmhvJ1AkSgNYECgf+3vXfbstzWlQUD1Mzd//+3vZ2TxHlABABSyqose3n1GT1S5WkpqRtFggjcCFJ6s6vJf6U1mBsuKz/EcJmW+D5YpnSQvNqTE3pGFV2ULME3vOJae8E5gW1YaVAGpi/pdAKkQFFrHofdmKfgbFBFJ3VGLKdyZ20qG1C6BoEBr2nMqWvqowRF8K3UCErd7yDi8PQryEViDi00p4Sgcd9i37u0JECJ2vQtXYColt/BAccxQK1qK+9/y4/QP0425cG3l0bQncmlTciXUGLEsBdp7NU0hasmSxIkLmkIVhMjzVTD0BiaVICacvhGLNW7aCJCMGd7sTFfZC3xdwDCi9e9AigwEeu3TJi9AERUU8yORmoMe8OLfnafAmDpT1h2QUueTt9BYRIUcn0KXPTBtTUWyJxTyAXBwayij2aMVl8XfFIQmMX8M0xVYIAAiJzsZtG/fYa1vk1fXT4FtP3vt++Dwhrtr2jkIHpvmgBKMmpLmhnTL0eY3kqJHnBM2u9XMvQDFHhdmZu+iEhy1bM0iwSIBIWKRJqs01wjQ0/XGqxy8104B6B8DEnhvbmtmEegQTmLvTH7br7pTF5wYqUNWA48eyij+YhqfgAAzUYeYapBcmGiurw5qX1QMu6DF8Hkl7G/XlhumA68PPSDF+cmSEYPaQ40HQ1GhMncF85nyDjvISeVptBkCh2bMZ22NpmNxPQlqwNagWsLPyTgDJqkUuIHKl2/ldnIFtnrwAYgyHvrfYDnHIfd0YzyqS/jdaQJr7tz0Z5GM7JPPaZQQAt1tAeTkRj68etl8guEbf5Iv+x0Vub1cW4wNbOZQGHgGq/QQMeVJswPagofY+A1ImhBvzFAkHDUbOM338HEmDQ/CozTNDS4utqQueiC2xswgw+Hjwn4G2tMpmPXkJz8Dq0ZTVo1MpLkWZI4golmKOdpPvKakzDXhUnz0JvawHsNmo6M5iWEQxoWP2+O5gMUltG84xfMY+6Bvy+4X/D3C7g+4OMFvGNGs88X8P4ArosAORCJAXcnea6ux1ZIAcEMZfr/3va3Hc2EfQAyG/WR1VRGLwlJjtp0AkNMvYAhz3kHB3uMTHKKd5qkViCCzYFcmkVJ/6AUh+VZLxxJ76Af9mOroV2AQCk3+OwOEqOuTJPR4LH26cxDDx09wIPXbM5ky5J6rtM81U1UToBh3crsou8rQjKE49i8P5WgBIWmBsgtI/BjhBS4mQ2t+h1N1qeBPswikqKdzLlkO8JPtnTW1nvZQafH30Za6LcascYRjF1ui2qCUBkcvifJ81YWOHc4nbG/KOsnXeesn0wLu4agsqe/kdfXfb1tRHM6V5pCMAg78uPIgduoB+Po7ww6MGkKV9Nwx26ma7Wrb6fm6SEaxVbO5EBmmVPaBC1zlInk+Rf3AmFGSp4PpfqX4NOFOQEs3Dan8vJyNPf5BxVqejqfFaIq7YPMufGQ4HFWextsdj6DDmRPK0vsgx+NVtaklkVgUWt7f3/RR/VzL/v99gfmI+n71eFaqzVVZmcUCkZpCgvxcShNIaR4a4w/Qj/n2sEgl8jEDgSLdZA5J+cZoBzNaRJyNE2hPyOGaK/H4otc+Y0SeJAMTiCQxxpOBIaN6TfmXaxVYaLXzuzN6OADnXunphAmozGU5wib+WhghNlIpiIfGEsAEOLwWBYx5M74fNQwKc2IDJoMbmExd1UkrJ4k6oGFaQajpkDUZVjvZDuG9JYzewlOKSeYQ3MDAlPpPERndWJsJblrnkSyS5O2EM80grPxQFlizTzDk2x5mVt5/RJTM7FrY9itlUbgkRcLQAumGGHDdgOwSluQOUtsurf5pimIAVHqY5rm8CcUI9o0A7P9b8g0xNw5NjAsJOCRTmVO9jKDnJXmIYGaGwaDCsxeGEPmow+aia6cLPmyC2MYXmZ4UUPoy71IpwkJXhFXcowHnWipnvjG0CyXTdKqaOOC06m8zOE24XZh2RsYnFRmCBrDoOo2N/PRLtnVlqDiCucc9CNIU4j9e4z0IbzpdH6vgemGNwxvj+CVdD47f6iQVP0dmh9BwV/hXPcX/PpITcGvVywm9I4yvGPSXmgzH+Hnshf6nIqeJkMmrCRsvrf8ob/f/tB8VBJamI5iMESMdHSCU80uxKOEII0gmbD2ngw5TUlrZ+DbD03ax/38rknsvoReVlqEgMFbHTsYxK+zUDiS+YeJCHksB3LJ7s22n/LYSMfx1Us1rwBXHndQUNK70Z6bmgQUaUS7sDf5r5mPjA7Ukd8U36UUEvIpDEQbDZdP4QVJ7QuTA/rFvyOVgcMwfAYwdwlIMfzJIqMfjYN6lUCTe8l1A5Z/BWML9llSt6FPlAJt23pWpdYIOox3SROoLddjsGqX9GYkw+dxmo1isJk7NTPW2us5AcrI9xmQUp5+u1bQHM03QJCEKB9C9yWUHSy0AkrhNJFYAoPCrppZiVlIB16kp/AlhWnyhWEX58IEDYZvIcxGCUdGkxEkUGwxuvlNQmWXfwqLx1GWc19MZR8x5vGBRUfzoqM5QOIDLs+/VEIjX5L6psHc+GLa4G0AdCq7v6B1E6ZfYe5hwrs0C7lhERT6Os0BIpamojouJVKaR/cHDDmaJ30Lk47mSefzHGE6ojYVQlQTGgQKnFWfWuUBDNjKfr39ofmIQ7ExzDQHUH2xFfEpsaQjgYGAImax1kpGPTmTOEJCe0QQNnNQpZloSJjqWWkUW1irtIzDcZ100vZwQAuYyz+SDZnfXsxf5hhwr/iNkf6DMv3sTmKDJpTpXAFA0x7Q/AcwaMaynguBTb5/lNlI13EgDq96nppCdibzGBkl/LU8tI2Q+TBw5bWXvbBcmVPZMj4JshezjHIpTwdBYVByRMnOJuke4qVkbMWuPZlpJ2iBixDbKCXuIKOHBgOho1kF24xK5PPEuAVE6SNLTUFg4Mffop2qbYCTobSXrBj6WroxyA37xLKLz6yIkyxTqGlqBmT2yfx7agQ6NNF9C/Fc4+QpE92xLESWF0teIcTYlRMjU8gxgUEK9wHYCknO9pbA5SH9kk4WIgWOM9zZ8aoHIXwJiyktlr2x8AHZ/t2AJd+Ezeg5izBXaSiRcK8PcJKEiylTg2HI7nI6fsfAJFC8KZGHBjDoaxsUYgsc5gpH80yQgOCNBhP1NQVoi7xG5WgmOAggBAx5/qoMsvp5matK8C2TYwmxZdT7zvYHM5p381HsirMaX26KSc+wIdA25rTpr0BamY1mMJC1gPfEJrlvPgLffx35ulM4ndDrvP7QPppZCmxMgZzMHYqcKmkMGb2TErid8f8VLXSaijoAZPx3lu3nMkqIMdjDNp0CMNTg9KiLAKDVJMCAAzR9ChBTyt4F3NOkhlUML6K3Fi73ZDIA0im8aFbSLGf3GWGqa8Ei7zZ8zpDmMLIzUmMgE3CK1mVuKYYajF+Su0NWaYWgunlEQSH5ZYrprn40YJk3LULaRiOQJIaVEUTkIuVoJkCoXW1FXSWoGLVnma6CaJBtrlXw3GRUGq3SByjAUmJGplI2wK6tTCYfwGD2gpzJa7yaU1kGnnBSmnMPOTwHhn+UxiBQsP9hyPMVc2BsMMCBDmYwjsmdJlQ5WpzovDjWLAU+c5ok07zLBXZMNIa4z95w+3/ooF2YaT6acHxiaaj6YlROOJnBZ6HNdN5I3YAtZ5Az1t9fYcZZA3O84G7hXDbD22U2Aj6d5qNlmCtMQ+8lwIhr09GMcHvL0TxTm3thKPT1/SpT0fUBHx/AWyalD8A+AL+oUTECCZyXQCvNmmrL8r9uvqeSs367/T1Hs5gHmbOJQUsk0zX9B5lriuGXuaeX6bgYPXCCg+VxdGYBw6Y95PsTy1p9Wn2dOpCLGWFnCrnZ8a+VbL6E0igksXdzU802Rt6R/gZ0t18DG9/fY6xj/iPjr7KSruv/lmV11rMNMw26wLCbnfiOCAMt4GFGohjM7rSvl8NZbbwFIzTpXO9P5zOKmRoYBEAwk/Dp7Yskl0trSbOfrpE9qiAARt1HkXN5S5o6i2bzJL/DQfMRwGgtPU2034aJ5ChZNThO1DtRyBDD1vNllGnAof6zUc5inW8OZOOx6zppGZrYllqG3td/xuCC+g2WpfP5oLnUgASu6cBmm7eJrfpFO0ToepnG5FTeF6OvCBvt4zqnRqTY/NKoPPxSm/3XWLfGB8zKhMT2LSYbe2U2lUN4tW9Y7Rfmm1pDYQtuAUp6l4ZibTzwp2d4+3s3wdLiIiCzfi+AzUTewCBJu/OxX29/LyS1N3jn3O6wxXAO7d2BGQTo09m4SlMt/0GYlsJ8pNDQU1OoDhFT71P8t4aHfBetgWE0Z1RjGiQpWJpe5AwNCtIA3aFgUJops5Aml2EzGT1qCipLc9DI4Xf6BaL8orlHvgJKp8YFddxgY2RZZlM1MhCUVlBpCmSrPzYPmz3aRL6xPMDCC8CCCUbHiFFogLtPYAG+PLJfOmBc87qrZoIFPiRorPMSpLAfLEd1BxnPdr1HNIceJp6rtUaz4KBbhObqtCku6foHoMEJtqQLLSE5qD3VmiLSdJxzIsg0aV/xEb0afREDnHI2KeuintTNPK88NxChwtIKBhdgAbWBkAg/wkzkA24v0jBz50hTcGoKNmB48WcY+AhKdGoKPnA5NQW/cDnpcsUktssNYykEVQYSAh0Wm25h+cU25JjHYiAKu5ORbhHQoH4Kelp4c78wOachNIbP4JOGCGVVUINdQYNwKARWYWJdYEjeMEaYaOjAxbq4SE43H0lTCE3gkxrDexk+acvX/v2FpjBFGex3R+Q4cryw3i+YHM3vV4akur/K0TxecY8ZKqtr+DekKdSEOVG5Je/8k+0Po4+K9AsIgLRHow9+Y4/VACsnbqFpJKM7Hct+OIfrHnGMbkK6aw6lubgkvHOQo8qUF8YOIOjSmCKJumZQoaG787e0gd2p/AwAPTqpaQ2c51COa0lxDaJ8pF/j9o+8Mx3hVm23RcEc4OAOJnobNCEFsA/2sbtDqx7Iz+D8nkVNQZkdzQctCYMmqdYvEG+3EuQBlK3ftrJyGCOZbZLj4CzjFAitaBNG5ttoFuHgLACg6WuG9LrRS5uLkO0sBsfjYPNDXxKDMf2+pC2mSlZ9KvUxgcEMXUqWHyBmHgsoJK1XmZ1l9Am4Vdm21u92r1b5IhX6VY7mdD7H8+IdCoG+mjmN3eRALcHqVLQkKDCIAZ4SsCvqx6UhAJ5+q6iXs2xh0cl80WQU/ghHRCxFqKcTDMQMpRN6jWlVz8gTNN6VTM5L+whmq+R2AQJzFSOey7hqI8umZTqL3dFcNn5NXoNZOJDRJqhx9rLPwX3MOPc54IN9t3psl8Yj+d1E5XPrcnobC9/1K/w5KJSuDTg/V45mDykquH1I+2n4c7T01OUY6aCQoah0dObHHaCgxV0ySkOonz3eAAlBhEAwuK6+xtmS1KKTgEwPYJLsxKrJoLmiWWoKY89IGkIqQ0dx+hTI/g8ntCHCSSHQyAHO968CpSHGRMapKKWoM7Ks51zS6M3jJJDs0B0sF6g9DUp3F5X8kG6cczh1oxbONH/Fdb5gixIiQcY31Y/mm/LqR7GZejUBwAGmUaD+IKV18DvoX4w+RrZDmeH0zIQgMD4a7pN0OeDr3QaYJ83Gcy2jkOSXUT94IhQNEcQfTw8sRdoh5g5o9rB8CvHESl0gTaGbTqIPasJSLdUYPgXX3i4yH/kjPuqZ8j1QK4h6hK1afoThBAUfuJbEliu0VWqkKWwM6o4ZMeBJX5GpaqUWr9m+RiEjQCImiplPwF98Qkj54Sr+CBaCiYkPhEjyP83PQO0A4He/GyiMfBa8JtpCfQNaD1KzurLtFp3/qSms+C1vvoRleK9g/HO1cNTUFIxyBePlCAqeIB+ztHvuI6z4G5N5jeYLGAweSF+SfCBNyJ4FBkuCcI6sEsS+s/25+cj1v8ax6ZgMR3OUyd6KNcJr7oo+2h3NYUZa0ag0MwQgyIShV0kbGKUxSMJIUCgA2HKSS0qgjbzKcmgj7a2OUO1d5pcdFEaufRypJKJsNFBg2eY4HlUmYKEDeU+JHUw0y5zA4m0gEgDifDCdyoJaQPAEAsKCKtOFwWxD+g1pPyaiDa5f4Li8Yo0MYOigM4abIOADy99kpgu+Zpg7ZqTWDt12bKKM/i/Hc4IBCBCs6hoBDCAz4gVktAA4JyMzdBLQDMj2U7xJgEHImrEOMJnGm+bLt2NxvW6Fumf4KUCnvmJ8ytltrPMIqSAd/G4XQ5FG0qBREi/n/R0UOlCslJ4DDKK9OCPWRoRpWkTrVM04J0GOZoZfRrjqq0CB0Tc5TwEXhsfchcsv2GqgIK2VCk/IBRRG4MH0YnYLBveWVob4DkNkGRCzCv5RPqmwx9N8ZGE+muY0G03uB6bRMm0Lyyx4C8hMnZoD987IkjT05QQwSeVs1zE2UJheoPBJ7eBzBv/6XIb3DPOQzEdyNDsKFCZqXe2YUg8sf2F4mITkaI7Zyy9gfMTeL/iLiwt5zHreUlssggGQoJCLiiGHGP59R3N/eB+cLvHI6vrt15i3lIs8NnbeYTLqH9aeW6AAcNQ105LtdUIN5lJ2j18zwciRI3PLoAiaoGAChcN/0OcVHKBQYaX78f5vpASaZYZkgP3KxtEJcqhoFx5XSCA/UZ/vVebtKcEosT1XgAwCUGoOfcDD9WV1rLbkPZujeaMFERGlzXpdlNE+4QQC5xyLqGADRvCb1U5qg6bdJSAyF48D9JWIgdDEsRY1BwvBZFpem3QkjQqmaVNQ9FScbnRvAgMJIJVfyCSIKDsptB/t+JXnsqxdPyxWBFPZIFP0VlaAUL6K3cGse8vsJ6Gkjo1agsjF2hCSz0l0Fa2T7AHN5ydag3yAzbmKAIYzL5EAIh3NpiU09bO2D0iKd3jui4941ilEkAJlrSborvQi51wEo2VD1g0l6rTMwCxHc7inWnZU8hZfRRPhWOa8hEGz0RqkPQYHiBaNgNLaUXO+JLwkT21BOUWP+Pb2B5rC1d4kXUQ1AX8Gm9Ie2MELqSkozYQmrCkk1TkT1tPRTE0hlRERDTYASNlyA4DmD3CxUWX97L4COfqudiytIGKpZVOF/AewNAsNQ5mFNu2hwMOoGfS5C+WX4HXSArwc2APSWFhmdS8ak+v7YPyHpqDtONbEsb75fgHE9hQXEqp9SF1yLIOaglGyMwws/2RfL4z1xlqGsSbWskgpMUnB0ijT8WzBeIHUDsJUx/pxmUc3A6402LcVv9jGPUxY4I0OpyJWzbZ908S5sD6BtRbme2G+ow/WlNil+lWUmJJ7BC2QYTJBnI2BdQ1qCy3v0KC0beVAPkEhtK9yOgdz0nKQkmK1v2hrD/NRJI4LsHGZj5Qzh6uVwQQEAim+31knv2BzkH65yI4PjMX2TK2s01azm0Np70oYU5RQRat59oT7C5V9VrOeaVpKM5JjmsPtjTcWlr25CJTBbXGm8MKyzwYkM/b0GQHUULyD+ECs/GYAw1GRoBM+hemWmsFy4K+3NAbDXyz7JCjIfBRaRpmPtG6ys/+Xf+C6woSEFzWFzw/goqbw2cJU7YOAIUezNAXA5WCeXo7mxpZjbP9roNAczS6R03LAhGOyO5qH4k1R2gFtt0y+prK1RstLFI+WLRcNGDYNIc1FHQwAtDIxeUm6CQbFomPfJgP1smTeae4pTaHSVO/ag+Yf5IQyMqiEgrTztzJJu2L4XsMpy/UN2fS2+RX06QKHdrOakcdy2j5Ricr3twPxDZp/KkvtYFTJAtMTQJrCYOK9sB/Lr6S0EJrlrDQl4efhmz2VibC4pBbE6wYlJlCSzdQdBbbl+D/bneYjJrvzFK8WI6ZIh5LWlmG9o57laC7NJp33WSVKcEbJzi/6tir5nDGqJ6R8+RPCBDQg/xadxQgJGPldzXwkc0emUP5ARtBkGc0iAgWE+cgIFJZ1kqmK5ixvLehsR4V6NY1M9NY3f9QUkCChkGMtbCOaEQiEXBAJ7hxhMllYqRksAMtedDS/CBoLM0HA6elam5QevILJMVkplyanUM9czawYbweFmf4DOp1TW2iOZtfEtYC/cILzeVbCaID2dUuTHX4Fag/SHDS5zYp3JSgkCdu2tnyX1QGUpecb2x+mzrbGtfUSz7kqkWNeNmNTvFiWLcLY8tFyHnkDB0+NQmCwm4+sgYNYl0BA0QXF4IudXmSmHASHVmCpDVxbmWYZp3RITUAO5FfzI5RTuTmkZUqSbdu67CRH9/4PjjpDLaLz7xiMfMoh7T8N0u1cHvvjhX67ruosH8LIfgkTEgBceGH5BNwwnOkLfCZoaD9jGigF9QhZ3tYsFk0RvJaBOfUtQ28hyZvaAeRzcbrkvf99JavrmoJnlBTtzFx+1Wek6FifhvnuoEBAdrI7Aa/aaoChojSvDTGBKxyarjDQC+HgNZT9Xk7iAoCK0TegaQzSFIz2bqP/wG1g2AefERpDLtvIZ9QcBZqj/AVpx9KM4Ts4pPYqTUwg2BVuNOZjdayAZdGpDEcLloKSm8JOL5iveL8bYhJZ0MfEm88LV3OEN3xgmdHP4FgWkOB2tZnDi8c1qTJs7gxNNUnQRu1JdFUM2MHwUqdPYYac+56lOXxy0tjnlCO90k0sTixLhi5BwdTX4fjP5TjnKxzMbzqacQFvprvQJDsJHi5QiPevGXxTATvIPvjXNQU0UCAVNFCAY4s+ij2AyXkHK8L9ouKMalmAc0ZzNy8FYyktQRS4p50QVRYAyPm8rzcrW6wcyAUAQ9ISVWXAUCmEx5Z6wrA7lV9bmZ7bzEdoUqrnEGksqpV5lW7nvM5rs64NnLz9ARQ2CLDn6zaakQAsG4HJbu4AHW/RP8yN745Fs9KFF+CO4RNjvaghvJmrbMEm0xxMijk5n6Tpu1lHw6J5yH2E2chphjEDBp21i6aiIQCmXO0FCpv24w7zdzAeBpT7NKz3G2sC8z0w/wqtYb7ZB/KNgI59OJTfwc0wrqCJdZHGwBQGGIB/kEY5J4CO3iGTEopRuGjY76Ag4WVRU8iUFjbg9gHA0oxU0UbUFHpZjgk5gcn4NY5cGkxpp10YSbI4gEH77i4yiJbiIDRwz3uDjTDlhgPG+QSapDYREWGTekCYjSaWXXhbOJrdIjmje5iRloU1IiR1pzZxkd+EjlGSs5Xv5QQFRyW8o1N5OfDZzEcBFIpMQgJDRFsxECZBesCG3iFAv8qp/A5TEuRw1twFuyICiaCgMNe1wIwQCNO75hetDswlWH93+w87mpu0d5ZJXUtTUjH8Mjkd79vKjudroG8A0dlqkxGtrrUmyZNlFwDwnmGtrIWYChxuDuTt+MFUJIkfYvTF5Deg6IRapfmM7TpdmmBiidFfbjx/0wjOi2QpNGSoZ3UMGKZK27A7rP/r9aGE3X/Zh20OS4Z9Mh3CBlzShnSdlVCQjlCq5UZNUZpCj1211i4GR49Sq0SAVR+naUAhf6prgiOaqWiUaVMmUjkTM+JI8zZw8VjRR2XT93RCjxJgmvZQ5p54puYjODLZRJqgEgRcGkI5VFNjlikjaa8LV70fQdDodAdAExU6eRDfDcWMXOY/aPi2NjOZdsRjwtFb8xrus5q16I0czRHyeQVZofwByo2UcxIRgdNwR8XsG8rMXBpahtHm3ATkvITYVzi9Quwj+Z2lVUXPUJ4iaVwOY/QTTURJJzSvt5nNKjMY7akGJSAFAQAyGfVf66Z/DRTmlLO22XS6o5n24sxEt67SINLpfGVUh0xFazVVKO19vr8GyEEsggVkgAHKPyAmb5R0orOVQK4Wo+9moSuBIv0GkubQAADK91JO5VfzH1zknn3egRh6Oo7Rx5CYPb+KIyZJdQO/O4icx18z+Yft6dpeRvu4WXuveGhKWYNmGAuT4JqwZRjrBV+OsSaGv+hofkWo+FpY0wMQJmPp2upKWo9b9RkWg03mBlyhRkui02IjaP1kS6vWjThu2k6Cokc+HqwFnwvrPeETWJ8X5nTMvwbefw34AuZnCDFimgtUEAz0bwSDuwhOyy/Orh6REhkDWJxR7C/Y+giTF8NJzSOCyFHaqxhU1xTka3C3zdzkYIw9Q03dOUdB7QQDXBPXDFvepAao0f8NJLb9TiRWIXE3TQFAzjRXNF3M5KbZjUKWJY2RWVJDMHjxAh+YmNQYEKYidE0hcgm5TbyHBX3ZFdqFTUyaqOR3cDimJrh1m1d+Nx30KMe4Jqy9F/D5bppCmo+oKUz5EkaCQq40Li3BRtCAGRwf0DwF9JDUWZpCLryDi2s7v5BmKQ0bagrr7Zi+Z5gW+01B8JvbH2gKkrq8tSiliEMjuGsJJQko50k9pqSCeF5X7eqVXYLpomQSb0o5XziQ0356OpDLqTxuZW2ugc5ZOZpr36OE9K6SsjpEdIm1TENVVEs52sN1d0DoGsIGEr/aTI36ACoGxvyXVGhmQWFmyJgb5jcaPhiaWnrX6toBOg2MdDRbk8ix6JbUvBRWpALJJFlZSeB8rnwIaUJs0nmVNUTQpyseXguZ9FDUZWFOSm3Bsy8lrMHkPI1v12SoDDUcV6vHVT+ZgZwOZ1NZAYCc9dEKtPdL0m92aRBUXM5qpzCk8940FoznMmj88B3SBlxt/SB8uMHSNnSnrWcGZCQDAyx8OMuM7ekIEFQYKUFVTLb5U8JvcKUPISKvjBrBDKe0BQ9ZxnlPpNowJRX78gSFAmLRjObkzKYpSH65O5rL4axJegFv8TOT+YjvkYZwagqHg7mHqZpJozakdSU1A5mN4htz7oK+te2/s/2NhHgohBUMsaVdajtTBYQ+p4EhB3I4lDx1nDZYKRuZhaSQTlZDMZcEgc5sCQIIdVuSIrjP6J8WUZSaQmoPkY4CCsPj9dd23T4nQY7mgeZURmk0BQQH80/gbOOKRsBU11Ft/AQGfbBGXe3L84/bFwMaQPKK8l1Y8SQfUVGGKC73mG3tF9csvjB8xd9Moz04F2CtxWsR0WoLjLhYyZhro/PXLaXxlOYuMT0y2jUyrDAGEBmzyQZvtEJFwy4H1mdoIfNtmJ+GOQ3zDcy34f1peH/GIJtvkK5ZJ7ZFvF6mJ5oCaMrBNRDr7DKrpb9Yz1f8CAoCDPPIUeSkMW/MqSe/26R9t/Ap0B7v1Fp3TaFJwNmBrXM1itJGKEGAzGwrO8jkgX40nGPYNiljEQiMQADDuhxmjmUjqsm+MVM4+ouM/kXzkFh+hKlOk/YALJt4c1GeCFMNDeENNE1hYpnTtNRj74rR6jiAJEBpkunPrinMAAf5FNzDp+BewBBfVL5MG6IPanQrZiqHRSUixoI+qDFwZrNrXQWaHjU/AUAwf81kfi86mi0XGtvCUv8dUJD9QDDb3iZIIloZJ110YNDC8LJ/BdpJK/A26Dq9UeWUxNnAQcw4rup+gu4s1nVh+qqynfGLmWdMNvq6BirroGA45yQ0uGGdCriinfRdpWG5t29ls940hLNMLfNU1lvu4fxx8ZdlGZz0ZEJwIJjTypDTQYAIB+4FWytTJSwHAcIxfEWa5IVYd0NzWJhzyGevlCPtzcsicRmdgJzeDFuvkKZ8MKzPak/JEin1hqABRMLF+R4VaURQeH8SGD7DbLQWMiRVIJuzrC0ciYPAsBie7Az/dA7yqC8ZgL+QTuf1QYmRsep09Aa9y28ghs42J4XB+2Q0+ge4KExNVOug0KKaWlgjrDTs/Km9Oj0VCf8SEPLWPE+Bj4AeslCsojZgWCOAIcah843N0ewr1zWYDRSmTe4LFLrDOZzNK8o8opbcJpY7Zk5si1r3fGpq62TuHRQmMvro8x3BMO9pTPcvUAC0vsHWxnYxUeWAZpQnGIxXhaTKdDR4jBF7C+FHi1rlJN8Jzu0C1rtrDA5ZZuMb7/31q+0fOppbGRs3ksuhAEE/lmnR9f6YvKfJF6K+Hv2QbNakGwyea3b8jfGXT8GwawX2UNYT08FUMjZQ2Gcol6YQPFTmkgKFTaJvmoK7tIgqU6PIz1Dtuj8nr+P/Te2UTWf7c562X2kKaAJmr9Oy6jsBFsF/cyjDIFNRle0mHxBQTCZHPselfcKYbNOCqdCsU+ki9mclN3I66yAnX3zYJsM4J00qeoM/n8ffrr2JvcUrWt4c5bJJBu674zAdg82k5e3acgirA6zKWdaDKbRqm4FmOFMZBQHVRX3Ztc6z31O73Ms2YeXx1gdpRr325esNbhr3FAiXxWfKxGHiDz2BnpLfydEcx0EuFyV/sEyhqKHRhfPZ6IBGvN+Mz606i3Z61gQtuZqgQNPRot2+zEd1fc7aZv8qWACjzEGeffvFT5aViMcm3TdHM4xmViOB1t5p6uzzFOJ78EfbHziaJbF0zhZ7o+QPSoUyEXGmCaxpCWFm4t+o1FXWJDqgGJ4AocIKxfzFlCH2HIz8AAXLMhRgoF23yfjN35AAwXvz7z3qqNjd/g8gIxXjVO8kE0S7hnLWVoatTCBx1zz28dmU/h3Av7Op7SVoLpTWMMik2WORdiIGw5gjzELLMdbF2cyRPwfLYu+GsRbGcjqlL2oKK7SFVZpCDk5FqIxBaTMq5hdt7lfEc6dT1Qw+41xEu1JosFKnZcF8v2kC+N/4zQl8/r/c/y/w+Rf2yWtsWR/G5HzhZ1oIKVCJ1FzOb7uAyUR06yPizscLvrjwzaBJaYRPQWkQUsLsQlYDBaOG4BRUXAEVqQFIq1Z7dVHL2u8knr3oa9I5EUPjl20s8tTnoPEys1RepofPKNKPx/2ZWFDswgddxM3RbDPzIE06mpctzBErOk6u4ZxlvmIeA+cyLK7SVv4L5AJJka+NdELJ/03h4D1JM+74fJNsVYZYhW1PwUMTtVmYT6ktpPlo/E9pAfMDyHkKH/XDgM8PxBrNNEMakAlGZziYlzv8XYCwJjWFpiX8+z6F3KyJT42A208STUq9fn9mAQOlFKvnF5PrgLAz5ZL4ec6OqKIs2zWEgpOmIcDC3MF/lw2Ogx0UgPJiJGh51TMAsrVU+/5Uw2WWeDQZYS/b9gfzP8s2reF4xldbdgIKtIaeG/WxpUtKG7Ss711b6LOM4Q5rLbbRSA9PJUBG01A6khMtNQX9yva+awq28b6Q7DUHBqkBKM771BBSU9B5N4wMQ0XaxZWTRhJu5TxqWoBCDbs0aKVR5JjpDnRYOppL0yYIoL4TJu0grivoAkEBKN/A07YNNpaoh3n+fkeTOJwyuZO8CjC6xhDGAYONCiLpYenFsEY+Vzb9DBeGQlPB9B4IX4HWLc4oLTqazeI6H5WoWY7mExRY9XifUXjQHrXmC8Ei15WX8zlBxEi7dAxDfToi0Z76XKAvjflRczBowYjQFEY2amZGbWt+etMU9EGeFph/DRS6piD4oSmIEqXT6RgtTb1wAcqAmPdTOu7kmNINkJKNNIKU5wUCm+kHGQUkDQCKDEIHA7L9Dh4cfKUp1IDcyjqjIxgBjDRyDdf2HW5N2kcx+dSWwI4zVNxYNW0CyNbcBagVnqr7unbywAL8i+O+dWFSgLBpCsjIRT3CSJy2LDUFxeMPOp/laI4BdtG/YDB/E2hmMMgFzUSSAhrHZhmFUT/a0uVgXgZw1rpz8EST6aNcJJcLOr0/uf/L8flXLPD0/vTmUxAoEMiNFudBADBDT7WMebGezEiq9XZBh7OFluArlnn0Ubn7c56CFRBomcXuAC3xm8JWcxar67but72/ngnjm9zCzmMxVS9Nv13Xqy1H8+K4cGE7Yqxr+olxSbsCC6WvaJPX9M+C2SskdY6AkjlGSO2a0DakPcw4XkyFIYe2pGlpkV7CABx4T5qLJvB+Ox3NvmkK7sBMs2AweyN9aC7KYF9nyhH5ExSAgHI0xzrN1Dj5dzqa3ap9pkdm34WmKRy54/BngAD8E03BSW6bo1nSD6JhmHlS9uMa7fctbc5Wkk0x8B0AlEL6Sgdyd/5yFuvYHc2nNtHzEYmpFhiojHZxKybfNZZydEuabpJ8Z/Q54zvaTM/KyN72Sxs7enmT/AUI2YyWx38bEPaO2LUGcMA2/iEtXz4GU16j/AkQytEc4PDCiCxeMYdgAWlHVaqJ/H7KoFotb9KElMsSjhhQuj/BQBIyP9nruK/b8f4MIPj8K4BhTsf7LxAcOijEvYOSN1aE4MIMfsW7HRf8ClNZRJKoboww2iJNLtqYA9g8UyJTyjTs2nYHBPU3ASE1tsaxb8AQT0UZajsxPEHGBvv3Uzznh9TjCKcx+oQ2VVuuEzJeM8u5DIv9Fdau+KJkzm7pM4hpaMpyFNm2pAEshqUuJsZbI6KV1jCstbDGxFrMjmRvgsJKWFvemKjTBMPsClo3/j0JEA580mQz30hHsxblKRExTIj7BMWr5ta4ACAijTSvJkCCPxsRfTTiWbGWNIovvJHp3n0ivnUSHNz/i47mrbDtU8UtNTZUpQUk8RIccJCbFSh0jaEzcjH9XSsojaHOX3sZqD2gspr2iKSaEWtMTGfp2EvTR9WsgUYp2QEI/JSNgaM6MBox2mLTCJ5/escuzLUyvTuPLcvb2N376Tw+N/ED+RNKmy8Nol5d55r5ZzMduaXmYFjlMJVmk8wPsddzIHoLVdnkW9jMk82Ry2cpUimbiYNCyxP2JV/nmyaA6WUy4mQg53E59FpV+0SF06ksx+KTKaA5mX0ZwWTEBDh9m1V73FLB9zZJvt3MRdm1ewbcYu8N5eH67+j4nRi2cJDO6Fu5k/DNkrzrWpqNkoD659AMIsd2q1ba5jWvKdi3zEc0LUHLPNGklE7lhZjkFeDhBCCZj8LZTUc0tYXF7xE4RIQ9zY3OME93zldwhqhqZjOfxfoa65nmI/S+382Ku9mopR05fpqngEFH9qr6wZFzFOJDPc1LcApW/xYo1BrN1YNi8GAFMyEeYm9elUtn87FlfH