multitask-learning-cnn-cifar100.ipynb

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   "source": [
    "# Mullti-task Learning on Cifar100 Dataset: A CNN Approach\n",
    "- Name: Minh T. Nguyen, Peter Chen\n",
    "- ECE 6524 - Final Project\n",
    "- Date: 4/14/2023\n",
    "- **Objective**: Build a MTL model for image classification.\n",
    "    - Task 1: Normal class classification (100 Classes).\n",
    "    - Task 2: Superclass classification (20 Classes).\n",
    "    \n",
    "- **To Do**:\n",
    "    - Experience with Different Model Configuration: \n",
    "        - Optimizers\n",
    "        - Regularization: Dropout"
   ]
  },
  {
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   },
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   "source": [
    "# import libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# import tensorflow\n",
    "import tensorflow as tf\n",
    "from keras.datasets import cifar100\n",
    "from keras.utils import np_utils, plot_model\n",
    "from keras.layers import Input, Dropout, Flatten, Dense\n",
    "from keras.applications.resnet import ResNet152, preprocess_input\n",
    "from keras import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ccd11082",
   "metadata": {
    "execution": {
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    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.11.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.version.VERSION"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41889d85",
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    },
    "tags": []
   },
   "source": [
    "# 1. Data Visualization & Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d67b7b86",
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 1.1 Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "03e6b48e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:21:59.557208Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz\n",
      "169001437/169001437 [==============================] - 6s 0us/step\n"
     ]
    }
   ],
   "source": [
    "# download data from Keras API\n",
    "(X_train, y_train), (X_test, y_test) = cifar100.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "494b91e5",
   "metadata": {
    "execution": {
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    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X=(50000, 32, 32, 3), y=(50000, 1)\n",
      "X=(10000, 32, 32, 3), y=(10000, 1)\n"
     ]
    }
   ],
   "source": [
    "# check dataset size\n",
    "print(f\"X={X_train.shape}, y={y_train.shape}\")\n",
    "print(f\"X={X_test.shape}, y={y_test.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4f1fb709",
   "metadata": {
    "execution": {
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    },
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   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the 9 images\n",
    "f, axarr = plt.subplots(3,3)\n",
    "axarr[0,0].imshow(X_train[10])\n",
    "axarr[0,1].imshow(X_train[11])\n",
    "axarr[0,2].imshow(X_train[12])\n",
    "axarr[1,0].imshow(X_train[13])\n",
    "axarr[1,1].imshow(X_train[14])\n",
    "axarr[1,2].imshow(X_train[15])\n",
    "axarr[2,0].imshow(X_train[16])\n",
    "axarr[2,1].imshow(X_train[17])\n",
    "axarr[2,2].imshow(X_train[18])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f71a9b8f",
   "metadata": {
    "papermill": {
     "duration": 0.017144,
     "end_time": "2023-04-23T16:22:09.609676",
     "exception": false,
     "start_time": "2023-04-23T16:22:09.592532",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 1.2. Creating Superclasses\n",
    "\n",
    "**Superclass**\n",
    "* aquatic mammals\n",
    "* fish\n",
    "* flowers\n",
    "* food containers\n",
    "* fruit and vegetables\n",
    "* household electrical devices\n",
    "* household furniture\n",
    "* insects\n",
    "* large carnivores\n",
    "* large man-made outdoor things\n",
    "* large natural outdoor scenes\n",
    "* large omnivores and herbivores\n",
    "* medium-sized mammals\n",
    "* non-insect invertebrates\n",
    "* people\n",
    "* reptiles\n",
    "* small mammals\n",
    "* trees\n",
    "* vehicles 1\n",
    "* vehicles 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a172523",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:09.655742Z",
     "iopub.status.busy": "2023-04-23T16:22:09.655428Z",
     "iopub.status.idle": "2023-04-23T16:22:10.382431Z",
     "shell.execute_reply": "2023-04-23T16:22:10.381308Z"
    },
    "papermill": {
     "duration": 0.758014,
     "end_time": "2023-04-23T16:22:10.385375",
     "exception": false,
     "start_time": "2023-04-23T16:22:09.627361",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# generate super-class of CIFAR100 dataset\n",
    "(X_train_super, y_train_super), (X_test_super, y_test_super) = cifar100.load_data(label_mode = 'coarse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1a4e9c65",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:10.421863Z",
     "iopub.status.busy": "2023-04-23T16:22:10.421556Z",
     "iopub.status.idle": "2023-04-23T16:22:10.426935Z",
     "shell.execute_reply": "2023-04-23T16:22:10.425871Z"
    },
    "papermill": {
     "duration": 0.026381,
     "end_time": "2023-04-23T16:22:10.429432",
     "exception": false,
     "start_time": "2023-04-23T16:22:10.403051",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 5]\n",
      " [17]\n",
      " [ 2]\n",
      " [ 9]\n",
      " [10]\n",
      " [ 5]\n",
      " [18]\n",
      " [ 8]\n",
      " [16]]\n"
     ]
    }
   ],
   "source": [
    "# check labels for accuracy (referencing image plotted above)\n",
    "print(y_train_super[10:19])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fc28383",
   "metadata": {
    "papermill": {
     "duration": 0.017142,
     "end_time": "2023-04-23T16:22:10.464454",
     "exception": false,
     "start_time": "2023-04-23T16:22:10.447312",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 1.3. Data Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6cf4ddbc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:10.500963Z",
     "iopub.status.busy": "2023-04-23T16:22:10.500061Z",
     "iopub.status.idle": "2023-04-23T16:22:10.926665Z",
     "shell.execute_reply": "2023-04-23T16:22:10.925453Z"
    },
    "papermill": {
     "duration": 0.447104,
     "end_time": "2023-04-23T16:22:10.928899",
     "exception": false,
     "start_time": "2023-04-23T16:22:10.481795",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape:  (50000, 32, 32, 3)\n",
      "X_test shape:  (10000, 32, 32, 3)\n",
      "\n",
      "y_train shape:  (50000, 100)\n",
      "y_test shape:  (10000, 100)\n",
      "\n",
      "y_train_super shape:  (50000, 20)\n",
      "y_test_super shape:  (10000, 20)\n"
     ]
    }
   ],
   "source": [
    "# normalize input data\n",
    "X_train = preprocess_input(X_train)\n",
    "X_test = preprocess_input(X_test)\n",
    "\n",
    "print('X_train shape: ', X_train.shape)\n",
    "print('X_test shape: ', X_test.shape)\n",
    "\n",
    "# convert class into one hot encoder\n",
    "y_train = np_utils.to_categorical(y_train)\n",
    "y_test = np_utils.to_categorical(y_test)\n",
    "\n",
    "print('\\ny_train shape: ', y_train.shape)\n",
    "print('y_test shape: ', y_test.shape)\n",
    "\n",
    "# convert class into one hot encoder\n",
    "y_train_super = np_utils.to_categorical(y_train_super)\n",
    "y_test_super = np_utils.to_categorical(y_test_super)\n",
    "\n",
    "print('\\ny_train_super shape: ', y_train_super.shape)\n",
    "print('y_test_super shape: ', y_test_super.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d342a32",
   "metadata": {
    "papermill": {
     "duration": 0.017487,
     "end_time": "2023-04-23T16:22:10.964163",
     "exception": false,
     "start_time": "2023-04-23T16:22:10.946676",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 2. Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d65ec6fe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:11.001067Z",
     "iopub.status.busy": "2023-04-23T16:22:11.000000Z",
     "iopub.status.idle": "2023-04-23T16:22:11.009478Z",
     "shell.execute_reply": "2023-04-23T16:22:11.008514Z"
    },
    "papermill": {
     "duration": 0.030054,
     "end_time": "2023-04-23T16:22:11.011579",
     "exception": false,
     "start_time": "2023-04-23T16:22:10.981525",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Define ResNet152 CNN model\n",
    "def create_model(dropout):\n",
    "    input_shape = (32, 32, 3)\n",
    "    \n",
    "    resnet152_base = ResNet152(weights=None, include_top=False, input_shape=input_shape)\n",
    "    \n",
    "    \n",
    "    # shared back-bone: convolution - feature extractor\n",
    "    inputs = Input(shape=input_shape, name='input')\n",
    "    shared_branch = resnet152_base(inputs)\n",
    "    shared_branch = Flatten()(shared_branch)\n",
    "    shared_branch = Dense(2048, activation='relu')(shared_branch)\n",
    "    \n",
    "    # task 1 branch - fully connected for 100-class classification\n",
    "    task_1_branch = Dense(1024, activation='relu')(shared_branch)\n",
    "    task_1_branch = Dropout(dropout)(task_1_branch) \n",
    "    task_1_branch = Dense(512, activation=\"relu\")(task_1_branch)\n",
    "    task_1_branch = Dense(256, activation=\"relu\")(task_1_branch)\n",
    "    task_1_branch = Dense(128, activation=\"relu\")(task_1_branch)\n",
    "    task_1_branch = Dense(100, activation=\"softmax\", name=\"task_1_output\")(task_1_branch)\n",
    "    \n",
    "    # task 1 branch - fully connected for 20-class superclass classification\n",
    "    task_2_branch = Dense(512, activation='relu')(shared_branch)\n",
    "    task_2_branch = Dropout(dropout)(task_2_branch)\n",
    "    task_2_branch = Dense(256, activation=\"relu\")(task_2_branch)\n",
    "    task_2_branch = Dense(128, activation=\"relu\")(task_2_branch)\n",
    "    task_2_branch = Dense(20, activation=\"softmax\", name=\"task_2_output\")(task_2_branch)\n",
    "    \n",
    "    # modeling\n",
    "    model = Model(inputs=inputs, outputs=[task_1_branch, task_2_branch])\n",
    "    \n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c65d2aeb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:11.053939Z",
     "iopub.status.busy": "2023-04-23T16:22:11.053287Z",
     "iopub.status.idle": "2023-04-23T16:22:19.027810Z",
     "shell.execute_reply": "2023-04-23T16:22:19.026578Z"
    },
    "papermill": {
     "duration": 7.999478,
     "end_time": "2023-04-23T16:22:19.030583",
     "exception": false,
     "start_time": "2023-04-23T16:22:11.031105",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " input (InputLayer)             [(None, 32, 32, 3)]  0           []                               \n",
      "                                                                                                  \n",
      " resnet152 (Functional)         (None, 1, 1, 2048)   58370944    ['input[0][0]']                  \n",
      "                                                                                                  \n",
      " flatten (Flatten)              (None, 2048)         0           ['resnet152[0][0]']              \n",
      "                                                                                                  \n",
      " dense (Dense)                  (None, 2048)         4196352     ['flatten[0][0]']                \n",
      "                                                                                                  \n",
      " dense_1 (Dense)                (None, 1024)         2098176     ['dense[0][0]']                  \n",
      "                                                                                                  \n",
      " dropout (Dropout)              (None, 1024)         0           ['dense_1[0][0]']                \n",
      "                                                                                                  \n",
      " dense_5 (Dense)                (None, 512)          1049088     ['dense[0][0]']                  \n",
      "                                                                                                  \n",
      " dense_2 (Dense)                (None, 512)          524800      ['dropout[0][0]']                \n",
      "                                                                                                  \n",
      " dropout_1 (Dropout)            (None, 512)          0           ['dense_5[0][0]']                \n",
      "                                                                                                  \n",
      " dense_3 (Dense)                (None, 256)          131328      ['dense_2[0][0]']                \n",
      "                                                                                                  \n",
      " dense_6 (Dense)                (None, 256)          131328      ['dropout_1[0][0]']              \n",
      "                                                                                                  \n",
      " dense_4 (Dense)                (None, 128)          32896       ['dense_3[0][0]']                \n",
      "                                                                                                  \n",
      " dense_7 (Dense)                (None, 128)          32896       ['dense_6[0][0]']                \n",
      "                                                                                                  \n",
      " task_1_output (Dense)          (None, 100)          12900       ['dense_4[0][0]']                \n",
      "                                                                                                  \n",
      " task_2_output (Dense)          (None, 20)           2580        ['dense_7[0][0]']                \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 66,583,288\n",
      "Trainable params: 66,431,864\n",
      "Non-trainable params: 151,424\n",
      "__________________________________________________________________________________________________\n",
      "None\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display and plot model\n",
    "model = create_model(0)\n",
    "print(model.summary())\n",
    "plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c2684870",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:19.074628Z",
     "iopub.status.busy": "2023-04-23T16:22:19.074320Z",
     "iopub.status.idle": "2023-04-23T16:22:19.079080Z",
     "shell.execute_reply": "2023-04-23T16:22:19.078058Z"
    },
    "papermill": {
     "duration": 0.02914,
     "end_time": "2023-04-23T16:22:19.081212",
     "exception": false,
     "start_time": "2023-04-23T16:22:19.052072",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define number of epochs and batch size\n",
    "epochs = 20\n",
    "batch_size = 128"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a883ec8",
   "metadata": {
    "papermill": {
     "duration": 0.020414,
     "end_time": "2023-04-23T16:22:19.122240",
     "exception": false,
     "start_time": "2023-04-23T16:22:19.101826",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 2.1. Case 1: Gamma = 0.5 - The model will receive the loss evenly in both tasks\n",
    "##      (Dropout = 0, Optimizer = Adam)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a3d49ec0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:19.166888Z",
     "iopub.status.busy": "2023-04-23T16:22:19.165270Z",
     "iopub.status.idle": "2023-04-23T16:22:24.120819Z",
     "shell.execute_reply": "2023-04-23T16:22:24.119562Z"
    },
    "papermill": {
     "duration": 4.980337,
     "end_time": "2023-04-23T16:22:24.123651",
     "exception": false,
     "start_time": "2023-04-23T16:22:19.143314",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define parameters and generate model\n",
    "gamma=0.5\n",
    "dropout = 0\n",
    "optimizer = 'Adam'\n",
    "model_1 = create_model(dropout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4e5993ee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:24.168257Z",
     "iopub.status.busy": "2023-04-23T16:22:24.167942Z",
     "iopub.status.idle": "2023-04-23T16:22:24.203378Z",
     "shell.execute_reply": "2023-04-23T16:22:24.202468Z"
    },
    "papermill": {
     "duration": 0.060364,
     "end_time": "2023-04-23T16:22:24.205428",
     "exception": false,
     "start_time": "2023-04-23T16:22:24.145064",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# compile model\n",
    "model_1.compile(loss={'task_1_output': 'categorical_crossentropy',\n",
    "                    'task_2_output': 'categorical_crossentropy'},\n",
    "              loss_weights={'task_1_output': gamma,\n",
    "                            'task_2_output': 1-gamma},\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "390e163d",
   "metadata": {
    "papermill": {
     "duration": 0.020386,
     "end_time": "2023-04-23T16:22:24.246710",
     "exception": false,
     "start_time": "2023-04-23T16:22:24.226324",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Train & Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ce26ba7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:22:24.289733Z",
     "iopub.status.busy": "2023-04-23T16:22:24.288894Z",
     "iopub.status.idle": "2023-04-23T16:39:56.330044Z",
     "shell.execute_reply": "2023-04-23T16:39:56.329003Z"
    },
    "papermill": {
     "duration": 1052.065138,
     "end_time": "2023-04-23T16:39:56.332461",
     "exception": false,
     "start_time": "2023-04-23T16:22:24.267323",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "333/333 [==============================] - 156s 149ms/step - loss: 3.6416 - task_1_output_loss: 4.4290 - task_2_output_loss: 2.8542 - task_1_output_accuracy: 0.0229 - task_2_output_accuracy: 0.0972 - val_loss: 3.5496 - val_task_1_output_loss: 4.3285 - val_task_2_output_loss: 2.7707 - val_task_1_output_accuracy: 0.0259 - val_task_2_output_accuracy: 0.1059\n",
      "Epoch 2/20\n",
      "333/333 [==============================] - 46s 140ms/step - loss: 3.3831 - task_1_output_loss: 4.1487 - task_2_output_loss: 2.6175 - task_1_output_accuracy: 0.0390 - task_2_output_accuracy: 0.1534 - val_loss: 3.5398 - val_task_1_output_loss: 4.3139 - val_task_2_output_loss: 2.7657 - val_task_1_output_accuracy: 0.0285 - val_task_2_output_accuracy: 0.1192\n",
      "Epoch 3/20\n",
      "333/333 [==============================] - 46s 140ms/step - loss: 3.2704 - task_1_output_loss: 4.0303 - task_2_output_loss: 2.5104 - task_1_output_accuracy: 0.0483 - task_2_output_accuracy: 0.1899 - val_loss: 3.3346 - val_task_1_output_loss: 4.0708 - val_task_2_output_loss: 2.5984 - val_task_1_output_accuracy: 0.0560 - val_task_2_output_accuracy: 0.1785\n",
      "Epoch 4/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 3.1901 - task_1_output_loss: 3.9344 - task_2_output_loss: 2.4458 - task_1_output_accuracy: 0.0639 - task_2_output_accuracy: 0.2171 - val_loss: 3.4263 - val_task_1_output_loss: 4.1982 - val_task_2_output_loss: 2.6544 - val_task_1_output_accuracy: 0.0479 - val_task_2_output_accuracy: 0.1751\n",
      "Epoch 5/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 3.0432 - task_1_output_loss: 3.7713 - task_2_output_loss: 2.3151 - task_1_output_accuracy: 0.0836 - task_2_output_accuracy: 0.2605 - val_loss: 3.4038 - val_task_1_output_loss: 4.2039 - val_task_2_output_loss: 2.6038 - val_task_1_output_accuracy: 0.0612 - val_task_2_output_accuracy: 0.2269\n",
      "Epoch 6/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.8741 - task_1_output_loss: 3.5841 - task_2_output_loss: 2.1641 - task_1_output_accuracy: 0.1053 - task_2_output_accuracy: 0.3039 - val_loss: 3.3497 - val_task_1_output_loss: 4.1383 - val_task_2_output_loss: 2.5612 - val_task_1_output_accuracy: 0.0776 - val_task_2_output_accuracy: 0.2428\n",
      "Epoch 7/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.9233 - task_1_output_loss: 3.6298 - task_2_output_loss: 2.2168 - task_1_output_accuracy: 0.1092 - task_2_output_accuracy: 0.2946 - val_loss: 3.3070 - val_task_1_output_loss: 4.0858 - val_task_2_output_loss: 2.5281 - val_task_1_output_accuracy: 0.1004 - val_task_2_output_accuracy: 0.2780\n",
      "Epoch 8/20\n",
      "333/333 [==============================] - 47s 143ms/step - loss: 2.7444 - task_1_output_loss: 3.4367 - task_2_output_loss: 2.0520 - task_1_output_accuracy: 0.1342 - task_2_output_accuracy: 0.3462 - val_loss: 3.3672 - val_task_1_output_loss: 4.1330 - val_task_2_output_loss: 2.6015 - val_task_1_output_accuracy: 0.1127 - val_task_2_output_accuracy: 0.3085\n",
      "Epoch 9/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.5362 - task_1_output_loss: 3.2030 - task_2_output_loss: 1.8695 - task_1_output_accuracy: 0.1738 - task_2_output_accuracy: 0.4008 - val_loss: 2.8315 - val_task_1_output_loss: 3.5308 - val_task_2_output_loss: 2.1323 - val_task_1_output_accuracy: 0.1561 - val_task_2_output_accuracy: 0.3676\n",
      "Epoch 10/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.4461 - task_1_output_loss: 3.0939 - task_2_output_loss: 1.7984 - task_1_output_accuracy: 0.1991 - task_2_output_accuracy: 0.4264 - val_loss: 2.8095 - val_task_1_output_loss: 3.5175 - val_task_2_output_loss: 2.1016 - val_task_1_output_accuracy: 0.1475 - val_task_2_output_accuracy: 0.3444\n",
      "Epoch 11/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.3490 - task_1_output_loss: 2.9775 - task_2_output_loss: 1.7204 - task_1_output_accuracy: 0.2200 - task_2_output_accuracy: 0.4516 - val_loss: 2.6580 - val_task_1_output_loss: 3.3336 - val_task_2_output_loss: 1.9825 - val_task_1_output_accuracy: 0.1860 - val_task_2_output_accuracy: 0.3943\n",
      "Epoch 12/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.1925 - task_1_output_loss: 2.7983 - task_2_output_loss: 1.5868 - task_1_output_accuracy: 0.2531 - task_2_output_accuracy: 0.4946 - val_loss: 2.6086 - val_task_1_output_loss: 3.2590 - val_task_2_output_loss: 1.9583 - val_task_1_output_accuracy: 0.1875 - val_task_2_output_accuracy: 0.4097\n",
      "Epoch 13/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.3996 - task_1_output_loss: 3.0226 - task_2_output_loss: 1.7765 - task_1_output_accuracy: 0.2246 - task_2_output_accuracy: 0.4402 - val_loss: 2.5794 - val_task_1_output_loss: 3.2299 - val_task_2_output_loss: 1.9289 - val_task_1_output_accuracy: 0.2067 - val_task_2_output_accuracy: 0.4148\n",
      "Epoch 14/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.4340 - task_1_output_loss: 3.0607 - task_2_output_loss: 1.8072 - task_1_output_accuracy: 0.2191 - task_2_output_accuracy: 0.4321 - val_loss: 2.8584 - val_task_1_output_loss: 3.5752 - val_task_2_output_loss: 2.1415 - val_task_1_output_accuracy: 0.1728 - val_task_2_output_accuracy: 0.3729\n",
      "Epoch 15/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.5202 - task_1_output_loss: 3.1475 - task_2_output_loss: 1.8929 - task_1_output_accuracy: 0.2102 - task_2_output_accuracy: 0.4129 - val_loss: 2.8199 - val_task_1_output_loss: 3.4961 - val_task_2_output_loss: 2.1437 - val_task_1_output_accuracy: 0.1656 - val_task_2_output_accuracy: 0.3465\n",
      "Epoch 16/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.4966 - task_1_output_loss: 3.1142 - task_2_output_loss: 1.8789 - task_1_output_accuracy: 0.2160 - task_2_output_accuracy: 0.4159 - val_loss: 2.6216 - val_task_1_output_loss: 3.2654 - val_task_2_output_loss: 1.9778 - val_task_1_output_accuracy: 0.1967 - val_task_2_output_accuracy: 0.3944\n",
      "Epoch 17/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.2691 - task_1_output_loss: 2.8603 - task_2_output_loss: 1.6779 - task_1_output_accuracy: 0.2560 - task_2_output_accuracy: 0.4697 - val_loss: 2.4497 - val_task_1_output_loss: 3.0753 - val_task_2_output_loss: 1.8241 - val_task_1_output_accuracy: 0.2193 - val_task_2_output_accuracy: 0.4363\n",
      "Epoch 18/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.1346 - task_1_output_loss: 2.7091 - task_2_output_loss: 1.5602 - task_1_output_accuracy: 0.2865 - task_2_output_accuracy: 0.5056 - val_loss: 2.9517 - val_task_1_output_loss: 3.5134 - val_task_2_output_loss: 2.3900 - val_task_1_output_accuracy: 0.2043 - val_task_2_output_accuracy: 0.3907\n",
      "Epoch 19/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 1.9693 - task_1_output_loss: 2.5207 - task_2_output_loss: 1.4179 - task_1_output_accuracy: 0.3176 - task_2_output_accuracy: 0.5462 - val_loss: 2.2596 - val_task_1_output_loss: 2.8385 - val_task_2_output_loss: 1.6806 - val_task_1_output_accuracy: 0.2879 - val_task_2_output_accuracy: 0.4932\n",
      "Epoch 20/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 1.7982 - task_1_output_loss: 2.3253 - task_2_output_loss: 1.2711 - task_1_output_accuracy: 0.3551 - task_2_output_accuracy: 0.5882 - val_loss: 2.4094 - val_task_1_output_loss: 3.0363 - val_task_2_output_loss: 1.7825 - val_task_1_output_accuracy: 0.2707 - val_task_2_output_accuracy: 0.4863\n"
     ]
    }
   ],
   "source": [
    "# train model\n",
    "history_1 = model_1.fit({'input': X_train},\n",
    "                        {'task_1_output': y_train, 'task_2_output': y_train_super}, \n",
    "                        validation_split=0.15,\n",
    "                        epochs=epochs, \n",
    "                        batch_size=batch_size,\n",
    "                        verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d27a8877",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:39:57.125751Z",
     "iopub.status.busy": "2023-04-23T16:39:57.125384Z",
     "iopub.status.idle": "2023-04-23T16:39:57.133310Z",
     "shell.execute_reply": "2023-04-23T16:39:57.132071Z"
    },
    "papermill": {
     "duration": 0.412727,
     "end_time": "2023-04-23T16:39:57.135352",
     "exception": false,
     "start_time": "2023-04-23T16:39:56.722625",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train loss: 1.7982040643692017\n",
      "\n",
      "Train task 1 loss: 2.3252787590026855\n",
      "Train task 1 acc: 0.35508236289024353\n",
      "\n",
      "Train task 2 loss: 1.2711288928985596\n",
      "Train task 2 acc: 0.5882353186607361\n"
     ]
    }
   ],
   "source": [
    "# train model results\n",
    "print('Train loss:', history_1.history['loss'][-1])\n",
    "\n",
    "print('\\nTrain task 1 loss:', history_1.history['task_1_output_loss'][-1])\n",
    "print('Train task 1 acc:', history_1.history['task_1_output_accuracy'][-1])\n",
    "\n",
    "print('\\nTrain task 2 loss:', history_1.history['task_2_output_loss'][-1])\n",
    "print('Train task 2 acc:', history_1.history['task_2_output_accuracy'][-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96215b8e",
   "metadata": {
    "papermill": {
     "duration": 0.393376,
     "end_time": "2023-04-23T16:39:57.972644",
     "exception": false,
     "start_time": "2023-04-23T16:39:57.579268",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e376f8fe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:39:58.814696Z",
     "iopub.status.busy": "2023-04-23T16:39:58.814160Z",
     "iopub.status.idle": "2023-04-23T16:40:13.267323Z",
     "shell.execute_reply": "2023-04-23T16:40:13.266267Z"
    },
    "papermill": {
     "duration": 14.904069,
     "end_time": "2023-04-23T16:40:13.270119",
     "exception": false,
     "start_time": "2023-04-23T16:39:58.366050",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test model results\n",
    "evaluation_results = model_1.evaluate(\n",
    "                        X_test, \n",
    "                        [y_test, y_test_super],\n",
    "                        verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b1b327e1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:40:14.152640Z",
     "iopub.status.busy": "2023-04-23T16:40:14.152270Z",
     "iopub.status.idle": "2023-04-23T16:40:14.158418Z",
     "shell.execute_reply": "2023-04-23T16:40:14.157388Z"
    },
    "papermill": {
     "duration": 0.406031,
     "end_time": "2023-04-23T16:40:14.160984",
     "exception": false,
     "start_time": "2023-04-23T16:40:13.754953",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 2.4221746921539307\n",
      "\n",
      "Test task 1 loss: 3.045034408569336\n",
      "Test task 1 acc: 0.27059999108314514\n",
      "\n",
      "Test task 2 loss: 1.7993146181106567\n",
      "Test task 2 acc: 0.4758000075817108\n"
     ]
    }
   ],
   "source": [
    "# test model results\n",
    "print('Test loss:', evaluation_results[0])\n",
    "\n",
    "print('\\nTest task 1 loss:', evaluation_results[1])\n",
    "print('Test task 1 acc:', evaluation_results[3])\n",
    "\n",
    "print('\\nTest task 2 loss:', evaluation_results[2])\n",
    "print('Test task 2 acc:', evaluation_results[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "890b5116",
   "metadata": {
    "papermill": {
     "duration": 0.395256,
     "end_time": "2023-04-23T16:40:14.946517",
     "exception": false,
     "start_time": "2023-04-23T16:40:14.551261",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "17930b99",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:40:15.786084Z",
     "iopub.status.busy": "2023-04-23T16:40:15.784999Z",
     "iopub.status.idle": "2023-04-23T16:40:16.299728Z",
     "shell.execute_reply": "2023-04-23T16:40:16.298761Z"
    },
    "papermill": {
     "duration": 0.910259,
     "end_time": "2023-04-23T16:40:16.302115",
     "exception": false,
     "start_time": "2023-04-23T16:40:15.391856",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# accuracy plot\n",
    "plt.plot(history_1.history['task_1_output_accuracy'])\n",
    "plt.plot(history_1.history['task_2_output_accuracy'])\n",
    "plt.plot(history_1.history['val_task_1_output_accuracy'])\n",
    "plt.plot(history_1.history['val_task_2_output_accuracy'])\n",
    "plt.title('Model Accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()\n",
    "\n",
    "# loss plot\n",
    "plt.plot(history_1.history['loss'])\n",
    "plt.plot(history_1.history['task_1_output_loss'])\n",
    "plt.plot(history_1.history['task_2_output_loss'])\n",
    "plt.plot(history_1.history['val_task_1_output_loss'])\n",
    "plt.plot(history_1.history['val_task_2_output_loss'])\n",
    "plt.title('Model Loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['combined' ,'train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1781696",
   "metadata": {
    "papermill": {
     "duration": 0.480409,
     "end_time": "2023-04-23T16:40:17.186872",
     "exception": false,
     "start_time": "2023-04-23T16:40:16.706463",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 2.2. Case 2: Gamma = 0.6 - The model will receive loss 60% from task 1, 40% from task 2.\n",
    "##      (Dropout = 0, Optimizer = Adam)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e660d303",
   "metadata": {
    "papermill": {
     "duration": 0.396855,
     "end_time": "2023-04-23T16:40:17.981431",
     "exception": false,
     "start_time": "2023-04-23T16:40:17.584576",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Get Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b7d2cd1e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:40:18.781688Z",
     "iopub.status.busy": "2023-04-23T16:40:18.780907Z",
     "iopub.status.idle": "2023-04-23T16:40:23.449175Z",
     "shell.execute_reply": "2023-04-23T16:40:23.448134Z"
    },
    "papermill": {
     "duration": 5.072924,
     "end_time": "2023-04-23T16:40:23.451652",
     "exception": false,
     "start_time": "2023-04-23T16:40:18.378728",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define parameters and generate model\n",
    "gamma=0.6\n",
    "dropout = 0\n",
    "optimizer = 'Adam'\n",
    "model_2 = create_model(dropout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d9be2f1c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:40:24.300016Z",
     "iopub.status.busy": "2023-04-23T16:40:24.299631Z",
     "iopub.status.idle": "2023-04-23T16:40:24.329662Z",
     "shell.execute_reply": "2023-04-23T16:40:24.328689Z"
    },
    "papermill": {
     "duration": 0.431931,
     "end_time": "2023-04-23T16:40:24.332125",
     "exception": false,
     "start_time": "2023-04-23T16:40:23.900194",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# compile model\n",
    "model_2.compile(loss={'task_1_output': 'categorical_crossentropy',\n",
    "                    'task_2_output': 'categorical_crossentropy'},\n",
    "              loss_weights={'task_1_output': gamma,\n",
    "                            'task_2_output': 1-gamma},\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ea89f6d",
   "metadata": {
    "papermill": {
     "duration": 0.452173,
     "end_time": "2023-04-23T16:40:25.262379",
     "exception": false,
     "start_time": "2023-04-23T16:40:24.810206",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Train & Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9a4d22ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:40:26.044928Z",
