OpenZICs.ipynb

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          "text": [
            "/content\n",
            "Cloning into 'OpenZICs'...\n",
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            "Installing collected packages: tokenizers, colorlog, huggingface-hub, transformers\n",
            "Successfully installed colorlog-6.7.0 huggingface-hub-0.14.1 tokenizers-0.13.3 transformers-4.29.1\n"
          ]
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      ],
      "source": [
        "#@title Prepare the running enviroment\n",
        "%cd /content\n",
        "!git clone https://github.com/JeonSeongHu/OpenZICs.git\n",
        "%cd /content/OpenZICs\n",
        "!pip install -r requirements.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
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        },
        "id": "y2EA-wkCiwSk",
        "outputId": "d4d69f68-d5fe-4e8f-9bf3-ce419b35fb17"
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/OpenZICs\n"
          ]
        }
      ],
      "source": [
        "# @title Import\n",
        "import os\n",
        "print(os.getcwd())\n",
        "import sys\n",
        "\n",
        "from utils import create_logger,set_seed\n",
        "\n",
        "import time\n",
        "import argparse\n",
        "import json\n",
        "from PIL import Image\n",
        "import torch\n",
        "\n",
        "from clip.clip import CLIP\n",
        "from gen_utils import generate_caption\n",
        "from transformers import AutoModelForMaskedLM, AutoTokenizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "K-rdVFhFDc1y"
      },
      "outputs": [],
      "source": [
        "# @title Define parameters\n",
        "def get_args():\n",
        "    parser = argparse.ArgumentParser()\n",
        "\n",
        "    parser.add_argument(\"--seed\", type=int, default=42)\n",
        "    parser.add_argument(\"--batch_size\", type=int, default=1, help = \"Only supports batch_size=1 currently.\")\n",
        "    parser.add_argument(\"--device\", type=str,\n",
        "                        default='cuda',choices=['cuda','cpu'])\n",
        "\n",
        "    ## Generation and Controllable Type\n",
        "    parser.add_argument('--run_type',\n",
        "                        default='caption',\n",
        "                        nargs='?',\n",
        "                        choices=['caption', 'controllable'])\n",
        "    parser.add_argument('--prompt',\n",
        "                        default='image of ',type=str)\n",
        "    parser.add_argument('--order',\n",
        "                        default='shuffle',\n",
        "                        nargs='?',\n",
        "                        choices=['sequential', 'shuffle', 'span', 'random','parallel'],\n",
        "                        help=\"Generation order of text\")\n",
        "    parser.add_argument('--control_type',\n",
        "                        default='sentiment',\n",
        "                        nargs='?',\n",
        "                        choices=[\"sentiment\",\"pos\"],\n",
        "                        help=\"which controllable task to conduct\")\n",
        "    parser.add_argument('--pos_type', type=list,\n",
        "                        default=[['DET'], ['ADJ','NOUN'], ['NOUN'],\n",
        "                                 ['VERB'], ['VERB'],['ADV'], ['ADP'],\n",
        "                                 ['DET','NOUN'], ['NOUN'], ['NOUN','.'],\n",
        "                                 ['.','NOUN'],['.','NOUN']],\n",
        "                        help=\"predefined part-of-speech templete\")\n",
        "    parser.add_argument('--sentiment_type',\n",
        "                        default=\"positive\",\n",
        "                        nargs='?',\n",
        "                        choices=[\"positive\", \"negative\"])\n",
        "    parser.add_argument('--samples_num',\n",
        "                        default=2,type=int)\n",
        "\n",
        "    ## Hyperparameters\n",
        "    parser.add_argument(\"--sentence_len\", type=int, default=10)\n",
        "    parser.add_argument(\"--candidate_k\", type=int, default=200)\n",
        "    parser.add_argument(\"--alpha\", type=float, default=0.02, help=\"weight for fluency\")\n",
        "    parser.add_argument(\"--beta\", type=float, default=2.0, help=\"weight for image-matching degree\")\n",
        "    parser.add_argument(\"--gamma\", type=float, default=5.0, help=\"weight for controllable degree\")\n",
        "    parser.add_argument(\"--lm_temperature\", type=float, default=0.1)\n",
        "    parser.add_argument(\"--num_iterations\", type=int, default=10, help=\"predefined iterations for Gibbs Sampling\")\n",
        "\n",
        "    ## Models and Paths\n",
        "    parser.add_argument(\"--lm_model\", type=str, default='bert-base-uncased',\n",
        "                        help=\"Path to language model\") # bert,roberta\n",
        "    parser.add_argument(\"--match_model\", type=str, default='openai/clip-vit-base-patch32',\n",
        "                        help=\"Path to Image-Text model\")  # clip,align\n",
        "    parser.add_argument(\"--caption_img_path\", type=str, default='./examples/girl.jpg',\n",
        "                        help=\"file path of the image for captioning\")\n",
        "    parser.add_argument(\"--stop_words_path\", type=str, default='stop_words.txt',\n",
        "                        help=\"Path to stop_words.txt\")\n",
        "    parser.add_argument(\"--add_extra_stopwords\", type=list, default=[],\n",
        "                        help=\"you can add some extra stop words\")\n",
        "\n",
        "    args = parser.parse_args(args=[])\n",
        "    return args"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "y75YazZuIM5Z"
      },
      "outputs": [],
      "source": [
        "# @title Image captioning\n",
        "def run_caption(args, image_path, lm_model, lm_tokenizer, clip, token_mask, logger, model_type):\n",
        "    FinalCaptionList = []\n",
        "    BestCaptionList = []\n",
        "    logger.info(f\"Processing: {image_path}\")\n",
        "    image_instance = Image.open(image_path).convert(\"RGB\")\n",
        "    # img_name = [image_path.spilt(\"/\")[-1]]\n",
        "    for sample_id in range(args.samples_num):\n",
        "        logger.info(f\"Sample {sample_id}: \")\n",
        "        gen_texts, clip_scores = generate_caption(image_path, model_type,lm_model, clip, lm_tokenizer, image_instance, token_mask, logger,\n",
        "                                  prompt=args.prompt, batch_size=args.batch_size, max_len=args.sentence_len,\n",
        "                                  top_k=args.candidate_k, temperature=args.lm_temperature,\n",
        "                                  max_iter=args.num_iterations,alpha=args.alpha,beta=args.beta,\n",
        "                                  generate_order = args.order)\n",
        "        FinalCaptionStr = \"Sample {}: \".format(sample_id + 1) + gen_texts[-2][0]\n",
        "        BestCaptionStr = \"Sample {}: \".format(sample_id + 1) + gen_texts[-1][0]\n",
        "        FinalCaptionList.append(FinalCaptionStr)\n",
        "        BestCaptionList.append(BestCaptionStr)\n",
        "    return FinalCaptionList, BestCaptionList   "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "7tptbdD15WFJ"
      },
      "outputs": [],
      "source": [
        "# @title GPU/CPU\n",
        "is_gpu = True #@param {type:\"boolean\"}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u8tYBMBF5WFJ"
      },
      "source": [
        "\n",
        "\n",
        "*   RunType: Select RunType equal to \"contrallable\" to control text generation.\n",
        "*   ControlType: Control text by sentiment or part of speech.\n",
        "*   SentimentType: Control sentiment: positive or negative\n",
        "*   Order: Generation order of text\n",
        "*   Alpha: Weight for fluency; Choose between 0 and 1\n",
        "*   Beta: Weight for image-matching degree; Choose between 1 and 5\n",
        "*   Gamma: Weight for controllable degree; Choose between 1 and 10\n",
        "*   SampleNum: Number of runs; Choose between 1 and 5\n",
        "*   Length: Sentence length; Choose between 5 and 10\n",
        "*   NumIterations: Iterations for Gibbs Sampling; Choose between 1 and 15"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "b11C9FxI5WFK"
      },
      "outputs": [],
      "source": [
        "\n",
        "# @title Select types and parameters\n",
        "args = get_args()\n",
        "\n",
        "RunType = 'caption' # @param ['caption', 'controllable']\n",
        "ControlType = 'sentiment' # @param [\"sentiment\",\"pos\"]\n",
        "SentimentType = 'positive' # @param [\"positive\", \"negative\"]\n",
        "Order = 'sequential' # @param ['sequential', 'shuffle', 'random']\n",
        "Alpha = 0.5 #@param {type:\"slider\", min:0, max:1, step:0.01}\n",
        "Beta = 2 # @param {type:\"slider\", min:0, max:5, step:0.5}\n",
        "Gamma = 0 # @param {type:\"slider\", min:0, max:10, step:0.5}\n",
        "SamplesNum = 1 # @param {type:\"slider\", min:1, max:5, step:1}\n",
        "Length = 9 # @param {type:\"slider\", min:5, max:15,  step:1}\n",
        "NumIterations = 20 # @param {type:\"slider\", min:1, max:40, step:1}\n",
        "\n",
        "args.sentence_len = Length\n",
        "args.run_type = RunType\n",
        "args.control_type = ControlType\n",
        "args.sentiment_type = SentimentType\n",
        "args.alpha = Alpha\n",
        "args.beta = Beta\n",
        "args.gamma = Gamma\n",
        "args.samples_num = SamplesNum\n",
        "args.order = Order\n",
        "args.num_iterations = NumIterations \n",
        "args.device = \"cuda\" if is_gpu else \"cpu\" \n",
        "set_seed(args.seed)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GzTnVb7_5WFL",
        "outputId": "d551df37-4144-49d7-81c9-2b2bde2e8170"
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      "outputs": [
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          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Generating order:sequential\u001b[0m\n",
            "INFO:ConZIC:Generating order:sequential\n",
            "Run type:caption\u001b[0m\n",
            "INFO:ConZIC:Run type:caption\n",
            "Namespace(seed=42, batch_size=1, device='cuda', run_type='caption', prompt='image of ', order='sequential', control_type='sentiment', pos_type=[['DET'], ['ADJ', 'NOUN'], ['NOUN'], ['VERB'], ['VERB'], ['ADV'], ['ADP'], ['DET', 'NOUN'], ['NOUN'], ['NOUN', '.'], ['.', 'NOUN'], ['.', 'NOUN']], sentiment_type='positive', samples_num=1, sentence_len=9, candidate_k=200, alpha=0.5, beta=2, gamma=0, lm_temperature=0.1, num_iterations=20, lm_model='bert-base-uncased', match_model='openai/clip-vit-base-patch32', caption_img_path='./examples/girl.jpg', stop_words_path='stop_words.txt', add_extra_stopwords=[])\u001b[0m\n",
            "INFO:ConZIC:Namespace(seed=42, batch_size=1, device='cuda', run_type='caption', prompt='image of ', order='sequential', control_type='sentiment', pos_type=[['DET'], ['ADJ', 'NOUN'], ['NOUN'], ['VERB'], ['VERB'], ['ADV'], ['ADP'], ['DET', 'NOUN'], ['NOUN'], ['NOUN', '.'], ['.', 'NOUN'], ['.', 'NOUN']], sentiment_type='positive', samples_num=1, sentence_len=9, candidate_k=200, alpha=0.5, beta=2, gamma=0, lm_temperature=0.1, num_iterations=20, lm_model='bert-base-uncased', match_model='openai/clip-vit-base-patch32', caption_img_path='./examples/girl.jpg', stop_words_path='stop_words.txt', add_extra_stopwords=[])\n"
          ]
        }
      ],
      "source": [
        "# @title Creat logger\n",
        "\n",
        "run_type = \"caption\" if args.run_type==\"caption\" else args.control_type\n",
        "if run_type==\"sentiment\":\n",
        "    run_type = args.sentiment_type\n",
        "\n",
        "if os.path.exists(\"logger\")== False:\n",
        "    os.mkdir(\"logger\")\n",
        "logger = create_logger(\n",
        "    \"logger\",'demo_{}_{}_len{}_topk{}_alpha{}_beta{}_gamma{}_lmtemp{}_{}.log'.format(\n",
        "    run_type, args.order, args.sentence_len,\n",
        "    args.candidate_k, args.alpha, args.beta,args.gamma, args.lm_temperature,\n",
        "    time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.localtime())))\n",
        "\n",
        "logger.info(f\"Generating order:{args.order}\")\n",
        "logger.info(f\"Run type:{run_type}\")\n",
        "logger.info(args)"
      ]
    },
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        "id": "0RMmUNsuL3at",
        "outputId": "ccb77e12-d0fc-4f3d-be31-ac7276eaad13"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): huggingface.co:443\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/config.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992535518800 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/0ae8a07720a54724ebd28ab5837bd55643aab9fa.lock\n",
            "DEBUG:filelock:Lock 139992535518800 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/0ae8a07720a54724ebd28ab5837bd55643aab9fa.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/resolve/main/config.json HTTP/1.1\" 200 653\n"
          ]
        },
        {
          "output_type": "display_data",
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992535518800 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/0ae8a07720a54724ebd28ab5837bd55643aab9fa.lock\n",
            "DEBUG:filelock:Lock 139992535518800 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/0ae8a07720a54724ebd28ab5837bd55643aab9fa.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/pytorch_model.bin HTTP/1.1\" 302 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992534622432 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/e9437103e694deabdba02cbb9220caa184b82f21b956ca837a08e9d5015dff40.lock\n",
            "DEBUG:filelock:Lock 139992534622432 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/e9437103e694deabdba02cbb9220caa184b82f21b956ca837a08e9d5015dff40.lock\n",
            "DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): cdn-lfs.huggingface.co:443\n",
            "DEBUG:urllib3.connectionpool:https://cdn-lfs.huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/e9437103e694deabdba02cbb9220caa184b82f21b956ca837a08e9d5015dff40?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27pytorch_model.bin%3B+filename%3D%22pytorch_model.bin%22%3B&response-content-type=application%2Foctet-stream&Expires=1684479998&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL2RhbmRlbGluL3ZpbHQtYjMyLW1sbS9lOTQzNzEwM2U2OTRkZWFiZGJhMDJjYmI5MjIwY2FhMTg0YjgyZjIxYjk1NmNhODM3YTA4ZTlkNTAxNWRmZjQwP3Jlc3BvbnNlLWNvbnRlbnQtZGlzcG9zaXRpb249KiZyZXNwb25zZS1jb250ZW50LXR5cGU9KiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY4NDQ3OTk5OH19fV19&Signature=xBqFY61XifrpBzwssZPw6HoM~sw28rRsmW3Pv7ZuGpHX2tmaWsnMq2oLLYN7CydKuq82Vgb8wfYKAL16euqBPCowjV~yYGCDcpo5SlTowrKxw~RYj3Wg96g1zoPpWdqbejQ~NGlVn2JrKldMsYAuxf0cXfTj4oCCIRsgnK7Mikkj84gSsg0oxF9CM9oB4PXhm4C~EBYWytWjF2r-c0yvKio9lpZJX4HhGNRlibioCOqTPnqxG~dVvEcIRtZEhlMlxqZEANWBaGJ9zlKKCXCeUTrawUl0SFwgSue7eklf9AHRyAW7zIgUhtB~U0p29pbhdA4Z0UP5nYz9XY6sfuX0SQ__&Key-Pair-Id=KVTP0A1DKRTAX HTTP/1.1\" 200 542716055\n"
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        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "9b5b746aa95a4a5ca520c30d2074fe97"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992534622432 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/e9437103e694deabdba02cbb9220caa184b82f21b956ca837a08e9d5015dff40.lock\n",
            "DEBUG:filelock:Lock 139992534622432 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/e9437103e694deabdba02cbb9220caa184b82f21b956ca837a08e9d5015dff40.lock\n",
            "DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.\n",
            "DEBUG:h5py._conv:Creating converter from 7 to 5\n",
            "DEBUG:h5py._conv:Creating converter from 5 to 7\n",
            "DEBUG:h5py._conv:Creating converter from 7 to 5\n",
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            "INFO:numexpr.utils:NumExpr defaulting to 2 threads.\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/preprocessor_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992537169008 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/4742d0484ad487ca91e7df814a7c079cb8fc3261.lock\n",
            "DEBUG:filelock:Lock 139992537169008 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/4742d0484ad487ca91e7df814a7c079cb8fc3261.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/resolve/main/preprocessor_config.json HTTP/1.1\" 200 251\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "d39a3d1580384013b3fc855ca56887b4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992537169008 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/4742d0484ad487ca91e7df814a7c079cb8fc3261.lock\n",
            "DEBUG:filelock:Lock 139992537169008 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/4742d0484ad487ca91e7df814a7c079cb8fc3261.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/tokenizer_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139991016598464 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/311bbad5faf9a7d5941d8fa183c26afee98e38bc.lock\n",
            "DEBUG:filelock:Lock 139991016598464 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/311bbad5faf9a7d5941d8fa183c26afee98e38bc.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/resolve/main/tokenizer_config.json HTTP/1.1\" 200 320\n"
          ]
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139991016598464 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/311bbad5faf9a7d5941d8fa183c26afee98e38bc.lock\n",
            "DEBUG:filelock:Lock 139991016598464 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/311bbad5faf9a7d5941d8fa183c26afee98e38bc.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/vocab.txt HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992537169008 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:filelock:Lock 139992537169008 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/resolve/main/vocab.txt HTTP/1.1\" 200 231508\n"
          ]
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992537169008 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:filelock:Lock 139992537169008 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/tokenizer.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139991016599328 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/40c4a0f6c414c8218190234bbce9bf4cc04fa3ac.lock\n",
            "DEBUG:filelock:Lock 139991016599328 acquired on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/40c4a0f6c414c8218190234bbce9bf4cc04fa3ac.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /dandelin/vilt-b32-mlm/resolve/main/tokenizer.json HTTP/1.1\" 200 466081\n"
          ]
        },
        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "52f22d6ca45b4f18a51954f7cf95a585"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139991016599328 on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/40c4a0f6c414c8218190234bbce9bf4cc04fa3ac.lock\n",
            "DEBUG:filelock:Lock 139991016599328 released on /root/.cache/huggingface/hub/models--dandelin--vilt-b32-mlm/blobs/40c4a0f6c414c8218190234bbce9bf4cc04fa3ac.lock\n",
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CLIP model initialized.\n"
          ]
        }
      ],
      "source": [
        "from transformers import ViltProcessor, ViltForMaskedLM, AutoModelForMaskedLM, AutoTokenizer\n",
        "import requests\n",
        "from PIL import Image\n",
        "import re\n",
        "import torch\n",
        "\n",
        "# @title Load pre-trained model (weights)\n",
        "multimodal_model = ViltForMaskedLM.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "multimodal_processor = ViltProcessor.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "multimodal_model.eval()\n",
        "multimodal_model = multimodal_model.to(args.device)\n",
        "\n",
        "# lm_model = AutoModelForMaskedLM.from_pretrained('roberta-large')\n",
        "# lm_tokenizer = AutoTokenizer.from_pretrained('roberta-large',use_fast=True)\n",
        "# lm_model.eval()\n",
        "# lm_model = lm_model.to(args.device)\n",
        "\n",
        "clip = CLIP(args.match_model)\n",
        "clip.eval()\n",
        "clip = clip.to(args.device)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "Sa7QUpE35WFL"
      },
      "outputs": [],
      "source": [
        "#@title Remove stop words, token mask\n",
        "def stopandmask(tokenizer, model_type):\n",
        "  if model_type == \"ViLT\":\n",
        "    tokenizer = tokenizer.tokenizer\n",
        "  with open(args.stop_words_path,'r',encoding='utf-8') as stop_words_file:\n",
        "      stop_words = stop_words_file.readlines()\n",
        "      stop_words_ = [stop_word.rstrip('\\n') for stop_word in stop_words]\n",
        "      stop_words_ += args.add_extra_stopwords\n",
        "      stop_ids = tokenizer.convert_tokens_to_ids(stop_words_)\n",
        "      token_mask = torch.ones((1,tokenizer.vocab_size))\n",
        "      for stop_id in stop_ids:\n",
        "          token_mask[0,stop_id]=0\n",
        "      token_mask = token_mask.to(args.device)\n",
        "  return stop_words, stop_ids, token_mask"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "kr0jcnIQ6tNs"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "#@title Select examples\n",
        "example_name = 'horse.png' # @param ['cat.png', 'girl.jpg', 'Gosh.jpeg', 'horse.png'] \n",
        "example_img_path = os.path.join(os.getcwd(),\"examples\", example_name)    "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "nnuU5yUKtKoU"
      },
      "outputs": [],
      "source": [
        "# multimodal_model = ViltForMaskedLM.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "# multimodal_processor = ViltProcessor.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "# multimodal_model.eval()\n",
        "# multimodal_model = multimodal_model.to(args.device)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "id": "niiS2-2FxDlo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 876,
          "referenced_widgets": [
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        "outputId": "9956a29c-b809-4aaa-e52d-634f8f08e4e5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/config.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139991014796512 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/45a2321a7ecfdaaf60a6c1fd7f5463994cc8907d.lock\n",
            "DEBUG:filelock:Lock 139991014796512 acquired on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/45a2321a7ecfdaaf60a6c1fd7f5463994cc8907d.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /bert-base-uncased/resolve/main/config.json HTTP/1.1\" 200 570\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          "metadata": {}
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139991014796512 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/45a2321a7ecfdaaf60a6c1fd7f5463994cc8907d.lock\n",
            "DEBUG:filelock:Lock 139991014796512 released on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/45a2321a7ecfdaaf60a6c1fd7f5463994cc8907d.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/pytorch_model.bin HTTP/1.1\" 302 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992305088544 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a.lock\n",
            "DEBUG:filelock:Lock 139992305088544 acquired on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a.lock\n",
            "DEBUG:urllib3.connectionpool:Starting new HTTPS connection (2): cdn-lfs.huggingface.co:443\n",
            "DEBUG:urllib3.connectionpool:https://cdn-lfs.huggingface.co:443 \"GET /bert-base-uncased/097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27pytorch_model.bin%3B+filename%3D%22pytorch_model.bin%22%3B&response-content-type=application%2Foctet-stream&Expires=1684479504&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL2JlcnQtYmFzZS11bmNhc2VkLzA5NzQxNzM4MWQ2YzcyMzBiZDllMzU1NzQ1NmQ3MjZkZTZlODMyNDVlYzhiMjRmNTI5ZjYwMTk4YTY3YjIwM2E~cmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qJnJlc3BvbnNlLWNvbnRlbnQtdHlwZT0qIiwiQ29uZGl0aW9uIjp7IkRhdGVMZXNzVGhhbiI6eyJBV1M6RXBvY2hUaW1lIjoxNjg0NDc5NTA0fX19XX0_&Signature=TaWuiYRzp~wMD8~9gadt0Qju3mXtxzsLBormJ~GwwXzuslS4FFM3BgTKPhOKAuHQumwvAjTTTOwlrZGJ5uCnqJDMF~GxisMdwsDsJxjTJ~mwHKFVJtqywLWlMX0WTtZJ~5GBqRl1AeFH2A3d5qYsFIsSSMOjeV7~NLw8T-ZKB6IZM6ngE3ClxCbeFKcO3wbDaRCS7fqoDY3lBrH5x1GU6iE5bEPvEPFXvtXhez9EAg7F-3UqZ8sOhMArOhxBV23hMh-qSjTvWZtfBJ2gOVPr9F3ISEM0U0z4Pyk0P2OO09Si6UuPXlAJESNRRmWoUc-UO5mvqaMs0i3gPcvBCQ7csQ__&Key-Pair-Id=KVTP0A1DKRTAX HTTP/1.1\" 200 440473133\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading pytorch_model.bin:   0%|          | 0.00/440M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "430c08b8321b4e8d98b30558c5a2cc73"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992305088544 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a.lock\n",
            "DEBUG:filelock:Lock 139992305088544 released on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a.lock\n",
            "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForMaskedLM: ['cls.seq_relationship.bias', 'cls.seq_relationship.weight']\n",
            "- This IS expected if you are initializing BertForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing BertForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/generation_config.json HTTP/1.1\" 404 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/tokenizer_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992303197424 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/a661b1a138dac6dc5590367402d100765010ffd6.lock\n",
            "DEBUG:filelock:Lock 139992303197424 acquired on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/a661b1a138dac6dc5590367402d100765010ffd6.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /bert-base-uncased/resolve/main/tokenizer_config.json HTTP/1.1\" 200 28\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "8fa04a4bd7e04aad8e291ba1913acb7f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992303197424 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/a661b1a138dac6dc5590367402d100765010ffd6.lock\n",
            "DEBUG:filelock:Lock 139992303197424 released on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/a661b1a138dac6dc5590367402d100765010ffd6.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/vocab.txt HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992304069136 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:filelock:Lock 139992304069136 acquired on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /bert-base-uncased/resolve/main/vocab.txt HTTP/1.1\" 200 231508\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "9fe46121508f4430bfaa208931d05653"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992304069136 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:filelock:Lock 139992304069136 released on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/fb140275c155a9c7c5a3b3e0e77a9e839594a938.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/tokenizer.json HTTP/1.1\" 200 0\n",
