{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Cub_Birds_200_2011_Classification.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "metadata": {
        "id": "5sQVmss-VqC_",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Calteh Birds Classification\n",
        "This Project is done using Google Colaboratory. 1st you have to mount google drive with Colab and place dataset in zipped format on Google drive to access it. This dataset contains birds images of 200 categories. Training images are 5994 & test images are 5794. I have achieved top1 accuracy 77.32% and top5 accuracy 94.30% on test set. This project is done using a ResNet18(pretrained on imagenet)."
      ]
    },
    {
      "metadata": {
        "id": "PjyWdaRlWIY-",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Next cell is for installation of PyTorch on Google Colab"
      ]
    },
    {
      "metadata": {
        "id": "KSgSPtVRlSwc",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "!pip3 install http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl \n",
        "!pip3 install torchvision"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "gktAVH9AmwO4",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "!unzip drive/Bird/Birds.zip # this line copies the birds dataset from Google drive to Google Colab and also Unzip it for further processing."
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "bTutjsYIpA3A",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# here are the necessary imports\n",
        "from __future__ import print_function, division\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "from torch.autograd import Variable\n",
        "import numpy as np\n",
        "import torchvision\n",
        "from torchvision import datasets, models, transforms\n",
        "import matplotlib.pyplot as plt\n",
        "import time\n",
        "import os\n",
        "import seaborn as sns\n",
        "plt.ion()   "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "UbrmvLcwWLr2",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Load Data\n",
        "We will use torchvision and torch.utils.data packages for loading the data. For the training, i have applied transformations such as random scaling, cropping, and flipping. This will help the network generalize leading to better performance. I also made it sure that the input data is resized to 224x224 pixels as required by the pre-trained networks.\n",
        "\n",
        "The testing set is used to measure the model's performance on data it hasn't seen yet. For this i have not performed any scaling or rotation transformations, but i had resized and then cropped the images to the appropriate size.\n",
        "\n",
        "The pre-trained network i have used was trained on the ImageNet dataset where each color channel was normalized separately. For all three sets i have normalized the means and standard deviations of the images to what the network expects. For the means, it's [0.485, 0.456, 0.406] and for the standard deviations [0.229, 0.224, 0.225], calculated from the ImageNet images. These values will shift each color channel to be centered at 0 and range from -1 to 1."
      ]
    },
    {
      "metadata": {
        "id": "vMGMhoC-pK8n",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Data augmentation and normalization for training\n",
        "# Just normalization for validation\n",
        "data_transforms = {\n",
        "    'train': transforms.Compose([\n",
        "        transforms.Resize(256),\n",
        "        transforms.RandomRotation(45),\n",
        "        transforms.RandomResizedCrop(224),\n",
        "        transforms.RandomHorizontalFlip(),\n",
        "        transforms.ToTensor(),\n",
        "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
        "    ]),\n",
        "    'test': transforms.Compose([\n",
        "        transforms.Resize(256),\n",
        "        transforms.CenterCrop(224),\n",
        "        transforms.ToTensor(),\n",
        "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
        "    ]),\n",
        "}\n",
        "\n",
        "data_dir = 'Birds'\n",
        "# loading datasets with PyTorch ImageFolder\n",
        "image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
        "                                          data_transforms[x])\n",
        "                  for x in ['train', 'test']}\n",
        "# defining data loaders to load data using image_datasets and transforms, here we also specify batch size for the mini batch\n",
        "dataloders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=8,\n",
        "                                             shuffle=True, num_workers=4)\n",
        "              for x in ['train', 'test']}\n",
        "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'test']}\n",
        "class_names = image_datasets['train'].classes\n",
        "\n",
        "use_gpu = torch.cuda.is_available()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "SG1uzQ1iXAQz",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Sizes of training and test datasets"
      ]
    },
    {
      "metadata": {
        "id": "XjD7ZMJ_qpYp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "41f6fd39-8e2a-4eda-a05f-9e16f0e311a5"
      },
      "cell_type": "code",
      "source": [
        "dataset_sizes"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'test': 5794, 'train': 5994}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "metadata": {
        "id": "oPrYtAjQXJZb",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Visualize a few images\n",
        "Let's visualize a few training images so as to understand the data augmentations."
      ]
    },
    {
      "metadata": {
        "id": "D-iZY_vhpxAf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "4005e01c-aaa8-4379-df98-023cf622570c"
      },
      "cell_type": "code",
      "source": [
        "def imshow(inp, title=None):\n",
        "    \"\"\"Imshow for Tensor.\"\"\"\n",
        "    inp = inp.numpy().transpose((1, 2, 0))\n",
        "    mean = np.array([0.485, 0.456, 0.406])\n",
        "    std = np.array([0.229, 0.224, 0.225])\n",
        "    inp = std * inp + mean\n",
        "    inp = np.clip(inp, 0, 1)\n",
        "    plt.imshow(inp)\n",
        "    if title is not None:\n",
        "        plt.title(title)\n",
        "    plt.pause(0.001)  # pause a bit so that plots are updated\n",
        "\n",
        "\n",
        "# Get a batch of training data\n",
        "inputs, classes = next(iter(dataloders['train']))\n",
        "\n",
        "# Make a grid from batch\n",
        "out = torchvision.utils.make_grid(inputs)\n",
        "\n",
        "imshow(out, title=[class_names[x] for x in classes])"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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19TUnmgclKSmJ/v37m8I9IyPDIwQw87sBj3ZSVdWjXzwqFi1axOLFi82QUsMw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ZFq5+lCCZJYY8nwfd/xHi3QUcZ7776Bhjb8P59/gJ9/223c/eab+fjHP8HWS66CoBfv8AqL587g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\nGKdXO1U8YnVLUCnhtprf9ZxvYhOb+P7CJrHdxCZ+4KAIdYTSm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p1hVyHHs//0NHvecC2X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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9f42a00400>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "76uC1hXfXZrk",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Training the model\n",
        "Now, let's write a general function to train a model. I also have written code to save the best checkpoint within Google drive for using next time"
      ]
    },
    {
      "metadata": {
        "id": "afcvSjddsuv_",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def train_model(model, criterion, optimizer, num_epochs=10):\n",
        "    since = time.time()\n",
        "\n",
        "    best_model_wts = model.state_dict()\n",
        "    best_acc = 0.0\n",
        "\n",
        "    for epoch in range(num_epochs):\n",
        "        print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
        "        print('-' * 10)\n",
        "\n",
        "        # Each epoch has a training and validation phase\n",
        "        for phase in ['train', 'test']:\n",
        "            if phase == 'train':\n",
        "                #scheduler.step()\n",
        "                model.train(True)  # Set model to training mode\n",
        "            else:\n",
        "                model.train(False)  # Set model to evaluate mode\n",
        "\n",
        "            running_loss = 0.0\n",
        "            running_corrects = 0\n",
        "\n",
        "            # Iterate over data.\n",
        "            for data in dataloders[phase]:\n",
        "                # get the inputs\n",
        "                inputs, labels = data\n",
        "\n",
        "                # wrap them in Variable\n",
        "                if use_gpu:\n",
        "                    inputs = Variable(inputs.cuda())\n",
        "                    labels = Variable(labels.cuda())\n",
        "                else:\n",
        "                    inputs, labels = Variable(inputs), Variable(labels)\n",
        "\n",
        "                # zero the parameter gradients\n",
        "                optimizer.zero_grad()\n",
        "\n",
        "                # forward\n",
        "                outputs = model(inputs)\n",
        "                \n",
        "                _, preds = torch.max(outputs.data, 1)\n",
        "                loss = criterion(outputs, labels)\n",
        "\n",
        "                # backward + optimize only if in training phase\n",
        "                if phase == 'train':\n",
        "                    loss.backward()\n",
        "                    optimizer.step()\n",
        "\n",
        "                # statistics\n",
        "                running_loss += loss.data[0]\n",
        "                running_corrects += torch.sum(preds == labels.data)\n",
        "\n",
        "            epoch_loss = running_loss / dataset_sizes[phase]\n",
        "            epoch_acc = running_corrects.float() / dataset_sizes[phase]\n",
        "\n",
        "            print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n",
        "                phase, epoch_loss, epoch_acc))\n",
        "\n",
        "            # deep copy the model\n",
        "            if phase == 'test' and epoch_acc > best_acc:\n",
        "                best_acc = epoch_acc\n",
        "                best_model_wts = model.state_dict()\n",
        "                state = {'model':model_ft.state_dict(),'optim':optimizer_ft.state_dict()}\n",
        "                torch.save(state,'drive/Bird/point_resnet_best.pth')\n",
        "\n",
        "        print()\n",
        "\n",
        "    time_elapsed = time.time() - since\n",
        "    print('Training complete in {:.0f}m {:.0f}s'.format(\n",
        "        time_elapsed // 60, time_elapsed % 60))\n",
        "    print('Best test Acc: {:4f}'.format(best_acc))\n",
        "\n",
        "    # load best model weights\n",
        "    model.load_state_dict(best_model_wts)\n",
        "    return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "PZkh0x9FXb_v",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Visualizing the model predictions\n",
        "Generic function to display predictions for a few images"
      ]
    },
    {
      "metadata": {
        "id": "6yUjTuX1szCP",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def visualize_model(model, num_images=8):\n",
        "    images_so_far = 0\n",
        "    fig = plt.figure()\n",
        "    \n",
        "\n",
        "    for i, data in enumerate(dataloders['test']):\n",
        "        inputs, labels = data\n",
        "        #print(labels)\n",
        "        if use_gpu:\n",
        "            inputs, labels = Variable(inputs.cuda()), Variable(labels.cuda())\n",
        "        else:\n",
        "            inputs, labels = Variable(inputs), Variable(labels)\n",
        "        #print(labels)\n",
        "        #_, lab = torch.max(labels.data, 1)\n",
        "        outputs = model(inputs)\n",
        "        #print(outputs)\n",
        "        _, preds = torch.max(outputs.data, 1)\n",
        "        #print(preds)\n",
        "\n",
        "        for j in range(inputs.size()[0]):\n",
        "            images_so_far += 1\n",
        "            ax = plt.subplot(num_images//2, 2, images_so_far)\n",
        "            ax.axis('off')\n",
        "            ax.set_title('class: {} predicted: {}'.format(class_names[labels.data[j]], class_names[preds[j]]))\n",
        "            imshow(inputs.cpu().data[j])\n",
        "\n",
        "            if images_so_far == num_images:\n",
        "                return"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "ryJ5vtkVXhRo",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Finetuning the convnet\n",
        "Load a pretrained Resnet 18 model and reset final fully connected layer."
      ]
    },
    {
      "metadata": {
        "id": "tjOZbefNs2W-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "cf9c63c5-52ae-4eee-e5a5-d8e6fb8203c9"
      },
      "cell_type": "code",
      "source": [
        "model_ft = models.resnet18(pretrained=True) # loading a pre-trained(trained on image net) resnet18 model from torchvision models\n",
        "num_ftrs = model_ft.fc.in_features\n",
        "model_ft.fc = nn.Linear(num_ftrs, 200)      # changing the last layer for this dataset by setting last layer neurons to 200 as this dataset has 200 categories\n",
        " \n",
        "if use_gpu:                                 # if gpu is available then use it\n",
        "    model_ft = model_ft.cuda()       \n",
        "#model_ft = model_ft.float()\n",
        "criterion = nn.CrossEntropyLoss()           # defining loss function\n",
        "\n",
        "# Observe that all parameters are being optimized\n",
        "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.0001, momentum=0.9)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/resnet18-5c106cde.pth\" to /root/.torch/models/resnet18-5c106cde.pth\n",
            "100%|██████████| 46827520/46827520 [00:01<00:00, 23950564.37it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "id": "WIjCTS2lX4Rm",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "You can load a checkpoint from your my drive or any other place if you have saved it. you have to load weights of model and optimizer"
      ]
    },
    {
      "metadata": {
        "id": "gLweeTCOs88w",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "checkpoint = torch.load('path to model')\n",
        "#checkpoint = torch.load('drive//Bird/point_resnet_best.pth')\n",
        "model_ft.load_state_dict(checkpoint['model'])\n",
        "optimizer_ft.load_state_dict(checkpoint['optim'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "YkNXw1v-YxST",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Train and evaluate"
      ]
    },
    {
      "metadata": {
        "id": "XpfSb7TytDbO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 4301
        },
        "outputId": "57b94f56-2737-4c3e-d458-bdb22055a02c"
      },
      "cell_type": "code",
      "source": [
        "model_ft = train_model(model_ft, criterion, optimizer_ft,num_epochs=50)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 0/49\n",
            "----------\n",
            "train Loss: 0.1660 Acc: 0.7027\n",
            "test Loss: 0.1140 Acc: 0.7518\n",
            "\n",
            "Epoch 1/49\n",
            "----------\n",
            "train Loss: 0.1674 Acc: 0.6982\n",
            "test Loss: 0.1136 Acc: 0.7520\n",
            "\n",
            "Epoch 2/49\n",
            "----------\n",
            "train Loss: 0.1642 Acc: 0.6942\n",
            "test Loss: 0.1143 Acc: 0.7511\n",
            "\n",
            "Epoch 3/49\n",
            "----------\n",
            "train Loss: 0.1630 Acc: 0.7072\n",
            "test Loss: 0.1155 Acc: 0.7503\n",
            "\n",
            "Epoch 4/49\n",
            "----------\n",
            "train Loss: 0.1626 Acc: 0.7115\n",
            "test Loss: 0.1130 Acc: 0.7546\n",
            "\n",
            "Epoch 5/49\n",
            "----------\n",
            "train Loss: 0.1622 Acc: 0.7130\n",
            "test Loss: 0.1119 Acc: 0.7511\n",
            "\n",
            "Epoch 6/49\n",
            "----------\n",
            "train Loss: 0.1596 Acc: 0.7154\n",
            "test Loss: 0.1112 Acc: 0.7563\n",
            "\n",
            "Epoch 7/49\n",
            "----------\n",
            "train Loss: 0.1552 Acc: 0.7211\n",
            "test Loss: 0.1119 Acc: 0.7577\n",
            "\n",
            "Epoch 8/49\n",
            "----------\n",
            "train Loss: 0.1557 Acc: 0.7239\n",
            "test Loss: 0.1117 Acc: 0.7577\n",
            "\n",
            "Epoch 9/49\n",
            "----------\n",
            "train Loss: 0.1553 Acc: 0.7237\n",
            "test Loss: 0.1096 Acc: 0.7608\n",
            "\n",
            "Epoch 10/49\n",
            "----------\n",
            "train Loss: 0.1545 Acc: 0.7257\n",
            "test Loss: 0.1099 Acc: 0.7642\n",
            "\n",
            "Epoch 11/49\n",
            "----------\n",
            "train Loss: 0.1537 Acc: 0.7304\n",
            "test Loss: 0.1091 Acc: 0.7618\n",
            "\n",
            "Epoch 12/49\n",
            "----------\n",
            "train Loss: 0.1527 Acc: 0.7237\n",
            "test Loss: 0.1118 Acc: 0.7551\n",
            "\n",
            "Epoch 13/49\n",
            "----------\n",
            "train Loss: 0.1490 Acc: 0.7357\n",
            "test Loss: 0.1105 Acc: 0.7611\n",
            "\n",
            "Epoch 14/49\n",
            "----------\n",
            "train Loss: 0.1521 Acc: 0.7299\n",
            "test Loss: 0.1130 Acc: 0.7528\n",
            "\n",
            "Epoch 15/49\n",
            "----------\n",
            "train Loss: 0.1531 Acc: 0.7232\n",
            "test Loss: 0.1095 Acc: 0.7606\n",
            "\n",
            "Epoch 16/49\n",
            "----------\n",
            "train Loss: 0.1491 Acc: 0.7359\n",
            "test Loss: 0.1098 Acc: 0.7642\n",
            "\n",
            "Epoch 17/49\n",
            "----------\n",
            "train Loss: 0.1485 Acc: 0.7352\n",
            "test Loss: 0.1109 Acc: 0.7598\n",
            "\n",
            "Epoch 18/49\n",
            "----------\n",
            "train Loss: 0.1437 Acc: 0.7392\n",
            "test Loss: 0.1087 Acc: 0.7623\n",
            "\n",
            "Epoch 19/49\n",
            "----------\n",
            "train Loss: 0.1430 Acc: 0.7429\n",
            "test Loss: 0.1086 Acc: 0.7613\n",
            "\n",
            "Epoch 20/49\n",
            "----------\n",
            "train Loss: 0.1436 Acc: 0.7377\n",
            "test Loss: 0.1090 Acc: 0.7635\n",
            "\n",
            "Epoch 21/49\n",
            "----------\n",
            "train Loss: 0.1450 Acc: 0.7297\n",
            "test Loss: 0.1088 Acc: 0.7623\n",
            "\n",
            "Epoch 22/49\n",
            "----------\n",
            "train Loss: 0.1445 Acc: 0.7384\n",
            "test Loss: 0.1080 Acc: 0.7661\n",
            "\n",
            "Epoch 23/49\n",
            "----------\n",
            "train Loss: 0.1434 Acc: 0.7467\n",
            "test Loss: 0.1092 Acc: 0.7620\n",
            "\n",
            "Epoch 24/49\n",
            "----------\n",
            "train Loss: 0.1416 Acc: 0.7487\n",
            "test Loss: 0.1071 Acc: 0.7670\n",
            "\n",
            "Epoch 25/49\n",
            "----------\n",
            "train Loss: 0.1391 Acc: 0.7524\n",
            "test Loss: 0.1109 Acc: 0.7598\n",
            "\n",
            "Epoch 26/49\n",
            "----------\n",
            "train Loss: 0.1401 Acc: 0.7506\n",
            "test Loss: 0.1133 Acc: 0.7496\n",
            "\n",
            "Epoch 27/49\n",
            "----------\n",
            "train Loss: 0.1402 Acc: 0.7477\n",
            "test Loss: 0.1073 Acc: 0.7675\n",
            "\n",
            "Epoch 28/49\n",
            "----------\n",
            "train Loss: 0.1347 Acc: 0.7566\n",
            "test Loss: 0.1080 Acc: 0.7661\n",
            "\n",
            "Epoch 29/49\n",
            "----------\n",
            "train Loss: 0.1359 Acc: 0.7583\n",
            "test Loss: 0.1067 Acc: 0.7663\n",
            "\n",
            "Epoch 30/49\n",
            "----------\n",
            "train Loss: 0.1359 Acc: 0.7534\n",
            "test Loss: 0.1058 Acc: 0.7708\n",
            "\n",
            "Epoch 31/49\n",
            "----------\n",
            "train Loss: 0.1372 Acc: 0.7521\n",
            "test Loss: 0.1093 Acc: 0.7632\n",
            "\n",
            "Epoch 32/49\n",
            "----------\n",
            "train Loss: 0.1343 Acc: 0.7548\n",
            "test Loss: 0.1110 Acc: 0.7599\n",
            "\n",
            "Epoch 33/49\n",
            "----------\n",
            "train Loss: 0.1317 Acc: 0.7656\n",
            "test Loss: 0.1046 Acc: 0.7701\n",
            "\n",
            "Epoch 34/49\n",
            "----------\n",
            "train Loss: 0.1333 Acc: 0.7611\n",
            "test Loss: 0.1084 Acc: 0.7665\n",
            "\n",
            "Epoch 35/49\n",
            "----------\n",
            "train Loss: 0.1338 Acc: 0.7613\n",
            "test Loss: 0.1105 Acc: 0.7599\n",
            "\n",
            "Epoch 36/49\n",
            "----------\n",
            "train Loss: 0.1333 Acc: 0.7574\n",
            "test Loss: 0.1079 Acc: 0.7630\n",
            "\n",
            "Epoch 37/49\n",
            "----------\n",
            "train Loss: 0.1334 Acc: 0.7626\n",
            "test Loss: 0.1066 Acc: 0.7689\n",
            "\n",
            "Epoch 38/49\n",
            "----------\n",
            "train Loss: 0.1303 Acc: 0.7688\n",
            "test Loss: 0.1060 Acc: 0.7705\n",
            "\n",
            "Epoch 39/49\n",
            "----------\n",
            "train Loss: 0.1295 Acc: 0.7648\n",
            "test Loss: 0.1063 Acc: 0.7715\n",
            "\n",
            "Epoch 40/49\n",
            "----------\n",
            "train Loss: 0.1284 Acc: 0.7674\n",
            "test Loss: 0.1047 Acc: 0.7732\n",
            "\n",
            "Epoch 41/49\n",
            "----------\n",
            "train Loss: 0.1219 Acc: 0.7803\n",
            "test Loss: 0.1055 Acc: 0.7710\n",
            "\n",
            "Epoch 42/49\n",
            "----------\n",
            "train Loss: 0.1264 Acc: 0.7719\n",
            "test Loss: 0.1055 Acc: 0.7713\n",
            "\n",
            "Epoch 43/49\n",
            "----------\n",
            "train Loss: 0.1285 Acc: 0.7701\n",
            "test Loss: 0.1063 Acc: 0.7708\n",
            "\n",
            "Epoch 44/49\n",
            "----------\n",
            "train Loss: 0.1268 Acc: 0.7651\n",
            "test Loss: 0.1074 Acc: 0.7727\n",
            "\n",
            "Epoch 45/49\n",
            "----------\n",
            "train Loss: 0.1287 Acc: 0.7661\n",
            "test Loss: 0.1090 Acc: 0.7656\n",
            "\n",
            "Epoch 46/49\n",
            "----------\n",
            "train Loss: 0.1258 Acc: 0.7734\n",
            "test Loss: 0.1069 Acc: 0.7710\n",
            "\n",
            "Epoch 47/49\n",
            "----------\n",
            "train Loss: 0.1239 Acc: 0.7786\n",
            "test Loss: 0.1059 Acc: 0.7689\n",
            "\n",
            "Epoch 48/49\n",
            "----------\n",
            "train Loss: 0.1218 Acc: 0.7828\n",
            "test Loss: 0.1085 Acc: 0.7698\n",
            "\n",
            "Epoch 49/49\n",
            "----------\n",
            "train Loss: 0.1253 Acc: 0.7661\n",
            "test Loss: 0.1066 Acc: 0.7706\n",
            "\n",
            "Training complete in 124m 1s\n",
            "Best test Acc: 0.773214\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "wSA7mHOAY2lm",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Checking Model's Predictions"
      ]
    },
    {
      "metadata": {
        "id": "LoSmnTp416QY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 905
        },
        "outputId": "cf7fe259-e4f6-4727-a4db-fde78e6592de"
      },
      "cell_type": "code",
      "source": [
        "visualize_model(model_ft)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1Jh6PE42FZVumTJnMJy/+JMnaOjp6+li8+BgyQ/l93IKWfxSsqFrGhzYoJGgd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\nLBbLPsSKqsVisexD/h+EloB8eROZmgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9f41a50160>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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LFsylWimQiiVQFYVEXQzPc9j40iYCoRChUIiRkQyT2ycBgqARRXguChKBSIyK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\nsZ9czXFX6yAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef4a334e0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jjz4a3/epVqtccsklfPSjHwXgX//1X/nqV7/Kddddh5SSs88+m1KpxJQpU3j00Uc5+uij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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef5f50358>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XvVqcG63yABMGKNHEWYDEGOMzVwKDS8UXatRLKGoSdbKrQSidWXajrZY0pFYI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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef5c8a160>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SoJTA015TjaO1RxAEeH5I4OfQOjO9zBh+MmGfMezkwgBjwA8UQoCzFucMvu9j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\ngg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef59bd4a8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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kCUliCZOYRCyRExInODROOZxTOAxX3vDPy4qQkfG/kUzsMtodK1cup66uE75f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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef4bd0240>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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H4MEHH2TcuHFMmjSJSZMm8cILL4Qm9tNPP80BBxwABOJ077330t/fT6FQ4KGHHgoDlO+H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\nzB7D/wU17NvrvTbbKQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef595b208>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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mZKHqaUSUDOLpGWhZAtufSVitpEVhFsayWqrMBI5tggS1kShVgRDduhWBrKN4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\nJDHdEgXq78QAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef3ca9fd0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "Dgw13mODZIbu",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Finding top-1 & top-5 accuracy\n",
        "Here i have defined a use full class and a function to find top-1 and top-5 accuracies"
      ]
    },
    {
      "metadata": {
        "id": "0gbYM9SG19U9",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "class AverageMeter(object):\n",
        "    \"\"\"Computes and stores the average and current value\"\"\"\n",
        "    def __init__(self):\n",
        "        self.reset()\n",
        "\n",
        "    def reset(self):\n",
        "        self.val = 0\n",
        "        self.avg = 0\n",
        "        self.sum = 0\n",
        "        self.count = 0\n",
        "\n",
        "    def update(self, val, n=1):\n",
        "        self.val = val\n",
        "        self.sum += val * n\n",
        "        self.count += n\n",
        "        self.avg = self.sum / self.count"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "ztOLl0h32E8g",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def accuracy(output, target, topk=(1,)):\n",
        "    \"\"\"Computes the precision@k for the specified values of k\"\"\"\n",
        "    #with torch.no_grad():\n",
        "    maxk = max(topk)\n",
        "    batch_size = target.size(0)\n",
        "\n",
        "    _, pred = output.topk(maxk, 1, True, True)\n",
        "    pred = pred.t()\n",
        "    correct = pred.eq(target.view(1, -1).expand_as(pred))\n",
        "\n",
        "    res = []\n",
        "    for k in topk:\n",
        "        correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)\n",
        "        res.append(correct_k.mul_(100.0 / batch_size))\n",
        "    return res"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Fzf62TrS2H8f",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def calc_accuracy(model, data):\n",
        "    model.eval()\n",
        "    if use_gpu:\n",
        "      model.cuda()    \n",
        "    \n",
        "    top1 = AverageMeter()\n",
        "    top5 = AverageMeter()\n",
        "    \n",
        "    for idx, (inputs, labels) in enumerate(dataloders[data]):\n",
        "        if use_gpu:\n",
        "            inputs, labels = inputs.cuda(), labels.cuda()\n",
        "        # obtain the outputs from the model\n",
        "        outputs = model.forward(Variable(inputs))\n",
        "        prec1, prec5 = accuracy(outputs, Variable(labels), topk=(1, 5))\n",
        "        top1.update(prec1[0], inputs.size(0))\n",
        "        top5.update(prec5[0], inputs.size(0))\n",
        "        \n",
        "    return top1 ,top5\n",
        "    \n",
        "top1 ,top5 = calc_accuracy(model_ft, 'test')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "yYQT7RdjZTGG",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Top-1 Accuracy"
      ]
    },
    {
      "metadata": {
        "id": "63TZRiRA2THk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "f1b35cd3-9dc6-4a32-9878-c2ded0381187"
      },
      "cell_type": "code",
      "source": [
        "top1.avg"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Variable containing:\n",
              " 77.3214\n",
              "[torch.cuda.FloatTensor of size 1 (GPU 0)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "metadata": {
        "id": "K6B0VvPGZW0D",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Top-5 Accuracy"
      ]
    },
    {
      "metadata": {
        "id": "9pcFjl112VC-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "9a7d68f5-5fb3-490f-d868-a436c59c5f33"
      },
      "cell_type": "code",
      "source": [
        "top5.avg"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Variable containing:\n",
              " 94.3045\n",
              "[torch.cuda.FloatTensor of size 1 (GPU 0)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "metadata": {
        "id": "9pAVjoT5cbno",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Inference for classification\n",
        "Now I have written a function to use a trained network for inference. That is, I'll pass an image into the network and predict the class of the bird in the image. I have written a function called predict that takes an image and a model, then returns the top K most likely classes along with the probabilities. It should look like\n",
        "\n",
        "probs, classes = predict(image_path, model) print(probs) print(classes)\n",
        "\n",
        "[ 0.01558163 0.01541934 0.01452626 0.01443549 0.01407339] ['70', '3', '45', '62', '55'] First I have to handle processing the input image such that it can be used in my network.\n",
        "\n",
        "#Image Preprocessing\n",
        "I want to use PIL to load the image . It's best to write a function that preprocesses the image so it can be used as input for the model. This function should process the images in the same manner used for training.\n",
        "\n",
        "First, I resized the images where the shortest side is 256 pixels, keeping the aspect ratio. This has done with the thumbnail or resize methods. Then I have cropped out the center 224x224 portion of the image.\n",
        "\n",
        "Color channels of images are typically encoded as integers 0-255, but the model expected floats 0-1. I have converted the values. It's easiest with a Numpy array, which I had got from a PIL image like so np_image = np.array(pil_image).\n",
        "\n",
        "As before, the network expects the images to be normalized in a specific way. For the means, it's [0.485, 0.456, 0.406] and for the standard deviations [0.229, 0.224, 0.225]. I had subtracted the means from each color channel, then divided by the standard deviation.\n",
        "\n",
        "And finally, PyTorch expects the color channel to be the first dimension but it's the third dimension in the PIL image and Numpy array. I have reordered dimensions using ndarray.transpose. The color channel needs to be first and retain the order of the other two dimensions."
