{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Model Training"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This tutorial demonstrates the training of the ```TemporalFusionTransformer``` model. \n",
"\n",
"The demonstration is using the processed version of [__*CorporaciĆ³n Favorita Grocery Sales Forecasting*__](https://www.kaggle.com/c/favorita-grocery-sales-forecasting/overview) dataset, as demonstrated in the __*Favorita Dataset Creation Example*__ tutorial, which is also part of this documentation. \n",
"\n",
"The training routine implemented below, uses *pure* pytorch, for clarity purposes. However, it can be easily adapted to frameworks such as [__*pytorch-ignite*__](https://pytorch.org/ignite/index.html) or [__*pytorch-lightning*__](https://www.pytorchlightning.ai/) to facilitate, orchestrate, and automate some of the training procedure.\n",
"\n",
"For a comprehensive explanation of the model and its structure, refer to our [**blogpost**](https://www.playtika-blog.com/playtika-ai/multi-horizon-forecasting-using-temporal-fusion-transformers-a-comprehensive-overview-part-1/)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Importing the required libraries"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import pickle\n",
"from typing import Dict,List,Tuple\n",
"from functools import partial\n",
"import copy\n",
"import numpy as np\n",
"from omegaconf import OmegaConf,DictConfig\n",
"import pandas as pd\n",
"from tqdm import tqdm\n",
"import torch\n",
"from torch import optim\n",
"from torch import nn\n",
"import torch.nn.init as init\n",
"from torch.utils.data import Dataset, DataLoader, Subset\n",
"from tft_torch.tft import TemporalFusionTransformer\n",
"import tft_torch.loss as tft_loss"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Data-related"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Setting the path to the location in which we saved the processed dataset in the previous tutorial:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"data_path = '.../data/favorita/data.pickle'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Reading the pickle we saved, and take a pick at its content:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with open(data_path,'rb') as fp:\n",
" data = pickle.load(fp)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['data_sets', 'feature_map', 'scalers', 'categorical_cardinalities']"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(data.keys())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Displaying the content of the ```data_sets``` key. \n",
"Note that the shapes of the array, in case you follow the previous tutorial, depends on the range of dates configured."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"=======\n",
"train\n",
"=======\n",
"time_index (shape,dtype)\n",
"(11532481,) object\n",
"combination_id (shape,dtype)\n",
"(11532481,) \n",
"The meta data specified above is available as part of the pickle we created when we processed the raw data, so here it comes handy."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"feature_map = data['feature_map']\n",
"cardinalities_map = data['categorical_cardinalities']\n",
"\n",
"structure = {\n",
" 'num_historical_numeric': len(feature_map['historical_ts_numeric']),\n",
" 'num_historical_categorical': len(feature_map['historical_ts_categorical']),\n",
" 'num_static_numeric': len(feature_map['static_feats_numeric']),\n",
" 'num_static_categorical': len(feature_map['static_feats_categorical']),\n",
" 'num_future_numeric': len(feature_map['future_ts_numeric']),\n",
" 'num_future_categorical': len(feature_map['future_ts_categorical']),\n",
" 'historical_categorical_cardinalities': [cardinalities_map[feat] + 1 for feat in feature_map['historical_ts_categorical']],\n",
" 'static_categorical_cardinalities': [cardinalities_map[feat] + 1 for feat in feature_map['static_feats_categorical']],\n",
" 'future_categorical_cardinalities': [cardinalities_map[feat] + 1 for feat in feature_map['future_ts_categorical']],\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that we add ``1`` to each of the categorical cardinalities. The reason for that is that the categorical cardinalities are taken from the ```LabelEncoder``` objects which were used for encoding the data in the processing phase. As these ```LabelEncoder``` objects were fit to the training subset, some categories that appeared on the later parts of the dataset (validation/test subsets) were possibly unseen by these ```LabelEncoder```s. Hence, the encodings we applied allocated/appended a new label index for each unseen category, and here we somehow *\"inform\"* the model the precise number of categories the model will need to embed for each attribute."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Adding the input structure we inferred to the configuration object:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"configuration['data_props'] = structure"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Model Creation and Initiation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The model is initiated by the configuration created above:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"model = TemporalFusionTransformer(config=OmegaConf.create(configuration))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For initialization of the weights composing the model, we use the legendary [__snippet/gist__](https://gist.github.com/jeasinema/ed9236ce743c8efaf30fa2ff732749f5) provided by [__jeasinema__](https://gist.github.com/jeasinema):"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"def weight_init(m):\n",
" \"\"\"\n",
" Usage:\n",
" model = Model()\n",
" model.apply(weight_init)\n",
" \"\"\"\n",
" if isinstance(m, nn.Conv1d):\n",
" init.normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.Conv2d):\n",
" init.xavier_normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.Conv3d):\n",
" init.xavier_normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.ConvTranspose1d):\n",
" init.normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.ConvTranspose2d):\n",
" init.xavier_normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.ConvTranspose3d):\n",
" init.xavier_normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.BatchNorm1d):\n",
" init.normal_(m.weight.data, mean=1, std=0.02)\n",
" init.constant_(m.bias.data, 0)\n",
" elif isinstance(m, nn.BatchNorm2d):\n",
" init.normal_(m.weight.data, mean=1, std=0.02)\n",
" init.constant_(m.bias.data, 0)\n",
" elif isinstance(m, nn.BatchNorm3d):\n",
" init.normal_(m.weight.data, mean=1, std=0.02)\n",
" init.constant_(m.bias.data, 0)\n",
" elif isinstance(m, nn.Linear):\n",
" init.xavier_normal_(m.weight.data)\n",
" if m.bias is not None:\n",
" init.normal_(m.bias.data)\n",
" elif isinstance(m, nn.LSTM):\n",
" for param in m.parameters():\n",
" if len(param.shape) >= 2:\n",
" init.orthogonal_(param.data)\n",
" else:\n",
" init.normal_(param.data)\n",
" elif isinstance(m, nn.LSTMCell):\n",
" for param in m.parameters():\n",
" if len(param.shape) >= 2:\n",
" init.orthogonal_(param.data)\n",
" else:\n",
" init.normal_(param.data)\n",
" elif isinstance(m, nn.GRU):\n",
" for param in m.parameters():\n",
" if len(param.shape) >= 2:\n",
" init.orthogonal_(param.data)\n",
" else:\n",
" init.normal_(param.data)\n",
" for names in m._all_weights:\n",
" for name in filter(lambda n: \"bias\" in n, names):\n",
" bias = getattr(m, name)\n",
" n = bias.size(0)\n",
" bias.data[:n // 3].fill_(-1.)\n",
" elif isinstance(m, nn.GRUCell):\n",
" for param in m.parameters():\n",
" if len(param.shape) >= 2:\n",
" init.orthogonal_(param.data)\n",
" else:\n",
" init.normal_(param.data)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"model.apply(weight_init)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then we specify the device, according to the availability of *CUDA* device, and transfer the model to the device accordingly:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"is_cuda = torch.cuda.is_available()\n",
"device = torch.device(\"cuda\" if is_cuda else \"cpu\")\n",
"model.to(device)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that the model is set, we initalize the optimizer, and point it to the model parameters:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"opt = optim.Adam(filter(lambda p: p.requires_grad, list(model.parameters())),\n",
" lr=configuration['optimization']['learning_rate'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data Preparation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As a utility class, we will declare ``DictDataSet`` which digests a dictionary of numpy arrays, and makes sure that each record/observation that will be retrieved using this dataset, will be output as a dictionary of tensors with keys corresponding to these of the original input dictionary.\n",
"This ``DictDataSet`` be useful because when we'll wrap it with a dedicated ``DataLoader`` object, our mini-batches will be ``dict`` objects as well, which is highly convenient. \n",
"__*Note*__: The tensor data-types are set according to the data-type of the corresponding numpy arrays."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"class DictDataSet(Dataset):\n",
" def __init__(self, array_dict: Dict[str, np.ndarray]):\n",
" self.keys_list = []\n",
" for k, v in array_dict.items():\n",
" self.keys_list.append(k)\n",
" if np.issubdtype(v.dtype, np.dtype('bool')):\n",
" setattr(self, k, torch.ByteTensor(v))\n",
" elif np.issubdtype(v.dtype, np.int8):\n",
" setattr(self, k, torch.CharTensor(v))\n",
" elif np.issubdtype(v.dtype, np.int16):\n",
" setattr(self, k, torch.ShortTensor(v))\n",
" elif np.issubdtype(v.dtype, np.int32):\n",
" setattr(self, k, torch.IntTensor(v))\n",
" elif np.issubdtype(v.dtype, np.int64):\n",
" setattr(self, k, torch.LongTensor(v))\n",
" elif np.issubdtype(v.dtype, np.float32):\n",
" setattr(self, k, torch.FloatTensor(v))\n",
" elif np.issubdtype(v.dtype, np.float64):\n",
" setattr(self, k, torch.DoubleTensor(v))\n",
" else:\n",
" setattr(self, k, torch.FloatTensor(v))\n",
"\n",
" def __getitem__(self, index):\n",
" return {k: getattr(self, k)[index] for k in self.keys_list}\n",
"\n",
" def __len__(self):\n",
" return getattr(self, self.keys_list[0]).shape[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In addition, we'll define a function named ``recycle``, which will be used for creating some kind of \"*infinite*\" data loader, i.e. by wrapping a dataloader with this utility function, we make sure that we'll be able to get batches (using e.g. ``next``), and the iterator won't get to its ending state. \n",
"\n",
"One last utility data-related utility function is ``get_set_and_loaders()``, which expects a ``dict`` of numpy arrays, transforms it into a ``DictDataSet`` object, and creates two data loaders for each set.\n",
"One data loader will be shuffled and, what was termed as \"*infinite*\", and the second one will be serial, for allowing us to perform inference on all the observations in the dataset, while keeping them in the original order. \n",
"*Note*: the input argument ``ignore_keys`` allows discarding some keys in the original dictionary, ``data_dict``, and not including them in the resulting ``DictDataSet`` and in the corresponding batches it'll produce."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"def recycle(iterable):\n",
" while True:\n",
" for x in iterable:\n",
" yield x\n",
"\n",
"def get_set_and_loaders(data_dict: Dict[str, np.ndarray],\n",
" shuffled_loader_config: Dict,\n",
" serial_loader_config: Dict,\n",
" ignore_keys: List[str] = None,\n",
" ) -> Tuple[torch.utils.data.Dataset, torch.utils.data.DataLoader, torch.utils.data.DataLoader]:\n",
" dataset = DictDataSet({k:v for k,v in data_dict.items() if (ignore_keys and k not in ignore_keys)})\n",
" loader = torch.utils.data.DataLoader(dataset,**shuffled_loader_config)\n",
" serial_loader = torch.utils.data.DataLoader(dataset,**serial_loader_config)\n",
"\n",
" return dataset,iter(recycle(loader)),serial_loader"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We set the configuration for the shuffled data loaders, and for the serial ones, and we also set the ``meta_keys`` which specifies which keys do not contain actual data (only meta-data to identify each record):"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"shuffled_loader_config = {'batch_size': configuration['optimization']['batch_size']['training'],\n",
" 'drop_last': True,\n",
" 'shuffle':True}\n",
"\n",
"serial_loader_config = {'batch_size': configuration['optimization']['batch_size']['inference'],\n",
" 'drop_last': False,\n",
" 'shuffle':False}\n",
"\n",
"# the following fields do not contain actual data, but are only identifiers of each observation\n",
"meta_keys = ['time_index','combination_id']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We use the utility functions for generating the required data loaders for each of the subsets:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"train_set,train_loader,train_serial_loader = get_set_and_loaders(data['data_sets']['train'],\n",
" shuffled_loader_config,\n",
" serial_loader_config,\n",
" ignore_keys=meta_keys)\n",
"validation_set,validation_loader,validation_serial_loader = get_set_and_loaders(data['data_sets']['validation'],\n",
" shuffled_loader_config,\n",
" serial_loader_config,\n",
" ignore_keys=meta_keys)\n",
"test_set,test_loader,test_serial_loader = get_set_and_loaders(data['data_sets']['test'],\n",
" shuffled_loader_config,\n",
" serial_loader_config,\n",
" ignore_keys=meta_keys)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training Procedure"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that everything is set in terms of the model and the data, we define some helpful utilities for easier orchestration of the training procedure. \n",
"\n",
"``QueueAggregator`` is, well, a queue, which will be used as a running-window aggregator of the training performance metric. We'll use it to for smoother (and less noisier) estimation of our loss during training."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"class QueueAggregator(object):\n",
" def __init__(self, max_size):\n",
" self._queued_list = []\n",
" self.max_size = max_size\n",
"\n",
" def append(self, elem):\n",
" self._queued_list.append(elem)\n",
" if len(self._queued_list) > self.max_size:\n",
" self._queued_list.pop(0)\n",
"\n",
" def get(self):\n",
" return self._queued_list"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also employ an ``EarlyStopping`` mechanism for monitoring the performance on our validation set, and indicate when can we quit training. \n",
"This extremely [useful snippet](https://gist.github.com/stefanonardo/693d96ceb2f531fa05db530f3e21517d) was originally contributed by [stefanonardo](https://gist.github.com/stefanonardo)."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"class EarlyStopping(object):\n",
" def __init__(self, mode='min', min_delta=0, patience=10, percentage=False):\n",
" self.mode = mode\n",
" self.min_delta = min_delta\n",
" self.patience = patience\n",
" self.best = None\n",
" self.num_bad_epochs = 0\n",
" self.is_better = None\n",
" self._init_is_better(mode, min_delta, percentage)\n",
"\n",
" if patience == 0:\n",
" self.is_better = lambda a, b: True\n",
" self.step = lambda a: False\n",
"\n",
" def step(self, metrics):\n",
" if self.best is None:\n",
" self.best = metrics\n",
" return False\n",
"\n",
" if torch.isnan(metrics):\n",
" return True\n",
"\n",
" if self.is_better(metrics, self.best):\n",
" self.num_bad_epochs = 0\n",
" self.best = metrics\n",
" else:\n",
" self.num_bad_epochs += 1\n",
"\n",
" if self.num_bad_epochs >= self.patience:\n",
" return True\n",
"\n",
" return False\n",
"\n",
" def _init_is_better(self, mode, min_delta, percentage):\n",
" if mode not in {'min', 'max'}:\n",
" raise ValueError('mode ' + mode + ' is unknown!')\n",
" if not percentage:\n",
" if mode == 'min':\n",
" self.is_better = lambda a, best: a < best - min_delta\n",
" if mode == 'max':\n",
" self.is_better = lambda a, best: a > best + min_delta\n",
" else:\n",
" if mode == 'min':\n",
" self.is_better = lambda a, best: a < best - (\n",
" best * min_delta / 100)\n",
" if mode == 'max':\n",
" self.is_better = lambda a, best: a > best + (\n",
" best * min_delta / 100)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Training Settings"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's go over to required parameters which will control the training routine:"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"# If early stopping is not triggered, after how many epochs should we quit training\n",
"max_epochs = 10000\n",
"# how many training batches will compose a single training epoch\n",
"epoch_iters = 200\n",
"# upon completing a training epoch, we perform an evaluation of all the subsets\n",
"# eval_iters will define how many batches of each set will compose a single evaluation round\n",
"eval_iters = 500\n",
"# during training, on what frequency should we display the monitored performance\n",
"log_interval = 20\n",
"# what is the running-window used by our QueueAggregator object for monitoring the training performance\n",
"ma_queue_size = 50\n",
"# how many evaluation rounds should we allow,\n",
"# without any improvement in the performance observed on the validation set\n",
"patience = 5"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"# initialize early stopping mechanism\n",
"es = EarlyStopping(patience=patience)\n",
"# initialize the loss aggregator for running window performance estimation\n",
"loss_aggregator = QueueAggregator(max_size=ma_queue_size)\n",
"\n",
"# initialize counters\n",
"batch_idx = 0\n",
"epoch_idx = 0"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For computing the loss we are seeking to optimize, we need to define a tensor, corresponding to the actual quantiles we want to estimate:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"quantiles_tensor = torch.tensor(configuration['model']['output_quantiles']).to(device)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following cell implements the way each batch is processed by our training/evaluation procedure. We transfer each batch component to the ``device`` we're using, feed the batch to the model, and compute the loss, using the labels (which are part of our batch), the ``predicted_quantiles`` output, and the *fixed* tensor ``quantiles_tensor`` stating the quantiles we wish to estimate."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"def process_batch(batch: Dict[str,torch.tensor],\n",
" model: nn.Module,\n",
" quantiles_tensor: torch.tensor,\n",
" device:torch.device):\n",
" if is_cuda:\n",
" for k in list(batch.keys()):\n",
" batch[k] = batch[k].to(device)\n",
"\n",
" batch_outputs = model(batch)\n",
" labels = batch['target']\n",
"\n",
" predicted_quantiles = batch_outputs['predicted_quantiles']\n",
" q_loss, q_risk, _ = tft_loss.get_quantiles_loss_and_q_risk(outputs=predicted_quantiles,\n",
" targets=labels,\n",
" desired_quantiles=quantiles_tensor)\n",
" return q_loss, q_risk"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, finally, is the actual training loop. This loop will go on until completing ``max_epoch`` rounds, or until ``EarlyStopping`` is triggered. \n",
"\n",
"Each epoch starts with the evaluation of each of the subsets. Each evaluation rounds includes the processing of ``eval_iters`` batches from the relevant subset, after which the losses and the metrics are concatenated and averaged. The loss computed for the validation set is fed to the early stopping mechanism for continuous tracking. \n",
"\n",
"After completing the evaluation of the data subsets, a training round, including the processing of ``epoch_iters`` batches from the training subset, is initiated. For each training batch, the computed loss is used for calling the optimizer to update the model weights, and added to the loss aggregator."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Starting Epoch Index 0\n",
"Evaluating train set\n",
"Epoch: 0, Batch Index: 0- Eval train - q_loss = 2.03305 , q_risk_0.1 = 2.15217 , q_risk_0.5 = 1.50869 , q_risk_0.9 = 1.42569\n",
"Evaluating validation set\n",
"Epoch: 0, Batch Index: 0- Eval validation - q_loss = 2.09707 , q_risk_0.1 = 2.79929 , q_risk_0.5 = 1.31844 , q_risk_0.9 = 1.11522\n",
"Evaluating test set\n",
"Epoch: 0, Batch Index: 0- Eval test - q_loss = 1.98208 , q_risk_0.1 = 2.24149 , q_risk_0.5 = 1.40397 , q_risk_0.9 = 1.35933\n",
"Epoch: 0, Batch Index: 0 - Train Loss = 2.020455837249756\n",
"Epoch: 0, Batch Index: 20 - Train Loss = 0.7724506230581374\n",
"Epoch: 0, Batch Index: 40 - Train Loss = 0.6347503349548433\n",
"Epoch: 0, Batch Index: 60 - Train Loss = 0.5004462844133377\n",
"Epoch: 0, Batch Index: 80 - Train Loss = 0.44857171654701233\n",
"Epoch: 0, Batch Index: 100 - Train Loss = 0.43766250789165495\n",
"Epoch: 0, Batch Index: 120 - Train Loss = 0.43416002750396726\n",
"Epoch: 0, Batch Index: 140 - Train Loss = 0.4331358313560486\n",
"Epoch: 0, Batch Index: 160 - Train Loss = 0.43066891729831697\n",
"Epoch: 0, Batch Index: 180 - Train Loss = 0.42729145765304566\n",
"Starting Epoch Index 1\n",
"Evaluating train set\n",
"Epoch: 1, Batch Index: 200- Eval train - q_loss = 0.42002 , q_risk_0.1 = 0.23620 , q_risk_0.5 = 0.56292 , q_risk_0.9 = 0.25254\n",
"Evaluating validation set\n",
"Epoch: 1, Batch Index: 200- Eval validation - q_loss = 0.39472 , q_risk_0.1 = 0.20502 , q_risk_0.5 = 0.53681 , q_risk_0.9 = 0.24385\n",
"Evaluating test set\n",
"Epoch: 1, Batch Index: 200- Eval test - q_loss = 0.43020 , q_risk_0.1 = 0.23920 , q_risk_0.5 = 0.58177 , q_risk_0.9 = 0.26610\n",
"Epoch: 1, Batch Index: 200 - Train Loss = 0.42498995423316954\n",
"Epoch: 1, Batch Index: 220 - Train Loss = 0.42323225796222685\n",
"Epoch: 1, Batch Index: 240 - Train Loss = 0.4226619130373001\n",
"Epoch: 1, Batch Index: 260 - Train Loss = 0.4221925890445709\n",
"Epoch: 1, Batch Index: 280 - Train Loss = 0.42066602885723114\n",
"Epoch: 1, Batch Index: 300 - Train Loss = 0.41808026492595673\n",
"Epoch: 1, Batch Index: 320 - Train Loss = 0.4159805303812027\n",
"Epoch: 1, Batch Index: 340 - Train Loss = 0.4174565130472183\n",
"Epoch: 1, Batch Index: 360 - Train Loss = 0.4196115469932556\n",
"Epoch: 1, Batch Index: 380 - Train Loss = 0.42100709676742554\n",
"Starting Epoch Index 2\n",
"Evaluating train set\n",
"Epoch: 2, Batch Index: 400- Eval train - q_loss = 0.41395 , q_risk_0.1 = 0.23116 , q_risk_0.5 = 0.55721 , q_risk_0.9 = 0.24765\n",
"Evaluating validation set\n",
"Epoch: 2, Batch Index: 400- Eval validation - q_loss = 0.38804 , q_risk_0.1 = 0.20017 , q_risk_0.5 = 0.52711 , q_risk_0.9 = 0.24130\n",
"Evaluating test set\n",
"Epoch: 2, Batch Index: 400- Eval test - q_loss = 0.42346 , q_risk_0.1 = 0.23246 , q_risk_0.5 = 0.57313 , q_risk_0.9 = 0.26003\n",
"Epoch: 2, Batch Index: 400 - Train Loss = 0.4180942130088806\n",
"Epoch: 2, Batch Index: 420 - Train Loss = 0.41510038435459135\n",
"Epoch: 2, Batch Index: 440 - Train Loss = 0.41567377269268035\n",
"Epoch: 2, Batch Index: 460 - Train Loss = 0.41648059606552124\n",
"Epoch: 2, Batch Index: 480 - Train Loss = 0.41558587193489077\n",
"Epoch: 2, Batch Index: 500 - Train Loss = 0.4143910664319992\n",
"Epoch: 2, Batch Index: 520 - Train Loss = 0.41360773086547853\n",
"Epoch: 2, Batch Index: 540 - Train Loss = 0.4148547148704529\n",
"Epoch: 2, Batch Index: 560 - Train Loss = 0.41554462850093843\n",
"Epoch: 2, Batch Index: 580 - Train Loss = 0.4137012666463852\n",
"Starting Epoch Index 3\n",
"Evaluating train set\n",
"Epoch: 3, Batch Index: 600- Eval train - q_loss = 0.40949 , q_risk_0.1 = 0.22791 , q_risk_0.5 = 0.55206 , q_risk_0.9 = 0.24633\n",
"Evaluating validation set\n",
"Epoch: 3, Batch Index: 600- Eval validation - q_loss = 0.38416 , q_risk_0.1 = 0.19762 , q_risk_0.5 = 0.52276 , q_risk_0.9 = 0.23902\n",
"Evaluating test set\n",
"Epoch: 3, Batch Index: 600- Eval test - q_loss = 0.41854 , q_risk_0.1 = 0.23092 , q_risk_0.5 = 0.56851 , q_risk_0.9 = 0.25763\n",
"Epoch: 3, Batch Index: 600 - Train Loss = 0.41306958615779876\n",
"Epoch: 3, Batch Index: 620 - Train Loss = 0.41319740533828736\n",
"Epoch: 3, Batch Index: 640 - Train Loss = 0.41450446128845214\n",
"Epoch: 3, Batch Index: 660 - Train Loss = 0.4108119714260101\n",
"Epoch: 3, Batch Index: 680 - Train Loss = 0.40992509841918945\n",
"Epoch: 3, Batch Index: 700 - Train Loss = 0.4079200464487076\n",
"Epoch: 3, Batch Index: 720 - Train Loss = 0.409369660615921\n",
"Epoch: 3, Batch Index: 740 - Train Loss = 0.4104118537902832\n",
"Epoch: 3, Batch Index: 760 - Train Loss = 0.4100472277402878\n",
"Epoch: 3, Batch Index: 780 - Train Loss = 0.4100530457496643\n",
"Starting Epoch Index 4\n",
"Evaluating train set\n",
"Epoch: 4, Batch Index: 800- Eval train - q_loss = 0.40630 , q_risk_0.1 = 0.22670 , q_risk_0.5 = 0.54644 , q_risk_0.9 = 0.24413\n",
"Evaluating validation set\n",
"Epoch: 4, Batch Index: 800- Eval validation - q_loss = 0.38275 , q_risk_0.1 = 0.19644 , q_risk_0.5 = 0.51953 , q_risk_0.9 = 0.24003\n",
"Evaluating test set\n",
"Epoch: 4, Batch Index: 800- Eval test - q_loss = 0.41674 , q_risk_0.1 = 0.22941 , q_risk_0.5 = 0.56476 , q_risk_0.9 = 0.25801\n",
"Epoch: 4, Batch Index: 800 - Train Loss = 0.40925871193408964\n",
"Epoch: 4, Batch Index: 820 - Train Loss = 0.4090828377008438\n",
"Epoch: 4, Batch Index: 840 - Train Loss = 0.4069894003868103\n",
"Epoch: 4, Batch Index: 860 - Train Loss = 0.40759585201740267\n",
"Epoch: 4, Batch Index: 880 - Train Loss = 0.4058069509267807\n",
"Epoch: 4, Batch Index: 900 - Train Loss = 0.40712576448917387\n",
"Epoch: 4, Batch Index: 920 - Train Loss = 0.40775597989559176\n",
"Epoch: 4, Batch Index: 940 - Train Loss = 0.4076818293333054\n",
"Epoch: 4, Batch Index: 960 - Train Loss = 0.40606608867645266\n",
"Epoch: 4, Batch Index: 980 - Train Loss = 0.4045009380578995\n",
"Starting Epoch Index 5\n",
"Evaluating train set\n",
"Epoch: 5, Batch Index: 1000- Eval train - q_loss = 0.40445 , q_risk_0.1 = 0.22491 , q_risk_0.5 = 0.54649 , q_risk_0.9 = 0.24098\n",
"Evaluating validation set\n",
"Epoch: 5, Batch Index: 1000- Eval validation - q_loss = 0.38038 , q_risk_0.1 = 0.19408 , q_risk_0.5 = 0.51852 , q_risk_0.9 = 0.23671\n",
"Evaluating test set\n",
"Epoch: 5, Batch Index: 1000- Eval test - q_loss = 0.41440 , q_risk_0.1 = 0.22713 , q_risk_0.5 = 0.56470 , q_risk_0.9 = 0.25405\n",
"Epoch: 5, Batch Index: 1000 - Train Loss = 0.4067613816261291\n",
"Epoch: 5, Batch Index: 1020 - Train Loss = 0.4067066353559494\n",
"Epoch: 5, Batch Index: 1040 - Train Loss = 0.40532047510147096\n",
"Epoch: 5, Batch Index: 1060 - Train Loss = 0.4045089113712311\n",
"Epoch: 5, Batch Index: 1080 - Train Loss = 0.4038675820827484\n",
"Epoch: 5, Batch Index: 1100 - Train Loss = 0.4051359671354294\n",
"Epoch: 5, Batch Index: 1120 - Train Loss = 0.40533805549144747\n",
"Epoch: 5, Batch Index: 1140 - Train Loss = 0.4062341320514679\n",
"Epoch: 5, Batch Index: 1160 - Train Loss = 0.40499836564064023\n",
"Epoch: 5, Batch Index: 1180 - Train Loss = 0.4051413434743881\n",
"Starting Epoch Index 6\n",
"Evaluating train set\n",
"Epoch: 6, Batch Index: 1200- Eval train - q_loss = 0.40266 , q_risk_0.1 = 0.22359 , q_risk_0.5 = 0.54319 , q_risk_0.9 = 0.23855\n",
"Evaluating validation set\n",
"Epoch: 6, Batch Index: 1200- Eval validation - q_loss = 0.38021 , q_risk_0.1 = 0.19417 , q_risk_0.5 = 0.51992 , q_risk_0.9 = 0.23482\n",
"Evaluating test set\n",
"Epoch: 6, Batch Index: 1200- Eval test - q_loss = 0.41308 , q_risk_0.1 = 0.22795 , q_risk_0.5 = 0.56358 , q_risk_0.9 = 0.25170\n",
"Epoch: 6, Batch Index: 1200 - Train Loss = 0.40418831825256346\n",
"Epoch: 6, Batch Index: 1220 - Train Loss = 0.40468450009822843\n",
"Epoch: 6, Batch Index: 1240 - Train Loss = 0.4058254724740982\n",
"Epoch: 6, Batch Index: 1260 - Train Loss = 0.4060604375600815\n",
"Epoch: 6, Batch Index: 1280 - Train Loss = 0.4070625078678131\n",
"Epoch: 6, Batch Index: 1300 - Train Loss = 0.40513818204402924\n",
"Epoch: 6, Batch Index: 1320 - Train Loss = 0.40423076212406156\n",
"Epoch: 6, Batch Index: 1340 - Train Loss = 0.40216550648212435\n",
"Epoch: 6, Batch Index: 1360 - Train Loss = 0.4020002579689026\n",
"Epoch: 6, Batch Index: 1380 - Train Loss = 0.40282262206077574\n",
"Starting Epoch Index 7\n",
"Evaluating train set\n",
"Epoch: 7, Batch Index: 1400- Eval train - q_loss = 0.39914 , q_risk_0.1 = 0.22295 , q_risk_0.5 = 0.53990 , q_risk_0.9 = 0.23707\n",
"Evaluating validation set\n",
"Epoch: 7, Batch Index: 1400- Eval validation - q_loss = 0.37719 , q_risk_0.1 = 0.19344 , q_risk_0.5 = 0.51450 , q_risk_0.9 = 0.23325\n",
"Evaluating test set\n",
"Epoch: 7, Batch Index: 1400- Eval test - q_loss = 0.40899 , q_risk_0.1 = 0.22704 , q_risk_0.5 = 0.55840 , q_risk_0.9 = 0.24897\n",
"Epoch: 7, Batch Index: 1400 - Train Loss = 0.402779341340065\n",
"Epoch: 7, Batch Index: 1420 - Train Loss = 0.40297271132469176\n",
"Epoch: 7, Batch Index: 1440 - Train Loss = 0.4026300513744354\n",
"Epoch: 7, Batch Index: 1460 - Train Loss = 0.40316272258758545\n",
"Epoch: 7, Batch Index: 1480 - Train Loss = 0.4022568541765213\n",
"Epoch: 7, Batch Index: 1500 - Train Loss = 0.4006280392408371\n",
"Epoch: 7, Batch Index: 1520 - Train Loss = 0.4012106776237488\n",
"Epoch: 7, Batch Index: 1540 - Train Loss = 0.40098224580287933\n",
"Epoch: 7, Batch Index: 1560 - Train Loss = 0.4003554481267929\n",
"Epoch: 7, Batch Index: 1580 - Train Loss = 0.40120102822780607\n",
"Starting Epoch Index 8\n",
"Evaluating train set\n",
"Epoch: 8, Batch Index: 1600- Eval train - q_loss = 0.39869 , q_risk_0.1 = 0.22295 , q_risk_0.5 = 0.54067 , q_risk_0.9 = 0.23733\n",
"Evaluating validation set\n",
"Epoch: 8, Batch Index: 1600- Eval validation - q_loss = 0.37542 , q_risk_0.1 = 0.19315 , q_risk_0.5 = 0.51215 , q_risk_0.9 = 0.23249\n",
"Evaluating test set\n",
"Epoch: 8, Batch Index: 1600- Eval test - q_loss = 0.40910 , q_risk_0.1 = 0.22636 , q_risk_0.5 = 0.55779 , q_risk_0.9 = 0.24879\n",
"Epoch: 8, Batch Index: 1600 - Train Loss = 0.4011056447029114\n",
"Epoch: 8, Batch Index: 1620 - Train Loss = 0.4003825575113297\n",
"Epoch: 8, Batch Index: 1640 - Train Loss = 0.4013179081678391\n",
"Epoch: 8, Batch Index: 1660 - Train Loss = 0.4005914378166199\n",
"Epoch: 8, Batch Index: 1680 - Train Loss = 0.400411833524704\n",
"Epoch: 8, Batch Index: 1700 - Train Loss = 0.39901186048984527\n",
"Epoch: 8, Batch Index: 1720 - Train Loss = 0.39950142443180087\n",
"Epoch: 8, Batch Index: 1740 - Train Loss = 0.40104600429534915\n",
"Epoch: 8, Batch Index: 1760 - Train Loss = 0.4011937004327774\n",
"Epoch: 8, Batch Index: 1780 - Train Loss = 0.3990417116880417\n",
"Starting Epoch Index 9\n",
"Evaluating train set\n",
"Epoch: 9, Batch Index: 1800- Eval train - q_loss = 0.39769 , q_risk_0.1 = 0.22267 , q_risk_0.5 = 0.53573 , q_risk_0.9 = 0.23551\n",
"Evaluating validation set\n",
"Epoch: 9, Batch Index: 1800- Eval validation - q_loss = 0.37497 , q_risk_0.1 = 0.19375 , q_risk_0.5 = 0.51019 , q_risk_0.9 = 0.23209\n",
"Evaluating test set\n",
"Epoch: 9, Batch Index: 1800- Eval test - q_loss = 0.40726 , q_risk_0.1 = 0.22613 , q_risk_0.5 = 0.55291 , q_risk_0.9 = 0.24664\n",
"Epoch: 9, Batch Index: 1800 - Train Loss = 0.3984821850061417\n",
"Epoch: 9, Batch Index: 1820 - Train Loss = 0.39621995747089384\n",
"Epoch: 9, Batch Index: 1840 - Train Loss = 0.397534641623497\n",
"Epoch: 9, Batch Index: 1860 - Train Loss = 0.39747892796993256\n",
"Epoch: 9, Batch Index: 1880 - Train Loss = 0.39800208926200864\n",
"Epoch: 9, Batch Index: 1900 - Train Loss = 0.3982150912284851\n",
"Epoch: 9, Batch Index: 1920 - Train Loss = 0.3992548805475235\n",
"Epoch: 9, Batch Index: 1940 - Train Loss = 0.40012820780277253\n",
"Epoch: 9, Batch Index: 1960 - Train Loss = 0.3997068899869919\n",
"Epoch: 9, Batch Index: 1980 - Train Loss = 0.3998417049646378\n",
"Starting Epoch Index 10\n",
"Evaluating train set\n",
"Epoch: 10, Batch Index: 2000- Eval train - q_loss = 0.39851 , q_risk_0.1 = 0.22142 , q_risk_0.5 = 0.53672 , q_risk_0.9 = 0.23679\n",
"Evaluating validation set\n",
"Epoch: 10, Batch Index: 2000- Eval validation - q_loss = 0.37541 , q_risk_0.1 = 0.19174 , q_risk_0.5 = 0.50991 , q_risk_0.9 = 0.23376\n",
"Evaluating test set\n",
"Epoch: 10, Batch Index: 2000- Eval test - q_loss = 0.40849 , q_risk_0.1 = 0.22410 , q_risk_0.5 = 0.55475 , q_risk_0.9 = 0.24999\n",
"Epoch: 10, Batch Index: 2000 - Train Loss = 0.3990354412794113\n",
"Epoch: 10, Batch Index: 2020 - Train Loss = 0.3999947690963745\n",
"Epoch: 10, Batch Index: 2040 - Train Loss = 0.39858454167842866\n",
"Epoch: 10, Batch Index: 2060 - Train Loss = 0.3993226552009583\n",
"Epoch: 10, Batch Index: 2080 - Train Loss = 0.3973876845836639\n",
"Epoch: 10, Batch Index: 2100 - Train Loss = 0.3981896710395813\n",
"Epoch: 10, Batch Index: 2120 - Train Loss = 0.3981538939476013\n",
"Epoch: 10, Batch Index: 2140 - Train Loss = 0.3983695012331009\n",
"Epoch: 10, Batch Index: 2160 - Train Loss = 0.3958142375946045\n",
"Epoch: 10, Batch Index: 2180 - Train Loss = 0.3963635700941086\n",
"Starting Epoch Index 11\n",
"Evaluating train set\n",
"Epoch: 11, Batch Index: 2200- Eval train - q_loss = 0.39731 , q_risk_0.1 = 0.22121 , q_risk_0.5 = 0.53701 , q_risk_0.9 = 0.23767\n",
"Evaluating validation set\n",
"Epoch: 11, Batch Index: 2200- Eval validation - q_loss = 0.37305 , q_risk_0.1 = 0.19094 , q_risk_0.5 = 0.50848 , q_risk_0.9 = 0.23342\n",
"Evaluating test set\n",
"Epoch: 11, Batch Index: 2200- Eval test - q_loss = 0.40681 , q_risk_0.1 = 0.22408 , q_risk_0.5 = 0.55368 , q_risk_0.9 = 0.24790\n",
"Epoch: 11, Batch Index: 2200 - Train Loss = 0.397286531329155\n",
"Epoch: 11, Batch Index: 2220 - Train Loss = 0.3975470417737961\n",
"Epoch: 11, Batch Index: 2240 - Train Loss = 0.39717461585998537\n",
"Epoch: 11, Batch Index: 2260 - Train Loss = 0.3976611328125\n",
"Epoch: 11, Batch Index: 2280 - Train Loss = 0.3975683742761612\n",
"Epoch: 11, Batch Index: 2300 - Train Loss = 0.39604835510253905\n",
"Epoch: 11, Batch Index: 2320 - Train Loss = 0.39686691462993623\n",
"Epoch: 11, Batch Index: 2340 - Train Loss = 0.39791470289230346\n",
"Epoch: 11, Batch Index: 2360 - Train Loss = 0.3995424944162369\n",
"Epoch: 11, Batch Index: 2380 - Train Loss = 0.39787294566631315\n",
"Starting Epoch Index 12\n",
"Evaluating train set\n",
"Epoch: 12, Batch Index: 2400- Eval train - q_loss = 0.39626 , q_risk_0.1 = 0.22156 , q_risk_0.5 = 0.53379 , q_risk_0.9 = 0.23491\n",
"Evaluating validation set\n",
"Epoch: 12, Batch Index: 2400- Eval validation - q_loss = 0.37278 , q_risk_0.1 = 0.19257 , q_risk_0.5 = 0.50609 , q_risk_0.9 = 0.23203\n",
"Evaluating test set\n",
"Epoch: 12, Batch Index: 2400- Eval test - q_loss = 0.40521 , q_risk_0.1 = 0.22495 , q_risk_0.5 = 0.55083 , q_risk_0.9 = 0.24609\n",
"Epoch: 12, Batch Index: 2400 - Train Loss = 0.39735854625701905\n",
"Epoch: 12, Batch Index: 2420 - Train Loss = 0.397556711435318\n",
"Epoch: 12, Batch Index: 2440 - Train Loss = 0.39656793415546415\n",
"Epoch: 12, Batch Index: 2460 - Train Loss = 0.3968496644496918\n",
"Epoch: 12, Batch Index: 2480 - Train Loss = 0.39582385659217834\n",
"Epoch: 12, Batch Index: 2500 - Train Loss = 0.39432197391986845\n",
"Epoch: 12, Batch Index: 2520 - Train Loss = 0.3937902343273163\n",
"Epoch: 12, Batch Index: 2540 - Train Loss = 0.39579939663410185\n",
"Epoch: 12, Batch Index: 2560 - Train Loss = 0.39682712018489835\n",
"Epoch: 12, Batch Index: 2580 - Train Loss = 0.39822638154029844\n",
"Starting Epoch Index 13\n",
"Evaluating train set\n",
"Epoch: 13, Batch Index: 2600- Eval train - q_loss = 0.39503 , q_risk_0.1 = 0.22192 , q_risk_0.5 = 0.53106 , q_risk_0.9 = 0.23303\n",
"Evaluating validation set\n",
"Epoch: 13, Batch Index: 2600- Eval validation - q_loss = 0.37233 , q_risk_0.1 = 0.19380 , q_risk_0.5 = 0.50514 , q_risk_0.9 = 0.23063\n",
"Evaluating test set\n",
"Epoch: 13, Batch Index: 2600- Eval test - q_loss = 0.40487 , q_risk_0.1 = 0.22607 , q_risk_0.5 = 0.54981 , q_risk_0.9 = 0.24570\n",
"Epoch: 13, Batch Index: 2600 - Train Loss = 0.3985908716917038\n",
"Epoch: 13, Batch Index: 2620 - Train Loss = 0.39708409547805784\n",
"Epoch: 13, Batch Index: 2640 - Train Loss = 0.39565754354000093\n",
"Epoch: 13, Batch Index: 2660 - Train Loss = 0.39411513566970824\n",
"Epoch: 13, Batch Index: 2680 - Train Loss = 0.39422193586826326\n",
"Epoch: 13, Batch Index: 2700 - Train Loss = 0.39611084043979644\n",
"Epoch: 13, Batch Index: 2720 - Train Loss = 0.3958034712076187\n",
"Epoch: 13, Batch Index: 2740 - Train Loss = 0.3957914996147156\n",
"Epoch: 13, Batch Index: 2760 - Train Loss = 0.39552177786827086\n",
"Epoch: 13, Batch Index: 2780 - Train Loss = 0.3972522002458572\n",
"Starting Epoch Index 14\n",
"Evaluating train set\n",
"Epoch: 14, Batch Index: 2800- Eval train - q_loss = 0.39454 , q_risk_0.1 = 0.22024 , q_risk_0.5 = 0.53524 , q_risk_0.9 = 0.23390\n",
"Evaluating validation set\n",
"Epoch: 14, Batch Index: 2800- Eval validation - q_loss = 0.37213 , q_risk_0.1 = 0.18976 , q_risk_0.5 = 0.50818 , q_risk_0.9 = 0.23144\n",
"Evaluating test set\n",
"Epoch: 14, Batch Index: 2800- Eval test - q_loss = 0.40552 , q_risk_0.1 = 0.22388 , q_risk_0.5 = 0.55365 , q_risk_0.9 = 0.24705\n",
"Epoch: 14, Batch Index: 2800 - Train Loss = 0.39746993958950044\n",
"Epoch: 14, Batch Index: 2820 - Train Loss = 0.3977667087316513\n",
"Epoch: 14, Batch Index: 2840 - Train Loss = 0.39638291656970975\n",
"Epoch: 14, Batch Index: 2860 - Train Loss = 0.3958066064119339\n",
"Epoch: 14, Batch Index: 2880 - Train Loss = 0.39620551466941833\n",
"Epoch: 14, Batch Index: 2900 - Train Loss = 0.39700751841068266\n",
"Epoch: 14, Batch Index: 2920 - Train Loss = 0.39792332887649534\n",
"Epoch: 14, Batch Index: 2940 - Train Loss = 0.3981608068943024\n",
"Epoch: 14, Batch Index: 2960 - Train Loss = 0.3968786609172821\n",
"Epoch: 14, Batch Index: 2980 - Train Loss = 0.39690771281719206\n",
"Starting Epoch Index 15\n",
"Evaluating train set\n",
"Epoch: 15, Batch Index: 3000- Eval train - q_loss = 0.39590 , q_risk_0.1 = 0.22212 , q_risk_0.5 = 0.53453 , q_risk_0.9 = 0.23504\n",
"Evaluating validation set\n",
"Epoch: 15, Batch Index: 3000- Eval validation - q_loss = 0.37228 , q_risk_0.1 = 0.19195 , q_risk_0.5 = 0.50551 , q_risk_0.9 = 0.23166\n",
"Evaluating test set\n",
"Epoch: 15, Batch Index: 3000- Eval test - q_loss = 0.40615 , q_risk_0.1 = 0.22639 , q_risk_0.5 = 0.55196 , q_risk_0.9 = 0.24593\n",
"Epoch: 15, Batch Index: 3000 - Train Loss = 0.39571544885635374\n",
"Epoch: 15, Batch Index: 3020 - Train Loss = 0.3961531764268875\n",
"Epoch: 15, Batch Index: 3040 - Train Loss = 0.39620076477527616\n",
"Epoch: 15, Batch Index: 3060 - Train Loss = 0.3955254822969437\n",
"Epoch: 15, Batch Index: 3080 - Train Loss = 0.3957783627510071\n",
"Epoch: 15, Batch Index: 3100 - Train Loss = 0.39409859240055084\n",
"Epoch: 15, Batch Index: 3120 - Train Loss = 0.394546263217926\n",
"Epoch: 15, Batch Index: 3140 - Train Loss = 0.3941196483373642\n",
"Epoch: 15, Batch Index: 3160 - Train Loss = 0.3953500097990036\n",
"Epoch: 15, Batch Index: 3180 - Train Loss = 0.39435318410396575\n",
"Starting Epoch Index 16\n",
"Evaluating train set\n",
"Epoch: 16, Batch Index: 3200- Eval train - q_loss = 0.39311 , q_risk_0.1 = 0.22106 , q_risk_0.5 = 0.53087 , q_risk_0.9 = 0.23375\n",
"Evaluating validation set\n",
"Epoch: 16, Batch Index: 3200- Eval validation - q_loss = 0.36995 , q_risk_0.1 = 0.19182 , q_risk_0.5 = 0.50196 , q_risk_0.9 = 0.23022\n",
"Evaluating test set\n",
"Epoch: 16, Batch Index: 3200- Eval test - q_loss = 0.40404 , q_risk_0.1 = 0.22498 , q_risk_0.5 = 0.54958 , q_risk_0.9 = 0.24624\n",
"Epoch: 16, Batch Index: 3200 - Train Loss = 0.39327936828136445\n",
"Epoch: 16, Batch Index: 3220 - Train Loss = 0.39240858078002927\n",
"Epoch: 16, Batch Index: 3240 - Train Loss = 0.39418687641620637\n",
"Epoch: 16, Batch Index: 3260 - Train Loss = 0.3960178005695343\n",
"Epoch: 16, Batch Index: 3280 - Train Loss = 0.39683654487133024\n",
"Epoch: 16, Batch Index: 3300 - Train Loss = 0.3963241118192673\n",
"Epoch: 16, Batch Index: 3320 - Train Loss = 0.39427025318145753\n",
"Epoch: 16, Batch Index: 3340 - Train Loss = 0.39327972531318667\n",
"Epoch: 16, Batch Index: 3360 - Train Loss = 0.39355730831623076\n",
"Epoch: 16, Batch Index: 3380 - Train Loss = 0.3935112875699997\n",
"Starting Epoch Index 17\n",
"Evaluating train set\n",
"Epoch: 17, Batch Index: 3400- Eval train - q_loss = 0.39267 , q_risk_0.1 = 0.21894 , q_risk_0.5 = 0.52937 , q_risk_0.9 = 0.23373\n",
"Evaluating validation set\n",
"Epoch: 17, Batch Index: 3400- Eval validation - q_loss = 0.36965 , q_risk_0.1 = 0.18946 , q_risk_0.5 = 0.50238 , q_risk_0.9 = 0.23064\n",
"Evaluating test set\n",
"Epoch: 17, Batch Index: 3400- Eval test - q_loss = 0.40385 , q_risk_0.1 = 0.22403 , q_risk_0.5 = 0.55088 , q_risk_0.9 = 0.24741\n",
"Epoch: 17, Batch Index: 3400 - Train Loss = 0.3934555548429489\n",
"Epoch: 17, Batch Index: 3420 - Train Loss = 0.39430442929267884\n",
"Epoch: 17, Batch Index: 3440 - Train Loss = 0.394860475063324\n",
"Epoch: 17, Batch Index: 3460 - Train Loss = 0.3947139686346054\n",
"Epoch: 17, Batch Index: 3480 - Train Loss = 0.3969425678253174\n",
"Epoch: 17, Batch Index: 3500 - Train Loss = 0.39629222512245177\n",
"Epoch: 17, Batch Index: 3520 - Train Loss = 0.39453535914421084\n",
"Epoch: 17, Batch Index: 3540 - Train Loss = 0.39338121831417083\n",
"Epoch: 17, Batch Index: 3560 - Train Loss = 0.39583060920238494\n",
"Epoch: 17, Batch Index: 3580 - Train Loss = 0.3953281724452972\n",
"Starting Epoch Index 18\n",
"Evaluating train set\n",
"Epoch: 18, Batch Index: 3600- Eval train - q_loss = 0.39411 , q_risk_0.1 = 0.22071 , q_risk_0.5 = 0.53185 , q_risk_0.9 = 0.23386\n",
"Evaluating validation set\n",
"Epoch: 18, Batch Index: 3600- Eval validation - q_loss = 0.37043 , q_risk_0.1 = 0.19030 , q_risk_0.5 = 0.50372 , q_risk_0.9 = 0.23137\n",
"Evaluating test set\n",
"Epoch: 18, Batch Index: 3600- Eval test - q_loss = 0.40424 , q_risk_0.1 = 0.22493 , q_risk_0.5 = 0.54978 , q_risk_0.9 = 0.24472\n",
"Epoch: 18, Batch Index: 3600 - Train Loss = 0.3962299686670303\n",
"Epoch: 18, Batch Index: 3620 - Train Loss = 0.3964512723684311\n",
"Epoch: 18, Batch Index: 3640 - Train Loss = 0.39531580328941346\n",
"Epoch: 18, Batch Index: 3660 - Train Loss = 0.3951317095756531\n",
"Epoch: 18, Batch Index: 3680 - Train Loss = 0.39483638882637023\n",
"Epoch: 18, Batch Index: 3700 - Train Loss = 0.39424086570739747\n",
"Epoch: 18, Batch Index: 3720 - Train Loss = 0.3934622985124588\n",
"Epoch: 18, Batch Index: 3740 - Train Loss = 0.39204382538795474\n",
"Epoch: 18, Batch Index: 3760 - Train Loss = 0.39244626939296723\n",
"Epoch: 18, Batch Index: 3780 - Train Loss = 0.39162741959095\n",
"Starting Epoch Index 19\n",
"Evaluating train set\n",
"Epoch: 19, Batch Index: 3800- Eval train - q_loss = 0.39236 , q_risk_0.1 = 0.21986 , q_risk_0.5 = 0.53063 , q_risk_0.9 = 0.23303\n",
"Evaluating validation set\n",
"Epoch: 19, Batch Index: 3800- Eval validation - q_loss = 0.36917 , q_risk_0.1 = 0.19038 , q_risk_0.5 = 0.50183 , q_risk_0.9 = 0.23023\n",
"Evaluating test set\n",
"Epoch: 19, Batch Index: 3800- Eval test - q_loss = 0.40360 , q_risk_0.1 = 0.22352 , q_risk_0.5 = 0.54832 , q_risk_0.9 = 0.24480\n",
"Epoch: 19, Batch Index: 3800 - Train Loss = 0.39128984570503234\n",
"Epoch: 19, Batch Index: 3820 - Train Loss = 0.3910816216468811\n",
"Epoch: 19, Batch Index: 3840 - Train Loss = 0.3931230807304382\n",
"Epoch: 19, Batch Index: 3860 - Train Loss = 0.39342101812362673\n",
"Epoch: 19, Batch Index: 3880 - Train Loss = 0.39307539820671084\n",
"Epoch: 19, Batch Index: 3900 - Train Loss = 0.39352298736572267\n",
"Epoch: 19, Batch Index: 3920 - Train Loss = 0.39266403555870055\n",
"Epoch: 19, Batch Index: 3940 - Train Loss = 0.39387556493282316\n",
"Epoch: 19, Batch Index: 3960 - Train Loss = 0.3941167360544205\n",
"Epoch: 19, Batch Index: 3980 - Train Loss = 0.3933072590827942\n",
"Starting Epoch Index 20\n",
"Evaluating train set\n",
"Epoch: 20, Batch Index: 4000- Eval train - q_loss = 0.39171 , q_risk_0.1 = 0.21977 , q_risk_0.5 = 0.52934 , q_risk_0.9 = 0.23252\n",
"Evaluating validation set\n",
"Epoch: 20, Batch Index: 4000- Eval validation - q_loss = 0.36842 , q_risk_0.1 = 0.18975 , q_risk_0.5 = 0.49880 , q_risk_0.9 = 0.22967\n",
"Evaluating test set\n",
"Epoch: 20, Batch Index: 4000- Eval test - q_loss = 0.40268 , q_risk_0.1 = 0.22340 , q_risk_0.5 = 0.54762 , q_risk_0.9 = 0.24478\n",
"Epoch: 20, Batch Index: 4000 - Train Loss = 0.3935540908575058\n",
"Epoch: 20, Batch Index: 4020 - Train Loss = 0.3945341455936432\n",
"Epoch: 20, Batch Index: 4040 - Train Loss = 0.3948543339967728\n",
"Epoch: 20, Batch Index: 4060 - Train Loss = 0.39625866651535036\n",
"Epoch: 20, Batch Index: 4080 - Train Loss = 0.3947367179393768\n",
"Epoch: 20, Batch Index: 4100 - Train Loss = 0.3921550667285919\n",
"Epoch: 20, Batch Index: 4120 - Train Loss = 0.3913376384973526\n",
"Epoch: 20, Batch Index: 4140 - Train Loss = 0.3914654874801636\n",
"Epoch: 20, Batch Index: 4160 - Train Loss = 0.392972172498703\n",
"Epoch: 20, Batch Index: 4180 - Train Loss = 0.3916538977622986\n",
"Starting Epoch Index 21\n",
"Evaluating train set\n",
"Epoch: 21, Batch Index: 4200- Eval train - q_loss = 0.39359 , q_risk_0.1 = 0.21875 , q_risk_0.5 = 0.53450 , q_risk_0.9 = 0.23349\n",
"Evaluating validation set\n",
"Epoch: 21, Batch Index: 4200- Eval validation - q_loss = 0.36954 , q_risk_0.1 = 0.18822 , q_risk_0.5 = 0.50501 , q_risk_0.9 = 0.23005\n",
"Evaluating test set\n",
"Epoch: 21, Batch Index: 4200- Eval test - q_loss = 0.40425 , q_risk_0.1 = 0.22260 , q_risk_0.5 = 0.55251 , q_risk_0.9 = 0.24582\n",
"Epoch: 21, Batch Index: 4200 - Train Loss = 0.39065551578998564\n",
"Epoch: 21, Batch Index: 4220 - Train Loss = 0.3920184302330017\n",
"Epoch: 21, Batch Index: 4240 - Train Loss = 0.39294574737548826\n",
"Epoch: 21, Batch Index: 4260 - Train Loss = 0.3921638345718384\n",
"Epoch: 21, Batch Index: 4280 - Train Loss = 0.39221913754940035\n",
"Epoch: 21, Batch Index: 4300 - Train Loss = 0.39228733897209167\n",
"Epoch: 21, Batch Index: 4320 - Train Loss = 0.39290284991264346\n",
"Epoch: 21, Batch Index: 4340 - Train Loss = 0.39263272523880005\n",
"Epoch: 21, Batch Index: 4360 - Train Loss = 0.39253047585487366\n",
"Epoch: 21, Batch Index: 4380 - Train Loss = 0.39298843801021577\n",
"Starting Epoch Index 22\n",
"Evaluating train set\n",
"Epoch: 22, Batch Index: 4400- Eval train - q_loss = 0.39157 , q_risk_0.1 = 0.21867 , q_risk_0.5 = 0.53062 , q_risk_0.9 = 0.23265\n",
"Evaluating validation set\n",
"Epoch: 22, Batch Index: 4400- Eval validation - q_loss = 0.36894 , q_risk_0.1 = 0.18825 , q_risk_0.5 = 0.50249 , q_risk_0.9 = 0.23015\n",
"Evaluating test set\n",
"Epoch: 22, Batch Index: 4400- Eval test - q_loss = 0.40272 , q_risk_0.1 = 0.22289 , q_risk_0.5 = 0.55017 , q_risk_0.9 = 0.24553\n",
"Epoch: 22, Batch Index: 4400 - Train Loss = 0.3928170812129974\n",
"Epoch: 22, Batch Index: 4420 - Train Loss = 0.39240060448646547\n",
"Epoch: 22, Batch Index: 4440 - Train Loss = 0.39123848140239714\n",
"Epoch: 22, Batch Index: 4460 - Train Loss = 0.39128577649593355\n",
"Epoch: 22, Batch Index: 4480 - Train Loss = 0.39194220066070556\n",
"Epoch: 22, Batch Index: 4500 - Train Loss = 0.3927388870716095\n",
"Epoch: 22, Batch Index: 4520 - Train Loss = 0.3947614371776581\n",
"Epoch: 22, Batch Index: 4540 - Train Loss = 0.39322260677814486\n",
"Epoch: 22, Batch Index: 4560 - Train Loss = 0.3928615152835846\n",
"Epoch: 22, Batch Index: 4580 - Train Loss = 0.3923887598514557\n",
"Starting Epoch Index 23\n",
"Evaluating train set\n",
"Epoch: 23, Batch Index: 4600- Eval train - q_loss = 0.39578 , q_risk_0.1 = 0.21877 , q_risk_0.5 = 0.53504 , q_risk_0.9 = 0.23619\n",
"Evaluating validation set\n",
"Epoch: 23, Batch Index: 4600- Eval validation - q_loss = 0.37264 , q_risk_0.1 = 0.18828 , q_risk_0.5 = 0.50772 , q_risk_0.9 = 0.23416\n",
"Evaluating test set\n",
"Epoch: 23, Batch Index: 4600- Eval test - q_loss = 0.40778 , q_risk_0.1 = 0.22321 , q_risk_0.5 = 0.55644 , q_risk_0.9 = 0.25071\n",
"Epoch: 23, Batch Index: 4600 - Train Loss = 0.3926751935482025\n",
"Epoch: 23, Batch Index: 4620 - Train Loss = 0.3935908442735672\n",
"Epoch: 23, Batch Index: 4640 - Train Loss = 0.392884778380394\n",
"Epoch: 23, Batch Index: 4660 - Train Loss = 0.3941209644079208\n",
"Epoch: 23, Batch Index: 4680 - Train Loss = 0.39364977955818176\n",
"Epoch: 23, Batch Index: 4700 - Train Loss = 0.39289494812488557\n",
"Epoch: 23, Batch Index: 4720 - Train Loss = 0.3917523670196533\n",
"Epoch: 23, Batch Index: 4740 - Train Loss = 0.39211202681064605\n",
"Epoch: 23, Batch Index: 4760 - Train Loss = 0.3919273245334625\n",
"Epoch: 23, Batch Index: 4780 - Train Loss = 0.39112240612506866\n",
"Starting Epoch Index 24\n",
"Evaluating train set\n",
"Epoch: 24, Batch Index: 4800- Eval train - q_loss = 0.39073 , q_risk_0.1 = 0.21867 , q_risk_0.5 = 0.52852 , q_risk_0.9 = 0.23234\n",
"Evaluating validation set\n",
"Epoch: 24, Batch Index: 4800- Eval validation - q_loss = 0.36755 , q_risk_0.1 = 0.18810 , q_risk_0.5 = 0.49981 , q_risk_0.9 = 0.22989\n",
"Evaluating test set\n",
"Epoch: 24, Batch Index: 4800- Eval test - q_loss = 0.40219 , q_risk_0.1 = 0.22368 , q_risk_0.5 = 0.54789 , q_risk_0.9 = 0.24424\n",
"Epoch: 24, Batch Index: 4800 - Train Loss = 0.39104080975055694\n",
"Epoch: 24, Batch Index: 4820 - Train Loss = 0.3915447109937668\n",
"Epoch: 24, Batch Index: 4840 - Train Loss = 0.39162757694721223\n",
"Epoch: 24, Batch Index: 4860 - Train Loss = 0.391264573931694\n",
"Epoch: 24, Batch Index: 4880 - Train Loss = 0.3915964841842651\n",
"Epoch: 24, Batch Index: 4900 - Train Loss = 0.392146959900856\n",
"Epoch: 24, Batch Index: 4920 - Train Loss = 0.39214262783527376\n",
"Epoch: 24, Batch Index: 4940 - Train Loss = 0.3912676954269409\n",
"Epoch: 24, Batch Index: 4960 - Train Loss = 0.390901859998703\n",
"Epoch: 24, Batch Index: 4980 - Train Loss = 0.3914948982000351\n",
"Starting Epoch Index 25\n",
"Evaluating train set\n",
"Epoch: 25, Batch Index: 5000- Eval train - q_loss = 0.39103 , q_risk_0.1 = 0.21824 , q_risk_0.5 = 0.52878 , q_risk_0.9 = 0.23258\n",
"Evaluating validation set\n",
"Epoch: 25, Batch Index: 5000- Eval validation - q_loss = 0.36727 , q_risk_0.1 = 0.18754 , q_risk_0.5 = 0.49930 , q_risk_0.9 = 0.22967\n",
"Evaluating test set\n",
"Epoch: 25, Batch Index: 5000- Eval test - q_loss = 0.40200 , q_risk_0.1 = 0.22221 , q_risk_0.5 = 0.54803 , q_risk_0.9 = 0.24508\n",
"Epoch: 25, Batch Index: 5000 - Train Loss = 0.39295695662498475\n",
"Epoch: 25, Batch Index: 5020 - Train Loss = 0.3930238527059555\n",
"Epoch: 25, Batch Index: 5040 - Train Loss = 0.39276827991008756\n",
"Epoch: 25, Batch Index: 5060 - Train Loss = 0.39349680066108705\n",
"Epoch: 25, Batch Index: 5080 - Train Loss = 0.39223547756671906\n",
"Epoch: 25, Batch Index: 5100 - Train Loss = 0.39093770444393156\n",
"Epoch: 25, Batch Index: 5120 - Train Loss = 0.3900302243232727\n",
"Epoch: 25, Batch Index: 5140 - Train Loss = 0.3915100681781769\n",
"Epoch: 25, Batch Index: 5160 - Train Loss = 0.39345851361751555\n",
"Epoch: 25, Batch Index: 5180 - Train Loss = 0.39556327760219573\n",
"Starting Epoch Index 26\n",
"Evaluating train set\n",
"Epoch: 26, Batch Index: 5200- Eval train - q_loss = 0.39117 , q_risk_0.1 = 0.21851 , q_risk_0.5 = 0.52961 , q_risk_0.9 = 0.23249\n",
"Evaluating validation set\n",
"Epoch: 26, Batch Index: 5200- Eval validation - q_loss = 0.36806 , q_risk_0.1 = 0.18893 , q_risk_0.5 = 0.50076 , q_risk_0.9 = 0.22973\n",
"Evaluating test set\n",
"Epoch: 26, Batch Index: 5200- Eval test - q_loss = 0.40395 , q_risk_0.1 = 0.22472 , q_risk_0.5 = 0.54988 , q_risk_0.9 = 0.24445\n",
"Epoch: 26, Batch Index: 5200 - Train Loss = 0.39528673231601713\n",
"Epoch: 26, Batch Index: 5220 - Train Loss = 0.3938353776931763\n",
"Epoch: 26, Batch Index: 5240 - Train Loss = 0.3929093545675278\n",
"Epoch: 26, Batch Index: 5260 - Train Loss = 0.393796883225441\n",
"Epoch: 26, Batch Index: 5280 - Train Loss = 0.3937105721235275\n",
"Epoch: 26, Batch Index: 5300 - Train Loss = 0.3911102694272995\n",
"Epoch: 26, Batch Index: 5320 - Train Loss = 0.39100204229354857\n",
"Epoch: 26, Batch Index: 5340 - Train Loss = 0.3912016826868057\n",
"Epoch: 26, Batch Index: 5360 - Train Loss = 0.3917206537723541\n",
"Epoch: 26, Batch Index: 5380 - Train Loss = 0.39080328583717344\n",
"Starting Epoch Index 27\n",
"Evaluating train set\n",
"Epoch: 27, Batch Index: 5400- Eval train - q_loss = 0.39265 , q_risk_0.1 = 0.21775 , q_risk_0.5 = 0.53054 , q_risk_0.9 = 0.23295\n",
"Evaluating validation set\n",
"Epoch: 27, Batch Index: 5400- Eval validation - q_loss = 0.37037 , q_risk_0.1 = 0.18791 , q_risk_0.5 = 0.50539 , q_risk_0.9 = 0.23140\n",
"Evaluating test set\n",
"Epoch: 27, Batch Index: 5400- Eval test - q_loss = 0.40449 , q_risk_0.1 = 0.22310 , q_risk_0.5 = 0.55233 , q_risk_0.9 = 0.24602\n",
"Epoch: 27, Batch Index: 5400 - Train Loss = 0.3907390028238297\n",
"Epoch: 27, Batch Index: 5420 - Train Loss = 0.391916623711586\n",
"Epoch: 27, Batch Index: 5440 - Train Loss = 0.39387652039527893\n",
"Epoch: 27, Batch Index: 5460 - Train Loss = 0.3932059967517853\n",
"Epoch: 27, Batch Index: 5480 - Train Loss = 0.39354217767715455\n",
"Epoch: 27, Batch Index: 5500 - Train Loss = 0.3938298052549362\n",
"Epoch: 27, Batch Index: 5520 - Train Loss = 0.39483376502990725\n",
"Epoch: 27, Batch Index: 5540 - Train Loss = 0.39367376029491424\n",
"Epoch: 27, Batch Index: 5560 - Train Loss = 0.39227177858352663\n",
"Epoch: 27, Batch Index: 5580 - Train Loss = 0.3912710964679718\n",
"Starting Epoch Index 28\n",
"Evaluating train set\n",
"Epoch: 28, Batch Index: 5600- Eval train - q_loss = 0.39010 , q_risk_0.1 = 0.21711 , q_risk_0.5 = 0.52652 , q_risk_0.9 = 0.23247\n",
"Evaluating validation set\n",
"Epoch: 28, Batch Index: 5600- Eval validation - q_loss = 0.36690 , q_risk_0.1 = 0.18706 , q_risk_0.5 = 0.49793 , q_risk_0.9 = 0.22968\n",
"Evaluating test set\n",
"Epoch: 28, Batch Index: 5600- Eval test - q_loss = 0.40209 , q_risk_0.1 = 0.22186 , q_risk_0.5 = 0.54638 , q_risk_0.9 = 0.24374\n",
"Epoch: 28, Batch Index: 5600 - Train Loss = 0.39116894245147704\n",
"Epoch: 28, Batch Index: 5620 - Train Loss = 0.39049896657466887\n",
"Epoch: 28, Batch Index: 5640 - Train Loss = 0.39136357307434083\n",
"Epoch: 28, Batch Index: 5660 - Train Loss = 0.3927433145046234\n",
"Epoch: 28, Batch Index: 5680 - Train Loss = 0.3914398127794266\n",
"Epoch: 28, Batch Index: 5700 - Train Loss = 0.3910479825735092\n",
"Epoch: 28, Batch Index: 5720 - Train Loss = 0.39200413167476655\n",
"Epoch: 28, Batch Index: 5740 - Train Loss = 0.3924363601207733\n",
"Epoch: 28, Batch Index: 5760 - Train Loss = 0.3915549123287201\n",
"Epoch: 28, Batch Index: 5780 - Train Loss = 0.3906639659404755\n",
"Starting Epoch Index 29\n",
"Evaluating train set\n",
"Epoch: 29, Batch Index: 5800- Eval train - q_loss = 0.39020 , q_risk_0.1 = 0.21734 , q_risk_0.5 = 0.52575 , q_risk_0.9 = 0.23267\n",
"Evaluating validation set\n",
"Epoch: 29, Batch Index: 5800- Eval validation - q_loss = 0.36615 , q_risk_0.1 = 0.18721 , q_risk_0.5 = 0.49772 , q_risk_0.9 = 0.22981\n",
"Evaluating test set\n",
"Epoch: 29, Batch Index: 5800- Eval test - q_loss = 0.40220 , q_risk_0.1 = 0.22248 , q_risk_0.5 = 0.54862 , q_risk_0.9 = 0.24761\n",
"Epoch: 29, Batch Index: 5800 - Train Loss = 0.39212010741233827\n",
"Epoch: 29, Batch Index: 5820 - Train Loss = 0.39072294294834137\n",
"Epoch: 29, Batch Index: 5840 - Train Loss = 0.39052855253219604\n",
"Epoch: 29, Batch Index: 5860 - Train Loss = 0.39218976140022277\n",
"Epoch: 29, Batch Index: 5880 - Train Loss = 0.3931941443681717\n",
"Epoch: 29, Batch Index: 5900 - Train Loss = 0.393218988776207\n",
"Epoch: 29, Batch Index: 5920 - Train Loss = 0.39163510739803314\n",
"Epoch: 29, Batch Index: 5940 - Train Loss = 0.3915703827142715\n",
"Epoch: 29, Batch Index: 5960 - Train Loss = 0.3931459194421768\n",
"Epoch: 29, Batch Index: 5980 - Train Loss = 0.3931496340036392\n",
"Starting Epoch Index 30\n",
"Evaluating train set\n",
"Epoch: 30, Batch Index: 6000- Eval train - q_loss = 0.39057 , q_risk_0.1 = 0.21825 , q_risk_0.5 = 0.52727 , q_risk_0.9 = 0.23261\n",
"Evaluating validation set\n",
"Epoch: 30, Batch Index: 6000- Eval validation - q_loss = 0.36738 , q_risk_0.1 = 0.18919 , q_risk_0.5 = 0.49924 , q_risk_0.9 = 0.22976\n",
"Evaluating test set\n",
"Epoch: 30, Batch Index: 6000- Eval test - q_loss = 0.40191 , q_risk_0.1 = 0.22286 , q_risk_0.5 = 0.54679 , q_risk_0.9 = 0.24536\n",
"Epoch: 30, Batch Index: 6000 - Train Loss = 0.3902744472026825\n",
"Epoch: 30, Batch Index: 6020 - Train Loss = 0.3907164472341538\n",
"Epoch: 30, Batch Index: 6040 - Train Loss = 0.39019503772258757\n",
"Epoch: 30, Batch Index: 6060 - Train Loss = 0.3909304445981979\n",
"Epoch: 30, Batch Index: 6080 - Train Loss = 0.3915932935476303\n",
"Epoch: 30, Batch Index: 6100 - Train Loss = 0.3912838155031204\n",
"Epoch: 30, Batch Index: 6120 - Train Loss = 0.39170918226242063\n",
"Epoch: 30, Batch Index: 6140 - Train Loss = 0.3924876689910889\n",
"Epoch: 30, Batch Index: 6160 - Train Loss = 0.39197428166866305\n",
"Epoch: 30, Batch Index: 6180 - Train Loss = 0.3910445886850357\n",
"Starting Epoch Index 31\n",
"Evaluating train set\n",
"Epoch: 31, Batch Index: 6200- Eval train - q_loss = 0.38975 , q_risk_0.1 = 0.21851 , q_risk_0.5 = 0.52767 , q_risk_0.9 = 0.23239\n",
"Evaluating validation set\n",
"Epoch: 31, Batch Index: 6200- Eval validation - q_loss = 0.36598 , q_risk_0.1 = 0.18756 , q_risk_0.5 = 0.49667 , q_risk_0.9 = 0.22891\n",
"Evaluating test set\n",
"Epoch: 31, Batch Index: 6200- Eval test - q_loss = 0.40154 , q_risk_0.1 = 0.22225 , q_risk_0.5 = 0.54562 , q_risk_0.9 = 0.24451\n",
"Epoch: 31, Batch Index: 6200 - Train Loss = 0.3908955878019333\n",
"Epoch: 31, Batch Index: 6220 - Train Loss = 0.3918736004829407\n",
"Epoch: 31, Batch Index: 6240 - Train Loss = 0.39150700986385345\n",
"Epoch: 31, Batch Index: 6260 - Train Loss = 0.39203780233860014\n",
"Epoch: 31, Batch Index: 6280 - Train Loss = 0.3901748996973038\n",
"Epoch: 31, Batch Index: 6300 - Train Loss = 0.38915141344070436\n",
"Epoch: 31, Batch Index: 6320 - Train Loss = 0.39070659518241885\n",
"Epoch: 31, Batch Index: 6340 - Train Loss = 0.3905073881149292\n",
"Epoch: 31, Batch Index: 6360 - Train Loss = 0.3902280455827713\n",
"Epoch: 31, Batch Index: 6380 - Train Loss = 0.3916871452331543\n",
"Starting Epoch Index 32\n",
"Evaluating train set\n",
"Epoch: 32, Batch Index: 6400- Eval train - q_loss = 0.38995 , q_risk_0.1 = 0.21762 , q_risk_0.5 = 0.52858 , q_risk_0.9 = 0.23154\n",
"Evaluating validation set\n",
"Epoch: 32, Batch Index: 6400- Eval validation - q_loss = 0.36668 , q_risk_0.1 = 0.18702 , q_risk_0.5 = 0.49939 , q_risk_0.9 = 0.22871\n",
"Evaluating test set\n",
"Epoch: 32, Batch Index: 6400- Eval test - q_loss = 0.40167 , q_risk_0.1 = 0.22138 , q_risk_0.5 = 0.54762 , q_risk_0.9 = 0.24413\n",
"Epoch: 32, Batch Index: 6400 - Train Loss = 0.39202110826969144\n",
"Epoch: 32, Batch Index: 6420 - Train Loss = 0.39096222519874574\n",
"Epoch: 32, Batch Index: 6440 - Train Loss = 0.39030987441539766\n",
"Epoch: 32, Batch Index: 6460 - Train Loss = 0.3898254519701004\n",
"Epoch: 32, Batch Index: 6480 - Train Loss = 0.39056360721588135\n",
"Epoch: 32, Batch Index: 6500 - Train Loss = 0.39097073435783386\n",
"Epoch: 32, Batch Index: 6520 - Train Loss = 0.3911157739162445\n",
"Epoch: 32, Batch Index: 6540 - Train Loss = 0.391190242767334\n",
"Epoch: 32, Batch Index: 6560 - Train Loss = 0.39081517279148104\n",
"Epoch: 32, Batch Index: 6580 - Train Loss = 0.38984852373600004\n",
"Starting Epoch Index 33\n",
"Evaluating train set\n",
"Epoch: 33, Batch Index: 6600- Eval train - q_loss = 0.38943 , q_risk_0.1 = 0.21677 , q_risk_0.5 = 0.52403 , q_risk_0.9 = 0.23132\n",
"Evaluating validation set\n",
"Epoch: 33, Batch Index: 6600- Eval validation - q_loss = 0.36607 , q_risk_0.1 = 0.18704 , q_risk_0.5 = 0.49742 , q_risk_0.9 = 0.22981\n",
"Evaluating test set\n",
"Epoch: 33, Batch Index: 6600- Eval test - q_loss = 0.40122 , q_risk_0.1 = 0.22210 , q_risk_0.5 = 0.54654 , q_risk_0.9 = 0.24553\n",
"Epoch: 33, Batch Index: 6600 - Train Loss = 0.39000167965888977\n",
"Epoch: 33, Batch Index: 6620 - Train Loss = 0.38943089842796325\n",
"Epoch: 33, Batch Index: 6640 - Train Loss = 0.39088996946811677\n",
"Epoch: 33, Batch Index: 6660 - Train Loss = 0.3900245302915573\n",
"Epoch: 33, Batch Index: 6680 - Train Loss = 0.3895224344730377\n",
"Epoch: 33, Batch Index: 6700 - Train Loss = 0.38981278002262115\n",
"Epoch: 33, Batch Index: 6720 - Train Loss = 0.38963438451290133\n",
"Epoch: 33, Batch Index: 6740 - Train Loss = 0.39057372629642484\n",
"Epoch: 33, Batch Index: 6760 - Train Loss = 0.3902643966674805\n",
"Epoch: 33, Batch Index: 6780 - Train Loss = 0.3898572677373886\n",
"Starting Epoch Index 34\n",
"Evaluating train set\n",
"Epoch: 34, Batch Index: 6800- Eval train - q_loss = 0.39050 , q_risk_0.1 = 0.21721 , q_risk_0.5 = 0.52811 , q_risk_0.9 = 0.23194\n",
"Evaluating validation set\n",
"Epoch: 34, Batch Index: 6800- Eval validation - q_loss = 0.36954 , q_risk_0.1 = 0.18786 , q_risk_0.5 = 0.50398 , q_risk_0.9 = 0.23089\n",
"Evaluating test set\n",
"Epoch: 34, Batch Index: 6800- Eval test - q_loss = 0.40233 , q_risk_0.1 = 0.22209 , q_risk_0.5 = 0.54882 , q_risk_0.9 = 0.24447\n",
"Epoch: 34, Batch Index: 6800 - Train Loss = 0.3901339966058731\n",
"Epoch: 34, Batch Index: 6820 - Train Loss = 0.390858815908432\n",
"Epoch: 34, Batch Index: 6840 - Train Loss = 0.3913135600090027\n",
"Epoch: 34, Batch Index: 6860 - Train Loss = 0.3918037086725235\n",
"Epoch: 34, Batch Index: 6880 - Train Loss = 0.3909101969003677\n",
"Epoch: 34, Batch Index: 6900 - Train Loss = 0.3903788596391678\n",
"Epoch: 34, Batch Index: 6920 - Train Loss = 0.3911781603097916\n",
"Epoch: 34, Batch Index: 6940 - Train Loss = 0.3906527698040009\n",
"Epoch: 34, Batch Index: 6960 - Train Loss = 0.39001287817955016\n",
"Epoch: 34, Batch Index: 6980 - Train Loss = 0.3880264741182327\n",
"Starting Epoch Index 35\n",
"Evaluating train set\n",
"Epoch: 35, Batch Index: 7000- Eval train - q_loss = 0.39028 , q_risk_0.1 = 0.22122 , q_risk_0.5 = 0.52642 , q_risk_0.9 = 0.23083\n",
"Evaluating validation set\n",
"Epoch: 35, Batch Index: 7000- Eval validation - q_loss = 0.36812 , q_risk_0.1 = 0.19225 , q_risk_0.5 = 0.49813 , q_risk_0.9 = 0.22896\n",
"Evaluating test set\n",
"Epoch: 35, Batch Index: 7000- Eval test - q_loss = 0.40325 , q_risk_0.1 = 0.22655 , q_risk_0.5 = 0.54788 , q_risk_0.9 = 0.24391\n",
"Epoch: 35, Batch Index: 7000 - Train Loss = 0.3893417567014694\n",
"Epoch: 35, Batch Index: 7020 - Train Loss = 0.39094632387161254\n",
"Epoch: 35, Batch Index: 7040 - Train Loss = 0.3901081711053848\n",
"Epoch: 35, Batch Index: 7060 - Train Loss = 0.3909002935886383\n",
"Epoch: 35, Batch Index: 7080 - Train Loss = 0.38972910821437834\n",
"Epoch: 35, Batch Index: 7100 - Train Loss = 0.39056070685386657\n",
"Epoch: 35, Batch Index: 7120 - Train Loss = 0.3917739289999008\n",
"Epoch: 35, Batch Index: 7140 - Train Loss = 0.39201636493206027\n",
"Epoch: 35, Batch Index: 7160 - Train Loss = 0.39356399834156036\n",
"Epoch: 35, Batch Index: 7180 - Train Loss = 0.3922375839948654\n",
"Starting Epoch Index 36\n",
"Evaluating train set\n",
"Epoch: 36, Batch Index: 7200- Eval train - q_loss = 0.38957 , q_risk_0.1 = 0.21744 , q_risk_0.5 = 0.52563 , q_risk_0.9 = 0.23092\n",
"Evaluating validation set\n",
"Epoch: 36, Batch Index: 7200- Eval validation - q_loss = 0.36618 , q_risk_0.1 = 0.18797 , q_risk_0.5 = 0.49785 , q_risk_0.9 = 0.22884\n",
"Evaluating test set\n",
"Epoch: 36, Batch Index: 7200- Eval test - q_loss = 0.40127 , q_risk_0.1 = 0.22190 , q_risk_0.5 = 0.54540 , q_risk_0.9 = 0.24297\n",
"Performing early stopping...!\n"
]
}
],
"source": [
"while epoch_idx < max_epochs:\n",
" print(f\"Starting Epoch Index {epoch_idx}\")\n",
"\n",
" # evaluation round\n",
" model.eval()\n",
" with torch.no_grad():\n",
" # for each subset\n",
" for subset_name, subset_loader in zip(['train','validation','test'],[train_loader,validation_loader,test_loader]):\n",
" print(f\"Evaluating {subset_name} set\")\n",
"\n",
" q_loss_vals, q_risk_vals = [],[] # used for aggregating performance along the evaluation round\n",
" for _ in range(eval_iters):\n",
" # get batch\n",
" batch = next(subset_loader)\n",
" # process batch\n",
" batch_loss,batch_q_risk = process_batch(batch=batch,model=model,quantiles_tensor=quantiles_tensor,device=device)\n",
" # accumulate performance\n",
" q_loss_vals.append(batch_loss)\n",
" q_risk_vals.append(batch_q_risk)\n",
"\n",
" # aggregate and average\n",
" eval_loss = torch.stack(q_loss_vals).mean(axis=0)\n",
" eval_q_risk = torch.stack(q_risk_vals,axis=0).mean(axis=0)\n",
"\n",
" # keep for feeding the early stopping mechanism\n",
" if subset_name == 'validation':\n",
" validation_loss = eval_loss\n",
"\n",
" # log performance\n",
" print(f\"Epoch: {epoch_idx}, Batch Index: {batch_idx}\" + \\\n",
" f\"- Eval {subset_name} - \" + \\\n",
" f\"q_loss = {eval_loss:.5f} , \" + \\\n",
" \" , \".join([f\"q_risk_{q:.1} = {risk:.5f}\" for q,risk in zip(quantiles_tensor,eval_q_risk)]))\n",
"\n",
" # switch to training mode\n",
" model.train()\n",
"\n",
" # update early stopping mechanism and stop if triggered\n",
" if es.step(validation_loss):\n",
" print('Performing early stopping...!')\n",
" break\n",
"\n",
" # initiating a training round\n",
" for _ in range(epoch_iters):\n",
" # get training batch\n",
" batch = next(train_loader)\n",
"\n",
" opt.zero_grad()\n",
" # process batch\n",
" loss,_ = process_batch(batch=batch,\n",
" model=model,\n",
" quantiles_tensor=quantiles_tensor,\n",
" device=device)\n",
" # compute gradients\n",
" loss.backward()\n",
" # gradient clipping\n",
" if configuration['optimization']['max_grad_norm'] > 0:\n",
" nn.utils.clip_grad_norm_(model.parameters(), configuration['optimization']['max_grad_norm'])\n",
" # update weights\n",
" opt.step()\n",
"\n",
" # accumulate performance\n",
" loss_aggregator.append(loss.item())\n",
"\n",
" # log performance\n",
" if batch_idx % log_interval == 0:\n",
" print(f\"Epoch: {epoch_idx}, Batch Index: {batch_idx} - Train Loss = {np.mean(loss_aggregator.get())}\")\n",
"\n",
" # completed batch\n",
" batch_idx += 1\n",
"\n",
" # completed epoch\n",
" epoch_idx += 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Explore Model Outputs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"After training the model, we can use it and its outputs for a better understanding of its performance, and for trying to explain its estimations. That is what will be demonstrated in this tutorial, using the module ``tft_torch.tft_vis``. \n",
"We will rely on the dataset we produced on the dataset creation tutorial and on the model we trained in the model training tutorial."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"import tft_torch.visualize as tft_vis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Apply the model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For collecting the outputs of the model, we'll first run inference on the validation subset. \n",
"Here we use the serial data loader assigned above:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|āāāāāāāāāā| 30/30 [00:10<00:00, 2.74it/s]\n"
]
}
],
"source": [
"model.eval() # switch to evaluation mode\n",
"\n",
"output_aggregator = dict() # will be used for aggregating the outputs across batches\n",
"\n",
"with torch.no_grad():\n",
" # go over the batches of the serial data loader\n",
" for batch in tqdm(validation_serial_loader):\n",
" # process each batch\n",
" if is_cuda:\n",
" for k in list(batch.keys()):\n",
" batch[k] = batch[k].to(device)\n",
" batch_outputs = model(batch)\n",
"\n",
" # accumulate outputs, as well as labels\n",
" for output_key,output_tensor in batch_outputs.items():\n",
" output_aggregator.setdefault(output_key,[]).append(output_tensor.cpu().numpy())\n",
" output_aggregator.setdefault('target',[]).append(batch['target'].cpu().numpy())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"and then stack the outpus from all the batches:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"validation_outputs = dict()\n",
"for k in list(output_aggregator.keys()):\n",
" validation_outputs[k] = np.concatenate(output_aggregator[k],axis=0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's say the subset we're working with includes $N$ observations, and each observation consists of:\n",
"\n",
"- a historical time-series that includes $m_{historical}$ temporal variables, spanning $T_{past}$ past time-steps. \n",
"\n",
"- a *futuristic* time-series including $m_{future}$ temporal variables, spanning $T_{fut}$ futuristic time-steps. \n",
"\n",
"- a set of $m_{static}$ static variables. \n",
"\n",
"In addition, let's assume that the model is configured to estimate $d_q$ different quantiles.\n",
"\n",
"In such case the outputs of the model will be as follows:\n",
"\n",
"- ``predicted_quantiles`` - the model quantile estimates for each temporal future step, shaped as $[N \\times T_{fut} \\times d_q]$. \n",
"\n",
"- ``static_weights`` - the selection weights associated with the static variables for each observation, shaped as $[N \\times m_{static}]$. \n",
"\n",
"- ``historical_selection_weights`` - the selection weights associated with the historical temporal variables, for each observation, and past time-step, shaped as $[N \\times T_{past} \\times m_{historical}]$. \n",
"\n",
"- ``future_selection_weights`` - the selection weights associated with the future temporal variables, for each observation, and future time-step, shaped as $[N \\times T_{fut} \\times m_{future}]$. \n",
"\n",
"- ``attention_scores`` - the attention score each future time-step associates which each other time-step, for each observation, shaped as $[N \\times T_{fut} \\times (T_{past} + T_{fut})]$. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Some of the illustrations below will refer to a single observation (sample-level), and some will perform aggregation of the outputs for the entire subset data. \n",
"For that matter, we'll arbitrarily set an index indicating the sample/record that will be used for the demonstration of the sample-level illustrations:"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"chosen_idx = 42421"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Target Signal Trajectory"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On this section we'll extract the historical sequence associated with the target variable, for the specific observation chosen, together with the futuristic label (the future target), and the predicted quantiles output by the model."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"# the name of the target signal\n",
"target_signal = 'log_sales'\n",
"# its relative index among the set of historical numeric input variables\n",
"target_var_index = feature_map['historical_ts_numeric'].index(target_signal)\n",
"# the quantiles estimated by the trained model\n",
"model_quantiles = configuration['model']['output_quantiles']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The trajectory can be viewed in two different scales: \n",
"Our first view will refer to the normalized scale. \n",
"Recall that before feeding the data to the model, all of our input variables were scaled or encoded. because the target signal was scaled as well, the outputs of the model are also designated to estimate the target signal according to this \"*new*\" normalized scale.\n",
"\n",
"In the follwing chart we can see:\n",
"- on the left: the historical values of the target variable.\n",
"- dashed line separating past and future.\n",
"- on the right: (solid) future target variable - what the model aims to predict\n",
"- on the right: (dashed) dashed lines associated with the predicted quantiles (see legend)\n",
"- on the right: a colored sleeve between and the lower and upper quantiles; can be seen as the uncertainty sleeve for each horizon."