     "iopub.status.busy": "2023-04-23T16:40:26.044543Z",
     "iopub.status.idle": "2023-04-23T16:58:42.684238Z",
     "shell.execute_reply": "2023-04-23T16:58:42.683155Z"
    },
    "papermill": {
     "duration": 1097.035005,
     "end_time": "2023-04-23T16:58:42.687045",
     "exception": false,
     "start_time": "2023-04-23T16:40:25.652040",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "333/333 [==============================] - 158s 159ms/step - loss: 3.8747 - task_1_output_loss: 4.5068 - task_2_output_loss: 2.9266 - task_1_output_accuracy: 0.0185 - task_2_output_accuracy: 0.0818 - val_loss: 4.0160 - val_task_1_output_loss: 4.6848 - val_task_2_output_loss: 3.0128 - val_task_1_output_accuracy: 0.0216 - val_task_2_output_accuracy: 0.0997\n",
      "Epoch 2/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 3.6295 - task_1_output_loss: 4.2381 - task_2_output_loss: 2.7166 - task_1_output_accuracy: 0.0332 - task_2_output_accuracy: 0.1318 - val_loss: 3.7866 - val_task_1_output_loss: 4.4195 - val_task_2_output_loss: 2.8374 - val_task_1_output_accuracy: 0.0276 - val_task_2_output_accuracy: 0.1223\n",
      "Epoch 3/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 3.4628 - task_1_output_loss: 4.0589 - task_2_output_loss: 2.5687 - task_1_output_accuracy: 0.0478 - task_2_output_accuracy: 0.1745 - val_loss: 3.9666 - val_task_1_output_loss: 4.6687 - val_task_2_output_loss: 2.9134 - val_task_1_output_accuracy: 0.0319 - val_task_2_output_accuracy: 0.1272\n",
      "Epoch 4/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 3.3565 - task_1_output_loss: 3.9436 - task_2_output_loss: 2.4759 - task_1_output_accuracy: 0.0615 - task_2_output_accuracy: 0.2062 - val_loss: 3.3943 - val_task_1_output_loss: 3.9874 - val_task_2_output_loss: 2.5045 - val_task_1_output_accuracy: 0.0595 - val_task_2_output_accuracy: 0.2211\n",
      "Epoch 5/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 3.2025 - task_1_output_loss: 3.7775 - task_2_output_loss: 2.3400 - task_1_output_accuracy: 0.0852 - task_2_output_accuracy: 0.2512 - val_loss: 3.3907 - val_task_1_output_loss: 4.0105 - val_task_2_output_loss: 2.4610 - val_task_1_output_accuracy: 0.0731 - val_task_2_output_accuracy: 0.2264\n",
      "Epoch 6/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 3.0848 - task_1_output_loss: 3.6505 - task_2_output_loss: 2.2364 - task_1_output_accuracy: 0.1011 - task_2_output_accuracy: 0.2861 - val_loss: 3.2669 - val_task_1_output_loss: 3.8435 - val_task_2_output_loss: 2.4019 - val_task_1_output_accuracy: 0.0867 - val_task_2_output_accuracy: 0.2523\n",
      "Epoch 7/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.9528 - task_1_output_loss: 3.5056 - task_2_output_loss: 2.1235 - task_1_output_accuracy: 0.1219 - task_2_output_accuracy: 0.3238 - val_loss: 3.1740 - val_task_1_output_loss: 3.7631 - val_task_2_output_loss: 2.2903 - val_task_1_output_accuracy: 0.1008 - val_task_2_output_accuracy: 0.2832\n",
      "Epoch 8/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.8576 - task_1_output_loss: 3.4006 - task_2_output_loss: 2.0431 - task_1_output_accuracy: 0.1400 - task_2_output_accuracy: 0.3503 - val_loss: 3.5327 - val_task_1_output_loss: 4.1442 - val_task_2_output_loss: 2.6154 - val_task_1_output_accuracy: 0.1056 - val_task_2_output_accuracy: 0.2735\n",
      "Epoch 9/20\n",
      "333/333 [==============================] - 47s 143ms/step - loss: 2.9806 - task_1_output_loss: 3.5294 - task_2_output_loss: 2.1575 - task_1_output_accuracy: 0.1284 - task_2_output_accuracy: 0.3206 - val_loss: 3.3679 - val_task_1_output_loss: 3.9738 - val_task_2_output_loss: 2.4589 - val_task_1_output_accuracy: 0.0855 - val_task_2_output_accuracy: 0.2432\n",
      "Epoch 10/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.9066 - task_1_output_loss: 3.4421 - task_2_output_loss: 2.1035 - task_1_output_accuracy: 0.1452 - task_2_output_accuracy: 0.3370 - val_loss: 3.1335 - val_task_1_output_loss: 3.6595 - val_task_2_output_loss: 2.3446 - val_task_1_output_accuracy: 0.1268 - val_task_2_output_accuracy: 0.2901\n",
      "Epoch 11/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.8601 - task_1_output_loss: 3.3914 - task_2_output_loss: 2.0631 - task_1_output_accuracy: 0.1513 - task_2_output_accuracy: 0.3493 - val_loss: 3.4917 - val_task_1_output_loss: 4.0923 - val_task_2_output_loss: 2.5908 - val_task_1_output_accuracy: 0.0732 - val_task_2_output_accuracy: 0.2064\n",
      "Epoch 12/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.7095 - task_1_output_loss: 3.2239 - task_2_output_loss: 1.9378 - task_1_output_accuracy: 0.1828 - task_2_output_accuracy: 0.3868 - val_loss: 3.0475 - val_task_1_output_loss: 3.6250 - val_task_2_output_loss: 2.1812 - val_task_1_output_accuracy: 0.1395 - val_task_2_output_accuracy: 0.3336\n",
      "Epoch 13/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.6410 - task_1_output_loss: 3.1520 - task_2_output_loss: 1.8744 - task_1_output_accuracy: 0.1964 - task_2_output_accuracy: 0.4132 - val_loss: 2.8155 - val_task_1_output_loss: 3.3560 - val_task_2_output_loss: 2.0048 - val_task_1_output_accuracy: 0.1800 - val_task_2_output_accuracy: 0.3948\n",
      "Epoch 14/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.5104 - task_1_output_loss: 3.0042 - task_2_output_loss: 1.7696 - task_1_output_accuracy: 0.2248 - task_2_output_accuracy: 0.4457 - val_loss: 2.7312 - val_task_1_output_loss: 3.2455 - val_task_2_output_loss: 1.9598 - val_task_1_output_accuracy: 0.1941 - val_task_2_output_accuracy: 0.4025\n",
      "Epoch 15/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.3855 - task_1_output_loss: 2.8677 - task_2_output_loss: 1.6622 - task_1_output_accuracy: 0.2482 - task_2_output_accuracy: 0.4751 - val_loss: 3.0510 - val_task_1_output_loss: 3.6173 - val_task_2_output_loss: 2.2015 - val_task_1_output_accuracy: 0.1675 - val_task_2_output_accuracy: 0.3463\n",
      "Epoch 16/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.3018 - task_1_output_loss: 2.7713 - task_2_output_loss: 1.5975 - task_1_output_accuracy: 0.2658 - task_2_output_accuracy: 0.4926 - val_loss: 2.7316 - val_task_1_output_loss: 3.2597 - val_task_2_output_loss: 1.9393 - val_task_1_output_accuracy: 0.2079 - val_task_2_output_accuracy: 0.4223\n",
      "Epoch 17/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.2577 - task_1_output_loss: 2.7199 - task_2_output_loss: 1.5644 - task_1_output_accuracy: 0.2788 - task_2_output_accuracy: 0.5043 - val_loss: 32.8565 - val_task_1_output_loss: 35.0342 - val_task_2_output_loss: 29.5899 - val_task_1_output_accuracy: 0.0788 - val_task_2_output_accuracy: 0.2116\n",
      "Epoch 18/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.2750 - task_1_output_loss: 2.7372 - task_2_output_loss: 1.5817 - task_1_output_accuracy: 0.2776 - task_2_output_accuracy: 0.5021 - val_loss: 3.0704 - val_task_1_output_loss: 3.6370 - val_task_2_output_loss: 2.2204 - val_task_1_output_accuracy: 0.1613 - val_task_2_output_accuracy: 0.3536\n",
      "Epoch 19/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.1924 - task_1_output_loss: 2.6408 - task_2_output_loss: 1.5198 - task_1_output_accuracy: 0.2967 - task_2_output_accuracy: 0.5188 - val_loss: 2.5327 - val_task_1_output_loss: 3.0331 - val_task_2_output_loss: 1.7821 - val_task_1_output_accuracy: 0.2525 - val_task_2_output_accuracy: 0.4652\n",
      "Epoch 20/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 1.9619 - task_1_output_loss: 2.3834 - task_2_output_loss: 1.3297 - task_1_output_accuracy: 0.3486 - task_2_output_accuracy: 0.5741 - val_loss: 2.5559 - val_task_1_output_loss: 3.0565 - val_task_2_output_loss: 1.8049 - val_task_1_output_accuracy: 0.2407 - val_task_2_output_accuracy: 0.4547\n"
     ]
    }
   ],
   "source": [
    "# train model\n",
    "history_2 = model_2.fit({'input': X_train},\n",
    "                        {'task_1_output': y_train, 'task_2_output': y_train_super}, \n",
    "                        validation_split=0.15,\n",
    "                        epochs=epochs, \n",
    "                        batch_size=batch_size,\n",
    "                        verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "30b1fc6d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:58:44.297203Z",
     "iopub.status.busy": "2023-04-23T16:58:44.296136Z",
     "iopub.status.idle": "2023-04-23T16:58:44.305180Z",
     "shell.execute_reply": "2023-04-23T16:58:44.304149Z"
    },
    "papermill": {
     "duration": 0.848634,
     "end_time": "2023-04-23T16:58:44.307454",
     "exception": false,
     "start_time": "2023-04-23T16:58:43.458820",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train loss: 1.961887001991272\n",
      "\n",
      "Train task 1 loss: 2.3833725452423096\n",
      "Train task 1 acc: 0.3485647141933441\n",
      "\n",
      "Train task 2 loss: 1.3296585083007812\n",
      "Train task 2 acc: 0.5741176605224609\n"
     ]
    }
   ],
   "source": [
    "# train model results\n",
    "print('Train loss:', history_2.history['loss'][-1])\n",
    "\n",
    "print('\\nTrain task 1 loss:', history_2.history['task_1_output_loss'][-1])\n",
    "print('Train task 1 acc:', history_2.history['task_1_output_accuracy'][-1])\n",
    "\n",
    "print('\\nTrain task 2 loss:', history_2.history['task_2_output_loss'][-1])\n",
    "print('Train task 2 acc:', history_2.history['task_2_output_accuracy'][-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6625e65",
   "metadata": {
    "papermill": {
     "duration": 0.774319,
     "end_time": "2023-04-23T16:58:46.066081",
     "exception": false,
     "start_time": "2023-04-23T16:58:45.291762",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f8f0cf9f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:58:47.671612Z",
     "iopub.status.busy": "2023-04-23T16:58:47.671234Z",
     "iopub.status.idle": "2023-04-23T16:59:11.526065Z",
     "shell.execute_reply": "2023-04-23T16:59:11.524946Z"
    },
    "papermill": {
     "duration": 24.624527,
     "end_time": "2023-04-23T16:59:11.528738",
     "exception": false,
     "start_time": "2023-04-23T16:58:46.904211",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test model results\n",
    "evaluation_results = model_2.evaluate(\n",
    "                        X_test, \n",
    "                        [y_test, y_test_super],\n",
    "                        verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d1120403",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:59:13.150916Z",
     "iopub.status.busy": "2023-04-23T16:59:13.150542Z",
     "iopub.status.idle": "2023-04-23T16:59:13.156756Z",
     "shell.execute_reply": "2023-04-23T16:59:13.155704Z"
    },
    "papermill": {
     "duration": 0.794358,
     "end_time": "2023-04-23T16:59:13.159451",
     "exception": false,
     "start_time": "2023-04-23T16:59:12.365093",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 2.5404319763183594\n",
      "\n",
      "Test task 1 loss: 3.031141519546509\n",
      "Test task 1 acc: 0.243599995970726\n",
      "\n",
      "Test task 2 loss: 1.8043668270111084\n",
      "Test task 2 acc: 0.45019999146461487\n"
     ]
    }
   ],
   "source": [
    "# test model results\n",
    "print('Test loss:', evaluation_results[0])\n",
    "\n",
    "print('\\nTest task 1 loss:', evaluation_results[1])\n",
    "print('Test task 1 acc:', evaluation_results[3])\n",
    "\n",
    "print('\\nTest task 2 loss:', evaluation_results[2])\n",
    "print('Test task 2 acc:', evaluation_results[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f673c7cd",
   "metadata": {
    "papermill": {
     "duration": 0.82939,
     "end_time": "2023-04-23T16:59:14.761085",
     "exception": false,
     "start_time": "2023-04-23T16:59:13.931695",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0893dc33",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:59:16.413438Z",
     "iopub.status.busy": "2023-04-23T16:59:16.413065Z",
     "iopub.status.idle": "2023-04-23T16:59:16.900206Z",
     "shell.execute_reply": "2023-04-23T16:59:16.899072Z"
    },
    "papermill": {
     "duration": 1.276603,
     "end_time": "2023-04-23T16:59:16.902395",
     "exception": false,
     "start_time": "2023-04-23T16:59:15.625792",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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O4xGjR4+md+/e5g5DEARBsGAiuSkmWrduzcSJE012vWPHjvHyyy8/1zUsJUH69NNPad68Ofb29pQqVcrc4QiCIAgFTCQ3JYgkSeh0ujwd6+npWWwGVmdmZjJgwABee+01c4ciCIJQ/N3YD5qUpx9XgERyUwyMHj2a/fv3s2DBAhQKBQqFglu3bhEUFIRCoWDXrl00bNgQtVrNwYMHuX79Or169cLb2xtHR0caNWrE33//neOaD7e6KBQKfvrpJ/r06YO9vT1Vq1Zl27Ztj42pdevW3L59m0mTJhljAoiNjWXIkCH4+vpib29P7dq1Wbt2bY5zN27cSO3atbGzs8Pd3Z327duTmpqa631OnDiBl5cXn3766WNjmTlzJpMmTaJ27dpP+1EKgiAIzyM6BNYMhCUtITny6ccXEJHcPIUkSaRl6szyldfFoxcsWECzZs0YP348ERERREREUK5cOePj7733HnPmzOHSpUvUqVOHlJQUunbtyt9//82pU6fo1KkTPXr0yFHqIjczZ85k4MCBnD17lq5duzJs2DDi4uJyPXbz5s34+voaS2tEREQAkJGRQWBgINu3b+f8+fO8/PLLjBgxguDgYEAuuTFkyBDGjBnDpUuXCAoKom/fvrn+LIKCgmjXrh0zZ85k2rRpefpZCYIgCAVEp4HN40CXAa4VwcHLbKGIRfyeIl2rp8bHu8xy74uzOmFv8/T/IhcXF2xsbLC3t8fHx+eRx2fNmkWHDh2M2+7u7tStW9e4PXv2bLZs2cK2bduYMGHCY+8zevRohgwZAsBnn33GwoUL+e+//+jcufMjx7q5uaFSqXBycsoRU9myZXn33XeN22+++SZ//fUXGzZsoEmTJkRERKDT6ejbt6+xxlhuLS5bt25lxIgRLFmyxBiTIAiCYEZ7P4HIc2DvDr0XgdJ87SciuSkBGjZsmGM7NTWVmTNnsn37dsLDw9HpdKSnpz+15aZOnTrG7x0cHHBycjKWKsgrvV7P3LlzWb9+PWFhYWg0GjQaDQ4ODgDUrVuXdu3aUbt2bTp16kTHjh3p378/rq6uxmsEBwezfft2NmzYQJ8+ffJ1f0EQBKEA3AiCIwvl73suBKdHP2gXJpHcPIWdtYqLszqZ7d6mkJ04ZJsyZQq7du3iq6++okqVKtjZ2dG/f38yMzOfeB1ra+sc2wqFAoPBkK9Yvv76a+bNm8f8+fOpXbs2Dg4OTJw40XhvlUrFnj17OHLkCLt372bhwoVMmzaN4OBgKlasCEDlypVxd3dn2bJldOvWDRsbm3zFIAiCIJhQWhxsyZqwETga/LuZNRwQyc1TKRSKPHUNmZuNjQ16vT5Pxx48eJDRo0cbWz1SUlK4detWocR08OBBevXqxfDhwwEwGAxcvXqVgIAA4zEKhYIWLVrQokULPv74Y/z8/NiyZQuTJ08GwMPDg82bN9O6dWsGDRrEb7/99kjiJQiCIBQCSYI/3obkcHCvAp0+M3dEgBhQXGxUqFCB4OBgbt26RUxMzBNbVKpUqcLmzZs5ffo0Z86cYejQoflugclrTAcOHCAsLIyYmBjjvbNbZi5dusQrr7xCZOT9EfXBwcF89tlnHD9+nNDQUDZv3sy9e/dyJD8AXl5e7N27l5CQEIYMGfLEKe6hoaGcPn2a0NBQ9Ho9p0+f5vTp06SkmHeqoiAIQpF3ejVc2gZKK+j3E9g4PP2cQiCSm2Li3XffRaVSUaNGDTw9PZ84fmbevHm4urrSvHlzevToQadOnWjQoIHJY5o1axa3bt2icuXKeHp6AvDRRx/RoEEDOnXqROvWrfHx8cmx4rCzszMHDhyga9euVKtWjQ8//JCvv/6aLl26PHJ9Hx8f9u7dy7lz5xg2bNhjW64+/vhj6tevz/Tp00lJSaF+/frUr1+f48ePm/w5C4IglBix1+HP9+Xv20yDMvXNG88DFFJe5xsXE0lJSbi4uJCYmIizs3OOxzIyMrh58yYVK1bE1tbWTBEK5iZ+DwRBEJ5Cr4VlnSHsOPi1gFF/gNI040Qf50nv3w8TLTeCIAiCIOTPgS/lxEbtAn2WFHhik18iuREEQRAEIe9Cj8rJDUD3b6BUuScfbwYiuREEQRAEIW8ykmDzeJAMUGcQ1O5v7ohyJZIbQRAEQRDy5s/3ICEUSpWHrl+aO5rHEsmNIAiCIAhPd34TnFkLCiX0/RFsXcwd0WOJ5EYQBEEQhCdLuAPbJ8nft3wXyjc1bzxPIZIbQRAEQRAez6CHLa9CRiKUDYRW75k7oqcSyY0gCIIgCI935Fu4fQisHeTuKJXll7sRyY0gCIIgCLkLPwV7Z8vfd/kc3CubN548EsmNkKsKFSowf/58c4fxiNGjR+co1yAIgiAUkMxU2DQeDDoI6An1h5s7ojwTyU0x0bp1ayZOnGiy6x07doyXX375ua5hCQnSrVu3GDt2LBUrVsTOzo7KlSszffp0MjMzzRqXIAiCxds1DWKvglNp6LEAFApzR5RnVuYOQCg8kiSh1+uxsnr6f3t2ocuiLiQkBIPBwJIlS6hSpQrnz59n/PjxpKam8tVXX5k7PEEQBMsUshNOLJe/770Y7N3MG08+iZabYmD06NHs37+fBQsWoFAoUCgU3Lp1i6CgIBQKBbt27aJhw4ao1WoOHjzI9evX6dWrF97e3jg6OtKoUSP+/vvvHNd8uNVFoVDw008/0adPH+zt7alatSrbtm17bEytW7fm9u3bTJo0yRgTQGxsLEOGDMHX1xd7e3tq167N2rVrc5y7ceNGateujZ2dHe7u7rRv357U1NRc73PixAm8vLz49NNPc328c+fOLF++nI4dO1KpUiV69uzJu+++y+bNm/PyoxUEQSh5kqNg2wT5+2YToHIb88bzDERy8zSSJPc7muMrjwXbFyxYQLNmzRg/fjwRERFERERQrtz9Wh/vvfcec+bM4dKlS9SpU4eUlBS6du3K33//zalTp+jUqRM9evQgNDT0ifeZOXMmAwcO5OzZs3Tt2pVhw4YRFxeX67GbN2/G19eXWbNmGWMCueJ2YGAg27dv5/z587z88suMGDGC4OBgACIiIhgyZAhjxozh0qVLBAUF0bdvX3IrXh8UFES7du2YOXMm06ZNy9PPCiAxMRE3t6L1KUQQBKFQGAzw+2uQFgvetaHdx+aO6JmIbqmn0abBZ2XMc+//hYONw1MPc3FxwcbGBnt7e3x8fB55fNasWXTo0MG47e7uTt26dY3bs2fPZsuWLWzbto0JEyY89j6jR49myJAhAHz22WcsXLiQ//77j86dOz9yrJubGyqVCicnpxwxlS1blnfffde4/eabb/LXX3+xYcMGmjRpQkREBDqdjr59++Ln5wdA7dq1H7n+1q1bGTFiBEuWLDHGlBfXr19n4cKFfP3113k+RxAEocT4bylc/wesbKHfj2ClNndEz0QkNyVAw4YNc2ynpqYyc+ZMtm/fTnh4ODqdjvT09Ke23NSpU8f4vYODA05OTkRHR+crFr1ez9y5c1m/fj1hYWFoNBo0Gg0ODnISV7duXdq1a0ft2rXp1KkTHTt2pH///ri6uhqvERwczPbt29mwYQN9+vTJ873Dw8Pp3LkzAwYMYNy4cfmKWxAEodiLugh7slpqOnwCXgHmjec5iOTmaazt5RYUc93bBLITh2xTpkxh165dfPXVV1SpUgU7Ozv69+//1BlE1tY5F25SKBQYDIZ8xfL1118zb9485s+fT+3atXFwcGDixInGe6tUKvbs2cORI0fYvXs3CxcuZNq0aQQHB1OxYkUAKleujLu7O8uWLaNbt27Y2Ng89b7h4eG0adOGZs2asXTp0nzFLAiCUOxpM+Rq33oNVO0IjcebO6LnIsbcPI1CIXcNmeMrH9PubGxs0Ov1eTr24MGDjB49mj59+lC7dm18fHy4devWM/6A8hfTwYMH6dWrF8OHD6du3bpUqlSJq1ev5jhGoVDQokULZs6cyalTp7CxsWHLli3Gxz08PNi7dy/Xr19n0KBBaLXaJ8YRFhZG69atadCgAcuXL0epFL/2giAIOfwzC6LOg70H9Pq+SE37zo14lS8mKlSoQHBwMLdu3SImJuaJLSpVqlRh8+bNnD59mjNnzjB06NB8t8DkNaYDBw4QFhZGTEyM8d7ZLTOXLl3ilVdeITIy0nhOcHAwn332GcePHyc0NJTNmzdz7949AgJyNo96eXmxd+9eQkJCGDJkCDqdLtcYwsPDad26NeXKleOrr77i3r17REZG5rinIAhCiXZ9Lxz9Xv6+1/fg6GXeeExAJDfFxLvvvotKpaJGjRp4eno+cfzMvHnzcHV1pXnz5vTo0YNOnTrRoEEDk8c0a9Ysbt26ReXKlY3r5nz00Uc0aNCATp060bp1a3x8fHKsOOzs7MyBAwfo2rUr1apV48MPP+Trr7+mS5cuj1zfx8eHvXv3cu7cOYYNG5Zry9Xu3bu5du0ae/fuxdfXl9KlSxu/BEEQSrzUWNjymvx9w7FQ/dEJIkWRQsptjm0xlpSUhIuLC4mJiTg7O+d4LCMjg5s3b1KxYkVsbW3NFKFgbuL3QBCEEkGSYP1wCNkOHtXg5f1gY5qxngXhSe/fDxMtN4IgCIJQEp1cKSc2Smvo95NFJzb5JZIbQRAEQShpYq7BXx/I37f9EErXffLxRYxIbgRBEAShJNFr5Wnf2jSo0BKav2XuiExOJDeCIAiCUFKkxsKOdyD8JNi6QJ8foBgujyEW8RMEQRCE4i78NPz3I5zbIC/UB9BjAbj4mjWsgiKSG0EQBEEojvRauLhVrhd1J/j+/tL14IWJUDPv5WuKGpHcCIIgCEJxkhwFJ1bA8WWQkrVgqdIKavSGJq+Ab6MivwLx04jkRhAEQRCKOkmCu8fhvyVw4XcwZJWlcfSGwJeg4Uvg5GPWEAuTSG4EQRAEoajSaeD8ZjmpCT91f79vY7mVJqAnWD29uHBxU/yGSAvPrEKFCsyfP79Q77lixQpKlSpVqPcUBEEo8hLD4J9P4Jsa8PurcmKjUkO9YfByEIzbA7X7l8jEBkTLjZAPo0ePJiEhgd9//92scWzevJklS5Zw4sQJYmNjOXXqFPXq1TNrTIIgCAVOkuD2EbmV5tJ2kLLq6TmXhUZjocEocPAwb4wWwuwtN4sWLTLW8AkMDOTgwYOPPTYoKAiFQvHIV0hISCFGLJhbamoqLVq0YO7cueYORRAEoeBlpsGJX+CHF2BFV3kGlKQHvxdg4Ep4+yy0fEckNg8wa8vN+vXrmThxIosWLaJFixYsWbKELl26cPHiRcqXL//Y8y5fvpyjaFZ2xemSasmSJcyaNYs7d+6gfGAxpp49e+Lq6sovv/zC9evXmTx5MkePHiU1NZWAgADmzJlD+/bt83SPGTNm8MsvvwCgyBplv2/fPlq3bs3777/Pli1buHv3Lj4+PgwbNoyPP/4Ya2trAM6cOcPEiRM5fvw4CoWCqlWrsmTJEho2bPjIfWJjY+nSpQs+Pj789ttvuRauHDFiBAC3bt3K189JEAThuWgz4NYhuPIX3Mr6IK52euDLOevLCWydn7zf2uHpi+fF34JjP8HJVZCRIO+zsoO6g6DRePCpVZDPtkgza3LzzTffMHbsWMaNGwfA/Pnz2bVrF4sXL2bOnDmPPc/Ly6vQxmlIkkS6Lr1Q7vUwOys7YyLxJAMGDOCtt95i3759tGvXDoD4+Hh27drFH3/8AUBKSgpdu3Zl9uzZ2Nra8ssvv9CjRw8uX778xEQy27vvvsulS5dISkpi+fLlALi5uQHg5OTEihUrKFOmDOfOnWP8+PE4OTnx3nvvATBs2DDq16/P4sWLUalUnD592pj4POju3bt07NiRhg0bsmzZMqysRK+pIAhmlhQBV3fDlV1wY59cssAkFA8kPk6PJkQp0fI9keTDS/lB4/FQfzjYuZoohuLLbO8emZmZnDhxgg8++CDH/o4dO3LkyJEnnlu/fn0yMjKoUaMGH374IW3atCmwONN16TRZ06TArv8kwUODsbd+epVWNzc3OnfuzJo1a4zJzYYNG3BzczNu161bl7p17xdGmz17Nlu2bGHbtm1MmDDhqfdwdHTEzs4OjUaDj0/O6YQffvih8fsKFSrwzjvvsH79emNyExoaypQpU/D39wegatWqj1z/ypUrdOjQgV69erFgwYI8JXWCIAgmZzBAxGk5sbjyl/z9g5zKQLVOULWDnIRokuWvjCTQJN3ffvD7HI8lgUEHSFn7kp4cT6U28qynqh1BqSqgJ138mC25iYmJQa/X4+3tnWO/t7c3kZGRuZ5TunRpli5dSmBgIBqNhlWrVtGuXTuCgoJ48cUXcz1Ho9Gg0WiM20lJT/lFKqKGDRvGyy+/zKJFi1Cr1axevZrBgwejUsl/DKmpqcycOZPt27cTHh6OTqcjPT2d0NDQ5773xo0bmT9/PteuXSMlJQWdTpej23Dy5MmMGzeOVatW0b59ewYMGEDlypWNj6enp/PCCy8wZMgQFixY8NzxCIIg5IsmBW4EycnM1d2QEvXAgwooGwjVOstJjU/t51sAT5JAl5EzCcp4MClKBk2i3GBToxd4VnvOJ1cymb3d/+FP6JIkPfZTe/Xq1alevbpxu1mzZty5c4evvvrqscnNnDlzmDlz5jPHZ2dlR/DQ4KcfWADsrOzyfGyPHj0wGAzs2LGDRo0acfDgQb755hvj41OmTGHXrl189dVXVKlSBTs7O/r3709mZuZzxXj06FEGDx7MzJkz6dSpEy4uLqxbt46vv/7aeMyMGTMYOnQoO3bs4M8//2T69OmsW7eOPn3kpb/VajXt27dnx44dTJkyBV/f4lnrRBAECxJ/C67svj9+Rv/Aa6GNI1RuKyc0VTuAo5fp7qtQgLWd/GXK6wo5mC258fDwQKVSPdJKEx0d/UhrzpM0bdqUX3/99bGPT506lcmTJxu3k5KSKFeuXJ6vr1Ao8tQ1ZG52dnb07duX1atXc+3aNapVq0ZgYKDx8YMHDzJ69GhjQpGSkpLvAbk2Njbo9foc+w4fPoyfnx/Tpk0z7rt9+/Yj51arVo1q1aoxadIkhgwZwvLly42xKJVKVq1axdChQ2nbti1BQUGUKVMmX7EJgiA8kV4Hd4/JycyVXXDvUs7HXStAtS5y64xfixK7PkxxYbbkxsbGhsDAQPbs2WN8kwPYs2cPvXr1yvN1Tp06RenSpR/7uFqtRq1WP1esRcWwYcPo0aMHFy5cYPjw4Tkeq1KlCps3b6ZHjx4oFAo++ugjDAZDvq5foUIFdu3axeXLl3F3d8fFxYUqVaoQGhrKunXraNSoETt27GDLli3Gc9LT05kyZQr9+/enYsWK3L17l2PHjtGvX78c11apVKxevZohQ4YYE5yHx/Zki4uLIzQ0lPDwcECePQfg4+Pz2HMEQSiB0uPh2j9Z3U177s84AlCooHwzOZmp1hk8qhb7eksliVm7pSZPnsyIESNo2LAhzZo1Y+nSpYSGhvLqq68CcqtLWFgYK1euBOTZVBUqVKBmzZpkZmby66+/smnTJjZt2mTOp2Ex2rZti5ubG5cvX2bo0KE5Hps3bx5jxoyhefPmeHh48P777+d7/NH48eMJCgqiYcOGpKSksG/fPnr16sWkSZOYMGECGo2Gbt268dFHHzFjxgxATlpiY2MZOXIkUVFReHh40Ldv31y7Cq2srFi7di2DBg0yJjheXo82227bto2XXnrJuD148GAApk+fbryvIAgllMEgj5sJXgw3D95f6A7kWUZVOsgJTZV2YtZRMaaQJEkyZwCLFi3iiy++ICIiglq1ajFv3jzj+JnRo0dz69YtgoKCAPjiiy9YunQpYWFh2NnZUbNmTaZOnUrXrl3zfL+kpCRcXFxITEzMMegVICMjg5s3bxoXFRRKJvF7IAhFUGYanFkLRxdB7LX7+71q3G+dKdsQVGYfaio8oye9fz/M7MlNYRPJjfA04vdAEIqQ5Cg49iMc+xnS4+R9ahdoOFquhu1W0azhCaaTn+RGpLCCIAhC0RN5Xm6lObfh/kynUn7Q9HWoP0xeg0YosURyIwiCIBQNkiQPEP53obwuTbZyTaDZBPDvJha6EwCR3AiCIAiWTpsBZ9fLLTX3sgolK5TyIndN34Byjcwbn2BxRHIjCIIgWKaUe3LhyGM/QVqMvM/GCQJHQeOXwdXPvPEJFkskN4IgCIJliQ6Bo9/DmfWgzyqf41IOmrwKDUaArYt54xMsnkhuBEEQBPOTJLnq9r/fw7W/7+8vGyiPpwnoKaZxC3kmflMEQRAE89Fp4NxGOamJvpC1UwEB3aHZm1CusVg5WMg3kdwIgiAIhS8tTl6b5r+lkBot77N2kLudmrwCbpXMG59QpCnNHYBgOSpUqMD8+fML9Z4rVqygVKlShXpPQRDM7OZBWNQU9s2WExunMtB+Jky+AF0+F4mN8NxEciPk2ejRo+ndu7dZY9Bqtbz//vvUrl0bBwcHypQpw8iRI41FNAVBsGAGPez/Alb2hJQocK8KfX+CiWfhhYmi1pNgMqJbSihS0tLSOHnyJB999BF169YlPj6eiRMn0rNnT44fP27u8ARBeJyUaNg8/v7ie/WGQ9cvwMbBrGEJxZNouSkGlixZQtmyZTEYDDn29+zZk1GjRgFw/fp1evXqhbe3N46OjjRq1Ii///47t8vlasaMGfzyyy9s3boVhUKBQqEwFjR9//33qVatGvb29lSqVImPPvoIrVZrPPfMmTO0adMGJycnnJ2dCQwMfGwiEhsbS+PGjenZsycZGRmPPO7i4sKePXsYOHAg1atXp2nTpixcuJATJ04QGhqa5+cjCEIhunkAfnhBTmys7aH3D9D7e5HYCAVGtNw8hSRJSOnpZrm3ws4ORR5mCQwYMIC33nqLffv20a5dOwDi4+PZtWsXf/zxBwApKSl07dqV2bNnY2tryy+//EKPHj24fPky5cuXf+o93n33XS5dukRSUhLLly8HwM3NDQAnJydWrFhBmTJlOHfuHOPHj8fJyYn33nsPgGHDhlG/fn0WL16MSqXi9OnTWFtbP3KPu3fv0rFjRxo2bMiyZcuwssrbr2diYiIKhUKM3REES2PQw4GvYP9ckAzgGQADVoCXv7kjE4o5kdw8hZSezuUGgWa5d/WTJ1DY2z/1ODc3Nzp37syaNWuMyc2GDRtwc3MzbtetW5e6desaz5k9ezZbtmxh27ZtTJgw4an3cHR0xM7ODo1Gg4+PT47HPvzwQ+P3FSpU4J133mH9+vXG5CY0NJQpU6bg7y+/oFWtWvWR61+5coUOHTrQq1cvFixYkKekDuQK3h988AFDhw59apVYQRAKUUo0bBoHN/fL2/WHQ5cvwebpr2lCwdInJqKLjsamcmUUyuLZgVM8n1UJNGzYMDZt2oRGI6/muXr1agYPHoxKJReRS01N5b333qNGjRqUKlUKR0dHQkJCTNKVs3HjRl544QV8fHxwdHTko48+ynHdyZMnM27cONq3b8/cuXO5fv16jvPT09N54YUX6N27N99++22eExutVsvgwYMxGAwsWrTouZ+HIAgmkt0NdXP//W6oXt+LxMYCSAYDt4cP50aPnlxt3oK7kyYRv2EDmXfDzB2aSYmWm6dQ2NlR/eQJs907r3r06IHBYGDHjh00atSIgwcP8s033xgfnzJlCrt27eKrr76iSpUq2NnZ0b9/fzIzM58rxqNHjzJ48GBmzpxJp06dcHFxYd26dXz99dfGY2bMmMHQoUPZsWMHf/75J9OnT2fdunX06dMHALVaTfv27dmxYwdTpkzB19f3qffVarUMHDiQmzdvsnfvXtFqIwiWILduqIG/gGd1c0cmZEk/fRrN1WsA6BMSSP7zL5L//AsAa7/yODRvLn81aYKqCL+uiuTmKRQKRZ66hszNzs6Ovn37snr1aq5du0a1atUIDLzfnXbw4EFGjx5tTChSUlK4detWvu5hY2ODXq/Pse/w4cP4+fkxbdo0477bt28/cm61atWoVq0akyZNYsiQISxfvtwYi1KpZNWqVQwdOpS2bdsSFBREmTJlHhtHdmJz9epV9u3bh7u7e76ehyAIBeCRbqgR0OUL0VpjYZK2bwfAuXt3XIcMJvXIv6QeOUL62bNob4eScDuUhLXrQKnEtnYtOdFp1gz7evVQ2NiYOfq8E8lNMTJs2DB69OjBhQsXGD58eI7HqlSpwubNm+nRowcKhYKPPvrokdlVT1OhQgV27drF5cuXcXd3x8XFhSpVqhAaGsq6deto1KgRO3bsYMuWLcZz0tPTmTJlCv3796dixYrcvXuXY8eO0a9fvxzXVqlUrF69miFDhhgTnIfH9gDodDr69+/PyZMn2b59O3q9nsjISEAee2RThP74BKHYuLFfnuadEiV3Q3WfB3UHmzsq4SGSVktSViuNS+/e2AcGYh8YiOebE9AnJ5N27Biph4+QeuQImTdvknHmLBlnzhK7+AcU9vbYN2qIY/Pm2Ddrhrpq1TwPITAHkdwUI23btsXNzY3Lly8zdOjQHI/NmzePMWPG0Lx5czw8PHj//fdJSkrK1/XHjx9PUFAQDRs2JCUlhX379tGrVy8mTZrEhAkT0Gg0dOvWjY8++ogZM2YActISGxvLyJEjiYqKwsPDg759+zJz5sxHrm9lZcXatWsZNGiQMcHx8vLKcczdu3fZtm0bAPXq1cvx2L59+2jdunW+npMgCM/BoIcDX0LQXEACrxrybCjRDWWRUv/9F318PCp3dxyaNsnxmMrJCae2bXFq2xYAbUSEsVUn9d9/0cfFkbr/AKn7DwBg5emJQ/Nm2DdrhkOz5lh7ez1yP3NSSJIkmTuIwpSUlISLiwuJiYmPjNPIyMjg5s2bVKxYEVtbWzNFKJib+D0QhDxIjoLN4+TBwyC6oYqAsPfeI2nbH7gOH47Ph9OefkIWyWBAc+WKsVUn7fhxpKzJK9nUVavgkNWq49CoEUoH069h9KT374eJlhtBEAQhf27sl8fXpEbLxS67z4O6g8wdlfAEhvR0kv/+BwCX7t3yda5CqcTW3x9bf3/cx47BoNGQfuqUMdnJuHgRzdVraK5eI+6XlWBtjX3dupT7cSnKfEyMMSWR3AiCIAh5k2s31C/gWc3ckQlPkbJvH1JaGta+vtg+sObZs1Cq1Tg0bYpD06bwzmR08fGkBQcbu7G0d++ii401W2IDIrkRBEEQ8uLhbqgGI6Hz56IbqohI3L4DAOfu3Uw+ENjK1RXnzp1x7twZgMzQUHT37pn0HvmOyax3FwRBECzfjSDYNF50QxVR+oQEUg4eBMCle/cCv59N+fLY5KGsT0ESyU0uStgYa+Eh4v9fELIY9LD/C9j/OaIbquhK2r0btFrU/v6oq1QxdziFQiQ3D8gu5piWloadGfsKBfNKS0sDyLW4pyCUGCnRsHEM3JI/8YtuqKIr6Q954b78DiQuykRy8wCVSkWpUqWIjo4GwN7e3qIXKRJMS5Ik0tLSiI6OplSpUsa6XIJQ4kScgbVDIClM7obqMR/qDDR3VMIz0EZEkHb8OADOXbuaOZrCI5Kbh2Svipud4AglT6lSpXJdHVkQSoSLW2HLq6BNA/eqMHiN6IYqwpJ2/gmShF3DQKyfUNamuBHJzUMUCgWlS5fGy8sLrVZr7nCEQmZtbS1abISSSZLk8TVBn8nbldtB/2VgV8qsYQnPJ3FHdpdUwQ8ktiQiuXkMlUol3uQEQSgZMtNg6xtwYbO83fR16PAJqMRbRFGmuX4dzcVLYGWFU6dO5g6nUInfXEEQhJIsKVweXxNxGpRW0O0bCBxl7qgEE0jaIa9t49iiBVaurmaOpnCJ5EYQBKGkunsC1g2FlEiwc4NBq6DCC+aOSjABSZIeWLivZHVJgUhuBEEQSqZzG+WuKF0GeAbA0HXgWsHcUQkmknHuHNrQUBR2dji1bWPucAqdSG4EQRBKEoNBHjR84Et5u1pn6Psj2D65yrJQtCRulwcSO7VtWyAVui2dSG4EQRBKCk0KbHkFQuQ3Plq8De2mg1JMnihOJL1engKOXEuqJBLJjSAIQkmQEAprh0LUOVDZQI9vod4Qc0clFIC04GD0MTGoXFxwbNHC3OGYhUhuBEEQirvQYFg/DFLvgYOnvDBfucbmjkooINkDiZ06d0ZhY2PmaMxDJDeCIAjF2ek18MfboM8En9oweC2UKmfuqIQCYtBoSN69GyhZtaQeJpIbQRCE4sigh79nwJFv5W3/7tB3KdiUvMGlJUnK/v0YUlKw8vHBLjDQ3OGYjUhuBEEQipuMJNg0Dq7ukrdffA9aTwWl0rxxFaLMu2EobdVYeXiYO5RClZS9tk23rihK0P/3w0RyIwiCUJzE3ZRXHL53Caxsodf3ULu/uaMqVJmhodzo1RsrDw8q796FQqEwd0iFQp+cTEpQEAAuPXqYNxgzE8mNIAhCcXHrEKwfAelx4OgDQ9ZA2ZLXNRHz/fdI6elo79xBGxaGja+vuUMqFMl7/kbKzMSmSmXU1aubOxyzKrltVoIgCMXJiRWwspec2JSpDy/vK5GJjebaNRK3/XF/OyTEjNEUrqTt9yuAl5TWqscRyY0gCEJRptfBn+/LM6IMOqjZF0bvBOcy5o7MLO4t/A4kybidcalkJDe6e/dIPXoUAOduJXeWVDaR3AiCIBRV6QmwZgAE/yBvt/kQ+i8DG3uzhmUuGRcvkrxrFygUlBogjzPKKCEtN0l//gUGA3Z162JTTkz1F8mNIAhCURR+Gn5qD9f3grU9DFwFraZACe6OuPftQkBuuXDOGlCruXTJnCEVmsQdcpdUSawAnhsxoFgQBKEo0WXCwa/g4NdyN5SzLwxZC6XrmDsys0o/fVqeKaRS4fHG61i5uQGgDQ9Hn5SEyrn4FgbNDA0l48xZUCpx7tLZ3OFYBNFyIwiCUFREnoMf28L+z+XEpkZveGV/iU9sAKIXLADApXcv1BUronJxwbqMPO6ouHdNJe2Q17ZxaNasxK3r8zgiuREEQbB0ei0EfQ5LW8uFL+3coP9yGPgLOIg3s9SjwaT9exSsrfF8/XXjfnVAAFC8Z0xJkkTiH6JL6mGiW0oQBMGSRV2ALa9C5Fl5O6AHdPsGHL3MG5eFkCSJe9/KJSZcBwzAumxZ42O21auT8s8/ZIRcNld4BU4TEkLmjRsobGxw6tDe3OFYDLO33CxatIiKFStia2tLYGAgBw8ezNN5hw8fxsrKinr16hVsgIIgCOag18GBL2FJKzmxsXOFfj/LA4dFYmOUeugQ6SdPolCrcX/llRyPqQP8AcgIKb6DihOz1rZxbNMGlaOjmaOxHGZNbtavX8/EiROZNm0ap06domXLlnTp0oXQ0NAnnpeYmMjIkSNp165dIUUqCIJQiKIuwk/tYO9sMGihejd4PVguo1AIs6EMmZmkX7hA8t69SFptgd/vWUmSxL358lgb16FDsfbOmfTZZnVLZV69ZtHP41lJBgNJO3YC4FyCK4DnxqzdUt988w1jx45l3LhxAMyfP59du3axePFi5syZ89jzXnnlFYYOHYpKpeL3338vpGgFQRAKmF4HRxZA0FzQZ4JtKej6JdQeUGBJjSEjA82VK2RcuEDGxYtkXLhIxtWrkJUMuPTvR5nZswvk3s8r+e+/ybhwAaW9Pe7jxz3yuHXZsigdHTGkpKC5cRPb6tXMEGXBST9xAl1kJEonJxxffNHc4VgUsyU3mZmZnDhxgg8++CDH/o4dO3LkyJHHnrd8+XKuX7/Or7/+yuw8/MFpNBo0Go1xOykp6dmDFgRBKCj3Lstja8JPytvVOkP3+eBc2mS3MKSlkRFyOSuJkZMZzbVroNc/cqzSxQVDUhKJGzfh1Lo1Tu0tazyHpNcTkz3WZtRI49TvBykUCtT+1Uk/fgJNyKVil9wkZlUAd+rYAaVabeZoLIvZkpuYmBj0ej3e3t459nt7exMZGZnrOVevXuWDDz7g4MGDWFnlLfQ5c+Ywc+bM545XEAShQBj08O93sPdT0GtA7QJdPoe6g5+rtUafkorm0kUyLl4kPSuRybxxEwyGR45VubpiW7Om/FWjBrY1a2JdtgzRX31F3M/LiPjoY+zq1bOoacZJf/6F5uo1lM7OuL/00mOPs/UPIP34CTIuheDSq1chRliwpMxMkv/6C5BrSQk5mX221MPFvSRJyrXgl16vZ+jQocycOZNq1fKefU+dOpXJkycbt5OSkignlqYWBMESxFyF31+Du8fk7aodoceCfNeF0icl3e9SymqVybx9O0eNpWwqTw/satTEtmYNYzJj5eOT6+uu59tvk3r4CJqQECKmfYjvD4stoiCjpNMRs1Bejdh9zEtPXKDPNntQ8eXiNR085dBh9ImJqDw9sG/c2NzhWByzJTceHh6oVKpHWmmio6Mfac0BSE5O5vjx45w6dYoJEyYAYDAYkCQJKysrdu/eTdu2bR85T61WoxbNdYIgWBKDHo4ukgcM6zJA7Qyd50C9YXlurdGnpBD9xZek/vsv2jt3cj3GyscnK4EJMCYy1l55n2mltLGhzBefc6tff1L27ydh/W+4Dh6U5/MLSuLWbWTevo3K1RXX4SOeeKy6upzcaC6FPPbDc1FkrADetSsKlcrM0VgesyU3NjY2BAYGsmfPHvr06WPcv2fPHnrl0nTo7OzMuXPncuxbtGgRe/fuZePGjVSsWLHAYxYEQXhuMddg6+twJ1jertwOen4LLr75ukz051+QsGGDcdu6bFljl5JtzRpyi4y7+3OHa1utGp6TJxP9+edEff45Dk2bYFOhwnNf91kZMjOJ+f57ANzHj0fl6PDE49VVq4BKhT4hAV1UFNY+PoURZoEypKaSvHcvIBbuexyzdktNnjyZESNG0LBhQ5o1a8bSpUsJDQ3l1VdfBeQupbCwMFauXIlSqaRWrVo5zvfy8sLW1vaR/YIgCBbHYJCrd/8zU26tsXGCTp9Cg5H5HluTGvyfMbEp8/lcHF58EStX14KIGgC3USNJCQoiLTiYsPffp8Lq1SjyOO7R1BI2bkQbHo6VpyeuQ4c89XilWo26UiU0V6+SERJSLJKb5L17kTIysPYrj614/8uVWde5GTRoEPPnz2fWrFnUq1ePAwcOsHPnTvz8/ACIiIh46po3giAIFi/2OqzoBrumyolNpdbw+r8QOCrfiY0hI4PIjz8GoNSgQbj06lWgiQ2AQqmkzNw5KJ2cyDhzlpglSwr0fo9jyMggdvEPALi/9ipKW9s8naf2z+qaKiZlGLIX7nPp1r3YdLOZmkKSchlxVowlJSXh4uJCYmIizsW4SqwgCBbAYIBjP8Ke6aBLBxtH6PgJBL70zDOhor+ZR+zSpVh5elJp5w5UTk4mDvrxEv/YTviUKaBSUWHtGuzqFG7BztjlK4j+/HOsy5Sh0l9/orSxydt5Py8j+ssvcerUCd8F8ws2yAKmi4vjassXQa+n0s4dqCtVMndIhSY/799mL78gCIJQLGUkwa994M/35MSm4ovw2hFoOOaZE5uMkBBif/4ZAJ/pHxdqYgPyKrjOXbuAXk/4lPcwpKUV2r0NqanELl0KgMcbr+c5sYEHZkwVgzIMybt2gV6PbY0aJSqxyS+R3AiCIJhaWhys7Ak3gsDaAbp+BSO2gqvfM19S0umI+PAj0Otx6tjRLIvqKRQKfD7+GCtvbzJv3ybqyy8L7d5xq1ahj4/Hxs8v3+vVZHdLaUPvoE9JLYjwCk32wn1iIPGTieRGEATBlFKiYUV3CD8F9u4w5k9oPB6Uz/dyG7dyFRnnz6N0dsb7w2kmCjb/VKVKUWbOZwAkrF1HyoEDBX5PfWIisT8vA8DjzTfzPZjZys0NKy8vkCQ0V64URIiFQhsWRvqJE6BQyC1owmOJ5EYQBMFUEsNgeReIvgCOPjB6J5Su+9yXzbxzh3tZpQa835uSr7VqCoJD8+a4jpTXlwmfNg1dfHyB3i92xQoMycmoq1Z95jf14lAhPHGnXCTTvlGjYjHrqyCJ5EYQBMEU4m7C8s4Qew1cysFLO8HL/7kvK0kSkdOnI2VkYN+kCS79+pkg2OfnNXkyNlUqo78XQ+THH1NQc1N0cXHE/7ISAI+33kTxjC1gttmL+YVcNllshS3J2CUlKoA/jUhuBEEQnte9K3KLTUIouFWSExv3yia5dOLvW0k98i8KtZrSM2dYzNRfpa0tZb/4AqytSd7zN4lbfi+Q+8T++BOGtDRsa9R4rnFG9wcVF83p4BlXrqC5fBmsrXHu2NHc4Vg8kdwIgiA8j8hzcmKTHAGe/vDSn1CqvEkurYuJIWruXAA8Jrxh1pWBc2Nbowaeb74JQNSnn5J5965Jr6+NiiZ+zRoAPCe+/VyJnXGtmytXkHKpgm7pknbIXVKOL76IqlQp8wZTBIjkRhAE4VndPS4vzpcWAz515DE2TqYbCxH12RwMiYmoAwJwHz3aZNc1JfexY7ALDMSQmkr4+x+YNHGIXbIESaPBrkEDHFq2fK5r2ZQvj8LODikjQy4qWoRIknS/lpToksoTkdwIgiA8i1uHYWUvyEgE38Yw6g9weP5aTtmS9+0jaedOUKkoPfsTFNbWJru2KSlUKsp8PhelvT3pJ04YZzU9L21YGPFZJSY8336+VhuQ47StVg2AjEtFa1Bx+unTaMPCUNrb49i6tbnDKRJEciMIgpBf1/6BX/tBZgpUaAkjtoBdKZNdXp+SQuTMWQC4jR6FXc2aJrt2QbDx9cV7mjw9/d7ChWRcvPjc17y3eDFotdg3a4pDk8bPfT24P2OqqJVhyB5I7NShPUo7OzNHUzSI5EYQBCE/QnbA2sHyqsNVO8KwDaB2NOkt7n0zD11kJNblyuE5YYJJr11QXPr2walDe9BqCXvvPQwZGc98rcxbt4wDlD3festEEYKtfwAAGUVoxpSk05H055+AWLgvP0RyIwiCkFfnNsL6EaDPhICeMGg1WJv2k3TayZPEr10LQOlZM4vMJ3WFQoHPzJmoPDzIvHade/PmPfO17n33Pej1OLZqhX39+iaL0da/OlC01rpJ/fco+rg4VG5uODRtau5wigyR3AiCIOTFyVWwaRxIeqgzGPovB6u81zfKC0NmJhEffQyShEvfvjg0a2bS6xc0Kzc3ynw6G4C4X1aSeuRIvq+RceUKSTvkbhjPt03XagOgrlYNFAr092LQ3btn0msXlOyBxM6dO1vsuCtLJJIbQRCEpwleAtsmAJJc0bv3YlDlrwRAXsQuWUrm9euoPDzwfm+Kya9fGBxbtaLUkMEAhE/9H/rExHydH7PwO5AknDp1wrZGDZPGprS3N06nLwpdU4aMDJL37AFEl1R+ieRGEAThSQ5+I1f2Bmj6BnSf99x1onKjuXqVmKyq1z4fTivSa5l4T5mCjZ8fuqgo48DovEg/f0F+M1co8HyzYMYaqbO6pjSXLX9QcUpQEIa0NKzLlsWufj1zh1OkiORGEAQhN5IEe2fDPzPl7Rffg06fQgGsECzp9XLFb60Wx7ZtcerUyeT3KExKe3vKfPkFqFQk7dxprGT9NPe+XQCAc4/uqKtUKZDYjIOKL1l+cpOY3SXVrZvFrExdVIjkRhAE4WGSBLumwYEv5e32M6DttAJJbADi16wl/cwZlA4O+Hz8UbF4I7OrUweP114DIHLmTLQREU88Pu3kSVIPHASVCs833iiwuIpKGQZ9YiKp++WK66KWVP6J5EYQBOFBBgNsnwhHv5e3u3wJL0wqsNtpw8OJzppZ5PXuO8Wq2rPHq69gW6cOhuRkwqf+D8lgeOyx9xbIVc9L9e2DjZ9fgcWkziqgmXnz5nNNVy9oyXv2IGm1qKtVMy4+KOSdSG4EQRCy6XXw+6twYgUolNDre2jycoHdTpIkImbOREpLwy4wkFKDBhXYvcxBYWVF2S8+R2FnR9rRo8StXJnrcalHj5IWHIzC2trY2lNQrLw8Ubm5gcGA5urVAr3X80g0VgAXA4mfhUhuBEEQAHSZsHE0nF0PSivo9xPUH16gt0zasZPU/QdQWFtT+pNZKApgoLK52VSogPf77wPy4oQZV67keFySJO7Nl8falBo0COsyZQo0HoVCgW1WEU1LLcOgjYomLTgYAOeuXc0cTdFU/P6SBEEQ8kubDuuGwqU/QGUDA1dBrX4FektdfDxRn34KgMfrr6GuVKlA72dOpQYNxLFVK6TMTMLfex9DZqbxsZT9+0k/fRqFrS3uL48vlHiMFcItdDp40p87QZKwa9AAG9+y5g6nSBLJjSAIJZsmGVYPgGt7wMoOhq4H/4L/tBw9dy76+HjUVaviPnZsgd/PnBQKBaVnf4LK1RVNSAgx38rjaySDgXtZ37sOG4q1l1ehxGPpg4pT/v4HEK02z0MkN4JQnGlSYM/HsH0SpMebOxrLkxYHq/rArYNg4wQjNkPltgV+25SDh0jcug2y3vQVNqZd6dgSWXl6UvoTec2b2J+XkXbsGMl7/kZz8RJKBwfcx40rtFhs/e8X0HzSIGdz0KekkHb6NACOrV40bzDPKFNn/p+p6ZfYFATBMtw6BL+/Dgm35e1rf8OAX6BsA/PGZW6pMXD5T7kA5o19oMsA21IwfDP4Bhb47Q2pqUROnw6A64jh2NWtW+D3tBRO7dvj0q8viZs2E/7+ByhsbQFwGzUKK1fXQovDpmJFFDY2GNLS0N69i0358oV276dJCw4GnQ5rv/LYlCtn7nDyLUOrZ8AP/9LG34u321VFpTTPsgYiuRGE4iYzDf6ZBcGL5W2XcqBUQfwtWNYJOn4KjccX2JotFin+lpzMhOyA0H9BeuCTpXtVGLACfGoVSij3vl2INjwc6zJl8Hr77UK5pyXxnvo/0oL/Q3v3LgBKFxfcRo8q1BgUVlaoq1Yl48IFMi6FWFRyk3LoEACOLV4wcyTP5pPtFzkXlkhYQjrDm5bHy8nWLHGI5EYQipPQYPj9NYi7Lm83GCknM0iw9Q15wOyfU+D2Yei5EGydzRpugZEkiDovJzOXtkPUuZyP+9QB/+7g3w28axZaopd+9ixxq1bJIcycgdLBoVDua0lUjg6U+eJzbg8fAQYD7mPGoHIu/N9DdYC/nNyEXMK5U8dCv//jpB6Wi406vNDCzJHk39bTYawODkWhgPmD6pktsQGR3AhC8aDNgH2fwr/fya0STqXl5KVqh/vHDFwFwT/A7g/h4u8QeRYGrgSf2mYL26QMegg9mtVCs/1+dxzIa9aUbw4B3aF6V3AtuEXiHkfSauUSCwYDzj174NiyZaHHYCnsGzSg9CezSD99BreRI8wSg61/AImAxoLKMGSGhqINDQUrK+wbNzF3OPlyLTqFqZvlDxFvtqnCi9U8zRpPvpObChUqMGbMGEaPHk15C2rKE4QSK+wEbHkNYrKmtdYdAp3ngN1DYxgUCmj6Gvg2gg2jIe4G/NgOun4BDUYVzW4qbQbcCIKQP+RxNGmx9x+zspUHB/t3h2qdwcHdbGGCPIhWc+UKKldXvKdONWsslqBUv36U6lew0+2fxDargGbGZcuZDp7dJWVfvz4qx6LTqpeeqeeN1SdJy9TTrJI7b7c3/4rK+U5u3nnnHVasWMGsWbNo06YNY8eOpU+fPqjV6oKITxCEx9Flwv7P4dA8kPTg4AU95stdLU/i2xBeOSB3X135C/54G24fgW7fgNqxUEJ/LukJcHW33MV27R/Qpt5/zNYFqnWRfwZV2oGNZbxBaG7cJGbRIgC8/ze1UAfPCrlTV5eTG11EBLr4eIv4P0k9dBgAhxeK1nibj7ee53JUMh6OahYMqWe2QcQPUkiSJD3LiWfOnGHZsmWsXbsWnU7H0KFDGTNmDA0aWPZMjKSkJFxcXEhMTMTZDP28gmASEWfl5CTqvLxdqx90/Qrs3fJ+DYMBjnwrDz6W9OBRHQb+Al4BBRPz80gKvz8g+NZBMOjuP+ZcVk5m/LuBXwtQWZsvzlxIBgO3R44k/fgJHF5sSbklS4pFYczi4FqHjmjv3KH8iuU4NG1q1lgkrZYrTZpiSEujwsaN2NWqadZ48mrD8TtM2XgWpQJ+HdeE5pU9Cuxe+Xn/fuZ1burWrcuCBQsICwtj+vTp/PTTTzRq1Ii6deuybNkynjFnEgThSfRaCPocfmwjJzb27vL07v7L8pfYACiV8MJEGL1DHqMTcxl+bAun1xRI6PmWmQrHl8tdZ98EwM535anbBh14+kPLd2D8Pph0Abp+CZVaW1xiA5Dw2wbSj59AYW9P6enTRWJjQYxdUxawmF/66dMY0tJQublhW8MCP2Dk4nJkMh9tlT9gTWpfrUATm/x65gHFWq2WLVu2sHz5cvbs2UPTpk0ZO3Ys4eHhTJs2jb///ps1ayzkRVIQioOoi3JrTcRpeTugB3SbB47POXDPrxm8egg2j4fre+V73D4sV8O2sX/usPMt5hoc+0lOsjSJ9/f7Nsqa4dQdPKoUflzPQBsVRfRXXwHgNXEi1mXFUvqWRO3vLy8kaAGDilOyu6SaNy8SNcZSNTpeX32CDK2BF6t58kYby/qbzHdyc/LkSZYvX87atWtRqVSMGDGCefPm4Z+14iNAx44defHFormyoiBYHL1O7j4KmgP6THnBuW5fy11RpmoFcPCAYRvh4NfyfU79CmGn5G4qj6qmuceTGPRwZRcc+1FOsLK5VoRGY6H2AHDyKfg4TCzyk08wpKRgW7cOrsOGmjsc4SG2AXILiSW03