1GCyE1gYoSwrayWQeIHRTGvqCNlSPaUHMMooTvynjwJqW7zhmdxNbGhFVE1NqEpwdG7+0YosyjrN2/6jk3QLiZk47uYO1+Cwa/IxB+FyThpUDpTWVo9eU32OxmpAvmkxoC29rDLavkeFgXzUeDjma2zxohE2pAGG2xzCAZoZ5tpSo5mClFKSWyp/RnKfUFKCz4WiHtTcfnp+OvvwIY3v8LhqZGSCrccj0F2jdgF81Gw/h+qfmSABVyelXZilBDt4hBd4asxqpjvNbY+BKgZCZA868IODbO+9XWCaWj+LrTySOhPDy/5A5e6TkA/NAQgn5IL8uAEfTjBLVJMFCASGAGzUf6ZreYpevBgMvpHPMNJqxpCMG4pw3MQW3CIoX2tDfWoJ6xYp7CzCilMEk5EMny1kofglOICPOR45Omms93lckRnRotzYFmxjTpDEZgrqPImHvB/CM0hPGKMr8QAQks20JSI9dV5NIy2rkAn7EglC+HvwMYQshZCWiUi3477Pv2tzWFlC0yoqYkKEmEnrZu/Wpy0uZMbr6COFegcDcbVZbSXXs4nMrW/QelWWyg4IDcxTqqr7M0He0CU7Pfo/HIGzB4Duwan2orlTWAyIa2vWzTChow9Ou3jqrrH4HAz4J94+RSlNjWn3Xcp/Pej+MnjaGcbfHtXd/a6IZMoDNC+VZSImraQp0TrdV3l7Mw2riv3dFDTdfyzdFcuWMMml2djlFUuOEWZSL7yKkVyByKqnMfI57fUSCQJqT+XgECumlt7+azj8/ZPirZyrI/jee7trBrCfmuhhcqc29goGM91oqeeviptOBuH4faQG3thlw3wCvEuKeg8E1TULjqSIAKgcJCO8jmj8R4yqRanpFohUXHdqa/9pXO5HQ8t1/5P3Z+lxYT0od32lBQActKY2jl/O7OR5MONPM/zdKo7ADuadZV+6prvrv9A/MRpV5IC2CHp4NsNCn6iuuoYwaj5lO6nV9RPYxby/BPaxPFMkspNq3ATGsc7GVmSBdyNykZOyeTtGHXB+AEJ7f6VCRcIIUktbgoS7jXtYLWedtx/xvt3g4Ka6/TDiI30a11GL4u+8WW474xAVkAJKR6dX38YgZRSvtak1mzljXJzSgV14xmb85jHa/GHEZOhnT6FCIFxchzSpKXydXUFW3QTk3wmZL8ynwUs5hRE9UyxUUMUldoypCgMGD+inUGvPIXaYW0XN2szbZ2+T64iIsbNR9EnpyhmE20b/D6FqAPajGH1u+t4+5d7O36k0OcgGB5h2hre57ILMnNSzKy43wjyVjLOR6wpjX/AYGQJj+DJ3BEHzLNPoDpFyYzn4arWXs5n8EJa0az0qI10qlNXIhFeMLhvIx3m9OZ7XWfO7UGxNKai45lahFzee5n1xRA6wbEv67sa01AQ6MFrdO8pUHhL31OM/xnYWqU+ZH+jxVaQZg9LQMjltJceLXld8a+tm+DwsaI0Jikx+AtsiPDpe0hznUO4thWDpPknky8nMqZpbT5EmpBm/AVqEyaQy1y05zUfa9/NsrGjTsgZJkYIvqwSa2ZP2u9cJb77mh+AoqnH/pzj8G/lVm7/qG//hAU8jppwxJg+6v0NyWS/J5MihgST66iJabvYVZCW5O3JKaQcHIpQhAcBieHCQC0AI5ZA4WBZTtdKlwwtQJqCpP+gvlJTeGN5lMwOuroQO5ibHLCcKJH31Q+I7BM6x2DJjOFn8o2HDlvLEEBZrkWQ2f426uFxFsX/g4QglCUMaCJ8xs9ef6/AwTavW3rpNaT4mGnlw4Q2z2JrZzfYtHmkWsL4Tx3r3UIPMAgoiyZA8mV8iL8CAEK9BsINGhSClIMv4IPzVMILWjZhCa6yZA0va3y5gZ3r7Xkc8Kap29qzb6wTQMFagJOZl5A0I7lVxBAJF1JSOI1DEstzQHQAlXh/yIY0HQkjSE1ZfxXHc2cwATjXqYUDuiQzaHl92BU/nJau4ChmYWaNnD6Be6awrn0pZg//Qi2zzgG35UhpuR2T9lH+4CzNhgFBN1vEGXRAOmUFKMk85bDswODb2Cy/9Suur4AiPU6JrRFBdtA/y5IPG3J8JGOZgci/FSaQn9PgkCvY5l34pEyF7V6dvNLMwtJLXO3cDB3R7NUZNZFk+fog8s6pZqvKAwtVTh17Nhyz6djrnO0LsyAWmv5uSohYoQbdr/WUNK7NCF1kwBNAR7vjTBf0sj2DTvIeevjxy4UA3g64TIHncAgSOjAEXud2RhK7zrSRWoJclWcwOBk+OxHNHPZZhbUqzVMXCuXRf2UemJbrwAtCR1kVooQVjmmk8T03RVGGNfJtOQVnqpszT06afke4snZGZDfyhutpyTVaDw1CAGHjyzLGf8ugVrtNLZxYaJICVDNQgNOIK40FxZOZ9HWH2x/ExRIQMkdgu2G+agTHJk0ZgwNa1lBFPEzmibQwCAGegHF1TWFXOWM4adpFuphrAo7LaYkTeE7YJCfyf2vIoVupiIgNYHNzNLLjusa/0G3mW9Mf7uundv64rn+t7JfbaJLPppje6fzs+6cY1ChHlaOetpKc1W0nMrvJQm1+8Jpx8G9mOVyIuPZ1wy/pVaIzXqhdcNyTILCnDQJbOYjUP0GpS2LB5KGw9rhUPTZNSJt+jUGrvHi3x+47OLvRfr8QObRyrUTAiAUeeQyg7Fhw0JoqZKVcHGCQlz3DAo7U+9lvj2gXZdg0QlFz2+Q2PFkI0kemdMPhTb/rgDIYWU+WnEcmkJ8s1Lnh3XZUuKXIz6ifQajgGIeQpQ5JpcAnh5vCism/QWDDF5JOLFiEtlyYExgzDhvoya86Z/Tce2W4bCTJqVJbUG/7jNyCg1KkJgaI38Rlj0w8MLARwRjKI36aXpUxNJShlj2yZSmMEo7mBRyRM9QiLe3/v/e9jdAgcxenU2q3Z3KAgRSUAuRi0ADqcsop3IzGz06kEeZfU4Hcjmm2z6Pu6SqOrJKvwKGNk52yf8498B4q6zuu5XpuuN5kqiVb6cDgDdgyN5o1/lD3c+6/Y445EtwNCBUFc57+V3bd+SvcxFrZfptb83rZe4oYKyff/HbquRkBJyPUKv71SDOaxxQ6u7ScIp2AnACeWQWiOAHaaT918SO/LuNCe/fePTXuR101UmnXXK75/ZHG7MuOjobCw9aRH+cPzz6SQbpdNpuVDv27AXd2V7X2/EcSeJyOsvR7wmW0YzW9nIgyzktWR9Ne3HAwoMQOTcWGfiqe6F38rnZH+WA35y4+iY3ah3Fb+SI2xaf0lErk2+zm7S7Bm19/GV7OsryQM2hd39r9z/RFv4AFNS2HLQJCPURksfRmTEzIhqAy6JZtViNtAGj9H9xwlloAnFOpiLlOdrCSpv5SCaitn5aAQCPUlMAkGkEto/k73f2/gzFbEw/tQD/8lwv+0pT6Mw4NK9Whofr2DcFIO26r8p+sbkjZy5X9CKJr9OrrnWUvd9rr3I0TaGbivYsupIWQ0PI3C56HsLWP6RQ0LlnnLjTBVOF4a21IvxUmsJyloXkuGYDBQ1IKNDhynw9g438GiO0g2vgY1wYY+B1vfC6Xriu0B5Ew5fJnFRZd2VCkmO8Z+wwgFoJgGR8jWG2vcZeEY02ax1ydHhn1K2sripBrk57nTuAoPOs/Ltf07A/+GLRQwYGyMKsftc9A80sNMpktGptg9zzOMyF0iz4lT1EdtBGODxSWMNpkmS5vRGZbQFNkVuYZRoCA1c5JmOdZ4U5o+hZzD0jMqLPh0xFHuGq0iRTo/QwN8rsuCV5TN7AdnOUozkcK7sZVFF0sOQ3OVa/uf2xo1mobqKC3Bc1xCCNRklQ6KajEQPcqI5LI0hT0hjJ6M9FbgQCfaZyx9/NmQw8momeQzvb7/z7ESwcCltMRs2ym4ZwlP3u15n8t4HhPH/023cAIbcFJGauAPHs5ePZXVMokMDO9NMM1iXm5+Oc1QyUrVYDfwHGWcbmYe2RiKLuzQlIbbp/RBqtrWxxpqpArJbw5Jjm7NrBv19jYAwjOLwwhsWe5qMxZD66mjYrwaTsyX1SXkTqUk633SxUaeX7gD7HXB+URxlP1L0NSFpZgoU0tPYM72UH/XSB9hEkRhW4o3xSTUtQ5l3Re2p/oJ+AbVAhoLU85lxo/oU2CxryJ9BXAI8OHIxsM4TtcSA4KFNw9MGv+zJc1ZW1FeGSdmkP1sZ1Q0JQW2wM3lzm7C9+zZeQWoa3sYCq4h6BhDJLtzBqact/6k8A/th81BXeIhh2c2sUxIfaIiMPB3PZ/ZGZJjefwkVfgcoQmgIsJH+gRR+h+SWE0AcYhARmbb6VJNDGdBujTwm9M/GlDmkDsJc1RhgAwOuE0jdQ6eBgBTTY6yEiMNegaQ4jXdfK8h60a/r+PP7Ntqf5xqYliEcUCPjWjidY5LeqDPq7E/7+U2ZS0HSABYakxtgeCL+BadALFJRLfpVTudt/lUHyXjcN5PzEpNXgKQPXNbiPqLdrXLjGhTGuEmwYEVcDXt/T6Ivvj8VQZBrg2BKfSTNa77sTEGo01oWtDGSKMjXspRs47MAQZX4re7jc8pFVlv2rsYAwExB89f1pkr6Z1TSr2H45P6AizGReUjUIZNuUfE8BvgY7SDsOTeEvYHNqG85yqTbHB/dG8XinnMZBU+JJ4V8YXXS1LsI2ejnGw+bPbWaizYza/JUuHnTQ23e3v6UpFIk1+dsG8V1jNJj6ME8Hc2RADi3humIAXpcGk+G6wnF8Da2VXGsfj9aA6UBW6CosQSCzdsom3OvfmMAm1YqpN8TNPRl5Z4A4rtvKGphkp6SpyPd6ABsolDlI9nR9Ax1xrR9wlN36/AkMvksYPSK0XrfxkBzYQKmtXntpC5L0o00MYUJxZBjqOWmnAwsUXcT9jJdLygdv6wjWZy+vFQ5mOZoV1x3MVpXXIOQcdxukVyctBji9rkEz0cDHKxj/x/XC67pwXQOvcVF7COAIoecq35Ucqvy2SSwLZiVByqubkhae+k4MiuFL23m/XedPZdvz+sv45Vnk92cQvTbe1TFKvBhiuEWrq0WTadnW0RnXovmIgsFciiRDHs9Vf8t85B1s2CaqAgYbfTlsBIHG+torQqR1jYHgUD1RPSKKaGXixl3jJfN/0gZkLrrSfHQxLc+V11Q4s0HRdi5pAaUxV/ZWZDr4SCoJCqjyndU4/e72h6BQqoz1E0n4aGesBDgWGf0IismGYQtJ/cpxnPe2f9lMiiSS3XKTlHapKSXVzpSTGnV/AwBoUOi+Rr3ns7aynfnnIH9419a2DRxOydJ0a7vtXnZ0/RNDeWIG22bPz394cHzmQXwaoN0eiqMdbs8Vk9qlo33Ft2KqaVLrfdDWTFCKi4whb2Xe35/qf2mVrRWKviTVtZ9MmDudUlIskXT7nv7d0g7uHLXPLXgChYOms0HtvDCvLYbeRm12Rr0Lt/dau07P6e9pJq9tPPXPEh1IUygaSe0R+7tuw+ro+87oaqjZVnZ8TuvQkURjmm5NR3Pse1lc17UEz4fhfDCA5ii2VpY8q4BjN3rzOZ1/tTbsmkI28zGmcxy2i852+u72NyavtW0DARblxDNAMcxmnmBgFpJCmo+ao7mbkmIvtaqZj24NjH1/DPpgIGTYqxhtMvDMSe43DWC319V1kvx9qgzpOPauDWQZqmdWNGatOFbnTCY61t3gzL3Urs++0PVf9M0TEPwWEPhcAFBficqyrz3RIhWlhSahHz8Hc9DH5K1FTSHz5CvsDoD7RAeIPndg6XhJU6BkyMSREH/nT7lpurQZoXv6DrWd5iNw+BplNZo7r4ibwGtcuC6FpEoruJJuy6k82vPFzIqh+OyAwKqb+sM2IC6g7N31ACS+XXD0scNT3/PtOt+4pgo7eHljSLvUjBzfVsPvfHVeXkKcL34jQ1DN6CNqPFHDKbUCB95rXy85fxwri/RwmsCqqx1pJhpeGXcHNQVOdoNZhLMaAgzMACweL/pGI/12AYi+zoAMLQ2ncpjRL5hRK+APdrVr+4RHalEKsFh7+7oHXS/nRMzpkR9q1ThM/8ragfO72/dB4annHWyYAzlzXnszJ6UgZQ0gQgIbY7Cc2sJo6SjyX0UTbYh8vDvHR2uFMMd4AUEHg87wO2B088/DdXIqlxlCz/2qrP7W2hPYymhHbyaGGHee5/o3hW326O1fgcPjdfcbrEWGGAG9Rux+vVZ2SgJ0PyaEtb0jmXzfe6rMMcBcM7qg/irmuhS545ZJ+zrfBARO8iEUQKw078kmS9BNqc7T3DMSGEBQUECE5tPQbyAg6GGpJkkQqe3kjGQvHmk5bgqQdoZfTPsMBz+vuzXCzpGPvc7tWsATwNz8GnWmwKADQ/DP2LRgAqqszPdWgrkENXhaxRIUgOZUbgKGjlOD8Jzotn2L9vmnZ1+HpMmXiZhstaZkYED7jL1tSVDpzNuF1c0UlKLsbk7qwgOgMYHcO7+zJquqXxqdb2PsSWtvNf8mMvwBKHy1nQS7b97PmJxBss8BlfQqPRLQbMYBg7JCLjV5k7q2qJy0wz/81H/NR/AICMwZgqlz2B3Iuv4oQ7/OfXun907dwIcQ96AppBDCbzJ4fZ8aVWW9oc+G/+XxFxTCgSNNT4ECm6YAoKurnQFPAkIw4gon7DNSo3+bpgAlOJMN3OKYgkH8rWUrI0yxIjuKAWTzc3BoFupi6gznRCcBQsqTSaDVJpbSDL9bZiFNSAquwvcyhxFictWAEsZXn8kypXd17UD9kcDgQEYB3WwgJ4fu4w/tul7W75OT2e/XJsYIwBylObTni7GOLom3/fnqVs60ZhgL9BHF/lFTQPcj2O5TcCtgAJknbP+ubn7Ut/MSrRcd/79oIrrEm0Ob8AYekmw5US8mYWqggrO10TQBCQrUBqxpA6i1mqUp9/DbuYDL6YdZe2M6Tt+KVoR7BoRkFfj+9s80hV9eK+4XW4EBoAkiGlA1MUXo3M655LkChRhPlgTbAcGSAbcqpLmnlbOxfbbrZruOlFamJD/KWsRNAxvv7xTwnGVAEJRGgOouCbb9XYvqePteVBn2sm1zfHHu1yRiafZr4+qGPpz6D2fCMC9QyEEcAKB9xZrLlATE6mMvKD68UhXsTGt5OOYWc8REhEfEgHeb61qq2yFNcTZqMT5Pnt9Zs7CggFH7kvhkMsglIN2wPBaDCZMEgiYPIOjNZ7f21PHRn72Pz837hb/a7lJBMXnH3VldvNXb+4vfsqwLuzr241hVH1CWc2CQz5KnGgFGJO7wjE1400T0XsCbQsY7w1IHJm9aOYhlKuveR36LcS0GPtszLxLpQ/1s3fksIFhhaoIjZiw7bDjGkI2GwkaaigbMPmA2EOnVYz3moJn286BprIFJxzuW4XNqHotznZfoIEct9vNWLi+ZSLvj2QWUrd++uf0tUHjUBw5U9uNXZdQKzKrMK6QMRH97eJ9DRLQ/fA/hbOcEEM2nUNK6F8M+zEcp3TvSbLNpC/15hxno67JeJzF+fyhDnjNQGgHoU0iOxna5lz11zfP5L26wat9nUIiTzv+L6XZC9NvxriVsWiFq8RSAaY/5bAMQK4whzrUIja5VSoJSRfXOeq6eNsin6v+OJqWeDZFf27UC2+51jwRsw+vdWgh+a7pjZG5h0hv39CpLIaDfe4y+m8SvZ/Sy+zVlery/v+OFNxpzPUMDcaGYpm5XVl+FFLWy9FExNYRxDozKxFvd0CYhUuY6zJDSECrqSN8gJD5UFJD3kCm4KcU2aYlpKYKcHOloNk8hqQZoCE41Qa4HxAwCAfcYOZBqplbRbvJE6LvYtBrjD5pCjLf72PuVyehPgOHboHBGgqREhap0qWT8MF4wxegQZWMgHE4WDTEsUHHSBnvJCQXhPp2vsJSYTUTdftaYeWf8aTJa7Twl280EpAbdzEeUWbPMm+bR7qXA8DRr+Q4KdCBv9ed3sc5i+LakGXkB3rn9ruyRIH5BJST6IHaiQ2dWvF//tCCJw1NTWJTw3A1zUrKbA+91YS3D219YvjDd2bQXFvPSKKVxMGyFPr5QdtqL7aPEc0he5VTLIvPlZA3DRxEmgoxihwZ4/6UUiTABDdEtU627A+aDZugRZk0CgRmFy5W8Am13tPsDCPQj/S99Z0/91tHsCTie3uVsg3GQgKNGG3o3N4bC2ln7MDFGOUTlxGVYc5zztN+bO/ntgl0Gm9SGDZkYNDSF6KdP10pnwOcCFpqm4ANTY6y3kcns2jWgqPsiLVDmz2yqbg4fdDyPK35w2BU0ZL4wLq6/cAV9pijr5I+OCDhV1oXxETOo7YO/AccHYqEgabsX3sswPDTMCxG6PxGa7LWceaMAMZS5uByocnm5470KODe511sTfHP7M1DYaEzI6JCvoFgHh13jj7CorLGcyhZMiKmMmByYkutkm9WXpVOqjIOo9Z+RzDshVW15A4Uquzma587I06l83OuKl/eH5/bnpb8hjk2NsQEFQSC5UhxbB4ON0dtRcP/z9+fuhWb13LuwtSNN/msOrow4cjkCfUtLoARnuUeshLUkLdlCC3RniL/BGbFR/oUw2WhhJnGy8nVICnMoL06BWwVXejvegaFcv0AwIxGmNNnpBmcKaLXd8hgTnW8+t7q3s0+TQvnxW7P3e/j3xrDPfnoCh3qG+1fnWMM2xqBapaNWYj/SFpSCYx+Psgg45WTZ4y2us8tgnCPgDsblh+1/AXiTlqaD9FP0FOm0UVpC+9wMVe/6mjeahdJoG9/HOgyDZ0RSfWdMxF0ATUbLEcdtrCvbqTLp2uB63Ra+MIf25UMwjguHwVbQ7NDnGLDgtRIit7VqUubUuPOHTK6dPLAf/2r7M/ORbX8JFligwQfANQgFBBoGgd2eYVameT0pYGQ6DAvmOVx3oghUxHyGa37FnDs4rPO6wzcANFCoDu8T2XqYapqa2vPyXf3e/n4cmoJURBcw1L2yu97CIE598Ls9/putDDEaDHr4nensoCB1Vk5eSi6QT2GEZCPfg1+cpMTQVtl3rZ4F0kCM7XDeLc4YdURKiZPtLjaaTJRBhwsZIF82RX6mp8Dt7YyuFG+Ik8GpJv0MjtB6jeaj9EUmSGRLZnvtTLzGRX2FVy/cdP5DEFCd+vfgqezhGm9hm7dzrcwrWivLNmBAmoPSCauoHgf5QjzTvGYVG0CHbR1XeiyH1lJ+sxneBIaFLlwszG4+VNWM72OgQm/zBAQAoU9WmSfjMQjpbcwQOofDrqAju2JCboYqkKTi8zkxzQw2PqIO4wWMWIZ10aS0vGY+2woTpC9Q3ImZ96l5HsLZlsqlhV0HEPg/AgTgT0BBNrNs3n7u/vJQq5sE5IAW0TZUumANMMWGA5ZJyBKsAQ4QihOyWyZI+MaEO9O3xthv0j5AGwfLpsr4Oj23l6X5yEsD6KDgRxnQTEugCo3qtbPeQPgRUgMq89FNcvwPAcFXW0rP+bLOlKLCMRhjxjBQMdLSFODSGIBFx6C74e10UCsSyRxrTNJJgYKDUuXghKJhmAwFLcdvbYvMP5gK1f3BjjJ1GOsvptWAARDYYWM0vbsUVz8E2sVDch83tnZUqbfzR8vW1Y49DPWLTRWEo809/+rCW5nnubujGVszsd9Vp3Q0H8BgRn88v10+B4+yzDoxOC6HJa3DEFmjOegXkXiSgS8H3jAKFGFDWD5yyNYmirA0S2VXkGmC4OIYub6zD4eypWIs4LriO9cLafn3xdUCnXMA2Ia8DQkKmtz4itoMrs89BhbXWwZijW7DwFrM7zbL/DhSs2oaWGrFpM+l1N1NSzjI++9sf8un0IncVIMu63grM6e6rUrGdWlu7HdqkLoCEdHCMJsfYVXZIyCczPYrTUFlh7nHH+7dc/t4u843ALhFJKk9jjLb3sF2yXo2QEijYD/Gvv+Pb20kJW/bAaGztJRQgNIYgHKAre4g645gQGvq5sxxaQoSDEy6S4WuSFNwxTf2zalxIJKY7XG8ojgQJNBUMX6d1WC3BL0Ns5PsIFBoz3JvVWqSvlqvC//Uc9uTFSpr7cJDO8D5vX3s+XH911qE43x+E7Ty0b2sXcdxmsnkMnQ3GiosgEJZr7FmVo7TpVBnhXYKENA0BVmDHRk46Bpyxr+P9mhiq8uJraq1ZijzImnEo37OXGvqT8sQqablKFxVAFgkhJyDYAatKokMZRZXqzD83tVLNAXQlE6fotr44PjSzOveolc07enWNL/Z/qaj+fkld4tGm3WLZitD+5kCTrVHdADf05liNj6Pt1QKX2oKKKa/vrjuMCndQOGL6ytMtc6fpqLNYtGus7MeXStZ+kbNaG7f0Nr/yz7+Zud/vflDmT2cj8pr1aoc/94AARVlsVwhxgvLX5AvoTSFaIBcGCRfa6UpmIUJyYAFJbBrAom0AfPyEveVzsXNRVeUSOv/gMwLciQa1D2+gcDwsvdaVrVpx7a3480alG14DqSzB57aXodPgHCCwXm/nO/nS8d+GRzYHNKSEprGIN+CVyME/xNoIIjiArDYXk1jwKwyn9Ck3gBYQ5oXlxEEwJBmlBkIQFNiChRKY+ifLjqNb9FynvG+AYxIi22kRVx181jhlB7ucPlBWjPBEQvo0HQFmTdHmD7dYknRMGkxmm5xDhZNXZpEXWHhAiMBbwmH8e7Gn84efaS332//wNGcr94K4q+yI/ZbxDAKEDrCFo6i3YMEgYbIklzaGH9ivOHUVZn/HhRa2U0zOCV7B01Kd9Bwv9fDH+t0PE/fyvpa++6z4w9+89Av/8ntlFaBs1LRTM3HACBT+KIDBOAY0GzoAATarU2x6r69RaYil+TVfw/CiouLNzNUfELK69mAgoOi1DQKIMFD1zqlNi8az+AsIM/tbXUAw1b0FUOnr+rWoU8A8hXjP5/ft1NbUFmrh7eyHtQgibU7lVtYavryR5WpGia/Q+6PsaDPacCQw9Nk8vE2XBh23KoZPMOqmjeJudq3a2nygboZkjOT8dsAzWMjbYYWfH1PxArxyfhozXiPqCOFUpfGkKH3XoAgIOiaiZo9hI/7wL9ZEP7h9mczmk8aVqFaPenpTowaQHqMtVu2sv7o7jNgBxcAOO6hnrgzW6Ck8idG/EXZ5lM4mH5d51+D0lcmpd/W13MUWPefpEh0tNG5/SvA8AQItVcYqJpMZ2ryDJmQt89OaS+WQIQh1enOrtJ8JAezAWlbtZNqGlOVY5nSFdEF2djJTIsj1VtXPiu0XYJGE2Lg9B+Y7wB9E5juTXeMiuPYs76+lZ0Pr+vu73u47qwE2/5+XX+ujo96no5mIqMBNXFtO69aeSzb2uP7VV1hzABkmokIoWIBFZtR80TWIa9ENzN02AoQSsBUTcpR7MbZ9Vu9eXFqNR5+ER3zs72DgtPLJTtYmo9qvoJm78daMxV9mcJF/qLNrf29RQKzr06e2Xv077KCP3Y0P5/D0TFk5mhjjwcnGGRZ33eec6pHm6mGxPobZvvlLOc/AYobKPhuKnp6fzdHAUe47C/q1L55q7va5FfbvwIKffP7cZp7moztNSC37uS5lde3qDWKXfkGC7IP4avZZyHweHKuts5KQur2CkkKAoYoU/2LAa4GC2RFPKfaK/x0HwCdAx01e+y7OzDcon2+0gI2W/9XzH+/t43C+/M2EDjf0Z5nbd/9CbQmpPScAFJVlB8h7yl8KHppGteitB5yUoFBH/bbZg9mo7NlXOy0oMEZPZmAxZnKoREQDC4PTX+U7d4u7LyGoBD/aN7MCXKWJs+FpiWomVpTu4CnVV6y0MANb+PYao/9cX+0/blP4XiT984/nGPZ8OxFQ7vE+5XHdnKRLCtmmf6EVna7Pq89JIW//bPtmed7nt7vvey8/un+LHOUR/Nsh/+vt/2Ddgde7bPq7P/6TK+/7fnTksxMc2DoONyGggY3t6cRIDrLQddemCS9MxANR1GxIsD8rKXxA25lz53kwBf9tw+qHFO/Y/K/vA6tvNr762uOd9w65SsWc1x/4GPuNxp/GLM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            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from matplotlib import cm\n",
        "\n",
        "def DisplaGradcam(img, heatmap, alpha):\n",
        "    \"\"\"\n",
        "    Displays the Grad-CAM visualization of an image.\n",
        "\n",
        "    Args:\n",
        "        img (numpy.ndarray): Input image.\n",
        "        heatmap (numpy.ndarray): The heatmap obtained from Grad-CAM.\n",
        "        alpha (float): The weight of the heatmap during blending.\n",
        "\n",
        "    Returns:\n",
        "        None.\n",
        "    \"\"\"\n",
        "    # Scale the heatmap values to the range [0, 255] and convert them to unsigned 8-bit integers.\n",
        "    heatmap = np.uint8(255 * heatmap)\n",
        "\n",
        "    # Get the 'jet' colormap and extract colors corresponding to the heatmap values.\n",
        "    jet = cm.get_cmap('jet')\n",
        "    jet_colors = jet(np.arange(256))[:, :3]\n",
        "    jet_heatmap = jet_colors[heatmap]\n",
        "\n",
        "    # Convert the heatmap to an image and resize it to match the dimensions of the original image.\n",
        "    jet_heatmap = tf.keras.utils.array_to_img(jet_heatmap)\n",
        "    jet_heatmap = jet_heatmap.resize((img.shape[1], img.shape[0]))\n",
        "    jet_heatmap = tf.keras.utils.img_to_array(jet_heatmap)\n",
        "\n",
        "    # Create the superimposed image by blending the original image and the heatmap image with a specified alpha value.\n",
        "    superimposed_img = jet_heatmap * alpha + img\n",
        "\n",
        "    # Convert the superimposed image to a PIL image, resize it, and display it using Matplotlib.\n",
        "    superimposed_img = tf.keras.utils.array_to_img(superimposed_img)\n",
        "    superimposed_img = superimposed_img.resize((150, 150))\n",
        "    plt.figure()\n",
        "    plt.imshow(superimposed_img)\n",
        "    plt.axis('off')\n",
        "    plt.show()\n",
        "\n",
        "# Create the saliecy map.\n",
        "saliency_map = MakeGradcamMap(x_test[sample], model)\n",
        "\n",
        "# Combine the saliency map with the original image.\n",
        "DisplaGradcam(x_test[sample], saliency_map, 0.005)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XYlBmiB4E8ot"
      },
      "source": [
        "As we can see, it is not the rider per se that gives this image as a horse, but the horse's head, saddle, and hind legs. You can use these functions to create saliency maps for any Keras-based model, and with a little bit of tweaking, you can apply this method to any CNN-based image classifier.\n",
        "\n",
        "----\n",
        "\n",
        "Return to the [castle](https://github.com/Nkluge-correa/TeenyTinyCastle).\n"
      ]
    }
  ],
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