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tft_vis.display_target_trajectory(signal_history=data['data_sets']['validation']['historical_ts_numeric'][...,target_var_index],\n",
" signal_future=validation_outputs['target'],\n",
" model_preds=validation_outputs['predicted_quantiles'],\n",
" observation_index=chosen_idx,\n",
" model_quantiles=model_quantiles,\n",
" unit='Days')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"However, in some cases we would like to observe the actual scale of the target variable. \n",
"For that matter, the method we're using, ``tft_vis.display_target_trajectory()`` optionally accepts also the input argument ``transformation`` , which can be used for scaling back the target variable to its original scale. \n",
"\n",
"In our use case, the target variable went through a log-transform ($log_{10}(1+x)$), and then scaled using the scaler we saved along with the data. We use this to formulate the inverse scaling, and *send* this transformation to the visualization utility."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"def scale_back(scaler_obj,signal):\n",
" inv_trans = scaler_obj.inverse_transform(copy.deepcopy(signal))\n",
" return np.power(10,inv_trans) - 1\n",
"transform_back = partial(scale_back,data['scalers']['numeric'][target_signal])"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAABXoAAAFCCAYAAABPUGXSAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd3iUZdb48e89LZPeE0JviqCi2FBRxLKIHXRtq6+ia3u32V113V13XcuK/uxb9HVFXSyoCKKrqKuAiKIogkovoSQhpEx6pt+/P57MZCYzk2RSSDuf65orM0+9ZzL1POc5R2mtEUIIIYQQQgghhBBCCNF3mXp6AEIIIYQQQgghhBBCCCE6RwK9QgghhBBCCCGEEEII0cdJoFcIIYQQQgghhBBCCCH6OAn0CiGEEEIIIYQQQgghRB8ngV4hhBBCCCGEEEIIIYTo4yTQK4QQQgghhBBCCCGEEH2cpacH0Bfk5OTokSNH9vQwRD9UX19PcnJyTw9DiF5NXidCtE1eJ0K0TV4nQrSt5eukuLg4eH3w4ME9MSQheh35PBE97ZtvvinXWudGmyeB3nYYOXIkq1ev7ulhiH5o6dKlTJs2raeHIUSvJq8TIdomrxMh2iavEyHa1vJ1opQKXg8N+goxkMnniehpSqmdseZJ6QYhhBBCCCGEEEIIIYTo4yTQK4QQQgghhBBCCCGEEH2cBHqFEEIIIYQQQgghhBCij5NArxBCCCGEEEIIIYQQQvRxEugVQgghhBBCCCGEEEKIPk4CvUIIIYQQQgghhBBCCNHHWXp6AKL/WrimiDlLNlFc1cjgjERuP30cMycN6elhCSGEEEIIIYQQQgjR70igV3SLhWuKuGvB9zR6fAAUVTVy14LvASTYK4QQQgghhBBCCCFEF5PSDaJbzFmyKRjkDWj0+JizZFMPjUgIIYQQQgghhBBCiP5LMnpFtyiuaoxruhBCCCGEEEKI3kVr3dNDEEIIEQcJ9HYTv9+Pw+Ggrq4Op9OJ3+/v6SHtV/+aORivP/JLgcWk2LBhQw+MqHdKT0+XxyMOZrOZ1NRUsrKySEhI6OnhCCGEEEIIIYQQQvQaEujtBl6vl927d2OxWMjKyiIpKQmTyYRSqqeHtt8ManCzx9EYdgTYpBRDMhPJTLL14Mh6l9raWlJTU3t6GH2C1hqPx0NNTQ27du1i+PDhEuwVQgghhBBCCCGEaCKB3m5QWVlJQkICBQUFAyq4GyozyUZNg4dqpyc4bUiGBHlFxymlsNls5OTkAMbrrKCgoIdHJYQQQgghhBBCCNE7SDO2blBdXU12dvaADfIGWCzhT69UuxxXEF0jLS2N2tranh6GEEIIIYQQ/do333wTvAghhOj9JPLWDbxeLzabZK76fOE1er1+jcXcQ4MR/YrVasXn8/X0MIQQQgghhOjXjjrqqOB1acwmhBC9n2T0dpOBns0L4G3RgM4XpTmbEB0hry8hhBBCCCGEEEKIcBLoFd2mZWBXAr1CCCGEEEIIIYQQQnQPCfSKbiOBXiGEEEIIIYQQQggh9g8J9Ipu45VArxBCCCGEEEIIIYQQ+4UEekW38GuNv0Wxfp8U7xdCCCGEEEIIIYQQoltIoFd0i2jZu92V0VtYWIhSShp07QcjR45EKcXSpUt7eihCCCGEEEIIIYQQIoQEekW3aFm2IdY0IYQQQgghhBBCCCFE50mgV3QLn2//ZfQKIYQQQgghhBBCCDHQSaBXdAuf3x9lmgR6hRBCCCGEEEIIIYToDpaeHoDon6KVaZBArxBCCCGEEEL0HQUFBd27g3Xz4b9/huo9kD4UTv0DTLyoe/cphBD9mGT0im7R2WZsCxYsYMaMGeTm5pKQkMDQoUO57LLL+Pbbb9tc9/PPP+fss88mNzeXpKQkDj/8cJ5++mn8UbKMAdxuN0888QTHH388GRkZWK1W8vPzOeyww/jlL3/JF198EXO9p59+mhNPPJGsrCwSEhIYMWIEV199NRs2bIi6zuzZs1FKce+99+JyuZgzZw4TJ04kNTUVpRR79+4lLS0NpRTvvvtuq/fzoIMOQinFE088ETGvrq6OBx54gKOPPpr09HTsdjsHHHAAv/nNb9i9e3er2503bx7HHnssKSkpZGVlccopp/Dee++1uo4QQgghhBCi/ykuLg5euty6+bD4N1C9G9DG38W/MaYLIYToEMnoFd0ieqDXj9YapVTM9fx+P1dddRUvvfQSAGazmdTUVIqKinjllVd47bXXePrpp/nf//3fqOu/9dZbXHLJJXi9XjIyMvB4PKxdu5Zf//rX/Pe//+WNN97AYml+2nu9XqZPn86yZcsAUEqRnp5ORUUF+/btY926dVRUVHDccceF7aekpIQzzjiDtWvXAmAymUhOTmbXrl288MILvPrqq8ybN4/zzz8/6jidTidTp07lq6++wmq1kpSUBIDdbmfWrFm89NJLvPLKK5x99tlR1//222/ZtGkTZrOZiy++OGzehg0bOOOMM9i5cycAFouFhIQEtm7dylNPPcW///1vFi9ezJQpUyK2+6tf/YpnnnkmeJ+sVitLly7l008/jRpQFkIIIYQQQogO+e+fwdMYPs3TaEyXrF4hhOgQyejthxauKWLKQ58w6s73mPLQJyxcU7TfxxCtdIMG/Lr1rN6HH36Yl156CaUU9913Hw6HA4fDwZ49e7jwwgvx+/386le/Yvny5VHX//nPf85pp53G9u3bcTgcVFVV8fDDD2MymVi4cCEPP/xw2PKvvPIKy5YtIykpiZdffpmGhgYcDgcul4udO3fy9NNPc9hhh4Wt4/F4OO+881i7di2nnnoqK1euxOl0UlNTQ3FxMTfddBNOp5P/+Z//Ydu2bVHH+cwzz7B582ZeeOEF6urqqKqqorCwkOTkZH72s58B8M4779DQ0BB1/VdffRWAk08+mUGDBgWnV1dXc+aZZ7Jz504uvPBC1q5di9PppK6ujm3btvGzn/0Mh8PBBRdcQFVVVdg2582bFwzy3nbbbVRUVOBwOCgpKeGKK67gtttuo6ysLMZ/TgghhBBCCCHiUL0nvulCCCHaJIHefmbhmiLuWvA9RVWNaKCoqpG7Fny/34O9sco0tFa+oa6ujgcffBCA3/72t9xzzz2kpqYCMGTIEF599VVOOOEE/H4/99xzT9RtDB06lIULFzJq1CgAkpOTuf322/n9738PwF//+tew4OmXX34JwBVXXMHll1+O3W4HjEzi4cOH88tf/pK77rorbB8vvvgiX3/9NSeeeCLvv/8+xx13HFarFTBqWD322GNcf/31NDQ08Nhjj8W8r6+//joXXHABNpsNgBEjRmC1WjnttNPIy8ujvr6eRYsWRayrteb1118HCAaFA+bMmUNhYSGXXnop8+fPZ+LEiZjNZgBGjx7NvHnzmDFjBqWlpfzf//1f2Db/+Mc/AnDllVcyZ84cMjIyAMjPz2fu3LmcdNJJMQPPQgghhBBCCBGX9KHxTRdCCNEmKd3QQ0beuf9qnjZ6fNz0+nfc9Pp33bL9wofOipgWLaM3MN0WYzsfffQRNTU12Gw27rjjjoj5ZrOZ3//+95x++ul89tln7N27NyybFeDWW28lISEhYt1bbrmFv/71r9TU1PDhhx8yc+ZMANLS0gCjFEN7vfjiiwDceOONwQBvS5dddhn//Oc/+eijj6LOnzhxItOnT6e2tjbq/bzooot4+umnefXVV7n00kvD5q9YsYLdu3djt9sjSkMExnbrrbfGHP/PfvYzPvjgAz766CNuu+02AL777rtg9nHLwDYYJS3uvvtuPv7445jbFUIIIYQQQvQvixcvDl4/55xzunbjp/4B3vkVeF3N0ywJxnQhhBAdIhm9oluEZu5aTKao01sKNFo77LDDyMzMjLrM1KlTgxmq0RqzTZs2Lep6aWlpTJo0KWK9M844A4BFixZx7rnnsmDBAioqKmKO0ev18tVXXwFw/fXXM2jQoKiXQAA2VuOzljV/Wwpk6i5ZsoTKysqwea+88goAZ555Junp6cHpu3fvZs+ePcF5scZ24403Rowt8Jjk5+czbty4qGM6/vjjw+obCyGEEEIIIfq3c889N3jpchMvguN+HT7tmBukPq8QQnSCBHpFtwgN6CZY2hfoDdR/HTJkSMxl7HY7OTk5YcuHam3dwLzQ9U466ST+/Oc/Y7FYWLx4MRdccAE5OTmMHz+e2267jS1btoRto7KyErfbDUBFRQWlpaVRL+Xl5QA0NrZoLtAkNzc35jjBCASPGjUKt9vNW2+9FZzu9Xp58803gciyDaFZyfv27Ys5NofDARBWhiHwmAwePDjmmBISEoKPvRBCCCGEEEJ02uBJ4bfzxvfMOIQQop+Q9LweEq3cQVcI1Oht9PiC0xKtZh48/1BmToodBO1KWmt8fn/wts1iot6IjbYa6A1wOp3dNbSofv/733P55Zfz+uuvs3TpUr744gs2btzIxo0beeKJJ3j++ee54oorAPCH3K81a9Zw+OGHd2ifgazk1lx66aU88MADvPLKK1x77bWAUd6ivLyctLQ0zjor/DkUOjaHwxGssSuEEEIIIYQQvZKzOvx2vTR/FkKIzpCM3n5m5qQhPHj+oQzJSEQBQzIS92uQF4xgbiCca1YKi1mFzYslkOW6a9eumMs4nc5gaYVoWbHFxcUx1w3Mi7beqFGjuPPOO/nggw+orKzk008/ZerUqXi9Xn7xi1+wb98+ALKzs4NB2tbG2RUCGbvLly8Pjv3VV18F4Pzzzw82jgvIz88PXo93bIHHpLXHz+12BzOVhRBCCCGEEKLTnFXhtyXQK4QQnSKB3n5o5qQhfH7nKex46Cw+v/OU/RrkhfBgrtmsMJvaF+g94ogjANiyZQtFRUVRl1m+fDlerzds+VDLli2Lul5tbW2wDm209UKZzWamTZvGu+++i9Vqpb6+ntWrVwNgtVo56qijAHj//fdb3U5nHXzwwUycOBG/389rr72G0+lk4cKFQGTZBjCC1YFgb7xjCzwmpaWlbN68OeoyK1euDD72QgghhBBCCNFpjVXht+slsUQIITqjQ4FepdQopdSTSqkNSqk6pZS3xfwMpdQflFK/V0pZu2aooq8IC/SawgO93lYCvdOnTyctLQ2Px8OcOXMit+vzcd999wFw4oknMmjQoIhlHn300WAN3VCPP/44TqeTtLQ0pk+fHpwebdkAm80WzN51uZo7wc6ePRuAuXPnsnbt2pjrA8F6uB0VCOi++uqrLF68mNraWgYNGsQpp5wSdfnA2B555JGYwXIwymtUVVUFbx9++OGMHTsWgL/+9a9Rl3/ooYc6eC+EEEIIIYQQIgrJ6BVCiC4Vd6BXKTULWAf8EhgHJAEqdBmtdRVwCnAv0A3tOUVvFhrMtZhMWFT7MnqTk5O5++67AXjyySe5//77qaurA6CoqIhLL72UFStWYDKZ+Mtf/hJ1G7t27WLWrFkUFhYCRsOxRx99lHvvvReA3/72tyQlJQWXv+KKK7jqqqtYsmQJtbW1wemFhYVceeWVOJ1OEhMTOfHEE4Pzfv7zn3PsscfidDo55ZRTeO6556ipqQnO37t3L/PmzeOkk07iiSeeaOvhatWll16KUorVq1fz4IMPAnDRRRfFrPF75513Mnr0aMrLyzn++OOZP39+WEO4Xbt28eyzz3LEEUcEs4MBlFLBx+hf//oXv/3tb4OB4NLSUq6++mo++eSTsMdOCCGEEEIIITolIqNXAr1CCNEZcQV6lVIHAfOAZOBZYCoQ69yK5zACwGd3ZoCi72kto9enW2/Gdtttt3HFFVegteaee+4hIyODrKwshg0bxhtvvIHJZOKpp55i6tSpUdd//vnn+fDDDxk1ahSZmZmkp6dz22234ff7Oe+887jjjjvClnc6ncydO5cZM2aQnp5OZmYmycnJjBo1itdffx2z2cw///lPcnJygutYrVYWLVrElClTqKys5LrrriMzM5Ps7GxSUlIoKCjg8ssvZ/ny5SilWg4xLsOHD2fKlCmA0fwNopdtCMjIyGDJkiWMHz+eXbt2cfHFF5OamkpOTg5JSUmMGDGC66+/nu+++y5ibJdddhm//OUvAXj44YfJyckhKyuLgoIC5s6dyyOPPBK1vrEQQgghhBBCdEhEMzYp3SCEEJ0Rb0bv7YAdeExr/b9a6xWAL8ayHzf9PaajgxN9U3hGr8Jsan6atZbRC0Z93BdffJE333yT6dOnk5GRQV1dHQUFBVx66aV89dVX/OIXv4i5/gUXXMCnn37KWWedhdlsxmKxcNhhh/HUU0+xYMECLBZL2PIPPfQQDz/8MDNmzGD06NG43W58Ph9jxozhqquu4ttvv+V//ud/IvaTl5fHsmXLmDdvHmeeeSa5ubnBjOCDDjqIK664gvnz53PnnXe26zFrTWhgd8yYMUyePLnV5ceOHcuaNWv429/+xsknn0xmZibV1dVYLBYmTpzIddddx3vvvcfll18ese7TTz/Nv//9byZPnkxCQgJaa0466STeffddfvOb33T6vgghhBBCCCFEULTSDW0kBwkhhIhN6TjeRJVShcAwYLDWurRpWgmQp7WOOJdcKVULaK11WtcMt2ccddRROtCMqz02bNjA+PHju3FEvdveaif7ap0A5KfZyUyysXGvUdrAajYxvqBPPx26VG1tLampqT09jD5poL/OBpKlS5cybdq0nh6GEL2avE6EaJu8ToRoW8vXSehZgPHEDtrt6WOgfFP4tDt3g11+M4reSz5PRE9TSn2jtT4q2jxLtImtGATUBoK87eACUuLch+jjfH5/8HpE6YY2MnqFEEIIIYQQQvQORxxxRPfuoGVGLxhZvRLoFUKIDok30FsPpCmlzFrrWCUbAFBKpQIZwL4Ojk30US1LN5iUcSRYa41fa/x+jcnUudq1QgghhBBCCCG61zfffNO9O2jZjA2MOr3ZY7p3v0II0U/FW6P3x6Z1jmzHshc3LdvNnwyit2nZjE0phVlJVq8QQgghhBBCiCYeJ/hckdPry/b/WIQQop+IN9A7H1DAfUqpmOsqpQ4FHgI0MK/jwxN9UctAb+hfAJ8U1xdCCCGEEEKIgS1a2QaQQK8QQnRCvIHefwLrgNOA/yqlZtFU/kEpdahS6myl1DPAl0AW8DnweheOV/QBLUs3hP5tOV8IIYQQQgghxAAUrWwDGKUbhBBCdEhcNXq11h6l1AzgHeAkYGrI7O9CriuMYO/5ultac4reLDyj19T0V0o3CCGEEEIIIURf8uyzzwavX3fddV27ccnoFUKILhdvMza01nuVUscDs4ErgaMBW9NsH7AamAs8r7X2ds0wRV/h9xsN18BowBaI70qgVwghhBBCCCH6luuvvz54vcsDvTEzeiXQK4QQHRV3oBegKYD7f8D/KaXMGGUaTECFBHcHtmiN2ALXm5fx7/dxCSGEEEIIIYToRZzVzdcTs6Cx0rgugV4hhOiweGv0RtBa+7TWZVrrUgnyimj1eUEyeoUQQgghhBBChAgt3ZBzQPN1qdErhBAd1ulArxChQrN1zRLoFUIIIYQQQggRTWjphuyQQG+DBHqFEKKjYpZuUEpNjTUvXlrr5V21LdG7+WJk9IZe90qgVwghhBBCCCEGttCM3uzRzdcbKsDvA5N5vw9JCCH6utZq9C4FuiIip9vYj+hHvC1q9Ea7Lhm9QgghhBBCCDHAhWb0JueCPcMI/mo/NDogOaeHBiaEEH1XawHYXXRNoFcMIC2bsUW7LoFeIYQQQgghhBjgQpux2TOMYG8gy7e+TAK9QgjRATEDvVrrkftxHKKfiNmMTUmgVwghhBBCCCFEk9DSDYkZRqC3Yotxu74MGN8DgxJCiL5NmrGJLhWe0WsKuS6BXiGEEEIIIYQQTUJLN9gzwjN468v292iEEKJf6LWBXqXUcKXUTUqpxUqpXUopl1KqVim1Vin1kFKqoI31bUqpO5RS3yml6pRSVUqpL5RS1ykVkl4qulS7SjdojdYS7BVCCCGEEEKIASs0o9eebmT0BtSX7/fhCCFEf9CpJmlKqYnAEUDgHbkM+FZrva6T2x0GFAKhAdkaIBmY2HS5Til1gdb60yjrpwGfAEc2TWoAEoFjmy7nKKVmaa29nRmniBSrdINSCrNJBQPBPr/GYpZ4uxBCCCGEEEL0VmeffXb3bTy0Rm+gdEOAZPQKIUSHdCjQq5S6BPgTMDbG/M3AvVrr1zs4LnPT3/eAucB/tdYOpZQNOBV4BhgFLFRKjdNa722x/nMYQd5K4Mqm7ZiAy4F/AGc3jf93HRyfiCFWRm/gdnigN3L9uXPnUlhYyMyZMzn88MO7c6i9zr333gvATTfdREZGRo+ORQghhBBCCCEWL17cPRv2efjXnidp9Gcat2/6BpgMvE2iycHV9cu7Z79CCNHPxR3oVUo9CfyS5mzbEqCo6frgpss44BWl1PFa6xs7MC4HMElrvTZ0otbaDbyvlDoTWAOkAddjBG0D45sEXNR08yqt9btN133Ai0qpDOBx4Gal1BNa630dGJ+Iwev3B6+3DPRaTAp3cDlNQpT1586dy7Jlyxg5cuSAC/T+6U/G03j27NkS6BVCCCGEEEL0X87q5iBvC43+TCndIIQQHRRXjV6l1KXArzCCvC8CB2qth2itj2m6DAUOAF5oWuZXTdm/cdFaV7cM8raYvxH4sunmkS1m/6zp7yat9TtRVn8WqMYo5XB+vGMTsWmtwzJ6LREZvc1PN2nIJoQQQgghhBADVGgjtmikdIMQQnRIvM3Yfg1o4BGt9VVa660tF9Bab9Na/xyYQ1Owt/PDjKqi6W/LAgAnN/39MNpKWutG4LOmm6d0w7gGrJZlG1r2vDOr8IZsQgghhBBCCCEGoNBGbNFIoFcIITok3kDvoYAfuL8dyz7QtOxh8Q6qLUopCzCl6eYPIdMVcFDTzR9b2cT6pr8TunpsA1lr9XlbTmuZ0Tt37lyUUixbtgyAq666CqVU8DJy5MjgssuXL+fGG29k8uTJDB48GJvNRl5eHjNmzODNN9+MOb7Zs2ejlOLee+/F5XJx//33M3HiRFJTU1FKUVVVFVzW4XBw8803M3LkSBISEhg2bBjXXHMNu3fvZunSpRFjaumHH37g6quvZtSoUdjtdjIyMpgyZQr/+Mc/8Hg8UccVMGrUqLD7Pnv27Jj7EUIIIYQQQojucu+99wYvXarNQK+UbhBCiI6It0avB3BrravbWlBrXa2Uqqa5lm9X+iUwCCOQ/GLI9DQguel6cSvrB+YVdP3QBi5vK2UboPVAb2JiIvn5+VRWVuLxeEhLSyMxMTE4PzfX6MBaV1fHSSedFJyemppKYmIiZWVlLFmyhCVLlnDdddfxz3/+M+Y4nU4nU6dO5auvvsJqtZKUlBQ2f8+ePZx44okUFhYGx1ZVVcXzzz/PO++8wwMPPNDq4/D0009z44034m+qV5ySkkJdXR0rV65k5cqVvP7667z33nvB/aanp5Ofn09paSkAOTk5mM3Nierp6emt7k8IIYQQQgghukOgjwjQtcHexiogK/Z8Vw14nGC1d90+hRBiAFA6jlPolVKfAicCBVrrVs+lUErlAnuBpVrrUzs1yvDtTsSoz5sIPBna7E0pNZjmxnA/0Vp/HGMb12LU6nVrraP1BEMpdR1wHUB+fv6Rr732WrvHmJ6eztixY9u9fFezbHibhM8eQtUWo1MH4zrxTrzjZ3X7fhs8mtIGI7iZaFEMSg5PGK92aSqdxvw0myI7MTKh/Mwzz2TFihX8/e9/57LLLovcR0MDN9xwAxdddBHHH388WVnGl4Oqqirmz5/PvffeS11dHS+++CKzZoXf5xtuuIFXXnmFlJQULBYLjz32GOeccw42m41du3ZRUFCA1WoNjiEvL4+nn36a6dOnYzKZWLVqFb/4xS8oKyujqqqK4cOH88MPP4Tt49133+VnP/sZqamp3HHHHVx++eVkZ2fjdrtZvnw5t99+O9u2beOqq67iiSeewOfzBYO6aWlpAHz//feMGDGiI/+CAWXr1q1UV7d5zEn0A3V1daSkpPT0MITo1eR1IkTb5HUiRNtavk5OPvnk4PVPP/20y/YzuOh9PltxLE4dmdSSaHJwdd7VfHHs/+Gy53bZPoXoKvJ5InraySef/I3W+qho8+LN6P1/wEnAX4Gr21j2IYxs3v8X5z5iUkoVAAsxgrzfAL/tqm23pLV+FiMYzFFHHaWnTZvW7nU3bNhAampqN42sDevmw0d3gKcRAFVbROJHd4DdDhMv6tZde+rd0NAAQILNSmpqeKasx+Sm0mnMN1si5wPBoKfdbo/6GKampvL2229HnX7rrbeSl5fHFVdcwQsvvMAVV1wRtozVagWMN+UlS5Ywffr04LyDDz4YML68rFixAqUUCxYsYMqUKcFlTjvtND788EMmTDAqfiilwsbo8/m46667AHjjjTc4/fTTw/Y/a9YsJk6cyMSJE3n55Ze5//77SUlJibif0aaJSHa7nUmTJvX0MMR+sHTpUuJ5DxZiIJLXiRBtk9eJEG1r7XXSpa+f5atxJC1hdf1FDM3ZSa31AKpL3Jw7+nmGNbwLwHETx8Jg+b4veh/5PBG9WVyBXq31YqXUzcDDTUHXB4GVWmsvBGvnHgfcBZwK3KS1fq8rBqqUysJosDYK2AKcpbV2tlisPuR6IrEFIox1XTG2Drl3P56O72mEBdcal+5wr5FV6WujdEPoNK+/e5qxnXPOOQB8+eWXYdmyoSZOnBgW5A21YMECAKZMmRIW5A0YOXIkl1xyCS+88ELEvKVLl7Jz504OOeSQiCBvwJgxYzj22GP55JNPWLp0KWeffXa775sQQgghhBBC9Ae+hmp+bPwJACOHFbPdM57qEjcVvlEMCywkdXqFECJuMQO9SqntraznAaY3XTxKqcA7cA5gbbreANyklLpRaz2mM4NUSqUDS4BDgF3AaVrr0iiL1mAEe5OBwa1sMjCvpDPjEuF8TTVpIf5mbPHwer28+OKLvPHGG6xdu5bKykrcbnfYMk6nE4fDQU5OTsT6xx13XMxtr1mzBoATTjgh5jInnnhi1EDvypUrAdiyZQuDBg2KuX6g3MDu3btjLiOEEEIIIYQQ/dX2wmQa/ZlkWXaRW6AorTNCE5XukDY69a1WixRCCBFFaxm9I9u5DRvRg6rJTZdOpW4qpZKB/wBHYdT8PU1rvSvaslprrZTa0LTswa1sdkLT3/WdGZsI15lmbO1VV1fH6aefHgyqgtEsLTc3F5PJqPkbaGpWX18fNdAbaOwWTXm5ccyioCB2n77Bg6MfQygpMY4buFyu4Bha09BU5kIIIYQQQgghBhJnvQ+bqufQpP9A4lSSE4x8scrGbAj0X5NArxBCxK21QO/JrczbL5RSicBi4HigAiPIu6WN1T7FCPT+JMY27RgN5QD+20VDjd+93dREat18WPybYI1eAKyJcM6T3V6jNzR4210Zvffddx8rV64kJyeHRx99lBkzZpCXl9e8XZ8Pi8V4WsdqNBitnENX8DdlNJ933nksXLiwXevU1tZ2y1iEEEIIIYQQorc6JOdLxlU/iUn5KbGeTUqy8RuuqiFdAr1CCNEJMQO9Wutl+3MgLSmlbMACjIBzFTBda/1jO1Z9FbgdOEgpdbbW+t0W868F0oFGILKrV18XCOb+989QvQfSh8Kpf+j2IC/EH+jVWqNU5HKteeONNwB46qmnuOSSSyLmtyeTtjU5OTls2rQpmJ0bTax5+fn5AOzaFTXhXAghhBBCCCEE4K+vxGYyWu74bakkpJo5/Pwssis/gI1NC0mN3oFn3fweiWUI0Z/E1Yxtf1FKmYFXgBlALXCG1vrb9qyrtV6jlJoPXATMVUpdobX+T9M2LwP+2rToY1rrfd0w/J438aIeeTNsq3SDSSlMSuHXGo3GrzXmFoHeQPmFWNm4e/bsAWDSpOjdVz/++OMOjT1g0qRJfP7556xYsSLmMp999lnU6YHav+vWraOoqIghQ4bEtW+lFFrrmPddCCGEEEIIIfoyV6OX7Wv2MbK2Ntg93WdLRSlFzohETJ6k5oUlo3dgaXl2cvVu4zZIsFeIOJh6egAxTAEuaLpuBRYqpfbGuHwdZf1rgW+AbOA9pVQ9RpO2F4FE4F3gj91/NwaW8Ize6E+ttso3pKWlAVBVVRV1/fT0dAC+//77iHl1dXXcf//97R5vNLNmzQLg888/54svvoiYv2vXLl577bWo65566qkMGzYMn8/H7bff3up+HA5HxLS27rsQQgghhBBC9GWbvtzLJy9t5L8lVwSn+Wypwesea0bzwhLoHVj+++fwEpRg3P7vn3tmPEL0UR0O9CqlhiulLlFK3aKU+r1S6g+xLp0clx3Ib+US0VlLa12DUdf3TmAtRkM4F/AlcD1wrtba24FxiVa0Vbqh5fRogd6DDzZ66C1YsIDq6sg6xj/5iVF6+ZZbbmHZsmXB7Nevv/6aU089lYqKio7fAeDkk0/mxBNPRGvNBRdcwPvvvx/cx5dffsmMGTOw2WxR17VarTz99NMopXj11VeZOXMm3333XXC+x+Nh9erV3HHHHYwaNSrmfX/ppZfw+Xyduh9CCCGEEEII0VnXXntt8NJZWmt+WGacoTnO3twux281Ar1VRS6+/3oQ39YZyTfUd+63nehjqvfEN10IEVXcpRuUUoOBfwJnAG0VWFUYQda4DsForZe2Y9ttbcONUabhr20tKzrP7zdKMYBRgiBGnDcs0OuNEuj9n//5Hx555BFWrFhBTk4OeXl5WK1Whg4dyooVK/jLX/7CRx99xO7du5k2bRp2ux2z2Ux9fT2JiYksXLiQ008/vcP3QynFv//9b0488UR27drFmWeeSWJiImazmbq6OvLz83nkkUe45pprSEhIiFj/3HPP5fnnn+eGG25g0aJFLFq0iMTERBITE6murm41gHvNNdewcuVKHn/8cf7xj3+Ql5eHUoqf/vSnPPLIIx2+T0IIIYQQQgjREc8++2yXbatocxWOvQ3YEmF0wioAfNZkMBnNsr0uTfluC3bbYRzB20ZGr9YQZ18X0UelDzXKNUSbLoRot7gyepVS6cAy4EygAngHIyDrBOYBHwN1TdMqMEolvNSF4xW9VMv6vLGarFnayOg96KCD+Oijj5gxYwbp6ens3buXnTt3Bmvzjh49mq+++orLL7+cvLw8fD4fGRkZXHbZZXz99ddMnz690/dl+PDhfPvtt/zmN79h+PDhwX1ce+21fPPNN2RnZwOQkZERdf2rrrqKTZs2cdNNN3HwwQdjNpupqakhOzubadOm8ac//YlNmzZFXe+5557jmGOOwWKxsHv3bnbu3El5uTQhEEIIIYQQQvRtgWzeQWNcmJWRABPI5gVIzjby0Cq9w40JPhe4avfvIEXPOfmeyGnWRKMhmxCi3eLN6L0ZGAN8BczQWlcppfxAtdb6CgClVBJwD0bZBI/W+rquHLDonXx+f/B6rLINLedFC/QCTJ06lalTp8bcxqhRo3j55Zdjzo/VzGzu3LnMnTs35nqhsrOzeeKJJ3jiiSci5v3jH/8AYPz48THXHzlyJI899li79hXqmmuu4Zprrol7PSGEEEIIIYToreqrXGz/rhylYOSYBmjKZQmtz2tPM2OyQIM3E6c/Gbup3sjqtaf10KjFfjV8cuS0GQ9JIzYh4hRvjd5zMUox3K61roq2gNa6QWt9N/Ao8HOl1GWdG6LoC9pTn7flvFiB3t6ssrKS559/HmiuFyyEEEIIIYQQIrYfPytC+zUZIyxkJDUEp/ttzUFcpRTJWVYAHN6m0/Xr5ezGAaNye+S0jOH7fxxC9HHxBnrHAH5gZYvp0bpTBWrjdr5qu+j1WpZuiCUs0Bsj87anrVq1il//+tesXr0ap9MJgNfr5ZNPPuHkk0+mpKSEkSNHcsEFF/TwSIUQQgghhBCi+1x33XXBS2dkFiSTlm+j4JAETO7mcgyhGb0AyVnGSccO7zBjQn1Zp/Yr+pBogd7dX+//cQjRx8VbusECVGmtQztK1QNpSimlQ86Z11qXK6WqgEM7P0zR23Uoo9fXOwO9tbW1PP300zz99NMAZGZmUl9fj9vtBiArK4vXX38du93ek8MUQgghhBBCiG713HPPBa93pjHbqMOzqWY3SUlJmHe0EujNtgKNVEqgd+BxFEZO2/PVfh+GEH1dvBm9RUBKi2l7ADMwLnSiUioRyACSOjo40Xe0N6PXEtKkzdtLSzccfvjh/OUvf+Gkk05i2LBhNDQ0YLVaOfjgg7n11lv54YcfOOaYY3p6mEIIIYQQQgjRJ1RVVaG1xmw2Y3bXBKeHNmMDSC+wMSR7N7nWpuxOKd0wcETL6N3zNYT0AxJCtC3ejN5twBil1Bit9bamaV8ABwI3ADeFLHsjoJrWEf1ceEZv7OMHfaF0Q05ODr/73e/43e9+19NDEUIIIYQQQog+q7Kknh+XF2ErqCc5KxGg1dINWcMSGHHkFgavW2ZMkIzegSNaoNdZDeWbIe+g/T8eIfqoeAO9/wVOB2YAzzRN+ztwJfBrpdQBwHcY5RrOwmjc9mKXjFT0agOlGZsQQgghhBBCiNj+dccKGmvcEdNtSSamXl+A2dMc6A1txhagE7Obb0igd2Dw+8NLN4yYAjs/N67v+UoCvULEId7SDa8CbwF5gQla66+B32IEdc8A7gTOxsjmfRt4tEtGKnq19jdja37KSaBXCCGEEEIIIfqXaEFeAHeDcQp+axm9AI0qlz2uQ6n3ZUqgd6CoLQGv0QidpGwYe1rzvN1Sp1eIeMSV0au1LgIujDL9EaXUf4ALgKFANfCR1vqjLhml6PUko1cIIYQQQgghRFvCavRGyej9fm0exY4/c0rak4yv37s/hyZ6SmjZhsxRMCykJ86er/f/eITow+It3RCT1no9sL6rtif6Fl9IgfTWAr0mBUoptNb4tcbv15haWV4IIYQQQgghRP8RntHbstc7JOUkwA4fld7hUP/9/hya6CmOHc3Xs0bD4EmgzKB9ULYRGqsgMaOnRidEnxJv6QYhompv6QalFGbV+xuyCSGEEEIIIYToemZ36zV6k/KM4K/DNxQaKsDv229jEz0kNKM3azTYkmHQIc3Tilbv/zEJ0UdJoFd0mta63aUbWs6X8g1CCCGEEEIIMXCYQpqx+ayRNXqTcxIAqPQOAzQ0VO6voYmeEhboHWX8HRpSvmG3lG8Qor1ilm5QSv2r6WqJ1vp3LabFQ2utf96RwYm+oWWQVykJ9AohhBBCCCHEQJSYZovakM2WZAKtW2T0RgZ6E9MtmPBS68vH40/AWl8GKbndOmbRwypblG4Ao07v188Z1/dIQzYh2qu1Gr2zm/5uBH4XMk0D8RRV1YAEevux9pZtiLaMVwK9QgghRLdbuKaIOUs2UVzVyOCMRG4/fRwzJw3p6WEJIYTo5f74xz/Gvc7VD58AgNPp5IcffiA1tTmYqzz1KG2UYvCbE9BmW8T6JrMiLaGSKlceDt8Q8urLOjh60SdoHT3QO/To5ml7vgG/H0xyUroQbWkt0Punpr/lUaYJERSe0dv2G69k9AohhBD7z8I1Rdy5YB1Oj9E4taiqkbsWGM1tJNgrhBCiNffee2+H13W7I7N6zWGN2CLr8wakJ1VT5cqjyiuB3n6vvhwCzwtbKiRlG9czR0JyLtSXgasayjdB3vgeG6YQfUXMQK/WOiKoG22aEPHU5225jAR6hRBCiO41Z8mmYJA3oNHjY86STRLoFUII0S3K99RSVV2N3xf+e6+tsg0Bh4/9kVN3/oVEUw3Un91t4xS9gCM0m3cUBEpBKmXU6d30nnF791cS6BWiHeLKe1dKTWy6pHTXgETfE2/phvBAr7+VJYUQQgjRWcVVjXFNF0IIITprxRtbWPLUFur2hgd6wxqxtRLotafbjCAvGBmdov8Ka8Q2OnzesJCGbFKnV4h2aa10QzTfAX5gEFDX5aMRfVJosHYgZ/TOnj2bF198kT/+8Y+dOsVJCCGE6EqDMxIpihLUHZyR2AOjEUIIMRBU7W0AICUnvAav2V0TvO5vpXSDz57ZfGMABnr/dceKqA3tEtNswRrI/UZ7A727vwYG2GMjRAfEW8m6GqjWWpe3uaQYMLxxlm6w9NNAb3t99dVX/OIXv2DChAkMHTqUxMRERo4cycUXX8xbb72F1j3zmHz88cecc8455OXlYbfbGTNmDDfeeCOlpaUd3uaePXuYN28eN910E1OmTCE5ORmlFIMGDerCkQshhGjN7aePi+iim2g1cfvp43pkPEIIIfqOc845J3hpL7fTS321G2WGlIzwQK8ptEavNfaJwh5bJkuqbuWVsifx1jjiH3gfFy2Q2dr0Pq2yRemGUIMngakpP7F8EzQ6BtZjI0QHxJvRuxmYpJSya62d3TEg0ff4OlG6wTuAAr1Op5PrrruOl19+OTjNbrdjs9nYuXMnO3fuZP78+UyePJk333yToUOH7rex3X///dxzzz0AmEwmUlJS2L59O08++SSvvvoqn3zyCYccckjc233kkUd44oknunq4Qggh4nDOYYO5df53hJZJ/MM5E6Q+rxBCiDa9++67ca9TVWpk89rTTJgt5rB57c3o9SdmUu5Joco3FEelj9y4RyH6jNYyeq2JMOhQKF5j3N6zGgh/TgkhwsWb0fsyRnD4im4Yi+ijpBlb2zweDzNmzODll1/GZDLxi1/8gvXr17Nv3z6qq6spLS3lscceIz09nVWrVnH88cezZ8+e/TK2//znP8Eg76233kpVVRXV1dX88MMPHH744ZSVlXHeeefhcrni3rZSijFjxnDxxRfzyCOPcMstt3T18IUQQrRhj6OBFr1wOGZUds8MRgghRL8XDPSmR4YbTO7mCpCt1ej12bPIsuwGoMJh7+IRil6ltUAvGA3ZAnZLnV4h2hJvoPcZYBHwuFLq50qpeNcX/VDczdhUSKC3h8oU7G933303y5Ytw2Qy8corr/DMM88wfnxzx9C8vDxuuukmVq5cSW5uLrt37+byyy/fL2Uc7r77bgBmzZrFI488Qmqq8YXr4IMPZvHixcHs3meffTbubT/yyCNs3bqV1157jVtvvZVDDz20S8cuhBCibVv3RbZVKK+N/+CdEEII0R6OVgK9oRm9vlYyer0JmcFAb1V97ICw6OMaq6Cx0rhusUNKlBJ/0pBNiLjEG6h9HqgCvMCzwF6l1H+UUi8qpf4V4/J8Vw9a9C5dmdE7cuRIlFIsXbqUXbt2cc011zBs2DDsdjujRo3itttuo7q6OmKbs2fPRinFvffei8vl4v7772fixImkpqailKKqqiq4rN/v5+WXX+YnP/kJubm52Gw2Bg8ezMUXX8yqVataHfuqVas455xzyMrKIiUlhcMPP5wnnngCf0hDupaKi4uD5Qv+93//l4svvjjmshMmTOCZZ54BYNmyZbz33nutjqezfvzxR9auXQvA7bffHjF/6NChXHrppQDMmzcv7u2bzXJajRBC9LRogd6yOgn0CiFEV1i4pogpD33CqDvfY8pDn7BwTVFPD6nHBTJ6kzIifwuYQ2r0+lvJ6PXbUsm0Go+lw5UPHqkc2S85QurzZo4CU5QQ1dCjm6/v+ab7xyREHxdvjd7ZgIZgT48cYEYb62jg53HuR/Qh4YHeto8dtAz0aq1RKjxAvHXrVi666CLKyspISUlBKUVhYSGPPvooixYtYvny5RQUFERs2+l0MnXqVL766iusVitJSUlh82trazn//PP5+OOPAaO0QGpqKiUlJcyfP58333yTJ554gl/96lcR237ttde4/PLL8fl8AGRkZPDjjz9y00038dlnn5GSEr2ZwAsvvIDH48FsNnPnnXe2+fhceOGFHHjggWzevJm///3vnH322W2u01GffvopAOnp6UyePDnqMqeffjrPPfccX331FXV1dTHvpxBCiN5pW1mUQK9k9AohRKctXFPEHW+uw+0zkj6Kqhq5a8H3AAO6DvqpV4wn/xAzXhUZnDV5QpuxtZKpq0ykJ9VAFVR6h0JDOaTvvx4mPS0xzRa1uVhimi3K0n1YW2UbADKGQ0o+1JWCu5bEZEVjfeSZr/3usRGig+IN9P6pW0Yhusy016dR4ayImJ5tz2bpxUu7fH9a67hLNyilMJtUMEDs82ss5vD1brvtNnJzc1mwYAEnnHACfr+fxYsXc80117B161auvPJKPvzww4htP/PMM1gsFl577TVmzZoVbHSWnJwMwBVXXMHHH3/MEUccwYMPPsjUqVOx2+04HA7+9re/8ac//Ykbb7yRSZMmMWXKlOB2t23bxlVXXYXP52P69On8/e9/Z/To0TQ0NPCPf/yDO+64I2YAdOnSpQAceeSR7W6wdt555zFnzhxWrFiBz+frtszY9evXAzB+/HhMMYL0EyZMAIz/9caNGznqqKO6ZSxCCCG6R9SMXgn0CiFEp81ZsikY5A1o9PiYs2TTgA70WmxmzMlerKbIwFt4M7bWSzIkp7hQ+Kj2FeCr3od5AAV6L7zzKEwJftZ99wPfvlyHMsMNT07DZO5n1TPDAr2joi+jlJHVu9FoDFiQW4dr+CBSRvjY9EEDqXlWrvjzifthsEL0DXEFerXWEujt5aIFeVub3ll+TbCOrEkpTO0I9AJRAr3h810uF++//z5jx441tm0ycd5555GWlsYpp5zCRx99xIoVKzjhhBPC1qurq2PJkiVMnz49OG3EiBEAfPzxxyxcuJBx48bxySefkJ6eHlwmMzOT3/3ud5jNZu666y4efPDBsA6zDzzwAE6nk3HjxrFo0SLsdqMhQFJSErfccgsNDQ38/ve/j3pfA8HUww47rF2PDcDEiRMBqKmpYdeuXYwa1fyhN3LkSHbu3NnubYXasWMHI0eODN4uKSkBYPDgwTHXCZ0XWF4IIUTfoLWWQK8QQnST4qrGuKYPFH6/H5fLFTURJrwZW+wavQAqKY1Dk97HbqrFXX0BiV0+0t5Ja827T6+lodbFuNPtpA+2oSx+GuvcJKf3s8Z0lYXN12MFesGo07vxXVz+JAp3JuKnlmOPy+aEa1Pw4op6lrAQA1W8Gb2iCx36YuzGVH847g9ceOCFALyx+Q3+/MWfYy77/ZXft2t/9668l3uPvxeAHyt+5JJ3L4m57Gtnv8bB2QcH13try1tR9+sLqU3bnvq80ZZtWacX4KKLLgoGeUOdfPLJHH/88axcuZI333wzItA7ceLEsCBvqBdffBGAa6+9NizIG+qyyy7jrrvu4tNPPw1m0mqtWbBgAQA333xzMMgb6qabbuLBBx+koaEhYl5lpVFcPju7/R3Oc3JygtcrKirCAr25ubk4nR2rUdUyM7i+vh6AxMTYX5tCy1/U1UUGC4QQQvReZXUuapzeiOnlUqNXCCE6bXCGnaKqyO/lgzMGSkgyUvHWKr5ctA1rlosDj4/M2I0no9eXkMmJaUbLH1fjlFaX7U/27aylsrgei12RkZ/M0RenU1NTg7LG7gvTZ7WndAPAMKPMYKHrKPzaRGqBmZSmoHdtrRO3201CQkJ3jlSIPkMCvaJT4m3EFlw25GibV0cGeqdNmxZz3ZNOOomVK1fy7bffRsw77rjjYq63cuVKAP7yl78wZ86cVsfX0NBARUUFeXl5bN++PdjM7aSTToq6fEpKCkceeSSfffZZq9vtCLc7vDbT119/3eX7EEII0T9t21cfvG4zm4KnGEszNiGE6LxfnjKWuxf8EDYt0Wrm9tPH9dCIel7FnjpKtlSTe6A16nxTSDO2tjJ6vfbM4HV/zd6uGWAfsPEL4yzK7DEWrLbmkI3L5YroQdPnhQZ6M1vJ6C04HExWtjuPBSB7aPhB7IaGRgn0CtGkU4FepdQgYDCQTHODtgha6+Wd2U9/1d5M3AsPvDCY3dsZgWxegIOzD25/JvDx94atGyre+rzNyzbXFoqW0TtkSOyaVoF5ZWVlEfNyc3NjrhcoOxAI2rYlkJ0bup/WShzEGnNWVhbFxcVUVLS/fEZ5eXnwekZGRrvXi1egdnFjY+zTy0KzlKURmxBC9C1bQxqxTRqewaodxlkmUrpBCCE6b8qYnLDbyQlm7p956ICuz+soNX472NMja8kqrxOT30hi0SYL2tx6YM5nz8Ltt1PqOYD6bZqDTuv68fY2Xo+PLV+XAlAwoTkz3O9R7C10kJmZGWvVvsddD3VNAXyTBdKHxV7WaseTfwS7SiYBMCq7EBiKY4+LH5fUUTRsK+f9WnrJCAEdCPQqpUzAzcAvgJHtWEV3ZD+ib+hwRm8bpRs6qrWmZf6mMhNvv/02M2fO7LJ9tmX8+PEUFxezdu3adq+zbt06wLg/o0e3cgpLJwUC18XFxTGXCZ1XUFDQbWMRQgjR9baF1Oc9dnR2MNBbXufG79ftrq0vhBAikqPBE3b7pANz+12Q95///Gdcy1c1BXqTMiNDAGHZvNY0o8lWK7wJmVT7BvOO48+kOx0cFNdI+qYda8txNXhJyjaRPcRIsmmo8rL6pRoSUuoYP6n7fhvud47C5usZI8Dcethot/V0vNpOnnULee4NVHAClgQTzho/FUWRJRSFGKjiCsA2BXkXAWdiZPBWARmAHygGcoBAAdN6oDxiI6JbZduzozZey7a3vz5sPDqa0dtWoLc9gcfWsnejyc/PZ9euXezatSuu9UL3U1xcTFpa9FOMYo355JNP5r///S/ffPMNe/bsYejQtrvFLlq0CIBjjjkmoibw0Ucfze7du9s7/DBff/01w4Y1HymdMGECABs2bMDv92MyRR55DzSTU0oxfvz4Du1XCCFEzwhtxDZhcBppdgs1Ti8+v6aq0UNWcmRHdCGEEO3jaAgvsVZa0//OlrjuuuviWr5qrxFwS82J/Hwxe0LLNrRenxfAZ88kx7IH8FPTmIbP58dsjvy90p8EyjbkHGANNhdLTDdjsihcdX4aa90kpvaTz+6w+rytlG1osr3a+O06OuFLEiuM38PJWRZMZmis8uJs8GBPil4yZKD41x0raKxxR0xPTLNx9cMnRFlD9EfxvkteBZwF7AVO1FpnNU3fp7UeDqQA04AVgBn4o9a67Ves6DJLL17K91d+H3FZevHSbtlfeEZv+59ObQV6ly1bFnPdwLwjjjii3fuD5vq977//flzrjR49Olg+Yfny6FVI6uvrWb16ddR5s2fPxmq14vP5eOihh9rc3xtvvMHmzZsBozlcS2VlZZSWlnbo4vP5wrZ18sknA1BdXR2z9u+HH34IwOTJk4OlHoTYHxauKWLKQ58w+4N6pjz0CQvXFPX0kIToc0IDvWPzUshJbT5NVso3CCFE51RFBHo71jC5v/C6fdQ6nCgTpGRFlmUwh2T0ttWIDYzSDVblJs28D40Zx95+0hh63Xx47BC4N8P4u24+YJRtqNrXiDLBkIObS+YppUjJMXL09u6s6oEBd5PKHc3XW2vE1uTocw/kuNQXGWv/nMSKH8Hvw2RWpOQYwd3SHVXdNNC+I1qQt7Xpon+KN9B7OUYphtu11p+3nKm19jfV4z0ZWAb8n1Lq2M4PU/RW3VW64fXXX2f79u0R05cvX87nnxtPvQsvjK9u8ezZswFYsmQJH3zwQavLOhyO4HWlFBdccAEAjz/+OC5X5A/jJ598MqyWbaghQ4bw61//GoC///3vvP766zH3u2HDBn75y18CMGLECK6++uqIZQoLC9Fad+gycuTIsG1NmDCBww47DCBqg7ri4mJeffVVIHrQWYjusnBNEXcuWEdRlVE/uqiqkbsWfC/BXiHiUOfysrcp6GA1K0ZkJZGbIoFeIYToKo768NIN+2pc6CiNpgeKqn2NoCEh1YTFGllSz+SuCV5vT0avN8GoR5tp2QNA2e6a1hbvG9bNh8W/gerdgDb+Lv4NrJuPxWrm/N9O5ODzkkhOCz+rMzXXCGbu21XdA4PuJmEZvW0HepOHD+eQrM9It5Ri8jaQUG2sn5pnPDb9KgguRCfEG+g9tOnv2y2mh72La619GHV8LcBtHRua6As63oyt9UCvzWbjjDPOYOXKlYBRX3fx4sX89Kc/BeAnP/kJU6ZMiWusM2bM4Pzzz0drzaxZs5gzZ05Yo7XKykoWLlzIueeeyy233BK27l133YXdbmfDhg3MnDmTHTuMo4+NjY08/vjj/P73vyc9PT3mvh988EFOOOEE/H4/P/vZz/jVr37Fxo0bg/PLysp44oknOP744ykrKyMhIYGXX36ZxMTEmNvsKg888AAAb731FnfccQe1tcaR9vXr13POOedQW1vL6NGjufbaayPWnTt3LkoplFIUFhZGzPd4PJSXlwcvdXXGUXitddj00MC6EABzlmzC6fGHTWv0+JizZFMPjUiIvie0Pu/I7GQsZhO5oRm9dQM780wIITqrZUav2+enqkXd3oHEYjUx7rg8skZFrxAZf0avEejNshin6ZfvqW1t8b7hv38GT4tG2J5GYzrgqHKQmhtZmiGlKdBbvrufZDVDeKA3s+0Twevq66nLnBC8bS83+toEHq+ynf3g+SFEF4g30JsCVGmtQ9+ZnEDEu7TWeiNQAxzf8eGJ3q4rMnq9UQK9jzzyCA6HgylTppCamkpKSgrnnnsuZWVljB07lhdffLFD433ppZeYOXMmTqeTO+64g/z8fDIzM0lLSyM7O5tZs2axePHiiPXGjBnDCy+8gNls5oMPPmD06NHB9W6++WZmzpzJeeedF3O/NpuNDz/8kJ/97Gf4/X6eeeYZxo8fT15eHunp6eTl5XHTTTdRVVVFVlYW77zzDieeeGKH7mO8zjzzTO677z7AyOrNzMwkPT2dgw8+mG+//ZacnBwWLVpEQkLrXXGj+fzzz8nNzQ1eApnN+/btC5s+adKkLr1Pou8rrmqMa7oQIlJo2YYxucYpoLlSukEIIbpMy2ZsAKW1/esg2pFHHhm8tCUjP4mjzhvKsKPsUeeHNWOzRe97EkpbEvFbEsk0G4FeR1E/yGat3hN1cm1lI7WORsrKyiJ6tACkNpUnqCyq79bh7VeO9pVu0H7NosfX8OWibdRlHBacnlj+PdCc0VvRnx4bIToh3kBvKdDy8FIZkKCUGhw6salxWyKQhei3fP7mjLuuLN0wduxYVq9ezdVXX016ejo+n4+RI0dy6623snr1agoKCjo03uTkZN5++23effddzj//fAYPHkxDQwMej4exY8dy0UUX8cILL/DUU09FrHvJJZfw+eefc9ZZZ5GRkYHb7WbChAk8/vjjzJ8/P1gsP5bExETmzZvHF198wfXXX8+4ceOwWq3U1DSfgnT00UezceNGpk+f3qH711H33HMPH330EWeddRaZmZm4XC5Gjx7Nb37zG3744QcOOeSQ/ToeIQalR/+BMDij+7PchegvtpaF1+eF8EBveZ3UaxNCiM5o2YwN+l9Dtm+//TZ4aQ+nM3agO7QZW3syesEo35DVVLqhoTp6qbw+JT16Y+7V7tm8fPcXlPzYgNkcWfYiUIe2ttyNz+ePmN/neF0hQW8FmSNiLlpaWMOejQ52f1+Db/DE4PTECiPQm5JrZeTkFIYfE/33gxADTfRzKmLbBQxVSuVprfc1TfsWGArMBP4WsuzZgBXY3dlBit6ro6Ub2gr0AgwfPpznn3++XdubO3cuc+fObff+zzrrLM4666x2Lx8wefJk3n333U6N4dhjj+XYY43S1bW1taSmpvLYY49xyy238M0337Bs2bJgiYr96bTTTuO0006La53Zs2cHax9HM23atAFdp0x03OkH5zN35c6waXaLidtPH9dDIxKi79m2LzLQmyM1eoUQostEK9MwkBuy7d5YSWV1FeYo9XmhRY1ea9sZvWA0ZMuxbuDneVew58S2G1v3eqf+ARZch9H6yOAxp7Ol4Ti0howh0YOVlgQTk87PRtucaO0n/py9XqZqF+imgHX6MLDEPnt02xqj3GLmCAuenPH4TVZMfg+22t2YXVWQkMHY49Opra3F6/ViscQb5uo/LFYTXk/kgYDEtMhyIKL/ivfdIdCA7aSQaa8ACvirUup2pdRPlFK3AC9ivHtFngcv+o0Ol25Q4YHegR4MvPnmm/n1r3+N3+/n8ssv59NPP+3pIQnRoxrdkV9QZk8ZycxJQ3pgNEL0TW1l9EqgVwghOidaRu++ARro1VrzwT++Z8ULxWhv9EBveI3elHZt12fPxKx82E216LoyfD5fl4y3xxx6IZjCA5Hbxz6Mx2MiOddMVkFyzFWzR9hJSDHjdveDM3IqQ8s2jIy5mNaa7d8Zgd6c0QlocwKuzObED3tT+YbAsq1llPd3Xo8Ps9UI8R12QSon/W8BgyfZOOSUAq5++IQeHp3Yn+IN9L4OVALBYqRa6zeAhUAy8BDwATAHSAe2AX/oioGK3kdrHQz0KuIL9JpMClNTsFejiZHUO6A8/vjjnHvuubhcLmbOnMmaNWt6ekhC9AitNcu3lEVMz0iSI9FCtJfb62dnRfMprqNzjR+OuZLRK4QQXSZ6Ru/AfG9tqHHjdvow2yAx1Rp1mXhr9IJRuiHA6q7q+0HOulLwhz9vNu40yhLmHmBpsxyg1hqXqx88x0IbsbVSn7eiqJ6askYsdkXuCOO7TGPOocH5gTq9zhove39ws/7z4u4Zbx+w84cKXA1ekrJN5AxLxd3go3iNmx+XlVBf3Q+eM6LdWg30KqUODL2ttV6jtc7VWl/eYtELgV8CS4GtwDfAg8BkrXVl1w1X9CbeFtm8bX0otRRevqEf1BnqJJPJxKJFi9BaU11dLQ3KxIC1dV8dJdWRR+M3lNREWVoIEc3OivrgwdghGYkk2YzsobywGr3ypV8IITojeo3egZlRWFVqHFy0p5sxmaKHGcyhpRvaWaPXZzda/qxvOJWlK45kzYe7OjnSHhYa4ARqfLnsKfSizDDk4NYfkwaHl+3LnKx8c3ury/UJ7Qz0BrJ5M4dbsFiN7zKhgd5ARm9DtY9dq1xs/jIyWWSgGHVYLlOvHMXQoxJQSpGcZSV3jB3tg2+W7Gh7A6LfaCujd4NSaqVS6nqlVEashbTWPq3137XWp2qtx2mtj9Fa/05r7eja4YreJLxsQ/w1gtpTp7e/cjS42VhSw45qHxtLaqJ+SRRioFq2ufkL2pCQ5mvriyXQK0R7bQsp2zAmr/n02KxkG4HjspUNbjz9oaGLEEL0AJfXR4M7soxA6QA9WyIQ6E3MiP270Oxu/mzytzOj1xeS0VvfmEL5nrpWlu4DKsMDbpsapwGKzBEWElNi16kFQEH5Vg/FG2tbX64vCA30Zo6KuVgg0Js1qjlL3BkS6E3a9w2jF51DQeMyAGr2ufpHs7oOUApMaQ2Ms61k9KJzOfDVyRzf+GcANny+F3ejt4dHKPaXtqJzCpiM0WStRCn1ulLqLKVUH6/8LbpCR+vzRlsnsK3CwkK01kybNq3T4+utHA1uihyNuJs+gNw+P0WORgn2CtEkNNB79QmjCLxTbC+vx+np43XZhNhPtoY2YsttDvRazCaymsqgaA2V9fLZI4QQHRGtbAMM3Bq9jmBGb+xQgckTf0av124EerMsewCoLm3s6BB7hxYZvY3+DJTyk39QG0FeIDHdjNmqcNf7aejrJUIcoTV6o2f0aq055uyR5B1kY9CY5udL4r41wVZ2CrA2lDL8u7+QlORC+6CiqB8EwuPk9/lpbGzEvmUxQ795CGvDXhSaof4vKLBtwOvys3ZpH8+GF+3WVsD2bOBNwAUkAD8F3gGKlFKPKKUO6+bxiV4stHSDpQOBXssAzegtrXbib9F8zq81pVFOVRdioGl0+1i1o7niz4xDBpGfZLxX+PyazaUD74ubEB0RGugdkxfe2EUasgkhROeFJmkMy2o+A2lfrQv/APptExDI6E3KiN6IDVo0Y7PGV7oh07IbgLoKd99+fFsEeqemPcf5Bz1D/ui2m9MppUjJMTJb9xZWdcfo9g+fFxw7m29nRc/oVUqRf0AyI6ckYE1obmCXu/ZvtIw+mHxO8tWPAOzdUdXFA+7dtNa8fv/XfPDPH8hePx+TP/wg/hHJbwKw7pPd+DwDM9t5oGk10Ku1/o/W+mJgEHAd8HnTrHzgZuBbpdR3SqmblFJ53TtU0dt0OqM3pKavty9/WMfJHeNUkljThRhIVu2owO01Xgtj81IYkpHIsLTmjyqp0ytE+2wti57RCxLoFUKIruCob87oHZRmJyPJCMD5/JqKAXi2RPU+I9M2JTtG81y/F5PXWEYrE35rUru2GyjdMK/8aWMzPvj7Lz7lmRs+4ZkbPuFfd6zo5Mj3M0dkrdR0z7Zg/dm2pOQaz7N9u6q7dFj7Vc2e5oZ0KflgS469aE1NRM1nS0Np1GVz1QYA9u0aWL8X9m6vobK4nvLd9aS6CiPmj7B9S5alEGetj61r9u7/AYr9rl3vJlrrGuD/gP9TSo0ErgQuB8YAE4FHgYeVUh8ALwKLtdYD79NtgAltoNahQK85JKNXD5xAr81sihrUtZmlIooQyzeXB69PPSAXgOGpJr7ea5RskDq9QrTN79ds21cfvD02r0WgN6QGYJk0ZBNCiA6pCsnozUiykZ9qD5ZzKK1xhh1UGwgu+f0xrPpsDak50e93eDZvCrSzGmSgdEOjPzPq/MaaPhR20Jp/fXcjjf70iFm2f5Yw9fqCNjeRmmOEcPp0reLKtss21Fe7WPHGFqw5jeQfEH5QwJuUj7UhMmCZleKAOijf3Ycfmw7YuLIYgOwxFvx1WZgbwxvSKQXH5ixi2+F3kTYs/riN6HvijixprQu11n/SWh8AnAA8B1RjBI3PBuZj1PN9Rik1uUtHK3qVzpZuGKjN2PLT7RHTTEpFnS7EQLNs877g9ZPGGYHeYanNH1XrJaNXiDaV1DhpbKpnnZlkJbtFc5ccyegVQohOc4TU6M1MspKX1vzeuq+2/5Rke+edd4KXVimNLVVjtUXPJTO5Q+vztq8RG4AvIaPdy/Z6jY6oQV4Ad0P7zu4MZPRWFte3sWQvFlq+Ikagd8facrau3kfJ+gYslvDnVNlhv8BvDv9u4zfbUZNOxZpkwpQwcM6U9bh8bPnG+P1UMCGJmpEzIpbxmxNIOO4UBh+YRklJCT6f9Dzp79p3fkAMWuuVwEql1K+BczEyfU8HMoEbgBuUUpu11uM7PVLR63Rl6Qafb+AEetMTrexuMS03NYHMpBinOQkxQBRVNbKtzPjSmmAxMXmUUZNtRFjphlr8fo2pA+85QgwUYfV5cyNr/oVl9EqgVwghOiS0Rm9mko3QvJV9fb1RVohzzjmnXcu53a1n1oZm9La3ERsAJktcgeFerTKybEO8UnKsZI+ykZLbqVBOzwoN9GZGr8+7/TsjKzVrpDViXm1TMLPgi3tRGEHdskOvw3PQaUwdp6mrq8Pv90eUfOiPtn9XhsfpIznXTFZBMt76yKxwx4GXUDtyBmbA7/dTtKOUYWMKUEp+T/VXXfLM11q7tdZvaq3PAQYDfwU0RhPEA7tiH6L38XVlM7YBVLrBG6VsQ0cePyH6m+Wbm08zmjw6G7vVaOaRkaDIbKp7V+fyssfRx7stC9HNQgO9Lcs2QIsavVK6QQghOiSidENIRm9pPwr0tscPy/bw7pPfU7HNE3MZUwcasQV4mxqy9XktGrF1hMVmYtLMXPIPNffdzExHYfP1KI3YnPUeijY6QEH+AdHr99aOnEF9QfMJ5L7kfIBg8NLlGhivwQ0rSwDIPdCCUgprbcuUMoDm+MPuLz0sfnQjRVsc+2mEoid02SEOpZRdKXUJ8BJwK0Q0QhT9jLezGb2mAdqMzRsZ6HV6+uiHtBBdaNmm5kDv1ANygteVUkwY3JzJIeUbhGhdXIFeyegVQogOaVm6IT+tuQxbaT8q3dAepTtr2bejDq879m86c1jphvgCvYGGbH1eFwR6A5RSfTeYGaN0w7/uWMEzN3zC87d+ht+vQcMXz1ew/J8lUTfjymjOKUxwbAle93k0laW10VbpVxpq3BRvqcJkhiETjNeUta4oYrnkki+D1xOSLaDh6/e67rkoep9O5/srpU4CrgAuAFJpDvDuA17BaM4m+qHQcgvmDpwWMVBr9LqjlKlo9AycOkL728I1RcxZsoniqkYGZyRy++njmDlpSL/db1/l9fn5fFtzI7aTDswNmz9+UBqfb60AjEDvjEMG7dfxCdGXbCsLKd3QRqC3XDJ6hRCiQ1pm9IbaVzOwAr1VexsASM6KPM0+wOwJyeiNsxSDz55JoskRtSGbNaEPnZ7v2AEc3enNeN1+ako87LFUcODhSW2v0Jto3aIZW3NGb6zGerHqF7syDwheT6gyAr3lhU6+e7uWXWN2cOHteV0w4N4rKc3GT393GN+t3EhiU1kuW5SMXnvVFsyN5fgScxg2KZmd39RSvKmG8j215AyN76BLb/OvO1ZEfd4kptm4+uETemBEvUOH3hWVUgcqpf6ilNoBfALMBtIAD/AWRr3eIVrrW7TWa7tqsKJ3kWZsHeOJUrrB6fGhB1D5iv1l4Zoi7lywjqKqRjRGDdi7FnzPwjWRRzq7er939cB++7LvdldR6/QCMDjdHpGFGJbRWywZvUK0ZltoRm+UGr05UqNXCCE6LTKjt3+Wbhg8eHDwEktVqRHoTc2O3XPE1NEavRilG67Ou5pfDprFT89cwWk3D+Gwc41yDh6Xnx1ry9rYQi9RuZ1EU/RT5u2W9jdXq9zlYsN7jXz3YR/8bVG7F7xNZdgSM41LB7kyQzN6NwOQlGHkMjpKGgfE72uXv57s0U3vPdofltHrDMl4DmT12hLNDD7EKIfx9X/6flZvrIMDsaYPFO0O9CqlspRSv1RKrQI2AHcBIzAyeL8GfgkUaK0v1Fq/q7WWc9H7Ma1155uxhWQBD6RAb7TSDX6to04XnTNnySacLbKlGz0+5izZ1O37bZmlvT/225ctC6nPO/XA3IjmAKGB3g1SukGImBz1birqjS+3dquJIRmJEctkJFqDB2hrnV4pHySEEB0Q1owt2UZeaOmGfpTRW1JSErxE46zz4Kz3YLJCYlorGb2hNXo7UbrB4qoEIHdMIqOPN7bz4fM/Ulnc/kBpj6ncztV5V5NnNYKSk6c7+OWgWfxy0CwuH3NvuzeTkmM8ztV7++DzLEbZho5wpwzDbzaCnNbGMsxOB4npZiw2hafBT31V/zng0pLb6cXr9VJWVkZSkpHVbWksw+Q33pe8CRnUjvhJcPnkvc3lG0YckQIKdnxXQW1lH3wOiTa1WrpBKWUFzsEozTADsNJcmqEI+DcwV2st0YsBxq81GiM4a1IKUwcCvSYFCoVG49cav193aDt9jTsko1cBgRC30+Mjoan5lOgaxVXRm3bFmt7X99uXLW8R6G1pTG4KNrMJt89PUVUj1Q0e0pNi/5gQYqDaGlK2YXROStTPVZNJkZOSwN6mQERZrYthWX3s1E8hhOhhVSEZvRlJVjISm7NZy+tceH1+LOY+VFaggxxN2bz2NBNmc+zfMqbO1Oi1Nwd6zc7mjNhRx6RSV+5h32Yn7z7zHRfdfQz25F76/dBVC/XG990Lcn/PqqnvkZySAOuM2Zb6EqOsgWr793BiuhmzTeFu8FNf7SI5PaHNdXqN0EBvZmQjtriYzLgyxpJY8SNglG/wDTqG1Dwrjj1uSrY7OODIgs7to5da/upmirY6GDrZRPI4I0PXWrsnON+TMpT6QceSu/YZAJJKVoHfByYziekWTCbj5kt3rwzb7kAvedBftPXJsxd4AyPYawOcGHV3TweGa63vkiDvwNTZbF4wCsiHlW/o46dWzJ49G6UU9957b6vLeUIydxMtzfdf6vR2vcFRMtlam97d+y1It0edPtBV1rtZV1QNGO8nU8bmRCxjNZs4IL/5FPQNeyWrV4ho2mrEFiB1eoUQouP8fh1eozfRhs1iIjvZCPb6NcGzK/q7qlIjk9ae3npooTMZvV57VvN2nJXB60opDp6eSUquhdoKF+//cx3+KGXyeoWQurQqYzjWFBOmlGz8FuN3g9lbHxYMb41SKpjVu7ewqsuH2q0cofV5O5fRC+DKCKnT29SQLTXPeB3uLazu9PZ7I3ejl23f7qOuwkVyRvP3OVtdc31eT8pQXJkH4E0wXjsWdzV2R3Pozh/jZK6BXvKgv2gr0Bs4dLYCuAYYpLW+XGv9kR4IBU9ETJ2tzxsw0Or0aq35dvVq7r/7VmadcixHHDicY8YWcMZxE7nmyst46623eqyW0Mcff8w555xDXl4edrudMWPGcOONN1JaWtrhbQaC361dzj777C68F+FuP31cxLREqznq9K7erznK0fgjR/STjsFd7LMtZQSe9ocPyyA9MXomxvgCqdMrRFu2tTPQm5PSnHkmdXqFECI+NU4PgZ8uKQkWbBbjZ3V/Ld/Qmoz8ZA6YnEPmsNb7vJtCmrH5rHE2Ywsr3RBe49ZsNXH4udlYExUq0Y3X20vLETVlsmoN3vQRxjSl8CQ3Z5xa6/e2e3OpTYHefbv6WDAzRumG8j21URY22JJih63C6vRWGSUxUvOMx6Z8d+xt9mVbv92H1+MndZCZjLzmM7Kstc31ed2pQ0GZqC+YHJyWVPLFfh2n6DmtvxvDn4CXtNY72lhODDBdkdHbct3+Huh1Op1cc821zJv37+A0u92O1WaleM9uivfs5r1FC5g8eTJvvvkmQ4cO3W9ju//++7nnnnsAMJlMpKSksH37dp588kleffVVPvnkEw455JAObz85OZmUlOgBh8zM7gt+nnvYYG5+/TtCn1l/Pu9gZk4a0m37BJg5aQhPfLyZHRUNYdOXbiqjos5FdkofOr1qP1i+uTx4/aQoZRsCJoQGeqVOrxBRhZZuGBOlEVtAaEZvmWT0CiFEXBwtyjYE5KclsKGplG1/asjWmoIx6fjt2ezd62l1OXMnm7EFt+OMbGZmT7Nw3BX5uP2N7NxVyJgxYzCZelnZjKYA55Kq26n8fgKDc72kpoInuYCEamOetb4YV1b7ElJScvtoMDNKoFdrzedvbgUgb4KViafntXtzoQ3H7IGM3qbHprK4Ieo6fd3GlcabTO6B1rC+Ji0zegHqC44jvfB9wGjIVnnIz/fjSLtfYpotahZyYlrsxpADQauBXq31n/bXQETf0lWBXssACfR6PB5mzJjBsmXLMJlMXHj5Vcy+9gaOn3ggO2s15WX7eH/hmzz7+F9ZtWoVxx9/PCtXrtwvwd7//Oc/wSDvrbfeyh//+EdSU1P58ccfufzyy/nuu+8477zzWL9+PQkJHQtQ3nbbbW2WtOgOFfVuWj6rDhmSvl/2HVqKIyfFRnmdm1qXlyf/u4U/ndfxoHl/o7Vm+ZbW6/MGhGb0SkM2IaLrSOkGyegVQoj4hDViS2oOKOSnDryMXoCGhgas1tZr44aWJYi7GVuMGr2hbElmbKTwyd9282Hj7oj5PV57tKlkQYnnIBpcGYxpSvwIz+iN3vAumkAws08109IaKgubb2cZNXp3fl/Bno0OLAmKMcfFl+3tyhgTvG6r2YHyuUjKsnHo2ZlY03xorSOaPPdlVaUNlGyrxmSBwQeFf88LrdHrTjXiCA2DJqObOiMlVvyAyV2H3xb7+2Ffc8X9x/H8LZ/h9fg55MIEjj5uUrA53UDWyw5zib4ivHRDx59GoUFibz8O9N59993BIO+DTz3H3fc/woTx41FKYbeYyM7J5fJr/pePP11Gbm4uu3fv5vLLL98vZRzuvvtuAGbNmsUjjzxCaqrxxevggw9m8eLFwezeZ599ttvH0tWifcEODYJ0F5fXR2mtsW+l4L6QwO68VbvYVtb9Y+grNpTUBoNMGUlWDm0lEB+a0bultA5Pb63BJkQPaXT7KGpq+mhSMDIn9hfd3BQJ9AohREeF1edtkdEbsG8ABHr9Pj9bVpdStrsWi6X1k4U7k9Hrt6aildHozeytR3ljP7beGL2Pe7z2aOUO6nxZNPizsFh9pOZ0MtCbZ+W4q3I4+Jw+FLRrqARXU6kJWwok5+Lz+fn8LSObt+BwK8lp8fU00dZk3CnDAFDah616ByaTIv+AJKxJRsJVf/CvO1bwzA2fMO+PXwLg98KKZ8tZ/s+m54zWWOuaSzd4mh4Tnz0zmCWutI+k0q/378C7Wcm2arweP0lZpr7VlLCbSaBXdEh3lW4YOXIkSimWLl3Krl27uOaaaxg2bBh2u51Ro0Zx2223UV0dWYcotBGay+Xi/vvvZ+LEiaSmpqKUoqqqKris3+/n5Zdf5ic/+Qm5ubnYbDYGDx7MxRdfzKpVq1od76pVqzjnnHPIysoiJSWFww8/nCeeeAK/P3bAqbi4mCeeeAKAK39+LTPOPR8Aa1Mtr0Rrc3faEWMP4plnjM6Yy5Yt47333mvjEeycH3/8kbVr1wJw++23R8wfOnQol156KQDz5s3r1rF0h321PRPoLalyBmvODkqzM+OQQRw72jjlzOvXPPifjd0+hr4iNJv3xANyW30/SU+yMqSp0Z3b55eAuRAtbC+vC773jMhOJsESu/t5bkjWmTRjE0KI+Djqm4NHoRm94TV6+/97a02Fkw//70d+fK8aszn2Zw5+H2ZP8/c2vzW+QC9KhZdvcFXFOdJeoHI7+zxG47CULH/w8QoN9FriCPSazIrkjAQ8Hg8+Xy+tS9xSWNmGUaAUPy4voqq0AXu6iVFHZnRos67MkIZsVVvC5jmd/eOAS6wDFe4GIw5hdjkwe43GiD5LMr6EjOAy9YOODV5PbqrTG6vucV8rebBng9GcMX1IW1VpBxYJ9IoO6e5mbFu3buWoo47i+eefp6qqCqUUhYWFPProoxx11FGUlET/EHQ6nUydOpV77rmHjRs3RnzhqK2t5fTTT+eKK67g448/pqKigsTEREpKSpg/fz7HH388Tz/9dNRtv/baa0yZMoV3330Xh8OB1Wrlxx9/5KabbuKiiy6KeR9feOEFPB4PZrOZG359a3C6zWy8/Oy25jE6PT4uvPBCDjzQqDX097//PeZ2u8Knn34KQHp6OpMnT466zOmnnw7AV199RV1d3wqsRfuCvT+Cg4GMOoChmYkopbjnrAkEzhr6eEMpX2yr6PZx9AXLNoWUbTggp83lpSGbELGFHsgak5vc6rLSjE0IIToutHRDVnJI6YbQQG+UhIP+pqrUqIFqT289rGBqCkAB+KzJYGolKBxDaEM2s7My7vV7lKcRaooo9YwFICk/MTjL28GM3lAuVx/5HA8N9GaOwlnv4at3jZIWw45JwJbQevmPWJwZzYFeu8NoyFZX7mH78ka+freww8PtS0LLNnhSh0JIuYr6guOC15NLvgStmXp9AafdPIRTfj0Ys9VY9rI/H9uz5U06YNd6470gY1jHnjv9lQR6+5nNJ5zIhoPGR1w2n3Bil+7H5wvJ6DV3faD3tttuIz09nc8++4za2lrq6+tZuHAhOTk5bN26lSuvvDLq9p555hk2b97Ma6+9Rl1dHVVVVRQWFpKcbPzgDQR4jzjiCJYsWUJDQwPV1dVUVlbyl7/8BbPZzI033sjnn38ett1t27Zx1VVX4fP5mD59Otu2bcPhcFBdXc2jjz7KwoULWbhwYdQxLV26FIAjjzySnEEhH+RRMnobPcbR2PPOOw+AFStWdOsR2vXr1wMwfvz4mA0LJkyYABi1VDdu7Fgm6rx58xgxYgQ2m42srCymTJnCww8/TE1N9wbqeqp0wx5Hc+H/oZnGqdOHDElnVkgTuPv/sx5/Py5X0h71Li+rdzZ/UW+tEVvAhMFSp1eIWLaFBnpbqc8L0oxNCCE6o6qVZmwBAyGjt72B3tCyDX5bfDVYA0Lr9Fpc0ev09lqOnQDBjN7UQc3Pk46WbgDYt7WRdW/VseqdHV0wyP3AETLOrNE46z2k5dhJKzAzdHzH+6i4MpsbsgUyev1eTdlmD7t/jDwbuD+y1YXU500J7/PTmHMoPosRD7E27MVWUxicZ7IockYZB6g2ry7u/oF2oYYaN+W76zCZIWdE6wkOA40EevsZX3l5XNM7yhtSqqA7mrG5XC7ef/99TjjBOKJkMpk477zzmD9/PgAfffQRK1asiNheXV0dr7/+OhdffDE2m3F0fcSIEVitVj7++GMWLlzIuHHj+OSTT5g+fTp2u/GmlpmZye9+9zv+/Oc/4/f7efDBB8O2+8ADD+B0Ohk3bhyLFi1i9GijQ2hSUhK33HIL9957b9SSEtAcTD3ssMNwh9QUDWb0Wptfhi6vH7/WTJw4EYCamhp27doVtr1AeYuOXAoLC8O2FciMHjx4cNSxt5wXK5O6LVu3bqWkpISUlBSqqqpYuXIlv/3tbzn00EODpSO6w74oWWrby+u7vfHfHkdzRm+g1ADAbdPHkdAU4P+hqIaF3xVFrDuQfLm9Ak/TQaODBqWGne4Yy4SC5lP91kugV4gwW0POWBibG0egt9a1X2rCCyFEfxGzGVvId5n+UqN39erVwUtLjqZAb2JbGb0hjdh81o7VlA0r3RCjIVuvVbkdrRX7mjJ6MwY3fwb7EjLxm43bZk8dppCgeJsUNDr8lO2MY52eFFa6YTQZeUlM+mkmB/4kufXSH21wZYQEeh2bQWuSc6woBfUVHjyuPlLaohOsIYFeT4tALyYLDYOOCt5MLvkybHbuWON9a/t3ZfQlezYaCUOpg8wk2CWjN5QUsuhBGw4aH3PeoD/9icyLjXIAjtfns/ePf4y57PiNG9q1v5Lf/4GC+/4MQOMPP1L405/GXHbkm2+SeMjBwfWq3ngjcqGPjfounSndYAprxtYcBL3ooosYO3ZsxPInn3wyxx9/PCtXruTNN98MBoIDJk6cyPTp06Pu68UXXwTg2muvJT09+hHDyy67jLvuuotPP/0Un8+H2WxGa82CBQsAuPnmm4PB4VA33XQTDz74IA0NDRHzKiuNN6CsrCw83uYf0jazCQ9gNpmwWUy4vX601rg8PnJymk9hr6ioYNSoUcHbubm5Ha411PIDtL7eOI0qMTEx2uIAYV0r4y3dcMQRR3Dsscdy1llnMWTIEEwmE1VVVbz++uvceeed7Nq1izPOOIPvv/+e7OzsuLbdHtG+YLu9fvY4GhiR3X1H/Yoc4aUbAgZnJHLtiaN5+lOj4cCcJZs445ACEm0d/2LTly3b3Pxloj3ZvAATCppfu+uLa/pdJ10hOiP0jIWxbWT0piRYsFtNOD1+nB4/9W4fKQnytVAIIdojVkZvdrINkwK/hop6N26vH5ulb+dWHXnkkTHnVe01fvskZbUeZImV0eu/cjaE9FIJysjA9OLcsEmhpRssrZRusCWZgnVLQ/Vo7VHHDjSKk9P/xu7k00jJOKt5nlJ4kgeTUGNku1rrS3C1s1ldao7xuFeX9pGDCi1q9NbW1uJwOEjP6liWd4A3KQ+fLQ2zuwazpw5Lw15ILiA520JduZfSnVUMPbDrf2v2Jrba3cHrntShEfPrC44jdc8yAJL2fonjoEuD83JG2lEmqNjVSH21q880NUvJtDN8YgbmtD7y/N+P5Bu96LROZfSGBGh8IdlE06ZNi7nOSSedxMqVK/n2228j5h133HFR1jCsXLkSgL/85S/MmTOn1XE1NDRQUVFBXl4e27dvDzZzO+mkk6Iun5KSwpFHHslnn30Wc5t+DRrjPlpMprAgd6LVjNtrfCFp9IR/MXG7wwuvf/113+mU+Zvf/CZiWkZGBtdffz3HHHMMxx57LCUlJTz66KM88MADXb7/0FPmkm1m6t3G0dxtZXXdGujdExboDe96f8O0Mbz29W7K61yUVDt5fsV2fnXKAS03MSAs70Cgd2hmIikJFupcXhwNHkprXAxKj687rxD9kc+vKSxvfu9pq3SDUorc1AR2VxrrlNW6JNArhBDtFCuj12I2kZOSEDyrrKzOFXZ2V38TKN2Qmt16EDUsozc0iBktyBtjemjpBnMrpRumXt9cCqGu3MOPH1ZwwPFZHHf6oa2OsVtVbsek/Iy1r8R24KE0tkhS8CQPCg/0hpQiaI09zYzZpnA3+PtGgK7SuI9FroNZ924CuUdux55i73zShlI4Mw4ged83gFGnty65gNQ8G3XlXvbu6PuBXpvdjNsZmZkcaKpmrWs+U9SdOixiudCGbEn7vkV5nWiL8RvKkmAia0QCdeVuykuqSU7P6+rhd4vBB2TQoNKorx+YSVOtiesbvVJqO7BPa31smwsby38GDNZaj+nI4Pq79mbiZl58UTC7tzMC2bwAiYcc3O79F9z357B1AX4sqibQ2rszgd5YNXqHDBkSbfGweWVlkacW5ObGDhYFyg5UxfpC0UIgOzd0P62VOIg15qysLIqLiykLKZ9hs4Q/ZnarmepGIzPA6fFRHrJsRkZGu8bbEYHaxY2NjTGXCc1STknp2KlW0UyaNIlLLrmEl156icWLF3dToLf56N4xo7L4tKnx19Z9dZxyUH6X7y8gtEbvkMzwL/cpCRZu+cmB3P329wD8fek2Lj56eNhp1APBzop6CiuaTvezmjlyZGYbaxhMJsX4glS+LjS+4K8vqZZArxBAWaMOlgfKS00grR2nsOWkhAd6R+VIfTMhhGgPR0hGb2igF4zyDYFAb2mNs98Get1OL846D8oMyZmtB3rN7uYzTnztzFZtKbx0Q/uasaXkWDnm0nxqa2tpbGxs9SzGbhWSyepOjvzNGNqQzRJHnV6lFKk5VqqK3ewtdDDmsEGdG2d3clZDQzl+bWJF3c8p/7EeV4KH8Se1L9mjLa7MA4OB3gTHZuqGnkRqrpUSYN+uvl/ubcwReWxYWcLwYxI4cEpkA2traEZvSpTnWMpg3KnDsdXuwuRzkVj2HQ0FzWG9Q8/IosFVhz2z75Ty8vv91NTU9NzruheL9zySkcDwOJYf2rSO6Ef8WgezbxUKcyeOwMUK9HZ4e63U9vE3lYZ4++230Vq3eRk5cmSnxwNGozOAdevWBadZzeEvPXuLhmyBZc1mc7AecHcIBK6Li2MXXg+dV1BQEHO5jpg8eTIA27dvb2PJ+Hl9fspDGgwdN6b5KG53NmTz+PzsDQkwD86IDEJedNRQDmjKtqt3+3js483dNp7eKjSb97gx2SRY2n8kdnxBaEO2PlKTTIhuVlLffDZIW2UbAnJTwuv0CiGEaJ+qkIze0NINEN6QbV8/bshms1u4+v8dz2E/TWmzvqo5JKO3w83YEkIzeqvavZ5SCrPZTGlpaYf22yUqd7C67qf80DCdRntktmVnGrKl5BrPv14fzGzK5t3UOI1yzyhsySZGH5PRZZt3ZTSfIRloyJaaZzw2FXvqu2w/PWXPJiPJJXNYZHKQyV2LxW30C/KbE/AmRg+e1xc0n/3csk6vJcGE3W6noqKiq4bcrfZscrDp62Lcjd6YTeUHsu5+RKxAZIEc0W3MOZFHd1qb3hGhAVmzSXXqVItYgd72BB5by96NJj/fyOBs2dysLaH7aW9ANNTJJ58MwNo131JaYpxS0bJWV2JIQzanx8eiRYsAOOaYYyJqAh999NEMGjSoQ5fdu3eHbWvChAkAbNiwIRgIbynQTE4pFQxa9wUV9W4CT6nsZFtYcLA7A717q53B/eanJUQNYFrMJu4+q/mxfO2rXWwuHVgBy2Wbm7PW21u2IWBCyP9yfXEv/1IrxH5SXNeBQG9YQzapbyaEEO0VVrohOTybNbS57L5+8N4a2ti5Ja/PS0Jq2yGF0AZjHW3G5gvJ6LXE2YxNO62semsX33y4o0P77hSfB5+jmNV1F7Ks5n/xp0fmzXUm0JvaFOgt3917f0v8644VPPPnSp7Z+zaf1PwaAHe9n1UvdV3D+NByFwkOI4kmNddK5nAbGcP69qn9NeWN1FY4MScosgYnRcwPb8Q2BFT012R9SAZvcskXEfNtNhuOfbXs213V+UF3szUf7uKTFzZTtbv/N9rriG4L9Cql0oA8oI+1xOzbDlzxGeM3boi4HLgidu3YeIV+sfH5ddjteCmlopZ+WLZsWcx1AvOOOOKIuPYVqN/7/vvvx7Xe6NGjg+UTli9fHnWZ+vr6qJ1oAWbPno3VasXn8/H8M48DkRm9VrMp+Di8/87bbN5sfDhddtllEdsrKyujtLS0QxefL/yNMBCErq6ujln798MPPwSM7NtAqYeusmrVKoCwZnNdJbRsQ16aPSzwsXVfXbd1mN8dUrahZX3eUNMOzOXEA4wDMH4N0x9bzpSHPmHhmqKY6/QXb67ezX83NGdVBOpTt9eEwSGB3hIJ9AoBUFLf/J42Jjf+QG95Xcc/y0W4hWuKmPLQJ4y6870B874uxEDi9PhwNvXUsJoVyS2a6uanNgd6S6M0Bu5P3G53u75Tmz2dz+j1htToTXBsZPSic0kt/CDqsqmFHzB60bkc+OpkRi86FzZ/TfkWL999tBtfnN87O61qF5WeIfiwkW7ZS0Jq5Gd0ZwK9GUNsDDsikbwDe28ZuMaa6N8xojXN6yhX2ii0yahMaqsvxuSuw5Jg4sgLcik43BrxO7gvCWTzpg0yY46SRGSrbQ70ulMiG7EFNOQdgd9kHJhKqNmBpT48y71kQwPfvVbPl4u2dcWwu43P46d4i/GY5IyUsg3RtBroVUpNVEpdEbg0TU4MnRblcqVS6kZgMWAG