KRmDSYuClPAJUnif1vOcf1eKj7OtswbWBelBYyzeVC+k5tGjRrRoUMHFi9eTO/evbG2frQZuEaNGgwePNgkAQpCiRZzFba8CmHH5e1qnaHHgoJ5o1eqoNV7UK4JbBoH0RdgaWv5frX7m/5+AKmxcGolHFsGiaFZOxVQtSM0flme7VQEPsXmJjM0VK4RpFJR+pNPUKhU5g5JeIht1qBizY0bSJmZZiuDoYuLI+PiRUBuubF0a/+7w9bT4aiUChYOrY+7o+VNKMp3cnPjxg38/J68RoSDgwPLly9/5qAEocQz6OHoYtj7iVweQO0CXebK07wLesxGpVZyN9WmsfLg3U1j5dlUnT4DaxMtyhV2Av77Ec5vBr1G3mfnCvVHQMMx4FbRNPcxo+R/5BYo+0aNsK1m/qmxwqOsypRB6eyMISkJzfXrxpacwpZ65F+QJNTVqxda8dBndT4skRl/XADgvU7VaVQhn2P9Ckm+k5vo6GgiIyNp0iTnAkPBwcGoVCoaNmxosuAEoUSKvS6vJhz6r7xduS30/A5cCnG8hpM3jPgd9s+FA1/C8Z/l1qMBK8Ct0rNdU5sBFzbLSU34yfv7S9eVW2lq9QNrO1NEbxFS/pErOzu1LfhCnMKzUSgU2Pr7k/bff2RcCjFfclNEuqSSMrRMWHOSTJ2Bdv5ejG/5jK8FhSDf7b1vvPEGd+7ceWR/WFgYb7zxhkmCEoQSyWCA4KXwwwtyYmPjKHcJDd9cuIlNNpUVtP0Qhm0COzeIOANLWsHFbfm7Tvxt2DNdnvH0+2tyYqOygTqDYOzf8PJ+qD+8WCU2uvh40k7KCZxTO5HcWDLbgKwK4ZfNM+5GkiRSD8uDiR0teH0bSZL4YNNZbsWmUbaUHV9b4DibB+W75ebixYu5rmVTv359Lmb1GQqCkE/xt2HbBLh5QN6u0BJ6fW+WMgGPqNpe7qbaOAbuHIXfRkDT16H9TLB6zBgFg0Getn3sJ3nlYLKWhnD2hUZjoP7I55/lZcFSgvaDwYDa31/MkLJw6upycpNhphlTmitX0d27h8LWFjsLXifulyO32HkuEmuVgu+G1qeUvXnGJ+VVvpMbtVpNVFQUlSrlbI6KiIjAykqUqhKEfDu/Gba9CZkpYG0PHWZBw7GWNZDWpSyM3i4v+HfkWzi6CO78BwOWQ6kHyrCkJ8CZtXLXU3bxTpDXoGk0Xh4QrSr+rxMpe0WXVFGR3XKTERKCJEmFvg5RdpeUfeNGKC10pf8zdxL4dOclAKZ2CaB+efOv5vw0+X6V6dChA1OnTmXr1q24uLgAkJCQwP/+9z86dOjwlLMFQcjhxC9y+QMkKN9Mbq1xr2zuqHKnsoaOn8hx/p41g+uHltBnCbj4ytO4z/4G2jT5eLWzPAC60TjwLDkDag0ZGcY1SxxFl5TFU1euDNbWGJKS0IWHF3pLW+phObmx1C6pxDQtr68+iVYv0bmmDy+1qGDukPIk38nN119/zYsvvoifnx/169cH4PTp03h7e7Nq1SqTBygIxVbwEvjzPfn7hmPlVXaVRWC6sH9XeOWgXHwz/CSsHZTzca8ackJTZ1DRqFVlYqn//ouUno5V6dLY1qhh7nCEp1DY2KCuVAnN5ctkXL5cqMmNIT2dtOMnAMusJyVJEu9sOENYQjrl3ez5YkCdIrPCdr6Tm7Jly3L27FlWr17NmTNnsLOz46WXXmLIkCG5rnkjCEIuDs2Hv6fL3zebAB1nF62q3K5+MGYX7PkIgn8AhUpeMbnxeLm+U1F6LiaWsleeAu7Upk2ReSMo6Wz9/eXk5tKlQu1KTDt+HCkzE6vSpbGpaHnLH/x08CZ/X4rCRqVk0bAGONsWnff4Z+r8dnBw4OWXXzZ1LIJQ/EkSBM2Vp1gDvPgetPlf0UwGrGygy+fy2jQOHkVyBWFTkwwGkvcFAaJLqihRB/jD1q1oCnml4uzxNo4vtLC4RPj4rTjm/iX/PD7uUYNaZV3MHFH+PPPIvosXLxIaGkpmZmaO/T179nzuoAShWJIk2POxPCAXoN10aDnZvDGZgk8tc0dgMdLPnEEfE4PS0RGHRo3MHY6QR7b+2YOKLxfqfY31pFpYVpdUXGomE9acQm+Q6FG3DMOalH/6SRbmmVYo7tOnD+fOnUOhUBirf2dnnXq93rQRCkJxYDDI42uO/Shvd/4cmr5q3pgEk8vuknJ88UWzLeUv5J86qwyD9s4d9MnJqJycCvye2ogIMq9fB6USh2ZNC/x+eWUwSExaf5rIpAwqeTgwp29ti2tVyot8zzV9++23qVixIlFRUdjb23PhwgUOHDhAw4YNCQoKKoAQBaGIM+jhjzezEhsFdJ8vEptiKrvkguiSKlqsXF2xKl0aAM3lwmm9yV64z652bVQultPls3j/dfZfuYfaSsmi4Q1wVBfNpRvyndz8+++/zJo1C09PT5RKJUqlkhdeeIE5c+bw1ltvFUSMglB06bWw+WW5yrZCKU+bbviSuaMSCoDm5k0yb9wAa2scX3zR3OEI+ZRdRLOwuqaMXVIWNEvq3+uxfL1bfv6f9KqFv4+zmSN6dvlObvR6PY6O8vRODw8PwsPDAfDz8+NyIWW8glAk6DLl6dLnN4LSCvovh7qDnnqaUDRld0k5NGpUKN0agmmpjYv5XSrwe0l6Pan/yrXjLKWe1L1kDW+tO4VBgn4NfBnQ0NfcIT2XfLc31apVi7Nnz1KpUiWaNGnCF198gY2NDUuXLn1k1WJBKLG06bB+BFzbI9dRGrgKqnc2d1RCARJdUkWbrb9cNFNTCGUYMs6dw5CYiNLZGbvatQv8fk+jN0i8ve4U95I1VPN25JPeNYvkOJsH5bvl5sMPP8RgMAAwe/Zsbt++TcuWLdm5cyfffvttvgNYtGgRFStWxNbWlsDAQA4ePPjYYw8dOkSLFi1wd3fHzs4Of39/5s2bl+97CkKB0qTA6gFyYmNlB0PXi8SmmNPFxpJ+6hQgSi4UVbb+creU5upVJJ2uQO+VkjXexqFpUxQWULZowT9XOXI9FnsbFYuGNcDexvwxPa98P4NOnToZv69UqRIXL14kLi4OV1fXfGd669evZ+LEiSxatIgWLVqwZMkSunTpwsWLFylf/tGpZw4ODkyYMIE6derg4ODAoUOHeOWVV8S6O4LlyEiE1QPlApM2jjBsA/g1N3dUQgFLCQoCScK2Rg2sswamCkWLdblyKO3tMaSlkXnzJuqqVQvsXqnG8Tbm75I6ePUeC/deBeDTPrWo4lU8ulTz1XKj0+mwsrLi/PnzOfa7ubk9UxPWN998w9ixYxk3bhwBAQHMnz+fcuXKsXjx4lyPr1+/PkOGDKFmzZpUqFCB4cOH06lTpye29ghCoUmLg5W95MTG1gVGbhWJTQlh7JISrTZFlkKpRO1/v4hmQdEnJZF+9ixg/npSkYkZTFx3GkmCIY3L06d+0R5n86B8JTdWVlb4+fmZZC2bzMxMTpw4QceOHXPs79ixI0eOHMnTNU6dOsWRI0do1arVc8cjCM8l5R6s6A7hp8DeHUZtB9+G5o5KKASG9HRSs16znMR4myLNuJhfAY67Sf33KOj12FSqhHWZMgV2n6fR6Q28tfYUsamZBJR2ZnqP4lUH7ZnG3EydOpW4uLjnunFMTAx6vR5vb+8c+729vYmMjHziub6+vqjVaho2bMgbb7zBuHHjHnusRqMhKSkpx5cgmFRSOCzvAtEXwNEbRu+E0nXMHZVQSFKPHEHKyMC6TBnjJ3+haFJnj7spwJab7PVtHFqYt0vq6z1X+O9WHI5qKxYNa4CtdREo2psP+R5z8+2333Lt2jXKlCmDn58fDg4OOR4/efJkvq73cHeWJElP7eI6ePAgKSkpHD16lA8++IAqVaowZMiQXI+dM2cOM2fOzFdMgpBn8bdhZU+IvwXOvjBqG7hXNndUQiF6sEuqqM8wKelsA+QZUxkhIXl6L8ovSZJy1JMylz0Xo1gcdB2Az/vVoaKHw1POKHryndz07t3bJDf28PBApVI90koTHR39SGvOwypmVU+tXbs2UVFRzJgx47HJzdSpU5k8+X79nqSkJMqVK/ec0QsCEHsdfukJSXfBtQKM+gNKFb0aLMKzk/R6eTAxokuqOFBXrQpKJfq4OHTR97D29jLp9TNv3kIbHo7C2hp7M9QeO3c3kYV7r7L7YhQAo5r50a1O8RwAn+/kZvr06Sa5sY2NDYGBgezZs4c+ffoY9+/Zs4devXrl+TqSJKHRaB77uFqtRq1WP1esgvCI6Evy4OGUKPCoJg8edjZf/7lgHumnT6OPi0Pp7Ix9QzHGqqhT2tpiU7Eimdevo7kcYvLkJrvVxq5hIEp7e5Ne+0lO3I5n4d6rBF2+B4BCAb3rleV/3QIKLYbCZtbJ7JMnT2bEiBE0bNiQZs2asXTpUkJDQ3n1VbnuztSpUwkLC2PlypUAfP/995QvXx7/rH7tQ4cO8dVXX/Hmm2+a7TkIJVDEGVjVB9JiwbsWjPgdHD3NHZVgBsYuqRdfRGFtbeZoBFOw9fcn8/p1Mi6FmLyMRvZ4G8dCGG8jSRJHb8SxcK+8hg2AUgG96pXljTaVi82U78fJd3KjVCqf2A+Zn5lUgwYNIjY2llmzZhEREUGtWrXYuXMnfn5+AERERBAaGmo83mAwMHXqVG7evImVlRWVK1dm7ty5vPLKK/l9GoLwbO4eh1/7yuvZlKkPwzeDvZu5oyq2DJmZpB44gEPz5oX6STcvJEki5Z9/ANElVZzYBviTtGOHycswGDIzSf3vP6Bg60lJksSBqzF8t/cqx27FA2ClVNCvgS+vta5MhWI4viY3CkmSpPycsHXr1hzbWq2WU6dO8csvvzBz5kzGjh1r0gBNLSkpCRcXFxITE3F2LrpFwQQzuHUY1gyEzBQo1xSG/SavZyMUCEmv5+6bb5Gydy8u/ftRZvZsc4eUg+b6dW506w7W1lT79wiqrJp7QtGWcvAQd8aPx6ZiRSr/udNk1009epTQ0S+h8vSg6oEDBTJY+e9L0Xy39ypn7iYCYKNSMqhROV5pVQlfV8v6cPAs8vP+ne+Wm9zGw/Tv35+aNWuyfv16i09uBOGZXN8La4eCLh0qvgiD14JavJkVpHvz5hmLUSZu3YbnG29Y1Oq/2V1SDk2aiMSmGLHNKqCZeesWhrQ0k7UYGmdJNW9h0sTGYJD483wk3+27xqUIeakTW2slw5r48fKLlfB2tjXZvYoSk425adKkCePHjzfV5QTBclz6AzaOAX0mVO0IA1eCtZ25oyrWEjZvIfannwGwKl0aXUQEcSt+wXvqB2aO7D7RJVU8WXl4oPL0QH8vBs2VK9jVq2eS66Yclhd6NFXJBZ3ewPazEXy37xrXolPka9uoGNGsAuNaVsTDsWRPpDFJcpOens7ChQvx9S0+SzcLAgD//Qg7pwAS+HeH/svBysakt5AMBnSRkVh5e6NQFa+FtJ5F2okTRGTNynR/7VXsGwRyZ/x44jdswP3VV7BydTVzhKC7d+/+Evqi5EKxY1vdn9R7h8gIuWyS5EYXE4PmkjyGx6H585Vk0eoNbDkZxqKga9yKTQPAydaKl1pUZEyLCpSyN+3rU1GV7+Tm4QKZkiSRnJyMvb09v/76q0mDEwSzkST4ZyYcyqo6Hzgaun4NKtNOMNSGhXH3rbfJuHABpZMT9oGB2DdqhH3jxtgG+FtExeDClHn3LncnvAlaLU6dOuH55pugUKAOCEBz6RLxa9bg+cYb5g6T5H375EKZtWph/ZR1uYSixzbAn9RDh0w2qDh7lpRtjRpYubs/0zU0Oj0bjt9lcdB1whLSAXC1t2Zcy0qMaOaHs62YrfegfL9yzps3L0dyo1Qq8fT0pEmTJrhawCcqQXhuukzY9iacXSdvt/kQXnxXXhzChFKPHCFs8jvoExIAMCQnkxIUZFwUTunggF3DQByyk50aNYp1sqNPSeHua6+hj4/HtmZNysydg0IpV4jxGD+OsMnvEL/qV9xfesnsM6dSssbbiC6p4im7jIbGRDWmUoxVwPM/Syo9U8/a/0JZcuA6UUnymm4ejmpeebESQ5uUx0FdfF8Tnke+fyqjR48ugDAEwUJokmH9CLixDxQq6Pkt1B9u0ltIkkTczz8T/c08MBiwrVmTsvPnoU9MIu3YMdL++4+0EycwJCWRuv8AqfsPAKC0t8cuq2XHoXEjbGvWLDZrq0h6PWHvvIPm6jWsPD3xXfQ9Srv745qcOnbEunx5tKGhJGzchNvIEWaL1ZCaSuq//wLg2Lad2eIQCo6xDMOVK0h6fY7uYr1B4vitOPZfuYdWb0BtpcLWWonaSoXaWolt1r9qq6x9Kih18BAKIKFWAzRxafJx1irUVkpsVLkvr5Ki0fHr0dv8dPAGMSmZAJR2seXVVpUZ1KhcsasFZWr5Tm6WL1+Oo6MjAwYMyLF/w4YNpKWlMWrUKJMFJwiFKjkSVg+AyLNg7QADf4GqHUx6C31KKhH/+x/Ju3cD4NK3Lz7TP0apVkM5sKtVE/eXRiPp9WguXybt2DFS/ztG2vHjGBITST14kNSDB7kHKOztsa9fP6sbqxF2tWqhsCma/e3RX35F6v4DKNRqfBcteqSrR2FlhfuYMUTOmEHsiuW4DhlstsQu5fBhpMxMrH19UVerapYYhIJl4+eHwtYWKT2dzNBQrPwq8N/NOHaei+CvC5HcS378qvgPq5wQxncJ8aRZqRn0dwK6vftyPK5QcD8RslIaE6SopAySMnQA+Lra8XrrKvQLLIvaSiQ1eZHv5Gbu3Ln88MMPj+z38vLi5ZdfFsmNUDTduwK/9oPEUHDwhKG/QdkGJr2F5sYN7r75FpnXr4O1NT7TplFq0MBcP7UpVCpsa9TAtkYN3EaNQjIY0Fy5Qtp/x0g79h9px46jT0gg9fBhY3++wtYWu/r1cGjcGPtGjbCtUwdlEUh24jdsIG7FCgDKzJ2DXe1auR7n0qc39777Dl14BEk7d+KSjzItpvRgl5QolFk8KVQq1FWrknHuHL+s2s1SZWViUu4nNM62VrSv4Y2no5oMrR6NzpD1pSdDK/+r0RrI0OlpGS5PAb/sUxUHBzvjMdkkCTK0hhz7slXycOD1NlXoVa8M1iplwT/xYiTfyc3t27eNhSsf5Ofnl2M1YUEoMkKDYe0gSI8Ht0owfJP8rwkl7dlDxAdTMaSmYuXtje+C+fmahaFQKrH198fW3x+3kSPkZOfqtfvdWMeOoY+PJ+3fo6T9e1Q+R63Grl497Bs3wqltW2NTuyVJDf6PyJmzAPB4cwLOXbo89lilWo3bqJHc+/obYn/6CecePYxjcgqLpNMZx0SJLqniR6c3EJzVQlMm3Ym2QNjxs8TU8MXFzpqONbzpWqc0LSp7YGOVt9+92yN/Ig3o/FJvhg7rCMhd05n6rIRI+1BSpDOQodVjrVLSoLwrKqVIoJ9FvpMbLy8vzp49S4UKFXLsP3PmDO7POApcEMzm0nbYNBZ0GVA2UG6xcfAw2eUlvZ57C74ldulSAOwbNqTs/HlYeTzfPRRKJbbVq2FbvRpuw4fJL5bXrpF67FhW684x9LGxpAUHkxYcTMx33+Px5gQ8Xn210BOCx8kMDSXsrbdAp8O5a1c8Xn/9qee4Dh5M7JKlaK5eIyVoP05t2xRCpPelnTyJPjERlYsL9oGmbdkTzEOnN3D0Rhw7zkWw+0Iksany+JZu9t60BVoQT5uXGtGiike+W08MqamknToFgOMDg4kVCkVWN5QKSuYaewUu38nN4MGDeeutt3BycuLFrKJi+/fv5+2332bw4MEmD1AQCsyxn+Q1bCQDVOsM/ZeBjenqruji4wl/511Sj8iLd7mNGoXXu+8UyFgRhUKBumpV1FWr4jZ0qJzs3LhB2rFjpATtJyUoiJhvF5J++jRlPv/c7GvF6JOTufPqa+gTE7GtXZvSn32apy4elZMTrkOGEPvjj8QuXYpjm9aF2jWU3SXl2LpVsZ65Vtxp9QaO3ohl57kIdl2IIi4roQF5enWnmj70bNYezm6hYkIYVas/W3Xw1P/+A60Wa19frMuXN1X4Qh7k+69z9uzZ3L59m3bt2mGV9cdtMBgYOXIkn332mckDFASTkyTY+wkc/FrebjAKun1j0jVs0i9cIOytt9GGhaGws6P0J5/g0r2bya7/NAqFAnXlyqgrV8Z18GASNm8hcuZMUg8c5Fa//pRdsOCxY1sKmqTTETZxEpk3bshddN9/h9I27x9f3UaOIO6XX0g/fZr0Eyewb9iwAKO9T5IkkrPKQYguqaJHqzdw5HosO89GsPtiJPFpWuNjbg42dKrpTdfapWlayR1rlRJ9SipXFAp00dHo4uKwcst/gdxU4xRw05ZcEJ4u36/mNjY2rF+/ntmzZ3P69Gns7OyoXbu2sZK3IFg0vVZew+bMWnm7zTR4cYpJ17BJ2PI7kTNmIGk0WJcvj+/ChdhWr2ay6z+LUn37YFsjgLtvvY02NJTbQ4fi/YQBzQUpau7npB4+jMLOjnKLF2Htlb9PxVaenrj07UPCuvXE/Pgj5QspudFcvYr2zh0UNjY4mmgJfaFgafUGDl+LYee5CHZfjCLhgYTG3cGGTrV86FqrNE0ruWH1UJeTytEB6/Ll0N4ORRMSgtUzrCxsrCdVgFXAhdw980fVqlWrUrWqmAYpFCGaZPhtpFwEU6GCHvOhwUiTXV7KzCRq7lzi18iJk2OrVpT58gtUFlJ93tbfn4obNxD+v/+R8vc/RM6YQfqpk/jMmJFjTZmCFL92LfFZK5mX+XwutjVqPNN13MeMIeG3DaTuP0DG5cvYVq9uyjBzlV3E075ZU5QOpuu+FEzvSlQyyw/fZOe5SBLT7yc0Ho42dKrpQ7fapWlc8dGE5mG2/gFob4eScSkk32UTMu/eJfP2bVCpsG/a9Jmeh/Ds8j2ysH///sydO/eR/V9++eUja98IgsVIjoIV3eTExtoehqwzaWKjjYrm9shRxsTGY8IEfBcvspjEJpvK2RnfhQvxmvIuqFQkbt3GrYGD0Ny8WeD3Tj1yhMjZnwLgOXEizh07PvO1bMqXx7lzZwBif/zJJPE9TXYVcCfRJWWRJEni0NUYRi37j47zDrD2vzskpmvxcFQzvGl51oxvQvD/2vNpn9o0r+Lx1MQG7lcIzwjJ/0rF2V1SdvXqiarxZpDv5Gb//v106/bo2IHOnTtz4MABkwQlCCYVcxV+bg8RZ8DeA0Zvh2rP/sb6sLTjx7nZrx/pp0+jdHLCd/EiPCe8YTGzkh6mUChwHzuW8suXofLwQHP1Krf6DyApa2HBgqC5eZO7EyeBXo9zzx64v/Lyc1/Tffw4AJJ27iTzzp3nvt6TaKOiyTh3DgDHNq0L9F5C/mTqDGw6cZeu3x5i+M/B7L9yD4UCOtf0Yc24JgT/rx2ze9emeWWPfE+rVme1CGqeJbk5nN0lJbowzSHfr74pKSnY5LIwmLW1NUlJSSYJShBM5s5/8HNHSAiV164Zt0ee8m0CkiQRt+pXbo9+CX1MDOpq1ai4cQNObQp3evKzcmjcmIqbN2HXMBBDaiphb71N1OdfIGm1Tz85H/SJidx99TUMSUnY1atH6U8+Mck4H9uAABxatgSDgbjly00Q6eOl7JNXlbWtWyffY4SEgpGYpmVx0HVafrGXdzac4VJEEnbWKkY18yPo3db8MCKQ5lXyn9A8KHttKM2NGxg0eV+VWNJqSc1ab+pZ6kkJzy/fyU2tWrVYv379I/vXrVtHjWfsPxeEAhGyE37pAelxUKYBjNltssX5DOnphL/3PlGffiqv09KtGxXWrcWmiA2st/bywm/5ctzGjAEgbvlybo9+CW1UtEmuL2m13J04kczbt7EqUxrf7xbKpSZMJLv1JmHTZnQxMSa77sOS9/4DiC4pS3AnLo0Z2y7QbO4/fP5XCFFJGryc1EzpVJ1/p7ZlZq9a+LmbZkyUlbc3qlKlQK9Hc/Vans9LP3cOQ0oKqlKlnnlcmfB88j2g+KOPPqJfv35cv36dtm3lirj//PMPa9asYePGjSYPUBCeyfFlsOMdeQ2bqh1hwAqTrWGTeecOd998S26qVqnwfm8KriNHFtmpngpra7zfm4Jd/XpETP0f6SdOcLNfP8p+/TUOTRo/83UlSSLy009J+/coCnt7yi1e/NyLFz7MvlEj7OrWJf3MGeJW/YrXpIkmvT7I9cCyV30WVcDN52RoPD8dvMFf5yMxSPI+fx8nxrWsRI+6pQuk5pJCoUAd4E/av0fRhFzCrlbNPJ2XPUvKoXmzHEU3hcKT75abnj178vvvv3Pt2jVef/113nnnHcLCwti7d+8jqxYLQqGTJNg7G7ZPkhObBiNh8FqTJTYpBw5ws19/NCEhqNzdKb98GW6jRhXZxOZBzh06UHHjBtTVqqGPiSH0pZeI+fFHJEl6puvFr15Dwrr1oFBQ9qsvC2RGk0KhwP3l8fL91qxBn5Ji8nukHjqEpNVi7Vcem8qVTX594fH0Bom/zkfSb/ER+i46ws5zcmLTsqoHK8c05s+3W9I/0LdAi0naVs8eVHw5z+ekZK9v00J0SZnLM00F79atm3FQcUJCAqtXr2bixImcOXMGvV5v0gAFIc/0WvjjbTi9Wt5uPRVavW+SNWwkg4GYH34gZuF3IEnY1a1L2QXzsfbxee5rWxKbChWosH4dkTNmkrh1K/e+/ob002coM+ezfM38Sjl0mKisRT293n0Hp7YF1+Lh2KYNNpUrk3n9Ognr1+M+dqxJr/9gl1RxSGKLgrRMHRtP3OXnQze5HZsGgLVKQa96ZRnXsiL+PoU3C/H+jKlLeTpeFx9vHHzuIAYTm80zr3Ozd+9eli1bxubNm/Hz86Nfv378/PPPpoxNEPJOk5K1hs0/8ho23edBoGkq1OsTEgj/3zTjOielBg/C+3//KxIVt5+F0s6O0nPnYNegAVGzZ5Pyzz/c7D8A3wXz81R8U3P9OmGTJoHBgEufPsbxPAVFoVTiPm4cEVOnErtiBa7Dh5tsXI+k1ZKyX54FKrqkCl50Uga//HuL1cGhxgX3XOysGd60PKOaVcDLufALMan9swYVh1xGkqSnJrhpR4+CJKGuWhVrb+/CCDHfdt3axeno0zQr04zGPo2xtSp+Ba7yldzcvXuXFStWsGzZMlJTUxk4cCBarZZNmzaJwcSC+WQkwspeEH5KXsNmwAqo1skkl07as4fImbPQx8SgsLHBZ/p0SvXra5JrWzKFQoHroIHY1qxJ2Nvyqsa3Bg+Rn3/fPo89Txcfz53XXseQnIxdYCA+M2cUSmuHS7eu3Pv2W3QRESRu3YrrwIEmuW7aiZMYEhNRubpiV7++Sa4pPOpyZDI/HrzBttPhZOoNAJR3s2dcy4r0D/TF3sZ8dbzUlSqisLbGkJKCNiwMG1/fJx6fkj3epoVlttrEpMfwwcEP0Bl0/HrpV+ys7GhauiltyrWhpW9LPOxMOy7OXPL8G9O1a1cOHTpE9+7dWbhwIZ07d0alUvHDDz8UZHyC8GS6TFg/Qk5s7N1h6Abwff6p3rq4OCI/+YTkP/8CwKZyZcp8/nmeBxQWF3a1alJx00bC3n+f1P0HiPjf/0g/dRLvDz98pHVEysyU62mFhmJdtiy+C78ttNYthY0N7qNHETVnLrE//0ypfv1MMpAzu0vKsXVrMTDUxCRJ4tC1GH48eJMDV+4Z9wf6uTK+ZUU61PB5rmncpqKwtsamahU0Fy+RcenSE5MbSZIeqCdlmeNtNlzZgM6gw9veGwmJ6LRo9t3Zx747+1CgoLZHbVqXa02rcq2oWqpqke2KzXNys3v3bt566y1ee+01UXZBsAySBH+8BTf3g40jjNgCpes+5yUlkv/8k8hPZqOPjweVCvdx4/B4/TWTTmEuSlSlSlFu8WJily7l3oJvSdiwkfQLF/BdsACbcuWArJlRn8wm7dgxlA4O+C5e9EyFBp9Hqf79iVm0GO3tUJL37DGuYPysJEkyVgEXXVKmdfZuAh9vvcDpOwkAKBXQuZYP41pWokF581asz42tfwCai5fQXAqBDh0ee1zmtWvooqJQqNXYNzTNelqmpNVr+e3ybwBMDpxMl4pdCIkLIehuEEF3grgYe5GzMWc5G3OWb099S1nHsrTybUWrcq1o5N0Ia5W1eZ9APuQ5uTl48CDLli2jYcOG+Pv7M2LECAYNGlSQsQnCkwXNlQtgKlRyV9RzJja6e/eInDWL5D1/A6CuVo3Sn31W4lprcqNQKvF49VXs6tQh7J130Vy8xM1+/Snz+Vyc2rQhfuVKEjZsAKWSst98jW21wi8UqnRwwHX4cGK+/57YpT/i1KnTc33q1Fy5Ild1V6vzXVdIyF18aiZf7LrMumOhSBLYWasY1KgcY1pUpLy7vbnDeyxb/+okAhmXnzxjKuWw3Gpj36hRvirdF5bdt3cTkx6Dp50nHfw6oFAoCHAPIMA9gNfqvkZUahT77+5n/939BEcEE5YSxpqQNawJWYOjtSPNyzSndbnWtCzbklK2pcz9dJ4oz8lNs2bNaNasGQsWLGDdunUsW7aMyZMnYzAY2LNnD+XKlcPJyakgYxWE+079Cvuzapx1/waqPv7T1NNIkkTStm1EfjYHQ2IiWFnh8coreLzyMopiOmj4WTk0b07FLZsJmziJ9NOnufva6zh3707Szp0AeL03BcdWrcwWn+vwYcQuW0bGxYukHjmC43OMe0j+R+6ScmjeHKW95b7xFgV6g8Ta/0L5avdl40DhPvXLMrWLv1kGCeeX2l+eMaW59OQZU8YuKQsdb7Pm0hoABlYfmGsrjLeDNwOrD2Rg9YGkadM4GnGU/Xf3E3QniLiMOHbf3s3u27tRKpTU86xHm3JtaFWuFRVdKhbyM3k6hfSsi1gAly9f5ueff2bVqlUkJCTQoUMHtm3bZsr4TC4pKQkXFxcSExNxtrCihkIeXd8LqweAQQct34F2Hz/zpbRRUUROn0FKUBAA6hoBlPnsM2yzXsyE3EmZmUR9+RXxq1YZ95UaMACfWTPN3kcf+dlnxK9chX3TpvitePayDDf79SfjwgVKz/6EUv37mzDCkuVkaDwfbz3P+TC5PI+/jxOzetWiccXC7bZ8HvqkJK40bgJAteCjqFxcHjnGkJHBlSZNkTQaKv2xDbWFDd84e+8sw3YOw1ppze7+u/M1cNggGTgfc56gO0EE3Q3iavzVHI9XcK5AK99WtC7Xmnpe9bBSFswA8Py8fz9XcpNNr9fzxx9/sGzZMpHcCAUr8jws6wyZyVB7APT98ZnWsZEkicRNm4ia+zmGlBQU1tZ4vPEG7mPHoLAuOv3K5pa0cyeRM2dhV78+vt8usIiWLm14ONc6dgKdjgq/rceuTp38XyMykmut24BCQdWDB0y+snJJEJOi4fM/Q9hw4i4ATrZWvNOhGsOb+uWpIreluda2HdrwcMqv/AWHxo+u3J1y6DB3xo3DytubKkH7zJ7kP+z9A++z8+ZOelbuyacvfPpc1wpLCSPoThD77+znWNQxdAad8TFnG2da+raktW9r2pVvZ9JxOvl5/zZJeqVSqejduze9e/c2xeUEIXdJ4XKLTWYy+L0Avb5/psRGGxZGxMfTSc3qH7etU4cyn862uE9aRYFz1644deoESqXFvJhblymDS/fuJP7+O7E//oTvwm/zfY3krDWN7OrWFYlNPun0Bn49epuv91whOUN+0+sf6Mv7nf3xdCq6g/LVAQFow8PRhITkmtxkv544vNDCYv4WskWnRbP71m4AhgYMfe7rlXUsy7CAYQwLGEZKZgqHww+z/85+DoQdIFGTyI4bO9h/Zz/typuvFpv5Fg8QhPzISILVAyE5HDyqw+BfwSp/L5SSwUDC+vVEf/kVhrQ0FGo1nm+9hduokSisxJ/Cs7LEKdLu48aS+PvvJP/9N5obN1BXyl/B1OxZUo5illS+/Hczjo+3nickMhmAWmWdmdmzFoF+ljcDKr9s/f1J+ecfMi6F5Pp4dj2p5xnnVVA2XNmATtJR36s+Nd1NO0HC0caRThU60alCJ3QGHWfunWH/nf1ISGadXSVe0QXLp9fChlEQdQ4cvGDYBrDL34tl5p07RHz4EWnBwQDYNWhA6U9no65oeQPhhOenrlIFx3btSPnnH2J//pkyn+a9GV6fnEzqf/8B4NROVAHPi+ikDOb8GcKWU2GAvKrwlE7VGdK4vEWsVWMKan+5NlrG5UeTG21UFJqrV0GhwL5Zs8IO7Yky9ZnG6d+maLV5EiulFYHegQR6m38avEhuBMsmSXIRzOt75dWHh64HV7+8n24wEP/raqLnzUNKT0dhZ4fXpEm4DhtqkS0Ogul4jB9Hyj//kLjtDzzffDPPdcBSDx4ErRabChXy3eJT0mj1Bn45cov5f18lRaNDoYDBjcozpVN13BzMP/7KlLJLj2RevYaUmZljfFn2LCnb2rWxcrWsVqpdt3YRlxGHl72XWbuJCptIbgTLduArOLUKFErovxzKNsjzqZqbN4mY9iHpJ08CYN+4MaVnf4JN+fIFFa1gQezq1cO+USPSjh0jbsUveH/wfp7OSxZdUnly5HoM07de4Gq0XIm9brlSzOpZk7rlSpk3sAJiXbYsSkdHDCkpaG7ezFHlPnu8jaOFFcqUJIlfL/0KwODqg7FWlpzJEkVvyLpQcpxZD/tmy993+QKq523FWUmvJ/bnZdzs3Yf0kydR2tvjM/1jyq9YLhKbEsb95fEAxP/2G/qEhKceL2m1pBzILpRZcj7l5kdEYjpvrDnJ0B+DuRqdgpuDDZ/3q82W15oX28QG5Hpr2UtEZDyw3o2k15N65AhgeevbnLl3houxF7FR2tCvWj9zh1OoRMuNYJlu7Ietb8jfN38LGo/P02maa9cI/980Ms6eBeQF2Ep/MgvrsmULKlLBgjm88AJqf380ISHErVmD5+uvP/H4tGPHMCQno3Jzw67u8614Xdxk6gz8fOgmC/deJS1Tj1IBw5v6MblDNUrZF68uqMdR+/uTdvw4mpD7KxVnXLyIPiEBpaPjMy07UJBWX1oNQLdK3XCzLTrrCpmCSG4EyxN9SS6GadBCzT7QfuZTT5G0WmJ/XkbM998jabUoHR3x/uB9XPr1s7hpmULhUSgUuI8fR/g77xK/chXuo0c/cbVhY5dUG1Eo80EHrtxjxrYL3IhJBeTilrN61aRmmUcXsyvObAOyWm5C7g8qzp4l5dCsqUWtkRWZGsme23uAgh9IbIlEciNYluRIeS0bTSKUbwa9fwDl/d5TSatFGxFBZugdtHdCybxzF+2dUDJCLqO9cwcAh1YvUnrmzDwPIBWKN+dOnbg3fwHaO3dI2LQZtxHDcz1OkiTj+jaiS0p2Nz6N2dsv8deFSAA8HNVM7eJP3wZlS+SHhgfLMEiShEKhMNaTcmhhWVXAf7v8G3pJT6B3IP5uJW/FdZHcCJZDkwJrBqKPuYtWVYlMz/FoV66+n8iE3kEbEQF6fa6nK11c8PnfVJx79iyRL7xC7hRWVriPHUPkjJnELl+G6+BBuX7C1ly6hC4iAoWtLQ4WNp23sEmSxPLDt/hiVwgZWgMqpYJRzSowsUNVnG0tp3WisKmrVAGVCn1iIrqoKJSOjqSfPgPIi/dZCo1ew8YrGwEYFjDMzNGYh0huhEInSRK6e/fQ3rlzP3G5fRvt6X1kxqSg15QGMuC3D3M9X6FWY13OF5ty5bEpXw5r33LYlC+HXb16udZ8EQSXPn2499336MIjSNq5E5devR45JrtLyqFFC5R2doUdosWISdHw7oYzBF2+B0CTim7M7FUTfx9RrkapVqOuVAnN1avyoGK9HnQ6bPz8sPH1NXd4Rn/e/JN4TTw+Dj60KdfG3OGYhUhuhEKRtHs3ib9vNXYlSRkZjzlSHuegcnXFunw5bHzLyf9mJzLlymHl6YlCKSb6CXmnVKtxGzmSe998Q+xPP+Hco8cjv0PGLqm2JXcK+P4r93jntzPEpGiwsVLyUbcAhjf1Ey2hD1AH+KO5ehVNSAjaqChAHrhuKSRJMg4kHlx9cIEVsbR0JfNZC4VKn5hI+Hvv50xolEqsS5eWExfrBGwS/8PaUY9N35lYvzgUlZOT+QIWiiXXIYOJXboUzdVrpATtx6nt/U+02rAwNJcugVKJY5vWZovRXDQ6PV/+dZmfDt0EoJq3IwuHNKC6j/g7fJhtdX+S+IOMkMtkXLwIWFaX1Mnok4TEhWCrsqV/tZJbzV4kN0KBS9iyBSkjA5vKlfH+4AO5BaZ0aXmFz3MbYdNYKAN0/hyavmLucIViSuXkJCc4P/5E7NKl8oyorBaJ5L37ALCrXx8rt5I1ZfbGvRTeWneK82FJAIxo6se0bgHYWovZYrnJnjGVevgwhpQUsLbOtZCmuTw4/dtFXXK76UXbvlCgJIOB+LVrAXAbORLHli9g4+cnJza3DsPvr8kHNn0Dmr5qxkiFksB1xAgUNjaknz5N+okTxv3Je/8BSlaXlCRJ/Hb8Dt0XHuJ8WBKl7K1ZOiKQT3rXEonNE2TPmDKkyCsz29evj9LBwZwhGUWkRLA3VO5eLYnTvx8kkhuhQKUePoL2dihKJydcenS//8C9K7BuKOgzIaAHdJxtviCFEsPaywuXPn0AiPnxRwD0SUmkHTsOgFMJKbmQmK5lwtpTvLfxLGmZeppVcuevt1+kY02xfMLTWLm5YeXlZdy2pPE26y+vRy/paezTmGqu1cwdjlmJbimhQMWvWQOAS5/e9xdPS4mG1f0gIwF8G0HfH3OsZSMIBcl9zEskbNhA6v4DZFy+jObKVXnGS+XK2FSoYO7wCtyJ23G8tfY0YQnpqJQKJneoxqutKheb6t2FQR3gjy46GrCcelIZugw2XpWnf5f0VhsQyY1QgDLvhpESFASA65AhWTtTYc1ASAgF14owZB1Yl9xpt0Lhs/Hzw7lzJ5J2/knsjz8h6XVA8e+S0hskvtt7jW/3XkVvkCjnZse3g+tTv7xlVbEuCmz9A0jdfwCVm5uxm8rcdtzYQaImkbKOZWnt29rc4Zid+LgsFJiE9etAknBo3hx1xYpg0MPGsRB+CuzcYPgmcPAwd5hCCeQ+bhwASTt3khK0HyjeXVJhCekMWXqUeX9fQW+Q6F2vDDvfaikSm2fk2LoVKBS49OltEctSSJLE6hB5IPEQ/yGolGLMlGi5EQqEQaMhYYPcROo6bChIEvz5Plz5E1RqucXGvbKZoxRKKtsaNXB44QVSDx1CSk9H5emBrYUVPTSVP89F8P6msyRl6HCwUfFJ71r0bWA5C84VBL1Bz/ILy/Fx8KF7pe5PPyGf7OvXp1rwUYsZSHw86jhX469iZ2VH7yq9zR2ORRDJjVAgknb+iT4hAasypXFs1QoOzYNjPwIK6LsUyjcxd4hCCec+fryx6KFT6zYW8QnclNIydXyy/SJr/5NrrtUtV4pvB9fDz90y3pALikEyMP3IdLZe34pKoaJl2ZYFMiVa5Ww5KzZnT//uUalHiZ7+/SCz/zUvWrSIihUrYmtrS2BgIAcPHnzssZs3b6ZDhw54enri7OxMs2bN2LVrVyFGK+RV9kBi1wH9UeycBP9kVfbuOBtq9jZfYIKQxb5xI+waBgLg3K2bmaMxrYvhSfRYeIi1/91BoYDXWldm46vNin1iI0kSnxz9hK3XtwKgl/QcCjtk5qgKVlhKGPvuyOs0iYHE95k1uVm/fj0TJ05k2rRpnDp1ipYtW9KlSxdCQ0NzPf7AgQN06NCBnTt3cuLECdq0aUOPHj04depUIUcuPEn6uXNknDuHwtqaUtqNcHIloIAOs6DZG+YOTxAAUCgUlFu8mAqbNuLQtHi0JEqSxLJDN+n9/WGu30vFy0nNr2Ob8H5nf6xVZv8sW6AkSWLuf3PZeGUjSoWSup51AQi6E2TWuAra+pD1GCQDTUs3pXIp0dWfTSFJkmSumzdp0oQGDRqwePFi476AgAB69+7NnDlz8nSNmjVrMmjQID7++OM8HZ+UlISLiwuJiYk4W1CzYnES/sFUEn//HecqEmUbRoCtC/RbBlXbmzs0QSi2YlI0TNlwhn1ZBS/bB3jxRf+6uDnYmDmygidJEt+c+IYVF1agQMEnLT6hgksFhu8cjqO1IwcGHcBaVfyqmadp02i/sT3JmcksbLuQ1uVamzukApWf92+zjbnJzMzkxIkTfPDBBzn2d+zYkSNHjuTpGgaDgeTkZNyesFy6RqNBo9EYt5OSkp4tYCFPdPHxJO34AwC3CjHg6Q+D14jBw4JQgA5cucfkBwpeftgtgBElqODlwlMLWXFhBQAfNfuIXlV6YZAMuNm6EZcRx/Go4zQr08y8QRaA7Te2k5yZTDmncrzo+6K5w7EoZmunjImJQa/X4+3tnWO/t7c3kZGRebrG119/TWpqKgMHDnzsMXPmzMHFxcX4Va5cueeKW3gCvZbET8ciafXYumZi27wDjPtbJDaCUEAydQY+23mJkcv+IyZFQzVvR7ZNaMHIZhVKTGKz5MwSfjwnrzY9tfFUBlQbAIBSoTS2ZBTHrilJklhzSR7bOMR/CEpF8e52zC+z/zQe/gOUJClPf5Rr165lxowZrF+/Hq8HlsJ+2NSpU0lMTDR+3blz57ljFnKRGov0S2/i950DwLV7axSDV4NaVBUWBFNLytDy2/E79P7+MEsP3ABgeNPybJvwAv4+Jae7ffn55Xx3+jsA3m347iMDarMXswu6E4QZR2AUiODIYK4nXhfTvx/DbN1SHh4eqFSqR1ppoqOjH2nNedj69esZO3YsGzZsoH37J4/jUKvVqNXq545XeIKIs7BuGCkXo9CmuqN0tMN58neipIIgmFCGVs8/l6LZdiaMfSH3yNQbAChlb83n/erQycR1oeIy4rgQc4HGpRujVlnea+ivF3/lmxPfAPBW/bcYVXPUI8c0LdMUtUpNeGo4VxOuFqt6S9nTv3tV7oWTjfgQ+TCzJTc2NjYEBgayZ88e+mQVsgPYs2cPvXr1eux5a9euZcyYMaxdu5ZuxWz6ZpF0fhP8/gbo0om/7QsYKDVgMEo7UVJBEJ6XVm/g0NUYtp0JZ/eFSFIz9cbHqno50rNuGQY1KoeXs61J7peuSyfoThDbb2zncNhh9JKeyi6V+bTlp9R0r2mSe5jCb5d/4/NjnwPwSp1XGF9nfK7H2VnZ0bR0U/bf3U/QnaBik9zcSb7D/jvyytpDAoaYORrLZNZF/CZPnsyIESNo2LAhzZo1Y+nSpYSGhvLqq68CcpdSWFgYK1euBOTEZuTIkSxYsICmTZsaW33s7OxwcRELFxUqgx7+mQWH5wOQ6dqS1NDroFDgOmSweWMThCLMYJA4diuObWfC2Xkugvg0rfGxsqXs6FmvDD3rlsHfx8kk42r0Bj3Hoo6x/fp2/g79m1RtqvExW5Ut1xOvM2zHMF6u8zLj64zHWmneWUdbrm7hk6OfAPBSrZd4o96Tl5doXa61Mbl5uc7LhRBhwVsXsg4JiRZlWlDJpZK5w7FIZk1uBg0aRGxsLLNmzSIiIoJatWqxc+dO/Pz8AIiIiMix5s2SJUvQ6XS88cYbvPHG/V/oUaNGsWLFisIOv+RKT4BN4+DaHnm7xdvEH7cHruPQ8gVsypc3Z3SCUORIksT5sCS2nQlj+9kIIhIzjI95ONrQrXZpetYrQ4PyriYbKHw57jLbb2xn542dRKdHG/eXdSxLt0rd6FapG65qV2Yfnc3u27tZfGYxQXeC+PSFT6nqWtUkMeTX9hvbmX5kOgDDA4YzqcGkp/48Wvm2AuBczDnupd3D096zwOMsSGnaNLZc3QLAsIBhZo7Gcpl1nRtzEOvcPKfoEFg3FOKug5Ud9PoOQ5VuXG3VGkNSEr4/LMapdWtzRykIRcL1eylsOx3OH2fCuRFzv8XESW1F51o+9KxXhmaV3LEy0QJ8kamR7Ly5k+03tnM1/qpxv7ONM53+3959x1VZvg8c/5wDh42AsocsB+6B5t6J4k5NyzK1svTb1JZtG9+07Fd9KzMrtWVq5sytKe4NGC4cgLKXyN7n+f1x8hSJAzhwGNf79eIlPOd+7ue6fRjXuZ97+AxhhN8IOjp3vGnmzbbobbx/9H0yCzPRqDU83elpprSeUqMbNG6P2c7L+15Gq2iZ0GICb3R/464TvUmbJxGRFsHbPd5mfIvx1Rxp9Vp5fiX/PfpfvBt5s3HMxgY1S6pOrHMj6qDzm2Htk1CUDXZe8MBycOtA1m+/oc3KQuPpiU2fPsaOUohaLeF6Pr+fSmDjqQTOJPy97pa5qZp7W7kwsoM7/Vs6YaExTOKQXZTNriu72BS1ieNJx1HQvZ/VqDX09+rPcL/h9PHog5nJrRf7G+o7lECXQN45/A574/by6clP2X11N//trfsjW912X93NnH1z0Cpa7mt2H693f71CPVj9vfoTkRZBSGxInU5utIqWX87L9O+7IcmNuDOtFvYtgJAPdF9794YJP4C1I4qicO3GPlIPPoDKpObeyQlRV6TnFLLldBIbw+M5HpOhP26qVtGnuSOjOrozuLUrNuaG+ZVcXFrMwYSDbIraREhsCIWlfy9kGugSyAi/EQz2HlyhTRadrJz4YuAXrL+0ng+Pf8ip1FOM3zieWYGzeCDggWr7Q7s/bj8v7H2BEqWE4X7DebvH2xW+Vn+v/nwR9gVHEo+QX5KPpWndnPBwJOEI0ZnRWGusGe1/64k3QpIbcSeF2bBuBpzfpPv6nidgyAfw11Lm+eHhFJ49h8rcHLuxY40YqBC1z86zyfx85AoHLqVRqv17BMA9vo0Z1cGdYe3cDLY9gqIonEo9xaaoTWyP2c71wuv61/zs/BjpP5JhvsNwt3Gv9DVUKhX3Nb+Pbm7deOvgWxxNOsq8Y/PYfXU37/Z6t0p1l+dI4hGe3/M8JdoSgryDeL/X+5V6FNbcvjnu1u4k5CZwJOEIA5oOMGicNWX5ed307zHNxmBjZmPkaGo3SW7EraVfhpUPQeo5MDGD4Z9A58llimT8sgKARsOGYergYIwohah1iku1/HfzOb4/FKM/1s7DjlEd3BnRwQ03O8P1HFzJusLmqM1sitpEbPbfi5Q2sWjCML9hjPAbQavGrQy6YrG7jTvfBH3DqshVfHryU44mHWXsxrG80vUVxjQbY5BrnUg6wTN/PEORtogBXgOY33c+purK/clSqVT09+rPL+d/ISQupE4mN1eyrrAvbh8qVDwYINO/70SSG1G+S3/Ab9OgIBNsXGHiz+DVtUyRkvR0srdtA8Bh0qTyahGiwUnLKeSp5aEcjb4GwKO9fHm4e1P8nAz7TjshJ4FX979KaEqo/pilqSX3Nr2XEX4juMftnkonA3dDrVLzYMCD9HTvyRsH3iA8NZy3Dr3Frqu7mNtjbpVmJYWnhPPUH09RUFpAb4/efNzv4ypPQdcnN7EhaBVtnRuvsuK87o1kH88+NTLOqa6T5EaUpShw6AvY9TYoWvDsChN+gkZuNxW9vvo3lOJiLNq3x7JdWyMEK0TtEhGXyZM/nSAhswBrMxM+mdjR4CsHAyTnJvPY9seIy4lDrVLTw70HI/xGMNBrIFYaK4Nf73a8G3nz/dDv+fHsj3wR9gX74vYxZsMY3uj+BkN9hla4F+d02mlm7ppJXkke3d2682n/T2872PludXHpgo3GhmsF14hIi6CDU4cq11lTcopyWH9pPQAPBcj077tRt1JXUb2K8mDtdNj5pi6x6fQwTN1cbmKjlJSQsWoVAA6TpItUiHVhcYz/+hAJmQX4Olqz/qle1ZLYpOWn8fiOx4nLicPTxpMtY7fw9b1fM8JvRI0nNjeYqE2Y1nYav474lVaNW5FVlMXL+17mxb0vklGQcecK/nL+2nme3PkkOcU5BLoE8vnAz7EwNczqyxoTDb09egN1byPNDZc3kFuci6+db73c3bw6SHIjdDLjYekQiFgNalMY9jGM+hJMy99TJickhJLEREwcHGgUHFzDwQpRe5SUanlv01lmrTpFYYmWgQHOrH+qF81dDL/fT0ZBBtN3TCcmKwY3azeWDFmCh42Hwa9TWc0cmrF8+HL+0+E/mKpM2XFlB2M2jGHP1T13PPdixkWe2PEEWUVZdHDqwMJBCw0+q6ku7hKuVbT6R1KTAiY1mN3eq0qSGwE5qfDDCEj6E6yawCMb4J7pcJsfooy/pn/bjx+HWjYmFQ3UtdwiHll6jCUHogF4ZmAzvnukC3aWht+iILMwkyd2PsGl65dwtnTmu6DvDD47yRA0ag0zO85k+fDlNLNvxrWCazy751leP/A6WUVZ5Z4TnRnN9B3TySjMoE2TNiy6dxHWGmuDx9bbozcmKhMuXb9UZvB1bXYw/iBXsq5go7FhlP8oY4dTZ0hy09AVZMHPY+FaFNg1hel7wKf3bU8pjIom99BhUKmwnyj7SImG6UxCJiO/OMChy+lYmZnw9cOdeSGoJWq14d9Z5xTlMGPnDM5fO09ji8Z8O+Rbmjaq3ductG7SmlUjVjGt7TRUqNh4eSNjN4zlUPyhMuVis2J5fPvjpBekE9A4gMWDF1fbLtd25nZ0dukMoN94sra7Mf37vub3Ge2xY10kyU1DVlyg20oh6U+wcoRH1oPDnUfhZ6zQdZHa9O+PmWft6RIXoqZsCI9n3KJDxF/Px7uJFev+04uhbW8em2YIecV5/OeP/3A6/TT25vZ8F/Rdndks0czEjNmBs/kx+Eea2jYlOS+ZJ3c9yftH3ievOI+EnAQe2/EYKfkpNLNvxuLBiyu0sGBl9PfsD9SNR1NRmVEcjD8o078rQZKbhqq0BNY8BjH7wcwWHl4DTfzveJo2N5fMdbpN22T6t2hoSrUK87ac47mV4RQUa+nXwomNT/WmpWv19DQUlBTwzO5nCEsJw9bMlsWDFxtt08qq6OjckdUjVzMpQPc7Y1XkKsZtHMej2x8lMTcRn0Y+fBv0LY0tGld7LAO8dGvcnEg+QWZhZrVfrypWnNO9kezn1Q8vWy8jR1O3SHLTECkKbHpet+qwiRk8+Au4d7yrUzN//x1tTg4a76ZY9+pZrWEKUZtczyti6rJjLN4XBcDM/v4sndoVOyvDj68BKCot4vk9z3Ms6RjWGmu+vvdrWjdpXS3XqglWGite7fYq3wV9h5u1G3E5ccTnxONl68V3Qd/haOlYI3F4NfLC386fUqWUg/EHa+SalZFdlM2GyxsA2f27MiS5aYj+eAfCfgKVGsYvBd++d3WaoihkLL+xj9SDqNTy7SMahvNJWYz68iD7L6ZhqTHhy0mdeGVoACbVML4GdHtDvRDyAgcTDmJpaslXg76ivVP7arlWTevm1o21o9byQMsH6O7Wne+CvsPF2qVGY9DPmooLqdHrVsT6S+vJL8nH386fbq7djB1OnSOL+DU0h76AA5/qPh/xGbQaeden5p84QeHFi6gsLLC/777qiU+IWmbzn4m8uPoU+cWleDW25JvJXWjl1qjarleiLeGV/a8QEheCuYk5Xwz8Qj8Itr6wMbPh9e6vG+36/b36s+T0Eg7EHaBYW1zl1Y8NrVRbyi/ndG8kJ7WS6d+VIW+9G5LwX2DHG7rPB70NgVMqdPqN3b/tRo7ExK56B/0JYWylWoUPt53nqV9CyS8upU9zRzY+1btaE5tSbSmvH3idnVd2olFr+GzAZ3Rzk3fthtbOsR2NLRqTXZxNaHLonU+oYQfiDxCXE4etmS0j/EYYO5w6SZKbhiJyK2x4Wvd5j6eh96wKnV6ckkL2zl0AODwkA4lF/ZaZV8yj3x9nUchlAJ7o68eyqV1xMNAO3uXRKlreOfwOW6K3YKoy5eN+H+tX1BWGZaI2oa+n7nF8bZw19cPZHwAY13ycTP+uJEluGoKYg7B6Kiil0GESDH7vtgv0lef6r6uhpATLzp2xCAionjiFqAUuJGczeuEB9l5IxUKj5n8PdOS1Ya0wNam+X5eKovDB0Q9Yd2kdapWa+X3nM7DpwGq7nvh73M2e2D0oimLcYP4hPCWc40nHMVWbykDiKpAxN/VdUgSseABKCqBFMIz6Aio4EFgpLua6fh8p6bUR9de204m88OspcotK8bC35JtHAmnjXr2PYBVFYcGJBayKXIUKFe/3ep8hPkOq9ZoCerj1wExtRnxOPJeuX6o1U+y/i/gOgFH+o3C1NvzeZA2F9NzUZ9ei4KexUJgFTXvC/cvApOL5bPYff1CSmoqJoyONggZXQ6BCGJdWq/B/OyKZ8XMouUWl9PRvwu/P9K6RxObzsM/56exPAMztOZeR/nc/yF9UnpXGiu7u3YHa82gq8loke+P2okLFtDbTjB1OnSbJTX2VnQQ/3Qe5KeDSDh5cAZrKbUJ3Y/q3/f3jUZlV35gDIYwhq6CY6T+e4IvdlwB4rLcvPz56D42rcXzNDYv/XKx/p/56t9cZ23xstV9T/K22TQlfcnoJAEE+QfjY+Rg3mDpOHkvVR/nX4edxkBEDDj661Yct7StVVcGFC+QdPw4mJjhMnGjAIIUwnsKSUq6m53ExJYePt0cSlZaLuama+ePacV8nzxqJYenppSwMXwjAS11e4oEA2aetpvXz7AdARGoEaflpNbaQYHmuZl1le8x2AB5v97jR4qgvJLmpb4rydGNskk+DtTNMXge2lV8g68Y+UrYDB6Jxlee/ou5QFIX03CIup+QQlZZLVGoOl1N1/169lof2H2NI3e0sWDy5C+08a2aJg+XnlvPpSd16U891fo5H2jxSI9cVZTlbOdOmSRvOpJ9hX9w+o/acLT29FK2ipY9HHwIay6SNqpLkpj4pLYbfpsHVw2BuB5PXQuPKb7BXmpND1oaNgEz/FrVXUYmWK+m5usQlLYfLKTf+zSGroOSW59mYm+LvZE1bDztmDW6Bo415jcT7a+SvzD82H4An2z8p79KNrL9Xf86kn2FP7B6jJTfJuclsvKz7XSvfD4YhyU19odXCxmfgwjYwtYBJK8G1XZWqzFy/AW1eHmb+/lh1k4XEhPHc6IWJSr3RA5NDVGoul1NziM3Ip1Rb/lRelQo8HSzxc7TB38kGPydr/JysaeZkg5OteY2v/Lrh0gbeO/IeANPaTOOpjk/V6PXFzQZ4DWBh+EKOJBwhvyQfS9PKjU2sih/P/kixtpjOzp3r3WrUxiLJTX2gKLDzTTi1AlQmcP/34F21TS0VRdE/knJ48EFZ/lvUuJzCEtaGxrExPIGLKTlk5hffsqy1mQn+zjb4OVr/lcTY4O9sjU8Tayw0JjUY9a1tjd7KW4feAmBSwCRmBc6Sn6taoIVDC9ys3UjMTeRo4lH9IOOacr3gOqsvrAZgevvpNXrt+kySm/rgwKdw+Evd56O/hJbBVa4y7+hRii5fRm1lhd2Y0VWuT4i7dSU9lx8OXWH1iViyC/9+rKRSgYe9pS5xcbLW/+vvZIOzEXphKuKPK3/w6v5X0SpaxrcYz5x75tTqeBsSlUpFf6/+rDi/gpDYkBpPbn45/wv5Jfm0atyKXu69avTa9ZkkN3XdyR90u3wDBP0XOhpmbMyN6d+NRo/CxMbGIHUKcSuKonDgUhrfH4xhd2QKNxaM9XW0ZnJ3b3r4N8HXsfb0wlTEvrh9vLjvRUqVUkb5j+LN7m9KYlPL3Ehu9sbtRatoUatqZpWU3OJclp9bDsBj7R6T7wsDkuSmLju7ETY9r/u89yzo+bRBqi1OSiJ7924AGsuKxHVa7l+Pdq7lFtOnhSMdPO0xUdeeX6B5RSWsDY3n+0MxXErJ0R/v18KJqb186NfcCXUtireiDiUcYtaeWZRoSwj2Cebdnu/W2B9Ocfe6unTFWmNNWn4aZ9LO0M6pauMV79bqyNVkFWXh08iHe5veWyPXbCgkuamrovfBmsdA0ULnR3S7fBtIxqpVUFqKVdeumDevHUuSi4pJzS7k+0PR/HT4in7G0Ke7LtDE2oz+LZ0Z1MqZPs0dsbXQGCW+2Gt5/Hg4hpXHY8n+Kz5rMxPu7+LF5B7e+DvV/d7CpNwkZu2ZRZG2iEFNB/HfPv/FRF33ep4aAo2Jhl7uvdhxZQd7YvfUSHJTWFqo3yDz0baPyveGgUlyUxclhMGKB6G0CAJGwPBPK7wR5q0oRUVcX/0bINO/66Ko1By+3R/NmtA4ikq0gO7RToCrLQcuppGeW8Sa0DjWhMZhqlbRza8xA1o6M6iVC76O1tUam6IoHL6czrJDMew6l6x/9OTdxIopPXy4v4un0ZKt6vDJiU/IK8mjvVN7FvRdgEZdf9pWH/X36s+OKzsIiQvh2c7PVvv1NlzaQFp+Gq7WrozwG1Ht12toJLmpa9Iuwc/joSgHfPrAuCWV2i/qVrJ27KQ0LQ1TZ2dsBw0yWL2ieoVdzWDx3ii2n03SJw0dveyZ0c+fwa1dMFGrKC7VcjzmGrvPpbA7MoWo1FwOXkrn4KV03t98Dj9HawYGODOwlTNdfRqjMdAu2PlFpawLi+f7Q9FcSP770VOf5o5M6+VD/xbOdfrRU3mOJx1na8xW1Co1b3Z/E42JJDa1XV/PvpioTLiYcZH4nHg8bDyq7Vol2hKWnl4KwNQ2U+X7oxpIclOXZCXAT2MgLw3cOsADv4DGwqCXyPjlr32kJkxApZEfuNpMq1XYE5nC4n1RHIu+pj8+KMCZJ/v509XHocwARY2Jmp7+jvT0d+SNEa2JTstl9/kUdp9P5mjUNd0qvgei+e5ANLbmpvRt4cTAAGf6t3SiSSUWuIu9lsfPR66w8nisfhq3lZkJ4zp7MqWnN82cbav+n1ALlWhL+ODoBwDc3+J+WW22jrAzt6OTcydOJJ8gJDaEh1o9VG3X2hazjficeBzMHWQ/sWoiyU1dkZ+h2+E7MxYa+8NDa8CikUEvUXD+PPmhoWBqiv2E+w1atzCcohItG8Lj+WZfFBf/GoSrMVExpqMHT/T1o7nL3SUNvo7WPNbbl8d6+5JdUMyBi2n8cT6FPedTSM8tYnNEIpsjElGpoJOXPYNauTAwwJkAV9tbzupQFIUjUdf4/lA0O88m67c4aNrYikd6eHN/Fy/sLOt30rwqchWXrl/C3tyeZzo9Y+xwRAX09+pf7cmNVtGyJEK3Qebk1pONsmhgQyDJTV2g1cLaJyD1HNi66faLsnEy+GVuTP+2HXwvGmdng9cvqia7oJgVx66y9EAMSVkFgG4LgYe6NWVaL19c7Srfi2droSG4nRvB7dzQahVOxV1n9/kU/jiXwtnELEKvXif06nUWbI/Ezc6CgQG6Qck9/R2x0JiQX1TKhnDdrKfzSdn6ens3c2RqTx8GBDjXqlla1SU9P52FYbrNMJ/p9Ax25jWzV5UwjP5e/fn4xMecSDpBdlE2tmaG713cG7uXS9cvYaOxYWKAbEZcXSS5qQv2fggXd/y1rcIqcPA2+CVKMzPJ3LQJkOnftU1yVgHLDsaw/MgV/aJ2zrbmPNrbl0ndmtLIwINw1WoVnZo60KmpAy8EtSQxM58951PZfT6ZA5fSSMwsYPnRqyw/ehULjZquPo2JiM/kep7u0ZOlxoSxnT2Y2tPnrnuR6ov/hf6P7OJsWjVuxbjm44wdjqgg70be+Nr5Ep0ZzcH4gwz1HWrQ+hVF4duIbwGY2HIijcwM2/su/ibJTW13YTvs1W2yx4hPdWNtqkApKqI4KYni+HiK4+Mp+uvfwsgLKPn5mDdvjmWXLgYIXFTVpZQcvt0XxbqweIpKdTOf/J2sebKvP6M7uWNuWjNTR93sLJnUrSmTujWloLiUw5fT+eN8MrvPpZCQWcD+i2mAbg+nKT18mNDFCzsrwyRcCTkJrLm4hjHNxuBl62WQOqvLn6l/su7SOgBe6/aaTO2to/p79Sc6M5o9sXsMntwcSzpGRFoE5ibmPNz6YYPWLcqS5KY2uxYFa//aa6Tr43e1+rBSXExxcjLFcfF/JTBx/0hiEihJTtY95rqFxtOmySqZRnYi5hqL90Wx82yy/lhXHwee7OvPwADjziyy0JgwIMCZAQHOKKMVIpOzOXQpHa/GVgw08KOnpNwkpm2bRkJuAjtidrBqxCqsNFYGq9+QtIpWP4h4lP8oOjp3NG5AotIGeA1g2ell7I/fT7G22KBT+G/02oxtPhZHS0eD1StuJslNbVWUB6smQ0EmeN4DQ+YBoJSUUJKcTJE+eYn/Ry9MHCVJt09eAFTm5mg8PP76cMfM0xONhwdmvr6Yt2xZE60T/6LVKuw6l8zifVGcvJIB6JYuGtzKhSf7+RHo3djIEd5MpVIR4NqIAFfDd62n5acxfcd0EnITAIjJiuGDox/wfu/3DX4tQ1h3cR1n0s9go7FhVuAsY4cjqqC9Y3sczB3IKMwgPCWcrq5dDVJvRGoERxOPYqoyZWqbqQapU9yaJDe1kaLA789B8mmwdkIZv4zM37eQ/t13FMXEQGnpbU9XmZn9I3m5OYkxadJEemdqiVKtwsZT8Xyx+xJRqbkAmJmoGdvZg8f7+NHMue6v1FtRmYWZPLnzSWKyYnCzduOZTs/wxsE32HB5A93du9e6Bc8yCzP5X+j/AJjZYaa8I6/jTNQm9PXsy4bLG9gTu8dgyc13Ed8BMMxvGO427gapU9yaJDe10bFvIOJXUJmQ1+YNkqfPpiAiQv+ySqNB4+6uS1r+SlhuJDAaDw9MHR1RqWX/mtpMURT+OJfCgu2RRCbrZhfZWpgyubs3U3v64NzIsOsX1RW5xbnM3DWTCxkXaGLRhG+DvsW7kTex2bEsOrWI9w6/R3vH9jRt1NTYoeotDF9IRmEG/nb+PNjqQWOHIwxggNcANlzeQEhsCC91eanKbwYvZVxid+xuVKh4rO1jhglS3JYkN7XNlcOw/TWKc9WkpPQma8WHAKitrXGcOYNGI0di6uQkyUsddiz6Gh9uO69//NTIwpQn+/kzpacPNuYN90eyoKSAZ3Y/Q0RaBHbmdvrEBuCJ9k9wLOkYJ5NP8tK+l/g5+Odasapr5LVIVkWuAuDVbq/KFgv1RA/3HmjUGmKzY4nKjMLf3r9K9d1Yjfhe73vxs/czRIjiDhrub9LaKDsJ7YoppJ+yJP2CHUrxRVCpsBs3FufnnsPUyfBr24iacyYhk4+3R7InMhUAC42aab18mdHX32Czi+qq4tJiZoXM4njScaw11iy+dzHNHf7etNVUbcr8PvMZ//t4zqaf5bPQz3ip60tGjFjX+/bB0Q/QKlqCvIPo5tbNqPEIw7HSWNHNrRsH4g+wJ3ZPlZKbuOw4tkRvAeCxdtJrU1Pk7X8toRQXkjl3PJdXQdoZW5RiLZZdAvH5bTXu778viU0dFpOWy7Mrwhj++QH2RKZiolbxULem7H1pAK8MDWjwiU2JtoRX9r/CgfgDWJhYsHDQQto4trmpnKu1K+/1fA+AH8/+yL64fTUdahlborcQmhKKpaklL3Z50aixCMMb4DUAgJDYkCrV8/2Z7ylVSunp3pM2TW7+vhbVQ3puaoH8iAiSX3qS/JgMwASNqzPOc17FdsgQGfhbh6VkFfD57ousPBZLyV/7EIzs4M7swS2qfQfuukKraHn70NvsvLITjVrD/wb8j0CXwFuWH9B0AJMCJvHL+V9448Ab/DbqN5ytan417dziXP7vxP8BML3ddNxs3Go8BlG9+nr2BXTrF6Xnp9PEskmF60jLT2PdRd3aR4+3e9yg8Ynbk+TGiIqTU0j95BMyN2wAQGWqxXHicBq/9AFqi4Y5oLQ+yMwr5ut9l1l2MJqCYt20/P4tnXgxqCVtPWQ5/hsURWHe0XlsvLwRE5UJC/otoKdHzzueN7vLbE4mnyQyI5LX9r/G4sGLa3zBvMV/LiY1PxUvWy+mtJlSo9cWNcPV2pXWTVpzNv0s++L2cV/z+ypcx49nf6RIW0RHp450cZHFUWuSPJYyAm1BAWlff83l4GB9YmPnk4f/O2NxfPMTSWzqqPyiUhaFXKbPR7tZFHKZgmItnZvas/KJ7nw/7R5JbP5BURQ+C/2MlZErUaHi/d7vM6jpoLs619zEnAX9FmBpasnRpKMsOb2kmqMtKyozip/O/gTAnHvmYGZiVqPXFzWnv1d/oHKPpjILM1l1XjfY/PF2j0svfA2T5KYGKYpC1rZtRA0bTupn/0PJy8PSRYXP4FTcHwpEc1/tXKBM3F5xqZblR6/Qb8EePtx2nqyCElq42PDtI11YM7Mn3f0q3p1d330b8a1+BsmbPd6s8No1vna+vNbtNQC+Cv+KsJQwg8dYHkVR+PDYh5RoS+jr2Vf/6ELUT/09+wNwOPEwBSUFFTp3xfkV5JXk0cKhhXyfGIE8lqohBWfPkvTBB+SfOAmAqasrzt1NaWR+DJVDUxj3HcheNHWKVquwKSKRT3ZEEpOeB+j2V5o9uAWjO3o0iF2wK+Pnsz/zRdgXALzY5UXub3F/peoZ7T+aI4lH2By1mVf2vcLqkaurfRfu3bG7OZRwCI1awytdX6nWawnjC2gcgIuVC8l5yRxLOnbXSUpecR7Lzy0HpNfGWIzec/PVV1/h6+uLhYUFgYGB7N+//5ZlExMTmTRpEi1btkStVvP888/XXKCVVJKWRsIbbxA9bjz5J06isrDA8emn8X9tEHYWx1BpLGDCT2BV+5bXF+VTFIWQyBRGfHGAZ1eEEZOeRxNrM+aObM0fL/RjbGdPoyQ2xaXFxGbFcjTxKOsurmNh+EJeP/A607ZNY3bIbE6nna7xmP5t3cV1fHhct3bTzA4zqzReRaVS8Wb3N/Gy9SIxN5G5h+aiKIqhQr1JQUkBHx37CICpbabWqoUERfVQqVT6R1N7Yvfc9XlrLq7heuF1mto2Jcg7qJqiE7dj1J6bVatW8fzzz/PVV1/Rq1cvFi9eTHBwMGfPnqVp05t/cRQWFuLk5MTrr7/Op59+aoSI7562qIiMH38kbdHXaHN1y+o3GjEC5xdmo8mOgF8m6AoO/wTcOxovUFEhJ69k8NG28xyNvgaAjbkpT/T149HevtW+AF9+ST6JuYkk5CSQkJNAYm4i8TnxJOYkkpCbQGpeKgq3/uO+88pO+nv15+mOT9Oycc3vIbYtehtvH3obgCmtpzCzw8wq12mtsWZB3wU8vPVhdl3dxeoLq5nQckKV6y3P0tNLSchNwNXaVWa+NCADvAawKnIVe2P3ou2uRa26fZ9AUWkR35/5HoBpbafJ7vBGolKq863OHXTr1o3OnTuzaNEi/bFWrVoxZswY5s2bd9tz+/fvT8eOHfnss88qdM2srCzs7OzIzMykUSPDb/inKAo5f/xB8kcLKL56FQCLdu1wee1VrDp10u30/U1/3YaYXR6FEbU7SRM6kUnZLNgeya5zup26zUzVTOnhzcz+zWhsbZgBpTlFObpk5R8JTEJugj55uVZw7Y51mJuY42bthruNu+7D2h1Xa1eOJB5hU9QmtIpu9tZg78E81fGpKq+8erdCYkOYtWcWJUoJ97e4nze7v2nQrvofzvzAxyc+xkxtxooRK2jh0MJgdYNuIbYxG8ZQWFrIx/0+ZojPEIPWL2qvotIi+qzsQ15JHiuHryx3DaZ/WnNhDXMPz8XZ0pmt47bKgHMDqsjfb6P13BQVFXHy5EnmzJlT5nhQUBCHDh0yUlRVUxB5geR588g7cgQAUycnnF6Yjd2oUbrtEoryYNUjusTGowsMnW/kiMXtlJRq+eN8Cr8cvcq+i6koCqhVcH+gF8/d2xx3e8sq1V9cWsz++P1sitrE0cSjZBVl3fEca421Pmlxs3bDw8YDNxs33K11yUxji8blJg0j/UfyeLvHWRS+iG0x29h5ZSe7ruximN8wZnaYqd/moDocSTzCCyEvUKKUMNxvOG90f8PgYxAmt57M0cSj7I/fz0t7X2LF8BVYaawMVv+C4wsoLC3kHtd75DFDA2NmYkYvj17svLKTPbF7bpvclGpL9QPlp7SZIomNERktuUlLS6O0tBQXF5cyx11cXEhKSjLYdQoLCyksLNR/nZV15z8glZF77BhXp04DrRaVmRmNH52G4/TpqK3/WqxNUWDT85AcAdZOMOFHMDWvllhE1SRcz2fl8Vh+PR5LUtbfMySGtnHlxSEtq7RTt6IohKeGs+nyJrZf2U5mYWaZ1+3N7ctNWtxtdMlMI7NGlU4MfO18+ajfR0xvP52vwr9i19VdbI7azLbobYzyH8WTHZ7Ew8aj0m0rT3hKOM/ufpYibREDvQbyfq/379itXxlqlZr3e7/P+I3jicqM4qPjHzG351yD1H0w/iC7Y3djojLh1XtelcGhDdAArwHsvLKTkNgQnu709C3L7byyk6vZV7E3t2d8i/E1F6C4idFnS/37F4WiKAb95TFv3jzeeecdg9V3K1adO2Pu74eZfzOcX3wRM89//ZE49i38uQpUJjB+GdgZ9o+IqJpSrcLeC7pemt3nU/hrQWEaW5txf6AnD97TFJ8qrCocnRnN5qjNbIraRHxOvP64s6Uzw/yGMcRnCH52fgbtbbiV5g7N+XTAp5xNP8vC8IXsi9vHukvr+D3qd8Y2G8v09tNxtXat8nXOpZ/jP7v+Q35JPj3de7Kg3wJM1dX3K6exRWPm9ZnH9B3TWXNxDd3dujPUd2iV6iwuLWb+MV0P66RWk2jm0MwQoYo6po9HH9QqNZEZkSTkJOBu435TGUVR+DbiW0D3vVITP8vi1oyW3Dg6OmJiYnJTL01KSspNvTlV8eqrrzJ79mz911lZWXh5eRms/htUpqZ4r1iJiU05fwCvHoHtr+o+H/wO+PYx+PVF5SRnFfDr8VhWHo8l/nq+/nh3v8ZM6ubNkDYumJtWbkBgen4622K2senyJk6n/z1TycrUinu972WE3wjucb3HaAMOWzdpzcJBCzmVeoovw77kSOIRfr3wK+svrWdCywk81u4xHC0dK1V31PUontz5JNnF2XR27sxnAz6rkS76bm7deLzd43wb8S3vHH6Hto5t8bT1rHR9P537iZisGJpYNDHIAGhRN9lb2NPRqSOhKaGExIYwqdWkm8rsj9/PhYwLWJlaMSng5tdFzTJacmNmZkZgYCA7d+7kvvv+XtZ6586djB492mDXMTc3x9y8Zh7/