            "DEBUG:filelock:Attempting to acquire lock 139992303197280 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/949a6f013d67eb8a5b4b5b46026217b888021b88.lock\n",
            "DEBUG:filelock:Lock 139992303197280 acquired on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/949a6f013d67eb8a5b4b5b46026217b888021b88.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"GET /bert-base-uncased/resolve/main/tokenizer.json HTTP/1.1\" 200 466062\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "98f42c41a14448a68a31d3c66ef82b44"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:filelock:Attempting to release lock 139992303197280 on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/949a6f013d67eb8a5b4b5b46026217b888021b88.lock\n",
            "DEBUG:filelock:Lock 139992303197280 released on /root/.cache/huggingface/hub/models--bert-base-uncased/blobs/949a6f013d67eb8a5b4b5b46026217b888021b88.lock\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/added_tokens.json HTTP/1.1\" 404 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /bert-base-uncased/resolve/main/special_tokens_map.json HTTP/1.1\" 404 0\n"
          ]
        }
      ],
      "source": [
        "lm_model = AutoModelForMaskedLM.from_pretrained('bert-base-uncased')\n",
        "lm_tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased',use_fast=True)\n",
        "lm_model.eval()\n",
        "lm_model = lm_model.to(args.device)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ahLYF7Q_5WFM",
        "outputId": "167a5abc-c1a2-4a71-864d-13e22f9c5eed"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processing: /content/OpenZICs/examples/horse.png\u001b[0m\n",
            "INFO:ConZIC:Processing: /content/OpenZICs/examples/horse.png\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 9332\n",
            "Sample 0: \u001b[0m\n",
            "INFO:ConZIC:Sample 0: \n",
            "iter 1, The 1-th image: /,clip score 0.360: [CLS] image of a horse drawing on a paper terminal screen. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 1, The 1-th image: /,clip score 0.360: [CLS] image of a horse drawing on a paper terminal screen. [SEP]\n",
            "iter 2, The 1-th image: /,clip score 0.370: [CLS] image of miniature horses drawing without a computer or camera. [SEP]\u001b[0m\n",
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            "iter 3, The 1-th image: /,clip score 0.383: [CLS] image of mini horse drawing used a software video camera. [SEP]\u001b[0m\n",
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            "iter 4, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 6, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 8, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 8, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "iter 9, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 10, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 11, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 12, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 13, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 14, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 15, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 16, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "iter 17, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
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            "INFO:ConZIC:iter 26, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "iter 27, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 27, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "iter 28, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 28, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "iter 29, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 29, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "iter 30, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 30, The 1-th image: /,clip score 0.383: [CLS] image of miniature horse drawing without a digital camera attached. [SEP]\n",
            "Finished in 46.609s\u001b[0m\n",
            "INFO:ConZIC:Finished in 46.609s\n",
            "The 1-th image: /\u001b[0m\n",
            "INFO:ConZIC:The 1-th image: /\n",
            "final caption: image of miniature horse drawing without a digital camera attached.\u001b[0m\n",
            "INFO:ConZIC:final caption: image of miniature horse drawing without a digital camera attached.\n",
            "best caption: image of mini horse drawing used a software video camera.\u001b[0m\n",
            "INFO:ConZIC:best caption: image of mini horse drawing used a software video camera.\n"
          ]
        }
      ],
      "source": [
        "# @title Run \n",
        "import gc\n",
        "gc.collect()\n",
        "from gen_utils import generate_caption\n",
        "\n",
        "model = multimodal_model\n",
        "processor = multimodal_processor\n",
        "model_type = \"ViLT\"\n",
        "\n",
        "# model = lm_model\n",
        "# processor = lm_tokenizer\n",
        "# model_type = \"BERT\"\n",
        "\n",
        "args.alpha = 0.05\n",
        "args.beta = 2\n",
        "args.candidate_k = 10\n",
        "args.num_iterations = 30\n",
        "\n",
        "stop_words, stop_ids, token_mask = stopandmask(processor, model_type)\n",
        "img_path = example_img_path\n",
        "\n",
        "FinalCaption, BestCaption = run_caption(args, img_path, model, processor, clip, token_mask, logger, model_type=model_type) \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "oPrtlmIR5WFM",
        "outputId": "091d18dd-a6b6-41d3-8357-a0952b16769d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 9332\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=256x256 at 0x7F527F97BD30>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Caption\n",
            "\n",
            "Sample 1: image of horse standing with no outline style drawn by person\n",
            "\n",
            "Best Caption\n",
            "\n",
            "Sample 1: image of horse standing near no solid line drawing free icon\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# @title Output\n",
        "Image.open(img_path).show()\n",
        "print(\"Final Caption\\n\")\n",
        "for i in range(len(FinalCaption)):\n",
        "    print(f\"{FinalCaption[i]}\\n\")\n",
        "print(\"Best Caption\\n\")\n",
        "for i in range(len(BestCaption)):\n",
        "    print(f\"{BestCaption[i]}\\n\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dense Captioning"
      ],
      "metadata": {
        "id": "1jmCi-GSUkgJ"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UYg3Wnp9mi3Z"
      },
      "source": [
        "### SAM (하다가 실패함..)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nBxYusnGBjLj",
        "outputId": "1ee32222-6b37-4705-c7af-df7f4ba15f96"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "13141457408"
            ]
          },
          "execution_count": 28,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "torch.cuda.memory_allocated()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ehuc_z-CBjZL"
      },
      "outputs": [],
      "source": [
        "del model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "F5ZxlK1DmxxP"
      },
      "outputs": [],
      "source": [
        "!pip install transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DdISsLNnRFCL"
      },
      "outputs": [],
      "source": [
        "!pip install ipympl\n",
        "from google.colab import output\n",
        "output.enable_custom_widget_manager()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569,
          "referenced_widgets": [
            "5ca29b3a0fb04e3491730182641362d0",
            "02546cb2482b4769bc3ffcf2513edef7",
            "7d33940839314a3c963cabff652d5b16",
            "3c69a54045074082bc279b69dbc8cb92"
          ]
        },
        "id": "G1Pn2Xk-RI2m",
        "outputId": "cf777590-8faa-4152-f69e-0126c1c196e4"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5ca29b3a0fb04e3491730182641362d0",
              "version_major": 2,
              "version_minor": 0
            },
            "image/png": 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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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3N8yr3XXuCV1+5iQk/XrvE+obIZy4PbrPaWbKrHqCrPq69WnB0fc+/1Od/5PdfYu7VP5jrQu2bXYzfDhz6p+30QZR+gEG83CYBCCPEIxoYmaux/92B6xxhiYkqY+zN478/7VZq+fowvf2XDq3cKOrWHtgv2jq6DGjg/37C5OCN2DfOiQCvDyeklZaax+RSdZZSzOWVREKPH2owhJKL3GKtRvqfvajaXFyjvmWhF23S4mLDGkJmMKnUQPKHrUChc5sbefP2A0gHVZqAduBwNKGWwKiMli+89SjuiSdx6/HH6j38//+nXOo4vjllkG7LU4EOHrzYkIrPVEXvzkma5x+mpomk6vvj5S+7d2fKe9y157wevsXfo0FkNakukR2mFSgaiHg+NqPt9AeHBnsD7k1PSw/sE7x8eeainoBDiD0UCoBBCPIJxsln6L/OG0uNItjiMk92iBlXSdpYXvxp57XVDr/bIlgdcv3GTZD3Hd97g8vyUNARmRcF0VtL7gdoPrFaHlLM9os7wEfphQCuPJRF9Yug7nI6oFBm8JzUtuR5Hwpk4YBgPjAxD5M27p/R9T9d0FNZx69Z1vB9oVWSuMkzWk3RLDB7jDMbkkCIGRQiBoanwdEzLBY9/54d4/fgun/m1X+XksuPQJfquIxhN60/wvWI6X7CalVT1lr4LqFiwOVd88bMtl2fnPP3sihtPlkyXGm1bYuyANJ4cjqDSONs47folKqV3jaXjQ3ORH14qfniCiBDiD0MCoBBCPAKlwi5qWMZGzpH7laixYJVIDCSd48Oc559f87ufe5l1WzC4wJOrW5TlhDdef4PjO2+QhpZ55kgx0TUdxlquX7vBdLYkotFKoWIieI+ylr4fgEQKHWEYUCnStj1tU6OVR0dP01SopHE2Y1OtaeuGtg8MPWzXFTEdc7A3ZXX9gF5rSAH6jiKzqBSotufkxRRrPAqH1TkxWfohkpTjPR/8Dr7y+c/z1Re/SH57H6M0wxAg9azXF+NoOGXIjKUNLQaLy0qcMZzfi3TNJffezLn1+JzDoyXlPKKzLUGt0bpBqRzuV1LvN83+hrOC7y8VS/gT4lHJRgshhHgUadfXD0hKPWhqTIrjRA+ViMmTTM7luuSFrxrO1pZtA/uHt7h163H8EKg3FYXL2FsumU6nDMNAtdmQQuJgeUBZTjFKk2tNYQHf07cNKXichgyP9g0MDVYHMpuwBmIIVFUDSpGXBUabcZJI0Phk6VPG2UXN5XlFChqjHYHIEAfqektdVSgVSanHDxX0NWYYUGEg+g5jDbeeeIo//b/5BG6xz/G2oYsaHxIqQRw8bdtCjGTWQYKm7dhuK+qqJfSG0M3Yns149TnDFz498IXf6XjtJYPv91HskZLZTUeJKHV/0V2j1P2JIfcbR+9GzwkhHplUAIUQ4hEoFKQHEfBB/lBqvDdGwC65uMz54pcuaLt9immECEdHNwl+4PXXXmaoK+bTHKMNPrQAOJdhlaFebygnnjgM4Mb9bb5piWgya7EoEgEfPWHo0dqS5xbrcmpAaYObTLFlgStLQkysNw1N0LRtxyw3xONzfPC890M5q1tzolVoO+6/S0DfddC2LOcrHJ7gPaiBzsOknPDh7/lezu+8zmd/7VeYYNAJfFNhXdi9noJJXlDmOW3d4uPAoCN13aO0J88OUXFCX0PdNpydr2nrksefvEk5P4d0SYotmN2ev6hQ5uGl34dJBVCIRyUBUAghHsnDDYvZZUBPwpOSBr2gqqb83mdPef75SJ7vcXq5ZXV4CApOT+/RVlushhQCm8stoa9xOrFYrVhMpzAMdNsOazRaO4zWEHoSmuh7ggZjHWYyZdgE+r7HlhlZXtA1Ay7LUcrQ9ANDjGTFhGG4pO56LjZrZjeOmM4nbNdbfuPX/iPLG9eZrvbJJwueevoZ9q8dkIDtdktb12gMVo8niG1URD+QzxZ8z8f+FK9/9Yv0p68zMZa+7wi+RimDNhaUJbc5RTbBdzVKBbSJxNTQtecURYbLpswm18CtOL17Segijz3tmO/NUSYBHlQkoVFRv3VARPb/CfHHIkvAQgjxCNLuf2MGGZdXx2XgQFKOpl7xuc94fvu3G0I8oB22XFQbFvsrhtCzvjwnxkjbNFRVRVVVNE1DUzXUdU3oO2LXsL04Zmi3JD/gnCXPHUYrjFZEpUlugpvuofMpUY1LuTEmuqphaFraakvXtICi2lYEP5CGnhtH13j2fe9j79p1quSY7N2kzJbEOnL++j2e++znefnLz9PXFfPplAjUw0CICd/2+Laiq7dU2w0H12/wvX/6+1leu4krp1gznuIIoadtK1LyWKuxZpxk0jQ9TdMRvMeHgWFosJkhkjB2gmLGvTd7XvlqzebcQpyMBT+VUFrdL7My3viNKoFCiD8sqQAKIcSjUoyHE5QaT6omRUglTbvk87+35TOfrVDqFjHlxFRx47Fb3HryCbq2JsTI4AeSD1xWFfiBIlNYneialpO7d7AqkYwnyxxohTaGoixp+jWQcHkOtiAqhck70mZDHDyDD6RuYFFOUErRVRu6zrOYTmjmLZOZYrZ3gMtLumRw159k20eIOcYH5rM9FvOSe2/cpW1qnvnA+7CTCW0IWO0gKWyMxBjpuhZnDe/90Ic5ef1l7jx3iSsLaBusBoKH6Ckyx2SiiENCaYc1lr5XlIWj7xN9P1AWU7quZxgC3ifuvu5xmaGcTTF5i6IfD6qoh04A7/Zdji1gpAooxKOSACiEEI9Ej3sAU0DpSIwB1ISuXfLZz655/vmAzQ5ohsBib4+Li57Z4QFNN1BVFcZajHVsLrcMTU1mYDZZMJvkOK1IaSDPM04uzrEuI9s1aM4yh9Oatt6QT+e7vXqaoiwJZTm2aomJ5XxOZzV12wAwKTKMdkxnC7qQ6JWjjYrLXvG7Lx3ze7//Vbq6RydY5pr3P3WD//77vhO76XntxVd59sMfIKhE8C3OlVjnCEoRidR1w2q+4tkPfzd3Xv4qmYokP2CMwjlL9D1KRWZTh2VC2wwM3hMHTV13GDsF5YhJM/jI0Ed8H3BmyendhsWq58ZTJez2SH4tmRYixB+HBEAhhHgEKWrQDqUbQujQdk7X7fPii46vfqVms82JumN1UJKVjuF4wlOPP43NLMFH+t5zfnZOV1UcrObcvn7Etf0DUgxsL864PLtHVdVYl+FDIgye7bBmNptA7Bl6T99syVyB0pphGPB9S9fWuGLKdLkEo6n6juAHlDLkk4JMOeyQ6NrIqyeXvHjnnM9/+UV+78U7dDjQFhNavnrvjJP1hj/z0e8GZTl+9Q32j/ap2wozW5JUhtZja5qBQN1aDm8/zhPv/yB3vvQZZvMZyQcSEeccKE1SCmssk4mmqgIxBcBTVZdM6gV2Mhm/vy1oqwZHQVdHXnv5hP1rc7KZgzS2v3nrB3H/HxIEhfijkAAohBCPQOlxCsXgFdatWG8m/P4XK373d3uaesFiNSdySddvuHdsKCbXiClxcnKPerMh01DmGcuy4Ma1fabFhLP1hjfvntBWNUOzIfUVt2+sUG4gDB6jFTomMmPoYsfQ1tiiI6rxAIg2lqyckM9WZMsDepNTxIhtK9CafDLnsvZ0Q6AeEm9etLx+2YL3vO89T7P33o/w13/ib/CTf/P/jN2e8ekvv8m2SfzAn/oelILMQL4oqLfHGLck+gGrDbaY0XWassj44Ee+mzef/wIqDDg8MUFWTohYYlDoIiPGgUQkhh6lAmVhCKEjxAEfwWqHtSUhgKOkb3NimEJsQA0kAgrD125fl/AnxB+FBEAhhHgESg2kqLB6zvpyzu9+bs2XvzpQdVOmiylZYblzpyKkRDlTuDms1+dkBo4O9oh9y1Cv0QTW63PeeP1V3rx3yQsv36EbAstZwfWDJdlFS9MGMpsxn+Q4a8iyDK0N09kClxc0Q0RbR3Al1mTYyQJfzFA6Z24dsbokhp4uKvrkqbvEyUXD3bOKiyZwc29OyGd89kuf4//5P/3fUdtznr6+x5th4PdevQfll8nLD7NcbbhZ5EyWM4a+IXU12jgSgWQ0IVqmyxV7h0ecffVLLHJHbhxaW7S2RAPOWerKU+QlKVq6tiOGRN/3+METkqH3PSHCNLNAIvQO3znU3JGsBR9AfX0AlL1/QvxRSAAUQohH0qGMpt0anv9SzZuvl5STJ7hsTpjvZWwvLzm+t+bg8DZluWB5mGNzTaY1dA3tdouK4zLovbv3uHvvlGimTPevsbl3ykt3zmh8oK8ce9OMwmksS7Q2ZIWnD5FD7UhKYzJHUooYI4VzqHzCoHPMZMIkL/Fa0W7P6X0komj6wNlFxbYeiCondFumswn9xV3+3b/8FzyzLHlqOcGqayxMDss9fu/VN9lc3ONPqe/kiWJGGirq9Sm5thSra4SuoLMG6xQ3bz/Gvee+gDEl3kdcprCZJqYBhcG0Cq0sQ0gYYOgS2MTQR0xZ0HU9KSZC7MkLR9snmnpgFs1uIsj9sHe//QtIABTij+Zbsg3Mr//6r/Pn//yf59atWyil+KVf+qWvuT+lxE/91E9x8+ZNyrLkE5/4BF/5yle+5mvOzs740R/9URaLBavVir/21/4a2+32m/guhBDvtEQi6v6tti4EkuqJKhExxGQhaQiBZBKemsiSevMMX/79jFdfmVAWt7Aq4ZTHZRPuntecbTYsFo7oa3wLGk/XbQgqkIwicxNCr3j5hWPariCb3WLI9qjsjH66z3lwbOoKnTnQBu8jMQRiSpTzBb3S9CGilMG4AlPO8FlJHSJGaTSaaHL0dJ9iuk+eNLbe0l0e0zYXGJ1Y5AXTG+9HKcsPfPgxfugjN/jT3/NeyAtMNuVwuc/1xZLF6oCLNvD8C69wcfcu2+NT6vM1bVXRtzWhb2AIbNctgYzpbIWzGqM8Bk/yPbkxlHnBbLZgOp1T5DkuM+QTSznJybPsQZwzZc6QoO0D2jl0pki6J4Rudwp4nBN8f/zeSFrCCPGoviUDYFVVfNd3fRe/8Au/8A3v/wf/4B/w8z//8/ziL/4iv/mbv8l0OuUHf/AHx/FEOz/6oz/KF77wBf7Nv/k3/Kt/9a/49V//dX78x3/8m/UWhBDvGmb3Zzfbd9dSZLwUxrm+FmIPin226yVf+VLPG68HjFmiraOqNsxmU+q6pWl6YozEMLCczwnBcHm+wWDQMVFvtqw3G774lZc4axOtnfL//d0v8R9+63f53ede44U7NXfXA94W5PMD8tke09Ues8WSxWqf+WJFTBBCAqNR1qBcDmZc0Ikh4EMAY7DFhGQdddOy3W7omg0Wz7VFyV6hefX4lLU3pGKFXd7kpdOW5944ZrG/T6kC1+cZ3/HM43z0e76T9zzzGJv1Ka+98CLrizNi9DityZ0lzzJm8wU2y6n7nhATRmusNWiliUFhjSPbNajWeuydqJSiLAu0GX8Vee/xfiDLSlBQTjRFqVHjgJJxCsuDgx8PVwSFEI/qW3IJ+Id/+If54R/+4W94X0qJn/u5n+Pv/J2/w1/4C38BgH/6T/8p169f55d+6Zf4kR/5Eb74xS/yy7/8y/zWb/0WH/3oRwH4R//oH/Hn/tyf4x/+w3/IrVu3vmnvRQjxTlKo6FBJ76LEuPdsjBkeZTVp8BAt6D026wUvfsVz5zWFSnugCpq2A5VYrfZ5+Y1jmm1DpjWLyQSSoqk7ssLglKW+vCR17XgSuOno8hlffvFNXrpzRu0VNx97nP/L//g/8u//7a/wxqu/y2Pesh40q2QplWGa5Shr6QcPaUD5iDEWYxxGgYmJMAx4AjZzWGtI1mHyYpymGz2LTLE3LWh6TdMvaIbAWZ1Y3z2nrhum8wJjPU9c3+NPfOApnrh2QGECReY5P3+dS9/Q+URbTei7Fhc8g+8JwdAPnnYIqOWEvh6wKpHnOSkaFJqYAiEFsrJEOc0QIn0MKD/go8J7T6bNWCGNHbMFuGIAAlrlkO4HwIgc/hDij+dbMgD+17z44ovcuXOHT3ziEw9uWy6XfOxjH+NTn/oUP/IjP8KnPvUpVqvVg/AH8IlPfAKtNb/5m7/JX/pLf+kbPnfXdXRd9+D6er1++96IEOJtpxKMQSLs8oSGZEFFlAY/eKxZ0A05J8eOV14JrE8mGLMgRsXQ96AiLss5O19zfnJJvak5XC3ZW8x48/QS7/ZYTvaIYaC5vET5ge2mogmKyyHy2smadki4zHF6espv/NZv8eWXXsaeb7l5sqVwljLXWKfJuo7SOazLSFqRgsdmDmMdsW9RYcAYUEbj+w5lFDbL2Ds44Oz4HvbuHQ5nGcu9gqb12HzFvXWFK+bEdAuXZeRZ5GCR8+wTtziczZmXOfiGtqlQKnHz+iHb9QZNwmlF7ixxNxO5j5FoLMV8QbXdEEIgpQhKoY1iOp9gnGHwka6KFLMCbIbNcoZ2wPuAItKZjqzoma8i1jWkGFD6/q+r+Af9OIUQj+DbLgDeuXMHgOvXr3/N7devX39w3507dzg6Ovqa+6217O/vP/iab+Rnf/Zn+emf/un/xq9YCPGOShF0v5vqUaCwkHqI4xLv5XrCl59bc3ycaOoJTk8oHEQCLh8fHnu4vKgY+kjygVtH12ibNdvNOXY1IypP19YoNe41TBiULrh795zgAzcO96nrhuPzM/7l//z/YAieW5Ocl944RvsaF/coHEynBXkZKXKFj57YN3izWwj1PaGvGRLofIJJGSiLUZDlObdv3mB9fkrX9yzLRMo0B0cren0dZTO63tN2HdPphMdu32QynbKcLQn9wOndE1JoSUPAEcfxbs4wntTt6WNNVk4xmcNOJ+TzBf1rr+B94P5+vcHXFJMF5WyK9RrcBJM5QlLUTUtdt8QQSErRdRuWB57FXkLZBkWCoEF/fd+/hw+FCCEexbddAHw7/eRP/iSf/OQnH1xfr9c8/vjj7+ArEkL8salEUh6UQkUABQpC0jTVhN/+nS2f/0LDdLrPwf4+EFEm4KyirVva3hOGSJYVGLVlWjqW85wwtCQ8xmq8b0hDi80cSRl0azmr7nFZNTTdwJOzCdeWc/q+xZU5J5cbWh+43Ky5qxrmpsPRYglMywletfQ+YLKcxneEGChzR4gDddVg+o68nMJgaZsGGwPTyYT3vfcZTk6PCf3AYjEnzPZJWY4rC2yW0TQdm03N3mJJPp3R+8im3pBPS0pXsD0LZLuKZ1lOICV83xJRdE1CGz1W6rSjHQLlMJBSABJ9n8iKiLKWiEJZQx/H6mAkcXJyQuh79pYlbuo5vO6YrRKJFqUtKaSHYt7DS8H3x8PJfkAhHsW3XQC8ceMGAHfv3uXmzZsPbr979y7f/d3f/eBr7t279zWP895zdnb24PHfSJ7n5Hn+3/5FCyHeOUqBMsQIWjGW9BJoveC552u+/JXAEG/RhylJg9YKrS11taHaNJiiwDoNTUdeaFJ05JmBGEhJ0/QDWR0pVGA6W5D6yOWdNzitKsrljMYHTk7PeO9TT/ChZ9/DRVWxXlfcPlpx/do+1m/ZbrYM+1Nm0xl929PWHUkp8nIgKkgqQcyI3pM5Owax6AlDoGtqlPcYBflkxr5WnB0f48qccjIjFRNaDXa+ZDqBfBYoJlNi8LTNlnpzSmE1GRn7B9fRfsPm8nJc7u06jK7R2pK0ZlKWDCFRtT0ogx88RhuU1jTtQEwKq+04yxiDJXB+eUpdN6SUmJYFs2nO6nBg/8hhbEeKHpRF6bSb/6sYA1/YXU/jSe0Hy/hCiD+Mb8lTwP81Tz/9NDdu3OBXf/VXH9y2Xq/5zd/8TT7+8Y8D8PGPf5yLiws+/elPP/iaf/fv/h0xRj72sY9901+zEOKdkdTuyEfKUTEbb1QesKy3GZ/53Cmn6wKvZmyahqpd0zYNfoCm9hidYU1GCJ623aB1YPAdQ4jUTU/V9lxcblivK9bbjraPnF5sODk/Y7GccPv2EU89dQsIPPf8C7zy6hu0my3P3LrBex+7xuNHe9w8WDKfFBzu75O7jDffeJOL83N819PVFb6riUPH0DVEH7Ba46zZLTdHjNUY5/Ap0ccE1lHMFtSdp60usQYwOYMq8Lokm8xp6i0nd16jOnmDiQrMcwspENEUiz3cZE5QFmUMMQyk0EEYmE0n5EVJ23vK6Zyu64k+orCkaCAZtLJkWY6xGT4m2r7n4nINSTMpC4rccHgd5qsBGFDaoFJCqQgp7H5ysgQsxB/Xt2QFcLvd8vzzzz+4/uKLL/LZz36W/f19nnjiCf7m3/yb/P2///d59tlnefrpp/m7f/fvcuvWLf7iX/yLAHzwgx/kh37oh/jrf/2v84u/+IsMw8BP/MRP8CM/8iNyAliIKyWRCBBzlALoQHkSU1591fPSywObrmdIr3OwZ7nceIIpsDEHNFnuMFlGFnuM0YQBhpC43HZYbWg6jy4im9ZzWm04vndKCJ7D+YTF3orGJ+L+nJNpyb07x0ynMx67dYOycFh/yWpiyMsZE11wuFxwfnrC0LcsJgVhqOnaQFZmuDwjEVE6w3cdm+2GkMBlGZOioMwdfa+IKaCjZbHc4+L4FIYtJnbkbko/RJRSdH1F7DYw1Nx77SUOVivmmaOczzG5owsD2XSOMo7MKLq+p68rZllBlxJZURKSZrna53R9gfcBkykylxMHT8gGTAYpBJQxhJAYOk9pCiZlxmyhObzRoV0FyQN6d1rnfvXv4bAnwU+IP6pvyQD427/92/zZP/tnH1y/vy/vx37sx/gn/+Sf8Lf+1t+iqip+/Md/nIuLC77/+7+fX/7lX6YoigeP+Wf/7J/xEz/xE/zAD/wAWmv+8l/+y/z8z//8N/29CCHeYSqQYkJpMwYOrWmbCa+/3rHaew/Nec/J6euU5YK2LZjOLD52YCCZsVNgQhFSoqpbtk3gYttTZIbLqmI+8zRtpFpXqHbL4XLKwXzGZDZnSIqQNDenGcPjR+ztrVitFhgd8dtzFpMcFz3d+hyjE11dM5uWeN8xtMNu/1ykHQYUCmszrHVENVb9ur6nbWoKZ5mWBdYamqpDa8ukKGm7imqzJS/2CdFTZI5maKguT3BGsVouKVxO3/XMVrv+iNahEhiX6NsGrXfNmVNAacd0sWRzesb16RRlLFVdgzGkaPC1Z5pZ3GS+W3pXKKWxxrFaLcjygf19w2TmIdbjzydpkk4orXbTQODBSeD0UGNoyYJCPJJvyQD4Z/7MnyGlP3jDr1KKn/mZn+FnfuZn/sCv2d/f55//83/+drw8IcS3lIRiPKiAiqQ04fRUcedupJweUPbnqLPEZl1xtDqimEzIM4gxMqTx3zECWEIytEOkCwmboG4ayuTpB8UweGLXEUNBs92SGcNyuSLLCj787DOsDo8IKXFyekxbbyiPrpFbjQkDdy/P8CFSTKdoZ2j68dQy2tC0nqQjWZZROENEUxYztHOE6FEx0DRb1utLlosZucuoNltc0iibk7TGWoVzFqMiQUeshrapmc9nTLKMGDwp+HHehjYYbRlCS+8HjEoYlzH4AWUzTFaybQeuzSfYvGS9XWOcG5fKfcL1NXkcyPM5zbbCD4HpdMJs5liuOg5vBYytSUS0yUhxt7cvqfGPergPoNn93DxfOx5OCPG/5lsyAAohxH8rCs1YQYrEqPDDhFdf7disNapUZM7ih4RXBuMcg/d4a0Fp+mFAaU1EoY0lkeij52K7oSj3MS5HYXAqgffo3Qi33kc8FbaYMlssmUxyCqdpuoHQ9fg+kgrLEBPbbcO2Gyi6nhLLtmtRSqGMxRrDdG+f5d41jDPENOBsQZZNaJoGFTy51axWe3TNmuO7b7JcLMgnJdXlBo3GAL7dkNuE7zrqizP6bYXvGnpfk4WMhGLopthJDmlsm+VcBrGE2BNTwlqH13asAs6XoC22KGiqczabDUU+BaUwTUPethSLPTbrLX4YmE0ytKnZP4osDjYo243VPWVQKozZL6SxRQ8BVBj7NSYzXte760KIPzT5L0YIcbUltSscRVAa7y3H9zb4YYqnIcQB7yP14Llz5w6+nXJt74Ass3Qh4LJxhJy243gzdOL0/JS91YzJZEYMCjV4nNJMlkuiht4Hus7jTy/oQmTbtMxmp4Dh/HxN8B5XFpRZztm6JtqcxkeG0KJ0YrXaIylNPl1ydPtpyvmStm+o6w1KOTQWk8+xRKr1BYTEdDJn/1rg9N4x1w+vs1jt011eokNP6DY0sUXFxMQZvNEURYaKFSoMaJPTdx196jA2UfUDYeghDUzLjIiibXvyxYLFYkHpMsrYEbenVBeOvveQeqy1DL2naVp03nF5cUnXdZR5opwobtwucMUxEFDJkML96h/EmDBW7w6C3F8B2oV3aQEjxCOTACiEuNpUGhszhxzocK7i8cctX32hpqmmqNyCUrR9pGoCR4c5xuVkWYlJkc53xDS2WbHJEHtFowMXmw15UUCKuCInhAm+7yisQ6VA1w0YG7lz2XHZrtH3LsmsRqdACp7VRnOhHOt6GKdkDDW3ri2YT2YY41D5jNneEdumo/WXOGeJPRyvz+n7YyZlyWo+Yzad4dsN68st86JAL1Zcnp0xX+wR8ozM5ViTM/QDKbRYDZNCE4PDqj2M3nXc8x0uawldQoeATn5sN5MVBBQxKHxdMyss5xFUvke6vI3JG2hOcNaNzxMCKlVYteFoteCUwGTScvsZy2yvIQWFNjkwnvxNgEoKrdXuUAiQ3O6H1+8CokOWf4V4NBIAhRBXV1IkHBpFUj2KAesybj12gM3uEAbPEDRBKRpf0YaMy2pLZixd2QGKumtIaWDoB0IcT9KGEIkhEnXAhxZnpxR5QTP0lEVB8IGzi3OyvET7wKbfMHQt00lBbg3GaKou0A0DdVURh4rHjq4xn82wLiObrVDFkiZatuuWur6k7no2VcP5xSV13ZI5y9HBiidv3+SpW9fI1cDl5SnTyYy5toQ4oJRivdmwtBkpBPqmIxDG9z0MJGuYrxYEoB48IXgGH1FAUeQMwTPEQLIZfgiQAj5Eun5AG8/i6Brb4zcI3tL0A1orXILtpiEvI8vZkm11yrUjxdENT1IXKDMAht2xbNQu2KkH+e6hoPeNbhNC/KFIABRCXGkq6XESiPYoEjE2FGXHdOE5rnuazoGxJAvbvqPqB+bDQNJgXcYQQKlxAob3HqUges/Qe7Rx47ItJaQ4nsKtK5wxFHnO+vKSpTIURUG0Dh8ibdfitGazt6LeVJAChXPkLqPpPUU+w+YLzqrAF1/4Eq+9eUzd9HRDpA2wqSpijGijyKzh+t6LfMd7n+b9T97kcOJo65ZrqzlaQ3W5JfgWUOQuJ7UN9WZN5ixlMR7AaNoabSwKRV1tAIsrHV4rlMkYQiKmwOADeWEpyxLXNGyqilU5Z3Z0yNnmLn3viXEgmYo8QlcPTOdLZlPN0XVNudySwhpN+dCyvBDi7SIBUAhxdSnGU6Wxh5RQJkMrmEwDTz0z4csv36PqFuNUi6TY1AMX24Hc1KhtJMsLklJMnCP5CCrhrKZtI0PbkuWWGMdugyjQKLTSWGspnGPwLXW9JcscWiu897RtR8ozLtZbfNPiYs+1wwVZXnDjiSdIxZLPPvcan/7CV3nh1TtcbCusybCuBK1Ba2xWYKxi4wPdWcPxZ77Il158hT/zsY/wne+9TaMapplmuucIakMg4bTGZdk4Bi8GMpvjXI7vW9aX5/gISRnyfMK0XIJzJBSZsQwBrIpYFIWxLKczkqpoQs90teSyKBjqCqJlu63RGrabU8qi5GA1YX+vQ4VjlNLgc1DjoRwhxNtHAqAQ4gpLJDqUBpUchPGUqdYNH3j/kt/53DkXL29wZPh+7Fl3vt7i+47gW6bTKXvLfZazBcpqssyS546uNUQ/4IxBOUVKEaXGgBWGlhDGGblGKfzQU23XGGMY/EDbNiitMVozX86J9Zqjo2tcu/0kPlvwG7/7HJ/+4su8/OYJPmnKxSHGOvIsx2aW5XzOdDYjxsj5+nI8aKEUdzc9v/3FF3nq6afIS0PdbZnkGco5umFAx0Dw46nmdmhJLWTRkVuLJrE9v8Roi10qzk7uMTs4HE/pDonxLLXC+47Q9egYmBYlddvhJor9GwWnpxeYVJJCT9e12PqEpilZTjTOWEIA6xzjr6Xhnf1rIcQVIAFQCHHFKcCSsGNLOa3QqePaIfyJ7zzklZdfoVD7OMYqXecH7KDGPXKmoywHQgikvmE6yWm7jmZrGIZADIlkLJ33lC7DWU0Xx2BYFgXGjvv8SAGtFMH3eD+QUmRoa3oDNw/2yIopncp47qU7/PaXX+HNi442OYwxTGcLbt+8xe3Hb+MJEDzXrx1RllOOT0754nPPcXzvHtHAnbMtn/vyS3z8O56hSDm9j6ANm/UZKXOEviKEAWsMmbMYrVEo5tMlsUv4wZMXGdl8zmQ6pWl62qpBG0NSCmccdb0lKU2WZ8TcsVxori9K3njNsznp0NHRtQFrBy4vTrFFTt8X5CmD2IFukfVfId5+EgCFEFeYGnvLjUOBdw2FI4qEDud814eP+MzvvMlnP3/O4d4ed9bH2ExRd+MS5aZu2F9F2qbBxh5FxGpF7hy5zTDaUUwW1H1AWYv3PcZa0m5Gr46BPLMUZYHW41zdrgVrNCl0hDg2mn7p9TdZ6ClfevUel63ijXvnOGeZTizGaCZlTl3VvHlyF980nN07RSnDxWbL6fk5iUg/JDYp8Onf+xI39lc8c2OPeZ4Y2oah6/ApoLynr2qmsyk6ge97lHEMnafIJ5AlknWYPKdq+7FXnzaElHbvQRNU4uzijHw+p5xOcVnFrWsdH/kT+/z//u1rhLDA6Bmh19SVx5x7Lk4DixtTUtyg9LDr6SchUIi3kwRAIcTVlXirgbAadnOAFSppjPPMyjP+hx96D5eb53nu9S25y6naLWQO5yw+RvphwPueWZnhMs3lusIqWE5zDg9W6MWC4XSN0no3b0ShUsJYh/aBoeuIPpCVliLPaHKLMYqh75mUBVXTsoma9fEld88q3rh3SggBlQKXbYVvK/qmgqQ5P19DHMjysbpXNd04/1dDXjhs5rDW8NtffJ6s/DCzImc2n7Mtc3zXYn2kqzvCMLCY3aZPCmUzCjdhc7nBOsd8/wBvMrrO09Yt0XvySUnQCh8C26am6XvazRprLaQOm53zHd9zgFVP8dXf33J2r8GnGSYYtpuaywtI/YSkHFq/g38fhLhC5D81IcSVNQ4P8yjuHzpIkCwpZeA9Ntvy+FOK7/u+Q7r6DrnWzPIFJINWOaSMthkockdR5CgFKQ44G8mywPWjOWUOxhqyvKAsS6y1aDMu32ZZRpZlGKPH16JAa0XwnqbrCUlRdQNRW16/d8LpxSVVVRF9T+hbfN9T1zX3Tk9Yr9cMXUu13RJjpO46js9OuXv3Lr5vMWiqTc1ktserd0+5c7FmQGGyjOl8QTmZ0IcBbQxWG4bek08m2HJCvlpx8OTjqNkUnZVjeFUWP0QGP/bq80NAG0cxmZHP5sSkqKuG0EPsEzbf8h0fnfCnf+CA939Xji1PiPqckC5JqgMFRme7nn7yq0mIt5tUAIUQV5dKgH9ojJjZBRCDUgOGjom75Pv/9A1efO2Sf/sf3sDaPUIMhCGRoqaqGrqup9We87MLUkqUpUVTc/P6jJdOziCFMfhpRV83JMYTv8MQUMoQY6RtOwYf0MrgY8IaQzQWkxe4+ZKT599gs62pNhv2F0uGvuXk8hJtDYvFAj23KKfwXWDAc74552JzQW4Nfdthl4b95T6ZzdFDT1+3xMjYt2/wpBAISqOcIxLZ1hWlMeT5lAFFUJAv5iRtaKqOpurxvadpaiazCSkm8IGD/WuQbdnWNX1VETqDTguSvwR1weFjM+b7C55874zTuw3onKObFm0bVBoYx7yrh/r+CSHeDhIAhRBXXHowbuyt1BEAhUqGmGoW0xP+T/+H9zHJLP/2P76KijMCgc4nVJ6hjcb7QNV0KG3JdEDRcLg/5dXTO2SZxVmHThqlNVYpgg+EmPDDQIwBbcDlOcVkyjAEtLXYrGC+f4Ca7tH5VzDOobXGaEPVe9puwDctvfdkZYECgkl0ocdHjzYKHyLaWoYUKbOCi/NzltYzs4bkoScQUiIBJi92B1AqaDts4QlVTaY0PgSKIud+a+bN5SXVpkbb8ZSzU5q2apjM98iLgp5EW9Xj/sqoMNaQdIK0pihbHnt6xs0nZ6SoMKZF6S0pdowhXPYACvF2kwAohLiyxgmyDpUMCkUigOqByFiKKtAaorrHrDjh//hX3kcxm/Av/5cXuFj3WDfDmMh0VjIrLCdnG/phIKWOIs9ZLaZYrShchiI+OP07Zk5NSmMlMMaEy3KMySAlkoooa1DGYOw4czgCe3v7wKsYl2FdQVKGpKHpei43FYv5HKsd9IHldI4zOd57tv1AfXLCcVXxbPYYi70cawND09LhmRQlySjWQ0/b90yKEhX8g6pedbam6zu6IkPPWuaTJZmz1CoxXy4wVhGCx2mLUgqT5dgUyacTikWHzlv8EDF2PmZs1UNao9QGY8fPJoUejEFF+bUkxDeD/JcmhLjC1HiS9a1rQNz9GXcIquAxJqF0S2Hv8r//oSeZL+b8T7/0OV6703JtuSB3U4zqSDqgyIi+Zn/PUc4i1k3JM0eKEZ8iCTXu+TOKzGV0ZjwV7JwjJcbQlUClBEqx3lQMWWLoerphzVNPPcXl+SUX2zWRiNZgjCUMAzFEQNMNEa0M+6t9nn3/+3n2/e/l5OyU1157FeNb9pdTppOSYegg9pSZIS9LlioxtC1KjUvQWluaumVI0LUt5ycnHD39FGZmWSz3WG/WkHqGzoDLsbYkGYNTCqcN82mByyLQYq0jRU1KCWUcME4rUcRdIDbjzyJp7kdzIcTbRwKgEOLKUvB1Eyfuh0Gzu9ODAZijI8DAwn2VP/f9+8zK9/F//b89Bx6m+YKqepG+r8jsDfrNPa7ftgR7QuNz9vf2qbZr6rompIgxBmMNWinmakZVVaAVeV7gQ6QfPCpGsizn5OwSXUYKZ3nhhRe5bMal40hkNp/gw4BRCmc1WkHdD2htcVZzcXHJSy+9zJ07d2m2l+wtJtw6WnHzYJ++H/ClxhjoGKuQWVlQTKb0VQXGELUDNy755kpzenrCay+8TJGtyCcztDWo6El9hymmrLuO0nbgE6brMdpjTUInDQSUDg99+G5XZU1vfeaJ3b5MIcTbTQKgEEI8koRzG/67j69ow7P8x19bU9cXtE0PyWC1J5v1PPuBJ9g2DcYeMput2G439H1PCIGmHnDO4cy4ZIpSGOfoB88wDFhridHTNg0xDLTVljyzHOzNSarBo9lUW7TRGKMZBo91GVprtB4raNZZXHQcH98lc45rh3t84P3vI6enbVsAOj9W+ozS9L4nhITOC/rtdgyjSnO5rbBZzv7qgPcuFnz5ued59Y03eM+zH+DGrdtUl6fkRUn0gRTC2BomJIahQ+sa8H/g5yiVPiHeORIAhRDiESgsKTZodcZ//7EPUl/M+Orzp2yqCgL49pJnnpxx49YRX3ixopi9n2IyZTqb0TY1fddRV1vKokDlBUkBWqG0JsscIQSqqifLx8ttU9PEBjzsLxco5Ti4fotmGPjyV75C03Ys5ku0UsQYKIqCEMI40cNqptM5mXMc7O/R1FuG0HK0OKQsSrKypA8toeshRFQMHF27gctLiIlNVXPv7JKoNI1PPPn4bR5/77O8/OpdmhA4vPk4ANvLc/IsMS0mBOWoh4EUA1p3OBP+6x+oEOIdIQFQCCEeQYoaTIZVNWpoyA3kheXuSYczFh0uefqpJ7HmgG19RtKKrMjZ3z9gGHqGviOGnhAGmi6RZTkoTYyRLMtQSpHnGVqrsaIH+K6laXqwJVZHfFezt9rj6Sef5O7xyThH12iMhhATfd+R52NfwjxzZM4S+pazk44nrq9w1nK5vsQSsAQmTmGNA61JxpFsRt92FLMVq2uRF19+jZPLV4jWce3oCF2sOVtX7B1eZ3l4k4uzC4bNlrm2eG3wPmCsYpInChv/Vz9TIcQ3nwRAIYR4FDqCSqhUEDpLXVW0vaLI56Ruzf4q8b4PPMb6MufeHQ2LFms1xmWUZTm2fNGQIng/Nl7OshxgnO07nXJ5eUmIHo2inJS0ITFVhmAy6rbn4vQeXd9RFhOuHx5wcbHGDx7fe7QzD6Z/kBJD14A39Dqx2lsyn82w2pBnOVpDYTNmhSNzmrzIQWvy2ZxkMpq6ZTrfJysveOPlF8lee5NyuU82mXNZN3QJ8nxC0o6225B3HcFYUlJoApluyXT3DT5EWf4V4p0m7daFEOJRmEBQDShL12mqqsfaktXqiMJFnn12yo3blpPzlmpbkEJgs93Qdi2LxXw8XasUmXN4P7DZbklpbKdinaWua4w1zOcLlFLjwZHgKTJH9J5JkWOVot1u2Vyco4LHaUUKHg1MsoLlfM50MiF3Fq0ikyJDpUjuHM4YrDH0Xc/Q1TT1JWenx5ydHNM1LevNmt5H5ss9iumcISqmsyVox8VmS9W07B8eYmzGEBM2nzBb7ROBfhhA691c4w4V12jV7D649HV/hBDvJKkACiHEIxnHxkUSMWm0cmQmB6XIF4nv/egNsuk5Kr9GVk7pqoF1WjOfT5hPS5bLJYQBpcZ9f3ePT3nzzTfYO9hnu9myWa+5dnQNgGpb03X9OGkkdaisZFLkzGcLqrZnXTXU63OKvMSMM+cIcew3OJ9MGKwh+J4UPEpZNusL3sRTcB0TBhrXkROZFznTsqDtekyRM1+u8CFQlhPu3D1jvV6TZxnb9YbL83OuH92gaVruvHmH5bPvAWOou4FkBiY5KAPJ90wmCWsGJPQJ8e4jFUAhhHgEKRoIDmMsZaGZlaDTOTq+zp/62GMcHTli2jKZG0wWIYL3npOTE9qmZblcElMixjiewDWa2WxKWzcoQGtN13bEOE7nKMuSsii5ffMmB3t7zMoJKXiaagPJE3xPGDqsURR5xnQyYbVYkmIkz7LdjGGFyzK225osyyiK8sEfl2U0Xce9kxOapoWksNbRdh2bbU05nYI2KD326Tu7+zoMLbMywxDom5rNdoNHYcspXYj46JlMLLOFAdMj4U+Idx+pAAohxCPQyo6T44aGPK+4cX1A24rHn1jwkQ+VOHMKakqeG7QeyPMpPgTOz86Z5I7FcsVkOqNvGxKQO0cInrqpKYuSmBLaGKbzOdvtFmMMISmmkwkX9045O9+Ql1OC92hjKIp8F+QKVgfXSFHx5p07FEVOWeQsphO0hjLL6Juaum1p2g4LmJnCFhm5cxAii+Ues8UCpQxoS91tuaz7cd9f07N/dJO5rolDT1mUJGVR0VMWBXvXrqFdQdMGtI4463H5QEqNzPUV4l1IAqAQQjyCFD3YNAafsuKj3zujjznTPYPu30SpRAorthcNwQ+klNP7hNaKzXrDfDphsViwjoG+7ymKjLpuSTGgFEymE1b7e4CiLArWXcekzGmqima7JTOGa4eHmCyjj4lmGMiKKUpprDW0bcdrr77Kwf4+7K24efM6i8WMpqlRJIyKNN3A+uycY9vz2M0jHJ5r+3vUbUfSDRMcffRUQXH3sqYZFI2ecHlR853XHf0w4MoJvms4ufMmTVOjXU7b+zHAMuBMQ2YblOqQxSYh3n0kAAohxKPQAWIElUGsKcue0mqGvkUbIGr6pgcfScNA3a+x2YS91R6+b6mrGmsdk8kU5xx5nrN2G4YQSClxsH9AjJDnGTEllFIMw0BShsV0SkiaertlvV5jigkRzRDG8XUvv/Iypyfn9F3HSy++xEsvJu7evsnjTzxGXmTMy5LMjKPjbDnBaMP5+SVWRSblhMEnsmxG23pOq5rXzra8dPecTRdRyhF6xfyV1zl67GmUsnTdhj54mqZl23W0PjHJM5RqmeUeq7ZAC0ze2Z+ZEOK/IAFQCCEehWI8/JFKUB5iCzHHqikq9JA6cguTPMeoftegOZJipOs6zvyAIaG0xuyWcI0xvP7mXUjgXEbVNJRlSUoJ3/fEEJjMp0RlWG9bqu0GPwwk69FZTtv3bLdb7tx5k/VFhUoGlRIxBl5+5TV633Pt2gHDfEauFarvmFjLtYMZKvVMMoMPkWmZEWKkrWqOTy954bV7fParr9FEy2rvGjcOD+mHNzGuoOk9Smnm8zk+ROrBk+JADAO5SyznGSrVKDOMo5WFEO8qEgCFEOJRxITGAGkMgCaikkdhSCRQiZTWWH2Hg72C9hRSiLTbNX7o6ULAaI21mhg9EJlNS8oiQymwWUa73lKdX/LYrVvctYptXRHVePrYh55AwmQFvY9oIpuLNXfv3qOqGlRS+DhO31BKEULk3r0TYgioEFhNp7TGk5UO7xNOwcH+ARDQRU4zJM7ON3zmC88RZnOCSlxenKCSor4450Pvn5OUYfADKINPBabwZCnhyn1SdcG8PCbPXwc1QFju5ioLId5NJAAKIcQjUOjxTKvyjKcbHOMetwAqApoUYW9ZcvvWHvcuewYfCcNA33WEGDHG0LQBP3R0mcGXA5OywGZjsAxDoOoHsjLn6MZNyrri8nJN23oW8xm+GggDRJ8YfCT6SF01xJiISoGGtDtpjALvA+cXF6To6RcL8kPFtCiIyqC0om09ykJhLHU18NkvPscbd8/Yyyc0Vc2sKMkyw+c+93v8D8/+SVIM2ExjbI4PCuMKlqXDpgkx8yyXCW3W4wcWc1DfqBm0EOKdJAFQCCEeQVIKUKACJI1KGaQEekCpBMmhVUGe5WROYVWk8gGfAiFGUkp0fU/wnsxZsiynazustThr6duWLDO0dc8QIQ6Rtu0pihKja6xOOHosoGOi3tZs1htCigQ9vjTiGABhrAIqY/A+cnJ2Qb3eYiJkLsPljqlT5NmAtlDdOWWxOiKfL+FkTdcFjt88ZrpYcHy5xk4zlI4o5XGuxJmSoQtYa8mnE3RQFKVhvtAoFCQNSlrACPFuJAFQCCEeyS5hERhLbZqk4i4QgkoWUAz9mqaqScEBBmMMzlmGwTMMgRQSOjekCF03QD+wyAu6pmI5n3N8fIzNM/b298mygqHrsUoRUqAwhrYbiH0P3rNdrzFaEdWu455SqF3vlfv5SxlDSok+Bu6cnrDZbtl/Y8HjN444Pj6hrdd84IMf5APv/yhn68Drlw3Hmw0XlxtmiwWFs4RgmU4KrE2kFAkhEVNEAX6IONVRTrdkrkElDcqSYpQ2MEK8C8nZfCGEeCT3p1qMJ28TEZQnqURKYyCEHm3WTMqBwiW0Thij0VqNjZ+nJUVR0DYdF5drusHjQ0ApjQ+eclIQYs+947vEmDg4OKIsp0wmU4gRoyBTCguUzqJTwAAahUFhlMJqza4Oh7MWYwxGG6x1hAR113Hnzglt69lsWnyXePLGU+xPVoQuMJkteOP0lA9913fi+4GZy1g5x+H+HtaoscKoFOW0YDKZjCvgqSHPLjF6wxiODYnwzv2ohBB/IAmAQgjxKHZLqySDIoHuSboHQCk33qdarOvY2yuZTSe7wxie++ExRs/gO5quoaprmqYlJkXTdsSQUAmWe0vOzs/50nPP0w2JZHJcOWOy2me6XDGZL3jyyaeYTiZoEtbswh8KpzRWa4zaBbWYyIyjcAUGA0PEJI0dYG+2x/616zz+9DNMixnr43NSHzk4uMZ8tWK+v6LtB/ZnMz7w5FMcXbsORIbB03UDPnq6vkMpg9M91lygdQUYSAa0LAEL8W4kS8BCCPEIFEBSgB3XV9Uu2CWLSmpXDYxEMnwq0HZClmtSasmco+9amqZBqcRsNiH4QIoJ53KqqgGl8T6w2tunnJzxmc9+kbpXPPH002hT0GjPvW3F+rLmI9/1Pl4/Piei0cpgVCDGcZwcKNCJGAKZdVgUhIRLmjLLWExm3Dxccfvadea39njiiVuooHj+pZdompazpuLZZ96Dj4Fts+GrL7/AX/4L/zvm8z0CDc4YlLZEIjEGrMoweIzaoGkhlqQUULsD00KIdxcJgEII8ShU2i3zml01MI373TBj+EsB1ISmu8ZLrwW6VLC3P+fi7ATftYRhIHOGEAJd34/996YzjLG0dU3fd7SdpyymHBxe49r1LV954WVevndGNIqA4o07J+hkefIDH6aPiqKcEohEP5BURClF2i3/xhAgJUxSlK5gWRRcXx1w8+iIx5YHPPnU02TX5tx87DYZht//8gu8fOcN8v0DCuP48ovPsbd3wJNP3oYyJ0YNSjGdznDZgtZvSNGghohTHqsHlLq/7JsgjSejhRDvLhIAhRDiESQg6YiK4w678dAHQCCpftcb74AvPBf59OfOmB8ccLCaMfhATJGiyIkxjMvCMWLu78+zBmstXT+wWa+ZMGU5nXK4v2LbDmzqmo0PND5wUTfg4fW795jOZqSQsEaTjEWZ8QRwiomoDVEbMmWY5yVHixVP37jF40fXeezmbW4eHDI93MOsSkwyvPDiS7z4xhvcuTjn6evXmRYTCpsxKSe8/OprfPDDH2K9qSkmEaVbuj7h6SjzCdYknA1owlvBWCmSkoPAQrwbSQAUQohHMoabpD1Eg0pmvFX1xBQJap9Xj6d8/vmOi3bO5uyS5WpFPpnSbAas03TNQO4ysr0cnyBGRVEUKDVWyorcEfuWTCUOFyUXF5a+GuiU47zp8CHRdx0XFxc8c/MWjoTVBhUTVumx9ctu/18TYVVOefz6DR47POLZx5/k1uF1jg4OWeytyBdTXJGx3qz5vd/6XV575XXSfEIyioODfYamw6CZZCVf/vzvc3k0ZXVwA2ctSVsIfqxqmkTmAoYIMQEetNrVIYUQ7zYSAIUQ4pHs2qsQdpcNSSVAE9KS0+qQ339RsR722A5b0rDm1TfusJpNiWhC8FhjiClibIbVhmHwkAIpBbQC37fjbGHg1uGSYehZv/g653VPWzcobXDWErynqypi1zMpSiZZQZnlFDajKHK01myrivlkynsef5Lr+4fcvn6To4NDJkUJWpE5x6ycUZgMh+Hk+JiD+ZOcn51xdn5O3WzZbNZMJyXbkzOabmw4DWCNYgiQUmToNjCpIe2WoFXY9UyUQSBCvBtJABRCiEdx//QvAcU4ng0ViMrSDtd49d6S108N542n7mrS0PFS3fChD7wPl5c06zNMDIQQMAHyshyfNgZUCmgV8END7jKqzRpnFEd7Mw5PZ5xVFwxtj1cWFQO5dUQfWE7n3Ng7ZDqdMp/MmGY508mELMvYNjV93/P0Y09wtH/A0cEhq9WK4MNYqQsJ5yxZkfPM+55l+PVfpW9b1mdnnJ6fcblZY6yGGNibr8jLjLbrSMETm5p2GHBO48MFKbbjoV/F+PkoQ0oS/4R4N5IAKIS4unYtXdJDnYrHS1+3ae1rQowarys9zv4lkFTEk3N66fjqy56Ty5xtVxEYGJqadTdwdnHB0WqOc9kYAH3D0PdYl+GHgdm0hNxhNVhn0LrA9w1NtWG6PODm0SH36oi5c46PeneKeEppC5567EluHl5jMZ2yN1+QGUtZlBRlQdN1nJ+fc+PgGnurFVmeY5wDa8gj5NaRFQVdCHzgIx/mfR98P4vDfU5OTnn85i1snnG+vcQPA5NJwXQ+YRgG+qaibhuK6Yw8K1DKY20Ymz6n3RIwZmxInWQToBDvNhIAhRBX3Lh8m7hf2Yu81ex5vG+MhXp3vQVtSGmOUg1wQUorTjcf4NNfWXLSFyh3jmrP6c4u6L0mKsVrb9yjcDlOZ3RDxWSaM/Qdydfkxo6FxKjItCWFRNOeMysd0SXqdk1uDNoHClcQ0RRx4MA5pk3Hk0+9h8LmrCYTZpM5eVHg8px8OqEnYFzG6uCQ2XSGcxaUZlJOUEmjtMF3HW5mKPdynvnQ+/ncF75EW1fMo2cKoB2p1HzkI89ybXHA+fk523aLKTSz1YxpDstMU+ZboAelQQcG5TEYjOQ/Id51JAAKIa4udf8faWxdkmD8h3roC+5fjruRb2438aMlJU9SS+p4k+derTnbFqBK+qbHtx6UJhBp6oY4DKymJUf7C2JK9H7cK9c2LSFBnnmU0jhnUClhlSFzDgyE1JNbxd5iikp3mU8nHJZ73Ng/JN+2HMz2cC6jcI5yUlIUJVleMFnMUM7iQ2BWlEzynNzlKKOwSmPKDOMsQWmUN8zNjMPZIVXVMaDQSjFZrdi7fsR7n7zBRz7wXoZY0/macpKz3FsxLRZkusE59dY8ZDQksEnJGDgh3qUkAAohrq77S7vqfuWPXY+/MfilXUBUsAt/kZgcKhmU2oKZ0PbXefneHi+fwKBzLs7OaasO3yeGEBmCH2fwDgMX6zXL2QSrDSEGyiwDoGt6QhhQ2qAjxOBxNoM0TgVJwaN84tr+jGmuOdtccHB0nYWbUOaag/mcZAzGOfKyYDabkRcTbJ6hjGE5m5MZi9N2DJUKnMtIDnAajAWvsL1hkc9ISfPEe5/E5ZajwwO++wPv432PXUM1Z1QXZyTtmc1XLGYLCAadwJmA0j1JhbGymPR4UCYlOQUixLuQdOcUQlxpSTEe5CDwYO9fUrv9fbvruzLWeNo3gQoQemKYcLI+5KtvLqnCERfbnqapCT7Q+0iI4EMgxkhCcbHe8Oa9e1RNQ+s9Td8z+PFASN/1BD+gFDjngEQIkWHoIQwUDq7vz/nAe55A+cRjRzeY25xrsxXzPGcxm7JcLsnLEps5XJ6RFwWT6QRr7fge9BhqA4lkNSopYojjiWSlcFpDirjc8PgTNzmcF3zHe5/k2WeeoHSWTGuCT+RZQZEX48SRGLAq4IxHqwbUwFtL5uwaQQsh3m2kAiiEuLoeVKbub1LT4/xa0u50r9ptBRwDzYOqVvREu6AarvPG+R7n1Yxt3bFdV7RNTbOt8WEMdjoqkjagYPCes4tLnNMcLmcoqzDKEE2gbVvarqXrO7RWTMsSkzl8TGRZzjSf0dgZN472yYxhbzaj1JZr8wVZ4VDTCdG4XVNphzIG6xyTyQSbOZTRYBRYgw+eFAYyDyYz2AysSQwOeu0xGWxPXud91w/4jhtLSjpiCPioyVSOKSy5y8bZw06TZYwHQPCQ/Pg5oneHa5IUAIV4F5IAKIQQwBjwLKDH+b4q8qCSlcaF4JQ00BFJdOk6x80tXjm1HF80rNdrms2GartlGDx96NAJTITee9qhh7LADx3GwCR3WJ3jlCbLC2KM+OBBQ+97suBIQ4IEk6xEG4cisZrPWM0zCquZ5vkYBld7DM6AzdHWoo3F5Tk2d2hrKIqClBLD4ClKxj6EIaKVJQz9+HZNRhtadFnwxDNPMVzeJV9k5P2GoYmYfErTD9D3uMKgQyLEYZz2ZgxJO2LSYyNo5UloUJaIwsgwYCHedSQACiGuNHX/0EfSD/YEJpWIjAGJpHd7BD0qpbEqaPe4tz7kS68a7l5E6rom9DW+acf+eKknhkBKby0jx5QYQqAPA1lrudxuyazG5DlGabRxhKGjrmtQCmcdEYXGkJQjRtBGsZyWvPepW0wKw3xeMs2mTGYzBmvBZiSlMM7R+Z5MjXsZM5fRti1d1ZCbseefTpCMJw4DfR0gRKpu4NYTT/HkB9/PG7/3m6z8BTF0QEGInsxqlBvITIYlEmIkKk0Xc9q0xOgDbOxQqQN9f0+lzIIT4t1IAqAQ4opT9zcC8mBNWCWU1rtRbwlSADWQlCIy57y6xnMvO166m6h7SGEgdj3jwZEIKWGVJegAWcAmRcoytNZ0faKqGo51QsWAn07IjcYAWhuU0iitiFEzDAkN9C5RWoczmmXmePbJm8xKw/7BklW2YLncp0ngd/v7bJkz1IEheLKUyPNinDjSD0QfUD7ijCX0FVprDJYQNC++/Cpvbi75k3/qu/HLBZOg8NaiswydwNcVJtXEQeF7wE7BZfTKUYcbWL3BKINNd1GpAjWgFch2cyHefSQACiGuuId2qD04DZwgaVJUY4VQR5KCpDPq4YhXz29wb21JqkSrhuA7ur6n9wE/hDFkRYVSmqAjIXlSSCQ9LvcmPG07MPgwLpVqg9KaSZGTTwpC8GzXHV1bM58vsa4EbQi+x2k4mBecnr5ONWx44ug2XmuKvKDzLVabcfnXWbqux8dAljuiNYxHUcb327ctoVpTzhaQac62W3753/xrbr/nFq98vieuTymv70E+Q7uSqc0gP6fd7oqlRLQKmNwR7R5tmqC8JqqCPDly/SqG0933K9+JH6wQ4r9CAqAQQgDspnqMe//S7jCIBhVJBELSDGHB6faQu5crhqQgRppqTVNXDCGMbVyMHZ9Dp7GxTAKjNX3oSSjyPCelRNM1XG4qCucw0wnKjqumKYH3AZUUs+kcay3bpkbrhNaG3BgOljNi0/Er/+5fc/mRNR//2J9FG4WLmqhgaBuGEMfVam1IaawuumAhJiKJfuhxfSRUPWau+fe/8R9o4yVHy1t0Jy8wKzLK+W3IJ+iYEeqOtt4SvEYXOcpaklVgNMrm+JBR+xtEDEFrUAO5qjF0cghEiHchCYBCCAHwcNuXxDjCjHHvX0ieoPcYwm3q4RYdS4ytIF6i44AziuAUqQerM7xLRHp0BOstKld0rR/7+sFYGYxwcXGJTgGVItMyJ0WHUhBjpChyvI/0Q09yGhUhSwkVEskHDq/t8fzxKf/6P/y/uf7Y43zgPR/CBIXvByIRYkTt/gfjKrdR4/tSfiD5njAEsqnjSy88xxde+DxHN+b46h6uGMfDUTiUcWgPse8xNmFcTpaX2LIgZQ5lLDGNyXVIBYmjMTwnT0yBgmOcat6hn6kQ4g8iGzOEEFfWGPnSWz3/docV7gcnpSJRDaA1yu7RDbfYNnuElJGip6s3+L4j+J4w1FgimcnQzpGyhLGJLGbkOiPPLVnmSGns7xdTomk7qrqhaVuGwRPiOB1EK4OPPSl5TKapu5qL9Zq2H6g2NQpFSIHH3/sEwXr+X//ml/itz/wmKkWMBu0jORoXE3rwxLph2GxRTUcWI85HiqjIZjN6k/hPn/1P7B8t8P2aYbsh1xlmMqNSim7whKYhtBVae7IsMoSBzkMgJ3hFu70g+Q1GD2AX9PoJqvh+mvQdePXYO/ozFkJ8Y1IBFOLbTPq6Sw8vv6Wk3rohpXF/2x9qVtf9AxIPVcm+bRb2xlPAX3tOVY1rsWm8L6qMLsw4vsg4OfM0fUPfVkQ/YI1mMimYTHL6LjF4Q+oTSnegDb5P9ClRFgVKGbz3kDQ9GUPyxAQhQlIGtAY1/kiM1Shn6MPAtqqwxtF0LdEGulOPnWQYrTm6fcjFvXv8+1//FRg8H/6O72S2mKKiYmh7UogMQ8ApMM5i0CijKOY5rfN86rc/xb3TV5keZrjkIRVMVvvMDq/T2gxrDGWh6NqezfqCpfMQe4IP6OQwxpFoSKnHmAJlLMSMkK7jrWHQCevfRLNBk1DR7DrrhN0nvft79DVTWXY/AyHE20YCoBDfdvRuHxu8Nd7s/mQGzbgDLKJVGm9/MPo2vjUb9+FfxokHj32wT+7bxJg11Bi+lN9NrbAkDOBRRFTMSXrFZlhxZ1Owrgea+pi+63DOMgw9cUiEMH6yg69h6CnMBJXDZXsBUeN0AdE/+Ij9kABD3XmOzzYMPrCaT1jMSspiHDc3+AE/DJgYianD64TRUF2eMw8L9pYr9hczTAycn5/wK//p/8Mr5y/zPR/+Xm5ff4xiXoAHUzr6psFYgysKKj/w+ukZv/H5X+e3P/Mb5CZydHCd/f0lB0fXUIspyuToJhD0hiEzmFwxnyzQqaeYTQhGQ4z4YSCpRB8ULjqcHkBHbF6i3dN0cULkjDx+miK1EItxf6TuxpF6STH+PdWAAe5PEpEAKMTbSQKgEN924te2Nbkf4BLjUqaKKCIoDX73fwH3qy5fP7c1PSgX8rXVv28n9yubD19OKKUhetCGiGWz9VRVy+ANWmum0ynDMOC9H5dvQxjHtpHI8vtLvQPWWqwyJBJ9GwBNTJFyMiX4SN91bKrt+L1iQJEwekbuDKAwWpNnGSlFYvCsz88IIWEXir5rCYNnPi3JrGVTtXzmc5/ixZe+zNG1m0wnM2bTBWUxoW0a/K4h9d3TU15743VOLt5gOZ/w2K0bPHn7NsvllMVqj2QM3vekZAhJo5SlKCeYGCA2KGNQRmOcoxl6vB+wzpBiIMYBpRQhpF01c4pxzxC7N4nxNbQOjH9Hx8kq9//CPRizh/kv6rFCiP/2JAAK8W1lXNYdK1i75sYwXiaOY7rUgCKSonrovof+nR4ai/bQ835t5e/brTpz/73df1+7EJ0SpIiPlqbJ8V5hjEbpbPyqGMeAZy3eJ2az6RgcgaqqqKoOYxUhJZyx+F7jXE6Iga7tyfJ8DJB9T9V0QMQYTVEUZNaRYsRZi7OGYRiomxpCxCpFW225PD0h+MBysWKxmLFaFHT9DGMtfTrj+M4rvPb6XdqmQ6PQKAbvmSwm3H7sNk8//QGuHR6wms+YzydYY0haPQiv2lmccxg7TkgxboJVGk8Ek2GNI0uKtNt7SArAeBp6/BwMkRnRvA/tzhiGNU5fonVEp/tV5Yc/9zTeluK3318xId5lJAAK8e1GJVQKjMtpMP4mDaB3S5zJjvelCKoDZb7ua7/myd56/P0l4vTtdnbs/qSKMbCo+2FQjXvVIoqQJqS0wLoJjoDvNW3X0vc91lqm0ynW9hjjaNuOvh3DXJZZrFFUbU/fNuR5BiTiEBmGAaXvj4FL+OBp+oG2HxhiGvv3FTkKqOtq/F7GklIiDuN+PN97Yky0TU1VzTg82MNay/rykqZrWaxWfM93vZ/gIyopnNZkzjGZFRRlhkLjXIZW0HYd5aTE+0hRWLTWZLmjLEqsNugQ0GVJvdnSh4Fimu+KygqtEzH8/9n7s1hZ0/ysF/y94zfFsIa99pBjzaOrjOU2uOSDGY/d3W61EFar1VIjkLhChSVAQggJIQYhS9xwZbiibfrCN3SLRrg5gEHgbo7LB7vaGGpwDa6szNyZe1p7rRXTN7xjX7yxVu7MKgOSK4usOvGTVmZErFgxfBGZ8cR/eB5PBJRUSCURCJRSoBqiqDDiwyT3CjmtETmTk3zrOweKLMp7TKT9l5dDFfDAgXeVgwA8cOD7jetFj1zajcA+m9WDaEjxiBRblBrJ6hGICZGr/TD+9azgdTvuHQkZ37c8+3x5qyUuJFkoYmgIYY6UFqMnSJoqV0ghSSYVQ+dUqn45FTNpJQRCKwIJIyWj99RNTc4JEQRt15JiwhiNEJlxGEAIkhCElEhA3NvGKGNoupYUIilHkocYI5ObCN6TUkIqxWbbMI47nJ+Y3MTQD5ydBUSmJH/kxEQmTQ2xrannc6zVoBQohW5aslQkIdBaUVcVxlqiD3jvkSRCzrgQUTGhUtpPDZSWudjPkuaUCCEglEaphEejuYXWd8juNXIO+/dp3B/z64+ifQbzQfsdOPCucxCABw58P5EBIW66uGKfbJHJICqCP2J9ccw4tMyXgfZ4QsoVpL0VSlY32a3ieoHkfzUCkG8z8wgJg48N/SDxLhGz32/yZlKMxBiRSCpjEE2LD6XFbk2L0ZppGIhpw+QNKUW0KpvAdV2TU2ZyjhANIXjIER8Cm90ORWK5XJZ5upxR2iClpBEtOSWklMQYb7aGbdPghWA7eSpjIHumceLy6QV1VRGDQwuB0pBw2EZjbYWta3wC0zRgDEobYhZobZFK473HjSMiBsx+7s+KzDQ5pPIos//yIEu7PKUEKZBzQiqD1I4hRVIwzMUxiZqcR6SQvNV6l29fRvq+f78dOPDfn4MAPHDg+40M7GcAswggIEaFELd49Ibl8mmHtc+x7S95rnqRrlMgrkgpIoW6EZFlI/a6NXpdGUy/691+b3O9+VxUSDlVBHFINecXnl2fcM7x9PwBWimOjo5Qbcs4TDjnMUYRA4gsaeZzco4YY3jqRpSSzLsZKUWsMaSuxXmPVJK6NgQvCUYRvGfXb9FK0BjDerNDK0lTVyglSQGUTHTdjHEcmO/FpFKqVObchECQA1S2RitJ3dRoLelmC6zVSCnQWtMeHaFMRRaKqrHopsbUDZOP1E1HVbWQyqavzKIIXaNo2gVCZYYxMEwTVuiSKmIFypTlEZmhm8+QWhH8ULbOdUtOczI1oPdfNK6rzYnSbKdkLx8E4IED7zoHAXjgwPcTAiCXD26hydkBESWPuXracP64JsVTyC22MTx8M3HnzoLZbCDngUxGCvFWC06kGy+8a5H0/efS9pbgePafEElZsesVr712yZsXjxhcYru54NatM6SU+Gkix4SWEueK554xZWEjhkD0AS0VJ8dHrDcbpjGSUqSpa6w1jMNIyglrFNHuZzFTwvmJq6sV1g4sF3OapiHGTAiRnDPBl9m/pmmLVs+ZYRhIOWAlWK2x1mKtwTaWujYUgVWeW93MaJslUmqsacAabN0itUFniVIGrex16C+z+RyRalIKSJnphy2Ti7gpU1UtSgiUFCipQEuUNuVIikxlNG5yxARJNgjVIcJl2XoWCkTcV5u/X79cHDjw3uQgAA8c+L4ig0gI1N7iLyKEIIWWJw8y09AhpEAoh8qScdtyqStqO0PbRM5uP0L47Y2f80018PtpSOs69xdKS1LenM5U9DvD+dORzW7NODh2uw11VXN6esrx8QnDMJbZv2zQSjFNA13bEkNkHAbaumY99EgSbV3jrq1irCF6x+QDSkms0eSkyTHincflvf1LAuc81mjE3k4mZfYzd6WCFkIoAjQntFQYa7CVBSEYJ09IkeAdSkqaqkHPKoiyzC7mUuEz2pAzKKXJMSOEKj+qVAzJEhEE280VV+sVSmlilAgiUqQSo2xACVWWVRKM40RbV1jZEAUgG1AdOSiEvG71XmcwPztzeuDAgXebgwA8cOD7EZHIOSMFQE2/VmyuBFZ1CCOwTdm4VKple1XRdzOWtwM5TWSRIJVZQCHfKQL5/tJ/N95zmptNZ67b4BHQ9L0lJkAGvOuJIbDrtwzDwGxWqnM5Z8axtC+rypBSYjWs8M4RQiCT0PsKmcga51zZ8tWKHCVpbxODtgQ80UdSykipcN6RtonlYoG1huAzIpZK4ejcfuYugVIorRFZMgaPT5G0z/7NYyaFgDUGKSzOeXbbHqWLnYzOmdrPQQu0rfGhLHcorRFSETMoZbG2YrvZEmJCaYFREklCi4x3E9bWSGmRomwX55hIUSAieJ1xqkHnBSqrkpSCLkbQYi8Gs9q/Boc28IED7zYHAXjgwPcV+w9RkRDZg1Ak33J1nsm+RVSSttEoI0lJME0Trm9YPw3MT4biCJMjYHjLGgbebgT9/fbBnIshsYj7lvfemDgHUlZMk0FrA5NDy0htLM451us1bduSc/HNa5oG7ydqXXF1dVnsVo5rcs5MceLxY0f0rvj8VRbvPUkIhhgJviSEGL0XRBpCDKy3G6wxVJWlqiy2ntPYDm0N0zgQnENnkFKicyIJIESGXc80TWQB1lqatiUrgwSC96zWl6QcOF7O8d6QnSJ4hzWWqqrIoohHaQ1CaYSUZDJDcGhbQ5ZF8KkKP41IeZ2aklFGIVXZLK5MhYyRyQ0EpYnMQZ6SRUMWm1Jpvv4ykRVgyMIdjKAPHPgucBCABw58X1EsNXIO+2gzSxgs2yuJFg2NLdWZ4DLG1EgxkoJhu9K4AeqFIMe0l3jXXoFwM58lvl8/mJ9tbZdnn1KELMnRkpNgmnqqymC0ZT3uePLkMcYYzs7uUNc1u90GAGMNR8fHkCkGz9seP2zJqbR6oy+bw1oqEAKjNdYYQijbxDGXOb8sMi54IhmfA2KrQAvausLsbWGcVvuQPoEMkRAiQkLWhkgm5UylNZ2tCD6QU6KuDIJEDCPOSToxQ0mJ0ZrKWqRSzOcdpqqKoBQSKRVKKYypSLsNUilETtS1JedA8I6qrgjeYSqKdUwus4laSapG4YQkUoNYILWFHMmIIr6z5DqCT8jruVP1bV+pAwcOfGc4CMADB76PKPYvEQh7f7YlwzAniQ7TnSKbJRhJGEeyG6mVIhuNc5ntWlLPOhA7shgBiUhFEGXEW/HAb7OH+d0Qbz+d4abUc72owt565qal/Oz8101ZCHFdlbue07tpF+7/8KZyd50l+845svTM7T17P8/E5JHIIhUBktmbQQuy6hhSw3YMxCBZdpbd1hOdY9jtWM7nnJ3dwodEzJnZfImUiowuMW0xIYVgMZsTnENKyWa9IXiHC57KVnRNAxkmJmIEhMKHhFCClAU5Qj9NZKHxIaIV3Dk7o6kqjKkQYr+1LCJKJlJwEBNRgpQKbQxWV6j98zxeHpXYNvZ5vdpg6hZpLaZpQRmkqcjSkLPc/x344PFuJMbiO9hoiU4T47BDGUtll2zGiKHUj7WxJAQpJ4RW2BzJQeHyKTIvqRCIlPYm0CAIezH4X3tvHThw4DvBQQAeOPD9xl7biGxIoWMaK5rmhNn8OXTdEUSi7zfEcUPcOXJ0xBDZrSS3bncIPZCZEBje7s8mSntyHzf3X+bb7Qo/2z5+dpDwd2srl6pcxpf7vl7OyOmZ5I79I8nXaSbX1ctnIt2ePftsRvIzB6tI0bcLUKUsvRNcbgb6Edqm2Kj0IqGkxGqNEkUQ102LqSp2/UTXGUxVE0PE2oRVmpgCMUQ22w1d10BOrNdrxjFiTIWScu8P6MtrpyQhOtL+GE0+UNURMTqslqXiJxTXC9s5Z6QCqQ0oiSIRgyytYW0xRpNToKlbjo6WCK1QWlFVNXU3p2o7hCrt3iw1CEWImRA8JgtkFEglkGQCGWstbndF3I5oLZFCIoSiqmsygpQzxIRUmhgh50RVSaAiTA0+11RSA4EbI8OcEISbd9dBAh448O5yEIAHDnw/IcTeCDojREX0mjApjJCoNGFFTV1XpKDYThlpFWLKuJ3j8qnnzvMGO5MIKSGb/TxhACIilzxY8bZM4G9H/tbT4tnL3yHCsnjH5UXu5Ztt3FLZy/sK1rW5dSnglQZo3s+PCcZn2tTPPI5v0avXj+vaAFrt7+d6EQQQNX0fmcaeqmqxbcXYR5SuyVxxefUUqWC+nLNIERdiqSCKFi0lKQVyziglUbpimiaUkKXtKQSLxYJxHIkxIsgYY/A+kGL5u+t4uBA9PgZSTKAV1lqkVDeVMkFJBYGMVgJhFBJL0qq0do0lxoBQgiwyvZtoTcvi6AhT11TtDFk1JIrQzCITskQIAwhi8ISc0AqUSBAdOXjcNGJFpLIGqRT9MNAuOzyJnEKpocrSSp8mRyUUJI1OAqUbUhD7Jm9+Rux9v44YHDjw3uN7MtTzZ3/2Z/mRH/kR5vM5t2/f5k/8iT/BV77ylbddZxxHPvvZz3J6espsNuOnf/qnefTo0duu89prr/FTP/VTtG3L7du3+ct/+S8Xh/8DB75HEeQiHnImZ01wFckbQj/y+PVXeOUrX+DJG68zjT3ej/jgQGaUNIwbzbQzQIkmEzct1Wuj3vyO0/8lchFXb/v5do9XvE0OireJgQjC7f+9twkR+2vcCMpUBKp0IPt3iL9nBafkrTm/tx5jJu8zaMssmsgZISYgkKIihBqpWpq2ISaP0pqmbWjrGqs13k9cXpxz+fQcowRNbRj7HWO/fatSKQTD0COlpK5rQigC+jpDWEpBCIEUYznuZEjlMaWU8b5UD3MCIRTGFLuWECLOeUKIZdvYe0Is84NSCozRGGuo65rZrOPo+AhtDUJJ2vkcVVl006LrEv8WEbgQmFxgnBzOObwPTOPE1dMnPLj/Gq7vSdPA1K+pjGI+n4NU2LpGSIUQgrqy+/svM6RSCmxVgSiPOyYBsiXnim+/Un6o/R048N3ge1IA/sqv/Aqf/exn+bVf+zV++Zd/Ge89P/ETP8Fut7u5zl/8i3+Rf/bP/hn/+B//Y37lV36FN998kz/5J//kze9jjPzUT/0Uzjl+9Vd/lX/0j/4Rv/ALv8Bf/+t//b/HUzpw4DtDBpETSmhEsrhBI1INKTNur5DRMe52pBAROTONU/GBE4YwWfoNiGRBQCJw/eFcZFfaz//9t3xJEt9aCMzfToTd/JK3/qCcLrrxHfODQFlO0ZQGhiq3KyKI6a37/m9qUV8L01Lxe2v2z5EERDln1VdMsUNXM+q6ouk0KTv8fptXkMkp0DYVtTXInIhuwnuHtSW6bdfvcM5x9+5dpFLUdYNSiu22WMnkfeJKjKFYxuRITsXoOcYSrXZ9WspSQSziz7Hb7djtdkyTJ6ZEjJ5MQgiJNgZjLe2s4+TWKYvlktPbtzm9cxtpDYMPRCRJapJQIDQpcXP7u6FnHAdS8qTgefrwAb/z21/ED2uMyKTrWcCmxdoarTXDOJBTJKVACp5pGrlu8ceYEcqQhMEnUzwBr1+rmwHT7z+b8QMH3qt8T7aA/8W/+BdvO/8Lv/AL3L59m89//vP8+I//OKvVin/4D/8hv/iLv8gf/aN/FICf//mf5+Mf/zi/9mu/xo/+6I/yr/7Vv+JLX/oS//pf/2vu3LnD7/t9v4+//bf/Nn/lr/wV/sbf+BtYa/97PLUDB37PiCxKRccbpkEjmVFXCaWv0LbCe1BRMJsdIULGjzuEkAQvePpkx+lzGmsNyNLKKxNZz27J/m7i6tt8aF93WLne6rzOGH7WUuZ3+7BXkAxCOjIJhH/mrkUxJkYXwZOuW9XPLpG88/Z/F2GYNeyFbSYAGp8XXPULXnkjIe0tZrZhHD2b86dMQyiVOyHo+y2b1Yr5fEbwvtifILF1g7SWEAIxJRaLRXkEQlDXNcOwI+fMarXCGIMQpVUaYyCliA8eZHWzKhNjZBxHptrQVKYIxxiZxom6rhFCoJQgiISWxbZFaY0xlrrtmC8WOOcQSiG0ph8dVWtxWaKyBKHIWRBcRBuNlDBNIw6IXmK14NbRjM3VBZuLAUkiBMckBVXTknJGSonQCiHy3m7GEWIqaSO2wqfy+ihTo8SC4C0auW/pX5PIyIP8O3Dgu8D3ZAXwnaxWKwBOTk4A+PznP4/3nj/+x//4zXU+9rGP8dJLL/G5z30OgM997nN86lOf4s6dOzfX+cmf/EnW6zVf/OIXv4uP/sCB7yxZCnKU+EnjJ4uUHVU95+T2XebHt1mc3MUFxTBlqmZBVbc0bYXWgvWVZ+xrUmhLNUZOFFNpSb6p4F1/b/zdxKB4xw+8vfL3jvZsVm/9IN9a1BCQxV6UCQ/Skfc/yJEsBjJu7+VcxOK3ry4+85ieFZDI8ndRI0hkiv+hT7e43Nzjf/nNgS9+rce2J9RNTQ4RiWLezamsJcZICAEhBP12x2Z1xdj3eDdyPVF4PesnpKTve7QqbdL5fFGEX4YYyu1M04j3RexKCUoX6xUhJCkldn1PPwxM08Rms2G1XjOMw83jmJzDe4/3kRATCUEWam+tYnAh8/jJBY+fXOGTwNQz0DVZWVA1MSuGwZFiWT3x3pFzpLKaFCYqo7h7+xhNhBzp2pr5Yk4WGaTAeY9SqljY5ISQxSh6GAdCDFht948vI9Qc5Iy3RLm8eb3Ef/FLwYEDB75TfE9WAJ8lpcRf+At/gR/7sR/jB37gBwB4+PAh1lqOjo7edt07d+7w8OHDm+s8K/6uf3/9u2/HNE1M03Rzfr1ef6eexoED3xGyKDOAgpoYK9wkSDmiKo2p5qh2QdPeIu22TNMlIQUmV/JplYZpEmwuK7qjIxADQrq9OBM3C8GgEOJ6EeS6hQffuuUr3nHZ9XX2rde90MvFA6RUgkQi51huUl5bvEhyrkixQghbNkXFRM4DQnly8U4BkRHPesf9LovGNxdlEEhETiXyVlS4OOf1Bx2/+YUVX30tQnVCJKFFoK4swbSkWEZIcs4YU+1jzxIpRobdFls3uGkgxYQ1FqSEFPcbuZoQAlobmrrBzzzb3XZ/mWZyE+FaSClZtncp/58L0TO5iaeXF1RKYbTGaM3kHQCJCEmWLGcEKQkigtVmx+LolBgFF5drslScmRpjO7RtSKkkvgzDxPn5BbP5gmkccW5iGgNWRiyJGB3e9SgySglEzmilyFIRQkDZIvC0LuK4aipiyuhUFlvGEDGqIgTwQWFku7eZfLbC/F9bMDpw4MB3iu95AfjZz36WL3zhC/z7f//v3/X7+tmf/Vn+5t/8m+/6/Rw48HtBaCBY/ARTPzG4K+Ryzm7coQbBTMyxpiLRkKYtpqrxcSxVm1SxulDUc8vxC0fE+AgRA1IpUInsPUi7H9W6FnPvFHjw7Vu71xu276gaagnRk3MsNyXLvJtIFbDAeUu/q9htLCkajPGcnnmsvYS8AyJClozcIuq+1fOvPNyyiFJm7vabxRnIEyl1OHnKNx5o/sNvbHn1DYnp7iC1wU1bGmvLrKGUBF8qbQBt21LVDVIoJBJbWYw27DY7hBo5uXWGVrI0NqXEObdv+QqU1swXc3zwpT0rRNnupYjhlAJSlGWOYcgYo8g54X3EjZFZ0yKlZBjHcuSzReRi6CxlYvSBrBIuTIyTZxgdQmhiSqxWO5wLmE6VRZIUWK3WnJ+f8/zz9/DeMQ490zTQGompDd57cgzkEGjaGgClSkyccw6p67IjHovvX04ZpTRtWyqz4+gIfthvLWsy1TMrP89+YThw4MB3g+/pFvCf//N/nl/6pV/i3/7bf8sLL7xwc/ndu3dxznF1dfW26z969Ii7d+/eXOedW8HX56+v807+6l/9q6xWq5uf119//Tv4bA4c+L2Tc8K5iZwrVG4JLpKSx7lSub68eMrm8gnBjegsIBf/O2Ma6rohJ0WaWn77Pz9m99SiOELKihwdZAcqA/HGfuWZsiDfusiR3v7grreB4RnrlwxxBBlBZWJOZCzSLBiHM+6/esJvf6Hhd75yzKu/c4evfXnJb/1m4Onjmpxm5GzIQgKGnMwzlci3hETe+8zlvX2MkAIhi29dzgqUxnHEV16R/H8+t+W1hzWiOkEayeRWTOMGhcRPkZQ9k+8B6LqOk5MTlssldd2gtcKaEtE2DTtyjIhcfAnHG5GWEVJSVRVaG5QyVFWFUkX4KVWMm6uqvtkqbiqLsYq2bZjNytYwJJSWNy1X7z3jODA5x+Acw+TpxwnnA6MLrDdbNrsdMZWlktV6xZPzc8jlPsd+x/rqgovzx2w3a6ZxQAiBtYZxnEAI5ssFVdMSc8I7T4zxpv2cU0ZrjdKavPcolFIh9gkiWgkaa1A676ulCoQtXx5E3i8IPSMADzrwwIF3ne/JCmDOmZ/5mZ/hn/yTf8K/+3f/jve///1v+/0P//APY4zh3/ybf8NP//RPA/CVr3yF1157jc985jMAfOYzn+Hv/J2/w+PHj7l9+zYAv/zLv8xiseATn/jEt73fqqqoqupdfGYHDvzeEFJgTE1YSa7OJ1JuqZoKn6FuFvjYc/74IfVux/J4iRSSGIoPYIogcsaoikf3e/6nB6/wR/7YRzg+M2g7kkNfKm1Z7cuMAOktu5N3Cr53svetK7w183XTmo0KkVtSPuLpo4FXv+kZx2N8tOx2gmGIBOcYpzUvvFxz+7mElnH/EDLixsePt3emy4EB0t4fUZICCBRCGLZxyZd+x/M//8Ylj58u0Laj0ophvGKzWTEMt4khEUJCKLCVRquOGCN2Pwvo3ERtDVoq5l2L0pqQwU8jPngm76ibhqW1N95/TdOUqDRtqeuGYeiBjBACYwwGgVQa5yOLeYcQpVgqK4vYW62UbeMKKSUhRMZcElFiLUAZlPEIFKv1hrTfzh2nIhIfPLhPPeu4dXabcezZbrdAYhx6lJLInOm6GYtZi60Mem+AnYc1bhwwaKZhICuDbmqU0mhjyVJjbFUWYqQuVd3kSdFjlSAZjaFCZLN/ffYt4Lxv4+d3jg0cOHDg3eB7UgB+9rOf5Rd/8Rf5p//0nzKfz29m9pbLJU3TsFwu+bN/9s/yl/7SX+Lk5ITFYsHP/MzP8JnPfIYf/dEfBeAnfuIn+MQnPsGf+lN/ir/7d/8uDx8+5K/9tb/GZz/72YPIO/A9S06QksK5isyC+fEpqmoRqqLSNUFoprBifbVCIKlbQ/BFuBmtkDJCdhwv7vG5//BNWn2fj318xvs/cYIylhzS3iQ6km8aeKUidcO3WHm8Ve17a8D/LQGYEUW3yQVu6Hj0huTN1ypW64osNS55fIRhcsQQyHicy0hZlScMkEsG7ttLR8+aTe/tbITct4JLC3icJP/5Gw2//p8ueHRp8NlCcqTdlpAcIWR8iKQsaOoW5zPR+9JWHUdSSvubz4Cl73fUTUWOMDlX7HScwFTF+qXYAorSTs0ZpRRVVRFjR0yx/A3FI1BJyeTK/FxbVaQcESRsXaGExE0T6ZnZwhQCIXiGaQSpMVVi8gGtBNt+y9FihnMCvyuLJFcXT3j0oOP46Bityvxd1zaQI9ZW1NUMHwJKG5qmQ6RAyNB1c3apWALFGLC2orIarcuCi61qjK2JCKTUxOyLhVDOCJlJJEIAoS3Xr5goL8473i8HDhx4N/meFID/4B/8AwD+8B/+w2+7/Od//uf5M3/mzwDw9/7e30NKyU//9E8zTRM/+ZM/yd//+3//5rpKKX7pl36JP/fn/hyf+cxn6LqOP/2n/zR/62/9re/W0zhw4DuOFBJyRb/J2OqY9uhFMJbRZaJL1N2CM1OzmBIxSXIOBB8Zdzu6SqBURJtcrFH8jDde8Uz963Sd5visIyGxjUaq63aqQohUPrvFdQvvnVnBYn/q2c3fvQAUueQNqxo3Wh7e9zy63zJuzhBJIk1EyYisBFNIpD4QYsI7SNEgsinFyJQgX8eKPXtEnp1FTGQSOZWWsJsCb7654re+2PJ0NQNVY5RCEfaVxkBGM4wTLkwYY9isA+Pg4Xqmz3vapsFai8gJ7xy2MggR8X5CGVOWXJSmqusbjSP3beBSuQvF6y8nnHc476iqCj9N5BQwplTWvHfE4FFaYmTZejbGUu19BcmlejdMU7mNGDEpo2rNNI0Yc4y1BiUliMyuLz6EMTqapmLWNWglqGtLXRmOj4+pm4bV6goXIm1lEQJk6hAiM+42pJTKHGAIWGPwgBQKW1VM+y8WKSW0uJb8GVJi6Ae6NmBuZjQP1i8HDny3+Z4UgDn/1wdE6rrm537u5/i5n/u53/U6L7/8Mv/8n//z7+RDO3DgO0q+ybfdL09cz0qJBCSy2C80ZFm88sgED1NcsF55zt/4DU5P58T6GDG/jbIaFSAOI5VReAfGzohpxTSNLLoGMT3lhbuWj3/qhJOTI261c8KbDb/5G69z8sJdzl54H+sHr5JVIopA0yTO7laYo4lkr8iiR+WAlCVKLqP2tT+FyI6sHQhPShmRlpBfYvfkhDfvRx496nFegvWIlJCiwaQ5WnqqmeZ8tyFMnlkHSvXkpPaLwgmSIOiITBaZBAhPlp6UK2SS5RjmkcxtNv4j/OZvC770lTUP1hOjM4S9yBtTBCS7YWC+mBP3diiTH8hE6qZU4/phxGhNzonoHZGINJKQHAJFHAdihLqqEcaiciSEsi0cfUQKRUoOKRV10xBi8RcESDFR0t0EKidULKbcOWcaXXz/ZG2wpqS2GC1LCoiC09NjpnGkNgKZHNlBZWtyTMy7BW70BBcIKSLSRE4Tt27dRQjFZjfhc8W8XhIoLdznn3+BYbdF5EzTtkSRiLsBkQVdNyepmqw7+inTNoboHeRMTKkkf0TIUiJUSTkRKZNCT/A9VguyiAgxkrOg5E8fBgAPHPhu8D0pAA8c+F8P70zJgJsKmuAtz7wb/7xIDpkwBbZPN6i+5/UnT5FHE/a2pu5qlrMaoRWmrrl1a86wVlgZWJ8/QbgJnwVHy1v8Dz/2PF1dMV6sefDNN3ET3LnzMrsRLi9GpAJTKfrVyDg47n3oCLu0CLVByJ6cJ7IICCIpJiSarCTRKYQykGpyOuXykeSNVy/ZbDQuKJSxWFuDyORkkFiuVm9wdXlJCgYlPMvFHCFisYqhiGGEQmb1TLWxeAzKnBDEIjzkEVt/iy99fcvvvAqbUdL3A+RcsnqlxFjL5eUlSiumaaKyFYKSr6yNZpo84+DQSjEMI9M0sVjMSdEz61rGoSdpg1YKRCYGj+t3+BRK5N44kjOkVGxUmqYmpsg47ui6jpwzV1dXe8upTE4lgbmuK6yx++UMW2qt+0UMrSXGNhhrS6u1qmibmvl8zna7o64NOUeSj1itmM/KnKIiMe22mDN47s5tJp/pp2JJU5lyW/12W1KYU0JJhbaarq64vJwIwTM7nkE1R5kaqS0R2A09bTcvzzVM+OyxIuOdY5oGxP4LzM37+fr9LdibhotDRfDAgXeZgwA8cOA9zbW44a1hqcy+3Sp5Nkn3ukqYRSYGR2PnaFfx4PETnrs954WXPojXkWF7BWo/t5fK7FzTNRjOiK4h54BtF0gRuXj0mEev3uebX3+VFz/wPtrlEa++ch+XBIuqpqsq+l6yupg4Ge6QZGK3Cczm0C0r8t5IWglJjpKcDEpURGcJruXB/ZHf+cpjBCfMjm6hhSSljNKmJGK4wDhsCb7HyMwYeuZzwdFxRWaFlKWlWOYOBTIpbnKDsypRcsKBjCQ5YzPd4c2LW7x5Eci6QpoRay3jMFDbCqPKLF2KkaouVicnpycIUbz/pmlkmhw5Z0JI9Lueuq4Zx4m6MoSQKHWujA8B5xxt1ZBEZnW5w+iqxLRpiwuBlDNKiiLyhKRpGkIISCnpura0fX0orXIBKQZiEkgpsdZitCalRF1VpJSxpsJNI/OjDms0R4s5i3lLv9sh0oQQkqNlS8oe25RFjX694uLxI5bHtzg6usViofExEWMqFUilESkglCSGiTT1e5/DgN3H4UmtQSpGH2lnHevttgjMnMl+JLgdxtakFAlhxAqPEhmRxd7Im/37l2c8Ig8cOPBuchCABw68h/lWTzueWbJ41sXpOjRMERVMocd7y+7qgrqyPHjjDcZuxid/+FM0zT6dwU94PyCUIGtJu5gz9hBTAmmJ44rHb77O6vKSF154gY9+7CMoJXj+pffhFy02R/rVFUpVeCch3yEMma//p69h9AUf/dQ96uWC7BxuO9I7j7QWaGjb29y/v+HVVxxa3aOZHYHUSCWoK0vOirEfCcGTokPkRKU1qsncvjNj1gpIHpTe27vsRXASZPXW8REZMoEsBGOe883HHa+8WbELC0xrCZdvYI2h326x2rDdbpmmiZgiUgjqpmZ5tEBkCMHjfcm/HYaB6GOJ0AsRgUKbitENSCGICUIM5BBxUpXljGEg2prFfEmKHikSwQem4AmxbC9rWaxk5vM5KUSc03hXKm0lVxesrYgxIoSgbRsEmaqyhBCpbc02BI7mC2LwRD/RzVqsKrnP89mcqmoY3UTVNuQsyCHQb1awj3NbHN+ibtvi2pgSkoQxiuQnpIj44Bj7XZntU5Icixl3yoGQEnM1p6oMw26DFgI/bPDjBhUCqioi0LmRaCLI6wWQdyyJHzhw4F3nIAAPHHhP8+180d45I3XdThMgJIKGcXJcrS4YV0+5e/cFjm/fYz0NPHn8iLq1aKPRRmKSIMZMTB5jKkxTEb3DbzaQHF1X0b70AjobtM6EEOhmx6x3T7FKEWPD8e07HCWNVB2uH5nWGlUt2TzueOWrj3n68Bw1SXwlQTve96F7PHoQeHoBJ6cfommX+Bi52jzFxwmtLWTNrFkw6yxvXDyB4NFI/LTm7GyGUG5v6FwqoVkU+5OSUJL3SwUCckkS8XnGk/WSVx52nG86kJoQBmIO9NsdkrKZ68YJYzRWGJz3fPjDH6KxNZv1FUrJctsp0jYNqtNo3TOOUzFnngLOR6xVpJgQKLJIxBQIMZJCwMWeTUoMw0TTdeTMjS0MUpJTxmhD17T0fY8UgqqyaK3KdQCtFNPkgIQsVo4lFURK6tpg1JzlfEZMEaUEOTiskujasNussbbi7p07oM0+A9ojRSbnwDTuGMeORhmEMmitIJX7EQrcOGCbirprcbs1wzjSNR58j9AJmSXr1VOquiblSAwJkSJx3NG7xEwZrFZEL/em189saYtrL8CDCjxw4LvBQQAeOPCe5q3eb745/az9CkAsSyH7PNy8W9IIySr2oCy6bZmfnNJ2HUprhLRIbdBGgA9Ym9FWkaYIWRD9BpkGvB85vnWbR0/WeJ/48m9/hQ/8YItpFH6cGHUGa6C23FqccbkaePLgdS4fP6K9u0SmmlrfIjvHdjth7Qkvv/hBhiHx5qML2tkJtpmR9+bHR/Y23jlSzOQoSSFRWcXJ8pjLJxMpBbQOnJ5ZhLraN1rLbN51GzHLa1FYtmKzyKQ8Yz2dcf/pMVt3QpYVOQ2Mw4YYHFIImrrGO4dom2LvkjPHJ8d85EMfAsA7hxICoxVts8CYis1mg1QCrRVZQMyQkWV5Q2QyRTCnuF/YCZ6QwY1Tye4dezICHwJJgNbFENqakrphjSEGjxQKVVWkGJicJ+eEUiXxI6cS42eURGgJOTDraoyWdMaSSfhpACPpmrrMB6bE0XJBFhpT1+T9wkZIJX3EuR5lDO28JJaknIlxJPkBsiMLyeLklEoKgvNMfU+jKypjQIGbNoy+J6P2iz6JShl67xjHHdoosqxwQVMrzc0XmLzPmRb/FT/JAwcOfEc4CMADB97TPFsR2acmXA8Dpn2yhkj7apglh5bxqqORDV2tOR+fMISMbmqkNbRdizEVUkmMyaTgSN6hlMLFSBh73PoCsb3i/PwJdAtmt1+i04Zf/qX/Fx/8oT+Ac5mn99/g1t1bbENC1if49ZbH99/Aigh55LXXLjm6c0R7dMyLH6p58MYj5id3qbs5l+cXHJ/dYRg9T1eXmKpBKgtC4saAHx0KgRt3pDCSnKOyNW5YcXximR0LEGNp/eaEEAKRr2clJTlfW4oEEJbe3+KNp7d4dHmEzzNymghuxI8jIUzMZ13xF4wBNwWmaUBpzfvf9zJN07DbbdFK4fxEVVUIIcp1lGSxmLHZ7JDK3GQDT2NPZTVkgZAl+1cQsVYjkCilcd6z2WwRUmG0IuXMNA0gQNuK6ANVZcjJokRxPvA5UVmDVJIYI/NZW5ZAciTniFYKo0DkiJYZq0uFLU4ZXeqRPH/nNrvRE8aBqmlx40g7m6NSIHuPmwaatiOFCTfs0FqVWb3kceMWKSJBGGZNx7xuGLcbNruSfKKkpG6aEkPnRlwE7zLZOxoJxijGaaCmweiWTEOitPAFEbIphcBDAfDAge8KBwF44MB7mrKskW9Of+vvc87krCHPcH7GbqeYxsjTy3OqzmLnDdtpy3PP38LU+sa6REw99CsII6LuCDES3IBfX3D5xuucbz337nyIOx/8AcaLJ2Br2m7JaxcrFlUNUZCoaU9e5NEr3+TxgyfcPZ1T1zXt8ZKQFCFLlnfOyJVFyhYvMkkqLp6uCEkwOkfMgrxvRVttyd4jiaQwkPyE6yfmbYNWI7fvtdgukilZvOT8jEROZPQ+fq20SJNYcjWccdE/x8SckCZSHEmjJ6cS56Zj5mK7Ybfd4L3HKM3p2RkvvvgimbQ3ny5VqZLnOyGlQCnDNDnqyqK02aeklEUNbTQuBBAKZUp5UClZWqKirO4oKYovYU40dUsk46cRIQQ5RepuVub7jMH5iWkaqKoKYy0xlFSOyhqiV8XbL0WEFBA9yTuSlEgJrbV4P5IV+DLkSRgTs9YipMaPPSkF2rZB6wqdI267Jk4DdV2hrCKFEZk8OXmENmXj2lTMjxvqucM5V2YnwwRyb56dBNY0IBR+dGAUSgqcG9HakGRLEvX+vZ3e+a7+Xd7vBw4c+E5xEIAHDnyv8E6DY6H2pxPQkOISPy2RpmYKG3zacvb8He6+9Bxyfoy0kpAmRFKInMhux/bqnGFzyenzLzFrjwnREgkoqXj5I5/g+U9/BtsueOXrv0N7egrGMJsZ1sFRac3p6XMoaXjw8ALnIuPoeeGFl8sMmLSEZLn/4JK6rWnqlidPV3zla6/Sj4mPfOyTnM06TFXycB89POfp46fsdj3jbkWOPbeOjlgujlHS0S0kz708A/H0Zsv3rQPzTPabSJAcWVYMccmTzQlXwxJHibSrsmHyNZP3pBQY+h1jv4NcZvtCCLz0/PPMZh3BeULwZSGkrstChFIkEs456rrCGINzvogvwFYWQankkUqSR1Vp3DThYySlCQRUdbXPaBbUVZk57J2HFMkxEqYRCVSVQUlQx8fEGElk5vOWmIpw9FKglUJLWSp/ykAK5OAIOdHUFq0sUsA0bkuSiJZo6Vkuj3E+IqSlxNAljIqlDCciIozEBGSPus5RVgqlNUmWGcK6ntFIGPodu/UKN+3odxuc9yyWpzR1x04KxnGgqhRSVOSkCbklihkpW1QOwN5Q/L/B5/XAgQO/dw4C8MCB9zzXebnPJmmUn+KZpoCWEJZ4d0w3a+heOubs+AjV1Czv3MMuzwgigBSkpCAJpGlQdUe4OmfY7ujOzggpsNluMPMT7n7kU9j5CcN2zWuvv8781h1EVSF3Oy6HgUXTMDtacn75lPuP3+QTH3oZnQZEUMgEuqpZbydk1dJ2S9abAR/g5NZt5Hri6994leXREcuTOd2s4/j0FndvP8/m4oqH919ldfGAFDOBiO0id55v6G5lYhrQ2ZS0kuLQd2OQLXIGEchSEcSCq+mY1bTAUSF12WiNY0AoRV3XCD8RRKZta3Kq8MGjteG5e3chp5tFjLquySEQo0dphRASC/t2sNtXBAU+RKw1kKFpKrybGPoeFz2TDyWKTgqMNlRVxpgSnxZCQOSINRolBaoqGcPGGACcc3Rdd7NNXFcVIFBSYuu6pIMYhRLQGIsWEqvLfJ02Cik1kFGSUtXTmhxGDAGlQCpRKrEiEceeup1R1aU6F1MgZ4FSFq0kQWlClqQsycogtUVrzayZYesZ/faCnBPD03NWTx8Tl8eoqgWX2K7XzLolMSuSbkj5hCwWwKrY91y/ht+S6HLgwIHvNAcBeODA9wRvmUHffC7uB6ayUORsgSVS3MbUEmNAKoWoW3RTBv5FikgBMYFQFiUauuUpRkpGHwlI0JZsG+688AmaO+8v531P8CMvvu8D6GbGsHkDNVugmg6E4MmTR9x78R4vffiDPLr/CtvHG1pbUVWaymqqdsFuOyGkpmpqugQ+S3rn2ey2mMay6Qe2q1exquJ0fkQ3O4bomHZXdLOW5Yng1t2AtquS+pEVIstnZiKvj0wRK0ku2PrbPN2dMqQOZTQ5jkQkQmuSGIvfoZCkxuAcuOCYxpHT01Nm844Y3lq4yDExOYebBowpEWw5QwoBIcBaRYyJrq2RqnjzSVkSWyanGLc9KUPXtiglUUKQoi/t3pxww0BVWVTISKWZvCeEWEyir6PiUsRai1IKrTVaa8iJ+awjhJIUYusixmpdtm0ra/ZpMRkhwepiCG2NJefMdvWUbjanNhZlDNo2bPoRKUBJ0NbigsIHj5AaXVWoqioJNUIhjCUIyFkQsyLbDlV5mtnEbJrw4wCUmLumaonTBjdskHVFpsWHJZU6BjEC476QqziovwMH3n0OAvDAgfc0Eq5j4J4lX1+S99cxGH2EnN1F6EAcStpCe3KGbDvCFMm+R2uDQJLdwNBfwOSoqg7VdiQ9YzdBruZUZy/i7Jw0bcmu5+6tY+7ee5HV1Yb+8oLTuy8wX5ywvlxz/5vf5A/82B+kOr3N5W9/lfMna56/fYogY7qW3TjhXERpiDlwcmvOneef5/ld5OJqy9V6zcnpMVpbHrz2Jk8evIkVgqOZYTGfoQy088z8VkLqNSlOyDwrzzu7sgQjFDc5xFnj0hGX/SmX/RFRtGgtIEkylqgC6ISUEZU1Y043IksI6GYzAKapzPrlnHHOEVMs9VZtEEIRQkRLTV0rnHNImWmaipgyzgeELK1SpSWmspANdduWCldKODdCLq+tFNA0DcPoEFLtzaAFMQZ8jMWCJpVUjrbr0LrMckoBTV0Tg2dwE9WsQ6WMVGWxJEmBNpaqqZBCoqQkek+lDUopvNuRsyP4EaTAKknXzUgItLVkKYhCgq3RVYO0DQmJ1pqcIOaESLkIbGVL2oiqQFU0TYeWkixE8SCsZzTGstuuELQkZig6GjvDaAuiL+9tYfZv7kMr+MCBd5ODADxw4HuB62QEcV34k0XrEElCIIRF2hnSLPBxQ1Aj3eIIjGDarlA5Y+KOOATuv3rBb/z/fotvvvoVCBNdd8wnf/+P84M/+mPMj86ojcarhmGzxqYdJgZOjk/QtuHy/BG1sSxP7/D4yRXDdsfp8Qnz5QkpaZr5Lax5SEJytelR0tDUMyotcDGwWW+YNp4mCkIwxBSp2xlvPnjMc3fv8Okf/AG+9qUvEd3A8miGzgllAs+/tGQ+f4wPK4xuKGWnVKLgRN7PjWXIgSQ7pnDEejxiiDOSUMV4GYmUFikdtlKYaHDbgeAdQoDWmpQzdV0hyHjvUNoW4Zcy1lgqrZFaY6oacma33ZSkEylQ2jIMA0qXjWDvPTGUWLWoNTklnPfIXKprCFGWOZRAa71/DMXce7lcMDjHZrOmrZtSKYwJqy0hBFopMcZgjUHpYhwt+x2mblAZFJkcAxEw2pKFQexb123V7cWjpOmqInylJiJY73raboE2lpAz0+QJKKq6RZgWj8TakmYSUkCQyzwgkuAiKUakrqi6OZURxLFnGEfilFBK0dgKaksSmXH0NNbiZYOVtsz/ies14HyoAR448C5zEIAHDrynuZ7xg1IJjOV8siADSQ5EFkhxjBANwa+JuxVmCIybc87feIXt0wGdIqoN1Gfv55VHmv/06gWTS5zMW17dOb74S/+ENx98nf/d/+H/hD75GOvdimr6BqFfk8yc2YsfQ9hiIN09/zyjAL04plIVd5bH7IQhJElTC6p4jkqaxd0fxMwXhOEKYzz91tHMFjx8+JSQPLPFjJc/dBeXJe3jC1aPz2lPan7o0z/E1eYKnQP9xasY8ya3Tm8BVyjRkYMtJs8i7I9QmQWUOZFxJI65Ci/Ry3skZcnOo4TE5UCIDpUSMhn62LMaVvjRY7QhIZDGYruWwRffP3xZ4rB1jZSghCSmwDiNJXmj6TDGEIPbGzonjBEYpRmGgZQSOWViKAbVU4w0dUUik4QgiRIDV1UlD7j4Lke6RmGUQkaLzEXEDc6hrb3J6a1thfeBYfTYZk7TLjH7yl7OmaaqygazLjN7OSmyMci6RtQ1WYAIGSVV+RvKTGNQFiFKtFtlFSqDkJqUSzU0pKLRpLbl+AsJQmOMxItA30+QDClovAOBRqqA9yNWG5qmw6cEMRPSjLU7QuoFjdoh07B/XQ+G0AcOvNscBOCBA+9h8o09xlsfhoK8H5jPSDRQI1IFCcI40K8vkF7zta9+HWE0Jy98nGEccGGNae+CfMIf+JEXuf3cB4hiRnP8AX7j1/8DX/vqF/nIN77Khz/1B2hmczZPnmKTodENuumYwoTt5igJlcgIWSGQCO9w20tMN8dYzTZk7p3c5uz2bVyMbHeJy4sLZN1xvDxiNjul7yd8iqyvLln3DikNw7Dlt3/7De6cHjFbzjC2Ynk859btGcL0ICSSMsNWuE6OiAjkfimkJeSOcawYBoXzJZZNSUlVN9TW4ncXDNOWGDxKKU5OTpi8YzdM+GnEh0BIkRwDOWSELFU5NznU3lpFSklVV2iliTEyOA8ImqbZbwW70qY1hr7vEQ30Q4+UEGLaFy0FWlekVNrFRipiDIiciTGSBVhrIZXbTaLMdU5uYrvdYo0h54T3rvghSkXOgqqq8d4jlabtZuQQUaokiRhbYUxFzqCu28iIMktKqbulXFKmVdkOQUt1k9KRM3gfUFIXj0ClEFIW825R4umauoUgGaeeMSYUudxWjEi1n1cNGa0tKSdStmTq8noK8Uy+9YEDB95NDgLwwIH3MvvNyLLleh0DfD3rFslJocQMYoOfItN2IIwr/E6Qs+BDn/5hjt//MZJS+OjptxC+9s/58PuPGXnKyp/xhS98lSgj/8Mf+lFefeMVXvzkD9EulpDuEIctWVqquiE6QJdWpMwT297z4M1HzAwsKK3Mq80Wszjj7KUPYuua8fKSME24YaKZnTAODpRhtbrCxciqH7l1+0XaZkY+O+P+5oKvf/0rHB0veO7Oc9w7g5c+1KHso7K9Ii1CuZIDnG05LiLuW4eKLOZs+orLlWDyFdpUaBOxpiJG2K0uGMcJ2C9kiISKEe9LNfF6vi9ngdIGH4uQU0riXCL5Mo8ndRF+MUzEGAkxFSsWrW/av01TWrfGlJaw8iVzuKqqIiBtSwiOpqoQJHKK+OAhZ2IMNxNwMRaLlNoahJYImfFuxLmRummLMJYCZTXOB2JMVE1DTpmQEiEmGm2xTU0CRhdQ1hB9ApXRSkHehwkKhTEGqTT7dx4pQcoJqRTa7KuDZYwRKQUiC6SUZSQzZ0hif1sSYyxWCVIK7FZXaBTGVEQJUxL4rFC5JeaOTNl4fnbc4cCBA+8eBwF44MB7nus84H1lRACkfSXMklNDGAx97/Bjj0qJ3/nmNzg+vcNy3pH8QK5nmHqGe/AEYmRZK3brkV//zS/xi/+Pz/HZP/Pj3DudkcaJJ4/u89H3fxBpJdunAi0NQsqSO6tK+3LYbLlab1lvdsjWkjc7hqstu+3I7NYLnK8mRP8E329RGU5u3SLVBqkrXEi08xqTErpuuTh/yhde/yJh2LFoNHfObnN0PGexUDQLh+1GUtoiZQvI/Rrzdf6xQmRVjgeBMS252CoGZ5GmxdQGcHjnGYeAUpqmboh4Jj8xjY7sJ5TRzNSMy/WGcZpQWuPHid1uy2I+p2lnKDlj6AdiShi1j0kLpRppjME7R4xlU9fu27Naq/2mb4mGE1qDkISQ0AqMbdBKMvRbhMwYY4FEzGXLxxiNFpLtdo2tKmrdMJstmaaJaRwAaNqOyU3UqiyPOOeYzeeEeL0lDlkZhLFoqYgZpNT72T3BFDMCgRDXsXaaiCQW5UcikjIoBEIm6srsn48gpkzKsWw8Z/Yt74jIlKzfLIgp7WccM6N3SNWitEFmRXCJkFpC6khoFBGS3neAD0sgBw68mxwE4IED3wO8lYwgKb6AxZBXCIMfLUOfST5htGG9UyyXdzg+OuP8tTc4fdES3ITuZswWNSJ7VpdrugqOzJb/6099go8/t2BpFMN8zjSOkDPZ1mCrUtXyvkSCScNu8gyT4/LysiwLSMsuGhyCqDoyMLhMrQ3t4hjDhJt2BCOpmophvaVbzhjGifOLp7z66gP61YAhkYyinllqrZnPJ87ueoQsM2GCuPc9tPtjkIqhddalCig9w7Sg9zPQM6QxxJwgF4uUrmtRObGLO9wuI6Wk6zpysqSY6AdHThnvAt4FNtstKXi0VkghQCuquiHt/flCEGhtCc7tE0AiMRZBGMK1h1953bTWpZ2LoO8HaluhbVV89bwrLdZctoHTjatNJuVMZQ0plUUTAYzjgLXFxiXFYkNDisTgUAK8mxjHEVvVKFshNYzO00+epm0xxuJcoBIKW1V74VbqfVJo0AaldGlTk/fLMxJEiaAbpxGlFFIVoRZTxPnyvFOK5OQhOHIKkCmLL8JgbXkfTiEihUZriReSLDoiM2LWGLHPcn6b7+WBAwfeDQ4C8MCB9zAi7wXfzWehIO9nsXJZhGW7Gbl4vEJLaFvFo/MrTm+d0S2XvP7qfSrdoGYz4nykPrrDBz7xSb72H/8FH/7oEe+/26LuLblzdIpMhvXVBS+9eIJAIVEIFKSMzHkvcCbGaeLqasXFxQUvPP9+dN0yZcHTJ+d8/cvf4Pz1V+nXgeWi4fd9+sN84H3PcXw0Y/IDLuxQWrNeX/H4/CkXFxsW8znzalYMiK2gspLKeLr5lvnxQA4eKWsgInIANGQDwgEBUOSsyTJyNR6xHlqc0OQYy3au0vgQYd9izUjqrgO7FzBeYFtDTBu8Dzjn8SEWUZcSPnikG7G2RmtNQJS2bwg0dY3bb2XXdYP3jpyLuLx+vWazOdM04L0n54mmqTFGU7c1KQTwILWCnDHakmJEiEwmEEMo0W8xklJEkBinqSSEGEuIieAd2miMarC2Yhgnht0WgFoZqrpBGUuIGaEM2rbURpOBEDNVVWGNLVGAweNjRqjSAkeWqrOUZYM4xkCMgZTLGILWGolExetIQnCTx4eAzAmhJDmC9748flG+xKQYSCSEbEDUZLpi/yL2W92H/u+BA+86BwF44MB7mXztAwilHiMoJh+ASKQQyo8LmBrOH97HhZ6z5+8Q4sTZvSWSnlrWDGPP5uIRL33yB2gXLa9/9dc5PuqYd8ekZPjCl7/BydlLmKQIV2tEdlgf0UqSYiIGj1Ca3eaCi4tz5vMjjm8/R5SGz//qv+df/st/yTBFXnj+OVSdeO2N1/nGN77CD3zyw/yhP/KHWM40KQekFWilee7uXRoz5/Ji4PGDR2yuzlncOyHlHVpL7t4BrS4R0SByEQeZSPnflgYCCL8/Rh0+aNb9LaI6JUSN2tvDuCGU6poUpFzSUEIsFi6VkRjbQUxMkyupHv1AChGFJKPwbkIqibYVWUpQEq0kQpT2phBlKSSEBFkgldgLHW6SPK5nDGezGSEE8n7OT2lB1VREL8tCiffEkHCTR5l9MoYQCCnIKTFN481MYfAOqQ1uGrGV5fLpE2azObP5gpAzKfgyJ5oTxlZlgVwohFZIZWialpQSMQYCGdvU6FTjnMOHhAsTOYPWhrrW+xaxKUsmMeBDIvuI1uVYpBxx3qG1AqNZX1yiUqmETv0WTSKT9wsqEu8DWUmQLZNX5Nocln8PHPguchCABw6813lbO6zYwkghSfvZKpnBCMHm8pIvffE/8sEP/yC73vN0dUmlem4tYbM7Ry9PWG83uBS59b6Pc/bcB3n9lS9xef4GJkV+8If+NygMr736VVrp6I4XqJCQVYubJoJ3hGnH9uoJUmRefN8HWJze5Z/90j/n//3//Md88gfex8uf/hF++A/+BL/6r/8nxMV9to8e8eWvfp2kZ/yxP/Ax2m6ByJlGSTa7EZETu9UT3nz9a4iccKFhvVlx+3ZDXTdIpn06hARUsQgRnhw1Ag0qktOEz0estkvOrxou+0jVJVT2JJ+RWZJT2VKtKk0MhpAlVduhVcQPjn67Kx5+UpJypu8HSJG2qUkxM40jVdvdbMs670kxUlcVWhtiCHvRVyqOJUFE3ZhIKyVpmobtbktMe2NnEtY2pBD2reAiEq2piCGipCQEdyMYrbWknEviyKzDO0/0gaqpid6jlGS3WeGnkW62JEuJG3b7DGOoZw3jFJBCIqViu91RNbYI4hARIpRKnywbv1oV0SeEKLN9Od+clkqXlJGcCH7Cu4mcAiF4ggCZIlobtpdrSB4tAiE4qtoSUyAkgbESlwI+RbwyZRs4q2fGHQ4cOPBuchCABw68l9nHeF0vfhQdmMi5OEILkdFCIDI8fvSY7a6nXt6iXdwjqI7t6pugDTJrps2Go1nNOJzTPzZUx/d48cMf4+X33ePh175Ef3XOm6++xtXTJ9xZJkRYUM+PQcOwW5MIiOjRfmQ5a3jxhRf48isP+I3/5df42Eun/MEf/iirSvL3/2//d+gf8cc+epcXly+x3iVCMjx98oTaWKyuETFhgdjvaAzcvr0ghsTkJlQdWB5rpLqugAXA8JbtS4lQI5clgyQFk++42txhN0rqrqVqFCkNeB+RVChZRFnKYKsKeXQMsWGzekzOAikUUkrk3i5lNwws5zMymclNVKrCTRMxe6yxZbGDUvkTgpvZvzKbF29sYHLON0I9hEBKxRLFGA2ytJKFlKXwJYrdizVFVIa4YxwGxjxBShhjSzKID2UjV8Nmsyn3KSNIUEIQpomeNXVdE6cRN+yIw0gnoKnbUkcWZZkj7a1ZjCpzjtfWNQhBSrls9QLPzuPFEAkhElOpsIocIcZizL230JEkJCXdxI8J32+pjSqTnDmRk0D4hK4UPkliNqRc7V9nDgsgBw58FzgIwAMH3tNcbwDL4gkoMiInhCjebNebmFebHevdyPs/9jGaW0ua0yVeCu6/5rh8/BrPnd2jrVu0cDQExss3CG6gmc+p3JrK77j/6tcYV1d88PlTZsYxhRXjIPDOc/HkHGs1VmmU83gf+Mpv/Ud+68uvE4Yd7//oXW7NLcM08J8//xt85gefZ1bB3cUps/lTPvjJTyHTm7zx4E1eeOEuxhpqramNpKngIx98ASlrpimwmPfcvScRbCBrsvDFGy4Xw2eIIBNESU6apFs245zzzZII9P0V/SjpugaRJcEnsqqoZxVVY/AhAZJp58hJQfZUVY21FqklUQgm54gZdpsNishs3pWNX1n88Yp5c4U2ZUHDOUcKxYvPeV9SQGLcC0SB90W4NXVDiAHvI9aqsl27L3ZVtsIohZISaw2VnDEMw164ZkKO+BAQQiKlAVWqdDkljLK4ydG2LXVXMY6O6EaUrSA4YsqMW4nRJfHDjT1V3RQz57T3AUwQvCvxdUrv/SaLyFVSFvOhlG6qmyRw3pGjL4JPJHJwBDdBTkQ3QQpUViOdJEwTWSSyMCAUMZVZR5QkJkWIFcJWe4sfDkXAAwfeZQ4C8MCB9zT7JJCs9hFZgWsfwBgSSMHleuTheUbPjrj78h1UY/BpS1XDvbvP89Xf+o9cihXL52esHl2SdSZYiw4ZlSYYV+wuz/HTyPPP3cPKzBtvPqA7u0MlPSFvCf2G0Gec0vTbDa8/esL5+efJ1REfeOE51tsrhJAc15L/8x//BA2eW7MaKRVV1/DDv/+H0eNz/IfP/c/85y9+mbPTY1544X0oAUYlrIa6a1gsaypzgam2ID0gyTebz9ezkIpMQshEzhXen/L4subRRuKVK/YpuiW7EhWntUYbTd207MYd/TggokBKTdcdMfhzcipVRWMNMSYuVlcIKTGkIgpjQumSu9s0DTEUkTdNE26a8N7vk0AiUpR2rVLqZhZQKYMQmhh9yQhOicpWWGvIKWKUpNKa6MNehAmUtDRVg/MTMSbcFNj1A03TIYRkHB3GFDuaGK63jwNCNFTW4MaBikwYDcpYkh/ZXD6mmx+jsmTcrbF12ZZWsmyUpxj2c3x6/5jLnGPYR+3lnPCTQ2qFUhprBDGDH0eyTGiRQGaUlKArri42DNOWmRGEnBjGnmw7rO7ICaYQQGdyEnivoapKpZl00H8HDrzLHATggQPvdXJZ/HjmAgCE0mRpEVXLyb173LrzAWwXmdaZXl7x9PFjpque06MjUu65//BrGG1ZnN3h7Owe0hrCdsv64pLzp5fcvvciZ8dnvPbN3yEJxa3mBKs7wjgxk5LLzRVbn9hsd/htz9Wbr/H+jyz4wIc+zuuPvsnDJytmM8vHTlsWRjHXilcen/NDv//38+IHX4TdjP/t2W2+9Fuf59c/96tcXfXcOj2itop2VoEsG85KCZSJCOn3z1QXwUdEIMhJI/YLIEJ0bDcdlyuLwyBUpFEtOSgmH+lmLU07wyfBarVjCD22MmgtUVGx3fX7amrJ7LXGsJm2bIaRum548c4ZcRrY7XbF9iSXjF3vPbvdrrwO++1XIQRt06BUMUa+nv8DaJqOGCKDiwgpUMqUNj4SYxRaiLJdm64FfiSETNd1qKnM5eUMQk2EWNqvGRC5+O+F4EFJ/N4H0E0T1V6ERle2ht04kpXBh0BdtUip2KVM3bRkbckhgJQIJC4mMhNqb24N3CyMWF22gUMMGFUqqMGP+GmHUQrnJnKOVNYiSfTjDjF4lLAkVaxthLYoDFlD0gYVK4SoSVmXVJd9LsmBAwfePQ4C8MCB9zJZcC0Iih1MqYtkAkhFjJYoGtqTM+a374AYaf3AK1/+Kl/+7S8xjZ6XXnyO45M5Tibq+Zzu5IR61jA5jyMhZ0ue++DHkCExDlvquqU7OqFtj4k+kJzHZIHbjlxudmzHiboyfODll1BEKhH4H//YT3J5+Qg37bg9E1idGP3ERz79MV7+6A+yO7+PJhNiRjUzorY8fPKUHDNNk1kcL8FUTA50pdE6kvFl/yNfGz8LclYg9ibYomaKR7z2ULHZGrTORczl0qZtZwtMVTH6iIuJmDJ11ZQFjJhwweNiKlm+JJSxSL0XeSmRYkRpQ3SubKzGxDT2CHGdmkFJ0UiJKQWUUnSzGcE7pnEqooxMXVVAxgdHzqlY7EhJVVVUlSWniFSS6CJiP4+320439izaaOq6IqVSAd1ud2w261IhE4IQA2H0KFNmDmdNw7DdEo2hqS3BT3RtQ8wRZMaPO5L31LbGywEtIyJXhFhi86QsG8lCa5zP7IJHKU1lbfHy8w4lFNF7tmNflnCmETcOyKZFZM/Ybwkj1NZij5b0mxXO+bLpHCLDbkvdNIgEWhXbHCE7cmoQ8pJyhOU7/2s4cODAd5CDADxw4L1MlsX+RPiiOK4FoSh2KCEY1uuACwPHIaBVZlw/ZrveYLs5y3tz2tNbZFtxdHTCnbtnNI0hjj1aS2antwjOMa0vGc8f4IcNQoK1LbvNgIiB6CKPHz5lczXQDxO9Hzg6nmMrTcqKZWu5d3aLFz/yUYZhJAdPzh5jIEwTm8dvMG13rDdrpli2f2Xdcrk+pxs8ISTmfWB+aqmNoFsolPJl1hG1f66Q0ZSU2pKdO8WOVx/Aaw8FUWhkHkG0hBxAO3I05GQYfVlMWMzmaCWJIZTZyZixTYv0kck7XMpoYzHa4Hxkt92y3fW01lLphhgj280KqRXGNnTdDFJgvVqhlaZqa0Io833DMJKJHM3nVJXlarNBCDBGkVIqVT8t8d5hjUFrjRsGrDWkEGi7OYJEygljDWpvOxNiLDOH3mG1IUuJNprLqyvqylJVlt1mQ2Ut2+2atinis9+sUVVFcANV3WGU2Js1e8Y4kZsZTbskC4H3juAnkhDYukFLQYwOkiS4hPOR7AbC0BN8j1SecdgRRo/fbbFWI0Vg3PWEQVHXDSiLUAmVMkZKdtExjgkZJVlZpAqkXEOuKWMOcBCABw68uxwE4IED72W+xRdtfyYLhFBoLCpI4m4kbXfkKvNovUPMl3zsQx/j+Q98EF019MPIYj6n0oqLN7/J7vIpbW0xpipxY9ZSzZds1gPLoxOWt18g70aS9CjT0S8m3niyYdU7xpRR48i8aVFS08wqdrsrTA7EEHFDz7Bdk1JkGnqGbU90AZciQwhEaZAottuBTbNB6Jp+CjTR03aBoyOP1m7fBZR765Vr8VsqoSl1bDYLHj1SKL0gRk0MgvV2RT2bcbw4wlQN/TDhfaCu6xvxpyTEmGmbmpFEv/P040Ai7/NuDSZExnFkGAZO5jOMlgQ/YYzBGM007sgpY7XBmrJA4r1HKcWUJ4TMVLZGSsl2uyWEgNYGpdTecDkRYxF8Uqkyd2d0ea65bM+O4w4pJNPoylJIVZOSwNqa7Xa7r6aF/RxgJuaI1orJj+QYWcy7/czeiFSCaxfFMWVSVTObLdBZMvnI1PcINHXVYeQ+ri4l3DBSdy1GWcJUUlEimRQ93o3s1k+RckLKDDGSkwTVYCqDqDv8FOl3HqEyUluS9+QY0FWNrioyiRRTiY1TkixEWUqRh/bvgQPvNgcBeODAexnB3vxZvHUBxZ4jh4QSDTNrefjqOV9b7zi5NWNxfIuXbt+ju3UHh2bnI9XiFD3ryHFifnbG0fGMsNuwW62pq4qqO+Hh1ZaLXeDJ4wesnybuLU8xOUNdUasF0wBkQ/IOfCJXpWV88fQx0hqEtvhpopIS7xz9sGNyjvVqw8X5BdrWjHFCmIYYBKZusF0NRjGOieAG7PGOtl0BfZn3E6kkniBLXi0eAO9nPHxcc7We0UeJTxMkSTfvOD49I0vJbtuTkNR1TdPUXC/PuMmXapxW+GkkI0gJmmaG8566bggxM8bxxuplt93RdTWzecuw64mx+OLJXMyRvfNkrpc/BE3bQs5st1sgY43FVqWNK1zAeY+tKrquA0o2b1M3xdx5vzWspGIci+jU2hJCpJvN6TLM50u8m+h3G+qm5vbt23g/UTUVy/kt1lcXNE1DCI4YMm6AmbG07QykxMVIv11T1y2V0biQGHc7cgStLUiJrWqsquhHR10XH0PnJlKOxWA6ely/IYQNkkhtapq6w8iEJDPvFnhTjkFKiSwFUinEteWMkYQIQlcIXaLmytKMQtyYnx84cODd4iAADxx4z/Ot+5BCCLJUiFzRtTMkW9aXD1jM75G5xW7XE8yKpGqiVLSzMlifc8SFiWl1gQgjmUDfDyRhOb51jxQ1n///fp7L1zdU75O0SrGbnvDKk4dMY2S73YH0HM3OWMxbRjsxbXfsLp9yfHrG1dUFa+9uvPT6ybHe9kilGfqJ7bDCtplhFJxfXHB6WlPZhmnw4AdmTY8xK0hTiXuT8eYYFFEQyVjWveX+o8x2rNCNxShR8mYXc1arFUpbbN2hpcJoRfAeYxQSGNxE1zRopZnNZ1y5AVNVZb5PKbpuRt8PTONIv9ux2W4JbqTrSkrGOAxls1gZUoq4MRFjRBtDCKUKGEIguAklBdZW+JgI+wWNlKHrOoSS+BBZLuZIIYjBkRzkDMYaUhDUtURrzTSOWGOJISKlous6grV0bU3dWG7dOmYcR6ZpRBvD8dEJTV0Tvbsxt5ZAmEakraiNASEZpwGURiiLMpKYAtGDNoZhGpDWYCuND1NJcRECkSPeO8Z+y7DbIfJIDo52oVE5UGmJtmXzum1amqZmcjvGYWQcNhgFUilSKjObGU1MiZgiUmZEkvulnwMHDrybHATggQPvca7XQG4sAUUJhUNowiTQdsZzLzzPenVBN+8IUiKlIE4OYSV101FbS3ae6Cd0FghjEQKCUMSk2Q0DOQdmyyU//kf+MNOTnte+8DXi5Hj90QN+/Stfpj5tObt3zAc+8DInxwvq2jJbwOXqinEYyDkipeD8asVuu2NxcszJrdts3UMePX6C94K2q2m6JUKLsnyRE4vZEWHrcP0lRg7ktC7PWoj9/J/Yi4FyOqaGJ1eCi62g6pYIlen7NUrW7C4CUlnapkWIRIq+bA0LIEHwnqYy1HVVbldIpLZIbfAhIqVG67L52tR1EYH9FiVhu92iRlWWIYwpub0pMe5Nn+uqwgW33/4dIaV927b45kmlSqs4REKKWK2wlb3JdVbaIOSIyBKldcn69Z6cE13XMY0jSirmsxk5J5q5RUpIwZUMX+d4+PAxxmg2V1cs5zNqWyFyZj6bQ5bMlu1NNrKUxbg6AEjQWiKVJuUSPYcUjEOPkIK6rnCTKzJcZPzUs7q84OLJU2atwijYbXusMqh5Oc4+bWlbidESa2cslkeMQ0eKMCZDIKNsRVQWqcqiT0oemVK5/4MCPHDgXeUgAA8ceE/zrCPutSdgJguJ0A27SbIdIQrDG4+f8sWvf4OTlz/K2fMvoJuJ+fIYbSwX5084Oz6GVObfcoTgMghLtW/thejpxx2zZsEoPd98+rBUzk47/vf/l/8jZlFxdGvBvDMM6y2r1SWL2YyTumK1WvP4/JLtrmfdT8Qs+fJXv8F2OzBbHDPrjrHLOUpIzp9ckVEsj5b4KSKzQaQtii1dLdEyQzLka9WbzT4eLAEV/bTg66/2bIcGzMhq9QRjNF1XYZTAWM007KjqFqUtYRqo65rgRrz3LJdLJufQ1hJSycmVg6JqWnKfkEIyn80JztPvtsSTJVppxmmkU11J+EiJcRyRWSByJsa49wUsxs3WGIIPhP2Mnq0t4+jwocStNU2DVqWiNwmP1RqlBN1sTtzHzA1DT/CeqrJ0TYvVirZt6fse7x0xKp4+PSf4ifV6Rd+PGG3pdz1SKN58+BgjFeTEyfFJyfG9uKSpW5pZi7E1qkkIJRndli1ruvmSqp4VQSo1lcrE6PH9hBCSYZzYDj2P33iTx6/dR7iJWh1xfvUUUuRB9Yjjk3NsW5OlQsnyEWObjtnxCafLOe18hoyaSKafHEoZmlZSSYHAgVRvJeAcOHDgXeMgAA8ceE+z9/x72yVlGi5GwdhnhjGRheKl932A28NEVIb140cM8SG3X3iBYbfl9OQWoevYrtao6FBZ4kIkExmHgWnYYK1k6Acud1dsLx2jzjz/0vN89NMfRXWWjRvop56LzQQxYuqmOPNJTTtf4mImSMMbFytunZ3x6R/+UR4/Ouf119+gszXHd05RyTIMmQcP7zO5ga45wk2Rtsncvl1Rd4kUKZ57KQEKkSXgISWy7HjzkebhEwmmZug3LLo5UikmN6KhZOuaGrRFiNJCHfsNzgeOjo+YpgmpND4EmqbDTxPaWHRwKGuY+gGjDY2t8GOPDwFrNQnouhlaKbbbDVZppDFAQuSM92OxhtGavnd47+gWS3LObDcbxmmiaWd0XUdMmcENCCFuMoNDSEyhpGqsV2uMkDRVjRKwXl+xvrpks1kTgsdYi9YKN01crS5pmgYprzeMDTkXf7/KGrq6YZomRE7EENnutgzTRNt2GDeyOFpyMp+x6wdW508Q6gqtK5quLYkeydO1LVJKGg3BGuZtw6USrHY7rqxms+3xbgSRudpsabuO2WJOVVUIIZhiIghJDBMnJxL0HJ9Lo1ekEmEnGcmpRxIRh+rfgQPvOgcBeODAe5i8l36inOH6jCBDTOQEUiraTtO2mtE6HnzzFR6dP4W65Xgxo1YaJQT9NFI1LckJXD8ipSozbZsdInhW6x3jGNj1mTfeuGRIkY9+6uMYm7i8eEiUghAi4zghQ6BrG46Wx6SYePj4CQ8fPWV55y5nL77M17/xCg+erjg7vc3x3bsIKRn7Dcv2Nm3TMLmeRMa5jAues+PM2T2LkhuENMUvT13n/eaS+iE1u7Him68HUjrCDZ55J3HjSMyCrERJoACUyaToSnbuPrf2+PSE6B0uBNpugRSSmBNKGbQ2CKlIsXgA5hiL9QowDAN1XRUzZR8gC4yx9LsdnYC2bRnHAYkgpsh6t8V7z/HxMdPkip+gUsxnc4SU9LseISVV3ZbcXcA5x3w2wwvYbta0TUNtLME5nPPE4JFSMJ/P8MHh3ESMmbqpOFEnOOdo6pYYIzFGqrpCSoFWCmUNeEfdNHjnAEHbdSgl8OPI9jITnUMZw3LeMU6BzXrFZnVJ19RIBW67oWkbqqqm0hVWK7QSJCLOO7rFHDdpgiv3o43F2hotJTGVhZmcMz4EJh/RSpJF2ucgZ4xMKDHsrXyu3/GHCuCBA+8mBwF44MB7GkmJQ0slNzWDyJS4rOyQBCQTOY54P7K+6tleXVIpiaktbhgQJyVY68GTC2xVIcNEhSC5yOpihUowbnuuLi9JSM6vJsYoqZZHvHL/NRobgEA9m1NpS708prOG4D2vv/EmUkjO7tyDek6yFTOfkPUjXnvwkK9+/Zs0dct83nF6pBmOJo6OTnnuubvcf/MhzgdcWHN0JlmeAMKDNKTgEBkkEpQiZwip5uGTzJsPPTk3WAPDsMPIGqkNUiTIicporJa4aWR0npgyi+UxIkXWmxVV25WDeL1fLcTe/FgiZNn6FUqhtUJKwTSN5aXYb+fmLCAnuvkMKTLj1OODJ+WS1qKVpmm6vUjsqa3d325pYitVNmzrpsF7T86Z5WJBSqXytTxaknxg2GwxWlFVFt1VzGYN41DuK+fEtI+gOzk5Yb1el7lFXTNNDqs1pIgxGkTG1hahJChJbauSY6w183pesn0FWCURWlHVLW074/z8nNVqxWzWkFJks1mzWB6hugXr1Qo3jTSNpe3KhnXdGKZ+R9u2CGmQQherHFthm5q8t/MJISESyNqikkOKjFEBnQYQI8XwWxyqgAcOvMscBOCBA98TPFP+A4QEpQVaZsK4ZXSl6uSc4Pb7XubJxSVThq5t6Xc9r752n9svfIBmvqStFKuH93ny+D5X5+dcXV7R91tycOSsMPWCj3/6U5A9b7z6FZ47W9DYhr6fSDoijSfGiq6bcXrvLtM48ejqiude+gCvPzlnN07cvnOPF+6+wBuvvc4b9+9zeXXFuJ5QuWa5nDNfLDjzsL64QJkdz71wC11tyMlDFCWtQ2RyiAgVSFEwhTlvPpYkWgSS6AesVTS2ZnAeRSb4shAxTo6UBChJW3dolbm4eII2FUpkcvT7jV2L1hJjNLYqSRcyJmRKpOCK116M5H2KyThOWAsxBOazE3a7K3L0GKVRAnxMzLsZznnGcWKxXJJSJEWPcxOgaLrZvk3ck1JisViQs6Dve6QE7yas1hyfHENOuGliu1vDPl6tvP4CZSybzQap9Y2djLWmiGBrUbIkleSc91YypiyXVBUhBZK7rswlWlEhaksWmRQjSUjmR8cYqxnHvgjRpmXd9+ik8N5jK82sXdJ1LWVnI9HLhK1rUi6V2CwFQhWbndrWdF1T2te2QhqBG3ZI5SFOiLxBMAINhwrggQPvPgcBeODAe5i3/NCeFYCSnEoRqzI1TVNhbEYpTVdbLvstp3dOMbrmzfuvs3OJj376R4jTSF3fYXQ9OzfRh0DVttzpGqyWNEZhhEaaFmEqnp6vqGrLN1+9z8nxCd18hjKK5XKBsg1XmxWJTF3VVLrm0cUFylY0TcfQj1Ta8KlPfpL3vfQSr3zzFbaX52yHLS5OKKWZtwumzSVd45nPPYIeoTI57qtz+XoTNCHUkqvLjgePRianQUxIFclZ8/TqEmMqlFS46Mh5S8qCumlLWgaRFDxagNUSUi6t1RBYLCwxlYOZUkIKUVrOotRetZJMPhBiJCdASLQ2aKPJwG63Q4mEF9DULWRB8CUrWFf25nWc+gGpFUqV9I9x8kipqZumzP/FshxCLpFyWQh2/Q4pBWPfM44jbV0jlUEZbpZJ2q4rvjFSUtcVgozWiqauqXWZBUyAMZayVpExujyuGGKxjVES72C3g2qmaOdLEprLqxVTSNiqwQdHiBFjGzKymGUbQ1MZjNZUVhP8yHzWgtTF208UH0epwNqKpmn3s44RhdhvQzuMqoh+C6IHFcr292EF+MCBd52DADxw4D3N9TZk5rodDCDQkBUxCnJSKGWpq47kNU12+NHx5itfZ3O55uTsOd782m/zwdmC1dNH7KYd3az+/7P3J7GypftVL/r76jlnFGutvXfunZmnso1NcQALya/h8/R0pYcAC1kICTdoYTdoIUMDSwhZokEhCtFBNIxbFqJjIYFEh0KmkIAnsIUfwpLB93Ix2D5F7tzFqiJiFl/9Gt9cK/Mc27z7nsg850CM1MpVxY6IGStizbHG/z/G4OmLp+ysRZIhL7haSbOnUiki0j1/ytP9wH+JiZevbrgIhefvPW0KWxJcPnnGuEy8fvuW3e6KKjWzD9iuY7/fk6aFXArKGD73Hd/JaX9JqROznwCHMYahU3z2sxs6l6AutKq3tvf3QGxq8cRiefkqcncvSVmgdUEpweIXkBapJLXI1pYHTe2SipwTolaCEK0rtyT8MlKWGW271pQRI6UUUkzU0nYAhRA4a+n7jiLamFgIges6jHWkFDiejggE/dCTwkIuCaNbHZxzHW7oWq1aSlRg6HtKhWkOIBTStl+/tdaP3S6klPDes+0czvX0T54Q5h5qu19aN+PNaTy28a41xBTarl0pGOMQlZUUy9aqq1R7LAUsiwfAOUtvt+ToCdEzLTNqDoSk6LeXbLd7Tqcj1zfXaKObMUcWnj6/wskKYYIcEbVSc0YKwWa7JaSM6RxFSkKcKSWDEHjv0RqEzE3fE42sWisRNSFlWzWotTTjz5kDnnHGJ4ozATzjjG9h1GqoIrWWhOrWCJhMzluU/E7mpWOePYXA7BXPX3wn/WS5vn3L/ukFZnfBaanUlDBE/uO//dc8efqU7sULOrkhFRBKI40iK0nOR4iRsBxbtp1WfPaz76KN5s3dLd20Ybi8ZJxHjtOMcj0XTz/Lh6/fUOqEVprxeERXRZGaX/u1r9APTaWc4onsM9oqFj9jZOT9dzXf/V0DQr+mqgJVIoRcBc8C2ZP1hpfXPb/6VUOpG0oeQQuiVyg9oG3B6ILMPVIlqoRK5nC653J/SU4BHzwXl1fMkwelyKWy6XuIMyWOaAk6Z6yQZGVINaO6Dj33bJWh5Ip1ligKNY6Imikp020GtLNUodeg5kShuYvH8QC1riHUHaDxy0xOGddb/DKiFeQUcM4ChRg8SkBndYun0ZppHKk50TmLVIIQSusQdpbxdGLoO4SQiAqdMc0IUytSNyURIVHGUoUg5YLUIEXbc5yjZ5mPiJwxWlHjzOnt1/DHe4bdJZebDU4qpmmiAnlZSH5uit7+CcsyUSlUJZE1I61jcBIhFTFnOrNByNpiXeSA21/hnEB3hZQ7ok9YfWAw/xUlDyC2iKI4j3/POOOTx5kAnnHGtzTKRw7gmkHUNdpkRxgly9hq2breYYYN8zwydB0v3nuPq3efk4Xj1dt7njx5wevXr/nKr/xnrj8cePnlS955/oLn77+L6S1uM6AEZBeZ5gWlFNpaxnlGO8uTd99B7wZ8TLx8+5bt7oKYKnevb9heFC6u3uGXf/m/cv32Ld/9Xd/FeLyn5Mx7n/kMX/nKlzHWIYTmq1/7Kr/6ax/w3nvvsusjT7+zY7fNSBHXxEPxaNCoRECSywW/9hXP4biOXn0i5UJKkk5tiTGRY2LXb3CbgXGa8N7TDwOl5sdcPr/M5FyggnEdSgrevnlDTInOOZQQWG3wKlBLJZWMMJqaEyUXOtcB4GNA5oiSipQlKjbVTUpJqontdss4jdzf39F3PVII+r7HGEsIkSfbHSFFwJBzwiiJX2akFHTWcTodEAKOpxOnU6W3Fq0kpRZSyMzzjI+BznUordCqkU8lmjtZKkEtBan1R4+paiqxMqB0C9SWCKR2KNNcwpJCDIFUMoufGGdPzIVp8i16xhkury6RApZ5IeTMdren5jVg3FiUXo0w2qC0oVQoNT1UOjestc4hJCQCLQJGnoBArRJ5Jn9nnPGp4EwAzzjjWxhCJKitxg3C2g28oaYN0yEjoqJXGi0sUkheX78BAfsne56884xUJb/lyTv03ZZ5OfA93/15lmnh1auX3N+94vbuQ569+x7f9Vu+hywqi48cF8+mc4Rl4fZ4ajVixmKHgfFwzzzPFLPj8uoph9c3fO3tr/C7fuf3sttd8fbNDf/xP/4Sn//ce5SSub8/cHn1jNNp5jh6jHXkMBPnkW4Pz591dHZBitRGuLRYkCojpQakvODm7cCXf+Weaa5UJnIJlJiR0lJLpBSJlJVcZnIUhDXXz2jNPE0MfYe1hpRL49G1MGxbNt79/T1a61ZxJngkTFprcoZh2DCmVoFmTMsOnMaJy+2AVoplnuldRy0wzhP73Y5aIIZE54amzElJKZVpGtls2s7fMo1IqfA54+cZpRX73Y4YA1JKlGp7nn3XiKkSFecsSslGzpcFqDhrWy2d1h/17UoNEuRKxhAKZRxSGSoCreo60pZARiJAaEoKFFlbK4ixlFjIMX/kchYOYxUxeuZlQgixRrxA128wWiJEG2UrrVfXdCQuiUKl7yMljQRvkHaLXyK6TkgOyDKCCKDqY+vNeQJ8xhmfLM4E8IwzvqVRm3RSABFab2rumA6G033BTxNhiijbowsIJdC2R7meJRWEMuy2e+ZxZL/pEe+/y3Q64YxqmWxh4iu/8t9IIfHee+9RcqZKTVaGJc5EIQgpk+NMyIWYBdr1eAxme4G0A+PbW776tZc8uXzCxf6S6xD43/+P/50v/o7fju0cv/xffpUnT56RcmWeJ3abgedPLnj3medyHxBqoYUpG1rIYdsFK0KyhIFf+ZXK6bhFKEsuga5zxDAhRSWniHN72u5YIIQ2/hyGAWM0tdpWzRY92jiCn3H9hgq8efsWhHgkT1pIQvRIJVBaUWtBCrMSJSiltno3Y3C27fdtd3tCiPhl4fnzdxAITocDdo1ameeZnDPLMrPdbkgpMc9zUwtTJKUEgJJuzegDKRpx67tWOReWBde3ncllmYkxIpVgnlvwtFiPgTWUWyiFlBKpNUJKkIpcJci2x2eVQQhBqZVSMkoaqljIpVJkuz9xzXv0ISKVRBToNx1CwZvXrwgh4LqOQsVoBVpR6rorqQRCysfsPyEUShqkiOQ0gdpRMSid6KrHqSNajkhSM47URlDPOOOMTxZnAnjGGd/CqChAIcggFNSOGPaMx56aOigHYjghjaGIyma7Y3f5HNs7lpTIVXN/OFFSbIaCZ5q03/P06orD8cSrN284fvia//M//UdOdzd0my3KaOYYiClyGidqqcwhkovA2A6tB96OnudFcJoWTseJXz79Mt/1Hd9FSq0SrdTCz/+/f57/5//2e7m9OfHz/+7f87t+12/lc595D43gar/h+TuCy6ceISYoCjAIUYC0BuZd8Ora8pWvFnLd4qMH4alVI7HUnNnsHZt+x93tW7IKSNWx319gTIs8qbVyPNzRdT3Wdkgp2W42bYzqPVdXV4305kJVohFB0/6dUoqcM0Iqak6kGLHO4rQmrS5cISTez1xcXqFkG+lutluM1njvKaUSY2sSeSB/m9W5O8/To2u36xxKy2ZGyRmnHQDLPCOFYFnaGLaUjPceYxtBLaXiQyTnphBqYxr5UwqpdAu3Fs1Yo63D2B6tNSFl4rJQSgIkpULMLermwbQihKCWZsZxxrHb7AihjctLyYzjSD9sEEISUsVZ0/qES6ZAi5MpGSElSlusllSjQFkWn0l+pN+esOIaxWkd/a+j4vMU+IwzPnGcCeAZZ3xLQ7dZmIBaO2p5SpqvcPIZSlWSPLLZWLp9R3e1Z/fsPZTdczceSVmw2W0IMeF9ghixqrb4jZTIOXN1eYXVhjdvr3nz4QeMi0c6i1CaUuCrX/sa1nUgNNfX9zx/9z36YcsoOi4uL3l7/ZbxdODmzTUXux3LtND3Pbe3r1kWz7/+f/1r/h//9/+NFAJf++BX+OJv/QLvvfMuxR8YNgvWPricLSChehr765mmK772UjH7DpSBPFFrJkWNlg5rKtt+QMmKMRK1ds/2fU8sTX06nU6EEFBrnt+m68klE7xn0w8oKRG5kGrF++aAplZCCBhjKKWgtCHVRuSMNijbauoeCOJ+v8c5x7IsdF2HMQo/N6VOKdWyBWVrFBmGAWssMfqWPWg0Rmm6zhFyJoSANoacA2EKDMNA33UIUcm5/cyEWImqbsekjcFah1SrU5eKUBqhNUJqpFBo7RDKkBCEkEk5k0qLrFHkdcRtHmOHlnkhxkyOCT97nr3zDn03cH17S8px3aWslFJJpZJKYWs7JJWUAlTRrlNrjDCgLOM0oapqe4PS0OeFQb1F1lfUemoj+NJWAD7Wf3PGGWd8QjgTwDPO+BZGrWvtGxrqE8L4FH/c4E+R6e5AmEeUEqS0sIz3KNOBWQipUNe8NykE/aZHREWOC1VKtHPYmAgpYYzi6cWezWbg5nDgtAS89yxLQNRKCgmpBB++fEkulVol3Tvvcbi7ZRlHqIX7+xs+fPk1NpsN0xx58e5n+JX/9l8JIfBLv/Qf+Z7v+R72e8d4etty6voLrDshVDu2ytqpKwJUSc57vvY1zZe/UghFUkVEyIKoGqUtSlqMrsQQmbOnlEQpYJ3Dx/xRemKt9P0AgFpVsWVeWlvHdmiRI7KwpMCyLEjTVLxaKznXVkcsBFobUkqExWOUQhtLCAsxBMxeM88zlEqpmXFaSCHiVqVMa8U4nhiGAaUUi1/YDANKCrSUSCGIMTCeThhjSTGSckbRKuIA+q5D649q47z3TemTzQQCEoREGoOUHx8Ba0pVCGXIVZJypdSKQCK1QRcDuVJyi8Pxy8w4jngf2i5jzJQ1Fuc0Ttzd3fH06oKaA4l1/KwMubRcv1giskpyrS2sXCpSbjmLxm2oZssSgHpkI24Z9DVG3SNEbAp3Acgfc4ycccYZnxTOBPCMM76FIUQFCiU5lmngdDMQF0OJEYpfT/6QY0bngMwLuWYEisENrSpOtF2vXJtJwHSOGirDxRYbEqJkrJTY1JSclA90rqOzgaHvSaXgbN/21YTmNE4YWTFKoKTAKEXvNMfDDRcXW27vTljnuLh8yv3tW+4Pd/zKr/4y3/Gd38PrMvHBy9d84b0rnHXrCd8gqqKKCGSq2HB3GPi1r1amMKCsQeKRUa1hybDMI8FDSpp+44BCTm1fUWqF0m0Xbr+/IKdIyZkUI3EJ5ALD1iFqU5pyaW0b3nucFJQiAdHGvLq5oWtK+DlgZHPX5loIMbEZNqtxBKQSjOOJkhLOWkppRFJrzTAMlFKYpondbreOhiNI2erm5gmjJDknaEmIaNUCnV3XtX3CaWQcx2asSI1gdq6nrG0eznWr+UJSRdv5E9IipaaK9tgZ2o6dFBB8ACmouel+uVZyAWMtSmlqgVpbfuJuvyPkRBUwjyeE1Ks6uCCEakaXYdOM6lIwL0uLszEaqQzSaFAdVW9bkDYjG3WHkW8RHFtMTDUIRPuD5+FBPeOMMz4xnAngGWd8SyNBUaS4ZTxuyOUZru+Y0ytmf6JTQzM1qEJNgfvbD4kY+t0TOvMMqQWCQhESpAEMSgti6AnBM58mhu2O2nWo2eNzbOqSsXTOEFNm9h6tFN/x+fcIMTP7LfRXaCnZDxvUpmc+3dH3A/vdFh8TIUSePn3GPJ3QVnM6Hfng5Ye8+/xd3nz1NdfXB95/LyEw7RhJCNn2HEu54OWN5TAZrNsxzweWZcEoB7mS8oyxCpCIdXTZDBWFlBK9a/tz2+2WmhMfvnxJbx3LNFGFxvUDVitCjEjZen2NMYQYqbkgWllIMzWsal+qtDFyzU0p1AqEQK77gDlFus6uzti2p+ecoes7UoztJ5lyI1fGUnNqxKwWlnlGiLoaQgTaWMZx5vLFc7quJ+XMNE3knJnmhZIj1tpHc0ouBYFGaUOuLeNPKYtQhoKiSNXUNeSqbBZyLZTSche1sWjV1EhrLJXcaFguLH6h1NYlTJZt/J0ypRYkAmdafV4uTXMVCGJKLce79RWinSNR8aFlQJrqceqevb3FiJum+n4s5PxM/s4449PBmQCecca3Mmqh1gvCvKHkK7IYUFqjh57+Yk84BVSpjWgUT1hGzHDFfruh04rFe0StDF2HEJaCIKSI1BpVCl0/0FmHn2dCqWy3W0puMR5x7dTtnGHyHlUK241lGAzu4jkba7nYbRh6R5hHEAVnFE8u9tzeHlACLnY7Xr/6gBcvnvPVX/sy++ELvPvue4w3bzjczcQgcLqCbuaPysDbW8uXP6wkuQcpW+0ZgpLa46FVpdaWo2etRWuFMZph6KkrIbNWIYVgDgG/LFilGwFzls0wkHMm+AVjNAJwxuKVJ8SAEJJcQRuHFJJCRSqFsgZ/mtDaczFcoZQmpgy1PW5aa+bpROfcYxfvPI5M08QwbFtOnjH4ELHWoK1lOt4jS0UpATmjtUaUwtXF/tHha4zheDwxzxNKKg73d7x48ZycM8fTyLDZUAXUaUZ3HU5rqmxvUluktMSVHJeSoRaUqFDz6rqVKGkwg8Z0Dr9M5BSIMRNSpO97qihM80itCSEktRS2mwGzqpNCKUopre1DCpzroVZirhTvibVStcFRMGJka2/p1E0zf1CorLuLwLkH+IwzPh2cCeAZZ3wLo9aOMDr8aYMzT0B37J5ekUOHRBDMgW23xTjDNIO1mqIdFMF8GokVhqHHSoH3AZ8yPmeEhK7rKMripxk3wFAyWsnHLtxcHKUcUEqiteJYTghRiSmyXevPZM1oKruhJ8bA4faWYbvl7volNV/ROcN4GnmZX3G52/K1r/w3vveL/zdKtyHFiZJb5LOQhVoEtez56svCV98kbK+QZDrnSChyaONUpTsOhwPOGYSqhLigtKIfBqqSLevOKKbxRFgWLnY7amnRIlI2cjHPIylFlJI4a5FSYrQmxgBUxNq1/LCL1vQtiVCyhSMvnk3fIwUoKRmGgePxQPCefrdDScX9/Q3LsrDbbimIdnvGUip4HzBKYq1Di4qfjigpmilFVFJYQLZYF6U0Xdfh/YJQku12h1gz9oRUlNqOqVSQyoDU5CoQQiO1I1cBSrYxdRbUHNv91ppQMzUVSs6EkhC1tJE3EI4jIUS0anEy8zyTYsJ0A4tvj521ht1uy+ID1zc3HI9Heme4vLjAWkvXd9SaIIRmuhGREt5i+7cYbtbIn1XNfag9FPLxET/jjDM+OZwJ4BlnfEtjz3zfEccetVV0W412A1JaUPcIcU/JI9O9YFpmXO/QnaHUgsgZrQQ1eg7jkfvjRBKa/ZMrur5HCUnOES/BGov3CiEMtbQ+21oraeiZ5qURpIsLUowswG4YuLm5RQmQFKyWWNnz5u0blCjMp1uW6Z5n77zg3ecv+OpXvsaLnaXEyN3tG9598j6l3FAqoKASqUIzz443ryshD2ghMbKQUyYGjwS0ajttQkiMNVTyWhnsKDXjtCHXSgqBSuvzddsNdze3jfQoiQ8eqWTLw5PNANH24sSaPyeoFKyzFCDEpnoprUlS4EOgnCb6fmAzDK0ZwwemaUKLZsAIoZk03nn6lPF04n4eubi8xLmOEJvTd7PpWWphOtyto2iJkoJxmhBSMuwvmgFcwBJCi4IslW7oWZaFmBLDxlEBYwxS6aahSYnWDqktRah2/6VByEZqc46klJEiY7RGKkVOAr9Eck5YIdFas9lsUVJiTFNanbVoqUip5fXllFuH8DhyfXvLOM2ra1pTgFQKsVSm8UROCeM8Kc0I8yH24g4pxvU5rmiqX2oh4KLtYIqzCnjGGZ8ozgTwjDM+NTyc0MTXfa3Wj39tzUJbP8+T4e5NIM2eEO95/8ULlHVUerruArG8YTneEpbCdnPBxdUTgttgup6MZF4WToc7xmlEKsvz979Av9+RykfuTmM0UrKevBXbTc80TYSYUUqx2+4IIQKV4APbYcPgOr42nUjRM2bP9evXbf9rmems4HOfecF/+eVfZuoG3n/vO7i/vqfTsN31pDAhlUQaRyoTVQhqjQjRcXubuLkBbbdIJamxMk0LsiRcZwhxpkZJ121QWiFEQaCYl4mQCld6dehGj9KWWjKlaEqpj3tqMQW22x25ZoIP5JzJpSCFQKtmMqm1ZeClmsk5Y61ZrRnNme19YJ4X9psNAIv3dF2PEjDNE5TaRqdrDqAxhmHYoLXGx4Rz/aPDeLPdcvv2Q3aboQU/a43rOpTS7C8u2vNDKeZ5pnMdpSbSSiIf9iCVtitJtUhlEGp139ZCFW08W0tZ6+JaUwhrVA6AtRZr1NrcMRFCayTZDC2zMCyeMHmkUCilUaZF4CzHI+PsySuJdp1lu9uhlKIU8CExza3f2I8T2gSUOaHlBGVp3I+H7udKFZV6Jn9nnPGp4EwAzzjjU8PDWGttvCDTznySx72nJmcBgpLh7r9u8Xce2SdUV/HTCREzCo3rDTk+RQqJMSc6XZmXmXGRmMkTw4JPkVgEbn/JO+9/Dt1vWpQLitkHrLWkrFEIQhbshz1SCqYi6YaKz4Hp7p7eWO7vTyjbg1QQ71FlxjqFLAUrEsF7yrKQjGJnBp71F+TTyHL/lt/5Wz9POLzknd37bC8v8OEDho2klg2iXiNF4jBe8H/8yhXXS4/aSrTKTMcJZEVpyxJiIy8lozWEZXkch1ol2xgzRmznMFqv6lWPlIaLp5bFe3zydLZns78g5cr9+BojC1Cw1lIrzMuMMoqQIpGC1pZSCkZqpBlQLKQws5zuOWrFxeUV/bADUfB+xscZ26RRptnTDTu2wwYhFfM0IXLm9s1rXNdxcbWnpsRTbQjzifvxQKkZIxJIePX6Ncdx4r333idTuTke2G33qOGSEgNZCbpuwLiOLDRLEpSVBAvlQEpqiuS0IGpaDR4FWQpSgNCOXOpjNuJ4OlLSgqIQlxFqbs9QqbG9g3XfMqbcshCLpKxVc0539EOHdT1QEDHhpxmjO5TqyFPmyf4DPnf5FTp9JJfmTBZkRBVQdXMDi3xeATzjjE8BZwJ4xhmfGr5e+fvGr9aH2rcqqGjmyfPq1TXHU8VGSdUHkjDYfk8/7HGdo99dMsUFf5qYxpG7+w/Rl1cMnUMrRddZdv3A9uoCrSXRe0LKKGNBaKowGCNIMWLcgLXt5L3dbAhhpu86pnKLoAX7lpQYhg3hdGK8vVsJWWFwDisF0QcO93dcPXlKoVApHMZ7thc73OaCiydP6Lqe0+lAibkFOyeQes+bN5nrmwkh225d9M2QMQwDyzihlV57e9uvrb53SCnX3b6WiVdzxs++EbZOo7V6DE0epCAe22g254wUzSgiJVjbtQ5h2RQubS0nH6mlIteQaas10Qdqao/D6XBAlIq1jm4YkMqiZEApgzaKlCvKdjjryKJlEo7jSMkZgGcvnrc2DWepAk7jjF8Cu/2GYbtnPB2wpuMLn/ssru85HC2HwwElFRmJMRpjOnKBEAu60y1iRWuotEBmJKUklBTk2LL+Yk0oAVZrrJE4a6g1U2uiLwPzlEnLiJAKgWzu51Kw1uB6RU4e23XEmFlConcbtOuRqrWTGNdBTZy8h1qwzgESoz3DJjEMbdyrpADKGvzc/iCqX/cH0RlnnPFJ4kwAzzjjU8XHHY7re/GxMbCAmgUCR1wKpzGi5ICsEpErRrZl/hADVUpyiOh+z6AMy2nknf1TXCdaI0P0SCK6RmqY8CfBac4M+yvub48o29P1jlw1NcOwuQAB0zgiRMUo2ZQiIAXPpu8IWWCk5PrDDxFhxukNp/EINUPJSAkxRZSWGKsQUpFLZNj09E+vqFqRU0FWTfQjhQK6x8cNr99qjrOmkpvjV7aR6zRN9F1HiREBjGPL0jPGEEKg1sowbNd+3UKRrcosxoQQCwiFUhWlZKs2y6URXqvY9AMxTjhroRRqrpjcdgxFbYqsoIVpa90aN8iBYjQheMZp5PbmLfv6hO1+j1QG120oORJCoO8HfCpIJZmXEWXar1xjDXd3d2jTCOft4cRpmug7h+s3LD6iFWy3Pdaq1ZzSwqzHaWIYdnRd32rrhKLKtfVjdePmEgihxbXklDFaIGsjWxLxWM9WaoXSlOhUCj60QOySErthYFkmTqcjxnQMmw7rHKUYpJAcxxlZwPZdUwC7AR8XUIoSE6UUSsmYClpVhmHi4jJibaSWuO5b/nqpT5xzYM4441PBmQCeccanBvmxjytfRwTXHSikQggNtScsBSU6UoDD7Vturw+8yJWnn3GYYYt2lm7oUSJTc2T/XBLmiTq/JSwz3geEBIOkCE0cPXZzyTKOSDT73Y6YC94npHHsrzYUP3N/e00IJ3qnSMFjVKXEiPcLdtiilUDkgBUVkqdGTy6Rw+HAEls/bd87vuM7PodzjWTs9z2Xzz5DmK453N3TSQcpMU2eS7a8vh64vm8jy1ISqkDwmdPpgNUWvyzNJ6oUSilqrY8RKd43clTXuBspFSEGgl8QQjAMu/VhboQuxYgolVoKm80GP+WP8gRjxlmHXy9DXSn7envKaFTUOGsQtZBS5u7uhlgyUutWH4fEuAGtLCFGQCAVbPoBqAQBiMq8TDzdPOU4jihlefrsOUoK5tlje8PltmezGYi5cH1zy+s3rwFB3w0MvUMJQfABoWxrysuVWjLWdUihoCZKLVQlm2NbCaRozSNKaYzr0bblIUa/AKCMRmrdRtkp0m+2bPeXCCRVCHIpaGUaRVOtUcZ0AylDVRotOoSCMI8tK1AJailIldnuJ3b7E3BEUNadyo8RQAGCsvZfn3HGGZ80zgTwjDM+NTwoHg9xF+unSJBtrChFRmCJAeYRQsioqrna7ZFaU5eFNI+orkcPPUVUtLVoMxB9pNSKkk/p+4TbXNLGaoKCxtieWApLmLh6+gJqZp5msjRshgtkLYR5QhtN9AWZK+TAdugIs6fmTE4LfgLnFLtNq5qLVpAybAfHIA2+wDtPWwSMVhJtDIdpQhnJ06dX3PqIPy3UkqkYxmng1z6Au2NHKJmUTzi7wfsWeBwXj6gFEJRauby8fCRkw7DhgVj3fY9AUHIztyjZTB0CSDkhlUJLSYqpmVCkxBmHrLGFO6/kEgE+xuakXjtta60UBEiNVgahW2WcEC3rblkWjscTxjqsMVijkUaTSsUYS281tWZub2+w1jRDR9dxf39P5xzGGpR03Fy/bqReWZTWXN/eoUyH63ts3zEeT5gcmacJ6xLWOYwz9M6hu56iTAvErpmSH1pkElZrhKhIUZsTOCXG8YRemuqcc6bWQtd1XGwHQrhiPB6bCWi3Y5o9PkSk1CjbnNIOia4CZV1TG5FU2cbfBYn3gU7LZjwRkd1uwto7almQ8mEPtqz7f6q9LkTl6/9QOuOMMz4pnAngGWd8qmgnvW+ccLUqMQmyQgEpDJv+CU+e9ZxuT4zHI6fTEdlbMIonzrHdX6CkIadETolKxXY9qttRU6CmhRw9tRasdfjURp+XVxcUMn45MY4ju2fvoZ3DH45M87RWkDlk8aQYKMFDqVir8bHw9u1rnLN0m3UHTxacucA4R66SN7cH/HRElo7t1UVTAUvheH9NNQKrNaFEgo/kfMmHbypffRk5LZU5eIQoaKVI4qPGCqs0MXi6zq0xMBWlFEJInHMtsiYl1Op4FaJVkknV3kQVCNFI4uF0IsaI1BYQVAFxrW9TRpNDIef1OoBaC6nSyLUxkC2yWFKKrUu4ZHJOnE5HlElsN60eTkuBkppa4XQ4cDoeuLy6JJWEFK1qLsdEpw1Sa8bTESEkF7s9MXrGcaEbdvS7C07TxDx7+s2GoR+QgNEKoyVa0XYpY6AikUpDrW3PUYLWEkml5IiQAqP1GgeTmOaFXDJGNwfweGp5hMPQsdvtUUoTUkIoDSLjup6+a60pGoVEo22HrhmpLcsysd/2bDZb7t6+IoTExg30XWW7CUhxpJG+ti/YXgeyEcCHkfDZAHLGGZ8KzgTwjDM+VdSPvRMfffx48mujYak0m82e+mJHDInxeI+QFVkyaTkRT/f4wxbbb9DOgKjEFJCmI9uBWBLGDCAUgkISEukkF9sLYi6EmJl8Yrvfs9k2whJzQGkFVVKjXLP2NLEkrLIsMWC1xnhDLo1IWmvh6SXkREqJbnvBdr/jcJy4uX6LkSAvJPvdnjqNXL96hcoFp8HYjnnp+dVX99wdNbF4EJnNZoMQmpSXRuKkJOfWMgGV/W7HsixcXl6te3+spg65BkL3nMbTo7KVS0YpiVSG3jjC2lhhbE/K8XGcmWtFakWN4rHDl9qIGlKDEAilGgksDlcKKkpKXfAhUeqE7QSjEKSo6fsOZzS1Vu6ub9huG3Hz84w2hugDUtDeZFMsO2eJwdN3ln7oiLmNdt+8ecvt3T2f/cxn2AzbRvhLbnmNIlCqxOoWaI2U5JjWKJamfJYccdaue6EVaiHHQI6BUgvTMiOoLPNEDIGvfXXk8uqSz3/+Cy1YOgas7TCuexSthZQoZVC2Q+aA0pacT9TawrGVlJAzOQW6LmH0RC0TEgNVfMNL4uFzsRpCzizwjDM+aZwJ4BlnfNMgvu5dQ2mOzFKY58gSPbazbC+25DRzONzyq/9lwvvI0PWomvCn5p50zqK1ZhyPQCbmQsmRKgQo0Nowzh6hND5mlGkqonMdp3Gm5Ai08WmVgsFt2V5cEt2C1hrtE6lUus0OP5/o+x6jDUZLSJHTeFoJBjx7eomSleNpAm3oSsEqwdZ1zIcjQQRklrx9U3nzWlCqIxWPsZIUCyHNxJjIJVBTxOkWRqykJISAMZacM2Vt+ABBKc1DWkpFab1yjNr20ITCdh2u6/Ap4mMmpojUCrEaPEqtzfmq2/jWQiO2GUpdu26lQhiLqI5SMqXkdeycySUiVaDkghcAGSk3a6jygJKK0/FErQVlRBvda9XiapRgETBNI0pWcpzxy8jV0+fc396x3W557733CDFyfxzZbDa4rkNIwbDZgtTU9ZhzjOS0dg2XQkqt+q2khAL8PCKFIHrf1g6kJKVECJ7sA/v9jidPn3I6jcw+oLWjSoWxFq0tOUWUdmhRyGuLR1NlBU5rxsOBw81rYohoUQhhQsmIEgtCZESxUAVCfuyJL8rHEjAf4pLORpAzzvgkcSaAZ5zxTYFgTePlQfkTQlFpgbolF8bTxOmQMVIz9D3edZRNjzIaEWbefvUruN2OfrfFdIYkAsshkopr8SdUYowgFbrr8ak0olAqOVUuLvYgDDUn4nTAKEiiorRizm0/z/U7SpGtmcIpgg+UUtn2mmVpMR8xZEr0SGRz1xpHreBcx+ITubSwj+sPPyQGqKliO0Uumvv7irVPKAiyH0khgOoQUpJXhcvI1kxhtCSn2MbWuw3LsuBchzGGnDMxBkoppBTRVpFz67+NMWE7R6kQUqIiURqUlsQQEXIljLk20iglru8ouVCioNRIru3norRCSkspAalWt/BaMedjYLyekEpjrW0uaCFQSqFSa7kopaCUIsc2/o2yjbLdxQ7XWVLyHO/vMFLy9NkTDnd3IDWXV5dM88w0LQzbPca6VTqEmFfVuNRGmCtoJVFKkBNEvyC0JNYEJRH9gpKt9URQyamphWm9rwjJs6fvgFCEVJAajHFobZpSLTXKWKyGhKIiqTVRc6Gzlvu3b7l+8xpZE91mQKqCIDTyVx+aViqs+4iPe7Hi42HoZ/J3xhmfNM4E8Iwzvin4+Mnu4e2j/LMK5FQJs2ez37B5MkDNiOvEPI28/eAD3ry65vnnPs9nus8TiYwHj9KGfrNHWNMI0ZpFF6KnCI0bdsSS2HYDVir8skBciKdb+s6Rl5Gud/TWUkuhVoEybm3CgBgSUhRkqWjREtxSyuRUcK6nzokYIsZYrDG89/77XN+PvHr9FlcK0+jbXpqRpCVTTCWURJIVrQWiapRQLH4hpbBGtxRKzaiVIEgpKKUgpWzkanUFl1IotUXQCCFRinUM2lpAcghNrzKKHJtxAwTD0MwjyEpKjYgYawmL/+gnkgu1trYQqRRVqpVANZOIlpJIa+gocSFGjVSCu8MBaw2DgN1203p+UyP4Wkj2+z2bTQvndp2jHwbiPCFE5YOvfZVnz9/l6p0XKCl49uwpr97ckEplYzdYZ6gUcknUCiVGlrC0+28cqlUAkyks04Q1CkpuQc6xEVLbDyzzQq2ZUgX9dos2hozADRtSbtHRWmkQLWantYEYlDEYodv4O58I0SNLYDzcUcKCkK16r+8MUozIh10/agt7flD6BED6uuf/GWec8cnjTADPOOObgm8kgOLxa0JIahVY2zNsTRs5Go3dbrHLqe1tpcq8LHzwa19mnE5cPrnk4mLPdt+R55GUNSVnnLWMx7sWumE6WtGWQilJPN1RqmL0I2W6JyVHGk9UtcNIwTxNa4VYbWaPUikxoZTk/vaGEBO227Ld7rhbPHlue2AfvnzJbr9nu7vAGcd2gNdvbjgd74k+oaWkZElVGrO1+FypVjNOC0Z1ZDwxTQwbR06ZmmmjUiGpJbd9OaXQujlrS2kfG2MQUuGsAWrrGS4Vv3hyVbgHc4a21Co43R/Y7z+qLatCIFXGGEciQJ1RUmCUJpdGmNSq9hX5kVNVtLkz1Mpm6DiMI7f3d0x+xrmBy6snDL3GJw+1UnOhxMTV5SXSaO4OR7b7puJqrbm4uOTm7Ru6rmOz3WCMpgqBtZbnL97lNAZiruQloc26b6da8HRKnpxbF3KxFucsvTOMaWkmkAoojdSGnDLaOXqpmOeJUDKdNGx2F6RSUcaRayalitaVSmlRPDVjEBjrEMoQ0kQtmbhM5PnIfLqnN/rRRKNU2xVsu39rxIvIa/KRbtEvYjWE1DZSPu8AnnHGJ48zATzjjG86yvqmEFVShYICfb+h7HuqNPQXOzZP9mgjuM6JEg8kUZinmfH6jkFbxgj5FDCXG1KQDH1PjQmiZ+gHfJgQWiJRLLcLwmzwRRCmA6omxmOlSoEf2ybWfDqx2e3QShIXj5aCFJem3KXIPM2gLCFntHHc3d1htOFyfwkIcki8unvF4eSZx7bTp41iMwxsuo6QEz57jNVkXTHGkT2UGqkyrs0aFlHWPb7cHMEPjl+5kjApNV3XrZ24LZ6l5IQxlpQrVts1X1FSymrugOZkdh0ChbEaUmZaWnbgw+0084hcU+taP3CVUEqm1rpGxJTmxI4B0w84ZziMlVJri3fRhnEeyUnjnAMqKWcWH5lev0UaiRt6TtOEcQ6nFEZJthcbtO1ItTTzjXV0ynH1tCeEjF8WtIIUF3KIbbxdS2vYKIngEyUtDM7hjKSk1s2SckYog7QPvcQOmSPaOWKpmK4jxATSIDRQBVIZSs4YowhLIMaMzBWpJTkl5nEijnfIOFFjxA0OZVQj5cgW+1INoJrTXbTnOw+ZfyKufSBiNYj8eqf8GWec8T8WZwJ4xhmfFh6cj48ntl+v/j3sBuaskHLD7ulTTvPMXCrGaORmz+bpcxAKrU/oyeOXhZsPXrMMG3aXl9ia2V1s8cITYmR/edl26uaFmgKNaArmacHnTGc1oiZO4wktBafp0HbiUiVNAuc65tOJU5hZplZldnH5FNUHFp+4fnvDbrfj/v6ew909l/tL/OKJKRHLuieWEkYbBAljBE/feYfDOJGXGRTMKaOVYUxzi2vpOkRu6lGuEb9ElBDrTp0mxbgqSxK9GjlyLihdmaYJrRW5JoRQSL2O1WvFGYMQkhwzWltCSMS8sNluaf3L7X4ao/FSPf5YpIJcMiUHahGUlKlldcJKiRAVIUHKwmYzwKpSOmspccZIuLjYt2q9cURU8L41iTx95x1i8OQ482S/I+XMbrfFWIuPqQUjdxVrOhIGlGGz32PszDKfGnHSiho9Na4GmZoQtRJjZowzxmi0MUjRxtet30Xic0akjJIaZ5vDV2qDKIJcQAiFMRJjLSkmUn2IzYmIELDakULAn+5I0z2WiBIFKWpTbY2iCMi1kMko8Q3Pd7G+Lqo8E74zzviUcSaAZ5zxqeHjZ7jMR4G34vGtshZW0FPqHqTFbVRrXTCG/plB2A5pLca+Rl3foE+REBeil4xHQQwjpkby0IFxKNNxGkdKFdTaTvwSSfZHcpqRds/iF2RNEAMhtA7ZzfaK8eYNh1TJJTMvE9YZ+s5ihz1juCeGheu3b1mmifubW7QUjPd3HA8nlDYU2cwFruuxxiJrZHAG21vm+xPzUomnBdkZUk1gSjOdFIPRmhACQjSHsxLNrdpy/pr6Zkzr+/U+IpWBdRfQ2i2pClAa7TpSboaDmjI+zO2yQjL7QCVSSodUCiMhp0AVAtM5YmwtIQ+NGTnHtstWWmOLVAltzEpGoeTIxdUVz55ctp3FWlFSsNlsMUo1I4hRGByn00iOEVESqhZETczjESVgmhOkAAWU0oi8paaKco6IJJaKdB2WSiqRFOcWXJ1b+4uqBSkFwghyzgihm0taVMzazZurIJfI8bSw7wyUSjdsyFVRpSCGFtattW2OXanwS8Zq3b6fMjJm4jRRp3tsHCk5oJVAa4XVhio1kURMnkKgioKoGoHmI+VbIqpa3b8ZxLkJ5IwzPg2cCeAZZ3xq+Hj92wPE139fgEBijCYJmOYTd/f3SCW5uHrCZtiyfWZZnGXqbQv1VTfIcaEWT/GRFCWHOiGt5ur5+0y31yyLR7uenApIyTR75lBQuqMUTcmSod+xTCeQcDpNuI1gnCM5NaMBQNdt2GwHwjRx9/o1SkqO19cc374lhkCVCq0UVksKFaObEialQEiNMy3wdxxHpnFmHCemaWR3tQWtkQhQilQS05KY5pGLfev5zSl/jOBplBZUMjF6/BLYbC0I0fpqBXR9T0iJvu85HkdSDMTQGj62W0cpbfdNqhaK/NAuQi1IqTBaU8pHP7k8J6L3GG2oNbc6MyHXQOo2Nr64uOD5O8/puh6jNcs8U3PGWkcuCacVVisOd/etLi17wjISlh5EQUmJtoYQEjUvlFywtlXhxXpsXgndoSwo0eJnpFCQK2FeqDkTqse5FlOjdWvmUNoilWEJCY1Aa0dJbfw7LQshlaYKSt3q+HJp4/RY205hLoSYkNpgrHmMxQl+Yjq2PwQokVwzUrZ+42aSAS0lWj2oqfUb3n6z18kZZ5zxSeNMAM8441PFw8ntozHY41dqodYEuXK8PXD/5jVTKITg6fqeOE1k7ZCmQ/Z73DPJ3va4i6fkaSROIzksyBRJOeDnmcPblxzubpG25+LqipAiMRSmJVGFYPtkz3w6Uaugcz3ee2SFcbnHjQvH04iUks5ZlDT4xXN3f0ecAofbOwC21lBKxamm0Ckp2F62ZpAkJJHmRK7SYVVhPh2o48Q8Txzv7zHGsOk3RAE5JJacmVJsgcVkhBQsi0esO3dth68QYwDRdvqM1SglQUEqmZICxBZpEkOglkyGlnGYWx9wDIGSMkZp/Lw8un9bDM+qNFKbwzYlJLXtH8ZIigFRMpqC1ArrLK4kNv0GZzuc61BCYre6kR9a1l+OC34u9Fa1xozBQk2MpwO2cwxPnjIMG1LKTNOBqhopTTlSwkQuhZBPWNvTDwOyNsNHCLHdx1ogQ4ypdRvn2ggxEmc7iswsPjGYFjnUdR0yV0qYQQq0NY3koUAVspAs0RNOJ4S09L2hStEq5aTALwvTeMAvE0pnhGRVRFuItpaWztEc3khElR+9DoT4GNf7WCTSmQCeccangjMBPOOMTw3lYx8/EMCHE1/ruhUosjDMk2caJ9xmxzKPFO9RpRCnmUOeKFJihw3dexfs3gWdIuF4SzjdI+LUFDsJPrSKLut6tG4ETomKyhMlZ44vb7ifIt3uCSeRmE4HtHU4a0ixGT8OhzuC0ThjCCkyLzOqVEpcEEKyGQaGzZ4QIyG1CJgqFW7YYPqeKUZM3xOS5Hj9imme2emeFBMhRpxzKAQIQW8sqMKYI1Touh6EIJeC0RpKwRhDCDO1JJSWjx22UoLUGiFF28MTGqUtfmnuW1ELzvZkmckprQqYBVpFnpQSYWxz6tZCzZmyhk2XnCm5Rclk0cbEWgCiImUjjiYlpnlmniYEgu12ixaKWjJ954jLzHg80hlFbw2LlgipCTkhKHTGMQwbjHYMvWO335FzZlkWqpCNeFGhRLwviJrZ9D0lBsI8PWrJLQRbrDmFilwFCkXMUKp6LJ3R2lJKpRt6xhQRyqJd14KwaxstK+uoITD7yLAdQCqKVFgNJQWW04EwnYhhpmpN1w/0wxZnO3IuGK1wRqBlRdSV9P2mTR8f34U944wzPmmcCeAZZ3xaeByBfcNJ7tEckkFoapQgHciW6WeM4eVXvsLrlx/y/MVnGK6eorc73PaCfnfZaGRKiM0FLi4oEtTWKCKlWseEghIDffDUUlD6hvl0wE8z1S/MMTFdf8gSPMZ1oDTTvDCPEzonclgYa0EohRbg+h5jDV03gNTsLy/xMRFyIddKLoL+4hJhLHutyAjqEhlnT4il0V0pG7EzBi0VArCyMoe121gKSq547xG10WNr3ermLWTR3LhNdYzUKsk5ts5epTDGNfeukuS8unaloNSWT2KtRWnF6XSglIo0hpwiOUTqWtHW4l1A0ghkiZkqBLkmlFSknKEUpNJN9VtDoEsuLPOElgKrDSF4aklYraEmcvD0ncN2jiokUmu6YUspMC8ehKHfbVElk5GknClUtBRse0MugmU+QQos84kUPEoKKhKhNUoZUhU451hCwmi3EkDQxiKlbs+NmhFKILVB1gpSU1BUWVqNoJRo19OZDtcPaOcQCKpILPPE8f4WP4+t91hrXNfjhgEl5BpKXdb4nDX3T3yc5H2j2vfxr3/88zPOOOOTgPz/fpFvPfzkT/4k3/u938t+v2e/3/OlL32Jf/JP/snj95dl4Ud/9Ed5+vQp2+2WH/qhH+LVq1dfdx1f/vKX+cEf/EGGYeD58+f8mT/zZ1rn5xlnfGL4xhPbWi8mWjNCrRWqJEWJsTvcsCVLw+7qHZ4+f4HSips3H3C6ecWgYXCOEBNjyARpKG5L7vfUi8/g+3com3cR+3dRV+8jL16wmC3u+WeRl8+4/Px38OQL38WTL/wWLp89ZdACkTz7oSfOM8vxxHI4kuYZKwS7oWO/3fDkyRWf/+znefaZ93nxhe/g8t132T9/jtlfcPn+ZxievsPV+5+lu3pKdT1ud0lRlq98+Ib/8l//G7P3dP3QiJMAqeTjIyIBkTI5BLSSWLuaD+paDxcS1jnmeSHGRIiJlPJjLEytlZgiRmlSbDExcQn0zmK1Xh3AkFNq+2lKkEsm50RKsbWIxEhKkRwTNWeMVmgpEBWs0Y1A5kgthZwz3ntCTChpGPotxljmeaGUhNaSoevIKbLMI50zdIPDB4/tO56+8w67/SUXV1coY5mD5/50JFNR1jTCJhSmGzCub8HXElKY6YzCSMEyjUzjiZQ8CIF2PVVplO1AWapy7WNtkca2Lt/SSOCDoxokcs0GrFKjtUWbbm10ka0ycHeB7TqUsQilCDEwno6cDnfkGOj7jmG7odu06BqkXH+mFVETQkRELfx6la9+w+vinAF4xhmfFr4tFcDPfvaz/LW/9tf4nu/5Hmqt/J2/83f4w3/4D/Mf/sN/4Hf+zt/Jn/7Tf5p/9I/+EX/v7/09Li4u+JN/8k/yR/7IH+Hf/Jt/A7SC+B/8wR/k3Xff5d/+23/Ly5cv+eEf/mGMMfyVv/JXvslHd8b/vPjGyJePHAZCPOxEaUrtqKJje/GEareoTvHs3XexSnC4eYuThbsPvwpU+qsXIA2lFJzVSKvIQWB03/LgREVQuTvdo/s9QRvYdohSwAxcvGPodpfcffAVnA8412OnhVplI1gxtSaL7dB2wzqHsg53cUVMCb/2Ay8+sn/2nDrO3N3f8+Kzn+N4HJmWwDh7rt/e8OqDDzAULoaOd15s8TEQoqfKQowRoxXbvmcMHmM7Ys6Pzt+cEn3XcTqNbddNaWpNLIvHmA7ZWZQ24CMP1XrLNLfImJTQuu0DhhCQSiIk1ALjPEFtkSU5tz8Ay6oWtkYNS6m1Kaq5SWi11LW1rMWsSCGANk52psP7hRgWRM1EPXGx3zH0HdNppJRI33dtzCwVqRSctritweTauomVZAkzNUa6rqmKMS1opZFKtvzHeUYqhY8BaTRCQ5WSqh0gSEKinCUJgR221NoaVEBCzeSSWxxOydTSlD/rDEIZYmrPyyokWWS07dDONoJYW6RL8As3N29YpiO1JIy2GNO11pi+o3iPn0aErJSyYFRGqYedvwpSUCkfo4Jn0nfGGZ82vi0J4B/6Q3/o6z7/y3/5L/OTP/mT/NzP/Ryf/exn+amf+il++qd/mt/7e38vAH/7b/9tfsfv+B383M/9HN///d/PP/2n/5Rf+qVf4p//83/Oixcv+D2/5/fwl/7SX+LP/tk/y5//838ea+0347DO+F8CDwTwoQO4fS7WrtlSQMmerttTy4YpVmLOrdXCaIw1eD+iSwJ/RTjeEaVl2O0pOXO6u2frhnaOVS3Ow/sFUSJW9xjjWuSL1Eg7UISgf/aCpAQuRLpuYIiZUiTTEgAwto01fc7oriMhwPXkJSBVwQlF1hOxijbqFYrTOOKs49WrN4zjTF4CXd9TY0BZh1lbKpRq41xjFKKCLAkrJaFWhGp9vmId46YYcNa1XT0BtVSUaq0exriWc+cFQkikaApUKS1CJpfCNC/tMko+On6VVmyHSw6n42O13EPUTItPaSYSUStaKWKMKAG5tp7lh0DqlBPeRzbbnsPhDqMkVknMxZZpGrl5+4q+c3TGoLQixcS8LCjtWJbAdr+j0CrrlIQSA12vkTWjhUJJyeI9OUeENBQkRUCiuasrgirkGoRdQWiksm0nUplGYGkGGiFkc/HWSkgZozXaWJRp0TgxRrQy1FqpSKQ2j8pfjpmaAnc3b5tjfHUDIyUVSUaQUmldx2swtRAJJT2C/LHXwMdfEr/RGPiMM874pPFtOQL+OHLO/N2/+3cZx5EvfelL/Pt//++JMfL7ft/ve7zMb//tv53Pf/7z/OzP/iwAP/uzP8vv/t2/mxcvXjxe5gd+4Ac4HA78p//0nz71YzjjfyV8wwhMrP9bd6OEUAgMokpKSogSWcYT0zRSALsZ2F1cMgwDYZ5ZxhNGCPzqqO06RwhH/HIg55mSZ1KaGZzBKEFJieQDsoJThrBEkjDI3RPs5TvY/RPM7glqe4naXNBdPsPsnyKGPXp3hd5cINwGXyXSdlTZ2iRKgZrbCJWSuXnzhjcfviSMIx98+ddQtVKFYImRQnPqCgFd1wEt8NloiaiF3hp6a9FCEkOkc4bNpsdaw3a7wTlHLaCUQWuHlIZUYZpnrHHU0kijNoacM7m2BoxKaW7g3IhIpeCMafVwSmGtXUmfQEqJNa1VRAjR1kNqWcfBlZqaOlprq5zzMXMYTxyOJ6TUpJyJOZFiZBxHVIXBGnprKCHipxkjJIOzbLqO3rr1Mg6NaK0iqiBFRmnZYl1qIcRMKaCtowpFrhKUQWhLlbrlPMpG+pR1KONItSK0WUmaaDEvVSCkfIxzUUq3cbBofbwVKAi0tZiuR2mHEIpaYRlPvH31kmU8IlhNMMaircNoh5KyjfPXPUotC0p6Wvblgwr58ddEGwM3rfpsBDnjjE8L35YKIMAv/uIv8qUvfYllWdhut/yDf/AP+OIXv8gv/MIvYK3l8vLy6y7/4sULPvzwQwA+/PDDryN/D99/+N5vBu893vvHzw+Hw/+goznjf0mIBwVQgmhtEmRBTYWwzEQvCT6w2W2pfcfdMnI6TPRGo5VECxj6jlwqpnM41zOe7rEKrOtJCFKK2KGntm0sUkztZnNCVlpuXMhtR4xCiAW/BJQyWG1Jad2zA7b7HUJosoC7+1v6vkeUTJonwuKpwbPpOmKp3J1O3Lx9S0yZwWmksdxHz+I9p2lmHwLDZmDxnv1u14wF5Ec1MOZKTq3LeH+xh9zMHsPQk2JkGDb4sDDPAaEN6TSy3W0Z+p5xmpi9JyMIKWPpGqGzFikbiZFCkFImpghKt6iUUggh4JxrKphuUSZZfFQ/BzRVq9L2AEuhlqY0xlzwMSFF5Xh/S4qBkiKXu33LP0yZ4zQxTyN9P7BxFlbaMx4PaK1Ra3uH0ZqSAkKLFnjtHNb1CGWoKNxmx3h7IORCFWIdw5q1w9fAut+ntGGeZ6xVbaSbGvlVa72dEE2LNlKuzSbNOFIraC3R1oHWxNLG3ylFDtdvOd3dIdKMcY3wtS5mi3UOiaRIiZGqlbuJipTx6xTAx9q3R5xHwGec8Wnj25YA/rbf9tv4hV/4Be7v7/n7f//v8yM/8iP8q3/1rz7R2/yrf/Wv8hf+wl/4RG/jjP/JUduJrj6e+1YTxMNuVIEwLSzHEwJJnCa8LLjtlt32AqsMJXjm6UidJ8w2st31VGO4P94jpMT0G2Is9P2ALJmcPClmao2UDEpKwrJALRglybW0DuKcSd4TprmNiJVGrpVlh+M9Ij2j63ukkCynO1QOWKkxORKWifF+ZhSCcTwxHQ501iClIKRCbfXG2K4n5MjheOByf8Gma7uKubSasMUvZCHIQmFtU60omZRD28ujOXyVtvgYiTEwjhNKKza7LT54hGoJgrHkxwgZkDykkEgpkEKSaqWkzLDbE2Ns492PKYE5Z4wxlBiw1rIsy5oNCFpJwkMu4BqSnUtlmmc62zITSwFrG5l8e5wYeoPTis12QAjBNB+RxiKSQhqDKJVcJF3fA5ByI+IJmoGj21BioCAIMXNze09YIllFag7YiwsE7dgejldK1aJmQkJrTUFgjGnHVQoiR4RojmwhJCjVmtkqKN3GvrHkNoqvlXmaefO1l8RpQhEQVmOtQes2WheIFrETW1UeRSBrRslIa/ngce3hoxfBx+ORzjjjjE8L37YE0FrLd3/3dwPwfd/3ffz8z/88f/Nv/k3+6B/9o4QQuLu7+zoV8NWrV7z77rsAvPvuu/y7f/fvvu76HlzCD5f5jfDjP/7j/NiP/djj54fDgc997nP/ow7pjP/V8HVpGHU1QGaC98zjEaMkSsD97Q1m8VSlWcYRq5pzOEaPUrD4kfF0pBt6+m0PIdHbgZIq0XtyjVCb+qekQohKrolaM8r0hBSpWaJloesMJQemcSLOGW0MpWSCHxmPglq2xJggerQzZL8w3d8RF09cFrTRdEphri4pQjL5yJISr65vmZelBRmXwvFwZOj6ls9XaouBqc2Ru6RMNR27/QUxZ5Zlaq5g08KeN5sNuVSurq44jiN397dcXF3gvSeFQCmVjGDjenIp656eRkjVXLshsd1s8YunW5U/7z1aG9S65weglFp/NC1sWso2ip1OD6NP2VpBHqJvammj01rZXeyxSpBiJtdEpw1Ihe07hIJaMomMEQrbdRjrCDEjtWoGidUwW4VYjSIG7Qq+FIwyvL2+4/r6pu0rFxA58vECtYddPxAYrR9H2835q5BCUtZjlEK1YzS6jedzQmuLUopcK7UKpFJE77m5vuH69StEDkiZkEIybDaYrl2eWkmhBWXXUto4XTUVkNX0UR+f9A/DZn7zaMAzzjjjE8O3/Q7gAx5+iX/f930fxhj+xb/4F4/f+8//+T/z5S9/mS996UsAfOlLX+IXf/EXef369eNl/tk/+2fs93u++MUv/qa34Zx7jJ55eDvjjP+rqEAVhSoe3L/iURHMQBERFJQq8Etmmk6MqZKwzHMm+ILqNqjNDrW7YHP5hNPdHadXHzLUgqZwuj8hzB6hbXPYElu3bcnU2kaeuVaEspTalKFcYQ6RhETbHmt7rHH4tVrM+4XNdkAKRQqR8TSyIVHGA4e3r5nHI1Irnjx/zuXzFzz9zPts33lKf3mBHXq0beHKKhemletWSAAAx2VJREFUccQvAS0NhIgWlSISSwlMMeJ9Juc2InyoFKtCYfsWL6JXI4x1hs12YLfdsOl7ZIE4BygCPwfiEkk+oFaSllJqo9ZxbLEvcUFLMEqwjBM5NAJVUkSuu2tGa4JfHomnMwZnzJoZaKmAcwZJgZKgVGKIeB+QUjPPnjdvrxnHiZhjM1FUCLEybC6w/Rbb7RDKIVWHMR3LNJOXGUUixfYcqbVQRXPqCumQsuP6+pb7+xukLBQKetiiugFlmxvaGNsUz9oUQefcanJpawEIKCVBKa3STgtiicRaSci2LygFRQhSFdQqqDHw+qv/jWW5Q6mE1tD3Pd2wR9oelKKECDkRY6BUjywTnV7QauIjF3xeyd7HRsD1gQFmzjjjjE8H35YK4I//+I/zB//gH+Tzn/88x+ORn/7pn+Zf/st/yc/8zM9wcXHBH//jf5wf+7Ef48mTJ+z3e/7Un/pTfOlLX+L7v//7AfgDf+AP8MUvfpE/9sf+GH/9r/91PvzwQ/7cn/tz/OiP/ijOuW/y0Z3xPzOqAFHbBtRDJEYV4lGFKbVgu4HdxZYYC932GTEmRKlst1uyrIQU6HqHBm7fXLPZOCSJ5D3D/pJUm9FjXiY2vUOv48xcBdZ1q8tTUWrCGL02WmgEcDieONzcYrVmPBwIy8z98Z7dbt8UpQIpJo7+hNIabRzDxSVSW/ZPnqKMbtEqIXCaRvphwwcfvmY8nZqBopQWPZJzM2pIyZISIjbylmImCwkp4b3Hdj3GrKRmDYsOwSO1olDoh46rcsk4jviw4JxDa401zclfS+F4PBBjxD15Qimtb7eWgqRVvuXUolxyiigpYa2c61zHOE1rP3DraVZa0fUdUqlHVZBaG8FOGSklPgS8b8HMHze4CilRqlXDVSQ5VaQCP3u07uhcx2nxBO8RjdY1tzLlkTCVKslIlmVBSIF1BgDb9xjXI6QGBEIqahHNyVvXrMnaFDnv/boPKUE03VAIQSylVblpg1CKUjIFiRCCnBOnwz23b1+xGRydFShZkUpSkM1xLBWKitSGGYCCKAtaeqT8aP9PPPK+rzd7iN/gozPOOOOTw7clAXz9+jU//MM/zMuXL7m4uOB7v/d7+Zmf+Rl+/+///QD8jb/xN5BS8kM/9EN47/mBH/gB/tbf+luP/14pxT/8h/+QP/En/gRf+tKX2Gw2/MiP/Ah/8S/+xW/WIZ3xvwh+w1PbutsmlEIoQ7/dk8ITxpPHmg5JIC4TZI+VipwD/n4mSYUxihA9YTqi+x1MJ6T1lLiaPFJFVNUq1Dq97rplrLaUkhoR0hpZBcu8kKaFm+trnl1dIGUlLBPFLwSl8IsnxcTQD4huw/bykq7fILRmGAZyqYzTwvFwaspdLLy9f0v0GaUMnahcbDdNHSoFpXTLlFs8RUiMNGuAcKsNqzlTS24Ei8oSPFJCFbXt+KXYrARSInWLSgk+tMfxwViNeBzpSinpuo6cEvPc6tpMSug1WialiFxbQ4w1LYSa9vuikaA2RtWmjVS1aqTdOYtUinGcW7hPLa19RbWuXKskMUpOpxPj8UDvHPvdDqkMYiWaJWe8L1hrqTmx+IVue4kUomXv5TYTlrJF2ISY2O129MMASLp+wFjX3NhVrFE5H93/B/e5EKqZX2Ij/1lISq3k8sBxm3lECtV2BAUYJVlmz/31K7KfkUaupppGgEte8yIloJqRpNY2elbaY038RF9TZ5xxxv9/+LYkgD/1Uz/13/1+13X8xE/8BD/xEz/xm17mC1/4Av/4H//j/9F37Ywz/vv47+05lVZTlqsC1aG7DkyHVpoYZ16/eYmkMvQDUipuxztigSfPn2OMQSKQMePThDMDxnaUmBBSoLXBGMXt3TVDt6HkhKyF0+lIv7sgJ8F4OKKBnCOLn7HGUJREih1SSrabDcFHrLVs3nkfbR0hRZYY2GhDniem05EwTcSYqCFxuj+SY0ZWATWxGRze85gfVyoou2bXldyiSWKkhMAyzyhjyLVwOp2QQnKx3aGNJtVWK5Zioht6jLOU0qraimikr9RCt9m0x0a2EGioKCmIqXULh+jR1hJjIJWy/ngUCIEPnlIe8hnLI6kUtB0+s8bM6JVgaaMQQjKOfh23SmJtoc1KFJSSaLmaHwpoozBSobUh5UytglISKTaFzqh2HQhBTplam9kil4pQgt32kq4fqAi6fkAbS0rtGFoAdl73+UwbwUtFLhljbCO7EvK6p6ebfYQHc0atrQVPKAE5c7q74f76Db2VKLWOo2mOaqPVmlWoKCVSSkVIgzYJayacOxPAM874VsS3JQE844xvR/xGoReCulbByVW5Mdh+oNRLzLZvJojTDUkJioROa5SUTHMgxIruHEJqlFDICnGaCCrQm4GcCkpZlIZaWx1ZDjNutyMsE8YofKiUVJBo+q6nxMB2u2XxC6fDgWEz0A0blLE8ffqMeW5RLtb1DJsth/HA7Gdev3rJ6f4Og0TmzHR7x+E0kn0iTBMScF3LsqMUNBKpFCIr4hJYYkQV6Ixt3FC2savRmmX2JAr73a6NYZVmmSekUuSU2HY9SSnu7u/ZDAPeBw7HI8YajG0VaNZaYoxIKVBSE0NA65aHV0omxIDUBmsMSllKLUzTTKmVUmurrpNQKJRamhNZCULgkSQ+EMKu69hst9QUyNow9B0Xl3vkGsYjpXo0/tScWwSMbQ0a42mEWvDL3MKytUTRUUpp1XlSgWqj/H4Y1vgagbU9FbWy09ZUUmsh5ow2mlrav00pY20jgCml1h0sJEIqJOJhJZWS2+hYC8k8H7m7fsV4f9Mq6DRIFKk2p7IUFYlAIQglsfgINAOTtR5jlk/xVXbGGWf8X8WZAJ5xxqeGtuj+60XA0poaBCBbm0ZEErKkUuh3O0QeObyeOU2F1FW027HttxTRXKen44EwBlIq7N57wnia6LodUktSTZScONzd4Kym5pZPJ4xjt70k5tbecHFxxXg6sN0XXr2aWFJhOYzstoqN1cwFvJRk57i7uyHGdmJXKTXl73jCx0gOiaHvoXbkfGI/dAit6TY9x9OJGCKbYcB1jpP3j20fKUeqNsTcQqKNbO0gOWW6oUcryzx7UsqEFDFrdEopheib61RpDSG0cW2STNOEVIHS9yzLgjOaqjV1JW191zWVTCmEEnRdR60QU4t40Uo1N2zOsO7DtU5eiff+sVFEiIpRbZ8u59aCoYRAyOagDSESw8J+6OmsZRgGYgzk1DIJnVFQEs4anDVMpxPLNIKU9K4H1eJ7Ks0Y41zXRt+qjWGltuTcHLsxJrRJFMrj3l8zfZQ1Z1GDhlozUqi1Iq7tS5YKdR3jKimRQnC6v2O8v0PUhNESrSUSg7MKYySCjKiZkitCFLxfoAhqTfRdwmr/657xZ5xxxjcfZwJ4xhmfGh6cjvWx+aPWtu/WSEQbqaWSyRWkdvRak+eZusyE04n72zuunr3HZ77zPex2R6mRw/0t8/Geje3YDh0lVXIOqK0k5kipCQGMk+fFs4EUQyNKUqOMpVbFfJqJCIpUhFwoVfLk2XMArO0wfU+qkiI1VRSchcPNdXPM1orKiae7LTlnQoikXOmGgU2pmFwQsoUK3x/uyTnRO4cQEPyCADZ9j1/JlZQtx6/kQg4Rq02rLyuts/d0GtG25dixVrKN44jSbW/twfWKgHma0cbSuQ5R4f7+wGYYMFpTK8zzDFLgbEdaw6aXxYOQ9H3fsgFlC0tQKxl0685ejK0yTkpJLm3vDypGaUII1ByZTyNaKkqK9J1FCEEIgWUamZcZbQz9sCGGQKkZJQUpQb/pCctCjrFdr25/OAjVlFNtbRsbA0Ip6pqpJ4R4rLFrBpBCKRkp9CMBrLRYm5TKqhS2CrpcKqVUTC2tUWQdpY/HA8HPaK3QoimmiHaZRnY9KEspCqUFSrdQaSULnYsIcVYAzzjjWxFnAnjGGZ86VhL4DV+qFBCFUiIxeaTOzPfXxOM1/v6OXkrkbofShuM883R/iTOK9GZh6DSdEdzevmbYP2d79YRlPGA2W7QxLXyjSKTsWoadsUjb4wso06N6SawZVOt9tV3H8ydPiSFgbUcVgtMyMwfP7Be6WlBCkmLCSEFJmYOfcV2H2WxRCGqMXG42nMapuWlXE8a8TAgpCDGw+IUlZjbbDVZvKKlgcgGh0ErTOYvRPcd5aWaI0gwLvbHkHMkpk8cRIVvAcQiBSmW72xJ8aCRLNWPJbrvFz1Pbh1OtrizFSDcMSNEcuzlGSkoY16GkoOpG+po420KOU0yklOi6pirWGls4tNYoKqFESilYY6jD0NRDLdBKMU4jm86QSzOUxBAogKsZIQXC6Bb7kitaSXJJrRLQNnKKMCgj6YeB0+meXNpYOYSmiKZUkFKQckYphTGG+vDcoimBTbWsK3lVa+dvQ/u7RFBqWQOdA6fTAUGh73pkiUzzCatMy/CrCUlGysIyzxQiWlrQld4J+l4AZwXwjDO+FXEmgGec8WnhIftMfOMQeA3FrYJCRqiEEJGcZlSOxGVE5ETvOiqKgCTWyv04Mh1vcVLy9OqCw+1bEAlK4P7mNVOuPHvvs/SbC1KB3e4pSIfUEmE0USiq0lTjqKlSUqCIlr+XY1ydxJX7m2ukVBynE9M8NyHTWZzWDF1HnD2u35CqJKJYYmF/dUWOkXmeOfiFCqRpQindnLi1YIRZXauVsHiM0SgpMFqRi0DUgja6OYPl2k9bodTCaRypNT+qh5vtlvvjEVkFfd/RDQOn46mRoZTJKdE5x8XFBSUFwjLTdR1KSKzSrWfXzy0SRiv6zpJLRZVWWPaorK3xNDlndrsd8zw/joGB1bHbjCHWOZQUhGXheDxCLQzOMs0zNSc2mw3aNHKdc2a/3RFD4HA44LTGGo20ihQjuhaUVmTaKNi5jnE8Au32aokoJQnBo3VTILuuVeDBOtpd3eYpJWoVpBhRuvUKCylJIayO4UJKrRYv+YnD3TVGVJy1RN/MM0oJOmfQErRWKAUpFUrKaFFRKmNtwqgIrcvkE35xnXHGGf+/4kwAzzjjU8PHqz++/ssP3agtIS5S8kgujhgXUs6c5sD93R0ow9Pnn2W4umK7u+TJ1RVpvAeRGbaXdJsdORZu7490w47pcM88BvaXT3HdgLB9U5mkRArNEiIyRHJKaCGJ6z5fXBZefu2rlJTIsVWdpdRIi9KSzbNnLNOMshYhNdM48/z9z3CcF04+4AvMMTPFzBwzolTiNJNTwFkDVXB3PDJ7T8qZEAJKtDYKJVtHsqCSgyd8LMOuUokpYaRCKUlOga6zQEaItrPXdx0S2Aw9m74n54xzDqUkZtMzTe3xt9YwjidiaLt8stJum0JenbhjTJSQkLT7VEttNXJrYHHbDfzICAI0AwusY325qoXd2rFb8CEgqGhjkFqz2W7xIUAVDMMGAfh5QkuBUQqp2j5eFnXNimxZfVIoaq6k6JGyGWYebssH/9j80e5XXqNkKt4HjNLUUtcEIkEpjVhroSk5k2JE1Mx0uif7mYtdDzlinUOQ0aJ1FDtrW2WfyE25LBUtQLKg5YQQTZE9J/udcca3Hs4E8IwzPjX8xn1XLQ+6rmO6CNVT4kjNlhAD47xwXDzC9bz3uS/w9P3PYXZXSOOI04zdSHIYyQWUqoR0QDvHk4tLru9GUkkM/RbZOYTSFKGR2tJ1Pbd3H3A8HtFa0CnJeH/TzCJOY6VingrObbi5vuF0PNJ3Dq0sMWSE0BwOI1dXV0gfQEh2+wvy8YSPiRQSp8MJue7addYSw8I4zVxc9SzHE6d5QSuztn4onLVomQhzxEkBJbddwJwZywkpBMs8IWSHQLbxc450zrIdelJK5BypteUCppSb6lc+ImxS0kajJbHfbSi5jUONlmgliSXjl4lSEnEOKG3WiJMW5WK0Ia+uX631I/HTWpNLWa+7EkJo+3tCoK1lXhaMEljtEKLt8lXgdDo1RdTadZRsyMqSY2yZhAIEhZgiRSpyyhjdbltAayaRPO4jCiHWyj/5qE6mlNozrdam9Lm2a6mEWltSBKyXj9FDreQYuLt5i5UVRW0NMkIjpcYoqClSlSGnilIV+RB8XRLGJLo+oVT4DZ/zZ5xxxjcfZwJ4xhnfAhBryFytGa0yWmZ8mFu1VgXlOmotZARLjMx3dxRhKLXSO0e3vSIvlvF0IOZKQRFjxUlDCgvj6ZZd94xYElVIOqEgw3w4crx5y3boOE4H4nIi+Zn95Z6Li0uWJRBTpipFLIXXt3dYrcl3J3b7HTGsjRdC8PLlB1jXkXLFx4RfPHmacEpxmGbu5xuev/OUZZ5ZvCfXSswF5zTaWIzVaC0xwpCXADlByWw3A1YoTtMMFbQUOG3oO0OOAb/GzEiloBameWS325FyZJpnjFYcT0fyGoEiBKty2DH0HSlmKqu6tta6hdQq8JTSKGnXnbiymkAMdR0tK6Xouo5lWfAhNCMKtY35RRuNWuuIKWKEfKxok1qhtGaaZ3yIbPY7xGp+EUK2fcKHq1lzCKtorl5Eu05nu0fTjDWakiNQCMG3vcUqyLW1k+Qc19DmdqxybSWpPByHeSSMJWekkBzvb5kOd834ET1WW3zKzYSiwCigQooZ15lGfFNFAb2rbDaCKgKUDOJ8qjnjjG81nF+VZ5zxqWIdhj1u3deWArP+l0tGiYLRhTHM5Dkxn0akkmx2O4QUvH39hiw0uyfPePL0BVIKTtOJXAS+gtQWkQsxFHLKXL95xaUq9Fd7QpiQWqB0wp9mxsM9MifSdOLVV77CbuuwWiKlYJxHtHHklNlc7HlaBS9fvuT2OCLlQkmJYdtze3vDZrPhdDoyvXrNMGyZF9+ITK0s48hgLcfTkdPpxGYYuDueuD+OTV2zFqkkSilCCIhcWq6cAFJCC8HVs6c8WZW66+trLq92zPOJeZ4ZTyc2uy0Xl5ccx4kQI7UWUkqMp4mbt2+5v7/HrTuAw9AxDANat2Dklt3nqKKuNXltl87HRN9v23XF3HLxtMMZi4yJeZ6x1tKvY+au60i1rBF/FaUUMcSWm6gEm00Lcm59vJn7wwHrHMN2g3MdOVess8zziF5VvFJaf7NMCd0pslBI0QwvxrQaOCkqRitirjirySVjbdfaS+JKAFMC1RTRRv7WdpNSKBlkbaPiXAs1Z3KJ3Nxck5NHk8gJjGo5hzlFhM50Q4dRGiVbCLSP7Y8VKQRGgzFtnC7Eef/vjDO+FXEmgGec8WlCPDiAKyDX/q3cdt6qRQsB3GIr1OOAnzydqSzzws1xQnc9F08usV3m9ObXCKcbuv6SoduwjCMiVkKxjHmBHqqfKfM98S34fkv34nNY11NK5vXrD8g5ImoiLAtKZp4/u2RZIqkowhxRWbQuXuMocmZ/9YwlfogqiRwXlkNzxJYlMGx2HA9N3Uu1EsOMM5oYRk6nE1f7LcEn/JIx3Y7j9R1zDlxY1XbdskQJgzKFVBKQ0BLKdKIcNTlETvOErIW3X7vl9nhPzBHrLDFMfPjBPTW1RoubeV7r3RIpV6xSGKWhVE6nhbu7E9Zarq6u2GwHlHNUJOiCipEUC2lecDUQThNFKKrpOIWJi96hC5QaEUax5ATKoJWBGBHKIrRZx68RRUXkjERirEGtdXYxJRAwno4453jy7B2UErjNFr8sLSYnJvzhxM5u6QfFlJvjt5RGMJWsRFpgc6NbBmMKuSakaHEsafGIUglppgLW9msotmKcJzb9U1StJDFRSmHQe95+9SuE668gykI1HVUZhJLsbccpeOoCSS70W4vTe0oRBCIoDVQ6d4/Rvwy1IMoe5PxNe8mdccYZvzHOBPCMMz4tiK97t34k2wK9kLQi2QzFI0QkppEYCykX5phJVVCAUAp+9JxOR7Q54roTY7chlxZ/Uovg3XffJyWPXybcZksslSVEtkohqBzvj9zf3JL8wnS4ZbdxvP/++y1IOCWUbbtlNaWW7bcEpBDsdltO44bp9gZrDCk3AvjmzVs2c6BzjrvDEak1u90Waww5tz2wKjVWObzP+OBRohHgWpr5w1iDFlBSIIvW3SukZvGew9c+oAjItZBy/v+w919NdmXZlh74Lb3FES4gIpCR4ioWzchq6xfSrP//Y7PZTRa7+t6bOgQCwsVRWy3ZD2sDEXWryljMIvPi4XxmEYh0ONwdwPE848w5xxjMy0zbdezcDqUlUkimaWKz2zAMIyEEhFK4rqfXFqk0udR6t8UHhJQQM4fzwOIXtvvCZrfD2ZakA1upMNaRYmAaFnKJNNKgkMRlZl48RiuykPhQV8PWubrKjxGh1ptBKWnbhjiNHI9HpBL0naumk9U53DRNXZ+mBIVVnEmkAK0UUqk1i7C+UAh+IcRU19OqoHVdSWcCYnWY195itbqTBYVMTLFG+iBBSmJKSJGRKhNiQVmNUDVU+8OHHzkenuk6g24U1lq0rg0mUtXbTKUUOSVSTpBlNTFphRIRa0ErsVb+XW8Ar1z5ErkKwCtX/mp8CoHmXzwn1m7Y+nMZZMK0oMzE4hU+FbCWF/ev2dzdI3Li8Piefb8hzBPxcsTPE6ppMcEgdUO/2fL0HMjC0N++ICyeWGpryHg88uN33/Pw4Uf8NOGMxJoepRTH05GCIKdC8IGNc3jvOZyPaGm5ubvn9uYOS2YcBqSo9WFKaZ6eHtHWYZxDAsFXx6+Uit3+hlwEwSfGeWScZoLPNMbRdx3arH24kipiRBXHKWUSsISA0HXKpbVmZ3fs9nuk1mvbhqbfJIzRbPY3pJSRSmNdi5Bq7c/Va2iypAhYZs8wDIx+Znk+Mke4ub2laTpst6Xd3bBMI0VaxsuZ7APWFMoyM1wGrHNo52qTRpE0bVdbSVIGITFGQdRQFEVrUoqEEBjHhJSCXd/hnCHF6oI2xqPmCakNm80GtQrIWAopLJAjtbAtEaKv94qpPn5SyhQyWgli+RRHU0OfpcjEXIOmy5r/p7UklYR19XZQqgaJQorE4fjIw8NbjCqYNS9RKarRRGQkBaFq/IvWEkGm5IQodR2tVMAakLJAyv+J2KMrV658CVwF4JUrf1XKf/zfP3+TqL29Qk6gZqbQ0e/u2d+/QDUdk/e0ruHNL3/D+PyRd89PIBWuaWi6lmGekDLz9HwEoXHbPUZbxDyxfXFPKYUfv/uOP/7zb2vuX4q8+NUblK6GEqU1CMUSPAA5J8qaf2ecRWpF03Z07jUPHz7gZw9GME5nvA9M08Lu9obdvmNaZi4DNH3PMi8YrQklMOfE5VOnsNU4Y2idIyfPPI0s04CIEd05UqzuV20tWRa8n2ltvT0zWqO1AaXR1mJcg9QKhCDmKgC7dkuWglIkxjbEAtM8kwu4jaDdB2SOnIcLl2XBP5/Y7aDrN1jTYqTl1rQY2zAcnyElUljqWpdCCgGBIq7Bz8Y1xCJQWlNKjUZZpgmrFVJCjIHGtSglGYYBvyhSiCgp2XSbGsejDckHlmmqsThGEeYJMZ4Rblcnb7lWrxUJyhgQAqkMiCo0hZSriK5CzIcZY2rEi5A/BT8bY0hRYFWDkFDSwo9vv2cej/RbgxICScYoidGSjGQq9fcONRMw51zvNpVGCTC6uoCFiCA+ve+VK1e+NK4C8MqVvxr/CfH3CSHqmwRARKqZfpv45te/QtotMRWePn7g8ekZlEIKKMvMrrHc3t2yvX/Bh8OFZQkoVftY++0evyTmnLHbDVlKzscTjx/ecz4d6LuGbtOy2e9IqbZXaGuJobZOKGuJJZMFSKMxTV1xWmfx48wvfvkrHj4+4JfAj+8+MgyX2haxhia7pmGcF5aYMNYy+oXDZcCXQlaSeQk4YyAXcoq1OSMa4iTwPhKNR2rDeL7Q7Dq01simYbvZ1LtEpVDa0m32CGNQxiAaB0LSCEkuEIqgCAVIQlZ1CugMao09SYsnJY9VDfFyZpgm4mlkDoW+72mcwbYb9mvsyng+Ms8LzjpQknFZUKatrl2tMbaQikAZzXi5kFImhMAyXdBao7XCG4UQ0JgqYkv8yaih1hW9Xxa2bcdlPNPalkIiLCNSOhC6VvCtkS9CCCbvq5MXSQwJ49Tq+o214zdEjGvJRaK1pSSQSDKgnUGIgkRyvpx4//aPWF1X1EZarG4wpv7dSyWQFAqRlAVISw4Rkqi/P5lwLmBMWN2/hbJWEV65cuXL4ioAr1z5V+MnEfjzrbAUBaEz+1vLOMLlfMT7iIiBXmWkc5hui5aCEiaK0nx8fKLtttze3nEeaobdOI1oYzBdjzaa2Uf85JHA/e0tTWvp91ts2xKjRiRP9DOI6kbVtraG4AAhUcoQQq0cs7s9Rmm+/sU3PD081d5gIfHLwjiOaGuR1qKN5fl4xDYNtnVVEKZMoQYJ922L1bpOGpEICdpWUVgNCwqtBNl7pBS0XVujV9oObSxSN5iuQ2pb17FtB1KRS22mAIHSjoLAx0RGkHIixEiMgXGceHp+YlkmxmEg+gVnDE3reHF7x+vXr5BKom1Dd3tPMZZ8OiJyYvQ/ddxKpZBKIxUgE0JppFL0mx6VF5LXNI1Da43REmM0nbNIClqqWruWEkpIRC70XUuJCb/MWKcBgWs3QMGHGtOi1pU4612kNhohC1kEimDtlk6ExWN0i8AgpUFJXVtOtAElKOvUOYXEw/s6/bvrDVppnGnRpkHJ2mpirGPQ78hZ4JzDGFfzEnOBkFFqQakZqaoTW0hV99FXrlz54rgKwCtX/lXJ//GbhECITNtLrJXMc2HTtuik6ERE77Y0t68QUiMJ+HlG+AVBhrDw4sUtz8eR8TJwc39Hlppx9mtmW6BtOnb9hiQyu7tbbNeRhguUGhZc1hsxrdTadyExriP5yPFwoOscm82OJUYo0G+3fPX11yzLgpASH6qpZQmRJSZSEYxLJBdoXItPC9NwoLGOvmtpW0fTOYSA+eKZlmo4kQJ88CgpMVKx6Ta0uw1FKWy/oek2aNeiTAPSgFIsWSKlwrgGbUHkQi4ShKJxulaiiRlpMiZn2n6L63oulwvPz088fvzIjx+fIUfe/fiRECO/+uU34Cy63aCR9EoxHZ+RUeOMIiPryhcBUiJ1vXssQuDajuVyIufCOI51Mtu1bDb9GvAMcQ2MNsYwXC5opZjERPJz/TvNiZIiWspq9ogJIWqbilJyjY/RSC2RCgoR1gmnXyJEhbNbEBIhZTVtKIXUioKt01edOB0+8uO3f6K1CqMVUmqKkEglyTmipKki0Ng1yFqvjw1HDmtTSolIOSHEVKfaQnId/1258mVyFYBXrvxVEVD+U8+IpeallTUzTRSUTrx8vUeYTJ4hnA/kHMlxIZeE0S2964ghktKEFpmmb3n/7h0JS9vv0dKwZE+MCZFBK4uxDUZJlALTdBRp8CGBDxATRgokMA0j6FpXFmKmcy1vv/8eJW4QQnM4HNnvblim1ZF7c0PTdTw/P3O6jKA1h9MJ2/VoITgdTiQUWmrmaaJZ+261VrUObZmZfeDpeMQYw+1uj08RIWtNntWGvt+AtdjtniWVug41DVnIGlgtBQqFFopcqhRCSISQCKVxSq+hxwLvqzu56ztevXxF+tVvOJ0u/Pa3/8zv/ukf+e77H5mmGWMsX3/9FaEoVNPVFbcPhFzbMQoCqernyDFinUVqg54dWhV8TIzTxHbTcXNzQ+MsxtSvT5basZtWB7DWilJKbV1pNdpWF3RrLDkGik4o5VBFkTJIqYgprfVzkpRAoBFoYqhRQ9ra2jIjQWhBLAUlau6kiAqjEqQLz+9+YDg80xhZm1OkRGhR+6VVqeKy1B8phZgSMdX2Ea00UKe1SnvAI0r9moooVx/IlStfIFcBeOXKX43P6c//mZ/7+c8nEB7rCs2m4xgThwWQFqEsIYMqgoeHJ0rO3N69JIWJtz++ZUmCze4lTlvmaabkjLOO5BPbfsd4XpiCx2rHMHvk7PGLrxl2MWFdAxnmYWT/4gXaOhSxtlIAp9MJpKHtWo7HA2RQneL29pbv374lIuqNXRE8ny5sikBrQ5hmhHEIrYCMkGU1RvgaMZItm7bnYs5chgGtNH3b1I+FJKeCVgbdb1FNh1YaaVqkdiAU1gmUtiilQSpEAS10vfVLmZQyo59rKDIwzzPBL6QYOJ7OFCTb7Q3/3X/3f+P25gV//N0/8+2f/8A//vMfaPqe/W6DWid83e6GiGBeZlj7ecXaequ0AalRrsEagbLVYBFjwGjFMAwoKbBa4YwhS0nOmdY1SCGIMaDWmrga/0LtH44ZK2R9W1ofKUKtcTkGiSYFgdUtSkjmMKPWLuGYM6h6AymzQAqFRqMZ2dgJP3/k/PRnDAm1xse4xmKdRhvQspCzZ4nT53MFuVYKQkLVlEOUKBiTkDKuL2bk1QRy5coXylUAXrnyV+OTy+NTM8K6/hX87E7qZz8nIkKOtLtbZH9Pu3kJ/kgk4ousHbBC0nQNPgRiSOz2NzwfB3KMBL8gjMUqjQ/h80eujQ8FVO11FSWRS1lTaAQxfYpikSzTzDhOlCK42d/y9ddvSCky+xktNY8PHzk8H3Cu5eXLVzRtx/L0zOn5yM3dLSklnp6euLu/5zLOuF6RY0IpQdMYnNOkkpjGASM0jTLs+y0pZlIq+JixUqGdoQCz97QpIXKi6XqEMmSpUNqBVCBqbl7KVYwJIUm5VL0kJVLXLMVlnliCZ54nlnEmpczz4cAPP7xj0+/4+uuv+dVv/pZpnjgcjvz49j1OK8iZ7aanCE27ycwpIdYOXikVQtSqtCIVUmukUTSbLf5kGc5nSko0raNtOxpr6JsWSV0Pz/PMsizs9nv2NztCWpBK07jqXhY5U3JG6vXx8rNJcr33W40haHL2QKzit2RQ6zq2CFQRNKLQqEhv3tO6J5Z8wIoHNm1HEbWSL8bMsniMbclRoIUgLB6pwOpaRae1I+eFFDO5JLIIaBWRJChq/Roz1z3wlStfHlcBeOXKvwqC//hJ8WdTQFGARJHPZO4pytHd36DijpgGnp6fmacLnRJIUZtCpCj1TixFxsuZmAT9zZ5cIKdIWCIpZKSRaKlZlhltNM4ZFq0ATaEQ1g5a62rF2TQNxJi5f/GCV1+/oYjC+fmR3/7TP7JME36eOB9PnM9nXr35hpu7O+aQGKaJtuuY55kSU403iYkMWKPYbXu2uw27fU+IgeAX5nEk+ojRhpATp+MZpzVWacQ8kw5PZKspy4ybZrTrcN0e1Qi0dRSpUcYgkbXeDFHz6RCEkMgkbGuxTcP25pZ5mhgvM4fDM7ui2O0K4zjx49sf+Oqr1/zyV7/mT3/8HU9Pz7z56iVSFLx1KOsw7QYzz/hlRqyO3EIBKdHWYUuNYDGupW07kl/IOWOMqW5pMj54nDGfO3210pSSKQWm2aM2hhATUlUXcogeYfIa8aLI+VOjzCoOhSDnhPdLzUeUrDGTClEkKoMTCxs90tuZG/s9Wr9jijMbNzDJhiVVQRljwsRUp41C07YdeYks4YJ0LTmX2o+sBUVCXCKlzEiR1sdvDTcvIiNQf6XvqytXrvyXchWAV678q/BJAMq1LQF+mhDWjDVEBg4ULsQcgC1+TozjhZIjgsjD+/cY69jfv2K4XPjTn/9EioW23+P9RBMaklhjRpIHBN2mIQ4jwXtKTihlcY2lRBCuoSRB8hFKJC4LXd/WA38K7XZDypnHdz/w3/zDP/D+3Xtudjt8SEw+ME4jUlm2N3uWeUGbjJbVVCBswxICIXisUjTOIiTs93uWaeLj0weCD2QKl3muzuMikFLVphBT3cJKgrM1CqWEQF7mGl5dCkFkVMx11akNGUnO1Go2Vf+8lbXkkpECVIab/o5ue8P58MjH9z/Sd5ZpGjmfj9zc3PCLb77h9PzA0/OB1/e3jNMMPtO2ms1mx7Q2YiipCSmhtEFIhXMNVhSsbViUYrOpLl7nXK3Pi9XgIhHEGDHGIKRYTUAC17ZY0yCo7ltWIV9yoBSx/lO7doUQxBzJJHJOCKFRivpzUiOzQgqJU4mtObFrfqC3H9jxDOUBqTX7Dh5yJmZBqzXaCKwRmE9hz0SUKoTooTS1RzhmlMoopUklV7OIqu0fQtQ1tvgUcXTlypUviqsAvHLlr84q8P4LUHrB5cQSI1IUEqXevglHTB7XOG5v70BKPnz4QONacLXxYzgdEFpgG4cymqZ1IAxL8ByOzzSuoZRILhnbNMhiINaA4bnUpgy0Zrvd0TQNRQh+/OF7ilBY19C2DfvbW7rNlphAW8sSM/MSye/eM1wudG3L/c2e4+GZLMAoyXBe2Gxa+rZFCcE8z1jrSKWwhEiRCh9j7btF1Mq1XCg5EZfAcDwyzjNaNyjlaFLGkPF+Rm9fUFIiZyjUmJQlZdLsyUDOmWmemKYJqw1N2+IXj2ssdy9fIgQcnh8ppXC6nLi/v2e73SFyQivDsgSkWRs3Ql6dsTUMWSrFdrcnoWt7i1BII5CfeoYRhLAwjYIpF7q+pXU1GkbJOm1NKWGMZV4WpNGElDGqCt8wjchO148kRW0Yoa7rP10Q5FJAaqzWlBJr60kxKCVpZGDfXNjZ92zsnzH6B9SSQRxxesd2s0OgsMbUu72cEGSkzEQfWeaMIGG0wRoDSSFKDcPOOZOzQJOQMgOZUtTnMOorV658eVwF4JUrfzU+X+HxH45E5L94v7reoyhyWTAk9Dwyx/eM0wElBCkIYnGo7S1jgOPjA12342a/4fD4yPlyYbfdEZaZJWfa7Y4sFTFGfIhorek3PXLt+DK2w6TMMD6szR+B0XtevHxJs9nQG8PT4wPP7z9Uwdm2DBGicUjrcLKaERqhaJdQHa+7jsPxyGbbU0rgeDgRxkhKHiG6Gu8iFCIWpBJsdjc8n+otXIyJuIqhvEaOiFwQpeDnyH7/iiQFm+2WkgI6TRhtkDnSbTYIZZhTIaRMZ3XNURSKcZoQUuKk4XQ6cz6d2O93DIvg9uaGdn/LUgTCjmRl0NpiVECisLrj6XDhlesxLjGPEWcsVneUUm8Ps5BIFLrUaa5UEttvCUXQWIvTAmtqTA1Kkde1cYyhRscUGIeJtu3ojMSahiIyxip0ruvtIDJFKDIOKTNSLIgoENIQSqAeD+SawiIMQlqUuHDTf+Tr9lv68k+o8pGcRoTYkmVAisC236KU4GbniHlCYhFCkQpkJKIosg/kLEgh0iiJxNeu6CWRQ8L1HmMyEEDonwLOr1y58sVxFYBXrnzBFBYKAzkduRxOHA/PaGlouw3KgNSKw8dHnh4e+fWvvmE6nzgcjrR9T9dveDoeyTFWL+ZqIrDOsFd72rZde2Hrjd08nuuTfSoM04RxDf1mU3t6c+J0OdG0jtevXxGsZZgmRr+wv70FITg8HVhiQAlFKpHd7oYUE8Ev9G3LNM4Mw4RSCucsSiuMNVhrSTlTSkEpxfl8JsaEjwHnHH3fo3UVryFnNo3j9u6WOdUO3RQjQhmskczTQAJc16Ns+7M1cF1J3t3dMc+eUia22y0xBi6XC0oojgU2+z3eexpraZ1hvgw0bUPabrHOEo+RcZ5oNw1aa3IpCARS1mBrhCRTWzGAOnlre4x1iJhxznI6PLOER+5fvqbZbtBak8JS+3kTLMtM0ziUksTgKSUx5YiSFrPZkUtCiIySYjV9SHKpU0C1rsKFtBjlKHFBpgf23RO37UecfAvxmYJHFLs6devKWWlQks+VgFrU4G8Aay3Re1LwSKlYlgXbWFhvHlMOCApKif/0eeuVK1e+OP7l6OHKlStfENIUEAe0eOD4/o9cPnxALAtOwunwxO9//wdC8Lx+dU8YB37885/Z7Pe8ePkKqWtHrlSKEOqNWfAeUcAZS9d1aKPXn69rPOsahnkhZtje7Ek5E3Nk8hMhBVzbEEriMs4czwNzSEwhgqzr3+9/eMfheGaZAyklbnZ7DIK8eF7c3WG0whhN23U0bUfbbdC29hAP01jvxYRkWjzz4pmm6XPdWc27g5xBKs1ut6Pfbnn1+jXWOVIuCJEYLwem8UxOC0YLrLXrDWRCKUXf92y2m5o1eHvLbrOhcQ7vPWFZ2Gx6mq6l325pmgbvPcbWoOkiJJdxJOVSTSdFIKVGScPkfTVyaF0r3ZQEKbG2wdqGp+dnpFDstlucc0ghmMb1FjNlxmFkmkbEWvPm55kSI1qK2j1cShVhMSAALSQl18aTVApkgRIK6xSu2dA0t/SNZaPe8ar/A1v5T6j0Z6Q6g0iUaOpjDEEphZpek8gpIoTGWFcfQ1rjnCWlSC6Fru1ASMZ5xodQswGFoJSEUhKx5v4JWMOg/zW/g65cufKf4zoBvHLlCybHBckzy+g5fnxmPFoe3r7F9B0vf/ELfvXNb0jLjB/ODJcTt/d33H/1hiIgeY+1DiFlfYKX1SFackIbQ9M0zN7XCZaQCGu5nE7Mi+fm7g6j3TpNEuSSiTkzTBP58ZFieoZhZrfbcXw68f3pLVIqdts94zASlpkcAlYJXtzeMc8TQ4w4Vw0Y292Gpm0QuubqIQMxJYZ5RihVb/iyWFeiI6NRGCXXCRtM84yREmMs/WZDOl0YLiOtbeg6i1KgRaH6gAvbzYZ5CUCdmvWbDUpXJ7RzjigTStUpZONcvemjILZbnp8fIGemeabddJzORy7DRNdtIWYyAqk1eS7VpKIVImcoAiEUSkv2d/c8/PAnng8Htq1l07Qs84gSgk3jMNYiY2T2gUJhGM/QNSilWEKiGIVrNTEsYBRaSQqS4CMxZ6TUIAxCZazLIBVGanadZUNkq95i41tkmavvaI2QEWSKEFAKzkLTCMYkVvOIxKj62CnUzEbbNPUFw1KgRGRj8X5Z7y0zVtfUxiJY8//+5bnDlStXvhSuAvDKlS+WT2vFgZsby5vXDf/04Uj2sH91x7btmYaFy/lEYyTt/oa2aXBtyzhNNF1PzKXelq1OUylEnQIqTYyxhiav+XEh5XofaC37m5u1xzUjhCALgWtajG1JGT7++JH379/z1VdfcXg+8MMPP3B7e8fr11/RNg2X04nzoVaqjZcTr1+/prOGxll8CFiradoGpQ2JQsyFgmRZPOfLQKK6YTf9BmMcl8vAfr9BAJfLwCsp6boN0zRxPg/YpuXWNCxhRhZB8DPWtVgKIUWcbSlFEjMorckUmqZBSkFKhnla0LkgdQ1BbpqGsBSCEjV82jimacTHxGWYal2dNhgH0QeM0RhrCTEhdM1QlJ8aSKRku79FuxZr6mgseI/SBq3qn7FSmmazQc1zXefmhBSFME+QE43uKDmjJGgliaJAXjuV13YTpRqMgSwmUgwscWBOB+73EZNGZAkIDCUpRMkgI6Co7TQZYzLaRKIPyOLQxqJUXRGXlBACjDYkAdoYRP5J2FV3ckSq1eD0OdeyXLuAr1z5QrkKwCtXvlgEZInQAW0nQhiZxjOpaL7/8x/47vt37O9e89//3/8tQmaO5yN2d8vkw0/rX2MoGawyCCnp2ra2XkjJMAw0/Ya43nV57wneY7VBidpOcT6f2PQNl/PINAfa/o7D8cJv//l3PD48cXo+EYLn+HzAzwuPDw9sNxu0VoSUiH7BGM3T8cju7obdbvdZDwghsM4xjAM+xBpWrTSn0wWhDF1T19dCCGKIzNOMVT1SCJTSWNfgfUApyTJ7mrZDKogpo7Ul+AU5Tyi3JadE23bMPiCkQklBShFrDTFWcVyjbkAphVKKsEzItQtXSsU4zQzDsE5CZ+ZlQStNKgUjFda2zMtU7yqtATQZ0FJjmpam3zCeHsiq4KyBkomhusHbtq1rYSUZLgOQ632ktIznE6VktFH44JElQgrEFChFIo1GSEWWULRimTJxSZACl/mBnYl0TQNCUVCIbGr+DSOl2qURRWBswtqEGAqlCFJK1FSatc+31EBnpRRz8FiliSEQc1ydygUpC0LU31P5/K8rV658iVwF4JUrXyTrik5aSAMQePHVa15+vef9h488PjxgzIZtv+Pw+AHddsxR8HAc6F2DbVqmySNQ1TSgFQqBXe/T4uI5PB946TpCyMx+pKRMSonGGXKIfPvtt8zzxO3dLSF4XLPhcBj49//0O959eGC4XJimkU3XMk0jzhomvzCNF6Z5Rsl673c4nfi7tkUNA33XUlKkMRqjJTFFMoKnw5ElhCrojCGmglIaJSXDONBoSRGC8+XCL9/8Em0dMWVc06CpLuJSCtY0pDQTvKftG3KMGJdR1JDsxllmH9eKNUkpEuNsXVTmwrJUV6vW9U4x+kC/2XA5nWsjipAIoYkZxiVws+8gBFIBlAapSQl0ESBrY0YRCmEa+t2eJS/sWwWpdrmV1URyuVwwxrDpe7SSjOOFw/MBIw2NrXd4KUaSgrRMSJOoo9u6fkZIoDB7z+k04edYK/qK4nnYctu8QKknRBxAGsiFovJq2FAICkYFurZQngKi1JtJa6vIyxRiCghTzwI2mx5ZQJSCoRB8JIQFSqKUvAZB18miqM1/V65c+cK4CsArV75I1sv5VE0R2nXs7r7mq19r3O4FX39z4fJ05vT8gX/8d0d2r95gNzteff2Gefb4kKookQJBYZ4X+r4nLnUip4ViXAIhBIQQGGs5TReEgL7veH584N0PP3B3d1udYkWQUuHtjx/5//y//39MywlrNBLH+eQpKZDihLWWjMBZzbIExnGkbVseHg80jWMOE6IUNm2D04aCIPiIX/9ZVtepkopcCvOyYKREo2ulW64OVWNsdSf7QskRrSQpFXLKWG2RpUDK5BwoMRDEgmlalDJoXY0JSimUFsRUSDFRRKHrutUQUwWa0RoQnM8XXNtijOH/+4//yJISd3f3bLdblLHEGBACtLH44MEHtBEIVZBSYGyD67YMzx8IMaHXzx9jZJxnrDWM80RTcl3R50ymuoiNMYSU0DljG00smeQnlNmTlKztI6VAjhwOz7z74R3OOXa3tyh1y8M5sLN7XvcbnBogzyA0pRiESDVvHIFWgbaRGFWnfJQCKRFiwiiBcxZtLMfzBWcEViqWecE2sgrFpaxOYrHGmdd/l/L50XzlypUviKsAvHLlX41P+7F/+fT4s45XqSlCk4sBs6W/u0W1t5yf3yGyZgkTox/58btv0e2e4XThfD7TbTbc3N3h2pa2a8k51a5aqSgZpJbklFnmpRoQqHlt/WZDWBZ++O47cko413B4PpARXMZn/l//0//C48cn2g6EEvh5okhoncVPAyV4XNOiUuZ2u2OynmEcuVxGLsMIMaDIlBhRgrpOHUe8D1WIpUIp1TgggJgiTjtiTozTjM+ZEFONdkm5GhCCx9nqArZagwCRCjkFkBD9Qo6Zpu1x1pGLIQtWdzHEOGPWCVsusCwLxiicMWhjWBZP1/fcNS0+RvrNlhAiz4cD+5sd237DFANSSLQyxFi7lUOIFBGwUqPbnt3dCx5//DNLnBFaEpaI0oqYEyJKrGvQxpBjwLQtqRREkfVPQlTzCjmjhCLmiKCsE0TIMTGezzy8fce7H95yc79je78hyZYp7nk437B391hzQuRxnRiuo7lc/xy0DnSdQ0uJyIKwLBgFSjkQhVwys/cEHwjzTGscJaUqUHMihFpHWG8AQawWnOse+MqVL5OrALxy5a9K+Rc/fuI/PSMpOYEUpKyResPu5S/Ya8n2cMtz/xbXG06nZ95/uFCC53/7n/+fxKKxbcNX33zD/vaWm7tblnkCBNtNT6Hgvcd7z3AZ2N9oEjWjTpXE+/c/cr4cudndfo7+UMbw8PAD79/9yKaztC7TNrY2QyhBs8atRB8gBrRQxBBoXINtOo7HI6fjGUMmzBd6Z9hsN5ymBT8t5CI4nweGYSDnXCdQopByqoOoUm/7shBQRL29Wyd3KQS0rFl/Sm8IMZFSjb2RWqAU+JLIySMFWKNJsGbnFWSt02AJoca3kOttnarB0dv9jt1ux2WcSDFirOVwOPL4eOD27oa26+q0lerMlcpQyORSu34RCtNo+v0N2jnCOGGNYAoLJhu69f6v5LoONtpQUiDESCkZHyPLxdMkyVYbZMlrS0cdrWljuAwTzx8fOT0+U1ICIinP+JSJyXHIew7dC9rNM5YZQUIIA1LVrl+g5DodjmFBlETTapQULNOE2TY0jWM8TUAmBk8o0FhHTomUIyWntfjjZ8YPIf+zj+0rV67863IVgFeu/NX52U7sf3c4kkAICpIkFbLr0E1LayzohnZrUe++x9hbjk8HnIzMcyEDl8tYJ2UFxmngcj7zb/6bf0AKSUiB6TIQY6ZpG5ytxofT8zPDcKnhy6ZOs2LJfPftn/njn/6IlIVlGthoTWca+m6DtRpnNJtNj/eRcfakoshSs6RMyImsJY+Pz9xvO0pMLONIDoESE8NlxPvIvCycTicA2laRUqTo2o+rhCT4gNtt2d/cIYT8vL4mF4JfavRNWm/j1i7lnAMiLYAm+YWcI0K7NaeuxuJIqNM7qRBCYtfJX/AeIQW7mxumceLy8Mh5HFDGMk0zh9OJH99/YLvf0zhH9JFMod4WFij161n8DEWjlUbbhnmoZgqtawD2EgJCSuy80DYNAjDGoG3L+XRhnGfarqVpGtqmIRLRQJLis2B9fvjA88NDnehqg3MtMoO2BqksRb1kyp7AGaueIQ9rCHSmoOspoAhseo3RomrCUhtKoK6hlaoB12EuKClr5V5KhFiDq11jMCatWY4Kslwfv/+nfvNcuXLl/ySuAvDKlb8q/wcPomQ91C8lE1MgykSWkmR7mhtFZuSlhN3Ws2kc8/TA+U8HUkjMw0hMhSIEMXqGy5nu+479dodtWkopXC4X7PMz222LkgUfPMZajKriZRxHhFYM44XttuN0sGgkX7+65cX9La9evwAKTeOQShFTYVoisUjmVHi6DHz39h0xJcISud/13Oxu6Jq6PrSmRqEcD08ssydnSCnQNA1CVCE1TTO9a4gxsTWO3W5PzoUYE85aNJHk6wp2Xha0VlXoCQ0lkYInkfFhIaeEkJmYfopqcVoTQsJpQyrlc2tKCLWJZBzH2vN7s+fdwwNaW5QypJx4fn7m6fmJ1y9fI5Uh5ly7gVMmrRE6QgjGeaYhoZ0lF/AxoLRCS8Myre0obVPzB6WkbRw+UVs3/FIr/Ja1icMIJIUi6wNpnmcePnxkHKqRRKAxaoMRPTlmUglk05LkPVHekpBoERFZU/K6RpYCSaJtbG04CeD9QsrQtTcopfC+ZiZqAc+PFy7TXL0eMjFPE1oVhKh/dj81wF1rQa5c+VK5CsArV/6q/Jd0o/48PLcADonDGEtRmoJCaQhzwrg9G9sxqCdi9HTbO17eFv747QeEPCLdwv2LFyzzTM6Fh8dHFr/wi1+8oe0s4+HI8XBASUHjDEJoXNuxjCOnwwHbdGjj+Or1L3jST3z3px958fKOX/76V9ze7Hn56gUhxtqvu9mC0swxs6ytHfr7twyHJ/LiaXvHrrfc3t6w3e+R3YY0B9quIyfPvAwUURBCoqWu8SkSdE5oMrJp2L94iXAOlMBpBzlhmg1CzJAi4+mItraaPFoIqUbbCNNC9kQ/YAUYJCEUlLG1xkyA0pIcMwhJDHUvOq9rXyEUL+7u+R1/4Hw5oYwixsQ0LTw9HOhcz83+hpgzKIWgBiLnklECEBLvI1JaQhHMPtC3ihTj5zu+cRgIStFaS9MopK6DtE2/QQtBiYFxuNDuN+QYUTmRouc8TWTAWoVrWqK2aGeRQuO0ICAIORCRFFpE6SBfKAIQGZQkkxAlYmVASkOR9WsShRoEHgNGiTWce6G1DSIklnlEW0UMGdnU2Jzy6W5RhhqGXdT/Fd9IV65c+a/kKgCvXPmr8n90GpLIGYRUGC0ZJk8ME22n6VqLkHtOT++IOdBuel5+/Q3D6Pnhx/ccD0+4zQ5rHTFmSoEQMs+HA/2mp+t7jucLy7Lg12iUlGoXcEyRlBPOWaTWTGXhx7fvaVvLP/zD3/Gbv/8bpBDoxiJyZkmZ7d0r5pBpnOUyj5zOR25u9vz6zdfMxxO3L/Y0XcvN3T27+5ckZTm9e8CnA6WAXxagBlcrBEYItBR0UqERyKZhd3ePchakpHEN4zAw+0SOmewDJUaEqcHNZMgpIxGkHMnRk/1UmzOUQSRBIRPDgpSmmmJ8IKVMoRDXGzxKIZfEtt2hpOTwfEBImIeZGAJPD09YbRFINtuOTKltJjGSc8H7OkksSVfHcAaCxxmNEqCVYllmLsDtGsBdpCKEBaUV8zgRi0AJwTwnhNXgWmRJXE4Tj8dTzXq0jm7Tg2voNzUTMfjIFBK7nUNpiVIKGS0U9TnbrwigFKTIaJnRRpBTwUgJst5hztNMUgWKocQJLRWtcwzDiRir0xkRUcogpAYkiARxvQEUVyPIlStfGlcBeOXKF0yR1NaGEhDFI7NH0kLKIAs+LpwvJ0rwiFQFy27X8+rVDT9+fEbKwuHwxPF0RiiFazv86Pnx3QP/8Pd7uqbh8XDmfLmQc4dea8IEiq7bkFLmdDkwzR7vZ25v9rx+dc+b3/yGYRgIfqZrGqanJ+bFY2xDTvDi5o6wLOACv/jN3yBSQrcaaw27/Q2b2xeMPpPeHzgPMzmDEpqSApvG0mqFEoWuaWmkogBdv2F/c1MFbUrkXO/NSilVaMVEQdAYi7INPiaEtDjnmEIkLJ7L6YQ1BmscqUCZFcraOtnKGUlt2wipxrE0jeNyieSciSlSqCtXIeuK3BhDzplhGDgcn3CNQcoqtKy1zPNMXCeIMme0sTTOUcqCs7ZG9EwLWim01tXpK+vaOISANhqtFTLVM4AQM50QKCmZponHxwM+C25u71ElkKWiCIEUYLQErXGbDiUDRs8IEYBAvZFU64Tuk1sXkAJ0Xb0rY0hhqfmDMpL9QikW8oJKirzeYPZdzzBd1inzWtYsrhVwV6586VwF4JUrXzACQCZSGpiGj0jxGqN2iBTRsjD6sd5qec90PhNzonWGVy/uQGoGn3h+eqIUWOaIj5BQnC4jwzxjnSOXI8fzBSklm65BW0vwMyknjs8Xun7LMAy0XUNjqmvV58wcIwhwbcNuv+fh40fu716QUiEsE5uupUTPtm1prAWjqk9Wa1IBHzM+FyafGGdP41qyrPErjdNIWZCiUESu4crO1RVnSgglibEKwKbriGte37SMFKlASISSCAHe15YPJaGEQC6x3gMCKAOip5SAWKvZwuosNlqRc2ZZ5tpBnBJ6bQnxfsZogxK1MWOaJw4HcM7RdV0VRn1PLoWUEkVEVMpoY2jblpAmlJCknJBSYqwl5sw4TWhd/2/ZWkMuCesM82lgaztc32KtZcnV1SwAYy1WK4yyaOeIUUBM+DAhlMMYiVYCJZa6+i1LDWgpn8T+z+/06jQv5UxOBb8ElEoYqzDC4b1gmBZ0UjTGsPhSp6QUco5Iybo3BvL19u/KlS+ZqwC8cuULRgCkgBALKR/J5YTRN4gIfh55/vAj0+XCpu3ILtO7Htk6EJqm2zLFzO+/fwuqIaTM83HAWoUVgoenZzabDp8zPmbamHCptkssITH7iG0aMoVhGLi7u8VPE85Z3n7/HZtNjyiZ8XzicjwyPB8o04xSmsHPvPj6JZuuOlelECyzR4tC9pGcFMfjhQ/v3+NjqGHBAjZ9h1YgVKFpLVpJSi5kBMY5hNZMy4Jzjhxrb66TCqTC9RuEFuRSuIwj1lis0XgfkKrW2wkSKeR6ayg1OUc8AikNUghiLMTgKSmCEMQQqoArqVadKUVOiegDzhi89yil0EaxLJLz+YyUkgKEGKsxJmcIARE8IiRygbS2rhijUVITYyLFQOMcANM0kkuNpdFKgyj4sCCDwqZMERGrFI21DLnGz6QSKTHRqIaSa+QNUiBKwUmPFSdEfqKwAOt8TsjVDcza+5yREgoZHxMxBVKIZCsxrUYgIXdcDgNWK6SSxJwIYUGahFI1U1CI2txy7YO7cuXL5SoAr1z5kskCyCgV6TeZ4XIhjk9Ml4mH99/y8O4tUhial69J80wqiVZmOmexrkG2PYfhzPNpxhrDNE+gOhrTcriMSGPJ1G7X87BgrSMrwRIKyjqapuHjhwd2+z05Bbquo+t7bE5sG8vTwwdsbhB+Ji0DIUeEsTx/eM8yn/j13/0tYwgMlwvhMhGDJ+fC5v6eRTqUgHE4Y4wie4GUha5vsFbStQ0qFXJMNE3Dzd0du90OLyXzNEHOFCmZZk/Tthhl0FrXe8fVxStl7Q2u7thC8B5JYQkzuYDUGtMKVCMhB6KPq1E7M00zUirapmEYJ6ZprmItJbquo+97Qgh47xESpBQMw4DSGm0MPgTatkVKybJEkvfomKBIhJA45zBaM88eKSXWOvq+RynFOI/otd6uMYamscQY0Vqz+AVfMu1WsGkb5jGuvcQZnQpaCrTKkBVaG4zJ9HaiU4/o8owkrOvf2vZRhWABkRCyYGyNb4khoHU1cOSUa+9vVKSU1tzCKmJDrCvyT5PA6gJel8qiPn6vTuArV748rgLwypUvmSJBQkkLVs+M5cjh/czx8cLT++9JfiCieHs5sSyem/2Gc6ltHEuIdJ3lN796w/Hf/47kJ3yQaGtJSTKMAWsCGc3sJ1K6sNlsMNqBtrSmZZonQiloY3h4fOD/8T/+D/TbDWkZIS4YEtPpgAZEXBjnkdJ23G17UJLldKwBz6czaalGDB8C0zIzC8Pzx49kv6BkYdM5RErkFBAYusbRaMMyLUjX0vQdaTVnKFWr4pSqlXYm16gblQNKafa3twQfSMEjhGCaRmKMWKNRRrFMI8pYbm5vGRYP2ZGCgFJQUjOnWl5bQ6k1StVpH0BOiXa7IecaowPQeEddg2ZCjPSbDW3bcjqdaLsO7Ro0GaMSsWmJgybndT1MQVuL0po5RHKKiJLxS8RaSwoeP89YZ0kpoZQmBU8MI1q1tG2LKI4UJvw0ka2otXfGIaVGp4leP9PJD9h8hBKBWsNXRRoUAUUUpMo4K6EEIGGVwzlH0whynFiWSFgWks9oBNY60ir+jNVoXdfuRQjEp8nilStXvkiuAvDKlS+YImtYL7IgskeXgThObF1P+9Urnp/f4UPCuY5pKGx6y5gktmmJYsE5wy9+8ZrRR/7dv/8DUhREzkQf6bqOeQrotqEAwzQRcmHykZBBF8kwzJQi+fDwiHGOfrtlCTVbL4eZnDMpRmKK3L+8Ryvz2ZQhtSb5SBwX0hKZpxFZEssy06fIu48f+fbb75kWjxGSVms651BFYpDIXDBaIVqH6np2+12dthlL2zSEZUFozb7bABI/e5q253wZsKlQiqhfh4RlnuowSsHleCIFT9f1jMMFoSzezyAzzvUsuQYsy6TIhdrXO06kXDgej/R9j5SSy+WCMZa2bWiaBmctKWWenp54eHzEGFP/EqVgu72lt4a7ViK1ASXxISKoK94iFD5EUgjMZFpn2PQdFJimgcbVKab3AZFKvV3MAS0a/DSilcKthg9NnXpK6ZBZIMuJVj6h8gOCEVEKRdQ1tZB1ZVvdzglBpLGKGEa2jUMryX67wapELBFY1niYmh2Yc6JQnb7G6OoGLp+aQArVAfyv8Z1z5cqV/z2uAvDKlS+YLGqjhCgFkRf8+MxwVjhtePXml7z61dcM80IKtdl1mS44JJvNjnGakUajnOPf/ttbuv6W/+l//neEuEBqWKYRITW6ZKy2DMPItASmaaJRiss4M80LMQTGceLNm6+xTcd5GBAiYaTBtBKhNQbQ1qKVJvrAw8cHhmGkdS2X0wWjzDrNWmjalqZtkerEOE7MPqCco8hqulDSYG2LUhqo4cJGa4y1BICUGMeB6AMJ0E2LdR1KKrz3LD5wGWaEgL7pWKZLrYZTEj+P1eksIC4zWrTE5DHK0DUtsmnJS6zO4aWGYs+L53Q+EWLm6emZttswXE5Irejb7rPrt3y67YuZcZ5J6VwDnL3nMvyWFzc7blvFq42mE4KYC42QdbKHQAoDOZLXqeXlcqFxbc1/JBJzouSMkgWnJVaDzQKjIKZAyJnGVkOJ1Lr+JsPCtpvpzQldLoiS1no2Pps1ql4rn6NaSi5oKUHAbrepq+75SCkZAdWVXASyiLV9pbafUApy/ftaQwb5KdPyqgKvXPnSuArAK1e+YDIRiai9rzKi5EzOgjkEbLenv+8YHx5gKdzs9jx+fIfTFutail7wMXA+Dyjt+G//239DjIX/9d/9O0qY8HFCCEWIDbrf4Izjw8cHutbR3t6wDBOn0wVrNE3T8erVa6TRSCyu6Widg+CraKG6OEQueH/ichn48P4jm35LjoU5zSxxQYrC7YsX3N6/oj/NbLY36Ll+jMu8sASPUIING/i0ogRSTghR6t3f2i8rpURIyThOONcRU0IbTRaKkDKUTN+2LH7t+BUFJSRGS6ZhQKnA/uaOIDXS2LoGpXbrypRBCKTSCKUJITL7WKvxUiLlwu3tLSklfFyYpqm2pghBptQ7Pe/XLMGCQPH48MSoItvfvKFp6y1dyhnvF8Z5AaoL21lLzoWwBKTQtE4RYyQXcG2tj1NSIEvEyLSKQYVIHlEiKEMRGVECnRq57y848YgsMwBFSHJZnbprZ68QgtovUqemzrVIkVdhW6opJSwgBNYafArEpVbYSalqfzGrkKSsIlNC+VTNd+XKlS+NqwC8cuULRiKQUiFyoYhAu3FYB5fThd/99nf43wfcdsOLl7/ghw9PXA7VEew9nMeZp8MTs18Yp4W+3/LmzdeE6Hl4fCDEhI+Jy1xXv9Y5no9HmuYlQijGcSaEyN3NDX3f89VXX9H3W4QoGGshBZCGEBZS8GgpmeeRsHga69BS8Hx45HZ/z2mYaPoG5yw3L17iNnumOZGKJIQEJZNzJpcqbmfvCdHQuhq7UnP4ElkkhNKfhaFzjiQkRilOwxNm0yNywShNKZmUYm35kJp5HNhtWlIMn3PuULI2f6SEjBHrQCpFymBtg9KaZV5IpeBDIKTIsgSMcQzDuBof4On5ee0UFrVWTUi89zw/P+N9YL+74Wbb8+bNN3z95g15fCQtJ3KpK3ktFbZxdF0POeHnCSlr1E1QEJYFbQsxJ+LiyY0mhRlpt2ihKAK0lAiZKWRCDtg80TcnevUDKr9DZA8YECBFXre0VbhLFFWwaQoaYxqG4xPP4kgIgmW4oPBIYVmWhZIhhEAuoIyrgeGl3kxSPq19PxlArly58iVyFYBXrnzByCJ/ZqJc0K1js1UcPz7z3Q/v8DLyN//m33ARlh++fcurV3c8fXyPcR3/9Ls/8nweePHqFT++e4fWhj/96Vv+7u//ln7Tcx5GXNPx+Hzm4+MBHwLOWawxxJzw3rPte5SUGGPY7/d1DRs9zjoe3j0jSqbkiDKKnArn52dUiBACWoA1CqEL96/vaLqe2xf3vPr6F8ypmjekMDXTGoGQCiGqg5dc140pZ6w1YDRlnSZpJckhrhl9CynXmBqtFDkuGFWQZIQUjONIigmkJOVCQRJTxjQdQhuGaQGdKUJjrai3cYUqirRCILlcBo7HE+fLiFIa18CyzGipCEvg+++/I6XEZlPFW1nNKY1t+Oqrr4kx0toGo+rEcloWWqWJFISUdF1bc/dKFVViNZMkH2hbU2NwckZpXdfiugYt5+RRIqOEZAmBQkBpQCWEiDi9sLFPNPIHZH6kziY1kBAiI4qqAdBlXdIWScqCZY4sPnEeRi7nM/e3gb4taAnzMhHDjCyqimapEUKSc1znfOXzVJF1KnydAF658mVyFYBXrnzBCFR9/pSFQkQ1hZsbyw/hSDyf0Vbw8Y+/59l9RCqLP5/4/ts/0G1v+f67b5kjnIeJ8+WCcw0A58uFr795g20ahLJ8880vabsNv/vTn9luNjRNQ4oRayxaa0rO3N/f45qGtz/+SEiBu37Hw7uPlOQpJdF2LUoULscj0gecEuw3Ped5pOksty9ekqWm3+9oNhsux5GMwMcECGLKUCJK16M0UQpybfmQUqKMoZSMlIKu7ZjKyDKOUAoJwRRHWmNYpgEhFfM0YJ1jmWfMuqa0rsHHjJTVeDEtASsNrWtRtiUjmOcZaZq6Ds5wHi6M88w4TozjBEUwzwta13aSt2/f8vDwyH6/Y5omlmliWWr7x93dHff398w5czocaNsGuMU5x65pOPlz/fNdu4CbpsXPM36pX7OSkpwz01Qz/ay1LPPCbtNjrWReZrAB1hOB6D0UgTQGJTOtyzh1QvOEECOIhpIlpQTUJ9UHq06TIDXBF54PJ06nVIVdiUzzhFMSbWoUTF5X7VpVk8ynda+UNd7mP+YqAK9c+RK5CsArV/4C6qVTXUTWc/fM53WXWKu1ymo7/XwMv9605QwkkFSV8dkpWdY7NEFBAQpJqL8qO0RWoEZsN1CagaANp6eBXYbNRjBPke/+8HsOo+fmNhGnEa0NH378gclnfMjsb2/5/sf3PByObG62aGN48eIlt7d3vPnqjmGY2TeOw+GZxhludj373ZavXr7kT7/9LX/6wx95df+St8M/1wo6PNYoyJG7/Q0SiCHwy1/+ku7FS37VtMwhcffiHmUlPhQePjzwp+/fMZwPdI2iFMc4eESRn3P7Ys7EGOhbQykSrRskmiVEjuPAtCzMs+fl7R2PHz8ghMBut9jW4UONKtHKYLQlJE/0HiVFnV46h0+FJARFCqQWLMtEUhHlqks3pcCyLMzzQsyC87yQBMTsKSSkNnz88JH3Hz+y3W7RWnM5X0hr/6+UinmuHcsCBVpx//KedtNh+w3KSIpoiAE0iUICQGmF8mCUZAqJ5XJkt+3pui3BB4bLEcM9ORhoLGn4wK7Z8cNhIClDlh23yfCSI1+1f2Lr/j2CJ8BB1ghivaVcH3O5FKRMkBNZOIbF8Pi0gHiBUJHWQMqeIDZYJLum4zQcUMLgiSxhppSCaSXOaZCZLHINoc7rnaGQVw145coXyFUAXrnylyKqO/c/eAN8Nj4WCkJkPj/7lVTPo8Qnh6QA5LomW3/hOg0SlCoOJVVD5giryHTblu0+kcJI9oHxdMaPgSUWhnlmWgTj8JZxHMlSoZEoCiVmRCyoLPnhj99z/+oFIUfeffsDX3/9Fb/45peY7YZ5GpnGgRe3d7x584aucTw+PvK//S//K8s4MZ0uLNPM6fSMazVhmdluWg5PxxrGLBXa9dy9eIGfAjd3d1zGhXwYeTqeWELhj3/8jj/+7veEAlrVyjO1NkgoXVeTMVcjhpASqdS6AlU/1acZzfF4YJ4m2q7DB4+2jnEY0dqhlWIcJ4QSCCFJKVF9JIJcMlLVLL5hGIkJ2l1DLnXFvCwLz88HLpeBx4cHcinElCDDZrNhXhYeHx/puo6bmz3jMDAvCyUlcs4YYzifL6SU6/vc3WCtJabEvCzs2y2u25D8hZTXlxMp1ZcKORODXx8OhWmckBLarsU5i/cLSknKUivmTCNJS0A1HbYYWn3kZveOrn2L5FQNHqW2iYhVaLJGt3xmjW+RsqCUQK0vQkQRLD4QfCRS+4xrUHYNss6AKPXjaKWQUlBKXh/762O8XO8Ar1z5ErkKwCtX/kJE+TQH/BRzsT6plrqSE9Rstc/xGiKtYq/Wb32Segixvov4/DErmZKgaBAiUWSBkjAONhsNacIUgQyJkCaWmEk5I1BM44iiVpk51xHI9NYyny+0jcULyfB8RDtDkvDuz9/SaMvNq1cUUWNNXNNAKQynM3/+/R94eP8eLSTLMDINFxCZFCBGTwlVJAghuL25Q/7wjiUktHM8H8/c3t9zefzI0/OR3d0LdpsNfdcwzoFUctW5YtW7SqJMXX8KFEIptDMoYzBSI2S908tKsvgFbQ1SSXJOTHOdDN7c9OScmf3Cbr+BLJin8Nn4mnPBmCoKYwi4dkNKGWkVKSYulwHvPcfjkcvlQvCeAqQYKTlzOZ0hZ252e/xSzR7zNFXx9imoehWC1lrCGqWz3/UIZbDdhv3Ll4wPkZwXtBB4vyByIceIVBJtLNNlpORMV+qdoHOW6COlgNWOMWZMgpvNhmUpbPG83H9kt/s9Tr9FxBmyXR9ngfoiQq3Zffnza486o84YLXBWsAzVmW2MISyJ4CNLyVjjatVdybWHuWlqTKXwlKoMV1lZfmYEuXLlypfINar9ypW/AFE+xah9EmyrCCzryrem5VLIlFKqTCyGUiy5mLriLbLGZny+xRLUJDW5frxEHf9V8Shk/XhCRG7vG1683NC1DqtMfSWXA0YJhExIVd9Py0RKM34ZcFZAXshxZrdpkCQkGac1IheG4UKKqfbSpipPw+L58PZHHt69wyLIoRoPWiO5227QZDaNxUjBvuvYdz1GCFIInJ6fyX7h9PTIn373Wx4/PrDMM33bsttuubu7Zb/dIksmx4ASNWOubRs2mw1am3WDKDGu3uXlTxPXVM0iTdPQbnrUWlnmfURbg1Kaaa5dwXX6V+rmvQhyKqRYRY33kRQTORXGYcZoy2UcOQ/j5xiXaRyJ3qO1IYaEKAK/eLabLcYYLpeBZV7q9FaI+mumCe/95xvGT5VwUta7uSUXdLtBti1JSHIq+NkTZg8p4ZeFFCOz95QMMRcen544n88IAcEHgg+UmCnR8+puw00789X2gZf7dzTqe0R+rlNVVH08ibSeGKyOX7G+OCm5PnqFREuJIkMOiJJwpvYNxxBYpolSMkpVcZ5SglLQuk5lg6/uaiHX2KLP0/GrCLxy5UvkOgG8cuUvRvyLjNufP9F96kaFjEGKDiE2UDQ5BygRISOiLGtWWq5PyOtkpnxShUJDnuv7SI2UCkTm7uuOv//vO/4oJo5PJ/J8wpW66owpESUsMdC1HUvMGJXJcWazsZSc0daQikRoKKKumsdxxEdPXIVpipHnj4+cHp/BR5ySlFjIKUFJ5OTZbto1/kRSUsHaBmMMTklEDDw/fEQ7xzTNIODXf/O3vPnVNzz/0+9pG8fiA43VlFIz8PquxRqDEAIlFAiJ1JZmu6n5f0IiCizzvNaiqfVHWbMC0Wtfrl+nn5YUAikmtFIoKT8L8iVEXNPgnGaYJprNLUjF+TQwjhPn45mSE09PD3TbPaRMCBErNdP5Qtu2nC8XlnEieE+M4Wdfz0/xNSlFXONQUhJCYAkJn6Df9Jh2y3Q5o4VEC0VIM4WMVJBLwhhNyJlxWqBA03QYrQkhEMcR3fcswxPbjeblLyM3/Z9x6iM6LYisgU/Tv9WlW+Tnx9jnCeD6IkQIRQ6FHBJWidpZXDJKCGJOzGFilIrNvqFkgfe5PhaURghqrd3PHcAlU4Sqn+f/su/BK1eu/KVcBeCVK/81/EdrrrKufTNFCnJxFLlH6FuEegOxwc+P5OWCFgtKzSgzgp5ALCDiTx+4fFonA3KtrwAKCd1Gvv77N0i75cP3Tzz8+Ge684HpPJG0Qah6J2ZVvQFMVqONQWlTn6xLIVtDLOuMUSkulzOn45Fms6VxjsePD5iUWM5n/DiRUl0h+jATlxkhMq20NTxZK0KOlBjIwJQTTdeC0FxOR7RpuH39kq9/9Q1ZCt59fEci0XWOFBqs0jiraRpL9J6JjDCWafbYW4l1DUIrnLZ4n9fOXrl26dY/r1JA6rrU8CEgJWgJ0zTVBf0qdupUsAYcu7aDHAlhYesa5nnhMozM88I4TVxOJ8Zh5OWrrzieBjrXcjg8I9Yh73A5A2V1KNfbwfrXJbHW4Fx1L/vFs7nZYa0jp8IwLdzsNnS7W5bDI3mOWGNI0RNCQCuJzIG2daSU0coghCalzJw8OWUa20DyJCbiIrh/M+HUH2HtUhbFUid9eT03qCcK4vMLjDWoWUpEhpKrwzmFiNWKksFqiXRglMULDyVQiiXE/Hm6KUR94SFVjYSpk+9PTcOCUsRPZ65Xrlz5YrgKwCtX/mI+rWpXJ+9nR29eT/sMRW4p+g00vwZek3zhfIS8NKgyYdRIt3HoTiFNgTLXY7hcP74otQf48+crAIEiZuxO8vI3b2i2X2MazfnddzyGd+QpoKyhNxqhFKI17NoGqQ0xZmLKhJRojGQOkYwEqeiaFmJAlkxYZg4PD+ysRcVAYxRRKMI8k3LkpmtpnQESWkkaLZGuW3PyOoQxLNFjWodtHK+/fsObv/kNN3cvePfwkWEcSLlOyvquwWpNYyyNM6QUa8VYzsxL4FZqcgEtFUooREl0Tb2JS+v6Uq4iRGn7OS8wp4j3C94HlKzTvwworSlSkgvIdVUspEZIzfPzkcs41dDpnFm8Z7vd1CFZLkQfWaYJZw3TNLDME23XchmqoOy67nMbhtYKrTXWWNrG0bUdXdOuHcGClKFxP8XP6OyrgUIUQk4YFFJVAZVSpJTMPNULPoSgIZOSByLL8Fgr5OSAKIo6+atnBOXzmFqtj6NYxVkxrFYlcskIkTEy0zjBkiLaKNrGkrUgZkljMiLWqXZd/4o1xqbeA5ZcfvYYZf2+kKsZ5GoDvnLlS+MqAK9c+Qsoa2zLz/l8/L4+qSYsyDu0+xswf0c4CIbHA5eDRLNBRosvhhQMLkm6nQV5Bpbq1hSi3m39B59hDZ3JCyGfUa3i5a/eICV8lJBjwZ4PkLt6gyZFrYUTCte05FLwPnAeBobZM3nFMEUenw9s7xQb5ygpcT4dmeeBm8agFajGEpZETopOGzYStMz0XYuzmpwTzjW4tqfpe0zfI61lSQXbduz2dzSu4XK58Pz0hBKCxhqMVBQtcdrSOFvNqFhSSeSQKAiUMbV9Yp5Runbt5pSQQtBtNpwvF2JI5FzQRhBjXbumEIilVKEi1WoAKeRcEEqQM8RUiEWgrMPHyOkyEEL83I/bdx19vyEEDwKWpYq/HD1h8Sil2O/2UOD7tz9gra3TwNXY01hXbx13e5xzWGNoXUNjXRWsa5ByAaSSpEL9mnMhp0zbtQRR20ekgGVJyJJpu64GXAsByePHTPQgnF1NR7Hen4q8VrzJVRiuLuACIClCQ8oIWUAsbHea3/z6ht//OWGsQisJQmMQeAJSlvX3KEkxIyTkVFBSkTPkVG1R8rOxPf/0OunKlStfFFcBeOXKX8zPj9w//VMnLqVIcrZod4dw3+DHWy4fPzI9PlGWGakUZEmILf4kUcGQ5T1NP6I4IOQRykBZswX/g8zBAkoWWpv4+PQRUXrc9oa7b36F0ArihcvpjPeetm2r8MvUAOQ1SmWcZsY58Xy+8Ph4Avme43gh58gyR/wyYaxGaUmjDKJksog0qkcogVWZvm+42W1o24YlBmzT0u32tNsdtt+CbchSIXVDzJkPbz9yHgemeabRGg2f17DOOjrXgCgsy0zGUEypncNdVwVGTJQSyLlGjbRtzzLNtSVDaUKo1XWfnLqfgpRjjCw5Y60ll4xCYBtV68tsQ148bb9lHBfGYSKGSE7V5KC1QUoJUq5GFUkqmXkegYQEjscjWmv6rmdeZhpr0VohhCDliBJgja4dy43FGI3RGiUkQlTjiFI1SDmHmgVptEGiMUqz6VoOpzPjMCC1whhF33UoaylCUCjEZSZOwMZQxLKak+ojpoh1Sl0koqy+P5GBuN6wSpAemFFq4quvf8Xvv3tcDUsCRTWvxJCwovYSyzVQJud6tyrWMOhqtFmjjT4N/q7i78qVL5KrALxy5S/mXwjAT1OPXBBSoaVFyBYWQThF4mUknJ/J4YxoDRSDUg2YDVkIxknh88B2u0fLd1A+IMXE52dSUSM8KJKSA+QzJTwT4x1FbVBtz+u/+TuUTJwOB5QSa+5dnXqVXPDLgpSKTbdH+UR7/xUvvsm8/psL3377PYMP5JwJMSIFSCVobYu1BpVbpBRoo7G7jtu7PU1jcW1TRa/StNtbfC7YvidJTUIyjguzXzgcDhSgMZbdZkuMAUpGKoUoBaVBKcM4jcSU2G623L94yW63QRpDEjDOIymBta42bqSMkZqMwDlHSBlnLQKNn2esazgvF4Z5pG1bUoh1rSoErq2RLLrpUcbx9OEdz4cjISdijDjrmMdpzR4s+MWTUsD7mZzrini77Zl9YBgG2qZZ4/QyuWQabUjeczoe2N3s0XJP0zQ0jaVpan+uSTMCyKLeLeZSMNqulwUCretEMSwz1mha6yg5sERPS4+QGplAi0xOvj5GSq28++z+JaxB5YWfgskzRcSaMSTXW0AViX5CiUKKgRgK26Z2K6cYIBek1rXvV9Spb6EgpSbFDEaumUWrc/2q/q5c+aK5CsArV/4CPk1YPmf5/fznpKyBz0CZRpbxHX7MqOKRIlFSxM+ZVCKJglENWm1BdoxTh9Y9vVKUIpHyB+raLq0u4fokLmVGyIWumVmmmWGsAmp7d0vJcN/f4peZ6D3zNNcQ4sVjdFvz9aSmaRRFaBpRaG7vUG3Pb3/3R+bhgjWWmCI+JsxNx8ZoOqPp+462b9m8/qpOAq0GATEnUpG4fsMyjJzmSL/pOR2OvHv7nsv5wnw+8/r1K8ZhxPsFYzUUsQq2akZNKX526iqtMI0hp0iJHqj/LYTC+ypkJZKQAkLrWieHIKVEjoF5XnAW0vp2rQ0pR+Tq1JVSEVIhFMF8vnC6DOScq3M3RARwOJ04nc6r6SEhKShRxWaMaTWUUPuKKfV9pEQpQVgWGmdpnCOt3cVKCbRRGK3QUpJDIoQFyGij65rXe0ouuL6pq2BRv34l9VrTp+rnzgmt662fUhZYgLg+Kqvpo2ZRijW0/NMj9JMJpL6wKCmu54ESpR0xFHJWq3lDkEti8QtKabR2LGmi5ESMAalASl2npNS1uuBTn3KhiE9fy5UrV740rgLwypW/mPK5BaEI+flJVbAeQ6WF6A+cniQlRAQarEPmLSnXo/ySJZlCSB4nb9DaMV4kstQVneofa1yM8CDT+rnWJgu54OxMGC4YJAjDux/fgrBs+h4/zxit8THhw4g1hqbrWJaFZYm4vke7nssyo7Th7rXhzRzxf/4WHzMET9NvePXLb3ix2+KMpulabNcgpWHxM0UJComMIoSMipG+6fjw4x/54Q9/xo8zzw9PCKno7m949eZrvv/uO7TVuMYhAK01Wkn87EkpYa3BFkPXtTStI8WAUhrrGqyWoA3L7JnGGSXrinYaR5SxCKmZ/cI8XeokLFcB2PeburqUkiIEUhuENCAURSnOxxEhFU3b4i9nYoyQa+xLzjUuxVlTHc+bDefLCSkFogjcZgPA5XLBuXrzp4Tg++++JedM33c4a4C6VhZQf60QeO8J3tNZjVOK6RLIoZpcBIKSMyHMiAJaGsbLjHW1h3j2M0YIZEm0Yo3iKZ+Ws2u00CeyWSNgYl33CkUpDULENb9QkZMmJ8OHD2es3mCcwVmHVJlcFKm+a/08sja05FxX7kJKQsgE/ynKaP0OKQUp+exgv3LlypfDVQBeufKX8PMnNMHnKcvn/41YBduESBdyPJHVFtPtUXZLjqClI+aEcJqsBDHNGNXx/DixnD3OOozpsSYgVaGUZY3YWO+tSkCbBWsiy5QoUeMXz83tDrGGEueYaJsWYzSFmtO22+84XwaeDk/sbgTaOko2sGS6bouzLX1bkFvB5uaW17/8Na9e3AOZTCKWyOXhGec08+TRRuGspaREWiZyzLzabcinM6pkggKk4OUvvmJ/f8fD8xP9vEWs0SmfqsKUWh2kuSDWJhKtFItf6JsWZw1LivgUORyeMNqhneJ4PKOMRVnBOA7Mc42p6dqWnOvYq20bco7YxpKExFiHUJqM4nIZ+fjwUNeYAnKINE3D8flQbxSbBikll9OJ4Gda1xB8QCtFhs8C6OuvvybGiKCQY+L169c4Z+i7lrvbG1rn6ra1ZEqOpBSIMVBKXkOfA2lVWUYZtNHMy0xMHq1VvYMs4JxDGkUoUHI1e6RczS4iqzXgOSNE+unG71MbofiUN6koWAQRoapgE8Iwz4UPH0449xtyrkHYjaoTy2WaCRFsU9BK0zYtMa2xN0IQQsYvabVAwdphyL8Iy7xy5coXwlUAXrnyl/BJ5IlQj+tRP5WBFAlCkfFId+L21ZbLQTJNBm22RA0+LeAcbX+DXwrL5cj54S13G4P2B5Z5QTnHj5fXvPoq0d8+kWWiyBldIiRV4070BdmcCY8NuTi22y191xFjou065nmm6VpC9MQUCcFznmeUNey2PclPCAWLr7VtRVnQFiEmFr8wp0y0G3L/ApkTMoyk4xPW1Uow6zQhejJgnCbFQFg8QsL+/p7lJnPz619RhMD0HT5GFp+ISdAYu56fFWSuOX2SQJYS2Tps0yCyIMaEVBofAsF7ckrkZUYbw7JMFFHIAsZlZhwHxmHgbn9LYx0heDZtvZuzziKNJRRFVg1IyzjMnJ6ri1gIgdKayS8IBNIYkNA5h59mgl9ASi6XCwZBlgKhJEIqrGvo2paSq0O5cQ1aCXJO7DYbXt3dobSgcRpFQBaPFg6cQ2rHfDnj8CgJttHVcVskWmsaa8gxYBRgaji2kga5tnhQEjFrfI51zysloOthYUkgl5oxKTWgKTgoComnCE1JBsFCkYkxZdAbdFHkFGhMhxUdS6mPk1IkFI9fMk27BSJZTKRgEXnP6Tjx1TexisDYInUELoD71/pOvXLlyn+GqwC8cuW/is95Fz+9qaxTD1EQIiDtTNcvSKuRdgOiRS8LPs2UFDFSkEXhNIycfELEyOV8Isya4+XAfE788m8lm9c7UvbEMteTLQFSJKzNNBvB6BNzXuiDRwlBCQtWFsJwZlpmjDU4UR2bfvacHg/My4Lb9BTrCNlTkkfJwjieUUZRcuZ0PPHi5VeUlJAZija0rSIEjyhgpKAIeH4+EEOkZIE1Df3+Brdm6c3LxPn5I9425DAiCYSw0DiHNrr+upIoqub0tX1Pt92QU2IJC8+HB7rtBomkSAgxMk0L2jY41zAvAR8TOUXu726wWpNzxDUWlASlyMoglKuBykWwhMDT4ZnT6cg8L2itKBSUqBOxdx/eE7ynMVtC8Ow2PSEEphgwXQNKoo0hpkjOEJaFtmlQ1nFzs8cYRSmZ+5cv2d/dUUgoXQ2yWWoiEtN0tP2W4/mB1lpEjsS4MAwnUt+y327QxjD7hVgyWhu6rq/2ClGIMSCEQkrDPI+UoiBHoJZIl1x/z6S03uLVxyTUVTSlIOpYEiE6BD0xw7LMGAOxZBRVPGdacjSUXBCyoI1kiTWnsKw5mPMc1jW0+Kll5Dr8u3Lli+QqAK9c+Yv5efzLzyqwPj3RUoAFoc7Y7kDK90QpsHKHaRTD+Mh4eSLNI63SNEKyXM50jSIsE+fjzOW8cHoYEHnHb+wed58R8hmSr9OdEjA2sL9v0f6GOQWSzyzLQkwBJQQ515Vm8L6aGTJYqeid5fnjAx8/vKO7uWV78wpEQipQRiMkzMPA2++/p+s23N3domVGKIltLZ/6JYLPkDN90zGUmRALRRkOl5HgF8bhzNPzA6VkXr56TfJ+dZp6hDAYW6vbxBr+HFKmEYWYq/mg1tSd0VbRdB2X0wWtNZnC7AOlBOZpQSnF/e2+Zv3FRNe2NaBYSLTrSMogbY9A4WNhSTOPj48cDgeapsEaQy6F1jmenh45Hw/0XY+fJlQRGGtQArYvX3A+HPExUHImhkDf9Wy3W1JK7HZ7mq6haRw3dzfsdju0bSglYRuNVBKpFUVXU8Xu/hWnxx/JBHIKpJgxumYi+mUmBU8KnrZpsNZRAGMMQklSypQUSalwOs34oDBGIoVf3b2QF4FUdn1NEqsCXbMBC6EKwgI5bRgujmUpTMtEzplBXogq4JxEKw0okB1CZoxVCLVhiYoSFCUmFn8kF4uWikJG5HW0e+XKlS+OqwC8cuUv4Oce4J+/BaiiY52IFAKFI1JqCluW0CH1BqtucNox58A8HikZGi2YpplhTvhp5ng84OeMAt5/X/B54vXfWm5fvkDLASkHEB44I9SMkA1W3VPiI3P2xJBRErQSnMeB6ANSKhrbsMwziMKLl7csb2c+/PAjS5SMCcZlwbYNYa5uz6eHj8Rf/wZRIsPpwH7rmJcFHxac1ihRIAVaLcEYolGYrmecZ3JJlJII00yzvcHZnnF6hxJl7ZMNtK1cXaSQQ0ZrBSnx/HzCNS3WOobLGT+NLPPMEtepklDkVNBac3OzZ9O3CKXIOSE//c1IjbItRTmKbii6xfvEMI2EMDAMA33XAXA6nWiahhg8x+cDp+cnNm1DionWWeapdv4KYzDOcfvinmEY2G42dE27rps7tBIYrdjf7nn11Ru0NSxzJMSMFhqhFUUZsqwicHf/Amkc0QeMUGilaVyL0rUphVIjZ3IBbU3NHNzsiDESbaJkg7WWEDuGRbJTA0I8QR4RSiOkROTq0v2UzFKKgeIQSgHVYT1PGz4+QEStaTG1VzqnASFblNC0XcMUItaBUoqm38BZ4UtCykKMmmUuqF6tYhN+aiC5cuXKl8RVAF658pcifgrT+A/XXBKxSpBMpOSZwgktH7Cqg7hjGiNhGShxRotEXEZESizLxPl4ZJ5npnlm8ZHWdEi553KW5O8Cjduz228R4gOlfCCVJ7QdUSESg0DZBhUi3W5b7wRzJEwTxjhySqBAGIFC09mOr/kK25xR/Yb5MjMty2pOKKSU8MuM0YKHdz/QNxJTFEtK5JSZwgjeU/zMPAykBLLpkGvwsbUKKQr3L1/z8pu/A8DnP9FqgdSy1pxlUNqQQkAbS7/dUKSsGX/KMY0n4jq5nP1Ct7slLQmhHLapAcxKCcI0IXKm6zrGcfxpAlbA2oaEZV4yx9OFy+XCMo+M47hWlYE1BqsVYc6Mw/nz9E1JxfPpgePhQNe1JNegtCHnzH6/xxmLkhKpwPuFUhK7/Zbb2zukUsSUiQhSEcQskKjqGhfq/9/eewfbdt713Z+nrLrbabdKupJwQRiXGDsYhfAyb6zBIX5TPRmGcRKHMMlARAKBYYA0SAEzyUwyKcRJSAKZSfGETCCE7hgwgRg3bJALsmzZqredtutqz/P83j/WPueeeyUXZCRd+T6fmXPP3muts/faz97nru/5le8PY1M2t3coh2Pc4Qq1Hq+GeHzXoRGs0b2hd5ailCLPc5LU4r0nS3NCCGRZRhs2uHrYUVWaMzsZmkPwLRI6tHao9VSUflyb7T+7IQFagjIsVzmzhWEw3sB1AdU5skRTV3PaxjIshlhrcU2HEYVWBq0SrMkISYsOmhAKqpVQlhZoEJX03e/RDzASuemIAjAS+f2mnyMGSvUzZiWAdFh1SK5TfFdSrWY0K9cLP9dB6Dg8PKCqlszmy94exHW0rqMsBySDAp2ktE3Lk4+2TMslp88Z8q0UJS0hTOmqyyxmc6wV0iIny1OWqyXWWMrRiNDUuLbBrWsEsZaqqnpzZMCgCF4IAZqmI7gOa7P19AdPZjSaQLNcoPOCsihoqhWt761AquUCHwLae3SWYWyKSQu0thTlhOHmNnt7e2hr+xSzdFit1p26CrQmy4p1d66Q5zlaQ9v2KV6lDTpJMTaj0IpyuIE2hrbpffOMTQmupW0akjTFo6kdlFmJ6BTvFIvVkr29farVkmq1ZLlaopQiSRJc02K1omka2qbGrO1lsjSla1vMWlBqpSjKfqbveDxGAWma0jYVKMXG1ganT58mHwwIKKq6xpMQ6MVo2zqa+ZKmrjlMDWc3CvI8IwwG+JXro34+UNW98XRiLVnaN1EovU4fS8AkhiRLWSwWfTe53WD3sOOBJx/nZV+6yanNEWXmsLrBSIWiRdGh8CgcGof4EtFCUJrWFYgecOrMHSxnM+r9KZlVNOvZw9okNF1LXhQY4zE6oW365pksy1DegExoWw8qI4QVWpn1ZBD/PP5CRiKRpyMKwEjkGXFyysENNU7qaJ9a+wT2w1A1U6x4JBjEjXG1RTpDu6xw7ZJ6NWexXOCcIGLI85LcakYbYyQLVG1NvVjxxKNXcc0uL35pzsu/chNdJtQrj28XZCrQLBssI65O92icZzwY0HqH9o7Z/h5l0YuyxWzB3sGU6d4+eTlkebDPpUt7tHULQVPXjhAqsDkOxe1nz9FMr1Akpo9siZAkCZIWtHXDcLxJ3dQkeUEXHEjv1ycebJIgqmO+OMCHvg4t0ZrUWrRS1M7RuhZlcgiBqu2YJAWL+ZTOtazqhk5pimFC3TiSrES8JwjrejlFIy0+NGg01ma0nScdjVBJwWxRUTeOK7t7zGYzjDEkacJmtomI9NYxXYc9Op+qt5FRCL5r2dwY4/2gn+FrLfloiFK9AEuSBGs0znecOXuWndOnGI0ndGsPQhGFSSxa+gacarnkiSce5/KlS7h6walhxrlJytgoMAp8ICsSjO6bTobrWcR125CHAu8dQSxuPWYuH5SICJXX2GKT/eWEX3nPjOFAMxkaxgXsbE3Y2Uwpc0emVyQcomWOBIOyDlHQdpYuDGlCxsbOeQ4rQfxi/do8Tdchvmbj1BitBKsz2taxqg5J0xSlUyTkBD/EuyVGc+KPoefwVzMSiXxeRAEYiTxTBK41gRxtOBKF/fSGa8cIihqtHcakZGlLLRn1wtKuOpp61ZtHI4jSJFnKeFIyGIypw5Ire1dYLjpW8xrtHFky4OJjiuFWwZk7z1OUd7ASh69rci3U8wO8smxtbNE1LVqgni/QQeiqGkFTpBmTcsCVJy8SlKLYGCIC1aomiKB1wqJuyELgiUuXObszgQD7V3fZ2togiOCC0LlAkg+xhH4c3GCAM4Zl08/k1Tqhqmp2D/ZYrVakiQER2q7FKED3HaPee6q6JlWaw+kcbSz7u1dJ8hJbDrBZgUlLvECh+8RikWaIVjRNR5YkaDPCBaHyCkkKOhLm8xVV3VFVNcE5RsMBPng657A2oa5qFoslo9EQYy2rasXGxhijNDvbm6RJQpEXdF1HkWZ0IdB4j7aasswBRZomjMYjRqNRL/a0JbgOUFiT0CFoBbPpIZeeeJwnH3+UJ598AtcsWIxyyi85z2R7dPxRyrIEcUIIgbbtEOm9DNM0xRiNWo/p00aj1q3Fdd2S5ynbZy7w2KVdXDri4uGSBx++xLDwnDuTMSotO5Mhd54uGGVDtFoRZEnwAecEm49Y1Iq6rhkMxsiqJSkyrOnnMRfDIU1XY9CIMf1nVgVQjoBHScpiDm2bkudpb0qtovqLRG5GogCMRJ4B6jrhd0IAHl/rTkxEkKMu4YDSHTabk3tLm3dUQSNOE5zDOU+aZYxGE5IkxYeG6cGU/eU++/MpbW0wQVMkCcONMcrnzPbGDLfPMhjfTV6uuPLk75InHpuXlHmBVoaudSwXC9rVgvGgoBwMEBRV0zGeTLj7S17EqvMkw22Kq0tEDmnbFmMNg7Kka3u7lCCBrq5oFwv8aopDUU42MTbDK8V0tkAh6Lal7jqwKQmKul5SLyuywYCqaQnS179Zq5CgemuX0NuvdG1LXTcc7k/RynAwW3GqnIBKCCphONpgMhqSJYbQOVarQwIKbVOCUtQuUHUeMQZbWOpVzWxZ432gqWu6rulrGyUQEKq6omscSZIwKEuM1hitGQ2H5GnC5uYmeZaRpSnOOazt/QipVqRpyng07DuHi4LBYABK0XUeUf3nQ+htVowG33bsXr7EY596mEsXH+dgb5e2WdAcau4+M4adcd8F3TbIIlCYHKXUcYrVWktV1eR5jklTdD+HDYzBJCml1qQmMBoU7O3v0/pAojTKjhCTUssmuIT2oKbzDac2BmwPr2DUEqUNSgltW3H5oKOtl2wmno2swyiNJ2CtIi1ytA8oDImxOPEE6SfBGKMQr1muFKtlRpEPEaao9Si7SCRyc6E/9yE3Pz/8wz+MUorv+I7vON5W1zX3338/29vbDIdD3vSmN3H58uXrfu7RRx/ljW98I2VZcvr0ab77u7+7HwEViXxePF3k78Suo+Grimv7lYBpSfMlw42WwdhhE4cLniQv2Nze4fTZM0w2JiCBvb199ncPmR+umO7PWS0qEqtJ0oQyH6JlQLW0HM4D6XALb3JsuUE52aEcboA2DAYDRIStnVOoLKURjy5SvAp0oWW4MeHMbbdTTjaweY42ltVq1Rs6I31XrYYszxmOhhTlgNVihqtXqNCB70is6qeNiLCYzVnNF4S6oZoesjw8oMwSTp85x3C4gShL5xTKpHjMen6sIs8ymqbm6uUruKZFgsKkJU0nNF0gTXOyJEN8oF5VzGeHzGaHVPWKuqs5mE1ZtoGqCzReWKxqZotV37HctHjv0NaQ5RnpOnVrrCZJEoaDwdqtRBgMCsajIadPn2JQFgwGBeUgZzgakGYJaWoZlQXjQUmeGrLUkGcJSWIJ3uO9x/tAEKHzvSlyCJ6Dg32uXr7E9HCP1XyGuIbRICfPUqqqpuk6UAab5CRp3k8RGQzI87z/lAVBrX0cjbEobfACaEtSlOTFgGZZs7WxwSC3rBZ7rFZ7rKpDqmZJ3XZUnWblxxzUOzyyO+LidEwt52jaAqSjrnb5+Mc/xoMPPsiTF5/EeY+2GaxrD50P6MSSpAmtq1nVK6xJsUlfo9h6hwsF02mKc2PAxvq/SOQm5QUfAXzf+97Hv/k3/4ZXvvKV123/G3/jb/CzP/uz/MRP/ASTyYRv+7Zv48/8mT/Db/zGbwB9uumNb3wjZ8+e5f/+3//LxYsX+Qt/4S+QJAk/9EM/9Hy8lMgLjmuRPda3+nmrst57wiNQSW+/0TvnIWZBNlZMTg/pOkurhmSDISbN6CrHcjZndjilaTrarmNYDtkY5ISuwaaerIAQWlaLOYOuo3WO8WDAYOc0Rns6NJZAajVaWU7tbBK8owuwamtwHVlRIElfT+ZtigkJaZZhU8t4OKSpV7R1g1UKaxPSvGQyGhDGY+qNnOlsilaatmtxTZ9eVfQj6FRQNMuaw/0DHr94kSTPeYnJcW2HtQnVcokSS5klKJuivKNpalZVP5d4OJhQt46m7ci8Z2M4YWdzi/FwQJllzKaHNK3HY3FBs5qt8Cga3xBQJHhccDSdx3Ud3nmSNDkWUzQNXVXRNS0iimZRkacbvRizhvF4xGg0ABHyPOvFXRCauiYxitSkpGmCkUAIHqsV1mimVYULkDiHMgZNwImjbVr2965yeLBHvVri2pqqXqBUigsdDz70ELef2mJcpngc6L4r2iQpbdvRNA1FOejtXjqHiCJJMxKbkOQl2WAEzrOcX2Y0GHPhjgs8fvkiWZqyZIFOUpx0SLOgbTOMLvAMePxQCGbCJJ2S5Qarp0x3H6VrBDc+jXdjYEBR5BijcEEobcZyPqdeLREfsElGlo2pmpqOQErJbNqyXCjGmylCHeN/kchNyAtaAC4WC9785jfzoz/6o/zDf/gPj7dPp1P+/b//9/yX//Jf+CN/5I8A8GM/9mN82Zd9Gb/5m7/JV33VV/FLv/RLfPSjH+V//+//zZkzZ/gDf+AP8A/+wT/ge77ne/iBH/gB0jR9vl5W5AXDCfPno3nArP3W1hNR1fFxHpRBBRDjQTlIFeVmyYYrSYYjVnWfkqyqFYv5lNnBlLZpadsWFIwmJekoZ3NrwHBQMD9YYhKDkoBNLN6knLnwJRxefJhVvcRPV2jfQNeRac1sPqfcmKCUxnWeRBssmmVd0+gAhaYoLPPZPk21IjOWPLXYsmA03iApR3jp6EyKLoaMdEIIwvLgkN3dXVB9BzEBDg7mLFcNHvAiDLKcdjVjuajwrp+6gVZoa/uJZdbiO81gskE5mFDX/Wi62+66wKlTp8myHCXgm4rD1YKqalG6T4MuOs/hoqPqHF2oKcsBXlTfeyCCAZI0xSYJXdfhOocCrFKk1rBc1GRZSlkUvRVMkqAS039XQppYrNFoq3FNTZKmfW0jQpYYpPV9vZ/3zOdzmjaASUjLEpsmVNWKq7tX2N+7ymw2pWtqhsMSH2oQh0kSDg4XrJqWYZHjHBiTgO/Q6w5lUAQf8C6QJnlvwaItaEvnA7SePLNkg5xOhO3T53n4iV28KkmHmyhaVtWK1DRsDBMsga5qkPRODqqKTEFiFgwHHZtDaBLDzuYILfQj67AorVA+0LS+T4NrIU8LkmRImg5wIpRDCE3AdyMO9xuGEwsmRCfASOQm5AWdAr7//vt54xvfyH333Xfd9g984AN0XXfd9nvuuYcLFy7w7ne/G4B3v/vdvOIVr+DMmTPHx7zhDW9gNpvxkY985Gmfr2kaZrPZdV+RW5lr3b69+FNcnw6+cToI9HFB1UfKaNDpgmLckOctvlkx352yd/EK8+khzjU451BBEzpPtVrQ+ZqsSMEqkkHGzrnbGY23ERK6kDHcvkCRDwlVzeLyJQ6ffJzFwS7Vcs54MGSUleQ6JTUJdVVxeLhH21aUmcWEllGRcmp7E9DYLCfJC7Is72vbXIcXwQdI0qKfbqF6o+nhIKdrGmbTQ+aL3g6G9WQPlCEvSsqNLToR6mpFEIfSQutaWuf6+bZZwWDjFKOdM+zccYHb7rrAzvYmmkBXL6lXMw4O97l85QqrrqVTmisHMy7vH7J3OGd3f0bXOLSAbxu6purH8dm+hq1uVrRNjXjfv/bpAavVgtGgZGtjQlFkJMYeuzhqpcmyEpRB1hLGGLAW8jxBG1BaYYzu7WfqFTq0+GZGNb3KarpLs5jhq4rV/lUOLj7J4ZXLzA4OCcEzGo+wSYqxKVlRUHcem+YkaYZNEoqioByUjMcT0iQnSTLyYkBSDsiGQzrnaKoK39T4dolzDTpN0Npw9sx5drbOUK0aVnVNWozIB5tgMprQ0bgak1jaxrF76LmyKJk3JRfOnuV1r7rAi26fsDkqyPICk6T9edmMoiwBzWA4YTDeoRxvkRUF1WpGZoRx2Y/mk6RgXqesqg0kbCDSISogShARBE0QhRAQ+uYnxCCiERyyjqpHIpFnjxdsBPDtb387v/Vbv8X73ve+p+y7dOkSaZqysbFx3fYzZ85w6dKl42NOir+j/Uf7no63vvWt/L2/9/d+H84+8sXDtWaQp5sKcr1VTFg7wpj1sQHUgiw/pE08oe7oFhXz3SnOVRirscaxNRyRZBmiPaPRkMnGKYKAaIcpC7JygNi0bwxIB1id0M5XpM7hXIsS25szA6FuEQkkWUpR5mQWlE7pxNGsVpjg2JiMCcGwtb2DzRKcBDQB5TvEOVy9YuUquqZGa0AJaZYynowYDEc0dcdcV5g0QTcdhR1y9vxtkI+pnVA1LaUClSQopWialiTL2d4+Bcl6QobStMH3XcZN78W3WCyYzRc4UWgHlVvw+MWriElxAbSyiDF04rFGgzbUHjo8zjvEO4z08s4HRZINSBLNaG1wrE2KSTKqpiHR4FzHaDzEB0GvJ3JYY3pzbS19RDJ065F8gria3HiC6QjVPqI6nO8nshTWkicJRZZRr5bMZnOG44Isy9AiGG24eGWfU9tbFNZi0xTjHeh+BF2apVibgrbUXccksbD0NIsFSWoJ3ZLEniIrhrSdIcVy94Xb8b7l0pWr7O83bG1uAIa6ackSTU6G9ksq13FpaqnanFMjOLVZUK96D0InQiCgtcF1LQmGPLGI7n0BjTbUqzl7V54g0YHJxg5ZuYFXCVW35PIe3JEmGNMgPqB0PxpOREBpRPm+U/g4eh7W5RLRODoSebZ5QQrAxx57jG//9m/nHe94x7WanueA7/u+7+M7v/M7j+/PZjPuuOOO5+z5I19MGPq0sAe7RCUtjhVV09K0S9Kkn/wgYcl4POknTyCcPn+OYTnh8SefIATBdzXz+W4/Q7ZIyAqDzVPyQcHu7golDq1h92CPQV0zGk0Yb23TSiDN0r5kEYtrA6vFjBA0me2L/Ld3thlvTpgtppRZQrOcIa7F+AZjLCvvMQIhQJpmaG2ZzeYkiWU8HqF0QtU5MJadU2c49Amzec1q1ZEnKShNkmR0bkWaJLRNxe7Fi3QhoIBl55lXDbPplLOnT+O94EOg7jxpMWS2qllUDcUgx5gEm2QkwwKV5wQF3kHnFUFpdJKg0oBRGi2axIO4Dq37DmJlE0w+pNOGZefxzYJlNSPPNGmaIli0TsjzASjB+xaCELoW3zaIkl7wuooUR+c81ueY4Pp+8KJksL3DpG0R6VgtD9GhJTEGkX6c3WI5Y1WtyIc59WpFkBWjNCEr+/m/vhPSPME1NfODfXAeGwK+rgiuxWztoEx/nlUb2NgaMzkc0fqOhz/5KS498Tjnz2wzLhOqEBiYHJ84xFiW3mP9iKwDZy1t6FhWDSEs+hF74lCqz4Io3QIgAVarmrZZMZ/uspxNqVvHeMtSTjZwMuDKQcWwHHBm4wxarZAwQ5sWxIHOQQzHUXPl+hpaeUFeliKRFxwvyN+0D3zgA1y5coWv+IqvON7mvefXfu3X+Jf/8l/yi7/4i7Rty+Hh4XVRwMuXL3P27FkAzp49y3vf+97rHveoS/jomBvJsowsy36fX03k1uFkxYUCej88pRfk44RTtwV2r84R3aB0Qdt2GK1Q4snznHxQsrU1pnWe4WjImTOnGW+OmdYLRBtGEkAEvbFNGIwpz5xnMsiom4r5fI5ogy0KsAYVAoKmah1VvaIcjBmNRsjKk+cFA6cYTSbkxQCTJhR5QrVYok0gMX3NozEK7x3G9vVpSvW+daJU30BhMmg6Gi80QRAMSVJgbYaIxpoEozWDsqCuV8yuzFBKMcgLFNB2S5ZXL9KtVuzWfT3kaDRGG0tXHZCI5lSSo2UJ3rIxTMiTgIQVrvMop0hNhrYJGNBGCL7FtQ5pAzoEssSSJhqbpZSZom47lFKkaY7RntlsxubmFjbRoBRpVqxr8jyuawiupq1Vby/jO9JEge/f534CjEdcQIlHSYf3NVp7slSjlWC0QuuExPYpZa1AuZaqrmmNYzjZQGtNADoJ5NaS5wneOQprGYxH1E3NolpRzRekqkCnGkVg59QmF/fG7M0W7Jw5xxOPPc7B4YrMTjAK5suOdCPH5EP29qY89vhVdsYZt5/Zxpk5gSXOdTjXICFFiaJtalw7Q0JviVPNlyzmc4JvGZQpmg6DI08zBsM7mM1Trl7dJXEjxhslaSoQ9kA5lHiQBFEgyoE4FGYtCkN0jolEnmVekALw9a9/PQ888MB1277pm76Je+65h+/5nu/hjjvuIEkS3vnOd/KmN70JgAcffJBHH32Ue++9F4B7772XH/zBH+TKlSucPn0agHe84x2Mx2Ne9rKXPbcvKHKLcHRFO/JF0+tNjiR1nDpf4LtN8tQz3U9oa0Vmx2ijKAc5xTDDZFCWOTqzpEVKEOk7QbMBNDDbX5JMNhjf9iLSPEeHhqEKpOOa3BjStWhruw5Xecq8F2Q6SRhPxiSF5uqsIZvssHPuNpquw0iOhA6T5PTzXQXvagaDnOV8RuU76qqmaTp8CASBTgQJnnlVUXlhW2sO9+f4tS+e844gHudbgjgktNxx22nOnDrFarFg7+ouTtVcGAbMeEBmE/JsjLFr+xP62sLWBdp2RhAofYvb26P1DhsEhcHo3j9PtKATjUk0+IAKQqogUwnL1SHWDUl0TdsII+VJiwFFmaMA5zU4RZZbHH1zidEJJjOkRUY2KGjrFa5p0EmKtg267fCiMUbj3IorF59gOTtEadBpRnABJ+AkIzE5XhuCciwbYaCF1AtZkhBcoGkcaVaQ5oZiUIJSeNd3dOvEkhQDyjSlcx3NwS6bp871no2u48y5c3zk44+wP6948uoU8btgE86cKnoRPFsyUDlBEnb3Fsx39xmmJWlS0tqOtluxqlYkicYqgzaKpu3QShgOMrIkpWsbvBO8a2hWc2bqEovFgtHGKQbDkmpR8khVsdMozp0bkSZLlFqtu+JPjIpTbj2f2KzNo2MaOBJ5NnlBCsDRaMTLX/7y67YNBgO2t7ePt3/zN38z3/md38nW1hbj8Zi/9tf+Gvfeey9f9VVfBcDXfd3X8bKXvYw//+f/PP/oH/0jLl26xN/+23+b+++/P0b5Is8OshaAx6PidB/tUALGkeQt5+4ckZiET3xsRb1MSG1OCIGsSDFZgiiFB4I21K1HGSFJc4ITuromz/upHDofUItmczAhtZq8aAnNioPdy6RW09R1X4xvFG3XUS+XNHVHPtxhe2sbM95ivLnFfFX1I9JUYLyxg/ELCuOZ71+ibRuc68enDYcjmm5KJ309V922KKtI87xvqbAWT0PbOZTRKC0412F0YDws2LztDIOiYD494MlHH6FaLtG+4cy4xCaG1BiyLKWqKhbLJdZaggjGeUY2pfOBbroPoskSuzZfNhR5ibSBVVOTlTmjjQlpadEi4DoUAe2ExfRxFvslQZVskpHYfv6vT1KcwHw6Y+BKRiNFEKEK0kewtMNqBVhINEZnJNmQtGuomwovHVY7XDVlMd9luayYzpdMFzXK5tg0IQuKJNVkWrG36ji7eQqpFUVuMCYFZUjyAm0SyvGYIIJvO1zX4ozubWjyAcb2s4pdW5PlAxovjMebJGlBkhboxLI3PeDxq1coJiNqAqVKUMsZ1XxFqA6p2wV7FzWbGxMUoZ9l3LQkq4phUaBRbGyeRqtAYtcNTUneN/FoQ5kZ8kyzXM2Y73lydQZrB1RtYPdwTj7wbG+OsdqfsEY6mkTd8bSempFI5FnhBSkAPx/+6T/9p2itedOb3kTTNLzhDW/gX/2rf3W83xjDz/zMz/Ct3/qt3HvvvQwGA97ylrfw9//+338ezzpyayAnvtY1T9LXQJlsyfb5TdpuQLMY0DYZIRhsWiAmoRyfJhuMaJuO1WpF4wJWB0wSMFqw2hOamjJNKM6dQ3UVbb2ibTuW0ylG9zVXWZKgFSznM2yeMxoUtFXDfHaIkCPeU7UtRVn2JsptQ+scpU24sreLqxoIjiwfYIMg2rCVDMmXFUr1I8oOZ3NGgwGSZDR1xWyx4OLlS+RaUU4GSIAsSRmUA4aDEd41aEXfnJIYjAJr+iha06w4XFYUZUmq+skhSD+CrAmBqqkIAsY5mrqjHA7IiiHGelrXkOeaja0RxbAgSfvZweL75g1dzclV3+hSd0ua0BC8UAy2eHI6JR+cJ00M04M9EiUMygFKFEEcTd329jde0FqTGoVyLakJjEvNajmDtOKl50sGkjIvHdMy5wlZcPnKlMN6duwkaZVQdg0vP7+JXZtKu87hvQetCVqhjEF5j1+n8K3NWFYrvOqtVkaDASQJKs1wTrNYVpRZipaWjWFKaAwHu49yZQAbG5uERmH8jKGGV790g1PDHcy6W3d/Biof4yVQt4E8DcwOD0AlFHlKllq2Tp+h3DrDYrEE32ByhdZQFJrOddTNgtHWKcxwSLfKOJzCsPRY0yFhitLd+vOvEWVRSD9aLhKJPOt80QjAX/3VX73ufp7n/MiP/Ag/8iM/8hl/5s477+Tnfu7nnuUzi0TWqMD1ljCBayPjLChQxmGLFWfvGDHb91y9BKulozQ5m9u3UY43CTrQNlOUNRhtUMrgvdC2DYnrSAiMhyXLdsbscIXvWtIsY3PnNNLWhK4hsQYlkJUtykBVVYyGQyqn2b0ypasdd27t4JoGcZ6mqknTlOnBRVbLJZPhCPEtrmtBFEmSMhhm5OWkn4TRNnStQ1mDzTNGW9t8+tIC7wN+3fRglGY4GFEWJXVVcXBwgISuN3LO8l4ia4VKEoy2pGlJ3bZIYmi7FqVguez987ROQIFLLMXoFKdvuw2lDMMsJ9GG5WrVj4ojpRhso22CoHvLlfku9WpOaBtM1zJOc5yx2JFhtLXDvG1ItYXWUM8X/ZQSrUmz3gfR+UDnPISAZIZxpqBdIjKnVBW5bdg6Zbl78yytc3hRhHAPXevpWsELtCHQOAc+kLAkUYA2GNunrbO8t2Lx3mOUwmhNYiyi+uxH17akacGqDRjlsd6TpxlKWSaZolQVt29pXnT6HEoFNFDkjsHQMho0bA1zxqmQ6SWJSVh1LXWnaULaT2CxQtM1KG3Is7yffbwxIegUbwdQpBSZBb8C1ZGknnaxYlYtaQ81yWBIaBX4goODmtTmJMkMVIMirKOAav2rcVQiEYsAI5Fnky8aARiJ3PwcjcSy1+4rx/U+gh5la2xpGJGyqHPEpqRpBjqldYoOwSQ5RZGjRHAOOknQKkEr248HM/2ItaIckCWbiO9YLmfYQiGmbz6pqhXOOTKTom3CcjqjDYYsy5hsbtM1NV3nqKqGRCtWiwVaG7a3d8h0YH64IlGQFTmCZtnUuHXwRmlFORysU9aCdy2TyYjxaECuQCtFnueURdHP6W0rvA8obRBt6ETQCqwxLFZLijynrSumsxmT8Rhr+wkZg+GIYjTCB6jqiqQYcv7OL2G8tYPCkCpNogSVLdifHtC0wljnpMWEbDABm9HqEltU6NDgmwVZmuAloGxCbi1DlYIesJfXXN2d4YOiaVuWq4rBaMRqVeO8x3cdqoNJUpCYDusqLMte5FiNV0Ju+9m+CgW+NwZHaVpAbEbTCqt5R7tq0DZH6X6Si6K3TjmaDayVRhnNen4dSmuU7tPiSsBohYSOYZby8pfcQSH7aBmTqJbEaIzqBZfSDosn0RUmNIjUiEoxegwkBKCuO1SiGA0KxhsbFFZhbErrAybNmTWH7B3MueP8ebZHY+jmrBaHZMMhic1B993qTS04DFeByajAJgmKOYoAZNeaPyKRyHNCFICRyHOG9MXtYd0NvC58RxQoA+sGA/BoW5MOWk7fNqZe9SLAGEtQCeINkGK16mvYDBilMalFaSFI6OOMRmONpqtXLBcLrAm9ya6vEefoqiWraoErhqT5AKFvqlCmn427rCvms0U/im4wYH//gLM7Y7IEwnIXq1qW00Pm+45sMCYpRiib4ANopQnSTxlxdJAWFJllczJCuZbtnU02hyUooW37UW1p1k/f6bKMPE1p26ZvcskLdg/3Cc6jjO0nZWjL9vYWgmL3YJ/lasGyatjIN5lsnGYw3kZjka7G1RXKppTDEatqwWx+SNCGfLKF04au2CIZgBZPOz9g2fWduqlWZDYh0wmjrW2GE83h4mEaLyibgXfMF0uMMVSzQ5R01N7hBx2FrTHSoKXFqI5GUvw6qhXWtaC9mAsoFQhBEHGgLC4IOi1QypCmBYlNEYEQhLppyIyl8w4CBCU4FyAEbJoTOo/raqwVUBZlE0apcHojZ3ZwSKo8dB6j++gxzmGUw5iASfp1hbX4thrTQeM8K9dhUwitIU0yjE3QiUUlBaJTnrh0lXNnzjJfVEhXozGMRiOyrKCqVxh6uyCrRqzahsO5MBiOUayA0IvAo47g41GKkUjk2SQKwEjkOUMdDQymT/vqvo7tuAqsL4ZHPKgaZYRifIm0mIA3eK/pfIslx/sUwnpyggqgAl4aAhVZsg3SENoV1HNctcJ2DavDKV09xzcVrmmwxpAajasUnVcoa+gaR9M2LBcz6sYhrkOJUFUVWgt3XbiNejklk4CRAK7G1yumqzlkI9LhBkobkjQlSQypNxhlKfOUThvOnN5mtreLa2umsxbX5SiEPE/JBgVN2yJ1hUoTBkVJXTUE79DpEJsbtsqSerUCUSyqjrptWNaew1WND+BEcK6vnSO0SFsBgaCFZJBhpWU6m7Jq+kki5EM+8chVyqJkPNlgUG4jumWYG1LVUeo+tS5ty6mts2xsjvn0k1exJiWxmmq5QjnPJHe4ZsEwFbTvMCZgVQfB9ZY50ic5RUFQCkGvq0D76dBWCy54rDakFqxOSYsB2iRo06f5nXO0dY0tC8R3BAU6NSjl+89Mu8KtViyrOct9RZIWZHmJBM+oyKmm/bxipUC8642ttUFhe7uaoPCqj94qhNwa2qBQmWE2naIThcoLKEdIUpLnI0wxYvOUx/mPMJ/PyYY5i/mSYlCwVW4iJqXMNygHBbNlDWLRYZO91YOMlh0bwwpY3PA74J/ymxOJRH7/iQIwEnnOOBH5W4tAIaG/8K2FoNL9BVm5fpuaY4xDVAdmgfgNgh6j/RglQ8QldF2g7UCCR7cFmfcg/cSOsJjhVwsIDusbqmrBcjZlOZ2RJimDYYkuetNkUYbgGppVS1cO+9SwUXQaFtWSNDU4Lyhj8ZLgg0GrBKsMXgKJ1biqIi0GpCLUiwXBe0ya4+oVVo25cukSFx97hERBYhRlnrO5OWF7Z5tTWT9GLMtLus7TtC1N4/E+kOQl89kc7wLTg0OM1jRtQ9t12CxBaYVznq7rODzYxwXfT/5QAZMYdJJhsiHDdEg5bBEl6CwhG+YMEkNbrzjwQpoPGUw2mUwGpKFhefUJgnfUiynYhK1RwWOhoaoXmNwwTFra5R6b45TRpiWhITMrMu1RqsNLn9K02oMHESGIop9/0VudaKUQCf1MZ22wOqDpEAMuOHRi0Bq6ZYVrG4LVWEJfNeA9rqmY7x0ybVuaZkXrKpTVlMMNXDnB2gyUI88Kmmred+8aEBXwCrSA1rpPIytBhYAxoJWnbVbYdEBRFAyGI8Yb2xy0ilFa4CjIyJlsn+WeL3sZwyLBJppyYweTZnTJhMFoC0TRqkC+PeHSlX2G2WkSHdidNozKFqPdugO4XytR60b5SCTyrBIFYCTyXHE09UC5/rsk9M0fAdTaAkPguCZQKZQ3/T59gFZzTLKH9ROU20K6LYQJiRqA5Igp0RQE7wn43nNOhFW1At/hg8O7QJpklKfOkua93VEnfb2YTjSZ1bTVElcvsZnQLJYcLlcsmo6t7W2cc+RpgZYJ1WIJJkfpjiwVrEmpVx3eLzi4uqJravKiYDjZpBxt4LHgoWs9SivwsPQrlFK0radpOrZPbZNlBU3b0DVNL3iC62f37u4SnCNNLKu6pm0bPEI7bZmvFohSaBJQj5APCoZlxqntDWw2IB9toNMRqc3JrcGLo9MBnWXcddYzq2r25ktmi0PyYQaJBq8JKvQzdn3HfH+XyWCLnXHJQw9/kgE521s5KksobMNkYLDSoaUF7/B4tOlNnL30s4SV+L7+b/0loTfVVlqhxRJE4YR+VnRwjIuUvMho2ob5/BDfNFjXkhrFdD7lcHpItVxQT+eErgUcygaK0RBpO+p5TV6OKUY5RTZAfIf3K6wG6PDGAn0todLr51V9R3maKNJE07iONE2xNiOIRRcDxA45WDiufvphhsOMO+++G+sbLIGm7QhJjh5sUTFgb/+Ahz/xu3zJyy5waX8G9YJXv/QOaPZxocWo6bXfieMGkEgk8mwTBWAk8pxxVOB+NBHEX9t25BF47IGmQRSizDpN7Pp6PzypqVFqr68nTBK8PsV0cYZFcwc63yJNc/xyiUWjcstke4OmbVlUfb2a8YEyy/vOWK1ougatFU1dU2YTjJ7TtA11aLm0u8vVvQNsktDUpxB/jqbVzK5eJdEBZQ2tOJQodF2jqiV1U4FWpFnOcDImGwxxIgxKze23naZezrl6eQ+VKYwJLOoZog3+6iEBzdnbT4PqPfC0cuwfHLCYz3CNgxBoVkumsynLpkESw3SxpGkdSZqxt3iS03UgT3O+7KUvYVhuIapvirB5ghNFZ1Myk2HampyEi7Xj6uWLKGVZNJ4iy9kaG1JVY8VjbI5TgUY6RsOCO2+/nSuPfpxT9oCzZUtRVFilUY3FKEtQLU45tNZ9WlUAafqGjaDAKzQerQWvNUiKCYpUOTo8WWZZNRbjNRuTHZTA9NJF2oNdqtk+U9fiNbTO4wMkSUo+nrCYHbCcz9jc3GY43MLYFAzU9ZLxxgaiPMPBhNmiQZk+zZoYjRZB41EIVitSIyjVUCYpZaIhJCRJQesdh1cex47Pc8XNWE5nfPLBBzl/eoe77zzPYJDhraIOgeAUbjGnCSsee+wRZvNdHnrQY7IJRQIXL/82r7jjElY/Tp8CPjELOHYBRyLPCVEARiLPFeqGG6qPuDzNAVx3AVT0XaCAEkHRoZQDG9ZzU0vyEkxRkg9SpJmxOrjE4srj+NkuvmuYLVbUzjOYbJAnGXVVU9c1xSAnz4ckScF8domqnpGmfUq184GqcjSVxntLUwkET1vPGQ0zuqoBY0iygqZpaUUoxyNKKUnSBLEpmJR6uWC1f0i26UgTjbIpVedZNS07WwVWQVevwAX2rjqGo5wkyzk42KWq5qxWU2aH+1SLBUYDIizmM5ZNB8YgAtJ5AoGmWbBvOoblkMDtpLnGhcDBwR4jmxFsiU1BFwVBQeUd+3v7fOzDD3D29Cm2T9+FDYG9K7u0qeAbT2ZzdKYJbU3TdQxKz0vvSrhtrBimK0Q3SFBoUoLrI39I6Gv9lO9NpwkgGuUVaAiybgCR/vUg9P57QSHicd4jVc3h4RTpWg4PD2gXM+bTKU3Xkg5K0BqTJJg0Z3Njm/O3n+fKpSdBKYrhhCzPycohVRtQaR/tdU5IsyHWNHTNnEQJRgUsAWM0RnuMAWVBuUDnBW8mhOQU82A5bDvCoeWTH3+IxcEBd5y9jWVIeHLPcS7fRLwjKEXrFM1yyuXdKR994Hc5u3WKM7ef493vew8ve+k5svZx5HzT17oqz7VLUcz9RiLPFVEARiIvCHpBqOhrtyS4tTzMCJKQpQWFzdGJw1VL6t3HuPqpj7D/xGN4F6g7wZuEoJ6kqlryPOfs+dMUg5TMpCQ6Y1AWzFYNoiDNS5pVhWAIYnDO0NS9mLGqI0tzMluymtckWcFwY4e288wOD3FNjTucUlUNWTHAWEuaZWTSsjUZkucpQdv1HFzL5mjYC7ggdFXFk48+xnhji8P9fVbVlHq5olouqaoKRBCE1gWSNKfpfJ9VF/BOoW1fE9mJwltL7UEZS1c3+DZQlClYTRMCwRiMVkzGBdsbOaXuKKnYyg3zZkmNpSwnFOUA0R0r38/+HecrRhcCQ1kiXYVH6BCwbT/LV0AFvb7RC1ON6rtbdYDQW+Mo+uaQvhUkoFVAJEEj/ZSWEFhWS1xTE4DheJPlqmI42mSwucVitWQ8GrM5HiNeMEZz7sLd7O/t0wYYFsV6xnFKUo7pnKCspcwsJixIMBAOSZXD6IA2Gq3BaI9Sniw1TDYy5vuHfPyhizw29ax0xv7VS8wODqgWKwZlyu5exeXMcmn/EpvbE/Ki6F+xyTjYu8LFJ55gevEKw6Lh1HDOYv8yX/mVpxkPOrTqrhX8ydGfPDH6F4k8F0QBGIncxKjrjKOPRKAH7UEMQk4IA3ynCc2c4Duq6R6Ly49ANSURh/OwWlR0wXD1YIoXzWhzi2Xb0QTH6S1FaivSNDAwOZcPD5iYEgkdi8WM+fKQrCg5PLxM09zNwGpaVyFdS9c6JCgOD2bsH0453N9lfrBLaW1vRNw2TCZDMuORxRW2iwlf8YovxdqMJx97jCwRMmuxSUrrPF0INHXN/tVddvf2WdUrquWqD6Cpgs47Gt/ROsu4nGCUo206ggk4H7AhYVlp8smITo1YuBRpPUW+yWCwgbE5HosLGmsKrDZMtkacPbNNJp5hrrHKMywG6LSfsWyLHKEldw2pTchMwKQ1ST3Dmo7W9758XntECypoVFCoEPpIoPRziUU8ohQiChPAq35usiIQxKN6C2ysUZh12rqta7a3NjGTAZZA0Jo2aPLxBs4MmGxvkGiY7+/hnGMwHmASy3K1JMksLBck2YiBKUgGE3wjlHkJTUJmM9pqiabBqIDWCq01VoHWLakV0k1I7QxX7aHDgsNGOLPZYLYNq0XFi7Yep2saCNDNWloZI1mONgnKZJRuwUvPzBmlHS/ahgt3jtkYDzi/OSNVl1FU9KnfI/Wn+tnAMRIYiTzrRAEYidzUXLsQ9mlgddQsjGDwfojzE9rW4rsVvllQX32CMN/Dhj5S1wbQFpIQuOu28+xPFzzy6ONsntpiMh4QqpbhIEdSwQ428aHvvE3TjFW1pG4X6FTx5OXHOTjYp9ga07QVWoRquWS6v8/u3j7T+YzVfEaZWDbPnCFPDILHr+Zo40kaT5CO2zbPM3rNl/FAKizm+2SZZXo4Z7aoUNYwGQ0BoaorFk2Ncx2afubtqmvoxFN3Haqaklq7jlgBytM2Dd5qLu1d5P/+1vuxoyF33nEHaZbjbULVBsT0/npK5ZigGIy2yIcbtPNDbDnA5ENUkmOKAcrm6OGAIA2q1RhboHVHYkqMvkyqOoR+lJmS3o5HB4UOghaPBMEf7UPWfn5rEYj0htNBEBNACVoFsjRB4fFeCMBkY4JyLU21xOYlly7ucXp8msn2CJtZZodXabqO1ChmBwekeT+z93BvnzxLwAk+G1COxnibsXt4wMZwSJaWmHAVIzUJzdqTsK9jTI3H2o5U9tncSnjxdorYM7RB9bWlqves1Cah7Rw2Tem8p/MetMGLEGjQpiA1d1HaBfmgRcujZKmB0KKoUEr69VtHt/tGqJMzsyORyLNFFICRyE3N9RdBdaJLOISEIBsEv4MKg358mJtjqkMKPE6EZdVxZb9itqjYnpRMcmGcDTl/eoO0KGm7mlW1xOot8rREgpAmDuf2GOQZG4OCplYYPeDSxcscTBec2ijwrkI5TzPb4/DJx6DzTBAGZcHO5gZlaqiriqqrEa1IspQkCxincbMrnD11J8krvpSPPvgQ+/MFu8uW3b05p3a2GI8ndNUUrVsC/ag68R6vBGd6Y2JnFfOmxbQdoBBtaMWjiwRlc64uHY9//FFc8Tt8TTLkzttvw0tvNqKC0DVtn+KuKqysSLKSsizJN09RiyHPh6TlGHSKJAV1Haglo105DucLzqYFk8Ti5QCjExQF2nlQ4ENvxo04RAw6WCweISBBeu/G0M+/CAFEPMr2Rs+OQJEpVGgJyRCdZMyqmmY5w0pA24TKdQSt0XlBEzqCthTDAVocQTzeg2jL5UuXOL01JjGWRAdC1zIYb7I7n1HrHJ1mJMkOaWhJcCjdraeMgFIBMYFEazLdgWuwYhGlSdLQj6Sztp9GUqwtaZQgOqC0xgeHNgplFD54tOrQukLhCD4BlaF0iogCDL0lku+z5nEaSCTynBAFYCTyQkDBekwIvX0IKF2gwiZKNlFiIawIXU1ZFDS+o24D00XDwWzFcrVkkAfmh4ec2t5mezSg84FWAhWa+XSGTkvGg4zxQLMxWTDeEB7d8izmmsYltJVmuaxBQa4C9eKQQjlu2xriO0dSlCQ2YzGfs3v1ChjLbLVCTILXc86anMGoQNqKvStPkE3OcOeLvhT36EXSQ4ewxGiNb2fgd9HhADpPsxTqSlF7y8wp5s7gUYQA3oV+sobReCxFPkKZojcqHm7wyUdbxDzEH3xNyotePAArBD8n8Q3t7pPoZklTC56KM7efY4WitBpPoG0rMJ7W1bi2olsesvvEE8wvP4LcVjO6PQE8ShRKOqzqa/e0VutpLB0iAYJZRwBDvz3024JA0P2INy2KIIKRQJkrjG7pTEIjioNlQ7WoGCaGNC8ZjCYczOa00tu0+BAYphlFNiYbBKpWyNKWWi5xdV4z2NghmJRgE1RacOq2u2mahk4npMk5dLfCqkOsaRE6jDUo5RAjiBK8NZjE9FM6lKLTAZNqAh6kQxuNIGgNWvcTTRILgkecx9oU0Rned9ikRHtLoH/9ovrRdfrIB/P4K9YARiLPNlEARiI3PWot/gJ9tKS3zFAkSMiRkBGcx7cVbdNg0pJkkpJXAb3vULYlzfro0c65U9xx+3nm8xWLg3lv1GxBGs98/5DJZJOdkeHUqZaN7Y6veFVKVV3mkcemZEnF/t4lRC5g2gapluiuZpBrOqMR7bGZZrPcoRbP5b19Ogy+0yxWAZIh2Iwsy1l0DlfV7Jy9i8euLvoxc6c32B4KZXrAl7/6LC//AxOmC89y4ZjPA7NamHbC0sGs7mjbQFV1zJc1h9M5s1XN1auHBKnALrD7hygDs6uP0C4u0bV/iJ2zt5OlOcvdy1RPfpq7z2yyaEs+9LGP8iKXsnU250xpSatA5gLaBupVBa5CVzWXPvkge08+wuliE7k9wSQ5Iazr/lQvBsOxoOkFnxGLeACPl4DovkZQhPVYuF4Eiu9TwCMFk4HiYOWxQaODYbpy+CRwphwzHI750Mc+zs65cwzKnNQAKiUbDTC2xDqYGMOpquPjH3uA2148Idk4A8UGlcoZbY2Qg33m+/t4l7KVjTE2w+olBE+SrK2HtOrL8bRH6w609LZESuFVQNM7EQn9jOK+OsH06XhZjynWfWczAlaXvQ3O+hhR/WdarUXfUQlgLP+LRJ4bogCMRG5qTvqj3XBlFIU4Rdc6VqsFoZ2hNbQmQ1AMN09x9hyIylgsl6SF4kUv/wogoPw+YenQAsY4NnLhcDpjOX+c2+5O2NmqyYsZ99yTMhht8rufmPHQJ1tc+yihfTldtcK3LVmeMyhzqq5hf77Appads+fIT51i/tu/g59VpN6yMRxTZGMGRYmyikGWcVi1uLZjc5RTmAW3bw/YGFa8+g/scMddgkotojLECxI0AUMn0Eg/Ss07Ad9HQ5dVzXyxYlpbVlVHVXlWDUwXLfuzlmVzmYsPv4vHHzlLObydq49fYsN4zmycZ2/hePcHP87Hrhzw4nvu4ezZAzbGWwyKMVontKuKsDjgRadKCmXRfgauQ/sMnR1NcunRctTSoEE0QgDpU7YisjZ4po8CAj4ASqNFEww4cZjEc+5MzqceVnROSCTFpGO64Lh0ZYY1CZuTLXzruLrY56UvfTFpntCaAdtn78bUHYjnznsKLh5MCcNTqK3b2J3WZMZivaGrPU988tMgwpfdJeSZwSqF0SnWZJigUaofzSbiUei+o1kJ5jg617+ea3fVesoNoE4YHKneXFod1/cdTcLpRWT/EBpRvfn5yV7gSCTy7BEFYCRyU3MkAI8igOtxWRL6YWLK49olTTNF+YZRMaTpPJcv75IpGJcGv5Hi2wWnz91GuXWG2XxGuZVQdv0kCh0Uoa2o88cZjnY5fW5CUcxArUiN5c4LBefv2OYP3XuedjlE2l0OV4cYa0jyEjMoSULLICvJh2NCVpDlmrMXLrD63YcYlznj3CJdS2gtwSskNXgnXLn4MDRTXnoBvvyllgsXttk6C84/glEe7zxaKawxqD7mSYHHmHWU6kgXjxWc02DStaoyYDJEj6hcxqLOubhneN8Dl3n/b/8Ojz10lfLCbaS6oN19mJ3sgA27YOA6Fo//LnuVJ8snuJBQZgWmWzFpN7jznOUPfvmLuOO2BUU6BV+h1vYpWoAQ+jm/ovu0vPRm30EUogQjfZr46LwN0ncCi0KJQwdP0Eu2NnK2xiVkOa0TnB6g8Pzuhz9Ebg2bO9sMNyaIUQSVEnRJMjyNzza4euVxLj3+abIEzt7xItLxDpcOa/7H//pF7rhwJ3/0a7+GshwgAdrGsVrVFKdStGgM/WxprY/E3TqUp00vVNXROMP1PmRds7dO3So5Ifw4PgYVeoGHWv/oUapXn5iMsraAjqPgIpHnhCgAI5Gbmmt1fye/9ZfKjuArgl+htQMMaTbEWMHYjLJMyMXhmyUXfcXW9jbzVUvAUtcLVoslaVaQmCGtbzhzLuful1oGkxkii+PIjJaO1LQkwwpVCKvDhn3VIKqg6hJ87fFao5IcnRSgM5rOM948RV4+xmSQk9KBb1ktA9l4TLWqcY3Q+QWDfMn/84dv4/xZT5IugAqTgRJNZgqOUuBCL7JEBYKTdbTo2jKpoMDbtZ2KJ7g56BWlSclSxea5ghedHfP/vvYC+7tbUDdsjx/mdS9P+KY3vZykTOm80LaK5dJxuKhZrOakaU4qwqlhx844YTRp0HoXfN3/D6oM4gN4hTIaYT3WL+g+NbwWSKJ6AS9BoVQfHdQovAhIQAdB2YCXJXkayBJPoxyzVcX+Yc3y4JC67aNkQTSTzW3GW5tMFyuScsCiA191fOrRx/jU7/4u53Y22Nic4Fvh0U88wqcfeZy9/Rmv+NIv5a7T29z+4i/lkw98mIOrl9F3OlLT9ZE7EcS6XrRhegGoHEopAra/e2Ld5aRhuVLH/bxH0TxRHlGOoAxKNFrJcdr3eOwhRynhqPwikeeKKAAjkZsYUQKhv6jKyZyYpo8u+QalOrQOhKDRdkTjO5LhNhunJ+RhRde1JOUlitGQ/fXM2Gp/j+nePhvbZ0jLFp0u2TmbMNrsBUhvCZKCUygJKOkQ2wAtg2HOaFIw21+izAClDa5tqboWaz1BHPOqJU0yssGQwaSgtIJKSxZVTW5TlrMFh4dLhoOEnQ3NHbdbjL2C6BaChpCjMP3ttfVNz3pGsl6bJaMQrfoUovSlktYoCB0QCEFhtMHQYsIhiZpRbGfctZ2inEarFQSPskLQHlxADVLYSBCd4oMC1aKCoHUNoSIcCTxt12IsoJQGm0BwoFxv1q0TTOjfJ0U/+aN/HeuUsQpr8dSP/SMIWgdwHXmqGY1TlouWYAeYwYhLn36csGo5c/4CpixxSkOSkY0TpouK6cEu3eUDHn/8CRaHM8pzZ+mWFVceu8iTV/c5vbFF5Ry/9cCH2fjar2Xjrpew+OC72TErlPJY3aBU0q+v8euav3WDx1qcafoUr3Ckv094VF53/+gDfLT3yMPyqJ716FA5/t5/W0cIT6aWI5HIs0IUgJHITc1R6hdOFFsdbzcmYIwj+BbnDEpnBJPgkyGNKdBacElGHRS2GNDWcw73DigV+M4zO5xi04rT54Uz5wuUnqJUn+4DDTr0z6oVvYmKh1Q4f9dt+HaKRZNYg5CRlwVZVlI7xdmzt7Gs5uTDIcOtAaUFJxnzzuOVoe48i8WcjdGYydiCXiC66h/fjMAl66hRu64/k3XacJ0+DH5tPXK0FP0drzwYDSIok6NCSnAK7Q1K2X40mxaC92idIM4TEoPgwAes0mst40FqDA7VuzX3Qi9ViAN8Dtg+Da1Cv14toA1Ke9AOFfRa1vS1b+pI+xynRrkmDvVRJ63HWIexws6pnGmoma4CXS1UwfHII48wmx/worvOs3PHORZti5iE3fmSedXysY89xNVHH8M0Sy6cPcPWxojVcokRxWgw4PzWJr/z4QfYOr3N9tYmtRxw/q4xabnXRyADoLP1eDqFVnadqO361yrmWp0foI5TvOvPpTr6rB6JPIUiIAhmvU2d3H/8Bh6lh/sGGfTT1LxGIpHfV6IAjERuZsQeXzD7S6Xrb4cUEEz+KKVMCTJgPkt47InfZrCzgdELPvnQw2xONnDKUGyNuXr5U5ze2qbdqygKy/iUIOxy/ksM5+/yJEXRG9Nh1qKqNyc+isxA2l+SRTDlE9x2T8lyMWOxXOG8wSYl02aOF03ul1x84iGSxOF1yswn7E4PWSwqBh4uXXyQwbDh7B0Vwy2NstO+h0AUhAZzLDJOtoWejDbp69KQR3cMBuXWR4WApur32f7nFBZCwNDC2mPQXF+0thaa/trjr29oNDiwYtYCruufUwHiIFufjGiM6D7Cp0+cu6hrL0eva+VEofEo8X1UF4UxCULL7Vv/h5EZ8PFPCTIL3FVMaTdaposr1Hg+/cQQnWwhumB3OuPSpSssp0sW1YLHH3+URw6u8DX/z1eSphmPfPoJzu+cwe/tc3f6MBfcjFdsTzj3/+2R6vWCadMLL7Vcn3Iv+o8ifWo92g4xJz+gN7wJhmt/oBxhrncx4ui9OLqpTmwL63WIRCLPNkpE4p9Zz5DZbMZkMmH6Sy9lPDCf+wcikWfEycjfuo5M+rgMKseHAa4r6LoE7w0qE1znWS0rjNIktr+weucZjzeoZgvSVINq0NqRFh3G9ibAEvxxLVcf3Xr6MxJxwIDgx3RdQusDbm1y7JzCaotzdW8F4gUJiiq0WJsTnBBCx3hsGQ4c2q5Qqupr90T1AuNIZJ2INt00yFFjDlwvgLjutsgJISR2LXmO9t34mPKUgJfXniBj6m5M5QY4pelCS6DDi6JaOhbLQN1p6rbDe9ePzPMeCR5rhdFGCaLoHOA1ozzhttMpG8O195906OP07bUTuGbTIsf3rxd5R/dvOOkbHicSuVmZLT2Tr/s40+mU8Xj8fJ/O80KMAEYiNzFrudCnQeGE+Aj0dhorjGnQVpPk/YVZpEUyxcYk6aM2IRBCH9FSZkpa0KcetQdpUGRA1tt9KE5EZD6LIa/pICx6AZlZUu3BCiIKJQbvPVoJIoHgA0mS4qhBNFolHEV7FH2XbJ9FNPTGcyef/ybkOpHzVOHX35TrelSOxdK6kPO6/pWjgrobjrfOIWpBkjkG2QF+XV+oxKG1glGCBIOsU839nGGHViDeYa1C1hHQIBptMsQHVGjRtP1jUcB6tNu1RqOTou/Ee6Ge7n25cdtN+p5FIpGnEAVgJHJTc2PdXy8E1dqO4yhKo8ShaNdZTN1bofjQR/GMwljAC6GrUcqujXv1OtKmwLu1CFHryFVYi4LPcFaS0Y/vAkXfHILveqGqc6wKR74oGKvAd5gjYYEneI/SvdhTx1Gl44I+0H59/2bMB34G0Xdy242RMBV6cXvS3+S4TE495aEEhSSjPrVMiyag1do/T69rHH0NIohO+oaUoxo8a6Bu13WbICH0aepQgz36Lz9FvO1T6Sff5+vy6jzN9qN9UfhFIi90ogCMRG5qjkTRUbH9OookfeeoOjrmuAhf6I3l1sIO1/+o6/3pdJKAk2v1+kf1XOaoQ0GupX6PuxaeBm/pa7vWQvI4umWQToPY/jwIoHXvN6hsH6VqW7TN+n1yJJbU8fkL68YK9E3sB/fZTuxpOliFEw0S6to3OVnjeGJfn7RHGYXgIQS0TgC77gkSJFGIVeB9bzeozXqcnIIk79dc236ix9rbz4V1Uw0aZTJY15SeOMnr34/P+Fo/lwiORCI3O1EARiI3MdfriBsjS3qtC09GZNYdlOJ7oaCPRBh9NOm4J0ERguvnuIa+ceFodoPSa5e28FmigCac0KXr51h3DiulwSSIc72HnIDSpheEIfS3lervm3WtIUeWKOtooLyQa2rVep1PCMHjrt8TxxxvVyeCatdEl1IBpennCB/X4wVEq7VQdr3xtAZ07zdooO+QXjdxB5F1pLd/TK1Y29EITyvwrosAfiZhFwVfJPLFQBSAkchNTThxW50IyK1DeMemuv2ma/pCHTW1rrta1VrM+T6FeCwC3FognLzgnxR9geMHuo7mWPCJ5lokT9ZNGxJQWvpu1yOBqo8tg/tnOrp/8qGPlMt1dY4vNI6iZ+rEG/J7F01KZP3y1TraexQZPUqlB4Jat2SIv+65rg1iOxrN1r/HGq5FEJWGY3OWozP/bMIvEol8MREFYCRyU3MkAI9Ekbphu6zrAE9wHPG58fsJhD4VKLJO48JJJfYUYXYjx80a6loa8ziKdWR0fPQ86yc8eYpH/14naE++rhtvv9D4bIv3dIc/NWesxHIyNc5aAB6tnWDQ4dq9axHUo4iicLKL+ni/OtGNfN2Zymdr+4lEIl9kRAEYidz0nEjvXqeqji7X+rrjlLj17c/eSPF0lWdPfd7PIAeOxUnfRHBNTtwg2o4EKOvvKpw45kg8AoQT0Sd34vlvxiYQeGoTxOd7/GfiSMCd2KJcL87lKOV7wpZH+uidOn6fWR9zIo3OUfe4P3Geaj2TV9YPexTh/T28lEgk8kVBFICRyE3Njaa7R/VgJ4SW3BgdPDr26W7fgFLP8MJ/VMPmuV6k3ZhKPilOw4mvo3M9GUkM3JS+f0/L76daOlGL95RuW7kuYsd1Ak8hSvrUMOu1U/Ti/Ciyu7YNUuvPS/8nQ59GVsdekteeMUb/IpFbhygAI5GbGDlxq7/0H9Xu3XhUL8R6yXBiSsbTRvFujMD9XsWMOiFC++/qqOpMrj2rnOxeZt18cFS7KCfr/PT1j30sHL+YQlKfK2IoT3NX3fB1IzeOS1PriF4A3Dr6d/3P94HjIzGuntnbH4lEviiIAjASuam5Funrozeaa0NwTx5zst7LrsUX1x2nTh57nB78vcZ8TtT9nZgUwdG5nTjXa096g/2JHM3I1SeiW55jm5QT9YXqBV0HeCO/RxGIOpHSPflOnYyk6vV62XWj8VEUVRDWEcHj+tGTT3WDJyG/909CJBJ5YRMFYCRyU3Njpd7JQv8jEXYUSXu6S/iNqeCTwvCZdnwedbgqUCdTvCdqFG88Frg2J/bpHu/kcV+snaif3VpF8TTB3eOfu/Exjt7vp0m5C9dE4HGt6PWfj5OflCj8IpFbkygAI5GbGPWUJgi5Frl5ypX7KPX7mUTGZ2nq+Lw5eu6ns4w5ke59yvPCyWjmyc7Tnhs7lb/YBODnej3rCS+f83FOpshPbHqKXU7/Wbh5jbQjkcjzTRSAXwCy/nN9tnyhFK5HIpFIJBI5um7LZ5p2dAsQBeAXwN7eHgB3/OlPPs9nEolEIpFI5PfKfD5nMpk836fxvBAF4BfA1tYWAI8++ugt+wH6QpjNZtxxxx089thjjMfj5/t0XlDEtXvmxLV75sS1+8KI6/fM+f1eOxFhPp9z/vz534eze2ESBeAXgNZ9Hc5kMom/zF8A4/E4rt8zJK7dMyeu3TMnrt0XRly/Z87v59rd6oGbm9VmPxKJRCKRSCTyLBEFYCQSiUQikcgtRhSAXwBZlvH93//9ZFn2fJ/KC5K4fs+cuHbPnLh2z5y4dl8Ycf2eOXHtfv9Rciv3QEcikUgkEoncgsQIYCQSiUQikcgtRhSAkUgkEolEIrcYUQBGIpFIJBKJ3GJEARiJRCKRSCRyixEF4BfAj/zIj3DXXXeR5zmve93reO973/t8n9Lzzq/92q/xx//4H+f8+fMopfipn/qp6/aLCH/37/5dzp07R1EU3HfffTz00EPXHbO/v8+b3/xmxuMxGxsbfPM3fzOLxeI5fBXPD29961v5g3/wDzIajTh9+jR/6k/9KR588MHrjqnrmvvvv5/t7W2GwyFvetObuHz58nXHPProo7zxjW+kLEtOnz7Nd3/3d+Ocey5fynPO2972Nl75ylcem8Tee++9/PzP//zx/rhunz8//MM/jFKK7/iO7zjeFtfv6fmBH/gBlFLXfd1zzz3H++O6fW6eeOIJ/tyf+3Nsb29TFAWveMUreP/733+8P14znkUk8ox4+9vfLmmayn/4D/9BPvKRj8hf/st/WTY2NuTy5cvP96k9r/zcz/2c/K2/9bfkf/yP/yGA/ORP/uR1+3/4h39YJpOJ/NRP/ZT89m//tvyJP/En5O6775aqqo6P+aN/9I/Kq171KvnN3/xN+T//5//Ii1/8YvnGb/zG5/iVPPe84Q1vkB/7sR+TD3/4w/KhD31I/tgf+2Ny4cIFWSwWx8d8y7d8i9xxxx3yzne+U97//vfLV33VV8kf+kN/6Hi/c05e/vKXy3333Scf/OAH5ed+7udkZ2dHvu/7vu/5eEnPGT/90z8tP/uzPysf//jH5cEHH5S/+Tf/piRJIh/+8IdFJK7b58t73/teueuuu+SVr3ylfPu3f/vx9rh+T8/3f//3y5d/+ZfLxYsXj7+uXr16vD+u22dnf39f7rzzTvmLf/Evynve8x55+OGH5Rd/8RflE5/4xPEx8Zrx7BEF4DPkK7/yK+X+++8/vu+9l/Pnz8tb3/rW5/Gsbi5uFIAhBDl79qz843/8j4+3HR4eSpZl8l//638VEZGPfvSjAsj73ve+42N+/ud/XpRS8sQTTzxn534zcOXKFQHkXe96l4j0a5UkifzET/zE8TEf+9jHBJB3v/vdItILcK21XLp06fiYt73tbTIej6Vpmuf2BTzPbG5uyr/7d/8urtvnyXw+l5e85CXyjne8Q772a7/2WADG9fvMfP/3f7+86lWvetp9cd0+N9/zPd8jf/gP/+HPuD9eM55dYgr4GdC2LR/4wAe47777jrdprbnvvvt497vf/Tye2c3Npz71KS5dunTduk0mE173utcdr9u73/1uNjY2eO1rX3t8zH333YfWmve85z3P+Tk/n0ynUwC2trYA+MAHPkDXddet3z333MOFCxeuW79XvOIVnDlz5viYN7zhDcxmMz7ykY88h2f//OG95+1vfzvL5ZJ77703rtvnyf33388b3/jG69YJ4ufuc/HQQw9x/vx5vuRLvoQ3v/nNPProo0Bct8+Hn/7pn+a1r30tf/bP/llOnz7Nq1/9an70R3/0eH+8Zjy7RAH4DNjd3cV7f90vLcCZM2e4dOnS83RWNz9Ha/PZ1u3SpUucPn36uv3WWra2tm6ptQ0h8B3f8R189Vd/NS9/+cuBfm3SNGVjY+O6Y29cv6db36N9X8w88MADDIdDsizjW77lW/jJn/xJXvayl8V1+zx4+9vfzm/91m/x1re+9Sn74vp9Zl73utfx4z/+4/zCL/wCb3vb2/jUpz7F13zN1zCfz+O6fR48/PDDvO1tb+MlL3kJv/iLv8i3fuu38tf/+l/nP/7H/wjEa8azjX2+TyASiTyV+++/nw9/+MP8+q//+vN9Ki8YvvRLv5QPfehDTKdT/vt//++85S1v4V3vetfzfVo3PY899hjf/u3fzjve8Q7yPH++T+cFxdd//dcf337lK1/J6173Ou68807+23/7bxRF8Tye2QuDEAKvfe1r+aEf+iEAXv3qV/PhD3+Yf/2v/zVvectbnuez++InRgCfATs7OxhjntLNdfnyZc6ePfs8ndXNz9HafLZ1O3v2LFeuXLluv3OO/f39W2Ztv+3bvo2f+Zmf4Vd+5Ve4/fbbj7efPXuWtm05PDy87vgb1+/p1vdo3xczaZry4he/mNe85jW89a1v5VWvehX/7J/9s7hun4MPfOADXLlyha/4iq/AWou1lne9613883/+z7HWcubMmbh+nycbGxu89KUv5ROf+ET83H0enDt3jpe97GXXbfuyL/uy4zR6vGY8u0QB+AxI05TXvOY1vPOd7zzeFkLgne98J/fee+/zeGY3N3fffTdnz569bt1msxnvec97jtft3nvv5fDwkA984APHx/zyL/8yIQRe97rXPefn/FwiInzbt30bP/mTP8kv//Ivc/fdd1+3/zWveQ1Jkly3fg8++CCPPvrodev3wAMPXPcf4jve8Q7G4/FT/qP9YieEQNM0cd0+B69//et54IEH+NCHPnT89drXvpY3v/nNx7fj+n1+LBYLPvnJT3Lu3Ln4ufs8+Oqv/uqnWF19/OMf58477wTiNeNZ5/nuQnmh8va3v12yLJMf//Efl49+9KPyV/7KX5GNjY3rurluRebzuXzwgx+UD37wgwLIP/kn/0Q++MEPyiOPPCIifUv/xsaG/M//+T/ld37nd+RP/sk/+bQt/a9+9avlPe95j/z6r/+6vOQlL7klWvq/9Vu/VSaTifzqr/7qdbYSq9Xq+Jhv+ZZvkQsXLsgv//Ivy/vf/36599575d577z3ef2Qr8XVf93XyoQ99SH7hF35BTp069UVvK/G93/u98q53vUs+9alPye/8zu/I937v94pSSn7pl35JROK6/V452QUsEtfvM/Fd3/Vd8qu/+qvyqU99Sn7jN35D7rvvPtnZ2ZErV66ISFy3z8V73/tesdbKD/7gD8pDDz0k//k//2cpy1L+03/6T8fHxGvGs0cUgF8A/+Jf/Au5cOGCpGkqX/mVXym/+Zu/+Xyf0vPOr/zKrwjwlK+3vOUtItK39f+dv/N35MyZM5Jlmbz+9a+XBx988LrH2Nvbk2/8xm+U4XAo4/FYvumbvknm8/nz8GqeW55u3QD5sR/7seNjqqqSv/pX/6psbm5KWZbyp//0n5aLFy9e9zif/vSn5eu//uulKArZ2dmR7/qu75Ku657jV/Pc8pf+0l+SO++8U9I0lVOnTsnrX//6Y/EnEtft98qNAjCu39PzDd/wDXLu3DlJ01Ruu+02+YZv+IbrPOziun1u/tf/+l/y8pe/XLIsk3vuuUf+7b/9t9ftj9eMZw8lIvL8xB4jkUgkEolEIs8HsQYwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5BYjCsBIJBKJRCKRW4woACORSCQSiURuMaIAjEQikUgkErnFiAIwEolEIpFI5Bbj/wdGTVjYTLDojQAAAABJRU5ErkJggg==' width=640.0/>\n",
              "            </div>\n",
              "        "
            ],
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "%matplotlib ipympl\n",
        "import matplotlib\n",
        "from PIL import Image\n",
        "import matplotlib.pyplot as plt\n",
        "import torch\n",
        "\n",
        "import requests\n",
        "from transformers import SamModel, SamProcessor\n",
        "import gc\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "\n",
        "def onclick(event):\n",
        "    ix, iy = event.xdata, event.ydata\n",
        "    print(ix, iy)\n",
        "\n",
        "img_url = \"https://img.freepik.com/premium-photo/labrador-retriever-dog-panting-ginger-cat-sitting-front-dark-yellow-background_191971-28714.jpg\"\n",
        "raw_image = Image.open(requests.get(img_url, stream=True).raw).convert(\"RGB\")\n",
        "\n",
        "\n",
        "cid = fig.canvas.mpl_connect('button_press_event', onclick)\n",
        "\n",
        "imgplot = plt.imshow(raw_image)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "myMcKnVRKsot"
      },
      "outputs": [],
      "source": [
        "\n",
        "gc.collect()\n",
        "torch.cuda.empty_cache()\n",
        "\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "model = SamModel.from_pretrained(\"facebook/sam-vit-base\").to(device)\n",
        "processor = SamProcessor.from_pretrained(\"facebook/sam-vit-base\")\n",
        "\n",
        "input_points = [[[347.8673945703814, 263.6954603379773], [227.9682010219943, 311.6551377573321]]]  # 2D location of a window in the image\n",
        "\n",
        "inputs = processor(raw_image, input_points=input_points, return_tensors=\"pt\").to(device)\n",
        "outputs = model(**inputs)\n",
        "\n",
        "masks = processor.image_processor.post_process_masks(\n",
        "    outputs.pred_masks.cpu(), inputs[\"original_sizes\"].cpu(), inputs[\"reshaped_input_sizes\"].cpu()\n",
        ")\n",
        "scores = outputs.iou_scores\n",
        "del outputs, inputs\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eWTmhLD33n9w"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "def crop_mask(image, mask):\n",
        "  mask = mask.numpy()\n",
        "  nonzero_coords = np.argwhere(mask)\n",
        "  try:\n",
        "    min_row, min_col = np.min(nonzero_coords, axis=0)\n",
        "    max_row, max_col = np.max(nonzero_coords, axis=0) \n",
        "    print((min_col, min_row, max_col, max_row))\n",
        "  except:\n",
        "    return None\n",
        "  cropped_image = raw_image.crop((min_col, min_row, max_col, max_row))\n",