+k7nKNEmR4M7rMGVRlPkaOxUsDc00Bv4mvD6669HPZ1/+fLlfP755wBceOGFce1n9uzZACxZsoQPPoj+pSDA4Wg+PqGU4oILLgDg8ccfx+WKPAXrySefDKtlG2rIkCH8+tfGkcs3Xv4XH7yzAFuLQK9SCrvVzPYtm3jgntsBGDFiBFdffXXE9goLC8NKTFTWu/h+TxVrdzuCl+/3VFFZ72qzHMWECRM47LDDAKI2qCsuLubVV18FogedW9PWl761a9fy2muvAXDWWWe1umxHhD5P89MSGJRmD34Rr3F6uy2oEdqIrbWabEopjh0d3hSgqKqRuxZ836+DAgvXFHH3wh8IfXb8v482xXWfD8xPJfC2UVhRT73L27WDFKIP6khGb46UbuhyC9cUcdeCdRRVNaIZGO/rQgw0jrCyDbaITNfQ0g2l/bh0w6fzNvLB3zZSX9Z2sC4so7epRq9ucaZhmCg9SpL2NifVKMDasJeCL+9l2EfXMuiLe4OXYR9dS8GX92Jt2ItCY23Yy+G77iYtrRFnrZcNX+zn92PHDko9RlmB7OTSqJnRnQn0JmdZGTMljcS8AX4itdmKK605eShQvgGM36VOZ9896FIUCPQOjt5iy1oXWp83dqBXWxJpzD08eDt5b3j5hozBRhC4eFMNXk/vDYyXbK/G6/aTmGkiJUqZRNF2Ru8s4IWQC0Bai2ktL/8C/h9wIuABHuzyUYseU1rtjAjg+bWmtLrjb5zRavzabDbOOOMMVq5caezD72fx4sX89Kc/BeAnP/kJU6ZMiWs/M2bM4Pzzz0drzaxZs5gzZ05Yo7XKykoWLlzIueeeyy233BK27l133YXdbmfDhg3MnDmTHTuM034aGxt5/PHH+f3vf096enrMfT/44IMcecxx+P1+7vr1tdxx601s3LgxOL+srIx5z/+DK2adjqOinISEBF5++eV2FRYvrXbi78T/JNAE7a233uKOO+6gttb4IrZ+/XrOOeccamtrGT16NNdee23EunPnzg2eylVYWBg279///jcXXngh77zzDpWVzQ0Tqquree655zjllFNwu93k5eVx2223tWus8QjNoMhPNbq5jmmR1dsdikICvUMzW///vbIqsoxIo8fHnCWbunxcvcWcJZsiMngbPf647rPdag5mLGoNG/f23lPVhNgftNYdq9EbWrqhrv8GI/anOUs20ehp+R7Xv9/XhRhoHPWhjdgiG1/mhQV6+25wqS2l22uo3N2IpR19FswhgV6/LQ3t86GfetqYcNppmBYtRN16q3H78MMxvTg3Yhs5PzwXMU1pP0nla0kv/E/wklS+FqXD34fN/kaOSDASTL75YCe6C3rDtFvlDvZ5xgKQlh7994fPno3fbDxvzO4aTJ74fqdYLBZcLhde78BOfggr31C1heX/LOHjx4r46vla5t66imdu+IRnbviEf92xogdHGb9jzhnNhOlZ5I6OHtS01TYfvPCkxg70QuvlGxLTLaTkWvB5NDt/6LqyGl1t93ojtpA+1NKpMqL9WVuB3kJgecgFjODt8lYuS4F3gAeAw7TWfetVJFoV6Ojd3untEVa6oekz95FHHsHhcDBlyhRSU1NJSUnh3HPPpaysjLFjx/Liiy92aF8vvfQSM2fOxOl0cscdd5Cfn09mZiZpaWlkZ2cza9YsFi9eHLHemDFjeOGFFzCbzXzwwQeMHj06uN7NN9/MzJkzOe+882Lu12q18vd5Czhz5k/x+/388+9/Y/z48eTl5ZGenk5eXh5/vOt2aqurSc/I5Ll/z+fEE09s133q7P/kzDPP5L777gOMrN7MzEzS09M5+OCD+fbbb8nJyWHRokUkJMR3OpDP5+PNN9/kvPPOIzs7O/gYZ2Zmct1111FZWcnw4cN5//3346633B77QgO9TV+4x4aczry1rHsCvXvCAr2xSzcAFFc1xjW9P+iq+xzekE3KN4iBbV+ti8am33apCRbyUtv3fh1eo1cCvV1hIL6vCzHQVLXI6G0pL6R0Q39txqb9mup9xtmMqTltf+ZEZPS+9x5s2gRZWairZhszJh5q/N2wAe3xRGzD0tC5ZmrjTP8hIdVEXYWbbWv2dWpbcancHszoTc+NEZRSCm9SfvCmpX5vXLuor/BQut7N7k29Nzi3P4Q1ZHNsjlkaIlYpid4qNTuBtBE+0nKiJxGFZvS2VroBwhuyJe39GvzhBwfyxhr72PJNfM/B/Wn3BiPQmzk08kCbMLQa6NVav6i1PjlwaZpcGTotyuVUrfUsrfU9WusOpy8opVKVUucqpe5TSr2vlCpXSummy0HtWN+klLpOKfWFUqpKKVWrlFqjlLpdKRX5iSzapWVt2YCWpQjiYYlSumHs2LGsXr2aq6++mvT0dHw+HyNHjuTWW29l9erVFBQURN9YG5KTk3n77bd59913Of/88xk8eDANDQ14PB7Gjh3LRRddxAsvvMBTTz0Vse4ll1zC559/zllnnUVGRgZut5sJEybw+OOPM3/+/FaPJnn9mgS7nQefeo5X3vmI66+/nnHjxmG1WqmpaQ5SHXzYESxc+hVHnzCt3fepK/4n99xzDx999BFnnXUWmZmZuFwuRo8ezW9+8xt++OEHDjnkkHZvK+Dkk0/mvvvuY8aMGcEavDU1NeTk5HDKKafw+OOP88MPP8Rda7m9Qk+VCzTFCM3o3dZNGb17wmr0tp7ROzhGaYdY0/uD/LToR6Ljvc9Sp1eIZqFnKIzJS2l3dkOulG7ocgPxfV2IgcbR0HpGb+h3ndJ+0IwtmlqHE6/HjzVRkRDlMWgpNKPXZ0pEL34XAPWL/0WlGN/PVUYGDBsGLhds2RKxjdBAaNh0Wzolk/8QvHht0c+y1Mk5jDjSKBvx9fvbu61fR0vusl04vEMx4SVlSEbM5TpTvqF0ayM7v3CxbU1Z2wv3Y86QjF571eYeHEnXamxsRGuNyRTjd39oM7bUYa1uy50+Gk9iHgBmTy32yvVh8wOB3l0/OvB3IpmvuzTWuSnbXYsyQ86Iru0f1J9EL/IR21XA/kpJOBV4uyMrKqWswELgzKZJbsAHHN50uVApdYrWunsiPf1YSoIloh6vSSny0zteGyW8GVvzB+7w4cN5/vnn27WNuXPnMnfu3Hbv86yzzupQXdjJkyfz7rvvxj2G0FPVjzpmMpeecxoAtbW1pKam8thjj3HLLbew4fvv+ObLz/nJWefh8/sxx3gzD5WaYKGyC/4np512Gqeddlpc68yePTtY+7ilESNGcM8998S1va4U+sU68IU79HTmbfsho3dIG4He208fx10LvqcxpAaS2aS4/fRx3TK23uDU8bnMWxVeky3Rao77Podm9K4vlkCvGNhC38/a24gNwjN6K+pd+P0aU5QGqaL9bj99HDe//l1YHfIEi6lfv68LMdCE/hbKjJLRm51sw2xS+PyaqgYPTo8Pu7Xt8gZ9SVWpkdhgTze16+CiyR3SjC0xE/XoI/D556ijjw5fcOKhsHs3rPseJkwIm1V22C8Y9NUDmHzN3/H9Zjv7jryV2pEzgtO0ycKgVfdh8nvClis77BcMGZLE9i9rqNzTSHlRLblDO9YYLh7OsnIG29ajtYLMETGX8yQPDl6PN9CbmmME2yuKemd4w57gxemKDD0lJERmbndGaEavrSqy30+o1f/ZwcSTh2FLjDcktn+tXLCVutp6kof7SU2NnK+8jVgajUxurcx4YhwQaV5B0TBoMuk7jLOYk0u+xJkzMTg7OdtCYrqZxmofRVscDDsoO9aWekSdw0XmoCR8ykVComT0xhLXs1pr3bHz5TtuH7Aao6FbEfBsO9f7C0aQ1wncAPwb8ANnAS8CRwP/BOLrLiVwecOLctvMJvLT7VG/5LRXaDBzP1ZL2q88IUfDbJbI4O3NN9/Mjh07eOqpp7j7xutJz8xizHlnkJzQdqDXFaVzbG5qQqf+J/1By2ZsEB4A6Y4avV6fn70hJSNaa8YGMHPSEAD+8t76YHO41AQL5x0+uLXV+rQ6V/h7yJCMRG4/fVzwsWivCSGB3k17a/H5dYuDRkIMHKHvZ+2tzwtGvevUBAu1Li8en6a60UNm8sD+7OissyYWcPPr34VN+59jR8T9HieE6L3aKt1gMinyUhMoaeqXUVbrYlhW6+W8+op/3bEi7LT32r0+Pn6sCFuSianXxzjjUmvMITVnfbY0VKIVzjgjYlF16ET0mu8gSp+SQDA3d+3fsDSU4k3Kp+ywX4QFeQPLWRr2kbfWqAGslYm9x9xN7cgZmIGDp2fit7owJ+2HerZ+H2n13zIzy2h6tSXlk5iLdjSjd/k/S4IlCsp3NPLMDcY+EtNsXP3wCR0ZdZfSWmNLtGDz7uW8zD+SatmHN2lQ1P9dZ/kT0vEk5WNtKMXkb708wzcf7OSA47Kx2lN54befRy3n0NOPofZr1n9ejKvey1GjM6MuY60Lqc+bPBhMbYf46gcfGxborTj0uuA8pRR5YxPZtaaOvTt7X6A3d1gqp//qALZtbT2QP9B16PCFMg7bzQJ+AgwDErXWp4bMTwaOBLTW+rMOjm2x1nphyDZHtnNsg4Abm27+tkVw+l2l1NUY2b6XKqX+qrVe18HxDThOj48GtxGkUUoxflAqlk6UbAiIVqO3vwnN6I1VauHxxx9n45btfPTBe9x8zWWMHvIRp0yZ3Op2XR4f9e7ILykJUYLJA01ojd5ArbQR2UlYTAqvX1NS7aTO5SUloeuO4u6tceJrau6Qm5rQruyNmZOGcPbEAibd9xG1Ti9VjR62ldUxNi/KIds+zu/XfLaluXbYu78+gUOGxG5i2Jrc1ARyUxMoq3XR6PFRWFEfVyajEP1JRwO9YLyWal3G50hZnUsCvZ20s6Ih4qtMmmScCNGvtFW6AYyyYYFAb2mNs98EemPVNo1VCxVAeRtQ2oen3kTVzjS0H1Ssr8jHTsZ03LExZhpB3PYEBx0H/Yyc75/F5HejtJ+GkAZUuWMScbvNFBUVkZmZ2b3NnGqKwWc8Zh5bBn5b7M9oT/Kg4PV4Ar29vQ7tvsJaaqogyWQjxVxO7YjplBz/l27bnyvjAKztqOc8fHICm7duwm63x3ysevoxrCiuw1XvxZasSMuJ1YgtpD5vG43YAurzj0ErE0r7sVeux+Sqwp+QEZw/4qgU8g+1kJPfO89EcDgc2BLku1Vr4o4GKaUOANYBbwDXY2TOTmuxmBN4HliqlOrQIRCtta/tpaK6AEgAqomSAay1XgRsBhTwsw7uY0AKPU0pzW7pkiAvtCzd0D+528joBTCZTMyb/xZrdzv4fP0uDpxwaJvbDf2iGSpalu9A4vb6qag3nq9KQU6KEbiwmk2MzGmu5dPVdXrDyjbEUY/RYjYxZUxO8Payzf2zkcKPxTVUNv1fclJsYVm5HSEN2YQwdCbQmyMN2bpUtLNFpLyMEP1LW6UbAPJD3ltL+2lDtvYyu2vRGkpWZ1C+Lgn90ssxl+2yoKvJgitjTPBmgiO8XqvNZqOhoYFdW7q5KZtjB+WeEfi0GXdy62d2hJduKO7ece1HW742gq5j7SsxKX/Y/ewOYXV6rdFrZNuSTIw+Kou0tLTuDfR30p6NDgDSBlti1ucNy+htoxFbgD8hHWeWURpFaT/Je78Om29LMpOSnojD4cDv7z1xhcY6N1X76qmpqYm7UfxAE1cqm1IqE/gYI4t3HfAmcBsQlnqmtfYppf4OPIIReF3RJaNtn0DTuOVa61jV7z8EDgRO2T9D6vu0NmpMBXRlWQBnSH1SfxcVxXc0uCmtduL2+bukvERnhWb0ttYkzW5tnhf6uERj/E+av2imJFioa8rKcg/wQG9ZXfMX6pyUhLCDEmNzU4I/xLeV1XHYsIwu229ooLetRmwtTT0wlw9+NLqbLttcxs9PGNVl4+otlm1u/jJ94gG5na4FOqEgjeWbjaYT64trOHti618cF64pYs6STRRXNTK4gyUj+pqBeJ8Hmle/2sm+kADtmp2VjMppf3OK0Dq95XV9IxjRm5/X0eq/b9grgV7Rtt78vBbhQn8TZcTI6A1ryFbTPxuytZfZXUNNYSL1JXZMNtCzZra5jq6ogOpq1OjRHd6vK+MAEis3AJBQtYWGQcc0b9+v2fQfF6v3/chlf0olI697Mq4biwp5veJx7KqGC0a82uqyoaUbLPV7u2U8+5vfr9nyjRHoPcBunOgdmrncHVwhgd5LDn6cPSdHNlkPZbX23szQok1GoDd9cOywna2uOaO3vYFegPqCY0ms+AGAgpW/I/e7p8LKaZhMJrweL6V7KikYntPapvabzV+VsmL+FvInWDn0dGnE1pp4z1m+FSPIuwQ4R2vtVUr9khaB3ibvYAR6j+/cEOMWqNr+YyvLBFoLjldKKb2/Wm72YXUub7DOrMVkIsXeNae7OxrcwcxLgPe/WIdJqTabWLW1zSJHYzBo7Pb5KWoKwPVUsNfja36KxSrdAEZTqgCnx4/WOuZRxnqXN5gpbDYpclISJNDbJPQLdaA+b8CYvOTgu0NX1+ktCgv0xveFceqBzR+gq7ZX9MvGHctDMpVPOjC309sbX9D80bO+jYzehWuKwhrfFVU1cteC7wH67Q/phWuKuHPBOpwe4/1gINzngWbhmiLufSe8W/LvFv6IyWRq9/84N6VvZfQuXFPEnW+tw+ntnc/raGeK7KxooNbpIdXee39Mip61cE0Rv31rXfCMrN72vBbhwjJ6Y5S7Cf3+GdoguC8qKmrOGHz7zxvbtY7/ytlQVQUYndwbMeqLahQqK6vVdfW6dejf/wHGjUM9/NeODBkID/i1zOhVJkV9uRc0zPvDl2HzurIua+n2SmAoWZbdeNOGtbqsLzEbv8mKye/B4qpCeRrQ1r5d8qN4SxUN1W5SrA7yrcb/IDSg3R1CG7IlODaD1sYpnn2M3+enaEsVANkjYsdGrLV7gtfbW7oBwitmKsDasJdBXz0AGCVS6io8rHm9no1pG7nivp6v9Qywe0MlAMk5/es3cneI99z78zCeE7dqrVutXq613gq4gbEdHFtHBd45WjvfITAvpeki2uCoDz9ybeqiN8vSaict4+x+rSmt7vgXotJqZ0RmcGe32Rla6xbN2GI/dhazKRgI9mvdagkGR1g2gS0sG9jlG9iB3tD6vPmp4fWMQk9r7upA7x5HQ/B6vBm9QzOTGJNrHJl0ef18taOyS8fW02qcHr7d5QjePuGAzh8ZPnhw+0s3zFmyMRjkDWj0+JizZFOnx9FbzVmyKRjkDejv93mgmbNkU8TnRLz/49w+VrphzpJNwSBvQG96Xm8NyegNLU21aW9tTwxH9BFd8VoW+09VO2v0Buzr46UbBg8eHLy0W1OQtyXtbkd+1dgDwGSCLVvQDQ1tLx9DWMCvakvEfH+Mkye7si7rvmJjJ3nWLW1nWyoT3qSQOr0N7a/TG0vhlj18/Z8d+P09k9cWKNswJnlVMNba3aUbPClD8FuMALnF5cDsrOjW/XWXfbtq8Th9JKQpUrOi1+cFsNY1B3o9qa0fTAiVsX1xxDSTz0nu2r8BkJRhAQ21ZW4cpfVxjLx7+Lx+ijZXAZA7um8fANkf4k3LHAU4tdbr21zSUAt0rNNOxwVyuBtbWSb0EyMFY5xhlFLXAdcB5Ofns3Tp0nYPID09ndra/vOF3q811Y0hgUo81NZ2TZdSd4yApNvn7/Bj2B3b7AyvXwcDzyYFDfXNb5Q+ny9iTBalCXx9dNTUk2KLDAy3/J8k4MHZ4EFhHInx+vxU19R0WUC+N3I6nTFflyt2Nn8B99VVhi1XXd38rW7dzn1xvbbb8sOO5redyt1bWOrcEdf6o5NcbGu6Pu+/3+Iv7j+1h74p9eJt+pI5Is3ED6u/aPe6dXV1Uf9PPr/GagKP36h/986Hn5IW5fXi9WuKqqIf6CmqauzS50BvUlQV/WOwP9/ngaYr/scVRc3vl99v3cXSpW03MOlJvfl5rbVmc0nzV8zxmSZ+qDA+cxYu+4a6Qsno7WmxPk96Wm9+XotI+6qbv8uvX7OaPQmR3z1Ky5p/K23cWcLSpVX7Y2hdorXXidkOvihfqcwJmsLCwuDt4a1sP3S5WPKHDyehsJDSTz/FefDBbS4fjcWbEByHrXoHO7dvQZtC34djvyd31euuap/xXT7PuoWddQdQ3cZ9zzZnkINxKn7l9rWUZ7aduWhOsOBzRT4HzQma/87diLPCxI+rdjD0OIXFvv9+G2qt2bbO+O4/zvJhcPq2Mhf+ysJu3Xde4jAya40DZdUbV1CeeXiry8d6DE3W2M+F7v48cdVoMscCFjc7d+6MuozyeziwqcyHRrGl3INu52N7YEP0+tSWhtLga9Seb6Zut4mP31pF7oSebfZev0/jdWmsqX7Kq/ZSUR35//L5fNTU1MSsZzyQxBvo1UC78qSVUhYgDeiThcm01s/S1MztqKOO0tOmTWv3uhs2bCA1NVo1i76pst6FboqbJ1rN5GR03X2z1dVEDczazKYOP4bm2mp8UY5admabnVHv8kKtkeGTYDGHjaG2tjZiTPX+RhoDWVUWK6mpkZmhjno3fm38mLRbzGSnp6CUwtZQi8tr/Ki02ZNJtPXf0xrsdjuTJk2KOu/rJRthgxEyPfygUUyb1nzqVoPby71fLAGgrBGOP2FqzAZ58frDV58SOI505kmTGZsX5/OtYB8fvWAUw9/eaGfatJO6ZFy9wYdvfw/sAuDsI0cxbdpB7V536dKlxHoPnrB+BWv3VAOQNerQiEzhepeX/533LeHH95oNyUiMue2+bsiXn0QNHvTn+zzQdMX/WG/cx79+MN53zMkZTJs2uSuH2OUKvvhvsJN9qN7wvC6uasS55BMA0hOtnDd5LD/8x6gP6U3JZ9q0iT05PEHrnyc9Ke/zj8NqbQf0hue1COfzaxqW/Cd4+8zTToraoHrQ3hoe/caoSeo2963/Y2uvk9DJ27Zto66uDrs9MtuwtXMLR44c2eYY/EcfDYWF5O3bh+mss9pcPhb3hiHY6oowaR8HZvhxZTXveytFMdfriv+X9vv51/wqAPKtW1EHHkNmQkar61j2jYZqo2zL0BQ/Ke14rEb+Iva8il1OfvhPJfWlmj1Lrcy4/lAGjdp/eXhTjvew6t2Pyf3eSH7x2rMYPubANtbqAuWHQlOgd3hCdZuPY8vH0OP0U1/jxJ5m4pBDDsFsjvxNvT8+T0pKSigqKooZw7DW7EQ1FWHwJuUzYvQBUZeLxrs2H2tDZC1ob1J+8DWa6Gnk+92VeCrsTJu2vyuyhvty4TYK2UnW8ARGjYqeuVxbW8uECRNISpKM33ijGzsAm1KqPVXRT8U4TLYh7lF1TuAQa2vnTYf+57v23O1+KLxsQ9fWuM1Pt0dknSoU+emxT09oS7QauCbVuW12RmjZhtbq8wbYW9TpjSa0NlhGsjVYxzc0YOn2td7MrT8L7W4c2gwDIMlmYUiG8fbg82t2VXbNqSg+v6Y4JOAyJCP+D5jJo7KD/8Mt++rCtteXaa2DTdMAph7Q+fq8AeMLmss3rC+pDptXXufi0ue+DNt3KKXg9tPHddlYepubTov8spdoNffr+zzQ3H76OFrmM8T7P+5rpRt+emTkqa82i6lXPK9DywGNzUthQhzlZcTAdt7hkacy23vJ81qEq2n0EKgQl2q3RA3yQnjpsL5euqG4uDh42V/UoYcYV9Z936nttFW+oTvV7inG6U/DrqpJsjfgs7UdYPWElm6o6/zjnT3czuTL80nNt1Bf5eatv37DMzd8Enb51x0rOr2fWOrqa8lJbr4f3V22ISC8Tm/8/3er3URGXhIej4eSks6X0OioyspKEhJin+Fpq+tYfV6AssN+gd8cvm2/OYGyw5qj3jkjEzCZwVHkpM7Rs7XGA/V5M4f3TM+lvibeQO97GLWab25tIaVUMv+fveuOk6q6v+e+6TM72/suy7J0kF4URMQGloigRBNTIJpEozGWaKLG5Jdi16gxmmJibDFWFKygiIKIqPS+sMD2XmbL9Jl3f3+8mTf3TX1vyhbY8/nMZ3dm3pu588p97557vucAj0BQAK+Nr2lxw9+TROtF/O/1UUpPHo+FFMDp9sLqEkqPCEjEZNl4kWXUoiTLILlJIgTINMT3PTxPQ4LICARFxEAFsbkk/ryxTzk2kC3YUxQAXB6vGLpGIA2Y0zGfH83f92RHtDA2AKjIC6R0Jsunt6XHIVoT5Ji0campDVoVTh8VCKiIRFAONRxvt6LeF1SXplNj5sispH22lEgJdOc1HVZc8fet2FsfIH+XTCpAETPhQylwWklg/ZMN00dkSp5rVAQPXD5lONjnJMJFUwolYRrFGXrF+ziXCWNr7xv8ZERRRug8/vTSjEFxXB9j/HlH55kkE1GHm3vhOcX984cRGSOyQyeHz59UMCiO62FIIQliizK2yDRqoPWNb3qdHqHCb4iipKREfPQbJkwA1GrgxAnQnvgnyqIFskWDy+VCd1v8/sAA0HqoGgBQoD0Kj7lUViCYhyFC1dbkEIz6NBXmXJUf8f1kehL74XF74bC60d7eDpM74JGb6iA2PyT73SJ/vwfDaDRi76YarH92b0iuUCrR2WjF/s116Grtg0YTmRdhg9hiekAHobf8QjTP/Q0oCRT5d41dgd7yC8XnKg2H7JHC2OnIjoEjvF0ODzqbrCAckDfSFHuFYSgmev8MoAvADYSQewkhOeybhBAzIeTbALYDOA0C6fr3pLRUPvz+wdHMfCb5/va32njIgQ38MuvVshSpSpFl1GJioRlqLhBC5ghDcMqB1eUJCWKjAEy6gbMwcDOEq1bG9tOqOVHl7PHyEkUwIN0naXqNZJ+wnx9MeJ9KYJUT+eZQJXcqAtn8RCagPIiNxdnjAmrXzUdPDqKXJaznj85Jaj8yiVX0NgoDgX313bji71tR0yHcoHMEuG/5afjnD2fjy7vOw8VTAmqJN3dELtsb6qjukA5QTDr1MGlwkqG6PbCPcw0EW+86T/E+zkkLEBUdVtegJyPD9dkHGntgcw08iRKs6M02aVHoqypxenhUdwx8mMkwBicaukIreA439/YrsTAMeeiSEcQGAIQQ5DNig3DWHCc1MjPDvkzCWNKFXU6nE8hejgNkePpGAqvs1AcperXG8PejGgPB1g278fLvtuHT/x6Ck9nnSjA6vxZX5/4cZ6T9V7ba0p0WIELDldXHC07Vv7ktJ/a047lfbcH+Da0wOAPjALepMMpayYMzYzQoEfavtrcWxBOfGtXrBGq/cqHqm3ZU7ei/DIOqHS3Y9L+jaN7nEit3w0HbVyf+r5ToBQSyt2vcleJzjg891vPHCPcx9ZUDFxSu1avx/ftPx8RvGaGLUxB4qkGRRy+ltJ0QchmAdwHcBeDXEESFIIR0QvDkJb5HJ4BllNL+vqv9FMAKAGcRQvSU0nBn9QW+v5/0X7OGHiilsEhmrVN3UhFCkKZXi9/X6/DAoFVqIQ1R6RoMm8sLrXpgyF6XN3CTrpGh6CWEQK9RiYNWh9srEmPCPol8gymxbjiFid6WXlbR2z9Eb4MlQLiUZsXvC7RwXB7wvjAHteVoOzxePmJZ4FDBJta2YVzybBsAYAJD9Fa19eHjgy24+dVdsLmEySKdmsNfvzsDiycHbiyvmFmKD/YJN89v76rHHUvGQ8WdfMGFNUGkksXmRq/DDbN++AbpZAHbfxWb4usnNCoO2SYtOq0uUAp0Wl2StPjBhipGNUuIoMy3urxYt78Zl89UPshJJoKJXkCoOmj2VZkcaOxR7t0+jFMC9WGI3qrWPuyt78a0oOqMYQws2LFRLEu7gnS9uG9bexwYlXvqKNG4F54H/9jjQFsrCqZ3I5vfDgCoX/hnyCUHyE0/BzIyQAzxCygcwYpeSkVl7cLrIqtLa3f3AAQ4uKUJB79oAsLMuRjStbjm4QWR2991AllqQVDQkXaOrPa6jQzR2zdwCspEcfSbFvBeCo2BQGML/A5PPyl6qVoPl7kMup5qEMpD130MjhzloX5aowpjz8rA4U8s2PRKJUZMzIHelPr76PrKLgBARkn079L0BQQrLnN439pYsBbNQ3bl/wAApqZtIe8f/VwQ0tTt68bT128UX491/CcbDqcNaXknb/5QsqF4VEAp3QJgGoBXAHh9n0EAZPr+9wJ4DcAsSumOpLVUPt4C4PS158fBbxJCLgUwHkJ3/Uq/tmyIwer0irYDKo7AnOLZE7MuQOz2xlne1OsIrMdaIFhdA+dX65IoeuWRSQZN4NRk7RtsLq8YtqYiBOn6YaI3GA63VyTDVRxBjin0JnxMXoDoPdaWnLmo+s7kKHrH5qeJCrAehwd76i2JNm1A4XB7se14oGTr7CQTvWk6NXJ8N1xenuInL24XSd4MgwYv//h0CckLCGRzrk/F2NLjxJaq9qS2KRGs2dWAMx/ciFF3vo8zH9yINbviVxzXdISWHEZKdh/sSOZ2OZnAWgUUmeKfrMhj7BvaZNo3DNQ+OcaQqcunB9TLq3fWh1u8X8HujzF5AqE7sShA7LL2MsMYBov6rkB/XcGQgYPhuD7ZkGjfJVfRC0jtw1pOMUUvpRTYvRs4eAhqEji+eU1a5JWCQAoLEyJ5AcBjLIRXI/TDKncv1DZ5qsyy6ek4/fv5MBeowpK8gAzLg87j4r8umWpLjyEXlAhj2OOvacBftiz0sXKVrM8aKDhtbtQcEO79CycYobEGlMn95dELAM7M+Gw7glEyxYiMYg2cVi82v344GU2LCrfLi5YTwkRDXnl08ZC2l1X0xle1Z8+fLnr1antrJeQxALjt4TmFVFh+hAOlFF4vD4vFEtXGYhhSxCX/oJTWUkq/DyALwEIAVwH4LoBzAWRTSr9LKa1JtHGEkFz/w/ddfmSy7xFCxN9BKW0G8Bff04cJIT8gROgtCSEXA3jO994rlNK9ibbxZEZX0Ix1cGhaspGmDxC9NqcXXl4ZUen28KLlAyEE+UzAjG2AfLEopdIwNhmKXiAokM0VWJ/dJxlGDbggFaI0jI0PsbE4FcCGCeWbdSHbCABG57NEbx94PvHtxKpxShIgegkhEjJ005HBQ0LGg+3VXWKoYEWuKawPYSJYs6tBMujyI9OgxuqfzcPs8uyQ9zQqDpexBNGOwTGQXrOrAXe+tRcNFjsoBFL2rrf2xU2ghSsTZyckhgrW7GrAXW/tS9p2OZnAKkiL0uJX/isNZBuofWJzecTJChVHcMv540TLw63HOgZ0IsNic6G9T7hGa9WceB2YVBQI3zk4HMg2jAhg7yFuOm+M+P/a3Y3iBP8wEkcy+i4lit58SSDbwAYZ9TsaG4HubiAzE1pj4H7Eq1WejUB5HtQT51iOEDiz2GAu+YRfWo4Gc79bENfXdjZa8cbWRfim79sAALfcoCxOJdobeB0R1IsWS1xtioZE/YhZHNvVBt5DYS5SwZxlgIbxGk6WdQO/clVMElyy3xMI4iOEYNIFWSAccPSrNtQd6oi9UgJoruoG76Uw5XAwMBPxIeC90FgDQXdyJxOCQVU62PJnis+NYVS9A4H//GoLnr5+I/72s0/xjxs/w7pHavDFPzqx+Z9DV+nen0ioHphSaqeUbqGUvkEpfY1S+hmlNDl10ALamMdO5vUvg94rC1rvHgAfADAAeBGAlRBihRAmlwPgGwDXJ7GdJx28PEW3Xf6MdTKgUXGiCpeCos+p7MaWVQGbtCqYGIWww80nhcxTCg9PRbJVxRHRhzgWJESvj7zmQ/ZJ6M0lR8gp79PLBrFFKj/OMWnFYEGby4umJNx8swRDIopeQGpvMNQD2TYdaRX/T7ZtAwA8sr4S4U5tvUYdtUT6CqbEe/2BZvQ44vNfSyYeWV8pkuJ+2N1ePLK+Mq7PO1kUvY+srwwJpkxku5xMkFg3JED05jI+vXKI3oHaJ8eZCoyR2UaU5RixYEwuAKEa9+0BVD+yat6KXJNoB8Mqev0+4sMYBgu7y4sOq0AeqjmCS6cWoyRTuI/otrux8VBrtNWHoQDJ6LvkhrEBUvuwllON6D3gi82ZNAlqd6Cagdcqs6+hb7wB+sOVwNatcTfFwSg79QqDuaL5o0ZD84lutNpK0OkRaApXmvyy+lQFlkXyJAaA957eA5cjOcKoo98Iqunc0RoQyku8hpP22yKR3czrkv2egKIXAEzZGlScIUxSbHzpENwprBb22zaYi6LbFKhtLSC8sM88+hxQTfxiGmvRPPF/U/PgIHojKYZdtlOP34gHQ9v4MQIopW4Al0Igc7dBsHKgAHZD8BVeQCkdrp+Lgh67WyQodWqVxAYhlWBVvX0KiRd2+TS9GmoVB506QBzb4gx4SwQSNa8Cn1WW6HV6vOB5ih6HG17ev084GLXh98mpbt/QwgSxFZjDz4ISQiT2Dcnw6WXLLhPx6AWABWNy4Rci76m3oMvaP6UxqcBmRpG8cFxu0j+/MQJxGWtANak4HRN9/r5OD48P9g787HCk3xLp9Whwe/mwpC57nA4VJHO7nEzgeYrj7Yl79AJBil4Z1g0DtU/YvtpfmbFiVmDSZvXOhgELrwrnzwsAI3NM4vW6vc+J1t5TjOwZRkywHv/FmQaoVRyumDm4bElOFiSj75JYN8Tw6mSrC9n701MB9KBA9JLJk8C5Av2jYkWvSgX09oLu3Rd3W6SK3viVneEQ6ZrTWiUINfI1VeBVOngN8u+BPcbUEL0LryvC+beWSB6LbiiCIUsFS7MdH//nQMLXUGu3Ew2VXSAcUDQhDWpHe4CM1GWBqhMTwyiBVNFbBdDExsUjZ6cBBOjrdOGZX2zCgVd5PH39Rjx9/Ub851dbEm2uCD/Rm1kafSJJ2xe4NsSr5vXDVnSG+L+xeTvAD2zALR0Agd7JBkWjAkJImcJHASEkit48OiilROajOsy6PKX0n5TSeZTSDEppGqV0BqX0YUrp0GVN+gmS2WqTJu7ZTKUw6wI3TL0Oj+yLDaVUouj1f46JIUNTnci9atUqEELw+9//XnxN6s8r/3RTcYQhqQGHxyu5scw0aiPuk2GiN3oQmx/sQPxYgkQvz1MJqeZX4sSLDKMG033hK5RiUHnIKkFztwOVLcKcmlbF4YyKnKR/R3GEbR3pdRaDbSCdF2FiQs5vCUZDl12cGGIRLvBnsCORfXwyo8FiFxXgOSYt0rQJePQqtG4YqH0i8cD19eGLJxUizVfBc6Ldip21lpS2IRIiEb0qjmB84bBP7zAio64r9P6BDRb8rLIN7TK9s4cRHfnpiV9nlYax+XHKKXr9RO/4MeB4YZvxnAZUpZAamDJV+LsvfsdFiVerQkVvLGx4/iC87tDxVusJgawr0ByFO61UDICTA3da/wSWAYBax2H6ZTlQaYHqvR345v0TCX1eU1U3KICMEhWMZl2QP2///S4A8Opz4NEJFm6cxxbiPasUnIrE79csEzxPoTOooNIQ5JZFFw5pWH9eudYgEeAyj4TbKNhqqDxWGNrlnW/xVEz7LRmCH36y3NrtxLN3fK74c4chhVL5xwmFj0YANkLIcULIPwghyqMOh9HvcHl49PlIUwIgyxD9JiaZMOpUohewy8vLJirtLq9IaqhVHPS+MDOjjiF6FVpBJAOsotdPwH799de44YYbMGnSJJSWlsJgMKC8vBxXXXUVVq9eLZLbeiaQrdfhkSiWo1lp6Bii1+mVT/Ru2LABl156KfLz86HX6zF69GjcfPPNaGmRF1oQCVarFQ8++CBmz56N9PR0mEwmTJ48Gffccw+6u7sT+uxwaOllid7IN5PsQJxNcY8Hrb1OuL3CfssyaiS2IfHiZLBvYNs9Z1QWjNrEt0sw7lgyPqTiwKBR4Y4l42Ouu2xGCdQ+6fQ31V2oCeNp259YMjnUB07ubwkG68/Lbp+haN1wx5LxUIUZIP3ygnFhlj51wPZbo5kKhXjAEr1+n9louH3xOATvEY2KxHWsKoFE0ev7zQatCpdMCQweB2rSJhLRCwCTigIKtkPDPr3DCEJDV6j1U3muCbNHCvEkHp5i7e7GsOsOQxmKMkIFAFqFfVeXNb4wttZTKIyNtrcDLS2A0QiuKBCzw2vMighPAEDFKMBkBJpbQOMck7gyRokBZ9q+BnBuZff90SwPjnzVgrV/2QlHX+C48Li96Gj1gsCLXPVxuBSScP1NiJqyNJhysSDG+Oa9apzYE/+4Y8ysfFx4yxiUzRXONTXjz+tJkj+vbCTgzzxQ4DiCC382GTO+Z4I+xkSSliGuE1X0ghCpfQPj0xvt+P/42f3gFfANQGRS3N7jQl9fH3psnaAJqq+HASgddccrFykH8FMAqwghN1JKn43zc4bRD2Bnqk06tewAsWSAIwRpOrXol9nr9EAnwzZCquZVi2pXlliyubyglPabOhkAXJ7ALJfX7cIPf3gdXnrpJfE1vV4PrVaLmpoa1NTU4PXXX8fpp5+ON998E4b0XNGTt73XKU4gmnRqaNWRtwn7nlyi/L777sM999wDAOA4DmlpaTh+/DiefPJJvPLKK9i4cSNOO+00uT9bRG1tLZYsWYLDh4WEUoPBALVajYMHD+LgwYN48cUX8dlnn6GiokLxZ0dCK1MaF8mjF5ASI4laN7Bll4naNvhx9rg8PLFBKC/bfLSt34/dZGDT0cCN4sKxyffnBQSyFhB89xotdhRnGnDHkvHi69GQm6bDovF52ODzP1y9swG3DSB5aAyaINCpOTxw+RRZvyUYrD/vnFHZIuk+FBW9y2aU4KEPD6EpqOw12vl9KuBYiI1B/CRCXlpgW7bJsBaYOiIzRNRyRkVOXMeqEkQiU6+YVYrXtgvKlvf2NOJ335oksUDqDxxj/IODifeJDNE77NM7jGDUS4jewD3EFbNKsb1GUAWu3lGPaxeM6ve2nUzYUdOF3XWhAoMlkwsV9V1KPHrzgxS9Q/FeLi4YjSA33wz09ULtZW0blPnzAgBRqUBPOw346mtg336gQHk4GlVp4UofBV13FQChjN+eN132+guvC0+89rS4sGtNO5qqevDGg9/g0pumI7PAiPa6PvA8Qba6HlrOgT6FJJzbVASPg4NK7w0fyJaZqejz5CB3lB6j55txbGsv6o61YtS0+O7bKaWwOi3ILhaug2xYmNtUnJS2KoEzcyxMzV8BEALZ+srOS9l3ffL8QRSOzkBhRQbWPrEL9t5QG0pDuhbXPLwg6ufYbDZBPRwDmj5W0SvfAzoSrEVnIPPY2wAEord92g0Awh//lgYndr7djqodbUjLPoYzrxgbskw8OHToEDiOw8yrMrHtuc6kfOapCkUMHqWUA7ACgAXAHgArAVQA0PseowD8EMAuAF0AlgPIAnABgI8AaAH8gxAyPSmtH0bSQSmVWARkm/pPzeuHWeLTK89uoZdZjl1fp+bEQBQPz8OlcMYpUfgVvW63G9+9YileeuklcByHG264AQcPHkRrayu6u7vR0tKCxx9/HBkZGfjqq68wf/58dLQEZkC9jIVFrJtKpdYNH3zwgUjy/vKXv4TFYkF3dzf279+P6dOno62tDZdddhmcTmUkAs/zuPzyy3H48GEUFhbiww8/FGbpenrw9ddf47TTTkNdXR0uvfRSeOJN0g2DgbBuqA+jxkkUU0szxcC4lh6naIEwVODlKbYcDVhOnD0+NUQvIBCBX9x5Lk48eAm+uPNcRQM2NpRt9Y76AQlt9CO4pDs3TRc3ccYSvXPLs6Dx3TB2Wl2wOpN3vvUHnB4v2sKoTN/cURdm6VMH0RSkSpFrVhbGFq7KINVWQR4vL1Gqj84zif/PKc9CWbZAkPU4PNhwKLFKFKVwuL2o8/lfcwQYlWuSvD+pmCF6hxW9wwiC1OM/cA9xydQisUrrYFPP8CRBAqCU4r73D4rP2ZwLNh9EDiwSK7Xoit50vVqs0LO5vGLF5MkOYjSCnHsOyNKlULniD2ITP89n30ATsG9wpEDZmV6gxelXF8CUq0JPuwMv/982PH39Rqx+eAcAoNMzEk83v423ti5V9LkubxqOf5APU4ETo7/vBLd2DchDD4LceCPIC8+De+H5pLQ/GOVzzZh9VQ70pda4qi5tPS7YbDY4nU6o1cJ5lQrrBtoQxYIhiAR3ZCUvkC0WDm9rxmcvV+LVP30dluQFYls8tNf3oavLIm6/aND2BiqY3MxkAr9yFfjLloU+Vq6K+nm2gjmi8l3fdRgqR2SiNbNEh1lX5CEtXwXTSAfc7tjZSg6rG5+/Fn0fpKenIy0tDWmZhohK4mgK42EEoNSjdz6AVwB8DmAOpfQlSmk1pdTle9RQSv8LYK5vmdcAjKOUfkIpvRDAWwBUAG5O7s8YRrJgc3nh9AgWBypCkK6PfgOTCkgC2ZweMRQuEjxeHnbGfzeNUcURQkJUvf0JP7H814f+iC8+3wyO4/C///0PTz/9NCZOnCgul5+fj1tuuQVbt25FXl4e6urqcP2PfxTiUcwRggxD9H3CegG7PHxMn+O7774bALB8+XI8+uijMJuFm7DJkyfj3XffFdW9zzzzjPwfDuDdd9/Fjh3Cjc4LL7yACy+8EBwntG3OnDlYs2YNNBoNDh48iOeee07RZ0eDlOiNbN1QkmkQb747rK6EAs/qw/jrJQoVR3DmmEBww6bKoWXfsKfeIirSC9J1GF8Q3819qnHuxHzxnGqw2PHViYGbPQ4exDdY7HGTsqwNxajcNIn/4FCzbzja0gePj4BnbSjWHWhGr8LQzpMJySR689KUefRuCkP0HmzqSWkQWm2nTbTIKUzXw8zcnxBCcDnrub2jf+0bjrdZ4f/pI7KNIWriCYVmsVr5eFsfHAMQDjuMwQvJPQRD9KbrNVgyOVDqPBi85IcqPtjXLPp3a1QEv75wgvhedbv8kFJKKToVKHoJIUE+vUPTvoFSKj6UgmOIXsVBbH5MnSL83bsv7uuM1Kc3eYFserMKc67KR0555GPB6VImnHK//iG8Lg5eJweNuwPE6wSZMAFk8QUgKVDz+kEIQWaxHkajEa/9fmdUH9VweOcvu/HGvTvh7AnsIw1j3eBOknUDfdFXHXv++eDWrgHmzxfaf801ISS4NJAtuUF8wahYYEROhRpaU3yqfXufC6/d+zU+fvIEtJoYxwyl0LBhbKw9iMUSfp1Ir/vAa9Ngzw1U8Bqbv466fEaRMNHBc24cOXIELpcL3iiT/pRSHNoqP/w6XHjg+beWRFTYD0MKpXT4XRDsHn5OKY04+qSUegH8AoKC927mrd/5/p6t8HuH0Q/osrlwoj1ADui1KnBc/5YXlZeXQ69RY/fXX6CpoQ6/u/0mlI0og16vx6hRo3D77beHzDBanR7cc+sNmDYiC//+y0Pwety47777MHXqVJjNZlTkpaHHt47N5QXP83jppZdwwQUXIC8vD1qtFsXFxbjqqqvw1VdfRW3fV199hUsvvRTZ2dlIS0vD9OnT8Ze//AU8H9qpUUrh8vBobW7Cy//5JwDgZz/7Ga666qqInz9p0iQ8/fTTAIDNmzdhy8aPJO8bNCpRoRwJKo5A4yN7KWhUFfOBAwewZ88eAMAdd9wR8n5paSm++93vAgBefvnlqN8bjA8//BAAMHHiRCxevDjk/dGjR2PpUmGG+8UXXxRf77K5cLipB3vrLTjc1CMpkZMD1rqhwBxZ0ctxBBW5jKo3AZ/eVCh6AcG+wY/NR4cW0csq/s4amzdoSxV1ahWWTguUkg3UQLq11xE2bOd4W3y+wazycWSOUXJcNgwx+wbW03ThuFxM8AVbOdw8PtzXHGm1kx7hgsniRZZRK15behyeqESkw+3FtuMd4nN/FUmvw5PSSQSJP2++KeR9Vp2/6UgbWhUEH63Z1YAzH9yIUXe+jzMf3Ig1u5QFtrB+yWPC+CUbtWqMyhHazFOgsllZhUai7RvG4AZ73gTfQ1wxK3Bcr93dIMl+6G8M1ePQ6fHiwXWHxOcr55XjrLGBifTaTvlEr93tFasXtGpOogyOBPZeVEm/NFRBe3rA/+OfoF9+CQBBit44r1VlZSDXXgPym7tjLxsBiXq1mqvXoWLtUox75XRUrF0Kc/U68T21lsP0y3KjrC0f9NAhYOOnAEdROKsbhABqa//e62g0Grjt4Qn1SIrUzkYrOhr64LB6kMlU3CTbuoEeOABs2wbodCDfuxoAQM4UiF76xRchy7vMI8FDOE81thZUrPmWZN8pRTSVacWcLMy4rAALfxr9d1ot4Sd8GiotAABDJge1JrqiV2VvB+cVPserTQcf7yRKcNsKzxD/NzV9GXN5QghMJhMcDgeevW0L/vHzz0InB+74HE6nEy3tjSibr0xEGO28G0Z0KCV6TwdgoZTGrJeklNZCsHiYz7x2EIANQD87cQ8jFrpsLjR02SXqWZvLq5hkSxZa6mvw3UvOxduvvgRLtwWEEFRXV+PPf/4zZs+ejaamwGwQa9tAPW4sXLgQ99xzDw4fPgyVSnoD1trRhSVLluCHP/whNmzYgI6ODhgMBjQ1NeH111/H/Pnz8dRTT4Vt06uvvoozzzwT7733Hrq6uqDRaHDgwAHccsstuPLKK0OW9/IUPKVY+/rL8LjdUKlUuPPOO2P+9m9/+9sYN06YdX7tRamdtc0tb58Eq3oj4dNPPwUAZGRk4PTTTw+7zJIlSwAIIXJ9ffLJ0JqaGgDA+PGRAy4mTBAUFVu3boXNZhOPQz857fLyaOiyyz4OrU6P6NesVXExS+pGs4FsCdg3SMsuk+PRC0h9bb850QWba+iU/LGKP5awHoxgB9If7msakO0cbNvgR1WbcssOL09R1xkgDkbmGCVKc/Z4HQpgS90nFWVICL03T1GFW0efU7RZMmhUKErQr5jjCHLTAuqRjigVDturu+DwJYyPyjVhZlmm+F4qS8tjkakjso04fZSQrs1TYM1ueSTUml0NuOutvWiw2EEhkG53vbVPEYkV6pccionF8QWyCe3bl1D7hjF44XB7RRW9iiMoDDqXF4zJFauT2vtcAxbOOpSPwxe31ojXxEyjBjedOxalWUb4dRON3XbZKnvW3i7LqJE1iZ3PVJe1yPBAH/I4eBD48EPQ994HkBxFLyEEZOlSkDFj4hYOOJkSfl33cYCXf69nrl6Hwq/vh8bWDAIKja0ZhV/fLyGdSBLEUdTrBf37PwAAGbPToDULx6VfFUvb28E/8y/wvmUGA/7zqy14+vqNeOWPgljK66LY9LcWbP5nE0B5CUmdDEUvfeNNAAC5fDlItnDNx+zZgFYLVFaCtkn7SHPtBhAExsIae2vIvlMCVmU6Zrk7LpXpf3/3Jb55/wTcQZXGDZWCJ3t6cewJJC3jz5twEBsDaSDbV4DMUDQ1DBFPKXuvG/v27UNnZyfKp2XLtmSQc94NIzKUEr1pANIIIZHroX0ghOh9ywfX63oAnLq1limGv7NVUmYBAC3djhCLBEopWroH5obkvt/dDbM5Hc+t/gA7qxphtVqxZs0a5ObmoqqqCitXrhTbyAaxPf/vf+LIkSN49dVX0dfXB4vFgmPHj8NgFMi322/8KTZs2ICZM2di/fr1sNls6O7uRmdnJ+69916oVCrcfPPN+CJoRvDYsWP40Y9+BK/Xi8WLF+PYsWPo6upCd3c3/vznP2PNmjVYs2aNZB0/Wbl9m/BZs2bNQmmpvI74sssuAwDs+mYbvN7ARUDuPpHr03vwoOBXNnHiRNFWIRiTJk0Sv9sfqiYH/hsxtv3B8Hvz8jyPQ4cOhT0OeQXHIZtonGfWxbwZHJOkQLaGCGWXiaIwQy9aHri8vERFN5jRbXNjT50FgBCuvGBMclQOqcK00gxREWl1ebFuf/+rRCMRZPEcl809DrH/yTFpYdZrJBMQQy2Qjd02E4vMuGxGsag+/fpEJ+oUqLFOFgSrW5NRfZMr075h05FW8f+zx+VJgsYiTVgkA3KsKthJm9U7GmSV+D687jDsbul10u724pH1lfLbFoOEBoBJRfH59D6yvhL2IBJKafuGMXjBqnkL0/VQq6T3YiqOSLzaB6rqZKgeh11WF/66MVCu/YtzxyLDqIFWzYmWRpTKnwBlbb5i2Tb4cTJYNygB9Y0t4Bs/qFyB/i5ej95kwKvLhNuQDwDgvE5oe2tlr5u352/gvNKxCOd1IG/P35LaRrz3PlBTAxQUwLhwjPiyaH/AccD77wMbN4I6Bm7S4NP/BhTykRS+LhsPlaMTHC/QPl5tOqgmtBpHKcjtvwSuugpYtizwml4vkL0AsFWqQs3b8zeQoPjYlOw7BfC4eHz97gm8/H/b8O/bNot8zf7NwsRZ/Q6XQJRHgaYvMMnmNieP6HVmT4BHlwkAUDs7oeuSZ3ehT4tOTptMJphMJhBCZFsy9Nt5d5JCKdF7FIJ1w09kLPtj37Li0UEISQeQDqA10krDSAyROttYxt+Ryvv7O7zMD6fTib+99CZmzp0Hh9sLLxXIz9dffx0A8PHHH2PLli1wenhJGVtfXx9ee+01XHXVVdBqhRuwilGjYDbqse3zz7Bx/fsYO248Nm7ciMWLF0OvF26+srKy8Jvf/AZ//OMfwfM8HnjgAUl77r//fjgcDowfPx5r165FRUUFAMBoNOK2227D73//+xBLCbePYD12RLgJnjZtmuzfP3WqEDrQ19uLpgbpTf15c08TZrajPMpyTJg2IgvTRmQh16wXX6+urpZ8ll8ZXVwcucSEfY9VUsfCyJEjAQjpmZHgJ5r9n53ocSjXn9cPliyoitO6gecp6i2pIXoBaYjZ5iPtUZYcPNhS1Q5/ptnU0kxkDUCooxIQQqShbAMwkGYVfrNHZon/H2tVbt1Q0y61bQCk5cD1Q8ijl1Iq2TaTitORb9ZjIVN2eyr6VsohFpUizyyP6GX7oYXjcoMITOXhLXJxjLExiaSavXhKkejjXNnSiwMxFMadVhcaI0wkNio4T+QoeicVxafojdQOJe0bxuBFgwzrpxXM9WnDwVZYBqDabqgeh09uPIoeX+VfeY4R3z9jpPheeU6AdGIDTKNBSRCbH+z9aMsQtW7YsWOH+IiJA8K9PZksEL0SRa8m/vJy6naDvvoq+HvvBQ1jmScHUvsG+X6talv4gM9Ir8cD2tEB+r//AQDIT38CT2ZggsdP9JLsbGDsWMDlAnzWewOBPncXKisrY44Lk23bAAAkLQ3c1d8VyF329Qj2Df2x78Ihmmp1xhU5MGZzsPU44bSFl8G6bNGPcW0vq+gdIf5PZYSiRQXhYCucKz6VY98gB5EEZRHBe6G2hRfepHrfnSxQFjMKPAfgMQCPEUJMAP5KKZVcGQkhRgA3ArgXAPWt44dfC74vvuaeXHj6+o0R31v0vfGYfJbQwR/4vAGfvRx5xvzGf5wr6/s+/e9hnPN9oVS+taYHbzywPeKy06+dAHOREVoVh0//exgHtzSGLCP3e+PBlVdeiYnjx4rptL0OD7JNWpxzzjmYP38+tm7dijfffBPjp82RrDd16tSwfrBGrQrvvPkKAOB7P1yFjIyMsN/7ve99D3fddRc+/fRTeL1eqFQqUErx1ltvAQBuvfVWkRxmccstt+CBBx6AzRY4HVy+0Jgei1CGkZOTI/v35+YGSIzurk6UlgVuTLNzcuF1R7/JpxTw+pRMBBDVb8FWFlarMHA2GCKTk0ZjQAmoxLph8eLF+Mc//oGqqiq8/fbbWL58ueT9/fv344MPPhCf9/b2QsURePlQBZZWJe/iICV6Y5cys0RvvB697VanqJrOMGiSHmC4cGwentl8HED4pPvBiGDF31DA8hkleGT9YfAU2HqsAw0We9KC9eSAVfgtnV6M7TVCvxHPBEQNo3Ad6RvISq0bBvfAnEWDxS4O0tP1avF3XDGrFJ/6AgpX76zHL84d2++e8gOJZAax+SEnkK2p247KFmHQrlVxOKMiR+IjnSpFL6VUQqZGIrfTdGpceFoh3vaVk7+5ox6nlYS/3td12rDyuchBI8Uyz38vT3GcmVyJtD+Clc88T2Uds8WZejRYQsmhoszE7DqGMTgg9fgPb/00tsCMqaUZ2FvfDZeXx7t7m/ADhrDsDxRm6NEUZlJE7nkyEDjRbsVLX9aIz++8aIKk4m1kjhFbqoT/q2USvV0Kgtj8YO9HW4eoone2Xy0JRK2UoHY7cPy4oDz1Wbep3Kx1QwKKXrUa9KOPgY4OoLYWKC9X/BHOzLFIaxSIQJ3lCHqxRNZ6Xn0W1I7QsF7KaUHcNlCNcO5qjVxYgi4S6SeBTgecfTbQ0wMyezbcxwMkFxtoRk6fC3r0KOhXX4NEsN1LNUbNzoTT6URDQ3TrFk0fG8SWWIAWrawERo0C0UY472bPBi66EGT+fMnLHmMBNGEIQ4+xIKH2xEIsK4d5PyiEpdmJHa/FV63JBrG50wKTAlCpAKMRsIXp02QG+VmL5iG9RsgJMjVvQ+fkVXG1MV4QjwNFX/4Wke6QUr3vThYoVfQ+CWAdBIL4fgBthJAvCCFv+h5fAGgD8CAADYCPfOv48WPf3/WJNXsY/QGOEBRkDMxAYtGiRUjTB+Yh+phk9bPPFrL8du7cGZK4Pm/ePISDUavGnu3CgO6xRx5CYWFh2MecOQJxbLPZ0NEhdLzHjx+HxZdS6f/uYKSlpWHWrFmS15IVmOFmSF2OEGzeug3Nzc1RHyfq6rFxZyU27qzEF/uqxNdHjBgR5ZuSi6VLl4oq5muuuQYvvPACLBYL7HY73n//fVx66aWS2T2O48CFsVpQchxKgthkEL3luQGPtvou+R5tLFIVxObH7PIsUaF2vN066MvUKaUSxd/Z4wa3bYMfhRl6nOmzmKAUeLsfVaIOtxfHfYQuIcBFpwVuDqvbrYr7kuAgNgAozQ4QCA1DyKOXJQ4nFqWLdiznTyxAuu8aUddpxzfVoQOwkxkSdWsKFL3hggEB4HPm3J4zKgtGrRpjC9Kg9nWktZ029DiS787V0uMUJ37NerWkrcFg1fnv7GkMa190oLEbl/99a8SwQ52awx1LIvvLs6jvsonfkWfWIcMQfrKvIF2HbF91Q5/TgzqZ5+FVc8Jft88a5JY4w5AHqcd/5HsIiTf5jv6vYvjW1PCkxfWLKvq5JfLx0IeH4fGJB+aWZ2PJZKk/qP/6CAA1HfKqZ1g1daZMojffzFo3DE1Fr2xUVgI8D4weDeITkXCSMLb4iV5CCDBlivBkX3yaMQfj06tXEMjmSgs/scLxTozYeANUDmFy3l+S/r0zX8CNhctxY+FyrLh4iyz/VpKWBu6Gn4HccTsAqZ8tS/Rirk9tuX07aBR7vEQRTZGq0aqg0+lgNkffnyzBmgjRS7u7Qf/v96A33AjaE74ihuj14K6/HsRXFetH27QbwKukY0IKoHP8d+JuTzJAOIKs4vh5Fi1L9JoD9wmE48C98j+QNW+DW7tG+njheVmfbS0MTCAY2vaAuOMLho4HnLMbpZ/eBHP9prDv85wWbdNu6Lf2DGUoUvRSSnlCyFIAvwVwGwATAipdFlYAjwP4E6USB+erABBKaep6pSEEuYrYyWeViOreROBX8wJA/sj0kO/vsrnQ0i14O2pVHAoy9MgyanHO9ydI1u0PlJSUwKzToBnCDVGv0wNKKQghKCkRtkVbWxusQSbmeXnh1YNGrQrtrYLMv6fbgh4Z1aV+dW4bY+oezeLA3y4//AO/9MwstLU0icSxHLS3BwbT2VlCGTe7T2IhOIzNv+2CYTIJaj+7PbLCj1Upp6XJJxRUKhXeeust0dN41apVkveNRiMefvhh3HrrrQAAg8kcQmgREJRkGWSrJlqZkIt8GdYNOrUKZdlGVHfYQKmg6p1cHF79FQks0ZsKBaheo8IZFdmienHTkTZJ6eFgw9HWPjT7BjJmvRrTSjMHtkEKsGJWKT4/Kpx7q3c24MZz4g/9UILK5l7R6mJUrgl5Zh2KfOopD09R02FTpNqsaQ+cs/7S1AKzDmqOwMNTtPe5YHd5YZCRFj7QYP15JzFhVnqNCpdOK8bLXwkee6t31uP0CvlVE0Mdx1Kh6JVh3bDpaOB66A+L1KlVGJOfhsPNwmD+cFMv5vpC0ZKFYAVztPNy3ugc8fzptLrwWWUrFjMEz9aqdvz0pR0icaxVcbj69BF45es6OH3X7W9NLZL4ospt2+i8yP6DhBBMLDLjiyrhXuBQU4+ouI+G9r7wFTwbK9tgdXpg0iktzhvGYEK9TI//pdOKce/7B+H2Uuyps6CqtS9p574cRMp7qGxOnS93Ivj6RCfWHQiQTL+5ZGJIvzEyDuuG4DA2OSg4hcLY6IEDwj8+2wZA6tGbkKIXAJk6BfSzz0D37gO59FLF6zszGesGizzrBuKxQ28JVNZSALzGBJWP/DJ0HkTZxz9G/TlPispKidoyhn+qv9SeaITjifiqLz0MMcoGmqGsDCgsAJpbgCNHgIkTZf0OpVASLhYJUuuGBIjeV14F7HZg0iSQdGX2H73lFwIQ/F7VtmYQCNWuho79sMTdogEGpdD0Bo4xfxgbtVhAfKrdcPdJtKEBOHwY5Lzzon6815ALR+ZY6C1HQagXppbt6CsNL3ZjkZCiHcJxXvrZzdD1nBBf6ys6E8bWHaJXb2/pOeI+HUZ0KFX0glLqoZT+H4AiACsA3Afgn77Hfb7Xiiilv6OUuoPW5YdJ3sGLLKMWE4rSMbU0ExOK0mWTa6mCXsOJoRRensIeROrylIrlQ1wEawI/dGoOvG/O4fF//RcOl0AcR3uUx1ESxMLvK1sxVpg93qPAS2nv3r0AhN9z/ulTFe8TtYoTFVY8pXB7w5dZ+YnrxsZQaw4/2PeKipRdpCsqKrB79248/PDDWLhwIUaOHImJEyfi2muvxY4dOzB9+nRx2bzS8pD1Kaio2pMDNuSiwCxvllTi0xtH8FWDjLLLRLGQsT8Y7PYNmyoD7TtrbG5IsMxgxuJJhUjzkSYn2q3YWWvpl+9l/Tr95d2J2Iqw1g1lPsWSWsVJSr0bBrmvoh/hto0fbPDWB/uaQ64RJyusTo+4/1QckUUWykGsMDYvT7HlKOvPG+iX4vWflYuq1gCZFMuTWMURLI8QXvXOnkasfO5riTr4hWvm4vdLT8PdFwcGy912+apkJTYaEj/jGP7BAOD0ePHOnsA1+D+rZoukUVuvE//02foMY+iC7YujKXqzTFqcOyFffN7f3uSbmXP/2gWjxP9f+bpOcn4OBvA8xX3vBzIgLptejGkjMkOWk3r0ylOsxWPdkB8UxiYnJHKogmTnAGPHgpx2mviaSqLojd+jFwDo8y8I/3z9NfjLlgUeK1fJWt+dVgpeLZxnakcnVPbY2Rfmuk/BeYT7Kmd6OY585ytUrfgULbN/BeorLtf21aHs42uh6xRCq7VhSDgW/MpVYtvpim+Drvh2yO9wGwtAiXAPrba3gXiFY48QAswRVL30q69k/e5UIqryNwnWDbSuDli/HuA4kFUrYy+/ZYvg48wItXrLL8Txy95B7QX/Fl9Lr90AffveuNo00FC5uqFyC/cevNoArz4bdMcO0J/8FPTtNWHXoRYL6G2/BH3qadCjsSc5rEUBLaexaZusdskNWQsHreUYyj7+sYTkbZ1xCxoWPY7WmbeKr3F8/3vUD1UoGoETQpb6HrmU0j5K6VuU0t9SSn/me/zW91r88fXDSAiG9PA3HZFeH6xobGwEIQRmRqnS6xuY+YnHrOxA2aImBplECEFunnCD3NRYD5sCQoBVCcslRCmlYhjbnHkLAAhBBvX18m7M165dCwCYO3duiCfwnDlzIlpPsI+zp4/DuTPH49yZ4zGitBiFhYWoq6uTfNYkXyLuoUOHwEcINvAHphFCMDGOWeO0tDTccccd2LRpE6qrq3Hw4EH8+9//xoQJE7Bz504AQH5+PjLyAzdC7Cykwy2/bF2pRy8gDc45FqGMNxrkll0mAtbnduuxjqTZgqQCm8Mo/oYKDFoVLpkSuBnpr4E068/rJ4LYcnwlExCUUsmAlR3ISn16h4Z9Q7ht48eMEZmoyBV+X5/Tg/WMeutkBms3MDLHKPGcTAQSRW8Y64Y99RaRAM036zChMKDMYtXWcghMpWD7ZjkqRnYSYOPhVnRaXXh2ywn84pVd4sRnQboOb1w/D/NGC0rwhUH9bCQFYzCqZHgH+yHZTjL8jD893CqGP5VkGrBoXD5uXxywlHhm8zE0RwiTG8bQANsXj4gxWbxiVqA89+2dDWEzDVKB2g4bTvh8qPUawdbkzDHCeePlKe7/4HC/tEMu3t3biD31QumeNooNSxljaVTfZYdHxr1VPGFsaTq1OIns8vCKJpKGGshFF4J79BGQOYEMFS5ZHr0AEKFsHz6LvZjgVHBmjBafylH1pp94P/D1oy4RPLYAWMauQOOCB8Fzwhhb7ehE2SfXw9TwuRgWRQknUebGbC/7OqeGxyCMXQmoJICKnHUWsHRpiB/tQCAauadmLCfCbgcZoC+8KNiBXHA+SFlZ7OW/2Ap8sx3YGhoi5sidip6y88Xn+bv+Ivi1DSCiEeWREKzmpW436DP/EkL6IhQ8kcxMYPFigOdBH3sc1BndL9xadIb4v6npy5RuJ0PrTpRt+Ak0diHjhXJqNM6/F10TrgYA2HOnBJZt3zvg+2yoQGm91xoAHgDJrckbRtJwzcMLBroJScGmTZuwatUqmPVqcfa81+FBQbrwHgCMnxzw4NGoYpdXz5l7OtbW1+GLTz+G7aabkGWSR35XVFQgMzMTFosFmzdvxoQJoTYWVqsV27cHwu28PBXD0JZd+T3884mH4Xa78eCDD+Kpp56K+n1vvPEGjhwRfKO+973vhbzf1taGlpb40ia9QV5O55xzDgCgu7sb33zzDU4PY+r/0UeCGfvpp58uWj0kC6+++ioAYMWV34HHRzRrVBxMOrXog2Z3e2WXprYyKrQCGdYNgHRgfiwORW+qPXoBoZw/y6hBl82NPqcH8x74BPdcMkl2aXEkrNnVgEfWV6LRYkdxpgF3LBmf0Ge+/k2daH0ACPtuqGHF7FK8tl2YEPnfV7X47HArfnXhhIS3dTRI7AnCKXoVHJdtfU5xIsusV0tKSwXFueBlG28gW7KPmWjodbhR61MnqzmCsQVSEo0QgitmleKR9UJJ5eqd9SndT4MFrMI7FrGoBLGsG9hqgoXj8iQTcpKgseZUKHpZe4TYv3l0XhpmlGViV60Fbi/FzD99LHl/TH4aXrhmrmTyozzHiLJsI2o7bbC5vNhe04n5o2P74LKBiWPyo5MYExUqn9/cEQi6uXxmCTiO4IqZpXjui2ocbOqBw83j0Y8q8ei3p8X8rGDIPZeTfc73Zx+SSiTjdzg9XrESiSOCV3w0LBqfhxyTFh1WF5p7HBh99wco6YdtyFq2zKvIgV6jwt0XT8S3/roFlAqTKV9UtYs+9wOFNbsa8PC6w2hkJj+uOXNUxGorg1aFgnQdWnqc8PAUjRaHWAUTCfEoegHBTqyvTRCstPY6Zfv7DnWYq9dBbQscP8bmr9AzetnANQiAM2scDB37AQg+vTZGuRgMtbUFxhZhfEdB0BNUMt434hzUn/sUSjb9Eip3LziPDSWbfynh2tLqNsZdau42FYo+txprk+jFSsaPAxk/TrKsuXqdz56gBR5jAdqm3TCwJe6UJuzRS/fuA775BtDrQb77XVnrkAVngm7dCvrFFyCXLQ15v33ajUir3wSOd8PQvg9pdZ+gjyF/+xvxWGRogv1516wBmpuBESOAb30r4nrkB98H3b0bqK0Fff4FkOt+GnFZe+408GoDOI8dWmsjNH11cJtjE+1yEThehWPEf8541SY0nvUQbIVzxWVd6aPgVZug8lihdnRAbW2CJy2yneYwBCiVgXQC6BlW7A4j1Xjttddw/PhxcQYcAOwuDz799DN88YWQlnruxULnzRECNRf7UP7hSqHcY+umjVi3bl3UZbu6usT/CSG44oorAABPPPEEnGFmwJ588kmJly2ruBxRWoqbbroJAPD3v/8dr732WsTvPXToEG688UYAwMiRI3HNNdeELFNdXR3TdoJSiqZuO/bUdWFPXRcaLbawdhSTJk0SA9MeeeSRkO9qbGzEK6+8AiA86ZwInnnmGXzzzTcwGo347jXXia9nGjVi+BgA2QFplFKJojc/DkVvPNYNrBonmr9eIli7uxE9Do/4vL3Phbve2oc1u6Kn3UbDml0NuPOtvWiw2EEhlI8m8plrdjXgnjX7Ja89vK4yoTYOBOo7bZIb9MZuR8LbOhp4norepkBA8SexFFFg3VDL+AyOzDFKyDh2IiIe64Y1uxpw11v7knbMxAK7Xcbkp0GnDrXmWT6jxC+uwZaqdjR1Dw1LikQgIT2T6NEZK4xtUxDRy4IlMA8398pSximBlEyV95sjEcLlOUa8ef28EE91QggWMuGRbKhkJFBKJRMxo/OjT4aOzksTPfQbLHZJsFMwOvqc+KyyVXx+uS+Mi+MI7rkkUF2zemc9DjTKCB5gEK7/v+PNPfj16j147Zta8fHr1Xtwx5t7knqduCuJ152BQrL6wiZL4J6lMF0fszpNo+IwuVha2dAf2zB4kgcAJhdnSALi7nv/UL8pjMPBv08agxTuI3Oi35ex1jfVMuwbJB69JnmKXkBqJ3ayBrLR48dB6+pEawpz9ToUfn0fCALHRcGOx2Cujj4GSzUcrE9vV3RFb3r1B2L7bYVz4TEWhCxjz5uO2guegdvoV98GQCiPwq/vj/s3s+SoJJAtCMK2vh8aWzMIBII1ke9NBlSOTnBe4V7CqzGD18q7dktsLX77W+FFhwP0llujr+jHrFmAVgtUVkrsG/xwp5XAMu5K8Xne7qdEW4yhAm1voELX7s4GfeNNAAC57qcg6sjiKKLVgtx6C6BWAx98AOqrrA0LlQa2gtniU5NM+wY5kB6vUpK37vx/SkheAACngiNnsvjU0B5fGOOpBqVE7wEAGYSQxAx2hjGMGNBqtbjooovw9VfbYNSqwPM8Pv34Q1x5pdAxLzr3PMyYI5QUGLUqyMlLuuxbF+O8iy4FpRQ3/uh7eOjhhyVBa52dnVizZg2WLl2K2267TbLuXXfdBb1ej0OHDmHZsmU4cULwj7Hb7XjiiSfw29/+FhkZgRAvF+OJq1FzeOCBB7BgwQLwPI+rr74aP//5z3H4cKDUra2tDX/5y18wf/58tLW1QafT4aWXXoLBED9xqAsKZIuE+++/HwCwevVq/OpXv0Jvr0CuHDx4EJdeeil6e3tRUVGBn/zkJyHrPv/88yCEgBCC6urqkPefeeYZvPTSSxIFcm1tLX7961/jZz/7GQDgoYcfRkZ+QImSZdTCoAm0Xa4qtM/pEZWMeg0n29uXJQ1OtFsVERSU0iB/vdR49D6yvjJkAGV3e0UlY7yfGWyLkchnPrK+UvSlTlYbBwKPfnQEwUPVVP6Oui6b6BeaY9Ii30e2jQ5Smsv19KuWEL1S0ok9PuNR9D6yvjLkfEzltgmndA5GcaYB832l95QCb+0cWoRRPFBiFaAEZp0aOp8NhM3lhdUZmFyy2FzYU2cBIFStnhWk3Ms2aVHkUyO6PLxY5p0MdNvdosJYq+YwIlteP/tFVXii1uXhI6rpWLuZTTL80Nv6nOIkXJpOjcIYE4waFSdRph+KYt+wdncjPL5+f9bILIzKDZzP88fkin6tlAokmxLfz/s/OBTS/7u9FK99U49fr94nPl77pj7E4z/R64Q9idedgUKy+sL6ODz+D4UJP0vlNnR5eHx5LBAmzFpJ3b54PPS++7WDTT14q599g1mE2ycA8NTGY1HXK2cUvHJ8etnJGSWqXEkgW0/oRNrJAPrf/4L+/CZgiyDIydvzN5Ho84PzOpC3528D0TwRzqyAEjaqdQOlyGBsG7pHXRJxUVfGaNRe8CwoCR17JPKb3aaAalEdRPRSux30w3Xgn3vet62lEwgDva1ZYlqRmleOrUUUEL0emO0jKMPYNwBAx+Qfwevzi9ZaG5F55A357RsEYBW9PR/XCZYNC88CmTIlyloCSEUFyNWCJQJ98q+gkexQAFgLg+wbkoRwxysA8Bqj5PxkIbFv6JASvezkgOn7P0DNzFk4NGEijiw4K2ltHopQSvQ+A0AF4KYUtGUYwxDx6KOPoqurC2eeeSamjy7GvPGluPmaq9He3oYxY8bg4Sf/KS5r1subUVdxHB596hmcs+QSOJ0O3PnrX6OgoABZWVlIT09HTk4Oli9fjnfffTdk3dGjR+O5556DSqXCunXrUFFRIa536623YtmyZbjsssvE5VliVasi0Gq1+Oijj3D11VeD53k8/fTTmDhxouBNm5GB/Px83HLLLbBYLMjOzsY777yDs85KrHNifRujEb0XX3wx/vSnPwEQVL1ZWVnIyMjA5MmTsXPnTuTm5mLt2rXQ6eRZIbDYunUrfvjDH6KwsBBGoxHp6ekYOXIkHn74YahUKjz22GP4zsofiwNUo1YFvUZ4+OF087IGsJIgtnR91FR2Ful6jUiuubw86hQQYB1WlzhYNuvVyDDIV3coQWME9WWk1wfiM1PRxoFAf/+O4LAx/3Gbm6YVjyery4tmmQogqT+vlDhI1KN3oLdNJKxg/FhX76w/qYNugPjUrXJACIkYyLalqh3+uaappZlhrY/YfXQwiYFsrFVFRa4JKk5e3x7Ju7Ypiqft/DG5YpDpoaYetPZGP++klhImWdedSTK3E+sRzion/bj74gnitth6rAOfMurfaPj6RKfE5igeDF8nkvM74vH4b4+w71K1DXfWdomTkaVZBsmEQ2GGHj89q0J8/uhHlQMWihnvPpEqemNfF7us8Vo3nNyKXur1Aod8ApaJgsUd6ynLItLriYL/3ytCO2LAmTkmEKLWWwPiCb8/9B37oe2tBSAoDftKF0X9XI+xAIiQOR/vb/aYCsX/QxS9FKD//jewdi3QGb7/T9W2lgONjSF60+Lz540XZMGZAADqqwIOBq9NR/tpPxaf5xz4DzinpT+alhRofURvb6MO7gN1grXFqh/J/4BllwGTJgJ9fYDPLjIcJIFsLTuSo3zmPaJdQzDUUcIRHQzRqw9W9EaYBPC2x67MOpmhiOillL4M4K8A/kAI+RMhZNirdxgpwZgxY7B9+3Zcc801yMjIgJf3onhEGVZd93Oh3D8roCYyy1RuAkBuVjqe+Pd/8dfnX8Ull16G4uJi2Gw2uN1ujBkzBldeeSWee+45/PWvfw1Z9zvf+Q6++OILXHLJJcjMzITL5cKkSZPwxBNP4PXXX5cM8FjrBo2PcDUYDHj55Zfx5Zdf4rrrrsP48eOh0WjQw8ykzZkzB4cPH8bixYsVba9wCCZ6o5Ef99xzDz7++GNccsklyMrKgtPpREVFBX7xi19g//79OI1Jz1WClStXYuXKlZgwYQLUajW8Xi/Gjh2LG264AXv27MGtt94qUUf4b5rVKk4sYeQphVNGKE4rG8Rmlmfb4Ee8fqisGie4DDiZKI7w2ZFel4OsCCEi8X5mUWb4bZ5IGwcCkdpLCLCrtivse4lAolplSnIJIVL7BpnHZQ2r6M0OVvSyRK9yUiAVx2E0SILYiiMTvUsmF8KkFSaHjrdZsdunPD0Z4fbyqGbUssm0bgAiB7KxpdtnB9k2+CGXwFQKpf68fsRzvKbp1Jg1Mkt8/nkM+4ZjcdhoyPHpPdTUgwO+vkGn5nDJ1NBB8ph8M747NxDOdf8Hh2NWpKzb34TvPxs5pd2oVeHK2aXiw6gNtUsB4j/nI3nQDrXrBHuesFD6OyT3EDKJ3v7uh6N5cwPAdWePFrdHS48T//r8eEraEQvxbpeREkVvdKLX4+VFBT8hUDS5n88cM60nIdGLmhrAZgPy80FyhTFaOJuDaK/LQmZm5Pdeew30d78D7eiIvAwAqjYEvG4pD113+GOWVfP2lp0Hqo49tpD9m5kqUAmCfl806wZiNABTpgCUwtoYvk9KaFsnCE0fQ/Qa+5fojWXfAACWMVfAlSYcByp3L3L2/6c/W5gQ/GFs2jQvyOTxIFd/FyRHPi1HVCqQW24B9HrQP90rqmHFx8pVAAC3uRSuNJ9tlNcBQ9uehNpNPHaUbL49Ul5c1OPVnhvgIvRdRyJO0AwjAEVhbISQjb5/bQDuBvBrQkgVgDYAkabQKKX0vPibOIxTFWVlZXj22WdBKcXBph6xdN2rMcDLCzfHGhUHnZrD888/j+effz7mZxq1anRaXVh43hJ865JvoTw3up9eME4//XS89957Yd9j28AOxLVBnmtnnHEGzjhDKIXo7e2F2WzG448/jttuuw07duzApk2bsGLFCkXtCgc1R6AiBF4qBMN5eQp1lNC6888/H+efr8yMftWqVVi1alXE98855xwx8C0cHG6vaLdACJHcNBs0KpEwd7i9EpVvOLQwyqt8mUFsfozOS8NWX2liVVsfzoe8GyOpGic1tg0AcMeS8bjrrX2SskQVIRGTpOVgXIEZ2050Sl4zaFRxf+aP5o/CfR8cStrnDRTCbWsA4Clw9b++wtPfm4FzJyTvxvmgRLUqDXIak5eGHTUCuVzV2oezxoYn2Fiwit6RQYreogw9VByBl6do63XKOq9Y3L54HG59XXqT509gTzY8Xh6VTIlyNEWvUavGxVOK8MYO4cZ39c56zCjLirj8UEZtp00s5y/K0Et87JOBcIFslFKJX+3Z43JD1gOCFL2NSVT0xulJHO5cltMnLRyXh698feOmI224YlaomlZsW1vgfJOrrmYnLSJtp9U7AmrexZMLIxJKt5w/Dmt2NaLP6UFVax9e+aYOPzhjZNhlX9pWg9+t3R8xrNqgUeH+5VMkoV7zR+fijjf3SOwbEunXl88swd8+lZbSa1WJXcsGAlkmbYgqWqtS3hdKrZ/kEbV3LBmPO1fvhYOZANepU9MPA1ILk3CTPCadGr+8YBzufEtQWP1j0zF8Z84I2TkJycLti8fhttf3SKyX5Byr5YyiN5Z1Q7c94M+brtfIri4AhEozP4aidUNRUQyi7sBB4e/kgI9m27QbUPTl/0k8enmVHm3Tboi7HdwLz4d9ne7dC/rY48D+A4KX682/AJk9O+yyAODIGieqdXVdR+DImSR5n3idMNcEQjx7otg2sGibdgMKv75fUpYe7jdzL74gqI8bGkDKIgdcsdYNIYpe3oP0gi70AOht0COzQjqBT0ES2taJgrWa8MQRxJYIiF4Punw5SJoJ0Efoi1QatE3/OUq2/BoAkHX0DVjGrUhq4FgqwLn7oHYKYwNNJgf85H6EeM7JACkoAO2NYB/FKGStRWdAe1TwADY1fQlb4RzlXwZA5ehCyaZbYeg8GPb9WH0Dr02HM70cup5qEOqFvvMQ7Pkz4mrLqQKl1g2LfI80CL7JagATAJzFvBfuMYxhxA1CiGQw29IduEEy69WyS/QBSNQpNpcnZSW+rKI3mOgNh1tvvRU33XQTeJ7H97//fXz66acJt4EQIlH1ylHF9jfY9OJ0vRpqZluxBJQcn95g6wYliEc5CQANXcoHafFg2YwSPHD5FAkJY9ByWDotvsRRSilqO6XKFY2K4IHLp8Sd3B2sminJNCT0eQMF/7YuyTSAAMhL08Ho8yC0u734yYs78Pr2uugfogCsR+ekIqnCgw12kntcsqWnwRNZahUn8RBVWuo7P0yi+s8WjU7JPj7RbhX7rMJ0PbLDWAWwYMm4d/c0wekZmPLhVCNedatchAtkO9LSJ1qHmPVqTCvNDLsuS2BGUqrGA4knsQKiN/hcltsnsWTWlqp28FECpuLZHywhXtXaF2Kt5PHyWLO7UXx+xczI7c1N0+Fni0aLz5/4+Ah6HW7JMpRSPLq+Er9dEyB5R+Wa8NtLJsbcNstmlOC2CwJ+eRwB7l9+WtznvEkbOjExvtA8pK4Tm460SSah/DhvYr7i3xHPZPGyGSV48Iqpop82ACwal5eSbdjW6xSV5WqOiH7owfj27BEYXyBMVNpcXjz2ceRS4FRhelmWhOsoztDLOt/LWEVvpy3q+S4JYotQFRUJEqI3hiXMYERjY6P4CAd6UCBvyKQAYWrPnSqSvBSA21iA5rl3o7f8wqS3j0ydCvLE48D06UBPT3iVIqNUdLKBbGF8etMaNkPlFs5zV1oJ7HnTZbWjt/xCNM+9G25jISgI3MbCiL+ZqFRRSV5A2GZ+mwm1vQ3wCscg8ThQvOVO5GuFgCxrsw42YwXchjzxPCCgEf1O+wMSj16Z1g10d2KKURbc1d8FWboUxGyOuExf6SLYfPuWUC/ydj+VtO9PBfiVq+BZ8X0cerUYh14tRuX/ckGXXwF6zbUp+06JfUNzfIFsmr4GlH38YwnJ21NytqzzhIUjh/HpHQ5kiwmlUhAF5h/DGEbykKZXizPpHj4wKDIrVDPp1JyoaPPwFC4PD50CRZtcuMJYN8TCE088gZqaGrzzzjtYtmwZPvvsM8yYkdhMlVbNiSSpy8PDpNxmN2WglMIiuWmWEjl6NpBNhucb63lWoFDRGy/RW99PRC8gDO6WTivGnPs2oMPqQp/Ti4NNPTitJEL5VxRUtfaFJFNrVPETxwBwsCmQ+n7d2RW466KJUZYe3Fg2o0QyODzW1oeV//ka9V12eHmKX725F609Dtx4zhhFE03BsNhcoqJLq+ZQkSclZpUelxabS+wn9RpOUirqR0mWQfzO+i47KhSQheHK8fMV2qTE813RbBv8mFuejdIsA+q77Oi2u/HJoVZcPKWfSwX7AfGSnnIRzqOXLd0+a2yuZEKOxchsI4xaFWwuL9r7XGjtdSTl+GA9epWGzwWfy3IwqSgduWlatPe50Gl1YX9jN6ZGILfj2R8ZBg1KMoXz0OXlcaytT0L+bj7aJpLs+WZdTCX/tQtG4X9f1aLBYkeH1YW/f3YMv7pQ8Mj0eHnc/fY+vL49oBCeVpqB/6yag5w0Ha5l/FUj4bqFo/G3z46h1+EBT4HZ5fG7tu2sCbW/Odzciy6rK6zv82CDl6d4gKlcyTPrJF7WShGv/dOyGSXQqDjc+D8hMf1gcw94noJToDCVgy1VgXN/5sisiJkYKo7g7ksmYuV/vgYAvL69DqvOLMeEwv7L7t7EeFSfP7EA/14ZWc3JIl2vQbZJi06rCy4Pj5ZeB4oywu+LeIPYAOl9aesQVPRGBaXAgQPC/5MDRK+JIYWsRfPQsOgvKW0GycwE/u93wNtrQF98MfxCPqWiJJCtK3RiIv3EB+L/PeUXQ1bqtw+95RdGJaxoTw9ASFQCUoRKA48hDxp7KwjlobG3wqtJQ+nmX8LQvhcwAvosFxxdWtQW3gJy+hko3nInzHUbfb/jfbRPH5hoJQnRK8O6gba0gD76aOQFotl2xAtC0DbjFoz8aBUAwFz/GQytuwavUjTBoLp4YMufBcqpQXgP9JYqqGxt8BpjVxj6oes8jNJNt0DtECqlKAhaZ98By1jl1cv23CnIOCFkKek7honeWFDq0ftCPI9UNX4Ypw7MutCbSwKhZEwJCCEwMooSawpCIzw8L9pMcISIwS6xwHEc1q5dC0opuru7EyZ5gSCf3hjeff2NPqdHVD6rOQ5pQV7LBoaAD04HD4fWJCl6j7X1yVZ6xxOkkgg4juCssQFVpZxU+HAIt57N5UVNp/KALj+kytT+G9z1B0bnpeGtn82X/K5HPzqC3609IJ7r8YDdZuMK0kRfaj/G5AUGAWyJeCQE+/OGI6HZ47RBoaI3XJl5Mkv0JZ8bxdIiHDiO4HImsIotfT+ZEK+NgVyEs27YfJTx6IxCOnIcwYTCwL5KxrHhcHvF6gNCEDIZkgoI/Wzgd26qDN/P9jrcotJZoyIYmS3fvieafcPqHQ3i/8tnlMQsD9cHlac/u+UEGix22Fwe/PSlHRKSd9H4PLzy0zOQkyZ/MpTjCKaPyBSf74zTq5xSil2Mf7a/usDtpXhnT3iV4GDDG9vrcNin5jVqVXj4iqnie0p9qV0eXpygJiSyz30knDcxH+m++6a6Tju+qe6MsYZysMd+JG9u9v2FvmV4KnhG9yc2H2XsZcbLJyEAqc1RdXvk+6BEFL3spFdrryOqcnjIoasLcDgE39nigGDA1BQgem2FZ/RLUwjHgVxxeczlWEWv3nIUoIFxhsreLml7z6iLk9vIDz4AXfUj0HfekbU469NraN2Fsg0/FUheH1TThf6fbt8BAOhmbCbSq9cB/ABUOFGqSNFLnU7Qhx4CenuBWTNB3loNbu0a6SOCbUfUz21sBP/iS6AbI1fKOnImoWfkEvF53q6/SI6HUx1UY4Q9d5r43NQc2ec/GMamr1D2yfUiyctzWjQueDAukhcQiF4/DO37IJYpRZgEUOWGtxo7VaDUumEYwxgQaNVcCAmiVXMRlUXRYAqyb0g23J7AzZtGxSWk+EsUuhRbN3TZXDjc1IO99RYcbuqRWDHEXNcauGHONGrABW0nrZoTX/PwvMQOIxxYRa9SFVm+WQedz7+41+HBvAc2Ys2uhhhrBfvrpc6jl8VCZrC1OU6ilx0QsRxCIsSMJFTsJCN6ASEx+7XrzsCZYwKlqy9tq8Hk/1uHUXe+jzMflHfMsJCoVsNss5Isg3gOt/c50W1zhyzDojqKP68f7HHKTlQoba8fySzRl3yX5HiSp1pnS9w/OdyKM+7/RPE+SQRrdjXgzAc3xn08yEFVAupWOcgLUvTaXV7RrxaQ9j/hILVviOD9pgDVHVb4+ZDSLIMiT+lEwJJaLNHN4jgz+VKeY1J0PxIpkK3b5sbHBwMp6dH8gVksnVaMqaXCeeL08DjzwY2Y9oePsPFwQOW4YlYp/vXD2ZLJbrmYyXheh1PlykF1hw2dVuEeIdOowY3nBCwnVu9M/cSM//xctc4a1/lpdXrwZ8aS4PqzR2Pe6BxxMr+mwxZimxENzd0O8dguMOuhUys7tvUaFS5lqnCSvQ15nuJz5l4h2iSPH7+5eKJ4T7H5SBvKY/SFyeoznR4vvjwWCOA6W0ZbWbCTNNF8ervChAfLhUGrEol5t5cqul8e9MjOBvnfyyAPPRgY8/AeGJu/ERexFvUP0SsXHkMePLpMAADnsUHTF5hsSq9eD0IFctSWNwPutOTZolBKQT/fAng8QKm8/p01Vi/86o/Q9ZwQXgZBy8zbYFt2MzB9GojPH9laNA8enVB5obG3wdjyddLaLxcqp0X0KfZqTOA1kSfsKaWg//gHcOw4UFgActttIKokXetPnABWrwZdty7qYm3TbgDPCee0ofMgxr16BirWLoW5Ovp6pwrY87fwqz9G3Tbm6nWoWLsU416Zi9LPbgLnEcYaXo0Z9ef8FX0jImf3xIIrYxS8GmHCX+3ohMYqnLfcC8+LEwLW/76EkTt3YOLhQxi35fO4v+tkwDDRO4xBherqalBKsWjRIsnrXTYXPF7p7LfLE9+NktSnN/mznBJ/Xpm2DamClrlQBvsAJooumwsNXXZRKezy8mjossvaJ16eR48jujKCECIZ1Dti+PSynmdKrRvW7m6Ei1FXNPc4cNdb+6IOOiil/Wrd4AerNNtR06VoYAkI2/Gr44EBEVveHi9p12l1ico2nZrDKIUhh0MFZr0Gz62aK7G4cLh5UAikf6xjJhgsmRkubEzFEYm1QlVbdOKsllX0RiJ6mfJg9viVg3DHx6GmnpQok1iSUI6iFwB21VokExdyzuNkYc2uBtz11l40WOxxHw+xQCmVKHpTYd0Q7NG77USHeO0Ym58WM8FeEsiWhEkAiTVCCojtSFjAVE7srLVIrld+JOKXPCnCdnp3b6N4TZ1SkoFxBfKOfY4jWDhWqlxhA9R+fs4YPLJiasiEuVzMHMkQvbWWuD6DJYhnjMjEpdOKxQyDvfXdONKS+MRAJAjn5z5xcjae8/Ofm4+LKveCdB1+clYF9BqVZN+H8+6NhGRUBLETAe/vbUqqeOFgUw86fMR8jkmLyTIsdMYXmjE3yNqjwWLHr