lJvYZCfBr1NAWwJt7oMet+7SFDVDq1U4cCmN5UevsOtcCqV/ddPYWWoY/1cvTWUfPeWX5LPn6h42RW3iUMIhSpVSAExUJvR078lI/5H09+qPpWnVxusYUgenDnwb9C0nkk7wRdgXhKaE8vO5n/ntwm88GPAg09pOw8HC4a7ri82OZfqO6WQUZtC6SWu+HPRljbb3Px3/w4nkE4SlhPHKvlf4Pvh7NOqKb06anJvM4lOLAZgVOAtbM1tDhyrqkAFeA26Z3CiKwrd/6nptJracWO3rLYk7M+pjqdmzZzN58mS6dOlCjx49+Oabb7h69SozZswAdL0u8fHx/Pjjj/pzwsPDAcjJySE1NZXw8HDMzMxo3bq1MZpwe6XFsHoq5CSBUwCM+hLkeb3RpGYXsvpkLCuPxXL1Wp7+eBdvByZ1a8qwdm5YaCrei1KqLeVY0jE2RW1i15Vd5JX8XXc7x3YM9xvOUJ+hldp4ryZ1ce3C90O/53DiYRaGLeTPtD9ZdmYZqyJX8XDrh5nSZgqNzG4/QyEpN4npO6aTkp9CM/tmLL53cY0nBaZqU+b3mc/438fzZ9qffBn2JbMCZ1W4nk9OfkJeSR4dnDow0n9kNUQq6pL+Xv35v5P/x/Hk4+QU5WBj9vcboJPJJwlPDcdMbcbk1pONGKW4wajJzcSJE0lPT+fdd98lMTGRtm3bsmXLFry9dTM3EhMTufrXdOobOnXqpP/85MmT/PLLL3h7exMTE1OTod+dHW/A1cNg3ggm/gzmlR+IKipHURQOR6Wz/OhVdpxJorhU10tja2HKuM66XpqWrhX/46soCpEZkWy6vIkt0VtIzU/Vv+Zh48EIvxEM9xuOr52vwdpSE1QqFT3de9LDrQf74/fzZdiXnLt2jm/+/IYV51Ywpc0UHm79MNaam3sp0/PTmb5jOvE58TS1bco3g7/B3sK+5hsBuNu4827Pd5kVMoulp5fSzbXbXW3KecOJpBNsid6CChWvdXutWgZBi7rFx84Hn0Y+xGTFcDDhYJnlAL6L+A6AMc3G4GTlZKwQxT8YdZ0bY6judW70/lwNa/9a6OuBXyBgePVdS9zkWm4Ra07GseLYVaLScvXHO3rZM6lbU0a2d8fSrOK9NEm5SfqBwZeuX9IftzO3Y6jPUEb4jaCDU4d6M6NGURT+uPoHC8MX6ttrb27PtLbTeKDlA/pBk5mFmTy2/TEiMyJxtXblh6E/lDvosqa9f+R9VkWuorFFY9aMWnNXY4hKtCVM3DSRCxkXuL/F/bzV460aiFTUBZ+c+IRlZ5Yxwm8E8/ro1mI7k36GBzY9gInKhN/v+x0vW8OP6RQ6dWKdm3ot6TRsfEb3eZ8XJLGpIYqicDwmg1+OXmFLRBJFpboF62zMTRnd0Z1J3ZrSxr3iz8KzirLYdWUXm6I2cSLphH4VYDO1Gf28+jHCbwR9PPqgMan4uI7aTqVSca/3vQzwGsD2mO0sOrWImKwYPj35KT+e+ZHH2z3OcL/hPL37aSIzImli0YTvgr6rFYkN6PauCk0J5WLGRV7b/xpfD/76jr0wv0b+yoWMCzQya8SznZ6toUhFXdDPqx/LzixjX9w+SrQlmKpNWRKh25U+2DdYEptaRHpuDC3/um4F4oxo8B8ID/0mG2JWs+JSLSuPXeXHw1e4mJKjP97WoxEPdfNmVAd3rCu4NUJecR574/ayJXoLB+MPUqwt1r/WxaULI/xGMNhn8B3HoNQ3JdoSNkdtZtGpRfop7aYqU0qUEuzM7Vg6ZKnBVweuqqjrUUzcNJGC0gJmBc7i0baP3rLstYJrjFg3guyibN7o9gYTAybWYKSitivRljDg1wFcL7zO0iFLaWLZhDHrx6CgsG7UOlkqoJpJz42xaLWw7kldYmPXFMYtkcSmmh2JSuetDae5kKxLaiw1Jvpemvae9hWqq6i0iIPxB9kavZWQuBDyS/6eGt7MvhnD/YYz3Hc4bjZuhmxCnWKqNmV0s9EM8xvG+kvrWXxqMcl5yVhrrPn63q9rXWID4Gfvx5x75jD38Fy+CP2CLi5daO/Uvtyyn4d+TnZRNgGNA2QRNnETU7UpfT37svHyRkJiQ8gszERBYYDXAElsahlJbgxp3wK4sA1MzGGi7PRdnVKyC5i35TzrwnS9B42tzXh2YDPGBnrSyOLuHw/dmOm0NXoru67uIrsoW/+ap40nwb7BBPsG09yhucHbUJdp1Brub3E/o/xHsfvqblo4tKixfaoqY2zzsRxJPMK2mG28vO9lVo9cfdMsrtNpp1l7cS0Ar3V7TTY8FOXq79WfjZc3sjV6KxkFGQCykWotJMmNocQcgJC/NvscITt9V5eSUi0/HbnCJzsukF1YgkoFk+5pyktDWmJvdXeLxCmKwqnUU2yJ3sKOmB2kF6TrX3OydGKIzxCG+Q6jrWPbejMwuLqYm5gT7Bts7DDuSKVS8VaPt4hIiyA+J553Dr/Dgr4L9PdXq2j54OgHKCiM9BtJJ+dOd6hRNFQ93XuiUWv0MyS7uXW7ZU+gMB5JbgzFowt0nqzbXqHTw8aOpl46eeUab6w/w7lE3f5g7T3teG90Wzp42d/x3BtTt7dEb2F79HYSchP0r9mZ2zHYezDDfIfR2bmzvGOvp2zNbPmo70dM2TqF7THb6eHWg3EtxgGw4dIGItIisNZYV2pNHNFwWGusucftHg7GHwRgervpRo5IlEeSG0PRWMCoL0BbauxI6p30nELmbz3P6pNxgG4l4ZeHtuSBrk0xUd++ZyUmM4at0VvZGrOV6Mxo/XErUysGNh1IsG8wPdx7VGoFW1H3tHdqzzOdn+HTk58y/9h8Ojp3xMnKic9CPwNgZoeZsk6JuKN7m97LwfiDtHdszz2u9xg7HFEOSW4MTd71G0ypVmHFsass2B5JZr5uttKELp68MjSAJja33lIjKTdJl9BEb+XctXP642ZqM/p69iXYN5i+nn2xMLWo9jaI2mdqm6kcTTzKoYRDvLj3RTo6d+RawTX87PzK3TNIiH+7r9l9mKpN6eneUx5d11IyFVzUSqdir/PmhtP8GZcJQGu3Rrw3pi2B3uXvcZSen87OKzvZGr2V0JRQ/XETlQnd3bszzHcYA70GllkyXTRcaflpjN84vsx4q28Gf0MP9x5GjEoIcTsyFVzUWdfzivhoeyQrjl1FUcDW3JQXglrwcHdvTE3KLr6WVZTF7qu72Rq9laOJR/WbVKpQ0dmlM8N8hzHYe3CFNn0UDYOjpSMf9PmAJ3c+CcBg78GS2AhRj0hyI2oFrVZh9clY5m89T0ae7hHU2E4ezBkWgLPt34+P8kvy2Ru3l61RW9kfv7/M4nptmrQh2DeYIT5DcLV2rfE2iLqlp3tPXu76Mn9c/YOXu75s7HCEEAYkj6WE0Z2Oz+StDacJvXodgBYuNrw3ui3d/HS7aBeXFnMo4RBborewJ3ZPmcX1/O38CfYNZqjvULwbeRsjfCGEEDVAHkuJOiEzv5hPdkTy05EraBWwNjNh1uAWTOnpg1qlcDTxKFujt7Lzyk6yirL053nYeOgSGp+htHBoIQP6hBBClCHJjahxiqKwLiyeD7acJy2nEIAR7d14fVgrUosv8snJBWyP2a5fJAt0YySG+gxlqO9Q2ju2l4RGCCHELUlyI2pUZFI2b64/zbGYawD4OVkz414rEkv3M+2P1/SbMQI0MmvEYO/BBPsG08WliyyuJ4QQ4q5IciNqRHZBMf/bdZFlh2Io1SpYWmbQs0Ms6RzlvfDL+nKWppYM8BrAMN9humXOTWRxPSGEEBUjyY2oNsWlWvZfTGVDeAI7ziRToFzD1P5PnF3OkkM0x3RL2KBRa+jj0Ydgv2D6efbD0tTSuIELIYSo0yS5EQal1Socj7nGhlMJbIlI5HpeMSqTHMxdN2BjexpUCjnoFtfr5taNYN9gBjUddNMOzUIIIURlSXIjqkxRFM4kZPH7qQQ2nkogMbNA/5qDYxQmzqsoVHTdNJ2dOxPsG8xg78E0sWxirJCFEELUY5LciEqLSctl46kENoTHczk1V3/c1sKUoDYOFDb6nb1J6ylRoJl9M+b1mUdA4wAjRiyEEKIhkORGVEhKVgG//5nIxvB4Tv217xOAmamae1s5M6qDB65Oabx1+DWik3S7cD/c6mGeD3wec5Nbb3YphBBCGIokN+KOMvOK2XYmkQ3hCRyOSufGmtYmahW9mjkyuoM7QW1csDJTs+zMMl7dvpASpQRnS2fe6/0ePd17GrcBQgghGhRJbkS5CopL+eNcChvC4wmJTKWoVKt/LdDbgVEd3BnWzg0nW11vTHxOPE/veU2/I/dg78G81f0t7C3sjRG+EEKIBkySG6FXXKrl4KU0NoYnsP1MErlFpfrXWrrYMqqjO6M6uOPV2Ep/XFEUNkVt4r9H/0tucS7WGmtevedVRvmPklWEhRBCGIUkNw2coiicjs9iTWgcv59KID23SP+ah70lozu6M6qjOwGuN29SllmYyXtH3mN7zHYAOjl34oPeH+Bp61lj8QshhBD/JslNA5WSVcC6sHjWhMZxITlHf7yJtRnD27sxuqM7nZs63LL35UjiEV4/8DopeSmYqkyZ2XEmj7Z9FFO1fEsJIYQwLvlL1IAUFJey42wya07Gsf9iKtq/BgabmaoJau3CuEBP+jRzxNREfcs6ikqL+Dz0c344+wMAPo18mNdnHm0d29ZEE4QQQog7kuSmnlMUhZNXMlgTGsemPxPJLijRvxbo7cC4zp4Mb++GneWd93C6kHGBOfvncDHjIgATWkzghS4vYKWxusOZQgghRM2R5KaeisvIY21oPGtD44hJz9Mf97C3ZGxnD8Z29sTX0fqu6tIqWpafW85nJz+jSFtEY4vGvNvzXfp59auu8IUQQohKk+SmHsktLGFLRCJrQuM4EnVNf9zKzITgtm6MC/Sgu28T1Oq7n8WUnJvMGwff4EjiEQD6efZjbs+5OFo6Gjx+IYQQwhAkuanjtFqFw1HprDkZx9bTSeQX66Zvq1TQw68J4zp7MrStK9bmFb/VO2J28M7hd8gqysLCxIKXur7E/S3ulyneQgghajVJbuqoqNQc1oTGsS40noR/bFTp62jNuM4e3NfZEw97y0rVnVOUw7xj89h4eSMAbZq0YV6fefja+RokdiGEEKI6SXJTh2TmFfP7nwmsCY0j7Op1/XFbC1NGdnBnXGdPOje1r1LPSmhyKK8deI34nHjUKjWPt3ucGR1moFHfecCxEEIIURtIclPLlWoV9l9M5beTcew4m0xRiW4bBLUK+rVwYlygJ/e2csFCY1LpaxSVFpGSl8Lai2tZcnoJWkWLh40H8/rMo5NzJ0M1RQghhKgRktzUUpdSsvntZDzrwuJIzirUH2/pYsv4QE9Gd3LH2dbijvXkFeeRnJdMSl4KyXnJJOcml/03L5lrBdfKnDPafzRz7pmDjZmNwdslhBBCVDdJbmqRG4+dfjsZR3jsdf1xeysNYzp6MD7QkzbujVCpVCiKQmZh5s1JS17Z5CW7KPuurm1uYo6XrRczO8wkyCeomloohBBCVD9JbozsVo+dTNQq+rW0p29rcG6STXzOIVZEx5B8+u8EJr8k/66uYa2xxsXKRfdh/a9///qwM7eTWVBCCCHqBUlujORSSg6/nYxjbVgsqXlpqM1SUduk4uqQiaNDFkXqJE7mJXL8rPa29dib2+uTFWcr5zJJjKuVK85WzvJ4SQghRIMiyU0NyS/J50xqFOtPh7E/5izJ+bG6hMY1DRuTv8fU5AK5/+iQsdHY4NPIB187X7wbeeNu446rtSsuVrpkxsL0zuNuhBBCiIZEkhsDUhSF5LxkojOjicmKISYzhqjMaCLTL5NRlPJ3QTPQmP39pVqlxsPGQ5/E+Nj56D9vYtFEHhcJIYQQFSDJjYFEZUbxwKYHbjsORim1xExxpZm9L728W9PWqRk+dj542XphZmJ2y/OEEEIIcfckuTEQVytX8kvyUaHGVOtEfm5jtEVOaAudsFK7EtyiPZO6tKadpwzcFUIIIaqTJDcGEplYSFHMyxTm2wEmmKhV9G/hxPhATwa2csbctPKL7AkhhBDi7klyYyCt3RthqXLB28Wc+wO97nqRPSGEEEIYliQ3BmJuasK25/ri0shcHjsJIYQQRiTJjQG52klPjRBCCGFsamMHIIQQQghhSJLcCCGEEKJekeRGCCGEEPWKJDdCCCGEqFeMntx89dVX+Pr6YmFhQWBgIPv3779t+b179xIYGIiFhQV+fn58/fXXNRSpEEIIIeoCoyY3q1at4vnnn+f1118nLCyMPn36EBwczNWrV8stHx0dzbBhw+jTpw9hYWG89tprPPvss6xZs6aGIxdCCCFEbaVSFEUx1sW7detG586dWbRokf5Yq1atGDNmDPPmzbup/CuvvMLGjRs5d+6c/tiMGTM4deoUhw8fvqtrZmVlYWdnR2ZmJo0aNap6I4QQQghR7Sry99toPTdFRUWcPHmSoKCgMseDgoI4dOhQueccPnz4pvJDhgzhxIkTFBcXl3tOYWEhWVlZZT6EEEIIUX8ZLblJS0ujtLQUFxeXMsddXFxISkoq95ykpKRyy5eUlJCWllbuOfPmzcPOzk7/4eXlZZgGCCGEEKJWMvqA4n9vVaAoym23LyivfHnHb3j11VfJzMzUf8TGxlYxYiGEEELUZkbbfsHR0RETE5ObemlSUlJu6p25wdXVtdzypqamNGnSpNxzzM3NMTc3N0zQQgghhKj1jNZzY2ZmRmBgIDt37ixzfOfOnfTs2bPcc3r06HFT+R07dtClSxc0Gk21xSqEEEKIusOoj6Vmz57Nd999x9KlSzl37hyzZs3i6tWrzJgxA9A9UnrkkUf05WfMmMGVK1eYPXs2586dY+nSpSxZsoQXX3zRWE0QQgghRC1j1F3BJ06cSHp6Ou+++y6JiYm0bduWLVu24O3tDUBiYmKZNW98fX3ZsmULs2bNYuHChbi7u/P5558zbty4u77mjTE6MmtKCCGEqDtu/N2+mxVsjLrOjTHExcXJjCkhhBCijoqNjcXT0/O2ZRpccqPVaklISMDW1va2s7IqIysrCy8vL2JjY+v9AoENqa3QsNorba2/GlJ7pa31j6IoZGdn4+7ujlp9+1E1Rn0sZQxqtfqOGV9VNWrUqF5/g/1TQ2orNKz2Slvrr4bUXmlr/WJnZ3dX5Yy+zo0QQgghhCFJciOEEEKIekWSGwMyNzfn7bffbhCLBjaktkLDaq+0tf5qSO2VtjZsDW5AsRBCCCHqN+m5EUIIIUS9IsmNEEIIIeoVSW6EEEIIUa9IciOEEEKIekWSmwr66quv8PX1xcLCgsDAQPbv33/b8nv37iUwMBALCwv8/Pz4+uuvayjSyps3bx5du3bF1tYWZ2dnxowZQ2Rk5G3PCQkJQaVS3fRx/vz5Goq68ubOnXtT3K6urrc9py7eVwAfH59y79NTTz1Vbvm6dF/37dvHyJEjcXd3R6VSsX79+jKvK4rC3LlzcXd3x9LSkv79+3PmzJk71rtmzRpat26Nubk5rVu3Zt26ddXUgoq5XXuLi4t55ZVXaNeuHdbW1ri7u/PII4+QkJBw2zq///77cu93QUFBNbfm9u50b6dOnXpTzN27d79jvbXx3t6preXdH5VKxYIFC25ZZ229r9VJkpsKWLVqFc8//zyvv/46YWFh9OnTh+Dg4DKbe/5TdHQ0w4YNo0+fPoSFhfHaa6/x7LPPsmbNmhqOvGL27t3LU089xZEjR9i5cyclJSUEBQWRm5t7x3MjIyNJTEzUfzRv3rwGIq66Nm3alIk7IiLilmXr6n0FOH78eJl27ty5E4D777//tufVhfuam5tLhw4d+PLLL8t9/aOPPuKTTz7hyy+/5Pjx47i6ujJ48GCys7NvWefhw4eZOHEikydP5tSpU0yePJkJEyZw9OjR6mrGXbtde/Py8ggNDeXNN98kNDSUtWvXcuHCBUaNGnXHehs1alTmXicmJmJhYVEdTbhrd7q3AEOHDi0T85YtW25bZ229t3dq67/vzdKlS1GpVHfcQLo23tdqpYi7ds899ygzZswocywgIECZM2dOueVffvllJSAgoMyxJ598UunevXu1xVgdUlJSFEDZu3fvLcvs2bNHAZSMjIyaC8xA3n77baVDhw53Xb6+3FdFUZTnnntO8ff3V7Rabbmv19X7Cijr1q3Tf63VahVXV1dl/vz5+mMFBQWKnZ2d8vXXX9+yngkTJihDhw4tc2zIkCHKAw88YPCYq+Lf7S3PsWPHFEC5cuXKLcssW7ZMsbOzM2xwBlZeW6dMmaKMHj26QvXUhXt7N/d19OjRysCBA29bpi7cV0OTnpu7VFRUxMmTJwkKCipzPCgoiEOHDpV7zuHDh28qP2TIEE6cOEFxcXG1xWpomZmZADRu3PiOZTt16oSbmxuDBg1iz5491R2awVy8eBF3d3d8fX154IEHiIqKumXZ+nJfi4qK+Pnnn3n00UfvuIlsXb2vN0RHR5OUlFTmvpmbm9OvX79b/vzCre/17c6prTIzM1GpVNjb29+2XE5ODt7e3nh6ejJixAjCwsJqJsAqCgkJwdnZmRYtWjB9+nRSUlJuW74+3Nvk5GQ2b97MY489dseydfW+VpYkN3cpLS2N0tJSXFxcyhx3cXEhKSmp3HOSkpLKLV9SUkJaWlq1xWpIiqIwe/ZsevfuTdu2bW9Zzs3NjW+++YY1a9awdu1aWrZsyaBBg9i3b18NRls53bp148cff2T79u18++23JCUl0bNnT9LT08stXx/uK8D69eu5fv06U6dOvWWZunxf/+nGz2hFfn5vnFfRc2qjgoIC5syZw6RJk267sWJAQADff/89GzduZMWKFVhYWNCrVy8uXrxYg9FWXHBwMMuXL2f37t383//9H8ePH2fgwIEUFhbe8pz6cG9/+OEHbG1tGTt27G3L1dX7WhUNblfwqvr3O1xFUW77rre88uUdr62efvpp/vzzTw4cOHDbci1btqRly5b6r3v06EFsbCwff/wxffv2re4wqyQ4OFj/ebt27ejRowf+/v788MMPzJ49u9xz6vp9BViyZAnBwcG4u7vfskxdvq/lqejPb2XPqU2Ki4t54IEH0Gq1fPXVV7ct27179zIDcXv16kXnzp354osv+Pzzz6s71EqbOHGi/vO2bdvSpUsXvL292bx5823/8Nf1e7t06VIeeuihO46dqav3tSqk5+YuOTo6YmJiclNWn5KSclP2f4Orq2u55U1NTWnSpEm1xWoozzzzDBs3bmTPnj14enpW+Pzu3bvXyXcG1tbWtGvX7pax1/X7CnDlyhV27drF448/XuFz6+J9vTH7rSI/vzfOq+g5tUlxcTETJkwgOjqanTt33rbXpjxqtZquXbvWufvt5uaGt7f3beOu6/d2//79REZGVupnuK7e14qQ5OYumZmZERgYqJ9dcsPOnTvp2bNnuef06NHjpvI7duygS5cuaDSaaou1qhRF4emnn2bt2rXs3r0bX1/fStUTFhaGm5ubgaOrfoWFhZw7d+6WsdfV+/pPy5Ytw9nZmeHDh1f43Lp4X319fXF1dS1z34qKiti7d+8tf37h1vf6dufUFjcSm4sXL7Jr165KJd6KohAeHl7n7nd6ejqxsbG3jbsu31vQ9bwGBgbSoUOHCp9bV+9rhRhrJHNdtHLlSkWj0ShLlixRzp49qzz//POKtbW1EhMToyiKosyZM0eZPHmyvnxUVJRiZWWlzJo1Szl79qyyZMkSRaPRKL/99puxmnBXZs6cqdjZ2SkhISFKYmKi/iMvL09f5t9t/fTTT5V169YpFy5cUE6fPq3MmTNHAZQ1a9YYowkV8sILLyghISFKVFSUcuTIEWXEiBGKra1tvbuvN5SWlipNmzZVXnnllZteq8v3NTs7WwkLC1PCwsIUQPnkk0+UsLAw/eyg+fPnK3Z2dsratWuViIgI5cEHH1Tc3NyUrKwsfR2TJ08uM/vx4MGDiomJiTJ//nzl3Llzyvz58xVTU1PlyJEjNd6+f7tde4uLi5VRo0Ypnp6eSnh4eJmf48LCQn0d/27v3LlzlW3btimXL19WwsLClGnTpimmpqbK0aNHjdFEvdu1NTs7W3nhhReUQ4cOKdHR0cqePXuUHj16KB4eHnXy3t7p+1hRFCUzM1OxsrJSFi1aVG4ddeW+VidJbipo4cKFire3t2JmZqZ07ty5zPToKVOmKP369StTPiQkROnUqZNiZmam+Pj43PKbsTYByv1YtmyZvsy/2/rhhx8q/v7+ioWFheLg4KD07t1b2bx5c80HXwkTJ05U3NzcFI1Go7i7uytjx45Vzpw5o3+9vtzXG7Zv364ASmRk5E2v1eX7emPa+r8/pkyZoiiKbjr422+/rbi6uirm5uZK3759lYiIiDJ19OvXT1/+htWrVystW7ZUNBqNEhAQUGsSu9u1Nzo6+pY/x3v27NHX8e/2Pv/880rTpk0VMzMzxcnJSQkKClIOHTpU8437l9u1NS8vTwkKClKcnJwUjUajNG3aVJkyZYpy9erVMnXUlXt7p+9jRVGUxYsXK5aWlsr169fLraOu3NfqpFKUv0ZCCiGEEELUAzLmRgghhBD1iiQ3QgghhKhXJLkRQgghRL0iyY0QQggh6hVJboQQQghRr0hyI4QQQoh6RZIbIYQQQtQrktwIIRoklUrF+vXrjR2GEKIaSHIjhKhxU6dORaVS3fQxdOhQY4cmhKgHTI0dgBCiYRo6dCjLli0rc8zc3NxI0Qgh6hPpuRFCGIW5uTmurq5lPhwcHADdI6NFixYRHByMpaUlvr6+rF69usz5ERERDBw4EEtLS5o0acITTzxBTk5OmTJLly6lTZs2mJub4+bmxtNPP13m9bS0NO677z6srKxo3rw5Gzdu1L+WkZHBQw89hJOTE5aWljRv3vymZEwIUTtJciOEqJXefPNNxo0bx6lTp3j44Yd58MEHOXfuHAB5eXkMHToUBwcHjh8/zurVq9m1a1eZ5GXRokU89dRTPPHEE0RERLBx40aaNWtW5hrvvPMOEyZM4M8//2TYsGE89NBDXLt2TX/9s2fPsnXrVs6dO8eiRYtwdHSsuf8AIUTlGXvnTiFEwzNlyhTFxMREsba2LvPx7rvvKoqi25l+xowZZc7p1q2bMnPmTEVRFOWbb75RHBwclJycHP3rmzdvVtRqtZKUlKQoiqK4u7srr7/++i1jAJQ33nhD/3VOTo6iUqmUrVu3KoqiKCNHjlSmTZtmmAYLIWqUjLkRQhjFgAEDWLRoUZljjRs31n/eo0ePMq/16NGD8PBwAM6dO0eHDh2wtrbWv96rVy+0Wi2RkZGoVCoSEhIYNGjQbWNo3769/nNra2tsbW1JSUkBYObMmYwbN47Q0FCCgoIYM2YMPXv2rFRbhRA1S5IbIYRRWFtb3/SY6E5UKhUAiqLoPy+vjKWl5V3Vp9FobjpXq9UCEBwczJUrV9i8eTO7du1i0KBBPPXUU3z88ccVilkIUfNkzI0QolY6cuTITV8HBAQA0Lp1a8LDw8nNzdW/fvDgQdRqNS1atMDW1hYfHx/++OOPKsXg5OTE1KlT+fnnn/nss8/45ptvqlSfEKJmSM+NEMIoCgsLSUpKKnPM1NRUP2h39erVdOnShd69e7N8+XKOHTvGkiVLAHjooYd4++23mTJlCnPnziU1NZVnnnmGyZMn4+LiAsDcuXOZMWMGzs7OBAcHk52dzcGDB3nmmWfuKr633nqLwMBA2rRpQ2FhIZs2baJVq1YG/B8QQlQXSW6EEEaxbds23Nzcyhxr2bIl58+fB3QzmVauXMl//vMfXF1dWb58Oa1btwbAysqK7du389xzz9G1a1esrKwYN24cn3zyib6uKVOmUFBQwKeffsqLL76Io6Mj48ePv+v4zMzMePXVV4mJicHS0pI+ffqwcuVKA7RcCFHdVIqiKMYOQggh/kmlUrFu3TrGjBlj7FCEEHWQjLkRQgghRL0iyY0QQggh6hUZcyOEqHXkabkQoiqk50YIIYQQ9YokN0IIIYSoVyS5EUIIIUS9IsmNEEIIIeoVSW6EEEIIUa9IciOEEEKIekWSGyGEEELUK5LcCCGEEKJekeRGCCGEEPXK/wMKUj/nh9SljgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# accuracy plot\n",
    "plt.plot(history_2.history['task_1_output_accuracy'])\n",
    "plt.plot(history_2.history['task_2_output_accuracy'])\n",
    "plt.plot(history_2.history['val_task_1_output_accuracy'])\n",
    "plt.plot(history_2.history['val_task_2_output_accuracy'])\n",
    "plt.title('Model Accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()\n",
    "\n",
    "# loss plot\n",
    "plt.plot(history_2.history['loss'])\n",
    "plt.plot(history_2.history['task_1_output_loss'])\n",
    "plt.plot(history_2.history['task_2_output_loss'])\n",
    "plt.plot(history_2.history['val_task_1_output_loss'])\n",
    "plt.plot(history_2.history['val_task_2_output_loss'])\n",
    "plt.title('Model Loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['combined' ,'train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "361cbe9d",
   "metadata": {
    "papermill": {
     "duration": 0.83263,
     "end_time": "2023-04-23T16:59:18.646147",
     "exception": false,
     "start_time": "2023-04-23T16:59:17.813517",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 2.3. Case 3: Gamma = 0.4 - The model will receive loss 40% from task 1, 60% from task 2.\n",
    "##      (Dropout = 0, Optimizer = Adam)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d0b20be4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:59:20.261141Z",
     "iopub.status.busy": "2023-04-23T16:59:20.260275Z",
     "iopub.status.idle": "2023-04-23T16:59:24.925088Z",
     "shell.execute_reply": "2023-04-23T16:59:24.923984Z"
    },
    "papermill": {
     "duration": 5.452494,
     "end_time": "2023-04-23T16:59:24.927826",
     "exception": false,
     "start_time": "2023-04-23T16:59:19.475332",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define parameters and generate model\n",
    "gamma=0.4\n",
    "dropout = 0\n",
    "optimizer = 'Adam'\n",
    "model_3 = create_model(dropout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "437b189c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:59:26.579978Z",
     "iopub.status.busy": "2023-04-23T16:59:26.579585Z",
     "iopub.status.idle": "2023-04-23T16:59:26.611471Z",
     "shell.execute_reply": "2023-04-23T16:59:26.610375Z"
    },
    "papermill": {
     "duration": 0.826415,
     "end_time": "2023-04-23T16:59:26.613995",
     "exception": false,
     "start_time": "2023-04-23T16:59:25.787580",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# compile model\n",
    "model_3.compile(loss={'task_1_output': 'categorical_crossentropy',\n",
    "                    'task_2_output': 'categorical_crossentropy'},\n",
    "              loss_weights={'task_1_output': gamma,\n",
    "                            'task_2_output': 1-gamma},\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54668a47",
   "metadata": {
    "papermill": {
     "duration": 0.799665,
     "end_time": "2023-04-23T16:59:28.300185",
     "exception": false,
     "start_time": "2023-04-23T16:59:27.500520",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Train & Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ee733c51",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T16:59:30.058945Z",
     "iopub.status.busy": "2023-04-23T16:59:30.058361Z",
     "iopub.status.idle": "2023-04-23T17:17:46.670291Z",
     "shell.execute_reply": "2023-04-23T17:17:46.668966Z"
    },
    "papermill": {
     "duration": 1097.424092,
     "end_time": "2023-04-23T17:17:46.672995",
     "exception": false,
     "start_time": "2023-04-23T16:59:29.248903",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "333/333 [==============================] - 158s 160ms/step - loss: 3.5435 - task_1_output_loss: 4.4962 - task_2_output_loss: 2.9085 - task_1_output_accuracy: 0.0193 - task_2_output_accuracy: 0.0899 - val_loss: 3.7520 - val_task_1_output_loss: 4.7669 - val_task_2_output_loss: 3.0754 - val_task_1_output_accuracy: 0.0193 - val_task_2_output_accuracy: 0.0820\n",
      "Epoch 2/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 3.2900 - task_1_output_loss: 4.2124 - task_2_output_loss: 2.6750 - task_1_output_accuracy: 0.0381 - task_2_output_accuracy: 0.1431 - val_loss: 3.3329 - val_task_1_output_loss: 4.2799 - val_task_2_output_loss: 2.7016 - val_task_1_output_accuracy: 0.0407 - val_task_2_output_accuracy: 0.1507\n",
      "Epoch 3/20\n",
      "333/333 [==============================] - 47s 143ms/step - loss: 3.0642 - task_1_output_loss: 3.9593 - task_2_output_loss: 2.4674 - task_1_output_accuracy: 0.0609 - task_2_output_accuracy: 0.2080 - val_loss: 3.2572 - val_task_1_output_loss: 4.1905 - val_task_2_output_loss: 2.6350 - val_task_1_output_accuracy: 0.0539 - val_task_2_output_accuracy: 0.1752\n",
      "Epoch 4/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.9304 - task_1_output_loss: 3.8074 - task_2_output_loss: 2.3457 - task_1_output_accuracy: 0.0828 - task_2_output_accuracy: 0.2571 - val_loss: 2.9290 - val_task_1_output_loss: 3.8105 - val_task_2_output_loss: 2.3413 - val_task_1_output_accuracy: 0.0921 - val_task_2_output_accuracy: 0.2653\n",
      "Epoch 5/20\n",
      "333/333 [==============================] - 47s 143ms/step - loss: 2.7519 - task_1_output_loss: 3.6029 - task_2_output_loss: 2.1845 - task_1_output_accuracy: 0.1118 - task_2_output_accuracy: 0.3035 - val_loss: 2.8314 - val_task_1_output_loss: 3.6756 - val_task_2_output_loss: 2.2686 - val_task_1_output_accuracy: 0.1196 - val_task_2_output_accuracy: 0.2921\n",
      "Epoch 6/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.6184 - task_1_output_loss: 3.4493 - task_2_output_loss: 2.0645 - task_1_output_accuracy: 0.1355 - task_2_output_accuracy: 0.3450 - val_loss: 2.8327 - val_task_1_output_loss: 3.6645 - val_task_2_output_loss: 2.2781 - val_task_1_output_accuracy: 0.1187 - val_task_2_output_accuracy: 0.3108\n",
      "Epoch 7/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.5129 - task_1_output_loss: 3.3337 - task_2_output_loss: 1.9657 - task_1_output_accuracy: 0.1524 - task_2_output_accuracy: 0.3779 - val_loss: 2.7572 - val_task_1_output_loss: 3.6041 - val_task_2_output_loss: 2.1926 - val_task_1_output_accuracy: 0.1336 - val_task_2_output_accuracy: 0.3321\n",
      "Epoch 8/20\n",
      "333/333 [==============================] - 48s 145ms/step - loss: 2.4820 - task_1_output_loss: 3.2969 - task_2_output_loss: 1.9387 - task_1_output_accuracy: 0.1649 - task_2_output_accuracy: 0.3889 - val_loss: 2.7115 - val_task_1_output_loss: 3.5513 - val_task_2_output_loss: 2.1516 - val_task_1_output_accuracy: 0.1528 - val_task_2_output_accuracy: 0.3508\n",
      "Epoch 9/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.3893 - task_1_output_loss: 3.1956 - task_2_output_loss: 1.8519 - task_1_output_accuracy: 0.1780 - task_2_output_accuracy: 0.4176 - val_loss: 18.3030 - val_task_1_output_loss: 19.7977 - val_task_2_output_loss: 17.3066 - val_task_1_output_accuracy: 0.0651 - val_task_2_output_accuracy: 0.1895\n",
      "Epoch 10/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.3313 - task_1_output_loss: 3.1266 - task_2_output_loss: 1.8011 - task_1_output_accuracy: 0.1922 - task_2_output_accuracy: 0.4314 - val_loss: 2.6861 - val_task_1_output_loss: 3.5480 - val_task_2_output_loss: 2.1115 - val_task_1_output_accuracy: 0.1547 - val_task_2_output_accuracy: 0.3725\n",
      "Epoch 11/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.2397 - task_1_output_loss: 3.0170 - task_2_output_loss: 1.7216 - task_1_output_accuracy: 0.2076 - task_2_output_accuracy: 0.4555 - val_loss: 2.5609 - val_task_1_output_loss: 3.4048 - val_task_2_output_loss: 1.9984 - val_task_1_output_accuracy: 0.1731 - val_task_2_output_accuracy: 0.4056\n",
      "Epoch 12/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.1642 - task_1_output_loss: 2.9307 - task_2_output_loss: 1.6531 - task_1_output_accuracy: 0.2239 - task_2_output_accuracy: 0.4781 - val_loss: 2.4776 - val_task_1_output_loss: 3.2470 - val_task_2_output_loss: 1.9647 - val_task_1_output_accuracy: 0.1984 - val_task_2_output_accuracy: 0.4000\n",
      "Epoch 13/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.2997 - task_1_output_loss: 3.0714 - task_2_output_loss: 1.7852 - task_1_output_accuracy: 0.2079 - task_2_output_accuracy: 0.4400 - val_loss: 2.4415 - val_task_1_output_loss: 3.2200 - val_task_2_output_loss: 1.9225 - val_task_1_output_accuracy: 0.1904 - val_task_2_output_accuracy: 0.4119\n",
      "Epoch 14/20\n",
      "333/333 [==============================] - 51s 153ms/step - loss: 2.1714 - task_1_output_loss: 2.9218 - task_2_output_loss: 1.6711 - task_1_output_accuracy: 0.2353 - task_2_output_accuracy: 0.4742 - val_loss: 2.7793 - val_task_1_output_loss: 3.6021 - val_task_2_output_loss: 2.2308 - val_task_1_output_accuracy: 0.1559 - val_task_2_output_accuracy: 0.3392\n",
      "Epoch 15/20\n",
      "333/333 [==============================] - 50s 150ms/step - loss: 2.0525 - task_1_output_loss: 2.7849 - task_2_output_loss: 1.5643 - task_1_output_accuracy: 0.2590 - task_2_output_accuracy: 0.5053 - val_loss: 3.5431 - val_task_1_output_loss: 4.5263 - val_task_2_output_loss: 2.8876 - val_task_1_output_accuracy: 0.0601 - val_task_2_output_accuracy: 0.1636\n",
      "Epoch 16/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 1.9643 - task_1_output_loss: 2.6714 - task_2_output_loss: 1.4929 - task_1_output_accuracy: 0.2794 - task_2_output_accuracy: 0.5282 - val_loss: 2.5039 - val_task_1_output_loss: 3.2895 - val_task_2_output_loss: 1.9801 - val_task_1_output_accuracy: 0.2019 - val_task_2_output_accuracy: 0.4053\n",
      "Epoch 17/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 1.8817 - task_1_output_loss: 2.5844 - task_2_output_loss: 1.4132 - task_1_output_accuracy: 0.2984 - task_2_output_accuracy: 0.5490 - val_loss: 2.3173 - val_task_1_output_loss: 3.0497 - val_task_2_output_loss: 1.8290 - val_task_1_output_accuracy: 0.2487 - val_task_2_output_accuracy: 0.4600\n",
      "Epoch 18/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 1.9845 - task_1_output_loss: 2.6959 - task_2_output_loss: 1.5102 - task_1_output_accuracy: 0.2850 - task_2_output_accuracy: 0.5264 - val_loss: 2.5102 - val_task_1_output_loss: 3.2871 - val_task_2_output_loss: 1.9922 - val_task_1_output_accuracy: 0.2139 - val_task_2_output_accuracy: 0.4067\n",
      "Epoch 19/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 1.9078 - task_1_output_loss: 2.6026 - task_2_output_loss: 1.4446 - task_1_output_accuracy: 0.3002 - task_2_output_accuracy: 0.5411 - val_loss: 2.9472 - val_task_1_output_loss: 3.8109 - val_task_2_output_loss: 2.3714 - val_task_1_output_accuracy: 0.1519 - val_task_2_output_accuracy: 0.3139\n",
      "Epoch 20/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 1.8961 - task_1_output_loss: 2.5819 - task_2_output_loss: 1.4389 - task_1_output_accuracy: 0.3090 - task_2_output_accuracy: 0.5457 - val_loss: 2.2500 - val_task_1_output_loss: 2.9843 - val_task_2_output_loss: 1.7604 - val_task_1_output_accuracy: 0.2560 - val_task_2_output_accuracy: 0.4704\n"
     ]
    }
   ],
   "source": [
    "# train model\n",
    "history_3 = model_3.fit({'input': X_train},\n",
    "                        {'task_1_output': y_train, 'task_2_output': y_train_super}, \n",
    "                        validation_split=0.15,\n",
    "                        epochs=epochs, \n",
    "                        batch_size=batch_size,\n",
    "                        verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6dcb310b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:17:49.178188Z",
     "iopub.status.busy": "2023-04-23T17:17:49.177803Z",
     "iopub.status.idle": "2023-04-23T17:17:49.184925Z",
     "shell.execute_reply": "2023-04-23T17:17:49.183904Z"
    },
    "papermill": {
     "duration": 1.308241,
     "end_time": "2023-04-23T17:17:49.187290",
     "exception": false,
     "start_time": "2023-04-23T17:17:47.879049",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train loss: 1.8961222171783447\n",
      "\n",
      "Train task 1 loss: 2.58193039894104\n",
      "Train task 1 acc: 0.30896469950675964\n",
      "\n",
      "Train task 2 loss: 1.4389159679412842\n",
      "Train task 2 acc: 0.54569411277771\n"
     ]
    }
   ],
   "source": [
    "# train model results\n",
    "print('Train loss:', history_3.history['loss'][-1])\n",
    "\n",
    "print('\\nTrain task 1 loss:', history_3.history['task_1_output_loss'][-1])\n",
    "print('Train task 1 acc:', history_3.history['task_1_output_accuracy'][-1])\n",
    "\n",
    "print('\\nTrain task 2 loss:', history_3.history['task_2_output_loss'][-1])\n",
    "print('Train task 2 acc:', history_3.history['task_2_output_accuracy'][-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35112e6b",
   "metadata": {
    "papermill": {
     "duration": 1.148129,
     "end_time": "2023-04-23T17:17:51.558529",
     "exception": false,
     "start_time": "2023-04-23T17:17:50.410400",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "24461f62",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:17:54.040825Z",
     "iopub.status.busy": "2023-04-23T17:17:54.040473Z",
     "iopub.status.idle": "2023-04-23T17:18:17.805466Z",
     "shell.execute_reply": "2023-04-23T17:18:17.804181Z"
    },
    "papermill": {
     "duration": 25.006334,
     "end_time": "2023-04-23T17:18:17.808447",
     "exception": false,
     "start_time": "2023-04-23T17:17:52.802113",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test model results\n",
    "evaluation_results = model_3.evaluate(\n",
    "                        X_test, \n",
    "                        [y_test, y_test_super],\n",
    "                        verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "bc348fac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:18:20.171028Z",
     "iopub.status.busy": "2023-04-23T17:18:20.170658Z",
     "iopub.status.idle": "2023-04-23T17:18:20.177218Z",
     "shell.execute_reply": "2023-04-23T17:18:20.176064Z"
    },
    "papermill": {
     "duration": 1.152903,
     "end_time": "2023-04-23T17:18:20.181021",
     "exception": false,
     "start_time": "2023-04-23T17:18:19.028118",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 2.2687997817993164\n",
      "\n",
      "Test task 1 loss: 2.996802806854248\n",
      "Test task 1 acc: 0.2513999938964844\n",
      "\n",
      "Test task 2 loss: 1.7834632396697998\n",
      "Test task 2 acc: 0.4657000005245209\n"
     ]
    }
   ],
   "source": [
    "# test model results\n",
    "print('Test loss:', evaluation_results[0])\n",
    "\n",
    "print('\\nTest task 1 loss:', evaluation_results[1])\n",
    "print('Test task 1 acc:', evaluation_results[3])\n",
    "\n",
    "print('\\nTest task 2 loss:', evaluation_results[2])\n",
    "print('Test task 2 acc:', evaluation_results[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38d8ea80",
   "metadata": {
    "papermill": {
     "duration": 1.349428,
     "end_time": "2023-04-23T17:18:22.743634",
     "exception": false,
     "start_time": "2023-04-23T17:18:21.394206",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f143aad1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:18:25.203413Z",
     "iopub.status.busy": "2023-04-23T17:18:25.202965Z",
     "iopub.status.idle": "2023-04-23T17:18:25.678979Z",
     "shell.execute_reply": "2023-04-23T17:18:25.677961Z"
    },
    "papermill": {
     "duration": 1.710172,
     "end_time": "2023-04-23T17:18:25.681396",
     "exception": false,
     "start_time": "2023-04-23T17:18:23.971224",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# accuracy plot\n",
    "plt.plot(history_3.history['task_1_output_accuracy'])\n",
    "plt.plot(history_3.history['task_2_output_accuracy'])\n",
    "plt.plot(history_3.history['val_task_1_output_accuracy'])\n",
    "plt.plot(history_3.history['val_task_2_output_accuracy'])\n",
    "plt.title('Model Accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()\n",
    "\n",
    "# loss plot\n",
    "plt.plot(history_3.history['loss'])\n",
    "plt.plot(history_3.history['task_1_output_loss'])\n",
    "plt.plot(history_3.history['task_2_output_loss'])\n",
    "plt.plot(history_3.history['val_task_1_output_loss'])\n",
    "plt.plot(history_3.history['val_task_2_output_loss'])\n",
    "plt.title('Model Loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['combined' ,'train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c79c60a3",
   "metadata": {
    "papermill": {
     "duration": 1.229869,
     "end_time": "2023-04-23T17:18:28.141578",
     "exception": false,
     "start_time": "2023-04-23T17:18:26.911709",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 2.4. Case 4: Gamma = 0.4 - The model will receive loss 40% from task 1 and 60% task 2.\n",
    "##      (Dropout = 0.4, Optimizer = Adam)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "63df2073",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:18:30.603856Z",
     "iopub.status.busy": "2023-04-23T17:18:30.602847Z",
     "iopub.status.idle": "2023-04-23T17:18:35.284912Z",
     "shell.execute_reply": "2023-04-23T17:18:35.283879Z"
    },
    "papermill": {
     "duration": 5.987169,
     "end_time": "2023-04-23T17:18:35.287648",
     "exception": false,
     "start_time": "2023-04-23T17:18:29.300479",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define parameters and generate model\n",
    "gamma=0.4\n",
    "dropout = 0.4\n",
    "optimizer = 'Adam'\n",
    "model_4 = create_model(dropout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2c7acdef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:18:38.124066Z",
     "iopub.status.busy": "2023-04-23T17:18:38.123688Z",
     "iopub.status.idle": "2023-04-23T17:18:38.154703Z",
     "shell.execute_reply": "2023-04-23T17:18:38.153720Z"
    },
    "papermill": {
     "duration": 1.178461,
     "end_time": "2023-04-23T17:18:38.157081",
     "exception": false,
     "start_time": "2023-04-23T17:18:36.978620",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# compile model\n",
    "model_4.compile(loss={'task_1_output': 'categorical_crossentropy',\n",
    "                    'task_2_output': 'categorical_crossentropy'},\n",
    "              loss_weights={'task_1_output': gamma,\n",
    "                            'task_2_output': 1-gamma},\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "516c716d",
   "metadata": {
    "papermill": {
     "duration": 1.219685,
     "end_time": "2023-04-23T17:18:40.584971",
     "exception": false,
     "start_time": "2023-04-23T17:18:39.365286",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Train & Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ec4925a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:18:42.993894Z",
     "iopub.status.busy": "2023-04-23T17:18:42.993308Z",
     "iopub.status.idle": "2023-04-23T17:36:21.663228Z",
     "shell.execute_reply": "2023-04-23T17:36:21.662239Z"
    },
    "papermill": {
     "duration": 1059.900854,
     "end_time": "2023-04-23T17:36:21.665526",
     "exception": false,
     "start_time": "2023-04-23T17:18:41.764672",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "333/333 [==============================] - 154s 152ms/step - loss: 3.5145 - task_1_output_loss: 4.4549 - task_2_output_loss: 2.8876 - task_1_output_accuracy: 0.0209 - task_2_output_accuracy: 0.0893 - val_loss: 3.3838 - val_task_1_output_loss: 4.3206 - val_task_2_output_loss: 2.7593 - val_task_1_output_accuracy: 0.0269 - val_task_2_output_accuracy: 0.1191\n",
      "Epoch 2/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 3.2754 - task_1_output_loss: 4.1980 - task_2_output_loss: 2.6603 - task_1_output_accuracy: 0.0336 - task_2_output_accuracy: 0.1378 - val_loss: 3.4997 - val_task_1_output_loss: 4.4214 - val_task_2_output_loss: 2.8852 - val_task_1_output_accuracy: 0.0292 - val_task_2_output_accuracy: 0.1273\n",
      "Epoch 3/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 3.1972 - task_1_output_loss: 4.1075 - task_2_output_loss: 2.5903 - task_1_output_accuracy: 0.0428 - task_2_output_accuracy: 0.1668 - val_loss: 3.5539 - val_task_1_output_loss: 4.5489 - val_task_2_output_loss: 2.8906 - val_task_1_output_accuracy: 0.0212 - val_task_2_output_accuracy: 0.1015\n",
      "Epoch 4/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 3.2053 - task_1_output_loss: 4.1075 - task_2_output_loss: 2.6039 - task_1_output_accuracy: 0.0495 - task_2_output_accuracy: 0.1692 - val_loss: 3.2203 - val_task_1_output_loss: 4.1245 - val_task_2_output_loss: 2.6176 - val_task_1_output_accuracy: 0.0513 - val_task_2_output_accuracy: 0.1803\n",
      "Epoch 5/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 3.0190 - task_1_output_loss: 3.8964 - task_2_output_loss: 2.4340 - task_1_output_accuracy: 0.0716 - task_2_output_accuracy: 0.2247 - val_loss: 3.2997 - val_task_1_output_loss: 4.2477 - val_task_2_output_loss: 2.6677 - val_task_1_output_accuracy: 0.0463 - val_task_2_output_accuracy: 0.1784\n",
