gan_practice.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "gan_practice",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPyUVlOanrf0et78SIhFoJp",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/drakcoder/GAN-on-MNIST-dataset/blob/main/gan_practice.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H1O2vlQh-xRA"
      },
      "source": [
        "from keras.datasets.mnist import load_data\r\n",
        "import matplotlib.pyplot as plt\r\n",
        "import numpy as np\r\n",
        "from keras.utils.vis_utils import plot_model"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q2UC8fcvvm_k"
      },
      "source": [
        "Loading Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oE95G8hp-1N-",
        "outputId": "71dbf904-fe21-4804-f012-fddcdf9d83f3"
      },
      "source": [
        "(X_train,y_train),(X_test,y_test)=load_data()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n",
            "11493376/11490434 [==============================] - 0s 0us/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T-QfB6tU-75b",
        "outputId": "6b52e8a7-e484-4104-ba29-90c6fc699417"
      },
      "source": [
        "X_test.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10000, 28, 28)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2fnJtgoKvq6a"
      },
      "source": [
        "Checking Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "B7BtBWi9-_C6",
        "outputId": "9de1b515-a176-490b-b0b9-3a4d6472fbec"
      },
      "source": [
        "plt.imshow(X_train[0],cmap='gray')\r\n",
        "print(X_train[0].shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(28, 28)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pUh2THIT_A36"
      },
      "source": [
        "from keras.models import Sequential\r\n",
        "from keras.optimizers import Adam\r\n",
        "from keras.layers import Dense,Conv2D,Flatten,LeakyReLU,Dropout,Conv2DTranspose,Reshape\r\n",
        "from keras.utils.vis_utils import plot_model\r\n",
        "from keras import layers"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RGS-JycJv0xl"
      },
      "source": [
        "Create Discriminator Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-tjzITy4_C2W"
      },
      "source": [
        "def define_discriminator(input_shape=(28,28,1)):\r\n",
        "    model=Sequential()\r\n",
        "    model.add(Conv2D(64,(3,3),strides=(2,2),padding='same',input_shape=input_shape))\r\n",
        "    model.add(LeakyReLU(alpha=0.2))\r\n",
        "    model.add(Dropout(0.4))\r\n",
        "    model.add(Conv2D(64,(3,3),strides=(2,2),padding='same'))\r\n",
        "    model.add(LeakyReLU(alpha=0.2))\r\n",
        "    model.add(Dropout(0.4))\r\n",
        "    model.add(Flatten())\r\n",
        "    model.add(Dense(1,activation='sigmoid'))\r\n",
        "    opt=Adam(lr=0.0002,beta_1=0.5)\r\n",
        "    model.compile(loss='binary_crossentropy',optimizer=opt,metrics=['accuracy'])\r\n",
        "    return model"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QMVPTWSx_PMk"
      },
      "source": [
        "model=define_discriminator()"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AJPzynBJ_WWX",
        "outputId": "09e6dc20-0480-462f-975a-58a2c521fa86"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "conv2d (Conv2D)              (None, 14, 14, 64)        640       \n",
            "_________________________________________________________________\n",
            "leaky_re_lu (LeakyReLU)      (None, 14, 14, 64)        0         \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 14, 14, 64)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_1 (Conv2D)            (None, 7, 7, 64)          36928     \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_1 (LeakyReLU)    (None, 7, 7, 64)          0         \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 7, 7, 64)          0         \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 3136)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 3137      \n",
            "=================================================================\n",
            "Total params: 40,705\n",
            "Trainable params: 40,705\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 976
        },
        "id": "aCfGLeNkjeoe",
        "outputId": "e1c9f89e-4002-4707-d2e1-47a01cf0a9f9"
      },
      "source": [
        "plot_model(model,to_file='discriminator_plot.png',show_shapes=True,show_layer_names=True)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4mIBx784v6hK"
      },
      "source": [
        "Loading Real Samples"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IifHLDOM_YsO"
      },
      "source": [
        "def load_real_samples():\r\n",
        "    (trainX,_),(_,_)=load_data()\r\n",
        "    X=np.expand_dims(trainX,-1)\r\n",
        "    X=X.astype('float32')\r\n",
        "    X=X/255\r\n",
        "    return X"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gkgc6xmov_au"
      },
      "source": [
        "Generating Real Sample for Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pU20t6_r_bGl"
      },
      "source": [
        "def generate_real_samples(dataset,n_samples):\r\n",
        "    ix=np.random.randint(1,len(dataset),n_samples)\r\n",
        "    X=dataset[ix]\r\n",
        "    y=np.ones((n_samples,1))\r\n",
        "    return X,y"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AzIKpcnOwE2t"
      },
      "source": [
        "Generating Fake Samples for Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TYgUJB62_cwP"
      },
      "source": [
        "def generate_fake_samples(n_samples):\r\n",
        "    X=np.random.rand(28*28*n_samples)\r\n",
        "    X=X.reshape((n_samples,28,28,1))\r\n",
        "    y=np.zeros((n_samples,1))\r\n",
        "    return X,y"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rCOR2tOWwJg5"
      },
      "source": [
        "Defining Discriminator Training Function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HSfSgkTK_eos"
      },
      "source": [
        "def train_discriminator(model,dataset,n_iter=100,n_batch=256):\r\n",
        "    half_batch=int(n_batch/2)\r\n",
        "    for i in range(n_iter):\r\n",
        "        X_real,y_real=generate_real_samples(dataset,half_batch)\r\n",
        "        _,real_acc=model.train_on_batch(X_real,y_real)\r\n",
        "        X_fake,y_fake=generate_fake_samples(half_batch)\r\n",
        "        _,fake_acc=model.train_on_batch(X_fake,y_fake)\r\n",
        "        \r\n",
        "        print('>%d real=%.0f%% fake=%.0f%%' % (i+1, real_acc*100, fake_acc*100))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "szvDOOPxwPd3"
      },
      "source": [
        "Training the discriminator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "34s2lrZy_gY1",
        "outputId": "a69134e8-6909-43b1-f23f-8cfa7b2764c8"
      },
      "source": [
        "model=define_discriminator()\r\n",
        "dataset=load_real_samples()\r\n",
        "train_discriminator(model,dataset)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            ">1 real=38% fake=36%\n",
            ">2 real=48% fake=57%\n",
            ">3 real=44% fake=69%\n",
            ">4 real=42% fake=84%\n",
            ">5 real=52% fake=91%\n",
            ">6 real=40% fake=100%\n",
            ">7 real=44% fake=99%\n",
            ">8 real=52% fake=99%\n",
            ">9 real=50% fake=100%\n",
            ">10 real=41% fake=100%\n",
            ">11 real=47% fake=100%\n",
            ">12 real=54% fake=100%\n",
            ">13 real=55% fake=100%\n",
            ">14 real=58% fake=100%\n",
            ">15 real=56% fake=100%\n",
            ">16 real=67% fake=100%\n",
            ">17 real=62% fake=100%\n",
            ">18 real=70% fake=100%\n",
            ">19 real=66% fake=100%\n",
            ">20 real=81% fake=100%\n",
            ">21 real=80% fake=100%\n",
            ">22 real=80% fake=100%\n",
            ">23 real=81% fake=100%\n",
            ">24 real=88% fake=100%\n",
            ">25 real=91% fake=100%\n",
            ">26 real=89% fake=100%\n",
            ">27 real=90% fake=100%\n",
            ">28 real=91% fake=100%\n",
            ">29 real=96% fake=100%\n",
            ">30 real=99% fake=100%\n",
            ">31 real=98% fake=100%\n",
            ">32 real=98% fake=100%\n",
            ">33 real=99% fake=100%\n",
            ">34 real=98% fake=100%\n",
            ">35 real=100% fake=100%\n",
            ">36 real=99% fake=100%\n",
            ">37 real=100% fake=100%\n",
            ">38 real=100% fake=100%\n",
            ">39 real=100% fake=100%\n",
            ">40 real=100% fake=100%\n",
            ">41 real=100% fake=100%\n",
            ">42 real=100% fake=100%\n",
            ">43 real=100% fake=100%\n",
            ">44 real=100% fake=100%\n",
            ">45 real=100% fake=100%\n",
            ">46 real=100% fake=100%\n",
            ">47 real=100% fake=100%\n",
            ">48 real=100% fake=100%\n",
            ">49 real=100% fake=100%\n",
            ">50 real=100% fake=100%\n",
            ">51 real=100% fake=100%\n",
            ">52 real=100% fake=100%\n",
            ">53 real=100% fake=100%\n",
            ">54 real=100% fake=100%\n",
            ">55 real=100% fake=100%\n",
            ">56 real=100% fake=100%\n",
            ">57 real=100% fake=100%\n",
            ">58 real=100% fake=100%\n",
            ">59 real=100% fake=100%\n",
            ">60 real=100% fake=100%\n",
            ">61 real=100% fake=100%\n",
            ">62 real=100% fake=100%\n",
            ">63 real=100% fake=100%\n",
            ">64 real=100% fake=100%\n",
            ">65 real=100% fake=100%\n",
            ">66 real=100% fake=100%\n",
            ">67 real=100% fake=100%\n",
            ">68 real=100% fake=100%\n",
            ">69 real=100% fake=100%\n",
            ">70 real=100% fake=100%\n",
            ">71 real=100% fake=100%\n",
            ">72 real=100% fake=100%\n",
            ">73 real=100% fake=100%\n",
            ">74 real=100% fake=100%\n",
            ">75 real=100% fake=100%\n",
            ">76 real=100% fake=100%\n",
            ">77 real=100% fake=100%\n",
            ">78 real=100% fake=100%\n",
            ">79 real=100% fake=100%\n",
            ">80 real=100% fake=100%\n",
            ">81 real=100% fake=100%\n",
            ">82 real=100% fake=100%\n",
            ">83 real=100% fake=100%\n",
            ">84 real=100% fake=100%\n",
            ">85 real=100% fake=100%\n",
            ">86 real=100% fake=100%\n",
            ">87 real=100% fake=100%\n",
            ">88 real=100% fake=100%\n",
            ">89 real=100% fake=100%\n",
            ">90 real=100% fake=100%\n",
            ">91 real=100% fake=100%\n",
            ">92 real=100% fake=100%\n",
            ">93 real=100% fake=100%\n",
            ">94 real=100% fake=100%\n",
            ">95 real=100% fake=100%\n",
            ">96 real=100% fake=100%\n",
            ">97 real=100% fake=100%\n",
            ">98 real=100% fake=100%\n",
            ">99 real=100% fake=100%\n",
            ">100 real=100% fake=100%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w9obRsi2_iav"
      },
      "source": [
        "d_model=model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kGawfYhpwTCd"
      },
      "source": [
        "Defining the Generator Function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3C4POTUr_umU"
      },
      "source": [
        "def define_generator(latent_dim=100):\r\n",
        "    model=Sequential()\r\n",
        "    \r\n",
        "    n_nodes=7*7*128\r\n",
        "    model.add(Dense(n_nodes, input_dim=latent_dim))\r\n",
        "    model.add(LeakyReLU(alpha=0.2))\r\n",
        "    model.add(Reshape((7,7,128)))\r\n",
        "    model.add(Conv2DTranspose(128,(4,4),strides=(2,2),padding='same'))\r\n",
        "    model.add(LeakyReLU(alpha=0.2))\r\n",
        "    model.add(Conv2DTranspose(128,(4,4),strides=(2,2),padding='same'))\r\n",
        "    model.add(LeakyReLU(alpha=0.2))\r\n",
        "    model.add(Conv2D(1,(7,7),activation='sigmoid',padding='same'))\r\n",
        "    return model\r\n"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GKyRKtFl_wGz",
        "outputId": "5cc51fe7-4663-4247-abeb-2c3b52548ad3"
      },
      "source": [
        "latent_dim=100\r\n",
        "model=define_generator(latent_dim)\r\n",
        "model.summary()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_1 (Dense)              (None, 6272)              633472    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_2 (LeakyReLU)    (None, 6272)              0         \n",
            "_________________________________________________________________\n",
            "reshape (Reshape)            (None, 7, 7, 128)         0         \n",
            "_________________________________________________________________\n",
            "conv2d_transpose (Conv2DTran (None, 14, 14, 128)       262272    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_3 (LeakyReLU)    (None, 14, 14, 128)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_transpose_1 (Conv2DTr (None, 28, 28, 128)       262272    \n",
            "_________________________________________________________________\n",
            "leaky_re_lu_4 (LeakyReLU)    (None, 28, 28, 128)       0         \n",
            "_________________________________________________________________\n",
            "conv2d_2 (Conv2D)            (None, 28, 28, 1)         6273      \n",
            "=================================================================\n",
            "Total params: 1,164,289\n",
            "Trainable params: 1,164,289\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 976
        },
        "id": "f5CKd_UPkGuw",
        "outputId": "28372c08-9b90-4c4e-bdb9-846574055fd5"
      },
      "source": [
        "plot_model(model,to_file='generator_plot.png',show_shapes=True,show_layer_names=True)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlcAAAO/CAYAAADiW+PfAAAABmJLR0QA/wD/AP+gvaeTAAAgAElEQVR4nOzde1RV5bo/8O/iutbCtQAVZQViAl7ynmkJatq2PCkbFfFCSm105ECtEDXD+wXRNDvCoGR33BmNnW4FxAOWYg13B92erF9trxtTEcO7glfucnt+f7hZxxWCLJiwQL6fMfijdz5zvs+ckyVPc77rfVUiIiAiIiIiJSRZWToDIiIioqcJiysiIiIiBbG4IiIiIlIQiysiIiIiBdlYOoGW7siRI9i0aZOl0yAiIlJEUlKSpVNo8fjkqoEuX76MXbt2WToNIvqdH3/8ET/++KOl02hRrly5wn/PWjHef+XwyZVCWOkTNS+TJk0CwM+mORITEzFlyhRes1aq6v5Tw/HJFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwREdVi3759cHR0xNdff23pVJqlWbNmQaVSGX+Cg4OrxRw4cACLFy9GcnIyPD09jbFvvvlmtdhRo0ZBp9PB2toavXr1wtGjR5viNBqssrIS0dHR8PX1rTHm8OHDGDJkCLRaLQwGAyIiIvDgwQOz4/bs2YMNGzagoqLCZL+UlBSTe9G+fXvlTpDMwuKKiKgWImLpFJq9tm3bIi0tDWfPnsXWrVtNtq1cuRKxsbFYsmQJAgMDceHCBXh5eaFdu3bYtm0b9u7daxL/3XffISkpCf7+/sjIyMCAAQOa8lTqJTMzEy+//DLmz5+PoqKix8ZkZGRg1KhRGDlyJHJzc7F792588cUXmD17ttlxY8eOhVqtxsiRI3Hv3j1j+7hx43DlyhUcOnQIY8aMaZyTpTphcUVEVAs/Pz/cv38f/v7+lk4FxcXFtT4ZsRSNRoPXX38d3bp1g729vbF9/fr12LlzJxITE6HT6Uz2iY2NhZWVFUJDQ3H//v2mTlkxJ06cwKJFizB79mz079+/xrg1a9bA1dUVq1evhoODA3x8fBAREYEvv/wSZ86cMTtu7ty56NevH8aMGYPy8nIAgEqlgpubG4YNG4auXbs23knTE7G4IiJqIbZu3YqcnBxLp1En58+fx/Lly7F69Wqo1epq2319fREeHo6rV6/i/ffft0CGyujXrx+Sk5Mxbdo0k8LyUeXl5di7dy+GDx8OlUplbB89ejREBKmpqWbFVVm1ahWOHz+OmJiYRjgzaggWV0RENTh8+DA8PDygUqnw6aefAgDi4uLg4OAArVaL1NRUjB49Gnq9Hu7u7tixY4dx39jYWKjVanTo0AGzZs2CwWCAWq2Gr68vfvrpJ2NcWFgY7Ozs4Orqamx755134ODgAJVKhVu3bgEAwsPDsWDBAmRlZUGlUsHb2xsAsH//fuj1eqxdu7YpLkmdxcbGQkQwduzYGmOioqLQrVs3fP755zhw4ECtxxMRbNq0Cc899xzs7e3h7OyM8ePHmzzNqeu9AYCKigqsWLECHh4e0Gg06Nu3LxISEhp20jW4cOECCgoK4OHhYdLu5eUFADh58qRZcVWcnZ0xfPhwxMTE8PV1M8PiioioBkOHDsUPP/xg0jZnzhzMmzcPxcXF0Ol0SEhIQFZWFjw9PTFz5kyUlZUBeFg0hYSEoKioCHPnzkV2djaOHj2K8vJyvPbaa7h8+TKAh0XI5MmTTfrYvHkzVq9ebdIWExMDf39/eHl5QURw/vx5ADAOaq6srGyUa1Bfe/fuRffu3aHVamuM0Wg0+PLLL2FlZYWZM2eisLCwxthVq1Zh8eLFWLp0KXJycnDo0CFcvnwZw4YNw82bNwHU/d4AwKJFi/DRRx8hOjoa169fh7+/P6ZOnYpffvlFuYvwbzdu3ACAaq9G1Wo1NBqNMf+6xj3q+eefx9WrV3HixAnF86b6Y3FFRFRPvr6+0Ov1cHFxQVBQEAoLC3Hp0iWTGBsbG+PTlp49eyIuLg75+fmIj49XJAc/Pz/k5eVh+fLlihxPCYWFhfjtt9+MT1xq4+Pjg3nz5iE7OxuLFi16bExxcTE2bdqECRMmIDg4GI6OjujTpw8+++wz3Lp1C1u2bKm2T233pqSkBHFxcQgICEBgYCCcnJywbNky2NraKnZfHlX1TT9ra+tq22xtbVFcXGxW3KOqxladOnVKsXyp4VhcEREpwM7ODgBMno48zsCBA6HVak1eZz1tcnJyICK1PrV6VFRUFLp3747Nmzfj8OHD1bZnZGSgoKAAAwcONGkfNGgQ7OzsTF6zPs7v783Zs2dRVFSE3r17G2M0Gg1cXV0b5b5UjTmrGnj+qNLSUmg0GrPiHlV1jR/3VIssh8UVEVETs7e3R25urqXTaDQlJSUAUOMA799Tq9WIj4+HSqXCjBkzqj2hqZpuoE2bNtX2dXJyQn5+vln5Vb1+XLZsmcm8UBcvXqxxKoWGqBpPl5eXZ9JeVFSEkpISGAwGs+IeVVVwVV1zah5YXBERNaGysjLcu3cP7u7ulk6l0VT9wf/9JJe18fHxwfz585GZmYk1a9aYbHNycgKAxxZR9bmWLi4uAIDo6GiIiMnPkSNHzDpWXXTp0gU6nQ4XL140aa8aN9e3b1+z4h5VWloKAI99qkWWw+KKiKgJpaenQ0QwePBgY5uNjc0TXye2JB06dIBKpTJ7/qo1a9agR48eOHbsmEl779690aZNm2qDzX/66SeUlpbihRdeMKufTp06Qa1W4/jx42btV182NjYYM2YMDh06ZPLFg7S0NKhUKuM3Kusa96iqa9yxY8dGPgsyB4srIqJGVFlZibt376K8vBwnT55EeHg4PDw8EBISYozx9vbGnTt3kJKSgrKyMuTm5lZ7egE8nAn92rVryM7ORn5+PsrKypCWltbspmLQarXw9PTElStXzNqv6vXg7wd0q9VqLFiwALt378a2bduQl5eHU6dOYfbs2TAYDAgNDTW7n+nTp2PHjh2Ii4tDXl4eKioqcOXKFVy/fh0AEBQUhI4dOyq2/M7y5ctx8+ZNrFy5EoWFhThy5Ag2btyIkJAQdO/e3ey4KlXXuE+fPorkSQoRapCEhAThZSRqfiZOnCgTJ05s0DE++eQTcXV1FQCi1Wpl7NixsnnzZtFqtQJAunbtKllZWbJlyxbR6/UCQDp37iznzp0TEZHQ0FCxtbUVNzc3sbGxEb1eL+PHj5esrCyTfm7fvi2vvPKKqNVq6dKli7z33nuycOFCASDe3t5y6dIlERE5evSodO7cWTQajQwdOlRu3Lgh+/btE51OJ1FRUQ06V5H6/XsWGhoqbm5u1drDwsLE1tZWioqKjG27d+8WLy8vASDt27eXd99997HHXLhwoYwbN86krbKyUjZu3Chdu3YVW1tbcXZ2loCAADl79qwxxpx78+DBA4mIiBAPDw+xsbERFxcXCQwMlIyMDBERCQgIEACyYsWKWs//yJEjMmTIEDEYDAJAAIirq6v4+vrKwYMHTWIPHjwoL774otjb24vBYJCFCxdKSUlJtWPWNU5ExM/PT9zc3KSystKkfe7cudKuXbtac/89/j1TTCKvYgPxl5GoeVKiuGqo0NBQadu2rUVzMIeSxVVmZqbY2NjIV199pVR6TaqiokKGDRsmW7dutXQqNbp165ao1Wr5+OOPq21jcWVRiXwtSETUiMwZ1N1SFRcX49tvv0VmZqZxgLW3tzciIyMRGRmJgoICC2donoqKCqSkpCA/Px9BQUGWTqdGq1atQv/+/REWFgbg4Sz2165dw+HDh42D4MkyWFwREVGD3Llzx7hw84wZM4ztixcvxqRJkxAUFNSiFmdOT09HcnIy0tLS6jxXV1PbtGkTjh8/jn379sHW1hYAkJqaaly4ee/evRbOsHVjcdUMvP3229DpdFCpVE327ZXGUllZiejoaPj6+jboOPv27YOjoyO+/vprhTJrej/++COee+45WFlZQaVSoWPHjoiKirJ0WiaSk5Ph6elpnOfH1dUVwcHBlk7rqbBkyRLEx8fj/v376NKlC3bt2mXplBrFZ599ZjKVwbZt20y2r127FmFhYfjwww8tlKH5Ro4cie3bt5us99icpKam4sGDB0hPT4ezs7Oxffz48Sb3ompdSmp6NpZOgIDPP/8cr776Kt544w1Lp9IgmZmZmD59Ov73f/8X/fr1a9Cx5ClYhHTw4MH49ddf8frrr+Pbb7/F2bNnjfP1NBeBgYEIDAyEt7c3bt26ZVzbjBpu3bp1WLdunaXTaBZGjRqFUaNGWTqNp8a4ceMwbtw4S6dBteCTK1LEiRMnsGjRIsyePRv9+/dv8PH8/Pxw//59+Pv7K5BdwxQXFzf4SVxz8TSdCxFRc8XiqplQqVSWTqFB+vXrh+TkZEybNq3OS160FFu3bkVOTo6l01DE03QuRETNFYsrCxARbNy4Ed27d4e9vT0cHR2xcOHCanEVFRVYsWIFPDw8oNFo0LdvXyQkJAAA4uLi4ODgAK1Wi9TUVIwePRp6vR7u7u7YsWOHyXEOHjyIF198EVqtFnq9Hn369DGuXVVbH5Zy+PBheHh4QKVS4dNPPwVQ9/ONjY2FWq1Ghw4dMGvWLBgMBqjVavj6+pos7hoWFgY7OzuTMRXvvPMOHBwcoFKpjGMVwsPDsWDBAmRlZUGlUsHb2xsAsH///npP3NjczsVc//jHP9CzZ084OjpCrVajT58++PbbbwE8HD9YNX7Ly8vLONP29OnTodVq4ejoiD179gCo/Xfvo48+glarhU6nQ05ODhYsWAA3NzecPXu2XjkTETUpi80C8ZSoz7wgS5cuFZVKJf/5n/8pd+/elaKiItm8ebMAkGPHjhnj3n//fbG3t5ddu3bJ3bt3ZcmSJWJlZSU///yz8TgA5O9//7vcv39fcnJyZNiwYeLg4CClpaUiIlJQUCB6vV42bNggxcXFcuPGDZkwYYLk5ubWqY/6eOmll6Rfv3713l9E5PLlywJAPvnkE2NbXc5X5OG8Ow4ODnL69GkpKSmRjIwMGTRokOh0OuNkjCIi06ZNk44dO5r0u3HjRgFgvD4iIoGBgeLl5WUS980334hOp5PIyMgnnst//Md/CAC5e/duszwXEREvLy9xdHR84rmIiCQlJcmqVavkzp07cvv2bRk8eLDJfDqBgYFibW0tV69eNdlv6tSpsmfPHuN/1/X3e+7cufLJJ5/IhAkT5Ndff61TjiLNY56rlobzHLVuvP+K4TxXTa24uBjR0dF49dVXMX/+fDg5OUGj0aBt27YmcSUlJYiLi0NAQAACAwPh5OSEZcuWwdbWFvHx8Saxvr6+0Ov1cHFxQVBQEAoLC3Hp0iUAQHZ2NvLy8tCrVy+o1Wp07NgRycnJaN++vVl9NCe1nW8VGxsbPPfcc7C3t0fPnj0RFxeH/Px8xc7Lz88PeXl5WL58eYOO0xzOxVwTJ07EypUr4ezsjLZt22Ls2LG4ffs2cnNzAQCzZ89GRUWFSX55eXn4+eefMWbMGADm/X6vX78e7777LpKTk9GjR4+mO1EionritwWb2Pnz51FUVISRI0fWGnf27FkUFRWhd+/exjaNRgNXV1ecOXOmxv3s7OwAwLgIrKenJzp06IDg4GDMnTsXISEhePbZZxvUR3Py+/OtycCBA6HVapv1ebXUc6maY6dqssw//OEP6NatG7744gssWbIEKpUKO3fuRFBQkHHNuKb63du1a1eLH89oCbxmRA3D4qqJVS2y6eLiUmtcYWEhAGDZsmVYtmyZyTaDwVDn/jQaDb7//nssWrQIa9euRWRkJCZPnoz4+HjF+mgp7O3tjU9XWjpLnsvevXuxceNGZGRkIC8vr1oxqFKpMGvWLMyfPx9///vf8eqrr+Kvf/0rtm/fboxpqt+9wYMHY968eYod72l35MgRxMTEWHzcJVlG1f2nhmNx1cTUajUA4MGDB7XGVRVf0dHRCA8Pb1CfvXr1wtdff43c3Fxs2rQJ69evR69evYzLOijRR3NXVlaGe/fuwd3d3dKpNFhTn8uhQ4fwz3/+E/PmzcOlS5cQEBCACRMm4IsvvsAzzzyDTz75BB988IHJPiEhIViyZAk+//xzdOrUCXq9Hp07dzZuV/L3uzbu7u6YPHlyox3/aRQTE8Nr1oqxuFIGx1w1sd69e8PKygoHDx6sNa5Tp05Qq9UNnrH92rVrOH36NICHf9A+/PBDDBgwAKdPn1asj5YgPT0dIoLBgwcb22xsbJ74Cq45aupz+ec//wkHBwcAwKlTp1BWVoY5c+bA09MTarX6sa+QnJ2dMWXKFKSkpODjjz/GzJkzTba3pt89Imp9WFw1MRcXFwQGBmLXrl3YunUr8vLycPLkSWzZssUkTq1WY/r06dixYwfi4uKQl5eHiooKXLlyBdevX69zf9euXcOsWbNw5swZlJaW4tixY7h48SIGDx6sWB/NUWVlJe7evYvy8nKcPHkS4eHh8PDwQEhIiDHG29sbd+7cQUpKCsrKypCbm4uLFy9WO1bbtm1x7do1ZGdnIz8/H2VlZUhLS6v3VAzN7VxqUlZWhps3byI9Pd1YXHl4eAAADhw4gJKSEmRmZppMC/Go2bNn48GDB/jmm2+qTQb7NP/uERHxO5cNVJ+vrubn58vbb78t7dq1kzZt2sjQoUNlxYoVAkDc3d3lxIkTIiLy4MEDiYiIEA8PD7GxsREXFxcJDAyUjIwM2bx5s2i1WgEgXbt2laysLNmyZYvo9XoBIJ07d5Zz585Jdna2+Pr6irOzs1hbW8szzzwjS5culfLy8if2YY4jR47IkCFDxGAwCAABIK6uruLr6ysHDx4061iffPKJuLq6CgDRarUyduzYOp+vyMPpC2xtbcXNzU1sbGxEr9fL+PHjJSsry6Sf27dvyyuvvCJqtVq6dOki7733nixcuFAAiLe3t3Gqg6NHj0rnzp1Fo9HI0KFD5caNG7Jv3z7R6XQSFRVV43n8+OOP0qtXL7GysjJej7Vr1zarc/nzn/8sXl5exntW08/u3buNfUVEREjbtm3FyclJJk2aJJ9++qkAEC8vL5PpIUREnn/+eVm8ePFjr09tv3sbNmwQjUYjAKRTp07y1Vdf1eVXxwSnYjAfv4rfuvH+KyZRJfIULOJmQYmJiZgyZcpTsRbe02LWrFlISkrC7du3LZ1Kg7X0c/Hz88Onn36KLl26NHnfkyZNAgAkJSU1ed8tFf89a914/xWTxNeC9FSqmhbgadCSzuXR14wnT56EWq22SGFFRGRJLK7osc6cOWNcxqS2n6pvHDb18ah5ioiIQGZmJs6dO4fp06djzZo1lk6JGtmsWbNMPsPBwcHVYg4cOIDFixcjOTkZnp6extg333yzWuyoUaOg0+lgbW2NXr164ejRo01xGg1WWVmJ6OjoWhdGP3z4MIYMGQKtVguDwYCIiIjHfnP8SXF79uzBhg0bqv2PV0pKism9aN++vXInSOax6FvJpwDfUTcvixcvFjs7OwEgzz77rCQlJVk6pXprieeydOlSsbKykk6dOpksdWMJHHNlvvr8exYaGipt27aVtLQ0OXv2rJSUlJhsX7Fihfj7+0teXp6xzcvLS9q1aycA5Jtvvql2zLS0NBk3blz9TsICzp07J0OGDBEANS799a9//Us0Go0sX75cCgoK5IcffpD27dvL9OnT6xUXExMjw4cPN1lWq7KyUq5cuSKHDh2SMWPGmCxLVRf8e6aYRF7FBuIvI1Hz1ByKq6KiIvHx8WkxfdS3uHJzc3vstg8//FC6desmxcXFJu1eXl6yfft2sbKyEjc3N7l3757J9pZUXB0/flwmTJgg27Ztk/79+9dYXE2ZMkW6dOkilZWVxraNGzeKSqUyWTOzrnEiImFhYeLj4yNlZWXV+ps7dy6LK8vh2oJERI1l69atyMnJafF91Mf58+exfPlyrF692jh58qN8fX0RHh6Oq1ev4v3337dAhsro168fkpOTMW3aNNjb2z82pry8HHv37sXw4cNN5oUbPXo0RASpqalmxVVZtWoVjh8/zok/myEWV0RE/yYi2LRpk3GhbGdnZ4wfP95kvcOwsDDY2dnB1dXV2PbOO+/AwcEBKpUKt27dAgCEh4djwYIFyMrKgkqlgre3N2JjY6FWq9GhQwfMmjULBoMBarUavr6+JvOFNaQPANi/f3+TzcNWk9jYWIgIxo4dW2NMVFQUunXrhs8//xwHDhyo9Xh1uTdxcXFwcHCAVqtFamoqRo8eDb1eD3d3d+zYscPkeBUVFVixYgU8PDyg0WjQt2/fRlv258KFCygoKDDOE1fFy8sLwMMvf5gTV8XZ2RnDhw9HTEwMv+HXzLC4IiL6t1WrVmHx4sVYunQpcnJycOjQIVy+fBnDhg3DzZs3ATwsGn6/PMzmzZuxevVqk7aYmBj4+/vDy8sLIoLz588jLCwMISEhKCoqwty5c5GdnY2jR4+ivLwcr732Gi5fvtzgPoD/+4ZpZWWlchfHTHv37kX37t2h1WprjNFoNPjyyy9hZWWFmTNnGtecfJy63Js5c+Zg3rx5KC4uhk6nQ0JCArKysuDp6YmZM2eafJt10aJF+OijjxAdHY3r16/D398fU6dOxS+//KLcRfi3GzduAAB0Op1Ju1qthkajMeZf17hHPf/887h69SpOnDiheN5UfyyuiIgAFBcXY9OmTZgwYQKCg4Ph6OiIPn364LPPPsOtW7eqraLQEDY2NsYnMD179kRcXBzy8/MRHx+vyPH9/PyQl5eH5cuXK3I8cxUWFuK3334zPnGpjY+PD+bNm4fs7GwsWrTosTH1uTe+vr7Q6/VwcXFBUFAQCgsLcenSJQBASUkJ4uLiEBAQgMDAQDg5OWHZsmWwtbVV7B48quqbftbW1tW22draori42Ky4R3Xt2hXAw6WpqPlgcUVEBCAjIwMFBQUYOHCgSfugQYNgZ2dX4zI/Shg4cCC0Wq3JK66WLCcnByJS61OrR0VFRaF79+7YvHkzDh8+XG17Q++NnZ0dgP+bh+3s2bMoKipC7969jTEajQaurq6Ncg+qxpyVl5dX21ZaWgqNRmNW3KOqrvHjnmqR5bC4IiICcO/ePQBAmzZtqm1zcnJCfn5+o/Zvb2+P3NzcRu2jqZSUlABAjQO8f0+tViM+Ph4qlQozZsyo9oRG6XtT9fpx2bJlJvNCXbx4EUVFRWYdqy6qxs7l5eWZtBcVFaGkpAQGg8GsuEdVFVxV15yaBxZXRER4+EcawGP/UN+7dw/u7u6N1ndZWVmj99GUqv7gm7O6gI+PD+bPn4/MzMxqk88qfW9cXFwAANHR0RARk58jR46Yday66NKlC3Q6XbXF1KvGyPXt29esuEeVlpYCwGOfapHlsLgiIgLQu3dvtGnTptqA5p9++gmlpaV44YUXjG02NjYmg6MbKj09HSKCwYMHN1ofTalDhw5QqVS4f/++WfutWbMGPXr0wLFjx0zazbk3ddGpUyeo1WocP37crP3qy8bGBmPGjMGhQ4dMvmSQlpYGlUpl/EZlXeMeVXWNO3bs2MhnQeZgcUVEhIevphYsWIDdu3dj27ZtyMvLw6lTpzB79mwYDAaEhoYaY729vXHnzh2kpKSgrKwMubm51Z42AEDbtm1x7do1ZGdnIz8/31gsVVZW4u7duygvL8fJkycRHh4ODw8PhISEKNJHWlqaRadi0Gq18PT0xJUrV8zar+r14O8HdJtzb+raz/Tp07Fjxw7ExcUhLy8PFRUVuHLlCq5fvw4ACAoKQseOHRVbfmf58uW4efMmVq5cicLCQhw5cgQbN25ESEgIunfvbnZclapr3KdPH0XyJIVYYurSpwlntCVqnuozQ3tlZaVs3LhRunbtKra2tuLs7CwBAQFy9uxZk7jbt2/LK6+8Imq1Wrp06SLvvfeeLFy4UACIt7e3XLp0SUREjh49Kp07dxaNRiNDhw6VGzduSGhoqNja2oqbm5vY2NiIXq+X8ePHS1ZWlmJ97Nu3T3Q6nURFRZl1/krO0B4WFia2trZSVFRkbNu9e7d4eXkJAGnfvr28++67jz3mwoULq83QXpd7s3nzZtFqtQJAunbtKllZWbJlyxbR6/UCQDp37iznzp0TEZEHDx5IRESEeHh4iI2Njbi4uEhgYKBkZGSIiEhAQIAAkBUrVtR6/keOHJEhQ4aIwWAQAAJAXF1dxdfXVw4ePGgSe/DgQXnxxRfF3t5eDAaDLFy4sNpyQebEiYj4+fmJm5ubyYzuIpyh3cK4/E1D8ZeRqHlqDsvfPE7VWnzNkZLFVWZmptjY2MhXX32lVHpNqqKiQoYNGyZbt261dCo1unXrlqjVavn444+rbWNxZVFc/oaIqKmZM9C7JSguLsa3336LzMxM4wBrb29vREZGIjIyEgUFBRbO0DwVFRVISUlBfn4+goKCLJ1OjVatWoX+/fsjLCwMwMNZ7K9du4bDhw8bB8GTZbC4IiKiBrlz5w5ef/11dOvWDTNmzDC2L168GJMmTUJQUJDZg9stKT09HcnJyUhLS6vzXF1NbdOmTTh+/Dj27dsHW1tbAEBqairc3NwwbNgw7N2718IZtm4sroiImsiSJUsQHx+P+/fvo0uXLti1a5elU2qwzz77zGQqg23btplsX7t2LcLCwvDhhx9aKEPzjRw5Etu3bzdZ27E5SU1NxYMHD5Ceng5nZ2dj+/jx403uRdUalNT0bCydABFRa7Fu3TqsW7fO0mk0uVGjRmHUqFGWTuOpMW7cOIwbN87SaVAt+OSKiIiISEEsroiIiIgUxOKKiIiISEEsroiIiIgUxAHtCklMTLR0CkT0iKplQfjZrLuqRYt5zVqnxli0urVSiYhYOomWLDExEVOmTLF0GkRERIpgWdBgSSyuiKjZq/qfGP5zRUQtQBLHXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREbyOlcMAACAASURBVBEpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpiMUVERERkYJYXBEREREpyMbSCRARPerKlSv405/+hIqKCmPb3bt3odPpMGLECJPY7t2747/+67+aOEMiotqxuCKiZsXd3R0XL15EVlZWtW0HDx40+e+XX365qdIiIqozvhYkombnrbfegq2t7RPjgoKCmiAbIiLzsLgiomZn2rRpKC8vrzWmV69e6NmzZxNlRERUdyyuiKjZ8fLyQt++faFSqR673dbWFn/605+aOCsiorphcUVEzdJbb70Fa2vrx24rLy/HpEmTmjgjIqK6YXFFRM3SG2+8gcrKymrtVlZWGDx4MJ599tmmT4qIqA5YXBFRs2QwGDBkyBBYWZn+M2VlZYW33nrLQlkRET0ZiysiarbefPPNam0iggkTJlggGyKiumFxRUTN1sSJE03GXVlbW+PVV19Fhw4dLJgVEVHtWFwRUbPl7OyM1157zVhgiQiCg4MtnBURUe1YXBFRsxYcHGwc2G5ra4vx48dbOCMiotqxuCKiZm3s2LGwt7cHAPj7+6NNmzYWzoiIqHYsroioWXNwcDA+reIrQSJqCVQiIpZOgprWpEmTsGvXLkunQUT01EtISMDkyZMtnQY1rSQbS2dAljF48GDMmzfP0mlQCzNlyhSEh4fDx8enSfutqKhAQkICpk6d2qT9KiE6OhoA+HlrhaZMmWLpFMhCWFy1Uu7u7vy/KTLblClT4OPjY5HfnYCAAKjV6ibvt6GSkpIAgJ+3VojFVevFMVdE1CK0xMKKiFonFldERERECmJxRURERKQgFldERERECmJxRURERKQgFldE1OT27dsHR0dHfP3115ZOpUU6cOAAFi9ejOTkZHh6ekKlUkGlUuHNN9+sFjtq1CjodDpYW1ujV69eOHr0qAUyNl9lZSWio6Ph6+tbY8zhw4cxZMgQaLVaGAwGRERE4MGDB2bH7dmzBxs2bEBFRUWjnAu1PiyuiKjJce7i+lu5ciViY2OxZMkSBAYG4sKFC/Dy8kK7du2wbds27N271yT+u+++Q1JSEvz9/ZGRkYEBAwZYKPO6y8zMxMsvv4z58+ejqKjosTEZGRkYNWoURo4cidzcXOzevRtffPEFZs+ebXbc2LFjoVarMXLkSNy7d69Rz41aBxZXRNTk/Pz8cP/+ffj7+1s6FRQXF9f6dKQ5Wb9+PXbu3InExETodDqTbbGxsbCyskJoaCju379voQwb7sSJE1i0aBFmz56N/v371xi3Zs0auLq6YvXq1XBwcICPjw8iIiLw5Zdf4syZM2bHzZ07F/369cOYMWNQXl7eqOdITz8WV0TUqm3duhU5OTmWTuOJzp8/j+XLl2P16tWPnfPL19cX4eHhuHr1Kt5//30LZKiMfv36ITk5GdOmTTMu2P175eXl2Lt3L4YPHw6VSmVsHz16NEQEqampZsVVWbVqFY4fP46YmJhGODNqTVhcEVGTOnz4MDw8PKBSqfDpp58CAOLi4uDg4ACtVovU1FSMHj0aer0e7u7u2LFjh3Hf2NhYqNVqdOjQAbNmzYLBYIBarYavry9++uknY1xYWBjs7Ozg6upqbHvnnXfg4OAAlUqFW7duAQDCw8OxYMECZGVlQaVSwdvbGwCwf/9+6PV6rF27tikuSZ3ExsZCRDB27NgaY6KiotCtWzd8/vnnOHDgQK3HExFs2rQJzz33HOzt7eHs7Izx48ebPM2p630BHi5RtGLFCnh4eECj0aBv375ISEho2EnX4MKFCygoKICHh4dJu5eXFwDg5MmTZsVVcXZ2xvDhwxETE8NX19QgLK6IqEkNHToUP/zwg0nbnDlzMG/ePBQXF0On0yEhIQFZWVnw9PTEzJkzUVZWBuBh0RQSEoKioiLMnTsX2dnZOHr0KMrLy/Haa6/h8uXLAB4WIr9fbmbz5s1YvXq1SVtMTAz8/f3h5eUFEcH58+cBwDiwubKyslGuQX3s3bsX3bt3h1arrTFGo9Hgyy+/hJWVFWbOnInCwsIaY1etWoXFixdj6dKlyMnJwaFDh3D58mUMGzYMN2/eBFD3+wIAixYtwkcffYTo6Ghcv34d/v7+mDp1Kn755RflLsK/3bhxAwCqvRpVq9XQaDTG/Osa96jnn38eV69exYkTJxTPm1oPFldE1Kz4+vpCr9fDxcUFQUFBKCwsxKVLl0xibGxsjE9cevbsibi4OOTn5yM+Pl6RHPz8/JCXl4fly5crcryGKiwsxG+//WZ84lIbHx8fzJs3D9nZ2Vi0aNFjY4qLi7Fp0yZMmDABwcHBcHR0RJ8+ffDZZ5/h1q1b2LJlS7V9arsvJSUliIuLQ0BAAAIDA+Hk5IRly5bB1tZWsXvyqKpv+llbW1fbZmtri+LiYrPiHtW1a1cAwKlTpxTLl1ofFldE1GzZ2dkBgMkTkscZOHAgtFqtySutp0lOTg5EpNanVo+KiopC9+7dsXnzZhw+fLja9oyMDBQUFGDgwIEm7YMGDYKdnZ3JK9bH+f19OXv2LIqKitC7d29jjEajgaura6Pck6oxZ48beF5aWgqNRmNW3KOqrvHjnmoR1RWLKyJ6Ktjb2yM3N9fSaTSKkpISAKhxgPfvqdVqxMfHQ6VSYcaMGdWe0FRNN9CmTZtq+zo5OSE/P9+s/KpePy5btsw455ZKpcLFixdrnEqhIarG0uXl5Zm0FxUVoaSkBAaDway4R1UVXFXXnKg+WFwRUYtXVlaGe/fuwd3d3dKpNIqqP/jmTHLp4+OD+fPnIzMzE2vWrDHZ5uTkBACPLaLqcx1dXFwAANHR0RARk58jR46Yday66NKlC3Q6HS5evGjSXjVmrm/fvmbFPaq0tBQAHvtUi6iuWFwRUYuXnp4OEcHgwYONbTY2Nk98ndhSdOjQASqVyuz5q9asWYMePXrg2LFjJu29e/dGmzZtqg02/+mnn1BaWooXXnjBrH46deoEtVqN48ePm7VffdnY2GDMmDE4dOiQyZcO0tLSoFKpjN+orGvco6qucceOHRv5LOhpxuKKiFqcyspK3L17F+Xl5Th58iTCw8Ph4eGBkJAQY4y3tzfu3LmDlJQUlJWVITc3t9oTDABo27Ytrl27huzsbOTn56OsrAxpaWnNaioGrVYLT09PXLlyxaz9ql4P/n5At1qtxoIFC7B7925s27YNeXl5OHXqFGbPng2DwYDQ0FCz+5k+fTp27NiBuLg45OXloaKiAleuXMH169cBAEFBQejYsaNiy+8sX74cN2/exMqVK1FYWIgjR45g48aNCAkJQffu3c2Oq1J1jfv06aNIntRKCbU6EydOlIkTJ1o6DWqBAEhCQkKDjvHJJ5+Iq6urABCtVitjx46VzZs3i1arFQDStWtXycrKki1btoherxcA0rlzZzl37pyIiISGhoqtra24ubmJjY2N6PV6GT9+vGRlZZn0c/v2bXnllVdErVZLly5d5L333pOFCxcKAPH29pZLly6JiMjRo0elc+fOotFoZOjQoXLjxg3Zt2+f6HQ6iYqKatC5iij3eQsLCxNbW1spKioytu3evVu8vLwEgLRv317efffdx+67cOFCGTdunElbZWWlbNy4Ubp27Sq2trbi7OwsAQEBcvbsWWOMOfflwYMHEhERIR4eHmJjYyMuLi4SGBgoGRkZIiISEBAgAGTFihW1nueRI0dkyJAhYjAYBIAAEFdXV/H19ZWDBw+axB48eFBefPFFsbe3F4PBIAsXLpSSkpJqx6xrnIiIn5+fuLm5SWVlZa151oUSnxdqkRJVIpwprbWZNGkSACApKcnCmVBLo1KpkJCQUG0OqaY0a9YsJCUl4fbt2xbLwRxKfd7Onz+P5557DvHx8QgODlYitSZVWVmJESNGICQkBDNmzLB0Oo91+/ZtuLu7IyoqCgsWLGjw8ZrD54UsIomvBYmoxTFnYPfTwtvbG5GRkYiMjERBQYGl0zFLRUUFUlJSkJ+fj6CgIEunU6NVq1ahf//+CAsLs3Qq1MKxuKJ6efvtt6HT6aBSqZpsEGtjqaysRHR0dIMW701OToanp6fJ19BVKhXs7OzQoUMHjBgxAhs3bsTdu3cVzJxam8WLF2PSpEkICgpqUYszp6enIzk5GWlpaXWeq6upbdq0CcePH8e+fftga2tr6XSohWNxRfXy+eef4y9/+Yul02iwzMxMvPzyy5g/f36D5uMJDAzEhQsX4OXlBUdHR4gIKisrkZOTg8TERHTp0gURERHo1atXoywH0losWbIE8fHxuH//Prp06YJdu3ZZOqUmt3btWoSFheHDDz+0dCp1NnLkSGzfvt1krcfmJDU1FQ8ePEB6ejqcnZ0tnQ49BWwsnQCRpZw4cQKRkZGYPXs2CgsLFV+oVaVSwcnJCSNGjMCIESPg5+eHKVOmwM/PD+fOnYOjo6Oi/bUG69atw7p16yydhsWNGjUKo0aNsnQaT41x48Zh3Lhxlk6DniJ8ckX1plKpLJ1Cg/Tr1w/JycmYNm1anWe+boiJEyciJCQEOTk5+Oyzzxq9PyIisgwWV1QnIoKNGzeie/fusLe3h6OjIxYuXFgtrqKiAitWrICHhwc0Gg369u2LhIQEAEBcXBwcHByg1WqRmpqK0aNHQ6/Xw93dHTt27DA5zsGDB/Hiiy9Cq9VCr9ejT58+xiUsauujMezfv1+xOY+q5mFKS0sztj2N14yIqDVjcUV1snz5ckRERCA0NBQ3b97EjRs3sGjRompxixYtwkcffYTo6Ghcv34d/v7+mDp1Kn755RfMmTMH8+bNQ3FxMXQ6HRISEpCVlQVPT0/MnDnTOJt2YWEhxo4di4kTJ+LOnTvIzMxEt27djMtS1NZHY6j6ZtqjMzzXV//+/QEAFy5cMLY9jdeMiKhVs+g0W2QR5k5qWFRUJFqtVl577TWT9h07dggAOXbsmIiIFBcXi1arlaCgIJN97e3tZc6cOSIisnTpUgEgxcXFxpjNmzcLADl//ryIiPzrX/8SAPLNN99Uy6UufdTHSy+9JP369av3/lW8vLzE0dGx1hiVSiVOTk4i0vKuGTgpotk4aW/rxc9Lq5XIAe30ROfPn0dRURFGjhxZa9zZs2dRVFSE3r17G9s0Gg1cXV1x5syZGvezs7MDAONTGE9PT3To0AHBwcGYO3cuQkJC8Oyzzzaoj+aiauC8Xq8H0DKvWWMsxPs0q1pOJTEx0cKZEFFTYXFFT1T1x8Hl3yvf16SwsBAAsGzZMixbtsxkm8FgqHN/Go0G33//PRYtWoS1a9ciMjISkydPRnx8vGJ9WMq5c+cAAD169ADQMq9ZTEwMYmJizN6vtZsyZYqlUyCiJsIxV/REarUaAPDgwYNa46qKr+joaIiIyY+5Tzt69eqFr7/+GteuXUNERAQSEhLw8ccfK9qHJezfvx8AMHr0aAAt85olJCRUOw5/av6ZOHEiJk6caPE8+NP0P9R6sbiiJ+rduzesrKxw8ODBWuM6deoEtVrd4Bnbr127htOnTwN4WHx8+OGHGDBgAE6fPq1YH5Zw48YNREdHw93d3bi2Gq8ZEdHTh8UVPZGLiwsCAwOxa9cubN26FXl5eTh58iS2bNliEqdWqzF9+nTs2LEDcXFxyMvLQ0VFBa5cuYLr16/Xub9r165h1qxZOHPmDEpLS3Hs2DFcvHgRgwcPVqwPc6SlpZk1FYOIoKCgAJWVlRAR5ObmIiEhAUOGDIG1tTVSUlKMY66e1mtGRNSqCbU69fn2Un5+vrz99tvSrl07adOmjQwdOlRWrFghAMTd3V1OnDghIiIPHjyQiIgI8fDwEBsbG3FxcZHAwEDJyMiQzZs3i1arFQDStWtXycrKki1btoherxcA0rlzZzl37pxkZ2eLr6+vODs7i7W1tTzzzDOydOlSKS8vf2If5jhy5IgMGTJEDAaDABAA4urqKr6+vnLw4EFj3L59+0Sn00lUVFSNx9qzZ4/07dtXtFqt2NnZiZWVlQAwfjPwxRdflMjISLl9+3a1fVvSNQO//WQ2fluw9eLnpdVKVInwxXBrM2nSJABAUlKShTOhlkalUiEhIQGTJ0+2dCotBj9vrRc/L61WEl8LEhERESmIxRU9Nc6cOQOVSvXEn6CgIEunSkRETzEWV/TU6NGjR52+Hr1z505Lp0pUZwcOHMDixYuRnJwMT09P4/8kvPnmm9ViR40aBZ1OB2tra/Tq1QtHjx61QMbmKSsrw7p16+Dt7Q07Ozs4OTmhd+/eyM7ONsZERkaiZ8+e0Ov1sLe3h7e3Nz744AMUFBSYHGvEiBE1/k9VmzZtzDrenj17sGHDBuPyV0TmYHFFRNRMrVy5ErGxsViyZAkCAwNx4cIFeHl5oV27dti2bRv27t1rEv/dd98hKSkJ/v7+yMjIwIABAyyUed1NmTIFf/3rX7F9+3YUFRXh119/hZeXl0mh8/333+Pdd99FdnY2bt26hXXr1iEmJsY4nq0uhg4datbxxo4dC7VajZEjR+LevXvKnCy1GiyuiKjFKC4uhq+vb4vvoy7Wr1+PnTt3IjExETqdzmRbbGwsrKysEBoaivv371sow4bbuXMnUlJSkJSUhJdeegk2NjYwGAxITU01Wa6pTZs2CA0NRdu2baHT6TB58mQEBARg//79uHz5sjFOrVYjLy+v2tPq0NBQfPDBB2Yfb+7cuejXrx/GjBmD8vLyprko9FRgcUVELcbWrVuRk5PT4vt4kvPnz2P58uVYvXq1cYWER/n6+iI8PBxXr17F+++/b4EMlfHnP/8ZAwYMQJ8+fWqN++abb2BtbW3S1r59ewBAUVGRsW3//v3VCtHLly/jX//6F/7whz+YfTwAWLVqFY4fP84ln8gsLK6IqNGICDZt2oTnnnsO9vb2cHZ2xvjx400WjA4LC4OdnR1cXV2Nbe+88w4cHBygUqlw69YtAEB4eDgWLFiArKwsqFQqeHt7IzY2Fmq1Gh06dMCsWbNgMBigVqvh6+uLn376SZE+gId/tM2ZSLahYmNjISIYO3ZsjTFRUVHo1q0bPv/8cxw4cKDW49XlPsTFxcHBwQFarRapqakYPXo09Ho93N3dsWPHDpPjVVRUYMWKFfDw8IBGo0Hfvn2RkJBg1jmWlpbixx9/RP/+/c3ar8rVq1eh0WjQpUuXWuPWr1+PuXPn1vt4zs7OGD58OGJiYrikDdVdE0+sRc0AJzWk+oKZkyKuWLFC7Ozs5KuvvpJ79+7JyZMnZcCAAdK+fXu5ceOGMW7atGnSsWNHk303btwoACQ3N9fYFhgYKF5eXiZxoaGh4uDgIKdPn5aSkhLJyMiQQYMGiU6nk0uXLinSxzfffCM6nU4iIyPrfO5V6vN58/T0lJ49ez52m5eXl/z2228iIvLDDz+IlZWVPPvss1JQUCAiImlpaTJu3DiTfep6H5YuXSoA5O9//7vcv39fcnJyZNiwYeLg4CClpaXGuPfff1/s7e1l165dcvfuXVmyZIlYWVnJzz//XOdz/O233wSA9O/fX0aMGCGurq5ib28vPXr0kE8//VQqKytr3LewsFB0Op2EhYXV2seVK1ekZ8+eUlFRUWvck463ePFiASDHjh178ok9wtzPCz01EvnkiogaRXFxMTZt2oQJEyYgODgYjo6O6NOnDz777DPcunWr2vJJDWFjY2N8KtOzZ0/ExcUhPz8f8fHxihzfz88PeXl5WL58uSLHq01hYSF+++03eHl5PTHWx8cH8+bNQ3Z2NhYtWvTYmPrcB19fX+j1eri4uCAoKAiFhYW4dOkSAKCkpARxcXEICAhAYGAgnJycsGzZMtja2pp1vasGrLu4uGDt2rXIyMjAzZs3MX78eLz77rv429/+VuO+69atg8FgQFRUVK19rF+/Hu+99x6srGr/U/ek43Xt2hUAcOrUqVqPQ1SFxRURNYqMjAwUFBRg4MCBJu2DBg2CnZ2dyWs7pQ0cOBBardbktVdLkZOTAxGBVqutU3xUVBS6d++OzZs34/Dhw9W2N/Q+2NnZAXg4ZQIAnD17FkVFRSYDzjUaDVxdXc263vb29gCAXr16wdfXF23btoWjoyNWr14NR0fHGovv3bt3IzExEd9++2218VWPunbtGvbs2YOQkJBa86jL8aruxc2bN+twZkQsroiokVR9ff3R+YWqODk5IT8/v1H7t7e3R25ubqP20RhKSkoA/F/x8SRqtRrx8fFQqVSYMWMGiouLTbYrfR8KCwsBAMuWLTOZR+rixYvVBoPXxmAwAIBxvFsVOzs7dO7cGVlZWdX22blzJ9avX4/09HQ8++yztR5/w4YNmDlz5mO/EGDu8TQaDYD/uzdET8LiiogahZOTEwA89o/3vXv34O7u3mh9l5WVNXofjaXqD7k5k1f6+Phg/vz5yMzMxJo1a0y2KX0fXFxcAADR0dHVpjw4cuRInY/Tpk0bdO3aFadPn662rby8HI6OjiZtn3zyCbZt24bvv/8ezzzzTK3HvnHjBv72t79hzpw5NcaYc7zS0lIA/3dviJ6ExRURNYrevXujTZs2+OWXX0zaf/rpJ5SWluKFF14wttnY2BhfOykhPT0dIoLBgwc3Wh+NpUOHDlCpVGbPX7VmzRr06NEDx44dM2k35z7URadOnaBWq3H8+HGz9nucKVOm4NixY7hw4YKxraioCBcvXjROzyAiiIiIwKlTp5CSkvLYJ3C/t2HDBgQHB6Nt27bVttXneFX3omPHjnU9NWrlWFwRUaNQq9VYsGABdu/ejW3btiEvLw+nTp3C7NmzYTAYEBoaaoz19vbGnTt3kJKSgrKyMuTm5uLixYvVjtm2bVtcu3YN2dnZyM/PNxZLlZWVuHv3LsrLy3Hy5EmEh4fDw8PDZLxNQ/pIS0trsqkYtFotPD09ceXKFbP2q3o9+Pv5m8y5D3XtZ/r06dixYwfi4uKQl5eHiooKXLlyBdevXwcABAUFoWPHjk9cfmf+/Pno3LkzQkJCcOnSJdy+fRsREREoLi42DtA/ffo0PvroI/zlL3+Bra1ttWVtPv74Y5Nj3rx5E1988QXmzZv32D7NPR4A47140nxcRFVYXBFRo1m5ciXWrVuHyMhItG/fHsOHD8ezzz6L9PR0ODg4GOPmzJmDV155BW+88Qa6d++ONWvWGF/B+Pj4GGfNnj17Njp06ICePXtizJgxuHPnDoCHY2H69OkDjUaDYcOGoVu3bvif//kfk3FLDe2jKfn5+SEjI8Nk/NR///d/w9vbG1lZWRg0aBDee++9avsNHjwY8+fPr9Zel/sQFxeH6OhoAEDfvn1x4cIF/OUvf8GCBQsAAK+//joyMzMBADExMZg3bx42bNiAdu3awWAwIDw8HHfv3gXw8DVaTk4OUlNTaz1PZ2dn/OMf/4C7uzv69+8PNzc3/L//9/+wd+9e4/xXYubcUh999BHGjh0LDw+Px24393gA8PPPP8PNzQ19+/Y1e19qnVRSn980atGq1s9KSkqycCbU0qhUKiQkJGDy5MmWTsVo1qxZSEpKwu3bty2dymPV5/N2/vx5PPfcc4iPj0dwcHBjpdZoKisrMWLECISEhGDGjBmWTqdBbt++DXd3d0RFRRkLzbpqjp8XahJJfHJFRC2eOYO/WwJvb29ERkYiMjLSZAHjlqCiogIpKSnIz89HUFCQpdNpsFWrVqF///4ICwuzdCrUgrC4IiJqhhYvXoxJkyYhKCioRS3OnJ6ejuTkZKSlpdV5rq7matOmTTh+/Dj27dsHW1tbS6dDLQiLKyJqsZYsWYL4+Hjcv38fXbp0wa5duyydkqLWrl2LsLAwfPjhh5ZOpc5GjhyJ7du3m6zj2BKlpqbiwYMHSE9Ph7Ozs6XToRbGxtIJEBHV17p167Bu3TpLp9GoRo0ahVGjRlk6jVZn3LhxGDdunKXToBaKT66IiIiIFMTiioiIiEhBLK6IiIiIFMTiioiIiEhBHNDeSv3444/GyQ2JzBEdHc0JaM3w448/AgA/b0StCIurVsjHx8fSKVALNXHiRIv0e+PGDRw7dgyjR4+2SP8N8eji0dS6TJw4EZ06dbJ0GmQBXP6GiJq9xMRETJkypV7rwhERNTEuf0NERESkJBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERApicUVERESkIBZXRERERAqysXQCRESPKisrQ0FBgUlbYWEhAODu3bsm7SqVCk5OTk2WGxFRXbC4IqJm5c6dO3Bzc0NFRUW1bW3btjX571deeQXff/99U6VGRFQnfC1IRM1Kx44d8fLLL8PKqvZ/nlQqFd54440myoqIqO5YXBFRs/Pmm28+Mcba2hoTJkxogmyIiMzD4oqImp3AwEDY2NQ8asHa2hqvv/462rVr14RZERHVDYsrImp29Ho9Ro8eXWOBJSIIDg5u4qyIiOqGxRURNUvBwcGPHdQOAHZ2dvjjH//YxBkREdUNiysiapb++Mc/QqvVVmu3tbVFQEAAHBwcLJAVEdGTsbgiomZJrVZjwoQJsLW1NWkvKyvDtGnTLJQVEdGTsbgiomZr6tSpKCsrM2nT6/V47bXXLJQREdGTsbgiombr1VdfNZk41NbWf7lgEQAAIABJREFUFm+88Qbs7OwsmBURUe1YXBFRs2VjY4M33njD+GqwrKwMU6dOtXBWRES1Y3FFRM3aG2+8YXw12LFjRwwdOtTCGRER1Y7FFRE1a76+vnBzcwMAvPXWW09cFoeIyNK4cHM9JSYmWjoFolZj0KBBuHr1Ktq1a8fPHlET6dSpE3x8fCydRoukEhGxdBItkUqlsnQKREREjWbixIlISkqydBotURKfXDVAQkICJk+ebOk0iFqFXbt2YeLEifXef9KkSQDAPxZmSExMxJQpU8D/B299qj4vVD8cvEBELUJDCisioqbE4oqIiIhIQSyuiIiIiBTE4oqIiIhIQSyuiIiIiBTE4oqIiIhIQSyuiIjMsG/fPjg6OuLrr7+2dCrN3oEDB7B48WIkJyfD09MTKpUKKpUKb775ZrXYUaNGQafTwdraGr169cLRo0ctkLF5ysrKsG7dOnh7e8POzg5OTk7o3bs3srOzjTGRkZHo2bMn9Ho97O3t4e3tjQ8++AAFBQUmxxoxYoTx+vz+p02bNmYdb8+ePdiwYQMqKioa/RrQ47G4IiIyA+d8qpuVK1ciNjYWS5YsQWBgIC5cuAAvLy+0a9cO27Ztw969e03iv/vuOyQlJcHf3x8ZGRkYMGCAhTKvuylTpuCvf/0rtm/fjqKiIvz666/w8vIyKXS+//57vPvuu8jOzsatW7ewbt06xMTEmDWP1KPradbleGPHjoVarcbIkSNx7949ZU6WzMLiiojIDH5+frh//z78/f0tnQqKi4vh6+tr6TSqWb9+PXbu3InExETodDqTbbGxsbCyskJoaCju379voQwbbufOnUhJSUFSUhJeeukl2NjYwGAwIDU1Fb179zbGtWnTBqGhoWjbti10Oh0mT56MgIAA7N+/H5cvXzbGqdVq5OXlQURMfkJDQ/HBBx+Yfby5c+eiX79+GDNmDMrLy5vmopARiysiohZq69atyMnJsXQaJs6fP4/ly5dj9erVUKvV1bb7+voiPDwcV69exfvvv2+BDJXx5z//GQMG/H/27jQqqivdG/i/kKEYiimCoIgyOKEgbaQjdGyn23YM7RRUUDFB+3pRo4hoRJxFRCBe4BKl0zEJ6cSogBo0KpplDJ2kY2yTaFR8tREBxQFwQGaZ9vvBRcWyGKqgoED+v7XqQ/bZZ5/nnF1YT87ZZ+8RcHV1bbbe0aNH0aNHD4Wynj17AgAqKirkZSdOnFBKRG/duoXLly9j/PjxarcHAJs3b8aFCxcQHx+v4lmRpjC5IiJS0ffffw97e3tIJBLs3LkTAJCYmAhjY2MYGRnh8OHDmDRpEkxNTWFnZ4d9+/bJ901ISIBUKoW1tTUWLVoEW1tbSKVSeHl54ezZs/J6QUFB0NfXh42Njbzs7bffhrGxMSQSCe7fvw8ACA4OxsqVK5GdnQ2JRAJnZ2cAT3+kTU1NsW3bto64JEoSEhIghMCUKVOarBMREYGBAwfiww8/xKlTp5ptTwiB2NhYDBkyBAYGBrCwsMC0adNw9epVeR1V+wAA6urqsHHjRtjb28PQ0BBubm5ITk5W6xyrq6vx448/wt3dXa39Gty+fRuGhoZwcHBotl5UVBSWL1/e6vYsLCwwZswYxMfH83F2B2NyRUSkoldffRU//PCDQtmSJUuwYsUKVFZWQiaTITk5GdnZ2XB0dMTChQtRU1MD4GnSFBAQgIqKCixfvhy5ubn45ZdfUFtbiz/96U/yRzoJCQlKa5bu2rULW7ZsUSiLj4/H5MmT4eTkBCEErl+/DgDyQcz19fXtcg1acuzYMQwaNAhGRkZN1jE0NMQnn3wCHR0dLFy4EOXl5U3W3bx5M8LCwrBu3ToUFhbi22+/xa1btzB69GgUFBQAUL0PAGDNmjWIiYlBXFwc7t69i8mTJ2POnDn46aefVD7HO3fuoLq6Gj///DPGjRsnT5SHDBmCXbt2NZvIVFRU4PTp01i4cCH09fWbrHf79m1kZGTAx8en2Vhaau93v/sdbt++jV9//VXl86O2Y3JFRKQhXl5eMDU1hZWVFfz8/FBeXo6bN28q1NHV1ZXfhXFxcUFiYiJKS0uRlJSkkRi8vb1RUlKCDRs2aKQ9dZSXlyMnJwdOTk4t1vX09MSKFSuQm5uLNWvWNFqnsrISsbGxeOONN+Dv7w8zMzO4urri/fffx/379/HBBx8o7dNcH1RVVSExMRHTp0+Hj48PzM3NsX79eujp6al1/RsGrFtZWWHbtm3IzMxEQUEBpk2bhqVLl2Lv3r1N7hsZGQlbW1tEREQ0e4yoqCgsW7YMOjrN/0y31N6AAQMAAJcuXWq2HdIsJldERO2g4S7Cs3dNGjNy5EgYGRkpPObqqgoLCyGEaPau1bMiIiIwaNAg7Nq1C99//73S9szMTJSVlWHkyJEK5R4eHtDX11d4nNqY5/vg2rVrqKioUBhwbmhoCBsbG7Wuv4GBAQBg6NCh8PLygqWlJczMzLBlyxaYmZk1mvQBwKFDh5CSkoKTJ08qja961p07d3DkyBEEBAQ0G4cq7TX0RcNdPuoYTK6IiLTMwMAARUVF2g6jzaqqqgD8lny0RCqVIikpCRKJBAsWLEBlZaXC9oZpBJ6d56mBubk5SktL1Yqv4fHj+vXrFeaRysvLUxoM3hxbW1sAkI9/a6Cvr49+/fohOztbaZ/9+/cjKioKGRkZ6N+/f7PtR0dHY+HChY2+EKBue4aGhgB+6xvqGEyuiIi0qKamBsXFxbCzs9N2KG3W8EOuzuSVnp6eCAkJQVZWFrZu3aqwzdzcHAAaTaJac82srKwAAHFxcUpTHpw5c0bldkxMTDBgwABcuXJFaVttbS3MzMwUyt577z3s2bMHp0+fRu/evZtt+969e9i7dy+WLFnSZB112quurgbwW99Qx2ByRUSkRRkZGRBCYNSoUfIyXV3dFh8ndkbW1taQSCRqz1+1detWDB48GOfPn1coHzZsGExMTJQGm589exbV1dV4+eWX1TpO3759IZVKceHCBbX2a4yvry/Onz+PGzduyMsqKiqQl5cnn55BCIHQ0FBcunQJaWlpjd6Be150dDT8/f1haWmptK017TX0Ra9evVQ9NdIAJldERB2ovr4ejx49Qm1tLS5evIjg4GDY29srjK9xdnbGw4cPkZaWhpqaGhQVFSEvL0+pLUtLS9y5cwe5ubkoLS1FTU0N0tPTtTYVg5GRERwdHZGfn6/Wfg2PB5+fv0kqlWLlypU4dOgQ9uzZg5KSEly6dAmLFy+Gra0tAgMD1T7O/PnzsW/fPiQmJqKkpAR1dXXIz8/H3bt3AQB+fn7o1atXi8vvhISEoF+/fggICMDNmzfx4MEDhIaGorKyUj5A/8qVK4iJicHu3buhp6entKzNjh07FNosKCjAxx9/jBUrVjR6THXbAyDvi5bm4yLNYnJFRKSinTt3wsPDAwAQGhqKqVOnIjExEXFxcQAANzc33LhxA7t378bKlSsBAK+99hqysrLkbVRVVcHV1RWGhoYYPXo0Bg4ciG+++UZhnNKSJUswbtw4zJ49G4MGDcLWrVvlj3U8PT3l0zYsXrwY1tbWcHFxweuvv46HDx92yHVojre3NzIzMxXGT33xxRdwdnZGdnY2PDw8sGzZMqX9Ro0ahZCQEKXyTZs2ITIyEuHh4ejZsyfGjBmD/v37IyMjA8bGxgCgVh/Ex8djxYoViI6OxksvvQRbW1sEBwfj0aNHAJ4+RissLMThw4ebPU8LCwt89913sLOzg7u7O/r06YN///vfOHbsmHz+K3XnloqJicGUKVNgb2/f6PbWzFV17tw59OnTB25ubmrvS60nEZxZrFUkEgmSk5OV5qMhos6pYe211NRUrcWwaNEipKam4sGDB1qLQR0pKSnw9fVV60f9+vXrGDJkCJKSkuDv79+O0bWP+vp6jB07FgEBAViwYIG2w2mTBw8ewM7ODhEREfJEU1Wd4e+lC0vlnSsiog6kzmDvrsjZ2Rnh4eEIDw9XWMC4K6irq0NaWhpKS0vh5+en7XDabPPmzXB3d0dQUJC2Q+l2mFx1gB07dsgHer7//vsaaXP79u0wMzODRCLRyODMzqI9rlVjwsPD4eLiAlNTUxgYGMDZ2RmrV69u1Y/BwYMH4ejoKB/3YGNj067/x67pvn8+/oaPVCqFg4MDFixYgJycnDa12dI1+b//+z/07t0bEokEOjo6GDhwoNKyKH/5y19gamoKHR0dDB48GP/6179adb7U/sLCwjBz5kz4+fl1qcWZMzIycPDgQaSnp6s8V1dnFRsbiwsXLuD48ePQ09PTdjjdj6BWASCSk5NVrp+VlSUAiL/97W8ai2Hfvn0CgDh//rzG2uwM2uNaPW/MmDFi165d4sGDB6KkpEQkJycLPT098dprr7W6TScnJ2FmZqbBKJvWHn3/bPx1dXWioKBAfPrpp8LIyEhYW1uL+/fvt6lNVQAQr7zySpPbv/nmGzFhwgS14xBCiBkzZogZM2a0al9NCAsLE/r6+gKA6N+/v0hNTdVaLKpKTk4WbfmZOHnypAgNDdVgRKSKtLQ0ERkZKWpra1vdhrb/Xrq4FN65om7JxMQEgYGBsLS0hEwmw6xZszB9+nScOHFCPli4O9PR0YG1tTXmzZuHpUuXorCwsMUFdql5kZGRePLkCYQQyMnJwYwZM7QdUrubOHEioqKitB1GtzN16lSEhYUpvX1JHUdX2wEQacPRo0eVynr27AkAas3U3B04OzsDeDq5IRERtYx3rrSorq4OGzduhL29PQwNDeHm5obk5GT59u+++w4uLi4wMzODVCqFq6srTp482WR7BQUF6N+/P3R1dfHaa68BAP77v/9bPu7FyclJPknf/PnzYWRkBDMzMxw5ckTlmGNiYmBkZASZTIbCwkKsXLkSffr0wbVr11o8n9YKCgqCvr4+bGxs5GVvv/02jI2NIZFIlJagaK3bt2/D0NAQDg4O8rITJ060y5xBXanvG15hHz58uFrnQETUXTG50qI1a9YgJiYGcXFxuHv3LiZPnow5c+bIZyMuKCiAr68vcnNzcefOHZiYmGDu3LlNtmdpaYmRI0fi0KFDOHHiBADgww8/hI+PD3r06IHvvvsOv/vd7wAASUlJmD59Ovbs2YMpU6aoHPPq1asREhKCsrIyREZGwsHBAaNGjYIQosXzaa2EhASlKS927dqFLVu2tKndZ1VUVOD06dNYuHChfLFX4Lc3u+rr6zV2LKBr9H1xcTH+8Y9/YNeuXfD29sbYsWPVOgciom5L26O+uiq0cUB7ZWWlMDIyEn5+fvI6FRUVwsDAQCxZsqTRNiIjIwUAUVhYKIRQHNRcU1MjZs+eLdLT05X2O3XqlAAgIiIi5GWPHz8WAwYMaNWAx3Xr1gkAorKyUl7WmvNpSmMD2ufOnSt69eqlUO/dd98VAERRUZHa5/C8devWiYEDB4qSkpJWt6Hq4O3O2vdOTk4CgMJHIpGIiIgIUV1d3apz4ID2rq2tA9qp6+LfS5ukcMyVlly7dg0VFRUYNmyYvMzQ0BA2Nja4evVqo/s0vE77/Dw5dXV1mDNnDnr37i1/JPSs8ePHY+DAgfj444+xdu1aSCQS7N+/H35+fhob8Nia8+ksDh06hJSUFHz11VeQyWTtfrzO3PdmZmYoLi4G8PQu5bvvvgszMzOlV7m7an//+OOP8skRqWUNS6fwmnU/P/74o8J6l6QePhbUkvLycgDA+vXrFeYWysvLkw+oPnbsGMaOHQsrKysYGBhg9erVjba1dOlSZGVl4f333290lXaJRIJFixbhxo0b+PrrrwEAn376Kf7617926Pl0Rvv370dUVBQyMjLQv3//DjlmV+n7DRs2wMbGBmvXrlV6g7I9+7u5R7B1dXWcs4eIOj9t3zvrqtDGx4L/+c9/BAARFxfXaP28vDyhp6cnfH19RXZ2tqisrBQxMTECgLh7964Q4rdHQ7GxsaKoqEj06tVLvPzyy6KmpkapvYcPHwqpVCp8fX3F1atXxaRJk1px1k819liwpfNRR0c9FkxISBDe3t6itLS0TfE2aO4R2D//+U8RGxsrhOi8fd9Y/J988okAIP7yl78olKva36pekwaWlpaiT58+Tba3e/dusXDhwmaP2RQ+5lAfHwt2X/x7aRPOc6Utffv2hVQqbXKG7UuXLqGmpgZLliyBo6MjpFIpJBJJo3XHjRuHnj174oMPPsDPP/+MiIgIpToWFhbw9fVFWloaduzYgYULF3bo+bSVrq4uampqNNKWEAKhoaG4dOkS0tLSYGJiopF2m/Pzzz/LF5ntSn3/5ptv4pVXXsHRo0eRkpIiL9dEfz97TRqMHz8et2/fxg8//KBUXwiBTz75BK+88kqrj0lE1BGYXGmJVCrF/PnzsW/fPiQmJqKkpAR1dXXIz8/H3bt35auinzp1ClVVVcjKysLZs2ebbXPKlCkICAjAtm3b8PPPPyttX7x4MZ48eYKjR49i8uTJHXo+beXs7IyHDx8iLS0NNTU1KCoqQl5eXqvaunLlCmJiYrB7927o6ekpLfuyY8cOed309PQ2TcVQU1ODgoICZGRkyBOJrtT3EokECQkJkEgkCAoKwqNHj1Q6B3WvSYOIiAiYm5tj5syZ+OKLL1BeXo4nT57g119/xZw5c1BbW4t58+apHD8RkVZo+95ZVwU1Hgv+7//+r+jVq5cAIIyNjcUbb7whhBDiyZMnIjQ0VNjb2wtdXV1hZWUlfHx8RGZmphBCiNDQUGFpaSnMzc3FzJkzxc6dOwUA4eTkJOLj44WFhYV8KY3CwkJRUlIi+vbtKwAIExMT8emnnyrF8rvf/U6EhYW1+ryjo6OFoaGhACD69u0rPvvsM/m2ls6nLdfqwYMHYty4cUIqlQoHBwexbNky8c477wgAwtnZWdy8eVPlY1y6dEnprbhnP++++6687vHjx4VMJlN42+55hw4davRNu+c/hw4dUvladWTf/+tf/xIDBw6Ux9m7d2+xaNEihToBAQECgDA3Nxfbt29v8Rxac00a5OTkiIULFwoHBwehr68vDA0NhYuLi9i4caMoKytroXebxscc6uNjwe6Lfy9tkiIRQoj2TN5eVBKJBMnJyUrzL3V23t7e2Llzp8JEmdQ9dPe+b3jjLTU1VcuRdB0pKSnw9fUFfya6H/69tEkqHwu+4J4dp3Tx4kVIpdJu++Pa3bDviYi0g8nVCy40NBRZWVn4z3/+g/nz52Pr1q1Kda5evao07qixj5+fX6tiaO/2O+oYXY0qfU/Unk6dOoWwsDAcPHgQjo6O8r/DxsbNTZw4ETKZDD169MDQoUPxyy+/aCFi9dTU1CAyMhLOzs7Q19eHubk5hg0bhtzcXHmd8PBwuLi4wNTUFAYGBnB2dsbq1atRVlam0NbYsWOb/Hfr2ZduVGnvyJEjiI6OVpoXjzoOJxF9wRkZGWHw4MHo06cPdu3aBRcXF6U6gwcPbtfb/u3dfkcdo6tRpe+J2sumTZtw/vx5fP7555DJZPDx8YGzszOKi4uxZ88e+Pn5wdvbW17/q6++wokTJ/D+++8jLS1Ni5GrztfXF1euXMHnn3+Ol19+GUVFRVi0aJFConP69GksXboUfn5+0NPTQ3p6Ovz9/XHp0iWkp6erdJxXX31VrfamTJmCnJwcTJgwAWlpaTA3N9fsiVPLtDniqyuDmvNcEZF2dYYBuhUVFcLT07PLHKO1A9q3b98uBg4cqDAXnhBP5z37/PPPhY6OjujTp48oLi5W2J6eni6mTp3appg7yr59+4REIhEXL15stp63t7fSUlOzZs0SABRexPnzn//c6PJbgYGB4uuvv1a7PSGECAoKEp6eno3Of9eSzvD30oVxnisioo7y0UcfobCwsMsfoznXr1/Hhg0bsGXLFkilUqXtXl5eCA4Oxu3bt7Fq1SotRKgZf/vb3zBixAi4uro2W+/o0aNKS0317NkTABRWMzhx4oTS8lu3bt3C5cuXMX78eLXbA4DNmzfjwoULiI+PV/GsSFOYXBERNUEIgdjYWAwZMgQGBgawsLDAtGnTFNZPDAoKgr6+PmxsbORlb7/9NoyNjSGRSHD//n0AQHBwMFauXIns7GxIJBI4OzsjISEBUqkU1tbWWLRoEWxtbSGVSuHl5aUwt1lbjgE8/eFuy3xt6khISIAQAlOmTGmyTkREBAYOHIgPP/wQp06darY9VfogMTERxsbGMDIywuHDhzFp0iSYmprCzs4O+/btU2ivrq4OGzduhL29PQwNDeHm5obk5GS1zrG6uho//vgj3N3d1dqvwe3bt2FoaNjiCyZRUVFYvnx5q9uzsLDAmDFjEB8fz2ETHU27d866LvCxIFGX0prHHBs3bhT6+vris88+E8XFxeLixYtixIgRomfPnuLevXvyeqouz+Tj4yOcnJwU6gUGBgpjY2Nx5coVUVVVJTIzM4WHh4eQyWQKj3nacoyjR48KmUwmwsPD1Tr/1jwWdHR0FC4uLo1uc3JyEjk5OUIIIX744Qeho6Mj+vfvL5+/rLHHgqr2QcOyXF9//bV4/PixKCwsFKNHjxbGxsaiurpaXm/VqlXCwMBAHDhwQDx69EisXbtW6OjoiHPnzql8jjk5OQKAcHd3F2PHjhU2NjbCwMBADB48WOzcuVPU19c3uW95ebmQyWQiKCio2WPk5+cLFxcXUVdX12y9ltoLCwsTAMT58+dbPrFn8LFgm/CxIBFRYyorKxEbG4s33ngD/v7+MDMzg6urK95//33cv38fH3zwgcaOpaurK78z4+LigsTERJSWliIpKUkj7Xt7e6OkpAQbNmzQSHtNKS8vR05ODpycnFqs6+npiRUrViA3Nxdr1qxptE5r+sDLywumpqawsrKCn58fysvLcfPmTQBAVVUVEhMTMX36dPj4+MDc3Bzr16+Hnp6eWte6YcC6lZUVtm3bhszMTBQUFGDatGlYunQp9u7d2+S+kZGRsLW1bXSpqmdFRUVh2bJl0NFp/me6pfYGDBgA4OmyWtRxmFwRETUiMzMTZWVlGDlypEK5h4cH9PX1W1ySqC1GjhwJIyMjhUdfXUFhYSGEEDAyMlKpfkREBAYNGoRdu3bh+++/V9re1j7Q19cH8Nucb9euXUNFRQWGDRsmr2NoaAgbGxu1rrWBgQEAYOjQofDy8oKlpSXMzMywZcsWmJmZNZl4Hzp0CCkpKTh58qTS+Kpn3blzB0eOHEFAQECzcajSXkNfFBQUqHBmpClMroiIGlFcXAwAjS7sbW5ujtLS0nY9voGBAYqKitr1GJpWVVUF4LfkoyVSqRRJSUmQSCRYsGABKisrFbZrug/Ky8sBAOvXr1eYRyovL09pMHhzbG1tAUA+1q2Bvr4++vXrh+zsbKV99u/fj6ioKGRkZKB///7Nth8dHY2FCxc2+kKAuu0ZGhoC+K1vqGMwuSIiakTD3ECN/YAXFxfDzs6u3Y5dU1PT7sdoDw0/5OpMXunp6YmQkBBkZWUpTXSr6T6wsrICAMTFxUEIofA5c+aMyu2YmJhgwIABuHLlitK22tpamJmZKZS999572LNnD06fPo3evXs32/a9e/ewd+9eLFmypMk66rRXXV0N4Le+oY7B5IqIqBHDhg2DiYkJfvrpJ4Xys2fPorq6Gi+//LK8TFdXV2G5obbKyMiAEAKjRo1qt2O0B2tra0gkEjx+/Fit/bZu3YrBgwfj/PnzCuXq9IEq+vbtC6lUigsXLqi1X2N8fX1x/vx53LhxQ15WUVGBvLw8+fQMQgiEhobi0qVLSEtLa/QO3POio6Ph7+8PS0tLpW2taa+hL3r16qXqqZEGMLkiImqEVCrFypUrcejQIezZswclJSW4dOkSFi9eDFtbWwQGBsrrOjs74+HDh0hLS0NNTQ2KioqQl5en1KalpSXu3LmD3NxclJaWypOl+vp6PHr0CLW1tbh48SKCg4Nhb2+vMOamLcdIT0/vkKkYjIyM4OjoiPz8fLX2a3g8+Pz8Ter0garHmT9/Pvbt24fExESUlJSgrq4O+fn5uHv3LgDAz88PvXr1anH5nZCQEPTr1w8BAQG4efMmHjx4gNDQUFRWVsoH6F+5cgUxMTHYvXs39PT0lJa12bFjh0KbBQUF+Pjjj7FixYpGj6luewDkfdHSfFykWUyuiIiasGnTJkRGRiI8PBw9e/bEmDFj0L9/f2RkZMDY2Fheb8mSJRg3bhxmz56NQYMGYevWrfLHMJ6enrh16xYAYPHixbC2toaLiwtef/11PHz4EMDT8TCurq4wNDTE6NGjMXDgQHzzzTcKY5faeoyO4u3tjczMTIXxU1988QWcnZ2RnZ0NDw8PLFu2TGm/UaNGISQkRKlclT5ITExEXFwcAMDNzQ03btzA7t27sXLlSgDAa6+9hqysLABAfHw8VqxYgejoaLz00kuwtbVFcHAwHj16BODpY7TCwkIcPny42fO0sLDAd999Bzs7O7i7u6NPnz7497//jWPHjsnnvxJqzi0VExODKVOmwN7evtHt6rYHAOfOnUOfPn3g5uam9r7UehLRmt4iSCQSJCcnY9asWdoOhYhUMHPmTABAamqqliNRtGjRIqSmpuLBgwfaDkVJSkoKfH191fpRv379OoYMGYKkpCT4+/u3Y3Tto76+HmPHjkVAQAAWLFig7XDa5MGDB7Czs0NERIQ80VRVZ/176SJSeeeKiEjL1BkA3tk5OzsjPDwc4eHhCgsYdwV1dXVIS0tDaWkp/Pz8tB1Om23evBnu7u4ICgrSdijdDpMrIiLSqLCwMMycORN+fn5qD27XpoyMDBw8eBDp6ekqz9XVWcXGxuLChQs4fvw49PT0tB1Ot8PkiohIS9auXYukpCQ8fvwYDg4OOHDggLZD0pht27YhKCgI27dv13YoKpswYQI+//xzhTUcu6LDhw/jyZMnyMjIgIWFhbbD6ZZ0tR0AEVGU4EiLAAAgAElEQVR3FRkZicjISG2H0W4mTpyIiRMnajuMbmfq1KmYOnWqtsPo1njnioiIiEiDmFwRERERaRCTKyIiIiINYnJFREREpEFMroiIiIg0iDO0t5JEItF2CERERO1mxowZnKG9dVI5FUMrJScnazsEom7jzJkziI+P598dUQfq27evtkPosnjniog6vdascUdEpCVcW5CIiIhIk5hcEREREWkQkysiIiIiDWJyRURERKRBTK6IiIiINIjJFREREZEGMbkiIiIi0iAmV0REREQaxOSKiIiISIOYXBERERFpEJMrIiIiIg1ickVERESkQUyuiIiIiDSIyRURERGRBjG5IiIiItIgJldEREREGsTkioiIiEiDmFwRERERaRCTKyIiIiINYnJFREREpEFMroiIiIg0iMkVERERkQYxuSIiIiLSICZXRERERBrE5IqIiIhIg5hcEREREWkQkysiIiIiDWJyRURERKRBTK6IiIiINIjJFREREZEGMbkiIiIi0iAmV0REREQapKvtAIiInlVUVIQvvvhCoeynn34CAHzwwQcK5TKZDLNnz+6w2IiIVCERQghtB0FE1ODJkyewtrZGWVkZevToAQBo+GdKIpHI69XU1OCtt97CJ598oo0wiYiaksrHgkTUqRgYGGDGjBnQ1dVFTU0NampqUFtbi9raWvl/19TUAADmzJmj5WiJiJQxuSKiTmfOnDmorq5uto65uTnGjx/fQREREamOyRURdTrjxo2DlZVVk9v19PTg7+8PXV0OGyWizofJFRF1Ojo6Opg7dy709PQa3V5TU8OB7ETUaTG5IqJOafbs2fKxVc/r3bs3PD09OzgiIiLVMLkiok7p97//Pfr166dUrq+vj7feekvhzUEios6EyRURdVrz5s1TejRYXV3NR4JE1KkxuSKiTmvu3LlKjwadnZ3h6uqqpYiIiFrG5IqIOq3BgwfDxcVF/ghQT08P8+fP13JURETNY3JFRJ3am2++KZ+pvba2lo8EiajTY3JFRJ3a7NmzUVdXBwAYMWIEHBwctBwREVHzmFwRUadmb2+PV155BQDw1ltvaTkaIqKWcXrjLiA2NhZnzpzRdhhEWvPkyRNIJBJ89dVX+Pbbb7UdDpHWhISEcI63LoB3rrqAM2fO4Mcff9R2GPQCy8/Px4EDB7QdRpPs7OzQq1cvSKVSbYei4MCBA8jPz9d2GNRNHDhwALdu3dJ2GKQC3rnqIkaNGoXU1FRth0EvqJSUFPj6+nbq79j169fh7Oys7TAUSCQSrFixArNmzdJ2KNQNcOLcroN3roioS+hsiRURUVOYXBERERFpEJMrIiIiIg1ickVERESkQUyuiIiIiDSIyRURaczx48dhZmaGL7/8UtuhvNBOnTqFsLAwHDx4EI6OjpBIJJBIJJg3b55S3YkTJ0Imk6FHjx4YOnQofvnlFy1ErJ6amhpERkbC2dkZ+vr6MDc3x7Bhw5CbmyuvEx4eDhcXF5iamsLAwADOzs5YvXo1ysrKFNoaO3as/Po8/zExMVGrvSNHjiA6Olq+YgBRU5hcEZHGCCG0HcILb9OmTUhISMDatWvh4+ODGzduwMnJCS+99BL27NmDY8eOKdT/6quvkJqaismTJyMzMxMjRozQUuSq8/X1xaefforPP/8cFRUV+H//7//ByclJIdE5ffo0li5ditzcXNy/fx+RkZGIj4/HzJkzVT7Oq6++qlZ7U6ZMgVQqxYQJE1BcXKyZk6UXEpMrItIYb29vPH78GJMnT9Z2KKisrISXl5e2w9CoqKgo7N+/HykpKZDJZArbEhISoKOjg8DAQDx+/FhLEbbd/v37kZaWhtTUVLzyyivQ1dWFra0tDh8+jGHDhsnrmZiYIDAwEJaWlpDJZJg1axamT5+OEydOKEy0KZVKUVJSAiGEwicwMBCrV69Wu73ly5dj+PDheP3111FbW9sxF4W6HCZXRPRC+uijj1BYWKjtMDTm+vXr2LBhA7Zs2dLoTPVeXl4IDg7G7du3sWrVKi1EqBl/+9vfMGLECLi6ujZb7+jRo+jRo4dCWc+ePQEAFRUV8rITJ04oJaK3bt3C5cuXMX78eLXbA4DNmzfjwoULiI+PV/GsqLthckVEGvH999/D3t4eEokEO3fuBAAkJibC2NgYRkZGOHz4MCZNmgRTU1PY2dlh37598n0TEhIglUphbW2NRYsWwdbWFlKpFF5eXjh79qy8XlBQEPT19WFjYyMve/vtt2FsbAyJRIL79+8DAIKDg7Fy5UpkZ2dDIpHIJyA9ceIETE1NsW3bto64JBqVkJAAIQSmTJnSZJ2IiAgMHDgQH374IU6dOtVse0IIxMbGYsiQITAwMICFhQWmTZuGq1evyuuo2n8AUFdXh40bN8Le3h6GhoZwc3NDcnKyWudYXV2NH3/8Ee7u7mrt1+D27dswNDSEg4NDs/WioqKwfPnyVrdnYWGBMWPGID4+no/CqXGCOr0ZM2aIGTNmaDsMeoElJycLTfxzcOvWLQFAvPfee/KydevWCQDi66+/Fo8fPxaFhYVi9OjRwtjYWFRXV8vrBQYGCmNjY3HlyhVRVVUlMjMzhYeHh5DJZOLmzZvyenPnzhW9evVSOO67774rAIiioiJ5mY+Pj3ByclKod/ToUSGTyUR4eHibz1UIIQCI5ORkjbTVEkdHR+Hi4tLoNicnJ5GTkyOEEOKHH34QOjo6on///qKsrEwIIUR