97cg9+/sx8f7GsSH79/Zz9+9eaepPSZ26u7RJuy8hyjxHdXDkaygWxRKpsSsW4AhnYg27vvvis+woGo1SBMYJuhfR9UHoE0dxsL4Uov749mygchcGYy9g0W3yQOpcg48b74erfMEDbZqKkB6usBsxmYOjXm4ubqdTB0HhCf+29xeHBomn8vLOO/A1JeDu4PfwDxj505NXrKAwrVjOOB39NfkASxGYuiW190dQE7dwFaLchdd4GkJfFaP2sWoNUClZWgbZHFMR5TEayFc8XnBIDG1ozCr+8/ucneSHYYGUECC0bhLG6br/6EvO2PIq32E/GRt/1RFH71J2hszSAIHK8ejRm1FzyTuCUG4eDIOU18qm/fB9rXJwQbDiMEcbNQhBA9IeQMQsjlhJAfEEJ+GOmRzAYP49RES7cDNChSkoKiJchnVA4MWrXY8Tjd3oRKr8NB4s+rGjg1LxBk3ZBkorel2wE+yOKAp/L2SbfdLa6r16hgiKAwMrA+vVGIXkqp5KZZadrzI+srQ5LI7W4vHllfGXGdLptbnCgwaVURU9GTjTyzThxweXgqUbHIwVcnOkV19+g8Ey6YVCC+Fy8xwxKA4wvNcSnthwq0ag5PXDUdabpQtUGsYyYYh2IoegFhH/kRy6e3WkL0hifbWUJBCdFrc3lwol0YtHEE4vFudXlDgv0SRWuvQ/QoNWpVEX9LMB5ZX4ng7lzpPokXD687DHuQxUyyv7u5xyHaDaXr1chNS76naX6QdQNbuh1LzQtIj+NkqL2PtQbUdakgtiMhN02H00qE3+LlKbZWtYcsI1FXK2xb8Hby2wWxqswVMtW8fry9K7z9QYZBg9uXjE+ouoi1bjjY1BMXochaPswsy0KmUYvzJ+WLr6XSbuWR9ZUh9xBKzs/mbgee2XxMfH774vEw+EQDEhsOBce8xJ83TqJ3xohMVPgmVq0uL9YfaI7rc8JhU5A3t1z/X/Y65IfLS/H81hrc8PJO8fH81hq4ggQc8faZbHVTLIuJcCjPlavojd+6ARjagWxLly4VHyHwhPYHUn/eMxR53PYXnFlMIFvXUd/fI9B1VwEAeJUevWXnJfU76ec+heH8+SDq2NUVeXv+JqqLWfC6TPSOvCDiej0MQZ3WsAmcS37+SDKgxLaBZGeDPPYYyF13gpSXJ7UdRK8H5vj8urdujbqsPoxXM+d1IG/P35LapsEEVglL3loNlAjqdXLVlZLlMqveDl2XdyP76Oso+eIu8ZF99HVwfOjEOFXr4coYHfJ6PAi2b6D/+jfoDTeCHjgQZa1TE4pH44QQEyHkrwDaAHwB4A0AzwN4LspjGMNICJH8ZePxnVVxRAxgowDsSbZvYAnVgVb0alREHNx5eF4SZJcoEtknrG1DtPI3iaLXFflzu+1ucbubtCqkKfRubozgVRrpdSA0Lbs/LTpYwkWpTy87IFo4Li8pxIwcwvJkAscRWJ3hJx6iHTMsXB4eR1sD6q8JEbab1D86uk8vO0Atj0j0Bga0DQqI3srmXnEypCIvDVOYEMBk2zewSufxheaYHqV+xHMeJwNdVldIuGEqvjs4+CsVfY4kjK3PGdJfxML4QrM4nj/e1hezEiMWEiFTE8XZkn42DNGbgLq6NMsghsl22QSv32NtfdjlU8tqVERxOGakY63HrqzqIxwyDBqM9f1GL0+xt747xhqhYJXAfoXwFYyv9tu7GuBJUZZAon3Dox9VilkBk4rSJe1mKw6U9IX1lsQrggghElUv6++cKDYpPPf9YG204kE8fWa8bfWjLDtwvYzm0StR9MYRHpgvCWQbWkRvJND2dmh+dA34Bx6UvG5q+lL8f0BsG6IEd9FduwBAoujV+xS9GSfeE1/rHXEOqCZ5FWqUUuDzLQAActYCWeuobS1hX1c5pRY6lOdBDx4EXf0WACFszuHzIea8TphrN8Tb7LggIXpN4YleVoVJcrJBZs5MSVvImWcK3/dFdKJXbQ8/noq0D/ob2ub9AMKL01T6xBWtRKUC+cEPAAB08+eSvJpEt4HaHnoPFS9YoldTswf4/HOgtRU4xf14w0ERC0UI0QPYCOAGADoAeyGost0QSN8q/6IAugBs9j2GMYyEoI2gEIz0eiywPr3JDmSTWDcMsLKREAKdKvmq3nBlrCyi2Qk4PV5YfeQ6AUFmFFUEG8gWTdHbkkAQG4CI5cjRypQbBsC2wY9g/0i54XGAdEB09rg8jMo1iT6wTd0O0UNRCWJZEJyMiOeYYXGsrU8srS7NMkRUhLMEUixFL1tyGsm6oTBDLxJxLb0OOD3y+r9gP+F4VWxyEG+wX6L7JB7Ud9lwxT8iDx6S+d2JEItyYWAmytxeiuM+FbdOzeH0UdnRVgUAGLVq0bqFp8pK2cMhEXuERMF6km4+EtrPJmKjwXEEExiC8GBjj0TReu6EfGQpJJJSffxLfHoVBrL1OT2obBb6CY4A03wK4YXj8sTJhdZeJ7aEUU4nA5G2gVpFYl7zDjR2S5TW91wyUaJuZT3ElfjcB08Wx4vlM0rEPv2LY+1JmVzqdbglVhtnKfC8jbSt9RoOF51WKD70mvD3x0qP15YehxiQp1ERnFGRE2ONUJQz18vaTlvEeyqpSCFBRe8Qs26IBH7/ARCXC3AHziOVowu6TkGZTYkKtoI5/d4uVqnof+Db3xba9MgjoPX1cEgUvUcArxvmmvXiaz3Jtm2oqgJaWoCsLGDSJFmreIwF8l7nedB77wV98UXQJoFkZdufzthR9AdiEb3U7Qa957fgX3kFNIkipHCg/3xG+KeyEvxlywKPlasky8ne1gMAQ8t25K6+BUQFGHJcmPidRslj1NVJmvg/43SQO24Hue9eiZgg0jbgVTr0jjhXfPCq8NaJydyGrHWDbXsL4PUCZ5wBUjDw+2mwQSkLdQOAOQCOABhLKfUbbXRSShdSSscDGAXgFQCZADZQSuN3XB7CUEK8DCM2CjL0IWFdHCEoyFBO6gGQhJEk26eXJVPj9cNLJpJt39BpdaEmiuIBEBQRkbx62dI3s14ddRvpNKzHsFf0Ag0+vyRBbAr9eQHgjiXjJaSyHz9bVBFxnYHw5/VjZlmWOFlR12kPWyoZDo0Wu0icaNUcTh+VA7WKw/jC+BRJfkhIQBk+ficDIh0zv7xgXJilQyE3vE4u0Wt1ekT/SI2KoChC36hVc2LaPaVAk0WeqkjS3uL0pJfoS74rzuMp3D5RcwR3LBmftLaxONTUg8v/tlUSysVCq+aS+t3H+kndyvr0+nF6RY7sILRI/rNK4eUpjg+gonfmyCyR9G6w2CWKepeHl0ysVOQpV32x22l/Qw/eZrxJWcWoXIQ7/g0aVdKOwZkjM8X/d9ZYFK27p84i2qqMKzCL21Wj4rBsOhsolho/7evODn8td3spVvx9K+oi2M9QSnH/B4fEaobzJuRj/hipaohV9B5u7pWtSpZYNyRAxhdnGnDm6FxfeyE5juLF1mMd8Ph22OTi9LB9QiREOg4fvHwq/v79WeLjwcunhiynIsr7a7bqYE55NkwKK7oAINukFRX2fU6P6E0cjETC2ACggNmOiSqfBwvogf0AADJpsviasfkrEJ/y0J5zGnhtdK/xa3dcixXbVoQ8rt1xbVLbSq7+LnDGGYDVBnrvfXByueA5gbDX2FqQXrMOaqcFAOA25sOWPyup348jRwQLizPPlB021jbtBvAq6f0cr9KjbdoNktfotT8GrEI/Rq//GfjLlqHj16/jyBqB/DK274Gmty4JP0IewhG9/MpVIslKV3wbOHgQePU10FU/Sm1juiNUoFgskqfhtjUlqpBt3d8w13yM0s9uhjm7B2OXNqNwrkXyfrjjIV4QQkAWLAixFYl0HDbP/Q0aFzwoPprn/kbW8ZoIeK0ZzvRR4D0EXVXCtZNcFsZSZhiKid5vQ9CM304prQm3AKW0llL6PQAvA/gjIeSiBNs45KBSqeAdNoVOKrKMWpRkGUSFrFbFoSTLENeNFhAcyOZJKjHvGkRhbMFtSITopZSitceB+i6b6Jes4ohI1GpUnFhiTUFR12lDW69Dsm0ppbBY2Rvl6IoIFUfEJGoKwOFTH/I8D44L/C72hjkeRe+yGSV44PIpKM6UrnukJTKxxqpx4vXXixdaNYd5owODzU2VrVGWDoAdEJ0+KjvgMZgAaef0eCUE5IRCeeFBQx2RjpkcmQNidjtHU0GX55jEgLG6LlvEUvgahuwfkWWM6pPMTkw0yFR/BbdXErqlQMUWz3fJhX+fsP1KeY4Ry2YkLzHbjy+PdeDKf3yJVh+5rlVxWDlvpOTaMnNEZlK/u7/UrXlpocdwcNBXNCTr2Gjosot+4rlp2rjCjxKBRsVh/uiAOpDtP2s6rKK/f0mmQTJ5LBfsJMb/vq5Bk8/+I9ukxaLx+ZFWiwj/8V+SaQDxteuBy6ck7RhkFb27arsU3Tex6lA22A2QBop9dKA5ZsVQPDDrpfuHraA43m7F5X/figONoWTAp5Wt+KJK8MFXcQR3XTwhZJmcNJ0YAOv08KiO4vHKIplVQVfMCuzj1TvrE76nTcTzVu5x6F+O7W9UHLB4sjJVVqK2DYBAbrABbpF8ei2MUCFaNVoknIyKXtEXc3JAoarUtqHbHZ6Ii/R6vCAcB3LrLcCoUcDkyYDBBFdGYBIod+8/xP97yi8GOHlkrOzvv+QSkGf/DbJ8mex1essvRPPcu+E2FoKCwG0sRPPcu9FbfqF0wSDS0g+vI/Ab0k98EEer40NYRW+ENkYkYvsZ/m3t0QeqlyhRo2/EwGkWMytfRfHW34i+t3xmLnrO+mns4yEJoBYL6BbBakTucSj7eE0Q9twpsJwwgHdxUI/IApkQem0eBqD0znQCBL7lo6DXw13t7gHwAwC/APCh8qYNXRiNRvT19SEzij/QMJQjy6iNm9gNhlbNQc1x8PA8vDyF08PLVitFg5en4uCPEAK1TG/JVELHEL3OOIleSikaux3o6AvcmOo1KozKNUkUuS7fIMdPRjV1O+D2UhRl6EGI4GvqJ8JVHIFZRoCZQcOJ5eV2txdGrRo2mw0GQ2Bg5CdbgPiIXkAYdCybUYINB1vw4xe3AwBe/qoWK+eXhyVVGiT+evGXXcaLs8fnYcMhwTNp89F2rDpzVMx1gm0b/EiEmDna0icqf8qyjTDr+yeUbjDAf8z86b2DeHbLCQBCoJCcgbFc1apeo8KIbCNqOmygFDjeZg27fG1nYGAaK3G8NMuIb6oF4oWdsIgEnqdiaSwgTAxkGjXQqjm4PDwaux2w2FxJIeIcbq+o4iRE+cTBshklOL0iG/Me2AgAaLA44PHySQ0IfG9vI257bY/Yl5l1avzzh7Mwf3Qulk4vwRV/F6wc9jf2wO7yihMqiaKqn4LJwqn3Fo2XT6Cwx2ciam9Wwdzftg1+LByXh48OCv3spiNtuGaB0M9KSPc49wXb77Kkz9JpxXFPEvv7pFRgdF4a0vVq9DgExWNtp012UGJwEBuLiUVChcDBph44PTze39uE784tS2rbNzMey5eP1eCxaxfjg31NuOXV3XB5ebT1OnHVP7fhmR/MEhW7Hi+P+z84LK733bkjMCY/fH80qSgdLT3C9fVAY0/E5fzweHk0MxPUidprLJlcCJN2P6wuL463WbG7zoIZQdtZLiilCZOnco/DZTNKcNn0Ypz32CYcb7PC5aVYf6AZy2fIU7R7eSqx+1iowGIiGOU5Jhzw3f/UdNgwa2SoVU2iil42KLh1iIWxsTiy4Cx426U2K/TOu0AzM8E9/x+Ymr8SX7cVzevv5kUF0euB++8DDAYQQuDMHAd9l2AzoWE8WruTbdvg//4c5dYiveUXJoUoy6j+AB1TfgKQFIuQKJXl0TsYQDdtAmbOBDGbwa9chW6LBd3QAwhUmpB3V4H895V+bhiPvN1PIfvwfwEA9g4NSFkJGs57Eh5TIbomr0rt1/f1gd5wA+BwAhUVIMXFso/DZB2v0WDPPg3WSiHwMX2aDpaUftvQhdIzXQ+gi1LKTrfbAYTc0VBK6wBYAKTGWXsQIz09HZ2dncOq3kEMQkiQqjc5+yrYn7c/A7oiQaLojSPohOcpajttEpI3TafG6DxTiO2CVs2hIs8kKZ1r73OirtMGnlLJTXKmQRNixxEOkkA2Ny+ogi0WmEyBASYbapGvoMQwHM6bmI8zKoQbfC9P8QAz0GMxkNYNAHA2M6D58lhHTK9Vj5eXDoiYwVsifqunWhBbOLBl1utlKNIopSGet9EwhiG5WPKLBWvfESmIzQ+2TLheRiBbTadN7CNz03TIM+ugUXEYVxBoV7J8eiube8US71E5priUkkUZBtG6wu72SkjqRPH8Fydw0yu7xL4036zDa9fNw3yfwn5mWaboUdvn9GD9geakfG+3zY12Xx+sVXMpnVzKTZMSGMUZekVEa3CFgN9yRymSQaYmCnbS5qsTHeIkpsQvOU4SelxB+KDBFbOU2zb0BziOSMhDuT69lFLsqrOIz2eWZYYsw6p632S8ipMBnqcSherUXOGe4uIpRXjx2rmi2rfP6cHK577GO3saAQCvflMn7uc0nRq3nB/Zlmei5JiP3d80dTtEUUC+WZew0MCoVePiKQEyJZFteKLdKl4XTFpVCDGfbBBCJNdQJW3f19AtqmzzzDqJjYZSsL724eywKKUSRW9c1g3pJ4d1QzDJK8Jigc5SBbWjEwDg0WbAkZUa66REQIyBAGWbvhy9DdJxgz3nNLjTRyb1O2mbsjyNZMKrFfonjbUJhtadKf8+ztUDziOcQ7zaAF6bEWONgQN97HHQH64Ef+ddERXHtDe1gb4h8LpRuO0PIsnrcXKo/iQPJ94yws31z7YkaWnAvPmA1wv63//2y3cqgY2UgPKAxuhBdtYJYNgyNSyUEr1NAIJHF00ANIQQiZyMEKKBQAAP3rM7RTCbzTCZTKipqYHFYoHHk1xrgGEkByzRW99lw+Gmnoi+snLBhnq4vXzCn5cMxGPd0GVz4XBTD/bWW3CgqQfdTGp3pkGD8lwTVFz47kPNcRiVY5KURlrsbhxt6ZNsD7kKO71vP1FKYbXZ0dTUBI/Hg6yswOAj0TA2FoQQ3HPJJDHcZMOhFnx5rEOyDKU0af568aIsxygGiNjdXmyvjj7o3lNvQa9DCMErTNeLCeqAVDVZ1donO6ALkBJ8p0oQWzAmFQesDPyKtGho7nGIA0azTh1zokCOTy9bahopiM0P9vvkEL3B/rzi/ymwb5AcTwn4PQeXmSeCNbsacOaDn6D8zvfx+3cPiveTFXkmvHXDfMk2EUgLaRl1MlDVFiCPKnJNYQnCZKGtV1pSXJZtVDRpmW/WIccXJGZ1eVEnQzUeDskgUxPFiGwjKnzEvcPN45tqgcBIhl+yXqNCblDgWmG6DpMHsc+5JJBNpk/v8Xar2N9lGTXiRAiLy6YXixVQO2q6cKJdnv2BHBxs6hE9V3NMWpSlB+49zqjIwRvXzxN9y91eil+8sgtTf78e96zZLy53wzmjxdC4cFA6WSq5f0jSRDFLlr+7pzGizU8ssKT4/DG5/WJBdvnMQKDc1mMdsgPlNlUyyuOxeQmJK0bGsG6wuQIVaTo1F1elRp7Eo9eJ+Q9+gjVJ8FROJoTr3UasWmfFmQ9uVNw+1rbBVnR6VPsDSik+bB64ol/qdMLyh7dQ/3kODr1aLD6qn+4MCepK6Hu8XtBf3g563fWgkewLUoiekYvF/zP6IZQtRM07CERPETF1KsBxwKFDURdT2VMTFOqHuXodKtYuxbhXTsfYN89BRnXgvGhtnwzwAEaPATH033iTXP1dQKsFvtgKeuRIv32vHHhGz8Ko5XaMWNQBjbsLmr7B1Y8OFiiVypwAMJIQMsKn2AWAbyAEsH0PwL3Mst8HoAJQnWgjhxoIIcjPz0dvby96enrQ2to6rO4dhOi2u0Xiy48GIvhuxaMis7k86LK5JZNKLbXRP8/hcECvT4yYjAVKKVotDvibRbv0UW+GbS4PLDY3womw0nRqqA0ayLGEpRSw2l3oc4Y/9tsIUC9jW3t5ihafd2Gfi8f8iWUYMSJf6tHLlMAlSvQCwGklGVg+owRv+YJh7vvgIN65cYGYtN1td6PPKRw7Bo0K2QrT0ZOFs8flofpLwS5985E2nBkUEsOCHRCdPU46IDLrNSjLNqK20wYPT1HV2ofJxfLm6CKRgKcarphZgnvfF7bF6h31UUuP2W02sTg95uCUVTNWRVD01ihQ9LJq0AYZRK/UM9fM/K9MxSYHckPqYmFGWSbe3ycMNnbWWvCDOKtH1+xqwJ1v7YXDLZ0kG5ltwOrr5yMrzLm/fGYp/vzxEVAKbKlqR1O3HUUZid2cH+sn24Y1uxrwsc8Sxo+dtV1Ys6tBtiUAIQQTi9LFCoKDjT2yS/xZVA1gEBuLhePycNxHPG6qbMNZY/MkbRsdRxAbIGzr9j7pZHB7nwtrdzemzH4hUUgC2WROoLD+vDPKssL2d7lpOiwan4cNh4Sbi7d21uOXi5OjBGRtCBaMzQVHpH6QEwrTsfqG+Vj5n6/FyYUe5t6QILxvNYuJCn3uU2H9NLc8G6VZBtR32dHj8OCTQ624ZKrykulkeN4qRVGGAQvG5OLzo+1ioNyN54yJud7mo8x9jQJ7mXBg+6iaMIreRG0bAODDfdIKj0aLA3e9tQ8ABsU5v2ZXA+56ax/svkmCBotdbJ9cmJq2if9bCyP78zq8DvzzxD/xefvn8TU2CSA6HWikipNkErL79ws+tCYTkNH/+reeUZeAvvch3HYVsjyfgsy6A1STuqqgQWfbkJkZfn9mZoL70x9BbTZgzx7QBx+K+BHp1evRNfF7KWmeuXodCr++H5xXGMsSPtDXdI1ahu5Pq4XXL0qtHUIwSE4O6KWXAqtXg77wAnDvvYOiUhkAQDg48ybD5BX6G0P7PrjNg7MaaiARlWEhhGwE0EEp/bbvpU0AFgE4D8DzvteeBXAVgN8RQooA7AYwBcB1EPx8X092o4cCCCFIT09HevqpS3wMdsx74BMx/IRFSaYBX9x5ruLPO/PBjWGDjaJ93meffYYZM2Yo/i6luOGRT8VStPW3LMT4KL6XkX5Hul6NPf+3WFEnTynF3z47hkfWV4Z9X862ppRi5b0bREXOpikToQ5KA22VKHoTs27w4/bF4/H+3iY4PTz2N/Rgze4GXO4rLwy2bRioC9/CcXl4wUf0bjrShrsunhhx2U1HxvtogwAAZpFJREFUw9s2+DGpKB21vuTxg409soheSmlEEvBUw7IZJXjww8Pw8BTba7pQ3W5FeRjlGqDc7oItmz8WUdEbGJjG9uhlFb2x1ZaRbCYkit4kWTckywqEDXySS0iFwyPrK0NIXkBQ/oUjeQGhX5tXkYOtxzpE0uKGRbFJi2io6ie/2kfWV8LtlQ58XV6KR9ZXKiIiJhUHiN5DTT24aIqywR6lVKroHUCi9+xxeXh+azUAgVjieZoU4v2R9ZXwBlV7eXjl27o/MX1EJggRJnIPN/fC6vRIrJrCYWetRfw/nG2DHytmlTJEbwNuPX+cOLmaCEK86XtCg39KMg148/p5mHvfJyEWVxTAExuO4tuzR0T8jvIcEwwaFexuL9p6nWjtdSDfHHnSme13k2X9xHGCBcJfPjkKQKgmUEr0Oj1ebDveKT4/OwHPW6W4YmYpPvfdp6zeUY8bFo2Oem/VbXOL1RqEAGdFmeiWg3IJ0Ruq6E00iA1A2Hthu9s7aM75R9ZXiiSvH/72yYWhfY/4f7QgNovbgu2d26EjOqhValg9odvcqOr//ItUgH4uBFphwYLUjReikJn2tDFwHMwA7wQ6D1PgzavDLse98HxSmqKxNor/S4jeKG1MJWL9LmI0AvPmIVrtdcaJ99E14eqUqJPz9vxNJHlZeDVpaFEtBlruBQoKgH7gC4JBLl8O+tFHwP4DwI4dwOzZ/d6GYNAvvwQmTYI9bypMzQLRq+/Yh55RFw1wywYfYtXjLAJwJvP8FQA7Aczyv0Ap3QDgKQik8fUA/gHgRggBbdsgVfkOYxiDBs1hSF4AskvG5K4X7+clE6xSIVYidKT29jo8im9QCCFRVRlytg0hRFoWGVQizvNUEmoRbXClBMWZBvzkrEAa7yPrK2H3+ZQOtD+vH2dU5ECjEvbJ4ebeiJ5vnVYX9tZbAAAcARaEGRBNjIO0a7DYReVTul49IBYWgwV+RZofb0Up2VfizwtIiaTj7VbR29EPp8eLxm7hmORI7GOyKDNwjjT3OCTe4mHby5xzbFk5a61Q1dor2xomEnheOnGQiEJ8cnE6tD57mJoOm+hvqxSR+qhwk4QsWM/J1TvqE7Zv6i/SM1nXsUQnATqsLtEyyKhViZ7LA4HTK7LFY+lISx921naJZEiWUYOcGGrPSBjM9wyRYNZrMM4XNOblKfb4rivRsCtKEBuLcybkiwRag8WObSc6Ii4rF70Ot0RRfFYU4jLTqI3YF8baJyqOYAIz0RmrwiFV1k9sv7PpSFuIDUssbK8OHNujck0xJw2TiSWTC5HmmzQ43m6V+DqHwxfH2sXKs6klGREn3uQi36wTw4u7bG50M8Su8Friit7Bfs5Ha9/MmTPFRzQQXrgndGSOhdcQmXzPoBm4sexG/GvRv7Dte9uwb+U+8XHn3DsBAMXa4ojrDxVQtxv4UrCzIGctSNn3cC88D27tmtDHC8+D6HQw/3gR0oodEGoUwiCJCmaNNaBcd+nyQT/8ENTrjdrGwQ7v0VroulJjX6C2tYR9nXNbQT8ULBzIhUtAVMkJ9lUCkpYG8u0VAAD64kugfGL3+YmCdnSAPvIo6E+vg80wVnzd0K6s8uBUgSLjJUrpUUrpHErpTUGv/wLAxRBUvhsArIag6F1EKR0cV69hDCMIkVKO400/NunCd8CJpiknA7G8x1hEsj5I5HdEGsjI/cxoZZFdNpeoQEvXq5OWcA8A1y8K+PI1dTvw7JbjAKRqnGT568UDk06NOeWBZGhWucRiS1W7aCkyfUQmMsKoUVhSTU7pqbBcYDA7sSi2BcHJDgm5t7MhYgiVxLpBBtGbYdCI3n4uDx+iwq3rtIv7tzjTAJ06+jmgU6tE5TtPI096AcIkgT8dXqfmJKqndL1GJJXdXhrRP1gu6rpssPomU7JN2oSCFXVqFU4rCWzbXYyqUAly0sIP6GP1XRdNKYTJ1xcda7NiT32oilAJ+ovoTdZ1MVFbD0kQW17agPYtRq0ac0YFCMrnvqgW/09kXyT7HqS/wNo3xDqveh1uVLYI+58jwLQRmRGX1alVWDotQOys3pG4597WYx3w+PrhycXpEo/UcEhknyixb2hI0WRxWY4Rc8sDYbJrdyvbhhLbhrGJKWSVwqBV4eIpheLz1TFC2TYHK7UTBMcR6b1yp/ReuYsNYjPFp+gd7Od8tOvdjh07xIcqN/yxwTHbxVp0Bq7dcS1WbFsR8rjmm2ug0WjwnTO+gxlloSrF5WOWI0ObgSp7FQ52H0zOj0sACU3U7tkD9PUBI8tAyiJbeqUa9gVXo/RsS798l5qxbujbcAL0H/8EfeqpfvnuhBBFWVzzWQ40a/+Tkq/1GML3X3ZPAbBzJ6DRAOefn5LvloWLLhLaUFMDuvxy8JctCzyS6GUtB/T9DwCvF5g1C86yWaC+iQudpQrEM0w5BiNpDvuU0nWU0msppUsopVdSSv9FKY0ePT6MYQwg7lgyHgaN9BRQEYI7lij3havtsIlqTxYGjSquz0s2pIre6KXao/JCFRyJ/g5hW0vJJyWfGU0dlswgtmCk6dS47YJA0vbfPzuG1l5HSvz14gVrw7A5AtG7WYbnXrBqWs6N7bA/rxTnTswXQwgbLHZ8daIzZJk+pwc1PosMFUcwtkAeUcSGUQUTqkqC2Pxgj9toYVksYTGh0BwSojhJoTdlNAT78yZK7kmCo+K0b5gRhpiS03cZtWqJXUEs0iIaHO5AoBlHEDbMKllItK/2oyLPJIY4NVjssCgMJh0stg1+sETSugMBtVIiNhrJ2tb9jRmSQLYYIaB13eIk1ITC9Jg2D+xk2Yf7m2B1eqIsHRtyrn0sEtknSsIp6y2sdUNy7yGumBWwAHhTYb8jIU8T9LyNB+z+jxYoRylNiZdwNJ9etg/LjFPRG+744ghw++JxEdboP/A8hT5M8F6443/cls8x8fAhTDx8CNr334PrtVfBrV2DUd8N7C9r0Tx0u8NPcPZ4ezBhwgTodOEnXowaI66acBUA4O36t+P9SUkDfeop8N++UkpwySS6/LYNZMFZ/dDSyPAY82ErmNMv3+W3buht0MH12R5ApQK5aPCX1YdTHJv+9mtkj+sDeIKeNZXg//dywhVawXBmjA55jVfp0V68HCguFiw/BtAKlGi1gDsCpdeP4YLUbgfWrRPadNll4DVpcGUIlbeEeqHvGPhJocGG1EepDmMYgxTLZpTggcunIpeZwfZSKpsoYfHQusPw2xpqVRwIBBXrA5dPGRS+W+XMb6qNQvQebenFV8el5FQyfoewraegJNMQ17aJpg5LdhBbMK6cXYqxPqLB6vLiiQ1HB411AyAkTfuxpao9pKyfUipL+VKcoUe6XhiE9zg8aIxRmg4kz0/1ZEGIIi2MfUNlc49IfIzOM0GvkadAH50fGIAGE73s5I3c0CtWZV8fJZBN6sEcuo/jsfyQ912J+z1LfHpjEFKR0BRkh6Kk72JJi3f2NMLpiS+U9US7VTxmRmQbZR8z8SDRvtoPjYrDOGYSQ+mxcWyQBLH5wRJJbB+bSNuSta37G+wEyq46S9RBLzvBwiqBI2FqaYa4TW0uLz7c3xxjjcgIIQNl+M0msk/kKno9Xh5NlkC/kux7iIunFEHvEzEcbu7FgUZ51QQtPQ4cbhbur7QqDmdU5CS1XXIwpzwbI7KF7dHj8GDDofAlzVWtfaJ9jlmvxvQoSnElKI9S/dZlZRS9cXr0+o8vtlqFp0CaPr7PSybW7G5AvSX+652mtw7aPuGeh1cbYM+dFnV5VYwy9KsnXA0tp8Wu3l2os9VFXTYhRFJx+l6nPT3Aps2AK8JkZRSii/I8cPiw8CSFtg1y0T3qkqjvU4sFtFVG2nYMaKzNcNs4NH0lXCvID34AMm7gJzPigb1oLrLP1KNgpgUgFHjtDdAnnhAsOZIATW89TK3fiM8pALexEM1z74b9vB+BPP0UyE9/mpTvGvLY+ClgtQITJoCMF44ne+4U8e1h+4ZQRJ9aH8YwTnIsm1GCZTNKcMPLO/CBLw333vcP4c3r58lWk+2o6RTT3QHg1evOiOpDNxBgyetoHr33f3BI9DxbMCYXL107N2kls/5tHQ/86jCXhxfVYX5FRStDxOQnKYiNhVrF4e5LJuJHzwkX4le/rkU24wU30IreiUVm5Jl1aOt1wmJzY2+9RaK4Otzci1afT1+mUYOppZlhP8fvhewPYjnY2BPTO/BgDBLwVMQVs0rx0jYhIO+DfU34w9LJEhXbQWaiQgk5LlfRWy5b0SuP6I2l2o7H8iPidyXJn9cPth/eW98Nt5eHRiV/fru9z4n9DUKb1BzBzt9dgHQFA/LTR2WjJNOABosd3XY3PjnUiosVhpIBoTYGqUYifTWLSUXp4vY71NSL+aPll4L392+OhfEFZhSk6yQVJAAwOkESOlnbuj9RkWtChkGDbrsbnVYXqjtsEVXmO2X68/pBiBAo9tA6gRxZvaMeK2bFl6R9ot0q9m0mrQqzRsq7L4t3n0woNItBdcfa+uBwe8NOyrT0OkU7idw0bdInbsx6DZZMLsTa3YKq7s0d9bLCVVlSfHZ5Foza/h8ichzB5TOYQLkd9fjW1FCfVratC8bkhlSaxIuyKNVvyfDoBQLH1/+t3S+G6T7w4SEsGp+n6PqUTNhd0sC1n58zBrN1TVi0aJHszzA1bRP/t+XPAlSJkdc5hhwsG7MMrx95HW/Xv41fjPtFQp8XCTGDutLTgb8+CXr9zxR/NuE44G9PA0eOgBQpv/YnG32liyBEKYUHffKvwKFDwPXXgZx9dlzfwbl6wTn7UPdlDrwuDpg5E7hsaXwNHgzgVOgpvwg59hegMXnRsC0XdMsXoJ9tAgVQBkB0rY0j0C5vz1Oir7Utdxrqzn9GEvhGCAGMg8PaZSDAr1wVOply+DD4lavAvfA87LlTkHlsDQDA0DFM9AZDzhUlgxDynwQez6b8VwxjGAni1xdOEEOtdtR0yVaRUEpx7/uHxOeXTC0adCQvIJCR/utGo8UeNjRpy9F2fFop3DwTAtx98cRB47kaTR2WSusGPxaNy8NZPr86ngLtfYEb/oEOICOESJRKm4+0S95n1bxnjsmFKkqKuRKPwV6HG7U+CwK1AguCkx3TSjMwOk8YLNpcXqwL6kvitbsYkx9QuLJqR0BaYlqWLU/Ry05QNEQjemOQ+cG2KomUtEmtG2ITE7FQmKEXz0+724vDCr1itxwNnEszy7IUkbyAQFpcMTNAGMVr3zDYbAzkQkkpezCOSX5z6qwq5CK4n/VjzCAgofsbHEcwoyxTfB5JLc/zVOLhK/feaPmMEvgvU18e7wjxJJcL9to3b3SuaCWSKph0atHDnKdAZXP4/obtb0tSNFEsqSbY3RgzcBNIvudtvGDbvvlouyRs149U2DYA0avfkmHdwOIX542F2R8+12bFK1/XJvyZ8eLZLcdFhXRumhbXLwotJX/mmWfERziYmr4U/7cWzUtKu1ZOXgkCgqN9R+HhE7NxSQSJkLREpQKZODHu9SP5HF+741rFn0XVenCmCBM4GRmAWg3YbKCPPQ7+z4+B9inPXdBYm9B+wAx7mw4qI0BuuVkgvIcweioEJbS5xImRF7QDngjHokIbA33bXpjrNorP22bcLJK89P33k6Ku7g/w9/wW9PMtilTO/MpV8qxQIm1T3+sORtGrb98HJNlWY6hDznStHsDKOD+fQFChK++NhjGMfsTIHBN+OK8cz245AQB48MPDOH9iQcyBwfv7msSBjFbF4c4LJ6S6qXFBr1GhOENQlvFUCBOrYAaoXp7i3vcD3jbfnlU66DxXI6nDWhhFb0EC4U3RQAjBXRdNxJaqz0OuIVuOtmH5zPgUR8nC2ePzRJuATUdacfP5gSTSTQoGb0qImcPMIHZMflrMALBTBYQQrJg1IqBI21mPKxhFWiwrhEhgCb6q1j5QSsWJGImiNzceRW94IsXp8UpIxgmFoXYKpVkGmHVq9Do9sNjcaOp2xBUsY7G5RLsQrYpDRV5yyL0ZZZmip/bO2i5MKZVPIEvJhPiCiS6fWYonN1YBAD470oa2XmfMQKhgVLE2BkOIWFQyccTC6gxYx6g5ItuOJNVYOC4PbwSR9dtPdGJE9sBWdQwEZpZl4TPfxPDO2i5JH+fH8fY+dNuFgV+2SSvbFqswQ48FY/NE4nHBQ5+iJNOAO5aMV6S0lV77+idYbFJROk60C/3xoaaesOFzbH+bKuunM8fkojBdj+YeBzqsLoz9zYdRt+FbO+ollWmeCEGi/YGyHCPmjsrG1yc6hUC5XY34ycIK8X2H24uvGf/75BK9rKI3chhbdpxhbCxy0nS48dwxePBD4V7hiQ1HsWxGieIJxUTR1uvE3z87Jj6/9YJxSAvjpX3dddeJ//80qJSc8G4YW3eIz61FZySlbWXpZXj+wuehadfA6/ZCHcPjeyBBKQWOHwcZLZDk1OUCXC6QtMSu2ZF8jiO9HguGv9yDsg3C/qMAPMYCtE27Eb3lFwq/4eMNoP/+N7B5M+jnn4efvI+iXFX31sPWrgVAkX1xIToyEp+0j4Rrd1wbdjtkaDLw7Kzk6Qxd6eWw50yGoeMADOnOqMvSTZuA4hKgpBj0ZzeEJyozM8E9/xzydz0hvtRTthiO3NOEz6iqAn3mX8ArrwLPPweiHrzHPQBg3z7QffuARYtAd++O/JvZYyYKgUvXrgVtawc6OmJ+tctcBq82HSpXD9ROCzR99QAyFf+EkxVyjhw3gC9jLjWMYQxx3HTuGLy5ox7ddkGp+OKX1fjxWRURl3d6vCKZAwCrziwf1AO+kTlGkfCo6ZASvat31IvEnUGjwi8XD74wmEgkZH8oegFBfTm3PAtfnZCql+5+ez8IIQNafnvWmFyxZHR3nQXdNjcyjBrYXB5srw60N5ZHoRK/1eDgrGEEsHxGCR5Zfxg8FRRpDRY7SjIN8PIUh5vjI3oL0nVI06nR5/Sgx+FBW58T+WY9PF5eYr1QJrMPKpFh3XC0pU8c8I/MMcIcZgBKCMHE4nRx4H2oqScuopc93sYVpiWthHVmWRbe2ysQGDtru7Byfrms9Xie4vOjLFGUH9f3l+eaMKc8C99Udwmkxe6GqNeVcGDVrYlaBfQnJjKThUdbe+Hy8LJUlaxifWSOccDKmYPRYw9Vq9y9Zj8IN7D9/0CAtUHYyah2WeysCbw+syxTUYXQyGxpH9JgseOut4SyTDnb2unxijZEQPznr1JMKk4XCdNI11CJx3+KKoJUHMHkknQ0MxPhDRY7fr16L2o7rZLtselIK/66sUoyif3UxqMoyTQM2HG9YmapeE1ZvbMePz5rlHj8bDveAaevKm1MflpSq6qKMvRQcwQenqK11wmbyyNaWCRb0QsAq+aX46Uva9BgsaPT6sLTn1bhroviV3/Gg8c3HIHVFyY9Nj8NV80eofgzjB37wPkS711pJXCbhc9IV6ejxxN6HuTo5fs/zyyYiW59N44cORIxvG1QYNdu0D/8AVStlig+xdMqjrL+VEDd1wQKAgIKAkBja0HhV/dC01sPW/F8YFYJ+NIb4XrmdfAnIlQhBZF0bHm9MJIU9lPHh53AD1LzO4Dkk+DR0DPqEhg6DsRcjj72eOwPs1hgrt0AQ8d+AADPadA27YbAZ3woBI7hnHMGD8mbmRmenM3IAPnOVaDrPwI5eyHoZ5+FX99iAX/f/YDDAZSVRf0q+p/n5LeLcLDnnIa0pq0AAEP7XiB3ofz1T3LIOXo6KaXnpLwlwxjGACPTqMVN544RrRj+urEKK2aVRryhe3FrDeo67b51Nbhx0Zh+a2s8GJljxNZjwuwYq1SwuTx49KOAN9dPF1aklDCNF5HUYWxZX36K213TEUqI2d2Ct9lADvSzTFpMLcnAnvpu8BT44lg7Lp5ShG3HO+DylWyOLzCjMCP69hlbkCYOcmo7beh1uMOSe0D8ytRTAYUZepw5JhefH20HpcDbO+vx83PH4kS7FQ63sD/yzTrkpskftBBCMDrPhD31wg1sVWsf8s16NFocIhmbb9bJ9lVkB8fNPQ54vHyIz6FkHxdG3seTigJE78HGHpw3sUDej5J8V0AhHu27lEISyFYbvsQ8HA429YgWLTkmLSYnUOFwxcxSfOObcFm9UxnR6+UpjrcH+uuhpOhN12tQmmVAfZcdbi/FsbY+WX3FYAti8+NvjOrNj8HQ/w8Epo3IBEf8FgU96HN6QlSA7Pk2Q6Gl1SeHQktWlWzr7dVdsLsF8qo8x4iyOEJ24wEbIhlJxd7QT2Gu++pDyQ6nh8djHx/FYx8fjbqu3c0P6HF90ZRC/O6d/XC4eV+gXA9OKxGUgaw9lZyAPSVQqziMyDaKquzaThsm+K5HrKI3EY9eFnqNCr+6cDxufnU3AOC5L6rx/dNH9pto5EhLL15lLCPuvmRiXH7H6S1fif+ztg3/mf0f9Pb2Ir84H2XF0cmdqJ+fng47Z0dNZw2mZE+JvUIqEIno8oe5dXYCRiNgi2A1o7CsP1XI2/t3EEhVuhzvQt7+Z4D9AVsOOgc4fCLUH9sP/o5fAdnZQE52xN/GW92yPEKHAnrKLkDezsfB8THsCebNAxobgaamyAF+AHJ2PiX+bxl3FTxpwramfX3A5s0AAHLhksQbniTEnKS46KLYH/L118LfKNsFAPCtb4Hk5AC5OaB/fizmxzpypzBE775hopfByXL+DWMYScEP55WL5YXddjee/KQq7HJdVhf+ujFwo3zzeWOREWcKb3+BLX9lPT2f2XxcDOvKN+tw3dnK1Gb9hXDqMCDIuiEFYWws2O9i0WiJ7HHaX2BtGTb5Smr9fwHB3iEWdGqVhFg5HMFjEEh+cNbJBjZAaPXOBlBKJQP/eLYZq+b0qzyrJUFs8kvc9RqVaCHg5alE+eWH3H3MKroPNcsv0Zd8V5zexbEwqSgdOp+KtK7Tjrbe6GV3frBl32eNzQUXxds6Fi6eWiS24VBTjyK/2voum9jX5abpBv11Jhjx+PQOVk/iSP38YOj/+xtpOjXGFQikJk+BvXWWkGWUBrGx8PuFBkPutlZiWZRMsN7ih5p6wYexQKi3sNYNqSP05PZ1kTCQx7VZr8GFkwvF535rKgDYfFTZfY1SSMKL2wP7ShrGlrx+eOm0YtHiw+XhJaFoqcYDQQHMi+I8V8yt34j/WwsDtg08L1y7ivISCyKrslThloO34MnjT8Idi2hLEbgXnge3dk3ow0eAkfPPA/lXeP/ieNHmbIu9kEKobS2yliOxGKIjR4Bt24D3P0i8UUMAvC4D1pKzYi7H3flrcE/+BeS1V6MuV/MKj5Zd6bDaMtHy+A7Ro5Z+7/siEUrv/k3c7U2mt7McEEJiVu2Qu+4E+cMfQH52fdTluJ/8GOTy5SAL5RG29mCf3mGIGCZ6hzEMBlq11Gf3pW3VqG63hiz3l0+OoschlOaMyjXhe6eP7Lc2xgs2ZMLv6dnS48A/Nx0XX7998fgBSVqWA786DADcXoqq1j54eSoZzCj1vlSKSCXp8ZSqJxusT93mo22glGLzUeXKl0kyfDU9Xl4SNDOs6A3F4kmFosLtRLsVO2stUuI0jm3Gkl7H2oRzmPXnleuB6Qer6g1n3yBXtT0xgdCtcN+VTCsQrZrDlJIA+SJX1bs5iWE/6XoNlkQgLWKhapCFkilFPD697G8ePYgUzIO5/x8IsGr5HUGBbD0ON4769qOKI5g2QplPY6LbOpnnrxIUpOtEErDP6Qnbr9b3k6I30rbSqAimlmaID38Qsdz1+wus7/Pa3Y1weXg0WOxi/6BTczh9VHbSv3dkdui9stvLo9d3z88RJNVHlxCC314SsGt4Z08jdoeZOEk2khXArLK1wdAtiGIop4atYBYA4L2m97CjbQdycnKg0SS2vcZkjsHI9JHo8nRhc+vmhD4rlUjUj5eFw+vA/x38v6R9nh8eY/iKK55Tw549UfKIBvLgAyB33A5y7TVJb6McfN35db9/Z/coIZRNpfeGX8Cv7gZiBtB5nSp0Vqah9h0j0B3BaiIBFXh/2lrIBTnjDJDp00DKy+WvxGzTSK87cib5jEgAXfcxcJ74AlxPRgwTvcMYRhAuPK0Qs30DGLeXSnx4AYG0+e+2GvH5nRdNSHmaczJQlh2q6P3zR5VieeOEQnPYQJXBhGASsqPPKaoRsk3alAeC3bFkPAwa6XcYNCrcsWTgPY2nj8iEWS8Qi03dDmw83CqWH+o1HGaXy1NUsWrKSKTdiXar6JFXmK5Htik5ZYwnEwxaFS6ZElCxrN5Zn7DdBVu27x/ssup8pURvaRSfXkqpbJXt2II0qHyK15pOG/qcytKxXR4eR1sDEwcTkjxxoNS+odfhlhBXZyWhPFhKWjTA7bNUiYXBamMgF5L+JA6idzD95sHc/w8EWJVu8Hm1u9Yier5OKDQrnkAOt60JgFuZoNFIaOlxiNUoGhXBGRXy/UATBSEk6JiXDqp5nkqUsiUpJHojHa+PrJiGd36+QHw8smLaoDyu548WAuUAoNPqwmeVrRICf+6obOg1yb/nk1S/dQrXVwtj25Bh0CRU4REOs8uzcdFpgcnAe987GD4EK0lIZgCzsWmb+L89dxqoxoROVydeqn0Jj5x4BAjNcFUMQghWTV4FAHin6R3wVN71cyhDr9JjSc4SqBD+GM9Qxxdy1jbtBvAqqY0br9Kj+fTfoXbJC5JHNJCJE0EWLABZujSudiSKTE1mv3+ntWgePLpsjFvWgonfaUTaP36N2r88EaLuloPyC9qQPoEIdh+nImQQuEBsJT0A8Jo0ODOFEERCeZgs/VcVMdgx+NmpYQyjn0EIwW+Y2fUP9zfjm+pAqMeDHx4SPTHnlmdj8STlfpQDAZYEquuyYX9DtyRB/DeXTBTJmsGKYNKADWLLT7GaFxBCYB64fApKMg0gEBSRD1w+ZVD4M6pVHBaMCSSL3//BIfH/eRU5sgdEcgLZhm0b5GHF7AC59+6eRuxvCAz6E7VuqBKtG1iiV5niky0bbggiehssdrFqIcOgQXEUf2e9RiWS0NTn2akEVa19cHupr00GZBiSa08wsyxT/H8XExAVCV8e6xD7+MnF6UmpFFgwJle0lmnvc0lsVaJBQnoOInWrXEwK6k9ikRduLy+ZvBhMit7B3P8PBCTnVZ1Fsm8TsW0AAtu6iOl3KCBrEom1bZhTng2Trn+rlFiP8eDJ0tZep9jXZZu0Ka2gknu8DtbjWsURXD4z0IbVO+slRG+qLDnKc0MVvRaJbUNqJrZ/feEEUV29vaYL6w80p+R7AGFbJiuA2dAYyGu3Fgm2DR+1fAQv9WJO1hyMyh2VWGN9uHjUxcg35KPB2YCdXTuT8pmDEX4S226348KCC/HFlV9g38p9ksdDMx/CBOMEeGkEZWkU9JZfiOa5d8NtLAQFgdtYiOa5d6O3/MLQhSORcRkDf99fhCKkq8O3I14SPCY4NXrKA765Gcffj758hO2n0nthyHEDN90CkoKAvlROEsVEEglcJXAw9g1pXQejLHlqYXDWaA9jGAOMGWVZuHRaMd7d0wgAuPf9Q3j7Z/PxTXUn1h8I+Bvd8634Sp0GAiadGnlmHdp8A41fvr5HVNwsGp+XFNVaqhFcBjyPUeqkOojNj2UzSgZ8ABQJC8fl4cP9wuDAX9rvf10u2G1c2dwbNqTroESZmgS5xkmK2SOzMDLHiJoOG3odHvg1q3oNp8hP14+R2UZoVARur+Cp2+twS6wblH6mVNErLXWShKMVmWP2cxOLzKhsEdY52NSLWSPll9SmOtiPJZr2Nljg9vLQRAmcYT0gk1X2reIIls8oxT82CYFeq3fW43wZk4QSG4NBpG6Vi9IsA8x6NXodHlhsbjT3OFCUEVnFWNNhE0n24gx9v5N0sTCY+//+xqhcE7KMGnTZ3LDY3DjebhWJ+Z21FnG5mSMz4/p8/7Z+ZvMx3P+BUFn1l0+OYvnM0qiTQQNl2+CHdEJa6nPP9rOptG3wQ+7xOliP6ytmlYohiBsPt0qqtlJF9LLVb36PXjaILTNFPunluSb84Ixy/OeLEwCABz88jHMnFCS9YtDm8uBRxgc4oQBm3itR9FqL5sHNu/Fx68cAgO9N+l5CbWWhUWnww8k/xKPbH8Xb9W9jdvbspH12UhErtC0KTlhP4MmqJ3HjiBtRllaGcePGQaeTTjR7eA+eOvIU6vrqsKF5A5YUKQ/s6i2/MDyxGwSRdOM9GPXBd6DtFYL7usYtgCQuM4HfrAS1tlo02BswRTcFaWlp2PydzVCppCKW5uZmbDi8AVaPFSZ18u2uekZ9C9mVrwAA0ho2QV1wdcRlg0nL4s/vgLl+EwDAlj8TfSULQUhwNF7iiGcCIFmIl6hNFPacKcisehsAYOo6MCBtGIyIevWglHKU0siRi8MYxkmMXy0ZD62PDNhTZ8G7exslKsll04sxtTRzgFoXH1jvMT8pw/m8uYYCgtVhLb1MEFs/KHoHOyINapUMdrNNWlFF5fTwov0DC0lJf1GKZs5PAhBCcPmMUDuUCYXpcann1SopQVzV2ofazgBxoDRZviSKdYPSfSzH8iMSEvUujoX8dL3oR+xw81G9YimlEkVgMlPdV8wKECmfHGqVqMQitWWw2hjIBSFEkYfzUCe2TyUQQjCDtW/w2Z3wPMWuBBW9LFbOL8eIbOH87bK58fSn4UNyAaEkfUtVwJu+P4PY/GD7wuC+pr/8eU8WjM5Lw3RfUJnbS0VFd1GGPmX94YhsA/zzmk3ddjg93qAgttRZVf3ivDFI91lwVXfY8BJjE5csJDWAuWk3VE4LAMCjz4Yzcwy2dmxFt7sbZfoyLBwlL0xJLq4YewXSNGmotFXiSO+RpH52shCvUrGqrwp/OPgH1Nnr8GHHhxg/fnwIyQsAak6NX8z6BQDgjYY34PCGD65MKjg12qbfJD7NPLoamp7Asen/zea//RITv9OIid9pRNktI5JK+jU7mvHHQ3/EY0cfQ6WzEqNHjw4heQHg7aa38VDNQ3ij7o2kfTcLZ9ZYODLHAQA4rxOFHVtlrWdo3SmSvADQOuNmIEVCMS5Gwb7Ho8xebSiADWQzdR0CBlLVPIgwbN0wjGFEwIhsI350Zrn4/OZXd2NPvVB6rSLA7UPQly/cJeWqOWVievZgh18dBgieaXvrAqXwcSsSTiKUZBpCBj8qjoRNRI+GWPYNwWrPYUQGW3rqx5GWXqzZ1RDX57H7d+uxDtErOcuoUWx5MIIhGhqCEtYPKVRty7H8CIc1uxoknuc9jtQkakt8emsi+/RWd9hQ1ylsC5NWhVkjEyOpWIzJN2NaqUCau7w8pv/xY5z54MaIx8JL26pF+wwCYNuxjqS1pT+hYxRpt762O+qx/+6ewHs7a7viPk+G0T9g7Rv8Kt5jbX1icFWOSYuy7MQ8CHVqFX7NhOQ+/0U16jrDh63srbeIfqr5Zh0mFPb/9Wl0XpooEmiw2NHNqEHZfrbkFA3xU4pw2REjs40pq6bTqVUo9lUd8FQg59lJucwUEr2ZRi1+cV7Ah/re9w9i1J3vR71OrNnVgDMf3ChruTPu/wRPbDgqvvbLxePitw/Z+zrw4nLxqSutFBQEHzR/AABYMXpFWCIuEaRp00S14t0H7saKbSvEx7U7rk3qd6Ua1+64VtL+O/ffiT5vH9REjYfOfwhabeTjbPHIxZiUPQkWjwXvNrzbL+3tK1kIW/5MAAChXuTt/mvIMhpro/i/25Q8nWCnqxN/PPRHWNwWTEqbhEtnXBox4O/ssrNBQPBhy4dotDeGXSZR9PhC2QBg0vFnULF2KczV68Iua65eh4q1SzHik+vF17rLL4KTDbuTaXcQC5vbNsPutqOnpwdZ2vD3rtm6bNjtdtjsNhy3Hg+7zFCE21wGr0rotzXuHuj/PkPoo05xDK6auGEMY5DhhnPG4KUvq2FzS43/CSHYXt0l8bgc7FizqwG7whB+Q4mo86vDvj4heCZ/WhkoHvL7X57qKMnQS1RxXp7i7rf3gxAiuzRzUlE6Nh4Wtu3Bph5cNj2wXmuvA+19ghrEqFUp9oU91TAi24jRuSYcY5TRNpcXd721DwAUl8uyRO8nhwI2MvHsh5LMQP/VaLHDy1NRaazUh1lq+dEj+axIWLOrAXe9tVckqwHgf1/VYlppZtLLiGeWZYpWPDtqLVh1Zvjl2LLveaNzk142OyY/TZwwBATi59er96Kt1ymxcthwsAUPrw8EgVJA8Xk8GLBmVwO2HQ8Q1D0OT9jfCwi/2W89AwBWZ/znyTD6B6xa16/iZf15Z5RlJYWQu2RKEZ4tO4FdtRa4vDweWncYT109M2S5zUcCat6zxuYNiLWWRsVhbEEaDvjU6webejBvtGAzJbVuGDr3jwMJVZhd6J8ESlW/MDLHKJLyNR1WiXVDVoqsG/z4wbyR+NtnVei0ukVRWrTrxKMfVYrXULnLAcLkoYaTf3371re+FXiy93Xg3V8A7sDEhb7zEBqOvoRj1mMwqUy4YtIVCn+5PNg99rCvd7u7w74+WBGpvR7qgUkf/X6OIxxum30bfvzRj/FO8ztYUrQE6ZoU++YSgtYZN6N8/UoAgLlhMwytO2HPD/TDmr4m8X+3qTDkI+Ti2h3Xht0+KqjwtyV/g9kQedw6KWcSlo9Zjreq3sKzx5/Fbyf/Nu52RAKv0oBCOIcIAI2tGYVf3wuVvR3W0oCK3VS/GXn7/gHOG5googAc2ZMkn5cM5fPbDW/j5bqXMcE4AY/PfxybT98ccVm73Y6HP38Yq5tW4+oRV2NZ8bIhY0MZCeaa9eD4QG4P19ci9FEAMPXKAWrVwGOY6B3GMKIgw6CBRq0CgoheD0/xyPrKITX4fGR9peh9yOKfm47jh/PK+79BcWISQ/T6y8+A/vPoHezYH6Y02u72KjpepV7IUo9BtvR6QqF50Af4DQZ0hCnRV7pP/GDDqdiJm5EKbRsAwKBVITdNi/Y+Fzw8RUuPA8WZBvQ63KIlhJojskpkc9N0yDfr0NrrhMMtWH7EWu+R9ZWwB/WtTg+fkr51ZpgS83DYJAn7yY24XLzYGkaV6/TwuO+DQ7iPsQYKh3iPmYHEI+srxfApP+T+XmBo/uZTCdNGZIIjgvKxsqUXvQ43djKBh8lSxBNCcM8lE3HF34Xgp/f2NuGaBV0hthCbjgQmf88eP3C5AxOL0kWi95CE6B22blCKpz89FvKay5vae/CROSaxr65ut0mtG0ypU/QCgqI4nGmn3H5T7nIUwJ8/PoLLwyimw+Hddxnl6OOnSUheAOB4NyZVvomlk1YgOy0b6caBD+w6mXF60emYXzwfWxu34o26N3BtReoVzc7sieguvwgZ1R8CAPJ3PYGaxc8DRJgw0NgCE7VuU1Hc3xOJBPfCi+y02PkPv5j5C6yvWY89vXuwvXN70v2ccw6+GFIhy3ldKNj9JLD7yajrEgDZh1+GZfxVSWvPe03v4eW6l0FAcGn5pSgpjt4vGgwGZOVkgTZRvFz3Ml6uezlkmQxNBp6d9WzS2phqXN3wL3SUh/ZlOTv+iM9OYaJ32LphGMOIgR57+FLiRkv4WeXBikjtHWq/I5KH57B1g4BOa3jfTyX7OZrfqtS2YfhGXg7Y0l0W8Zx7LHnKWlDFq6xmy4f9JIQ/jdv/fWwATjRE86YMh/7skyYVp0OvCZRTt/aE+to5PV58yRCxZ4/LT3o7mrsT89Mbav11Mto71H7zqQSTTo3xhcJ5Tymwp65bouhlrR0SxayR2bhkSoA8uO/9Q5J08W6bG7t9k1+EAGeNSf5EjVwE5wn4wRK9JcNErywMxL1rOTNxWttpg8Wa+jA2Fl0R7hmSjbi3YXd92JcL+1qwLG8Zrp91fdj3U41qa/WAfO9A4bZZt4GA4IuOL+D0OmOvkAS0T70BvEqooNR3HkZ69XrxvVRZNyhFjiEHP5v2MwDA89XPw80n93xS21piL5TC9Vmsb1mP52uex/+3d99xclXlH8c/z5ZkWzadNEhCTQESuogoAYVQpIigIKIiAooiWLCgYFBQhJ8FwQL8FAQFVETAAkTEgAV+EEgoCQQIKZBeN9uy9fn9ce7szs7ObJ3d2Zn9vl+vec3cfu7MPXNnnnvucwAumX4J5x5ybpda537+4M9z45wbU07PthbyW5Ld+gFsGeSNkdSiV6QTE0cUt8tfGRufTXJlP1LdRq7UDUE6Pucpo0ooGZJPTX0Tm6vq2Fi5k12GhUB6d2/pl/TWvT3GJg/oTu1Bi14Itw/HUgms2V4DjGrbEVs3PuOZE8pZsCy0iF26bgcnz+74h/4u5UPZsKP9n5O++E4qzM9j1qQRPLMy3A3w/OptHL9f2xYnz63cRm1DyP83dXRJtzu364pUx0J+nrXJmfzWtpBKI9ny2aSr+wu5s8+DzcFTRrRc2Pnnso28HqUOKsiztHdY+9XjpzN/6XoampznVm3j4ZfXc2IU/P3P8s3EDp9Zu47o85aXHUl2sbS52ZWjtwcy8ds1/g6ZlVuqW3IuQ992xhbT2/NEn59Phu8KFW+1G91QvAulpaWUlmYmpdeXX/oys8pnccrEU7hp+U1Jg1XZ1lKxI9NGTeN77/4eu1Tvgjc4pDclclKNpePYNu1sRi+9A4AxL/6Myt2OxguKKGiTuqHnLXrT4SPTP8J9r93Hyh0reXjdw5wy6ZS0rbuxZFyb1ssxbvltAtyF1WuxKKd04vI9lSqtRXF+MZ867FPdSsFwzJRjelwOyQ5q0SvSicvnTqO4sO3Zs7gwn8uzrDO2XNmPvXYpa5cuwCzcOi7p+Zzz8qxNJzbxrXjbdtKlQG9XpLPulQwpSBog6EnqBmh7+/DbUSdk8Z9xqhb0ybRN+dF5i94Jw9u3wu/L76QDp4xoeR3rOCpefNqG9+zTN7d9pzoWfnDmbBZcfnTL4wdnzs6J7+uu7m8u7fNgE58+4ffPtgZ/Zkwop3hIeiMPk0eX8PG4VFPXPfwqdY3hj/QTy+LSruyduda8ADPGt34XvrGxivrGZjZX1VEf5UgdUVLIsKK+bxmaCzLx2zX+DplVW2paOviD/mnR29vzRJ+fT957FRS2/naoB86dMJ6fTj2CseMylzKlKK+IF3e8yDWvXpOyRWK2tVTszEl7nMSM3WdQX1/f5g6HvrR15sdoHBpSKBTWbGDksnuxhhoK6sN725xXSFPx6G6vt6G5gX9v/ndayliYX8hXD/sqp045lUNK0pu6YdPsi2nOb/v7tTm/iHWHf4sVJ/+x5bHu8G8lnW/T7It7vO1Ux29tU23W59mV9FOLXpFOxHKA3fDoMtZur2XiiGIunzst63IG5sp+FBXms9fYMpZtaA0+ji4dSmG+rltB+j7nmRPLW4JhS9fu4Kh9xrKzoYk3N4XWWmZkpEfzbJTuurfnLmXtWvv0OHXDyPapG5b2MNDbUcqPRM+v3sbit1p/sBr0+XdSZ3l62+bn7Zs/q109FnLl+7o7+5Er+zzYxNeryrrGuPEj+mR7lxyzN/c9/zbba0Iu8bueWsX5R+7Ok6/3/YWarhpeUsikqFVmfVMzyzdVUVPf2rJL+Xm7LhPfC/EXTt/eVkN8/KQ/WvSm+zyRjvdw3rx57V//49t4xdv8beR4FhcVsoWNfH5E5zlUe2N00Wi27Gyf63500WgePO1B7l16Lw+88QBv1yRPLzEQvFXzFmX5ZVQ1VbWbNrqo+wHSsrIySoeXsmDNAo6eeHQ6itih5sIyNu9/AeMXfh+AUUt/Te2Y/VqmN5aMb8nb21Vratdw4xs38mb1m2kr55GTjuSICUewdOlS6urqGDo0PQ2CKqceD8DYF35GQc0GGkvGsWn2xS3juzufSF9RoFekC047cFJO/NnMlf2YMWFYm0Cv0ja0lY7POVnrzGXrK1tujd19dCklQ3QK6ap01r29xpbxZFxQsmxoAaN7eJtyfMBhzfZaGpuaWba+Z3mYp44upagwj50NzWysrGNzVV3SlvbuzjV/WdoyfOL+4/nZOQf3qPzdER+QenFNBfWNzQwpCH9GNuzY2ZKbuDDfOHyP7v/Z6qquHgu58n3dnf3IlX0eTKaMLmFU6ZB2+eEPSlNHbImGlxTy+WP25tvRd8hNj7/B7N1GsC7Kfz2sqIADdhvRJ9vujhkTylsuyL2ybgcFcRejlbahe/r7e6FkSAFjhw1lU2UdDU3Oys3VLdP6I9AL6T9P9PY9vPrqq1tez5s3L/RkP+tDvLl8OXc8/yWoWc4Ze55Bfn7f5g9Y8OEFHU6/6MCLuPCAC5l156w+LUdv3LHqDqqaqrh4z4v5zJGf6fX6mr2Zbyz9Bm9UvMHoktHMGtH3+16x56mMfO33DN2xgvzGasY/e13LtO6kbXB35m+cz69X/Zr65nrGFI6hjjoqGyrbzduTIHheXh5TpkzhxSUvUumVjClKz90elVOPp3Lq8axcuZKpU6d2Ol82emzDYxy9y9HkWz/kBOmFZm/ufKZBSv/SRSTrzJxYzgOLW5P+qyO29EvWmUx8S88Zys+bMfEdsgFMHlXS41u2dh3ZtuXSis3V1EW3F08YXtStPJf5ecb08eUtHSK9sm4H7967fcu6v720vqW1eGG+8dXjp/eo7N01dthQdhtVzFtba6lvbGbpuh0tAaH4wPmhU0dROlQ/j0S6wsw4aPIIHntlY5vx8RdW0u2jh0/hzqdWsnJLDRW1DXz2t8+3TDtyrzFtgqqZMnNiOY+9EjrdWbp2B6PKWr9L4793ZWCaOrqETZUhh3x8etv+SN2QTV6rfI3lNcspzS/lgzM/mOniAHT6e2jBpgW8e8y7MxLAWrx9MS9UvEBxXjGn7XdaWtaZZ3mcsMcJ3LToJu5adRfXD7++72/jzytg0wGXsOuTXwRgSOXqlkkNpeO7tIqKhgp+/ubPWbhtIQBHjTmKq4+6mtFl6b3QfuJfT2R73fZ247MtX3NfpOZI1UJ+aN5QfrHiFyzctpAv7P0FhuYP3AZVhlGeX86OpvZ3Evbk4kAu0T8ZEck6MycMbzP89JtbeGDRGrUES6Np44dhFnpSf3NTFTsbmtp20qX8vBmTGOh9c3NVj4//+JZla7bX8vLa1nQKPcnBPGNCa6B36dr2gd66xia+/8irLcMff+fUHqed6ImDJo/krSgX8fOrtrUGel/f3DJPpm/7Fsk2B04e2SbQm2ewcOVWdhvVNwHNIQV5fO2E6Xz6NyHAu7GytVPHYUUD46/NzAmtqY2WrtvB1DGt33NK3TDwTRldyrMr26b4KS7Mp6hwYLdu6w9zfjenXXCouqmaU/98aqctbgeCm5ffzP1r7ues3c7i8FGHk9fNNAM91ezN/Gb1bwD48NQPM2FE+jos++0rvwVgRe0Kzvy/M1vG92Uws3riu6gedyilG55tM37YW49TM+6Qdi1ZU3UkBnDFrCv48OwPk5eX/s8iWZAX2ue7TVW+gRIQfnTDo2lfZ6r6unD9Qi75xyUs3L6Qq5ZcxRUzrmB44fCk82bK27VvM6pwFE21Tdz5zjvZY489lKc4wcD4NSQi0g0rt7TNa1VT38TX738JQMHeNCkZUsDuY0p5c1M1zR7SNvS0ky5Jr9c2tL2lbWdDc4+P/9KhBYwsKWRbTQMNTd6mQ6OefMbxeXqTdch211OrWL21BoDhxYVccsze3d5Gbxw0eSQPRncDPL96G59kd5qanX/F5/dM0gpZRFKrqW9sM9zscMWfXsbM+uycPHff8ew+poQVm2vajH9w8VqO2HNMxn8LxF+QVuqG7DMlyUWKkWrNC5C0BWBH4zMhVUvFssIyygrKWFu7lntX38svV/ySisb+Ce49uflJVtasZFThKC44+IK0rnvrzq1Jx/dpMNOMTQdeSskjHyU+vJbfUMX4Z74L0CbY21FHeGcfeHb3tp0mb9W8xW4luwGpyzcQOvB7q+Yt7lx1Z8rp6W65esj4Q/jtSb/lovkXsbxmOZ967lM47VsUZyoIvqluE/OWzqM8v5wrZ1zJ1KlTFeRNQoFeEck6P1/QPll/bUMTNzy6LON/7nLJzAnlvLkp5KZbsnZH20CvUjdkzM8XLG83rjfH/64jS9hWE37IPv5qa6u8nnzGyVJ+xGyrrucn/3i9Zfjz792b4f38xzlZh2wvralo6VV97LChzJigTgZFuuP+59e0G9fX52Qzo2pnU7vxdY3NA+K3wK4jixk2tIDKuka21TSwePW2uGlK3TDQTRnT/k6TEf2Un1d6r6OWxQ1NDdy37D6KG4q5cvGVSeepaKigyZta0jv0NkBa11zHvW/dG9Y17XzKS/r3N/Sb1W/y1Jan0h7MrBu5D55fjDW17SA4r2knY1/42YDPT7ujageVTZWd5paODwi3OxbWh6e+Cno2NDdw4xs3Uu/1zBkzhxtPuLFPWj4n2mPEHtxz8j18ev6nWbZ9WdJ5MhEEr26s5tpXr2V7w3YmDp3IrH1m9Xlu8GylQK+IZJ2122u7NV56ZsaEcv7y4joAHl2ynuqo1/BRpUPYZdjAzdeU69J9/O86spiX1oQfazt2trbM60nqhulxKT+Wb6pmZ0NTy62uNz3+Rsv6p44u4dzDp/SovL0xfcKwlg7j1lbsZH3Fzjb5ed+z91i1ChDppvVRR2iJ+vqcvLmqLun4gfBbIC/PmD5hWMvt//HfrZOUumHAmzo6SYveUrXozQWF+YWcPTO0IE0V6AU46//OYnjhcPYo3aPXAdJH1j/C5vrNTC6azFmzzup+oXuhsrKS5zc/z582/KlL8zc0N1CYV9jl4LY1Jf/+L6jZ0FqGJJ2rDQTvnPFO8pry2Lkz+T7E/GL5L/j2zG+Tn5/f7y1/73nrHlbWrGRs4ViuPurqfgnyxowpHsOdJ97JO+5+R1rX29MLJw3NDVz/2vW8Xfs2k4ZO4uZjb6akSBdOU1GgV0SyzsQRxS29WSeOl/SJb9EZf2v7zAnlCoZlULqP/2T5IkuG5Ce9dbUzpUMLmDq6lBWbq2lqdl7fUMX+uw5n5eZq7np6Zct8XzthOkMK+r/DpML8PGbtOoJnVoTbHJ9fvY0n4gO9+6SnR2aRwSRT5+SB/ltg5oTydnley4sKGF6sgOFAN2WUWvQKbG/Yzrad2zqfsRNHjz2a9VXrOW6v4xhS2L/H0ezZs/H1TtHwIu547Y6U81VXV1NQUMAXln6BhuaGLgc0G0vGUVizvt18jSXjANhSt4XvvPqdnu9AH5owpmt5kmePnE1DQwPV1dV9XKK2Xqx4kYfWPUQeeVz9jqsZVTaqX7cPUFKY/kBqV4+tVAFhw7j5mJsZW65Uax3JfLe0IiLddPncaRQndIhRXJjP5XOnZahEuSn+Nvz4Xqd1a3tmpfv4T5Yvcvr4YeTl9SyYH398xNJ9XPfwqzQ0hYPo0Kkjmbtv13pl7gvx6RsWLNvY0nmcGe06jxORzmXqnDzQfwskuytiktI2ZIXhJYWMSEgtpBy9g8tz5z7H/NPn88P3/bDX6yryIs6beh7HTTsuDSXrnsLCQg7d7VC+9M4vdTjfuHHjKBxayPb67Wxr6Hpwe9Psi2nOL2ozrjm/iE2zL2Zt7Vq+seQbvF37do/Kng6p8td2J6/tle+9ktmzZ3PQQQd1ON/lL17OlrqQG/r8587njKfPaPc4/7nzu7zdlypC/xtnTTmLI/c4ssvL9admb07r+u59617+vfnfrKhekTIg7Dh77bJXWrebi9SiV0SyTiz33g2PLmPt9lomjijm8rnTMp6TL9fsMmwoo0uHsKW6vs145efNrHQf/8nyRfbmM545oZy/vRRadyxdt4NnVmzlkSWtrT2+cdLMjLYIP2jyiJbXf1q0hqboKsasScMZVaoWWyLdlalz8kD/LZDsezTZHRQyME0ZXcr2mu0twyPVohdI3dFZujuEyrTCvEImDOu8xefi7Ys5YMQBSadVNlRSlF9EbW0t06ZN67Pb7tPxmUyaNIlJTOKZvZ9hTeUaTnrgpC4tF8vDO/aFn1FQs4HGknFsmn0xi8fszbVLvsmOxh3sVbIXW5q2sK2ufQC5r4+bjvI1J5ajs/ews1yw2+u3k78zn3qrT0uKhzPHn8k+xftwxmFnDNg7Kb/58jf59J6fZnLJ5E7nrWio4MG1D3Y4z31r7ktX0QY9BXpFJCudduCkAfNnLleZGTMmlPPvNza3GR/fm7hkRjqP/11HtQ889OYzjg9uLFlbwaK4TohOmT2RA3Yb0eN1p8NBU1pb9MZaGQO8Zx+15hXpqUydkwfyb4F9xg0jz9reEaNAb/aYOrqEF6I7PkCpG2K6GjjLBukIkF7z6jWcNuE0ztrtLAry2oZW/nfl//J65etcuvelHFp+aK/Lm0pag5l5+Uwe3nnQrtmbybMQuK6cenybjtfeqHqDeUu/xc7mncwun83Nx93MiNIRXSpjpqTjuL7luFsYa2PZuHFj5zN3wN1xd2prazntgNMoGlLU+UJ9KNVxYxivVb/G5S9dzmkTT+ODkz7IkLz235OxAO8jGx6hvrm+3fR45+59Lsu3L2dV1SrW1Lbv6FW6ToFeERFJaebEtoHeIfl57DG2fe46yV7JUjf0Jj1H/O3K8fkphxTk8ZXjM39L9ZiyoUwZXcKqLTVtxh+lQK+IpFFRYT57ji3j9Y1VLeOSfd/KwJSYp34wp2644IILMl2EPtHbAGlxQTF1jXU8sO4B9h22LweOOrBl2htVb/CfLf+hwArYd8q+A6JFZrqC9Ms2LuOmNTfx8Skf59BR7QPYk4onMWHoBCYWT+SHx/4wpzrM6ihYPmPsDADGjBkDz6Zex46GHZQXJr9zbt3Odfz49R/z0V0+yhF7HUFZWVlayt0bqY6byvpKfvDMD/jj8j/yxzV/5E9r/kQzHadyOHj4wTxX8VzK6V854istr/f/9f49Kq8ECvSKiEhKMxNyDDrOX19cN2BbUEn3DSsqpLgwj9qG1h9nr2+o4sC4XLbdMb68iJLCPGoa2v7Y++S7dk+aJiITDpo8sk2g14DVW6o5ZGr/d3QhIrlrWFHbv1rJOo+TgWnK6LYXta/96yvkmQ3K3z+33nprpouQUR0FSBeuX8iTK55kr8K9OH/h+VQ0JnRW5o2c//j5WdcSuqOA5sLmhayvW8/3X/s+BVZAoze2m294wXDu+8B9/d75XF+L/xwXLFjAnDlzur2Oi56/iNsOvo2ygrKUHY59d+V3WXjkwl6UtO8NGzKMeUfO45S9T+Gqf1/FqqpVKec9ePjBfObAz3DY5MM4+vdHD4r0L5mmQK+IiKS0rqLtn9KGJufr94fOAQbjn51c9MCiNexsbBuU/dZDSxhSkNejz/jBxWvbrQ9gyuiB05ItP6FhjQPfeGAJeXk922cRkUQPLFrDi2+3/QN/9/+tZvauI/Q9kwVWb61uM7ylul6/f6SdQ8YfwiHjD6G2tpaKJcnzryYLag10HQWmG5sb2Wv0Xty8+GZqm5JfvKporMi5IG+67Fe+H801zVTnV6fM2dvgDX2W0zndDhp3EPefdj8H/+bglPPcfurtLa3a05lqRFJToFdERFK66+n2V2drG5q44dFl+qOTI254dBnubcf15jO+4dFlbXJSxtz8+HLOPmxKD0uZXk+8vrndOB3XIpJONzy6jMaEL8O6xmZ9z2SJ3z37drtxOk9IKsXFA+didl8ryCvgY/t9jLm7z+V9970v08UZkDoKUv7q5F9RX1fP1q1bM1CyvjEkv+Ogfk9Sl2RbK/iBRoFeERFJad32nUnHr9Xtpzkj1WfZ08843evrC5sr65KOH0hlFJHslg3fhZLahh36/SPSkXGl4zJdhAGrsyBlQUkBJSUDI52Z5KbsaA8uIiIZMTFFxzGpxkv2SfdnnA3HTDaUUUSym75nsps+v1YXXnhhy0NERAa+nA70mtl4M7vRzJab2U4z22Bmfzaz92a6bCIi2eDyudMoLsxvM664MJ/L507LUIkk3dL9GWfDMZMNZRSR7Kbvmeymz6/Vbbfd1vIQEUkmVe5c5dTNjJxN3WBms4DHgdiRtQMYA7wfOMnMrnD36zJVPhGRbBDLQ3fDo8tYu72WiSOKuXzuNOWnyyHp/oyz4ZjJhjKKSHbT90x20+cn3TUYO48ajPucTrn0/imn7sCSk4FeMysGHiIEeRcB57r7EjMrB64CvgR818yed/f5GSyqiMiAd9qBk/THJsel+zPOhmMmG8ooItlN3zPZTZ+fdMdgDHQNxn1OJ71/0ldyNXXDRcAUoAo42d2XALj7Dnf/MvAAYMD3MlZCERERERERERERkTTJ1UDvOdHz3e6+Jsn0G6Lng8xs8CVaEhERERERERERkZySc4FeMxsGHBwNPppitqeBiui1OmYTERERERERERGRrJZzgV5gBiEtA8CSZDO4ezOwLBqc2R+FEhEREREREREREekruRjonRD3em0H88WmTehgHhEREREREREREZEBryDTBegDpXGvazuYryZ6Lks20cwuBC4EGDduHAsWLEhL4UTiVVVV6dgS6YTqiUjnVE9EOqd6ItK5juqJ6o9IoPOJDGS5GOhNC3e/FbgV4JBDDvE5c+ZktkCSkxYsWICOLZGOqZ6IdE71RKRzqicineuonqj+iAQ6n8hAlouB3uq418VAZYr5SqLnqs5W+Nxzz202s1W9LZhIEmOAzZkuhMgAp3oi0jnVE5HOqZ6IdC5lPTGzZKNFBiOdTyTTpqSakIuB3vi8vBNp7XQt0cToeV1nK3T3sb0tlEgyZrbQ3Q/JdDlEBjLVE5HOqZ6IdE71RKRzqicinVM9kYEsFztjexXw6PW+yWYwszxgWjS4tD8KJSIiIiIiIiIiItJXci7Q6+6VwMJo8NgUs70DGB69/kefF0pERERERERERESkD+VcoDdyd/R8jplNSDL9y9Hzc+6eKrWDSH+4NdMFEMkCqicinVM9Eemc6olI51RPRDqneiIDlrl753NlGTMrBl4hJCd+HjjX3Zea2TDgSuDyaNa57j4/Q8UUERERERERERERSYucDPQCmNlsQlqG0dGoHUAZoRWzA1e4+3UZKp6IiIiIiIiIiIhI2uRsoBfAzMYDXwfeD0wiBHufAX7k7srNKyIiIiIiIiIiIjkhV3P0AuDu6939Unff092L3H0Xd3+/grySaWb2ATP7i5mtM7MGM6s0s8Vmdp2Zjetk2Twzu9DMnjKz7dGyi8zscjMb0l/7INIfzGxSVC9eMrMdZlZlZq+b2d1mdmoHy6meyKBjZvlmttDMPHrM62R+1RPJaWY21swuMrM/mNlyM9tpZtVm9oqZ3Wxme3VhHaonkvPMbLyZ3RhXTzaY2Z/N7L2ZLptIfzCzyWZ2WXTcrzazuuj7/oXov0iyvp/ilx9iZl+J/tNXReeLp6Lzh/XXfohAjrfoFRlozCwPuBM4J250JVAC5EfDW4Hj3f3ZJMsXAg8AJ0aj6oEmoDgafhY4xt2r0l54kX5mZmcCvwSGRaNqCKl3SqPhf7j7+5Isp3oig5KZXQb8KG7U1e4+L8W8qieS88ysASiIG1UFDIkeADuBT7r7PSmWVz2RnGdms4DHUcpDGaTMbDdgFRAfkN1B+M8R+4++Dfigu/8zyfLlhDp0cDSqhnDuiZ1r/gJ8wN0b0196kfZyukWvyAB0Aa1B3h8D49y9HCgCjgdWA6OAe6KgcKJrCH82dgKfIASIS4GTCQHiQ4Fb+q74Iv3DzE4E7iEEeX8FTHf3UncvA8YAHwT+lmJx1RMZdMxsV+A7hD8qG7qwiOqJDAYFwJPAx4EJ7j6McKwfCSwm/P66Mwp0JaN6Ijkt6sT8IUKQdxGwn7sPB0YCPyAEvr5rZsdlrpQifS4WzP0rcCYwKqoHJYRzwApCnXggSg+a6DZCkHcr4fxQFi37CcL54/3A1X1YfpE21KJXpB+Z2RPAe4DH3b3drVBmNgeIXSU80N0Xx00bD6wEhgKXuvtPEpY9ldDqxIED3P3FtO+ASD+Iroq/CkwAvuvu3+jGsqonMiiZ2Z+A04BTgZ8AU0jRolf1RAYLM3uPuz+ZYtpY4GVgF+AOdz8vYbrqieS8uDtBqggX1dckTI+dW55394PbrUAkB5jZcGCqu7+QYvp0woWQImCeu18dN+1A4Plo8FR3fyhh2UsJDbxqo21sTP8eiLSlFr0i/SuWf3dRiunPxb0uTZj2QcKfjQrg1sQF3f1B4DXClfeP9K6YIhl1HiHI+zYwr5vLqp7IoGNmpxD+iP8l8Q9GCqonMiikCvJG0zbRemdIsgCW6okMBrE7De9ODPJGboieDzKzaf1UJpF+5e4VqYK80fRXgaejwcTzRez7f1mK32C3Es4jxcDpvS2rSFco0CvSv1ZGzwemmB47cdQBSxOmHR09P+nuO1MsPz96PqZHpRMZGGJ/Ou5z94ZuLqt6IoOKmZUCNxNailzSxcVUT0SCLdFzfpJpqieS08xsGK3/PR5NMdvThCAVgDpmk8Es1fkidq6YTxLuXgv8KxrUuUL6hQK9Iv3rtuj5GDP7kZntAmBmBWY2F/h1NP3b7r4tYdmZ0fOSDtYfCw7PUO+eko3MrAg4IBpcZGbTzeweM9sY9QL9ppn93MympliF6okMNt8BdiOkOVnZxWVUT0SCo6Lnl5NMUz2RXDeD1s6nkh7n7t4MLIsGZyabRyTXmVkB8K5o8OW48QZMjwa7cq5QHZJ+oUCvSD9y9z8C3yD02HwZsMHMdhCStD8CVALnuft3kyw+IXpe28EmYtPKoodItpkKFEav9yHkvDqLkMqkAdgd+DTwQpTTOpHqiQwaUV64zxNuH7++G4uqnsigF+XYPSQavD3JLKonkusmxL3uynE+oYN5RHLZZ4HxQDOtDbMAymlNt6g6JAOGAr0i/e97hB44q6PhYbTeAlIKjDGzZHUzdhKp7WDdNXGv9YdDstGIuNdfB7YBc4GyqLf0dxGCWuXAH8xsVMLyqicyKETniVsI54/PuXt9NxZXPZFBzcwm0Zp39yF3fyTJbKonkuvi+wPpynGuY1wGHTObRfj/DnCzu8enV1QdkgFJgV6RTpjZVWbW2MPHtQnrGgb8GbgL+CfwDkLAaiqhlWI5odOD3/brTor0UhrrSV7C64+5+3x3dwB3/y9wBuGK+hjgU/22kyK9lM7zCaF1yaHA79397xnYHZE+keZ6kmz9ZcADwC7AKuD8Pt4lERHJQmY2gXC+KCZ0mv7VjBZIpIsU6BXpXB6hxVRPH/F+CJwEPObuJ7v7M+5e6e6r3P0WQk+cDpxlZickLBtrAVzcQVlL4l5XdWsvRXonXfUk/rhd4u7/SNyQu78EPBYNJnYMonoiA1la6omZTQSuIaT7+UIPyqF6IgNZOn93tRHlgX+QkLJhEzDX3TenmF31RHJdddzrrhznOsZl0IjuGpxPSBv3OnBSko45VYdkQFKgV6QT7j7P3a2Hj6/F1mNm5cB50eCPU2zrCUJOUoBTEybHcvtM7KC4sWlV7l7ZrR0V6YV01RPa5rdalridJNN2SxiveiIDVhrryfcId4BcD+wws7L4B62d6wyJGxdP9UQGrDTWkzbMbAhwH6HX8+3Ace7e0XlG9URyXfxvrq4c5+v6sCwiA4aZDQceBfYDVgPvc/cNSWbdQWuwV3VIBgwFekX6z960tjRZ0cF8b0bPUxPGx/IB7dvBsrGePF/pVslEBoioZVWyH1IpF0kYVj2RwWBK9PwdQqvexMfkaPrX48bFUz2RQSXqMf0ewl1VVcCJ7r64k8VUTyTXvUrr76ikx3mUD35aNLg02TwiucTMSoG/Ee78WE8I8q5ONm+UWi72/d+Vc4XqkPQLBXpF+k9z3OvJKedq/QOf+Mf8n9Hzu6NbD5M5Nnpud7u7SBaJpWWY1sE806PnlQnjVU9EOqd6IoNGFKj6NSE9Vi1wirs/1YVFVU8kp0Wt0BdGg8emmO0dwPDotY5zyWlmVkzoT+cIYAshyPt6J4vFzhVJ61B0/nh3NKg6JP1CgV6R/rMMqIteX5BsBjM7CDgoGvy/hMn3R8uPIEkHVGZ2MiEw5oRWKyLZ6s7oeV8ze1/iRDPbn9bcvH9LmKx6IjnP3ed0dPs6oYMpgKvjxsVTPZFBwcwMuBX4CFAPnO7u/+x4qRaqJzIY3B09nxN1PJXoy9Hzc52kOhHJalF6n/uBo2lN77OkC4vGvv+nm9n7k0y/gHCxpBb4UxqKKtIpBXpF+om71xBalACcbma3mdluEK70mdmphF49Cwj5fu5IWH49cGM0eL2ZnWtm+dHyJwK3R9PucfcX+3JfRPqSu88H/h4N/trMjo3+rGNm7yTkWMwjpEC5PWFZ1RORTqieyCDyI+B8oBH4kLs/0tUFVU9kkLiFcHFwGPAXM5sJYGbDzOx6Qkt4gCsyVD6RPhd9t98NHE+4q/YEd3++46UCd18E/D4avCM6P2Bm+Wb2MeD70bQfufvG9JZcJDkLaUVEpD9EHeI8DBwZN7qa0Etn7MJLJXBGFOxKXL6QEAw+MRpVBzTR2pPns8B71SGIZDszG024FWr/aFQN4VgfFg2vJfSW/nKSZVVPZFAzs5WENEBXu/u8FPOonkhOM7PJtLZubwC2djS/u49Psg7VE8l5ZjabcEv56GjUDqCM8N/EgSvc/boMFU+kz5nZe4AnosGdQEUHs7/l7ocmLF8OPA4cHI2qIfTNMzQa/gvwAXdvTFuhRTqgFr0i/cjdq4A5wCeB+cAmwgmgFniZ0PJk/2RB3mj5BuBk4NPA04Q/HA4sBr4KHKk/G5IL3H0LcCjhuF5EyHFdACwBvgvMShbkjZZVPRHphOqJDALx/3MKgXGdPNpRPZHBwN1fAPYDfkLoFHooIT/pX4FjFeSVQSD+fFFEx+eKsYkLu/sOQl7frwEvEM4TdYTzxkWE3PAK8kq/UYteERERERERERERkSynFr0iIiIiIiIiIiIiWU6BXhEREREREREREZEsp0CviIiIiIiIiIiISJZToFdEREREREREREQkyynQKyIiIiIiIiIiIpLlFOgVERERERERERERyXIK9IqIiIiIiIiIiIhkOQV6RURERERERERERLKcAr0iIiIiGWJm88zMzeyODGz7jmjb8/p72/3FzD4R7eOCTJdFes/MVkafZ/xjaqbLlUlmdkCS92RBpsslIiIimVGQ6QKIiIiIZFoUaP14kklVwGrgCeAmd3+lP8vVE2Y2ArgMwN3nZbIsvdXB59IVu6exKAOOme0KfBY4DtgLKAY2A+uBF4EFwKPuvi5huU8AU4EH3H1xvxU4vbYB9dHrpvgJUeB3RZJlqoEK4G3gOeAx4M/u3tB3xewXDcCG6HUxUJ7BsoiIiEiGKdArIiIi0qoB2Bq9NmAMMDN6nG9mH3X3P2SqcF00AvhW9HpeB/OtA5YRgoMDVQWtQax48QGtZNMhBAArCPu4Ov1FyxwzOxn4LTAsbvR2wmc/ATiQECC/kSjoH+cTwFHASmBxHxazL53u7gu6MF98QHgIMB6YCBwGfAZYb2aXuvvv+6SU/cDdlxD2KxbEvz2jBRIREZGMUuoGERERkVb/dffx0WMcUAScQAiKDQFuN7OxmSxgurj71919urvfnOmypOLul8Z9Hi0P4NK4edpNjx5vufufon38WAZ3I63MbA/g94Qg73PA+4ESdx/p7iWE1rqfBP4ONGeqnAPE6XHHwyigENgP+CKwihAg/V0upy8RERGRwUWBXhEREZEU3L3B3R8BzolGlQIfzGCRRC4kXIBYD8xx97+6e21soruvcvfb3f044IpMFXIgcvdmd1/i7j8iBHz/HE36lpmdmMGiiYiIiKSFAr0iIiIinXuKkK8XQhqHdsxsiJl9zsz+ZWZbzazOzFaZ2a/MbEZ3N2hmu5rZl83sETN73cxqzGyHmS0ys6ujXLyJyywgLj9pkk6a5sVNa9cZm5mdE41bb2b5HZTtndF8DWY2Jsn0/aL9XmFmO81su5n9x8w+bWaF3X0veqqjztjiOvaaY2YTzOwXZvaWmdWa2Stm9gUzy4ub/8zos90efQ5/NbP9Otn+WDP7npm9ZGZVZlZtZi+b2bVmNqqHu7V/9PyEu1d1NKO774wryyfMzAlpGyC0To8/NlYmKX+3j+n448rMiqJj9dXofd1oZveY2T492/X0id67j9BaX76dOI+ZjTGzi83swWgfKqPPcKmZ/dDMJiZZ5mNxdShlmjwzOzqar8bMhseNH2Jml5rZf6NjrcHMNpjZC2b2UzN7Zxp2X0RERHKUcvSKiIiIdI1Fz+0CoGY2AXgYmB2NaiZ0/jQZOA8428zOcff7u7G9H9PaerieEGgeARwQPc4xsznu/nbcMlsJOXdjwdfE/LUdBgaBB4AaYBzwXmB+ivnOjp7nu3ubHL9m9jlCbthYkLQKKAOOiB4fNrOT3L2mk7L0l92Bewi38e8g3N4/HfghsAdwiZldB3yVkPe3hpA24UTgCDM7zN1fT1ypmR0JPAjEArr1hONi3+hxrpkd6+7LeljuSd2cv5ZwPMRSGOyIxsVsip85Dcf0UOCfwOGEfd8JjAXOAk4xsxPc/clu7kNauXuVmd1IqGsHm9m0hM/ja8CXoteNhPdsODAjenzUzN7n7i/GLfMH4CeEOnQCra2GE30yer7f3SsAosDwfFqD8U7IMz0a2AWYFb1+qkc7LCIiIjlPLXpFREREOncEIW0DwJvxE6IWqg8SAmL/iOYtcvdyQsdPPybcan+Xme3ZjW2+Anwe2AcodvfR0XrmAM8CewK3xC/g7qcDh8YNJ+at/Z+ONuju1cBD0eDZyeaJWvp+KBq8O2HaacBNhIDgV4Cx7j4MKAGOB16Pyv+jjsrRz35EaNU5292HEzp5uzKa9lkzu4KQ0/UyYHj0ue5P6ORtBHBt4grNbAohwDcK+DmwN6EDudJo2fnAbsD9HbWcTmFh9HykmX22q8u7+++i/Mb/jUYl5j9uOW7SdEx/hhCY/BhQFr23BwLPE46H35vZyC7vdd95OO71uxOmrSakv5hFax0cChwCPEoIXN9tZrGLQERpNGL14rxkGzSzcuD0aPBXcZM+Qgjy1gDnEuVejrY5Bfgc8EI3909EREQGEQV6RURERFIws0Izmwv8JhrVAPwuYbaPE4Kr/wJOcPen3L0BwN3XufsXCAHZEuALXd22u1/p7je5++vu3hyNa3D3JwhB003ACWY2ted7mFQsSPUBMytKMv1oQmvFGkILYKAlAPzjaPBMd78h1trX3evd/VFCC8ca4JNRi9GBoBk4MdYq091r3P0a4HFCK+5rgWvc/cYoEI67vwxcEC1/ipkNSVjntYQg8HXufrG7vxHlh22Olj0ZeJGQBuQD3Szvz4CN0eubgTVmdreZXWZmR5jZ0G6uL5l0HNPDgQvd/a64ZRcDc4EthGPos2koa2+9DtRFr3ePn+DuP3H377n7S+7eGI1rcvfngFOBpYTW2e9JWOdt0fP7LXnnjWcR3rsVhFbPMYdHz3e6+29iqTeiba5295+6+/d6tpsiIiIyGCjQKyIiItLqiCi35noz20C43fwRYCohIHhRQqoECEExgBtjAa0kfhs9H5uOQrr7VkLLTCO0tkynRwgpIIYT0hMkirX0fSgW+IzMIbQ6fDkK6rbj7suBpwnpw+akqby99Qt3355k/GPRcz0hjUOi/xCOj6HAXrGRZlYCnEk4XpIth7vXA/dFg906Jtx9A6HVZ6xl7jjCZ/KjqEzbosBv0lzSXZSOY3oVCS2+AaLgf6wl+hk9LmGauLsD26PBLudNdvc64O/R4LsSpi0itFwuBD6aZPFYS987ou3H7IieB8pFEBEREckyytErIiIi0qqQEDhLtBWY6+4L40dGOTUPiwZvMbOfplhv7Pb63bpTGDM7DPg0IZi7K63pI+K16xCqN9y9wczuAy4k3ErekoM1ai0au+U8MYgXCzjvbWbrO9hErOOpbr0XfeilFONjrWZXJuv0zN2bzWwz4XOJT0FwMDCEkF/1pbi7+hMVR8/dfh/c/VXgXWZ2CPB+wnt/ECF/azEh8Hu6mX3U3e9Lvab20nhMP5EQxGwzjZASYT8zGxIFvgckM5tOSJnwHsIFnzJa83XHJKuD/0tofX0ecalKok7sDidcCLgjYZmHCbmgTzWzh6LpT7j7ll7uhoiIiAwSCvSKiIiItHrC3edAS1BzOvBNQsvDX0adn22Lm38UIagHIcjWmeLOZwnM7MvA9bQGlZqAbYQWphACpkUkD/721t2EQO9JZjbM3Suj8ScQUhJsJbT8jRdrhTiU5MHyRCVpKGc6rEsxvqmT6fHzFMaNi70PRjffBzN7luSB0/9Jll85uvDQcvHBzA4ktMb9LOFz+LWZ/cfdO9qHROk6ptd0sExsWj4hSJ7YaWC/ifLrjogGtyZMOwu4k9bPt5nQOVos1UMZof4lq4N3A/8D7G9mB0fpHqC1E7bH3H11/ALu/oSZXQVcRUjvcXJUjleBvwK3JOv4T0RERCRGqRtEREREknD3Ond/gdDx2KOEDpluSZgt/rfUge5unT26sm0z2xf4PiFYeDMhD+hQdx8V6zyL1lv/u7TObnoSeJsQSD49bnwsbcN9SW7pj70XD3blfXD3eX1Q7oEg9j5UdPF9mBO37FhCcDjxUdaVDbv7Ine/jNbUACWEfLA9KT+k8ZgewPYmBMUhrqPFKLfubYQg7+8IHbAVufvIuDoYa6nb7j1w9wrgD9HgedE6CwidrEHbTtjil/sOoQPGrxO+d3YQLjh9CVhqZh/r2W6KiIjIYKBAr4iIiEgHotvPP09ovXmmmR0VN3kLra06J6dxsx8k/E571N0vcfel7t6UME9XWov2SLTP90aDZwOYWRlRC0OS5F6ltVVmOt+HbBR7H8rNbHiHcyZw96lpCorfDdRGr/fp5rLpOqY7SikSmxZrpZ5JJ8S9/lfC+DJCh2sfcffnklzc6KwO/m/0/JHoDoETo2W2EteRYSJ3X+Hu17n78YQW1kcTLr4UAD8zs1062a6IiIgMUgr0ioiIiHTC3V8jtOoDuDZufAOtt86fkLhcL+waPS9KNtHMSgl5PpNpjpuvN60tY8Hc90aBpVMJt+m/TQg6JXoqep5lZpN6sd1stxBoJLTyPD4TBXD3ZloDvYn5b2PHR9JjI43H9FFdmPZyJvPzRhcvLosGn43qeUysDr4YvZ+JyxpwTEfrd/d/A68S0lOcRmtL67ujztw65e5N7r6AkIu5gZAm4pCuLCsiIiKDjwK9IiIiIl0Ty5H6LjObEzf+juj5E2Y2u6MVmNnIjqbHqYie908x/RvAsBTTdsS9HtHF7bXj7osIQaoC4ExCx2wA96boZOsfwFuEvKs3dLTubrwPWSfKZ/zHaPDbZpbqc8LMCqJgY5eZ2ZFmVtTJPLGWoACLEybHjo8RHazijui5N8f0VDM7O3GkmY0i5H+G1tQG/S563+8mdLDmhLy48WJ1cL8UF0wuAPbswqZirXq/CJwUvf5lijINSTY+Uk9rS+uhHcwnIiIig5gCvSIiIiJdEAU+H4sGvxk36ZfA04R8to+b2QVmVh6baGbjzewcM3sCuLSLm/t79HySmX3dzEqidY01sxsI+Tu3pCjndmBtNHhesnm6Idaq9yLg2IRxidttAD5HCJqdbWYPmNkBselmVmhmh5jZ9cCKXpZroPsa4fb8fYD/mtnxZlYIoSWome1tZl8kBNK72zrzMmClmf1PFPRt6QzNzCaY2deA30ej1tKayzlmSfR8egepJdJxTFcAt0XzFUTLzSLknR0LbAR+1rVdTo/ovZ9hZpcBL9GaiuQqd0/sXPAxwrG8H/ATMxsRraPczC4HfkqKOpjgTkKQ9jBCvt9F7r441bxmdruZzY2/QGBmU4FfEz6PWtqmmBARERFpoUCviIiISNddHz2/18wOh5YA56nAfwitKG8FtpnZFjOrAtYBvwHeQwgcdcrd5wP3R4PfBarMbCsh/+uXCYG4v3Swilgrwh+YWZWZrYwel3VtN1vEgrr7E4JUr0YB71Tlfgg4nxDYOhVYZGY1ZraFEKB6Frgc6Fbu2mzj7isJaRvWEgKFDwPVZrYZ2Am8BvyA0CK0S8dEnAZCntcvEQJ+1Wa2zcx2Rtv7HqG19xrg/VEL43h3ET6fI4HNZrYmOjb+HVf+dBzTPwdejuarMrMK4AVCYLsGONPd+zo/7/1mtj56bCW8d0sJnahNJezHh9z9msQF3X0Z8ONo8HOE/d9GyCl8PaEF+y86K4C7bwIeihuVtBO2SBHwCeARoCL6XKsJF0Y+TGjRe5G7b+5suyIiIjI4KdArIiIi0kXu/nda8+ZeGTd+IyHv6DnA34BNtKZWeJXQqu9DwHXd2NyHCS1DXyEEqIwQePu4u3+qk2W/DXwVeDFabkr0GNGN7ePuy4Fn4kYlbc2bsMztwDRCkGwJIThVTmj9uAD4VjQ9p7n7s8B0wufwX6CK8P7XEHLg/gQ4yt2f6OaqzwWOI6QS+RehZWxpNG0doTX4pcD0ZEF5d3+V0Dr7EUKr2/GEY2PXhPl6e0zXAXMIx+IqYEi0jnuBg9w9WZ7ndBtJCIqPIwRRNxEuNvwCOB2Y7O4p00e4+xcJaSYWEfYnP3p9GSENQ2MXyxG7aFMH/LaD+b4GfIXw2bxJeM/ygeXA7YT37a4ublNEREQGIUueYk1ERERERKR7zOwO4OPA1e4+L83rXkkISh8ddVCWFczsNuBTwO/c/aw+3M4nCAHhJ9x9Tl9tR0RERAYutegVERERERHpA1Ee5Fhw99ZMlkVERERyX0GmCyAiIiIiItIN/zSz2Ovdo5zIA46ZDQF+CJQBL7r7432wjQNoTScjIiIig5wCvSIiIiIikg02EXLtxmvKREE6YmZnEHIojyHkT3ZC53l9oYHQSWO8rX20LRERERngFOgVEREREZEBz90PzXQZuqiMkEu4jtDa9tvu/lhfbMjdlxA61BMRERFRZ2wiIiIiIiIiIiIi2U6dsYmIiIiIiIiIiIhkOQV6RURERERERERERLKcAr0iIiIiIiIiIiIiWU6BXhEREREREREREZEsp0CviIiIiIiIiIiISJZToFdEREREREREREQky/0/Tfk1EeRJRwUAAAAASUVORK5CYII=\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tft_vis.display_target_trajectory(signal_history=data['data_sets']['validation']['historical_ts_numeric'][...,target_var_index],\n",