      "Epoch 6/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.8636 - task_1_output_loss: 3.7265 - task_2_output_loss: 2.2883 - task_1_output_accuracy: 0.0916 - task_2_output_accuracy: 0.2686 - val_loss: 3.5743 - val_task_1_output_loss: 4.6708 - val_task_2_output_loss: 2.8434 - val_task_1_output_accuracy: 0.0476 - val_task_2_output_accuracy: 0.1821\n",
      "Epoch 7/20\n",
      "333/333 [==============================] - 48s 145ms/step - loss: 2.7204 - task_1_output_loss: 3.5678 - task_2_output_loss: 2.1554 - task_1_output_accuracy: 0.1139 - task_2_output_accuracy: 0.3115 - val_loss: 2.9946 - val_task_1_output_loss: 3.8767 - val_task_2_output_loss: 2.4065 - val_task_1_output_accuracy: 0.0957 - val_task_2_output_accuracy: 0.2669\n",
      "Epoch 8/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.6729 - task_1_output_loss: 3.5106 - task_2_output_loss: 2.1144 - task_1_output_accuracy: 0.1240 - task_2_output_accuracy: 0.3264 - val_loss: 5.5076 - val_task_1_output_loss: 7.2512 - val_task_2_output_loss: 4.3452 - val_task_1_output_accuracy: 0.0336 - val_task_2_output_accuracy: 0.1367\n",
      "Epoch 9/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.6273 - task_1_output_loss: 3.4606 - task_2_output_loss: 2.0719 - task_1_output_accuracy: 0.1362 - task_2_output_accuracy: 0.3482 - val_loss: 3.1806 - val_task_1_output_loss: 4.0563 - val_task_2_output_loss: 2.5968 - val_task_1_output_accuracy: 0.0895 - val_task_2_output_accuracy: 0.2393\n",
      "Epoch 10/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.4522 - task_1_output_loss: 3.2601 - task_2_output_loss: 1.9135 - task_1_output_accuracy: 0.1652 - task_2_output_accuracy: 0.3925 - val_loss: 3.7580 - val_task_1_output_loss: 4.7896 - val_task_2_output_loss: 3.0703 - val_task_1_output_accuracy: 0.0833 - val_task_2_output_accuracy: 0.2544\n",
      "Epoch 11/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.3119 - task_1_output_loss: 3.1026 - task_2_output_loss: 1.7848 - task_1_output_accuracy: 0.1920 - task_2_output_accuracy: 0.4293 - val_loss: 3.7740 - val_task_1_output_loss: 4.8177 - val_task_2_output_loss: 3.0783 - val_task_1_output_accuracy: 0.0092 - val_task_2_output_accuracy: 0.0459\n",
      "Epoch 12/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 3.1291 - task_1_output_loss: 4.0159 - task_2_output_loss: 2.5379 - task_1_output_accuracy: 0.0684 - task_2_output_accuracy: 0.2021 - val_loss: 3.4720 - val_task_1_output_loss: 4.4222 - val_task_2_output_loss: 2.8386 - val_task_1_output_accuracy: 0.0389 - val_task_2_output_accuracy: 0.1211\n",
      "Epoch 13/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 2.8210 - task_1_output_loss: 3.6413 - task_2_output_loss: 2.2741 - task_1_output_accuracy: 0.1256 - task_2_output_accuracy: 0.2932 - val_loss: 2.9044 - val_task_1_output_loss: 3.7355 - val_task_2_output_loss: 2.3503 - val_task_1_output_accuracy: 0.1113 - val_task_2_output_accuracy: 0.2705\n",
      "Epoch 14/20\n",
      "333/333 [==============================] - 47s 141ms/step - loss: 2.5655 - task_1_output_loss: 3.3529 - task_2_output_loss: 2.0406 - task_1_output_accuracy: 0.1685 - task_2_output_accuracy: 0.3643 - val_loss: 3.7722 - val_task_1_output_loss: 4.8297 - val_task_2_output_loss: 3.0673 - val_task_1_output_accuracy: 0.0504 - val_task_2_output_accuracy: 0.1552\n",
      "Epoch 15/20\n",
      "333/333 [==============================] - 48s 144ms/step - loss: 3.1443 - task_1_output_loss: 4.0009 - task_2_output_loss: 2.5733 - task_1_output_accuracy: 0.0768 - task_2_output_accuracy: 0.1983 - val_loss: 3.0938 - val_task_1_output_loss: 3.9589 - val_task_2_output_loss: 2.5171 - val_task_1_output_accuracy: 0.0808 - val_task_2_output_accuracy: 0.2161\n",
      "Epoch 16/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.8537 - task_1_output_loss: 3.6563 - task_2_output_loss: 2.3186 - task_1_output_accuracy: 0.1217 - task_2_output_accuracy: 0.2740 - val_loss: 3.0045 - val_task_1_output_loss: 3.8668 - val_task_2_output_loss: 2.4296 - val_task_1_output_accuracy: 0.1044 - val_task_2_output_accuracy: 0.2503\n",
      "Epoch 17/20\n",
      "333/333 [==============================] - 48s 145ms/step - loss: 2.7514 - task_1_output_loss: 3.5425 - task_2_output_loss: 2.2239 - task_1_output_accuracy: 0.1384 - task_2_output_accuracy: 0.3085 - val_loss: 2.8569 - val_task_1_output_loss: 3.6887 - val_task_2_output_loss: 2.3023 - val_task_1_output_accuracy: 0.1272 - val_task_2_output_accuracy: 0.2948\n",
      "Epoch 18/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.7957 - task_1_output_loss: 3.5955 - task_2_output_loss: 2.2625 - task_1_output_accuracy: 0.1316 - task_2_output_accuracy: 0.2951 - val_loss: 2.8170 - val_task_1_output_loss: 3.6497 - val_task_2_output_loss: 2.2618 - val_task_1_output_accuracy: 0.1223 - val_task_2_output_accuracy: 0.2881\n",
      "Epoch 19/20\n",
      "333/333 [==============================] - 47s 142ms/step - loss: 2.6063 - task_1_output_loss: 3.3800 - task_2_output_loss: 2.0905 - task_1_output_accuracy: 0.1627 - task_2_output_accuracy: 0.3461 - val_loss: 2.7583 - val_task_1_output_loss: 3.5609 - val_task_2_output_loss: 2.2232 - val_task_1_output_accuracy: 0.1348 - val_task_2_output_accuracy: 0.3125\n",
      "Epoch 20/20\n",
      "333/333 [==============================] - 48s 143ms/step - loss: 2.4785 - task_1_output_loss: 3.2371 - task_2_output_loss: 1.9727 - task_1_output_accuracy: 0.1851 - task_2_output_accuracy: 0.3807 - val_loss: 2.6475 - val_task_1_output_loss: 3.4424 - val_task_2_output_loss: 2.1176 - val_task_1_output_accuracy: 0.1568 - val_task_2_output_accuracy: 0.3436\n"
     ]
    }
   ],
   "source": [
    "# train model\n",
    "history_4 = model_4.fit({'input': X_train},\n",
    "                        {'task_1_output': y_train, 'task_2_output': y_train_super}, \n",
    "                        validation_split=0.15,\n",
    "                        epochs=epochs, \n",
    "                        batch_size=batch_size,\n",
    "                        verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0514705d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:36:24.776231Z",
     "iopub.status.busy": "2023-04-23T17:36:24.775192Z",
     "iopub.status.idle": "2023-04-23T17:36:24.782520Z",
     "shell.execute_reply": "2023-04-23T17:36:24.781384Z"
    },
    "papermill": {
     "duration": 1.60085,
     "end_time": "2023-04-23T17:36:24.786108",
     "exception": false,
     "start_time": "2023-04-23T17:36:23.185258",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train loss: 2.4784820079803467\n",
      "\n",
      "Train task 1 loss: 3.237126111984253\n",
      "Train task 1 acc: 0.185082346200943\n",
      "\n",
      "Train task 2 loss: 1.972718358039856\n",
      "Train task 2 acc: 0.38070589303970337\n"
     ]
    }
   ],
   "source": [
    "# train model results\n",
    "print('Train loss:', history_4.history['loss'][-1])\n",
    "\n",
    "print('\\nTrain task 1 loss:', history_4.history['task_1_output_loss'][-1])\n",
    "print('Train task 1 acc:', history_4.history['task_1_output_accuracy'][-1])\n",
    "\n",
    "print('\\nTrain task 2 loss:', history_4.history['task_2_output_loss'][-1])\n",
    "print('Train task 2 acc:', history_4.history['task_2_output_accuracy'][-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "884810b4",
   "metadata": {
    "papermill": {
     "duration": 1.595421,
     "end_time": "2023-04-23T17:36:27.967084",
     "exception": false,
     "start_time": "2023-04-23T17:36:26.371663",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "af760084",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:36:31.319691Z",
     "iopub.status.busy": "2023-04-23T17:36:31.319320Z",
     "iopub.status.idle": "2023-04-23T17:36:45.238103Z",
     "shell.execute_reply": "2023-04-23T17:36:45.237064Z"
    },
    "papermill": {
     "duration": 15.683208,
     "end_time": "2023-04-23T17:36:45.240614",
     "exception": false,
     "start_time": "2023-04-23T17:36:29.557406",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test model results\n",
    "evaluation_results = model_4.evaluate(\n",
    "                        X_test, \n",
    "                        [y_test, y_test_super],\n",
    "                        verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "95896d92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:36:48.340017Z",
     "iopub.status.busy": "2023-04-23T17:36:48.338955Z",
     "iopub.status.idle": "2023-04-23T17:36:48.345790Z",
     "shell.execute_reply": "2023-04-23T17:36:48.344679Z"
    },
    "papermill": {
     "duration": 1.598302,
     "end_time": "2023-04-23T17:36:48.349237",
     "exception": false,
     "start_time": "2023-04-23T17:36:46.750935",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 2.6397483348846436\n",
      "\n",
      "Test task 1 loss: 3.4251270294189453\n",
      "Test task 1 acc: 0.16519999504089355\n",
      "\n",
      "Test task 2 loss: 2.1161606311798096\n",
      "Test task 2 acc: 0.34929999709129333\n"
     ]
    }
   ],
   "source": [
    "# test model results\n",
    "print('Test loss:', evaluation_results[0])\n",
    "\n",
    "print('\\nTest task 1 loss:', evaluation_results[1])\n",
    "print('Test task 1 acc:', evaluation_results[3])\n",
    "\n",
    "print('\\nTest task 2 loss:', evaluation_results[2])\n",
    "print('Test task 2 acc:', evaluation_results[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95e200f9",
   "metadata": {
    "papermill": {
     "duration": 1.603709,
     "end_time": "2023-04-23T17:36:51.534233",
     "exception": false,
     "start_time": "2023-04-23T17:36:49.930524",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "61332b51",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:36:54.888969Z",
     "iopub.status.busy": "2023-04-23T17:36:54.888611Z",
     "iopub.status.idle": "2023-04-23T17:36:55.346796Z",
     "shell.execute_reply": "2023-04-23T17:36:55.345823Z"
    },
    "papermill": {
     "duration": 2.117161,
     "end_time": "2023-04-23T17:36:55.349061",
     "exception": false,
     "start_time": "2023-04-23T17:36:53.231900",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ePObOnVumn5VAYGbnW3DudzDkwNV/7G2NQCCwIqKJXylk6Qy0fGObXfY+M38IWk3pvyIfHx80Gg1arZZatWoVenz+/PkMGjTIfNvf35927dqZby9YsIANGzawadMm5syZU+w+M2fOZPLkyQC8++67LFu2jEOHDjF06NBC5/r5+aFSqfDy8ipgU3BwMC+88IL59pNPPsmff/7Jzz//TLdu3YiJiUGv13PvvfdSv359gCI9Lr/99hvTp0/nq6++MtskEJSZk7/AgU9u3066aj9bBAKB1RGem2pA586dC9zOyMjgpZdeomXLlvj6+uLp6cm5c+dK9dy0bdvWfOzh4YGXl5d5VEFZMRgMvPPOO7Rt2xZ/f388PT3Zvn27ee927doxYMAA2rRpw/jx4/n6669JSkoqsEZYWBj33Xcf3333nRA2AsuJOQ6/5Yl433ry92QhbgQCZ0J4bkrBXa3izPwhdtvbGnh4eBS4/eKLL7Jt2zY++ugjGjdujLu7O+PGjSM3N7fEddRqdYHbCoUCo9FokS2LFi1i8eLFLFmyhDZt2uDh4cEzzzxj3lulUrFjxw4OHDjA9u3bWbZsGXPnziUsLIwGDRoA0KhRI/z9/Vm+fDkjRoxAo9FYZIOgGpMRD2ungj4LGg+CDtPg5/shKdLelgkEAisixE0pKBSKMoWG7I1Go8FgMJTp3H379jFz5kzGjh0LQHp6OpGRkZVi0759+xg9ejTTpk0DwGg0cvHiRVq0aGE+R6FQcNddd3HXXXfxxhtvUL9+fTZs2MBzzz0HQEBAAOvXr6dv375MnDiRn376qZDwEggKYdDBzzMh5Rr4NYL7voHkPG+lCEsJBE6FCEs5CaGhoYSFhREZGUl8fHyJHpXGjRuzfv16IiIiOH78OFOmTLHYA1NWm/bu3cuNGzeIj483723yzJw9e5ZHHnmE2NhY8zVhYWG8++67HDlyhKioKNavX8+tW7cKiB+AoKAgdu3axblz55g8eXKJJe5RUVFEREQQFRWFwWAgIiKCiIgI0tPTrf6cBQ7MtrkQuQ80njBpNbj7Qg05r4vMeMgRfw8CgbMgxI2T8MILL6BSqWjZsiWBgYEl5s8sXryYGjVq0LNnT0aNGsWQIUPo2LGj1W2aP38+kZGRNGrUiMDAQABef/11OnbsyJAhQ+jbty+1atUq0HHY29ubvXv3Mnz4cJo2bcprr73GokWLGDZsWKH1a9Wqxa5duzh58iRTp04t1nP1xhtv0KFDB958803S09Pp0KEDHTp04MiRI1Z/zgIHJfxHOPSVfHzv/yCouXzs5gPuNeRjkXcjEDgNCqms9cZOQmpqKj4+PqSkpODt7V3gsezsbK5cuUKDBg1wc3Ozk4UCeyP+DpyM60dgxTAw5ELfV6HvKwUf/6oPxETI3pzmI+xiokAgKJ2S3r/vRHhuBAKB85IWKzfqM+RC85Fw90uFz6kRKn8XeTcCgdMgxI1AIHBO9DmwbjqkxUBgcxj7JSiLeMkz5d2IsJRA4DQIcSMQCJwPSYI/XoDrh+S8mkmrwdWr6HPNnpvIyrJOIBDYGCFuBAKB83FkORz7HlDAfcvBv1Hx5/rmeW5EWEogcBqEuBEIBM7F1QOwNS+3ZuCb0GRgyeebPDfJV2WPj0AgqPIIcSMQCJyHlOvw0www6qHVvXDXM6Vf41MXUIAuEzJu2dpCgUBQCQhxIxAInANdljxaIeMW1GwDoz8FhaL061w04B0sH4u8G4HAKRDiRiAQVH0kCTY/LfercfeDSatA41HqZWZEObhA4FQIcSMQCKo+B7+AE+tAoYLxK2+Xd5cV0/nCcyMQOAVC3AiKJDQ0lCVLltjbjELMnDmzwLgGgYD/9sD21+TjIe9Awz6Wr2FOKo60klECgcCeCHHjJPTt25dnnnnGausdPnyYhx9+uEJrOIJAioyM5MEHH6RBgwa4u7vTqFEj3nzzTXJzc+1ql8BKJEXKk74lA7SbAt0eLd86ohxcIHAq7C5uPv/8c/MMn06dOrFv374yXbd//35cXFxo3769bQ10IiRJKnF6dn4CAwPRarU2tsj2nDt3DqPRyFdffcXp06dZvHgxX375Jf/3f/9nb9MEFSU3Q04gzkqCOh1h5OKyJRAXhci5EQicCruKm3Xr1vHMM88wd+5cwsPD6d27N8OGDStxojVASkoKM2bMYMCAAZVkqWMzc+ZM/v77b5YuXYpCoUChUBAZGcmePXtQKBRs27aNzp074+rqyr59+7h8+TKjR4+mZs2aeHp60qVLF3bu3FlgzTu9LgqFgm+++YaxY8ei1Wpp0qQJmzZtKtamvn37cvXqVZ599lmzTQAJCQlMnjyZkJAQtFotbdq0Yc2aNQWu/eWXX2jTpg3u7u74+/szcOBAMjIyitzn6NGjBAUF8c477xT5+NChQ1mxYgWDBw+mYcOG3HPPPbzwwgusX7++LD9agaMiSbDxcbh5CjyCYOKPoK7AkFNTzk3qdTDorGOjQCCwG3YVNx9//DEPPvggs2fPpkWLFixZsoS6devyxRdflHjdI488wpQpU+jRo4ftjZQk+ROiPb7K2FBs6dKl9OjRg4ceeoiYmBhiYmKoW7eu+fGXXnqJ9957j7Nnz9K2bVvS09MZPnw4O3fuJDw8nCFDhjBq1KhSReW8efOYMGECJ06cYPjw4UydOpXExMQiz12/fj0hISHMnz/fbBPIE7c7derE77//zqlTp3j44YeZPn06YWFhAMTExDB58mRmzZrF2bNn2bNnD/feey9FDa/fs2cPAwYMYN68ecydO7dMPyuQxbGfn1+Zzxc4IP98DGc2glINE38An+CKredZE1zcQDJCyjWrmCgQCOyHi702zs3N5ejRo7zyyisF7h88eDAHDhwo9roVK1Zw+fJlfvzxRxYsWFDqPjk5OeTk5Jhvp6amWmaoLhPerWPZNdbi/6LLVM7q4+ODRqNBq9VSq1atQo/Pnz+fQYMGmW/7+/vTrl078+0FCxawYcMGNm3axJw5c4rdZ+bMmUyePBmAd999l2XLlnHo0CGGDh1a6Fw/Pz9UKhVeXl4FbAoODuaFF14w337yySf5888/+fnnn+nWrRsxMTHo9Xruvfde6teXP023adOm0Pq//fYb06dP56uvvjLbVBYuX77MsmXLWLRoUZmvETgYF7bDX2/Lx8M/hHrdK76mQiHn3cSfl0NTfg0rvqZAILAbdvPcxMfHYzAYqFmzZoH7a9asSWxsbJHXXLx4kVdeeYVVq1bh4lI2Xfbee+/h4+Nj/srv0agudO7cucDtjIwMXnrpJVq2bImvry+enp6cO3euVM9N27ZtzcceHh54eXkRFxdnkS0Gg4F33nmHtm3b4u/vj6enJ9u3bzfv3a5dOwYMGECbNm0YP348X3/9NUlJSQXWCAsL47777uO7776zSNhER0czdOhQxo8fz+zZsy2yW+AgxF+CX2cDEnR6ADo/YL21RTm4QOA02M1zY0JxRwKgJEmF7gP5TXHKlCnMmzePpk2blnn9V199leeee858OzU11TKBo9bKHhR7oLZOQq+HR0Hvz4svvsi2bdv46KOPaNy4Me7u7owbN67UCiK1Wl3gtkKhwGg0WmTLokWLWLx4MUuWLKFNmzZ4eHjwzDPPmPdWqVTs2LGDAwcOsH37dpYtW8bcuXMJCwujQYMGADRq1Ah/f3+WL1/OiBEj0Gg0pe4bHR1Nv3796NGjB//73/8sslngIGSnwtopkJMCdbvDsA+su37+GVMCgaBKYzdxExAQgEqlKuSliYuLK+TNAUhLS+PIkSOEh4ebQydGoxFJknBxcWH79u3079+/0HWurq64urqW31CFwrJOp3ZCo9FgMBjKdO6+ffuYOXMmY8eOBSA9PZ3IyMhKsWnfvn2MHj2aadOmAfLv8OLFi7Ro0cJ8jkKh4K677uKuu+7ijTfeoH79+mzYsMEsUgMCAli/fj19+/Zl4sSJ/PTTT4WEV35u3LhBv3796NSpEytWrECptHuRoMBSjEbY8IgcNvKqAxO+l8cmWBNRDi4QOA12e5XXaDR06tSJHTt2FLh/x44d9OzZs9D53t7enDx5koiICPPXo48+SrNmzYiIiKBbt26VZbpDEhoaSlhYGJGRkcTHx5foUWncuDHr168nIiKC48ePM2XKFIs9MGW1ae/evdy4cYP4+Hjz3ibPzNmzZ3nkkUcKCNywsDDeffddjhw5QlRUFOvXr+fWrVsFxA9AUFAQu3bt4ty5c0yePLnYEvfo6Gj69u1L3bp1+eijj7h16xaxsbHFhj4FDsrfC+H8H6ByhUk/glfhD0AVxlwOHmn9tQUCQaVi17DUc889x/Tp0+ncubM5XBAVFcWjj8qNuF599VVu3LjB999/j1KppHXr1gWuDwoKws3NrdD91ZEXXniB+++/n5YtW5KVlcWVK1eKPXfx4sXMmjWLnj17EhAQwMsvv2x5onUZmD9/Po888giNGjUiJycHSZJ4/fXXuXLlCkOGDEGr1fLwww8zZswYUlJSAFnE7t27lyVLlpCamkr9+vVZtGgRw4YNK7R+rVq12LVrF3379mXq1KmsXr0alUpV4Jzt27dz6dIlLl26REhISIHHiqrAEjggZzfD3+/Lx6OWQnAn2+xjyrkRYSmBoMqjkOz8Cv/555/zwQcfEBMTQ+vWrVm8eDF33303IFfnmPq1FMVbb73Fxo0biYiIKPN+qamp+Pj4kJKSgre3d4HHsrOzuXLlirmpoKB6Iv4OHIi4c/DNAMhNh26PwbCFttsrOxUW5uXjvXodXL1st5dAILCYkt6/78Tu4qayEeJGUBri78BBMOhkYRNzHEJ7w/SNoLKxs/n9BpCVCI/uh1rCIywQOBKWiBuRWSkQCByTfxbLwsa9Btz3re2FDYhycIHASRDiRiAQOB6xJ2/n2Qz70DYJxEUhysEFAqdAiBuBQOBY6HNh42Ng1EPzkdBmXOXtLcrBBQKnQIgbgUDgWOxbJHtu3P0qNum7PIhycIHAKRDiRiAQOA4xx2HfR/LxiI/AM6hy9xfl4AKBUyDEjUAgcAz0ubAhLxzVcjS0urfybcgflqpehaQCgVMhxI1AIHAM9n4AcadBGwAjPq7ccJQJn7qgUII+C9ItGworEAgcByFuBAKB/YkOh30fy8cjFoFHgH3scNGAd7B8LPJuBILycfIXu///CHEjMBMaGsqSJUsqdc+VK1fi6+tbqXsKHAx9jhyOkgxyKKrVGPvaI8rBBYLyc2E7rH8IvhkIqdF2M0OIG0GZmTlzJmPGjLG3Gaxfv54hQ4YQEBCAQqGwaPyGwAHZsxBunQWPQBj+kb2tEeXgAkF5iT0JvzwAkhGaDgWv2nYzRYgbQZUjIyODu+66i4ULbThnSFA53DgK+5fIxyMXg4e/Xc0BRDm4QFAeUmNg9UR5DlyDuyu/jcMdCHHjBHz11VcEBwdjNBoL3H/PPfdw//33A3D58mVGjx5NzZo18fT0pEuXLuzcubPMe7z11lt89913/PbbbygUChQKhXmg6csvv0zTpk3RarU0bNiQ119/HZ1OZ772+PHj9OvXDy8vL7y9venUqRNHjhwpcp+EhAS6du3KPffcQ3Z2dpHnTJ8+nTfeeIOBAweW2X6BA6LLzgtHGaHNeGgxyt4WyYhycIHAMnIzYM1ESL0BAc1gwg+gUtvVpEoY1lK1kSSJLH2WXfZ2d3FHUQblO378eJ566il2797NgAEDAEhKSmLbtm1s3rwZgPT0dIYPH86CBQtwc3Pju+++Y9SoUZw/f5569eqVuscLL7zA2bNnSU1NZcWKFQD4+fkB4OXlxcqVK6lTpw4nT57koYcewsvLi5deegmAqVOn0qFDB7744gtUKhURERGo1YX/8K9fv87gwYPp3Lkzy5cvx8VF/Hk6NXvehfjz4BEEwz6wtzW3EZ4bgaDsGA3w62y5R5U2AKb+BO6+9rZKiJvSyNJn0W11N7vsHTYlDK1aW+p5fn5+DB06lNWrV5vFzc8//4yfn5/5drt27WjXrp35mgULFrBhwwY2bdrEnDlzSt3D09MTd3d3cnJyqFWrVoHHXnvtNfNxaGgozz//POvWrTOLm6ioKF588UWaN28OQJMmTQqtf+HCBQYNGsTo0aNZunRpmUSdoApz7TAcWCYfj1oCWj+7mlMAU85N6g25946Lxr72CASOzPbX4Pwf4OIGk9fe/nBgZ0RYykmYOnUqv/76Kzk5OQCsWrWKSZMmoVKpADlP5aWXXqJly5b4+vri6enJuXPniIqKqvDev/zyC7169aJWrVp4enry+uuvF1j3ueeeY/bs2QwcOJCFCxdy+fLlAtdnZWXRq1cvxowZwyeffCKEjbOjy5JnR0lGaDsRmo+wt0UF8QwCF3fZvpRr9rZGIHBcDn0NBz+Xj8d+CXW72NeefAjPTSm4u7gTNiXMbnuXlVGjRmE0GtmyZQtdunRh3759fPzxx+bHX3zxRbZt28ZHH31E48aNcXd3Z9y4ceTm5lbIxoMHDzJp0iTmzZvHkCFD8PHxYe3atSxatMh8zltvvcWUKVPYsmULW7du5c0332Tt2rWMHTsWAFdXVwYOHMiWLVt48cUXCQkJqZBNAgdn1wJIuAietWCoAyaFKxRy3s2tc3LejX8je1skEDgeF7bDVtk7z4A3odVY+9pzB0LclIJCoShTaMjeuLu7c++997Jq1SouXbpE06ZN6dSpk/nxffv2MXPmTLOgSE9PJzIy0qI9NBoNBoOhwH379++nfv36zJ0713zf1auFEzGbNm1K06ZNefbZZ5k8eTIrVqww26JUKvnhhx+YMmUK/fv3Z8+ePdSpU8ci2wRVhKgw+Pcz+XjUUscKR+XHN0/ciLwbgaAw+Uu+O0yHXs/a26JCiLCUEzF16lS2bNnC8uXLmTZtWoHHGjduzPr164mIiOD48eNMmTKlUHVVaYSGhnLixAnOnz9PfHw8Op2Oxo0bExUVxdq1a7l8+TKffPIJGzZsMF+TlZXFnDlz2LNnD1evXmX//v0cPnyYFi1aFFhbpVKxatUq2rVrR//+/YmNjS3WjsTERCIiIjhz5gwA58+fJyIiosRrBA5AbqYcjkKCdlOg2VB7W1Q85qRiUTElEBSgQMl3H7uXfBeHEDdORP/+/fHz8+P8+fNMmTKlwGOLFy+mRo0a9OzZk1GjRjFkyBA6duxo0foPPfQQzZo1o3PnzgQGBrJ//35Gjx7Ns88+y5w5c2jfvj0HDhzg9ddfN1+jUqlISEhgxowZNG3alAkTJjBs2DDmzZtXaH0XFxfWrFlDq1at6N+/P3FxRc/22bRpEx06dGDECDlXY9KkSXTo0IEvv/zSoucjqGR2LYDEy3Jjr6Hv2duakhHl4AJBYXLSYfWEfCXf39u95Ls4FJJUvUbfpqam4uPjQ0pKCt7e3gUey87O5sqVKzRo0AA3Nzc7WSiwN+LvwAZcPQArhgMSTP0Fmgyyt0Ulc24LrJ0CdTrAw3vsbY1AYH+MBlg7FS5slUu+H/qr0iujSnr/vhPhuREIBLYlNwM2Pg5I0GGa4wsbECMYTBj09rZA4Chsf00WNg5W8l0cQtwIBALb8td8SLoiT9se8q69rSkbprBUViJkp9rXFntx9Dt4OwDO/WFvSwT2xoFLvotDiBuBQGA7Iv+BsLxcqHs+ATcf+9pTVly9QJs356o65t0Y9PD3+4AEZzfb2xqBPXHwku/iEOJGIBDYhpz0vHAU0PF+aFzFZoGZQ1ORdjXDLlzYKieNAtw8ZV9bBPajCpR8F4cQNwKBwDbsfEv2evjUhcEL7G2N5VTncvBDX98+vnVe5N5UR1KjYdUEhy/5Lg4hbgQCgfX57284nPcGec8ycCu5ssEhqa7l4LcuwJW/QaEElSsYcuQSfkH1ISdd7mWTFu3wJd/FIcSNQCCwLjlpsClvGGvnWdCon33tKS/VdTr44W/k702HQq028rEITVUfTFO+Y0841JRvSxHiRiAQWJcdb0ByFPjWg0Hz7W1N+amO5eA56XB8jXzcZTbUbCUf3zxtP5sElcu2uVWq5Ls4xGwpgUBgPS7vhiPL5ePRn8lVR1WV/GEpSapS+Qbl5sQ6yEkFv0bQsB8k5IWjbp6xr12CyuHQ1xD2hXxcRUq+i0N4bgRmQkNDWbJkSaXuuXLlSnx9fSt1T4GNyE6FTU/Kx10eggZ329eeiuJTV8470WdD+k17W2N7JAkOfysfd5kNSiXUbCnfFp4b56eKlnwXhxA3gjIzc+ZMxowZY1cbdDodL7/8Mm3atMHDw4M6deowY8YMoqOj7WqXALmDaco1OZwz8C17W1NxVGrwDpGPq0PeTdS/EHcaXNyhfd5suqA8cZMSBdkp9rNNYFuqcMl3cQhxI6hSZGZmcuzYMV5//XWOHTvG+vXruXDhAvfcc4+9TaveXNoJx76Tj8d8Dq6e9rXHWtSoRnk3pvLvtuNvJ5Bq/eTO0iBCU85KFS/5Lg4hbpyAr776iuDgYIxGY4H777nnHu6//34ALl++zOjRo6lZsyaenp506dKFnTt3lnmPt956i++++47ffvsNhUKBQqFgz549ALz88ss0bdoUrVZLw4YNef3119HpdOZrjx8/Tr9+/fDy8sLb25tOnTpx5MiRIvdJSEiga9eu3HPPPWRnZxd63MfHhx07djBhwgSaNWtG9+7dWbZsGUePHiUqKqrMz0dgRbJTYNNT8nG3RyG0l33tsSbVpRw8LRbObpKPuzxU8DFTUnGcCE05HU5Q8l0cIqG4FCRJQsrKssveCnd3FGVQ0OPHj+epp55i9+7dDBgwAICkpCS2bdvG5s1y6/T09HSGDx/OggULcHNz47vvvmPUqFGcP3+eevXqlbrHCy+8wNmzZ0lNTWXFihUA+Pn5AeDl5cXKlSupU6cOJ0+e5KGHHsLLy4uXXpLjt1OnTqVDhw588cUXqFQqIiIiUKsL/wNdv36dwYMH07lzZ5YvX46LS9n+PFNSUlAoFCJ3x15s+z+5m22NBjDgDXtbY12qSzn40e/AqIe63aB224KPBbWEi9tF3o2z4SQl38UhxE0pSFlZnO/YyS57Nzt2FIVWW+p5fn5+DB06lNWrV5vFzc8//4yfn5/5drt27WjXrp35mgULFrBhwwY2bdrEnDlzSt3D09MTd3d3cnJyqFWrVoHHXnvtNfNxaGgozz//POvWrTOLm6ioKF588UWaN28OQJMmTQqtf+HCBQYNGsTo0aNZunRpmUQdQHZ2Nq+88gpTpkzB27sKNoqryuiyYftcCP8RUMjhKI2Hva2yLr6h8ndnDksZdHBU/sBSyGsDULO1/F2IG+fCSUq+i0OEpZyEqVOn8uuvv5KTkwPAqlWrmDRpEiqVCoCMjAxeeuklWrZsia+vL56enpw7d84qoZxffvmFXr16UatWLTw9PXn99dcLrPvcc88xe/ZsBg4cyMKFC7l8uWC306ysLHr16sWYMWP45JNPyixsdDodkyZNwmg08vnnn1f4eQgs4NYF+GbA7YZvA96A+j3ta5MtqA6em/N/QFoMeARCyyJy18y9bs7IFVWCqo8TlXwXh/DclILC3Z1mx47abe+yMmrUKIxGI1u2bKFLly7s27ePjz/+2Pz4iy++yLZt2/joo49o3Lgx7u7ujBs3jtzc3ArZePDgQSZNmsS8efMYMmQIPj4+rF27lkWLFpnPeeutt5gyZQpbtmxh69atvPnmm6xdu5axY+VSQ1dXVwYOHMiWLVt48cUXCQkJKXVfnU7HhAkTuHLlCrt27RJem8pCkiBiNfzxAugyZXf2vV9VvaGYZcWUc5N6A/S54KKxrz22wJRI3PF+cHEt/HhAE1CqITdNbs5o+pkIqiaJV2SvDdis5FuSpDJ/SLUVQtyUgkKhKFNoyN64u7tz7733smrVKi5dukTTpk3p1Ol2OG3fvn3MnDnTLCjS09OJjIy0aA+NRoPBYChw3/79+6lfvz5z584133f1amEXftOmTWnatCnPPvsskydPZsWKFWZblEolP/zwA1OmTKF///7s2bOHOnXqFGuHSdhcvHiR3bt34+/vb9HzEJSTnDT4/Tk4+ZN8u0EfuPd/4FWr5OuqMh6BoNbKQi7lGvg3srdF1iXuHETuk/v5dJpZ9DkqNQQ2h5sn5dCUEDdVm+2vyfPCGva1Scm3ZDAQ/fIreNx1F75jx1h9/bIiwlJOxNSpU9myZQvLly9n2rRpBR5r3Lgx69evJyIiguPHjzNlypRC1VWlERoayokTJzh//jzx8fHodDoaN25MVFQUa9eu5fLly3zyySds2LDBfE1WVhZz5sxhz549XL16lf3793P48GFatGhRYG2VSsWqVato164d/fv3JzY2tkgb9Ho948aN48iRI6xatQqDwUBsbCyxsbEV9kIJSiA6Ar66WxY2ChX0fw2mb3BuYQNySax5DEOkXU2xCaawYrPh4Fu3+PNEMz/n4L89cO53+X946PtWL/mWjEZiXnud1N9/J/bNN9EV8zpeGQhx40T0798fPz8/zp8/z5QpUwo8tnjxYmrUqEHPnj0ZNWoUQ4YMoWPHjhat/9BDD9GsWTM6d+5MYGAg+/fvZ/To0Tz77LPMmTOH9u3bc+DAAV5//XXzNSqVioSEBGbMmEHTpk2ZMGECw4YNY968eYXWd3FxYc2aNbRq1Yr+/fsTFxdX6Jzr16+zadMmrl+/Tvv27aldu7b568CBAxY9H0EZkCQ4+CV8OwgS/5Ob2s3cAne/CEqVva2rHGo4qbjJSYPja+XjLrNLPtecdyMGaFZZDHrY+op83PUhCGpu1eUlSeLmgndI2bABVCrqfPQh6lr2+/CjkKTqlSGWmpqKj48PKSkphfI0srOzuXLlCg0aNMDNzc1OFgrsjfg7yCMzETY+LldUADQfCfcskxu7VSe2vgxhX8JdT1ftQaB3cuhrOXfKvwnMOVzyp/hLO+HH+yCgqXyuoOoR9pU8XsHdD546Bu41rLa0JEncWrSIhG++BYWCOu8vxMcGjVVLev++E5FzIxAICnP1gNwDI/UGqDQw+B35054TdC61GGecDn7nHKnSfq+mcvCES6DLAnXZix0EDkBGAux+Rz4e8LpVhQ1A/BdfyMIGqPXWWzYRNpYixI1AILiN0QD7FsGe9+Q5M/6NYdyKwo3dqhPOWA5+dT/cOisnS7ebVPr5njXlT/xZiXDrHNTpYHsbBdZj9wK5k3itNnJVnBVJWLGS+E+WARD0ysvUmDjBquuXF5FzIxAIZFJj4PvR8ic8yQjtJsPDf1dvYQPOOYLBPEdqQtm60ioU+fJuRFJxlSL2JBxdKR8Pfd+quXJJa9cR9/77AAQ+/RT+M2dabe2KIsSNQCCAizvgy7vksmC1B4z5Um7u5SwDMCuCKSyVleQck7FTY+SKGSi6I3FxmDsViwGaVQZJkpOIJaPczyb0LqstnfLbb8TmFYb4PzQb/0cftdra1kCEpYqgmuVYC+6gWv3+9bmwaz4ckN3K1GwD41fIjdsEMq6ecrPCzHg576aqe7KOrpTnSNXrAbVal/06UTFV9TizEa7+Ay7uMOhtqy2bum070a/+H0gSNaZOJfC55+zetO9OhOcmH6ZhjpmZmXa2RGBPTL//ooZ7OhWJV2DF0NvCpuvDMHunEDZF4Szl4Abd7RBFaeXfd2LudXNKjGGoCuRmwva8thy9nim5j5EFpP/9NzdeeAGMRnzuvZeac//P4YQNCM9NAVQqFb6+vub+Klqt1iF/aQLbIEkSmZmZxMXF4evra57L5ZScWg+bn4acVHDzhdGfQYuR9rbKcakRCjeOVv28m3O/Q3oseARBCwsrWgJbAArITID0OPCqaRMTBVbiwCdyV22futDzKassmXEwjOtPPQ06Hd7Dh1H77fkolI7pIxHi5g5ME6+LaiAnqB74+voWmnzuNORmwp+vwLHv5Nt1u8N931jtU53T4izl4IfyOhJ3ut/yOVkarTx+IuESxJ0W4saRSb4G/yyRjwe/Lf/uKkhmeDjXHn8cKScHz/79qfP++ygc+AOgEDd3oFAoqF27NkFBQeh0OnubI6hk1Gq183ps4s7Czw/IJcAooPfz0PdVUImXgVJxhnLwm2fk/AuFCjo9UL41araSxc3N09Cov3XtE1iPHa+DPgvq94KWYyq8XNbp01x7+BGkzEw8evYkePHHKBw8bC9e1YpBpVI575ucoHohSbKnZusr8gueR5A88LJRP3tbVnVwhnJw0xyp5sPBJ7h8awS1gjO/iXJwRybyHzi9QR6GOmxhhRtv5ly8yLUHZ2NMS8O9UydCPl2G0rWI6fEOhhA3AoEzE3cW/nobzm+RbzfqD2O/As8g+9pV1cgfljIawUHzDIolOxVOrJOPLSn/vhNRMeXYGA2350d1mik37asAuVevEjXrQQzJybi1bk3dr75Eqa14iKsyEOJGIHBG4s7B3+/Ln+CQQOkC/V+XEwur2huzI+ATIodzDDmQfhO8a9vbIss4vhZy0yGgGTS4u/zrmMTNrfPyIEYR0nQsjn0HN0+Cmw/0e61CS+mio7n6wAPob93CtWlT6n3zNSrPqtP3SvxlCgTOxK3zsqg5tR7IK9dtORr6vHK7lFdgOSq1HMpJjpLzbqqSuJGk2yGpssyRKgnf+qDxlIVSwiWrT5YWVICsJNlLC9BvLnj4l3spXVycLGyiY9CEhlJv+beofH2tY2clIcSNQOAM3LoAez+Ak79gFjUtRsmixpJGbYLiqREqi5vkq1C/h72tKTuR+yD+vNx5ut3Eiq2lVEJQC7h+WA5NCXHjOOxZKM/+CmwBnR8s9zL6pCSuPfgguqtRqIODqbdyBS4BAVY0tHIQ4kYgqMrEX4S/P4BTv8gt1gGaj4Q+L1f9TrqORlUtBzfNkWo3UQ5XVJSarfLEzWloM67i6wkqTtzZ27/nYQvLHS40pKZy7cHZ5Fy8hEtQEPVWrkBdRdtiCHEjEFRF4i/leWp+vi1qmo2Avi9D7Xb2tc1ZqYrl4Ck34FxeMnlFEonzY54xJSqmHAJJkntXSQb5g03DvuVaxpiRwbVHHiX7zBlUfn7UW7kCTd2q2/9KiBuBoCqRcBn2fihXvphFzXDZU1OnvV1Nc3pM4qYqlYMfXSm/6dW/y3o5V6ak4jgxQNMhOLcF/tsDKlcYvKBcSxizs7n2xByywsNRentTb/m3uDZsaF07KxkhbgSCqkDCZdj7UZ6oMcj3NR0me2rqdLCvbdWFqua50eeWf45USQS1kL+nXIOsZHD3td7aAsvQZcP2ufJxzzng18DiJaTcXG48/QyZBw+i1Gqp9/X/cGte9XOphLgRCByZxP9kUXN87W1R02QI9H0Fgjva17bqhinnJjUa9Dng4uCNzM5thow48KwpJ5dbC/ca4B0Cqddl7039ntZbW2AZBz+TxbZXbej1nMWXS3o9N158ifS//0bh5kbIl1/g3s45wtpC3AgEjkjiFdj3EUSsySdqBsvVTyGd7GtbdcUjANRa0GXKs3sCGtvbopIxz5GaKZeyW5OarWRxc/O0EDf2IjUa9i6SjwfNB1fLetBIRiMxc18jbds2UKsJWbYMj65dbWCofRDiRiBwJJIi8zw1a8Col+9rPFCeARXS2a6mVXsUCjk0FXcGkiMdW9zcPA1RB/LmSM20/vo1W8HFbSKp2J7sfAt0GVC3G7QZb9GlkiQRO38+Kb/9BioVIYs/xrN3L9vYaSeEuBEIHIGkq3memtW3RU2jAXL4qa7zfJqq8vjWl8WNo+fdmMqCW4wE7zrWX988hkGIG7tw7VDeOA0FDHvfosaMksHAzfffJ3ntOlAoqLNwIV4DB9rOVjshxI1AYG8OfwNbX74tahr2kz019brZ1y5BYcxJxQ5cMZWdAid+ko+tVf59J/krpqrirK2qjNEIW1+SjztMtaigwJCeTvQLL5K+Zw8AtebPw2fUSBsYaX+EuBEI7El0xG1h06AP9Ps/qNfd3lYJiqMqTAePWCOHKwJbQKiNQg3+jUGlkccwJF8tV5WOoJxErILocHD1hgFvlvmy3Kgorj3+OLmXLqNwdaX2O+/gM3KEDQ21L0JuCwT2QpcNGx6RhU2Le2DGb0LYODqOXg5eYI7UgxWbI1USKjUENpOPq2O/m9xMCPsKIvfLP/PKIjsV/ponH/d5CTyDynRZxsGDRI6fQO6ly7gEBVH/xx+cWtiAEDcCgf34az7cOgceQTByie3eiATWw9FHMFz5GxIuysMt21ZwjlRpVNdOxUYD/DpbDg2tHA5f94fTG+Qp6bZm7weQcQv8m0DXR0o9XZIkElevJurB2RhSUnBr25bQX37GvU0b29tqZ0RYSiCwB//9LfeoABj9aYUm+AoqEd968vfsZMdsYGeeIzUJ3Lxtu1dQXsfjm6dsu4+jsf11OL9FDssplBB9DH6eKQvfHk9A+6kWl2WXifhLcPBL+Xjoe+CiKfF0KTeX2HfeJXndOgC87xlF7bffRunq4P2ZrITw3AgElU1WMmx8XD7u9AA0HWJXcwQW4OoJHoHysaPl3aRch/N/yMfW7EhcHNWxYurQ17c/lIz9Ep45Jfee0vrLfw9bX4LFrWSvbFqsdffe9ioYdXITzyaDSjxVn5RE1IOzZWGjUBD04gvUef/9aiNswAHEzeeff06DBg1wc3OjU6dO7Nu3r9hz//nnH+666y78/f1xd3enefPmLF68uBKtFQiswNaX5QZoNRqUexaMwI6YQ1ORdjWjEEdWyPPGQnvfHpFgS0xhqcT/5BwUZ+fCtttVSgPegNb3gWcg9HtVFjkjPga/hrJXb98iWNIGfnsC4s5ZYe/tcHE7KNUw5N0ST80+f57IcePJPHwYpacndb/8Av8HH0RRzcLedhU369at45lnnmHu3LmEh4fTu3dvhg0bRlRUVJHne3h4MGfOHPbu3cvZs2d57bXXeO211/jf//5XyZYLBOXk9EY4sVZ2Z9/7P9u4rwW2xRHLwfU5cOw7+bgyvDYgJ7NqA2RBdcsKb+COTMwJ+PkB+bl2mF541IFGKydwzzkCE1dB3e5gyIXwH+HzbrBqPFzZW77kY32u7LUB6P5oic0j03buJHLyFHQ3bqCuV4/QdWvx7NPH8j2dALuKm48//pgHH3yQ2bNn06JFC5YsWULdunX54osvijy/Q4cOTJ48mVatWhEaGsq0adMYMmRIid4egcBhSIuF35+Rj3s9K5rzVVUcsRz87GY50dSrNjSvpCoYheL2pHFnDk2l3IDVE+Ty+gZ9YOTi4pP/lSq5ceKD2+DBHXkzvRSy1+W7UfC/vnDyF8uSj8O+hIRLcuHB3S8VeYokScR/8QXX5zyJlJmJtkd3Gvy0DtdGjSx+us6C3cRNbm4uR48eZfDgwQXuHzx4MAcOHCjTGuHh4Rw4cIA+JSjTnJwcUlNTC3wJBJWOJMFvcyArCWq1leP0gqqJI5aDmxKJbTFHqiScvWIqJw3WTIS0GAhsDhO+L/vPt25XmPgjPHlU9qa5uENMBPz6IHzSAf79XF6/JNLj4O8P5OOBbxaZJG7MyiL6+ee5tfQTAGpMm0a9r79G5etb9ufphNhN3MTHx2MwGKhZs2aB+2vWrElsbMmJWCEhIbi6utK5c2eeeOIJZs8u3g373nvv4ePjY/6qW7euVewXCCzi6Aq4tANUrnDv16VWOggcGEcrB489CdcOgtLFNnOkSsLcqdgJxY1BD7/Mkn++HoEw5afyVcf5N4IRi+DZ09BvrhzKS4mSQ00ft4Idb0JqTNHX/jUPctOgTkdoN6XQw7qYGK5OnUbqH1tBrabW/HnUem0uChdRCG33hOI7k5wkSSo18Wnfvn0cOXKEL7/8kiVLlrBmzZpiz3311VdJSUkxf127ds0qdgsEZSbhMmybKx8PfBOCmtvXHkHFyB+WMhrtawvkmyM1CrxqVe7eJnETe6pym9nZGkmCP1+Ww0kubjB53e3fe3nx8Jcb7z17CkYtlXvV5KTA/iVy8vGGxwp6wG4cg/BV8vGw9wuNuMgMD+fK+AlknzmDqkYN6q9YTo0JEypmoxNhN3kXEBCASqUq5KWJi4sr5M25kwYN5Fbfbdq04ebNm7z11ltMnjy5yHNdXV1xrUblbwIHw6CXuxDrMuUqlm6P2dsiQUXxDpGnbRtyIT3WNoMpy0pWMpz8WT621RypkghsLifHZyVC+s3KF1e24uAXeZ2eFbKnNaST9dZWu8setg4z5MnqB5bB1f1wfLX81WgA9HwSdr8LSHIzxjvy85I3bCT2jTeQdDpcmzUj5LPP0IQEW89GJ8BunhuNRkOnTp3YsWNHgft37NhBz549y7yOJEnk5ORY2zyBwDrsXwzXD8tzYMZ8IQYMOgMqF/AJkY/tnXcTsVoWzkEtoX7ZXzethtod/PKSVp2lmd+5LbDt/+TjwW9Dy3sKnWLMyiL+669J+vlnci5dQiqPB0+phGbD4IE/YPYuaDVWFoqX/4IfxsD1Q6D2gIHzzJfIE70/IObVV5F0OrwGDSR09SohbIrAroG55557junTp9O5c2d69OjB//73P6Kionj00UcBOaR048YNvv/+ewA+++wz6tWrR/Pmslv/n3/+4aOPPuLJJ5+023MQCIolOgL2LJSPh38IviLfy2moESqHpZKu2kdUgBwSq4w5UqVRs5U88uHmGWg80D42WIsbx+TRCkjQeRb0mFPkaTfffY/kn38231Z6e+Perh3uHdqjbd8et7ZtUXla0OYhpBOMXwmJV2SvUfgPsmjt8xJ41wbAkJrKjedfICOvOjjg8ccJmPMECvGBqUjsKm4mTpxIQkIC8+fPJyYmhtatW/PHH39Qv74c24yJiSnQ88ZoNPLqq69y5coVXFxcaNSoEQsXLuSRR0qfsSEQVCq6LFj/8O2hmLae8yOoXGrUhyvYtxw8ch8kXgaNl33/vmq2hjMbq37FVHIUrJkki4rGA2HYh0UKxvR/9puFjXvHjmSfOYMxNZWMffvMwgOlEtcmTXDv0B739u3RduiAul690hvp+TWA4R9A31cg/gLU7QZAzpUrXH/8CXKvXEHh5kadhe/hPXSoVZ++s6GQJGfKAiud1NRUfHx8SElJwdvbxrNXBNWXP1+Fg5+DZ0147F8xO8rZ2LdIbrHfbrLcht8e/P4sHFkOHWfAPcvsYwPIYZy1U6BmG3jsH/vZURGyU2D5UHnCeVArmPVnkWXXhvR0/ht1D/qYGGpMmUKtN15H0unIPn+BrPBwsiIiyAoPRxcdXehalZ8f7u3b3/butG6N0t29VNPS/9nPjeeew5iaikvt2tT97FPcWra0ytOualjy/i3qxQQCa/PfHlnYAIz+TAgbZ8Te5eBGg9y4D6DlaPvYYMJUMXXrHBh0ldtnxxoYdPDT/bKw8awFU38qduho3Acfoo+JQR0SQtDzcpdihVqNe+tWuLduBdOnAaC7GScLnTyxk336NIbERNJ37SJ91y55MRcX3Jo3x71DB9zbt0PboQMutWubvTuSJJH0/ffcfP8DMBpx79CBkGWf4BIQYPufiRMgxI1AYE3uHIpZyoA7QRWlhlyxabeE4qiDckdiNx8Ivds+NpjwqSeHxnLT5E66lTHXylpIEmx5Hv7bDWotTFl3O1n8DtL37yf5p58AqP3OOyg9PIpdVl0zCPWQwXgPkZvUGnNzyT59mqyI47KHJzwc/a1bZJ86RfapUyT98AMALkFBeWKnPTkXLpCyYQMAPvfeS6233kSpEf2xyooQNwKBNdn6EqTekAfoiaGYzoup50laDOiyQe1Wufuf+U3+3myE/RtCKpXyGIZrYXLeTVUSN/uX5s3kUsC45VCnfZGnGdLTiXn9dQBqTJmCRzfLRqcoNRq0HTqg7dABHpiJJEnoo6PJDM/n3Tl3Dn1cHGnbtpG2bVvehUpqvvwSNWbMqHaDLyuKEDcCgbU4vRFOrJPLOceKoZhOjdZfLtPVZUDKNQhoUnl7G435QlKFy5TtQpBJ3JyCNuPsbU3ZOL0Rdr4pHw9dKJdlF0PcBx+ijy4YjqoICoUCdXAwPsHB+IyUZ4EZMzPJOnXK7N0xpKUS8MijePbuVeH9qiNC3AgE1qDAUMznoG4Xu5ojsDEKhVwOHndazrupTHFz4yikRcuhoIb9Km/fkjDl3VSViqlrh+XmmgBdH5GnbReDJeGoiqDUavHo2hWPrmKgrjUQBfICQUUpNBTzZXtbJKgMTKGppCuVu++ZjfL3pkMqPxxWHOYBmmfsa0dZSIqUS7712dB0KAx9r9hTKxqOEtgPIW4EgopyZLkYilkdMU0Hr8xeN5IEZzfJx44SkgI55wYg9bos8h2VrCRYNR4y4+UPIvd9C0pVsadbOxwlqDyEuBEIKkLCZdj+mnw88C0xFLM6YY9y8JgIudmcWguNHagSz81HrpoCx/Xe6HNh3XS5OZ53sDzlu4S8uIwDB26HoxYssFk4SmAbhLgRCMpL/qGYDe6GbsXH7QVOiMlzU5nl4GfyvDaNB4JGW3n7lgWT98YR824kSc6Ji9wHGk+55DtvrEFRGNLTiX5N/tBSY8pkPLp3qyRDBdZCiBuBoLz8YxqK6QOjPxdDMasbppybygpLSdLtEnB7N+4rCnNSsQMO0Nz3EUSskisZx6+EWm1KPD3uw4/kcFRwMEHPP185Ngqsing1FgjKQ3Q4/C2GYlZrfPPCMNkplZNnEndGniWlcpWTiR0Nk7iJc7Cw1MlfYFdez6nhH5baWDPjwAGS160DbFsdJbAtQtwIBJaiy4L1j8hDMVuOhrYT7G2RwB5oPMAjSD6ujLwbc0hqALh62X4/S8lfMWU02tcWE1f/hY2Pycc95kCX2SWebkjPEOEoJ0GIG4HAUnbOg/jz8lDMkUuKnBwsqCaYy8Ejbb+XKSTVwoGqpPLj10j2KukyIDnS3tbIyf5rp4AhF5qPhEFvl3pJ3IcfinCUkyDEjUBgCf/tgbAv5OPRn4HWz67mCOxMZZWD37oAt86C0gWaDbXtXuVF5QKBzeRjeycV63Ng9QTISoQ6HeUWDaXkxIlwlHMhxI1AUFbyD8XsPEsMxRRUXjn42TyvTcO+4F7DtntVBEdp5nd2szzE0yMIJq8ttbJMhKOcDyFuBIKyIoZiCu6kssrBTfk2d4SkjLm5SAaDbfe2BEepmDr2vfy98wPgVbPU00U4yvkQ4kYgKAunNxQciqkRLmsBlVMOnngFYk+AQiXnjuSR898VLnTpSuwCBxLajtDrJvEKXPkbUED7qaWeXjAcJZr1OQtC3AgEpZEWC78/Kx/3fl4MxRTcxhSWSo6yXYWQadxC6F3g4W++O333bqScHFJ/24Sk09lmb0sxhaUS/4PcDPvYEP6D/L1Rv9visxgM6RnEvCbPjvKdPAmP7t1tbZ2gkhDiRiAoCUmCTU/KfUxqt7PJUExjbi65kZFWX1dQCXgHy0m+hlxIi7HNHsWEpLLPyHktxsxMsk87SFdgzyDwCAQkuHWu8vc36CF8lXzc8f5ST4/76EN00dGog4Op+cILNjZOUJkIcSMQlET4j3BxO6g0MPYrUKmtvkXs/PlcHjqMjAMHrL62wMaoXMAnRD62Rd5NynW4cQRQQItRBR7KL2gyDoZZf+/yYs67sYPgurQD0mNB6w/Nhpd4asa//5K8VoSjnBUhbgSC4ki+Bn++Kh/3mwtBLay+hSE9ndRNmwFI27Xb6usLKgFbloOflf82qNcdvGqZ7zakpxfw9mWEHbT+3uUlyI7ixpRI3G4yuGiKPc2QnkHMXLk6SoSjnBMhbgSCopAk2DQHctMgpCv0fNIm26Tt3ImUmwtAVni4TfYQ2BhbloObQlJ3zJIyhaQUrq4AZB0Lx5j3d2R37OW5SY2BC9vk41JCUiIc5fwIcSMQFMWRb+WGfS7uMOYLUKpssk3q71vMx9nnzmHMsFMSpqD82KocPO0mRP0rHxcKScnixqNXL1QBAUg5OWRFRFh3//KSX9xIUuXtG7EKJAPU6wGBTYs9TYSjqgdC3AgEd5J4Bba/IR8PfBMCGttkG31CAhn/ym9eSg8PMBjIOumAE5UFJWOrcvBzmwEJgjvfzuvJw5Rv4966FR7d5IZzmY6SdxPYXG6ZkJUoVxpWBkbj7SqpjjOKPU2Eo6oPQtwIBPkxGuG3J+T5OPV7QddHbLZV6p9/gsGAW+vWePa5G4CsCBGaqnLYynNjmiXVsvAsKVNYyq1VK7R53XQzwhxE3KjdwD/vA0FlhaYi98k/f1fvQiG8/JjDUXXqEPS8CEc5M0LcCAT5CfsSru4HtQeM/rTUeTQVwRSS8h45Avf2HQDIPHbMZvsJbIRvqPw9LQZ02dZZMyMeIvfLx3eUgBvSM8i9cgUAt5Ytzd6HrOPHMWZmWmf/ilLZnYqPfSd/bzO+2AabBcJR776DylOEo5wZIW4EAhPxF+GvefLx4LfBr4HNtsq9fkNOIFYo8B42HPeOHQHIijiOZKtmcALboPUDjad8nBxlnTXPbZHzR2q1LfR3mHPuLEgSLjVr4hIQgDokBHWdOqDXk3nUQcSxSdzEVcKMqczE21VlxYSkRDiq+iHEjUAAYDTAxsdAnw0N+8mDMW1I6h9/AKDt2hV1zSDcmjVF4e6OMTWV3P/+s+neAiujUFi/HNzUlbiokFRevo1bq1Z52yvQmvJuHKUk3DxAsxLCUifWyU0Ua7WFOu2LPCVu0UciHFXNEOJGIAA48AlcPyzH7Ed/Kr9h2ZDULXkhqRFyozGFWo17mzaACE3lRzIYyLl82fG9WeZy8MiKr5WVBP/9LR+3HFP4YbO4aWm+z8Ocd3Oo4vtbA5Pn5tZ50NuwRF2Sbve2KcZrk3HwIMlr1gIiHFWdsFjchIaGMn/+fKKirOR+FQjszc0zsPtd+Xjoe4UqU6xN9oUL5Jw/D2o13oMHm+937yjn3WSFR9h0/6qAZDSS+uc2rowZw38jRpLw7bf2NqlkrJlUfP5PMOogsAUENCn0cP5kYhMmz0326dMYUlMrbkNF8akrf1Aw6iDhou32uX5EDn25uMv5NndgSM8g5v/mAuA7aaIIR1UjLBY3zz//PL/99hsNGzZk0KBBrF27lpycHFvYJhDYHoMONj4qu7WbDi3TFOGKkrpFDkl59u6NytfXfL+2g0ncVN+KKUmSSNu5kytj7+XGM8+Qc/ESICfLOjTWLAcvISRlzMwk9z85mdg9n7hR16qFJjQUjEYyjxypuA0VRaGAINOEcBvm3ZgSiVuNAXffQg8XCEe98KLt7BA4HBaLmyeffJKjR49y9OhRWrZsyVNPPUXt2rWZM2cOx4Q7XVDV2PcxxBwHN18YtdTm4ShJkgqFpEy4t2sHQG5kJPqkJJva4WhIkkTa7t1cue8+rs95kpzz51F6euKV59nSXbVB919rYi3PTU4aXPpLPi6ipDn73DkwGnEJCsIlMLDAY+aS8IOOkndj44qpnDQ4tV4+LiIkVSAc9c4CEY6qZpQ756Zdu3YsXbqUGzdu8Oabb/LNN9/QpUsX2rVrx/Lly5EqszOlQFAeYo7D3g/k4+EfFZjdYyuyjx9Hd/06Cq0Wr379Cjym8vVF07gRUH28N5Ikkb5vH5ETJnL9scfJOXMWpVaL/6OP0HjnDoJelJM/c6OuOXbeTf4RDBV57buwDQw54NfotucjH9mn8vJtWhZ+zBRycZhmfrYew3DqV7kflX8TuStxPvRJSQXDUT16FLWCwIlxKe+FOp2ODRs2sGLFCnbs2EH37t158MEHiY6OZu7cuezcuZPVq1db01aBwHroc2DDY2DUy63t24yrlG1T8kJSXv37o9RqCz2u7dCB3EuXyQoPx6t//0qxyR5IkkTGgQPEL/vUPDZA4e6O37Sp+M2ahUuNGgAoPT3BxQUpJwf9zZuoa9e2o9Ul4FtP/p6TKicEa/3Kt87ZfLOkivAi3lkplR9t166yCRcuoE9IwMXfv3w2WAtbi5v8icT5flbGnByuPzFHDkeFhIhwVDXFYnFz7NgxVqxYwZo1a1CpVEyfPp3FixfTvHlz8zmDBw/m7rvvtqqhAoFV+ft9iDsNWn8Ysdjm4SgASa8ndetWQG7cVxTu7TuQ/PMvZDqx5ybjYBi3li0j6+hRQB7+WGPKFPxnP1joDVnh4oImOJjcq1fJvRrluOJGowXPmpB+U867KY+4yc2Eizvk4yLybQCyzxQvblz8/HBt1oyc8+fJPHQI72HDLLfBmgS1kL+nRcu9aMor+Ioi9hTcOApKF3kCeB6S0UjMq6+SdewYSi8v6n7xuQhHVVMsDkt16dKFixcv8sUXX3D9+nU++uijAsIGoGXLlkyaNMlqRgoEVuX6UfhnsXw8cjF4BpZ8vpXIPHQIQ3w8Kh8fPHv2LPIcU8VU9slT5mnhzkLmkSNcvX8mUTNnknX0KAqNhhozptNox3ZqvvxSsZ4Gdagc8smNcvC8m4qWg1/aCbpM2QtUu32hh41ZWeRclnsgFSVuALTdZO+NQ4xicPO57dGydjM/0xypZsML/P/eWryY1D+2glpNyLJPcG1SuNpMUD2w2HPz33//Ub9+/RLP8fDwYMWKFeU2SiCwGbosuTpKMkLrcSXOobE2KXnjFryGDkWh0RR5jiY0FJWvL4bkZLLPnjUnGVdlMsPDiV/2KRkHDgByTx/f8ePxf+Rh1DVrlnq9pl59MoDcqpBUfP2QnHdTHkyzpFrcU3RIKi+ZWBUYgLpmUJFLeHTvTtL3PzhQ3k1ruWvzzdMQ2ss6a+qy4bicKEzH+813J61dR8LX3wBQ++35ouy7mmOx5yYuLo6wIj4VhIWFccQRShAFgpLYtQDiL8ghhOEfVtq2xpwc0nbIIQefYkJSIHebdc8rCa/qoamskyeJevhhrk6eIgsbtRrfiRNptO1Par3xepmEDYAm78OUztF7a1WkHFyfIycTQ7GCO/t0Xn+bIpKJTWg7dwalktzISHSxlTSRuyTM5eBWrJg6uxmyk+VeOo3kpPz0vXuJffttAALmzMF3zBjr7Seoklgsbp544gmuXbtW6P4bN27wxBNPWMUogcAmXP0X/v1MPh71iXVzAEohfe9ejGlpuNSqhXunTiWea27md6xqipus06e59uhjRI6fQMbefaBS4Tt+HI22bqX2vLfkOUgWoKkvhzZyI6uA5wbKF5a6vBty08CrDgR3LvIUUzKxezEhKQCVt7c5ZJXpCKEpWyQVm3rbdJgGShXZZ85w/ZlnwWDAZ8wYAp543Hp7CaosFoelzpw5Q8e8IX/56dChA2fOVMKQNIGgPORmyLOjkORGfc2GVur25gngw4ejKGXSuNbsuTmGJEkoKiHZ2RpknzvHrU8/JX1nXp8WpRKfe+4h4PHH0NSrV+51TZ6b3GtyOXhpPz+7kb8c3FLMIalRxU6iL6lSKj8e3buRffIkGQfD8BldeWHXIjHNmIo7C0Zjsc+tzCRchsh9gALaT0UXE8O1Rx9DysxE2707tefPqzL/LwLbYvFfmqurKzdv3ix0f0xMDC4u5a4sFwhsy863IOkKeAfLIxYqEUN6Oul79gCFG/cVhVvr1qBWY7gVj+5GtI2tqzg5ly5x/elnuDJmrCxsFAq8R42i4ZbfqbPwvQoJG0D29Li4IGVno4+Ls5LVNsAcloqSB7GWFX0unJfFb3EhKWN2NjmXLwOlixttNznXJCPsoP37jfk1BBc3OVE66UrF1zMlEjcegEHly7WHH0EfF4drk8aEfLK02Fw2QfXDYnEzaNAgXn31VVJSUsz3JScn83//938MGjTIqsYJBFbhv7/h0P/k43uWyVUclUjazp1IOTloGjQoMV/ChNLNDbeWchltVrhjd/3OjYriyvgJpG3bJoua4cNo+Ptmgj/8ANcGDayyh8LFBXWwHMrKverAeTfewXJpslEHaTFlvy5yL2SngEcg1Cs6CTbn/HkwGFD5++NSSq6StmMHUKvRR8egKyKFoFJRuUBgM/m4oqEpgw4i5N5pUttp3Hj6GXIuXkQVGEDdL79E5e1dQWMFzoTF4mbRokVcu3aN+vXr069fP/r160eDBg2IjY1l0aJFtrBRICg/2anw2xz5uNMD0HhApZtgmiXlPXJEmV3m2vZVY85U6p/bkLKycG3WjAYbNxL88ce4Nmpk9X3MoSlHLgdXquQkV7As7+ZMXuO+5iPlNYrAPAm8ZctS/4aUWi3ubdsCDjKKwRSaqqi4ubgd0m8iaQOJWXOIjAMHUGi11P3yS9TBwRW3U+BUWCxugoODOXHiBB988AEtW7akU6dOLF26lJMnT1K3bl1b2CgQlJ/tr0FKlJwPMfjtSt9en5hoLoH2GVF8ldSd3K6YirCFWVYjfe/fAPhOnIBbs6Y220dTL69iqiqUg0PZ824Mejj3u3xcQluC2/k2pXv+ADzypoRnhh0qmx22xJRUHFdBcZPXkTjhZntSNmwEpZLgjxeVmGAtqL6UK0nGw8ODhx9+2Nq2CATW5eLO25UVYz4HV69KNyH1zz/BYMCtdWt5anMZMYmbnPPnMaRnOGSXVUNKCll54svTxh3JzZ4bRw5LgeXl4FEHIDMB3GuU2AfGXAZexjdybfdu8PnnZISF2T8p3RoVUyk34OJ2UiLduXVQXqfW66/h1bdvxe0TOCXlzgA+c+YMUVFR5N7RRfWee4puGy4QVCpZybDpSfm422PWayBmIeYqKQu8NgDqmkGog4PR3bhB9onjeBTT0dieZBw4AAYDmkaN0ISE2HQvczl4lfHcRJbtfHNIagSo1EWeYszJIefSJaDkMvD8uLdvj8LVFUN8PLmXL+PauHHZ7LEFQXk2J16BnHRw9bR8jYjVZMS6EH1Injnm9+AsakyeXMpFgupMuToUjx07lpMnT6JQKMzZ+KZPBgaDBVUCAoGt+PMVeaaNXyMY8IZdTNDduEHWsWPmRFtLce/QAd2NG2SGhzukuEn/ey9ge68N5M+5ibK/J6IkLCkHNxrlhnQALYoPSeVcuAB6PaoaNXAp42wtpUaDtlNHMg78S8bBMPuKG89A8AiCjDi4dQ5Ciu7jUyxGIzm7vuP6P35glDt8Bz3/vG1sFTgNFufcPP300zRo0ICbN2+i1Wo5ffo0e/fupXPnzuzJK3cVCOzKuT/g+BpQKGHsl/JQQzuQ8oecSKzt2rXM3Xjz496hPYA59ONISEYj6fv2AeDZx/biRl2nDqhUVaAcPFT+XhbPzfVDkB4Lrt7QsE+xp+Xvb2OJqDOVhGeGOUJScflDU/qjm7i2OQejTol7+3bUWfie4/Y6EjgMFv+F/Pvvv8yfP5/AwECUSiVKpZJevXrx3nvv8dRTT9nCRoGg7GQmwuan5eOeT0LdrnYz5XZIqvTeNkWhzWuWmRURgeRgHtHs02cwJCSg1GrNdtoShVptrohx6NCUSdykx8pzzErC1Liv2TBwcS32tOx8lVKW4NFdTirOOHTY/n8/5RQ3xsxMrr2yAF2mC+oALSFffIHSzc0GBgqcDYvFjcFgwNNTjpkGBAQQHS03Gatfvz7nz5+3rnUCgaVseV52fwc2h77/Zzczci5elHuTqNV4Dx5crjVcmzRBqdViTE8n59JlK1tYMUxVUh539ay0xmlVYsaUew3Q5CWuJ5dgpyTlC0mVnKeYVcbOxHfi1qoVSg8PjCkp8tBNe1IOcSMZDNx49mmyb2Sg0hiot/hdXGrUsJGBAmfDYnHTunVrTpw4AUC3bt344IMP2L9/P/Pnz6dhw4ZWN1AgKDOn1sPp9aBQyeEotf0+4aVskb02nr16ofL1LdcaChcX3NrJ/Uocrd9N+l4538ajEvJtTJg6HTu050ahKFs5ePQxSLkGao8Sey8Zc3PJuSgnE1sqbhQuLvIgTRygJNwsbk7Jwq4UJEni5nsLSf/7HxRKiZCxAWi6DLGxkQJnwmJx89prr2E0GgFYsGABV69epXfv3vzxxx988sknVjdQICgT6XGy1wag9/NQp4PdTJEkqUDjvoqg7ZAXmnKgTsX6xESyT5wEKieZ2ESVKwcvKe/GFJJqOhjU7sWelnP+Auh0qHx8zF2aLUHb/fYoBrsS0Ez+0JGdXKbuzUnff0/Sjz8CUKd7EtqRD9rYQIGzYXG11JAht9Vzw4YNOXPmDImJidSoUcNxKxgEzo0kwe/PQlYi1GoDd79oV3OyT5xAd+0aCnd3vPr1q9BajtjML+Off0CScG3evFyJ0uWlypWDF9frRpJul4CX0LgPIPvM7f425Xl9NeXdZB0+gqTToVAXXW5uc9RuENBErpa6eRq8ixdqqdu3c3Ph+wAEtUvBu5ES2oyvLEsFToJFnhu9Xo+LiwunTp0qcL+fn58QNgL7cXGH3OVVqYYxX4KLfYfnmUJSXgMGoNRWrFLLvX07UCjQRUWhj4+3hnkVJn1vXpVUJXptoHA5uMPiW4rnJvakPETSxQ0alzyPz9LOxHfi2qwZKh8fjJmZZN3xul3p5A9NFUPW8eNEv/gSSBK+3YPxa54BrcaCm5gbJbAMi8SNi4sL9evXF71sBI6D0Qh/zZOPuz8KtVrb1RzJYCD1j61AxUNSACovL1ybNAEg0wHybiSDgYxKLAHPj7kcPCsLfdytSt3bIkrLuTmb57VpPLDUhnbZ5UwmNqFQKtGaRzGElWsNqxGUJ9CKSSrOjYri2mOPI+Xk4Nn7Lmo1Oo1CAXScUXk2CpyGcuXcvPrqqyQmJtrCHoHAMk79In8SdPWBXs/Z2xoyw8IwxMej8vHB00qN90yhKUfod5N14gSGlBSU3t64t2tXqXsrNBpZ4AA6Rx6gmX8EQ1EepjKGpKTcXLmBH+UXN5A3igHIOGhncWMeoHmm0EOG5GSuPfwIhsRE3Fq2JPj+zigMmXKuTt1ulWyowBmwOOfmk08+4dKlS9SpU4f69evj4VFw5s2xY46T+ChwcvS5sGuBfNzradD62dce8oWkhg61Wom0e4f2JK9b5xAVU6YqKc9ed6FwKff0lnKjqV8f3bVr5EZFoe3SpdL3LxO+cm4QOamQlVTw7zLuHMSfl0OoTUuu/sm+eBFJp0Pp44O6AuMtPPKSirOOHcOYk4PStfieOjbFFJaKPy//7+aFj405OVybM4fcyEhcatcm5MsvUG6cIJ/bcYZcgSYQWIjFr05jxoyxgRkCQTk4ulL+dOxZE7o9am9rMObmkrZ9B1D+xn1FYWqSl33qlH3fnICMvyu/BDw/mnr1yAByIx3Yc6N2B89aciO/pMiC4sYUkmrUH9x8SlzmdvO+FhXKadQ0aIAqMADDrXiywiPMScaVjk+I7GHNSYH4C1CrNZLRSMyr/0fWkaMoPT2p+9WXqA2xEB0uC8B2k+xjq6DKY7G4efPNN21hh0BgGTnpsPcD+bjPy6Cx/9TsjL17Maal4VKzprm/iDVQ162Lyt8fQ0IC2afPoO1onzJ3XVycuXrHs3dvu9igCb2dVOzQ1Kh/W9wE5+vgbCoBb1n6gGHTz7qswzKLQ6FQ4NGtO6m//07moTD7iRuFAmq2hKh/5bybWq25tWQpqX/8AS4uhCz7BLemTeGPvGrH5iPAI8A+tgqqPGJAh6Bq8u9nkHEL/Bo6TMJhSr4J4NacfaNQKPLNmbJfaCpj3z8AuLVpg4u/v11sUFeFRn5QdDl4wmU5P0yhgmale/ayT+eVgVs4dqEoPBwm7yZPqMWdJvmXX0j43/8AqP3223j06CGPrDixTj7HQf6vBVUTi1+BlUolKpWq2C+BwOZkxMOBvIaR/V8DlZ16d+TDkJ5B+u7dgHVDUia0pqTiCPuJG3O+jZ1CUgCaelWtHDyfuDF5bRrcXWp+mKTTyeM7qFgysQlTM7+sEycwZmRUeL1ykyduDJEnuPneQgACHn8c37Fj5MfPbILsFPCpBw0r1iNKUL2xOCy1YcOGArd1Oh3h4eF89913zJs3z2qGCQTFsm8R5KZD7XbQcqy9rQEg/a+dSDk5aBo0sMon7Ttxz+tUnHksHEmSKr2vlKTTkbF/P1D5JeD50YQEg1KJlJmJ/tYt1EFBdrOlRIqaDm7KtylDSCrn0iWk3FyUXl5mb1VF0ISEoA4ORnfjBpnHjtktrGiqmErccw5jhgLXJk0ImPPE7cePfS9/7zgdxORvQQWwWNyMHl24fHHcuHG0atWKdevW8eCDok22wIYkR8Hhb+TjgW85zAtggZCUDYSHW6uWKNRqDAkJ6K5dM89Zqiwyw8Mxpqej8vPDrbX9egmZysF116+ji4pyYHGTrxwc5L/b6HBQKKH5yFIvzz8J3Fp/T9ru3Uj5dT0ZBw/aT9wEtcCgU5B4UgIUBDz26O0QbvwluPqP/DNqP8U+9gmcBqu9M3Tr1o2dO3daazmBoGh2vwuGXNm17yBua31iIhkHDgC2CUkBKF1dzeEJe+TdZJhCUr17WTWfqDxUiRlTprBU8jUwGm73tqnXEzxLF2T5xy5YC1NJeKY9825cvUi6HowxV4kmpCZe+cb5EJ7ntWk8UK6sEggqgFVepbKysli2bBkhFejFIBCUys0zcHytfDzwLYfpf5H6559gMODWujWuDRrYbB/3jrdDU5VNup1LwPNTJWZMedeRS5mNOkiNzheSKrlxn4msfJ4ba6HtKicVZ585gyElxWrrWoIxM5PEk/Lbjv+wdihMeZoGHUSslo873m8X2wTOhcVhqTsHZEqSRFpaGlqtlh/zprgKBDbhr/mAJL9BBHeytzVmzBPAR1R83EJJ2KtiShcdTc7Fi6BU4nnXXZW6d1HknzHlsChV4FsXEv+DqINwLc9b0qL0kJSk15NzzpRMbD1xo64ZhKZBA3KvXCHzyBG8Bgyw2tplJemnnzBk6lF76PFpoLv9wIU/5epHj6BSmxsKBGXBYnGzePHiAuJGqVQSGBhIt27dqFGjhlWNEwjMXP0XLmyVy2j7v25va8zooqPJOnoUFAq8hw+z6V6miqmcixcxpKWh8vKy6X4mTIMy3du3R+XrWyl7lkSVKgdP/A/+XSbfDula4jRsEzmXLyPl5KD08DALOWuh7d6N3CtXyDgYVunixpiTQ+K3ywHwb5mOIv7s7QdNicTtpzhE9aOg6mOxuJk5c6YNzBAISkCSYOdb8nGHaRDQxK7m5Cf1D9lro+3SBXXNmjbdyyUgAHW9euiiosiKOI5n71423c+EI5SA58f0hq+7etUulWNlxpR3E3Nc/l7GkFT2qXzJxFbOb/Lo1p3kNWvJPHjQquuWheRff0V/6xYuQQH4hkbDrXNyPlJaDFzKy9cUvW0EVsLi/5wVK1bw888/F7r/559/5rvvvrOKUQJBAS5sg2sHwcUN+r5ib2sKYK6SssIE8LKgreTQlDE3l4x//wXsWwKeH3VICCiVGDMzMcTH29uc4jGVg5toMapMl1V0EnhJaLt1BWTvn74Sf3ZSbi4JX8tVjv4PP4LC1Q10mXKpfPgqkIwQ2hv8G1WaTQLnxmJxs3DhQgICCrfEDgoK4t1337XYgM8//5wGDRrg5uZGp06d2LdvX7Hnrl+/nkGDBhEYGIi3tzc9evRg27ZtFu8pqEIYDfBXXv+kbo+Uya1fWeRcukTOuXOgVuM9eHCl7Oleyc38Mg8fRsrKwiUwENfmzStlz9JQajSoa9cGHDzvpka+kFKdDgVvl4AtKqVMuNSoYf49Zh46ZPX1iyP5t9/Qx8SgCgzAd/x4CGohPxBzHMJ/kI+F10ZgRSwWN1evXqVBERUh9evXJ8rCF5p169bxzDPPMHfuXMLDw+nduzfDhg0rdp29e/cyaNAg/vjjD44ePUq/fv0YNWoU4Q4wLVlgI07+DHFn5CGDvZ61tzUFME0A9+zVq9JyUUzN/LIijiPp9Tbfz1QC7tHnbocK/1SJcvD8npsWpTfuAzmZOPvcOcC6ycT58ehWuaMYJL2ehP99DYD/rAflwa9BecLt4OeQck3+/y6jZ0sgKAsWi5ugoCBOnDhR6P7jx4/jb+G8mY8//pgHH3yQ2bNn06JFC5YsWULdunX54osvijx/yZIlvPTSS3Tp0oUmTZrw7rvv0qRJEzZv3mzp0xBUBfQ5sOsd+bjXs+DuOAnrkiSRWskhKQDXxo1QenpizMyUK5hsjKkE3FHybUyoq0I5eI1QIE8QljHfJue//5Cys1FqtWhCQ21iltY0ZyqscvJuUrdsQXftGqoaNagxcYJ8p2nG1PXD8ve2E+Vp6gKBlbBY3EyaNImnnnqK3bt3YzAYMBgM7Nq1i6effppJk8o+nj43N5ejR48y+A53/uDBgzmQ1xCtNIxGI2lpafj5FT+nJScnh9TU1AJfgirCkeWQEgVetaHrI/a2pgDZJ0+iu3YNhbs7Xv0qr5mgQqXCvV07QO4abEtyr14lNzISXFzw6NnTpntZyu1ycAcWN+41YNQSGLm4zLkkpmGZri1b2KxZorZLF1Cp0F2NQhcTY5M9TEgGA/FffgWA3wMPoNRq5Qdq3hFyE71tBFbG4v+eBQsW0K1bNwYMGIC7uzvu7u4MHjyY/v37W5RzEx8fj8FgoOYdFSY1a9YkNja2TGssWrSIjIwMJkyYUOw57733Hj4+PuavunXrltlGgR3JSYO9H8rHfV4Gjda+9txByu+/A+A1YMDtF+xKwr1jXt6NjZv5mUrAtZ06ofL0tOlelmIeoOnInhuATjOh86wyn25KJna3Qb6NCZWnpzmfJyPMtqGptO3byb1yBaWPDzWmTL79QH5xU6cj1LLfSA+Bc2KxuNFoNKxbt47z58+zatUq1q9fz+XLl1m+fDkajcZiA+6M45e1tHPNmjW89dZbrFu3jqAS5su8+uqrpKSkmL+uXbtmsY0CO3DgU8hMAP/G0GG6va0pgGQwkLp1K2C7cQslYZ4QbmPPjaOVgOfH1KVYd9XBp4NbiC0rpfJjyrux5SgGyWgk/osvAfCbPr2gQPYIAM9a8rFIJBbYAIv73Jho0qQJTZqUv99IQEAAKpWqkJcmLi6ukDfnTkwDOn/++WcGDhxY4rmurq64urqW206BHUi/Bf9+Kh/3fw1U5f4ztQmZhw5huBWPysfHLh173dq2A6US3Y0b6G7Goa5p/eGRxqwsMvM+1TtKCXh+1HXrgkKBMSMDQ0ICLkVUcFY1JIPhdjKxDSbL50fbvRsJX39NRliYzXoFpe/aRc6FCyg9PPCbPq3wCUPfg6sHoN3kwo8JBBXEYs/NuHHjWLhwYaH7P/zwQ8aPH1/mdTQaDZ06dWLHjh0F7t+xYwc9S4jvr1mzhpkzZ7J69WpG2LjdvcBO7PsIctPl8tmWY+xtTSFMVVJeQ4eiKIe3sqKoPD1wbdYMgKyICJvskREWhpSbi7pOHTSNHK/3SJUpB7eA3CtXkLKyUGi1aGw4owxA27EjqNXoY2LQ2eDnJ0mS2WtTY+pUVD4+hU9qfS+M+AjUblbfXyCwWNz8/fffRYqKoUOHsjfPjV1WnnvuOb755huWL1/O2bNnefbZZ4mKiuLRRx8F5JDSjBm3XZZr1qxhxowZLFq0iO7duxMbG0tsbCwpdhoCJ7ABSZFw+Fv52IGGY5ow5uaStm07YJ+QlAlzM79jx2yyvqOWgOdHE1oFysEtwBySat789kBJG6F0d0ebl5hui5LwjH37yD59GoW7O34zRbKwoPKxWNykp6cXmVujVqstrkSaOHEiS5YsYf78+bRv3569e/fyxx9/UD+vEiImJqZAz5uvvvoKvV7PE088Qe3atc1fTz/9tKVPQ+Co7H5XnqTcsK/85WBk7N2LMS0Nl5o10XbubDc7TM38Mm3QzE+SJIctAc/P7RlTkeVeIyVTR3hUkpUsqhhZlZRvY0LbvTsAmVYuCZckifjP5XYeNSZNwqWEalaBwFZYLG5at27NunXrCt2/du1aWpYjTvz4448TGRlJTk4OR48e5e58L6YrV65kz5495tt79uxBkqRCXytXrrR4X4EDEnsKTvwkHw98y66mFIcpJOU9fLjNSnXLgkncZJ85izE726pr5/73H7obN1BoNObEU0dEUz8UoNxhlQs30xi6dC9jPz9A2H8JVrSsfJjKwG3VvO9OPMz9bg5ZNSk7MyyMrIgIFBoNfg/MtNq6AoElWJyp+frrr3Pfffdx+fJl+vfvD8Bff/3F6tWr+eWXX6xuoKAa8dd8QIJWY+V8GwfDkJ5B+q7dQOU27isKdXAwLoGB6G/dIvvUKat6kUxeG23XrpVe5m4Jpoqp3EjLy8GPRCYya+VhUrPlLs97LtyiW0PLmpBaE8loJPusPCXblmXg+XFr2xaFmxuGhARyL13CtQIFIvkxeW18x49HXUIlq0BgSyz+6HnPPfewceNGLl26xOOPP87zzz/PjRs32LVrF6E26qgpqAZcPQAXt4FCBf1es7c1RZK+6y+knBw0DRrYvJqlNBQKxe3QlJVLwh25BDw/GlNYKsqycvDtp2OZ+k0Yqdl6fLVqAA5fSbSJjWUlNzISKTMThZubzZOJTSg1GjmxGOvl3WQePSrPrFKr8Z/9oFXWFAjKQ7n86iNGjGD//v1kZGRw6dIl7r33Xp555hk6depkbfsE1QFJgh1vyscdZ0BAY/vaUwymxn3eI0Y4RJKteYhmeITV1jSkp5N59CjgmCXg+TGXg6enY0gsmzhZcyiKR388So7eyIDmQax9WM47OX49mWydwZbmlkiBZGKXymt9YMq7sdYoBlOFlO+YMeZqNoHAHpQ7aWDXrl1MmzaNOnXq8OmnnzJ8+HCOHDliTdsE1YXzW+H6IXBxl7sROyD6xEQy9stjQexZJZUfbcfbzfyslTOR8e+/oNOhqV/fPOLAUVG6uuJSW24EV1rFlCRJLN15kVfXn8QowYTOIXw1vRPNanoR5OWKziARcS25EqwumuxTlZtMbMKUd5N56DCSoWLiLuvECTL++QdUKvwffsga5gmqKDqD0a4fFsBCcXP9+nUWLFhAw4YNmTx5MjVq1ECn0/Hrr7+yYMECOnRwvDwJgYNjNOTl2gDdHwVvx/y0l7ZtGxgMuLVqhWslhQ1Kw61FCxQaDYakJHkGlBXIXwJeFSjLjCmDUeK1jadYvPMCAE/2b8z797XFRaVEoVDQpYFczXPIjqGpyupMfCduLVvKg1hTU8k+e65Ca5m8Nj6jRqERY26qLdHJWUz86l/mbT5jVzvKLG6GDx9Oy5YtOXPmDMuWLSM6Opply5bZ0jZBdeD4Wrh1Ftx84a5n7G1NsaSYJ4CPtLMlt1FoNLi1aQNYJzRVsAS8T4XXqwxKmzGVrTPw+KqjrAqLQqGA+aNb8fzgZgXCit3yxM3hSPuIm/zJxJUtbhQuLvIgTSpWEp599izpu3eDQoH/ww9byzxBFWP3uTiGf7KPY1HJ/H4imtgU61ZyWkKZxc327duZPXs28+bNY8SIEahs3GRKUA3QZcOe9+Tj3s+Bu69dzbkTQ3o62efPk7JlC1lHj4JCgffwYfY2qwC3Q1MVb+aXc/48+rg4FO7uaLvYr4ePJZg8N7oiwlIpWTpmfHuIbadvolEp+WxKR2b0CC10XpdQWdwcvZqE3mC0qb1FkXv1KsaMDBSurrg2aljp+5tLwiuQVGya/O09bBiuDR3DsymoPPQGI+//eY4HVh4mOVNHm2AftjzZm1o+9us+XebMtX379rF8+XI6d+5M8+bNmT59OhMnTrSlbQJn58i3kHINvOpA18r/tGdIz5DnMxX4uk7ujRvobkRjvKPztbZzZ9SlzD2rbKxZMWXy2nh0746yisxjM5eD3+G5iU3J5v7lhzh/Mw0vVxf+N6MzPRoVXerdrKYX3m4upGbrOR2dSru6vrY2uwCm/jauzZtVajKxCXMzv6NHkXQ6FGq1RdfnXLpE2na5a7f/o49Y3T6BYxObks1Ta8I5lOf5vL9Hff5vRAtcXezrACnzf1KPHj3o0aMHS5cuZe3atSxfvpznnnsOo9HIjh07qFu3Ll5eXra0VVCFiZ3/Nqlbt6L09ETl5YXSU4vqZhhKlQ+q5l1RfbMSpZc3Km8vlF5eqLy9UXl7o/T2RuXlhcLd3eIKJWNmJrobN/LEyg101wsKGUNycqlrqHx9UYeEoK4bQoADutvd27cHIPfSZQwpKUXP8Ckj5hLwKpJvA4XLwRUKBZfi0rl/+SFuJGcR5OXKyge60rKOd7FrKJUKuoT68de5OA5HJtpB3Mj5NpXV3+ZOXJs0QeXriyE5mayTp8zewLIS/9X/QJLwGjQQt6ZNbWSlwBHZe+EWz6yLIDEjF09XF96/ry0j2jpG3qTFHxO0Wi2zZs1i1qxZnD9/nm+//ZaFCxfyyiuvMGjQIDZt2mQLOwVVmNxr10havRoAQ1ISOvMjKsAD/jsEHCp5ERcXWRR5e6EyiSBvn3z3eWFIS0N3I/q2eClDebDKxwd1cPDtr5AQ1MF15OM6wag8PSrwzG2Pi58fmtBQciMjyYqIwLNP+XJlDCkpZOV5fzx797amiTZFXa+eXA6eloYhKYkT6Qpm5bnGGwZ48N2srtT1K70RYdcGsrgJu5LI7N6VGxqyVzKxCYVSibZbN9K2bSMz7KBF4iY3MpLUvK7d/nkzAQXOj8EosWTnBT7dfQlJgpa1vfl8akdCAxzn9bJCPtBmzZrxwQcf8N5777F582aWL19uLbsETkTKxt8AOawT+NxzGOOuYfjlSQxZuRibTcDgFoIxLRVDapr5uyEtFWNqGobUVDAYQK/HkJR0hzgqHaW3N+rgYDQhsliRBcxtMaPy9LTNk65E3Dt0IDcykszw8HKLm4z9+8FoxLVJY9TBwVa20HYoXV1xqVULfUwM/+6N4KGjOWTrjLSr68uKmV3w8yjb1HZTxdSRyESMRgmlsnL6GElGI9lnTGMX7CNuQM67Sdu2jYyDYQQ89liZr4v/+mswGvHs08dunidB5RKXms1Ta8M5+J/84XFqt3q8PrIlbmrHysO1SoBXpVIxZswYxowZY43lBE6EZDSSsnEjAL4TJ8qfCresgpBkCO4Es5eUOPlbkiSkzEwMabLQMRb4nk8Mpaag1HrIIiYkJM/zUgeVd/HhCGfBvUN7UjZsqFDFlDnfxsG7EheFpn599DExfP/zP2TX7UTfZoF8PrUjWk3ZX95a1/HBTa0kKVPHpVvpNK1ZOSF2XVQUxvR0FBoNro0aVcqeRaHtJufdZIWHY8zORulWeiJo7vUbpPwme+oDHhNem+rA/kvxPL02gvj0HDw0Kt69tw2j2zvmh6HKz14TVCsyDx1Gd+MGSk9PvAYOgMQrcHSF/ODAt0oUNiCPGVB4eKD08EBdq5btDa6CmFroZ504gaTXW5yUKhmNpO/bB1SdEnATkiRx0cWHYKBW+i3u6xjCwvvaoFZZ1p9U46KkY70aHLicwKEriZUmbkxeG9dmzSxO5LUmmgahuAQFoY+LIysiAo+8JOOSSPjma9Dr8ejZw5z7JXBODEaJZbsusvSvi0gSNK/lxWdTO9Io0HE93/YbayyoFqRs2ADIU7SV7u6w+x0w6qFRf2hQ9bwEjoimYUOU3t5IWVlknztv8fXZp09jSExE6eFhcTKpPTEYJd7adJqtSbIouNsjh4/Gt7VY2JgwlYRXZjO/LHO+jf1nlWnNJeGl97vR3bxJyq/rASwKYwmqHrfScrh/+SGW7JSFzcTOddnw+F0OLWxAiBuBDTGkZ5CaVyLqM3YMxJyAkz/LDw58y252ORsKpRL39u0AzEnBlmAOSd11l129B5aQozfw1Jpwvvv3KtEeAQA0zk2q0Myv/M38rDXOojRMZeD2zLcx4ZEXmsosQ7+bhG+/RdLpcO/cydwEUOB8HPwvgeGf7OOfS/G4q1V8PKEd749ri7vGsfJrikKIG4HNSNv2J1JWFpoGDWS3tWnMQuv7oHY7u9rmbJhDU+URN1WsBDw1W8f9yw+x5WQMapWC+8f3AuReNxURJR3q1cBFqSAmJZvrSVnWMrdYJEkyh6UcIRlX20323GSdOoUhPaPY8/Tx8SSv+wkQXhtnxWiU+HTXRaZ8fZBbaTk0CfJk05y7uLdjiL1NKzNC3AhsRnJeSMpn7FgUV/fDpR2gdIF+c+1smfPh3r58zfz0CQlknzwJgEcvxy8Bj0vNZuJXBzn4XyKeri6sfKArgwd1ApCTzMvQu6g43DUq2oTIfYIqIzSlu3YNY2oqCrUa18aNbb5faZiS8dHryTp2tNjzEleuRMrJwa1tWzx69qxECwWVQUJ6DjNXHuaj7RcwSnBfxxB+m3MXTSopD81aiIRigeVIEuRmQGYCZMZDZiJkxOe7nUDutWiyjpwBBfhcfwdWJsnXdrwf/O1XFeKsuLdpDSoV+pgYdDExqGuXrZFWxj//gCTh2rIF6ppBNrayYvx3K50Zyw9xPSmLAE9XVj7QhdbBshhxqVULfWwsuqtXcalRo9x7dA31IzwqmcORidzXybafUs3JxE2botCUrWTd1mi7dyPll+tkHAwjt1N3Nh+P5r5OIXi6ym8V+qQkElevAeQKqYqEAQWOx+HIRJ5cHU5sajZuaiXzR7dmQueqOQRViBvBbRIuQ1qMLFIy8kRLnli5LV7yvvQlD0RLPuEFeOFRKxu1Mk/YeAdDn5dt/zyqIUoPD9yaNSP7zBmyIiLKLG5uD8p07JBUxLVkZq08TGJGLqH+Wr6f1Y16/reb82nq10cfG0vu1asVqtzp2sCPr/b+VymeG3s37ysKj27dSfnlVzIOHuRFr7s4ejWJ6OQsXh3eAoDE779HyszEtUULPPv2ta+xAqthNEp8tfc/Ptp+HoNRomGgB19M7USzWlXLW5MfIW4EYNDBhkfg1K+WXadyBY8A0PrLX3nHkps/KTt+AdLwnfkUDBuWd44fKB0/Ea2q4t6xI9lnzpB5LBzvYaUP+JT0etL37wccuwR89/k4Hv/xGFk6A22CfVjxQBcCPAvOvtLUq0dmWBi5RQzQtITO9f1QKOC/+AxupeUQ6GW7GVuOKG603boC8pTv86E3QKNly8kYXhnWHGNaGkk//AhAwKPCa+MsJGXk8vzPx9l1Lg6AMe3r8M7YNni4Vm15ULWtF1QcfQ78/ACc3wIKFfg1AG2eYPHIEy3m2wGyQDHd1ngU2acm88AB9AkrUHp74znpcagiQxirOu4d2pP0449lTirOOnECY948Kvd2bW1sXfnYdDya59ZFoDdK9G4SwJfTOhX5oqsJlaeD50ZVTNz4aNU0q+nFudg0DkcmMryNbebkSJJElgNVSplQBwUh1QtFERVJ2/jL/BvchutJWZyOTqXWptUY09NxbdIYr0ED7W2qwAoci0pizqpjRKdko3FRMu+eVkzqUtcphKsQN9UZXTb8NAMubpO9MBN/hKaDK7xs8oaNAHiPGF5lpks7A9q8CeHZZ89izMxEqS15plKBEnCV43nU1h+7zgs/H8coyZ8mPxjXDo1L0TUQ6npFTwcvD10b+HEuNo1DV2wnbnQ3bshT59VqXJs2scke5SFbZ2CfZ33uJpJRxmi8Ww7iz9OxbD/yHyNXfgeA/yOPolCKWpSqjCRJfPvPFRZuPYfeKNEgwIPPpnQsccBsVUP8hVZXcjNh7WRZ2Li4w5S1VhE2hrQ00vJ62/iOHVvh9QRlR12nDi61aoHBQNbJU6We78gl4D8dvsbzecJmcte6fDyhfbHCBkBTzzqeG6icZn7Zp/JCUk2aoHSQZGKAD7ed52/PUAA6JV5mWBu5K3j2rz9jSElBU78+3sOG2tFCQUXRGYzMWRPOgi1n0RslRratzaY5dzmVsAEhbqonuRmwegJc3gVqD5j6s9wx2Aqkbt2KlJODpnEj3Nq0scqagrLj3qE9UHq/G93Nm+ScPQsKBR69elWCZWVndVgUL/16AkmCad3r8c6YNqUOstTUkys6jCkp6JOSKrR/17xmfmdjU0nNtmRMa9m5PSzTvp2J83Pgcjzf/nOFkwENkRQKDP/9R59AFZ6Snr7HdwDg/8gjDunlE5QNg1Hi+Z+Os+VEDBqVkrdHt2LZ5A54uVWN5p2WIMRNdSMnDX4cB5H7QOMJ036FBtbrb5KSF5LyHTvWKeK2VQ1TaKo0cZORN0vKrU0bXPz9bW5XWfn+30j+b4Pcd+eBu0J5e3TrMk3oVrq741KzJiAPo6wINb3dqO+vRZLg6NWKCaXicLRk4tRsHS/8dByAkb1a4Na8OQCKiKM8mn6SGjnpZPkH4TNqpD3NFFQAo1Hi/9afZNPxaFyUCr6c3pHpPUKd9nVaiJvqRHYK/HAvRB0AV2+YvhHq97Da8jn/XZHfVFUqvEeNstq6grLj3kHuVJwZEYFkNBZ7niOWgH/7zxXe+E1+03/47oa8MbKlRS+8mvp5oSlr5N3YMDQlSZLDiZu3fjtNdEo29f21vDaiBR553Yoz9u7j7mN/AvB7q0FVZjyHoCCSJDH/9zOsO3INpQKWTupA/+Y17W2WTRHiprqQlQTfj4Hrh8DNF2b8BnWtOxMmZeNGADx79UId5NgN4ZwVt+bNULi5YUxJIffKlSLPkXJzyThwAHCcfJuv/r7M27/LoZrH+zbi1WHNLf5EqalvSiq2Qt6Nac6UDcSNPjpa7qTs4oJr06ZWX99S/jgZw/rwGygV8PGEdni4upiHaKZs2oQ6KYFb7j784NOGqwnFj2UQOC6Ltl9g5YFIAD4Y144RbW2TKG/iTMIZLiZdtOkepSHETXUgIwG+GwXRx8DdD+7fDMEdrbqFZDCQ8ttvgDxuQWAfFGo17nm5TsWFpjKPhWPMyEDl5+cQnoPPdl/iva3nAHhqQBNeHNKsXK5ys+fGCknFJs/N8evJZOsMFV4vP6ZJ4K5Nmti9mjAuNdscBnysbyM61Zeft7ZzZ1Cp5G7kwNEeI9GpXNh6KtZutgrKx2e7L/Hp7ksAvD26FeNs2HlbkiRWnV3FtD+m8fzfz5Opy7TZXqUhxI2zk35LFjaxJ8EjEGZugdrW72mSceBf9DdvovLxwbN/P6uvLyg77nlDNIubM2Wukurd2+4lvUt3XuTDbecBeG5QU54b1LTcOQDWLAev768lyMsVnUEi4lpyhdfLj3kSeMsWVl3XUiRJ4qVfT5CcqaNVHW+eHnDbi6Ty9MS9dWv5OCCAwEkTAIS4qWKs3H/F/P/16rDmTO8RarO9UnJSeGb3Myw8tBCdUUeodyh6SW+z/UpDiBtnJi0WVo6AuNPgWUsWNjVtU52Rkjck03vkSIcqba2OmCumjhUnbv4G7BuSkiSJRdvPs3jnBQBeGtqMpwZUrN+LyXOjs4K4USgU5tCUtfNubldK2ddrtvpQFHvO30LjomTxxMKl9t4jRgAQOGcOgzvUQ6GA49eSiU62/cR0QcX56fA13tos/609NaAJj/Sx3Uy/iLgIxm8ez65ru3BRuvBK11dY2m8p3hr7lZcLceOspEbLwib+vDzT6YE/ILCZTbYypKSQtnMnIEJSjoA2b7ZS7pUrhcqic6/fIPfSZVAq8bjrLjtYJwub9/88z7Jdsqt87vAWPN634lOxNXXlcnBDSkqFpoOb6GbKu4m0nrjJn0zsbkdxcyU+gwW/nwXgpSHNaFrExOca06fRZN9eakyaSJCXG53rywNJt50W3htHZ/PxaF5ZfwKA2b0a8OxA2zSKNEpGlp9azsw/ZxKTEUNdr7r8OOxHpraYavcqLCFunJHkKFgxDBIugU9d2WNjw0ncqVu3IuXm4tq0qUP17aiuqHx90TSSf99ZEREFHsvYJ4ek3Dt0QOXjU9mmIUkS72w5y5d/XwbgzVEteejuhlZZW6nV4pKXyG7NZn5HryahNxRfeWYJ+thYDImJoFLh2sw2HzZKtcFg5LmfIsjSGejR0J9ZdzUo8jyFQoFLYKD59pBWckM/EZpybHaeucmz6yIwSjClWz3mjmhhE6GRmJ3I4389zuKjizFIBoaGDuWnkT/RKsD+eXwgxI3zkRQJK0bI333ryx4bv6JfvKxF8no5JOUjets4DMWFpuxZAi5JEvM2n+Gbf+QqrrfHtOaBYt5Yy4s1y8Gb1fTC282FzFwDp6NTK7we3O5v49q4MUo3N6usaSlf7LlMeFQyXq4ufDShXZn6CAEMbS2Lm8ORidxKy7GliYJy8s/FeB5ffQy9UWJsh2AWjG5tk9fkw7GHGb9pPPtv7MdV5cqbPd7kg7s/wFPjafW9yosQN85EwmVYMRxSosCvETywFXzr2XTLnEuXyD5xAlxc8LlH9LZxFIpq5mfMySHj4EGg8vNtjEaJ1zaeYuWBSBQKeO/eNkzvXt/q+6itWA6uVCrM3htrhaay7Nzf5uT1FJb+JZfozhvdimBf9zJfG1JDS9sQHyQJtp8R3htH40hkIg99f4RcvZEhrWry4bi2ZRauZcVgNPBFxBfM3j6buKw4Gvg0YPWI1YxrOs7hPtgKceMs3LogC5vUGxDQVPbY+ATbfFtzb5u773aoTrfVHVMzv6yTJ5F08giBzEOHkbKzcQkKqtSQiNEo8X8bTrIqLAqFAj64ry2Tu9pGdN8uB6+45wZuj2IIs1JSsTmZuGXlh2+zdQae/UmesD6sdS3GdrD89cHkvflThKYcipPXU3hgxWGydAb6NA3kk8kdcFFZ9+09LjOOh3c8zOfHP8coGRnTeAxrR6ylaQ3792oqCiFunIGbZ2DlcEiPhaCWco6NVy2bbyvp9SSbe9uMsfl+grKjaRCKyscHKSeH7LNy4mj+QZmV9SnLYJR48ZcTrD18zdwkbnznujbbzzxA0wphKbjdzO9IZCJGo1ShteRkYvvNlHr/z3Nciksn0MuVd8a2KdffwLDWcvO3fy8nkJyZa20TBeXgfGwa05eHkZajp1sDP76c1glXF+vO/9p/Yz/jN4/nUOwh3F3cebfXu7x919to1Vqr7mNNhLip6sSehO9GQsYtqNUG7v8dPCunO3DG/v0YbsWjqlEDrz59KmVPQdlQKBS43xGaMpWAe1RSvo3eYOT5nyL49dh1VEoFSyZ1YGwH2zUQg9tdinVWCEsBtK7jg5taSVKmjku30iu0lj4uDkN8PCiV5tlNlcX+S/Gs2B8JwAfj2uLnUb52DQ0CPGheywu9UWLn2TgrWigoD1fiM5j2bRjJmTra1/Xl25ldcNdYT9jojDqWHF3CozsfJTE7kaY1mrJu5DpGNXL8FAQhbqoy0eGwciRkJkCdDjBjE3hUXmjIlEjsPWokCtHbxuEwiZvM8AhyIyPlN3y1Go8e1psnVhw6g5Fn1kWwMUIe0vfp5A7c066OzffV5DXyMyQnY0hJqfh6Lko61pNLoCva78acTNyoEUr3sue6VJSULB0v/CwPxZzarR79mlXsw4+paurPUzEVtk1Qfq4nZTL164PcSsuhRW1vvnugK56uLlZbPyY9hll/zuLbU98CMLHZRFaPWE0DH9sWqFgLIW6qKtePwHejITsZQrrIs6K0fpW2vT4pifRduwDwvffeSttXUHa0HfM8N8eOkf637LXRduqEytO2FQ25eiNPrQnn9xMxqFUKPp/akWFtbDvLxoRSqzWXL1ujHBxul4RXWNycsk8y8Zu/nSImJZtQfy1zR1S8K/KwNrK42XsxnvQc+3Wgrc7EpWYz7ZswolOyaRjowQ8PdsVHa72hpruidjFu8zgibkXgqfZkUZ9FvNb9NVxV9h0XYglC3FRFog7KQzBzUqBeD5i2Htwqt2dJ6h9/IOl0uLZoUekudkHZcGvdGlxc0MfFkfTTz4DtS8Bz9AaeWH2Mradi0aiUfDmtE4Nb2T7/Kz/mpOJI6+Td5G/mJ0nlz7sxTwKvxGTi309EszEiWs53mtgerabin+yb1fSiQYAHuXoju86J0FRlk5iRy7Rvw4hMyKSunzurZ3cnwNM6oiPXkMv7h97n6d1Pk5qbSmv/1vw06icGhw62yvqViRA3VY3If+CHeyE3DUJ7w9RfwK3yW1yn5IWkfEUiscOidHfHrYX8ST33stw0z5Yl4Nk6A4/+cJQdZ26icVHyvxmdGNCips32Kw5zObiVKqY61KuBi1JBTEo215PKP3rAXCnVunI8NzdTs5m74RQAT/RrbA6vVRSFQmGumtomqqYqldRsHTOWh3HhZjq1vN1YPbs7tXys0y/pWuo1pm+dzo9nfwRgRssZfD/se+p62a4AwJYIcVOVuLwbfhwHugxo2A+m/ASuld80Kfv8BflTqFqN9yjHTyyrzphCUwDq4GA0Da3TDfhOsnUGHvr+CLvP38JNrWT5/V3oW8HcjvJiqpjSWSks5a5R0SZE9oyWNzSli4tDf+tWpSUTS5JcpZaSpaN1sHeF53bdybA8cbP7fJzVp6ZXBVKzdaw7HMW207EkpFdOQ8PMXD0PrDjMqRup+Hto+HF2N+r6Wada6c8rfzL+9/GcSTiDj6sPn/b/lBe7vIhaZb1QV2VjvewjgW25cQxWTwRDDjQZDBN+ALV9OpyahmR69e2DSw3rfBoU2Ab3Dh3gu+8B25WAZ+UamP39YfZfSkCrUfHt/V3o0ch+PY+sHZYC6BrqR3hUMocjE7mvk+UVX6aQlKZhA5Ra25fP/njwKnsv5A3FnNAetZV7nrQJ9iHY150byVn8feGWOcnY2dEbjKw5FMXinRdJzLhdCt8gwINO9WvQuX4NOofWoFGgp1X/10wfHo5eTcLbzYUfHuxG46CKf7DN1mfz/uH3+eXCLwB0DOrI+3e/Ty2Pqv/7FOKmKmDQw+anbwubiT+Ci30SuySdjpTNmwHwGSsSiR0dU8UUWL8EXJIkwq8l894fZzkcmYSHRsXKWV3NCbj2QmMOS1nHcwNyUvFXe/8rt+fG1N+mMoZl/ncrnXf+kHsbvTK0OU2KGIpZURQKBUNa1WL5/iv8eSrW6cWNJEnsOX+Ld/44y6U4uSVAgwAP1CoFF26mcyU+gyvxGfxy9DoAvlo1nerVoFNoDbqE+tEm2Ac3dflKtHUGI0+sOsb+Swl4aFR8N6srLetUPBXhv+T/eGHvC1xMuogCBbPbzObx9o/jonQOWeAcz8LZOfItxJ6Qk4ZHf243YQOQvu8fDAkJqPz98ezdy252CMqGumZNvIYMQX/zJh7du1tlzYwcPRsjbvDjwSjOxsgzl7xcXVg5qyud6tvfk2cuB09KwpCaisq74m8EXUL9UCjgv/gMbqXlEOhl2f9gdiWNXdAbjDz703GydUbuauzPzJ6hNttrWBtZ3Ow8e5NcvRGNi3NmOZyNSeXdP86y72I8AH4eGp4d1JTJXeriolKSkqnjWFQShyMTOXI1iePXkknO1PHXuTj+yku41qiUtA72pnOon9nD41+GJGCDUeKZdRH8dS4OVxcl387sQocK5k5l6jLZcGkDS48tJUufhZ+bH+/1fo+edXpWaF1HQ4gbRyctFnYtkI8HvAmegSWfb2NSNqwHwGfUKBTqqhuPrU6ELF1ilXXOxaay6mAUG8JvmEuAXV2UjGpXh0f7NKRxkPU9BOVB6eGBKjAAw614cq9G4d6mdYXX9NGqaVbTi3OxaRyOTGS4haXtlVUp9dnuyxy/loyXmwsfjiv7UMzy0KleDQK9XLmVlsOBy/F2y7GyFXFp2Xy8/QI/HbmGUZIFygO9QnmiX2O83W6/9vlo1fRrHkS/5nkT6fVGTkencPRqEkcikzhyNYn49ByORSVzLCrZfF1poSyjUeLlX0+wJa+lwlfTO9G9YfnDvVdTr7L23Fp+u/Qbabo0ALrV7sbC3gsJcA8o97qOihA3js62/4OcVAjuBJ0esKsp+sRE0nbvAeQJ4ALnJ1tn4M9Tsfx48CpHriaZ728Y6MHUbvW5r2MwvlrHa+CoqV+frFvx5F69ahVxA/KcqXOxaRy6Ypm40d+6hT4uDhQKc/WaLTh+LZlPdslDMd8e3fr/27vvsKiu9IHj32l0GJCO0lVUsMfY04zYE3uJMaaYRGOKKZte3PyyG1PWdEssKauJrtEYe++9gRVRQYrSe4cp9/fHyEQUkDLDAJ7P88wjzNxyrheYd855z3nxqUVRzLqQy2UMCvVk2ZEEtpxLaTbBTYlGx+L9sczfE0NhmSFZelgnb94e3K5GCbxWSjld/Vzo6ufCtP6GIa2ErCJjoHMyPqtGQ1kbTifxx0nD6t7fTepWp/9fvaTnwPUD/HbxNw5eP2h83s/Rj8c7PM74tuNRyE1bqqGxEMFNYxazG86tBpkchs0FuWW7ffM2bACtFpvQUGxCGmexNME04jML+e1oAqtOXjMmTirlMsJDPXm8pz+9g10bXRXgm1n5+VN84qTJpoODYWjq18Pxtc67KZ8CbhUYiNze3mTtuVlxmaEopk4vMayjN492Mf9q0GCoNbXsSALbLqTyyUi9yYs1NiS9XmLd6SQ+33KRpNwSADr7OvPh8PZ09697HplMJsPf1R5/V3tjMnpOURmnEv7u2alsKMuwL3w5rpNx6n1N5ZbmsvbKWlZcXMG1AkPwJENG/1b9mdRuEn18+iCXNd17VRMiuGmstKWw6Q3D1z2eBZ8uFm0OQM6fawFQjxa9Ns2RVqdn58U0lh9NYN+ldOPzPmobJt3rx4Qevng4WWaGXm2V592YqsYU/F0hPColj7wSTYWhieoUN0C+zWdbLhKbXoiHozWfjAxrsMCzZ2ALnO1UZBWWcSwuiz7BTXN443hcFp9suMDpa4aSHS2dbXlzcAgjOvmYZWjP2c6Kh9p58lA7wzpQlQ1lZReV8X+PhtWqHlt0VjS/X/ydjbEbKdEZAjRHK0dGtx7NhJAJ+Do1zTVr6kIEN43VwW8h8wo4eMJD71m6NZRERVEaFYVMpcJp6FBLN0cwodS8ElYcS2TF8QSSb3xilcng/rbuTO7pz4Mh7k3uE7lVgGmrgwN4Otng72pHfGYRJ+Oza1yjydyVwPdfTufnQ3GAoSimSx2LYtaFUiFnYHtPVp28xpZzKU0uuInPLGTO5otsvrEYob2VghcebM0z/QLrPLupLiobyirV6mvUBo1ew86Enfwe9Tun0k4Zn2/r0pZJ7SYxLGgYtsqGq2XWWIjgpjHKugr7vzR8Pejf6DRyCvdtozgiEseBD2PXrVuDNynnxto2Dg89JNa2aQb0eolDMZksOxLP9qhUdHpDWYEW9laMv8eXx+71w8/V/OuxmEt5z40pp4ODYWgqPrOIY1ezahHcmC+ZOLdIwz9WnQHg8V5+Fsl7GdLRyxjczB4RatYkZlPJLdbw/a7L/HwoDo1OQi6DCT38eG1g2xrNhCvSFLHp6iaUciXB6mCCnYOxU5nu90Umk90xsMkozmDVpVWsil5FerGhp1UhU/Cw/8NMajeJbh7dGvXQsbmJ4KaxkSSkjW9QkqajsKQjBXP+pDhyNugMiW1Zy5bh869PUD/ySMM1qayMvPUbAHAWQ1JNWnZhGatPXWP50QSuZhQan783oAWTe/kxOMwLa2XTTzBU3VilWJeVhS4/H4WjaWZy3RvYgj9OXuN4DfNutJmZaFMMvQLmCG4++OscKXklBLrZ8+5Q8yUrV6dvazccrZWk5ZcSkZjTKJYDqIpGp+e3owl8veMS2UUaAPq3ceO9Ye1p51WzJQNic2J5dc+rxObGVnje296bYOdgY7DT2rk1Qc5B2KtMl2clSRKn00/z28Xf2B6/Ha3eMGvR1caVcSHjGNtmLJ72DV/ypDESwU0joU1Pp+DgQQo3rqTw2Fl0pe5A5o2HIRlR4dqC4hMnSXrzLcquXcNtxowGiczz9+5Fl52N0t0d+759zX4+wbTKF9tbdiSeDWeSKdPqAcPaNKO7teSxnv6EeDWOadymonCwR+Hmhi7jxnRwE9VzuvfGAoWnr+VQotHd8dO1MZk4IMDk1dh3X0xj3ekkFHIZc8d3NklRzLqwVip4qL0Hf0UmseVccqMMbiRJYtfFNP61KYrYdENQ39rDgfeGteeBtu41/ju6+epmPjr0EcXaYtxt3QlSBxGTG0NGcQbJhckkFyZz4PqBCvt423sT5BxEa3VrQ/DjHEyQOggHq5r/PJRoS9h8dTO/X/ydqKwo4/Nd3Lswqd0kBvoPbNKlEsxBBDcWIpWVUXQqgsID+yk4cJDSixdvelWB3EaFff/7se/bD/t+/bBq1RJJryd97lwyFy8h49vv0Fy/jvfs2WZfbya3PJH40UeQKcWPTFMRl1HIhjNJrD+dTHRqvvH5UB8nHu/lzyOdfbC3br7308rfn+KMDMri40wW3Pi72uHhaE1afimRiTl3XHfEXIv36fUSX2yNBuDpvgH1XtitvoaEefFXZBKbz6Xw7tD2jWo45EJSHv/adIGDVwwfFG9dhK8mynRlfHH8C1ZErwCgp1dPPrvvM1xtDfc/pySH2NxYruRcISYnhpjcGGJyKgY9N0/FBvCy97qtlydYHVwh6LlecJ2V0StZc3kNuaWGZGcruRVDg4Yyqd0kOrg2XIX5pqb5/mVrhMri4yk4cIDC/QcoPHYMqaiowus2vs7YOybi0MYF248OILOr2E0qk8vxeOMNVK1akfLx/5G7eg3a5BRafvuNyT8VltNmZFCwdy8A6pEjzXIOwXSuZRex8UwyG84kc/Z6rvH58sX2Jvf0o4uvc6N68zEXKz8/ik+eNFkBTTDkQvQIbMHGM8kcu5plseBm87kULiTn4WCt5IUHWpv02HVxf1sPbFRyrmUXcz4pj7CWaks3ibS8Ev6z7RL/O5mIVM0ifHeSXJDM63tf52zGWQCe7fgsM7vMrLA+jLONM91sutHNs2I+ZG5pboVgp/yRXpxOSmEKKYUpHEyqGPR42nnS2rk1MpmMg9cPImHIh/Ox92FCuwmMbj0aZxvnOv6v3D1EcGNGuoJCio4dpfDAAQr2H0CTmFjhdYWbGw59+2Dfrz/2bVugXDEcJB1M/gnsqh7/dZk4EaWXF9dfe53CQ4eIn/w4vgsXoPIyfX2X3PUbQKfDplMnrFtb/o+ocLu0vBI2nk1m/emkCiugKuQy+rZ2Y3gnbwaFeqG2vbu6rY01pkw4HRwM0583nknmeNyd827MMQ1cp5eYu93Qa/NMv8AGnR1VFVsrBQ+09WDL+RQ2n0u2eHCTlFPM8O8OGNdoGt7Jm7dquAjfzQ5eP8jb+98mpzQHJysnPu3/Kfe1qnmNNrW1mm6elQc95T09sTl//5tWnEZqUSqpRanGbXt792ZSu0nc1+q+ZrvgnjmI4MaEJL2e0osXKThwkMIDByiKiACN5u8NVCrsunbFvl8/HPr3wzokBJlcDno9/DTEENi0HwFtBt7xXI4PPID/r7+SOGM6pdHRxE2YiO/CBdi0a2e665EkctcYyi2IROLGJbOglM3nUthwJomjV7OQDB/ukMkMb74jOvswONSrRvVrmitjdXATTgcHjIVBT8Zno9VVvXBd6dWraJOSQS7HpoPpkn3XRlwnJr0Qta2KZ/oHmuy49TWkoxdbzqew5VwK/xhkur9DtSVJEu/+eZaswjJaezjw2ZiOtV6ET6fXseDMAhaeXoiERAfXDsx9YC4tHVqapI1qazVdPbrS1aNrhedzS3O5mnuVKzlXyCnN4SG/hwhSB5nknHcbEdyYSMnFiyQ8Mw1dZmaF51V+fjj064t9v37Y3dsThUMlmfORyyHxCKjsYfCcGp/TNiyUwBUrSHj+ecquxBA/+XFafvMNDv1Mk/RbcuECpZcvI7OywmnIEJMcU6i73CINWy+ksP50EodiMo3TtwG6+7swvJM3Qzt649lEFtozN5WZpoOHeDriZKMkr0TL+aQ8Ovs6V7pdzh9/AGDfv5/JZmuVafV8vfMSANPvD67V8Iq5PdTOAyuFnJj0Qi6n5pulGnlNrD51nT3R6Vgp5Sx4vFuta55llWTxzv53OJR0CIDxbcfz5r1vYq0w/wcFtbWaLh5d6OLRxeznau5EcGMiVn5+6PPykNnZYd+zJ/b9+uLQr5/x02OVirJg+4eGrx98B9Q1X40SQNWyJQG//ca1l16m6OhREp9/Hu+P/4nzmDF1vJK/5a4xrG3j+PAAFGrLj6HfjQpKtey4kMqGM0nsvZSORvd3QNOxpZoRnb0Z1smHlmauI9QUlf/u6TIz0RUUmCwvTS6X0SOgBTsvpnE8LqvS4EYqKzMm4ruMG2eS8wKsOplIYlYxbg7WTO1zh78tDczRRkW/Nm7supjG5nMpFgluUvNK+Hi9YShw1sNtah3YRKZF8sbeN0gtSsVWacsHvT5gRPAIczRVMDMR3JiI3M6OgJUrsGrdGrlVLcbAd3wExVng0QF6Tq/TuRVOTvgt+pGk998nb916kt97n7LERNxfeaXOiaP6sjJDLSlAPWp0nY4h1E1xmY7d0WmsP53ErotplN6Yug3QzsuR4Z28Gd7JhwA389Qpai4UDg4oXF3RZWYaCmiaMO+lR6AhuDl6NYtp/W8fNsjftRtdVhYKdzcc7r/fJOcs0ej4bucVAGY+GGyxqd/VGRzmZQxuXh7QpkHPLUkS7/15jrwSLZ1aqXmukvtS3b6/XfyNL49/iVbSEuAUwNwH5tLGpWGvQTCdxvfb0YTVepGuhKNw6lfD18O/gnqsUyCzssLns89QtWxJ5vwFZC5YiCYpCZ9PPkFWm2DrhoJdu9Hl5qL09MS+T+86t0uomVKtjn2XMthwJontF1IpulGNGCDIzZ7hnX0Y0cnbYl39TZWVvz/FmZloTBzclNeZOhGXhV4v3bYqb86qVQA4jxptsqUalh9NICWvBB+1DY/19DPJMU1tYHtPFHIZUcl5xGcW4u/acAH4utNJ7IhKRaWQ8fnYTjWe5l2oKeSjQx+xNW4rAOH+4Xzc92OTLr4nNDwR3FiKTgsbXzN83fVx8OtV70PKZDI8XnkFq1atSP5oNnnr1qNNSaXVd9/Welgp90a5BfWjjyJTiAx9c9HrJRbsi2H+nhjyS7TG51s62zKisw/DO3kT6uN0V0zdNgcrPz+KT50yed5NmI8aG5Wc7CINV9ILaHtT0Fl27TqFhwz5Gs5j6z88DFBYqmXebkOvzUsD2jTaVaRd7K3oFdSCg1cy2XIuhefvD26Q86bnl/LROsNw1IsPtqnxasNXsq/w6p5XicuLQylT8vo9rzO5/WTx+9YMiODGUo4thNRzYOsCD39s0kM7jxmD0tOL66+8QtGxY8Q9NhnfhQuxalWzTH9NWhoFBwyrbIq1bcwns6CUWSsj2X85AwBPJ2uGdfRhRGfvu2YtGnMz13RwK6Wcbn4uHIrJ5NjVrArBTc7qP0CSsO/T21jjqr5+PhRHZmEZ/q52jO1eu7y8hjY4zJuDVzLZ3IDBzYd/nSOnSEN7bydeeLBm59wQu4GPD39MsbYYDzsP/nP/f0QibzPStEr9Nhe512H3vw1fP/xPsK9+IbC6cOjXF//ly1B6elIWE0PcxIkUnztfo33z1q8HnQ7bLl2wDmo8U02bk6OxmQz9dj/7L2dgo5Lz+ZhOHH57AB+O6EBXPxcR2JiIuaaDw99Two/dVGdK0mrJXX1j+QQTJRLnFmtYuDcGMCTJqm4Mt+SW5jJr9yzWx6w3yXlMZVCoJzIZRCbmkJxbbPbzbTqbzOZzKSjlMr4Y28n4/1OVMl0Z/3f4/3hn/zsUa4vp5d2LVSNWicCmmRHBjSVsfRfKCqDVvdB1itlOY9OuHQErV2AdEoIuI4P4KVPI37272n0kSTJWAFeLtW1MTq+X+GH3FSYtOkJqXinB7vb8NbMf43v4Nolqyk1NeQFNUw9LgWE9IYDjcVlINxYaKti3H21aGgoXFxwGDDDJeZbsjyWvREsbDwce6fx37+uyqGXsTNjJJ0c+IackxyTnMgUPRxvuuVFfasu5FLOeK6uwjA/WngNgxgPBd1w88HrBdZ7Y/AT/u/Q/AJ7v9DwLHl5AC5varYMjNH4iuGloV3bAhbUgU8DwuSA37y1QeXnhv3wZ9n37IhUXc23mi2T//nuV25ecPUvZlRhkNjZibRsTyywo5cmfj/PF1mj0Eozu2pJ1L/ZrdkUrG5PyYSldRga6ggKTHrurnwtKuYzk3BKuZRt6KMoTidUjR9Zu1mQVMgtKWXLgKgCvh7dFcSMA1ug1rL60GoAibRHLopbV+1ymNDjMGzCUiTCn2evOk1lYRltPB158qPoV1Pdd28f49eM5n3ketbWaeQPm8WLXF8Wqv82UCG4akqYENr5h+LrndPDq2CCnVTg44LtgPuoxo0GvJ+WfH5P6xRdIev1t25b32jgOHGiyhccEw9DF0G/3s+9SumEYamwn/jO+c7MuXNkYKBwdUbQwfCo3ZY0pMJQcKO8pOHY1C01qqrEOm/O4sSY5x4K9MRSW6Qhr6cSg0L/Lq+xJ3EN6cTpKmeHn57eo38gvy6/iKA1vUKgnYOjVSs8vNcs5tp1PYd3pJOQy+GJs5yqTrHV6Hd+e+paZO2eSV5ZHmGsY/xv+P/q36m+WdgmNgwhuGtKBryD7Kjh6Gxbsa0AylQrvTz7B/ZWXAchaspTrr7+OvvTvPzz60lLyNm4CwHnUyAZtX3NV5TDUPb4ir6aBmDPv5uahqdw1a0Cvx/ae7lgH1X/J/NS8En49bGjz6+EhFX5eVkavBOCJ0CcIVgeTr8nn94tV98g2tFYudnRqpUaSYPuF1DvvUEs5RWW8d2M46rn7gqtcJTqzOJPndzzPorOLAJgYMpFfhvyCj4OPydskNC4iuGkomTFwYK7h68GfgnXD94rIZDLcZszA5/PPQKUif/MWEp56Gm12NgAFO3eiz8tD6e2NXc+eDd6+5iazoJSnbgxD6fQSo8QwlEWUz1gy9Ywp+Dup+HhsBjl/GIaJTLUi8fe7rlCq1dPd34UH2robn4/LjeNo8lFkyBgfMp5nOz0LwH8v/JciTZFJzm0Kg8MMPU2bzyWb/Ngfb7hAen4pQe72zHq48oX2ItIiGL9+PEeTj2KrtGVO/zm81+s9rBSWLzQqmJ/Fg5t58+YRGBiIjY0N3bt3Z//+/VVum5yczGOPPUZISAhyuZxZs2Y1XEPrQ5Jg0xugK4PgAdBhpEWbo37kEfwWLULu6EjxqVPET3qMsoQEcm4sF68eKda2qa/jcVkM+/YAey+lY62U89mYjswVw1AWofI3T40pMAQ3MhmooyLRXL+O3MkJx0GD6n3cxKwiVhw3tPeNW3ptypNh+7fqT0uHlgwOGIy/kz85pTn8L/p/9T63qQy5kXdzOCaT3CLNHbauuV0XU1lz6joyGXwxthM2qop/qyRJ4veLv/P0lqdJK04jUB3I78N+Z1jQMJO1QWj8LBrcrFy5klmzZvHee+8RERFB//79GTJkCAlV/BEqLS3F3d2d9957j86dOzdwa+vh/J8QswsU1jD0C0PpZguz79WTgN9/Q+XjQ1lcHHETJlJ48CAAzmJtmzrT6yXm7bnCxB+PkJJXQpC7PX+92JcJPfzEMJSFmHNYSm2nIsTTkcFxRw3fjxiB3Kb+hUu/3XkZjU6iX2s3egf/vVREibaEv678BcCEkAkAKOQKpnWcBsDP53+mRFtS7/ObQqCbPe28HNHqJbZHmWZoKq9Ew7trDMNRT/cNvK3ad4m2hPcPvs+/j/4braRlUMAgfh/2O8HODbPejtB4WDS4mTt3Ls888wzTpk2jffv2fP311/j6+jJ//vxKtw8ICOCbb77hiSeeQN1UCjmW5MGWG/k1/V8D18bzS2bdujUBK1dg06EDuuxsY77AHYt9CpXKKizjqZ+P8/kWwzDUyC4+rH+xX41XSxXMw8o4Hdz0wQ1Af3cFvZINa0g5j6//kFRsegGrT10DDDOkbrYlbgt5ZXn42PvQ16ev8flhQcNo6dCSzJJMVl9eXe82mEr50NQWEw1N/XtjFCl5JQS42vFGeEiF15ILkpm6ZSrrYtYhl8l54543+OK+L0QZhbuUxYKbsrIyTp48SXh4eIXnw8PDOXRj6XJTKC0tJS8vr8KjQe35FApSoEUQ9J3VsOeuAaW7O/7//RWHBx8EoMXj5lt3pzk7HpfF0G/2VxiG+mpCFzEM1QgYp4OnZ6ArKDT58e+LPYZK0hHvEYBNSMidd7iDr3ZcRi/Bw+096OrnUuG18mGncSHjKkxhVslVPB32NABLzy2lTFdW73aYQnlws+9yBgWl2jtsXb39l9NZcTwRgM/GdMLW6u/rP5Z8jAkbJnAh8wLO1s4sHLiQqaFTRW/pXcxiwU1GRgY6nQ5PT88Kz3t6epKSYrq1ET799FPUarXx4evra7Jj31HyGTi6wPD10C9BVf/uanOQ29vTat4PtDl4AKfB9c8XuJvo9RLz98T8PQzlZs/amWIYqjFRODmhcDEECZpE0+bdSJKEx35DwcW1LXuQV1K/3JKo5DzWn04C4NWBFXttLmRe4GzGWZRyJaNa377A5sjWI/Gw8yCtKI21V9bWqx2mEuLpSKCbPWVaPbsvptX5OAWlWt5efRaAqb396RlkGKqTJIlfzv/Cc9ufI7s0m/Yt2rNi+Ap6ede/Vp/QtFk8ofjWNwBJkkz6pvDOO++Qm5trfCQmJprs2NXS6w2FMSU9hI6C1qZZrdRcZDIZSlfTl4FozrIKy3j6l+N8tuUiOr3Eo118WPdSP9p7i2GoxsZceTdFx4+jT4inRGXNnpZdOBmfXa/jzd1+CYBhnbwJ9ak49F7eazPQbyCutrf/rloprCr03mj0pkvirSuZTHbT0FTdP7TO2RzF9ZxiWrnY8ubgdgAUa4t5a/9bfHniS3SSjhFBI/h1yK+0dKhZDT2hebNYcOPm5oZCobitlyYtLe223pz6sLa2xsnJqcKjQUT8CteOg5UjDPq0Yc4pNJgTcVkM+3Y/e6INw1BzRnfk6wldcKjDMFSRpoiItAjjEv6C6ZmrgGbOqj8AiOvclxKldYU6U7UVmZjD9gupyGXw6sMVe23yy/LZdNWwBtX4kPFVHmNMmzG42rhyveA6G2M31rktpjTkRnCzOzqNEo2u1vsfislg2RHDfftsTCfsrZVcy7/GlE1T2Hx1MwqZgrfvfZt/9fsXNsrG2TsuNDyLBTdWVlZ0796d7du3V3h++/bt9OnTx0KtMpHCDNj+keHrB98FJ2/LtkcwGb1eYsHeGCb8eITk3L+HoSbeW7dhKEmSeGnXSzyx+YlGM5TQHKnK17oxYVKxLieH/K2GISnlCMMw0fF6BDf/2RYNwKiurWjt4VDhtfUx6ynWFtPauTXdPbtXeQwbpQ1Phj4JwOKzi9Hpax9MmFrHlmpaOttSVKZj76X0Wu1bVPb3cNSke/3o29qNQ9cPMXHjRKKzo2lh04JF4YuY3H6yGAYWKrDosNRrr73G4sWLWbp0KVFRUbz66qskJCQwffp0wDCk9MQTT1TYJzIyksjISAoKCkhPTycyMpILFy5YovlV2/4hlOSAZ0e49zlLt0YwkezCMqb9eoI5mw3DUI90rv8w1LqYdRxLOQbAorOL0Orrl3QpVM7KPwAw7bBU7rr1SGVlWLdrR9hDhhyP09dy6tQ7cTQ2k/2XM1DKZbctSidJ0t+JxG3H3fFNfHzIeJytnYnPi2dL3JZat8XU6jM09cXWaBKyivBR2/DOkBCWnF3CjJ0zyC3NpaNbR1YOX0kPrx7maLbQxFl0KseECRPIzMzk448/Jjk5mbCwMDZt2oT/jfHx5OTk29a86dq1q/HrkydP8ttvv+Hv709cXFxDNr1q8Ycgcrnh6+FzQSFmyzQHJ+OzePG3CJJzS7BSypk9IpRJ99avhEJOSQ7/OfEf4/eJ+Ylsi9vG0KChpmiycJPyYSmNiYalJEkyFsl0HjcWFzd7PBytScsvJTIxh15BNc9fkySJ/2wz5NpM6OGLbwu7Cq+fTD1JTG4MtkpbRgSPuOPx7FR2TOkwhe8ivmPRmUUMCRyCXGbZ9MrBYV4sOXCVHVGplGn1WCnv3J4TcVn8fCgOgNkj2zD76Ntsjzf09I9uM5p3e76LtcLanM0WmjCLJxS/8MILxMXFUVpaysmTJ7nvvvuMr/3888/s2bOnwvaSJN32aDSBjU4DG183fN1tKvjea9n2CPWm0en5esclxi80DEMFutmz9oW+PNaz/rOhvj71Ndml2bR2bs3znZ4HDL03eun2gqZC/ZSXYNCmp6MvrP908JLTpym9fBmZjQ3qESOQyWT0uFFnqrZ5N/suZ3AsLgsrpZyXHrq9lEB5r83QwKE4WtWsdMekdpNwVDkSkxvDzoSdtWqPOXT3c8Hd0Zr8Ei2HYjLuuH2JRsebf5xBkmBoVyXzL73C9vjtKOVKPuj1AbN7zxaBjVAtiwc3zcqR+ZB2Aexc4eHZlm6NUE/RKfmMmneQr3dcRqeXGNHZh/Uv9aODT/2T0iPSIoyLrX3Q6wOmdJiCvcqeKzlX2Ju4t97Hb0hRmVGczzyPRmf52TlVUajVKJydASgzwYzJ7Bu9Nk6DBqG4MUnh5iKaNWXotTHk2kzp5Y+XumJCbEZxBtsTDL0V1SUS38rRypHH2j8GwI9nfrR4srpcLjNWCq/J0NTc7ZeIzSjEzf0KEbrZXMm5gputGz8N+onxIeNFfo1wRyK4MZXca7BnjuHrgR+DXYvqtxcaLa1Ozw+7rzDiuwOcu56H2lbFNxO78O3Eus2GupVGr+Hjwx8Dhu71bp7dUFurjcvpLzq7yOJvRjV1LPkY4zeMZ+KGifT8rSePbXyMfx35F39d+Ysr2VcaRUJrOeN08Lj65d3oCgrI27QZqLgicXkRzZPx2Wh1Net923YhlTPXcrGzUjDjgdtXL197ZS1avZaObh3p4NqhVu18vP3j2CntuJh1kX3X9tVqX3MorzW17UJqtf8/EQnZLN5/BSu3HZS5LaFAU0AX9y78b/j/6OLRpYFaKzR1IiHEVDTF4NEeFCro/JilWyPU0ZW0Al5fdZrTiTkADGjnwaejO+LhZLoppssvLOdKzhWcrZ15tdurxuendJjC8qjlnM04y7GUY/T0btyV2SVJYu5JQ6V7pVyJRq/hbMZZzmacBUNnBHZKO9q7tifMNYwwtzBC3UJp5dDKIp+8Vf5+FJ8+Xe8CmnkbNiIVF2MVHIxtt27G50M8HXGyUZJXouV8Uh6dfZ2rPY5OLzH3Rq7N030DcXOwvuV1HauiDT1Etem1Keds48yEdhP46dxPLDyzkPta3WfRHo+egS1wsVORVVjGsbgs+gS73bZNiUbH66uPYtXyv6gco5Aw1NB6q8dbqBSqhm+00GSJ4MZU3NrAM9uhOBvkokOsqdHpJX46eJUvtkZTqtXjaKPkoxGhjOnW0qRvCMkFycw7PQ+A17q/hrONs/E1N1s3RrUexYroFSw6u6jRBzc7EnZwPvM8tkpbNo3eRLGmmHOZ5ziXYXhEZUVRpC3iZOpJTqaeNO7nbO1MqGsooW6hxqDH3c7d7O01VY0pYyLx2LEVfjbkchk9Alqw82Iax+Oy7hjcbDiTRHRqPo42Sp7tH3Tb6weTDpJUmISTlRODAwbXqa1TO0zl96jfOZtxlsNJh+nT0nLLbCgVcgZ28OR/J66x9VxKpcHN/23bTYr956is01HJVXzQ6wNGtbl9NWZBuBMR3JiSXA72YpXfpiYuo5B//HGa43GG1WX7t3Hj87Gd8Fbbmvxcnx77lGJtMd08uvFo60dve/2psKf449IfHE0+ypn0M3Ry72TyNpiCVq/l21PfAvBEhydws3UDW/B18mVI4BDA0PMQmxvLuYxznM88z7mMc0RnR5NTmsPBpIMcTDpoPJ6HnQdhrmHGgCfULRS1tWmL45YPS2nqMSxVcuECJefPI1OpUI+8/f71CDQEN0evZjGtkoClnFan5+sdlwF4/r4g1Ha390qUJxI/2vrROi9O52rryti2Y1kWtYyFZxZaNLgBw6yp/524xpbzKXw0IhS5/O/gcGnEev5Km43Cugy1yo35A7+lo3tHC7ZWaMpEcCPctfR6if8eiWfO5osUa3TYWyl4f3gHJvao3xTvquxK2MXuxN0oZYYZH5VNz/Vx8GFY0DD+ivmLRWcX8d1D35m8HaawPmY9cXlxOFs7MzV0aqXbKOQK2ri0oY1LG+On7zJdGZezLxt6d2708sTmxpJWlMauol3sStxl3N/X0Zcw1zA6uXfi0daP1nimUFWMqxTXY1iqPJHYceDDKF1cbnv93htJxSfistDrpQpv3jdbc+o6VzMKaWFvxZN9A297PakgyZgnM75t7YekbvZk6JOsjF7JqbRTHE85btF1Yfq2dsPRWklqXikRiTl093dBp9fxXcQPLDm3CJkc1LJ2/DVqQaUlJgShpkRwI9yVErOKePOPMxyOzQSgd5Arn4/tdNsaI6ZSpClizjFDwvnU0Km0dmld5bZPd3yadTHr2JO4h0vZl2jr0rbKbS2hVFfKD5E/ADCt47RaBR1WCitC3QxDUhMwJFAXaYqIyooy9PBknOdc5jkS8xONj81xm4nJjeGj3h/Vq93lPTfatDT0RUXI7Wp3r/VFReSt3wCA87hxlW4T5qPGRiUnu0jDlfQC2nre/n9TqtXxzU5Dr80LDwRXmqT+x6U/kJDo6d2TAHVArdp5K097T0a3Gc3K6JUsPLPQosGNtVLBQ+09+CsyiS3nkmntJeft/W9z4PoBAOR5/Vk99Qtcbe0t1kaheRDJIcJdRZIkfjuawOCv93E4NhNblYJ/PhLK8mk9zRbYACw4s4DkwmRaOrTk+c7PV7ttkDqIh/0fBmDJ2SVma1Ndrbi4gtSiVDztPJnYbmK9j2ensqO7Z3emhk7l8/s/Z9PoTRyYeICFAxfyVNhTAGyM3UhBWUG9zqNQq1GoDUNddZkOnrdlK/qCAlS+vtj1rDwfykopp5ufoUenqvVuVhxL5HpOMZ5O1jzey/+21zU6jXGZgPIZdPX1dNjTKGVKjiYfJTIt0iTHrKvyWlMbLp5i0sZJHLh+AEmvpPj6BD657308nURgI9SfCG6Eu0ZybjFTfzrOu3+epbBMR48AFza/0p+pfQKqHD4whUvZl/jv+f8C8M6972CrvHMuz7MdnwVgS9wWEvJMW+yxPvLL8ll8djEAM7vMNNtCamprNX18+vBqt1cJUgdRrC02Fo6sD1VA3aeDV0gkrmbSQPmU8MqCm+IyHd/vvgLAiw+1wUaluG2bnQk7ySrJwt3WnQd8H6h1Oyvj4+BjXN34xzM/muSYdXV/Ww9s7VPJd/mWxPxEFPoWFMXPYIDvYIZ3EnX4BNMQwY3Q7EmSxKoTiYR/tY99l9KxUsp5f1h7VjzXmwA3835K1Et6PjnyCVpJywC/Adzve3+N9mvv2p5+Lfuhl/QsPbfUrG2sjV/O/0JOaQ6B6sAalQKoL5lMxti2YwFYdWlVvdf/qeuMqdLLlymOiACFAvWokdVue+9Ni/nd2t5fD8eRnl9KKxdbJtzjW+n+K6NXAjCm7RhUctNNf57WcRpymZz91/dzPvO8yY5bW9cKY7HxW4xMUYyizJ/cKzNxlAXwfyPDxOJ8gsmI4EZo1tLySnj21xP8448z5Jdo6ezrzKaX+zOtfxAKM/bWlFt7ZS0RaRHYKm15+963a7Vvee/NXzF/kVqYao7m1UpGcQa/XvgVgJe7voxS3jApe48EP4KV3IqLWRfr/aZcXoZBU8uk4pw//gDA4cEHUHl4VLttVz9nlHIZybklXMsuNj6fX6Jhwd4YAF4Z0KbS+koxOTGcSD2BQqZgTJsxtWrjnfg5+TE00FC3bNGZRSY9dk3F5sYybds0tOSjK25FztUnkXT2fDSiAx6OpltLShBEcCM0S5Ik8VfkdQZ+tY8dUWlYKeS8OTiE1dN709rDoUHakFWSZVzkbmaXmXjZe9Vq/26e3eju2R2tXssvF34xRxNrZdGZRRRriwlzDWOA34AGO6/aWk14QDhgSLStD6s6DEvpS0vJXfsXAC5VJBLfzM5KSVhLQ27PzUNTSw/EkV2kIcjdnlFdW1a6b/n07/tb3V/rn5eaeLbjs8iQsTNhJ5eyL5n8+NWJz4tn2tZpZJVk0cY5BO31aaC35aF2HlX+fwhCXYngRmh2MgpKeWH5KV5ZEUlusYZQHyfWv9SPFx5ojVLRcD/yc0/MJbc0lxCXECa3n1ynY5T33vxx6Q+yS7JN2bxauZZ/jf9dMrzxzuo+q8GHD8qHpjZd3VSvxOLynpvaTAfP374DXW4uSm9v7Pv1q9E+t9aZyikqY/H+WABefbhtpT+HRZoi1sWsA0yXSHyrIOcgBvoPBBq29+Za/jWe2foM6cXptHZuzZJBi5jeP4wuvs78e1RHMRwlmJwIboRmZfPZZAZ9tY/N51JQymW8+nBb1s7sS4hX/dZIqa0TKSf4K+YvZMj4oPcHdR7C6ePTh/Yt2lOsLWZZ1DITt7Lm5kXOQ6vX0tu7t0VWTu7m0c0kicXG6eCpqeiLi++wtYExkXj0aGSK2xOAK3NrUvHCfbHkl2pp7+3EsI6VJ81uvrqZAk0Bvo6+9PLpVaPz1MVznZ4DYGvcVq7mXjXbecolFyTzzNZnSC1KJUgdxOLwxbjYuPBaeAhrZ/a9rVioIJiCCG6EZiG7sIyXf49gxvJTZBaW0c7LkbUz+/LKw21QNWBvDRim8n5y5BPAkBTa2b1znY8lk8l4tpOh9+b3qN/rPR26Li5lX2JDrGF9l1e6vdLg5wfTJRYrnJ2Rl08HT7jzdPCy+HiKjh4FmQznMaNrfJ4eAS2QySA2o5Co5Dx+PhgHwOsD21Y6M0+SJGMi8bi24ypd4NFUQlqE8IDvA0hIxplv5pJamMrTW58mqTAJfyd/FocvFovzCQ1CBDdCk3coJoNBX+9j3ekkFHIZLz7Ymr9e7GvMe2hov1z4hZjcGFrYtGBWt1n1Pt4AvwEEqgPJ1+Qb3wAb0nenvkNCItw/nFC30AY/fzlTJRYbq4PHx91x2/JEYvv+/VD5+NT4HGo7FSE3FvCb+dspijU6Ovs6M6B95cnI5zPPE5UVhZXcipGtR9b4PHX1fCfDWksbYzeSmF/7NX9qIr0onWnbpnGt4BqtHFqxOHxxg9QQEwQQwY3QhOn0El9tv8TkxUdJyy8l2N2e1TP68MagEKyVNRs+MLVr+ddYeHohAG/c84ZJ6iPJZXKmdZwGwK8XfqVEW1LvY9ZURFoEe67tQSFT8GLXFxvsvJW5ObF41aVVdT5OTWdMSRoNOX+uBapekbg65VPCY9MLAfhHeEiVuSXlQWt4QDguNreXdTC1MLcw+vr0RSfpzLJQZGZxJtO2TSMuLw5ve2+WDFpilgRpQaiKCG6EJik1r4TJi4/wzc7LSBJMuMeXDS/1p8sdKjGbkyRJfHrsU0p0JfTw6sHwoOEmO/aQwCH42PuQVZLFmstrTHbc6kiSxNcnvwZgZOuRBKpvr4HU0MqHpjZf3VznITpjUnF89cFN/u7d6DIyULi54fjAA7U+T3neDRgSjPu2rnw4Jrc0ly1XtwDmSySuTPlK2X/F/EVyQbLJjptdks2z258lNjcWDzsPlgxago9DzXu9BMEURHAjNDn7LqUz9Jv9HInNws5KwdcTuvDZ2E7YWlmmt6bcroRd7Lu2D6Vcyfu93jfpDBCVXGUsRfDT+Z/Q6DQmO3ZV9l/fz6m0U1jJrZjeebrZz1cTNycWb4zdWKdjGKeDx1c/HTxnlWFIynnUKGSq2i+mV95zA/CPQVX32qyLWUeJroS2Lm3rlZ9VW109unKv171o9VqTLRSZW5rLc9uf43L2Zdxt3Vk6aCm+jpUvVigI5iSCG6HJ0Or0fL7lIk8sPWZMGl7/Uj9GNoI1Mgo1hXx67FMAngp9iiB1kMnPMarNKFxtXEkpTGHj1bq9sdeUXtLzzalvAHis/WONZkjBFInFNZkOrrl+ncIDhmKOzuPG1qGl4Olkw+djOvHvUR2556ZenJtJkmRc22ZCyIQGnxJdPnNqzeU1pBel1+tY+WX5TN8+nYtZF2lh04LF4Yvxd7q9dpYgNAQR3AhNQnJuMZMWHWHeHsMKr5N7+rF2Zl+C3RtmQb47mRc5j9SiVFo5tDK+YZiatcKaqaFTAUNBTZ1eZ5bzgGHY51L2JRxUDjwT9ozZzlMX5YnF0dnRnMs4V+v9VeXTwVNSqpwOnrN6DUgSdr16GYOhuhjfw5fHela9/7GUY8TlxWGntGNY0LA6n6eu7vW6ly7uXSjTl/Hz+Z/rfJxCTSEzdszgXOY5nK2dWRy+mCBn0wf4glBTIrgRGr1dF1MZ+s1+jsdl42Ct5PvHuvKvUR0rLTpoCRezLrI8ajkA7/V6Dxul+dbtGB8yHkcrR+Ly4tiRsMMs59DoNHwf8T0AT4U9hbONs1nOU1cVViy+XPsVixXOzsidnIDKq4NLOh05awx5TXXttamp8kTiEcEjsFc1fDVsmUxmzL1ZdWkVWSWVVzKvTpGmiBd2vMDp9NM4WTmxKHwRbVzamLqpglArIrgRGi2NTs+/N0Xx9M8nyC7S0LGlmo0v92N4p8aTnKiX9Pzfkf9DJ+kI9w+nX8uarWBbV/Yqe+Nqx4vPLq53IcnKrL68mmsF13C1ceXx9o+b/PimMK6tYfbS5qubyS/Lr9W+MpnspqTi2/NuCvbvR5uSgsLZGceBA+vf2CqkF6WzO2E3YAhaLaWvT19CXUMp1hbz3wv/rdW+xdpiXtr1EqfSTuGocuTH8B9p16KdmVoqCDUnghuhUbqWXcS4BYf5cZ9hyfon+wTwx4ze+Ls2/Kfb6qy+vJoz6WewV9nzZo83G+Sck9tNxlZpy8Wsixy4fsCkxy7SFLHg9ALAMJvGTmVn0uObSlePrn+vWBxb+xWLy9e6qWw6eHkisfrRR5FbWdWvodVYfXk1WklLV4+utHVpa7bz3IlMJjMOpf5+8XdyS3NrtF+prpRZu2dxLOUY9ip7FgxcQKir5dZBEoSbieBGaHS2nk9h6Df7iUzMwclGycIp3Zn9SKjF1q6pSmZxJl+d/AqAF7u8iKe9Z4Oc19nGmfFtDZ/0Tb3C7PKo5WSWZNLSoSVj25h3SKY+ZDKZsfemLonFVv6VTwfXpKVRsGcPAM7ja7+2TU1p9VpjEVBL9tqUe8D3Adq6tKVQU2gcYq1Oma6MV3e/yqGkQ9gqbZk3YB6d3Ds1QEsFoWZEcCM0GqVaHf9cf57n/3uSvBItXXyd2fhyfwaFNo6ZOrf6z4n/kF+WT/sW7ZnYbmKDnvuJ0CdQyVWcSjvFiZQTJjlmTkmOcUrwi11fRKWo/fTnhjQieESdE4v/XqW44rBU7po/QafDtls3rIODTdbWW+27to/UolRcrF0I9w8323lqSi6TG8t8LItaVu0aQhq9hjf2vsH+6/uxUdjww4Af6ObZraGaKgg1IoIboVGIzyxk7PzD/HSjBs+z/QP53/O98W3ROIdFjiUfY33sekNhzF51L4xZVx52HoxqPQowXe/N0nNLKdAU0NalLUMDh5rkmOZUn8RiVSXTwSW93lhuoS4rEtdG+fTvkW1GYqUw39BXbQz0G2go81GWz4roFZVuo9VreXvf2+xO3I2V3IpvHvqGHl49GrilgnBnIrgRLG7jmWSGf3uAs9dzcbZTsWTqPbw3rANWysb541mmK+P/jvwfYBhS6Oje0SLteDLsSRQyBQeTDtar1hIYChz+dvE3wFAc05yFG02pronFVgEBAGiTk9GXGMpZFB05gubaNeSOjjgNHmTytpZLzE/kYNJBAMa1MW8QVRsKuYJnOxp6b349/ytFmqIKr+v0Ot478B7b4rehkqv4+sGv6ePTxxJNFYQ7ahp/wYRmqUSj4/21Z5n52ynyS7Xc4+/Cppf7M6B9w+Su1NXP538mLi8OVxtXXu72ssXa4evoy5DAIQD1rg+04MwCSnWldPPoRv+W/U3RvAZR18RihbMzckdDYUvNjeng2asM9arUI4Yjt7U1fWNvKK+L1denL75OjWv13iGBQ/B19CW7NLtC/S69pOfDQx+y6eomlDIl/7n/P/Rv1XR+ToS7jwhuBIuITS9g1LxDLDtiGBZ44YFgVjzXCx9n872pmEJiXiI/nvkRgH/0+AdOVk4WbU/5Ans74ncQmxNbp2PE5cbx5+U/AUOvTUOvklsfdU0svnU6uDYri/wdOwHzDkmV6cpYe3kt0DgSiW+llCuNRVp/Pv8zJdoS9JKejw9/zLqYdShkCj6//3Me9HvQwi0VhOqJ4EZocH9FXmfEdweISs7D1d6KX56+lzcHt0OpaNw/jpIk8a9j/6JUV0pP756NIi+ltUtrBvgNQEJiybm69d58H/k9OknH/a3ub5KJoXVNLP47qTiB3LV/gUaDTVgYNu3bm6upbIvfRnZpNp52ntzX6j6znac+RgSNwNvem4ziDFZfXs2/j/6b1ZdXI5fJ+bT/pwz0N9/aP4JgKo373URoFvSSnq9OfsXjG6cwdPlLvLH1e0qU0XQPUrDx5X7c39bd0k2skW3x2zh4/SAquYr3e5q2MGZ9lH/S3hi7kesF12u17/nM82yN24oMGS91fckczTM7tbWaQQGGHJmbh1LuROX/d89Nzo0hqYZKJB7bdmyDJ6HXlEqh4umwpwH48sSXrIxeiQwZn/T9xDgMKgiNnQhuBLOSJIl/Hvo/lp5byumMSBK1e7Dx2oCd/2IuWf+DcZvDeWrLU3xy5BNWXlzJydSTNV5ErCEVlBXw2bHPAEMwEaAOsGyDbhLmFkZv797oJB0/nfupVvt+e+pbAIYFDSOkRYg5mtcgyotpbonbUuPE4vKem/xt2yi7ehWZnR1Ow8xX3+lS9iUi0iJQypSMaTPGbOcxhVFtRuFu645WrwXgn33+yYjgERZulSDUXOP86CA0aen5pZxKyOZkXBabk+eTo9qDJMkoy3gYO2sZHQOKydYmkJifSE5pDidST3AiteJaLe627rR2bk1rl9a0cW5DsHMwwc7BFqm/A/BD5A+kF6fj5+jHMx0bVyFJgGc7Pcvh5MP8eflPnu/0PO52d+4NO5p8lENJh1DKlbzQ5YUGaKX5dPXoSrA6mJjcGDbGbqzRukNWfobgRpeTA4DT0CEoHMz381Xea/Og34M1uj+WZK2w5tXur/LpsU95rftrjGozytJNEoRaEcGNUC86vcSl1HxOxmdzKj6bkwnZxGcWARLWnhuwanEQSZKhzJrIQN+hvDu0Pe6O1gCUaEu4mnuVKzlXuJxzmZicGK5kXyGpMIn04nTSi9M5nHy4wvlaOrQk2DnYEPg4t6aNSxsC1YFYK6wrbZ9Gp6FIW0Sxttjwr6b47+81Nz1/6/e3bHch6wJgKIxZ1bks6R7Pe+ji3oXI9Ej+e+G/vHbPa9VuL0kS35z6BjBMp/Z1bFyzdmpLJpMxtu1YPjv+GasurWJCyIQ7DhtaBfhX+N7FjENShZpC1sesB2BCyASznceURgSPEL01QpMlghuhVvJKNEQm5BiCmYRsIhJyKCjVVthGJpPw9N9Ooa1hLY9XOr/LtC63v9nYKG1o79qe9q4VEzgLNYWGQCfnCpezL3Ml5woxOTGkF6dzveA61wuus+/aPuP2cpkcP0c/7FR2twUs5d3qpjAsaFijXddDJpPxbKdnmblzJiujV/JMx2dQW6ur3H5Xwi7OZpzFVmlrrCvU1I0IHsHXp77mUvYlzmacvWM5AIWLC3IHB/QFBVi3bYtNJ/OVD9gYu5EibREBTgHc63Wv2c4jCIKBCG6EKkmSREJWESfjszlxo2cmOjWfW2fb2lsp6OrnQjd/F7r5OXM4+1d+i94FwIe9PzRO1a0pe5U9ndw73fbmlFOSYwx0LucYgp4rOVfILc0lLi+u2mMq5UrslHbYKm2xU934txbfO6gc6OzeuVbX0dD6t+xPiEsI0dnR/HbxN2Z0nlHpdlq9lm8jDLk2UzpMwc3WrSGbaTZqazXh/uGsj13PH5f+uGNwI5PJsAoOouT0GZzHjTNbgrgkSayMXgkYpn83lkR0QWjOZFJtK841cXl5eajVanJzc3FysuwaJY1NiUbHueu5nIzPNvbMZBSU3badXws7uvsbgpnufi6EeDmikMuQJInvIr5j0dlFALzf830mtDNvF7wkSWSWZHIl5wplurLKgxOlXaOvk2QqW+K28I+9/0BtrWbbmG2VVvX+8/KffHjoQ9TWajaP3oyjlaMFWmoeEWkRPLH5CWyVtuwct/OO11YcGUnBoUO4TZuGzEwVwCPTIpmyeQo2Cht2jNtRbY+aIAhVq837t+i5ucsl5RSzIyqV7RdSORqbRZlOX+F1K4WcsJZOdPd3obt/C7r5O+PhaFPpseafnm8MbN6+922zBzZg+PTtZuvWbHof6mug30D8nfyJz4tn1aVVTA2dWuH1Ul0p807PA+DZjs82q8AGoIt7l1olFtt26YJtly5mbVN5IvHgwMEisBGEBiKCm7uMJElcTMln2/lUtkelcO56XoXX3Rys6e7vfCOYcSHUR42NSnHH4y44vYD5p+cD8I97/sHk9pPN0n6hegq5gmfCnuHDQx/yy/lfmNhuYoUE6JUXV5JSmIKnnWeTSWytjbokFptTTkkOW+O2Ak0nkVgQmgMR3NwFtDo9x+Ky2H7B0ENzLbvY+JpMBt38XBjYwZOH23sS7G5f6zeDxWcX80PkDwC83v11ngh9wqTtF2pneNBw5p2eR0phCn9d+cu4zH9BWYGxZ+2FLi9go6y8B66pq21isTmtvbKWMn0Z7Vu0J9Q11GLtEIS7jQhumqnCUi37LqWz/UIqu6LTyCnSGF+zVsrp38aNgR08eaidp3Fqdl38dO4n45TiV7q9wpNhT9a36UI9qRQqngx9kjnH5rD03FJGtxmNUq7klwu/kFOaQ4BTAI8EP2LpZppNbROLzaWgrIAV0SsALN6DJAh3GxHcNCNp+SXsuJDG9gspHIzJpEz7d/6Mi52Kh9p5MrCDJ/e1dcPOqv63/tfzvzL35FwAXuzyorEMgGB5o9uM5sczP3K94Dqbr26mj08ffjn/CwAvd3u50S79byrjQsaxPna9IcG6xz8aPLeooKyA53c8z/WC67SwaSHKFghCA2vef+GaOUmSiEkvYNuN4aaIhJwKr/u72jGwvSGg6e7vYtLClMujlvPFiS8AmNF5Bs93ft5kxxbqz1Zpy5QOU/jm1DcsObuEsxlnKdYWE+oaysN+D1u6eWZX28RiUyoPbM6kn0FtrWbBwwsqnbUmCIL5iOCmidHpJU4lZBvzZ65mFFZ4vXMrNQM7eDKwgxdtPR3M0hW+4uIK5hybAxhm3FS1nopgWRNCJrD07FJicmOIyY0BYFb3WXfF8IhMJmNcyDjmHJvToInFBWUFTN8xnTPpZ3CycmLRwEW3LVIpCIL5ieCmiTidmMPvxxLYfiGVzMK/155RKWT0CXYzJgR7qc2bJLrq0ir+dfRfADwd9jQvdX3prnizbIocrRyZ2G6iMYm4l3cvenn3snCrGs7woOF8dfKrBkssLg9sTqefxsnKicXhi0VgIwgWIoKbRqxMq2fzuWR+PhRXYcjJ0UbJQ+08GNjBk/vbuuNo0zAL1K25vIaPD38MwNQOU5nV7e7oBWjKHu/wOMuillGsLeaVbq9YujkNSm2tZlDAINbFrGPVpVVmDW4KygqYsWOGCGwEoZEQKxQ3Qml5JSw/msBvxxJIzy8FDD00wzv5MKZbK3oGtUBlwvyZmlh7ZS0fHvwQCYnH2z/Omz3eFIFNE3Eh8wKFmkJ6ePWwdFMaXPmKxTYKG3aN32WWxOJCTSHTt08nMj3SMBQVvogOrh1Mfh5BuNuJFYqbIEmSiEjM4eeDcWw+l4xGZ4g5PRytebyXP2O6e2JtXYaLtQsKecMGNutj1hsDm4khE0Vg08TczW+0Xdy70Nq5NVdyrrAhdgOT2k0y6fFFYCMIjZPoubGAYm0xuaW5ZJdkk16Uxa5LV9lzJY6k/ExkikJkiiLUDmU4O2jQywvJLc2hWGtYeE9traanV096+/Smt09vWjq0NGtbN8Vu4p0D76CX9IxvO573e70vAhuhSVketZw5x+bQxqUNq0esNtnPrwhsBKFh1eb9WwQ3JlKsLSYiNYKc0hyyS7PJKc0hpyTH8O/Nj5IcSnQlJjuvn6OfIdDx7k0P7x44WZnumrbEbeGtfW+hl/SMaTOGD3t/iFzWsL1GglBfuaW5DFg1gFJdKcuGLjNJdfdCTSEzdswgIi0CRytHFocvFoGNIJiZGJaygJySHJ7fUfO1XiRJgaS1Q9LZYyVzwN/ZnVAvb7wcXHG2dsbFxgW1tRoXaxecbZxxtnbGRmnD+YzzHE4+zOGkw5xJP0NCfgIJ0QmsjF6JXCYnzC2M3t6GXp1O7p1QyeuWbLw9fjtv73sbvaRnZOuRIrARmqybE4v/uPRHvYObWwMb0WMjCI2P6LkxkWJtMY9vehwX6xtBiY0LztaGoMRe6UTUdR27zhcSkyoh6exBb8W9ga482SeA8A6edVpgr6CsgOMpx43BTlxeXIXX7ZR29PDqYezZCVQH1qhLflfCLl7f8zpaScsjwY/wcZ+PUcjvXDxTEBqrmxOLd47fWecezkJNIS/seIFTaaeMgY2oGSUIDUMMS1WjIXNurucUs+xIPCuOJZB9o7aTtVLOyC4tmdongA4+pj1/SmEKh5MMgc6R5CNkl2ZXeN3DzsPYq9PLuxeutq63HWNv4l5m7ZmFVq9laOBQ/t3v3yKwEZo8SZIYvW40V3Ku8G7Pd+uUWHxbYDNwEaFuIrARhIYigptqmDu4kSSJI7FZ/HIojm0XUtDf+N9t6WzLlN7+TLjHFxd7K5Of91Z6SU90VrSxV+dU6inK9GUVtglxCTH26nTz7MbxlOO8svsVNHoNgwMG82n/T5t9DSLh7lGfxOIiTREzdswwBDaqGz02IrARhAYlgptqmG1YqkzH2sjr/HIojosp+cbnewe58mTfAB5u74lCbrlZRiXaEk6lneJI0hEOJR0iOju6wutWciv06NHqtQz0H8jn930uAhuhWalrYrEIbAShcRAJxRZwKTWfd9acBcBWpWBUt5ZM7R1AiFfDViOuio3Shj4+fejj04fXeI2M4gyOJh81DGMlHyatKA2AAX4D+Oy+z0RgIzQ7dUksvjWw+TH8RxHYCEITIHpuTOjF307RxdeZcd19Uds1TEkEU5Akiau5V0nIT6Bvy751nmElCI1dZFokUzZPqVFicWWBTZhbWAO2VhCEm4meGwv5/rFulm5CnchkMoKcgwhyDrJ0UwTBrDq7dzauWLwxdmOVicVFmiJe2PmCMbBZOHChCGwEoQkRC5cIgnDXkMlkjG07FjBUuK+s47o8sDmZehIHlQMLBy6ko3vHhm6qIAj1IIIbQRDuKsODhmOtsOZy9mXOZJyp8Nqtgc2PA38UgY0gNEEiuBEE4a5SnlgMsCp6lfF5EdgIQvMhghtBEO4649qOA2Br3FbyyvLEUJQgNDMioVgQhLvOzYnFq6JXceD6AWNgs2DgAjq5d7J0EwVBqAfRcyMIwl3n5sTir099zYnUE9ir7FkwcIFJqoYLgmBZIrgRBOGuVJ5YDGCvsmfhwIUisBGEZkIEN4Ig3JXU1mqmdZyGv5M/Cx4WPTaC0JyIFYoFQRAEQWj0avP+LXpuBEEQBEFoViwe3MybN4/AwEBsbGzo3r07+/fvr3b7vXv30r17d2xsbAgKCmLBggUN1FJBEARBEJoCiwY3K1euZNasWbz33ntERETQv39/hgwZQkJCQqXbX716laFDh9K/f38iIiJ49913efnll1m9enUDt1wQBEEQhMbKojk3PXv2pFu3bsyfP9/4XPv27Rk5ciSffvrpbdu/9dZbrFu3jqioKONz06dP5/Tp0xw+fLhG5xQ5N4IgCILQ9DSJnJuysjJOnjxJeHh4hefDw8M5dOhQpfscPnz4tu0HDRrEiRMn0Gg0le5TWlpKXl5ehYcgCIIgCM2XxYKbjIwMdDodnp6eFZ739PQkJSWl0n1SUlIq3V6r1ZKRkVHpPp9++ilqtdr48PX1Nc0FCIIgCILQKFk8oVgmk1X4XpKk25670/aVPV/unXfeITc31/hITEysZ4sFQRAEQWjMLFZbys3NDYVCcVsvTVpa2m29M+W8vLwq3V6pVOLq6lrpPtbW1lhbW5um0YIgCIIgNHoW67mxsrKie/fubN++vcLz27dvp0+fPpXu07t379u237ZtG/fccw8qlcpsbRUEQRAEoemw6LDUa6+9xuLFi1m6dClRUVG8+uqrJCQkMH36dMAwpPTEE08Yt58+fTrx8fG89tprREVFsXTpUpYsWcIbb7xhqUsQBEEQBKGRsdiwFMCECRPIzMzk448/Jjk5mbCwMDZt2oS/vz8AycnJFda8CQwMZNOmTbz66qv88MMP+Pj48O233zJmzBhLXYIgCIIgCI2MqC0lCIIgCEKj1yTWuREEQRAEQTAHEdwIgiAIgtCsWDTnxhLKR+HESsWCIAiC0HSUv2/XJJvmrgtu8vPzAcRKxYIgCILQBOXn56NWq6vd5q5LKNbr9SQlJeHo6FjtSsh1kZeXh6+vL4mJic0+Wfluula4u65XXGvzdTddr7jW5keSJPLz8/Hx8UEurz6r5q7ruZHL5bRq1cqs53BycmrWP2A3u5uuFe6u6xXX2nzdTdcrrrV5uVOPTTmRUCwIgiAIQrMightBEARBEJoVEdyYkLW1NR999NFdUajzbrpWuLuuV1xr83U3Xa+41rvbXZdQLAiCIAhC8yZ6bgRBEARBaFZEcCMIgiAIQrMightBEARBEJoVEdwIgiAIgtCsiOCmlubNm0dgYCA2NjZ0796d/fv3V7v93r176d69OzY2NgQFBbFgwYIGamndffrpp/To0QNHR0c8PDwYOXIk0dHR1e6zZ88eZDLZbY+LFy82UKvrbvbs2be128vLq9p9muJ9BQgICKj0Ps2cObPS7ZvSfd23bx8jRozAx8cHmUzG2rVrK7wuSRKzZ8/Gx8cHW1tbHnjgAc6fP3/H465evZoOHTpgbW1Nhw4d+PPPP810BbVT3fVqNBreeustOnbsiL29PT4+PjzxxBMkJSVVe8yff/650vtdUlJi5qup3p3u7ZNPPnlbm3v16nXH4zbGe3una63s/shkMr744osqj9lY76s5ieCmFlauXMmsWbN47733iIiIoH///gwZMoSEhIRKt7969SpDhw6lf//+RERE8O677/Lyyy+zevXqBm557ezdu5eZM2dy5MgRtm/fjlarJTw8nMLCwjvuGx0dTXJysvHRpk2bBmhx/YWGhlZo99mzZ6vctqneV4Djx49XuM7t27cDMG7cuGr3awr3tbCwkM6dO/P9999X+vrnn3/O3Llz+f777zl+/DheXl4MHDjQWG+uMocPH2bChAlMmTKF06dPM2XKFMaPH8/Ro0fNdRk1Vt31FhUVcerUKT744ANOnTrFmjVruHTpEo888sgdj+vk5FThXicnJ2NjY2OOS6ixO91bgMGDB1do86ZNm6o9ZmO9t3e61lvvzdKlS5HJZIwZM6ba4zbG+2pWklBj9957rzR9+vQKz7Vr1056++23K93+zTfflNq1a1fhueeff17q1auX2dpoDmlpaRIg7d27t8ptdu/eLQFSdnZ2wzXMRD766COpc+fONd6+udxXSZKkV155RQoODpb0en2lrzfV+wpIf/75p/F7vV4veXl5SXPmzDE+V1JSIqnVamnBggVVHmf8+PHS4MGDKzw3aNAgaeLEiSZvc33cer2VOXbsmARI8fHxVW7z008/SWq12rSNM7HKrnXq1KnSo48+WqvjNIV7W5P7+uijj0oPPfRQtds0hftqaqLnpobKyso4efIk4eHhFZ4PDw/n0KFDle5z+PDh27YfNGgQJ06cQKPRmK2tppabmwtAixYt7rht165d8fb2ZsCAAezevdvcTTOZy5cv4+PjQ2BgIBMnTiQ2NrbKbZvLfS0rK2PZsmU8/fTTdywi21Tva7mrV6+SkpJS4b5ZW1tz//33V/n7C1Xf6+r2aaxyc3ORyWQ4OztXu11BQQH+/v60atWK4cOHExER0TANrKc9e/bg4eFB27ZtefbZZ0lLS6t2++Zwb1NTU9m4cSPPPPPMHbdtqve1rkRwU0MZGRnodDo8PT0rPO/p6UlKSkql+6SkpFS6vVarJSMjw2xtNSVJknjttdfo168fYWFhVW7n7e3Njz/+yOrVq1mzZg0hISEMGDCAffv2NWBr66Znz578+uuvbN26lUWLFpGSkkKfPn3IzMysdPvmcF8B1q5dS05ODk8++WSV2zTl+3qz8t/R2vz+lu9X230ao5KSEt5++20ee+yxagsrtmvXjp9//pl169bx+++/Y2NjQ9++fbl8+XIDtrb2hgwZwvLly9m1axf/+c9/OH78OA899BClpaVV7tMc7u0vv/yCo6Mjo0ePrna7pnpf6+OuqwpeX7d+wpUkqdpPvZVtX9nzjdWLL77ImTNnOHDgQLXbhYSEEBISYvy+d+/eJCYm8uWXX3LfffeZu5n1MmTIEOPXHTt2pHfv3gQHB/PLL7/w2muvVbpPU7+vAEuWLGHIkCH4+PhUuU1Tvq+Vqe3vb133aUw0Gg0TJ05Er9czb968arft1atXhUTcvn370q1bN7777ju+/fZbcze1ziZMmGD8OiwsjHvuuQd/f382btxY7Rt/U7+3S5cuZfLkyXfMnWmq97U+RM9NDbm5uaFQKG6L6tPS0m6L/st5eXlVur1SqcTV1dVsbTWVl156iXXr1rF7925atWpV6/179erVJD8Z2Nvb07Fjxyrb3tTvK0B8fDw7duxg2rRptd63Kd7X8tlvtfn9Ld+vtvs0JhqNhvHjx3P16lW2b99eba9NZeRyOT169Ghy99vb2xt/f/9q293U7+3+/fuJjo6u0+9wU72vtSGCmxqysrKie/fuxtkl5bZv306fPn0q3ad37963bb9t2zbuueceVCqV2dpaX5Ik8eKLL7JmzRp27dpFYGBgnY4TERGBt7e3iVtnfqWlpURFRVXZ9qZ6X2/2008/4eHhwbBhw2q9b1O8r4GBgXh5eVW4b2VlZezdu7fK31+o+l5Xt09jUR7YXL58mR07dtQp8JYkicjIyCZ3vzMzM0lMTKy23U353oKh57V79+507ty51vs21ftaK5bKZG6KVqxYIalUKmnJkiXShQsXpFmzZkn29vZSXFycJEmS9Pbbb0tTpkwxbh8bGyvZ2dlJr776qnThwgVpyZIlkkqlkv744w9LXUKNzJgxQ1Kr1dKePXuk5ORk46OoqMi4za3X+tVXX0l//vmndOnSJencuXPS22+/LQHS6tWrLXEJtfL6669Le/bskWJjY6UjR45Iw4cPlxwdHZvdfS2n0+kkPz8/6a233rrttaZ8X/Pz86WIiAgpIiJCAqS5c+dKERERxtlBc+bMkdRqtbRmzRrp7Nmz0qRJkyRvb28pLy/PeIwpU6ZUmP148OBBSaFQSHPmzJGioqKkOXPmSEqlUjpy5EiDX9+tqrtejUYjPfLII1KrVq2kyMjICr/HpaWlxmPcer2zZ8+WtmzZIsXExEgRERHSU089JSmVSuno0aOWuESj6q41Pz9fev3116VDhw5JV69elXbv3i317t1batmyZZO8t3f6OZYkScrNzZXs7Oyk+fPnV3qMpnJfzUkEN7X0ww8/SP7+/pKVlZXUrVu3CtOjp06dKt1///0Vtt+zZ4/UtWtXycrKSgoICKjyh7ExASp9/PTTT8Ztbr3Wzz77TAoODpZsbGwkFxcXqV+/ftLGjRsbvvF1MGHCBMnb21tSqVSSj4+PNHr0aOn8+fPG15vLfS23detWCZCio6Nve60p39fyaeu3PqZOnSpJkmE6+EcffSR5eXlJ1tbW0n333SedPXu2wjHuv/9+4/blVq1aJYWEhEgqlUpq165downsqrveq1evVvl7vHv3buMxbr3eWbNmSX5+fpKVlZXk7u4uhYeHS4cOHWr4i7tFdddaVFQkhYeHS+7u7pJKpZL8/PykqVOnSgkJCRWO0VTu7Z1+jiVJkhYuXCjZ2tpKOTk5lR6jqdxXc5JJ0o1MSEEQBEEQhGZA5NwIgiAIgtCsiOBGEARBEIRmRQQ3giAIgiA0KyK4EQRBEAShWRHBjSAIgiAIzYoIbgRBEARBaFZEcCMIgiAIQrMightBEO5KMpmMtWvXWroZgiCYgQhuBEFocE8++SQymey2x+DBgy3dNEEQmgGlpRsgCMLdafDgwfz0008VnrO2trZQawRBaE5Ez40gCBZhbW2Nl5dXhYeLiwtgGDKaP38+Q4YMwdbWlsDAQFatWlVh/7Nnz/LQQw9ha2uLq6srzz33HAUFBRW2Wbp0KaGhoVhbW+Pt7c2LL75Y4fWMjAxGjRqFnZ0dbdq0Yd26dcbXsrOzmTx5Mu7u7tja2tKmTZvbgjFBEBonEdwIgtAoffDBB4wZM4bTp0/z+OOPM2nSJKKiogAoKipi8ODBuLi4cPz4cVatWsWOHTsqBC/z589n5syZPPfcc5w9e5Z169bRunXrCuf45z//yfjx4zlz5gxDhw5l8uTJZGVlGc9/4cIFNm/eTFRUFPPnz8fNza3h/gMEQag7S1fuFATh7jN16lRJoVBI9vb2FR4ff/yxJEmGyvTTp0+vsE/Pnj2lGTNmSJIkST/++KPk4uIiFRQUGF/fuHGjJJfLpZSUFEmSJMnHx0d67733qmwDIL3//vvG7wsKCiSZTCZt3rxZkiRJGjFihPTUU0+Z5oIFQWhQIudGEASLePDBB5k/f36F51q0aGH8unfv3hVe6927N5GRkQBERUXRuXNn7O3tja/37dsXvV5PdHQ0MpmMpKQkBgwYUG0bOnXqZPza3t4eR0dH0tLSAJgxYwZjxozh1KlThIeHM3LkSPr06VOnaxUEoWGJ4EYQBIuwt7e/bZjoTmQyGQCSJBm/rmwbW1vbGh1PpVLdtq9erwdgyJAhxMfHs3HjRnbs2MGAAQOYOXMmX375Za3aLAhCwxM5N4IgNEpHjhy57ft27doB0KFDByIjIyksLDS+fvDgQeRyOW3btsXR0ZGAgAB27txZrza4u7vz5JNPsmzZMr7++mt+/PHHeh1PEISGIXpuBEGwiNLSUlJSUio8p1QqjUm7q1at4p577qFfv34sX76cY8eOsWTJEgAmT57MRx99xNSpU5k9ezbp6em89NJLTJkyBU9PTwBmz57N9OnT8fDwYMiQIeTn53Pw4EFeeumlGrXvww8/pHv37oSGhlJaWsqGDRto3769Cf8HBEEwFxHcCIJgEVu2bMHb27vCcyEhIVy8eBEwzGRasWIFL7zwAl5eXixfvpwOHToAYGdnx9atW3nllVfo0aMHdnZ2jBkzhrlz5xqPNXXqVEpKSvjqq6944403cHNzY+zYsTVun5WVFe+88w5xcXHY2trSv39/VqxYYYIrFwTB3GSSJEmWboQgCMLNZDIZf/75JyNHjrR0UwRBaIJEzo0gCIIgCM2KCG4EQRAEQWhWRM6NIAiNjhgtFwShPkTPjSAIgiAIzYoIbgRBEARBaFZEcCMIgiAIQrMightBEARBEJoVEdwIgiAIgtCsiOBGEARBEIRmRQQ3giAIgiA0KyK4EQRBEAShWRHBjSAIgiAIzcr/A2yahgtiotOWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# accuracy plot\n",
    "plt.plot(history_4.history['task_1_output_accuracy'])\n",
    "plt.plot(history_4.history['task_2_output_accuracy'])\n",
    "plt.plot(history_4.history['val_task_1_output_accuracy'])\n",
    "plt.plot(history_4.history['val_task_2_output_accuracy'])\n",
    "plt.title('Model Accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()\n",
    "\n",
    "# loss plot\n",
    "plt.plot(history_4.history['loss'])\n",
    "plt.plot(history_4.history['task_1_output_loss'])\n",
    "plt.plot(history_4.history['task_2_output_loss'])\n",
    "plt.plot(history_4.history['val_task_1_output_loss'])\n",
    "plt.plot(history_4.history['val_task_2_output_loss'])\n",
    "plt.title('Model Loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['combined' ,'train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84230cad",
   "metadata": {
    "papermill": {
     "duration": 1.59753,
     "end_time": "2023-04-23T17:36:58.466671",
     "exception": false,
     "start_time": "2023-04-23T17:36:56.869141",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 2.5. Case 5: Gamma = 0.4 - The model will receive loss 40% from task 1 and 60% task 2.\n",
    "##      (Dropout = 0.4, Optimizer = SGD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ac913774",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:37:01.668429Z",
     "iopub.status.busy": "2023-04-23T17:37:01.668065Z",
     "iopub.status.idle": "2023-04-23T17:37:06.566729Z",
     "shell.execute_reply": "2023-04-23T17:37:06.565721Z"
    },
    "papermill": {
     "duration": 6.492807,
     "end_time": "2023-04-23T17:37:06.569952",
     "exception": false,
     "start_time": "2023-04-23T17:37:00.077145",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define parameters and generate model\n",
    "gamma=0.4\n",
    "dropout = 0.4\n",
    "optimizer = 'SGD'\n",
    "model_5 = create_model(dropout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b5b74e4c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:37:09.961639Z",
     "iopub.status.busy": "2023-04-23T17:37:09.960619Z",
     "iopub.status.idle": "2023-04-23T17:37:09.992500Z",
     "shell.execute_reply": "2023-04-23T17:37:09.991546Z"
    },
    "papermill": {
     "duration": 1.635348,
     "end_time": "2023-04-23T17:37:09.994639",
     "exception": false,
     "start_time": "2023-04-23T17:37:08.359291",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# compile model\n",
    "model_5.compile(loss={'task_1_output': 'categorical_crossentropy',\n",
    "                    'task_2_output': 'categorical_crossentropy'},\n",
    "              loss_weights={'task_1_output': gamma,\n",
    "                            'task_2_output': 1-gamma},\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7372b93c",
   "metadata": {
    "papermill": {
     "duration": 1.622241,
     "end_time": "2023-04-23T17:37:13.222067",
     "exception": false,
     "start_time": "2023-04-23T17:37:11.599826",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Train & Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b5155509",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:37:16.565268Z",
     "iopub.status.busy": "2023-04-23T17:37:16.564230Z",
     "iopub.status.idle": "2023-04-23T17:53:02.362260Z",
     "shell.execute_reply": "2023-04-23T17:53:02.361202Z"
    },
    "papermill": {
     "duration": 947.411653,
     "end_time": "2023-04-23T17:53:02.364555",
     "exception": false,
     "start_time": "2023-04-23T17:37:14.952902",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "333/333 [==============================] - 93s 145ms/step - loss: 3.6301 - task_1_output_loss: 4.6151 - task_2_output_loss: 2.9734 - task_1_output_accuracy: 0.0130 - task_2_output_accuracy: 0.0809 - val_loss: 199.1914 - val_task_1_output_loss: 208.9479 - val_task_2_output_loss: 192.6871 - val_task_1_output_accuracy: 0.0123 - val_task_2_output_accuracy: 0.0511\n",
      "Epoch 2/20\n",
      "333/333 [==============================] - 44s 134ms/step - loss: 3.4954 - task_1_output_loss: 4.5489 - task_2_output_loss: 2.7931 - task_1_output_accuracy: 0.0210 - task_2_output_accuracy: 0.1330 - val_loss: 13.9311 - val_task_1_output_loss: 15.1078 - val_task_2_output_loss: 13.1465 - val_task_1_output_accuracy: 0.0095 - val_task_2_output_accuracy: 0.0504\n",
      "Epoch 3/20\n",
      "333/333 [==============================] - 45s 136ms/step - loss: 3.4064 - task_1_output_loss: 4.4648 - task_2_output_loss: 2.7009 - task_1_output_accuracy: 0.0331 - task_2_output_accuracy: 0.1561 - val_loss: 4.1853 - val_task_1_output_loss: 5.1337 - val_task_2_output_loss: 3.5531 - val_task_1_output_accuracy: 0.0209 - val_task_2_output_accuracy: 0.0717\n",
      "Epoch 4/20\n",
      "333/333 [==============================] - 45s 135ms/step - loss: 3.3103 - task_1_output_loss: 4.3481 - task_2_output_loss: 2.6185 - task_1_output_accuracy: 0.0454 - task_2_output_accuracy: 0.1788 - val_loss: 3.8616 - val_task_1_output_loss: 4.8041 - val_task_2_output_loss: 3.2332 - val_task_1_output_accuracy: 0.0153 - val_task_2_output_accuracy: 0.0755\n",
      "Epoch 5/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 3.2311 - task_1_output_loss: 4.2404 - task_2_output_loss: 2.5581 - task_1_output_accuracy: 0.0527 - task_2_output_accuracy: 0.1955 - val_loss: 3.7847 - val_task_1_output_loss: 4.8916 - val_task_2_output_loss: 3.0468 - val_task_1_output_accuracy: 0.0153 - val_task_2_output_accuracy: 0.0976\n",
      "Epoch 6/20\n",
      "333/333 [==============================] - 45s 136ms/step - loss: 3.1467 - task_1_output_loss: 4.1205 - task_2_output_loss: 2.4974 - task_1_output_accuracy: 0.0633 - task_2_output_accuracy: 0.2181 - val_loss: 6.1619 - val_task_1_output_loss: 8.2849 - val_task_2_output_loss: 4.7465 - val_task_1_output_accuracy: 0.0104 - val_task_2_output_accuracy: 0.0561\n",
      "Epoch 7/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 3.1084 - task_1_output_loss: 4.0475 - task_2_output_loss: 2.4823 - task_1_output_accuracy: 0.0704 - task_2_output_accuracy: 0.2182 - val_loss: 4.8730 - val_task_1_output_loss: 6.9613 - val_task_2_output_loss: 3.4808 - val_task_1_output_accuracy: 0.0188 - val_task_2_output_accuracy: 0.0888\n",
      "Epoch 8/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 3.0204 - task_1_output_loss: 3.9346 - task_2_output_loss: 2.4110 - task_1_output_accuracy: 0.0817 - task_2_output_accuracy: 0.2418 - val_loss: 3.7186 - val_task_1_output_loss: 4.7636 - val_task_2_output_loss: 3.0220 - val_task_1_output_accuracy: 0.0267 - val_task_2_output_accuracy: 0.1112\n",
      "Epoch 9/20\n",
      "333/333 [==============================] - 45s 135ms/step - loss: 2.9453 - task_1_output_loss: 3.8354 - task_2_output_loss: 2.3519 - task_1_output_accuracy: 0.0968 - task_2_output_accuracy: 0.2626 - val_loss: 3.5756 - val_task_1_output_loss: 4.7165 - val_task_2_output_loss: 2.8150 - val_task_1_output_accuracy: 0.0447 - val_task_2_output_accuracy: 0.1593\n",
      "Epoch 10/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.8717 - task_1_output_loss: 3.7449 - task_2_output_loss: 2.2895 - task_1_output_accuracy: 0.1071 - task_2_output_accuracy: 0.2832 - val_loss: 4.2053 - val_task_1_output_loss: 5.3756 - val_task_2_output_loss: 3.4252 - val_task_1_output_accuracy: 0.0313 - val_task_2_output_accuracy: 0.1211\n",
      "Epoch 11/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.8483 - task_1_output_loss: 3.7074 - task_2_output_loss: 2.2756 - task_1_output_accuracy: 0.1116 - task_2_output_accuracy: 0.2868 - val_loss: 4.2372 - val_task_1_output_loss: 5.5992 - val_task_2_output_loss: 3.3292 - val_task_1_output_accuracy: 0.0219 - val_task_2_output_accuracy: 0.1319\n",
      "Epoch 12/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.7917 - task_1_output_loss: 3.6387 - task_2_output_loss: 2.2271 - task_1_output_accuracy: 0.1209 - task_2_output_accuracy: 0.3023 - val_loss: 4.9528 - val_task_1_output_loss: 6.5358 - val_task_2_output_loss: 3.8974 - val_task_1_output_accuracy: 0.0269 - val_task_2_output_accuracy: 0.1285\n",
      "Epoch 13/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.7221 - task_1_output_loss: 3.5584 - task_2_output_loss: 2.1646 - task_1_output_accuracy: 0.1308 - task_2_output_accuracy: 0.3178 - val_loss: 3.1288 - val_task_1_output_loss: 4.0690 - val_task_2_output_loss: 2.5020 - val_task_1_output_accuracy: 0.0664 - val_task_2_output_accuracy: 0.2308\n",
      "Epoch 14/20\n",
      "333/333 [==============================] - 45s 135ms/step - loss: 2.6334 - task_1_output_loss: 3.4608 - task_2_output_loss: 2.0818 - task_1_output_accuracy: 0.1429 - task_2_output_accuracy: 0.3430 - val_loss: 3.1376 - val_task_1_output_loss: 4.1312 - val_task_2_output_loss: 2.4752 - val_task_1_output_accuracy: 0.0791 - val_task_2_output_accuracy: 0.2453\n",
      "Epoch 15/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.5520 - task_1_output_loss: 3.3719 - task_2_output_loss: 2.0054 - task_1_output_accuracy: 0.1556 - task_2_output_accuracy: 0.3640 - val_loss: 4.1392 - val_task_1_output_loss: 5.3093 - val_task_2_output_loss: 3.3592 - val_task_1_output_accuracy: 0.0400 - val_task_2_output_accuracy: 0.1356\n",
      "Epoch 16/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.5001 - task_1_output_loss: 3.3145 - task_2_output_loss: 1.9572 - task_1_output_accuracy: 0.1625 - task_2_output_accuracy: 0.3804 - val_loss: 5.5358 - val_task_1_output_loss: 7.6472 - val_task_2_output_loss: 4.1282 - val_task_1_output_accuracy: 0.0421 - val_task_2_output_accuracy: 0.1612\n",
      "Epoch 17/20\n",
      "333/333 [==============================] - 45s 135ms/step - loss: 2.4547 - task_1_output_loss: 3.2698 - task_2_output_loss: 1.9112 - task_1_output_accuracy: 0.1688 - task_2_output_accuracy: 0.3949 - val_loss: 5.3075 - val_task_1_output_loss: 6.8215 - val_task_2_output_loss: 4.2982 - val_task_1_output_accuracy: 0.0471 - val_task_2_output_accuracy: 0.1499\n",
      "Epoch 18/20\n",
      "333/333 [==============================] - 45s 134ms/step - loss: 2.4671 - task_1_output_loss: 3.2779 - task_2_output_loss: 1.9265 - task_1_output_accuracy: 0.1700 - task_2_output_accuracy: 0.3909 - val_loss: 4.1860 - val_task_1_output_loss: 5.2473 - val_task_2_output_loss: 3.4785 - val_task_1_output_accuracy: 0.0451 - val_task_2_output_accuracy: 0.1431\n",
      "Epoch 19/20\n",
      "333/333 [==============================] - 44s 133ms/step - loss: 2.3823 - task_1_output_loss: 3.1846 - task_2_output_loss: 1.8474 - task_1_output_accuracy: 0.1847 - task_2_output_accuracy: 0.4136 - val_loss: 3.0516 - val_task_1_output_loss: 3.9563 - val_task_2_output_loss: 2.4484 - val_task_1_output_accuracy: 0.0884 - val_task_2_output_accuracy: 0.2765\n",
      "Epoch 20/20\n",
      "333/333 [==============================] - 45s 136ms/step - loss: 2.2482 - task_1_output_loss: 3.0418 - task_2_output_loss: 1.7191 - task_1_output_accuracy: 0.2011 - task_2_output_accuracy: 0.4528 - val_loss: 3.2913 - val_task_1_output_loss: 4.2610 - val_task_2_output_loss: 2.6449 - val_task_1_output_accuracy: 0.0869 - val_task_2_output_accuracy: 0.2552\n"
     ]
    }
   ],
   "source": [
    "# train model\n",
    "history_5 = model_5.fit({'input': X_train},\n",
    "                        {'task_1_output': y_train, 'task_2_output': y_train_super}, \n",
    "                        validation_split=0.15,\n",
    "                        epochs=epochs, \n",
    "                        batch_size=batch_size,\n",
    "                        verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b2cfb353",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:53:06.422968Z",
     "iopub.status.busy": "2023-04-23T17:53:06.421936Z",
     "iopub.status.idle": "2023-04-23T17:53:06.429382Z",
     "shell.execute_reply": "2023-04-23T17:53:06.428260Z"
    },
    "papermill": {
     "duration": 1.996477,
     "end_time": "2023-04-23T17:53:06.432513",
     "exception": false,
     "start_time": "2023-04-23T17:53:04.436036",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train loss: 2.2481513023376465\n",
      "\n",
      "Train task 1 loss: 3.0417516231536865\n",
      "Train task 1 acc: 0.20105881989002228\n",
      "\n",
      "Train task 2 loss: 1.7190823554992676\n",
      "Train task 2 acc: 0.45284706354141235\n"
     ]
    }
   ],
   "source": [
    "# train model results\n",
    "print('Train loss:', history_5.history['loss'][-1])\n",
    "\n",
    "print('\\nTrain task 1 loss:', history_5.history['task_1_output_loss'][-1])\n",
    "print('Train task 1 acc:', history_5.history['task_1_output_accuracy'][-1])\n",
    "\n",
    "print('\\nTrain task 2 loss:', history_5.history['task_2_output_loss'][-1])\n",
    "print('Train task 2 acc:', history_5.history['task_2_output_accuracy'][-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "394900dc",
   "metadata": {
    "papermill": {
     "duration": 1.943052,
     "end_time": "2023-04-23T17:53:10.375584",
     "exception": false,
     "start_time": "2023-04-23T17:53:08.432532",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Evaluate Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "85f9bce0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:53:14.558891Z",
     "iopub.status.busy": "2023-04-23T17:53:14.558526Z",
     "iopub.status.idle": "2023-04-23T17:53:27.997031Z",
     "shell.execute_reply": "2023-04-23T17:53:27.995928Z"
    },
    "papermill": {
     "duration": 15.436878,
     "end_time": "2023-04-23T17:53:27.999717",
     "exception": false,
     "start_time": "2023-04-23T17:53:12.562839",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# test model results\n",
    "evaluation_results = model_5.evaluate(\n",
    "                        X_test, \n",
    "                        [y_test, y_test_super],\n",
    "                        verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "440c2153",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:53:32.605194Z",
     "iopub.status.busy": "2023-04-23T17:53:32.604182Z",
     "iopub.status.idle": "2023-04-23T17:53:32.612592Z",
     "shell.execute_reply": "2023-04-23T17:53:32.611644Z"
    },
    "papermill": {
     "duration": 2.09906,
     "end_time": "2023-04-23T17:53:32.614827",
     "exception": false,
     "start_time": "2023-04-23T17:53:30.515767",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss: 3.2708852291107178\n",
      "\n",
      "Test task 1 loss: 4.231666564941406\n",
      "Test task 1 acc: 0.093299999833107\n",
      "\n",
      "Test task 2 loss: 2.6303629875183105\n",
      "Test task 2 acc: 0.25049999356269836\n"
     ]
    }
   ],
   "source": [
    "# test model results\n",
    "print('Test loss:', evaluation_results[0])\n",
    "\n",
    "print('\\nTest task 1 loss:', evaluation_results[1])\n",
    "print('Test task 1 acc:', evaluation_results[3])\n",
    "\n",
    "print('\\nTest task 2 loss:', evaluation_results[2])\n",
    "print('Test task 2 acc:', evaluation_results[4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d2e19a2",
   "metadata": {
    "papermill": {
     "duration": 2.010381,
     "end_time": "2023-04-23T17:53:36.772477",
     "exception": false,
     "start_time": "2023-04-23T17:53:34.762096",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0a7e77a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-23T17:53:40.746053Z",
