{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "825fe381",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "This notebook demonstrates the process of training a new openWakeWord model, using synthetic speech generated with open-source TTS models, and negative data representing music, noise, and speech. While the process here is complete, only small samples of datasets are utilized so that a new model can be trained on CPUs. In practice, much larger volumes of data (both positive and negitive examples) is needed to produce robust models. See the [documentation](https://github.com/dscripka/openWakeWord/tree/main/docs/models) for the pre-trained openWakeWord models for more information about how these models were trained."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd8e4597",
   "metadata": {},
   "source": [
    "To start, we'll need to install the requirements needed to train new openWakeWord models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ba07a8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install requirements (it's recommended that you do this in a new virtual environment)\n",
    "\n",
    "# !pip install openwakeword\n",
    "# !pip install speechbrain\n",
    "# !pip install datasets\n",
    "# !pip install scipy matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c914b0c9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:26:26.308309Z",
     "start_time": "2023-02-18T03:26:24.785801Z"
    }
   },
   "outputs": [],
   "source": [
    "# Imports\n",
    "\n",
    "import os\n",
    "import collections\n",
    "import numpy as np\n",
    "from numpy.lib.format import open_memmap\n",
    "from pathlib import Path\n",
    "from tqdm import tqdm\n",
    "import openwakeword\n",
    "import openwakeword.data\n",
    "import openwakeword.utils\n",
    "import openwakeword.metrics\n",
    "\n",
    "import scipy\n",
    "import datasets\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "from torch import nn\n",
    "import IPython.display as ipd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b40a7f25",
   "metadata": {},
   "source": [
    "# Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aee94c6e",
   "metadata": {},
   "source": [
    "## Download Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00ea736a",
   "metadata": {},
   "source": [
    "Next we'll load the data used for training. For the purposes of this demonstration, we'll use a small set of positive and negative.\n",
    "\n",
    "For the positive data, there are ~3400 synthetic examples of the phrase \"turn on the office lights\" that were produced with the text-to-speech models documented in a [separate repo](https://github.com/dscripka/synthetic_speech_dataset_generation).\n",
    "\n",
    "These positive examples can be downloaded [here](https://f002.backblazeb2.com/file/openwakeword-resources/data/turn_on_the_office_lights.tar.gz).\n",
    "\n",
    "For negative data, we'll use small, already prepared samples of the [fma-large dataset](https://github.com/mdeff/fma) for music, the [FSD50k dataset](https://zenodo.org/record/4060432#.Y-hA2BzMJhE) for noise, and the [Common Voice 11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) dataset for speech.\n",
    "\n",
    "The fma-large sample can be downloaded [here](https://f002.backblazeb2.com/file/openwakeword-resources/data/fma_sample.zip), and then extracted into the working director.\n",
    "\n",
    "The FSD50k sample can be downloaded [here](https://f002.backblazeb2.com/file/openwakeword-resources/data/fsd50k_sample.zip), and then extracted into the working directory.\n",
    "\n",
    "And we'll use the HuggingFace Datasets library to get a portion of the test split of the Common Voice 11 (CV11) corpus.\n",
    "\n",
    "Note the data provided here is intended for non-commerical applications only; you will need to verify the license status of this (and other) data if you intend to use it for commerical purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "a31f760c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-12T16:08:32.045657Z",
     "start_time": "2023-02-12T16:07:24.104475Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Reading metadata...: 16354it [00:00, 26183.62it/s]\n",
      "100%|██████████| 5000/5000 [00:44<00:00, 112.28it/s]\n"
     ]
    }
   ],
   "source": [
    "# Download CV11 test split from HuggingFace, and convert the audio into 16 khz, 16-bit wav files\n",
    "\n",
    "cv_11 = datasets.load_dataset(\"mozilla-foundation/common_voice_11_0\", \"en\", split=\"test\", streaming=True)\n",
    "cv_11 = cv_11.cast_column(\"audio\", datasets.Audio(sampling_rate=16000, mono=True)) # convert to 16-khz\n",
    "cv_11 = iter(cv_11)\n",
    "\n",
    "# Convert and save clips (only first 5000)\n",
    "limit = 5000\n",
    "for i in tqdm(range(limit)):\n",
    "    example = next(cv_11)\n",
    "    output = os.path.join(\"cv11_test_clips\", example[\"path\"][0:-4] + \".wav\")\n",
    "    os.makedirs(os.path.dirname(output), exist_ok=True)\n",
    "\n",
    "    wav_data = (example[\"audio\"][\"array\"]*32767).astype(np.int16) # convert to 16-bit PCM format\n",
    "    scipy.io.wavfile.write(output, 16000, wav_data)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a12ab3d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-12T02:04:47.611837Z",
     "start_time": "2023-02-12T02:04:47.606080Z"
    }
   },
   "source": [
    "## Compute Audio Embeddings"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfea6a2b",
   "metadata": {},
   "source": [
    "Once all the data is downloaded, we can now get the audio embeddings for the positive and negative clips. As this part of the openWakeWord model is frozen (i.e., not updated during training), it makes sense to pre-compute these features so that they only need to be prepared once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "473349ce",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:26:45.282504Z",
     "start_time": "2023-02-18T03:26:45.093446Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dscripka/anaconda3/envs/torch_gpu/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:54: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'CPUExecutionProvider'\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Create audio pre-processing object to get openWakeWord audio embeddings\n",
    "\n",
    "F = openwakeword.utils.AudioFeatures()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e757355",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-12T02:14:32.160470Z",
     "start_time": "2023-02-12T02:14:32.154438Z"
    }
   },
   "source": [
    "### Negative Clips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ab401215",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:27:23.911209Z",
     "start_time": "2023-02-18T03:26:47.968057Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "200it [00:00, 2779.44it/s]\n",
      "100%|██████████| 200/200 [00:01<00:00, 141.58it/s]\n",
      "1000it [00:00, 2806.48it/s]\n",
      "100%|██████████| 1000/1000 [00:05<00:00, 177.36it/s]\n",
      "5000it [00:01, 2555.99it/s]\n",
      "100%|██████████| 5000/5000 [00:26<00:00, 188.73it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6096 negative clips after filtering, representing ~12.0 hours\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Get negative example paths, filtering out clips that are too long or too short\n",
    "\n",
    "negative_clips, negative_durations = openwakeword.data.filter_audio_paths(\n",
    "    [\n",
    "        \"fma_sample\",\n",
    "        \"fsd50k_sample\",\n",
    "        \"cv11_test_clips\"\n",
    "    ],\n",
    "    min_length_secs = 1.0, # minimum clip length in seconds\n",
    "    max_length_secs = 60*30, # maximum clip length in seconds\n",
    "    duration_method = \"header\" # use the file header to calculate duration\n",
    ")\n",
    "\n",
    "print(f\"{len(negative_clips)} negative clips after filtering, representing ~{sum(negative_durations)//3600} hours\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "221d8662",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:28:06.568812Z",
     "start_time": "2023-02-18T03:28:06.524651Z"
    }
   },
   "outputs": [],
   "source": [
    "# Use HuggingFace datasets to load files from disk by batches\n",
    "\n",
    "audio_dataset = datasets.Dataset.from_dict({\"audio\": negative_clips})\n",
    "audio_dataset = audio_dataset.cast_column(\"audio\", datasets.Audio(sampling_rate=16000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "37ec1163",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:30:38.082245Z",
     "start_time": "2023-02-18T03:29:08.355371Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 98%|█████████▊| 94/96 [01:26<00:01,  1.09it/s]\n",
      "15it [00:03,  4.61it/s]                        \n"
     ]
    }
   ],
   "source": [
    "# Get audio embeddings (features) for negative clips and save to .npy file\n",
    "# Process files by batch and save to Numpy memory mapped file so that\n",
    "# an array larger than the available system memory can be created\n",
    "\n",
    "batch_size = 64 # number of files to load, compute features, and write to mmap at a time\n",
    "clip_size = 3  # the desired window size (in seconds) for the trained openWakeWord model\n",
    "N_total = int(sum(negative_durations)//clip_size) # maximum number of rows in mmap file\n",
    "n_feature_cols = F.get_embedding_shape(clip_size)\n",
    "\n",
    "output_file = \"negative_features.npy\"\n",
    "output_array_shape = (N_total, n_feature_cols[0], n_feature_cols[1])\n",
    "fp = open_memmap(output_file, mode='w+', dtype=np.float32, shape=output_array_shape)\n",
    "\n",
    "row_counter = 0\n",
    "for i in tqdm(np.arange(0, audio_dataset.num_rows, batch_size)):\n",
    "    # Load data in batches and shape into rectangular array\n",
    "    wav_data = [(j[\"array\"]*32767).astype(np.int16) for j in audio_dataset[i:i+batch_size][\"audio\"]]\n",
    "    wav_data = openwakeword.data.stack_clips(wav_data, clip_size=16000*clip_size).astype(np.int16)\n",
    "    \n",
    "    # Compute features (increase ncpu argument for faster processing)\n",
    "    features = F.embed_clips(x=wav_data, batch_size=1024, ncpu=8)\n",
    "    \n",
    "    # Save computed features to mmap array file (stopping once the desired size is reached)\n",
    "    if row_counter + features.shape[0] > N_total:\n",
    "        fp[row_counter:min(row_counter+features.shape[0], N_total), :, :] = features[0:N_total - row_counter, :, :]\n",
    "        fp.flush()\n",
    "        break\n",
    "    else:\n",
    "        fp[row_counter:row_counter+features.shape[0], :, :] = features\n",
    "        row_counter += features.shape[0]\n",
    "        fp.flush()\n",
    "        \n",
    "# Trip empty rows from the mmapped array\n",
    "openwakeword.data.trim_mmap(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c60aa86d",
   "metadata": {},
   "source": [
    "Now we have all of the negative features prepared, and saved to fixed durations clips in a Numpy array. For this data, the array is small at ~160 MB, but in-practice the memory mapping allows the array to be very large (e.g., 100s of GBs)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b49b9c6",
   "metadata": {},
   "source": [
    "### Positive Clips"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f3f9ed0",
   "metadata": {},
   "source": [
    "First, [download](https://f002.backblazeb2.com/file/openwakeword-resources/data/turn_on_the_office_lights.tar.gz) and extract the positive clips into the working directory.\n",
    "\n",
    "Then the positive clips will be prepared in two way:\n",
    "\n",
    "1) Mixing the synthetic positive clips with negative data at random SNRs to simulate noise data\n",
    "\n",
    "2) Aligning the positive clips with background data such that the end of the input window aligns with the end of the positive clip. This way the model will learn to predict the presence of the wakeword/phrase immediately after it is spoken.\n",
    "\n",
    "In practice, there are other possible ways to augment the positive data (e.g., creating reverberation with room impulse response files, mixing with synthetic noise, etc.) but in practice we have observed that mixing with realistic background data provides the best results. Again, see the [documentation](https://github.com/dscripka/openWakeWord/tree/main/docs/models) for the pre-trained openWakeWord models for more information about the types of data augmentation used.\n",
    "\n",
    "After this prepartion, the positive clips will be converted into the openWakeWord features in the same way as the negative files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fe1964fb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:31:01.912793Z",
     "start_time": "2023-02-18T03:30:43.623741Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "3388it [00:01, 2771.26it/s]\n",
      "100%|██████████| 3388/3388 [00:17<00:00, 198.61it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3203 positive clips after filtering\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Get positive example paths, filtering out clips that are too long or too short\n",
    "\n",
    "positive_clips, durations = openwakeword.data.filter_audio_paths(\n",
    "    [\n",
    "        \"turn_on_the_office_lights\"\n",
    "    ],\n",
    "    min_length_secs = 1.0, # minimum clip length in seconds\n",
    "    max_length_secs = 2.0, # maximum clip length in seconds\n",
    "    duration_method = \"header\" # use the file header to calculate duration\n",
    ")\n",
    "\n",
    "print(f\"{len(positive_clips)} positive clips after filtering\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5d9dc47b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:31:05.710564Z",
     "start_time": "2023-02-18T03:31:05.699618Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define starting point for each positive clip based on its length, so that each one ends \n",
    "# between 0-200 ms from the end of the total window size chosen for the model.\n",
    "# This results in the model being most confident in the prediction right after the\n",
    "# end of the wakeword in the audio stream, reducing latency in operation.\n",
    "\n",
    "# Get start and end positions for the positive audio in the full window\n",
    "sr = 16000\n",
    "total_length_seconds = 3 # must be the some window length as that used for the negative examples\n",
    "total_length = int(sr*total_length_seconds)\n",
    "\n",
    "jitters = (np.random.uniform(0, 0.2, len(positive_clips))*sr).astype(np.int32)\n",
    "starts = [total_length - (int(np.ceil(i*sr))+j) for i,j in zip(durations, jitters)]\n",
    "ends = [int(i*sr) + j for i, j in zip(durations, starts)]\n",
    "\n",
    "# Create generator to mix the positive audio with background audio\n",
    "batch_size = 8\n",
    "mixing_generator = openwakeword.data.mix_clips_batch(\n",
    "    foreground_clips = positive_clips,\n",
    "    background_clips = negative_clips,\n",
    "    combined_size = total_length,\n",
    "    batch_size = batch_size,\n",
    "    snr_low = 5,\n",
    "    snr_high = 15,\n",
    "    start_index = starts,\n",
    "    volume_augmentation=True, # randomly scale the volume of the audio after mixing\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70898754",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-12T03:35:32.377177Z",
     "start_time": "2023-02-12T03:35:32.349576Z"
    }
   },
   "outputs": [],
   "source": [
    "# (Optionally) listen to mixed clips to confirm that the mixing appears correct\n",
    "\n",
    "mixed_clips, labels, background_clips = next(mixing_generator)\n",
    "ipd.display(ipd.Audio(mixed_clips[0], rate=16000, normalize=True, autoplay=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "621c2ee6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:33:35.853508Z",
     "start_time": "2023-02-18T03:31:44.655774Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 400/400 [01:50<00:00,  3.62it/s]\n",
      "4it [00:00,  5.66it/s]                       \n"
     ]
    }
   ],
   "source": [
    "# Iterate through the mixing generator, computing audio features for positive examples and saving them\n",
    "\n",
    "N_total = len(positive_clips) # maximum number of rows in mmap file\n",
    "n_feature_cols = F.get_embedding_shape(total_length_seconds)\n",
    "\n",
    "output_file = \"turn_on_the_office_lights_features.npy\"\n",
    "output_array_shape = (N_total, n_feature_cols[0], n_feature_cols[1])\n",
    "\n",
    "fp = open_memmap(output_file, mode='w+', dtype=np.float32, shape=output_array_shape)\n",
    "\n",
    "row_counter = 0\n",
    "for batch in tqdm(mixing_generator, total=N_total//batch_size):\n",
    "    batch, lbls, background = batch[0], batch[1], batch[2]\n",
    "    \n",
    "    # Compute audio features\n",
    "    features = F.embed_clips(batch, batch_size=256)\n",
    "\n",
    "    # Save computed features\n",
    "    fp[row_counter:row_counter+features.shape[0], :, :] = features\n",
    "    row_counter += features.shape[0]\n",
    "    fp.flush()\n",
    "    \n",
    "    if row_counter >= N_total:\n",
    "        break\n",
    "\n",
    "# Trip empty rows from the mmapped array\n",
    "openwakeword.data.trim_mmap(output_file)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77a31736",
   "metadata": {},
   "source": [
    "Alright! At this point the positive and negative features have been pre-computed and saved to disk, and now a model can be trained that takes these features and predicts whether the wakeword/phrase is present."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cab316e2",
   "metadata": {},
   "source": [
    "# Training the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a514773d",
   "metadata": {},
   "source": [
    "At this point, you are free to use any type of model that you like, but in practice we've observed that a simple full-connected neural network can often perform quite well. For this example notebook, we'll create and train this network in Pytorch, but any framework that can export a model to the [ONNX](https://onnx.ai/) format will also work."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0dab37e",
   "metadata": {},
   "source": [
    "## Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c7ed4de5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:33:52.884948Z",
     "start_time": "2023-02-18T03:33:51.191681Z"
    }
   },
   "outputs": [],
   "source": [
    "# Load the data prepared in previous steps (it's small enough to load entirely in memory)\n",
    "\n",
    "negative_features = np.load(\"negative_features.npy\")\n",
    "positive_features = np.load(\"turn_on_the_office_lights_features.npy\")\n",
    "\n",
    "X = np.vstack((negative_features, positive_features))\n",
    "y = np.array([0]*len(negative_features) + [1]*len(positive_features)).astype(np.float32)[...,None]\n",
    "\n",
    "# Make Pytorch dataloader\n",
    "batch_size = 512\n",
    "training_data = torch.utils.data.DataLoader(\n",
    "    torch.utils.data.TensorDataset(torch.from_numpy(X), torch.from_numpy(y)),\n",
    "    batch_size = batch_size,\n",
    "    shuffle = True\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d1ba9e4",
   "metadata": {},
   "source": [
    "## Define Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d7c71798",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:33:54.913238Z",
     "start_time": "2023-02-18T03:33:54.896447Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define fully-connected network in PyTorch\n",
    "\n",
    "layer_dim = 32\n",
    "fcn = nn.Sequential(\n",
    "                    nn.Flatten(),\n",
    "                    nn.Linear(X.shape[1]*X.shape[2], layer_dim), # since the input is flattened, it's timesteps*feature columns\n",
    "                    nn.LayerNorm(layer_dim),\n",
    "                    nn.ReLU(),\n",
    "                    nn.Linear(layer_dim, layer_dim),\n",
    "                    nn.LayerNorm(layer_dim),\n",
    "                    nn.ReLU(),\n",
    "                    nn.Linear(layer_dim, 1),\n",
    "                    nn.Sigmoid(),\n",
    "                )\n",
    "\n",
    "loss_function = torch.nn.functional.binary_cross_entropy\n",
    "optimizer = torch.optim.Adam(fcn.parameters(), lr=0.001)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bb834c1",
   "metadata": {},
   "source": [
    "## Train Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5bc28f8b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:33:59.286835Z",
     "start_time": "2023-02-18T03:33:57.795926Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10/10 [00:01<00:00,  6.74it/s]\n"
     ]
    }
   ],
   "source": [
    "# Define training loop, metrics, and logging\n",
    "\n",
    "n_epochs = 10\n",
    "history = collections.defaultdict(list)\n",
    "for i in tqdm(range(n_epochs), total=n_epochs):\n",
    "    for batch in training_data:\n",
    "        # Get data for batch\n",
    "        x, y = batch[0], batch[1]\n",
    "        \n",
    "        # Get weights for classes, and assign 10x higher weight to negative class\n",
    "        # to help the model learn to not have too many false-positives\n",
    "        # As you have more data (both positive and negative), this is less important\n",
    "        weights = torch.ones(y.shape[0])\n",
    "        weights[y.flatten() == 1] = 0.1\n",
    "        \n",
    "        # Zero gradients\n",
    "        optimizer.zero_grad()\n",
    "        \n",
    "        # Run forward pass\n",
    "        predictions = fcn(x)\n",
    "        \n",
    "        # Update model parameters\n",
    "        loss = loss_function(predictions, y, weights[..., None])\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        \n",
    "        # Log metrics\n",
    "        history['loss'].append(float(loss.detach().numpy()))\n",
    "        \n",
    "        tp = sum(predictions.flatten()[y.flatten() == 1] >= 0.5)\n",
    "        fn = sum(predictions.flatten()[y.flatten() == 1] < 0.5)\n",
    "        history['recall'].append(float(tp/(tp+fn).detach().numpy()))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4231dd84",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:34:01.172348Z",
     "start_time": "2023-02-18T03:34:01.043030Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot training metrics\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(history['loss'], label=\"loss\")\n",
    "plt.plot(history['recall'], label=\"recall\")\n",
    "plt.legend()\n",
    "plt.ylim(0,1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03a3ae78",
   "metadata": {},
   "source": [
    "## Try the Model on an Example Clip"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c43bb6",
   "metadata": {},
   "source": [
    "To confirm that the model is working as expected, let's test it on an example audio file (obtained from Youtube) of someone talking and then saying the phrase \"turn on the office lights\" at the end of the clip. We'll simulate how the model would be used in production, by predicting every 80 ms (1280 samples) and plotting the predictions over time.\n",
    "\n",
    "This clip is a good sanity test to confirm the model is performing in the right way, as it contains about ~30 seconds of speech that does no contain the target phrase, but does contain related words (e.g., \"lights\") that should not result in an activation. So ideally, the model scores are low up to the end of the recording, where there should then be a spike right after the target spoken phrase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d6ad350e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:38:17.596854Z",
     "start_time": "2023-02-18T03:38:16.926888Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 394/394 [00:00<00:00, 19403.48it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load data\n",
    "sr, dat = scipy.io.wavfile.read(\"training_tutorial_data/turn_on_the_office_lights_test_clip.wav\")\n",
    "\n",
    "# Pre-compute audio features using helper function\n",
    "features = F._get_embeddings(dat)\n",
    "\n",
    "# Get predictions for each window\n",
    "scores = []\n",
    "for i in tqdm(range(0, features.shape[0]-28)): # 28 is the number of timestep frames for this model\n",
    "    window = features[i:i+28][None,]\n",
    "    with torch.no_grad():\n",
    "        scores.append(float(fcn(torch.from_numpy(window)).detach().numpy()))\n",
    "    \n",
    "plt.figure()\n",
    "_ = plt.plot(scores)\n",
    "_ = plt.ylim(0,1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6531eefd",
   "metadata": {},
   "source": [
    "Overall, the model is working well on this test clip. There are a few spikes around the word \"lights\" spoken in other contexts, but the clear activation is around the entire phrase.\n",
    "\n",
    "To make this test a little more difficult, let's arbitrarily mix the test clip with some background music from the fma-large dataset at a low signal-to-noise ratio to simulate a more realistic (and challenging) scenario. Listen to the clip below to get a more intuitive feel of what the type of audio environment this represents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2f72631b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:40:11.733430Z",
     "start_time": "2023-02-18T03:40:11.721719Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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/p3+tv7n9TP0JQm/IUAl4h6QG7UZOBqmGk4ZaRhdD1kAfPkM91jxWOyB7OvxMfg5+cr9zQvwExEavylnMQgpySBzHAcVfxCvC1QBmfnM+Zn+YwMyA8L/qgOUCwINswlZBXj9rPNe6/fr6fBm8zn59gTiFdUmGysfHm0SWQis8bjfd+JN50vjot0p4OXtDvND7arpuuc/5uHjndzC0rTSVNzK6fX2mAA+CKIQIxZQDWD+PfBQ4aDW09PV1m7Z+tsc5D3sDOxW5rThxOKJ51ro6eSR67r4Qf/0AkwF+AWzDIYQIQMr7R/bYNpy34vai9OZ1cblo/Lj87D51gR1C4wM6AW3BJ4O4hTFGQAjuyCkFtsZCRcjApP3N/mR9KXyDv13AtX5ZvaX/o4CfwHJAqICWwEnB9oLFwcjBfAFCwgjE80hOiucLOgstiYAFlkJ0v5H/6QOHxbXG20t4TR/KWskZyWSHEQPpgEx7q7iCuqw+jwN6B0jLXc3eznsNbgwAiqKG2kIfQSoCkwQkhYCEWkOkBt9IkogmiFzINEY+BARCzIF4gGKA9oNKSOSMIErEScNJx0d2Qw7/J/rKeEU4sju7f8VDC0SaRPHEkIRGQMv6xLhPehH72Lzyv0XDTQZUB6/G/4UNBPJFYUUkA5fBpH+m/bt6mLlleuy6u3ie+nh8t3nbN4i6+X34/lT/e3+WP2f/Gj5GPwBBCj87erP3eHLPcbr1UHnVPVY+/P3EvnK+ufyuObl1/LKQ8tY0T/Sj9fE5Ufzlf4ABh0C5fwo/vf8tPb87o/g69Gm0UjSN8lEwlTB1cK6xynLtsWBwY3PQeM562D1VAYHExcaTBruFUgS+ghH+T3iz8p9wzfIx9CV4Ivs9euR9LMACQKzBQkIBP928Wro0eZJ56jrrP6QErcXuRi1GaoWkhElA+XvRfGCAOn+rPUe+8EAGvys/FAC9f4k9nz04/z8AhkAogEZCooSgR0LH/IVbReDFpgGXPTL3nPU2eGD7RD7ng9CEXMSxSGWIlwZGRf8EWcL9ASn/SMBlgiODcsWXxl5FeIZAB3FEnUDfPcz9iv9Qf/h/en/ngTNCQsMYQOw9XrxFvcVAJAKaxkXLE43CDTFLJQp9iVCH4gWIwqf85XaTtcg5SfuffNQAuAaui+9MQApdSaBIJ4RjAPM+J/1cPz6Cb8Ynhl3DL0Flg6iE5oGdPr3/i4ItwwTCkgIkhOYIJwmqiT2HH0S3gNW+2r/RAdCDNcQVheWHCsafRQ8GI4avwyF+i/lP9Fo08beIeIk6sz2qgNpE88UNAuBDu4ShAueBjYAZvTr9Y4AIwJJ/sL7+f4NBlsFqv3X9xb2AvZH8o3qoedU69DuuuwA5tHi4+RF51jrrO9i72jxxwK/EOIIxwGYBdwIHwrHABDshdqH0mTb1eyZ9Cj3wwDTDewUfxHcDHcPGRNzD04EL/j+74/w0vsNBFX/Fv7oBSsDL/Qn6fPnGO7+9NXyQe7V+kIPrhYvE1QNYwRs/Dv5LfP17Sv2WAhnFJ4ZRhoVFVYRrA0HAZvvIN7HztHNRd3n6iT0QgT0FHsZYRH+CV0F+/8S+/zxtORw5M74GQy3E+oXJReeE0wUhRGUCTAAqvVw9E/27+0c7G76gwlIEY4PDwV0/6n98/fE9Un7+AXeFbcjFSEPGdkZWhigEj4NCQFw8EnkCubV8yb5+foRB9ERRhVMF5QZCRzdHFAX+gxR/7bzGvXA/EQEOglICBMLOhCECt4DUgN5AVb/0vfI7KbuqvzVCOAMuwiYBDgHtwV4/qr7ev+BB5YK+gbmBwUPwRSzGGcY1w9MAwLw8dTNy8/UCth53uHsfvrcA7kDP/oU9SD0Iu0i5UXekdf427rtOfx5BmUSXxrFGUgUgRAhC2z+n/Hf6ovl7eQS7QL0rvLl6+Xkj90G1v7UMdgc3fHq6gGUEKIToBZzF/wT0wzV/Ofn89dDzv7NZNMl2xLsKP86CJgRQh/FJCck6iCgFYIE9/WJ8sL1n/tfBSEI/glrEKQLePzl8d3yCvnh9n3v+e149W8A5ATHA7sDkgIfAd4Bdv7Q+hkEjBTqH0ImgyYKJLcjBCJGGOwIi/u67ZPeFtvl5q7zL/4rDRkgLytCJvohfyNaGIoFwPTz5SLkZO9w+YIGaRc4H8kgoh6oFicNewWmAiMElgYyDyEbBiOcJpokOB8fFycHrPT+7PPwtv0FDpYW4BvLI5gliyM4IwgcJw++/zXrSd3A3Ovike6KArMW/CNGKGEmcSgrKRUgcxOcBAL2l/Ip9ov6fQURETgWVBg+FuAOSgfTAar7R/KB6inwtwANDB0N2gnaBBD/bPOq4Rzb1eKP6GbmN+YG7mj7bwkpFYUb+BfRD10JTfpc327R39cr3rbjO/EW/qYChAj8DBECVvOu6Y3cGs7NyWDSi+CZ7NX2dwCYBKQBMfyR9yvwaOjN5Jvj1emZ+V0G8AYABO4CPfsg7Jnch9Hh0bLgZPOH/bkCVAmoDFIJCwKL9UXi39BByeXKTNNM4LDsS/TM/XkNuxiKGUYU3AYI9Azmz9yR2ZngM/HmBXMSihFvD18PlAY5+4f1eu/l6fznSe1R/ckK1Q2IDk4MxQO+9+frO+Ua5YXsmfqvCFIPkhL4Gx0ifR4pHAkYXwf1717dIdlg3tvgIuxCA28RuRm3H7cbIRlKF/QLZv8Y9xjzDPjgAdoKcRT+G44d/BZ1DIIBtPHN5OHhleLn59n3awxxHy0rbSheIBEamhRnFS8aNBsvGZITjA5vEkYYWBhUGvwcqBaMDd//VOnE3/rowvH1+owMgRy0KYc1uDPHKaQhUBL7/CLui+Zw5XrxOgeUGKgftR9SH7AefRgTD7MEqvZw7NDy7gFOC4MSXxZIEjYNTAQU8T3eO9mk3KDc6d/b77UAGQ34GUYcMhLoB6H4auDdzc3JZM8Y1rLfzPA0ArcSWh3PGv4WkhKqATXrydjC0cbcIO5Y/VsJ9AyGDAcMuwfgABD1CuV/3PPX+NGg1N/dCOW472b4APhw94/1VPKs+nkKDQy7AyMHtRDXE6wVLxVMDD4AO/Vm6VDcVNVk2o3eld/d6Xz4wQj6GQ0ecRXmDBz9SeXT2BraheCf7msFiBbXHLUgpiElH5IcyxbZC03+zPX1+LMB2AixC4EKQApjC/wIKQTd/0f/OgUlCCwBEP7gBYMT/h3gGMcLcv9S7uHdqNrP35PjdvHoC78hli3hLrQo1yMdG68IK/bb6jHoo/OvBVoSHR4jJ4clgx9cGugQuQFa9e/xN+/K7uH7DQ1dFsEXHxFrBEn23+9q9mL+LgJCCK4PfxYKItEt8iyyJmAnLSbRHhkVTgRP9UH3DP2+/FsFERfVJLYpmieQJP4efxKAASTxR+ZY5rbvwv4fEB0XrhUtGGUaeRfLFDQQRgF98PztffSF+ykFPArcCwcSmhG7CAkD8fdi41raj95031rlgf2QFPQTPA0ADqQEgfE/4WzQrsfLzlLV/tVH3ivxsP+mA3sHxwqoAhryruK03nvlK+tY82j/pAWOCHsMLgxWBxj/ffLK5iXeidTG0JHaOem67Y3myt5w14/PGtII3JXduNqg3onn9fQXBuwRRBQEEbMJKgC2+H3vkeGu1B/Q39Pn2NHd4eoG/rEIeQYjAN35kfEr50fatNbN45fyU/ycB+YPCRLiEzgTyQyiAATtf93X2yffM+Ye9XMC4AqwFY4fxyLPI+IiSB1AFlsO1gSu/Q8ABQ/LHt0gBhwPG2MVbwW89r7qVN3X2uPkZu9W/jQRUBxQJRMt5ifqGuQNn/wK8Yn1K/zgAlISph9YJSEs4TAAKzwhRhhrCkoBqwMFCbsNOA8rDkQJKv+r/1YKBQzRCEwHYPiZ6En27g6BG9Ek5ioCKIcj3yHuH18c1xa7DlsILQvTERMVCRd/GZAcIxwLFbULLgOH+L7zIP2KClYUMRofHOQa8hc0Fp4T8Ay9A0v4suyj62z0cvqN/SMClAPoAtwHoAmkAJPxrOOX4PPiauiN/DYR+BEpC4QKCQbM+PrsrOJF2vzXi9Qpz9HWgep68cLs++4k8TvsO93Eya7Gx8zrzL7UVOSo7pf9sxGIGCsU6hMuDV75/OKB0zPRAtdk2enTtNWD2wzcCuka/Mz6QexY3kHRZs2k0h7dbOrj8sb5hgO5DOoQpA/yA9DxZulS4XPUNdvR727zle4G9on/SgMXAbr1rO8S+n0CdwBEAY4GoA2IGDYfGxqYEzAOqgZKAsz+Sfxu/0YBYPkW8Vzy6/Ut/VIQjh7RGmUUQBFUBwr+LgbBEZwOUA9UGl8YYRATGZYi1x70GlAYmg7gBEP/kfbp8P7urOcU5WzqieaD5O3yP/3WAUQORBdxGLkdoiW2KZwsyyq/Iikelh5lHxUhUh1/DX78CPf1/ZAJwQ/8D80NPAHQ8nb50QgjD5gVeSAxJvgmriqFLnstLSl7IpYZTBCgC2MVtCPkHpgVSh2gIdEapBUTDKgDgw5tHEAczR7LJ3snRCHJHyMg9B0nGaoPywAg+a0GbxY8ExkN4AutAD30M/Yt+gb0TeoE6H/pUu39+6oMdxGkDBkIqAaOBCEBlACaAsUFNgtlC1QJuwwTC/P+WOwG1gTKYsi8v2i/VtHM4Kznsu5R8Qjv0fAa853wyu4O82j4yvor+fP2dPsRAtn9OfNN57zWStBU2q7lzufG5ALkKeS654fwbPcM+MTxQ+Zk36Hi0edu5HDY0dLd1ovZqN6m7lz7zvyd/0//UfOX5XLdL9PdycfQuOTx9l0Dign2DC0SABA6CNT/g+242d/XQ+AW6f34Tgn8DikOSgyQCGcGsQdGAxr2bugO3mjaOePT8n/3yvAa8Lb2PfSd7jX59gU2BkYJkhQNH6ApnC3yJxkkLR/kE9gGyPQh3L7Q/NjK3TPePevO+yECxwXwCvYL8AofCPICMAIJC2Uc4yqQKiMhQhv0GdMbER7mGpIVLRHiCckD2gTqBxMJuQrPDNkLXwtSEsEZBB30Id0ksCOmIuAiOCeWK/oo0SKFHGsW0xBbCNv91/KH7of7mAsJETwY5CF9JeYqYC95KbIhnhpfDNMBFQf2EBsVgxc+GRMYsxhQGtwVaww7/6zsP9/t3Qrih+gz79X1pAHkCvgKKwq/CmUFgfkS8n/y0/EQ99MK2RpfGT4ScxA2CX73TeWL2zHb4dfh0wDdKeom8GT2HP6J/+f9Dvz79H3m4dtc3mLhPd0M2+/bctwp5YH3Vgr6D+YFM/6885XhneJu7i/orOHZ6HLu7/Ss/tf/fviq7v7nwuIn29/crOgm84n9SgTYA88DKQKV+CLrkefA74Hyie377WTzevl4/10DxwegDCMPsxGmEtUPfRCxEhkMOAL7/Qz9lAXDGkgk2RrcFq4Rhfti8fX64fIG4MziO+o56Q71bwmaC+/+Mfmn/60H7AvoEGsT5g93Ds0U1RfTD2MC6fl+/cMC/gKSABr7+/Vq9VH3JPep+OH8ev/RAMEGFRLXF9sS5gfr/fP4Q/53DUgcDyAhFbEMFxS/HKocOh3NHTYTHwTf/Nn91wfqEwITEw1rD4YQVBTJJZ4ttSGQG8EZDw8FCaYILAD+9+AAWBGWFIYNcQlUBCj/6AYbEbMJ2/lL9Gj2//vsBzoSsw0q/hr0ifDd7yT4l/0E9t/wxvHQ8CT0S/h99Kj1Wv4v+zft9edJ6HDjtNqo0SPNaM9H2IfnVvfh9wrtwOy478jowuHK2h/WsuKu8wb6BwGOCEAH7gBe+znxk+MO2OHPi8yJzJ3TOeE/4ivSzcpU0DXa9/OSEEYPRAAW/En1bPaqDWUXuwf1/rr7N+505KHgrtTfyIfJcM5gzgbXsPDBBX8S4B1IFgsD6/sz93vnl9pF3tfuDP2xBO4QABqHGocaZRhKDiv+Hu745Xnpg/MXAvQRPheoE6QSPBbLIZgstyYAHTMbfw8hAXcMmBrNDikGwQmxALj+zRI8FpQDEvwY/In/qg6kG04hhSBdFvgNgQo2A1b6fPYA/04U0yWJLd8xOTP+MBUotxr4EToLHP1U7evrGvuYC88WbSC9HW0RGRaOKLswjSwzHVAI4f7WA8MOpBwXKOYnVB+mHFYiCinhK6AhDxAbDGMQ3BS7JTk4JzrjMi0uPic2GOoK0wRa+1rx8/w2GFIi9h0xIugowSd5JCMffw928gLbwttQ6DX51w3yGXEYuxUvFowZwRmvCkX6S+6u233QLdkU59/1fQ5IIsUejBSYFbkTNgM978TeyNZ33KrlYOgt677wj+/M6oHqL+la3ePOOcrd07zp7fhJ/WUDRAZjBh0MUgfI8ariBNsfz2bNst2D6hDmMd6b233cpewTCVAMGPOH47zbHc3Ey1jhBvC26LroVPQc9wr4nfzv9MvclcnZxdfIgcxB1j3qpf59CcsJmgJL9z/rvttYz9nVIunf80n5UgbXEh0Y5B3wIEwSaPzr7GTdI9W44PnzOfrj+agEAhUZHPAZoBW9C8z7T/Az7HrrEvgbDw0X6BNYGXkcoBVCFIoJmehJ2U7il+OT7FIJ5BrDG4oeLR+5FDwB9+zd5YnuKPib/fQG9A5lEXMW4hf+DCUBePw1+CDzrvLQ9vAAsw9dD9oDzxFWK20uhS/LMZ4edw5EEbULYwW7EkYbDxRaEaoSTgytCdkO1Qs8A4YLihm/GzgofTm7NEgqAC3kJ3EWjBKgCnjrBOYC/3sDUAjDIpoqaSqPM+wuER8rDiL3g+JY3iXqYwAjCv4DjAj4FsMeKR8vGa4QJwNm7ATcVNvl3CvocQS9EAkHsQSxCToBofVw7DHdOdfZ4hjt+/j6D3cWkgytCS4DrO3d3snW08dmyIvcYu0e9NT+cRD8EF0DAABi+g7jXNMIzF7CMcgY28Llg+nA8v38bw2gFlIKj/5u9n/kedgh4onnQ+I96lrzbO5U9Nv+VvXV6nTdl8zRzdnUJdEc2v72DwIAAFsEtP8c8Pjmyt/A1fHZwuu69y39kgfHEDoVaxgRFKIIJPpy4yfRttC22lDpzvQC+9oFhRNAHQAgfR6MGVgN/f7E9nDzM/ikBQAJZwA0BeQQWQxnC1sNGvpU5T/omfDI8CT/WhPTFKYRExgZF3UI8fxH94HtxuuV/rUOohFKGQsk+CAhD4wC9/yZ7gbmtvEt+Bj3EQ0IHrEPvRRcLQYlRBnRJb8dOgdfBn8GSAB5ChschSQbJrslCyRrIEIYig3cCGcFbQOMCLkQExtEJ0wuBixKJoElpB9UEccK9gRpApQNpBeDG04hxSdiJwsiThqQCpv0vupL6yDvRfpW/gr4nAAfGOgY1REpFAsPrv8W9Uv38fWJ86IC0xEdCtwIig2zAxr9qvhi5xzQ3caizRDXbt2b704JyQsdBLkEUgJP+AjpMdhY0vHTMdwa8R76/fcpARL9f+yd8mb5QeXE2hLpAOeb4ZH0VfxU87T8EwkpBPH1svBo8KLevtYM5BDnDO1hA/QFCQE0CogFVvQ98KToIdX8z5nXaNgl25H18gdpCUgPyQkr98rtAOOL1Nnfzu++8ID/yxdOFloXJyXdHZwVOBR+/V7mQ+dY69PwDPot+FP5AAXPB5wMThXkDFQAvwFi/Wz8rwovD/gJtwiDCeIMBRIbC5wEqAEG86zuKwQ0CcsK0SlQLj4b+iQrI78LeQ+WC1LyHPPt9kPoKesM91r5jf6d/k/7rAc0EWcGOgnwGGEQ8g/BJfQdjgRzDckdeRJ7DOwhJyLiA1IAhAdq/PH+7BAEDcMFWBBnFZAXjhz6GgYZNBl9HvQj1yTkIUghRCLbFpgK4Aa+9gLnZPSX9IXxqgR3DAIL/BtlJKIhayi/HKILvwcU//74NAZMELcHvPnaBeoXbRCeC9cN5gIC8F7fS+M95wTl4/n6BbLz/PJ2/fzy0vRSAkIAe+zM7Jf7Lfpw84EGpgyR7+3zwQCD4tXZYujtyHHFsOiq53rtMg9MBkvqj/AI7IHexOYU50PjHPA37gDqqvSH6T/ovP+1AB75qPa29FTt5ddOy6TVxN0Q4r7uR/Xl8zXw8fOj+FT19fCb6Kzah9gU3Mjdh+n37ifsvuzA6BDl5eOH4CTvQ/zZ9uwEmhYhB0wHhxaKCHj2uPqb8nncBOYz9Kzvf/PLARMFhghjD1wYkhhAF30eoBK3B2MNqAv4CWMTAwcM97sCcQe9AH8GiACw8of2xvvRApgM0RiBJ2crwSMpKcUoxxPRFIwdAgzK+EgHxxIDBBUJpBMo+SfvK/6R95X2R/Tv7UYIBh4JGYcjBCQvDmMVdR3BDXEjVj1IJYcYYRw0Cm8KVh+QHOwXXRboEOIOWBGyFmUQ0wptGx0e1xInItkhNg6zFWMlExkHEOwUPhpQEkgIUBlMIMEQVBOKHqwPjg7VF3EF0/Yk9gDlGupZDC0HhfRQCAcL8fyaFfohAA23EGkTEPLC9OYNbv7U/fALk/LC5BztDOHLz7zN/tLh3RDk6+Z/+gUBRfVy9gsE1/wr8pv26+RuznDVedcGzSPmIPp2693v7/PX4d3r//nT5YfhbOQW29PoTfon8jftdO+Z4dfkFvbz69vlT+/C2VjKUN8e44HbL+wQ91Ty1/uu/8r4TfgW7q7bk9rh3UPYzeRB64HZ+OXC+fHlDuHn8YHsS+rj+7z8Zu/O+oEFFv1WBx0c9hzyGaAZ5gPh5k7gj+a+4sTp+/rv89/2mgn+B5YLzxzRGdoPrw7VCWsNZw/l/mT+DxJKHAYVpBYhHw0VuQnbEi8bmhayGTwR9AbbEgkbcwpfB60J7fgx954F4AmuDVwdzx+YIsskOBwPHCUjXxb4CgQTjhHiC5wQAhaOE0YTGQdzAhcLUAuWEJAVjAfX+54MCB7TK8c3ITZpMbQwSDBEKRUaUhQ2EOoFDxdhIAUJoARdC7sACQneF9gI2AXFDbUAK/xCEtsgxxhjE6gTMg4yFlwprCBjDfgOzP+D7Lb4sPSk3KHm8gFk+/35WxSID18B2Q0wBu30M/0E/hz2XvD+4iXftOzO8CDwlgHHAUv1dwHb/IPs0Pxg+KHjyvEm8e/dDOe64B3PZNaizu/OFODh1h/SqNxO1m7mHwg4Cn8HEwdu9znokerv8xr08erO8rr8HuG21FbfKc3vyeXeRdD6wWzY590Qzz3dhfjn+0H+EwQK+RbrL+Ez5p30Dur+42D0eObC1vvzvPf+21LkBvJ53pnYS+f15eXecOyL94nwAAf0IiUR4ANYD535he7XEHsPKPdCCUIPUfYDAyEZQgT1+zoOBwGZ8q0CigPQ72rtm/II8If1AwPNCl8Xfxj6DxsjXjWcKtMkpC4bH4wS+CPJHB0H9BLRDWLysPZ78DvZCOes+FDvCvusDzYSlhdaKWcwoileKRcn2RT2AeQAn/sv/BEQyxvZIrIvlCacEU4JggevDLkUZxnkG+IVhhG7H9snmifLKJwl0SC/H1geKRBGAtcJnBtSHysh9it3JHkYqiHqHt4U+hkPDCv6rvkr7X/spgMPETwW7hoAGSEUphKxC8MCRAXuCbMJqhFQGaYRzRIRFh0O2g1rDP3/BPto7LjQaM2Vz7zIydRF7pfvFO+2/6QDdQPoEjgXSAmmBTQAzO0A4i/fm9c12b7jsOhF6rLo0+gI7HTr6fBB+ff2i/K67Qbs9e/x8Znxuvlq/C/rtuZw6KzbM9363fHV7+CV5qzcXOUG8u/t6/evCdMHqfp08yvtfeTb46Lfe9TE1EfdoeRq6TXnXOLN41Turvkg/7D/sQF4/kv7kf4S+7b6bwTqBYv7UfiV9wLshedy6xLmL+rA9vv00/Mx/+gDLgwKIdMiPBoxG/INvPtu/tn6uPJg+cz53/IY/YoJTgdIDIoZPBT0C4MS8gtfA/AN1xTNET4UzxUwD94KFwzkBlADoggnBV7/4gUdBBsBigtjDxsURCB9KEYmFR1tGl0YEwu5BgIIogI2CJ4RDxZQGvIW3hGsGjEoZC9GMhU00TB9Ki8r1yozJZYhtB6UFvQJBQNOALb95AADCi4MLQr2CVIHyw30HuwsZDJtOJo3JzDdKvwihx3VF+YD1/N89bD0fPmmAr8AQ/7A/9gF+AtSCQ0HIQbJAEwA6ASSBu4CSf4c/IPzdOvl6QjosOb15L7hk+Eg6Z/vn/Lb9Sn1VvOy+Gz9f/eh7unpwuQE34/aDNtB3oPfK+EU2lDX4dtQ3jXs5fYi87TzIPKD71b00PT+8V7sXOPP2KTNWM+42EXgRe3T7xLmk+Ag4O3dsN+R5pnlBOS26S/oleVq6Gbqqut25T3kTOPC3szie+Tv4VLlket68ov3R/2X+yLqUuUS6C/iS+XI7sr1g/lo+kIAFv9MBBMWZxfVFHUVMg00Bf/89fX+8entf+926gjo7+6T6sbqS/Xz9Xz89gnZEDoUWBbLFBUSzx11Jssc+h+MJr0aBBwEIC0ScwcE/GrqXOJ33+/iHPA0AhsRtw2sEA0fcyDRJZgr+h6kGjYeYRqkHLYj5iXLJZ4j5B7BFMULTA9EEwYXCyGaJG0k1S1kNTM5CD6uPBk1/DGHLqwhAhgZGFIWmg/2Dk4SFw5pC+ASThf+GS0eGyaaMJgxnjDHKb0ZeRJ/Bmz6dvvx90n8CwuQE6QefykOLIUqPiMCGhEQ9gSs/2r+bQKCCEgDIv/PAR72O+h76xTlNdiF3SvfNdms3yDpNfDE+qACkgGR+A7tsOqd7Yvv2fPl8QTz1fW477j1hf1e+nD+0v/S/7UAFPl99MDyQfQc/Gr8DvYr7crhLduJ15HUstMM1cDQi8yZ2LbmDOcj52jppvEhAYgCVACvB7D/9/It77Lb+sctyJfIssVQyD3MoNRg4GjqLfP+84n0o/UE7czqVO857Y/qFOSw3P7kaPFe7zvmeeM13wbTws4Y1VzWKd4e6jPjtuYO+Rr9OARaD18TfRrDGcMS8g4dAs7wS+BBzufLuNUc4cTzzQYREQ0Rew04D0YLj/2J8OXuxPcA+aP4yP3x/zQLQiN3Misv0R4rDccFTA9bEc8Amf4TAof9GP+y9JXmvO0x+UwLGxqsEPwBg/wwB+4YJx1rGV8P0Qz8GUAhmCNQLPwxjy5jK2kjgxX+DPIEHPyo9efo3+Qn8w8GHRQzHMkigSTdJ8kyzTUALcUg0Q/DBGUGvQwHFW8ZbxRZDTwLWAvZD+4YYxQPC38EQe+B6XD8wPvE8wr52gSOFFwf/CSgH04QbQQc+jf0cvU97rzil+0rCEgVThg6DrL7HvQ53mDJWtzl7XjnI+bl6tnxDv/aA0P4oe3f55HgIeJ/8sL7+/hY/qsDWPn5+vAOThPJE4cXeQ74AyD8/O1/4kniuunj4+3T/NLf0vLNi9Rq5wb4dQYCHdclBBS3BXkHuwON+lP8Wvkg7LLnZOto8eX6vv2n8jvmheyB/l0H2RJpGuwJngGtBnsDexCMInUh5Bk6FL8L+AuiE/gNFwDz/K7+M/r38xDr6d6X3qPwUARbE2UQAwpfDiMKqwFUCLsTexoXKL82QjzbM6goFx30CwkDJQREAmMFCwrt/j3s1+L85Lz1DxAZI28u9i3+G0gN4AcfB68PvRK7DEQEyQMCExsb+hSmE0YMyQdGF3EkuCtKK/QbqA42A3z1kAGzEZgJdQk6HrYubzRvL/Ig7hPeDWUSshhpFm8VWiGNLSsweSw6LOwlGxbJBG74zv9vCRUEVAxpGCsatQ50+w76k/51E6ofgQwv/mT9cP9o/rEF+gw7+8EE4hBUB7EGPgzz/s3fyNxo08rgifHP5k3zVgkhCAkGVAMA+eIKDxBGAX/x5+se++XVWrTt8vv4ofaHHTQOAO58/44YJ+mGBcMkQ+1i2tL6gfmL4nDk/NftxCu8d9n87rTj0+lKCzYCTuD58KQb5AQ4AaYlGwZo8YX9YPKf2nng29jPw0y/6bbVwRrRCs6qy5PQm9mT2CvmCu9N6UnzHvfE93b1gf5++6PqQeKw1JHLb8s/2K7hN9Wsz1zQ3cY9ycnZvN972ivgtucI9c0ErgrNBbz42flP/lT18fCQDB8OWvb//8L7EuPN1zPgpt8p0o3YfeRS6fHywPmj+38H9hCMBycViiBAEscmwydvDt4QXBaCASD0zPfU/wz0CuV8/lH8cOBH9s8FyPKwGRkXie+FIJVEwxllGwoyFRZQEOAbeyfwBQDssxkjIhDr4e2EAjvrfPryEUwHnAHNDIMN//n//CEdIxprE44l9idEI/IpHRew/wIiUg7NCUwuh/7kA98zkA4t9IcoAigyAh0ZKy13Ir0oITJ9J1QmpiagHaweHSMLG7kZ6B0nGZIX0xdvFBUP1w0rFLAZtxWkEQkYxRZQE/4S7g3WAhsIewxbA/gA/vj58hzp49wE2IvoMeYr3N/x1+0C4cjuzvUn78z0eP3C+q77K/8x9b7x+fJm7frqhenh4BLa49py3T/iKeCF3Jfdqtwn34vqpexo6SfzIQHiCZILYQ0yEGULYwoRFKYQ1wi5Dx8SOAYTA0oHUf+h+foAtQF2+gcBbwSAAGkI0wxjBssIFxGDD3kObxJMEdcIaQQAALT2qO836inktuKu4NHiAOWu2I3WrNgQ1UPaVt6D38bk2ebE3nTdKd6w1nTZm+Sh4RrnqPSd7crwAvUC533lcuoS4UzdEuEC46zqcvYz+UH9LgQjAhEAVgfBDgT/VgwjGAkKDRvgICUYJR9gKhkmwSEbJEgebR1YHtsbvR4bIoUgFSQfKM0jYyCOIQQgqB2kHCUhYSLJIU4p/ip1KkAr/CkpJm8dHRZ9C+4Iigkx8mDnzPlP8p/mJ/S45VrplgFi9PvzVgYRBS//AwmtCdgBvv/d/Hb1IO8C8I/tJO7j8KPzZPZk9+361fyw+fv9eQJo/vv/hACp/r7+sQSoAo4JXQ5OCJ4U4hYjDdkPDRCSB4wMWg8AChcMzw9MC4oMBBSxDiUIrwrDBlP+BwVIBzoFkgmzCWMEHQGoAt4ADP8r/ZH8BvuZ+PHwHO7j8hbcTNWo5wbiy8tU0O/VAsKky83VWM8t0g7aVuF74tfo3/T88lHxWvde8Ifsj/Fs8m7s2eo96nnnQ+ef5YviGORM4tHfEOq68PP0TgLcDAMD6hOUFwAFAhwyFrEC4g9UFjwOLxLkFTIT0xWQFjIYihneGFIZmhmOEuIOWxLyCqQGaw9rEM8O4hjBHYcXrhtaG6oM8BELFsMKggg8B3j90e8C5mrsAupk2yvujfLX4v/5uvdB40f9PAIt9PwBXwZCASEIJQas/CD+U//f/VP+Sf0W/EX93AEDBDYAXwKKAbcAqgQRAQD49fyEA7z4Wvl5DbsTkheoIYMZCiGoJVYmMSQNHRkgOhvBGA0WshkjH0ohDSI4JWMjgx4LIIohrBkdFoUVcxQ+DyEGTAZQBlX/NgD8CTICrwRUCSkSiBKUB9UAaQbO/0fxK//M40XhLf5D4vjNhe8p6QLHi9vz73vi59v66tPqM+DG59/vdul46p/qoeHn5bDkDOYC50HjduNQ6Ufq+egI8KPueO6u7ofrReEm+vXtLe4pADn1kf/l+uYLCwnLDI4OuQ5MGRkSmBJlFEgWlhJEEgITAhLDDZAKxw8VEqgK9gw6FewQxRMLHB8V7hbwHOAXZRLgFKgVsRMAGYUZ8BDZEiMVdQsvD1sG1gRg+3D0YwKZ6uPqeeMQ5Ynx2dto3kXu4emR4FHx2e1U8Bb09e5W84XpNeyD9rrp5eI57tfmg95o5e/rdOtD8ov1WO+47MTouuzA+Ivwh/ETBDn4RfgqADADKwoRBycIJw/+FKoN0ROmFwIPUAt5DVcH2gKgCJ4BgAE2AHr4uPzmAg8BQAPBCvwQ5A4pCX0NOBF/D7UNzQmQCiT7bPfI89Ly3+yT3dPuDtyyyW7W+e4C4UHI9Ndy3FTh+szT1EXwZtMl2z/wTNx13KbqPerh4fXtQ/Pd5Ufpgew96p3q1fG8+M70ifde+iTzbPDl+ckFIwH8C6Qb+guxC78lwyP8DIUf7i9GHV4j0S4jJC01oDjbJ/oxsDSSKiEtVDHPLTwo5iH8J1wmOCK0JWAppiyyL7owwyzNLWsvpixQLMMrLydCJ7UfuRVaFY4XSAif/Mb9tvRR8Q7vduPb73r8vOxm5+3+KPxg8YwMtvjT8+wISfWB72r6XP148XbwXvuB9MTzvP+J+6z6n/3G+e/y0fB47W7q8+4K9Sn1uvDd9/oCh/k98oEG3BVKEeQFex5nLs0TvxKNLdMkXQ9lItUg5Be3HrkctRr0E8cNrhScFzYQww1CEvIQ0wzRDRsUzRdnE20Z2xlrEhMSKxIZDx0MCwUBBQT+KfFT+HDyM+as7rLlANVs3hLNmss553PX49vp4mrRFN014jPSrNP434HSOdKs3JvQK9Km3o/addvT4VbcH9qo3QDZN9Yh15HPFs4103nUrNVY2CPhruMc5XjsZPR7BZAFPAzuFeIUvRPDEcMUxQ8VD+gQyQ6aCvYIvwhAC4QMvQ5IEagY2xzNGZIbBiDPIdMgjiXuIVIgDSQjHlYYBhs+G5QVYxPVFbsTogkPAcsDhgFU8u/44gTd75Hg+/uN/OPW+fI0CRrc7+AM+oPm19d/6Army9097ZPn8978527sqOb86dPzausx5+npk+MW4y/qAupu50PqHObp4g7mGuBw3knwQ/EXAKAHcQLeEe4QfQ7kEbkbphGBDc0UOhB9CuYLwQzVBKAMVA/wCQAR+BDBDVIVmBKFEgcYVBIVFFwZdxN9CuwJmgZW/Tf5KfZB/NvvaPUG/oXm3fTp+t/vtu/d9c/pkebWAiXpvN4bAvX19+Qt7LTy0+fh3XbvAO1w5Y3w0+859vn9KPdq/DP/Lfha9Mj3mfke+bD7Rfs4AAD8Evl5C4ENWP7bEm0llA3sEZE1QCvJGKgpwzE6HbchiTpMKRkiADGOKg0knCoLI0IeDi/iJkgdeyPPIVoh7B+LJrYo1yUrKcMl8hwvHEobSBfZFTYSyRVYFtwC8/x7CtEAIvzDAUQRzQbT870LjA8A8jYADxEM6Gb8Hw1S0wTlSgY74a7iS/LM65HpR/E59cDz3/Vs8Bjuyuga50Ps2+oS95X4TeaB++AB0e6h/LUGogBpCx0JmAsrE8EGWQ0bEUn5sQFlB5Pzjf30CvgE2/LC/nUKDwkpCFkLux+oFPIErhS9FiMF3BTqGGcKBRL2C6oDQALLB7z5swQhCxD3lfkyCIoCo+nI/nMFKfhQ4WT1kgF31+HnWP5Y5L7RZOFP7lbZ4crd7FLp/tMK5tHrd9cK3ND4j98t4GD7pttF1FzrANTsv8bdWN9OygbbbN6F0qbe79uH6NPs9efb+yb00PIU/hT+aPxo88jteQF08kfw4BKV60Ht6ho2Abr7SBg0F6wUSCR7GBEUjCVWGOQZWCUIGuQXER+aFZoYaSWQFmkg/igfG+gfWil7I3McBCGSJCspBB+JH/goriNGJJwkCR3qFjQOoAJpBqYE0Pm9BwQQbPtnCn0ctxEtDTYH2xF8/4Pu9fYn5UXXM+c77CnVUuZU6Lrgo+jr6K7l1+RN+WT2l++T/Gj+keY789YBkeIx2WTxo+jC0RjkietF15PsKfew7PQDZvPBAYEOffaxBjYCxu4ZBGsPtvaV8pP+MfdY82T69/b2AST82/oHFQcCsvYRChEE6AQjDQIMdwPZ+B0BsPox8yUC6e3G2ivxTuXCxsjbf+QxzXLhCPF/2BrfjfQK6/Xc//kA+iHWK/AC6h/IaOSi4T3Dwtdg5PTU+tQn7pfuhewr/w0CdwdKB1IHDwhEAcb7RAbt+E/0DQt6/3j7uQ88HqQOvRJlJm8p9CUbJ1w4rDV1MxI5zTRmOzE4TiycOm8z5iZQMqAw/ipnOAA+czOBN7I7Qi7yLUw2dylgJWMo/iIfGAYhdyn2F44UACSsDHz67AryA6IELgNIAagHMgIsBJ/61/nLCRj7KfBT+cjxXtwt42Tth+D23uPrHOh94gr20P+V+dwE7BOsDo4PqBdfEKYA0wUABWDxPfFy+3by/PFxAeYMuQWDDiMs2STBHnEovSozIT4giSfuIy0cLR5fHdkTZRVnF5QOqgzoFJINgRDwGvgP4g1fF7MNPA5KGzgKxQglERr+n/tzAtP0Gus98YPgNdTv4UHXO85U5XjknNFB5jfs3dhi4lbzWt0QztHbRMX2vkXVqMWHxfzcWMu6wT3ayNYIyUnb2+XL3Y3pg/D15j3ybPWH443ndPSB3WrOHvQ77hLRrvhw/BznhgpbEQUF2RB9FskItP+IEfAIpfsJFvoRZQuIFbMLqBEdEUQSVhh5FDMesCDHEncVliIKH/QZuSGoIf4TjBqeGYQNnBbuECcDLglIBSEBWQSMCJYE1Q53HIMNuQ+FFIMUkg/+CawO2AdR8jvywPwg6m7P+t3t6rbL6dms7kHeVuif+grwdO7VA3T6aueF8l7zbuBQ1tneWNIrznfZ387+05vXL9cE3yPfGuTv+UPqneToAPnwP94M/Nv4Gtqf7STvfdwp33bnFOMe5Wb2RAGF/YX7swNZChsHlgjqEawRswiqBFQQywIrBFYW1wbeAlAO9gZP/FIJ6gZN/n0QkhP0BmUWtyQvHG0eCCV5G2cGuwhCAd3i/Omb9EXdN92H8bboXun3+oAAVweH+2sEiBdo+93zaQPA+kXitOQp7k7ff9iy593kbN907qrxpfa9BAsM6gEpDMcV7ANIC9kWZwHp/RkNp/9a/JYHlgPyBCsRiBi1F2Mhpiv6KQIv9Cz4OF49KTUOQphBWDpIOko/nDr4M/IyFTBxIxUmqCvLGh8rDDs6KM0yfz9jK6IymjsXL2AnnigpHNES4hPFB60Dtwgo/1z1Iw3f/KPyZww1/Aj6GRG+/+Hr/ge9BNnk/O+y877dGuD14ofUFNbt5VzV19wt9wDsAPXoCOP8uvEi+Dn0VOb42qbnJ+zG4VTi7e1c9F74GvcO99MFcv8uA30CHvWEA0ANgP/uA2sdsw3JBlYdxQk0AC0KqATC/8D6FPck9kv39/2EBPP+3AeuGEwNogn2E2UM5AaYAtn0M+TC4m7das7dz5HU0dcCzSvTZN6+3Vrl/uIl60vx/vCF6GLauOIM1zHJNcpKxuPHh8TfzKTS8tFg3p/mGOcv50HsjfE/8nrxqO9H7uPoeuxi9grpNe2T+6bvbPR3BFkCDQEjDwkXQhRKFtchrB7LFd8fNSMVHrcbgSDPGwYaLyM8IZ4YTh1rID4RBxiqHrMTShpnJckfXiKULbgv7CwfLZYu6CREGbUTDQmN+Y36VvSR6HzzQ/rV8pv3Hwn+CM8BVA2UC/P7DwP6Bkvy0O4U8Mjih+Sh5arimdyo5ibyduys8Xr0ofkQ/eH1Mfjp8VLl4ep/4lTc7+Cu327h7eLf6+HvHPKh+T3/GPyIAYQG3AAAAsMDHwOrAXT6HQB3CrbvaP1QFEP6P/v8EUH76fI6C0360P91Di8TUB3gIYMlESj0J78eIyEXF+wJqAi6/ynx1/DX+CbwbPFQAJ3/5gDkEp4SFRjfJZodgx8vIXkXjhN/EZgGJvXz87TxNd6o427zienh73cGywVdC+4QOhE2EG0GmARa/DX3avKR8GjxwOla7GTz5fXI9+n8YwO5A68E8gqKDXsRJxJOECEUWhy1GYMREx3THScWrBjmGHcV6A7oD/wVuRO/GGUmNyqaKLYtqjK7KoUySDVWLmAzGS7kIg8f/heYBDgDjgd0/2cDYRNMF/QUzyLFK38rUCIxI4kiXwm5BIoArvDC5yDicuEW34/bpt/h6NfpSelR+wL2Fud//Iv38+QW6+HhMdk318/O69NB1THNrs2F3PjZNdxQ7kHvsvI5+wj5+fsO/f72aQCeAHb74ACkAd36uQTn/279DQjf96X19/Xb6xjof/qMAhb+ERPgIYki5CScK8UrriUXHXUUtwUI9d3sd98I3CHgWN8G5PzrJPEm9gMARgWeBiEJVgcNBBT/Lfhq7XfhH9xg0s3PbM+ZzMvMTtS+3Wzay96s7LDwGPEr/kH3yOle8mbsSd7X5DfgLeG07MTuuPY1/Zf+RAbJCHb51gAbBdn2cPqECyEKQgmKHgIh1xbuHeosCigPH90mzST+FY4WqBh7DkQXWB8GHoswyzPNLG823zScKQYugyrmIEweRhVGEP4C7/qoAVj/1v9/DZ4Ptwt1F2EYyQ5xF3USYwhjCyv/APIt63vm+tsA1+HZJ9hW153h/OUW4oHt9+8i6rDqFunz5MbSCs2N0vrH8MUQzIHMoMRBz3PUtMyd2lDXSs+N2PzVN89Y2FzdldyP5Nvq5+0U7uvtYu/K8Yvv1etw7aPswOP65OXkBOBw6ZvuZPXr/uYI2gycDRkU/hQCEGkQfw2aA8b5ffCT8AbvtPB8+QcEBwbNDx8fDR3yIWEl5B6JHHEa6g74CC4EfPZ6+qf/bPeA/8MAIP0rB6QICwu7DtMP5hFjFqYNRAbVBnz77/VY/Kz7P/fI+mT5GwAVCc8HLQsdDR0MfQuaB6QEjAaMB7cHsBETFnETpByWI7keqh7uIaYggxwpFLMWfROqBuIO6himFtcj7i4VM+w+RjxANSk4tjKDJ+YnBBxxDJgPWQ3qBHsL/hXsFr8boikrLbIudTSqMforhSdxHx8XbxIBBfoB3AHS8tvyfvxF8xzy9f+0/YH5CQQyCZIEmAV7B8kCM/d28VjpBuLA4QLie+CB2qThl+hs4mLji+au3iDdieLh5YHnHOZ06ALw4/G+9dX8uPcE9Zn5yvFq5rznUONS2N/e8eXl4dHwNgGQB6ASzxukHpocOh/VHWUbMRlQDhUK8AFo9nz2UvRU+a0BGwSqCXsOCw/gFrQgyxxpGLUXJQ6uDOwMdQIA/3L+kfymAa8LhROWG9kS0wquDLcAvvxnCDAJ6gPwAhL6i+0S7QrwDO0G+cD4wvIC+hL6yPTS8nr09fNH8b72/f96+jv67ARWAj3/XQV2+rbzdPcW9q70+e546jnsDu6b7EP0cPdk+K8DFQ4XHHUcUBaMG9wUUg0ACqsCK/S652Tdz9Azz2zXbufr7qz1MAGEAP4BXQCn8pHwUvBu4W7c39jHyvbOvNNazUzLqsfJyMTYeeOX4XTgVN4e5Yvu7+MO3EXm09jJ0GbYFtCJ2cTurO4a5QDdl9P0z5PI38blzfDLIcwM0uvW1dVy39fvi/uEA9EGawZk/3/70Pl48T/tTegt3kndYt2V2fzdofgEDQYYoiWsIOgW9BLXFs8SVAp3EnEbjBVWETIRqv1/7yfxLf0TEpgiUibBI7QdwRHFEYUcwxhrF/gqKSojGuAdCyAJHh8sTjnFNoExYi4GJnERuwRGEwskQiuqJ4gUWAh1CXMQjBRKGG0YphxiLJYx0S32KH0qEDNOPjc8FS/0J7Ie1SB3LgA1CDdINScr2R3sC1YIoAshETEc+hh3ElsRIQ0PDyshpi1oPPZIqEIKMoUgihZcGvYkhyJOE+IFuwBzDHUefRVODJIYRiK7J0QrVid5HEIcShq1D5wPExA8EOYQvQwjAoX6EveR7z/x4fct+Efwn/OF+r74XQRlEEAPmg4nCKHyzOrQ9rL51efrz2/BGcd71qLiJ+xq5F7Wqtvf5sLm0efh7HLpzONH6afyIPSF7jvqCOYr2ZHNgcYCxUrJxNDj0rzUe9Xb0/XeJeO25B7ubPMA8nrre+kE58zjlea259/lCt9i5+n4L/pk+Mb8Jv68/joMQBVQEWEOSBYnHtEWFxNUFiEN+AIBAKf8O/lm+rcGZwchCP4bHyv8ImEaVBf2DGcDngOrAsj7Mfqb7+HotulQ69L2WwMt/qfzbOLV2ZfoJPTA+9wAFwTkBDAD8f4/+WTw9euk6dHhvN3Z0rLEMcoM3srvKwLFERcOcwb6B9gGZwRABikKCQxlDtERNg70B6sDWv18+CT24fAG8Br0g/IA95P+KP3l/agEdwsfBUgARf8W9wbvFu6d9bL14/S2+RT6IveR+koE7gUc/0vw/OQG7s729/K26ZPkZOxY+fQA1P4v+QD15e8O743reut89Qz+yP149/7w9fI4BCcc2x6YEXUJVPn+5nDnk+vn5Uvrlffn8TfmYO0NAZQQ+h0lJFIXWQT1/U4EmgH9+Xz5LfFw7BDug/Fw7Svf/t6F8If4R/qrAG77xwJaF2ccCR5aK0Q16i7LJzokABs8E2cVBiGDKMkhQhgbD0oQ3hgpIm8xhzTbKlQmACB3E9cVpBuwGpgakhdjEf4IcwIpAbcD6gPp+pPtAObM5xjuPewa4BLeJ/HuBSkOMgrmAiwBPgBW9/Hue+uu6t3x+/iR+dv1CPixCYwUBwruAXT7wPeKAg8R/horIFwexw2+/6P5zPUPA7kdCCHaCRj6Q+994nvuEQT0AQsBlgxlD8UQ6BdOC5n3XvgG/6z6JvCL6wz0mgAG/dD08/4S/sLrKfEK9HvnwuvG/C/9jfWq8ufn899s5X/2CQieFbkdCiCSGfgPzv8t+x0PWCGBKsErMSKgGcMWngkx+crrcOkU69XkCuiX9voAeQtEHi0gKxqDHVoZZQlN9yv1EQD4ApYAU/vh86roatQ9yZHOAtvX5dHxfPib9ckBhgyUBdcK8BczGmMX4BZMHe4dyRvHFVIWFyYvLv4tDC43MOEl0xazFu4ZoBFGEHciLyL2CAUCOA6KEwsTexYtGJwPJwFY9m75xP/7+Of30wGs+XvdjdaN18DQ79gY6Rjz+e4l62bu+uga4nLi4d715nbzfehF2iDfhfJdCjgaYxdnFDASEP6j7WbzKP5ZASL9qvv37XfRXM/X5EXj2ddJ6Kn7NfsY+6sDhfzC8JX3m/5m+s70vuKB32Dy8ebl00XWy8c8roeusrSqrb+sqr2NyAzH4co1zvLP7doc30rZ3dbP31rqP+7d9mkFdxG7DJn8Rfis/Sb7//pdAiL7UOqj794IBh0pJlAqpCnyGjgE1/Fy8ywBJwekAiwAvw44ETgVwSW7HFIPEwjS83/rFPBk8F72gAAVAhb9N/+YB/oFvQucGbcVMBO3G6AgkiTDJYckuyLVJE4l/CDBKYky8iz2JaoaLQ5IDtsbOCRAKKg1ZD8fQaBAIz1iO6g4KS4NJLsfMRgwE5YZKRvFEf4TVBsNDrb2Zu3I5NvdL+zC+Gr4Wu8h4LLiZPizCccIeQNZAFHwi+nS8/70+fHK9BD/5AFs/6QI5BlnJ+Ya1/3x+A0CywrdG7Y1EjzZLGkhaxumD3EKPhHFEnsJEvfl7ZX+BA2SFhcfkBZhEbEIP/pP8lThQddc2SDh7+58+uv2P/QA8rDeYMxm1+vwo/+cCdoKEQVZAMkFKRAEDfYFJQI19y3x6fG+8/X+/ASGBckGGwHiBfgXAib0J4wkphm7GV4s9jF9K54krB+DHiEbzR+eHzEW/hCSCO/26esG7BDp4+pL9o//3foM9u/1cOlu3n/h4+DE5jH30Pyn/RL7JvuOBsUONgz+CToITgeb+TfkRekS/4gMThR9EUARIxsvJc8oGTMTNHEhhg65Am78UgNSGkw2uka2N9sdCRygGMsPZwL78rbvh+ub44vq9/M/9pvwvO9w4/rKi8y+2g7Yj885ytPQlenh/80HiAI/+qf0sO5U6zHde86Vx9vDMc6o16raifKCApIFrAjYAcT/pgb2DIAC+OYt0HnXUuw79kn7uPWL7Mrrxuy65UjV8dR/333Wqslewcm6ULjbvFbAvrqNuba/c8QrwdG5Nb5kw+7FAtT22X/ddObR5knuzvn77inhJdnA28TjO93h5If8QhJxF1QGVAktGNkYpBnBJAgqSCQ+HFAkXDPqMSU4VEnpR7Y60y/qKoUjyyCUH8khjShxIt0Y7hqsEPIJgQ99Cu/9vPq7BR0GrAk6DbcABP1GCY4F3gB7AkoD0PrV7FAG0fGs6R8kGxIi6pgJlgmd8ZgT/hq8/dgJ8hCkAh0UnCF9FKALpg70EFgQ1RbPGfwStw3eCZIONBs8I6YhDxZ3Bkf0tuUr3bjeruVO5jXlpuaD8zoAWQbcD0ATSg8dCoQIbwgRAwECpAbXEpQfniPoKLAjmhdvGA0cAB8ZIwQkWBrBC7MN8BxMJzEuUDQVNkIp/hngGN8kiyXPHQAegRtdFXcUjB55LC0kWhRUFCkJ6fK43zvRutL40j/ImciV3jfmy93A4b7jMdxo10HRGMXsuonAXtAE4DnsP/Ry9P32vvmJ7PrV68kbx4/BYsSHxT3LYOf8557YOeCD5+vo8/AQ9crrsuzZ/M0IaxCYFmkZMxrLFK4M+gNL9qznyNe+yePHM9dD5MLo/uoK5rrlau+j7i3jfd/E1ljRIuOR93/8//xXA9UE0P1H9mT1avaj/Lj8VvYfAVIKUAS5AkIMWw5GCq0JKRg5MckxgxxUF0glzSSiIs01WEtvRjM5HzeWN6Y0tyTVHjgiGxKp/2T+if/19zv1+gauFZgVAhFlDCMB6euR7IwFIRDaCwIOmBfZHJgX/hqqI94cExGYCV8ISAbI/lIL5B6mGM0NhhNxG2sXwRJbE3UUzw5fCxsVwyROL1QnzRxKHnUc0xh/IR8kShixDPgSMSQzIi8XWAsx/Jvy5+sW3XHMqMdayuHWQexP92T6QAIjCKP5dua652rr/OXK5mbrZvLM+uP6jfSf7d3g69h25Pvtmeaq25XXbOAg8mD96f9GAQ0IGQutAp/7rQHXE14dtRDt/4oACQTNANYB9/64+e/25++X5dXVJ8mmywbSBsv8yOXUneOP9Hz0HuzE+K0IswUk/t3wldeuxTXHVtcn5WTkNdBvyEHSl8Z5ufq9yb+BvJy6O7wMxHvEOccr28boi/HwBHkRgf/15KzcI+Ko6Qbpje0//9cTNiS5G1b9l+oC6U3o0+Rg5pHrOfg8CHkLvQpAESca/B95HX0Mm/2/A10NxQ67E54bHxbmDSkOL/6h8FIKtyFlGhMU5hEbGIEmRiu2JX0syUAdQuM6hzRzJsMXphOWGOIjADbsN+IjUBHXEmkpzzzsRFpJK0N5NEYu7CrqI2csVjrVN6IswygVLRA300EOQjU61zFCJnkbWB9vIj4hFS8fPLg1SDD8M28vUCVIH8ciAClSJlolDydGIKwUAgkNDE4WgxF2/gr1EvsZA6QRZxvqHTggvR+eHSMYMg8HC2MTRiEVH28Ykh08GFgSZxnuGowP8gSl/331TfC29Vj5DwIjB1z8IPQz+FIB6gIfAfIA3f3X/O38o/mT+qH7cvUQ8enx0PJH5rbUCshcwh3LR9nI4yXqsul/4xjfydjP0tfXJd5c23fKJ7u+wUXQTtbx0m7PG8kVuyuwE64Kr66sa627rROoN62yu4fBbseJzSfSi9WZ1Q7RL8cQw8fBMcJSzSPbsuTp6ivnMeK+42jlAOX65G7kheWN4wLef+Iv6QLuAv7NCAL7R+1F5sjaYNQM17bZ4daL1QbZIdtJ4GTptPEK+V7zFOOf3M3igeqB8b71qvhe/K75AvSf8RzxZu/b5jPiEuYl6XTwuP5vDl8VDxqLKMUpJSC1H5ga3hH0DYgT1x8LIdMbGxpvGfwd8CGcG6YXzxiqD78AOf7DBjYLwQ/mE+YMMgj8D8UYaSDXJ5gsgStYIaAYfw6MBQME6/49+az97gWKAEX0IO+y7mT1ewMXD0wWkhn4FTgUsRPBFDQdyySuI1wZNBK3FxMboBWwFw8kPimWHhcUkA+qDC0NsBSyISMg3RdWHPgjBDDjPT0+fzdAMTMpTCA4HAgbkB3ZJeEmqB8PHGUdhxmzElQROhIGFGcVUBmwHXUfxSKiKeYvCjHoKDMefRGxB+AOphLBDEgSRB5pHPATsw/uC94OjBBvBe/7VPge/ycRzR8CKJwnmCMKInMgrhpADon+EvfA+KsC4hH0F3UPfwkyEHETAhNbEw0SqA9zCYgAQ/o2BDYVLRQADpIRuRIEEPIOwQ+OCvQDigSV/bTwN+wv8bT3ZQFjA5X2BPSB9HLuyvIW+KX2fPu1AREEJQUFApn7Qfnp9ybzL/L+8YflGNTCze/SldlK2zXfSeEM4cTmT+oE5TXee9tW3V7eO9cO1HLgwPKT+tn0GO5B7Arld9ga0HXQldQS1aLUTNNQ1c/hIOvV6ifqoemy5IPah88txenBFMhI07bYldbp20nkAt2o0iHYvNh9zUHMJ9Gi1gDd/ty60krHFsQQyfTOb8RithWzO7tixDfDBMAWwIXC8MCRwmDIEsZBwnvDAMmo0ZXWctde3pvpquWJ3bzcR9lz1t/Xttm+54P6M/ci9Lb30/Cs8Kf43/ha81z0QgDPCVAOWQ3DCEoL9BFYDDgDVgVhART6lf2kAS//UAC5CL0OdQ8bEwsVUBIyErUQpAuYDA8R+BJtFLAZDSHdKGUuliwhLZwqbSUvJkIl9BicB/QEtxbuKE4ssCyeLs8vPjNkNI8u6iSMGxUT2RfyJ8cwkDFtLzUw4y8RMkQ6DkDVOZwp3SIlHZAUHxZhG8kgHS0+PhBExTl/LmcpnCdEJhsgKRUGG+YsCjLsO8dHdUCLNRE0BjAvJr0XUA/XEuAWIx+OLBA9O0QlPts1qjIhLOIf1xpOGVAX/hs4IQgeFRzZGEwRsBA4F4YUAAaX/I//mgV1CccNkAlfA0oO6CGDIrUU5AoA/o/3Of8r/Pnxi/R/9GL30QZbE7IYABRdDJAJzwbBAlQFNAZfA2sFogZ3BhsHFwhQABb/hQ/8FOYPPgbz+Un8HQWCAugEZQw2BcsDTgnT+OnjLePp7z39vwHmBjwKBwUm//P/tQNMBjYCzvij9OXweOwC7Gz02gH0BCcFsQNq9y3u9+V74ij1gQrNAbj4yQAlBW0LiAt8+3Lqk+u28GzxJ/Ng7ajr6/VU+5n00ewC7NPgZNCw0u3W69K62lDncO3X8rr5uvms9sTxHuSg293WvNSHzhDC4cmN4ZXuUO1F5DXZy9QQ3fPkl99U1ajPyNzd82D7Q/jv+4D/TfyF+tP4evTx6HnVg9GD4XvtqvJ07r7k0edB9DHz/Ok17IfggdHt1vzTAMmcxvjGx8kf1e/kk+vj4RrXWNrl1TPK/sSsvKy5z8RQ0QzWVtZS1LrVj9nA2/jVasnVwnvAc8ay1qrmhfodBXL+R/09/ij3f/VH8AbqLfJ488jxuPp9AysSJyDqH/giwxucAef7tQwJF3cZYCH6KHcvgTGuJlwd6h4xHVQTWxGKGEAXsw9CC54KDRVlIcsivR4nGNcRhAcm+Rz4R/h99lIIxxScEIgauSEPC54FMx9UItEgAjCJLpYp3TGBMIsoRiwVLLYm+igbKmMkbRl5DhEQuRrRHqwhvSUhIQYg5iL2Ikwk+h0fE78NdwpGCOAJrQiKBZ4E7AF4/Hz8h/3E95v1pgHFDrD/7/Iv/l0JwxQRFwUKawJ3CMUIaQAyBg8N3gRIA1IHLgRpB6wJK/u67z/2FwB1BDABDP8pDUgPBP7WATIZViOxFd4QcxcPDOgB4AiFEaINHRKkJiMibw1ODPAIh/Fk3nLXFtGNz8LZtuSH6U/rl/Cf+NT6k/uN+bDrdN9u2zXfge2AAWcO/AlUAzgFdRNSFmkGywGGApn6dPU58zv1xwM8Fd8gISArJZIxJy+BKLkrlCxIIvwRdQi/ECUchSFYH8sXqhF/EOIRyxH6CzX+Q+sn4nz36gx5Eo4cvx+uD2j6m+/V96QAqfmq/Z4G7f3X8Y/xbPgHBlQTExnTF5wCpueB5PnwIOXI2RTz1f0C6tX3lB9UGXb2DOrj/XkZhxUr/MsGxRkLASL4BiB3NtMeSBKoGxkSiAXsCzwEXPspCOoPrBS9GXEIpOqj5ifoxt8Y6AD0h/LE/F8Kl/9q/EoCKfb19WEEXvbZ3MvUf8SYt5PDAMsGzOnYzOdw7d32+f7E8cLaP8r2zIvW3dRy3XruGvAv5gjjvPRe/MjqQe++//ICpgv4EA0BbvnuDPIF3+Dz2iXtZvKh8k4BDQhT+Hb4rQNk/Xb+rAy9BsjvFOW87nz5sPLZ6J3p4f3DERsIzwI6FwYdOhNxD6QODQq++JPz0QBWDR8TwwbM+SsF8AuR/an6Dv/57KjkWQPdGTgPwxNpLBMuQh1vGX0Y2AkFAwEFxw1AHkYqhy/2Kjog7BlSIIUq2S3mJeIVAhBJ9KDMEN1s+6r1qvs6Fy0jJyNhGbsG+gO/CdHwHc0xy2baK9/f4ljvtPBa6WDpUOtU9t4BBvOs4SLjP+fC50HqZPdzAfP2xu8a9KrtVujA6hbp8+yX9CLwJetk8qP4jfh28JvwMfjE6c3VN9Jw0YPKG8xw2CXlEvOqB+4RFQa889ve1dKZ4eXsBN4C3UvpHOul8oH4fPGL8TPz5es97ivyyOp54Rzfotps0KzP49tJ4o3hbumw6+3gHOLd+ogJ3f4v+MUAzQ2OFhkX6BKOEfQKuQJYCA8T4BbkE9EXwSxUQhZHwUJIRGRHkUA5Ln8XdxC7FG0GrvBU7zIB5BG3FZQUKxWsHEYneSQnHdMlvyZ/GaYZmhigDO4FdwfJDi0e9CsIKdcc+hfVF3cT0RNtH7Ikgxu7GaYX7gQY+dL3fvmvCyscUCCYKZou/h6UEMEXWhmIEBca4y2gLfAhXh86HDYSXwkrBU4IEQ0tDHkKFw7+EfIM4gUCDTgYLxZxE6wS5A5UD3EKFQECCl4h3yw4IGcRGQb/+l8AKQbj9r7hQ9u+1gjPsslov+6337iBwWLK6czV2qbsXug323vYxNUz2W7sGvnX/0IJuwDO8gjuAOAW3EfxqvwY887wm/JQ6KHn6fTI+XT16/Tt+VX+N/dW4/bYsNoE2znYatka6AAAQhS5FjIQvQ/0B0/2TulH3a7LvsKmwZfBUNPR7Mb3cvc7+ZQBfQTwAU4HPAgt+0n4oAa7Fm8dwRY8D+AOUBV3IR8ePhJ7HHklXBpcFjEXKRARDa8KvQO3CF8UHRFtDh0YWhYNCSsEcQ1MHtMqvSzZJE4hDxz4CCv5hfmB/WsAlAu3DRsGsw2cGDALP/up+df4Nfn9+mj0P+Tr2frVwtpk7H737/EG9F0D+gh0/t/pJeNP97z/Cvef+EQDswngBjoOQh4AJpwdERNQEHcH5ArwFHsQOBApGLsfhhIW/Iv/hf6T5VTZed6d4O/mxujP4H3nEPHX5UHZTuT3+gMHDwTiBr0Rhgq2+Mzq3d/Z3CPbVtMZybLLpNDDxUy/icle3Wjo3+iu7arx7e3375H6yPvG+ib9TfvG/04RdyCUGnMEJ/R99Qj31/AI7NPrYvJg9wD5rv3qBt4RZQ8lBXUIuwvRBagG/g0pF2AnBDPDLWklZR5tF+AZaxacCscH7AmcCgUQqhRSBNP3NAUEEQUORgfTALT7vPgv8/PqR+RQ4WjlDPbmEfYg0x3VFZoHN/qy6sLdfefI+G7/nAUVHLgy9DU5NVAwJydgJZwqWiZOC2z16/dnAV8EDwpUE2MRBhfXKVQsbSBAGSEODP55ASMOew74DhkYCRasC1gQShoJGmMNcQXiA+v10OyR9HD3gfRg9CT54/a431jMtMzVzQTRGuFW8ZABwxWBJbUi4Als7mjk5eVy443hXNXjw7TCMceg0Cvect6o2arjtvQM+vX3Q+vI1pXUaNtO3gDoPfTC+PIAfRP2IIEfIxVzCf//Av9W/VjtIOF34SHiy9/82/rWR9QQ0zfWcuFu53rro/EQ9scCnhYCHZwdoCSMI7Ac2xoEHYkc4BicEgUOtQoZAtX1Peu86BD2VAkHFPwTDRh3Jw48okxMUZxP9kk/SntH7jq2LN0dig1ICu4cHS/8NM8vcyZfIBkgqh4ZEgEDRAhYHs0wgzd1NGAxaS21IrIY4BtUJEwd/grPB6QRaxLWBAD3+/R8+En64fZu68/hHuMQ7Gr4lAJzBqYMlhsZJZ4nYCukHiwF0vgn8mLtke3P5LLaxtp24hDyKQRQDf4IwwQJBn0Dzvqu8PPtVvXcAoUQHRvbHYoQ8/vb8xD3uu0p1IPFK8mmzinNtMPJvrbE0czr3BbvKfFu7HvnTNqBzvzMas8U1sjkbPHG8gLxQfIx627XuM0M0FLKI8Y3y8TNcdHA3YvjsODv3snVYtJB4rrtCO8994YCJwiBFrYmCR1SCFz+Rful9e3zxvF25pnnyvVbCrYlyzhrOms12TXmNHcwYCyaIGkMfwDl/mD3yus/6XTmzud/+G8MiBXNFKwUXRhGH8sjayJEHlwe9iIZI90cIxWQDK79svO49kv3QfWd9LLwUO+d9dEAqAlWEZgZ9h5QImUgsxvuG7IewyHVJr0mHRkrAuny0/ioAlj6Tund4qzoJ/Mi9e/tcOhF5nzxaQpIGoUaKRrBGPAaBCBKHLkTzQ5ADpALgQtKCwz/0O5H6DfpyO0U+IMLoCFlJ18eAhnmFMkKWv5u9SDvEuv+6GTZ1cHLt7+517zdupO1XLYOxEjVMeca9qz1KfdUDqQnmjDsNFIsRBTRAZn3XvAz6TXfutX60ajc5fIPA94IQAsJE7UaGRnmDZ4Bsvyl/SkCzQiODX0MRATh/PAC8gZB/ffs39sC1j/dYubZ6ePqSesQ7n7/axQlFQkSShyyJYMosCbZHPYWXRhdEvoGkAAjAVj70+4Y7crwZu0I8C392AgpGl4qFSx7Kh8rdymWJjUkyR/BFh0M3AhjCfQIYQsZBi3yTeeT8Aj8MANhBOX/DP7BA3kVdS2/Oz06OTOBMTctVCHiFPwGL/VB7X3xTfGf7vzu7+6T8scAIwx/B2cB8AHS/Z3yJ+bx15vSHN106hDyCPUc9eXvK+EG1VDXzd1y5/zxavuBCM0UwxgFEnUKHQuSC20DTfqF+hT9rPdN83D4IQFm/gz20Pp1B9UKXQRW/Df1pu+m8C31vPIU7NfoBu4A+iv+zPiX84PqOeJi4O/blc47vgy3EL8l0ATgMeti74/xS/rTBUIMZRCSFLEV/hEJChb+4+zh4jnk5+RJ53LxXPps/1cFwweKBmUHIwVU+3L6oAVYDqoS/hKaD0oTSCG0Kh8tay0TJ04bJQ7aA0n/VvjC7yDyYvfh/T4MhRsNI14mViyiKncgJRYuCKf2pu8K8vHy8/c6BEwPvxmFKUQxxyoNHUoSawvFAdf7UvPj6THtT/qQC7MVsBcRFycVhg+EBjX/ZPK45+fj9dyR1xDZdN4G6039OAtOF+AgNiSgI8kggRsHFL8KGwEI+t33O/Wy7W7oHOg363vuKfIW9sT2f/Dz4y/j2/AXAFIJfw+9FW8ZVhriGRcWuQuP/GrsruIU4fjkpupN78T2L/+BBnMPWBKYEJwTBBYTFB8O5Ab2BysRJxn0Gz4etyFCIt8gmB6mGp4W0RIRBuPzn+sg7/H2bwhGHO4eeRd5FgAYtRDaBRDyk9uk127gvuyp+8kGkg6kE7EPyQYXA4gAfPbC4kHNkceYxpPGIdUt7Az+/AVvCgsPkAv3+cTjQ9Lbyz3SBNsO4wbzdwGQCXsNKwwHDdMILfLj2D/WYt133THjdPMa/+wLpCQjMxUuTCh3Jikavwhe/of71frE/1YNphlaGgAVCxQwE4YO9AHv6NvNFsgx0enUdNw37Y/9ZwvDEsUP3A/DEhELfvxs7HThCONL7K71ZQK/DwUQaQQE+i3w/uYQ4xTiCOj178D0UfzmA5gPjhZIE4wR8AwhA7D2qOzM5V7lQ+st8+P+5hBxHFoXTg7RCwIJQ/y29VbzGPEK8Ef1JPvl7OHbLdZH1XfZot+05jv4bwgyFfQi3SgzIfIbNh3+Dy36YPBu9f34XQaKE9kQig2ODCEG7/xq9Xrr9+eV6IHvfQGcFN0fpCJKJO4pxTJQN8E4WDIXHogGzvdF8xzxIO+j99wJ8Bx5LIssXCJSGvQSaQqDCc0OZwryDuQUrwllAaf7xuof107L6cVgwgTDIc5c2hzg/uYn7VTveu/x8LL7WPtq7TPl1dpkyivGnMofz+/XpN9q7zgHGxTmEgARlgjd+IPo3djr1QbcGOAA7sEAnARZAb7+OfEW5r7l79zv1HfaEuXT9bsJHQ2kB/YGrQZZBxcPgw7+CRsISgIC+hbyf+7Z6vnvSf6KEisfRCwxMwoq3S5GL78pYytUJvwcCyACI/YjqCrNJYMctxmUH4Ulrh/DG1oiUCUVKckt0S2NLFAkShlxJYM11SuYJrsgPB74I3cbvQII6pHgg+QA7eHxMf9nC1gL2RJQGYEQzQpEBtEA4gMPBpgFuwl7A4n///vx7SLnsNrn1Y3fpOBo4fjmI9kI2JfmneYW7mkCuxVvIC8apBF1D5f99/JY6/HaHdDR3mrf0eNB+0P6XvJF7v320PEW55vq/uXlz9ncfPPZ7Vbxavzh7rLhJ97Z5eXu4/LXCYoKjf+1BmccfRAVA38JngpZBKABrBBvDAEFcQWtAt38KP63CL0SPCNxMGIymDFEMLYvoCJEGXMV4g5pD9sVCyGQGCUN1Qki/e/l39vh6fHurPgfDRMNIwW9DL0V+hjiFoUVCRk2GpAZqBncFCcNWwnZ/9D0l+lW24HUBttY40nqDvWP+vYKCxgPEuwa8ikCLUow7DMpLgoomijyHwQTTAIa/FQBp/2+/BTvQ9rG0ZPNqtWX6/Xv2e75+ZwIPA7mBdEDlgRrBK8NAhWYECcDLfq9A3kCtwEo9YngeeLM4ADcjd/87IvyBQA4EZIdxRmiFKIijiNQJxckJRMpBuHyzeIE52DsS+1F7o/wuPes/Fr/ofk38qzuo+jn5srtCO/d5KbtEOdxzinOKdeZ3tHdgeDd3hblxPd8/QL5if7NBW0VSBxKEEoN3AdGCiMGR/9F8DnoXOUx7C0IVg5aEuocph/oGIcbGxyxEZoOzw8pDHEKOgcc/nb3+fRL6q7R+Mcn0N/aI+iD+BD5p/XQ/g7+wu+X+EYYtyBAImswkDD4JdMdaRBm9eHk1ecI5GTbENCF0cLO68h94uv/SA4GIms8c0BOP0Y3shsHBHrrCtRIznfQz9LA2+Hm+ex2+LT8J+rE5u3uTOLI4tn2rvwuAGkLiBKkBc7ubNxo0NvU39QC1CfSj8lK0yfcP9bC3Tn3XwyuFtkixyOIFpoOmAVc9TfpZuPj2O/bO+Je4Bbnl/M5+HT8Kv1P8Mb17ASIBF8BGw5EE6wOvRC7DBkFVPq27rTrM/H665PbQ84fyD/FedHv7ToFVivbUX9m6WfvU/hAXDV7IskN+f+d8ADs5+q+6tXzKv/cBwQiVjoRN90q6CRlMS06/jCqLJg1EzFnKJQ2zUROQBc5qCs2E8MFFvga7IvvtPK07zn4KwvmFJgicziBOZon1RzgGDAQuQc+BeIAXv3/+uP3svN56qjiyuxWAlALkAoJBTQIWBgEG7cWuRw6JhMqAigxI7cX1wpP/ff1Dvcx8VblGOQY7VbqzeJB2N/IJ8jpyPzAf8T20MvVNduJ2WDPdt+wENc48j8rM90XpgAi8Cna/MkjucmkyZ0XqGu7Ds7h81oovksfX+FbIUfqJ+wA0Pcr+TfoptW6yJHTAueu8Ov10wAuBT/rLd1Y8Nf2wPFo+LUCVAh7FI0rWC9xJgQcEQlc6wzFecP45fH2qf1IBH8LRBf2IWspwyNzJLYniR4+GRcZ+BfXFn8agSKMHp4Uew6SBbj8vvMY6rrmbOwG9cr71Ppw97j+gxCKG5oNP/kG8cjpO93VzVa2jaa/qvavLcEFAbpTAmSoS5FK20rjL8cG/vO+73vfKdPh14XgIuVCAKoyZkwvU8BRx0ERHRz02+gU6XrtVOzM5UYEyyYMKR0fMSf+MQT/3cnbx2LRdt+V5ML08gGR/GkR+iPbIdEHqOfT6Fjcg9i4+oEQDxywGKQO2AqN9k3ml+ZR8s7+JPYI7C3nGuWj5aTeVOJ96XvvogJEEB8NVgsEIY0rvxFUCzISWwSn92DtENoGxovA/sVOzAzTSsd3vNvJqNrV5dD27Cgeaf9/pGfCU/pXYj/FDAj7XO49yHutg6YArKi+h+gNH6Y//Fm+bKZr61M8NBsvrjKLMV4fsQxpHK4oNBsPApH7xPtc2J7N+uLp6oXuLe1+/0YTjhXbI/Yt+i7ZJxkcDR38GMUamiU8JNcW9/cK4zHjTN0U31bqtvJQAqYQ4CBeI1gUlAa+/VgSOCZjFUQHJQt7BJ336+3n3o/InLqDw/zM9s5YycG6P7uVydHQBtRD2GjWUspcvbTOqATyNR83hRobDbsM4/4U4WzO0713mnmAd4G/lva1k+a1GFwn7jVDUTNhg03BKBkmTistIysMFO+P6Gbktt3N4DnxzvpBzUCpQcPv32Dr3ffkCLAUexqyJH0l8hrNDr0DOAcdCdMRMyY1JUwY3A9dDqYG3+/A58bsAPdT/SL2iAWHHwInvymiLlA4fTXyJloY2gDt74HmduIp5aznOe5P75n0Age/C3MHcwIG99vp1+Av4DnfWuBe+jE5OWReUsEnHxBnDOf33+cz8OXlTM8vzD3amd/z8EIoaz+ROd84nDlkOkwmgx7uGugLT/um6TH/lhbRF6gNSe8i+ysFHufI5Sntuu9o7+nxHQMwC2ESSBD0ClYHaO4I317bz9le6THskeJ73VDe2ew7/FgOshgNFYoXKRA5/3T5JP60+injPdI5zlrUptwY22TqDP50+nTgcNFW5KjyTfcz/Lz4n/rHAmj+COlH1hjRCM/444UaeT3qNckgbxp7IdcXxQad/zvufdbd1OvmTfNg8I4Spji4OpY5xTdiOGkfaxQZHY4f4SnBES4DvRwfJscSk/R7B0olQhKkDuoY/h+WGiEHJwMS+bj4BQsPEckLqf+o9lH3q/+KFmMfOhCX+q7gVOMdAKoP6BYlFKYTJSDwJYcmXiJcH7IWqf+H54nVWtN90pfPst1a8MrxO+UG6BD7aPr17ePkyNdB2EXlEPK++inxTOCm7UIcoESTP44X2feu71rnCM8jwfDFM8j0y1zIxMkdzyPhlhGoJOYqEyopKBklEQuiCn0Qrgyh/3jyIwbTEhEEl+9o8BkR+BDiAbMNIxN5GQcVaRBfG2MXbQy7B9oET/gn58jqePKR/AQPyQ5ECu4EIv3YAgUKvxXoHTobBCBfH94asB1EIuAdLw7XBikFMggFEVARLRMyEPn/Cu095C/qqOuP4qjj9fJKAloOjhU2A1ze0cZgzsb+BjecPyEcifgY+on9pu/9+IwG3ADf7WLgg9jvzznV0PTDDv4YdSKuL3EzhST0IWEaBA0t8PbWrutCAogFogwnHcEhCQ017H3gheY94eXTJdiN50PovuVN6GrsZOt45brcL9ay4SD6awoPB7D1yOXn5Svl8d055mrzxQLuBogAEQV5AOfzDOQ/zdnJuNyH9Ar7Vvb3+Xz5hfY/+hD3tuJzwhW39tNH9ssEMgPE8g7Z7cPuwu3SdPXbHtMq6Bft+0H5GwukD+gVBCjHKbIgaw5jAy/5VPJrADf+3/rl/lIPdRwjIAw4Zku2R/wtjSmgPz8/xTLBMEQ54z5nKtERzQi/BPH/6/SJ+IP+ifke8xT3awNi/nj09fQv/6QUYiqcOyM8UinbI/4oSCQvHtUaBhthH5QaJxS/F44i6iOgDm798/nz/csBLgFQDckXzRRzCZX7ZO+o4FLZCOFP99EMfwz9/SfoqstSus2+qsxa7eEkvzlvHmT4ferz+7L8jfgz+bDoytz+3CDqrOMY0QbguOqR9df+7AQHCkPxeO37+AD7qvJF4mz2GwqeEUAYQBaSKRkhJ/DN0wrXYOFi3vrhwOYh2lTVFOKN7hzc3cwc5pHw+fDgCp4eCBo4DIoKGw7oEdUb3ygIOgJBBDM8HDIHjgS9Cj35otv20dfeDvI2CZIZlhb6EYoPbwrgBzQIlhQrHNoNyQL4B1QK5/US2mLL28VazC3Ui+mHHOM2tR1D7H/Y9/OSB8EVgSe/KWcbyQYY+Onf19LZ7cELBBMDBicPpCaQEYn4hfpY/VDnotGJ6qINnhY+DYYT/jBKOYklpggY/JX8svT17mDkjdFOxmLGQb/ypi2mErtSxqbYpfZOFTQb1QqQAb0ABQVhAskEVhTHFgEFavGX9B0DKPvr3Wa/TLFMvdndqwC3DeAAvvwRDiER3gEPBN4S8AlW9N3ykfpW9VLjstHjwbS4wMj82NnT39bv/dUlLxgg+ef37AqKEfIHqhb6LWkrXBeUA+n5SfLFAssdCRuHGJofpijXHCkJPhZUKvI5njboNylbbnLKab5OEEQbRB0lGP7V6wbxLAMXDFYMwv6s7fPnXunV5wTm8/5YGQcSAA1jJB8zYyJWFFgZTB7dJbAv1zJcMGMsYylrHFYN5Af8BAMGrA1vFPQXSBplFFkCIPTQ8Pn0sPz+E0o700VxMGcbNgUz6EHQw8BpuIm7UssK06jF1bZSt+/T6gOWH/wQ9+xQ03LS1dX61U7gCveOC5AM7/vf7H3pzOpL7z/4PfS29JIK1QB33PrXfPd9DW8CJveH9m8CXw2IDjgUiA9e/i3pP9we5GLxAPyF9Ezgk9ft1J3VXteZ0N3Me8pgyLTOaPSLL9lArCbgFRklni/+JUYfThDd/GzvzuhP9lkJ3RqFJMUaKw0LCkYWbSD6Fo4SbxdGGIcdriVnLpYmYw0E+ivsFOq+7KHlLeDX0zPJXMRIx1TaL+cj6BrdFOQTGbBSN1wtJ9vvg+X845HpqAQKIOIguxHaCWr4m+9xE8M9mkGSIXsPDRTiCan4GvZfAD/8zOz585AROifoHuYH9/Qp3WK9mLFSw8TdvvRODn8PbvDP4sr07/rb31TXUfqgE+YPKQU4AV71EtY5vvi+AMsf2czvHQm9CFT3R+/n7Zvs/Ojb9RMS9h3PGmsWqgjV7dnWTMk9vuHCydm/ASknGSxMHNEIifSk6d3rYOog4sziauWi4TvW6c4fzYnNXstzvGC4pNuzEMkx7igCC/wFQhMJGE4eezg9VJ5SRDwGKeQbBhl/J482PDJGIBsbbxOgATn9BQ9KJtchoAoVA0YK5Bf2HO4c5CNeJnMbCxRAHtMxaEK0S/Y9WCAyB6H7eQUtHhE39jyJLScgEx9cICkWuv7h7XnpYPH9+8kHfxKvCOP1ne4e9ZYSUDqNUBtOgT7NKHcTHxFhFQANmAQLAhz/Fvce89PuleKL2snZvOIE88j8hf9e8O/PFL2NvbbAqsjl1NXaf9HAwr61Oaotq+O5YtSu9PgNnhE6C9ERcxUFDl8OXQ9tAa7z6/Hj6ZHfrO9IEC8aCQ4LA0P1sNhUwKa+18gl0yPZ+Nuu7vQTwzG8Nj4rbyXVI3kZLgs+Bp4QYR1eI2kUm/dw9PAOvxbBBeAHWxS7D6YHkgPmBkwRihlaFE4EQ/o7/K8I9BCMCon+7fIQ64vt2/es/YQCuw2/E1IUqhT0Ft0ouDwMOi8mRBSiB4/3wOxN6o/nOeTr5GbwK/ho7pPrOfkK91TiyNmk4TXvP/hB+1P5T/p29KPlN9x90onPi+wAFdsdywaP8M/iNdbj1h7xeRXgIVQTEPs/30HR3/RpLS89RCvHG8cL9fOl7n0DOhvuGR0GtPPZ3GzQFuuuENkQHPR03UXTSd3I+WkPlhrdIL8WwP4Y7ArdaNew3YXZh8/RzuPQz9A914nfXuPO6+vr0d8h3C3pyPg5+lzvDuPP2y/i9/9ULwpGwzsxMocoBBY6CYUT+iMtKQwrLSJIEOoKnBfmIo4XwwX5/tL0aOnd67MANhP4FQ0RQAzuDUYThg5GBV7/K/ft7XTsCPJq92MA5g7DHQArYDcUSyVUwzwTIpAiFyVYGaImTERUQtUkVBATC6gDev4ZEDczSEYAPOYqYxKN+Ef97BSyH7IZhxpGJzMyCDhkOKAupB9GFtgHUfPK7iv0lfUa/EIIqALE47TLfc/R4abrHPEPBRMVAhOECIP2xOJJ3wrpeeQW04fJc8y01VDZd9nj2sLcUukE+s75/fOn+rb4OeK+2WDk3ent8GT8p/6u8CDkMerE9zf2Wuoe4AjWJ9Jo3CXtcvWu7mLhleKk6iDzXwP2DEoNjBVCIJweExZ5CrD84epU34vpCvvE/Y3x1+Q72jfZoe2oCUog6ii9Hs0a5Bm/D9sZDDk1Qd0nsRFKB7jzJ/GqCQQicS+0MLkszx5EDwkKzQj2CkQQlh6qKRUi8BpCEvoDZP9q/STyieAt4fn82hC1EEoQSAuh9OHj1fPcBSMAzPkr8wLi5dm+51b2l+y42znX3dQ70QDfMfhq+KTi4eDt4ADV+uXXCT4cBh+qGUIJ+fVN9bb9GPyV8lLpDOrr5efoK/nG9W7no+mF6ivbP9V52qzVR9do6lb1k/Xb+poEoATb8/rkK+Eg3YfZidxU2Z7P2dfT7Dn17/p/AGL4GOif23fYUNa606jcMef43ZnTid2D5JHdruPC8t/u0eI/8BMTESpgKs8knh2MESkUGS2kQ/ZGFUJcNGsQLfL79ZgH0xDFFw8Z/A+IFaonQCgbH7kgkBvh/DPfdut3EuwlVCfHL38nWg72DfQdPh/uHD4nSCaqENgG8BQjG2kPzxUPKzwnKxheHJIiDxsxHd0oYCboHDoawRp/HIwd3SKWKBMf5hPyFZgZRhvXIisiUhRAEgYb+BlSEfH/SeQv17DbKehe/scWXCL+IqYY0wlZCVYN2Qv+CwkOXQigACr7wPAl4qjQl8D4t5y3RsGu0xrh89/P3/zqWPHG7iXq3eBi0gbIWsmuzw7S29Zq3LLTUsTlyJHbMeSP6bDzswFnBxkFFQQm/an4ewOsFQ8g5ilGO909Ci3HHrIZ3hT0C7cBT/g9/FII3grHCicVQh/yHVYRYQR1BqYQ6hCoEeQWlhDNAIX2zPQg8j3x6/Xn+kYAzQdEDuoMdQi1ES8hMSRCIpgmcyI4ErEDevce5i3X7dsY6Qbn6+Qx80v/ggLTB3kLxwruCuAFl/zv9p31R/ge/OX1yOi647Lqh/W2+pX2T+1U5vrkrOZo7Jn2XvuR+oP8zPul+u3/ZwRZBJ//lflL+nz9p/z+9i/re9513d/l5el05YHdI9WLx1i6ObzjydPTk9kg4ATgWt2X49/po+3h8f7te+O25jfs1+ab587uCvCs7w71HvXl8tL29/fX8iDyRfWD/LcDDwhECtoJGwURAn0HphA2HQwmMySDH/wbZRiSFS0Oev4I8Frl69334STrDvC685H2BPZJ9aP23/ytCHcUPheSETgN2xLJHr8gIRnVFt4VcxPXFfwPswFjBfwWaxmmF4UjxzFiOTE9TDhtLoclxSU1LSsrZyOqHc0ZJRhGH2sp5i2RNB1ACklgSeNBGTh7MAovbTCwL7owRjNaMnEnLRkND+oGjgWSCW8AyvPT9If5Q/08B9oMjAQU+JXwJPbXBQ8S5hE8C/H8T+sC4+3eUt8g5VjmHuTM5mDpLeYj4PbUgcakwhvHH9DI4JXuzupM3sLUss62zqbURdTPx7K+5cey29Xq0PhZBW8DBvcK7Vrr2fHv/2cU3SP2HbkKFP4E+XD6uwXVEYcV+BOoFUYXThFUC4ERpBg0EkIGjAP4DLAbDSUlI6oUYQScBUIQoBDsCzAKUAieBn0FVgJfARUDXP8m9PjiK9TC2Jvv0QKqA/n4+fLS9DP6dQZEEh0TjArXBdoIqAoNDUoS3BIhDbMHWQfRCdcLaQdjAvgAKfjM7grwO/b+9ffyCPZ/+eP41fnU+pf08e5s8+/4+/TE8Xvw3+hi5SPnxNw302DXDtrb2QbhPegY6vzvrPY7+7j9f/ZY6/Hq5+205yvYrMkQwwDHGNB70ajP+tEC1TvZl+Gm6aPwpfKN6YXf/uAa4T/eBN/R3kfYKc8p0KbZSeaB+uQNVhgLIqQrwSxtKZQjQBjLDkgLvQd7BI4H/hCaHI4kEyMfHWccCR2QGIUTShH6DEgLWxCME7ESyxOFFlYXOhcJGfIUJQjaACj/R/nR7eHlbOto+5oJDxXfHn8iPiS3JEohpCDLIOwZThoNKmIw2SchJ6QqkCaOIjogGxaBB/QCJRBlJy85nkHAQ4ND3UD4PW0+bz6oOok4aTa0Ld8jfxvPFhUgYCvLKXUn/ikvKHEeLxUPD7cMDQ2mBon6PfZy//IN1RcAFWEKfQVUBREDbP1F9HDsbumq7Sj1fve497j3COzJ0iXGEsc5xQLKUNNU0YXGrsIlyo3Tg9rE5Arp897A0VDLusc7yEPTJ92m1pzNvNRu3crbVNxu3fXdxuWl7aHtg+tQ7q72sP5xBdERlBysG6gZ7BjHEIoG8//X/kwAXv7t/zIDo/zA9vn9SgZIC88PlhENDYIF1wVzCDwDiflm7+/mcuGk36The+YS6+nv0O0l46biuOum6mroMfNo/NoCPgoJDwIRKw6IBq8CrQTyA6gFzwn+Bf/+7/rp9/P+GxMvJokuRDBcLq4oKyRQJuQlRBq5CXD98fa07wDsPfNs9gD0vvhc/CL3CPJJ9sMCGxDZGGserBtEEooPVBIFD70CfPYQ8UnvQeqN4IHaOd534sLfnd6o5brvK/q0/nT6HvBc5JXe5dnrzWzK09PT2aThxOqb7QDqg+Ci1nvPtM1y1pfjWu8i+oX8qvvK/+AB7gQrELkSAwyODdMJzvfr8O/yGvamBB0UNBtjHqgZJRJtD+gS9hthGTwMBwi5CZoQ3hltFS4J9gQtDn0UbQu1CKQS0Rq0JdcygTMjK/YlyyGWGTQNRgKgAZwDM/7h9JPuP/F2/OoD1wmgEocWcxiyGzwXRBBCE3EVsREbFc0XXxQNGq4jdSXoJf4jBh0vFrsO8gYpA1YGXwxfFyMo8i7fLt8veyu3Jh0gVBM4DLMHMgH3/zoBzP5c+GjzO/QU9PXz1/bf89XtpfN4/ML7l/0dAO37vPtU+iL23/Wm8cLqcOCk0gTLUM4e2C3bQ9t/4enibucC8x7sFOEz3OPVBNpW4l7nKet55Brbbtkh3grr1fp5BPoAxPWh7qjqqO0C+KP6yPS+56zdo+bt8Rj7iAfVCVAHmgNo/Kr4zPXd+bkB+AV9Dc8TCxiaHN4cCR29GjQVDxY6F78WHRhAFwAdNyhvK2klfR5fIDMj+hm3ELEToA9fB0gLvQHr8I3yrPgRAK8EXQXqEdMXMgZJ8RzszvMU/X0Gog/8DTIDuv6D/s75i/j7+zn+9f+eA3kE7ABfACcIwRKsG8UhtCJGIGMbpBLeCmMIkgMQ+2Dz+enf43DwZwBF+2z6SAHt+38BSgwNBSwDhgo8BuACdQpMA3Lz5+6Z5M/X4dgU11bQBsfstwSzUrj2v43OJ9+B50fsUO6T6/zmh+Hx3DvcM9y+2HfZEN4r3HLgdOkY4Vjcod+X23nchd623Fjhxuto+Dv9T/Y58IXssu1i9jH1O+uk5nbkg+VL7d33zv6SAXcCOAIjAVkChgaMB/QEVgNQBEgJogr0BQUKSg3eBIP+QARrElgZ6A8RCJoIuwfiC/IYpiUIKZYmOS36MVQrLyg6IwAecSOJKd8oMy7LNGAw5zY1SKhJuEWFSDtGtDzLNYUvhSjNLAYx8iuSIzoVPgqzDAYT2RSQEvoT0xPwDAUMvRCmFZIdLx9AGxUaFxWmCfn+hf5H/yL1kesc6FTkEOXQ7af1cPnG/KP+Xv0M+hz34/LM68LkNeQx6LLk0dzn2H/X69+T8bDy6equ9fv8mfKd7pXmUNnb5Jn5YPvr+/f7Tuk34Rro6eBH2xTjjed06azo+t9Q4GLvxvj7/70RYxqzFNwQOgzaA9wCJQknClP+bO6w5rjowO+p+twHLw7cDbMKPAHl+vv/SAcLCP4CRgTZC5AKHwQ4AOX4su0a78T5uu+H4CTqrPXkAYgVihUyD7IbCilYKAgh6hsAGssX/hGmBnT7ofzXCDgSJxQxFGEW0R/oKCkmIR/sFKIKvwvJDW8QTBVdD5IGuwFD+Qz4ngQ6CD364+/z8FP58gnmGwYn/i7bM7AtWhxdDMUJUg/8DQ0F/fz1++YA3/kW5rrez+aj8Pf2T/RD6lrmzumw7a7zM/Y/83T6HQLn9m7kWNaXy6DEAsMlxGbFQ8w51KbWtt687Wz49/2/ADn+uvlo9aHwUvD57SXn6+bR4/HdSeU387b/FQMx+q70+/Xt9Lr0+fYx+8EBcQiSC1YI2f+l89fqCOnf45Hgruis6LLgyOX58DH+LxW0IPYXlBKBFLcTcQ/VCckOHx+qI38YCQs4AzoOSiMlJhEgHSl5NjM1+C4vKC0cux6sLJQmmhxKILAcWhFOCq8CoAT8FQIe3hb+E3kXSB1aIc8fCBzyHKooqi/dIqwSCwqEBRUIWQJP8YHvZv6UDGkOrwHj9p4AHQ8bDtwIOg/qHGsdzQvX/R79xwH0AC/xdNz6zUHKutNc25PYc9bl28jloe6y8jf4l/7X/8T80PE94XDeg+l05x7YidDdzmrPWNN318/jYPZCAP4CN/zK8qH3Rf8K/nj9dv6UARcEuvds5Cnby90a5oXk39lo2uXl/vCP+az+NAI+C1sSiBKeEogOVgP79dnqTuDb0H/LFt9W8KbtruZS6cT1TgCOBKIMhxthJHEhxxfqDRkNhhT+F04UKQ8rCjAC9++u2vrVfeAO67TrDOhB9l8RrCRaLqQv+izsLHspTCJeHUAarhM4CAz2j+A911rfBPZdCV0GIvla9ycAJQf8CIgOqBtCJdckdx9aHSEbvxRID0IEmfj9/4MJRf4S7LDp6fh1C0oUhRDgC0IQIRTeEaoG7/L16SDtz+i04T/jg+bt5S3ljd6N1VTgWPYi+mTvYOpo6/PwXPn3/nEHFRPFFDIJtvWH5mLq3fYS+czv9eiX8dv+Sf1e9R72JwDPCwAPyQfS/cT5mf57AIv1YOzQ7I3u/O9m8Z3vyugx4e3f8dwS2WrkM/mYB7UIRgXqC6gWaRgyFZ4VkBshHH8RJQRbAEQJihNOErMKxw0fHkwkaxeDDwAQdw8XD8MNewpOBxEKpBQvFpIOShILH2clcSQxIiUiySNeIMcWKwuECeIbMSiFF7MC5/zb/IH97f0wBRcXYyY4K4kitxT2FOghoiuJJgkZlBcLIAkaZQMG8HrsJPZ6+i3t/N2D3AznBPQS9qbx0vVJ/un+GPuF+Sj5h/d78HnhqtRK3BbwzvHT2ADDSMe001LZddqD26bij/IU/kP49/FW+7sHyQ5vDEv5YOwa9P3zYuLf1IvSRdd23yXlfeff7RT9ZQeeAYH4O/sCCNES9hGICw8GcP628w7l5dff2ljn3+lc4EzYquGb9l0CLAO1BnMUQCPyI3cehx6uHfoboBrwEWkDn/oQ+rj3euxH47zqxPwuCi0MBQRF/+YHyw+cCscEbQtnGF4eihvRFy8VQgoE9VLmxunV+xkNbQor+yD4kAWmER0VTBkhIbQnTCZ7HhEXLQ3yDKog+ClzGeoN7BPsFoMT8BDqCRcH5g7bEQ8LPAW1CD4S1xMHDAsKxRNGHMEXhg/LCQr94e6w52TklewDAJoLoggZAFH85AGxCOoFOf0O+oD/NAPt+Frn/uAI6OXzm/0q/X76WQDoAPfzP+Zk4zHuhfse/Onyvu2n88r4K+763yfde+Nu7jvyDO1o7LDr3+SP3zvhle9rBQIQfQOq6JXX29qb41jqdvM/+20DzwwuCqIBtwMXDlIc/CaUIRMYbxg8F3sQHQgAAEP/aQTsB6YIvQbLAsr6pfHE9sELlh2wIdMfXiFKIVYc9BnsF/IYJSdMLlofYxMHCYv4cPds/Az4svsHCpAW3hh7Es0PExJdGdUixyD0GEganhrBEc0F+fnn9wb/GvwM7qzkBOu0+9v/9/Vu8X76aw4nHNcbjBmOE9oHifyN7/flFOmo7lbn39P6yMnN6dRk2kHltPJJ++oBqwKy+vf2O/tq/l7+7fhU8rDy6fLK6+ffh9O+zrDU9d+T5YHeXNhW23bfxuWl87EC2QxbDwMMMAbS98bkYNkI1L7W7+Dx4WLdLd6J3/jjNemb6Kjv1/30A4QDdvzQ8nT3rQdMFNsW7BKDEIYNSAhIA3D4yOtB8bMAuQBg95f42gcRGZIcqBSqEtsXpBkLFdoPRAgS+UftUuo961P4Cw53F4ETpg2IC1sP3BMHFXUXCRy1ICEjux6sFxsVbxc4GAIUzQ5tC1YLkgy/C5IFdv+iBX8XsCa0JjweohhKGB8cbRrZDQEC1P8E/ND06fYv+PztCuU57GMBQBXiGWMOvwAI/bMB3/3t+aoA0wmxELMQpAEi61jj3e9fAgULIwZ29uHr+uiJ5wTfhdmy467v0PQe8iDsTekI63vorOQU5zvw2/n19xbznfMY7rrhm93G6Hb5aP2R7qraEM9x0X3eh+SN5JPuxvxtBcsBbPZq8n76qAYREYoXtRr6GV8UBw5OBKf5eP3iCOQN5A5UC4n9euzM4w7qU/hMBfIRlhu/ICEpqiqBINwUJwpKDmUecSWHHR8Mev5CBwcXsBOWEtUhzS8VNtMsWCHdG20d/CyoNDEpRiGkIyUa+g/oCiv4Teyf/VoOtQr4B68PyRZpFp4SABYvH+Qq8i9rJr8c9g83+J3nWOAl33vrwP30B7ME8/U78CT4aPuR/bUE7A82HB8fgRiKD6gGMgb8C+AMlgKf9nLx7ekY16zEGMUjzzvfVO6y81r03fZc99v3g/vU+RD7wwIZBH7/K/eB6y/eh9OeziPSm9t34eveENch1+vhJ+da7k/+MApIE0ATXwl8/6z2VPMM+AD2bu6s7vny++7K6CLmzOPd69L+eRHPFfgPDwyMCYQJqgZq/Dv5kASeCDv+GvZN8lDlQdYh1cDgT/Et//YFRgCp/uAJhQ8VETEY1SBvI+gdqBvFEoQAqPf1+3r/uv6mAg8MDRNdFUwN6ADS/4oK+hGKD4ENwxJAFgcUjg6MBlIHyRZvIqQZCw+9CugBS/fR8Yv1AQIjDJQPuw4pC+YJWwLQ+C3+LQzsFnccbRioCjYAQAElAJn6wPpUAtoN6BJMDOn61+es23DYyNv22QjYUt5s6eXxvvAp67LkXucM+AsBj/xe8pXnct0C1QDaKeYI8JP1h/TA6+Xg1dgUzHfHCtR94IHotPA58lzylgANEugTQAl5AcMDCwbx/KHoj9WqzzvXIORc7wb8Tgt9FlwcLR1fF20PjBGyHBEioh7ZFsMKSf097UnhEOXr7ZnvGPIG+g0BlANfB7EQlh5ULuc3ADsIOLgxZy5YJs8dXBpEE0gQdRLHDxcHjAFKAIX+sv3v+hT7sQGMDUodlCU3Jy8lRCNaK8E0LTF3KYwiKxJ8+hjmut244ovp0+xF8Ab4ZwWKC18M0xSMINEpuC+uLBUmqiXiIy0etxTsBTn8bv/aBMD7Zufb3HTcd95741LjauX578T83ABe+kP2pvGD7qbwpfHV8CftsOL01OPP09pm5bzjpuiR8hb4hgDPAIn2L+/88ZH2XPdN9SDyo/b4A+wJU/4C88DvUfPj/poEFP879EvuffFR9Vb41f3cBUQOFw3eBGz+Pfga+YYBsQf4Bj/+KfEK4eXXn+A38Xj/qAlSEMMSHRGaDPgD0v1a/vYBLgwxHKombyZhIqofmhqSEwITYRREEj4PvQkfA/f6P/PO8vX4+/zh+0P96gYJEXkO7gK8+5X/JQ8dI0wotCLuH/wVQgneA3D9PfHV54XpS+wI6bLoIu9Y+PoGYxgTIUYn8DFxNYMv7ihcI1YZQA5ODjIS6AuL/ZHqMdis0ivWtthK2p/ctOBa6NXw5fF08Kj3QgfPFHMZ1xJnAJXrbtrCzBjIFstFzTPTnd9J5/7o7+Yg5Cfmieuh87L7DQO/BlsGpAV3AR7zP+LP3WThieLn3hrXmc1uzLbYyuRc56bnEvINAdoMxxU4Fr8RvQ97ENoN5AMK9wrsieNO3FTbKePd7XD2Sfgr/fYK0RXwGuwcAB5GJfotNTCQMKQusidQINMb5hU4CysH1QiYCScIVgS9BV8PPB1tJm8nayrsLVwtQis2JQIdxxqkHg0hsB0pGd4RLQfVAi4FwQdUDl8a+CPLJWUkRCH6GqgUBRCoEpIdeSNSIZwfbyFGHUwU/g0RB+3+Vf1EABb7o/PK9Uf8MgAc/OPug+N34kfluuGu2ufYBNvT4A7odOsK5z3fwNrx27rhwuLj3/rhfepS8Zv1qvvU+oXw8+Sw4GDkSezM9If2MfG06JPfEtm01yfbQ+Wq8NX2Vvk7+E329fPn7XbptOGL1+nY+OCu5+fv0vvLBiEMfw0tCXb7tOvG2ovPptA91mze/uor9QD32fV49Tv4xv0qAAEA9gM8D4MbKx91Hx8hBB51GPoScQqh/qr05fIS9RT05fT99tn1BvmIA+QLSBArFXUXERdaGcsdwRslFGUPOAu/BkYEif5o+HT29/UI+toE5g+sFr0Z4hh9FXEVZR5eKjU0JTt9OkYzOiwzJU4caRPcDuIM6AjYB94KaQ+FEwAQwwRN/k4BogT3//f0he3V7pXx/u5F7ufvyuwM5CDdVN6B5Wju4/YY/6IH2Qz4CwMLpgr8CA0HAwURAi39jfY172TquOrp6dnjQeLr5EHo0ezj8Rr1k/cC/lYCFv7M9Hrueu8O81j1gfQm8AjqI+BS2B7aleA16CnvhfN88rjyifucCNsTShuFHl8eyR2kGbEP5gZQBcUEkAHoAk4GRgUXCG8Sphr4G5gcoh25GocVXQ/aBlP+evjz9tf6twQjDLsIoAFV/t4ACQj2DskRBhRjFeIXJx7TI8ElsiVYJVYjQh6SFnsMCQatBb8Dif/G+1H79gJGD3UZLx/uI0wouSiLJu4iBBveEKgGywDC/9f9WPoc9brrheLl3InbbN5S3zXcL9uo3qLkEPBT/4MJJw3gDVkNVAurAyD3oe2s6u3qZOzX7xT19/oDACEDIQIA/vP6i/p69UPpg95u1nPPDM5S03nV5dM91PbSe9B10Z7UyNjN4T3tCPVu9Vb0CPcM/UIDWQYtB3UDdvo788ztAOm66szxMfrgAbcGMAvoEWkX6BfVFFYQlAkNAaf6mfc3+CT6yPq++5/8M/cI6kXhO+Ws7njz8fFD8JnxZPclAeoLjhV5HfgkiygzJrkgDRnREdUNNgw8DCMLkAraEO4aniFUJNklbSXXIo4eiBh3EK0FO/uy9677lgFQBuoHUAaMBG0FqAezB28IqAorCvoKQBGWGPAcfx+kIG0ecRk4EBkFaPtm8wTueOwQ7O/rOe5o9ewC8hJYISsosib4H/oVwQke/4v63fc19JvugecI4s/bNdF7zGzSFNoY4OPkS+Rs3XDZNd4K6CDw8fVe/FkDxwjNBsb7YPBg7DPrCOo36VjoJOyD9pQA1QiwEJgWDRnTFSsMVv2T7RLgstqR3tHmsvCL+YH8U/ot+gz9wQPoC10PIQ5zCzAIBQrwEpgZxxv2H/wj5iI4IjMhtBw4GYEXaRSBDxUPsBOuGikjsCjNKKInuyhaKNMlNSJYHuIbcRqKFwUSmgsdBRkB9ACKA/ICgfyn9dfzZPj4ANUI1w23E8UbIyIfJNEiER2cE+4Nmg0JDfgK/gslEOwSZRU4GpQgYyQhJKYe6hXwBzX0UOHp1kfV9tR52EHfbOXv5wDnqufA7Yv49gBOAdf6HvJw6mLlbOLp4GLiDuWy40feQ9nN1UXUotiJ4BDlxuXV6Brw4flABrcQsxJjDZAFWPyy9UHzOe456OHkO+F73JvYN9fE2NPeReQa5HvijeOF5SDlKeUG61T0Kfpo+jv4DPc79xz4vPfA9aH1k/iF/cEB8AO7AmkBoAh3Fo4gVCSQIhkbuRGEBnr8avkc+Cv2wvc1/MD/twMTB1YJGRDeHOwneyr2Ji0g/hUJDFAHOAS5AID/nAATAkQBQ/6H/U4CMAprEfoWhxvRIbQsJzjhPXE9ujkRNnUxnivmJhEgFxZ/Cir9HvZF+Nn5BvmV+zQB2AOBBsEJAwrkCOgGVAEK+gT1aPCL7Mbsne6l7t3uzO+j77TvGvKZ9Cn23/iH/F8AdQcrDuoNBQcc/UXwyuGy1zXT7dEW0LLNvMsMyrDLvNBs2Mbjge/x99v6ePct7xLnR+Cm16bQns6ez5fPss7fzRTMEM1K0yvayN4/5Xvti/UhAJIQ5h0EIHkcABbNDeQFp//h+5v4rPTT8BLvg+929Lr5Fvko9l73WP5hB0oRGRmQHJYfNiB9HJ4XhRVaFVoT9A8PDRkLSAuzDUQP4A5ZDH8NIRiOJ8EyTjZnNMkuoCgTI5gbqhPTDpgOdxFlFt8ecSiiLYsrZSaWIlIhgyAPHwIfuR2oGuQWmhEXDdEIIwKu+qH0Yu7E6GDl9eQC6ZHvZvRk9ij8AwfHDs8QwRBpDmcIbwScBfoEsPxw8OvkyN2V3+fqHPh1ADQA+few8MTvbPIk9PfxL++P8QT2EPW08CfxdvR8887uwOnI5Zvk1+as6RzrbOoW6NfoVvAc+pX+5/1e+7j3xPGy7LLrk+qd5Lrcstmo4l71KQYbD4oUTBvgIKQgNhi/DTwHVwIY/rz6zvSo7YPlGN0K26rdWOGD6DHyAvhk+icB8goJEt0Y7B5aHt0ZTBa1EmMOHwtSBhL/9/tW/Mr4FvOf7wjvdPQRA7kSZxysJGAoTiV1IjMgUBlWECcMLgq5BikFXQL/+Zvxfe4M7zHxnfeQAbsMcRfBHdccQBesDg0FsPy68yfqVOaj6ifv6+u+47ThGumh9A0Bqgk6DNoMExAXFRUYtxV3C6r8xvKd7qbrXule577mpuRU34/YBtV51j3awOAv6fPtFu4m8sT+fwyIFKoX/hRhCnD8Zu8c4XvUkdDl0lLYheQE8yL5CPg9+uQCEQ7bGaIiDyRaITMeGRnDERsMDQtzDrESwRKzDb8HwwOBAzgKaxRGHFojjSj4JlgiNB6aGTEX8BXyDhkCavnE+eP8Fv5GAcELtx36LZY0MTTNMREw6i5ELLclkBphEHsN/g+SEmEV8hmHHYkdlBolFZQN4AZCBNwECwQa/zv52/g1/ysG4Am9C6oMAwzNCYoCo/Sy5zngoNrx2MveO+V/6BTui/OP9Fj61wmWFT4UzQr//T/0DvNR8yLzNfu9BC4B7/e48zvvney289v7sv3U/3cBS/8NAdYEg/5973DisNUAyOfCyceqzw7cSe+q/K78l/yWApQJ4hGiFyUO5/XT57bugfYz8e/rge/K+E4HGRIREFQIfQDp8kHmtuaj7ufzzPorBQMKxQbuA5IE6ARUBCwDQAEZAccAKPu08rDtavBy+XkE5AmQBmcH4g+qEcMMmgqQBnz/Of4DAYYBWQOaA6z8CP9hEzgjWCQAIrAgqhx7FOoJBQOSBkwKhgPS+ZvznfNY+vYFihMPF0gLLgLkBi0JS/7G8KHn+ONw6zP3yvueAowQyRUPD1AITAYRBzYGUAH5+Cfyzu0g59vhi+VU7Pvx5gCQEhUSdQbaBSUMsQ+GCnr7uPDz6pHh59VYzonNQ85i0ifdyuOq4rjh6+qo87bzi/Mm9Lj1DvXr78btePIi9jf3vvgo/5wCVfx/AdwQPBnHGuoUcQ70C20IdQXFAhEE8AhIBiv8Q/Nc7yb17/sz+pf37AInFRsdohy/GvQW5AwhDMMRbw2eCwcQ1wrBBHcC+ghCHpokuRMdCOQNoA/h/FQBtR6OE1YSfyh1H1AQER3bH7sPWBZrFan+ZvFGAuYHtvLI6hzpR9jh2z31Zu0U3KXxIwPX64PiCQacGi0N1STdLx8TYRCSIvwYwv60/M7znd3A0jvkDPDn6sTy7f5F/vX5qwBF/3b7LQrZFBcMdwGEAzgIIQdSDIMKigBR+jn/UAJ89u/raNxzzj3QAtU31wjjn/HA+BsJXh88KocmqB78GwYVsBOyHLkoXCIJEWsNev933z3NN9y8553rDvd++mTyAOyb7DPzRfeF+VcDGRI2F7IdYiiDGIwQig6zBooEpf6m7HLqLfMz7nbygeIh18DjpfOqAkYLShbHHH0Z4h6sJgsa+A+MDtgHAwuxDbkHFwen/oPvgdsrzf7J8deF6FLkTuQi78r8JwPsCaAFtv56/R7yVf/LEgkZXxekDFYD1/vG+nEIgRnTBuABqge+84Xq3+Bu6qrrruRzAkQNSAQEFwYlGQ4+Aof+3fDr68DnvPDl8nzyuQDX+iv2ZP4585Hik+zO79X1+AswCpwFVPrA/V8JnA0CI6wqiSaOJ+4iQhUpE3UVkA/mCKv+9/lV/qP+/f10/Vb1S+/z7jHvzPls/JwGRBQNBpIRCxbaADoNGx/DFJ4QuRh7GnkXYw/qA2rz4exo8CT12/qzArUMDxlpFgsHpAVdFc0VphXTFjYPrBQ8DuwGlgOs9ynn5+ON26LaK+lN7If0Gv497vPdsOL557LnM+fQ8mjy7/Tp9iPj/NWF4Kjj8d3C9JoFJwEsAckLzw39/arzfepB4dvg6dwM2IPeNenR577uN+gEzDfjzuox5Jfm0eB26kraH9jA4Y3gmecz/775duzK8VAGpgxV/kAAOfKd96X+Cvrx/wcJMRbmFND+0PQO+of5Hv36DdEZ2hBfH0YtKRgXFvgYKw8LD+gH/fueAufuXwPDEhjdKfoZOqYNEv17O1oSWPzRDtMa0RAz3fX0GSf6DZnufzFnLeoAtSElLpIHhgRzMicLk+ZzEZQYmfkS94YIEPrv9XkQvQohGPQblBERJQkFaPF5JEIY1/N9KQo0aQziFyUlCRaSGgonniDPH+Yh/BuQFc8NkgAG/hkF8glaDxEWdRdzGcUcShdhDgcNuRF7EagSexInCLkECQDZ9RjvGucc4yHeut8v433eyuFQ5qbkgeI95AzmCuf16bDrRfHb8Lbsn+zl7Mbpf+Na5kXt2+++8Kz46/d97YfrpOhi42Lm0e2T7qzwqPCw9s8C5ARWDxsY8BHHD/YV9hRxEhcW4BngFyMSeRUfGaYW8BPuGBUbLRQbE9wWBRAZD7sUsQ70DxUZohekFEQVwRDwEUgTKxMyDqQDGQQ6CMEAo/Z0+Ef02+Xx4/Hnfdxa1j/h0eFL4Tnnpuot6kniIOBL3fHaqtcK1X3eYOAz3fHkWOed3azhj+K02dPc+N302vHaUOC+5hDvzvWX+pf+ePaq9rL7wP+d+9/2PgF2+pP9bwptCdMKqhfsGpAQAhSKFPQLMARc/nD7rPkz/PIA2gL2AxUGKwjmC0oQuQy5Bi0KlAlpCKwOkg36DaQO7BFAEPQOCQnf9/X2TerE1crfrui44JXuk/Tt84gI2RddElsLuQHZ8QzyBPUG727swu6q7kP9XQwlE1oZtRMuBhj8zPHV6SvwCvWT/ycL2gYFDs0YvxXqGqoodSXVIOYpHSqMJagiXiHXH/4Z4hrJJAYjkhwTG/gavSAtJlYlVCIxIDEgsB+SGDATQA9UEGkRShJnE4EN7A1aGAAXRA61D8EIsPmh8qP0DvtU84Hsf/Iz8hbfEtB05LbiTtXX4I3nI+bK6hb2ofOD6j3t+e995gDrgfGP7ZPyAvY/6FDjqPAt99f7zwRYCYIHewNy/YP+lfoQ9x75zQG6/54I2x/BEYgXYx+eEXUVcxvDFTIVShqUFMsQABWgGegYDxzbG10abyD0I0YpwSu3JVwfMRs2GHEYWxSOEXcXIRcLFIMZIxu7FbMQOAxfAWL5Nfbh9Bj1l+Zg6XvvQdsE5I36WOeJ5kX0oN6L3rzwpe646QrpTuKw3MvaJ9kv1vbWNd9i8FTye+oG7lTv0Ozf8AL4h/Ch8Kzv0fAW7yXiZuVQ78znK++89o/y5f2j+lj6O/O6+/wD4/Z/9DX2xvsfAsUF2gGD/ff0EO247KjtPfNAAJP/S/Ow5IHi1+Qv4pPi/PCH8gbuwPj38XLwePu+/7jt/O8c4x/Zf+f82qHjUulczEfRrPu49bjhm+6y6x7YUOO+9EfyGPOy8gblGtuq3uPgg+4t+cj2+/PE6crxWwW1DWEDEP+L+9X7vQLsDLkF4glOENwJBB0lDv4U7hAREqoflCZrIzgTeyWiI5AeQCRgKBEluyVzKs8oQCPfISMfYxg0D+IMhhP6FKQSCRtpHskbvShMK5ofih2kJM0iQhm3DfgDPf39+rDywO5k5LDwBv+J5qj1HPJ56Vb31/H78mbh9tjR49Phzduo8cj61+kr54fgYOmq87DzQgbwAWzpp/0XCtv1yO+w5eva+tp/5gjx/vc3/xcISBhMHSMPUAxrA2jyjADgDIwSZRkbH4wkMSkbL40sdSaWLFwy1yuaJ3kjBCHoHogXfRieHCEcnB/wK8swYilGKTwplirZKrQq8CqeI44eLx3mEnULOhFUDewMhf+y+DQL9AD7+CULHRxjB77zn+7z5FjcosuB5ZPvI+hw+XT00em465vyR/bj+j3zZuEE5J/sK+uL5+Xd698A6kXr4ehk5C3hmeH860/wFOP45onstOCd8kgO3gMXAkYgoh1QDV0XXQvG+/4MAQDh8zwIDQNY92MAoAo4B9EEOgmEBFryQ+yZ84H17/u3CKACXPwXCRUQNA6/EI4LUgYADqIO1wiy//74kfFk8Mbv1+jh5qzgm9yk6s7wcuFQ4HL6tvcp81cBFuO430Xp/NZM2HbgR9s7z9vLP9ch1zfYau9w9J35Sg6YEyMEtPtH9qHwrPbn/uP6P/M9+5oLjgmCBfoUmB4ZG38YhyQxH6QH6gCWGVATzwDRISkorBm7JOwsNSe5KWcyli8EKCMcJRVjGbcaRhUbDxET0RMjFRcR9AkREb0YwRyMIbkbvww8BcMAjABJ+cbgZtlJ6xLs2+3T6CPaNeq48SLqGPTv6mjfL+627IPeFOQ76Krhbu2V9STx9/Dz8PPyk/4nA5YCogLI/Mj0+fE/8JPmWuLb4aHk+OLZ5Cbx1ftrDaYXOCbRKUAcgRumGVYSHw6mGncbVhniJjomEyPBKp4oHSQAJishHRtUF3UYuRcEEn0SAhy0JAoo1SnLJ8MmpijBINwWlhGxCi4BuP/0CcsPMApjCykWzw93Ay4C+fN03kfqofHZ0QDV5fKF5HvZh+nn42bhl/fC+vH1fv3C/f/5zv+R+lLuqvD+6wbfANu20AzBZMd906DVBtmq3RLluvAa/wkAM/5MBdf65/pU9UftsvAt+KX7AABpFUQKeQBCAxz2wucp64vpwNaD0t3bXOal8s8Ang8XGpYbxxz4Gn0RzQOB/mj3Qe6l7sb2pgCp+v38YPyb9CMHcwMG/30KVgL99GzyS+pO08ThCubp0hzmGO572OnX2fVhBGT60/dw8YXmJvO+/8L8kfab6ofutPY/833xM/Rk/zIJXQiR+uvzvvhw9AD6wQcI/Ov5axOcEyMAuwa9CBD+bwGiGAYxCCIGI7oxyx8hGAAchRQNCj4F0/QO6YH9AAgpEnUrhTJvL7AtWi5OKdsdxxGD/ynzYvxjBKYFlgDI+Hj20vxy/hMDAhE2DHz/1fIg9rTlsNW+8REEl/tMCdUF2d4a+CELVPHWAVQCI+B732ruj/iu8QDjI+SD78r3kfi4+kP1kfYG+w761QOh+378DxQwEwAJaQ1KDgkPzwff/vYJFQNSCr0p6h8zIJg7EyxrIiUoWBwAGN4cYxqKE/4MrhSUMko0VCdcLnctWCJxJrQexxI4DvAQWB4pI7YnoCffKosodSL2GkYZJwVR9CD+kATR8efervsx6MjcgwuQGZQHbwdIGx0ZMgIwBPAOXPTT6qzu9eXr2Ofkg/qV4UnhbPuu4sLY++5o1z/FR94M4nfV6ezl+XTqpe8Q8M7xzuoc63/wVNtB3BrnVuhq6GzgIuPO+Wbnus/n2YvGOcvX+KrnGNRH9GMC/ArFH6AVPf76Ao/0LeuB9NXmgdqh6wsBdQYLEQMAnfIG+Qzm6eMc+SL1ifD6B5gN/AfLA5f32fti/f4Dlg42DwgbzRwjGCUcOh19DD30ouQG0aLNeeZ28oP1BO2P+mkY7g7iD5wPGPp/9GMAie6f6r70FPGB/YP6n/id+KX5gfw388rlL+yh6FjpLQv4C8MCRB4VJjYQlhGxFasD/BI6Eiv1vwkAAQ8GhR+zDzQHqAc5+IvwZPqo8nz0RAWUDYUZeyWyIGIpUiFhCz4VtQm+7031swFF/wb9/vcK5pXdOeck7+H7oBAZBJ3yRAncBbj0kgwTBefjAvBF/mjxsvrkDQMC9/MZBCDvjcOsxWLBTLtu1T/ioN76AZwgeyDPGbAZLgsW/78KtwHC91ruCPQLBIgGfwzPG0ggSBp5FSkIYPhdBVojLRklElIjkCzXKBkoqi0hKGsr5TcINT42wTtWObRAvzzuMREv6ihlHDEYxxlcGu4b/BvoH40rKzEGKxUnIx7JFwAUNBAVElYRqA5nFBER1wwyELEEKfZy6Xvtm/ct+eIIVAlF/AABbvcW7533/fM55Ufkyufd4vnorPtrBtD1xurr4I/GFb0pwtW9WMJ51frezObz+pYEeQGCAiv8WuiN3n3kqO0c85Hrvu5c93r9Bv4t+y36rPNe8YwBgQu1AmcNgxFhDoUUexCkBzgFwQF0+7T7j/ZY/AcVUBmMDoEOhABw4hrRicohzDXc4exB+H8Q/hpIC7cJ4gzM+OvxR/ok7wL1pgfRBCb9n/6n8mzb69vL0fTJpuOX78j0qAW5A+/8rw+/D/f2zPKT9U/xXPij+8j40QdYGAcVCQ9nE30FjenE5TvbuMHX14Pz5/VAAqAFIwXcDjwXGxzTHUwmbyN7FbUYeQc6AjARPAmGDYIC0PLsA5oNlgpdC6n6pvEjDVgebw/U/az5UvDT9lIC8frBBpob0R63JR0l7AqH8EXi0dib1QbgK+V/7NL7VwfcFscPqgKoDDYDtvmmDIEWpAwBACUPsB+sDREMmAl47rzlruUG3xjfz+tY9e/8UhSeGSsROgegCvIRggHV94/q1/R3D30WWw8DAQLpAOTf6Dnltv5GDQb68gCQHfQRfRLJJBUewxygI9EfdR06IGEa1xXDFDQTwRwXGOYG2gQVAIfz1+cm9eX7OgjJKVgt0yRjKuwo5BtpGU4TrwtzCy4L4AvFC18FbwBY73TituKy20Xgrtzj1Tvsavhs7Aj8DQvr+gD3NfWJ6g7oqNxq477p/NtY3vzrzuf0zYm+XLZ/sWuyL76RxXfQoeSu6kfvgfpi+XjvBO0746bl9e3b4GjROc1uzLbOVN9B6ePlDulL8KH50vvf/88AnAEFDa8L3A3cB+QA2gBAA0YScRXqG64oZyg1IwQcHQ4W/VrszOx2/ZICHQAXE6gjKyQMMd8zjioCJdkZwQVrBOYIsvW68y381fLl8/IQKQlJ8y//1fpw/RsU0RPJCJocniL6EMMTrhA1/Kr8hAVbASv4hf0DCL0OZRg8BHjpptrt1/XhUu0c/lkLVAaqDwYhIyOyJYkpISUpFbcCg+xN6yvmgdU311Ll2flhB0/++unZ+eIFnfoyEoUhax/ZM9c78C7+JMkYtQb8AeoMnAWf+NgJ6hXuEEgTig5T9+Htn+oU3gjikfEM/+QJ7BkGHwkeDyB7H38UtwJH+KzgHN5Y7e/qPfj1/9D5JvRS7V7xp/KX/AEEWxCDJgAoHylrLMEfkA04BysCAPs19EP6jAt1Dw8NkA50/pvzDwDl/+AAbwCH86X56gymFXcWIRm3IHkgGRrHGMUNDPpy7YXpIPeaCDwTOhvJFc0N2Rb8Ef4DuxaqJJIk3y7sMaAlMR4rGgUQuwrwAPntXOCV4FLpK/HA+7MAeO7f54X39/OL6NHoWPCH9bkGKRKOB4QKvxDBAhzzGuhe0XfM8dUr1IXa9eMK2NHMPdj61znLwNFo1LzYuO75+kwI6BLgBsj8yv4S+nLtWOTV3RLSRMm0zfTTANJJ12Tj3edS6+fvl+vd7an5VwDS+9YByxUwDUH+dQFg9cDde+Fm7p/1jf2KAdUBLf0o+2L0Qe/t8KX9lgpfDcUYfx8LHw0ioiMtH1gZQBEbBl8AZPw56z3gxO2s9WkAsQv2Be4DWQb4CeoOOBbeHIgTqA04G/QWhgDX9+/oFtUA2ffkCO818cb0i/9IBF0SvxUDBzwBxQUfCa4MZxGoDaQHywUrB8cIOAevAUf6FvQx7lrhHtc9zfzPZuqB+FsAqAYJBhsSIx0GIEYllidaKBsnACacINwMTfOR2rzLc9Wi5D3wKQY4FM8ZISKHJqYlYSOgHAYaaR+WHPgWbxPPFLAUvRdIJeYeWxMpE/gKAPZ744fkfely71H8qwAG/WcFtxpWH6YYVC6eNz4knB2eDlT5vu/X5LTaCuJD7hzrcu269sEAjBQbGlATaxZ7GLsdBBvyC04JAwBH+lsGdQqiBTgMWg9/C5oRlAqcAmr/fPVe82cHKxGSBJQJwRjiFuoQWhKeDdoNTBL0D44Kswfl/ybytOQM3GbY49Y52bratN0Q7MsC/gqQB/YIBQ7aCXsCDwHI8F7eTN0/18vNJcmwyQ7UsNwM2InRJcvhx/LLBNF92TfYss+w05PdReAI5dHwvv1++9n0K++02+3M9syDyBjHWNFk1PLS+tIh2N3Y4d458Fr8IQ6qH7knLSZ3H2cWngvuCZ4JVAJu+9f9Dv5ABrMQ2Am1B80KhAMuAhEKuQbNB0YT7iHkIUQXZxugIJIcOhh5FUYKTAIdCF8PjBtUHTgN3gKD/3MEGwZWBCEJDROgHMkmtDCLLhEs+CTyHTYZswtc/8z6pAFe/tDw9fQU9PrrUfeh/rbxGO9m+4/9vwuDGbsJlAUyFPwRMgbp+4Xm9tSk1bbeaucU8zYEfw57Cu4EKQN+/LrzbPwwC6ARPCIALLItEzUZMsMsDyYpF2cLTAPyAwAHsQLyAGL9m/nV+4f96f27AAsLdRy/Leg0Vjf0Nb8vfShIH1sRjgRk+/nt0eiw9Q8FhA42F3UQdQq1CJYFdwMZBOoPIxnmIeoplCucKDMimB+kH1Ab3BKrAgz9Cv5H77ri6eFS42LuhfhP8lTpi+6l/XsPyR9zIhcgMyVvI5YVZQqD+1zinM450sLih/LeBgYZ9hWQFj4egxMRCH8AxPvwAgAOUhAXDzIQDRKKEHMPVA7iAg75f/so/WD8N/uZ8xzxrvPK8bbqFuJO4Qzs2/ZAAcsJlANXAfIAVul51pXWpsP6tOy+6cHhv1LSuuJU4Ofj9erf5xjmM/Lx9gL1Gviw/q78i/Dv52blXt/I2b7YMdZM1evT8dLN1WbXidm05rztAOqX5d/gEONY72L7zQGiEZwkDR/mFpgVgQTh7M/f4deH1I3eQ+2H+bkEFQ4pFHEXZxkCI14oUihMK2IohSLZIWEfshf6FFsTlAwXC6YLqgkRB4gChARQBycHVAer/0fwuvF4+rEACQ6FFCEUnhltGwcPN/8M8XDifdzh4OfmnfEi+Nn5/flD+JP4xPJN7VH5jgUCCkoVKx3wHQ8e3BWzCZYFp/vt8C/0vvjl9ifyxOjn4gLm/O7Z+kf/EPuJ+D389gbTCn0IYRLsGeAW8hEVDdf/S/eZ8j/pHurl73D3Cv9+/P/6BwPJDB0TCxbgHvQlDSi6L/Q6QDbkKR0lvR06D+n9p/KB7ZXr4ezR8MLxPfTJAA0MHQsbDAAJuP08BkoT+BpvJgsh9BobHy8Z4gx/AvzvWugE8onz5fmoACT+RfrTAIYOiBD8DBMTwRqyHsco6jGULykqGScVIAAY2Q/2BeX5/fPA7x7sUu0C61zmTehg9sMAngOODDoWVhZQE8sPQgwXC78IXwXI++3o5djy1CnU+tRH4invsPVg+xT6aPM/7s/pxuUt533tXPbeAEAKjBIyF8MQ4gRS8kHeDM3Zv3e/usa2zR3TJ9di1aLYO+UO6bDmaOly7272Nf/TAf35BPIv5arTostxzIvMns3y0X/fAupW8ML0cO0x8R76U/n++IP+qwKOB/oSIx25HP4ZcRmmEtcGT/yJ8rTqn+yD8Z/weO6m8MbuIO7x+XcEbwPFB9wVbR+wJY0pYCaqI+Yg9BWmDVsDp/RH6mjpJ+c/6cz9eQzaDbsREx4TIhcc8BcTFdwV1xoJGi8cTCkbLOoiSh+5GeALWQEM+u32g/pW/oP9wvRq55/bStkQ4Ufng/SUB/oUMR4ZJJ4mRCNMHdwQwv8p77Tf19IGzRbOl9NY5Ar3m/x3AGELXxG/DsUI+gd1BG0AYQV7DBMUShk4GDgXLRWaCwEFzwEwAHUFGwXp9D3mz+Ru7LrzGPe4+wT+ewR3GTovezW0NYk2gS63IhsZ6gnQ9d3f1dEK0hLcKe8nBkYc+il7MZQ2tjSWKDoVNgnuA+oFoheBJiMf2xkTHm0ZbxXqFOINogVUB3kRDRSkB3z8++3r3LLkXu5m5fHrBwaOFislEDIGLpIofyQEGOwHHPc/5bDXL89EyuPSEuwi/+ADkAY+CQ0LAwswCZYFLQcdDV8PKRHcEpIQWwveC70Iq//79BjtSfMQ+cTyL+h03N/R29ab4/jej9UA3zPufvf3/lAHzQxWDzAM4f5g6ZfVG8jlufK27r7XyNvUmeOB5aHmQ/JR9z/1tvPO+EABHwZzBtoDwvvZ8XTs1++H8WDoN+K06vXwSfHT8cLqO+Sh4wjnHOSL2/bYh9r36HMCaRWKHmAh4iEvIuwdWhK5AyTvANtY0jXT0+Cj9KoHThY2HbshiyIfJAsjWhwPG90YERO1FG8Y2xQJERUS7hH4DlYPThM2FF8S8BNaGb0VBwZs+2rzyOZo3ZnhHvAnBQ8Y+CA6HH8P2Q0bCxr8+fLE7sDlgeQ/5nngGuUn8yD5Hv2iAUQKnBDYCt4F7gTDBxUHTgDd/10EtP1c+YoCgQSZ+5f1f/D57j4D+hJpCRr9avQO7lTtYOg93rrd0/B3CGETERtUHBscxSCiJYcj7BdIEfoSYwqA/UP9JwOzDdwTohqqI+Qn8jHDNy0tSibVKu4qCCayIoUdUBjRGAgbnBojF3kRpAvyDuAVXxgtEP/5R+y46Mrtp/ygAG0AtwPkCl0Wjht7GTYedyHXH+gk9B/oDhEBie+T2pHOlcoI1SPiBupu8/35hANIDpQSGRC5DIII3gJKAyMGywLV/gD70PwI/+f4g/Za+pf//AZtByL/m/BW3+3aS+I74ZveuOdJ8W7+wxH4H8cfCB3ZHtEZYRDRBU310eRU3GbVwMw3zZvbbut49QL3VAFSElYS+f+V7u/gzdkO4CLrwPeh+I34cwCgBYoFOf+D78LiN9+L3IXgSeEG2QzV9tAEzzXRWs/G1lDmzPGJ91z6FPlN/PYBswbaBNX4Q/HT7YfimdHJzC3Wj+pw/wUHngLBA6gHSASJ/Hz5zPzM+tf6pASmDqYPLw+5ExsXShAwBpn9n/o7/y4JiA44Btf/uv0O/Pf/JwNF/af0uP0REJwbgyXkLXcxFzKuKxUZ2ggr+WTo7+HN2VDVFOgrBwQWBxXwDgcHywl5Csj9MfT77m7rtu8M/1gNVg65CLMMlA8fCOQB+/7FAwsHU/0m8P7h0dCTyQrRXtrC1+nVvuMx/tEYLSoZKw0hxyGoH2EZIw5+/RbxIuzv7SfqDuMx5zv2cP9EBPQEGQjNEfISHQ6IDX0RuxWkH7YuwTekOGs4kTtQO5Q07i0dJYMW2RQXHnUWswUO/ar24fhvBb0MsBFMHoU2FUM5PME1njBlJzgjLSP6GZoSdxJ3EhUOMALK9E/0CQFhCKYIk/5W9eP9EwLb+yD8NAE8ClYYpiJ5H6wZsxVMFAYYjBNGCHT9GveJ9Sb0yOjp2Y3N28cGz9HUd9I/09XWi+Ni+v4AVv3Z+aX5yv9IA+H74/NJ8ajyvu9y4DnRHc4708LU8tFUyLbFndOk553x2epc3s/Z8d3l5BL58AbgBfoQUh/oEhb7Oe0K3rrSM9iw2jfUkdNs2eXdL+XZ7s/nqufQ96YEkgz0EKANrQZGCXEM+AZfAEQB9/9s+JnvP+B/z8nNpNgx31TmUuuR6KPxg/26/ogBLAMlBkQSux9IJr8jIxr4F10adQqq+T/0qO/p8l79HP8p+ov6n/6oBgATOhQ6Cv4DawcPC1QL2Q7FDYYPshpxH1gYuRNCFIgP0QyMDFsJOAO0/cEAuQC89hbx//oZEB8gYifZJRcfMyGcK7IxVjCiKGMcqBQxF5gVoAQv9QDu/PEz/0wK3AtxCV8KEQy1EAAKqvq881j3pf82C/IShRLqDkQUgRykHGEc+BvJGWkRggPE7xTYbMcIyxTaT+oQ8/Xz8gL6FHkc+h5EGGUP8hJnGBUbKRmMDg0AePs6BOYCO/fX8Arx/fbV/ev4HPNF8frsXPIK+czuy9/I2qTf7+mu7UPtvO5N9xsKCRcbEdEEl/pg72rmR974yjO8e7uJxC3aQ+wS8UftaPZ/BCEIcwRH+xr14/bj/GsBbQJ2++X1xv2WDSUNFwSQAdX+twQnDZIEIPew78joheqq7JvgwtSw2o/waQnwHOgk0SEjIHMnnC6LKcsfUhctD3EGaPxm7YvcgdZJ4TX5tQrZDVcD3ATDFdUXfw+5CdwGTA0XGBMY9BGeCt4FAg0VGdUVDwf9+Hb5ggYjC9oC+/WF7qjrHPGw+THzI+Zq6jn8xwsXEysUIxF7FAAjzSNaFYwQoA27B20FOf/Q8IvgSdu851r7RArJCT/7vP7+DE4QGwcG9nLum/bNA+gMYRT8EgsRIR9cLaohDwlc98TvvvgsBWD8buwE6bDpGvIY9x7rBuDN5Vj3xwL6ACb4DvIC+foKWBeQEmMMAgryBRkAHPQn4uXSz9Ec1yDk2+2j6+3l1enC/zwNnAYa/K79gQclDLkNoAzYAVj7CQP4CTYAf+3Z333a5eTb8931hfQq/GEGzxEAElQBi/N97LbuGvmX+4H3DvqSBY4UAiB5Hs8WgRfiHn8gzRfPDVz8AOdy38ThwutP/BsDogMbE1Yglh95FEoEdQKWCmsSrBc0FP4GCQSYD9kZJxRUB4QH0w4TGfobywtq/Kr7dPo7+fH1yusi5aHpQ/X6AKoGYQdxDZIaTidrLsMp+B5lGRcTRgvX/Ljnm9Q5x9PHM9eo6rDwaO7v/RMZqio8KkoakAy9DqoVaxLZErASlglMD0ggOCHVE6oGev5ZA/YRzRAFCKQHoAmMDlYNkgPp+Vj3dwNEHEAreyhrH9kfmivXLy8p6CBfHX0bUhTBBFbywONJ3HfZz+YO/jIOsxElClgN8hovG+QLpfz1+dEDbQfcDPoTsQ0CDkAaVCDRGB8JtPUS6QzsEvOZ60Hgn+N9643wtPQm8Dnkn98/5sLwm/b39nL2tvyICDwQuw5ZBYgBHQAk+0nwAuRy1w7KBMZuzvHcQeMa5vrouvKIBRMMPgS+/bb+mAW7DQAVUBiuFHkN4AiSBgT+l/Mp6XDjXOqb8i3wSe6w8R74Yv/uAh8BuvlY70PnUubb5H3iGuHd6OH59gU+Cd4HtwUNBNYBNfXK6BjiTNJYxcTJ1dJJ2gTdd9kc5fn63gMnArz5Sfb593z0vvFk8j3uDueo5i/szO194gTZH9rz4Xrs/u2X6X/pn+si7AbrJ+M514fLO8ug2Tvneuuh7wD+/BGUIXskkCA0H7satw5q/9Xw397AyxDFQ9I56dn4yPeX8hsCLRd/GTAO7gOaBi0Org3NDWENxwIrAXcPMRtOHLsT6AnuC44YER7wE+oKDQnuCQcHfvwp8F7ki94W6lIArw7ZFZ4e/ifXLmkzMyteHTgYtxEjB3L9sPFi4k7aUN8e8A0Eawkv/C36gxBUHRUVGQiJ//QEpA6WDRUQlhTwDCEP1SPoKDEXMgWy+TH66gUnCPv34etq8FP3ePyB/z36zPaB+dEDpBFvEikNvQ8+GuwoIy4GIyUbhx2SHfQW7gptAKH5zu4S8eYGNBU0E0oNzxf+K9MweSHyD4MLJxDLFRMcaR7gGFwZ9iO9KI4d+gkp+jf1Pf95CeABMfkdAIYOdxbeEXkIhfty7C3r+fPz8azqJOsG9sEJHRm3E7EIWQyaGLUYTAfz9LrjVNWR093fqO8t87LmrOkVAJYK7gdT+0X0pABSD9sT8BIJCkgCLQdrEK4PqAJJ9hTyyPoNCewEqPf5+ZQD0Q2QEJIFlfv99037UAZOD6oQBwwpD2Aj1zLDLrcmfSaiKKopBCH4Duv3CuLT1WzbCu4O+efzCO+MBTYjdSwNIHEPgw4rEwQUWxRbDLj94/oJBPwNMAfA+HDv3erd+b0OAwql+jf5GP5+/uP1Iuei2r7UoNw770f2PfJo8rz5qAbqEjQUoAu9BkIET/4n8THeQcxovsu8RsuZ3s7pquYg44vyIwT8BJH32ebx40vs8e+P9Dn5kfW2968DswpzBOn11+dQ54vxOfZJ71zpaOpJ71HzzO8K6PXfaOFN787+ogTJAfABWQdSDeoNqgIE+Y30Yu896srfddWyzgDKe9Db4jnvzvNw8YH1cQc0EE4GwvF5533v1fca/pIEfQCn/foGVA53BefzDucE5TnwwPiN71bjI+XZ7kv6kf1R95vxXO/V85P9swH3+sTypfcLBW8PKxPZDGsLxRXBHK4ZtRCEA172o/Oj/TwJ7gmoABkBQBVSJ/QotyB5GIobyyRlKKwpiSW0INMkRC5QK5QbVg+zBikGxRDXEBcENgTkCSkOuRKzDtMBZPZW9/YDxQ7sDg0Mqgu/FGMl0y3NKA8lDSZvIo4WhAQW8ZPb+tK43O3pfPVY9bLw+/7ZEbUY7BRdCScJERhOIL0d/BT4BJ368AB1CS4ByvS07y30QAdaFvgP4gbqBB0DnAWCAWjwh9/J2KTgpe9s+NL6DQCoDYkdPiYXJDYa/BGDDuIFevd56EfaK9PI3CDxbP6L/gD1VvwvEN4UHRBKBYX60v4PBzAJPgkPAsT8kgLLC1sHk/l985PyEvoDCCwE+/Al6GDmbubx52bgpNO80yvhQ/Ei/hsAfv9/C+4Z4iLZI0AadRBtBeX5VOzn2l7JBr+0x0fdPe+y9jv2wvzgDocWPA/V/gjwmfDS9X/6dwAA/Zn3AAHZE4oYRAoG/6j28/NW/Zf7ZO7l7G7xP/kBBK0CofgQ86X18f13BgsI9AWKBxMPgRdtF7UPNAx9CGsCjgAk9+HogeJy4p3t2f91BuX/svsuBMcKdQbE/azy+e+N++AGbRBlF3kShA3JFVAc/A88AIn2wvOl/L8AWPWB7Kjriexm8gD3jfF27LTwaPqsCCkNHQZQApII0xHqGIoXPg5ODvwRrw8XB1T6+urp3wbl2fFP9U3um+RF7Gz/6gizDDoI5gR7EEAa3RlzGX0PuQCmApwM+ARe84fnMeFw7E//h/+8/YEGfwprD7ASVgZP9SLuyvDQ/JoCzvwo/VYJVBq/JYwl5B6BILAldxx7CO/zIN6qzofO39pB5azoDufx61cBjg/BCq7/tvofADIKpg0RD44P8gk4DTYavxk+CLb53/FW94IHTgnp/17/dQLgBiMKhf8G7iDgbtmg3k/rAPFU8rr9RBTuKN8wVivBIX0bGxKGABztj9mJyN3FqtMO5kXxN/R/9lAJmh8tI5waYxGiDwQT1ROsE5AS4A5GD9cTmBYTD4QDi/7mAlsPThRfC4EEuwMDBVII0wIW9qztvPAt/bUJfQ4XDX0MIRVOIxMmWBxEFXEWLxd1ETwD8/MS5xDh0eef9F7+6AKmBCsNCh91JnkZHQe7ACcB+gGKAuIEAwjyCZgR9B48Iv4VYQjW/3L9sv7Q+RLvqOnf6U/v9/NU8GDpCOe26/Xyl/jr+AD5TgADDGcRuQwfA7EAkgRKAw76feqk2ZXRH9MI2Ynhf+bT6CTswPXz/4f+fPOq7J3y8foAAAUHogshCIYK3g/wCUH6oehL3vPf4+il7k3wGPLE+X8FawtKBHj4Hu2s5dvnk+qD6OXnL+2f+JQJtxNfE9kOLw5jD3cJofzO7hLjFtyo2ynguuam57rlVOd08C/7Ev0Y+Mz5qAHeBIgEYQd1ClgJXwi/CN4G1/pL7Wrpl+wp9Lr7Ofvp+RL/nANdAQD98/ce74HsR/C+8vPxvPII/QQOzRz0KHctpixlMWQyVCP8Cxj23+Az0wLSFNu66U/3JwSzEscjEzTFM6QjPhkPFpYQpAzDDdoOnA6IEsMa7CBfICsYRg+iDIMLnAjTBg0IJQ9CF4gZ5hXZC+f+Avbt8ZHuke779a0ACw91H78lDSMtIcEexxeUDOv9gfD66qbuQ/PC8JH25gRrCqoOgRRrEowIePyn94/6xPnZ+IH9PAIyCMcP6hCxDgAMqAI/+zP6zPW07cTl9t/14M7mJO799GT5APyX/pABvQJ/Ad35nfA98y37MAFMCbELXQ5QFm8V2gsFAhD3pum63FDUBNmk43vpYu7S9jYBsQXj/3D6P/tJ+mb6WwBICTIM6gp7DG8OJQm0/D/xoehB5a7pqO949SsBrAnqCy4Nognv/uPy4evd5w7i69zj3mrqsvobBqgK9gzHFKAeRBsTDbcASfPM5CDfh92D2U7d8+Oy5e3s5fgI//v9dv7qBTQNLxHDFQAXHRbkFfIU4g4rBcr+iflR9o/55gAwCXsStxrFHHsWgw4wCk4AyPN086n5TgHFCpwQAhWeGR8dWiFCJB0l9iKWHE4RzwPb9Cvkxtr21pPYBOg7+kIFNg4+F9cgWiXwIIcY7BLXDgcIiAVMCmUMdwqaDAQSxRJhDPQDYvrE8wTzh/HV7YHuyvNy+fH6cPVk7CLo8e3v8/fx5+uw7LD2bQLNDP4SyRAfD0ATGRFUAz/vQd0W0DfLK9GR3c/ncvD/+28IXRTZFToIVvly9Bz1evZa/M0J9BUVG30ekh/8GQUMMftH79PmzeHh40/q/vFu/F8K5BVvGB0SOgi6/8r5xvgW+/n7JwBUCcMMfwiBBjYE/AEDB5YKXwbaAcD9EPe27cLnQ+ka6XLp7fIr/Uf9tPsS/AT59fVB90v5uPr3/gUCoAATA1AMLw5dBC34J+/b6r7s4fBS80X1zv7kDFASdwwhAIPzS+q06KHpyOYG6RDzbP97Dh0bmCDfIv4n0Sr4I6QVwQSL8yDiIdbC15/hVuty+IoGZRKUHAAhgx4ZGb0QbwkACZINIRGkEWMT1xmmHncZQA7NAlz86/vz/skGYQ8jFgge/CCSG/4OQf5g8WjopuGV4KjnjfKaANMSYx3THkod4BWxDaQIDwBu90/zke7+5xTm4exJ7+PrCO2288D+wQtYEl8O1gNW94nw7/B08pfvAO6f910KjBSFD2UH0QJB/g78xPzG92zyhfN/+VX/JQBy/Kn4Cvb79Gj0zvST9kP3yvg9/cME4gxSFsseViCiG6wVHQ2H/jPvP+Zy5PXn2+52+NwCkgzoEkIQqgjz/grzturX6zfzpfnRAdcN3RiOGg8QMf9w66LbGtgx3C/if+6WAbATMR5KHaYQWQD59bLuzOVO3tnb4d6L6Kz2Yv/VA0QLCxO5F6IXMg64/nDvBOJW1zfRg9Fq13vh++3h/CEHGwx/DwcQYRAFEiEUxxQ6FW8YnB0CIdEdnBOiCbECJQBOAID/PgIACnUWKyRnKbsg1w9bA7r/tPoK7uvgkd+28EQJEx8hLS8zADltPqRAJTngHw8Auub+1o3TxtTN17bfqu5tBDMb9iqNLN8jjhr6EuQM4AXG/t39igAwBwsSXRh7FIMKgALZ/Wj5bvZk9Rb22/p1BQUQjBQ2ETAIh/6P9Prml9ds0ifbJ+27AEINOBErEmMVVhuuGM8G9/Az4C/Xc9e82yPhk+kI8of9QAxtFawSUAah+f7ysvBs8SD27fnK+rUAWQtEEx0TnAn9/I/yf+6b7Tfp8+Nk5Nvs9fvyCHUMQAgnBCMC8fuF8dfmQeDN4RbpMfHZ+NoAywnPEWUUBQ+GAg7y4eMr3aDdIODR5LDqJPNT/zgJrwtjCGEE/f/E+//6M/yr/uQEigvqD94PPgqMAR73R+w/4/jeat9i5bLw5f9YEIcb5BwrFx8NpAEG9VrmQ9qm1x7gg+zx96gEPBSgIykteSrPHAcJ+/Pn4a7X19Yx2hjhR+7O/ssN7hSMFaAVDxSQD3ELxwplDLASphtCILIfkBkfDWMATfal7O3juOBm6bT7OBAEIIMnxSaFIqAdVhVKBC/uI95Y3RTseP7NC9cUzR4CLF4zSCt5FIH4L+G400zSL9hs3H/gg+pa/UQS8h3iHFgU4A7qD6ARIRERDX0I0wdGCmsJBwIS+ar1avnS+wD5i/fd+Bj94AMpCTwLpAyqDncQdw+1B/n4qOrZ5PXoUvP9/tUHsQ2oFZQhPiXsFqX9/uNQ0hTNUNPC3PzjR+0Y/5YXjCawI+4W9gf9/C337/Jq8K7wCPfqB6oc6CbJI78b6hFfB278Q+8Y4pHYTNbl3oXurvxXBBcHfQtYEjoSWQco9/7q2+tg9nD+XQD+AikLLxVIFWkGQ/F/4AbaWN4Y5bzoLe90/sUTcyE+HjwP0v6R82LxcPRL95v6bQFWDlQgIyt1IkIO3ftm8SntJ+cO4IHeMeOB7wACRhC1FNkTgxKcExcWtxERA5/x7+eD6dDwM/WJ89ny+fm/BYYK2gGu9CDuhe6q78br0+aj6+f5SgV/BrT/XPpc/VkE9ghKCTYJWhB9Hgwp8iVUFrsGbQHsAP/5e+y44Y3ghedc8Xj6KgCqBZgNoBUdGvAZrBNSB7b6J/QA9AT5uv4lAH8ArwSYDSkTdQun+hTvCOqP5Evfpt3d43jyzP0rAqwJHRROG/gcKxtYGLsXaRoNH/QgCBs+DooE3AH3/9v68/M/7gzrwO5L93r6avaj8xj2N/7HBj4KhAzbEe4Xihs8Ge4Q0wo0CdYEN/pc7bDlruVg55Hpeu6w8gbyWPKh91H8DP+9AXEGIQ+1F2sdniGqHhsWBBOoFREUewxSBWMEgQjRCrsImgRR/hj39/Lf7/rmCtsM2EXkM/XZ/5gGuRE+ItUydzknMLUbOATl8rTq1999zWLCDMdO3kv5jghIDgsRhRR5FuYRdQTp9w71S/pc/ykBFwG9BVIOVBRAFSsPlgeSBTIHLgdnBRcF2Ar6ErMQbwOb8Ifaosr2yGTT+t5Y5v7wUgY1IDMzdzcpLyEgaw3x+TXohdWPw9G8G8kE5ysEjhOBGGMbrB7NHQUSqvtB5jfeUOQ38JX81QbZDxEZHx/DHsUazxIuBzX+n/kK9B7vGO7K8GL2f/n+9Ivpz95S3QjkFuum8JP6wQv8HUInbSV/HxcZgQ8wADftl9rjzZPL09M14rrxTgFnDtMWsBzFH+IZ7Atc/Lzun+t08Rb2GPtrBEoSwR+5JIcd4g2D+ovqbOSi5NPnfe///GUKkg7PDs0Oogi3Ar0FdweEAIn/VgbiBVAFvRCzGQkYnBcpEiMD4+8U3aHgIud54HTacuG07b76SAzf/E/9rBTv87zTrOMv6inlR/beA4wJsBQ2DNL8HPib6pXZk9Djy/TN59qf7gsEdQ8jDJwFCP7j8Ajkk9503OPdxOfr91sIvRWmGxscux5eHTYPU/s97SnoyuZF5A7hDOmkBaIbex3wH9cmXilvLvY1yTOLLXEs6CeJIHMgxR53GN4UtxMjEskROBGxDl8NihBIFxUaXRnFHFAhrh+HGzwUMgjQ/7b7rPjb/JIK1Rf+HHEeZSBKHC0OQfuu6kPdjdXZ1fraMeW086oCdQ1tEgcSHwxMAv74HPEk6rbr5fMx8ljr9+p268ro8eYn4UHbIOBw3rjUWNSJ2dPadN/65sLmzeMn3zPbdN264VjnGvKL+f35T/3mAqIH0Q7uDcr55+rO5/zaN80CyY/KaNbb6ZPzm/VfAn8TBBvgGl0VEwvTA7cBKPu+9Lb4IQJ5DJQcjCSOGn8P7AvkCUYJ3gYm+VL0//uu/tUItRj4GaAX3x9aIkgdgRy5G4wZCB04HToW3BJpDFr9O/tZCEIIGwApBLUKYRBfHugoFSSMHWEaSheDHjwimhtrGggeKSK3IkQkPCU1JcsrEy3PKCElqB3uF7kazxYbDdwNeQ8VGFAeCB6JKC8tsimFLB8r5B3JGMcY/hNCFaoWOhP0FLMYeRlnFjINTAUNBvoKiA7+EPQJkADO+F7tqO6zAUoHNf1pBJAQhgYe9uHxS+817S/05/Y16aDexNZGze/OK9GsyuHMe9zd5LrpPfSu9nrsCuRL5t/qwue+4gLbLdNYzmrGYr4nv9/Im9EM2qjftOGB4/rcDMuwu8e3zbuJxnnXM+jf9fX3AvLn8MDpXN5g1gbUzdjC4ZPb0cnbxNXESMV7ztHdHu7X+Wb2+esp4ovZfdQxy23DhcFIwg7GGciq0rDhRd953pvogeMj3nbnTOFz1gjfzd852Z/h9+nX7QT3aPRs5iPo2/Wf90H0AQCzDg0THRGYDK0H/Aq1EpYMVwWSCT4JCQZlEgAjNygXMCU4+jLsKX0qQClcJW8neSR/ICcd0xaaH5E1TkPPS0xQc0hMPwg/+jlxKs8oyTLDMhM8tEtGSjNEN0dKOMEfeyOJIEIRohZWJ8E0UjkTMbQsxTINKhshqiZIKX0lGyLbLMcxEy6kLP4kJxsdG4EjHx8xHYEiOiHqGkYiYC4+LI0zAjZIKScgzRLr/cL28/s/+TP9rw3HGckmKzIjLystmDHbLNseiBjJEX8M8A9MBtn9JwTkD/oSAheBGY4VaRhAFSkKnARW/Lr14/Dj6qf1DvuD+sb4L/vZ/cr67+4r5JnqCvPQ8CLvffDK6DPtz+uw3VbX3dSJyn3HNcxS0ofa1+G85gbjtuOZ4k7S48WZzGrLWMYOzgzbEOdc9pP+O/gQ8xTqBtd/xMXBYMQUuVqx27Mhsi+9NdUO3o3ei+N24azfj+hD7dvrienR5KTdotVY0TnU49624lrhYuOg3XXWCNu+5k/x4fW+88zvjemi4JHSvsakzwreBt+64I/s+/YU/IIB+gMPBgkLmgr5+szrT+st9en0BOMt4Prqm/gsBS0KAgnK/xzwYuKP3UnZrtKH2CTyNgL+BDgRwRR1E0QTQgRi++H6i/2UBHsIcwSWAhcSPiBjJospHShEIzQdFROeBIv2jezO8OP8hAs8G5IjgyQGIVgdIxhWE3UTbRTJEOwJJQ8xIOEjPhLVAHz1dO267pvwvPS8/KQMKRikDAIKcRXLGc0gfyMfFhsKWQeeBpIE7gRUBwsFTgglGBMi6Ce7K8ciKRw0HfAXCxWYHYMcsxoNJXsp4SMpG8UOhRnTM902gzXjMrAh2RPiHXUs4S/yLewtLTIQM3M09DTDNpw7kTuqNsExyy2ULVQtMySoGpoWjA9/BnMGLxWMJOwmSi3yN48xcyZ/IXUUtv1/9Bj8bv3Q+hUEaQ+FFx8nqi9/KZYidRzTDvAB1/xe8EnYbM+226rhxOhD9TgDtxLmGhkfNhsnEwkMjgy7EFQK+AJGAQj/yvps9qjtjeMl5yb2gfox+uv77/nE9030e+927w72KPh+/DID8/2N+sD55euk5zH4tvuR9gb6tvD85KbpUuyk5qTgWODb2tPOTtBg1pfVBNL+0gDWwtNo03vaJeHn3ovYtM95z8rbvuSH6G7pFujb56jnJeDG2wLhgdzvzxnJ9sdixCW+ZLt7u0S53beuwVTOgdPt2Grhf+HI3l7jl9rTxsXGstpc5p3qi/I360Ph3+uJ+Lr0vu3t6UnepNKmzsDHRL/hvk7Lrtl/3BLi7e8Y+/P7tvNc60zh8tOi16rn2+3M8JvzGvFY6OvfEuDV4DnfWtsQ15nartn80nvUcN3C6LT0SgOeDEYLFwpQD3UTgwys/9Pydupu63T2tQJa/l734/vd/70GShSWG+QdXyAfGqoMJwHb+Wj0++4W7Uf13f97BckXrC9gO7g+zT+cQd892TJ3I6wS8gYNB7MOoBFAElIYrCApI5wm5jQ7OccuYSb0H1IUdxDoHX8neSYZJlQnsCacJZ4iOhplEnEWXh4EI0gp6C2/LawpYCZEKXElrBgdFBESiAltCLkQwRWSGCUfGSb+JAIrnjROLVglfSjZJAIWzw3kEy0cIx1MIVgowTLdQjtAgyzyIugcAhnFFisOUA74EDgNOg+cHPYrEDayPQQ9JzLZKFAk9BlaFcsUngJo+bsLZxtAGsMdJySJHIcXWhx1H8Ei/CH2GkQXYxIXCMz4m/S6+KruFO9w/TX/APvf/hUIgRW3IegjNB80FvgP3AwpDEQKLABU94n2Cv2u/8D0rOv35DXSJcgd0a7dAu6oBgQYYRH8AXkA+gL38F7kIueL2gbaeeqF7RbyhAFACZoFcQl1EH8OZwp/Bcj32+UK1r7GFsEtyZfSldkn6Cb6MgOMACr+rv+h+9P3uvr99/HlldCPx0XSyt/N3eXY+tmD1dXNK9Yz4v7gR+Ua7i/tDPBk+03/nfZi5bDands72snUaNaP4JnmWPJxBUAMrQnVCu4IggAr+dHtqOCV1RvPc9JQ2PHciej+8oXv9/DI/yEJ6Ak4C5wJVwJW+uf0/fNP9iv4O/f/+rUBdQm1E3cb9hm1EZoKMgBU+iL66+0I3hbWg85S0mjp7AFEENsWXRqaGAUQPAS8+zf6eviH8VbowuHZ3R7fneTb75n53fdR9Nf57/3v9GT0ZwDS+v7msNnR0PbXvueN8O37MgpaEC0PhgiqBUYStRnyFEQLR/4I8sDtvvXA+M7rwuBq3bjdWuQW7TvxDvNe/lIOhhRfHIUkCx84GEQSbwHG88LzO+oa3A7ipe1w8rr9vQA9+UICABbmHaQYrBPVDAL+gfZT+gz5LfRB68LhM+UU8P/8IQvuFYcedSNII0IkBCRpHvoR4/ym63/tFvZL91j4eQENCQEFVgLmBA8FewXDC4QOwQxfFvgkABycCMUD1Psc7CDlP+wn8xj3BQaqHRMotilcNjU+czWmLpwrgR+WEXsCk+vI44vyj//NBpgNsxGSF5YgySYtKpQpjCF3EkYHK/wi6xLmdunA51rxrvy7AToWESrdLjUlBBJa+yfocOZD5SXVkdD64d/xVANaExkNTgm9F2sd+hsxHn0aEw+y/5/5zPrp+NT5zv88Aaz78/8tEdMfvRwLE9sWdRvPD+gFmgM99IPfBOC47FbzpgfZHPAeCCjbMWAooiK5K6YqNiA6GDoLifmZ72j3EvkA8aj3vQFxBvQFXPfx8tEEHxO0HwQrYSBMD7sL2ACZ7I3nies/5pPjXuxk9YD9LQfXDi0VABkVGFATYQ2gAn/0yOjL3zvbP9lM3U3kzORF7QD+uwFdCVQcohzJEfQSzxKOCA0EOgST9YPleeG85ontcPQM90frWOjt9o3/h/rv+rL9jgE8DegWvxbyCqH8++1g4Wblo/Az7kXrOfbJAMMDYxCIGVASDxJxFP3/cuao4Jvbh9KT1iXgVuU38C35pfmu/qoE1wmiD5YN7AqYDeIKOANY+Yvu9eft5SLj3+Xf6qf0ihPRKVAo9B2FEoIFcvUS4PTOx8frwhjL4+sXDMEPXRTLILUZCxB/F7kRav7S+d/04eEp2lrgau9nCNoNxw/6HE4hsB6JHSsZsxFzCu375euy4I/XSs87zXLZuOT66vf9IRLsEiML8gZQAXMFhAlJ+ljuh+SJ2z3gy94e3Tnd79K40u/lyvF968TytwaGEEgalh0tC+//8f2Z7WLmxOvX6iTtyPQU/EIM9hkZG6geHR5MGZoWWg6YAHjzNeqb6NnrePAz8LzqzOzZ8v70Iv08GHsneR67HowhOhAfCfoZ2yDRGBsOk/pa5g7uN/xUAFAPxRuQDB0BNA9WCxD+LglWDbECTAFq/+X7n/79/D/x4ehw6rDw0vfb+9L8KwKgBx0CDP1e+wz+QghN//fpsub449HZtN1w59/syvq/A7UAGv+MAIQMNBusHscgcRqX/QbmXurh+wUNXxVSENoLdxJWGmMcjB/bIAkUevwW5nLc6dvt3dPoj/1GDGkO9hgfJsMephFME0oTFQeq9unnneaJ7gzy2/Oq8XTzcQVCEL0PRBb4GrsRDQknCEoE9fyJ90Py+usM4H3IpMZc4bj1hAczG4ofpB2qGzYbnCZQKVsR7ft/8s3dz9oY7CTvAOnb7Vz6XP5IB6oZTiH+IYEjjhyqEJv/R+4v6J/qEueh4BbpIPkLBJASPic1M9c0jzuPPgoxsCmQKu4egw3S/O3nCOFc45nm5/02FIMRAAx/DdMSJRuyIvogWxQbBpvvk+SX9/4GXvyN9+H4Ley+7Ov5N/sfAL0Ep/J74vfkjeSH4031bQYABFQByQTZ/VT6dww+GuIV+hCmC8kCpAEpCG0LSAqSC+YREQ+h/QDuXvAC/SwEbwaCB54GnAFYCOIV4hU4EJILngmoDq4R8BDmCisCuwYFDg0PNBwTKQAeEw4NBkv9evep+9wAmAc8Dx0QuQ32DZgOOAwlDWMQ0RJGDpgB5/qb+gb3xvV6+EP07+t/7DHsk+Xz5x7vDPkbDoMaBxGqDsUVqg9fA1P2M+xN6DPpk+x/7Krqh+qd9OoAuwm9FfIcoBllFZgaoB63HaIYZwto9qDe89WR1+HVpuAK7rTseuvQ8SsCKxHRFRcVcxY8FzwKtvEg5Wjn+t9/1bLYl92s3MruKwysFaAWmB3DIDggTBy3B2Ttf96L1/zSAtFW0WbWYuRy8P31oAMXC54DAgnVDiv8bO0O6FzaYNjL33LcXN3X5gLwgfUv9UYByQ4CB2EAbvrR6S3tePs/9/HyFPB34kPieOvt5WzhuvKqD1gY6g0rCbMNDQwZBN3/qfn+7dn01QqWDAIQZx61GAUJ/AFa+mj1J/OJ72rzke/h3zXfVORB45Ht9fGT6Zvrk/Wd/WEKZyACKtsbZQli9t3gkd8C77Tv+ucp6GbpkecQ6B7yYv7yBb0JGw2BEBMN0QpIDtkPKw/DDe4EWwFZClgJvQbBDrULNAQlDm8X9BTBFSEYsRTuERsMYwCp/pQC3fxq9xr5GP4jBtkLOBjqJg0ppCndLDcovR+gIwgrhSbyFwz/5eWg3XXdJ+SH7gT3SAruGnkbER/4KfAlsxhpD+QAqu8C6v7m9d2D28DfpOFa5iT1UAa5DgURZRO7ElgOwwqUCJP+GPCF6RTiGtgQ1q7epe6l/t4QgR0AHhUeIx5CHMcYyQ8fA4v8Q/si+uP+IQm1DN4GiAPVAMD6gACMC04NEQ9vCZH00+eu6ALuLfEC8bj35/v+9nD9ThFOHGkY4BAJDXcCyO5S53jvrvL16xLrJPYuAEwFewovDqYUyRvwGBkORgPz93/uBO9B7vHlJeRQ5RTkLeuH9of3xPioB+wQPBE2GccnMSr+GDYIo+7+0HnTSeM97hMFfxmkHNMghye7JeAg9hqQEJYD+fX+6BbnT/Qo+pvyJPO2/Ov/hALkC78SohVMF5YZXRolGHcWTBBjBu/6bOew2QTeQeHX4AbujfVa7wzz+/es9BLwYPJ+/RMEpgYpBMb9KPzp9ffq+uGF143Vndx23jXj9e1m+JIAIQS9DOYO3f8W98z1Zu335z3l/udN+jgLngw+CaIR6BU4EQIXsh7gHfIe+B88HLcVvweu+azvDOrx6aPsoe+J8yv9GwvqF3EjySa7GHcMBQ69DXEF+gBICCkQjBAJFFoa4hSWAu33qADWAb74UfsJCtMRHQl7B0wFn+/C4eHkfeYM77L9FQCrAy8XKR86Et4ISgdW/67wZOiy3pvUct6B8O37BQmIDaoFRgNKA87/Lfq67Fjq0vqh/gL0BvcJAaf+wPwa/9n+dwhUHUwqAisrKHEf7gvZ9rrpJdaaxIXI1c6ZzTfgsv42DAgfbyz8IPAX8hcLEIwG3APK+xLv1enK5N/eL+d77mDy6ALZFcsVAA/4FTohiSL0HuogIxfqBCj5vvGV8cbwS+xD9W0Avv5xDV4mdRy/AKP48/KB6ZHsuvOH+F8GihaMGCsLHPe873DySfq9CK4P2xOYIFAlYR9/IB8gBxWiC17/L+QY0wbcje7G+D//MAtYCyMEOAixCmcHQAuOC4YAT/wJBXkM2AonB2z9aOwA5WLh+tU1zoHUM+Tx7VjlZuDf6zP03/So6/HiO+xT+/H+/f48BZQDQfoQ+Gzuj9lJ2tXrsO7R6Mbjvurt/t4FXPrR7ZXomeWk5KbpEvRL/x8KLRIpF30cwxc4EoUVaRLLC2MHYwVMBpIIMBCgGAAcCR7TGysOpf77/iEGsP2s9Wz+5gOEBEoM4Au9BZAVaSjXJO4jri1SL/4saywIJDITsv6X6FDbOdew2DHm8fkADSMgSCsjK9sqPiNIC9v7uPtN7zPhe+nn9lb4XPN086j2VPYr/G8HrQimDmccIRZQAwT2qupD4IXcR9t902zQkd037nT9nhLFIugpvTF3LKwXQgbM/ysBfP199ALv4+5D9u32l+fA31TjmeNo6RrwavGA/qgS7BMHAnz49fYG7uvr1/Cj9QL/vv4m+Uv+xQBL9yD0Evy2++n5+/yR7sLdwOmL+vP5GwALEr8XExgHGHsLJwFzAZH/1/5w/pX4m/+1B1j3ReM93XbhM+wv8U/zVANSErcXWh2/ETP6CPEW61ztvQAABw8PMy5WN90q+i1YLMEbpBH4Al7jH9B31eXfyuab7gLw3ety9yUFJwXLBS0Q0x2/IIoWXxBvFyckzyfVFkn/VvAg5jHiqOWj5bLpuvbf8wrh49Ue2ons8gAjDbsQYxITGrsffyKwHssRDw+MCxj23etL8VTpHOpQAYYMBQtCElYccRTz/u3uruXZ5NHu5fel+4IDhhGgHGchaSUrLQA2QjZAMMEsISkVJFwfnBg4DgAFwP3784nqCOFu3SLwywvoGqYm7jAEMBksUChMHuoRihLZHlAdQhYVHl8dnA7qCBsFru8a3OXnUfgc86zvFvt1A/wCuwdfCjf/Cv2kBkAKYxDVFEoV4h6FIC8XIxVWD4wBtPoY9pPsK+pY7HTkLdlM2ZniaOs3733tz+sn8bj20Ph9AfYSjB4+GugW9hSzCuYDCv6L7/rpTe+h4WTTbuN47YvV9MPZx5W/Vr6+2WTt0vaSCEIWyxvFGy8WDxNxDhMDKfh76nbg5d/h1pfIsMnCz93JsMYY0Y/dPeU58IH5U/o2AVAPjBtzG38RWBAFDpv9uO6F6l7qXO5o9JftPdu+zFLFuMdK1xLmf+Up44PtM/Zs9Cr/gRJCEgcN8AMK8TX2BA+DFrkPjBC7EhsNFwff/QDr7dZazYXIbcI9wp7KxtHI3Df40QdZBb0QRh+cIN0fJx+qHBcXDQwJAsL4qO1u6+XnzdUSzovUrNUx3I3wCQTeArz0KfitA3cIphOQG78atyFxI2cW1RWiIDMehROaDxkFxvFJ8ZH4O/Hx7AD0dvcm+x0BvvuB9yD/3gtjG4cllC0tOZ45mjGBNjU69iw4JJYjuRuGE70SoAtk+U/sn+t47M7uGPpbADn0o+4rBRMWrhhEKvI22zQbM7gtHyiwJF8gIRtpFiMNogAt+hr7ofhF6NHZ89h13Gzhl+p2+/wRvSLTLIU1ZjTsKykrbyryIbAa3hLBBx8Bsv90/qn5k/Wu8d/mpOS07dXy1/7oES8RewBzA78UPhcLGX0i1yEJHFIZ/BdWGwsemBtMGtcW5gmf+VLs9eK84AzjtObX7Fby3/jyAfIHKQ5bFJIWWh5MJG8fwx2BHOgT9g0tC8r6bufn5TniRda41vzVmslGzrbhyulc83EMRBppEEwPih/VIYUZyxvFF28KFQVL/93vleeJ6PPe/NFu0MLQwNTZ4BDjot9a53/vhfPb/0gKogklD0AUrBIVGQAaPhG5DewGlfIx4vrjyON75HD1Vv64+XL7BvgM6xDtpfeu9Yv18gNEBhTw1+uqCBscfxsnGnkWGw5ABqf9CPPQ7gL3TfaB5A7bldvT2WzZtNs75Ar2SgXRDdkUPhnJG+gcDxsJGisZHxF3Bfv7FO434RrgwOCJ33TmtO1D51Lb69md3aLhNfRrCHUOuRdxG68EwvNtAqAL/gKMAIf+dPKJ5kXjR+PZ7OoGtxewE/gOmAuqBP/94fmh/xELAhCqDUQGZv5+/rkFrQV3BScQUhawEh8QjA27Avf49fRe8TXvPfcXB0YG1P7iBtcKAv+4/VoOexHgEYwZjg4pC0IhwyfbGMcWxxfBChL+AO8x4EvlYPLR7BTiQepy+rsCnAUwDR0ZNiFjIBsX4BE4DZABdvyL/aP98f/t+1HwNerl5m7lQe3j+oQFIwr6DqwSzQrt/GTyzOHN0znhVPih/6ICCQdzA9L+rQcPDSr+f/f1++ftLd4n37DnAPq1CB7+PezZ7ifwAt8/3IHsUvXQ/UwLRAplCG0UpBsxHI4bHxYfD4IEavXK7e/utu3R6nTt4+3h6iL1dP3t9FzzNfbf7t33sxlnJlAWeQ4pAsroL+xCBcUH3gdUGCcSK/Vm4X3ecuYI9n0FxwL+AVsQ6g8RCwkYFR+HGCEUlAjh8Hfiz95a2Jvc+fF7ApAEjAZxCef+6+yV4RbkZOqL52jt9/jl7wzknePj1onP1eb9+tMGQhVvEgMJPgsAEmMTphHLEUYD3+K40oPS8tLp4+n61QRKCKwK9gcdAH79NA0LI8ElMR+HHBseBCU1KHUhJRjwEkQMmgR6+jHyn/nFAisITBucMW83czV1N+U1jin2Fc8CBP76DVwfvR5dEB0DtQexFMUZ7iLVLEwtAibiFdEBK/RB+nkGWQXuA5IDLgEuBw8RHxj0JZQ12y9lIDYa7g1g/8UCjgdZA+YGnA4yEnkS0wrsArsE+gC2+Qz+eQCN/HcEAhGWDYQKswaQATYXFyqKGOQDbvs59BD1RfSs/iMTRAa47Qjmjdq0z5ndmfn0DRca/h4jIFIdDxPDDF0OmAeT9M/jMeBy5tXv0/ff8vPngeSB2VLKqs2u3zHoLet0+QkJkhCvCwcK1Q9zAGjbPcctxT/DDtGJ793/svY/85IAcwhKDPoSNAkk+nLwXNrjyTHQXNrT4SLoM+T+5Cn1h/xq/W8IwxPPFEYOnAnVBEv75+h508/N8daV3UPg5+ed74n0IPmu/+IHmgdOA/AE+AbYBD39GvOJ8Mr15f/6DsUPcP3G7p3odOjQ8jYGHxXDEaAKXwn79szlpvDT9BjwVf/kDDQJ0QbNCGEJUA1jFNkTCQtjBTQB2fi08zn0APksALcCqvlL7GDiANnA31TzKPxjA88OuxMREPwBO+/G4VbcLeBm63EA0RRtDlkFjBa5HDgS1xr6HBcCQ+3+5X3ZoNSX7H8HDRhxLpwztydnKMkqAiPRI7kmYRzDEgsNqgcyADf1BvXI/qYD1QgxFkAe1Rz2Hx0mbyjwKDgpgyNGFycOuwgjAr75HvSL+XsB2AegEoEJi/RJ/K0HOgQfFgIsER/4DyMM1/IA3lbrBPOo5nnltumB63L49ggAFfYd3x6HFhcPzwdJ+vHo8doO1B/SWtMA067caOu+6rzqQ/rTCSkR3RqgH10Y8BRGEd/5neAQ1l7OxM3p3Dn1yPmj7EX0bwC6+2MB9g1/A8DzxOyf3ZfTP+Ep8fH7xxBhGNoKPAhpCRb+evoK/1QAHwAS/vv6HvQK9+ACrP6s9jv52fis73bql/IY/ST/o/+cBPYGYQ76GysX1wbTAe/+5/etAtcXlBK2/BbzevCj6Y/1tRMGHTIWihFlCHz7rvbf/KwGmg7sEqgPXQveDuIWAB34IB8lpB42EBsGoffx3fLOR9ka6+H8jg7iFs8UnhILEH0HIwaIDjgUmhBzCE4FWPm+4GbZvOFM4/XpT/o8BQ0JDQ0hE44XABspHn0a5g8PAmrrmdkx2wDfIuXS9l8D5gUlBrEFTAYdCfYN/BDmDMUAuvgm+DvvauKq4Pjc6c09zQzbReKo6OH1eQf+E8UfpCsjKkYiQiJhHGkH3/Go3onRDNgx6+P1hfU/7vHvM/wTCvYdxR7sEFoQ2Aih9Znw9fAz6kHpKe7G9JQCHRNcFtUUzxvNG7sTvxBSDrcF9fdJ6f7rEv99CqYJ5AgyC+oNvxU4FcsE+/pT/zwC/gdpE0AUSA+kB7b0TerFAIYTuwxYEoUU5fwr9CsBTgDr/IEH6/5N62TtJO1e5675DxO1Gi8alhtAGCEN0wf6CwIKKwjoCjgBo/mq+6jzl+T+4qbwjfq2+yr7h/n1/rUL5Aw4ETEf6hZSB5wFR/j+3cLTldDP0CDoXv76Cm0WOBDqB94PRhjqF2kUogse/M/oENhB0yXWIN6651LxXwD2CHsGAAbsCEYMbxErEsUGTfJ032DSwMpgzdPU2dvv5yD1zv/RDL8bqiCHFWsLfQpbDG8QOg6GBGz60eto2LbWjeto79nlS+h/4h7dkfMJEfQWMhc+HuQN2fZ++KH1JOlH7uX31fbf+CD8Gvij/OgLnhRSGNkcCxcNDXEJ6AG09o3ugelJ6RzwBvG26FrtFP/LCPQIBQ6aFeoczR+sGfYb+BzeCVztk9+o6dDzjflhCjwO3/Xb8l0LkAzqAQAJBQ6eC1oPSAxCA6wIjg4JCL8SMyp1JlYTWQkyARsEbQ+gBdX53gLPACDztvhQAW8E7g3sDh0Qih1YG2sHwQLgD0QdtyJhGpgWcxouDSv5ifa2+Xrv7/CtBcUR4hQpFQka3R5vHdMjSCdzH/gWdQqf867fgeTj8yT8TAvqGd0aCBuzGv4VoBqLIzod4g+CBIf6Je0S2jfYHuSR6HjtJPwVDmsaSh/RGgUSpBJSFfoOngLr+Abwh+C01qDVZtRk1L7eWu07/ewEZPgv9KH47/Ww+m0ELghQBcT/9fjV7wLrS+pH5ivhR98p4f7mFOuN8DP+VgjRCKIJuQr6BhsA2/hQ6/7a9NPR0E7OKdSk2zPb+tvN4EnpYvzBFcEdJxLwD5AQ/AHx9UXj1cQhwAjPTM6Bz/HoCPYx7iT2EQKn+xEEcRixE6wHPgaD8zvWNdvj7EntxvMlAA8AMfs/+2b5bPOn9gkDew4hE7MNkAHI8i3yDwI6EhscShJ3AQ8ANgPWBNcHAAvFENEUYRGKEpgYXw1y9g7y0v+GBBEP8CkhIm8IBQ0yEbcG3go2GmUbfRpCG+oNhgj+E6wXOhayHHEZFQsNA1P95fk+A9wSMRsrHgAcVhJzA/31R/Rq/PgEQguuD9MUBhk6GmUgCiQZG28NrP4W89frK93vz4XQJ9aR20Hjqvl3DRkD4/viBPoDiAMjEOYWRBSKELz7ruDG2w7gDt314Xjyg/uN/Hz+VwacEM8PShGDHVYcPBB3Chb+leca4PHhn9s53THxggT8CSUQpBfyHIUoSC+gJ+wgCyLZGlAMQffh2s/QI+Ll977/ggUVCu4I5BGDJCcwcy2OKt0nCBsdDgkFngF9AVb6svUC+j/95/r9+0gGExFSFPgSQhHND3UO1P835jXa8dpa3KHk1P72FVYUaRExGfYciheKEjoRRg5/DOYIDPk35CfZVNf83c3iUOZT+AABJ/Sf9gIL/BJOErkWnBgpFWcR8Aiy9kvggdU11OfVpNyq4qXtevzuBnEPRhaOFpIUKRU2DYH+rvEA5wjfgdlg1wLcDuZB7hbxxvfsCaIYgRjiEfAPgw8JBmr3HN6ZyCfP2dd31qjjLAQbFE4OnBaOI9sfmBlEFf4MvQdGAZXweePz46LkxudS8Vr3Dv3VA3sEMgYXETQXUhJCDBEDP/NB5JfZUNa43XLpzP+IGr8cGxWyHPgdlhYPF6wQ8AEA+EHztOU/0jHMh85H0i3cOfCKCJAZyx7gH8kj9iQLH6IY+BP8DHcD8/T63DXJXsjLz1TUk+Cn9joCDwVWC1oP3BCqFOQR7AYx/lHzL+Fa1hraut264JXrRfR2/y0RIxUJFbUfgSAvFWUQMAmp+ajvWusl4o/TI9NH4HvoS/XLEbYj6CB/JPYpmiNpHZgcyRn6E1ILXPmD5XLfI+Rg6WbzjAPeDlAVbR59JHslTidgJggi3R4VG94RQAMt8ljthfiYAdUJlBGmFbAbtB0vGTEY3hXkDAMJzwhdC5QGAPFQ4Y3lP+/f9yMNvyKDIo4b6hxEFvYI8gfRBcz6KfLh5qrVbM4U1r7e0+v8AVsPtxIjGeYb5BVQDK0AFvde88Dxf+5c55Xextw74U3ojfXDBewPDRgCGlQQ5AmKBLL0dOeZ6QjpBNwW18bZm9cc4BD3jBHTJCslbSLkID4W4AuKB3sA1/QQ7tvlk9bPzGDM19Gg2C/gHOuh+IwPayIhI80feR8CF1gLdQveBMLyGujz5QrhBt1F5crvxvlzDfYeqhtfFuYbBBhnEYMR3g5zCnEDAPfM5ynak9aV4Snx0QNnFNMY3RoEH8ce8hmWFV0Q6AZm++nv4eim55niCN7N5KPvDPzTCjIUkBnoHpIimCDXGogXaxNrCgT+i+x9283Y2d/z5r7zGwSIDcET6hc2FG0QphCMDtUJ2ACJ8dPjVt/44k7jGuOF8bUDLgsdEyMbbxYdEIMLfP7v8+nxwvAI7ZvmEOBM3h7mxu7v9MMCmhbJJLIixReQD44BAPXl8Unott4E5Dvr6e1u8u/7xwtCGPQbnBkxF64WphKUDDIH1f0U9nz3L/iH85nvDO89+G0LYRZEHC0kESMxHNkWRgq0+lz30Pnb94n1NfLl7y/5gQmMGIkiGSRgJEQmDSLHGK8OwQYdBa8FPgIU82rh2d/z6bb0aQS1FHcaKxxtH44eLRhOD5gIyPum63nm1eUE66z04/TQ7xj4jggJCa8K9hvdHxMXHRi7DqrzTepu8XL2XP0M+5nkstb64njxWvtEBbERcSHHJdsddRMpBUX36/XZ/h8DdQHyANf9M/ds+YD+U/b99gUIaQuUAwkM/BaeDXMFCwZe/pv4L/xL9n3hvtEn2czq0vnZC4oYwxcyECUHFv/d/X0G7A+vDhEFfP1o9QTkMdcO2o/dxuBF8UwCBQV7BWcL1QxMCIYK9g/sCUYAKPfE6unn6/Dt8lTsN+kl6xD1AQLyAvf0f+wG7nTxp/pfBfwJIwiF/87pCtpO5p/3wwL8GUAiBRCEDsMRrQJ6/h8GAP+u89XuIORB2K7YCOPX7qsAhxdEH2kc5BsnFl8MrAQRBmUN0wwwBuf/Dvh/8O/u8/Mo/K0DrgxKF2cSZwB++SD14e2y9a8CgP838Rjh79bZ4SDzswE+IxA1jCPTHGkZLf476zHxT/Ni8br62gEK+Lbr7exY+KYCsQZICXsUniTLKccnOCTmHP4Ttwq+/zX2au4g6XDmQ+bd7x0AtQrmE2ccFxVSB2b+1fu5C3skOCGSETQVxw738QrcoN1m5vnrTfrJC2UT/hPeFnsiHys4JPgbrBrcE0YK/f0G5OnV2d/R5C3n9/UpBugOyRRAF2EUfw8ZC78Naw86C94HogEW8n/hzdwY3Lbe5eij9lABuwEyA7MOqhbJFrkTqg/8CGz7butD4ATgEOYk65X19gLYCIwI5geYBFkCHwUNB38JoAizBAMB/vQY4NXVwNjl2BzgyPTLCoUXRBktFS0RQg3XB4YGtQPv9VbeYtL24NHtwv0bGY4bwQ+WDFICsPRw8df4ngY8DkYJNfwI6WzZ893v6QbzNAVSGZAesBveFVYKyQazDe4TtQ+OBeH93fCu4CvWI9Ry3nvt4/gZBbsQWxMZENUJEwFGARcMXQ/DCF8C/fao6+nugfeL+rcEtQ7TB4QBzQOh/44BAhIJF7sOQApQALDxBvLr8bbwYv0rDBUY/h3DHWUdvxk0EdcNIRQfE28J3AYuAcTsANqJ1PbUWNiP4FzuePqgAckQACj0LNcgXB3gGXsIGPNu4fHUntTA13TYQ+EQ8c73k/w2DVAZiR3NH3EYMg9ACRD53+FK08/O189gzwzQctgA7HMFjhUrHWEfih3uGZYURA8lCQD5UOHG1TfWgdUt11zk9/Hz/hsWOifmJTEj4iTVIYMbyRmMFbUJavcp5YHggeWy7Jn1f/oi/qYJwxZQHvQhrh+FGZQXVBbPCJ3wBuhm8fn1IPucCUwXBhsjHKobVg0+A4gMvQ+vCCwGnAEc8qPoXPP8AnUJtwxxFI4cyx00G7sVig1xDO4RWBDwBdX6HOnA2pfZwN2o66oFZxYwE6ASlhXRDNoIjBMlEjIHMgaUBD/8VPKH43TdyOZP7O32ng0XGGMX1RrRGCUOiAYRAHD2hfQY+8r2DN+HyyPOddiT3hLt7/8yDMEZbyAtHuQdEx3gFQUOxwXz953njdr2z4nK4dCZ2wLiwOtD+wsKvxi5HHcVExIJDFb+hfEM4gLPrMlQ0M3QqNw59WL5OfcPCMkWOBfJFg8WhQ/JBkv7Vuas0gDPCNW80kXVXOsW94X2zQOqEFIVFR1CHAcUYxBxCtL96+kc2JvYHN/b5aX19AAPA3MH/AsXDqoSBBEtCQkJEwptA6n74+1O3SXYVNeD3Lr0XRHwH28j4SSgJIcehRgfETH/l/JW8i3oUtfE1ATaEtyu5NT6IRDyF5oZuRjsER8QIxgVGL8MRAXZ+OHjFtyi3GjZXuFa8E/15fkNBc8NWhoVJqogYxjoFeQGrvHM54fpj+6+8bsC8BzTJ3UkOiSQJMsZAhC7FEIbYRHDB+YI7f568If1LARMC7MVpiUGKvwnbSpgLq4vWi8VLL0k/B57GKIJQ/ZY6WDnXO4U/hMLDxAtFLUXtCCuKhUmKR+gI6QlqiMTHeoKgfWN7Nftn+8K9v37qACmC/YVtxnwHV4fBxegDLECmfBW2t3P39M72QDhvPKT/ywDHQwLFzgbeRojGRkYZxKEBtD5/up311DNBM5c0krYYNkc1IvVT+p9C6oifyJxHLIbSBOmBAz2tN/f1RLfAtz+2gr0+gRV/gr95/9N/ZIFwxN9EJwDN/7t9ZnjldZS1HLVd9pQ6Lbym/BY7tP27AGkCOIT4B7BHWsVsQ4TBHbyd+Oo3FDcP+L57Wr9SgpWEnsc4SPXITMc2hDcA6ADuQemACnubuE74QzmaPgZD9cTjhTFGzMd/hvsHE4aVhLYBpn5Guo13D3cM+kC94wJqhteHBkYUBiQFdEVfxmmFzYXtxNUAxrzXOyb76f4tQOECCUIHwuYC7UHHQaMCtcOrhHJFBkRLgoo/azm4dd513DaieKH/FIOYQmBCOIHDP3x+SEALgXLBasB7fuy7qDcptff2xzdf+J56vnosOfd8c73zvdi/6YROCJeG4YLPAiT/rzqWuDb11jNx9D439PwCwYxFuYWLxZCG1QafxWsEUgIBPrZ6XLcuN7x5vfoQ/SBA1QHRAwTFnkYmBiYHMMaOhHmCFb9NeyP5aPrFPCB8WL0CPRR9rsAAA04FHEW/hr6IYEbsw93DQUHn/gp8efrL9/b2kfiwOpW+PYHTBDwFi0egR9MHFgVaQmh+evll9hO19ffReyN9ZgC5A1EDogLMgxjCIIBPATHDTANlABu8xjpFuFk4EXofPXmAWUFNALcAYYEBwlYDwUNjAMC/04BbQQPAtL7svYA9Rr4swDmC8MSgxXoEvgE0/ib9lT2UfU59xD39/EA8d3yyvJq9379wQGkC64SLgxQBRcEAv759+35Cv+cAzgIYwwrEPQRsQ5ACxcJ7ACL9nvpFt7p5eH1i/+xCOYSHRVIEhsRQAwfAt/4pfL87mzy4ADwCzwM1RGBF3kUqhS5EmcGofqD9FLrEuOb4ZvcZNid40n46ATuCDILgw/iFU4VihBAEI4PYwqiAvnzgeFD0UTIrsox0MvVaOJa8cb2ZPZq+s787fkE+h7+AQB4/l70meTv3kXlK/Be+20A8ftB9NfrXOcU7Uvxru/386f++AjwEDwOdwH793/0WPDd8nMFwRkPI6Ikmh4+G2MgISPsIe4k0SgnJXUhYSD2GccUzxpWIbQefx9MKAAo2R9SHlIcpBbNFxsc+BkTFm0WCRh3GZohqiiJJ6wnDCnTJfAgqhb+BD/zcOml7uv+WAzVGDMm0SZtIIwdqBR3ASLwHuVQ3vHgsuxe+nsE6gY8B4oLWAv2B1IJswxWD28Pdwh5BFcEIP689iLvn+Ld2LLTts41zd/RyN037CT4IQFCAen6HPdY9KzxJ/Ks9h7+JQfkDk4P8gdo+/PsMehH6ovijdnT21Tipueq7onz1/Cj75v0CvFi6mjsyuy66A7oEuds5EXmMe0v+mkQSCG/GnkPPgyV/XvqaOZO5lzfM93h5KzoBOgt7H/xCPmQDJ4gkCBdGZwTIQQK/EQGjAoyCREOZQ8tD7EUYRHcBcL/Jv0Y+7z54/ge/agGGxKDHFwdkBd/EssLkgAI9XLqTuBa4cbu7/+kE9UhGyHHGlIU5AueBHr9CvKo7Aj6rAz8EtsWHRkjExsNKQfK/H31S/EK6wDuEv9bDy0V9BMjE+QT1REXC5wAuPgr9+X5cP6WBIoHWQLE/N/8IP3h+CD3Sfs6AagI5hWYHtMdDR1eHfAalg/X93njDOEO50fwYPkg9+HwxvWzAiUM7BDBDtECEvKw5YXi193t0pPMasxozGLPgdox543wIPqOA6oE/vaB4d3Ux9P81aLavuQ97WjysPeN+GL0L+474/rUk84IzXHIc8kv1SvktvrLFxsieRuKFxkTVgeZ+rbx3+um7p/+uRJ1G6YaCB9tH6QYzRYdFLcNdw1hEkwX0RpfGysaQhl7F8cS1wkM/bDxcvN6/vAKJRkKIFwhVCUGJ8UiGRzREe4BdPY5+QkF+gwXDb8KYQu5D+YVyxVAD2UHGwJVAPv8aPlN+ov5IPnM/Mz2uOaH4/7r7+3Q75v06/IQ8XDxLe4G7in08/lpAQ0Lhg9SDpgKqgBy8mboGOEl28/ctOTX7rL4CwOoCEoEzPty8zPtHO7G9PX7dP+5ADAGMAsCCYgFdv2675fj2dVmzKbTIuWN+bES7iPFJDEgNhdlBiD4FOxM3Xfbwul89YX6TAW9EJ4TFw8HB9b/XvQr43/eS+c178b+ohawH8cfYSQlIJQPdv8/9e3vzPIA/8MQQCG9J/Aj9CAzIYccnhO3Cb7+0/aZ9FH0vvklBNUM1xI2ElgJqAVxBwkIjg4vGeggcyfwKZgmjiLFG54PqASKAt4L5BktHdsWBxYRF6ALNAO9EQsimiYTMGk4UDNlLJQisBsGIG8cawOF7xb+FRbHCqoZPT/XMQwqeTczI7EAExh/HbcBRClvOw0ZlB3hNNcnXxgnHDYG9dzz28zzmfc3+7AYNS/XJIcZEyKcJJYCp/vuB3rvbOvVBW0OQ/dN9D/uQ9TrzhTZld0Y2J3dZucS7r7rzvZbA+37CQH0B4f4m+mw5/PjVN0O2e3Z69tg2UPctvKB7+PgaOg727TB2cT82fjcFuVT/DwEjgQnCSUN4gh7BScJvwoVCgIIWQmUBMj6JPdi8innVtxy3bLZWteq5cTuk/QLAZAD3gEpDQQTsw0tEi8TdQ7yD8cM/gF/93Dtyt8U3QrmsPFs8lzo/vGX/Jf13/c//OPuKexk/oIEgQPZD4YMuwUXDHkFRfxB+lr1uOmq4fPZN9UtzoHKptT14GDp4+Pf4qTk4eEc71r5pOr599MYjBTVELUWgQjl/2r5YN/tzVzInMdK0WbXWOKL+oP+7/GH8EHnfdms2rLeBt996doDhxaIFyUR7BN3D20FggecAhL+5fKH8pPzK9qo2fPnTNfj237+ofjE+rUPp/s38wr7QfRJ6XryRAF5Ch0kGTE4JMUiVieeF10EXQGo87roswOtCIwQuxwyDRj+q/879hL4UAlAB5Yayx29EdEcxSYjFschNSqgEYwNohC1DBEDjgB29c7oruwY/nUO8hW/IeIoLR4VDgsHAwIFBHUMvQiqFOMx5CuFJ644BjA+G9cY6gTI76f97/2Z+tMICRGtA6IExwsTBqwLbyjXL2Unoiu3I8EjphvbF3cKpge9Em0RMg1UBC4MfwAO4CfoqADsBO4PQhtSF5QJWwV/AJP06/IU+mT8Ag2cIKgiTB48GOIVaQeZ7bLeWu9747bg1P/d+/wGrwU39RMCCwKAAc0J6Aj0A78AqAZSAyTwN/99Acb6PhW1AycDpAq08ybwDOx06i3pZPP6AZAIpBAZHFoXHxE4EPX5uQP8Ce3+jhIEGs0PEw6YEaYIUfyOAdoBVvtAAM0AbQP8ADP4m/nE9x70APis/Evrtuuf+674/f0Q46Hj3/FQ3pXiT/s0CpX86gp1EuX1n/Tb+frZKeYA8/HruPwVA4n4e+yH7GzRAM9z0ErEfc0l3HDgYuYC5KTZOdrx48jlFu8nBI/7UgBCBrzyEujG68Dn9eUS6pfmMd546EfkutgA4b7etuEK7BD6FQA//U/8l/RH4vzbHuGw4ZXce+Tx9+YDxw7XCiUF3fh76jvqlevZ6Ofrf/Ex7Dv5tv5u9lb+cQtKCScKlBIDCjn80+3p5DPXoNOy3hzo5/9cFpwYDw9nBt36TfMv9+Py8++h+Wz5IPsRBvwPnhrPG/4V4hk+IpIZKxhvG/4Njfzf+l7wid0C8un6mfjgCU4PXwxUC1IEtQJbDUYX8CeaMRA1iTGcLOU1/Cu9GpILHPvA/+4MGQpjGG8qmhk+FkgX3gF9BrIWxRN/HX8x0y6UJVQrkCA+GpwglhmWFnUTtQW6/Fr7HQIHBlkC9g+wGr8dSCE8F2sKAPuZ70/zbu2659f1BQx3G04iyyzfMKAojBrmBoHrP9vJ0wDTTeRH91cDTgexBTP+DwCmBbj+Kv0wA/wBMAHZ/NL1tvog+i/6fwimD5gMbxa/GjIP3gda/u32L/Fu+cEM4BfwINMeQBKcENUPdwGu+4/8wv6oCUobsiRtK5Q0jy6wJIogPBJXAgAEewHqBvIUEyMrKlgitCTDKegptiy/KV4gAhqOErET/gwyBX8KhAhhBPQHAgycDwQZohc8FF0Qfwbj+mLzdP1jD1oalBXiDlIJqPUk7FztR+jt5ynxo/4RBa4MiheuD+X8ge1Q4OnTrtF92mLfVuLl7hz4ieZ328Tk+t9J28/eotL00E7b9dwC6IfvQe0M7xbrsubt8a704e7Z6E7bDtgG1qDI28Xb0tHdAOK+4TXVss7C1S3VEM4ay4HQR9d34qTo8e2d+hUBGvFK2dHTMck1wbTE18Ubz3vg8eZs5BLoevFH/Ef9YPgv9I3rJOkI5cDdk9eRz0XR/Nm24FToVvKN9MTz+fVc+rb7ZvVw9T4FhRFpD6QF9fP66tvtl+4i7/n2vwVMGFwdwxI4FOgdihncBtv7tvhq8p3slfAC/A8DxQ8GFH8Icwx7I0YxaTm6PI8zsDIANWUrfSCDH4wcjBVaHHEfCiCLJ5Yf2xJ1EKIZ9CaoL1QvmivZL6wtAh/XFncV+BNOGJQdKR8dHt8dCx8GIWkoNS1WJgQcaQ+8/7TxL+4v9Kr9mgUbBzQJ8AcZC7EUphikF5oTjBWsG1wY/gz8Ad/2CO9a52TeoNzb6LLzXvcr89XxKP5UB64PaxXbF20RAQR89j/uDO/t8vX4ifw1/jgGBw2QCDoODxw1ILkXkgYm+Grz2/Ba8AD0YvgLBqwMIwn+Ck4QJRiQG54Z7BhMGUwcqCOyIRccuRsRHI4XYwfb+Sb4LforBJISKRX+FFwaTBe/DgIOCwpy+8jvyOpk65fxBvYk+3EDKwqCBm7+fv6EB1IKh/qT62DpTejj3ADZ/N2F4fHsfPHv67juNfTA9Kf3Q/Ii5HLjQ+0g88j0O/EY5MLc1dgKzWjEVMIKwmzBpMUCzNHPddRo10zf4fAC9iDrCOJJ23LXQ9gY1UzRWtjn3kzhAuho8435xvgm9T3jvNTn1gDTy8y60WraMd102nDaptg53yvxVvu3AB8Cmfxm+W72Oe7n6Prmquiy667rGuk/6gDrSe3M8sL0f/u5AmMBGP5ZAcL+jfGf56jgVNzf2zHkfPZtAScE5gsvEfAU7h2wIeQW7AUJBpYGT/nK9YP7/gDwB94KXQ4jHJAr8DMVLoklBiH+GH0Qpg0RD6wO1w7uE0IYSBaIF+gdACRtJlAoripAMOo0xzMRM9MuYyw5LEQrFyYzIFIewR9MJ+gsSio+Iocg+C3TOWs4WjKeKqonbyeBG2UQLxT8HO4g0R0RGfgYvxhQFx0a7htOGt4UExEbFZwTzwziCIQGfQZIC4oPGw5bEYcVBxTZEEwNsw+5FEoSIQo6ASTz2+mw5iPkrOT77dUEERd7E1cET/7oA6QMexB1EhcUKREjDW8BrO224tfm5ewI7+/1tP+/B7AR/hhMHDgakBFOCPoDjgA393TsxumD79v1M/qq/NEAtwzqFLUXcxqKHTogwxyBGCUSFwMg9jvy7+057In6SBENGVQTRBPPFKQTexQEEhUGVv01/br3eenT4d3mXvKJ+sr70v9fBvwHSAhhBrD/Hvp68z/oFN0a1zHaUN1H4Q7tUfRo8bbvPfL88TnteOYj4d3fVORo6v7nod+u2d3V2dQ92JPZEtq05CnvuuM/0arK3cZOwyvNsNvE2qjbMd8x1iHVruG+5TXgFOBN5xbwDPVm+nsCXQJi9gbnEtrt1e3YUtd3z/TKBM4c1B/WYNgK21rfM+jC7LjspvFg/GcDPANs+lzwIuvb5N3c6dnj4NHxmAAe+w7xrPN+/D4DvQAfAX8D4fs57S3cCtSP2jvkyuHz3n3rq//TCc0OlBu/JL0gqhm5Fu4S1Q3iAk3y4+kG7WD1XP36AnUN9hjJIGsqzzB5LAAn1yQAG3kT4g67AwL2vPC29AsGtyRpN302BjHoL3Uw+i8ALrgvSDJWLVQjIRq7Fp4gKzD0Mo0wADPfMvIuADF5N7I5azZaMbIsVCjLIfgUDwVc/4wJ7hZ3Hwwl2SvDMqoztCycJMcg2RuWEp4IrQeqCqgI2gOoAPH7hf8HFVQlfyIXGwYVqggsAK0AuQNMCM8ITADl8d3naOfM6KrlauG64m7sJvSZ+GUEdRHTFzoXDQ8CDNwQSA9q/nDpxOBi4MbeieKH8LD/vwdUCe4HOgxnFpwYZRCBB/IFPgEI9rLqCuIW5Gj1CwcfCwAQHRh3Fw0U2Ri3GscUiBEtEMcItQB6/u/+Mf1Y+30AGQlED/QTXxkbGikXOhWcDf4BRfvd83vkTNRozqjTaN+08GkFkBiaIJgdShjHElQMwwF274fbYNVU2nXZI9QU1Xne2+/r/1cCVAM0C+ALnAN6/d/7Tf0Q/JPxL+GV0YvNUNcK3nbeXuL85jXmi+Lz4pfmnemh7GjrJOoY7rLsJeHT2InayuKD7PnxXPbK+z/+4/bz7ATryOwE6vfhRd7j3jXeRd2o3HLZKdxa6jXyZO1k7cz2Sfwk+on1+/Ua/d/+YvOP4qjYMdh24I/l/N4E21zfN+Gf4abqS/lWBVkJ2gVjAA799/XG6dfhAt8n3UrZldbz3NDvrv+5BMMKBhM6FVkN8gCR+UH5AvqZ+lz6xPes+bME7Ax1D6oWeR93I6glMybNJbAj6hfPBML0eeo36DXyIvfv9I/9rguzEqoZ8iYlNhc/BEGiQgBA2TkjMpwkig8fBBEI5ArXC38UDyHZJworBi1rL40xEyxlIUYeWCEAH+gYwQ9zA7kAjgzmFwQZPBwPH8kY0RMpEm8SuxxCJpggHRURCz3/ZPwW/8r5//nuAq8EaP/3/53/TfUQ7xj6IQ5IFpQQ/gkNBToCpgD/+j/xCu0I743vxvFY+M7+hgLU/7j2JPYfAOICU/7K+uPz3+4M9N/2g/W0/lQGdwFH+5X5ifyoCXsUvwmB+hDy7+is5jXp+uUI6SLzhfYe+0AJuRSgGlgiaSaiJ8klShxYD20AxvJg8Xz4wPlq/icMtRIwE0wZKx5hG8EXsRPoDP4GvQFy/Mr3UfGF8J/67gKoBtoPxxXVE9cRfQzXBwkNtw9QA+XyzeKi10veGOo17yr7xwaqAlcBtQmDDBMKrAe9BkwJJQmp/ifvJ+Co1BrW5+BH6kvxN/UY8tHwo/YM+iv0HOd72zPXvtRc0c3R59bn3Vjqk/eB+vP8ZwStBqIArPMI4bbZWuGR42TcTNcc03HMUMtM0FzX7dwl3rLd2eMl7Rj20PyB/Df81QCeAzv/pfK23zvRP86R1DXfn+Z75wToh+4x9Wz3bvab83jxT+6f58bisuJ/43Tn5e528IfszO/A+X0BRgLf+uvzxvjqA2sImgl/BND2+upY5sLqmfhtB5ILWAq7DgkV0RlKIt0pqChaIscZwxAwBN/2OfAS8HD2ZwPXD9ETyRRrF2Md2yU4KfInzyleKvAjXx+IGyMXBB3qJ0YrFS+WNwg7YjvZOoswfyAGHcskACkZKXEjZRtUFn0PnA0TFm8egSBOI2kmYCRUI6AjTh2QGeYdtRwdGLMRPgbh/I/6Vv95DFIWBxVSE7EVQhjkElsDg/X+9PH0pupc5DvpmfRfBBULofxi8MryxPUO+S36j/Sf87L/ywtCEfAXIxS/B5oBGPfh6RbrFupH3U7aAuEU5Wbq9+9q9MMDnBc0FycK8gbLCQULkgs6DskVIRUyB+oABwbJBPn9VfxQAb8JPAvRBSMGXQq3DiMZ8BwwEogbBC2HHrkX0yWcGrMGawR8+6r9ZRjkErb3xvce9abjje0pAO/8swFzE4gTIQq9DzYVAwxxBWMHNgE19XLpPdmqzmbZkfC5BTYY/BqBDTAGRAm3CYoIfQIK6qbPtMv6ySnGg9yP85Hiz9rK/QcMl/+eBWj/puAY3aznh91i4HTtYOF/03/V69fO5sD4I+h53CXsbu7Z4qbnYPMA8CXtaPBL9GruGNxUz1TPRc9S1ALiIukr6IPrQ+476pvsDO9a8m73he7632jiDOau31bnuu+D88MAnAc//N/xXOrh3gTiQ+zb9U38ifIi44PfbOJH4WTmsudy4AbgCOEI58L69AiKDLEPzQqaBmsLpAX1+GT5LfOD59XxPgK2/un65gWqCKAI3A8xFYwYjBjqC2z8KfbX/P4HVANg9vn54AagDmMcpiO3EkwJQheIGi0eRjGJLjUgOiFQFh0Nwx2/GYoHUBYtIN4Z1S1OPH0uDCnDLBUgHxpGI1geuxP0EZgNzQnqEtMaihMlEykkripCIFIiRit3IDwRsQmcAo4AkgtQEVYGvQMNFQwohyu0H7ENwQesBKzyke6R/nEAJ/Su9GD2bPDf/X0PkgUc84X8iARc+IQFfxhQBPftvPfA+Gjwk/7HDe4HMA2/Fb8F1wo8E275XOxZBVIFrOog55fvLe8A6RzqCO1lAX0IrPSu+F8I9getCVsN5//TAewIvQF7DlAiDx9tHM8jxxtbDJ4ERfqT8tP1WvJL+YMKHwwPCKwNZQYI/DwK5BFtDaAQXxXyBs0BxQx1AGrt1fAc9EPrQfjHDSEKpAe7C/X87+yL+wsLp/nx8jwFNgbI9t3+6gaw9x77fwff/O/5ogoPBNntXOew3sfRhdEv07LMPcl3zUPe/fltAYn7GwGT+Grm2+zp8mbqf/No+IXggdvn7lrt+OHd6QrrYtU/0aLfHtpWyYnKBtG+yqjE9Mrd2VbkVOpW7sz0WP2D+/vviej+4OHSKc/+2pvjdNjE0WDX1dLfywbMJc4O0bbV4d6H8FkAqgZxAWD0pOcc3xzai+Oo73juGvFP9yb+CQaoCXr3keBi3Lbk7+x96XDlUOg16oni4+QO9kIF1Qj2DQ8Uwws0C+IY0xSOA3kFKwYE/bUIrBo4Gikd/ivRJnsPZxO7IisaDxSiHzwn1SwxPuFCLzFpJncr0y/yMeY10y/PHXkSzxgPI6Yf1R+kItcauRszLPY0pjLfNPQ2zTFiL0A7vkHwNJYtwzXJM7Qv2zgjOtMoaR0nIXEjHSdMLckuOikxJUoixxlhEdwNOAoVAWb5gfrVB54fWitKJBkgQh6cEPYMoBg2FKgJ6A25D3kMgRIPFrsO4gxUEyEP7At5F5wdKRWBCawGLg1tEKwFEvwBACUI3AcjAcz63fJo8G7vqud75uHsk/BU9yL8sPEa4ovhGudw5VzoYvWqBfoQXBfTF3sUkhSiFhcPLgMyCH0NogD3+P4B9gsPDVsIfQCw+fv4evwO/U/4OfUm71jhENrt4cbt9el55gjzXP0wBmEV5hb6BeAAzv+l84n02gc6FaAUJw8CDT4IqAFxCJgJgfpP+s0KPA6ODHMOEQrkAnkAdPtu9s76qvio6RLd1dx03xDhtuHN3iXbStyi4qHoAPCw+J337ewm8mMAnf1w9iv6WQCkBjINAgvl/qjzFuuk3bbYauU99Wz55/al9TPug97h1rjb69ti2Sff3edy7330yu3d367Xc9Pt0P7TbNcU17bXd9Va00XcQ+eh5dfdddj21UvequxY9K72/fOD68brDPWN7TvgDuff8g70O/Tn99nxYOWu3EjUwM+T117hQebb79XxLebA3DPatNzK4t3jVt5B2sbhGvI59Abt0e/T8pPywvuMBuYHJQNc/e322/iMAl0EtwSOCEYIFwvVE90XLxaMDQAElgeeEegQ0QU4AKoKBBVbFHcY1R3gFfwJwv8E9Df2MAM+BssG5BAVGdUbexrwGUIf5CEbICMosDo9Q49C0T29NiswIy4EMjE1njOkLPwn1yRSHe4YRh2cItUiFR55FsETuxzVJfQkpCEzIuAigyGSG70S1w9GDzwMlBH0GskaCxhbE4QHtwXNEkwd9CbbLg8uzyhtILAWSBLcFKAXtRrTHwoh0Rl5DJH+R/d4+j4CrwiMCuYChfgp9tf3tvgO/cr/pflN8mTxCPXj+tX9R/gn8F7xaP6oAfvyQ+hL6J/qZPMpAgkF9/4i/qr4henp5wz4jgPuCK0IGvuL6Krag9QU2SHiZOfd6Snssus36T/sAO+D7ALvzPYk98Tu4+H80znMf8yP0dfV09sz36rZcNgW4uXrhfXp/jX+4f2MBjgEFvlR+pgCZQlzD3UOlAdpAv35iexw5DnpXvFu+bkFngmEADf6avcW+LsFCQ/eCGsA8/zZ+6X6j/LV6e/wDwOkDjILoADA+tD98/8Q/+wFShEXGdMbWhjBFiUbyR7NIN0cLQ5o/A706/VH+az9GwnkETgM2gGJ+JXrzOdR9Nf6rvhN/hEErv6F9LrqyuDA12bXO+TO7wLz5e+j7tv7jg8JFFIMSAf6ApP/cP6j/aH87gTkF+oePhHoAhT67+4g6ufneeKm5UvvQ+1W3vPaferd+uIF7AtOCuIHwwQ1+rbsUt7Z1YnfUu079toAkfyu51TgP+kQ7qj1QAJ1B5gJTAmp/+n4+gM+FJoa3hXsCjv+HvSN7hrm/Nta3ADj1+Nm5bDw6/t2+XjyKPklDT4cKxqUBzPyj+5D8U7pReg59pwGBxPuEjQJ6gNxAlQFTgZR/TwAsBb0IuocYRSKFCkgtCDRDHMB1QRxB70LwxDFE3cY2xXyBMr7xwoIG0AcNhY4GBklbS4RJwYaXhvZHlQQdv6h/RsDwQi3Dg8IcPyxA1AYuyoXNs86yT6HQdE6rC34IEYgJy8fMpQlQh9pHYcWOhf8FqwGS/t99qruPfLz+xkCEQ0CFD4YViFEIOoPXwI7+UXsj+jl9G8F4hICGhMSCQdADUIRHwg4DIcZ9hdIElALvveF74D99AsjEfoOJQdD/XTwVOXx6GLyVPmA/6r7UO9Y6E3uS/1GB18Csvlk7kHaGtRo3FTiXOcC6+3wEQM8FLUKkfT18H76kgL2CkwMgQXaBqYLZQX7/Rr/+ABQAm0AL/hH8jnxcOxM4qzay9sM6r77/AE//+X41/QA+T/7Wvg1+yMBFQMg/jHu1dsW1yHaK9w15lHwCOOZ0lDgWPmSBXUR5B+3ICEaIRhpE1IJvQQ6CjoP8gYa+xr2n+2+5wDwjffb+uIEJQfI/M70FO+Z7Y/2+//2BEgL+g3qCIAAqPPl6ZXt1fZo/QL+f/oe9jHv9e1g9fH3dvhEAEYHFwzBCSD8QfqYCWEVkBszHFsTtwwbCYX/jfIC5dff1eZQ61DppuoG8GDyk/Sw+fv7uPy+/wMAIPYt54nbOc93x7jRkel2/Mj7kejR2D3eYOkv8mUCYQ1EC30IIwFi9UX0i/40CeQLnAHn97zw2dtxy0zNNdd06OX8gQWP/4P2BvBU7N3uTfeZ/Rj8R/O26bLlGOT+38DbuNmw3sbsXPh68i/jz9zP4GjjruI56IHzqAIXFKATfQMXA8kQThzyIV4cFRSDEiEMkf6q89XuFvNR/OIAAP3I7/rlM/C7AVYRiSEjJMMarBPHCYH9GvZe84H79gotENoHOfqq837+fQwPDjAO6BXiHuAh4BZrBIgDHRUTIa4jliP8HT4bjhgXD04N4hAtFLccMxq1CTAFtw6WFIEV1xZ3E4EJggDp9bDlsuCq66j0pf8EFYEowSzZH+ISKRHLC+wD6AAx+bL4MAj+Cdf/Zwz8GkgPcQa9CaAGJQ1QFQEAMeop9PQE7g9/IAsigRMfCUn/2gDwDXETpBy5JFoXYQn0A3j2heuj70H6TAUZEHsRTAeOCGUXrBvNIDUxfzCOJugrqCsKIp4iOiY8Jtskaxy1FHUQKwhjDtUfsBnLDNwUoh+WJLkgKRP2Bk38kACaFnMdCxGUDZAMQf4C9ij1DOxa76wINA+P9J3kjfB0+TPywOcY5NXvzwf2GMcXbQl0+X77yQn2Bib8M/wO/IX1keTryEHBANOB5XjvTeqw2H/UvOeF9N31xQIADkAJvwEc+JnfGsxqzzHTjdnz8FID+ftO6D3fGOLb41bpzvKs7z3xCQJMBwMAU/2zAdwEtvz58oXu+t64zGzKOdAA2SnkZOo77of4wwYtC4wEuwElBS0HggPC+rLvzufK4pXbvtXz3TP3vQ4rEXj9M+4Q99//MfwG/kQGQhOcHbkTfP6u8InwEwTuE44KAwgjF64VQAWd9X/ldOY58Pnvcu1J5pXjHPTNCaAZOhraDDwLwxC3Cq0HogukBbT2xu3z8sr/BQpABlP9xwZlGB8S5gRADMcPqAcFBLD97/XU/MMHawlYDx0XQhjTIIEjMBLsBvoIWwYXBjYJwwVACm8TGwpy83LszPlKCjoQ+gil+sD0BP9tBHT8Hv2sE5AqoC4PI/YO2/5UAHsKcwgpAp4IsBSgGbUTAAZzAUoU3yUvHxcVmBTmDiEDS/pL8KrurvphABT+kf/39yDpO+3C9gb6pAQ8CWkDMASiBsT4l+Tz2FzP69UM8NL7k/WV8NnpFuUe6KjnIOmX+M0KvQ7mArrvzeD43ZXil+Ne2tHSENmV3tnUjcr6zn/ZQdtS133aLeN25lzm1+k16/nuHvnS+1TqVNWR1XLfh+Tb60PzDv02ENEYSA+V/9v0JPUo94H1avl9BiMUgRzTHzYhRiFnICsgsCBWIF4bMhJCDqoPcwsfA+P+UATuC38KUAyIF8kcnBsJHWMgbSPZJOYhmB11Fw8I2fxtAWMNDx0zJskaiglCAfv9vPyYA6wSFxaiE5gaShUAAGz4QABGDtMhhSX4GUIaMRxSEUQDEvDP4l7sWvjl+Sv67fe6+owEvwUg/yb/1wb4D6wNsPgK6xzr2eQz277V2drK7V8EFw8+A0fz2fd1A7kI+g/mENMKsBMvHDYNZP9pAF0EIQfVAOH2YPf1+sj3yuu+2/jWI+gnAvANfQvDEG0TBwwtCzAGwwDmBDALAwd6/FbwuuTj6QTyP/Xp/eICqvqT6Grq+AcPFLUEkgK5EKwZQB8EHowJuPZpAysSiA0rB1IOngSB/pgJM9RkyPwA592utpXaO9vry/nuavf349n6cQ6ODNkYiBveCw0IZwKV7lzeFNvE4njoR+VB2bzZ2+1u9e/5fwu/D78LShzRKQ8bCQ6DEWsZUCaBLUomqCMhJfod7hghFMUIgwmQHJQqhyqgKlIsaSrVJ5YnViWJKPgyfzFgLbovDC4rK88oOiH4FlIbKyotKskglBkNEysSThjFIsEr1ymwJpInuR63EVIJIQe/EPwV9BCaEeASMArVA20EmgGV/88Aqf739gTu0+oW6YfkAuMO5jHwzvsg+inwYue42E7NpsjXwJzD8syPyunM9tLuxwTHRdPpzm7LoNS61g7VxNV10RLNN9Cw0x3VUtdw2UnhQeVa3xrfheIx3UHZCN5k3JPX+t++5SXerNli2ZPhEvVL/i379/iH9SLwZO4g6arg3eWV8Mzvj+Ry3gzmxPMjAFAHBw5MFYgWrhj2HisbeRQJFoMV6BAEDrsJJQXPBskFsPwz+VkCQg/gEKgK+gspDUwOBRFdDTgLmA4pEToQrg5jDs0MUAowBDf2LemH6x77rAacA2j3xvOF+qf9vQH8C7sSQB3XJXkigyKgIVQe8BwNGBcQkgwPDzQPJQ0uC7UJHQeGBjQLFQ7kC0wNERPFDhsJZQsJEX0X9hYfFS0XVhcGFgQTGQlN9srxYQAbASf0Re2X8DX7TgJw/Br41P5tBIIG7AB68HDkHOxZAAkIlgATACEJUgl8+W7pkeaX6+friefv3gDZQ95Q48beldwc5CftK/O87mzhEtdS2sblwuYO1oXLsNaD3xDgptqRzj3O59rd3aDZVuBi7gr70QF/+C/pXOkn7/npHOPM43jq4+8e6IvZVtdw5yT57AAG/531NfR1AEP/WOor4G7g2+KH6DnjstVs1THej9rJ1fHfBuiD7Jv+Hwxy/G7uWP1lCbsC+gGzDLASXxNnGOIdHxzsFBMUbxq3G0oXtxbeHNkfPBSh/2b4CwLPE5InESvsIKQpIUHTRUo+7EBMRwhIVkWkPuw3oi91KlQsMSZ5GLsU5CY9Ojk5Zy8pKCEsuDgEQW1D+kQ9RnVEPUPAQgQ/3TVnL2IxUC11HPAWeyBSIeAcVhnoFrUaxyHLIR8dKRxxHzojex6BFL8RaRquJvIoih59FWUR5gq7AXLygetL9R79MgBi/Gjyf/kADFIOSAolEYwYvxsbIH0aLRBpEPoTBRLmCFr/zPmB9+v3yPslAGcDLQhtCTQG+gWiC7EP6AuGBMUBsQTHCRkLFwWkAf4BZwFCAjQDZQELASkF2gXLBBUE8f9i/EH5vPYk8/fsBPAA/fABR/5D/dX93/5y/Sb2S/GR8P7uxOzl6d3jptoU1wLcnd3f0q7IVtHn3JnSlcnf1n/k6+lQ6T/cf8rrwbTCwsICwFC+psl12/Hc19WVzvjDj8NBzcDI/sC0y7jal99e3EXRK8fRynvWLdkpz2zHoMqc0snQKcfyxE7IWM7L2BTdsNvz3qLi1d8K2gTVPdLJ1unfWOZi6/HrVOLN1pPOnsgOylLTOdys56HsxODP37Dy4fo9+RsAgQSsBY4J4gAc75/qvu/58nrzru6X7vn6HQSZ/SDzl+1F64Hwf/iF+9EBQhqsKm8cAA55CqILigxrApf3sv0PBl0D2/1s9k/x2/3eEyccrhBc/tYBpBMCFiMO3AyuF0YnAC0tI7EVbQ8wEicb+hmQCqgEOhFvFwULFPzv94X/TgvbEZ4OTg67GjcpLS4pK5IlTCWqMw4/oDnlM38zkDGHJqQTSgXLBCsTtCKUKJooBCw+OEpA8jgzKhskoCz0OE4/TkBeOlo4RENGSTtEcz7bPwpCRj6mOGQxfyU6HjEl2ydzHpYZdSBrK4Uvti5YLYstXjG4MnMx0zHRMpoxli5WJycaogwlDgsc9h2QEWEKHQz+CMUAdP/4Cn0ariDyILkdLRG1B2cIjgfW/033dPaoAikQ1QnV+1H2WPDX6MjixuAx5FbqYO576DngCuLQ7sT92gbPBFz8Pfl49i/rFOQn5lLqifO8/Bb/4/r59az1l/Yt90X5h/xJ/wUASf/S/Vz8vvoQ93TybuyJ5jHrO/Wn87bu5/CL8h7z7fUx9w76/f2d/J/5mfi49JvteOl46kPpxOnX8qzyGujj4rrYqMRux/Xh8e0363jrzu4c7wLrdOQM3svbJ9zX3SXdptTfynHHGclmy+fNqtEE2n/j+t8QzQC+Ar74wX/EwMoO1c/gK+fC4jPfBtp5yc3BdcmTy3vI4cugzW/L9shgxcfFXMyH1Yfgl+fT4TXZJ9wI4fbb9tZ73M7o0/ON+9L73/HC5B7gl+OX38/VuNTt2tPhyOZ46grtbukE4lrgO+Kw4JnksPNB+2j2jfuKBUYExwGYAuH7LfVL9uPv4+Px37zedOCw7mr8m/7WABsKmhNGE5wFavfX95IBNAwPFaAVUhREHbclMyBrEd4FnAQlBTgE3gR9AgAAvwGSBlQMMBGDGOYjeSgpIeAZFRlQH7smhydYKQwu7iviJRch9BS1BtkLrBsvJIElsiCFIkAzqj8lPSU8g0GNRZNJ3UYrOLgsujJCO5o1dy1nL406zUS4QS02dS9ELPYsiy6wJVYcMyVYNylArEFYQOw7OTe0LMMe+hyYIlYkjicCLTUuxytKLHs0HTtGNgIuwy8VOQQ88DOkKZoldSh1L+ozZzC5KZAmFyXTIRsagxG5EF8ZIx/FGkAXqBi5FzITOg3TBZIAvQDDBVQEfPaF7hT1VQDBCvYPjgkz/rT49/Px6cLiid7d2yXmsu8r6HDiRevV8wbwUueV4MrfaOVq7HvtxOe86Lzy+fxN/kHzZOMc2X/VVtSH12rb398n6SDxuO9/7Lz1UgOCA3D4Cu+053nkAupq64/m4ev/+Rr+LfaD63veTNSi2Kzn3/F47d/lJvGrAnECWvsnAnEO7gxdB1cGewIY/6H86/Qc7Efml+J348bmFOdW5+vo+uoe78jvAOqR6ATwVvgx+Zn2+/VQ7j3gPdkv3D/gYOEp5Jfi89nL2N/Y+s+B0KbeDuXd3/HcJ+QC8c71Je7V7ov/VgruC6wNfQv5/9nvFuLp1P7JzcpK2Gbqavhe/sj+K/41+lzxjeY93arbI+SH65foquPO6TH51QpWFVoOtQSQAk362ehY2n3S8Mu+yWjS/Nxe5C/xifms96r3tPfx9E/5gAKOCGcR0xa9DAEE1gSF+7DrMeaL5pHpAO/p8GTuYu198VP2KflP+5/7CPm88yvq9eOy6H3yCPxjAwMJKxGOGiUcrBf0EuQILfrv69/j3+oc+an98fhg9an6AwkyFIETyRFnGMciQCo+J7cbIxQhFbMZ2xhrFCEVjBvuIGcfJRRKB/4CAwW3Cp4P+BInHCEooiaiHNMbzx7uHTEeNB/fHrYjUi6/M6owRCY4EoX+CP11COANUg3PDikXJSLPJi0nGSovL8cxDy6WJC8bXhwEJ0IrYieuJFInKy41M7IwPimmH8MXhxgVGS0O5gKvAbsGlA4PFuocGSSJKd8pkCOyGrAXvxjLEYgFfP0a8fPiRefv91UA9gCYBEgIEQPK9bDpDuV25zHwJv8CDM8MiATG/S/7M/Um7xDyAvk5+jH0AOwn5D/dMdf6z+HJHcffxj/MWtZO35fkl+wm+Nv/rwPLAWj6uPQE8Kbi2dRs0pvQ8c6k2ljx8AK5DZoU3hKGDTIHqfyL9Yf3pfl++iL/1QMjB+AM6hEAEF8LUgb9/3T/qwKGAZQDiAv+DawM7g08DGUJ6AwnENEOywyICL8B1P1e/5QC1QT2BQEEp/6u+935TfKJ6ovt7fc+A+AMuQ74C+YLigbI9Qzs3/M4AK8MTBRSDx0ET/s99nr0nffr+8UBrQZUAS33xPWf+HDxDurK7AzzAwDuETIWaQqn+p/s6+es7JftfefP51ryLfwuAjwFawF/9K7kJ99w46blkeZw7Fr2eQRxEUYQywnHDRERQgxxB20AvvTA7J/mBtvZ1Hbf2/JxAq0IJwM5+Ofz6fR09sj45f6tCGcJ1/+8+3r9bPhL8cjuoemR5vnsN/Ez7jHuvvAn7ovpVujl7Rb0TfCl63Tw8fbI+E/3dPWT+EIDnhIVH88hCx29F3ET1QmH98blYt2o2Xfa8+Xh86f7kgINBvoAq/51BQsLwwlzB20DtPxg/NgCuwSj/70ADQpEDhsMewdF/B7tDuGi3iXsVALPDToLVAxvGGMhnB8jG7UYWBrZIu4qOijXInckRCLXFZ4F5fU78Jv3CwD+A4gFYwgfERMZyRYJDG0AKPnC+g0JZxMdD10OERltHf4ebyy4M1Aq0yJ3H+APVv018Qbf9NaD5czzJv4VDqggVCk4JqggRhvwE2EQ2Q+oCVsDhARbB4oGtQHV+Zn2rvnr+5X0O+c931zhHuPR2vLUK9iw3EfjSemT51rq5/vwDi8S9gM38sTmjeKL4eXb39DFykHIRsWuyM3RANmP3k3oT/U8AF8GZQRy/Rz3K/Kf7+/w/fV/+7z+wQKSB6gJMg9OF+oXQhOuEcUPxwZR+zP1YvHj6THqP/uuDQkX3x1MHg8YPhrsIWsfmBqFH0oiyx3XHJwcIRFGAOP3gfryAVkJ3AvVCKYMYRgvHWEb2xvdHFIb+heWF14cVCBxIi0kZx4EEyMMBwreCSUK+gavAOn9Q/6V9nDmTN+i5DPqTfKcAwAT/hkLH70caRFYCegGtQZnCZ4FSfjC7Q7sm+xo6BzoGvPE+kP7JwL4Bt38k/FH8h769AZrFYoaBheqEyUNzwAQ9azteuuq7y/1aPQx8xT4N/yp+r7zeOoU5HveZNca1SnWN9HPztXYFuTl6pfwEvPT9q8BVAv8DAIOzQ0q/k7jy9N70ofSYtL60s/S29ak4UXnmeMQ5evwkf5bChURrw4+CqAFK/lW6OfaaNSF2N/iyus99TQBeQ0pGhkhgxmiDJIE8/xe8jfopuB93LTjSfQ8A/wTSiUXKdMmQiv0Lqwo4hu9DcMAKP/gCToQ6As6DZwV8hakFPYWbReoF5AdGyH+IGAnNzBrL0InXB8bHD4cfRsGHUIjhyb0JVAmCCawI6YgzxjNC4oGyQgbCOAJuREfE/YNNhBEFssX0yAhLXcpTh9nHrkfGxmgErATgRMyE5AcPiZ1JpwiPBvwENoL2gmOBVsH/BH4GOYbtx8THjIZhRaOEskMvwVi+7rzYvWy+KP23/Im8bjxhfYY/LL6FvXE7OHgytoY3BjWBMw30Yng8+nj7RTtj+Rc35nk8+e45vzqoert3fHXTNuJ0d/Ae7wdvA66sMJz1KzeIOPA6EHrzOp/7KHwCPey94vukeYz4JXSbMn6za7PFNGT4YP1eQFQDcEQxQkwBrsBffJu5dHm9ejV5lbswvST9wkDbxP0EFcGNAs0FWMVwRO7E78PEwzeCq8DNfeb7nbt+fOQAAMK8Ay9EdsW5BSxD5wMuQuIDP4J8gQnBHkB3/sAADYGGP7X9EH4fP3W/2EDS/108Cfyvvjn81L1rwKzBZoDJQyzEDANOhEPEeQAVPiq/Sv6uPD58T/0CPPM+bj/KvuP+cj8+fmd9ib0L+uk5+3yAPwk+4n9awSmCrUNoAZg+k/1Ke/M47ThfeMn3ZXcNef166jvyPzDA/QAAQHn/P7w2e/C9LLm/NQ32UPhK9+q3uvgFOgz/JQPnhUpGfoagREFBNX3Vunn4UHluOTI3yHhl+Tz53rzYwDkBJgLhxcTGfQQ4gzFCdwAfPYx7P7iIODz4SnpsPbLBegSOiWPNoE1ySrXI7AX8gLb+zoBMf2b9aP6KQPFB+gOMBI8EdUZ+CLVHXUcoiRgIggbIxuqFoYOtw2YC10FAAfJDEYQFxkEIwYm5ipiNMc3AjZEND4tNSPwHagU/gUfBogQaxGIFKghYSYIK2I6/jmMJ5YhaySJHaIdEyeuIscXyxmUGwsSpAu/Db0TSByFIbAj2Sx7Nb8xSCshKY4jTiAGJDggMhQyDeQLngzeE3EbPBtnHqgmHyZgIe4gph0XF2cRnAQ19Mruk+1a6ZXsrPMG9KH6MAuzD9EG/AGs/HDxuOxq6T3a28ukym/LNcemxy/Qqtvx5i3uvPHM+YgAtvhL6ALZEsmHvNm3vbQTs563UMCVyHnOVs/v0K7fS/YDAUQFoAfU/Z/w5eZW1abEVMls1gDfT+yZ+UP9UgX6ENMOrAniCwcFj/Yn8z3xDuL61bjaLePT5iTtVvkbCccYriCoH44fayInIDoaAhKqAu/0GvO48lztiezj8L70FPmj/HsA8gvNGXUebxwIGQcSsQsNCscEM/6V//4BWP/h/qQAU/4Q/1kI7gqmAvABrASb/On4Av9++4H18f6UBxsBbvfd8Azuk/Wq/OX20PYbBqAOcQ7uETIReQ5fEkAOuvtc6/re9NZO387u1/YU/ykLkhOsGVQcxReoEskPIwh4/aH1ZOog3SnbtN/z3wjoSfx1BQABlgEbAfn1cu9g8LzovN6F4MTkgeKm37bfZuU/9y8OOBnPGiMdiBtjEbD/O+ch0rjKRsrby/rRN9gn4D/w8f9ACG0QqhdzGLsWPhRrDUwCsvH637jXpNVW0r7TcOIS9TQBqhGeII4eiBgCFqAKAPxc+e/3Hu0t5hToie1D9/n/xP+9AGkLLRUbGD4ZWBiIF04ZAhbeC4QB9/XX6/zqcuqo5HDqmAEIGtcr9DaiNyE0hTQtMqApCiH8F1oORgdF/5P1YPNY+w0EUgw+FwsabxNYFuwfMxryDCELZQ/yFIwgTiGBHpoqFy3uHi8W6hS1E9seFTBOMZQuIzTFM7AqJRqxEdwHo/o7+0wCUghfESEgqCtEKVYmrik6J+4gdyMLIncOQgP+BeP8h+yf6Jfs/OqX7Sn6KPzI8fXylfrZ9sL0IvxT9+HwWPNJ7Nnde9iy4CDnneei4OHbn+W66UfsK+x45abnfecU4rbNj8LVxSHDsMQpySvRaNlo6HkJmg4tE30YHxGxEJYEOfKX2tnZg+dU67jvGPdy9Y/8LgiQEDAOrhJKEsEJfwrgAn30h/A98LLoi+yH+B8FaQjZG9UfaxOsHdsgDxpnG5oX7Asq/R75vvhm7CTp2+Yn4i3sWwBxDQ8V1yE4IEwdRh5dGMsQhA6sBIH4EvEQ8L7rwu8G9kXxAO2T/Ef4avpT/pH6OftP+kf/+AKl/jgEN/zZ+pn0KeaX5KTpK/Vs6WbptO2y8nr8UAzkDhkFL/wi+Dn49e736pXand2k48ToBPSF/aACwQ6oFtMR4BEPBgAAbvO06LLgydha0XfcDOiJ6H/57/ls9Xz7IvuH76bs5+qT9xT0buZL5A7nHOh48hT7/f8dDm8VAhMCFo4WLgqZ/ZXuaOyX5pnV89rh4FbXm+Mx7mrvJPUREkoaPAqgGlweYRt3HmseMANi9KX/+f1o+gcFFQ7gBI4NhSNzIowXgSFGM04RPBDqH7cGBvpZA4P7wO4m/fgGFQkTGrYu/CnVOoE7QkK+O3cyGyc0CJn5zvuR9hjmJ+S69Fj/Og3qIcEnxzTnRBVChT87QUQzACviIGsTZwTiDlsLqwNKEykLqAu9GuoUXiDmGzwUBBItCIoNwP9EDewI/gclIJQjDSNOKb8qJypzGRUq7CcPHegoLx99F+wMxwJP7WzsKfU78HL0uwH5+n785AI0CAsP9haUF6gUPgnj/5/+n+cn6o3wndZH0sLhtsrjyhjeZtOo1Wzpkexi4HvjEOVg2hTX5dF71BzRz8rT0uXLpsr81ATQJdsp7UfouOQx3Mbbusn4vcG17resuCW5O8CRyFbftOWT+wMH8Au7DUoIsQUAAMTuh99u1UrZVOJJ633l8esv/SD13AYbEsMIxQqUC+IIDwGd+pn7YP3T89nu6/YZAYH/ihHRFeQK0xYfGJIKUhAbG0IRof/oBSwCaPFMBEoB+e2h8Kz5RAnDDoUfISneGLsmRCpzGNwIGwst9d/WL/Cw9QbeP+z3/9DvGvvuGQYbmgw6IMUdNAQlE18ZSf4z+G8ALfSs41LrwPTC5uPqKQIpCkANeRgvHl8QyxH0HXz/sPgPAqn4K+9g+Qr/zO+y6P747AGiA3ULAhSxE6gQ/hMm+9/mRe0S593aqtqP4V7eQeLwAuAEGvy7BisIyPfI+zYHPfvt9NMCevgl6brsU/as9RcBJwRo+n/7JQZxCcEJcQveA/7vP+DR7qXvJ9836EnyUO/38Ufve+Qc5+f1i/84CwQXDRhKDmMKawAC++nvh+3v+zP6awEJBY4DAwJ5FdkiOiACK8spjBgwDa8LwPyV7dHlj+n17uX2yQfXD5Yqvzf6M4Mp8iy9LuoadQ/iDdgBJvF99p/97/8dBjEZZSLmMf47bTGBLok1Ajv4KFQpuCvHG0gSThPPGQUNmg8FEsEXZRtpJDgr1SRUKJor2x2BFk4hBBIJHfAkNiCaH+MsMzZaKokmniq2J0Qp7C08KHMq4ieuJHEd2x4vFkoCJP24/M743/57ChMV+BIpHG0pYR2uHXsaNBSeBkH81/Gb8DfvYuG+1bzZ49yR2m7nXPN/8YfqmevA5OPk7fCV7f7b+OPX46rWJ9we2kza6d222fjWNd0i41zi+N/f4BDWychWucmyrrpovgDD1dS66WD1p/nFB1YRLxBWDegF1//X9WLntN+22oPez+CL3iDqzO9w7RD0GQG3C0wJngv2A8j7KQF7AY/8xvRR9br1CPyWA4IIBwmsCjIJIw3TDUIJcwvmB/v8g/WB7qjkO+K84LThXOko+Hz+KwxvHYEcMReMFxkYcw7PBjP0y9qe0XvQ9NLR1DHlYPdD+oACNhbVFg0KLxDTEWD/yvO27U7kJeVH5g7d2+Sy85301/PgA5gMPAH2AwkDCPwv+c7vR+uy6BLl+uMi5GjrSfDG7WzpzOyP9TPzK/X6AUIKHQ5AE/wMif738MziKd204Ard78720R/ZWtqH5AzrpvBH+ycAQ/q8++4DBQF89sDxeO897DXvXvd8/Cv8wvrr+Ev3xvsA/+4Bqf96+Dvv/uMt2rrfCOvA7ALrzup06/fx7ALyDeoUrB1rI70fIxyqGvARcQU+CVoO3ADNASMHCwbeCskYfxu5FQke1SasJOQWThD+BVz8yPKP8pf9tQ2aG/gjdy0+NYM1oDMZQG1EXDshKb0XAAnC/Nf3o/p1ABUJVA0lEA0edS0QOC9AHUsvUZFKi0OTOu4qwRsrEnkUUhotHHUYzRMHE9EVgxaQFwQcjCFlIWEckCBxJOYcJxk8IMkfHRxOKug0bTDFMQo3azXBLicv+CrBJOYgCxsxFnkKGv8c+kv3n/4jAqAELxFSFKYaYSIZG+4YwRy3F+ARwREpBq72Qe9Q7mLrzeQz3pvYndrj5A7u7eaJ4TnltNp02ADqWOyk4ePmk+zd4xrnduUr3ZvhgeHf1PjXP+ab5c3jZON52znSDswEypXHnMWTyvTOP9ZL5RTwJvS8/agEqATqClIGgQOCCIP+QfGN6OXjquJu4/zhUOcE6tnsm/nO9nz0f/Z47C30nAfJBFj5S/WP9sr3EPkhADIQ5A8nCHUP8gyzDnMLNgHX/dn6ifM36yDeoNR05crqK+UA/IwJkATDEIwYaxhnGooU/AviAWz26efz15/aXt0r2pvyvQC48ir+rBIfDJQNJQ7z/vny1eg755PkCtu+0VbZ0ehs8qH3/AaHFpgPOAe1EVAHuvXz8jPjvOUY6Y3h+uS28xrxdPIQ+qP1sP5T/rr1aQJtBCUEQg5F/fHy0/FL56bceeUO7Qri9ePr88L1oeqm8BbzgfGm7xjssu9Q5hL2kgIQ9nj+lgYo/E4JlhNc+kQLMR1S8fXmof2sEd4APeUPDAAC0O02EZwXm+6f75obHO3h5gAyJxA14vINTi65DyMBqAqF4qDKaQF1FiD1nAfoKKQRBvthF7YwZRXPFsUuDwxw+nEIRhao9yfl+OP0zQzT6d+h9rsIhRq9DoEJCQ2F+9wOog8HBxkQEwwVDR0QrB4ZIBkcnBXwC3sIzxrDLU4iWjjDNYEXOAdGAwIQZPoyBeonWCn2MkZCxUlORFZKOUsASFQ/+j3pQ4EvOB6aGvgPWvMS7j/9vv/wBLkZmCasKw0oWCOcIsUcWhT8EuoTTgk2ElAR2f1V/SD8CvJ/46bpYPNu78zsXO0S9/7mhd4I5YHWEtQz4pPYLeZo9iDyo/bK9gjyHPRL+untO+NW3M3MkcMCyaLI9Mrp1J/iHuFD5XrrL/PyAYYFGQq/A4YOwRbwF54dihiGDysBIvcv+VT56fOJ/j4CsPTr+BsKzwb1/NwG4gv+AEII6BZKCycCigmDErUJN/5w+QL4EvTr95YJYP4O8Uv6QfLd1+XcqulF2qLaHuZk5OXw2/+/BhEP5A+cCZQIHxHBEG0L2QyGBxj40er124nPVtjx2RrWJOoi787pkfw2AZ/4zvyUAHb8//zS/q78rPd89PH/awA2ApIM2ReaH44pvDWUN1ww/ivHIoQKHPvO+CMARfp98qQEkhamE7kg1SY+IwAoZSRYJlgkThnRC8sAdO4v5DPgyNl24I/xo/7r/ysHKwo0AML73/2xAR75FPA18LTkvtiB2uvTSs530jfL2dEz4IPnGPTp9036n/7r7abbLdT40oHXIOWP5EXXGN624IXVxNAK2HnWjdMv2K7hFvMr+yj1HO9Y6Snj4d494JncGt5k8v383gIlEeYq5zg7O4E8XDcrMVwlvx1IDiMAsQOmCF8GHP6qAtgEVwZlFooc2xQPFDYbDRshFF8TuRhpEi0JGQWMA+3/jAFlDFQTABkfI/YjERp9FEgJYvwx/Yv3HO6V9gD8k/jM+CD9ywKCBhMLuxgXKmIu1zJrLH8d0w/S+PfoKd+82mDcm9yg3RjmN/Hd8tD2yQOxAwQPACkrLJwhBh86F2MF6/xJ+2r9LAOeGrI39EjPX7ppH2DCUIVEvzXXIwcYQA5hBbEAUAcpB7j4o/oBADX/uRPDMOE1gzCiNK4qIRUTAsry1ewE7Jf4OgmDDQcKUAlrA3z4RfcY8lDnuOdO6UvnyulF8Z3jj8yayHvFssXHyzvX+t4i5MTrCO7f70nsQ+YK5NHrWvIM7wDuZuiJ3n3PUra4p2Wkg6ZMrcG/wNHA4JX69A6gGHMY6hbNFhMcLxwhGagQ+/6p+6z+TglMKGk/NzOqJmUnSCCmGjIZAA+OBSsG3gJN+YnzUfel9z/6zQyJHc8sezX6N540TC/ZKLIWn/2P8J3wkfTZ+uP2bPey+jwC+BBUFYYO7gfuB4v7PfIr+q75pfEv9I/1DO+N80n/tv6iAR0OXQ+zBJAAPfzz39nVbtx50xvI38Q3x1rHGtQv5Rjm1dPLzwTUStDb2pnz9AlvCMT59ebl5tT9lgEo9on12gFpCqgGfRf0N/BGhS5e/xTpIOiN6XbfUtn83bTg9eA/2Z7UL87ZzmzgS/h3C+4QaRJzBCb3eP1Y+M7tlfCB85Pwh/a4+9nzsulS3SXUqNN/2FTc/N6m5cTt6fPV9p3wz+dU5lDhAtvE3fPnl/WeAFAOYR0jITwflhfDCdwK/BT+E3cPJQtq9t/fAtiB1JXRttL60mjLBs6024fn3Ak/QkNbkUhkL8srvS0vGQkFvwcfFd4UwxXdLplOl2IOTkgmrBbFG8EixxumHW0mAiVxJOImQi03K2A1YEcZS9FMYkteQo0ykidzH1IT0w0yCFz/XQIdEf4f9CdELi0wuS5zK+gj9BT2EdUc+BnmEE4L0QLuBJIZGytQNzE+Qj4OPbY9CDmJMkYibQaL9Dfy1/lQBEQQCQ93BI39pfvp/bz80Phu8wbpyN0A1FbQQ9qw/BUeTh29CQL7igPqCHr5auuX8Qr4l+Gy4Gr+tR30JnsEe/B/8Rr60PVB4IHjFOrn7ALpMemL7jHpz+Ye7P7xNfN++wMDdvyF9pv1YPR76jXZotZm3dfeS+Ba44HqCPY1/nr94fal72zxWve2+ND5JO0/293X+tsG2pvb0+h47on4xQEdA6wMyxNIDl0EVgRXBC/+Hvih8mDtJ+l54ofeJ90E29/aVNcd0/HS/Nrn84Ubjy7ZF6r16e7I/fX8ifR9AkobtxxKCs0S6jFzS8M2UgKV9jIEQAwM+gDum/iy+Fr9NgSqC6YCOfqq+lr5QAEDC4IG7/Ob5Rjel9mq3jfqCvb8BE4QJxXgEs0T0xIuDAz9gep315rIk87t28LiXOI93t3fO+zA+sz8+fb+9+fzi+gS4P7eJeCJ2pPVXtZe1/rawN132/Xb2eJ26Sfj+Nj01tPSz8U1vzHDvL8VuO3I0exdAW77g/DM8uv5NfhJ7YPrDPYC+TXtuPbsHH86DylN+8rmMeGg3EjUrNd948LorvxpD8MW1w/RC64ROBieIQYpVCyLKRcfgwxH/wr+1QC/CDwWBxjPFWcjdyzfJTwpLyldFJABtwEVBn0E8gcAB6f5CPTb+vf64/olD2QtCj5UQvpANTx/NOguLShxHhEcWB0bHU4ezyQXKZ4kgxiQDG8GAwGd+STxUO+y8lrx5/UnFYc5qkGkMpgtkz01RDE62zPwMfQrVCL8GqYf1zZMRPghmAU2D0YpBj19QdVCvDzuPs1CgzxnLdEVbwM8AB8EgggVFTQfsB7+Gc0WbxlrKZ49cUAZO/g4EDjLLdMg2xZKBvHwGuFH1d3VCuQr7D/qyuds6yvsNebr2+nSvtXN5aPubOFH2+Pk1+VF4o3kneiR6MzqFPDz727uo+t/3a7Hhblzsvipy6XiokSkEas5s67K3+7PBE3/BPO88Tv5tQHyA38AQf1q+Ifx5fq/EoMfyw357wTjR+KF8eX+o/yX/YgBiAKgBtwTABBa/nkC3AyCB7cKlh3uJ9UgcxuQHiUhqCJ3H80VKQt1B1IE0P5k/1AFogTf+QDyzPTC/JQBUgWzB20JmAjLAun5ifST+jYDWQd1BG7+Gvqw+Qr/DQK7Bt4MGQTK+PX2cOy02fHQk8s7vkC6OcP4wUa+Xs4z4yDvFwu4MUQ47B/gBov81fnV7graHNIC2G7Wxtct8XUbfTZcK5wKFv7iBBcGPf058Tfpjd+43vzhcuLV4j3hkeAh4dnlGu5U+foF7gWD9qbuEvgK+2z0R/5bDG8JiAIAAMz3VPI9+cD1UOjn4i3mBOah4kXhFNkzzv7GicLpwe3OFueV+EH7cPjV+Hj8lf0c+435NfeZ9yb7//80A9wF/gOR8uHfh9oQ02+9VKxlqbCyIdR1BlIeDxbZDNcOFxuDLKYvTCQdJCUoNBlvEtc1VldGQJgEvOI37awJphjVFxcdjifRJ4EidyhkMsctOB/PFjwXDSHJMBVASkSqPjM6KTy6OzMyjS2cLQokKRgvEcUJHQNzBYEN/BMNHlgu5TmuQX9Gaz+iL20kThkfA1b0h/jC/bkBoBKwJTExGzy8RIE/NTZMNO4xkCWGD+f0I+Ae1uvOmc781l7evOIg5hLwpgZSKwZITEY+LTwV0xDZDfH7AuqZ7/v8CPen878Vg01BYQ454gqgAr8QHw+P+CTu2fFo51bOFsmN3bLpOevf9hsHZRHZGB0bfRSBCvX+5/IW6lDluuQ78JYANAnqCsMMSA27Bf332eyZ54HjIN3P1pXS7cvHwQzCXMyy1knhj/HqADoHpgh5B4wBrvmZ8zfo1+FJ53LuvPUc/EP7PfS29Uv2Hul93pHXSsfXrsehPq4c1jIDhREVA3L9MBGYIP4X6A6sFwQi/A/39B75+BkCLYwKl+VU5Mj+uRI0Dw8XRCVaJfAN+/wjAiv66+CT0IPdBvVSDugkSi1KKjEkJx2FFSUPYwa0/vn5mewY2NXW9+z//bT9GP9vCMcSThcbEmELAwS668TIBLYIt/q7CL4AxJHSO+jqAU4UQhgHE68OtwwXA53zXOVQ2pzMObwCul7BI8dKzPzOpM49yv7O8+QBAPAHbPVY3AbXauXA6M/eZuDh8W765/UjA8En00yLRegSNe+k6E/u2d8f0lzXIOH65hLgxubX+EQC7/un+PYEiBFUGRsZThWGDdwIcQt/ErUYBhfNFTYW+Akg9CLx4/5IAjf58/O09Aj67AQFC1gN2g+WBQbzvu3d+SMDqgOiBC//3fspBRUN6AuUCMcKiA+YFHEZXxZME7kTEQ51BicE3AZ5ChMF8/Ra5RTr5AuuKG0nTA1s+jgAtwv4B1YDdxJYGxUODQSuJHlZ6XhoXhc0eS6iPBA97iV7IxUpcxx1ASLuAvgdB9EDdvDb9DwRXiyYOxtE2UMzOz4wGSCYDpAGzQbNBaADvQBKAs8U4y2WMwApzyNzIOIYcxBnCLL+Le412RLK+M1a46zzp/rBAdgFIQkjFmcm6il9H+ASswGb84XvruPZziu/QLc3shW8PdSw4EXbN89zy1bnpBbmIzIItOig3pPh0eQv6f36rwwG/qrZBtt7Duc6ki3O/WbpL/P1/+f03+bA8Xj53+xa3srufQbBCYP8JvCw60vuT+w/3zPYsNc50iPWgev7/y0HPg2gEg8P2AlACbkJAgplCmMK3gwtEVYK2fvT8ALl09JGyMTIXs7N2EXkEOuD7tv2xwcGFd0aUBllFUAXbRcnE9UOuQ/DDqAAeelK03XMgc38xEyzRK0/y3EAriVpLFIacQX5/Hz3le/X9ssP/Bc8DiEWRj0Eayl0+EieIHcWtRjuDGkDbw2gCSbxcNvn36H3jATV/HL0LgO/HI0oDyfDKdcnFxcrBNf7xPi89f7xUOrP4s3hAuVo7jIBZxNMHnEkhSdeJ1giSBWF/n/s9ezA7o3n5+P+46HlHOd/4DfXl9k97KP8dP9KAd4CgP3563LW/s0GzuvLDMjb0RjlBu+h5qTVUtZJ888EQ/Y332rX/N2V35vcN+iAAUAMZPaP4skAezz+XC86hxXJDJoYBh9IFG8VWhcNCabgIcaq1cLqyu1L6OHzJQgnGWkYzRC1Cov/1/Co8bMImCS/NAwztyUfF3kJKv3V+DP98gFABZQOIx6wJx8pCBw6AWjvM/Ny+wMDfw1rF2MfESCBHY4bux/yIJoRZQbiBH0FfwA9+xr4VO/Z40HdYuD572r/Cv9681H8dSxeUXFM0TEIIIEacQfI5fTa5e0g+W7k89mGAJg+zGiwUN0y8C9QPt9F4UCXS49Nqj74JPoTcRX8ER8BJ+6s8tYEOBc4IWkoxyW7EhL7CPEz/LUStiNzJXckPipMK7Aniye2KaIlxR69FZoRBRJQDzAAj+Yz1UzTHtZB3pnspfyqB8sI/g9MGjgbuxUTDSMKHwNP+UnsS+Af2VLNvrkjqYuttL+exVi9i7UAwVbvrhwZJTwQTAEXCGcGEvkp89v5sPUS2CnCANJ4+7AQwPPK27LbrOWN7hr8/BYdIRcQh/nv9CUHrBLBCAb5DP4CDHMRBA9lDuYGDu8d00TI4c7r3LbjFOJo5WTxEv04BKgM2RQAGK4YuRdvH9Ul2x6YEIP+Yupm1hLDibu2wRTRvtub23/mEPzTB/gJNg1UGE4cBxdzDbMGkgHK9z3qQd7N2iDettlDy2280b8e5YwKaRHRATH3zP2V/1b9jAgzHEIdzwMK+hkYsEIrVfQwSBXFCWEBzPH35iL3tPs162zcpOatAoQM6gZhA/4M3Bb8HvgmEy8AKZoTGP4q/j4CzvgK5cbYBNh90y3OmdA33NvpFPIa/SkMaSC/Kx0p0R5nES0IjANY/Cb7aPhW7d3dRsv0wSHEIcs704nYieRo6MTkwt/n3WzecNpi1MLUtuUE9gTxleRs3pviaPZtA8T8Bum+3dPk3eEC1abW+uvR707XBtEO9lgkqDtKKloiQiGHH9senB/LLosnCQiF6lrjwO6m5yPfbOin+pP9aPqYBb8WJxreDEIBaQ8nJ9cwUCc4IR0lZRqYCF0DpAZ7BeX8ofki++gEPAuKChEM5AjPAtoCFQl5FtUjli2kLDEg8hrZGE4TngstB1sLSAa2+Hbu8/Dr8zvrgeKZ3WLhJ+bx5ajlnect9CkbFUMOTKI6NSpUKcEmmBqqDSkQ3BIW/grp1/h7HPA2Mym7FuASNSPNNM833UpwWAZEYytcKSU3zSykFNEHyQvgDuQFbvtXAdMHyQAE7fro4fiGChsT4hPdF30ZOhzwH28gpB+iHXsdGRwLIeQfLxJbA5vwVtx1zbbHoM6+2Hnf1+EO6QL7ZQnHDvYLOAmGD0gS5gse/qfyS+Yj0vy9Oa7sqG2rWqbPngyj8rFMy1zuMhAXFQUJjgo8FG0TMAsRDf4NKv5J6PfqUgYPJKgXePor6d3n/O3M8gD8swMXBgz+KPU8A/gXZxYdBzQIsBa5HzEcCRj4DI/4l92yy1bL5dRi5NPsie1y6/vto/Ny/WkLXBUvG5AcBCG9KGIqLSJ1FO4Gg/iq6R7fIN0l41jiUtYz1bTiT/WQAM8DLgY+DEwUihK9DN4KvwRU+Rrqtt591/jPccQQtwCxO72D3skCTggY9fjmR/XuEmEctxYEGi0pVCIxFBUfvkJeUEYvAQZD8Qr16/xEBpgNqAjf+R7y8/ed/LbtHt0e3aXwdweaGfwmdy1QKSkbuwZGAHsAi/cC63/l8d8t2IXP38k/yufXuuoz+qoJCBszLXM2Ui3qHY4RZQkY+r7oEOFs4kPjL9301h7ZFt2H2mzR69DC3HTsDvmtAWEBqftk/V0KihI0DFsAyvbr7Dvk/OPC9W0FswG27ZnY+tFk03DXKdei0fHSedXh4G8A+C1vSV5BsiqgIJAkrCElE5QFPfsA8hTuyvdzA20E8fw5/QcHjg9vFGcYKRy5ISkrni9MLrYsiyY4HT4akh3kF/wJQgLBALj5ie598GsB6A6eF4chpCgpJ1ojwR+iGVYcwycdKtciqB9WInUegxnVFcUMrwDn9iTtpubA6B7wHvB27uPxTfqMB+QW0yOqIgkYcxmKIFQkVh8CD+39rvTl8xzsxuO44GDa58zFwkrKHtp771AHVBYbIGsqBjNiMtEvRjMtMjorkCEnFC4BJ/Bm6ufn+uVe7g8BVhhEJ+gqeyqBKLAmWiMPJN8qsChCHLAVFR2LJSseaw1nAioArPib5mTZrtb02FDUFM5F1HThXu509T32O/Y7/MMH+gusCZgEKvwx8tPnidxq0kXMg8kjxGq9mr0byUzZ3eQI7Z33uQTZFS8gsBptCcb7Dvvb+tX4YvOX6lzczdGw0znVuNDAzE7R79Xx2tHuLgV3FXsftCHdIm8rCjptQXU+9DOaIbkS/AwnCT4CGPuw+uX9GQFGA7UCZP8U9SnxgfsZCAcVcSRGLv4mRB5/JTgrfSS1GDgPZwda/7j12+XC0vzFSsWczB3Uat0O6gzzcvsFAQUBxwCKBowL2Aq9CCEGNgGT9s7ncN6F3/HjPd/01L7NKdKV5MTx2fmgA1kKYwuxD4UaaxRIAaHyVOeZ4u3nyvT9+Jn0sO0A5E7cpNq44RbutPbU/owHdQ9/F0AcaRrbFkYYsiF9Jp4kVh6WEaQAdPI18FjxxvB97o/myt0Q3Ljj4etW7jn09AAAFf4p/DA+KM8bKRP8BeX46fbZ9VLvyOZ23snT8skCxI3Dk8lU0PHUO9175tPs/vOr/+gFzQYtDjEVfRUAFXUXDxPWArL2p/N08TvvpOgl37bVutQY4GDvsv3VAewBYQSECnMVhSGNMVQ2Di3mH4EWVBbRGSkefRwXEO4CZvsU/KH9wvle+FUAPBGsJms8lUp3SIdC10LsRN1EDD9zN5gp3hYhErIfpin0GvAFSfsO9qP6XwYjDtMOShDoFm8dYSSBKM0qbyx7KOQhyRmkEHEFL/rO8aHs/OxL7pXsieMQ2FDVxtj83arp+fZT/r8GvxZcIgsjUhyDFOYNpgdVAHT/sQaaAufzcOUS1cDEK8HCysvSTN576jn4GQaiB4wB+ADTE6Ai8h6OG6ocOBspEXsHbwRpABT5Ne9N5frbBN3z6QryR/WT/kgIGRAPGMseDyHPHycfWh3PGlYZNBc+FVgQFQdu+rbnatRgxqjA6cTA0HDbJ+CN6f7w1fKd9yT92/8AAH7+N/uV/CoAWPsU88brQeQr3+HbAtCLwbDA38aRzt3a8eoG89D2PAJhDA0PpBSeGcEUhAMU9GzyuPDb8Gr1JPhH8j3nbuP+33TgQefh8GDybu4/9CMI7B2QJ0IoESimLTc1JzjPMd0nqB7yFJYSSBWFEkQCpfEl64/v4f4AB8UAuPfO+ugJuxt9K2cxOi32JlAjtSGmHGkVHwtB/0/3/PGq6M/YPcyqx4vKptfp4gTkOeUW7MT1N/6gBaoLtwzHDGUPmhECEagNxwUU9vjm+t5c2iXRrsISvtXEI8lqydPTCulq+VQBxQKEAQMErA6OGgIWIwm2+4P4kgjdG1YrBhrr/EnkXtKo0tHW+OC43/zfYPI2EEowvzbhKJQddxqcGXUVuRK/DYYCkAFhCTwP8ASL7Yngbt285DXsDOqh6Prql/uQFXEqHy7kHFYZhyV9KWshmBXRDFcCkAKUDQ0NTgKF8iPkH9t72Gzf7eMn5yLx1QTPHGAtVjEEKnMk4SVpI2sYEw97DN4G6fqF7Azag8cluiG2dcXr6GsK4A/yBNoAIwz2H+YneyRvIW0f0SB7OLxWk2c3WvBBTiSEBvH8IvWR84Po393d528A2yZ1N9MxHyesIXskACXZI7UeERlKJGs0BDrfLlYZDwwXBEwAtvQU4FrV8d0n87cDIQ3gEIgLJw1IFgAcHRs4EBUOKRfbHO4XIw95EUoRbwXO9FLn5d5K21Tj5+hc5lTvuwdSFRkRTg1rCbkGXwg4BQz2LeM12FTTQdC+zJjBnLSFv/zgAPwU/GTq7eA55YH41wkv+4Po2etjA0AhmDcOTzNQFEGkLccRgQUo+IPqVteBw+PG/NMe8m0DJv1y/F0FeRHXEGMK1QVSBYMXKSq0LFolEx2cHtkZewhD7DPOQsKkwsvGVssA07DgSevQ96X9yPTK9Fb/8gaaAtL/8Al9EgQagxxtFZAOpAaT9aTgSM9axTHDH83b4NHxxv4JCGsOpg4PBZf39+w15YfbhdO80OnRMdM12iL0/BRQIOYJK+yb42rh8eE73YXXI9uy3/P5pCZ5RkpSpE3AR20otQ0tDkABVO6y0yXQ4d4W75v8U/pR/hcH5hBrE1b/yPNtAXEXeyEIGfAYyx0jJPIjcQ999qzdi8sGyBLMd8+Fz3HQYNKR02jhCu/O7kvnVt8Y6OP7rQWUB6wTPiNKI3MfOCTFG68AUOa61mzMqMIxx6bN78t90cDlXPwq/iv4xPZ88o3q3+Wo6DfjANcv0bTZS/uOGI4ebw0jAW0HiAF09AzhH85GxivHo+b0CU4uFFbnXXdZUD9KOxs0GRbyAl7tCvIE+30KMhQfEJgbPilrMYMglABP+zYEQhLiGDEVhRojJtVAUk0bQ7AvtxMA/Z/tm+ZF4R/cy91q4yvvo/44BpoJKQSu/QsA+Al3FNUXoBr8Hh0ogThaQ80/EDXdJzoY8gDG6hrbicqDwLbFQdMM5c74vQROCPgRIx36FisHgfhi5/bX69lY988ZmikGJvofsClaMLAf4AFg5k7P1bzFuGTLuOpvIXdKg1bZVJdSP1amQeYh4f5F7nrx1/nsADP/vQl1I3E0GSvyEfoDPgdOB9/97/Kj9pQD4hc8L7Q2wzFzK/4hFQvQ8OfaOceytsuwDrUxxgzb+ucY7qP3GQr8EscXkBiWC+ABjAbiDhUR0RKOFaQV8hVWDU35GuS80EK/H7Qntbq5a7xKwmLP3+Fa87j/bwfTBbb4lecc4Sb05gmDFFAR9g36Hmcfcw26+fPkJ84jspinH6gbu5PjCvqoG+w1ljuwQS1DxzuYGj4KvP5B9lr8of4ACmsQYxgVFPYArP6GAE/+WuxM253fwuoNAaoM9BHHGOoZGRllFWcTOAIE6FDX0891y8nMxNKB2mzhSetY9fX5HwB5A7EM3RprGyMQvQzTCiEDEwkPGdkcihSIDTgCpuue1/7MjcH0tZa2RsACxRLKMdp89GsHDQYv+Uvw3gTsIDcmFRiWC/AZ9h9bDD3xmdyqzd+4uq+TtuPAh9uf74ACkBrwNwJOSDoOMvwxuSw6HlYN1wsuDKIdgSQAG6gU2gnHC/4K1//b6YvSy9CJ0dfhCPekBZQRQBfmIL0lxSs2IhcMk/hg7CfpEOFM1gbSkdgK6YH2U/lY/ToB4gR3Eb8fMxprD1sS/BIxGM8o3zMXK7Ac+BFdARD2avHr4qrO68XEy1jPPc1z1gTs9f5UA+X/qPeu/IgYSCuBLOElaykfOb0zcRfmAsT7O/A51lzKc89W4Pn0N/3TGDsziUAGTXVLvkLlPL5CSjXRICsc4CLbODc5ayziJ6omUCSMFaIGk+/22R/OaMnn2ZHuCQBvDEQZJShrMYs43TBEHLcKaQRnAhzzENzl1Hngh+0W9hr+VAbaDGUZQCgAJEoXyxV/D6wHCRIRHowf9B/JH+QaXBZGD7kCxvOT5J7X29I5ztvEhcEny8LXAN103n/dpuktDtssQDN1Lv40nEj2RTEsOhOvAPXo9sk3ulK/k9XQ8Mj11/vuDbQlczjVOEAvTCBIJeYgEQjgAEAQ/CNMI8Ec1xagEdkV0xAfAUnl68wYxi3DVMdUyYnSGuUe9twFHxWHJ8ckhRLsCK0EfPuf5VjTbtAC1Tnh+e/v+PX5SfiT99X47fV47JHwJvfh7jHzSgSICCUIXxKIGIgVsBUtEEAArvK47znpQdTdu/qvKbXyvTW9z7NrtbLIFun4D8chLyWyLR9Ag04TOSkZPgHr6SnOi70vzJHdj+6q9t3y7gGHGN0sNzG4LB8kERnFFKP88ezC/PYVySEvIJYneywCMhk2vyi7DoHsmdVKxH20lq+wrTm1ZsLh0mrptQOaFP4RGRAGE0gPiAB27K7hsuNq6zX4sQXsA/v43/UC8TvmOeQ/7YX5l/+f+KHxevMe9Lj6LQrRETIPwQ5EDNoCjf7A/N3vDt3A0gTIVLacqJShqqPVrfS8ctSu9/wRKR15K9dC005KOY4aNAvqAmrxjd7K26DeBOuR/scCfQRtDuwf4SXHIQgZuQS4/Lj6rQHJE3UlHS8jLjk38jwQPBI8WDKMHNn5neDnzB++h7xCtEC5Ws5L4brvewJdFOYWbxvHIqIm0yEbGOwarBugFR0UkhA+CbkE6gAc9MrsDvX9/U4EzwcrCVYMGxP4FqIaYieQKeQkGyjoKR0pySbJJXUaGwXE7FbTEMLFsjqrmqnhryu9+M47+DEhoDJYPN1MGF+oXi1SJUJ7LtEbfwRY8tvqyuyX+Rz+h/pm/U4JQBumH+QeMx6JIPIk6iHJJqItNzTwNVIyyzJtNDM9gzsMK4USQ/g/6GLWvsdMv76/8saqzC/Yl+Iv73T/exJpJ8cxTDZzO5M9Yjd5LTMlWBqgCgj5BO095IvYx9FS1wbg+evA+dL8tv8PC6oSMRY0H0Ai6BwxHKweiRyIFVYJ5fcl5n/RSrysqxee8piBnTeomrUhyUvkgfxjE90mizmDQwA9dzR/KdccRgk78OXkBuad6fnnUOD62kPZ6+gM/rMHcwvTCIoL9g7TE6YYAh0vIkgdeRy1GoMXGxeDD0oD7/Db41zWDMB5r+yoi6vBqMmpQLjxzqPtCQSuEbIcpiuDNRM0BjRlLoohmhVYCi33J9+0z5PG+r41vGbEtNQn5U/yf/a0+30IPhIRG1ofXxzbFXsT/g5GBIn9zPF03n3LtMFiu06tQqSWpKalqKlkuwrgzv+iDpgYoCbfOrg/EDdMMDUotxqiBbTycubX3vbfP9w508/SsOCZ9Bj9tQ0rH04l/ihMJR8mLy0XNHkr1RqoFl8RQA4jCuH/DPJ041jhrNZ7xJW7Mbr2u+u8H83n4Z3xjAMRFEomKTOiN+M0vzO0NtMv9COmGQAOwvwn7RznqttEx7q/YMxB2rLkl/VQAfwHuRMnJEgzwTjfMeglOCKQG4QOIwPX9ZXkd9b+0CPFdbFxqRWvE7SRupHRtPEfCZobCipEOpdQgVAIPwY2/jCOIUYNrv0k8QTzuP6H+zP0+eyX7iUEJxRtGlIgZSqkKBkjZyeHKpgxli2LJb8lzSQGIyUc8hT2Bgj64/K+3rLMaMPJyCvRqtXX5S/58g1MG3EkdS9zN/Q48DKcNAo2CC8MKW8fgROWCIABGvfp4sLPqMlF1fXgPfC1BDQPpBl1Kfo2SDtOOk40DyxCJccXAwp8/dHqmdsj1AjLqrsOr4er17FYvHXHl95B/zYX4iRnL149eUjLQOo2ezEZJQ0R+fx071roCvR/AW79wPj37r7sk/oZBzAMbw57FDIN6Au5FbkczySsH7sfCyNvIbIeVBe1DAL2f+cv3NHLecXfwsvGRsyV1yTq1PrWBH0ImBRMHpAhQiJCHbUdCiE2H0IY4g/wBd/6n/RJ6rzZQcmiwj/NjdwE6of3qwNxDRMY6B8jH+wbXxqWFscPVAnVAWb3aOpg23/Sos1ewTWvAqT4o3+q/rjp06H40xFAGrsiLzV1Oo4taSTBHCsOWvo/8MzvqO+L+AcCmANxAaP55/rmA4oK3gV/BmsPrAeYCIoYIyJrG/AXRiCKHJgb7BzFFhUKFvu09S/oWNuF0+/M0dAI2QDiWOeN+N4EzQBUBjQSABueHL0h3yZCIUIdGxonE+IGjfsg86znptzP0TnTfd+64yDpGvyzCjYOyRPFFXMUXxpAHnkXFxFWBwT8LfZF6C/U/spayKa7LbCYr+aunLRBy5HtMAV5ELAaOS9iQ4U9ETKcKMEapAft8j3sk+vz8FT4/fm+/BD6xwFxCscGSAoVE88XNAxUDGEcsiTmKT4kHx9EF28X8h2SEVYHxQCZ/N/2jfGX627atNVg1fbZi+np+PgDkgTPEAAeCiBMIggjnCYXJwQjohSIA4v7ePKZ7Hjrme2B6eXlvvPWA0oMdRg3Kegp3yBYJSErZSSmGyUWHQw3/zn1L+nX2GzLb8lBzEzJ9Mdxz/TX2d1U7PwJtyQzMXsztjMAPs88YCsTGZgJDP949VbtBOZi60P6yP7VBAIOyxXsJwg13zioNagykDCQKgQq8ijiJw8ZNApEABjwgfb3/PvzrvFg+uv+i/rz/5H+uv1EAywCtQYlCx8OVggrA9YEAwGl+dHurPIQ+9/4Avnz9ajyIvNg9d/z9/lQAiL+ngTgDSUSJxG/CkALXwvgB80HfwTS8l7nHum43u3RWtQf0+nHaMnn0dvQic+w0EXRuNdQ3mzkK/Mt+lTxm+gO9gcMZRJvEawI7fWd54nhm9N905XuMgFKCL8VxRMREgYgcybZKSEpvR+sDWMFuP4A8qrtwt010QrgSfQv82L4vQ17CBkGWhHNBW7yxOmj6TXkTuLE4onfP+Sf9W7/Iu3x8tYEVPQx+/4QOAaOBjwbbQsY+pQIcwBB85X2RfqX/lP/BQBQAXb+twJMCu382/ieDPIC3/WzAzH0StpJ5Xni38cKzhbaZMkWwRbIM8l70jvi0vPmAkAMgxTZFEweTi1YMTooeR+YEOPv392R4PzisOqV9asA5gMPArMMDxVdGt4aXBrqGR8aeyHdHfwZBhTiDskRUg5UELULcQdpAiLy0en84r7czdiB3SXnrO7O9Tv3zQSeCPYEKxm7HRMP5A1tHZgXYwz0FIYIDwMLDp4FeO6+7KrzM+SP4Sn01P/U/bcNdxuGDtcVwykpF3EHvRtSFdL+fwopDcDuWuH139/Wz9yV5wbdws660yvfJ+v3/TYX9CxIMfZDzVNxQEI4XEG7LscTJwdW7wLvcQdg/68D6CHVGJYhcTvXNKg+lUy/PVY6ZEGwO2BIz0JeHn8myy0+G3kiHSCxEBcQrh5pIUwWlhUCEYYFbQfmFH8U+BgzIfQSNg1zF9UQ0QTkD5gtYjOmJdUp+CWcDSsEYxFMCHL+DQHp9rrrP+0PAREJfwghGX8i2xU6GR8ZXv/2AlwZngrI+n/1wOft18nFtL+YwOG+osMQy7DA2c8k/sERERTRII4cSB0jLCkah/hc7JXZF7V3uAzVm9y+5poDlA9GDnMgSDQALPQszzJYHnsI/feF7GDnBvEi62rQwtJi47znJ+iJ8T3wtuy890vpDuQ78arld9Oy0O3RwtAc5+/sWOQQ76X4ffHz7VP/JwWV/gz+vPa83LbKb8vdxePBttdu2eXPf+Xt7VzeyOu4+4HwuPNW+vvzaPdD+M7p/uRH3wzXzdIMzi3EoL11xNPMnskMzRjgVNnX03LyzwbM/NL5lA/4GkISTgwdBFH1K/a28nTk3+ij/RkJn/6wELAksw5MCZATQAXcAB8U0wvf9yUPJRs4EXkSMxriGggbSiXREn8Eev5g+3L4S/SP8/PjPeEW6j/wMfhZALr+Ofcz8UvxMfd78HLrWvn79SnyGQEO/1H4Wwe/Ck37yPoU/8r5EPnLAIP5CufK4b7d0dGT31HwrvOQBFoQ9BWQHOARFQa9Aq7ldcx11S3MrLTluWa4N6lrshDMauLS/LsStQolFiUwfyaoHfQeIQ0a8P7cLdZF1e/b2+wNC+QpyTcpRgxA0TMQMwYg4BFdEcsLxQE0A1j3O+UE7rz0xwMCGXUhRjT6OkQ6RjwnNx0oiBSvBJ/whfHO8O3eVNwp7XDz3/VfD88cTh3fJgQoax+uF4YUZw+uEhEfoB/LGRcYzxpjHTEbvw9vB8cL/BDmBGT8dQofGiMhAC3qMhsiWBhfFLUGjfLC6wLpe9744ofqdPXh/TACOBB9I6g12TDmHaodTiYEHpwR1QsQ/2zvoe6V/fYJjhvTMBM9QERcSWZXL10MVLhBriN5EIEO0xiYH1IltiUNEycHMADz/UoCOBioJ1oarg86BhUHeQeBBlAKVATt/KID3hWKC1b4kfmB69PXsN1q8vX5bv7oBnEJ4AgRC3URfw6KFnUepA/HAu4ErP7A5azhJPAp8jnwlecE24HjAvsFCtwKHPs79gsBh/jO6zHenMuk0dHeRdXhyprGibm6u0HNM8xD0dPi6fR9BPYFLgaIB+f8BOSD1xza2+I36THtPfcC9zv+5BCSE4MaNSO7HpwgIR6KF2sdJx3cBWb1+/qvBWMIqfq89BT6K/9dCq8NAAGT+Vj9Av5rAf4Jmg7BDOgKAQamAPXx39dU2JXuYPpxAQ0JqA2/DOoIiAnaA4QBxQyeFccUtxP2DlkBsvYU7DXZpNPx2x/TNdgA5/HzgQi3AyL6XwrDDtD6dPLd4mzRYM6gvyevfbhGvZfAAudpB0gAT/cO/Wb12ebV157Ivri9stPBAtgI5FLvAACsDeoWIRTLCdMG3BDHEQr60+Up8FYDOgoDBXb3wupH6lDrIPfPAGD8k/ge8I/1xvuL7/PnwPfX+grwl/RD+nb3aPZk9ZoBuQ5AAy4BQAWMAX75Tugz0y/Husgz1ardM+LK7xbwdPVKERMYVhtULfovSCDqGlwhpAMG4mT0KwzgDeohuyuODsED3gkt+NfqO+2L377f5f/sBcT3ZwnFIuQn0Sf6JWkjHxzsGfAbdQUG+z4DDQUbFWEgqiBtJ5YpBiYIK/4t3SQNJYsrwygMMLA+7kZ7VNFXl0xvRCVFg0++VNVMM0Y3OYgbgRBxEh0AXvgO/fXwbO7eAnUWiSEbLl45NzVgMGIs0RjoBFb39edi27LZTtWbzS3ZFO1e9Jnv2eyn9Mz+kAKcBs8KsQkuDC0VXRMrBcD4Jv7HDk4T8g3wBe38bPj18znold7x4Y/0TgUZFMMT3f+MBMUTShG5B8sBXwmzAMLvduuT5BLmHumZ8DP7RAILDvAWXxTbEZwVZRXVEDgOrQW++wcACwgpA9T8Xv+L9Qr1ABZvKlQm+inoJcEKDP9bBX/7yvE78LzkL9BIywjck+uT+gb+aPWh9wD8J/PE6IfpAubZ3UvfXN870uvArrmLs+GmZ6Vit33PL+Ow78LvUO7RAGsNIwHf/BcAQ/OZ4K7afdMWyNnDecLRyXDT49rl4TPgzeMU8H/0J/K69//9qAO3EhkJLfAa77LpFtkS2SnRbbxzt5HEH8sI04/levecBYoONiKgLFgnihiUA7sIjBZ9Ed4QcRC1DMELfQkFDQkcazXHQKIwuRi1BRT2o/U18vXwePRm+WsDTf+GAAb+XQYXIOIm2x8JGT4QfwYuBWMDCvrZ8JHledluzaLIpMp9xv7TCPPLBB0MLxtQI9McmBjPEB8F/gSYB04C4AI8BLUEofxL7LzjK9l3z2jVidmX2rbnsvK29wLwavoVFTUhwR5jDVH+tPTV6EfjCNuky9e9h8G+2wb11QTiCHUVUhBzC+IR4ifmHKYZbTyy/BkOLVR9GKX/gSAlASj2AB6xEDgDvRD0AzgCJRy3KLYrdTU9PxdFM0A1LgQfjBdnEYEEdPuGAXEM5hH4Fn0b8BBQChkLOgV3A44D9giKDFkGzwkVFVgV+hYrIKwklC6FOaw6CjeNNxM0BCzPK8MvDy3ZJRMjux5QGB0ZOhtUF7UbTipvK2Eh+B0RHdUgbyhYJIcYPhPRDR8ACvR06Vjgbuen9dv4yvWf+m8KrBU2GRMabRs1Kc0uCh8bF6AVFwrr/xMDuQZH/7j4J/Mp6nvpfPLt/UIBwQB9AMj+twbFAk35g/qh9IHgi9Y74SfPwsVO1znIj7YVu568TrmcuLizPqjfoYOoZrI1vdnUAOXv4WbxCQj4A+H25fVQ56rPptwK4C3Ij8mL06zQHNWe2FzOm9X+5bLjWucU9679bwKxDfoHzPtw+LL0p/MG+o4FMAQlAr0D0PNm6u30IPbj53/qifQc8Cj2dwGsBykN2RNxGwAjFSULI9UmFSrRKckrezD6MSEwNzHlMCUgPBXJGXkVVgt5ETEWDQfXDdMobS0rH9MhFyvPJF4i9B5rGFQS0Q04CWEBT/tu/bMIMAxCEWcTYQ2SDncORgz2EwQa0xpAHUobCRSvDjIOsBN3GcMU8BQfF+oVTBhCGmkWng4PE+YghyNIIXcmYCiDJp4i9BzkFXcK1/wK7M3krus/82z8AwOAASb5ru2b6pnmQeZJ7kvuduxW6UHkruVH7o/yUfBc777sNemB7GLo7+G634fbaNyk5N/vK/Fc65/sBPAO9P39EQYJDMr83ebN5BDm4drXz0jJwMKux9HTM91O3MnXndZy1RDRDtAAybC1Wq5Ot7K6M7rquyG+QchS0hrTgdFm1KbNwsgr1vHdBNc9zrDFl8Dnxs/O9s87z4fTHNov5lr2+AfuBtn6dQFhAYPzL+vC6f7h897N41Tefdiy5UHp69z85KHsvOlc7AT7lAr2EMEVtRaKEh0QzRPkEn8TKR5eHtUQqAvkEgAecyQ6Jb8oPC2HMSU1okEnUJtZy1zXUplOAlEKSxBGN0TZOKgzGTz0Pt8/nEUdRydKQU0tSItAtDwZNS0rOCjXHycYNBvyHAghjiwrMVIqyyQRJeAhpCHbJWEksB+SIZYgCRXZEDYRPAqOEXccmBq7H38k1xykFB8ZCRJ5AvAHPhNGGL8YXRZ9HNcbFxWxEJoGev0U/SMDFP+8+pwAeP9w+n8BNAofEYYPbwqoC+AHj/yl9Lr8ZwSkAi8Q5hhQCZQCkgGSAwkH9ANZA5gN5hM4FqYj0yt3KjEpOiG5FogOSAhWCvQBxvWV+NYEAAtIBjwAKQKr/qH7dQMg/674ofGX6QDkutrf03PWz9+i4ArVTMYAuC+3I8O4yhDTZto11ofVENT6yHvK8c/J0mLVttBFzQTQK9H0xMu3/LigvKC9GM5N5kHrSecl55XioNM9yNXGLcRKx6TMEMjwx5nO8dXj52LyzOUK3nDe29YrzUbD8r0huXW6Dr7luMe8/tN07L7uBu8I8ovwGP0wCVAGZwz2Crb7+/3PC0wPzQzoCYD+XvXX8zf1evY59Q7xFvGw9xL5svkJA+4LFxVOHAIgWB0EFmMOfwQk/xr9n/pB8UXuyu+q56zhheEW4ZPncPUE/XMBmgmKDhcKIQppDLMIlgasC1AQtQtL/l70P/6KCSEPkiD+NLAwbybqI3cd3BGICbUNUAoFB+gHAwpjDqQQ9BiFHKoVMRY0H0wmoiAjGRkTxQYRCsULWQBB+K76IwPsDgkSFxD6HbshpBCIAN4EfQ5bEbIdzyd9KI8wdzePOf4/8DryMI02eTknOYU4qCqUHb0gdS7oOARI11diWxRY21EIRqY3CC6aJZAayRBKEPwVRBcJF/4XXRg1IG0s7CyyJUYkzSB5GwkcCRtOELcHgwpUCZgQbyB3Hy8bXB3gFwQQYQ2kDeYRdxBMENsaZyIzJNEjtyTDJOAdwxRME3cSdQsABBD7i/5ZAt307fcbCj4FAAGDCtwDzvjr99v1i/DK8EPwWOdM3rLbR9873dvdFOg97yD0h/shALr9mAIfCScCUf3d+HLzbP84CxMGpAIW/3z4NfaZ+5n9ifhP/k39KfBJ7Vjvyugp3D3RHdIO4KrjttcnzVzGh8Yv18jmaueh53nky9qs08TLw8TNxQjCQLhcuaq4BLLFs9247LzRwLK6iazDro3DL9Hp2Qjk1emm8Q712e0p5X3e/tM/zkPOOcr+xEHD08Ixv9O/y8kh0zfZbOJU7mTt0eR73snPL8Y5x9nMntBD0tHTJ9Uv0/rLf8282kHn9++b88DxVu0v6E3k09xa2Mbem+VQ6dPwwvY/+Q0ClAz2DBERmBptEh8FAgcDCPAH1wmGBegEAwrFCQ8CPALU/0X2ru9/7ATnQ92y4dPr1fHb85X1Gv0I/5/5bvEn6ZPsWPB07Sn0Dvt98yvt0+9u9bEBThHoJAoxuy4vJxcesBUNFSUZ8BR7D+4QxxUNFfAVhRw6HtsoSjS7L6Yw7j/FRyNF7EVcPrIrVB+gHCMdayGDJ5wkEx7uHeYcWBnLE4wQVBNaHNknfSwrLtsrZykvJ2sdPhkGJQYwuCvHIhsc9hXFEiEaSiTbKsU7/EaYQndAd0ayS7ZBzzRULl4nUiGmGicV4hjmIP4niymULC04qDspOGs38jLsKMcbJQyqBOwGEwGZ+68EwwmSCysV7BbYB1r+ZP0yAAUJcwdzB30Pjg13AkP7K/Ry98EF/gK49/f8vQMt/EX99AfeC7IWqCPoHxscxSDgIi8d7BPqDWMNOgkZAaf8dPI56HDk5+FU4o3o6/Qx+9v5dv+YBIEF5AN0/zH3wO/Q887xl+2P8N3w3ew53n/N9sbEzVLfIO5B9Of6+gJUAC3z4ewl7pX2qAFlBm8ROBrFDR78g/mqAmcOCx19JL8cJRlvGNEP8AgLBaf7zO2f483eed2P3JPfsuC63hDpPfpXAEgAZQFe/br0svDK7AbqYO8e6AbRJ8uN0fTOddH+yoG537nDvy/Dm9Xr7J/0qPMm+hEF3gmIBcr4ruzZ6rDv9/Av8E3pm+Yi6SPnT+509wkBLQ0dDycDOgFEAHj0i/BF5eXXg8910eHUENh05fX2swbVAIoAVga8/Z/31fnV+ZXzAPNL+W791/rYAkwJAwnDD0gYbxx5GMMMMAHDDEwaKxf0HVQnCh9lFL8NsP1Y+ysLHw+QDTIJRfpc51DZqNIc2+fon/dhCy0J1/ZB8G7z6+4733fSQcsazX/RwtaF4gLskexW6KrsNfMq/NUJJRW5GTQPuQSB+Ovt8/VUA54FIQTLBYgEIwBc9Zvjk9ud627+JQnJEVoWyx36HJAMdvbM60PxvvMY7/zvHO/A4arXaNNezfjS7+Oq8Dn6NgbXFVwfsxhzC1QAnAa8/OXkh+oK8c3ff9ey64f81P6CBOgR8BlGK/g6GUDbPdEqSiW7LJIxRDBGLZYiwRCiBhL3Auda4xTvuPYt+fwOBiHiFlYNSg+aA+Pwm/EjBNEOzw6zCRkGbQhEApIGrhaJHCckkjD4NtUx/iKoEKQDi/2u+Aj3f/gz+7z1L+nh9eAQIx0pKs0wTiE4G7smCh9fELcW0xt3HbcdFQ28/gAHgQ0jA6H0VuoE3rjPf9H1538DWxIAFV8VkAzQ/wL7XPOH6kHqh+z368zxKQMe/CfsneVw7JQArAbqGfg17jPNJfwtCj8CPm0tESKHHfgZnhieDQQXvyvPLYEoOTbXSWBCBDnNLqoxWjamKtswFzKUGb8JPhS7HnUU+f/l89Hmttqq4FTxrPty99v2qwJAEogXZQryAEABNgUuCsETIxmaB+/y2+CD0+PbdvCL/44Gsw2UG3UbqBIrEkACcPDj787pf9hm1N3gjehw9vILpAxpBxEH5gPNAmUHjA74BEXxKepU5CXVh82o0QrTXM5YzN/MJcZKv8vAycRq0f31bQXA+GDsz+L22lLUJ97h7A7vDN9J22j0Ivrd6nL4bwXwAq8OVhiuJpAzOjEKJOYiSjVWLugVAQNs9HblBtt75SDwbOZ71aDWGPAi8mbfUt4A1TnIhdWH8uwCh/y87SPiI+Cf6EHp+eca3pXLf85u1gjeeO5k9S/t7+Qn5yXqR+439OP6FRVcJrUfGR+YESb/rBB/HoEKNAdWHlAf5BO/FYYQHwen+Qzggc5Szm7Q+MqwyYXQqNRa3uXozOSV307lz+tW6F7f9uCq8zX+39sxwkHEx8pvyEK9h8lczkzCI7l7wa7hRAvqIO4tsj91QVY0iyT0JsMsRDKqLPQfZybuGb74tuxo9FT2Q/ZQDkoc8BXNEqgMuxfeHGMFo/o/9S/rEuNa5Tn2m/bG8F769gGp+Ajnke3A+gz+TBB3JK4nXh3qFoUcrCAnINcm2SsvJfIY2xFUGBUkBijiIzEkBitQM1oyYCJnGwIbGRXNHNsj1yDBIWcgBBv0E30E1fgC/TQCOgITC/YQRgeA/q7uUNiBzxTBHcLb12rPSsPL1OoC+A0dBuIlgSy/HFsRNhHdICMrkCWUKOgyXj8hNd0m6DZiMG8TRfmcAfAVJw6iC5IbMTtMRI0vIy+SHTf5Q+rX/csd8ggA6CPm5dzlyhLD19LP2T3FVMiy4kP0zv1CBDwVhRo8FX8XlhnuFC4E5fUS9qn6NAMDCRL/P/eT/ysExwCCCNwPzw2uGz4yWDofO3ku0xlQEl8DuO357lr6WOxD4HjsP/PM+fQA+fb87HnjI9d11DXY2dlY29/pxOx/6JoG/AUn4M3HwtroA437dQAhIUwcyP1s888OMR9vBFj2yvOV5Cnpn/L2DdcqvzNcLHUmH0I9RdcdcwoEGUgt2xhzBdENNft91y/Kgd5m2JGzc7FiuDPB0clF0jXqsOeL1L7YLe8t/THvBOWw7+3tm+nf8RD/lAIi/Sj6HPWB99MD+AacCBUWyzL+QN81qjNWLyEcvR2uKFwj6BslFeYMrQTcAwAHiAi9BGb8k/1QB/YPtRCODr0TyRCEBUgDk/la5q7WcM2qy6DNquxF/JPood9c6y0NSAy29/4ANghe9dXtRBYXQ1ZDaTawM8calBGQFnsfrjEnLNMZOAy/K2pNiS48D94HCwbE9XLh8+o3643ei9+n/pAcIwV/7DXofe66+d/0Ivrh8sTUCs0j3Xvwk+oM0OPCBroOuMLC9tqs8Qj8mguoHEYdNB8jHn8V4hUPHaIaXwvO/zv+FPRL7fHyzPVs7dfjcO7A/bEExQv+EW0SDwrNCKYJKQEr+YXq690e2BTNXsnjygLKVsFEvcu/cbOqtYPS19BSvpjA/u/oG2UV/hC/GFkIBuZw54EUPitnGfQQcRA0FfwtkCmUIv4oLx69AQr1eRRaHeAJLxSNOpxJbSpYHqIdawKL8JP5dReiGA0A5fOy69LyePKJ7cTsddW0u1q68s+w6O/yxvyJ/o/9xwuwE18SQhMpGeQgLS0bNUgqtRRSBvgFcw3JCeIB/AQW+Z/gGOIU9uwCkApQE38R4gaeBIoFGRJSHTQWtQ2vCfIFSf0m9r7sOdvpz67M6cXRw5XJHtqH+N4JZRcJHcMCj9jf2Nf/GP5P/skhhycsArzu6hNAN2Y2ySxQK6woLzFIN/Q2Ak3pWCtKGTZ/NXM3xxPP6hjumAUbAzgAbRUXHHEKxPJq+S0JuPV45LLa4dfG3J/vmhCsEjwEHvjQ7arspu0A8Df9pBT2I88czxW/CgD+4/pJ9azs9/PI/NDtJeGy6Xj4IQ0nKggvBB25GkofCBuwFYETYQ9KAqPzIu177aHwyuvN4KLXBNZayjO5rsLh1RTdAOH14vrcf9TL0MfTQ9pg6ssFpgh7783V7+Ry8arg7+uZ/pX1XNm45G0UjijRJjMzED5OMW8m9BgnEXcefSD0EhURSiX0JSj7c9Zg1+PgsNuw25HocuXvyY3LifHFBP4GcwVvBDH5z+i68Nvpf9Jc003qXv8lB4QHVf289lbypusz9gMGzRB5DwsB9/x5BjQUgRNlCyMOXxEXEScXtCSkIoEP2giiDF8LjgEm9tDsGtgKyN3Iic4f0sjWute63QL0AwgXEPgU3hjcEV8GggdWCmj+1+Q73Y3hPeF06qzr9NQ5vvzNg+XK6Df0UAbTEWkEYPtdE80svy+mNxBOIVExUtFNnjmOJbMPuwHV+qQLvydlJNcQaQ4JGm8PdPvYBUoLUuqb1pns2ffx74n4IQ0yC2sB9gygEZYGOfsS+ZYC8gvHEpwXXBX+CvYMjBfiEXMPKxnwJCEodR+WHpwh/BSvBTIJfQQp9Hb+hgwO/TX5hgqYEWcK2gSiD7AW2Q9WC6gO2xM2DDID1wbeEUwSewbiB/wMFwEv90P5FPnR7EHk7eHr2dPJvMJ72Q708/urAOgYfzLkKZYhmDMEPj4q/BbBGkojNhxtC1IJmhYfG5gTrhXqH8cdGwzb/IEMdRsPA5v2KRPmKAQe8AaP/E3y09241dHautrj20vgYOgE9Wb3GPW28LLtsPJq9cz6HwUJCD/+n/N09tv24fab+Ivo79fn2R7e59Z94xb+KwFu9tf2wQGL+ofmANxu2vbantb13NfkxuiZ8cb46Ai3GeIUpAOp+EfvSeot6IXcxNR3zhvL39P84Dnn4ekg8ev19fsU+njqCu3p+ef1GOz86mbzeeiqy1jNi/Gf+Nvd7eTBCQIhGRwyFGEXqh0KLbw1EzuqPoc1sCCSCkAKZQbl5MDLpNTC46zfsN9e9vf6594A0DXWfdA3xkHK1dl09IYO4B/kIqAe7iZYJw0WYQsdBkX3zeIK3BLlT/Fu+icAVAk2DeoFjAEdBLD/qu1y53r7HwsI/DfnkeR28LcADxVOKLQjMRVvDiv/+ev867T6KgBMBAIJpAagBMMD5fkC7knwKP6gDSMSAANY9K7lqNO+01Ld+/O/C+YBMets61j4xu2y4xLzywnHEeYRMSYfRB1MuEvhVQpPoEl5QS0UbPA58invP90g7pwUiA197J/0OhA6Cz/2N/j0DuwL0PyEBCEIVglUDwEFpfBU7mL/j/9y7wz08AMdCEIQkCVvNeQqQBZQEm8Q//vf50HyBBEpK44syR+DG1IKh+eq3yj8uw5ME2McxRi9DzwJ3f7t9kPxmfUpCoUdnBuGFAsX+gyj/cD/fQP9+v/98gmWAzHyAOPX2j/UO8cSu8vCHdH+ySvHTuLgA/gTvSbnSzFWHT7bJ5YTXwCV9iv4tQFcHQQ1YjWJKxEmdStrDqjdJ9p29aXyidQQ4sENUAsI+AIPmixrJm8SXweQAc8FaQm++6r0IwkbEqoCPgbXE0IHYuqq5aYKITS6MHMcyR97Gg7+EvQ3/Tf6VQGqDbcEmgA0C6YDyOdO56gHOCGFJQggnhgLFNoM8ABQBIogXDYpLVYeiR1fGNMFifFN63brBO2l7v7kaNaszTvRsuaGAuQDjegp0MW3J7GVxKLN49Ou8XkaXiWkIG8uk0igTIUpvRtgIvYNeu1e4tXocPMnAUgKeQLmAaYdcxbb8yb5CwlU7VzFKdO29y/zdudU9+H9fvk2ABEDWwizEDwTNACP3fXiifVi6mDw4BQCKOYQCviu/Jn4/tq+y27WDuRu9MD/T/oA8z/9XQZ2+dHvAPY/9knsj+yT+KgJhRb0DtMAK/py62LOYrx9wU7Jg9AW3aH2BBMHDIP2K/dJ7pHY89WL2OHgsPJk9+vuieq26JfdNc9uyZ7SyNkC1FLcne8O8nTmM+ScAiMXlhZ1Gx8S9gI7+o/xEuqq9tUM7hmSFcsX0xmf71rZ5+vU/wsKAQLx/JXx+tgf2Jftdv/TG6I5sDTJKVYxpC6GCgDxRgbRFLMONhA0C8L1nesx84PtOeD42R/ISLEvwH/jJvqqEl4hkBo+IQo4HzVzGdgFmfp05tvfwPsFEtENmf1J9YHtM+RQ7rj4Cv7uChcYex2KHpogyyANJhUkoCSmLL0mcRIU/DXh3cDXut3L59cA4K7mi+S627rgBweyKzMqBCA8LKRI404SRYU64yshNVxIWD8ILWs0QjCFEi/2nfvTEOAEeQFIC/QH/gBSAEf5WOyP+VQS+BzkLzdR61bVS+FVz1vRTCcrfQsRARz1Pen35bLlBuEg3lricO4U/lX9VO+w7FUBcxaLJvYxRDKNMoc1zS1QEufwZN4A5TPyVPGw6eHeh9MMzNfam/Y0ElQzNT/4MOwqbSsbDrTxwPUm9nz09ftU9yfbRs5m27TbsM1Bx9fIDr8KvHe/qrozvDPECN5IEHE65z3XMG9BeUhKIVH+S+7b4KDcOd5Q4/n/nBN8/FjsAv8RCzfzxO6l+bLmCN2L5mLnPeAc6TP/wxSYMM1II0zXO+EyQivcFcb/PeZxyai357vJvFK3N8p/8B0DhfSu7ivpUtn+2/zqEwRaISMiohJbDg8RAhX4FrMPGQUFCAAFcO6H5ZPpIufE68D8rwgEDY4VLx25IUgi/CUGKQsY0wNL8uflHNrE0CPK6bsdw7bfGQNMFvAG9/wk/RDo09gl4UXUastm7eIPuxm7HBEs3zjLPuo+wytUF8sCVOwK3h/btOHP5b7pHvREBOAKnBJjFg0D/val86TqKd+V0XHK5db876IGVCDROfxQ9lhcTew1jAn21om/9MOcx6jQ/OBo69X8GxLBHuEpJzAtKcEiESiaJqgUm/076yPo3/I1/ckBzP0397D9IwesBrT79elD6Fz5RgbqDZYY5Br2GXsX+AkJBzYWYChKKLARRge29xLVrM1W3tfef93p7Uf5yvqy+2r+qPZw7In3EQiqD2EShxltHx8kzS0ZKSEeexXyBIHstuIv7qP0Yvm6/qAABQaICbb8L+rR6wLwHuyF8lQGJSFIJRcTYRG7C8b/Xxh3MwotTCmLMdcmMgp/+QT07ev+6ZHsleeu5/7rneHP2bblEPCF7inwkf3DDX0ZRiCqGOIKoAaJ/5PnKdSe19Xg8ebA6nvgatL81dnhHvllGIwUmgHE+Ofr4fh7Co35aPUJBcsARff88WDn49mH1cLeYOSm4vPdf9TTw9/Amdb66rkBKyQ7O1g6MTcvNj4dBv/f+7kEvQDv/B8AlfSL6ArgR9Sk26r2VhXoIhUYtwnG/rbjUNfI9L8GqguWHuEksh1EJFYvIyzsJ4Uk1RqcCsTyCt4t02zN6drb+6ILQgivDTQPP/0i9XL9DwJACE4UjhfHDycKXQYDAKP0Yuts7jP61Qj0Dw0GjfHV4GLR5dUc8RD/OgLBBzgIuQnHD1kNmgQ5+/zqjdvV3mrrIu7K86YHjA9vA8r/cQIe+uXu0/Gf+AsEmBglIgokViYxJwshXRiBHRsnfx0tDJIMThMLGy8aCwvBDJwR/gUPB9UUZRRhEZIVMRe7FhkQmANbA4oKTBYKKZE0JTo8NXMtXC46KPQcBxTiB7zv/t244qTpDuoO7kP27/0VBnULjAoRE98hBB9rCxT2VuY55OH4YQjl8ifirOAM1MDgl/Wf7PXtlf5D/gr2Guvz2mrmOgDgB1QViR1bDxMCUfZQ3rDInsKNwtW/SLyFw5XI9MVm0PfqrQfiFAYXCRuWGkoUQgvZ8uHYKdgI8EYSTCVvGDQPfQwi7c/hwvPr5g7NVssW1LTVctl97vX8IwSwHj4u5iRMHikbbxFAAD/rGORe9Ab9EPQv7pvy3/p3APAFYxBfGFIMP/9Y8/zfJd7V5R7ng+3M/tUdMTnjMVIcxxSJ/ufdsuCj6BjckdXp17zZl+WV+1QEUAkdHVQvXCzkKJYmkBiGCZH5++439VkCkgK8+wb2S/KD+E371P7eDE4VGRSoEJQKWP5k8yXnP/EnEBsv7UmoRO42/jgAGwLz2/91DRz3aO8/83vrmfZfAlQEmBrjNmg7zy1EJ3kaywJw8X/tifdfCoMdrCUAIogXKQpCAE3/9APFELUbBQ/n/wz7ienZ2JHeDuzl9+gWFzzVODEmvSxEISwGohBAGncHL/5/+LbltuFy7B7rRe8bCEYPsQJ7Bpn/4eWD32bz/AW1FUwiQiMKJIockA2xBxcKEQkyDrARmAMr/f36auJgyWrE9s3t1ZfotRKOHJYL+hbFFlTyQe+/C28G7/WB+MD1xvBa+04CggSkDhkOrAVzAsD6ZOZ71MjbyOqd9JoEShEjC2b8cvaB90/3JvSj+VkHAwtrAZH53/E56JPhh94Y5C/1wwu0HpQYjgiBDHb7Stdc4df+YvWf5T/p8e49+fAB7gD4B7MRdQnYA0YFevjE4cvJ08fI2KbecvF1D68JfPjHAfYH2Ag4FAcT1wkwC/AINfwI8broXuGH02jUsORw9EQS2xNR+9/+sQJ67ZPvmAJB9Xvq8e899WUDuwuFEHMe1yM0F0gRhgzl87zWRdUg4nDlXvPTDPIVlgWR/xcFlgNdCikTYQtKAmcLfwCd7sTtzOlJ6vXnNe+eDScpPCvyHccYGRQ4CkgEfQft+wTkvOej+OH+HwvuGAYjjSlaJ88lfSQ2GZQAbuSs3mbsPfJ//DIHcv+J/70TGRUHCckPcxJGAGzu3ek/5w7hrt6b4yfm2evU+r0KZxxjIdcPPAAo+RblGtqD4fjYNdOJ16zfj/mQFQofHyLmKvIoWCInH4wPaPcK5hzhpOqEAAIS9BpfH/oXjhq/IGsZQhdOGjwWPgRJ8Z/tVu057ev4qf1e+XELbx8GJm8lxxtfHaIaPgNc9uH7tPEn3oHhaPSgCpoc+CTVIfodaSTFG64O4AzG/SDzGPmkAc0TOCBjGxEZ5BQdEm8XcQ1fBtoIL/TM47zlwtvv2wbsHO8E95/8eP0VEm8Z5geV/SECIPw73pzRuOU75eXY8eq8/3kO/hLWAQT6yvsk8RTuxOh12iveTOP+6fv2WQAACsUPEQtEEOwaog5bCXcIuPih6BLbwt2b6HrrevLM99/0p/Oq74nyHQII+UnnGPbd8+PXqtbZ5DPlQeGf7poLnBfTEh8KwQIY/f730PTX63nfHtt33cTcauFi6KzzbwEfCMMRJxq1Fw0UCQsC87Dn4+jZ4Tvg4+eu8EP7HQQJAS/9zwg2FKAMIwt/FncOFPIr4Bjn0el96iv+wxZ1HGMTUBRCFg0FCvoXAFP+JPc39Rry1ewc6nbsmfgnAC4GbxS3G/IZ5hxCHdcS1QQa9OHwFvrj/Z4DIxY2HYENAAALATIDbw0xGpoMfv8c8W7YaN6L7DXorvNrD38hoiMCHr0YhAsI9ofy+f3+9WrvGPRw62zdPd6X79n+og69IB0jaR5MHssYMgdY8hDqR/Kj/kIGnhQGICEZwxQhDnb7Xvb0CmUgMhZKCgcHYOZO1o/tPfAA9+wfnjIAI3cjVisjGEQCof8HCEoOaRXVG1QRxvWB5Hvv0QLFDrUZUBx1Ff4NyQfX+IHjg+AO56rq5/0CGEodgRbJE0oHVPAC9NcOxyMII1QVMAif8cLdOeEt7TH8tRFEGkARlhEJEVr2FNwU4kn2SgEbDdkMTfoc7CnqGvRbBcMVRhvcE4gMZwMI+NftPeVB6GLwXwIGF/4diBncDoMKqvy45Ufg0+6w/eAMKQXC5innzPTd+w8SKy4bMHsgtB0CE4P8AOp05dXrO/4VFZwVawdy/+n3tu6j8WsD7BfHGZgNawfM/KXr/umD7PftSffwDC8X6BPNEqAGm/O87sjpEOPp53rwVAPXCJwAKwJtCw0Lfxi2KEoabwvuAGD4rOnN3fbdUuaf/28bsBnRCeQG3gFP9i4AsQ2aEuIQOgOL95ft+eiR6H/qyvLmAGsMBxZ1EMEEVwX//kv4N/DR5ADVcc+y2ZXkqgMvGtwTax7bJBUWHQ6F/2bhus4c1Nvhru1/9YgHyRROCagEWA1ICycLmgH+7pPmYusU5XnaIeDK5Ljm5+zS+YIClg3uF6QWrBVOC2cATAMY/4nnYM3RwBLLkdfZ7+AgDC2oG7kg2x/JD8MFOfNB3/jgJvEc+xcBFw61F44VXRe2I7Iqsh8GHUYapgykDA8Il/5L+78A/AI8BfQMlBgnG1oPzRCUD60HWQaoBysBQ/FO3BrNUNWV5Yf4Jx4jMRsjTh8bJKwSm/s19Cfle+R99dgCRgqgD7cRQAjBCXMY2R6YH5Ia5BABBMTwFPDE81LuL/VCAxkFbwdhG2cbew3iDaIQvxO5DGkLBwrh+ALjLdFOzI/S89sr6zQLoiH8F5IVnBhpCEP3bu2V5Jfpkfbr/WMFZRERCen9Hw3yIO4dvRGWCZP+du0c3J3a+Nsn1ZnoL/0NAF0DZxAtFp4DpgMJCAEAMAINBEX8AvBY3KTHGb9QzTPbd+CvAccg3he/DUIR5fzZ2GTaVOkI4Zvin/Z1AYX5JvHr+dUN1x51HJ4R9g9vCOf2auOe1gbiRe/v/vgUcRqFGloXWQy9BjIQrhUlEC0Mywh69p/hRdp/1LDb9+Z29HUSfx1EEUIXbxMK+/HqwOq28ij1GwBMFYcfQh4jGQIRAhtlJrUa3BbPFUwBuOyB2tPgNfKR81AEhxumGVIYcyDbGB8Q4hHoD38PYw4FBXb6wuuk3AzZxt+V5FrlIvcNFkIbrQcXBlP+z+GJ3ybyMe2f5TP1ZwOeDaQL9gGqEL8hRCPsGgkWaxHuBcz0duYY4iDzSge/CfASlh00FgIMyQvNCqgHcQrXDH8KQgNY/mL1Uux96CPjbOpL/2kXdxkND3MSexUjARTmFu1e+AbwL/x/G3kdXw0DCrkLDQ7mGF8aDw/eEAcNBvw76+vjcOtk+TAAzwN7DTwPlA9OC6sBIQS9C2URHRJYDMD+Oewp2pPRhdfZ38blAwLeGGEGcwbsFpQAVuXM6lb0l+yL9EwLhhKDChEGqgVzB9gKfQeiBdEEYvn86TXcLdDA1mjmg/WJ/+gGtQ+oEK8LcwmBCEoCk/4rAywCNfT36THdkc5q0k7eZuN2/KQZ0Q51Aa4QWApq77DqUOkj4O/ntPl8/6798/fM9tUDYw8fC5QAg/8v/crw59w70+/W1dzA5z/xzPeiCW8TCQkwBPwI0wlpA38A5/+R+cDzDOib1vLNmdkQ5U304hBdEHsE7BJKDlr8UffV6+/odvdlBPQQyRb2EDYNrhLwES0MmAUi/Vb+l/vz6dnkZOud66rxl/n+AJgO9BpQGs0QBQ7FDJgMPg3uD0oL7ATK/WTnpM8n1LDhxuPFBBcfyQhMBw0RTf6V9qP3YuyR6wTz3fxECAUGhfnj+fIEZwtpDgYU6hFSDKwHHvwt8gj1pfxB/Un58AItEDYQGxB7EPQNjBXRHlQYNBR1D0gEk/Qa5NnVzdzI9dkSvyKqHFgl3zSBKvIjih4+BQsA3AonDA0Gyw4jGFIU9A/LDs0M+hKWICknWBviFLMYrA8ACqIBYPaj+Vr+KgCl/1YI1x3JLTcrayZlIpAbkA+++8bej81U0o/W6eV7A+4K/goPHrIgQBm1GysRL/mD9P7y0ezz7df6uwaIACn1Lf0lCYYF9AySDVIGTALp/Nn2Kejj2HXVGNkc4cL2IwY4E7chAB/+E9kMIQbK/bz6bvOT4BDRpsy4z7roqf3O/gcPtCTmIV0Wcxo6CmztHt8A3GbgwOYO92UEwQPd+yv6svuQASEQZRp7FsEOZQiP9b7eL9Ow0O/awOa06Sn0DwtOG/IaGxDTDnEQdQe/AyLz6dpk0ZfVHOCN4ZHkBPDRCEYk2SfoG64bMArv8oHn9t+25ADp1fKF/jQFbQv0CIoIsQ21DqoQkBPgDiEFvvpR8Jvcy9X34rzs0PQXAcEUBiS0IPgbdxjeElcF4/cE9ADxO/Bu/hECpuQ521rwDvzXDRsg5h/VGZYcqBaq/evsaO5H7ontePuWCoUPWQboAlsEHQg2EpQdfx5/EycN/f+q6fPdfeK46vHoEPOQAf4FSgkrDF0JMABF9fH2JvqX/JAIUAMA8iDpDuHG6rT81QMVGfgsUiqaHLQc2Qzj7GzvPf0k/MsB2xEjC/32YO/x8Yv+QBPoKYUhsxLXFskVHw0JAAz0HPaw/68D5AfLDfoWHSCSGRMPQglQDKYROhD8Cb7/Rfmw4xDUJeaB9S/4vxGHNKY07iZpLQsk9An3/yUAFvrM+e3/3fwv7qznFvAnAIgWRCZWHuwQ8BKQE4D/ZOhL43bpyvMx/l0ISg2QEEYWaQ+gACwCTArgCCUCXP20+kXvOdwA0arZAuSl6+wGOCuQLScgsiUpIOoGqu6b6lz0M/NU74n0++/r4/HprPlzAgQPuxjFEUYRcxHb+93gUNvx5evtVPOD+p/7MABWB/AJNg6xEegRywkLAJH/5fkc6DfZZs7JyM/UHOT9+jYdjCPHFFoWwxWaBQTwK+vI83LxP+3r8pn2S/BU69n2NAm1EoEXFxcJFQIR+gXv+PHuDufT4hLlieqj8vX6PAIvD18acw1lAi4G+gFH+9Dx6eeL46bS28Ns1UvuqvF8+9URsRWMD0ISHwdB6y3eQ94U2HPRFtol4tvc697X7aP8YQRdD0oWqg1ABCj9meuN2HvNTs3l1qrcqOLK8XUC6hG3GtUUBw5nDREG8/a89Kf5UOkK0KbMWuGl8V77/g3JI3kphSKoH6gVFQO0+t/9R/4K/toLCRKsCMEL0RyLJbkmoC3TMeEt9im3ImMX+An6AHsCMgLHBN4MpBXoJZovnCZpIkwo1ST2HV0YQAql/fXsyNoO21LuuPzqAeAZFS48HzEUnhXyAWbkm9SH1d/ak+H556bnid8U2+/gl+wTAqwSBBLFCUYFgwoTBIHmM9tJ5QTj7+JN8tYDxxi4MKowMyQnJxkmsxq7DF0G2/Uc4dnZedTf1b7aAODQ8M0SgSbTH54V6ghq6RjOg9aw4Z3gvPQXDCECyvLO+Nv/7geeEZISABBlC0IBEuyq1PjM+NBz0dHTfeCb9N4OtB6uGEobJR7PDGb02+fG6hrpFuXT5JPoifUz/qQA8hMnJ1QeLxYPFqwIEPAl1v7Je8tczd3TAtpH0ofKGtWh9y8VjB5nG5wTxRiIEyj+eO9Y8cbzFurp7w0Gkh26NjVBXDoxO8VHZEW+O5QwGR2aEtkPywSkAS0YwyIGGpIcxSlGMOongxUlBXzzbOVg6gr61QbJFVIcGxmJItkwqjTPLIwn3SRcId0cwwso//n+AwA1887mwPK7BHkUZxugHbsm7Ca9Fn0FRfsv8evnwuOm4l7i9eor9Z4CShX8GIoMGw36DVP7EOPJ0UHG7rkOv5HRd+NN64fzR/vl9eP4eQM0BkIDDwaEBKHzuOXI6rj5tPts9qP8yQyyIPQs3TfqO6QrbRfPBs716eYz3dXTYNVm4kXwJQE4EPoVdws8AkgLSgfO8GTiP+KT3gLdCO+N/FH2l+Wd3bjp3/rFCKgRwQX99HT1JPnI8A7jVta4yl7DbcVMyt/T0+joCH8ezxjRFf4Sev7f6EHi092u2HXd4+io8qH0M/sbA1H/U/1D/gL1ouGkzLi/7L2ByJvdaPBQ7qTohfSzAQkJAhC9HvgnEyW9JHMdqgoa/CUJGxauE4wYBh0jKUI7a0RtPEg1CDo5MPgg0RMg/uHrP+Rw44/rVPZvAAYVpCOOItEp2y9pHugBfPPx8rrvYvZOB6YC3+zl5dL8WBY2IOQlWiYKJJQbIQjl6/rXptFo0ufhUu8Y7fztR/+MFoEg5By5G3ETQ/Dn3JHlbNlizs3Z59p93Zf66he5GmUOCwXh9lzaKbs+ruqwkbaJwRLKZtRM4SvuaPvHCpojuSy5IwAj/h6sC3j4p/Nu/IIEhg1aGyUjzxpfHWk1DkheRytBYkasP0wk/gp6+Xnqkd/C4i/sWv4xGtkqOi/mJ+wgnh/iGGUKJwGD/NX5awFzBsEJExKiG9Ufmh+kInkgVhgHD/ADtPpc8xTyXPjK+HjzwPP+9fP5sQeJHfIu5CrJJRkv4iiUEwD9QepF3knej+z7+SkFyRBCD68CuP4v/LzvP+Zi6ZPzzPI58Mrupt4/1OncYO99AVsT7iAhIjwjBiSsE2UGMgtCE9oP+hPuHOoc5htrHBkr7DdSOeo4WjZgJRkFYO7E6KTkFuJ05nD4IQ9YF9cRLg13CBcC4f5U8/zwVvjZ92z1JPUE71Dkf+Z77UnrWPIO/Dn3ge0x6uXe5dQ32DXWndSN10PpAAQtCRUCjgLDASsGMg7wDjIN/AZ07TfSsM/byynFycdk0hbpXv5i/A70dvZc6znQQcsQ1brRN82JzjnOVMbvzl7opfe6/8sNphTkEisTZxc8EvP/dO4O7NDxHPKBAysWjBkyFNcPVhu0LgAvAClMKlwlMhTsB0v4+uHR25Hl5/c2EssqriYbICsknhvgBSL+jgOaAlsDUgIc8KLZ+tHV1wzf8+hY9vv+j/3E+3z9J+8C3BrSvtew353j3+7v8Y3yZPRg9FH7VwZGGhMlbxoXEFj9TuPN1YfX09l/2/jlCPeiEgkNofel8aTfjc6PyG7XUujK42LgHtoh25XcbNwK7Z4A1xDwEwcYWBygDUAAnfwp+hMB0xBnGM8TbRCMFa4iNB0FD5ITJR+LMH8yGSITH5ASzu/z6HD+mgoAGDM0sEE8OJgw5is2H2MY3hcjFV0SDwtw/T/p2dte3zfrQfp5Eysjxx4JFgQf1R3HBMD81P2WAKwE1w8XF2ES5BbmIX0kkhSQDuAbdSWyH8EOXBikA67bQ+Cb69Pop/dMGW0ZuRTbEVAOxQ4m/y0HkBOvCbsBmfjr9Grhl+SF/iMGMRvRG1kMWQyaAU//qfyzAAIRiAvYCr8Wpgej+rsIewK4+on/HQb2FIkodyr4FgUSEQCF3s7noAQEDR0ecSvqHvodyR/NBdLyPAJrBH3uQAAXAX/hHuBk6X3zMgpQELMOExdvD6YC7fMm8zvj0enQ+/oDKwpN/pgcewxa6Uft6eWV3vPast4PAeoFwuF12KbNJcIQ0+/R6fzqFIXl+/mV+THUGbORyJnok9D6087yg9p/zZ/f+NPp+Rr71/fwD64VxP6V7YnutOQl7C/oUfwfCc71SBHkDUoBlgXkAfIOT/gz/0H4Iv6gJuIGKQjHANHuQga1D0QadRgyGB0RBBu7B6rsEQ2yFvQNzxTZI54k1f36Gm0Jk/LqKO4bvw7HHHkn0/UNAIwQcO8ZD3kiexjFAMM1YyL37vwrawoI29D72c8n53vp3fG5FJoA4BAc2ZYCBCN48lr82ABR9mbelcI368bqptUn9C4KBPH57BTu2+S5GdfsvQ19LB0B4hOF83vw+ATz6wD6TBff/isMRgieFuQXQ/Kf6Z/9heqwykrbuN5Yy2DQVQDwB20BNAboLZgJaQJEJrzgwOjRAO/aqfzTEdnYKdxfFT3le+8TEEoPhSmF+UYW7g7O8rD609Z8/n0MkgH6EsEYOh9k9dD3KREA72EAQgcEGm0Ij98Q96rDm9En8+XblCgGJOf9XB8dMHT5cOWWADvd5fJZB2D3/gHl2aLYBhS8+6oVISxtF0Yb+hFbC1r0xPO6420H7hjK/OMu2RRzBSsqCvYHEtsWUANjEJQU5/5o89/zM9Kqy6Px3ecm/kY4/DTXKo4jKTZWFjYQ4fD6BisUuuppBdELHRUU9ckMlD/2FmUgISXfM6QX6hEbHOXzYymL818AxzfO9bAe8Cs3/mApsxJGFvYRAwQ+EwAAJO2l7+3vycmT7gDYneRWHSsQJSL4J/wGgwtH7ifecOIW5tfNgd/yDOnC9gtSJWDzAhPqJzgd4gllDl0Hnfi00zPjxv054K7/9iT+5TweSBCh54coohAC4oYNKxd941Lsge97zL7luuvr7ychtv7XGxUiaRZpIoEEK/5P8EPywO0j4JwIfRQ8B6ofBwt7CJIf4/8nBgcV+fg766zYl/nQ/evpCxnJAM0PCxuR8/4pYP22+CL48+X37hjTMdO6y3byOdP35DoT+s1/7hEBTAb0BM70EP/E6NvmfchuyYvobbV761T3GNsNGLkLmeP6F1YW0c9lDlzwsNHVDt3RVMnr8j/i+t5KEmEPJ93BFfzwO9Ws8hjKENDX3/7agbzI9DnkmduBELjg3+3VA4UQGSHh/eX1yRF1v5rCn/c7vcbXHvWZ8KIO1x2j/0QDrAvt+kv69gL7+ajsi+/j+FrykeAxHUYRQ/WOKDoLPfYNCoX+uOWJ+FT0I9sp+uX8yu3wIVYRCv78APPprhF5GkArphExIp/97ergBNXJ1fhIDbT0+DoVEOAEuDIc5U4DUB7Q8YkkwS153S8PFxcr+VQLfTZzDbkT6kFCAb8TDSc/4SD17/do4HEH9fdEIQ451w02EHMm7eTgBWs2uxMzO2MnFv4XDwT6cue9HeYP4BDHN9cbWAhrLncglgMPHvIWdzZENkALnCNgSEYEzwrHMoYFTBIZEbAVVhNUAXT6cPrr7hLvneqkBkglDQ6/B88awxHR4xz69A7h8cspXCnr70gTf+dKyRkMPfYKzYP94B7t91YI9guSAh8AvQGaFWb5FxxlBHbpi/hm/kHkaP3PK6buLgALIykBBP8G9+PCDPz+55PotwWb+mkzDO9IFnUT3/8PHEPjPBO/GRccMSE0Dx8I/vCWAs76HwX6Alz9MyssAXUIFyxc3g8O1S8VAiUJLxz6B8j0swfA8BjoCxp94asDEx8A3H/x6eRixkXul/RYyaYbDwi62Xb9CPau1KDeaP9Q6lIXuR8e9aoLFOMAvOHX3evd4FroIRIa9iTpNgzp5Mjb4f7qBunqigSqD43BfPxF+7LCrwrwCo3iKPWL/V7SotCd4j2/Rc/x/5/beOpvGY3XGvD+H5W8I+BGGhC/Le0XKtoDZPIn9HDzTOG69S8Xp/x05Xz7IviN9JoItQTl/eIVognb6in5bv3X9S/3ogRe+lIGbPP57xUZgeY0BEgA7d4wAD/6O/R9CmUD/upAEbkGmfOUAvgJfSgXDE3+Zy/G607cswrR7OP4iBOoA/v33fiMA3ECEwzeEtEWgxWcDHMc0QQHBNX++OJo7gISEP+0/k4dePK3C0bGYO2yMbCyzx5WEyv01QbgA7kFbNq3B2EBCQnyDDHyxO8+GaAGjBDbPlwcmCodIzcpTg12/dHcThI+MysZ4STfKRM14h1tFXcn4g0A+KgJdQb+B/4d+BrBEPgR/N9g3wL98fCq8AQY2Rwm+4/+nAJ/8dve7BOh/Kfz9ftDzt3oFvvd8nsjTg73/DoPN/Lt8wbb09g17cj2f/UpAPYKuuizAmEFffDoAPoJJwavC9n98fTNBSXotNt5ukzNmfTU/GMKuRycA4AAHRN69u/4AwbiEMshbQsU6yT9g/C5BAYwOTILIqgnhSWGCsMZ2AMi7wQSXxdUGEAuISakIvwdxQ1CHNsX3gKiGs0aMAGF/Ef68ffR6xTvtPGp/cUdLgSQEf4LtPMfDfPpAvV4/brw8/xW9Jf1ldCR5jHqXONQI+IctR+iIjQIk/8r8/7kJd3h5FLzT/pWFj4KrwPLDSvr8gugHUX+awqQBEPf+OVu0B22CNt10ofjuQWYCnEJAP8g+2b8rvTO6/n2pu4S80v8j/nVAxbzUNTE3/nv3/27FHkqlCSxAlb9hfU743DjkAYm/Wr4WCDYB5gH0wqn9rsCywE+CX8ACvWX88joduhy2JHedOyq4VoSXBk+AXMfzwXwABkBPfXFB0QIWwNhDIP84+NW4+vdWNkU8gsIERqWLikTxQrsIWD2Sds4BpgDl/TO/2MP/BDgEZwa/g1EArUToBEZEgUP8AVi+XDlKeft4nDntvqGCdEYaRWBDNwI0Ptg+UP1OgddCpf7PATsB/4MtxT5/1z+OAKQCocs/DDmNA4ssCQ8H28PqBnFDa0EaRHsGOgSvwmeCckKQ//6D8kvkB+h/mMRqgSk0+3hcvIo9fv92SMtID35RgdUA9/zZPLDA7j2J+kr6O/eYPGj7HbpcO6b6frrnANzHV8flCAGHwkW0v1D7HL8EPV96VjtNejK5d3xcv10+wb2BQWWFM0IK/fP51LWi9AK7joCWhFKFTgPzxCQBgURHwDWAgkYQgERBWcUBwR9ABkPVB1rFmUV6gw1/WMFbQ/4GAAmcSm9IwApEx82AoICdQHZ6SbyuP6YAzwMHxPPBg0B7ANrBlYKf/a48oQBP/fz/YYOUAV094oA7gBi54frS/T37BTjVOrd4YfQGNSi2VDs5/VpABj+Oeu474fh9NqR/6oY4BrcBk3ubuH23N/3DQib/Hzxvuyq3d/NSdsl4FThXPQS/H/ueObI6wzpXvWOAw0C7/r59i3n59zf68zwEOxH7HTmANim2HfZVtkl67sAMAOs8tngm9fJ0A7f8/ymGlggWQy/A2kHSfly7wjxENhMw7LQld716rj3k/yh+nrxjfBB/YYHGw7RFdsRZQw+BJH33fXyB0APqAYJBan+HO4M7BLyrP42Fs8jBio6IXUUbQmV95vvJPPA8UX7gQmkGGUk6CpQJpghXCBfE+QABunv68zy/OWm6oHmHNbI3Yv7RBMbG+4aAhFYCjP/qvX67CnuffTO7PPpmeh07DX25/NV/hcOBxTPGIYSWA/+GrclriN1IPAc8hicDfQKYxvFPFhMFzw5NR9AKzEPHHEtXitnFQIUCRD8Aw76DQRdE18YeyLNNY8zbyAxLCkln/316uPqtvCb87z+pgcO+yn3Mfq4+rcC5A0vETwMohGsDZn5JezG7IHp9eJ9307cQeoTBegheSbcFQkU5g0G99XjGtvE39/bLeJ29N3/8g7oFS8dUhyiHUocyxdIC2jySebE9dnzFO9s8rTupfAI9E39rwoNDMMGjhMXFBsNew74FPIWZQlOAPv5Lew75fHyUhh7OPZBhTl9NnErzxTkAC/27fwa8D/j9fG7AcEEshbkK2kotidAMCMfmg5EA3/kUMnJwF7HSNU13ofzRgVQAvgCeQN4+T3qFOom8PPvvPCb6+ngFtqo2j3idPDj9PP46AevDD4U7BlCEEQKAwPz7AbfCtwr0BDL1dDn4ZH7IQthBBz+YQEY+9v4GvNm36LFTrhEuwLD5dR45OPlYPIPA0IA1f25AUQECwBSA5gCYP6Z+HvwZPW8/x0FuP8t/uYBMA30G38nQCxOG8kO+gnf9AbVJ9Dp39vpjAZrIikkEyHRG80NvQUPDc0NDP6l8HDnyOVw6dXzGQK5CMER7hK5CYv/2/id+tX+dQgJEagTMAvA/GL4Ne3v5SD7EQhIBRUHIwXb/78FWho3KcUXZPHG5C/h69549s8F7AGZ++P5bPVS5fzqLfkI/ycDqvjf7kPsRfuJ/on6+g+BJZQsniNSHpIfsxnTIrAsWigfH0oX4hPHGBsjcytxOU42dyNlB/P5QAjDEP4UIRkNHR8a4BMPErsZER+KHIEQAP2u7crjvu9xAhcISAaqAIP6K/Bw7KHtaurV9ff+dPYz7NPvZO9q7UHy+/9ABRT6ZOmf42jsruiw5qjtN+tQ4crmZvPp9Evx+uvd54fhtN4c9FAKrAhKA7z94/Gu6dHk09p31EXqgAF07/XdEuAK51bu0vvHD4gXIRxMHbIZxRe7DRUPKSCHJ7cn5iZjKKwoJx5SFuYp6jXoIAkTyxn0GhcPhfzz8BDv0exy46TfS/E4B/4hCisVGKgVtRQz+TXln+N75T/mR+oS7kXl19263yXqwPptC5QOQg5zCQsAUO+q4kXnvu6l97r9Avxa8lTmO+Px5WrlyvO/CNoN9A00CCv+/fZe7L7fTM0zwcvJL9JB34ABzQnx75fq7epm1DPDd9WR6H3yyP1F7ALbid5S5h7x+AYrJi0c9gghE1IKMfKb+GMSRhycF5wVhxpWGlsCMfRtAc8NlBJEAT32LfRW8Azw5/Bi7ynoavFc/mMINhuuM0Y2BCiaHBsT0QxQDEgThhI4Cir+eOvv59Py0vo4DCsgzRoRFIkg6Cc0GlgQkBNSDh0I0QSxAg7+AwZEFloe5CHLHS0h2SA8HisbjBQ8D+oE7erA2Yfgzupe8Uf5Tfsp8ATwrQSvDs8K+g1fFpYZYwLS9R8JYwuzBNwNrCPTHkARCR7fL3EyDCvjM+NByTkELWI0CkAILwcS+hToIRMVKQcfDtsZbxfcEegVRBArBaP8L/5WBcMJfxVnH9EXTgOo9bzreOhq/dwSlgpB/dv8n+mi06bRh9Sb08/WwOnr+zn5culu4RzgHum6/+AIHQX0AWDy09wK3znqqO509IYEIwdzApX9YPHR5ZXcl9eBym7HRMgKy3vY0d4Q1IXKaM5vwwK8O9YA/+oWOBHRDkYXfwbp9UH5AQRCAeH69gVrCLL6JvXDDg4ypi2iICEr7i3XFUH2bPbLArD5ZOyD9zgFTAI6AT3+/fN458rhKeqd9rECJRlQJeQW7gjr/kHovtnI2xTj6ebn7eH9YP4k7OnbZtqj5dfvFPshAxz4O+aw3GDf7ez9+nkGig/wEH8N0QvcBP/55fMU8t370QkfD2sKOf+d6z/ZwNOXyX3Lkd7E6ljsWuNS1H3Egb/pvvLIK+eIA+4VKxKxDIEVJRrqHQ0gvSBMD037l/r78cTfMeDl/AIbiSQAL0o+9jWeH/wNZQUJAbr2VO3S9B7/MAfcDGsNDworEhkhNB8GH6IlKy9QQE47YR1fBuPv59SD08boru/j6/7kFtnV0hrh3ANCIposQCZfGmEPyvqX6OXv2fevBUwlHzdWMTEnrCBIGEIXnCNQJTgbWBCEAWMArv8C+HT3aug7yTG8P79gx/7Xmeb+5c3UWMsa1NPhGPyBJZhG51BzSC86KSAdFdcbaSDnNtcosP/K+p3wDNnh66ISyRwpJ1guoB0JEeIDtvymAy0RzSdrJ+gbOiXsMJAxXC6iK6gdbRxeLkA3HTsEMzYTqvkn4GK+TrPJut3FutZi5l7qOebf5LTmjemb8WMHtiSJMo8uWB5pEgsQkBruI2AhphkCCMr21+Q50VzLCNBq0fjUieN++kAHxQMU/sj0496JzQLICsffyvTPStPj1cDTXsfXvznAxMqh8s8ZyyN1KuE71z29JHsOUgOL+6n6uQNpDkYKwPqw83z1lfdB8Vr85hEPC/v8GvZa+tX+ifkz+nMDDRR9HKgbtSJ5LGsplBPmDkQjwy2wLn0tRhqq+53hsrh7ld+j68GgzMfT/uFP76zkqsyX14XzEP8LEQ8hQhuiJHdGg1QERqQ6azH6HegJM/di2TXEbcIpv6bF/N1U8wAAXwdYEikamhRMC+X2/tr61Z3gUuuH+rbwsNhF0lDR79EE37ru1/QlAqQGR/lR+VkMux/LJYknHyhlFDX/TAMLDJYQfww8AKn8ZvTl2BjTsPBJ8Fjf3+VY92UA8Am1G38mwS22KuwkNSHNFEwGWA4tKHs7+EGmJTP8HObf3BbUQ860z0POns9a0DnRQdNO1ATene5ECZIrvEV9Tx1LiUG4QKBNg1YxRzUwJyCy/bbY+M89yiW+h8Pp11jq7/c2A7sGKQSQA5oJ2QyiCrEPaxG5DlgPgQk7/ajwUOis3mLfTe/d9SbxewBGDjQBrvkyAB0XAjFgRLhPd0XhKeIV6g5nC20T8BcLDzACmfnI6z3syPt4/8z8ewmHGh8gYyq6MY8uSh8dEnUP9glbD1gdWiXZMWg5QChZC77vf9lB1vXkT+xM3tPVAMoQrVitK9J08SMHBijjOC80CDJkNZgx5CYKIRkaBBmiG9UN2/Rc4SPJvLHVs9/BosW2ye/abuQi7F762fzt+Vb3yPvsCJoMhgqoBo3zwNw924PovO4g71zo/t3A14PGEL9IygrRSdm68ZAROCBhIkIjUiUnITMggR8JB83lK9TN1KjPnMOeyevinfAS9qoBpgqDC1ABLgAlC5ANHQQC86zgdt549hEVoC4VObYu1yEyFkQGZPvx9zX1ne/N4kXVqsSss669HuHVCBcs2T6WOOoyDkK+TvhDzzW7KgQXGwiB/+gBUgnj/gTveO8p6hTlGPH19/38PgYtB6QIoAz0Bi/8WP1rEzwnwSpSJ4kg0xOxCzALcwSp+t3u+uD40ATKXNys6bTwmf6FGFIxAjhSPJo+ADnVJGsV+gJL59/Pk8mb0srgHvfYCl8UKRFlD+4TXhsbFAD+Cvil+srtuuXv7P7ncuLT8JAMlCYnM4EzKSm9GcsGHvI/4zXX08xvykjIMcSJyRvOYtL45lsGmhbkFrMZjBYVC1IC1PnZ8EvuAOP20GLKcNJO4RLyyvmB8o3wWPOd9eP3h/N75RLZgduT6H32rwQHCmb/sO/O6hDuZPSy78TewtBcyOPDBsUUyefVQ/UPAtEBQgkdFkgdnB2YJfIoAB7uDUoGkfey5rTdMd2w3/bS+tG47DwUvyIxHK4k2TPuK7UeXx8GGskN+AKWAw8M1RIyF4cW1RxgKIkwKznsOKworg6p/Ab2P/KJ7O/fttoc7pIQ/CnXM90930JSQR9A8EHHQ6Y9Ny6kIFIcxQ9q/7b0bOai1+/YvuroB/IbXBekGBMicyXwJ14wCDLLJYEidyiiLZIrYR2mCr7/K/7E/CL4Oe/t2ADFOcqw1w7pSf2X/zwD8hozMnc6a0VoU4tUJz4EIAUN0PVK29fGccElvfiwNbJzyq7Yj93l+dMfhzodOaAllBXRCIYBRgcNFMkbNydENB00LyoRI8EOyOm8zzW7ObG2tWq7+rxEuOiwlreJzsjmPgBgI/5Bh0Z9OQgsNSTJHCsXgQka+hDzUOoc4jvabM1mxt/N2dds3j/l0+p976r4dQsjGFQbxyNWKegizx0dFnkElfwa/MDt8dYGyrbB8rgftGStnpqenc3IJe6SBZIhFTrlQ2JOblZYTRU1HxymDf33HuP83ZPjYt/A0KbOXuKh9OfuSesG7wTvmehm6YH3KQU8D6oXTiRnLJIs4iagHOQT5BHgEcUHifn77VTcBsLfsxW20bg3wGzMptLI3H/tFvUA/P39aPE/9dUIJwuGB7cLHwRW9KPr29+g1VrV4dYe2lrag9J9wI+z8rd7wB/PGu2MEi8nYCk3KZgp8iVQGpILyQBa+fXpHNy81cvLl8BvvA7EJd0z9rcHihpUNy1QwlNYT8dCEy6DFD4O0xAHAiLuyuoK8QTwzPa1C0QlYC1YKokqYjGWLVgYWwqcAof8M/9ZDN4WlCMZL+gtDi7TMEovgx7DBPHtk98C0xrNstTn1zvbyOgS90n3av2xEKwbcR2QGXMQawmP/kvrqtvT2JXo2/vgCOYRzQot+7r//BBtFfARcwkO977nsuSu6D/4LAYLAyT/HQDaAH8G/A+IDuQFyQkLD68H4fey3rDMjeKMEYEnPCzmNctBrERgRS1IxTpOIBsNAAvV/FjmPdzR4FDn1erd9FsP0zDjNQg6z09YWn9LTj+iPd8yVjCSOGI/OUOBQIcrlBqaFrcNkf999sTzzOWR0wzIRssa3R7y/gA2E78yKUojVJdYG1K8QTE0tiasD3/2kejE60/wg+li6JnwGvPf+uwMuRpCHwYcBRAQ+V7jg9si7kQMIRYxHqosBC2LJSEedwzx9mDmGt4r3SXaRsxrvX2+CNnHC54xQDrlPBRG10nCUr5bCEzVJ4EK8/1P6zXT1cB3uWa76cbG3X8FNiCaG5QgEzNEMgYiIR3eDdnuieW09LcFCR5mN4csrhGUCOoIZwWp/Hvn58fZtU6qf5wrqbrRhfcwDCUU0xqUJzUrbRrYA93td9XL0qbicti4ylbKWMPHx07cPeAz2Azeg+Pv2GrNI8Jrq46dyaYjukPKd9Ya2GTSAMq+vgC4I7qev+fBJ7/2tpGxf6kjnwytI9Jk7O/1nAINDX8E1fZw8S3mFNTLw924ZKjkm0SmUr0CxYnGHuA+A94c3SjmLz4uvSOQGjQR8gFJ9M7yKPsABFgNVhpYHQ0dMRqzDYP/ZPQ56HDWgc2R1GDpgQXRGD4gWimyONk+3zr2MSUghAom/wz9ePpN9d/vBvXFChUiFyREErkJuRN7HKQWjAN99t32Lf2mBa0IMgW8/wsCHwoNDh0P7gkTA1b4N+E9zZvO1doI56v/ExusLZQ6mkJxNCUcohmkHjQUhf/18oXoReRa6/v3ZwKgBBkFcQ9tIwIqYSVzHuAeADG+R1ZO10TBO3Ev2yTkIxkfYRH//03tGONs6fP34AIZB10D2/yP/5AK/BnLHq0IevDf86v+9gCiA04JbwwZEZwaIRyBFTIQWhGWEEoOCwNg/3EGMgT2BuwVphJ/+HbhuOGUBV0UVvis2uXV7+Ss17S379Od2X/NUBY5TXMxhTgWaZVLPU6uaSMw6fdD85foPcwU0JnZBL0ttyvfBu6J+90zLUrPHbsBQgniGLMY9DbHTn8w2ywQT+9V4zIPLh0kAvHx02jvAvv83HvcTenj6Fry7A44GjYhWjm0OWcoNSjqJo4aCxhjHckUWwZhBqQScxJCBH8Obwsn5WbR0+Ht6Evek+FM4jng5fgEJHM4qi/NKIspSiJdD8UDAwOZ7bDiuwJtHfIURAt7EV8c0SawHWj5vtyw0mrhJvmb9532XxG2J14iISEhIUwhShYM/sjrsOcr8fgAWAh98xrpYu8W8FroWN/h36HgWOJu7yL8M/pc9yj1tuvr7zf77/m0+onwWt30yC/BBsrTzZ7JG74nxi3R59g92TnMtM4i4z/p29rT3eXSL8SX06jgRdsl1NvcYNqozDnRUuB73H/Lhdm82vi+SsK67CMXWCpWLGkhFyCoKWAvHxOy5+HNRMW22fXkUOJJ9wcOJRLTB1P9vwpxIJAWVgeIEYEWRCigQwQ1MhauElAHmemB7ZQDKw0pBxD7U/6CCIoFEvm67e3fI9bh4QT0yP0XE4MfIxg0EmcL0vqH6GjdstvG5tLzCwxhCNvk2eAC9XzzXOyh94XzmeYS4WTWj83RzrLcUuda5fXpqfzuCYvsi8EAxb8Cj0CuWB1P3UcbTpg37hh67HHJib4IyETKYsYC4dYALxM2BrTpIdz79IEVZx5aLVhLO1G+Rhcz+Azz+vwBj/eu4s75HyI+JnsFj+1w/3UEUOnA2wrlpfStBOoLEQDLCKYeuSBbEKQBCQIrBnUMjgRB/TACZv+F94ns1+BB4C/l9eLK4MD4dxpOJK4dPBJADwQWkBN4/Ufv/OS224/f1fItHWA8XjaJHGEguyU2HHMatQvX77LnsPlm8gDltvQHF0QnNhZSCwsfaD9QRr49dzYENxs7rEA1MQsdViYXJ70PIQu7Lx1BEyhpFM0U0RYEDuYLIRBYEmkbbyZzLt0oLSHmGCcGXvOH5yfr/vSiAj4K/BH4HSUdoA6Z/4AAyP2N/04SaxwlFl0Ogw51Bhbz1eqN7WTxf/iJ+t/zle2vBG04LUUfKX8Wvy6LNh0gJRCh9dHeOdRe3FLT3cOTv43P7e4W7xTmnfroGvwiwxZR/jnwAu8I9934Q+eu4kf7MAlZBS8elhhe3D26SLWsugrFnMyFyifCTsSszhjcaOXZ5I/hhemV97b8evg/78TlM9rjzcfBN7XdvofY8+bG6Nvt1+kK0fjEXs623mDm1+Bw2gTdwuT84YvbDvjPN3teiVe8On86MTcIIzwPbPFo4F7Xf+U7383Q/tvX6LL1ne5a4CD930HjXedImDtaNHkXQgkPBccFjCFxOc8wliN7QR1IfxEn8XDu3e877UX0DvRB7tn6K/pJ7DnjgeoM86f6fwnwDUYBUfHK4R/THdXN3y/zRA1YFFkAffZ3CxkF/uVK20vl4+2+3ivQHNT63T/ld93b0hr/8k0fVVA1kCuLRPBDvySWFZYA8f39/XT1DtnVwfq/Hb9H2n/uWuw6Bpo6oEbLHkoKuQ0ZAyUGmhKYJ787miNWB3MaGz5mOCkKEvTmCaIeswte83TkfdN/1R3Sqsqo7sEcKxu/Da4NyQkwA332puS84tX0qf8c+E/zbvJk9pP8/f1c9yfr+uzx9vP4ZPIj5ZvVQL7l0WEjTke7M4gU6BEjGKQKLxs4EhEMER/dMvo+3hIQ3w7Ui/XVBsziQd7gEocufRWb+qgb1z7ARVpJcUkKTlBIKzQtJZ4xUDg+I/gcrB8VGIcWkBqOEkAFWQJJ9rbnzPG1C70Rrg0fEisWuRdtDHECnftJ9y38Vgm9E2UAeegi8EAGoBOkBv70WPbj/4H9Fut02w7WJQOWRtlJWi3iF7Yq3Su1HN8/OUSDLgYe/B1rFCDzhdfTyL7TEs1rrGzE+/zz+d/VOdu/CQUPDwoGJcEz2SzVFt4Y0R0yCFjnGsyk1rbgGs9Uy33oZvE/1Fq+sr81y9vQ1doS20bOtM0I1nfayNz02FLAfb8h2mjeGNecy3HBRMCixynNXsfrxY3Ei84t04HOlcrf31Yd9ibeBRzoEPgRCST9dSNiM+gk/g5lBzQJM/FN7f74Vwa88yfRifRWKOgRAOLC4nEHCxJKC20OFxXLGm8bWiq6QQRDCCzVEkgTOiTsHscGrAYm+iDdIeIv7n3ol+2CBcMJCwdnDpQCUfZJ7SDmtOyZ+ysKpgi3BPP6VuYO1svN8M2D0nnivOhY02jA1cE59XE3ayu+/1b7aShCOd8y8EasNEwUCP0hAKwWoBhSDqQOER4tDYvhDuNa8e/k198U97cP8/mw7EYFBBF3DMcMrh2UMJozih9MDDYSihe1E9cYxyIEEsruTtPuxZXHZNmN6lzW/rlQzpv0fwUA+3viVuOYA/gaRhk2E1AIzP078oPY58cvzRrZNdMQz1TW3/IZEtn7NeaJ4+4DZxpWFSUlOB1SGTocDyItI+4YtRwjKX8vQBnx+ogSBC9MGJH8CvsS/tXkg9br8skHfv7R8AcOjT3ZRjw0XBs1IAAxri7JJoUYPgl3DPgeSC1cJUQZkBC3BmMBMfnx/04QUhSWFn0WcQ2tB4YE6gZrEJAW9AmtB7ER2xITE3MSWw0TEiEk4iWqIfYTExtEJt8tyR4AGmUjvuSb+rIsO/yQCb8yYP4E5a0CigOIG0418BmzEXclvxPFBvIkxzEdHbEIdwdvGIEakAGV62DwcQV/EZALrvnp62rwh/p3AGD6cPMz+vv7WPcG9Hz6nANF/rTuyOCP1KTMxM2Z1MTqhfdc6B7jVOeR5Ab+xxwIGfAOrA3+EDEeCiMbFgcM3gTV9vftJwCBCXryj9+N2indst5H5OXlK+N94Gzji/E799nvZvAfA5IJMAD9+9oBMgVa/WD3+fVk+w8ANf3/+bDzLeGexgS8AslO2XLc39KHyfHRzd4a3YHOE7Vjps2uz7vhwTnIXsEOt4e+i7sAs0TG5duy0SvV0eqs79vchdAQ2SDe7+5Y/Lj6h/7HC78WrhorD6QHFwfYBUAFXvhB8k36cvzM52Dme+y63BLSedeL7ncFIQ7f+3bosPXsFt0pQCYPGssVMRpAGAUR0wolEAAZgxygHP4RiAb4ACr7UfXp9n/5dO/b33PXI98r7Dvrwt6d3hzyUA8+IcchqCW9JoogwyBQKQAl3SCmKlYsnCodKlYjzxLG/kwBYyEfM0woJyNnOHNM9EViO5oypC+POdtKh0W0MQwuoig+LMM2FTVjLL0r5i53KqIopCSiGOwI2f7wAiUUuyfNK8UkQB4jGPgeoCVpH04bDx4tHysZvxMRDMz6AOQ12lLn4/pc99DttPeFD8kTDvlm8tER0TCPMgIesw6YD8EcRCkdJ6wTZQSBDC8VsxBxAEH2dv9u+enmsOYv6Xnlduej6bbv9/mn+qXvsO64/JYO9BCV+dnnHurp6QbfANiyzRzVIOmu6YHjvtyRzbi9ssAOyCXKQcbPtwCyRsA34Kr4EPLl2+3asu1y+E/1FOLj1GTWUNpU4ajeYM530arjHud557bmwuDp3A7Z49bV3mLrHui83Y/UWtLj3k/rkeyf4OfrRAIADLENfP684MXJGMxH1MLZl9ds05/dWvDA8P7itOFs6I/tHO735ZvTUMuD1tve2dyV1EPLUtTK6ooB9AgVCuIVGxJc/WL9GRJCFWEETfolChEb7CBgI4clRih5LGA4Oz4SRDVDzT0vN4MtyTDjRARXvkflN9c9h0L0P4M/30EGQrY7njLZLao2FEdiRWg6oi9nKuE0ukFUPOMxizLTMo0xKS/2KuomGSgCLWAoeR0tHd8oNS/bKN8eKx4nJJ4o0ygAH1YUnhJfELsNKw8+Dq8PnBFYEZ4VQhQwDeAHk/5D91HzEvTJAOwOxQTZ7iL2sQyYFfQKVAZ3Di0LXwfcC80PTgf+A3EDzPvh9Z/1awTTDz4HHPke+of9ifxi+UXt0d2H3RTmi+fK5rzm9+yT8cTx2fJg9bzo3dOJ1qHjI+Oq17TIpMBQwPLD7cop1Frd5+Y96A7eqtjK3vPlSeDn1ETK9M1q3FrdutJexFi7YsYe29XaCsjlwPbMN9Zw1o/UoNKkzjPHbcPrxrbQdN0i5MrcZtND1OXZnd873gLWsM+Xy6jKJdXO55PwFO6L5q7bUthJ3SLptPo0As74QfO6/YwPgRmFEysGFPsS/J4G8hHsEtYDN/vDBccOrgt1BbUC1QTWAxr+P/9dCMsSMg6p+mDrWOvS9l8D0whEAfH8j/17BwQYSBwtFlgOzxFKExkRGQ1XAff3JvzWArr8qgYAJi06NS29GHUYMSX6M3U7ojQ2JH8iJS+cOko/zTYbLQ4y9jLhJXEdax55IaYhHxUO/ov1xwGcDtkMpf2w8wr8pAjwEKQX8BhhGJQbqCXPI9MTEQo2BMb8K/Pf6xrsavCn9fYAYQQv/q8AEwm/Ch0IDQsAF8EllC22LOYe6AwfC+4ZOibkIRMVKRCYFg8cOBeWCugBXQQEDc8R2gxICV8OXxasGYcYbR1zJyctfyopIPwVhhS3HccnxSSiHJwdRCNgJe4fJRFrAHL+/ggHD4oNmhALGUwWNg36CccMXRkKJhEihxr4G5YcVB+aIR0c0RUHENEIPAlhDqgQwRUxFkwRyQ1pCXsFeQzgEuAJawPcAz4CFQZEDTIIDP1w9zX8twTqASv3yu857t/uQ+477E3s0emo6EPptukC9VgLaRPcAlT1WvToAD4JxQDE88LhKdTN3Tfvuu1S4xjig+bK4HLbdODb4mbiTuL4267OVL2wtcfFuNOozHHFbsgQ0engIOgx3RTWc9bh0yHTTNDCxVzC/MUbyP7Ii8ktzuPXvuB03sbX9NMlzivE47n6tKC5VMV5z0zRWsrHyM3V5eQK6ffkGNvI1R7ZgdK2wva6c7wpwrbKO87jyXHJbtSJ44nsvuwt6knoP+bN4z/c+tPI1uPiVuBO0Z7MNdJw3/Ht7fGu7XTpieWm4FTarNq05Y3xvPiJ+20AzwyOFtkaMxsvFJwNwxQ+HCkYBRAlCPID3gKaBVAN+BOcFHEWBBg6F1IXbxk+GXcVUhZxFzoXdxeoFuoSig1xEQYi2TasOn8tvSGcFEoJewYuCCkLShL2IHMuES8fJjUloi5zNAQwwSprL/4zjTIjLBMl5iKLK+M/TE22SM06lDXPOSk8kzqJNykzjixiLDszkjMZKq4ixSInI5AhiyTTL8M5eTaHLRkqqCG5Dk4AP/zf+5IDhxWoJTorZydtH0QZ6ht/HaYYnhvLI1YgOg9q+v7tj+8/9oH8MgPTBZoH7A0TEn8SRA0wApP8MgJxCtwMdQhAAhsBQAWiCmEM8g8nGGMe2x9AF4IEL/cW+dUAmgZvD30XVhYHEskMwQGr/t4J6hEHE8cVOBeIFtUVEQsK9xjvvvtpCi8OWwsbCaAKZRIRGG0UKQ3gCOoM/hDPDQkEFPyH/UoIdxUrFdUK3glfDNwHIwEv+eHv4+0e8n/ysvRu9932QfWu8FDrJ+ef5Mzj0+Ea3QTgQ+jb6p3s2+xk6TXphfKX+ZXye+zf8cr57fqX8Unjydi00j3RI9XR04fMf9Qt6z/18fHX7srxjfiV9broLd/X1cbQ1d0z7ATtwuuP7xTxCPKX89Dv4esA65/prOL22IXV3dlk1/rMmszv1A7d3ejA9Lz0FPa+/zYByvfG5sfS8MjNzQjTsM28xqDIedM741rutuvd5N3k5+VS33XR8MjT0+vo1/Jw8lTyYPBU7tn1zv1jAOwDOgaYBlcDifV95brhaOad6jvsHvAK8xLz4/Th+qQBSgT+B4oOdQ5rBg8DcQicDCsHuPlB8Qb2kACEBikFSAPsBmEM9gY79WLmDuZ98yUCTgiBDbcTER0jKMEmaxsZEl0SXxuiIpwbbws6BRsMDRXwGcUdFyBUH3EhPiDqF2sOxQV8/4f/1gDz/RsEWhZSKr811TeJOE448DSkLpokGx0VHccbcROzCYoMmB9ENnU/QjUjKncmCCK0HZYanhOaD5oWDxoVExkLvQTLAZYIWhT4GaoamhojG/wagRgfFMkPDQUv8SDjVt5m3BDkffNi/UIFQA9xEhcStxHDC5IBtPq+9AbqCt1K1mzczOpB+eYCMgLI9bjqbOmj6SLjXtsU2dHbUuGb5NnjNeKo5S/to/JY+BD+xQL8CMkMYQey/MD0FPBm7xLxbPPX++wG7grNBgkA+fkS90/3zvXx8rDyP/cI/bb8K/dm9Hr6awV1EREVpg5nDF0LKwZ/CKQSgRTuEjYTwQygBMj+Cvcz9Cb9dQoTGJIh4CDuHCsapBHTCEoI9gWqAVADpAZAB+4K8BCoDuYHZwMr/S/1EvSN9nTwN+kt64XwT/jmBOIPIxW9FqoWvRL6DZoIOgO1BNcHpAYY/d/s2+EE5NXyFQKtBc8CXQMNArj9Uf7U/Fj11fE79P3zrvS6/OwAYQDmBMULxRGSFs0T5gnBA1QB7/sp9JPr0eM93ynl0PixCaoLWQa/ASEBcQK3AWz+pfvK+gL3Gu926Nvn3+uj8rL4SflB+FH21/JP8ffvk+v84+3hLeaw6Ufu1fCZ7ALn3eoS/IgQEx7XHfYPR/6h777pnesQ7Pfp/u6n+nEGng7sDCkElf/8AeIEGwd5BCb+M/wM/2MELgqYEJgWoBaUD2kN1xH6FFAVXRbgGkwc9hfiEWMMDQZ+/877cQPXEskcsCN1JegcJREhC+gKkAsDCBMCawBjBXEPtRiHHt0eAhsVGhUVxQTp99P4Pf0q/j/9hfxw/tEBhAZADycZux2/GscTnA5vDuQS0RZtGaQXog13A6IDrAsZD78Oyw2cDCcMtwmYAmD8wPwNAC4A0PY752Tb1dqu403v2/gBAJgG/gsRDg0LGwO49Kjig9Yj1EzUh9RU19/beOV29rEBwPwa8d/m3d3r16bVg9K8yQ7EecfEyg7Mos7y0CvQM81ay0jKk8hsx0jGkcRkxSPJcMw10OvU1ddi2rbgAOvl8rTxYOmq4X/ci9kx3Bbl0+7x+bkFCw0nDgkLQAeaAeH4Yu/O6U3pYO4Q9LD4sQF1Cq8NqAtbChELngsTDpoQng3TBm0DPAYEDVASlBQ8Fs8Z8hsyF2EOsQzTFQgfXiV5I7AarguT+FT7VQCF/tMAOANdBvAD7AOUCq4R6g8hBY/8gP5fB2kP3hEED20N2Q6GFEISmA7NDF0PqBqHIDEkgSGUH88enBSzDqwJjAOxAAADlAZfDbMZih36GCkSGQ9ICTIDtwB/BwcPTg4FCxMIewukD2cXMR11GqwWOA04AVH5UfZe9T32P/XT9E36dwPmDsEUhRlnHTMaDRZAFWkNswFc+kXzVvVo+bT9EwNvBkILqglvCYYI4gK++GzxtvBy63DrBO6y66js4e5V/FYIGxHmEo4R8hryGeYU1Q5ZAH3xhehk53vsXO646pfp7+gQ76z6GQHkAzIN9gy1Dx0MPgOGCdUP+BBbEPYHpfih+9v9O/vWAgAEDQ8XGvQY2RU+Cuf/FPwM+ir79/6UAv4SlhgJHYwc9heiIN4T9A76DtkN2xO9GOQbNhSBFOAS4hnTGrIXNg6CAtP4tvC6+Z39VwFF/4YCrAxjFL0ZCiaWNss0yTUnN142+DIVMkItkiR/IrIblh6wHYMKfQTHCW8VNhd9FQAZ6BQRDegJYRDLCIgMcwgjAJIGhg+9EkAM0RBADKAQMxzTEQ8RWwZ67j/spujT58LnyuSb5s3icuxy5j3woe2R7grvWvAE/Zn8Yv3K9Fb2ieU/5O3Stsm+zlLL79ZmyrzHvMHqu+G3SMTwwf7D/svG1nDgOeZo9KPwGvPR5Qzmd+CP5rLve9lS7w7sf+RY/Vr8sO/t8IHpQeT21I3Qicz2xH/SI9jn4e3mi/Ag8A73KQv2ClkI9A99FVkGQBT4DY3yyvda5e3fj+sW/zAFIv/BCH7/vP4RCvn6RAjb/cb+9hDRBnsN0wJzBmj5S/j9+BbqaQS03C/olfFu4tEBnf2h/c0Uevsn9Cj95eTS9zfxVPaN/zYFRBzLBvwarBQNFmcQJwOCB4YHS/7+BRb03/bp9SvjDQkM+V8AYv459bz/wQOQCJgPdwg6AkH9EwH8GOX89ggZApX3nf7mAy0Jdw15B4wE8fzp/YID+/8uC2T3vwbK8+IDsOWs4BbutNMg5BrsKfW5BbkN2RoVFWcHhgqkBuQCXwCu8Lz7P9148xLraOH58vbazObT9pf1zQdxDOgDkhStBIYDpg8x7f4RbPwwAAr2Gw2F9EnxNBgC7VQoFRvaBVIcjflY9cD6IOrr1hbyVt48AH8b9+3bF3MVsQlMNXUj4ysZOponViHLIqgINgiQEa8I3BYRDSb/1QlSFbkCuShYHjQVXjDsHRcuMS8pJyMxXRQXJh0Pi/mcGMEESAlfEogLqBjoG9cQjCNKBe4WMheiHjISo/tfF5vwfRXgAaISpDAvLgQ63z7HOXc1IzuUHhMvzRKeFLAQlAXl/T4OlBgbEy0aJxVSFbsK9gusCN4J3BUyFs0OUg06CVj96/NH+tHqAt+3CgT1oA1nKzga9B0zItkZT/oS/+/oUNSR2e3LRMjj1VTN1eJw88zyAQRc6Sv1k++X6qDY6+wa3pS5AOpMu4fCkeMZxPbZS+eD2RDw1fzV6u/41fV34pnik+vE1ofYQeJH2Tnq9fOT7cz8eP8/8On7g+4c8vzotuHv3JfVjdaq0Vrnn90M5w8C//sC+7r61gPI+5H/4BgHBQ0Zpg5jAIgT0Py5BOwL1+5s+6YCTfWsETAPNAfHELkNwPthBZYC/gAK/gTwsuvZ5P7nHu2P8onwEQPDBvIKAA0nEUgJLQ+xAtD5Tfu+8+P7lej36XvtBt203nr2Vu/LCZ4ZGwuoLQIgLRl9CKX2he3A9Hr5Iuar/0fvdOwk/B75awqwG+gc9Bf0Gy4AAAAI75Xn4+CT3Vzs/PKT/OHwnAlc/18EaRTTCjYW9B4wD/QK/fvT5kPmj9pH6u3ZuOhP8mzucwDV8nkBJv7K+OADxPquC+H2RfhF+dPjBvVD8fPsHwW2/PAM0SYxH90j3hBUCu/4sNUY8X3mpexH93DpmfG28hkKlggGF5YcfRZ/DdMK0vxw/bb9COmN9FP3AP/cDtUGvvv79ajzpf0e+wULsxQrFQgfQiLPEikS9gjHEBkeAh41KNsUZSP+FQ0TtCc6CQgrVBgIIEYjpA1hFHcFBv3T97LzfPhGC04LTgI2B0IL7BsnGTwSaRusIQ0OHwo0DbzoCPs/9LEAWwlXAscW9Ap5ELET+Cl1IrIkax6WLckvMypaKfQaOiR7ACEWOBEv/Y4Zmgb+Cn0aPgtGCuYIsv1Y99n7rPj9/O/60v1B9D/90wEhCZwfsBGHGj4ROA9k/aX1cPCD2NvnKeBc3cTdoeDx0Cvkfd1a4FjyQcuq2PzYrtbT5AzWc9XX3jPQttxF2EzZHNLX5BDLTsxk8aLHj+pq7fbWcu5q2yDgHNv81aznj9Sj71jyifXPBa0EHPuq7/f1Rfe44X3e6+hW2TPWH8Ql3ZnOf+1P8ywEzxVpFPAagQMNG033xRYq/04NOhbqAtEdWg/TCkQdlA/DEJoxrQQJHeQROgqkFWkMSBuAAcMT/vWYEhsNLe61DIXsK/U6AskBlg5dGkQN2SHHGUIF2xFvE/APbQjwBEP6gRzl/+HwFRhZDQEDgx1CCa4LxyZrCGAlJyG++S0dDQ8jBiUcWwXgBs0VohZvA88HPf4e7tcRFRbbEdkQzwG48cDccOep/u/wNfxABU4CoAPE7N4SGRfZC9UYp/9CBdYBg+gr3b7T0dp91TfhdOfR6YIHjg2oCrsEFP8PABz4lfyJ/CDfEPhy/17vL+6l7k4D4/dnBaP+gQakB2UOn/i29FTtQeCb1rbaxOg15GUFEvd/DlsPaPz8JLAQ2Q+oEo4Q2ARu9sTml+sM4e33DN8M19fySAts/8ERADkjD8MtyS+aJhsYVh2/A7cDZxal/yMKuRG3HGMQMTxtIwAc6in2C7UcQARWC2kW/gauHI4bYwxCJc8e8h/DKXcrZxhzETQarAtCHQIHpA+KE5wFcvwr/ugLiejS9X0CeQtKFDwrJzQtPBM3xTQSPfInVCYKIEwhaxT6JicZfS6oFncLxymQCLES0Q5pGP740xHV+JHwLSkc++gIkCLTB2EGvQp1EVz8Iwls/t/pJw7REDIH8A82EfIQbu5/8cLqg9r+AF7W7dYsBATh/vKl/0/wBQS/CiXjO9xqz/7Jw8aBws/TSMyFy4Pc79QSuFjcvtxWzArgnso1wz3OVNE9yfHYEMcr1EPRtL3+2vrjO8fP52zxTOAACdfvcPHC4Tfel85awDHCorcZuzXACNS+1cD0k/gXDiUUBRBAE3sHKfoj35vgjd7l8T/rcPsrEYP+WwOmEUAD3/oyCD389fIS+RLksu89/QrwsvYVDIfrS/Vs+vvv6gCf+FkHTg+OCwcNLgieEH8BpvG6+RrfNevj9FLvKRDVBrcgtSDLKy8fXw8dE9oCuxIABJf27ALwE7MGpCYEFiUbLRz2BC0Of/Gf8/f4f/jn9nr9p/aBEoMhaQq7JvoLPA3NCyr9VvrLC538bQeOER8L1wkv9HEJIPNa667uAvXV9dnu1QveAsET9hIv/9oD6AUW94ICUgYbAUH4RApe/18CsBFB95gW1P/79bzsDOCf6nDXEP/+DFz9BBgwC0wK4/4DBhLrTfX3+yXfAvqu+bL1AgpUJMcNhSCKGgkIvQMv5/jif+iV877qZO7qByMawxHsH8UfiAttFUopCRGqEHcg5AaGADEcvQUPBloqCRHTCXcY6/6j8qwQHQ2cEAIXExzLIuQclhtYEIgSyvyCCPgFo/HDAu393R55MXMksiB7HNoB5/if34nbK/OH3B7ylAtlGmclvzhAOrQftjvXIJIZiBlSCOQDnAUvIeoc0SgPKCcvfSV7IrMYcwmKAoYMXPzG+gcRyv9fG/IPoB4XEgQNlhGDHf4bCw3TKBkJCRYdATwVHwYg86YENeEr8E35du8ZBpYQKQugFA8gXiP2CjIP3gv17uXyUfg18ZvofwaL+Yf97AgE5YPpcuzG3O3gFNzPumTO3b93ynffptvS+Un30/bI/Zfvn+Ne9vPcxs8W9aLYWtDHCqTnReMvD1jccOe47uHHrNHT3NPGg8Hj0kXXfdMx5BTv+/Sj7OQBjAfv4DIXvwXl9XENk/QC/FLvWwhH74X6wPEM5Nfu4eZ/BVTzlAs+C4oO5hGrAFj8o/Bq9YfjewWV/bcEDRLVAvwLEQRbBkH4Wu0i6brV18u4+7rloeMxIKgTwx/yKLstwQ04EbEOHQU+Cvv6JwTh+9saShOWDskXXQC/A937kBJzC7L6TB1m/DYCfPFo3rrz7dw37xD+swMsAkgC1xaMC0gSQhkZEKoSXBuoCPP5Wv9g5L7OxOot43TcvQal+44QZyecA/oGkAf360X+CP7r66v/au3E8H8EhAEVFTYCWxAXCnr+IvkW6oXqps8m8mzWicys+p/dKv86AUv9AwIi+DwHSAKT96gV1wg3/94SBRE+A6YDxPTJunnnFtNYz4QGg+D79HUBMfg6BQAANAddFR0Al/ueFW7r1Qtk/vYDohsDCKIUkhYLBJn4KPhU6lX/JOl1BqH74gh++aP8tx7t8W0hxPekCm0T0+raEI4EIwRtLREh1x+YIar4bv0e9uXiyu0e7c7vsu1dC9wARg6SEkIC6hq1DhMZDCYvKIwePh+0I4cp5CpIIOwm9CmwHC0vDRuBGicyMgQMKg4reQyOGA0QIRZD7XMEVBCL6eYkmCWFGjQciyy9HSspOzgXGhEMKxG++wjZKPp47hzyYvBnJ+wY9CEORwgpMS6JJkQetwgCGRz+gfQ//NDyywIr8pIY4/59AFwa0eIG82DqzOjC8C/ndNzG+P7v4+Vq2cnVot872+YHRfQ0Bv39uwE8CuQHvP0g8pfgxOQCxenCT+5ByLLoTfx48rL+wwCd/WbxZNzl0o3c+tHA7b712dtEAWsBGPstHBT5FwD9+rz+h+tk7+PzneGxEhLitvlrEg7kfQo7+znrHv+H+aPxfwGeDs/oUgukDp32PBII7E3/591iv0HZtMPz7BznFOc+C2TuIRKDHaX+qh08CDv6EQr87BrsZv4Y/Zf7kgu+/uv9ngP3/0PwZvaR+RLuAgrA9bkDyQUx5nkGofXO9LL0hd7r6qzchfse+J//fRT+9xL+kBvf9n/2uwPt4/bed9kO7ePMlf/9/LkBXidOBlsUDw31/0wEyP3+6tkLLfIz5PgaaN9a8VwXDOcZAO4PBPFGBA8D/OvNCToGigP5/bcJg/tk84ft6dzZ2OvQKfUz9TwQQB7RI9UwfypxHIMVpApy5svbdOiV7Pvt9ffNDdMUexp5IPYS2gVGC+4KcxKDDHMCDQQxGF8eqg4ZHqwRkhAZDjEUBB+DC3kXliCUFK4gbwu1A/QTCPxSAQQQOAKMAcceYSMLFewhayYVKAI4GSB3Ij4a2/qb9KPsDuVi5NnfgwtxGrsr/DhcK2sdpg1OEV8Cxvu49GT/XQLBD4gSHyozH7Aj/i/hKxsdKR9eJc8YExzJF1IaMg5gKUIDzxUyFR70KwGw7ZoH+/Oy/csRQhCHHYwYaSEnH4wCAAIU+S3YdOcS5Ev3HOPC8Hb1WvzkKlcE7CRSH7ryl/Mg70vfZvb66bT1HROkCoEEjAFB/i/mqu0t53nbCujx1oHZpt6szQDLNeBwz4HIe9nn153YwsbM46DSWtw6D94Ghx6DEovoR9YM2DfFxbgOxtnXIcCHy5AEbvaaBkQZuO+0+fH3FtYS7sz4iduo3LjubuJw6mz95/mR+uH45/9W/In93/wz8F7xLf/P5aP+yv/v7BECHOuT/BES5gIfApIYxv4RFroyqhysHUIT2Aal9XXZQc096n3uCOHE+0Pj3fjoGKQTHxm4KuwIsBHJJnEANhfp/NEAnhk8C8sczRMNF4wR7gtOD/AEKwv2BKwVNhXVBnET3Ah7AgT+uPjV6zP56BHRDKoYVApW7rES7iyeEPoiby4nAqz759Qe7MDl7eF1C3D17BtAHjgI9fnqDxz+jfkdMkoOhgRlJ+YCYvyzEnj0S/uFEccNEv59CF7/+/Gb/2L8WPhU5+P4Hu2KBBj8I+Uz9pnY7fy24VP5qgwO4l0aJwR46WMPwvVK1dvpbtm8zRcG5/kk8lcAxPA6AVsSZRyOB5IB3gUa67brlfsK9u337hB7DmT9FvPwAtoHAwI4BJHzWv4v78D7vwvt/JoJ/fsFAgcN2+/+4Yn3Se02AZATtx6cG0YjYDUTCnsmKwuD93MBx8md1TvY1eENBZAIOBWsLhkbpg+1GtoFZv3wCvQMQe9S83b99gVnE4MaCQkZJjgp/gcIK2MEOAnuF+oSJx8nEEAIoBLVIVsDnBT4CBrsNB7M+7j6jB6cDmsaKybVF/P8ngZ+94fkFum83kn2k/us/38KAA1nFkgYmBZWAhUf4A5tCCcQm/cJDbb8/BT0Gb8SExjgAvIPAvrz/lsEcOta+ljb/uOf8+/Pl+DI4IPmauau4h74TuF08qn4Duud9cT4PfYM+lH+UutV/bzPTNAMzT28ed8/4EfmBxNrFnEMpCBa/kn6g/C28uXsj+fl8OvRpunb/MbxmfeZ8NX3qvK+9JAR8/dIA6wHcv0RAy/3OAZH7lQNXv1L7bkFVOl48dwHbwZrF20qWivbLDQb5BY6A9vtctrP1vXl8+l88m8LrhtIEaQdxx/uAisIqwL1/FQOqBO1AnkLAh9/FToVPh3HImkUyw0RFiEOkfveB04W0wXRFPIROAekHEAK6+Yc+l71xtf57ST+awNEDfAbwR8AEwUQk/nQ9BDwytq+yrjtcOiR0kf6if27CPIRkCemGWsQ2gka8aH1O+7T6dPwqfqgA+39tv67Cd/78AKzCVsFvu6A/zf7f+mm8BLzld2h5xsCYNR06lb0hdSf9on+2fVdDaIFdw95DRMEQ/Xn1qbQTsN/0t3US96669fmtQ4GE1IVxxgXCdUJAP766ev4l/A76LTwOf8jALT/KxJ9CdEGVgqD/BL5Bvp2+BkBzv1IAMLz3fuT/nT01/q48+Hztu7P60v2APgTFYEgphICNjMfAhSIFPPvQ/AI59XqxPU1/b0H8/uMHFANtRDsHcUPOCRtEtUb3BNhBJQRqA6OCe4K8/tCCwsV3AmYGRkZ8g6oGfoubRKYGw8oMBA8Gm8T6A5IFNcGwQvRFlQDsBP0E44TdyYHGKQafxrl+x7xvO6R4iLv1v8p+uIB3yfmH+Ag3zhpH7ka3RqvBHkJBQPO+MMAHQ8uCcMEwRNCF3sQyxJrHIEWFQ0rCE3/SAKmAHjyngVw8HrtJvNc24vmrOhH6GDnjetF7Jf7p/6eD5oMrPGh9HbiG8nh1EncP9eb3mD6WPqP/owcl/T6Er0BQeo8BFTpz+VO1ZPacuMe38rj+/QI6VTwBwcY9S/wN/ZQ4XT2rvW23PQCquxY7XL3+fBS5/zih/XZ9e3+MfwnCIIB0QtxCKQI1xXK7sj2jd41033jqt2y/87q5AaoHBMMqBcCClAa9AsHByMOM/mw57b42fjj9h7/AwLC/9wMqBBCDhsVkhOuE38JlAcXBsD+FQm1D6P5AA9fB/v2Jxh3CPIE4gbyCncHKwG/FrkGwwFs/pHqcOIj42bb89857VbtYQPLEqQMmiS1IhMGAh6KEK8B3gVD/hLyGu668nDmm/o7/VTzzP8pE9n/ywaKEyEHdwXJAbz+P/SBBlrx7+yh86rnwOvBAvH43/CSDn77uwn8BzoHTAieBtL+kdJ/2EjW68x5193sEPbv+tEjFSXNIGEdqg8JEiL+VAjmEbbvjecS9HDr9+hk8aHzTAFhBN/6Jxz8FjwJBCGoA8b49gQBAQMAKfqiAAT+O/KUAfgB8gAFEWkMUBGcD+YWwwXmAfgCzujK8bTvQ+cM9mr8/ALTDLkS4BM8CowV9Bo2G/oaCxiKEAcQGwowDnkLWOMk/3j6rOzVBFT4/gWoD5AU0SYtIYMmsxriHMUnVBA4DzEahRKWD9Mbihf8FYUSQhVxGGERjBofAkYKqAKe0xbgUOho5VLbT/wBAW8HUi+wJ0Yj/CYpG5gctyfqHnUCoBw2B6PrL+zR76bxwOe+/m76lgAGFKQJqBymHmUGoBnNFLUBfQG/CJPrbPCj8crqSe1k+NcL8g2YFtMMVwXQ+Fjo/u9ezRrOct9DzVLkxNK86k//8gYFDnkItwcRHJIMBQ4XFwcHawaf94nbCtIlz3/OctaD5BjgNdmf+C39g/+X/oQH3fUa6br3quR12Z3ikdMc61z9VPJe7LcRsQS65zQDne8K35ftrOXp07Ljh97K2tnlydQU30f92gL7/DIJBxDl910IwQKkAQAJbQEpACD5k/+R3dve7+uH3ZHsOfHmA8UGgR6sHqwR1R+oA9UU1yoHCOwEqhaKBEnsEvvsAtv/exwzG0YYjBkXEZoBJQEe7LzRBPKZ7xzp2f2f+rbr9hDJHPYTtibmK+gXcR3wJHUKfxEJG9gGnf8e9GDgGvEi7Snyl+yZ9IwCZw0MKYEVOBtAKNL+wwNW8n3iYu3E9Gj6kgAAAxb4qAtzC1YICQgpAgkU4/sr2KjmoNS8xqTb+ulg46zpSgOQDwAWGwVIB0oXN//aAuYRlgeID54McQJXAaHfDOIm88DkvOF45njtK/pnEK4aRgzVFuQLmfxjDdwKuPY38t37P/P39tL8RfhpDxMSg/0RE0YS0fDC+4gAN9rn8YYMnAFB9cz8Hv8U/d4OmgCkCVwgHRDDGQYvJQ7cEBMgKQa0+qf0VvCH6876svNc72D+L/trEpYm5iFMH2Iq3yFOFNoJtPn6Cs0GKwZfGWUSsBxWHm0fqit9HTQXSiO7ENL+3fPf3SDpl+Z/8Aj8dwpgIfgNIyzfKkgUDiwxJN8eCRbiDIUdrBYdER0P5feb3gzxFPNrACcPog0KJGcguyBEHy8gkBzTEh8amhAK/WMEXQd7CEoQQgWaBlIaaxiaEbcG9gnYAYnpYuxJ2tHbIvD169wFRAFw728NOhRnAmcFHQed/XkKPAixAcsKfQUi/9UFXv0E4LbrHvPK3iDdo+Uc6nj7k/xKAKoMHQA56z3skehQy/LOdOpM40XbHvRm8d3oj/Zw9PXwQfmn9N/p/OMC0NPCtMw/2VzgcOOq9lH4bvPz/PXyUO7b8lTeZt/n8ZfkduRtBuoA39+Z5vrn0dy03BjcTtqk6D/slfVZBjv44fMXBFgMT/6F+ZH5pub58NPyHOyd/NUJaQiYFwkdQgroBmb4Bubh24vG7cUA4bLoZOLf+EQQFwwJFmcOQfp+/zYKpBB7ItEQwQ5EHqoWsBrTCkv4gfSu/rLsBuJy/J37KwgPJ38m4h+0J+IoBBfBB9vxUOOf4ZntUAfeD1YVjhMTInsitxa9GCcLgQTp98rtWNuT3dnqJeUS+pQHPA/VE18eFxnaCcsQmg0hGlYbDw5hDGsP1wzWBHML9AOh+BMFdviJ6+/yFPJu9q0F3A40DxEbgxXZ/D3qdNtO1c/c6eRD7274Yv1xBfIK2RgAKW8mNBvRBZX0UuP4xonKL9V51uniK/XJBfIMHwwbB/4A+fxY/wAGPA02CzAG/AXp+cr5pfjR6n3wZO106+H6Gv5lCEgVsw/XHscf+BUjHs0kMA4I9rz1L+1i6Qbyl/zoAKgHxRr0KRkrlinVKMcaJRJEAWjkO/COAPv9AApWF2shqiM8HkIVdQhjA30TmhwlHDEikhVQFX0UtQryDfYZdRsdFVQQBxZ5I6gjRig+NR8n5Bi1IEAdPg/2Bsjy6+Sy6wj0tQQ8Dg0Q7CIELLQqvDh/NgQlXiEVBtXp2+SV5unmM+oU/TANkhjhJt0jmhVhDxMOfxWSFpgOBweODTgK3APsBq8CKwQXEcMJmfhGAPX78/fqCvwMmf69ArcRqAvFBrb/i+wO43DdMdha2qbmJeml83EIyvnd+YYCfPim63TaDsXfxSXWVs9u1Lznn+qL+1IHVvsg7EXk395e4tHhIdFK0inVIdII5sDzJPS49DP3Zu5W3CPUtM+u0zvgcu548FLvJ+8z72T2P/YU3gDSsspoyEPOVt3t7Cv5tQDM+gr7UAEDAvH2duLpy0zFUM5Y0yfUcODK8fQAsRM+D3jzVuXC5sTv3fiQA4gH+fiw9HL54fZe7hr4aQvcBqgIUgqxAqQH+g9hDYgFNAqmDa4KyQqqBqf8dPZR9E/v5eVu67UN1x11F78hVC0bHHkZKyCQABLrT+907yDzGP1pARkRfynmMNkjdxYrBiEAFPad9foEcQH+ATYRUCBcG4EbZygbLFQv4ie5FpgNHw7mD3UW4hCvBs0RrBh3HrcPn/cK9ZX70PXP6EfzBP0pAu4PhhQLF1wVCxKKChz3EOiB7R74meyw7VH+jBFKGqYRqAaX80frqOKF4K7tKemF4mzsJvq++wcB5hQ6H98kGyOBFw0JXPyT9RzuUuW04+3oavT6BLsFFv1m+Bbr9+cS6YPjuO7I/8UEShHmFAsJsQ69EI/6wPDr6T/kQeyJ8BDsfvoRCU4NvRVWBx78zv/z/ckAfQjcCowMnhFjD+ASMhUxFSUjliXfHqoSsP/V9Lj7TgbcA/AGng7uGlgm+icxHxcPmgtxBUn89flOAfwTwyOkLUAp1yszJuIfoBTG887piezt6mruFwG/FVojXDmJPAAqphpWEWELBA5ACTwDkAbXCwsUER30I4khkCtlL+IcSA9IAUPz7gAdDhkP+hbwG88cvyKaG68GrPta+HzxEu/58Sb06AzXIhkdsxAbC1kGjgAM9oPcN9FB1g7e9eau75f74gn2FX8VrAVN7t/eVucx99Dzk+9D8MDvCPnJAef/ofYr9Lr75/eL6JXbM9JK12rqJ+zZ4iveNezX+4P9T/gU5yLpDvIU75nne+Tj7qX1au/j5WjiWOT151DgM9F3zT/T5doC16zXquLj7zn7sPkU6MLTnNA72cbcpuBu5BLoHvf8B7UR7hEPEMkWUhowDmT4ZOgr26zTldsQ5OXfheD657LnL+o/7bDtnfNo+en3Q/3eDTEcqiBvH+4cshn+E4wDi+RqzS/QxNbd3N/lh/O/AmUaaScxIb8cFRbiEBkNKQP1+bb82AOiDqoc5B9GH/on6CaBHHcU4gwVDIYU0R4xHw0aIRG/CNgFIvyZ703tGPRk/Jf+EPzM+8EJnhwTInUdFRpCF78N8ABk7wjiCOCV5xLzePGZ/FgNaw63DagGtP3A92z3M/hB9CfzPfkjCtkTSgUS92TuL+8ZAcMIpgRbAxD86/JS8l70wO7Z6n/vvu9g8PHzFPOw9cb7S/9q/e3+4AX+Et8eRhjkC9T+6+ZG0AbEoMXjz2bfxvDZ/ZoNdRk4HNUXXQ0DApH8Qfyu/NX5ifNR93UEPhQLHWcaYxN/EMUOkAX9/Fb3DvTn+r8GpApGC5wRxRu1Hl8XLg3iBtMJ0w9dEcsM/glUDocamCThJwonXCPwHC0STAEC9ZHz3fhWA1sLwRJ5HuYmKyk4Jt0bHw4wCk4JFQc4DlIVMR0TJ3ssPCS7Hxkn9ioGJ1Ad2RT2C3cCvPr7+aAAeQthGN4cMRj4ER0PiA4LEXMRTBRIGcsdvSIlHb8T7AQx8jnmxt6L4WjtEvvVAwMCrQOGBwULuw1ACcsDRACB/tT6L/ci87zuk/0NEeYXwxctFvIZNBr2EWr8ie0l5GLfIOH13ePg0e1u+Mr4avQa6evqKPy5AY/+Tfxw/1IDjgVxCIIFjAB8+FbkCMxvvPC89Mrd1QrbeeHx6gL5IQSOBRL7Le/K6lbpzOoY6Xfi793R4WTrvuta5rjqOfHd9nz/3f+4/ar5aPHp5m7XH8/l1c/kaOuV6vXq9+r36u3lZOKq57r3qgQ6DA0ONgiGAwz55ed700HILcwa4Dny9/SH9gT6Qf8FBLMDoAEnBpwMeQ0JClz/9/IA7m7xk/af9sb3xQGzDuQYwxw0HcUYUBODE80KDPn87lj3uwJIAkn9VPsY/w8JlA+1Ed4YliO2JcUgAB/FHP4SJwdo+ZnmId9u55XxyvVY+s8GyRIvGFga4hMVC/QLwQoFCfoHewKy/lX9yQNhB8MGGQnFDzoXFRYvFwIWjg6aCisGBPzv8cbtlfCd8RLsAOj16Jvz9gGEBA0FmAv+DI4I0wisBX79i/hg7nLlz+MU8egAVACl9i/tFOs773bzaPOV9g0F8hIRFiUK9fVm6sDof/HC+H/6OAL8D7sYiBATAs70FPXsAMEHSgYBBDgHaQ3gDY4BM/WF7LDpCutD70/zYPzaDCcbTiCOIP4gNh25Ewj+/OSH2q7iGvFw+3cEmg3+FHEbNBzREisHtwL4A04Am/cK+UYG8hL8HCsjCR48ElANBQoDAS/4+faX/WkGmBBdGbIhbyNQHNkVKQYU7w7k0eIE6ij59gcbF9skAiqaJWAhfSAZFjADo+/22+XSGNnh57j61wV1CdwP9hd5GgAWng+/CXMCCvx29ADxuvbV/qoMgRUbD+IGyQEi+5X01PnVB4MQ6BH8DtMB/vNy8iv4Mf4x/1z2hen65/Xwm/c5+hcBdwXaCH0Omg9dCa0ASfSf3NXIpsMdy27b1+xo+bsCdQtxD+4LxP6P8SvtKe0Y60vnS+bf6CDy3frI/CL8svhu99329fEI6vfksOVc5XLn8+uD8Df7swFH+lbsut3Z1mDbbuYW8RL3f/rA+sL+1wUhBgADU/zV6VzRFMVsxo3S0+N97pHwBPVU+8b8l/4Q/9f8yP2d/3z8g/Lf68zumfZY+YH0evVW+RD5sPWj8xL2Lf+cC/YOLxDwC0YH9AeOB4f+P/C06jXsEPWp/6wEDQYFC/IRTBmWH3UfjhvkE+n/3eT41QbaGudH843+Jwg4EBcZNiCOH+oa9hljHlAekBP+CsMH/gRdA4YB+f13ACkIdw51DbMKcQpbDmUWwxhKFyUThRJ3EkgMUAHG8qbo6+kU9eACeQ/XFsUYXxegFBUa4B5AHnsaWweH7cTbUtsQ43vmHOu+8Nf6qgfeEmMbQB2YHbAayxPwCPH9APhR9RD9bQQLAWL7ifsDABkF2gpdC78NxxSxErUOCQ3aDccP9A1tAlzyIO2b7mD2QACmCEQUjh1zIDof/CJaKJgmOh0nCXLtj91D5Tfzcvvd//ADUBHuHQ0jVCS2I70mwyl9Kf4i9hsnFMELZwnLBaYC9gpAFFAX5BrZIJwjMSiBKTQfrhdzGOYcERrTExkIrP2u/UYDqhDeGoEkgTCYNPAsjCRKJx8qMyZUHfIG4ey65QbyGP+5BWMKAhF1GfYeDyBYIVQjNSSSJZolwyQVIwAggxX0BAb5FPknAvIIzwq9Cd4PBhbHGlYaERSKDQsKAA9ZDSMEDvn38q72XP7FBUILTA9bE8ESswiiASsKOBPNEkQFlejv0Q7SFN5i55Pug/Va/XUAf/uf91H8VwK/BzYKWQZlA70BHPzV7YPe3c5gzt3Xidoa36bnrPLb/oMMaxIXD2UHk/3f8nDlyNc5zVrDBMCmxs3TIuRH9i4H4gpOBU/9ZPis9knxgeTLzai5BrmRxYXTVNvN3hjkCOw38JXwxvE/9Bz4uvlW+pv3k/KF7l7ltNbvymrKj9dq4IXm/u+j+KQBrwhjCmkCn/fb767q2eND2RbR9M6J1rjkBvQc/94HnhNjFR8KGwHO/4AC7gB89f7fc85Mz6LcEO0g99f87gODCTYKDwXcAf4DBQcACmkNvxHZE2cRuwNc7v7fHuM18aX5FPwnAvgKOBOoHJwdjhNhB7MBVgOSAjn+dvlg9J/yJPjx/wkIdRHRGPYbABd1Dg8JdQfVBwT/he5W4wjipOTf6Y3yQ/n8A5QOhg+7CtMLWBRAG9kZSBVOFlYb0x63EyT5FN8Q1pPeCuNg3xrjbO+UA90aDCV5HmsU4BFpDewDcPg/7dXktN8j4qPoP/acCXUazyC9Gk4O/gSvAov8me0Q3YXS09Ba1eXcYukz9WECExCSFYwQ2AoPC0ILpArcCpIOuxG7DscCRetg0r7K+tWd4s/q0/QRAmcUEST2KoMmABstEtEKfwB/86Ps6+m26N/rO/IK/9wNaxszIggc+hEAC78GwwNY+s/rvOF/4kPll+x++7EHRhPwGlIZShJMECsSSBLyDgIMCRIRG/YdbxQM/yLoj+SB8FH1HvSH/E4OTiAPLC8qdyMZHOAVIQ7PAqX45fQA+/oAMARCCM0SRCFWKSkmgR2zFA8LPANi/CnxsOTt4wztFPKP+KwFDxBvFgcVMgn9/m8BCwuuERcUUBgpHx0hDR1tDHTt/NZe1xbfFuHv4jHrO/sHEM0d0xyBFQkMBQXE/LzxfeZY4vXo3+648i34uQHPDA8SRAxUABj02+ed317ZTNLjzz/U2ddy1GLWP+Xv9ev+/fwY9gz0bPk7/3cAvP5w+9/92gMuA4/2heB7zgjKas2k0GrTfdd/4QTyWv6eAooBif2R96bwm+i84sTkxOqV7BTrm+649/4DLgreBfX7GvAe5PjbwtY/zjfJbtCH1jHYXuMc9rUEWQiMBIf98/ZJ9N31/fgU+Qj9Ugr0FYcWTAwo+Cvhg9SF0+vWxtpo3mjqGv7oEXUZqhYNFG0Pcwe0+lryg/Ko91H9cwHYA8kKbRgXH/YadxCgA+33+fEn7w7pBOgp7kfukeqT8B8Axw2FE4YQIwmaB28OXRdGGy0aphlQHtEjGyK3Ez38UOt26MLrj+7K8GD05AHPFEgf7h7VHeoePhqxD04EZP0c/5AGPgmeBWsJDRmQJmAnsB4yEtYD6fZo7DPjQeDb6bby9e6j64X1Bwr2GxsebRSWDloTXBg6FpgRaw95FPgg9CfdIJAQnAKb+crtVuP43gbhcOn1+XcMnBc+HXkjtiVpG/QKP/5W/h0IgRGgGKAc5iH8JkIqMSfbHMURxwdu/Kruk+Gq4PXuEPoQ/HMA/A2HH4kreSYJFooNkhNWIF4o6CvuK4krCi51LpwnVhnkDvoJPAG69M7squ8e+8cGzxLFHJgmsDBGNiczsCB3ECsPeRiwIScovSsvL8s1hTc1MNklgxojDU4CSfuf9rL1PgCoDTIOSAVIBZ4QExy1H1YcExnRGn0iiSZpJfIifyHoI64qmirBHdMR7AuYASTwi+PC4k/sXv5QEOIXXRodIMEj0R1UDnsAGv1UBN4NABHyEOgTQhp3G+wWdxAyBQz2+ufR1x/MN9KP43bwhfKs8a72eP67AQT7VO5H6uvxg/0HA28COgHmAVkFKQTG+Fbtyuv36vjh0dSwzQbO39X43CHddt/P6gL5i/1e+Krp9uC044Pphe1H7w747AJvB6YDDPzE77rf39Nkyh/BO8EYzh/bCt2H29HerOck8rD1UfK67LLrIO0i70nw6e248Fz4kf4A/Cv14fGX8cTuXuKT1MfPSNVe3r7i+OAn49/rFvn+AtYAXvbl8e/5LAKOA28BhALoB6oNCQ/FDEAIPf2L7/Pg79FszFjVzuf18nzzyvfwAW8HAQWP/mz5YPygBMkKUAu5CQ0MABPqGSsadRPZDikRWA4m/xDv6eWT5OXrBvRP9436QAb2FeYbzRT2CQsFhAfoDkIUFRhOHyEmjCQhHwIatxA4Bc74qOv233/cz+gA9yv6zPp7A+gSUhwLGfgMxQOtBA8JrworC9MNVhPNG54gyRgJDfAL6g8HDPYASfe87n3qS+3t7hLsTewM+A8IwRFAE4oS5hKUEAsOcwvRCTYNuxKoFaYVlhIuCp/9O+5i3DvTMdpe6Wj0i/bE+cMCuwwVD0gHJP0Q+Sr7Xv1H/mL/IQT4Ch0RRhDmBQsA3AQ8COgBIvm48njtbuqJ6e3n9ec57t35igM8CYMNERBMFQAY9hVQE4YSdRKKESURwQ7RDVkMMAmtAB7wk+P44o3pUO5H9iEE5hI4IHcjfRsEEzQQhg46CIwCywEyCA0XpCNAJEQanBQJF7UaLxfTDTIH4gES//X6svTA7wjyWPp1BLkMQhIbG6whex/JGO4UtRRjFgkZBhmzF0wYOhYdDSb+nesA3EfdaOhD7b7twPQpA/QPXRcTFQ0JAv+f/bT98fnd9Kj04fvuB6gQ4g7FCPwGIwjsAhr4ie6q5onieeDC3JXaTN/86J/vrPEY8tv2dv1lAqACM/2p/TYEzQncCIEHBQcHAzP+UfO235XNwMoM0NXSHtYr3sjrIvnVAfIAifhJ83DyHvEA7W7oyuiX8Cr7vvvM8WrsVvAi9I/yBu6V6hzqEOv35dnZsNFY0QTZ0+Bk5ArpTfEv/E4EBQaOAJf/QgP8BPgD4AHl/9n51/Dz4mDTaMpmy7TPUtMp2hDoxvu5CqoNWQpzCMMHiANy+/nvzOjb7WL8+gpWC0gHIQqDDJYHevwx8nLuGvT3+kH5S+/I6S/vsPa49t/y2fbJBNcVMSBII2kggxxOGjoWyREPDjQMFQhV/t/uTOHP4KTlLeaw5u3tT/5GEVIe0R5dGbAYgRm3FcMNSAUFAQEEwwttEAkNQgddCFILrwa6/OX1TfYv/H0BL/5o85nqUO1J8inyO/DX85wABQ8tGlYdcR8PIqQgIxt9FDgQtQycB/36dueq2XfcSeWX5kHjleaN82MEsRLTF0gV5BRlF+ITGQrQ/xr8JQAlBykJPAbiB/IO6hEfCdD8SfV69en6Xv+d/ND1pfPz9mr3JvF7617uzvzgDAkWqBnFH2MmxSYLItUZaxHcCaIAZO+b3BbZaONW69/qXO4E+68MXBw1IXkdzRnXHSEfmBYpCj4EfQcLEUYXExHXC+oPwxdUF4wOWwjFCgQV6hsbFn0IgP7I+lj4YPSm8VL0sQDeE9Ukey5CNC85WDbdK2khNhiID1YHP/2l7Onie+la9ar5lfdy/BcKUhn+H1of1x2BIMEiwR0NFAkLcQg4DjwTPA7iBUwICRTFFvAPnAfaAWEALgRMBGz7qPX39434n+/V5u3lcu4e+7kEzQ0hGcUovTMMMqgkIxazC4ICL/e85NHVHtmT6o/zYu266WrvDPlrAr0Cvv0nAbkNmBOoDG0CcPwS/6wF7AYc+5Pv8/N8+7r2TeyD6gjwBPguAMj/evcY9VL1cO0n3krSsNFg21zpHvJi+F0F8hdMIYMdCRXJCQT/Q/Mc48DN5cO+zRzcUuAS3m7jYO4E+JP7nfcA9GD9uwv0D/QJewM0A38G+AfX/L7q/uTC7sT4cPnj9cb1hfshA1YCHPi870HxU/Y38h7jUtTZ1QrkYPIe+h0ADxG7JKIrxyQVGtUOYwQt/E3sOdqw14foMfcc91r1f/xICSsQJQ1OBF8DkA7TF+IU2ghlAfoFog5WEbsH8/wK+9n+KvuJ8ivx/vYuBDQPJw6iBcMBwwKF/xj0uuXE3u/iNe8r+PP6pgF5FFwp5TIlMM0lgRjyB2D23+A10NXTwORH8HLyCvaUAF8NlhJQCHT63/iAAj4L0Q2sDdEOGxWWGgkSS/267/7zQ/rT9VrwcPJL/F0JzxBQDXEFqgUXC80ErPLR4+fhUOYt7JXyeviQBsUYzyOoIlIeexpQFG8JM/UM3qzUpuHl8ALzEPJY+ZAIvRY0G3ESXQglC+oSaRJUDJ4KnhFGHtck9hrsBiT7HPzd+7r1KfUE/hMNmBy9I0gebRVOEqgQGwj3+2bz0/Dz8Zf0fPg3/p4MVhwzJgApwSgzJcMeOBUhAFDo3d4C6Vj1i/zTBEIPABxKJRckwxW5CgIN8BGcESMPfxBlFYcdXiETFtcFzwBCATX6e+/r6w7zaQQfE+4WbROYE5AVoA1/+03pCuNQ59ntdu6l8b8BnhcjIMsbExiHFxUWUA9H/qzjj9jI5Uvz3/Dx6zvzvwGWDscO5gKu+br7av8Q+bbvK/GIAewVYRwED3770PAE7Z3loNiyzmjTZOivAPoJzwUhBOAExP226x7a4dJk2VLkyuVc3azdSe7v/uYDJv1F+Df5j/sS9cbf6cbNvhvLwNcl277cWuhi/R0LcwSN9EvthfFT9sb0WO7P6vny4AQHErsN7AB/+eH5rPZk5+nVEM812O/rP/yAAX8BqgjJDgAGdvGm4Eve+uZ88Qz1mfBD87MB/giCAmz5bvygBR0MrQVw8zvk0+Vw8p3x3eqB8DIH4h6WKMcfvw1SBjgFfP4t8wbuk/VbCFgbIRzuDHsCdwHv+6PqaN0e4FLy4AgfFBMROgzHEJwRAQTd8I3nsuuJ+Bb/OfaD7rr5cQhzCMcAQ/3TApwJeQb58EvdduB689f7XPQY9DQDBBq5IY4UaQP7/xEEP/wY7RTmVvBfCPIdXh3BC7MFvwugBQbvpNt/2Y/mIPuBB9wGCQa1DKYQ/AOy7qziQerz+dECHP+89qj3kf6IAo/+yPh99Yv6hgF8+inp5eL87SD2o/PA7XryDQRSF+4Z3gmn/YoBDQprBhb57/AE+Q0NWhxzGdMMKQnwDsUNhf9Q7MDkge+J/hkENgOsB70QshgrFzwHRfW08Hb6AANMB0QK4gtIEDARkA06BzYIuwqYCHEFmfw99Cn2sQbsC+AAT/3cCGMbgSctK0YkLx5zIdcg8hYnCs0G2Q0ZHLspwSl5IY4eRiCMF6IEpfbQ9AsBhhLeGk4bwRvqHkIduxXiCMr6j/qUCUob9CAEIqAmoCcEIrUbnBgrE6QOWwtOAbjzo/QyBysS2QySCPwQFSJpLJwphx+HGRcaYRnuFLEL3gTsCbMYhSEtGogSWBbPG7AVZQeX+k30BPoLA7kEyQNpClYVexoLFBMEpfjr/NgIxQuMBLD9Jvr19C3xHvG48Jnx+fUS+hryR+Zs5wrxfPH55wToYvS5CJoVyxXDDz4InANL/UP0cueT5LzyaQU4Ct//DvpF++35MfFu5vPhKebZ8Rz3Wu9i6bjwVv2y/pnzh+Tb3UXjCOo77Frr1/GP+lr+WPoM89vwQfA57cTdJc76zBjeJvCZ9IPzl/YlBWcSkBLqBen/rQbHCIX/0PP+7vvwIPX19v7x4+om8rMFyRDYCGT8EPgc9l715/EG7eHpsuvI8VHxMekz4hboYvU8AGkHwwkAD78UqBCQA0Pzn+pc6STrJ+QC1arRHOF/+SkCdP3t+UYARhDqGNcQNAFOAD4HhAW7ALL93f6cA68NsRAZBYX+CwgVFVgSIQdlAC/+//4a+rDtpON05xD2BwLWAuP5DvRs+PYAiACV+S/8pgroFVQVrwgU+dv0/vbx7vzYRs2R2Vzz2gGX/Of3EQH4FO4b1Q/+AscFQBLVF/ITbQjDAzgKBRAnBwb15fNvBewUIRFIA+f7awI6DxkL7/mF75f1WwEVAhj45e7r9YYJNBhbFHkIkgwxGSMfbRmEDs8FNgOQA0/1bN+X07zixvzBBZoA3ALoFx8t4TP6KL8cexsKIRsi5hgZDdoLXRbJGY4KqPbn9KIERBOiFvIRFw2oE9EgpBwbBQj0g/ZUAy0NJw7XCYQGQgziFawXsQ63CtwW7iSFLV4ryyFbEvwEZPzd7vbdhdWs5icBBw/RDUQP9BtzJ6gpsB1YD3cNSBR9FmUMxP0K+OX+mAkCCXz/uPs6BQcPNgvLAcb8eQNMDuIMuv2X8LrvO/ah+k/2zu/58uYAPgsZBlj3bPTb/JYGyQcFAEX1JOzt6QbiqtLVxTvQO+YO8tPyQfPK//oO9hNAB3L58/eP/tMDof3G8M/qpfFy+ZXzWOhu6pn38f0z+THwpOor79X0CO9i4/Hgl+iw7fXqvONw32blh/Hb9lLwFuy489L+0QNIBBcD4f+d92Dp/NfLx5jDGMw32RDgleeh+FIN+hqkFpoJbv+X/vn81feL8d/sFPJw+mD+0/Rq6kHuGvdD9dPqwuqs80X62f37+UPxP+x27030+uzz4+Hm/PLf9sT3Lfuy+20Bdw1YFb0SgQnv+ij5j/7O7LzI2cWZ2g7gpNMh3WsA1gSkHYMzvSOQDQIWih4wBC0Wnhmd+OXitP/LFUfvk+jx8PTSc8p/9Mr7aOzkCXsmSg3b+VIJ+iJpDUwHmCl/E6IA6A/uIZwE7/SH+s7qleUi5wcAVALh9cT8ofJM2jXZaO609Cv/khtYJWcwQDiHM64ujiLJF7cIzPo58Ef6Tf6d+pwIyvps3SHYm/E/+nTwbQAJDA0Q+hvBKgIn4Bd1Gw8Yaw2QAuQICxMAB6gHvQJ4667dyunt9Dvw5f3RAlb8l/2p+4v1ePZP/mz+nhXFISsnOTqaOIku9iZ5HQMLkgWQA3/8Re3V3ljuaPaw7D/xFPiX9yL68gCOA0wTFyMzJYUmTB5gISkf4BsXG9cLsvr39Y/4JOkS32beP+62/KP+8graD0AOPBOsCY3vxu1s+nMCLgmWDn0i5iwVHHscKxkHCNEH5AbZ7z3m0/j5+K7vFvMPAaf4N+3uBaANuwSyGH8q0yAVHXUe5BVhGEAamBzcFWMEJQGm6tXaWuOy4kHaVOls9Nn5XBkAG+AbpBzDDJX1CO9q90fmqu6xC1IDo/Y8EPQXYwECD5wNl+d8/FAAqfkTDQ0Ck+3O+Uv78fROBU/4mAJxEXUD8AdEEdL5Q/YEDv4JdPl6//gCIPkg+InwN+jT6ij1sPugALcFDxNaJHMZWBayHQ0anBXBDLEEUAXx/dnukgHuAb7vIwPNBioAFQ7REcEOeQkfDaAG/gOBDjAQEQ2/F6IXywxW/3b1NfHL1vfhfenS9G0QhxvZGUoPFRCmAXvlM9wY3RDdVOxjA3sHxwIRD8cOHv8jALEBo/wE9knf09r42zHWeeZq6CXjzOzE6xDmcPkI+6rcmfrT7hO1tuw+APS8Hc9g+1jol/ItCyDnzOUx/abbFs903iDeAua2+i/+cvrj+oHyK+Pj4/fqYOZq517n+uNL7GT5EQDyBTgLawWL//gB4AGgA7z67e2Z8dD1Zu3C9+oLUhi2K30tvShtL20slCNOJwYoMyIIJE4jsB9EIcMe8haaFU4StQy7Egkalh+aJRUluyRKJDYeihl5Dun88/lXBJwKpgyYE3UevyOoKUYxPC1cJ6QjHxYO/f7qS+mH7HDyswJbEPoT4hTXF6QVcw8fDe4CAvXR7OH0pfiT6mrmi+6Z8fPpDOLG2O3Qx9Ax1dHRicsr2tPkDNuo2RzoGOlU5xjqvt8Y00XUqNp12b7ZI+LR7Of3uQG6/tf09+Yc3QjREMwp1RLW5dOs4aXyM/Lz8mT+2/108/PxhfE58jf4swWID4oTQhO/D4gQUg86DSsVohsXEQARNBGYBjIQrB/ZHmMbxx3uG5AffxvyDFIJ+AM7/dL/7gYHCnESAiNAMOwreyNUJhcj6BcCEzgH4/Yc9kP6lgA8CzgXpCVGKl4g/B9rJMUYOhACHKIdcxdfGgsarBZzFNwRhgNYCcUdEx5cGwsfWiJSHawdBiDLGtcYyRoCGzoOLAPqBhcLuQpfEEwb8B2JJREtOil5JKAaXxFnELkJbvYI8on9SAR7CsUOsQzLCT4LqBDBEQALWQQY/gT6le8j5Z3s3fr3/qP2jeuk5dnjPeG65THq8eX87cb8bvYa5u3d8dTt0gTeFORW30PWFNVJ2p/ZddTN0TvUNd8K69HjjdBExlS/f7fuuX++SrhIt5PEm86VzW/J2c+P3onrsu3f62juAuvP6PPqmeuB7E3t8+yL4lTS38/815fY69Kg0e/PWtUA4KbhkeFY4+noGOvN4A7WP9EdzWTKQ9Be1y3Y394x9IgELfvQ8/HyOeI13fHmXOXr4+3r1+0z7jPzDvnQ/aoEhRjVJ5Ic1wv8CY4B/f+mBF8BFwiUDK0EZP1GAcEK7hzhLAQpsiYbLmIyXDRzNZAsBhz4GdMfdRxUF4wdsis9PDVNkUyLRbpGukKyNkg2qD72OYE0/DsAPIknCh/oLLg1ljpmQGQ/cz3HO3M2hS3TIR0b8CF1KrkskCsTJlAmqCJYHLkcMR+MJ/QxDjJ7K4ku6jF7MPoygTC7JR0gFR3oFE4MPgdxAycArQMjDiMSkhOyINMoISK3GmsUdQff/SUEMgZs8q7tIQS7C1ACTgM2A4gHihnkHSMYHxJQD+oJaQCF/iD/iAFSCqYIgf1o/jIC1ft69Cvyne779JYBEP/z9kXye+p249Hmn+sW6RzsjfR29InvCO7X6tvse/Bu6cjdBNZy2Iff39k7yajDQ8kz2WbqVvLC8b7vevUW8gziTtoa3IPf/N9g0KbBEsMazqrWZNKmyynN1dZi3LDZj9Rk0svaHOgp5pfZPdIn0bzWWuBm3vjWwtpU3qbgn+Y164nzHvlY8Hbrk+ag3RrgWNvVynPKuswAyTPadvIm/xcGjgSn/I34g+wc3b7e3+zQ8Oviwtr82gDetua68BjzsPR0/mEEKwHA9s7qSdwM38DtGvKq8VTwsu928Rj7sv/V/tv6n+8t6vnx4fM/+DoJThbLF0YNgAJ6/Lz0aO4I95X8xPY5/8UKCwZnEIEiNiWHL0I0HyglJoUnoBuqDXEL8hUfHz4nmirZH7sWgxQRF28dPCFUJHEpQiwKLLcjAhB1Asj86/jPBagXRCL0LXcrZSNgIqQe8horJH8sMSjuJcUl5B38E4URFxP6HGMn8jHBPGQ8TjGgLQ4swSC5Gyca3RwTJYEoAh7VFwYeSCLwKqQxJyr6InUs4TgrN3MmUBNhEA0bUCPmJZwmOiW9JvAtDDF3KsEiaScfKDgapA4+EJYaqiKDJTgWtQO3CEgQ6AqvB2MGww3dIRkuUi7BJ2MhsB+oGdgG8/Lf73T8EQFa+lH2rvwTCx0YCx29Fv4UkBFODPQTMhNtBwIHzQpZBbL8UfAz4grisOwl7hTshfOw/GL9ofa68vvwJeyq8I37xv1c+t/ye+Y94UHoS+aL3TPhk+oG5wriNe1w+Cj/IwQ9/gb3uvi2+GTzoesp4MLZAOIW4kHbMdnE17Teh+SL4fbeat4/2CnXL9QAxfq8wcCcx5vVOeBD2gTUXNLNy7bGBsRGwD3F69F913PQ/Ma0w8nC5cCivw6/Pcad2A7pJ+mk5ePkBtiiyg7CErxau6jA+MyuzBvJAti+54HoNees58/fVtvt3QTacNCmywrSId6j6qj3n/WD7D/vCu4A4SHZ7dwn5NnrxPZw+fnyJ/KF71jt7e9F6xbpbPLG+On4uP0sAD/8bvnv8v7wEvdT+QT6xPn+8QDwWPrI+LTt+esp6jHtnAElEK8NVg0GE78PxQXoALz6VPBe9Mr7pvBJ6HLlSeI/7CL8bQdbAr71PfTl9ev9dv7M8Hbz1Q0LH7UV/gimAar3FvME94H6uPpvBWEU0RiHFRkM4gakDPALwv8tCUIhCisGJ1wX5hDJHl4iJxxrIyUjmBsEK9c2Wi0GJQgjdyJxG5oRTAnd/lkB6BH0EOgFHwsZHboz+EbuR1A7MTBnKYsorivoLFAouSTJI1QjVisALG8eXB6UIUweYCMVLik1fTP8KHEV9grmFrkk+iNzIgomHSw5OHM+9jqgMxkxETWYLvoayRS7H5onpi7jNRU2dzX4OI83uC2HG0YNuRFEFp4OkAv0DOwTtCHmJf4l5irBLZ4lPB5QGUgJvPsDAOgF0v12+jP8+fxB/TX51/rcAs0TrCEvGgIMVgjBCKYDU/hD7j/u7fZY/rz7Qfvf/ZH8+fbM7azittwl4VbncOT124vepuc189D+EQDl+Gb2CvU19kH/NfoI6pfhmdsl4JHul/NY9f/6MAL7/ykB+gkrBg0D8gZrBpP9oft+/BT2j/DR6oPoXu/I9RTz4fYi/C381/47+cjq1+au72T3k/Qe8aPyGu2P5S/f3dSsyXXLGNSf3LbnO/Av+5oFeQy5ETgNdP6f8hrqxOJa3ALKx7kIxWLaNeXx7Gbwk+if4gDmXOpk7rTvaPBH+ZQAuvaL8ST1N/At8tf0qPGJ9L72YvLz7SXp0+3K+sr3Iugl4XLjo+pH76zsBu989mj2DvHv7ArkjeZN9Qr9oAFrCCcOlBR7D0H8XOof1xrKctIx5t/pJ+fh6OnsXvnJA9UJgQbmBgAVmhnkDqwFJv+b7mDnKfBs7oXrcvhJ+cLrbu2d9Gr7SApIBTvxdO367JXnR+N54GbbyOB6+OwI8gnLCT4RzxPFCzgB/vZP+JADmgoE/NHp+e0Y/6wPzRFMCLUG6BMtIPwcFQ9hBYIBbv1N/rcE6AVWDJga0SJEHr8ULxM4EkIO0QUQ+O3ymfm0/+wCKQAg+BL7KwcRA032zPXn+Cj8XQI+AJf9Gwu5GW8eOiLVKtEzriohEZX/7+yd2nDf4est+10NRggVBL0UnBpIFJYWfR46JZQoNiInGn8U6g3XD1gbbx4ZHicnhSzBKU4p3yqBLGUuCi0EJRsXCQthAkf6yvXb+m0EYRCwH5guPjUXOAg8XDfkL40vezIKKqwa9gyu+yvp3eJU7tD7ZQMVBvAJsxUxIQ8nmCleKccnYyTHIAsgpBpvFBcQtwfFAf39bvU37HjtBPfYALkGrQVfCFsPcQtV/1P4yPmn/OH+5/i27d3pm+rd82EAWwsNFPwWaxSIChj+g/Kq61zk19pW0hbSouRB++oHERKeFDoS0xIRCdDxWOHt32Tcut6m5yfvBPq7BoIF7/lN8ovoqu07/DP42+nA5Z3rqfkv/THu0+J34kftSfh0+rb2i/TO9lb55/MM5szksPBJ++wB7ALJAKgDwwUM8sjbz9KgzArWL+VD5znpg/MjAzQNRAzDDUAVtxXLD1ALKvyB8TP5OgBMBLUH3g7PGVYbmhekFpINEQeaD2MR0wboAOn68eyZ4gzie+IQ5Z/1NAhYEaYaWib0KugoiSgPH3sR5ArcAPXtwN452F7VaN9i7Tn/Fw9WFZgdsCD+FIIFHwC++3D06e8v+IoDbwegCskMLQlEANn+4gMDAhD6GPfr/5YJkgcW//H30vbf93L5ePzt+3Lz1fG8+3b89/xSAjIFoAwbEqgTKRiFFnUMnATt9+fl8dxg3Fbfnein9jv/LgmkGtEjBCBWFfYMdQVu+2z87AMz/mjzhfPR8fvyM/ka9inzaO474eXgkekC6aXsGPzl/77zXPF88fPme9mJ19fbquFU7ST3p/kx+80CswAI92jxpOjh4MLgN9hzxdW9ecrP3vrnsOaL6UPsVuoa8Cb1EO1J6b7te+7X6gDkzuYx8Yv/cQx7BfX3uvTz9Gryqu756/zxL/z380nkM9rt0o3YWuHj31Tig/FMAl0LxQsyCZoJexB5EjAMMgryCN38Q/NP6ofX2c662RbsfvzYCREQPBffJmAouxRABs0A2f5P/ar3ePC29TIIexUjH14hVhkGFE4OgQQz+PHxh/dzAQAMqhKOD3cLMA9/Cp37sPg//aP83AFzCHUMBBlCNOc+0zSeMgonnhngFfQMKQKZ/60B5f+8+UHzS+8z9gUFzQ4wDqQMNhdQIocjDSFzHicUdwyFEtwTEwv9/CT5QgWoCfAFigA7+d330P0g+Vry3ABICtwBbP1w/U/7IwILBGr8DP7qBhsRnhiwGmMR3A7gGAAWkgZW+Xr0HuuF2CfbDPKkAM8NJyWiM5wyCizNHWESJRBSFR8Xbw7uEY4lCjDHKeYj2SLVHtEXWAtZAp39IPoVBLUUvR34HxcgGxqSGG0Z3A3sCs0OyQv+EYEVog8tFkYeshZzCLb99fst/8D7wPib+uP0svoPCY4ERfwk+xL2PfAa8WTwrvYnCF8UZRJICSv87/cBBI4LBwfuATgDRArJDHT9Iu686BLmL+rZ+XD+oe/n6ZXzsvVe8HbxCPAW7+vvCPBS83/8OAWzDbcTYxieHssVDwL38b7oCN4t11bb6+TO6uXuyPyiDx0SNgrXBtEHtxITD2b0Eugt+VQFfw1GEHsDxP2+90vzkfUz9IPzvPhT+1IBkgXV+P7kfduF3kXdBtUp15vqnAG/ERURmAwjEzYQwwKgAUwI9fpL59viK94M01bOxNGm0sfOP86H2EPsXv4NCkYSJRZUHugfDRsNGmMSFQ5GE70MYP2H9E3qEOxy+NHuwtj4zoPQh+DG8f34AAIPDmsUMhV3CoP4uPBD643f5dN30L7auu60/TIK+BLmCnMBtvpS59XcJdi0z93Y8eoA7Y/rtu1B6f7u0e4962D3EQgjDQMEdveT9EP+1wdQFAkYKQo8Auv/jfJs6+Pv7/Ia/poODw4bChcK8f1u9hr5U/cQ+isJWBvBH2capBi7Ft4T+hbBItMk5CLhJVwlAB5/Egz/k+XE3abfg+Er7V0BxRhrKtMoISF3IjomvR/gEBMDQ/ge+1kEwwotDzoSrhNKET4Q5Ajl+S36iAKA/xz+GwjRD8ELeQQAA5v/YPDj5f7mO+zz9u4AEw1GIAQq3x8LFUgRkgEr8S/v5+qu4V7fFOKs7HL4j/Qa+/oKMAfM/6f/AAH6CkAY8hLNBCr+GwaMEG0OEweb/FH0k+xy5evkLeoW81IFRBKKB8EB7A+1F7kWUAwr+Y32yv+8+TfvRe5H6HTwgQNlCToOABolIhUjsCHVGF8FWvEn5/bbHc6R0inn8/M+BSMZ9BvuGx8gqBzJDbMALfcv93cDOA74EmsShhLbE/YGKfZa9Rr24/YPBDQQCxX0HjEfkhHNBmb1GOyo8z/0wvNF+Vj8yQZaGYUkRiaiIloeIRzTDYHyn+Fc3svfZOTd7yT/4grFEmMTQA7mBH/4HPfgBccQ5AfE+3z79fz386ruyvs4B6IIHwd3CiMONgkhAuX3XOyD6azz+AC1CLEGVfyj9hj5GPyMBOYK+ARUA+YJ/g76D3sO2g+5EskPVAopA6z1xues6LDyhfVN8y31aPeL/XcMGRrqJxcrRCK3F7kHuvVi8OP29/xnBBcOxxbFFYUPbQsm+zftxPEt9b71vvofAnEJ4BWWHhkQzvor6yfXusqFyxTOxNn17QMCSBLJGpodKx4IIFoakgdg8FrYicnAzvzWhdAfzdnU6drb5B7zHPpW/lYI0w6/DZQLQgiV+zP49AQv/ljxN/Q37enk2e4a8yvtlevp6+XncOcg7mbwo+qm4NPaI9kU3rrquvIx+I4F+A9OEbcUyxXTDtUD4fCe1yPPXtSJ2NvkhfLE9OP59gxcGBkPSgST/gL03/HX+vf3UO977Zvz9AA6BncKhxd9HVYW/A08A5/2tvGf7vn2YQZQC+oKyQknBhUAo/e47xj0Yv/YAAsDTBEXGnUYBxZQGBEg6B+UGGURwQVs/9wGaQIY8BjsNfLBBGEYMhhIFOQQVAt5D5AZLRk4F18cWCOcJYUcUBLyDgsLTAUsAKz5gfnyAkwMphULIJ4kkCMTIM8Zywt8+EfrIuSZ3vHZg92N7GkCVhROH4UrsDFgLaofdQIv427c5eUc7XvqId5737Luuvl3AmULrgzZDFgQgQt/Aqz6avnqARMJQgfTBHMHqAhKCtcHi/wK9J3xO/OZ9un3Nfn//q0BXvc78LbuUOhg5dPvgP6UCbsZtCfbKjEspiboGqoVTAxe98Tpjem+4azi3/ed/Rz33/yKA+QEzwXb/H3x8/cJAgcF2AqxCa8JXBeQHcUYOBszHpIZDRRhCgj8euw15b7qqvEv9Yv7OAnyFKAZnhhxEXcEvvNu6E7n3eoz868GSBQHE+QTCB1WIuwbCRQ+B5Xxf+Oy5xrrWubt58rsKfSB//oARfco9878swLRC8cMcQ2uFH0XtxdzFEgGL/sm+n/1vO2P6LboWvSxA6QN7BFYEOQKyP/r6RbZPdKmy+HOe9sj5IvwuQniEzYPCQ91CpYEWwEg+1HzgetU6IPxvvl97xDg9tgx1efcXu9a+0oDjAueEAARRAUe83bmAudD9PP/zwaKDcESihErDlgIzvl266zozvAQ8q7qpu1c9XL5sPvA/tL+1/Vo8K7vrO5y83z9MgdxCMMFMgWiBEoDvv1D9BTpeeV76fXpquf36Sfycvoc/6gAxP9B/Pv5N/hW9GzvR+fT4Uvt0wWIGe4m1ykfH0AZfRcLC0v3YugK48LofPY4AM8IExXVFrMNpAaD/rD2K/Xl8lryPfoHAZAJyRXwFzgXgR3HICUdohmMFUYO5gHd9l7xbOpq57rpQ+319/YIXBWqHnEogS4PML8qMyMTH04axxZUFkIP1QrTEtwTMAySB5AHCQ3RFh0bwxu3JTgrgyGGE1QEMfMW7hDxoe+f8RT/aRszM4s5BDhAMnMpcSAGFOoADPBi6ffreu6+7mDyjfxCDOoY0xmwE3kSMBLZDowHfP/f/8UJUBaSHKAbbxbBFF8SdQbf9s/nqt383SfksOS64Dnn5fjVAgz+8fXl8qXw3+1/69XmIOr59br4M/T+8zv1Wvw+CUQK/fmV5bLbS91L3u3Y9tao4sz1FwYTCLMAi/0Q+4/+ewVEB1sE8gc8D4EPBQ2tBaQCvQa5BiUBAPn38qP1h/5vBQIK8AvuC+ILFwk7/8byieoE5Pzfh+Rc87cKpB+kJfQi4CAjHYcY3hQNDkoBZOwW2QzVmdcG1bLWz+Hr7ev8JwjsBVQAVgIFB4oFuQELAcUCawZrCqgEZPaX703xDvAr5TXXf9Dd00zZQ9+R6eXx3/mCAtT++uyV3yfbMdes1JfTDtj66If69gKvA+n8R/WL8dPsP+Ra1z3IVMRQymzOGNHf2LDj2fBQARMK5AhtBykGlf4A9HLr+utP87b7GwTyA//8VPfX8WLof+PC5OHn4+83+r0DAgtbD2cOJQXh9S/q0efC61L0P/8uCXUW3yXBLBMrHyUCHt4XERJ9C4gCQ/VD58jkuupB7wTzrPv8CQAWgR2WIgYmjibiIrsdZRw2HzokzSiSJ1IfnBa3EL8IVwG6/dX7qwBvDVYW3RqMJG0sLSyeKUAnWCPiHXkYqhdOG6wc1xz4Ifgozy+4Njk0UCo6Iowd0Rn0EjIIQ/39+LT8SAFtAb8CAgqUFY4dYR42HZQbqhjDFIMT4BKYFIgbJSFUH4MW1wyzBSb/8fcm9Qb2Jvcq/X8DnAX4B8sJ8AjeBuQA4/aT7dHoFuuN8On3lgICDuQSFxLmEHEMcwMc93/qReDA1RvLUsgpzUHQmdOR2sTjHvJs/0ADKwaqDkYU5g/cBnL+EPhY9nD6uvq08NPqavAS9H3vHO248Sj75AVlC0ILUAkhBU38MfBY5YHdKdpi3UPnrvD9/C8QRhwlHZ4aqhgxFSsROAiH943mqNmb1fjYvNvA3X/kPe9w/68MAAzuCToRdxfZEkYL1gO/A+gNyxXiFLsLBwY0CLEIAP9488bwNfNL9/33l/X99Tf48faL7gLjSd5q5dHt9/Ht99oCOBINHBUb4hKDCeQEKQVfAh728+VH16zPuNIY1qTXtN2D6YP6zQdlCVcEwwMDBhsGQgaSBhMLFxLJFw0XDQwfAZ34HvIz7Y3q9+1/9Xb9uwHBBfwJBQtlBxcBN/im7tvqUutH7YfyLfu3BncTjBz4IAoh6hyMFq8PEwYO9nvi19Pf0SPYdNsA3T3j4/LBBwAVKxkGHd0jsCU1IVIa8hVzFcEURBKqDN4JswoDC7EIXwNy/lH/qgcADWsMVAyMC6QIXQQo+3jtGuUz5sbqk/D19sT+Pgy9GU4gzx61F9cQAAwHB+H+tPP+5MDZm9qm30PiOeb37of8NAkbDbcIXQU2BR8CcP2F+qH7awHeCT4R5g5lBrkCqAB4+QLzIPLV89n5uwCKAaz/Sf49/fv55e+B443fTeQ36znzxvoXAvgOqBsGHzEd5hg+E0oO6AYC+1Dvsub44U7oBvJS9Vr4+gKiEjYc/huKFIgRlhKMEhcTaRD4DMcPqhVUFAkPHQv8CNoIwQVV//X72gAbC9sRPBGiDY4L5glZBkH90fEQ7hLz6fh2+e36BQIrDG8VoBoNHDEdnh7dF8EK8fu66eXYWtRa2wDhGuef8eH/AA/sFQsRzwjXBiMEaP2Z9i/0n/glAMkHpggJBHMCFQKh+p/tyuWw517xAPrX+kP5vvlq+vf3yOyq3OXVdNyq6Lry6/hH/1YMqhm7GvIS8gjPA20EgAJ4+8TwtOQl2y/b7eL16EnuyvYPBG0RXxXFDwAIpAfFCRsJ+AixC7sT/Bn0G9cY9hI8EBcQGQ6cBi3/p/+sCC8RsBCsDJIKYwp5CIH+m+9N5g7pFvFD9D/zFvcPBeYUkBwZHl4f6iHJJHchgxS5Ay30xOVO3sbgjeN76Vr3gwnNGUIfIxyDGfoZKxWIDAkGWQMZBtcJDQyzCUIFVgPuAUH8Q/Qp9HD6GwJbBgAEUgGP/ib40+4z4lLUGNA72Azjauyy9NT/aQ5GFTASsw2iB1QB+/yn9Ljl5dcbzsnMXtY13mrituyd/gcMBw7JB7MCwwIm/7z4sPOd8p/4cQLmBJX+aPs1/If7DPWV6zHpRe9T9zH5o/Xb8gL0P/dg9Kzqg+WD6ivw7fJ99ov89gieFK4YPBu1HKgaDRmMFdgIWPgY6OnZrtY/3ArjnerK86oBkBNxHc0dHRxQHEwcGxtUFs0QuRGuFbUZXRdxEPQMWwsRBtL8avb19TX80wWEDBsP4gy3CeIGM/7l78rl4+dU8EH36fpw/28KOBVzGaoYfRbuEwcRgQwjAJnuxN6+1OHSjdXC1+Hb5ect+28OIRghGCkYkBsyGf4QsQbO/XL9QgF7A3sACPxT/NUBrAQVAGT9QgHNCFkMeQoyCPQFlgQFAvf4P+wn5onrT/YsAcUJbxLHH5ootyiYJG0e3RgVFIoM+/5Y7j3eVtjZ4QDpwuqN8n8DCxnZJicnCyBAHZIZJxAyBov+8gCaCs0RERGOCy4G9gEE/dPy0epk7rT4WQCxAn0B2/4v/nD8RfMK5onfIOYc9YgBfwaICrcSCxqiG2UYQhMED64NYQu9Ad/xid++0UrOBNF70X3UbOGq9poL0RMAE5oTDRf2ExsJWv2o9rT4Of7JAMb6ofVT+TP8dvfn7jvqzuvx8Uv0evEC8PXw4fKD8EfkYtb20+Xc2+m48pf4dwGUD5YX4BbHFaATeRB/C7kAHu+d2QDI1cM7xz3Lvs+q2gDsmgEtFLAalhnwF2EUdwuWBrkCVAK/CS8SIxRbDZAISgiOCZQGJQN/Bm0NbRI2EwQSCQ9tDFkLVwWB+xL4Cv1KB8kQGRVSGfQhDCnFKUomniLgIQsixxz8EDYBdPIS7EvrAOvX6/fz5gK/Ff4luyspLW8usi7sJvoYzQ7RCy8Q3hN9FLsQ3A1nD8kNawdN/fn49/3oA/gELgN1AQj/IP379aboBuCX4KzndO8A9dn7XwfoEQkWpBaiE5wPrAuUBlb7hegd1PjIvMpizTXQTNjr5wL8aQxpEkIRBRAJD44L+ANF/gT+QAJCBkIH4gNzAQUC3AAv/fP2o/LM9Jn7Uf/I/9v/BP8E/Y/3cO1k5J/iZOfz7rr1LfswBGEOCxGmEKIQog5bC1AH5f7Z727dpM2+yTnNrs4r0mjdGPBxAz4OPg9EDDILgggJAnD68/Xp+V0BawfuBgAEvwQrBpIC7fr99QD2O/2iA4oD5AGOAasB6f4G99XtyujI6RLxSfjr/OIFlBPBHJAfYx9fHFoVawxhAsr0auUl2SHVtNcp22LeWubC9L8EFw1tD4oSHRVEFYMPbwgDBe4FXwhKClYI8AKrA1IG+AJN+y/1WvMc9jX63foe/CD9Of1k/Bb10+kt493hCuSD6lHxg/jRAgUNiBQbGZ4X5BFADBkF8/o37DvbbNSd2DPfsOJg55X1IQoEG1ohYSN1JDwlfyOSHHkVIxOoFjQbkh3XGVwVaxUVFAcNLgTX/zYC6gdMDDwQvRNaFrkYXxjJD9EDXP7O/jgDAAm7DugWiSMnMJE1bzM8LPgk+iAPGvILwPmk6SniFON75xzqcvCw/XsQGyBhIyMg3R32HG0YPBCMB/AEkAlxDjoPdwlxAwUDVQG2+iLzAPG+9X7+XwQNBZ4CKv3E+PPyN+i03sbd2eIk6Rzw5/fDAlkN6BRWGYEXtRB/CKP/wvF74InRWMuHz0HVEtxS5gL2QAgRE28UShENEvwSWxDyC/4IoApMDS8QMAwABZwDLAToAEv4P/FB8GL18/kM/S4ANgG9AcD+1/VH7GTmM+VY6YXwJPjmAjYP/BbFGqYZ8hKzCkwC/vb858LYcdDy0XLYj91045vuQf/PEL0YfxqeG90eniDVHRMXuRE6FAkWbROiCwcFxwNMBM0AtPcK8W7xxvhi/IX71/ul/tgBQgBg+ATvoeog527kK+SZ57jwHv5zCa8PBxTmFDQRSAkW/AztwNuHyi3CmsSZzPLT69zC6BD6XQhACykJIQieCbUHqgXDANn78/oK/B79uvd/8LjsP++N7kXoJeOk4yvsavOV9nb3GvgE+F72LfF76ablXOdw7FT0i/00B9MTzR3yIWEhyxyQFhkQ9gcK/Y3vBuLG3gzo6e+u8lH5BQmcGjUkSiNjIKAjLSZAJdkgdxy/G38dAB4CGYMT6hIpFi8VYQ0wBuAEnAlYDu4Oew1EDoMQGw70BN35BPRL88j0Q/h2/TIGjhMRIKQmJShYJVgfUhiuDlsBIPIY4m7Y09ms3GLdGuEI7fH/gQ4FESkORg/LDvgK2gN0+yv5g/yOAIwAk/yX+Aj6/fly8gzrWujt7L70uvij+Nf3dvgM+NDxtOWX3M/aCt4e5Unu5fdjAo4OXxh7HKIbrBc2FMsO7gQo9tHj1dNO0GzYqt7t4QbpXvrsD/YdvR5aGZAXPBeOFgsS9gu/CaINgxTPFXsOuwdrB7kF8/wW8kvucPGF9678yv4//X/8Uf2H+bzx4+my5+HrdPS8/QcHvRITHvQlWCgzJ54j0R1tFW0MYwDl7nvfsNzj4SDnIOzx8+oEtRXXHOAYsBNnEhsTJRToD4gKLQrJEXUUgxBMC2EGOAQk/zn1Le1c7f7z3/rb+034Fvct+Br10O5i5s/gYOLz6in15fu9AhUMMRYEG3UZWBezFN4QuQm++fPgGck7xRbPDthJ3FTjZPNfBAIOdQqgA8UAxQC5APX8YPjZ9xT/mATHA/P+hfuH/DP6rPSw7+HvUvRN+43+FvzV++3+MAHZ/ev1uu3p6uHvCvci/aYC3gqeF5oeqB72HLcaaRfuEQsJXPjj47LWm9fx3y/mS+zQ94YJXhukI44fLRjREhMROg6WBhD/cP9dCAsOQg9vDJIJaQghBrMA4/ab8VH11f5dAan8i/mn+fP4EPRJ66ThMd6h42LsHvNk+L0AEQymEUQQBwzVCA0Fsv/l9UXkidBcxrLKEtKw16beUO08AeoOAhFAC+YFgAIU/yn6xPNB81z7IQPXBdECdP+V/tv6pvG66RTpRe1a9gT7p/lH+FP7GwBw//73uu477YPyxPrWAWcH8hC5G/YhuyPuIeYeiBplEmEEwvIK3u3PYtGX2vXj0Oxu/F8QniC0JOAfFRvwFdcRQAtpBJ4ALgVMDQsQCw4FCSEIhAcNAkX5/vT++L0BvQuaDycR2xQRF7ETuQkK/pn3yviB/WUDBQstEzEdtCXBJ/QkpCApHZQXng6YAE/tpNti1Qjbi+Rc7S33WQawGG0miSb2HQcTCwyzCScEev1a/IgGbRHgFTASdwoZBlQCsPzj9G7wYvHp9/3+aQDgANMC3gREA177N/N278DvYPF/8xj3+/wFBwIQ/BOaE28SHRICDn0FKPiN5iPUc8u2z0nZ/OGs6yT+NhL2HhEhkBvTFL8PdQwpCIwD3AL6C1gYXBtYFsEQfxBlEOQL4gM2AOYD1QymFfQW6hTNFMsU3g24/+/xDu8S90gAJQkpEg0fRC3VNL8yJy1rKEwjmhzqD1r9Repw3SvbieGq51btYPltDKgcxSKQH+QbuxoGFJ4KywGs/kQDsQtjEOYMDQhvB3MHlf898eHktuDr5C/sYvF69Qz6p/0Y/L7zUujb4CXgGuNe58rrQfGl+Nv/xwOqAk//nf0r/CT3dOkp1g7FP8H0x7rOndRS3FzrOf2KCZALPgdxBfABfvwi95Hz+/Ri/GsGuQjgBA7/hfy++i3y4ejX5bzq5/Mk/LL+uv6qApIF1QI7+kvwXuz87jH0+/cr+9MACwreEhMWnBTkD64LwwY3/vzvvt7v03nU6d075ADoAvHgAbsT/Bt3G/wXzRYXEx8M3gOl/lQCEwxIFA0VJxG3D30R5A4FBo3+wP7iBfoMDw82DkwOtQ4+DI4DSfiw8dDxxPWf+k4Aqgg8EzMbEx5WHPIY4hQnEH8JOf7v78rj7d2k3crfpuLA6oX5BwshF+AZfRcHFKIPlAf1/878wv/RBSEM1Q6vDC0LZwrmBwL+S/JY7YfuuvFm8xr1IveH+Rj63/Y98E3rZOsC7ofvS/GD+KQDgw0CEw8WVhcxFn0UHxDmBbr2S+fV39fe6d+N4qjoBvZtCS8b4iGHIrcjYCSBIIEYIxKgEbIWuxlQGvIXShVUFt4VQA9KBP/8//2sBPwIzQswEqYYrBumGfYRkAfv/1P8aPxk/hMBewnqFWkdXx99HrkbZRdAEkIKBP3n7Pzhtt9Y4GjgaOH36TX5KQmOEeQRgRFjEPYM1gMO+hD0NfQK+I/6yPyn/rkD6AV5AT34Iu7n6ProO+ty6xztdvHI9Sv4p/ZR8fzqWOXv4mzl7ehm7y/6iAT4DFgSnBIXD1IKHwXr+8buReKV3JPcLdwO3YPjP/JlAxERtRUyExMR1w8pDpQIVgQsBf4K+g+wEWMT4BMyFKoRDQoY/xL3f/ZR+UH6zvjA+D38i/+h/Vr2eOxB5N3h+OMr553sf/chBRcRohndHOobFxf+DiEBsu6D30rYsti82NfYBN8x7jIBbw3iES0SSBXZF/IWgQ/YBbcDVgbiCKwHMgYDBlAF0P8/9pnrVOMz4hLkzOSB6Onwnfid/Pf7Zvft7frjvt8E4jvn0e2Z9pgAigsLFdsYERWODuYG0Pti6pnW1cwKz0PSkdLX10Xn5fvyCewMlAmOCG8KHQuIBkH9ofnO/G8DigXeAycDNgSBA3T9K/Za79Dv0/XI+jP9U/+BBLELqhDuDs8JsQQJAdwA/ADO/4ACvQtlGBEjPCpvLMUqvSX4GnEKaPiy7CLrie6w7sTwfP0jEpIiUCgpKAgpBC3BLzEu9ib+IcsiWCRrIgofcR/BITMiWh0bFs0NnAVZATQAJQB9AogIVBDHE44QwwlSAcD34fDl78LwFPSV+g0HRBbJH90gFxzbFJ4JDPtB6HDYAtMY1YPUVNHX1QDlU/cwAYQCtwJnBmcJcwiN/1z18fE183b1ifFF7njvKfSB9J3tzuf+5PHlruaL5WbkAukI8oH5gfjp7jHnkeMe4N/cUt0K5M7yHwT4EKAYiBrJF6wSkAUi8hrfttPf0arTQ9Mn0lzcUfATAU4EHwQbB8UL7AzyCH0DoACkBZIJNgllBbEERgeGBV77du/z67Tr7+uZ6sjpwO019zACxwhQC0oL5goyCYoFJQFW/fP8jAIHDbMZRiWeK+EsKys+Iw0VZQLA8dvsru226wLoAO50/7cS6ho8GLsWlBuiIsEjNiCBGzwdbyFrIMkafRXeFuAaAhkJD/oGQgPYAsMByv3r/BsCCwslEfAQHQumBiMCn/uR9rL0lfbO+/YF1REEHAAgph+BHPgT2AOs7vzbOdPG0zPVyNRS2sLqvP6sDaIRcxHTEjYUNBKqDOwGkAQNCC4K4AgJBJwBkAKKAJf3S+6b7OvvIvTZ9On1BPr3/+AFJwnqBv4Bk/2p+7D5xPb59ZX4eQDmCqIVcRxQHugcLRa1BnrwkdxY1JPWpNdH2IXfuO/sAeIN3g/XDdMN3g9dEkoPmgjLBGEHKQcNAtD7xvtMAQ0Advfj7fPqnevl6pnl4+FL6Dfxfvco+wj7VPgi9t/zJO4M6NfjaOSV6pXyKPv6AMED/AJB/GjtXtshzsnLEs9Yzd3L49V/6on9fwXDBtwIdwvPDNwKIwf6AUgCHwboBFAAzPvI/Xb+R/OD4VzXBNY51YXTd9In1hTdUuYO7fHrdOZ745vhpN0G2ljaUN1F4l7pEPI3/MMDWQaaBYn95+zC3KbTzdJW1XnWh9kn4tfw/gI6EPwVuRpzHdcbgxa1D10JXQlxDQQRFxScF+4duSE2H3MZrhclG0Af2yLVJegrrjKDNrg3RDfVNjs2LzRQL0As1SwRMKAx8jBCM3s5sDxiO904zzRALXshGxURDjYNaw15DdMQshkGJlQwkjFOLqgq0ydWJWkfdRgxFIwVLxdrF20UUBFWD/oJZwAG9E/rrOg76yXugfA99Mr5uQD6A8MAVvo59NXuXuqZ5pfiHuLx4znmj+wO8k3zWPLT71bpf96R02LO4c8O0U7T8dYW4GLsZvYW+zP8EP5B/HL5p/TA7yvtqO4/8lP2rPlF+qf6CPiX7+vlheHt4VzikeNo7Pf8twlQDOQKcwg6AnL7Hvcp9Rz0+/aJ/LT+wPxe/a0FVA5/EWMQ0w0uCTYAaPlT9+P3ePqw/IP9wP9rCRMW2R65Ht0XgRGeCQEBfPhS86H1Qf7oBJYBJvwG+hz9sv9c/5wA+ANAB70JQg5WEr0XShtdF/oNCQWkBisPphNpEAcOoBDPFDoYBhl5GDoa3hySGKYKzvpo9QD9awjyEEAZcSYxNYE7ujiLNFwzPjWkN6I2mDPjMA8t8CnsKHsnFyWuI80jeyKYHy8a1xI4DUYN3hMvG7sgfSRaJnUnNSaHISUcKxkjGBcVZQ+gCZYGvQYVCCEH0QEi+wD1uu5N5aLcd9qP3pnjIOX+5ovsBPSf+Nv5CPsI/ev9ePtR9Qzw9eyJ6ofol+Ww4d3f59+63UnZEtXR0wTVcNTf0dfRuNSo1tHVotE5zkHQ+tR/2NfaJd5D4kfl0eUn5jPoWOtL7FTpZuP83efaYNl71xjVBtaR2hTgJeQt5zXpJ+rG7Bjy5fgE/bz60vhB+7b92f2H/cD/2ALFA6gCVwKkA0oFwwfDBmMD8gLqBG8EAwKtAVsFJQlvCUIJ8glQCr8L2Q6wEvgWERkHF2cUCxF3CaYARfmL9QL13fRs9VH3Jvpy/TwCtQWKB6wGUAPkAJgB4gLRBLsIlAqSC0wNoA9IEIMMqAUO/nD28+5U6vflGuIM42bnaOsz6nvmDug/7qbxFvRY9RTx2+uR7UP0M/iF9oH0BPZ29bDvg+lD5GzgBuEl4z3jDOQx6ZPz9fzV/K76DP13Ab0DBQP2ABD/2/9lAKv+IvrC9+n7U/1F9FLpDOe87eP2EPvp+Vb2avLK8D3xqvFq8ib2jfvx/y4E4gjLDHUPVhHNFeAZ7hmoFS0OqARy+hzwVuhL5OnhneHT5QzxLgLgE54gKydSLOMxsDNAMegpwyJCHYgZOh2kIXMgbx4XH4Ee8ByMG04ZiBW7ENoPtRXXHLAipib0JvonhyoKKn8lISDfHhMkqCioJ5AmlCfPJjwlJSSwIrIgbR08F3cPWQeGAUQCXQX+CC4NVBHPFdUb6CH+JQYn9CNGH/wbtRYHDyEHfwFR/1H99/nr84nrNeYp6R7s8+aB4ZHm0PIS/ID+MfqH7xDjbNiV0pHRvNRF27Diyun570H1avQ166HfAtoY2HPWptV/0WzLG8jlydPQdNka3tPedODd5ZvufPQg9YfzIO/x6B7oLe2F8xD4N/v//U384/bE8VTr3eNJ4Pzkk+2n9/oAawXLBDABof/VAUwENga/B44HigUwBg0KDQ15DiEMhAdjANX2Du+b6wztePK0+IX5o/eX+T3/+gcEEtEWhROiDkYP9hL8EMUJpgT5//P6xPt/AUgFfQdnDB8M2AGd9TfwWPFL9Y/77gDp/8z78/yaAMcCFwUNCQcHTf+l/xML8hawGz4YThO/C3b+HvCR5+fl6+Rg4C3aNeGs5yTrXPWqARcJWg+UFFQQjA+OAPf+5BE6Aarle+T65G7hS+dU4R7aO+DT37bbYOJ06NnsxvrDBM8HwwWf/D/wBuzl7artgewr7Hr0TgMvEP4TYQ+kB///4/wi/hT/xvxo9671sveV+lkBlAv4F0YjrCsILisv+DLFMDcrcyktJx0inB6gHDEc3RwGHkgh3yVCKNso3yimJxknkie2J2knYycjJwQntyVYI0Qk4iQzIwQh7B6SH5YgrCH0IsUhoh4EGx0YKRVjEK0JtwOP/6z95AKMDWEXxR/RJK4jgx1tF6oVvRW/ES0L4Ab6AtL8Q/g3+bj6vPrt+M7z8+p/3hTY+N9D55/j3eCN5CXqh/Cj86PvEuoQ5z3lzePV48jncO3d8vH2ffaL9BzvJ+Qt3CXZMdmw2JPVy9VS3JXk5+x69M7zau3G6sLq5es/7VjuDvEm9an40vpu+cT03fC87I3mJeMW6IHy8fzDBS0JngSf/Hz4evas9oP+IQVtBdwDqgMjA10C/AMyCLsLMg5zDWkHdP4I9d/wk/E/8uvzNfuzAI4CEQmGEDgUgxP0ElIVMRYrF7UUeRArDG0F6f5bAfQJwQhGCWkPThEhE7cWYxZrFKQTgRKwEpoT7BJnEX8QGxCxDxMNVwb5/KH3Cv3sB38ObxLwFB0WFxXBD/IKjg1IEQcMcQEW+fvxL+/58nT8UA5SHHcbRhPHC4oFAv8g+SfwuuoU8Nf0XPal9YPwMel55u/q5+7b8UH1APFF6T3qNezA7BTyIPND7JXnSeRu33Lgl+bV7QDym/Dj66Hl2dq4zA7Dw71eveXBrMTlxt3OwtgC3jngjefC9LD2WuoI4Ynd8dfC0lLPi8jVxqrN49Gg0fbSR9T22LrgOd7n2gTdAtmN1E7UG8+wyIHJN89q0H3Q/tEt0ZzSXtVJ13/bO+Rq7Wz2avl28+ntg+247VTsh++f8J3sRe208nb8igtWGDYd+h+gIn8jESUvIuobnBrbHLUcDR7uIf4ioCZzKxct7C1aLjUuDy88Mr0yczI3Mys1azgnOi85HTk5OnM5mDSyL90tPC+cNPw3yzZtNnE1aS7JJk4ksiGuG10WWxSIF64dXyD4IAApiTP8Nccyfy5QKx0mCiJvHagUYw9EE2sYsBngGlgZYxZvFc0P0wlfD+IWvRd9GUYXNA1GDPYPKQ8ACf3+Tfm+/iEMWBPgG5omCCdlHkwXAg0sAFP+mgBq/Sj7Of9XAF0A/AVzDScXMSM8Ii0Z/BiUFXcNzQxSCkgFPAUVBFkC+gJUBlAI4AdIBjQF9gTTBJQEyQMVAff6sPDS8l0AKgCn/p3+Dvs5+yb8CPrS+Lr7TfpT90X2VO905H3cqtdo1cTUBtHN0JfWqNm24IPsEvgq/2D/T/vE9A7t5eQh4l7d+NZF1s3c6eYv6k7igdbf0bLSe9Nx0VrRVNVw293kZuqk6g7u+e334vTXH9Pdy1rEUMVe0GLj2fCR9H31UvRU77rvf/DV7MTsKezM4QbZ/tmV2Krceeqh+iMBqgEFAgMEDQtbDD4