" signal_future=validation_outputs['target'],\n",
" model_preds=validation_outputs['predicted_quantiles'],\n",
" observation_index=chosen_idx,\n",
" model_quantiles=model_quantiles,\n",
" unit='Days',\n",
" transformation=transform_back)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Selection Weights\n",
"The temporal fusion transformer model has an interntal mechanism for variable selection. Each input channel has a separate dedicated mechanism - historical temporal data, static descriptors data, known future inputs data. In the following section we'll describe them visually."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Although the input to the model required us to split between the categorical variables and the numeric variables for each input channel, after the inputs are transformed upon feeding them to the model, the entire set of variables composing a single input channel (historical_ts / future_ts / static) are treated as one block, and the variable selection mechanism acts on them without any distinction. \n",
"\n",
"__*Note*__: in the suggested implementation, the numeric inputs are stacked first, before combining the categorical inputs (on each input channel separately). Hence, we conclude the complete set of input variables for each input channel as follows:"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"static_feats = feature_map['static_feats_numeric'] + feature_map['static_feats_categorical']\n",
"historical_feats = feature_map['historical_ts_numeric'] + feature_map['historical_ts_categorical']\n",
"future_feats = feature_map['future_ts_numeric'] + feature_map['future_ts_categorical']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The description of selection weights can be done either on a data subset level, or on a sample-level. For performing data-set level description, we'll have to perform some-kind of reduction/aggregation. Hence, we use a configurable list of precentiles, for describing the distribution of selection weights for each variable on each input channel:"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# the precentiles to compute for describing the distribution of the weights\n",
"weights_prctile = [10,50,90]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On the following we use the functionality implemented under ``tft_torch.visualize``, for performing the aggregation and ordering of the attributes, for each input channel separately. \n",
"For that matter, we supply a mapping specifying the name of output key associated which each set of attributes:"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Static Weights\n",
"=========\n"
]
},
{
"data": {
"text/html": [
"\n",
"
\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mapping = {\n",
" 'Static Weights': {'arr_key': 'static_weights', 'feat_names':static_feats},\n",
" 'Historical Weights': {'arr_key': 'historical_selection_weights', 'feat_names':historical_feats},\n",
" 'Future Weights': {'arr_key': 'future_selection_weights', 'feat_names':future_feats},\n",
"}\n",
"tft_vis.display_selection_weights_stats(outputs_dict=validation_outputs,\n",
" prctiles=weights_prctile,\n",
" mapping=mapping,\n",
" sort_by=50)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The tables above display the specified percentiles of the weights distribution for each feature, on each input channel. The color of each cell is highlighted according to the corresponding value (brighter color implies higher value). In addition, every table is sorted (in descending order) according to configured percentile. Note that for the temporal inputs (historical_ts, future_ts), the time-series of weights gets \"flattened\", so that we can aggregate along time-steps and samples likewise. Generally, the selection weights for the temporal data, are generated for each time-step separately. Here, we look at all the time-steps altogether, but this can be another aspect to examine."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Some interesting findings that are easily seen using these tables:\n",
"\n",
"- For the static weights, the attributes that seem to have the highest weights (thus considered more important), are the ones associated with the identity of the instance - *store_nbr* , *item_class* , *item_nbr* .\n",
"- The most important variable, in terms of selection weight, among the historical features, is the variable we aim at predicting into the future - *log_sales* - which makes sense, of course.\n",
"- Among the known (futuristic) inputs, we see that the knowledge about the next weekdays and the upcoming promotions is of high importance to the model."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As noted earlier, we can examine the selection weights from the point of view of an invdividual sample.\n",
"Using the functionality implemented on ``tft_torch.visualize`` we call ``display_sample_wise_selection_stats()`` function, each time for another input channel, specying the observation index for which we want to observe the selection weights distribution.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- For each of the input channel we get an ordered barplot of the selection weights. Note that for the selection weights of the temporal attributes, there's a step of flattening and averaging. For the barplot we also allow specifying the ``top_n`` argument, for keeping only the ``top_n`` ranked attributes on this plot.\n",
"Note that the selection weights on the barplot, for the static variables (which do not require flattening and aggregation) sum up to 1.0 (unless truncated using ``top_n``).\n",
"- For the selection weights of the temporal input channel, the same function will also provide some kind of \"*spectrogram*\" indicating the distribution of selection weights along time. This visualization can be configured to rank the attributes separately on each time-step, by setting ``rank_stepwise=True``."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAABXoAAAKqCAYAAACEr+agAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAACTMElEQVR4nOzdeZxcVZ3//9cnCUsgCbshgBBchkVABFREgaBDXAARZNSBUeMoIC6gghuog44LXxkEnXEB/SHigMio4IIKigQQkB0FRFQkoOxrFiBAJ5/fH/cWXelUVdfSnaoLr+fjcR+13HPP/XT16Ur63afOjcxEkiRJkiRJklRdE/pdgCRJkiRJkiSpNwa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkaaBExCkRkRGR/a5FeqaIiHnlz93cftcyViJibvk1zet3Lc9UETGz9n4eEUeP87n8fkuSnvEMeiVJqpCIWDki9o+IH0bErRGxKCKGIuLhiPhjRJwdEZ+IiJdHxKR+11tVETGnLpxoZzu73zWrmiJi+4j474i4JiIeLH+eH4mI28vg6oSIeFNErN3vWtU/EbFn3fvN8W20n9dh+7+XbR+JiJXHpmpJkrSiGfRKklQREbEN8HvgNGBfYCawOjARWAPYAtgb+E/gt8B+DfpYYbOr+nlOFSJiVt1rP6ff9WhYRKwSEScDVwHvA14ErEXx87wa8GxgV+Aw4PvA6X0qdWA8w8fzxcCS8v6sVg0jYhNgk7qnRmv/XGCj8uGlmflEdyU+PUTE0XXjbGa/65EkqRPO9JEkqQLKX9wvAGqz+n4HfBe4HlgITAH+CdgJ2BOY3ocyx0RmzgHm9LmMel8HvjZKmwUrohA9rZxO8QcbgPuBk4BLgLsp/o++AbA98Dpgu34UWHWZOavfNYyVzJwfEddRjIltImKtzHyoSfNdy9slFH842CYi1szMh0dpDzB3DMp9SmbOA2Is+5QkSc0Z9EqSVA1fYDjkPSYzP96gzW+BkyNiAkXYe8eKKu5p7t7MvKHfRejpIyJmMxzy3gDslpn3N2h6NvDJiNgMeMkKKk+Day5F0DsB2AX4cZN2s8rbc4BXUvwhcBfgJ6O0r51DkiRVlEs3SJI04CJiIsWSDAD3Ap9o1T4zl2bmTzLz6nEvTlI39q27f2STkPcpmXlzZn53nGvS4Jtbd3/XZo3q9p0PXNpB+0eBK7qqTJIkDQSDXkmSBt96FGt2AtyamUtaNW4mIhK4te6p/2hwUbF5I46JiNg5Iv5fRFwcEXdHxBPlReD+EhGnRsTOY3zOU2r72viadoyIb0TEjeUF6Z6MiPsi4qKI+Ew5E7JvImKniPhmRNwcEQsi4rHyInqnRcSsUY6dFBGviYgvR8TvIuL+8utbUF5478Ry3eZGx84sX78L6p7+doPXfu6I42rPnzJKbS3XsBz5PYyI1SPiIxFxefl1ZESc0OC4TSLimIi4KiIeKMfaXRHx84h4e4xygcGIeEFE/E9E/KF8nWrj4aaI+HFEvC8iNmzVxwoys+7+X8aq04h4bUR8NyJuieKiWo9ExJ8j4lsR8aIxOseEiHhzRPwgIm4rx/SCiLghIr4SEc9rs58pEXFYRJwbEXdGxOMR8Wj5s3JaRLwlIlYp23Y7nuc2eo9pUMvUcnz+thwvT0TxXveriHh3RKzU4tjl1iCPiG0j4jvl6/N4RNwbET+JiFZhaztGXac3IjYCnlM+vKjcWrWfCWxcPrwkM59s0GbliDgwIs6JiDvKr+mhKC4g+IWImNGs4EavT4u2b4iIX5Sv1+Io3itPrr3PjXxfGU35ff1ERPw+IhaW21UR8aFocMG5KC/CCfxH3dO3NhhnR484bqXy9akfy4vK7/+VEXF8RLymnZolSeqVSzdIkjT4Hq+7/7yIWKnRL+Pj5DCg0RXbVwKeV25vjYivA+/LzKUroqiImAJ8C3hzg93rAjuX2+uBbVdETfUiYjLwTeCABrtnltv+EXEqcFBmPt6g3X9RvP4jTaW48N4WwIER8YnM/PxY1D0eImJT4Fzg+aO0OwL4HDAygFkfeG25vT8i9s7M5ZYliYj3AF+hWJO03rrltjnFeFgT+GzHX8jYqv9+bwn8qZfOImJt4Axg9wa7n19u74yIYyhmELcVlDU4zybAj1h+zeBVgReU2yER8cHM/J8W/bwWOJXi+zLSP5Xb/sA+FMtXjJuI2LE8x8h1zaeX2z8DH4iIPTLzljb6Owj4H4r3yJr1gL2APSPiPZn5jW5qHbFO7wuj8bq7s8rbh4E/ULxfAGwbEWtk5vwm7aHBsg0RsS3wQ4bD45qVKS4g+CKKn8u3Z+YP2/9qljnHROAU4N9G7JoJvIPivfJdHfb5fODnFP9G1du+3F4fEa9u8t7byXmeBZwHvHDErpUpLpa6MbAD8H783VuStAL4j40kSQMuMx8qZ6TNBNYBvhoRh2bm4g672priAk/nlo8bXWRs5NXWJ1FcKOonFGsA/wV4hCIA2Zril9dnA4cAf6dYS7jXc7ZUzsQ6l+LCcwC3lf1eDsynWMt4O4pQb0onfY+FMrT4GcXamFB8fPo0ipnNC4HNgIMoPi79NmApRZgx0iTgHxQh1OXA34DFFK/nDsD7KMbD5yLi1sz8Xt2xd1C89i8GTi6f+wTLr+n5SJdfZifOAjaluNjYWRTLj2xEXSBbzpCrzaK7meL7eXPZdgPgjRSv1fbALyNix8x8pO74rRgOeR8AvkEx+/E+isBtY4rX4vXj9DV26hqGazk2Iq7PzK5m9pZ/9LiIImRNiiD2bIrx9iSwDfBeij94fIxiDH26i/NsAFwGzCj7/S7wK2AexcW2dqD4w8Rzgf+OiIWZ+Z0G/byeYhxMoBj7Z5Y131o+9xyK8PGNdYeNy3iOiM2BX1MEclBcIO904C6K99sDgddQ/MxeGBEvzMwHWnQ5G3gpcBNwAkXQOonijxQfoQj/vhwRv8nMP3dSa525LLtO78h1d2uzhi/OzKURcQXF93xVij9+/axJ+1rfT4mIrSl+jqZQLOtQu2DgbcAqwCsovufrA9+PiNmZ+ZsuvqZjGQ557wK+SHHB0aB4n/8IxR/2/thmf6tRfJ0zgGMogtj5FH9U+STFHxJ2BT4OHF133NnAVcB7KP5NA3g1cOeI/u+tu//fDIe85wH/S/EzsZDi36ItKf4tmN1m7ZIk9SYz3dzc3Nzc3AZ8o/hlOuu2+ylmQB1IEWqu3GY/M+v6OLqN9hsDq7TYvwpF2JMUv0hPHYNznlJr32T/5+r6+ykwuVX9Xb7ec+rO8TVgqxbbpiOO/Xh53BPA3i3O8aW6c7yiwf7nABNbHL8mRZCUwC3AhAZtZtWdY04bX3et7SmjtDu6ru3MVt9Dio+a79Gir5dTBH5J8YeC5b6Ost0+de0+MWLfZ+rO98JRal+7mzExlhuwIbCoruah8ufo4xSzctftoK8Tyz4eBl7WpM0kikA1KULaTRu0mVfun9ukj3PL/bcDmzVpszrFH4QSeJAR7wcUM3jnl/sfBWa3+Lomj3wduhjPc8u285rsv7iuv3c3aXNsq58Lln1/S+CXNHjPpPhDRa3Nl3oYO3vW9XNcg/1/Lvcd3uB1OLZB+7+V+xYBK9U9P5EiWE3g98D6Tep5FsUfZbK8nTBif/3rc3SD47emeI+ovY9Nb/Lzcnv96zzK97v279E2DdqsSxHUZnm73Hsso7y/1bVbleJ9PoEfjfJ9W6fb77mbm5ubm1snm2v0SpJUDV9h2Zmw6wBvp5hhdTWwIIo1dI+IiPXG6qSZeXu2+Ghrue/w8uE0io85j5uImEYxixiK2a7/mpmPtajv9jE47SHA9S22b9fVtxrDr8eXM3PkjMN6H6OYvQZFYL+MzPxbtliPOYuPbNcuzPcclv/o8KA4NTPPabH/KIqZe1dQLCvQcPmPzDyLYuYnLP96rV/ePpSZv29VTGY+OHrJ4yuLpSfeSBHOQhGq/TPweYpZgfdFsbbuVyPiJc36Kddjrc0GPyozL2tyviGKcfwEReg7p5N6yxpqMxIPycybm5znEeDd5cO1gP1GNHk/xfsEFN/r85qdMzMfy1EuUteLiNiOYkYqwC+z+XIKH6eYoQvFEgLPatHtYuDtTd4z/xe4u7y/a4P97Wq6Tm8567q2RMpFdbsartMbERtTzLYHuDSXXRLojRTLwyRwQGbeTQOZeS/D73m1mbKdeDfD1405NDPvaXCOO4APddjvpzLzDw36up/h9+z1KGbcdmtthpfomNuqYbaeCS5J0pgx6JUkqQKy8F6KX6J/zPLLHdQ+Rnss8LeIeD/jIIqLam0SEVtGxFblR+br/z8xJhd8amE3htec/EZmLhrn83VqF4oQHoqPgDeVmU8Al5YPXz5axxExLSI2jeKCY7XXfqiuyXi/9t3632Y7ymUHauvKnpGZOUpfc8vbjcuQs+Yf5e1aEbFvV1WuYJl5LkWQdizLfzQcisDuPcDlEfGjch3ekfZkOGj6XoP99ed7gOIPE9DGeBuh9prOp1j3tNV5bqBYPqPReWrLVSygmIncT/UfpW9aSxmSf6t8uBJNLmpW+nWjoLLsZynFH+Vg+fVu25bFGrvXlQ+3jYg16nbXQtaFFMuD1NSC3heVfywb2R6WvdAdDH/Pry+/p63Mrbvf6diq/XHwHuAXLdqdDTzUQb+ntdh3Zd39rr8XFJ+sqS2h9JaIWL1VY0mSVgTX6JUkqUIy8yLgovIXypdSrFm5HcUv1xuWzaYAX4mIqTkGF+kqZ4l9EHgDxfqb0aJ5o4srjaXt6+6PDCbGy6cz8+g229bPvrwmotVLtYyGV62PiH+ieO33oFgLuZXxfu271WqG7XYM/3/0SxHxpQ76ncFwwHsaxczLVYEfRsTFFGuXXgJc12rWdzvKC8o1C3GeyC7XWy1nSX4kIj5KscbujhSvyUsogvvaH1H2ATaNiJdn5qN1XdSPtwd6HW8t1M6zBrC0m/NExCSK9YIBLu/1ezIGtq6733AmdJ1L6+5vQ7EMRiOjXVSvNpt8WstWo5vLsuv0/rR8vhbcXjLi0wCXUSzZsRLFHwR/PqJ9rc96te/5NhEx2h9g6rU9tiJiFYZnIF/VbDY/FIF7eSG63dro+v5RZoPXz+rv+nuRmU9ExHcpPmHwMuC2iPgBxbrsV2Tmbd32LUlSt5zRK0lSBWXmI5n5m8z8f5n55szciOKX9qvqmh0dEZv0cp6IeCVFeHEExdXLR0t4JvdyvjbUL0vRaBZkv7X6WHcrq418IiIOAG6g+GjzaCEvjP9r361Ws/C6fb2g7jXLzFuAvRkeEztTzJS9FHg4Ii6MiHdHRLev0bdpvnRH0+UH2lXO2L8hM7+Vme/JzB0ovudfofjoPBQXUztsxKFjNt5GMRbnWYfh3z0G4We3NvN+KcteXKuR+mUL1mnaavSLwdWCzF5/B5tbd39Wg/sX1jcul9S4pkX7R1h2liusmLG1FsP/poz2PYBi1m872v0+QN1FIbv0AYpPLSTF2DiY4g8B8yLi7xHxjYgY1E9bSJKehpzRK0nS00RmXhQRr6KYQTmTYvbWG4Avd9Nf+VHxMymWShgCvkrx8dk/Aw/U1qGMiAkMrxnZ9lS/p6n6/1vNZngN3o5ExPOBkym+h49QXLjtl8Bfgfl1r/1zKC5gBAP62rdaZ5hlX6+jKGbhtuvWEec5LyKeSzHmX0cxc3FTYGWKWY+7AB+NiL0brd05aDLzTuCwiBhieH3SN1FcsK6m9volxRrN7c68HLn0y2hq57kDeE0Hx40WuKk7tXV6J1LOyo2I6cBm5f6LGhxzEcWnQGrtN6T4hAYUM4CHRrSvfc+vBP69g9o6WV6h8soZ9m+NiM8Db6aYcfxiij+8bUQR/B4cEcdnZqfrDEuS1DGDXkmSnkYyc0FEnEYRmkFxcZxu7cfw7LX3ZuZJTdqt1cM5OnVf3f0NgHkr8NztqK/v4TbWtmzmHRQBJcC+LS5aNdav/VKK2YajzTgcq7Uo61+vJ3t4vQDIzMXAGeVGRMygWAP4QIrgdyZwVkRsPuLCU6P1O6uXunr0dYaD3pE/z7XXL4C7M/M+xsd9FCHiGsCNbayl3MgDDI+vDcawtm7V1hGeQDF7tdVs0fXr7vf9olqZOb9cxmB7htfprS3D8CjLz86FIuj9MLBdREyl9bINUHzPNwJW7/XnsoWHKP44EbQ3g7iXTwCMq8y8CTia4pM0KwE7UCy5cjDF8hAfjIgbM/P/61+VkqRnApdukCTp6ecfdfdHBjKdBDT1a1ie0aLdDqP0000o1Ez90hTtrNW4ol1dd3+XHvqpvfYPtgh5Yexf+4Xl7WgB8hYd9tvMtQx/jLqX16uhzLwrM08t+z6nfPo5LLu27aBr9fM8VuNtNLXzTKFYQ7hj5YzR2nrNL+1yGY2xfC+pn9W94yhtd6q732rN6RVpbnk7kWKpklnl48ua/BHjtxQ/a5Mo1nSfVbev0Xrnte/55hGxXoP9PSs/mfCX8uH20WLx53KN523Ho44GehpnmflkZl6WmR9h+GJzAG/prSxJkkZn0CtJ0tNPffh3y4h99RdAWmWUfuo/+dNq3cX3jNJPJ+cczQXAgvL+wRExpcf+xtr5DNf33ojodC3Umtprv2q5NMZyyucPHqWfTl/7v5W3TUOXiFifZcOLrmXmgwyvJ/raiHjBWPTb4DzJsmvpjktw1a5WgVYDrX6ef8LwsikfajZWxsCP6u5/uId+flzeTgMO6uL4sXwvqR8PTWuJiInAO8uHT9B49ms/zK27P4vhGboXLtcSyMyHKdaUHtl+Ecv+Aa2m9j2fABzedZWj+3V5uz6tlwV5PbD2ONZRb8zGWWZeyfByFn1935EkPTMY9EqSNOAiYkpEXBER+5Szmlq1fS3w9vLhEoaDlZoHgcfL+6Mt6/DnuvtzmpzvUIpfwFvp5JwtZeZCigtUQXGxqtNbzQyMiHYuYjZmyvr+q3y4KfC9iGi5zEFE7B4RLx/xdO21X41iXdZGjgVGu8hP/UWv2nnt55a3M4C3jtwZEasAp9B7yFbvaIoZdBMpllV4TqvGEbFFRLxlxHP7RkTTi2SVwersuqf+1qztCvKNiPjkaDMlI2Jd4L/rnvph/f7M/BvwnfLhTsDXWr1HRMSEiNgvIrbspNjMvAj4TfnwzRHxiVHqXjki3lmuG1vvf4CHy/tfiIjdW/Qxufz663U6npvKzGsp1roFeF1EvKtJ088Btdfr9HFcHqNTtXV6oVgioFZjo/V5GbFvP4Zfv0br8wKcDtxc3v9wRLy9QZunlP9OdfPHhm8wPKv/K41+JsolWL7UYb+9aGucRcRzyguWNhURL2H4ExL9ft+RJD0DuEavJEnV8GKKGVb3RcRPgMsoLsz1MMVFX/4J2JviF/7abMEvlkHQUzJzKCIuo5jRtVdEfIDil/9HyyZPZmZt1uD3gc8DqwKfjYiZFBdju5dirdO3lef8LcX6pw11eM52/CfwSopgay/gjxHxdeB3FLNp16L4iO/eFGuKrugrnn+e4qPRr6YIwW+OiJOAS4H7Kb5fz6b4nu5DcUGkA4FL6vo4FXg/xffy5PKq7b+imBm2GcVM3l0Y/bX/R0TMo/h+vTMibqT4SHYteH80M2+vO+RE4H0UF4E7qby42S8oAqUXAodRBEqXAS/r7GVpWuNFEfFJ4LPA84HrI+IUihmX/6CYmDCd4nu6B8XH7E9j2eVEDqUI/X9FMUPwRoq1VFejWKrhHQwv9XHRAFyMbR2KWaSfiohfUwTsv6cYH0sp1rDdmWImaS3A/gtwXIO+DqNYTmFbinGxW0R8i2Kd1ocp1lPelOJ126fse3fgjx3W/G/A5RRj9z8j4g0Uof91FLNCp1K8D+1EcUG8tSm+n0+tfZuZD5SB4VkUPwe/jIjvU7y3zaMY7zMp3iveRPFzcXbd8Z2O59EcWB6/OvDNiNgV+B5wN7BJuf+1Zds7gCM66HtcjVint/bHkccpvkfNXETxvvLcuufmNul/KCLeSPG+tAZwSkS8jeL1uZFi1uuaFMu47ALsSbG0x1cYDm7b+Tquj4gvAx8EngdcGxFfLL+OoHif+SjF+/q1rJj3898yvHbw58s/FN3CcLB+f2beD2wMnB8Rt1D8UfUK4HZgMcV6wrsCh5THJMUFTSVJGl+Z6ebm5ubm5jbAG0XQeifFL4rtbI8D/9Giv1cBQ02OnTei7b8BT7Y41zUUIVzt8SljcM5TavtafA1TKGY3jvZaXNflaz6nro+juzh+ZYpf6pe0UeNS4E0N+vjYKMf9iiJ0bVnniK9l5Da3QftDypoatX+CIkw8uu65mQ36GPV72OCYgygCw3bG+FdHHDu3zeN+B0wfgJ/pE1q8xo22C4ANWvQ3Dfi/NvsaAl7WoI95zcZEXZsNylraOc9i4NlN+tmDIogfrY839DKe68bFvBZf044UwW6rOv4EPLfJ8TPr2rV8r+jm52KU/v5rRJ0XjtL+WQ2+th1HOWZzij9CtPM9XwBM7PT1oZjN/91RxtK/UfwBLIHHmvQz6ve7bDerru85Tdp8u0U9RzfoZ7SfhXeP9/uKm5ubm5tbZrp0gyRJgy4zFwMbUgQSR1Ksy3kzxYWzlgCPAH+nmAH5ceD5mfnpFv2dTzHj9AyKcGdxi7b/SzGj6vvAXRSh730Us7wOowgJWl2tvuNztiMzF2XmGylmTH2bYnbzI2V991KsU/kfFDMYV7jMfCIz3wu8gCKMuYoi2Kp9v24Bfkqx9uXzMvPMBn0cQ7EW7s8oZno+SRFI/ZpihupshmdFt6rlFIq1L39MMSvxiVHaf51i9utP6857B8Us2pdl5omjnbMbmXkSxSzKj1EsE3B3Wevi8vwXUHyMfsfyta33FuDfKYK0qyhmAj9eHnsbxQzSfwV2ame8jrfM/ADFzNh/B06mmH1be62fKO9fCXwN2C0zd8vMOxv3Bpm5IDP/heIic1+lWIv1IYrxtpAiqPwBxXraG2XmZV3WfWdm7kYxI/jkst8F5Xnml+c9jWJ8rp+Zf2/SzzkUs1A/QvGzeh9FAP0oxXvbd4E3MnwBvfpjT6GD8dzG1/Q7ipnHH6OYdf8Aw+8jv6b4w8c22dmnDlaUuSMet1q2gcy8l+J7VtNsfd76Y/5EMYv2jRTLOdxSHjdEMcauBf4/ip/B9TNzSZOuWp1jSWa+leL9+pcU4/9xip/dU4CXlP8WrVkeMr/Tc3ThXRQ/LxdRjIlGy1tcTDHz/j8p/v39E8VrMkQxm/5K4Bhgi8z8xviXLEkSRGb2uwZJkiRJkpqKiL9RLENyUWbu2u96JEkaRM7olSRJkiQNrPKClZuWDy/tZy2SJA0yg15JkiRJUl9ExBoR8awW+9cHvlU+TIrlHCRJUgOT+l2AJEmSJOkZa1Pg0oj4MXAuxTrNj1FcPG4XigtArlu2/Upm3tyXKiVJqgDX6JUkSZIk9UVEbEtxUbfRnAy8OzOfHN+KJEmqLoNeSZIkSVJfRMSqwD7AbGB7ipm8awOPA3cCvwVOzsxL+lakJEkVYdDbZ+uuu27OnDmz32UMrEceeYTVV1+932WowhxD6oXjR71w/KhXjiH1wvGjXjh+1CvHkHrh+Gnt6quvvj8z12u0zzV6+2zmzJlcddVV/S5jYM2dO5dZs2b1uwxVmGNIvXD8qBeOH/XKMaReOH7UC8ePeuUYUi8cP61FxG3N9k1YkYVIkiRJkiRJksaeQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFXcpH4XIEmSJEmSJI23pUuX8tBDD7Fo0SIWL17M0qVL+12SGlhjjTW46aab+l3GuJo4cSJTp05l7bXXZpVVVhmzfg16JUmSJEmS9LQ2NDTE3//+dyZNmsTaa6/NaqutxoQJE4iIfpemERYuXMjUqVP7Xca4yUyefPJJFixYwO23387GG288ZmGvQa8kSZIkSZKe1h588EFWWWUVZsyYYbirvooIVl55ZdZdd12gGJszZswYk75do1eSJEmSJElPa/Pnz2edddYx5NVAmTZtGgsXLhyz/gx6JUmSJEmS9LQ2NDTEyiuv3O8ypGWstNJKLFmyZMz6M+iVJEmSJEnS056zeTVoxnpMGvRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJEkaWKeccgoRwaxZs8a03zlz5hARHH300WPab79M6ncBkiRJkiRJ0iCY+bFz+l1CT+Yds0e/S3jGuO666zj77LOZOXMmc+bM6Xc5gDN6JUmSJEmSJA2wNdZYg80224yNN96436U85brrruPTn/40p5xySr9LeYozeiVJkiRJkiQNrH322Yd99tmn32UMPINeLWPQPqJw+NZDzBmgmvwIhCRJkiRJkgaRSzdIkiRJkiRJWs5zn/tcIoJzzll+Et773/9+IoKI4PLLL19u/7/+6782vNDZ0qVL+e53v8vuu+/Oeuutx8orr8wGG2zAm9/85ob9wOgXY1uyZAknnHAC22yzDZMnT2a99dZjzz335JJLLgF4qs558+Y1/VprfbzwhS9ktdVWY+2112bPPffkqquuWq5tRPCOd7wDgAsvvPCp/mvb3Llzm55nPBn0SpIkSZIkSVrOrrvuCsBFF1203L4LL7zwqfut9tf6AFi4cCGvfvWredvb3savf/1rHnjgASZPnsxdd93FmWeeyU477cSJJ57YUY1PPvkke+21Fx/84Ae5/vrrGRoaYmhoiHPOOYdZs2bxwx/+cNQ+hoaG2GOPPfjgBz/ITTfdxMSJE3nooYc455xz2HnnnbnsssuWaT99+nSmTZsGwEorrcT06dOX2VZeeeWOvoaxYtArSZIkSZIkaTm77LILsGyoC/DAAw9www03MHXq1Ib7//KXv3DXXXex8sors+OOOz71fC3g3W677Tj33HN59NFHmT9/Pg8++CCf/exnmThxIh/96Eefmonbjs9+9rP84he/YOLEiZxwwgksWLCAhx56iHnz5vGa17yGd73rXaP28dWvfpUrr7yS73//+yxatIiFCxfy+9//nq222orFixdz2GGHLdP+7rvv5stf/jIAO+20E3ffffcy20477dR2/WPJoFeSJEmSJEnScmqzca+++moWLVr01PMXX3wxmckBBxzA2muvzW9/+1uWLl361P5a8PuSl7yEyZMnA/DrX/+as88+m80224zf/OY3zJ49m1VXXRWAtdZai6OOOorPfOYzLF26lC984Qtt1bdw4UKOO+44AD7zmc9w2GGHPXW+TTbZhB/96Edssskmo/bz8MMP8+Mf/5g3velNT83G3WabbTjllFMAuPLKK7n99tvbqqmfDHolSZIkSZIkLWfTTTdlo402YmhoiEsvvfSp52tB7m677cYrXvEK5s+fz3XXXbfc/vplG77zne8AcOCBB7LGGms0PN8BBxwAwAUXXMCSJUtGre+8887jkUceYdVVV+XQQw9dbv9KK63Ehz70oVH72XnnnXnFK16x3PPbb789G220EQA33HDDqP30m0GvJEmSJEmSpIZqYW398gz1Qe5o+2tqQfFnP/tZ1l9//Ybbi1/8YgAeffRRHnjggVFru/baawHYdtttmTJlSsM2O++886j91M7byIYbbgjAQw89NGo//WbQK0mSJEmSJKmhkUHu/Pnz+f3vf8/mm2/O9OnTl9t/66238ve//51JkyYts1btXXfdBRTLJNxzzz1Nt5pHH3101Nruv/9+AGbMmNG0zQYbbDBqP7W1hhupLS/x5JNPjtpPvxn0SpIkSZIkSWqodkG2K6+8kscee4yLL76YpUuXPhXwbrvttkybNu2pdXtrge/222/P6quv/lQ/tTV8zzrrLDKz6bZgwQIyk5kzZ67YL/RpwKBXkiRJkiRJUkObbbYZ06dP54knnuCyyy57KsidNWsWABMnTuQVr3gFDz74INdff33DZRsApk+fDjCmFzVbd911geHZwo202vd0M/BBb0SsHxFfjohbImJxRNwTET+NiFd12d96EXFwRPxfXZ+PRMRNEfE/EfG8UY7PNrb9uvtqJUmSJEmSpMFSm9V74YUXNgxyR9sP8LKXvQyAX/ziF2NW14te9CIArrvuOhYtWtSwzcUXXzxm56s3YUIRq2bmuPTfjYEOeiNiG+AG4FDgOcDjwLrAnsCvIuJjXXR7J/ANYL+yzyeBScDmwHuB6yPiX9vo537gnibb4i7qkiRJkiRJkgZOLbT92c9+xjXXXMM//dM/LbMubm3/d7/7XW699danZvnWmzNnDgDnnnsuv/zlL1uer90Ln82ePZvVV1+dxYsX89WvfnW5/UNDQxx//PFt9dWpadOmAcWaw4NiYIPeiJgM/ARYB7gW2Coz1wDWAo4DAvh8RMzusOtJwEXA24EZmTkVWA14BXAdsCpwahkyt/LizFy/yfazDmuSJEmSJEmSBlJtxu4111zDkiVLlputu8MOO7D66qtz5ZVXAsPr9tZ7zWtew7777ktmss8++3Dsscdy3333PbX/wQcf5Oyzz+bNb34zH/rQh9qqa+rUqXzwgx8E4BOf+AT//d//zWOPPQYUS0Tst99+3Hrrrd190aN4wQteAMAf//hHLr/88nE5R6cGNugFDgY2ARYBe2XmjQCZuSAzjwDOpgh7v9Bhv7tm5q6ZeWpm3l32uSQzLwFmA/dShMEfHJsvQ5IkSZIkSaqurbbainXWWeepx7X1eWsmTZrETjvt9NTjkUFwzamnnsob3vAGFi9ezEc+8hGmT5/OWmutxbRp01hnnXXYZ599Ol7a4ZOf/CSzZ89maGiIQw89lGnTprHWWmuxySab8POf/5yTTz75qbarrLJKR3238vznP59ddtmFoaEhdtxxR9ZZZx1mzpzJzJkz+d3vfjdm5+nEpL6ctT0HlLenZ+YdDfYfC7wB2C4iNsvMm9vpNDMvarHvvoj4OTAH2L6zciVJkiRJklRl847Zo98lDKSIYOedd+bss88GGge5u+66K7/61a+A4RnAI62++uqcddZZnHPOOZx88slcfvnl3HfffUyYMIHnPe95bLfdduy2227827/9W9u1rbzyypxzzjl85Stf4dvf/jZ/+ctfmDRpEnvttRdHHnkkm2+++VNt11xzzfa/6Db86Ec/4lOf+hS/+MUvuOOOO3jwwQcBWLy4P6u6DmTQGxFTGQ5az23S7HfAfGAN4FVAW0FvGx4obyeOUX+SJEmSJElSpZ111lkt9x911FEcddRRbfW1xx57sMcejUP1hQsXMmXKlGWemzNnzlNr/DYyadIkPvShDzVc8uH8888HYJNNNmHy5MnL7DvllFM45ZRTWtY6d+7cpvvWWWedhmsD98ugLt2wBcWyDAA3NmqQmUsZDne3HMNz1/4kccMo7c6MiIci4vGI+EdE/DAi/LOPJEmSJEmSNCCOPfZYAHbfffc+VzL+BjXonVF3/84W7Wr7ZrRo07aI2BvYoXz47VGav5hi1u+TwIbAvsDPIuLMiFh5LOqRJEmSJEmS1NySJUvYb7/9+OUvf8n8+fOfev7GG29kv/3249xzz2WllVbi0EMP7WOVK0ZkZr9rWE5E7A+cVj5cKTOHmrQ7DdgfOC8zX93jOTcErgGeBfwkM/du0u4U4HvA5Zn5cPnc5sBHgHeUzb6ZmQe1ONdBwEEA06dP3/6MM87opfQxdf0d80dvtAJNnwz3PNbvKoZtveEa/S5BHVq0aNFyH/mQ2uX4US8cP+qVY0i9cPyoF44f9WoQx9Aaa6zB8573vH6XoTYsWbKEiRPbX1F1aGiItdde+6nH06ZNY2hoiEcffRSACRMmcPzxx/OOd7yjWRd99de//nWZgHo0u+2229WZuUOjfQO5Ru+KFhFTgLMpQt7bgHc2a5uZcxo89yfg3yPifuDDwLsi4rhmF4jLzJOAkwB22GGHHHmlwn6a87Fz+l3CMg7feojjrh+cYTrvgFn9LkEdmjt37nJXA5Xa5fhRLxw/6pVjSL1w/KgXjh/1ahDH0E033cTUqVP7XYbasHDhwo6+V5nJ1772Nc4991yuv/567r33XpYsWcImm2zCLrvswgc+8AG22267cay4N6uuuiovetGLxqSvwUnQlvVI3f3JwMIm7VYrbxd1e6KIWBX4McWSDfcBr87M+7vs7tPA+yhq3pOxu0CcJEmSJEmSpBEigkMOOYRDDjmk36X03aCu0Vu/Lu8GLdrV9t3VzUnKtXR/ALwSeBiY3WwWbjsy8xGGL+L2nG77kSRJkiRJkqRODGrQ+yegtnjwCxo1iIgJwGblwz92eoKImESx1u4eFDOCX5eZ13VcqSRJkiRJkiT12UAGvZm5ELiqfLh7k2YvBWpXxjq/k/7LkPg7wL7AY8DrM/OyLkod2e/qwFblw1t77U+SJEmSJEmS2jGQQW/p9PL2gIiY0WD/EeXt1Z0stxARQXEhtP2BJ4B9M/OCDo5t5ZMU6/Mm8PN2a5IkSZIkSdL4yszRG0kr0FiPyUEOek8EbgOmAj+LiC0BImJqRHyRYjYuwJEjD4yILLejG/R7PPBOYAh4U2b+soOazoyIz0XEDuX6vrXzbRYR3wQ+Wj71nczseDkJSZIkSZIkjb2JEyeyZMmSfpchLWPp0qVMmDB28eykMetpjGXmYxGxN8WyDNsBN0bEAmAKRUCdwJGZeV67fUbExsBhtVMAJ0bEiS1qWH/EU+sB+1GEy0siYj6wCrB6XZsfAO9utyZJkiRJkiSNr9VWW41Fixax5ppr9rsU6SmPPvookydPHrP+BjboBcjM30fEVsDHgT2BDYEHgCuA4zOzo7V5WXYG80rA9A6P/zzwB2BHYCNgbWApxXq8vwNO6SR4liRJkiRJ0vibNm0a999/P1OnTmXixIn9LkciM3n44YdZffXVR2/cpoEOegEy826KWbiHjda27piGa+lm5jxgtHV2W/V7HmCQK0mSJEmSVCFTp07lscce47bbbmPttddmypQpTJw4kdEvxySNrczkiSee4IEHHmBoaIi11lprzPoe+KBXkiRJkiRJ6kVE8KxnPYuFCxeyYMEC7r33XtfsHVCLFy9m1VVX7XcZ42rSpEmsscYaPOtZz3pmrNErSZIkSZIkjZWIYNq0aUybNq3fpaiFuXPn8qIXvajfZVTS2EXGkiRJkiRJkqS+MOiVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIob+KA3ItaPiC9HxC0RsTgi7omIn0bEq7rsb72IODgi/q+uz0ci4qaI+J+IeF4bfUyIiIMi4rKIeDgiFkbEtRHx4YhYuZu6JEmSJEmSJKlbk/pdQCsRsQ3wG2Cd8qkFwLrAnsAeEXFkZh7TYbd3suzXvQhYGdi83N4ZEf+emd9rUtNKwNnA68qnngCWANuW279ExCszc1GHdUmSJEmSJElSVwZ2Rm9ETAZ+QhHyXgtslZlrAGsBxwEBfD4iZnfY9STgIuDtwIzMnAqsBrwCuA5YFTi1DJkb+SxFyLsYmFMeuzqwF/Ag8GLgxA5rkiRJkiRJkqSuDWzQCxwMbEIx43avzLwRIDMXZOYRFLNqA/hCh/3umpm7ZuapmXl32eeSzLwEmA3cSxEGf3DkgRGxPnBY+fCjmfmd8tjMzJ8B/17u+9cWQbEkSZIkSZIkjalBDnoPKG9Pz8w7Guw/trzdLiI2a7fTzLyoxb77gJ+XD7dv0OSNwCrAfOCkBsf/GPgzRQC9f7s1SZIkSZIkSVIvBjLojYipDAet5zZp9juKwBWgqwuzNfFAeTuxwb7dytuLMnNxk+PPK29fOYY1SZIkSZIkSVJTAxn0AltQzIoFuLFRg8xcCtxcPtxyDM+9a3l7Q4N9tfM0rKn0x/J2i4iIFu0kSZIkSZIkaUwMatA7o+7+nS3a1fbNaNGmbRGxN7BD+fDbLepqp6Yp5SZJkiRJkiRJ4yoys981LCci9gdOKx+ulJlDTdqdRrEW7nmZ+eoez7khcA3wLOAnmbl3gzZPACsBB2bmt5r0szvDyzdskJl3NWhzEHAQwPTp07c/44wzeil9TF1/x/zRG61A0yfDPY/1u4phW2+4Rr9LUIcWLVrElCn+zUXdcfyoF44f9coxpF44ftQLx4965RhSLxw/re22225XZ+YOjfZNWtHFDKKImAKcTRHy3ga8czzPl5knUV7MbYcddshZs2aN5+k6Mudj5/S7hGUcvvUQx10/OMN03gGz+l2COjR37lwG6WdM1eL4US8cP+qVY0i9cPyoF44f9coxpF44fro3qEs3PFJ3f3KLdquVt4u6PVFErAr8mGLJhvuAV2fm/aPU1U5NPdUlSZIkSZIkSe0a1KC3fg3cDVq0q+1bbnmEdkTEysAPgFcCDwOzM/PmFofU6mqnpkWZubCbuiRJkiRJkiSpE4Ma9P4JqC0e/IJGDSJiArBZ+fCPnZ4gIiYB3wP2oJh5+7rMvG6Uw2rnaVhTacvy9qZOa5IkSZIkSZKkbgxk0FvOhL2qfLh7k2YvBWpXxjq/k/7LkPg7wL7AY8DrM/OyNg69oLzduVzyoZFavR3VJEmSJEmSJEndGsigt3R6eXtARMxosP+I8vbqUZZbWEZEBMWF0PYHngD2zcwLWh/1lB8BjwNrAu9q0PdeFLOMk2K2sCRJkiRJkiSNu0EOek8EbgOmAj+LiC0BImJqRHyRYjYuwJEjD4yILLejG/R7PPBOYAh4U2b+st2CMvNu4Mvlwy9GxFsjYmJ5ztcB3y73fS8z/9Buv5IkSZIkSZLUi0n9LqCZzHwsIvamWAJhO+DGiFgATKEIqBM4MjPPa7fPiNgYOKx2CuDEiDixRQ3rN3j6E8BWwOuAU4FvRsQSYLVy/5XAu9utSZIkSZIkSZJ6NbBBL0Bm/j4itgI+DuwJbAg8AFwBHJ+Zna6DWz+DeSVgehc1PVku0XAgMIfi4msTgesolms4ITOf6LRfSZIkSZIkSerWQAe98NRyCYcxPBO3nWOiyfPzgIb7OqxpKcXSEk1nA0uSJEmSJEnSijLwQa+kapn5sXP6XcIyDt96iDkDVNO8Y/bodwmSJEmSJOlpaJAvxiZJkiRJkiRJaoNBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVXEdBb0S8LSL+pYP2+0bE2zovS5IkSZIkSZLUrk5n9J4CnNBB++OAkzs8hyRJkiRJkiSpA90s3RDj3F6SJEmSJEmS1IHxXqN3TWDxOJ9DkiRJkiRJkp7Rxi3ojYh9gTWAeeN1DkmSJEmSJEkSTGq1MyIOAw4b8fR6EfG3VodRBLxrAAmc1VOFkiRJkiRJkqSWWga9FEsvzKx7nMDEEc818yTwPeA/u6hLkiRJkiRJktSm0YLeU4C55f0AfgM8CLyxxTFLgQXAXzLz0R7rkyRJkiRJkiSNomXQm5m3AbfVHkfE7cA9mXnheBcmSZIkSZIkSWrPaDN6l5GZM8epDkmSJEmSJElSlyb0uwBJkiRJkiRJUm86mtFbExETgJ2ArYC1gJVatc/Mz3RzHkmSJEmSJEnS6DoOeiNiH+C/gRntNAcSMOiVJEmSJEmSpHHSUdAbEf8M/B/Fkg9PAFcAdwCLx740SZIkSZIkSVI7Op3ReyRFyHshsH9m3jX2JUmSJEmSJEmSOtHpxdi2p1iKYY4hryRJkiRJkiQNhk6D3gAWZOZt41GMJEmSJEmSJKlznQa9NwGrR8Sq41GMJEmSJEmSJKlznQa9X6NY1/et41CLJEmSJEmSJKkLHV2MLTO/ExGvAE6IiIWZecY41SVJkiRJkiRJalPToDciTm5x3OPAaRHxBeAqYGGLtpmZ7+yyPkmSJEmSJEnSKFrN6J0DJMUF2JrZpNxaScCgV5IkSZIkSZLGSaug99MrrApJkiRJkiRJUteaBr2ZadArSZIkSZIkSRUwod8FSJIkSZIkSZJ6Y9ArSZIkSZIkSRXXao3e5UTELh32/zjwMHBLZg51eKwkSZIkSZIkqQ0dBb3AXCC7OM8TEXEhcFxm/qqL4yVJkiRJkiRJTXS6dMPt5fYYEOU2BNxTbkN1zz8G/B2YD6wCzAZ+GRFHj0XhkiRJkiRJkqRCR0FvZs4EjgdWAn4O7ApMycwNMnMDYAqwC3AOxWzhL2bm2sDzgG9SBMCfjIhdx+wrkCRJkiRJkqRnuI6C3ojYgyLo/U5m7pmZF2fmk7X9mflkZv42M/cCTgW+EhGzM/NvmXkw8A2KsPc9Y/g1SJIkSZIkSdIzWqdLNxxOsUbvkW20PZIi1P1w3XNfLG936vC8kiRJkiRJkqQmOg16XwjMz8z7R2tYtnkY2K7uuXnAQmC9Ds8rSZIkSZIkSWqi06B3FWBaREwdrWHZZhqwcoNzPtrheSVJkiRJkiRJTXQa9N5QHvORNtp+GJgI3Fh7IiLWBlYH7unwvJIkSZIkSZKkJjoNer9Ose7ukRHx9Yh4zsgGEbFpRHwVOIpiPd+v1+3erby9tptiJUmSJEmSJEnLm9RJ48z8TkS8AngncBBwUETcDdxVNpkBrF/eD+DkzPxOXRd7AHcAP+6pakmSJEmSJEnSUzoKegEy88CIuBT4JDCTItydMaLZbcB/ZubJI4799y7rlCRJkiRJkiQ10XHQC5CZ3wa+HRHbAS8C1i133U+xLMO1mZljU6IkSZIkSZIkqZWugt6azLwGuGaMapEkSZIkSZIkdaHTi7FJkiRJkiRJkgaMQa8kSZIkSZIkVVzTpRsi4m/l3b9m5uwRz3UiM/O53RQnSZIkSZIkSRpdqzV6Z5a3ixs81wkvyiZJkiRJkiRJ46hV0Ltbeftog+ckSZIkSZIkSQOiadCbmRe285wkSZIkSZIkqb+8GJskSZIkSZIkVVyrpRtGFRHTgWcDq2XmRWNTkiRJkiRJkiSpE13N6I2IN0fEH4A7gcuB34zYv2ZE/Coifh0Ra41BnZIkSZIkSZKkJjoOeiPiC8DpwFbAE0ACUd8mMx8G7qG4eNube65SkiRJkiRJktRUR0FvRMwGPgosBN4CTAHua9L8OxQB8Kt7KVCSJEmSJEmS1Fqna/S+j2IG70cz80yAiGjW9rKy7Qu7rk6SJEmSJEmSNKpOl254aXn7v6M1zMxFwAJg/U6LkiRJkiRJkiS1r9Ogd01gQWY+0mb7ptN9JUmSJEmSJEljo9Og90FgWkRMHq1hRGwITAPu7qYwSZIkSZIkSVJ7Og16ryhvX9tG2/eWtxd3eA5JkiRJkiRJUgc6DXq/RbEcw+cjYoNmjSLiQOAjFBdj+0b35UmSJEmSJEmSRjOpk8aZ+dOIOB3YH7g6Is4EVgOIiEOBjYHXAFtQBMJfy8zLxrZkSZIkSZIkSVK9joLe0hzgPuBQ4P3lcwkcX96P8vFxwEd7rE+SJEmSJEmSNIqOg97MHAI+GBFfBd4OvAyYQbEMxD3AZcCpmXnTWBYqSZIkSZIkSWqsZdAbEdsB12ZmjtyXmX8FPjlehUmSJEmSJEmS2jPajN6rgAURcQlwYbldlZlLxr0ySZIkSZIkSVJb2lm6YRrwWoqLrAE8GhGXUYS+FwGXZ+YT41SfJEmSJEmSJGkUE0bZvwPwIeBs4AGKC62tDvwz8BlgLvBwRFwQEZ+OiFdGxKpjWWBErB8RX46IWyJicUTcExE/jYhXddnfKhHx6oj4RET8OCLujIgst9e0cfy8uvbNtiO6qU2SJEmSJEmSutFyRm9mXgNcA5wAEBFbALuU287ARsCqwK7lc58AnoyIqxle6uGSzFzUTXERsQ3wG2Cd8qkFwLrAnsAeEXFkZh7TYbdbAL/spp4RHgKazWR+ZAz6lyRJkiRJkqS2tLN0w1My8ybgJuBEgIiYyXDwuwvwPGBl4GXAjsBHgSFglU4Li4jJwE8oQt5rgbdm5o0RMQ34FHA48PmIuCYzz+uw+4eBq4Ery+2HndYH7JuZc7s4TpIkSZIkSZLGVEdB70iZOQ+YB5wKEBHTKQLffYF/oVgaottzHAxsAiwC9srMO8pzLgCOiIjnAm8AvgB0EvT+AVg7M7P2RER0WaIkSZIkSZIk9V9PQW9NRGzA8HIOu1AsjzDa+r+jOaC8Pb0W8o5wLEXQu11EbJaZN7fTaWYu7bEuSZIkSZIkSRooXQW95Wza+mB309qu8vY24GLgt+Vtp/1PBbYvH57bpNnvgPnAGsCrgLaCXkmSJEmSJEl6umkr6I2IrRgOdncGZtR2AUuB6ylC3d8CFzeZgduJLRgOjW9s1CAzl0bEzcBLgC17PF83jo+IjSiC5gcpLlr3v8D3M3NJH+qRJEmSJEmS9AzVMuiNiLOBVwBrMRy8Pg5cwvBs3Uszc/4Y1zWj7v6dLdrV9s1o0Wa8bAs8CiwGpgOvLbeDIuINmflwH2qSJEmSJEmS9AwUddckW35nxFIggXuArwO/Aa7MzCfGtaiI/YHTyocrZeZQk3anAfsD52Xmq3s4X+1FeG1m/nKUticAFwEXZuYD5XMbA+8HPkSxNvGvMnN2iz4OAg4CmD59+vZnnHFGt6WPuevvGOvMvjfTJ8M9j/W7imFbb7hGv0sYeI6h1hxD1bJo0SKmTJnS7zJUUY4f9coxpF44ftQLx4965RhSLxw/re22225XZ+YOjfa1s3RDAOsDHwNeCVwUERcDl2XmI2NXZjVk5gcaPHc78OGIuBX4KrB7RMzOzPOa9HEScBLADjvskLNmzRq/gjs052Pn9LuEZRy+9RDHXT8m1wwcE/MOmNXvEgaeY6g1x1C1zJ07l0F6j1a1OH7UK8eQeuH4US8cP+qVY0i9cPx0b8Io+3cEPgL8lGKJgl2BT1JcIO2hiLgiIo6LiDdExLpjWFd9gDy5RbvVyttFY3juXnwdmFfe36uPdUiSJEmSJEl6Bmk5zS0zrwCuAP4LGl6UbYdy+0C5/2aKZQ0uprgo2+1d1lW/Lu8GwM1N2m1Q3t7V5XnGVGZmRFwJzASe0+dyJEmSJEmSJD1DdPR55sy8AbgB+BpARDyH4eB3V2Dzcjuw3P8P4KLMfGuHdf2JYm3gAF5Ag6A3IiYAm5UP/9hh/5IkSZIkSZL0tDHa0g0tZebfMvOUzHxnZj6PYobtW4AzKYLaZ1NcLK3TfhcCV5UPd2/S7KVA7apG53d6jvEQEQG8uHx4az9rkSRJkiRJkvTMMSZXKIqIGRQze2vbFhSzcXtxOkVoekBEfCYzRy7PcER5e3VmNlvaYUxFRGRmtmhyMMWyDQCDdUUqSaqAmQN4Mb9BusDgvGP26HcJkiRJkqQB1VXQGxGbsmywW78ebS3gXQpcB1zYZW0nUqz9uwnws4h4a2b+MSKmUlwQbt+y3ZEN6quFsZ/OzKMb7F8LmNjgnNNGXFRufmY+Wff4KxGxFPg/ioD5sbK/ZwPvZTh8viAzf9HelylJkiRJkiRJvWkr6I2ILRgOdXcGNqzfXd4OAVdTBLsXAb/NzAXdFpaZj0XE3hTLMmwH3BgRC4ApFEtOJHBkZp7XRffXUgTII31/xOPdgLl1j6cCbwcOBZZGxHyKwHhaXZsLgf26qEmSJEmSJEmSutIy6I2IHwKvAOpnudaC3ceByylC3YuASzPz0bEsLjN/HxFbAR8H9qQImB8ArgCOz8wVvTbvN4D7gJ2AjYF1KELnv1OsKfw94IeZuXQF1yVJkiRJkiTpGWy0Gb371N1/FLiUItS9ELg8M58Yr8JqMvNu4LBya/eYlusDZ+bMLmv5HfC7bo6VJEmSJEmSpPEyWtD7c4aD3aszc2j8S5IkSZIkSZIkdaJl0JuZe66oQiRJkiRJkiRJ3ZnQ7wIkSZIkSZIkSb0x6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIoz6JUkSZIkSZKkijPolSRJkiRJkqSKM+iVJEmSJEmSpIqb1O8CJEmSxsLMj53T7xKWcfjWQ8wZoJrmHbNHv0uQJEmSNI6c0StJkiRJkiRJFdfVjN6I2AJ4I7AVsBawUovmmZmv6uY8kiRJkiRJkqTRdRz0RsSXgEOBKLfRZKfnkCRJkiRJkiS1r6OgNyLeC3ygfHg98GPgDmDx2JYlSZIkSZIkSWpXpzN6D6SYofvfmfmBsS9HkiRJkiRJktSpTi/G9k/l7afGuhBJkiRJkiRJUnc6ndH7CLA4MxeMRzGSJEmSJEmSpM51OqP3cmBaRKw3HsVIkiRJkiRJkjrXadD7BYo1eo8ah1okSZIkSZIkSV3oKOjNzEuAdwEHR8Q3ImLmuFQlSZIkSZIkSWpbR2v0RsTfyrtLgAOBAyPiQWBhi8MyM5/bZX2SJEmSJEmSpFF0ejG2mQ2eW6fcmskOzyFJkiRJkiRJ6kCnQe9u41KFJEmSJEmSJKlrHQW9mXnheBUiSZIkSZIkSepORxdjkyRJkiRJkiQNnk6XblhGRASwGbBe+dR9wM2Z6bq8kiRJkiRJkrSCdBX0RsTzgE8A+wKrj9j9SET8EPhcZv61x/okSZIkSZIkSaPoeOmGiHg9cC3wVmAKECO2KcDbgGsjYs+xK1WSJEmSJEmS1EhHQW9EPBc4g2IW79+Ag4HnA5PL7fnAu4FbyjZnlsdIkiRJkiRJksZJpzN6PwKsClwAbJOZ38zMWzLz8XK7JTNPAl4IXAisAnx4bEuWJEmSJEmSJNXrNOjdHUjg4Mx8rFmjct/BFEs5zO6+PEmSJEmSJEnSaDoNemcA89u5yFpm/hl4uDxGkiRJkiRJkjROOg16HwVWi4iVRmsYEStTrNPbdOavJEmSJEmSJKl3nQa91wMrAW9vo+3by7Z/6LQoSZIkSZIkSVL7Og16v0ux7u5XIuJdEREjG0TEqhFxKPAVivV8v9N7mZIkSZIkSZKkZiZ12P5k4E0UF2U7Efh0RFwM3AGsCmwMvBRYhyIQPg84ZayKlSRJkiRJkiQtr6OgNzMzIt4AHA+8i+JCa2+imLkLRbgLsJQiCD48M3NkP5IkSZIkSZKksdPpjF4y8zHg3RHxBWAfYDtgvXL3fcA1wI8y8/Yxq1KSJEmSJEmS1FTHQW9NZt4GnDB2pUiSJEmSJEmSutHpxdgkSZIkSZIkSQPGoFeSJEmSJEmSKq7p0g0RcXJ5967MPGrEc53IzHxnN8VJkiRJkiRJkkbXao3eOeXtn4Cj6p5LIDo4RwIGvZIkSZIkSZI0TloFvZ8ub+9v8JwkSZIkSZIkaUA0DXozc7lQt9FzkiRJkiRJkqT+8mJskiRJkiRJklRxHQW9EXFyRHypg/ZfjIj/r/OyJEmSJEmSJEnt6nRG7xzgLR20/xeGL+omSZIkSZIkSRoH4710QwA5zueQJEmSJEmSpGe0cQt6I2IC8CzgkfE6hyRJkiRJkiQJJrXaGRHTgDVHPD0xIp5NMVu34WHlMW8DVgV+31uJkiRJkiRJkqRWWga9wAeBT414bl1gXgfn+GYnBUmSJEmSJEmSOjNa0BssO3M3aT6Tt77NAuBG4FuZeUrX1UmSJEmSJEmSRtUy6M3Mo4Gja48jYilwd2ZuML5lSZIkSZIkSZLaNdqM3pFOBR4ehzokSZIkSZIkSV3qKOjNzDnjVIckSZIkSZIkqUsdBb0RMRl4MfBYZl45StsXA5OBKzJzcfclSpIkSZIkSZJamdBh+38DLgDe0kbbAztoK0mSJEmSJEnqUqdB737l7XfbaHsSEMCbOjyHJEmSJEmSJKkDnQa9mwFPAL9vo+01ZdvNOy1KkiRJkiRJktS+ToPe9YFFmZmjNczMpcDC8hhJkiRJkiRJ0jjpNOhdAKxZXpStpbLNmsBjXdQlSZIkSZIkSWpTp0HvH8pj9m2j7RuBicANnRYlSZIkSZIkSWpfp0HvmRQXWPtSRLygWaOI2Ar4EpDlMZIkSZIkSZKkcTKpw/YnA4cALwSujIiTgV8At5f7NwFeB8wBVgWuB04ak0olSZIkSZIkSQ11FPRm5lBE7AH8DNiWIvQ9pEHTAK4DXp+ZT/ZYoyRJkiRJkiSphU6XbiAz7wR2BN4HXAEsoQh2o7x/BfBeYMfM/MfYlSpJkiRJkiRJaqTTpRsAyMwngK8BX4uIScDa5a4HM3NorIqTJEmSJEmSJI2uq6C3Xhns3jsGtUiSJEmSJEmSutBT0BsR04FnA6tl5kVjU5IkSZIkSZIkqRMdr9ELEBFvjog/AHcClwO/GbF/zYj4VUT8OiLWGoM6JUmSJEmSJElNdBz0RsQXgNOBrYAngKS4ENtTMvNh4B5gN+DNPVcpSZIkSZIkSWqqo6A3ImYDHwUWAm8BpgD3NWn+HYoA+NW9FChJkiRJkiRJaq3TNXrfRzGD96OZeSZARDRre1nZ9oVdVydJkiRJkiRJGlWnSze8tLz939EaZuYiYAGwfqdFSZIkSZIkSZLa12nQuyawIDMfabN90+m+kiRJkiRJkqSx0WnQ+yAwLSImj9YwIjYEpgF3d1OYJEmSJEmSJKk9nQa9V5S3r22j7XvL24s7PIckSZIkSZIkqQOdBr3foliO4fMRsUGzRhFxIPARiouxfaP78iRJkiRJkiRJo5nUSePM/GlEnA7sD1wdEWcCqwFExKHAxsBrgC0oAuGvZeZlY1uyJEmSJEmSJKleR0FvaQ5wH3Ao8P7yuQSOL+9H+fg44KM91idJkiRJkiRJGkXHQW9mDgEfjIivAm8HXgbMoFgG4h7gMuDUzLxpLAuVJEmSJEmSJDXWzYxeADLzr8Anx7CWhiJifeDjwJ7AhsB8iovCnZCZ53fR3yrALODFdduMcvdrM/OXbfbzL8AhwAuBycBtwA+B/5eZCzutS5IkSZIkSZK61XXQuyJExDbAb4B1yqcWAOtShL57RMSRmXlMh91uAbQV5rao6yTgwPLhELAY2Bw4CvjXiNg5M+/s5RySJEmSJEmS1K4J/S6gmYiYDPyEIuS9FtgqM9cA1qJY/zeAz0fE7C66fxg4HzgGeGOHdR1CEfIuBT4MTMnMqcDLKWb1Pgc4s4uaJEmSJEmSJKkrTWf0RsSnxuokmfmZLg47GNgEWATslZl3lH0tAI6IiOcCbwC+AJzXQb9/ANbOzKw9ERFtHVgu+3B0+fDLmflftX2ZeWlE7ANcDbw8IvbKzJ92UJckSZIkSZIkdaXV0g1HA9lifzui7KOboPeA8vb0Wsg7wrEUQe92EbFZZt7cTqeZubSLWmr+GXgWxdd0XIO+r42IXwO7U9Rv0CtJkiRJkiRp3LUKek+l96C3KxExFdi+fHhuk2a/o7gw2xrAq4C2gt4e7Vbe3tAkfIai3t2BV66AeiRJkiRJkiSpedCbmXNWYB0jbUExGxjgxkYNMnNpRNwMvATYcgXVVTtPw5pKfyxv14uIdTPz/nGuSZIkSZIkSdIz3KBejG1G3f07W7Sr7ZvRos1Yqp2nnZrq20uSJEmSJEnSuIm6a5INjIjYHzitfLhSZg41aXcasD9wXma+uofz1V6E12bmL1u0+zPwfOBzmfmJJm2eD/y5fLhTZl7WoM1BwEEA06dP3/6MM87otvQxd/0d8/tdwjKmT4Z7Hut3FcO23nCNfpcw8BxDrTmGWnP8tOb4ac3x05rjp3oWLVrElClT+l2GKsrxo144ftQrx5B64fhpbbfddrs6M3dotK/VGr1NRcQ04F0Ua9E+G5icmc+t278GsDfFGr//m4OYJvdRZp4EnASwww475KxZs/pbUJ05Hzun3yUs4/Cthzju+q6G6biYd8Csfpcw8BxDrTmGWnP8tOb4ac3x05rjp3rmzp3LIP0/UdXi+FEvHD/qlWNIvXD8dK/j3z4i4mXAD4HpDK+ju0yQm5nzI+IDwAuB+4Cms2SbeKTu/mRgYZN2q5W3izrsv1u1uia3aLNa3f0VVZckSZIkSZKkZ7CO1uiNiI2AnwHrA+cCbwMeatL8GxRB8N5d1FW/zu0GLdrV9t3VxTm6UaurnZpgxdUlSZIkSZIk6Rms04uxfRhYCzgtM1+Xmf8LPNGk7S/K2x27qOtPDM8SfkGjBhExAdisfPjHLs7Rjdp5GtZU2rK8vS8z7x/neiRJkiRJkiSp46D3tRQB7CdHa5iZfwceAzbttKjMXAhcVT7cvUmzlwK1q4qc3+k5unRBefuCiJjRpM3s8nZF1SRJkiRJkiTpGa7ToPfZwCOZOa/N9o/Sej3bVk4vbw9oEqoeUd5enZk3d3mOTp0P3Evxuh0+cmdEvBD45/LhaSuoJkmSJEmSJEnPcJ0GvY8Dq0REjNYwIlYF1gQe7rwsAE4EbgOmAj+LiC3LfqdGxBeBfct2RzY4d5bb0U1qWysi1q1tdbum1T8fESvVH5eZjwO1Pj8YEYdHxCplny8DzqJ4TS/JzJ91+XVLkiRJkiRJUkc6DXr/DEyi9Rq1NXsBE4HrOy0KIDMfo7iQ2wPAdsCNETGfIjj+MMUSEh/PzPO66P5a4L66reb7I55/eYO6vg58k+K1+y9gYUQsBC6lWKbib8CbuqhJkiRJkiRJkrrSadB7NhDAUa0alUstHEsRxv5fV5UBmfl7YCvgKxQB6ioUwe85wO6ZeUy3ffciMw8C3kyxZu8iivD7T8DngG0z885+1CVJkiRJkiTpmWlSh+2/DBwEvCkihoAvUQS/RMRUYBOKC7YdAawH/BE4uZcCM/Nu4LBya/eYlktLZObMXmoq+zgTOLPXfiRJkiRJkiSpVx0FvZn5SES8Fvg5cACwf93uh+vuB8UM3Ndn5pO9FilJkiRJkiRJaq7TpRvIzJuAFwKfB+6gCHXrt3uB/wdsn5l/G7tSJUmSJEmSJEmNdLp0AwCZuQD4BPCJiNgImEERGt+TmfPGrjxJkiRJkiRJ0mi6CnrrZeY/gH+MQS2SJEmSJEmSpC50vHSDJEmSJEmSJGmwjEnQGxHvj4hrI+KRiHgoIi6IiL3Hom9JkiRJkiRJUmstg96IeHFEPBgRt0TEyk3anAGcAGwDTAbWAHYFfhQRHx3jeiVJkiRJkiRJI4w2o/eVwJrAzzPziZE7I2J/4E1AAPcCJwHHA7eWz/1nRGwxlgVLkiRJkiRJkpY1WtC7M5DAWU32H1be3g5slZnvzszDga2Aa4GJwDvHolBJkiRJkiRJUmOjBb3PoQh6Lx+5IyLWBV5c7v9MZj5Q25eZjwFHU8zq3XWsipUkSZIkSZIkLW+0oHd9YEFmPtJg307lbQI/bbD//PL2OV3WJkmSJEmSJElqw6RR9q8ODDXZ9+Ly9q+Zed/InZn5aETMB6b2UJ8kSZK0Qsz82Dn9LmEZh289xJwBqmneMXv0uwRJkiS1MNqM3geAVSPiWQ327Ugxm/eqFsevDCx3ETdJkiRJkiRJ0tgZLej9fXn7b/VPluvz7lw+vLDRgRGxPjAZuKOXAiVJkiRJkiRJrY0W9H6f4oJqn4qIfSJi5YjYFDiV4dm6ZzU5thYE3zAmlUqSJEmSJEmSGhptjd7vAu8Ftgd+MGJfAv+Tmfc3OfYtZZvf9lShJEmSJEmSJKmlljN6M3MJ8FrgVxQze+u37wIfb3RcRDwHeH358KdjVawkSZIkSZIkaXmjzeilnLH76ojYDNi6fPrqzLy1xWFLgTcAT2bmX3uuUpIkSZIkSZLU1KhBb01m3gzc3GbbecC87kqSJEmSJEmSJHVitIuxSZIkSZIkSZIGnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRV3KR+FyBJkiRJVTfzY+f0u4RlHL71EHMGqKZ5x+zR7xIkSXrac0avJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRVnEGvJEmSJEmSJFWcQa8kSZIkSZIkVZxBryRJkiRJkiRV3MAHvRGxfkR8OSJuiYjFEXFPRPw0Il7VY7/TIuKzEXFTRDwaEQ9ExPkRsd8ox82LiBxlO6KX2iRJkiRJkiSpE5P6XUArEbEN8BtgnfKpBcC6wJ7AHhFxZGYe00W/GwEXAZuWTy0CpgGvBF4ZEV/PzPeM0s1DwBNN9j3SaU2SJEmSJEmS1K2BndEbEZOBn1CEvNcCW2XmGsBawHFAAJ+PiNkd9hvADyhC3nnAyzNzKjAV+AiwFDgkIg4cpat9M3P9JtvXO6lJkiRJkiRJknoxsEEvcDCwCcVs270y80aAzFyQmUcAZ1OEvV/osN+9gZdSBLr7ZOalZb+LM/NY4Ctlu89ExMo9fxWSJEmSJEmSNM4GOeg9oLw9PTPvaLD/2PJ2u4jYrIt+f52Z1zXY/19AAutTLOUgSZIkSZIkSQNtIIPeiJgKbF8+PLdJs98B88v7nVyYbbdW/Zah8o3lQ4NeSZIkSZIkSQNvIINeYAuKZRlgOHRdRmYuBW4uH27ZTqcR8SyGL+zWsN/SH9vo9/iIuC8inoiIuyPi5xGxf0RMbKcWSZIkSZIkSRorgxr0zqi7f2eLdrV9M1q0Ga9+twVWAxYD04HXAqcB50fEmm3WI0mSJEmSJEk9i8zsdw3LiYj9KUJTgJUyc6hJu9OA/YHzMvPVbfS7E3BJ+fD5mfnXJu0+BxwJ/DkzNxux7wTgIuDCzHygfG5j4P3AhyjC819l5uwWdRwEHAQwffr07c8444zRSl9hrr9j/uiNVqDpk+Gex/pdxbCtN1yj3yUMPMdQa46h1hw/rTl+WnP8tOb4GZ1jqDXHUGuOn9YcP9WyaNEipkyZ0u8yVGGOIfXC8dPabrvtdnVm7tBo36QVXUzVZeYHGjx3O/DhiLgV+Cqwe0TMzszzmvRxEnASwA477JCzZs0av4I7NOdj5/S7hGUcvvUQx10/OMN03gGz+l3CwHMMteYYas3x05rjpzXHT2uOn9E5hlpzDLXm+GnN8VMtc+fOZZB+T1X1OIbUC8dP9wbnX/5lPVJ3fzKwsEm71crbRV3220yn/dZ8HfgwMBPYC2gY9EqSJEmSVDNzAP9QMGh/vJh3zB79LkGSBt6grtFbv37uBi3a1fbd1ed+AchiHYwry4fP6eRYSZIkSZIkSerWoAa9fwJqiwe/oFGDiJgA1NbP/WM7nWbmfcD9rfotbdlJv5IkSZIkSZLUTwMZ9GbmQuCq8uHuTZq9FKit6H9+B91f0KrfiNiQ4RC4k36JiABeXD68tZNjJUmSJEmSJKlbAxn0lk4vbw+IiBkN9h9R3l6dmTd30e/siHhhg/0fAoJi2YYL6neUQW4rB1OszwswWAsaSZIkSZIkSXraGuSg90TgNmAq8LOI2BIgIqZGxBeBfct2R448MCKy3I5u0O+PgcspvvazImLH8phVIuJw4ANlu//IzCdGHPuViPhyRLwiIp66mFtEPDsijgH+p3zqgsz8RedfsiRJkiRJkiR1blK/C2gmMx+LiL0plk/YDrgxIhYAUyhC2gSOzMzzOuw3I2I/4CJgU+CyiFgErMrw6/GNzPxmg8OnAm8HDgWWRsR8YCIwra7NhcB+ndQkSZIkSZIkSb0Y2KAXIDN/HxFbAR8H9gQ2BB4ArgCOz8yO1tCt6/cfEbEt8FGKmcEzgYXAdcDXM/P/mhz6DeA+YCdgY2AditD57xRrCn8P+GFmLu2mLkmSJEmSJEnqxkAHvQCZeTdwWLm1e8xoa+mSmQuAo8qt3X5/B/yu3faSJEmSJEmStCIM8hq9kiRJkiRJkqQ2GPRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsVN6ncBkiRJkiRJ6t7Mj53T7xKWcfjWQ8wZoJrmHbNHv0uQVghn9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFGfRKkiRJkiRJUsUZ9EqSJEmSJElSxRn0SpIkSZIkSVLFTep3AZIkSZIkSZL6Y+bHzul3Ccs4fOsh5gxQTfOO2aPfJbTNGb2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEGvZIkSZIkSZJUcQa9kiRJkiRJklRxBr2SJEmSJEmSVHEDH/RGxPoR8eWIuCUiFkfEPRHx04h4VY/9TouIz0bETRHxaEQ8EBHnR8R+bR7/LxHxm/K4R8t+PhsRU3upS5IkSZIkSZI6NdBBb0RsA9wAHAo8B3gcWBfYE/hVRHysy343Aq4DjgI2B5YA04BXAv8XEV8b5fiTgDOB3crjlpT9HAVcFxEbdFOXJEmSJEmSJHVjYIPeiJgM/ARYB7gW2Coz1wDWAo4DAvh8RMzusN8AfgBsCswDXp6ZU4GpwEeApcAhEXFgk+MPAQ4s230YmFIe/3LgNopA+syOvlhJkiRJkiRJ6sHABr3AwcAmwCJgr8y8ESAzF2TmEcDZFGHvFzrsd2/gpRRB7T6ZeWnZ7+LMPBb4StnuMxGxcv2BEbEKcHT58MuZ+V+Z+Xh5/KXAPkACL4+IvTqsS5IkSZIkSZK6MshB7wHl7emZeUeD/ceWt9tFxGZd9PvrzLyuwf7/oghr16dYyqHePwPPKvcfN/LAzLwW+PWI80iSJEmSJEnSuBrIoLe8oNn25cNzmzT7HTC/vN/Jhdl2a9VvGSrfWD4cGfTWjr2hSfhc3+/IYyVJkiRJkiRpXAxk0AtsQbEsAwyHrsvIzKXAzeXDLdvpNCKeRbHmb9N+S39s0m/tcTvHrhcR67ZTlyRJkiRJkiT1YlCD3hl19+9s0a62b0aLNmPZ74wR+1sd20ldkiRJkiRJktS1yMx+17CciNgfOK18uFJmDjVpdxqwP3BeZr66jX53Ai4pHz4/M//apN3ngCOBP2fmZnXP/xl4PvC5zPxEk2OfD/y5fLhTZl7WoM1BwEHlw80Ynpms5a0L3N/vIlRpjiH1wvGjXjh+1CvHkHrh+FEvHD/qlWNIvXD8tLZJZq7XaMekFV2JIDNPAk7qdx1VEBFXZeYO/a5D1eUYUi8cP+qF40e9cgypF44f9cLxo145htQLx0/3BnXphkfq7k9u0W618nbRCuq3dnw7x3ZSlyRJkiRJkiR1bVCD3vp1bjdo0a62764V1O+dI/a3OraTuiRJkiRJkiSpa4Ma9P4JqC0e/IJGDSJiAsX6tgB/bKfTzLyP4TU+GvZb2rJJv7XH7Rx7X2a6nkjvXOJCvXIMqReOH/XC8aNeOYbUC8ePeuH4Ua8cQ+qF46dLA3kxNoCIuAJ4MfCNzDykwf6XAZeWDzfPzLYuaBYRZwL/AvwyM1/bYP+GwN+BAF6TmefW7XsdcA6wFNgoM5ebsRsR5wKzgTMy81/bqUmSJEmSJEmSejGoM3oBTi9vD4iIGQ32H1HeXt1uyDui39kR8cIG+z9EEfLeBVwwYt/5wL0Ur9vhIw8s+/vn8uFpHdQkSZIkSZIkSV0b5KD3ROA2YCrws4jYEiAipkbEF4F9y3ZHjjwwIrLcjm7Q74+Byym+9rMiYsfymFUi4nDgA2W7/8jMJ+oPzMzHgVqfH4yIwyNilfL4lwFnlf1ekpk/6+qrliRJkiRJkqQODezSDfDUDNnzgXXKpxYAUyjC1ASOzMxjGhxX+6I+nZlHN9i/EXARsGn51CJgVWBS+bjhchF1x58EHFg+fBJ4vKwL4G/Azpl5Z6NjJUmSJEmSJGmsDfKMXjLz98BWwFcoAtRVgAco1sndvVHI22a//wC2BT5PceG3ScBCiqUa3tQq5C2PPwh4c9l+UXn8n4DPAdsa8kqSJEkaFBGxXUS8ot916OkvIqKd5yRpRaq9D0XE2k/396SBntEr9SIiXgLcm5nz+l2LqikiIjMzIiZn5mP9rkeDIyImZuaSftehZ5aIWB94IDOf7HctGmwR8QLgzsx8qN+1qP8iYlWK5efmZeY3ImJCZi7tc1l6Gqr937m8vzNwB7AoM+/tb2WqkrrfwV4IrA/cAtyVmY/0uTRVVN2Ymk2xDOxHMnNBv+saLwM9o1fqVrlm8ikUazxLHav7x2Av4MsRsVa/a9JgiIh/B46JiMPKPyhJ4y4ingOcAKzU51I04Mpw5QfA2v2uRYMhMxdTBCXviYhphrwaL3Uh77eAw4D/AL4WEWv0tTBVSvk72B7Ad4E9gR8Br+9vVaqycky9BNgfOO3pHPKCQa+ehiJic+CzwFGZeX1E+EuxOlb+Y/B64NPAmZn5UERMiAjfN5/BIuLdwNuBnwKfAHbrb0V6uqv7aNk84LkUvzhLDUXEVhQXKn5PZt4SERP7XZP6JyI2qf2hOjO/CVwFzC73+f8ZjYuI+AzwaGbuBzwP+ENmzvd3MrWrnMl7JPBq4DxgCPh1uc/3LnUsItYEPgXsBFxSPjep1TFV5g+JnjbKEG4isAWwIUUYQ2Y+6T8I6lRErAa8AzgAuDoi9gFOB94dEdP6WpxWuPL9ZSbFL8h7A/8EXAP8V7nfmSoaLxMAyhl4nwSmg+sdallRWIXiF5iXALsDZOYSx8ozR0RMrIX7EbEx8BPguIg4MSLWBh4BXgxPvadI42EI+F45q/e6zPxMOS5fGREr97k2DaCI2DgiNqt76nHgmxQTKj4F/Etm3hcRrwGe3Y8aVXkLgGMo3p9OAMjMoafrH8QNv1R5dX+JWSUzl2TmWcD7gCz/okxmLjXs1WjqFmhfHVgMrAscS7EMyLYUF4N8MeDi5s8A9eFI+QvxXcDfKf7DuTfwhjJE+RDwmv5UqaebiNgwIl4eESuXv/RcHxFvKGe3XAXsExEvq308Vs9stf8DZeFx4NsUs6C2i4h31Pb5f6Cnv3Id3tcCG0bEG4D9gH8FvgisB3wG2A54f0Ts0q869fQy8g9J5ePVKd6LHsrM95a7vga8LjOfWMElqhoOBX4aEVuWj9eheO/6KPCy8hMqO1MEdC5LpFHV/V7/ivJTum/IzN8C7wK2iIgvQvEH8T6WOW78T58qKyKeVV4kaygi9gTOioj/LyI+mpm/Bk4Enh8Rx4IzF9Ra3Zq8rwM+ThHmvgn4HfCfmfkfwFeBbSj+86GnsTI8eU95/x0R8YUyRNkCODAz98rMxyLiTRSfHriuf9XqaeZg4HPAjhRrap4IvIzhdepuAt5Yztzz/3HPUHUfxx+KiNdGxLfL/+/8c2aeCJwF7BURB5ft/D/Q01y5Du+WwNkUnza5ITP/mJl/ysx9gS8DXwIuBzbvW6F62qj937m8/+qIqP0f+XsU68n/KSJmRcRxwEbA4f2rVoMsM48AfgV8OyK2zMxLgC9QLP2xd0QcAvwPcERmXtvHUlURdb/Xf43iuk0/KP8AfgXFpJ2dI+KEPpY4rsIJIaqi8mP1XwQmAmcAnwdOAh4t75+TmR8oZzTsD3wi///27jvOrrJa4/jvgQABQhWkKFUFUbioiCBFUJAiLVQrvUiXYkSKEFAUpQYERIogoqjUEIoISucq7dJREEHpIL2H8Nw/3vfAyTgzScjM7CnP9/OZz8ycs/fMmpOTc/Zee71r2X9vKNwYIOqbwY+BneoVv/b7NqFUSR1k+6Im4ou+JWk0sAfwN2CN2l9uFspJ8uPAY5TE75a2724qzhgcJM1r+4n69Y8pCZvDbV9Tb1sK2JxSkfch4OO2X20q3mhOfR06DrgduJZyMeDXwPTAdyj9eX8jaVdKf8OdbD/SVLzRu1QGNY60fZSkhSg95F8Atgceqgng9gvaa1LawKyZCfbxXnVI8p4KLAU8AcwO7EipIt8CGE5ZMr1ba5n0YK2gi/emw3PpZ5TVk1vYvru+j32K0nbmQttXtG8f0ZXavujXwJcpK3MPBta3/Vi9f0XgLdt/aSzIXpREbwxItZfK2sA6wOLAL22fXu/7AHAp5SDjVmA22082FGoMELXH6lhgNHA1ZbLrasDDlAqYXwFn2x7bVIzRt+rJ8BnAy8DirROTWu27LqV/2D22H24uyhgM6nvaL4Efti4aSDqCUnV3JPC/tYJ8WD1RHgtcaXtMc1FHU1T6xG8GrALMCxxp+7J631qUpa1rUS5+z2D73w2FGn1A0vyUnpUP8+5qzb2ARYFjbF+j0mN+Jtv3SNqAsnJptSR6Y2pJ+hawtO1tJH2Qcny0FTASeLo9qZskb3SmXqya0/bN9fujKO9vm9u+p9HgYsDoeAGgvjfuT7kg/i3KxYP7JW0D3Gv7xoZC7RNZ8hcDTv1PPAG4DLiQsjRoB5UhJNh+FLgNGG779SR5Ywr8G/gKcC6wOiXBtyylcnxr22M79iKLQe1K4COUC0d3SZq33v5p2xfYvjRJ3ugJ9T1tK+CN2oJomrqM8V5gT2A5STPYfqvuch+lB2IMQbZfpLxP/QFYhFKt0vInSqXv9LafSpJ3cKsXfx4DHgSuAfa3/Vh9/XgM2F3S/pTnxfC62whgmyR5471oPw6WtBFlcPHL9abHgfOAR2i7QN7aL0neAJC0sKRl69cbAJcAJ0m6WNImtveiJOfOkfTxul3Ov6JLtUf98vXrT0n6GvA8ZXXcjynD/O6X9FnKhdBB/3xKojcGlLZlZ7PZfqtWsOxDSdAdLWl2SUsAK1GWeER0qq1B+3z1efUCcBrlZOlw27sC44AFgTmAN6H0+2ko5Ogjkr4haTtgK9sv2d4NuB74q6Q9gLMlZeJv9Cjb4ynvW6sAJ9TXpVGUZO8BwIq1L+98wJKU5dkxhLS9b01v+zlKH8yDgHkkjaqbfRT4NDBDM1FGX6mvEa05FbsAOwArSBoDUI9jrqcspd/N9q1119+kSi7eq7Yl9itSLohfBnxc0touQ7GfAmalVJn/134RlLaK50tah3KhclPby1AuSK1be/TuAdwAzAZ5/sQkfRBYRdLvgbOA/6vtzX5JeR4dImkLSqurfW3f0FyofSOtG2LAqX1UD6Q00v6r7V+pTA/+AaVv4U3Az1rLGCM6artgsC4witKD9WHg57afrtt8Hjia0t95XHPRRl+StDvloPNUytLWP9puDWUbDSwM/CQnydET2l6L5gams/1YrRy/mNJ6aId6/1HAWbZvqfuNsP1yNz86BilJa1MG9t0E/Nn2DZK+Tum5+gKlR+bPbV/cYJjRR2qLoR9TBhRdUVs0XARcXm9zW8sXQRImMfUkfZSSPPk0MJ7ymrQ0cBelrdVngfVsv9lYkNGv1WPqrSjDjDe3/ZKk6Smzdx6rF6oiJpukvSkznM6krMS1yuDaD1P6hT8C3Gr7j0Ohz3MSvTGg1GUeP6RcqZmHsqz+StsnSloZ2Bb4aavHT0RHbYmVtSlN2Ternz8J3Ah8H3gNOJHS+3ncUHgzCJC0HqUqam1KT6cVKVUp99jevm4zg+03mosyBpu69HUfYE7gqPp+Ng+lNdEDlBOgVgVV+hsOYZKWp/RsHkcZdLQIcHxN8G0FbEDp83xTc1FGX5J0AvAH2xdKmrH28v4IcAWlvce3bb/dbJQx2NS+8mOAsbYvl7QYsA3weeA22zvW7Ya1tRyKmOg4RtJ+wK6UAosb6wWpL1MuFIyiDMrK+Vd0qe28/v2U4+jPU9ruvQacZPtf9b5nh9pr0bCmA4iYXPXA9TBKVdPptQLqEWBkTb4cI+ke2/9pNtLoj1QmUS9g+7raz3kjysHFxyn9ew6jVCQcQplavp3tF5PkHbw6HGzOQelruQuwJaVH8xrAdsAxkt62/U1qC4+IniBpdsrzbRfKxcvj2t7PRlKWxC4J3Anv9PKNIai2pToEGF2rUT5MSezuLGm6elx0ee3XGkNATbYtRunZDaWyEsoQvj2BZ5LkjanVfhwsaRnbt9ieIOmfwGGSrrH9d0knUY6R5qttHC4daomV6Frb82ie+p71sO0fSpqZUlzzO0n3Us7Hdq3trCK61GGF7haUlgwnStoYWAfYRtLdlPk7ewMPNRdt30uP3hhIPgC8DWwnaa66xP5SSgP3L0haMEne6ExdrrgOcLqkz9eKzN0pS1xHAevb/jXwJDAjMK/LsJsscRyk6gny1pLWkPQN4KeUwTX/olR3H1mXHJrSwuFHkOdDTL22PqtLUarHb7Z9c11q/01K4m4f208An7F9Z4PhRj8gaRpKwn9BylJXbD9AGXp0C7CrpPclyTu01As/pwDrSFqtVsOtQBli9IDta1qvNxHvRb0g3krybgQcKum8usLyN5SeqisA2P4npR/ma8D8DYUc/VCHhNw44FhJ41T6ze9PWam7P6WS96u2L85rV0xKfU6tRWnfebjtf9TbzwXOoFT4fh843fZDjQXakLRuiAFF0nKUCru3KZOFn5H0PmCGnOBEdyTNBWxOGQCwj+0/1eXRZ1OuHj9KuaK8cxIrg5+kYcCqlIPLF4BPuDTtR9KBlGrvEyjVlqvZfrChUGMQUuk1/1PgKUol71cofcPG17YyPwdWBh7OxYWAdyZKr0F5H7vT9iH19kUp5zv/bDK+aIakWShty0YBfwCWA76THs0xtSTNCqwH/J5SIf485ZjpYGB6YDVgJuB823u27TeP7Sf7PODo1yStBhwBbAysCRxPGRa5Rm05Mxq4yvZVjQUZA0a9AA7wC+Bq4HzKat2NgAnARvXi5zy2nxyKK3ST6I0BocOyoc9RTopnAfaqlb0RnZI0je2324aRfJvSC6qV7D0M+ASlUftetsc2GW/0ndrT8juUpYajbV9Qb5+OkuBdGjjRGbwWPaj2MjwEOLAudz0DEHAcZUrw+FqdmRUqMRFJM1GqwDcGHrK9X8MhRT9RVwjMALxu+66heFIbPUtlsN+3KCvi7rO9ftt90wBrAV8EVgG2p1ysdNs2eQ4GAJJmpFyQupLSP3UfYEPgz8BzwFquA2bzvInJIWl+lwHG36NUgs9OWeV9J/BV4DDb/9dchM1Lj94YEGppvlxcU5ddfx2YF0iiNzpVnzNv16VCW0r6GnAqZTn+TyTtaPu7tX/vLDk5Gjok7Qx8jlLhvSBwgKQ5bZ9GqZq7zPYpTcYYg4+keSltQBalJGWgtGs4AfguZVrwXygnPhETsf2qpEuB6YBNJH3E9v1NxxXN67gSKccxMbVsP1RXP80OPF77qo6v970NXCLpOuBYyjG0O+yf5+AQ1iq0AagVu2dSLmr/hDIk8ilJvwF2oPQav7Vum+dNdEvS/MA4SYcCh1Paxzxu+15Jn6C0unqtwRD7hfTojX6v1aOn/YXf9p8pS9OyxD661KF3zxm2x9t+DjiNsvzsTEmr14EAd7X2aTDk6AOSdqA07d+rXu39G6V9x+6SzqIk4mbo+idEvDe17+6vKK1i1pK0iO3XgZ0oB6Vv1O0yQGmI66o/YW0xM5YyrCZJ3ojoTQdRlkK/AZxQW4UgaU2AOs9iOcoKqAhUBl5TC21WlLS7pI8Db1EGRs4HTC9pRWAZ4Iu2b20u4hiAXqEUSHwH2MD2n4D76jn/WcB3bf+tyQD7g1T0Rr/R1qh9oXrTf2y/3DHx1pb4fbb9amFEu/o8GU5ZvvEd25e3qhFsPyfp55Rk3pC/4jeU1APQ1SlXgGeQtA+l7/c9wNaU/peHtBr6R7xX7RcpJS0BzE0ZvHa+pAmUVSkTJF1o+x+SNs+FpqGr7RhoNuBN212+N9Vk76t9F11EDDX1NelZ4Lra0uqrwPGSXgVmlHQFMCtwpu0xTcYa/UNdtbSNpN8CCwAnAfdT2jScZfsUSedSZhQIODgJuZhckj5m+x7bL0j6PeUC1ChJb9Zj608Ce9q+vOFQ+4UkeqPfqCc461P69jwFvCTpWNs3d9h0GtsT6snQPpK+390JUQxNNWHyWj04XQy4vLXkrPZ5vtv2YU3GGH3P9huSrgaOAu6iTP/9EqXK+znbezUZXwwebX3l16VUjN8FfFDSD2yPlfQ2pW3DMEnHAa83F200rR4DbQjsAswhaU/b13TcTtK0bcdAWwI/zQXviOhpHdrm/VnSK5TjpcWBzW1PoLQZ+iFMvFQ/hqwFgOUpQ/oWBDaubfF2Br5Yn04/qsU209t+PC3zoiuSFgTWtH2ypJmBMZIes71lTfaOo/TnHSPpLUpf3jyXqrRuiH6jJt/2BdYHbqIMx3qgffli2wnO7MCFwMVJ8kZnVExLSa4sWJcNUa/2nQIs0WR80aiTgZHAV22fCCwCzEwq5KIHSFpc0pfr15+jtAJZAziXctFpF0lr2x5HeS7+0fZrOTgd2iTNA+wFjKZMuT+1XiRo36b9GOgC4KYkViKit7SSvfXrv9oebfurLsONh3XYNq9FQ5ztmyjt8hYBlgIWrrefQBm8NlLSjsALth+v9+XYJ7qyJLC3pJ1tv0LJE80l6USA2o7xNuBiSrFOnkttlMcj+gtJ61EqmmalVPVu5jII4DPAHcD4tiqW84DRtq9tLuIYCGorkB8DIyhLPBan9O4Z12hg0bh6krIVZar019LzO6aWpAUoVeI7A7cD/wO8SKlsafU6/Amlp+Eo2+c3FGr0A23tGhajvDct2loCXSugdgP2q0sS2yt5z6Usec0xUES8Z+3VlJKG157xXW07UcVuKjGjpb39ou2HJf0PsD/wAPA727fX7XYBbrB9W5PxxsBQq3hXBw4ATrN9oqRPUS4mvEHp03s0sIXtW/OaNLG0bojGSfoi5YrfHJQemY8A69t+QqXZ/yHAJrb/XatYLgb2sX1dQyHHAFEPSh+uBxaLAnNSpnLekTeDAKYH3gY2tX1f08HEoLAs5YLlc5TKzGMorYj2Ao6x/aikscC8wN8bijH6iXpivB5wJGVQzRuSrrB9t+0Tak/xoyVdZ/tpSXNQLnR/L8dAETE1OiR5jwRmlvQEpdXZDZ1s+3b9elXgQdv/6uOQox9qS/KuB+wlabd6njWG0opoU0nDbN9i+/iGw40BoO21aVrbF0qaBviuJGqyd3tgDKX92QGuw/xyXj+xVPRGoyR9jNLbaV/b90q6AXiBMqTms8ChlP/A4+r2q1L+H1/dTMTRn3WWvE1CN7qTnnLR0yQ9AMwDrGX7eknDKQnfJ4B/ANtTVhXc0PVPiaGgVvL+mDI5+j/AGZTBNSfbvrdus5Dth+vX2wP/cJkwHREx1SQdTxmMdQZwGbCT7bPb7m9PCH8D2InS+iqJ3gBA0hqU1Urb2r5F0izAm8AHgSOA+4Af2n6pwTBjAGi7cPAl4HvAOpTWemsD3wXOqK1AkDTC9ss51+9cEr3RmHqCcwPlhGbfettswPnA88AMwPG2L2nrD5UnbLyj7c1gklPK69Xkt/owvIgYQmpP8BmAP1IGkfzb9vr1vq8Dq1F69B5h+4Km4oz+obYVOhqYG9jQ9jOSFqZUqTwOHGv7nlyMioie1CFx+1Fg9/rxU8qx9O6SZgUMvNy27deAPYCtbd/dSPDRL0iaD1jW9tj6/WjKitzrgFWAL9dNtwbmA163/X99H2kMRJJWoxRI7G378nrbDMBalCLA02wf1VyEA0MSvdGYWob/C2A9YDHbz7TdNz0w3PaLTcUXA4PappQDmVIeEY2SNKPt1yRdCbxt+4v19hEAqT6IFknbApsDZwHn12TvopS+c3vZvqdt2zxnIqLHSFqH0mbom8DswP22v13v+xkw1vYl9fstKJW827a/LsXQU8/fv0oZgvWE7Wcl7UYZpj4H5dz+YUrCd2x6ycfkqoV901Cqw2+x/ev2Qq16/8aUNozXNxjqgJBEb/SZturL9wPYfqrefgqwMrBK7cvbSsrlpCa6pTKl/BzKFM6VgG0pyd5xbdu0Tyk/nzLY5sYm4o2Iwa/tvW5O4NfArLZXaDquaFbb82J54APAM7avlrQNZdjIFcBFtRdvt0ORIiKmhqTvAfPb3knSFZSCmwXrfT8CPgWsY/utuvrgQuAbtu9qLuroT+r5/A+B62yfLmlp4AWXQepLAr8FtrJ9U6OBxoAj6XBKO5n9bL9Zb1uTctx0S6PBDSDTNB1ADB31BGdtyjC130i6StJHbG8HXAncLGke2xNa2zcZb/RPrTYetfXHZ4BzbF9n+zDKMtjDa5Vvx0rec4ADk+SNiN7Ueu+y/Syl6uVNSZ9pNqpoWj0GWo9SrbskcKyknW2fRlnuugGwoaTpKL0NIyJ6nKSjgYUoRRIAmwAvSLpG0jjK61MryTtt7RG+cpK80SJpJUrP1H8Cn5e0pe3ba5J3I+BsyuD0JHnjvbgHmAtYTsX/AEdRhqrHZEpFb/QZSctSGv3vBNxE6QW1ADDS9iu1svfMDFqLSVGHKeWUKoO76317At+i9I7KlPKI6FWTWn3SWnaWVSpDm6TFgROBjYA1Kb0uN7H9aL1/Z+BG27c1FmREDGp12f1plIuQn2y1YahFFJ8FXgdur0US01LaDznvX9EiaQngJEorvEcp7fOWBq62/Yva5uNR21c2GGYMYPW15whgEWC2+jG61RM6Jk8SvdFnasn96rZHtd12NXC97f3absvBRHRJmVIeEQ2awiGQ07ZWqcTQJulDwFcoPTG3pEytf1DS+sA/bd/ZaIARMeh0dU4l6VRKD9WVbD/Ryf0ZAhn/RdIngd8DR9s+vt42O+U9bUVKT95fNRdhDHSt15568WkRYBbgFdsPJEc0ZdK6IXqFpJnrFT8krdj6GthS0iJtm/6WMl36HfkPHF2pfcIOoyzneK4ujd4N+BDwLUkfq5v+u7WP7ZOT5I2InlKTvBsC5wLXSfpcZ9u1t46RtHutpIohQNIISR+vX68qaWVgZmA1YCveTfKuShk6MkNDoUbEINWeFJF0hKRjJf2+zrfYDrgcuFLSfB33TZI3uvAI8CKwQ+sG288DvwT+AuSCZbwnrdaMrSSviwdrS5AHmo5vIMpJR/S4+h91AeCg2gdqDDCj7T8ApwLn1BOf1SltHO5tLtoYSGqV7sXABEovw7lsPwTsCSzctt3b8O6bRkRET6knyXsBoymVLadKWrfDNu1DIC8AbsqJ85AyP3CMpOOAk4HXbN9BGbj2FrCxpN2B44Fv2765uVAjYjBqS/KeDCwKnEm5qPQr4AO2dwbuprRCi/gvbXNR5pI0r+2nKcNDX5P0zjJ6288BY2zf3lCoMUC0PacWqh8jYOJCv7bXrmHt+6QYcMqkdUP0GklHAt+kvPDvX/+TzkbpS7ca8ALwM9vjmosy+rO2JdKZUh4RjWl7LVoMWBxY1PaYet/OlJUF+9k+XxMPgTwXONj2tc1FH32lPj9esP2kpFHAocBRtr/bts32lIvhw4ArbP8pyxEjoqd0qOSdj3KxaaTtt+ptvwNmtr1OPTdTLkRGV+pclFGU/s1PArsD0wK/o/RwXr3B8GIAqi2r9gGeAl4Cju14wbvDsfQ+wPe7a5UW/y0VvdGj2q7SLE85GT6CMo1zm1qC/7zt0bZXpgwhGZeqy+hKTaxkSnlENKrttWgcpUf4Vq2l+bZPAH4OHC1p7npgOgelknd0krxDyjzAErUK5VLKyfEmkraT1GrP8GvbB9rer9VWKEneiOgJkmZsS/IuShlYvDTlGLplH+CZtuXRb6e1UHRG0heAg4BvUFp9LA1MsP0MsBkwQtKnGwwxBpja7mxfYH3gJuDDwAPt+aAOq+IuBC5OknfKDWs6gBhc6snw+pQ3hb1tXyXpH8COkl4B7gC+D2xLuYKTE5zoksqU8j2BL1CmlL9KecHH9gn1PeEm2+MbCzIiBr1aqbkNsA7vDoHcVtLJtu+1fbSk8+qyRoBNKNUH1zUUcjTA9rWSZqVMIl/O9hhJjwKHU5a6vgzspDKV/Okc/0RET5E0I7CXpPuAFQBs7y3pDOAkSVvbvgfYFRjeYal0KnqjMx8EdgaWohzXbGD7RUnL2r5J0kqtSvGIyTQbcCCwKjAS2Mz285I+I+kOYHyHVXHfs319Y9EOYGndED1KZRjW2cD6th+StBTlis2dwMHATMAo22O7+TERQKaUR0TzVIZAHg3MDWxo+xlJC1P6zz9OWXJ2jzKlPCqVYX0nAMvbfljSJpST5emBY2yf02iAETEo1deeXwD32V6+3jYXpa/8dsCfgdmBdWy/lbYx0R1J36a0aniEcm7/jKQvAj8ANgIey/MnJkd93iwMzAFsTXlObW77CUlrAodQVnv/u1byXgzsk4KJ9y4VvdHTxlP+425aDyzmB9YGTqH05Z3H9r05sIiOajP2hWzfrTKJfAKlj/NqwAjgK554Svk3mok0IoaSmqi7GNic0irm/Hohc09KMq+13TtDIPP+NrTVXs3jgVskLWP7HEk3UJa8PpnnSET0lA6vJ58G7gKml7SZ7d/VZfb7STqV0rbxwVoxN63tCU3FHf1L2yyC+ShD1B+kXDT4LPBqW5L3cEqV5aNNxhsDRy0E3AXYt+aBRlIG074paR3KPIMDbP+77vIJytyLJHmnQip6o0dJmolyxXgzSjLuImB5SquGHVLtFF2pS6OPB+4D1qJU794saT9gXeB8Sq+xb1Ku8GWIX0T0uLaTnQyBjKki6UvAecDith9uOp6IGFw6DF47kVIkcRBlWfQo4ETbZ0jai/K+dX/dNitQ4r/UBNyhlMFr/wKOq3ftDryfch52hO2Lc8EyJkc9v78BONn2vvW22Sjn9c8DMwDH276k1ac3z6uekURv9ApJ09keXxtuHwfsn8RcdEaZUh4R/UwdvHYwpSf4RsBJtS/4zpR+4RdTKl0m5GQ5ulOfS6/ZvqLpWCJicJJ0HDCL7a3q96sAcwKjgWcpA4u/lAre6IqkDwPfo6xU+j/KQPUZKVWYT9eVum/Vfqo5B4vJUgc9/gJYD1isrjBo3Tc9pV/4i03FN5gl0Ru9ok6c/iTwU+BQ22PzphCdkbQyMC1wHfBRSquG3YDDgDNtvyFpZtuvNBhmRAwRdQjkiZQE75rAHpS+YY/W+3cGbrR9W2NBxoCTY6CI6A2SZgHOoqyKM+V9a0vgKmB/yhDRY2tP3lTyxn+pSdwngTNsb1NvGwZcDVzbXnwT0Z22VXHvB7D9VL39FGBlYJXal3fa2kImx0a9JIne6DWSZqb05H0w/4mjO3VK+f2UKeUP1cE1hwMHAC8DOwGZUh4RvS5DICMiYiCprRm+DVwKXABcD/wO+LLt/9Rt0pM3uiRpbeBcYCnb/6i3bQPMZ/vQRoOLAaU+lw4BXqQUc21v+35JJwDrA8vYfrLJGIeCDGOLXlMrMB+sXyc5F12y/aKkHYEbJS1fB9fAxFPKn2o0yIgYdDIEMiIiBoExwAV1gBaS9qcMyH62tUGSvNEd25dK2pRyLvZd4DFKC6sdmo0sBhJJywJHUoq0bqKs7j5B0kjbO9d2DR+lVJBHL0pFb0T0G5LWBU6nXOl7WNL8ZEp5RPSSDIGMiIjBoA4ymoWSnFsSWDvtGmJKSVqTUhl+OKWVwz05B4vJVZ8/q9se1Xbb1cD1tvdruy3PqV42TdMBRES01CTKFsDfJC1k+7HW0o68GURET5G0mKR5bP8duJySyD3X9s0Atn9IGR4xCzAvsJvtca2JwBEREf1JPU6eQJlw30ryTpskb0wJ238A1ga2Ap5uNprozyTNLGmJ+vWKra+BLSUt0rbpb4HH2/fNeX3vS0VvRPQ7mVIeEb0pQyAjImIwS0/emBqSNqIcE33c9vim44n+pRY+LA6MpiRxVwZ2sH2rpB8BawB7U1rFHg3smfP6vpVEb0T0W1nWERG9JUMgIyIiIjonaYTtl5uOI/ovSUdSVsWNsb1/TQDPBuxBKaJ4AfhZWp/1vSR6IyIiYkiStCFwArB87Qu+CRMPgTyn0QAjIiIiIvqJViGWpOUpxRE3Uyp4T7F9Wodth9t+PcVbfW9Y0wFERERENMH2+ZLGA7dIWsb2OZJuIEMgIyIiIiImUpO86wMHAXvbvkrSP4AdJb0C3AF8H9gWeKm1T2MBD1Gp6I2IiIghTdKXgPOAxW0/3HQ8ERERERH9jaSPAWcD69fWZ0sB6wN3AgcDMwGjbI9tMMwhLxW9ERERMaTZvkTSpsBHgCR6IyIiIiL+23jgEWBTSXMB8wNrA6dQ+vLOY/verIpr1jRNBxARERHRNNsX2b6iDpKIiIiIiIiJPQpcBmwAXE8ZXLweMBfwvO17Ie0ampbWDRERERERERERETFJkqazPV7S54DjgP1tj2s6riiS6I2IiIiIiIiIiIhJkjQM+CTwU+BQ22PTrqH/SKI3IiIiIiIiIiIiJoukmSk9eR9Mkrd/SaI3IiIiIiIiIiIiYoDLMLaIiIiIiIiIiIiIAS6J3oiIiIiIiIiIiIgBLoneiIiIiIiIiIiIiAEuid6IiIiIiIiIiIiIAS6J3oiIiIiIiIiIiIgBLoneiIiIiOgxkk6X5Mn42KPhOEdKGi1p1Sbj6C2SFu7weK/fzbYfbttu4T4MMyIiIiJ60LCmA4iIiIiIQWk88Gw397/SV4F0YSSwZf36qubC6DOHSLrItpsOJCIiIiJ6RxK9EREREdEbbrC9atNBxDuWBjYDftt0IBERERHRO9K6ISIiIiJicLu0fj5Y0rSNRhIRERERvSaJ3oiIiIhonKRpJG0u6Y+Snpb0pqTHJP1W0nJd7DOtpLUlnSTpFklPtu13vqQvdLLPqpLMu20bDurYP7ht263qbVd1E/fous3pHW5fuP3nSVpe0jmSHpc0QdIxnWx/nKS/SXpV0kv1b9pH0syT+TB25UfAy8DiwBZTurOkz0kaI+kv9bF9U9JTki6TtEk3+7X6NY+WNL2kAyTdW/++f0k6VtIcbdsvI+k8SU9Iek3STZJGTiK26SXtKulaSc9KekPSw5JOk7TElP6tEREREQNZEr0RERER0ShJswB/AH4JrA68D3gNmI/SbuAGSbt2susSwCXADsCngOHAm3W/kcCVkvbtsM+bwJPA6/X7V+r37R89StKXgWuBjYEZgQkd7t8IuBfYFVgMMDBD/ZsOA26UNM9UhPA0cGz9+kBJ001B7COAq4Hdgc8AIyj/NnMDawK/l3TSJH7M9MAVwPeBhQEBCwC7AZdLGi5pA+B6yr/b8PrxaeA8SZt1Edt8wF+B44CVgNmAN4AFga2BW+tjGxERETEkJNEbEREREU1rJXhvpSQPZ7I9GzAncAAlMTpG0ood9nsTOK3uM5vt2WyPAOYBvlf3O7S9Itj2Dbbn5d1etUfYnrf9oxf+vlOAC4FFbM8OzAQcAyBpWeBsyuyMQ4EP2p6ZkhBeAbgZWIryGE2Nw4HnKYnW7adgv7eBc4ANgffZnrX+28xBSUy/DOwgadNufsbOwEeAdYGZKcnikcBLlGTuaOAM4Cxg/voYvZ/ymAk4RtJEs0VqsvpCSu/hKymP1XDbswLzUx7f4cCZkj40BX9vRERExICVRG9ERERE9IYV6hL8zj5+0dpI0uqUpN/fgC/Yvtz26wC2n7N9KHAg5bh1oupc23+3vW3d58W225+y/QPgYEqicMfe/mMn4XZgM9sPAdh+q/U1cDQwHbCr7QNsP1q3mWD7RkoS+3FgDUmffq8B2H4eOLJ+e4CkGSdzv1dtb2r7AtvPtv8828dTkri0fe7MbMBXbF9s++36t11IST4D7APcWv8tn6g//2ng65Rk8HyURG67LYFlKZXSa9u+0fb4uu/jtvcETqIk1fecnL81IiIiYqBLojciIiIiesN0lMrazj7maNuu1Sv3ZNsvdPGzzqqfPz+Fw8Quqp87VgL3tSNtv93xxlppuiKl0vbUznasydXWMLUvTmUcx1DaOMwH7DKVP6ul9Rgv382/zY22r+7k9ivavv5RxzttvwL8b/12yQ53t543Y1oJ3k60njdT+7hFREREDAjDJr1JRERERMQUu9r2qpOxXatS8wBJoyax7UyU/r1PtW6olak7AhsAH6MkkTse484/OQH3ohu7uL31t48AHpHU1f4j6ucFpiYI2y9L+jFwBLCPpJNsvzSp/WrbhC2BTSmtEuak9N1tN5zy2D/TyY+4s4sf/VTb13d1sU2rZ3L70LZhlH7BACdJOr6LfVuJ56l63CIiIiIGiiR6IyIiIqJJ89XPs0/m9jO1vqjDuK6iDDBreQV4jtJbdlpgLkpf2CY93cXtrb99GKXSeVJmmvQmk3QCsBcl+b0HZUBal+owtj8wceuE1yh/U6tKuRX7zHSe6H28ix//zlA625Papn2AXHui+X1d7NdustpURERERAx0ad0QEREREU1qHY9uaFuT8fFQ277HUJK8DwIbA3PaHmH7/XWo2vJ9+pd0wfaELu5q/e23T+bfvlUPxPIaZegbwN6S5uhue8pQuxUoCdwtgXlsz9T2GH+gbdsuS5J7WPs5zCcn57Hro7giIiIiGpVEb0REREQ0qbU0f8Ep2UnS9JR2DQBft32e7ec6bDY5VbLdeat+Ht7NNrNNxc9v/e193VrgFOAhSuzfmcS2m9bPu9n+pe2nOtw/tY/xe/Ef3q30naLnTURERMRglkRvRERERDSp1b927Sncby5ghvr1bV1ss3o3+7faDnRX7fl8/fzBbrZZtpv7JqX1t88pabmp+DlTxPabwCH1293oPlnb+tvfy2PcK+rwtZvrt1P6vImIiIgYtJLojYiIiIgmnV4/rylpre427NBm4CXA9eulOtl2PkoSsysv1s+zd7NNa4jYByQt08nvWBlYsZv9u2X7PuB/67c/kTRdV9tKmlHSDF3d/x78Evgbpa/uvt1s90L93NljPALYvwdjmhKn189bSVq6uw0noz1FRERExKCQRG9ERERENMb2ZcB5lMra8yWNkjR3635Jc0oaKWkscFTbfi/xbpL0NEmfqNtPI2k14Gq6r9a9u35eqyaFO4vtYeCv9dvTJS1Vf8d0kjYFLqAMfpsauwNvAJ8DrpS0kqRp6u+ZVtJSkg6k9CHuNM73ovYNHl2/XaebTf9YPx8laRVJqrEtC1zJ5A1D6w2nUv79hwN/krS9pFlbd0qaV9LXJV0NfKuhGCMiIiL6VBK9EREREdG0LShJ0+HAT4AnJT0n6UVKP9bzgfU62W9P4DVKteltkl4GXgauoCQgt+3md54PPEsZ5vaIpMclPSTpoQ7b7V5/x5LAHZJeqr/jd8BNwAlT/Ne2sX0TsCGlcnZl4FrgVUnP1N97B3AwMC/vVjD3lN/Wn9+dAyiD2BYArqqxvUxJgC8FfK2HY5ostX3DBsD1wJzAz4HnJP2nxvc48CtKAr2nH7eIiIiIfimJ3oiIiIholO1XbG8IrEup7n0MmAmYDniAklTdmg6tGGz/Bfgs71bWTgc8BZwEfAK4vZvf+Qzw+fr7ngbmBhaqHx1/x0rARZSevcOAvwOjKJWwbzGVbF9KSTj/ALiVUuE7O6W9xA3AYcAytcK4x9g28L1JbPMg8BlK0vQpYFrK43AWsKzty3sypilRB8OtAnwduITy7zhLvfs+SnuKzSiPX0RERMSgp3J8FxEREREREREREREDVSp6IyIiIiIiIiIiIga4JHojIiIiIiIiIiIiBrgkeiMiIiIiIiIiIiIGuCR6IyIiIiIiIiIiIga4JHojIiIiIiIiIiIiBrgkeiMiIiIiIiIiIiIGuCR6IyIiIiIiIiIiIga4JHojIiIiIiIiIiIiBrgkeiMiIiIiIiIiIiIGuCR6IyIiIiIiIiIiIga4JHojIiIiIiIiIiIiBrj/B5IIVENwGLN4AAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAACEoAAAUsCAYAAAAqhuDUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAADRxElEQVR4nOzdd7guZ10v/O9vtd1bGqmQEKpU6VKDBQv4gggiehRERF8PIh4rIq9RUVE49gNHpORYQURARAUPEkCxgCBFIRKSQDrpye57r3W/f8wsstystXbJzlrJvj+f63quWc/M3DO/mXnaeub73FOttQAAAAAAAAAA9GBitQsAAAAAAAAAAFgpghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAKATVXVeVbWqOne1awEAAIDVIigBAAAA3O4WnKA/2O3FR2l95463rUdjeXcUVXXJIe7HA2+XrHbtt7eqelhVvb6qLqiqHVW1a9xfH6qq36iqp1XVhkXaHZOPFQAAAJY2tdoFAAAAAF3Zl+T6ZabvOErr+dlxeF6SG4/SMu8IrkmydpHxW8bxS+3fa8bhlUkuSHLt7VLdKqmqn0/yM0lqHDWX4bifmuRuSb4qyQ8n+ZYkbz+g+bH6WAEAAGAJghIAAADASvpQa+2c1S7izqq19vDFxlfVeUmek4Ps39baS5K85HYpbpVU1bOTvGy8+6dJfjXJx1tr+6tqMsl9k3xjku9epRIBAAC4gxGUAAAAAODO7IfH4btaa89aOKG1NpvkU+PtlVW1WG8cAAAAdGZitQsAAAAAOFBVPbeqWlWdv8w8547znLdg3HlV1RbMdvE4T1tk3vPHcc9dZh2XjPOcs9S6q2qiql5YVf9SVTeO4x98wPzfXFXvqKqrqmpvVX2xqt5ZVV9/aHvk6JjfP1V17gHjz5zfR+P9R4z1XlNVt1TVh6rqmxbMP1NVP1lVn6qqnVV1dVX9blUdd5D137+q3lBVF1fV7nF//UNV/UBVTR/hZj1gHP7lwWZsre1eUMshP1YWtDmxqn65qj5ZVdurase4D35xqW1f+BiqqrtW1euq6tJx+y+uqldV1Zalaq6qp1bVX437eF9VXV9VF1TVn1TVs5ZqBwAAwNL0KAEAAAAcS25KcnWSu4z3r00ye8D0o6mS/HmSp47rueW/TBxO/r8xyXcuGH1zkhOTPCXJU6rqV1trP3mU6zpiVfXUJG/J8L3RzUk2JvmqJO+sqm9P8s4kf53knCS7k7QkJyV5QZKHV9WjWmt7F1nuC5P8Zm794c72cdmPHm/Pqqont9Z2HmHppx3m/If1WKmqxyZ5R5L5QMTeJHNJ7jfevquqvq61dsES67tHhkuDnJhh21uSM5P8aJKnVtXjW2tXHrDOX0zy0wtG3ZJkXZJ7jbcnJnnzoW0uAAAA8/QoAQAAABwzWms/3Fo7ecGoh7fWTl5w++ElGx+Zpyf5hiQ/mGRza21bhhPvF43TfzVDSOLCJN+WZGNrbUuSzWObW5L8RFU9+yjXdVv8nyS/n+SU1trWDCGId2T4HunXk7wqyX0yBD02JtmUIShyS5KvTPL8AxdYVU9L8ttJdiT5iSQnttY2JVmfYf99NkPw4tePoN6PjMMfqqrHHWqjw3msVNXdMgREjkvymiT3zBBY2JChR4v3JDkjyZ9X1eQSq3xVhvDF48Zt35DkaRkCGvfIsN+/pKrOTPJT491fzrDPNrfW1mU4Js9I8q5D3V4AAABuJSgBAAAArKRHj5efWOz2xtUu7ghsTPKi1tpr5ntCaK19sbV2c1XdM8kPJ7kmyVe31t7SWtsxznNLa+01GXphSJKXrkbxS/hoa+35rbWrk6S1dk2GsMfNGXpt+O9JntVae1drbXa8/UWSV47tn7FwYWNw4DfGu89srb2ytXbtuOy9rbV3J/nGJDuTPK+qTjnMen8hQ88OW5J8oKo+XVX/u6q+d7zURx3m8hbzi0m2JnlFa+0HW2sXttbmxtunknxzkk8k+Yok37LEMtYk+cbW2t8nydj2HRkCNEnydWOvFfMekeG7u8+01n56fp+Nba9prb21tfa9R2HbAAAAuiMoAQAAAKyk6Qw9Lix227aKdR2p65K8YYlp353h0hxvbq1dusQ8f5ZkT5L7HUFA4PbyigNHjAGPfxrvfqi19oFF2r13HN7/gPHnJLlbkk+NoYgv01r73Lj8qXH+Q9Za+78Zemb4/DjqPkm+P8nrknwyyZVV9cqqOv5wljuvqtYneWaGMMavLVHD3gzHMkm+bolF/Wlr7cJF2r4vyYfGuwtDJjePwy1jDQAAABwlU6tdAAAAANCV97fWzlntIo6ij7TW9i8x7dHj8DlV9cxlljE9Ds9IcuVRq+zIfXKJ8V8ch59aYvrV4/DAwMv8frhnVV21zHq3jMMzli/vy7XW3llVf53kSePtkUkemOHSHndJ8mNJnl1VX9ta+8xhLv6hSWaStCSfXKaDinXjcKn6z19mHe/PsJ8esmDcPye5PskpSf6xqv5Xkr9trV18aGUDAACwFEEJAAAAgCN3zTLT5nuI2DTeDuYO0WtAa22psMbsODzY9AO/b5rfD2syhBYOZn2SVNUZST68xDxPb619aOGIMbDyV+MtVTWT5PEZLn/ylAyXDfnjqnpoa60dQh0H1l+HU/8iLl+mzfy0E+dHtNZuqKrvSvKHGUIfv5skY9jkPUne0Fp7/yHUAwAAwAFcegMAAADgyM0uM23+e5cfaa3VIdzOX4F6V8P8fnjHIe6Hc8f5J7P0ZVpmDrbS1tre1tr/ba19c5LXj6O/MsmDj7D+mw6x/nMOc/lLaq39VZKzkrwgyZ8muSLJyRku63J+Vb32aK0LAACgJ4ISAAAAwB3R/OUs1i4zz5Zlpt0R1jF/KYq73oZlHAuOaD+01i45iqGS1y/4+16H2Xa+/s1VdVseD6cewrQv66GktXZTa+33WmvPaq2dluR+SX5vnPx9VfXk21ATAABAlwQlAAAAgDuiG8fh6cvM8/Blps1fWqGOdB1VdY8kW5dpfzD/OA6/4TYs41gwvx8eWFWnrVINOxb8vfeAaQd7rHwkQ6imctuO5RMOYdpHD7aQ1tp/tNZekOSfDmG5AAAALEJQAgAAALgj+uQ4PK2qHnrgxKp6XJLHLNP+5nG49RDW8f8sMf2nlivwEPx+hpPw962q719uxqradhvXdUf23iSXZriUxiuXm/FI9kNVfW1VLReISZLvWPD3vx0wbdnHSmvtliRvHe/+fFVtWqaWqarauMTkZ1XV3Rdp8/jc+lh+y4LxB7u8yK5xuOYg8wEAAHAAQQkAAADgDqe19vkk/zLePa+qHpAkVTVdVc9M8vYkNyyziH8fh99dVZNLzPNnGYIMD6iq36yqreM6Tqqq30ryXUl23oZt+I8kvz7efXVV/XJVfan3iqraVFVPqqo/zIIT5Mea1tq+JC/MsK+fXVVvr6oHz08fj+nDqupXk1x8BKt4U5JPVtWPV9UDqmpiXO5kVX1FVf3vJD8xzvvO1tqB6ziUx8pPJbk+w2U7PlRV31BV0+N6qqruWVX/I8lnkjxsiWXsTfLXVfXosd1EVX1zhsdhkvxta+0fFsz//1bVu6vqO6rqlPmRVbW1qn46yTnjqHcvsT4AAACWICgBAAAA3FG9KMOv5u+f5BNVdUuS7Un+NMmHk7x6mbavG4cvTrK9qj5fVZdU1avmZ2it/XuS31iwrhuq6oYkVyX5wSTfn+Sa27gNP5HkNRm+g/mpJJdW1U1VdWOSmzKc5P7ODL0tHLNaa3+R5HszhAWemuRjVbWzqq7LcIw/nOTHk2w5gsXvS3K/JL+a5BNJ9o7L3ZMhBPH9GS6b8Q9JnrtI+0N5rFyS4bIbV2R4PP51kh1VdW2S3Un+M8n/THJ2br2Ux4F+LMm2JP+w4LH8F0lOTHJhkuccMH8leVKSP0pyRVVtHx+fNyT5xXH6a1trf7X87gEAAOBAghIAAADAHVJr7Z+TPDbJO5PcmGQqwwnpH0/y5CT7l2n7xiTfl6FXiv1JzkhytyQnHDDrj2YIRXw8wwnvliG88NWttfOOwjbMttZ+cNyOP0zy+QyXSlib5AsZTpS/MMkzbuu67ujGY3LvDOGUf08ym2RzkuuSnJ/kZ8fph+veSZ6d5LVJPprhUhpbMgQlLsrQY8O3JXlca+36Jeo66GOltfbhJPdJ8pNJPpQh6LA1Q68jH0nyW0me0Fp7/xJ1Xpiht4k3ZAjJTCa5JEPA4mGttSsPmP+Px7renOTTGQIhG5NcmeFx8/+01pa9pAsAAACLq9aWCrkDAAAAALdFVV2SIXjxxNba+atbDQAAAIkeJQAAAAAAAACAjghKAAAAAAAAAADdEJQAAAAAAAAAALpRrbXVrgGOCVXVpqenV7sMAAAA4A5k3759SZLJyclMTPjNEgAAwErZt29fa60t+o/Y1EoXA8eqqampPPmkZ692GSvuft9510yvn8pF774qN12yY7XLWVHH3WtT7vbEk7Lji7vzn2+7fLXLWXEPeM6ZmVo7mQvfdUVuuXTnapezok643+ac8biTsv2q3bnwL69a7XJW3AO+666ZXDORz77zimy/Ytdql7OiTnrw1pz2yONz82U787l3Xbna5ay4Bz7vrExOT+SCt12enV/cvdrlrKhTHnZcTn7ottz0+R256G/6e94/6HvPysTURC7488uy67q9q13Oijr1kcflpAduzY0Xbc/Ff3v1apez4h70/LtnYrLy6bdclj039nXsT3/M8TnhK7bk+s/eks//3RdXu5wV9+Dvu3tqovLvf3RJ9t6yf7XLWVF3feJJOf7em3Pdp2/OF97f4bH//rNTVfnkH3w++3f2dezP/Nq7ZNvZG3Ptv9+cyz507WqXs+Ie9PyzUlX5xHmXZHbP7GqXs6Lu/g0nZ8vdNuSLn7gxV/zz9atdzoqbP/b/9vqL0/bPrXY5K+rsJ5+Szaevz1UfvSFXfri/Y/+V3392kuTfXnfJ6hayCu7xlJOz8eS1ueLD1+fqj96w2uWsqIk1k3nQc8/M3GzLJ95w8WqXs+Lu9bRTs/7Etbn8n67NF//txtUuZ0VNb5rK/b/zzOzfM5tPnnfJapez4u7zjNOz7vg1ufQfrs21n7pptctZUWuPm8l9n3lG9u3cn0/9wedXu5wVd99nnZG1W2dy6d9fl+su2L7a5ayoDXdZk3s+5eTsuWVf/uOPv7Da5ay4u331SfmtP/qfS57EEJSAo2jH1XtWu4QV12aHXml237C3u+1ff5e1SZK5fa27bU+SNrfw2Pd1wnTTXdcnSWb3zvV57MfeqHZd39/zfv5EUa/HPmNHZF0e+x3jsd/T57Gf74Ru57V7s/OLfW3/vh3DiaL9u/s89sPBr+y6dk93IZl9O8djv2u2z2M/2nnNnuy5ad9ql7Gi9u8ajv2+Xfu7+5ybZHi/r2TnF3d/6TWwF/t3j8d+5/6un/c7rt6d2T19nSzfP27vvh19v+bvuGr3l77n6cXc3uHY793R+/O+v22fHY/9vu39HfuJmfFHta3P7zRn9w2vc3tv3tfdZ72ZXeMpwdbn835u/8Jj39f2z3+X3+b6PvZ7bt7X3fdakzOVZDiX1+Oxn///fin6+wMAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISjBUVVVT6+qv6mqa6pqT1VdVlV/VFUPWWTeM6uqVVUb7z+mqv5ybLuzqv6tql5YVcs+Tqvq/lX1hqq6uKp2V9WNVfUPVfUDVTV9COu9f1W9qaquGtt/pqpeVlUzR2u/AAAAAAAAAHDHICjBUVFVE1X1f5K8NcnXJ9mWZGeS05J8R5IPV9X/u0z7b01yfpInJ5lKMp3kQUl+O8lbq2pqiXYvTPLxJN+T5Mwk+5JsTPLoJK9J8p6qWr/Mep+U5F+SPCvJ2nG9907y80n+9JA2HgAAAAAAAIA7DUEJjpafSPLdSVqSlyXZ1lrbluT0JG/J8Fj7nap6/BLtX5/k/ya5+9hu67jMuSRPG//+L6rqaRmCFDvG6Se21jYlWZ/kG5J8Nsk5SX59mbrfnOSdSc5qrW1NsjnJS8bteGpVfdMhbDsAAAAAAAAAdxKL/kofDkdVbcwQLkiSX2mtvXx+Wmvt8qp6dpJTkjw2ycuTLBaWuCzJ01pre8Z2O5K8sqo2JPnZJD9ZVb/RWts5rnMyyW+MbZ/ZWnv3gnXuTfLuqvrGJJ9I8ryqOre1duUi6/1wkm9vrbUF631FVT0myVOSPCPJXx3qvth2j42HOusxo6aGvNXG09Zl2Iv92HjymiTJ1NqJbLtnh8d+spIkm05bl5qoVa5mZa0/aTj20+sms+0eG1a5mpU3f7w3n74ukzN9ZS7XnzBclWl6/VSfz/vxqb7ljHWZXj+5usWssHXHjcd+Q+fH/m7rs2bzl13Z7Ji2dtuwvTOb+jz28wd/y93WZ+22vq5Mt2brcOzXbJ7u89iPtt59Y/Zu37/aZayoNVvGY79lJtvuuWmVq1kF42v+1rtvzP7ds6tbywqb2Th8TbZm60yX/9/P23aPjZndO7faZayomQ3DZ9u12/o+9sfdc2PmZvv6cmdq/L9m3XEzXb/f9/jdxvS68dgf39+xn5we3+yrunzNm1ozHPv1J67t7rPe9Ph+VxPV3eM+SSbXDN9jrj9xTXfbP/8/zsRUp8d+/A57w0lrunvPW3f88F3OxHSf57EO9j1mtd7ObHLUVdW3JPnzJHuTnNxau2GReZ6UZD7McEpr7aqqOjPJxeO457XW3rhIu81Jrs5wWYxvaa29fRz/NRl6oPhUa+0By9T23iRfneQ7Wmt/Mo5buN6vaa393SLtvjfJ65J8uLX2iGV3wGhmZqa99KUvPZRZAQAAAABgVbTWUtXXD58A6NO55567s7W2aEJGjxIcDQ8Zhx9fLCQx+kCS2SST4/wH9tJw/mKNWms3V9XHknzV2O7t46RHj8N7VtVVy9S2ZRyescT0Dy8x/vJxuG2ZZaeqXpDkBUkyOTmZvbv6+sVFkkyvrVRV9u9tmets8ycmkqmZSptL9u1b7WpW3vTM8CPTHo/95OSQvp+bbd39yi5JptdPDs/7PXN9HvuZieHY7+ls45NMr5sYj33L3FxfYdvJqRqe93Mt+7t9za/s25vuepCanEwmp9L9837fztn0FrKfnJnI5PT4mr+3r21Pbv2cv2/3XH/P++nK5NT4Wa/H1/w1Hb/mTw2v+7OzyWxfHakkufV/vH275tLZoc/UTGVisjK7b6673jSSW//H6/rY72+Z3dfb1icz64Zf2O7d3d+2T01nOPY9vuZXMjNTaS3Zt3e1i1l5U9PD97qz+4f3/J5UDe/3rbXs29nZxieZWjs5vt+3zO7v63WvJirTa2o49h2+5k+vqdREZf++lrnOHvo1kUx3/Jo/eZAkhKAER8OJ4/DypWZore2uqmuT3GXB/Ast2XbBtIXtThmHa8ZlHsz6Jeq6ZYn5d4/DZftkaa29Nslrk2R6eqZ99M1LLe7Y9ZBv25SZ9ZXP/fO+3HB5X18mnHDmRO7xqJlsvyX5+D/11QV9kjzyibOZnkk++/d7ctOVfR37u9xzMmc9Yk22X7Ern/rDy1a7nBX3iB85O1NrJ3PBe27JLVf19W3CqQ9am7s+YkNuvmJvPvPOpbKBx66Hf99JmZyufObvdmf7dX09709/4HROf+BMbvxi8pmlYpbHsEd+03Di6N//MdnZ2cedu903Oe3s5IZL9uSzf3vzapez4h7xfSemJpNP/cEXsuv6vs4Yn/X1J+WUh2zNdRfvzefO37Ha5ay4Rz5vW1LJp952U/Zs7+s1/+5P2JCT7rU2114ym4s+3NdnnSR55LOGy8x99B8ns29vX780vfcDZnPiyS1XX1656NN9XWIuSR7zpOFb43/70xsz21lA7N5P2phtd1uTqz56Uz7/vutWu5wV91U/eXaS5KN/dktaZycP7vuk9dly6nSu/OTuXPavu1a7nBX3qOcflyT517/o63NektzviVPZfGLlsosql17c12v+xNRcHv3VLW0u+fD7+tr2JHngV81l05bkC59Nrrior886M2tbHv41yeyeuXzk1V9Y7XJW3IOec1o2nLQmX/jY3lz9n319zl+3pfKgb16ffbtaPvrm/r7beNDTN2Xdlsl8/pNz+eIlfX3O3XR8cv8nTGXP7uQjH+zvPNa97r/89xmCEhxNa1dwXfOf4N7RWnvaCq4XAAAAAAAAgDux/uKC3B6uGYd3XWqGqlqb5PgD5l/o1GWWPz9tYburD7ZOAAAAAAAAADiQoARHw0fH4T2r6rQl5nl8bu3B5KOLTH/CYo2qalOShyzS7h/H4QOXWScAAAAAAAAA/BeCEhwN70lyc5LpJD9+4MSqmkzysvHuB1trVy2yjB+tqplFxr84wyU9bh7XM++9SS5NMpnklcsVV1XbDlI/AAAAAAAAAJ0QlOA2a63tSPJL490XVdVLq2pjkoy9PfxJkscmmUvyM0ss5q5J3lZVZ47t1lfVjyY5d5z+K621nQvWuS/JC5O0JM+uqrdX1YPnp1fVdFU9rKp+NcnFR2VDAQAAAAAAALjTmzr4LHBIXpXkK5J8d5KXJ/m5qro5ydYklSEk8UOttQ8s0f57k7wpycVVdWOSjbn18fmOJL96YIPW2l9U1fcm+d9JnprkqVW1K8muJFsy9DYBAAAAAAAAAF+iRwmOitbabGvtOUmekeESGTdmCDtcmaFHiUe01l69TPu3JnliknclmU2yP8nHk/xQkqe31vYv0e6NSe6d5DeS/PvYdnOS65Kcn+Rnx+kAAAAAAAAAoEcJjq4x8PDWI2z790mecgTtLknyI4c5fx1knvMPNg8AAAAAAAAAdz56lAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0I2p1S6AfrXWLklSq10HAAAAAAAAAP3QowQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADoxp06KFFVz62qVlXnr3Ytt1VVnTluSzsKyzpvXNa5R6G0o7Le+W2rqjOP5nIBAAAAAAAA4HDcqYMSAAAAAAAAAACHY2q1C7iNbkpyQZIvrHYhHNQF43DfqlYBAAAAAAAAQNfu1EGJ1trbkrxttevg4Fpr91ntGgAAAAAAAADApTcAAAAAAAAAgG4cUlCiqi6pqlZV51TVaVX16qq6qKr2VNW/LZhvY1X9dFV9uKpuqqrdVfXZqvqtqjrjIOt4TlX9c1XtqKrrq+p9VfWUA9d/QJvnjuPPX2a5T6+qv6mqa8Z6L6uqP6qqhywx/5njMtt4//5V9aaqumrcns9U1cuqamaJ9qdX1Y+N6/xsVe2sqpur6mNV9XNVtXW5/XC0VdVkVb24qj4+1nJ9Vf1lVT3sIO3OrqrfHY/z7qq6oao+UFXPr6rJI6ijjbczl5j+yKp651jf9qr6t6r64apa9jFaVQ+pqldU1d9X1RfGY3xdVZ2/VK1V9XdjLa86yLL/zzjfHx/WxgIAAAAAAABwh3W4l964V5K3JDkhyc4k++YnVNV9k/x1kruNo/Yn2ZPkHkl+KMl/q6pvbq39w4ELrarfS/L88e5ckr1JnpDknKp68WHWOL/MiSRvTPLd46jZJLckOS3JdyT59qp6YWvtNcss40lJ3p5kXZKbkkwnuXeSn0/y0CRPW6TZbyT51vHvvUm2J9ma5MHj7Tur6pzW2mVHsl2HaSrJu5J8fYZjtSfJtiRPTvI1VfXVrbV/PLDRGFB5S5K146ibkmxI8rjx9qyqelprbcfRKLKqvj3JHyaZDzXcmOR+Gfbl4zLsw6W8J8nx4987x9txGR4/T0jyLVX11Nba/gVtXpfkiRkekz91wLT5mjYlecZ49w2Hv1UAAAAAAAAA3BEd7qU3/meSK5M8prW2obW2MckzqmpLkr/KEJJ4S5IHJVk7Tj87yR9nOEH/1gN7VKiq78mtIYlfTnJca21bkpOTvD7JK5OceATb9hMZQhItycuSbBuXe/pY40SS36mqxy+zjDcneWeSs1prW5NsTvKScZlPrapvWqTNp5O8KEOoZF1r7fgMgYNzknw4w/743SPYniPx35M8PMmzkmxsrW3KcGw+Ndb0mwc2qKqzk7xpnP7+JPcZt31Tku/PELb42sXaHolxfW/MEJJ4T5Kzx+O0JcmPZgijPG2ZRbwnybOTnDI+Jrcl2Zjku5JcleSbkvzIAW3+PMkNSe4yTl/Ms5KsT/L5JO893O0CAAAAAAAA4I6pWmsHn6nqkgwhiBsznDi/+oDpL0/y0iR/0lr7jiWW8ddJviHJj7fWXjWOqyQXJTkzye+11l6wSLt35daT2U9srZ2/YNpzM5xkf39r7ZwF4zcmuTxDsOEVrbWXHLDMySTnJ3lskg+21h6/YNqZSS4e7/5tkq9vB+ykqnpnkqckeWNr7XmLbe8S++C4JJ/J0CPH3Vtrlyy23tZaHeoyl1jPeUmeM959XGvt7w+Y/tAkHxnv3q219oUF016f5HlJPpfkga21nQe0fUGGoEdLcq/W2oWLrPfnWmvnHtBufh+edcB2z6/vgiQPbq3tPqDdzyT5hfHuly13OVX1uCQfSHJJa+2sA6b9ZoZAy9tba9+ySNsPJfmqw1nnzMxMe9ELfvJQyztmbDhuMhOTlV03z2X/3tWuZmVNr0nWbprI7P5kx3L9nhyjNm5OJiaSXTfNZf++g7+XHEum11bWbpzI7J657Lx2z2qXs+I2nrI2NVHZecP+zO7t69jPbJjImo2T2b9nLrtu+LIOiY55G0+aHo79jXOZ7ex5P7Ohsmb9RPbva9nV42v+1qSqsuPmZG52tatZWTPrkjVrk/2757Lrps42PsnGk6aGY3/1nsztn1vtclbUmq3TmdkwlX2757L75r62PUk2njg5HPtr92dutq/X/LWbJzO9biL7drfs3t7XtifJxuMrVZXtNydznT30161PpmeSvXuS3btWu5qVt2lLUpVsv2Z/2lxfj/11WycztWYie7fvz56b+vucv+m0oVPZ7dfsT19HPlm3ZSJTMxPZu2Mue3Z09qKXZNNJQ4fTt1zX37av31yZnK7s2Z3s2X3w+Y8lVcNrfpLccuOqlrIq1m9MJqeSPbuSvb0d+4lk45akzbVsv6q/7zTXnziTyemJ7Nk+l727+nrHm5xK1m+bzNxcy45r+/tuY8Nxk5mYquze0bKvs4f+5NTwnjc3l2y/ebWrWXnr1ie/+Evn7mytbVhs+uFeeuP3DwxJjOZPyv/PZdr+cYagxNcledU47iEZQhJJ8qtLtPuVLP2r/6V8XYaQxN7Flttam62qX0jy7iSPq6qTW2tXLbKcVxwYkhi9PUNQ4v6HU1Rr7frxBPxTkzw6ySWH0/4IfPDAkMRYx79W1WUZete4f5IvJF8KrsxfNuTXDwxJjF6X5P/LcAmTZyR5xZEWN67v6QvWt9jHkt/I0IvH+sNdfmvtg1V1Y5Izq+rU1toVCya/LkNQ4slVdVJr7YsL6rp3hpBEyxDEWW4bXpDkBUkyOTmZTSce7lPq2LFu8+F2UHNsaG14o9m8dbUrWT3rtvR67Fsm10xk02nrVruUVbN+W5+vea21TK2ZyKaTZ1a7lFWzfmufz/skmZqubNq22lWsng2bV7uC1TO1diKb1vb72N9wlzWrXcKqmV47kemej/0Jfb7fJ0M4dnrtbfodw53axo5f82fWDLdebez4u42ZjVOZ2djv9nd97DdMZGZDv+/3m47vd9vXrB1uvWltDExsXe1KVs+adcOtN6211ERl06kdPvBHazZOZM3G1a5i5bXWMjFRXwrJ9WjthsraRU+XH9taG3702vN5rKUc7rPhHw8cUVVnZDjhniR/taDngAPNn004Y8G4rxyHVy3smeAA/5RkX5Lpw6jzIePw4621G5aY5wNJZjNc8uEhGS4dcqAPL9H28nG46NfkVfWIJD+QIQxxepLFnnanLrHso2mp+pNhG07Pf92Gu2e45EWSvG+xRq21uao6P8l35tb9fKTunmTr+Pf7l1jf9qr61ySPW2ohVfXMBfWcmOGyIQc6NcmXghKttU9W1b8keUSS/5bk1xbMO99LyHtba59fbgNaa69N8tokmZ6eaRd+tL8k3pn3n8jUTOXKz+7Pzhv6SmFuOqFy0t2nsvvm/bn8Y/393OhuX7UhUzMT+cKVk9mxq69/qLdums0pJ85lx+7kkmv6O1l+71P3Zmoyufyzc9l1y2pXs7K23iU54bSJ7Lyl5YrPrXY1K++sBySTk5XLPrUve7b39YujbadP5rjTp7Lj+tlcdcG+1S5nxZ31iDWZmKxc+uHt2bu9r887x91jTbadsTa33JxccUVf73dJcs97zWViIrnwyuns2d/XCeNTtu3PcRvncsv1c7n64r5e85Lk7K+cTE1UPv/J/dnXWc9xJ91tIptPmMgNt1Suura/LxHvc+a+VCWX/Muu7nqQOuleM9l04lRuunR3rv3Pzn5imuTuX70lVZWLPtm660HqlLOSDVsq191cuerGw/kK8tjwFWfsTVVy0b/s7a43kVPuM5X1Wydzw2X7c/2lnT3wk5z9VUMq7HPv7+yf+ySnPnhd1m2ZyvUX78kNl/b1P97EVOWsR2/I3GzLRe9b6vTJsev0h2/O2i1TuebK5MZrV7ualTU1nZx1n8r+2eTCi/v7nHvmGfuzdk1yzef25uar+upBamb9RM74yrXZv2cun//nxX4jfWw7/aHrsmbDZL746R25+fK+upRYu3Uqpz9sc/btms0X/qm/bnJPuu/yibjDfSW8ZpFxpyxc3yEsY2HPACeMwyuXmrm1treqrkty8iEse96J4/DypWZore2uqmuT3GXB/AfOs9QnxPn/lr/sP6eq+rEMvVjMf4s4m+SGDL1bJEMQYW0WD08cbct9wl1sGxbuhyX3XZLLFpn/SCxsf8WScy1RS1VNJfnTJAsvnbEnybUZ9vv8Oiay+P5+XYagxPdkDEqMl2X5rnH6G5Yv/8tds2ys4th0168Yhjdf1XLDFX19gdzaRE66e7J/d8s1F/T15pokd33E8LS6/ubJXH/T5CpXs7ImJlpOOXEue2cncsUN/X2Jdq9Th7e0G65Kbr5ulYtZYVMzyQmnDV0zfvHS1a5m5Z019qV14+Wz2X5dX1+grtk4keNOT/bubLnmwr7+mU6SMx8+fIF6w8V7svO6vrZ/3bapbDsj2b27cvWVfb3fJUNQIkmuvnkqO/f0FRTZvG4ux22cy+7tyTWX9PWalyRnjz9ruO6ylj2dfY+2+fiWzScku3ZP5Mrr+vusd58zh5NF1128L/s665J4y6lT2XRisuuG2Vzz6f7C8Hf/6uG3M9dclsz29Xaf405ONmxJtu+ezJXX9/e8/4ozhv/xrrloNq2vr3Zywt2SbE123NhyzUU9BiWGYY/fa514r7VZtyXZcd1srvnPvlKhEzPJWY/ekLR0+X538gM2JluS7TdVvnh5X2HwmbVzOes+w6/Lr7ymv6DE6afMJmtatl8zm2s+21dAat22ISgxN5vuXvOS5NQHDr+vvuWKvd297m06ZSanPyyZ25dc85n+wuCbT1v+h66H+03XYp8WFy5jW2utDnI78zDXeVusaN9BVXW/DJcKqSS/k+R+Sda01o5rrZ3cWjs5yZ/Nz76StR2BO0O/S9+XISSxM8NlNM5ora1trZ24YH/PBzAW299/kmR7kvtX1cPGcd+YIfxzQ5K33a7VAwAAAAAAALDijsZPgq5e8PddD7PtfMdGpyw1Q1XNJDn+MJc73/PFkvVU1doFy12sp4wj8a0Z9um7W2s/1Fr7j9bageGSuxyldd0eFu6H5Y7l/KVWbut+W9h+uUuRLDXtmePwF1prv91au2zhxLF3iBO+vNmgtbY9yZvHu98zDucvu/EnrbX+olUAAAAAAAAAx7jbHJRorV2cW8MS33iYzT82Dk+uqrOXmOeRWeQSFwfx0XF4z6o6bYl5Hp9bLz3y0SXmOVzzAYKPLTaxqjYkedRRWtft4aIkN45/P3GxGapqIsk5493but8Wru/xS6xvQ5KHLTYtB9nfSR6Tg/eM8bpx+OyqOiPJU8b7h33ZDQAAAAAAAADu+I7WRWbPG4c/tkwwITXYumDUx5J8fr7tEs1+4gjqeU+SmzMELH58kTomk7xsvPvB1tpVR7COxdw0Dh+wxPSXJtl0lNZ11LXWWpI/H+/+cFWtX2S25yc5LUlL8pajsL63jndfXFVrFpntRUkWqyNZZn9X1VSSlx9CDf+U5FNJtmW4FMd0ko+31v71YG0BAAAAAAAAuPM5WkGJV2ToHeCEJB+qqm+rqnXzE6vqrlX1ggw9EDxtfnxrbS7JL4x3f6CqfqGqNo9tTqyq1yb5+iQ7D6eY1tqOJL803n1RVb20qjaOyz0twwnxxyaZS/Izh7uxy/jbcfjkqnrJfNBg3JZXJnlJkuuO4vpuD7+UZEeGy128q6runSRVtaaqvi/Jb43zvb619rmjsL5fTrI7yX2TvL2qzhrXt66qXpzh8XHTEm3n9/fLquqpYwAmVXWfJO9M8ohxWw5mvleJx4xDvUkAAAAAAAAAHKOOSlCitXZjhkDDp5PcNcmbk9xSVddW1c4MvUb8bpIHZ+iJYKE3JHnj+PfPJLm+qq7PcDmP5yf5H0muHafvOYyyXpXk95NUhp4FbhyXe2mSZ2YISfxQa+0Dh7HMZbXW3pNbe2T4pSTbF2zLjyV5fZK/PFrruz2M4YdnZwgvnJPkM1V1Q5Jbkrw2yZok703y4qO4vu9JMpvkG5JcNK7v5iS/nuTtSd6xRPNXJflcks3jfLuq6qYMj8OvS/IDufWxs5w/yK2Prb1J/ugINgUAAAAAAACAO4Gj1aNEWmsXJvnKJD+Y5H1JbkiyJcn+JJ/IcJL9yUn+8IB2Lcn3Jnlekg9nOGFdSc5P8uTW2u9kOBGeJDceRj2zrbXnJHlGhktx3JhkY5IrM/Qo8YjW2qsPe0MP7llJfirDyfp9GbblH5I8p7X2/NthfUdda+2dGS5n8XtJLslw6YudSf4+yQuSfP3Ya8fRWt+bMvTm8K4Mx2kmyX9kCGN8W748XDPf7vokj0rymiSXjaN3ZQhNPKG1dt4hrv/6JO8f776jtXZH7/UDAAAAAAAAgCM0dSgztdbOPMT59mQ4af2awyliDEu8Mbf2LPElVXV2kq0Zfun/uQPanZfkvIMs+61J3noYtVySIdyw3DznLzVPa21/kl8Zb4tNf26S5x7Jeg/VUus4YJ5zDjL9wgyhiKOy3tbawfbpPyd5yhKTl1vutRnCOT+4xPQzl1tvkoyXSHnUeNdlNwAAAAAAAACOYUetR4nb0U+Mww+01vauaiUcq56dodeSz2fofQQAAAAAAACAY9QdIihRVW+sqmdU1fELxp1VVa/Orb0a/M/VqY5jWVWdmeTc8e5vtdbmVq8aAAAAAAAAAG5vh3TpjRXwdRkvrVBVO5LMJdm0YPrLW2t/swp1cYyqqjcleWySUzIEhv4zyatXtSgAAAAAAAAAbnd3lKDEjyd5apKvTHKXJOuTXJHkH5O8urX2d6tY26qpqqsOs8mrWmuvul2KOfacnOS0JNcneV+SH22t7V7dkgAAAAAAAAC4vd0hghKttT9J8ierXccd0F0Oc/6Nt0sVx6DW2jmrXQMAAAAAAAAAK+8OEZRgca21Wu0aAAAAAAAAAOBYMrHaBQAAAAAAAAAArBRBCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALpxpw5KVNVzq6pV1fmrXcttVVVnjtvSjsKyzhuXde5RKO2orHd+26rqzKO5XAAAAAAAAAA4HFOrXcBSqurFSbYmOa+1dsmqFgMAAAAAAAAAHBPusEGJJC9Ocrck5ye5ZIl5bkpyQZIvrEhF3BYXjMN9q1oFAAAAAAAAAF27IwclDqq19rYkb1vtOji41tp9VrsGAAAAAAAAAJhY7QIAAAAAAAAAAFbKIQUlquqSqmpVdU5VHVdVv1ZVF1fVnqq6vKp+r6pOWaTdpqp6blX9aVV9qqpurKpdVXVhVb22qu65SJtzq6pluOxGkrxvXPf87fwF8z73wHGLLO/pVfU3VXXNWO9lVfVHVfWQJeY/c35d4/37V9WbquqqqtpdVZ+pqpdV1cwS7U+vqh8b1/nZqtpZVTdX1ceq6ueqausyu/qoq6rJqnpxVX18rOX6qvrLqnrYQdqdXVW/W1UXjdt9Q1V9oKqeX1WTR1DH/PE7c4npj6yqd471ba+qf6uqH66qZR+jVfWQqnpFVf19VX1hPMbXVdX5S9VaVX831vKqgyz7/4zz/fFhbSwAAAAAAAAAd1iHe+mN05OclyHEsDNJS3Jqkucn+dqqekhr7YYF8z8nyW+Pf88muSlDOOPs8fYdVfW01tr/XdBme5Krk5w4zntDkr0Lpl9/KIWOJ9jfmOS7F6z/liSnJfmOJN9eVS9srb1mmWU8Kcnbk6wba59Ocu8kP5/koUmetkiz30jyrePfe8ft2ZrkwePtO6vqnNbaZYeyHbfRVJJ3Jfn6JPuS7EmyLcmTk3xNVX11a+0fD2xUVU9J8pYka8dRNyXZkORx4+1Z43HbcTSKrKpvT/KHSeZDDTcmuV+Gffm4DPtwKe9Jcvz4987xdlySJ4y3b6mqp7bW9i9o87okT0zy36rqpw6YNl/TpiTPGO++4fC3CgAAAAAAAIA7osO99MZvZwguPLq1tiHJxiRPzXBi+8wkLzlg/muT/GKSRyRZ31o7PsPJ9/sm+aMMJ9//uKo2zDdorb2qtXZykkvHUU9vrZ284Pb0Q6z1JzKEJFqSlyXZ1lrbliHs8ZYM2/47VfX4ZZbx5iTvTHJWa21rks3jNrYkT62qb1qkzaeTvCjJvZKsW7DN5yT5cIaAyO8e4jbcVv89ycOTPCvJxtbapiQPSvKpsabfPLBBVZ2d5E3j9Pcnuc+47ZuSfH+GsMXXLtb2SIzre2OGkMR7kpw9HqctSX40Qxjlacss4j1Jnp3klNbahrHtxiTfleSqJN+U5EcOaPPnGR7HdxmnL+ZZSdYn+XyS9x7udgEAAAAAAABwx3S4PUrsSfK1rbXrkmT8Jf5fVNXLk7wqwy/wf2J+5tbamw5cQGutJflMVX1XhhPVXzu2+z9HtAWLqKqNuTW08SuttZcvWP/lVfXsJKckeWySlydZKizx4STfPtacsQeFV1TVY5I8Zaz7rxY2aK297MCFtNb2JXl/VX1Dks8k+caqOrO1dsmRb+Uh2Zrkca21v19Qyyeq6rlJPpLk4VV119baFxa0+ekMAZbPJfmm1trOsd2eJK+tqmQIejyvql7RWrvwNtb40xlCGRckeWprbfe4vp1Jfq2q1if5haUat9a+Y5FxO5L8YVV9PskHkvxgklcumL67qv4gQ6Dle5L8xSKLft44PG/++B+KLSce6pzHjvmLo6zfVpmdrdUtZoWt2zxs7+TMRDafNr3K1ay8+QvbbFo/l0N/lhwb1q8dNnh6suW4jbOrXM3Km3+mb9x262tAL9ZtHIZTM8mWE1a3llUxHvwNx09kYqqvJ/6aDcPGT62pbD75sK9CdqdX47HfeJfpTK3t64m/ZtOwvTMzydZtc6tczerZun42a6c7e96P2zuzNtlyUl+fc5N86TV/0/GVtRtXt5SVNrNu2Pg1My3bNvX3WW/eprtMZf+evl735o/9zMbJbD590SuudmHLCcnsl/W9eWybWjMM1870+T/evC0nT2Sus83/0rHfUNl8cl+fcxfq8XutqTXDa/7azZPZfOrhnia5c5ucGj/oVbLljDWrW8wqmJwZtn/dhpYtxx9k5mPM9PjxZqKSbVs6e8FPMjk5/I+3bstENp/S13c7899tTEymu9e8JJkYX/fWHTfd3eveuuOG411TyebT+vsfZ2b98p/v6lDOAVfVJRkut/ELrbX/b5HpZyeZP2G+8VAvyVBVL07y60l+r7X2giXW+cTW2vlLtH9uht4I3t9aO2fB+G/J0GvA3iQnH3A5kPl5npTk3ePdU1prV43jz0xy8Tj+a1prf7dI2+/NcPmGD7fWHnEo27qg7dsz9MLxna21P14w/kvrba3dpm/hquq8DJc9+WBrbdEQSFVdmqF3jSe31v5qHFcZelrYkuSFrbX/tUi7iSRfyHAJk5e01l6xyHp/rrV27gHt5h9oZ80HRMb1XZ8h0PEDrbUv62ljDL1cnaF3hy9b7sFU1Q3j8k9rrV2xYPwDknwiwyVJTm+tfXHBtHtnCLS0sd7PH8q6ZmZm2ktf+tLDKQ8AAAAAAACA28G55567c7xSxpc53NjQh5cYf/mCv7cm+VJQoqpOT/JDGXqOODvDJRwOjG+ceph1HMxDxuHHFwtJjD6QZDbDJR8ekgN6hhgdbHu3LTaxqh6R5AeSPDpDGGGxnX+0t3kxS9WfDNtwev7rNtw9Q0giSd63WKPW2lxVnZ/kO3Prfj5Sd8/weEmGy3wstr7tVfWvSR631EKq6pkL6jkxQw8VBzo1yZeCEq21T1bVv2S4LMx/S/JrC+ad703ivQcLSVTVC5K8IEkmJyezb09fv7JLhl9VV1Vm97W0ub62vyaSyemJtLmW2X19bXsypK+rKvv3J62vH5plYiKZnBq2e39nv7RKkqnp4dflXR77yWRyMpmbS2b7C95namo89vtadz3JDM/7ytxcy9y+1a5m5U2O7/f797YhStqRicnhlwfdP+/3p8/n/fxrfu/v950d+8nJ4fh3f+x7fM2fSiYmK3OzLXMdHvv59/t9+9Pdsf8vz/vO/sdJkqnJ4Xm/b1/6O/ZTC459h5/1pseOJPbtXd06VsOXjv1s6+7YV5KpmUprLft7/P92KpmYqMzOJp19nZ0kmZ4aPt/v6+xxnwzvdxM1vN7PdfZ+XzX8f99a0uGpjEzVcOz3z/X3vK9Kpic6ft4fpMOwww1K3LLYyPFSBvN3v9RPV1U9IclfJlnYUedNSXaPf69LsjmLBwlui/kLIFy+1AxjzddmuPzHohdMaK0tur25tf4v65Osqn4sya/m1p7JZzP00jD/cXNLhhP5R3ubF7NU/cni27BwPyy575Jctsj8R2Jh+yuWnGuJWqpqKsmfJvmWBaP3JLk2w36fX8dEFt/fr8sQlPiejEGJqppM8l3j9DcsX37SWnttktcmyfT0TPvIO/r7ZPnQb57OzLrkwg/syA1f6OubpBPOns49Hr8hO66bzaf+cvtql7PiHvrszZleW7ngY8mN1/bVHfXJd205+37JzTcln/xIf12VPeqc/ZmaTj79r5Wbb+jr2J961lzOundy0w2VT/1bX130Jcmjn7A/k1PJpz84m+039PVfxRlfMZHT7zuZm66YzQXn71ntclbcw799fSankv94z+7svLGvbxPu+pDpnPoVM7nu2sqn/72/1/zHPmFfqpKPfmw6u3b11R31Pe6xL6edOpdrr0o++4m+tj1JHv2kuaSSf/3IdPbs7uv9/l732ZeTT2655rLkwk/2te1J8uhvGt7jP/5Xe7Jv90FmPsbc49HTOeGuk/ni52ZzyUf7+v82SR75rKEb4n/+yJrs7+zSmve/z96ccPxcLvviVC68rL8uiZ/40J1Jkn/5wGTaXGfH/iGz2Xp8y6WXT+biL/R3+YlzHjO80P/Le/s67kly/0e2bDkuueyClssv6Ov/24mp5JHfPJk2l3zknf293z3giZPZeFzlosumculVfT3v18zM5TFfuSf755L3/8dKnKK6Y3nUPXdm07qWiy6eyhVX9PW93vr1c3n4w/Zlz1zlb67dtNrlrLivOf6WbJpq+fcb1uTS7X191ts2sz+POWVXdu+rfPCC9atdzoq7/+nL/1N7u33bU1XTSf4wQ0ji/yZ5fJJ1rbWtrbWTW2snJ/kf87PfTmUs1rPA7aaq7pfkVzJsz+8kuV+SNa214xZs85/Nz76StR2BFd13R+j7MoQkdiZ5UZIzWmtrW2snLtjf8wGMxfb3nyTZnuT+VfWwcdw3JjklQ7jlbbdr9QAAAAAAAACsuNvzZzFfleHSDtcneWpr7YOttQNjG3e5ndZ9zTi861IzVNXaJMcfMP9t9a0Z9um7W2s/1Fr7j9bagR2Z3F7bfDQs3A9L7rsMx/XA+W/r+pa7FMlS0545Dn+htfbbrbXLFk4ce4c4YamFtta2J3nzePd7xuH8ZTf+ZJHHKwAAAAAAAAB3crdnUGL+ZPp/ttZ2LjHP1y7Tfr5P3yPpeeGj4/CeVXXaEvM8PrdeeuSjS8xzuOa3+WOLTayqDUkedZTWdXu4KMmN499PXGyGqppIcs5497but4Xre/wS69uQ5GGLTctB9neSx+TgPWO8bhw+u6rOSPKU8f5BL7sBAAAAAAAAwJ3P7RmUuGkc3nPsveG/qKonZYmT8aObx+HWI1j3e8b200l+fJF1TyZ52Xj3g621q45gHYuZ3+YHLDH9pUnusBf/aa21JH8+3v3hqlrsYjXPT3JakpbkLUdhfW8d7764qtYsMtuLkix10Zwl93dVTSV5+SHU8E9JPpVkW4ZLcUwn+Xhr7V8P1hYAAAAAAACAO5/bMyjxD0l2Zri8xe9X1SlJUlXrqup5GU6QX7dM+38fh89eLGixnNbajiS/NN59UVW9tKo2jus/LcMJ8cdm6LXiZw5n2Qfxt+PwyVX1kvmgQVWdWFWvTPKSLL/NdwS/lGRHhstdvKuq7p0kVbWmqr4vyW+N872+tfa5o7C+X06yO8l9k7y9qs4a17euql6c5BdyayDiQPP7+2VV9dQxAJOquk+SdyZ5xLgtBzPfq8RjxqHeJAAAAAAAAACOUbdbUKK1dmOGYECSPDPJFVV1Y4aeHl6f5MIkP7fMIl6/oO1NVXVpVV1SVW86xBJeleT3M1y64+VJbqyq65NcOi5zLskPtdY+cMgbdRCttffk1h4ZfinJ9nGdVyf5sQzb9JdHa323hzH88OwM4YVzknymqm5IckuS1yZZk+S9SV58FNf3PUlmk3xDkovG9d2c5NeTvD3JO5Zo/qokn0uyeZxvV1XdlOTTSb4uyQ8kufYQyviDJHvGv/cm+aMj2BQAAAAAAAAA7gRuzx4l0lr7rSRPz629S0wl+UySn03y6Awn35dq+3dJviXJ+5PsynC5h7slOfkQ1z3bWntOkmdkuBTHjUk2JrkyQ48Sj2itvfpItusgnpXkpzKcrN+XIajxD0me01p7/u2wvqOutfbODJez+L0kl2S49MXOJH+f5AVJvn7steNore9NGXpzeFeG4zST5D8yhDG+LcNlPhZrd32SRyV5TZLLxtG7MoQmntBaO+8Q1399hsdZkryjtXZH7/UDAAAAAAAAgCM0dSgztdbOPIR5aonxb0vytiWanTfellrm2zOc9F5q+rLtx3nemuEyH4ektXZJhnDDcvOcv9Q8rbX9SX5lvC02/blJnnsk6z1US63jgHnOOcj0CzOEIo7Kepd6fCyY/s9JnrLE5OWWe22SHxxvi00/c7n1Jsl4iZRHjXdddgMAAAAAAADgGHa79igBdxLPznD5js9n6H0EAAAAAAAAgGOUoARdq6ozk5w73v2t1trc6lUDAAAAAAAAwO3tkC69AceaqnpTkscmOSVDYOg/k7x6VYsCAAAAAAAA4HYnKHEHVlVXHWaTV7XWXnW7FHPsOTnJaUmuT/K+JD/aWtu9uiUBAAAAAAAAcHsTlLhju8thzr/xdqniGNRaO2e1awAAAAAAAABg5QlK3IG11mq1awAAAAAAAACAY8nEahcAAAAAAAAAALBSBCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQm6U1XnVFWrqktWuxYAAAAAAAAAVtbUahcAR1NVPS3Jg5Oc31o7f1WLAQAAAAAAAOAOR1CCY83Tkjxn/Pv81SsDAAAAAAAAgDsil94AAAAAAAAAALohKAEAAAAAAAAAdENQonNVdUlVtao6p6pOqar/XVWXVtWuqvp0Vf1IVU0smP+ZVfXBqrqxqm6uqndV1f2XWf5XVtUfjsvcU1XXVtW7q+pbD7Gm46rq16rq4rH95VX1e1V1ygFtzqmqllsvu/Gz4zK+dFtmfY+pqr8ca9tVVR+vqhdWVR36ngQAAAAAAADgzkBQgnlnJfloku9PsjnJdJL7JPm1JL+ZJFX1iiR/muSrMjx2NiX5piQfrKp7HrjAqnpBko8k+c4kpyfZmWRrkicl+bOq+oOqmlymptPHmn4kyUlJWpJTkzw/yYeqatuCefcmuTrJ7vH+jvH+wtuXqarnJnn/uB1TSdYmeWCS307y68vUBgAAAAAAAMCdkKAE8349ycVJHtRa25IhLPGycdp/r6qfTvI/krw4yZbW2uYkD0hyQYbwwy8uXFhVPTrJazI8xv4syRmttW3jvD+TIfTw35K8ZJmafjvJDUke3VrbkGRjkqcmuTHJmQvbttY+1Fo7Ocmbx1Gvaq2dvPC2yPJPTPK7Y52ntNa2Jtk2rjdJXlRV91umPgAAAAAAAOD/Z+/OwyzJ6jpxf7651b72Dk3T7AwNyKIoiNAgIqIjjMKggtq4MI7rOP4U16FxBWVmHJ0ZR0REBQUHEWRccIEGBVEEZBNBmi5637ururr2zPP7IyLpJMnMWrq6sqrO+z7PfSJvxDkRJ+LcG3f75Ak4xVRry16RgA5U1Y4k980QSLh/a+32Rcv/OslTx7svaa399KLlX5bkXUn2J9ncWjuwqN67kzy5tTa7qN7PZwg67E5y79bariXadEOSi1prtyyq+0NJXpHkitba/Rcte02Gy2+8tLV26TL7fHGSd4x3X9Va+84lynw4QxDk8/Z5OTMzM+17v3Ol3MfpadMZlYnJyp7bZnNoX1/nk+l1ybqtU5k92HLnzbOHr3Ca2XjOZCYmKnfuSg4dXO3WnFjTa5P1G4b9vvOO1W7Nibd5a1ITye5dyeyh1W7NiTWzNlm3Pjl4MLlz92q35sTbsjWpSnbf1jJ7qK9z/tr1lTUbKgf3t+y9fW61m3PCbTp7IlWV3bfMZq6z5/2ajZU1GyZy4ECy587+rsy2ZWtLVbJrV2Wus4f+2nUta9ckB/Yne+9c7daceJu3pdu+X7euZc2a5MC+Tvt++9D3d9w8l9ZZ36/dnMysnciBPS37dvf1XidJNp1Vqars3FXp7evCDetbpqeTfQcqe/f393q/deNcqpKdt2X416aOrN+Uoe/3Jft67PstQ4fvvOUwBU9DGzYnU9PJvjtb9u9Z7dacWFXJ5jMrrbXsurmzJ32SDVsrU9OVvfsq+w709byfqJYtm1rmWnL7nf39H/XmdXOZmkz27K0c2L/arTmxJiZaNm9O5lpy68GVBno/PW2dms3URLL7YGX/bF+P/amay5Y1LbNzyc49fe17kmxYM5df+LlL94z/kP95pk50gzhp/Z/FIYnRX2UIPBzIcBmOxd6d4XIXa5M8MMk/V9X2JE8Zl//C4pDE6OUZLqmxMcNlL16/RJlXLg5JjN6cIShxv6ra0Fq7O19d/cIy89+SISjx8JUqj5cXeVGSTE5OZsvZ/Z1k5q3f1t+La5K01jI5Xdl8Xr+n0w2bV7sFq6O14QP1lu2r3ZLVs7HTvk+GL9K2bjt8udPVxm2VpK8vE+ZNr6lMn9Pna16SbDyj332fmUlmZvr7EnHe5s397vvMmuHWq677fu1w69WmM/v9fDuzvjKzvs/3OkmypePn/dqZlrUdv95v6fgzztq1ydq1Hff9GavdgtWzdkNl7ZI/nZzeWmupqmw5q9/Xu3VrW9Z1+LxvLZmoZPvGzhKxC6xf17J+3Wq34sSb7/szZ/r7p895G6dbNk73t/+tJZMTfT/vl9PvL3ss9pFl5t84Tne01j7vf2dba3NVdXOS8zNctiJJHp3h15OW5J1LrbS1trOq3p/kS5M8JksHJd63TJuuWfD31iTHGpS4tbX26cNsY8WPiK21VyZ5ZZJMT8+0Hf/YWQwxyfmPnMnUTOWGT89mz86+3lhu3F45676T2b+n5drL+9r3JLng31QmpyrXf2o2+3b19QK76cyJnHHBZPbuSa77TH8fKO/74JbJyeT6TxzMvjv6euxvPnci28+fyp47k+uu6e/HgwsfMJfJyeTay1v2713t1pxYW89Otp1d2bNzLjdc0dfjPknu+4iJTExWrrx6Igc6+4+bM7bPZdvWlt27khuvOXz5082FD0kmJpLPXD2Zg52NIHXWGbPZsjnZfetcbrqyr/c6SXLhF0ymqnLF1ZM5dKiv5/3ZZ85my8aWWw9M5Jp906vdnBPu4Zv2pyr5zCf7Gz3s7HsnG7ckt+9Kbrqlv3DgAy+cTVWy4xPpbiSZc85PNmxKbtk9kRt399f3Dz3n4ND3H5ntbjSRc+9XWbdpIrfsrNy8q7+vyh9yn+EN3hX/1NkJP8m5D5zIuo0TufXm5LZb+nqvMzHZcr8HDqOGfXpHf+e88+81m7Vrk+vvnMgte/t63k9PtDx4+8HMziWfuLm/97n323Yw66aTW66Zza6bVrs1J9bMuuTeD5nMoUPJjiv7e95fcP5sZmaSm3ccyu6b+3qju2Zjct5DZ3LwQHLVp1a7NSfe2fdeeXlfrwKs5Lpl5s8eZvnCMvOvrGeN051LhSsWuHpR+cWWHNC+tbav6rNvXu/Oq/lKA+bvO5b1X/8v/X2ouNdF00kqt107l9uu7evT9Jn3nchZ900O7k+uu3y1W3Pinf/gZHIque2a2ey8vq++by0544LJHNifXHtlfz+WX/DA2WQyueXK2dxxY19vLCcmp7L9/GT//sq1V/f3oeLC+w/9ffO1ye7bV7ctJ9rUTLLt7GTfnuT6y/t63CfJBY8YznU33jSZOzsbnnPNzMFs29qyb09y3Wf62vckufAhw+P9hpsms2dvX/u/bm2yZfNs9t7Rcv2n+nveX/jIyaSS62+ayr79ffX9xvUtWzbOZtfsZC7f299wIg/fNPwDwA1XJQc7C8dt2taycUuye89krr6+vx8PHnjh8PXO9VdVZjsLSG05Yy4bNiW79k/mylv7e94/9Jzhx/LrP53uLrmz7dxk3aZk157JXH1Tf8/7+aBEj+91zjh/Ius2Jrt2TuTaq/t6rzMxNZf7PXDo82uu7e8norPPmsvatS237ZvOjl0zq92cE2rt1FwevP1g5lrymdv7e707f8ts1mUuu27q77uddZuHoMTcXJ/P+3udOwQldl4/m5su72tEiU1nTeS8hw4h+B7/6XPjlpV/u+rrHQAnWn+vtAAAAAAAAACc1AQluCfMD1q0rqqWGy0iGS7XsbA8AAAAAAAAANyjBCW4J3wwyfxYJk9ZqkBVbUny2PHuB47jtufHS+pv/BgAAAAAAAAADktQguOutXZrkneMd19cVUs9zl6cZG2S3Un+9Dhuftc43Xoc1wkAAAAAAADAaUJQgnvKT2UY3eExSV5fVecnSVVtrKofT/KjY7mXtdZ2LbOOY/GxcfqMqjrvOK4XAAAAAAAAgNOAoAT3iNbae5J8d4awxHOTXFlVtya5PcnPZbg0xuuSvOw4b/qPktya5MFJrq6q66pqR1XtOM7bAQAAAAAAAOAUJCjBPaa19utJvijJ7yW5LsnGJDuT/GWS57bWXtBamz3O27w5yVOSvCnJTUnOSnLf8QYAAAAAAABA56ZWuwGsrtbahYdZ/pokrznWdbTWPpDk+cezTWOZWmHZh5N8/QrLL8swosVK639NDrPfAAAAAAAAAJx6jCgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISnPSqqo23C1e7LQAAAAAAAACc2qZWuwH0q6ouTnJxkn9qrb15NdsCAAAAAAAAQB+MKMFqujjJS5I8+zDlPjHeDt7D7QEAAAAAAADgNGdECU56rbWHrnYbAAAAAAAAADg9GFECAAAAAAAAAOjGaR2UqKqvq6o/r6qbqmp/VV1dVa+rqscsUfbCqmpV1cb7D6+q11fV9VW1r6r+pap+qqpmltlWG28XrlB3zTJ1LxvrXlJVW6vq5WOdPVV1+6Ky51TVf12wfGdV/UNV/dAK63/NuP5Lq2qmqn6yqj4+1r+yqn6lqrYtKP/YqnrT2P69VfW+qnr2YY71Ebdr/lhnuOxGknzrguP32eO41LFdZtsPqKpfr6pPj8f7tqp6V1V9R1VNHsExXzcem0+M+3vj2H8PWmmfAQAAAAAAADj1nJaX3qiqiSS/leRbxlmzSe5Icu8k35TkG6rqe1trv7ZM/acneXOSdUl2JplO8pAkP53ksUmevcLmn5DklUk2JNmVpBbUfWZVfUVrbfcydc9K8v4k90+yP8mBRe16XJI/S7J9nHVHkpkkXzTevrmqnt5au3GZ9c8k+askX5Zk3zjvPkm+L8njq+rLknxlkjeMZXclWZvkC5O8qaq+obX2B4tXegztmk1yQ5KN43Hal+E4LzS7zD4s3vbXJPm/YzszrmfDuI9fluR5VfXs1tqdy6xic5J3J3l0hmM+l6EfnpfkK6rqca21y4+kLQAAAAAAAACc/E7XESV+JENIoiX5qSTbWmvbkpyf4Uf1iST/s6qetEz9NyR5a5L7tda2Zvgx/cfG9T2rqp65wrb/d5J/TvLI1tqWJJuSvDDJ3iRfkuS/rVD3v2QIZXxVkvWttc0ZQgoZR3x4c4YwwkeSPG5cvjHJc5PcluQLkrxuhfV/d5IHJfmaDGGCjRlCH3eM27k0yW+P67jXuO9nJ3lLhsDHL1fV54RrjqVdrbWrWmvnJnnFOOsNrbVzF92uWmE/5rf9gCSvzxCSeGeSh45t3pTkP2QIPjwtyf9YYTUvTbItyTMWHJMnJbl63KdfOFw7AAAAAAAAADh1nHYjSlTVxgyhhiR5eWvtZ+eXtdauqapvTHJekicm+dkMP4ov9r4k39Baa2O9O5O8rKq+NEPI4DlJ/nSZJuxP8ozW2q1j3QNJXlNVyTDKxbdX1c+21q5cou6aJM9srX10QZs/Nf75vWO7b0/y9Nba9ePy2SRvrKpdSd6W5GlV9dTW2tuXWP+WJM9qrb1zwby3VNUvZRjx4sVJ3tFa+/YF27+pqp6f5Lpx+09I8q4F9Y9Hu47Vj2cIN1ye4bjtGbe9P8krx2P+60m+rapetuBYLrQmyVcsWvY3VfWfkrwxyddW1czYj4e16azTNXu0vJqoJMm6zZVDR3SUTh/rNg3Tialk0/aVy56Oany4r98ykblDc6vbmBNszcbhcT81lWze2la5NSfecHpN1m+dGCKEHZnZsKDvt/T1uE8yxCaTbNhy1zmgF2vGsaumZ5JNZ9TqNmYVzO/xxg0tk5N9PfZnxovITc8kmzo858/buKFleqqzvp8Z9nd6bXX5vJ9/4m/a0LJm5ogG/DttzMwMz/W1Ey3bpw+tcmtWz6atycGDfZ33pqeH6Zrpli2b+jrnLbRpazJ7qM++XzvVsnVdX+e8hTadkbTOHvpT830/07JlQ8993997ncn5c/7als1b+jrnTU7etb+bN3f2pE8yNe7/uqm5bFvT13u9NeO+VyXb1vZ3zpusYf/XbOjvvLdmwzCt6vN5PzF+j7lu00Q2ndXXOX/d1uGxPjGZbNrW174nyfSalZfXmAU4bVTVv0vypgyXrTi3tXbbEmWenuHH+yQ5r7V2fVVdmOSKcd6XL/WDflV9e5JXJXlfa+1xi5bNH8ifbq29ZIm6E0k+k2FUix9srf3ygmWXJXlykj9urT1rmf36UJJHJnlFa+2HlynzniSPT/LrrbXvWjD/NUm+NcnftdaesES9xyd5z3j36a21v1yizF8k+Yok39Na+9/HqV2XJnlJkt9urV2yVN2x3PyxvV9rbcc4rzKMVrElyfe21v7XEvUmklyZ4ZIrP9Zae9mCZZdlOOa/21r7liXqTmcIvVSSi1pr/7xc++bNzMy0n/iJnzhcMQAAAAAAAADuYZdeeume1tqGpZaddiNKJHnMOP3QUiGJ0buSzCaZHMsvHh3ifcvUu2acblth+5ctNbO1NldVf5PkGxe0cbG/W2pmVc0kefh49x0rbPvtGQIJy63/I8vMv3HB3x9dpswN4/Sz+34c23Us7p8hJLHstsdjflmS56+w7SX7urV2sKpuTHJOVujvqnpRkhclyeTkZDr7Z5skw0mkKjlUSW85xIk27H9Ly+zkarfmxJucTSqVQ+mw7zP0/VyGx35vptuQIuux7yfH21wb3kj05rPn/A53viqZnND3h+a6G0gmE5VM1tj3ve18kqka+v5g+ut75/wFz/vOOn9yYnjuz821zHXY+ZNTSVV1+Xo/UcN/m83NDbfeTE4ueK/X2fN+YnJ83nf6ej89/pdll8/7z57z+3zeT42/Dhw60N8Df3JqGCl3brb12ffTwxdahw6uckNWwfBeJ5mb7fB5X8PzvrVktsNz/vx7nbnZ4TW/J5Xhsd9ay2xfA6kkueszztyhlrnOOr8qmZyeGPq+w3P+xGGSEKdjUOKscXrNcgVaa/uq6uYMP4KftcTyO5apum+cTq+w/WW3u2DZ521zdNMy87dn+F3ucOu/+jDrv26Z+Z99SWytHa7Mwn0/Xu06FgvXdXe2vVxfJ0fQ3621VyZ5ZZJMz8y0t+zevMLqTk9fveGOrKuWd503mas29jUO+/13zubLbpjLHRvn8r5H7V3t5pxwX/be9Zk5VLls3bpcO3U6vpws7yH79+eLDxzIjTMT+dOzDzN202no+dfszZqW/PW6dbmhs76/aP/+PPbAgdw0N5l37VsyhHpae/b6XZlO8v5Pr82uvX0lxO5/9v484NxDua5N5W8PrV/t5pxwz5nelckkf3Prhuw61FffP2zjvjxo44Fcv28q/3hrf33/1fca+v5ttSG7qq++/8K5vXlwDuaqQ9N53751q92cE+7rNu5KJfnbHeuz91Bf7/Mfcc6+nL/lUG6+Yjaffl9/3yJ+8fOG97d/99F1OdBZKvjh99uXc7bP5brrJvKpy1f66uf09KQv258kec8H1+bQbF99/4gH789Z2+Zyxa7pfPy2tavdnBPuq+97R6qSt39qQ+ZaX33/hffZmzM3zObqqyayY0dfn2+T5ElPHq6j+4+/v3uVW3LiPewZ67L5nKlc/YmWqz+52q05sSamki/5msrcbPIPbzt8+dPNI544XGbqM59Mrv10X+e8mbUtX/Tlyeyh5O/+pr/3Oo953MFs2Jhc8cnKdVf19Rln/ca5POYJLQf3J+//s94SQsmjnjaRdZuSK969Ozd9Yv9qN+eE2nTOVC561tYcuLPlg3+0Z7Wbc8I94EtX/v3mdD4TnIqfao4kw3ey7tdqtutkPSYAAAAAAAAAnGROx6DE/KgMFyxXoKrWJjljUfnj5V5HsOxot3lr7hrdfNn9SnL+Ma7/WK1muxau62Q6JgAAAAAAAACcxE7HoMQHxumDqurey5R5Uu667MgHlilzrJ681MyqqnG7R73N1tqBJB8d7z5lhaJPPZb1H6vj0K75kMWxjG/16SS3r7TtqppIcvEy2wYAAAAAAACgQ6djUOIvkuxKMp3khxcvrKrJJD813v2b1tr1x3n7/7Gqti4x/wUZRjeYS/KmY1jvG8fpJVV13uKFVfX0JI8f7/7BMaz/WN2ddu0ap1uPdqOttZa7juMPVNVSF4z+jiT3TtKS/N+j3QYAAAAAAAAAp5/TLijRWrszyc+Pd7+/qn6iqjYmyTjCxO8neWKGwMJP3gNNWJvkz6vq4eM2p6vqW5P8n3H5b7bWrjyG9f7PJNclWTeu/wvH9U9W1dcnef1Y7q9aa2+/W3tw4tr1sXH6xKp60DFs++eT3JnhkiZ/UlUPGbe9pqq+M8mvjOV+s7V2+TGsHwAAAAAAAIDTzNThi5ySXpHkYUm+JcnPJnlpVe3KMHJBZQhJfF9r7V33wLa/O8lvJPlIVe3MECCYGZe9N8l/PpaVttZuq6pnJ/nzJI9M8r6quiPDyBlrx2IfTvL8Y2/6CW/XZUkuT/KAJJ+oqpuT7BmXPbG1dvVhtn15VX1jhpEqLk7yL1V1e5IN4/aT5K+T/Kdj2DUAAAAAAAAATkOn3YgSSdJam22tfWuS52S4FMftSTZmGPng95M8rrX2v++hzb8nyRdn+PF+f4bLPnwiyX9JcnFrbfexrri19g8ZAiD/PcknM4QBDiX5xwyXGfni1tqNd6v1J7BdrbWDSb48ye8muSbJtiT3HW9HFOJprb01ySMyhFN2JFmfIWzxt0lelOQrx1FGAAAAAAAAAOC0HVEiSdJa+8Mkf3iEZXdkGG1ipTKXHa7MWO6jSZ53JNsdy198FGWvzzAqxRGPTNFauyTJJSss35HD7/vh1nHU7RrrfSbDyB8rlTlc2z6VIRRxNNu9+AjKXHg06wQAAAAAAADg5HdajigBAAAAAAAAALAUQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuTK12A04XrbVa7TYAAAAAAAAAACszogQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADoxikblKiqNt4uXO22nEhVtamq/ltVXV5VB8ZjsGO123Wqqaod47G7eLXbAgAAAAAAAMCJM7XaDeCovSnJ08a/dyW5NclNq9eck8sYnLkkye2ttV9e1cYAAAAAAAAAcNIRlDiFVNVFGUISB5M8qbX23lVu0snowiQvSfKZJL+8qi0BAAAAAAAA4KRzyl56o1MXjdMPC0kAAAAAAAAAwNETlDi1rBunu1e1FQAAAAAAAABwijppgxJVNVFV31dVH6qqvVV1U1W9taoev0KdNVX13Kr6nbHezVW1r6o+U1Wvq6rHLlHnwqqaq6pWVQ9fYd0bq2r3WO7px2H/Hl1Vr62qq6pq/9jWt1XV1y9R9tKqakleM8568tiO+dvFx9iGS8f6r6nB91TVB8f9vK6qfruqzl9Q/kHjvKvH4/rRqvrOw2xj87idD43r3V1VH66ql1bVlsO1a7z/rVX191V1R1Xtqqp3VNVXLFFvR5J3jHfvu+gYtaq6ZJntba+q/1ZVV4x9cU1V/UZVnXdEBxIAAAAAAACAU8bUajdgKVU1leSNSZ41zjqUoa1fk+QZVfW8Zap+RZI/GP9uSW4fpxck+aYk/76qvq219rvzFVprO6rqr8a6L0zyQ8us+3lJNiS5MslfHdueDarqRUl+LXcFVW5PsjXJ05M8vapem+SS1trsuHx3khsyjCixOcnBJLcuWOWBu9Oe0e9n2McD4/rPTfItSb6sqr44yQOS/NnYzp1JZjJcCuSVVbW1tfZLS+znAzMcq/uOs/aM00eMt0uq6mmttX9drlFV9aok355kNsmdGfb/4iRPqqp/31r7wwXFbxqXb0syN95faO8Smzg/QwDlvmP7WpJ7JfmOJE+rqse01m5brn0AAAAAAAAAnFpO1hElXpwhJDGX5IeTbGmtbUty/ww/vL96mXq7k/xKkicl2dha295aW5fhR/BfzhC2eGVVXbCo3qvG6QvGkMZSXjhOf7u1Nnf0uzSoqifkrpDEG5PcZ9y3rUl+MsMP9S9I8mPzdVprr2itnZvkB8ZZ72mtnbvg9p5jbc/o2Um+etzupvH2pCTXJ7lfkp9J8vokf5vkAa21rWN7/89Y/6er6oxF+zmT5A8zHPurMoRANo63p2UInFyQ5I+qas0y7XpWkucn+Y9JNrfWtmR4DLwrw/H71YX91Vr7oiRfN969atExOre19oYltvGrSW5L8oTW2oaxfc/KEF65MAv6AQAAAAAAAIBTX7XWVrsNn6OqNiS5LsOP9S9trV26aPmaJB9I8rBx1v1aazuOcN2/meTbklzaWnvpgvkzSa5JcmaSZ7fW3rKo3oOTfCJDiOEBrbUrjn7PPruuv07y1CTvTvLkBaNGzC//+Qw/zu9Ocu/W2q4Fyy5J8ltJ3tlau/hY27BgfZcmecl495LW2m8vWv7NSX5nvPvJJBe11g4tWD6R4bg8MMm3ttZ+Z4m6B5M8prX20UXrvijJB5NMJ/n21tqrFyxb2K4XtNZet6juvZJckWFUiye31t61YNnFGS6/8ZnW2oUr7PuODCGOG8b9umXR8h9K8ookV7TW7r/cehaamZlp3/7i/3IkRU8rZ03OZrKSW9YkeydrtZtzQq0/1LL9QHJosuX2zbOHr3Ca2X77ZCZa5eaJieyvvvp+w9xctraW/ZXcNHOyZg7vOffaP5eJJDdNTORAZ32/cW4uW1rL/la5dba/vj9ncjYTldx+50QOzfbV9+vXzGX9mpZ9rXJb66/vz63ZVCW3HJjMoZPr48M9buPkXDZMteyfrdx+sL++P3vN0Pc3ZjKHDl/8tLIlc9mQlr1zlZ1z/fX9OZND39+6ZyKzra9z/qaZuaydbtm/p2Xv7cf8fxKnrC3nTaSqcuuuicx1ds7ftG4ua2aSffuSPXv6etwnybZtbXje75zISfZ14T1u44a5rJlO9hys7O7w9f6sdcM5/+Y7J7vr+y1rZzMzlezdm+zd29/zfvv2ocNvv7q3d3rJxrMmM7Wmsnd3y747V7s1J1ZVsvXsSmvJ7YvHZO7Apm3J1HSyd3eyb8/hy59OJiaTLWckbS657bb+znmbt7RMTSV7dg/v93oyOZls2ZbMzbXsvHG1W3PibT4zmZyq7Ln1UA7s7usz3uSayqZzpjN3qGXXDf39jrV+20R+/hd/es/4z/Kf52S89MbTM4Qk9if574sXttb2V9UrsvyoEit5a4agxJcuWueBqvqdJP95XP6WRfXmR5O47G6GJLYnecp49xcWhyRGL0/ygxlGNnhmhpEc7mlXJ/ndJeYvvMTIKxaGJJKktTZXVe/IEJR4+KK6zxmnb1kckhjrfqyq3pjkG5P8+yzdn1cm+b0l6l5bVf+Q5Injdt+1uMxReOXikMTozRmCEverqg2ttSXfLo+XUXlRkkxOTubcqf5OMvPO2J8MWaK+tLRMzVbOvO1kPJ2eGGfO9fXGYqE1LTl/f7/7f1bPfV8t53V8zt+6od++X1st51W/fX/GTL/7vmay5ZzJfvf/7PS77+smWtZN9Lv/29f3e85fs76yZv3kajdj1Wzf3G/fr12brF3b3+fbedu39Nv366db1k/3e84/c0O/+75uXbJuXb/P+63n9/u91rqNlXUbV7sVJ15rQ2Bi29mr3ZLVs25j+u37iWT7Gf2e89ZvHG69aa1lYqKy7dzVbsnqWb99Kuu3r3YrTrzWWiamKlvv3e/r/XJOxiPymHH6T621ncuUeedylccwwvck+aokD0myJcnibzbutUTVV2UISjyzqs5prd0wrm8yybeMZX7ziPZgeY9OUhl+TV5yH1prO6vq/RnCHI/JiQlK/PMylxNZmCv7vLDD6IZxum3R/Pl+fMcK2317hqDEY5ZZ/o9t+SFPrllmu0frfYdZfzJcZmTJoERr7ZVJXpkk0zMz7ZO3ztzN5px67rflQKYnkx1zU7mjs/+w3Vqzuc/EbPYdTK7cOb3azTnh7r/tYKYmkyv3TWV3Z/9Zv21yNuetnc2e2WTHvv6e9w9ZfyCTlVx921T2Huwrfb5t3WzO3DSX3bPJlR33/ZW3TWXfob76/owNszlj/Vx2Jrliqr++f8ShA5lMsmPnVPZ3ds4/a93BbF/Xsutg5Zq9/b3eP2TTgUxU8q/7pnMgfT3vz5s6mO1TLXfsrdyw62T86HzPesDZB1OVfHLfdA52NqLEvacPZutUyx27k5s6DETf7/xDqUo+sm4qvf1j/YV7D2X7XHLrgYncsK+/vn/opgOpSv5lz0x3o4ncZ82BbJpKbp6dyPWH+uv7i2aGvv/UjdPdjShx760Hs35NcuPsRG6Y66/vHzF9IEnysT39fca5cM2BbJhMrl+f3NjZD6YTLXn4TclcSz6+v7++v9/0gayfTG44MJFbDvb1vJ+qlgevP5hDST6ypr++f8j+A1mf5IY9E7ltf199v2ZyLvfbfCgHk/xzOuz7HMjaJFfPTua21lcYfn3m8oCpQzk4MZer73NgtZtzwp1108rf5Z2MZ4Kzxum1K5S5ZqmZVfWwDD++n7Ng9h1J9mYIJ8xk+GH984bXaK19vKrek+QJSV6Q5L+Oi56RIVixM8mbjngvlja/bztba7tXKHf1ovL3tOuWmtlam627hlRfskzy2X8tW/xIm2/7kn01mt/PM6qqlghF3LFC3fmBke7ut9VLbqO1tm/Bvh/ZNlryqdvW3M3mnHou2Hww02m5qk3nmrvdHaeWC9uB3Cez2X9oIp++pb++v3DrwSTJVftmcmNnHyrut3b/EJSYm8wn9q5d7eaccA9aN/xYfu3O6dy2p683lvc7Y3/O3DSXPbN99v2D1x1IKrlm53R27uur7ydqf85YP5c7JibzkZn+zvkPPzR8kLryjpnccaCvvp+aaNm+7mB2H5rMJ3d3+LzfNPT9pw/O5I65vvp+bbVsnzqYO/ZP5tM39fe8v//ZB1NJLj+wJns6u/TIhom5bJ06lDv2TOYz1/T1GScZghJJ8rEN09k72VffbzvUsn3/bG4/2Oc5/6HjOf9Te9d0F5DaNjWbTVOzuWV2Kh8/2F/fXzQz9P0VN89krre+3zCX9Wtmc3Obysdn++v7+aDEJ/b1t+/nTB/Khsm53Lgp+djZfT3upw61PPym4QeTj+/vr+/PmzqU9ZnLjQen86m9fb3PXzcxlwevP5i5JB9e19e+J8mFBw9l/dxcbto3nR139BUW2DR1KPfbfCiHUvnYRH/P+wvnDmZtWq6bm86n5/rq+zNyKA+YOpTZ6eSq++5f7eaccOv3rvyZ9nT7xPtbGUISH8gQcNjUWtvcWjuntXZukueO5ZZ75/Mb4/SFC+bN//37rbW9x6mdPb0C9XfGBQAAAAAAAOCkdTIGJW4ap0tdHiPLLauqC5I8LsMIB1/bWnvbEqM2nLO43iJ/kGRXkouq6ouq6swk/3Zc9urDtvzw5vdtXVWtNFrE+YvKn4rm237BCmXm9/OWFS6xAQAAAAAAAADHzckYlPjAOH1UVW1epsyTl5j32XBBa225yz08baUNt9b2JPn98e63JXl+hst1fLS19r6V6h6hD2YY0SpJnrJUgarakuSx490PLFXmFDHf9iX3c/TURWWPh7lx2td4aQAAAAAAAAAckZMxKPEXGUZ1WJPkBxYvrKqZJD+0RL2d4/Scqjp7iXqPSPJNR7D9+ctvfEOS7xz//s0jqHdYrbVbk7xjvPviqlrq+L84w+Uqdif50+Ox3VXyxnH6VVX16MULq+qiJM8Z7/7BcdzurnG65TiuEwAAAAAAAIDTxEkXlGit3ZnkF8e7L6mq/1xV65Kkqi5M8kdJ7rNE1Y8nuTrDSAJvqKoHjnWmq+rrkvxlhvDB4bb//iT/lGRrkouSHEjy2mPfo8/zUxlGPXhMktdX1fljOzdW1Y8n+dGx3Mtaa7uWWcep4A1JPjz+/eaqelpVVZJU1ZdnCIFMJ/lYktcdx+3+a5KDSbZU1dcfx/UCAAAAAAAAcBo46YISo5cneUuSyST/NcmuqrotyRVJnp7hshifo7U2l+T7M4QQLk7yr1W1K0M44g+T7E/yn45w+69a8PdbW2s3H9NeLKG19p4k3z2287lJrqyqW5PcnuTnMgQ9XpfkZcdrm6uhtXYgydcn+UySCzIGVarqziR/Nc67MsnXtdb2H8ft3pm7Lp/yxqq6vap2jLfnrFQXAAAAAAAAgNPfSRmUaK0dyvAj+/dnGJXgUJLZJH+S5MmttTctU++Pkjw1w4/yd2QYseAzSV6R5NEZRpw4EgvX/+pj2IUVtdZ+PckXJfm9JNcl2Zjh0iF/meS5rbUXtNZmj/d2T7TW2qeSfEGSn07y0QWLPprkZ5I8srX2yXtg09+V5BeS/EuGS7jcd7xtvAe2BQAAAAAAAMApZGq1G7CcMSjwq+NtqeW1zPx3JnnnMqu9LMOIDYfz1HF6TZK3HUH5o9Za+0CS5x9lndckec1xbMOlSS49TJkVj9fh1tFa25nkJePteLbrkiSXLLNsb5IfH2/L1b/wCNpxJI8VAAAAAAAAAE4hJ+WIEieB7xqnrz4dRnYAAAAAAAAAAAaCEotU1bcneWKS/Un+zyo3BwAAAAAAAAA4jk7aS2+cSFV1fpK/TbIpyfZx9i+21q5dvVYBAAAAAAAAAMeboMRgKsl9k8wluSLJbyR5+UoVqur6o9zGK1prrzi25q2sqt6X5D5HUeUNrbUfuCfaAgAAAAAAAAAnM0GJJK21HUnqKKudc5TlNx5l+aNxVo6uPVvuqYYAAAAAAAAAwMlMUOIYtdaONlhxj2mtXbjabQAAAAAAAACAU8HEajcAAAAAAAAAAOBEEZQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG6dVUKKqLquqVlWXrHZbjkVVXTK2/7LjsK4d47ouvtsNOw7braqLx/k7jud6AQAAAAAAAOBonFZBCQAAAAAAAACAlUytdgPoxp4kn0hyzWo3BAAAAAAAAIB+CUpwQrTW/iHJQ1e7HQAAAAAAAAD0zaU3AAAAAAAAAIBudBOUqKrNVXVpVX2oqnaPtw9X1Uurasth6m6oqv+vqt5TVbdW1b6q+nRV/XFVPb+qpheVf0xVvayq/raqrqyq/VV1S1VdVlXfUVWT9+zefl77t1fVf6uqK8a2XFNVv1FV5x2m3lOq6k1VdX1VHRinf1RVTz2GNlxcVa2qdqxQ5vlV9d6xb26tqrdX1VcfZr2TVfVVVfXrVfX+qrphbOu1y7V17M9dY3u+ZoV113jMWlW96Kh2GAAAAAAAAICTUheX3qiqByb5qyT3HWftGaePGG+XVNXTWmv/ukTdhyX5kyQXjrMOJdmV5D5J7pfk3yZ5d5IdC6r9RZIzFmxrT5LtSZ483v5dVT2rtXboOOze4Zyf5DUZ9n1PkpbkXkm+I8nTquoxrbXbFleqqp9N8hPj3ZZkZ5Kzkzw7ybOr6mWttR87Xo2sqv+Z5HvGu3NJDia5OMlTquoHVqj6b5L86YL7u5IcSHLegrb+eGvtF+YLtNburKrXJ/nOJC9M8v+WWfdTM/T7niSvP7o9AgAAAAAAAOBkdNqPKFFVM0n+MENQ4KokT0+ycbw9LcmVSS5I8kdVtWZR3e1J/jzDj+VXZPjhfUNr7Ywk65M8MclvZQhPLPQXSb4xyXmttQ2ttW3j9r45yfVJnpnkB4/zri7nV5PcluQJrbUNYzueleT2DPv1eWGHqvqG3BWS+J9Jzh734axxfUnyo1X1guPRwKp6fu4KSbwiyRnj9s5L8jvjvLOWqX4gyauTfGWSLa21La21jUnOSfJTSWaT/FxVffGieq8ap/+2qs5cZt0vHKd/2FrbdZS7BQAAAAAAAMBJqIcRJZ6X5JEZRih4ZmvtowuW/XVVPTPJB5NclOT5GX50n/ejGUaOuDnJl7XWrplf0Fo7mGEkiXcv3mBr7ZuWmHdnktdW1WeSvCvJdyf5pbu3a0dkf5KntdZuGdtxKMkfjyNGvCLJc5L8yHzhqqokPzPefX1r7fsW7MMtSb5/DBZ8Y5Kfqarfa63NHWvjxu29dLz72621H16wvRuq6pIMI2A8ban6rbVPJvn2JebfmORnx/X/dJLvSvL3C5b/Q1V9OMNj4/lJ/seidm1J8nXj3YWPiRVtnpk90qKnjYlqSZKNNZdtra/931DDQ39yomXzmr72PUmqhunGybkc6Kzv100Oj/upatk62de+J3f1/YaZucwe8yvAqWnNlL5Pko1r5tLa6rblRFszPu+nk2yf67Dvx+mm6bnP/t2Lz/b9RMuW6X77fvPEXE7o9QNPAmvG97kzky2b1vbb91smZjNTfZ3010yMz/uplo0bOnuzs8C2Q3NZP9dZ34/7u6bTc/68LVOzOTTX1yv+9PivZGurZetEv32/ee1cOnvaZ2o8569Ny7bqt+97/Hw7NZ7m1h1Mtu3t64E/Pf7bZyVdnvMm5/t+or/vdtZMDO9tK8n2Q33te5JMZniur5ucy5bOfsvZMH6nOZF09ztOks9+n7G+5rp7vd887m+1ZOMdp/34CZ9n+uDKn2uqnUbfclfVZRkubfHC1tprxnlvSfK1Sd7YWnvuMvV+L8MP/29rrT1jwfzrM4xM8KOttZcfx3belmRrknu31q5dMP+SDCNUvLO1dvHd3MaODKNo/Exr7b8ssfwBST413t04BjlSVY9O8oFx/sNbax9bou5DkvzLePfxrbX3LrHdp7TWLlsw/+Ik70jymdbahQvmL9zeQ1trn1hie09J8vbx7ues93Cq6lEZgjD/2lp78KJl35fkV5J8qLX2qEXL/kOS/5Pk8iQPakfwRJmZmWk/8RM/cbhiAAAAAAAAANzDLr300j3jVRc+Tw8jSjxmnL5jhTJvzxCUmC+bqrowQ0giSf70aDdaVc/NMFLBYzJcNmLtEsXuleTaJeYfT+9bZv41C/7emuTO8e/5Y3DTUiGJJGmtfaKqrkly77H8e5cqd4Tmt3fDUiGJ0XsyXN5kycdrVa3LMGLEs5I8LMm2Jcrea4mqr03yi0m+oKoe01r7wIJl3zZOf2ulkERVvSjJi5JkcnIybbLD/zaarVQqs0lOn9jVkakMScSW4RovvZnMcAy67vvWcd9XMlctra9/NEvNJROp4Xnf2b4nyWQbHv8TE4fS27ACc7MTSSa67/s20eF7nbnhvU5Ly1x/wftMzKXb93oT462lDU+C3sy/z6/W3Tn/rtf7lkx02Pfjee9QZyOJJEN3TwyveKkOP9+32Ykk1fXr/VySDvf+s1+i1eTiqwuf/trs8O1Gr+/1JsfRY6Y67PtDY9/PJelsEJ0kyfjP5anORlRI7nq967Lv23DO7/377KrZTHT2fmdurtLaVFpax99r1fhhr7PPOXOVtIlun/eHe3vXQ1DirHF6zQplrh6nZ1RVjT+Mn7Ng+ZVHurGqmkryB0n+3YLZ+zNcvmP+MXhWhr5ZMr1ynN2x1MzW2r6qz54NpxcsOpLjlQzH7N4Lyh+r+frLBkZaa/ur6uYk5y5eVlXnJbksycLRIu5McluGz7aTSc7MEse6tXZbVb0pyTcleWHGkS2q6qIkjxvr//ZKjW+tvTLJK5NkZma65dn/tFLx09P/e0SyfzrvWrs2V01PH778aeT+Bw7kifv355bJifzJ5vWr3ZwT7nm3787alrx9/bpcO9XDy8ldHrJ/f75k/4Hc3Cbz9kMn4lR+cvl307syk+Qjj7gzO7f29fbq/Ctncv8d63LDxuSy+692a068r/9IMt2SJz7zT7L9rJtWuzkn1D+//7H55IcfnavWTeSvz+3r9S5JvnnH/ky15I4n7cjclv2r3ZwTau1Hz87ay8/IjWfM5sMP7Wvfk+TL37M+1ZI/y4bc0dnFN74we/OgHMzcfW7P7Bce8UfC08b0mx+ZtOTdj96XfWv7+iLpon+dzr1vms7e++zKzi/o6/UuSc79fw9IkvzJv0n2dfaS9/gdyQU7k00PuipnfNHHV7s5J9yO33t6kuTWp386bbqvHw82/f29subGjfn41HQ+MLPU/zqd3l6w545Uki943lsz0VlI6JN/+cTsvv6cXHPffbn6/ntXuzkn3Je8Y3uS5Me+4w2r3JIT7zVv/opcdcPZ+dCZE/nImX2lZKYOzeWbPjWXTMzmvs/7q9Vuzgl37Z9/SQ7cuiUfOHMiH9ve12ec9Qfm8twdszmY5A3rNq92c064r9m3O9vaXB75xe/NAx72z6vdnBNq5y3b8tdveU72TyV/9qi+vs9Nkqd9ZDKb9icbv/Bfs+4B1612c06oAzduyc63Pzp3VuVNGzeudnNOuCfuXfn9XU/vAE7Up5zvzBCS2JPk+5Pcp7W2trV2Vmvt3NbaubkrFHAy57ZOlU+Fv5whJPHpJF+fZHtrbWNr7ezxWH/JYer/xjj9pqpaM/79wnH6F621q5eoAwAAAAAAAMApqoegxPy/f1ywQpnzx+ktCy6zcMOC5fc9iu09d5z+TGvtVxf/0F5V8yMcnKzmj9d9DlNu/pjd3X+vma+/1KUxkiRVNZMljtk4/1nj3ee31t7UWrttUbFzsoLW2mVJPpVke5KvHUcEecG4+NWHbT0AAAAAAAAAp5QeghIfGKdPWaHMUxeVTWttR5Lrx7vPPIrtzQcIPrjM8i/NyT1aw/wx2FBVj1uqQFU9OMNlNxaWv7vbO2dc71KekKUvE3NmkvlRIJY73k87gjb85jj9tiRfnSFccUuStxxBXQAAAAAAAABOIT0EJd44Tr+qqh69eGFVXZTkOePdP1i0+HfH6Q9V1b1zZHaO00cssa2pJD97hOtZLf+UYYSFJPnxZcpcOk53JPmH47i9Fy9eWFWV5EeXqXtHkvkRQJY63ucl+b4jaMNrkhxK8vQF23pta+3AEdQFAAAAAAAA4BTSQ1DiDUk+PP795qp62vjje6rqy5P8aZLpJB9L8rpFdV+e5JoMIxf8TVV97Xi5h1TVdFU9uapeX1XnL6jzl+P0p6rqWeOlNlJVD03y1iSPS3Lncd/L42S89MhPjnefVVW/WlVnJElVnVFVv5LkG8flP9lamzsO27t0vPttVfXyqto6bu+cDJe/eGqSPUvUvSPJe8e7r66qR431Jsa+fWeSOoI2XJ/k/2V4PnzJ/PqObY8AAAAAAAAAOJmd9kGJcVSAr0/ymSQXZAgy7K6qO5P81TjvyiRf11rbv6juLUm+KsnVSe6X4VIMu6vq5gw/3F+W5Hn53MtCvCLJ5Uk2J3lzkr1VtTPJx5N8RZLvSnLzPbCrx01r7Q1Jfm68+71JbqyqW5PcmLtGaHhZa21xsORYt/e6JP9rvPsjSW4et3ddkkuS/H9Jblqm+g8m2ZthRIkPVtXuJLsz9O0ZSb79CJvxqgV/v7+19uFlSwIAAAAAAABwyjrtgxJJ0lr7VJIvSPLTST66YNFHk/xMkke21j65TN2PJLkowygL/5jhR/kNGcIVb84wusLVC8rfmmFUgl9bMH/vWPbJrbXXHJ+9ume11n4yyZdnCIfcnGRjkluS/HGSp7XWfuw4b+97k7wgyd8n2Z9hJIh3Jvma1tqvrFDv75M8PsPxvS3D6CA3Jvn1JI9K8qEjbMKf565RK4wmAQAAAAAAAHCamjp8kVNHa+3iFZbtTPKS8Xa0692VYYSFnztc2bH8zUm+e7wttfzCZea/JslrjrZ9R7ONRWVWvCxFa+3tSd5+PLbbWrssh7kMxjiyxJKjVKy0P621DyX5dyus+rCX38gQblmfZF+S3zuC8gAAAAAAAACcgroYUQKOwHeN0//bWrt9NRsCAAAAAAAAwD1HUILuVdVXZriESpL8j9VsCwAAAAAAAAD3rNPq0htwNKpqR5J1Sc4eZ/1ua+39q9ciAAAAAAAAAO5pghInsap6QpI3HWW1r2utveeeaM9p6L5JWpKrk7whyU+tbnMAAAAAAAAAuKcJSpzcZpKccwx1OAKttVrtNgAAAAAAAABwYglKnMRaa5cl8WM+AAAAAAAAABwnE6vdAAAAAAAAAACAE0VQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3RCUAAAAAAAAAAC6ISgBAAAAAAAAAHRDUAIAAAAAAAAA6IagBAAAAAAAAADQDUEJAAAAAAAAAKAbghIAAAAAAAAAQDcEJQAAAAAAAACAbghKAAAAAAAAAADdEJQAAAAAAAAAALohKAEAAAAAAAAAdENQAgAAAAAAAADohqAEAAAAAAAAANANQQkAAAAAAAAAoBuCEgAAAAAAAABANwQlAAAAAAAAAIBuCEoAAAAAAAAAAN0QlAAAAAAAAAAAuiEoAQAAAAAAAAB0Q1ACAAAAAAAAAOiGoAQAAAAAAAAA0A1BCQAAAAAAAACgG4ISAAAAAAAAAEA3BCUAAAAAAAAAgG4ISgAAAAAAAAAA3egyKFFVbbxduNptOZGqalNV/bequryqDozHYMdqt2u1VNUl4zG4bLXbAgAAAAAAAMCJMbXaDeCEelOSp41/70pya5KbVq85AAAAAAAAAHBiCUp0oqouyhCSOJjkSa21965ykwAAAAAAAADghOvy0hudumicflhIAgAAAAAAAIBeCUr0Y9043b2qrQAAAAAAAACAVXRaBiWqaqKqvq+qPlRVe6vqpqp6a1U9foU6a6rquVX1O2O9m6tqX1V9pqpeV1WPXaLOhVU1V1Wtqh6+wro3VtXusdzTj8P+PbqqXltVV1XV/rGtb6uqr1+i7KVV1ZK8Zpz15LEd87eLj2H7PzXW/b9LLHvsgnX/2hLLv3JctmOZdT+8ql5dVVeMx//2qnp3VX1XVU0fpl3/tqreUlXXV9WBqrpx7PevPNp9HNf3zVV1cOzj/3gs6wAAAAAAAADg5HLaBSWqairJm5L8SpJHJpkab1+T5F1V9XXLVP2KJH+Q5JuTPCLDsWlJLkjyTUneW1XfvLBCa21Hkr8a775whWY9L8mGJFcuKH9MqupFSf4xyfOTnJ9kT5KtSZ6e5I1V9btVNbmgyu4kNyTZNd4/ON6fvx04hma8c5x+2RLLnrzg7yetsPydixdU1fcm+VCGY3nh2NaNSZ6Q5NeS/EVVrV+i3nRVvTbJHyf52iTnJNmb5KwM/f7nVfXyw+7V567ze5L89nj3W1prnxf6AAAAAAAAAODUc9oFJZK8OMmzkswl+eEkW1pr25LcP0NI4dXL1NudIVzxpCQbW2vbW2vrktw3yS9nCFu8sqouWFTvVeP0BWNIYynzIYrfbq3NHf0uDapqPjAwkeSNSe4z7tvWJD+ZIdjxgiQ/Nl+ntfaK1tq5SX5gnPWe1tq5C27vOYam/H2S/UnOqaqHLlo2H4S4I8nDquqsZZZ/TlCiqp6d5FeT3JnkR5Kc1VrblGR9kmck+dckFyf570u05xczBEc+leTfZ+i/LUk2J/nusS0/UlXfeCQ7V1U/keR/ZgiRPKe19tojqQcAAAAAAADAya9aa6vdhuOmqjYkuS7JpiQvba1dumj5miQfSPKwcdb9xlEhjmTdv5nk25Jc2lp76YL5M0muSXJmkme31t6yqN6Dk3wiQ4jhAa21K45+zz67rr9O8tQk707y5Nba7KLlP58hJLE7yb1ba7sWLLskyW8leWdr7eJjbcOC9b0zQ6jku1prvz7Om0hyc4ZQyW8n+d4MQYM/HJevT3J7kukkD2ytXT7On0xyeYZQyjNaa29bYnsPSPLhJDNJLmitXTfOf1CG43tzkse21q5aou43JPn9JB9rrT18wfxLsuiYVNUvJfn/MgQ2ntVa++sjPSYzMzPtx//X9xxp8dPH9ZtTcxO5aWIieydOx+zV8tbPzeXMubkcqOT6qcnDVzjN3PvgbCaT3Dg5kX3VV99vnJvL9rm57G+Vm1p/fX+vOpSJSnZuPpSD06fP+4gjsW7vRDbsmcy+yeTmDavdmhPvXruGtOYZ51yXmTX7V7s5J9Su27fmzl1bs2cyuWlNX+e8JLnPnrlMJDl45p1pU8ec+z0lTe6ayeSeNdk/PZedm/ra9yQ569bJVCrXZzIHU6vdnBNqW2azMS1t3YG0rXtXuzknXF23OZXKzVtmMzvZ1+v95t0TWXdgIofWHcyhzX293iXJmhs2pFK5blPLbF9P+2zfk6w/VJnasCcz2+5Y7eaccHuuPjtJ5cDZu9M6e7szddvaTO6fyq6q3D7R32e8+8weSiXZcv61SfV1zt994xmZ3b82e9fNZu+G2cNXOM1sv3kmSfKQCz/vK9XT3meuOzv79q/J7TPJrpm+XvCqtdznziRpWX/+javdnBNu7w3b0w5O57aZ5I7pvvp+srXce8/wX8ZXTyz3f7+nr3PnDmUmyeZtt2TDpr7e6x08MJ2br793Zqvlhi19vdYnydm7KlNzlamtd2Riw77Vbs4JNbd/Oodu3ppDSa6d6u95f8bsbH7pJS/Z01pb8tv80+2IPD1DSGJ/lhh5oLW2v6pekeVHlVjJWzMEJb500ToPVNXvJPnP4/K3LKo3P5rEZXczJLE9yVPGu7+wOCQxenmSH8xwuYpnJnn9sW7vCLwrQ1DiyUl+fZz3iCTbkvxZkrdnCEo8OckfjssfnyEkcc18SGJ0cYaQxEeXCkkkSWvt8qp6b4agyMUZgg9J8i1JKskblgpJjN6Y5DVJLqqq8+ZDFguNIY9fT/IdGcIcz2yt/d2ye39XvRcledH8/Ze+6Jf3HK4OwGliKsmh1W4EwAnkvAf0xDkP6I3zHtAT5zygJ+uWW3C6BSUeM07/qbW2c5ky71xm/nwY4XuSfFWShyTZkmRxjPxeS1R9VYagxDOr6pzW2g3j+iYz/JCfJL95RHuwvEdnCAS0LLMPrbWdVfX+DGGOx+SeDUq8M8PlPp68YN7Cy2q8K0Nbl1u+0BPG6YOq6voVtrllnN5nibrfWlXPXaHu9IK6i4MS0xmCF/8+yY1Jnt5a+9AK6/qs1tork7wySarqH1trX3gk9QBOdc55QG+c94CeOOcBvXHeA3rinAf0pKr+cbllp1tQ4qxxeu0KZa5ZamZVPSzDKAjnLJh9R5K9GX7wn8kwWsLnDc3RWvt4Vb0nw4/2L0jyX8dFz8gQrNiZ5E1HvBdLm9+3na213SuUu3pR+XvKe5IcTHKvqnpga+1TuSsIcVlr7Zaq+liSR1TV9tbarQuWv2vRus4bp2vyucd/OeuXqLtpvB1N3XlPWPD3c440JAEAAAAAAADAqaezKw6u6Lcy/Ej/gQwBh02ttc2ttXNaa+cmmR+tYLmLVv3GOH3hgnnzf/9+a+14XdR2zXFaz93SWtuT5P3j3SdXVWW4FMfuBfPfmeF4fVlVrU3yxQvmLzT/OHxLa62O4HbpEnV/8AjrXrbE7nwkyT+Pf//vqjrzGA4JAAAAAAAAAKeA0y0ocdM4XeryGFluWVVdkORxSWaTfG1r7W1LjNpwuJEO/iDJriQXVdUXjT+2/9tx2asP2/LDm9+3dVW10mgR5y8qf0+aDzw8OcnDkpyZ5N2ttUNLLP/iDCGPG1pr/7JoPTeM0wuOoQ13p+68W5N8eZJPJHl4kr+sqm3HsJ5X3o02AJxqnPOA3jjvAT1xzgN647wH9MQ5D+jJsue80y0o8YFx+qiq2rxMmScvMe+z4YLW2pKX5kjytJU2PI6w8Pvj3W9L8vwMl+v4aGvtfSvVPUIfzHAJkCR5ylIFqmpLkseOdz+wVJnjbP4SGk/OXcf1nYdZvviyG0nyd+P0kVV176Nsw3zdZxxlvc/RWrs+Q1ji8iSPSvIX4/E8mnV4cwF0wzkP6I3zHtAT5zygN857QE+c84CerHTOO92CEn+RYVSHNUl+YPHCqppJ8kNL1Ns5Ts+pqrOXqPeIJN90BNufv/zGNyT5zvHv3zyCeofVWrs1yTvGuy+uqqX67sVJ1ma4/MWfHo/tHsbfZhiF44Ikl4zzLptf2Fq7IcMoDY9K8rXj7MWX3UiSv05yVZLJJL+00gaXGOnhdzIESP5NVf2Ho6z7OcaQzFOT7EjyhUn+rKo2rlQHAAAAAAAAgFPLaRWUaK3dmeQXx7svqar/XFXrkqSqLkzyR0nus0TVjye5OkkleUNVPXCsM11VX5fkLzOEDw63/fcn+ackW5NclORAktce+x59np9KMpfkMUleX1Xnj+3cWFU/nuRHx3Iva63tOo7bXdK4jQ+Nd78oyZ1J/nFRsXdmeJw9dsH9xes5mOR7MwQevrGq3lxVj5pfPvbDF1bVLya5YlHdf07y38e7/7uqfmH+uIx1N1XV06vqtUn+7xHs05UZwhJXJ3l8kj+pqvWHqwcAAAAAAADAqeG0CkqMXp7kLRlGJ/ivSXZV1W0ZfmB/eobLYnyO1tpcku/PEEK4OMm/VtWuDOGIP0yyP8l/OsLtv2rB329trd18THuxhNbae5J899jO5ya5sqpuTXJ7kp/LEPR4XZKXHa9tHoGFwYf3jKGH5ZbfkuRjS62ktfbHSb49Q7jkWUk+WFV7quqWJHuTvC/JDydZ6nIYP5Lk1zI8nn80yVVVtbOqbs8wWsjbMlwKZfJIdqi1dkWGsMR1SZ6U5I+rau3CMmMA42ur6meq6s+q6uaqauPtoUeyHYBTUVU9pKp+tao+UVV3jufbj1fVq6tqqctbAZx07s57uar6kqr6gap6bVX9S1XNjfVO5HtwgCN2PD6/VtW6qvpPVfW3VXVTVe2rqs+M61tq5E6AVVNVF4znrLdW1ZVVtb+q7qiqD1XVy6rqvGXqTVTVU6rqR6rqD6rqigXny+860fsBcCSO9Zy3aB1bq+r/b+/O42Q5y3qB/56cJCRkBRNI2BEhyHZRwAVZIggGQTYXLiCLoqCIgF5AQO81yFWQ5SJuCCpEr6KAskWWoEhQQZAIKGETlAAf1hCW7DkJee4fVWPmDjM9Z7qnp+ec/n4/n/pUV731vvVUdU1Vd/Uzb/3Pqjqrqr4y/jbzn1X16qp65A5sBsBCHLzoALZbd19RVT+UIaHgJ5PcLMPjId6Q5Ne7+51VtV6911TV3ZL8UpLvSnJIkk9mSLp4VpLb7GMIr07yO+Prl86wKevq7hdX1XsyPELk5CTHZ0gG+JckL+nuv9zudW7i7Ul+ftXr9cpX/EN390YNdffLquptGR6bco8kN0xydIYEiw9lePTIX6xT7+tJHltVf5bkp5PcOckJY/GnMvR68Zb16k6I5WPj8XBmkrsneU1V3b+7LxsXuXuGHkoAlkZVPT7DI5IOHWddOL6++ThcmfWvBQC7zSyf5d6c9ZN3AXarmb6/VtUtkpye5JvHWZcnuTjDYzhvkOH7+/NnjBFgW1TV9TM8Vnf1DeDzkxyR4f7ubZI8uqp+qLvftqb60Un+bifiBNgOM57zVtq4S4beuFceS3/ZONx4HG6T5LQ5hA+wcAdcokTyXz+c//Y4rFf+jZkSw/y3Z+MfeM7M/3+x2cjdxvFnMvRksO26+70ZekjYSp3TMoeLWXe/LhP2S3d/ZlL5Osufk6sSL7YayzuSvGMLy5+WCfukuz+SqxIu1vPFDI8aeU+G9/sl+7pugP1NVT0myQszJEP8RpLfGx9XlKo6IcMN8kMWFyHAlk37We6SJB8d652VIcn3tnOID2A7TXXOG2++vy3DjfN3JHlaknd095VVdUSGR4M+cC4RA0xnpUfZN2S47/fW7v5KVR2aIXHsdzP88Pfaqjqpuz+/pv5FSd6bq86Z/yeT7w8CLNJM57yq+vYkb8yQWPH6JM8Yf39KVR2T4Z+Kv2cnNgRgEWrCP/gzhar6hyR3SvLM7v5fi46H+aiqPWNCzsr0jTI83iVJvnVMsgA4IIznuA8muXqSR3f3Hyw2IoDZzPJZbp26Zya5a5Lf6O6nzidigOnNeM57Q5IfyPDPI9/f3XvnGCrAzMYf9m7U3f+6QfnNk7wvyWFJTu3uZ6wqqwz3y69cNe+cDL3e/kx3//48YwfYqhnPeXsyJIbdJsMj3R82qUdwgAPRQYsO4EBSVY/KkCRxWRIfnA9gq28yASyBJ2RIkni3JAngQDDLZzmfA4H9zbTnrar6bxmSJJLksZIkgP1Bd39tox8Mx/KPJHnXOHm7NWW9OkkCYLeb5ZyX5D4ZkiQuSfJ4SRLAMjogH72xk6rqekn+MclRSa45zn5Od392cVEBwLZ6yDj+84VGAQDATlp55Of7u/vDC40EYHudN473TFwK4MCw0Tlv5bPeGd395R2MB2DX0KPE7A7O0P3asRm6rnx6klMnVaiqz29xeNK8gq+q92wxlhfOKxYAdp+qukmGZ1Inyfuq6ruq6vSqOq+qLqmqj1TVc6vqWpPaAQBgv/Pd4/h9VXVsVT2vqj5RVZeN9wdeXVV3WmiEAFtUVQcn+Z5x8uxFxgIwb5uc81Z/1rtuVb2kqj4zftb7dFX936q69c5FC7Dz9Cgxo+4+J0ltsdq1t7j8kVtcfiuOz9biOWZegQCwK9101euTk/yvDBnoFyTpJCeNw0Or6h7d/cEdjxAAgHlY/TnwrCQ3SXJ5kosy3Ed4QJL7V9WTu/v5C4gPYBo/m+SEJFcm+eMFxwIwb+ue86rqsCTXGyevkeT9SY7L8Fj5S8ayH0vyoKp6eHf/xQ7GDLBj9CixAN1dWxxOnWMsN9piLI+cVywA7ErHrnr9K0n+Pcl3dffRGRL5fiDJF5OcmOSvxkx1AAD2f8eO40ckuUGGG+1Hd/c1ktw4yRsy/OPIc6vqrguJEGALquo2SZ41Tv5Od39okfEAzNMm57xjV71+fJJDk/z3JEd297FJbp3k3UkOSfKyqrrZ3AMGWACJEgDAJKs/K3SSB3T3u5Oku6/s7jcl+Ymx/KQkD9zh+AAAmI+DVo1/o7t/r7svTf6rd80fTvLpDMkSv7iQCAH2UVWdmOS1SQ5P8i9x3gIOYPtwzjtozetf6O5XdPcVSdLdZye5X5ILkxyW5IlzDhlgISRKAACTXLjq9Zu7+6NrF+juN2ToaSJJ7r4jUQEAMG+rPwe+cG3hmDTxonHy5KrasyNRAWxRVV0zyVsy9IbzsST3Xkn8AjjQ7OM5b/XnvK8lOW1tO939hSQvHyfd7wMOSBIlAIBJPrvq9TckSaxTdv05xgIAwM5Z+Rz45e7+0gbLrHwGPDzJN80/JICtqapjkpyR5FZJPpXk+8Yf/wAOOFs4512Qq5Il/qO7v75Bk+73AQc0iRIAwCQfSnLlFpbveQUCAMCOOnuLy/scCOwqVXVEkjcmuX2Sz2f4wfBTi40KYD62cs7r7k7ywS0073MecECSKAEAbKi7L07yT+PkSRMWXSk7Z64BAQCwU/52HF+zqo7bYJmbj+MLkpw3/5AA9k1VHZ7k9CR3zHB++r7u/thiowKYjynPeSuf9W4y4RFqK5/1zpk5SIBdSKIEALCZPxnHp1TVNyRLVNW9k9xsnHzjjkUFAMA8vSZXdcn8xLWFVXVYkp8eJ8/o7q30QgYwN1V1aJJXJ/neJF9Ncs/u3sp/TgPsN2Y45/1Zhl5kj0ny4+u0e+0kDxkn3e8DDkgSJWBKVXXcypDkGquKjl1dVlX+zoD93UszPIJjT5JXV9V3JElVHVRVpyT5o3G5d8UXJ2A/Me1nuao6ck3dQ8aiw9fUu/pObQvAZqY553X3eUmeNU4+paoeOyZHpKpumORVGZ5XvTfJ/96ZLQGYbPyv6JcnOSVDbzf36u73bqH+MWvOmSvnxSPWnC+vtv3RA2zNLOe87v5wrrqn9/yq+tGqOnhs95ZJXpvkiCRfSfKCbQ4dYFeo4VFEwFZV1b7+8dy4u8+ZZywA81ZV35zkzAw3w5Phy9eeJCs/BH4oQ8b6Z3Y+OoCtm/azXFWdluQR+1DvGd196tYjA9h+M5zzKkPvYj82zro8Qy8TK8kWe5M8orv/YptCBZhJVd0lydvHyUuTfG3C4p/u7jusqX9mkrvuw6p+vLtPmyZGgO2yDee8w5K8IcndVrVxWYZeJjK294Duftu2BQ2wixy86AAAgN2vu/+zqm6d5MlJHpDkxhm653tvhv8m/O3uvmiBIQIAsM16+O+ah1XVXyd5dJLbJjkyyaeSvDXJ87r7Q4uLEOAbrO4N7LBx2Milc44FYN5mOud196VVdY8kP5XhHwJuMbbx8SRvSvLc7v709oULsLvoUQIAAAAAAAAAWBoHbb4IAAAAAAAAAMCBQaIEAAAAAAAAALA0JEoAAAAAAAAAAEtDogQAAAAAAAAAsDQkSgAAAAAAAAAAS0OiBAAAAAAAAACwNCRKAAAAAAAAAABLQ6IEAAAAAAAAALA0JEoAAAAALImqOq2quqpOXXQsAAAAsCgSJQAAAIC5W/UD/WbDE7dpfaeOw7Hb0d5uUVXn7ON+XDucs+jY562qbl9Vf1RVH62qi6rqknF/vbOqfrOq7l9VR6xT74A8VgAAANjYwYsOAAAAAFgqlyf58oTyi7ZpPb8yjk9L8tVtanM3ODfJYevMP2acv9H+PXccfy7JR5N8aS7RLUhV/WqSX05S46wrM7zv10lywyTfneQJSR6Q5LVrqh+oxwoAAAAbkCgBAAAA7KR3dvfJiw5if9Xdd1hvflWdluQR2WT/dvfTkjxtLsEtSFU9OMn/HCdfmeQ5Sf61u6+oqj1JvjXJvZI8fEEhAgAAsMtIlAAAAABgf/aEcfyG7n7Q6oLu/nqSs8fhuVW1Xm8cAAAALJmDFh0AAAAAwFpV9ciq6qo6c8Iyp47LnLZq3mlV1asW+8S4TK+z7JnjvEdOWMc54zInb7Tuqjqoqh5XVf9cVV8d5992zfI/WFWvq6rPV9XeqvpiVZ1eVd+/b3tke6zsn6o6dc38G63so3H6O8Z4z62qC6rqnVX1A6uWP7SqfrGqzq6qi6vqC1X14qq65ibrv1VVvbSqPlFVl4776x1V9dNVdciUm3XrcfzXmy3Y3ZeuimWfj5VVdY6vqmdV1Qeq6sKqumjcB7+20bavPoaq6gZV9YdV9elx+z9RVc+rqmM2irmq7ldVbxz38eVV9eWq+mhV/XlVPWijegAAAGxMjxIAAADAgeRrSb6Q5Nrj9JeSfH1N+XaqJK9Ocr9xPRf8f4XDj/8vS/LQVbPPT3J8kvskuU9VPae7f3Gb45paVd0vyasy3Dc6P8mRSb47yelV9d+TnJ7kTUlOTnJpkk5yrSSPTnKHqvqu7t67TruPS/LCXPWPOxeObd9xHB5UVffu7ounDP26W1x+S8dKVd0pyeuSrCRE7E1yZZJbjsPDquoe3f3RDdb3LRkeDXJ8hm3vJDdK8j+S3K+q7tLdn1uzzl9L8vRVsy5IcniSm43D9yZ5xb5tLgAAACv0KAEAAAAcMLr7Cd19wqpZd+juE1YNT9iw8nQemOSUJI9NcnR3XyPDD+//OZY/J0OSxMeT/GiSI7v7mCRHj3UuSPKUqnrwNsc1iz9O8idJTuzuYzMkQbwuw32kFyR5XpKbZ0j0ODLJURkSRS5I8m1JfnJtg1V1/yS/neSiJE9Jcnx3H5Xk6hn238cyJF68YIp4zxrHP1dVd97XSls5VqrqhhkSRK6Z5EVJbpohYeGIDD1avCXJ9ZO8uqr2bLDK52VIvrjzuO1HJLl/hgSNb8mw3/9LVd0oyVPHyWdl2GdHd/fhGd6TH07yhn3dXgAAAK4iUQIAAADYSXccHz+x3vCyRQc3hSOTPL67X7TSE0J3f7G7z6+qmyZ5QpJzk9ytu1/V3ReNy1zQ3S/K0AtDkvzSIoLfwHu7+ye7+wtJ0t3nZkj2OD9Drw0/m+RB3f2G7v76OLw+yXPH+j+8urExceA3x8kf6e7ndveXxrb3dvcZSe6V5OIkP1FVJ24x3mdm6NnhmCR/X1Ufrqrfr6pHjY/6qC22t55fS3Jskmd392O7++PdfeU4nJ3kB5P8W5JbJHnABm1cLcm9uvsfk2Ss+7oMCTRJco+x14oV35Hh3t1HuvvpK/tsrHtud/9Vdz9qG7YNAABg6UiUAAAAAHbSIRl6XFhvuMYC45rWeUleukHZwzM8muMV3f3pDZb5yySXJbnlFAkC8/LstTPGBI93jZPv7O6/X6feW8fxrdbMPznJDZOcPSZFfIPu/o+x/YPH5fdZd/9thp4ZPjnOunmSxyT5wyQfSPK5qnpuVX3TVtpdUVVXT/IjGZIx/s8GMezN8F4myT02aOqV3f3xdeq+Lck7x8nVSSbnj+NjxhgAAADYJgcvOgAAAABgqby9u09edBDb6KzuvmKDsjuO40dU1Y9MaOOQcXz9JJ/btsim94EN5n9xHJ+9QfkXxvHahJeV/XDTqvr8hPUeM46vPzm8b9Tdp1fVm5Lccxy+M8ltMjza49pJnpTkwVX1fd39kS02f7skhybpJB+Y0EHF4eN4o/jPnLCOt2fYT9++at67k3w5yYlJ/qmqfjfJ33T3J/YtbAAAADYiUQIAAABgeudOKFvpIeKocdjMrug1oLs3Stb4+jjerHzt/aaV/XC1DEkLm7l6klTV9ZO8Z4NlHtjd71w9Y0xYeeM4pKoOTXKXDI8/uU+Gx4a8vKpu1929D3Gsjb+2Ev86PjOhzkrZ8SszuvsrVfWwJH+aIenjxUkyJpu8JclLu/vt+xAPAAAAa3j0BgAAAMD0vj6hbOW+y893d+3DcOYOxLsIK/vhdfu4H04dl9+TjR/TcuhmK+3uvd39t939g0n+aJz9bUluO2X8X9vH+E/eYvsb6u43JrlxkkcneWWSzyY5IcNjXc6sqpds17oAAACWiUQJAAAAYDdaeZzFYROWOWZC2W5Yx8qjKG4wQxsHgqn2Q3efs41JJX+06vXNtlh3Jf6jq2qW4+E6+1D2DT2UdPfXuvsPuvtB3X3dJLdM8gdj8U9V1b1niAkAAGApSZQAAAAAdqOvjuPrTVjmDhPKVh6tUNOuo6q+JcmxE+pv5p/G8SkztHEgWNkPt6mq6y4ohotWvd67pmyzY+WsDEk1ldney7vuQ9l7N2ukuz/U3Y9O8q59aBcAAIB1SJQAAAAAdqMPjOPrVtXt1hZW1Z2TfM+E+ueP42P3YR333aD8qZMC3Ad/kuFH+G+tqsdMWrCqrjHjunaztyb5dIZHaTx30oLT7Ieq+r6qmpQQkyQPWfX6/WvKJh4r3X1Bkr8aJ3+1qo6aEMvBVXXkBsUPqqpvXqfOXXLVsfyqVfM3e7zIJeP4apssBwAAwBoSJQAAAIBdp7s/meSfx8nTqurWSVJVh1TVjyR5bZKvTGjig+P44VW1Z4Nl/jJDIsOtq+qFVXXsuI5rVdVvJXlYkotn2IYPJXnBOPl7VfWsqvqv3iuq6qiqumdV/WlW/UB+oOnuy5M8LsO+fnBVvbaqbrtSPr6nt6+q5yT5xBSr+IskH6iqJ1fVravqoLHdPVV1i6r6/SRPGZc9vbvXrmNfjpWnJvlyhsd2vLOqTqmqQ8b1VFXdtKp+IclHktx+gzb2JnlTVd1xrHdQVf1ghuMwSf6mu9+xavmfqaozquohVXXiysyqOraqnp7k5HHWGRusDwAAgA1IlAAAAAB2q8dn+K/5WyX5t6q6IMmFSV6Z5D1Jfm9C3T8cx09McmFVfbKqzqmq560s0N0fTPKbq9b1lar6SpLPJ3lsksckOXfGbXhKkhdluAfz1CSfrqqvVdVXk3wtw4/cD83Q28IBq7tfn+RRGZIF7pfkfVV1cVWdl+E9fk+SJyc5ZormL09yyyTPSfJvSfaO7V6WIQniMRkem/GOJI9cp/6+HCvnZHjsxmczHI9vSnJRVX0pyaVJ/j3J85PcJFc9ymOtJyW5RpJ3rDqWX5/k+CQfT/KINctXknsm+bMkn62qC8fj8ytJfm0sf0l3v3Hy7gEAAGAtiRIAAADArtTd705ypySnJ/lqkoMz/CD95CT3TnLFhLovS/JTGXqluCLJ9ZPcMMlxaxb9HxmSIv41ww/enSF54W7dfdo2bMPXu/ux43b8aZJPZnhUwmFJPpXhh/LHJfnhWde1243vyUkZklM+mOTrSY5Ocl6SM5P8yli+VScleXCSlyR5b4ZHaRyTIVHiPzP02PCjSe7c3V/eIK5Nj5Xufk+Smyf5xSTvzJDocGyGXkfOSvJbSe7a3W/fIM6PZ+ht4qUZkmT2JDknQ4LF7bv7c2uWf/kY1yuSfDhDQsiRST6X4bi5b3dPfKQLAAAA66vujZLcAQAAAIBZVNU5GRIvvre7z1xsNAAAACR6lAAAAAAAAAAAlohECQAAAAAAAABgaUiUAAAAAAAAAACWhkQJAAAAAAAAAGBpVHcvOgYAAAAAAAAAgB2hRwkAAAAAAAAAYGlIlAAAAAAAAAAAloZECQAAAAAAAABgaUiUAAAAAAAAAACWhkQJAAAAAAAAAGBpSJQAAAAAAAAAAJaGRAkAAAAAAAAAYGlIlAAAAAAAAAAAloZECQAAAAAAAABgaRy86ADgQHFcndB7s3f7G66aXDx1uzMvMOV659RusknI89qemReY03qnrDzHt2dx651gEcfMHJvu3biPNzO3uBazL3pS4W58Dxb2tzd5xRP340zrnVfDi1nvTPtpiY5H+2lnOP9tgxlimtt5M9md+2qSXRhv78KYkuzKfTXRwuKd8Be2W/fhboxrppjmdJbbJKaF7MYZVlrzvRpsvN657ajJ27M7b4tM/x7Maz/OclzM65bJ3GKapW4tKqZFHTMbr3d/3J75HVPzOw/V3I65XfjebrrEhJjndFzsl/ti6rUu5njbvO5m653X+zevujPsi00/k04X9eL20/S1Z/k1dFLpv/zbZWd09ynrlUmUgG2yN3vznXX39QtrcuctddCkb2hzqjupXjLxU0gdtElnNJM+wcxUd5MT4bTbu9knrnltz0zrnaXd+RwXc9ueTer2xHYnNzuv7ZkYUzI5rnmtd4Z9sen2TCre7AfxKffFpj84THxvJ1edZT9OrLvpeicUzrQvJpRt8rc3OabJq512e2ZZ7yzHxSz7ceJxvFndBeyn/bHuLOehmf5GduW+mNzuwrZnUuF+to83K5/XezDTeWiXHhdza3dX7seN/wp27fsz5fZsut5p17lZu5vd4F3EvljQ9mz6o8EMMU8un77diTfo51p3UuEmN7QnlE/+KjnLezv9TfZN6065PQfN1O5mdeez3oM2+7FiyvVutj3zqrv59kyoO8t6Z2l3QszzimnTujPFdOX0dee03j0zrXf67dkzZbubtb359swS83R192y2PRP2xaZ1J723m/zNT1t3s/dn2v20Wd257seJ653Q7oR6yWb7eJP9OPE8tFnd6da72XVicrvT/+1t9v5MPh5nOKZmanfScbHZ39507SaTbynv2eTz7J4JnwAntzu54YMmtDtpnZvW3XS9G0c9ud3JN2AntbvnxI8dt3E9AAAAAAAAAIAlIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKVR3b3oGOCAUFVvTnLcouMAYEPHJfnSooMAYNdwXQBgNdcFANZybQDY/32pu09Zr0CiBACwFKrqrO6+/aLjAGB3cF0AYDXXBQDWcm0AOLB59AYAAAAAAAAAsDQkSgAAAAAAAAAAS0OiBACwLF6y6AAA2FVcFwBYzXUBgLVcGwAOYNXdi44BAAAAAAAAAGBH6FECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIA2G9U1QlV9cKq+o+qurSqvlBVp1fV3ads72pV9f1V9ctV9bqq+mxV9Ticst3xA7D95nBtOL6qHlNVr1rV5kVV9eGq+p2q+pbt3gYAts8crgsnjd8XXl9VH62qL1fV3rHdM6rqEVXlHivALrXd14UN1rGnqs5adU/p1O1qG4D5qe5edAwAAJuqqtsk+bsk3zTOOj/JkRkSPzvJ07v72Vts87ZJ3rdB8b26+83TRQvATpjTteHyJAevmnVhkkPHIUkuTfIT3f3nM4QOwBzM6brw1CTPWjXrkiRXJjli1bx/THLv7j5/ytABmIN5XBc2WM8Tk7xg1axndPeps7YLwHzJdgYAdr2qOjzJ6zN8sX1fklt19zFJrpHk+Ukqya9X1T2naP6rSd6a5NlJfmhbAgZg7uZ4bTg4yd8neUSSE7v7qCRXT3KnJO9PcliSPxlvugKwS8zxuvDBJE9Lcsckx3b31bv7yCTXSvLUJFdkuEa8YOMmANhpc76XtHo910vyzCSfTPKFmYIGYEfpUQIA2PVWZeZfmOTm3f2ZNeWvSXL/JO/t7tttod2DknSv+kBUVSuv9SgBsIvN8dpwl+7++w3Kjk9ydoYfx07r7h+fLnoAttu8rgv7sN5nJvnlDD0OHd3dl29X2wBMb6euC6vauV+S30pyw+hRAmC/oEcJAGB/8NBx/PK1X2xHzx3H315VJ+1ro919ZcsaBdhfzevasG6SxFh2bpI3jpPb9iMbANtiLteFffCecXxYkmtuY7sAzGbu14Wqum+GJIm/7u7XT9MGAIsjUQIA2NWq6qhc9WPUGRss9q4kXxtf333uQQGwUAu+Npw3jvdsY5sAzGDB14U7juOLk3xxG9sFYEo7cV2oqiOS/E6SS5L83FbrA7B4EiUAgN3uWzM8NzIZng/8Dbr7yiQfHSdvsRNBAbBQi7w23HUcn72NbQIwmx29LlTV4VV1UlX9apInj7N/V291ALvGTlwXnpnk+kl+vbvPmaI+AAt28KIDAADYxImrXn92wnIrZSdOWAaAA8NCrg1Vdb8ktx8nX7YdbQKwLXbkulBVV+QbexS6IsmLkvzSNG0CMBdzvS5U1bcleXySf0/ynK2FBsBuIVECANjtjlj1+pIJy108jo+cYywA7A47fm2oqusmeck4+frufvOsbQKwbXbquvD5DPdTj05y+DjvRUme3d2XT9kmANtvbteFqjooyYszJM49rrv3bj08AHYDj94AAACACarqyCSvTXKtJJ9M8qiFBgTAQnT39br7hAw/wN0wyfOT/EySD1TVXSdWBuBA8bNJ7pDkld39N4sOBoDpSZQAAHa7i1a9PnzDpZKrj+ML5xgLALvDjl0bquqwJK/L8MiNc5N8f3d/adr2AJiLHf3O0INPdfeTkvxCkmsmeXlVXX2TqgDsjLlcF6rqOkn+d5ILkvz8dKEBsFtIlAAAdrvVz5K8zoTlVso+N8dYANgdduTaUFWHJvnLJHdL8tUk9+zuj07TFgBztcjvDC9JctnY9r22sV0Apjev68KzMjx+6TlJzq+qI1cPSWpc7tBV8wDYpSRKAAC73UeS9Pj6lustMD4f8qRx8kM7ERQACzX3a0NVHZzkz5PcO8N/mP1Ad79/y5ECsBMW9p2huy9Lct44eZPtaheAmczrunDDcfzMDL1KrB1uMJY/bdU8AHYpiRIAwK7W3RckOWucvMcGi31nkmPG12+de1AALNS8rw3jTdM/TvLAJJckuW93/9MUoQKwAxb5nWH8b+Hjx0mPAQTYBdxLAmBfSJQAAPYHLx/HD62qE9cpf9I4/hddogMsjblcG6qqMnSj/pAke5M8sLvfNlOkAOyEeV0XDt5kkSckOWR8/Q/72i4Ac7ft14XuPrm7a6MhySfHRZ+xah4Au5RECQBgf/DiDF82j0ry11V1iySpqqOq6jkZ/uM3SZ6+tmJV9Ticul7DVXWNqjpuZVhVdPTq+VV1yHr1AViYeV0bXpDkUUmuSPKj3f3meQQPwLab13XhQ1X1c1V1kzGZbqXOSVX1wgzdryfJa7r7A9u4PQDMZm73kgA4MGyWEQ0AsHDdfUlV3S9DV4jfnuSDVXV+kiMzJH52kqd391umaP59ueoZk6u9Ys309yY5c4r2AZiDeVwbquoGGf4zOGP9F1fViyfEcMK08QOwveb4neGmSX5rHC6rqguSHJHk8FXLvCnJw2fcBAC20ZzvJQFwAJAoAQDsF7r7X6vqVkmeluQ+Sa6b5Lwk/5zkBd3teZIAS2YO14bVvS4ekuTa2xIoADtiTt8Z7pvk7km+J8l1khyf5PIkHx/b/bPufuM2hA/ANnMvCYBJqrsXHQMAAAAAAAAAwI44aPNFAAAAAAAAAAAODBIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBoSJQAAAAAAAACApSFRAgAAAAAAAABYGhIlAAAAAAAAAIClIVECAAAAAAAAAFgaEiUAAAAAAAAAgKUhUQIAAAAAAAAAWBr/D4vRHDTwdLT+AAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# static attributes\n",
"tft_vis.display_sample_wise_selection_stats(weights_arr=validation_outputs['static_weights'],\n",
" observation_index=chosen_idx,\n",
" feature_names=static_feats,\n",
" top_n=20,\n",
" title='Static Features')\n",
"\n",
"# historical temporal attributes\n",
"tft_vis.display_sample_wise_selection_stats(weights_arr=validation_outputs['historical_selection_weights'],\n",
" observation_index=chosen_idx,\n",
" feature_names=historical_feats,\n",
" top_n=20,\n",
" title='Historical Features',\n",
" rank_stepwise=True)\n",
"\n",
"# futuristic (known) temporal attributes\n",
"tft_vis.display_sample_wise_selection_stats(weights_arr=validation_outputs['future_selection_weights'],\n",
" observation_index=chosen_idx,\n",
" feature_names=future_feats,\n",
" top_n=20,\n",
" title='Future Features',\n",
" historical=False,\n",
" rank_stepwise=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking at the barplots above, we can see that although in some cases the ordering of selection weights observed for the individual sample does go hand-in-hand with the ordering observed in the aggregative form (on the dataset level), this might not always be the case. Having the ability to observe selection weights on a single sample level enables us to investigate specific samples and understand which variables of this specific sample affected the model the most, and led to un/successful prediction. \n",
"\n",
"Now, to the additional visualization: as explained above, the distribution of selection weights is different for each time-step. The image-like visualization is used to describe this distribution along time; higher selection weights are depicted by a brighter color.\n",
"When ``rank_stepwise`` is set to ``False``, the visualization is using a uniform scale of selection weights along the entire time axis. Therefore, on time-steps where the distribution of selection weights has higher entropy (less concentrated with a narrow set of few features), the selected input variables seem (according to chart) \"less important\". In order to overcome this, one can set ``rank_stepwise`` to ``True``, and the chart will display the same information, but the cells will be colored according to the order of the features (or according to their resepctive selection weight, to be precise) on each time step separately."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Attention Scores"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The temporal fusion transformer model has an internal attention mechanism for weighting the information coming from the sequential data (whether it is the historical sequence or the future sequential data). Part of the model outputs, for each observation, are the attention scores of the model. We can use these scores to try and infer which preceding time-steps affected the output of the model the most. Recall that due to masking, each Future horizon can \"assign\" attention only to steps that came before. \n",
"On this part, we examine the scores both globally (for the entire validation set) and individually (on a single-sample level). \n",
"\n",
"As in the case of aggregating the selection weights, for supply a quantitative description of the scores distribution we use percentiles."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### One step ahead"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The attention scores are horizon-specific, i.e. every future horizon maintains a different set of attention scores for the corresponding observable time-steps. First, we'll examine the attention scores for a one-day horizon (t+1) into the future."