        "  return cropped_image\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vLmgNbRODALF",
        "outputId": "56f51cf3-e8e3-4ee2-fc9b-4688417da15f"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "DEBUG:urllib3.connectionpool:Resetting dropped connection: huggingface.co\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/config.json HTTP/1.1\" 200 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/preprocessor_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /dandelin/vilt-b32-mlm/resolve/main/tokenizer_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /openai/clip-vit-base-patch32/resolve/main/config.json HTTP/1.1\" 200 0\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Initializing CLIP model...\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /openai/clip-vit-base-patch32/resolve/main/preprocessor_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /openai/clip-vit-base-patch32/resolve/main/tokenizer_config.json HTTP/1.1\" 200 0\n",
            "DEBUG:urllib3.connectionpool:https://huggingface.co:443 \"HEAD /openai/clip-vit-base-patch32/resolve/main/vocab.json HTTP/1.1\" 200 0\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CLIP model initialized.\n"
          ]
        }
      ],
      "source": [
        "from transformers import ViltProcessor, ViltForMaskedLM, AutoModelForMaskedLM, AutoTokenizer\n",
        "\n",
        "import gc\n",
        "gc.collect()\n",
        "torch.cuda.empty_cache()\n",
        "\n",
        "multimodal_model = ViltForMaskedLM.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "multimodal_processor = ViltProcessor.from_pretrained(\"dandelin/vilt-b32-mlm\")\n",
        "model = multimodal_model.to(args.device)\n",
        "processor = multimodal_processor\n",
        "model_type = \"ViLT\"\n",
        "multimodal_model.eval()\n",
        "\n",
        "\n",
        "clip = CLIP(args.match_model)\n",
        "clip.eval()\n",
        "clip = clip.to(args.device)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W_PqKxoMGoPK"
      },
      "source": [
        "### functions for Dense Captioning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4JtpfXqpGRJ8"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import torch\n",
        "import torch.nn.functional as F\n",
        "import random\n",
        "from utils import get_init_text, update_token_mask\n",
        "import time\n",
        "\n",
        "\n",
        "def generate_step(out, gen_idx, temperature=None, top_k=0, sample=False, return_list=True):\n",
        "    \"\"\" Generate a word from out[gen_idx]\n",
        "\n",
        "    args:\n",
        "        - out (torch.Tensor): tensor of logits of size batch_size x seq_len x vocab_size\n",
        "        - gen_idx (int): location for which to generate for\n",
        "        - top_k (int): if >0, only sample from the top k most probable words\n",
        "        - sample (Bool): if True, sample from full distribution. Overridden by top_k\n",
        "    \"\"\"\n",
        "    logits = out[:, gen_idx]\n",
        "    if temperature is not None:\n",
        "        logits = logits / temperature\n",
        "    if top_k > 0:\n",
        "        kth_vals, kth_idx = logits.topk(top_k, dim=-1)\n",
        "        dist = torch.distributions.categorical.Categorical(logits=kth_vals)\n",
        "        idx = kth_idx.gather(dim=1, index=dist.sample().unsqueeze(-1)).squeeze(-1)\n",
        "    elif sample:\n",
        "        dist = torch.distributions.categorical.Categorical(logits=logits)\n",
        "        idx = dist.sample().squeeze(-1)\n",
        "    else:\n",
        "        idx = torch.argmax(logits, dim=-1)\n",
        "    return idx.tolist() if return_list else idx\n",
        "\n",
        "\n",
        "def generate_caption_step(out, gen_idx, mask, temperature=None, top_k=100):\n",
        "    # out, gen_idx=seed_len + ii, mask=token_mask, top_k=top_k, temperature=temperature\n",
        "    \"\"\" Generate a word from out[gen_idx]\n",
        "    args:\n",
        "        - out (torch.Tensor): tensor of logits of size (batch_size, seq_len, vocab_size)\n",
        "        - gen_idx (int): location for which to generate for\n",
        "        - mask (torch.Tensor): (1, vocab_size)\n",
        "        - top_k (int): candidate k\n",
        "    \"\"\"\n",
        "    logits = out[:, gen_idx]\n",
        "    if temperature is not None:\n",
        "        logits = logits / temperature\n",
        "    probs = F.softmax(logits, dim=-1)\n",
        "    probs *= (mask)\n",
        "    top_k_probs, top_k_ids = probs.topk(top_k, dim=-1)\n",
        "\n",
        "    return top_k_probs, top_k_ids\n",
        "\n",
        "def general_generation(generate_order, model_type, img_name,  model, clip, processor, image_instance, token_mask, prompt, logger, cropped_image,\n",
        "                          max_len=15, span_len=None, top_k=100, temperature=None, alpha=0.7, beta=1,\n",
        "                          max_iters=20, batch_size=1, verbose=True,):\n",
        "    \"\"\" Generate one word at a time, in L->R order \"\"\"\n",
        "    print\n",
        "    if model_type == \"ViLT\":\n",
        "        tokenizer = processor.tokenizer\n",
        "        pixel = processor.image_processor.preprocess(cropped_image, return_tensors=\"pt\").pixel_values.to(\"cuda\")\n",
        "    else:\n",
        "        tokenizer = processor\n",
        "\n",
        "    seed_len = len(prompt.split()) + 1\n",
        "    batch = get_init_text(tokenizer, prompt, max_len, batch_size)\n",
        "    # if cropped_image is not None:\n",
        "    #     image_embeds = clip.compute_image_representation_from_image_instance(cropped_image)\n",
        "    # else:\n",
        "    #     image_embeds = clip.compute_image_representation_from_image_instance(image_instance)\n",
        "    image_embeds = clip.compute_image_representation_from_image_instance(image_instance).to(\"cuda\")\n",
        "    clip_score_sequence = []\n",
        "    best_clip_score_list = [0] * batch_size\n",
        "    best_caption_list = ['None'] * batch_size\n",
        "    inp = torch.tensor(batch).to(image_embeds.device)\n",
        "    gen_texts_list = []\n",
        "\n",
        "    print(inp.device, image_embeds.device, pixel.device) \n",
        "    index_list = list(range(max_len))\n",
        "    if generate_order == \"shuffle\":\n",
        "        random.shuffle(index_list)\n",
        "\n",
        "    for iter_num in range(max_iters):\n",
        "        if generate_order != \"span\":\n",
        "            for ii in index_list:\n",
        "                if generate_order == \"random\":\n",
        "                    ii = np.random.randint(0, max_len)\n",
        "                token_mask = update_token_mask(tokenizer, token_mask, max_len, ii)\n",
        "                inp[:, seed_len + ii] = tokenizer.mask_token_id\n",
        "                inp_ = inp.clone().detach()\n",
        "\n",
        "                if model_type != \"ViLT\":\n",
        "                    out = model(input_ids=inp).logits\n",
        "                else:\n",
        "                    out = model(input_ids=inp, pixel_values = pixel).logits\n",
        "\n",
        "\n",
        "                probs, idxs = generate_caption_step(out, gen_idx=seed_len + ii, mask=token_mask, top_k=top_k,\n",
        "                                                    temperature=temperature)\n",
        "                topk_inp = inp_.unsqueeze(1).repeat(1, top_k, 1)\n",
        "                idxs_ = (idxs * token_mask[0][idxs]).long()\n",
        "                topk_inp[:, :, ii + seed_len] = idxs_\n",
        "                topk_inp_batch = topk_inp.view(-1, topk_inp.shape[-1])\n",
        "                batch_text_list = tokenizer.batch_decode(topk_inp_batch, skip_special_tokens=True)\n",
        "                clip_score, clip_ref = clip.compute_image_text_similarity_via_raw_text(image_embeds, batch_text_list)\n",
        "                final_score = alpha * probs + beta * clip_score\n",
        "                best_clip_id = final_score.argmax(dim=1).view(-1, 1)\n",
        "                inp[:, seed_len + ii] = idxs_.gather(1, best_clip_id).squeeze(-1)\n",
        "                current_clip_score = clip_ref.gather(1, best_clip_id).squeeze(-1)\n",
        "                clip_score_sequence_batch = current_clip_score.cpu().detach().numpy().tolist()\n",
        "\n",
        "        elif generate_order == \"parallel\":\n",
        "            for kk in range(max_len):\n",
        "                probs, idxs = generate_caption_step(out, gen_idx=seed_len + kk, mask=token_mask, top_k=top_k,\n",
        "                                                    temperature=temperature)\n",
        "                clip_score_sequence_batch = []\n",
        "                for jj in range(batch_size):\n",
        "                    topk_inp = inp_.unsqueeze(0).repeat(top_k, 1, 1)\n",
        "                    topk_inp[:, jj, ii + seed_len] = (idxs[jj] * token_mask[0][idxs[jj]]).long()\n",
        "                    batch_text_list = tokenizer.batch_decode(topk_inp[:, jj, :], skip_special_tokens=True)\n",
        "                    single_image_embeds = image_embeds[jj].unsqueeze(0)\n",
        "                    clip_score, clip_ref = clip.compute_image_text_similarity_via_raw_text(single_image_embeds,\n",
        "                                                                                           batch_text_list)\n",
        "                    final_score = alpha * probs[jj, :] + beta * clip_score\n",
        "                    best_clip_id = final_score.argmax()\n",
        "                    inp[jj][seed_len + kk] = idxs[jj][best_clip_id]\n",
        "                    current_clip_score = clip_ref[0][best_clip_id]\n",
        "                    clip_score_sequence_batch.append(current_clip_score.cpu().item())\n",
        "        else:\n",
        "            for span_start in range(0, max_len, span_len):\n",
        "                span_end = min(span_start + span_len, max_len)\n",
        "                inp[:, seed_len + span_start: seed_len + span_end] = tokenizer.mask_token_id\n",
        "                out = model(input_ids=inp, pixel_values=pixel).logits\n",
        "                for ii in range(span_start, span_end):\n",
        "                    token_mask = update_token_mask(tokenizer, token_mask, max_len, ii)\n",
        "                    inp_ = inp.clone().detach()\n",
        "                    probs, idxs = generate_caption_step(out, gen_idx=seed_len + ii, mask=token_mask, top_k=top_k,\n",
        "                                                        temperature=temperature)\n",
        "                    topk_inp = inp_.unsqueeze(1).repeat(1, top_k, 1)\n",
        "                    idxs_ = (idxs * token_mask[0][idxs]).long()\n",
        "                    topk_inp[:, :, ii + seed_len] = idxs_\n",
        "                    topk_inp_batch = topk_inp.view(-1, topk_inp.shape[-1])\n",
        "                    batch_text_list = tokenizer.batch_decode(topk_inp_batch, skip_special_tokens=True)\n",
        "                    clip_score, clip_ref = clip.compute_image_text_similarity_via_raw_text(image_embeds,\n",
        "                                                                                           batch_text_list)\n",
        "                    final_score = alpha * probs + beta * clip_score\n",
        "                    best_clip_id = final_score.argmax(dim=1).view(-1, 1)\n",
        "                    inp[:, seed_len + ii] = idxs_.gather(1, best_clip_id).squeeze(-1)\n",
        "                    current_clip_score = clip_ref.gather(1, best_clip_id).squeeze(-1)\n",
        "                    clip_score_sequence_batch = current_clip_score.cpu().detach().numpy().tolist()\n",
        "\n",
        "        if verbose and np.mod(iter_num + 1, 1) == 0:\n",
        "            for_print_batch = tokenizer.batch_decode(inp)\n",
        "            cur_text_batch = tokenizer.batch_decode(inp, skip_special_tokens=True)\n",
        "            for jj in range(batch_size):\n",
        "                if best_clip_score_list[jj] < clip_score_sequence_batch[jj]:\n",
        "                    best_clip_score_list[jj] = clip_score_sequence_batch[jj]\n",
        "                    best_caption_list[jj] = cur_text_batch[jj]\n",
        "                logger.info(f\"iter {iter_num + 1}, The {jj + 1}-th image: {img_name[jj]},\"\n",
        "                            f\"clip score {clip_score_sequence_batch[jj]:.3f}: \" + for_print_batch[jj])\n",
        "        gen_texts_list.append(cur_text_batch)\n",
        "        clip_score_sequence.append(clip_score_sequence_batch)\n",
        "    gen_texts_list.append(best_caption_list)\n",
        "    clip_score_sequence.append(best_clip_score_list)\n",
        "\n",
        "    return gen_texts_list, clip_score_sequence\n",
        "\n",
        "\n",
        "def generate_caption(img_name, model_type, model, clip, tokenizer, image_instance, token_mask, logger, cropped_image,\n",
        "                     prompt=\"\", batch_size=1, max_len=15,\n",
        "                     top_k=100, temperature=1.0, max_iter=500, alpha=0.7, beta=1,\n",
        "                     generate_order=\"sequential\" ):\n",
        "    # main generation functions to call\n",
        "    start_time = time.time()\n",
        "\n",
        "    generate_texts, clip_scores = general_generation(generate_order, model_type, img_name, model, clip, tokenizer, image_instance,\n",
        "                                                        token_mask, prompt, logger, cropped_image,\n",
        "                                                        batch_size=batch_size, max_len=max_len, top_k=top_k,\n",
        "                                                        alpha=alpha, beta=beta, temperature=temperature,\n",
        "                                                        max_iters=max_iter,)\n",
        "\n",
        "    logger.info(\"Finished in %.3fs\" % (time.time() - start_time))\n",
        "\n",
        "\n",
        "    final_caption = generate_texts[-2]\n",
        "    best_caption = generate_texts[-1]\n",
        "    for i in range(batch_size):\n",
        "        logger.info(f\"The {i + 1}-th image: {img_name[i]}\")\n",
        "        logger.info(f\"final caption: {final_caption[i]}\")\n",
        "        logger.info(f\"best caption: {best_caption[i]}\")\n",
        "    return generate_texts, clip_scores\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WOQLkxZMGAu8"
      },
      "outputs": [],
      "source": [
        "def run_cropped_caption(args, lm_model, lm_tokenizer, clip, token_mask, logger, model_type, prompt, cropped_image, image_instance = None, image_path = None):\n",
        "    FinalCaptionList = []\n",
        "    BestCaptionList = []\n",
        "    if image_path is not None:\n",
        "      logger.info(f\"Processing: {image_path}\")\n",
        "      image_instance = Image.open(image_path).convert(\"RGB\")\n",
        "      img_name = [image_path.split(\"/\")[-1]]\n",
        "    else:\n",
        "      image_path=\"제발\"\n",
        "    for sample_id in range(args.samples_num):\n",
        "        logger.info(f\"Sample {sample_id}: \")\n",
        "        gen_texts, clip_scores = generate_caption(generate_order=args.order, \n",
        "                                                  model_type=model_type, \n",
        "                                                  img_name=image_path, \n",
        "                                                  model=lm_model, \n",
        "                                                  clip=clip, \n",
        "                                                  tokenizer=lm_tokenizer, \n",
        "                                                  image_instance=image_instance, \n",
        "                                                  token_mask=token_mask, \n",
        "                                                  prompt=prompt, \n",
        "                                                  logger=logger,\n",
        "                                                  cropped_image=cropped_image,\n",
        "                                                  batch_size=args.batch_size, \n",
        "                                                  max_len=args.sentence_len,\n",
        "                                                  top_k=args.candidate_k,\n",
        "                                                  temperature=args.lm_temperature,\n",
        "                                                  max_iter=args.num_iterations,\n",
        "                                                  alpha=args.alpha,\n",
        "                                                  beta=args.beta,\n",
        "                                                  )\n",
        "        \n",
        "        \n",
        "        FinalCaptionStr = \"Sample {}: \".format(sample_id + 1) + gen_texts[-2][0]\n",
        "        BestCaptionStr = \"Sample {}: \".format(sample_id + 1) + gen_texts[-1][0]\n",
        "        FinalCaptionList.append(FinalCaptionStr)\n",
        "        BestCaptionList.append(BestCaptionStr)\n",
        "    return FinalCaptionList, BestCaptionList   \n",
        "def stopandmask(tokenizer, model_type):\n",
        "  if model_type == \"ViLT\":\n",
        "    tokenizer = tokenizer.tokenizer\n",
        "  with open(args.stop_words_path,'r',encoding='utf-8') as stop_words_file:\n",
        "      stop_words = stop_words_file.readlines()\n",
        "      stop_words_ = [stop_word.rstrip('\\n') for stop_word in stop_words]\n",
        "      stop_words_ += args.add_extra_stopwords\n",
        "      stop_ids = tokenizer.convert_tokens_to_ids(stop_words_)\n",
        "      token_mask = torch.ones((1,tokenizer.vocab_size))\n",
        "      for stop_id in stop_ids:\n",
        "          token_mask[0,stop_id]=0\n",
        "      token_mask = token_mask.to(args.device)\n",
        "  return stop_words, stop_ids, token_mask"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xAlm9vSp5ypn",
        "outputId": "61038db7-45e5-4102-f17b-1a625c505be4"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 70 9\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 91 65445\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 70 9\n",
            "DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 91 65445\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "\n",
        "example_name = 'orig.png'\n",
        "example_img_path = os.path.join(os.getcwd(),\"examples\", example_name)\n",
        "\n",
        "cropped = 'cat.png'\n",
        "cropped_img_path = os.path.join(os.getcwd(),\"examples\", cropped)\n",
        "\n",
        "crop = Image.open(cropped_img_path).convert(\"RGB\")\n",
        "crop = np.array(crop)\n",
        "\n",
        "raw_image = Image.open(example_img_path).convert(\"RGB\")\n",
        "raw_image = np.array(raw_image)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0pYCpBFn59Dn",
        "outputId": "4e0ffa4e-c75b-465c-a8cb-5ec4adf0a5e3"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Sample 0: \u001b[0m\n",
            "INFO:ConZIC:Sample 0: \n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "cuda:0 cuda:0 cuda:0\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "iter 1, The 1-th image: 제,clip score 0.317: [CLS] image of a cat and an in the middle with the left paw [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 1, The 1-th image: 제,clip score 0.317: [CLS] image of a cat and an in the middle with the left paw [SEP]\n",
            "iter 2, The 1-th image: 제,clip score 0.380: [CLS] image of a cat and dog in white background on front left side [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 2, The 1-th image: 제,clip score 0.380: [CLS] image of a cat and dog in white background on front left side [SEP]\n",
            "iter 3, The 1-th image: 제,clip score 0.379: [CLS] image of a cat and dog against white background standing front to right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 3, The 1-th image: 제,clip score 0.379: [CLS] image of a cat and dog against white background standing front to right [SEP]\n",
            "iter 4, The 1-th image: 제,clip score 0.397: [CLS] image of a cat and puppy and white background left facing to right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 4, The 1-th image: 제,clip score 0.397: [CLS] image of a cat and puppy and white background left facing to right [SEP]\n",
            "iter 5, The 1-th image: 제,clip score 0.353: [CLS] image of a cat and beige on white background both left to right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 5, The 1-th image: 제,clip score 0.353: [CLS] image of a cat and beige on white background both left to right [SEP]\n",
            "iter 6, The 1-th image: 제,clip score 0.397: [CLS] image of a cat and puppy and white background from left to right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 6, The 1-th image: 제,clip score 0.397: [CLS] image of a cat and puppy and white background from left to right [SEP]\n",
            "iter 7, The 1-th image: 제,clip score 0.364: [CLS] image of a cat and beige on white background from left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 7, The 1-th image: 제,clip score 0.364: [CLS] image of a cat and beige on white background from left on right [SEP]\n",
            "iter 8, The 1-th image: 제,clip score 0.399: [CLS] image of a cat and puppy and beige background from left to right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 8, The 1-th image: 제,clip score 0.399: [CLS] image of a cat and puppy and beige background from left to right [SEP]\n",
            "iter 9, The 1-th image: 제,clip score 0.346: [CLS] image of a cat and person of white background from left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 9, The 1-th image: 제,clip score 0.346: [CLS] image of a cat and person of white background from left on right [SEP]\n",
            "iter 10, The 1-th image: 제,clip score 0.334: [CLS] image of a cat with front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 10, The 1-th image: 제,clip score 0.334: [CLS] image of a cat with front on beige background on left on right [SEP]\n",
            "iter 11, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 11, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 12, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 12, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 13, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 13, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 14, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 14, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 15, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 15, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 16, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 16, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 17, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 17, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 18, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 18, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 19, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 19, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "iter 20, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\u001b[0m\n",
            "INFO:ConZIC:iter 20, The 1-th image: 제,clip score 0.342: [CLS] image of a cat in front on beige background on left on right [SEP]\n",
            "Finished in 13.249s\u001b[0m\n",
            "INFO:ConZIC:Finished in 13.249s\n",
            "The 1-th image: 제\u001b[0m\n",
            "INFO:ConZIC:The 1-th image: 제\n",
            "final caption: image of a cat in front on beige background on left on right\u001b[0m\n",
            "INFO:ConZIC:final caption: image of a cat in front on beige background on left on right\n",
            "best caption: image of a cat and puppy and beige background from left to right\u001b[0m\n",
            "INFO:ConZIC:best caption: image of a cat and puppy and beige background from left to right\n"
          ]
        }
      ],
      "source": [
        "# @title Run Dense Captioning \n",
        "import gc\n",
        "gc.collect()\n",
        "torch.cuda.empty_cache()\n",
        "\n",
        "# @title Image captioning\n",
        "\n",
        "\n",
        "args.alpha = 0.2\n",
        "args.beta = 2\n",
        "args.num_iterations = 20\n",
        "\n",
        "\n",
        "stop_words, stop_ids, token_mask = stopandmask(processor, model_type)\n",
        "\n",
        "args.candidate_k = 10\n",
        "FinalCaption, BestCaption = run_cropped_caption(args=args, \n",
        "                                                lm_model=model, \n",
        "                                                lm_tokenizer=processor, \n",
        "                                                clip=clip, \n",
        "                                                token_mask=token_mask, \n",
        "                                                logger=logger, \n",
        "                                                model_type=model_type, \n",
        "                                                cropped_image=crop, \n",
        "                                                prompt = \"image of a\",\n",
        "                                                image_instance=raw_image ,\n",
        "                                                image_path=None) "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "id": "bCFZs4jS__wH"
      },
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",
            "_dom_classes": [],
            "_figure_label": "Figure 3",
            "_image_mode": "diff",
            "_message": "",
            "_model_module": "jupyter-matplotlib",
            "_model_module_version": "^0.11",
            "_model_name": "MPLCanvasModel",
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            "_rubberband_width": 0,
            "_rubberband_x": 0,
            "_rubberband_y": 0,
            "_size": [
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            "_view_count": null,
            "_view_module": "jupyter-matplotlib",
            "_view_module_version": "^0.11",
            "_view_name": "MPLCanvasView",
            "capture_scroll": false,
            "footer_visible": true,
            "header_visible": true,
            "layout": "IPY_MODEL_02546cb2482b4769bc3ffcf2513edef7",
            "pan_zoom_throttle": 33,
            "resizable": true,
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