Flf/5/bD7LACrAwUDfwM4AxcGdQRy/C/tYuYg8Fj03/Vc/B0CVAPNAtoCcwCAAbMB1/qp+1IBEwc0DlQNrQdnAtD8j/XZ8br1bPbn8lP2avnV+lAFfxd9KGQ0uDPoKBUgXxdWDR8HpAMY/80AmgmODSsRNh4+J1Qryy7bL0ovgSvZJlgcbxYXFJ4PVheLJS0l1x6qHEQXxxILE2EVax03LYM0czloO7I4ljMAKJYa+hGxDrcHlglUEb0XiSFCK5owBjIjMs8xgS8vKQgiNSGWH9kaLxcJGQQiniUzIAYZPhFACh8JWweaBRUH7gnqDtwU4BeMGUgZrhFCC5IJewCN9EvwHus56YXybPslAGcEWwSh/ff1h+7+7KjteeoY7fHsIOWJ5PXsof0RD0AYnB3kGvoPawaf//H3kfUo9dP1g/h49iv10vuT/WD7vwBs/nL3h/as9Dn4AAMAAsr9fwFN/ib2g/J56N3eVuHM7oX+wQaoC5gNqg6EDlAJGv7O8oHvyOy64VDZzdxS7S39CwP4ELMVjAdIAMD76euT2rjPk8sM1Y/fod8566r9qvrK9qf/GPoa72LvWOq83J7SZNXv3UXgi+P+6BbpAOYA4cjZ3dUv2Uzeh+Zc7ffqn+kE583dOdJgzYPKL8jRx4vEx8RGyEXOndtW7j4BuQr2Bx0EQADn9CXpJ+uV7hzyqu665iTqdukS6ADv5+wz5ATk7eLr3k3ltO/V9/v+ZP5J/AL40Owa37rXqNLwzNPMEtFm1D/YZOpdAiEKYQQI/Y/zYOtU5mjgaNtQ2NXUN9Yt2dHYAOSX+ZQLzxknGMsFKPoe8vnosOoo9XD4Q/EK+OADQ/y29DPycPHR73/q8esr8r78qghtDVoQLRY2HLQfeRXYCqYK+A1IFxMgVCCmIt8wzzUMKxUfaxYvEZwK0wQlBb0KLRnmLSlAbkzpTVRFYESBQ401KzFnLG8ccRF/GVgjXCHhJjk34z9YPCU+zTtCMpgvfytGIicZUBQyFpAY1x6gITwhoB99Hc0YYRAwDckS1R+cKbks2S15LLYniiDDFTwIKP8K+lj5ePp++ZH79AFzCOAPtxOiEuwSIwzaBg8GCQi/DoYQmgw2CHcFsQC1AuwHQAl/B0AD5/4x+0n6ofqxAM8JBQ+YE7AX8hMyC6ABfPgg8SXtg+6y9Y4BBw9rFikdwR2WFwsQ/gqUADn3yvpq+DX2EvZ89P4A3hfdIj4m1SaSIH8b4BY4EVkKLQf+B7sCFvm4+IYAtQLf/9f+Yv+R/QEB1QAA/Bz91/2Z/QD2vO2X8W7xuOj63VDcm+Yz9H0C5gdAB+wHTAT9+invWumZ4UHV69XZ2ZfYbN+q6Xbvtvy3BAD+N/3U/AL2OeyJ4gThJeZo6S3yKfnT8WrxewCkA/n93/pL8LDg7dTA0V7VdNkt4B7sf/ZN+2j/OAGF+/P4DPkW+df8DvyD9776aP3/+tD5KfMt6pvkwtmT09XaMeVm6Y/nBuwa+jYBDQWvCuALYQSy/VH6cvW0++YADvwz+br0h+4Q9Br95fka99vzIOxa6a7sOfKd+KoAOgRL+0Pwzueu357VLcvEyVrTZOOJ8csDuRNMG7UfhxtMFKgPvQZH9Z3oHuEO2DPUIdZS3mTyKwwLIXkpxSjhJAQhsh8EHRkaPBWaEW0QaQ5GDWsOQg4JDIENIRCKEUgSExawFaoU9Bb+GPYYcxk8HccaDxWqEHsMQghpCUAPwRAVFEoWMBPyCiEAIP1/9zHsM+qf7kvx1fXC/t4DkA1aEmUNlAkbBZH+5/Oh6bbgTeWj7d/uYvTh+7sBigW1DDoIXP2o9KHosNk1zGjKAs3f1uXdGOLx6SLrDu8c8evoqOH65kHug/O2/oIIdwnmB+QDp/rf7SPmFNzv0wzXmddg15vgFu9U+g0D8AXsCgUNERKDE30MVA1pEjgSAg1/DwALKQVrCnUMJQoJBycFdwQuAqsA3gR/D/AXyRwvFGUOohF3CvwBSfjR7hrrLfXkACcLihg1IcslGyPTFZQHpgBB93jy0PIx7UXlO+Vi7DX2TAiDGnsgFSD+IMUbShKiCW0GqAOn/875vu/f8TQAVgxKDoQJ/gyaFaQRyQTn/7MEXQ/6ESsHT/1F9CDvGvMG+scAXQgHDmsQsBPuFxUZGRhrIqghrBVYCdn3++/Z6tDuZPwVBzIVcyWFKqomwSYxIhcXtw/YBwUJ9gs0EPgboh7DG2UguScNITYYewqP9/31L/ao7uvpFO359i4CLQoFDpwNWwsRDB0LjgH59c7vdu7d7fnrje+h8fXtsO/l7SPjneAa6DXj59pa4Cnnpe20+AAEeQTcA/QEewdQCGUHFxCiEnkM6AtrCtoAdv5ICYERNBANDlsP1Q46DhkQDxTdGI4a2xh9Fi8U7BKFECkMDQzJEscYwR2WIJ4jOCtSMNUyMzQQM0IvxyiHH0QWswnn/IH0kfHK+LkKdx13J9EuWDFQLnsrrCa1HW8XMhJMDWMIxQAm/j/9BP2s/8MAZP9D/Nv0Xu4E8sj4lADTBasBcv1L+0nv7eBu2XXR/sz60fHXRdsh37TiyOQt57LlIN1H1HvLDsYQxrbJe9D+12Tdf97h4iLlL+Fm3j/bptau0cTRBNF30ZvY+t8g5onuR/SD8D3sUuRs2RTSvM5Gz7jRvtb+21bgUuFe4gjkf9/j3dHkn+qo6vHqHO6l7mLxAPYe85XulerN5Hnej9q42YHX39P+1ADYld5i6GbxKPcv+sb/jgRbBQIHOA0FB038aPjh8ZHq8+oE8+vw/OoS68zubvHr8VryMfa/AXEG8f9m+RD2j+6L6CPj4d455CvvQfaJ95P4KgCqDyUZrhf0ERkGZPih8d/qvuEC3b7fEOts+b8C1wesEFgcoCK0IuAfYxqwEv4O0xBCEtEROhIEE6gRbxE+FEAWnhl3HbQe3x5GH5QdBBn+Et4KiAZnBKsAT/8ABPgNRBeBHOAdCB65HMkZCRv4FnMJpf8O/qf/JQXoCIAAgP1QBiMJwwf6ChMORgssBkoDkgUbEUYbqBsbFrsQ6hHsF6IZERFfBR0AfwHVAQr/f/rX92r7lAfDFlgcXxchFcMashveGPwVxxBYDfwOOBMpFvoZnh/qI+IkjiERHIEZ1xohGhUWdRN5FLcWphdxGvIm0TjjPwA7yzaNNyE2vTBcLGcpUCMGIOgeshxKG/4YfRfeFvgWThhhGhsbGRvJGHEVWBKQDOYCJvp/9n322fZN/MUGyxAlGG8a1RplGq4b2xpjERkAl+4e4pnVTs7L0NHXi9uw3WLnsvS2/O/+n/5H/en71PmB9Ovr7+Tt35PeI93G3GbePdsf2YPdcuAl4B7mLe8M9Tv0xu6y6ufnWuTI31baBNWR1SHZAN3p4ePn6+vb7+30QfYE8X/oL+UO5nDn4eiJ7S/1WPmy97700PLx8W7zh/UG87zuWvL/+8sB/gIdBaoGIQkyDJoMOAm7BgEFf/wn8Vzqgelw7fvx0vWn+cL+AQFa/3T7S/aP9U35q/4bArkDYQIZAqYFbwZ9BFP/M/d47m7txO0/6FDk8eU96h7squ3r7Dft3fiKB70MWBFKFxcWdQ84CvgEh/03+aH5kf63AID/WwFbBHUEJwJ5BD4NIRcLGdESmhAND8UGCP0Y893s0PFk/JABMAZOD10XTh1rH9Mekh0GF54NxwjuAOfyBOi25IfqBPWN/QUAdQPRC1QPrwzNCUYIsQf8BUYCQfwA9mDy+e737NDs1e2P9VP/PAPsAPn+WP2698Dwo+1F793ooNl10jnUI9ox6VL09fRW+KQBDwivBz4CS/yb+uH2UfCF7enuvO4r8bj5SANWCWUOCxBWDQQOhhC/C6QFJw3wHPwo3S5KLfYnBCgjKMciIx8vHt8e0x5pHZYbZRn+F18Zfx3gIFwkiyY3JpQm2SamJuwkWCD8G2sauRnVGkgclhuHGkwazxR9DFsIpgZZBJoA3/4x/Un+EwKUBuIFggJMCGER6hdzHDEf/BgCDgAFO/ps87TvGu4K6xboh+qh7K7qtOV/5FLpBPYg/in51/N77UXiWNYQzXvJ2ct1z+fVZOEM6Wru3/WZ+mr8cvnI66baaNK6zUHGXML0wy/HZM++3Y3tfvl9AlgJCQfb/Y/7YwOoBHL7BvPz7UHsg+9L7gzog+rr8pX3DPip+YD+YwcjDXUKlgZdA879Yvcp8dnr8edi51bqvO7d81j3Iv95CsUNZQnNAfP2aO4a6j3o0+3d+YEEvwsREJ4MrgrgDM0KwwOX/ov+mgCAAMz88fuWApAOLRjZHCEaexWuDqsC6/gp8rrrcOkv77b2qADRC1ATfxdYFewIT/yl/eQFJQzcD+IU5h6wJ0AoxSB3FzAOQAWzAHT86/Zk9jX7bQBMBtEKtw59FTQdQCSiLAAyHy86LCMrGSbmHSUVJxLmF6YdYxnkFH0WXxRZDDIGVgVICrcVlCAdIOQWdRDiDGMEn/a07GDqbukt5njk2efT8In+bwgHDY4RWBFSBaH0Vuhu3LjVhduT42Llfen+9V8FQBCzEeQMDQvBC4gM4gs0Brj9Jvay8RbuVu7d74X2iAMACaIHEwoADc0G+AegEEgQogojCkoOLRLiFaIUMhDJDVgTABxjHuQeUiJWJckkyyGQGEYHWvTh6yTsHvPiAmsXySqPNW815jDRLjcnThyHGL8Vfw3JCOALhhHeGMMclhdrD9cIogEA+z/0Reyh5vHnQe3A8/P81gRlCdEJrwYXBD4D0v8p+MLvYubj3uHdI9sn1UXTAtFKy2jOIdRu0GrR9Nrj3xbf9t3K2mzdn+X+6d/syvHV9KH4K/8G/bj2BPQ19I3wI+ho5JHmgek55xrgzdkY2mTgYOhi7lH1ggCMBZP+Bvha+L72JvmqATAAzPaH9XT4vPaX9/v8P/+T/jYBDQJm9kvkdNte3FzfbOQE68D2fQumHbYjbSMTJCknTiklIxUVCwdSAH8CrwQjAXz5au/G6tfqmeMt2/7hePH7+lIANAOiBCkHawVw+6HvIuuX7PfsuOjd5x7uR/Pt9KH1HPIz7Z/vIPLt5z/YANFI1Fbck+RQ7Dv0OgKwFn8iwxx9E+QQBw61Bj3+aPYW8u/3lALeBtcFZQWICBUIxvyy7kfswPGV9gT46ff3/AEG9A1ID8MMqgtWDUwShxn6IfgnOCcXG0gJTfmX7ZvkcN683VbeyN5k5H3uhfSn9TH37/pF/8kBewNrCIgOLROIFw0ZkBWaELkMJQwHDHUIAAMLAGUF+AY1/GzrxuFw48LoxO6J9cEA+gwyFqAZ6hUXEPIPvRHZDagJjgi9BRL/FvZP8Ev2swLkDOwTqBh/GLMXGxY8Dr0FqAfiF0Qp6DD+MY8z4zVUOF434zFxLVgsmimuI0QdSBYpEgATUhQHEikRlBRhGTYakhZ7E8ETdxO3ECsMZwbVB04N+g13DH0QXRZ7GfAbPBoHE0QKvwGy+BLxtumb4/jieeP34VLnn/WiBfoRAhUnEOgP4hEEDQAIHQMQ+UXymfKy73TnN+CJ3OPdO94t20veKeWT5ZPjEubN5C/hZOV76+voDuII4ADkS+vC8ND12fcv9e30ZPBU4ErPUMhYySHLAM150cLauub57HDsK+tH7gb0dvUQ8dPs2/Gu+Rz/VgJhA6oEigToAbr7vves9Xr2i/cY9NfuL+3f8pf29/CZ6aHqtvFu9uX4+/hL+scBvQ6BFjgQQglvCS4JjgO4/hb67/Sw9Lb0Te5Y6EHtQ/Y9+on5M/jp+O4ASA8bGPAYSh7wKWAw5TAzMJAuWCx5KIohwRi9DxUHsv5H91z1f/niBIwV+CIdJIMg4iE8Hm8TrAvsCx8M5gwlES0UBxZ/GycihyPwH6QajhJ/B3sA+/wQ+Zn4L//gBKoEVggCEV8aBCHiIoofkB3DI3Mr2yqsIlgcUhrPFzIScwtnAqn5R/TO65nfXNoE47Dz6/+GBF8GNAqsCmUBCvaB8L7uvPE9+U/+BwHYAjoEpAUdBfIBCP+d+j3yqOlU4z/fYOB05fzlIOMG5UntnfixALEAZP1L/l8C2gf+DNoPaRXTGxMZmBBUC/AHGwRJ/n/0dvAc+JACrQjHC+AN6g+zEVQPawrXBnsH+AuYDmENNA3HDuANwwyeDFsJQgezCIYES/n77entEvgBAS4HJw78FHUYcRllFqgM8AGR+5v7QAERBwAKJw2iE6IUoA+aCQ8DsPrh8EnkAtWN0cnZS+Q/7xj6RgJAAsj7rvMv5lTWbs05zKzMic9B1rTeFOMg4x7jO+NH5OHisNsh0zvSidf+2B3U/tCo03DYEt0G4EzhUOUG76f00/WH+eP9fv+8/Fz0aumV5LDmXuXr31LZTNR30xzYnd1O4X/pM/dXBKYJKQcHAL75KPYM9KzxCPC480f6dPwi90nuledD6X/x8/Xp8njvVvPh+m798/kE+KH/HQ1IFd4QHwUJAR8Gzwd1AY/6Cv0HCtcYwR3PFUIM6gsnDmMF6fY/8f343gR/CQ8H+AbLDxkd4iQZIxcecxz2GYET8AxlCTwK0Q/sFbUYqhe9E7EPwQvoBZH/vwCaCUYTGRsIIPIi5CYVKdki9hieFPoV1RlGHNkc/h+3J78uojGgMBku9iv2J+4dCRJrCzQLrw84EwcUKRYZHvAlNSeMJHcigyKsIXMb/g/NAyv7MffT9iL44/cI9yL5PgHeB80D1/u8+vwAAAptEQkRhA4VEE4UMhLVB44A8ACKBOgH5gs6EZ4XaR0PHGcN6fo59Mb23/Ri7S3m+uY78Zn72/16/OoAYw6uG+gaHRNGEYoSQhC7DF8KLQl5CrEMIwvcBfoCewOcA8r+qvgp+L77of8uBawMGROuGM0bwxk0FkYWoBdMGGUVtRB/DcsQVhoPIEga8AssAID+QAR7BcD+nfeX+RECpgZ/BUgGLw6HFm8Z+hVWElsQWA2mCEABP/u0+aX6gfYa627e2deo2IvaP9iR1jfd1ekI9sL8kf6P/XL9zvti8nvk39rh2J3a9NqD1VrSsNwr8ZAAR//I8Fzgctgn2ErY19PvzFDM79JH2RzcXOBQ6HvvsPEi7k3q4+g15rDczdGqzzvUdddc1WLPJclvyZ7R8dVK0nHRJdeZ3HbfzeDA4Nni+ek17iLr8eU35qzrM/Dd8dPv3e188mb9IQWvAUHyUt8K1Q7WVN0S4Wrfhd+R5X3vxPgM/nUAnAaMDfQKGQHE+qn8XwE0BCEFVgQ8AjP9YvFH4+HdUuLh587p1+2097UAJwdtDpQXWiDZJM8gyRWvDAMJUAl1DEIPWA9WDn8RhxoVI30hpBQyBn8BwweuD7URSgwfCKYLPhHsE/4Wzx6LKn8y1TBpKEwknCdcKbAiFRjsEewOpgkk/lHxg+xP8C31RfvyB1gXeSLTKSMuAC4VKqwjhxonDywGEwNXA2UCDP83/UgDphHwHdkaCwrz/AD+3AULCg0LMgx1Du4O7AvTCJYMIRYfHZobLRGYBsEDHwgRDPYMuwxIC/QIYQNe9rTiXtag3AbpL+1e7MzwYPxGC+YVYRjZGNkcQB80GZQNcwf+CXENDwsVBJQEgxSiKC8sCBvJBHr8ywRdD6oOrwQRAcMLLxdYFQUOEw6qFvYbphUPCuYF0w+iH5YnSiQlHXUYMhVvDDv6dOZu4Dfrl/Y195f1qgAxGXksPi9lJ28h6iFjH1QSIwHd9THw3+8o95YEFxHHFpoUUg8tETob+iFcHUIPIwMXAoQIaw1KCw8HogYRCH8EAPq88cz2BQfRFJ4XFxTsEvAU2RCxAZnu6eGy3QTbWtVW0GDVfeeX+jwCUABs/Nv7MgIpCEgAl+pO107YHOzK/4QAwvDt5rby7ghQEnEKVf5q+Aj0Nehq2SvYsueo95/1O+I30L7L5dJk28Lext/P5I3tO/Nc8CvogeJy4UHgQ9ecxLS4H7xMyP7SmdCizFbTNeLt8PX0ge6040XYAs+JzsDbeu899hbrLd4/4afzuQaQCyMBifLE6cboOezQ7onrFORs3kXc6dmN17TYn93t4Vzjk+VF7xj8OAIZAKr8l/7RBBkGof/S9BDpbuHI34fk+ecx5fjkbO+J/F7/jfZ27zf5VBJtH8MOuvKP5tP2HRNtJTgjcxc2FFAYOhZxC38D0QRYCvIHvvox7zf0TgWBDqwFzPWm72b1U/2EAKIDog7JHwQocyA4E2EMpg3PDnMHcvi46mjmrurb7iLteeoA7pn5RgwGIBkoaR5vDjYJtRFUHrclcSXgIkofyRhfEfwP3BUxHGMdKxfRDAcESgRUC/QOAAnA/KzzbvO2+RT/2gIpCqgTtRYhEloPlBPyGikf8humEckDwvS66SPmQ+nT6rTmUOiB/RcewyslHOIHRAuJJIc57jYtJxkb7BiWG1gbZRd7EikTNBneGNgJj/nz+qQNfxqsDwb6evIE/NoGpgi9CgsUpBlCEv4E5/+BB2sWFSQjKUQhlBO3CrUIywYW/V7sQeKo7oYKFxtdEPn9RgIvHdsyFzP8J5wfdR/2H6QaZRJMDjYPThC1Cmz89+/K81QFqhCOC3MBYQFZCqwP/gx1CMUHuQck/33wYOk98On/0Q0LEQkKCwFP/b7/4AEe/7L0EOm+6oX4GP5s7i/ZwNdL7eYIFxsjH/QY/g84C8EM3g7wC9MEm/8E/Ab1auzt6VzwJPqD/0/9MfjC9R73YPp+/Gz8rPpi+dD2uvAt7MLulfjYAGUAN/mL8G7uQfMW9cTr8+In7H8C6ArT9MbUxM435j4FQBXaDOX5/fPuAwYXKxpYD0oGQgUlAiL0rOTb5t35eQjLBn75cOvI5UPuhfsY/9X6qvoLAMD+WvRD7dXy//6aBGj+UfFm6GzoWug54LbbHO2eDaYdjglu6HDj8f8nG7Mbhghs9l7tUO4c9nj6n/zgBbERDwsm8UPgZO8vDycephQ+BC38KPvU+b71LfRL+l0DRgMO9njope2sBRMZAhRF/Qrq3+fR8RL4qu1w2xbd0vxMH7cdevpk4UHxGxYPKbki4hGr/xDsDuKT5YvqM+zj7vzxM+6s6ZvtYvmtBCMKUgyoDJ4H6fx99k376gIpA2z7BvK46yfrT/E3+t/9o/qu9vfybOz+4O/Uz9B73dT7wxhWFyn4keCB7R8OrCNiJ4EdvQsO/I/2l/dF8u/jHtn+2aLedt4r38jpXP6gErUapBXBCpYG5BAzIcEmYR17EtkOWQwDBXT+tP5IBbcIMgPn9zXvrO4v8KHsUuzb/vgbgSRvEN/7wwO1IGY1+DWOKmsa+ApGCgAZcSCcE0oCYPfE7PHeuN/b8qICTgqgD4wQqg2zD0oYzyA+JbAoNyrNI/IUzwq3EBsb/Bm1DRb/ifVw8zn0je/Z48bjCP0THqwmvQ1y8yT7Ex1QNQI2JyviHDYPEQx3EjQSzQzPDtEQggQI7+PjcOnl+doMMhcCEqoC4fjn/wQS+B0JHpgaUheYEg0QUhVaHpgh8h13FcsI8/og8abp9+Jc6AMBxxwIH1cDcOtm9PwRMyeoKqokUBeCB3UBWQivDEYHHwdtCav+Zuqd4ofx3AZ1EzgT+ARF78bgYuTn8on8aP1P+uXyPea03ofoLf9SEkIXEQ3M+Qjo098G3LbWYtrG8pwPLQ2V5tnKGt32BLMZ3hLFAfXvCOUW66r3fPaT7HrtnfIA6T/Uhcol2BDvsP03/+n2UuwS7FT6AgoLDn8J3ATE+oXnPdlU3IPrfPa+977zCOzv4GDW8dKs3I/1sRMTH7sJ0egp4qf+BBwbIrkYYwtJ+u3rHO5c+CT5jfQ194X2Dud03I3k/vP2BMMTuRNXA1Hywu7f9i4AUANQA6IC5/1L9g7yp/aEAg0L+gc7+hbmptMMy7zPWOI8AOYZlhTO89PiCPbVEB0bDxuaFgIKo/ij8Qzz4/Dz82sAVwTl9hrn6eXI8aIBIRDuFrkSngiN/qr6mf8DB+gK4Aib/fzrVOD+4ZHxHQQVDfAIRfmw5yPfhd+26NgARBwhH7cD6erX8bcMXiFWK5YpuRttClX/g/yj+S/4h/40Av73bukn5UPt+fkuCcsXcRo0EC4G0QVSDAIVaRt/GVAML/wA81HwwPF6+FAAMAOu/jnzo+b433nnTgErIhMtexXr+ND1Cwr6HzEszSyaI/4YZxFdCv/+wPjh/3kLawu8/VTxGvF4+18Mrh7FJqggeRMnC/IM/BDbFAQaXRpbEFb/T/U7+lQGywtZCWUGrQG8+CXsLepg+oEXYCthG/38dPwIGj4u2S2cJEAYngjQ/PH6f/MY6e3vKQR7Cu/9xvbNAqwUpBsIHJYb0RjLEXkNog9nDGsFvQdQDQAGKfGo38DeK+vG9v73BO0K3p/akeCu6y/+uxb2HUIHK/RL/+oVex7iHB8XwxE6DScI+/0Q8jHwHviD+nvrn9rl2BLmevdvCNcQbQ1jCV8Q9BzXHvAVEQ4CCoICDPKP3yfa8d3Z4s/pS+zt4rzUO8701aHq4AZrGLUEdORy62UUji2WJxEXpgueAn76rPY97i3nYO/f/az76efv2T/ko/0+DaYMg/417vfn2e9B/ncBJvvV+FP7Q/fR8FrxffTn8gDwBPQE8xTiO84Iys/ZxvezFC8VOffx37LsvwoTHHcb7BBWCG8DDP4I9C3qtOzx+oIEDPym6C3eZudV/BERERuSFUAJTANZCLcNyQvTCZ4LIQYA8yHfgdt55Kzt8/T1+HjuotmZ0QbjtQCaG1YsqiE0B1z+OA8EIgYiShcED6IFm/pe9CXsdOem8b0Ebwsg/IHneOTZ8EgA+gy5DD4F+gHuBFAIPAguBxEMuxETDAj+1e/d5wDnWOvQ7Qjn19xY1RLYn+pfCAIgrhojA+f3aQQdGAgiTB+IGPgVwRNOCsL49epF6xz37f7G+O/ryuYg82UJXxnuGEoRMBEGG6giZRoJCzAGtwwrDR0ERful9KP0+/9fCUf/5+iX3mLvRgvXH/Qd4AL58XUE/iEKL4srnB5pE38OpgyCBCL11fCP/FcDrPx68wTy1frgCJ4V8BauDQcFvwjVEnkVmBGoDgUPeQ7gCVsCK/zA99L41fsU917nBtbn1cLrBQmoIhEq4BX2AwAMfx1EIv4cQBimEaAHYwAU+x7z3/S3Aq4LYQQv9dHuZvfYB4wXax9vF4gHOgBzB6oSLRgLGeYYKRXsDCEI5gY6AzABuQQnAcjsotOb0EHp4AkRIwQjdQge+lIO5ChCLuolFyVWJEIYQAyX/qbpHOMc887+f/jd6s/mL/F1Au4Shxp3E0YITAc6EAkVHw/4Bx8G9gWZ/9n3EvAQ6YnqPfMY+QDw0dkS0THjuv8CG4cgEQwW+VP3xwmUGm0WXQy7CLEHSgTr9iXofeZS8Vr+uvyX64XcdN1J7bj/fwYTABD6SALRDeILaQLd+wL9NgE+AA75Zu716MLvyvdu8i3af8Noy/XpdwopFiv82+Kl9KQZfyttJBEaohSoC1cHcv9S5+HXNeE36YXeuM/60VbmCv5zDpQMxv5w+VUAOAVT/1P3bvTK+A76DPC65e/il+bz8Dv7M/KL2ALHbs/A7EALLR3DD/7yvO8ABMcSZxGWCYwF3gEQ+GTrcNxS2T3sPAHgARDvk97j4efy4gPJC+4FOfov+WcBPgNL/ysDYw9CFmsM1PqR79nr6+6l9dv3l+to2ALXAu+5DVwlxSVAETQD8gc+GTYkLx84Fh8T3g+mCRb3cuF24Ivv2fzZ/M7zLfD39iMH1xcXHXkX4A/TD6gTxRDLCr8JpAwDDEoHigJU+vPxm/LE+lj29d+u1evkzv0nGS8k+g2s9nUACB3mJ7kfrhbcDjwKuwnz/+frxuLv7Dv8WQBU95ftHPNfBcMRqg9vBZ//3gQjD10UsBGmDYEQsBG5Cg0E2f4t+Un2K/ly9cLiL9mj6PoGiyYnK+oNJvpMCdMgRCdUI2ceABZ1DTYGxPas6O/vzwJCCogE9/to+94EjBNtH/gdLxKKCs0Mgw51BuX/awY4Dm0I1f3/+f/7JwJlC0oOdv+H6D3hBPAwCv4juyQZCon3WwKaF4kgFyGQH5AcjBXcBrzvVt6q5Yn8AwlIBAz3f/Ai+AcIWBeFG4YT5gvRCDoFqwGQAjIMAhTDC1z+pfpq+n/6LfyZ/OnzuuOw4YvyEQmwIWkqQhlODDoU7iGJIb8YvRbVF8MV7A3I9dnel+VB+7MIMgVR9/Xw2/vuC2cRzQnYAQEEIQwEDaYAlfPK9lsFuwiV/sjykeoa7Lz5n//X8LzbO9gM7BcBAhH4Ekf55eygBNMT0Qp/BFIGEQonDnkG6+nj0DHXuOyP9hTuDuDI38jvAwLiBzn+SfQI9xEBOgAA8dfnGPEa/7kBvPfb5mTewuZa9kf0TNyTzonftvyuDPwUOAt5BXUkojFOFXj+OgKUCIH8xvMt4ufJVsuZ4Gj1QflL8lTtavjRC2MSswVs9ajzGPzwA+P/nfU/9T4A1Qd1CeYH5f2T9Rb5HvxJ7yvdUt1y8XMIxRuHG0IDyPhACkQemhvcDogISgQXAzQBAO7n1O/Xfe6X9xTwpOWh5xj3GQqcFVQPVwMZBr0SphP4Btn8KPz2AAUGcwFs9PztrPTkAKgBfe714FzwPgxGIoclnA2q9Qj80xrsK+ofwROuDhUKUAqOAU3pBN0t7LsBTgfX/HL1Uf25EAogwxswDMMBKwZODy4InfQi7pv5dQQRBiv/L/WZ7532Of949H3ffeDO+yEVcR42E1P5OfDeB5gfQhoNCqoFyQRY/2D5kec9167jZPiF/NDz0+z38t4GzxjkGLsKMgDBBjoUqhLVA3/4M/eL+0H+yvh07uXqyPEA9xzuXODA47r7PhhIK8kjcQ6EBeYOayAdIgIV5AuaCRcL1gSq78/iru7cBagQ7gbS99v2mAjyHfIgaxQbDAANZxDHC3z9zvZQAUoOJRA+BqX4T/WxAUINbwMi60vjyPbuEnkoGSXuC0gAAg+sImcmkhsNEH0KSgmsBwb3Qd4n3F7u/f21AD/4uPNR/78Tyx40FmkGgAHBBwsKVf207W7qVvBD9xr5YvCm5bjlHu8C75vfttli6oYGiSI4JlgPbwGQCEAY0xz0D3UBuvh08/PvsOON05XUzOb7+UYA9fm89QEAbxMGIIEYHQl1AgMGFw82C3D4/O1S8//8xwBF+VrqReHA5zXvWuQ/2frnEQY4H2EhmAmy9gAC4B4dKiUbWQwDCa8KjAj196bfuNWX4U3vYu7M5MDgRetUA9kVBhPcBO3+NgZODO4Fofqj9ZH5awGH/kHsstyi29fmzu7r5GLWAtzx9ocYpiRODoH2NfagCdEbnhcJBPX1n/QK9xbqotOX0czm6/qkACv4Net7718GFxfoEQMBDPVi+EQAIvxo8QzuzvYpBH0IR//A8Lzp1+3t6jvf6+GD9YgM0xvREwj+5fZWBfoYkB2KEqAEBPWh61jr2d8A0CPTneNH8H3xwOhs4p/ptvxzDJAKJv8M+gz9h/9/+zH3Fve4+Uv9xvon7XDe4dcA1HvQrtWD61YD5hV7G3kIAPg+AFQUPhyxFL8LKQOV9g7vYucx2SnZf+uH+6z/Zvp0+IAChhCMG7UcfRW1DrMNWg+5CKP6XPghA+wLTBFYErEMngfiBmL/ffD+8EwLGyfNMM8kWg91BHMLqiC0KKQc5Ba9GhsYbQzV+bLoh+mL+wAKSAZw+jv8/AvTGHMc8hUFDhcP6hTXErcDAvNq8un8tQAY/XT5tvcp9UHwzeWd27jjLgHdHvQr5BwJA1P9EQ2iHqgdOBFQBST6N/NL7ADbm9Kk4Hb0N/9J//v6Zv7qDu4f8iBSEQADcQBUBJ4ANfQz7GbvFPo4Asz+MfjC9xD8JPtU7k7op/kLFrktTDFCGWkDTgP0Fn8oYCE+ETgHCQGeART+oepJ4272BQ3sE3EHvvkyAR0ZPix1Kh0X1wU2BBEQsxNSBRD6Hvte/1cBcP9o+Cnzf/U79IXq++0yBwAkHzQrKhMSXQi7EzUnOisCH0oUswg1+tnuTOAK1JHb3+31+i38CvXl+pQQ/iSDLJgmqB3LFjYPFwjG/NPt2et29Aj2M/TC843r1+No5Jvm7+2mBcsmuzSkJG8P5AgPD5oeqiO7GMkSVA+gBR77Te3X3tPjGvs+CNUArvSB9A0CLxE2F54P+gGf/q0FkAep/Y/zdvTt+2j/vPq68grrVuhJ5aDYBtNW5w8GDSEbJmsMyvonAeoQMxvgFrML4ACl9LTprtqkzNHN3dpH67LzZO124yTs6gJYEPwMAQQuAJoB3ACJ9lLn0eLp63T2QfTd5jXdJdwO3kPcWNhU3oPzfxEhJnsbKwbj/dUCRhGyFwQP6AatABj3Ke7V4pHbMebQ/b8LTAcQ+Tn07AEhFBkcfRNUBGkAJwpSD38ENfgg+aIC2ApvDUoI9gKMBeQEZvb+6HTykAm0IXstTBuoAn8BRhbmKZQobxsTEgsNzQymCI/2AOiX7nb+lgZ/Amj5AP5KEHEenh8nGWcTzxNnGJoTWQNR9uv3UAAdAZf6yvRH9eX6fPrI7wbwuwWqIWI12S9KGl0NKQ4xHDgjqBbJCvgDtPpY8kfmf9zK5Z37VgtSCfn5o/jFC88ZZRpIFK4LAQYZBfQBXPUa6knxfwGxBcj+tvcA9mD4h/WV7Nfsav0bFE4osiQNCw7/MAoJHCsk9h6YEyMHMf269s/rZOLQ7ScEswqgAt/1Bu4g+TwOkBVZCsD8q/9ECV8IyQUJBikFFQgVCan7vurp5v7qyufE3lzdIOt/A6oa2Rz8BSL3BQEnEg8c/htEFVoOBQpCAb7vj+A35NX3LgMS/tDyru99ADEY4CA2GowNXwiqEYYQ4ffR30Xajee6+1YGkgdYCb8KpgZe/wb6AP7TEQIpQik2ENX1vuRi69MK+hdZDa8MPhRYFLsKavoC7UXt0PzgDOwIxPFB4vPr9ADqEDoZZRj8ELUPdROWC3T+T/yKAIH+8fAg3SnPss3b0SPSEtSb4lb+iBpOHfoN1wbwBZARaxx7DzQAIvZo57Tag9I5yxLPEOZD+p3+Ufvt/MEJaRjeGVsNNf+h8/fzfPsW9Vjoeu39/xMDUvRs54HiDuVi5oPbydVF57cAzxPeEjP4Wubj8cEIkheSFugOjAjsAin63+fy1O/RpuAx8N3vLeUg5Rj2xwuzGs8XPA6xDq0JDv7j7iHY79Ol7KQA1/us7kXomePt4xDsMeX62wju3gNKCx0GWPQK7/QGhRq9Fe4RMBIVCBL+FvGD0yXEedGk4Ono7fDE9DAAVA55Db8MjA6ICLMAYwG0/Nfok9oz5RL4QgBg/NfwcOly4zfbSdke4l71ww2MHVsUAwO0+dX5GQxvEhECmfin92z39fiZ78TdvOB/8lH3NfKL5rjg9e3l+3EAZwQ0CX0OCxKzDtUF8/VW7DHxsvO68QTuZuqF7/PxEul24c7ptwkZJqodOg3iCZYG4gtcGJQZig/LAzXzeeKb2kfbYN/M6435qvVY8Dn3JwGeEKoe7B0ZEo4KNAc7/ib4wPkW9JPxmf6UA8MAEwSBAzn9sP2OAxsOniHDMXEiNA2qArz90wgjEIEEbv57DocVxQ4M/2bwL/yj/cz5zxaMDfIDuSWWKg8HeRWPMFsM0SRkQd4QtvToDTQRVv2tALr3JeBS6hcF5f+h94oKeymYOVQueSqDO7IsnCayM5Ik6BB1FpYbHwkm/onnl9QY2FzjavHX/R8ItQthGlofbRsvG5oXrB9xIg0b1RBEB44A7fpfAx8Dn/m4+AD+0v6Z+Q8E7AkbDgQNAQE9/BT/UBVcFa0DNgolGc0T3AY6BXb5QfkrBRMe+CZQDpISzxcJCAz+2/dY6bzaid5/5X/rK+hg3brp+ACqAo4EHROSDAUN8hiy/8jvIQbqFZAJPfFU8jX3ffQe/S4H4f4A+ZX4ke+R5HnVmdsc7sr+BRHqFOICBwqqHCEaWhcvGfoTmAo0CO3/cPA/4fHd1eZY7P7gIeHp5T/eHOjb/NPzgQ+DOb0YOhJGKykdcQ4rGgQTUAeeAy4HJQN92evSCPVk+inXXuPM94XZ0O1CDyULhAjBCWL9GPUFC1wbMgFH6en0oAB4+F8J8gjt8QADauNW4SbzvNHQ7e4dZRb6BjgYDROcDk4fLx3oFcMZZxvLFI4QMg1bA6IBUAnYAYXyjegM8I39igtEHccdGReHHP4dnhp3HC0VNgV2/Bz8/fN/58jpdOOs1pHhle/V+A0KtQK+8+/+EO9N5s74KfMa7NfrUOSu6gb8cPXR6Hjr0PF89XD55f2N/hUEawrkAwj1NelO6RTxVPde+zn8uvhg/+X+aOib5df0YvnC/sMMxxuHL6IvGyMZKDwnFR1IH1wlXh5OH9EisBz4HjUikh32HGscaxMpE5gUYQrDApQGmhCyFuYUqhYxG70cRB7XG6QbVBFbA1P6DO2d5BLiReEI3sLg7eq08Gb+YxBH/oPnwOlB6e3s/fa49Qr8zQwuBrj6uvio8Krsl+475p/dGuEK5ynx9fsc/0wFNhGeFogUAhHXELsNmgKq8fzlo/VXAQMLFSHwHqQY3x4dJAAi3x6HHUIbexiYFpYWSBdYHbIh5iBvHc0Zkhg0FRUHT/fb9Jf69AK7C2cVDSBzHcsUIRRzDm8Bk/Qp5mjgz9553PfqcvMW/JgEuvHb6jXvHuh97tX3m99/0eHkMenC6jn/XQrwBysIqAIO9qTjXNA3y0zPDsmBxdnXtPLgCtUSswn+ByUP9gdL/MT6xuus5RrxQ/xc+xT05gRtCPX/LAFu+vvt4e49+U//9gBZADILjhWQDe4HogzBCtEGYQPz9u3bd8tH1Lbai95F8En9QgncE88Q0xIhEAME4/rV7Jvb79aX1ovVQ96b8df6me9/6pPvM+TT2wLiId3l267jvu6R8Fzu0P99EmcRnAZOBnUFhfok7Jfa09El1RTfJeuj8gD5Rf9UBfIIIwc8Al8DT/qy95QPigfK/0QVexU8EOgUKxAwA67+uvbE4XfbO+kc+1gSpCPRHFwaTiWcHaYUCxizEX8GWvv+6q7gJeBD41Lup/2OArkEsQ0xFQQafRUHClr4ReVU7UfzSeeF7UPyuO05+Zf9Ofnb/w0BL/Z/7PHnuuxH91sJOBodD6wHwRSzFjQL4AuuCon5SfDI9Hvt1eRu9EYNKx5aGg8MRAtfFDIXThaODV0KNgOYBqoSAwcPBYMOTBc8GV8VmhKxD54IcPZN5ofiCOQk8QILGx8PGsEPphgvHKYVOhXwEc0EM/228abhS90C3MjfJOnX/YgQBxQ0DrkV5Blu9kvoBvKF6Bjrm/9g/LDzdwSoBy3vsODN4NPay9fr2iHaXN0j5uvz5g8IIpQVpBdpIisY1Q1/C431Jd3C5aPl6dvz45f16giQH4MWRA0lEbAUbRVbDDoQlghQCi4MKw/FDmcEcQoZFQsTpg9WFUITawoM/7boMdaT5a76jBKcIQkXwxeHHUAZCR6UIWMYwQ9CC+gGcvmb7Hbpzutu8aHw/u2n9Kr8mhJvFCMJogb389nuKenj6ZnpxN2R5bzr9tmwzMbY+NxB2eXaBNvP3f7nk/hKC5AGSgO7G4gbVAYBBbD+uOpB8FHxvNKsx/Ha4+6CAMkHBwamDFIXdRmqF64aXBfZEu4Suw46BK7zo/VpDJwT8BNvHi8gphtQF6oDFOzr8w8MFRv4JTEhXBwjI6YeIRgGFgcRGxauI28Y6AHp9BLjkeb989D66/XsAXkmqCT6EpoRAA2R9vn1lAFB+TvvvvHqA0YAWOwi6ZXe2djr477jtN9Y5JvyYwYXDUv31/DRAGkOQhueGYoPIQYQ/TvztuDj2eXhJOnX/rcHlAARDnMdpBm5F0weCRy3F9EclBmGD6wPNgr7/e37i/t+9+4C4BbJHLsYDwtm/s8EVhjqJskh9hlQHKwb2xazE7kNm/649mkEJxMPClj61Pke+az0Iu5J7ZP4kAOGETgZexB9EtUU2f2m4fzaH9m23Pv03/TE8uPyeeeF7K7u2eBg3JPuNARUFQcPJPFD3nTeZuQM9pgGWhO7HXMWqghc8wzR6cTP12raQ9fd7UAI8Bh9HAsbAhxrG2kgzSO3HV8DJvbS+BzyUvHj7F7ugf9/C1ARJRRIErcgcSpOG+ANWQofCIcc0yfDE28VrhUhB/YP0RJ8+2T2rwGkBegDuPvd7g70+A8PIsEh0x5vEqsBOAOV8frWl+HC7Gr21wvBDIgFcRLLDxr0GuRL6Yv2lAJlHCsZSfe871bsDOn58IPw1/EJBV8WtxLmAuHxCtv41hDnXueR74QGOBtEIZwcWB0EGVsS/BSqIKAVawk+DaQAzPTx69Xa29mT9GkI/g25E6oXBCLmJJAa2RUwDwMDkg1WJLQeJRMHFjQMFvZL6ovkxuBW7HD5NfMx5OHn+/Kn+cEN0xfsDTgXhSIAB7DkI9oz0NXIwNbK3dXdCvnuEM7+UfCN7dnmM/jPEM0SSAJ/81LtvO7t7IXhAOEr8vYG3BAwEL0Kfv8p+lryL99/2+XoYvusHqok1xHDF3kYTgaqBtkW1QeEBysR8ANq9VrscunT6ir7IPvx9ikR1SVOIVgb4hIt/vv5ShCSHUwb7BcjGFYOZP3C6Y3Mj8gt30XqUfVB+s7tzvM0B7kTAwrG/SL7EQtIFFL1ZuvG36TIHNVw3uvdo+5KA1IJigAr+MLve+8nCKAe4BVjBx8GqgCzAtwFZvi48//6EQZvF8sVqgYdB6X7vOtB/nUO9gQREssj8hQFEBsXPgsM/94SRhyeD5YWhxrmDUAAWvJN6IX2OAY6Br0WSCMyGc8UmBKeBtEA2g8XGVAUmhcfG6QVnAoE/L7p6eJk6d/snfCw6Rrf0eiN+2MF+fYQ90ARZRh9DSMGPfIU0DvMIdY/0UfRxtuu6EHv4fNR+tL3bvHV+WcIpf4z8GD2+/bA9UfxvOTP4cDdHucA+Yvz5ejz8VDrvtuR3XLpbwPeFqoakBe9FjoU3AnqA876ePL5+cb6K/3sBisHSf0a/+IMrQBN9tMStSE2EhMWHwyH7TvzNg97G/wXbx1cI7kiRB8lEXz0zOsW8KPugfdu9KPr1eGb7Z/rN+Ea+gkRsBo8FdMKWP+d77DvSfpD6ZfhIPhs/pfrwuPV6FjeIOYsBEAJDwkVEJX+EvMDAJv7n+to8Tf0qvJk+Evvke9q8abstvSF/doFdRYfHvYR5gphE+YRVv4q/7T7Qef5/wIWJP2n+e4GKQXgCykSQAqwHiE27izBKPIm/A5YCXkk7CauHoohdSPmInEkOiO9HRsTWxMjJtsg/go4BRMIAgc3/8j83/oa/eggVC0dFUYaohuV+zH3fwzb/S3zDQ8tFRT38ePA9aH5vPvZFEgLofap+zwA0/Ae7F7lquJq7MD1wP+J58nPGNaw3Qbfj+e85PHoUAUFDzAFOAe9BrL4uPaX8OvaUNGs0f7V/t8/3cLnHOkz1InjrPOF8ysSbSCDDc0HlfvR8Dv5j/ay7z/+h/uH8Pn/MfRD10PhuPhhBC0VTBfPAjv6avc76MrmYPnE9zQBXBf4BhzxdvMG8arnR/aiBWj7dPivAIHz69rh2jnoXOwG/2UEYPhzBDoLFvka9xj4/Oxe8Z39svjr7YPv2+IG5o/tTN4A29Prp//eFFQWEQhpBfX9SAIwDbcLg/8v/Pf+evbZ5HnYcttu4vfpUfBUCeooFyLFHIcqtSHkGrUaiANF8NYBDxo6Gc0MdQCV8H74LxFAIforSCSkFmcNof7O9HTysPMyC4ceUh0CFMEFWPgi8Q8BxQr2CZIVNgmT/E4F0vpu+rAcnC1OH7QeLyGcEwcCmfKo6Y/ysw5SG0YWohZ5DncJaROvDvX+rvcC+sEFng9tFPAarB3ZH9kjcyXeG3cXZRtvFH8IsQJ8+knu6ee+5nb0WwK0HdExfSNjJ8sw5CHHG5wj1RuBEloYlBPFA7L2+uGu3I34dwu3CxsKDQHoCNUT3AO69iv7mfVS7rz8zwDV74frbvG21mrNQeV73c3TBu2R+NXpwvEe9vHz0QLHCQsFtwlWCZ3sIN0j34/UKdDz2nnZHt+n/7UROBFYEzoKofgE/VcC7e6l7vQBEv4ZCVYYpANH+X7+vQBlBzQR8hE1/xDrVNd1xs/V+uaL+BEcXiCDGDoh/BpbEPwYOCFGHnUbeRUpBmDzrudo6Jnz3/2X/4360P+mEAsPPAFR+enxRfAG9Of53gqiE30Havcv6tfem9946Sfi1dhk5Rzyzv32E+gX9AQfAd0ZFRWB+t377e4A4hLl3dTZxoXSzOa09KgK7BwVFIgIEQGT8mbnwPCn9gT51QDQ8+HutvKf8eIGZx5EFSManic4Cp/s1+0v6wjwuxBEJNUjySm4L8ElZxktFDQdcSe7KIEoTCWYHEoerCOoF5AEBP84C30a2S7NI1oR7BE4CFYNvx8VIIEYfSF7LLYjkh4ZHZQJCQH2A8L7pe6X+scVkCGMJN8gJx3kFQ8OvQ72CG0EwQH9+H/jkcvp0ZfbN9hw6BUIYw14/Sv8HP1L7LTmGvWh9Mzw3fVB8aHmR98a2zPh9fQS+yb1+fsK/QLpS+Bs5qjone8c8Inv7ffyBrkJyvZL6i3iaOJP9fX65/4uBI4AoAneE9wUKQtnCHsOxQz2BI4D8f0o/B8E5fTK5HDnK+5i/cETRB3VGjIZew3M9Yvv6/gDBEYSXxPFC/gOXRFMCR8HPAzFC0QMFQpF/s/pDNGozJHQlcywzwTjwvnmBRsMGQsRA2r74faT8Int9+bl1RrW9eBY4KzqIvgk94fvCOes5CPhM+LC6n/1R/vj+pH75f1bAs79bPrp+Pny5/BN7mbnaubd8ov30QS7GFYTNA0vE+4WZxKuDvoNPgNy9cb1+/Tx7Hr05gGcCUAfTDGBKF8fERRH/yj/ohIxIfAg2xxjINUfcxtCGmcZcRcEGYcVww63CYYB3f0x95Pv2+fP5iT06AAhEYwcXBfNFIwSYQoDCBEKlgwrE9UQOAEn8xzw/PIC7unpuuY/3RDjN/dAAuISsBwTDEADRANo+gz9ew/VE68EkgC+8uvTTtwo+K74DP9vELEIewFEDsUIS/p5BzYMCQyUF80OJP7G++HwQd+J4O/nNfVzBegJQfvZ6nLtHPUnBUgVZQ6WBbMEYv3X+jX9sPt6/37/ofrd+Pv2Ivrh/8b3eeq45ATfxObG9eP4f/fWAP4HLf7z9HDzvPb9+wr6+/jn//oCuP358QjkqtlW3Z3wXwR3DPYBNfQS9i/5Xv2zCB0PJxHJEaAMmgIE6hrZYO5H/hL0dvaV/kgF/hZQE3kDdwRm/JoCBhikA8bm4+D437TfKepo8X/5MAkdCYQCnfKh6Hz1+A7PIkohDRZQESEMOgQU+2D1KvuR+Qb/8ASZ8WLkqu3T9I36aQWiCX8ESgMND9kQbv0E7w7tOeam7pH2YvcFAlgOLR8pHBcLj/6q+Dn6LAWsF2AiVB3sFZQWeRDJCE4NRBHJFQ8gRhvTFOwPHwJk+AD5uQaiDw8UHyLdI+AaEx6aHC0VBhjLFtcQWBZnGWcOog11C7D7Pfay9lbyvu+eA9kXcxrHI2cmxRr6GrYkCB9IGNUX/A4rBmsDuPta8bbuP+a05vHxJe7b6G7kUOnb/9MN8gphCncQFQq6/kvwJdyu3qbp5+Rq4KjboNqV5VzfFs+F1d/mWOxAAisWDwRY8sLt3eUp2xTW+NzI7c8Bxwco9pHomd7R4Zv2ZwYNCPgHMAzXBUH+gfjl/fIPsBVdDCcOmg2p/mD09fRN9bzzN/nd/tgD8/3C77zzIP3VBt0atB+sHmEkeR5GFnsaqhqQF2UWpgpm/Svs9dzA2RDWvtPp2wTrqvs+CXUSWBigGJATWAnM8uvineVe5lbmSejM7A75xvmD5ZnTqNGg2hzh0+qYBYoMM/6tBPAGg/ox+Hr3j/a7CrkRofoE8W7oquSR9uf/m//iBDQNMhXkHN4WcQ5GFb0ZpB0zGs8XThzdF1ActCMRG5QbuCuYKG0e8g5c/ToBiBGSIyEsni+0M8kuvSdAKMUm5CM1IyUgoBg6EBkDK/rI9KHvTfTz9VHzKwInGTweZxzdF5AR4AVe8QbpN/naCfgNxw1hB2z2hewC5jfXCNxo75/81gJSB8T/1ezp5pfprOog+JIIKwtXAQLw0du61Vjl9fBy94n8dPcO+68GkAQVB28TOhHkDlQSswl2+87yvvOw70vtcPx7DOoUDxG9AQbtwt4e56r7CxDbGuIWjhH0ENEM5AAS+ykELxLkEhEHIP0/+OX8AwDA9TXuvunf6SbzwvsnBBsEawCu9mLyof40AN/3uPYE/04E5AKL94fkptjR1IXYXuSV7e/vm/OB9O3pzOPd8hkJ+hkIGXUFGvul7KbTO9xs7sTnYu3r/10E4gHiBBUKoA0bDlkNUgfM+tfzk+oY4QzdidnA7SkWXCGWETIKbO8zztngGwPLD90eiyoxJugfkhYpAIPzKQVtF2EPU/xk8CvyIwAJA5v30+wn60X+IxQGE67+YvE97o3rifvYCdcIjg8PEmEB0/irAM8OAhtbD9n7gegj5dT6pAnDA7T8bvcS+cUT5CjNKeQfPhV1C6IFGQt7CK8C+AySEkgHUAAJAmUGBBTwINEe2RiIExkPhg2iArj1rPau+5wJkiVSNT4ptRhtDbDu+uT4DLIq6CXfIZ4ooCE8GAQYTg73/ar6+fnp+jIF4ATT84HirN2D4Ajx0RWiKr8Ygwqw+grtCQHFDqAHrP839Ljjd93E1GDOn96y7gLqyOE71R3JMdTn2PbVqNpy5Ef74hj4GdYAAOsd0GbRl/Ei/f/5qfnT80vvgfQW+QL6Qfs7+330f+6H7mju3fNw+Xbz3+ov77MHGx40FlAL9ges8THe393+5HD76hnLJVoc/hLsDL8E3BWiJJQOM/5+/4IE3gouAnLi6dKR6bUDrhlvHmsHiflw8HbmL/N9A6wEWQe7CsrxddJM2M7oqPPeBUQHf+4a38DcGta82KjecOIA+hsU3hjbE/4SmAR/5FDZn96X5vP1QgKYChkI4/d28JX61wlOEFAKh/yD78ruwPfM9njlduaP+dwGlB8VLG8Zew51CtoHVB3jL/Ij4Bj4IUgncSQGIREd9iCgIREa6hZEEkgLognLEh8PVPj1+ZYMZxcAFlgODwLl+1QSgymyJzYe8BycFZgJOgej9VbkVurZ7tP13Ah9D1QHsQIS7zXZS99g8+oJuSHPHvIMkAjT9Cbw5AOYBSEFBwe1ANnvUtvn3NPuK/tOBeP/suwQ7hz77/9IA+4EwQTkBTQHSAMQ+tnwxN9g2T/z2gcLBZ4Ifwbx8R7ssvQA+REHCRSUDnUO2Q+CAr70o+jh29fd6eu88t36NAsZCHb8gP2B/1QIbxkpHWkNsQbBBarwquBL77L62/YO/M78i+2k6e/0j/Tl8HDp09jR25X1yQ+eHjQZAAsrCfYRHRB4/mLvleuo8hj1uOwx6c7tavFV/PoHswDQ96P81PmD7fPmGOZY67T8LxBbBFztJdwfzLLUTeiH+OQBTf209+PtI9263r7yLAbkH+Qk5hCKDmsKxPLb4JPWNdN45u4B6gzgBYv1AuVB5Kj2JQt5GiMe3RcdE30OYQugCMcEKQdbBlr8Sfj19LbzK/pi/oP4f/TTB/4auSd3MmswhSYhHTobDSSqKockER/XG4oQAQZIBxMFmffO7tnywvXT9q0BbQuBC2cTYSOyKN8s/i9SJHkY4gn160PixvU8AYYHNBMnD3kGVAeP/pv3XwecGIMfmh+kD4QGUhACGVgUcwemBEAVKSO5GM0OjAIC4nTc0PST/JwFwRptI5AfLSBeH8ccZSLmI04dhReiCgb0O+oI7j/vVvJOAbUNxwhJ9yTrAO0x930KxxT4DncT6B9YHeAQ+AVq9pPyPgX+CdD0892V0BTToNx94hLsSfMyAFIZvx3FDH8Dg/Gk467uM/DR6QzutvO29LTyTek/5YHsYu++8NT6kgNbCOARwQ3h+bb11/9UBNoGWwvTC+QBxvlm78jen+KJ9JQDERYtIaoYZxKQEbEJgwumFyMXXw9IDNYEMfiN61jci9Tt4HD4Cw42GpARRf5N7TXhg+xXAFQS0yD2GuYTDROMBtP1VPPC8b7zigCUARb2aOeo3t/YZtid4nnp4fPiDS8fExXyCPv6xu0x+m8DS/9dAi//nfep/4IE+fau+OP/VPWd9ncAYP/uARsJhAuOEMUX+BhzFEIS4g9QCjv+wusz5wbvFvPE9Sj9HwvJER0SsxmyImskoiBzHFoSlgUr9bLnIuiu5nblgfpKElYQYwW+9hrcHNj87S37tw3BGscXShnuGIMMOfnI8rb7VAJy/X/3bvLr6jPn6+bd46ritvO7DmEYWA5nC0oLgfvh9wMMbxOBA3b9zQBi8/jhzeH58aYAawUE/uHkTtTb3EvrTfTX8eXu7f80GxMjaxGKCKoB7+5H9QMEhfcp7M7zsPPv7MDtUujp6PX+FxVMGqAVjhXTEgIHwvuw8C/lUuoK/rcKwQab+8TzeOR/1MbWo+mb+38LUB6qIkQY+BHPEXsTOBKEDIgIIwJ6+7r37+Pvyu/JJ9TP3i3wqf0sBGsHNgZrBKACAAHmBgQV4hgdCcTuaNi+z/bQed6o9VX+XPWL63Dgc9Qp1d/j2fZzBxkTRB2MHYgQzQXh8V7ZS+hACbcO4gN6/scA5f5R9mDuM+6l/FQShxvZEHMG6AXLBPoFfwUC/+oDxxb2HV8Vig8ZAw7xXvF89aP1SAiBHIsjOB5MEEgN6BZeI6QeZRJpEcMLcP8r9RLn29c325nuav18/BDoHNQI2DHkf/JMB20MKQglCowCm+8n4zvhUOli+70BDvY36lbhO9d51Y/fO+QC+jMh0yqKHx8Z/Am07RzhdOrV/K4RfR38FrkNQgY79875qg6iF7AZRCIAJe4bsxIFDloOcxcTI6IsNTHVKbIcRBINAcz2cQUbEqQTzRWoEScMpA46E70VOBhQInEoMSGIFOYGCPkI8OvuHPE/9yEC+hbNJBEaGwop9Vjbg9zn854AAgiGFLsRmgdpB4YBU/pR/4gCL/zO9j/05e0941TXl9A72N/xnBA+IOYZ3BCQCR782fdJ+vn3zvugCk4NQ/sg6J/f0eOF988IsQaP+zH0HPE76IPZuNTd3nT1khM6IlIVav/V6/rYuNgC52z0Nfs19UPrP+Gu4cTyZQH8A6YMDxZlDs8BcPXx5qbfl+LX5j/uywIjFu4TrAaL92rsEvXyBjQMOAnRAn75HvjO/fwEAgvVFQ8jmiCWEbD/h+2m6Evy1PmX+AT8BBI8KPonvR3cDDf5WQIbIQQyzylpJL0iSAo/9H/10vyOCPwcVh1CCuQBO/5V/aQJzRD4BEQEiBvZLPIkNBh1CpvreOkVCa4aXCM6Legk5g20883bcOF7A6Ijuyg6GX0R5AOb7KHnTuhu5+vyKw7sKaApABZfB4/sathe7A8EiBM+KX8wYSHLFhkLyPc7/XEQTAqL9inondwd1Y/SM9EQ0MTV399L7kH7i/6y/uf6Jeke4FTx1gIwEgQiwx6eEUIFDvCD4qzqp/niABUAfPcg7PXjTuWJ8dD9PAq/FHMUhg+vDfYHBvxq7Rru2/6mDC8WNhbLDPgBaPQc7HDxxP4ZDJQQdQurA6H5IPD161DurPq9CyUVSAv59AbbAMlH0d/icO149x0BEQZxBFH9P/DA3+3bRefX7DflLdjbz0POP9BQ11zgFOxc/gUIp/vj51LWpswO2JfveP9/DEYU6gxnBq0BYPygAVsO4hC3AYPwK+ff6nj6XQjTDnkUwx8tJC0eDRrJEw0GxwOsFDogOiLmJ5IrnCa9IqgfXRq3GwYfrhugFDoP8A2MEi0Y8BtxIdsm8CbVJQIo5CPTEvH49eid7Rr6ywXqETEbzxohEcsK0RDXFjQX9ha3Dvn/EvWH7ATm2eLd4dvrWP+UD/QWJQqH8u3cTtTx5Lj5fQktFfIVRBF9BwzyfeKT6e/4awQfBl77dOvG2zvSrNQO4EfuO/0HDlodXx3LEvoKM/MI2qrkQ/vDBrUJXQC0703okeli5/Xoi+6B8XLyNfPj7F7ee9iN4Yvxnf2vCgsZ0xV9CiUD8+t/1Eff3/L1/JIEg/8U98z48fyy/3UHWhACFccVBQ4Y/9ntUuWD7H3wUfJzAc0SIxYZEtcH0e7M5VP5ww82HIUc3hMhDfQQIxPVC0YHQg2BEgkO1QL868jVsNQ94qrq8fNzDRkg4h1GGLULUvL57EwA4g1AELMLVAVk/cb2CPRD9SsCnBQtGdMO9/7j67zhXue49DoAQgWiE/oi6hmuDWEBjfAz/bUTKxPFC5IITgn2COwBL/oHACURdSFeJjQeNhL4AzP+/f6h9szyM/5UEJoj3SYzGrUN8f3Z9g0BuQcuBuAPWB6qGrUMkgOYAtMLIRdhFXEOoA7FBgL0i+Dh0GbNbNqu7/wJyx5dGjQOngVL9DnxoAdjFzoW4A4JBQD0+uaq5wTt7fXDA70NeQz0BOX5zuyZ5Fbrdveu/WkGxREJDbT7Wule0fjMfeLC9UX/Ivzr65vcrtmf3FTgh+3JAHsNYxCQBRrxoeJm3NvaM9to2Qjd6+5i+GDuVN76ybDGMdgi5Rrs8+8e7+3y5fSf603pDvVEAsMKAggK/ZHzRerK4Kbb4dxo6Hb+GxWgGPIMAwT7/UoHDRzkIqAh5CSDIykdBBdvCrr+0we7GykcShD4DYEInADWAdn+tP/ZFr8yNzR3KL8kThSvBy8d0yvqHn8ZBhtzE54GWvTx50vtQgI2Ge4clBOQDpANLANL7RzhtuoDBNMi5CnPENn2MeDP2qruEQCQC90Y1RrsCrryjeEc6qoD1RjFGyURogVg/jX+vvnX7S/rO/YlA7sNmA+CBB77WPaN6+3np/QNBpobvSV7FYP/ZPgr/GcARgV/CQIKoAtpD20MUf6y6z3kyufl7TgBwR2sJ54fYxk+BdX00weIGYkd2x8CF6YDWu0U3YPXZtxk7YIC7AhrAy/+T/ts+zH9/f1D/WME6Bf2JbUbWAl78HfUJdkt9CMIPhcGHIENQ/tu6+XlFPamDUwaNhexDHEFWP4U9bby2/fVAMER4h17E8cC5++w2RDeuve7BmUUriQ6JCcb1w4I9mDqN/2vDNoF0PYz5pXZTN1e52jrP/F0/csKlg1zAa71xvX4AXMS9hbPFI4cmiEbGYwSBwu/ASMFYwvmBVb3Iuuo5srqYvP79X/49gU6GWUnwSRzG4oSvvuJ7/X/JQbA//QFdQkBBTQDn//z9yv1tPxfB44JLQvJDtgHqwFWBWEFaQNzDCMbWCBMFwsKAu3Nzt3UWOrC/Q8QSBDRAQ7zSeim8cD/FQG5B4QMtwZc/r7xEuDV0aDNENfT6ZQCkBn2FWkBher40vTZRflEENMc6B2wFx8Pjfwi6IfhRegp+WcHdv8U58/V79LH0zfS/tLN2YXpAAaMGUASwwB6727fXOQK+PH+KwgNElcHJvjz7zfkS+HZ8jP/tPlU8kXxXvXb/3EG+gPYA5ALbRfJGg8SVgvZ/dfjld0p6Lrp4/imFFIbrhMrCtoAeQZQG14lIR6HGisc/BRhCk//QfEx76P7MhL8KCMluRRdCE/rQdmT6o/7FRDuL9E1PCc8Ht4UgxEfH8ElUhtGEi0H0PLA4yPgP+C26Ov7vxBhHgIZ5g0RCAr2heuy+bkFxw6/GtsXCQ2KA/X0ZO4k8+v07/JD8UPrAN15zaTLjdcn6EgAlhRlFpoNzwRF9j3j/uJP8ST72APNBcr4ZOzK6ZvlR+Rs7yr8UgKgAvf5YumZ3c/ebubn7r76DwqID38FyPj+4qLPddkr7rr7PAFH+fHvOfGP9oX65/pMAeYQCxSEC+YADu4a4+/p/u9N76XwOf4ZEBULqvaX4OfMDtFo62kF+BWgHMsXKQ1zAin3ZO+L9c0GGxBMDSUFAvfx6wDpyODp1mrd2/OOEa4i6hdtBp30Seqs/a4PSBHqGwYlih5rEUH7feFi4Sv2MgbeDpYNAwRm/WD84/zC//wFQhF1Ji02HS4PH+oPqPf78FQBSgvmExEiRiJhE0wIewD0ANsW0ygTJ28hhxoPDkP7vuyR7ov6lAwZI1YpcRZfBkv99fK49oQAHQgLGuQrVCx/IMsOgfzt+w0M8BZhG+QWMAUt7/jaqNFa11blUvUhBRcMogOb/RkBHQATAcsH+A6IF5IZYRGaCYwByvtpAc0EEQG1ArcFrQD59JXgEND+0xDowvonCjIWiBQ2EdwOo/506VTlGOxJ9Fz/Fv9u9UXxvO1c6BjnQeda7VcAVA9hDXUAcuvr2OvflfTz/8MPfxpYDpoAtO/+1WDPSdqu4cbprPMK98D1T/Oo7RjpLew99OP/8gpUCDX8CO/82UbNWNas4/nymAmzDgj8sOjT1xrVdOnG/7cOTBjXFyMVfxKUCRkCwwHBBhkNrBHmDVb+dvH66CPcoN5y9KIHYRtjKmsiYRikFxMSVBDBFqQarh5OJQoiZRP6Brb+XvoRBQ8U+BfuEeoEgP1zAAUOGx8GK6oxNTBQLfYnnBoTD1ALSAhOBpYGIwkvD88PLQft++P2pgGmF1YqkjGyKm8ddw6mBuwP6hqcH2Ug+hbgCXj+hfv0AoQGtQRi+3/um+8e/3cLRA2BBan8dQVKGZIdig7K+d3tp/R9BNcM0QAn6mTcidYv2s/kBuyP9qYF1w9aEowLKQAK+hrzsOdw5T3rlfU3/pP4vOS009vUkeJS8cb6m/qH8sjxuPbd+gUE5g0+GNkbKRNxDkQMngAr9qbv591BzqDUK+Tz7JPp8+At5wUBNhykJ8UbTAmD/gr+gwl1CHD2me6n+eIIlg+ICWb7oe3r5Lbk8+Vq6iT7JwwXEQsLXwBKA6AYpCXTG78P5gmL+/vyl/xR+dfl1+GF6kfzoAG9Dv4U3hgTFWsLCQfRCh8U3ReeCH3yGO9D/gsSQh/PEaPzZuKR5Jn1LAIz+Fbntu4hDJgmkjCLJkgagRQZD1ISCRfBEpYMXwPX7LzWQdhw5qH5Ug76DkwDuP+xA3kR2RxMGO4RxRP2FpITXwpW/h71svEW8cD27gC3Ahr6Duw/2unV8+PC9bUPLyNvGw0O0whMBuAIswrwBS4EeQwxFooRyvzR5ADV89Zm7HEGUhTsEQAKhgLQ93TzMfo+AuoN8hcZEZAGvPkI3ifQZNjb3o/mxO0z7dvrTeoj5CPbN9oc61sCBw9YD7sIIv2J7e/gQd1k4VbrqvjE+aTmedIGykbNJ9lD5aHup/VB+6n+m/2N9z/uXue06WLwOfA77OnqFubt3CPbf+Ip77cBGRQLGhsPCP109Yn/kBI6HmUZexOgFg0ZdRrXFxcKR/p6927/8AHX/CT4yvw6CowVfxfwEUoQ9BqaKGUpJSBlFpgOrw8LE2sJkfxU+vAAPAzcELMITgDRAeIJ6A8uDXsFwwhnGAwlzyOMHFwasxQyDqwG8fII4ljksPKq+672+uzT60fzTgJCEn0YjB2JIgAc4Awz/TPwBu5Y+Cb+evZH6lbmQ+zv74fped0Y203qxvw8C+ISbwR/7/zpaPPqB5oTqg9ZBX/3+uud5ZXkqueZ6qjq5e0g9qX72/4i/KHswt5m4MbowvI5/jgBO/fI7YnsM+y+7e/xqPQ39oP2fPFs6aHkAORD6qH3EQf2DqQJCwD1/VkDrQYsAj/3Iu+L9RkDGwjJA6H9xv3kB3EQqA9KELkTNhJtDX8EKfYg8Kf9VhDHFfIOVf/x94YEMgrp/df09feUAvoQRBYADHcKmB5YNqY89ixAFgECEv1CDAAYCRIbA9n7igHFCiMRZRQjGGUeCyFKGoYPAwvBDDoQExKvD70OPhfZImsiRBKaATf/MgmSFf4aHRZQDowKtwjFCcEO0xkRKLAnSBmYCEP07+Ra4Y3lT/AY/LT+OfdL9gMDFRCeEmES1xhQIOgkvSBhD9f7M/BN8hEBaQ80EgsM3gPK/h0A7AMwBmsIkg4wE4US5hQTGuAb1xpvF18RvQsXCGcIjAeX+/7r2+I34qrv4AXuEOoJKP6f/A8JrhvXJR0gNhMrBgT8ePYn8tXrCOJk2bDQk8t308jkxvRk+P7w4eeZ4j/lM+6B9ZH38/mP/Ev1VOTI1HXPHNXj3v7kMeK+1O3Kj89L36HwIvib99fwsvDd/64MDQnn/Iv4mf3eAjICePv+8f7qn+sr7znuHO5k8xT6ogELCEoJhgpdEA0ZdSKFKVwuGzDbKv4iiR6cGr0V5BQfEoIGcPxH+bL5h/34CPgZSChKL6gsxSOyH+gj2ST8G/gRwwyDC3kMXQe+/P74T/4dArj8HPNu8Kr5EQqYFRUW1RQGHXspDC1EJicYUARm+FT5/fgv84Psz+mo7KHtIudD4Lbi7+sm9pX+NgUuDDARThAlCugDDwCF/sL+EP6l+jv1GuuR3yfY8c/PyRTMndTr4ZnymgC3B3UJSAUe/n77Fvty9/nuMeOR2sbWotbt28DigeVq5aHjLd8j2yHY6dMY1XLiZvY4B2URqBOxDvIHbwGF+sb1S/TC9Lz1k/Ev5k7ZidFu0+Pe0+6y/QsIHwu/BqoCBwK/AlcF1QeKCVIJdQa9A0ABRfz59UXyo/Lb9f34vvwI/hD1uuSb23nkhflSEAQgRCHdGS8XJRqqFfQFEPeD9T4CyQ7JDaABnfaF9Vb8GQVpCxsRaRrwIkokdx9WF4UQExK1GfQbPBTeBj350fEz8VLzyPv+CwQajh1UFfYHlf8G/lH+XP+IA/ANdx5zK14s6iExFQUO3gx3DvQO6A6OEXET+g6/AyD2yu5i9BsD/BFKGlwY1Q5vBTABcQF7AXECRAcbCnMF//wM9aPsn+mj8Kn6Q/9c/Un4DPQi8MLqQenb8icGqB3VLtstzyGWGAIYSB0EIGcawxE+DIQJNgSb9h7oi+Tb68r0+/a08RLucvDG8/nwI+cW40PvJQNpDq8IGPMS3R7XRd4Y5hjnR+H+2kXYPdYU0SXMdcvAz9XUVtST0YnS09r+5+vxqvPE7vfo6+Nm3/HaEthu2SHe3+Os4sLZUNOy1V7etuSh5O/lvvGxBd4XaR4ZFF8C9fhu+Tf9uQCGA5IGVAk0CbMEfwDgA04PRhm7Fp4KAwI2AkIHpg4JGvwm5TA1Noc2iTCFJIoaDRhKFpYPdQnFCPgK6gpnBtwCAgiDEyMeIyKQHJgUbROKGCkeQiGWHq4VkgtvBr0Gcwc+B8EGzwVvAmj88/ga/KoGOhJaFdcSpBWDHnclFyXdHzwbBBgTE6YJOfxm8dXxKfruAmMKqA+FEkgRmAkU/dXxBu6q9M0CdRAfFl0RsQUE9/nsJ+6+9I/2evPf8rD1U/Yt8xLwL/Be9en/NAiGBysBdvlL8NPo7+Yi6pvxL/km/UH83fdu8i/txumT6T3trPMe+nD6GO6u3HDUz9jb5bj01gJUDVYPQgpjAPP0BO0n7IXxWvhL/Kr9g/0x/J/9swKrAhj6VvB77e/wyvLI7cziydho2Zfokf3RDRUXCRshHDYc0RqOFSMORAtKEJAW2xOvBArxR+S24gbrCvbK+p36+/0HBSMJpgdtBQUIlhLDJCUyHS9jIxUedx6qGkgQ1QJU+Jf1f/mf/+IEyQriEJgQrwiQBQsT8iwKPYk3LSjgHaIiYi4bMdcjhRFvCvoL7ggp+hrn4d7M52720v3U/If9FwjoFjge/hoAFa4TsBgEHQcVbwBa7ivok+rn7njzYvhR++X6Jvgc9hD34fxhBGkF4f92/QkEGxGIGY4WExCwEdkcbyULIc8UVAlnAg7/aPgA60PfSeGq80ILIRUbEFQKcw0RGU4hLRqECG76ofNm71rpouQM6aP3kgScA2T0VOPz3nbmXusO5QLYzczhx1zHnseizbTgrPtrDgAOBwMC/mUAMf5i8dXh6dkn2IHWHNMK0f7T8dpJ3LDU48/l1/HqqfwBBR8EuP6295PvxuuJ8nL+BwIM+FLort+w4Rzqj/Xv/7kH7g32EFIT6BawF1AU6BI2GJggdSOMH2cc5BlAE0YK/gJtAlQKYxSQFqYMg/tB75HxuPtWBmESAB2sIKIdMhRlCEgF1Q3NG4kjaxncAZvmQ9P21dnoifySBEAErQakDuoXMRx9GJINQgXXBRsKUgvqB1UB9fj79Gr8oAVCBdECNAIO+UXt3+t97gjzGv/XChUK0v9P+2UC+AuaDwAQIwv5+4nscOMY3vXfcus99sL5RgD6EHcixyagH/IXnA0i/kfx2+jn4vzlN/QrAfoDhf4C95XwGuvX5y3nheuy+KIK2RiFIHUg8hi3EbkOjgyxCGD9eelc25XccuZL95wNtRiqEaAAqvN4+9MO4g5k/Uv1EPm1BbcW1RQv/2bsruND6TH78AEz+nb15eug1ZPIFtJY6kn+ofXd3PbbIvGGAqoZKyrdHgARuQJa5EfS6drb2mDcFvRpApPvtNM9zYHg4/Jo7nb5VhvsIy8Yux2YHrkMAvrr4SvSd+P79oH3vwMlGXskyR4fEkAOEQmj7ovT+tX+6MDxqvXLAX8O3yGLM8sxbSmuJ8kr1y5IJX0M1fSX8IPvxQCYHnkL9/OSCYf8aNtR+ZgVSBZOItsdogwvD1gS5A6KDzYU8BVbC9cHNBdEKVgXXPrHCAIZXRRcHx0aGP6YA/H1ttPG95YPZt5S1kX7dPofAi8rey5lIYcryyczGpQbLRfHCFr3P+qX9QD92fvDESMgng3aA0wFUAKQG80i1fycApwWDu6X6v4kHyjYAVYGev600+/bm/an9QsDaSErJAIWRhmYGG8IdPSV4znpzPOJ8t//OhQ2FfQKTBCKFlgTmgy4+6bxawJu+RLaDPJEFNUAi+xH8wDqaN4p7az+GQD2Bo4PQAs1/Pn3Vvls7o3d+Nzj803zjeFY0WzgVgI97Z3cR/MW8Qrroe8v653teOTwy7TRl+Ar0mbJhdbX1+nXz9rz1iDkXPUZA2kSSAwq/Yn/evmu4bTVDOTZ6/XoQ/opDugOswhCEsEXtwvHA0H6uQBvFmUJDQFhGFoaDQkrC7USlhLeGDgdAB9pHZQeWCeaJSciXiYNIgcV5AemCp4Z1RjuEzgf3SGeHoskUCimIpIXhgTt7oX5FRTbG0AR0QvWAU3qEvQwBtUCFQeh+gjqm/P4B0ADLf/PGAsMxvJ8/ePwUuFo8fzfBtHv6vvw9d3O8qwGf/Mi6aztge3Tz2rGQd0e2+XLqtL62mDZkeQA6jXVLc/R20Pe4+kI9h74IvEt5b7nbuJi1+vfzeBO2/fsZQzeCc7t5fKf9mTYntQa60PqIOvS9WsH/A7A+hTwbOpB353vggHz83j0gQc6EysH6/hYEMcb7hI+H1IjtxJQCnsTmAun/6wPoBm1F5IpvTCUEncgOT5WIIcc4zBOId8h1SiaEBUZgTCYG0wUAhpjGfIeBByuE14cqC65HNUTwSDqEMz8QhCoIRsJ2g5SMBMvCyPFKWUpYxDJAUYQhAfz96IMUBZ7GkIpNyjuHH0coBeX/lYKKyeHI8kaGQj2GMk0khv2ER8dUAND+JQadx9UGZ4kESHXHIki8B6yGQAdEx6iFgsQMhCqCLUIPhNEGOQSWwt/C4oER/a1ACUMqvJg7Sj3xv7+BxkBGQE8Ac7souOy/3kF5/F09A7+K/H83rLXdcuextnbId+82zvgf80vyn/N7MHfx5HeEshprWjC4c2RyVTMJcM1vxDUVuBo2tXLy8bHwonBZtKo2DfPFuD5/nDywOHG8cjomcxI0o/VpMfvzZnoDPLp5t/6Vgz3+O3pifid8xzxVwFq7T3qEP5ZASLz3fVN/JfpqtWT5I/7Dvjh/fADS/wY6wTqRekr4EX1qv3I38/nzxLZFx8JIRP8FqIAZu6P5GjwIvkr8ef0dv6qDkYY0w8REpoalg2Z+lrvuPCZ9cT1ifFD6qXyQgtYEzEWBiryIq8Km/5m8WzvzP29BNUOYieDM0ocNA5nCG0BAhLgEhkcXi6aKQcYdRV5G1ANngaDEW8lBDgvNJ4qyy7oK4UgJx5fGxcJNgMTIEog/hiPNkAtWBwPLycuLRrDCvAGwROcBWDqIwUhJF4xWDOMIb0iaxij+27wU/kc/w7/2REGF5gMThPoE4EZ2y2sJzoQrQiZ/GL1bQJB/MsEXigjJLsF+hGzEr7tl/Gq+lrqcPriFR8fUCKuJnsp2x8CEt0XpiKUEdcV5iJEGzEaexkpD0wHRgME/AUD0xfXFckH6A3mFOAJ6/sg/UwKHRkAEpIF3g0hHccUpgdAD8cOVATWAX8EpgENCIQAL+tH9ikMWxL2CI4AwP0W8sbhatuJ3UrVFtLV5xD2UO9c+AUHCvC45Cvwk9PRucXNdNvI1Dvhj/Nc67TVbNzf9Kzrbtt6++H2LdIE3Tv+0PtW4HDlgcigtlLM5ctY2Hr8P/fR5af4lfNQ3O/Uj8wnw+XFPchW1jnjK+8I9EX2+gP3+hL28/8t707S/tIE38nQndfQ8Wj4fQWP/sL7fP0p7aP48AGk5nXUS+Gw/FISoBNYCx0J7gJs8KHnf/QdCtUBo/UACdMNJep558MHsvQn3p4Myw055+4HiyPTBmrwdPeo9Bj6IvyMDRMf4BmUE0YRrw+sDDYQHv6B9P70O9eu3hkRqAwo/FT3ZRJcJx8WFRT2FT/9cOX3+ZgIwQzZDkYBsPC6/SkkQhY9/XscPB0TARULLASN/BMmjiiBDZgUrA7N4UzXRecj5aLkKfaiBMUUmjFiKUwYEw2291zfbu84C1IQ7BZpIpYVEvoq/Yn5P+YE8OII8fj16ikEmBjFBTHtmewG9K74j/91DI4QhRngD53uEwEhGIQBew2BKHMVlgXz+pHrtPikDIYMjgY6DJAIFxQhJB0cwx/XKGsiOCMxMnstCxYxHzUr4BY2EckWcwhw+y8O4guvC0gkizGJKLIkjzEbJZIV8BWUF9UJYv7aCPgfbxoPFd8e9AXj9sMJCQnwB0QQZxKFGKAMigLf+Y3nIuUe+Hby3/Rc/pvrPg25JogKIwbkBSD3l/Rg/S/psuKYBtP4FORa8z/5Ev3TDFAD1etN8Rr08fPl+Ar3vRD2EdD5QBgLDjXrg/he8GLfHPwhDqAGZwxxEHcHgQUbCBcBh/yZ92z7gfNi49/l1e+Z5o3jYvnM9ajaVPMfH536cuEp6/rZeeZ/+9/vDObv0tm7CMeJ2EPR79Fg5JHvk/lEAAb53/AO9vf0GNjHuiO/d8flv5rG79wz2TvYjei64QDvAP2V9JvkieUZApnvdOpQDaf4Od1Y23fLWM3p5O3tcPa1DtUddRREEPQOewRP+AroGPctEtkP1QwnGMkV+AfA+tn76B3sH68J6BYvGy8ONgjcAb76GwI0AcDyzQA0GqIbcQOoB8MasBWMG/gimh72GKoQvPUx4JHyGvas4srx7gm7D2cNvv2/Bg0W1Pp47Uvw2e4c+mEFzwFMCS/xvtvZ/tv4HNWX28D1+e3E718N4iVjJAYlfyQXBHTcL9k77+Puj/JL+Wj5bu/K6ATyXPsk+cj85BThKWclMhmzF20S+gQE9zf49BBxHjQd9h+cIOQk2SPTKKQs2RorFN0iQiFQC3EEGRAwBYv5wQ9QIrkqeTT6L9kjoCHTJDwoIy2wJxMrGTS3IvQZxxDuCUoLrvwz8q713fysB7cXXCtSMf4amCQGLxcHe+xY/J/1XNsU77UEAQS1CYgbMSFcGuQSOhLBKYsodQ0XDtMM1/d88o3v8ecn7SvucuhS9RkU5iGMFp4XQhxnFFwVABWiFuwQcP+u+sD/p/3+AV0TIRkPGUQZThZjD8ETGROBBeoCnhRnHzYSERJ5EXcEl/3C9IXpFvgAAhcABw+/GTgKDv8TD3j+rton0UHWsNUG1o/fQ+sU4AzSEPALA/zw4+RW8wj7meCH0u/Rc8TDvpzBG8fHyZnZ5+sW1xDJ/uUn5+nSgerC+/Hn0d9D5XDXKcICxIHKL8Key+noZuv45RUGfQeb9NEGmAh/99v65AeBAx76LAKs+yTqXvEE8Bbfvteh7x0GUAkTFPAXYRWIGVoWtQeN+m71/f/JBOH/SAcFD10BJv40Brrt5/ILGmcUggNnAx8AxOzG6CLxyOIM7dkRqAGH5gUAfvct3skA2gbt9DQET/dY7wDxPdp5yP7UUtybzpPTn+PG8HsM+BmtB9gK0w81/yve8tLl52Du+fMXA4P7FPC87Tffntdq64P4XvwfD5ookiqDFXcTmAn557TXtOuj71DsMArgGrEFJQBxCa74HwFaKOUxFx/2G8UeVgqD+