6erqYOnWqwj4bN24U+vr64rPPPhPFxcXi4sWLYsSIEaJnz57i3r178nqq9t+qVauEgYGBOHDggHj06JFYu3at0NHREefOnVP5HHNycgQA4e7uLsaOHStsbGyEgYGBGDx4sNi5c6eor69vct/y8nIhk8lEUFBQs8fIz88XLi4uoq6urtl6LbUXFhYmAIjz58+3fGIa0pHfN2qTFN65IqIO4eXlBVNTU1hZWcHPzw/l5eW4efOmQh1dXV35nRQXFxckJiaitLQUSUlJGonB29sbJSUl2LBhg0ba6yjl5eXIycmBk5NTi3U9PT2xYsUK5ObmYs2aNY3WqaysRGxsLN544w34+/vDzMwMrq6ueP/993H//n188MEHSvs0139VVVVITEzE9OnT4ePjA3Nzc6xfvx56enpq9V3DgHUrKyts27YNmZmZKCgowLRp07B06VLs3bu3yX0jIyNha2uLiIiIZo8RFRWFZcuWQUen+Z+/ltobMGAAAODSpUvNtkPdE5MrIupw+vr6AJ6+ct+ckSNHwsjISOFRVXdUWFgIIQSMjIxUqh8REYFBgwZh165d+P7775W2Z2ZmoqysDCNHjlQo9/DwgL6+vsKj2MY833/Xrl1DRUWFwoBzQ0ND2NjYqNV3BgYGAIChQ4fCy8sLlpaWMDMzw5YtW2BmZtZo0gcAhw4dQkpKCk6ePKk0vupZd+7cwZEjRxAQENBsHKq019AXBQUFKpwZdTdMroioUzMwMEBRUZG2w9CqqqoqAL8lHy2RSqVISkqCRCLBggULUFlZqbC9YRqBZ+d5amBubo7S0lK14isvLwcArF+/XmEeqby8PKXB4M2xtbUFAPnYuQb6+vro168fsrOzlfbZv38/oqKikJGRgf79+zfbfnR0NBYuXNjoCwHqtmdoaAjgt74hehaTKyLqtGpqalBcXAw7Oztth6JVDT/k6kxe6enpiZCQEGRlZWHr1q0K28zNzQGg0SSqNdfbysoKABAXF6c05cGZM2dUbsfExAQDBgzAlStXlLbV1tbCzMxMoey9997Dnj17cPr0afTu3bvZtu/du4e9e/diyZIlTdZRp73q6moAv/UN0bOYXBFRp5WRkQEhBEaNGiUv09XVbfFx4ovG2toaEolE7fmrtm7disGDB+P8+fMK5cOGDYOJiQl++uknhfKzZ8+iuroaL7/8slrH6du3L6RSKS5cuKDWfo3x9fXF+fPncePGDXlZRUUF8vLy5NMzCCEQGhqKS5cuIS0trdE7cM+Ljo6Gv78/LC0tlba1pr2GvujVq5eqp0bdCJMrIuo06uvr8ejRI9TW1uLixYsIDg6Gvb29whgZZ2dnPHz4EGlpaaipqUFRURHy8vKU2rK0tMSdO3eQm5uL0tJS1NTUID09vUtOxWBkZARHR0fk5+ertV/D48Hn52+SSqVYuXIlDh06hD179qCkpASXLl3C4sWLYWtri8DAQLWPM3/+fOzbtw+JiYkoKSlBXV0d8vPzcffuXQCAn58fevXq1eLyOyEhIejXrx8CAgJw8+ZNPHjwAKGhoaisrJQP0L9y5QpiYmKwe/du6OnpKS1rs2PHDoU2CwoK8PHHH2PFihWNHlPd9gDI+6Kl+bioe2JyRUQasXPnTnh4eAAAQkNDMXXqVCQmJiIuLg4A4Obmhhs3bmD37t1YuXIlAOC1115DVlaWvI2qqiq4urrC0NAQo0ePxsCBA/HNN98ojDVasmQJxo0bh9mzZ2PQoEHYunWr/NGMp6enfDbtxYsXw9raGi4uLnj99dfx8OHDDrkO7cXb2xuZmZkK46e++OILODs7Izs7Gx4eHli2bJnSfqNGjUJISIhS+aZNmxAZGYnw8HD07NkTY8aMQf/+/ZGRkQFjY2MAUKv/4uPjsWLFCkRHR+Oll16Cra0tgoOD8ejRIwBPH6MVFhbi8OHDzZ6nhYUFvvvuO9jZ2cHd3R19+vTBv//9bxw7dkw+/5VQc26pmJgYTJkyBfb29o1uV7c9ADh37hz69OkDNzc3tfelF59EtOZbRR2qYW2r1NRULUdCL6qUlBT4+vpqdULERYsWITU1FQ8ePNBaDOqSSCRITk7GrFmz2v1Y169fx5AhQ5CUlAR/f/92P56m1dfXY+zYsQgICMCCBQu0HU6bPHjwAHZ2doiIiJAnmh2hI79v1CapvHNFRJ2GOgO2uxtnZ2eEh4cjPDxcYQHjrqCurg5paWkoLS2Fn5+ftsNps82bN8Pd3R1BQUHaDoU6KSZXRERdRFhYGGbOnAk/P78utThzRkYGDh48iPT0dJXn6uqsYmNjceHCBRw/fhx6enraDoc6KSZXpJL58+dDKpVCIpF0qXldDh48CEdHR6UBqlKpFA4ODliwYAFycnI0dryuep20be3atUhKSsLjx4/h4OCAAwcOaDukTmvbtm0ICgrC9u3btR2KyiZMmIDPP/9cYU3Irujw4cN48uQJMjIyYGFhoe1wqBNjckUqSUpKwqpVq7Qdhtp8fHxw48YNODk5wczMDEII1NXV4ebNmwgPD0dycjJGjRqlsXE+XfU6aVtkZCSePHkCIQRycnIwY8YMbYfUqU2cOBFRUVHaDqPbmTp1KsLCwpTeviR6HpMr6nZ0dHRgbW2NefPmYenSpSgsLMSpU6e0HRYREb0gmFyR2iQSibZD0BhnZ2cAT2dv1rQX6ToREZHqmFy9gGJiYmBkZASZTIbCwkKsXLkSffr0wbVr11BXV4eNGzfC3t4ehoaGcHNzQ3Jysnzff/7zn/j9738PIyMjmJqawtXVFSUlJfLtOjo6OHbsGCZNmgQzMzPY2tri448/Vjj+d999BxcXF5iZmUEqlcLV1RUnT54EACQkJEAqlcLa2hqLFi2Cra0tpFIpvLy8lBaLbSnWEydOtHlCyIY5eoYPH67WsbvSdSIioo7F5OoFtHr1aoSEhKCsrAyRkZFwcHDAqFGjIITAmjVrEBMTg7i4ONy9exeTJ0/GnDlz8NNPP6G8vBxTpkzBjBkz8PDhQ2RlZWHgwIHyNbSAp3PVmJubY//+/cjNzcWIESOwZMkShcVZCwoK4Ovri9zcXNy5cwcmJiaYO3cuACAoKAgBAQGoqKjA8uXLkZubi19++QW1tbX405/+JJ8AEkCzsQK/vbZfX1+v9jUqLi7GP/7xD+zatQve3t4YO3aswvYX6ToREVEHE9TpzZgxQ8yYMUOtfdatWycAiMrKSnlZZWWlMDIyEn5+fvKyiooKYWBgIJYsWSIuX74sAIijR4+q3Oann34qAIjLly83GUtkZKQAIAoLC4UQQgQGBgozMzOFOufOnRMAxJYtW1SKVV1OTk4CgMJHIpGIiIgIUV1drVC3O16n5ORkwX8O1AdAJCcnazsM6ib4fesyUnjnqhu5du0aKioqMGzYMHmZoaEhbGxscPXqVTg6OsLa2hr+/v7YvHkzcnNzW2yzYZ6X5hbSbajT3ASRI0eOhJGREa5evapSrK3R8LagEALvvPMOhBAwMzNTmqumO1+n56es4Kf5D/B0oWFtx8FP9/hQ16Gr7QCo45SXlwMA1q9fj/Xr1ytss7W1haGhIU6fPo01a9Zg27ZtCA8Px6xZs5CUlCRfu00Vx44dw7vvvovMzEyUlJQ0m1A8y8DAAEVFRSrF2lYbNmzAZ599hrVr12Lq1Kno27evfFt3vk4cq6UeX19fBAcHw9PTU9uhUDfg6+ur7RBIRUyuuhErKysAQFxcHIKDgxutM3ToUHz55ZcoKipCbGwsoqKiMHToUGzYsEGlY9y8eRPTp0/HG2+8gY8//hi9e/fGe++9h9WrVze7X01NDYqLi2FnZ6dyrG0hk8kQFRWFgIAALFmyBF9++aV8W3e+TlyzTD2+vr7w9PTkdaMOweSq6+BjwW6kb9++kEqluHDhQqPb79y5gytXrgB4+qO9fft2jBgxQl6mikuXLqGmpgZLliyBo6OjfLbylmRkZEAIgVGjRqkUqya8+eabeOWVV3D06FGkpKTIy3mdiIioLZhcdSNSqRTz58/Hvn37kJiYiJKSEtTV1SE/Px93797FnTt3sGjRIly9ehXV1dU4f/488vLy5D/kqrC3twcAnDp1ClVVVcjKylKaOgB4+jbdo0ePUFtbi4sXLyI4OBj29vYICAhQKVYASE9Pb9NUDBKJBAkJCZBIJAgKCsKjR49eyOtEREQdTKvj6Ukl6r4tGB0dLQwNDQUA0bdvX/HZZ5/Jtz158kSEhoYKe3t7oaurK6ysrISPj4/IzMwUubm5wsvLS1hYWIgePXqI3r17i3Xr1ona2lqFNgcMGCCys7PFnj17hIWFhQAg7Ozs5G/ChYaGCktLS2Fubi5mzpwpdu7cKQAIJycncfPmTREYGCj09PREnz59hK6urjA1NRXTpk0T2dnZCufRXKxCCHH8+HEhk8lEREREk9fiX//6lxg4cKD8DcHevXuLRYsWKdQJCAgQAIS5ubnYvn37C3edVMG3BVsHfHuLOhC/b11GikQIIbSS1ZHKZs6cCQBITU3VciSasWjRIqSmpmpsPb8XVUdep5SUFPj6+oL/HKhHIpEgOTmZY66oQ/D71mWk8rEgaUVz0w3Qb3idiIi6HiZXRERacOrUKYSFheHgwYNwdHSUz2U0b948pboTJ06ETCZDjx49MHToUPzyyy9aiFh1Y8eObXKuJhMTE62316C+vh5xcXHw8vJqdHt4eDhcXFxgamoKAwMDODs7Y/Xq1SgrK1Oqu3fvXnh4eEAmk6Ffv36YP3++wpqlR44cQXR0NP+HqZtgckUdau3atUhKSsLjx4/h4OCAAwcOaDukTonX6cW2adMmJCQkYO3atfDx8cGNGzfg5OSEl156CXv27MGxY8cU6n/11VdITU3F5MmTkZmZiREjRmgp8rZ79dVXO0V7WVlZ+OMf/4iQkBCFZamedfr0aSxduhS5ubm4f/8+IiMjER8fLx+q0SA5ORlz587FzJkzkZ+fj8OHD+Pbb7/FpEmTUFtbCwCYMmUKpFIpJkyYgOLi4lbFTF0HkyvqUJGRkXjy5AmEEMjJycGMGTO0HVKn1B2vU2VlZZN3ELrSMVoSFRWF/fv3IyUlBTKZTGFbQkICdHR0EBgYiMePH2spwraTSqUoKSmRr4jQ8AkMDGxxLreOaO/XX3/FmjVrsHjxYri7uzdZz8TEBIGBgbC0tIRMJsOsWbMwffp0nDhxQmF9z7///e/o3bs33nnnHZiZmcHd3R0hISG4cOGCwlvAy5cvx/Dhw/H666/Lky56MTG5IqJO4aOPPkJhYWGXP0Zzrl+/jg0bNmDLli2QSqVK2728vBAcHIzbt29j1apVWohQM06cOKGUON66dQuXL1/G+PHjtd7e8OHDcfDgQcydOxcGBgZN1jt69Ch69OihUNazZ08AULjbdevWLdja2irMVdew6kNeXp7C/ps3b8aFCxcQHx+vdtzUdTC5IqJWEUIgNjYWQ4YMgYGBASwsLDBt2jSFNQ2DgoKgr68PGxsbednbb78NY2NjSCQS3L9/HwAQHByMlStXIjs7GxKJBM7OzkhISIBUKoW1tTUWLVoEW1tbSKVSeHl5KdwNaMsxgKc/3G2ZL00dCQkJEEJgypQpTdaJiIjAwIED8eGHH+LUqVPNtqdKHyQmJsLY2BhGRkY4fPgwJk2aBFNTU9jZ2WHfvn0K7dXV1WHjxo2wt7eHoaEh3NzcNLYkUlRUFJYvX66RttqjPVXdvn0bhoaGcHBwkJc5OjoqJe0N460cHR0Vyi0sLDBmzBjEx8fz7dwXWYfP/kBqU3eeKyJ1tWaeq40bNwp9fX3x2WefieLiYnHx4kUxYsQI0bNnT3Hv3j15vblz54pevXop7Pvuu+8KAKKoqEhe5uPjI5ycnBTqBQYGCmNjY3HlyhVRVVUlMjMzhYeHh5DJZOLmzZsaOcbRo0eFTCYT4eHhap2/EOrPO+To6ChcXFwa3ebk5CRycnKEEEL88MMPQkdHR/Tv31+UlZUJIYRIT08XU6dOVdhH1T5Yt26dACC+/vpr8fjxY1FYWChGjx4tjI2NRXV1tbzeqlWrhIGBgThw4IB49OiRWLt2rdDR0RHnzp1T+Rwbk5+fL1xcXERdXV2b2mmP9l555RUxfPhwleqWl5cLmUwmgoKCFMozMjKEnp6eSEhIECUlJeLy5ctiyJAh4s9//nOj7YSFhQkA4vz582rFqu73jbQmhXeuiEhtlZWViI2NxRtvvAF/f3+YmZnB1dUV77//Pu7fv48PPvhAY8fS1dWV35lxcXFBYmIiSktLkZSUpJH2vb29UVJSovK6kK1VXl6OnJwcODk5tVjX09MTK1asQG5uLtasWdNondb0gZeXF0xNTWFlZQU/Pz+Ul5fj5s2bAICqqiokJiZi+vTp8PHxgbm5OdavXw89Pb02X+uoqCgsW7YMOjqa+cnRdHuqioyMhK2tLSIiIhTKx4wZg9DQUAQFBcHU1BTDhg1DaWkpPvzww0bbGTBgAICny2DRi4nJFRGpLTMzE2VlZRg5cqRCuYeHB/T19RtdykdTRo4cCSMjI4VHX11BYWEhhBAwMjJSqX5ERAQGDRqEXbt24fvvv1fa3tY+0NfXB/B0MXAAuHbtGioqKjBs2DB5HUNDQ9jY2LTpWt+5cwdHjhyRL9nUVppuT1WHDh1CSkoKTp48qTT+a926dfjggw/w9ddfo6ysDDdu3ICXlxc8PT0VBr43aPgOFBQUdEjs1PGYXBGR2hpeJW9sjiFzc3OUlpa26/ENDAxQVFTUrsfQtKqqKgBodgD1s6RSKZKSkiCRSLBgwQJUVlYqbNd0H5SXlwMA1q9frzCPVF5eXpNTFagiOjoaCxcubHQAf2doTxX79+9HVFQUMjIy0L9/f4Vtd+/eRXR0NP7nf/4H48ePh7GxMRwcHLB7927cuXMH7777rlJ7hoaGAH77TtCLR1fbARBR12Nubg4Ajf6AFxcXw87Ort2OXVNT0+7HaA8NP6jqTCLp6emJkJAQ7NixA1u3bpUv+A1ovg+srKwAAHFxcQgODlZr36bcu3cPe/fuxbVr1zple6p47733cPLkSZw+fbrRRDYrKwt1dXXo3bu3QrmpqSksLS2RmZmptE91dTWA374T9OLhnSsiUtuwYcNgYmKCn376SaH87NmzqK6uxssvvywv09XVlT960oSMjAwIITBq1Kh2O0Z7sLa2hkQiUXv+qq1bt2Lw4ME4f/68Qrk6faCKvn37QiqV4sKFC2rt15zo6Gj4+/vD0tKyU7bXHCEEQkNDcenSJaSlpTU5E3xDEnv37l2F8tLSUjx8+FA+JcOzGr4DvXr10nDU1FkwuSIitUmlUqxcuRKHDh3Cnj17UFJSgkuXLmHx4sWwtbVFYGCgvK6zszMePnyItLQ01NTUoKioSGnuHwCwtLTEnTt3kJubi9LSUnmyVF9fj0ePHqG2thYXL15EcHAw7O3tFcbctOUY6enpHTIVg5GRERwdHZGfn6/Wfg2PB5+fb0mdPlD1OPPnz8e+ffuQmJiIkpIS1NXVIT8/X544+Pn5oVevXiotv1NQUICPP/4YK1asaLKONttryZUrVxATE4Pdu3dDT09PadmdHTt2AAAcHBwwbtw47N69G99++y0qKytx69Yt+fX/61//qtR2w3fA1dW1zXFS58TkiohaZdOmTYiMjER4eDh69uyJMWPGoH///sjIyICxsbG83pIlSzBu3DjMnj0bgwYNwtatW+WPQ54d8Lt48WJYW1vDxcUFr7/+Oh4+fAjg6bgUV1dXGBoaYvTo0Rg4cCC++eYbhbFLbT1GR/H29kZmZqbC+KkvvvgCzs7OyM7OhoeHB5YtW6a036hRoxASEqJUrkofJCYmIi4uDgDg5uaGGzduYPfu3Vi5ciUA4LXXXkNWVhYAID4+HitWrEB0dDReeukl2NraIjg4GI8ePQLw9HFWYWEhDh8+3OK5xsTEYMqUKQqPMp+nrfZ+/PFHvPrqq+jduzfOnj2LX3/9Fba2tvjDH/6Ab7/9FgBUnoNKIpEgNTUVfn5++Otf/woLCwu4uLjg5s2bOHjwIEaPHq20z7lz59CnTx+4ubmpdAzqgrQ7FQSpgvNcUXtrzTxXHSEwMFBYWlpqO4wmQc15h7KysoSurq747LPP2jGq9lNXVydGjx4tPvroo27RXnu4f/++kEqlYseOHWrvq+73jbSG81wRUeemzgDwzs7Z2Rnh4XfAgB0AACAASURBVOEIDw9HWVmZtsNRS11dHdLS0lBaWgo/P78Xvr32snnzZri7uyMoKEjboVA7YnJFRNSBwsLCMHPmTPj5+XWpxZkzMjJw8OBBpKenqzxXV1durz3ExsbiwoULOH78OPT09LQdDrUjJldE1CmtXbsWSUlJePz4MRwcHHDgwAFth6Qx27ZtQ1BQELZv367tUFQ2YcIEfP755wprOL7I7Wna4cOH8eTJE2RkZMDCwkLb4VA74zxXRNQpRUZGIjIyUtthtJuJEydi4sSJ2g6DOsjUqVMxdepUbYdBHYR3roiIiIg0iMkVERERkQYxuSIiIiLSICZXRERERBrEAe1dRH5+PlJSUrQdBr2gzpw5AwD8jrVCw7UjImogEULFOf5Ja2bOnPlCvYZOREStk5ycjFmzZmk7DGpeKpMrIur0UlJS4Ovrq/J6b0REWpTKMVdEREREGsTkioiIiEiDmFwRERERaRCTKyIiIiINYnJFREREpEFMroiIiIg0iMkVERERkQYxuSIiIiLSICZXRERERBrE5IqIiIhIg5hcEREREWkQkysiIiIiDWJyRURERKRBTK6IiIiINIjJFREREZEGMbkiIiIi0iAmV0REREQaxOSKiIiISIOYXBERERFpEJMrIiIiIg1ickVERESkQUyuiIiIiDSIyRURERGRBjG5IiIiItIgJldEREREGsTkioiIiEiDmFwRERERaRCTKyIiIiINYnJFREREpEFMroiIiIg0iMkVERERkQYxuSIiIiLSICZXRERERBqkq+0AiIielZ+fj7feegt1dXXyskePHkEmk2Hs2LEKdQcNGoS///3vHRwhEVHzmFwRUadiZ2eHvLw8ZGdnK2375z//qfDff/zjHzsqLCIilfGxIBF1Om+++Sb09PRarOfn59cB0RARqYfJFRF1OnPnzkVtbW2zdYYOHQoXF5cOioiISHVMroio03FycoKbmxskEkmj2/X09PDWW291cFRERKphckVEndKbb76JHj16NLqttrYWM2fO7OCIiIhUw+SKiDql2bNno76+XqlcR0cHo0aNQv/+/Ts+KCIiFTC5IqJOydbWFn/4wx+go6P4z5SOjg7efPNNLUVFRNQyJldE1GnNmzdPqUwIgTfeeEML0RARqYbJFRF1WjNmzFAYd9WjRw/813/9F6ytrbUYFRFR85hcEVGnZWFhgT/96U/yBEsIAX9/fy1HRUTUPCZXRNSp+fv7ywe26+npYdq0aVqOiIioeUyuiKhTmzJlCgwMDAAAkydPhomJiZYjIiJqHpMrIurUjI2N5Xer+EiQiLoCiRBCtGbHlJQU+Pr6ajoeIiIiIq1rZXoEAKm6bT14cnJyW5sgImpWXV0dkpOTMWfOnA4/dlxcHABgxYoVHX7srurMmTOIj4/n7wN1SQ3f37Zoc3I1a9astjZBRNSi6dOnQyqVdvhxU1NTAfDfOnXFx8fzmlGX1dbkimOuiKhL0EZiRUTUGkyuiIiIiDSIyRURERGRBjG5IiIiItIgJldEREREGsTkioioAxw/fhxmZmb48ssvtR3KC+PUqVMICwvDwYMH4ejoCIlEAolEgnnz5inVnThxImQyGXr06IGhQ4fil19+0ULEqhs7dqz8fJ7/tGaVAk2316C+vh5xcXHw8vJqdHt4eDhcXFxgamoKAwMDODs7Y/Xq1SgrK1Oqu3fvXnh4eEAmk6Ffv36YP38+7t27J99+5MgRREdHo66urtXxdhQmV0REHaANExJSIzZt2oSEhASsXbsWPj4+uHHjBpycnPDSSy9hz549OHbsmEL9r776CqmpqZg8eTIyMzMxYsQILUXedq+++mqnaC8rKwt//OMfERISgoqKikbrnD59GkuXLkVubi7u37+PyMhIxMfHY+bMmQr1kpOTMXfuXMycORP5+fk4fPgwvv32W0yaNAm1tbUAni6FJZVKMWHCBBQXF7cq5o7C5IqIqAN4e3vj8ePHmDx5srZDQWVlZZN3GrqCqKgo7N+/HykpKZDJZArbEhISoKOjg8DAQDx+/FhLEbadVCpFSUkJhBAKn8DAQKxevVrr7f36669Ys2YNFi9eDHd39ybrmZiYIDAwEJaWlpDJZJg1axamT5+OEydO4NatW/J6f//739G7d2+88847MDMzg7u7O0JCQnDhwgWcPXtWXm/58uUYPnw4Xn/9dXnS1RkxuSIi6mY++ugjFBYWajuMVrl+/To2bNiALVu2NDr3mZeXF4KDg3H79m2sWrVKCxFqxokTJ5QSx1u3buHy5csYP3681tsbPnw4Dh48iLlz58oXVm/M0aNH/z97dxoW1ZHuAfx/kKW7gWZRUVAIm0sIoCaSKEqIZuJG3DdcMlfjgktElhgE1CgiijrAoDBGdMgdnSggBo1xyVXDMK6TRFHEG0UUQUQRAbvZBNq6H7zdoW3AbuimAd/f8/hh6tSpes8y6Zdz6lShS5cucmXdunUDALmnXQUFBbC0tATHcbIya2trAMD9+/fl9l+/fj0yMzNbPdGnJlFyRQghGnbu3DnY2NiA4zjs3LkTABAfHw9DQ0MIBAIcOXIEY8eOhVAoRO/evXHgwAHZvrGxseDxeLCwsMCSJUtgaWkJHo8Hd3d3ub/ofX19oa+vj549e8rKli9fDkNDQ3Ach5KSEgCAn58fAgMDkZubC47j4OjoCODlj69QKMSmTZva4pS0WGxsLBhjmDBhQpN1wsPD0bdvX+zZswenT59utj3GGKKiovD222/DwMAAZmZmmDRpEn7//XdZHWWvFfByqaZ169bBxsYGfD4frq6ualsGaMuWLVi5cqVa2tJEe8oqLCwEn8+HnZ2drMze3l4h4ZeOt7K3t5crNzMzg6enJ2JiYtrv63bWQklJSawVuxNCSIcwbdo0Nm3atFa3U1BQwACwHTt2yMpCQ0MZAHbmzBn27NkzVlxczDw8PJihoSGrra2V1fPx8WGGhobs5s2brKamhmVnZzM3NzdmbGzM8vPzZfXmzJnDevToIdfvtm3bGAD25MkTWdnUqVOZg4ODXL1jx44xY2NjFhYW1upj1eTvg729PXNycmp0m4ODA7t37x5jjLELFy4wHR0dZmtryyoqKhhjjJ04cYJNnDhRbp9169YxfX19tm/fPlZeXs6uX7/O3n33XdatWzf26NEjWT1lr9WXX37JDAwM2KFDh1hZWRkLCQlhOjo67JdffmnVcT948IA5OTkxiUTSqnY00d4HH3zABgwYoFTdyspKZmxszHx9feXK09PTmZ6eHouNjWUikYjduHGDvf3222z06NGNthMcHMwAsKtXr7Y6/lep4f5NpidXhBCiZe7u7hAKhejevTu8vb1RWVmJ/Px8uTq6urqypytOTk6Ij4+HWCxGYmKiWmLw8vKCSCTC2rVr1dKeJlRWVuLevXtwcHB4bd2hQ4fC398feXl5WL16daN1qqurERUVhSlTpmDu3LkwMTGBi4sLdu3ahZKSEuzevVthn+auVU1NDeLj4zF58mRMnToVpqamWLNmDfT09Fp9nbZs2YIVK1ZAR0c9P9vqbk9ZERERsLS0RHh4uFy5p6cngoKC4OvrC6FQCGdnZ4jFYuzZs6fRdvr06QMAyMrK0njMLUHJFSGEtCP6+voAgLq6umbrDR48GAKBQO71VWdXXFwMxhgEAoFS9cPDw9GvXz/ExcXh3LlzCtuzs7NRUVGBwYMHy5W7ublBX19f7rVrY169Vrdu3UJVVRWcnZ1ldfh8Pnr27Nmq6/Tw4UMcPXoU8+bNa3EbmmxPWYcPH0ZycjJOnTqlMP4rNDQUu3fvxpkzZ1BRUYG7d+/C3d0dQ4cOlRv4LiW9Bx4/ftwmsauKkitCCOmgDAwM8OTJE22H0WZqamoAoNkB1A3xeDwkJiaC4zh8/vnnqK6ultsu/Zy/sXmeTE1NIRaLVYqvsrISALBmzRq5eaTu37/f5FQFyoiMjMSiRYvUtni5uttTxsGDB7Flyxakp6fD1tZWbltRUREiIyOxePFijBw5EoaGhrCzs0NCQgIePnyIbdu2KbTH5/MB/HFPtDe62g6AEEKI6urq6lBeXo7evXtrO5Q2I/1BVWUSyaFDhyIgIADbt2/Hxo0bYWNjI9tmamoKAI0mUS05t927dwcAREdHw8/PT6V9m/Lo0SN89913uHXrVrtsTxk7duzAqVOncPbs2UYT2ZycHEgkElhZWcmVC4VCmJubIzs7W2Gf2tpaAH/cE+0NPbkihJAOKD09HYwxDBkyRFamq6v72teJHZmFhQU4jlN5/qqNGzeif//+uHr1qly5s7MzjIyM8Ouvv8qVX758GbW1tXjvvfdU6sfa2ho8Hg+ZmZkq7decyMhIzJ07F+bm5u2yveYwxhAUFISsrCykpaU1ORO8NIktKiqSKxeLxSgtLZVNydCQ9B7o0aOHmqNWD0quCCGkA3jx4gXKyspQX1+P69evw8/PDzY2NnLjZhwdHVFaWoq0tDTU1dXhyZMnCnMEAYC5uTkePnyIvLw8iMVi1NXV4cSJE+1+KgaBQAB7e3s8ePBApf2krwdfnW+Jx+MhMDAQhw8fxv79+yESiZCVlYWlS5fC0tISPj4+Kvczf/58HDhwAPHx8RCJRJBIJHjw4IEscfD29kaPHj2UWn7n8ePH+Pvf/w5/f/8m62izvde5efMmtm7dioSEBOjp6Sksu7N9+3YAgJ2dHUaMGIGEhARkZGSguroaBQUFsvO/YMEChbal94CLi0ur49QESq4IIUTDdu7cCTc3NwBAUFAQJk6ciPj4eERHRwMAXF1dcffuXSQkJCAwMBAAMGbMGOTk5MjaqKmpgYuLC/h8Pjw8PNC3b1/8/PPPcuOPli1bhhEjRmDWrFno168fNm7cKHtt0nBg8NKlS2FhYQEnJyeMGzcOpaWlbXIe1MHLywvZ2dly46e+//57ODo6Ijc3F25ublixYoXCfkOGDEFAQIBC+ddff42IiAiEhYWhW7du8PT0hK2tLdLT02FoaAgAKl2rmJgY+Pv7IzIyEl27doWlpSX8/PxQVlYG4OXrrOLiYhw5cuS1x7p161ZMmDBB7lXmq7TV3qVLlzB8+HBYWVnh8uXLuHbtGiwtLTFs2DBkZGQAUH7JJ47jkJKSAm9vbyxYsABmZmZwcnJCfn4+UlNT4eHhobDPL7/8gl69esHV1VWpPtqcFueBIISQdk9d81y1ho+PDzM3N9dqDKrQ5O9DTk4O09XVZfv27dNI+5omkUiYh4cH27t37xvRniaUlJQwHo/Htm/frpH2aZ4rQgh5Q6gyiLszc3R0RFhYGMLCwlBRUaHtcFQikUiQlpYGsVgMb2/vTt+epqxfvx4DBw6Er6+vtkNpEiVXAMLCwuDk5AShUAgDAwM4Ojriq6++eu3/cRcuXAhjY2NwHKfWAYxEdbdu3cKKFSvwzjvvwNjYGLq6ujAxMUHfvn3h5eWFixcvajtEpe6z1NRU2NvbK4xN0NfXh4WFBT766CNs27ZN9opBytvbW2Gfpv4dO3asrQ+dELUKDg7G9OnT4e3t3aEWZ05PT0dqaipOnDih9FxdHbk9TYiKikJmZiaOHz8OPT09bYfTNC0+Nms3PD09WVxcHHv69CkTiUQsKSmJ6enpsTFjxrx23wMHDmhsCn6inD179jA9PT324YcfspMnT7KysjJWU1PDcnNz2cGDB5m7uzv75ptvtB2mSveZg4MDMzExYYwx9uLFC1ZWVsZ+/vlnNm/ePMZxHLO0tJRbTmPmzJnsp59+YuXl5ayuro4VFRUxAGzChAmstraWVVZWsuLiYrZo0SL2ww8/tNkxdwbafi0YHBzM9PX1GQBma2vLUlJStBaLstrq9+HUqVMsKChI4/2Q9iEtLY1FRESw+vp6jfajjteCNM8VXk4g5+PjI/uSZMaMGUhNTUVycjIKCgoa/QxUHaqrq/Hxxx/jwoULGmn/TXDp0iX4+PjA09MTp06dgq7uH7e0vb097O3tYWpqKjcwWFtaep9xHAdTU1N89NFH+Oijj+Dl5YWZM2fCy8sLt2/fhomJCTiOw7BhwxT+2uQ4Dnp6etDT04NAIFD503KifREREYiIiNB2GO3SqFGjMGrUKG2HQdrIxIkTMXHiRG2HoRR6LQjg2LFjCp/oduvWDQBeO6sux3Et7nfv3r0Kq4AT1YSHh0MikWDz5s1yiVVDo0ePxhdffNHGkSlqzX3W0LRp0zBv3jwUFxdj165dAIADBw4o9Rjfx8cHn376qQpRE0IIUVWbJ1f79u3D4MGDwePxYGhoCFtbW2zcuBHAy882o6KiZIuTmpmZYdKkSXJrMsXHx8PQ0BACgQBHjhzB2LFjIRQK0bt3bxw4cEBW7+233wbHcdDR0cF7770n+/H66quvYGJiAh6Ph2+//bbJOAsLC8Hn82FnZycrY4xh27Zt6NevHwwMDGBiYoJVq1a16Dz4+fkhMDAQubm54DgOjo6O2Lp1KwQCAYyNjVFcXIzAwED06tULt27dwr///W84OTnJYndxccGpU6dUOicA8K9//Qvvv/8+BAIBhEIhXFxcIBKJEBsbCx6PBwsLCyxZsgSWlpbg8Xhwd3dXWF9LmevUXF/Ay4GT69atg42NDfh8PlxdXZGUlCTb9+TJk6+dc6e2thZnzpxB165d8f777yt97tv7faYM6dxGJ06cUGk/AHSfNbjPCCFEI9rynWR0dDQDwDZv3syePn3KSktL2TfffMPmzJnDGGNs3bp1TF9fn+3bt4+Vl5ez69evs3fffZd169aNPXr0SNZOaGgoA8DOnDnDnj17xoqLi5mHhwczNDRktbW1jDHG6uvrma2tLbOxsVF4P+vv78+io6ObjLOyspIZGxszX19fufLQ0FDGcRz7y1/+wsrKylhVVRWLi4tr8ZirqVOnMgcHB4U+ALCVK1eyHTt2sClTprD//d//ZSkpKWz9+vWstLSUPX36lA0ZMoR17dpVpXNSUVHBhEIhi4yMZNXV1ezRo0dsypQp7MmTJ4yxl597Gxoasps3b7KamhqWnZ3N3NzcmLGxMcvPz5f1pcx1el1fX375JTMwMGCHDh1iZWVlLCQkhOno6MjGER07dowZGxuzsLCwJs/f7du3GQA2ZMgQlc57e7/PGJMfc9UYkUjEADBra+tGt0vHXE2cOLHR7XSf/TFe7XW0PeaqI+pMY3LJm0cdY67aLLmqra1lpqambMSIEXLl9fX1LCYmhlVVVTEjIyPm7e0tt/0///kPAyD3Iyv9D3x1dbWsTJrk3LlzR1YmTeaSk5NlZZWVlczGxoY9e/asyVhDQ0NZ3759mUgkkpVVVVUxgUDAPvnkE7m6rRnQ3lxy1fDYGhMREcEAsOLi4ib3e/Wc3LhxgwFgx44da7RNHx8fhR/0X375hQFgGzZsYIwxpa9Tc31VV1czgUAg10ZVVRUzMDBgy5Yta/a4G/r1118ZAPanP/1J6X3a+30m9brkijHGOI5jpqamjW5TNrmi++z1KLlSHSVXpCPrUAPar1+/jvLycowePVquvEuXLli5ciV+/fVXVFRUYPDgwXLb3dzcoK+vr/DK4FX6+voAILeu1sKFC7F+/XrExMRg+vTpAID9+/dj0qRJEAqFjbZz+PBhJCcn46effoKxsbGs/M6dO6iqqsLHH3+s/EFrkPQT1Obmvnn1nNjb28PCwgJz587FypUrMW/ePIXVyV81ePBgCAQC2auY7Oxspa5Tc33dunULVVVVcHZ2lu3P5/PRs2dPhVc+zZGuU6XKeCVl42+Kpu8zZVVWVoIx1mT76kL32UsPHjxAcnKySvu8yaRTn9A5Ix2ROqbuabPkSjoGQroK+avKy8sBoNGFHU1NTRtdtfx1jIyMsHjxYmzbtg3/+c9/8P777+Nvf/sbDh061Gj9gwcPIioqCunp6Qqrc0vXMZKuet7WfvzxR2zbtg3Z2dkQiUQtWpyVz+fj7NmzWL16NTZt2oSwsDDMmDEDiYmJza4sbmBggCdPngBQ/jo111dlZSUAYM2aNVizZo1cG5aWlkofj62tLXg8Hm7fvq30Pu39PlOW9Jj79+/fov2bQvdZ4y5duoSZM2eqtA8BnTPyxmqzAe3SH5GSkpJGt0uTrsZ+3MrLy2WrZqvK19cXenp6iI6ORkZGBqytreHg4KBQb8eOHdi/fz/Onj3b6A8ej8cDADx//rxFcbRGfn4+Jk+ejJ49e+Ly5ct49uwZIiMjW9TWO++8gx9++AEPHz5EUFAQkpKSZItnNqaurk7u/KtynZrqS5qgRkdHgzEm90+VvxgMDAwwevRolJSU4Pz5803WKy0txcKFC1WOXxXqus+UdfLkSQDA2LFjW9zGq+g+a9q0adMU2qB/Tf+TfjSg7TjoH/1ryT91fPTSZsmVra0tzM3N8dNPPzW63dnZGUZGRvj111/lyi9fvoza2toWz8/Tu3dvzJgxA4cOHcLatWvh5+cnt50xhqCgIGRlZSEtLa3Rv5Sl8eno6OBf//pXi+JojaysLNTV1WHZsmWwt7cHj8dr0RQQDx8+xM2bNwG8fAK3efNmvPvuu7KyxqSnp4MxhiFDhgBQ/jo115e1tTV4PJ5aZrVfv349DAwMEBAQILeQa0M3btyQTdPQ3u8zZTx69AjR0dHo3bs3Pv/88xa38yq6zwghRD3aLLkyMDBASEgIMjIy4Ovri8LCQrx48QJisRg3b94Ej8dDYGAgDh8+jP3790MkEiErKwtLly6FpaUlfHx8Wtx3YGAg6uvrUVZWhpEjR8ptu3nzJrZu3YqEhATo6ekpLBUi/Wu7e/fumDp1Kg4dOoS9e/dCJBLh+vXr2L17d4vjMjc3x8OHD5GXlwexWNzkKxjpCuanT59GTU0NcnJyXjs2qDEPHz7EkiVL8Pvvv6O2thZXr17F/fv3ZT9oAPDixQuUlZWhvr4e169fh5+fH2xsbGSf/it7nZrri8fjYf78+Thw4ADi4+MhEokgkUjw4MEDFBUVAXg5xcDrpmIAgIEDB+Kf//wnbty4AQ8PDxw/fhzPnj1DXV0d7t27h4SEBCxYsEA2dqi932cNMcZQUVGBFy9egDGGJ0+eICkpCcOGDUOXLl2Qlpam1jFXb+J9RgghGsFaqKWj6Xfu3MlcXFwYj8djPB6PDRo0iMXFxTHGXi7zsW3bNtanTx+mp6fHzMzM2OTJk9mtW7dk+8fFxTGBQMAAsD59+rDc3Fy2e/duJhQKGQD21ltvsdu3byv0O2LECLZnzx6F8qysLAagyX/btm2T1RWLxWzhwoWsa9euzMjIiA0fPpytW7eOAWC9e/dm165dU+lcXLlyhb311luMz+ez4cOHs4CAAMbn82Wf2Ddc9T0oKIiZm5szU1NTNn36dLZz504GgDk4OLDVq1crdU7y8vKYu7s7MzMzY126dGFWVlYsNDRUNoWAj48P09PTY7169WK6urpMKBSySZMmsdzcXLm4lblOr+vr+fPnLCgoiNnY2DBdXV3WvXt3NnXqVJadnc0YY+z48ePM2NiYhYeHK3Uu8/Pz2ZdffslcXFyYkZER69KlCzM1NWWDBg1iCxYsYOfPn1cpfm3dZ0ePHmWurq5MIBAwfX19pqOjwwDIvgx8//33WVhYGHv69Gmj50EkErEPP/yQmZubMwBMR0eHOTo6sk2bNsnqREZG0n32//eZMuhrQdXR14KkI1PH14IcY4y1JClLTk7GzJkz0cLdSTu0ZMkSpKSk4OnTp9oOhXRiHe0+k34BmpKSouVIOg76fSAdmRru3xRa/obIae6Te0LUhe4zQkhnRsmVGv3+++8KY2ka++ft7a3tUAkhhBCiIZRcqVH//v2V+szz4MGD2g5VQUhICBITE/Hs2TPY2dk1OUcTIa1B9xlRxunTpxEcHIzU1FTY29vL/jD97LPPFOqOGjUKxsbG6NKlC9555x1cuXJFCxGr7sWLF4iOjoa7u7tS9WtqatC/f3+FOds6S79hYWFwcnKCUCiEgYEBHB0d8dVXX6GiokKh7nfffQc3NzcYGxvjrbfewvz58/Ho0SPZ9qNHjyIyMlK7T8i1OOCLEELaPRrQrrrW/D6sW7eOjR8/Xm5ZKAcHB9a1a9cmlzo6ceJEk0s9tUe3b99mw4YNYwDYgAEDlNonICCAAWChoaGdsl9PT08WFxfHnj59ykQiEUtKSmJ6enpszJgxcvUOHjzIALDIyEhWXl7Orl69yuzt7dnAgQNZXV2drF5MTAzz9PRkZWVlKserjgHt9OSKEELauerqaqWfNLTnPl5ny5YtOHjwIJKTkxWWhYqNjYWOjg58fHzw7NkzLUXYeteuXcPq1auxdOlSDBw4UKl9Lly4gBs3bnTqfo2MjODj4wNzc3MYGxtjxowZmDx5Mk6ePImCggJZvW+++QZWVlZYtWoVTExMMHDgQAQEBCAzM1Nu6piVK1diwIABGDduHOrr61t1DC1ByRUhhLRze/fuRXFxcYfvozl37tzB2rVrsWHDBtmKGA25u7vDz88PhYWF+PLLL7UQoXoMGDAAqampmDNnDgwMDF5bv7q6GqtWrUJMTEyn7vfYsWPo0qWLXFm3bt0AyK8fW1BQAEtLS7kJjq2trQEA9+/fl9t//fr1yMzMbPUxtAQlV4QQomaMMURFReHtt9+GgYEBzMzMMGnSJLkFo319faGvr4+ePXvKypYvXw5DQ0NwHCdbKszPzw+BgYHIzc0Fx3FwdHREbGwseDweLCwssGTJElhaWoLH48Hd3V3ur/fW9AG8XGZJmcl81SE2NhaMMUyYMKHJOuHh4ejbty/27NmD06dPN9ueMtcgPj4ehoaGEAgEOHLkCMaOHQuhUIjevXvjwIEDcu1JJBKsW7cONjY24PP5cHV1VcsyKa8TGhqK5cuXt/m6ttrqt6HCwkLw+XzY2dnJyuzt7RX+CJCOt7K3t5crNzMzg6enJ2JiYtp8WhBKqI4G5AAAIABJREFUrgghRM3Wr1+P4OBghIaGori4GBkZGSgoKICHhwceP34M4GUyMWPGDLn94uLisGHDBrmymJgYjB8/Hg4ODmCM4c6dO/D19cW8efNQVVWFlStXIi8vD1euXEF9fT0++eQT2WuU1vQB/DFlxosXL9R3cprw448/ol+/fhAIBE3W4fP5+Pbbb6Gjo4NFixbJFudujDLXYNmyZfD390d1dTWMjY2RlJSE3Nxc2NvbY9GiRXKrZqxevRpbt25FdHQ0ioqKMH78eMyePVthiSZ1On/+PHJzczF79myN9dGe+m2oqqoKZ8+exaJFi6Cvry8rDwkJwaNHj7Bjxw6IxWJkZ2cjJiYGo0ePllsFQmrQoEEoLCzEtWvX2jJ8Sq4IIUSdqqurERUVhSlTpmDu3LkwMTGBi4sLdu3ahZKSklYtmfUqXV1d2ZMZJycnxMfHQywWIzExUS3te3l5QSQSYe3atWpprymVlZW4d+9eo4udv2ro0KHw9/dHXl4eVq9e3WidllwDd3d3CIVCdO/eHd7e3qisrER+fj6Al1/MxcfHY/LkyZg6dSpMTU2xZs0a6Onpqe1cN3YMfn5+iI+P10j77a3fV0VERMDS0hLh4eFy5Z6enggKCoKvry+EQiGcnZ0hFouxZ8+eRtvp06cPgJdrp7YlSq4IIUSNsrOzUVFRgcGDB8uVu7m5QV9fv0XrNSpr8ODBEAgEcq++OoLi4mIwxpp9atVQeHg4+vXrh7i4OJw7d05he2uvgfRJifTJ1a1bt1BVVQVnZ2dZHT6fj549e2rsXIeEhGDx4sXo1auXRtpvb/02dPjwYSQnJ+PUqVMKHzaEhoZi9+7dOHPmDCoqKnD37l24u7tj6NChcgPfpaT3lPRpZVuh5IoQQtSovLwcwMuvn15lamoKsVis0f4NDAzw5MkTjfahbjU1NQCg1EBr4OXC3omJieA4Dp9//jmqq6vltqv7GkhfP65Zs0ZuQuj79+/LDbZWl3PnziErKwsLFy5Ue9vtsd+GDh48iC1btiA9PR22trZy24qKihAZGYnFixdj5MiRMDQ0hJ2dHRISEvDw4UNs27ZNoT0+nw/gj3usrVByRQghamRqagoAjf6Al5eXo3fv3hrru66uTuN9aIL0B1CVSR+HDh2KgIAA5OTkYOPGjXLb1H0NpIO6o6OjFSaFvnjxokptKWPv3r04c+YMdHR0ZImcNIZNmzaB4ziNjPXSVr9SO3bswP79+3H27FlYWVkpbM/JyYFEIlHYJhQKYW5ujuzsbIV9amtrAfxxj7UVSq4IIUSNnJ2dYWRkpPAjdPnyZdTW1uK9996Tlenq6soNmm6t9PR0MMbkBvaquw9NsLCwAMdxKs9ftXHjRvTv3x9Xr16VK1flGijD2toaPB4PmZmZKu3XUomJiQpJnPRpZGhoKBhjCq88O3K/jDEEBQUhKysLaWlpjT5xBCBLiouKiuTKxWIxSktLZVMyNCS9p3r06KHmqJtHyRUhhKgRj8dDYGAgDh8+jP3790MkEiErKwtLly6FpaUlfHx8ZHUdHR1RWlqKtLQ01NXV4cmTJwpz9QCAubk5Hj58iLy8PIjFYlmy9OLFC5SVlaG+vh7Xr1+Hn58fbGxsMG/ePLX0ceLEiTaZikEgEMDe3h4PHjxQaT/p68FX50dS5Roo28/8+fNx4MABxMfHQyQSQSKR4MGDB7Ifem9vb/To0aPNl9/pDP3evHkTW7duRUJCAvT09BTW492+fTsAwM7ODiNGjEBCQgIyMjJQXV2NgoIC2fVcsGCBQtvSe8rFxaXVcaqCkitCCFGzr7/+GhEREQgLC0O3bt3g6ekJW1tbpKenw9DQUFZv2bJlGDFiBGbNmoV+/fph48aNstcXDQfoLl26FBYWFnBycsK4ceNQWloK4OU4EhcXF/D5fHh4eKBv3774+eef5cYutbaPtuLl5YXs7Gy58VPff/89HB0dkZubCzc3N6xYsUJhvyFDhiAgIEChXJlrEB8fj+joaACAq6sr7t69i4SEBAQGBgIAxowZg5ycHAAvp6vw9/dHZGQkunbtCktLS/j5+aGsrAzAy9dPxcXFOHLkSLPHeenSJQwfPhxWVla4fPkyrl27BktLSwwbNgwZGRkqn7fO0K+yc1BxHIeUlBR4e3tjwYIFMDMzg5OTE/Lz85GamgoPDw+FfX755Rf06tULrq6uKh9jq7R04RxaW5AQ8iZor2sL+vj4MHNzc22H0aiW/D7k5OQwXV1dtm/fPg1FpVkSiYR5eHiwvXv3Ur/tRElJCePxeGz79u0q7UdrCxJCyBtMlQHg7Z2joyPCwsIQFhaGiooKbYejEolEgrS0NIjFYnh7e1O/7cT69esxcOBA+Pr6tnnflFwRQghpF4KDgzF9+nR4e3t3qMWZ09PTkZqaihMnTig9Vxf1q1lRUVHIzMzE8ePHoaen1+b9U3JFCCEdTEhICBITE/Hs2TPY2dnh0KFD2g5JbTZt2gRfX19s3rxZ26Eo7eOPP8Y///lPuTUcqV/tOXLkCJ4/f4709HSYmZlpJQZdrfRKCCGkxSIiIhAREaHtMDRm1KhRGDVqlLbDIB3UxIkTMXHiRK3GQE+uCCGEEELUiJIrQgghhBA1ouSKEEIIIUSNKLkihBBCCFGjVg9onz59ujriIISQdunSpUsA6L91qpAuOULnjHREqi7D1BiOMSXnnX/FxYsXERUV1eoACCHkdR49eoSrV69i7Nix2g6FEPKGSElJafGuLU6uCCGkrSQnJ2PmzJlKr0FGCCFalEJjrgghhBBC1IiSK0IIIYQQNaLkihBCCCFEjSi5IoQQQghRI0quCCGEEELUiJIrQgghhBA1ouSKEEIIIUSNKLkihBBCCFEjSq4IIYQQQtSIkitCCCGEEDWi5IoQQgghRI0ouSKEEEIIUSNKrgghhBBC1IiSK0IIIYQQNaLkihBCCCFEjSi5IoQQQghRI0quCCGEEELUiJIrQgghhBA1ouSKEEIIIUSNKLkihBBCCFEjSq4IIYQQQtSIkitCCCGEEDWi5IoQQgghRI0ouSKEEEIIUSNKrgghhBBC1IiSK0IIIYQQNaLkihBCCCFEjSi5IoQQQghRI0quCCGEEELUiJIrQgghhBA1ouSKEEIIIUSNKLkihBBCCFEjXW0HQAghDdXV1aGiokKurLKyEgBQVlYmV85xHExNTdssNkIIUQYlV4SQdqW0tBS9evWCRCJR2GZubi73v0eMGIGzZ8+2VWiEEKIUei1ICGlXevTogQ8//BA6Os3/54njOMyaNauNoiKEEOVRckUIaXc+++yz19bp0qULpkyZ0gbREEKIaii5IoS0O1OnToWubtOjFrp06YIxY8aga9eubRgVIYQoh5IrQki7IxQKMXbs2CYTLMYY5s6d28ZREUKIcii5IoS0S3Pnzm10UDsA6Ovr49NPP23jiAghRDmUXBFC2qVPP/0UAoFAoVxPTw+TJ0+GoaGhFqIihJDXo+SKENIu8Xg8TJkyBXp6enLldXV1mDNnjpaiIoSQ16PkihDSbs2ePRt1dXVyZUKhEJ988omWIiKEkNej5IoQ0m796U9/kps4VE9PD7NmzYK+vr4WoyKEkOZRckUIabd0dXUxa9Ys2avBuro6zJ49W8tREUJI8yi5IoS0a7NmzZK9GuzRoweGDx+u5YgIIaR5lFwRQto1d3d39OrVCwDw5z//+bXL4hBCiLZ1yoWbL168iIKCAm2HQQhREzc3NxQWFqJr165ITk7WdjiEEDVxd3dH7969tR2G2nGMMabtINRt+vTpOHTokLbDIIQQQkgzkpKSMGPGDG2HoW4pnfLJFQBMmzYNKSkp2g6DEKKE5ORkzJw5E839rXfo0CFMmzatDaNq/ziO66w/TuQNwHGctkPQGBq8QAjpECixIoR0FJRcEUIIIYSoESVXhBBCCCFqRMkVIYQQQogaUXJFCCGEEKJGlFwRQgghhKgRJVeEkE7j+PHjMDExwQ8//KDtUNq906dPIzg4GKmpqbC3twfHceA4Dp999plC3VGjRsHY2BhdunTBO++8gytXrmghYtW9ePEC0dHRcHd3V6p+TU0N+vfvjzVr1nTKfsPCwuDk5AShUAgDAwM4Ojriq6++QkVFhULd7777Dm5ubjA2NsZbb72F+fPn49GjR7LtR48eRWRkJCQSSati7qwouSKEdBqdcE5kjfj6668RGxuLkJAQTJ06FXfv3oWDgwO6du2K/fv348cff5Sr/9NPPyElJQXjx49HdnY23n33XS1FrrycnBx8+OGHCAgIQFVVlVL7hIaG4tatW52237Nnz+KLL75AXl4eSkpKEBERgZiYGEyfPl2uXlJSEubMmYPp06fjwYMHOHLkCDIyMjB27FjU19cDACZMmAAej4ePP/4Y5eXlrYq9M6LkihDSaXh5eeHZs2cYP368tkNBdXW10k8u2tKWLVtw8OBBJCcnw9jYWG5bbGwsdHR04OPjg2fPnmkpwta7du0aVq9ejaVLl2LgwIFK7XPhwgXcuHGjU/drZGQEHx8fmJubw9jYGDNmzMDkyZNx8uRJuSXjvvnmG1hZWWHVqlUwMTHBwIEDERAQgMzMTFy+fFlWb+XKlRgwYADGjRsnS7rIS5RcEUKIBuzduxfFxcXaDkPOnTt3sHbtWmzYsAE8Hk9hu7u7O/z8/FBYWIgvv/xSCxGqx4ABA5Camoo5c+bAwMDgtfWrq6uxatUqxMTEdOp+jx07hi5dusiVdevWDQDknnYVFBTA0tJSbgZ1a2trAMD9+/fl9l+/fj0yMzNbfQydDSVXhJBO4dy5c7CxsQHHcdi5cycAID4+HoaGhhAIBDhy5AjGjh0LoVCI3r1748CBA7J9Y2NjwePxYGFhgSVLlsDS0hI8Hg/u7u5yf6n7+vpCX18fPXv2lJUtX74choaG4DgOJSUlAAA/Pz8EBgYiNzcXHMfB0dERAHDy5EkIhUJs2rSpLU6JgtjYWDDGMGHChCbrhIeHo2/fvtizZw9Onz7dbHuMMURFReHtt9+GgYEBzMzMMGnSJPz++++yOspeAwCQSCRYt24dbGxswOfz4erqiqSkpNYdtBJCQ0OxfPlydO/eXeN9tYd+GyosLASfz4ednZ2szN7eXuEPA+l4K3t7e7lyMzMzeHp6IiYmhl7LN0DJFSGkUxg+fDguXLggV7Zs2TL4+/ujuroaxsbGSEpKQm5uLuzt7bFo0SLU1dUBeJk0zZs3D1VVVVi5ciXy8vJw5coV1NfX45NPPpG9MomNjVVYxy8uLg4bNmyQK4uJicH48ePh4OAAxhju3LkDALLBvy9evNDIOXidH3/8Ef369YNAIGiyDp/Px7fffgsdHR0sWrQIlZWVTdZdv349goODERoaiuLiYmRkZKCgoAAeHh54/PgxAOWvAQCsXr0aW7duRXR0NIqKijB+/HjMnj0bv/76q/pOwivOnz+P3NxczJ49W2N9tKd+G6qqqsLZs2exaNEi6Ovry8pDQkLw6NEj7NixA2KxGNnZ2YiJicHo0aMxZMgQhXYGDRqEwsJCXLt2rS3Db9couSKEvBHc3d0hFArRvXt3eHt7o7KyEvn5+XJ1dHV1ZU9hnJycEB8fD7FYjMTERLXE4OXlBZFIhLVr16qlPVVUVlbi3r17cHBweG3doUOHwt/fH3l5eVi9enWjdaqrqxEVFYUpU6Zg7ty5MDExgYuLC3bt2oWSkhLs3r1bYZ/mrkFNTQ3i4+MxefJkTJ06FaamplizZg309PTUdv4bOwY/Pz/Ex8drpP321u+rIiIiYGlpifDwcLlyT09PBAUFwdfXF0KhEM7OzhCLxdizZ0+j7fTp0wcAkJWVpfGYOwpKrgghbxzpX+kNn5o0ZvDgwRAIBHKvuTqq4uJiMMaafWrVUHh4OPr164e4uDicO3dOYXt2djYqKiowePBguXI3Nzfo6+vLvU5tzKvX4NatW6iqqoKzs7OsDp/PR8+ePTV2/kNCQrB48WL06tVLI+23t34bOnz4MJKTk3Hq1CmFDxtCQ0Oxe/dunDlzBhUVFbh79y7c3d0xdOhQuYHvUtJ7Svq0klByRQghzTIwMMCTJ0+0HUar1dTUAIBSA60BgMfjITExERzH4fPPP0d1dbXcdunn90ZGRgr7mpqaQiwWqxSf9PXjmjVrZHNucRyH+/fvKz2lgSrOnTuHrKwsLFy4UO1tt8d+Gzp48CC2bNmC9PR02Nraym0rKipCZGQkFi9ejJEjR8LQ0BB2dnZISEjAw4cPsW3bNoX2+Hw+gD/uMULJFSGENKmurg7l5eXo3bu3tkNpNekPoCqTPg4dOhQBAQHIycnBxo0b5baZmpoCQKNJVEvOmXRQd3R0NBhjcv8uXryoUlvK2Lt3L86cOQMdHR1ZIieNYdOmTeA4TiNjvbTVr9SOHTuwf/9+nD17FlZWVgrbc3JyIJFIFLYJhUKYm5sjOztbYZ/a2loAf9xjhJIrQghpUnp6OhhjcoN4dXV1X/s6sT2ysLAAx3Eqz1+1ceNG9O/fH1evXpUrd3Z2hpGRkUIicPnyZdTW1uK9995TqR9ra2vweDxkZmaqtF9LJSYmKiRx0ieUoaGhYIwpvPLsyP0yxhAUFISsrCykpaU1+sQRgCwpLioqkisXi8UoLS2VTcnQkPSe6tGjh5qj7rgouSKEkP/34sULlJWVob6+HtevX4efnx9sbGwwb948WR1HR0eUlpYiLS0NdXV1ePLkicLcPwBgbm6Ohw8fIi8vD2KxGHV1dThx4oTWpmIQCASwt7fHgwcPVNpP+nrw1fmReDweAgMDcfjwYezfvx8ikQhZWVlYunQpLC0t4ePjo3I/8+fPx4EDBxAfHw+RSASJRIIHDx7Ifui9vb3Ro0ePNl9+pzP0e/PmTWzduhUJCQnQ09OTe/XKcRy2b98OALCzs8OIESOQkJCAjIwMVFdXo6CgQHY9FyxYoNC29J5ycXFpdZydBSVXhJBOYefOnXBzcwMABAUFYeLEiYiPj0d0dDQAwNXVFXfv3kVCQgICAwMBAGPGjEFOTo6sjZqaGri4uIDP58PDwwN9+/bFzz//LDdOadmyZRgxYgRmzZqFfv36YePGjbLXIQ0H/C5duhQWFhZwcnLCuHHjUFpa2ibnoTleXl7Izs6WGz/1/fffw9HREbm5uXBzc8OKFSsU9hsyZAgCAgIUyr/++mtEREQgLCwM3bp1g6enJ2xtbZGeng5DQ0MAUOkaxMTEwN/fH5GRkejatSssLS3h5+eHsrIyAC9fPxUXF+PIkSPNHuelS5cwfPhwWFlZ4fLly7h27RosLS0xbNgwZGRkqHzeOkO/ys5BxXEcUlJS4O3tjQULFsDMzAxOTk7Iz89HamoqPDw8FPb55Zdf0KtXL7i6uqp8jJ0W64SmTZvGpk2bpu0wCCFKSkpKYtr+z5GPjw8zNzfXagyqAsCSkpKUrp+Tk8N0dXXZvn37NBiV5kgkEubh4cH27t1L/bYTJSUljMfjse3bt6u8r6r3bweSTE+uCCHk/6ky2LsjcnR0RFhYGMLCwlBRUaHtcFQikUiQlpYGsVgMb29v6redWL9+PQYOHAhfX19th9KuUHIFYPv27bLBnrt27VJLm5s3b4aJiQk4jmuzAZptQRPnqjGRkZHo378/+Hw+DA0N0b9/f6xduxYikUjltlJTU2Fvby8bW9CzZ0/MnTtXA1G/pO5r/2r80n88Hg92dnb4/PPPce/evVa1+bpz8te//hVWVlbgOA46Ojro27evwtIon376KYRCIXR0dNC/f3+cP3++RcdLNCs4OBjTp0+Ht7d3h1qcOT09HampqThx4oTSc3VRv5oVFRWFzMxMHD9+HHp6etoOp33R9rMzTWjJa8GcnBwGgP3tb39TWxwHDhxgANjVq1fV1mZ7oIlz9SovLy+2fft2VlxczMRiMUtOTmZ6enrsk08+aXGbDg4OzMTERI1RNk0T175h/BKJhD1+/Jj94x//YAKBgFlYWLCSkpJWtakMAOyDDz5ocvvPP//MPv74Y5Xj0PZrweDgYKavr88AMFtbW5aSkqK1WFSBVrxWOXXqFAsKClJzRORNkZaWxiIiIlh9fX2L22jN/dvO0WtB0j7p6+vLFjQ1MjLC9OnTMWnSJPzP//yPwifCbyIdHR1YWFjgs88+wxdffIHi4uLXLrJLmhYREYHnz5+DMYZ79+5h2rRp2g5J40aNGoUtW7ZoOwzSQU2cOBHBwcEKX5GSl3S1HQAhjTl8+LBCmXSpiI42VkTTHB0dAfyxaj0hhBDtoidXzZBIJFi3bh1sbGzA5/Ph6uqKpKQk2fZ///vfcHJygomJCXg8HlxcXHDq1Kkm23v8+DFsbW2hq6uLMWPGAAAWLlwoG/fi4OAgm6hv/vz5EAgEMDExwdGjR5WOeevWrRAIBDA2NkZxcTECAwPRq1cv3Lp167XH01K+vr7Q19dHz549ZWXLly+HoaEhOI5DSUlJq/sAXs4cbGpqirfeektWdvLkSY3MG9SRrr30M/YBAwaodAyEEEI0g5KrZqxevRpbt25FdHQ0ioqKMH78eMyePVs2I/Hjx48xc+ZM5OXl4eHDhzAyMsKcOXOabM/c3ByDBw/G4cOHcfLkSQDAnj17MHXqVHTp0gX//ve/MWjQIAAvZ/GdPHky9u/fjwkTJigd81dffYWAgABUVFQgIiICdnZ2GDJkCBhjrz2eloqNjcWMGTPkyuLi4rBhw4ZWtQu8XH6ksLAQO3fuxOnTp7Fjxw7Zgq/AH193vXjxotV9NdQRrn15eTn++7//G3FxcfDy8sJHH32k0jEQQgjREG2P+tIEdQxor66uZgKBgHl7e8vqVFVVMQMDA7Zs2bJG24iIiGAAWHFxMWNMflBzXV0dmzVrFjtx4oTCfqdPn2YAWHh4uKzs2bNnrE+fPi0aLBgaGsoAsOrqallZS46nKY0NaJ8zZw7r0aOHXL1t27YxAOzJkycqH4NUjx49GADWtWtX9te//pXV1ta2uC1lB2+312vv4ODAAMj94ziOhYeHK5wXZY+BBrR3bOi8A4LJG6AT37/JNOaqCbdu3UJVVRWcnZ1lZXw+Hz179sTvv//e6D7ST1FfnStHIpFg9uzZsLKykr0SamjkyJHo27cv/v73vyMkJAQcx+HgwYPw9vZW22DBlhxPe1BQUIDy8nJcvXoVwcHB2L17N86ePQsLCwuN9dmer72JiQnKy8sBvHxKuW3bNpiYmCh8Bt1Rr/f06dO1HUKHEx0djZSUFG2HQQhpgF4LNqGyshIAsGbNGrm5he7fv4+qqioAwI8//oiPPvoI3bt3h4GBAb766qtG2/riiy+Qk5ODXbt24ebNmwrbOY7DkiVLcPfuXZw5cwYA8I9//KPRNZw0eTztkZ6eHrp3745Ro0bh4MGDyM7ORkREhEb77CjXfu3atejZsydCQkJkS66ocgwt1dwrWIlEQvPdEELeePTkqgndu3cH8PKvQj8/P4Xt+fn5mDx5MqZMmYK///3vsLKywo4dOxr9kZ0xYwY+++wzODs7489//jMuXboEXV35Uz9v3jyEhIRgz549sLa2hlAolBu4renj6QgcHR3RpUsXZGdnq73tjIwM/Pbbb/D39+8w197Y2BhbtmzBvHnzsGzZMvzwww+ybeq43g3PiZR0MeKm3Lt3D9bW1i3qDwA9gVERx3Hw9/dXGPNISEfAcZy2Q9AYenLVBGtra/B4vCZn2M7KykJdXR2WLVsGe3t78Hi8Jm+UESNGoFu3bti9ezd+++03hIeHK9QxMzPDzJkzkZaWhu3bt2PRokVtejytpauri7q6OrW09fTpU8yePVuhPCcnBxKJpFU/3k357bffZAvNdqRr/+c//xkffPABjh07huTkZFm5Oq53w3MiNXLkSBQWFuLChQsK9Rlj+Pbbb/HBBx+0uE9CCOkMKLlqAo/Hw/z583HgwAHEx8dDJBJBIpHgwYMHKCoqgo2NDQDg9OnTqKmpQU5ODi5fvtxsmxMmTMC8efOwadMm/Pbbbwrbly5diufPn+PYsWMYP358mx5Pazk6OqK0tBRpaWmoq6vDkydPcP/+/Ra1ZWhoiJ9++glnz56FSCRCXV0drl69iv/6r/+CoaEhAgICZHVPnDjRqqkY6urq8PjxY6Snp8sSiY507TmOQ2xsLDiOg6+vL8rKypQ6BlXPiVR4eDhMTU0xffp0fP/996isrMTz589x7do1zJ49G/X19fjss8+Ujp8QQjolbQ+p1wRVvxb8y1/+IvsqzdDQkE2ZMoUxxtjz589ZUFAQs7GxYbq6uqx79+5s6tSpLDs7mzHGWFBQEDM3N2empqZs+vTpbOfOnQwAc3BwYDExMczMzEy2nEZxcTETiUTM2tqaAWBGRkbsH//4h0IsgwYNYsHBwS0+9sjISMbn8xkAZm1tzfbt2yfb9rrjac25evr0KRsxYgTj8XjMzs6OrVixgq1atYoBYI6Ojiw/P1+l45gwYQKzs7NjRkZGzMDAgDk4ODBvb2+WlZUlV+/48ePM2NhY7mu7Vx0+fLjRL+1e/Xf48GGlz1VbXvvz58+zvn37yuK0srJiS5Yskaszb948BoCZmpqyzZs3v/YYWnJOpO7du8cWLVrE7OzsmL6+PuPz+czJyYmtW7eOVVRUNHNVm0ZfC7YMOu/XVuQN0Inv32SOMcY0n8K1LekXRx1x/IaXlxd27twJOzs7bYdC2tibfO2Tk5Mxc+ZMdML/HGkUx3FISkqiMVekQ+rE928KvRbUsobjlK5fvw4ej/dG/ri+iejaE0JI50TJlZYFBQUhJycHt2/fxvz587Fx40aFOr///rvc5/RN/fP29m5RDJpuv6366GiUufaEaMrp06cRHByM1NRU2Nvby/4/2NiYuVGjRsHY2BhdunTBO++8gytXrmghYtW9ePEC0dHRcHd3V6p+TU2UdtmWAAAgAElEQVQN+vfvjzVr1nTKfsPCwuDk5AShUAgDAwM4Ojriq6++anS91u+++w5ubm4wNjbGW2+9hfnz58utX3r06FFERkYqzO1H/p+W30tqREtmaNeW0NBQpqOjw6ytrdnRo0e1HQ5pQ3Tt/0BjrloGLRyzsm7dOjZ+/HgmEolkZQ4ODqxr164MADt27JjCPidOnGATJ05sVbxt6fbt22zYsGEMABswYIBS+wQEBDAALDQ0tFP26+npyeLi4tjTp0+ZSCRiSUlJTE9Pj40ZM0au3sGDBxkAFhkZycrLy9nVq1eZvb09GzhwIKurq5PVi4mJYZ6enqysrKxFMbf0/u0AkunJlZaFh4dDIpEgPz9f7V8IkvaNrn37Ul1drfSThvbcx+ts2bIFBw8eRHJyMoyNjeW2xcbGQkdHBz4+Pnj27JmWImy9a9euYfXq1Vi6dCkGDhyo1D4XLlzAjRs3OnW/RkZG8PHxgbm5OYyNjTFjxgxMnjwZJ0+elJuI+JtvvoGVlRVWrVoFExMTDBw4EAEBAcjMzJT7MnrlypUYMGAAxo0bh/r6+lYdQ2dDyRUhhADYu3cviouLO3wfzblz5w7Wrl2LDRs2gMfjKWx3d3eHn58fCgsL8eWXX2ohQvUYMGAAUlNTMWfOHBgYGLy2fnV1NVatWoWYmJhO3e+xY8cUltXq1q0bAMit3FBQUABLS0u5+fuk8wu+OsXO+vXrkZmZ2epj6GwouSKEdEiMMURFReHtt9+GgYEBzMzMMGnSJLm1E319faGvr4+ePXvKypYvXw5DQ0NwHIeSkhIAgJ+fHwIDA5GbmwuO4+Do6IjY2FjweDxYWFhgyZIlsLS0BI/Hg7u7u9xf763pAwBOnjzZqrnaVBEbGwvGGCZMmNBknfDwcPTt2xd79uzB6dOnm21PmWsQHx8PQ0NDCAQCHDlyBGPHjoVQKETv3r1x4MABufYkEgnWrVsHGxsb8Pl8uLq6IikpqXUHrYTQ0FAsX75ctrJBW9FWvw0VFhaCz+fLfUxjb2+v8EeAdLyVvb29XLmZmRk8PT0RExNDX/s2QMkVIaRDWr9+PYKDgxEaGori4mJkZGSgoKAAHh4eePz4MYCXycSrn3nHxcVhw4YNcmUxMTEYP348HBwcwBjDnTt34Ovri3nz5qGqqgorV65EXl4erly5gvr6enzyySey1yit6QP4Y7Hv5tZsVJcff/wR/fr1g0AgaLIOn8/Ht99+Cx0dHSxatEi2TmVjlLkGy5Ytg7+/P6qrq2FsbIykpCTk5ubC3t4eixYtkvtqdvXq1di6dSuio6NRVFSE8ePHY/bs2fj111/VdxJecf78eeTm5ja6KoQmaavfhqqqqnD27FksWrQI+vr6svKQkBA8evQIO3bsgFgsRnZ2NmJiYjB69GgMGTJEoZ1BgwahsLAQ165da8vw2zVKrgghHU51dTWioqIwZcoUzJ07FyYmJnBxccGuXbtQUlKC3bt3q60vXV1d2ZMZJycnxMfHQywWIzExUS3te3l5QSQSYe3atWpprymVlZW4d+8eHBwcXlt36NCh8Pf3R15eHlavXt1onZZcA3d3dwiFQnTv3h3e3t6orKxEfn4+gJdfzMXHx2Py5MmYOnUqTE1NsWbNGujp6antXDd2DH5+foiPj9dI++2t31dFRETA0tJSYVkuT09PBAUFwdfXF0KhEM7OzhCLxdizZ0+j7fTp0wfAy6XByEuUXBFCOpzs7GxUVFRg8ODBcuVubm7Q19d/7XJErTF48GAIBAK5V18dQXFxMRhjzT61aig8PBz9+vVDXFwczp07p7C9tddA+qRE+uTq1q1bqKqqgrOzs6wOn89Hz549NXauQ0JCsHjxYvTq1Usj7be3fhs6fPgwkpOTcerUKYUPG0JDQ7F7926cOXMGFRUVuHv3Ltzd3TF06FC5ge9S0ntK+rSSUHJFCOmAysvLAbz8+ulVpqamEIvFGu3fwMAAT5480Wgf6lZTUwMASg20Bl6uT5mYmAiO4/D555+jurpabru6r4H09eOaNWvk5r67f/++3GBrdTl37hyysrKwcOFCtbfdHvtt6ODBg9iyZQvS09Nha2srt62oqAiRkZFYvHgxRo4cCUNDQ9jZ2SEhIQEPHz7Etm3bFNrj8/kA/rjHCCVXhJAOyNTUFAAa/QEvLy9H7969NdZ3XV2dxvvQBOkPoCqTPg4dOhQBAQHIyclRmORW3ddAOqg7OjoajDG5fxcvXlSpLWXs3bsXZ86cgY6OjiyRk8awadMmcBynkbFe2upXaseOHdi/fz/Onj0LKysrhe05OTmQSCQK24RCIczNzZGdna2wT21tLYA/7jFCyRUhpANydnaGkZGRwo/Q5cuXUVtbi/fee09WpqurKzdourXS09PBGJMb2KvuPjTBwsICHMepPH/Vxo0b0b9/f1y9elWuXJVroAxra2vweDxkZmaqtF9LJSYmKiRx0qeRoaGhYIwpvPLsyP0yxhAUFISsrCykpaU1+sQRgCwpLioqkisXi8UoLS2VTcnQkPSe6tGjh5qj7rgouSKEdDg8Hg+BgYE4fPgw9u/fD5FIhKysLCxduhSWlpbw8fGR1XV0dERpaSnS0tJQV1eHJ0+eKMzVAwDm5uZ4+PAh8vLyIBaLZcnSixcvUFZWhvr6ely/fh1+fn6wsbHBvHnz1NLHiRMn2mQqBoFAAHt7ezx48