     "iopub.status.busy": "2023-04-23T17:53:40.745663Z",
     "iopub.status.idle": "2023-04-23T17:53:41.207940Z",
     "shell.execute_reply": "2023-04-23T17:53:41.206949Z"
    },
    "papermill": {
     "duration": 2.533851,
     "end_time": "2023-04-23T17:53:41.210149",
     "exception": false,
     "start_time": "2023-04-23T17:53:38.676298",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/0KNHD5hMJtxxxx145ZVXauW4S5YswYsvvogjR46gZcuW+Pzzz9GgQYNq7++BBx6AyWTCyy+/jFmzZiEoKAidOnXCtGnTAADBwcH44osv8PDDD6NLly5o3749XnzxReUmaX8giUBobPOy7OxshIaGIisrCyEhIbW2X9lqxcnO8QCANgf2Q32N9VhJRFQThYWFSE5ORlxcHAwGg6/DIR8p7+egst/frGrwIpVOB5Xr7nQ2ZREREfkGkx0v4xNZREREvuXTZGfx4sXo0aMHzGYzGjVqhNGjR+PkyZMeZYQQmDdvHmJjY2E0GtGvXz/8/PPPHmUsFgsef/xxNGjQAEFBQRg5ciQuXLhQl6dSJqUXZdbsEBER+YRPk53du3fjsccew/79+7F9+3bY7XYMHjzY43G8l156Ca+88gpWrlyJgwcPIjo6GrfccgtycnKUMtOmTcPmzZuxceNGfPfdd8jNzcVtt90Gh8M3XYoXxSeyiIiIfMunT2N9/fXXHvNr165Fo0aNcOjQIfz1r3+FEAIrVqzA7NmzlW6q169fj6ioKHzwwQd46KGHkJWVhdWrV+O9997DoEGDAADvv/8+mjZtih07dmDIEN90PuV2tRkr06dxEBERXav86p6drCznsAoREREAgOTkZKSmpmLw4MFKGb1ej5tvvhn79u0DABw6dAg2m82jTGxsLDp27KiUKc5isSA7O9tj8hZ2LEhERORbfpPsCCEwffp09O3bVxn7IzU1FQBKdLIUFRWlrEtNTYVOp0O4q7motDLFLV68GKGhocpUdLTY2sZmLCIiIt/ym2Rn6tSp+Omnn/Dhhx+WWFe8i+7yxhWpTJlnnnkGWVlZynT+/PnqB14BPo1FRETkW36R7Dz++OPYsmULdu3ahSZNmijLo6OjAaBEDU1aWppS2xMdHQ2r1YqMYslE0TLF6fV6hISEeEzewmYsIiIi3/JpsiOEwNSpU7Fp0ybs3LlTGVTMLS4uDtHR0di+fbuyzGq1Yvfu3ejduzcAoFu3btBqtR5lUlJScOzYMaWML6nDwwAw2SEioupr0aIFVqxY4eswSkhISMDo0aN9HUaFfJrsPPbYY3j//ffxwQcfwGw2IzU1FampqcrIqZIkYdq0aVi0aBE2b96MY8eOISEhASaTCRMmTAAAhIaG4v7778eTTz6J//3vfzhy5AjuuecedOrUSXk6y5fYjEVEdO3p16+fMnZUbTh48CAefPDBGu3DXxKmF154Ab1794bJZEKY6zvS23z66PmqVasAOH8oilq7di0SEhIAALNmzUJBQQEeffRRZGRkoGfPnvjmm29gNpuV8suXL4dGo8HYsWNRUFCAgQMHYt26dVCr1XV1KmXSFB0MtBL3GhER0bVBCAGHwwGNpuKv4oYNG9ZBRHXDarXirrvuQq9evbB69eo6OabPm7FKm9yJDuCs3Zk3bx5SUlJQWFiI3bt3K09ruRkMBrz++uu4fPky8vPz8cUXX3j1CauqcNfsCJsNIj/ft8EQEZHXJSQkYPfu3Xj11VchSRIkScKZM2eQmJgISZKwbds2dO/eHXq9Hnv27MHp06cxatQoREVFITg4GD169MCOHTs89lm8VkaSJPz73//G7bffDpPJhNatW2PLli1lxtSvXz+cPXsWTzzxhBITAFy+fBnjx49HkyZNYDKZ0KlTpxIPCn3yySfo1KkTjEYjIiMjMWjQII/Of4s6dOgQGjVqhBdeeKHMWObPn48nnngCnTp1quijrDV+cYNyfSaZTJB0OgC8b4eIqMaEAKx5vpmEqFSIr776Knr16oUpU6YgJSUFKSkpHn+Az5o1C4sXL8bx48fRuXNn5ObmYvjw4dixYweOHDmCIUOGYMSIETh37ly5x5k/fz7Gjh2Ln376CcOHD8fEiRNx5cqVUstu2rQJTZo0wYIFC5SYAOeI4t26dcOXX36JY8eO4cEHH8SkSZNw4MABAM57YMePH4/77rsPx48fR2JiIsaMGQNRymeRmJiIgQMHYv78+Zg9e3alPqu64tNmrGuBJElQh4XBnpYGe0YmtI0b+zokIqLAZcsHFsX65tjPXgR0QRUWCw0NhU6ng8lkUp4qLmrBggW45ZZblPnIyEjEx8cr8wsXLsTmzZuxZcsWTJ06tczjJCQkYPz48QCARYsW4fXXX8f333+PoUOHligbEREBtVoNs9nsEVPjxo0xY8YMZf7xxx/H119/jY8//hg9e/ZESkoK7HY7xowZg+bNmwNAqTUyn3/+OSZNmoS33npLicmfsGanDvDxcyIicuvevbvHfF5eHmbNmoX27dsjLCwMwcHBOHHiRIU1O507d1beBwUFwWw2Iy0trUqxOBwOvPDCC+jcuTMiIyMRHByMb775Rjl2fHw8Bg4ciE6dOuGuu+7CO++8U6KrlwMHDuCOO+7A+vXr/TLRAVizUyfYizIRUS3Rmpw1LL46di0ICvKsHZo5cya2bduGpUuXolWrVjAajbjzzjthtVrLD0er9ZiXJAmyLFcplmXLlmH58uVYsWIFOnXqhKCgIEybNk05tlqtxvbt27Fv3z588803eP311zF79mwcOHBA6S6mZcuWiIyMxJo1a3DrrbdC57p1w58w2fGiI9+cQ/KPlxBj7ogwHODj50RENSVJlWpK8jWdTgeHw1Gpsnv27EFCQgJuv/12AEBubi7OnDlTJzHt2bMHo0aNwj333AMAkGUZp06dwvXXX6+UkSQJffr0QZ8+ffD888+jefPm2Lx5M6ZPnw4AaNCgATZt2oR+/frh7rvvxn/+858SiZivsRnLi7LTC5ByOgt5+kgArNkhIrpWtGjRAgcOHMCZM2eQnp5ebo1Lq1atsGnTJiQlJeHHH3/EhAkTqlxDU9mYvv32W/zxxx9IT09Xju2uuTl+/Dgeeughj1ELDhw4gEWLFuGHH37AuXPnsGnTJly6dMkjGQKARo0aYefOnThx4gTGjx8Pu91eZhznzp1DUlISzp07B4fDgaSkJCQlJSE3N7fWz9mNyY4XGczOzNamDQbAZIeI6FoxY8YMqNVqtG/fHg0bNiz3/pvly5cjPDwcvXv3xogRIzBkyBB07dq11mNasGABzpw5g5YtWyr99syZMwddu3bFkCFD0K9fP0RHR3v0iBwSEoJvv/0Ww4cPR5s2bfDcc89h2bJlGDZsWIn9R0dHY+fOnTh69CgmTpxYZs3W888/jy5dumDu3LnIzc1Fly5d0KVLF/zwww+1fs5ukijt+bFrTHZ2NkJDQ5GVlVWr42T9tOsC9nz0K5pE5KPNppkIGT4cjV9ZVmv7JyKqzwoLC5GcnIy4uDgYDAZfh0M+Ut7PQWW/v1mz40VGV82OVbCfHSIiIl9hsuNFxmBnsmNxOO8DZ7JDRERU95jseJHR7KzRsVid3XLbM/k0FhERUV1jsuNFBlfNTmGhgIAER2aWjyMiIiK69jDZ8SJ3sgMANm0QRH4+ZIvFhxERERFde5jseJFarYLe5Lxfx2YIBcD7doiIiOoakx0vc9fu2MOiADDZISIiqmtMdrzMGOx67Dy0kfM1I9OH0RAREV17mOx4mbuvHXtwBADAwSeyiIiI6hSTHS9z97VjM3LkcyIiqp4WLVpgxYoVvg6jhISEBI/hJfwVkx0vM7j62rHpzQCY7BARXQv69euHadOm1dr+Dh48iAcffLBG+/CHhOnMmTO4//77ERcXB6PRiJYtW2Lu3LmwWq1ePa7Gq3unqzU7miAAgCODzVhERAQIIeBwOKDRVPxV7B64M9CdOHECsizjrbfeQqtWrXDs2DFMmTIFeXl5WLp0qdeOy5odL3MnO1bJOXgZa3aIiOq3hIQE7N69G6+++iokSYIkSThz5gwSExMhSRK2bduG7t27Q6/XY8+ePTh9+jRGjRqFqKgoBAcHo0ePHtixY4fHPovXykiShH//+9+4/fbbYTKZ0Lp1a2zZsqXMmPr164ezZ8/iiSeeUGICgMuXL2P8+PFo0qQJTCYTOnXqhA8//NBj208++QSdOnWC0WhEZGQkBg0ahLy8vFKPc+jQITRq1AgvvPBCqeuHDh2KtWvXYvDgwbjuuuswcuRIzJgxA5s2barMR1ttTHa8zN2MZXENBmpnskNEVG1CCOTb8n0yCSEqFeOrr76KXr16YcqUKUhJSUFKSgqaNm2qrJ81axYWL16M48ePo3PnzsjNzcXw4cOxY8cOHDlyBEOGDMGIESNw7ty5co8zf/58jB07Fj/99BOGDx+OiRMn4sqVK6WW3bRpE5o0aYIFCxYoMQHOEcW7deuGL7/8EseOHcODDz6ISZMm4cCBAwCAlJQUjB8/Hvfddx+OHz+OxMREjBkzptTPIjExEQMHDsT8+fMxe/bsSn1WAJCVlYWIiIhKl68ONmN5mTIYqF0NgI+eExHVRIG9AD0/6OmTYx+YcAAmranCcqGhodDpdDCZTIiOji6xfsGCBbjllluU+cjISMTHxyvzCxcuxObNm7FlyxZMnTq1zOMkJCRg/PjxAIBFixbh9ddfx/fff4+hQ4eWKBsREQG1Wg2z2ewRU+PGjTFjxgxl/vHHH8fXX3+Njz/+GD179kRKSgrsdjvGjBmD5s2bAwA6depUYv+ff/45Jk2ahLfeekuJqTJOnz6N119/HcuWLav0NtXBZMfLig4GKsBmLCKia1337t095vPy8jB//nx8+eWXuHjxIux2OwoKCiqs2encubPyPigoCGazGWlpaVWKxeFwYMmSJfjoo4/wxx9/wGKxwGKxICjIeZ9pfHw8Bg4ciE6dOmHIkCEYPHgw7rzzToSHhyv7OHDgAL788kt8/PHHuP322yt97IsXL2Lo0KG466678MADD1Qp7qpisuNl7podWQYcagOTHSKiGjBqjDgw4YDPjl0b3ImE28yZM7Ft2zYsXboUrVq1gtFoxJ133lnhE0pardZjXpIkyLJcpViWLVuG5cuXY8WKFejUqROCgoIwbdo05dhqtRrbt2/Hvn378M033+D111/H7NmzceDAAcTFxQEAWrZsicjISKxZswa33nordDpdhce9ePEi+vfvj169euHtt9+uUszVwWTHyzQ6NTR6NewWB6w6MzTZlyDsdkiVuPueiIg8SZJUqaYkX9PpdHA4HJUqu2fPHiQkJCi1Irm5uThz5kydxLRnzx6MGjUK99xzDwBAlmWcOnUK119/vVJGkiT06dMHffr0wfPPP4/mzZtj8+bNmD59OgCgQYMG2LRpE/r164e7774b//nPf0okYkX98ccf6N+/P7p164a1a9dCpfL+7cO8QbkOKI+fa4MBAI6sLF+GQ0REXtaiRQscOHAAZ86cQXp6erk1Lq1atcKmTZuQlJSEH3/8ERMmTKhyDU1lY/r222/xxx9/ID09XTm2u+bm+PHjeOihh5Camqpsc+DAASxatAg//PADzp07h02bNuHSpUseyRAANGrUCDt37sSJEycwfvx42O32UmO4ePEi+vXrh6ZNm2Lp0qW4dOkSUlNTPY7pDUx26oA72bG7x8diUxYRUb02Y8YMqNVqtG/fHg0bNiz3/pvly5cjPDwcvXv3xogRIzBkyBB07dq11mNasGABzpw5g5YtWyr99syZMwddu3bFkCFD0K9fP0RHR3v0iBwSEoJvv/0Ww4cPR5s2bfDcc89h2bJlGDZsWIn9R0dHY+fOnTh69CgmTpxYas3WN998g99++w07d+5EkyZNEBMTo0zeJInKPktXj2VnZyM0NBRZWVkICQmp9f1/8fqPOPfzZXS49BWifv4Szd9/D6ZiN6gREZGnwsJCJCcnIy4uDgaDwdfhkI+U93NQ2e9v1uzUAWUw0CD3YKCZPoyGiIjo2sJkpw5cHQw0DACTHSIiorrEZKcOuPvasemcg4HaOT4WERFRnWGyUwcM7podtfNxSdbsEBER1R0mO3VA6UWZg4ESERHVOSY7dUAZ+Vx2vnJ8LCIiorrDZKcOuJ/GKrQ7P27W7BAREdUdJjt1wBDsbMZyOCQ4VFomO0RERHWIyU4d0BnUUKklAIBVa4aDT2MRERHVGSY7dUCSpCLjYwXBkZUF4YVxT4iIqP5o0aIFVqxYUafHXLduHcLCwur0mHWByU4dMRTta0eWIefk+DgiIiIKZAkJCR7jWPnKpk2bMGTIEDRo0ACSJCEpKcnXIZXAZKeOKIOBuoeMYFMWERHVA3l5eejTpw+WLFni61DKxGSnjrj72rGbGwDgE1lERPXVW2+9hcaNG0MudrvCyJEjMXnyZADA6dOnMWrUKERFRSE4OBg9evTAjh07Kn2MefPmYf369fj8888hSRIkSUJiYiIA4KmnnkKbNm1gMplw3XXXYc6cObDZbMq2P/74I/r37w+z2YyQkBB069YNP/zwQ6nHuXz5Mm644QaMHDkShYWFpZaZNGkSnn/+eQwaNKjS8dc1ja8DuFYo9+wERwIA7Ex2iIiqTAgBUVDgk2NLRiMkSaqw3F133YW///3v2LVrFwYOHAgAyMjIwLZt2/DFF18AAHJzczF8+HAsXLgQBoMB69evx4gRI3Dy5Ek0a9aswmPMmDEDx48fR3Z2NtauXQsAiIhwthyYzWasW7cOsbGxOHr0KKZMmQKz2YxZs2YBACZOnIguXbpg1apVUKvVSEpKglarLXGMCxcuYPDgwejevTvWrFkDjSZwU4bAjTzAuIeMsBucQ9CzY0EioqoTBQU42bWbT47d9vAhSCZTheUiIiIwdOhQfPDBB0qy8/HHHyMiIkKZj4+PR3x8vLLNwoULsXnzZmzZsgVTp06t8BjBwcEwGo2wWCyIjo72WPfcc88p71u0aIEnn3wSH330kZLsnDt3DjNnzkS7du0AAK1bty6x/19//RW33HILRo0ahVdffbVSSZ4/YzNWHXE3Y1m1zsFA2YxFRFR/TZw4EZ9++iksFgsAYMOGDRg3bhzUajUA530us2bNQvv27REWFobg4GCcOHEC586dq/GxP/nkE/Tt2xfR0dEIDg7GnDlzPPY7ffp0PPDAAxg0aBCWLFmC06dPe2xfUFCAvn37YvTo0XjttdcCPtEBWLNTZ5QhIzgYKBFRtUlGI9oePuSzY1fWiBEjIMsytm7dih49emDPnj145ZVXlPUzZ87Etm3bsHTpUrRq1QpGoxF33nknrFZrjWLcv38/xo0bh/nz52PIkCEIDQ3Fxo0bsWzZMqXMvHnzMGHCBGzduhVfffUV5s6di40bN+L2228HAOj1egwaNAhbt27FzJkz0aRJkxrF5A+Y7NQR95ARVrh6U+bTWEREVSZJUqWaknzNaDRizJgx2LBhA3777Te0adMG3bpdbX7bs2cPEhISlAQjNzcXZ86cqdIxdDodHA6Hx7K9e/eiefPmmD17trLs7NmzJbZt06YN2rRpgyeeeALjx4/H2rVrlVhUKhXee+89TJgwAQMGDEBiYiJiY2OrFJu/YTNWHXEPGWFxuAYDZc0OEVG9NnHiRGzduhVr1qzBPffc47GuVatW2LRpE5KSkvDjjz9iwoQJJZ7eqkiLFi3w008/4eTJk0hPT4fNZkOrVq1w7tw5bNy4EadPn8Zrr72GzZs3K9sUFBRg6tSpSExMxNmzZ7F3714cPHgQ119/vce+1Wo1NmzYgPj4eAwYMACpqallxnHlyhUkJSXhl19+AQCcPHkSSUlJ5W5T15js1BF3zY7NoYIsqZjsEBHVcwMGDEBERAROnjyJCRMmeKxbvnw5wsPD0bt3b4wYMQJDhgxB165dq7T/KVOmoG3btujevTsaNmyIvXv3YtSoUXjiiScwdepU/OUvf8G+ffswZ84cZRu1Wo3Lly/j3nvvRZs2bTB27FgMGzYM8+fPL7F/jUaDDz/8EB06dMCAAQOQlpZWahxbtmxBly5dcOuttwIAxo0bhy5duuDNN9+s0vl4kySEEL4Owteys7MRGhqKrKwshISEeOUYQhZY9dguCAH02fcMQppH4bovtnjlWERE9UFhYSGSk5MRFxcHg8Hg63DIR8r7Oajs9zdrduqIpJKUx89t2mDW7BAREdURJjt1yBDkuklZa4YjMxOsVCMiIvI+Jjt1yKgMBhoMYbNBzsv3cURERET1H5OdOqQMGWEIBcAnsoiIiOoCk506ZOBgoERERHWOyU4dctfs2E3hANixIBERUV1gslOHlL523IOBsmaHiIjI65js1CGjqxdlqyYYAJMdIiKiusBkpw4Z3ONjqZ2DyTHZISIi8j4mO3VIGflc6AHwnh0iIipbixYtsGLFijo95rp16xAWFlanx6wLTHbqkNKM5VBDQGLNDhERVVtCQgJGjx7t0xhsNhueeuopdOrUCUFBQYiNjcW9996Lixcv+jSu4pjs1CH3cBECEuwaE5MdIiIKaPn5+Th8+DDmzJmDw4cPY9OmTfj1118xcuRIX4fmgclOHVJrVNAZNQAAqy4Y9kw2YxER1TdvvfUWGjduDFmWPZaPHDkSkydPBgCcPn0ao0aNQlRUFIKDg9GjRw/s2LGj0seYN28e1q9fj88//xySJEGSJCQmJgIAnnrqKbRp0wYmkwnXXXcd5syZA5vNpmz7448/on///jCbzQgJCUG3bt3www8/lHqcy5cv44YbbsDIkSNRWFhYYn1oaCi2b9+OsWPHom3btrjxxhvx+uuv49ChQzh37lylz8fbNL4O4FpjDNbCWmDnYKBERNUghIDdKldc0As0OhUkSaqw3F133YW///3v2LVrFwYOHAgAyMjIwLZt2/DFF18AAHJzczF8+HAsXLgQBoMB69evx4gRI3Dy5Ek0a9aswmPMmDEDx48fR3Z2NtauXQsAiIiIAACYzWasW7cOsbGxOHr0KKZMmQKz2YxZs2YBACZOnIguXbpg1apVUKvVSEpKglarLXGMCxcuYPDgwejevTvWrFkDjaZyKUNWVhYkSfKre3+Y7NQxo1mLrEsFsGqD4chM8XU4REQBxW6V8fY/dvvk2A++ejO0enWF5SIiIjB06FB88MEHSrLz8ccfIyIiQpmPj49HfHy8ss3ChQuxefNmbNmyBVOnTq3wGMHBwTAajbBYLIiOjvZY99xzzynvW7RogSeffBIfffSRkuycO3cOM2fORLt27QAArVu3LrH/X3/9FbfccgtGjRqFV199tVJJHgAUFhbi6aefxoQJExASElKpbeoCm7HqmMF1k7JNa4bIz4dssfg4IiIiqm0TJ07Ep59+Covr3/gNGzZg3LhxUKudyVJeXh5mzZqF9u3bIywsDMHBwThx4kStNP188skn6Nu3L6KjoxEcHIw5c+Z47Hf69Ol44IEHMGjQICxZsgSnT5/22L6goAB9+/bF6NGj8dprr1U60bHZbBg3bhxkWcYbb7xR4/OoTazZqWPK4+d6MwBnXzuqqChfhkREFDA0OhUefPVmnx27skaMGAFZlrF161b06NEDe/bswSuvvKKsnzlzJrZt24alS5eiVatWMBqNuPPOO2G1WmsU4/79+zFu3DjMnz8fQ4YMQWhoKDZu3Ihly5YpZebNm4cJEyZg69at+OqrrzB37lxs3LgRt99+OwBAr9dj0KBB2Lp1K2bOnIkmTZpUeFybzYaxY8ciOTkZO3fu9KtaHYDJTp1zDxlhD44E4Ex2tEx2iIgqRZKkSjUl+ZrRaMSYMWOwYcMG/Pbbb2jTpg26deumrN+zZw8SEhKUBCM3Nxdnzpyp0jF0Oh0cDofHsr1796J58+aYPXu2suzs2bMltm3Tpg3atGmDJ554AuPHj8fatWuVWFQqFd577z1MmDABAwYMQGJiImJjY8uMw53onDp1Crt27UJkZGSVzqMusBmrjrmbsexGDgZKRFSfTZw4EVu3bsWaNWtwzz33eKxr1aoVNm3ahKSkJPz444+YMGFCiae3KtKiRQv89NNPOHnyJNLT02Gz2dCqVSucO3cOGzduxOnTp/Haa69h8+bNyjYFBQWYOnUqEhMTcfbsWezduxcHDx7E9ddf77FvtVqNDRs2ID4+HgMGDEBqamqpMdjtdtx555344YcfsGHDBjgcDqSmpiI1NbXGtVS1iclOHVMGAy3SjEVERPXPgAEDEBERgZMnT2LChAke65YvX47w8HD07t0bI0aMwJAhQ9C1a9cq7X/KlClo27YtunfvjoYNG2Lv3r0YNWoUnnjiCUydOhV/+ctfsG/fPsyZM0fZRq1W4/Lly7j33nvRpk0bjB07FsOGDcP8+fNL7F+j0eDDDz9Ehw4dMGDAAKSlpZUoc+HCBWzZsgUXLlzAX/7yF8TExCjTvn37qnQ+3iQJIYSvDv7tt9/i5ZdfxqFDh5CSkoLNmzd79AaZkJCA9evXe2zTs2dP7N+/X5m3WCyYMWMGPvzwQxQUFGDgwIF44403KtXG6JadnY3Q0FBkZWV5vZ3x7LHL+HLljwhBJronzkb0vLkIHzfOq8ckIgpEhYWFSE5ORlxcHAwGg6/DIR8p7+egst/fPq3ZycvLQ3x8PFauXFlmmaFDhyIlJUWZ/vvf/3qsnzZtGjZv3oyNGzfiu+++Q25uLm677bYS7Zj+wl2zY1U5LxibsYiIiLzLpzcoDxs2DMOGDSu3jF6vL9GHgFtWVhZWr16N9957D4MGDQIAvP/++2jatCl27NiBIUOG1HrMNeUeMsIq6yDAZiwiIiJv8/t7dhITE9GoUSO0adMGU6ZM8WgzPHToEGw2GwYPHqwsi42NRceOHf2qrbAoo9l5g7IMFRxqA5MdIiIiL/PrR8+HDRuGu+66C82bN0dycjLmzJmDAQMG4NChQ9Dr9UhNTYVOp0N4eLjHdlFRUWXeOQ447/OxFOnMLzs722vnUJxWp4ZGq4LdJsOqDYadzVhERERe5dfJzt13362879ixI7p3747mzZtj69atGDNmTJnbCSHK7fFx8eLFpd55XlcMZi1yr1hg0wXDkZnlsziIiAKBD5+jIT9QG9ff75uxioqJiUHz5s1x6tQpAEB0dDSsVisyitWOpKWlIaqcjvqeeeYZZGVlKdP58+e9GndxRmXICA4GSkRUFvfglPn5+T6OhHzJff1LG6y0svy6Zqe4y5cv4/z584iJiQEAdOvWDVqtVhleHgBSUlJw7NgxvPTSS2XuR6/XQ6/X10nMpVGeyNIGw5FRsmdLIiJy9gkTFham3KtpMpkqPU4TBT4hBPLz85GWloawsDBlXLHq8Gmyk5ubi99++02ZT05ORlJSEiIiIhAREYF58+bhjjvuQExMDM6cOYNnn30WDRo0ULq0Dg0Nxf33348nn3wSkZGRiIiIwIwZM9CpUyfl6Sx/VLRmR87JgbDbIWkCKu8kIqoT7qdxS+vQjq4NYWFhZT6VXVk+/Yb94Ycf0L9/f2V++vTpAIDJkydj1apVOHr0KN59911kZmYiJiYG/fv3x0cffQSz2axss3z5cmg0GowdO1bpVHDdunU1ygC9zeDuRVnn6kU5KwsaPxxLhIjI1yRJQkxMDBo1agSbzebrcKiOabXaWvk+92kPyv6iLntQBoBDX5/B/s9+R8zlQ7j+6Bpc9+UX0Ldq5fXjEhER1ScB0YPytcrd147NGAaAHQsSERF5E5MdHzAEFWvGYrJDRETkNUx2fECp2VGbAIAdCxIREXkRkx0fMLrHx5Jcg4GyZoeIiMhrmOz4gLufHTs0cKg0THaIiIi8iMmOD+iMGqjUzo6xbNpgODIyfRsQERFRPcZkxwckSYLB1ZRl05pZs0NERORFTHZ8xN2LspXjYxEREXkVkx0fMSq9KAfDwaexiIiIvIbJjo+4m7FYs0NERORdTHZ8pOhgoI6sLAhZ9nFERERE9ROTHR9RmrG0wYAsQ87O9nFERERE9ROTHR9xdyxoM4QBYMeCRERE3sJkx0cM7mYsYygAJjtERETewmTHRzyascDxsYiIiLyFyY6PKP3suAYDdWRm+TIcIiKieovJjo8oPShLesiSis1YREREXsJkx0cMwVrAOTyWa3wsNmMRERF5A5MdH1GpJBhM7vt2glizQ0RE5CVMdnyo6E3KTHaIiIi8g8mOD10dMsLMZiwiIiIvYbLjQ0ZzkSEjWLNDRETkFUx2fMjdi7JVx2SHiIjIW5js+FDRmh17ZiaEED6OiIiIqP5hsuNDhiD3DcpmwGaDnJfv44iIiIjqHyY7PuR+GsuqDwHA8bGIiIi8gcmOD7mHjLDrzQDAJ7KIiIi8gMmODxncNTuuwUBZs0NERFT7mOz4kLtmx6YyQkBiskNEROQFTHZ8yP3ouZBUsGuMbMYiIiLyAiY7PqTWqqAzqAE4m7JYs0NERFT7mOz4mMHd147OzGSHiIjIC5js+Ji7Kcs5ZASbsYiIiGobkx0fU4aM0AaxZoeIiMgLmOz4mNKMpTXDzmSHiIio1jHZ8TGPZqyMTN8GQ0REVA8x2fExd187HPmciIjIO5js+Jh7fCybNhiioACyxeLjiIiIiOoXJjs+ZnDfoKxzjY/F2h0iIqJaxWTHx5QhI3Sukc/ZizIREVGtYrLjY1ebsYIgwJodIiKi2sZkx8fczViypIFDrWeyQ0REVMuY7PiYVq+GWuu8DM7Hz9mMRUREVJuY7PiYJEnFhozI9G1ARERE9QyTHT9gdPWizJHPiYiIah+THT+g1OzozLCzGYuIiKhWMdnxAwazezBQ1uwQERHVNiY7fsAY5B4MNBiOzCwfR0NERFS/MNnxAwZz0cFA2YxFRERUm5js+AH3PTtsxiIiIqp9THb8gPtpLJsuGHJODoTN5uOIiIiI6g8mO36gaM0OADiyeN8OERFRbWGy4weu1uxw5HMiIqLaxmTHD7jHx3KoDc4xspjsEBER1ZpqJTvnz5/HhQsXlPnvv/8e06ZNw9tvv11rgV1L9CYNJJUEALDqgtmxIBERUS2qVrIzYcIE7Nq1CwCQmpqKW265Bd9//z2effZZLFiwoFYDvBZIkqTU7nB8LCIiotpVrWTn2LFjuOGGGwAA//nPf9CxY0fs27cPH3zwAdatW1eb8V0zOBgoERGRd1Qr2bHZbNDr9QCAHTt2YOTIkQCAdu3aISUlpfaiu4YYiw4ZkZHp22CIiIjqkWolOx06dMCbb76JPXv2YPv27Rg6dCgA4OLFi4iMjKzVAK8VxuCiQ0Zk+jYYIiKieqRayc6LL76It956C/369cP48eMRHx8PANiyZYvSvEVVo/S1o2OyQ0REVJs01dmoX79+SE9PR3Z2NsLDw5XlDz74IEwmU60Fdy0xuPva0ZrhyPjDx9EQERHVH9Wq2SkoKIDFYlESnbNnz2LFihU4efIkGjVqVKsBXit4gzIREZF3VCvZGTVqFN59910AQGZmJnr27Illy5Zh9OjRWLVqVa0GeK0wcDBQIiIir6hWsnP48GHcdNNNAIBPPvkEUVFROHv2LN5991289tprtRrgtaLoYKCOrCwIWfZxRERERPVDtZKd/Px8mM3OcZy++eYbjBkzBiqVCjfeeCPOnj1bqwFeK4o2Y0GWIWdn+zgiIiKi+qFayU6rVq3w2Wef4fz589i2bRsGDx4MAEhLS0NISEitBnitUGp2NCYISGzKIiIiqiXVSnaef/55zJgxAy1atMANN9yAXr16AXDW8nTp0qVWA7xWGIJcD8ZJKti0QRwfi4iIqJZU69HzO++8E3379kVKSorSxw4ADBw4ELfffnutBXctUalV0AdpYMmzw6o1s2aHiIiollQr2QGA6OhoREdH48KFC5AkCY0bN2aHgjVkDNbBkmd33qScmeXrcIiIiOqFajVjybKMBQsWIDQ0FM2bN0ezZs0QFhaGf/7zn5D5FFG1ucfHsmmD4WAzFhERUa2oVrIze/ZsrFy5EkuWLMGRI0dw+PBhLFq0CK+//jrmzJlT6f18++23GDFiBGJjYyFJEj777DOP9UIIzJs3D7GxsTAajejXrx9+/vlnjzIWiwWPP/44GjRogKCgIIwcORIXLlyozmn5nCGIfe0QERHVtmolO+vXr8e///1vPPLII+jcuTPi4+Px6KOP4p133sG6desqvZ+8vDzEx8dj5cqVpa5/6aWX8Morr2DlypU4ePAgoqOjccsttyAnJ0cpM23aNGzevBkbN27Ed999h9zcXNx2221wOBzVOTWfUp7IYrJDRERUa6p1z86VK1fQrl27EsvbtWuHK1euVHo/w4YNw7Bhw0pdJ4TAihUrMHv2bIwZMwaAM8mKiorCBx98gIceeghZWVlYvXo13nvvPQwaNAgA8P7776Np06bYsWMHhgwZUo2z8x2PISPYjEVERFQrqlWzU1ZtzMqVK9G5c+caBwUAycnJSE1NVfrwAQC9Xo+bb74Z+/btAwAcOnQINpvNo0xsbCw6duyolAkk7podjnxORERUe6pVs/PSSy/h1ltvxY4dO9CrVy9IkoR9+/bh/Pnz+O9//1srgaWmpgIAoqKiPJa7h6Zwl9HpdB4jr7vLuLcvjcVigcViUeaz/aS3YoNSs8NHz4mIiGpLtWp2br75Zvz666+4/fbbkZmZiStXrmDMmDH4+eefsXbt2loNUJIkj3khRIllxVVUZvHixQgNDVWmpk2b1kqsNeV+GsuqDYY9k81YREREtaFayQ7gbC564YUX8Omnn2LTpk1YuHAhMjIysH79+loJLDo6GgBK1NCkpaUptT3R0dGwWq3IKHZ/S9EypXnmmWeQlZWlTOfPn6+VmGvKGFz0BuUsCCF8HBEREVHgq3ay421xcXGIjo7G9u3blWVWqxW7d+9G7969AQDdunWDVqv1KJOSkoJjx44pZUqj1+sREhLiMfmDov3sCJsNcl6+jyMiIiIKfNXuQbk25Obm4rffflPmk5OTkZSUhIiICDRr1gzTpk3DokWL0Lp1a7Ru3RqLFi2CyWTChAkTAAChoaG4//778eSTTyIyMhIRERGYMWMGOnXqpDydFUjc9+wIlRp2jRGOzAyog4N8HBUREVFg82my88MPP6B///7K/PTp0wEAkydPxrp16zBr1iwUFBTg0UcfRUZGBnr27IlvvvkGZrNZ2Wb58uXQaDQYO3YsCgoKMHDgQKxbtw5qtbrOz6emNFo1tHo1bBaH6/HzTKBJE1+HRUREFNAkUYUbQ9z93ZQlMzMTu3fvDrgO/bKzsxEaGoqsrCyfN2m999w+ZKcXotvhpei47FkE39TXp/EQERH5q8p+f1epZic0NLTC9ffee29VdknFGIJ1yE4vdI18zieyiIiIaqpKyU5tP1ZOJSk3KetczVhERERUI377NNa1yj1kBAcDJSIiqh1MdvyMZ187bMYiIiKqKSY7fsag1OxwyAgiIqLawGTHz1ztWDCIyQ4REVEtYLLjZ5RmLF0w7LxBmYiIqMaY7PgZg5nNWERERLWJyY6f8bxBOdO3wRAREdUDTHb8jPueHVmtg93igFxY6OOIiIiIAhuTHT+j1auh1jgvi1XH2h0iIqKaYrLjZyRJKvJEFpMdIiKimmKy44c8+trJYMeCRERENcFkxw+5h4xgXztEREQ1x2THDxmUJ7L4+DkREVFNMdnxQ+57dqy6YNjZjEVERFQjTHb8EPvaISIiqj1MdvwQn8YiIiKqPUx2/JC7ZsfKZIeIiKjGmOz4Iff4WDadGQ4OBkpERFQjTHb8kFHpZ4c1O0RERDXFZMcPuZuxHBojbFk5Po6GiIgosDHZ8UN6kwaS68pYCgWEzebbgIiIiAIYkx0/JKkkGIKKNGVlZfk4IiIiosDFZMdPGc2uvnY48jkREVGNMNnxUx43KbMXZSIiompjsuOnio6PZWfNDhERUbUx2fFTV0c+ZzMWERFRTTDZ8VOGokNGsGNBIiKiamOy46eUISN4gzIREVGNMNnxUxwMlIiIqHYw2fFTfBqLiIiodjDZ8VNKPzus2SEiIqoRJjt+yqA8jRUEeyZ7UCYiIqouJjt+yp3sQFKhMLvQt8EQEREFMCY7fkqtVkFncF6eQgsgZNnHEREREQUmJjt+zH3fjlVtgpyd7eNoiIiIAhOTHT9mNOsBOG9StvOJLCIiomphsuPHlL522LEgERFRtTHZ8WMefe0w2SEiIqoWJjt+zGC+OvI5x8ciIiKqHiY7fow1O0RERDXHZMePKb0o854dIiKiamOy48eu9qLM8bGIiIiqi8mOH2MzFhERUc0x2fFjRQcDtTPZISIiqhYmO37MXbMjVBpYsvJ8HA0REVFgYrLjxzQ6NTRaCQBQkGf3cTRERESBicmOnzMGaQAAhQUCQggfR0NERBR4mOz4OWOIazBQyQA5j01ZREREVcVkx88ZzAYArsfPeZMyERFRlTHZ8XPKYKDaYA4ZQUREVA1Mdvyc0teOLhiOTHYsSEREVFVMdvxc0b522IxFRERUdUx2/NzVISM48jkREVF1MNnxc+6aHeeQEWzGIiIiqiomO37Ofc8ORz4nIiKqHiY7fs79NBYHAyUiIqoeJjt+zhDsbMaS1XpYMrJ9HA0REVHgYbLj53QGNVSuq1SQbfVtMERERAGIyY6fkyQJBqPzMhVyMFAiIqIqY7ITAAzKYKCyjyMhIiIKPEx2AoAx1Dk+lgV6yIWFPo6GiIgosDDZCQCmUA4GSkREVF1MdgKAx5ARGexYkIiIqCqY7AQApa8ddixIRERUZUx2AoC7rx02YxEREVUdk50AoAwZoQ2Gnc1YREREVcJkJwBwyAgiIqLqY7ITAK42Y5mZ7BAREVWRXyc78+bNgyRJHlN0dLSyXgiBefPmITY2FkajEf369cPPP//sw4i9w12zY9eaYLuS5eNoiIiIAotfJzsA0KFDB6SkpCjT0aNHlXUvvfQSXnnlFaxcuRIHDx5EdHQ0brnlFuTk5Pgw4tpnMGkhQQAACrIKfBwNERFRYPH7ZEej0SA6OlqZGjZsCMBZq7NixQrMnj0bY8aMQceOHbF+/Xrk5+fjgw8+8HHUtUtSSdDrJQBAQQ4HAyUiIqoKv092Tp06hdjYWMTFxWHcuHH4/fffAQDJyclITU3F4MGDlbJ6vR4333wz9u3b56twvUbPwUCJiIiqRePrAMrTs2dPvPvuu2jTpg3+/PNPLFy4EL1798bPP/+M1NRUAEBUVJTHNlFRUTh79my5+7VYLLBYLMp8dnZ27Qdfy4zBOmRlFqKwUPg6FCIiooDi18nOsGHDlPedOnVCr1690LJlS6xfvx433ngjAECSJI9thBAllhW3ePFizJ8/v/YD9iJjmAG4UAirrIWw2SBptb4OiYiIKCD4fTNWUUFBQejUqRNOnTqlPJXlruFxS0tLK1HbU9wzzzyDrKwsZTp//rzXYq4tpjAjAFdfO1l8IouIiKiyAirZsVgsOH78OGJiYhAXF4fo6Ghs375dWW+1WrF792707t273P3o9XqEhIR4TP7OGKIHwMFAiYiIqsqvm7FmzJiBESNGoFmzZkhLS8PChQuRnZ2NyZMnQ5IkTJs2DYsWLULr1q3RunVrLFq0CCaTCRMmTPB16LWOvSgTERFVj18nOxcuXMD48eORnp6Ohg0b4sYbb8T+/fvRvHlzAMCsWbNQUFCARx99FBkZGejZsye++eYbmM1mH0de+4zuXpR1wbAz2SEiIqo0SQhxzT/ek52djdDQUGRlZfltk9b5E1ewZUUSgvJSMGqEFuFjx/o6JCIiIp+q7Pd3QN2zcy1zj3xu1QbBkckblImIiCqLyU6AcDdj2bVBsGdk+jYYIiKiAMJkJ0AYXDU7QlKj4Equj6MhIiIKHEx2AoRao4JWIwMACrIKfRwNERFR4GCyE0AMrsFAC3M5GCgREVFlMdkJIIYgNQCgIN/h40iIiIgCB5OdAGI0O29SLjKGKREREVWAyU4AcY+PVejQQDhYu0NERFQZTHYCiDE8CABg05jgyM72cTRERESBgclOADGGGgAANq2Z42MRERFVEpOdAMLBQImIiKqOyU4AUQYD1QbDwV6UiYiIKoXJTgBx1+zYdKzZISIiqiwmOwHEEHy1GYvjYxEREVUOk50A4u5nR6i0sFzmyOdERESVwWQngGh1aqgl5/hY+Zn5Po6GiIgoMDDZCTB6nQAAFGSxG2UiIqLKYLITYAwGDgZKRERUFUx2AowxWAMAKCyUfRwJERFRYGCyE2CMZj0AoNAi+TgSIiKiwMBkJ8AYXYOBWuxqCCF8HA0REZH/Y7ITYEyRwQAAqyYIcl6ej6MhIiLyf0x2AowpwgTANWQEe1EmIiKqEJOdAGMIcg0ZoQ2GIyPDx9EQERH5PyY7AcbdizJHPiciIqocJjsBxhhcpGaHyQ4REVGFmOwEGPfI5w6NAdbLbMYiIiKqCJOdAKMzaiDBNT7WZT6NRUREVBEmOwFGkiToNQ4AQH4GBwMlIiKqCJOdAGRwDwaazcFAiYiIKsJkJwAZjGoAQEGe3ceREBER+T8mOwHIoAwGyuEiiIiIKsJkJwAZQ5yDgVo4GCgREVGFmOwEIFN4EADA4lD7OBIiIiL/x2QnAJkauAYDVRkhFxT4OBoiIiL/xmQnALlHPrfpzOxFmYiIqAJMdgKQe3wsDhlBRERUMSY7AcgYzMFAiYiIKovJTgByj49l1wbBxvGxiIiIysVkJwDpg7QAnH3s5KVn+zYYIiIiP8dkJwCpVBJ0krP35IIruT6OhoiIyL8x2QlQVwcDLfRxJERERP6NyU6AMhicr4U5Vt8GQkRE5OeY7AQoZTDQfA4GSkREVB4mOwHKGOx8IouDgRIREZWPyU6AMoY527EsVl5CIiKi8vCbMkAZw00AAKus8XEkRERE/o3JToAyNTADACySAcLKm5SJiIjKwmQnQAU1DAHgGh8rK8vH0RAREfkvJjsByhjqvGfHpjPD8ttvPo6GiIjIfzHZCVDuwUBt2iCce/BhpL/zDoTD4eOoiIiI/A+TnQDlfvRcSGrYhAaXlr2CsxPvgfXMGd8GRkRE5GeY7AQotVYFncHZsaB55vNQBQejICkJv4++HVfe3wAhyz6OkIiIyD8w2QlgYVHOx893HYsAlrwHY68bIQoL8efChTh3//2wXbzo4wiJiIh8j8lOABtw7/WIiA1CQY4NOz65iOM9n0DIU89DMhiQ/3/78fvIUcjctBlCsJdlIiK6dkmC34TIzs5GaGgosrKyEBIS4utwqsRhk/HD12dw+KuzkGUBvUmDG/uHI2jDIhQmJQEAggcMQMz8edA0bOjbYImIiGpRZb+/mewgsJMdt/QLOfjf+uNIP58LAGjWPgLxmiPIX7UcwmaDOiwM0fPmImToUB9HSkREVDuY7FRBfUh2AMDhkJG0/Ry+/zIZsl1Aa1Djhj5mmD9YCOvx4wCAkOHDEf38HKjDwnwbLBERUQ0x2amC+pLsuF1JycOu944j9fdsAEDj1qGIF9+jcO2/AIcD6oYNELtwIYJvvtnHkRIREVUfk50qqG/JDgDIssDRXRew/7PTsNtkaHQqdLvBiLAP/gnb76cBAGF33YlGTz0FdXCwj6MlIiKqOiY7VVAfkx23rEv52PXeCfzxayYAIDrOjM6WfbB/+BYgBLSxsYhZtAhBN/b0baABQDgcsJw8ifzDR1Bw+DDsGVegiYiEpkEk1JENoGnQwPU+0vk+IgKSVuvrsImI6i0mO1VQn5MdABCywM/fXcS+Tb/BVuiAWqNCfLwGkR8tgOPCeQBA+L2T0Gj6dKgMBh9H6z/kvDwU/PijktwUJCVBzs+v0j7UoaFQN3AlQpGRUDeIhCaySFIU2QCahq7ESKfz0pkQXXuELMOekgLL77/Dcvo0rKd/hy01FSqDAargYKjMwVAHB0MVbIYqOAhqs9m5PCgYanOwq4wZKpMJkoq9tPgrJjtVUN+THbecK4VI3HAC536+AgBo2CQInfN3Q2xaCwDQxcUhdsliGOPjfRmmz9j+/BMFhw8j/9BhFBw+jMKTJ4Fi442pgoNh/MtfYOrWFdrYWNgvX4H9cjoc6Zdhv+ycHOnpsF+5UmLbiqhCQ6GJjFSSIl3jxtC1aAFdXBx0LVpAHREBSZJq85SJAp6wWmE9dw6W33+H9fffYTn9O6ynT8OSnAxRUFDzA0gSVEFBzuQnOAjqYHOZyZI6NBSaqChoGkVBGx0FlclU8+NTuZjsVMG1kuwAgBACJ/en4ruPT8GSb4dKJaFTBwkNP5oPOS0VUKkQOWUKGj72aL2uaRCyDMup31Bw+JBSc2P7448S5bSxsTB27Qpj1y4wdesGfatWkNTqSu3fkZkJe3o6HJcvw55+2ZkUXb4M+6V0V2LkSpKuXAHs9gr3qQoJga5FC+jjWngkQbrmzaEyGqv1OVD1CCEgCgvhyM6BnJMNR7ZzkrOzry7LyoYjJxtydo5zveu9XFAAXZMm0LVuBX2rVtC3ag1961bQNGrEZLYccl4eLL8nw/r7aVhO/w7L787aGuv582X//mi10DVvBv11LaFreR10TZpAWK1w5ORCzs2FnJsDR24uZNe8I9e1PMe5vDK/l+VRmc3QRkdBExUNTVQjaKOioYmKci1zTuqwMF73GmCyUwXXUrLjlpdlwe4PTiL5x3QAQES0AZ2yd0L93w0AAH3btoh96UUY2rb1ZZi1Ri4oQMFPR1FwxFVzk5QEOSfHs5BKBX27tjB17QZT1y4wdu0KbXS012MTsgxHVpazRsidGKVfgu38BVjPnIE1ORm2lBSgnF9VTUwMdC2aQ+9OgFyv2tjYSiVngUIIAWGzQVitgN0O4XBA2B2Aw/3eDjgcnu+V9TKE4+qyou/hsHssk/PySk9WsrLhyMmBnJ0NYbPV6rmpQkJcyY9rciVD6gYNrpkvQyEEHFeuOJuditXS2FNSytxOZTJB17Il9NfFQXddS+hbXgfddS2ha9qk2vfNCSEgrFbIOTnORCgnF3JervP65+Y5l+flFkmccmHPuAL7n2mwp6ZWuslb0uudCVCjRtBEF0mKoqOgjYpyLouMhKTRVOs86jsmO1VwLSY7gPOX+bdDafh2468ozLVBkoD2rWREfboAuHIJ0GphHjgQKqMRkkYDSat1TjotUHTePWmKzWuLldFogGLbAABkGRDCOXipACAqNw9Zdg6F4Z5kGUJ2z8twZGWj4MgR5B85gsJffinxV5pkMsH0l3gYu3SFqVtXGDrHQx0cVOnPTghApaqbLyG5sBDWs+eU5Md65ozy3pGVVeZ2klYLbfNmV5OgFnHQxbWArlkzSAYDAGf8kuT6n3vC1XlJKVCsjOTetuRn4K75kAsKIOfnQ87Ph8jPLzLvei1wrSsogJxXZL17uVLu6mtN/9quVWq1816PkBBXM0YIVOYQqENCoAoxQ20OKbLMDHVICCSdDtazZ2E5dQqWU7/B8ttvsJ47V2azpzo01FkL1Lq1Z01QREQdn2zVCSEg8vNhz8iEI+MKHFeuwJ6RAceVDDgyMmDPuKK8d1y5AvuVKyX/CClCHRkJ/XXXQdfyOqW2Rt+yJTRRUX6XEDpyc2FPTYXtzz9hT/0T9rQ/YUv9E/Y//3Qu+/NPOK5cqdzOVCpoGjaEpmFDqCMjnPf6RUZcve8vMsL5kERkBNTh4fXqD5yKMNmpAq8lO7tfAn7+DJBUru8U9xeE+8tCVXIZXMs9lqHs8soyVZF5FNuHqpyyEgqseuw5Ho9TKU0BAKHGHHS8+An0P/5Qe5+FH9A0jICxYzuYOreHsXMHGFpd50y4JFWJyWYDcrPsyM2yIyfTjtxMG3IybMjNsCInw4LcTCscdhnGIC2MZh2MITqYzK73Zh2MrvemkKvzWr3aK/8g2zMyYE0+UzIROnvWWQNSV4omSu4EtC5oNJDUauc/8K73cM0XXSZp1IDatV6jhlT0vcpzmSooqGSyEhpyNbEJcS5TBZlq5ZrKViusycnO5OfUKVh++w2W307Bdu58mZ+jOiLiai1Qm9bK+5p2GOrxB0SRSThXOmu93MmJkriUncQIi6VqAUgStI0bX01orouDvmVL6K+7rkbnJoSA7BCQZQGhTM5uOoRwzsuuZcK1rNx5WUAWV/cjZAFJJUFnUENn1Dgngxpag6bMP4pkqxX2tDSPpMj2Z6pSO2RLS4M9La1q9/+pVFCHh0MTEXH1gYiiyZBHghQJlV5f7c8TDoezptVud05WG2B3zbuX29zvbdA1bwFtVKNqHa8sTHaqwFvJTs7Hj8H88/u1tj9vSy7sgcTsh5EvRwCQ0U5sQ9ucrVDLNkgOOyTZ4ayFkSXXL7fkmuDxilKWlVUe0tU8ECg6L5R54Op3qHu5VKT81XnhMS+pBQwRNpgaWGFqaIXG5IAkAbJQIV8OR46jAXIdDZAjN0Su+72jAXIdDVEoar+GTyNZYFRlw6jOhlGdA6M6GybXq1Gd63yvyXWu0+RDpUKRBEwqNSkre70EISTYcgWsV+ywZjhgvWKDNcMG6xUrbFl1VzsiadVQ6TXKJOm0rvdaqAxaqHQaqAxaSHotVAYdVHqda51OmSSD3rVOC5VR76ppVAOSyplsuBN7oJT3gMcfDsXfl7VNKX98CEhwyCrYbRJsDgl2mwS7Q4LdroLdLsFuB+x2CTa75Jy3OSui7DbnOptdguwADEYJJrMKpiAVTGYVgoJVMJnVMJhUUKlVyh8istUK67kUWM6chyXZPZ2DLeXPMj9vVVCQ81Sc2cnV2k4IV82oK3lx/9NfpGbUWySdDuqICKgjwqEJd9Y+ON+HQ+2a10SEQx0RAW1srHIPmhACDpsMa6ED1kI7bMVeiy4vusxWbJ3VYoetwAFZ9s3XnVavLpEEOV9dk7HIfLH1Wp0EVX4WpMxLcKRfhuOKq6n7ymXlwQj3MkdmZpX/yFAFBzsfioiIcP674UpSYLdBWIskMjbP96hGM270gvkIHzu2ytuVp7Lf32wE9KLXbb1xCCFQCRVUEFAJZ5OAJAAJElRCggqASjiHn5dc61WQoIKMq/+8Ctc/wwIqZd65TCU5/4FSQ0AlCef+JGc5teTcXi25yzqXqyS4Xt37g7NMkIDKlAh15l/gyL8OJ6RhOBEyrJQzc0CSZECSIbneS0Xeq6Qir3BAJcmQJAdUcLjWOV/VsLu2k51lIDvP2/VeLTlcy1yvkkNZr4IMFezOV9dyZzn3cZxNXpfs4ch3hCHfEYG8jHDkOSKQ7wiHQMXVvFopH2Z1OoJVl5yvavdrOsyqS1BLVhTKIciXQ1Egh6JADivy/uqUL4fCLoywCz1yHA2R46jcgKwaqRBq2KCRrFBLNqglKzRwvqol13LXvEaZL7JOskEN5zp1kA3qYCs0zWzQS1YYhc35WQn3tRHO6wfZ9RnKnp+967OF+xpBQBLy1ZzB9T1alEojIKkEZJUONqGHXehhEwbYlfeARahgFxrYhQo2oYXdooOtUA+7MJTYxjlvgF3oIAsNABmS5PxdgMfvhQAkh+v3Ry62TnYl1HLJ7SRZORlZaIrEqXO+hx52oYPzt7UyRBnvyybBAaMqCyZVBoLUGTCpMmFSZVydj85ESGwmDCIDco4MS5YGliyt61UDe74Gcl5eJeOrPpVOQGMQUBsE1AZAbQA0BkBtkKA2StAYJaj0EoRRD4feBJtkglUEwSLrUSgErI5CWCwZsF60wHI+E1bZCIvDAKvDAKush9Whh831Kir9eVef5P5Zcv08qdzvXZOq6HrJ+W+o898puOady2UhwebQwmrTwurQwiE7/52xWRywWRzIy6pJTauAXmOFXquFQRsJvdYMQ0gs9A1sMGht0Ots0Gus0MqF0NrzobHkQlOQB1VBLkRuIey5FthzLXBkO1/tORbAIUPOzYU1Nxc4e7bmH6RKBUmjcv4xolY5a0s1GkgaZy2rWl2797lVBZMdLzqkOYRf47ZXa1shVIBwNTu5XoVQASi+3PUPgXCnPxIgiv7VWnSZ53pRYh2c+4v8A01zmuGvF/+KcGt4KdGpIYS61C+4QOGAjFxNIXI0FuRoCpCjtiBHU1hkssCmshdJTtWQEOWaXJ+kUD5BOD9NCXAlCxKuALgClesLVStrYHRoYJD1MDp0MDj0MMpaGBx65yQ7l+kdOuhlPVSQnF/sMMDixx+ygAxABiThei+u1r4JDSA0rs+l/pFgh1qyQiVdTUCvvre6Ek7PSSNZoIIMqxwEixwCiyMEFjkEhXIoLHIwBNTIlyOQL0cgvYLKN62UD2NwJkwhmTC1cCZFRmRCZ8+9mvS5ajuVfxHcNaau31xJWX+1VvTqeqF8mSvLJECWdCiACRY5CFZhglW43wfBIruSGksQrIUmiKzau3dEKxVAJ+W7XgugVTlfdVI+tKrCIuvyoVMVepZ3ldVKBR5/XCmTl35EHULj/IxkE6zC6Ho1eS5T3pe9XIYGgASLXQ+LXY/sKj5Rr5XyYQjOhT4kB4YmudCrcqGXcqEXudA68qC150FjK3D97qogVCoIVy2x870EAbXzVVI7a4AkFYSkhoAKsrss1JCFyrkMnvNCqGHQSvDVXbH1Jtl544038PLLLyMlJQUdOnTAihUrcNNNN/k0pp5x0Uj9LQQO4YAsZDhk16twQFSQJrhrTjyWeTPYYlKCf8NHMTsBAaiEWpnUssZZUyU0rvki61zLVLIaavc2rvLKOo9tnOskoYIkJKigdtZuCWfdlsc6oYYE5zqVx3oJklBD5VpXdL2AQJ4uE7n6DOeky0CuPhO5ugzk67IhpLKvgQpARS3Zrq+SSikEUPZtl8V3LMFgN0Hr0EMtNFDLWqhlDTSuV7Wsg6b48tLKCXd5LTSuV3c5jaxxfm7FPmvlM3ctc68vi6tuEh7flWV8KA7JDpvKArvaCrvKCpvrtcz3aitsqmLvXetkyQFAguRK3N0/G4C7hlRS1pf9HoBQQVnqSvolSHBIdthVNtexbUpsdpXNFYMNsseJFvkDQxSbL1qm1HXOPzgkWQWDPRhBNjNMthCYbGaYrGbnqy1YeQ2ymaERWtiECTaHCdmOWMB3fzBXSIYMq9oCm8oKm9oCm8oCq9oKm8oCm9rivOaudcrPgMoKR5FXh8p5gqV8clffi+LrTZBgLLVs0fJl7lMUnXcnhxKu1rQreb3HtqX9+Jf+K1HgnKQr5Zdz/RuslvXQyDpoHAZoHQZoZT20DgM0sgEah2uSnZPaYYBa1kMtGyBBcv6sCBNy5HLulyktGxAAqtZdWLkyzqTiztrbXZXUi3t2PvroI0yaNAlvvPEG+vTpg7feegv//ve/8csvv6BZs2YVbu+Lp7GEEHAIh3MqkgR5vMqOkstKKS/gunmu6HvIrieGirwvUk6Gs5nHva608kX3B0CZl4Vc6nzxbdzr3ImdLK4eq+ixix6j6LbCVXVUfH8lyrle3TEo/5Wyz6KxFi3ncazSypUWU7F/mor/KhVdXyK5LTFbcl9Fj1f8syoek/vaFT+n0s7bva9Kf46yUL6MIVxJgWtSCRUgu+cBSVYpCYhN+eKywKa2QoajlLiVKDyOT+UQgM5hgNEWgiBrCIzu5MgaApMtBHq7u88lVyIoJI/NS61pU5LGq6VKLSskOFQ2WNWFsGoKYFEXwKopgFVdCIsmX1luVbuXFcCustbtX2qkkIQEnd0Ivd0Eg90Evd0EvT2o2LwJBnsQ9A7nz40MGUKSIUvOVwEBWXJASK7XIvNKuWLbuPfhuR8ZzVr+BS/c/bdaPcdr6gblnj17omvXrli1apWy7Prrr8fo0aOxePHiCre/Vh89J/JHFSWYxZOiiv4Jq0pS6p4vWqasBLp4rKUuL76ulPNQElr3HwrFtintcyj+h0hZiW3xskXXu//4KL6ueAJcNNF2b+M+pkf5InGW9geQcszi+y923uV9th7vi36exZaXd52K/+wU36b451m0XNGfn1J/HgVKJHbFE8biT+9JHilm+WVLfMbFfh4qvK7Fr1Wx/RX9Y9j9B3nRZbIse/wx7PyD27W+yHsBGQ7Z+Xp1vYyZ3Z/GuOtrt27nmrlB2Wq14tChQ3j66ac9lg8ePBj79u3zUVREVF2S5GpYYm0AEdWSgE920tPT4XA4EBUV5bE8KioKqamppW5jsVhgKdL3Q3Z2tldjJCIiIt+pN0O5llbdV1ZnX4sXL0ZoaKgyNW3atC5CJCIiIh8I+GSnQYMGUKvVJWpx0tLSStT2uD3zzDPIyspSpvPnz9dFqEREROQDAZ/s6HQ6dOvWDdu3e/Zns337dvTu3bvUbfR6PUJCQjwmIiIiqp8C/p4dAJg+fTomTZqE7t27o1evXnj77bdx7tw5PPzww74OjYiIiHysXiQ7d999Ny5fvowFCxYgJSUFHTt2xH//+180b97c16ERERGRj9WLfnZqiv3sEBERBZ7Kfn8H/D07REREROVhskNERET1GpMdIiIiqteY7BAREVG9xmSHiIiI6jUmO0RERFSvMdkhIiKieq1edCpYU+6uhjj6ORERUeBwf29X1GUgkx0AOTk5AMDRz4mIiAJQTk4OQkNDy1zPHpQByLKMixcvwmw2Q5KkWttvdnY2mjZtivPnz18TPTNfS+fLc62/rqXz5bnWX9fK+QohkJOTg9jYWKhUZd+Zw5odACqVCk2aNPHa/q+1kdWvpfPludZf19L58lzrr2vhfMur0XHjDcpERERUrzHZISIionqNyY4X6fV6zJ07F3q93teh1Ilr6Xx5rvXXtXS+PNf661o734rwBmUiIiKq11izQ0RERPUakx0iIiKq15jsEBERUb3GZIeIiIjqNSY7NfTGG28gLi4OBoMB3bp1w549e8otv3v3bnTr1g0GgwHXXXcd3nzzzTqKtGYWL16MHj16wGw2o1GjRhg9ejROnjxZ7jaJiYmQJKnEdOLEiTqKunrmzZtXIubo6OhytwnU6woALVq0KPU6PfbYY6WWD6Tr+u2332LEiBGIjY2FJEn47LPPPNYLITBv3jzExsbCaDSiX79++Pnnnyvc76effor27dtDr9ejffv22Lx5s5fOoPLKO1ebzYannnoKnTp1QlBQEGJjY3Hvvffi4sWL5e5z3bp1pV7rwsJCL59N+Sq6rgkJCSVivvHGGyvcrz9eV6Di8y3tGkmShJdffrnMffrrtfUWJjs18NFHH2HatGmYPXs2jhw5gptuugnDhg3DuXPnSi2fnJyM4cOH46abbsKRI0fw7LPP4u9//zs+/fTTOo686nbv3o3HHnsM+/fvx/bt22G32zF48GDk5eVVuO3JkyeRkpKiTK1bt66DiGumQ4cOHjEfPXq0zLKBfF0B4ODBgx7nun37dgDAXXfdVe52gXBd8/LyEB8fj5UrV5a6/qWXXsIrr7yClStX4uDBg4iOjsYtt9yijJdXmv/7v//D3XffjUmTJuHHH3/EpEmTMHbsWBw4cMBbp1Ep5Z1rfn4+Dh8+jDlz5uDw4cPYtGkTfv31V4wcObLC/YaEhHhc55SUFBgMBm+cQqVVdF0BYOjQoR4x//e//y13n/56XYGKz7f49VmzZg0kScIdd9xR7n798dp6jaBqu+GGG8TDDz/ssaxdu3bi6aefLrX8rFmzRLt27TyWPfTQQ+LGG2/0WozekpaWJgCI3bt3l1lm165dAoDIyMiou8Bqwdy5c0V8fHyly9en6yqEEP/4xz9Ey5YthSzLpa4P1OsKQGzevFmZl2VZREdHiyVLlijLCgsLRWhoqHjzzTfL3M/YsWPF0KFDPZYNGTJEjBs3rtZjrq7i51qa77//XgAQZ8+eLbPM2rVrRWhoaO0GV8tKO9fJkyeLUaNGVWk/gXBdhajctR01apQYMGBAuWUC4drWJtbsVJPVasWhQ4cwePBgj+WDBw/Gvn37St3m//7v/0qUHzJkCH744QfYbDavxeoNWVlZAICIiIgKy3bp0gUxMTEYOHAgdu3a5e3QasWpU6cQGxuLuLg4jBs3Dr///nuZZevTdbVarXj//fdx3333VTgobiBe16KSk5ORmprqce30ej1uvvnmMn+HgbKvd3nb+KOsrCxIkoSwsLByy+Xm5qJ58+Zo0qQJbrvtNhw5cqRuAqyhxMRENGrUCG3atMGUKVOQlpZWbvn6cl3//PNPbN26Fffff3+FZQP12lYHk51qSk9Ph8PhQFRUlMfyqKgopKamlrpNampqqeXtdjvS09O9FmttE0Jg+vTp6Nu3Lzp27FhmuZiYGLz99tv49NNPsWnTJrRt2xYDBw7Et99+W4fRVl3Pnj3x7rvvYtu2bXjnnXeQmpqK3r174/Lly6WWry/XFQA+++wzZGZmIiEhocwygXpdi3P/nlbld9i9XVW38TeFhYV4+umnMWHChHIHiWzXrh3WrVuHLVu24MMPP4TBYECfPn1w6tSpOoy26oYNG4YNGzZg586dWLZsGQ4ePIgBAwbAYrGUuU19uK4AsH79epjNZowZM6bccoF6bauLo57XUPG/foUQ5f5FXFr50pb7s6lTp+Knn37Cd999V265tm3bom3btsp8r169cP78eSxduhR//etfvR1mtQ0bNkx536lTJ/Tq1QstW7bE+vXrMX369FK3qQ/XFQBWr16NYcOGITY2tswygXpdy1LV3+HqbuMvbDYbxo0bB1mW8cYbb5Rb9sYbb/S4sbdPnz7o2rUrXn/9dbz22mveDrXa7r77buV9x44d0b17dzRv3hxbt24tNwkI5OvqtmbNGkycOLHCe28C9dpWF2t2qqlBgwZQq9Ulsv60tLQSfx24RUdHl1peo9EgMjLSa7HWpscffxxbtmzBrl270KRJkypvf+ONNwbcXw5BQUHo1KlTmXHXh+sKAGfPnsWOHTvwwAMPVHnbQLyu7ifsqvI77N6uqtv4C5vNhrFjxyI5ORnbt28vt1anNCqVCj169Ai4ax0TE4PmzZuXG3cgX1e3PXv24OTJk9X6HQ7Ua1tZTHaqSafToVu3bsqTK27bt29H7969S92mV69eJcp/88036N69O7RarddirQ1CCEydOhWbNm3Czp07ERcXV639HDlyBDExMbUcnXdZLBYcP368zLgD+boWtXbtWjRq1Ai33nprlbcNxOsaFxeH6Ohoj2tntVqxe/fuMn+HgbKvd3nb+AN3onPq1Cns2LGjWom4EAJJSUkBd60vX76M8+fPlxt3oF7XolavXo1u3bohPj6+ytsG6rWtNF/dGV0fbNy4UWi1WrF69Wrxyy+/iGnTpomgoCBx5swZIYQQTz/9tJg0aZJS/vfffxcmk0k88cQT4pdffhGrV68WWq1WfPLJJ746hUp75JFHRGhoqEhMTBQpKSnKlJ+fr5Qpfr7Lly8XmzdvFr/++qs4duyYePrppwUA8emnn/riFCrtySefFImJieL3338X+/fvF7fddpswm8318rq6ORwO0axZM/HUU0+VWBfI1zUnJ0ccOXJEHDlyRAAQr7zyijhy5IjyBNKSJUtEaGio2LRpkzh69KgYP368iImJEdnZ2co+Jk2a5PGE5d69e4VarRZLliwRx48fF0uWLBEajUbs37+/zs+vqPLO1WaziZEjR4omTZqIpKQkj99hi8Wi7KP4uc6bN098/fXX4vTp0+LIkSPib3/7m9BoNOLAgQO+OEVFeeeak5MjnnzySbFv3z6RnJwsdu3aJXr16iUaN24ckNdViIp/joUQIisrS5hMJrFq1apS9xEo19ZbmOzU0L/+9S/RvHlzodPpRNeuXT0exZ48ebK4+eabPconJiaKLl26CJ1OJ1q0aFHmD6a/AVDqtHbtWqVM8fN98cUXRcuWLYXBYBDh4eGib9++YuvWrXUffBXdfffdIiYmRmi1WhEbGyvGjBkjfv75Z2V9fbqubtu2bRMAxMmTJ0usC+Tr6n5Mvvg0efJkIYTz8fO5c+eK6OhoodfrxV//+ldx9OhRj33cfPPNSnm3jz/+WLRt21ZotVrRrl07v0j0yjvX5OTkMn+Hd+3apeyj+LlOmzZNNGvWTOh0OtGwYUMxePBgsW/fvro/uWLKO9f8/HwxePBg0bBhQ6HVakWzZs3E5MmTxblz5zz2ESjXVYiKf46FEOKtt94SRqNRZGZmlrqPQLm23iIJ4bqTkoiIiKge4j07REREVK8x2SEiIqJ6jckOERER1WtMdoiIiKheY7JDRERE9RqTHSIiIqrXmOwQERFRvcZkh4gIzkEgP/vsM1+HQURewGSHiHwuISEBkiSVmIYOHerr0IioHtD4OgAiIgAYOnQo1q5d67FMr9f7KBoiqk9Ys0NEfkGv1yM6OtpjCg8PB+BsYlq1ahWGDRsGo9GIuLg4fPzxxx7bHz16FAMGDIDRaERkZCQefPBB5ObmepRZs2YNOnToAL1ej5iYGEydOtVjfXp6Om6//XaYTCa0bt0aW7ZsUdZlZGRg4sSJaNiwIYxGI1q3bl0iOSMi/8Rkh4gCwpw5c3DHHXfgxx9/xD333IPx48fj+PHjAID8/HwMHToU4eHhOHjwID7++GPs2LHDI5lZtWoVHnvsMTz44IM4evQotmzZglatWnkcY/78+Rg7dix++uknDB8+HBMnTsSVK1eU4//yyy/46quvcPz4caxatQoNGjSouw+AiKrP1yOREhFNnjxZqNVqERQU5DEtWLBACCEEAPHwww97bNOzZ0/xyCOPCCGEePvtt0V4eLjIzc1V1m/dulWoVCqRmpoqhBAiNjZWzJ49u8wYAIjnnntOmc/NzRWSJImvvvpKCCHEiBEjxN/+9rfaOWEiqlO8Z4eI/EL//v2xatUqj2URERHK+169enms69WrF5KSkgAAx48fR3x8PIKCgpT1ffr0gSzLOHnyJCRJwsWLFzFw4MByY+jcubPyPigoCGazGWlpaQCARx55BHfccQcOHz6MwYMHY/To0ejdu3e1zpWI6haTHSLyC0FBQSWalSoiSRIAQAihvC+tjNForNT+tFptiW1lWQYADBs2DGfPnsXWrVuxY8cODBw4EI899hiWLl1apZiJqO7xnh0iCgj79+8vMd+uXTsAQPv27ZGUlIS8vDxl/d69e6FSqdCmTRuYzWa0aNEC//vf/2oUQ8OGDZGQkID3338fK1aswNtvv12j/RFR3WDNDhH5BYvFgtTUVI9lGo1GuQn4448/Rvfu3dG3b19s2LAB33//PVavXg0AmDhxIubOnYvJkydj3rx5uHTpEh5//HFMmjQJUVFRAIB58+bh4YcfRqNGjTBs2DDk5ORg7969ePzxxysV3/PPP49u3bqhQ4cOsFgs+PLLL3H99dfX4idARN7CZIeI/MLXX3+NmJgYj2Vt27bFiRMnADiflNq4cSMeffRRREdHY8OGDWjfvj0AwGQyYdu2bfjHP/6BHj16wGQy4Y477sArr7yi7Gvy5MkoLCzE8uXLMWPGDDRo0AB33nlnpePT6XR45plncObMGRiNRtx0003YuHFjLZw5EXmbJIQQvg6CiKg8kiRh8+bNGD16tK9DIaIAxHt2iIiIqF5jskNERET1Gu/ZISK/x9Z2IqoJ1uwQERFRvcZkh4iIiOo1JjtERERUrzHZISIionqNyQ4RERHVa0x2iIiIqF5jskNERET1GpMdIiIiqteY7BAREVG99v8JAEUtbxgHUAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# accuracy plot\n",
    "plt.plot(history_5.history['task_1_output_accuracy'])\n",
    "plt.plot(history_5.history['task_2_output_accuracy'])\n",
    "plt.plot(history_5.history['val_task_1_output_accuracy'])\n",
    "plt.plot(history_5.history['val_task_2_output_accuracy'])\n",
    "plt.title('Model Accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()\n",
    "\n",
    "# loss plot\n",
    "plt.plot(history_5.history['loss'])\n",
    "plt.plot(history_5.history['task_1_output_loss'])\n",
    "plt.plot(history_5.history['task_2_output_loss'])\n",
    "plt.plot(history_5.history['val_task_1_output_loss'])\n",
    "plt.plot(history_5.history['val_task_2_output_loss'])\n",
    "plt.title('Model Loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.legend(['combined' ,'train task 1', 'train task 2', 'val task 1', 'val task 2'])\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 5523.216887,
   "end_time": "2023-04-23T17:53:46.936635",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-04-23T16:21:43.719748",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}