demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## An example of model inference and visualization\n",
    "#### Prepare the input data and model\n",
    "\n",
    "We generate the cropped images from COCO2017 valiadation set by using the GT human bounding boxes. And we load the model with the COCO pre-trained weights. The models also can be directly loaded from torch hub ([CoLab demo](https://colab.research.google.com/drive/1v2LY_rAZXqexPjiePmqgma4aw-qmRek6?usp=sharing))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading annotations into memory...\n",
      "Done (t=0.19s)\n",
      "creating index...\n",
      "index created!\n",
      ":: conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.downsample.0.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.downsample.1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.downsample.1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.downsample.1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.0.downsample.1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.1.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer1.2.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.downsample.0.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.downsample.1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.downsample.1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.downsample.1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.0.downsample.1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.1.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.2.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer2.3.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.0.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
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      ":: layer3.0.downsample.1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
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      ":: layer3.1.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
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      ":: layer3.3.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.3.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.4.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.conv1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn1.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn1.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn1.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn1.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.conv2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn2.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn2.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn2.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn2.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.conv3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn3.running_mean is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn3.running_var is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn3.weight is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      ":: layer3.5.bn3.bias is loaded from models/pytorch/imagenet/resnet50-19c8e357.pth\n",
      "=> loading model from output/coco/transpose_r/TP_R_256x192_d256_h1024_enc4_mh8/model_best.pth\n",
      "model params:13.363M\n"
     ]
    }
   ],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import os.path as osp\n",
    "import sys\n",
    "import os\n",
    "import torch\n",
    "\n",
    "from visualize import update_config, add_path\n",
    "\n",
    "lib_path = osp.join('lib')\n",
    "add_path(lib_path)\n",
    "\n",
    "import dataset as dataset\n",
    "from config import cfg\n",
    "import models\n",
    "import os\n",
    "import torchvision.transforms as T\n",
    "from utils.utils import collate_fn\n",
    "\n",
    "os.environ['CUDA_VISIBLE_DEVICES'] ='0'\n",
    "file_name = 'experiments/coco/transpose_r/TP_R_256x192_d256_h1024_enc4_mh8.yaml' # choose a yaml file\n",
    "f = open(file_name, 'r')\n",
    "update_config(cfg, file_name)\n",
    "\n",
    "model_name = 'T-R-A4'\n",
    "assert model_name in ['T-R', 'T-H','T-H-L','T-R-A4', 'T-H-A6', 'T-H-A5', 'T-H-A4' ,'T-R-A4-DirectAttention']\n",
    "\n",
    "normalize = T.Normalize(\n",
    "        mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]\n",
    "    )\n",
    "\n",
    "toTensor_normalinze = T.Compose([\n",
    "                            T.ToTensor(),\n",
    "                            normalize,\n",
    "                        ])\n",
    "\n",
    "val_dataset = eval('dataset.'+cfg.DATASET.DATASET)(\n",
    "        cfg, cfg.DATASET.ROOT, cfg.DATASET.TEST_SET, False,\n",
    "        toTensor_normalinze\n",
    "    )\n",
    "\n",
    "val_loader = torch.utils.data.DataLoader(\n",
    "    val_dataset,\n",
    "    batch_size=cfg.TEST.BATCH_SIZE_PER_GPU*len(cfg.GPUS),\n",
    "    shuffle=False,\n",
    "    num_workers=cfg.WORKERS,\n",
    "    pin_memory=True,\n",
    "    collate_fn=collate_fn\n",
    ")\n",
    "\n",
    "\n",
    "device = torch.device('cuda')\n",
    "model = eval('models.'+cfg.MODEL.NAME+'.get_pose_net')(\n",
    "    cfg, is_train=True\n",
    ")\n",
    "\n",
    "if cfg.TEST.MODEL_FILE:\n",
    "    print('=> loading model from {}'.format(cfg.TEST.MODEL_FILE))\n",
    "    model.load_state_dict(torch.load(cfg.TEST.MODEL_FILE), strict=True)\n",
    "else:\n",
    "    raise ValueError(\"please choose one ckpt in cfg.TEST.MODEL_FILE\")\n",
    "\n",
    "model.to(device)\n",
    "print(\"model params:{:.3f}M\".format(sum([p.numel() for p in model.parameters()])/1000**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Obtain the predictions\n",
    "\n",
    "We feed an input sample to the model, get the predicted keypoint heatmaps and further obtain the positions of keypoints. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "from core.inference import get_final_preds\n",
    "from utils import transforms, vis\n",
    "import cv2\n",
    "from utils.utils import get_valid_output\n",
    "from utils.transforms import flip_back\n",
    "from visualize import *\n",
    "\n",
    "model.eval()\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (length, input, pos_mask, target, target_weight, meta) in enumerate(val_loader):\n",
    "        if i != 1:\n",
    "            continue\n",
    "        input = input.cuda()\n",
    "        pos_mask = pos_mask.cuda()\n",
    "        outputs = model(input, pos_mask, length)\n",
    "        if isinstance(outputs, list):\n",
    "            output = outputs[-1]\n",
    "        else:\n",
    "            output = outputs\n",
    "\n",
    "        output = get_valid_output(output, length)\n",
    "\n",
    "        if cfg.TEST.FLIP_TEST:\n",
    "                # this part is ugly, because pytorch has not supported negative index\n",
    "                # input_flipped = model(input[:, :, :, ::-1])\n",
    "                input_flipped = np.flip(input.cpu().numpy(), 3).copy()\n",
    "                pos_mask_flipped = np.flip(pos_mask.cpu().numpy(), 3).copy()\n",
    "\n",
    "                input_flipped = torch.from_numpy(input_flipped).cuda()\n",
    "                pos_mask_flipped = torch.from_numpy(pos_mask_flipped).cuda()\n",
    "\n",
    "                outputs_flipped = model(input_flipped.cuda(), pos_mask_flipped.cuda(), length)\n",
    "\n",
    "                if isinstance(outputs_flipped, list):\n",
    "                    output_flipped = outputs_flipped[-1]\n",
    "                else:\n",
    "                    output_flipped = outputs_flipped\n",
    "\n",
    "                output_flipped = get_valid_output(output_flipped, length)\n",
    "                \n",
    "                output_flipped = flip_back(output_flipped.cpu().numpy(),\n",
    "                                           val_dataset.flip_pairs)\n",
    "                output_flipped = torch.from_numpy(output_flipped.copy()).cuda()\n",
    "\n",
    "                output = (output + output_flipped) * 0.5\n",
    "        \n",
    "        c = meta['center'].numpy()\n",
    "        s = meta['scale'].numpy()\n",
    "        preds, maxvals = get_final_preds(\n",
    "                cfg, output.clone().cpu().numpy(), c, s, transform_back=False)\n",
    "        ori_preds = preds.copy()\n",
    "        # 只取一条数据看attention map\n",
    "        output_res = output.split(1, dim=0)\n",
    "        imgs = input.split(1, dim=0)\n",
    "        pos_mask_one = pos_mask.split(1, dim=0)\n",
    "        preds = torch.from_numpy(preds)\n",
    "        preds = preds.split(1, dim=0)\n",
    "\n",
    "        index = 0\n",
    "        img = imgs[index].cpu().clone()\n",
    "        pos_mask_one = pos_mask_one[index].clone()\n",
    "        preds = preds[index].numpy()\n",
    "        output = output[index]\n",
    "\n",
    "        ori_img_patch = meta['image'][index]\n",
    "        ori_img = cv2.imread(ori_img_patch, cv2.IMREAD_COLOR | cv2.IMREAD_IGNORE_ORIENTATION)\n",
    "        ori_img = cv2.cvtColor(ori_img, cv2.COLOR_BGR2RGB)\n",
    "        ori_img = toTensor_normalinze(ori_img)\n",
    "        # inspect_all_atten_map_by_locations(ori_img, input, pos_mask, length, model, ori_preds, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)\n",
    "        break  \n",
    "\n",
    "\n",
    "# from heatmap_coord to original_image_coord\n",
    "query_locations = np.array([p*4+0.5 for p in preds[0]])\n",
    "\n",
    "# print(query_locations)\n",
    "inspect_atten_map_by_locations(img, pos_mask_one, model, query_locations, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "ename": "IndexError",
     "evalue": "index 16 is out of bounds for dimension 2 with size 16",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_7208/2978446742.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     69\u001b[0m         \u001b[0mori_img\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcvtColor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mori_img\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCOLOR_BGR2RGB\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m         \u001b[0mori_img\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtoTensor_normalinze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mori_img\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m         \u001b[0minspect_all_atten_map_by_locations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mori_img\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos_mask\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlength\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mori_preds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"transposer\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'dependency'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msave_img\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthreshold\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/yiwei/yiwei-01/project/POSE/TransPose/visualize.py\u001b[0m in \u001b[0;36minspect_all_atten_map_by_locations\u001b[0;34m(ori_img, inputs, pos_mask, length, model, preds, model_name, mode, threshold, device, kpt_color, img_name, save_img)\u001b[0m\n\u001b[1;32m    373\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"dependency\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    374\u001b[0m                 attention_map_for_this_point = F.interpolate(\n\u001b[0;32m--> 375\u001b[0;31m                     \u001b[0mattn_map\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    376\u001b[0m                     \u001b[0mscale_factor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdown_rate\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    377\u001b[0m                     \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"bilinear\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: index 16 is out of bounds for dimension 2 with size 16"
     ]
    },
    {
     "data": {
      "image/png": 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IiIiIiIiIiIiIiIhIGT0vBQ9mNggsBE4801p3/6SZXQ78N+D7Kbo9AAx3H99qDvgI8G53f+wsdsd8h4QQRSRJ5eTTFqLipflODJbPt1fgiS0TvFv08G3vplsYYTheFBpQ1DKEKIYo6XaMCEXBg3ePCRFEfrJxQ1Kp0tvbSxzFxHFECAEjnLyGO0WhgOdkeYZZAAukDrPNFjOtDs2OM9VKmWx1mGxljE/NsHnXIaaane57seK6wbr7pdizQxTFRFHMkt46w406FmKsuw4LECKiOCZOEohiQrWB5Sk05wg4tXqd0UWLODbbpKd/iEVLFnHs8BFq9Tqvef0buO/uzWy5714qlSpxvefMIxQRERERERERERERERERkfPOaRc8mNlG4MpvebpuZj/+dIcBg8APAgG453Su1S1c+DEz+1fAKyhGVywF+rpLpoADwBbgq+4++2TneSb2LSMhzIwoTjCseC1OitqG0J3C4d9SmDBf9OBO0QrilNMZJ887/7uFADjN3Mgs4PMFDyEU3SPybpeIEHWvU4zPSOKEWpxw5HO3EScJ/RsuIe7vY/axvVSXLKQVRdTqdeqNGpYFoigijotxEf31GnmeE6KIYEWRggVjbrbJrsMnmGrlYFFRvBACELr7nP98IITi9UOHD8JFK7AQ4VlG2k6LY6OEKIqIQiBvt7B2kyRJqPb0UqtVGV04ysTEJLWsQz4xRv/QEIMDw2zYcAm7tm9lz+7d9A0MYhhhvuBERERERERERERERERERETkaZxJh4fvA979Lc/1A39+GsfOlwH8zhlcj24hw2e6j+eAnfLw4gv3aP7L/1M6METx/Ia6Yy3yU47vPn9qccMTpjL4yQKJovOCkVtEbDxeSJEH8E73uG6nBQ8nz5lUqiQEJm/7GgNXbmD/X96DdzKqC4dpr1rJrV/4AgMDg7zmDa/lupddTxxF3Lv5HkYXLWT56hWEvChimB8XEUIgJAmdEBfvs7svQsBChJkRh0ASRZDnRTED0McsgUCIEvK0Q6vVJMchTojiGDPoZBlZ5mTpHFGA3tFh9uzdz+z0JNHQQohrtI9P8dab3sSW++/h/vsfJE/bEMeELAOMFUsWPNtBi4iIiIiIiIiIiIiIiIjId5gzKXgYB/ac8vsqIAf2Pc0xOTBJ0YnhFnf/yplu8DllUGzxlA4P80UIFooCADc8RI93cbDQHWuR83jBQ7cAotuR4cmv4wQzDMhDRERG0UAhFNMw5osczIquCSeLKiCKE+IQEWM0d+wh6W+Qjk1w4b/5WQ4fOUrvN7/BW77vLXzsI//A7PQMWeYcP3aEnl095A71vn6qlYRqJSEKgUq1QhRF5BRFEN4dgUGIIOsQOi2snRC1U2JyPMtoE3E8L7pEVJIaFsXU6nUsrp7s8JCmHTx3QjB6+gZZvGiUvXv2kWU57pBOTdLT57z2Na/kzjtup1Kv02jUmDjRBDLc/WRRhoiIiIiIiIiIiIiIiIiIyNM57YIHd/994PfnfzezHDjq7muei409H+xbqhMsGHEcAY6bFR0ZKEZR+HyRw8kJGPNjLgC37nOPF08wPy5j/hKeE0XF+VKKgoeieKLYCSEujrVQ/J53nzcjqiRFMUZSZeiqjUxv2wHtDs3d+8lsfn6GMXbsKPfcdRdr1q3jkUe2Qe6cmO3QrA9hBgnF++vtqdPf388Kn6CnfYzpdptO7qRph/b0CbxeI40CczhVM0Ic4xjVap3JdkajmpDEFSyKiu4XcUIUIvI8J3enb3CQwcEBdu89SE6xxkJOX6PGa294Ofc98BA7t22lXm9wxdVXc99d32RurnlylIaIiIiIiIiIiIiIiIiIiMgzOZMOD9/qPcD0s7WRF8YpoygoOjwUHQa8O+IhKiZShLgodsjnj7EnHmvdggcPj59uvhAhzI/MiEji4gv9PMQkOEShmIZhOU+Yg+FACCeLJuI4JuntZcmP/BC9F6wh9PcTN+oc+qdPE738WhqNBp/8x0/yfT/4Azy85SGm2s7IstUEdzppTnNsP7lDe66JBaO/f4AFl21g7/6DtPZvJUpbRCsuY7xnGaRG0j5BFiKSbreGaqVKXKkSGczkgf5GA49yDMOjBKKEOA5UKxWq9Rr9/X3s27uPLO9+jm7Ua1Ve8YqXcu99W9i28zFIU4LN8cB9W7jq2uv5xh2302q1n9DZQkRERERERERERERERERE5KmcS8HDF4H26S42s5cANXe/7Ryu+ayy+S4Mp4y0ODlSIUQQouJL/W6nh6KIoTvawu2JX85b98v9eU63WwMnv/RPut0jiGLiqBiZQe6PFzfMd3swg7zbTQIjCRFxtUq0Zh1ZpUJ8xTXU6lVs3aVUa1XeddGltFttGj0NrrpiEx///Je4YPUQK3uqzHU6HEtz6HapyB3Gp6YZb3ZIl68ny2GhTxGNjjKEMRcajE3MESoVsjjCLGBxAhYIcczxuZSBehWzVvE2oxhCTFKJiZKYLE3Zv/8AuXvxlvKcnp4eXvPqV3LfffezZ9/+4j13P7OJ8WNs27qDTddexx23f40sy56DpEVERERERERERERERERE5DvNuRQ8fAk4CCw7zfV/B6w4x2s+y6z4Ur77/XsIgTgKxaiLKAIL+HwBAhEEsDzv1iXMdy/oHvyEzgTdY8weH5thUIni7msRFsVgMVjafS4U3SBC1B2d8fi54yjQ6WREUYTnThzHxbiNEJE7VJKEOI7Jc6Ont59qtcE1o/28ZeVCZjs5f/nYEVqVCj2NOp6nhCMRmRn9U4c4snsLk0PDNPwxOmnGXJ5BtQYhkBlEFk4WcgSH43MtBnt6gBae5yffSyWJSZIKk+MT5FnxWTjQP9DPa159A3fddTf79u0vPpZguNMtJoEjh/cxODjEdde9lDvuuP25DFxERERERERERERERERERL5DnGvxgT3zknNa/5wKwejpq5OmKVEUUakkhBBRq1eIKjFtz8lD0i1MADzglnNyboXnRVGC++PdHOaLKCwqlpz8r5xakgCGh4i8OwqiGGVxsuKiOE9uEIWiiwQ5cRSRVCoMLkgws1MaSdj8FYnMMJw0TXHPuWp0kChKSIKxcfEQOzsw10m7HSyMpFqjMzmGB6OTpUxNTdJJO7TimFBtYBQ1HSFA3ukwNzVBZM5MO+PC0Rrx3DQOVCoVhqIOjShiZmKi2I87bsbAQD833vh6br/9G+zbu7d4LQTccwwn9/nP0tn66BaufckruPTSSwF1eRARERERERERERERERERkaf3fHZb6AE6z+P1nplBHMdEoeg6EIVQ/BtHxDGkeQuPEzwqihfwqNt14ZRCh/lihfkTYt1nTnnec8BIku5IixBheU4wyELR8aHb+qA4h2fFOjMgEMUxIQp4dxTE8aMnyPO86EgRxwQL9PTW6R/oJU1TyDI6eUTTjNycC3obPHJkkiiKuu8vJkoS6pWEuFqnUqnSyZ00L6ZNxAZuxfuoZG3mxo+y68QRLh4cZnRZnbVLqhw5HBHFge+/9gLuj48zPnaEE+MTXLHxUiKDek8vL7nuWrZv3UqjmnDRhWsJIRAlFeI4wUIgCoFOmpLmGWknZWzsIBevv5yDjz383OYuIiIiIiIiIiIiIiIiIiIves9LwYOZXQwsAPY9H9c7bV50ecio0Ol0cIoOBHEckZoRzx2jFhmzSQ/uDp4TzAhm5G5khG55gxf1DWbFj93xFpYXnQy8WyQRnRzl4JB2iDpNsqjaHWcRdQse5rtHOMWoC6hUqsRRTG7FeUMItFsdhkZ66evrJcvy7lSMCLOMTpoym2Yca+ZYFNg50yan6LzQaqe0mh0GRyJIW0RJlRDFQE6Iou4+ikEcZkYzqjO4eAXLV6zkn+/eyt5Hxvm+LIKO41nOFz/xUQ7v28WqCy9lZMECxseO0emkvOblL+ez//xJDh8+jFko6jkwQgiEKGAhMNDfT5amtNop1h0lcsdXv8Sq5Yue5z8EERERERERERERERERERF5sTntggcz+17ge7/l6QEz+7OnOwwYBL6L4pv8r5zJ5k45939z911ncuzpajZzMiDv5Lg7njvBAmFoKenAKqhWIXQ/JgfcKf5jGFYUM3SLINwzwLBuwQO5Y+SQZeAZSTDAqYScbPoEPbOP0Fm4ASyj22aimCHRLa7ADEKgEhWdHNyL4olms0W1VmFutkmnmdJupQyNDBL6I2hDO8s53mqxvLeXmRx2zLQgRKRZjueQeU4SJ1injYXimsGhUkloh4TQHZthgFsgTqpUk4ROVGHGqjQadeamWrjnTE3PcmximgsbvcRRRFypcuOb38inP/FP7Nu3F5ufYtKdwzFfDAJgnpHnOdMzsyc/RyxSwYOIiIiIiIiIiIiIiIiIiDyjM+nwcCXwk3R7GXSfq3efOx1HgfecwfUAfhxIgXee4XGnxUKg3tcPQCdNiZMqAJlFtKyKV3rxOCb3iBAAjCzvfmFvVjzyHAjkZpgXIyu8qGsAd7I8A4swd45PN4uuEu605+Zo9wzhUdLt7AB4gMzAvPjZHdyoRQlRFJHnOXme05yZYWZqmtmZJrVqDTPYv+8Am152VVFgEAKPzLTwygxTWc5UmmGRkXeLCnKMahyRt5uEEE42lYjjGLcEusUcxa6s+Gw8o2MJnRAxOzdDZEW3igwjIyJOKiTVKje87g386S23sH//fgzorVYYatSJ45jjc3NMzs51ix6MKArdSxtDg/1ceuV6FtRz9h1qPhdxi4iIiIiIiIiIiIiIiIjId5AzKXi4F/iLU37/CWAO+ODTHJMDk8AW4CPuPn6G+zsC1LyYCfHsc6c1MwkWFbUFnhNFESFrkedZd/xCBFlEblYUIMy3PuiWAxQjIAAMn690sFB0aJh/Pc8Bp7enF4Ch4QXkaYadHGPBKee2k90Q5p/rqVSKfYWAu3PZ1ZfjFJ0ozIrn8jyjVqnQ6aTU4pg7H97OtqERsrxTdKCIEyoh4Aazc22SJCZtdwAnz3PMnSiKISSAF90d3IlwkigQ8owWgRzYsvcgVywbBZyLLr2YNevWsmrVSvbt2sVXb7uN/fv3dT8Ho9HfIEoSkjihEZzJ2VnAMAuEKKa/t8brXzrKS9dHBD/K4eMd9h0afE7iFhERERERERERERERERGR7xynXfDg7h8DPjb/u5n9BDDh7j/1XGys607gLWa2zN33P9snD1HEosVrGR4Z5ND+3VQqNZKkSr3eS5pUmc1z0jwmiaLiAOv2Izilg4MD1h09AVG3/4WB58VECqASjL4kYnxyEncnCUZldA1J7yIqcULuRXGBY/OlBkURRbf4IQSjkzmB4ucQimubGSGKCKHoLBEoujT8q5/6YXbtfIyly5byN3/xV3zus//MG777Lay++GJ2bH+MdcuWs2DRIqLBBSQHH2N2ZoYoTsh6+/FqRJZlUKsTtTtYXCNOEvIsJY3rENfoaQxy5ZrVTJyYYs3qtUzMTLJn7z4a9Qr79u+lu3nAyXKY7WQ0s6I7hbtjFmj09bN8zTJuekmE5yn37845fqLFurVLgdlnO2oREREREREREREREREREfkOcyYdHr7Vq4H2mRxgZle6+71ncMjvA2+hGIXxL8/kWqejt6+X3/+/f8zxo0cZHzuERQkDQyNcumYDXu0lrw9gIaaadD+mPO12VSjGTuR5htn84AeK8RDdIgTPc6JgxAH6+xrElvLwQ1s4fHiMl16yjOvf88vs33eA6XZMqPaSGbgbndxJ0wy3iE6nTWaBWhyxbX8HyzOSEIgNLDKSJKaWGHESSMxJYiNJjOHhhSwcXUwwZ8GCRWzYeDVjRw4zfmKcqNZHODbFrk9/iaG4RmVkKY2BlLYZzbRDPDdBNLKAqFKl0qiTJlWyzJlrNmmGCiHEbD8xzYMPPkQ2PcptX/giAyPDLFq6nJGFS5mcGO82pihGXhw/MUEUAo6TZTnVSoXhJctYf0E/i4d7OD6Zkk/H+OxxLlxYYTQ5oz8pERERERERERERERERERE5T4WzPdDdv+zutz/TOjMbNLN3mdldwOYzvMYXgV8EfsLMPmhmV5/ldp9Uq9XmQ//09/zD7Z/jtm338ckvf4av3HEbX/j6F/jjv/gjfuv//AEf+OYWFg86CxodBipNepNZ+ipzDNTaLBqKWTQUWDqSsGJRjeWjFVYsqLBsOGL5gpjFg4GBRk6UzxIsZXTBMH39PYQAlSTQ11ujUUmp2RRVn6KanaAnPUG/n6Cvc5R47iifvXsLH7nzfv7mjnv52zvv42++cS8fuPM+PnrnvfzD3Q/y93c9xD98cwv/eMfd/MPmh/iHbz7Cx7/xKB//+oP88zceZc1V1/PWt/8Eb/2Rn+D73/Fj/NDbfoDvfs0r+L7Xv4p3vuMd/PzP/By//HP/hnf91M/whhtex8KBAUK7Tew5lmZcvnABr7nmKi67+HL+8xuu5bdvWMP3bVhE1h5n4sQRHnzgm3ztS5/hoXu/SSUxPJ+fPlKMrfA8x8gxnDgyFq9ey8YLq3zvVYfYtGIPFy7YT84+hgZmuWRth+VLpp7NiM9Ln/rUp7j44otZt24d733ve590zQc/+EHWr1/Phg0b+OEf/uHneYfnH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpZyUS/kok3JSLuWjTMpJuZSPMikn5SLP5Fw6PDwtM3st8NPA9wFV5mccnNk5dnZ/7AA/APyAmc0Bx4DsKQ5zd7/gdM6fpSnbD+xk8cbLSCzCppsYThInJElEc3qKvNZgaHiQrQ/u4uEtDzA3O0OedRgYWsAb3vJ6qtUKIUTFm+uOsZh/q3mez28IgJ7efiqVCp0sp96osrS6lJF2C7zbHeLx9427MzE9x/vuO8bBuc78C8UjSzFSPE7BArhTmT5Ke2ARWDF+w/IcghX/ZinmHcwD4ATPsc4cIc8J9V4saxPlGUaK5THQLsZxGDy2fy933nMXtZ5+PnEQBgd6GKrkrO7p5w9+739x3XXXMrJoBV/83KcZO3KUaqVKCKEY0eEZ7jmXXnQxS5aMctf2o1ywNOfNG4+SpxmtdpvjUxF7D3cY6qvy5XtmWLxo8DT/OuTJZFnGu971Lj772c+yfPlyrr32Wm666SbWr19/cs22bdv4H//jf/C1r32NoaEhjhw58gLu+DufMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSTsqlfJRJOSmX8lEm5aRcykeZlJNykdPxrBY8mNly4Ke6j1XzTwNzwD8DHzzDU65+kuca3cdTOf2iCodDW7czPXaMgNGTVJhdGbN1+yMcHLyY1tKLSCoVoijG3RkYGGbV6pVMTk7SP9DH2NETeJrR29dgdq5N3klxnMVLR9mzay9xHGMBqtUqDsxMTbNsySKacy2q1ZgoBIIFsCcveKhWK0RxApZ3ix0o/sVxB0IE3eM8xBDiogACw4MX64qDgPjxT8bALMbM8VovDsVoDnP6KvdTCREeIrIo4kRUo0lEZcFyHtozhp8I1GbGeSM7WblqNVO1RRx66EHWrbuQz336M/T09hKCgUOa5kRxDHS4Z+cES4edq1e2uHdnLweP5UxNp+w44JyYdEaHjddcO0qlsQ7YcdoRyhPdeeedrFu3jrVr1wLw9re/nY997GNP+B/+P/7jP+Zd73oXQ0NDACxcuPAF2ev5QpmUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKSflUj7KpJyUS/kok3JSLuWjTMpJucjpOOuRFvPMLDGzHzKzTwG7gN/g8UKFjwHvAEbd/Qfd/UwLHn7qLB4/fdp7D8aqazex8a3fy8Y3vZbFF11CvbePN/7Cu7jgmpeQx1WSOMIM+gd6WbF6KVGcMLJwlIGhYSZPTDJ2+DDTU1Mc3HeIY2Mn2LV9L8eOHOOh+x9k1/adPPrgVh5+YBt3f+M+Tpw4gXvGvt2HaTXbxFFEFEWEEIpHFIiiCLNiHETxr3ULG6KioCFEECUQV4pHt9Ahj5JuwUMEUXddUUnx+PHzHSIIYAHHujUQER4CboEQDLeAz6+NE2o9PSTVWlFUkWd0dj7A1IkxFi1ezEA+x2PHm8TVOkkSgac0ehrUGnVCFKhWKzy4dS+HH3uYpf3OiWwxW8dXcKyzkFYYYcGCAV57/RKuurDG57++gz/68Fc4evToGf6ZyLz9+/ezYsWKk78vX76c/fv3P2HN1q1b2bp1Ky9/+cu5/vrr+dSnPvWk57rlllvYtGkTmzZtUibn4NnMBJTLs0X3SvnoXikn3Svlo3ulnHSvlI/ulXLSvVI+ulfKSfdKOSmX8lEm5aRcykeZlJNyKR9lUk7KRU7HWXd4MLPLgXcCPwIMU7QRALgDuL7784+6++zZXsPd/+Jsjz0dZsbQ4CBDtTpjY3uYGz/O4hWrqVeqTE3PYJZQDREOtFpt9u85yMSJCdZevJadj+7lgotXcHDPDHv3HGFwcJBlKxez45FdtOZm8TyhUull4sRhWq0xkqTO8bETuBd9F7746a/RqNdwc6I4wTF6+6pcuelyzKw7DsPI6RYeBCu6N8wPBrFwspsDeLfIIYDPd3QIxTF5BubF45QuEp4b5vPFD3byPAHH7PFmEB5igkXkuUPahsmjsPpiPN8L04dZOlinb2CQ3p46nXabLM9ptzvknpPnOVkG8cBS6OR86fbt/OKFG+hbHpG2ZzgxmZFGw/TVnVarznXf+1b+8eAy1ux//3MZ+3kvTVO2bdvGl770Jfbt28crX/lKHnjgAQYHB5+w7uabb+bmm28GYNOmTS/ATs8fp5sJKJfnk+6V8tG9Uk66V8pH90o56V4pH90r5aR7pXx0r5ST7pVyUi7lo0zKSbmUjzIpJ+VSPsqknJSLnFGHBzPrN7OfNbNvAvcCPw+MAPuA3wIudveXPeu7fI6EEIjjhEZ/P2vXXsXwgoUEC0RG0fbEIE6KLgy4sWjZYgaHBzl66BiVOOHooWMMLxxiaHiAgcE+TowdZ3ThAtasW8WC0RHwjOUrl/GyV72MCy66gOHhQdxhaLCfRQsXsmrtSoZHhuhp1KkkEVma0Wq2gaIYI8udjnc7PFj0eJGDRY+Pt+g+ZyfX2ONvcP71+bEWFigiD0V1yvyYjPnyhtzBs+6x4F6MxDAzyFLoNKF3EHoW0NM7wOFDBzk6OcNsO2dqapr+gYHu6fzk9RxYu6ifl29YQBycT37+ER7asoVHt+5mNq2xdedBPvuNw+w7MAY9C7lg6PQnksi3W7ZsGXv37j35+759+1i2bNkT1ixfvpybbrqJJElYs2YNF110Edu2bXu+t3reUCblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykm5lI8yKSflUj7KpJyUS/kok3JSLnI6Trvgwcz+CjgI/B/gGmAW+Cvgte6+yt1/zd1fZH89TppmTI1PQlKh2ugld2ds7AStuSZJbPRVA5EZfYO99PbUWLtuFQsXDrFyzTKWrVjG8MggowuH6e1vMDw6xOjSEfoH++gfbNDX3wMWyNJAktSZGJ8GnE474/ixCeZmU9rNjFarw9iRYxzad4ytD++EbpFBOl/wYKeOpQgYjjkw3/0ByOeLHUIoHvOFD0bR6SHMF0yc0gHiZCGEnfw8cCd3mP/TyBxC6K6p1PDeQbLeYYZXXMDePbs5dvwEuedse/RhLtt4BcsXj3Ljq1/GotFh4jghS9ssWzjI6JKVTDdzth+p8LWtVb7yUEQzq9NXz1i7sMOCvpTeg1/h8qXV5yv870jXXnst27ZtY9euXbTbbT7wgQ9w0003PWHNW9/6Vr70pS8BMDY2xtatW0/OPpJnnzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUk7KpXyUSTkpl/JRJuWkXMpHmZSTcpHTcSYjLX6EohXAFygKHT7i7jPPya6+hZktB34JuBFYBdTcPT7l9SHg57r7+213T0/nvO5AHIj7esirMVCMl4gsQGuWjjewkBAsMDs5w6H9h1m+YhmTE00mJ2YZHB5h/969GBEXrl/Dho0XFjvwnFVrV+DuGJDnOXEcceTQIvLcWbF6Ees3riHLcsDJ8gx3yPKcYFacwsEtkBVv8JRxFEWxgs93bwgBc4gjo23z8y4oihyK+RndTg7zxQ1AngM5ZsV5rHvN7qfS7f5QHJd1mzW4GSQViBMIESGK+He/+mv82n/4ZeY6OZu+61WMjCxg69Zt9NcrGEZcqeCe8ZWv306lWqHWaEAUk2Y5rXbKp+6FqHoRlRjCISe9+wGuuUgzc85FHMe8733v48YbbyTLMn76p3+aDRs28O53v5tNmzZx0003ceONN/KZz3yG9evXE0URv/3bv83IyMgLvfXvWMqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUSzkpl/JRJuWkXMpHmZSTcikfZVJOykVOh7mf3ggBMyu+nYcHKQoe/trdDz7D2j53nz2nDZq9Hvgg0E93AAPg7h59y7o7KTpPfJ+7f/x0zr1i1Rq/7sfewbINl9Hb08uhzffSH9dIVq3gs9vnuO9wzr+4Yhn/9tUXc+zICWZmJjm0exchiVm2chW9fYPkeY6FQBxHVKsJ7jlRFIPnRRGBO5iRJDFHDh+j0aiRVKoMDPQWIyO6j7z7cHfyPMfdOXR8ml/50NeZyiMOeYP5jgyWd4oChLhSFDJ4TtScIusZoIqTWE7uDnlOmhX5dizm8ahzotlxiBPySg/Q7eKQthh58B9JA9TrNaq1OhPVUX7q6guJRlfy/94/jlfqmBk/NTDGzTe+hHf/p//I7Xun+IV/8Wb6GhXu+NRHqEQxX39wOxPTswQzhnuqXHrJJdz90KPMNZukacbs9Bw+dAUkPUVxRpZTaW7n5esXM9nK2Lx58zn81cizbdOmTcqkhJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5mNld7r7pbI49kw4Pvw38GHAZ8F7gt8zsc8BfAh919+bZbODpmNkK4MNAH/Dx7rX+GBh8kuV/BmwC3txdezpXIISItNXixPQE5ikhiqn21pmcPQahQSWJCcHYsXUnn/vo++mJ27Sbs0zOpqy9/BVctOEKpqdbTE+dYGThIPt2H6RSqZGlbXoavbQ7M9Trvbz5+1+HmZHnRdcFO9lGgaLDQu7F9/5ZjllR+FAPGd/Tu4d7msMcavZ0R1UAHopjnjC2ImAhcG1tkstrxzk60+HAeJOlvYGZqJcvzS1mjm6NiM+Psyg6PFQt5/W9R8nac2yNnWNZ0echx/FuZwl3umM1unsgxzDcjSSOSeKEtN1mYHgBR6cDQ8uvJBzbz9SJ/bRaLWbnZunv66XVagNZsf9QgSiB4OARkUGtkjDZys7gr0RERERERERERERERERERM5Hp13w4O6/amb/Cfge4J3AGylGTLwBmDKzDwN/6e63PYv7+2WKYocPuvvbAczs/zzF2k93/732TC5gGHNTUzR3P0rcdMLyYdpz06TtObAeGkmEmbFz60M8fP8dXHPNlfRevI6RyQnaE4fo6buO1ResYmJ8it6+Oje89mVkWUaWZeRZTpqmhCgiSeKiGQNFMYPZKcUO7lgoih6K3yGEQJuYr7WWsbtTL44N3TEWnnULD7rnyLsjJwz2ZXWmJ/vp3PGPeGuOtL+X+sZXkFt3fdF2ophsYfNFD7Cz3c9QlpG7zZ/2ZJHDyb0G6xZAFJ0mcs/J3Mk8J4pjWrPTbD04w85DHfoHhliw4jLacxPkzRNMTU0x0NfDkSNH5k8MFnWLKICQE8yJT47uEBEREREREREREREREREReWpn9O2yu2fu/jF3vwlYAfwnYDvFuImfBr5oZrtOPeQc93dj9xy/fhp72wW0gDWne/Ki40JOpd6gsXoDycBCQojodDrgTghGLYkJZlRiGO6twsJhOv/qX7P7v/wmC6+9Hs8CM9OzNGdmqNcqTE/OkOdOtVIDAoNDg1SrFbIsJ00zsjTt/pxjZt3uDnDqZJEoigkhpjdx6hEcyetFoUGIICqKBPzkdI9CsKIIYXenyv4DB+lMTbJ4dBFzU9O0pqawULxevPFwsisEweiEmD15D4HiecMJ1i18sFB0jzCK61txTHHNQI6TpjlRFJF7Tp43WfK2TXTeeoC57ChxFLFwdJS5uTkG+vuJKzXipNLtSBEXRQ8EjOIaSZKcbnwiIiIiIiIiIiIiIiIiInIeO5ORFk/g7ocoRlu818y+C/iXwA8Aq05ZdpuZ/R3wIXfffRaXWQnMufu201w/DQycyQWydkrW6TC8YITZyRlwqNbr9A8vYv+JQJxEdNotju14iGUjg7xysJf1X/s8E4vX8VjPMP1D/Rw/MsHE5CRJtcqJ4ydYtHgRadZh7+59bLruSr7yxdu54poN7N97iA1XrmPPY4d4+P5dvOr11+Du3aYLRecHALPiy//UI5oeut0b5jsrUBQenJyLYWA5boYTimKF43uZ2HQFPjzIcP84trdFms8f3i1WwPHQLZ4w8JAzQpOD3XEaOfONGAKe5+Tu+HyXiG6hhoWAxQkWBaI4hixnwSuvZ8f1l3LtfV9hwWLj4c5CFiwc5tjYGCMjwyxfsYK5uTlCGKNTj/CoeA8WB5b2L6BerZ5JfCIiIiIiIiIiIiIiIiIicp4664KHU7n7V4CvmNm/Ad5B0e3hJcA1wNXA/2NmdwF/5+7/6wxOnQPR6Sw0s5ii08TkGWyc9sw008ePEbIO3pylr7dOPjtLnkFvJaEaR+zY8jCvvu5KLrz0B5g8cpQt2/bgkwPk9SEe2bKDWq3G6rUrufyqdXju5LmDwdUvWU+eOW/70ZuI4sDgcD95lrF46TBD6weKYodTWjtkmdNqdejpqeLuTKQxD7SGKZpcPN7RwaHbpaFbgJAbbnHxe2RMXvIqFk7cSfvGV7P49scYWrqYvkYPj05k7Jnu4EAwJwtF9waAOYv49OwIwx6Rk2FYccUQYxg5BlF8cn3x8eWEKMYsEMcx7k5ty4N0/voDPOzOlVcu4XjPOmp5m8GhlP56lSsvWk270yZcdiH9vf142qbVyQhxQqNyBXNTpx+fiIiIiIiIiIiIiIiIiIicv56Vgod57j4F3ALcYmYbKLo+/AiwANhEUfxwJgUPu4FLzWylu+95hrWvBBLgdLtBgBnNg4eZPnSQ/Z4zOjDM0EUDfO1jH+fYgpcw27+WzlyTVWGCjQt+iOYVR/jHe7Zx1ZU/QZxUyfOcPM3IHaq1hBAF3HJCFLqntyd8wkmS0GnnxHFMvVEUNWS5k7mDO7k77XZOo6cohGinGVlxpifUPBgU3RZC9+RRDh4RGVxVnWRD+2Emju9j1Yc/xOjoWl79hk309Tc4PNPh5z99iEfH2wR3LOqOqDAnj41m1G0aQVGwYWasyif4+n1HWLOxDvGCouChW6iRZhkHDh7HQkIcR0DO0NAQV1x1BVsf3cZcY5SXXnMlX7lvF0vjfgbTcUYG+6nEER0PVEPOYKOXaqVCKw8cP36MyROd045PRERERERERERERERERETOX89qwcOp3P1B4BfN7N8D30tR/PC6MzzN54BLgZ8F/tNTLTKzBPhNirKAfz7dk5sZI4uHSRoJNHcTe4s4ClxwQZ39HSPFOPTAN1l9+XqOfbGH4+s/wr6V+1hx4rXccccjxCGi3W7R29dgzQVrOHz4GNdcdwmNnnox8qGoHjhlVIXh7kQhYKFbxEBRZOBAtRJTGY5IsxzPc/xkVwc7ZdPzD3v859zxEFicpPxSZYjlL3sr2fe8jgP7DrB46WJ6+/qoDT7AsaETvGHVerZOjWNhvmjCTnaKsLzb18GLgocc6LMWD+/biw+tgAULi/U5xTEOrXaGxTWSOCJtt5kdO8LYY/uYPJrzhiOvZ9/bvs6Fk5Pct6WHwdE+FlerREAtShhsJNQbdbK0Q73WS07gvkfPZvKJiIiIiIiIiIiIiIiIiIicb8IzLzk37t5x9w+7+3cDq8/w8N8F2sAvm9k7n2yBmV1NURhxHTAF/OHpntwM4mpC3+AAK0em6a1OEyJjYXUrtTBNg5SN/RF92y7isyfaTMzuobUyxys5a9etYuXaZaxas5Kh4REMGB0dod1Kac62mJtpMjfbZG6mSWuuRdpJyfMcB+IkBjfyvKgtyLO8OwojJ88dzx0LAbeA+ynFDrkXlRF5Dp4BxQkMwGBdrcPGgxex/as5Wx64jwOHDjA712Tf3gOkncM8MPAIG1cY/UkgdwOLIERF1waLsHy+jsKILQKHuVYLo+hOQYieUGjh7kWhhIGFCHNjZnycoVovSWuY6W8O8A9zX2T9pcdI3Xn00DQ7t+8gjiISUuI4BosJUUKapsy1OuydVIcHERERERERERERERERERF5Zs9Zh4cn4+77znD9bjP7l8BfUIzJ+C1gAMDMvg6sAhZTfAWfAj/u7mNnco24klBt1KizmBajhABDfZPELaNv9hgX1Qfo7B7l03NHWFc/whg9HLHD7Nk5x7JVC9m37yCBiEP7xxhdNMi2rTuYnphhZnaSRqOPeqNOJa5z9Ohh1ly0jAsuXsnsdIu7bt/MsWPHWb5iMQcOHKXdanPdK69gwaJhpiamqNVrzDY7eJYTcBwIeY57jOc5ZgE3PzliIpixug7VbIidnYSlyQhDvQ0effQoe/Yd5R2jOxhojNBauYeXLF3JN44+RmZOVpy527EhI/ccAAuG0y2+cKdWqZzsLOEh4HSLMcyoVRKiKKaSZ6y44CK27zzAiPXQYyuZW1Ph4nSGrN1kymMuuGg9wTLq9QYWIqqVmPZcG3Pn+PgkD+05zJVLe84kQhEREREREREREREREREROQ89rwUPZ8Pd/8bMjgD/B1h3ykvXn/LzduBn3f0LZ3RyM6rVKvV6gyMHR5g81qLe5xw9ktPxQDQ5xsWtDRwbmmbr5iPk4Qjbd49Sze7g+2/4Me786hbwiN7+XlrNNn0DfbSaHS68cCVHj46TphnLVizi+NEpRhb1kWZt8Jx6b5VrX34prU5KnMSsvng5GDR66szOtDi07wSjiwcxoJbOcgGHIO3QQ5NK/wKOkXAw7+OE9ZACgYwqxrJKTJJUOHq8zkW9g8zOpWx5+BiNniqNWgf/cswjV99DwxcSkRYNG0IoRmcYkGdkeV4UOjhgUE8qxCFQTeKiuwNFR4c8z+c/RKoG1UqFiwYG2PrQ3Rw8dIhqtpp2pYeJtMaiRXNY5wSTeZWx2YyefIaZuRaGE0eBdG6GNMt5ZOcBvDUHqOBBRERERERERERERERERESe3vNS8GBm84UI7u6vPdPj3f2zZnYx8Erg5cBSIAIOAV8Dvuju2RnvC+jp7adWrZOMLsI7EzgRef9r8Nkh1jQfZdQX80G/h+mm4+kERz9bIXlVhcP7xxgaaZB2nEq1Rq2eEEJgYKiP/sFeJidniIIRgtHoqdGcm6XT6eBm5EC9XuHw0eM0W016e3vZuecgo8tXcvd9O6lVAz0Lejl28CAbW4+wcKCHSqXKsf2HWTLSw1Kf5cK5QxyYcvaEBeTDK2h5TnV2jubx46SzNf7mw5+kd7jOtZdcxshwjYULh6k/uoldd7yPmSOriTzHLcYtAnMMA8/Js5zcHXcnEGjUqsQhEMdJ8YmZgYN7URiB57SnJ8k9Z9djO5jNMqJOigPbvM7cjgZ5fJw6R5nOlnLfPY+yMdvPsbkOazZdhdWq7N25C5uagNoQ3m6faYwiIiIiIiIiIiIiIiIiInIeer46PNwA+LmcwN0d+HL38ewwI/MczBhctIrmzCGiOGHphddh97VZmh7HGs7tdx+lty/HehssX7CeydFj3Hb/Vxg6PEQl7iHPc9qdFo2eXhYuXESaOlvue5hKtcID9z3M0uVLWbholEWLRkk7Kdse2c79dz3EF7/yBfYe2EO9XmdkaJB/9ws/w3dvWsf+o9Pcf889PLxzG/0xhDylVu0lThLazTmSOGb22BFqEyf46Veu5robruXdH/40f/zAQcI3xrhm6gcYv6DJ6uUJ6y8eoN6IqNUippN+dvbFrD9+hOTgEGmIu2MqIghFwUPR4QHcHDOIopgNa9aycGQYJkP3cwN3yN0hzyHLCRaw5iy7dj1GNe6hbn3s7p8j//xhDtohli5by9hjzkzoobfey0g0wzUXLKEVjGzHI6xZu5jPnvDixCIiIiIiIiIiIiIiIiIiIs/g+Sp42MNZFDyY2Wp3f+zZ3073/BhRFBXdDTDcnTzPGZ+aw2ZmmZudxg7VuWblBu7d/1Wm2xWWDKzkjYfXcu8P7+C66dcweGwpZk4SxYQAWNHV4Ud/5gfJc8c9wzDMjBPHx2m15li2fAljx0+w9c8eIM1SZqcDU+NH+NX/9F+48TWv4FWveQPT42PQmaUWVUib08ykc/T31sg7bY4fPcTc+Akuu/Qirr76GlaODvGqBTl/9k//zO9u+h6G77yNDZU11Orj7H1sBwsX9dJu5zTbznRYSnVknOCDRbcGCxACHgw8JXfHzDAC5nDw+DgvXX8ptZ4emDQwL5IMVoy1MCNUG0RRIDOjv7eXI8di3tX7Dv7wt+9l1d8tZ+sju7hgXcxD+2KmLKE2MESlNUd9dpJDk1P0tZrUogHmZmdo1GvPVdwiIiIiIiIiIiIiIiIiIvId5HkpeHD31Wd56HYz+yzwR8A/ns3YiqdjBiHERCGi3e4wNT1DCA2+cf+9zLRGeezgQcbmDrPcl5NnO9kzZjy871GW729w0eGF/PO17+ex21/Blj09uEMSGSFJSOKIKDKiYCQGFXcaAXryGX76mlEeO3yCP/3bv6fdmoXcsSim4xkTnTYf/OjH+dCHP8qqNatYu+FyZmbmCOZYMNrtjN5qxIKRIV529Q3UanWOHpumlhzhspHlfNdAgy8NL6G6qMlcWAjxFCGq0j80QBRV6Gn0MT6xjlb/g8SkgBWdHQwIhmU5mTtmAbOi+GMvvbwiz/AQirUAFK8ZYGaEOMYsUGs0CBZ4WfslzPzUYY5PdRi/byXbF13ClZenRFFEC9g70eGlg72ETsbhnftYWk+oxDH1nl5GR4eezYhFREREREREREREREREROQ71PPV4eFsBeAN3cdhM/tT4E/cffezc3qjUqkwPjHNw4/tpi+F4Z5BlgwOkiaLuP/LY3xh/20sDT9Nu/0Qj+yNmT0xxccrI4x/OeHah5Zzw8h2XrN0JTuzAb46HrFlpkNmWXdUBEU3hNzBc5b4ND+ZL+DE1BS7p9rgAfIOJEbW6YDnWIiJyCGKaM9MYg6z0zMklSq054irg6y96HL6Fi3l+KFD7PjmN+hcfhWtdou7ptpUa1XWrMsZ9osYWTjDstWrGV08ADbBdB5hjyxkVW03d+VZt9ghdPdq5HlKnmeEELpdKaC5/BJq/RHtEHDrRlJMvyBY8SbjKBAMQoiwPOING17PX7zuT5j+hSsYm+iwf2Itb1hwgGq1Tp522DHpXJHknDgxwfTR48wsGGGqHdNJqjRn56DR8+zEKyIiIiIiIiIiIiIiIiIi37HCC72BZ/A64ENAB1gM/Cdgh5l90szeambRuZzcDMAIIWL6yHGa4xO0m7Ms7uvhZzYO0hsCf/vAP5LMzRJ3DtPePUFf3E99aIjd9aV8eGoD79m6lr//+kPkX/s4PzB+N/WIooBg/gI2PwbCcRzMiNzJ0w7eO4pZoJJ3SPI2g1HO+jXLGLx0HYsvupBqJSHOO4wdPEB7epxOu8Vlm65ndOkKcovJQ8SW+7+JxcaOfQcYWLCMHnL66kdo9C5h6bJlDAz0EyyQpgvwTpuFR8ZYvGuW3rwNIX58j4BnKd4d7WGAO2AR7uAWijdmBhYVXSBCAPPuKQyrVBgcGuKO677I7f/1IXZse5R09gT79rSYnO1hvjPEZGWQw7MdHtq6m5YlzFqFSU+YauUUc0FERERERERERERERERERESeXqk7PLj7F4AvmNkI8JPAO4FLgO8GbgQOmdmfcZZdH8yMZYMLqfXUmVwzRZzn1HsX8MjBfdz1WB+j619Le+ow+0ZnuLx6A6+74hvs+3APnev6uXrhQFEYEIZor1zJA1mTGZvh8sogTtHYYb5TQiOCRZWc7PgcRo6ZQZRA2ibOO1wXO8ejQH+jShaMSqOXRx98gMvWrqXTbtPfU2N64gQ97Q6Htz1Ktd5DUqnR6TTZ/ujDbN32KJ/+/EeZWnkNc56Qzu4h9B2gksQkcUKIcnLvY8NwTM/EYWo9bXpak3iYL2Cg+DdLiyoHL/ZoOFig1WmR535KcURRwNFuzmHu3UYRgcwi6oM1jt73KI/dOUfOJBbB0Z0nOHhoGZ53SPOcCasyHSocO3KAuNbDbAqHWhF5yInjc6phERERERERERERERERERGR88RZ/9/pzewNZnbczN5/Gmv/vrv21WdzLXc/5u7/y93XA68E/gZoAUt4vOvDP59p14dggSXDC4lazqZLLmXdshUsGOjnuy7byEtGa9zw6u/iZTfcwOakh5e/4pX09V3Cj37/Mq5sHeZlPdO8rGeW63tmuK53lst7OvT0xFyRTHBlMsFVlSk22DEuC2OstzFeMtjiknqT8bFjgEOcYHmHUOlh/WCD9Qv62bByGRsXLWKw2kPU12Ds6BHGDh8k7bRI8oyXrlxB9euf4t7PfYLjRw4wdmAvSZywduVKJqZOQL1GPZtjpL+HVquPdrND2mnTac6RZ49RmZtmctVGPjw1zKGoB7dibEV3HgWWp0RmBDMCEIeARRH1SkISR3QnWBAskKcdbv/aV9n98Dd47K7P8/cffD+79h5gfHKWu/YcI0vbWP5mYIL21FF+9z9+gv7kBAPDi8grDXacaJNZoOIpY6lzsOPFx2L2tJnJM/vUpz7FxRdfzLp163jve9/7lOs+8pGPYGZs3rz5edzd+UmZlJNyKR9lUk7KpZyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbnIMzmXDg//AhgA/vY01v4d8Fbg7cAXz+GauPtXga+a2c8DPwb8S+By4A3dx3zXhz929z1Pd67ccx7cvZ3FC4eo9lU4sm+MdhbRGO3jT3dB6+gkfPwv+MHrX080uIXf+dTn+PEfdz7+j5s4+vJ3MmkV8mJTGFaMrYhD0cHBAIshd8gz4p0TLPCI910ywvH2OGYRFtcgqrBsUYPB3gFmZqYYO3yAuLGAnoFhju3eQdRqEUcxC9yJpg9igyM8dv99WKXGzP59rFi7guGhQWy6TbPZpjl2hC/c/SWy9pvY+sgHyJmh2pjk3/zCHL/6nsUceskPcOSSNzCw+x4sGJFBZ75rQ9rB6FbBuBPMMAu4O+453q1FcJzcM/7wD36X5RdsoD40yu1fu43Lli6j3ulwz55j4MPAajwbg3ScxctqrF50kHsfNUY6E4T2LFm1QmOwnywOtNodJo4fI23OQt/AufyJnNeyLONd73oXn/3sZ1m+fDnXXnstN910E+vXr3/CuqmpKX7/93+f66677gXa6flDmZSTcikfZVJOyqWclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5yOk46w4PwPUUkxu+dBprP9ld+9JzuN4TuPu4u/8BReHFbXRLDHhi14f3m9mqpzkHX/nMF/n4h/6ej7z/g+x9bBdzs02+9Jkv0eykWGOATRteytbtE9y/5QEeeTjisotH+cCvfx9vWxFDCMy3PXAzPASwgJsRB7rPFa91QkQaYsAIIUD/AvKRlVi9n4H+QdZdchkLl69lycgQF9QjanGN0GwSgEHPuGLdRUzEg6T1PgbiQN+OLfj4MXoXrAAzltzw/cyNXkwnqfLY/n3sOXicb9y9j7vuf4B9h49Qq06QZy2i2QmaoYLnjgMdusUZ7liWEofQ7fDgmBfFDfOsO9LCA0zs38OKlatYOFCn4U1e9opXse3IIbIlS2i2ZnG/GtiDpcexUKXVzFi3aDutw9sYntnPSBXo66cTJRzwmLjeQ0p31IectTvvvJN169axdu1aKpUKb3/72/nYxz72bet+/dd/nV/91V+lVqu9ALs8vyiTclIu5aNMykm5lJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqV8lEk5KRc5HedS8LAcGHf3qWda2F0zDiw7h+udZGYVM/tRM/sy8CDwXd2XdgO/230uoiiGuNfMrniKfXH7F7/MP3/0H/jEhz7KgX17ac7N8fUvfJFO2mGQFi9bvY40O8Kdj9zPD15/LY32y1i1Zoq3rY7oi7woeOh2SDj5oxkRgHefsG4hRAiAE6KIvGcQH1wIPYMcP3qQe+/dwvRsk0ZPRF97nMqxMS7q7WFdbx8bRkfoCc5wX4P+Cly8ZICLF1TJ04x4eAlJtU5zxUY6lQbeGMSjhCjuQFQlyzKy1ElTpzU3S9Zu40Ca5+B+stghylLqWYtapUJvtU69WqNRrVAjw8wIIQKLiiIPYGbyBIsWLWZ4wWL6+gcYGVlApVpjx5Emcf8IIbwCzz+Bp3NY3mFu1lm6OKWnr4+B0UUsWraClZdfRbRkJcctZv++nTxyz1eZGDvA0aNHn40/k/PS/v37WbFixcnfly9fzv79+5+w5u6772bv3r28+c1vftpz3XLLLWzatIlNmzYpk3PwbGYCyuXZonulfHSvlJPulXJSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+Uip+NcCh5ioHIG6xOgfg7Xw8w2mNnvAQeAv6AodHCKDhJvAda6+y+7+0bgNcADFGM3/p+nOmeI4qIgIRiGkeeOhQAhMBJSBvoWsm75HJctX0g9itj7yABx33bW9GS8rK8YAUGY73xgJ/shtDwUxQTYyaIIN8hzL4oHag3oH8EHFmCVBqE9TaczzaGxKdI0YjkZSxYsYfXoQlaMDLN66UISS6nWa8y2M0IU0YoSto/PcOTYCebmmnieAY7nKcH2EXwB5hnT0zAxEZHljkcxiackeY7hRWcHz6kd2cGK7DgjA4MsX7mGnp5+BgaHuHB8G1HWIZ8vjug2hMBTHGd6pkWIKrjD7PQsEx0YWL4eGlcAdxCqA9QWrCSjSq3Ww4Klo1y8djVJEmFxhfqCRdR7R+gZWkS9McBLrr2e0dHRc/kzkaeR5zm/9Eu/xP/6X//rGdfefPPNbN68mc2bNyuT59CZZALK5fmie6V8dK+Uk+6VclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5SJwbgUPB4AeM1v3TAu7a3qBw2d6ETOrmdlPmNnXgPuBnweGgSPAb1EUObzF3T/h7ifnL7j7l4AbgRR4yVOe33PcHXfHzLqPgAF1c0JYxNIF4/T0D/DJxjV88uvjjB2ZIq6M87rRFPO8e8FvPfH8kz7/RnCM3HOiOMJqDWj00uwd4PdsDf/U7OPLO4+x4/AEM0cP0j9+gMaJgyydHaN19DCHtj/McDXgc7NEaYvxLKFd72ff+An+6DO3cXhiHPIM4irUGvQNPMzwwgBrr6LdDjxydyDNcrxnkNyNiIz5YgwzGJk+QKO3l0suvJTv++438dbX38hlF1/C0sEeqpWYEEJR1+E5mFHrX8CRw4epJDGVJObo2BEsxORxDcJivHoMaJK3Jpg7so201eQ97z5KrTbFozMwNtdh/Phx3AIbL1hOb0hpNpuMHRs70z8ROcWyZcvYu3fvyd/37dvHsmWPN1aZmppiy5Yt3HDDDaxevZo77riDm266ic2bN78Q2z0vKJNyUi7lo0zKSbmUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpFzkd8Tkc+1VgLfDvgZufYe2vUnzz/5UzuYCZvQ/4EaCfbgkB8EXg/wIfdff06Y5398NmdoinHKVh3bqE+WoFJ89SyHMq3ua63mmqcxHDvQf4RvUCHlqwkRPTI2z68jf57tcbF/YVbSta7uA5ePT4Lk+5xsnnvOggQQgQx5BU8EqVo2kfR9McJpvQibGOYxP7CVmHV1x+DTv278aCwzD0DC2iv1bjYHWQE4MdWhbx2MQEneF+LJ2F+jCs/y4uiQ+z7uJL+IujVfjaEXr+eoa0r0Z7YAF4VhR5hKILRf/UIXqm9jOTZVywaiWXr1mOA5UI9h49ypQbeF6M6+h+ZstWreXBT76fC3oGaUQN7vjabfSOrsJ6+mlOLCIa2k828Ars6G6SAHnzOK9882qyziHuf6BN0jxCvPsxBgeHWbFyBSM9Cb29vWx56FGu3Hjx6f+RyBNce+21bNu2jV27drFs2TI+8IEP8P73v//k6wMDA4yNPV5UcsMNN/A//+f/ZNOmTS/Eds8LyqSclEv5KJNyUi7lpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KRU7HuXR4+P8ovsp/p5n9lpl923gLM6uY2f8A3nnKMWfiX1OMpBgHfg+4xN1f6+4feqZih1N8HbjtqV40i4ofvKjISDspPdWYN/ZN8T0rEy6/qkmwx3h4aD1piNjfs4zdx9fSuXeWZmbkRjEWAi8mV1D83CA9ed7iQgCBLM/JLSqesNB9RBAlUOuBWi/eO4ovvJC8f5RtEyeYimvMLbmEvQsv5pHKMA8ko6SLLud4Msiynhr91qRmORXP6PVZ/IIr8Sjm8g3rCT1DhFUbWJ9m9DX6CHFELc+KbYWiGCPbtYUTB/czPnaEO+7ezJ9/6CP89d//A1+/85scO3yI+x/dxtzcXHGMGYGckM7xb3/lP7L59i/z+U/9A9de/3LSPOLo1s2sXbCPgQUPQlLDG0NUY8jTDndtTtkwO0Tf8g20qyMcOTHJI9t28KnPfp7bvvJ1KtXKkxSMyJmI45j3ve993HjjjVx66aW87W1vY8OGDbz73e/m4x//+Au9vfOSMikn5VI+yqSclEs5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNykdNhp0yBOPODzX6fYsSEA8eAzwK7uy+vAl4PjFB8jf0+d/+FMzz/7RTdHP7O3ZtnvdGncPGlG/yKq17N3//9reR5xuve+N1s2HAVl/e2+a6XvZTq6HI+8v7385FDMd9Y8BLSKCbkOX+0dD8/2DzC3y65nJ/fEpFRdEAgirGi6oHYnE4I4CfbOzCUzvK/Xz7EeF7j3/7Tg2TTx2HyKMyMw9wUzE5Bew46HXCwKGK4v07S6KU1N8N432Lcc6zTYsPCdUwQWFCZZKrdZvfgKnqTiIVVY1syyrq7Pshv/uLP8uN/8GFqs5P87bZvcPNFL2H61W/jqjDBY9u3snPjmwnuLLj9A/TMHgYLDI0upqdWJwoR7k6at0mimBWbXsMHsiWk7jTyJt+/97P89PffxH/5jd9iaHiIt7zlzfzm7/4JyYKV/MrP/CC/+D//jLnZGZKZYyy1E8x1YDJL+NEo5vIVF/JXy9ay/asfoj03RafdJg5GnCRMjE9w1ZUb1GqmZDZt2qRMSki5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUj5nd5e5n1ZrjXEZaAPwi0AR+GVgAvP1b9wZkwG8Dv3amJ3f3l57j/p5Wp91henaGuFIFz4jNeePGVVy8dg21Rcv5/T/+G/5k4gKOjS4lB8ihSsaiqEly/AQssfmNAlZ0iQhAMDqnNM8wiooQN8MdzAyLK1DrhbQNWQfSFkQxRZuI4rweAi1ihho95J4TeY55SgjOruO7eMnqa3hsag7rTGHutKhw1Kp4SJiqDlKrJFR23o0RimMHF9EgZV87pp0X+7b2LMnsccgdt5xjUxOcmJ4hMiOYMTTQR5Z3ODx2jOrIUqLcwY04CpB3WDAyRK3eIEQxNAZ44w0vYd+xaazSoJ6lDLtRpU5cdWbHW3y8NsirDu3iu6t1/nbFJYzve4g4TmjOzTJz4gT5ORTgiIiIiIiIiIiIiIiIiIjI+eOcCh7cPQd+1cz+BPgJ4GXAYorv9w9RjJO41d13nOtGnwtmxsMP30ujrwHAFcsXcMHa1dA/wv97y9/w4YlhxvqWnZxKgTueZ0zMzJFPz5C0mzj1+bNRvO3HOzoUYyvmp1oYbkaeZVgExDFU6lDvg6yN5RmkKZ51IPfiLEmFJASGfY4lvVWIIzKrgGccmz6OTz1KlR7Szix9+RwnwhBzoY5jTLQypqeniZpTZM05pvKUAZ/FaLHTawymKeY5oTWN5SlRCBACI4uGydKMyRMz4E6eZwB02i16zZkF8Jw4BNwz1i5fxEw7x3CSSoXXvfQKfu3/fJA4TxlkhstWL8S6n8Gy2Rb3bN3Pf+ik/Omjm9l36bXcc9FVRNOHaDabzM3N0umc7qQSERERERERERERERERERE5n51rhwcA3H0bZ9HB4YVmwajW6iStCletW8VP/sgP04rq/Lf/9pt8YuQGQpIU6+Bk0UObwNbpjLbnRDOz4DVOLiIvRlt4TGxFawsHum0dwBwzJ8KL0RchxixQS9sMMUdccZw+rBoz0NtDb9WwSoVxamzvBPIsYGkbspSON4hz52CWsiJt0j++l5m5Dl5p4EmMT4/z1a/dTtqaJXXn7jzn4N23sXywnxWhwpEje6nc+Y8k7RlizwgWMzA4yGjfEBPNgzRnnXbTMc+JQkSjNc1FNkcrOBnT9EcQRQlLly3jwJHjnJia45ILL2Cq2eHI2AmG5sZ4w7VrqVei4u2HQBQCy5Yu4wv3PcZ7pmf4b7se4sQVryBZuYQFPUUxSJ7nfPOubz7ffwoiIiIiIiIiIiIiIiIiIvIi86wUPDzXzOwK4F3AK4DlQM/TLHd3P633ZWbEccyqhaP85194FyemmvzZn72P+3YfxYba9DJLbn00PTCXOtad0HH/TMKUQZiaxLJeggUsBIIFwMjyNt59rrgQuDvkKZ7nRDEkASohh+ZxXhId5ZILlpFmsPvIGONzUxzvpOyaSJkLhltajMvIM6reYjC0qcQVeqxB7+RBlvUbD01PU5k7QFKp0mm3yY/s4f0f3Ear3SGY8Vf9I8SNXoJnLBmos3j9pSQhZnw85WgTHCeOY7I0ozmT0r9kgOO7p4quFsCIT/E98WN00pQ06TCRxMRxhd5ahaPjk/zT332GH3rr6/mTD/wj/Z1xfvR7rmN4uA+D4nNzp5NnrFi2mEatwie+eh//t5nyE3sf5Y+uejUrRpw1AxDFsQoeRERERERERERERERERETkGZW+4MHM/g3wO0DE4/Minq1z8+qXfRc3Xb+OgVqFO778Ca5e009P1OKDn/9jmq1ZKnHCysE6zU5GRDH2YaanytErLmF47yOsu/MD5DgeYiwKYBFZnhOimCSOaeVOiwgDqkkCV/4USZaz6Bt/TV8V9u3Zy0OdNkte9VKmJmeYHjvMvl07cDP6LTAQIkKcEJlBCDSSiMVDDdI0sKxSZ8WI8dju/YxkOVetWU2j4Rw5cpSd1ZxWtY88b1OPjTnvUEnbDI8f5BWXLiXLnCiOuWs65VgIBKwo2Mhzpo7NESY6YKH7OQVmZmfJW9MEBzptcgcwHnx4G3u33MP3X7KUqa2bObZjN2+/4QoWDPaSpTlJkhAnEVEUkec5Brz06vUsHOrl1o99iUuiE1zbegjPV1OJe5mvEREREREREREREREREREREXk651zwYGZ9wPcAG4FhIHma5e7u7zyDc18H/H731z8EPgF8EjgOvA1YDLwO+GFgEvgF4ODpnt/d+eEffDMjTPLglgd5dGwWc6eTDLKgdhir91OPjbWL+pmea+FAlkMSJ+yPEpZVqqwZrJJmGWYQouLjbHcAS8E7EDmVSgJuxBXwToe+3jpvuXSUKMCDocXsXIfJExPEcWBkcIDRTZuwYIQQEccJUfdnM8CM0K0KGD92nGxujrWrVlJv1OkdGGRqappWO+WCNWuZmp4hG0jo6+vj4YcfoVZLWDg6xHBvgxAiUnc6nQ5xMILnjB89zPH9+wiNHjxzojiQRDEhGK3mHPt37oQo0OjtA4dOa5qYlB955RquWdug3qjw+suvZYwh8jwnbXcIwSB3LKIoqDDIspw1a1bxk9/zMlazh+uuHGVo1WoeOuLsPzZ7uvGJiIiIiIiIiIiIiIiIiMh57JwKHszsJykKEnpPffpJlnr3eQdOu+CBooDBgN9z91/qXhOg7e5f6K55v5n9b+DTwH8Drj7dk7s7f/dXf8WP3fQqbtuyg/v2HMeihBDFLFp7KXFcJfOcMTNoPP4ucuBI7wBXrF7JwsnA0ZkZwIiimGBQ634K7jBQjRjpqxNHgSgEIjMqSUL/wmWY51w/vAjPc4IZ7jkO5O7gEEIgREYSxWDFQA3cSXOnk6YM9fTQnmuyaMlCGo06cVIhCoGrL11HEkeYO7nnZFnGm254Oe1OSn9/P/VqBYsi3Ix2mhGbkWUZc60mIc8ZWbiImVYLzIhCEaeHwMDgIMEg7XTwNGdu4ig/8orFJLOB6elp4mo/9WrCoV0HsDgiskCSJIQQiDsRForfkygm5G0uGa1y8YJ1dDxm346tZD5M8NoZ/HmIiIiIiIiIiIiIiIiIiMj56qwLHszsRuBPKQoSmsDtwAEgfXa2BsDLKcoMfv9bnn9CUYW732tmPw98APgV4N2nc/I4irBGH5PT05yYniO3gDnkWUaeOa1OCha63RXs5L8EyOt1KpddzE1JLx+67W7mOilmAQuG4cV6M4b7Gwz195BExuTkNOZAntPT6CVrzxKZEYVAkjwehZnhDmYQB+teO5DEMWaGYXSyFLeie0IOtDudosIiz4kMkjgmiiLiJCaOIkIIOEaIItwgy525dptWu110YKAosPC0Q95pYRbotpTAPSfNA72DA5g77VaLmROT1PtHuOOurzM7foyJ6SarRo1O0iRNEyyLSC3Q7nZ5sO77BMhbsywNY8RRzIHxOlN5IE2GqPY2SKqln7IiIiIiIiIiIiIiIiIiIiIlcC7fLv97isKD24HvdfexZ2dLT7AIaLn77lOey+k2UfgWHwU6wPdzmgUPaZox22ry6M6DvPLStczcv52pdloUNViAkwUMxRf2DuAQGfQmEQf27+fqi1dw4crFfPWerXxz+x46/njxQMBZNjpInqUcHTvK0WPjHD58lP6+HlatWEqtd4jIAnmeEUcRURQRokDULawoulk4eZ4R8hzP825RRaAR6oQ4AgyzQO6Oe158QHnR1aHdbpN3OnTSrOiskCQYTp7mkOd4s0273aYoawDvXrPTahFqPYQQFSMpHNIsxzEGeuo0k4Tp2Ra5xYys3ciS4ATPyboFIssqlW6BBaRpSid3sjwrijiATrtF1llEEgemOikpRhRFeJ6RtvOz+kMREREREREREREREREREZHzy7kUPFxD0X3hJ5+jYgeA2e41TjUF9JtZ1d1b80+6e8fMZoFVp3tyd+exxw4wMztD/+AIAwtGGewWGxQFBE7c7aqQZRkhREX3hzxj855j3L/nKEP9jzLQ00NqMX2NOln33Ekcs6A3YXiwj2PHjrNr914sFMUMff0NHOjt6yMJEWZOwMjzHNyJ44g4joniiGABDwHPvejgQFFQ4XmGdZ93HCwi95wQAjjknpN2UjAIOHnWXe/g1m2Rkaf0V2OmpiZwM4Ibued0mk0q1TqxgWc5eE6IImpR4IH7txAqdRYuXMTD92/BPOWitSvIW20wI8ty8iwjRBGVOMbdu0UjkHeLHjzPCCEUhRYGdD/rNMtop9mTZiUiIiIiIiIiIiIiIiIiInKqcyl4iIFpd9/2bG3mSewHLjGz2N3nR2XsAK4CrgW+Or/QzJYCAxRFEqclSRJufte7qNarbN+5m927dxSdGULRRSGEgHtRb5F7XnR6gO7DCWbMRjHN7trhkRpxFMiylLTTYuFQL8Gd9twcq5YvZ3qujbtTqdZwnHq1SiWpdLsoFB0a0jTFoNvxwEnJCLkTxTFOMYYjimMsGKE7diLP86JQoZMSQiDPc9IsI44TrDsbI3LHc6fZmqPZSZmYnOLgoSPUsg5JlhOSChNjh8g6bfpWNEimx8nnZmksXsKCJcsYbFQYHmiwZvli5nJj4XAvcRzR7gQmJqYZHhwgqSTk3YKHNMtoddpEFhGHmCxPcULx4cWBLAf3vCjYcO921YiJEo20EBERERERERERERERERGRZ3Yu3y7vAC42s8jdn6v/W/7DwAbgcuCe7nNfAq4G3m1mN7l708wqwP/uvv7A6Z48TTssWriAKIk5dOgwS5csIe5+4R7M8NxJKhWyvBizEEIAwMyIzAhR8bt7TlT8RJ5lZFnG7MRxBvr6aLdadNKMNSuWMtfOiJOYNM3p7+unlWXEiZ8cU+FuJHFCFEXgebe1hRHmr11MuCDLMrJOjpkVXSfyrNtVIYDnmDsBqHS7U4AVXRbM6O3tIU1TFi5cyEXrLuD6a69mttkic4gj48jR41QqFRYvWUQtCsRRwKKItJNSSRIGB4cJZmR50f0iTTtkWU6rOUdzrgmek6UZdEdhtNIWtVqNKI5I0xTPc+JgpFnW3VcxgsPMyHPvtnwQERERERERERERERERERF5eudS8PDXwHuBNwL/9Oxs59t8Bvgh4C08XvDwf4B3Aa8F9pnZo8BFwDDF+Iv3ne7Jm80Wd91zHxYM9wwzK4oPuoUFmJNmKeZOu90pOhjkOXEUAUbaKYodgjkDQwNUKzFRFNNqNWlXnLiSUKtVuOrKjVgoigeCdYskcLIsJwqGd0dQmAPkpJ28O96i2IbnOYYz12xSrVSwbvGD++PdJvLu4I8QRXTSDp4X5zCs6FhhRhRH5A5pp02wogAimFFLIvIsJ05iViwcLs44N8tMnpN1OuQ4zXaHYIFOp02r0yHPnBBH5GnKkbET1CoVCIFOu8XUxCRxEtOoVknqNXp7++jp7aXZanJg/z7SNMMwKrUq7lCNumM7nJMdNURERERERERERERERERERJ7OuRQ8/B7wA8Afmtmjz9Foi48Ay4ED80+4+y4z+2HgzymKHF7afSkHftvd/+Z0T54kEf09UfHlPxFYpVscADh00pQsy3GMvnqDKBhRFIrxE3lOmjuVpAJZh1VLh5mcnCbLOnTyFkePHwf37hgMx4Asy8nzjLTTJo4iMoDccTPazRZp2sGiGMfIvegq4TnkeUYnTXHPSEIxxiLLnTzPqVUrzM01yfOMKI4JOFmW0U79ZGeKqDuiY74IIo5j4jjQbneKbhBRIM9yoigQRzFZJyUKRjtLMTOcQKfdxN3J3clyJzIjB8ydvFtUkbnjWUqeO1EUiGZmcHfm5poEC0RRRKfTIqfo4hCiCPfivUYhAoMorpzTH4yIiIiIiIiIiIiIiIiIiJwfzqXg4R3AXwH/FbjPzD4MfAOYerqD3P0vT/cC7j4OvOdJnv+omX0ZeBOwApgAPuPu20979wAY9997D0kc4UAn7RCsGBERQiDPnRwIFpHlKZ5nRAZpmpFnKYuXLKbR6CWkGVMTx0mzDp12i/5GHU8T9h7cR3//EAcPPFYUShCo12pMTU/hWQY4mVsx5qKTkmUZFkV0KwlI04zenj7m5mbpZClLhobYNzH++GiLPMVzJ4pjsjQliiLiKKKTpuRejIoo3mbAPcfznE7mDA8NMT01TrVWwywi7cySZymVSoy5sbxRZ9Aids82OZ6mLF64lonpvWRZikUxaZZTq8b01nuZnp0ldD+/alIhjqOim0QUFaM+QsRAt8Ch6E5h3TEbTpwkmAWq1QqVJMbdqVZrbHnw3jOLUUREREREREREREREREREzjvnUvBwK8XEBSi+gv+R7uPpOHDaBQ9PeyL34xRjNc7aY7t2jP3e7/727mdjP/Lsueaaa655ofcgIiIiIiIiIiIiIiIiIiLlFs7h2D2nPHZ/y+9P9dh7Lpt9OmY2YGZ3m9ldp3uMu4+6+yY9zu4B/BrQBwwCH36S198PNIAKRReOHzjN88o5+NSnPsXFF1/MunXreO973/ttr//O7/wO69evZ+PGjbz2ta9l927V/DzXlEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmXclIu5aNMykm5lI8yKSflUj7KpJyUizwjd/+OeAAjFMMgshd6L+fDA4iAHcBaioKG+4D137Lm1UCj+/PPAX93Oue+5pprXM5Omqa+du1a37Fjh7daLd+4caM/+OCDT1jzhS98wWdmZtzd/Q//8A/9bW972zOeV5mcvecqE3flci50r5SP7pVy0r1SPrpXykn3SvnoXikn3Svlo3ulnHSvlJNyKR9lUk7KpXyUSTkpl/JRJuWkXM4fwGY/y++tz6XDg5zfXgJsd/ed7t4GPgB876kL3P2L7j7b/fUOYPnzvMfzzp133sm6detYu3YtlUqFt7/97XzsYx97wppXv/rVNBoNAK6//nr27dv3Qmz1vKFMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSTcikfZVJOyqV8lEk5KZfyUSblpFzkdDxvBQ9mdr2ZvfL5up4855bxxBEl+7rPPZV3Av/8nO5I2L9/PytWrDj5+/Lly9m/f/9Trv/TP/1T3vjGNz4fWztvKZNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpFzkd8ekuNLMcOOju3/altpn9LtDv7u98mlN8FBg9k2vKdwYz+1FgE/Cqp1lzM3AzwMqVK5+nnZ3f/vqv/5rNmzfz5S9/+Ulfv+WWW7jlllsAOHr06PO5tfPWM2UCyuWFoHulfHSvlJPulfLRvVJOulfKR/dKOeleKR/dK+Wke6WclEv5KJNyUi7lo0zKSbmUjzIpJ+Vy/jrTDg/2FM+/HfjJczheXnz2AytO+X1597knMLPXAf8ZuMndW091Mne/xd03ufum0dHRZ32z54tly5axd+/jjTf27dvHsmXf3njjc5/7HL/5m7/Jxz/+carV6pOe6+abb2bz5s1s3rwZZXL2ns1MQLk8W3SvlI/ulXLSvVI+ulfKSfdK+eheKSfdK+Wje6WcdK+Uk3IpH2VSTsqlfJRJOSmX8lEm5aRc5LS4+2k9gBw48BSvHQSyZzj+GdecywMY6e7xObuGHk/4vGNgJ7AGqAD3ARu+Zc1VwA7gwjM59zXXXONydjqdjq9Zs8Z37tzprVbLN27c6Fu2bHnCmrvvvtvXrl3rW7duPe3zKpOz91xl4q5czoXulfLRvVJOulfKR/dKOeleKR/dK+Wke6V8dK+Uk+6VclIu5aNMykm5lI8yKSflUj7KpJyUy/kD2Oxn+b31mXZ4EAHA3VPg3wCfBh4GPujuD5rZfzWzm7rLfhvoBT5kZvea2cdfoO2eN+I45n3vex833ngjl156KW9729vYsGED7373u/n4x4uP/1d+5VeYnp7mh37oh7jyyiu56aabnuGsci6USTkpl/JRJuWkXMpHmZSTcikfZVJOyqV8lEk5KZdyUi7lo0zKSbmUjzIpJ+VSPsqknJSLnA4rCiZOY6FZDhxy96VP8tpBYKG7R09z/DOuORdmNgIcBfy5uoY8PzZt2uSbN29+obchp9i0aRPKpHyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+ZjZXe6+6WyOjZ/tzZwLM8te6D2IiIiIiIiIiIiIiIiIiIhI+ZWq4AGwF3oDIiIiIiIiIiIiIiIiIiIiUn5lK3h4zwu9ARERERERERERERERERERESm/UhU8uLsKHkREREREREREREREREREROQZnWnBwyIzy57qxad7jWJchZ/h9URERERERERERERERERERES+zZkWPNhzsgsRERERERERERERERERERGRM3AmBQ8aNyEiIiIiIiIiIiIiIiIiIiKlcNoFD+6uggcREREREREREREREREREREphfBCb0BERERERERERERERERERETkTKngQURERERERERERERERERERF50VPAgIiIiIiIiIiIiIiIiIiIiLzoqeBAREREREREREREREREREZEXHRU8iIiIiIiIiMj/n73/DpPkuu77//e5VdVpenLYMLMRCyywCyzSIjKBCRBJEaQSBZIKpGTBsiHLliWbVqItybJp62dJlCh+JVBUoCQmMQigCGYABAPSIi8WwOYws2ly7FR1z++P6lksQITZXMSeF5/iTHffqrrdn7l4Hjx9cK4xxhhjjDHGGGPMDx0reDDGGGOMMcYYY4wxxhhjjDHGGGPMDx0reDDGGGOMMcYYY4wxxhhjjDHGGGPMDx0reDDGGGOMMcYYY4wxxhhjjDHGGGPMDx0reDDGGGOMMcYYY4wxxhhjjDHGGGPMDx0reDDHTUR+RESeEZHtIvLfXuD1vIh8pvn6/SKy8gxM86zz1a9+lbVr17JmzRo+9KEP/cDrtVqNn/7pn2bNmjVcddVV7N69+/RP8ixjmWST5ZI9lkk2WS7ZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WS/ZYJtlkuWSPZZJNlkv2WCbZZLmYl2MFD+a4iEgA/AXwFmAd8G4RWfe8Yb8IjKvqGuBPgP9zemd59kmShFtuuYWvfOUrbNmyhU996lNs2bLlOWM+/vGP09nZyfbt2/m1X/s1PvCBD5yh2Z4dLJNsslyyxzLJJsslmyyX7LFMsslyyR7LJJssl+yxTLLJcskeyySbLJfssUyyyXLJHsskmywXsxBW8GCO15XAdlXdqap14NPAO5435h3A3zd//xzwRhGR0zjHs84DDzzAmjVrWL16NblcjptuuonbbrvtOWNuu+02fv7nfx6An/zJn+Rb3/oWqnompntWsEyyyXLJHsskmyyXbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJssleyyTbLJczEJYwYM5Xv3AShE5LCKbgcHmc88f80sish14GKgA3ad3mmeX3/7t3+aee+7hwgsvBGBgYIChoaEjr6sqmzZt4t3vfjcbNmzg8ccfp729ndHR0TM15Ve8oaEhdu3aRV9fHxdeeOEPZAIwODjIxz72MdasWcNll11GoVCwTE4xWyvZY2slm2ytZJPlkj2WSTZZLtljmWST5ZI9lkk2WS7ZY/8emU22VrLH1ko22VrJHlsr2WRrxSyEWIWLOR4i8pPA+4APAp8g3a7iKlX9laPG7AZ2Am8ErgLuBgZUdeQFrnczcHPz4YXA5lM3+9OmB/iB93qKLQFKQAF4EugCysDe5uvtwGrSzzcHLANC4Gkgft61eoDe5u8l4KFTOfHT6HTn0kla6LMfWAUc4LmZAFwE1ICtQAuwFnicH8wEXpm52FrJJlsr2WNrJZssl+yxTLLJcskeyySbLJfssUyyyXLJph/mf4+0TE4eWysvz9ZK9thaySZbK9ljayWbzkQup8JaVW09rjNV1Q47jvkArgG+Bqwk/YfIbwK/+bwx+4APNn8PSf/BsmQB1950pt/fSfqMTvv7aObybWBz8/FzcgH+CngMuKb5+BlglGbx00tcd/ZMf54/rLmc4rXyisjF1ko2D1sr2TtsrWTzsFyyd1gm2Twsl+wdlkk2D8sle4dlks3Dcsnmcbpz4RT9e6RlclJysbWSoVxsrWQvk6NysbWSoVxsrWQvk6NysbWSsVyy9j6sw4M5LiISklaw/RzpP0xi4D2q+uRRY54AdqjqO0XkJuDDwNtUddMLXO9Ih4eWlpbLzz///NPwLl6ZarUa27dvZ/369T/w2vbt21m8eDHlchmArVu30t/fT0tLyw+MHR4eZmQkLQgTESyTE2O5ZI9lkk2WS/ZYJtlkuWSPZZJNlkv2WCbZZLlkj2WSTZZLNp2MXCyTk8vWSjbZWskeWyvZZGsle2ytnB0eeuihWFWj4zr5TFdr2PHDewBvJd2yogb8dvO53wdubP5+B3AnsB14APgesPHlrnv55ZerOX67du3S9evXv+Brb3vb2/Q73/nOkcdveMMb9MEHH3zZa1omJ85yyR7LJJssl+yxTLLJcskeyySbLJfssUyyyXLJHsskmyyXbDrZuVgmJ87WSjbZWskeWyvZZGsle2ytnB04ga4b4QkWW5izmKreISJvAP5VVf+w+dwHjxqyD7hbVT8FICLPAEOnf6ZmXn9/P/v27TvyeHBwkP7+/jM4IwOWSxZZJtlkuWSPZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZJPlkj2WSTZZLtljmWST5ZI9lskryvDxnuhO5iyMeZ7bgZ+T1NXApKoeONOTOpvdeOONfOITn0BVue+++2hvb2fJkiVnelpnPcsleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslyyyXLJHsskmyyX7LFMsslyyR7L5BVl5HhPtA4P5riJyKeA64AeERkE/jsQAajqX5JuafFW0i0t5oD3n5mZnj3e/e53c/fddzMyMsLAwAC/93u/R6PRAOCXf/mXeetb38odd9zBmjVrKJVK/O3f/u0ZnvHZwXLJHsskmyyX7LFMsslyyR7LJJssl+yxTLLJcskeyySbLJdsslyyxzLJJssleyyTbLJcsscyMQsh6ZYYxpxeIvIjwIeBAPhrVf3Q/GsbN27UTZs2nbG5mR+0ceNGLJPssVyyxzLJJssleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJssleyyTbLJcskdEHlLVjSIipN8hv5X0P6h/n6o+/FLn2pYW5rQTkQD4C+AtwDrg3SKy7szOyhhjjDHGGGOMMcYYY4wxxhhjzBn0FuDc5nEz8P+93AlW8GDOhCuB7aq6U1XrwKeBd5zhORljjDHGGGOMMcYYY4wxxhhjjDlz3gF8QlP3AR0isuSlTrCCB3Mm9AP7jno82HzOGGOMMcYYY4wxxhhjjDHGGGPM2emYv0e2ggdjjDHGGGOMMcYYY4wxxhhjjDHG/NCxggdzJgwBy456PNB8zhhjjDHGGGOMMcYYY4wxxhhjzNnpmL9HtoIHcyY8CJwrIqtEJAfcBNx+hudkjDHGGGOMMcYYY4wxxhhjjDHmzLkd+DlJXQ1MquqBlzrBCh7MaaeqMfArwNeAp4DPquqTIvL7InLjmZ2dMcYYY4wxxhhjjDHGGGOMMcaY06i3+fMOYCewHfgY8O9f7sTwFE7KmBelqneQ/sEe/dwHATZu3HhG5mSMMcYYY4wxxhhjjDHGGGOMMea0GwZQVQVuOZYTrcODMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37oWMGDMcYYY4wxxhhjjDHGGGOMMcYYY37ohGd6AieLiOSAmwBU9RNneDrGGGOMMcYYY4wxxhhjjDHGGGOMOYVeMQUPQCvwd4AHrODBGGOMMcYYY4wxxhhjjDHGGGOMeQU7LVtaiMjO5rHjdNzuNNzDACLyIyLyjIhsF5H/9gKvLxeRu0TkERF5XETeeibmebb56le/ytq1a1mzZg0f+tCHfuD1vXv38vrXv55LL72UDRs2cMcdd5yBWZ5dLJNsslyyxzLJJsslmyyX7LFMsslyyR7LJJssl+yxTLLJcskeyySbLJfssUyyyXLJHsskmywX87JU9ZQfpF0XPJCcwnt0n+p72PGczzsAdgCrgRzwGLDueWNuBf5d8/d1wO6FXPvyyy9Xc3ziONbVq1frjh07tFar6YYNG/TJJ598zphf+qVf0o9+9KOqqvrkk0/qihUrXva6lsnxO1WZqFouJ8LWSvbYWskmWyvZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WS/ZYJtlkuWSPZZJNlkv2WCbZZLmcPYBNepzfW5+WDg/APcC3mz9flIi89ngP4NrT8k7MvCuB7aq6U1XrwKeBdzxvjAJtzd/bgf2ncX5npQceeIA1a9awevVqcrkcN910E7fddttzxogIU1NTAExOTrJ06dIzMdWzhmWSTZZL9lgm2WS5ZJPlkj2WSTZZLtljmWST5ZI9lkk2WS7ZY5lkk+WSPZZJNlku2WOZZJPlYhYiPB03UdXrFjj0btIvyU329QP7jno8CFz1vDH/A/i6iPwHoAV404tdTERuBm4GWL58+Umd6NlkaGiIZcuWHXk8MDDA/fff/5wx/+N//A+uv/56/vzP/5zZ2Vm++c1vvuC1br31Vm699VYAhoeHT92kX+FOZiZguZwstlayx9ZKNtlaySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJssleyyTbLJcsscyySbLxSzE6erwcKzkOA+TLe8G/k5VB4C3Av8gIi/4N6eqt6rqRlXd2Nvbe1onebb51Kc+xfve9z4GBwe54447+Nmf/Vm89z8w7uabb2bTpk1s2rQJy+TUWmgmYLmcTrZWssfWSjbZWskmyyV7LJNsslyyxzLJJssleyyTbLJcsscyySbLJXssk2yyXLLHMskmy8VkreBhrPnz3wCrjvG4/HRP9iw3BCw76vFA87mj/SLwWQBVvRcoAD2nZXZnqf7+fvbte7bxxuDgIP39/c8Z8/GPf5x3vetdAFxzzTVUq1VGRkZO6zzPJpZJNlku2WOZZJPlkk2WS/ZYJtlkuWSPZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZI9lkk2Wi1mI4y54EBEvIs//gvulxu8Skfhlhj3c/LlEVfccywHsPd73Yo7Lg8C5IrJKRHLATcDtzxuzF3gjgIhcQFrwYD1iTqErrriCbdu2sWvXLur1Op/+9Ke58cYbnzNm+fLlfOtb3wLgqaeeolqtWiXbKWSZZJPlkj2WSTZZLtlkuWSPZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WS/ZYJtlkuZgFUdXjOgAP7D+G8buA5GXG/O/mdb9wHPPpbp77kvew4+QdpNtUbAV2AL/dfO73gRubv68Dvgc8BjwKXL+Q615++eVqjt+Xv/xlPffcc3X16tX6P//n/1RV1d/93d/V2267TVVVn3zySb322mt1w4YNevHFF+vXvva1l72mZXJiTkUmqpbLibK1kj22VrLJ1ko2WS7ZY5lkk+WSPZZJNlku2WOZZJPlkj2WSTZZLtljmWST5ZI9lkk2WS5nB2CTHud31pKef+xExAMHVXXpAscPAX2qGr3EmJ8CPgPsVdWVxzifbtLuAaqqwULOyeUK2mjUjjyOchH5YomZqSkQB8U2QEDk2ZNUQUifV5q/N59/qXsFjlIhYnFPNxMTEwxPzZC4cEHnOoEwcKgqXtPhqoqKNCeg8x/CC1/g6Hke/ZzqD76oHvF1XBAQuAARyDtHqaWF6UqdQj7H6MwcXcUci7o72bV7H9ValdAJfX29TE6MU5mbQ0SaH53DuQABwijC+4S40cAjEISICEEQ0NrSQrVSoZYkbDj/PDZt2vSSn4k5vTZu3GiZZJDlkj2WSTZZLtljmWST5ZI9lkk2WS7ZY5lkk+WSPZZJNlku2WOZZJPlkj2WSTZZLtljmWST5ZI9IvKQqm48nnPDkz2ZFyIiHUAfMP4yQ+8Bfg9QERE9tmqMMWDVscyrWGqhMflswUPP4kVccPGlfPurXyfJleDStyEKmiukA7x/tjjhOcUOQtpc4kWo0gDOW9XLn3/gl/ni577AX397E6MtPWmnhCQB9ekF54spEn/k+svaC9z8mvMIwwhxAbFCrZEw1/DMVOtMVhuMz9WYqSdMVxvM1GNm6gm12FNrxMSJJ0HSIgNAxSGaoPUaxM03IgKBINVp8jNDlFpbKba1U3SwprXERZdczpcf2c2rL17Hx+55iLdcOMB/es/b+dl/9xs8vX0r3a0Ffu0//ns+9fd/yyOPPIzm8kgYQZKgcYMoDOhdMoBzwp6dO/Fxg1CE9q5e3v6Od/LYw5t49KFNOHfcu6wYY4wxxhhjjDHGGGOMMcYYY4w5iyy44EFENgCXPO/pooj83EudBnQAPwk44JGXuoeqHiIteDhmzeKIPcd+5rMdElwQEEW5I0+LC9KX5jsxiJ9vr8BzWyZos+jhB2bVLIwQFE0LDUhrGVwQQhA1O0a4tOBBm+e4AAI90rghyuUpl8uEQUgYBjjnENyRe6iSFgqoJ/EJIg7EESvMVWvM1hpUG8p0LWaq1mCqljAxPcumXQeZrjaa70XS+zppzpd0zgpBEBIEIUvKRbpKRcSFSHMc4sAFBGFIGEUQhLh8CfExVCs4lEKxSO+iRYzOVWlp62TRkkWMHjpMoVjkDW++nsce3sTmxx4ll8sTFluOPUJjjDHGGGOMMcYYY4wxxhhjjDFnnWPp8PBjwAef91wb8LcLOHe+quCPj+F+p5w8b0sIESEIIwRJXwujtLbBNXfI0OcVJswXPaiStoI46nLCkevOPxbnAKXqhUQcOl/w4FzaPcI3u0S4oHmfdPuMKIwohBGHv3kPYRTRtv58wrZW5nbvI7+kj1oQUCgWKZYKSOIIgoAwTLeLaCsW8N7jggAnaZGCOKEyV2XXoXGmax4kSIsXnANcc57znw84l75+8NABOG8Z4gI0SYjrcXpuEBEEAYFz+HoNqVeJooh8S5lCIU9vXy+Tk1MUkgZ+coS2zk462rtYv/58dm3fyt49e2ht70AQ3HzBiTHGGGOMMcYYY4wxxhhjjDHGGPMSjqXgYQLYe9TjFaT7OAy+xDkemAI2A7eq6neOdYKnlhx1aPqFezD/5f9RHRiC5sek2tzWwh91fvP5o4sbnrMrgx4pkEg7LwheAkLh2UIK70AbzfOanRbUHblmlMsT4Zi653u0X7KeoU88gjYS8n1d1Fcs5+/uvJP29g7ecP0bueraqwmDgEc3PULvoj4GVi7D+bSIYX67COccLopouDB9n8154RziAkSE0DmiIADv02IGoJU5HA4XRPi4Qa1WxaMQRgRhiAg0koQkUZK4QuCg3NvF3n1DzM1MEXT2QVigPjbNO298K5sff4THH38SH9chDHFJAgjLlvSc7KCNMcYYY4wxxhhjjDHGGGOMMca8wiy44EFVPwx8eP6xiHhgWFVXnYqJnRYCaU3GUR0e5osQxKUFACqoC57t4iCuua2F59mCh2YBRLMjwwvfR3EiCOBdQEBC2kDBpbthzBc5iKRdE44UVUAQRoQuIESo7thL1FYiHpnk3F/5ZQ4dHqb84P28/cfezm2f/xfmZmZJEmVs9DAtu1rwCsXWNvK5iHwuInCOXD5HEAR40iIIbW6BgQsgaeAaNaQeEdRjQjyaJNQJGPNpl4hcVECCkEKxiIT5Ix0e4riBesU5oaW1g8WLetm3d5Ak8ahCPD1FS6vyxje8lgfuu5dcsUipVGByvAokqOqRogxjjDHGGGOMMcYYY4wxxhhjjDHmpRxLh4fn+z1g5mRN5EyQ51UniBPCMAAUFUk7MpBuRaHzRQ5HdsCY3+YCUGk+92zxBPPbZczfQj1BkF4vJi14SIsn0pngwvRccelj33xehCAXpcUYUZ7OSzcws20H1BtU9wyRyPz+GcLI6DCPPPQQq9as4emnt4FXxucaVIudiEBE+v7KLUXa2tpYppO01EeZqddpeCWOG9RnxtFigThwVFDyIrgwRBHy+SJT9YRSPiIKc0gQpN0vwojABXjv8aq0dnTQ0dHOnn0H8KRjxHlaSwXeeN2reOyJLezctpViscTFl13GYw89SKVSPbKVhjHGGGOMMcYYY4wxxhhjjDHGGPNyTqTg4S6gvtDBInIlUFDVe07gnifZUVtRkHZ4SDsMaHOLhyDdkcKFabGDnz9HnnuuNAse1D17uflCBDe/ZUZAFKZf6HsXEqEQuHQ3DPE8Zx8MBZw7UjQRhiFRucyS9/4U5XNW4draCEtFDv7r1whedQWlUok7vnQHP/aTP8FTm7cwXVe6+1fiVGnEnurIEF6hXqkiTmhra6fnwvXsGzpAbWgrQVwjWHYhEy39EAtRfZzEBUTNbg35XJ4wlycQmPWOtlIJDTyCoEEEQUQYOvK5HPligba2Vgb3DZL45ueoQrGQ59WvvoZHH9vMtp27IY5xUuGJxzZz6RVXc/9991Kr1Z/T2cIYY4wxxhhjjDHGGGOMMcYYY4x5MSdS8HA3cADoX+D4zwDLTvCeJ5XMd2E4akuLI1squABckH6p3+z0kBYxNLe2UHnul/PS/HJ/ntLs1sCRL/2jZvcIgpAwSLfMwOuzxQ3z3R5EwDe7SSBELiDM5wlWrSHJ5QgvvpxCMY+suYB8Ic8t511AvVan1FLi0os3cvu37uaclZ0sb8lTaTQYjT00u1R4hYnpGSaqDeKBdSQe+nSaoLeXToSKKzEyWcHlciRhgIhDwgjE4cKQsUpMezGPSC19m0EILiTKhQRRSBLHDA3tx6umb8l7WlpaeMPrX8tjjz3O3sGh9D03P7PJiVG2bd3Bxiuu4r57v0eSJKcgaWOMMcYYY4wxxhhjjDHGGGOMMa80J1p8IC8/5ITGn2KSfinf/P7dOUcYuHSriyAAceh8AQIBOBDvm3UJ890Lmic/pzNB8xyRZ7fNEMgFYfO1AAlCkBAkbj7n0m4QLmhunfHstcPA0WgkBEGAeiUMw3S7DRfgFXJRRBiGeC+0lNvI50tc3tvG25f3MdfwfGL3YWq5HC2lIupj3OGARIS26YMc3rOZqc4uSrqbRpxQ8QnkC+AciUAg7kghh1MYq9ToaGkBaqj3R95LLgqJohxTE5P4JP0sFGhrb+MNr7+Ohx56mMHBofRjcYIqzWISOHxokI6OTq666hruu+/eUxm4McYYY4wxxhhjjDHGGGOMMcaYV4jT2W2hBWicxvu9LOeEltYicRwTBAG5XIRzAYVijiAXUlePd1GzMAFQh4rnyL4V6tOiBNVnuznMF1FIkA458n+eQhQBgroA39wKIt3K4kjFRXodLxC4tIsEnjAIiHI5OnoiROSoRhIyf0cCEQQljmNUPZf2dhAEEZETNizuZGcDKo242cFCiPIFGlMjqBMaScz09BSNuEEtDHH5EkJa0+Ec+EaDyvQkgSiz9YRzewuElRkUyOVydAYNSkHA7ORkOh9VVIT29jZuuOHN3Hvv/Qzu25e+5hyqHkHxOv9ZKluf2cwVV76aCy64ALAuD8YYY4wxxhhjjDHGGGOMMcYYY17aaSl4EJG1QA8weDrut2ACYRgSuLTrQOBc+jMMCEOIfQ0NIzRIixfQoNl14ahCh/lihfkLIs1njnpePSBEUXNLCxcg3uMEEpd2fGi2PkivoUk6TgRwBGGICxza3ApibHgc733akSIMceJoKRdpay8TxzEkCQ0fUBXBi3JOucTTh6cIgqD5/kKCKKKYiwjzRXK5PA2vxD7dbSIUUEnfRy6pU5kYZtf4YdZ2dNHbX2T1kjyHDwUEoePHrziHx8MxJkYOMz4xycUbLiAQKLaUufKqK9i+dSulfMR5567GOUcQ5QjDCHGOwDkacUzsE+JGzMjIAdauu4gDu586tbkbY4wxxhhjjDHGGGOMMcYYY4z5obfgggcReQfwjuc93S4if/NSpwEdwGtIKwC+cyyTO+raf6Cqu47l3AXRtMtDQo5Go4GSdiAIw4BYhLAySiEQ5qIWVBXU40RwIngVElyzvEHTdyeS/trc3kJ82slAm0USwZGtHBTiBkGjShLkm9tZBM2Ch/nuEUq61QXkcnnCIMRLel3nHPVag87uMq2tZZLEN3fFCBBJaMQxc3HCaNUjgWPnbB1P2nmhVo+pVRt0dAcQ1wiiPC4IAY8LguY80o04RIRqUKRj8TIGli3nKw9vZd/TE/xYEkBD0cRz15e/yKHBXaw49wK6e3qYGBml0Yh5w6texTe+cgeHDh1CxKX1HAjOOVzgEOdob2sjiWNq9RhpbiVy33fvZsXAopMetTHGGGOMMcYYY4wxxhhjjDHGmFeWY+nwcAnwPppf7TefKzafW4hh4PeO4X4APwfEwC8e43kLVq16EsA3PKqKesWJw3UuJW5fAfk8uObHpIAq6f8EQdJihmYRhGoCCNIseMArgockAU2InABKznmSmXFa5p6m0bceJKHZZiLdQ6JZXIEIOEcuSDs5qKbFE9VqjXwhR2WuSqMaU6/FdHZ34NoCqEM98YzVagyUy8x62DFbAxcQJx71kKgnCiOkUUdcek+nkMtF1F2Ea26bIYCKI4zy5KOIRpBjVvKUSkUq0zVUPdMzc4xOznBuqUwYBIS5PDe87S187cv/yuDgPmT+T6W5D8d8MQiAaIL3npnZuSOfIxJYwYMxxhhjjDHGGGOMMcYYY4wxxpiXdSwFD48Cf3/U458HKsBnX+IcD0wBm4HPq+rEMc7vMFDQtEXCSSfOUWxtA6ARx4RRHoBEAmqSR3NlNAzxGuAcgJD45hf2IunhPeDwIoimW1ZoWtcAqiQ+AQkQVcZmqmlXCVXqlQr1lk40iJqdHQB1kAiIpr+rggqFICIIArz3eO+pzs4yOz3D3GyVQr6ACAwN7mfjtZemBQbO8fRsDc3NMp14puMECQTfLCrwCPkwwNerOOeONJUIwxCVCJrFHOmsJP1sNKEhEQ0XMFeZJZC0W0WCkBAQRjmifJ7r3nQ9H7/1VoaGhhCgnM/RWSoShiFjlQpTc5Vm0YMQBK55a6Gzo40LLllHT9EzeLB6KuI2xhhjjDHGGGOMMcYYY4wxxhjzCrLgggdVvQ24bf6xiPw8MKmq7z8VE2t6AHi7iPSr6tBJv7oqtdkpkCCtLVBPEAS4pIb3SXP7hQCSAC+SFiDMtz5olgOkW0AACDpf6SAu7dAw/7r3gFJuKQPQ2dWDjxPkyDYWHHVtOdINYf65llwunZdzqCoXXnYRStqJQiR9zvuEQi5HoxFTCEMeeGo72zq7SXwj7UARRuScQwXmKnWiKCSuNwDFe4+oEgQhuAjQtLuDKgFKFDicT6jh8MDmfQe4uL8XUM67YC2r1qxmxYrlDO7axXfvuYehocHm5yCU2koEUUQURpScMjU3BwgiDheEtJULvPmaXq5ZF+B0mENjDQYPdpz0qI0xxhhjjDHGGGOMMcYYY4wxxryyHEuHh+d7PVA/lhNE5BJVffQYTvkw8HbSrTD+zbHcayFcELBo8Wq6ujs4OLSHXK5AFOUpFsvEUZ4574l9SBQEzTfQ7EdwVAcHBaS59QQEzQ0/BNSnO1IAOSe0RgETU1OoKpETcr2riMqLyIURXtPiAkXmSw3SIopm8YNzQiNRHOnvzqX3FhFcEOBc2lnCkXZp+Lfvfw+7du5maf9S/unv/4FvfuMrXP8jb2fl2rXs2L6bNf0D9CxaRNDRQ3RgN3OzswRhRFJuQ/MBSZJAoUhQbyBhgTCK8ElMHBYhLNBS6uCSVSuZHJ9m1crVTM5OsXffIKVijsGhfTQnDyiJh7lGQjVJu1OoKiKOUmsbA6v6ufHKAPUxj+/xjI3XWLN6KTB3sqM2xhhjjDHGGGOMMcYYY4wxxhjzCnPcBQ+q+u2FjBORDuC9wC8AFx/LPVX1LhH5NeD/iUgb8CFVffg4pvuCyq1lPvyXH2NseJiJkYNIENHe2c0Fq9aj+TK+2I64kHzUnLKPm10V0m0nvE8Qmd/4gXR7iGYRgnpP4ITQQVtriVBintqymUOHRrjm/H6u/r1fZ2hwPzP1EJcvkwioCg2vxHGCSkCjUScRRyEM2DbUQHxC5ByhgARCFIUUIiGMHJEoUShEkdDV1Udf72KcKD09i1i/4TJGDh9iYnyCoNCKG51m19fupjMskOteSqk9pi5CNW4QViYJunsIcnlypSJxlCdJlEq1StXlcC5k+/gMTz65hWSml3vuvIv27i4WLR2gu28pU5MTzcYU6ZYXY+OTBM6hKEniyedydC3pZ905bSzuamFsKsbPhOjcGOf25eiNjqmGxhhjjDHGGGOMMcYYY4wxxhhjzFnKnaoLi8gbReSfgP3AnwGX0tz84RiusRP4T0AD+AngQRGZEZE9IrLzRY4dC71+rVbnn//1C/zLvd/knm2Pcce3v8537ruHO79/Jx/7+7/if/3Fn/PpBzezuEPpKTVoz1UpR3O05iq0F+os6gxZ1OlY2h2xbFGBgd4cy3py9HcFDPSELO5wtJc8gZ/DSUxvTxetbS04B7nI0VouUMrFFGSavE6TT8Zpicdp03FaG8OElWG+8fBmPv/A4/zTfY/yqQce45/uf5RPP/AYX3zgUf7l4Sf5wkNb+JcHN/Ol+x7mXzZt4V8efJrb73+G27//JF+5/xlWXXo177zp53nne3+eH3/3z/JT7/oJfuQNr+bH3vw6fvHd7+Y//NK/49f/3a9wy/t/ieuvexN97e24ep1QPRInXNTXwxsuv5QL117Eb19/BX903Sp+bP0ikvoEk+OHefKJB/ne3V9ny6MPkosE9TqfXrrdhvcIHkEJA2HxytVsODfPOy49yMZlezm3ZwjPIJ3tc5y/usHAkulj+RMxL+CrX/0qa9euZc2aNXzoQx96wTGf/exnWbduHevXr+c973nPaZ7h2ccyySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJsslmyyX7LFMsslyyR7LJJssl+yxTLLJcjEv50S2tPgBIjIAvL95rJh/GqgAXwE+e4yXXPkCz5Wax4vRl3jtOZI4Zvv+nSzecCGRBMhMFUGJwogoCqjOTOMLJTq7Otj65C6e2vwElblZfNKgvbOH69/+ZvL5HM4F6QYOzW0s5rdz8N6nE9J0Si3lNnK5HI3EUyzlWZpfSne9BtrsDtGUdkdQJmcqfOSxUQ5UGvMvpEcSI8RoGIM4UCU3M0y9fRFIuv2GeA9O0p9JjGgDUQcoTj3SqOC8xxXLSFIn8AlCjPgQqKfbcQjsHtrHA488RKGljS8fgI72FjpznpUtbfz5n/4/rrrqCroXLeOub36NkcPD5HN5nHPpFh2aoOq54Ly1LFnSy0PbhzlnqedtG4bxcUKtXmdsOmDfoQadrXm+/cgsixd1LDQ+8wKSJOGWW27hG9/4BgMDA1xxxRXceOONrFu37siYbdu28b//9//me9/7Hp2dnRw+fPgMzviVzzLJJssleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyWbLJfssUyyyXLJHsskmyyX7LFMsslyMQtxwgUPIhIB7wR+EXgjadeI9Bt/uA34DPAlVZ07jsu//0Tn95IUDm7dzszIKA6hJcoxtzxk6/anOdCxltrS84hyOYIgRFVpb+9ixcrlTE1N0dbeysjwOBonlFtLzFXq+EaMoixe2sveXfsIwxBxkM/nUWB2eob+JYuoVmrk8yGBczhxIC9c8JDP5wjCCMQ3ix1If6KoAi6A5nnqQnBhWgCBoE7TcelJQPhsKYiASIiIooUyCunWHKK05h4n5wLUBSRBwHhQoEpArmeALXtH0HFHYXaCt7CT5StWMl1YxMEtT7Jmzbl882tfp6VcxjkBhTj2BGEINHhk5yRLu5TLltd4dGeZA6Oe6ZmYHfuV8Smlt0t4wxW95EprgAU36TDP88ADD7BmzRpWr14NwE033cRtt932nH/wf+xjH+OWW26hs7MTgL6+vjMy17OFZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WSzZZLtljmWST5ZI9lkk2WS7ZY5lkk+ViFuK4t7QQkYtE5E9Jt6z4NHA9EAD3HzXsZ1T1M8dZ7ICq/v3xHAt+D05YccVGNrzzHWx46xtZfN75FMutvOVXb+Gcy6/Eh3miMEAE2trLLFu5lCCM6O7rpb2zi6nxKUYOHWJmepoDgwcZHRln1/Z9jB4eZcvjT7Jr+06eeXIrTz2xjYfvf4zx8XFUEwb3HKJWrRMGAUEQ4JxLj8ARBAEi6XYQ6U9pFjYEaUGDCyCIIMylR7PQwQdRs+AhgKA5Lq2kePb8+Q4ROBCHIs0aiAB1DhWHc4KKQ+fHhhGFlhaifCEtqvAJjZ1PMD0+wqLFi2n3FXaPVQnzRaIoAI0ptZQolIq4wJHP53hy6z4O7X6KpW3KeLKYrRPLGG30UXPd9PS088arl3DpuQW+9f0d/NXnvsPw8PDx/LkYYGhoiGXLlh15PDAwwNDQ0HPGbN26la1bt/KqV72Kq6++mq9+9asveK1bb72VjRs3snHjRsvkBJzMTMByOVlsrWSPrZVssrWSPbZWssnWSvbYWskmWyvZY2slm2ytZJPlkj2WSTZZLtljmWST5ZI9lkk2WS5mIY6pw4OItAHvIe3mcNn808A+4B+Av1fVbSLiT+osTxERobOjg85CkZGRvVQmxli8bCXFXJ7pmVlEIvIuQIFarc7Q3gNMjk+yeu1qdj6zj3PWLuPA3ln27T1MR0cH/csXs+PpXdQqc6iPyOXKTI4folYbIYqKjI2Mo5r2Xbjra9+jVCygogRhhCKUW/NcsvEiRKS5HYbgaRYeOEm7N8z3zhB3pJsDaLPIwYHOd3Rw6Tk+AdH0OKqLhHpBdL74QY5cx6GIPNsMQl2IkwDvFeI6TA3DyrWo3wczh1jaUaS1vYNyS5FGvU7iPfV6A68e7z1JAmH7Umh47r53O7927npaBwLi+izjUwlx0EVrUanVilz1jnfypQP9rBr65Gn8Kzj7xHHMtm3buPvuuxkcHOS1r30tTzzxBB0dHc8Zd/PNN3PzzTcDsHHjxjMw07PHQjMBy+V0srWSPbZWssnWSvbYWskmWyvZY2slm2ytZI+tlWyytZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5mAV3eBCRfwAOAH8BXA7MkRY5vFFVV6jq76jqtlMzzVPDOUcYRpTa2li9+lK6evpw4giEtO2JQBilXRhQYVH/Yjq6Ohg+OEoujBg+OEpXXyedXe20d7QyPjJGb18Pq9asoKe3GzRhYHk/177uWs457xy6ujpQhc6ONhb19bFi9XK6ujtpKRXJRQFJnFCr1oG0GCPxSkObHR4keLbIQYJnt7doPidHxsizb3D+9fltLcSRRu6QI6/DkfIGr6BJ81xQTbfEEBFIYmhUodwBLT20lNs5dPAAw1OzzNU909MztLW3Ny+nR+6nwOpFbbxqfQ+hU+741tNs2byZZ7buYS4usHXnAb5x/yEG949ASx/ndCrm+PX397Nv374jjwcHB+nv73/OmIGBAW688UaiKGLVqlWcd955bNv2Q7V0f6hYJtlkuWSPZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZJPlkj2WSTZZLtljmWST5ZI9lkk2WS5mIY5lS4v3AgXgTuB9wGJVfZ+q3nUqJnY0ERkQkT8WkSdFZEZE4ue93ikivyUivykix9C1QonjhOmJKYhy5EtlvCojI+PUKlWiUGjNOwIRWjvKlFsKrF6zgr6+Tpav6qd/WT9d3R309nVRbivR1dtJ79Ju2jpaaeso0drWAuJIYkcUFZmcmAGURj1hbHSSylxMvZpQqzUYOTzKwcFRtj61E5pFBvF8wYMcvS2FQ1BEgfnuD4CfL3ZwLj3mCx+EtNODmy+YOKoDxJFCCDnyeaCKV5j/00gUnGuOyRXQcgdJuYuuZeewb+8eRsfG8erZ9sxTXLjhYgYW93LD669lUW8XYRiRxHX6+zroXbKcmapn++Ec39ua5ztbAqpJkdZiwuq+Bj2tMeUD3+Gipfnj+yMxAFxxxRVs27aNXbt2Ua/X+fSnP82NN974nDHvfOc7ufvuuwEYGRlh69atR/Y+MiefZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WSzZZLtljmWST5ZI9lkk2WS7ZY5lkk+ViFuKYtrRoWtQ82oDZkzudHyQibwY+27zfUd/MP0tVx0XknaSdJ54Ebl/ItVWB0BG2tuDzIZBuLxGIg9ocDS0hLsKJY25qloNDhxhY1s/UZJWpyTk6uroZ2rcPIeDcdatYv+HcdGbqWbF6GaqKAN57wjDg8MFFeK8sW7mIdRtWkSQeUBKfoAqJ9ziR9BIKKo4k/RCO2o4iLVbQ+e4NziEKYSDUZX6/C9Iih3T/jGYnh/niBsB7wCOSXkea95z/aGX+NiIkzWYNKgJRDsIIXIALAn7jA7/D7/y3X6fS8Gx8zevo7u5h69ZttBVzCEKYy6Ga8J3v30sun6NQKkEQEieeWj3mq49CkD+PXAjuoBI//ASXn2d75pyIMAz5yEc+wg033ECSJPzCL/wC69ev54Mf/CAbN27kxhtv5IYbbuDrX/8669atIwgC/uiP/oju7u4zPfVXLMskmyyX7LFMsslyyR7LJJssl+yxTLLJcskeyySbLJdsslyyxzLJJssleyyTbLJcsscyySbLxSyEqC5sCwER+T/AzwKLSb9G98A3gU8AX1TV6lFjfXNMq6rOHffkRJYBm4FW0iKGTwAfAzpUNXje2F8GPgp8TFX/7UKuv2zFKr3qZ99N//oLKbeUObjpUdrCAtGKZXxje4XHDnl++uJ+/tPr1zJ6eJzZ2SkO7tmFi0L6l6+g3NqB9x5xjjAMyOcjVD1BEIL6tIhAFUSIopDDh0YplQpEuTzt7eV0y4jm4ZuHquK9R1U5ODbDf/nn7zPtAw5qifmODOIbaQFCmEsLGdQTVKdJWtrJo0Ti8argPXGS5tuQkGej9gRzExBG+FwL0OziENfofvJLxA6KxQL5QpHJfC/vv+xcgt7l/N/HJ9BcERHh/e0j3HzDlXzwt36Te/dN86s//TZaSznu++rnyQUh339yO5MzczgRulryXHD++Ty85Rkq1SpxnDA3U0E7L4aoJS3OSDy56nZetW4xU7WETZs2He+fjTkFNm7caJlkkOWSPZZJNlku2WOZZJPlkj2WSTZZLtljmWST5ZI9lkk2WS7ZY5lkk+WSPZZJNlku2WOZZJPlkj0i8pCqbjyecxfc4UFVPyAivwX8KPCLwFuAG4DrgWkR+RzwCVW953gm8iJ+nbTY4bOqehOAiPzFi4z9WvPnFQu/vOBcQFyrMT4ziWiMC0Ly5SJTc6PgSuSiEOeEHVt38s0vfpKWsE69OsfUXMzqi17NeesvZmamxsz0ON19HQzuOUAuVyCJ67SUytQbsxSLZd72429CRPA+7bogR9ookHZY8Jp+7594RNLCh6JL+NHyXh6pdnGw2tLcqgJQl57znG0rHOIcVxSmuKgwxvBsg/0TVZaWHbNBmbsri6nQrBHR+e0s0g4PefG8uTxMUq+wNVRGk7TPg0fRZmcJVZrbajTngEcQVIUoDInCiLhep72rh+EZR+fAJbjRIabHh6jVasxV5mhrLVOr1YEknb/LQRCBU9CAQKCQi5iqJQuP0BhjjDHGGGOMMcYYY4wxxhhjzFnpmLa0UNUEuA24TUQWA+8D3g+cC/wC8H4R2Xv0KSc4vxua1/jdBcxtl4jUgFXHcgNBqExPU93zDGFVcQNd1CszxPUKSAulKEBE2Ll1C089fh+XX34J5bVr6J6apD55kJbWq1h5zgomJ6Yptxa57o3XkiQJSZLgE08cx7ggIIrCtBkDaTGDyFHFDqqIS4se0sfgnKNOyPdq/expFNNzXXMbC02ahQfNa/jmlhMCg0mRmak2Gvd9Ca1ViNvKFDe8Gi/N8WnbiXRnC5kveoCd9TY6kwSvMn/ZI0UOR+bqpFkAkXaa8OpJVEnUE4QhtbkZth6YZefBBm3tnfQsu5B6ZRJfHWd6epr21hYOHz48f2GQoFlEATiPEyU8snWHMcYYY4wxxhhjjDHGGGOMMcYY8+KO+9tlVT2oqh9S1bXA64B/ACrAiqOG3SMivyEiK17wIi9vOVBR1W0LHD8DtCz04mnHBU+uWKK0cj1Rex/OBTQaDVDFOaEQhTgRciF0lfPQ10Xj3/579vz3P6TviqvRxDE7M0d1dpZiIcfM1CzeK/lcAXB0dHaQz+dIEk8cJyRx3PzdIyLN7g5w9M4iQRDiXEg5UooBHPbFtNDABRCkRQLa7A4xz0lahLCnkWdo/wEa01Ms7l1EZXqG2vQ04tLX0zfujnSFwAkNF7LXt+BInxcUJ83CB3Fp9wghvb+k56T3dHiUOPYEQYBXj/dVlrxrI4137qeSDBMGAX29vVQqFdrb2ghzBcIo1+xIEaZFDziE9B5RFC00PmOMMcYYY4wxxhhjjDHGGGOMMWexY+rw8GJU9TvAd0TkV4B3k3Z7uBK4HLgM+D8i8hDwGVX9f8dwaQ/z+zC8NBEJgTZg6ljmntRjkkaDrp5u5qZmQSFfLNLWtYihcUcYBTTqNUZ3bKG/u4PXdpRZ971vMbl4DbtbumjrbGPs8CSTU1NE+TzjY+MsWryIOGmwb88gG6+6hO/cdS8XX76eoX0HWX/JGvbuPshTj+/idW++HFVtNl1IOz+k7yX98j/WgKq6ZveG+c4KpIUHR/bFEBCPiqC4tFhhbB+TGy9GuzroaptA9tWI/fzpzWIFFHXN4gkBdZ5uqhxobqfhmW/E4FDv8arofJeIZqGGOIeEERI4gjCExNPz2qvZcfUFXPHYd+hZLDzV6KOnr4vRkRG6u7sYWLaMSqWCcyM0igEapO9BQsfSth6K+fyxxGeMMcYYY4wxxhhjjDHGGGOMMeYsdVIKHuap6jRwK3CriKwH/g3wXqAH2Eha/HAsBQ97gAtEZLmq7n2Zsa8FImCh3SBAlfrsDDNjo7ikgVbnaC0X8XNz+ATKuYh8GLBj81O8/qpLOPeCn2Dq8DCbt+1Fp9rxxU6e3ryDQqHAytXLuejSNahXvFcQuOzKdfhEedfP3EgQOjq62vBJwuKlXXSua0+LHY5q7ZAkSq3WoKUlj6oyGYc8Uesi3Yfi2Y4OCs0uDc0CBC+ohOnjQJg6/3X0TT5A/YbXs/je3XQuXUxrqYVnJhP2zjRQwImSuLR7A0BFAr42102XBngSBEnv6EIEwSMQhEfGpx+fxwUhIo4wDFFVCpufpPGPn+YpVS65ZAljLWso+DodnTFtxTyXnLeSeqOOu/Bc2sptaFyn1khwYUQpdzGV6WOqVzHGGGOMMcYYY4wxxhhjjDHGGHOWOqkFD0dT1SeBXxOR/wq8g7T44U3HeJlvAhcAvwz81osNEpEI+EPSWoCvLPjqIlQPHGLm4AGG1NPb3kXnee1877bbGe25krm21TQqVVa4STb0/BTViw/zpUe2ceklP08Y5fHe4+MEr5AvRLjAoeJxgZuf13M+4SiKaNQ9YRhSLKVFDYlXElVQxatSr3tKLWkhRD1OSNIrPafmQSDttuCaFw88aEAgcGl+ivX1p5gcG2TF5/6Z3t7VvP76jbS2lTg02+A/fO0gz0zUcapI0NyiQhQfCtWg2TSCtGBDRFjhJ/n+Y4dZtaEIYU9a8NAs1IiThP0HxhAXEYYB4Ons7OTiSy9m6zPbqJR6uebyS/jOY7tYGrbREU/Q3dFGLgxoqCPvPB2lMvlcjpp3jI2NMjXeWHB8xhhjjDHGGGOMMcYYY4wxxhhjzl6nrOBhnqo2gM8BnxORgWM8/U+Afwv8uojsUNWPP3+AiFzWHHcV6XYWH13oxUWE7sVdRKUIqnsItUYYOM45p8hQQ4gRDj7xICsvWsfoXS2Mrfs8g8sHWTb+Ru6772lCF1Cv1yi3llh1zioOHRrl8qvOp9RSTLd8SKsHjtqqQlBVAucQ1yxiIC0yUCCfC8l1BcSJR71Hj3R1kKMmPX/Is797RZ1jcRTzn3OdDFz7TpIffRP7B/ezeOliyq2tFDqeYLRznOtXrGPr9ATi5osm5EinCPHNvg6aFjx4oFVqPDW4D+1cBj196XhPeo5CrZ4gYYEoDIjrdeZGDjOye5CpYc/1h9/M4Lu+z7lTUzy2uYWO3lYW5/MEQCGI6ChFFEtFkrhBsVDG43jsmT0L/uMwxhhjjDHGGGOMMcYYY4wxxhhz9nIvP+TkUdXBYxy/h7QzREC6TcYhoBNARL4vIkPAg8BrgBj4OVUdWej1RSDMR7R2tLO8e4ZyfgYXCH35rRTcDCViNrQFtG47j2+M15mc20ttuUdzntVrVrB8dT8rVi2ns6sbAXp7u6nXYqpzNSqzVSpzVSqzVWqVGnEjxnuPAmEUggrep7UFPvHNrTA83ivqFXEOFYfqUcUOXtPKCO9BEyC9gAAIrCk02HDgPLZ/17P5icfYf3A/c5Uqg/v2EzcO8UT702xYJrRFDq8CEoAL0q4NEiB+vo5CCCUAhUqthpB2p8AFzym0UNW0UEJAXICoMDsxQWehTFTrYubBdv6lchfrLhglVuWZgzPs3L6DMAiIiAnDECTEBRFxHFOpNdg3ZR0ejDHGGGOMMcYYY4wxxhhjjDHGvLxT3uHhRKnqP4nIYeAvgDVHvXT1Ub9vB35ZVe881uuHuYh8qUCRxdToxTnobJ0irAmtc6OcV2ynsaeXr1UOs6Z4mBFaOCyH2LuzQv+KPgYHD+AIODg0Qu+iDrZt3cHM5Cyzc1OUSq0US0VyYZHh4UOsOq+fc9YuZ26mxkP3bmJ0dIyBZYvZv3+Yeq3OVa+9mJ5FXUxPTlMoFpirNtDE41AUcN6jGqLeI+JQ0SNbTDgRVhYhn3SysxGxNOqms1zimWeG2Ts4zLt7d9Be6qa2fC9XLl3O/cO7SURJ0is3OzYkePUAiBOUZvGFKoVc7khnCXUOpVmMIUIhFxEEITmfsOyc89i+cz/d0kKLLKeyKsfaeJakXmVaQ845bx1OEorFEuIC8rmQeqWOqDI2McWWvYe4ZGnLcf+9GGOMMcYYY4wxxhhjjDHGGGOMOTucloIHEZkvRFBVfeOxnq+q3xCRtcBrgVcBS0m7PhwEvgfcparJcUyMfD5PsVji8IFupkZrFFuV4cOehjqCqRHW1tYz2jnD1k2H8e4w2/f0kk/u48ev+1ke+O5m0IByW5latU5reyu1aoNzz13O8PAEcZzQv2wRY8PTdC9qJU7qoJ5iOc8Vr7qAWiMmjEJWrh0AgVJLkbnZGgcHx+ld3IEAhXiOczgIcYMWquTaehgl4oBvZVxaiAFHQh6hPxcSRTmGx4qcV+5grhKz+alRSi15SoUG+u2Qpy97hJL2ERCnDRucS7fOEMAnJN6nhQ4KCBSjHKFz5KMw7e5A2tHBez//IZIXyOdynNfeztYtD3Pg4EHyyUrquRYm4wKLFlWQxjhTPs/IXEKLn2W2UkNQwsARV2aJE8/TO/ejtQpgBQ/GGGOMMcYYY4wxxhhjjDHGGGNe2unq8HAd6WYMx01VFfh28zgpBGgpt1HIF4l6F6GNSZQA3/YGdK6TVdVn6NXFfFYfYaaqaDzJ8DdyRK/LcWhohM7uEnFDyeULFIoRzjnaO1tp6ygzNTVL4ATnhFJLgWpljkajgYrggWIxx6HhMaq1KuVymZ17D9A7sJyHH9tJIe9o6SkzeuAAG2pP09feQi6XZ3ToEEu6W1iqc5xbOcj+aWWv68F3LaOmnvxcherYGPFcgX/63B2Uu4pccf6FdHcV6OvrovjMRnbd9xFmD68kUI9KiEoAoggC6vGJx6uiqjgcpUKe0DnCMEo/MRFQUE0LI1BPfWYKr55du3cwlyQEjRgFtmmRyo4SPhyjyDAzyVIee+QZNiRDjFYarNp4KVLIs2/nLmR6EgqdaL1+suI1xhhjjDHGGGOMMcYYY4wxxhjzCna6Ch72chwFDyKyUlV3n/zpHLkBiXoQoWPRCqqzBwnCiKXnXoU8VmdpPIaUlHsfHqbc6pFyiYGedUz1jnLP49+h81AnubAF7z31Ro1SS5m+vkXEsbL5safI5XM88dhTLB1YSt+iXhYt6iVuxGx7ejuPP7SFu75zJ/v276VYLNLd2cFv/Oov8SMb1zA0PMPjjzzCUzu30RaC8zGFfJkwiqhXK0RhyNzoYQqT4/zCa1dy1XVX8MHPfY2PPXEAd/8Il0//BBPnVFk5ELFubTvFUkChEDATtbGzNWTd2GGiA53ELmxuUxGASwse0g4PoKKIQBCErF+1mr7uLphyzc8NVMGrgveQeJw4pDrHrl27yYctFKWVPW0V/LcOcUAOsrR/NSO7lVnXQrlYpjuY5fJzllBzQrLjaVatXsw3xjW9sDHGGGOMMcYYY4wxxhhjjDHGGPMyTkvBg6quPM5Tt4vIN4C/Ar50XNtWvARBCIIg7W6AoKp475mYriCzc1TmZpCDRS5fvp5Hh77LTD3HkvblvOXQah59zw6umnkDHaNLEVGiIMQ5QNKuDj/zSz+J94pqgiCICONjE9RqFfoHljAyNs7Wv3mCOImZm3FMTxzmA7/137nhDa/mdW+4npmJEWjMUQhyxNUZZuMKbeUCvlFnbPgglYlxLrzgPC677HKW93byuh7P3/zrV/iTjT9K1wP3sD63ikJxgn27d9C3qEy97qnWlRm3lHz3BE470m4N4sA51AlojFdFRBAconBgbIJr1l1AoaUFpgRE09IVJ+m2FiK4fIkgcCQitJXLHB4NuaX8bj76R4+y4jMDbH16F+esCdkyGDItEYX2TnK1CsW5KQ5OTdNaq1II2qnMzVIqFk5mxMYYY4wxxhhjjDHGGGOMMcYYY16hTleHh+PlgOubxyER+Tjw16q652RcXAScCwlcQL3eYHpmFudK3P/4o8zWetl94AAjlUMM6AA+2cneEeGpwWcYGCpx3qE+vnLFJ9l976vZvLcFVYgCwUURURgQBELghEggp0rJQYuf5Rcu72X3oXE+/qkvUK/NgVckCGlowmSjzme/eDv//LkvsmLVClavv4jZ2QpOFHFCvZ5Qzgf0dHdy7WXXUSgUGR6doRAd5sLuAV7TXuLuriXkF1WpuD4Ip3FBnrbOdoIgR0uplYnJNdTaniQkBiTt7CCAEyTxJKqIOETS4o99lHm1T1Dn0rEApK8JICK4METEUSiVcOK4tn4ls+8/xNh0g4nHlrN90flcclFMEATUgH2TDa7pKOMaCYd2DrK0GJELQ4otZXp7O09GtMYYY4wxxhhjjDHGGGOMMcYYY17hsl7w8CbgZuCdwGLgt4DfFJGvA7dywl0fhFwux8TkDE/t3kNrDF0tHSzp6CCOFvH4t0e4c+gelrpfoF7fwtP7QubGp7k9183EtyOu2DLAdd3becPS5exM2vnuRMDm2QaJJM2tIki7IXgF9SzRGd7nexifnmbPdB3UgW9AJCSNBqhHXEiAhyCgPjuFKMzNzBLl8lCvEOY7WH3eRbQuWsrYwYPsePB+GhddSq1e46HpOvlCnlVrPF16Ht19s/SvXEnv4naQSWZ8gDzdx4rCHh7ySbPYwTXnKngf432Cc67ZlQKqA+dTaAuoO4cKQDpePThJ32QYOJyAcwHiA65f/2b+/k1/zcyvXszIZIOhydVc37OffL6IjxvsmFIujjzj45PMDI8x29PNdD2kEeWpzlWg1HICfzLGGGOMMcYYY4wxxhhjjDHGGGPOBu5MT+ClqOqdqnoT0A/8F+AZ0jn/CPB5YK+I/IGIrDie64sACM4FzBweozoxSb06x+LWFn5pQwdl5/jUE18iqswRNg5R3zNJa9hGsbOTPcWlfG56Pb+3dTVf+P4W/Pdu5ycmHqYYkBYQzN9A5reBUBQFEQJVfNxAy72IOHK+QeTrdASedav66bhgDYvPO5d8LiL0DUYO7Kc+M0GjXuPCjVfTu3QZXkK8C9j8+INIKOwY3E97Tz8teFqLhymVl7C0v5/29jacOOK4B23U6Ts8wuJdc5R9HVz47BwBTWK0ubWHAKqABKiCikvfmAhIkHaBcA5Em5cQJJejo7OT+666i3t/fws7tj1DPDfO4N4aU3MtzHeGmMp1cGiuwZate6hJxJzkmNKI6Zon3RfEGGOMMcYYY4wxxhhjjDHGGGOMeWnH/e2yiFwvImMi8skFjP1Cc+zrj+deqjqqqv9PVdcBrwX+CagBS0i7PuwQka+IyDtFJDiG90B/Rx/n9q/gglVrGVi2mmK5h8EZ+PjuVnrXvZF6VweDvbNcdMF1vOnibspPt1CK27isr51L+9pZu3w59ct+lCcufzfbl1zMRYs6uHpxG1ctbuOaxe1cu6SDNy3v5r1ru7muN0TwiAgEEcR1Qt/gqrDOeTnhgnKeFifkSmWeefIJ6vUajXqdtpYCM5Pj+OHDHNr2DCOH9zM3NUqjUWX7M0+xddszfO1bX2S8bzkTGhHP7cXJfnJRSBRGuAC8trK+K6Rl8hAFrdNSm0KdHFWUIZDEaZWDpnN0Aoij1miQeD1qLKDKd799J3u33Me+h7/FbV/4ZxIJKHYUGH7sGXY/UMEzBcEwh57cxH99/79Sm9hP7D2TkmfG5dg/PEbc8MzFMFgL8M4RhguOz7yIr371q6xdu5Y1a9bwoQ996EXHff7zn0dE2LRp02mc3dnJMskmyyV7LJNsslyyyXLJHsskmyyX7LFMsslyyR7LJJssl+yxTLLJcskeyySbLJfssUyyyXIxL+dE/nP6nwbagU8tYOxngA7gphO4HwCq+l1V/VlgKfAfgc2k7+N6ntv1YfnLXcuJY0lXH0FN2Xj+BazpX0ZPexuvuXADV/YWuO71r+Ha665jU9TCq179Wlpbz+dnfryfS2qHuLZlhmtb5ri6ZZarynNc1NKgpSXk4miSS6JJLs1Ns15GudCNsE5GuLKjxvnFKhMjo4BCGCG+gcu1sK6jxLqeNtYv72fDokV05FsIWkuMDB9m5NAB4kaNyCdcs3wZ+e9/lUe/+WXGDu9nZP8+ojBi9fLlTE6PQ7FAManQ3dZCrdZKvdogbtRpVCv4ZDe5ygxTKzbwuekuDgYtqKTbVjT3o0B8TCCCE8EBoXNIEFDMRURhQHMHi7RjRL3Gn/3xH9G/+iJWXvp6vnfPXTz85NNMTM3x0N5RkriO+LehOkY8c4ily0r0dIe0dy3C50rsGK+TiCOnMSOxcqCh6cci8tKhmZeUJAm33HILX/nKV9iyZQuf+tSn2LJlyw+Mm56e5sMf/jBXXXXVGZjl2cUyySbLJXssk2yyXLLJcskeyySbLJfssUyyyXLJHsskmyyX7LFMsslyyR7LJJssl+yxTLLJcjELcSIFD1cDCty9gLF3NMdecwL3ew5VnVDVPyctvLiHtO+A8NyuD598qe0uvHqe3LOdRtQg7Ag4PD3C4OghRv0UH99V5WPbpvjIx/6emaEJggOb+eM/+SZJ/Lfc/qUv8A+7Knx0T8xf7GrwkR01/nJPwl/u8vzlPvirQeGvBuHjB0M+NhTw53vgN+6f5K/2BJS7ugnDEJEACQuQb6V/0RJWr1xNQWDm0H7C6Vla2rsYnRhlbmaK6twcpVqNYOYA0tHN7scfY+fjj7D3/u+ybPUyujo7kJk61WqdiZHD3Hnn3dx9d5WPfPTT/Lff/l/8xm/9Lvc/9FE+8ME/4OD0HA+dfz2NKI84IRSaW1ooxA2E5h+FKg4Qcagqqh5t1iIoytjQLgYGlpMv5MmHcO1rXsvWPbs4MFXhkb2joF3ASqjtRMqLcU5ZuegAc4e20z2xA1efI4lylDraiUJHrd5gcnSEuDp3sv5EzkoPPPAAa9asYfXq1eRyOW666SZuu+22Hxj3u7/7u3zgAx+gUCicgVmeXSyTbLJcsscyySbLJZssl+yxTLLJcskeyySbLJfssUyyyXLJHsskmyyX7LFMsslyyR7LJJssF7MQJ1LwMABMqOr0yw1sjpkA+k/gfkeISE5EfkZEvg08Cbym+dIe4E+azwWkxRCPisjFLzIvvvP1u7j9n7/A5z/5Wfbt3kVlrsrdX7+baiNGSu1sXH8NW7dP8vjmJ3j6qYAL1/by6d/9Md61LATnmG97oCKocyAOFSF0NJ9LX2u4gNiFgOCcg7YefPdypNhGe1sHa86/kL6B1Szp7uScYkAhLOCqVRzQoQkXrzmPybCDuNhKe+ho3bEZnRil3LMMRFhy3Y9T6V1LI8qze2iQvQfGuP/hQR56/AkGDx2mkJ/EJzWCuUmqLod6RYEGz25RIUlM6Fyzw4MimhY3HPW5gwjqoDY9xeKlS+koQCGZo7u7l/FalWTJEqq1OVQvQ/X7oDHSqDE7E7Nm0XZqh7bRNTtEdx5obaMRROzXkLDYQkxzqw9z3IaGhli2bNmRxwMDAwwNDT1nzMMPP8y+fft429vedrqnd1ayTLLJcskeyySbLJdsslyyxzLJJssleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslzMQoQneO6x7D8QneD9EJH1wC8BPwN0Nu/vga8AfwncoaraHHsd8KfABuD/AD/y/OupKvfe9W0qlXFQ4fU3vIlcqZvv33kX+t43s4ga165cwzf3H+aBpx/nJ6++glK9j95V07yrsYTPHFImk2bBANosCEgLHQKUhjZfE9d83gGKCwJ8Swfa0Qd4xob3sXVOaWlvpdQS0Do+Qa5S47xyCyIBS1rytDil3FpC4yprl7SzoiAM7Z4m17WEKF+kumwDjbkEEDSICGjgfZ4kSUhiJY6VWmWOpF5Hgdh7UE1LXlQJkphiUqOQyxEGIcV8gVCEAgkignMBSNAsjkhQFAG6ehZTbTQAaGtrZ8fhKmFbN370WjT5EBIK1KepeGXp4piW1lba2yMWtZcorFhJfXqKscOTjAzuZNuj91MqlHBJ+4n8mZiX4L3nP//n/8zf/d3fvezYW2+9lVtvvRWA4eHhUzyzs9exZAKWy+liayV7bK1kk62VbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJssleyyTbLJcDJxYh4f9QIuIrHm5gc0xZeDQsd5ERAoi8vMi8j3gceA/AF3AYeB/AatV9e2q+uX5YgcAVb0buAGIgStf7PouCNOCBCcIgveKOAfO0e1i2lv7WDNQ4cKBPopBwL6n2wlbt7OqJeHa1nQLCNx85wM50g+hpq5ZCJG+hggq4L2mxQOFErR1o+09SK6Eq8/QaMxwcGSaOA4YIGFJzxJW9vaxrLuLlUv7iCQmXywwV09wQUAtiNg+Mcvh0XEqlSrqE0BRH+NkEKc9iCbMzMDkZEDiFQ1CIo2JvEfQtLODegqHd7AsGaO7vYOB5atoaWmjvaOTcye2ESQNvOqRTUMEKJXLHDp0gJnZGi7IMTIygsaeyQa0D6xDWtYC42hSRX2VajXh//6vKYotIWtXrySKAiTMUexZRLHcTUvnIoqldq684mp6e3uP9c/ENPX397Nv374jjwcHB+nvf7axyvT0NJs3b+a6665j5cqV3Hfffdx4441s2rTpB6518803s2nTJjZt2mSZnICTmQlYLieLrZXssbWSTbZWsslyyR7LJJssl+yxTLLJcskeyySbLJfssUyyyXLJHsskmyyX7LFMsslyMQtxIgUP323+/K8LGPsBQIHvHMsNROQjwAHgb4BrSL9rv5t0q4plqvo7qrr3xc5X1UPAQeBFWwaIelQV1bRDQ3o4BCiK4twilvZM0NLWzh2ly7nj+xOMHJ4mzE3wpt4YUd+82fMvPP+kzr8ZFMGrJwgDpFCCUplquZ0/lVX8a7WVb+8cZcehSWaHD9A2sZ/S+AGWzo1QGz7Ewe1P0ZV3aGWOIK4xkUTUi20MTozzV1+/h0OTE+ATCPNQKNHa/hRdfQ5WX0q97nj6YUeceLSlA69CQNoNAhFEoHtmP6VymfPPvYAf+5G38s4338CFa89naUcL+VyIcy6t61APInQOnMPg3r0kjRphIHz/u3dTbuvChwVwi6HokJ7zidoGKPdfRLl7Kf/lf1zJORf28cwsjFQaTIyNoeLYcM4AZRdTrVYZGR05lj8R8zxXXHEF27ZtY9euXdTrdT796U9z4403Hnm9vb2dkZERdu/eze7du7n66qu5/fbb2bhx4xmc9SubZZJNlkv2WCbZZLlkk+WSPZZJNlku2WOZZJPlkj2WSTZZLtljmWST5ZI9lkk2WS7ZY5lkk+ViFuJECh7+P9Kv9X9RRP6XiOSeP0BEciLyv4FfPOqcY/HvSYsVJki3pzhfVd+oqv+sqvECr/F94J4XfkmadQlppwNQfBKD9+S0zlXlGfJhQFd5P/vaz2FLzwY+n9/Ifd/O0dIlnNua7tORnu9/sOiheY/5Dg80O0jgHIQhRDk0l2c438rWXAf3xy18o1ri81M5PrHjELc+sY07K0U+ufMwn3hqH3/21CRfnOng6cIKHskPMN6xhJoE7J6cpJHUkXgOggjWvYbz1x7iLW9bi7/w1RC20PKPShwUqLf3EGuSFnm4tAtF2/RBWqaHmG3EnLNiORetGuDiNStY3d9P4iKmVUB98y2kRSGlfI5f+8Bv8+jD3+M73/oyV137GuJSB7OHdlIZn8C1b4WOHhIc9ekxarPT3PfgLG52C48/s4Pv7NjFXZse4M7vf499u7fR3RJRLpfZvOWZBf9xmB8UhiEf+chHuOGGG7jgggt417vexfr16/ngBz/I7bfffqand1ayTLLJcskeyySbLJdsslyyxzLJJssleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslzMQshRu0Ac+8kiHybdYkKBUeAbwJ7myyuANwPdpIURH1HVXz3G698L/CXwGVWtHvdEX8Q5556vY2MVJqcPg8Ib33I9iwfW8uXb/pk3vP8/cvOyhKC0hvvv+hR/0/IqdrSeg0sS/qDwOL+wtpvvuB7e+1iehm92PgjD5rYPQkk8swSgwnynh66kwp+9qpOpJMd//OLDNGYnYGYU5qagMg2TY9Cop8UFjVlkdpglHa3MVutEi1Yw0j4A4igmDa4+53we27eTclcnjdoME13nkORL5IotzM7M8qrBu/jxd9zIf31wjNZn7uPjW+/lV/vP58DbfpkcQteO+xm6+EdQEVof+zot+x4B51h37gUs6uklDAJqjZiD46Pkw4hzrn4DH5vuxAOhJvzs+H28/21v5Ld/87fo6Ozix3/iJ/jD//thqsVeLr3war73xJOMje+DicO0xuNoUGDRQCs/sTTPHbULmdr3ODMju/FxQuITcrkcLgwZHRnjkovWvmiLcnNmbNy40TLJIMsleyyTbLJcsscyySbLJXssk2yyXLLHMskmyyV7LJNsslyyxzLJJssleyyTbLJcsscyySbLJXtE5CFVPa7WHOEJ3vvXgCrw60APcNPz5wYkwB8Bv3OsF1fVa05wfi8pDAPefMPb+cIX/g7vE0QcPR1l/n+3vJfXXHsu+d4BPv/JT3KHnMOe0nJAQaCvu5vC4GFGlixKOzYgaXMHPdIzgjpyVP+M9Ln5DS4ScfhcEeqVtCODC9IjXwBRaDTQXCsUO6i2FSmUytQqs+AiVD0VrxyebFBqW0GXm2I6yDEsjrI26Esm2dbWy6FKzMCSPsI996DeU1SQUhttxFzqJtktCQCB95RmRijlcyCOyblZ4sOewAWoKt7XiTVhrlIlEFBV8lonnh4lqVcRCXEuIIkbJJKjVG7nxjev567H7ieIckSlIr1SpdKAgwdrTA4n/PKycf7hotex/buHSeJpGnGC+iphFKHJQht3GGOMMcYYY4wxxhhjjDHGGGOMOZudUMGDqnrgAyLy18DPA9cCi0m/1z9Iup3E36nqjhOd6KnQqDeYmZslzOVBE0JR3rJhBWtXr6KwaIAPf+yf+OvJcxjtXYoH8JAnYVFQJRobhyVpIUO6HYaAgjrACY2jdgs50uNBBFUQESTMQaEMcR2SBsQ1CMKjtr8AdY4aIZ2lFrx6AvWIxjin7BrbxZUrL2f3dAVpTCOq1MgxLHnURUznOyjkInI7H0Zw6bkdiygRM1gPqft03lKfI5obA6+oeEanJxmfmSUQwYnQ2d5K4hscGhkl372UwCuoEAYOfIOe7k4KxRIuCKHUzluuu5LB0RkkV6KYxHSpkKdImFfmJmrcXujgdQd38SP5Ip9adj4Tg1sIw4hqZY7Z8XH8CXQcMcYYY4wxxhhjjDHGGGOMMcYYc/Y40Q4PAKjqNo6jg8OZJiI89dSjlFpLAFw80MM5q1dCWzf/99Z/4nOTXYy09nPkK3hV1CdMzlbwM7NE9SpKcf5qpGUNMj84/T2tgwAEFcEnCRKQbn+RK0KxFZI64hOIYzRpgNf0KlGOyDm6tMKSch7CgERyoAmjM2Po9DPkaSFuzNHqK4y7TiquiCJM1hJmZmYIqtMk1QrTPqZd5xBq7NQCHXGMqMfVZhAfEzgHztG9qIskTpganwVVvE87QTTqNcqizAGoJ3QO1YTVA4uYrXsEJcrleNM1F/M7f/FZQh/TwSwXruxDmp9B/1yNR7YO8d8aMR9/ZhODF1zBI+ddSjBzkGq1SqUyR6NhHR6MMcYYY4wxxhhjjDHGGGOMMca8vJNS8HCqicjFwC3Aq4EBoOUlhquqLuh9iRPyhSJRLcela1bwvve+h1pQ5A/+4A/5cvd1uChKx8GRooc6jq0zCXX1BLNzoAWODMKDetCQUNK9PNKtLrTZuUERUQIUEQEXIuIoxHU6qRDmFKUVyYe0l1so5wXJ5ZigwPaGwycOieuQxDS0ROiVA0nMsrhK28Q+ZisNNFdCoxCdmeC737uXuDZHrMrD3nPg4XsY6Ghjmctx+PA+cg98iag+S6gJTkLaOzrobe1ksnqA6pxSryqi6fYWpdoM50mFmlMSZmgLIAgilvb3s//wGOPTFc4/9xymqw0Oj4zTWRnh+itWU8wF6dt3jsA5+pf2c+dju/m9mVn+YNcWxi9+NdHyJfS0pMUg3nsefOjBY/4bMcYYY4wxxhhjjDHGGGOMMcYYc3bJfMGDiPwK8MdAwLPtE07WtQnDkBV9vfz2r97C+HSVv/mbj/DYnmGks06ZOby0UlVHJVYEARIen42YFnDTU0hSxolDnMOJA4TE19Hmc+mNQFXBx6j3BCFEDnLOQ3WMK4Nhzj+nnziBPYdHmKhMM9aI2TUZU3GCSpxul+ET8lqjw9XJhTlapER56gD9bcKWmRlylf1EuTyNeh1/eC+f/Ow2avUGToR/aOsmLJVxmrCkvcjidRcQuZCJiZjhKihKGIYkcUJ1NqZtSTtje6bTrhZAt07zo+FuGnFMHDWYjELCMEe5kGN4Yop//czX+al3vpm//vSXaGtM8DM/ehVdXa0IpJ+bKg2fsKx/MaVCji9/9zH+shrz8/ue4a8ufT3LupVV7RCEoRU8GGOMMcYYY4wxxhhjjDHGGGOMeVknXPAgIq3AjwIbgC4geonhqqq/eAzXvgr4cPPhR4EvA3cAY8C7gMXAm4D3AFPArwIHjuH6vP7a13Dj1WtoL+S479tf5rJVbbQENT77rY9Rrc2RCyOWdxSpNhIC0m0fZlvyDF98Pl37nmbNA5/Go6gLkcCBBCTe44KQKAypeaVGgAD5KIJL3k+UeBbd/4+05mFw7z62NOosed01TE/NMjNyiMFdO1AR2sTR7gJcGBGIgHOUooDFnSXi2NGfK7KsW9i9Z4juxHPpqpWUSsrhw8PszHtq+Va8r1MMhYo2yMV1uiYO8OoLlpIkShCGPDQTM+ocDkkLNrxnerSCm2yAuObn5Jidm8PXZnAKNOp4BRCefGob+zY/wo+fv5TprZsY3bGHm667mJ6OMknsiaKIMAoIggDvPQJcc9k6+jrL/N1td3N+MM4VtS2oX0kuLDNfI2KMMcYYY4wxxhhjjDHGGGOMMca8lBMqeBCR95EWJJSPfvoFhirP7gyx4IIH0gIGAf5UVf9z854AdVW9sznmkyLyZ8DXgD8ALlvoxVWV9/zk2+hmiic3P8kzI3OIKo2og57CIaTYRjEUVi9qY6ZSQ4HEQxRGDAUR/bk8qzryxEmCCLgg/TjrDUBi0AYESi4XgQphDrTRoLVc5O0X9BI4eNLVmKs0mBqfJAwd3R3t9G7ciDjBuYAwjAiav4sAIrhmVcDE6BhJpcLqFcsploqU2zuYnp6hVo85Z9VqpmdmSdojWltbeeqppykUIvp6O+kql3AuIFal0WgQOsGpZ2L4EGNDg7hSC5ooQeiIghDnhFq1wtDOnRA4SuVWUGjUZgiJee9rV3H56hLFUo43X3QFI3TivSeuN3BOwCsSkBZUCCSJZ9WqFbzvR69lJXu56pJeOlesZMthZWh07hj+PIwxxhhjjDHGGGOMMcYYY4wxxpytjrvgQURuAD5OWpBQBe4F9gPxyZkaAK8iLZL48POef05Rhao+KiL/Afg08F+ADy7k4qrKZ/7hH/jZG1/HPZt38NjeMSSIcEHIotUXEIZ5EvWMiECJI2UbHjhcbufilcvpm3IMz84CQhCEOIFCc4aq0J4P6G4tEgaOwDkCEXJRRFtfP6Keq7sWod7jRFD1KOBVQcE5hwuEKAhB0g01UCX2SiOO6WxpoV6psmhJH6VSkTDKETjHZResIQoDRBWvniRJeOt1r6LeiGlra6OYzyFBgIpQjxNCEZIkoVKr4rynu28Rs7UaiBC49KNW52jv6MAJxI0GGnsqk8O899WLieYcMzMzhPk2ivmIg7v2I2FAII4oinDOETYCxKWPoyDE+Trn9+ZZ27OGhoYM7thKol04LRzv34oxxhhjjDHGGGOMMcYYY4wxxpizyIl0ePivpIUH9wLvUNWRkzOl51gE1FR1z1HPeZo1Bc/zRaAB/DgLLHgIgwAptTI1M8P4TAUvDlHwSYJPlFojBnHN7gpy5CcOfLFI7sK13BiV+ed7HqbSiBFxiBMETceL0NVWorOthSgQpqZmEAW8p6VUJqnPEYgQOEcUPRuFiKAKIhA6ad7bEYUhIoIgNJIYlbR7ggfqjUZaYeE9gUAUhgRBQBiFhEGAcw5FcEGACiReqdTr1Or1tAMDaYGFxg18o4aIo9lSAlVP7B3ljnZElXqtxuz4FMW2bu576PvMTYwyOVNlRa/QiKrEcYQkAbE46s0uD9J8nwC+NsdSN0IYhOyfKDLtHXHUSb5cIsqf8C4rxhhjjDHGGGOMMcYYY4wxxhhjzgIn8u3y5aQ9D953ioodAOaa9zjaNNAmInlVrc0/qaoNEZkDViz04nGcMFer8szOA7z2gtXMPr6d6XqcFjWIgyMFDOkX9ko6m0CgHAXsHxrisrXLOHf5Yr77yFYe3L6Xhj5bPOBQ+ns78EnM8Mgww6MTHDo0TFtrCyuWLaVQ7iQQh/cJYRAQBAEucATNwop0+w7F+wTnPep9s6jCUXJFXBgAgojDq6LqAfA+7epQr9fxjQaNOEk7K0QRguJjD96j1Tr1ep20rAG0ec9GrYYrtOBckG5JoRAnHkVobylSjSJm5mp4CelevYElTnHqSZoFIv25XLPAAuI4puGVxCdpEQfQqNdIGouIQsd0IyZGCIIA9Qlx3R//X4sxxhhjjDHGGGOMMcYYY4wxxpizxokUPITAjKpuO1mTeQFDwPkiEqrq/FYZO4BLgSuA784PFJGlQDtpkcSCqCq7d+9ndm6Wto5u2nt66WgWG6QFBErY7KqQJAnOBWn3B5+wae8oj+8dprPtGdpbWoglpLVUJGleOwpDesoRXR2tjI6OsWvPPsSlxQytbSUUKLe2ErkAEcUheO9BlTAMCMOQIAxw4lDnUK9pBwfSggr1CdJ8XlGQAK8e5xwoePXEjRgEHIpPmuMVVJp7gviYtnzI9PQkKoJTwaunUa2SyxcJBTTxoB4XBBQCxxOPb8blivT1LeKpxzcjGnPe6mX4Wh1ESBKPTxJcEJALQ1S1WTQCvln0oD7BOZcWWgjQ/KzjJKEeJy+YlTHGGGOMMcYYY4wxxhhjjDHGGHO0Eyl42AGsFZFAVU/Vt9RPAeuBi4BHms/dDVwGfFBEblTVqojkgD9rvv7EQi8eRRE333IL+WKe7Tv3sGfPjrQzg0u7KDjnUE0bTHj1aacHaB6KE2EuCKk2x3Z1FwgDR5LExI0afZ1lnCr1SoUVAwPMVOqoKrl8AUUp5vPkolyzi0LaoSGOYwSaHQ+UmATnlSAMUdJtOIIwRJzgmttOeO/TQoVGjHMO7z1xkhCGEdLcGyNQRb1SrVWoNmImp6Y5cPAwhaRBlHhclGNy5CBJo07rshLRzAS+Mkdp8RJ6lvTTUcrR1V5i1cBiKl7o6yoThgH1hmNycoaujnaiXIRvFjzESUKtUSeQgNCFJD5GcemHFzoSD6o+LdhQbXbVCAki29LCGGOMMcYYY4wxxhhjjDHGGGPMyzuRb5f/EfgQ8BbgX0/OdH7A14GfAt7OswUPfwHcArwRGBSRZ4DzgC7S7S8+stCLx3GDRX09BFHIwYOHWLpkCWHzC3cngnolyuVIfLrNgnMOABEhEMEF6WNVT5D+hk8SkiRhbnKM9tZW6rUajThh1bKlVOoJYRQSx5621jZqSUIY6ZFtKlSFKIwIggDUN/fyENz8vdMdLkiShKThEZG064RPml0VHKhHVHFArtmdAiTtsiBCudxCHMf09fVx3ppzuPqKy5ir1kgUwkA4PDxGLpdj8ZJFFAJHGDgkCIgbMbkooqOjCydC4tPuF3HcIEk8tWqFaqUK6kniBJpbYdTiGoVCgSAMiOMY9Z7QCXGSNOeVbsEhInivzZYPxhhjjDHGGGOMMcYYY4wxxhhjzEs7kYKHPwV+AvioiDxzira2+DwwAOyff0JVd4nIe4C/JS1yuKb5kgf+SFX/aaEXr1ZrPPTIY4gTVBNEJC0+aBYWIEqcxIgq9Xoj7WDgPWEQAELcSIsdnCjtne3kcyFBEFKrVannlDAXUSjkuPSSDYhLiwecNIskUJLEEzhBm1tQiKZvI2745vYW6TTUewSlUq2Sz+WQZvGD6rPdJnxaHYELAhpxA/XpNQRJO1aIEIQBXiFu1HGSFkA4EQpRgE88YRSyrK8rvWJljlnvSRoNPEq13sCJo9GoU2s08IniwgAfxxweGaeQy4FzNOo1pienCKOQUj5PVCxQLrfSUi5TrVXZPzRIHCcIQq6QRxXyQXPbDuVIRw1jjDHGGGOMMcYYY4wxxhhjjDHmpZxIwcO7gX8Afh94TEQ+B9wPTL/USar6iYXeQFUngN97gee/KCLfBt4KLAMmga+r6vYFzx6IooC2liD98p8AJNcsDgAUGnFMkngUobVYInBCELh0+wnvib2Si3KQNFixtIupqRmSpEHD1xgeGwPV5jYYigBJ4vE+IW7UCYOABMArKkK9WiOOG0gQoghe064S6sH7hEYco5oQuXQbi8Qr3nsK+RyVShXvE4IwxKEkSUI91iOdKYLmFh3zRRBhGBKGjnq9kXaDCBw+8QSBIwxCkkZM4IR6EiMiKI5GvYqq4lVJvBKI4AFRxTeLKhJVNInxXgkCRzA7i6pSqVRx4giCgEajhift4uCCANX0vQYuAIEgzB1LhMYYY4wxxhhjjDHGGGOMMcYYY85SJ1Lw8HfA/H+OL8B7m8dLUWDBBQ8veSHVMdJtNU6A8PijjxCFAQo04gZO0i0inHN4r3jASUDiY9QnBAJxnOCTmMVLFlMqlXFxwvTkGHHSoFGv0VYqonHEvgODtLV1cmD/7rRQAkexUGB6ZhpNEkBJVNJtLhoxSZIgQUCzkoA4Tii3tFKpzNFIYpZ0djI4OfHs1hY+Rr0ShCFJHBMEAWEQ0IhjvKZbRaRv06HqUe9pJEpXZycz0xPkCwVEAuLGHD6JyeVCRIWBUpEOCdgzV2Usjlnct5rJmX0kSYwEIXHiKeRDysUyM3NzuObnl49yhGGQdpMIgnSrDxfQ3ixwSLtTSHObDSWMIkQc+XyOXBSiquTzBTY/+eiJxWqMMcYYY4wxxhhjjDHGGGOMMeYV70QKHvbybMHDGSci7cBdgKrq5Qs5Z/euHSN/+id/tOfUzswcq8svv3xB+RljjDHGGGOMMcYYY4wxxhhjjDl7ueM9UVVXquqqYz1O5uSfJwQuaR4Loqq9qrrRjuM7gN8BWoEO4HMv8PongRKQI9125CcWeF1zAr761a+ydu1a1qxZw4c+9KEfeP2P//iPWbduHRs2bOCNb3wje/ZYzc+pZplkk+WSPZZJNlku2WOZZJPlkj2WSTZZLtljmWST5ZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5mJelqq+IA+gm3QwiOdNzORsOIAB2AKtJCxoeA9Y9b8zrgVLz938HfGYh17788svVHJ84jnX16tW6Y8cOrdVqumHDBn3yySefM+bOO+/U2dlZVVX96Ec/qu9617te9rqWyfE7VZmoWi4nwtZK9thaySZbK9ljayWbbK1kj62VbLK1kj22VrLJ1ko2WS7ZY5lkk+WSPZZJNlku2WOZZJPlcvYANulxfm993B0ejpWIXC0irz1d9zOn3JXAdlXdqap14NPAO44eoKp3qepc8+F9wMBpnuNZ54EHHmDNmjWsXr2aXC7HTTfdxG233facMa9//esplUoAXH311QwODp6JqZ41LJNsslyyxzLJJssleyyTbLJcsscyySbLJXssk2yyXLLJcskeyySbLJfssUyyyXLJHsskmywXsxALLngQES8iQy/y2p+IyMdf5hJfBO48lsmZTOsH9h31eLD53Iv5ReArp3RGhqGhIZYtW3bk8cDAAENDL7hsAfj4xz/OW97yltMxtbOWZZJNlkv2WCbZZLlkj2WSTZZL9lgm2WS5ZI9lkk2WSzZZLtljmWST5ZI9lkk2WS7ZY5lkk+ViFiI8xvHyIs/fBPSRfql9POebVzAR+RlgI/C6lxhzM3AzwPLly0/TzM5u//iP/8imTZv49re//YKv33rrrdx6660ADA8Pn86pnbVeLhOwXM4EWyvZY2slm2ytZI+tlWyytZI9tlayydZK9thaySZbK9lkuWSPZZJNlkv2WCbZZLlkj2WSTZbL2eu0bWlhXnGGgGVHPR5oPvccIvIm4LeBG1W19mIXU9VbVXWjqm7s7e096ZM9W/T397Nv37ONNwYHB+nv/8HGG9/85jf5wz/8Q26//Xby+fwLXuvmm29m06ZNbNq0Ccvk+J3MTMByOVlsrWSPrZVssrWSPbZWssnWSvbYWskmWyvZY2slm2ytZJPlkj2WSTZZLtljmWST5ZI9lkk2WS5mQVR1QQfggf0v8toBIHmZ8192zIkcQHdzjqfsHnY85/MOgZ3AKiAHPAasf96YS4EdwLnHcu3LL79czfFpNBq6atUq3blzp9ZqNd2wYYNu3rz5OWMefvhhXb16tW7dunXB17VMjt+pykTVcjkRtlayx9ZKNtlayR5bK9lkayV7bK1kk62V7LG1kk22VrLJcskeyySbLJfssUyyyXLJHsskmyyXswewSY/ze2vr8GCOi6rGwK8AXwOeAj6rqk+KyO+LyI3NYX8ElIF/FpFH///s3Xm4JGd53/3v/VRVb2c/Z87si2Y00kgz2jVCQuybZDaBNwI4tsF+Q/yG2Hnt2CaxA7Hj2CFxvBBjxwbjjRgwxiaSjQBjQCAWSYwktEuj2fflzMzZTy9Vdb9/VJ/RSAhpFi0F8/twFdNd/VTV0/3r0nXN1ffcj5nd9DxN96wRxzEf/OAHuf7667nwwgt5y1vewoYNG3jf+97HTTcVH/8v/dIvMT09zY/+6I9y2WWXccMNNzzNWeVMKJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpFzkZVhRMnMRAsxw44O5Ln+S1/cBCd4+e4viTGZOd1GSeYpqAP9U1pPw2btzomzZter6nISfYuHEjyqR8lEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUS/mY2Z3uvvF0jo2f6cmcIXu+JyAiIiIiIiIiIiIiIiIiIiLlV7aCh19/vicgIiIiIiIiIiIiIiIiIiIi5Veqggd3V8GDiIiIiIiIiIiIiIiIiIiIPK1TLXhYZGbZd3vxqV6jWK7CT/F6IiIiIiIiIiIiIiIiIiIiIt/hVAse7FmZhYiIiIiIiIiIiIiIiIiIiMgpOJWCBy03ISIiIiIiIiIiIiIiIiIiIqVw0gUP7q6CBxERERERERERERERERERESmF8HxPQERERERERERERERERERERORUqeBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQURERERERERERERERERERL7nqOBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQURERERERERERERERERERL7nqOBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQURERERERERERERERERERL7nqOBBTpuZ/YCZPWJmW8zsPzzJ61Uz+5vu67eb2TnPwzTPOp/73OdYt24da9eu5f3vf/93vN5qtfgX/+JfsHbtWq6++mp27Njx3E/yLKNMykm5lI8yKSflUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqV8lEk5KZfyUSblpFzk6ajgQU6LmUXAHwKvBdYDbzOz9U8Y9tPAMXdfC/we8N+f21mefbIs493vfjef/exnefDBB/n4xz/Ogw8++LgxH/nIRxgaGmLLli38/M//PO95z3uep9meHZRJOSmX8lEm5aRcykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclIucDBU8yOl6AbDF3be5exv4BPCmJ4x5E/CX3cefAl5lZvYczvGsc8cdd7B27VrWrFlDpVLhrW99KzfeeOPjxtx444385E/+JAA/8iM/whe/+EXc/fmY7llBmZSTcikfZVJOyqWclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5yMkwBS6nw8x+BPhNYAg4RNG94Wp3/7cnjLkfuAN4KTDbHXu5u489yfneBbyr+/Qi4P5n9Q08NxYA3/Fen2XnA71AC3gAGO4+33XCmMuArLvtANYADwPpE861ABjtPm4Adz5Lc36uPde5DAFLgZjiM97Pd2ayAZgG+oAciICH+M5M4PszF90r5aR7pXx0r5STcikfZVJOyqV8lEk5KZfyUSblpFzK6Xv575HK5Jmje+Xp6V4pH90r5aR7pXx0r5TT85HLs2Gdu/ed1pHurk3bKW/AjwD/CFxBUZzw48AHnzBmB/AlwIBrgCaw4CTOven5fn/P0Gf0nL8P4L3Ap4H7u88flwvwOmAKWN7N5HZg69PlAsw835/n92ouz/K98n2Ri+6Vcm66V8q36V4p56Zcyrcpk3JuyqV8mzIp56Zcyrcpk3JuyqWc23OdC8/S3yOVyRlfU/dKyXLRvVK+TLrX1L1Sslx0r5Qvk+41da+UMJeyvQ8taSGnay+QAEe7z5d3950oAm7x4lu6iaIqLnnOZnh2+meK6rZ5T8zlTcA2YIW73wYMdrcjz9H8zka6V8pJ90r56F4pJ90r5aRcykeZlJNyKR9lUk7KpXyUSTkpl/LR3yPLSfdK+eheKSfdK+Wje6WcdK/I09KSFnJazCwGNgM/AfwJRVuYt7v7AyeMuQ/Y6u5vNrO3Ah8AXu/um57kfMeXtOjp6bnyggsueA7exfenVqvFli1b2LBhw3e8tmXLFhYvXkxvby8AmzdvZtmyZfT09HzH2MOHDzM2VnTAMTOUyZlRLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmU0zORizJ5ZuleKSfdK+Wje6WcdK+Uj+6Vs8Odd96ZuvvpFRA93+0ptH3vbhRtYrZRrJvzq919/wW4ofv4ZorWPluAO4CvAxuf7rxXXnmly+nbvn27b9iw4Ulfe/3rX++33nrr8eevfOUr/Vvf+tbTnlOZnDnlUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEs5PdO5KJMzp3ulnHSvlI/ulXLSvVI+ulfODsAOP83frOMzLLaQs5i732xmrwT+0d1/s7vvfScM2U3R2ufjAGb2CN/Z/keeQ8uWLWP37t3Hn+/Zs4dly5Y9jzMSUC5lpEzKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lJNyKR9lUk7KpXyUSTkpl/JRJt9Xxk73wPBMzkLkCW4CfsIK1wAT7r7/+Z7U2eyGG27gr/7qr3B3brvtNgYGBliyZMnzPa2znnIpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpZyUS/kok3JSLuWjTMpJuZSPMhFAHR7k9JnZx4GXAwvMbA/wn4EEwN3/mGJJi9dRLGkxC7zz+Znp2eNtb3sbt9xyC2NjYyxfvpxf//Vfp9PpAPAzP/MzvO51r+Pmm29m7dq1NBoN/vzP//x5nvHZQbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUk7KpXyUSTkpl/JRJuWkXMpHmcjJsGJJDJHnlpn9APABIAL+1N3fP//axo0bfdOmTc/b3OQ7bdy4EWVSPsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqV8zOxOd99oZkbxG/LrKP5B/Tvc/a6nOlZLWshzzswi4A+B1wLrgbeZ2frnd1YiIiIiIiIiIiIiIiIiIvI8ei1wXnd7F/C/n+4AFTzI8+EFwBZ33+bubeATwJue5zmJiIiIiIiIiIiIiIiIiMjz503AX3nhNmDQzJY81QEqeJDnwzJg9wnP93T3iYiIiIiIiIiIiIiIiIjI2emUf0dWwYOIiIiIiIiIiIiIiIiIiIh8z1HBgzwf9gIrTni+vLtPRERERERERERERERERETOTqf8O7IKHuT58C3gPDNbbWYV4K3ATc/znERERERERERERERERERE5PlzE/ATVrgGmHD3/U91gAoe5Dnn7inwb4HPAw8Bn3T3B8zsv5jZDc/v7ERERERERERERERERERE5Dk02v3zZmAbsAX4MPBvnu7A+FmclMh35e43U3xhT9z3PoCNGzc+L3MSEREREREREREREREREZHn3GEAd3fg3adyoDo8iIiIiIiIiIiIiIiIiIiIyPccFTyIiIiIiIiIiIiIiIiIiIjI9xwVPIiIiIiIiIiIiIiIiIiIiMj3HBU8iIiIiIiIiIiIiIiIiIiIyPccFTyIiIiIiIiIiIiIiIiIiIjI9xwVPIiIiIiIiIiIiIiIiIiIiMj3HBU8iIiIiIiIiIiIiIiIiIiIyPecUhc8mNmAmQ2fwvhrzOylz+acRERERERERERERERERERE5PlXyoIHM3unmW0GjgKHzWyPmf1nM2s8zaGfBr707M9QAMzsB8zsETPbYmb/4UleX2lmXzazu83sXjN73fMxz7PN5z73OdatW8fatWt5//vf/x2v79q1i1e84hVcfvnlXHLJJdx8883PwyzPLsqknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOykWelrs/6xuwrbttPYmxvw5kQP6ELQMeAi56imP3A9lz8Z7O9g2IgK3AGqAC3AOsf8KYDwH/b/fxemDHyZz7yiuvdDk9aZr6mjVrfOvWrd5qtfySSy7xBx544HFj/tW/+lf+R3/0R+7u/sADD/iqVaue9rzK5PQ9W5m4K5czoXulfHSvlJPulXJSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+Vy9gA2+Wn+bv1cdXg454TtuzKzK4BfBQy4F/hl4OeAvwccWAd8zcxe+OxNVU7SC4At7r7N3dvAJ4A3PWGMA/3dxwPAvudwfmelO+64g7Vr17JmzRoqlQpvfetbufHGGx83xsyYnJwEYGJigqVLlz4fUz1rKJNyUi7lo0zKSbmUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpFzkZ8XN0na9S/Pj9dP4NxTIbtwKvdvdOd/8Hu0UOHwNWAZ8zs9e5+9efldnKyVgG7D7h+R7g6ieM+TXgn8zsZ4Ee4NXPzdTOXnv37mXFihXHny9fvpzbb7/9cWN+7dd+jeuuu44/+IM/YGZmhn/+539+rqd5VlEm5aRcykeZlJNyKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi5yMp6TDg/u/nJ3f4W7v+Jphr6EojDiF04odpg/xzeBq4DbgT7gs2b24mdlwvJMeRvwF+6+HHgd8FEze9LvnJm9y8w2mdmmw4cPP6eTPNt8/OMf5x3veAd79uzh5ptv5sd//MfJ8/w7xn3oQx9i48aNbNy4EWXy7DrZTEC5PJd0r5SP7pVy0r1STsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXOS5WtLiZC0D2sBdT/aiu49RdAm4FehFRQ/Pp73AihOeL+/uO9FPA5+E4wUrNWDBk53M3T/k7hvdfePo6OizMN2zw7Jly9i9+7HGG3v27GHZsmWPG/ORj3yEt7zlLQC88IUvpNlsMjY29h3nete73sWmTZvYtGkTyuT0PZOZgHJ5puheKR/dK+Wke6WclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5yMkoW8FDDLTc/bsuf+HuM8BrKZbJ6AFuNrMXPUfzk8d8CzjPzFabWQV4K3DTE8bsAl4FYGYXUhQ8qGTqWXTVVVfx6KOPsn37dtrtNp/4xCe44YYbHjdm5cqVfPGLXwTgoYceotls6j/szyJlUk7KpXyUSTkpl3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+UiJ8XdT2sDcmDvKYzfDqRPM2YHkAFDJ3G+BnBLdx4TwIuA/UB2uu9J2yl/B14HbAa2Ar/a3fdfgBu6j9cDXwfuAb4NXHcy573yyitdTt9nPvMZP++883zNmjX+X//rf3V39/e+971+4403urv7Aw884Ndee61fcsklfumll/rnP//5pz2nMjkzz0Ym7srlTOleKR/dK+Wke6WclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5nB2ATX6av1lbcfypM7McOODuS09y/HZgpbtHTzHmJuD1wI+6+9+fxDkbwGeBlwBTQAJUn+oaUn4bN270TZs2Pd/TkBNs3LgRZVI+yqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXzM7E5333g6x8bP9GSeQoWiG8NTuQV4A/B24GkLHtx91sxey2NFDwAnXcFRqdS802kdf55UEqr1BtOTk2AB6v2AgdmJFwWj2O90H3f3P9W1okCjlrB4wQjj4+McnpwmC/FJHRsM4ijg7uReDHd33Kw7ge7xJ87zRCfO88R97t/5oudY3iZEEVGIMINqCDR6epiaa1OrVjgyPctwvcKikSG279hNs9UkDsbChaNMjB9jbnYWM+t+dIEQIgyIk4Q8z0g7HXIMohgzI4oi+np6aM7N0coyLrng/Kf8PERERERERERERERERERERJ6TggczGwQWAseeZuiNwP8EbjCzc91969Od+4Sih88ALzuVedUbPXQmHit4WLB4ERdeejlf+dw/kVUacPnrMQev1IoBef5YccLjih2Mp6zlcKcDnL96lD94z8/w6U/9PX/6lU0c6VlQLA2RZeB5ccL5YoosP37+FQM13vWS84njBAsRqUOrkzHbyZlutplodjg222K6nTHV7DDdTpluZ7TSnFYnJc1yMqwoMgDcAuYZ3m5B2n0jZhAZ1pyiOr2XRl8f9f4B6gHW9jW4+LIr+czdO3jxpev58Ffv5LUXLef/e/sb+fH/9xd5eMtmRvpq/Py/+zd8/C//nLvvvguvVLE4gSzD0w5JHDG6ZDkhGDu3bSNPO8RmDAyP8sY3vZl77trEt+/cRAjhVCIUEREREREREREREREREZGz1EkXPJjZJcBlT9hdN7OfeKrDgEHgR4AA3P1U13D3rWb2YoqlKeZOdm7doofXnXCdU/BYh4QQRSRJ5fhuC1Hx0nwnBsvn2yvw+JYJ3i16+I6ZdQsjDMeLQgOKWoYQxRAl3Y4RoSh48O4xIYLIjzduSCpVent7iaOYOI4IIWDH36bjTlEo4DlZnmEWwAKpw2yzxUyrQ7PjTLVSJlsdJlsZ41MzbNp+gKlmp/terLhusO58KebsEEUxURSzpLfOcKOOhRjrjsMChIgojomTBKKYUG1geQrNOQJOrV5ndNEijsw26ekfYtGSRRw5eIhavc4rX3Md99y1ifvv+TaVSpW43nNq8YmIiIiIiIiIiIiIiIiIyFnpVDo8/CDwvifs6wf+/CSOna8q+N2nG+ju3ziFOZ143Bzw0VM5xp6wJISZEcUJhhWvxUlR2xCi7kWeUJgwX/TgTtEK4oTTGcfPO//cQgCcZm5kFvD5gocQiu4RebdLRIi61ymWz0jihFqccOifv0qcJPRvuIC4v4/ZHbupLllIK4qo1evUGzUsC0RRRBwXy0X012vkeU6IIoIVRQoWjLnZJtsPHmOqlYNFRfFCCEDoznP+84EQitcPHNwP56/AQoRnGWk7LY6NEqIoIgqBvN3C2k2SJKHa00utVmV04SgTE5PUsg75xBj9Q0MMDgyzYcMFbN+ymV07d9I3MIhhhPmCExERERERERERERERERERkadwKgUP48CuE56voljHYc9THJMDk8D9wIfc/dZTneCzy07YvPjBPZr/8f+EDgxR92Ny7y5rkZ9wfHf/icUNj+sx4ccLJIrOC0ZuEbHxWCFFHsA73eO6nRY8HD9nUqmSEJj86tcZuGwDe//qbryTUV04THvVSv7iS19iYGCQV173Kq6+9hriKOLbm+5mdNFClp+zgpAXRQzzy0WEEAhJQifExfvszosQsBBhZsQhkEQR5HlRzAD0MUsgEKKEPO3QajXJcYgTojjGDDpZRpY5WTpHFKB3dJhdu/cyOz1JNLQQ4hrto1O8+YbXcf+9d3PvvQ+Qp22IY0KWAcaKJQue6aBFREREREREREREREREROT7zEkXPLj7B4APzD83sxw47O6rn42JPScMipqMEzo8zBchWCgKANzwED3WxcFCd1mLnMcKHroFEN2ODE9+HSeYYUAeIiIyigYKoVgNY77IwazomnC8qAKiOCEOETFGc+sukv4G6dgE5/3bn+HgocP0fut23viDb+TGv/u/zE7PkGXO0SOH6NneQ+5Q7+unWkmoVhKiEKhUK0RRRE5RBOHdJTAIEWQdQqeFtROidkpMjmcZbSKO5kWXiEpSw6KYWr2OxdXjHR7StIPnTghGT98gixeNsnvXHrIsxx3SqUl6+pxXvfKl3HHbN6nU6zQaNSaONYEMdz9elCEiIiIiIiIiIiIiIiIiIvJUTqXDwxP9OjD9TE3k+WBPqE6wYMRxBDhuVnRkoFiKwueLHI6vgDG/zAXg1t33WPEE88tlzF/Cc6KoOF9KUfBQFE8UMyHExbEWiud5d78ZUSUpijGSKkOXX8L0o1uh3aG5cy+Zza+fYYwdOczdd97J6rVrefjhRyF3js12aNaHMIOE4v319tTp7+9nhU/Q0z7CdLtNJ3fStEN7+hher5FGgTmcqhkhjnGMarXOZDujUU1I4goWRUX3izghChF5npO70zc4yODgADt37yenGGMhp69R41UvfxH33Pcg2x7dTL3e4NIrruCeO7/F3Fzz+FIaIiIiIiIiIiIiIiIiIiIiT+dMCh6+DLRPdrCZvQCouftXz+Caz7ATlqKg6PBQdBjw7hIPUbEiRYiLYod8/hh7/LHWLXjw8Njp5gsRwvySGRFJXPygn4eYBIcoFKthWM7j1sFwIITjRRNxHJP09rLkx36U3nNXE/r7iRt1Dvzj54ledBWNRoOb/+FmfvBHfpiH7n+QqbYzsuwcgjudNKc5tpfcoT3XxILR3z/Agos2sHvvflp7NxOlLaIVFzHeswxSI2kfIwsRSbdbQ7VSJa5UiQxm8kB/o4FHOYbhUQJRQhwHqpUK1XqN/v4+9uzeQ5Z3P0c36rUqL37xC/n2Pffz6LYdkKYEm+O+e+7n8quu4fbbvkmr1X5cZwsREREREREREREREREREZHv5kwKHm4B9gPLTnL83wArzvCazyib78JwwpIWx5dUCBGEqPhRv9vpoShi6C5t4fb4H+et++P+PKfbrYHjP/on3e4RRDFxVCyZQe6PFTfMd3swg7zbTQIjCRFxtUq0ei1ZpUJ86ZXU6lVs7YVUa1Xeff6FtFttGj0NLr90Izd98RbOPWeIlT1V5jodjqQ5dLtU5A7jU9OMNzuky9eT5bDQp4hGRxnCmAsNxibmCJUKWRxhFrA4AQuEOOboXMpAvYpZq3ibUQwhJqnERElMlqbs3buP3L14S3lOT08Pr3zFS7nnnnvZtWdv8Z67n9nE+BEe3byVjVddzW3f/DpZlj0LSYuIiIiIiIiIiIiIiIiIyPebMy0+sKcfckbjn2VW/Cjf/f09hEAchWKpiygCC/h8AQIRBLA879YlzHcv6B78uM4E3WPMHls2w6ASxd3XIiyKwWKwtLsvFN0gQtRdOuOxc8dRoNPJiKIIz504jovlNkJE7lBJEuI4Js+Nnt5+qtUGV47288aVC5nt5PzVjkO0KhV6GnU8TwmHIjIz+qcOcGjn/UwODdPwHXTSjLk8g2oNQiAziCwcL+QIDkfnWgz29AAtPM+Pv5dKEpMkFSbHJ8iz4rNwoH+gn1e+4uXceedd7Nmzt/hYguFOt5gEDh3cw+DgEFdf/UJuu+2bz2bgIiIiIiIiIiIiIiIiIiLyfeK57LbQA3Sew+s9rRCMnr46aZoSRRGVSkIIEbV6hagS0/acPCTdwgTAA245x9et8LwoSnB/rJvDfBGFRcWQ4/+XU0sSwPAQkXeXgiiWsjhecVGcJzeIQtFFgpw4ikgqFQYXJJjZCY0kbP6KRGYYTpqmuOdcPjpIFCUkwbhk8RDbOjDXSbsdLIykWqMzOYYHo5OlTE1N0kk7tOKYUG1gFDUdIUDe6TA3NUFkzkw747zRGvHcNA5UKhWGog6NKGJmYqKYjztuxsBAP9df/xq++c3b2bN7d/FaCLjnGE7u85+ls/mR+7nqBS/mwgsvBNTlQUREREREREREREREREREntpzUvBgZuuABcCe5+J6J80gjmOiUHQdiEIo/owj4hjSvIXHCR4VxQt41O26cEKhw3yxwvwJse6eE/Z7DhhJ0l3SIkRYnhMMslB0fOi2PijO4VkxzgwIRHFMiALeXQri6OFj5HledKSIY4IFenrr9A/0kqYpZBmdPKJpRm7Oub0NHj40SRRF3fcXEyUJ9UpCXK1TqVTp5E6aF6tNxAZuxfuoZG3mxg+z/dgh1g0OM7qszpolVQ4djIjiwA9ddS73xkcZHzvEsfEJLr3kQiKDek8vL7j6KrZs3kyjmnD+eWsIIRAlFeI4wUIgCoFOmpLmGWknZWxsP+vWX8z+HQ89u7mLiIiIiIiIiIiIiIiIiMj3vJMueDCzNwFvesLuATP7s6c6DBgEXkJRAXDrqUzuhHP/hrtvP5VjT4oXXR4yKnQ6HZyiA0EcR6RmxHNHqEXGbNKDu4PnBDOCGbkbGaFb3uDFuzMrHnaXt7C86GTg3SKJ6PhSDg5ph6jTJIuq3eUsom7Bw3z3CKdY6gIqlSpxFJNbcd4QAu1Wh6GRXvr6esmyvLsqRoRZRidNmU0zjjRzLApsm2mTU3ReaLVTWs0OgyMRpC2ipEqIYiAnRFF3HsVCHGZGM6ozuHgFy1es5LN3bWb3w+P8YBZBx/Es58uf+TQH92xn1XkXMrJgAeNjR+h0Ul75ohfxhc/ezMGDBzELRT0HRgiBEAUsBAb6+8nSlFY7xbpLidz2tVtYtXzRMx61iIiIiIiIiIiIiIiIiIh8fzmVDg+XAe+g+9N+d1+9u+9kHAZ+/RSuB/ATQAr89Cked9KazZwMyDs57o7nTrBAGFpKOrAKqlUI3Y/JAXeK/xmGFcUM3SII9wwwrFvwQO4YOWQZeEYSDHAqISebPkbP7MN0Fm4Ay+i2mSjWkOgWV2AGIVCJik4O7kXxRLPZolqrMDfbpNNMabdShkYGCf0RtKGd5RxttVje28tMDltnWhAi0izHc8g8J4kTrNPGQnHN4FCpJLRDQugum2GAWyBOqlSThE5UYcaqNBp15qZauOdMTc9yZGKa8xq9xFFEXKly/etfy+c/84/s2bMbm/+qdNfhmC8GATDPyPOc6ZnZ458jFqngQUREREREREREREREREREntapFDx8G/jLE57/JDAHfPIpjsmBSeB+4O/cffwU53cIqHnRIuEZZyFQ7+sHoJOmxEkVgMwiWlbFK714HJN7RAgARpZ3f7A3K7Y8BwK5GebFkhVe1DWAO1megUWYO0enm0VXCXfac3O0e4bwKOl2dgA8QGZgXjx2BzdqUUIUReR5Tp7nNGdmmJmaZnamSa1awwz27tnHxmsvLwoMQuDhmRZemWEqy5lKMywy8m5RQY5RjSPydpMQwvGmEnEc45ZAt5ijmJUVn41ndCyhEyJm52aIrOhWkWFkRMRJhaRa5eWvvo6PfOhD7N27FwN6qxWGGnXiOObo3ByTs3PdogcjikL30sbQYD8XXraeBfWcPQeaz0bcIiIiIiIiIiIiIiIiIiLyfeSkCx7c/UbgxvnnZvaTwIS7v/PZmFjXHcAbzWyZu+99xs/uTmtmEiwqags8J4oiQtYiz7Pu8gsRZBG5WVGAMN/6oFsOUCwBAWD4fKWDhaJDw/zreQ44vT29AAwNLyBPM+z4MhaccG473g1hfl9PpVLMKwTcnYuuuBin6ERhVuzL84xapUKnk1KLY+54aAuPDo2Q5Z2iA0WcUAkBN5ida5MkMWm7Azh5nmPuRFEMIQG86O7gToSTRIGQZ7QI5MD9u/dz6bJRwDn/wnWsXruGVatWsmf7dr721a+yd++e7udgNPobRElCEic0gjM5OwsYZoEQxfT31njNC0d54fqI4Ic5eLTDngODz3jUIiIiIiIiIiIiIiIiIiLy/eVUOjw80SuA9qkcYGaXufu3T+GQDwBvpFgK4/85lWudjBBFLFq8huGRQQ7s3UmlUiNJqtTrvaRJldk8J81jkijqvoFuP4ITOjg4YN2lJyDqLvhh4HmxIgVQCUZfEjE+OYm7kwSjMrqapHcRlTgh96K4wLH5UoOiiKJb/BCC0cmcQPE4hOLaZkaIIkIoOksEii4N//qdb2f7th0sXbaUv/7Lj/LPX/gs1/3AGzln3Tq2btnB2mXLWbBoEdHgApL9O5idmSGKE7LefrwakWUZ1OpE7Q4W14iThDxLSeM6xDV6GoNctvocJo5NsfqcNUzMTLJr9x4a9Qp79u6mO3nAyXKY7WQ0s6I7hbtjFmj09bN89TJueEGE5yn37sw5eqzF2jVLgdlnOmoREREREREREREREREREfk+E073QHf/irt/8+nGmdmgmb3bzO4ENp3iNb4M/Dzwk2b2STO74jSn+6R6+3r5wB9/mJ/9/36ZX3rPe3nHT/wML776Zfz8L/4G7/3pn+Y333gN73/t5fzeG64ottddygdefzkfeP0VfOCNl/N7b7iUD7zxcn7/DZfxgdddwh+84TL+4IbL+cM3X8kH33Qlf/TmjfzxD23kL378Jfzvt72Al61bzMGDY7zwgmX88a//e37nba/kf15/Mb//phfyuz94Lb/75mv5Hzdcw2+97gX85utfyK9ddyXvvW4jK0YW8ejeDpt3z7F1d4sdu1vs3N9h7+Gcw0dyjow7kxPOzAy0Wsbw8EKuvvoaVq1YwYIFi9hwyRWMHTrIpttuZ3J6lgNHpvjy529hKK4xOLKUBUtX07NoBVZtEM9NENVqRJUqlUYdkipZ5sw1mzRDhRBithyb5oEHHuTG//sp/vD3/jt//ad/ws7tWxlZuJTJifFuY4qi6OHIkWMcPHSY/QcOcfDQEaqVCotXruKajSvZsKqHo5MxRw7U8Jkm5y1MWJicUg2NPInPfe5zrFu3jrVr1/L+97//Scd88pOfZP369WzYsIG3v/3tz/EMzz7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEs5KZfyUSblpFzKR5mUk3IpH2VSTspFns6ZdHh4Smb2KuCngB8Eqsz/k/9TO8e27sMO8MPAD5vZHHAEyL7LYe7u557M+VutNn/7j3/PVN4ikDFz8CjLFy/jwIEDbNm1n4NZnXOveQ3ved2lpO2UTruFQ3epi0ClWsUMohARx1G3r8FjS1547nTSlJDPEuLA6IJh+vp7yByiKNDXWyOfboJNkTp4llHJHPeMPHUm59p87uHDtDHiKBCRE5lRDUYtgkq9TiWOqUSBWt4i1OokcUwtiojJqcYRqy+/hnMvvpxqNaYSJVSSiAiDPCfr5HjRLoLJVpv7Ht3M179xC8fabeKkgqUZFy9bwCuvvJwoxPzquh7IW+zalTG3dxs3/u3HuOLKjfQMjbLpG1/h6Nh+PJ+PuIjbPefc1atw1MY2XAAAw/ZJREFUjLEjRxheuoILVsLrLz1AlicEnIemnaEBuGCNUa9NAfVT+ZrICbIs493vfjdf+MIXWL58OVdddRU33HAD69evPz7m0Ucf5b/9t//G17/+dYaGhjh06NDzOOPvf8qknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUSzkpl/JRJuWkXMpHmZSTcikfZVJOykVOxjNa8GBmy4F3drdV87uBOeCzwCdP8ZTnPMm+Rnf7bk66qCJLU7bs28biSy4isQibbmI4SZyQJBHN6SnyWoOh4UE2P7Cdh+6/j7nZGfKsw8DQAq5742uoViuEUBQ7eHcZi/kf+/M8LybkxZR6evupVCp0spx6o8rS6lJG2i3woohinpnh7kxMz/HBe46wf64z/0KxZSlGiscpWAB3KtOHaQ8sAiuW37A8h2DFn1mKeQfzorgheI515gh5Tqj3YlmbKM8wUiyPgXaxHIfBjr27uePuO6n19POZ/TA40MNQJac+Mcmy5csZHuylZ6CPdRdcyIP33U+1UiWEUCzRkWdYFDHY38fo6DCzUT/nLm3z+ksOk6cZrXabo1MRuw92GOqr8pW7Z1i8aPBk45Mncccdd7B27VrWrFkDwFvf+lZuvPHGx/2H/8Mf/jDvfve7GRoaAmDhwoXPy1zPFsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUSzkpl/JRJuWkXMpHmZSTcikfZVJOykVOxmkvaTHPzBIz+1Ez+xywHfg1HitUuBF4GzDq7j/i7qda8PDO09h+6qTP7nBg8xa2fOkrPPzFLzO5dw+zs9Ns3vIwe+tLaW24nqRSIYpi3J2BgWEuWH8hy1edw7IVSxg7fIw9O/Zx9PARdu/az65te9mxdQ/NuSabH9zCji272LltFwf3HeLAvkNMHhsHoDnXIs8yohAIFoqOEU+yVasVojgpihhCDCEqtijC559HEcRx9/n8mBiPEzxE5CEijxKyuE4aV0njGu1Kg3alj1a9n9laP9M9C5jsX8LEwAqySoOoVsdDRBZFHItqNInIFyznwU6Nrx8L/PO2cSaOHmHJ0uUcyPu49757aTQabN+2jZ7eXkIwomDF9wN4aPOjfPHWb1H3o1yxssW3t/Xy+bv6+MfbKnz0C4Ev3u185X4jqY1SaVx4il8ROdHevXtZsWLF8efLly9n7969jxuzefNmNm/ezIte9CKuueYaPve5zz3X0zyrKJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpFzkZp93hwcwuBn4a+DFgmO5CDsBtwDXdx//S3WdP9xru/pene+zJsGCsumojyy6+iNCeYWbnYepxwmt/7t185YFJvrVrjiSOMIP+gV7ieCmzM3OMLByl0WgweWyS1uw0sICDB44RRxET41MkceDBex+gr7+PTiclSWrMzs6ycMkw7hl7dh6kVltOb2+DKIpw96LDgxVLYhQdIQyzYiNEj3V3MIo/iSCuHH8veZQUBQ8YhACeQ54Vj+dXE+l2nCguFHDybjuMCA/FmBAMt4DPXy9OqPX0kFRrRVFFntHZdh/5UAczGMjneOBok+GhjMHBQY6OHaLR0yDPc/KZlChEVPtX0Jye49D+gxyYu4wd41XanTk8tFiwoMMV64eIvMkXv7GVGd9PbzV5NmM/66VpyqOPPsott9zCnj17eOlLX8p9993H4ODg48Z96EMf4kMf+hAAhw8ffh5mevY42UxAuTyXdK+Uj+6VctK9Uj66V8pJ90r56F4pJ90r5aN7pZx0r5STcikfZVJOyqV8lEk5KZfyUSblpFzklDo8mFm/mf2MmX0L+Dbws8AIsAf4LWCdu1/7jM/yWWJmDA0OMlSr05k8wtz4Uar1OvVKlanpGcwiqiHCgVarzd5d+9mxZSe4se2R3VSrCUfHZrj7Ww8yOzVHX38vYwfGuO/uh/A8oVLpZXa6xaEDe2jNzXF07Bju4Dhf/vzX+eLNt/L1L93O7bfezTe+chf33vkAZkYI4fjSGDndwoPQLWSY36K4WM7CouLPKC7223yBQ+gWQHT3hQBx3N26BQ7WHWfGfL1KwDF7bF0QDzHBIvLcIW3Dsf1wzjoay9Zy8MB+lg7W6RsYhDxldOFCsjyn3e7Q7nRwh2qjn2aeE1XrNGoxjXySjctneMHKKc4fnWP9Of0sGelhoG+Iq9/008xc/YuMjo4+59+F7xfLli1j9+7dx5/v2bOHZcuWPW7M8uXLueGGG0iShNWrV3P++efz6KOPfse53vWud7Fp0yY2bdqkTM7AM5kJKJdniu6V8tG9Uk66V8pH90o56V4pH90r5aR7pXx0r5ST7pVyUi7lo0zKSbmUjzIpJ+VSPsqknJSLnIyTLngws48C+4E/BK4EZoGPAq9y91Xu/p/c/cn/xltSIQTiOKHR38+aNZczvGAhwQKRUazzYhAnEVEUgRuLli1mcHiQwweOUIkTDh84wvDCIYaGBxgY7OPY2FFGFy5g9dpVLBgdAc9YvnIZ177sWs49/1yGhwdxh6HBfhYtXMiqNSsZHhmip1GnkkRkaUar2QaKYowsdzo+3+GhW9hwvMiBbseHYp8dH2OPvcH51+kWNFigiDwU5Q3zHSPmyxtyB8+6x4K7491OE2QpdJrQOwg9CxhdupLdu3ax88BhZlopjzz8EBdfcmn3dEWHihDFzE6Ns3phH1ed22B8co577t3Jg/ffzyObdzKb1ti8bT9fuP0ge/aNQc9Czh1y5PRdddVVPProo2zfvp12u80nPvEJbrjhhseNefOb38wtt9wCwNjYGJs3bz6+9pE885RJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl3JSLuWjTMpJuZSPMikn5VI+yqSclIucjFPp8PBjQA34EvAOYLG7v8Pdv/xsTOxEZrbczH7XzB4ws2kzS5/w+pCZ/YqZ/UczO4VlOpw0zZgan4SkQrXRS+7O2NgxWnNNktjoqwYiM/oGe+ntqbFm7SoWLhxi5eplLFuxjOGRQUYXDtPb32B4dIjRpSP0D/bRP9igr78HLJClgSSpMzE+DTiddsbRIxPMzaa0mxmtVoexQ0c4sOcImx/axvxyFul8wYOFoughFEUPhmMOzHd/APL5Yof5DhDzhQ9GtzvEfMHEfDeHEwsh7PjngTu5w/xXI3MI890gKjW8d5CsdxiPK/z79/xHvnXHbczuvJcLNlzMoiVLaM7OcMmFa1k0OkwUJ2Cwc/tmHty8A4tqPLCvwtc3V7n1wYhmVqevnrFmYYcFfSm9+2/l4qXV0/uSCABxHPPBD36Q66+/ngsvvJC3vOUtbNiwgfe9733cdNNNAFx//fWMjIywfv16XvGKV/Dbv/3bjIyMPM8z//6lTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUk3IpH2VSTsqlfJRJOSmX8lEm5aRc5GSY+8n9i3ozyylaATxA0dnh/7j7/qcZ2+fus2c0QbPXAJ8E+plfdwHc3aMnjLuDovPED7r7TSdz7uUrV/s1P/F2ll90ET3VOofuvpeeKCFatoSvPHiUuycb/MilK/iFV13Iw/dv4cDeAyxfsYydO/YCOYPDI+zdvRsj4rz1q9lwyXnFu/aczB13x4A8z4njiEMHxujt7SGOK/T1N8iy4mPK8gx3yPKcYFacwp1Dk01+/GN3M5k6RI+9XctS3ByiCoSAeU7SnKDdGOZ4twZ38BzyfP4Deuzjy3OsNY1ZIK82sO41yVOG7/+/WATVWo1Go4eJygg/eeU6opHl/I+7DuO1BhbF/NTQMd513Qv41ff8It/cM8PP/ovXs2hkgJv+z59C1mb74UkOH5sgBGPdquWsXrOaf/ryrWS5k2Y5rdk2NnQRUbWHSgzBnXRqO1eev5i5LGPTpk2n+lWRZ9HGjRuVSQkpl/JRJuWkXMpHmZSTcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8jGzO9194+kcewrdEPht4MeBi4D3A79lZv8M/BXwaXdvns4EnoqZrQA+BfQBN3Wv9WFg8EmG/xmwEXh9d+xJnB+gKEwgCuSAWUSUVMl6BvHpnBCKTgejC0do9CQc2LmdgYGYZStX09s3yNrzl2MhEMcR7WYb95woisHz44ULmGEYZqH7vFhOw8xwd0II5O6EbpFE3i1S8CxjUZimEUcc8AaPdWSg2/Wh6NjgGJlFEKAKJJaTu0Oek3YLWjoWcby2JRjBM4iKOQBEwSDPic1Ii8+e3J28WNui+LCSCkRJcU13HCdEMSEEohBotVoM9DWoRP08emCcECKCGUeOHGXh6ELqjR7mmk2cDKzoSpF7RCczyHIqQBLDXHby3xERERERERERERERERERETk7nXTBg7u/x8x+BXgD8NPAa4HrgeuAKTP7FPBX7v7VZ3B+/56i2OGT7v5WADP7w+8y9vPdP686+dMbIUSkrRbHpicwTwlRTLW3zuTsEQgNKklMCMbWzdv4509/jJ64Tbs5y+RsypqLX8z5Gy5lerrF9NQxRhYOsmfnfiqVGlnapqfRS7szQ73ey+t/6NVFEUHu4PPFFkWxgZnhuRMMsizHrCh8qIeMN/Tu4u7mMAeaPd0CB8C7xRKPW7YiYCFwVW2Si2tHOTzTYd94k6W9gZmol1vmFjNHt0uEzy9nEXAzqpbzmt7DZO05NsfOkQwcI8fxbsGHO91lNbpzIMcw3I0kjknihLTdZmB4AYenA0PLLyMc2cvUsb20Wi1m52bp7+ul1WoDWTH/0C2gCA4eERnUKgmTLVU8iIiIiIiIiIiIiIiIiIjIUzuVDg+4ewbcCNxoZouBdwDvBM4Dfgp4p5ntOvGQM5zf9d1zvPck5rbdzFrA6lO5gGHMTU3R3PkIcdMJy4dpz02TtufAemgkEWbGts0P8tC9t3HllZfRu24tI5MTtCcO0NN3Neecu4qJ8Sl6++q8/FXXkmUZWZaRZzlpmhKiiCSJMQPvdpSY76ww3+XBQlH0UDwvOkC0ifl6axk7O/Xi2GBFZwfPjnd3ALCcovjBYE9WZ3qyn85t/4C35kj7e6lf8mJy6453KMoZILf5ogfY1u5nKMvI3eZPe7zI4fhcg3ULIIpOE3l36Y7Mc6I4pjU7zeb9M2w70KF/YIgFKy6iPTdB3jzG1NQUA309HDp0aP7EYFG3iAIIOcGcuFtgISIiIiIiIiIiIiIiIiIi8lRO+9dldz/g7u9393XAy4CPAnPAqhOGfdXMftHMVj3pSZ7eSmDO3R89yfHTQM/JnrzouJBTqTdonLOBZGAhIUR0Oh1wJwSjlsQEMyoxDPdWYeEwnX/9b9j5n3+ThVddg2eBmelZmjMz1GsVpidnyHOnWqkBgcGhQarVClmWk6YZWZp2H+eYWbe7A48tNwFEUUwIMb2JU4/gUF4vCg1CBFFRJODd7hDzghVFCDs7Vfbu209napLFo4uYm5qmNTWFhe5yGFAUTXS7QhCMTojZlfcQCN0VM5xg3cKH7tIZRW1E1H1u3WsGcpw0zYmiiNxz8rzJkrdspPPmfcxlh4mjiIWjo8zNzTHQ309cqREnlW5HirgoeiBgFNdIkuRk4xMRERERERERERERERERkbPYKXV4+G7c/VbgVjP7t8DbKLo9vAC4ErgC+O9mdifwN+7+O6dw6hzm12F4amYWA/3A5KnMPWunZJ0OwwtGmJ2cAYdqvU7/8CL2HgvESUSn3eLI1gdZNjLISwd7Wf/1LzKxeC07eobpH+rn6KEJJiYnSapVjh09xqLFi0izDrt37mHj1Zdx65e/yaVXbmDv7gNsuGwtu3Yc4KF7t/Oy11yJu3ebLhSdH4r3Uvz4n3pE00O3e8N8ZwWKwoPj62IYWI6b4YSiWOHobiY2XooPDzLcP47tbpHm84d3ixVwPHSLJww85IzQZH93OY2c+UYMAc9zcnd8vktEt1DDQsDiBIsCURxDlrPgpdew9ZoLueqeW1mw2Hios5AFC4c5MjbGyMgwy1esYG5ujhDG6NQjPCreg8WBpf0LqFerpxKfiIiIiIiIiIiIiIiIiIicpZ6Rgod57j4FfAj4kJltAP4f4MeABcBGiuKHUyl42AlcaGYr3X3X04x9KZAAJ9sNAtxpz0wzffQIIevgzVn6euvks7PkGfRWEqpxxNb7H+IVV1/GeRf+MJOHDnP/o7vwyQHy+hAP37+VWq3GOWtWcvHla/HcyXMHgytesJ48c97yL28gigODw/3kWcbipcMMrR8oih1OaO2QZU6r1aGnp4q7M5HG3NcapliH4rGODg7dLg3dAoTccIuL55ExecHLWDhxB+3rX8Hib+5gaOli+ho9PDKRsWu6gwPBnCwU3RsA5izi87MjDHtEToZhxRVDjGHkGETx8fHFx5cTohizQBzHuDu1+x+g838+wUPuXHbZEo72rKWWtxkcSumvV7ns/HNod9qEi86jv7cfT9u0OhkhTmhULmVu6pTqVURERERERERERERERERE5Cz1jBY8nMjdHwB+3sx+GXgTRfHDq0/xNP8MXAj8DPAr322QmSXAb1LUAnz2pM9uRnP/QaYP7Gev54wODDN0/gBfv/Emjix4AbP9a+jMNVkVJrhkwY/SvPQQ/3D3o1x+2U8SJ1XyPCdPM3KHai0hRAG3nBCF+Xk97hNOkoROOyeOY+qNoqghy53MHdzJ3Wm3cxo9RSFEO83IijM9rubBoOi2ELonj3LwiMjg8uokG9oPMXF0D6s+9beMjq7hFddtpK+/wcGZDj/7+QM8Mt4muGNRd4kKc/LYaEbdphEUBRtmxqp8gm/cc4jVl9QhXlAUPHQLNdIsY9/+o1hIiOMIyBkaGuLSyy9l8yOPMtcY5YVXXsat92xnadzPYDrOyGA/lTii44FqyBls9FKtVGjlgaNHjzB5rHPS8YmIiIiIiIiIiIiIiIiIyNnrWSt4mOfuHeBTwKfMbPkpHv57wL8G/r2ZbXX3jzxxgJld0R13NcVyFn90sic3M0YWD5M0EmjuJPYWcRQ499w6eztGinHgvm9xzsXrOfLlHo6u/zv2rNzDimOv4rbbHiYOEe12i96+BqvPXc3Bg0e48uoLaPTUiyUfiuqBE5aqMNydKAQsdIsYKIoMHKhWYirDEWmW43mOH+/qYCdMen6zxx7njofA4iTlFypDLL/2zWRveDX79uxj8dLF9Pb1URu8jyNDx7hu1Xo2T41jYb5owo53irC829fBi4KHHOizFg/t2Y0PrYAFC4vxOcUxDq12hsU1kjgibbeZHTvE2I49TB7Oue7Qa9jzlm9w3uQk99zfw+BoH4urVSKgFiUMNhLqjTpZ2qFe6yUncM8jO0/6yyEiIiIiIiIiIiIiIiIiImev8PRDnjnuvucUx++k6AwRUSyTcRAYAjCzb5jZXuBbwEuAFPgJdx872fObQVxN6BscYOXINL3VaUJkLKxuphamaZBySX9E36Pn84VjbSZmd9FameOVnDVrV7FyzTJWrV7J0PAIBoyOjtBupTRnW8zNNJmbbTI306Q11yLtpOR5jgNxEoMbeV7UFuRZ3l0KIyfPHc8dCwG3gPsJxQ65F5UReQ6eAcUJDMBgba3DJfvPZ8vXcu6/7x72HdjH7FyTPbv3kXYOct/Aw1yywuhPArkbWAQhKro2WITl83UURmwROMy1WhhFdwpC9LhCC3cvCiUMLESYGzPj4wzVeklaw0x/a4D/O/dl1l94hNSdRw5Ms23LVuIoIiEljmOwmBAlpGnKXKvD7kl1eBARERERERERERERERERkaf3rHd4OFPu/tdmdgj4Q2DtCS9dc8LjLcDPuPuXTvX8cSWh2qhRZzEtRgkBhvomiVtG3+wRzq8P0Nk5yufnDrG2fogxejhkB9m1bY5lqxayZ89+AhEH9o4xumiQRzdvZXpihpnZSRqNPuqNOpW4zuHDB1l9/jLOXbeS2ekWd35zE0eOHGX5isXs23eYdqvN1S+9lAWLhpmamKJWrzHb7OBZTsBxIOQ57jGe55gF3Pz4EhPBjHPqUM2G2NZJWJqMMNTb4JFHDrNrz2HeNrqVgcYIrZW7eMHSldx+eAeZOVlx5m7HhozccwAsGE63+MKdWqVyvLOEh4DTLcYwo1ZJiKKYSp6x4tzz2bJtHyPWQ4+tZG51hXXpDFm7yZTHnHv+eoJl1OsNLERUKzHtuTbmztHxSR7cdZDLlvac9vdFRERERERERERERERERETODs9JwYOZzRciuLu/6lSPd/cvmNk64KXAi4ClFF0fDgBfB77s7tlpTIxqtUq93uDQ/hEmj7So9zmHD+V0PBBNjrGutYEjQ9Ns3nSIPBxiy85Rqtlt/NDLf5w7vnY/eERvfy+tZpu+gT5azQ7nnbeSw4fHSdOMZSsWcfTwFCOL+kizNnhOvbfKVS+6kFYnJU5izlm3HAwaPXVmZ1oc2HOM0cWDGFBLZzmXA5B26KFJpX8BR0jYn/dxzHpIgUBGFWNZJSZJKhw+Wuf83kFm51Luf+gIjZ4qjVoH/0rMw1fcTcMXEpEWDRtCKJbOMCDPyPK8KHRwwKCeVIhDoJrERXcHio4OeZ7Pf4hUDaqVCucPDLD5wbvYf+AA1ewc2pUeJtIaixbNYZ1jTOZVxmYzevIZZuZaGE4cBdK5GdIs5+Ft+/DWHKCCBxEREREREREREREREREReWrPVYeHl1MsxnDa3N2Br3S3Z4QBPb391Kp1ktFFeGcCJyLvfyU+O8Tq5iOM+mI+6Xcz3XQ8neDwFyokL6twcO8YQyMN0o5Tqdao1RNCCAwM9dE/2Mvk5AxRMEIwGj01mnOzdDod3IwcqNcrHDx8lGarSW9vL9t27Wd0+UruumcbtWqgZ0EvR/bv55LWwywc6KFSqXJk70GWjPSw1Gc5b+4A+6acXWEB+fAKWp5TnZ2jefQo6WyNv/7UzfQO17nqgosYGa6xcOEw9Uc2sv22DzJz6Bwiz3GLcYvAHMPAc/IsJ3fH3QkEGrUqcQjEcVJ8Ymbg4F4URuA57elJcs/ZvmMrs1lG1Elx4FGvM7e1QR4fpc5hprOl3HP3I1yS7eXIXIfVGy/HalV2b9uOTU1AbQhvt5+peEVERERERERERERERERE5PvYc1XwsIvTKHgws3PcfcczP53jFyDzHMwYXLSK5swBojhh6XlXY/e0WZoexRrON+86TG9fjvU2WL5gPZOjR/jqvbcydHCIStxDnue0Oy0aPb0sXLiINHXuv+chKtUK993zEEuXL