CLte+uP/3cAaOuP7hT2hgfuHiUN3ASsGBUsxxthDFsNq//t/fv7PgB9BRD+DPge/JQNxylYH7sEThCIESb3XO/8CykY0xAFEb0aJSTsGCEJFvU5+RkOSgLyBDooTDiFH2EYjh0LAjnncOm694nzEvmgFuwlBiQGJK4sIzPwMQQ2jidnGgAcBxAK+8bspe7LBCEgySteK2kkpiGFFDQJ8h0RIuAd8ikxHhsVbxNu/nTqVgPVHeATexP6G/gkYiycIr8jljBeKGEX4BJxIZgdoA4dFKIOHvzS+kXsoNMG2ZvsAvFJ9FgN2R7yHXkYbxO5B1zx4dZq0Z3gYtSZzarpqvL56G7VYNdN7nr00Pk97eHZXt+o3/zL7dOb3JvfP+/M7lH2o/+F5hnJHtvM7Y3klfjaAVboWvTE8xbPaMTN1IfZ8dMU5OH04gE6F3sWKQgnFGcRfwGD+NX99gj/+bkDihjeBb72dQi9DCb7DwLFE7sPBhP2GSMOkgslDAUALevP2E7d0+NS7h0FmBDLCqoHZP6y+qYWmg3I+wkLpAEm8DPveeTZ4rD6lAWw+sr9iAX77RrXI9953yvWj+mSBp4TyQOy/Q0DsvAI2lbZCuiP5qPxWwctDwAVIxdECyECogFS82TvewXd/r8FBCAlC6QFUApV/p3yCPnPARL5Vga9HYEYywgtEbMHR+Y/1V7dJ+gC5Lzy6guaD2L0rO7aCg8RZwsZAdoAmAWB/r7xaN3N1N3eEuI149//AhLb+5Pvl+kt4FLfENd26QMMBwGB6QzteOSF2B7eAOzl7g73qAyaFagaGRWmGL0ZNAOJ7sjjxux69j31ihLiJrUIewrmHlgPKQWYA8MLexuSHrcjHyvdJowkLSQnHBsP/gekEKgIbwFvDQkazxOgBsclmjnuHg8fkimWG+gS6gzcAbz8bQr4D7sKtiaLMC0UIQ0CDm8HMf5q+s8OjCXRFA8BcQ99BRTgSdoa+aAIRAcrGM8gMyTBK/AgswpD/u3nWunLAhEHhRyaIK8N0wYtDzQFqO6N4vzlVgWYEV0FwQ0dHDoF0vw5/e/VDNUk9Y3rEOWqB4MO4+SD84Mc+AcC8Fb1tv/iBIPpKdhD7yLxUuFw6+YFtwsx/Zf6FO8W2BLZENJszGbh1P9QD2kKtw40D5Hz484QzwDq1+ay7b8C3gZYFF8T7AFCAJ/7gezl6QsILRwLB6IA1QVpBeH71eu+6L7/XxTVCf4IERPHDJIDyQGb9iXmod9N5knzQfcm964KQBzWAYP4BBy5GwAI5AtL/HbibOVL9UoA0vJg6Q8EuQ3iC1oVVgqeAUX0qtl96Qj0yt93AREPKeo4CLkhXPgr4MDzYvYt4iL0ABI4FFgdHyKUDpoFCvNz1C3dIPcLA88dzyMED7kSjAv+64njg+vd8bD0WvNi+yMLYQlm8sr19f057h/XYtnZ5bTXed7t8xbk5+LYAPP6ZPbmB/YD2+cE4cD0S/D43eHg6/SvA3/3dPiiDqYIVu6N3wjqh+ms5YYDqglq930Kdw1k8fHoqfho+d/4kBiyKnstdy6UGSwCwQRfBV8A5hWiL88tWCrfM0gwkB5CG6oeOhRfHUgtPCcrK5QxOTOOK9UgUihnJeoOKxgZMF4gzSHHJToNXCAfOXEgOiBxMG0qgxsLE2EYqg7ZDfISQCGNMt8nwyJ7JHUO2fV98934mf51ADANESmmLVYgTCMxFv348eiH82L++/FvAaIbpCCWISUeYRYDCyn63e08B7UfOglQB2kaew6y8Fz1MAK+/ZYOrhHqAtMFexAyA67ko+ah+Fr0EOqk6hUF6gKX6HD0dvoI5V7bruql+lH9ZOrC2bjv0QEn8RjhJeGH9jH4zPdMCLr2WNd71SnSZsCJyUTHzcQC6BEC1e8O8TwB0eDbu1q/sM+m3Nns8fuBCKz9o/Cw4+PJoL0S0VDu+++H+QINcPsE9TwBXPcQ6Rrq9eZQ7EX9XO9s6OYFTAwW98UAhgZP8Nnb399S5OvVXuS6/mL8of4RC3kGQgbmFzoV1wZCA/X25+Up36P7GQl5BBEVZQ+8+bjvl9UOyH3fBO1H+cURphKgBdMJ4ADC5m7bwPQt/0nt7+5H+aIABOxK1VTv4gV88iLxRgCF6Hbq1gOqAiT+MgNdC6747+WV2/Pc2eSJ25HjLAW0+0zisu267aLam9sa993+rPUPBT4Ni+us52UGkfqL7wkB5f7BBXEJyPSu7QzszQO7JcMbpBN5Dmj7UfYg32rZ9AfTGEQQex/+LEomHxTgD0wGn+2f4r74OA5ZBmMYMTEQMycySCC7E7UWJyKeLZwjEyPTK8MpOivTOhA7pCdcGjwbHSngG88EaxbDJm0OHxzDNzor+B6/KR8i2f4XCXcVEwoK/xETniCYEjMtPj1rLi8pySF1CWkDiiAAIqgb7jiuNGcYCBrNEmLobuwrGSEFawFCNlA/zSNeJg8vohVL+94C8hm1DJILnCtEM9Mhcx55HA8Jzxk3LY4a0RpvLuYgNBbTHVQZQBL0DcL++fKKBScQtwzNDt4OBwQk+en+Tf5Q6lbmNeyZ8N3qTNXA21zi5dei4qf3zvuH9qrvduh11vDEVMt24IP4o/5W8EXpUt1YwEa0Ib2Z0ZvWYtQ16PnzyNqD0xztO9vPumzG394vzn/IS96F6TX9DQK090n81P8/5wjbFuq+8f/8ewkABI/9OAHG/cz4LfBL6E3zN/6rA0AGhAWxCQAINAMhCs8MwQuGCAACAPTP4KbiwPQU/Hb7vQgXDvwIyQdvAGD2FvB55OXipvGV9ZYCtQf57Q7tqPOf5CvraO416lr4twRnAXjvKe0c7hrevMcjyh7evNwE4H/qdPCd8hLlkeH998Dz1dzb99MYOA2B82LwaQHb/qX77gQz99ntyu2f2lTgqf0JC+YLrhYCF8j7GObp10nb5ekS8oD+OA4TFagQjAdWBzYZjhyvCTIWGyL7/eP2XwxhCEoNzR9pDlr35/5R9YnbbuV3BccPfRklNJgxqhviFq0FwvGo46Xr2AC/BloODSJCJl8J4AWzF3MR1QHgCfYbeRd5AgEBUhOaGcEhGSNADDIO0SH+DW75qgspHFYcIxTFFKAZwwyKCC8h1Rpq+Qz+MgTX/Gr7JwYAGZwr2TrwLTUkrifPF20HEwJ3FeogvR1IH90X+BWBFbEEDv3qDfwTPh4XLpojbxj4GL8IqutP7SURrBF5A/YTSiPXIYccJxy5Fu4G8fbn/xMQKRPmEEgRWhfVFNwC5/Un7GDXjdps7ZvlXuvRCgALp/lq94nucN6y28DmFu1W5Rrhbt872kziCuDx0X/klf3V+wDk/uFN+T/l68FY1mDybvWf9z3tQecQ6H3Trs4W7+Hovt8c/f4ApvCF9Hj0jeOF4wrYpNor6iveReBk+OQM0Q6mEN4R3gnDBssKJxFvBMzx7AqIG1UBEQEyC9f6quiD5QTwmfoZAg8QAgtUAtwHmgIW9CL5WQxJ+6zqhAL0AtHio+bO9ajuRgUlJeQQjgM0Dwr5Kdqy4A7xCvDr9cLyuu7G9s/rMdfG6jgWNgwo+6AWyxql/iDyO/A/5VLYndSZ6SUByP4RDr0XCPhH+G8JI+h/5H8SuROGAtwWfSUREaYKdxTZCwsAK/ms7DX3FQAc8Of9VhENDSwDVv5m+ogEVA2l9K7dM9gA3CDi/uh8/ccMig2DHQsc5/4x9Fj4ifC83fXrOgqtAGL+ggaJ8Wrv4eu+y+3U9ep34dvo+AO7EegDxw93IZn+TN0K6HrvkeQr8i4L7BsXI5QeBhP8ATv8phIpCBDu4AGHGCsVDwaOCtEPIwFe/voVvyiwJUolpCv2Iy8dex6eCnT3JRFaNd8lcxEvIcUetQiw+33y9/owB5oLABgVIU4rcSvTJN8nExW/E14pAijZJJ4bSAq7ABL44fxYCO4FlBJlLbAqQBP6E2kPtvYp5dD5fRfJDDoebTolJCUdoCb2CDHw7gpQGcb/ohcNJDwBig4RDuHyrhBCHG73ogchIEv86/PkDn8E7/I/83b6avw3+uAGGxMNCrb9hfWw4bjfpfd6/owEdR0pGLL+R/Hf2JPFQcyD2vjcBOnqDbESYPw5/Vj11dAdzB7c89qq6LT+Xv3v+DoI+AGV7v7cd97TAo4QIPs98k/ydNykz5vb++0yBYMYmhL2DgIXVA28/QL44e0Q6cr/2gvmA3sE8ghMArb4OfYG6JXRL+EDA6X/CwIwCtwFRhHwDJX69fc5/88AgAAsBrcItwpGCRcDkf4U+MbxCu0K6EP09AdR9zvqiAHz+hbZIOPkA/QJOgrBENELDP5c60XVANfX2qjaVAHZGGL9AAHkF7r3QdJO0jnVstTn4SXo3+Pn8KH2wONo4xDrAO9c+A8CDPpB5O3iJ9UrwXfPqN4I2C/i2f2mB8j0f+RF4SHZPcy0y/7fk/Gr/wsIyQZ/Ay38+OOb0ATorAQPAGcEphFGBpX1Hu+m5YPtRABm+ZABphJ9Dq0FBQgwDkgN9g1OE64cSCCQI5gjBBdKHaQhFwddD7Ix5C2BJ4Mw9CUrH1IfZwPt7UoHMheWE9kuXELuNoc1uDO0HhMCUvBXApoLzwHiI9VCnCl5JiUqqAnE/zgX3yDwHqwpfyzXH+wIk/A38ccU+COmHegluSlnIUwhUB+Z/9Plk/B3EBcZuweYG540Cxs2B2j9TN1W4RD/RAUEEtkhFR3sFAcTo/7r6Vr8sQrJEB0pSijiFSshSCtAENP2Je0C+OIJKfh88Y4Mfwm9Aa0Hk/LT7l0GVgbkANkZUh9pDgAI4f+l8mD6PhC1AdoCqCWzGbEAtw0LBrLgGMlIzwTgO+AI5NMBMA1lDVITUgdL/jn34fUrBUQKnAEZB0gDRenG08varuuu7Wb0hgVfCBUFqAXM9ZvqZupU7ogDQgl6/1sEKvxw+cD19d4E1uXrhgaqBfoCGwlrA1r18e6F4hTifPQz/GMIUhFKAvP+QgON8zfgd9n36g791P0dCIYFbuwS8Nfzstli1KPri/nr+NXsaOWi3yfWYs5QwFrZWPz987rxbQVD/S/dO9DRzcDJXMoC1EneR/X6CfnuJduB5a7ZI8hWxuXCI8vN4YPjCuST6xjbdctS2WroId6q6IYEWAmkDH8LuP2d8VLdk9DC3NPen+hVAVIA7/C47tHxeeqP6U3/phrkKKYlnB+zGtMCg+Yi5Hz2f/phA8UgySkdGTwK7geMCh0A0e7b+0ATZSBlKhMjphtpHEIUThl1I3shdyHHGkwkfzP+FFH5QgOoFjoc5hBOGXkp5i7+Kv4biA9pATH4jAIZDvwLKR3BMn0iBBBOCOf42fUCB0AVgRxcJ30n0Rl3EUwIZPAC8V0FwQK9CUgmMy7gGYoWqiA4CEHqFPVQCdwG9gptHa4hExyiHVAXlglYEl8fVBS1FAIb9AKy81jxoN6X54QJIxhzJ+42rjFpKGElUhPQ9nzyAwxaHtsfSiVOHW8RXQ7p/Z3tXPLX+kP8WwawFbsUlgGOAKIEYv/kGIEsZxsRFlwfHQn78zYCzQN49Pv4eRG/Di//ywlW/yj9HwgVAncRdxTQ/67//gJ/5/foqgnx9nDyUhTYB0PrT/Ro6UPg6g+/GHT8mAK3BUPzYu+R4i/SO9XT3z31L/0W5tfsBhQjAmDkbvxZDTX39fuD+2rXd8c71Jfl6eIQ6DwIRgU16SXtbuNqxcXDycpy1fXqHvau+dvq3+In0rC6ZMsU2RTYQfO3Dlb8DOJ11NnDSsNUzaDQstlS4Bjb492w3oPUbNXj2ZvogQNhBa0DvRb2BLThxOEW4efWIOcc9EPkGtlW2e3hQ98r1S/gMfOT+Hz6/gQjF8MjvRfTEp4Qgfov68jzuPY36iT77hPeFa8NfyITLaoTphnVH4oJEQ8+J1QTSga9EmT+Xv1rJMkjnBlUNUw3fR9aIVwg3AqWANkO2xglE+EkzzygLDEUXBZzDg8BbQuOH1goFzHfMDoevRuBGJf8eQA3KdkpBBTyFZoZZxFlEgkY5hFnBXcRiySuIx0ivRr+CnL5rvRxEbgqMRT6FP4v2xTn9gATOCrwGJghfzPwGiMTcR/2DvoEDwYx70jWe9/786rwAvfNFj4mphSJHDkuBxhYD0IQUfGT6HMHsxCf8YPeswSR/cDNAN5F/D/50v2kEYwB6+5i/f33sOmD+Bb7wuNL4Wb4qvjM6+f92g2Z84HhCP4TCLT86gbFADvnj9d/2y/zM/HE5ZgFBwPA47D38gxvBo4A1gAJApAC6AMfAc0DVArS+O/toe6j5iPkMfJSBMMAR/gx8rrwZOF34YgLo/9a4nb78AZN8d/c4fXsAXbeVvTFAqjhP+ki/ef7p/ef+IH0m+kg45HbnsrBvLDCMcp91Iftj+uN4l7sEO+d6vXcJvmFD2TqGuW68mLeNcPwzDfVasYh0DXkzuwk8rr7O/Xf6mj7Ofz87mrzS+3f41be+tbh1y/mQ/qCAJv/ofj5/cb1quDd+vACR9sY5GcG9/Zk8WcZqhpc/jwAdO9H8VQJ1wiDIEAxCCK3HJgWoAumDrcWaxKMA/7vHOog+8j3mfHmC6YXNAvoFdcywSi9Ensn3S2KGHMTgyroM8EntCrqFbj7iBNfIH8UcSkhOCciWxGQFnEOGQV9GWUi7BGoA6v/mApWCjIO/CbNPFA5iyiRO+w2Vg6/FDEp9hj4Cs8OABVICtoITgatBVwfXxvNIEg6dTLwGm8eHya1G7Ub7iOqHYgNyv9jCDYN7gGzDd0cLRqB/0AEdy0nI5v/VBGHGywGbweQG8UXl/8A9NXm8+i9CBkfgR01Irkh7Azr95gBsQyiDcMQMAjf91zloNnZ6TIBngdnEo4JTeab3Iv5yvKJ8aogBCMHCBkRxRpQC4oDEwAK4Q7QcOz19sr2xRLVIqQQhAzZG64SAQVzCfv+kep66+37p/8jAisYVhDl+9oAcQXp9qXul/xH8DnbNeCJ5THh0es//j3+BwSsCXD4xu5s98D7L/G09W8SNgox8iD6BO05yMC/6851zYG8qMjE3M3OTMDr3qf4Dugp7gjzst302rDh/N+g2x7iO9gQys/Ul9fK22DmJe0a4WzIndtH6TnaCu0M+TXf8dZB40zYw8aL1AbnM9/40y3eJOnz4bLo6/Cn+E4CLfQU+28CO/LC4wTgJ+Lvz5vR2fpGBt4BtRBvCwLxQ+bv9/4F8gcADYgSWQT84WzbBvTj9FT6NA5tCwAAdwJH/4vwsvs4CcsS9CQnLYEhjBBc/8Dz0e2s+eoNNBojJk4n0yWzG3sMVgp3Bj/46fGX+z/+ruwt+wcXXx1SJM0pUi+eKdEhjh+gDpAXMR/2EYsiXCeKH10ZpBRADcz0VPhnCv4G9AVrDLkdlh3kIT0/KzolJk4lzxvZ+SvmEQCKFbsVfxKaBFYCXQPcFbsjvyFSItcQpAXJEMceShQyD6AapAIA7AEDigC074gISiKDCf3+Xx5fHwIWdRvDHlgQuP7V/DX9JPrf9CL8IwS26g7q4gi7DZYR3hnoDNwAWxB7EJAIuyc2IP33twgpGbMILQ8MKpgiDxIPIPgf2Q7VEX0REwJH/3kIMgppBWb90PWoAeAQPhOsGAgdERa5CzAEmftH/wYXYxe1B1QIVPZa02DYofJY8OX6DyFvFmsBHxcZFxEAWvmP/KHx7eLb3crcpttB12/KWsQEva7E+Np32nDgrO7r5uXdN+7O/jP+RgBJ/pHiM8wGwrTBRMrhz8Dg6/K+4JHVVuwK6QbowPPj48vUXNNUw3+/39FK0vjWCvIY98Lm896i4M3ey9dB6y39i/9m/y/6sPpm5YnOVtuD5Hfal+Ww/FkBHvhy/qv/N/Gy9n75Jvtk/CnwzOSd4hDpKenl+TYW2Rn+DU4BNgl+/3Dq/gGcENMCmARIF5YKnemm73327enK8ykO/BnRCR8LQi0ZLeYmXDO9KOgdQh0NC2jskfNL/InkTe3f/on2Ev5nIGIsvx/wLC82LywpJxcuETYKH5IR1xjyAK7zGw7yEKgLAihiMIodMyH2Ih0YOCGoJb0gcSVSGbkTmigZKOQVVBGkAqH0dxDFGNUJMSHqJ3MI6/2FE6oguwSCBlgawO3P1Xz3KQU0ARMduDYzLyUpOCpnH2kNgf6F9aHpCuke8yfzn/2EDRcKIPqb/AkKHPME6B0LVgq++wsQsCfwISUQ9BWsEIfuZOSeBQQUAA59GzomuR6YG7UavxAlC4oNtwgY+8L0xPHE6HTsHvvz+9ED9Bq9IOgUjhn2IKoPZv5GD7QoVBTgA/gQ6gAY4wjbReVk4zvVCuzmAhr4sP30CmcJlgUe/lz2herV3MvTgdTh1JPT/Nrz2zfkpesA3NnmWPuu4HfP+OMz47rB48+N49u9lrOmylrYQdxs5cjv3e8x6FjgK9tS2DPe1eOB2nPSz9XEzMfReehk4QDOCs0U2C3RNc4M7ST0xuuYA6ARHPdH5qj10+3J2ALcXOS88I/suOLQ8CcFEQ3PAqYIsRGR+KbtVu0E2tXS7eAK+EgEGwHI/hEPXwS26+oAPAvS/SkQMS5xIV0K0RsdHgj+GutQ4b7oEPA17CsCnhgPHeYgzyemLQgqAiU8Hy8VggGZ7VTymf57AiMGeRNYGncHxRHqJccRGQgHFQkRP/sJCwwsJSjPIisdZQ/qEMsWax+HK5IxCi+aLIcxczAfJ+wkySLeGNUGcPwRCKoIDPuzAqofnBTn+OAcjzRIIOgmyy9aIloWyx0dI1gQMBBKFwcEIPrPBLMPxxDPFNUUgQW1DhcbBwkjAGcJ9gjO+VH9YwZY9bTmzvKmBxj4IvBjEV4b0w4wCscTFRm9DSUXXh+UAgbwofP43p7SJPf8CvAMZyYRJ7cWESGqKcsYRBKkGJoJJvsK97z+bwHI+tUJSBAq/+IDtRLl/CLzmAyMErUCNgeyGlodUBD6CU4BXOEn12TznACh/aQSgR76CvYKGRARAuABCwTK9fXiJ9FgyUTKTtdw6ZvsTuMQ8ysCn+JW2WzmCtgGyYnTbOsr98j3nfbO6x7hxNUzxNu/i8cQzlDO9Nkr6Z/o/uz38xrpCN8I12bNUtJk1svSstA/0BzWk+6Z9Eni3eXK7H3oj+cI55HaP8511Nvbh9OFzuHdHu8Q9y/77AJjAbEFvxp7ELb+GwQfAVjypex45xjXvOAv9Mrqe9xy5KbutOan97MQ3g9rCQAAww4VIT4cCh8wEyv7OfST68TzlA1tEjEU9CK/JpIXGQ7qG9kjcQxB9aPzJPdH/SsM1RuSJy0n7CUCIF0GXPzNC8EPeQb0DbIaCCblOLY51y32KN0bbQhR++4CXQcQ/1IVazEvMhMyJ0AlPGssUi69JdMFKPe9A2EJIQQZEr0svSwpKHc1jTXfJFAVXxDPFpYc7hCtAckSHx/kDY4LAiDJIG0UrCI4KXsbhRLTHokkbxHwFlAXifWN6sj9qwNB+9fyZPjt/sTmZu3eHIcomgp6/ZYV9iXfJochIxBIArT+Texk36X00v+OCqgjdRpGB28QVh/dGtMKQgr5/0ftGvIbBg0W5AsrBccUkBMZBfAA9/mB9eHv3+3LBDgQdRACGzobNBQ2EKgFAvf+94fvl+C06G70XwDqEzgXWQIz/V0FT/6R7hLf9d263wzIjc8U74vr1erQ8tDsoN5I06LbpOYA5dnkEOON3SvRVsfNx1bXO+lO5IHjnfAi60fsAABY8Q7Q9NHl4eHans8lyUrEkcE/xlbSy81izOXdHuyl7xzhI81o0iXj0+7Z/uwIwv345YHk0OwC5SvWy84x4xbp2+BY870IgQde9lrvl+6F6lLqFPJq/oAA9/og7ZXbL9tg4qPrIvBY7LD1mgZ3ChcI1Q9eHrUT+f+1A77/svAG8eX9OfuJ9A8JBh6uINcWsw67CYH8PftY+lrxT/cVBk4OCRIwDhMFmgz+G+IJme/t/BMbbyNvFm0bzRy7EjIZhhOEAREAmBDZG6YXbRmwJ5wsYSVYIg8mLyGOGy8UZwc8DWMLoAWaEV0arhsNE/ocZyaWBjv2AA0dHUASRh5cQ7Q30RqmGIIE0+2F/F0S1w3DAxcRzx8EHX0U5iLXLPgWaRaBGtwEav/NDpASVwJ88+fm6+lMBHsHBPq0+DQCeQOl/8Mb3TM3JvQb7BsXCnbsTfSkCk36swLXHTgVmAV9ESsf0RJhGd0jaRYEEVINKwSGDMUZfxcnDf4NSgoi+kQAyxP6EssIExjgIb8R1Q/yEisKIQltDYMVVBCeB0QYKRsED5YPDxHLBwUByQJB/DP2mfOf6azkYN5o6E3yheaw8Cn6rt2kz2zmz+B03b77UgSf/WL7L/ZN6aDIi7q8yKTCfcyh4HnREM0r6bD+GOrR0lbYnNHJyLbKN8zC0eXUTs+6wUjHzdXPx6DDNd3442LN5dEz7mD1tvtZAi3zieFu1xTMLckzzErP+NU13Hfci+MS89f2UfRP9Zn1ffDf43TdcuMn5ovhrOVP+i/39t4r5NX5Sfcv9m8FNABu/mkPOhfmBVH6IwnRCy31Vuqy9D/92AnsEOgSbQ9pA7MNRA/z+hL4rP4XBsMVFQ8x7pILDC2Z/Z/o8f7z9mj0iBb0ILUacywdMI4VrQRvBaAToBw0GCMTkgZ4/v4E5BpGLCcwyyp3JKwiVBcsAYYGdSNxKYQOBQgvGCj9bPo2HCMUBPkjDkorbyFCKcs/gTTdIFwlLxiD9DXywwgfCvYMNBLPEDgn8DmmNMkxoC65JS8VFv7x8VcF9hHmBEQRMAff6dL+pAhk7crw1xCHHZYVEyNxNPQrDC0dNaggUAagBxkJdQZpCDf/HQVMHZIeDRXgFqoTaxBMFAUGPAKKCbzrAO59G7kMuvqoIuIeXPzx/WcLswknBnUf2TWwIskUyyN5GaH9Ufxo/0H8fP2L9ccBvxy5JI4YgxG5DtEAQ/Mt8m0Mywu66ivtAvrN2sLPavBR/3L3o+3Z5/PhPe4+BwkKg/jj89X2qN4WxDnP+tkx1Zvd2d382Qbjj/Im/hT/XPYC5ofed+JN5dXVusAQ1FDh68IhvVDPhduuz2DBd8iRyyPcEvgyAoEFS/0E5tfXus3hx1TDuMgA0xTYvObx+cD9vu8Q8CfwJ9w51HfiP/AA57DeEOzn3wzj6AHh77bUN9rx4fTVRdM77LcCBRJ9FoEIZQdSCCD/zvbO6YngPeA98h0LpBS7DAsQkB/mD/f97glQEOgPxRCB/TXj5eF09xcFHwf4FUwdpAeiBLIX0xAbDrsp6CjgCr0TyRdY8ybzSg3K+i314B5YLAopZjZMQDUu6h/ZHTwMfw76H8Ui9iHXF4/+Jv6eACv22/0ZDxsZDyTmLLAtYkC4Rbo1dy+mJLUQNA6iGnMbfwAS+SMash+vDsMhBj3ZKE4dlig6DD31dwm/FbELBQpeHLkk4iDNGzYKtvLV6+X5MgRnDDUiMzZUNqwmEx+QFCsBGQRD/QbxcQHDEB8PlhQnJlQf/gyoEWsS+g5QEEgQXQ62/WT1svco/5IPKRMuCxMIhgppDawOSBBQHegelA+/D7UOgfYx8tUCZPHt6EACmf1y6+ILHS3yGPgKpheDD7MAEwBm/ZnzP+B/2BDf4+PE8XD9xvU96/PqMe5F5sjp4gCgEIMMdPhq7Ovcm9a61jnCz8vX5bjlOeE59NECUucp4MTuidfbx4vadPKs7VbYFNnG03fQP9JUxQy8/Lt9yMjVTNeX4pn0IPn39hruNdi82TPs/NFvvpXZd+A50gzl3gT9+3nmaPGu717XxtVq5U7e68jPz7TZUN6k6RT0VPkC6xDX79Va3gzgYu3VCeYVRgGy+HL6n+4c6brcbOAt8lrxEPvPHWcsCBpMEmUYyxOoCV8BigjRCqP1N+0e7SffI95R9r0FSAX8DJQOAApzIe4roCGwLFQvhxlGEvYb8gwY/+gU6g++9foEtyINKbYklClAJd0c+hdfEbsOigU8CuQhAicZFUYRiR5lFQ8G0QUFAGENXCN5IfQoljtkNLcgFyakKooT6/2eB6wM2fuMCbsqKzMzJ+AikiBhGbESZRHeGYYOjg0LHUgQUAQPD30S8gDS+V75dPeSARsN+hK0IsUpIQvd/CULKQDG7Kr5KQff+xbzyQGvCrUQ0zFSNu4bihveGicIBQT5/tfy4e4e8y3+WQaWDncW0RFjAdD93f1zAjQTACGHJ6YbwxJSD/3+vPZdA9wDtQGvDwIV6A/PFUQe7hSoDaQMfwhbCLMJBQj+BMz8PfAi6o31qfyh9dHte+9c8IXsbu0c7PH83Au1Bw8Gbva+4S3lgeFQyhTHrNnV5azrFvbI/G7wdOVS7ybz4+Ir1H3Sl9U33q7V/MM10HbiO9S6uVS508QrylTV5eND8UvtyOPx6fzVqsJq2rTcUsXwyd3andjp377+mgYn867nl95o1ArXO9PZw8fIbt241J7UqvPI/7r/IQk6BVLssugv/Lz/UAfoEYwFeQDl9NHl+eqb7gjzHP6mBGz96fqgA+P2bvAc/177WP9GDsMJ3/7oBW0Wew1zBJ4JAhTFHQIeqiS3G54J1QlWEYoX6h8IKcMnxyDqHpwOi/md+un/MhFQJF4mSCRQHNciWBtQBgAMvxfsJPIuyzC0L7owHytpHGkHJe2T/kAl0SF1LcVDRi7DGx0ggRLcD9craSOBExEm3R2kEGccbx32LZFBOzX4K9MuQhu1AMEA7gCJ+voJ8BxlLZwvJSHsH6oa8gy9BFsGhg/qI54zmB5rEJYN5++P6/AAvP5y/QIVKxukBZH95e6J4r8AFxR9CZ38yPiy++vy+uta6xjy+/G69Q8AwvBL7sL1S+V05UP0m++N6f//MRr2Fc0UOBAo+GDugflpBmEFIPgn64/qwvFc9qYHyxa5B8UE6gyYArr8Rf+T++/7VgsjAvHmIuuu8OvySAt/EQMMrBBYCen5XPMo+en7m/c98PvxhgXiELUQmA82DkYFT/KB4b7Pc8cx0BTb4+OH4UfUfdk35pH0yPoY7GrrbPSm6/TYFNwl5hzfst4x3ZXQfdDJ0P7X4d0e1rDRGM+HzoPQndwt2kzRO+bZ6T3P787812jbzvFVAMzwuOPV7o3xsODv0W7ICM/825nhxN9H3srx8gZYDlAIwvLV4vPsuv8M/pHv2fGvAtMK5f5R9Ab8jAGcCgIT2Abl8m72lgy5BMjnuuvBAewJRBT0IYkm7CTjM6It/gDr8DYJhSL+GQUKvwIk+wAABQl/CWz+Kw9vK1QgOiBeME4osip1OE4rWBHLElApqiQXHd0q7DETJlYTxQNL9Pn6fQzkGTMoTByWBKIA2ANID0gY9iHlOB1AuzJSJgofLRnsHZAdKRFP/3rxXQMhHAIWhAy5EgAZiyvTPnEyphqkDhUHSf/uAPYErwWOEFIUAhj6FqQPBh1vJEIlFR/uDNwCLQ1OF+YK5ApbDBcCHQYr/2DrruV/6BLwxvxjFgokvyNKKs8olCjdGJQCngaeEjEU/AhU9Vz0CwHf89nhXuxT+Xj6mBMzHAUI7AF67yffrN19107Y2/ArFA8e2Qwg+EvjyOKqBLMbyww3/4D+wPSZ7SvnMfBpAOHrst8K7d3ff92D/VARk/+F6gDpO9vVzRDRJ+ay/Df4h+WP3l7fL92P2cziXu4c6A7RBtAt+B0IfPgg40zNos+P37jltulP9QkOjAzx7uPUyc224cDdyNaq4SPhouKL7e4DYPH80QDRicm8z5fm5fpa+y35XOcM1LLmTf7+BCkEm/0c/6r90dohyTXYFuM74a7Wi+IM9BT57/4p36zlRhCOBWTsPfdjBRb8K/aq78j7VgoFCcUKNgVQ6dnXN+dEAc8W1wyk25PHAt0Y4wjWi+l7AxcP5CTHGaoCiBWiNVArJxOCAHz5zQrTGckY+AZY61zkSeY/4U/vsBRYH/wMKQFN8WENOS0tH/ou8iPwBn8cqCWvC273ShMW+Hvu8DEhMbcUOi4IPs8bRg52+hbg9+u7A64TVhmFFrko4znJJXknBDmDIH8fBDYbLy0k4iBaKi0XrAeaBxTxBO75/YMa+CmHHmcSDwW4/z4DqBLfH9Mk6jFeM+YnbyfTKmspPin0IW0M1gCKAYMKrCyDKVgP3BGX9bjSyuqEAZH52xf+J0wHqA1jI3kKWhKkMQ8cZRC3G5wWnA1fEQ0NePtc7SvbdNsY7InuUfxa/Nnv0Po2CxkKng0nGOIMTg/oBFb5+ApGBhL6fQX+ByT2UvE39a7tjfDZ/enxedsv3j35eO6m16n6L+oM0yj30P3DAzANyQhAC+QODxALCqf7evyN/tfx/uX84NXZpt205szkMfjn/NPvif5R+QDgS/IXGnkBtPQHBCTyYP8M/ATqP/II5AbeZuJ7y4PXVvz0BqABCP8k9MjeaNqF4BbbDN8O9fX5AwOqDDAEzPlm+y3oRexADD/upuXYCMr4bNeu3/re4dG863vw5e10+OXY8tSP9u303gPFHo4HWxKwJxUMZPkuAwsCqOTR5I/vXt+H1/7vk/zz8M0HXv7v394BGwy+87sFbQ8a9M73fP6vA9UYexQNEn8LrPxjALMKFQuOBJgF5/Df1jHW5+Gq7YYH1R88HZAQ+ATkAN4FCB5rJAsKtP8AIMEaswq1GUwReQ3+BOvwk+7LCQUKP/UC83D1/PKs+ccTIyDVHa4YcxQVBbzq1ebv+KoC8B3hLrccMhPPEjgXACCoFF0DGP9q9TX1/uyUBXEc6/g96onv/Nle5HMFP/yh/SEWog05+OwZRCPz+/oBgQVi2LDk2/7I7FP86iZKEN/3bQqB/gr1xQZlDlj3+gGs9fXqlAn2AmT5QBKmCarx7f/S9fv5Awf9/dv5U/p3F3UcMgSqDscNgfLj/A8EaOo77tUMIPx89MMYqhW1AbUJOh+5EoP9/gOmC9fvf/dGEUPzOfANE5Prbs7LCq0FkfLJF0AmohjwBJ/21+fG2GDfJ+pi+rQdli5cHIgZXh3iDdgB+/jX+jANMghvA3kdrg0JAw8U0PEz2zH+n/Bi30AYTiwfDQr3AgpII6YGQftjGJoFWOcFAWMKTule9iMSAwTkA1oiLyjV/Hj8njI8F/zUcPukA7bVJvxaHzgE6+kE87j659Wox0P15+722i0R6ic9+Vbt3gq89QDMoekCCR7sGvPsGjAQCve7GtUN0O+DFIgUlB93HAsJKxc6C6PnAvUzHpYV9gjeEYYP9gdfDd4IMAxlIH0gABYRGT4aHQVg7VH2kgeT/uwO8iL6FRsZVho+AwrzPgHC/27xNAFm/5Xw5fRs933aYNUO96fy4dx/5I3/IPAf0+3y7fwA8eIA8/rl7y/rRdrt0ZXept/p3+Hzau0x5UgAHvtc+KYXQgSR7jn4tO858dcKNgiT8vH/phMm88Lm8BHsHikJbw7hI0YTMgZnFuoYoAhXA9T5DvWSCnMUyRZzG7cclhuyFgsKogrmFp4VGQyqCl8Go/H3+AD4N/59G2kL3ehL8NMFwuvb37bxVPCy/ycMfPtQA1QHut3006z7hfcx6TACNAAY2H/OkdLC0UrZeORw6yDiaN2q6yn4m9vL1i/6kesOyCfm+gV09EPko/OCBY3vsvCGCyL+ZvMm+GbXBMlg4/zfHuCkAykO8/sCCK4NTADsB8L5suEx3efbHO7O+Z/s1xH6Kij+jetN61H3WQG28BcEYx00EdsWCyHLCVsBKQ4S/7jz2xGuEOwBYRP4GYgAbPJAAw8HERvjNMEpZRpcIr8WyPtD/xcdzTHgGowSHSF3HhULigpOIR8d5BPuJFwktQxpEA0VWvxD+qAbbxixDKIlIzRgLbssgSwCJdMi+Bt1FBUcXCXZHMcSxRi5I0QZ4A4dFogVvQ2vB1QBGwTqBbT+exJIIR0QFxDRF/wAVvoyB7j1JPPeD88c5g/2E9wOcPJxBl8PN+KD8DIY0+nt04EP8BFs277jwOmTz3vWIdYl3QT78ABW+fP/0vOD3Grndu3d0ZPPKeT61C3RJO1J/rDyFut27u/gWN6ay/DMCu+w1+61/sqN6DPpYOCf7dXybNgSxDO/g8st1cDQrOG6+e/oytuL88jqdNs79yby1dTT3jfwyPRi86bqXuuL4tfJFsw593EPifF25dDysOj6zf7TRfau/CDjOc53zVTVatxL5PPsGPtU73vXS+Oy5PzZz9zR4XvgO+kBATYS/gC5BLclg/+o077syPwv79PzPA8bJR0Up/wTA6wF4//TCoH3xO/BCWcDrv4bGkAtzR1/IFYwvR0AFH8ySjJtHGMq0zrJJjofUj/CSAY3wThCSFZBBDoGPW86gT2HPVQ1izSTPY04tyJCGaYUGw2KEAQuHT+9NXMu4SxWK7AcohkMLy8sBBfuKHc5DCmJJ/44UieKDVsO9hMdCML3jA9MKyUOPfIdBogUTiKgLJgaAwsi/bjv9/gyDc8o0SxUEm0Q/ApY4czuWhEjAaoFFyHqEscAbR7hJdX7tO4wEtoJPfFYEJQlyROYDHEPCvgg8UQOXwb8ASEP8/pB7t31ZP4rCj4PT/1e89/xK92N6K4SYwGD6MsA0/Ve2QcDjBGd40XrxQzL3FC52+UK8lP5BQwC+wD1Wvg72cLKldpu1J7J19PR1OXhS//E9Y3mGvM33uW9ctLx6Azh9Nps6OHrsujM6/HjzdUS3dD0Qe2b4NfiTuU58UPi49u1ATABh+CL4WLsh9d7y+/dwt2D3IQEVBEE9g73bvKm0fHQifAm8EfnCwBw+qX4DRMt9Xbgj/p0+fzqevKd/ogPvQrx8t3/FwOD6xDwFO/r9Hb/gewC8SLw198XBFodYQSMDVYOz+ME5A0FevMY6UQFwwh1D3L6XPJUFp4LHPan82rz5/j6FYob0xWWJ8MYUgDb6cr5GQnM6jQC9Bhe/VsJpi8+G3UMazO0Id3rUAoxJEn2jgSHLHEiWwdUBg0MzxKcLg8fAwMLHBEnqgugGMMt5iOeIWMZFwmZ/vPlle1vCrEQSBZWJ8EiVhLTHUQWKPZN6bT+ifmJ96gmbS5jFpYSVAFJ/egYCxCq8w0IySX2E4QD1Qo6CsL/fPSeA4wevwN24crvYPcO7azxzQ/RHVsQwyMIKxsCgfBUA+/0yu+OFZ4hrA2u+Jf5mBXRKGsMFP1hDdkNyQxOCIMT3yPcBFj5rQQc/nbygAHuDcEOvx1/Fmsh/CcJGooeIR6UEdcOUAxODwcQSg2aGFYU7gfDBgIVAhHE/msNShCh/tDzmf2IGtkRRAN9EJoIVOzZ5k3pR9+86670RfI8BEH4duGD9IfyEtcG7nb0m87C4Kr2Buzl5yvcYuS07lzmAOga/U4XvPw92M7wgP+B6t3uHQPI63LWI+Avx6a/O+ka7PzoVhHoCqHxgfst9ZXb5elY8YnTP/OFF70FLQiyH28VuQYuDMsKuwIXBXUFZQF7C80MKP3x/GUFWv7S+RL8TeW03Svyo+VW6NwS+hpQA9wLPhIv74PhGurv3+vphgWp/FrctOPU/N3rNdjj+BMJy9uh4gUIKes10hbwm+eNxsDG0cJBwS/JHOCB8G7jjeGN9SLqR+LO9nDiJ89Y4QLpduml80QGAvcC7ewS3/0W0UX5OhlP9ufs4gbE8sTaHv1SD0YN+gyUBTf41+U16tf/vvyy+2se/CR5DjIPhhAt8UflYPaq9xr7Og51Cdvq8gy6MCsCVgWYMsEZXP2KHa4dKgCOAOgC7AU7/10JNhMi7i3Y6fPj+3brawU3Mg4xDRi/GLMWtuzd21H4l/zO/OYWyQwg70IOWBbX9SkVFz2eHV0PqCYjIDIPGRBMHH0XogMpDe4S4fyy++oPPBGf+04JjCO0HjQP1SyqPJwWUgcbCzQNjAjiDc8bBB19JcEsUhkNIUw43SKcEDMkiR2GDH8XgR06GocfbSeiEVr33/EU9HUHZRi/Hm8reSQHF0YYuxEp+GrlVu8v+GDwFQOQEvINwy2yOGUbKR+wIWD/0PLiBCMEUuz6ApISePLuBycmJv8Y6XT0Utyo4ssLcwjXB2ciUBUNCEwS6f9w4MzmN/n56y3r4fhs9SnvO/Fq/scIAAUfCpoL7gc6AYQDlgUI8H/x/gWh9fPcT/U/86Dacu7Z/1jyU/0jF1T2Oe0Q+5XrWtnP2DHs0e6P9QMDiAb1+rbxm/itCN//KPzTAxbpqOxJ/o/pg94nAxUTbOhY5uf27cpCxEXpFOrE5QIHgw4g8fIEWQhy4TnV3dRmy67IFt0g8oEEbw3sB+4MywRg67TrN+0i6tX8TfBQ2nDnjfiL9kfrJ+sO79vrjeQ/7s8N1RFdCAcVOhHj+6z2Q/An3uvvcPcC4rDxFQL99DX1BxdrHqYCfRTbIoEEbQMTEzX+p/fiEtcVrvyh9lkHYwLv7dnxbQTp9xLs0Rg1KDX+CQs4GR7ozdwuAcToedZP+nkFP/pMCVIosQ6eCYstnBMU9z4NggO+75332gjgG6oPuv7BDYP/WtQr7M8GJ/MuCO4sLxEm/tUM0/jP1wjfevjE9oQHcyQPJAImAi6HJtMb5BQrBN359hdtKugPFQUdCWENCyAlHQsVHR3kBPXlT/fRDv4JKx/uMsEeoBzJJNgKIOyj9Qj/suqh+20KOfDBCdseww62JjUpoAQsAvIcjiHNDLj+qvqb8T/rfen1+uQNQfId0oPqXvg52ovpvwlIABzzPf1/+b7kCN9Y81rtM+cW92r3Fv9H+ZgIlhc0CdT7CPmj+Kf67+wW7JgRjgvQ+JgHnA7v9tXj+Ndg4Uf4CPU8Bq4fcwuIATwSZQjv55/ZofH78gLwngPeCIUTQBsZC3cNuRmKAgT5/A1B+D/fKP6WDYP+mAELE2saHwzM+aHxxOurAFgMfv+3CSEJtOoi5znmDs5gzu/c1eBo56r14/Lt9XsAJQRrA+f8Wvle/+QKqf908AT9nAOu79/udwHFAxTyBOUz0OvLR+Tx4GDoPBVnHxEDgQY+DrTooN7+A6Hxe+C5BNURSgkEGEwoTBtjDTwZiRxdB28CMf75+iMJtxnwDqAQmB+/Fs8KUgjkFE4JBP7uCkAjwSToFKAWRBIz+7r1jhUHDl8AWhjuHqwcDyBnEcj4TfII/SELuw2DCtEEHwP2FcMUrgrgGfP8DOgjAJ/u/flMGHb/IwB3IVwV6fl/Aznwk8hg2k3wwtsC6RcGHPXP6uoWpCmzAan+aQroBssNFwIQ820DPgMi59HoCwwHDxDp+freB27xrQD1/7r11P9tGM0WmgB/BqQEk+JH3GMA/ABR8e/6NAFtCgwm9iisEpQVvRP1/aH22f0ACEoGQ/tD+ZwO4hN090vvmeX81YvhHuoc7BEEMR2KFvARIRSy+kzSGNps9V7pk+xi/yT3uPzyDmb+1/rVDR0LAPgI9NL6JO+V3H/Z9+jBCHb+HPBzDGMAVuWo8cr3/u00AZAEJO2F+b8Gxujr1wrfUO33+ZwA+AfuDkATPAlH93/yvv/v94/4ABiwGg8F5/3C+b8OxQYI6fv+GQAa34vpUgm8/YQD2yYpF03/XwxF+ajaJ+Xd62Taj+Zk+dEAex1WK14etxV7GEoOwv9a+nEEcxDf9bzofQpjEj/rz+vXEF779tAr4/X8dvBi9EYU2Rv//28EZxI58wTdKfY571zR4+8CDLkQPB9CEpgC+BvDJQMIcvv8HvQkLfVJ+vQsbRvZ8QEFLgtS5PPaJvkLC6gG3hEvJzgcHwzbHVAkUgKj8OoMWxEx/dMRoB2UE5Afbw7+8SUSwyZ/CWENISYBA4/d+fM4ERkd8hdbDnEV8grx6jnoEQVq/kX8niyWJTIFsBSYBu/Zttge6JfZxtjr70f4BwyoGaX9JO19Ah709+j2G20WduIU5tP44e/56wr/5/755/re5866zb7kaO+6/YwQAgep+Aj5n905w4PZVuvt3Fbkm/5CA8kDzQUpDPocbRO4/zIS6BwuAXL8QBdlFJYC5AziEoEDlfrd7+ndtu9i9r7v3g4RJHMWhxgrItL+xt4i7eX61ep8+r0ZbxQg/AjwQg/mFwTmtPeoKogEVONW/McDRfEx/ScFrOp93ufgiddH4Y36cPAx80ISXQFY4pH2jfaJ0hDbsPFW0kHO5/VN83D50wg4BKQUcwrR6bD51Q077rTcYPWzAwUCxwTgE2cLdPV2/tX7+uSAAkohXRX8HlQrayBvHZQbR/jv8owTL/wl4jYBFRbBCtoD6CchQQcR0wTVMWMoiAQAE4Uoohg+Dokh0SEfCDv+Q/0t6Nve4fxjCQsB4htCLBERnAUbDKr6uPGaBuv3Q/G7AT3uieYQ/hUU0wTG8zoS9BOs8Sn0evuL+JYDFQ4tD1cApfHf9Fromcop29/7WvOB/9EkUBfd/wUQjgXV49Pxj/4K5k33kA/JA6ANJyVpEAj55heuJOINNgR1CI36vOU38MUE5gT4AzQQhg5N+2ThqO25CdoCfQ5IJsMXmgqiFzgJ5fu08mbdtvKH/mjq1/NnC7EOjfn+7fwK7BbcARsLTCBhBd/2YQ6GB2T8Bvu67Uvox87Zwznm7efV4hEHFxgq/If8DQgO7KzajdGDyifS2de830X26guZ+0fjDvK5CpwF/feT/uP9EO+o8V72g/oTBY31f+iu8X/b29NJ99/ysuU2BN4KlerV+sMYEwly9z/y7fd2+ZP2lAdQHuQiwxJdD5gfvxdACR0SgxWD/932bQbDBOYJiha/A935XPxF7w79nhxEE/gQiy0dIR8JeRgVEkv5NfF779D1GOef4uf7BQy1CQUA+AmwFdsTnhW7FeoREwraBewKzwsTFM8YwQLO9AbyAt7n4VT7bvQRACMsXCNOEGcjwxjl+6Xy0fGD9+nx6+2l+Jn/fQZUCgATCiKcI3MZzRrLGowHZwf4E3sNPhl9H5P+FP6gBKjf1eFMAYP5yQMjIkoQAgeSGh8DNdpS2k/vKebM610LoAh/+y/63fY6AMMTFQ20//YCuvaT4CfavNnV5hb73epF4H78EPDZ1rTxAPZY4wkBVhQk+JX9vQlQ5vjQ1d8O5ifXsuN8+zf7XwWzDQkHWg8LGfIQxRKWG88UFRAEDmkP5BYuDKP4DPojBYXx8+Ya/g8DrQcRKrAyWCLoKr0p8BGrAK0HDwCb7aX/awohBoMKdQttE8cYWBbHE/gJ/AtrDzYA6f/FFToTeQxzCrL8Lfq06e3aWPHv+u3yZQYRGG8KrATRCNX2cudF6y/r9eDR4vXurverAkoTsxfdF5AiOhRzA9D8HOYE4SL/xw2iFOAgAwwpB2ES8/149UoR0xDFBI4Y/CC5E9MOwxT4D3sK1QUG/az0zP4nBx0FWxCzE3sY6CjiKJQjpCxMJ/gRhhBCGR0WnhBlBgj4Teq83vPcJeSF6SD8Fw3JB6ATrCTiFdMIJRHeAbrirtec0qLU9t4I6qz2wPbp7gjyhfOw8N3wCNwlyfzZFOIK32D38f9Y6hLm09wn1RDjydle0uHk8+x56e32/AuKDUgAKgA3/Hvro+fE5ArfqOWo7vHhoNz56Z39LAZbBp/7tOnI7ivz/veeA/YWQhkCDpwKDwy3Bdn36fPr44/eQefR6xT0eQVvDzQGEPi++MD55/nx/nT13+9882bvEOqf/e38EQO5IEQa2AjPBR8FngJ1Bqn80/Sq/Cb5zPB29UvsKd3V3s/eR+WP9lQAP/0m/V8MKQYi+y4JMf/Z+i4Aj+tg71ACBvtjAzQR2grFEwQZ9BLRExESPAklA4YJ1xsIGgIKJRJ1GpoJ8hRIHb0E7AQFBOoBmgAdAw8YfS53Iycfyy9aKRUh5h2mBXLwavAK793/Kw/2FWcY/BhnEqYLTAfcAH0G0QzoD4EOZwbS/8MHNfpW6sr0e+Pf5bkEQ/Ia5bL5fPcx8UAH3BHaC/oJ7fs369XXR9fR3Fzco+c975AD2gIg6l7yGwBB6T3jAvNJ+dX4GPn+7qrioeum5xrfVu7XCa4QlAeIBJIKKxDsFQcPoglnCiMEGwdGAyMFgxZ7FxcQgRY+C1H/DQprDUoEMASMAF8NnBCgAr0gwSL4GR8vlC1CJMsoaykRIAsc4B51GKITUBddE80WWwrG9L8HIv3d/bsk6gk=\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load two clips and mix them\n",
    "_, dat = scipy.io.wavfile.read(\"turn_on_the_office_lights_test_clip.wav\")\n",
    "_, dat_music = scipy.io.wavfile.read(\"fma_sample/000182.wav\")\n",
    "dat[-20*16000:] = (dat[-20*16000:] + dat_music[0:20*16000]*.7)/2 #quick manual mixing\n",
    "\n",
    "ipd.display(ipd.Audio(dat[-16000*6:], rate=16000, normalize=True, autoplay=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "344383c7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:40:23.392725Z",
     "start_time": "2023-02-18T03:40:22.770119Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 394/394 [00:00<00:00, 19051.83it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pre-compute audio features using helper function\n",
    "features = F._get_embeddings(dat)\n",
    "\n",
    "# Get predictions for each window\n",
    "scores = []\n",
    "for i in tqdm(range(0, features.shape[0]-28)): # 28 is the number of timestep frames for this model\n",
    "    window = features[i:i+28][None,]\n",
    "    with torch.no_grad():\n",
    "        scores.append(float(fcn(torch.from_numpy(window)).detach().numpy()))\n",
    "    \n",
    "plt.figure()\n",
    "_ = plt.plot(scores)\n",
    "_ = plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "078a1bc2",
   "metadata": {},
   "source": [
    "The model is now less confidant in it's prediction than before, but the score is still above a default score of 0.5 which confirms that the model at least represents a good starting point."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0367ee93",
   "metadata": {},
   "source": [
    "# Export the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4eb66ce",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-12T20:00:58.877229Z",
     "start_time": "2023-02-12T20:00:58.868037Z"
    }
   },
   "source": [
    "Now that the model is trained and passes basic performance validation tests, it can be exported to ONNX so that it can be used by the openWakeWord inference engine. With Torch, this process is quite simple."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "75acc3bb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:40:40.474020Z",
     "start_time": "2023-02-18T03:40:40.401258Z"
    }
   },
   "outputs": [],
   "source": [
    "# Export model to ONNX format\n",
    "\n",
    "output_path = \"turn_on_the_office_lights.onnx\"\n",
    "torch.onnx.export(fcn, args=torch.zeros((1, 28, 96)), f=output_path) # the 'args' is the shape of a single example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03bd9f1e",
   "metadata": {},
   "source": [
    "# Evaluate the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c671f55",
   "metadata": {},
   "source": [
    "Let's now load in the ONNX model with openWakeWord, and use that to run some more rigorous testing. First, let's just confirm that the ONNX model works as expected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "295fd55c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:41:08.824352Z",
     "start_time": "2023-02-18T03:41:08.615724Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dscripka/anaconda3/envs/torch_gpu/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:54: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'CPUExecutionProvider'\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Create openWakeWord instance\n",
    "\n",
    "oww = openwakeword.Model(\n",
    "    wakeword_model_paths=[\"turn_on_the_office_lights.onnx\"],\n",
    "    enable_speex_noise_suppression=True,\n",
    "    vad_threshold=0.5\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6f009d79",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:41:13.924834Z",
     "start_time": "2023-02-18T03:41:12.995975Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Do a quick test prediction on the test clip to confirm that the behavior is still as expected\n",
    "\n",
    "scores = oww.predict_clip(\"turn_on_the_office_lights_test_clip.wav\")\n",
    "\n",
    "plt.figure()\n",
    "_ = plt.plot([i[\"turn_on_the_office_lights\"] for i in scores])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d26f14af",
   "metadata": {},
   "source": [
    "Since that looks fine, we can now conduct a more rigorous test to evaluate the false-accept rate in something closer to a production scenario. Specifically, we want the openWakeWord models to respond consistently when a user speaks the target wake word/phrase, but also does not activate even in the presence of many hours of continuous background noise and un-related speech.\n",
    "\n",
    "To test that, we'll use a few clips (for a total of ~ 1 hour) from the [Santa Barbara Corpus of Spoken American English](https://www.linguistics.ucsb.edu/research/santa-barbara-corpus) to produce a more realistic metric for the false-activation rate per hour.\n",
    "\n",
    "The combined clip (already converted to a single-channel, 16khz, 16-bit WAV file) can be downloaded [here](https://f002.backblazeb2.com/file/openwakeword-resources/data/santa_barbara_corpus_test_clip.wav).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "756d7100",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:43:13.392821Z",
     "start_time": "2023-02-18T03:41:57.091857Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Estimate the false-accept rate on realistic test data (will take up to several minutes an a desktop-grade CPU)\n",
    "\n",
    "scores = oww.predict_clip(\"santa_barbara_corpus_test_clip.wav\")\n",
    "\n",
    "plt.figure()\n",
    "_ = plt.plot([i[\"turn_on_the_office_lights\"] for i in scores])\n",
    "_ = plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b9e2f282",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:43:20.326550Z",
     "start_time": "2023-02-18T03:43:20.309552Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False-accept rate per hour: 94.0\n"
     ]
    }
   ],
   "source": [
    "# Calculate the false-accept rate per hour from this result\n",
    "\n",
    "false_accepts = openwakeword.metrics.get_false_positives(\n",
    "    [i[\"turn_on_the_office_lights\"] for i in scores], threshold=0.5\n",
    ")\n",
    "\n",
    "print(f\"False-accept rate per hour: {false_accepts/1}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04d294cf",
   "metadata": {},
   "source": [
    "It looks like the false-accept rate for this model is very high, and would need to be reduced quite significantly to be viable for a production deployment. Of course, this was expected as the model was trained on a very small amount of positive and negative data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c758890a",
   "metadata": {},
   "source": [
    "# Create a User-specific Verifier Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "362c6812",
   "metadata": {},
   "source": [
    "As we saw, the simple model trained on this dataset performs quite well at detecting the presence of the wakeword/phrase, but often activates when it shouldn't, leading to an unnacceptably high false-accept rate.\n",
    "\n",
    "In practice, there are two ways to improve the performance of the model:\n",
    "\n",
    "1) Train on much larger amounts of positive and negative examples. The models released with openWakeWord are often trained on >100,000 positive examples, and over 30,000 hours of negative data.\n",
    "\n",
    "2) Create a user-specific \"verifier\" model based on examples of a specific person speaking the both the wake word/phrase and unrelated speech. The openWakeWord inference engine uses this verifier model to filter out likely false activations by focusing on only known speakers.\n",
    "\n",
    "We'll demonstrate the 2nd option here, as it's a very quick way to significantly improve performance at the cost of making the model far less likely to work well with other voices. The approach behind this verifier model are relatively simple, and are discussed in more detail in the openWakeWord documentation [here](https://github.com/dscripka/openWakeWord/docs/custom_verifier_models.md).\n",
    "\n",
    "For test data, we'll use 20 examples of the wake phrase generated with the [Tortoise](https://github.com/neonbjb/tortoise-tts) TTS model. While this is also synthetic data, it's very high quality and trained on different data than the TTS models used to generate training data. For unrelated speech, an English [phonetic pangram](https://www.liquisearch.com/list_of_pangrams/english_phonetic_pangrams) sentence was generated with the same TTS voice.\n",
    "\n",
    "This example wake phrase clips and reference negative speech (phonetic pangram) are included in the openWakeWord repo (in the `notebooks/training_tutorial_data` directory)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f6b88046",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:45:18.538259Z",
     "start_time": "2023-02-18T03:45:18.525190Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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type=\"audio/x-wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Provide paths to positive and negative speech from the target speaker for training a custom\n",
    "# verifier model\n",
    "\n",
    "reference_clips = [str(i) for i in Path(\"training_tutorial_data/positive/\").glob(\"*.wav\")]\n",
    "negative_clips = [str(i) for i in Path(\"training_tutorial_data/negative/\").glob(\"*.wav\")]\n",
    "\n",
    "# Listen to one of the clips\n",
    "ipd.display(ipd.Audio(reference_clips[0], rate=16000, normalize=True, autoplay=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "937e0df5",
   "metadata": {},
   "source": [
    "Now that we have the data (note that all of the clips *must* be 16 khz, 16-bit PCM WAV files), we can train a custom verifier model. This is simply a scikit-learn logistic regression model, using the same audio features from the normal openWakeWord pre-processor, so it is very fast to train and adds negligble time to the openWakeWord inference engine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7f965293",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:45:57.606472Z",
     "start_time": "2023-02-18T03:45:56.587146Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing positive reference clips: 100%|██████████| 3/3 [00:00<00:00,  4.77it/s]\n",
      "Processing negative reference clips: 100%|██████████| 1/1 [00:00<00:00,  5.53it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training and saving verifier model...\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "# Train verifier model on the reference clips\n",
    "\n",
    "output_model_path = \"turn_on_the_office_lights_verifier.pkl\"\n",
    "openwakeword.train_custom_verifier(\n",
    "    positive_reference_clips = reference_clips[0:3], # use 3 reference examples for the wake phrase\n",
    "    negative_reference_clips = negative_clips,\n",
    "    output_path = output_model_path,\n",
    "    model_name = \"turn_on_the_office_lights.onnx\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ad4d2ec",
   "metadata": {},
   "source": [
    "After the model is trained, we can instantiate a new openWakeWord instance and include the path to the trained verifier model, as well as set the threshold score from the base model required to invoke the verifier. In practice, you can set this threshold score a bit lower than normal, though as usual actual testing in the deployment environment is recommended."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "50b99677",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:46:01.357976Z",
     "start_time": "2023-02-18T03:46:01.146646Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dscripka/anaconda3/envs/torch_gpu/lib/python3.9/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:54: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'CPUExecutionProvider'\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Create openWakeWord instance with verifier model\n",
    "\n",
    "oww = openwakeword.Model(\n",
    "    wakeword_model_paths=[\"turn_on_the_office_lights.onnx\"],\n",
    "    enable_speex_noise_suppression=True,\n",
    "    vad_threshold=0.5,\n",
    "    custom_verifier_models={\"turn_on_the_office_lights\": \"turn_on_the_office_lights_verifier.pkl\"},\n",
    "    custom_verifier_threshold=0.3,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6666dadb",
   "metadata": {},
   "source": [
    "Finally, we can run the model on our test clip from the Santa Barbara corpus and see if the false activation rate has decreased to an acceptable level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "19fd5f51",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:47:25.076640Z",
     "start_time": "2023-02-18T03:46:07.021368Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run false-accept rate test again, now with the verifier model\n",
    "\n",
    "scores = oww.predict_clip(\"santa_barbara_corpus_test_clip.wav\")\n",
    "\n",
    "plt.figure()\n",
    "plt.plot([i[\"turn_on_the_office_lights\"] for i in scores])\n",
    "_ = plt.ylim(0,1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c59007d2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-02-18T03:47:29.856142Z",
     "start_time": "2023-02-18T03:47:29.836354Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False-accept rate per hour: 0.0\n"
     ]
    }
   ],
   "source": [
    "# Calculate the false-accept rate per hour from this new result\n",
    "\n",
    "false_accepts = openwakeword.metrics.get_false_positives(\n",
    "    [i[\"turn_on_the_office_lights\"] for i in scores], threshold=0.5\n",
    ")\n",
    "\n",
    "print(f\"False-accept rate per hour: {false_accepts/1}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c7375c6",
   "metadata": {},
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    "Sucess! Now the false-activation rate is at most <1 per hour given that there weren't any false-positives in our ~1 hour test clip, which is an orders of magnitude decrease! This model is now much closer to being ready for a production deployment, assuming that each user is known and can provide the neccessary data to train the verifier model."
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