      ]
    },
    {
      "metadata": {
        "id": "CIFr77GhccIg",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def process_image(image_path):\n",
        "    ''' \n",
        "    Scales, crops, and normalizes a PIL image for a PyTorch       \n",
        "    model, returns an Numpy array\n",
        "    '''\n",
        "    # Open the image\n",
        "    from PIL import Image\n",
        "    img = Image.open(image_path)\n",
        "    # Resize\n",
        "    if img.size[0] > img.size[1]:\n",
        "        img.thumbnail((10000, 256))\n",
        "    else:\n",
        "        img.thumbnail((256, 10000))\n",
        "    # Crop \n",
        "    left_margin = (img.width-224)/2\n",
        "    bottom_margin = (img.height-224)/2\n",
        "    right_margin = left_margin + 224\n",
        "    top_margin = bottom_margin + 224\n",
        "    img = img.crop((left_margin, bottom_margin, right_margin,   \n",
        "                      top_margin))\n",
        "    # Normalize\n",
        "    img = np.array(img)/255\n",
        "    mean = np.array([0.485, 0.456, 0.406]) #provided mean\n",
        "    std = np.array([0.229, 0.224, 0.225]) #provided std\n",
        "    img = (img - mean)/std\n",
        "    \n",
        "    # Move color channels to first dimension as expected by PyTorch\n",
        "    img = img.transpose((2, 0, 1))\n",
        "    \n",
        "    return img\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "tSsEYuJ5czZA",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def imshow(image, ax=None, title=None):\n",
        "    if ax is None:\n",
        "        fig, ax = plt.subplots()\n",
        "    if title:\n",
        "        plt.title(title)\n",
        "    # PyTorch tensors assume the color channel is first\n",
        "    # but matplotlib assumes is the third dimension\n",
        "    image = image.transpose((1, 2, 0))\n",
        "    \n",
        "    # Undo preprocessing\n",
        "    mean = np.array([0.485, 0.456, 0.406])\n",
        "    std = np.array([0.229, 0.224, 0.225])\n",
        "    image = std * image + mean\n",
        "    \n",
        "    # Image needs to be clipped between 0 and 1\n",
        "    image = np.clip(image, 0, 1)\n",
        "    \n",
        "    ax.imshow(image)\n",
        "    \n",
        "    return ax"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "opnb8wLnc766",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "outputId": "ceb46e91-5942-4237-ef32-8b9d559bec02"
      },
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.listdir('Birds/test/018.Spotted_Catbird/Spotted_Catbird_0001_796797.jpg')"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Spotted_Catbird_0020_796794.jpg',\n",
              " 'Spotted_Catbird_0001_796797.jpg',\n",
              " 'Spotted_Catbird_0025_796819.jpg',\n",
              " 'Spotted_Catbird_0009_796795.jpg',\n",
              " 'Spotted_Catbird_0016_796803.jpg',\n",
              " 'Spotted_Catbird_0006_796823.jpg',\n",
              " 'Spotted_Catbird_0027_796796.jpg',\n",
              " 'Spotted_Catbird_0032_796828.jpg',\n",
              " 'Spotted_Catbird_0044_796809.jpg',\n",
              " 'Spotted_Catbird_0026_796818.jpg',\n",
              " 'Spotted_Catbird_0018_796800.jpg',\n",
              " 'Spotted_Catbird_0047_19400.jpg',\n",
              " 'Spotted_Catbird_0048_796817.jpg',\n",
              " 'Spotted_Catbird_0010_19436.jpg',\n",
              " 'Spotted_Catbird_0022_796821.jpg']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "metadata": {
        "id": "ysKFbiGgc4_q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "outputId": "54f726ec-0d63-4a5e-fed1-72eb5ff885c0"
      },
      "cell_type": "code",
      "source": [
        "image_path = 'Birds/test/018.Spotted_Catbird/Spotted_Catbird_0001_796797.jpg'\n",
        "img = process_image(image_path)\n",
        "imshow(img)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9f0b2b1dd8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/9x4A4vEYTz/9NOGONmN7mWgxRtAvlrO5NIpiZ3JCCNXpqUn6+vqZnRVC9atf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DLJxStXCbnq5/lahWK9xsGjhwA4feYs+x+MsGuX6I/PLc5w+cJZ/uePfxyA86de4MhOIWMXxEtl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\nMhgMxhxgTpTBYDDmAHOiDAaDMQf+D9mtbQqqzuwjAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9f0bddbc18>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "g3Rzv7fTczKO",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Class Prediction\n",
        "Once I have got images in the correct format, I have written a function for making predictions with my model. A common practice is to predict the top 5 or so (usually called top- K ) most probable classes. I have calculated the class probabilities then find the K largest values.\n",
        "\n",
        "To get the top K largest values in a tensor I have used x.topk(k). This method returns both the highest k probabilities and the indices of those probabilities corresponding to the classes."
      ]
    },
    {
      "metadata": {
        "id": "2d4QfOW9dX2a",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def predict(image_path, model, top_num=5):\n",
        "    # Process image\n",
        "    img = process_image(image_path)\n",
        "    \n",
        "    # Numpy -> Tensor\n",
        "    image_tensor = torch.from_numpy(img).type(torch.FloatTensor)\n",
        "    # Add batch of size 1 to image\n",
        "    model_input = image_tensor.unsqueeze(0)\n",
        "    \n",
        "    # Probs\n",
        "    probs = torch.exp(model.forward(Variable(model_input.cuda())))\n",
        "    \n",
        "    # Top probs\n",
        "    top_probs, top_labs = probs.topk(top_num)\n",
        "    top_probs, top_labs =top_probs.data, top_labs.data\n",
        "    top_probs = top_probs.cpu().numpy().tolist()[0] \n",
        "    top_labs = top_labs.cpu().numpy().tolist()[0]\n",
        "    \n",
        "    top_birds = [class_names[lab] for lab in top_labs]\n",
        "    return top_probs, top_birds"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "50c4BVByeGrJ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#Sanity Checking\n",
        "Now I have used a trained model for predictions. Even if the testing accuracy is high, it's always good to check that there aren't obvious bugs. I have used matplotlib to plot the probabilities for the top 5 classes as a bar graph, along with the input image."
      ]
    },
    {
      "metadata": {
        "id": "oKY8aitPd3X-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 640
        },
        "outputId": "ed4b0778-5cbf-483c-8479-99104330c3b8"
      },
      "cell_type": "code",
      "source": [
        "def plot_solution(image_path, model):\n",
        "    # Set up plot\n",
        "    plt.figure(figsize = (6,10))\n",
        "    ax = plt.subplot(2,1,1)\n",
        "    # Set up title\n",
        "    title_ = image_path.split('/')[2]\n",
        "    \n",
        "    # Plot flower\n",
        "    img = process_image(image_path)\n",
        "    imshow(img, ax, title = title_);\n",
        "    # Make prediction\n",
        "    probs, birds = predict(image_path, model) \n",
        "    # Plot bar chart\n",
        "    plt.subplot(2,1,2)\n",
        "    sns.barplot(x=probs, y=birds, color=sns.color_palette()[0]);\n",
        "    plt.show()\n",
        "image_path = 'Birds/test/018.Spotted_Catbird/Spotted_Catbird_0026_796818.jpg'\n",
        "plot_solution(image_path, model_ft)"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py:1428: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
            "  stat_data = remove_na(group_data)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FKvPY+dOwCAewSC9nkmw8J4hQSyESkGDjqaWwzAUcYRhNPVr292M+R1cis1IKofaE2AGV\nvrffSwjMuxmL3NtcSOAzt9/Hqd9wIloqImoT4G+exEiwgJBFznQpEWJHLePzqVWBnpSUIQTEokcR\nGaM1/BZUhnupFUrOiL97zXKpxCCUFq4CIQREoBQh+rHjPGVDY4bPt/u98/b7ecZpJxICsGg3tTqP\n7R7K8OsQE7Vki4ijvSe1qiM5EPx+qlaoSgyGbBytNjnNyb5mdsIJJ7B377iL/dKXvsTxxx//hMc3\nBxPEYTtfd1QVgv3e1gClasEcJ1TNNBQuBJjNkkFStSckHLIsKwsSINDNOmpVaqkDfBkcOmuOqy00\nKSViEHJfaMitiC3w6s5Moo1JCxTJEA36rQDVQTsJSFAUpdRijq5CDRg0KwoNntXKuM2wfweEXCsq\ndjtxvB1zgqrkxQKJDue6L4lzhwpzRYoS1OZRtaAolbjB57RpUlFCaot4sIcifl/+vNppEoWSC3nJ\nCDPaA/X/trsA1BbZgvqzLuNiHUAaJKmAz2+0IVOkEIrPUVWiCFlxhzZc3p9ncz6V4hCuiD3n8f2K\nOJLqcGklBIfCfRehFSQmIKMDkqwOfQpabBwhJETCkB4Yn16FkO354zBsxcdTh8+wn8XnToa0A+6Y\nmgURJESCFmqDTQX7fBiO1ep/F3tSWgrdbI5IGCDxWitBkk0uoxMezO/j0Y5PMDi3auFRZ2wwbTd7\nlNrRux2Y7H+7nX/++ezZsweAW2+9lRNOOOEJodnJJptssv+INkWak33N7JxzzuGss87isssuQ0T4\n1V/91S97fM0t2hOChSX2s++SSdF36RkGugmIBHqHAINANzNCQq0RVfUdvF1LPRoRFYqTVIpHgSnY\neblfIg4xKUKQQEoBkUCIvoPPFi3G4KQMIEgFqoVEEqkilJrpKwNhiVAJVagiVApBheKInwQc6nMi\nBYWiFsHUYmQgBSgF6aKdoCs7eG2RY3VCVKVUpaBDtCcWDBODoDGQ+0JfM3EWkSLj/Ei0A0NhCCMU\nJxBZ1F48vG9/FhGHWAulikWwVQe4Lja4ujp0p0rRQgC7T78XqYGAOIowRthF1ShMOrwaJBGCCMWj\nX4axDKOyuSyOAqjBtiEEUpr7nCpZ7flosWMkGOzawkojStnNNii9KkipKEYYaqkARFCHvu19hqq9\nzUWoqARQobYo0C8YxMg8CgN6kVKHaou6V6JAEYJWRBigWHsFChJmiI+7+CtJ8utHey+UQOerfUqJ\nWqpFTI5W2HP154ETi6SNE5Rg3zEUfx1A7HfBj7Pvc6WqPc+j1SanOdnX1H7hF37h33xOrYoYYAiY\nwylqeTkJYczjSB1Yg2XEzOh7pZslQhREEiFFoi8EjXVZgT5n1JmuDUFExHJojRFbgWoLbZ+z5dWq\nGosXCBqGa1rOyxfYJJRi8F4MqzmmQC2FXM1ZxxAGRm/7/NIWrZW82Cr8VVWJ8lhQSLUQRJzNq55z\na380ByckJEW6lNBgsGvO6hhTILR8nShoRYptLmwhrbYBqQUto4sap06MWRyEkg2mrsKwYEoUyHYz\nIgGlEpxZCZjjcUsSDPqkkrBnnELAhqWUxjglGJQeI2xYmDc6TQeMgezOK5LzepvyYaIk2Gctc6HW\nOm62SqWIeE67/e7ROUpjAStCzqUB85Y3F6iIw6bF4fGNjiTESJJg73rN7vCUEGwDYRsrGea65TUb\nDFyrMX9TKBv5A74JDcHGkXNvm4HUMGmhzz1rzIlhQMNpcLxnRMbnrMa/ljYed5ZtHAO7XYK9V0d5\n5f/kNCc7YtYWhEa0yS0N6Im5qlaiERBbjFu+SgupJaUEoJBLdmeVPFPjC7O74ug5oeKlJi1uLblS\nambuTm50XJYDKsAsJYIEVHCSka0K0ReZXHrQkcSEKrV49NgXqprniCHazr+o3485c/UIrlZbSCX4\nAunLlqX56rB42+g8nyXmPPucKUXpNiWCGKEHICVb0Je1Qhchwjx0FCCHMub5fC5V1PO8dm8qihKp\n6AanDtBni6a0VjREFCvzYbX0AtBgkf7qQoyMi60OmU6G8wRfrMUi2dhQiCiEGI1AJTIiBC1qbaSU\nWogxISGipcfy4YGSezuuAQHBnG/JPUpAJPnfrUQnBBmcPHXMfcdSWdqjtui+VisvAWoR4szIS7la\norYipBgtam75x1LJKwQvK0+xiFVrtk1bmxPPsdsGcszHhwD9srDqqSTKkK4EI1fVWgZSVC7KrJvT\nEX1DU9GiFMWi4kfZKgFv1bTlXdv8iG0odaWc6Gi0yWlOdsRsYIQGqyEbYwSBEMlYdKlRQYXg+FLJ\n6nCkQay1ZipKqRZZJIVItFW32CJZPAJMEgdCS5CIqEVR5LajT7ZQFXPes+hxUwzEBuH5sEusKMUX\nQYtCNAq5rCwkCBLmdCKUWqg1IFKRENBicJfQYL3mzBW0mCsRyFqNY4Q5fbAISaXabIXo167k3mpS\nW2Qq2aIErQp9GRya4Y4GB/qND3WJCTWCT802j16LqD7OVgsZsDraWiBUo0CJxIFAUnvHVWsL7QOl\nGi6ttbjD8qlyopMNy+ahF4hif5TkS1WIFsEpXnlanYjTwkH7TwwJVJFSiAhl0TPrAnE2p6w4K8Wc\nr4oFkTE4QoGitVgUJu2aRtxSjJjVkd1BBFIc0QUtvvlyGD5IsM2QRCPq+OYjOgnN5kAJsTKXaEQ3\nVaKWoQZSa0a6GbHh+gCa0QplBQyNKZCa89ZMEIOP7fPbfZgj7HOx6Lm9qSLEgUgVh01qiJEuRIv2\nayUoiKMxYWXOhQrF0IGj2SanOdmRM//utzxN2/1LMKdYJECtFI9oSs4ksdWtLeBVA9Vf4xggkI0e\nj60tseVlQqRSiNGiklINDrZSlTU6L6eI0fKi1N4cRrHwSFFK6SlZ6NxhF4GMWiRlAzenEE3gAKBo\noCJohVoCtY4Qc18yaB5KOaqjW+JhVo11YA9bZFapPknZeakiwiwlh/mqrdjVYD8Arb39Www8rIXh\nPFFbDG3SLSqWENF8GCk9HZEQDWJcLhbE6P0mPZCIwaL6oWyFQGQUniiY4zAY26Ia9TVfSx0cdiCO\n5Qtt+XeEuOUTg993X+sQAYqsQt3qCL5viGKi7/PAcl30PYFISAkcTvaZJUpFurY98CjOc6LLKoPT\nDKporJSSbUMRguXAqVbK0hjIVI+Ug0XIwf6tpVgJTRjLQ2KwEqDgN6ylgNq7GVIcmLJtnAWLDPGo\nUKikxgHw7wDB0IfmnKuLZbRcvIihD100YY1ajGlsUXAgdR0xjfB5xmDzZb8gdTNmKQ1CBqvogzR5\nkhUI/mi0yWlOdsSsfbEMwqrDDjVUqLokizmDKBFJeQO5QD3Hlds5ySOiWqkKCScorCiqNEUai4RM\nOQURymIBnUOkxb4SATWFG7VavBQCeWnKOCGOX5uiHgVLBRVUcRJRc+qFPlu+MUkaCDu1MnqQR2/N\nHStNDr+2qNVyaI2MI1anF8zJhxgMAl1ZuIdLAUSHLh36jCqsmkUNyTOjgeikmVKtxCKmcSOQPOJX\nVYpW35xYZFfqGB1ZTSIDpPloG/KH7oWrw7fqBKAhT8tKeA+I6OBE2zGWq1ZSSCvHWV1ujMI8zqk5\nU3vbbrTP1DLsAagyFlm0eQvC8CwlWkSaUrKTAoPT3khLanNtSARVjSjEmENtVr0Ux0LsyrJBm+JK\nUUNOE6pYfrzv7buQukSIiSQyQr4KeN4eRvJW9ZrO9txoakI+T6lLtPx+zj0lr0CsEjz10SFBKGqR\ntnreuxWgzJO9s7nPQ93z0WiT05zsiNkIDanXHdpP9sUESoY0QyLEEvEMoJ3hp9bqhJcs0EVKrsRk\nZCDB2KwApRbm3YxSisuZBRTL3ynKY2sQnYzSBUfDlNCZnN6w5MVAzC3MjENekMog0xaCkERGRiKg\nGq14PASHyvxeMHapVIctdYQeVyM6wCAyEVQrfZ+RkLzQ3h2aL1pVjCxkJI1AQqhBqSVa1N0WfRVS\nVyla6eZzKMoy9+TeQqW1tc3k3qBuHaJYBwYlEqNscEDjFMUNpK1Va4zXIVqUlse0vDOlGKQp5rjb\nu6IVamiMaga31fK79rwbZG5oRDQCqwkgUMdzpeWMLfvdnFtVc8K5gLG3IVSrgxVxoQFM3s9IYzqS\nsIBabDNRqteJAhIiqA7zGDxfa59n7/awvbDi3w1FgVUMNlfUor+aiShRurG+k5brtEh8WWyLIGWU\n5Fs1Xf2HKrlmr7MMQ5641mIbwxjJeaxxHvPTjqpgkHDVPOT9j0abnOZkR9xETFM26Phz0BZwrSSV\nVheVMRbwk6wcJK5tptbCsu9BYBbG3GfOvUNVDKzcIIHQlVGkJQZCNVYsEboQyCVTFLoYCJGRyakg\nMaLF4EP1NTDn4vlGQC0qMtKE3YuqEUcIgqqMi5N6rtPLJIoX9JeinqcciS4G4dpHWJnHWF4hQbzU\nwBb6EKLn7XzRV4FoObUWqQum+BNqhb5HgjBLc2KolGpOWOtAS/FxmVPPmgm1OSGLsJo11aUNCkPt\nCbZoqDkVv3RzhUVAPOrU9rzV/q/P1Zm7fp++4yoLj8RVLTpWg/U1BntW2ULE2FQi3LGFGBGHzsGe\nZ0VNEnbl/bNnWOn76nPYEA6DtpuFaOIRbWNQC1CaMEHLOa7OhmkBh1kw2LOV6AwfbeUcIQlIN8Td\nGaDUYZMkLXfp0G2MwdjQjLD5MO+r5B61/HPRQpc6YifOEYCQ/UgfX8XIbAYn10HAohHaUB30lI9G\nm5zmZEfMGnv28axWpThVP/rKkZxZWvoRqpXgZJAQBojMdu0GKYnncWJKlGw78zTrKH3Psl9QRFgd\nhtbe9v5aCESyBmKwHE2fl5A9bwSoJFopnaJoDbaArNDx8ejHBLgt+qlaMKahxVhLh8IMwrXItVCH\nexzVbuJQAykrFRdd6pzoYZDm6loYYoIQh0XPAwpzQhKQgfkodN3M1HEI9HlJVYhphhSl154030i2\nCSmQ0gx6LCL1xX5gxdZK9YW0i7MBEh3m2i9UchmcpRGY6pjTDCsOdZhPc/gDOxceAweKCCkFqJ6L\nLu5EcYfE6OAM0Sye82vXtBrY+WyNFkKWWsg+rhACi7xOqZ3lsktlpXxy2CiElc1CQzNaLndVek8a\n4qBW9lKcRTQ4ONWhJhTfZFQYXo6B1RvEI9pqDOwmVfgo5nMQYblc0BivIQSqKJHEsl8gEsfGBA6H\nxJQGVEZlBMzb61ZqQSQQRYa5Phrt6L2zyb7+rbH5fMUc1hf/FnYxDWUXUMlZnTHJcLDvha3oHVjk\n3qHIMjg0MAJJ1yVLcfrCJ8HyOCI6RJoi0bucWEmHSb9ZvrXBeuJ5MxMSMHyvanUCBqxqi7boz7Q8\njZEY1Dp1tDuLK2Qcq5GPlN6g0ogJLbRbbhGkolCtM0dboETa5+mwWGaF6KxWT4xBMMbuKsgmro0a\nxBxlKVBYoN4Fo2M+EEMa+aMJOKSUIPee312BhnVjKYYEGZ6thFHWzYgz9mRVKkmSRYBeJ+uJN38N\nKohFuE0fVbz0p9X7tnkvdSQKVS0k6Wj7iiEH2J6Bl0r0KxuOGJITp0YIVanukCO5RrQoEqtF96s1\nlbmHwkjAEXvuORdybvM31vIaTKys9+uD5mzO1RjkOEFK6lAuBaDBNpGre5HVnGbJhTTvVr5YZiYE\noqRuNgoTNPJWI2g96pxSCloKZRXhdZR7+I6udKJ5HGDhqLHHz9BPNtlkk0022WSPsSnSnOzrwrSO\n9We1VNupEyFZr0VLGFbfVSsD47TapjiYbImTVKzEI68UWXfA4X7J5rU1E/OmkjrrvxglDhGHwZZC\ncsUXE7q2kpcUokPEfmzvbE2BvmSPmL20o+WP/HqlWLmLSBrgxKp4JOYRW3B1oBXmorjUX1+yR8Se\nI7MkGTEE+mykmC5F+mzdWWYzKw/JaszNRiZSUYqa0k1RD7vcSjbS0LJkCJE034RW9flSlg61thrQ\nNOtYLhcW4aVAykaZGXbiDnlWVUrfD9Fli1BbsX0jvApOnIkW2edikWSUlWVKBNWNe32LtgK19kOn\nnNVIJ6aOoFa+o9FKS4ZuNMX5wl2CKivqNiZkkEsdI2wAGdWiaAzfascPfSW1rPS9NLWmEO16MbLS\n89NgfPU6Vit1Kg6pCymNC3QheE2o4x1BTMpHTTS+rkT3rcwqRhs/qmNOGEdTQqEuMyElcq2UXIjJ\nepiGEKil0q8I589SMqZ0y2AVtYUKAAAgAElEQVSuYrNDoOnPuhSOZn2DyWlOdsQsDoWZsoGKLxKY\nhRnSpQE+Um9SHWem4arLlosztqwANWdyAZklUpwTukbnH3gLLPpMCoFZNwdRcslDuzD/IBRYeh2n\nNQQ2h11UoShSG6RlOVVV42lY6lVJcWxyHLyutCaDrCw32lvuh6Y6NrJITXPV4NTO26uUvvcaTQbC\njS3uVj+nTo6x5tWew2plHzFCkGGNq9XLbR6jd7bCLMIZwa1IEkEpdGk2PJ/hFAK59qTy5dVGJYSR\nrOLEr3ZC0UJqz6Aqy36Jc1nMQaw0E1cv0ZBg0oBgxKzq9ZlDA+xZZySl9QUAseusobUNYBhX8UW+\nEyvh6YaOM7BcLB2BdPg7GSko555cMqmzuk/ViqgOJVSqal1yYjQHUq0ueEhzr+Y5vWuIQbmwNl8b\n4GPNOjyCGCth5o26W97Y9zz2/o4bCVNKsmdTcjZnLWP+Q9Ehd22TUEGrkcY8zy5YXeowX6oummAN\nq7VkxDeRLV8qxSQA+5Wyo6PRJqc52RGzYbdvST+05b7UnE0M3u2+GA2+Rv+iFx3OTcFYh4IRPALJ\n9FKjZcoGtimV+dom+n7J+nJJFxNdl+jSzHfj+HFWIiAhWu6sOsO1gKTESjtDz4cmhGpCO04qyrV4\npAyLfknXdVYGIOZ8xJm+IYSVIprRYugA8Z6PAhKIST1X1Mo9lpijNGawqpUUxBSG+jnwtlcazB2H\n6KzRbkX3/bGuLgbvVSqmigO2UDSmahPLXywWqCrz+QyWSu1XnicMhfnNhhyn6srCbqW0QzlOtFx2\nEJOhk9Ku1a5tpSA1Z1KM5FI89xmZdcl2MkAttjEZBZDKwMJVHWXnggg0glAplqMGSs02p3E2KBdZ\ndtMcYkomllFzXslOt9dCnP1sUbIkI+bUokMJlB/oZ0aTeYxANZWhquo54ha9BoIoUisB3aDxm3PZ\nQPQZ2OFOBEpd5wSjRtAqlu+M1t/Vk/J2rIiRumpBViQlhUIkIUkgBHI1da0uxiHqDFoJmGDG45W3\nHC02Oc3Jjpw9ylsMcY1ErHOGwVXWGcKL2LESgrEy3piyiu24Z7POuplUVwhqnSdiJFej36SYIAaW\nvvh3Ege4V4I1VY4ixNBZVxS7OBEv3fCFed7NSPOOXAp1aVFJW6i0sXZXeCxOGzLBdxEkqJV/uDWh\nhNkssVxm+r4nhMBsnkZm50CAsmbAWpUiFa2FqFZiMWiCgingVNt8SK3UKg55PtGiFgYBeVRx6VRK\ntajczO5/bfNm1KOoKsWZuXUDk9X6T+rwb/U+l2KYuj8b74faSjKCUWZLX1w+cDW69SL9WsjFZOCE\nwGzW0XWJsnTRiz5TtGfe2Qag9JmY5qZxXEewMgQxYQx1pMI3O9ZW1ZjTg6A+FRV7ht2so+8NuQCx\nRs3u2JvKj+YloZvbhs4bbYdgWrDgKIBW3wQqsfimTa2bS1phoFYvCbG5EDpxxySQ82pJTjVMphoc\nHTzKrERUW82yeu2m2iYqCqJCChAIaO1tDIPMYYG8glCU6kpZFS1h6FZTqm1mYpQv8379x7fJaU52\n5GxA5Gyh7VrNnZi4gXpOKyCoVfNDtUWp1dmJmMCBAJI6q8Wr1SOOaFJuQM22kw6SmM+tAW+WbAtT\nvyKaUA2CK9LKISwKjTEMQuYtB9mXTF03Z5hzBjG4rbVjgjHqAoPcordSKu4k8mrnjGCQZe4tyokx\nkGJCiCyX68Q4RmeKR2ueC2v/Cy4M0HJcMSTLQlWLNFoEUAV4VE6zQXzquqIqVshetEWNG8sWZrOZ\n6bguDmMBmy0nQyyVbfZjK70QceapH+ebFq0ZwSIj1UIhEsXh1mCQdQwub7dSC6mKNd/2pOhy2Y+1\nvgFC8fKkaMpAbaMVJA4sW0LYMAVD6UY0QQhlFN1obGMRz7dGGcqh7MGMjmLedabhr5D73h18QYlD\naYp49Ok1QEgU5l0kF3G0A0cbLIfdzWaE1cYA2F4vBhlEGQrBNd/tuGXfD2zZ0ua7FKJYg2otGakm\ntKBFvfmAt83z71gtkVyLO3ibhRQjVKXqqBkdKlTnHdSNwzyqbHKakx0xS22R8ULuoVN9KFSUXtTK\nFbz3n7jqTIhiERQMJQ7i3SEkF8/RKCJlKLzOfSatrQFGSsklu+JPR5EwyIapJyitNLwfF8xWprKC\nxJVSrYOJB4CSEinZJnzh+bNSKiFVFzgYWPpOLoneZ3KlQL9C1mx53TgjxEAt6pBdHPpfNucRmxpP\n7dyZW/nGUMNYBcFzxoj3P0zkpqT0qNqAqgwpTSF4Tq34NT1f6nNlOUJjgsSUqFSixnGjEEE8Z7hK\nUMl9P/S1BJCSSF3CO5zREsumtuPlPg3yHTqEGCqQQkRCpO+X9H3PmueBRSISrXuHyQFHar9A1Rx4\n0w+uaqVMEqM50/bAkyMW1CH3HqMRxqoqNfcbgRLVUdoRQw1arluCEFNHt3kTtRQWC1cE0mit58Qc\nXVaohxbg5K+Y4uDEg0LtyyBIUKqO1960tqECtqoSiilOaS700hs5zY8qEYvY+55Y1GDeFi0Wi6St\nQ8y4W4jSqmXVnIZgkSa44jCEuVh+OY8yfkejTU5zsiNmyfeos2CRXyOvBFFKJ/Sdacn2ZclcEnMJ\nLKp1MZFBs6ySCSSJpu1alDW7iH2VWx1aF4haXGMTpApVM+uHD9J1W0cyUDHn7J6NWRcpJVg3jyrI\nymrQdSPrtohBjNk9azef2z12M8uDOou2Em3pavJ4skKQqZYDi+40tK+WX5LCPCZil4bFqBbLcYYa\nEKyXaMm2UMcURzm9ImNDZcZWaDFZPnWQLnSx+VoKtTNnEjw4qyVv0NsdVYmCKd1Ui5hUxPz/EDkz\nkKZiq1f0FmYhmZapjTESi0WhFoG7XF/12ldG3dRWZ2nVgYJWExzXEt2B2jj7PiMSTZ81WI/QyCPN\nxTMP9nwyASmFUh2G9vdqnUCvlaQ9Mbh+67JFWS5okK0LTEi2xWh9x7Vklgi1ixbSxzCQxKoEih9Y\nEJIkalX7rBBJbHEHWsh9xX07MXWoOhqjgZCNGNbEDlqIHQ3ugKKkOCMkkzFUgeIXy0EhVCR1LFRN\n8D2AVG9+GiDrArKPU7FGAaa0P5Cuon922/xUbONaGY85Gm1ympMdcSu1OvbVIE3PsWDRThATTA9q\nBJ24sjMGhnZGfe6RvjKbzzAnPKq0zGdz+j47m9DPi4kQ4gDhAaSZCSBkZz2CabTGODJ5G+nC/KO3\nXarGgixVvZfjmEu18oTC2toaKkJZrIOEgb/atFxTMBWWkotFKlUH5qJoZRbikF/rlwtmnUnjHXZ4\nVGI0CG+FhGHdK3QDsFprbf0oBim3sHKEwDCGKN7qSVY0dIYIpCU8naWs1chKnW9UeqX0ywGOLdmg\nvOQhZYMLJUApwXpY1joQdrJHPQbR+9hcMUmilfEMbFrZWFA/wNhqkablwz2EjoNEhjF5U6IU044d\nGN3VH/DKe5n73li7M6GL8yHqbGMc3ESMRFFi8QZkWRzu7ZBSqWUsOYminmMWOlFCsHyvzdD4/gqm\nuBMw6D1gUHyURF9G1SzznwadShY6SQRVhIIj3iR/1NHfQdzvRomQVqLEIZcrDs/7+xgErYVlaQ2z\nfbNbqkXs3UYt3KPNJqc52ZEzX9lSjGgY+0qmGIFMv96b85RAkmCsythybitswUa80Eo3mw2Qo8GV\nDknl6uUYdeyZ6wtw7MbayyDBWncBYWaQsYhBpzG04xzyLdWpn2qpsYKxFIsOxKJ56pjHjlwydbGg\niuXQRCshNsm8FTJQLuTWR1GwcgdXWMl1VAtNMbjqjcnDFc/rWkqpUF0U3CDpjRY35AU958so0B0U\n5jFSFfplT+l71tY6eifZjLmxagtvSpQ+ewntyNIEvPuML+auujNArX7fQbEwu9SGC3s1i+dY1clY\njFJtXbANj10rDmNvZJchR70qFu/OX0ulr2O3mKpGRhpE3jFxm5TWyItHhp1FCmOZTK2eLRdp/VKG\nvxWESCbVbHq/gBTxTwNCI+QwtnRDCRhpKPkEWFVJI/gUtGZLKQ6wbzLGbe6GspiAeqmIEGvLzQqi\nleTXmmVjRicnQBn+Yb1lRdLQGWXVVK0gOkVB1TZv6mQ98XxzAWLxLjiPvcRRY5PTnOyrtiuuuIKb\nb76ZnDM/+ZM/yXXXXcett97Kjh07APjxH/9xLrjggiM7yMkmm2yyr6FNTnOyr8quv/56Pv3pT3P1\n1Vezb98+LrnkEl7wghfwcz/3c1x44YVP6holryitwLBTVzFyQdI80O8lG/nCCCTjORqsuH3gj1Rl\nsVwQotB1cxqw15eetfncoLpaPWKs1AJd11E8B7PMhVQjMYjVAeZsrFNG/dcWqeXsiTAxsop4FLBp\nPhvGl3trnB0RixLEmgaLOrlDGeCtXLPpsTb1bhGCGAwn0RopNzJNms2M2Zoz3SyhkkysOxkvtHWo\nSBsmeJxjsHkYokKpw99ETWAdlLy+pJaCVJh7H82sLZK3+k8NClGoRShFN/RiTDFZqYrCrOtYVhN3\n6FKiWxEuX6UjeTA+sKdhZIOGlUgvhOjiEwaZ57wCiztjtLoOa0oRSWmooayNVW0JZhdIYGwllzPz\nNYvyx0Y6wXN4sL5YmmBBq/FcGX8VmCnMvX62NUxH6tiwHINHLU411SGbzRkq6iSmVZEAQy8E6+np\nqg+WA9ZBpoAWisZgSkPqkXuoI0Qf1OD4nL0jOZVK8VrMFdSjkclUrWzJIAHvU+vlVyuoQimFEgqx\nrhCqjkKbnOZkX5Wdd955POc5zwHgmGOO4fDhw4MA95O1JlCwLMXYsStJqZgiM2sfTxeDkWJKISSr\nWWythyz1VKgSSEHQvg7XKTU3hM9IK1WppRKTQ1tii2OpY5d7SjGBdokEgZSEWsWl5DJVR9Zn8jo5\ny/l5b0wYWoGBLVa9a/1ZrtFguko16E3HThZgpIpgBXaoQ3eqSlLZ2IS7VoOkqeQSDOqN0ZVnZBB5\nt2qT0TnKMA7/88qHj6o7lb5fAtClCLVDcyF2zXGt5DRRY47WsQXYKqmqjWFjGYzVnLZcdJA0qOm0\ntmJW7G8bg6rFJeQga/WRJmIsTcvA2rGtwsKuzF9Kg2mNbUord3Xl8RAhxhllufRm2m2Oy5CDXW0N\nVqqSikOzwZ5kXkkV+Kd7yZS9n43zKgHQMZ9a8B6XVQiNqVyN3WrKUAFdwTlFohUfG0+MUt35NZF1\nH1OtppikZM+/++Y0DO22Wdl2ellRIYrBtoMNIhXedaVWrLKqEmIk0BSPxu+9VmXRLzekAI42E119\n0yab7Kuwq6++mptuuokYI/fffz9937Nr1y5+5Vd+hWOPPfYJz/vkJ/+VM8/85v+NI51sssn+d9jJ\nTzuOu+/ae6SH8e9ik9Oc7H/J/u7v/o7f+73f4w//8A/5+Mc/zo4dO3jWs57FO97xDu69917e+MY3\nPuG5T3nqdu754n5OOWWnMfcaGSdGa1xVMlKsF2ZysW8thdilgSRSqCZKHmy3HvpqcKeIK7qssEIl\nULU4KUW8ZKJsgJKkgkSTcEsysnT75ZIYYTabD3T6QDewLRXbjTfZuQr80633cN5ZT3EoWOibWENw\nxjCgwQvH8cAsWNuwpRphKbrcX6omAt70aCUazBhdW7bUSkqRmQvS9wuLFFOaoap2nhjRSFxkIMQ4\nkD5EhNlsNkjjqTNna630yyXz2abhWK3CTf/0Sc553hmkkOhzNmZpFBM49+OCiBGJ/L4b1Cjghf7O\n+IxNyq0JDoAWpaiJT5jGrLOGS4FsYveCCSW0SDqlNMC5VnJiUXWtlfl8Ts0Lay5dW+9MQxzW19dR\nmri68Jk77ucbn3k8tUDfL4eoPXWJZZ/pcyYmZ1OnSKnZmmL7cQpINr7Pps1rHD68zmxtjcPr68zm\naRAzr5hI+iPr6yaGoIEubiFFWCwXlLygm8fh2M1ra+zff5C1tTViSBw+tG6C65pWBBiUlAISAv1y\n4c0OHOolc9+dD/GUU2wjO+82WyRfKoFCaIpVKdLnwsKFFUKMSJhTVOmi0OeesuzpZh0xJZaOSmht\nzyCQYuD22+959Ff+qLAJnp3sq7Z/+Id/4Hd/93f5gz/4A7Zt28YLX/jC4W8veclLuPzyy7/s+Spj\nTnOpmdbMMORsMnbRmK3qdWtedU3xEox2LrQ/hUEwYXCDMkJrVStVnfHpDX0NSRxzM625cxi0Uc3B\nzOfJ6v5SGFRaVE2L1DJTjdLoEGirZQwG5xZVX5Sr3Ysq1qzaVHuGMfpNJQmmKIOiOQ/JvJaLCy4i\nULE8F6E1mDaH12oVYoxjxxXvWGKiDsk2DK2OtVYWi4WJFNRq53j+TwWWOa/I44XhnJ5igvIrc77a\ngDuIUFrJSHAtYK3kMs65lmzMWtdbjWo53LU4t2uJrtT9VYgQ6yg4EIKQs3dE8XrSJoLQylL6vvcc\nqmzwz0PXDj+2makyKd28cza3WWsOoMByuSQWK/NBMrXl6EshxjWkS+zbf9DY2UWZr62x6NeHLidr\nm9YIQBdMK7dfFjRWDuceSYG1tW4oOVk/vM4j/bpL3WUeefggO3buYP3wAsQZq0CIHQcOH6QvmR07\nj7UNgRZiJ3Rxk93zWkdZLFlfLggh0kXbcOJCFFEsPRLbHMIgj7j05xtmkSKYQP5K+rL4prT1XD0a\nbXKak31VduDAAa644gquuuqqgS376le/mte+9rWccsop3HDDDZx++ulP6loSjR4/NLj1HEoVrNC6\nZshK55JqNasJR9Pq7xSR5Dk2l5UblkInfLgiTXNm7YNUq9cRjnVu7b+NdGQ+wCNK1VE0XW0xKe1n\nsTKKXCtxRc/NcqYZDRFCoagRl4ImKyXwzyye+zP92ojERK1GotHYsSJTa8f76r16R6V6Nxa/k5zz\nqEMbTAowRis1KKWMiy2BxWLJWgxD5NYyXxKi58mcANRqGYO3tmpepM3dMImrnTea6lEwlSJRah27\njrRCeVq5RGAgmqiWITK3wwWCoqUOdaZKJVcdlI601aiIl21IoVTbBOScN16LUQKwOc7gDr9iUnTt\n2Vs+PaJ9Zh6TKfYsM2l1fCQOL9ZJazNma4nNazMeeeQg3aZNrCVhy7btAJx4wvEcPHgA2M7JJ5/M\ncbuOY62bcXj9ERaLw2zZuslyysChwwfZu3cvD+/fjyocPtxz6JFDrK0FMom9+x4CYH25YPuuHXRb\nt7L/wEOEGCyvW8OwUah9oevmuIaESflhuWO0iYzI8CCDBgpGYsLz1il1o1i+jzGkMd9/FDc5mZzm\nZF+dvec972Hfvn285jWvGX73yle+kte85jVs2rSJzZs38+u//utf9hoDScMkcwaiiwQoQU0yToux\nXbVCjXTJ9FbDCiwKXoS/0sV+JBV5xCWV1HUesdRBPFxrobpgOLR1W11gvQVsweryagbSsMAu3ckJ\nDI6jMXuHCLiLxCqo92F0tolpgWqGOkY9YJBpDMGFDhKq0SPkVpva4LpmdYA5q6ozTscFb7VWdYgg\nGZ1zN/P5SbBcOpzqcHJ1cYFB0LxF2K3YvxZiEKOqaEVqcCfXngG+9rZNRjXyiv89yOoWxaTsUnCi\nlCpl2aM+9kGvPUaSmBJQX2w+QojWoq3qAKVKjEN0KmLjWi7zOK6B9GSQYniU4zcFI+tHuVjpKxmi\ndfHopTDvZkiBXJfE2A1kpZIzHYW1pKxtWuNpTzmJLkZ27tjBlk2bmM3s/TnphBP44l13cvDAAUru\nWd/7RU5+xtN46qnfwCc+cSunPGUH247ZDMDdd/d86zefw759D/Hgg/s46aSTufvue1g/3LO+3MRs\nkykcfeK2T/OZL3weLcrc+9XNuo55mo9kt0VFOpjN7PugfU9PJvjG0mpph4nCgHAnm+Vsc9UQCpTQ\n6nud4OUvyVFrk9Oc7KuySy+9lEsvvfQxv7/kkkue9DUay7JgC1IDyqIaA7MPQr8CJwKoC6avBl2h\nsVMZCH+As0EbUuhi682BiAtsV3fK7Twrhq8WIVIRIqkLiOoYvWxgFYrlX9ufxDpgtKiwrx6vpWQC\n3VIpJRg0LSbo0NR4Rsct3si3uKBCGPpzjmCijuUMqkObMfHGzy0qXC57VAspdUOkOZt1LBZL6324\n9Nxnl5jPZ6wfPoTOOxAZRAy62RytsKwbhQNa66qq5vmLWAeYMefLhsXXIp6e1q8rrCy8xfOEXYom\nBJE9Go92pYaQSivZ2BDFtmHpoMkbVhx1CKbK1KQMWx9OsKhTxPuPljJ2eEEHDfbUtIHFNmwiwiwk\nNBdynwlVEC1DXnHL2laOf+pO1o4JnHH6GZx80lP4xw99iAfu/hzbv+GZ3Pmp2wE4eM8OPnPbp5l1\nkS2bN3HMtq2s7y187sEvcMenPsHywRNY22zO8IQTT2AL21mvBzluE6T1B9EDX2Jrt8bxO5/CI+vr\nALz4eedy9jedzsc++Snu27ePQ4ue5aF1WIusdXatTWkOiEWKaj1YI9Hymk2AQmRsFl5MVlGqfZ+K\nQkvMhijDu76BO3/0VpxMTnOyI2fRHWHyfoOxfeuCICESvKSgCXNHbBecyygD58ASUKgSkcJABEKG\n1J7XtRkUOuYbrdegiZm3qFcGXdug0ZoBY/BdK8loFHvF6f8NWfQIJsTA0heV5WIdBKsZldjOohJM\neF4iTe7GItsA1XOIfUE6dy7F48lxTR9MvQzDfu333WDHeTdAjq0sQ9GhKfRyaU2aRQKz2QwlkGJn\nkR4KFZIqNT82dJDoAvApeBRbvAym3Y+OeUvG1l8WncswZhNNL6xJQFJndZc6KvDEFak2UYdYS6Fk\npenx1JJNTcmfzbwzwXVE6Dp3eslqWWNMG9qX1TqWw7SJbaWySACv5hB/S5b9kqgQCSb8bkk/tm05\nBoBvOu10Ztvgzi9+hhs+9A/knNm5Yyv0mdtvu5WZa+4++1lncPz2rWxa63j605/OU044jrzYz3xt\nzknHbmZtU8fnP/85+/D1h5mziy/d+Wl27DiWk596HNvmp/Cxj/4rjzyUSDNrgfaZuz7H1mOP4/nn\nfAt7Hz7Ivfft5fYvfJEDBw8P3y9RJapyWC2OTzEwj6Zh3LYxInEg25Gt/2YMxTr4+N7T9kNxZaO6\nmtk+ekPN8JUPmWyyySabbLLJYIo0JzuCNkCYeWF9Af3nLiakFNLCtV2rQihUMYJH1UJ0iC2GSIoz\nY4+WzCyCqlibJWVQYwkhkfue2SwwS4n1wweZxUSM0LMc84oqiMxArWtIDAIlUSRb/oc6bMCjdMSQ\nXHDcCuFjitSypLb8WYXUrdHFTeS+EoISO8/7qVLzWKAvYuo4taipCM06g4AXPRKEeZectAF9vyB2\niRgMNg3Bo4aUkE4oTrKJSxMLX+aMiiDzGb22ht6BGixCOdQX1vsFQeakArmvzKsp6NCrPY8hV+nd\nPsRYnzX3SBcppVIopDAuKyVYojdrpacSg3WqQWE+M13cUCLIkkpk2VeoQjdbQ3NBe6UE6Bwy0KJG\ntEodcy/HKLkipKG8BCClOSKF5XJJr8Wi6BDINbPoF01DgRSFUnpmybqWlAFkzPTLdR7u1gieL0wK\nkpdE6akVFutLdm3fwVo3Y7GeWdtq9/P5++7i4U/v59lnn8GD+77Awwfv5eDhQ5xy8gk879z/m3vu\n3g/AgTrjuNO+iWOO20TaFrg/P0R5+GFOPvZknvGs0xAtLIvBrifs2kkthzjtmSdx7M5jOP7ExHG7\n5hy365v410/39MVg9kN5P6Uc4t6772bT1hM47RtOZuvWrXz29jt4cL/VTWrYR46FZXwKpQRKFHot\nlOU6a12CAkky86abK5lZWkJWyjzSB0ErBO1AOzT7F6JYwwNCIdf1L/PN/49tk9Oc7IjZAN0prEI7\ntSiCWq/AIEiMxkB1Sv/a2trACO2XPSUVZskW/77J0DmMN3ZqsGxg7jO9/9ryhhXmBk3ahwu9N56e\nzTr6ZU/OmRDrUM7RnH1IaYBuuy6xLJYnRJW5kz22bttCUaEW7784YKwCavJlLY+WgvWVNNjRoFat\nGaLYRmJVtkzVHHUQui4RJHrTMYVaBudaSiZoeJTyD+Te8let7hNAs0GoVuLZno16XWscYN5SN+Zg\nQ7K2UVHEOmn4R/Ule4lPRCTSJSPtRG0bmdZpxRpu+w/2mboi5B+EUcSoQAjDpskaa8vYi9XNWMOm\nuNN1yVSOcrE63cLYxDzEYREUiQPsH1MihsRcElRvN/bIAbbMOzbPN5PXD7F91w5O3LWLvfffz45t\nm9m1y0o6Ss6cePzTOHzoYXbt2I6W/Zx//nO4+677WDzyCFvn5lylFE77hlPZdExk38P3oszZvutp\nrG3ewe2fv5fbP/tZZk5sOuPsZ3Ln5z/Lqd/0HGapUnTBfEtH1shTn9Zxy0duAmD79m3IfM7d9+3j\njts/TejuZ+dxT+XYY3fSl8P2nqVgz+zAA8zSnM1pjapW9iW91QLXWljv2wZCgDlEHRoKoJEkwfps\ntnxzMiUqk+87ehWBJqc52RGz0GoJOyvAbl3h+5wJCF2IVBnbVokIuRaWfR7IHN2sM0eFOcHOSwVa\nwWWT24vRXUrT5kyRWYyUfsn6ol/pfBJ90Y9W3xbF5EeDIGEGVEJ0IpBAv8yIKDEJJS8Js/mYD8OG\nERW0VlIMZCkeBVr9qUqA6PddC/3CyTYaBwaw5QMzkVGCjSAkb21GZSgH0FLRsNFJmo2kIa3GTrVe\nxJ7vUxOKEAUddF1NN7aUTEzjPMujLi0iVtfoo82uPZv73ljRwdiYVRXxkgUYSVsSIgM3Z3DIBYkR\nURnJP9h8BUx71lixRuJq9afz+Wy4dpP1q1VZ9L21BFNrPdby04h9flG8EXX7oBmIRdvlsOewl5V5\nEg4feIhtmzpOOf5Y9j1wD5tnyubZki/d+1kAduzYxua1E4gSWesKO7bMmYc53/bC87njc/fyLWed\n7cedwD//yz/z/v95HTiu9/UAACAASURBVPsO7GU2Sxy79QS++eyz2LLtGB5ebuK+u+4D4I697ycv\nD/GZu+/n284/h53bt7P+yEN8ad8+CDs49RtPsTnXzMOPHOb4445h6zHH8vnPP8jDD+3l6U97Oi98\n4fMA+M6LX86/fPxmvuUbd/LAA/u464v3cWjRs5YixI5+UQixI65tBSxluyiFFOcIPbFft5efaHnv\nlV6eSk+hrhDWjj6bnOZkR8z6ZavTMwJMDCME1yIOzdbcWKIxaBNpg9altYpKI9P9Uc6iOUMNK9QE\nv14XzREUjYPIuFAIoQO14vX5bEZwoeyUGnnFnWYw0lHOS2OGaiVFgcBQ3rBcPIKERExzW8h7ZVmV\nFGzRD1EIQw0oaGklEo2SAdFJNErdwFAs1VinKs4+1kroOoOY/b5bqzTNQsbYrqoG/xrU7Q2WK15W\n0EQD/Flka49G7h+FDNiGodRsLdJW6vpaYXtoOrdarRekiDktZ7i2Eg2RaKzNoUREoFqdbnCR8DpE\n2AWw9lRQB7ZsjHHDszehdhOUsOtV0tqM6sLsA+NTlSZKm1bqcRd9tbnqM2ttg0ZiS0ycfMJJxNiz\nb++9PO3k40F6lnlBC8xKOUCXdpJC4o47Psvp3/gMnvPs/4sdx+wg1C0cf+zxAPzPD13Pu/76Wu66\n7wG2bTOW6h39Q9z6qbvZun0HvcCuE060z+52cN/ez/G5uz/Blh3HsH2LctYZT2fL9m2EuEaYW2lK\nSIFwv6Eh+nDlmGP+f/beLMay7azz/K1h733GmCMjI2/mHfNOnikjWxRNte1qQHZ1N4hHdzVSNzwg\ntSWkbgTiDZ5R88ATTyBVPZRAtKqE1F0C2g0FLsBVAoNtru/1nXOO+Zw4cc7Zwxr64Vt7n0hDQ7kF\nulWpWFLem8OJM0bsb63v+/9//4IH94/Y293HJ3LPztYW//jT/5hPPXuTzFpmi5IHB8d86533+fZ7\n9ziaXnA0WzKdtvFyA5zN8S7QiwrjM1KYHEoFLvNxvUe+/55gucxV0bxaH9hqge3Ry0CzPYEoo0BF\ngnPdD19rTzDaYLOsQ7U1dUPQgaKXy4XTObnAKlFxxpT2EZs2LDjh92pHk2u0VhR5D58Sen3yqvkY\n5fqMhFlrFXBOo3Xo2pRBabLCimrUObJejtbQBIdKu29tIhGXsG8WZWIy7ptV/Y2tEjigMo1SWlI3\nvCdGDcpgrREweFgpbWNwxKDQme2KIT4Q0V1h80Fwcs7XUnCDo4mkuWPskmaUUphL4IY2aFtrOZ2F\nEDsLQvc5aZDmpkMpKzmgPqJt+5kliEIDVmpcwvMZArLZgJRdmWU0PqKMtHnl83VobUXB3BZYonS2\nEwShJf5chtJ/55IWbZbawVY+m0vhACGK9QiVYVurSpBHG+QZqm2fK8A5br/wImvDnGV9QfAVPjaU\n05KPfExOkGsb67z79j1OJqc88/xtrl3fI8SMb795h9mk5K23/hiA3/zN/4vJ+Tlra2sEXxMjWGWw\nqsd05plVDbWW2WCtSl549R/RzyrOF1OKTPHa699iZ33A9t6Y80cCN5icn/Hi7Zc4OPwWi4uKrY0d\n3n/nERfTU+6lOfebr7/OdHFOcXCX3e0ttnb3eOX5p/noxz5KGQ13Hp3w1a//FV977Q0AHp2e46qK\nvCgwzsrniCPogDGgOvW3bEAUZgXAeALXVdG8Wh/YKpJvDEVqA8ofNXTCIG11VzCdF1+cSsG6IBfb\nzNqULCJzOiv9VBq/4gIpBZm1GB0xKlCFIGi1zFCXvsOvWaU7elAx6IH3qwQOIATdnYhqXzHsZWhl\naaKjyCw+OhpXkiWRS7+fUzUJUaccyhgyZSGFPvsQ8VEuZjLLVagsI6jkkrHig2tcky5WrSUitZ8R\nYRNa0x7AY2rByu3kVkoZsd9Yi/KR2jcoZbsioUnn5xBAha7dqbXB2pymqVgFf7ekAY0yqQBrS2gi\njau602rQEF1IrVSVwBHSugved/SeDnLQzoo1hHZOhkbpVURWO181Kutea1s45XNW6T6EVdy+jnY2\n292m+4OWjU7pZQyQnrtVckI1WaSci3Dn9nPP4Zolb779bba31tnd3cJFg8179EeWh0dzAE5ngUcn\nU3pFj+HmDvlwk9e+fY9vf+vbFNmQb3792wDMlhWD0Qa1N0wXNQXQo8LpnGAsG2vb7O3eAKA3zHjh\n+ZfZv9ZjnF3g5g8ZZhWzyTGn5xMuSnnsqlryR//+K+zu3MCeVkxPj4nBs1jMqBMC6PTkhMPjQ77+\n8B6vvPgSLloeHU9QxYB8NGZzd4//7oc/x2c/+08A+No3/orf/YM/5OHBQ4psi2wwpHJzgesSupm8\nsVp4yUFh1ZNbWp7cV3a1/rNfK1EL6RTSws41mTJou8pKtJklz5SY1CPdhdkaLXOrKMYxrRRNaHMB\nFSt2jnBevfeE6MizDB3a2VfKxkz3Z7TM0QiexiW2p8m6+9Hp9/1eTvLL0+/1USbia4GMt0rgumkI\nIdIr8gQuj/gI3jcS/5XajQBZbgWlRxCwe2bk1CghoCLaSS3ssqzwMTLoDfDe4aoIWmEyUf62uwXf\nNJg8Ez5smoP64IW/q1azT+c9BhEGyXssXj05rYfOG5nu9dKHKGrfxpWAwuQWn1rTwUWsFvFP09QE\nHynyDKM0PjbYtFHJi1xes1aoKK3VzFo0mrJckOUWm9rFwXu8dzQpO7M79badiEuc2Cyz3dxTKWlZ\nW6VxMXRF2NN0733wsTuAtjGaNneMe7IBKuOc3b0thv3rzC8umNeO05MJ82VJUIazybl8rc3Je4Hc\nNRQnZ9w/PGN6OkM5IEw4PpcCR56x8DBfNuBH9NYG2MWBwNCLDFcuUclHu//MdYZZhmocjw4fsLeh\nmU9nWGOY1p4ieUSrpmF3b4irAhsbmywWU26/8AwPD6ccvXcHgMPDA/rDHo8Op2xOlxSbjrywZFmk\nns24WMzpD0cUI2n5/lefeIlPffg5/uDf/T5/8IffZHZRk2ci9IpmFb8XU16aR8ElVOGTtp7cxvPV\n+s9+dYDsS7t+lO6Yn945og8478TMnvBeRq9aaz54GldTN2IJUYBrkzWMtGOV0jTOUTep4Goj6DTT\nqlE11mbyS4tS16Wvt9ZgjUERiJ0iV0MUhqr3wjwNMeKdtAxjmzMJK7xf4nVmCcOW2YxMG5n7xSi/\ngExrbOLDKiMzT2UE8CC5jIFIwBiFNZK32dQNMXgRtwRRCLuywpWVtHlTEWxPoJ2Qp90xpLleCNJ6\nbpMq6qahqqqOmtOmo7QFjBjSJsRjlElF+PHP2AVPjMLSzTOZPbvg8G6lRnZBPltpMbsEQAAfG0KU\n02JqttOGZVsrOEOtdXc/l9uzUlBbji5iOfEenJfA8Pa1aPl8tZbs1KYWhWluFLgK50p297fY3d8i\n6ykuynMGawNuPfs0F4slr73xNkV/TO0g643IeiM+/NHvZevaHq9+7FVMXnA+L9m+to/OChofWNvc\nZG1zE0ekbhyajLw34vu/7wcYb4wJrsGqAPUCypn8Ws6YHt5nOT1jrT/k0YMj8mJMVcF796dM55Hp\nPLK29RTjtV18sFS1ZzYTRu3BowNe/ZDE8JWlY75omJTwaFoyrSLe5tItCAEdPH0TMdUcU805eucN\nmtOH/Pef+TQ/+T/8GNe3RvSso2c91A25yclNTlMHjLIdHORJXVcnzav1ga3WcqAk6gOd5mhKa3QA\nFfWKoxpilwqi9Yor2l5g2yUukzTf8rGzIoSYQN3pBKHQohQloHS2OqEoiUqK0RPJyQrbsXGDF7RY\ny72tQ03wCVQdgJaJayDLRMWZFxm+qoSfq00SN7mEZBMJUCucidqnbWwkJKFL+6qUSYkdtDYPK8+/\na0Ea8TD6JqlJ5Ss9YsEJXgqOqEcFuq7QXWoK2qKTOqZuJB7MGt29143zK1VV8mEKPS8m+JLCR5nt\ntnNRo2RT473DGovpNiROxFjtq0tKWJA2rrSKBUtnrEnounTjVt18qYg3CahuL+HxhBWcUjvSibRv\nMgIi/HRp5yBwvQA4mqpie01g6r6+4Ma16/R2M26//BwAi4s5k9NTptNTHl4smEzO+PjHX+X6/k3G\naxusb24DMF7bRvdeIet7FjPHzvp1Th6d8Zd/9hdkxvDt118DoDCe9c11Tk5LyuWMP/zTrxCmZ+S9\nnLKc89KrL+NDit1aTlnv7TMqco6OHrG1scvdh4c0zjOZKZqTCwDKbc0gsxTFOudnU7SyLErHc8++\n0LGet3d3KfoFz3zsacbDMaNhH1sUDMcDisxgVITYdDSt4dqQ4BtO79/jlWef43/7X77Iv/iX/4pv\nvf0uNrdUC5m7jofrVE2TRGxX6tmrdbX+3tcKqp7+3NoflGDtFFFEQQFpvwa5eLa4tnYZLbM30Wk4\nssyCUTSubgl15FkuJ6wopxoVItYorMnQqrgUC+WwOrX1vEfocRG84NcUqlP5EnO0DUnYI0VJwsnM\nCsWnDSsjm8aIPFYUtUZSV3yiBgQ8tSMVDilnSe9C1JHG+W5jkVkpBJFVZqb3jhhSkklSlQbvAWkR\nawxBOxygg8dHhbrkb7QYcA1Nar+2rW+tDUZH6qR2vjTilU2MMvgoqLUQBRjQ/qOJoviVOXH6osBj\n2ZcxOFBBQBERlGpFPzKHFkRf28oPNE1EG4tKs9fWWtKKlgCqlCea5zlaa5qmQXkrArMYCMk2FJUn\nqIjWkUEvp6qk+FzbGbO73ef+6SHf+Jq0U7fWx4yHfd57+z12tkY8d2uXT37ykwyGI/b2rrO9I6rY\nsm4o1uBocgA7PYbZFrf3n+K5/WucHD0kR9q4/8+D+xAsPeNECDU/J1jF9s4G5bLk6PiID738rHyP\nR4dqapZzhdZ9mjjk3nEDxnB44imX8nofPriDCRUbozGnBxNiyDG24PnbL5KcwvzQD/0g480xtlEU\nWUaWZeSZlqzMuiY3GoJDtRuq6KmrEjuwVBcnrA2H/E///Ef5l//q3/D1N95llDYa08kcmzyoT24w\n2FV79mpdrat1ta7W1fpPXlcnzav1ga32dCdzwrA6wZg0pyKB2aPEWCmEGuAvwQN0OgnJPCuIPcBY\naT36lRhBJ28mIRns29OpFqP7JX63ZClaneajlcxBlQZvQEVc2kcbpWXuqCFGR4xiYQnRdQb/pgmA\nJstkxpYkqkmlquHyc9QaSeFS6NQ2DK3KNopPtAsaUaJadQSiT2b9KK1lje5STogR58S354PH1xCN\nInZe0JWARiPqx0wLWamuGpraYTMrcIe0x3bpOYfo0coQoqepXdtB70Q2bYuu9VK2FiNtFJfSy5JP\nN0m3lLTUfYgYYvKLrnIzVRSaj9KPt2WV4pK6N91WqVWMW12jnbTOo4as9aNqBRaCr2nKOc88JWrV\nwkYe3HsXZ3tc29oC4PD+Pe7NLxiNNrj9zA2ef+EWT93YYDTqMz2/z9GD+wCsjcdU54r1XoFycPfd\nN3HLSK41BQv+2x+UsPaBcXzlK6/RG1rKueOicWw88wznsylP3djnxedvghMh0KifU5Ulx5Mzxlub\n/N4f/UfWt3doAiyrHlUlt3PVkp7J0GbEKx96lkGxxub2dXqDNa4/La/thZdfJOAYOi9Qi9RC900A\n7ygb0Q60s2ttMrCaqq7JwpRqds6tmy/xw//0Bzg8mXEwkccush7eWaF5qIYndV0Vzav1ga1Wqh69\nzNm6C6MPaEAbK2pP7QhIgVKKx7yAIvbwuEZEQP1cZnDKKFGjpq5rSEZ1o1Zt4bqu5Sqc2a6dqYi4\n2KBcoNfLiNFCVEnoYolBrXIJrUZrmy70Ae8bwdkZ2yVXiTpWXljjPIUSPJ/z0sp8HP8m+L7IZQGs\nSHyNFfxcnewpSquUt+mpmwatrLR6CTgfSCmXGJWegzLJzyhBbDE2kiSS2shG3kyiCzRG5pfaKFCa\npm6oXdMFIl/O5FQq0FQNPgoPVhvdpbY0Tni8VovlpbXqyH34FTUpfT5aKWLw+OAIzqMyQ6YzlBKk\nHsj/vQ9EeoSwJISANZZIlMKYWufiy1y1//MsJyMDPFprWn6RAoITStPutW2efvop+d4olzhXUpZw\n//0HAAx6lh/6whfYXu8Rw4L1vuHi7AGLc0+IdcetPXww490H92lUwfH9klG+zUdf+TBV4yAumStp\n937m+z/Gh154jj/9kzep5paTylNurTPKn+XlZ2/Rt5G1XrpEB8eDh/fxxvDGnQdMl4E6q1nWgfms\nxjXyer73E9/Lpz7xCtXFBYO8z8Z4i/F4G9sbcHJ+CsByWRK1pzk7pl4sqJpGcJQ+YrKMclljsgyb\n5vLaWPK8wLlIPb3D1rrlzW83PHfrRT758Y/z27/zpwCMt8ZcVDVaRQJPrnr2qmherQ9s9dK3X6Y1\nWmUrUUqMchBTUHuHj7FTObrG4bxDabF9WBXAR6zSKA2N+PsJjYgTbJsqj/wgey+kmQyNNaLA9Mrh\noty+yCwDr2U+t2gY2IyolZygNDjlunmYw+E8KR4LIFLFEh0MOvkIg8pSMLIhKlG+aqSoqxgxOuvm\nsx4pvq71sWiNB1QIDIIoUVuRjQqRpizxPp32guRRCo2ooWlzJXUCPGjJ7gxEqsYLKzc4miSIqXH4\nWGGLnL7TaBSNF2VyEI8PTTJPJl4EZbRooMl6FHiy6AQ2kYqqAoipfAcH1mCNFfB+8F3BbmPKfASl\nLUpZtPYYLergEFZxbHXjRYGrLvDKoTNLhRRZokYnf2CWZQTfUJYlxoqA69RWDAY9mrIkS/AJX1X0\nC4vRBWPV5+B9gZqfTjzGjGiqJbmVInf7hRe5/dIepycPeXj/PncfBPr9Dao6EFCsbW4CYOyIYHu8\n997bvP/WfXJOmJw3bI422Fhf58//6k0A1jfXuP3SbT76mQHrW5u8eecOlc7Zu7bL9PwcmxsOJlLo\ndne2mR4vKS9KchNh+pD1AjaxlONrxCBzxXHcIC77nB5OqAc1dXXBbBEZrq0zuRBlMGEk2Zo3drEx\nMsCjoiOGWjJfXUOmNf1ktTFoXO0IITJq4OL4Du/df0SzMNzY3qHfBhj4QOYBExIH+clcV0Xzan1g\nqz15iMbn8R+yGAMrR8rjtKBMZ93JQwWhXGoNKEVQQu2JWAjh0mkjJTimEGGFSsHUiazTekS9RhmD\nDZK96H0E7+QSYMArTcuoMyZLqDctSk+jiCm5uCMZabGmxCgtr0hMilZ5VlpJOza9aGnKiphYcj41\nKKfwyefYLinUUvSrSiwhaDk4J3kwIMXGNWJUUSpHZRarjQiEfEjPV7rEclKqaWrBiQYlrXN5r0wn\n7rjcyg5otAqP8WhbXawcVAXCEJST+0NsJT4EyWYkPWelL0F6gliFEIvPZb1YGyyuTewIOiAh3Urp\nDoeYtZ0IIwXTaI2xmkW5RCvI0p0WhWU4GrI9GnNyfIxJyuBXX/0wxlgODx/wkQ/fBqDX8/zJH/8x\n8/kZT9+8xWg0pjfYIqqC+w8OeP3b4oOs6pJGOWazCmWGBJ/x3p0j/mr2Pk3j2d3dAeCWVzw6+Sqe\nisG4x9bOFnXjmcQF5/ML1re2ubgQ0dBkesZzt1/kT//4PzA/PcfoHsenc5qlY/36OjvbGwCcnR7z\n5392xjNPP8XHPv4xQgw0Tr5/b67vA/DU/jXqxlGrBq0UxoIxER29wP6birosUXFFhSJ66rLm0ekp\nzbxiVjv+9f/xb2jMmLwvG8RlMweby6ZKP7m2k6uiebU+sNWOoAKxszu0SymJtFJKYqpijHLKDOIj\nbJoWbO7BAUZsFF6FDtIOCtcVGoeO4nm0xqaSpvAhphDqVhOncV7maSGQAow1QYu1whjTFeIqhQ+H\nKEVDRTkNB1jBTVNAdAjtI4RUjKLYJqJ6bD5LAJNYqO1rUCpitEk2mFVbOqbnaIzB+0j0MbFdL4F2\no8wefYho7dFBVKdN0wjXtlUsa+S05wN1HcU6Yy/pBGO8dJ+x/eBAi7JVbC4yl7wsL2xfW4iA90QT\nQEfxorZ356XFKlnbId19AswTO5qQ3LXMJYNy3Xskfkspsl09TzNTITJ6gnfEaMiMYdjLWcwEOzca\nDdnd2qBeLLi2u4NLANnTs2NGwzGf+8xnODsVaPrZ6RkbG0MmkxNs3me8vsXbbz/k0dGEyfSC88UM\ngNo1TM4n5FnO+nibuvHMzksIGVUFy/snAByeHDMaZ6ytKexp5PatPXrjgmv71zg4NkzmMzYH6bRX\nDHn33btMzmuGa/vce/+Q+WLKqDfk8N1vobOXAHj9G18ny+H2C/8jdbOk18sYjPr4EMl6QuAaDjRD\n1WNZOrxraJqa+qLEuxrnakJTc3F+TrlYpo9bUZcNVemoFg/pF5o37p7yYFpSG8fSSxkphhvUVZ02\nMFeWk6t1tf7eV3vS0LRUl+5fgNasnk5CCnRrxO9uI1+NhTzFU1V1g9UdFK4rzI5ArjQK09kk5N/F\nj9h5BmOUC7wiCZDauSsoG9EqdLtoeSpK0keSAV9nGSFIMojcJsHArQiBxH/qExN3hflrX5PWBqKS\nLNAQcAGU95jk82zbsyDJIt4HsqwApTqqkVaqs9pEnTydEuNBdE7uM4oYRq+ASaiItKWRU5+KMVlW\ntLBn02ahg+BHhwoWfCvU+Y5jbjJUikjKif82uTCNUR1YyF86TV4W88Q04I0xdukjUUVUUJjM4lXy\ndWoRNLVEoe67Q0URayFz0iyzGBNYLM5xtbTjbz51m6dvXGd6esr9+3dRqa1+/foux8fHvPbaa+RZ\net3K8ejgnMWi4cHDY77xzfd4+51HYHpgLFXC1KEVRT7G2B7TmcN5helt453HUKJ1yjrtRW4+tctT\n+yOevrnD93zkJaxbYns9nruxw8HpOV9/4x0ALuYzlDIcTy84nsLZIoIaM583DJjQNCLG+dT3f5rT\no0fcvfceu9c22NgYM4xDtNFUswUAs+kB2uQszic431CWC6pqKfN876jLkqqqqZZyn5Ozc+7de8jJ\n8TFeeQ5Pz2V23rf4aKCQMnLhLwhWgB3f4SZ7otZV0bxa3/X66le/yk//9E/z4osvAvDSSy/xkz/5\nk/zsz/4s3nt2d3f5pV/6pVVG5f/HMkr/jX+vjca7QO2ENBOihBBrY6F2uMZ1bTSFTh5FLUkolz2K\nynWHnrbYdACctqhGEc7Y9mtiRKOwNkfjOxWsUkBMxcO1kFchCxkNIbpOvKPpUs6Q8aQIZrRO0VPe\nSORnksJ2PFnAai0zwCgPasKqcERWmLe2WIRgHuO6SjtT2mnd+6wNyihitBLh5R1GGzJ1STXcIuRC\nxGs5HceQ/HYxiYfa+LTHTpounWZBArxT9aXddwgm0BrxSEpxDlKM2wKnVtmY7d8ZbVLbVqXXTvd5\nkWZsTeOJOmLlhuiw6kAoZVExoA3CFXYCfmhSfNz+zesA5Bm8/dYbzGfneOe5mMsJ9PDoEScnp6io\nGI+GAPT7UPQGXNu7Rlk6prNjIpay8gzXx6yNpUW6dEvmkzmhiihTELQGW2AyjbeG0Jynt6+m6Bn+\nm89+mu/56Assp0eM8jVqD2ezObtbBfvXxgD86//zj3j7XgW54fjkCNSY2tX4xtPL4M7de/K+GYUx\nGSgB3c/O5xweHZHnGfPFBf/kn8HdO3coqwodPXmeUZZLqmpBjFCWS6bnMybTGacnwtw9Pjrl9GyC\nd5EKhcoL6iB+X7Jsxf3VLUTPdrmkT+K6KppX6//X+tSnPsWv/MqvdH/++Z//eb74xS/y+c9/nl/+\n5V/mt37rt/jiF7/4t95HWwB866NoSTJRTqGFFk5qqCINDuMjPopApGvBClVN4N+xnc+1p7xVYLTE\neol9wXuh7SiVftCV7U6ePjQJV5fR+ARNR1rFRtwv3enThyiHzjbGKwgD1mRtjJjMLEMMECRrEK0k\nBit6IjIz7UANSqGNwniZZaIN2oAyhgLhiq4gDKK0NUanmZMiRonvUpdUoy7K7VRUGGT+1xYkFXks\nv9IYmSHqdMHzUUDpSlsJF+6Or0noE0F7BO0XNaGbzbK6Xasejg5jNdYqYtApyDrdUK8ezyV6kE6x\naW0ySvc9Q2rda411whgWMpBJm532fRfQvVakUG6HzURRvTVe4/qezBXPJ6f4puLGjT3m8wUhiBBo\nubjg1q2nGA02ujSW/qBgc2sk7z2R4WANtzXk6PSC5aKhaqHyuSIvLLGO6FxTTkvqsiT6iNKejYHc\nbr6YsFzkFHbOfPo+mfK8/e4B9w8O2Ltxk7fu3Ofde48A2NpULCs4OJsz6ltQjmXtqYmM17bY278p\nz3G4wWxyxvt3HvHg/iHLxTlluWBje4P79w/5n//X/51/+2+/zHh9iNFij/HBU5ZLyrri9PSMo9NT\nLmalqH0BpXKiz+XTsn2aAM416EJRupquXSF7otRr+Ns3zP8lr6uiebX+XtZXv/pVfvEXfxGAz372\ns/zar/3a31k0W7+f0nLBW7XoBNIu6Dnx2vno5SIeofGNBBxzOSlFYY2hSgHWWimsNSsriZJYrRg0\nKE/URgQ8ScTT9v9M1JKgYYwwV5E0erlYG4yBspSLKFpsKKIS9SkKK6Ci6epGcB6d5dhEtolRCr8P\nErJsVBTlJzLPw0ursd2n+yBFLEafosLkno0toPOXymmsS/bwvhNOxahwzgmMPZeiUjqPUUo2Gpfa\nsz6ksOjgV+kwWp6Lc+6vnx2iAyUMpKgN2lhicNSpVag1ZLYghkYiyqJwcds5ZdfGVbKRMDHigkNl\nYPNMKDRpI9GKoFyKfsuzjNwWSS3b+nNiB4GPwWE1NE2VQsE9mSkY9fsMegXLCyH/nJ1M2BiNsFrR\nL7LO27u+PmJtfcCDuw87BXbdWI5PD9jc3hRxVVDsXLvGcG2HRyfHkNq4i2qGyRTL5QXLsylBWazO\nsLmm11fs7/QB2B1d54c/83HyfElwDaY/wK4VmAvLncM7qBx2d+WUu761ifNvcTEruba/RxNyzs8r\n8nzM1to+06kolh1u9QAAIABJREFUfKeTOZPjY4rMUi4uKMsl4/Uh82XgL775LgBf+8vXcB7ynmUw\n7gGRsiwpmwZQuBiBjIj8bAU0ed4DZVDB0lQVJutBcGRRd9YU75yI2TzgrnyaV+tqPbbeeustfuqn\nforpdMqXvvQllstl147d3t7m6Ojo77yP3//yVwF4cHfyD/pcP8j1R3/y4IN+Cv9g6+5bf/dn/F/q\n+u0/evcDedxbwKf+gR/jzYfLf+BHgJu3tv7BH+ODWldF82p91+vZZ5/lS1/6Ep///Oe5e/cuP/7j\nP36pbfh4O+1vW5/9p5/m4f0Z+zfXMUoTujmjqEB9iEJ7SScvpUQ0FGIU+DoJ0p0eL8tWGYtdhuIl\nf0TWpZ5Iq7VTwsbYtXtjFGWntoa6LiFCbiTqKy9yCpt1Ip+6AdsrROEbSrQKRCUxU6jI7/3+e3zu\nv76F1hatDc4HQvS4phbvqdU4F2naE7cREUUaY3ZONwUY56ga17Ves6wABIAegrR5vZe5pwuh+9pM\ne5oqnU51jveBpnFkNucyNF0eUaASzoja1ujkq4xyYr78sb7/5hHPvbgnz09pah8IWhq7Pp0yTAKt\nWyLWigo4Rk/0MmtsXCIM1VAUPZSCsi4xqUsQvJdZtlWoVmsbJaoMSMGbqvP1piav/Ldx9AoLxmOt\nwfuKqqx59eWXubazzcEDmQGq4Njc3GDY7zGZTHj48BH/99fO+MwnNrl56xnmF46qlJPzxcUxdbNk\n99oWg96Y+cxz/caz3H94yHS5YLQhUVpvvf8ma4OC5XxOnvVY39pgUS2xOvDc09d45bZYP7bGkU9+\n9Gm2x7C31eNstuDuNFIul5TlkqZ2fPOvviWvxylOzpaE2KeXb3JweIFzGdr2OTwZ8K3X5HZroxH9\n3oDRcEBwDRC4f/8um7sbHBwdcjCr2B1nbO1sUEeX+qkKl+xfNsuFt6wyYpT33DlQJiNETc9DoRSO\nOgVnV6gstaVV6sZ7sN+hhn+S1lXRvFrf9drb2+MLX/gCAE8//TQ7Ozt84xvfoCxLer0eBwcHXLt2\n7e+8n7aVZrVOs7Q0G0y+hTa0IhJwQYQ0XFJdAqmFKrM9UYbGTr2njOkQbkq18HKPzSQEWkQrhtBU\nK9WltiRRLEpbwdkZaZN67/F6FYpttGQ0ooMksmgN0RG86/I+RcgUBfkWBSFnc4uOyf+mLpkeM1HO\nRi/tW6L4JrTqdEGdoEkKqyekpBHvZfqqjcagHpvrWqtwLuJcQ8TIhdHLXK7zsSaLRtRtuzx5SVWU\nGafRXRv5cqlVCXMYSPB0RIwCkmcZnSNETwy2g+8rNMqTMk8lacQHR1EUZDEnuAYfPFYbcbU6UC2S\nDyXoQiUbhRjlPdCx/czSTNNAExp8U1NkhsZV7GzuMO4POT064k7KlvzERz/Mp773kxw8fEhVVrx4\n+3b6bC1nJ2cUg3VMnj7LzLK/e5218QiCZtjvcXT4kNwattd6nM/PALh5bZ219TUmp2fMZhNsuODG\nes6zt27w3LPX2N+R4joaBnS4YD6ruVd6Hh1PiGu32N7d5t233yJ4z1P7AoHf2d2jXMDkrGZt/Qbv\n3znmj//9Nzk4fMTRrM9wTVq+Tz/9NIePjnj46IDr1/eZLy5osNRYtq4LRk/3hyw8mLyXWvQxBYhq\nmqiovEOruEohshkRTe0dWQhEnVTkQMSQWB/44IhNEOTkExwPdlU0r9Z3vX77t3+bo6MjfuInfoKj\noyNOTk74sR/7MX7nd36HH/mRH+F3f/d3+YEf+IH/5PvTxnSmdEjFUyuC6HZkTpfmbDFlP7YreJ8i\ntsSjZ3WW1KjhUkoJQCQTAkKn0owrxkA3RbRauKyNi2Ak1Fmn0GIfoGkabAta0H3xS4aYsH+KGDXO\n1WKPQTySMieMErMVPbV3XeF1yXgOIoAiZV5Cm/conlKvnDB2u9ftkHjImBJVAigrJ1UZwMr9Nw5j\nsySWihJbZg1lUyelb2sSlfdIBUWmIsFDxMmMVhnwdGZ3OvSeQhGJUZEZgzcIhKH9dysq4aZ0NK5B\nB4lj00hxtjqJRQol81yEdxrIhP+rFcF5XAgdCEMBxut0Ak7RX9gEqghE33YglHzP+Ib+Wo+N3pi1\n/iYX5zOODw/Y3pT24fRswu/9zu+igfWN9U4QVhQ95osFnpxbz4jIZjx+BoPj8OARwTlG45zv+9Qr\nLJdL7j+6T38uj934ORtba4wHQx7ebRgX8OHn93jlhZusjSxrMqZk0DeMi4yqqSnrQFb0qZua+fSM\nfmbZe2qf83OZvXqn6Ns+25tr+Djg8Lji3bunFMWA8XpGloufc1HN8DRkPcO8nHM6m9JfH3FRl6gs\nfS6jPqVzrBc9VNPgfJNm+hHna1FDB9chHq0RY5VVGh+XlF5EXWmXgk8/OxIV51DWcmlf9cStq6J5\ntb7r9bnPfY6f+Zmf4ctf/jJN0/ALv/ALvPrqq/zcz/0cv/Ebv8GNGzf40R/90b/zflr2bN00jxVC\nUpixDyoFUgtMXCudKDNZ5/1Pwnd8FJBBblqLiJYy2mlNTBKEJIVtCPJ778WSoFeP7YOndE0Hdfcx\nkqmVetakI3DUhpjaxSS/ZqLkQhtvpUhtTrld7b2wa5UWsHsIXSFUfmVD7VShmg6ArtojJ6R2bEe4\n7wqZdwIjbGHbihQKHD2o2LWWlZVzXksEUkaeQEi5lpiIutQfVgZifFwKZIzYUhSiCm1PpiHxcZ0T\nqDzaoEKQDM/kSNGw8ulGcHWgqqUN2gZ3R+HqYXQUpi0JbqCSgjmG9D6lNzquRgNaWbSOmF6Pjc0N\nBoMhYREYDIZsbmzJSRq4mE2lhawNozG88qrYqM4m5/R7A/JexvGpzG4ja+xf2+TlV15EOcXu1h77\nezc5Oj4Cluwj1fD2SzeJZsjZecPB3jbl5BG3tjfY7WtyKoq0k8u8xZeapgkEY+kVfR6+/R7OOZ57\n9jmyACYJy8ejTfLeDvcO5vz6v/hN3nn/nMk88OrTN5jOjukP5P2ZL87pDTXBFxweH4qgTWuwhkbL\nay5xmIElhIboKwjJB6sURkV6RS95gOX2JjbE0IjAzTagGqLKCFGKeavANspCluF1hCv27NW6Wqs1\nGo341V/91b/297/+67/+Xd2PaRWePoEBUmuty9lMEnajBeTtfMBF0MqRXQocFnKQomnk1KYQNJhS\nJnFf5T51bAOHZfnk/5NrSXpsK3B2ayI2t1LYoyczkpMZnUd3PzYmEWxSELMSc722hhjlouGcI7PS\nCnZ1jYtSAKyxRC0trVVL0RCa2BV6mSVGYtr1a7N6zUrJyTZEORVqY3FeUGdBG/Jc5ruuiajUarXG\nQkwAJWtFqNti4VWQVnVblYO8VzEotJbC1sGVWh9mek9DRIpxaj27lLvphc2HUoosL9AIED54j4+g\n02cRjU7tbIEpeBWSLSekxJmVJcjqVnUbuvaugCBcan+n9nWQEOt+PyfPc+p6jo1DZtMLAeqn17Kx\nvsWjBw+I0bO/v8/r33oDEPDDcn4hvsq0eyh6mrLssT4e4L3jwYO7vPn6mzjnGIwMy1p8jfNpzuEE\ntN3k2ZtP06znhPkh5wcLdrcK+j1pz/aMYTqdEYsC2xvTyzJurK/R+ADVkkenp2TFCIDa1MyXc772\ntdd5/c2HTBaWFz/8vXib8+wLPW7efAaA6eScd95+nwf3j4k0KGMgA9PLaNoiOLCUdUXPa4z3EGJK\nrJHph/UVwTVEn+D3RXqPfUNtSpz1okFQVqhNIW2mshytFXWoHpt/P2nrqmherQ9sudAKYJKAoE0G\nIRJcCiVWiuASVk76nFIg2r5rhMaFZFuwKYkjQIrVqpMoRaWIKUXEoBJeLaJQVDFKADOggsxrLAoa\nKXg6AMElNmugalvJRmwjcj2PNM6BiYlws2pRkqV2l/HYBBUPEaJz6EvIsVDX+BDI8gLvAk0jb4rR\nEpbdeElSASEaKWvTaTAJbAgoIwbzVpeltcaFSHTCn9VKkSMRZ4oV3zem990QqEPAao21Oc456qrG\nKo1p51RpUzNvSjKbiTAnKjKVo5TCpyIT0bgYMdbSKEVsPCoGjDUJm5hmw95gMAQcjZJZq/M1IKdp\n4+kCyp0y6BjoBU0HPoiK2jmUMR1mMB9kLMsF+3v75KMBy3LBsKfpFTknh0e4FFL98Y98jBt71/jG\nN7/J2++8yzKddnvjHmePJoyWhq2NcXqeFRfTQ3bGOWujdS5CZFJPOT2Z8M67E/oD2ai88frbhKLP\neHuX6uYu7uKAMD9g/Pw+F02gmgiZZ+iHzJYVKi/YygdMzkvKssdwNGQxr1CqjzZSNI+PGxZuyuHx\njGgsKEvVzNleH/J9n76NtjLTfGAt777zkMmiYrQ2xsVAVA11VdKk16yXJeOsh/GAFjiH0JcEiSiO\nqh4ma+fnkp5jjMboPs452bxqLR2N9P0bfUWIBhsjl6YtT9y6KppX6wNbriOym3Tc62ikANiWFIMY\n9o3SIubRCl9LwdUpKioAhW2hAe158tJ2N3qBvMfWzI/MwKImy7NuBBO8F1SbUpL0UdXkVpGrDGMN\nIc012+dtjLQTI3JyVdJRXPkkgcbVgudTIXkuIXovdNXLtzVBTsPeS6vMSDqKGPwvZY8CaAg+0jQO\nk05lbYSWj3TABGMydGxwhPR3GqMivqkfy6FQaT5llEFpeU8ya1GqRjlRoD5mpAWiikQjM1TtNRaF\n86FrJ3ulsJmhdh6Cw6ISQcnga9dpoKzSNL5Gaci0pUEgDbm1RO9Ql+LTTJTM1BA9deMoih5GWXxd\nM+z3hXQP1FXJtd09nrpxC3DkWYZenOOaBRsb405MdnZ6ynKxpK4lLGxtfbP73G4+8wyxcgy6tA+S\n19cnUZnibHLO8emU49Np8jzCclmxdXODRb3km2+8xo2tIaFyPJzOmFeK63vbcn9OUXtY7404P50y\nv6iJLuPw+JD+cEhWZJxMxY51vhDGa5ZlbIxHrG+McPWMl25/D9aENGOU2fl0tsTYDOeAXIAOo6LA\nJfZsFhTGBZTKu41q23RQMeKSz1ebLH3eAa09PkaMLsAbmSUbTaZNFwPmQ5CCohX4KyLQ1bpaf++r\nBQ+I6OUys1ROFj76DpOngqhFY4zdrAuE/KKs7dSjYrtItgMuzc2CRlmFSIYkVySBesi07dqpPpn4\nTS4JIrpVlUKH4GvvM6r0l5cVsMgpsHsO3uPjSlShdAKrJ7mS9x4V2kQOg9bS0pUTgCh5nfcicLEG\na7Pu/XEu4L0TtFzL0k1zvZA2ByEKo0UpaJ+VDx7nHFHp7gQncHMl7TzvaWrJWNRaJVJQWCEXWvVw\nahcHL8B956OocjslMim8OgUdK