2XholEWLRol7aQ8+vAW7r3zQb5865fYvW8X9XqdkaFBfvHn/hU/sHEtew9Pc+/dd/PQtkfpjyHkKbVqL3GS0G7OkcQxs0cOUZs4xk+99ByufvlVvO9Tn+fD9+0n3D7GlVM/zPi5Tc5ZnrB+3QD1RkStFjGd9LOtL2b90UMk+4dIQ9xdpiKCUBQ8FB0ewM0xgyiK2bB6DQtHhmEydD83cIfcHfIcspxgAWvOsn37DqpxD3XrY2f/HPkXD7LfDrB02RrGdjgzoYfeei8j0QxXnruEVjCyrQ+zes1ivnDMixOLiIiIiIiIiIiIiIiIiIg8jeek4MHdzznNQ7eY2ReAPwH+4bSWrXgKhhFFUdHdAMPdyfOc8ak5bGaWudlp7ECdK1du4Nt7v8Z0u8KSgZW89uAavv32rVw9/UoGjyzFzEmimBAAK7o6/Mt/9SPkueOeYRhmxrGj47RacyxbvoSxo8fY/Gf3kWYps9OBqfFDvOdX/jPXv/LFvOyV1zE9PgadWWpRhbQ5zUw6R39vjbzT5ujhA8yNH+OiC8/niiuuZOXoEC9bkPNn//hZfm/jGxi+46tsqKymVh9n946tLFzUS7ud02w702Ep1ZFxgg8W3RosQAh4MPCU3B0zwwiYw/6j47xw/YXUenpg0sC8KF0JVixrYUaoNoiiQGZGf28vh47EvLv3bfzRb3+bVX+znM0Pb+fctTEP7omZsoTawBCV1hz12UkOTE7R12pSiwaYm52hUa89kxGLiIiIiIiIiIiIiIiIiMj3qeeqw8PpCsB13e2gmX0E+FN33/lMnNwMQoiJQkS73WFqeoYQGtx+77eZaY2yY/9+xuYOstyXk2fb2DVmPLTnEZbvbXD+wYV89qqPseObL+b+XT24QxIZIUlI4ogoMqJgJAYVdxoBevIZfurKUXYcPMZHPv73tFuzkDsWxXQ8Y6LT5pOfvom//dSnWbV6FWs2XMzMzBzBHAtGu53RW41YMDLEtVe8nFqtzuEj09SSQ1w0spyXDDS4ZXgJ1UVN5sJCiKcIUZX+oQGiqEJPo4/xibW0+h8gJgWs6OxgQDAsy8ncMQuYFcUfu+nlxXmGh1CMBaB4zQAzI8QxZoFao0GwwLXtFzDzzoMcneowfs9Ktiy6gMsuTomiiBawe6LDCwd7CZ2Mg9v2sLSeUIlj6j29jI4OPRPRioiIiIiIiIiIiIiIiIjI97myFzy8GngX8GZgMfArwH80s38CPsQZd30wKpUK4xPTPLRjJ30pDPcMsmRwkDRZxL1fGeNLe7/K0vBTtNsP8vDumNljU9xUGWH8KwlXPbicl49s4ZVLV7ItG+Br4xH3z3TILOsuFUHRDSF38JwlPs078gUcm5pi51QbPEDegcTIOh3wHAsxETlEEe2ZScxhdnqGpFKF9hxxdZA1519M36KlHD1wgK3fup3OxZfTare4c6pNtVZl9dqcYT+fkYUzLDvnHEYXD4BNMJ1H2MMLWVXbyZ151i12CN25GnmekucZIYRuVwpoLr+AWn9EOwTcAIrxnkOw4k3GUSAYhBBhecR1G17DX776T5n+uUsZm+iwd2IN1y3YR7VaJ087bJ10Lk1yjh2bYPrwUWYWjDDVjukkVZqzc9DoOYOvjIiIiIiIiIiIiIiIiIiInA3C8z2Bp+LuX3L3twLLgF8CHqGY8w8AfwfsMrPfMLNVp3N+MwAjhIjpQ0dpjk/Qbs6yuK+Hf3XJIL0h8PH7/oFkbpa4c5D2zgn64n7qQ0PsrC/lU1Mb+PXNa/j7bzxI/vWb+OHxu6hHFAUE8xew+WUgHMfBjMidPO3gvaOYBSp5hyRvMxjlrF+9jMEL17L4/POoVhLivMPY/n20p8fptFtctPEaRpeuILeYPETcf++3sNjYumcfAwuW0UNOX/0Qjd4lLF22jIGBfoIF0nQB3mmz8NAYi7fP0pu3IcSPzRHwLMW7S3sY4A5YhDu4heKNmYFFRReIEMC8ewrDKhUGh4a47eov883/8iBbH32EdPYYe3a1mJztYb4zxGRlkIOzHR7cvJOWJcxahUlPmGrlFOuCiIiIiIiIiIiIiIiIiIiIPLXT/nXZzK4zs6Nm9rGTGPv33bGvOJ1rufsRd/8dd18PvBT4a6AFLKHo+rDVzD5rZm82s+gU3gPLBhdy3rJVXLh6HctXrKHeu4A90/CRHX2Mrn8V7eFB9ozOcPGFL+fVl47Q+3APjbSfKxYOcPnCAdatXEn7ijdw35VvY8uSS7l40SDXLO7n6sX9vHDxANcuGeTVK0f4sXUjvHw0xsgxM4gSSNvEeYer4zbnV4wLe6v0BKPS6OWRB+6j3W7Rabfp76kxPXGM/PAhDj76CGOH9jE7eYROp8mWRx5i86OP8PkvfppjC1cy7gnp7C6C7aOSxCRxQogg9z42DMf0TByk5m16WpN4sBOKMgyytKhy8GKOwQALtDodstxPGAu487WvfIldD97G7ru+yI1//7dkFlEfrHH4nkfYccccOZMQHebgA5v45Xf+I63xfaR5zoRVmQ4V9h0+StrJmU1hTysiD4E4Pun45Lv43Oc+x7p161i7di3vf//7v+u4v/u7v8PM2LRp03M4u7OTMikn5VI+yqSclEs5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNykadzJv+c/l8AA8DHT2Ls3wCDwFvP4HoAuPvX3P3HgaXAvwPup3gf1/H4rg8rn+5cwQJLhhcStZyNF1zI2mUrWDDQz0suuoQXjNZ4+StewrUvfzmbkh5e9OKX0td3Af/yh5ZxWesg1/ZMc23PLNf0zHB17ywX93To6Ym5NJngsmSCyytTbLAjXBTGWG9jvGCwxQX1JuNjRwCHOMHyDqHSw/rBBusX9LNh5TIuWbSIwWoPUV+DscOHGDu4n7TTIskzXrhyBdVvfI5v//NnOHpoH2P7dpPECWtWrmRi6hjUa9SzOUb6e2i1+mg3O6SdNp3mHHm2g8rcNJOrLuFTU8MciHpwK5at6K5HgeUpkRnBjADEIWBRRL2SkMQR3RUsio4R7Rb/63d/m2VrLuacy1/B17/6Ze564GHGJ2e5c9cRsrSN5a/H/Sjp9EGWrmiwYCRmYHgReaXB1mNtMgtUPGUsdfZ3vPhYzJ46NHlKWZbx7ne/m89+9rM8+OCDfPzjH+fBBx/8jnFTU1N84AMf4Oqrr34eZnl2USblpFzKR5mUk3IpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLnIyzqTg4RrAgVtOYuzN3bEvPIPrPY67j7v7H1AUXnyVou+A8fiuDx97quUucs95YOcWOkmHeDDi0NQYe44c5Eg+yUe2N/nwo5N88MN/yfTecaL99/O7v/fPZOmfc9M//D0f3T7HH+1M+cPtHT64tcUf78z44+05f7wb/mSP8Sd74CMHYj68N+IPdsIv3j7Bn+yM6B0eIY5jzCIsrkG1j2WLlrDmnDXUDKYP7iOemqFnYJgj40eYnZ6kOTtLo9Uimt6PDY6w49572Hbv3ey6/WusWLOC4aFBbLpNs9lmfOwQX/rSLdxyS5MP/tEn+A+/+lv84q+8l9vv/CPe877f4MDULHdecB2dpIoFIza6S1o4pB2M7pfCnQCYBdwd9xzv1iI4ztG921m+fCXVWpVqDNe+5KVs3rmd/ZNz3L3rCPgwcA60tmG9iwnBOWfRfmYPbmFkfCuhPUuWVGgMDpDEgVa7w8SRMdLm7DP1FTkr3XHHHaxdu5Y1a9ZQqVR461vfyo033vgd49773vfynve8h1qt9jzM8uyiTMpJuZSPMikn5VJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRc5GScScHDcmDc3aeebmB3zDiw7Ayud5yZVczsX5rZV4AHgJd0X9oJ/F53X0RRDPFtM7v0u8yLW//py9z0t3/P333sk+zesZ252Sa3/NMtNDsp1hhg44YXsnnLBPfefx8PPxRx0bpRPvHeH+QtK2IIgfm2B26GhwAWcDPiQHdf8VonRKQhBowQAvQvIB9ZidX7GegfZO0FF7Fw+RqWjAxxbj2iFtcIzSYBGPSMS9eez0Q8SFrvYyAO9G29Hx8/Qu+CFWDGkpf/EHOj6+gkVXbs3cOu/Ue5/a493Hnvfew5eIhadYI8axHNTtAMFTx3HOjw2BIVlqXEIXQ7PDjmRXHDCZ87mOEBWlOTLF66lMEa1LJZRkZGOdZqki1ZQrM1i/sVuH8DPMU6LWamU9Yu2kLr4KMMz+xlpAr09dOJEvZ5zMEDe3nk/js5eGAPhw8ffia+JmelvXv3smLFiuPPly9fzt69ex835q677mL37t28/vWvf8pzfehDH2Ljxo1s3LhRmZyBZzITUC7PFN0r5aN7pZx0r5STcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSkXORlnUvAQA5VTGJ8A9TO4Hma2wcx+H9gH/CVFoYNTdJB4I7DG3f+9u18CvBK4j2LZjf/+ZOdzd7755a/w2U//Xz7zt59m357dNOfm+MaXvkwn7TBIi2vPWUuaHeKOh+/lR665ikb7WlatnuIt50T0RV4UPHQ7JBx/aEYE4N0d1i2ECAFwQhSR9wzigwuhZ5Cjh/fz7W/fz/Rsk0ZPRF97nMqRMc7v7WFtbx8bRkfoCc5wX4P+CqxbMsC6BVXyNCMeXkJSrdNccQmdSgNvDOJRQhR3IKqSZRlZ6qSp05qbJWu3cSDNc3A/XuwQZSn1rEWtUqG3WqderdGoVqiRYWaEEIFFRZEHRSGEAcMLFtPXPwBAf/8AWw81iftHMLsW8r8qiiTaU8zNOksXp/T09TEwuohFy1aw8uLLiZas5KjFLL/wYuoDg7zkZa9idHT0TL4m8hTyPOcXfuEX+J3f+Z2nHfuud72LTZs2sWnTJmXyLDqVTEC5PFd0r5SP7pVy0r1STsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXATOrOBhH9BjZmufbmB3TC9w8FQvYmY1M/tJM/s6cC/ws8AwcAj4LYoihze6+2fc/Xg7Ane/BbgeSIEXfLfzhyguChKCYRh57lgIEAIjIWWgbyFrl89x0fKF1KOI3Q8PEPdtYXVPxrV9xRIQhPnOB3a8H0LLQ1FMgB0vinCDPPeieKDWgP4RfGABVmkQ2tN0OtMcGJsiTSOWk7FkwRLOGV3IipFhzlm6kMRSqvUas+2MEEW0ooQt4zMcOnKMubkmnmeA43lKsD0EX4B5xvQ0TExEZLnjUUziKUmeY3jR2cFzaoe2siI7ysjAIMtXrqanp5+BwSHOG3+UKOuQzxdHdBtCNHp7OXhwP9MzLUJUYWxsDE9zJjowsHw91rMOOIZnTTxv0mxm/I/fmqTeE7NuzTkkSYTFFeoLFlHvHeHYkaN0ZuewLD3Vr4icYNmyZezevfv48z179rBs2WONVaamprj//vt5+ctfzjnnnMNtt93GDTfcwKZNm56P6Z4VlEk5KZfyUSblpFzKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUi5yMMyl4+Fr3z18+ibHvoejEcOupXMDMPgjsB/4MeCHFb+23UCxVscLd/5O77/pux7v7QeAARZeHJ7+G57g77o6ZdbeAAXVzQljE0gXj9PQPcHPjSm7+xjhjh6aIK+O8ejTFPO9e7Iknnt/p828Gx8g9J4ojrNaARi/N3gF+31bzj80+vrLtCFsPTjBzeD/94/toHNvP0tkxWocPcmDLQwxXAz43S5S2GM8S2vV+9owf40/+6ascnBiHPIO4CrUGfQMPMbwwwJrLabcDD98VSLMc7xkkdyMiY74YwwxGpvfR6O3lgvMu5Ad/4HW8+TXXc9G6C1g62EO1EhNCKOo6PAczhpafy55du8g6LeLI+MbXbqG3f5g8rkFYDPWALbiApH85vcsupndkKb/0ay/g3IsW8sgMjM11GD96FLfAJecupzekNJtNxo6MncpXRJ7gqquu4tFHH2X79u20220+8YlPcMMNNxx/fWBggLGxMXbs2MGOHTu45ppruOmmm9i4cePzOOvvb8qknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOykVOxpkUPPxvip/1f9rMfsvMvmN5CzOrmNl/A376hGNOxb+hKFYYB34fuMDdX+Xuf+vuJ9sK4BvAV5/8JevWJRSdDsDJsxTynIq3ubp3mmocMdy7j90D5/Lggkv4u+pGbvtKhZ5h47y+Yp2O4vj8O4seutc4Ya0L8tyLZSHiGJIKXqlyuNrH5sogt6c9fKHZ4O8mK/zV1oN86L5H+dJcnY9tO8RfPbSb//XQBJ+eHuTh2iruri7n2OASWhaxY2KCTtbG0lmIElj/Ei5Yd5DXvn4d+UUvhriHnv/jpFGN9sACUs+KIo9QdKHonzpAz9ReZjop565aycWrl3Pp2lWsWbaMLCRMuYHnx5frMDMa1Qo//55f5dt3fZ1bv/gZrr72JaSNQWYObmPu2DhhYDMMLiAj0J46Smtmitu+NUOYeZB7H9nKrVu38+VNd/Clb3yd3TseZaQnobe3l/sffOSkvxzyneI45oMf/CDXX389F154IW95y1vYsGED73vf+7jpppue7+mdlZRJOSmX8lEm5aRcykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclIucDDthFYhTP9jsAxRLTDhwBPgCsLP78irgNcAIRWHEB939507x/N8E/hj4G3dvnvZEv4tzz7vAjx6dY2LqEDi86rXXsXj5Oj5z49/yynf+O961IiNqrOX2L3+cP+t5EVv7ziVkGb9Ru5efWjfCrWEBP3ZPlU7e7XwQx91lH4yG5cwQgRvznR6Gszn+14uGmMwq/LtP30VnZhymj8DsJMxNwcRR6LSL4oLODDZzmCWDfcw02ySLVjE2sBwsUM86XHPuBdyzexu9w0N0WtOMD59LVm1QqfcwMz3Di/Z8mR960w388reO0vfIbXxk8zf5uWUXsP/1P0MFY3jr7ey99AdwM/ru+Sd6dt8NIbD+vAtZtGCUOIpodVIOHDtCNU4495pX8uGpIXIg9owfP3Yb73z9q/jV//grDA4N80M//MP85v/4AM36KJdfdA1fv+8Bjh7bDeOH6EuP4VGNRcv7+OGlVW5uXcTk7nuZHttBnmZkeUalUiHEMUfGjnLZxevUaqZkNm7cqExKSLmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPmd3p7qfVmiM+w2v/PNAE/j2wAHjrE+cGZMBvA//pVE/u7i88w/k9pTiOeM31b+Tv//4vyPMMs8CCwV7+57t/jJdcex7V0eX83cc+xs12LjsbKwEHg4UjI9T2HGJsyaKiYwNWNHfw4z0jaGMn9M8o9s0vcJFZIK/UoT1XdGQIUbFVa2AOnQ5e6YP6IM3+OrVGL625GQgJ7jlzuXNookOjfxXDYZKpqMJhC/R6h4XZBI/2j3JwLmX5koXEO7+K5zl1B2v000/K5WGCHZYBEOU5jekxGtUKWGBidob0UE4UItydPG+TesbsXJPIwN2pept06ghZu4lZTAgRWdohswqN3gFueM0GvnzP7URJhaRRZ9SazHXgwIEWE4czfmbFMT568cvY8rVDZOkUnTTD8yZxkuDZyTbuEBERERERERERERERERGRs9kZFTy4ew68x8z+FPhJ4FpgMcXv+gcolpP4C3ffeqYTfTZ02h2mZ2eIK1XwjNic116yinVrVlNbtJwPfPiv+dOJczkyupQcIIcqGYuiJsnRY7CkKGQolsMwcPAABKNzwmohx3s8mOEOZobFFaj1QtqGrANpC6L4hOUvwEOgRcxQo4fccyLPMU8Jwdl+dDsvOOdKdkzNYZ0pzJ0WFQ5bFQ8JU9VBapWEyra7MEJx7OAiGqTsace082Le1p4lmT0KueOWc2RqgmPTM0RmBDOGBvrI8g4Hx45QHVlKlDu4EUcB8g4LRoao1RuEKIbGAK99+QvYc2QaqzSoZynDblSpE1ed2fEWN9UGedmB7fxAtc7HV1zA+J4HieOE5twsM8eOkZ9BxxERERERERERERERERERETl7nGmHBwDc/VFOo4PD883MeOihb9PoawBw6fIFnLvmHOgf4X986K/51MQwY33LOP4TvDueZ0zMzJFPz5C0mzj1+bNRlDXY/ODicVEHARhuRp5lWESx/EWlDvU+yNpYnkGa4lkHci/OklRIQmDY51jSW4U4IrMKeMaR6aP41CNU6SHtzNKXz3EsDDEX6jjGRCtjenqaqDlF1pxjKk8Z8FmMFtu8xmCaYp4TWtNYnhKFACEwsmiYLM2YPDYD7uR50Qmi027Ra84sgOfEIeCesWb5ImbaOYaTVCq8+oWX8p/+8JPEecogM1x0zkKs+xksm21x9+a9/IdOykce2cSeC6/i7vMvJ5o+QLPZZG5ulk5HHR5EREREREREREREREREROTpPSMFD882M7sUeDfwYmA50PMUw93dT+p9WTCqtTpJq8Lla1fxjh97O62ozm/8xm/ymZGXE5KkGAfHix7aBDZPZ7Q9J5qZBa9xfBA5eA4eE1uxlkex1IV3Ozc4Zk6EY2YQYswCtbTNEHPEFcfpw6oxA7099FYNq1QYp8aWTiDPApa2IUvpeIM4d/ZnKSvSJv3ju5mZ6+CVBp7E+PQ4X/v6N0lbs6Tu3JXn7L/rqywf7GdFqHDo0G4qd/wDSXuG2DOCxQwMDjLaN8REcz/NWafddMyL5S0arWnOtzlawcmYpj+CKEpYumwZ+w4d5djUHBecdy5TzQ6Hxo4xNDfGdVetoV6JircfAlEILFu6jC/ds4Nfn57hN7Y/yLFLX0yycgkLeopikDzP+dad3zrl74iIiIiIiIiIiIiIiIiIiJxdSl/wYGb/FvhdIOKx9gnP1LmJ45hVC0f51Z97N8emmvzZn32Qe3Yexoba9DJLbn00PTCXOoYBGffOJEwZhKlJLOslWMBCIFgAjCxv4919xYXA3SFP8TwniiEJUAk5NI/ygugwF5y7jDSDnYfGGJ+b4mgnZftEylww3NJiuYw8o+otBkObSlyhxxr0Tu5nWb/x4PQ0lbl9JJUqnXab/NAuPvbJR2m1OwQzPto/QtzoJXjGkoE6i9dfSBJixsdTDjfBceI4JkszmjMp/UsGOLpzquhqAYz4FG+Id9BJU9Kkw0QSE8cVemsVDo9P8o9/80/86Jtfw59+4h/o74zzL99wNcPDfRgUn5s7nTxjxbLFNGoVPvO1e/jjZspP7n6EP7n8FawYcVYPQBTHKngQEREREREREREREREREZGndcYFD2bWB7wBuAQYBpKnGO7u/tOncO6rgQ90n/4R8BngZuAo8BZgMfBq4O3AJPBzwP5TOD+vuPYl3HDNWgZqFW77yme4YnU/PVGLT37xwzRbs1TihJWDdZqdjIhi2YeZniqHL72A4d0Ps/aOT5DjeIixKIBFZHlOiGKSOKaVOy0iDKgmCVz2TpIsZ9Ht/4e+KuzZtZsHO22WvOyFTE3OMD12kD3bt+Jm9FtgIESEOCEygxBoJBGLhxqkaWBZpc6KEWPHzr2MZDmXrz6HRsM5dOgw26o5rWofed6mHhtz3qGSthke38+LL1xKljlRHHPndMqREAhYUbCR50wdmSNMdMBC93MKzMzOkremCQ502uQOYDzw0KPsvv9ufuiCpUxt3sSRrTt568svZcFgL1makyQJcRIRRRF5nmPAC69Yz8KhXv7ixlu4IDrGVa0H8fwcKnEv8zUiIiIiIiIiIiIiIiIiIiIiT+WMCh7M7B0UBQm9J+5+kqHOYytDnHTBA0UBgwG/7+6/0L0mQNvdv9Qd8zEz+1/A54HfAK442ZO7O2//kdczwiQP3P8Aj4zNYu50kkEW1A5i9X7qsbFmUT/Tcy0cyHJI4oS9UcKySpXVg1XSLMMMQlR8nO0OYCl4ByKnUknAjbgC3unQ11vnjReOEgV4ILSYnesweWyCOA6MDA4wunEjFowQIuI4Ieo+NgPMCN2qgPEjR8nm5lizaiX1Rp3egUGmpqZptVPOXb2GqekZsoGEvr4+HnroYWq1hIWjQwz3NgghInWn0+kQByN4zvjhgxzdu4fQ6MEzJ4oDSRQTgtFqzrF32zaIAo3ePnDotKaJSfmxl67myjUN6o0Kr7n4KsYYIs9z0naHEAxyxyKKggqDLMtZvXoV73jDtZzDLq6+bJShVefw4CFn75HZU/h6iIiIiIiIiIiIiIiIiIjI2eq0Cx7M7HrgIxQFCU3gm8A+IH1mpgbAiyiKJD7whP2PK6pw92+b2c8CnwB+CXjfyZzc3fmbj36UH7/hZXz1/q3cs+soFiWEKGbRmguJ4yqZ54yZQYPjZRs5cKh3gEvPWcnCycDhmRnAiKKYYFDrztAdBqoRI3114igQhUBkRiVJ6F+4DPOca4YX4XlOMMM9x4HcHRxCCITISKIYrFhQA3fS3OmkKUM9PbTnmixaspBGo06cVIhC4IoL15LEEeZO7jlZlvG6l7+Idielv7+ferWCRRFuRjvNiM3Isoy5VpOQ54wsXMRMqwVmRKH4qD0EBgYHCQZpp4OnOXMTh/mxFy8mmQ1MT08TV/upVxMObN+HxRGRBZIkIYRA3ImwUDxPopiQt7lgtMq6BWvpeMyerZvJfJjgtdP9roiIiIiIiIiIiIiIiIiIyFnkTDo8/DJF4cE3gTe5+9gzM6XHWQS03H3nCftyujUFT/BpoAP8ECdZ8BBHEdboY3J6mmPTc+QWMIc8y8gzp9VJwUK3u4Id/5MAeb1O5aJ13JD08rdfvYu5TopZwIJheDHejOH+BkP9PSSRMTk5jTmQ5/Q0esnas0RmRCGQJI9FYWa4gxnEwbrXDiRxjJlhGJ0sxa3onpAD7U6nqLDIcyKDJI6Joog4iYmjiBACjhGiCDfIcmeu3abVbhcdGCgKLDztkHdamAW6LSVwz0nzQO/gAOZOu9Vi5tgk9f4RbrvzG8yOH2FiusmqUaOTNEnTBMsiUgu0u10erPs+AfLWLEvDGHEUs2+8zlQeSJMhqr0NkuoZr7IiIiIiIiIiIiIiIiIiIiJngTP5dflKip4H73iWih0AZrvXONEU0G9mVXdvze90946ZzQKrTvbkaZox22ryyLb9vPTCNczcu4WpdloUNViA4wUMxQ/2TjGbyKA3idi3dy9XrFvBeSsX87W7N/OtLbvo+GPFAwFn2eggeZZyeOwwh4+Mc/DgYfr7eli1Yim13iEiC+R5RhxFRFFEiAJRt7CiWL7DyfOMkOd4nneLKgKNUCfEEWCYBXJ33HMA8rzo6tBut8k7HTppVnRWSBIMJ09zyHO82abdblOUNYB3r9lptQi1HkKIiiUpHNIsxzEGeuo0k4Tp2Ra5xYysuYQlwQmek3ULRJZVKt0CC0jTlE7uZHlWFHEAnXaLrLOIJA5MdVJSjCiK8Dwjbeen/20REREREREREREREREREZGzxpkUPMTAtLs/+kxN5knsBS4ws9jd55fK2ApcDlwFfG1+oJktBQYoiiROiruzY8c+ZmZn6B8cYWDBKIPdYoOigMCJu10VsiwjhKjo/pBnbNp1hHt3HWao/xEGenpILaavUSfrnjuJYxb0JgwP9nHkyFG279yNhaKYoa+/gQO9fX0kIcLMCRh5noM7cRwRxzFRHBEs4CHguRcdHCgKKjzPsO5+x8Eics8JIYBD7jlpJwWDgJNn3fEObt01QfKU/mrM1NQEbkZwI/ecTrNJpVonNvAsB88JUUQtCtx37/2ESp2FCxfx0L33Y55y/poV5K02mJFlOXmWEaKIShzj7t2iEci7RQ+eZ4QQikILA7qfdZpltNPsSbMSERERERERERERERERERE50ZkUPGwF1plZ5O7P1q/UDwEbgIuBu7v7bgGuAN5nZje4e9PMKsD/6r5+38mePEkS3vXud1OtV9mybSc7d24tOjOEootCCAH3osFE7nnR6QG6mxPMmI1imt2xwyM14iiQZSlpp8XCoV6CO+25OVYtX870XBt3p1Kt4Tj1apVKUul2USg6NKRpikG344GTkhFyJ4pjnGIZjiiOsWCE7rITeZ4XhQqdlBACeZ6TZhlxnGDdtTEidzx3mq05mp2Uickp9h84RC3rkGQ5IakwMXaArNOmb0WDZHqcfG6WxuIlLFiyjMFGheGBBquXL2YuNxYO9xLHEe1OYGJimuHBAZJKQt4teEizjFanTWQRcYjJ8hQnFB9eHMhycM+Lgg33bleNmCjRkhYiIiIiIiIiIiIiIiIiIvL0zuTX5f8DvB94LfCPz8x0vsM/AT8KvJHHCh7+EHg38Cpgj5k9ApwPDFMsf/HBkz15mnZYtHABURJz4MBBli5ZQtz9wT2Y4bmTVCpkebHMQggBADMjMiNExXP3nKh4RJ5lZFnG7MRRBvr6aLdadNKM1SuWMtfOiJOYNM3p7+unlWXEiR9fpsLdSOKEKIrA8+5aHkaYv3axwgVZlpF1csys6DqRZ92uCgE8x9wJQKXbnQKs6LJgRm9vD2masnDhQs5fey7XXHUFs80WmUMcGYcOH6VSqbB4ySJqUSCOAhZFpJ2USpIwODhMMCPLi+4Xadohy3JazTmac03wnCzNoLsURittUavViOKINE3xPCcORppl3XkVS3CYGXnu3ZYPIiIiIiIiIiIiIiIiIiIiT+1MCh5+H/hh4I/M7JFnaWmLvwOWA/vmd7j7djN7O/DnFEUOL+y+lAO/7e5/fbInbzZb3Hn3PVgw3DPMrCg+6BYWYE6apZg77Xan6GCQ58RRBBhppyh2COYMDA1QrcREUUyr1aRdceJKQq1W4fLLLsFCUTwQrFskgZNlOVEwvLsEhXnxNtJO3l3eopiG5zmGM9dsUq1UsG7xg/tj3SbyojqCEEV00g6eF+cwrOhYYUYUR+QOaadNsKIAIphRSyLyLCdOYlYsHC7OODfLTJ6TdTrkOM12h2CBTqdNq9Mhz5wQR+RpyqGxY9QqFQiBTrvF1MQkcRLTqFZJ6jV6e/vo6e2l2Wqyb+8e0jTDMCq1Ku5QjbrLdjjHO2qIiIiIiIiIiIiIiIiIiIg8lTMpeHgb8FHgvwD3mNmngNuBqac6yN3/6mQv4O7jwK8/yf5Pm9lXgNcBK4AJ4J/cfctJzx5Ikoj+nqj48Z8IrNItDgAcOmlKluU4Rl+9QRSMKArF8hN5Tpo7laQCWYdVS4eZnJwmyzp08haHjx4F9+4yGI4BWZaT5xlpp00cRWQAueNmtJst0rSDRTGOkXvRVcJzyPOMTprinpGEYhmLLHfyPKdWrTA31yTPM6I4JuBkWUY79eOdKaLuEh3zRRBxHBPHgXa7U3SDiAJ5lhNFgTiKyTopUTDaWYqZ4QQ67SbuTu5OljuRGTlg7uTdoorMHc9S8tyJokA0M4O7MzfXJFggiiI6nRY5RReHEEW4F+81ChEYRHHlVCIUEREREREREREREREREZGz1JkUPPwFMP/P8Q34se72VBw46YKHpzyR+1GKZTXOgHHvt+8miSMc6KQdghVLRIQQyHMnB4JFZHmK5xmRQZpm5FnK4iWLaTR6CWnG1MRR0qxDp92iv1HH04Td+/fQ3z/E/n07ikIJAvVajanpKTzLACdzK5a56KRkWYZFEd1KAtI0o7enj7m5WTpZypKhIfZMjD+2tEWe4rkTxTFZmhJFEXEU0UlTci+WiijeZsA9x/OcTuYMDw0xPTVOtVbDLCLtzJJnKZVKjLmxvFFn0CJ2zjY5mqYsXriGiendZFmKRTFpllOrxvTWe5menSV0P79qUiGOo6KbRBQVS32EiIFugUPRncK6y2w4cZJgFqhWK1SSGHenWq1x/wPfPrNYRURERERERERERERERETk+96ZFDzs4rGCh+edmQ0AXwbc3a88mWN2bN869vu/99s7n92Zyam68sorTyo/ERERERERERERERERERE5e4XTPdDdz3H31ae6PZOTf4IYuKy7nRR3H3X3jdpObwP+E9AHDAKfepLXPwY0gArFsiM/fJLnlTPwuc99jnXr1rF27Vre//73f8frv/u7v8v69eu55JJLeNWrXsXOnar5ebYpk3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lpFzKR5mUk3IpH2VSTsqlfJRJOSkXeVru/n2xASMUi0Fkz/dczoYNiICtwBqKgoZ74P9n77/DLTvL+/7/fT9rrV1OL3OmnekatRlp1EZIFIOoAmMEbgRcsYn1tYPtX2zHIXFiEiexQ76OYzvG/sbY2HEDTDHFIDqIKiFGfdSm93qmnL7LWuv+/bH2GY2EyhRpZsF8Xlybc/baz1rr2ftzHl2Xrn3rfljzpDEvB7o6v/8S8I+ncu3rrrvO5cykaeqrVq3yrVu3erPZ9HXr1vlDDz30hDFf/vKXfXp62t3d/+zP/szf/OY3P+t1lcmZe74ycVcuZ0NrpXy0VspJa6V8tFbKSWulfLRWyklrpXy0VspJa6WclEv5KJNyUi7lo0zKSbmUjzIpJ+Vy4QA2+Bl+b33GHR5Ol5ndaGYvPVf3k+fdC4At7r7N3VvAB4E3njzA3b/i7jOdp3cCS87xHC84d911F6tXr2bVqlVUKhXe8pa38IlPfOIJY17+8pfT1dUFwI033siePXvOx1QvGMqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUSzkpl/JRJuWkXMpHmZSTcikfZVJOykVOxSkXPJhZbmZ7n+a1PzSz9z3LJT4GfPl0JielNgrsPun5ns6xp/N24DNP96KZ3WpmG8xsw+HDh5+jKV549u7dy9KlS088X7JkCXv3PuWyBeB973sfr3vd657ytfe+972sX7+e9evXo0zO3HOZCSiX54rWSvlorZST1kr5aK2Uk9ZK+WitlJPWSvlorZST1ko5KZfyUSblpFzKR5mUk3IpH2VSTspFTkV8muPtaY6/BZhP8aX2mZwv38fM7KeA9cDLnm6Mu78XeC/A+vXr/RxN7YL293//92zYsIGvfvWrT/n6rbfeyq233grA+vXrz+XULljPlgkol/NBa6V8tFbKSWulfLRWyklrpXy0VspJa6V8tFbKSWulnJRL+SiTclIu5aNMykm5lI8yKSflcuE63YIHkTl7gaUnPV/SOfYEZvYq4D8AL3P35jma2wVrdHSU3bsfb7yxZ88eRke/u/HGF7/4RX73d3+Xr371q1Sr1XM5xQuOMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSTsqlfJRJOSmX8lEm5aRcykeZlJNykVPi7qf0AHJg39O8th/InuX8Zx1zNg9guDPH5+0eejzh846BbcBKoALcD6x90phrgK3Axadz7euuu87lzLTbbV+5cqVv27bNm82mr1u3zjdu3PiEMffcc4+vWrXKN23adMrXVSZn7vnKxF25nA2tlfLRWiknrZXy0VopJ62V8tFaKSetlfLRWiknrZVyUi7lo0zKSbmUjzIpJ+VSPsqknJTLhQPY4Gf4vXU4Z5UV8n3F3VPgl4HPAY8AH3L3h8zsv5jZLZ1hvw/0AB82s/vM7JPnaboXjDiOec973sPNN9/M5Zdfzpvf/GbWrl3Lu971Lj75yeLj/83f/E2mpqb48R//ca6++mpuueWWZ7mqnA1lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqWclEv5KJNyUi7lo0zKSbmUjzIpJ+Uip8KKgolTGGiWAwfcffFTvLYfmO/u0TOcfypjslOazDNME/BnuoeU3/r1633Dhg3nexpykvXr16NMyke5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUj5nd7e7rz+Tc+LmezFmy8z0BERERERERERERERERERERKb+yFTz8zvmegIiIiIiIiIiIiIiIiIiIiJRfqQoe3F0FDyIiIiIiIiIiIiIiIiIiIvKsTrfgYYGZZU/34jO9RrFdhZ/m/URERERERERERERERERERES+y+kWPNjzMgsRERERERERERERERERERGR03A6BQ/abkJERERERERERERERERERERK4ZQLHtxdBQ8iIiIiIiIiIiIiIiIiIiJSCuF8T0BERERERERERERERERERETkdKngQURERERERERERERERERERL7nqOBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQURERERERERERERERERERL7nqOBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQURERERERERERERERERERL7nqOBBREREREREREREREREREREvueo4EFERERERERERERERERERES+56jgQc6Ymb3WzB4zsy1m9u+e4vWqmf1j5/Vvm9mK8zDNC85nP/tZLr30UlavXs273/3u73q92WzyL/7Fv2D16tXccMMN7Nix49xP8gKjTMpJuZSPMikn5VJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRc5Nmo4EHOiJlFwJ8CrwPWAG81szVPGvZ24Ji7rwb+EPgf53aWF54sy3jHO97BZz7zGR5++GE+8IEP8PDDDz9hzPve9z4GBwfZsmULv/Zrv8Y73/nO8zTbC4MyKSflUj7KpJyUSzkpl/JRJuWkXMpHmZSTcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3KRU6GCBzlTLwCqwJ3APcAHgTc+acwbgSEz2wL8FvAaM7NzOssLzBvf+EZ2797NLbfcQqVS4S1veQuf+MQnTrzu7vyP//E/+NSnPsW6detYtWoVX/rSl3D38zjr72933XUXjUaDG2+8kWuvvfa7MgH4+Mc/zpEjR1i9ejW/+7u/y+c+9zll8jzTWikfrZVy0lopJ+VSPsqknJRL+SiTclIu5aNMykm5lI/+PbKctFbKR2ulnLRWykdrpZy0VuRUmAKXM2FmPwa8DXgX8LcU3RtucPdfPmnMDmAb8ErgBuB2YIm7jz3F9W4Fbu08vQLY+PzN/pyZB3zXe32eLQK6gBrwEDAE9AC7Oq/3A6soPt8KsBSIgUeB9EnXmgeMdH7vAu5+Pid+Dp3rXAaBYWAfsBLYzxMzAbgSaAKbgG7gUuABvjsT+P7MRWulnLRWykdrpZyUS/kok3JSLuWjTMpJuZSPMikn5VJO38v/HqlMnjtaK89Oa6V8tFbKSWulfLRWyul85PJ8uNTde8/oTHfXQ4/TfgA/BvwlsILiHyI/DbznSWOOAu846XkLWHsK195wvt/fc/QZnfP30cnlg8DGzvMn5AL8ObCbovAE4DFgBzDvWa47fb4/z+/VXJ7ntfJ9kYvWSjkfWivle2itlPOhXMr3UCblfCiX8j2USTkfyqV8D2VSzodyKefjXOfC8/TvkcrkOclFa6VEuWitlC+Tk3LRWilRLlor5cvkpFy0VkqWS9neh7a0kDO1l6JKas6SzrGTpZ0HZhZ3jtWf/6ld0PZSVLvNeXIuoxTViUtPGj8AHDkXk7tAaa2Uk9ZK+WitlJPWSjkpl/JRJuWkXMpHmZSTcikfZVJOyqV89O+R5aS1Uj5aK+WktVI+WivlpLUiz0pbWsgZ6fyDfBPwMxTVUynwE+7+0EljHgS2uvubzOwtwB8Dr3f3DU9xvRNbWnR3d1932WWXnYN38f2p2WyyZcsW1q5d+12vbdmyhYULF9LT0wPApk2bGB0dpbu7+7vGHj58mLGxogOOmaFMzo5yKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqWcnotclMlzS2ulnLRWykdrpZy0VspHa+XCcPfdd6funpzRyee7PYUe37sP4AeBbRT7Ff2HzrH/AtzS+f0vgTuBLcBdnbGLnu261113ncuZ2759u69du/YpX7v11lv9/e9//4nnl1xyie/bt+9Zr6lMzp5yKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOyqWcnutclMnZ01opJ62V8tFaKSetlfLRWrkwADv8DL+z1pYWcsbc/TbgFcBmd//dzrF3ufsnO0M+BhwDLgZ+FRhz9/3nZbICwC233MLf/u3f4u7ceeed9Pf3s2jRomc/UZ5XyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmXclIu5aNMykm5lI8yKSflUj7K5PvK2JmeGD/7EJGnZmYfAG4C5pnZHuA/AQmAu/8f4DaKLhBbgBng587PTC8cb33rW7n99tsZGxtjyZIl/M7v/A7tdhuAX/zFX+QHf/AHue2221i9ejVdXV389V//9Xme8YVBuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSTsqlfJRJOSmX8lEm5aRcykeZyKmwokOESHmsX7/eN2zYcL6nISdZv349yqR8lEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflUj7KpJyUS/mY2d3uvv5MztWWFnJemNlrzewxM9tiZv/ufM9HRERERERERERERERERETOHyv87853yA+Y2bXPdo4KHuScM7MI+FPgdcAa4K1mtub8zkpERERERERERERERERERM6j1wEXdx63Av/fs52gggc5H14AbHH3be7eAj4IvPE8z0lERERERERERERERERERM6fNwJ/64U7gQEzW/RMJ6jgQc6HUWD3Sc/3dI6JiIiIiIiIiIiIiIiIiMiF6bS/R1bBg4iIiIiIiIiIiIiIiIiIiHzPUcGDnA97gaUnPV/SOSYiIiIiIiIiIiIiIiIiIhem0/4eWQUPcj58B7jYzFaaWQV4C/DJ8zwnERERERERERERERERERE5fz4J/IwVbgTG3X3/M52gggc559w9BX4Z+BzwCPAhd3/IzP6Lmd1yfmcnIiIiIiIiIiIiIiIiIiLn0Ejn523ANmAL8BfAv3q2E+PncVIiT8vdb6P4gz352LsA1q9ff17mJCIiIiIiIiIiIiIiIiIi59xhAHd34B2nc6I6PIiIiIiIiIiIiIiIiIiIiMj3HBU8iIiIiIiIiIiIiIiIiIiIyPccFTyIiIiIiIiIiIiIiIiIiIjI9xwVPIiIiIiIiIiIiIiIiIiIiMj3HBU8iIiIiIiIiIiIiIiIiIiIyPccFTyIiIiIiIiIiIiIiIiIiIjI9xwVPIiIiIiIiIiIiIiIiIiIiMj3nPh8T+DpmNliYBTY5u5HnvTaAuCtwGpgErjd3T937mcpIiIiIiIiIiIiIiIiIiIi50PpOjyY2YiZ3QbsBu4EDprZX5lZtfP6G4BNwB8AvwT8W+A2M/uqmQ2cp2lfkMzstWb2mJltMbN/9xSvLzOzr5jZvWb2gJn94PmY54Xms5/9LJdeeimrV6/m3e9+93e9vmvXLl7+8pdzzTXXsG7dOm677bbzMMsLizIpJ+VSPsqknJRLOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcpFn5e7P+wPY1nlsfZZxEbAByID8pEcGvBdYAkx0js0Ce4HWSWM+fy7ejx4nstoKrAIqwP3AmieNeS/wS53f1wA7TuXa1113ncuZSdPUV61a5Vu3bvVms+nr1q3zhx566AljfuEXfsH/7M/+zN3dH3roIV++fPmzXleZnLnnKxN35XI2tFbKR2ulnLRWykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclMuFA9jgZ/i99bnq8LDipMcz+WngWooChv8OvJGikwPA24B3Al3ArwMD7j4KDAH/DTDglWb22ud05vJ0XgBscfdt7t4CPkiR18kc6Ov83g/sO4fzuyDdddddrF69mlWrVlGpVHjLW97CJz7xiSeMMTMmJiYAGB8fZ/HixedjqhcMZVJOyqV8lEk5KZdyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI8yKSflIqciPkf3+RrFl9/P5s2dcb/j7v+tc+yfzcyBfwP8K+BP3f2P5k5w9yngXWa2EPiXwFuAzz6Hc5enNkqx7cicPcANTxrzn4HPm9mvAN3Aq87N1C5ce/fuZenSpSeeL1myhG9/+9tPGPOf//N/5jWveQ1/8id/wvT0NF/84hfP9TQvKMqknJRL+SiTclIu5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfZVJOykVOxTnp8ODuN7n7y9395c8y9KrOz7980vG/Oen3P3qac/+k8/P605yePH/eCvxfd18C/CDwd2b2lH9zZnarmW0wsw2HDx8+p5O80HzgAx/gbW97G3v27OG2227jp3/6p8nz/LvGvfe972X9+vWsX78eZfL8OtVMQLmcS1or5aO1Uk5aK+WkXMpHmZSTcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTspFztWWFqdqHtBw9wNPOr6j87Pl7tue5tyNQAtY8jzNTZ5oL7D0pOdLOsdO9nbgQwDufgdQo8j4u7j7e919vbuvHxkZeR6me2EYHR1l9+7HG2/s2bOH0dHRJ4x53/vex5vf/GYAXvjCF9JoNBgbG/uua916661s2LCBDRs2oEzO3HOZCSiX54rWSvlorZST1ko5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNykVNRtoKHBtB+8kF3n+78euzpTnR3ByaA+vMzNXmS7wAXm9lKM6tQbCXyySeN2QW8EsDMLqcoeFDJ1PPo+uuvZ/PmzWzfvp1Wq8UHP/hBbrnllieMWbZsGV/60pcAeOSRR2g0GvoH+/NImZSTcikfZVJOyqWclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5yClx9zN6ADmw9zTGbwfSZxmzBciA6tPcb9+znD8JHDzT96THaf8N/CCwCdgK/IfOsf8C3NL5fQ3wTeB+4D7gNady3euuu87lzH3605/2iy++2FetWuX/7b/9N3d3/+3f/m3/xCc+4e7uDz30kL/oRS/ydevW+VVXXeWf+9znnvWayuTsPB+ZuCuXs6W1Uj5aK+WktVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcLgzABj/D76ytOP/0mVkOHHD3xac4fjuwzN2jZxjzZeBlwFp3f/RJr91AsaXFvU9z7ghwENjo7utOZU6VSs3b7eaJ50kloVrvYmpiAixAvQ8wMHv8JHcwiuNO5/fO8We6VxToqiUsnDfM8ePHOTwxRRbiUzo3GMRRwN3JvRju7rhZZwI+9yE89QVOnufJx9y/+0XPsbxFiCKiEGEG1RDo6u5mcrZFrVrhyNQMQ/UKC4YH2b5jN41mgzgY8+ePMH78GLMzM5hZ56MLhBBhQJwk5HlG2m6TYxDFmBlRFNHb3U1jdpZmlrHuskvYsGHDM34mcm6tX79emZSQcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR8zu9vd15/JufFzPZlnUKHo0vBM7qYoeHgx8ISCB3f/9rOc+5LOz/tOdUL1rm7a448XPMxbuIDLr7qGr37282SVLrjm9ZiDV2rFgDx/vDjhCcUOxjO+NXfawCUrR/iTd/4iH/vIP/GXX93Ake55RaeELAPPiwvOFVNk+YnrL+2vcesPXEIcJ1iISB2a7YyZds5Uo8V4o82xmSZTrYzJRpupVspUK6OZ5jTbKWmWk2FFkQHgFjDP8FYT0s4bMYPIsMYk1am9dPX2Uu/rpx5gdW8XV159HZ++dwcvuWoNf/G1u3ndFUv41z/xBn76l/4Nj27ZxHBvjV/7//0rPvA3f829996DV6pYnECW4WmbJI4YWbSEEIyd27aRp21iM/qHRnjDG9/E/fds4L67NxBC2XZZERERERERERERERERERGRMjonBQ9mNgDMB449y9CvAq8FRs/gNm/r/Lz99E57vENCiCKSpHLisIWoeGmuE4Plc+0VeGLLBO8UPTyZdwojDMeLQgOKWoYQxRAlnY4RoSh48M45IYLITzRuSCpVenp6iKOYOI4IIWCEE/dwpygU8JwszzALYIHUYabRZLrZptF2JpspE802E82M45PTbNh+gMlGu/NerLhvsM58KebsEEUxURSzqKfOUFcdCzHWGYcFCBFRHBMnCUQxodqF5Sk0Zgk4tXqdkQULODLToLtvkAWLFnDk4CFq9TqvePVruP+eDWy8/z4qlSpxvfv04hMRERERERERERERERERkQvSKRc8mNk64OonHa6b2c8802nAAPBjQACecjuKOe7+KeBTpzqnk+YWAR8F/ul0zrcnbQlhZkRxgmHFa3FS1DaEzi4c/qTChLmiB3eKVhAnXc44cd255xYC4DRyI7OAzxU8hFB0j8g7XSJC1LlPsX1GEifU4oRDX/wacZLQt/Yy4r5eZnbsprpoPs0oolavU++qYVkgiiLiuNguoq9eI89zQhQRrChSsGDMzjTYfvAYk80cLCqKF0IAQmeec58PhFC8fuDgfrhkKRYiPMtIW2lxbpQQRRFRCOStJtZqkCQJ1e4earUqI/NHGB+foJa1ycfH6BscZKB/iLVrL2P7lk3s2rmT3v4BDCPMFZyIiIiIiIiIiIiIiIiIiIg8g9Pp8PDDwLuedKwP+OtTOHeuDOB/ncb9Tpm7Z8Dfnv6ZdtLDiy/co7kv/0/qwBDFczfqbGuRn3R+5/jJxQ1P2JXBTxRIFJ0XjNwiYuPxQoo8gLc753U6LXg4cc2kUiUhMPG1b9J/9Vr2/u29eDujOn+I1vJl/N8vf5n+/gFe8ZpXcsOLbiSOIu7bcC8jC+azZMVSQl4UMcxtFxFCICQJ7RAX77MzL0LAQoSZEYdAEkWQ50UxA9DLDIFAiBLytE2z2SDHIU6I4hgzaGcZWeZk6SxRgJ6RIXbt3svM1ATR4HyIa7SOTvKmW36QjQ/cywMPPESetiCOCVkGGEsXzTv9KEVERERERERERERERERE5IJyOgUPx4FdJz1fDuTAnmc4JwcmgI3Ae93966c7weeVQTHFkzo8zBUhWCgKANzwED3excFCZ1uLnMcLHjoFEJ2ODE99HyeYYUAeIiIyigYKodgNY67IwazomnCiqAKiOCEOETFGY+sukr4u0rFxLv7lX+TgocP0fOfbvOGH38AnPvpxZqamyTLn6JFDdG/vJneo9/ZRrSRUKwlRCFSqFaIoIqcogvDOFhiECLI2od3EWglRKyUmx7OMFhFH86JLRCWpYVFMrV7H4uqJDg9p2sZzJwSju3eAhQtG2L1rD1mW4w7p5ATdvc4rX/FS7rrzDir1Ol1dNcaPNYAMdz9RlCEiIiIiIiIiIiIiIiIiIvJMTrngwd3/GPjjuedmlgOH3X3l8zGxc8GeVJ1gwYjjCHDcrOjIQLEVhc8VOZzYAWNumwvArXPs8eIJ5rbLmLuF50RRcb2UouChKJ4oZkKIi3MtFM/zznEzokpSFGMkVQavWcfU5q3QatPYuZfM5vbPMMaOHObeu+9m5erVPProZsidYzNtGvVBzCCheH893XX6+vpY6uN0t44w1WrRzp00bdOaOobXa6RRYBanakaIYxyjWq0z0croqiYkcQWLoqL7RZwQhYg8z8nd6R0YYGCgn52795NTjLGQ09tV45U3vZj7H3yYbZs3Ua93cdW113L/3d9hdrZxYisNERERERERERERERERERGRZ3M6HR6e7HeAqedqIufHSVtRUHR4KDoMeGeLh6jYkSLERbFDPneOPfFc6xQ8eHj8cnOFCGFuy4yIJC6+0M9DTIJDFIrdMCznCftgOBDCiaKJOI5JenpY9JM/Ts9FKwl9fcRddQ586nNEL76erq4ubvvn2/jhH/tRHtn4MJMtZ3h0BcGddprTGNtL7tCabWDB6OvrZ94Va9m9dz/NvZuI0ibR0is43j0KqZG0jpGFiKTTraFaqRJXqkQG03mgr6sLj3IMw6MEooQ4DlQrFar1Gn19vezZvYcs73yObtRrVV7ykhdy3/0b2bxtB6QpwWZ58P6NXHP9jXz7zjtoNltP6GwhIiIiIiIiIiIiIiIiIiLydM6m4OErQOtUB5vZC4Cau3/tLO75nLK5LgwnbWlxYkuFEEGIii/1O50eiiKGztYWbk/8ct46X+7PcTrdGjjxpX/S6R5BFBNHxZYZ5P54ccNctwczyDvdJDCSEBFXq0QrV5NVKsRXXUetXsVWX061VuUdl1xOq9miq7uLa65azye/dDsXrRhkWXeV2XabI2kOnS4VucPxySmON9qkS9aQ5TDfJ4lGRhjEmA1djI3PEioVsjjCLGBxAhYIcczR2ZT+ehWzZvE2oxhCTFKJiZKYLE3Zu3cfuXvxlvKc7u5uXvHyl3L//Q+wa8/e4j13PrPx40fYvGkr66+/gTvv+CZZlj0PSYuIiIiIiIiIiIiIiIiIyPebsyl4uB3YD4ye4vh/BJae5T2fY1Z8Kd/5/j2EQByFYquLKAIL+FwBAhEEsDzv1CXMdS/onPyEzgSdc8we3zbDoBLFndciLIrBYrC0cywU3SBC1Nk64/Frx1Gg3c6IogjPnTiOi+02QkTuUEkS4jgmz43unj6q1S6uG+njDcvmM9PO+dsdh2hWKnR31fE8JRyKyMzomzzAoZ0bmRgcost30E4zZvMMqjUIgcwgsnCikCM4HJ1tMtDdDTTxPD/xXipJTJJUmDg+Tp4Vn4UDff19vOLlN3H33fewZ8/e4mMJhjudYhI4dHAPAwOD3HDDC7nzzjuez8BFREREREREREREREREROT7xNkWH9izDzmr8c+rEIzu3jppmhJFEZVKQggRtXqFqBLT8pw8JJ3CBMADbjkn9q3wvChKcH+8m8NcEYVFxZAT/5dTSxLA8BCRd7aCKLayOFFxUVwnN4hC0UWCnDiKSCoVBuYlmNlJjSRs7o5EZhhOmqa451wzMkAUJSTBWLdwkG1tmG2nnQ4WRlKt0Z4Yw4PRzlImJydop22acUyodmEUNR0hQN5uMzs5TmTOdCvj4pEa8ewUDlQqFQajNl1RxPT4eDEfd9yM/v4+br751dxxx7fZs3t38VoIuOcYTu5zn6Wz6bGNXP+Cl3D55ZcD6vIgIiIiIiIiIiIiIiIiIiLP7Fx2W+gG2ufwfs/OII5jolB0HYhCKH7GEXEMad7E4wSPiuIFPOp0XTip0GGuWGHugljnyEnHPQeMJOlsaREiLM8JBlkoOj50Wh8U1/CsGGcGBKI4JkQB72wFcfTwMfI8LzpSxDHBAt09dfr6e0jTFLKMdh7RMCM356KeLh49NEEURZ33FxMlCfVKQlytU6lUaedOmhe7TcQGbsX7qGQtZo8fZvuxQ1w6MMTIaJ1Vi6ocOhgRxYEfuf4iHoiPcnzsEMeOj3PVusuJDOrdPbzghuvZsmkTXdWESy5eRQiBKKkQxwkWAlEItNOUNM9I2yljY/u5dM2V7N/xyPObu4iIiIiIiIiIiIiIiIiIfM87JwUPZnYpMA/Ycy7ud8q86PKQUaHdbuMUHQjiOCI1I549Qi0yZpJu3B08J5gRzMjdyAid8gYv6hvMil8721tYXnQy8E6RRHRiKweHtE3UbpBF1c52FlGn4GGue4RTbHUBlUqVOIrJrbhuCIFWs83gcA+9vT1kWd7ZFSPCLKOdpsykGUcaORYFtk23yCk6LzRbKc1Gm4HhCNImUVIlRDGQE6KoM49iIw4zoxHVGVi4lCVLl/GZezax+9Hj/HAWQdvxLOcrn/4YB/dsZ/nFlzM8bx7Hx47Qbqe84sUv5gufuY2DBw9iFop6DowQAiEKWAj09/WRpSnNVop1thK58xu3s3zJgnP8hyAiIiIiIiIiIiIiIiIiIt9rTrngwczeCLzxSYf7zeyvnuk0YAD4AYpv8r9+OpM76dr/1d23n865p6rRyMmAvJ3j7njuBAuEwcWk/cuhWoXQ+ZgccKf4n2FYUczQKYJwzwDDOgUP5I6RQ5aBZyTBAKcScrKpY3TPPEp7/lqwjE6biWIPiU5xBWYQApWo6OTgXhRPNBpNqrUKszMN2o2UVjNlcHiA0BdBC1pZztFmkyU9PUznsHW6CSEizXI8h8xzkjjB2i0sFPcMDpVKQiskhM62GQa4BeKkSjVJaEcVpq1KV1ed2ckm7jmTUzMcGZ/i4q4e4igirlS5+fWv43Of/hR79uzG5nYx6ezDMVcMAmCekec5U9MzJz5HLFLBg4iIiIiIiIiIiIiIiIiIPKvT6fBwNfA2Or0MOsfqnWOn4jDwO6dxP4CfAVLg7ad53imxEKj39gHQTlPipApAZhFNq+KVHjyOyT0iBAAjyztf2JsVjzwHArkZ5sWWFV7UNYA7WZ6BRZg7R6caRVcJd1qzs7S6B/Eo6XR2ADxAZmBe/O4ObtSihCiKyPOcPM9pTE8zPTnFzHSDWrWGGezds4/1L7qmKDAIgUenm3hlmsksZzLNsMjIO0UFOUY1jshbDUIIJ5pKxHGMWwKdYo5iVlZ8Np7RtoR2iJiZnSayoltFhpEREScVkmqVm171Gt733veyd+9eDOipVhjsqhPHMUdnZ5mYme0UPRhRFDq3NgYH+rj86jXMq+fsOdB4PuIWEREREREREREREREREZHvI6dT8HAf8DcnPf9ZYBb40DOckwMTwEbgo+5+/DTndwioebEnxHPPneb0BFhU1BZ4ThRFhKxJnmed7RciyCJys6IAYa71QaccoNgCAsDwuUoHC0WHhrnX8xxwerp7ABgcmkeeZtiJbSw46dp2ohvC3LHuSqWYVwi4O1dceyVO0YnCrDiW5xm1SoV2O6UWx9z1yBY2Dw6T5e2iA0WcUAkBN5iZbZEkMWmrDTh5nmPuRFEMIQG86O7gToSTRIGQZzQJ5MDG3fu5anQEcC65/FJWrl7F8uXL2LN9O9/42tfYu3dP53Mwuvq6iJKEJE7oCs7EzAxgmAVCFNPXU+PVLxzhhWsigh/m4NE2ew4MPC9xi4iIiIiIiIiIiIiIiIjI949TLnhw908An5h7bmY/C4y7+889HxPruAt4g5mNuvve5/riIYpYsHAVQ8MDHNi7k0qlRpJUqdd7SJMqM3lOmsckUVScYJ1+BCd1cHDAOltPQNTpf2HgebEjBVAJRm8ScXxiAncnCUZlZCVJzwIqcULuRXGBY3OlBkURRaf4IQSjnTmB4vcQinubGSGKCKHoLBEoujT8Pz/3E2zftoPFo4v5h7/5O774hc/wmte+gRWXXsrWLTtYPbqEeQsWEA3MI9m/g5npaaI4Ievpw6sRWZZBrU7UamNxjThJyLOUNK5DXKO7a4CrV65g/NgkK1esYnx6gl2799BVr7Bn7246kwecLIeZdkYjK7pTuDtmga7ePpasHOWWF0R4nvLAzpyjx5qsXrUYmHmuoxYRERERERERERERERERke8zp9Ph4cleDrRO5wQzu9rd7zuNU/4YeAPFVhj/8nTudSp6env44//zFxw9fJjjYwewKKF/cJjLV67Fqz3k9X4sxFSTzseUp52uCsW2E3meYTa38QPF9hCdIgTPc6JgxAH6eruILeWRhzdy8OAYL7xslBt/5zfYu2cfU62YUO0hM3A32rmTphluEe12i8wCtThi8942lmckIRAbWGQkSUwtMeIkkJiTxEaSGEND85k/spBgzrx5C1i77lrGDh3k+LHjRLVewpFJtn/udgbjGpXhxXT1p7TMaKRt4tlxouF5RJUqla46aVIly5zZRoNGqBBCzJZjUzz00MNkUyN87ctfoX94iAWLlzA8fzET48c7jSmKLS+OHhsnCgHHybKcaqXC0KJR1lzUx8Khbo5OpORTMT5zlIvnVxhJTutPSkRERERERERERERERERELlDhTE9096+6+x3PNs7MBszsHWZ2N7DhNO/xFeDXgJ81sw+Z2bVnON2n1Gy2+PCn/omP3/FFvrb5fm776uf5+p1f48vf+jJ/8Td/zu/96Z/wwe9sZOGAM6+rTX+lQU8yQ29llv5aiwWDMQsGA4uHE5YuqLFkpMLSeRVGhyKWzItZOBDo78qJ8hmCpYzMG6K3r5sQoJIEentqdFVSajZJ1SepZsfoTo/R58fobR8mnj3MF+7ZyEfveoB/uPM+PnDX/fzDt+/jg3fdz8fuuo+P3/MQ/3T3w3z8Oxv55zvv4eMbHubj33mUT377MT75rYf4zLcfY+U1N/Kmt/wsb/rJn+VH3vrT/Pibf5TXvuIl/PCrX8bb3/pWfuUXfonf+KVf5h0/9wu85qZXMb+/n9BqEXuOpRlXzp/HK667hisuvZL/8Jrr+f2bVvLDaxeQtY4zfuwQDz34Hb55++d5+L7vUEkMz+d2Hym2rfA8x8gxnDgyFq5YxbqLq7zxmgOsX7qLi+ftJWcPg/0zXLaqzZJFk89lxBekz372s1x66aWsXr2ad7/73U855kMf+hBr1qxh7dq1/MRP/MQ5nuGFR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKSflUj7KpJyUS/kok3JSLuWjTMpJucizOZsOD8/IzF4J/Dzww0CVuT0OTu8a2zq/toEfBX7UzGaBI0D2NKe5u190KtfP0pQt+7axcN0VJBZhUw0MJ4kTkiSiMTVJXuticGiATQ9t55GNDzI7M02etekfnMdr3vBqqtUKIUTFm+tsYzH3VvM8n5sQAN09fVQqFdpZTr2ryuLqYoZbTfBOd4jH3zfuzvjULO+5/wj7Z9tzLxSPLMVI8TgFC+BOZeowrf4FYMX2G5bnEKz4maWYtzEPgBM8x9qzhDwn1HuwrEWUZxgplsdAq9iOw2DH3t3cde/d1Lr7+PR+GOjvZrCSs6K7jz/5oz/ghhuuZ3jBUr7yxc8xdugw1UqVEEKxRYdnuOdcfsmlLFo0wt1bDnPR4pzXrztMnmY0Wy2OTkbsPthmsLfKV++dZuGCgVP865CnkmUZ73jHO/jCF77AkiVLuP7667nllltYs2bNiTGbN2/mv//3/843v/lNBgcHOXTo0Hmc8fc/ZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTsqlnJRL+SiTclIu5aNMykm5lI8yKSflIqfiOS14MLMlwM91HsvnDgOzwGeAD53mJVc8xbGuzuPpnHpRhcOBTVuYGjtCwOhOKswsi9m05VH2D1xKc/ElJJUKURTj7vT3D7F8xTImJibo6+9l7PAxPM3o6e1iZrZF3k5xnIWLR9i1fTdxHGMBqtUqDkxPTjG6aAGN2SbVakwUAsEC2FMXPFSrFaI4Acs7xQ4UP3HcgRBB5zwPMYS4KIDA8ODFuOIkIH78kzEwizFzvNaDQ7E1hzm9lQeohAgPEVkUcSyq0SCiMm8JD+8aw48FatPHeR3bWLZ8BZO1BRx4+CFWr76YL37u83T39BCCgUOa5kRxDLS5d9s4i4eca5c1uW9bD/uP5ExOpWzd5xybcEaGjFdcP0KlazWw9ZQjlCe66667WL16NatWrQLgLW95C5/4xCee8A/+v/iLv+Ad73gHg4ODAMyfP/+8zPVCoUzKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lJNyKR9lUk7KpXyUSTkpl/JRJuWkXORUnPGWFnPMLDGzHzezzwLbgf/M44UKnwDeCoy4+4+5++kWPPzcGTx+/pTnHozl169n3ZveyLoffCULL7mMek8vr/vVd3DRdS8gj6skcYQZ9PX3sHTFYqI4YXj+CP2DQ0wcm2Ds4EGmJifZv+cAR8aOsX3Lbo4cOsLDDzzE9i3beOyhTTzy4Gbu+fb9HDt2DPeMPTsP0my0iKOIKIoIIRSPKBBFEWbFdhDFT+sUNkRFQUOIIEogrhSPTqFDHiWdgocIos64opLi8fPnOkQQwAKOdWogIjwE3AIhGG4BnxsbJ9S6u0mqtaKoIs9ob3uQyWNjLFi4kP58lh1HG8TVOkkSgad0dXdR66oTokC1WuGhTbs5uOMRFvc5x7KFbDq+lCPt+TTDMPPm9fPKGxdxzcU1vvStrfz5R77O4cOHT/PPRObs3buXpUuXnni+ZMkS9u7d+4QxmzZtYtOmTbz4xS/mxhtv5LOf/exTXuu9730v69evZ/369crkLDyXmYByea5orZSP1ko5aa2Uj9ZKOWmtlI/WSjlprZSP1ko5aa2Uk3IpH2VSTsqlfJRJOSmX8lEm5aRc5FSccYcHM7sSeDvwk8AQRRsBgDuBGzu//5S7z5zpPdz9b8703FNhZgwODDBYqzM2tovZ40dZuHQF9UqVyalpzBKqIcKBZrPF3l37GT82zqpLV7Htsd1cdOlS9u+aZveuQwwMDDC6bCFbH91Oc3YGzxMqlR7Gjx2k2RwjSeocHTuGe9F34Suf+yZd9RpuThQnOEZPb5Wr11+JmXW2wzByOoUHwYruDXMbg1g40c0BvFPkEMDnOjqE4pw8A/PicVIXCc8N87niBztxnYBj9ngzCA8xwSLy3CFtwcRhWHEpnu+GqYMsHqjT2z9AT3eddqtFlue0Wm1yz8nznCyDuH8xtHNuv2MLv3bxWnqXRKStaY5NZKTREL11p9msc8Mb38Q/7x9l5d73P5+xX/DSNGXz5s3cfvvt7Nmzh5e+9KU8+OCDDAwMPGHcrbfeyq233grA+vXrz8NMLxynmgkol3NJa6V8tFbKSWulfLRWyklrpXy0VspJa6V8tFbKSWulnJRL+SiTclIu5aNMykm5lI8yKSflIqfV4cHM+szsF83sO8B9wK8Aw8Ae4PeAS939Rc/5LJ8nIQTiOKGrr49Vq65haN58ggUio2h7YhAnRRcG3FgwupCBoQEOHzhCJU44fOAIQ/MHGRzqp3+gl2NjRxmZP4+Vq5czb2QYPGPJslFe9LIXcdElFzE0NIA7DA70sWD+fJavWsbQ8CDdXXUqSUSWZjQbLaAoxshyp+2dDg8WPV7kYNHj21t0jtmJMfb4G5x7fW5bCwsUkYeiOmVum4y58obcwbPOueBebIlhZpCl0G5AzwB0z6O7p5+DB/ZzeGKamVbO5OQUff39ncv5ifs5sGpBHy9eO484OLd96VEe3riRxzbtZCatsWnbfr7w7YPs2TcG3fO5aPDUdySR7zY6Osru3btPPN+zZw+jo6NPGLNkyRJuueUWkiRh5cqVXHLJJWzevPlcT/WCoUzKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lJNyKR9lUk7KpXyUSTkpl/JRJuWkXORUnHLBg5n9HbAf+FPgOmAG+Dvgle6+3N3/o7t/j/31OGmaMXl8ApIK1a4ecnfGxo7RnG2QxEZvNRCZ0TvQQ093jVWrlzN//iDLVo4yunSUoeEBRuYP0dPXxdDIICOLh+kb6KVvoIvevm6wQJYGkqTO+PEpwGm3Mo4eGWd2JqXVyGg224wdOsKBPUfY9Mg26BQZpHMFD3bythQBwzEH5ro/APlcsUMIxWOu8MEoOj2EuYKJkzpAnCiEsBOfB+7kDnN/GplDCJ0xlRreM0DWM8TQ0ovYvWsnR44eI/eczY89whXrrmLJwhFufvmLWDAyRBwnZGmL0fkDjCxaxlQjZ8uhCt/cVOXrD0c0sjq99YxV89vM603p2f91rlxcPVfhf1+6/vrr2bx5M9u3b6fVavHBD36QW2655Qlj3vSmN3H77bcDMDY2xqZNm07sfSTPPWVSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpZyUS/kok3JSLuWjTMpJuZSPMikn5SKn4nS2tPhJilYAX6YodPiou08/L7N6EjNbAvw6cDOwHKi5e3zS64PAL3Xm9/vunp7Kdd2BOBD3dpNXY6DYXiKyAM0Z2t6FhYRggZmJaQ7sPciSpaNMjDeYGJ9hYGiYvbt3Y0RcvGYla9ddXMzAc5avWoq7Y0Ce58RxxKEDC8hzZ+mKBaxZt5IsywEnyzPcIctzgllxCQe3QFa8wZO2oyiKFXyue0MImEMcGS2b2++Cosih2D+j08lhrrgByHMgx6y4jnXu2flUOt0fivOyTrMGN4OkAnECISJEEf/mnf+R//jvfoPZds76H3gZw8Pz2LRpM331CoYRVyq4Z3z9W3dQqVaodXVBFJNmOc1Wymfvg6h6CZUYwgEnvedBrrtEe+acjTiOec973sPNN99MlmX8/M//PGvXruVd73oX69ev55ZbbuHmm2/m85//PGvWrCGKIn7/93+f4eHh8z3171vKpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclEs5KZfyUSblpFzKR5mUk3IpH2VSTspFToW5n9oWAmZWfDsPD1EUPPy9u+9/lrG97j5zVhM0ezXwIaCPzgYMgLt79KRxd1F0nvhhd//kqVx76fKVfsNPv5XRtVfQ093DgQ330RfXSJYv5QtbZrn/YM6/uGqUf/3ySzly6BjT0xMc2LmdkMSMLltOT+8AeZ5jIRDHEdVqgntOFMXgeVFE4A5mJEnMoYNH6OqqkVSq9Pf3FFtGdB555+Hu5HmOu3Pg6BS/+eFvMZlHHPAu5joyWN4uChDiSlHI4DlRY5Ksu58qTmI5uTvkOWlW5Nu2mMejzolmjkOckFe6gU4Xh7TJ8EP/TBqgXq9RrdUZr47wc9deTDSyjP/3geN4pY6Z8XP9Y9x68wt412/9e+7YPcmv/ovX09tV4c7PfpRKFPOth7YwPjVDMGOou8rll13GPQ8/xmyjQZpmzEzN4oNXQdJdFGdkOZXGFl68ZiETzYwNGzacxV+NPNfWr1+vTEpIuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5lI+Z3e3u68/k3NPp8PD7wE8DVwDvBn7PzL4I/C3wMXdvnMkEnomZLQU+AvQCn+zc6y+AgacY/lfAeuD1nbGncgdCiEibTY5NjWOeEqKYak+diZkjELqoJDEhGFs3beOLH3s/3XGLVmOGiZmUVVe+hEvWXsXUVJOpyWMMzx9gz879VCo1srRFd1cPrfY09XoPr/+RV2Fm5HnRdcFOtFGg6LCQe/G9f5ZjVhQ+1EPGD/Xs4t7GEAca3Z2tKgAPxTlP2LYiYCFwfW2CK2tHOTzdZt/xBot7AtNRD7fPLmSWTo2Iz21nUXR4qFrOq3sOk7Vm2RQ7R7Kiz0OO453OEu50ttXozIEcw3A3kjgmiRPSVov+oXkcngoMLrmacGQvk8f20mw2mZmdoa+3h2azBWTF/EMFogSCg0dEBrVKwkQzO42/EhERERERERERERERERERuRCdcsGDu7/TzH4L+CHg7cDrKLaYeA0waWYfAf7W3b/2HM7vNyiKHT7k7m8BMLM/fZqxn+v8vP50bmAYs5OTNHY+RtxwwpIhWrNTpK1ZsG66kggzY9umh3nkgTu57rqr6bl0NcMT47TGD9DdewMrLlrO+PFJenrr3PTKF5FlGVmWkWc5aZoSoogkiYtmDBTFDGYnFTu4Y6EoeiieQwiBFjHfbI6ys10vzg2dbSw86xQedK6Rd7acMNiT1Zma6KN95z/jzVnSvh7q615Cbp3xRduJYmcLmyt6gG2tPgazjNxt7rInihxOzDVYpwCi6DSRe07mTuY5URzTnJli0/5pth1o09c/yLylV9CaHSdvHGNycpL+3m4OHTo0d2GwqFNEAYScYE58YusOERERERERERERERERERGRp3da3y67e+bun3D3W4ClwG8BWyi2m/h54Ctmtv3kU85yfjd3rvHbpzC37UATWHmqFy86LuRU6l10rVhL0j+fECLa7Ta4E4JRS2KCGZUYhnqqMH+I9v/zr9j5n36X+dffiGeB6akZGtPT1GsVpiamyXOnWqkBgYHBAarVClmWk6YZWZp2fs8xs053Bzh5Z5Eoigkhpidx6hEcyutFoUGIICqKBPzE7h6FYEURws52lb379tOenGDhyAJmJ6doTk5ioXi9eOPhRFcIgtEOMbvybgLFccMJ1il8sFB0jzCK+1txTnHPQI6TpjlRFJF7Tp43WPTm9bTftI/Z7DBxFDF/ZITZ2Vn6+/qIKzXipNLpSBEXRQ8EjOIeSZKcanwiIiIiIiIiIiIiIiIiInIBO50tLZ7A3Q9QbG3xbjP7AeBfAj8KLD9p2NfM7B+BD7v7zjO4zTJg1t03n+L4KaD/dG6QtVKydpuhecPMTEyDQ7Vep29oAXuPBeIkot1qcmTrw4wOD/DSgR7WfPNLjC9czY7uIfoG+zh6aJzxiQmSapVjR4+xYOEC0qzN7p17WH/D1Xz9K3dw1XVr2bv7AGuvXs2uHQd45IHtvOzV1+HunaYLRecHALPiy//UIxoeOt0b5jorUBQenNgXw8By3AwnFMUKR3czvv4qfGiAob7j2O4maT53eqdYAcdDp3jCwEPOMA32d7bTyJlrxBDwPCd3x+e6RHQKNSwELE6wKBDFMWQ58156I1tvvJzr7/868xYaj7TnM2/+EEfGxhgeHmLJ0qXMzs4SwhjteoRHxXuwOLC4bx71avV04hMRERERERERERERERERkQvUGRc8nMzdvw583cx+GXgrRbeHFwDXAdcC/8PM7gb+0d3/4DQunQPRqQw0s5ii08TEaUyc1vQUU0ePELI23piht6dOPjNDnkFPJaEaR2zd+Agvv+FqLr78R5k4dJiNm3fhE/3k9UEe3biVWq3GilXLuPKa1Xju5LmDwbUvWEOeOW/+qVuI4sDAUB95lrFw8RCDa/qLYoeTWjtkmdNstunuruLujKcxDzaHKJpcPN7RwaHTpaFTgJAbbnHxPDImLnsZ88fvonXzy1l4xw4GFy+kt6ubx8Yzdk21cSCYk4WiewPArEV8bmaYIY/IyTCsuGOIMYwcgyg+Mb74+HJCFGMWiOMYd6e28SHaf/9BHnHn6qsXcbR7NbW8xcBgSl+9ytWXrKDVbhGuuJi+nj48bdFsZ4Q4oatyFbOTpx6fiIiIiIiIiIiIiIiIiIhcuJ6Tgoc57j4JvBd4r5mtpej68JPAPGA9RfHD6RQ87AQuN7Nl7r7rWca+FEiAU+0GAWY09h9k6sB+9nrOSP8Qg5f0881PfJIj817ATN8q2rMNlodx1s37cRpXHeKf793MNVf/LHFSJc9z8jQjd6jWEkIUcMsJUehc3p7wCSdJQruVE8cx9a6iqCHLncwd3MndabVyurqLQohWmpEVV3pCzYNB0W0hdC4e5eARkcE11QnWth5h/Ogeln/kw4yMrOLlr1lPb18XB6fb/MrnDvDY8RbBHYs6W1SYk8dGI+o0jaAo2DAzlufjfOv+Q6xcV4d4XlHw0CnUSLOMffuPYiEhjiMgZ3BwkKuuuYpNj21mtmuEF153NV+/fzuL4z4G0uMMD/RRiSPaHqiGnIGuHqqVCs08cPToESaOtU85PhERERERERERERERERERuXA9pwUPJ3P3h4BfM7N/C7yRovjhVad5mS8ClwO/CPzW0w0yswT4XYqygM+c6sXNjOGFQyRdCTR2EnuTOApcdFGdvW0jxTjw4HdYceUajnylm6NrPsqeZXtYeuyV3Hnno8QhotVq0tPbxcqLVnLw4BGuu+EyurrrxZYPRfXASVtVGO5OFAIWOkUMFEUGDlQrMZWhiDTL8TzHT3R1sJMmPfewx3/PHQ+BhUnKr1cGWfKiN5H90KvYt2cfCxcvpKe3l9rAgxwZPMZrlq9h0+RxLMwVTdiJThGWd/o6eFHwkAO91uSRPbvxwaUwb34xPqc4x6HZyrC4RhJHpK0WM2OHGNuxh4nDOa859Gr2vPlbXDwxwf0buxkY6WVhtUoE1KKEga6EeledLG1Tr/WQE7j/sTPZ+URERERERERERERERERERC404dmHnB13b7v7R9z9tcCK0zz9D4EW8Btm9vanGmBm11IURtwATAJ/dqoXN4O4mtA70M+y4Sl6qlOEyJhf3UQtTNFFyrq+iN7Nl/CFYy3GZ3bRXJbjlZxVq5ezbNUoy1cuY3BoGANGRoZpNVMaM01mpxvMzjSYnW7QnG2StlPyPMeBOInBjTwvagvyLO9shZGT547njoWAW8D9pGKH3IvKiDwHz4DiAgZgsLrWZt3+S9jyjZyND97PvgP7mJltsGf3PtL2QR7sf5R1S42+JJC7gUUQoqJrg0VYPldHYcQWgcNss4lRdKcgRE8otHD3olDCwEKEuTF9/DiDtR6S5hBT3+nn47NfYc3lR0jdeezAFNu2bCWOIhJS4jgGiwlRQpqmzDbb7J5QhwcREREREREREREREREREXl2z1uHh6fi7ntOc/xOM/uXwN9QbJPxe0A/gJl9C1gOLKT4Cj4Ffsbdx07nHnElodpVo85CmowQAgz2ThA3jd6ZI1xS76e9c4TPzR5idf0QY3RzyA6ya9sso8vns2fPfgIRB/aOMbJggM2btjI1Ps30zARdXb3Uu+pU4jqHDx9k5SWjXHTpMmammtx9xwaOHDnKkqUL2bfvMK1mixteehXzFgwxOT5JrV5jptHGs5yA40DIc9xjPM8xC7j5iS0mghkr6lDNBtnWTlicDDPY08Vjjx1m157DvHVkK/1dwzSX7eIFi5fx7cM7yMzJiit3OjZk5J4DYMFwOsUX7tQqlROdJTwEnE4xhhm1SkIUxVTyjKUXXcKWbfsYtm66bRmzKytcmk6TtRpMesxFl6whWEa93oWFiGolpjXbwtw5enyCh3cd5OrF3acToYiIiIiIiIiIiIiIiIiIXIDOacHDmXD3fzCzQ8CfAqtPeunGk37fAvyiu3/5tC5uRrVapV7v4tD+YSaONKn3OocP5bQ9EE2McWlzLUcGp9i04RB5OMSWnSNUszv5kZt+mru+sRE8oqevh2ajRW9/L81Gm4svXsbhw8dJ04zRpQs4eniS4QW9pFkLPKfeU+X6F19Os50SJzErLl0CBl3ddWammxzYc4yRhQMYUEtnuIgDkLbppkGlbx5HSNif93LMukmBQEYVY7QSkyQVDh+tc0nPADOzKRsfOUJXd5WuWhv/asyj195Ll88nIi0aNoRQbJ1hQJ6R5XlR6OCAQT2pEIdANYmL7g4UHR3yPJ/7EKkaVCsVLunvZ9PD97D/wAGq2QpalW7G0xoLFsxi7WNM5FXGZjK682mmZ5sYThwF0tlp0izn0W378OYsoIIHERERERERERERERERERF5Zuek4MHM5goR3N1febrnu/sXzOxS4KXAi4HFQAQcAL4JfMXds9OeF9Dd00etWicZWYC3x3Ei8r5X4DODrGw8xogv5EN+L1MNx9NxDn+hQvKyCgf3jjE43EXadirVGrV6QgiB/sFe+gZ6mJiYJgpGCEZXd43G7Aztdhs3Iwfq9QoHDx+l0WzQ09PDtl37GVmyjHvu30atGuie18OR/ftZ13yU+f3dVCpVjuw9yKLhbhb7DBfPHmDfpLMrzCMfWkrTc6ozszSOHiWdqfEPH7mNnqE61192BcNDNebPH6L+2Hq23/kepg+tIPIctxi3CMwxDDwnz3Jyd9ydQKCrViUOgThOik/MDBzci8IIPKc1NUHuOdt3bGUmy4jaKQ5s9jqzW7vI46PUOcxUtpj7732Mddlejsy2Wbn+GqxWZfe27djkONQG8VbrdGMUEREREREREREREREREZEL0Lnq8HAT4GdzAXd34Kudx3PDjMxzMGNgwXIa0weI4oTFF9+A3d9icXoU63LuuOcwPb051tPFknlrmBg5wtce+DqDBwepxN3keU6r3aSru4f58xeQps7G+x+hUq3w4P2PsHjJYuYvGGHBghHSdsrmR7fwwN0P85Wvf5nd+3ZRr9cZHhzg3/zqL/Da9avZe3iKB+69l0e2baYvhpCn1Ko9xElCqzFLEsfMHDlEbfwYP//SFdxw0/W86yOf4y8e3E/49hjXTf4oxy9qsGJJwppL+6l3RdRqEVNJH9t6Y9YcPUSyf5A0xJ1tKiIIRcFD0eEB3BwziKKYtStXMX94CCZC53MDd8jdIc8hywkWsMYM27fvoBp3U7dedvbNkn/pIPvtAItHVzG2w5kO3fTUexiOprnuokU0g5FtfZSVqxbyhWNeXFhERERERERERERERERERORZnKuCh12cQcGDma1w9x3P/XQ618eIoqjoboDh7uR5zvHJWWx6htmZKexAneuWreW+vd9gqlVhUf8yXndwFff9xFZumHoFA0cWY+YkUUwIgBVdHX7qF36MPHfcMwzDzDh29DjN5iyjSxYxdvQYm/7qQdIsZWYqMHn8EO/8rf/Eza94CS97xWuYOj4G7RlqUYW0McV0OktfT4283eLo4QPMHj/GFZdfwrXXXseykUFeNi/nrz71Gf5w/Q8xdNfXWFtZSa1+nN07tjJ/QQ+tVk6j5UyFxVSHjxN8oOjWYAFCwIOBp+TumBlGwBz2Hz3OC9dcTq27GyYMzIskgxXbWpgRql1EUSAzo6+nh0NHYt7R81b+7PfvY/k/LmHTo9u5aHXMw3tiJi2h1j9IpTlLfWaCAxOT9DYb1KJ+Zmem6arXnq+4RURERERERERERERERETk+8g5KXhw9xVneOoWM/sC8OfAP5/JthXPxAxCiIlCRKvVZnJqmhC6+PYD9zHdHGHH/v2MzR5kiS8hz7axa8x4ZM9jLNnbxSUH5/OZ69/PjjtewsZd3bhDEhkhSUjiiCgyomAkBhV3ugJ059P8/HUj7Dh4jPd94J9oNWcgdyyKaXvGeLvFhz72ST78kY+xfOVyVq29kunpWYI5FoxWK6OnGjFveJAXXXsTtVqdw0emqCWHuGJ4CT/Q38XtQ4uoLmgwG+ZDPEmIqvQN9hNFFbq7ejk+vppm30PEpIAVnR0MCIZlOZk7ZgGzovhjNz28JM/wEIqxABSvGWBmhDjGLFDr6iJY4EWtFzD9cwc5Otnm+P3L2LLgMq6+MiWKIprA7vE2LxzoIbQzDm7bw+J6QiWOqXf3MDIy+FxGLCIiIiIiIiIiIiIiIiIi36fOVYeHMxWA13QeB83sfcBfuvvO5+byRqVS4fj4FI/s2ElvCkPdAywaGCBNFvDAV8f48t6vsTj8PK3Wwzy6O2bm2CSfrAxz/KsJ1z+8hJuGt/CKxcvYlvXzjeMRG6fbZJZ1toqg6IaQO3jOIp/ibfk8jk1OsnOyBR4gb0NiZO02eI6FmIgcoojW9ATmMDM1TVKpQmuWuDrAqkuupHfBYo4eOMDW73yb9pXX0Gw1uXuyRbVWZeXqnCG/hOH504yuWMHIwn6wcabyCHt0PstrO7k7zzrFDqEzVyPPU/I8I4TQ6UoBjSWXUeuLaIWAWyeSYvcLghVvMo4CwSCECMsjXrP21fzNq/6SqV+9irHxNnvHV/GaefuoVuvkaZutE85VSc6xY+NMHT7K9LxhJlsx7aRKY2YWurqfm3hFREREREREREREREREROT7VjjfE3gWrwI+DLSBhcBvAVvN7DYze5OZRWdzcTMAI4SIqUNHaRwfp9WYYWFvN7+wboCeEPjAg/9MMjtD3D5Ia+c4vXEf9cFBdtYX85HJtfzOplX807ceJv/mJ/nR4/dQjygKCOZuYHPbQDiOgxmRO3naxntGMAtU8jZJ3mIgylmzcpSBy1ez8JKLqVYS4rzN2P59tKaO0241uWL9jYwsXkpuMXmI2PjAd7DY2LpnH/3zRukmp7d+iK6eRSweHaW/v49ggTSdh7dbzD80xsLtM/TkLQjx43MEPEvxztYeBrgDFuEObqF4Y2ZgUdEFIgQw71zCsEqFgcFB7rzhK9zxXx5m6+bHSGeOsWdXk4mZbuY6Q0xUBjg40+bhTTtpWsKMVZjwhMlmTrEviIiIiIiIiIiIiIiIiIiIyDMrdYcHd/8y8GUzGwbeBrwduAx4LXAzcMDM/ooz7PpgZowOzKfWXWdi5SRxnlPvmcej+/dw945eRta8ktbkQfaMTHNl9SZeddW32fORbto39HHt/P6iMCAM0lq2jAezBtM2zZWVAZyiscNcp4SuCBZUcrKjsxg5ZgZRAmmLOG9zQ+wcjQJ9XVWyYFS6enjsoQe5YtUq2q0Wfd01psaP0d1qc3DzY1Tr3SSVGu12gy2PPcKmzY/xuS99jMll1zHrCenMLkLvPipJTBInhCgn917WDsV0jx+k1t2iuzmBh7kCBoqfWVpUOXgxR8PBAs12kzz3k4ojigKOVmMWc+80ighkFlEfqHH4/sfYcdcsORNYBIe3HWP/gVE8b5PmOeNWZSpUOHJoH3Gtm5kUDjQj8pATx2dVwyIiIiIiIiIiIiIiIiIiIheIM/7P6c3sNWZ21Mzefwpj/6kz9uVnci93P+Luf+Dua4CXAv8ANIFFPN714TOn2/UhWGDR0HyiprP+sstZPbqUef19/MAV63jBSI2bXv4DvOimm9iQdPPil7yU3t7L+KkfGeXq5kFe1D3Fi7pnuLF7mht6Zriyu013d8xVyThXJ+NcU5lkrR3hijDGGhvjBQNNLqs3OD52BHCIEyxvEyrdrBnoYs28PtYuG2XdggUMVLuJersYO3yIsYP7SdtNkjzjhcuWUv3WZ7nvi5/m6KF9jO3bTRInrFq2jPHJY1CvUc9mGe7rptnspdVok7ZbtBuz5NkOKrNTTCxfx0cmhzgQdeNWbFvR2Y8Cy1MiM4IZAYhDwKKIeiUhiSM6O1gQLJCnbe745jfY+ci32XH3l/inD72f7bv3cXxihrt3HSFLW1j+emCc1uRh/vDff5q+5Bj9QwvIK11sPdYis0DFU8ZSZ3/bi4/F7Bkzk2f32c9+lksvvZTVq1fz7ne/+2nHffSjH8XM2LBhwzmc3YVJmZSTcikfZVJOyqWclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJRL+SiTclIu5aNMykm5yLM5mw4P/wLoBz5wCmP/EXgT8BbgK2dxT9z9G8A3zOxXgJ8G/iVwJfCazmOu68NfuPuuZ7pW7jkP7dzCwvmDVHsrHNozRiuL6Brp5X3boXl4Aj75N/zYja8mGtjI//rsF/mZn3E++c/rOfzitzNhFfJiUhhWbFsRh6KDgwEWQ+6QZ8TbxpnnEe+5bJijreOYRVhcg6jC6IIuBnr6mZ6eZOzgPuKueXT3D3Fk51aiZpM4ipnnTjS1HxsYZscD92OVGtN797B01VKGBgewqRaNRovG2CG+fM/tZK0fZNOjHyRnmmrXBL/8q7O883cWcuAFP8qhy15D/857sWBEBu25rg1pG6NTBeNOMMMs4O6453inFsFxcs