ECl/aSvB1+dH0mVa6BsP/Pnz8eBAwcQHx8PkUgEiUSCBw8eyH7ovb290aNHjzZffqcz9Hvz5k1s3boVCQkJ0NPTU1h6bPv27QAAOzs7jBgxAgkJCcjIyEB1dTUKCgpk13PBggUKbUvvKRcXl1bH2VlQckUI6ZC+/vprREREICwsDN26dYOnpydsbW2Rnp4OQ0NDWb1ly5ZhxIgRmDVrFvr164eNGzfKXl80HKC7dOlSWFhYwMnJCePGjUNpaSmAl+NIXFxcwOfz4eHhgb59++Lnn3+WG7vU2j7aipeXF7Kzs+XGT33//fdwdHREbm4u3NzcsGLFCoX9hgwZgoCAAIVyZa5BfHw8oqOjAQCurq64e/cuEhISEBgYCAAYM2YMcnJyALycrsLf3x+RkZHo2rUrLC0t4efnh7KyMgAvXz8VFxfjyJEjzR7npUuXMHz4cFhZWeHy5cu4du0aLC0tMWzYMGRkZKh83jpDv8rOQcVxHFJSUuDt7Y0FCxbAzMwMTk5OyM/PR2pqKjw8PBT2+eWXX9CrVy+4urqqfIydVtsttdN2OtLagoSQ9ru2oI+PDzM3N9d2GE2Cimuz5eTkMF1dXbZv3z4NRqU5EomEeXh4sL1791K/7URJSQnj8Xhs+/btKu+r6v3bgdDagoQQ0hxVBoC3d46OjggLC0NYWBgqKiq0HY5KJBIJ0tLSIBaL4e3tTf22E+vXr8fAgQPh6+ur7VDaFUquCCHkDRIcHIzp06fD29u7Qy3OnJ6ejtTUVJw4cULpubqoX82KiopCZmYmjh8/Dj09PW2H065QckUIIY0ICQlBYmIinj17Bjs7Oxw6dEjbIanNpk2b4Ovri82bN2s7FKV9/PHH+Oc//ym3hiP1qz1HjhzB8+fPkZ6eDjMzM22H0+7oajsAQghpjyIiIhAREaHtMDRm1KhRGDVqlLbDIB3UxIkTMXHiRG2H0W7RkytCCCGEEDWi5IoQQgghRI0ouSKEEEIIUSNKrgghhBBC1IiSK0IIIYQQNeq0XwseOnQIHMdpOwxCiAro/7OqmzlzJmbOnKntMAghDXCMKbngUAdy8eJF2VpehJCO7+LFi4iJiUFSUpK2QyGEqJG7uzt69+6t7TDULaVTJleEkM4lOTkZM2fOVHrxWUII0aIUGnNFCCGEEKJGlFwRQgghhKgRJVeEEEIIIWpEyRUhhBBCiBpRckUIIYQQokaUXBFCCCGEqBElV4QQQgghakTJFSGEEEKIGlFyRQghhBCiRpRckf9j787joizX/4F/hm1mgBkWFQER2UJFUCtJwIi0c1LjuG+4VJoVaidCMRVRUkQU9QBfVE6JHvseKQXFsDguHTUyyzx2Ehf8pYgbrqACwyrb9fvD70yOAzgDAzND1/v1mj+6n/t57utZYi7nvp/7ZowxxpgWcXLFGGOMMaZFnFwxxhhjjGkRJ1eMMcYYY1rEyRVjjDHGmBZxcsUYY4wxpkWcXDHGGGOMaREnV4wxxhhjWsTJFWOMMcaYFnFyxRhjjDGmRZxcMcYYY4xpESdXjDHGGGNaxMkVY4wxxpgWcXLFGGOMMaZFnFwxxhhjjGkRJ1eMMcYYY1rEyRVjjDHGmBZxcsUYY4wxpkWcXDHGGGOMaREnV4wxxhhjWsTJFWOMMcaYFnFyxRhjjDGmRZxcMcYYY4xpkYmuA2CMsScVFxfjq6++Uir75ZdfAABbtmxRKpdIJJg6dWqHxcYYY+oQEBHpOgjGGJN79OgR7OzsUFFRAWNjYwCA/M+UQCBQ1Kurq8Pbb7+Nzz//XBdhMsZYc3ZztyBjTK8IhUJMnDgRJiYmqKurQ11dHerr61FfX6/477q6OgDAtGnTdBwtY4yp4uSKMaZ3pk2bhtra2hbrWFtbY9iwYR0UEWOMqY+TK8aY3hk6dCi6devW7HZTU1PMmDEDJiY8bJQxpn84uWKM6R0jIyNMnz4dpqamTW6vq6vjgeyMMb3FyRVjTC9NnTpVMbbqaY6OjvD39+/giBhjTD2cXDHG9NJLL72EXr16qZSbmZnh7bffVnpzkDHG9AknV4wxvfXmm2+qdA3W1tZylyBjTK9xcsUY01vTp09X6Rr08PCAj4+PjiJijLFn4+SKMaa3+vTpAy8vL0UXoKmpKWbNmqXjqBhjrGWcXDHG9Npbb72lmKm9vr6euwQZY3qPkyvGmF6bOnUqGhoaAAAvvPACXF1ddRwRY4y1jJMrxphec3Z2xuDBgwEAb7/9to6jYYyxZ1OZ3vjEiRNISEjQRSyMMdakR48eQSAQ4Ntvv8WxY8d0HQ5jjCns3r1bpUzll6vCwkLs2bOnQwJijDF1ODk5oXv37hCJRLoOpVk///wzfv75Z12HYVBu3rzJ3zfMYLX0/Da7MFdTmRhjjOnK5cuX4eHhoeswmjVp0iQA/LdTExkZGZgyZQpfM2aQ5M9vU3jMFWPMIOhzYsUYY0/i5IoxxhhjTIs4uWKMMcYY0yJOrhhjjDHGtIiTK8YYY4wxLeLkijHG9Mj+/fthZWWFb775Rteh6L3Dhw8jMjISmZmZcHNzg0AggEAgwJtvvqlS9/XXX4dEIoGxsTH69euHX3/9VQcRa66xsRGJiYkICAhQq35NTQ369OmDZcuWdcp2Y2Ji4OXlBalUCqFQCA8PDyxatAgVFRUqdb/88kv4+vpCIpGgV69emDVrFu7evavY/vXXXyM+Pl6xAoQ2cXLFGGN6hIh0HYJB+OSTT5CcnIylS5diwoQJuHLlCtzd3dGlSxekpaXhX//6l1L9b7/9Frt378aoUaOQl5eHF154QUeRqy8/Px+vvPIKFixYgKqqKrX2iYqKwsWLFzttu0ePHsVf//pXXLt2Dffv30dcXBySkpIUU6HIpaenY/r06Zg0aRJu3ryJffv24dixYxg5ciTq6+sBAKNHj4ZIJMJrr72G0tLSNsX+NE6uGGNMjwQHB6OsrAyjRo3SdSiorq5W+5eLjrR27Vrs2rULGRkZkEgkStuSk5NhZGSE0NBQlJWV6SjCtjtz5gyWLFmCuXPnYuDAgWrt89NPP+H8+fOdul1LS0uEhobC1tYWEokEkydPxrhx43Dw4EEUFhYq6n322WdwdHTExx9/DCsrKwwcOBALFixAbm4uTp48qaj30UcfYcCAAXjjjTcUSZc2cHLFGGOsSdu2bUNRUZGuw1By+fJlLF++HCtXrmxyxv6AgACEh4fj1q1bWLhwoQ4i1I4BAwYgMzMT06dPh1AofGb96upqfPzxx0hKSurU7WZnZ8PY2FiprGvXrgCg9GtXYWEhHBwcIBAIFGU9e/YEAFy/fl1p/xUrViA3N7fN5/AkTq4YY0xPHD9+HM7OzhAIBNi0aRMAICUlBRYWFjA3N8e+ffswcuRISKVSODk5YefOnYp9k5OTIRKJYGdnhzlz5sDBwQEikQgBAQFK/1IPCwuDmZkZ7O3tFWUffPABLCwsIBAIcP/+fQBAeHg4IiIiUFBQAIFAoJjE9eDBg5BKpVi9enVHXBIVycnJICKMHj262TqxsbHw9PTE1q1bcfjw4RaPR0RISEhA3759IRQKYWNjg7Fjx+K3335T1FH3HgBAQ0MDoqOj4ezsDLFYjP79+yM9Pb1tJ62GqKgofPDBB+jWrVu7t6UP7T7p1q1bEIvFcHV1VZS5ubmp/MNAPt7Kzc1NqdzGxgZBQUFISkrSWrc8J1eMMaYnXn75Zfz0009KZfPmzcP8+fNRXV0NiUSC9PR0FBQUwM3NDe+99x7q6uoAPE6aZs6ciaqqKnz00Ue4du0afv31V9TX1+PPf/6zosskOTkZkydPVmpj8+bNWLlypVJZUlISRo0aBXd3dxARLl++DACKwb+NjY3tcg2e5V//+hd69+4Nc3PzZuuIxWJ8/vnnMDIywnvvvYfKyspm665YsQKRkZGIiopCUVERjh07hsLCQgQGBuLevXsA1L8HALBkyRKsW7cOiYmJuHPnDkaNGoVp06bhl19+0d5FeMqPP/6IgoICTJs2rd3a0Kd2n1RVVYWjR4/ivffeg5mZmaJ86dKluHv3LjZu3Ijy8nLk5eUhKSkJw4cPh5+fn8pxnn/+edy6dQtnzpzRSlycXDHGmIEICAiAVCpFt27dEBISgsrKSty4cUOpjomJieJXGC8vL6SkpKC8vBzbt2/XSgzBwcGQyWRYvny5Vo6nicrKSly9ehXu7u7PrOvv74/58+fj2rVrWLJkSZN1qqurkZCQgPHjx2PGjBmwsrKCj48PPv30U9y/fx9btmxR2aele1BTU4OUlBSMGzcOEyZMgLW1NZYtWwZTU1OtXf+mziE8PBwpKSntcnx9a/dpcXFxcHBwQGxsrFJ5UFAQFi9ejLCwMEilUnh7e6O8vBxbt25t8jjPPfccAODcuXNaiYuTK8YYM0Dyf6U/+atJUwYNGgRzc3Olbi5DVVRUBCJq8VerJ8XGxqJ3797YvHkzjh8/rrI9Ly8PFRUVGDRokFK5r68vzMzMlLpTm/L0Pbh48SKqqqrg7e2tqCMWi2Fvb99u13/p0qV4//330aNHj3Y5vr61+6S9e/ciIyMDhw4dUnmxISoqClu2bMGRI0dQUVGBK1euICAgAP7+/koD3+Xkz5T818q24uSKMcY6OaFQiOLiYl2H0WY1NTUAoNZAawAQiUTYvn07BAIB3nnnHVRXVyttl79+b2lpqbKvtbU1ysvLNYpP3v24bNkyxZxbAoEA169fV3tKA00cP34c586dw7vvvqv1Y+tju0/atWsX1q5di5ycHLi4uChtu3PnDuLj4/H+++9j2LBhsLCwgKurK1JTU3H79m2sX79e5XhisRjA789YW3FyxRhjnVhdXR1KS0vh5OSk61DaTP4FqMmkj/7+/liwYAHy8/OxatUqpW3W1tYA0GQS1ZprJh/UnZiYCCJS+pw4cUKjY6lj27ZtOHLkCIyMjBSJnDyG1atXQyAQtMtYL121K7dx40akpaXh6NGjcHR0VNmen5+PhoYGlW1SqRS2trbIy8tT2ae2thbA789YW3FyxRhjnVhOTg6ISGkQr4mJyTO7E/WRnZ0dBAKBxvNXrVq1Cn369MHp06eVyr29vWFpaamSCJw8eRK1tbV48cUXNWqnZ8+eEIlEyM3N1Wi/1tq+fbtKEif/hTIqKgpEpNLlacjtEhEWL16Mc+fOISsrq8lfHAEokuI7d+4olZeXl+Phw4eKKRmeJH+munfvrpVYOblijLFOpLGxESUlJaivr8fZs2cRHh4OZ2dnzJw5U1HHw8MDDx8+RFZWFurq6lBcXKwy9w8A2Nra4vbt27h27RrKy8tRV1eHAwcO6GwqBnNzc7i5ueHmzZsa7SfvHnx6fiSRSISIiAjs3bsXaWlpkMlkOHfuHObOnQsHBweEhoZq3M6sWbOwc+dOpKSkQCaToaGhATdv3lR80YeEhKB79+4dvvxOZ2j3woULWLduHVJTU2FqaqrU9SoQCLBhwwYAgKurK4YOHYrU1FQcO3YM1dXVKCwsVNzP2bNnqxxb/kz5+Pi0OU6AkyvGGNMbmzZtgq+vLwBg8eLFGDNmDFJSUpCYmAgA6N+/P65cuYLU1FREREQAAEaMGIH8/HzFMWpqauDj4wOxWIzAwEB4enriu+++UxqnNG/ePAwdOhRTp05F7969sWrVKkV3yJMDfufOnQs7Ozt4eXnhjTfewMOHDzvkOrQkODgYeXl5SuOnvvrqK3h4eKCgoAC+vr748MMPVfbz8/PDggULVMo/+eQTxMXFISYmBl27dkVQUBBcXFyQk5MDCwsLANDoHiQlJWH+/PmIj49Hly5d4ODggPDwcJSUlAB43P1UVFSEffv2tXieP//8M15++WU4Ojri5MmTOHPmDBwcHDBkyBAcO3ZM4+vWGdpVdw4qgUCA3bt3IyQkBLNnz4aNjQ28vLxw48YNZGZmIjAwUGWfU6dOoUePHujfv7/G59gkekp6ejo1UcwYY6wFEydOpIkTJ+o0htDQULK1tdVpDJpozfdNfn4+mZiY0I4dO9opqvbV0NBAgYGBtG3bNm5XT9y/f59EIhFt2LBBo/1aeH4z+JcrxhjrRDQZ7G2IPDw8EBMTg5iYGFRUVOg6HI00NDQgKysL5eXlCAkJ4Xb1xIoVKzBw4ECEhYVp7ZicXDHGGDMokZGRmDRpEkJCQgxqceacnBxkZmbiwIEDas/Vxe22r4SEBOTm5mL//v0wNTXV2nE7dXIVExMDLy8vSKVSCIVCeHh4YNGiRc/81867774LiUQCgUDQYW99sKY1NjYiMTERAQEBWjnexYsX8eGHH6Jfv36QSCQwMTGBlZUVPD09ERwc3C6vS2tKnec2MzMTbm5uKgM6zczMYGdnh1dffRXr169XjPOQCwkJUdmnuU92dnZHnzprg6VLl2L79u0oKyuDq6sr9uzZo+uQ2tXq1asRFhaGNWvW6DoUtb322mv44osvlNZ15HZ1Z9++fXj06BFycnJgY2Oj3YNr0IdocIKCgmjz5s304MEDkslklJ6eTqampjRixIhn7rtz504CQKdPn+6ASFlTLl26REOGDCEANGDAgDYfb+vWrWRqakqvvPIKHTx4kEpKSqimpoYKCgpo165dFBAQQJ999pkWIm8bTZ5bd3d3srKyIiKixsZGKikpoe+++45mzpxJAoGAHBwc6NSpU4r6U6ZMoW+//ZZKS0uprq6O7ty5QwBo9OjRVFtbS5WVlVRUVETvvfceffPNNx12zp2BPoy5MjSd6fuG/fG0NObKRLupmn6xtLREaGio4vXbyZMnIzMzExkZGSgsLGxyrgttqK6uxmuvvaayACtT35kzZxATE4O5c+eisrKyzSuV//zzzwgNDUVQUBAOHToEE5PfH303Nze4ubnB2tpa6a0rXWntcysQCGBtbY1XX30Vr776KoKDgzFlyhQEBwfj0qVLsLKygkAgwJAhQ1R+ohcIBDA1NYWpqSnMzc01nt+HMcbY7zp1t2B2drbKvCZdu3YFgGcuRSAQCFrd7rZt21BUVNTq/RkwYMAAZGZmYvr06WovddGS2NhYNDQ0YM2aNUqJ1ZOGDx+Ov/71r21uq63a8tw+aeLEiZg5cyaKiorw6aefAgB27typ1tiH0NBQ/OUvf9EgasYYY3JaS6527NiBQYMGQSQSwcLCAi4uLoqlBogICQkJipXabWxsMHbsWKWFLFNSUmBhYQFzc3Ps27cPI0eOhFQqhZOTE3bu3Kmo17dvXwgEAhgZGeHFF19UfNksWrQIVlZWEIlE+Pzzz5uN89atWxCLxXB1dVWUERHWr1+P3r17QygUwsrKCh9//HGrrkN4eDgiIiJQUFAAgUAADw8PrFu3Dubm5pBIJCgqKkJERAR69OiBixcv4ocffoCXl5cidh8fHxw6dEijawIA33//PV566SWYm5tDKpXCx8cHMpkMycnJEIlEsLOzw5w5c+Dg4ACRSISAgACVRUnVuU8ttQU8fjskOjoazs7OEIvF6N+/P9LT01t1LdVx8ODBZ05oWFtbiyNHjqBLly546aWX1D62vj+36pBPHHngwAGN9gPAz207PreMsU5Ogz7EZiUmJhIAWrNmDT148IAePnxIn332GU2fPp2IiKKjo8nMzIx27NhBpaWldPbsWXrhhReoa9eudPfuXcVxoqKiCAAdOXKEysrKqKioiAIDA8nCwoJqa2uJiKi+vp5cXFzI2dmZ6uvrleKYP38+JSYmNhtnZWUlSSQSCgsLUyqPiooigUBAf/vb36ikpISqqqpo8+bNrR5zNWHCBHJ3d1dpAwB99NFHtHHjRho/fjz9v//3/2j37t20YsUKevjwIT148ID8/PyoS5cuGl2TiooKkkqlFB8fT9XV1XT37l0aP348FRcXE9HjuW8sLCzowoULVFNTQ3l5eeTr60sSiYRu3LihaEud+/SsthYuXEhCoZD27NlDJSUltHTpUjIyMlIa96OpwYMHNzvmKjs7myQSCcXExDS7/6VLlwgA+fn5adSuvj+3RMpjrpoik8kIAPXs2bPJ7fIxV2PGjGlyOz+36j+3POZKczzmihmylsZctTm5qq2tJWtraxo6dKhSeX19PSUlJVFVVRVZWlpSSEiI0vb//Oc/BEDpS1H+B7m6ulpRJk9yLl++rCiTJ3MZGRmKssrKSnJ2dqaysrJmY42KiiJPT0+SyWSKsqqqKjI3N6c///nPSnXbMqC9peTqyXNrSlxcHAGgoqKiZvd7+pqcP3+eAK46ZyYAACAASURBVFB2dnaTxwwNDVX5Aj516hQBoJUrVxIRqX2fWmqrurqazM3NlY5RVVVFQqGQ5s2b1+J5t6Sl5Eodv/zyCwGgP/3pT2rvo+/PrdyzkisiIoFAQNbW1k1uUze54uf22Ti50hwnV8yQteskomfPnkVpaSmGDx+uVG5sbIyPPvoIeXl5qKioUFnE0dfXF2ZmZio/8T/NzMwMAJQWGX333XdhZWWFpKQkRVlaWhrGjh0LqVTa5HH27t2LjIwMHDp0CBKJRFF++fJlVFVV4bXXXlPvhNuZfJ6NliYCfPqauLm5wc7ODjNmzMCKFStw7dq1Z7YzaNAgmJubK7pO1L1PLbV18eJFVFVVwdvbW1EmFothb2+v0kXTkeSLe2oyXknfn1t1yV8GaO742sLP7WN79uxRe6oL/ggwZcoUANB5HPzhT2s+8ue3KW1+W1A+ZsHa2rrJ7aWlpQDQ5OrV1tbWKC8v17hNS0tLvP/++1i/fj3+85//4KWXXsLf//73Zud12bVrFxISEpCTkwNHR0elbfLFGrt166ZxHNrwr3/9C+vXr0deXh5kMlmrVqoXi8U4evQolixZgtWrVyMmJgaTJ0/G9u3bFeuFNUUoFCpWMlf3PrXUVmVlJQBg2bJlWLZsmdIxHBwcND4vbXFxcYFIJMKlS5fU3kffn1t1yc+5T58+rdq/OfzcNs3Pzw/z58/XaJ8/shMnTiApKYnHtzGDJH9+m9Lm5Er+R//+/ftNbpcnXU19GZWWlsLJyalV7YaFhSEpKQmJiYmYO3cuevbsCXd3d5V6GzduxKFDh3D06NEm/wCLRCIAwKNHj1oVR1vcuHED48aNw/jx4/GPf/wDjo6O2LhxIxYtWqTxsfr164dvvvkGxcXFSEhIwNq1a9GvXz8sX768yfp1dXVK11+T+9RcW/LlDRITExEeHq7xObQXoVCI4cOHY9++ffjxxx8xZMiQJus9fPgQixYtwtatW/X+uVXXwYMHAQAjR45s9TGexs9t85ycnDB58uQ2HeOPJikpia8ZM1jNJVdt7hZ0cXGBra0tvv322ya3e3t7w9LSEr/88otS+cmTJ1FbW9vq+XTkf8T27NmD5cuXq/xRJCIsXrwY586dQ1ZWVrNfUN7e3jAyMsL333/fqjja4ty5c6irq8O8efPg5uYGkUgEgUDzKSBu376NCxcuAHj8C9yaNWvwwgsvKMqakpOTAyKCn58fAPXvU0tt9ezZEyKRSC9ntV+xYgWEQiEWLFiA6urqJuucP39eMU2Dvj+36rh79y4SExPh5OSEd955p9XHeRo/t4wx1rI2J1dCoRBLly7FsWPHEBYWhlu3bqGxsRHl5eW4cOECRCIRIiIisHfvXqSlpUEmk+HcuXOYO3cuHBwcEBoa2uq2IyIiUF9fj5KSEgwbNkxp24ULF7Bu3TqkpqbC1NRUpa90w4YNAB7/oZ0wYQL27NmDbdu2QSaT4ezZs9iyZUur47K1tcXt27dx7do1lJeXN9tl4uzsDAA4fPgwampqkJ+f/8yxPE25ffs25syZg99++w21tbU4ffo0rl+/rvgCAh4vI1NSUoL6+nqcPXsW4eHhcHZ2Vryqr+59aqktkUiEWbNmYefOnUhJSYFMJkNDQwNu3ryJO3fuaHxe6jhw4MAzp2IAgIEDB+KLL77A+fPnERgYiP3796OsrAx1dXW4evUqUlNTMXv2bMXYIX1/bp9ERKioqEBjYyOICMXFxUhPT8eQIUNgbGyMrKwsrY654ueWMcaeQYPR7y3atGkT+fj4kEgkIpFIRM8//zxt3ryZiB4vy7F+/Xp67rnnyNTUlGxsbGjcuHF08eJFxf6bN28mc3NzAkDPPfccFRQU0JYtW0gqlRIA6tWrF126dEml3aFDh9LWrVtVys+dO0cAmv2sX79eUbe8vJzeffdd6tKlC1laWtLLL79M0dHRBICcnJzozJkzGl2LX3/9lXr16kVisZhefvllWrBgAYnFYsUr8Tt27FDUXbx4Mdna2pK1tTVNmjSJNm3aRADI3d2dlixZotY1uXbtGgUEBJCNjQ0ZGxuTo6MjRUVFKV75Dw0NJVNTU+rRoweZmJiQVCqlsWPHUkFBgVLc6tynZ7X16NEjWrx4MTk7O5OJiQl169aNJkyYQHl5eRpdwxMnTtCQIUPIwcFBcc/s7e0pICCAvv/+e0W9/fv3k0QiodjYWLWOe+PGDVq4cCH5+PiQpaUlGRsbk7W1NT3//PM0e/Zs+vHHHzW6Hrp6br/++mvq378/mZubk5mZGRkZGREAxZuBL730EsXExNCDBw+avA4ymYxeeeUVsrW1JQBkZGREHh4etHr1akWd+Ph4fm41eG75bUHN8duCzJC19LaggEh5XZGMjAxMmTKlzcuNMP0xZ84c7N69Gw8ePNB1KIypzdCe20mTJgEAdu/ereNIDAd/3zBD1sLzu7tTL3/DftfSK/KM6St+bhljhoiTKzX89ttvas15IX/riKnia8gY07bDhw8jMjISmZmZcHNzU/wdefPNN1Xqvv7665BIJDA2Nka/fv3w66+/6iBi9cXExMDLywtSqRRCoRAeHh5YtGgRKioqVOp++eWX8PX1hUQiQa9evTBr1izcvXvXoNqVa2xsRGJiIgICAto9vq+//hrx8fHt8484DfoQmQGKjIwkMzMzAkAuLi60e/duXYfE2DMZ4nPLY64015bvm+joaBo1apTSygXu7u7UpUuXZmfjP3DgQLOrEeiboKAg2rx5Mz148IBkMhmlp6eTqakpjRgxQqnerl27CADFx8dTaWkpnT59mtzc3GjgwIFUV1dnMO0SPV6qbMiQIQSg2VU5tB1fUlISBQUFUUlJicbxtuvyN4wxxvQjuaqqqiJ/f3+DaaO13zdr1qwhT09PlWWZ3N3d6YsvviAjIyPq0aMHlZaWKm03pOQqODhYZR3SyZMnEwCltTWHDh1Kjo6O1NjYqCiTv2By/Phxg2k3NzeXxo8fT2lpaTRw4MBmk6v2iC8sLIz8/f01Tgrbdfkbxhhj+mHbtm0oKioy+DZacvnyZSxfvhwrV65UTAL9pICAAISHh+PWrVtYuHChDiLUjuzsbBgbGyuVde3aFYDyUl6FhYVwcHBQmmuuZ8+eAIDr168bTLsDBgxAZmYmpk+fDqFQ2KHxrVixArm5uc1OCNoanFwxxpiOEBESEhLQt29fCIVC2NjYYOzYsUprGoaFhcHMzAz29vaKsg8++AAWFhYQCASK1THCw8MRERGBgoICCAQCeHh4IDk5GSKRCHZ2dpgzZw4cHBwgEokQEBCgNDdZW9oAHq8EoM58c9qQnJwMIsLo0aObrRMbGwtPT09s3boVhw8fbvF46tyDlJQUWFhYwNzcHPv27cPIkSMhlUrh5OSEnTt3Kh2voaEB0dHRcHZ2hlgsRv/+/bW2vM+tW7cgFovh6uqqKHNzc1NJduXjitzc3Ay63Y6Kz8bGBkFBQUhKStLem6sa/MzFGGOsGa3pFoyOjiYzMzPasWMHlZaW0tmzZ+mFF16grl270t27dxX1pk+fTt27d1fad/369QSAiouLFWUTJkwgd3d3pXqhoaFkYWFBFy5coJqaGsrLyyNfX1+SSCRK3ShtaSM7O5skEgnFxMRodP6t+b5xc3MjLy+vJre5u7vT1atXiYjop59+IiMjI3JxcaGKigoiarpbUN17EBUVRQDoyJEjVFZWRkVFRRQYGEgWFhZUW1urqLdw4UISCoW0Z88eKikpoaVLl5KRkRGdOnVKo/N8WmVlJUkkEgoLC1Mqz8nJIVNTU0pOTiaZTEbnz5+nvn370vDhw9vUni7bHTx4cLPdgu0VX2RkJAGg06dPqx0ndwsyxpieqa6uRkJCAsaPH48ZM2bAysoKPj4++PTTT3H//v02rRLxNBMTE8UvM15eXkhJSUF5eTm2b9+uleMHBwdDJpM1uyaktlRWVuLq1atNrsf5NH9/f8yfPx/Xrl3DkiVLmqzTmnsQEBAAqVSKbt26ISQkBJWVlbhx4wYAoKamBikpKRg3bhwmTJgAa2trLFu2DKampm2+1nFxcXBwcEBsbKxSeVBQEBYvXoywsDBIpVJ4e3ujvLwcW7dubVN7um63o+N77rnnADxe3ksbOLlijDEdyMvLQ0VFBQYNGqRU7uvrCzMzs1YtKaSuQYMGwdzcXKnryxAUFRWBiGBubq5W/djYWPTu3RubN2/G8ePHVba39R6YmZkBgGKJs4sXL6Kqqgre3t6KOmKxGPb29m261nv37kVGRgYOHToEiUSitC0qKgpbtmzBkSNHUFFRgStXriAgIAD+/v4oLCxsdZu6bFcX8cmfqXv37mklNk6uGGNMB0pLSwGgycW5ra2tUV5e3q7tC4VCFBcXt2sb2lZTUwMALQ54fpJIJML27dshEAjwzjvvqCzaru17UFlZCQBYtmyZ0vx9169fVxpsrYldu3Zh7dq1yMnJgYuLi9K2O3fuID4+Hu+//z6GDRsGCwsLuLq6IjU1Fbdv38b69etb1aYu29VVfGKxGMDvz1hbcXLFGGM6YG1tDQBNfoGXlpbCycmp3dquq6tr9zbag/wLUJNJH/39/bFgwQLk5+dj1apVStu0fQ+6desGAEhMTAQRKX1OnDih0bEAYOPGjUhLS8PRo0fh6Oiosj0/Px8NDQ0q26RSKWxtbZGXl6dxm7psV5fx1dbWAvj9GWsrE60chTHGmEa8vb1haWmJX375Ran85MmTqK2txYsvvqgoMzExUXQ9aUNOTg6ICH5+fu3WRnuws7ODQCBAWVmZRvutWrUK2dnZOH36NJydnRXlmtwDdfTs2RMikQi5ubka7fc0IsKSJUtQUlKCrKwsmJg0/VUtT/7u3LmjVF5eXo6HDx8qph7Q93b1IT75M9W9e3etxMq/XDHGmA6IRCJERERg7969SEtLg0wmw7lz5zB37lw4ODggNDRUUdfDwwMPHz5EVlYW6urqUFxc3ORcQra2trh9+zauXbuG8vJyRbLU2NiIkpIS1NfX4+zZswgPD4ezszNmzpyplTYOHDjQIVMxmJubw83NDTdv3tRoP3n34NPzI2lyD9RtZ9asWdi5cydSUlIgk8nQ0NCAmzdvKr7oQ0JC0L179xaX37lw4QLWrVuH1NRUmJqaqiwTtmHDBgCAq6srhg4ditTUVBw7dgzV1dUoLCxUxD179mzFMfW5XXW1R3xy8mfKx8enzXECnFwxxpjOfPLJJ4iLi0NMTAy6du2KoKAguLi4ICcnBxYWFop68+bNw9ChQzF16lT07t0bq1atUnRfPDlAd+7cubCzs4OXlxfeeOMNPHz4EMDjcSQ+Pj4Qi8UIDAyEp6cnvvvuO6WxS21to6MEBwcjLy9PafzUV199BQ8PDxQUFMDX1xcffvihyn5+fn5YsGCBSrk69yAlJQWJiYkAgP79++PKlStITU1FREQEAGDEiBHIz88HACQlJWH+/PmIj49Hly5d4ODggPDwcJSUlAB43P1UVFSEffv2NXuOpOZcSwKBALt370ZISAhmz54NGxsbeHl54caNG8jMzERgYKCirj63CwA///wzXn75ZTg6OuLkyZM4c+YMHBwcMGTIEBw7dqzd4pM7deoUevTogf79+6vVxjNpMG8DY4yxZujD8jdNCQ0NJVtbW12H0aTWfN/k5+eTiYkJ7dixo52ial8NDQ0UGBhI27Zt43b1xP3790kkEtGGDRs02o/nuWKMsT8wTQaA6zsPDw/ExMQgJiYGFRUVug5HIw0NDcjKykJ5eTlCQkK4XT2xYsUKDBw4EGFhYVo7JidXjDHGDEpkZCQmTZqEkJAQjQe361JOTg4yMzNx4MABtefq4nbbV0JCAnJzc7F//36Ymppq7bicXDHGWCe1dOlSbN++HWVlZXB1dcWePXt0HZLWrF69GmFhYVizZo2uQ1Hba6+9hi+++EJpDUduV3f27duHR48eIScnBzY2Nlo9Nk/FwBhjnVRcXBzi4uJ0HUa7ef311/H666/rOgxmoMaMGYMxY8a0y7H5lyvGGGOMMS3i5IoxxhhjTIs4uWKMMcYY0yJOrhhjjDHGtKjZAe0ZGRkdGQdjjBk0+fIZ/LdTffLFjPmaMUPU0mLcAiLl+eQzMjIwZcqUdg+KMcYYY8zQkeqyPLtVkivGGNM38n/08Z8rxpgB2M1jrhhjjDHGtIiTK8YYY4wxLeLkijHGGGNMizi5YowxxhjTIk6uGGOMMca0iJMrxhhjjDEt4uSKMcYYY0yLOLlijDHGGNMiTq4YY4wxxrSIkyvGGGOMMS3i5IoxxhhjTIs4uWKMMcYY0yJOrhhjjDHGtIiTK8YYY4wxLeLkijHGGGNMizi5YowxxhjTIk6uGGOMMca0iJMrxhhjjDEt4uSKMcYYY0yLOLlijDHGGNMiTq4YY4wxxrSIkyvGGGOMMS3i5IoxxhhjTIs4uWKMMcYY0yJOrhhjjDHGtIiTK8YYY4wxLeLkijHGGGNMizi5YowxxhjTIk6uGGOMMca0iJMrxhhjjDEt4uSKMcYYY0yLOLlijDHGGNMiTq4YY4wxxrTIRNcBMMbYk27evIm3334bDQ0NirKSkhJIJBK8+uqrSnV79+6Nzz77rIMjZIyxlnFyxRjTK05OTrh+/ToKCgpUtn3//fdK//3KK690VFiMMaY27hZkjOmdt956C6amps+sFxIS0gHRMMaYZji5YozpnenTp6O+vr7FOv369YOXl1cHRcQYY+rj5Ioxpnfc3d3Rv39/CASCJrebmpri7bff7uCoGGNMPZxcMcb00ltvvQVjY+Mmt9XX12PSpEkdHBFjjKmHkyvGmF6aOnUqGhsbVcqNjIzg5+cHFxeXjg+KMcbUwMkVY0wvOTg4YMiQITAyUv4zZWRkhLfeektHUTHG2LNxcsUY01tvvvmmShkRYfz48TqIhjHG1MPJFWNMb02cOFFp3JWxsTH+9Kc/wc7OTodRMcZYyzi5YozpLRsbG/z5z39WJFhEhBkzZug4KsYYaxknV4wxvTZjxgzFwHZTU1OMHTtWxxExxljLOLlijOm10aNHQygUAgBGjRoFS0tLHUfEGGMt4+SKMabXLCwsFL9WcZcgY8wQCIiIdB2Etk2aNAl79uzRdRiMMcYYa0F6ejomT56s6zC0bbeJriNoL35+fpg/f76uw2CMqeHEiRNISkpCenp6k9sbGhqQnp6OadOmdXBk+m3KlCkIDw+Hv7+/rkNhTGNTpkzRdQjtptMmV05OTp0xG2as00pKSmrx/9lx48ZBJBJ1YET6b8qUKfD39+e/dcwgdebkisdcMcYMAidWjDFDwckVY4wxxpgWcXLFGGOMMaZFnFwxxhhjjGkRJ1eMMcYYY1rEyRVjrNPYv38/rKys8M033+g6FL13+PBhREZGIjMzE25ubhAIBBAIBHjzzTdV6r7++uuQSCQwNjZGv3798Ouvv+ogYvXFxMTAy8sLUqkUQqEQHh4eWLRoESoqKlTqfvnll/D19YVEIkGvXr0wa9Ys3L1716DalWtsbERiYiICAgLaPb6vv/4a8fHxaGhoaFPMnRZ1QhMnTqSJEyfqOgzGmJrS09NJG3+OsrOzSSqV0tdff62FqPQfAEpPT9d4v+joaBo1ahTJZDJFmbu7O3Xp0oUAUHZ2tso+Bw4coDFjxrQp3o4SFBREmzdvpgcPHpBMJqP09HQyNTWlESNGKNXbtWsXAaD4+HgqLS2l06dPk5ubGw0cOJDq6uoMpl0iokuXLtGQIUMIAA0YMKBD4ktKSqKgoCAqKSlpVcytfX4NQAYnV4wxndNWcqVPqqqqyN/fv13baM2X05o1a8jT05Oqq6uVyt3d3emLL74gIyMj6tGjB5WWliptN6TkKjg4mOrr65XKJk+eTADoxo0birKhQ4eSo6MjNTY2Kso2bdpEAOj48eMG025ubi6NHz+e0tLSaODAgc0mV+0RX1hYGPn7+7cqKezMyRV3CzLGWDvYtm0bioqKdB2GksuXL2P58uVYuXJlk/OGBQQEIDw8HLdu3cLChQt1EKF2ZGdnw9jYWKmsa9euAICqqipFWWFhIRwcHCAQCBRlPXv2BABcv37dYNodMGAAMjMzMX36dMUi5x0V34oVK5Cbm4ukpCSN4+7MOLlijHUKx48fh7OzMwQCATZt2gQASElJgYWFBczNzbFv3z6MHDkSUqkUTk5O2Llzp2Lf5ORkiEQi2NnZYc6cOXBwcIBIJEJAQABOnjypqBcWFgYzMzPY29sryj744ANYWFhAIBDg/v37AIDw8HBERESgoKAAAoEAHh4eAICDBw9CKpVi9erVHXFJVCQnJ4OIMHr06GbrxMbGwtPTE1u3bsXhw4dbPB4RISEhAX379oVQKISNjQ3Gjh2L3377TVFH3XsAPF7mKDo6Gs7OzhCLxejfv3+zSyJp6tatWxCLxXB1dVWUubm5qSTA8nFFbm5uBt1uR8VnY2ODoKAgJCUlgTrfUsWtp+OfztoFdwsyZli01S1YWFhIAGjjxo2KsqioKAJAR44cobKyMioqKqLAwECysLCg2tpaRb3Q0FCysLCgCxcuUE1NDeXl5ZGvry9JJBKlLpPp06dT9+7dldpdv349AaDi4mJF2YQJE8jd3V2pXnZ2NkkkEoqJiWnzuRJp3q3i5uZGXl5eTW5zd3enq1evEhHRTz/9REZGRuTi4kIVFRVE1HS3YHR0NJmZmdGOHTuotLSUzp49Sy+88AJ17dqV7t69q6in7j1YuHAhCYVC2rNnD5WUlNDSpUvJyMiITp06pfY5NqWyspIkEgmFhYUplefk5JCpqSklJyeTTCaj8+fPU9++fWn48OFtak+X7Q4ePLjZbsH2ii8yMpIA0OnTpzWKVdPn14BwtyBj7I8hICAAUqkU3bp1Q0hICCorK3Hjxg2lOiYmJopfYby8vJCSkoLy8nJs375dKzEEBwdDJpNh+fLlWjmeJiorK3H16lW4u7s/s66/vz/mz5+Pa9euYcmSJU3Wqa6uRkJCAsaPH48ZM2bAysoKPj4++PTTT3H//n1s2bJFZZ+W7kFNTQ1SUlIwbtw4TJgwAdbW1li2bBlMTU3bfP3j4uLg4OCA2NhYpfKgoCAsXrwYYWFhkEql8Pb2Rnl5ObZu3dqm9nTdbkfH99xzzwEAzp071+4xGwpOrhhjfzhmZmYAgLq6uhbrDRo0CObm5krdXIaqqKgIRARzc3O16sfGxqJ3797YvHkzjh8/rrI9Ly8PFRUVGDRokFK5r68vzMzMlLpTm/L0Pbh48SKqqqrg7e2tqCMWi2Fvb9+m6793715kZGTg0KFDkEgkStuioqKwZcsWHDlyBBUVFbhy5QoCAgLg7++PwsLCVrepy3Z1EZ/8mbp3716HxG4IOLlijLEWCIVCFBcX6zqMNqupqQGAFgc8P0kkEmH79u0QCAR45513UF1drbS9tLQUAGBpaamyr7W1NcrLyzWKr7KyEgCwbNkyxZxbAoEA169fVxpsrYldu3Zh7dq1yMnJgYuLi9K2O3fuID4+Hu+//z6GDRsGCwsLuLq6IjU1Fbdv38b69etb1aYu29VVfGKxGMDvzxjj5IoxxppVV1eH0tJSODk56TqUNpN/AWoy6aO/vz8WLFiA/Px8rFq1SmmbtbU1ADSZRLXmmnXr1g0AkJiYCCJS+pw4cUKjYwHAxo0bkZaWhqNHj8LR0VFle35+PhoaGlS2SaVS2NraIi8vT+M2ddmuLuOrra0F8PszxgATXQfAGGP6KicnB0QEPz8/RZmJickzuxP1kZ2dHQQCAcrKyjTab9WqVcjOzsbp06fh7OysKPf29oalpSV++eUXpfonT55EbW0tXnzxRY3a6dmzJ0QiEXJzczXa72lEhCVLlqCkpARZWVkwMWn6a06e/N25c0epvLy8HA8fPlRMPaDv7epDfPJnqnv37lqO2nDxL1eMMfZ/GhsbUVJSgvr6epw9exbh4eFwdnbGzJkzFXU8PDzw8OFDZGVloa6uDsXFxU3OTWRra4vbt2/j2rVrKC8vR11dHQ4cOKCzqRjMzc3h5uaGmzdvarSfvHvw6fmRRCIRIiIisHfvXqSlpUEmk+HcuXOYO3cuHBwcEBoaqnE7s2bNws6dO5GSkgKZTIaGhgbcvHlT8UUfEhKC7t27t7j8zoULF7Bu3TqkpqbC1NRUqYtRIBBgw4YNAABXV1cMHToUqampOHbsGKqrq1FYWKiIe/bs2Ypj6nO76mqP+OTkz5SPj0+b4+wsOLlijHUKmzZtgq+vLwBg8eLFGDNmDFJSUpCYmAgA6N+/P65cuYLU1FREREQAAEaMGIH8/HzFMWpqauDj4wOxWIzAwEB4enriu+++UxqnNG/ePAwdOhRTp05F7969sWrVKkV3yJMDfufOnQs7Ozt4eXnhjTfewMOHDzvkOrQkODgYeXl5SuOnvvrqK3h4eKCgoAC+vr748MMPVfbz8/PDggULVMo/+eQTxMXFISYmBl27dkVQUBBcXFyQk5MDCwsLANDoHiQlJWH+/PmIj49Hly5d4ODggPDwcJSUlAB43P1UVFSEffv2NXuOpOZcSwKBALt370ZISAhmz54NGxsbeHl54caNG8jMzERgYKCirj63CwA///wzXn75ZTg6OuLkyZM4c+YMHBwcMGTIEBw7dqzd4pM7deoUevTogf79+6vVxh+CbqaAaF88zxVjhkUflr8JDQ0lW1tbncagKWg4T1B+fj6ZmJjQjh072jGq9tPQ0ECBgYG0bds2bldP3L9/n0QiEW3YsEHjfTV9fg0Iz3PFGGNymgz2NkQeHh6IiYlBTEwMKioqdB2ORhoaGpCVlYXy8nKEhIRwu3pixYoVGDhwIMLCwnQdil7h5ArAhg0bFIM9P/30U60cc82aNbCysoJAIGjzAE190h7XSh01NTXo06cPli1bpvG+mZmZcHNzU4wtkdJoFQAAIABJREFUsLe3x4wZM9ohyse0fe+fjl/+EYlEcHV1xTvvvIOrV6+26ZjPuib/8z//A0dHRwgEAhgZGcHT01NlaZS//OUvkEqlMDIyQp8+ffDjjz+26nxZ+4qMjMSkSZMQEhKi8eB2XcrJyUFmZiYOHDig9lxd3G77SkhIQG5uLvbv3w9TU1Ndh6NfdP3bWXtoTbdgfn4+AaC///3vWotj586drVoSQN+1x7V6lgULFhAAioqKavUx3N3dycrKSotRNa897v2T8Tc0NNC9e/fon//8J5mbm5OdnR3dv3+/TcdUBwAaPHhws9u/++47eu211zSOQ9fdgpGRkWRmZkYAyMXFhXbv3q2zWDSBNnSrHDp0iBYvXqzliNgfRVZWFsXFxVF9fX2rj9GW51fPcbcg038//fQTzp8/r+sw9IqRkRHs7Ozw5ptv4q9//SuKioqeucgua15cXBwePXoEIsLVq1cxceJEXYfU7l5//XWsXbtW12EwAzVmzBhERkaqvEXKHuPkium16upqfPzxx0hKStJ1KHrLw8MDwO+r1jPGGNMtTq5a0NDQgOjoaDg7O0MsFqN///5IT09XbP/hhx/g5eUFKysriEQi+Pj44NChQ80e7969e3BxcYGJiQlGjBgBAHj33XcV417c3d1x+vRpAMCsWbNgbm4OKysrfP3112rHvG7dOpibm0MikaCoqAgRERHo0aMHLl68+Mzzaa2wsDCYmZnB3t5eUfbBBx/AwsICAoEA9+/fb/Wxo6Ki8MEHHyhmb37awYMH22XeIEO69/LX2AcMGKDROTDGGGsfnFy1YMmSJVi3bh0SExNx584djBo1CtOmTVPMSHzv3j1MmTIF165dw+3bt2FpaYnp06c3ezxbW1sMGjQIe/fuxcGDBwEAW7duxYQJE2BsbIwffvgBzz//PABg+/btGDduHNLS0jB69Gi1Y160aBEWLFiAiooKxMXFwdXVFX5+forZeVs6n9ZKTk7G5MmTlco2b96MlStXtum4P/74IwoKCjBt2rRm68jf7mpsbGxTW08zhHtfWlqK//3f/8XmzZsRHByMV199VaNzYIwx1k50PeqrPWhjQHt1dTWZm5tTSEiIok5VVRUJhUKaN29ek8eIi4sjAFRUVEREyoOa6+rqaOrUqXTgwAGV/Q4fPkwAKDY2VlFWVlZGzz33XKsGC0ZFRREAqq6uVpS15nya09SA9unTp1P37t2V6q1fv54AUHFxscbnUFVVRYMGDaKbN28SEVFxcXGHDWjX13vv7u5OAJQ+AoGAYmNjqba2tlXnwAPaDRs674Bg9gfQiZ/fDF5bsBkXL15EVVUVvL29FWVisRj29vb47bffmtxH/irq03PlNDQ0YNq0aXB0dFR0CT1p2LBh8PT0xD/+8Q8sXboUAoEAu3btQkhIiNYGC7bmfHRp6dKleP/999GjR48Ob1uf772VlRVKS0sBPP6Vcv369bCyslJ5DdrQ7rdcRkaGrkMwOK1Z1Jgx1s50nd61B238cvXjjz+q/Eog//j5+RERUXZ2NgUFBVHXrl3JzMyMBAIBAaA7d+4Q0e+/Xvj5+dHAgQNJKBRSXl5ek+0nJCQQAPr3v/9NRERDhgyha9euter8m/rlSp3zUVd7/3L1ww8/0GuvvUaNjY2Kso785Upf7/3T8ctkMrK3tyeJREI3btzQ+Bw0uSZyAMjX17fZ7YcPH6YRI0aofTw5+S9X/OEPf/5Yn876yxWPuWqGfAB1YmIiiEjpc+LECdy4cQPjxo2Dvb09Tp48ibKyMsTHxzd5rMmTJ+Pf//43rK2t8dZbb6G+vl6lzsyZMyESibB161ZcvHgRUqkUvXr16rDz0Sfbtm3DkSNHYGRkpBjwLY9/9erVEAgEWh83dOzYMcX6Z4Zy7yUSCdauXYvy8nLMmzdPaZs27veT10ROvhhxc65evYqePXuqdfymPB0rf1r+AEB6errO4+APf1rz6cw4uWpGz549IRKJmp1h+9y5c6irq8O8efPg5uYGkUgEgUDQZN2hQ4eia9eu2LJlC/773/8iNjZWpY6NjQ2mTJmCrKwsbNiwAe+9916Hnk9bmZiYoK6uTivH2r59u8r/hMXFxQAevz1IRBg0aJBW2pL773//q1ho1pDu/VtvvYXBgwcjOztbqUtNG/f7yWsiN2zYMNy6dQs//fSTSn0iwueff47Bgwe3uk3GGOsMOLlqhkgkwqxZs7Bz506kpKRAJpOhoaEBN2/exJ07d+Ds7AwAOHz4MGpqapCfn4+TJ0+2eMzRo0dj5syZWL16Nf773/+qbJ87dy4ePXqE7OxsjBo1qkPPp608PDzw8OFDZGVloa6uDsXFxbh+/boWIm/ZgQMH2jQVQ11dHe7du4ecnBxFImFI914gECA5ORkCgQBhYWEoKSlR6xw0vSZysbGxsLa2xqRJk/DVV1+hsrISjx49wpkzZzBt2jTU19fjzTffVDt+xhjrlKgT0nTM1d/+9jfq3r07ASALCwsaP348ERE9evSIFi9eTM7OzmRiYkLdunWjCRMmKMbOLF68mGxtbcna2pomTZpEmzZtIgDk7u5OSUlJZGNjQ8Dj5TSKiopIJpNRz549CQBZWlrSP//5T5VYnn/+eYqMjGz1ucfHx5NYLCYA1LNnT9qxY4di27POpy3X6sGDBzR06FASiUTk6upKH374IX388ccEgDw8PFTGBGmquTFX+/fvJ4lEovS23dP27t3b5Jt2T3/27t2r2Eef7v2PP/5Inp6eijgdHR1pzpw5SnVmzpxJAMja2prWrFnzzHNozTWRu3r1Kr333nvk6upKZmZmJBaLycvLi6Kjo6mioqKFu9g8fluwddB5x6ywP4BO/PxmCIg6X8fnpEmTAAC7d+/WcSSaCw4OxqZNm+Dq6qrrUFgH+yPf+4yMDEyZMqXTj8PQNoFAgPT0dJV55hgzBJ34+d3N3YI69uQ4pbNnz0IkEv0hv1z/iPjeM8ZY58TJlY4tXrwY+fn5uHTpEmbNmoVVq1ap1Pntt98Ub8219AkJCWlVDO19/I5qw9Coc+8ZY4wZHk6udMzc3Bx9+vTBn/70J6xYsQJeXl4qdfr06aPWa627du1qVQztffyOasPQqHPvGWsvhw8fRmRkJDIzM+Hm5qb4B05TLyS8/vrrkEgkMDY2Rr9+/fDrr7/qIGL1xcTEwMvLC1KpFEKhEB4eHli0aBEqKipU6n755Zfw9fWFRCJBr169MGvWrFYvgq6rduUaGxuRmJiIgICAdo/v66+/Rnx8vMrEyez/dMTIro7WmklEGWO6wwPaWwetHBAcHR1No0aNIplMpihzd3enLl26EADKzs5W2efAgQM0ZsyYNsXbUYKCgmjz5s304MEDkslklJ6eTqampioT3O7atYsAUHx8PJWWltLp06fJzc2NBg4cSHV1dQbTLhHRpUuXaMiQIQSABgwY0CHxJSUlUVBQEJWUlLQq5tY+vwYgo1P+NePkijHDog/JVVVVFfn7+xtUG635clqzZg15enoqreBA9Di5+uKLL8jIyIh69OhBpaWlStsNKbkKDg5WWZtz8uTJBEDpzeWhQ4eSo6Oj0moQ8jd/jx8/bjDt5ubm0vjx4yktLY0GDhzYbHLVHvGFhYWRv79/q5LCzpxccbcgY4zh8coARUVFBt9GSy5fvozly5dj5cqVEIlEKtsDAgIQHh6OW7duYeHChTqIUDuys7NV1ubs2rUrAKCqqkpRVlhYCAcHB6VJgOUrDLRmnj5dtTtgwABkZmZi+vTpEAqFHRrfihUrkJubi6SkJI3j7sw4uWKMGSQiQkJCAvr27QuhUAgbGxuMHTtWaWHqsLAwmJmZwd7eXlH2wQcfwMLCAgKBAPfv3wcAhIeHIyIiAgUFBRAIBPDw8EBycjJEIhHs7OwwZ84cODg4QCQSISAgQGnS2La0AQAHDx5s00S4mkhOTgYRYfTo0c3WiY2NhaenJ7Zu3YrDhw+3eDx17kFKSgosLCxgbm6Offv2YeTIkZBKpXBycsLOnTuVjtfQ0IDo6Gg4OztDLBajf//+SE9Pb9tJ/59bt25BLBYrvZHr5uamkuzKxxW5ubkZdLsdFZ+NjQ2CgoKQlJTEU6k8Sbe/nLUP7hZkzLC0plswOjqazMzMaMeOHVRaWkpnz56lF154gbp27Up3795V1FN3UfEJEyaQu7u7Ur3Q0FCysLCgCxcuUE1NDeXl5ZGvr6/KYtltaSM7O5skEgnFxMRodP5EmneruLm5kZeXV5Pb3N3d6erVq0RE9NNPP5GRkRG5uLgoJoZtqltQ3XsgX0z+yJEjVFZWRkVFRRQYGEgWFhZUW1urqLdw4UISCoW0Z88eKikpoaVLl5KRkRGdOnVK7XNsSmVlJUkkEgoLC1Mqz8nJIVNTU0pOTiaZTEbnz5+nvn370vDhw9vUni7bHTx4cLPdgu0VX2RkJAGg06dPaxSrps+vAeFuQcaY4amurkZCQgLGjx+PGTNmwMrKCj4+Pvj0009x//59bNmyRWttmZiYKH6Z8fLyQkpKCsrLy7F9+3atHD84OBgymQzLly/XyvGaU1lZiatXr8Ld3f2Zdf39/TF//nxcu3YNS5YsabJOa+5BQEAApFIpunXrhpCQEFRWVuLGjRsAgJqaGqSkpGDcuHGYMGECrK2tsWzZMpiamrb5WsfFxcHBwUFlbc+goCAsXrwYYWFhkEql8Pb2Rnl5ObZu3dqm9nTdbkfH99xzzwF4vO4qe4yTK8aYwcnLy0NFRYXKAt6+vr4wMzN75lqPbTFo0CCYm5srdX0ZgqKiIhARzM3N1aofGxuL3r17Y/PmzTh+/LjK9rbeAzMzMwC/T6Z78eJFVFVVwdvbW1FHLBbD3t6+Tdd67969yMjIwKFDhyCRSJS2RUVFYcuWLThy5AgqKipw5coVBAQEwN/fH4WFha1uU5ft6iI++TN17969DondEHByxRgzOKWlpQAAS0tLlW3W1tYoLy9v1/aFQiGKi4vbtQ1tq6mpAYAWBzw/SSQSYfv27RAIBHjnnXdQXV2ttF3b96CyshIAsGzZMqWJha9fv6402FoTu3btwtq1a5GTkwMXFxelbXfu3EF8fDzef/99DBs2DBYWFnB1dUVqaipu376N9evXt6pNXbarq/jEYjGA358xxskVY8wAWVtbA0CTX+ClpaVwcnJqt7br6uravY32IP8C1GTSR39/fyxYsAD5+fkqKwho+x5069YNAJCYmKgyufCJEyc0OhYAbNy4EWlpaTh69CgcHR1Vtufn56OhoUFlm1Qqha2tLfLy8jRuU5ft6jK+2tpaAL8/Ywww0XUAjDGmKW9vb1haWuKXX35RKj958iRqa2vx4osvKspMTEyU1nFsq5ycHBAR/Pz82q2N9mBnZweBQICysjKN9lu1ahWys7Nx+vRpODs7K8o1uQfq6NmzJ0QiEXJzczXa72lEhCVLlqCkpARZWVkwMWn6a06e/N25c0epvLy8HA8fPlRMPaDv7epDfPJnqnv37lqO2nDxL1eMMYMjEokQERGBvXv3Ii0tDTKZDOfOncP/b+/eg6K68jyAfxtoaB7d8hKCIuEVXYkgk8iMoAxDMuMjzozxjWOypTEVhsyGQXF8RuOgwRBdoUxkE9FyqzSjvAxkKTFTMWGtTNTRGlGDlYT4iKhxUHk0IIbXb//I0pMWkG64cBvz/VT5R8499/5+fftq/9Ln9DlJSUnw8/NDYmKiqW9oaChqampQVFSE1tZW3Lp1q9u1hDw9PXHjxg1cuXIFDQ0NpmKpo6MDtbW1aGtrw7lz55CSkoKAgAAsXrxYkRilpaWDshSDi4sLgoODce3aNavO6xwevH99JGveA0vjLFmyBAcOHEB2djaMRiPa29tx7do10wd9QkICfH19H7j9zoULF/Dmm28iJycHWq22y/6l27ZtAwAEBQUhPj4eOTk5OHbsGJqbm1FVVWXKe+nSpaZr2nJcSw1Efp06n6nw8PB+5/mwYHFFREPSa6+9hvT0dKSlpcHb2xtxcXEIDAxEWVkZXF1dTf1efvllxMfHY+HChRgzZgw2bdpkGr744QTdpKQk+Pj4ICwsDM888wxqamoAfD+PJDw8HM7OzoiNjcXo0aPxySefmM1d6m+MwTJjxgxUVFSYzZ96//33ERoaiosXLyIqKgqvvPJKl/MmTpyI5cuXd2m35D3Izs5GZmYmACAiIgKXLl1CTk4OUlNTAQDTpk1DZWUlACArKwvLli1DRkYGvLy84Ofnh5SUFNTW1gL4fvipuroaxcXFPb5GsXCtJY1Gg/z8fCQkJGDp0qXw8PBAWFgYrl69isLCQsTGxpr62nJcADhx4gQmT56MESNG4OTJkzh79iz8/PwwadIkHDt2bMDy63Tq1CmMHDkSERERFsX4UVBnCYiBxXWuiIYWW9j+pjuJiYni6empdho9gpXrBFVWVoqDg4Ps27dvALMaOO3t7RIbGyt79uxhXBtx+/Zt0el0sm3bNqvPtfb5HUK4zhUR0YNYMwHc1oWGhiItLQ1paWlobGxUOx2rtLe3o6ioCA0NDUhISGBcG7Fx40ZERkYiOTlZ7VRsCosrIqIfkTVr1mDevHlISEiwenK7msrKylBYWIjS0lKL1+pi3IG1fft2lJeX4/Dhw9BqtWqnY1NYXBERdWPt2rXYu3cv6uvrERQUhIKCArVTUszrr7+O5ORkbNmyRe1ULPb000/jvffeM9vDkXHVU1xcjO+++w5lZWXw8PBQOx2bw6UYiIi6kZ6ejvT0dLXTGDBTpkzBlClT1E6DhqiZM2di5syZaqdhs/jNFREREZGCWFwRERERKYjFFREREZGCWFwRERERKeihndB+4sQJzJs3T+00iMgCndtn8O+s9TIzM5Gfn692GkT0Aw9lcRUdHa12CkRkBX9/f8ydO7fH4zdv3sSZM2cwffr0QczK9j3onhHZurlz5w7YRtVq04hYuOEQEZFK8vLysGDBAov3RyMiUlE+51wRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCWFwRERERKYjFFREREZGCHNROgIjoh1pbW9HY2GjW1tTUBACora01a9doNHB3dx+03IiILMHiiohsSk1NDUaOHIn29vYuxzw9Pc3+Oz4+Hh9//PFgpUZEZBEOCxKRTfH19cXPf/5z2Nk9+J8njUaDhQsXDlJWRESWY3FFRDbn+eef77WPvb09Zs+ePQjZEBFZh8UVEdmcOXPmwMGh51kL9vb2mDZtGry8vAYxKyIiy7C4IiKbYzAYMH369B4LLBHBc889N8hZERFZhsUVEdmk5557rttJ7QDg6OiIX//614OcERGRZVhcEZFN+vWvfw0XF5cu7VqtFrNmzYKrq6sKWRER9Y7FFRHZJJ1Oh9mzZ0Or1Zq1t7a2YtGiRSplRUTUOxZXRGSzfve736G1tdWszWAw4Fe/+pVKGRER9Y7FFRHZrF/+8pdmC4dqtVosXLgQjo6OKmZFRPRgLK6IyGY5ODhg4cKFpqHB1tZW/O53v1M5KyKiB2NxRUQ2beHChaahQV9fX0yePFnljIiIHozFFRHZtJiYGIwcORIA8O///u+9botDRKQ2btysoOPHj6OqqkrtNIgeOlFRUbh+/Tq8vLyQl5endjpED52YmBj4+/urncZDQyMionYSD4t58+ahoKBA7TSIiIiskpubi/nz56udxsMin99cKWzu3LnIz89XOw2iPsnLy8OCBQtgi//PVVBQgLlz56qdRrc0Gg0/nGjI0mg0aqfw0OHkBSIaEmy1sCIiuh+LKyIiIiIFsbgiIiIiUhCLKyIiIiIFsbgiIiIiUhCLKyIiIiIFsbgiIsUdPnwYw4YNw//8z/+onYrN++ijj7BmzRoUFhYiODgYGo0GGo0Gzz//fJe+U6ZMgV6vh729PR5//HH84x//UCFjy6WlpSEsLAwGgwFOTk4IDQ3FypUr0djY2KXvX/7yF0RFRUGv1+PRRx/FkiVLcPPmzSEVt1NHRwcyMzMRExMz4Pl98MEHyMjIQHt7e79yJoUJKWbu3Lkyd+5ctdMg6rPc3FxR4p+FkpISMRgM8sEHHyiQle0DILm5uVaft2HDBvnNb34jRqPR1BYSEiJeXl4CQEpKSrqcU1paKjNnzuxXvoMlLi5Odu7cKXfu3BGj0Si5ubmi1Wpl2rRpZv0OHjwoACQjI0Pq6urkzJkzEhwcLJGRkdLa2jpk4oqIfPXVVzJp0iQBIOPHjx+U/LKysiQuLk5qa2v7lHNfn1/qUR6LKwWxuKKhTqniypbcvXtXoqOjBzRGXz6ctmzZIqNHj5bm5maz9pCQEHnvvffEzs5ORo4cKXV1dWbHh1JxNWPGDGlrazNrmz9/vgCQq1evmtri4+NlxIgR0tHRYWp7++23BYB8+umnQyZueXm5zJ49W/bv3y+RkZE9FlcDkV9ycrJER0f3qShkcaW4PA4LEtFDbc+ePaiurlY7DTNff/011q9fjz//+c/Q6XRdjsfExCAlJQXXr1/HihUrVMhQGSUlJbC3tzdr8/b2BgDcvXvX1FZVVQU/Pz+zlcJHjRoFAPjmm2+GTNzx48ejsLAQixYtgpOT06Dmt3HjRpSXlyMrK8vqvEl5LK6ISFGffvopAgICoNFo8PbbbwMAsrOz4erqChcXFxQXF2P69OkwGAzw9/fHgQMHTOfu2LEDOp0OPj4++P3vfw8/Pz/odDrExMTg5MmTpn7JyclwdHTEI488Ymr7wx/+AFdXV2g0Gty+fRsAkJKSgtTUVFy8eBEajQahoaEAgCNHjsBgMOD1118fjFvSxY4dOyAi+O1vf9tjn82bN2P06NHYvXs3PvroowdeT0Swfft2jB07Fk5OTvDw8MCzzz6LL774wtTH0vcAANrb27FhwwYEBATA2dkZERERyM3N7d+L/n/Xr1+Hs7MzgoKCTG3BwcFdCuDOeUXBwcFDOu5g5efh4YG4uDhkZWXZ5PZVPzoqf3X2UOGwIA11Sg0LVlVVCQB56623TG3r1q0TAHL06FGpr6+X6upqiY2NFVdXV2lpaTH1S0xMFFdXV7lw4YLcu3dPKioqJCoqSvR6vdmQyaJFi8TX19cs7tatWwWA3Lp1y9Q2Z84cCQkJMetXUlIier1e0tLS+v1aRawfVgkODpawsLBuj4WEhMjly5dFROSzzz4TOzs7CQwMlMbGRhHpflhww4YN4ujoKPv27ZO6ujo5d+6cPPHEE+Lt7S03b9409bP0PVixYoU4OTlJQUGB1NbWytq1a8XOzk5OnTpl8WvsTlNTk+j1eklOTjZrLysrE61WKzt27BCj0Siff/65jB07VqZOndqveGrG/dnPftbjsOBA5bdmzRoBIGfOnLEqV2ufX+oVhwWJaHDFxMTAYDBg+PDhSEhIQFNTE65evWrWx8HBwfQtTFhYGLKzs9HQ0IC9e/cqksOMGTNgNBqxfv16Ra5njaamJly+fBkhISG99o2OjsayZctw5coVrF69uts+zc3N2L59O2bPno3nnnsOw4YNQ3h4ON555x3cvn0bu3bt6nLOg96De/fuITs7G7NmzcKcOXPg7u6OV199FVqttt/3Pz09HX5+fti8ebNZe1xcHFatWoXk5GQYDAaMGzcODQ0N2L17d7/iqR13sPN77LHHAADnz58f8JzpwVhcEZFqHB0dAQCtra0P7DdhwgS4uLiYDXMNVdXV1RARuLi4WNR/8+bNGDNmDHbu3IlPP/20y/GKigo0NjZiwoQJZu1RUVFwdHQ0G07tzv3vwZdffom7d+9i3Lhxpj7Ozs545JFH+nX/Dx06hLy8PHz44YfQ6/Vmx9atW4ddu3bh6NGjaGxsxKVLlxATE4Po6GhUVVX1OaaacdXIr/OZ+uc//zkouVPPWFwR0ZDg5OSEW7duqZ1Gv927dw8AHjjh+Yd0Oh327t0LjUaDF154Ac3NzWbH6+rqAABubm5dznV3d0dDQ4NV+TU1NQEAXn31VdOaWxqNBt98843ZZGtrHDx4EG+88QbKysoQGBhoduzbb79FRkYGXnrpJTz11FNwdXVFUFAQcnJycOPGDWzdurVPMdWMq1Z+zs7OAP71jJF6WFwRkc1rbW1FXV0d/P391U6l3zo/AK1Z9DE6OhrLly9HZWUlNm3aZHbM3d0dALotovpyz4YPHw4AyMzMhIiY/Tl+/LhV1wKAt956C/v378fHH3+MESNGdDleWVmJ9vb2LscMBgM8PT1RUVFhdUw146qZX0tLC4B/PWOkHge1EyAi6k1ZWRlEBBMnTjS1OTg49DqcaIt8fHyg0WhQX19v1XmbNm1CSUkJzpw5g4CAAFP7uHHj4ObmhtOnT5v1P3nyJFpaWvDkk09aFWfUqFHQ6XQoLy+36rz7iQhWr16N2tpaFBUVwcGh+4+bzuLv22+/NWtvaGhATU2NaekBW49rC/l1PlO+vr4KZ03W4jdXRGRzOjo6UFtbi7a2Npw7dw4pKSkICAjA4sWLTX1CQ0NRU1ODoqIitLa24tatW92uTeTp6YkbN27gypUraGhoQGtrK0pLS1VbisHFxQXBwcG4du2aVed1Dg/evz6STqdDamoqDh06hP3798NoNOL8+fNISkqCn58fEhMTrY6zZMkSHDhwANnZ2TAajWhvb8e1a9dMH/QJCQnw9fV94PY7Fy5cwJtvvomcnBxotVoTKwqdAAAVuElEQVSzIUaNRoNt27YBAIKCghAfH4+cnBwcO3YMzc3NqKqqMuW9dOlS0zVtOa6lBiK/Tp3PVHh4eL/zpP5hcUVEinr77bcRFRUFAFi1ahVmzpyJ7OxsZGZmAgAiIiJw6dIl5OTkIDU1FQAwbdo0VFZWmq5x7949hIeHw9nZGbGxsRg9ejQ++eQTs3lKL7/8MuLj47Fw4UKMGTMGmzZtMg2H/HDCb1JSEnx8fBAWFoZnnnkGNTU1g3IfHmTGjBmoqKgwmz/1/vvvIzQ0FBcvXkRUVBReeeWVLudNnDgRy5cv79L+2muvIT09HWlpafD29kZcXBwCAwNRVlYGV1dXALDqPcjKysKyZcuQkZEBLy8v+Pn5ISUlBbW1tQC+H36qrq5GcXFxj69RLFxrSaPRID8/HwkJCVi6dCk8PDwQFhaGq1evorCwELGxsaa+thwXAE6cOIHJkydjxIgROHnyJM6ePQs/Pz9MmjQJx44dG7D8Op06dQojR45ERESERTFoAKmzBMTDietc0VBnC9vfJCYmiqenp6o5WAtWrhNUWVkpDg4Osm/fvgHMauC0t7dLbGys7Nmzh3FtxO3bt0Wn08m2bdusPtfa55d6xXWuiMj2WDPZeygKDQ1FWloa0tLS0NjYqHY6Vmlvb0dRUREaGhqQkJDAuDZi48aNiIyMRHJystqpEDgsSD1IS0tDWFgYDAYDnJycEBoaipUrV/b6QfDiiy9Cr9dDo9H0aUJsX+P25ssvv8Qrr7yCxx9/HHq9Hg4ODhg2bBhGjx6NGTNm9OlXUEqz5LUXFhYiODi4yzwNR0dH+Pj44Be/+AW2bt1qGr4h27VmzRrMmzcPCQkJVk9uV1NZWRkKCwtRWlpq8VpdjDuwtm/fjvLychw+fBharVbtdAjgsKCSHqZhwbi4ONm5c6fcuXNHjEaj5ObmilarlWnTpvV67oEDB/q0BUN/4/Zk9+7dotVq5ec//7kcOXJEamtr5d69e3Lx4kU5ePCgxMTEyLvvvtvn6yvFmtceEhIiw4YNExGRjo4Oqa2tlU8++UQWL14sGo1G/Pz8+rRVidrDgmvWrBFHR0cBIIGBgZKfn69aLtZAP4ZVPvzwQ1m1apXCGdGPRVFRkaSnp0tbW1ufr9Gf55e6lcfiSkEPU3E1Y8aMLn9Z58+fLwDM9nfrTn+Kq/7E7c7x48fF3t5ennrqKWltbe22z5EjR8z2wFOLNa/9h8XV/fLz88XOzk58fHykrq7OqhzULq6GKn440VDG51dxnHNF3SspKenyk29vb28A6HWVZo1Go0rc7mzevBnt7e3YsmVLj+vJTJ06Ff/xH/9hfbIKU+q1z507F4sXL0Z1dTXeeecdRXMkIqLesbiyAfv27cOECROg0+ng6uqKwMBA0yrMIoLt27ebNrH18PDAs88+a7bHV3Z2NlxdXeHi4oLi4mJMnz4dBoMB/v7+OHDggKnf2LFjodFoYGdnhyeffNL0gb1y5UoMGzYMOp0O//3f/91jntevX4ezszOCgoJMbSKCrVu3YsyYMXBycsKwYcPwpz/9SdH7013cI0eO9LpOUUtLC44ePQovLy/89Kc/tTierd9zS3SuB1VaWmrVeUREpACVvzp7qPRlWDAzM1MAyJYtW+TOnTtSU1Mj7777rixatEhERDZs2CCOjo6yb98+qaurk3PnzskTTzwh3t7ecvPmTdN11q1bJwDk6NGjUl9fL9XV1RIbGyuurq7S0tIiIiJtbW0SGBgoAQEBXYafli1bJpmZmT3m2dTUJHq9XpKTk83a161bJxqNRv7zP/9Tamtr5e7du7Jz584+DwtaGrekpET0er2kpaX1eO5XX30lAGTixIlWxbT1ey7y4GFBERGj0SgAZNSoUVa9dg4L9g04rEJDGJ9fxXHOlZKsLa5aWlrE3d1d4uPjzdrb2tokKytL7t69K25ubpKQkGB2/O9//7sAMCssOj/om5ubTW2dRc7XX39tauss5vLy8kxtTU1NEhAQIPX19T3mum7dOhk9erQYjUZT2927d8XFxUV+9atfmfXtz5wrS+Ja6vTp0wJAfvnLX1p8jq3f8069FVciIhqNRtzd3R/Y534srvqGH040lPH5VVwe9xZU0blz51BXV4epU6eatdvb2+OPf/wjTp8+jcbGRkyYMMHseFRUFBwdHXHy5MkHXt/R0REAzPZfe/HFF7Fx40ZkZWVh3rx5AID9+/fj2WefhcFg6PY6hw4dQl5eHv76179Cr9eb2r/++mvcvXsXTz/9tOUv2go9xbWUm5sbAOvmK1VUVNj0PbdUU1MTRKTH6/emM0+yXGZmJvLz89VOg4hsAOdcqchoNAL4167296urqwPwryLhh9zd3dHQ0GB1TDc3N7z00kv47LPP8Pe//x0A8F//9V89Ljx38OBBvPHGGygrK0NgYKDZsc59rIYPH251Hr15UFxLBQYGQqfT4auvvrL4HFu/55bqfM3/9m//1qfziYio7/jNlYpGjBgBALh9+3a3xzuLru4+0Ovq6ky7plsrOTkZWVlZyMzMRFJSEkaNGoWQkJAu/d566y18+OGH+Pjjj7stNnQ6HQDgu+++61MePektrqWcnJwwdepUFBcX429/+xsmTZrUbb+amhqsXLkSu3fvtvl7bqkjR44AAKZPn96n8/kNjHU0Gg2WLVuG+fPnq50KkdX68wtv6h6/uVJRYGAgPD098de//rXb4+PGjYObmxtOnz5t1n7y5Em0tLTgySef7FNcf39/zJ8/HwUFBVi/fj1SUlLMjosIVq1ahfPnz6OoqKjHD/lx48bBzs4O//u//9unPO5naVxrbNy4EU5OTli+fLnZJrk/9Pnnn5uWabD1e26JmzdvIjMzE/7+/njhhRf6fB0iIuobFlcqcnJywtq1a3Hs2DEkJyfj+vXr6OjoQENDAy5cuACdTofU1FQcOnQI+/fvh9FoxPnz55GUlAQ/Pz8kJib2OXZqaira2tpQW1uLp556yuzYhQsX8OabbyInJwdarbbLVivbtm0D8P1w4Jw5c1BQUIA9e/bAaDTi3Llz2LVrV59ysjQu8P0SA70txQAAkZGReO+99/D5558jNjYWhw8fRn19PVpbW3H58mXk5ORg6dKlpi0jbP2e/5CIoLGxER0dHRAR3Lp1C7m5uZg0aRLs7e1RVFTU5zlXRETUD2pOp3/Y9HWF9rffflvCw8NFp9OJTqeTn/zkJ7Jz504R+X5rk61bt8pjjz0mWq1WPDw8ZNasWfLll1+azt+5c6e4uLgIAHnsscfk4sWLsmvXLjEYDAJAHn30Ufnqq6+6xI2Pj5fdu3d3aT9//rwA6PHP1q1bTX0bGhrkxRdfFC8vL3Fzc5PJkyfLhg0bBID4+/vL2bNnLb4P1sQ9fPiw6PV62bx5s0XXvnr1qqxYsULCw8PFzc1N7O3txd3dXX7yk5/I0qVL5W9/+5upry3f8w8++EAiIiLExcVFHB0dxc7OTgCYfhn405/+VNLS0uTOnTsW3/cf4q8F+wb8tRUNYXx+FZenEREZjCLux6DzF1acr0JDVV5eHhYsWAD+s2AdjUaD3NxczrmiIYnPr+LyOSxIREREpCAWVzSgvvjiiy7zh7r7k5CQoHaqRDbto48+wpo1a1BYWIjg4GDT353nn3++S98pU6ZAr9fD3t4ejz/+OP7xj3+okLHl0tLSEBYWBoPBACcnJ4SGhmLlypVobGzs0vcvf/kLoqKioNfr8eijj2LJkiW4efPmkIrbqaOjA5mZmYiJiely7IMPPkBGRgba29v7FYNUovK45EOlr3OuiGwF51z1DQZ4zsqGDRvkN7/5jdlq/SEhIeLl5SUApKSkpMs5paWlMnPmzAHLSUlxcXGyc+dOuXPnjhiNRsnNzRWtVivTpk0z63fw4EEBIBkZGVJXVydnzpyR4OBgiYyMlNbW1iETV+T77bkmTZokAGT8+PHd9snKypK4uDipra3tUwxLDfTz+yOUx2+uiMimNDc3d/t/8kMthlLeeOMNHDx4EHl5eV1W69+xYwfs7OyQmJiI+vp6lTLsPzc3NyQmJsLT0xN6vR7z58/HrFmzcOTIEVRVVZn6vfvuuxgxYgT+9Kc/YdiwYYiMjMTy5ctRXl7e6+4JthT37NmzWL16NZKSkhAZGdljvz/+8Y8YP348nnnmGbS1tVkdh9TD4oqIbMqePXtQXV095GMo4euvv8b69evx5z//2bRo7w/FxMQgJSUF169fx4oVK1TIUBklJSWwt7c3a/P29gZgvn1VVVUV/Pz8zBa9HDVqFADgm2++GTJxx48fj8LCQixatAhOTk4P7Ltx40aUl5cjKyvL6jikHhZXRNQvIoLt27dj7NixcHJygoeHB5599ll88cUXpj7JyclwdHTEI488Ymr7wx/+AFdXV2g0GtMuBSkpKUhNTcXFixeh0WgQGhqKHTt2QKfTwcfHB7///e/h5+cHnU6HmJgYs28N+hMD+H5Ve0vWThtMO3bsgIjgt7/9bY99Nm/ejNGjR2P37t346KOPHng9S96r7OxsuLq6wsXFBcXFxZg+fToMBgP8/f1x4MABs+u1t7djw4YNCAgIgLOzMyIiIpCbm9u/F/3/rl+/DmdnZwQFBZnagoODuxTFnfOegoODh3Tcnnh4eCAuLg5ZWVn8Fe9Qou6w5MOFc65oqOvLnKsNGzaIo6Oj7Nu3T+rq6uTcuXPyxBNPiLe3t9y8edPUb9GiReLr62t27tatWwWA3Lp1y9Q2Z84cCQkJMeuXmJgorq6ucuHCBbl3755UVFRIVFSU6PV6uXr1qiIxSkpKRK/XS1pamlWvX2Tg5qwEBwdLWFhYt8dCQkLk8uXLIiLy2WefiZ2dnQQGBkpjY6OIdD/nytL3at26dQJAjh49KvX19VJdXS2xsbHi6uoqLS0tpn4rVqwQJycnKSgokNraWlm7dq3Y2dnJqVOn+vW6m5qaRK/XS3Jysll7WVmZaLVa2bFjhxiNRvn8889l7NixMnXq1H7FUzPuz372sx7nXHVas2aNAJAzZ870O153Bur5/RHjnCsi6rvm5mZs374ds2fPxnPPPYdhw4YhPDwc77zzDm7fvt3n1fq74+DgYPrGJSwsDNnZ2WhoaMDevXsVuf6MGTNgNBqxfv16Ra7XX01NTbh8+XK3e1DeLzo6GsuWLcOVK1ewevXqbvv05b2KiYmBwWDA8OHDkZCQgKamJly9ehUAcO/ePWRnZ2PWrFmYM2cO3N3d8eqrr0Kr1fb7PUlPT4efnx82b95s1h4XF4dVq1YhOTkZBoMB48aNQ0NDA3bv3t2veGrH7c1jjz0GADh//vygxKP+Y3FFRH1WUVGBxsZGTJgwwaw9KioKjo6OfZrsa6kJEybAxcXFbEjrYVJdXQ0RgYuLi0X9N2/ejDFjxmDnzp349NNPuxzv73vl6OgIAGhtbQUAfPnll7h79y7GjRtn6uPs7IxHHnmkX+/JoUOHkJeXhw8//LDLBP5169Zh165dOHr0KBobG3Hp0iXExMQgOjrabAL6UIpric5n4J///OeAxyJlsLgioj6rq6sDgG43mnZ3d0dDQ8OAxndycsKtW7cGNIZa7t27BwC9TnjupNPpsHfvXmg0GrzwwgtdNipX+r1qamoCALz66qtma9Z98803ZpPBrXHw4EG88cYbKCsrQ2BgoNmxb7/9FhkZGXjppZfw1FNPwdXVFUFBQcjJycGNGzewdevWPsVUM66lnJ2dAfzrmSDbx+KKiPrM3d0dALr9YK6rq4O/v/+AxW5tbR3wGGrq/EC1ZhHJ6OhoLF++HJWVldi0aZPZMaXfq+HDhwMAMjMzISJmf44fP27VtQDgrbfewv79+/Hxxx9jxIgRXY5XVlaivb29yzGDwQBPT09UVFRYHVPNuNZoaWkB8K9ngmyfg9oJENHQNW7cOLi5ueH06dNm7SdPnkRLSwuefPJJU5uDg4NpSEkJZWVlEBFMnDhxwGKoycfHBxqNxur1qzZt2oSSkhKcOXMGAQEBpnZr3itLjBo1CjqdDuXl5Vaddz8RwerVq1FbW4uioiI4OHT/sdRZ/H377bdm7Q0NDaipqTEtjWDrcfui8xnw9fUd8FikDH5zRUR9ptPpkJqaikOHDmH//v0wGo04f/48kpKS4Ofnh8TERFPf0NBQ1NTUoKioCK2trbh161a3awR5enrixo0buHLlChoaGkzFUkdHB2pra9HW1oZz584hJSUFAQEBWLx4sSIxSktLbWopBhcXFwQHB+PatWtWndc5PHj/+k3WvFeWxlmyZAkOHDiA7OxsGI1GtLe349q1a6ZCJCEhAb6+vg/cfufChQt48803kZOTA61W22VrrG3btgEAgoKCEB8fj5ycHBw7dgzNzc2oqqoy5b106VLTNW05bl90PgPh4eGKXpcGDosrIuqX1157Denp6UhLS4O3tzfi4uIQGBiIsrIyuLq6mvq9/PLLiI+Px8KFCzFmzBhs2rTJNMzxw4nBSUlJ8PHxQVhYGJ555hnU1NQA+H6+SXh4OJydnREbG4vRo0fjk08+MZuT1N8YtmbGjBmoqKgwmz/1/vvvIzQ0FBcvXkRUVBReeeWVLudNnDgRy5cv79JuyXuVnZ2NzMxMAEBERAQuXbqEnJwcpKamAgCmTZuGyspKAEBWVhaWLVuGjIwMeHl5wc/PDykpKaitrQXw/XBWdXU1iouLe3yNYuHaTRqNBvn5+UhISMDSpUvh4eGBsLAwXL16FYWFhYiNjTX1teW4AHDixAlMnjwZI0aMwMmTJ3H27Fn4+flh0qRJOHbsWJf+p06dwsiRIxEREWFRzmQD1FoE4mHEda5oqLPVvQUTExPF09NT7TR6hAFaJ6iyslIcHBxk3759il97MLS3t0tsbKzs2bOHcfvo9u3botPpZNu2bYpd834D9fz+iHGdKyIaGqyZ2P2wCA0NRVpaGtLS0tDY2Kh2OlZpb29HUVERGhoakJCQwLh9tHHjRkRGRiI5OVmxa9LAY3FFRGTD1qxZg3nz5iEhIWFIbc5cVlaGwsJClJaWWrxWF+Oa2759O8rLy3H48GFotVpFrkmDg8UVEdm0tWvXYu/evaivr0dQUBAKCgrUTmnQvf7660hOTsaWLVvUTsViTz/9NN577z2zvR4Z13LFxcX47rvvUFZWBg8PD0WuSYOHSzEQkU1LT09Henq62mmobsqUKZgyZYraadAgmTlzJmbOnKl2GtRH/OaKiIiISEEsroiIiIgUxOKKiIiISEEsroiIiIgUxOKKiIiISEH8taDCCgoKoNFo1E6DqF/4DFtvwYIFWLBggdppEJEN0IhYuMES9er48eOmvcuIiIiGipiYGPj7+6udxsMin8UVERERkXLyOeeKiIiISEEsroiIiIgUxOKKiIiISEEOAPLVToKIiIjoIXHi/wCq/70S/peBEwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YStCuU-BwXaW"
      },
      "source": [
        "Generating the Latent Points for the Generating model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k3JRK6CF_xhr"
      },
      "source": [
        "def generate_latent_points(latent_dim,n_samples):\r\n",
        "    x_input=np.random.randn(latent_dim*n_samples)\r\n",
        "    x_input=x_input.reshape(n_samples,latent_dim)\r\n",
        "    return x_input\r\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iV4W3vQVwg9X"
      },
      "source": [
        "Modifying the fake Sample Generating function to include the generator Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ixWjuW19_ziT"
      },
      "source": [
        "def generate_fake_samples(g_model,latent_dim,n_samples):\r\n",
        "    x_input=generate_latent_points(latent_dim,n_samples)\r\n",
        "    X=g_model.predict(x_input)\r\n",
        "    y=np.zeros((n_samples,1))\r\n",
        "    return X,y"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6CsM8LlEwuAy"
      },
      "source": [
        "Showing how the Generated Samples Looks Like Before Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "UpLOJb9s_1eQ",
        "outputId": "df07a185-0ec0-413f-d8ac-fc9434df87f5"
      },
      "source": [
        "latent_dim=100\r\n",
        "model=define_generator(latent_dim)\r\n",
        "n_samples=25\r\n",
        "X,_=generate_fake_samples(model,latent_dim,n_samples)\r\n",
        "\r\n",
        "for i in range(n_samples):\r\n",
        "    plt.subplot(5,5,i+1)\r\n",
        "    plt.axis('off')\r\n",
        "    plt.imshow(X[i,:,:,0],cmap='gray_r')\r\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 25 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sJaQUQLf_3VZ"
      },
      "source": [
        "g_model=model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jFjz779Fw62w"
      },
      "source": [
        "Defining the GAN Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G_Fa0XG4ADQt"
      },
      "source": [
        "def define_gan(d_model,g_model):\r\n",
        "    d_model.trainable=False\r\n",
        "    model=Sequential()\r\n",
        "    model.add(g_model)\r\n",
        "    model.add(d_model)\r\n",
        "    opt=Adam(lr=0.0002,beta_1=0.5)\r\n",
        "    model.compile(loss='binary_crossentropy',optimizer=opt)\r\n",
        "    return model"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lz0cz5X6AGZP"
      },
      "source": [
        "d_model=define_discriminator()\r\n",
        "g_model=define_generator()\r\n",
        "gan_model=define_gan(d_model,g_model)"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7UQV2YdvAIAi",
        "outputId": "d9d26e7b-9845-4c52-82b8-17771f85ea6d"
      },
      "source": [
        "gan_model.summary()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_8\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "sequential_7 (Sequential)    (None, 28, 28, 1)         1164289   \n",
            "_________________________________________________________________\n",
            "sequential_6 (Sequential)    (None, 1)                 40705     \n",
            "=================================================================\n",
            "Total params: 1,204,994\n",
            "Trainable params: 1,164,289\n",
            "Non-trainable params: 40,705\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "id": "fIq7rZiOmDhH",
        "outputId": "1c151b28-3c88-4ba2-bcbe-fd68deb5b4e4"
      },
      "source": [
        "plot_model(gan_model,to_file='GAN_plot.png',show_shapes=True,show_layer_names=True)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "orpZcax2AJlQ"
      },
      "source": [
        "def train_gan(gan_model,latent_dim,n_epochs=100,n_batch=256):\r\n",
        "    for i in range(n_epochs):\r\n",
        "        x_gan=generate_latent_points(latent_dim,n_batch)\r\n",
        "        y_gan=np.ones((n_batch,1))\r\n",
        "        gan_model.train_on_batch(x_gan,y_gan)\r\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gpteyushw-hT"
      },
      "source": [
        "Defining the Train Function"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lH6Df76eALZ5"
      },
      "source": [
        "def train(g_model,gan_model,d_model,dataset,latent_dim,n_epochs=100,n_batch=256):\r\n",
        "    bat_per_epo=int(dataset.shape[0]/n_batch)\r\n",
        "    half_batch=int(n_batch/2)\r\n",
        "    for i in range(n_epochs):\r\n",
        "        print('epoch:'+str(i+1))\r\n",
        "        for j in range(bat_per_epo):\r\n",
        "            # print(str(j)+'/'+str(bat_per_epo))\r\n",
        "            X_real,y_real=generate_real_samples(dataset,half_batch)\r\n",
        "            X_fake,y_fake=generate_fake_samples(g_model,latent_dim,half_batch)\r\n",
        "            X,y=np.vstack((X_real, X_fake)), np.vstack((y_real, y_fake))\r\n",
        "            d_loss, _ = d_model.train_on_batch(X, y)\r\n",
        "            # gan_model=update_gan(d_model,gan_model)\r\n",
        "            X_gan=generate_latent_points(latent_dim,n_batch)\r\n",
        "            y_gan=np.ones((n_batch,1))\r\n",
        "            g_loss=gan_model.train_on_batch(X_gan,y_gan)\r\n",
        "        if (i+1)%10==0:\r\n",
        "            summarize_performance(i,g_model,d_model,dataset,latent_dim)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "258dYYfeAZsi"
      },
      "source": [
        "def summarize_performance(epoch,g_model,d_model,dataset,latent_dim,n_samples=100):\r\n",
        "    X_real,y_real=generate_real_samples(dataset,n_samples)\r\n",
        "    _,acc_real=d_model.evaluate(X_real,y_real,verbose=1)\r\n",
        "    X_fake,y_fake=generate_fake_samples(g_model,latent_dim,n_samples)\r\n",
        "    _,acc_fake=d_model.evaluate(X_fake,y_fake,verbose=1)\r\n",
        "    print('>Accuracy real: %.0f%%, fake: %.0f%%' % (acc_real*100, acc_fake*100))\r\n",
        "    save_plot(X_fake,epoch)\r\n",
        "    filename='generator_model_%03d.h5'%(epoch+1)\r\n",
        "    g_model.save(filename)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8BA7f8teAckI"
      },
      "source": [
        "def save_plot(examples,epoch,n=10):\r\n",
        "    for i in range(n*n):\r\n",
        "        plt.subplot(n,n,1+i)\r\n",
        "        plt.axis('off')\r\n",
        "        plt.imshow(examples[i,:,:,0],cmap='gray_r')\r\n",
        "    filename='generated_plot_e%03d.png'%(epoch+1)\r\n",
        "    plt.savefig(filename)\r\n",
        "    plt.close()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TLzW7k93xC1_"
      },
      "source": [
        "The Training Operation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3WSwOpDOAeW4",
        "outputId": "4cad9e5c-d6ba-4fad-ba23-c45799c3fd78"
      },
      "source": [
        "latent_dim=100\r\n",
        "d_model=define_discriminator()\r\n",
        "g_model=define_generator(latent_dim)\r\n",
        "gan_model=define_gan(d_model,g_model)\r\n",
        "dataset=load_real_samples()\r\n",
        "train(g_model,gan_model,d_model,dataset,latent_dim)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "epoch:1\n",
            "epoch:2\n",
            "epoch:3\n",
            "epoch:4\n",
            "epoch:5\n",
            "epoch:6\n",
            "epoch:7\n",
            "epoch:8\n",
            "epoch:9\n",
            "epoch:10\n",
            "4/4 [==============================] - 0s 8ms/step - loss: 0.6568 - accuracy: 0.9000\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.7080 - accuracy: 0.3700\n",
            ">Accuracy real: 90%, fake: 37%\n",
            "epoch:11\n",
            "epoch:12\n",
            "epoch:13\n",
            "epoch:14\n",
            "epoch:15\n",
            "epoch:16\n",
            "epoch:17\n",
            "epoch:18\n",
            "epoch:19\n",
            "epoch:20\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6723 - accuracy: 0.7700\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6962 - accuracy: 0.4500\n",
            ">Accuracy real: 77%, fake: 45%\n",
            "epoch:21\n",
            "epoch:22\n",
            "epoch:23\n",
            "epoch:24\n",
            "epoch:25\n",
            "epoch:26\n",
            "epoch:27\n",
            "epoch:28\n",
            "epoch:29\n",
            "epoch:30\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6818 - accuracy: 0.6900\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.6824 - accuracy: 0.6900\n",
            ">Accuracy real: 69%, fake: 69%\n",
            "epoch:31\n",
            "epoch:32\n",
            "epoch:33\n",
            "epoch:34\n",
            "epoch:35\n",
            "epoch:36\n",
            "epoch:37\n",
            "epoch:38\n",
            "epoch:39\n",
            "epoch:40\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6381 - accuracy: 0.9600\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.7206 - accuracy: 0.1300\n",
            ">Accuracy real: 96%, fake: 13%\n",
            "epoch:41\n",
            "epoch:42\n",
            "epoch:43\n",
            "epoch:44\n",
            "epoch:45\n",
            "epoch:46\n",
            "epoch:47\n",
            "epoch:48\n",
            "epoch:49\n",
            "epoch:50\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6865 - accuracy: 0.6000\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.6791 - accuracy: 0.7400\n",
            ">Accuracy real: 60%, fake: 74%\n",
            "epoch:51\n",
            "epoch:52\n",
            "epoch:53\n",
            "epoch:54\n",
            "epoch:55\n",
            "epoch:56\n",
            "epoch:57\n",
            "epoch:58\n",
            "epoch:59\n",
            "epoch:60\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6820 - accuracy: 0.7400\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.6887 - accuracy: 0.5500\n",
            ">Accuracy real: 74%, fake: 55%\n",
            "epoch:61\n",
            "epoch:62\n",
            "epoch:63\n",
            "epoch:64\n",
            "epoch:65\n",
            "epoch:66\n",
            "epoch:67\n",
            "epoch:68\n",
            "epoch:69\n",
            "epoch:70\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6913 - accuracy: 0.5900\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6847 - accuracy: 0.7500\n",
            ">Accuracy real: 59%, fake: 75%\n",
            "epoch:71\n",
            "epoch:72\n",
            "epoch:73\n",
            "epoch:74\n",
            "epoch:75\n",
            "epoch:76\n",
            "epoch:77\n",
            "epoch:78\n",
            "epoch:79\n",
            "epoch:80\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.7043 - accuracy: 0.2700\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6742 - accuracy: 0.8800\n",
            ">Accuracy real: 27%, fake: 88%\n",
            "epoch:81\n",
            "epoch:82\n",
            "epoch:83\n",
            "epoch:84\n",
            "epoch:85\n",
            "epoch:86\n",
            "epoch:87\n",
            "epoch:88\n",
            "epoch:89\n",
            "epoch:90\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6877 - accuracy: 0.6100\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.6928 - accuracy: 0.5000\n",
            ">Accuracy real: 61%, fake: 50%\n",
            "epoch:91\n",
            "epoch:92\n",
            "epoch:93\n",
            "epoch:94\n",
            "epoch:95\n",
            "epoch:96\n",
            "epoch:97\n",
            "epoch:98\n",
            "epoch:99\n",
            "epoch:100\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.7162 - accuracy: 0.0700\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.6651 - accuracy: 0.9800\n",
            ">Accuracy real: 7%, fake: 98%\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}