4PxcroNUeLcQNTR3juUNuTWYlzEAVGlqC+9+s6IgIuRma7Iehll\ndPQyixrkLHyNSvzdjbUxN/f3WM8zNja2WCzm1PM+F+fnLOdLzo4Fmn4SFUVeYI3F+cgzt6TNORys\ncXh6wu7WNr3RKD16Sek9dw+OmE3eY3K6ZDJZ0DjD5rV9lo34H0PmOD2ds8aYcl5yY3efJlY8Og1M\nTMDRBkaf0biS3WsCa9i9tke19Ay05c69u1hjWd8ScpG1hlCWLGYTPvahF+mNd7G9Mc8//wxro4r5\nQjZyxyenTC/O2VjboAqeqDwhNNRNUhgj3/NNVdHLDSts/srqpVIFDW1XI6nQg3NicVKx298GYreR\nE9UsPNG9Wa6K5tX6AFebiSkV6XI0hhZVpkRjyK4+WTiC90KPSYXLWFFRiu1ELvhEg1dRDrCXLBpN\n7ZCgqkimFUaJMrWl1MgSW0uMaR6ZW4iepgk477FG2pYAPuiOY9u2NxXgGi/K07TaoGrwqGQjAfEX\nSsc5nVxjC5TX0uolyklRGxFtxJX4xyTLjErWC7RDYROnNXSCmJD8M8YYfPTgU6RWlnWtTLmFkj9H\nMds574kxkNkMm2WJZnQpKqpdSc0c0OA8WmnyvCXJQPBBorliKpzOo7Qlz7Jur+Fcg8ktQUUqJ95B\nhaGqarS2WC5fhw1RR8rMEkyOryqJ/1IWX5bcSLFb/+gjH+Li7AQ3n6EKTZidM58vub63z8Xsoptp\n3rxxk7XxmMOjQ+7cuUNVCcj9+WeeZXNjg9IFxhtr6XvNsZxPOF8sKRtH6QPYHt5DozLOLsRykvd6\nLJYL1mKG0iMOjpYsZw2zQcZoYJkuhD0b6wvWRz3OZ/fZ29lmY32PykdmF3PmyxJrDKMkshkOhrz7\n3j16ueblD71CNH2efv5lUU/nNX/59f8IwF/8hVi/AhleBQbDgkVZUjdlx1c22pAXhSAcLwt2opC4\niiInBI937cZL/NJaKxpi2qTR0a0eL5LqiS+aT+4Z+mpdrat1ta7W1fp7Xlcnzav1wa2WOOLFL9gS\nT41O0VRawoh1XGUqBqX/RvpQ5ynToILERF32ismJssGbpI4NgI2gTAcJB7CZTWMxMdw3iyXGKPLM\nYm2GMauNdKs4TM7D7rFCvDwtNJ3ZP0ZN9G07TCdCzmr+qKK0m41WuNjaObTwzLXBhdilrsQISluU\nsnIIV/JYtHFq7dPx7XOKiTMrfjybmL2hO00ksLwPGAxKRxQaY7OuFd7FPXXpNDrNUxU4jw+iZLZJ\n2dw4J/NMwCpFryiwURFdJPrQfY5BQ54X1M7TNBXGZmilCdGQaStAg9ZKAugiwyvP2eKcnfE6MURm\nsxnPXL/GC89Je3XUz6kmgb3NDXIdyUZ9tnZ3KcuS3d0tXn1VIAZP7e8TfODO3SEvvPI8G9vi3/zC\nP/tBauc4mVwwm4sqdjI5wNdjUSY7w6NHE07PSu7eO2S2WLAo5ZRajDbo9focHR2JnUpnVJVmsmzY\nCQU2ne5sNAQVuLG9QZGPefedO4yu7YLJsXmPpmmYnsupdDZbkOeG9c1NNBU7W3uU0xMmswt6W2u8\n9e57AJxOpmxs7VHWovpugiMiwq4sMWKttRhvUeY7g99j+pBj1xmRf9AE77p8UlRbNhKpK7F5ZeQh\nQQQtOP9JXFdF82p94Cu6SDB0KRrRpiDlEIkp5NgY1dUBpbQYsv/aSjMyTcvvTnQhAZ4oQYsLLCAq\naRkSBFCdkhoks1NBAhqI3UEKWOMczl8uHjIj7epUDESvMSZbSZF8oImxQ+kFLwVDa5NmRaD8aq4U\nYqRuHCiLNRk+SFvYJPP5CuCzahJZa2lrYuyKpPxf4tcC0bXtV598mzKLDJf8sellCDRdyeYiRvBN\nIEbfkYDaUbT3Hm3EU2lshmqS2CisrCAtHKEVAEXvcTjsagyLNu1GI6K0SXNYsDYTXGDw+FqUnw6F\nqh29zNMvCqgqlDbsrI/Z3d6ksPLC5xcTtPYcHz+gl4uF6OHDO5yenTIejxk9EtvH177RsFiUaCVt\n1WLQ458D/+HPv8LNmzfY33+WofAFcPUxZ+WC5dyjVY/dnTVu3LjJS7dfpPKOeSnQ9KPjQw4P73N4\neMF4bcTZ+YzecCzF3Vmu74gQiGqGV0uy3ogQDUV/RENOf5Axr+/h6wZjpBDPFwv6wzWMjuAbmvqC\nqgpcTC94ODvnPGVlam1YLkuispRNg0XoUtaojujkaidiHaUfozuhIlYFSTDRmqxIYQgpPk9+HqVy\ntjK3y3HpAQkxV6zm/k/iuiqaV+sDW+2pydoMpaFl4wQPXaRUMrG38xW5vcUY+YH2PuB8I2QewAXx\ndaJEtdMWj1SO5eRmTGswIQSZ77WrahoUiswIks5qKWyCcxNkX4vm01YEMt4HlBZhTDf3SxVBaSOz\nO6nDKN0i7WoUWk5lauXpBFHT+uBx6BSKLMKdwGoOrJQmxHQS14a6bjphkQu+S21RWJyToudT8VZK\nS2qJMt3zDMl+Y8zqhG5Mezn0MhNNJ8Mm2XhC2lgonTIcvceFBp8ipQzg0DJ/VuCqipjSToyx3YW1\n8U2alanOe2SyDKOgaYSu1B5uVfQQPNs6x6Coy4rr17e4dWOfUa9gUKREkmrObHnG+0cP6fcsRZFT\nrI1xasHZxZxzqUVsbK2RrVl8cEyWE6qZiHT+7Jtf4euvZ+xsXKdIJJ0QlpwcPUDFyMbaLvNZg1FD\nRut79AcD1ntykmtGmkytsbs74Gy6YPLuQ6IxNBGquqLI5cWs9RWlj7x37x7vNxc88/xzDPM17tx5\nn8VSis8ofd5VHdCmZmO9YDjoM5+ds762zXi8xtfvn1BX8tn0hiPOLxx5z9IfFKBqlJefJd/uqKKQ\npKxtPcYKazPZ9AVDE4QQ1PqoPfLtpI2mCpEQIjYFfkdWP7cqQtDqkrToyVxXRfNqfXArVTRtdRIX\ntKVNANxtW1Mb07Vf5ctih6FrV/tnsXaYZH/3XcuXCDoGnAYTjCjiU9RWNJrLRCJjRFWqtWFZLrFW\nQpS1tckz2baVWz+iFLyIFDN8+7cAOtF0gqhMtcFoS93UKB9wuI4T64InzwqURiw1UYAPHgOh6U60\nAFHHdOoVapL8m/weZYTEQ2r5Jravabu2UWg7XvuOZdvhzn0kU4L7E+pOyg3VqjuVtH7N3BZyP85h\nEtg90SXksTNN3ihCaHcNHoUAChQtC1jeR0VA6QyNJs8lSu3i4oJ+YRn2e7hKTlJ1WVIYi13MWF9f\n5+WPfIKXX3qJEBvev/Mejw7uA9A0Cyq3QI8tqmfprQ2wuaHvC8brA7IU42V6huXyAlSgKEDXyeaU\nl0QbqdxZ52WdnB0wHhbc3L/OfLokDjyuXLA4v8/sLHCUyEFKB4brQ5oY2dpcxxZPcXw2p25gejbj\n5DSdmkcZfj5hY2DY2+7zzr0HXNPrNI2idopqWbO5LoV4UdZsbl/HRTibzFhf3+b1N94Ak/Ptozn3\nHj5KP0sjTGYJKp38nMMYISl1gAhrIQh4sulGEwkVGT1ZLv1+nxTlsYUfRAk4ELazTnmrofvZUcqk\njshjZq8nbl0Vzav1wa1Wth4afIiPnSaN0Wn6lgqDbm8rvNHLCSDWZAkbp1a5x7pl26zMCgEtyLbo\nMMlcr1EsqwqbHiDPcykABKJz9Ht9XHT40PoerTBc5dnIzA9wZaBpGoqiIBK6E673KXEkyfljIz5D\nrbT4HEPsrBuC51M0TUBhMCZPilMnilTvL12M2tSQgHM+nXANSlsy3ep45XpmWstAFACDD57MZhJQ\nTdsKlUzTum7wSlp64iFNgPoA36kbbK04PkZRIHcz0/bjNWBTy7tFGia1cYiua3NnWkluaEK5eefA\ne6yG6B1VdUG9lNlebjV71zfYH+4xGI1oyjP+5E++TO0qXPA45BQ8GPfojfqorEeWK1RmmZxPqajo\n2ZwySuGq5yVFL+NiMSUE2N0TQPr69Q0U0FcF5ULariHzXL+1w2IxAQMvvvQcxwcXHDw8pt8ruLEv\nGL1BL+fOwUOaAEo5hvmIfGfEZFrSLCInh2J3KWeKYV/T85aQjziZnpFPa9bGY5Zn58wvHPNSClfR\n30CZAq37HB6f0etvEVUOKuP9uw8geSqNzTEElLVUdUmIDRGPxXR+YIXC6AxlXFJ8y9jA+dX3RoxR\ncI9paaVpGkfIhc4UEwkrxHDJOibfCzpC+I5N7ZO0rorm1frAlk4lwHvZsbbzOpvZZN0If+PXKVbc\nWq0U1ujko4zi6dOKgCYE1zlZFEoQbEl4Y4iJu6rpFdnqgpJao/hAJCSPohhKjMm6Niu0J7ggCS1G\nY4xFK42PilZEEbp5J8SgUTFgbY5S0IRahCJp/mmsQQRCGm0UPgRAY3LbYfouFy6NxydvKgg6jvTI\n7clcB0vXnI4RMGgd02m9w7UTfBBMnlJp5pnCnq0WlN6ldJlWuCRiJEVuLKpJxVerjoYkJ08x5LSw\ndyUfAFEpsd8gLddMWbEPedIGJZIpaf7lWvHs7VsA7O/tkFtFuTznZH7EYrFAZxbVM9SuYWNrXR5b\ne6pQpfQwTdlUrF3b4Xw2ZeEddZA27NItGPUHqNGAyck5fiq2kdpEVFQcXEzbbGkGO2ucNRd4v2BY\nDChDyXirz6OjhoOT/5e9N/mxLc/q/T6/Zjenjf5G3DYzKyuzqCKr8BNIeOKBkfCgGMMYxMwSEyZI\nCMGQCaOSsGSJ/4CBJSSDJQaWLNl6VTwbXB0F2WfePrrTn938Gg/Wb+8TN6uw3gPKaV3FkqryRsQ5\nZzdn771+a61vc839B+Ls88u/8ovYH2o+/PhzRrnhra+8wcHBGY8/e8F/+r/+gbERAYW6qWjbisvF\nlvrxBURN8/gFD+6ecTXb0tYNrZdH9GC0z2xRUww05eiQy/mWB298lY8/e8xyuUZrGVdUbYPzijIr\nyHOL91kSGwh9e9a7gI81eVqYdkAyFdLiSXX3V0cxMigtOsh18DuSSkydkxvyjt7LvPT1nWjeJs3b\n+BKj54ipVmZWnWBBEu7x3u/0aLs3KS0VWbcKTjPFNDAUsEkQtR0fVYfvAYsI6KmQROAjWmpCcp3t\nwKZBJPhs8pKsmxZNFL5mSrrd3NI7SfYxRnFa0QYfIu4V9KygkpSYgYocn/fiE9q1U+navZEYGqwp\nQBt864SnaA1tVQtgia4VpvDeESLkeUYkS04gSnRikzB7iMlmjCS9pw3KGOq6JcssKlUJjZNWtTUW\na4RTqZUWoXsjCwOTyeNCp4TsnIjeGyuv02l22QsrONe3+MQLQ1YQAmze1cwmVch40txYow1MJgPe\n/uobnByNGJRybWxW1zx5+imbskXlmiq0QMtoNGRUjlkmME5bV2yqFYNBxnQ6IoTIs4s5jW8JNBTj\nNMfOhzhjWK432FFOPhEhg6vVGh0tTSOengCT3FJtNpwd7RMcvP/4Ewo9hEIzPhxQe2khL5sFe/tD\nhnnGKM84no65szflWr+g8JFf+g/vyT5Gxfsff0rlPYvthrZuCZsXlMUQkw0JEeYrEUwo84LJZIqy\nI4ZFzt7+MZuq5Qc/ep/L6wXGdNxhAZCFKPeAzVObXjto0yzeKFTMaNtKBENI/rOImIjJZA7vutuz\nrxoTQK8zsBSZAAAgAElEQVQbhSQzgX5Wiurb+Lu2/+sXt0nzNr60iP3NpkWrJv3c+gDBvJowb9yE\n8nBPWqReHvAmyc7FG4O/GASVCyIG4KPHKnbo0eCEtO8kUXbb6sxEAjJPlU0p6qaFGHuBdUJDmedo\nI/ZgtashpIScklEMAdJ8UWtF26ZEm3RirbU7VHAMNK3HRYfOMhQK1zqi60BNfrew6Ea1MeJcQNBK\nAYXFGIVrdzNeawwKk45J2uBaSSXYzSmLzArQKKFtIQF9ugWCv0FB6PZXa3lIqnTeky7wF9T2iEES\ntzKpIZ48QjvBdZ32rWkczjumkymP3rjP6ckBTbvk/MUzZlfP0ilfUx6UzLKGzGZk44I8y1lvG56c\nP+6FF6bDAdkgI6pkWK4hqoLJ/gGLzTVtWrBVrmE135CVlrwsuVoJQmjbwnQ8IhtY6loSsXMVh+MB\nF5s1JRZdFlxdr8mU5c7pCUUCIf34w39m9myOioaLl89532s2p3Pa+Zo3z055/P6HAAwOjplOT7h+\necnlIhI9jJxhudhy9+yIxhhmc0nEZeGonUJnE4Yji59vePL0Jc8uZmRZjqKTnDTJQL0F7dAmQnT4\nEDA3gEAiyiEtczFsD2kxJ21Y2GEKOt9SpUT8InIDQ6BvaBnEQEhOKT7+7C7R6xC3SfM2vrTY0S1l\nvthbXXnEZSTpynYpzKQHog++N3kmpmSbuGMiYSdSbtJ1Sg/mCN4J6Cdq+X1QFky3zW5mKRnTtTXK\npZ+1qNAoJXPHIq3eQxNBGakwoxfOoyL5anYHF1E4aZ1qaT3LQ0s0Pr13vZeoMgZtC5lROk9UGh9d\nn+y12um/KhLq18eUOFtCgDyT1yibtt9Ki1dbLQowXvw9lUpenqkizRLQKbgWbwwxJX2fzo2Poc+Z\nNvHyLGIg7jvPUGMJuBs8VQNaicexlrpe5l8yp+2+M6MgRkemDUeHBxwfHWK14+mzj2jdihC2bBMQ\nqChaBqMRTCdyPBGWixm+aXE4svSZ+Tijbj0NHlMq1tWW4NaUrWcbt6h0rTnlCUaBVmzXa9ptSqYe\nFi8vCRYePDwFYDbbUi3WDDJNQcs4zylPS5rFls8vPuNosg8IWEmbSBNbRuMjPn92xYeffs5gMCK4\nIVdz2fbyxQfceXSHUF9yOLDYbML8csnz8yum0wmL2ZqTY2nlFmVOlmUcnxyQ5QM+f/qC5XJOXVc0\nThIjJJ/VIKC6wmao4CDm6NDi0jXuvJPryRp2kB2VFnqKEDoD81e1oI3RaBfStSwWB6HjbpKSq3d4\nOt3k1zNuk+ZtfHkRu7aPSZCcG8ADQCmPVon7F9PrlELu9e7GdhitMEbQntaYVPUI9aTX1owq+ViC\n78AvWuZoyte9ybE2ojfrXMRYJZVp9II+1HLDxLYTi89xrciIGZMRVQsqYpSmcTIzi6HFGE3rakxu\nsMbQth1KGJlFpU5hiAEfIGpF4xKiSQkOWAgnN5f1As5RwjbHVY1Uk0pQj851PFYjfode921TYzQh\nBOxNbkB0vdBB5SIk0QQPaCOOpnQJNplHR19jbIFyjlaDyRRtG2nS95jlhhjk+1AYvKtxCpTXaAc2\nDQubpsYoGE0K9iYZm+058xfnFKMMO1Bs/AIzlpnd8GiCH2bMFg1NtWZvUKKBsrAU2hPSdbGsFjgD\nPjdsdGCbKfaGkZWb47J25/kZGqLSRC/tZlsIf3PbBvJiSFQLHj/7FIC6hXIwYl7XTMeWbGzxboMZ\nVYxHOSZJ3vm5Y72t0JkhmxwwzqaYfMPV7Jz5hafYuyfnh5bN4jEj68lUQVVDOMjYLls+efyMHMvh\nQWrdN4HhSDGZ5Pz4Jz/i6PAe11eB9XKOyvd7qzxlxW5OG0UWITqDsTnK5Kgk12iN/K83CnpFHjGm\nzkG4sfCTcM6RZRar02LWe0x3IYNcHwEwqm/hv47x+i4HbuM2buM2buM2/p3jttK8jS8tOqi6JtlL\ndfw+Ywje0fqWPMvIUivWt0Lg1+ZGm1J1vDGDJs2vEkVFwDc3FU+6WWRqU+GTwfxOtDoCaI3JLNYI\nClYpfeOtEdc51UfhR4Zk5RWDoHedc7Sp5RpCwHuFB0zU+BB7uL4npvbybreC734v4BsBEWmUThV0\nV40HTcATHbShs1jTNG2D823PIe1EumNCy6IF6eu9KPx08oExRhFUaB3kpWzHRzAiIJ8gy3LeOpRu\niPggs1lcxLVyrvK+uifRR4L0yrvWMGKo3YknmCJnMh3iYsvl+op8oClPRqy2MwqbcfbwYe/teDm/\nYv7iHDUYMSpKQusYDDKhWRQG5xIHMjq0yWgaT7WeUwwHUFWMy5KqDdTp/AyKKaCotxXjctrzW3Nt\nyLTGqjFVEnEfZSWZLrhaLjg72OdgssfLz87ZyywH0z0GUVoGedQ4VTEYlRC2lEPNnTtTjJozVCWL\nS5mR3jmakA8tq/Uc35S4DbTtlrIoub5c8fYbD1guBM17cbHmzB/w9//wfcrRmE3j+OzxMyKG3Ob9\nnL2zlQsxpnasBy8j786Q3Wgr1/C/yArpENBfrBZVQldrjI7EYBKSOl2TyQpOzM5vZ5q3cRs/t9gh\nPeVnA6JIEnf2XyHGfo7ZqZh0f+vnm0D3JBCtWt23XUEeHB0YPkR5mLiEou0+Tx40osbivEcnHVwS\nQMaH0H+mJDWhcajgcd6hgsbmQtCX/dD4KHxM53yi0gAEohZ/0B5H0XHpJHPTP4wQ30/hrtxwJtGd\nK4nw6GIIhCAUgaJIPV+nZOaIJMXY803NqxJq6dSJaXaitsQgsnfpfJuOupKSp9bSVjc2IyRUcCQQ\nO8pJKyNj54TOYrQhs7K4MQpGe+Ieko9ytPY432Iyy7pdUtU1B6clo+mYyng2W0k06xgImWVgLTHI\n78eTI5QxuNBCalMWtmSxWtHUjuGwxKoMv1lRlpnYqzXpO6wU620FykpbOkiCNNqwXixp2kCWiU9m\nu/X43HGyf4/Z5Yr15YzSBO49HKOMYjwWustbD99hevE+nz15hg4N1kNdL7l/d0TYm/LDmYCaNCX3\nz46ZLS2X54rJNKdebDmcjHjr/kOWixXDoZhLzxYv2WwH3ClLojZ8+vgpnz59hi4GON8SUq+1A4gp\nLde4YGIdRLWTfyS5BdletPjVy6C7t/SrfxMvWZEMMclvVl6yE00IQsS9Rc/exm18Mf7yL/+Sv/qr\nv+p//uEPf8h7773HZrNhOJS50B/8wR/w3nvv/Yuf0XEtffzCijYm1Rmz43ECvZRbR9mAJP92M4l2\nRU4UX81eSShGoUTQAYtShEBgJzAdo6d1YI0iukCWA1FmgLqb9XQcSEO/8kZrVBAdVn+D5B+U8DyN\nscJniwabBWI0eJUMrLtKE3mf8ogRNrtFQgzhlYeeUlrmwFpRKksbPLVvcU6q3TyJc2sjs88QgiRN\nL8lzMBj8FIHdKIOyKikXSgWsiMlnU2FVf3Lls7UgKUOUB6aKUoV2uymG3AaTg46dMhCURc7edMq9\nhzLbW7uK6/kLJgdjFtsL1s2awV6BmRpqWzNfbtBJYL7c32O9WMGmYnowIc9khteoQFZoNtvkAdk6\nikGJtYI+NiYwHGQYIk3tcEk0wEeNbywuAKXCpEpzs61w0ROjZZO8Ko2xCS2cEbxitqrYH8NsuaZW\nNdOR2JJVERZ1xWcva77+xohpbnCbJ5weHaPGJc+msqBZrbfcv7vPwfGY9eqS8d4hxbBlf3rIdHKM\n0VBVMhu/f+8ei/Wc8d4el9crlpsalQ1YzbcUk9HO0L1fJIrcHVEWfiSZRDnm7jtXN+gku9ghpncL\n0Bjls6LSRBQxCkpcXifbLGyGitB6xyAvf+pzX5e4TZq38a+K3/zN3+Q3f/M3Afje977H3/zN3/DB\nBx/wp3/6p7z77rv/eR/SE94T2rQXGBUidfQkeoZUVT7J3t2U0DNGqjOldYLjxr56U9BXoT0tgn4T\ngtk1Gu9aOjXabn+0yYhJXcZ3JH3lpQ3WVbyKlECDmGRHJWo3buf/6ZPdoDJaatwE9gFxOIk37QxV\nl+xjTwsAeYiF8CooQ14fxKRZpbZq1BgdCFr3yVD/DBSjNXaH2L1RmaeNpWNJreNkVG207lu9u3ac\npXGO0NSUtkjeivRSah1NxRhFbkV1Rot+AyZTbLaihH65uKRql8y2K5b1msmx5ehuxqbZonXGcG+A\nsaK2U1eeGOBwMiaiGA1LrrdLogr4YGjNbpGkNELHUAEVoRgqfKiJ2mALeai7NscWhuAibZBWMYAd\nlZQWVosW6+R4Dg4OWK3WPHt5zuFhyeRoRFl65tvAOjToJxcA/Hj5nEX1gsZB4yzLpmKUwDdZprl/\nR1C2z86vyEzgYDwiqKdMJiXBZ4yGOc12RZEZrq+XANw5u4PKFYvVGp0XzFYbFqstMfEzu+5HCHEn\nZRc9SiXhDWRx0UWeZT2t6qeuq6RpvKs403UsG0rcXdBBOkDdXeVCSMn59Y7bpHkb/+b48z//c/7s\nz/6M3//93/8ve+ONFo5Shu72Mx1p2vsdHyyEviK11kqSBAih/7c2KtWRQpGwyvTVmUq/D7FLmEls\ngJCcQHZ0Fpt6XFGbBFiNeAIm6kSOSUmhEdUcHUIPz49ONqY6x5YY6dTqWi/7ao2YRWsUIRMRAHlt\nVwVIezSmf4cgbeOb7dSIT0lVEpuXkyhqQ1r1I6XoY3fwMkNOea91LUabVyTQOlNhrcwO2JzEI2LQ\n+Fj3+wkyezbGoJNOrQgTmKRsBMp4tltpd+bjASY3FLnCtRXnVxUXs6f9sWRDRT7wfOOdM1TRcr2d\nURQWHz0+KDYbSR7GlNw5PkbN51y8vKQxDjXOKccD1lXV013KIuP6akUW4XA8xjeepd7io8H5DK8l\nCVMY6kpDYblezMhias9OClpXMz7NaJv0XeYt1hgODg/YrGbo4HAbTWkMQ1vyyQtZBPjaEENBpi0X\n5564WfL1N8fsTY7J44TDI3nsvv/JJ/zwx3/P4dkpLmwYDBSrhcc1G/JswnKxpVvzXF9fMz3ew+YZ\nL1/OeP/DTyjKfRSGtm3679AIGRajEGUs7zG82polBpmRIyjzm+OOXaieWiRm5x7vxaItgiC3tcKg\n0v0jn9MGT6ZN3415HeM2ad7Gvym+//3vc/fuXU5ORLPzO9/5DtfX17z99tv84R/+IWX5L7dp/o//\n7XsAXJ0v/z/Z1y8j/v4fXnzZu/Bzi4/+8fGXvQs/t/i7/+Hnf2z//c99Cz87Pv7w/Oe+jbfeefhz\n38aXFSre7Fndxm38F8Yf//Ef8xu/8Rv86q/+Kn/7t3/L1772NR49esSf/Mmf8OjRI373d3/3X3zv\nydke58/nHJ5MMEbvEJ/GYJUiRieKOkibtTc3bndemt3fO3kv4T4KwEGq05szO93/LFJuOsm430By\nKkVmDQFP27ZYpbA2mSvrV1udPtaUZYExhqZuiQrRp0UTiHz/B8/51jfPkuekIA2Dc8nqSvcG1J3M\nXewqXiXVXAjSalZaY61OYgS77VtrUFrTJB/L3hvzhqqPVZYQg1SWxpBlIsbt2k4j7dXvRCuNV8IJ\n7XmdKtl79Qo/8Ok/P+ONd+8CIuxgBCpLZrL+fVVVcXQw5fTsGGU8Ly6eYXOI1mGsYpzLnPJgUBKs\nww4Mjaq5WF7gNejMk2UFg2LMIJfKcD6b8/Llir1pSdSO0cGYq82CNrY4HdFZVwdotpuGg8kepSkI\nrmVwoLm8nmHyEWiZu59fLvHBsKoqjk8OMQY++B+f8cbvDKibCq/g9DSJMMSCYTllM9+ifWS7WrM/\nHFKvGlRrGeUy0zw+eMDTD35C6Qwn04cot6DafMSDexn7gyM+/3gGwP7BmJP7JU1w1M2An/zoKYVV\nHB6e8cH7nxHJefDwDQBW2zV7J4csthXF6ID/+L0f4WOJ1gO0ibjunvAhVfrSqSmsKGvFIJZxH3/w\ngrfePunb7kBCc3fyjDq1Z292IKSrobUmmgznpetjVbJ46zr7DkTMQ3oiH73/Oa9j3Faat/Fviu9+\n97v80R/9EQC//uu/3v/+137t1/jrv/7rf9VnxhCIiRYBJOur2PtNdq/56TfGJHsnSSvceI21Vv7+\nyttCD6bp5zfWStJob6wlO0qLNii9+71OknUhBIISdaCYjHi7VnKbCOBWG4zN0FFoAdZaAdw4R2Gl\nGg9ajK5jaisbFcRxJXjq2qWHV0y7pGjdbhapUEIpQSXsb4cSDj2IyafBVNeO03qXGOX8AUoWLd7t\nZA3lb7pXbOqmVk2SH5S5sHx2wPVE+72DKa2v+PzpJ+SlYl0vOd4bM5yWqAyKXklmw8urK1RpyYaW\n5RbQluPJGKNgtVzhkhnz/mjMwVfHzJtK7NWMwVUNo8kAUxiygZzL69mC3FoiinVbUw4HZMMSN1sL\nuCZdCI4KW2acHIwYlpHOns7YwH5ZYoeOupbrrt16qmXN1QvH0Z7l5GCMDTAcF+QMGRcTAF48+QTt\nVmTKcH31mMm4IJ9kfPpiy3Nzznye5CKLgl968xso7fjR//0Uow0X1wuuF5/gfCQvbK+sE4nM53Pu\nP3rE5bxmvdky2Rvj251TDZASmigCpWWgLL4SmKy/H7RG2c4nFEJIIw4NdeMhNv34RChdadapFUYV\nIkwbo6hshd18XOtuJHKLnr2N2/ipePHiBaPRiDzPiTHyO7/zO3znO99hOp3y3e9+l3feeef//QN6\n2sjP/rMxAsjRSuG97/0XtTF0XmE3HwRKqZQwA8F5gnc3KsiOQiKvDSEmzqfI4UXTzRVFLs8axcCW\ntE2NCxGlEqgF3c+ZjLZ4H2lvcCJd8ChtyNMDxxhxbAku0QBCmte2Iqjd8zURGoB3gagke+mUzLUy\nGCPVX3e83ssiwocW0+vXqh02OCXX3MrcUhlRRGrS/MsaeyPR7hCQIc2CjQVcormk8GnbPRGmm20G\nGAxH1HVNllv29yR5bJYzAp68MOwfDTjIC8gDdVgxGo4YDqTS1E3D2AyJWUY+njC9m6Myw4vnz4iu\n5d7pGY/uiZSdDo7L6ytWW3jjjQfE0NK6irOzO5TDktVWBM7rbSUAnwiL7Zbh8QGEjEf332BTV5xf\nvARgOFBMpgURz2p1yXQkSbeIntJkVFWLCQK2KfMct3E8vDOCtmJEJLQVB6MJNkR0lJnmfuG49wvH\nUK2ZzxU+btGFSBCv1o4sUW3WLvDDf/qIO0f7PH9+QfCKwbigbUQT11P11/nJnTu0UczIDw6m7E8H\nrJYryvE+wbm+CwMK1zSgg8gsdog46CtLayw2F9s5AZnRL8ZCUGTJ7u5mY0WutwZZqXVOQaQFZXeN\n6D5hmp+akb4+cZs0b+NfHefn5xweHgKSsH7rt36L3/7t32YwGHB6esrv/d7vfcl7eBu3cRu38e8b\nt0nzNv7V8d577/EXf/EX/c/f/va3+fa3v/2f/wFdq7G3G9qtThUKlEmtIdVXjP3ru1lmRylJnxES\n5SPSiSEkpGtwKC28wfgKfUPhESSr7FNSwsFgrUIZI9zN1hGtAmzftgpB3DN8jOC9zIGUVG/dbM1Y\ni3cRFxyhEb9JHRNUX9FXerKPaRd8QrFiUEqoE1oregnetN9olXR3u+NUOyeTnoIgyi823epKSSUR\nQkgCEOn84AnRk6kc1zbC4SQSE4zWOYe1qTJMVURZ5ihl8c5RNQ1EyPNB38ZtmpbhuKAcKhyOarOk\n0FCMDbb01EpE2CMtlWmY7h8y3Dvi5cWczWzJfOVotmvu3Tvjo08/A2B+cc2dsym6HPDs5TOWswWl\nhe1qyWo23/mn+kjrKmoUtQosmwpVO+kSaM/RvlTDjd+w2a7xOLIAg0zO8CQXQfIsm6CNHLfbNAzL\nkv1BSR4KSu159xff5erlCy4enzMdCpXk/vGIghnZcMPJyQnBFrxcNFC1TA/PKM0DAC5fPOeH//QJ\nj06PWcwqVvPA13/5KyxmGzab54xHY1yiifgqMD2YMF8tOb9+RlVVTCfH+CB6VqrjDiuwmUnXqKb1\nbRLM2LX2nXfQyHUr+hwdEpvUhhXBkU5lyJostYlz2ijvF2tXKzzjrnvjPI1PlJcbqOzXLW6T5m18\nadHPyILMxXoB8RsQ9m6