/4sz/5Q5ZctJb64Ah3fPNrXLF4lHq7zb27joAPASvwbAzS4ywcrbFiwX7ue8wYbo8TWjNk1QpdA31kcaDZajN+9AhpYwZ6+8/mT+SClmUZ73jHO/jCF77AkiVLuP7667nllltYs2bNE8ZNTk7yx3/8x9xwww3naaYXDmVSTsqlfJRJOSmXclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5SKn4ow7PAA3UuzccPspjL2tM/aFZ3G/J3D34+7+JxSFF1+jU2LAE7s+vN/Mlj/DNfj657/CJz/8T3z0/R9i947tzM40uP3zt9Nop1hXP+vXvpBNW8Z5YOODPPpIxBWXjvDB3/5h3rw0hhCYa3vgZngIYAE3Iw50jhWvtUNEGmLACCFA3zzy4WVYvY/+vgFWX3YF85esYtHwIBfVI2pxjdBoEIABz7hq9SWMxwOk9V7640Dv1o348SP0zFsKZiy66UeYHbmUdlJlx9497Np/lG/fs4e7H3iQPQcPUauOk2dNoplxGqGC544DbTrFGe5YlhKH0Onw4JgXxQ1zrLOlhQcY37uLpcuWM7+/Tpc3eNFLXsbmQwfIFi2i0ZzB/VpgF5YexUKVZiNj9YItNA9uZmh6L8NVoLePdpSwz2Piejcpna0+5IzdddddrF69mlWrVlGpVHjLW97CJz7xie8a99u//du8853vpFarnYdZXliUSTkpl/JRJuWkXMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+VSPsqknJSLnIqzKXhYAhx398lnG9gZcxwYPYv7nWBmFTP7KTP7KvAQ8AOdl3YCf9g5FlEUQ9xnZlc9zby44ytf5TMf+zif/vDH2LdnN43ZWb715a/QTtsM0ORFK1aTZoe469EH+LEbr6er9SKWr5zkzSsieiMvCh46HRJO/GpGBOCdA9YphAgBcEIUkXcP4APzoXuAo4f3c999G5maadDVHdHbOk7lyBiX9HSzuqeXtSPDdAdnqLeLvgpcuqifS+dVydOMeGgRSbVOY+k62pUuvGsAjxKiuA1RlSzLyFInTZ3m7AxZq4UDaZ6D+4lihyhLqWdNapUKPdU69WqNrmqFGhlmRggRWFQUeQDTE8dYsGAhQ/MW0tvXz/DwPCrVGlsPNYj7hgnhJXj+aTydxfI2szPO4oUp3b299I8sYMHoUpZdeQ3RomUctZi9e7bx6L3fYHxsH4cPH34u/kwuSHv37mXp0qUnni9ZsoS9e/c+Ycw999zD7t27ef3rX/+M13rve9/L+vXrWb9+vTI5C89lJqBcnitaK+WjtVJOWivlpFzKR5mUk3IpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KRU7F2RQ8xEDlNMYnQP0s7oeZrTWzPwL2AX9DUejgFB0k3gCscvffcPd1wCuABym23fgfT3fNEMVFQUIwDCPPHQsBQmA4pPT3zmf1klmuWDKfehSx+9F+4t4trOzOeFFvsQUEYa7zgZ3oh9D0UBQTYCeKItwgz70oHqh1Qd8w3j8Pq3QRWlO021McGJskTSOWkLFo3iJWjMxn6fAQKxbPJ7GUar3GTCsjRBHNKGHL8WkOHTnG7GwDzzPA8Twl2B6Cz8M8Y2oKxscjstzxKCbxlCTPMbzo7OA5tUNbWZodZbh/gCXLVtLd3Uf/wCAXH99MlLXJ54ojOg0h8BTHmZpuEqIK7jAzNcN4G/qXrIGuq4A7CdV+avOWkVGlVutm3uIRLl21giSJsLhCfd4C6j3DdA8uoN7Vzwuuv5GRkZGz+TORZ5DnOb/+67/OH/zBHzzr2FtvvZUNGzawYcMGZfI8Op1MQLmcK1or5aO1Uk5aK+WkXMpHmZSTcikfZVJOyqV8lEk5KZfyUSblpFzKR5mUk3IpH2VSTspF4OwKHvYB3Wa2+tkGdsb0AAdP9yZmVjOznzWzbwIPAL8CDAGHgN+jKHJ4g7t/2t1P7L/g7rcDNwMp8IKnvb7nuDvujpl1HgED6uaEsIDF847T3dfPbV3Xcdu3jjN2aJK4cpxXjaSY550bPvnCcwd97o3gGLnnRHGE1bqgq4dGTz9/ZCv5VKOXr247wtaD40wf3k/f8X10HdvP4pkxmocPcmDLIwxVAz47Q5Q2OZ4ltOp97Dl+jD///Nc4OH4c8gziKtS66O1/hKH5AVZdQ6sVePSeQJrlePcAuRsRGXPFGGYwPLWPrp4eLrv4cn74tT/Im159M1dcehmLB7qpVmJCCEVdh+dgRq1vHocOHqSSxFSSmMNjh7AQk8c1CAvx6hGgQd4cZ/bQZtJmg99512FqtUkem4ax2TbHjx7FLbDuoiX0hJRGo8HYkbHT/RORk4yOjrJ79+4Tz/fs2cPo6OONVSYnJ9m4cSM33XQTK1as4M477+SWW25hw4YN52O6FwRlUk7KpXyUSTkpl3JSLuWjTMpJuZSPMikn5VI+yqSclEv5KJNyUi7lo0zKSbmUjzIpJ+UipyI+i3O/AawC/i1w67OMfSfFN/9fP50bmNl7gJ8E+uiUEABfAf4P8DF3T5/pfHc/aGYHeNqtNKxTlzBXreDkWQp5TsVb3NAzRXU2YqhnH9+uXsTD89ZxbGqY9V/9Dq99tXFxb9G2oukOnoNHj8/ypHucOOZFBwlCgDiGpIJXqhxOezmc5jDRgHaMtR0b30vI2rzkyuvYuncnFhyGoHtwAX21GvurAxwbaNO0iB3j47SH+rB0BupDsOYHuCw+yOpLL+NvDlfhm4fo/vtp0t4arf554FlR5BGKLhR9kwfontzLdJZx0fJlXLlyCQ5UIth9+DCTbuB5sV1H5zMbXb6Kh257Pxd1D9AVdXHnN79Gz8hyrLuPxvgCosG9ZP0vwQ7vJAmQN47y0tevIGsf4IEHWySNQ8Q7dzAwMMTSZUsZ7k7o6elh48OPcfW6S0/9j0Se4Prrr2fz5s1s376d0dFRPvjBD/L+97//xOv9/f2MjT1eVHLTTTfxP//n/2T9+vXnY7oXBGVSTsqlfJRJOSmXclIu5aNMykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5SKn4mw6PPx/FF/lv93Mfs/Mvmt7CzOrmNl/B95+0jmn419RbElxHPgj4DJ3f6W7f/jZih1O8i3ga0/3ollU/OJFRUbaTumuxryud5IfWpZw5TUNgu3gkcE1pCFib/coO4+uon3fDI3MyI1iWwi82LmC4vcu0hPXLW4EEMjynNyi4oCFziOCKIFaN9R68J4RfP7F5H0jbB4/xmRcY3bRZeyefymPVoZ4MBkhXXAlR5MBRrtr9FmDmuVUPKPHZ/CLrsajmCvXriF0DxKWr2VNmtHb1UuII2p5VkwrFMUY2faNHNu/l+Njh7jzng389Yc/yt//08f51l3f4cjBAzzw2GZmZ2eLc8wI5IR0ln/9m/+eDXd8lS999uNcf+OLSfOIw5s2sGreHvrnPQRJDe8apBpDnra5e0PK2plBepespVUd5tCxCR7dvJXPfuFLfO3r36JSrTxFwYicjjiOec973sPNN9/M5Zdfzpvf/GbWrl3Lu971Lj75yU+e7+ldkJRJOSmX8lEm5aRcykm5lI8yKSflUj7KpJyUS/kok3JSLuWjTMpJuZSPMikn5VI+yqSclIucCjtpF4jTP9nsjym2mHDgCPAFYGfn5eXAq4Fhiq+x3+Puv3qa17+DopvDP7p744wn+jQuvXytX3XNy/mnf/q/5HnGq173WtauvYYre1r8wIteSHVkCR99//v56IGYb897AWkUE/KcP1+8lx9rHOIDi67kVzZGZBQdEIhirKh6IDanHQL4ifYODKYz/O8XD3I8r/GvP/UQ2dRRmDgM08dhdhJmJqE1C+02OFgUMdRXJ+nqoTk7zfHehbjnWLvJ2vmrGScwrzLBZKvFzoHl9CQR86vG5mSE1Xd/iN/9tV/kZ/7kI9RmJvjA5m9z6yUvYOrlb+aaMM6OLZvYtu71BHfm3fFBumcOggUGRxbSXasThQh3J81bJFHM0vWv4IPZIlJ3uvIGP7L7C/z8j9zCf/rPv8fg0CBveMPr+d0//EuSecv4zV/4MX7tf/4VszPTJNNHWGzHmG3DRJbwU1HMlUsv5u9GV7HlGx+mNTtJu9UiDkacJIwfH+eaq9eq1UzJrF+/XpmUkHIpH2VSTsqlfJRJOSmX8lEm5aRcykeZlJNyKR9lUk7KpXyUSTkpl/JRJuWkXMpHmZSTcikfM7vb3c+oNcfZbGkB8GtAA/gNYB7wlifPDciA3wf+4+le3N1feJbze0btVpupmWniShU8IzbndeuWc+mqldQWLOGP/+If+MvxizgyspgcIIcqGQuiBsnRY7DI5iYKWNElIgDBaJ/UPMMoKkLcDHcwMyyuQK0H0hZkbUibEMUUbSKK63oINIkZ7Oom95zIc8xTQnC2H93OC1Zcx47JWaw9ibnTpMJhq+IhYbI6QK2SUNl2D0Yozh1YQBcpe1oxrbyYt7VmSGaOQu645RyZHOfY1DSRGcGMwf5esrzNwbEjVIcXE+UObsRRgLzNvOFBavUuQhRDVz+vu+kF7DkyhVW6qGcpQ25UqRNXnZnjTT5ZG+BlB7bz2mqdDyy9jON7HiaOExqzM0wfO0Z+FgU4IiIiIiIiIiIiIiIiIiJy4Tirggd3z4F3mtlfAj8LvAhYSPH9/gGK7ST+r7tvPduJPh/MjEceuY+u3i4Arloyj4tWrYC+Yf7f9/4DHxkfYqx39MSuFLjjecb49Cz51DRJq4FTn7saxdt+vKNDsW3F3K4WhpuRZxkWAXEMlTrUeyFrYXkGaYpnbci9uEpSIQmBIZ9lUU8V4ojMKuAZR6aO4pOPUaWbtD1Dbz7LsTDIbKjjGOPNjKmpKaLGJFljlsk8pd9nMJps8xoDaYp5TmhOYXlKFAKEwPCCIbI0Y+LYNLiT5xkA7VaTHnNmADwnDgH3jFVLFjDdyjGcpFLhVS+8iv/4px8izlMGmOaKFfOxzmcwOtPk3k17+XftlPc9toE9l1/PvZdcQzR1gEajwezsDO32qe5UIiIiIiIiIiIiIiIiIiIiF7Kz7fAAgLtv5gw6OJxvFoxqrU7SrHDN6uW87Sd/gmZU57/+19/l08M3EZKkGAcnih5aBDZNZbQ8J5qeAa9xYhB5sbWFx8RWtLZwoNPWAcwxcyK82PoixJgFammLQWaJK47Ti1Vj+nu66akaVqlwnBpb2oE8C1jagiyl7V3EubM/S1maNug7vpvp2TZe6cKTGJ86zje+eQdpc4bUnXvynP33fI0lA30sDRUOHdpN5a5/JmlNE3tGsJj+gQFGegcZb+ynMeO0Go55ThQiuppTXGKzNIOTMUVfBFGUsHh0lH2HjnJscpbLLr6IyUabQ2PHGJwd4zXXr6JeiYq3HwJRCIwuHuXL9+/gd6am+a/bH+bYVS8hWbaIed1FMUie53zn7u+c6z8FERERERERERERERERERH5HvOcFDw838zsKuAdwEuAJUD3Mwx3dz+l92VmxHHM8vkj/IdffQfHJhv81V+9h/t3HsYGW/QwQ269NDwwmzrW2aHjgemESYMwOYFlPQQLWAgEC4CR5S28c6y4Ebg75Cme50QxJAEqIYfGUV4QHeayi0ZJM9h5aIzjs5McbadsH0+ZDYZbWmyXkWdUvclAaFGJK3RbFz0T+xntMx6emqIyu4+kUqXdapEf2sX7P7SZZqtNMOPv+oaJu3oInrGov87CNZeThJjjx1MON8Bx4jgmSzMa0yl9i/o5unOy6GoBDPskPxTvoJ2mpEmb8SQmjiv01CocPj7Bp/7x8/z4m17NX37wn+lrH+enfugGhoZ6MSg+N3faecbS0YV01Sp8+hv3838aKT+7+zH+/JqXs3TYWdkPURyr4EFERERERERERERERERERJ5V6QsezOyXgf8FRDy+X8RzdW1e/qIf4JYbV9Nfq3DnVz/NtSv76I6afOhLf0GjOUMlTlg2UKfRzogotn2Y7q5y+KrLGNr9KKvv+iA5jocYiwJYRJbnhCgmiWOaudMkwoBqksDVP0eS5Sz49t/TW4U9u3bzcLvFope9kMmJaabGDrJn+1bcjD4L9IeIECdEZhACXUnEwsEu0jQwWqmzdNjYsXMvw1nONStX0NXlHDp0mG3VnGa1lzxvUY+NWW9TSVsMHd/PSy5fTJY5URxz91TKkRAIWFGwkedMHpkljLfBQudzCkzPzJA3pwgOtFvkDmA89Mhmdm+8lx+5bDGTmzZwZOtO3nLTVcwb6CFLc5IkIU4ioigiz3MMeOG1a5g/2MP//cTtXBYd4/rmw3i+gkrcw1yNiIiIiIiIiIiIiIiIiIiIyDM564IHM+sFfghYBwwByTMMd3d/+2lc+wbgjztP/wz4NHAbcBR4M7AQeBXwE8AE8KvA/lO9vrvzEz/2eoaZ4KGND/HY2AzmTjsZYF7tIFbvox4bqxb0MTXbxIEshyRO2BsljFaqrByokmYZZhCi4uNstQFLwdsQOZVKAm7EFfB2m96eOm+4fIQowEOhycxsm4lj48RxYHign5H167FghBARxwlR53czwIzQqQo4fuQo2ewsq5Yvo95Vp6d/gMnJKZqtlItWrmJyapqsP6G3t5dHHnmUWi1h/sggQz1dhBCRutNut4mDETzn+OGDHN27h9DVjWdOFAeSKCYEo9mYZe+2bRAFunp6waHdnCIm5SdfupLrVnVR76rw6iuvZ4xB8jwnbbUJwSB3LKIoqDDIspyVK5fzth96ESvYxQ1XjzC4fAUPH3L2Hpk51fhEREREREREREREREREROQCdlYFD2b2NoqChJ6TDz/FUO8cd+CUCx4oChgM+CN3//XOPQFa7v7lzpj3m9n/Bj4H/Ffg2lO9uLvzj3/3d/z0LS/jaxu3cv+uo1iUEKKYBasuJ46rZJ4zZgZdj7+LHDjU089VK5YxfyJweHoaMKIoJhjUOp+CO/RXI4Z768RRIAqByIxKktA3fxTznBuHFuB5TjDDPceB3B0cQgiEyEiiGKzYUAN30txppymD3d20ZhssWDSfrq46cVIhCoFrL19NEkeYO7nnZFnGD970YlrtlL6+PurVChZFuBmtNCM2I8syZpsNQp4zPH8B080mmBGFIk4Pgf6BAYJB2m7jac7s+GF+8iULSWYCU1NTxNU+6tWEA9v3YXFEZIEkSQghELcjLBTPkygm5C0uG6ly6bzVtD1mz9ZNZD5E8Npp/HmIiIiIiIiIiIiIiIiIiMiF6owLHszsZuB9FAUJDeAOYB+QPjdTA+DFFGUGf/yk408oqnD3+8zsV4APAr8JvOtULh5HEdbVy8TUFMemZsktYA55lpFnTrOdgoVOdwU78ZMAeb1O5YpLuSXp4cNfu4fZdopZwIJheDHejKG+Lgb7ukkiY2JiCnMgz+nu6iFrzRCZEYVAkjwehZnhDmYQB+vcO5DEMWaGYbSzFLeie0IOtNrtosIiz4kMkjgmiiLiJCaOIkIIOEaIItwgy53ZVotmq1V0YKAosPC0Td5uYhbotJTAPSfNAz0D/Zg7rWaT6WMT1PuGufPubzFz/AjjUw2WjxjtpEGaJlgWkVqg1enyYJ33CZA3Z1gcxoijmH3H60zmgTQZpNrTRVIt/S4rIiIiIiIiIiIiIiIiIiJSAmfz7fK/pSg8uAN4o7uPPTdTeoIFQNPdd550LKfTROFJPga0gR/hFAse0jRjptngsW37eenlq5h+YAuTrbQoarAAJwoYii/sHcAhMuhJIvbt3cu1ly7l4mUL+ca9m/jOll20/fHigYAzOjJAnqUcHjvM4SPHOXjwMH293SxfuphazyCRBfI8I44ioigiRIGoU1hRdLNw8jwj5Dme552iikBXqBPiCDDMArk77nnxAeVFV4dWq0XebtNOs6KzQpJgOHmaQ57jjRatVouirAG8c892s0modRNCVGxJ4ZBmOY7R312nkSRMzTTJLWZ41ToWBSd4TtYpEBmtVDoFFpCmKe3cyfKsKOIA2q0mWXsBSRyYbKekGFEU4XlG2srP6A9FREREREREREREREREREQuLGdT8HAdRfeFtz1PxQ4AM517nGwS6DOzqrs35w66e9vMZoDlp3pxd2fHjn1Mz0zTNzBM/7wRBjrFBkUBgRN3uipkWUYIUdH9Ic/YsOsID+w6zGDfY/R3d5NaTG9Xnaxz7SSOmdeTMDTQy5EjR9m+czcWimKG3r4uHOjp7SUJEWZOwMjzHNyJ44g4joniiGABDwHPvejgQFFQ4XmGdY47DhaRe04IARxyz0nbKRgEnDzrjHdw67TIyFP6qjGTk+O4GcGN3HPajQaVap3YwLMcPCdEEbUo8OADGwmVOvPnL+CRBzZinnLJqqXkzRaYkWU5eZYRoohKHOPunaIRyDtFD55nhBCKQgsDOp91mmW00uwpsxIRERERERERERERERERETnZ2RQ8xMCUu29+ribzFPYCl5lZ7O5zW2VsBa4Brge+MTfQzBYD/RRFEqckSRJufcc7qNarbNm2k507txadGULRRSGEgHtRb5F7XnR6gM7DCWbMRDGNztih4RpxFMiylLTdZP5gD8Gd1uwsy5csYWq2hbtTqdZwnHq1SiWpdLooFB0a0jTFoNPxwEnJCLkTxTFOsQ1HFMdYMEJn24k8z4tChXZKCIE8z0mzjDhOsM7eGJE7njuN5iyNdsr4xCT7DxyilrVJspyQVBgfO0DWbtG7tItk6jj57AxdCxcxb9EoA10Vhvq7WLlkIbO5MX+ohziOaLUD4+NTDA30k1QS8k7BQ5plNNstIouIQ0yWpzih+PDiQJaDe14UbLh3umrERIm2tBARERERERERERERERERkWd3Nt8ubwUuNbPI3Z+v/yz/EWAtcCVwb+fY7cC1wLvM7BZ3b5hZBfjfndcfPNWLp2mbBfPnESUxBw4cZPGiRcSdL9yDGZ47SaVClhfbLIQQADAzIjNCVDx3z4mK38izjCzLmBk/Sn9vL61mk3aasXLpYmZbGXESk6Y5fb19NLOMOPET21S4G0mcEEUReN5pbWGEuXsXO1yQZRlZO8fMiq4TedbpqhDAc8ydAFQ63SnAii4LZvT0dJOmKfPnz+eS1Rdx4/XXMtNokjnEkXHo8FEqlQoLFy2gFgXiKGBRRNpOqSQJAwNDBDOyvOh+kaZtsiyn2ZilMdsAz8nSDDpbYTTTJrVajSiOSNMUz3PiYKRZ1plXsQWHmZHn3mn5ICIiIiIiIiIiIiIiIiIi8szOpuDh74F3A68DPvXcTOe7fB74ceANPF7w8KfAO4BXAnvM7DHgEmCIYvuL95zqxRuNJnffez8WDPcMMyuKDzqFBZiTZinmTqvVLjoY5DlxFAFG2i6KHYI5/YP9VCsxURTTbDZoVZy4klCrVbjm6nVYKIoHgnWKJHCyLCcKhne2oDAHyEnbeWd7i2IanucYzmyjQbVSwTrFD+6Pd5vIOxt/hCiinbbxvLiGYUXHCjOiOCJ3SNstghUFEMGMWhKRZzlxErN0/lBxxdkZpvOcrN0mx2m02gQLtNstmu02eeaEOCJPUw6NHaNWqUAItFtNJscniJOYrmqVpF6jp6eX7p4eGs0G+/buIU0zDKNSq+IO1aizbYdzoqOGiIiIiIiIiIiIiIiIiIjIMzmbgoc/An4U+DMze+x52trio8ASYN/cAXffbmY/Afw1RZHDCzsv5cDvu/s/nOrFkySirzsqvvwnAqt0igMAh3aakmU5jtFb7yIKRhSFYvuJPCfNnUpSgazN8sVDTExMkWVt2nmTw0ePgntnGwzHgCzLyfOMtN0ijiIygNxxM1qNJmnaxqIYx8i96CrhOeR5RjtNcc9IQrGNRZY7eZ5Tq1aYnW2Q5xlRHBNwsiyjlfqJzhRRZ4uOuSKIOI6J40Cr1S66QUSBPMuJokAcxWTtlCgYrSzFzHAC7VYDdyd3J8udyIwcMHfyTlFF5o5nKXnuRFEgmp7G3ZmdbRAsEEUR7XaTnKKLQ4gi3Iv3GoUIDKL/f3v3Gxv3XR9w/P3xXZw0Kw2hwGBJtMZylZGyqCNWG57AqiLRdlryYKUN2liRWkVs8IRJiCImJCqhZUKCaWorVBE0/kiloxpK0NR2oy3ZozYNrIUkrF2StcQm00q7RknDXN/5uwf3o01cOz7b8d3n7t4v6Sv5fD9fvj+/+4lB+cpXH17SfzCSJEmSJEmSJEmSpMGwlAMPHwW+DdwFPBMRDwJPAqcv9EWllG+1+weUUl4BvjjL578fEfuBm4ANwCngX0opR9vePQDBT5/+d1bUaxRgqjHFULTeImJoaIjp6cI0MBQ1mtMNynSTWkCj0WS62eBd734Xq1dfylCjyelTL9NoTjH12iSXrb6E0ljBiZPjXHbZWk7+8vnWQQmGuGTVKk6fOU1pNoFCs0TrbS6mGjSbTaJWozpJQKPR5NLfegu//vVZppoN3r12LeOnXnnjrS2mG5TpQq1ep9loUKvVqNdqTDUaTJfWW0W0bnOIUqYp09NMNQtvW7uWM6dfYeWqVUTUaEydZbrZYHi4TpRg/epLeGvUeOHs//Fyo8G73jnCqTMnaDYbRK1OoznNqpV1Lr3kUs6cPctQ9f1buWKYer3W+m0StVrrrT6GaqypDji0fjtFVG+zUaivWEHEECtXDjO8ok4phZUrV3Ho8NMLyyhJkiRJkiRJkiRJGjhLOfDwD7TecQFa/wT/p9W6kAK0feDhgi9Uysu03lZj0Z7/r2O/+ruvfvmFi7EfXTxbt27d2u09SJIkSZIkSZIkSZJyW8qBh1/wxoGHrouINcDjQCmltPUP5qWUdyzvrrQYY2Njaf67kiRJkiRJkiRJkiTlNLTYLyylXFFK2bjQdTE3P0MduLpa6oCIuCEino2IoxFx5yzP/1VEHImIn0bEoxHxu93Y56B5+OGH2bRpE6Ojo+zevftNz3/lK19h8+bNbNmyheuvv54XXvCXnCw3m+Rkl3xskpNd8rFJTnbJxyY52SUfm+Rkl5zsko9NcrJLPjbJyS752CQnu2hepZS+WMDlwDTQ7PZeBmEBNeAYMAIMA88Am2dccx2wuvr4L4AH2nntrVu3Fi1Oo9EoIyMj5dixY2VycrJs2bKlHD58+LxrHnvssfLqq6+WUkq59957yy233DLv69pk8ZarSSl2WQpnJR9nJSdnJR9nJSdnJR9nJSdnJR9nJSdnJSe75GOTnOySj01ysks+NsnJLoMDOFgW+e/Wi/4NDwsVEdsi4gOd+vO07K4BjpZSjpdSXgO+C+w494JSyuOllLPVwyeA9R3e48A5cOAAo6OjjIyMMDw8zM6dO9m7d+9511x33XWsXr0agG3btjE+Pt6NrQ4Mm+Rkl3xskpNd8rFJTnbJxyY52SUfm+Rkl5zsko9NcrJLPjbJyS752CQnu6gdbR94iIjpiJiY47mvRsSeeV7i+8BjC9mcUlsHnDjn8Xj1ubncDjw015MRsSsiDkbEwRdffPEibXHwTExMsGHDhtcfr1+/nomJWccWgD179nDjjTfO+tx9993H2NgYY2Nj2GTxLmYTsMvF4qzk46zk5Kzk46zk5Kzk46zk5Kzk46zk5KzkZJd8bJKTXfKxSU52yccmOdlF7agv8PqY4/M7gXfS+kftxXy9+lhE/BkwBnxwrmtKKfcB9wGMjY2VDm1toH3nO9/h4MGD7N+/f9bnd+3axa5duwAYGxvr5NYG1nxNwC7d4Kzk46zk5Kzk46zk5Kzk46zk5Kzk46zk5KzkZJd8bJKTXfKxSU52yccmOdllcC30wIP0GxPAhnMer68+d56I+BDweeCDpZTJDu1tYK1bt44TJ974xRvj4+OsW/fmX7zxwx/+kC996Uvs37+flStXdnKLA8cmOdklH5vkZJd8bJKTXfKxSU52yccmOdklJ7vkY5Oc7JKPTXKySz42yckuaksppa0FTAO/nOO5k0Bznq+f95qlLODyao/L9me4zvt+14HjwEZgGHgGuGrGNX8AHAOuXMhrb926tWhxpqamysaNG8vx48fL5ORk2bJlSzl06NB51/zkJz8pIyMj5bnnnmv7dW2yeMvVpBS7LIWzko+zkpOzko+zkpOzko+zkpOzko+zkpOzkpNd8rFJTnbJxyY52SUfm+Rkl8EBHCyL/HfroY6drFBfKaU0gE8BjwA/B/6xlHI4Iu6KiO3VZV8GLgW+FxFPR8S+Lm13YNTrde6++24+/OEP8573vIdbbrmFq666ii984Qvs29f69n/mM5/hzJkzfOQjH+Hqq69m+/bt87yqlsImOdklH5vkZJd8bJKTXfKxSU52yccmOdklJ7vkY5Oc7JKPTXKySz42yckuake0Dky0cWHENPDfpZTfmeW5k8A7Sym1C3x9O9c029rMBbYJlAv9GcpvbGysHDx4sNvb0DnGxsawST52yccmOdklH5vkZJd8bJKTXfKxSU52yccmOdklH5vkZJd8bJKTXfKxSU52ySciflxKGVvM19Yv9maWKLq9AUmSJEmSJEmSJEmSlF+2Aw9f7PYGJEmSJEmSJEmSJElSfqkOPJRSPPAgSZIkSZIkSZIkSZLmtdADD78dEc25nrzQc7TerqIs8M+TJEmSJEmSJEmSJEl6k4UeeIhl2YUkSZIkSZIkSZIkSdICLOTAg283IUmSJEmSJEmSJEmSUmj7wEMpxQMPkiRJkiRJkiRJkiQphaFub0CSJEmSJEmSJEmSJGmhPPAgSZIkSZIkSZIkSZJ6jgceJEmSJEmSJEmSJElSz/HAgyRJkiRJkiRJkiRJ6jkeeJAkSZIkSZIkSZIkST3HAw+SJEmSJEmSJEmSJKnneOBBkiRJkiRJkiRJkiT1HA88SJIkSZIkSZIkSZKknuOBB0mSJEmSJEmSJEmS1HM88KBFi4gbIuLZiDgaEXfO8vzKiHigev7JiLiiC9scOA8//DCbNm1idHSU3bt3v+n5yclJbr31VkZHR7n22mt5/vnnO7/JAWOTnOySj01ysktOdsnHJjnZJR+b5GSXfGySk13ysUlOdsnHJjnZJR+b5GQXzccDD1qUiKgB9wA3ApuBj0bE5hmX3Q78byllFPgq8Led3eXgaTabfPKTn+Shhx7iyJEj3H///Rw5cuS8a/bs2cPatWs5evQon/70p/nsZz/bpd0OBpvkZJd8bJKTXXKySz42ycku+dgkJ7vkY5Oc7JKPTXKySz42ycku+dgkJ7uoHR540GJdAxwtpRwvpbwGfBfYMeOaHcA3q48fBK6PiOjgHgfOgQMHGB0dZWRkhOHhYXbu3MnevXvPu2bv3r3cdtttANx88808+uijlFK6sd2BYJOc7JKPTXKyS052yccmOdklH5vkZJd8bJKTXfKxSU52yccmOdklH5vkZBe1wwMPWqx1wIlzHo9Xn5v1mlJKAzgFXN6R3Q2oiYkJNmzY8Prj9evXMzExMec19XqdNWvW8NJLL3V0n4PEJjnZJR+b5GSXnOySj01ysks+NsnJLvnYJCe75GOTnOySj01ysks+NsnJLmpHeMJFixERNwM3lFLuqB5/DLi2lPKpc645VF0zXj0+Vl3zq1lebxewq3r4XuDQMt9CJ7wdeNO9LrO1wGXAC9XjtwGXAr8455qrgOeAqerxe4H/ABozXuvtwDuqj1cDP16G/XZDp7tczCbQn12clZyclXyclZzsko9NcrJLPjbJyS752CQnu+TUy/8/0iYXj13m56zk46zk5Kzk46zk1I0uy2FTKeUti/rKUorLteAFvB945JzHnwM+N+OaR4D3Vx/XaQ1btPHaB7t9fxfpe9Tx+1iuLsCr3f5+9mqXZZ6VvujirORczkq+5azkXHbJt2ySc9kl37JJzmWXfMsmOZddcq5Od7FJviZ2ydnFJvma2CVnF5vka2KXvF2y3YdvaaHFegq4MiI2RsQwsBPYN+OafcBt1cc3A4+V6r9YLRu75GOTnOySj01ysktOdsnHJjnZJR+b5GSXfGySk13ysUlOdsnHJjnZJR+b5GQXzave7Q2oN5VSGhHxKVqnpmrAN0ophyPiLloncPYBe4BvR8RR4GVafwlpGdklH5vkZJd8bJKTXXKySz42ycku+dgkJ7vkY5Oc7JKPTXKySz42ycku+dgkJ7uoHeEBF2UTEbtKKfd1ex9L1S/3ARAR3y6lfKzb+7gY7JKPTXKySz42ycku+dgkJ7vkY5Oc7JKPTXKyS0790sUmOdklH5vkZJd8bJKTXfJZyn144EGSJEmSJEmSJEmSJPWcoW5vQJIkSZIkSZIkSZIkaaE88KCuiIgbIuLZiDgaEXfO8vzKiHigev7JiLiiC9tsSxv38vGIeDEinq7WHd3Y53wi4hsR8UpETM52L9FyT0Scrq75WdYu/dIEICIeiYhG9T2fa1aei4jXIuJsRPxRN/bZjn7p0k+zAn3VxVlJxllJ28VZScZZSdvFWUnGWUnbxVlJxlmxy3KzSU52yadfmoA/77uxz/k4Kzk5K/k4KzlVXf4nIg7N8XxExN9X9/rTiHjfvC9aSnG5OrqAGnAMGAGGgWeAzTOu+Uvga9XHO4EHur3vJdzLx4G7u73XNu7lD4ETwLOz3QtwE3AY+BqwDfjPjF36rEkNmAD+uPrez3Yv9wC/AAL4a+Clbu97ALr0xaz0UxdnJedyVvItZyXnclbyLWcl53JW8i1nJedyVnKufulik3xN7JKzS5818ed9wuWs5FvOSs7lrORcwAeA9wGH5nj+JuChala2AU/O95r+hgd1wzXA0VLK8VLKa8B3gR0zrtkBfLP6+EHg+oiIDu6xXe3cS6+YBI4DU3Pcyw6gAXyzlPIEMA18KGGXfmpyDXAI+BlQmP1etgNfL62fAruBNRHx7o7usj391KVfZgX6p4uzkpOzko+zkpOzko+zkpOzko+zkpOzklO/dLFJviZgl4xd+qmJP+9zclbycVZyclYSKqX8G/DyBS7ZAXyrtDwBvHW+WfHAg7phHa0TVb8xXn1u1mtKKQ3gFHB5R3a3MO3cC8CfVL925cGI2NCZrS3YOuDkOY9n3ss64C28cb/jwK/J16Xfmsx3L2to/Y+o38zKa8DmjuxuYfqtSz/MCvRPF2clJ2clH2clJ2clH2clJ2clH2clJ2clp37pYpN8TcAuGbv0WxN/3ufjrOTjrOTkrPSmdu/3dR54kJbfD4ArSilbgH/ljd9coe6xSU52ycku+dgkJ7vkY5Oc7JKPTXKySz42ycku+dgkJ7vkY5Oc7JKPTXKySz4D3cQDD+qGCeDck0Xrq8/Nek1E1GmdfHupI7tbmHnvpZTyUillsnr4dWBrh/a2UBPAub8SZua9TACneeN+1wOXkK9LvzWZb1ZOAb8Pr8/KMHCkI7tbmH7r0g+zAv3TxVnJyVnJx1nJyVnJx1nJyVnJx1nJyVnJqV+62CRfE7BLxi791sSf9/k4K/k4Kzk5K72pnXk6jwce1A1PAVdGxMaIGAZ2AvtmXLMPuK36+Gbgsep9jbKZ915mvK/MduDnHdzfQjwFbARWzHEv+4A6cFtEbANqwKMJu/Rbkytp/WUezD4rPwDuqN5T6k7gVCnlJPn0W5d+mBXony7OSk7OSj7OSk7OSj7OSk7OSj7OSk7OSk790sUm+ZqAXTJ26bcm/rzPx1nJx1nJyVnpTfuAP4+WbbQzK6UUl6vjC7gJeA44Bny++txdwPbq41XA94CjwAFgpNt7XsK9/A1wGHgGeBz4vW7veY77uB94GShAA/gn4BPAP9P6yzGArwFngEngUNYu/dKk2uuPqh6F1gnQ26sm91bPr6rmZAo4C+zo9p77vUs/zUqfdXFWki1nJW0XZyXZclbSdnFWki1nJW0XZyXZclbsYpPBa2KXnF36pUm11x/hz/tUy1np/r7nuBdnJdlyVrq/7wt0OVnNwng1K58APlE9H8A91b3+DBib7zWj+kJJkiRJkiRJkiRJkqSe4VtaSJIkSZIkSZIkSZKknuOBB0mSJEmSJEmSJEmS1HM88CBJkiRJkiRJkiRJknqOBx4kSZIkSZIkSZIkSVLP8cCDJEmSJEmSJEmSJEnqOR54kCRJkiRJkiRJkiRJPccDD5IkSZIkSZIkSZIkqed44EGSJEmSJEmSJEmSJPWc/wcSPBTeVQQiFAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 2160x576 with 80 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np \n",
    "from core.inference import get_final_preds\n",
    "from utils import transforms, vis\n",
    "import cv2\n",
    "from utils.utils import get_valid_output\n",
    "from utils.transforms import flip_back\n",
    "from visualize import *\n",
    "\n",
    "model.eval()\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (length, input, pos_mask, target, target_weight, meta) in enumerate(val_loader):\n",
    "        if i != 1:\n",
    "            continue\n",
    "        input = input.cuda()\n",
    "        pos_mask = pos_mask.cuda()\n",
    "        outputs = model(input, pos_mask, length)\n",
    "        if isinstance(outputs, list):\n",
    "            output = outputs[-1]\n",
    "        else:\n",
    "            output = outputs\n",
    "\n",
    "        output = get_valid_output(output, length)\n",
    "\n",
    "        if cfg.TEST.FLIP_TEST:\n",
    "                # this part is ugly, because pytorch has not supported negative index\n",
    "                # input_flipped = model(input[:, :, :, ::-1])\n",
    "                input_flipped = np.flip(input.cpu().numpy(), 3).copy()\n",
    "                pos_mask_flipped = np.flip(pos_mask.cpu().numpy(), 3).copy()\n",
    "\n",
    "                input_flipped = torch.from_numpy(input_flipped).cuda()\n",
    "                pos_mask_flipped = torch.from_numpy(pos_mask_flipped).cuda()\n",
    "\n",
    "                outputs_flipped = model(input_flipped.cuda(), pos_mask_flipped.cuda(), length)\n",
    "\n",
    "                if isinstance(outputs_flipped, list):\n",
    "                    output_flipped = outputs_flipped[-1]\n",
    "                else:\n",
    "                    output_flipped = outputs_flipped\n",
    "\n",
    "                output_flipped = get_valid_output(output_flipped, length)\n",
    "                \n",
    "                output_flipped = flip_back(output_flipped.cpu().numpy(),\n",
    "                                           val_dataset.flip_pairs)\n",
    "                output_flipped = torch.from_numpy(output_flipped.copy()).cuda()\n",
    "\n",
    "                output = (output + output_flipped) * 0.5\n",
    "        \n",
    "        c = meta['center'].numpy()\n",
    "        s = meta['scale'].numpy()\n",
    "        preds, maxvals = get_final_preds(\n",
    "                cfg, output.clone().cpu().numpy(), c, s, transform_back=True)\n",
    "        ori_preds = preds.copy()\n",
    "        # 只取一条数据看attention map\n",
    "        output_res = output.split(1, dim=0)\n",
    "        imgs = input.split(1, dim=0)\n",
    "        pos_mask_one = pos_mask.split(1, dim=0)\n",
    "        preds = torch.from_numpy(preds)\n",
    "        preds = preds.split(1, dim=0)\n",
    "\n",
    "        index = 0\n",
    "        img = imgs[index].cpu().clone()\n",
    "        pos_mask_one = pos_mask_one[index].clone()\n",
    "        preds = preds[index].numpy()\n",
    "        output = output[index]\n",
    "\n",
    "        ori_img_patch = meta['image'][index]\n",
    "        ori_img = cv2.imread(ori_img_patch, cv2.IMREAD_COLOR | cv2.IMREAD_IGNORE_ORIENTATION)\n",
    "        ori_img = cv2.cvtColor(ori_img, cv2.COLOR_BGR2RGB)\n",
    "        ori_img = toTensor_normalinze(ori_img)\n",
    "        inspect_all_atten_map_by_locations(ori_img, input, pos_mask, length, model, ori_preds, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)\n",
    "        break  \n",
    "\n",
    "\n",
    "# from heatmap_coord to original_image_coord\n",
    "# query_locations = np.array([p*4+0.5 for p in preds[0]])\n",
    "\n",
    "# print(query_locations)\n",
    "# inspect_atten_map_by_locations(img, pos_mask_one, model, query_locations, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Obtain the attention maps and visualize them\n",
    "The attention maps can be returned by the forward function of the model, or can be hooked by the hook function of pytorch. Here we conduct the hook implementation in the function `inspect_atten_map_by_locations`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from visualize import inspect_atten_map_by_locations\n",
    "\n",
    "inspect_atten_map_by_locations(img, pos_mask_one, model, query_locations, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from visualize import *\n",
    "\n",
    "inspect_all_atten_map_by_locations(ori_img, pos_mask, model, preds, model_name=\"transposer\", mode='dependency', save_img=True, threshold=0.0)"
   ]
  }
 ],
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