OqZTqW1AxRsIXQDndg9wn7TmFQhlN7NwsWidUD2nKQvSEEDAGssz23DYA\njwieV9ElRxMDxksb+Uaia9okYK0UTYy4xpGVBd45mqRy5FvXc9l89GgPeCdi2VpE43tXkBgxNkNF\nT2zFNFhFjfapfRrCzlxaWQpboDQ0zgl3jl1S7c6Oj57YiiJRD+yxhtCEbpPdSU/AJDn/CqEqRC0t\nzqiDPGyhlxEMUdrerY80TeDRG48YDizVdg7AV77+BjGsWazPGe0PGNkxVVizbNbU65os2WO0Tcum\n8lTX16jFhlUlbUObZxwe3eX9zx5DK3SXsoQPn7ZsjQLnZB8zw2p5jkJRDCXBtQrWtYNhSTksmK1W\n1OuWosgoRxZSO95RUQ4hREU2MgxLuQgP94cYMhYbzXKWPC215s3791levOBoOsRvl1w/P+fZJ1ec\nHRuqlQB8jo5KyhKaKmJsxWRvxKyCWMHx6QH7YxF1ePONe3z6QcaTjz6mmjuOjs84u3cX555z/+EZ\nw8GkN2J//vQJJ6f/FUdFQdQFw/KCGD2bdYXJM2qfBBjSfRLxaaHTtdhVbwSONqLQZHVKkCqNH+SC\nKIo8SSp2gDuhPckiC5TZkZ98DP3sO6ooIxV0Pxt+HeM2ad7GlxZZd+cFcSqxNu//FpIzRvBiA5YZ\n0wschC8IHMBuJmcLC1bjXJAZaLp3rckBBU3E2gwXFLSOzFgCOzQuCnKtBYFrIqFtsUasjqw2qAgh\nIU9VNPhWeJ6FyqQijEFghN28FifWVwqUivjQ0oZAnhe4ZJatc0lx9bbGRE9UELSXije36GjRtexT\n93BEidJP2zq0sf1xatICIinbRKXxJiTXF4NWkqRQhrp1Io4AKGVFbtYLAMm1gUAAE9IM2eA6zd7e\nYgpcG9A64/7dNzm9c5/19hnZJM1dB+esm+fYOy3NMKKMxQeDdQNqZ6jT4qPWlphHxqMh7baBdk2R\n52irqdyWjYn4tGDalhlZlmE2gflyxWQwYt1YfBMYDSfMNskLsrSUY2itp6Ki9o7BEDZUzDeOciKf\nNz4YUfmKPFm21V5mvovtglJ7Cs4YTkUer9lc4Vaf8rWH+ywvrnCrihdPG84OxozzgvGhJPbTM8Ns\nM6VxUx7df8Agy6iu9zi/WHLvHcOjr0hizuyEk71vMsTyHz/5R776bsHDt+7z1htv8p+++w98/M8f\n82v/7a8B8Hf/55Lt4hKygslgjG8dSmnGoz1aX/WdF6shRocPsUdKewRQ1qNlswIXAlbZhCIPPQ86\nRgGdCTez6G+LbpbuQgtGY6xGLN66GTyYPPnK+prXmZRxmzRv40uLTq0nyyzBe+q63v0tJZ2QkJ4h\nyZJ0tl9B//RNGWOkrVustQJE0KonWQcfhHJRmPRvRW5KMextN6jkVm2MTiIIkeg8hRU6itE7N/p+\n06l1LP6ZkaiUVMmq8yaUqrTxLd61aGPJrKXIM5TRu5V/ik5owHtRvelazyEGkbhD9Z6iJEF6pUXc\nXvZHp926UTVr0cpVSqOVIQSP82B0asmpToThxveiDcpGlCcZD2sIukceF7kAReqqYjQYMpmMODku\nqTfPWG+eM5UuJfVmLdSScsSqWtE6R1ZarCmp6oatE37uYK/A5BmL5TVNXVPkBcXAEIgsV3OU1hyk\ndioGVusKbUp0kVMrR5lZTGGodUXdiEbtdDwlGFisr/Das783ZOJFR1ZnGq87ioZnXA6JriVXhraW\npDlwJZNhxnxdE1RniQYXL1eoqmWvVEz3hhg0xXDI3tE+zkm7+fD0jEM7Yj6vGE9GVMs1m3qLNpAX\nJSp9z9eLOVlRcHb3HkdHH+O95/zFS06P7rO/t8+d09O+c3B0dMzV9TXR5rSxpixK5suq1xjuOyVa\nOg5Kp3tF7a6rTvEiRjEhb9sWknmASteu1l03ZifiIT+IGEL3WQYjVJX0SqBXklLxVSGO1y1uk+Zt\nfGnRKZl8cVFqjcVkwjXrWorOtcREEbHW9pVcF1ELujMEL23NLoF0N7Qh+QNqnGtRypAXMo8D3bcz\nzQ1HE6l0I0p5SApCN7eqEA6ckh9ECUhsRHYVnM1EQtdqijwHBXWzJQZZKHg8hpyb4T1Juk7hInjn\nUQFaJYLo8iJ6FGOQ8hBIFfiNnYxBKnN5qIpzSvSOoDIIntA9a2/w8rTVGGVTK9qiMPigCKldN56I\niHhh4StvnGGsYXb1AXv7OYfTFheknXl8MCJYw2w9I0ZFng3xjWJbb1EqZ3/vSK4Du2azWaEjjCdD\niFDVa5SB8agg5hCTGlFTtbSNY1k7ylGJNkYWBtHjQ830TPics+UlLgQGo8h4UlCWilGbU1c1mS6w\nKdk0TUNcN7RVjTIlp0MBth3ZMdXllhyN1pI0r6/XHEwMpydjDkZDVrMtx4cnHB/dYbmYoY0gbw9P\n7xIwvLz4hH9+/wn1ZsN2u8Zknvc/fJ/LlST2yeiE1WVNs2gpBwWz2YqPP/yYp5+9YH65Yjra58c/\n/JF83TFQlCV7Ryd8/8cf4oOnLEe0IXLTh7af1yvozNhJdJKOo+ydF8Pz7j0Ct0YrUQFy7lXJRq2k\nFa/YzcCJAUJHPpL/N7rTy7JwmzRv4zb+/aNLbDFIkaRDl+B0f3Oavs0YCPFmNng104YogBedKjEB\nA+2cGqzuEmRqJRlxaPC8KlrtiZiYHg5KPld5SUhKRaw2vZ5r9DuBgM7GKwBa7wjfotUp9mU74QWp\nBrQxECHL5AHetuqGeTTI7JXkHCL6vH01Gm4cn7K9ImGkE0notv/TmrXyQOs4sN13EcU2TCmcb3BB\nrJ8ioILI8mVKkuVqJhXimw9OGQ8Vm+2Co+OI8+eECHt78jplPZt1DTGnKIb4CA3S4suy3dxrsVkT\n6vPmBK4AACAASURBVMjBwRirDW1TMRhl6MyIMENwND1535FZaGLBYDIi4mj8Gm0j1mjWQRJSPvTc\nmVjGg1Is5SpHu6lwTcT4iPZyjobGMBgMiXpAu24Zezm/7dWWB8d3mDWO5UYUdN66O+LgoORwOmSz\n3NI2NWtlmX/yqYBvjJzTf/jxj7E6o6kaog6iWWxgslfS+pbra7H7qirDdtawfLlhvlqTWc2d0zvU\nG8dnsyf88rd+hR/94AcAXF/NODm9w3S8x53Tu1xcP2HbOJS2r0jW+e7fVifbri7phV48xCfusFLm\nhr6xANtuUKF/Zoh+skL5JPMYb1xDXss1+TNl+V6fuE2at/GlhU18MOloigg0yPzEpeopzyxKKbzX\nNzQuXyV0hw79p0BptVO1cfGVgjQCdV0hKjaBqtkCMq/s+Z7B45XGKqn0jOr0N1ObN4beflOcSBDH\nB+8JGmwUcfNO3KBuxAMUJQ+rPESiF1swOS5Hm2akIQSiT2jYiMyLIPlpKlTQu7a1MUTvUdqiO8uu\nrjK/0fZVOpnFRE9QRs6PVRht8Owqcp2s2JRWu/acVlgsWhWJkymf24kJfeUrD1lvLhlbKEcZy3Vg\nOJ70aMrZekUxHpBbw8vZnPW2ohyW2IGiqlcs5umDrGa6N8Aay7baAp4yH0CMLJbCfez1bANkxjKa\nDIg4nKoJJmCywHBYMMjTIskbBloR146whWFWgC05GFtsZnFpNuxcy/Z6jdvWjPOS9eUVAI/OTlhc\nrZnNZ5zdl9bw6Z0pkS3b9ZKyLBkMRmzWju22ItdwfSWC7S8ugwCOTMbAWjabLZm1vPeNb9BieP9j\nUcp5ef4C3RbMZjOq2nH37C6jwYjrl89Yryo+/PBDXr68BGD/aA+tNZtqy4MHj/jRT55SNTWDwSDN\nH7ubxyVUtqhaQXK68Rpim67bhApP444OMSv/u7HI6ji8XU6OYkwAEZRPhkE77WeUuOgEYn+vvo5x\nmzRv40uLnQVRxNpX0bHeO4zukl4kxg5FqzHm1VWsCrLq7VKFsRqDJM5OFSgSya2ldg5rJTF55wWV\na3SPxpX5obSAjRVqSwxOxBCCE6GDtLQ2mU01Y/f8EHeRiKJtkhly69C5JU/V5BcjeHCq7f8NYHQm\nIukxubUYMXP2wYPO+nPno9hwdWL3cj7lv13bNVcGH508HBExdqxJFYImPQUBUXLRCja+hajQ3uB1\nhBDwLpL8qnnvF99N56pC2YbQVrSqxgwyQq5oOr/N0ZCtgsVqzdJV+MwxHBui8uisoQgCNBkMDhiU\nBdvNihgzfFBcXs0FfGULiqLoz2fAMMhKsgLatmaQa7J8SIgtsfGoKJ9ZryqG2ZCpPSTLNeOyZK0D\nyhrOL865uJinbWsOpoa90Zh6tWKYFIWurh5jlOLNe1MOjwQIlGcQomG4f8j+/iGLZcNoYogvr1gs\n5+h0/brQsNlUmEHARgcqUJZZ+s5gf38vfd8VTz+94OJyDgr29w85OTrBxoIPfvwxP/nJTzg+FGm+\nvcke2aDAZBnrpma5WTEY7ON8JNNmpxwUpUdjrOkXd0aUKlCpilYk4QKvxQFGdfN3eb2PURZeN2UZ\n0+yzr2qV2tnK3Rx9KhFxV/q20ryN2/h3j52aTwDMjl6idYLNO6Gl9BZiCajTzfHoWpziFWm0Qdkk\nDddVRv2DwKOUTfJ1EXz7KoWlT64h6cJGmrrBICt1rZFEY1V6CMnsr3VSSeZ5nirMQOt9D+IxRY5R\nipDcRnSEPCtoUiIuyzLJ3oGjJUZomk4yT6fPSYuC5KgCkrCVFg5p6BIlCDhJ74zOnHf44MTlK9F6\njM6kpfzKc032LwSHMRafTp13NUYpJuMhDx8JVeIrb98HYLmZMdo3hFrTKk1tLJvaYYYp8SyWzLcb\nykmBzw22MNRZTfAt+VSjanldGScsr+est1uaZoPSmvG0EER1liU/Szmi8XCKsgrimvG0ZL1coWPO\nMB8xu1oSEz/264++xX42QVWR+YsLzp9s+f7VZ1R1w3hiefMNQStNJxlNtQTtuHtvn2Yjle3eHQvR\nczia8m5StrqcPWO9bRlPhizWCxarms1G0KbWWlSaaTYuEprA3mTK0XSfxdU10Qd+9KMf8uCNtylL\naV9vNpcYBZmFclRw5+SEk6Nj6o1jNBxx7+wBd8/knH/2+BOG+1OC0nzw4ccURUnVejAZbdPQ1HJd\nZHkmtKTge45ndKJCtVP98TQ1lNrimpZIi81E1tEYWeDVddW3eq2hn3NmWU5w4mijjcbYXQrRSu69\nkIBsr2u8vjX0bdzGbdzGbdzGv3PcVpq38aVFRzmxNksdoFRFad0j9m7YZiKiP+Le0FWQAvTRGNJs\nxvveTzLE2LeAiRpjFT4aTHIO6Vfe3vcbUnRmuiDVl4hVC7DhVfBR6/yOEhMiKMH32l4LVj7RB0FL\nWC1zJK0gzwvqusa5gLYd3aXAuZYQGrSWqtiFICR1Jajirjp0Tnh6KHEZubG5V8IYyPICpeSc1E1L\nU2/6VmJZ7Kzbmqoiz3JiECSkVooiyzg5PODhg4ccHYpm6ovzT+S9E8vLq+dUocIOLKYsCCrw5LmQ\n/Ldhy2BvgDMBM9QUowzfVvjg0ZnFJ07l1cUV63olM88RHJ9NyEqhPrimZtu27Ccey3C8R+O2jHOD\n945xXlKtHdWs5rQ84c17b8pxbzWffXTO9fMF58/mUkHeH/L2G3c4PRsDIgDv6hWTyRBNRTGw3D27\nC8CyXvML7z7gzZOvcX0hx7OYXaPzyEcffUDjItoOCN6SZTkm2GS6DZaMrCgZFkMO9g+JVcOzJ8/w\nrWO9XhES3cXVFc7VaOD4+IDgG64urlnNl4DijUePGAwEDbz+pw13i5Lz6wX37t7jJx+9oPGWvMjQ\n1hDTINloA0qoISoTg/X+Wuh8Z7Xp6VKYRFFJpgghOJo2Jg/V1H3RSmhUnTmARtqzIYLfIYeCElqW\n/yIc/jWL26R5G19adHOP4MNPtTy0UQSvknycRuvQ3+ySPDtB9MSN5IaxLgplUssypFliEAd7FSKh\nA/cEhQ8Cl8j6pCkt1hgj2t4c1uzstm78UigZVt7jXYAb86XuNZLNxYECH0S8IEBoQajnPdRW1JGU\ntGRvSpoJ/UPJNhBQkc0s2lhidD3PDoR+Qz+OUnIevJyXzFjyBMBy3lPVVdq0/D1EEStAyRz5wYO7\nPHrwgM12yWdPxDS6DsJHnNdLVp0SvRJj6xeX54SEeB7uZUTjMIUVScAYKIsBeTlksViyfC7UFD+v\nyAeaO0d75CPFZDIiasd6s6JxNXcfHDMaSMJ2TaDIMlZ1zXZZM7R7sLVcPVlxvt7y4d9Jgiv0hvm1\ngwh7+4YH7x5x9u4JeZGR5Yq2SYpNyjKwcHZ2n+3qmufPBCl7994Rl9eXNPP3GZaSuMrJiLpZETSY\n3PYjgDLLmI7HSVQfVstrmtqxWVac+5es50uKrODg6JjKexYzAffkFvAto6Hlm994hyefPyUfFnzy\n4WOuLmdsNxXrlZzr9WpNk0Blo8lY1LJCgLbB+tCjyZXytK6lm/CHJPH4xQUfMaITranLcaHTaQwy\nFukAYbRuJywCEBW+u2RewQ3JL6K/Rc/exm38XKInXROTL19CPloLOvYiAvL7jri/S5hddL9TRJq2\nwRhDDKkyjN1K29Blkp67mZJLr6KDCAoo7xJQRt14GMk+CMw+0VasRRmhpoiTVpAkGLyo9MjGUIh9\nWONaMqV29Bclx9qmeZEPHqMyrNWEEAVVqzSZFYSsUFfS4eysN5NCkvw76qQ3mx54LvFQRdwgokyq\npp1LLi1tOheK8XDMdluhNGy3FXdOpkz3Bjx78RHHJ3ucPbwDwGwtielydU0xGaLyHN/Mef7kClPC\n0bHwTnWpCVZAWKPhHpnOCHVku6wI11tG6WD02DAY59x5cEyjtmzdimigGCtGh3u0zZZVJUmubj3X\nl9cU45yDvSPaGcwvV/gVhC0USgBDs41DZTlf/fqIswf7TA7G6GrDwAZml+cUSS7vna88xLsNm/mc\nZrshJu5wbnK+9vYvcDB+g01KXC8uPud6fclkuofWhqYJ7I9POD06I1OK+bWgZ9vFFVoX5JMxhdZc\nby8ZDgZ88xvf5HK54PlLQeg+fnLO/mTM0ekBTb1iUGZ8+OGH/ORHTxgPS66vZ8xmAljK84LlYoXK\ncj757DOUsYzzEW2rsTeWnEYbXAf40hCcS8CeV5OmgO18L2UZouoxBWWRJyu90L9WKYVzpGvS9Nc2\nRLkH6PKtvEeb26R5G7fxcwtt7E7phnSThtC3ZGNqs6ok4I41hD7R3HggKI2xSeTdJM3N0CneKPEe\njB5F4lGmSkFE2TttkyjghhAJ0Qv1Tov4gVKKqMyO/5bE2jtEoTIJPRtj79cofE9N1AG8UAG0MqJn\nrSPKZP3iQIAX0va6KUOm0YTQpGqyO1SpEOrQSCJX9hWN7JvVQ2YEwEQUI2vnPEZbAk7soxBS/HK9\nIvrAcLTPL33rmxjVsF5cUNUzGqf4+DOpNLvi/eDkkJeLGU3d8q137/P2owOu13PaJEu49hWT6ZjD\no1OCUywvt1hdUmhH6zL2p9Iavnt/glMOVQScibTzGcW0ZN22bLZzAb00Im6wrWumhwPUYMhmA1cX\nK+JWkekxVVthE/r1F75+ytmbU0Z3DUt3zjJ7wZt2iKuv+Ppbd9hLCkPXly9ZLhY433J8dNhr+/43\n//V/h/OBq8sNl4lXGbRC5xYXHceHh5hYMC4mFNawvLrCb4Uj+tU3HqLMHvNly3p2zWQ0xhpNvdmC\nDwwTUGq9WvDw7lv86jd/hf/lf/qfWS1blo3ivV98i4uXM+bzOQ8eiLj7508+4+nTp3ztW79EfHaN\n846m3lIO9on1rrLzMQrX12istr0X7U0Lr44SJUYIuqesGC2jBOcDRscd5zNVpc57fBBZRZVUsAjc\n4CQnnrL0e3ld4zZp3saXFu4LTOrOlzK2LcqAuZEwRTBa5O2stjSpLxSDmD5rnRJUDARJM4g4QFpJ\nh/TviFRcKftoLa/svCKjA524obJqVtgv3P+9OHwQUewYIcvzXhpPdy1Z0v6LhAKZFSJ6JJAbS+1a\nfN30rTQxb9bUTZU8NGU2GqLrZfm6Vb3WhrZtCG145fnUm1Kn3xV5TvCBtmkJCNe1LEuc81TbLaOh\ntD2jBtc2vPPuOzx6+22ib/nHH/89xBX7Bxnz5TmXc6kwYyb78tHnn1Du7RNNhiaS28hoYLhaLtL3\nWDG7rFjNtwyyAbEqqCt4+vEFs5c1+18XZOhbb9yl8g2PLz6lHBr0ytO4FTG2BDwuVr0Qe5YPqVvP\ni8slts1o2gitYWBK7t874f49qYYnRwZ7UOOyOd6usUO4lx3z4OyrLBdznjz9FIDRcMT9d96iyEtC\nUCyWkvg+/qfPqJqWJipeXr6Qa0htMJnn9O4JRV6ymm+olzWXzQXatZRp3dds1gRtCK6gzAeo6R4f\nfvgRbfAMp2OeX0kS3t+bcHnxgk8/+5jJZEz0WygymtYxne5xeHjI6an4iC43S06GAy4vLnj27Ins\nD9C0rXh59jP+kMYATrSGTdJvVrqv/myWoULAt040bI3BGjFQ6NuyybS9u8e0NVilcNqgM93LNzrv\nCOHGak2lxcXrmzNvk+ZtfHkRUjZSViy9Ov1MSRAebXzvGGa0GEOLmEBLbne8Sq3FAFqhoI2IOrkh\ns4qY5mutl0o1RJkHNkkQ3mSaWO9MfH0MtE1DZjMRBDMq8et+2ljXKA3WysOnadA6Ccuj8I0kdVM7\nbC/QECEoEXDXotHpYtsL1Rub4aLHOINSmswY8IE26tSdVrSp4tI31InKssR737uQZCrvz2V0IuAQ\nlCFE+a9Tmio2jPbHzFeS4KaDkoFVuHrGP3/4v7NcXzEYFezvj1hvN2y2LT5PCTYBl4rRgHzQ4uOc\nv3/+HGeh8S1dG7wsCkosYzKuLlbcGRV89OQ5l5s57VDxIord19/906eoQYYrNG0Ny3GkamqMMYz3\np6gKwrW0TdnU6DrysDwjtIZZUzE5OqTILV/5+ikHp0nYvXqKb644yyY8qo8Jl57F3hWfPFtz/ewl\nRaKwHO7tY9cbqFpaDHUlc9YfPP4YbEarW9ZtElgInlEo8E+uKaylMDmFLVhsV/gA263s4/ZpzcGg\nYWSmKAV1DaHc49PnM9TLOdttmiMrQ71t+F+/9z0ePrzHvPI0bUaznTEdjBkc5RSTpFAUHPvDCc/O\nl+SmJNbXlEWOZ02rYq8HjAI7KIgh0PiWwuRYY1ABcdgBVOsxQTjKWEuIUl3KNZioXzFi0/cco4wL\nbJ4xJuKCJ7YteMgxaN/LSsniM/g0R3094zZp3saXHpGAC+w0NHvUbEK4drOVpKLTqZjIL4PYXiEt\nx7Is8aHzCeSVNmdmM9rgJXnFFpSSGeLA9tzL1jmid3jvaV1DkQ3FUCQhdo2xvbdn45yIIRiLQQvQ\nKLV9O3RqlzAhaXOm6tl5J/ZX1vQQDRelavUKLB3fTcBBJE3cTiNWa0Hpeh9pmlreFzzEiFe+F2tQ\nSriaDkBbEX1HYZXG1Y5xameWZYmKgeVqiWngzv4d8pGmbrdUbcOy2ZAnJOdgKlVfPtGo0lHmBt84\ntDIMR2XvC6qicAGV0+yP9jFYmvWa0+N9BpMx08POdUO0abermjZG8lxTFnsQAvUC/Lam2chDWPnI\naDSmKApmixUnJ0f84te+yXhSoIstq+Zpui5q9sdjhnnJarYgbDy1rYlRUYynuLUkrg8/f8xkOGK1\nrcBm4j0GYBRNaPHOkaUEa7Qc52pT4a1l5SOh9QwGY1bbqvcbNTbj88efUmLR1jIaDSiGlqo1bDYV\ndZ2cWDTEmHF2dsaDB29xcfmPGKN48Og+s/NLBsOS88vzdF02fP8HP+T+o6+y+cnHKK0oi5x1La3w\nzuUnpHtCDkFRVZUIgiiNuXHPvHoDJgCaFsUpa8wOHYvMyL0PvXJWiF5MDJTGR/GqlS9HrnWNRb3G\nmeU1PrTb+P97hP7mFVqHSXeaieJsZYzotjrvCc7RNk1qJd0wpFaiaiKfgjibuIDrTJjTgjcQaECc\nNo3C6kwSkVHUVYPV3VxSwDlGG7LcpsrWi/qJVqB8j3W1ykAHYIoij+cS8raTfQtIwvU+SPWYQD7e\nezBSVXeWW97FG21dcHT2ZgFtEuK2N5cW9CtpXqWVfkWXthPnRoNTsQc8mQi0nli16CJjWAjRXiso\nigF3753RzlcYYLtcsgorVKnYP5vSdMPXoTwk27JG2YpGeVQwFFEE7HshGQyjbESmFIXJefH4JW3j\neHh6gNIZbQLtbDHoFnRjmdqC3Cua65bVtkEDXqkepFns7TM4OGL5fE42yfiV//AthuS8eP4Z6+ol\nOpf26v5RxtXFjCYb8fD0IYfDQ9xwxWa9ZLtegU6+m1XNyijcoGDbttRr0dWdLxeoPKfAMMmHAAzK\nEt9UuO2WMi8IzrNptoQ2Eprdd+ebSPQVo70xea4oS1nw1JXGN4ZlMvMZ748pp2N+4Z33GA332Bu/\nYF1tePH8CdWqJgTH48+lFbteb5hO98nLgtW6YjgcM1+tiMqKmHq3MEsoapXE+a0R4X3TCyR3Iw/Z\n3RBj35JVXgaUIiDSAcq66ywgTnuCxPU+3mjBdlrMEUxEWX3bnr2N2/i5RJ80IxrVy+PlJiPEBh88\nRZ5jrMUbQ3vDkLr307wBcECJg4NrWxyxw9umLUBd1dgsw2TiwuB9hyIVDifIQ8Q5hycSYisqRIj9\nl3AdI23YzWL7TWuD1Ya8yKjrtp/PtkkhpQ1eOKUhEzNpPAoj9JNXtGJtvyhQvuOydujh0FfEXVXZ\n7YBSO+syo7uHG9RG1Ims00L78B7fRvKgOBpMsXmqoqzm/psPefL8CUdMqTYrGtsSc9iyZjAekQ1S\nNa4l2amBI8tEAWeaFwwZJEBSUloKGTSa9WLDylWs1xVnp3uMBiWXF+dsa9nHVd2yV5QcFCNsE6ln\nc1xd/T/svVmMbelV5/n7hj2ceYg54s4358FO0sY2FHa1jQ12dxe4ytAtWSAh8QYPPPACCKmFeEIg\nHpBoqWUJkOChkd1qdUmtwmaoATDOdNkGZzqHezNv3jnmiDOfs/f+hn749jkn0jauLjVWViexpJuR\nEXHi7H3O+fZe31rrP1CLE0yiGThLrRN4mi6Nud/vsdqsoQs4Or7H5OiYeiyop0G8HUDkKS4vqNRS\ndFThdDCBPKcoBL1hvtCebTSaGFvQn4wwAoiWdBztHGvNLpvdNSBYoo2HQyZqQKRUaOl3JKenferV\nFsNRaO0eHp8Sx5r1jTrb2xfIc8vx0SlRBJ1OE1OE5LW5scV07Lh7ZxeT7dI76XP/YI/1bot2p8ab\nb91gMgwVca3aZXV9g7fu3iMrcmpVhZCatFJjNBjg550FKdFKYmy4FuIkQlAaIIi5prACZxddGCnO\n6MuW4crqE0IiFioK838v8dbivMP60LfQJcXKUOoqC4nj257wXRTnSfM83rkoE45zNiS/eVUoCqwz\nGFsEmzAtA8qPpX7rXKYO7xZ/ByF5qEjNdQlYiF6V/EcdBVsxYyzGBGCQVtEcZIs1JoCNSqqIYNkK\nnn+dd3z126D3hNmnCcjdxU5bCIgU2geXE2Mt0hPmq4QqdNGetbZ0oAi2TcIF+bMAAs7xnkVreJ4w\ntVIlGCnMckPR6xc3rUxAKoMIgsgs0kEl0lQqzXCzK6v7pJHy5u1bVFs1ZrOc0/ExomlIOgk2KXA1\ng1Eh0WSlmIL3JuieaktsQDuQXoEJ7/l0UjAczBgOp4AjmxYUxvHGWzepxZr2SgDtdNYa6MJz+7U7\n6DxjrVVFRyky0kSVCroSc1puVGZFjo4jcpfRqDcYDPeo6Iy1dpPjoz0q1bJ1PhrSqNSQKubh7gGp\nrpMYqDfaiGbK0TC0PSdG4FCkjTZ5ni/anJUoZnNtnUdWLrPSCFqxxuSIWYFOPZUkIYqjgOh2GoTG\nFiXQBs32Rpvrj1xGoDg6usdoNKTdbpMmjcU63tzc4OH9Q27efJP93QGtToUkgjQN7fPRaMTGepAs\nTKsdhpMpRyengKTX7xNVGljnA7Bn3qGgtOsSYRSQzfKys6LQZxDqAchjkULglAqJoKSmWHdmkRMS\nsZQyGAo4h/MlWKj062Qp2rj4G/sunmmey+idx38xbty4wcc//nH+5E/+BIDd3V1+9md/ls9+9rP8\n0i/9Enkppv1v/+2/5TOf+Qw//dM/zec///l38pTP4zzO4zy+L3FeaZ7H94zJZMJv/uZv8kM/9EOL\nn/3e7/0en/3sZ/nUpz7F7/7u7/KFL3yBT3/60/z+7/8+X/jCF4iiiJ/6qZ/iE5/4BO12+x997qhE\n/KlSdH1OyLfOI6QiUTHee4o8o1SiW7Qgz1aXweEj0EgkwfZqzk+bewg664mSqKz2SmCDkOg4ArcE\nDDkXLI9UEoFwaFEKGpQzIiEF0RxVmBsEoKMYorJF5VzgtM1fiy+FDoQM4B9niRFIHZVzIoufEyyF\nRHqH0gGBKywgPUoILDo4v5StTyFEaNEi38aJ83NRhrKCdBR4UfpvFgU1ndKq1kgrKbV2jZPxoDzv\nnKgecTI6oSIg2dTotsLUp8jEk2nDHElSUyUQyGmiLKYWVzAYsmKGyWZMBqUQwRQQCWmjQaVew7iM\nRFkqGjr1KqYsx2++dkTvZMTaSkStkzKloNFsgXIcDwfESQMxF+0vcqr1OikSKXLazYg0z7DTY5op\nRCUdptZuU6l1qdXWMJlCkpDimWYzUq3p1MOxB9MexsN0MsZ7S1KirVMv6aQNEi8pRqFFOp2MyYcz\nKmnC+so6aaXCaDzF5PBw9wBVmj1f2NohUjnZVDAejxj2Z2iVUq/WaLW6KBHARm++eZPdB328n1Gr\nCzY2mgiVMB1P2bm4jbcRWRbOczSacXgyxEuFimOMk+R5QVpNSNOUvBRlsAvTg0BZMpRyi4jFGp8b\nVc/NyXUpKem9wBqDKhG1Z8M5R17So5QMLibz6ta40nLMBa6yUOK727i+S+I8aZ7H94w4jvnc5z7H\n5z73ucXPXnjhBX7jN34DgI9+9KP8wR/8AVevXuXZZ5+l0Qik8eeff56vf/3rfOxjH/tHn3t+8Xrv\nUILFnEl6Rax1AMOYIswLSwECY+3bgEDh7/2CZxkEeuRi1jk3sSaGIjeLVqgUYY4nlSJWS8NeIYKK\nStB2BaUpFXscSRyhpCIv5tSOYDhtvAsUEyGQWgVpvjJZG2sDElgopJRYoHAuSJ9piZJgFhxyh0Ui\nTNCnlTJYj/kyqUupKEy+eN3z90GraAEQEmWSn89/nbJYoREOKtUKMZJ6o0ZnpU1/3KPWLNV7mjH9\nkz1UBVTHImuKke9TiBlSCSqNhGxWSvhNw7HW0w10bnG9GUMzxQpBNnOMhuEc07hCa7WDjWKslqTV\nKr3DfZK4wt3dQ/YfBqUdXYGVdkKtrdC1iEwKerHFekO0UcfOMmoqbLA26u0AmEpiLq10aLqcdCYw\nw1NcLrl29ToA1WaXqZF4l1KpJYxHGbFNyXNDkeVlAxwiGyMU5DmMJxO6aysA1HWKmGZMizG6RA1P\nx1NmkxmtZhM8zKbh+0F/wLDfZ7VsN6906pwcH3D7jSOm0zHD4ZRr16/S7XRZW1tn2L8VXrc2SD2i\nWU25/sgFppMZWtdRaNbXt7h75yH3HwbJvfX1K6yubbJ/cpfeYExnbZ1ZEZDTSrCw6VoYu/tADVmo\nbnm/mFta50tJRgtaEWmN1hJjCvJw0QVlLPn2RqTUauGn6UutZfBnWsMl6E2Icz/N8/jnG1rrBYdx\nHtPplDgON9uVlRUODw85Ojqi2+0uHtPtdjk8PPyez/3vv/h3AOzeG/4Tn/V/O3Hrxsk7fQrft/jz\n37n9Tp/C9y1+6395650+he9b3Htr7/t+jK2La9/3Y7xTcZ40z+P/U/hva+P8l35+Nj78o+/ndnTQ\nDwAAIABJREFU8P6EC1caKCkXupV4j1ahFTqvMK1zpfuJLMEOS+CD9x4lJUKWu2cv8OLtFagveZRL\n/mapIIREmDPoVRW4aqKsalWpSi3naElYeHl6ArpViADy8XNXFK1wzvL6a4c8+sQac+9K6zzKBj5q\nQOeCFQvoRgDzuyUSVs471j4AfM5WlEApZv+dAKXwQsKXjFAxJ5HmwuYGcaQZDvqgC4wqUNXwwELl\niKoiSjW9dJ+4Koni8FqHfWjV66xUQhU2OTV8+X+9zwf/5zWqWjHtT3mgB1TXK1zudElKnb3ptGAm\nBEPvmSpBWqnT3zuimsFW0iaea53WIkQjZiBmTGLLWMwgAmkNbaXp+JhoFKrXptesdlbIazVim2H6\n+8R2hityrJVkrgQ21Vao1tuhZe89lVgjsiaNZhBr6PeDTqwjo7AzdASPP/4o1UrKZz7zeT7/+X+N\nNQaTO7JZaSjuck56p9y5+xZeQK1WZzqZkUYpzz/3fhq1IP4wGoyIojonJyNu336T69cv02rXmU5H\nHB7t0euFjdTu7i6Xr1zm6pVrvPjiV9jcuMzpYcHewQGRbnDSK6g2wnNevPIEr7x2mxe/9k3q7RVG\n44worZSC7G6JuMaTZwXOOyIdBXlKEXxcBXD7zV2uXN8qQWUa58xSLq9cRHM92sWP3oaEDfYCHsAr\nvOXMb2WQvXRuIU/7bozzpHke/9VRrVaZzWakacr+/j7r6+usr69zdHS0eMzBwQHPPffc936ixSiu\nFECfu89bi7OWSAXtzLmepShtuoIZw3IGOb/mFUF7FifxuFIEoZw1+oBE9SIkmnCzCdkzTeIzV37g\nU3rrcM4QRRHeCpw1WIJTyjx5FqVHSTiPMHSNdPz2GaOdo1+D0LstX67zjoLgeIJcXoa+pM1AgRKa\nSIZ5qLcW1Hc6+wZRF81sNgtyflFoa89v9GDprqzw6GPX6Q17DKdDOhdWOOg9hFSQqzCvkwkUfkIS\n1akkMdVqwvBkSC1JuHZ1i97BlOFuoHMUk/LYWnHz7jHdtuTC9Q3iZoLILEUeHtCopwifkzvIfDCt\nTpOUtq6yVd9GlfzaiZiR2RylwI+HVCPNZmcV7SxqmlOc9OjEgU9aJ+L4rV1qG6vkLuPo3h61FNZW\nV6k0u6SN0CLVaZOkUsObGX42Jo1hZOpkxjHNZ8TzeTqCw8NjjPDs3b1PlESL9WKA3BtmPryXk+mY\nqZlRadUZTycMpiO8sUwmE9548watenv+luOcIi8Es9mIGzduIDUksaY/6HF6GpJmtVple+sK2cyj\ndRNnNL3jYybDnNW1CuvrXfYOw8y5Xu8wHL9GvdFmOBoTpXVUpMgn0yWK+7uEscuZ5jys83hrKQqD\nFEGAQytdykLa7+BYOi8W19sCFF66BcxbsgA6Cvq1TgreZn/yLovzpHke/9Xxwz/8w3zxi1/kJ3/y\nJ/nSl77Ehz/8Yd773vfy67/+6wwGA5RSfP3rX+fXfu3XvufzyHKu5ADhlrPKQCdTKKkXwBYh9ds1\nVudOJULinV1UlFiHQAWRgzl8nmXl6ylpKUKEGY8LmpvujA5uFOugolImx+B8tZwNzU9jlmUIrUiT\nJLAorcMUJgB5zlqXAcqpwM0UCiHnOruSwi8ZbUFAWyEwWBPOS5TSeFpREs7nWmgCyVzmLIgkOO8W\n1WaahPZ5PU7pNjtYY9BJxBOPP83tvTeIOymZn5CVN7xIGba3V5nOxmQ5ZMcTaiKhTZ2TN3rkE4gJ\nsz1Rvtf3j465+GyNZjfCJBGTSY4uDCuVkHjG4z6DyYiBAFutkCYt2nGLbblOV3S4sxeI+3YjRYkE\n0z/mqSuP021WOdl/yODwlFgI1tIOLR2SZi1OWa+v0R+cMB4NWalW6XabdFbX2b78JFE9tAW9rGBN\njpn2cJHHzPqMbIbWGpEqJr2wWbCTIS43pKnGW0+WhQT5xr07TIucVIZZH8DJ6RHTfEaz1SJVFcaj\nMc6CcZY79+5Si8M4oqITChc4t+PJgCzP0VowHk9xVtFshPfx0sVHyaeS/f0jxgO4d+tNZmPP0888\nSRTXefXmPTbWgz7v/mGP2cxgPAitiRPNcDwm0UkwFyhX0byiDB2ZueCA42zp563Fek8cRVhjyHOD\n1R6tJDqKKLLs7Z6YZ3jEoZtyJgVLFvnRO4+TlNrL5zPN8/hnGi+//DK/9Vu/xYMHD9Ba88UvfpHf\n+Z3f4Vd+5Vf40z/9U7a3t/n0pz9NFEX88i//Mj//8z+PEIJf/MVfXICC/rGYC0h76zAstS6VUlhb\nUJRo0zkQKLh/OKIoWlyUcxStdQ5jbdlwDQkpJJHy4vUuyOdpFS7qMrwPN5G5eLyjrN6UxjsoXEEc\naaQOYmqulMALJypBCnJbLDYAcyUga+aoXYtELtG8zgS0rgibASXkAj1rrcUUBi0VUaQCubyYG2nL\n0sGiBDwpWdLjJKYwJEmMMY7C5GgV0ayHG/NmvUNWFCRRysraOkeDY6a2YGSmzPyIOAnvRb1d4WRw\nxGyW0a436TSbZMMZ+alBzgSpTRmWKNKTUtT8mR+4ykgccip6kDWoRy1qqqB3GMAr08mMtK5JV2u4\naoPCVOnQ5PC1A+7efIXXdoMQun6yzXsee4Inrj1FHXjwjdfJTk9Ya9ZoN+vsrG2iy7VyctqjP+jR\nqiSk9RbVSovrj1ylsbKBVS2G8wJbeGbTHGUM2ltmoz5DoZFGkU9H9E/DOWpTsLW2wtpql0anyd7x\nAQDjIueg1yM2hqg8tpUQVVIMltwZnIDMWNY3V1mpd4lLxHKqUwajAYfHByhlkcKQpjVq1Rrra1v0\n+6ES33t4wuvfusfJyZTZNGNrYx1pJ0S6AmhGowmOYA22FncYTctugk6ZTGckSYIvlabmQCBP6AAI\nwBuLUKIE9CxF1IWUCOvCZlBrpDGwQKAH1x99JmkGm71gGOQXknllYhZuYeBuvQMDXsmlJOa7MM6T\n5nl8z3jmmWf44z/+4+/4+R/+4R9+x88++clP8slPfvL/9XOX3Tm0UEGqrkwIQiqEjvC4QDVxoQmq\nhAwGzTbMGWE+03R4GSq1GIl1LiByUUtZOiKEsHgDtiRhy/ls1HuixZUg0N4gjSEu7ZMkhkgIUBJb\nFIs2qUKTG4NGB5swG1R/hJCIuRh9FGFxZN7jlUJ6C8ZQFBYnFUpFixlSAOl68MEPUfjgiCIQRDOF\nxy4NrsVcpq8gx2ILQzVNKZyj021SLxGfk5FlbWeTervOKO/Tm+5z2LtD0hA0GjFzne9KlNA/GpLG\nNbrRE4z3xwhfBTuhP+sxtUOidjj2xqNhzpbJIWZiWG2tgq5xeHTCsCiol4bRlWqbZqtJo75KkUfs\nPhzy0t/f5OEbR1zoXOLJJ34AgO0n2lzaXiUfHXH7/pvY6YCVbpON9Q6Xdy5RrVbIi6A99+DoPhev\nrPPYepPj4wGD/pTBgcBOcwpxgEzCBylTyaB3gJceY2bkaKSz2OkYPR2hxyEZdas1Ht+5jKxUOJ1O\nUeW5S+1IEoPTOZM8fD6dZodKXMMVnlF2inSWbqfO9SuP021tYfNS1GEMJ8VrjJMZvcmMtNakc+kq\nO5sXiOOY/isvA3D3/i36J4ZYCxorLaKaotefEdcivvLC17j62BNESdh4ZtYwnfQph9ykMgj/Z6ZA\niCpxqXsrvCfLMry3aB2B90HRSqpFxaikREuJchphDMZLMAIrABlqVlvO6YHSozVoIkdSIX24vkzZ\ncdB6idi1zgYLvH/0qv//f5wnzfN4x2LuoRkqzGX7SAoRFEiURIkg+SWFJJJhB228fxs4QUiF1uW8\nszD4EmQj8Tg/r2btmefWoYrzwTTauOAYAhCpMBv1NnAzBRLvRZAVM4bC5gt7LqQu7bxCS1kIwFqM\nN8tk7R1OEABCSuKzokzSEU4ICr9sdUVCBd9N73HOogim0doIIhQFZ0A/paC2k54kjrHWMJlNg4ci\nS/uyrcs7tFYaZGJKf3DI/d23SFuSzlqL0aTP8VGQfhsPCtZXVqgkKScnAyKpmIzGZLM+GTMa61VW\nLwV0tNHhZpkZx0pjg8nRiKPxAyrNlHpjlWp5o19rbVHRTQ7uHPP3L36TB7f7bHQbfPTDH+TC1kU6\na+FxcZLh7YhEWbIqNFdXee/Tz7De2UA4Rb/XQ6rweddqKdNsxJt396ikXZJqneE453Swi4olPgkb\nov7kFBdB2qhxeDwgrtSoVhNG+RAzGrHeDq/l+qVLeO85ODxm7B19E6rok+MDjJ3hvGBtNajytOsd\nhFWktRiRO8a548LmFpcu7CCocHIcKsjxNKM/GJIVlmazxfrqRa5dfZwkSrhz+00m43CM9bU2qx1I\n4zobaxd5cG+fVqfF3/7ti1Sbqzz7nmf56jdCgr1zbx/jDEJEQUeWsNa1jLBOLBV4vEepIHenBKG7\nImBubBAeA154tAwWX976hSYzQgQtZO/xc8Wu0g/Wu3l3RJU4gqBD6/2c7iSChOO7t8gE3t0bgvM4\nj/M4j/M4j3/SOK80z+Mdi0Vb0gQBgIXazxzEY8L8T/iSpuHCTjgQtefCCICUyHJSaY1h3jx13pUV\nIxgTDKelXE40nbc464NdF3N1ExXUToKlJw6/cG9wWIzxc91riCCOYpxxWGdIpMZ5G34/fy0Bmx9a\nt07grEU5h05irA2o2/lMU0gV5kfeUpbKKGSwFyvVjuz84CL8KzIDSqNkQNq2m02uX79Osx6quNlk\nyMlwj93T+/TzY9JKTK2RMhvPMLllfXUVgPW1FU4P+wxmGV5lHJ8MyWZjmtWY59/7GDaC/ZIqEdXq\nAORDyf2HPbppm0ubTWqdOt36NtKFYx/eH/GVb7zEw7f2kc7w3NOP8t73XKdRl1h7TL10S9lY3aGS\nNhmPFI1oSj4dcrq/R9Ybo2WCM460GoBN7WbQmLXacto7wRoNRIFOVFh6pwGMI1MNTtGbZVgf0ag0\nyTNLd2WDoSk4PQhcxYfHB+TG0ZtO0c0G4zxU3hSWRpJSra3TKhG57XqXapLy4O5dpqMJly7scGFn\nA++n5EX4B3B8us/o9BBpCrZ3VrmwusV6rcloMGL31h1Gg9AafvLxx4h1hbt3HlLTFVxm6Q/GXL9+\nlSuPPM6D+3vEpcPK/Xv74EOXxJUANkdYz9ZbijyAlfAQRRGRDu39+XoUjnI2DtYaUOUMfS7cvriu\ngomBPVNpzu0yge+YVAbrzFKFSAXxdqGW6//dGOdJ8zzesZgDE4I4O4sWaaxUkONyHln6L8sFXja0\nJue5I3AbLbZUeQs61SGjCLG03ZIyyNvBXGqspLlohRfRwkrLWxvAFkKjoghfPtYhcF6Gm8FcZcV6\n0GGOJJ1HxxpfBMCIUHPHEYUvaTHWepIoQlqPMRbvBUropY2XD3Oq+Y1pSRTwGGGx2AA+Ci8IgSNK\nUrTQFHnG1WtX2FzfYGdnh97pKQCj7JDdoz1Oxz3qqwm1VgIRCK9YqXdptQJN4ujolHqlwWg4Zq9/\nQFFYrlzu8NyzT/DmrdvkHuqdDgDjLJxhTa8RNWLqqkY9VWysbjA4yvlP//5rANy+uUsia1zbvsaz\nTz3C9kYF5w6oRCM2LlVoVsP8MI2q2KKPThSiXuFofMrw5ITT2THeRdQbLZJqkJ6r1yusrq4ztKdM\nhjO8gDSJ8M4wzcZE9XBLG89GZDOoNdfZWLmA0hW81NTSmGRtE1lKv+VCMvEFmYQsy5ElkCuysN5o\n0l27TKcb2rP5LMfNLBVVIZYxeM90OuC0twdCMx6H5zwe3iNRhpascaG1xnZzlex0xMGDh0xPhmyu\nBr5rt9Fmf++EfJQTixhvJU89/QMoHXN0NCC3ktPTQDkZTzLipBLarQi01IHu4TxSKHw5JvDGYUyw\noou1RKnSEUj4pZuODPgAYyyuFGBHCKQN1JLgv7lEdc9NApwEl+dgHVKFa0Eqx9k0Mkepf5tf+7sq\nzpPmebxjMXcqibTGWb9A04ZENudiBq+RhbmzKNGA87GiB4svd8MeqRRz9olgyf3ES6IoDpQNG8AU\niGDkbITGFUsTX2ccQofk66XAlV6USAkqWjqsOI8rcoQHLQQYhxQSW8oBAmAskgB2khIiJRBYiizH\nEJLmYtZEqBrndysRvKexWJbPWIIvUHhkMBqeGp558mmee+5ZRoMhJ8cnTKbhZntv/0364wGXrl9g\nxgyLIdIJzXpIWONBqI4qcYs3bt4B52leStneXmezu8rNW7ep11skKI6OwyyuuxJoEJNTuLiywSM7\n19AVxV//+d/w1S+/RDUNVeEjF7d5zxNPcOXiFp1mTKIzTo4ttphApnA6oHGLvMcsO2XY3yfWUEsr\n9E8mzGaWSKdAzLA0oZzllrQR4+KU+ko90HxmGUUxI6rCrDR4Pu0ds7Z+kWatjSKlXV+jWmni8jFJ\ns0a7UwJssjG9cZ/ZySnjWU6j5INudtZ54tJl6t1LTMJp0u8NOdw75GDvAcPxEUcHt1ldr5NUQwJ7\nsNsLxx4aHttYpS6rxGjy4ZS33nrAq6/dYDLL+MD7rgJQrzR4/eQttjYvcdobs7d3xNhE1BoNdi5d\n5ebLN3i4F1C+9XqTogDrCgQRIgrSiIUrUDokUQAvgjVeoCcFAQwpvk34Yh7SI8MlhtTzHWxYY3Z5\niRGuMILYhmCRMOeWYURll8YYnLEIuZTIfDfGedI8j3cs5uAcpTVRJBbKJNZYnAg9KFeyEX3ZKzLW\n4q1d6GLOK0uLD3mwFKZ2fo5CLZe4gKIUtV5aeXmKosBrvagwhJQI53Dek+WmfKzHOQFKhV16mTSl\ngCLPiaREKk2eZ0GA4dvY4d4HHql3MDMW7UtzYMfCLHse1hqEW5oGe+tCCa3FUqSWIKBdWENhDB/+\nFz/CRz78I7zxxk2k9hwe7fPmrdcBqG7NWGk2GM1OsRLWdjYw3tDvDUjilGHJ0Tg+PEaScv3qFdrX\n68SR5Pi4RxJ32X3Yp7uywaXNUHG98nqQmPuBp97HdmuTl1/8B7784jeYzmY89cgjPPHYBQA67Yj1\nlZTVbkajZnF5xmRgyU3M6NBw9GA3vI/REd7PmE5OSWNJPsvJnaK7vkOnu0WUVpcITekhcuSyX2rB\nTsP77S3ZGaWfelrl8tYFKukGSbJGo76OVQJihXATpuVSKLBMiowCR7VRYaWUgry8dYFmXOX48CEH\nR2EDkk0KBr1j8tmUC1vbpBVIa4LCZVgPSo0AWO3WeOT6U4hRzuuv3mRv70XywuNwbO1sklRDe/vo\ntMfR6YDcVbl7+yat7ha11gpJWmU6c7Taq7x5O7xHo9GMOEnROgEPpgi0qkhqpFAUNrwg5z1JkuC8\nxeQZWsTl+nWLNqq3Jri5WhV4zDJ0SxAi8D1LcPocbBdQ7OG7he6QCxh04ZacTCUEQn8XlaF3WZwn\nzfN4x2Ke+II4z5mE4IOHZRRFJXrWByk560FKnDF4lvSUeU/T4pDlHEdJjUBRFPPWp0QIEW4ezi66\nnNZZrDELtKkgXBRnTXsXTVIXSOG6dLOQMiCAffk7IQRSqaVBNpSJXLLQVCl360F6L7TS5jcdrZeS\ngV7IUL1Sir4rjUx0eDyQ5zlxHNOq16nXarz66qsUZsZx75Cj3h6t1VBJ1TckReGYFRnrG+sY5/A+\nuH7cvXNEJQltz8s7l3j88SeRKN7q7TPs93Azw87aJu998mlu37nL117/FgBXrjwCQDaa8b/98R8Q\nm4ynHnuS9c1VWq0IY8Ls0+WneFtlOta4XJKohI3VLqPTGXsPjzDl5z8e9XA2o5JqTo5OkEJz5dLj\ndLs7JJUmOq4sIIvWG7zMyKdDhJNoFEIossIxG46olJuk69cfZbW9Rhy1adQ3yGaKiQ63/azImUxD\n1TyZDTk6OUJEEa3WCq1W8M7c393D9vscTnr056Wmizg82KdRa7K+tsrKShO04fjkmMF4SiRCMtzY\nvMws9+SjMV5qeqOMOE2pNRvUuh3u7od56o033qQ/nuGijKtPPMP6+gWclxwen7C9c4kXvvYtesOA\nyI3TSmjxu0AhUVKFNeUszi83nFiPk/ONmAzzcSHL9T4XBAncaOsBqcpuTMAQWO9QUqG8D+MA5mIJ\ngRY2X9nWBeN4qdVSncuHzo5HocW3Tz/fPXGeNM/jHQ9X7oDlAhCztB0CAlz+jLW8Ugp39tcWEAE0\nI8XS7SG4jS0nhEopnHNBkg8JItwg5tVkCBHmhS78zluLxSOFxEmJdAXOh2apcwopBc66hXWZFGKp\nzVk+nZACpTTeWrTWlBij8rWqheUWMmjWhhrb42WYR2k0hTcUmVkq/qRV8PD88++j3z+l0d7m1Tdu\nMByfIhSsrYX5o1UZWkvarQbjyRSdVDg+6TMa5Vy9dJ3NjS0AtjYucLB3yI0br/H63hHbmzv82H/3\nSY4f7vHl//gNLl2+wE986jMAnJyEluGf/7s/45nHr7CzssHqWkyzE1OrJKTJxfLztIzHPVyRkxWW\n4axHrCeMh1OmZoQuOZFx2kWQk+dDqq11trcucvHCNbSqkxVgEUxL7b7MZihRUIwy8kmBMyCsRPuI\nRKRsbYZ54ZXty1SSNs5VUYVFFQ6rHFk2ZDw45fQkVKTD0THD3hGd9U02V1dZ7ZS0msIxHIw4GDzk\nZBha2NW4QhTD9s4mly9fZjabMBhOsYXm5HCCycLt9JWXbuGzCavtOkLEtNdXMA6iWo27e4ccl/Nm\nFWvqK+vsXHqUZ5/5AC+88HV2NrYRMuL27fvcvnsHrcKmpjAGJ1QQMRASJW0A7jhTupfM55UO60Pr\nVCuxAL4FmvGS1uUIes0hmZYWdd6HTaoErF2oZAkCuMdbgycoWqlvv0YJHRVjwwb3HAh0Hufx/Ygz\nF51bCossLkbnPTiDsJRiBQHpI8RS3cR5MM7gJSAkYqG+U6oBnbl4rQ3VoECdqSJLFZ/yWwlIX6ql\nuCCUbl2Q8ImlJEcupOzOIlmDtVhoqWqpFi1aodSCx4YIFbUnfDXO4aVc2Jd5Gf7jZcDyOlGCpaQI\nSN7C0Cr9SZ2FZ559GmMKuistXnnlHxiMD6m3a0QVSS5CkumPZqytrjGZzPAiZffOEZtb2zzz1GUa\n9Q5xFG7KL37l67z88rfodNf48Y/+j1y5dJm//au/QhrDv/kf/g39wQl/81f/CYDDwyP4NfiJT/1L\nRgeHbK/Wee79K+hkwnTssaasxKkRizreQb/fAzFmmo85Gh5SqSmqrXDsavsKkSo4OHhArZpw4eJl\n0kqDWe4x3pHlGeMstD6H0z7WjKmaHO8EphBIq2k3t7iwvs1oFBLS3Tt7aHWKlk2UbCBIyVZS+r19\npv19ZqMwf5wNT6hpxWarxUq7xWQYjnPt+qO89g9fZ+9oyvp2EIqoxk0msae7tk6/N+b45JCDw136\nwxG9/pjVtbBZGA776FSS1BvMZo7WSoODw0O6a2s02k1ev3kDgNPekOPeiPe8d5WDoz7N1iobWzvc\nfOset+/dIs8hrc2BXy6szbnaj7el7rAMVaZfdl5UOccUhLXnRSlxN1+HEpQLICFvobAGWxhUpIl1\nEOdwQuMWYlr+zFBULI7jncWYfHEdKymWfOjvopP8bonzpHke71jIb9upnvlNmAPakKyEDzcFL1TZ\nKhLY+QVt3cK1BML8xTqPKhWC5tqvUmiKwoSEvFTWKxWBzjiH+IBIVOUTSiVQ3qOERyqIPOTljcGe\nmauqudOJdxi/fF3WW6wLwu7GeyTh+9zaoAAk9LKdFkCMQU3Ie7zwGCHQeIT1NOp1bOnlubW1hRDQ\nbNa4ees1jvr7XHn8AhMzwKsCHYeqYiW+xHAypZhBkiQ88/T7WOmuUK83OTk+5c/+4j8C0Bud8mOf\n/BRXLl/hm6/d4oU7b/Gh9z1HLATf/NqL9AYn1CvhdrHznuBZ2agpWpsd8lGPr3/1VZotQbdzgTQO\nNBahJJIKhYXCzJjMxhz3TvACrl7eoVLbACCJusSxBZ8zGQ+4d/8ekTokimpoFeOlxRZhrjgZ7tHv\nH5P6iJ2ti3TaLbLRBGsyCgu1kh4ymQyYZhnWHCPlhHq9y/HxCZPREcXwCD8NtA8/nbC+ssq17S2Y\nznBZABy9euMmR/0hrZU6aTW0ui/sPEYxlbx56x6z8QwhHScnB0gFOzs7pKUKU7vdJY013hu819y6\ndQ+lYzY3NumPB/R6vXL9CVZaKzz37Pv46gvfYnt9h2mWMRiNefDgAWkakeV5ua4FWoV1PKcxgUOJ\nkCRtOW1U5YbSeVfuRH0oQu2Z2Xk5x5wbVnvnCIJB84oztGmX/JLw/yocAF+CgJzUmGK2NEYvE6ko\nN7Dv1jhPmufxjoVzy1aqUpxR0bGhrcnbk6oQwSoM53DmjIG1koESgn+bmbQUIgB4vkvMEasq0lhn\nmG+rnXcolnQP6YKyioTQsnIGJUu+27wIIMw1518ddpGHC2vxCowLFaYTElnCEJVSeKEXLi1zc2AV\nOsdhtus9WkckEUxHYy5cCCCbSpTSbbV5/dVXqLVjHt28Si87YsaYTreOLhGs00kVYwouXXmKVrPJ\nancdgeClb77MV194kWeefA8AP/uxn+XBwwd87Wvf4JHHL7LavsSdm6/ROzxk1B8wzad0q6HlO5cf\nnY5PaemIOPVU4jXcpODBaY+4El58vWmwTjLLC4bTEf1RD53Wufro06ytr1Dk5WfgHPlsShopptYw\nm4xxOiVzQ4QSzLIxkyJ4rmZFn1h6Oqs7jAuDG2fU0hYVKfE+YzgKbVehK0hVMJ1mWDfBG8XEGsCA\nmxHLcp1I6FRihvv7RLU2k1l4cSeDHplzNOttuhtXAKg2NhmaDK1HRLFiNDwmTVM63SbXrl1iOApt\nXK0TrPVMx2G97j3c4/HHn6KaVPjWyy9TUeGzyR185EM/wunBCdppVtqr/O1//hsm0wnjyRiLQped\nAE+YbQthy7XpUYARBkR6xpkkdDysc3hTLABUwVHgzAXgAtpVSInWS9WreTLWggA+g9DKXaXCAAAg\nAElEQVQC8cH03ElFZiyOMAtVSi9Q7wLxbs6Vi/hn8BLP4zzO4zzO4zz+aeK80jyP/wZCBO5XGd77\nMM+TovS8LCtSSgcU58jLthVSkEQRToAxRQDvKIFWGufEwhVk3r+VUmKdxXm7qOqCQEp4nCy1ZwUC\nKeY6QaHlZa3BW7NwMkEEkApSEfCHoUKcV5VA6ZepkNKXovOAE2grsVLi0RSl9ZS1Fi9lOZsNrWel\nIMtm1JRge3ODWiUoxFy+fIl7d+/SaNTprjU5Gu8xmQ15/Llr3Nl9AyWCgHeRdXjssfeQRDGNWoPR\nYMZffukvKazhp/71/0S3JNrfvHGLSiXl/T/4Ae7cfZGvv/ilIH4/K4ikoFKJGPQPyvcoIExn2YBO\n3EYrC9kq0iVoO8SVXMnJZEDmxszMlKm1TOyUVrLJNE+5c99SdntJOMLkEyQZifZUpEZ5T15kFHnB\nuHdA7kKl2ehoas0W1BrU0ga1KOjB5uMZs8zgSgsxpGAynTIyU7wPhtgjb4lsxrR3ynq1bCniyfsD\nMhETJzWm4zDTrLc6WA+11g6r64FXmU0CD3Rz+zrHhw+ZTIZUU8X6epfJ9IRKLRw7TSWzsWc6cLz0\n0sustNtc3rnAyeExg+MeSenZWa1WeezyNV788itEusPu3YccHh1y/8FDVBSVZzfnD4c5fFEYtAwe\nmHiHMTlWaBZiHVIt1pkRYIxDzccUall1+lIV6OyIRApR+tcGmtf8N4aSd7kQBwlCG0qlCElQ1eJt\ntrDnPM3zOI/vR/gFWCYruWHhe+0SfAQFDi0CBxLCXCe3RXBSKP9Wq+BdKUq6iVJ5EKT2S7H28LcS\nqVQp3SeQPghfC6sAswA9zFusQVggEEVUeALwYWYUlSjEoOAX2rfOWLzzSKlIhMItRAgCrSUgayXO\n+XDT8b6UBzQot0zoOEclSsmzPLRtjUTFFUzaoLK6wZVrAWxy/96bbF/uUG+k3H/4FiYf8fyzz3Pr\n7h16p7CyFgBDjz36FJVahSStcOPm67z41Rd49LHH+OAPvp/jvV1u3Qn2XE89/gi3Xn+dv/uLryBd\nj5U0phKnpN2Y0WBMYSzd0uotLRNyNI0wCNKohkskXoU299yTctAb4sixrkBFMdrA6e4e/cMBOq6x\n3gozQFUMcN4SxYJarUIURVjnSGtVYuuYzcZsNcOcdGtzBS8lrrJGnnvyYkq/PyHLZtRTSZKEDzLP\nCk4Pj8jzgkq1ySjP6KyvQjGksdJC5WGmWW1VWFlfY2XjOuNMUa2HxHe8f49up8bTFy4yPg0JezKc\nkOqYw4MHPNi9x2w2or26jfUx03GOs3O7Osnh/oCTwzHjseH9738PXgj+4R9eotZo0e6Ejcosgz//\nD3/Dw4d96rUxIk446I+5t3tMvVEnTRKGw2G5NjxpnFL4LIDNghRVmNH7pRdsyJ0Bv621wBRhbQuh\nS8s8QBhQHmGiMN70pTWBKFWvvCU/g1b3pdyktQYSgSlnnMa5cG2WrW4lwIqAOP/20cq7Kc6T5nm8\nYzFPVIYZkYfIhfmN9gpbWLy2AVEq5QKNaq0nN8USaCAkzgTxAGcNiCygBudohzmNxTkoid4giERw\nA/FFQLDOn997EYBF0ge5Pko0YWnwLJUKdBUAG5wjPAJvDRJJEsd47xY3HWEd3gQEI0IitURojZhX\nwHMyOUF8IVIJNsuJEAiV0qjXOeyNuHD1Mhcfv8rB8T0ALj2yw2iwz+hol+5qjXii+Ys/+wpRrcZH\nfvQnSUuJuqSRMM2nfPHPv4hV8PF/9eNU6gkPT+7R7VZIS0+0L/3f/zsyL9jorrDduYpSCh1F9EdD\nCjmh0+5QSUOSi8uZ3JWNa6x215gMpwz0IRPfZzKYLisUa8knBVJIus0GUTUlNxlxNWY0PeVk/yEA\nzShGaAUuxSSSuBISV0HYcERRlVoa5qmp6DCdTBmdHkCccDqeMswLklTjhESVBqt+NqOpEzIb4XJN\nXdeJ85hmrUPOiP2TuwB0Lm2ydukCo6lEVFqQT8r1knNhcwPTO2HWC+Cgfu8QpwS5M0yyY2qNFqtb\nOxzuHZOoKrNxeF9e/eabOKeIkyo/8uGP8trrL3NweMhkNuaJnYvUWmEDcPf12+yf5LQ6W1DVnI6G\n3Lx9H11JQWuyWbFYa2mSgvGlw4jFzYUurCQo6M07Ne4M32kZ3pslTavkCTvrA0e6/HHhPPgCHUfl\nVVI+XCfBVg8C5STyeOcx3qKFWiRI75fiB+pdPPk7T5rn8Y7FnDXmLUilUUmoYFwRkp5WwYjZWIdw\nEilkCbOPFuLT3jt82WIKrVeBkAopgvXWPIwDjSkdNCU+7Jcx1uB1QObOo0x3AWFY+ls6Hx579p7k\nhcQ7T+5s0L1VpRmwJPDdCC1mhWLZrArHX9zijMOWreb533jvKIwlTVOG/R5b62s8c3mVt175Gh/8\nwfcCcHK6R2E8Mm7w4jdv8XD/iB/4oQ/w9Hvfh9cpoqzOd+/f4T9//Wtcf+QaH/jQD3L7zi06okY9\nrfG1v/5beoeBaL+z0uWpp55hpd2mIQRKSe7eu0c+mXD1yjVanc5Cx7fdClzG7oV1stxQJJ5s4sgy\nj8sVdhZej8lykighTWOyfEK7W6fW6tIfnTLJMpjbfdVbrKytktaqyEgjhCCKNWmSMhkNyCLFQSmw\nfuvma8RRTLW1QtpoUxQOWxTMnMVMCvpZSHrFZEQkJUiJF5JWp0sljUninLtvHS00dy9dfoTJOKOw\nmtlsyMHh0WINvHnrDsXshCgqLczSmFqrgbKGVmeV1bUNarU61z7wCN/8xss8eHAfgLSSYI3i2vVH\nWFnpcuXKVU77PZ689jTbFy9wcBSq3KtXr2J8QhI32dy+zP/xf/5fjIZD6pUa3jiyLEOVmzlnHHmR\no6VCSoUrTDhJJZBn1m6oFB3gy4mEPMPnmot0sJTDO5PcpHd4J8JG0PulfrIIcpK4IHgghQqi7N5i\nnCGae7sGlQ9irfDmu2Tud0mcJ83zeMfCltJfQioskmI+G3GunL+4heCBL4ncEEQQ5hQT50vovBBh\n1yuShe6msWdFBhSZM0gvUbhgsusdzhYUblmhlJYn+Hly9A6pNZEQ6Ehj57wQSim8ADZEeIfHM8tn\nQYrvjNqRmAseKIJ3obXhdQkQKjilACgdBBmKwpJWYsbDCStrbT70vmfJh/s8trPKyf4DAIbZlFFW\n8Hd/8zXiepMP/eiP8fiz78GgMF5y67XXAJgN7vGxj/wLmo06h2+9RR3Pa19+gRuvvsTF7U0+9sEP\nAbC9sUarUccWBWmWcXR0hBLwxGOPsXFhBydVqERgUb0P7RjrIVc506zATENrMp+WVIbCUWvWuXxp\nG+cyKrWI8bTHwf4dao2Y7cvXAOhUdojiCC88QpW+o96QzcY4W4R1Um6SkkpMo1oniiL6p6fEzQ61\ntMJpv4fwBbqcD0cywlpLWmvQXtmi2ujgTMFsfIDUVXQcnu/u/X0yI5gVCbtHE1RZRa+tr3N0sId3\niqQeKuzNC9s0Wy1u3X2LSrXJxsY2nc4qr752g0azxfpqEIq4/dZtJiPDo488hnU5d+45cmN45pn3\n8sqNNzk8CpSTH/nwj/JX/+HvqNVy7t4/4MG9h1QrNayzGGtJ0yT4vgLj0ZgoidBKL0UFXNBaDt2R\nOefKgVdhPl5iuikNDJaiW+Xmrgwl5lJ4ChQYW4BbGijoSEMRQLTGGZy0REKVLd0zspIIiiLHGsu7\nGWN6njTP4x0LX97gtIzwTjArW5YRYY7ii4xIx6VJNTgrKe1yQ8KilOBzpnRmkEgUhbXkhQ27bhlA\nFzoSUIRZjxCB2oF3oIJQ/Dw5lzruQY9TCrIsJ5YSncQB9IBd3KCcs0hUsO7yHmcsTjqcc0sbpnmb\nuLzPCXQw/xUC6y3eiYUZt80dUaLIc4Nz0GxX2djoMugdUfMzkmqTqLT8evkbd/j7V29w9alH+cBH\nPsKVRx7FCcnR3i4vfPWrvOfJJwD4wHMXMVnG/v07mMmYN197lQjLT3zkX9LuNKg3Q0LoDXpkkwHt\nbpfCFpz0T0FICldw++4dolp1gfQYTkI1t39yiFaa6WSCnU0YnZ4yGU+o1wJYaWd7m+2tdRr1CnHS\nwLgJe/unrHWbrG928aUIwmAwIYolUkniRCPV/DN1DAenHO3vk5Rt5M3NTappBU1MqxtxOimYTnPS\npAY2C5QkYDYakMYJUZxSWIdQEQrPLDNsbF5A+FDt3bl3h0Z7DeIqKtHU60EKbzyZkaTQ7lzgwqUn\nAajWU3KTs7q+TZ7nJEmVF77yVZIopbJaJy47JePRhM3NS6RphYe7J9x/sMfHP/Hf88prb/DqjTf4\n2Md/PDxumgOKu/fvs//wmKwogqydCPQPU+RBMQqIkgghBMZblJ+LabhAqfJB+DGsX7GgU4WJfNj9\nnaVe2XL2aoxFEjo14oz8o5IqaD+L5caP8ghaabSixCBIhLcLA2ypNEoqjC2I1bL6fbfFedI8j3cs\nFKEicV4gZYyKSq6kDYkrKnfVzvqFeFDw/gOlo8XziBIHIaQKu1yvSgTqcnftTOmeYixBaiAgUxVQ\nyOV8VfozO3IR/uO8Iy+KciZkg3A7YKxHC4GQFl8EWbOoPK+53ZfWAdnrvMU4RwREQmG8xeUGUyZ8\nCNgmbx1KBHTjxWuXyIscpQWrKxtMneMv//pFAO4c9Hj6/c/zwY98lPb6OsPJjFdeeYlsOuRffeLD\nTCdBW/Xw9IA7t25xsrdLcXpKt1bj2s5FZv1jbh88CDsUoNZps7GzxWH/BD2bohsJdx/s8sr9t2i0\nu0H7tLwxzyvjw92HzKZTtFKofIbJpnTaTS5fDFzSrc1tGrUazuZUKzF5AbW0QT6bcPNbrzOdhttP\nrXKRzc01qo0qiPLzsTnT6YhB7xTv3UIJaWV1hVhFiEIwteDtDOkFrXoDLZtQelqudjokUYwXGpXW\nqDdqTAaWonBUajXmVjj1xipeRgipqDXrFEXYyBUWmpU2a1sX6axvhp/lU3DQbHbY3d3jpZdeoX86\n4PLFy3Q6qwx6AXnbH4746Eef4uDggC//3Vc46Y959bWbvHrjFp/48R+j1gzz2Vdfu0WUVLlx4yVw\nYeNmXdi1RTqiyAtkmZDiOMaVcnem9IAVgDcGLfSZKjJUlTKosC+S67fPOb0TaL1U0HKlycFc6jFc\na+XGzziMswgkOg5DjgD2ASHU4nHOBp1brfW5Ndh5/POOGzdu8Au/8Av83M/9HD/zMz/D7u4uv/qr\nv4oxBq01v/3bv83a2hpPP/00zz///OLv/uiP/mjRuvluEc27TNYjtSAqb8ZGBHCMjpJQkRUGY5fJ\npSjyhZSdEBLvXTl7LEhkDAi0VBj8wujae1+2UF3p0+mwbtFdnY/XKB+M+X/Ye7NY27b0ru83xpj9\nXP3a/eluW/dW3aoyhct22UTBFEI4BmyQHEuOyrJQeAqISIlcip9A4SVEPFhCVh4swQNyEgWSBwuk\nmASIwdgul32ruX172n3O7le/ZjeaPIy51jlVgAXIToXL/qR7977rrjXnWnPPNb7xfd+/sQbdONIk\nwT3j9yCUeoYe49GyzjpPG3EgIq9HuyGSO2tx0htua9OQRAkYj6QVUiAMWwpC1VTEcULZFBwc7hHG\nioOjA27eusnHH37Ib3ztdZaNv57f98Pfz5d/7M9S4Xh0/IjHx3cZ9hK+/7VPs756wNWFR8W+/uE7\n1OsV3/fiy9hOTHl1xfnZI5I4xJiG4aFX5ekOexROszQ1uIrKVATDDv1OSl0bynXBxr5bpf5naCxR\nEGCamtXqgt1xh1defY5+d9h+9oaqXhOqkPW6plxXBCKlWkG9VowGuwD0BrvknQ7WVGgcSRxQa816\nMcdZze7uLvv7rXpQklCtC/S85HxeUGhB1hmRZR2UgCj3YLI0VlxdXhAmEZ1uh7IumU2v/LV2NRft\nXLFqHGHg1YBH4zHFaiPODlnaZzzao25t49ZFidENx48ecv/Bfc5PT/n0p1/jzu3nydIODx94R5Lu\nYMjvfP113nnzXRCSl1/7NMcnT/hzP/nnGe0f8NGHHoS0XFV8+423CMOQpnIEKvSUKq0JVECYBH6O\nDi1NyuK023ZbNhrF2rh/xVlHQst32rRon1E2aFHlQni4jrEGIXzybJxDt0pBVj2dsfvq1WCMaMcX\nfsQQheFWoxbnBdt9e/16pnkd/5HGer3mb/yNv8EP//APbx/7xV/8RX76p3+aH//xH+dXfuVX+Lt/\n9+/y1a9+lU6nw9/7e3/v3/rYndy3s6RT6MaywfEpITHO0VTVdtf6tBrzvph6Yyu2/X/eMswJicNb\nhTnYVoXCesi8c5ZACkSoCPBf/urZNyV8W1aisFa3qkUeSUur4blxf3BIr9qD9R6brb6ns2qrTGRx\nCKkQ1hJEEQJLUdTEaUKgFE1Tbxe8MA5Yrkp6/R6379yhP+ozHo9568OP+No33qSWAX/mp38SgMM7\nL7CsSh4cPyCQlj/y2ssou+Kjt36Hd771Hl0PniXodDk6eI6Ghrou0K5mXTmSrM/e4SG7N/wczoQh\nF4sZlbUU5cLPxITCKYkLFZGSBO06OBr4pDjOMlaTCaayZMOMTi9guThjufAJKQpz0riLFCFNpbGm\noaoswibk8Ygk8m9yvDNmPOphbYMUhsX8ktnkkqpYE8UhNw4OSTPf8q2q2ssQ1hVFsSbpjMg6HYIo\nJotDbIt+ff/dt3HW8NzLLxEFglWxwuiCThazmM69xRaQ5hknk3NcXROm2ZYqpETIwe5NkiTh/mOf\nDGeTCednT7i4vKTf6bC3s8+nX/mMV2xKMrLWo/TR429iyhOUVRzduc2X/8Sf4v179zi7mvD48n1m\nM/8e3/voHtP50tt3tUAb67zUo/kunqN1FqMNMpBIEeBaYX+hRAste5o0hWCbtNyGP/Vd4Vps0Oa7\no4QgTvyGwysFCT/rBLwGUft+nPOPb1DpwGZ+aZzBad1KXV7PNK/jP9KIoohf/uVf5pd/+Ze3j/21\nv/bXiNv5zXA45K233vr3OvZzt/2CLbFIodCN3+U7BVEY4BpJrTWBUp7j6LyHpHdn+M4vZRSEiCCk\nLk1LVRO4Z8AIHi7v6SMeGCvaBNma624S4WY2KgRhHD51YBEKh/BJcbN+CIlxrcl0ELSCBMb7D7a1\nqXEO2fJKg0BgNQQhSOGoTQPSolvXFG00Tln+yPd/P3Ea0+v1eP+Du/zz3/xN4sGYn/m5/4KjW7cB\neHJyyumju3S7Gc/fOeKdt36P9976PYrZBaN+Qhr7r7aJE4xpKHSN1iUqgCiOObh9xP7BPi7yVe7J\n1YTFck3jLIWpEXj3FmElaZzTjXL2h74yjNvPNur0cYs1B4c3ufFSh1l9ycmTK6aTWXuBYowOkDIi\nECGBlBhTsV4UjIZ9brWSgPkgx9iGpikQrqEsVkwnV9RVxfPPfZZer4doZ9OOkOnlgtOTJyxry+5g\nj7yT4/Dz7vncg2yUdAyGfWyzBldRV3Oi0HJx8YRIws6GK6lL4iQhyGOMqbdOIFnchVrx/rvv8vq3\n3wRg2Oszm03J0xRnDHmSsjvaQYUJ9x8c8/a7HwCwe3iDTpDz4KP7/NCXvsT51YTf+trXSXt9bt5+\ngTffvgvA48dnIEPKskXZSIluk6aUrSH6hrokBFEceeSsa03XrQGhCEXwzPjCjwKE3djtPZswn1Z/\nQkIYBi0mwHOTNxWmVGqrpcz2nt60gw0iCAiEam31rO+sANpYmhaX8G/Wlf4PP4T7JNfR1/EHFn/7\nb/9thsMhX/nKV7aPGWP4uZ/7Of7yX/7L/PAP/zBf+MIX+PKXv8zx8TF/+k//af7iX/yLv+8x7997\njzvPvfKH/dav4zqu4//jODwc8uTJ5Hv9Nv5Q4rrSvI5/rzDG8NWvfpUvfelL29btV7/6VX7iJ34C\nIQRf+cpX+OIXv8jnPve5f+Mx/sf//r/kl/7Ob/DS7Q6oECM3rgs1QRChCNpW09PXOJxHrT5DRdHG\nEASKQCnK9YaE5itNI/51sx7jdX+s9gdPwqebcOul8wInUKI9l1Ktf6BCY7CtAoshwHi6N2HokYNN\nVSGDAGMM779/xfMvDUB6FRUVSCIRoBxUjaZuSgIVeOk8YF2uee1zn+O1z34WpOCdd9/hN37963zf\nD77Gn/xzP0kQBDx8+LC9EIajG/s8vPcx3/rW77FcnKB1xdFBn0YXDAat1J0cYquSThKwnJyTKvhj\nP/JD9DsdyqrmonXcWFUNTgTMlyusrAmiAGMkyoUMuyNG3QH91u0jsJb/9r/+O/xPv/izXJ09od/J\nscGMeTmlqSVN0/IBRUocdtGN89QJ01Csp3Q7KS8+f5Os59uZ68bTS0xTIJxmenXO1fkZo/EOr7zy\nGaSKmbeelvPFmo/e/wBdTLj14qvs3/4UKu1TViXFYo4pvRtKQMl0csbe0QG90Q4ffvwxer2gqWpu\nHB5tK6EnFyckg4ykl3Hv0QP2Rrv8wn/zW/zS//Bljj+4y5PFAtsKkh/uH7KYzdgZ73B6esaP/Cd/\nHGTIW+9+wEcfP+T289795fbzL/D1X/9tjsYHvPZ9n+cbb73Nk8srBnsHrIqGN97ydKDTkwsiFVMX\nFUmY+KpSGp5F0WzM2bfYNOU5zBvOrEIgmvCZl/g55gac4wftT4UKHj+84PDWCJwjiRN0Y9FN/R1i\nBg6+c0bamsVGYeSBaVKhlKJuao9af8an0+MLzL9OX+ETE9dJ8zr+veIXfuEXuHPnDn/lr/yV7WM/\n8zM/s/39S1/6Eu+///7vmzS7LWhDtnzJqHVVsBKM0wgUQRBgtaZpaoIg3NJPNiok1hlw1ttsOVDK\nu51s1HyeNmgVTaO3fBLrDAEKIfBtyA3IBY+gVVJ4/U2hWrslBVIQAtq0FBjVOjt4BzOsbf06t8Rx\n7zFoFDht0VaAbQhwrWxcAEjKxvNVx3s7vPKZT9MfDfmN3/wav/VbX+eP/6k/xg/80A949Z/5nP2x\nFxaoyxX/7B/9KvPFGUVVkOYBo90dZKQY9W9wceGNorvGo5Pr5YosSrhxuEOSJEznU5pa0xQtV1Y7\nlHTkIqapGyIZoFRElvTYHR/QyfskUbS9RgBrZ2hCycenj7F6jbWaRkvi1lw6SWLqxtMjup0MXIVF\n0ulK1tU5J3e9GMCqkUQB5HGIMxXFeknY0ngePXiICjPmCz95Xq0rqtrS6fUY7+4RpymXixmrZUEo\nDFGLwJ5dXnH65CG7+wMe3H2X1WJGUyz5zMuvsl5V3G83H6O9XbI0Y7FeUVcrup3nANjf2WfxeEbU\nzUlbub/z0zOSQDDqdVgvlty/e5fHT84pGscrr36avSMvcXh8ds5ssWSnU/Pbv/018vEOQZSggpjX\nv/U6J2f+bxOIiLoySBEQBQmNq1uJSOC7u5ut640UxqO423tdSIUtm6eUqWdMp4FnkqcfCQCI9qeu\nNdpu6CIttSUIPAqWp4naYPy81fifXm/W/04gthxaf2xvbG3Ed85kP0lxnTSv4985fvVXf5UwDPmr\nf/Wvbh/7+OOP+aVf+iX+1t/6WxhjeP311/mxH/ux3/c4rkW2DvsjpsvZ1nMqiCzSCKz1wgUeKdty\nxuwGObjRa1Uo6e29jLF+1tmiBq1ruZp4wI+vUNtb3rUmzwiwBtGqmmzmpbL1EwyFaCG2XhVo450J\nYIRftIQE0+itzJ5zbBceaMUNlJ8bGXQLq/BCC6UuyTq+KvyjX/wi+4cH/P1/8H9w96NH/Pif/TN8\n5rXXWK2ndDNDd5Tw9re/BsDxg48py4pAGnb6GUGeEaQdCgxOJixla/B8taLX79A4S56FZHHC/Xv3\niEOFcBLl2g2A9vOqfpxRVxWpTYiSDoPePvvjI5wMkMGmIm7pLMsZMpAEwy7FhaBZ1zipkPiKVKke\ncZoQhoIg0AgM1gXMlsc8PD6lMn4uHmf7dLKISOUEwrK3MyZPUwIV0Wg4fnJF2aK1ZJBS15p03KEx\nhg8++pBZ0RCoGL2ekYf+HmrWc8Bw7+P3mC4X3HnheQaHfYpqzvnJOaallqRJxGg4YHJ8xWAw2HJM\n14s1nbhHECw5fdIKSkxmfPGLP8DhwQ2mVzOK5YI8y+hEOQcHR8xWvhpeFTWj8Q5Hh4dUQjIvS+48\n9zz/5z/9dU7Pz4nDrL0vAhwG5RRlWaKE9GIYbWWH4DtGkjIQbTZ0ILyUe0Ar7bgFyj19gTedfoZk\nuaFVtfNS3WiscYRhi9o1BikF1npVoWeR7wbjaScbOcs22T6LjdfWbBOyEP9m1Px/6HGdNK/j9403\n33yTv/k3/ybHx8cEQcCv/dqvcXl5SRzH/OzP/iwAL774In/9r/91Dg4O+Kmf+imklHz5y1/m85//\n/O97bGt9lXN0c8Diwyn1BohgAqQMEFJijBeFDqL2Nc61u+6WcoJHy3o0n0NbLybghKDRlqd+IwKp\nAo9yNQZjPf8zCgLCpyYRSCmx1niAhG5QgTe+VlJ6fprVyE21KyKc83B+h9g6mmjdbD+LcRCqCIdB\nO0iUJBAGVxq0M4z6I37oR34EgBu3n+d//pX/jcv5nD/3n/8kL7z0PPNiTn8Qc3r/Q9745rdYLnzC\nipUmULC3v0NlHYXRFOslw8MDHlxcbN1Q8gTfiktial2xWC65eeOIYl1SFRVae/BVKAOkslhWdDNL\noEo6WYfxICEKHOu6Yta2SJdrz0cM4pimWVM2NbXVZN0ucZKiWmSqVI44Duj3M3SzwtkK6RKWc+8U\ns9OicDu9Aw4PdsnjiKpYYbWm3+1RVQ2LyYIgThGtetR8OSfrdbh/8ognsxnd4QHLVY1Sin4WYE3R\n3lsF43GXTq/Liy+9SKc/4PzkMVcXVzTacOPmkb/3bhyxrArWyzWdboewBRydX11R1w2XVxdMWzTw\na5/5LHsHR1xezUiTjNVkhlQhz92+w3pdkLbel90oxnVyTi7P6I526A2G/MN//JaEhekAACAASURB\nVE+4f/eYJOvi2mVXa41CgYSyKsnSBGE96Mz6GwzVQpa1dywHqbBaY4zXmvCtVPmUU+lo5xlehENI\n30NpvQDaawMb4ooVDuMM1hgv6eiMP4h8aqcpgEBuXDzZ/qMC1ZogmKdPbLnN8rsr5U9QXCfN6/h9\n47Of/ey/NY3k53/+5/+djr1e+jbVrTspl/OQ8wv/rdYuQxhFQwXOIJTyDgrW4Kz2KikbnVbjFx8p\nFXGU0OiKpqoJ4xjp3FZyzLUCJ7r22npJktNUGqECtJ6j28ojyxJqZ8mzFKOhNBolJELqDb0NpVru\nZy3RVhAGQbvbdzjpkwnBxglF+RmfDZEOpFUoUxIYT7X4Uz/248Qtr/Ef/O//iNUc/sJPfYVsGDNp\npoi04l+8/jVm9x+Q5zmv3nkegIvzK5Io8ZJruvaKObZBLi+5nViq1sVDx4eUZokpFty8NebWjRuY\nRrCuDE2jnkoZphrjrogCTayWhJ0+u7d26fct0/kZ84WhrPwCXhQ+MZXLBdBgqwIZ16gspNYFeewr\nzfFoTBI5kqBGW826aFhNK3QZ0+/c4c6dlwHo9/dJ0oTlagVBxGI5Z9nUVFXDurCcXs4IQp/MLuYT\n8m6GyFM6/S79jsSVS24c7FCtZ5SFdwUJVcPRjecYDHYIVMxqWbBYCGoTE3UShvt7ACRZwsnZCbKC\n3f09IuPF4s/WS4qmZr7SZLlPsC4c8s+/9m2qQpOnGZaYcX+X2cUch+DwwHcMnkymIAzZ4Zi7D455\n9527PDmekkcddMnWWk4IiRMGLTSqo6it52da551wVBjQeuxgnUGJiEiGrZqHBhTOgpZmi7JVrf5r\nAAQi2AwxcOZZLLnHAjgFUontBlQGoISX/vDOPm3nZwMscKCFABUStOMH085MAQIV4qzFfJfD0Cct\nrpPmdXzPYrH0FUue57z6yivUzT0ATk9XxFkHtK/6RG0g8ELVSIWS3mILoGlsu354sI1z2i8CVrey\nX616jwYajUJghcQZjTGaMFTEKkVs/RkiAlFjasAKD9DQmro2KKUI4whjfIJ1zpDFKdZqHM4nXuG+\nQ5JMYNF1RSfvo7WmrGvqECoFP/qf/gidgzH/y//69wEojeMv/Vd/CW01s/UlVTnlN7/2T+hkiju3\nb5BnXYqV71P2On26eZdHx8f0en2SLEHFAWknZV0uCIPWo5MGpyuyJGF/f0yahZw8uiSJMxaTKVnq\nq6NYhRTliu6gTy/e4blbz2FcxAfvPWS+tiyWtZ8bA65tAU4mF4ShIwwlSRhjqoY879Lv+eSRxil5\n1qFcLSlWBY8fP6ZYTRmN+hwe7HHQChZomzCbzlkXBUIqJpMZy+WSOEmZzWaURYVxLR3JCRazNaPx\nHgd7B/Q7in5HIq1hOdUI4yvs526/QCfrosuSk8kjLq9OmC8sURgx6u/wqZc/BcDjJ485OTnzkwEn\nOH7knVds4zClZnd3zGrh79M33vg2N45ucPvWPidPzlgXa7Jun7JquHHzDr/2j/8vADr5gPHRHh/d\nPea3f+v19roFSCkJAvUdwDax+Zf1rc5ASqy16Fad5xn1O5wz1Ma/IIgCEAJdN35T2apzSOPpW0/9\nMB1N0yCE3yAAJElCrRtESyuxRuN8idrqO3/nUNVzkf1DDrYlq3W+Yt3ONFsOpxJiq738SYzrpHkd\n37Po5r4iubo8J812uX3zBgDL1QOqRoNQre+t855/2uGcaeeKrYmwDFBJQBBEaF1TGs2gl6OEYjpb\neskxPGjCOG+g67RDJB0CqVFO4qzEbfQ4MQgUVV23C4JfE9I4xwHr2YJoA4iRAqzG1CUqDFDbRcd6\nqysgCgBrKIsZOEUlDS4P+IEf+EGGdw751f/7HxF2/WL2F376zzObXrBeLnnvvW8xWzzhBz//GUaj\nLuenZ1xeXPl2HlAVFcWqJo1T0jjjcP8QFStqXXkJvXanr6IKGTleeeU5AmX56OP3yeMh68Wcbp5h\n/CpMUzheuP0KSSZZTxd8/PGCk9MzrmYL0m6fqmmQLYp0sx7qpvCm31IRhSl1XdNLOxzte9m5JIxZ\nLhZcnp8TBwpdN0ihePH5FxiN+iwXnuQ/nc/RumE6nVKVNZP5nDiKOT+7ZDafMej3yeK0PecEayS9\n5AYHgwN6g4qz83OO7z8kDQYMh74S10WH48s1Vsy5nD5GBCu6+R6HRzc4ONhn3baar84nVOsaKSPO\nz6bMp779bWq4dfN5oCZqZeX+yBeeI027vPnm2wgR8tzLr9Ib7dAVIa+/8Q7dsd8EZEnGN998l2+9\ncw/dQL87Yr5YI5zCaLltXXrATFsdtgCy70hW3/V9sdqB0EgUUZhgJTRVs52xQytW4EAIi0RiXYMQ\nChGI7UbTWs8F1XXzHdB0IQRKPiPJt1Hs8l/B9jlqewNIa7HuKZ8TZzHuKXjukxrXSfM6vmdR1y2p\nv9FUZUEc+2SUpzF1vWpdFqRHCeKJ1E2jcRhEO3ARW03ZGqu9k0a9XmGMJQkC8twvtsY4pAg3XSaC\nIKKpaoIoIos728UjigKyLPfQeiWZL2Y4aymKNeAY7t/AtoAlqy2Nrr2Yu5KEaYB1miAMka0G7eHe\nLnVtuLi4xNmGMA154Y9+jqPnb/Pm+28zPtjlhdbtoywXnD55yO/8y39JN1f86I/+ILdvjTi9OCWQ\nijiIWEw9pSIJYuI4xVrLznBEr5NTNAVlWYC15JmfKyaJQoiEq8kZUSBIk4jVfAomZjn3psoAB7tH\n3Dy8zWJxxZPJnKJcUzeKJMn9Iis1qr3mm5YuzoOZTGMI44CDo31u375FFPlzzydTrs7PWUwmnJcr\nnGm4eXiEM5bHDx+zLPzff7G0lHXJfL5Aa0NVV6T7ByRJxGj0HDu7OxRrX2Fba7h543lu7r6CEJes\nl3PK1Yy6mHF4dJvdgU/YmAHDvuX45G1mkynDPcXezg5xEFGuKx7c81J2zgkCIopCk8YQR16w/TOv\nfJ7FcsUHH37Erdt+M9fp9nn73fdxQchLn/oMyIj5qiHv5ogoI0taO7Ynp3zrrY+IsxxHyPHJlJ3B\niKrSXue1vf+ltSjZCgG01ZwHr/mxghJy48uORBDEIbo1wLTOohvt56JR8DSptcpCmzDWeelAAVWL\n0q6qGhWotpXrk6KUEqG8/KSjpbq4p2C2zW9beE8r8q6c2xaaxvo2sVSG74QIfbLiOmlex/csNtJf\nWRyzXK+4uvK7/LJYooRDo73ijpG+jZpIRJqQRDlxC9gIg4T93UP2dg8wtube2fvMZjNf9eR9xmNv\n+KvrBqVCbt2+Q553mC+WLFcrxuMdup3BdvcfhiGdTofpbIYElssl1mpWqxVVVRNH4VYiLIpC1sWK\nLEuZLiaEkSLLUhxu65bxU3/hJ6gbzUcf3eP+x/doejl3XniJBx99SBJJPvv517j/0T0A3vjgjDe+\n+QavvHiT/+zH/gTdjqQpp0hTE0pBEijioW99CiS6auhkOUkkKZZz5uspFk0SSYKonakKQa/fJwwF\n5WpJ3RQkSUi5bKjrJa+85ClBt2/cwNQl88mEOE5xQmKF8QlSaLp5sG0B1o3//KGSpGFCmnbopTn7\n4x1srXl47GXnpldXzGczcAZdldy+dYMbNw65ujxjvVqyKH3L9WpWUpUFQkq6vT59lXHjxi5xkjIY\nDAnDkEePfdv0RrDLeNihKWeoeM1icsHV+YTRYIcXnn8Bof0maT3XLFdzHj9+SBQlvPD8iyThmOVy\nzeXyktXSV5pKxUiRcLQ/5s7t57Fug6IO+fY33mK8n3KzVS56+PCYx0/OePW1z9NYxZPTcwbDPb7x\n5nus1hX3H3oKzQcf3CdMe5xfrEizmE4nQ1tQYYiprecI0wJabYufkeCMo7EeJKWUQAXBNgHW6Kfe\nrgZcIBHSjwusc9tNn9ja1IHFehCukF5zeVv9eWWsQOI7KRtl5ZY6tQH0tE1ZTAsMQrS/u/a4Xodv\n24pVAC161plPLuXkk9t4vo7ruI7ruI7r+AOO60rzOr5nsbupAhsvCtDJfJVwdBASJhEqlhhjENaS\nxCFJkiCdJAoiui23MU+8KLgzcDWrODo84OjggOlkwuXZBfPLc4CWnyl4eLdhb/+A0d4uCMvV5JT1\nespmgJNlKcYMmM/mKKVI4wQpQl547lOcnJzwzlvvsLfnNVj3dg5YLiMGgx5VtQQMezsjyqokbwXG\no8C/39defYnxoMuiMZw9POHV/UP6/Zxv//bv8M2vvwHA5LLk8597iT/5J77MuNdFyoKmMEwnE6zR\nJIH0CvVAJ++SxSlJErOqVjSmIU0kcZqj3TNI33hImkTgDGESotIhSsDJo8eEOxlR5Ft2x48+IGhB\nVnGmaGigqclTgYoCarNGtOcOn1GjCUTE3uiAfhojMNz9+D5XrbBCGAY0dUFdFfR7XQ4P95jNp8ym\nUwSwXPhWswohCxRhGNHrRXR7PY6OhjgEVbOgKDVN49HAYSR5cvo+/bSDWDcsFxOycMSoN+Ts9Ixq\n7atcXQvWZY0MGp678Sk66T5SROSZQjdzOplHLF9eTUjjLnu7RzRaUBS++v32t95if/+QF1/d53Li\nVZPmyzWvfPo1itIyWZ1jXMi33vqAOMl4+/2PeXJy5i+6kJRlQ97pIwWsq5IgURSrNXmabe3HlPB0\nJYEv0JxoxQictwlrrcv9IRHEUYg2glprmtpgpUE3NUEYbcE53jlPIoS38FEy8L6ZgSBqEchB4CtE\nbayvmlozAuscCt8alg6a70YsiRZpa8FJhWrPua00Ay9IYbR5tkP8iYvrpHkd37NQrdDAoN9lNl+T\nZ94zcW8npaGhP0rJ85SqLKnrmqooWc6XlOWakxM/k+rnPaSMCURI2TQ0ytHUNaEKiKKQqDWr7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wB/2XSUJYryaslpeksSJJFOViwaJYEcUJxaoFalnLwf4BgQxpmprLi0uSNGVnf8R8vmCx9pW4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\nKEzfig+P6QCUEaI3b+5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ToZVGKA0iVJXCPmVYAmihcPR6qjtnD0cAh3l/ZZUpAC+QUgIS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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9ef63f37f0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}