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tft_vis.display_attention_scores(attention_scores=validation_outputs['attention_scores'],\n",
" horizons=1,\n",
" prctiles=[10,50,90],\n",
" unit='Days')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The dashed line stands for the separation between the historical time-steps, and the futuristic time-steps.\n",
"For each step we compute the relevant percentiles of the attention scores.\n",
"The attention scores for the further time-steps are zeroed out by design, using the internal masking mechanism within the TFT model. \n",
"We can see clearly the 7 days cycle among the attention scores, and the general trend according to which the most recent cycles (the ones that are closer to the *separation* line, are more dominant than previous, gradually forgotten, cycles."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Multihorizon Attention\n",
"As noted above, each future horizon step has its own set of attention scores.\n",
"Using the same function we can describe the attention scores distribution for multiple horizons at once."
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tft_vis.display_attention_scores(attention_scores=validation_outputs['attention_scores'],\n",
" horizons=[1,3,5],\n",
" prctiles=50,\n",
" unit='Days')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see that the attention scores for the historical time-steps have quite similiar *characteristics* among the different horizons. They all are decaying towards the past, they all have weekly cycles, but, their weekly cycles are offset due to the difference in weekdays."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The attention scores can also be explored in the single-sample level using ``display_sample_wise_attention_scores()`` function. \n",
"The following chart presents the scores associated with each output horizon (see legend). When we compare scorings of different horizons, we can see that the attention scores signal is somewhat correlated between two differnet horizon."
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAABuIAAAKqCAYAAADPMUi8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzde5xcdX3/8fdnZvaWzSYgCbkBBrwhKEISq0WLUWq0hov1Z/GCN1RCqVasVYtay2KtUsHW2FYhtDZopV4QEYgWqBIUUQsJeOGmGAFJstxCLrvJ7ty+vz/O2ZnvzM59Z2fO7Lyej8c85sy5zWdm57bncz6frznnBAAAAAAAAAAAAKC5Yu0OAAAAAAAAAAAAAJiNSMQBAAAAAAAAAAAAM4BEHAAAAAAAAAAAADADSMQBAAAAAAAAAAAAM4BEHAAAAAAAAAAAADADSMQBAAAAAAAAAAAAM4BEHAAAAFCGmbnwsrHdsaA+ZrZx8u/X7liaycze4b0uV7c7HgDdic8iAACA2pGIAwAAmCXMrM/MniR5hErMbLP3GnFm9pUat5trZqNF275jhsMFJElmFjOz08zsq2Z2v5ntNbN0eP1rM/uumX3SzP7YzPraHS8a5yfRS1xGzex3Zna1mb3ZzHraHW89zGy43s/PooTX8MxGCAAAgJlAIg4AAGD2eK2kp3m3X29mQ9U2MrPV9RwYNLMHw3U3NxxpmxQdBF3e7ngi4nW1vE4k/ZmkwZkOBihmZkdI+rGk70h6s6RnSxqSFA+vnyXpTyR9TNJNkv6qPZGiBQYlLZf0p5K+KukOMzuyrREBAAAAVSTaHQAAAACa5p3h9T4FB6cHJZ0h6T/aFlGHc85Zu2OYQRlJWUlzVNvr5B3h9QFJAzMXFipxzm2UtLHNYbSMmc2TtFnSZLLlbklfknSnpKcUfM4dKelFkk6V9PTWR4kZ9E5Jt3u350t6saQPSFoq6ThJ/2NmxznnJtoQX9fqts8iAACA6aAiDgAAYBYws8Mk/XF4858k/TqcfmfpLQClJV0fTr+j0opmdpSkPwpvfnsGYwKKna98Eu6rkl7gnPsn59zNzrm7nHM/ds79l3PuL51zyyW9QoWJG3S23znnfuVdfuyc+6ykEyQ9FK7zbPFdBwAAgAgjEQcAADA7vEPBbzsn6cuSrgjnn2hmz25XUIi8jeH1S83sGRXWe7skk/SopO/NdFCA53XhdVrS+5xzmUorhwm67898WGgn59xjkv7Bm/WadsUCAAAAVEMiDgAAoMOZmSlf0XSrc26bgmRcNpxXslLAzJabmZN0szf7P70x1Jw/FpyZbQ7Xn2z99rIS65Yde83MjjWzz5vZL83sKTObMLNHzOxbZvba8HGUe4ybw30/GN4eMrO/NbOfm9m+8HKHmX3AzHpLbP+OMPYLvNm/KxH7cNF2k/M3lovNey4/a2a/MLM9ZjZuZg+b2dfNrOIB4snYwsvqcN7pZvY9MxsJn6cHzezysDKtmb6rILkmlamKC/8ubw9v/peChEhNzGyBmX3czH5sZo+ZWTK8/oGZ/aWZ1dTi0syOMbN/NrM7zexJM0uZ2S4z+6mZXWxmK2vYR4+Zvc/M/i98/Y2Z2a/M7MJqY+SZ2eFmdp6ZXWNmD4TbJsO/zw1mdq6Z9VfZx7Rew95+prxeSqyzwMz+zsx+4j1fT4Wxbw6XHV/Lvs3szPDv9Zj3nP2Nmc0p2vbk8Pn5ffj6/52Zfc7MDqn0vNRgeXj9pHNu1zT3JUkys14ze5eZfSd8nx4IL9ss+Dx6l5nNrbD9883si2Z2f/h3229mvzWzjWZ2YpX7Lhin0swSZvbnZnaLmT1qZlkzu6bEdtN6L5nZ083sM2a2xcx2h6+JJ83s1+Fr+ENm9qyan8Ro+Ik3vbzUCtbc750FZvaJ8D37VLjs/c18QNNlTfwussCbzex/zGyHmaXN7K5y61fYVy2XByvE9VIzuyJ8f+4P33P3mdkXzOzYKo9p4+R9hLcb/h4AAACYFuccFy5cuHDhwoULlw6+SHqZgko4J+nd3vybwnnbJcVLbLfc267SZXO4/uYa119edD9xSZ9VMCZZpe3+R9L8Mo9x8r4flPQsSb+pFK+kvqLt31Fj7MNF203O31jh+T9H0kSV/V4jaU6Z7f3YXqFg/Kty+9kt6Q+m+XqZfC7Hw9ufDW8/JMlKrP8K7/6fJ+mN3u13VLifN0vaW+V5eUDSsRX2kZD0+RpeO7tLbLvRW75QQbvCctv/StIhZWJ4moKkdrXXzj2SjqrheX9QDbyGy7xeVpdY/mJJT9YQ7/9W2fcfS7qqwva3KBhf0CRdXOVvvGgar9c94X6y5f5Gde7vhZJ+V8Pz8/4y23+ihtfjpSrxmRtuP+ytt0LS/5XY/ppmvpcknS5pfw2P+d+n+/w246LC9+6U17i33tHeevcWLWv2984qSTtrfZ1UiNn/+7+jxm3e4W0zXGG9Zn4XvUpB6+Li7e8qs/7qCvuq5fJgiXgSkv69ynZpSX9X42up4e8BLly4cOHChQuX6V4SAgAAQKebrHg7IOkb3vwrFBxMXyrp1ZI2FW23XdLzFRyY/lI4728lfadovbHw+ixJg5JuCPd5Rziv2Pai2/+hfEXVHeHtByTtUpAMfKuk1yo48PctM3uVK99+bo6Cg4NLJF0k6UYFB+qPkfRxBWMFvUzSRxQc8Jx0TXjffyHp3HDeqyTtKNr/Y2XutyQze4uCg+5S8PyvV3Bgd7+k4yT9taTnKjgQ/i0ze41zzlXY5SckvUTB3+o/FSQMDlFwUPPNkuZL+qqZPdc5V3NlWhUbJX1A0hEKkm7Fbf3eEV5vcc79ysyeV22HZnaW8q+p7ZL+TdIvFTzfCxS0kTtX0jMk3WRmK5xzIyV2daWkPwunH5f0RUk/UpBomqfg9btW0h9UCenbkl4g6QsKXt+PSzpK0ofDbY9VcND+HSW2jSlIAv1Awevtl+H2g8q/fl+p4O98jZmtcs4lK8TS6Gu4Kgsq6b6pIHmYUfAa2qQggZCWtEjS8Qo+Dyq9DiXp7xUk9b4p6SsK/o5PD+N6oaSTFDx/eyV9UMHr5jJJv5V0qKT3K3iPPUPBc/uWeh6LZ6uk1QoSfhvN7C3OuT2N7MjMVkn6oaTJ6sXvSvpvBUnRjIL3wB9Jen2Z7f9Wwd9Ikp6SdImChGRawevobyQtU5AQkaQ/rxLSlxS8Lr8exvF7BcmCRd59Tuu9ZGaHKqhkHVDwuXS5gpM0HlXwnC6VtFLSKVVijaIXeNMz+b0zV8FnyHwFSecbFJwU8QwFnwVtNwPfRf+o4Pm9QcHr77cKHv/RNYZ0jYLnvZI/VfCdJwXJzmKXSnpXOP2IpM8oSFwnlP/8OUjShWaWdM5dVOX+pvM9AAAAMD3tzgRy4cKFCxcuXLhwafwiaUhBosxJurJo2RzlqyiuqrCP1arjDH0FB8ycwkq5Kuu+ydv3uRXWO89b7y0llm/2lu+RdFyJdRYoSKS58LpUFeCwt5/lNcQ/ue7GEssOVr5aZ1TSqhLrDCg48F/2+dXUyoHhMrH4lXKnTeM1M/lcjnvz7gjnfaXC6+s94byKFXEKDmweCJd/WeUru/5Q+SqdKZU4ks727udnqlCpIOmIEvM2etunJP1xmb/P3eE6SUkLSqzTK+npVZ7Td3r39fYqz/t0X8P+62V10TK/evG8KjFPeT5LvBb/psQ6cxVUT04+jnFJXyixXkL5aq+Sz22Nr9fTi2LaJ+lrkt6rIFFYsrqnzN/xd+E+spLeVmHdhKQlRfOeE76OnIIk2JFl/n73lvv7hOsMFz2eSp+L034vFb02T6/3NdGOi2qoiJPUJ2mLt95HvGUz8b0zJmllEx6b//f/mIIq42qXj3nbDJfY50x9F/1jlcfir1/y71Rh2xcq/93ye0lLi5af7O377lKvTQWJ0BHlP+OfWeW11PD3ABcuXLhw4cKFy3QvjBEHAADQ2d6oIOEmBRVwOc65/QqqWSTpVDNb0MrAQpPVI1c5575YbiXn3Hrlz54/u8o+/84594sS+3hCQQWQFFSVHFNnrPU6S0FVliT9vXNuytn/zrkDkt6m4ACgFFQJVXKnpAvLLLvYm35Z7WHWZGN4/bqicXLOUPD6mlBQsVOLDyqoOPq9pHXOuYlSKznnfqKgMkGS3uKPcRWO2/TR8OaYpNc5554sd4fOuYerxPSvzrn/LbHdAUn/Gt7sUZDQKF4n6Zx7qNLOnXNfUvC3k6TXVYlFmrnX8GJv+uZKK1Z6PkN3OOf+scR2o8p/1sxTUJ34/hLrpZWv0OmRVHHstApxfkfBa2FyzMu5kt4g6V8UjBG218xuN7MLzOzpFXZ1pvLjiH3eOfflCveZds7tLJr9HinXUeavnHO/K7HdE5Le7c16f4V4pOBkhrKfi2rCe0nNfU20nZnNM7M1CpJkK8LZuxRUY06aie+dzzjnttQfcUWfVFDdWO3yySr7mYnvogcUJACbzsyOkHStgu+WUUmnOueKq9PP86bfWeq16Zz7rYJKPyl4b763yl03/D0AAAAwXSTiAAAAOttka8gdkqYcYFL+gHmvggPRLWNmRytohSUFLQaruSW8frGZxSus99UKy273po+q4T6nY014nVXQ7q0k59yDClqESdILwlZx5XzVOefK7OdeBQctpeY/tisVVALMUZB8m/SO8Po659yuGvf1p+H1t51z41XW3Rxe9ylojzfpOOWTJv/tnCtuO1ev/6qwrK7XjJnFzGypmT3HzJ43eVG+zekJNcQzU6/hR7zpd4YJzUZVSrze5U1/y5Vvxemvd2SjgTjnPq0g6fJV5d8Dk+IKxu8alvRrM/tkmc+P07zpi0ssr2by/f6kpG9ViPXHCpInkvSKKp9llV6XUnPeS/5rwk8SdoqbzcxNXhRUft2goBpSClqEvnby82kGv3eq/a3aaSa+i77mmtf+OMfM5ilol7tYQTvYNzrn7ipaJ66guleSfu6c+1mFXX5DQSJWyj8P5TTtewAAAKBeJOIAAAA6VHjAcfLM7f9ypce3+ZGCdmxS6fHcZpI/btfV/sHUUhflz2zvVTDGVSlPhFUn5fjJonll12qO54fXv64hSXWbN31chfXuq7Kfp8Lrpj62MP5rw5vvkCQze4akl4bz/rPEZlOElQ6TFTjvq+Fvfp23+RJv2k8kVKziqVGl57Xqa8bM4mb2LjO7RUEiaHu4T79qZW24erXK05l8Df9YQWtEKagouc/MPmVmrzKzQ+rcV6XnbHcD603rNeuc+7lz7i0Kxkx8iYJxDb8iaZu3Wq+CKp5SVVCTr6nf1JvYNbM+BWP3SdLtNSQoJt/vQ6qcgPx5hfts1ntpciwsSfqsmW01s4+b2eowKTItZrbMT0gXX6a7/wp+qyCheqxz7kfe/Jn43hkLq6+a7SznnFW7qPp390x8F5V9bTbKzBIKEmeTr4sPOOeKx66VgkTYYDj9k0r7dM6llE+iHW1mPRVWn9b3AAAAwHQkqq8CAACAiHqnN12yzZpzzpnZlyVdoOAM+BXOua0tiU6qdLZ9NXPKzB+rsl3Wm65U3dAMk4mNkRrW9deplBCp9fHNxGPbKOn1kl4aJuHeEc7fqaACpRbN+psv9KaLW5bVzTlX6Xmt+Joxs/mSvqvaWysOVFk+Y69h51zGzE5RUM32BwqSRx8JL87M7pZ0taRLS7ReLLa/xhhrXa8pr9mw+u42eQkFMzte0j8qXxFztpn9Z9iycdLka6qR19PBkiarCxt5vz9QZr2nysyXmvRecs7tMbNXK3hNPFtBxeZk1WbGzLYqaGF8uXNudwP39Q+S3l5h+XSqMqXge24y0eIUjJn3hHNub5n1Z+J7p9LfKQpm4rtoJh7zv0h6VTj9r865z5dZz4+rnsdkCpKpj5ZaaTrfAwAAANNFIg4AAKADha2b3urN+lWNXejeKalViTj/t+ZZyo/FU4tpJ19Qt/9RcEBzsYLXyVvC+eWqLUvx/+ZfUOnKpHIeqb5KW3xO+STcjxQ8ri0KEpT7nXNZSQoT3m8ttYNWcs5tk/QiM3u5pNdKOklBxUxcQSXK8yR90Mze5Zz7WtsCbSLn3F1mtlZBReBkRdQZqlJNEwGV3ldNey8557aa2TGSXiPpVAWVrkcreE28MLz8jZmd4Zz7QR330wq/c879qo71Z+J7p9bPv9mkqY/ZzD4g6c/Dm99V9THqAAAAZhUScQAAAJ3pNcq3LavHm83sr51zE80OqITHvemxOg+mdoInJS1VbX8Hf50nZyac6Qmrqb4i6UMK2v71h4tqaksZ8v/mmsbf3N/P0gb3MW1mNiTpzeHNH0taPZl4K+Hg1kRVG+fczQrbeoaP4yQFj+WNCip/vmJmdzrn7m9flM3jnEub2eXKJ+KeXbTK45IOV2Ovp10KqrFMrXu/N+u9NLl9RkH7yuskKWxV+nIFla9rFVQhXW1mR9UxHqScc+9Qvno2Cmb7904pkf4uMrPTlR+X8RcKxoWrlOjz46rnMTkVtpgEAACIDMaIAwAA6EyTbSkzkt4m6U1VLp8N1z9YQZWMz9V537Wuv8WbPqnO+5gp9T7WSn4RXj/bzMqNLTTJb2v4i7Jrtd/G8HoyCfd/zrl7y6xbyu+UPxD6R9OIw69iefk09jNdz1YwdpQkfaNcEs6CctSVpZZFgXNun3Nuk3PuTEnnh7MTClqRziZ+JVjxe33yNfUsM1tWz07DdpiTCctVYUVyJZPv933Kj9FZr2a9l0pyzj3pnLvKOXeKgoo7SZov6U+afV8tFsXvnZkW2e8iM1sp6UoFx552SjrFObevymbbFIzFKUkvrrL/hIKKTkm6NxwzDgAAIHJIxAEAAHQYMztUQQWDJG12zn3FOfe1ShdJfy8pGW5zVtEuD3jTfTWEMLl+tXV/ruCAmiS9LYy73ep9rJXcGF7HJL2r3Epm9nRJrw5v3uWce2ya9ztjnHP3KKj8mggvX6pz+6yk74Q3nx+OTdWIXyr/2nlTvYmTJvI7iJQbP0oKkttLZjaUpvHH+1tYdq2IsBp77oZWedO/LVr2HW/6gw2EMvl+XyDpdeVWMrM/VNAKVJK+X0db1wJNfC/VoqNeE1VE8XtnpkXyu8jMDldQgTlHwViSpzrnfl9tu/A9M9ki9Xgze2GF1f9MwbhwUv55AAAAiBwScQAAAJ3nLZJ6wumv17KBc26P8gdbX2lmh3mL/XFxitu5lTK5/jMrHSR3zjlJw+HNeZK+Y2YVD/Ka2R+Y2WtqiKFR9T7WSv5T0t5w+uNmtqJ4BTPrl3SF8n+vz03zPmecc+6lzrn+8HJZA7v4lIIkniRdEVZElGVmh5tZwcHj8LXzqfDmoKRvVar0CA/4zoQHJE1Wwb3RzKYkb83s2cpXFLWVmf2RmR1dZTU/obOt7FrR8SMze3v4XiorfJ19yJv1raJVrlT+8b7PzMqO52dmCTMrTqz+m6R0OP25MKlRvN0hkv7dm/W5SjHXYNrvJTN7dQ3vj057TZQV0e+dmRa576KwHe71Ck5QyEo60zm3pfJWBdZ7018ysymtf83sSEn/FN5MK3iPAgAARBJjxAEAAHSeyYq2tKSr69juG5JOVXAy1tsl/YMkOeceMbMHJS2X9C4zu1tBe6/JA8D7nXMPe/v5kaSTFVSGfNHMvqzCcVl+O9keyjn3FTM7SdK7FbSYus/M/l3SZkkjCtr+LVXQ1u80BZUk/yDpu3U8rnrcqvxYT58KE4m/VdDiU5KecM49UcuOnHO7zew9kr4iaUhBwuBzCs7KH1PwWD4o6Zhwk/+R9OUmPY7Ics49YGbvVvBYD5X0EzP7bwUHZR9UcFB2gaTjJL1K0mpJP5X0H0X7+Q8ze5WCiocXKXjtfEHB6+9JBc/58ySdEi5fMAOP5Ukzu17Ba/MFkm41s3+W9BsFCcJXSvpLBf9XbZU05QB4i50s6e/M7GcK3kN3KXifSdIySacreO9LwXP4360OsAFHK2iZ+vnwb/FjSfdJekrB836UgnaKb1Y+yfDfzrkf+jtxzqXM7A0KXj/9kr5sZm9UkKD7jYLPgMMlvUTSGxQc4P+ct/2vzexCBdXFSyVtMbNLJP1QwWfxH0j6G0mTJzlc5py7ZToPvEnvpTdKeouZ3aLgZIxfKBhHrUfSEeHyPw3X/Y0Kq+M6UgS/d2ZURL+L/lXB61IKKqsfMLPnVVg/6Zz79eQN59wPzOw/FFT4PU/SXWZ2saTbJcUVtB39kPLVcB93zj3Q5McAAADQNCTiAAAAOoiZ/YGCg1KS9APn3JN1bP4dBcm1PknvUJiIC12o4Kz6+SpKiEi6RcEB3kmXSjpX0iJJ54QX35EKDhJPWifp95L+VsFBsw+Hl3L2VHkcDXPOPWhmVyh4/M9TYbs6KXgehuvY33+Z2VwFZ+/PkfTR8FLsWklvCqs1Zr3wedmr4LW0QME4hm+rsEm5v/mZkp6Q9OcKWuZdUOf2zXCugtfKUQpaH361aPmYgjhPV/sTcVKQZH6xKo+tNCLpdc65x1sT0rT8XtIhCqqb3hxeyslKukzSeaUWOufuMLOXSbpKQdLtNeGlJs65T4ZVkR8NY/p0mVUvk/SeWvdb5T6b8V6KS3pFeCnn1wpaB05UWKeTROZ7pxUi+F3kV4y+O7xU8pCCk4F8f67g8+ydCpLG/1Jiu6ykC51zFzUWJgAAQGuQiAMAAOgs/vhu36hnQ+fcPjP7noLxrJ5pZi+brNhwzm00s50Kkg6rFCQ9esvs51EzW6XgoObJCg64zVFwwKzU+k7SJ8zsSwoOjr5C0rMUHBxNSXpMQYXLjyR9xzn3q3oeVwPeLen/FFSCHKsg+djw72Ln3KVmdoOCyqhXKng+ehU8rp9K2uic68hKi+lwzl1rZssVvGb/REFF2QIFr5OnFFTfTFZubS6zj5SkvzCzyxS8dlYrSKDMUXDg/NfhtlfO4OPYEbYE/KCCyqGjFFRAbVdQPfQvYeXS6TMVQx0ulnSngvfYCgVVP4cqSL4/JelXCqqp/t05t69dQdbDOXeCmT1f0h9L+kNJz1VQdTakYNzL3Qo+P34s6avOufuq7O//wnaiZylInr5AQVIto+BvulXBuFZXldn+42b2TUl/IenlCioNYwqSmz9SUAl32zQecqn7nM576a8UVECtlnS8pMUKXhNxBZVxv5D0bUlfnkVJuCh+78y42fZd5JxLK6jS/08Ff8OXKmh1Ofle/YGkf5sNfzsAADD7WZeclAsAAAAAAAAAAAC0VKzdAQAAAAAAAAAAAACzEYk4AAAAAAAAAAAAYAaQiAMAAAAAAAAAAABmAIk4AAAAAAAAAAAAYAaQiAMAAAAAAAAAAABmQKLdAXS7BQsWuOXLl7c7DCDSxsbGNDg42O4wALQQ73ugu/CeB7oP73tgdtqxY4eWLl06ZT7veaD78L5Ht9myZcsTzrmFpZaRiGuz5cuX64477mh3GECkbd68WatXr253GABaiPc90F14zwPdh/c9MDuZmXbs2DFlPu95oPvwvke3MbOHyi2jNSUAAAAAAAAAAAAwA0jEAQAAAAAAAJi2FStWtDsEAAAih0QcAAAAAAAAgGnbsmVLu0MAACBySMQBAAAAAAAAmLZ169a1OwQAACKHRBwAAAAAAACAabv88svbHQIAAJFDIg4AAAAAAAAAAACYASTiAAAAAAAAAAAAgBlAIg4AAAAAAADAtG3fvr3dIQAAEDkk4gAAAAAAAABM25YtW9odAgAAkUMiDgAAAAAAAMC0nXbaae0OAQCAyEm0OwAAAAAAAAAAAIBmyWazeuqppzQ6Oqrx8XFls9l2h4QOEI/HNTQ0pKc97Wnq6+tr2n5JxAEAAAAAAAAAgFkhnU7r97//vRKJhJ72tKdpzpw5isViMrN2h4YIc84plUpp7969evjhh3XEEUc0LRlHIg4AAAAAAADAtF122WXtDgEAtGvXLvX19WnJkiUk31AzM1Nvb68WLFggKXgdLVmypCn7Zow4AAAAAAAAANO2bt26docAANqzZ48OOeQQknBo2Lx587Rv376m7Y9EHAAAAAAAAIBp46A3gChIp9Pq7e1tdxjoYD09PcpkMk3bX+QTcWa22MzWm9lvzWzczB41s+vM7ORp7neemX3SzO41s/1m9qSZfd/MXl/Dts8ys38zs/vCbSfM7CEz+5qZvWw6cQEAAAAAAAAAgMZxYgCmo9mvn0gn4szsOEm/kvQ+SUdJmpC0QNIpkm4ys/Mb3O9hku6S9DFJR0vKSJon6RWSvmlmX6iw7Wsl/ULSX0h6jqS4pJSkIyS9QdJmM/v7RuICAAAAAAAAAADA7BHZRJyZDUi6VtIhku6U9Dzn3HxJB0v6rCST9CkzW1Pnfk3SVZKOlPSgpJc454YkDUn6sKSspHPN7OwS2y6Q9GVJ/ZK2SnqxpAHn3FxJzwj3K0l/a2Yn1fWAAQAAAAAAgA52yimntDsEAAAiJ7KJOEnnSHq6pFFJpzrn7pYk59xe59wHJV2jIBn36Tr3e7qkFylIuP2pc+62cL/jzrmLJX0+XO8TZlbcSPZUBQk7hdv+zDmXDbffJunNkh4Il7+uzrgAAAAAAACAjnXddde1OwQAACInyom4M8PrK51z20ssvzi8XmFmz2lgv//rnLurxPJLJDlJixW0qvQtCq+fdM49XLyhcy6loG2lJA3WERMAAAAAAADQ0U499dR2hwAAQOREMhFnZkOSVoY3byiz2k8l7QmnT65j9y+vtN8w6Xd3eLM4EfdgeH2ImR1RvK2ZJSQdF97cWkdMAAAAAAAAQEe7/vrr2x0CAACRE8lEnKTnKmg7KeWTYgXClpD3hzePqWWnZnaogjHnyu43dE+Z/V4naSSc/raZvcjMYuG+j5R0paRnSvqVpC/VEhMAAADQrTZt26Q1V63RXz70l1pz1Rpt2rap3SEBAAAAQNfauHGjhoeHddddd7XsPn/xi1/o0ksv1bve9S4dd9xxSiQSMjO98Y1vbFkMMy3R7gDKWOJN76iw3uSyJRXWadp+nXNjZnaKgvHpViioykuaWUpBK8o9kv5N0seccxM1xgQAAAB0nU3bNmn4tmGNZ8YlSTvHdmr4tmFJ0tqj1rYxMgAAyrvmzu26+Ib7tWP3AS09aEAfetVz9NoTlrU7LAAAmmLjxo265ZZbtHz5ch1//PEtuc+3ve1t+vnPf96S+2qXqCbi/PHVDlRYb394PbdV+3XObTGzV0j6bwXtM3vDi8LreeFlT/G2k8xsnaR1krRo0SJt3ry5xvCB7jQ6Osr7BOgyvO+B2e8fH/nHXBJu0nhmXP942z9q8GGGWwZmO77r0Ylu25HSxl8llcwGt7fvPqAPf/Mu3XPvPTpxaU97g4uIm2++ueR7m/c80H3a+b6fP3++9u3b15b77nSZTEaSND4+Xvdz+KlPfUoXXXSRzj//fH30ox+tebtYLKbjjjtOJ5xwglasWKFrr71W3//+95VKpdr6dxwfH2/aaziqibjICpNo/6agReWbJP1QQeLuBZI+Lemtkk42s5c6535Xah/OuQ2SNkjSqlWr3OrVq1sQOdC5Nm/eLN4nQHfhfQ/Mfruv2F16fmY373+gC/Bdj070sYt+kEvCTUpmpU0Px/XRN69uS0xRs2HDBq1bt27KfN7zQPdp5/v+3nvv1dDQUFvuu9PF43FJUn9/f93PYV9fX+66nm1vv/323P1K0tatWyVJPT09bf079vf364QTTmjKvqI6RtyYNz1QYb054fVoK/ZrZi+RdJmklKRXOOe+5pzb4Zzb7Zy7RdLLJd0raamki2qMCQAAAOg6iwcX1zUfAIB227G7dHOlcvO70TnnnNPuEAAADdi4caPMTLfccosk6ayzzpKZ5S7Lly+fsfv2k3CzVVQTcf74bUsrrDe5bGeL9nteeL3JOfeb4o3CceG+EN481cysxrgAAACArnLeivPUG+stmNcf79d5K84rswUAAO219KDS53SXmw8AQKcYGBjQokWL1NMTtFqeN2+eFi1alLssXLiwzRF2tqgm4u6T5MLpY0utYGYxSc8Jb95Ty06dc49LeqLSfkPHlNnvc8Prki0nQ9vC6wFJi2qJCwAAAOg2a49aqzOec0budsxiGj5xWGuPWtvGqAAAKO9Dr3qOeuOF51wP9MT1oVc9p8wWAIBuc82d2/WSi36gI8/fpJdc9ANdc+f2dodUkze84Q0aGRnRiSeeKElav369RkZGcpfbb7+9zRF2tkgm4pxz+yTdEd58ZZnVXiRpfjj9/Tp2f3Ol/ZrZMuWTdMX7newEfkSF/T/dm2ZESAAAAKCM4xYel5s+uO9gknAAgEh77QnLdMYLD8/djpv06dc9X689YVkbo4qWa6+9tt0hAEDbXHPndn3k6l9q++4DcpK27z6gj1z9y45JxmHmJNodQAVXSnqhpDPN7BPOueI2kR8Mr7c45+6vc79/JmmNmb3AOffzouUfkGQK2lLeXLTs55KOk/QnZrbMOVfwDjKzuKSzwpt3O+fGBAAAAKCkicxEbjqZTbYxEgAAavP8ZfNz0wcP9pKEK7Jy5cp2hwAAVS0/f1PL7utAKqP3f/0uvf/rd83I/h+8iJMZO0GUE3GXSXq/ggqz683src65e8xsSNLHJb0uXO+jxRua2WRbywudc8NFi78j6WcKKuq+bWZvds791Mz6JL03vE9JusA5V3w04FJJb5U0T9INZvZeST+WlJb0bEmfUZA8lKTP1/2IAQAAgC6SzOR/bqez6TZGAgBAbcZT2dx0Mp2tsGZ3WrZsmZxz1VcEAHSsxYsXl5w/OjoqSbrkkkt06aWXllxnZGRkxuKKssgm4pxzB8zsdAXtIVdIutvM9kqaq6ClppP0UefcjXXu15nZ6yX9UNKRkn5iZqOS+pV/Pi51zl1eYtvbzOyvJV2soH3lzQqScCkFY8JN2uCc21BPXAAAAEC38SviUplUGyMBAKA246lMbjqZIREHAOg+jz76aMXlY2NjGhujWaAvsok4SXLO/dzMnifpI5JOkbRM0pOS/k/SPzvn6hkbzt/vI2Z2vKS/UVBZt1zBeG53Sfqic+6bFbb9JzP7oaS/kPRHkg6TFJe0XUGl3eXOuf9pJC4AAACgm/iJuLRLK+uyilkkh7EGAEASFXEAMBvMVDvHyTHiDngnbQz0xGfdeKLlKp+Hh4d14YUX6oILLtDw8HBrg4q4SCfiJMk5NyLpvPBS6zZWwzp7JX0svNQb0x2S3lnvdgAAAADy/NaUkpTKptQX72tTNAAAVDeRzh9czTopnckqEeckkklnn312u0MAgLaZTLZdfMP92rH7gJYeNKAPveo5syoJh8ZEPhEHAAAAYHbyK+KkoD0liTgAQJT5FXFS0J6SRFzehg2M1AKgu732hGUdnXiLxYLvNMb7bC5+KQAAAABoi+KKuGQ2WWZNAACiYdyriJNoT1ls5cqV7Q4BADAN8+bNkyTt3r27vYHMMiTiAAAAALRFqYo4AACibKK4Io5EXIGtW7e2OwQAwDQce+yxkqSrr75ae/bsacl97t+/X0888UTuMjER/J+YTCYL5o+OjrYknplAIg4AAABAW0xJxGVJxAEAoq24Im6CRBwAYBZ561vfqt7eXt16661asGCBli1bpuXLl+ulL33pjN3nZz7zGS1cuDB3+drXviZJ+va3v10w/73vfe+MxTDTSMQBAAAAaAtaUwIAOs1Eqqg1ZYZEnG/JkiXtDgEAMA1HH320brrpJr361a/W/PnzNTIyooceekiPPPJIu0PraIl2BwAAAACgO9GaEgDQaYor4FIk4grs2LGj3SEAAKbppJNO0kknnVT3dsPDwxoeHm7Zdp2EijgAAAAAbVFcEZfOptsUCQAAtRkvroijNWWB2X4gFQCARpCIAwAAANAWxRVxtKYEAETdeKow8UYirtCFF17Y7hAAAIgcEnEAAAAA2qK4Io7WlACAqKMiDgAA1ItEHAAAAIC2oCIOANBpiseIm2CMOAAAUAWJOAAAAABtUZyIoyIOABB1VMRVdscdd7Q7BAAAIodEHAAAAIC2mNKaMksiDgAQbSTiAABAvUjEAQAAAGgLWlMCADpNcWtKEnGFVq1a1e4QAACIHBJxAAAAANqiOPFGa0oAQJQ556Ym4hgjDgAAVEEiDgAAAEBb0JoSANBJipNwEhVxAACgOhJxAAAAAFrOOTelNSWJOABAlBWPDydJKSriClxwwQXtDgEAgMghEQcAAACg5Uol3WhNCQCIslIVcaXmdbPh4eF2hwAAQOSQiAMAAADQcsXVcBIVcQCAaCtVEUdrykJLly5tdwgAAEQOiTgAAAAALVcqEZfMJkusCQBANIynSowRR2vKAjt37mx3CAAARA6JOAAAAAAtl8xMTbrRmhIAEGUTaSriAABA/UjEAQAAAGg5WlMCADpNyYo4EnEFVqxY0e4QAACIHBJxAAAAAFquVEVcqXkAAEQFY8RVt2XLlnaHAABA5JCIAwAAANByVMQBADrNRImkG2PEFVq3bl27QwAAIHJIxAEAAABoORJxAIBOQ0VcdZdffnm7QwAATMPGjRs1PDysu+66q2X3uXz5cplZxcsll1zSsnhmQqLdAQAAAADoPqXaUKYyJOIAANFVMhFHRRwAYBbZuHGjbrnlFi1fvlzHH398S+/74IMPVm9vb8llg4ODLY2l2aiIAwAAANByVMQBADrNeKnWlFTEAQAgSRoeHpaZaXh4uKHtr776ao2MjJS8nHvuuc0NtsVIxAEAAABouVIVccns1HkAAETFBK0pq9q+fXu7QwAAIHJIxAEAAABouZIVcbSmBABE2ESpijhaUxbYsmVLu0MAADRg48aNMjPdcsstkqSzzjqrYIy25cuXtzfADscYcQAAAABajtaUAIBOU3KMOCriCpx22mlyzrU7DABAnQYGBrRo0SLt2rVLqVRK8+bN08DAQG75woUL2xhd56MiDgAAAEDL0ZoSANBpSlbEkYgDAPh+8Q3pn58nDR8UXP/iG+2OqCZveMMbNDIyohNPPFGStH79+oIx2m6//fYZj+Gv/uqvtHDhQvX29mrx4sV6zWteoyuvvFKZzNQTYToNiTgAAAAALUdrSgBApylZEUdrSgDApF98Q7rufdKe30tywfV17+uYZFy73XXXXdq/f7/6+/v16KOP6nvf+57OPPNMnXzyydq9e3e7w5sWWlMCAAAAaLlSFXG0pgQARBmtKau77LLL2h0CAFQ3PL9195U6IF19dnCZCcN7Zma/LfTa175WJ510kl72spfpkEMOkSQ9/PDD+pd/+Rf90z/9k2655RadccYZuvHGG9scaeNIxAEAAABoOcaIAwB0mvHU1KRbqXaV3WzdunXtDgEAMMMWL15ccv7o6Kgk6ZJLLtGll15acp2RkZEp8z73uc9NmXfEEUfo4osv1pFHHqn3vOc9uummm3TjjTdqzZo1jQfeRiTiAAAAALQcrSkBAJ1mIl2qIq7zx61pJjOTc67dYQAAZtCjjz5acfnY2JjGxsaacl/nnnuuLr74Yj344IO67rrrSMQBAAAAQK1oTQkA6DSlKuJSGZJOANBxZqqd4+QYcakD+Xk9A9Kpn5eOO2Nm7rMNyp1wMTw8rAsvvFAXXHCBhoeHm3JfZqYXvvCFevDBB7Vt27am7LMdYu0OAAAAAED3KVURl8xOTc4BABAVJceIy9CaEgAQOu6MIOk2/3BJFlzPsiQcGkNFHAAAAICWK1kRR2tKAECElRoPLpN1ymSd4jFrQ0TRc8opp7Q7BABor+PO6OjEWywW1G5Fpc2wc0633367JOnII49sczSNoyIOAAAAQMtREQcA6DSlKuIkKVkiQdetrrvuunaHAACYhnnz5kmSdu/e3ZL7q5bwu+yyy/Tggw9KktauXduCiGYGiTgAAAAALVcq6ZbOpiNz5iUAAMVKVcRJJOJ8p556artDAABMw7HHHitJuvrqq7VnzwyNped53/vep/POO0+33nqrDhzIj633+9//Xueff77e+973SpJe/vKX60/+5E9mPJ6ZQmtKAAAAAC1XqjWlFCTjeuI9LY4GAIDqJspUxE1kMpL47pKk66+/vt0hAACm4a1vfasuueQS3XrrrVqwYIEOPfRQ9fT06LDDDtOtt97a9Pvbt2+frrjiCn3+859XLBbT/PnzlclktHfv3tw6L3vZy3TVVVc1/b5biUQcAAAAgJYr1ZpSCirlSMQBAKJo3Kt860vEchVyVMQBAGaLo48+WjfddJM+/elP6/bbb9fIyIiy2Zn7nvvzP/9zLVy4ULfddpsefvhhPfnkk8pmszr88MO1atUqvelNb9L/+3//Lzd2XaciEQcAAACg5cpVxKUyKYoKAACR5I8RN2+gR4/vC04qIREHAJhNTjrpJJ100kl1bzc8PKzh4eG6tnnxi1+sF7/4xXXfV6fp7DQiAAAAgI5UriIulU21OBIAAKpzzhUk4ob68+e2JzMk4iYx1isAAFORiAMAAADQcpVaUwIAEDXprFM2zDHFY6Y5vfHcslSa5NOkDRs2tDsEAAAih0QcAAAAgJbzW1P2Wm9uOpWhIg4AED1+NVx/IqbeeP6QWjKTKbVJVzrnnHPaHQIAAJFDIg4AAABAy/kVcf2x/tw0rSkBAFE0nsq3n+zviavHS8RNMEYcAACogEQcAAAAgJbzK+L6LZ+IozUlACCKJtL5qre+REy9Ca8ijkQcAACogEQcAAAAgJZyzpWviKM1JQAggoor4vpIxJV07bXXtjsEAAAiJ/KJODNbbGbrzey3ZjZuZo+a2XVmdvI09zvPzD5pZvea2X4ze9LMvm9mr6+wzbCZuRovN08nPgAAAGC2SmfTcnKSpEQsUThGHK0pAQAR5I8R19cTL6yIy5CIm7Ry5cp2hwAAQOQk2h1AJWZ2nKQfSDoknLVX0gJJp0haa2Yfdc5d1MB+D5P0Q0lHhrNGJc2T9ApJrzCzLzrn/qLEpqOSHq2w65ikheH01nrjAgAAALqBXw3XF+9T3OK521TEAQCiaEpryjgVcaUsW7ZMzrl2hwEAQKREtiLOzAYkXasgCXenpOc55+ZLOljSZyWZpE+Z2Zo692uSrlKQhHtQ0kucc0OShiR9WFJW0rlmdnbxts65S5xzi8tdJJ3jrb6xvkcMAAAAdAc/Edcb6y1MxFERBwCIoImC1pSMEQcAAGoX2UScgqTW0xVUoZ3qnLtbkpxze51zH5R0jYJk3Kfr3O/pkl6kIOH2p86528L9jjvnLpb0+XC9T5h5PXJq8/bw+k7n3C/r3BYAAADoCslMMjfdG+9VwmvUkcwmS20CAEBbjXsVcf20pgQAAHWIciLuzPD6Sufc9hLLLw6vV5jZcxrY7/865+4qsfwSSU7SYgWtKmtiZgskvSa8ubGOeAAAAICuUtyaMmH5RBytKQEAUTTuV8Ql4uqN56u5qYjLO/vsKQ2mAADoepFMxJnZkKTJ0V1vKLPaTyXtCadPrmP3L6+03zDpd3d4s+ZEnKQ3S+qRlJJ0ZR3bAQAAAF2loDVlvLcwEUdrSgBABBWMEVfcmpKKuJwNGza0OwQAACInkok4Sc9V0HZSyifFCjjnspLuD28eU8tOzexQBWPOld1v6J569huabEv5XefcE3VsBwAAAHQVvzVlX7yvYIw4WlMCAKJoakWc5W5TEZe3cuXK6isBANBlEtVXaYsl3vSOCutNLltSYZ0Z36+ZPV/SivDmxhrWXydpnSQtWrRImzdvruVugK41OjrK+wToMrzvgdntgfEHctMHRg9oSEO52/fcd48279jchqgAtBLf9eg0v3owX7H9xGM7ldqTT8Q9sO1Bbd5c6TBT99i6dWvJ9zbveaD7tPN9P3/+fO3bt68t943ZY3x8vGmv4agm4ga96QMV1tsfXs9t834nq+GekLSp2srOuQ2SNkjSqlWr3OrVq2u8G6A7bd68WbxPgO7C+x6Y3Xq390qPBtOHPu1QDYwOSGG3yuXPWK7Vx65uW2wAWoPvenSa+275rXTffZKkZyw/Qgvm9kq/CW4vXnqYVq+up6nS7Fbqvc17Hug+7Xzf33vvvRoaGqq+IlBBf3+/TjjhhKbsK6qtKTuGmcUlnRne/G/nHINaAAAAABX4Y8QVt6ZkjDgAQBSNp/JjxPUnYuqNM0ZcKUuW1Nq0CgCA7hHVRNyYNz1QYb054fVoG/f7KkmLw+mNNcYBAAAAdK2JbD4R1xvvVcLyjTpSGRJxAIDo8ceI6+uJqzfhjW/KGHE5O3bQohMAgGJRTcT539pLK6w3uWxnG/c72ZbyV865rTXGAQAAAHStZCaZm+6L9xUm4qiIAwBEUEFFXE9cvQmvIo5EXM7w8HC7QwAATMPGjRs1PDysu+66q2X3+Ytf/EKXXnqp3vWud+m4445TIpGQmemNb3xjzfv4zW9+o3e961064ogj1NfXp6VLl+qNb3yjtmzZMoOR1y6qY8TdJ8lJMknHSrq/eAUzi0l6Tnjznlp26px73MyekLQg3O8NZVadbOxdcb9mdpCk08ObV9QSAwAAANDtiltTppXO3faTdAAARMWEl2zrS8QKEnETtKbMufDCC0nGAUAH27hxo2655RYtX75cxx9/fEvu821ve5t+/vOfN7z9TTfdpNe+9rXav3+/JGn+/PkaGRnR17/+dX3rW9/Sf/7nf+otb3lLs8JtSCQr4pxz+yTdEd58ZZnVXiRpfjj9/Tp2f3Ol/ZrZMgVJulr2+0ZJfZIykv6rjhgAAACAruUn26a0pqQiDgAQQRPFFXFxKuIAAPANDw/LzOo+IaOnp0fHH3+83v3ud+uyyy7Tq171qpq3HRkZ0etf/3rt379fr3zlK/Xggw9q9+7dGhkZ0Zlnnql0Oq13vetduvvuu+t8NM0V1Yo4SbpS0gslnWlmn3DOFbeJ/GB4vcU5N6Virsp+/0zSGjN7gXOuONX6AQWVeDuVT9qVM9mW8gbn3EgdMQAAAABdq7g1ZdbyBzCTWSriAADRM572E3Ex9XkVcSkq4gAAaNhPf/pTxeP5sVdvu+22mre96KKLtHfvXh1++OG6+uqrNXfuXEnSoYceqiuuuEL33XeftmzZor/7u7/Tt771rabHXqtIVsSFLpP0kKQhSdeb2TGSZGZDZvYZSa8L1/to8YZm5sLLcIn9fkfSzxQ89m+b2YvDbfrM7K8lvT9c7wLnXNmjAGb2bEkvDm/SlhIAAACokd+asjfeq7jl/+lKZaiIAwBEz0TKb03JGHHl3HHHHdVXAgBEzsaNG2VmuuWWWyRJZ511lswsd1m+fPmM3befhKtHNpvV1772NUnSueeem0vC+fv9wAc+IEm6/vrrtXfv3ukFOg2RrYhzzh0ws9MVtIdcIeluM9sraa6CJJqT9FHn3I117teZ2esl/VDSkZJ+YmajkvqVfz4udc5dXmVXk9VwTylI7gEAAACoQXFF3LjGc7dpTQkAiKLiirgeWlMCAGaRgYEBLVq0SLt27VIqldK8efM0MDCQW75w4cI2RlfaPffco0cffVSSyrazXLNmjSQpmUzq1ltv1Wte85qWxeeLckWcwraRz5P0eUnbFIzH9qSkTZJe6Zy7qMH9PiLpeEmfknSfggTcPgWtKM9wzp1baXszi0l6a3jz6865iUrrAwAAAMjzK+L64n2MEQcAiLxxryKuv6eoIo7WlDmrVq1qdwgA0Fabtm3SmqvW6LgrjtOaq9Zo07ZN7Q6pJm94wxs0MjKiE088UZK0fv16jYyM5C633357myOc6p577pEkmZmOOeaYkussWLBAhx56aMH67RDZirhJ4dhr54WXWrexGtbZK+lj4aXemLKSjqh3OwAAAAC0pgQAdJ4JryKuLxFTIkZFHACg0KZtmzR827DGM0HHj51jOzV827Akae1Ra9sY2ey0c+dOSdLBBx+s/v7+sustXbpUjz32WG79doh8Ig4AAADA7FLcmpKKOABA1BVXxMUsfw44iTgA6CzPv+L5Lbuv8cy4zv/R+Tr/R+fPyP5/+fZfzsh+O8HY2JgkFbTQLGXOnDmSpNHR0RmPqRwScQAAAABaakpFnPIVcclsstQmAAC01XjKGyMuEZeXh9MEibicCy64oN0hAABm2OLFi0vOn0x0XXLJJbr00ktLrjMyMjJjcUUZiTgAAAAALVWxIo7WlACACJqsiDstdquWbfywYvu269beQ/SZ9Bn6SebkNkcXHcPDw+0OAQAwwx599NGKy8fGxnLVajNpcHBQknTgwIGK6+3fv1+SNHfu3BmPqRwScQAAAABayq+IozUlAKATTKQzOi12qy7q+XfF9wUnlBwWe0IX9fy7PpFKSPrj9gYYEUuXLtWOHTvaHQYAVDRT7RyLx4iTpP54v4ZPHJ5VY8Q550rOHx4e1oUXXqgLLrigJSdmLF26VJL01FNPaXx8vOw4cZPfS0uWLJnxmMqJVV8FAAAAAJrHr4jrjfcqbrSmBABE20Qqqw8nvqE5Vvg9NceS+kt3ZZuiip6dO3e2OwQAaJu1R63V8InDWjK4RCbTksElsy4JFyXHHHOMpCAxeM8995Rc54knntBjjz1WsH47UBEHAAAAoKUqVsTRmhIAEDGZrFMyk9XSxBMlly/Rky2OCAAQVWuPWtvRibdYLKjdKlf1FiXPfe5ztWjRIj366KO66aabtGLFiinr3HTTTZKk3t5evfSlL211iDlUxAEAAABoKT8R1xvvVUK0pgQARFcyHYwPt8MtKLl8hztE2Wz0D1i2QqmDoACAzjFv3jxJ0u7du9sbSA1isZje+MY3SpK+8IUvTBmXLpvN6p//+Z8lSaeeemrusbUDiTgAAAAALVXQmjJW2JqSijgAQNSMpzKSpM+kz1CyqLnUftcbzM9k2xFa5GzZsqXdIQAApuHYY4+VJF199dXas2dPS+5z//79euKJJ3KXiYngxM1kMlkwf3R0dMq2559/vubNm6eHH35Yr3vd6/Twww9Lkh5//HG94x3v0O23367e3l5deOGFLXks5ZCIAwAAANBSFVtTUhEHAIiY8XSQiLs2+1JdY3+cm59xpvNT79a12ZdqIk0iTpLWrVvX7hAAANPw1re+Vb29vbr11lu1YMECLVu2TMuXL5/Rto6f+cxntHDhwtzla1/7miTp29/+dsH89773vVO2Xbx4sa666irNmTNHN954o57+9KfroIMO0qJFi/SVr3xFiURC//Ef/5FLMLYLiTgAAAAALVVQERfvLUjEJbPJUpsAANA246l8ku2BnmflpiesT9dmgwOTSRJxkqTLL7+83SEAAKbh6KOP1k033aRXv/rVmj9/vkZGRvTQQw/pkUceaXdoZb3yla/UXXfdpbPOOkuHHXaYDhw4oEWLFumMM87QT3/6U73lLW9pd4hF9fQAAAAAMMMmsoUVcXHRmhIAEF0TYUWcJA3G0rnpPiUlOUlGa0oAwKxx0kkn6aSTTqp7u+HhYQ0PD7dsO9+znvUsfelLX5rWPmYSFXEAAAAAWsqviCvVmtI5146wAAAoya+ImxPPJ+XiyqpHwW0q4gAAQDkk4gAAAAC0jHOuYIy43nivYhZT3IKqOCentEuX2xwAgJYbT+WTb3Os8DuqX8HJJSTiAtu3b293CAAARA6JOAAAAAAtk3ZpZV1wsDJucSViQTVcT6wntw7tKQEAUTLhJdkGYoXfUSTiCm3ZsqXdIQAAEDkk4gAAAAC0jN+Wsjfem5vuiXuJuCyJOABAdPgVcf1FFXF9FibiGCNOknTaaae1OwQAACKHRBwAAACAlvHbUvbF+3LTBRVxJOIAABFSmIijIg4AANSHRBwAAACAlilbEUdrSgBARPmtKcsm4qiIAwAAZZCIAwAAANAy5Sri/KQcFXEAgCiZ8Cri+kRFXCWXXXZZu0MAACBySMQBAAAAaJlaWlP6VXMAALTbeCqfZOsrqogbMBJxvnXr1rU7BAAAIodEHAAAAICW8dtOlm1NSUUcACBC/DHiestVxGUygmRm7Q4BACRJzrl2h4AO1uzXD4k4AAAAAC1Da0oAQKfxx4jrdYVV27SmBIDoicfjynCCBKYhm80qFmte+oxEHAAAAICW8RNx5SriaE0JAIgSvyKupzgRR2tKAIicOXPmaHR0tN1hoIPt379fAwMDTdsfiTgAAAAALeMn2QrGiIvTmhIAEE3jaS8RV9Sasi+8PUEiTpJ0yimntDsEANC8efO0a9cuquLQEOecdu/ercHBwabtk0QcAAAAgJYp15qSMeIAAFE1kcon2XqypVtTpjKMRSRJ1113XbtDAAANDQ1pcHBQDz30kHbv3q10Os2YcajKOaeJiQnt3LlT6XRaBx98cNP2nWjangAAAACgilpaU6YyJOIAANEx7lW7JdxEwTLGiCt06qmnkowD0HZmpkMPPVT79u3T3r179dhjj1Edh5okEgnNnz9fhx56aFPHiCMRBwAAAKBlyrWm9JNyVMQBAKLEHyMuXlwRNzlGHAd4JUnXX399u0MAAElBMm7evHmaN29eu0MBSMQBAAAAaJ2CirhY6Yq4ZNFBTgAA2slPxN3Ym9YXDl6qkURci9MZHffEY9JuKuIAAEB5JOIAAAAAtEy5ijhaUwIAomoiTLIl5t2pf5jXo/GYSZJ29iT0+KIdSmTvVDL99HaGCAAAIqx5TS4BAAAAoIpyY8TRmhIAEFUTYUVc38Ibckm4SemYU9/CG5TMUBEnSc65docAAEDkkIgDAAAA0DJ+Iq5cRZxfNQcAQLuNp4Ikm/XsLrncenbnqua63YYNG9odAgAAkUMiDgAAAEDL1NSakoo4AECETKSDijiXml9yuUsdxBhxoXPOOafdIQAAEDkk4gAAAAC0jF8R1xPvKTlNIg4AECWTFXF6/GT1ZgtbL/ZkpYnHX0UiDgAAlEUiDgAAAEDLJLPVK+JoTQkAiJLxsCKub+/ROmPfvoJlp++KK733BKUYIw4AAJRBIg4AAABAy9QyRlw6m25pTAAAVDIRVsT1KaXnTxSeLHJkuCxJIk6SdO2117Y7BAAAIodEHAAAAICW8avdeuO9Jaf9qjkAANrJOZeviLOkJswKlu9OBMtoTRlYuXJlu0MAACBySMQBAAAAaJlaKuJSGcaIAwBEQzKTlQuHhRuMpZUsSsQ91UMizrds2bJ2hwAAQOSQiAMAAADQMn4irlxFXCpLIg4AEA3jqXyCbW4iOyUR93giyNJNkIgDAABlkIgDAAAA0DJ+a8pyFXG0pgQARMVE2JZSkuYm0lNaUz6WCG4zRhwAACiHRBwAAACAlqE1JQCgk0z4FXGxzJSKuJGe4NAarSkDZ599drtDAAAgckjEAQAAAGgZvyLOb0fZE/cScbSmBABExHiquCKucPlT8bjidoBEXGjDhg3tDgEAgMghEQcAAACgZWqpiKM1JQAgKvyx3+bE0lMq4iSpv+dxWlOGVq5c2e4QAACIHBJxAAAAAFqmlkRcOpNuaUwAAJTjV8QNxqeOESdJvT2PUxEX2rp1a7tDAAAgckjEAQAAAGiZcq0p/WlaUwIAomI8VVgRVyoRl+jdpRQVcQAAoAwScQAAAABapqbWlBlaUwIAosGviJtjqZKtKWM9TymVccpmXStDi6QlS5a0OwQAACKHRBwAAACAlkll8tVufhWcn4ijIg4AEBX+GHH9sUzJijj17JYkxomTtGPHjnaHAABA5JCIAwAAANAS6WxaaReM/xazmBKWyC2jNSUAIIr8iriBWLpkRVymZ68kEnGSNDw83O4QAACIHBJxAAAAAFrCbznZF++TeQczaU0JAIii8bSXiCvTmjLds0+SlEyTiLvwwgvbHQIAAJET+UScmS02s/Vm9lszGzezR83sOjM7eZr7nWdmnzSze81sv5k9aWbfN7PX17h93MzeZWY3mdmImU2Y2SNm9gMz+1szG5hOfAAAAMBs4yfY/Aq44ttUxAEAomIilU+u9SlVsjVlJjEhWZJEHAAAKClRfZX2MbPjJP1A0iHhrL2SFkg6RdJaM/uoc+6iBvZ7mKQfSjoynDUqaZ6kV0h6hZl90Tn3FxW2XyrpOkkrwlmZMLalkpZJermkjZIeqTc2AAAAYLaayEzkpvtifQXLErH8vyYk4gAAUeFXxPVZsmRFnCTFep4iEQcAAEqKbEVcWFF2rYIk3J2Snuecmy/pYEmflWSSPmVma+rcr0m6SkES7kFJL3HODUkakvRhSVlJ55rZ2WW2H5J0s4Ik3N2S1koacM49TdIcSS+U9I+SxuuJCwAAAJjtKlXE+a0pUxkScQCAaBivUBF3aDqdm7aepxgjTtIdd9zR7hAAAIicyCbiJJ0j6ekKqtVOdc7dLUnOub3OuQ9KukZBMu7Tde73dEkvUpBw+1Pn3G3hfsedcxdL+ny43ifMrLfE9hdJerakexUk8b7rnEt5+7jDOXe+c+6JOuMCAAAAZrWCirh4YUUcrSkBAFE04VXE9apwjLgjU/lEXKyXijgAAFBalBNxZ4bXVzrntpdYfnF4vcLMntPAfv/XOXdXieWXSHKSFitoVZljZgslvTu8+dfOuT113C8AAADQ1Say+URcpYq4ZDYpAACiwB8jrtclCyrijkzlTxyJUREnSVq1alW7QwAAIHIimYgL2z+uDG/eUGa1n0qaTISdXMfuX15pv2HS7+7w5iuKFv+ZpF5JT1aICwAAAEAJfmvK4oq4uMVlCg5uZl1WmWxGAAC023gq/33Uo3RhIi6ZT8QZY8QBAIAyIpmIk/RcSZO/bO4utYJzLivp/vDmMbXs1MwOVTDmXNn9hu4ps98/DK9/IanHzD5uZveZ2biZPWFm3zOzU2uJBQAAAOg2lVpTmhntKQEAkVOQiMsmlczn4bTcb01JIg4AAJQR1UTcEm96R4X1JpctqbBOM/f7rPB6VNItkj4h6ZmS9kt6mqRXS7rWzD4vAAAAAAX8irji1pQS7SkBANEz4SXX4m6iaIw4KuKKXXDBBe0OAQCAyEm0O4AyBr3pAxXW2x9ez23Rfg8Kr9cqqNj7hKRLnHP7wmq7iySdJekvzex259xXSu3czNZJWidJixYt0ubNm2sMH+hOo6OjvE+ALsP7Hpid7hq7Kze9Z9ee3Ps89573ulHe8qNbNBQfaml8AFqH73p0iu2PjuemD4ztlpsXJOISTlqUySjhnNJmiiXG9H8/v0OJxwbL7aorrF69uuR7m/c80H143wN5UU3ERVXMu/4v51zuNB/n3GOS3mlmz5P0QkkfkVQyEeec2yBpgyStWrXKrV69eiZjBjre5s2bxfsE6C6874HZaXTbqPSjYHrZ4mVafdJqSfn3/JxvztHo/lFJ0gtf/EItHlzcpkgBzDS+69EpLvv1T6XHn5Qk9fXHJQVVcH2xuGKSlqbTergnqOhesPxgrf7DE9sUaTQsXbpUO3ZMbULFex7oPrzvgbyotqYc86YHKqw3J7webdF+/dvry2z7z+H1c82s1paZAAAAwKznt6YsHiNOKmxNmcowRhwAoP0m0vly7bTzxjq14Nz2pen8OHGPHxhpXWARtXPnznaHAABA5EQ1EeefOrO0wnqTy2r9lp/ufv3t7y+zrT//8BrjAgAAAGa9iYx3ALNaIi5LIg4A0H7jqfy4b/53U2/4nbXMS9Q9OUEiDgAATBXVRNx9klw4fWypFcwsJuk54c17atmpc+5xSU9U2m/omDL7/VUt9+PfZZ3rAwAAALOWXxHXG++dstyfRyIOABAF4wUVcV5ld5iIW5rKV8TtSpKIW7FiRbtDAAAgciKZiHPO7ZN0R3jzlWVWe5Gk+eH09+vY/c2V9mtmy5RP0hXv93+96eeotKO96YfqiAsAAACY1eqpiPOTdgAAtMtEQUVcPunWG36P+a0pdycfbV1gEbVly5Z2hwAAQOREMhEXujK8PrPMWGsfDK+3OOfKtYmstN81ZvaCEss/IMkUtKW8uWjZZkm/D6ffX2b/k/PvcM49VkdcAAAAwKzmJ+KoiGuNTds2ac1Va3TcFcdpzVVrtGnbpnaHBAAdxR8jLuny3019iX5J0jIvEbc3xWGgdevWtTsEAAAiJ8qJuMsUVJQNSbrezI6RJDMbMrPPSHpduN5Hizc0Mxdehkvs9zuSfqbgsX/bzF4cbtNnZn+tfCLtAudcwWm4zrm0pPPDm282s2EzGwq3P9TM/kPSC8Plf9fAYwYAAABmLb/KrWpFXJaKuOnatG2Thm8b1s6xnXJy2jm2U8O3DZOMA4A6TI4RZ8oq6byKuDARt9RL1O3LkIi7/PLL2x0CAACRE9lEnHPugKTTJT0paYWku81sj6Tdkj6kYPy1jzjnbqxzv07S6yX9TtKRkn5iZvskjUq6RMFzcqlzruQvB+fclZI+raBq7gJJT5nZk5JGJL0zjOuDzrnv1fWAAQAAgFmuntaUqQwVcdO1fut6jWfGC+aNZ8a1fuv6NkUEAJ1nPBUk2nqVVlKWmz/ZmnJhJqOEc8G62b3an9rf+iABAECkRTYRJ0nOuZ9Lep6kz0vaJqlPQWJuk6RXOucuanC/j0g6XtKnJN0nKSFpn4JWlGc4586tsv1HJb1K0nVhPEMKEnHfkHSic+6zjcQFAAAAzGZ+RVyp1pQ9cS8RR2vKaRsZG6lrPgCgUDqTVTobJNn6Lamk5RNxk60pY5IWpfPjyO0c29nSGAEAQPQl2h1ANc65EUnnhZdat7Ea1tkr6WPhpZG4bpRUVzUeAAAA0M3qqYijNeX0LR5cXPKA8OLBxW2IBgA6z4SXYJufyGrCO9o02ZpSkpakMtreE5ckbR/drmcc9IyWxRg127dvb3cIAABETqQr4gAAAADMHn4irmRFHK0pm+q8FecpbvGCef3xfp23ouZzHAGgq022pZSkoURayZhfETcnN31YOj923I7RHa0JLqK2bNnS7hAAAIgcEnEAAAAAWsJvTdkXm1oR5yfn0tn0lOWoz9qj1uoFC1+Qu90f79fwicNae9TaNkYFAJ3Dr4gbSmQ1UdCaciA3fXg6//3W7Ym40047rd0hAAAQOSTiAAAAALREQSKuWmvKDK0pm2HBwILc9EuWvYQkHADUwa+ImxtPFyTiehN9UtiecqlXEbd9lNaMAACgEIk4AAAAAC1RV2vKLK0pm+FA+kBuejwz3sZIAKDzjKfyFXFzExkl/Yq4uJ+Iyyfsur0iDgAATEUiDgAAAEBLVKuI85NzJOKaw0/ETaQnKqwJACg27iXYBmNFFXHxXqknaE/pV8TtGOvuRNxll13W7hAAAIgcEnEAAGBGbNq2SWuuWqPjrjhOa65ao03bNrU7JABtNpGtvSKO1pTN4SfieE4BoD4TXkXcnHj5iriFmYzkgkNsu8Z3aX9qf2sDjZB169a1OwQAACKHRBwAAGi6Tds2afi2Ye0c2yknp51jOzV82zDJOKDLVR0jLk5rymajNSUANK6gIi6eLkjE9cbyFXFxSfHU3NyynWM7WxZj1Jj3HAEAgACJOAAA0HTrt66fcsB3PDOu9VvXtykiAFHgjxFXMhHHGHFNV9CaMkNrSgCox0TKb02ZmtqaMqyIk6ReLxG3fXR7awIEAAAdgUQcAABoupGxkbrmA+gOfkUcrSlbo6AiLk1FHADUYyKdb005EEtPbU0ZVsRJUn9qTm56x2h3jxMHAAAKkYgDAABNt3hwcV3zAXSHahVxfnKOirjmoCIOABo37lXEDVi6YkXcQCo/3c2JuFNOOaXdIQAAEDkk4gAAQNOdt+I8JSxRMK8/3q/zVpzXpogARAGtKVsrk80UPOck4gCgPuOpfEVcf5WKuMF0PhHXza0pr7vuunaHAABA5JCIAwAATbf2qLU6cdmJudu9sV4NnzistUetbWNUANopk80onU1LkkymRCwxZZ2CRFyGRNx0FSfeJjITcs61KRoA6Dx+RVy/CseI64v3FVTEzUvlq7q7uSLu1FNPbXcIAABEDok4AAAwI5bNXZabPuaQY0jCAV0umc2P+dYX75N5BzMn0Zqyufan9xfczrpsLhkKAKjOHyOu31JTW1N6FXHz0/kTTHaMdW8i7vrrr293CAAARA6JOAAAMCNohwbAl8zkE3E98Z6S6/gVcf76aIw/Ptyk8cx4GyIBgM5UUBFnKSW9c0iKW1MelDY5F5ck7Rrfpf2pwpMhAABA9yIRBwAAZsR4On+wt9TBYADdpdr4cBJjxDVbqc9eTowAgNr5Y8T1VmlNOaCUXOqg3O2dYztbEiMAAIg+EnEAAGBGUBEHwFdTIi5OIq6ZSlbEpamIA4BaTaTzFXG9SirpJeJ64j0FFXH9llQ2dXDu9vbR7a0JMmIYixQAgKlIxAEAgBnhH+zlwC8Av9WkPxacj9aUzUVFHABMT0FFnEsVJOKKK+L6lVLWq4jbMdqd48Rt2LCh3SEAABA5JOIAAMCM8MchYkwiAPW2pkxn0zMe02x3IEUiDgCmY9yriOtRcmprSq8irk9JuWS+Iq5bE3HnnHNOu0MAACBySMQBAIAZMZEubE1Jmxqgu9VSEefPpzXl9FERBwDTM+FVxPUUVcT1xnuLKuKSyqaelrvdra0pAQDAVCTiAADAjPCr4LIuy0F1oMvVWxFHa8rpY4w4AJgef4y4RLZyRVy/JeVSVMQBAICpSMQBAIAZUXywl/aUQHfzE3FUxLUGFXEAMD3jKS8R55I1VMR5ibix7kzEXXvtte0OAQCAyCERBwAAZkTxwV6qMIDu5le49cWqV8SRiJu+UidAcFIEANRu3GtNqey40mEiLiZTwhKFFXFKyqWHFLeEJGnX+C7tT+1vabxRsHLlynaHAABA5JCIAwAAM6I48eaPGQeg+9CasvVKHQDmsxgAaue3psxm/RNKemRmBRVxA5aUFNMh/Yty83aO7WxJnFGybNmydocAAEDkkIgDAAAzorjqgioMoLv5iTVaU7YGrSkBYHr8irhUtkSL5aKKOEk6pC+fiNs+un2GIwQAAJ2ARBwAAGi6TDYz5SA6rSmB7lZvRRyJuOkjEQcA0+OPEZf2TyiJhYk4ryKuL0zEHdy7ODdvx2h3jhMHAAAKkYgDAABNV+pALxVxQHfzPxfKVcQVJOIyJOKmi0QcAEzPRDpfEZeusSLuoJ5Dc/O6MRF39tlntzsEAAAih0QcAABoulJJNyrigO7mV7iVq4hLxBK56bRLK+uyJddDbUol4vgsBoDa+RVxSZfOTee+x7yKuH4LvufmJfKJuG5sTblhw4Z2hwAAQOSQiAMAAE03kZ5acUEVBtDdamlNaWa0p2wiKuIAoHHOuYKKuIlsvjVlXyL8HitRETc30d0VcStXrmx3CAAARA6JOAAA0HQHMlMP/pY6IAyge9TSmlKiPWUzUREHAI3zk3C9cSs4OaQ3HlbC+RVxYSJuMO4l4sa6LxG3devWdocAAEDkkIgDAABNR0UcgGLJjFdJUKYiTipM0lERNz2lEnFJr6IDAFDeRCqfiBvscZqQy93um0zAeRVxA5aU5NSr+blWy7vGd2l/an9L4gUAANFFIg4AADRdqaQbiTiguzVSEecn71A/KuIAoHHj6fz4cPMSWU2Y5W7nvsdiccn7TutTSumMacngkty8nWM7Zz7YCFmyZEn1lQAA6DINJeIs8Doz+6KZXW9m3y9aPmhmJ5nZHzUnTAAA0ElKHfylNSXQ3aiIaz3GiAOAxo2nvERcT1pJLxFX8D2WyFfF9SmpZCarpXOX5uZtH90+s4FGzI4d3deOEwCAaupOxJnZsyT9QtI3JZ0j6TWSVhetNi7pPyRtNrOXTjNGAADQYaiIA1DM/wyolIgrGCOORNy0lKp+G89QEQcAtfDHiJsbz5SuiJOkHn+cuJRS6ayWzV2Wm7djtLsSU8PDw+0OAQCAyKkrEWdmB0v6X0nHSvqlpL+TtLd4PedcRtIXJZmk/zf9MAEAQCcpdaCXdmhAd6u1NeXkuDoSrSmnwzlXuiKuxBieAICp/Iq4oURhRVxvzPseS3iJOAsr4gbzFXHdloi78MIL2x0CAACRU29F3F9LOlzSDZJWOec+Kalcn6lrw+sTG4wNAAB0qJJVGCTigK7WSGvKdDY9ozHNZqlsShmXmTKf6mQAqM14Kl8RNxjPlm9N2ZNvTdmvpJLp7m5NCQAApqo3EXe6JCfpr51zFf8rds49ICkp6ZkNxgYAADpUqYoLDv4C3a3Wiji/NWUyS0Vco8qNy8lnMQDUZiKdP5lhMJ4u35rSr4hTUhNd3poSAABMVW8i7khJ4865e2pcf5+koTrvAwAAdDhaUwIoVmtFXMEYcRnGiGsUiTgAmJ6CirhYuvaKuExhRdyOse5KxN1xxx3tDgEAgMipNxHnat3GzBKS5qnEGHIAAGB2K3Wgt1RyDkD3qLUizl+WypKIa9T+9P7ctD+WESdFoNNs2rZJa65ao+OuOE5rrlqjTds2tTskdAl/jLjBeKagIq4gEVc8Rlw6q4UDC3Njnu4a36X9qfxnMgAA6D71JuJ+J6nXzI6qYd2TJfVIurfuqAAAQEdjjDgAxfyKuJpbU2ZoTdkovyLu4P6Dc9NUxKGTbNq2ScO3DWvn2E45Oe0c26nh24ZJxqEl/ETcHEuVb01ZYoy4eCyuJYNLcvNHxkZmNtgIWbVqVbtDAAAgcupNxG2SZJL+qtJKZjYo6WIFFXTfaSw0AADQqUpVv3HwF+hu/mdAza0pqYhr2IFUPhF3UN9BuWk+i9FJ1m9dP+U3xXhmXOu3rm9TROgmE+l8a8qBSq0pC8aISykZbue3p9w+un0GIwUAAFFXbyLus5KekvQXZvZJMzvEX2hmQ2b2Z5LukPQ8STskfbEpkQIAgI4xkaY1JYBCNSfi4iTimsGviJvfNz83PZ4el3OuHSEBdStXRdRN1UVoH78ibiCW0kQ+D1e+Is4mlMwEibhlc5fl5u8Y7a5x4gAAQKG6EnHOuSckna5g3LePSBqRtFCSzGyXgiTd1yQ9R9IuSa91zo01M2AAABB9pZJutKYEuhutKVvLT8TN7ZmrhAVjFTk5pbPpdoUF1GXx4OK65gPN1FhFXDJfETfoVcSNdU9F3AUXXNDuEAAAiJx6K+LknLtV0gsk/bekTLgPk3RQOJ2R9HVJK51zW5oWKQAA6Bilkm60QwO6G60pW8s/IWKgZ0B9ib6Sy4AoO2/FeVM+L/rifTpvxXltigjdZMKriOtTHWPEZaa2puymirjh4eF2hwAAQOTUnYiTJOfcw865t0g6WNJJkt4g6U2SXiHpac65NznnHmpemAAAoJOUSrr51RkAukvWZQuSar2x8hVx/sFNEnGN88eIG0gMFCQzODECnWLtUWt19vPPLpj3gZUf0Nqj1rYpInSTca8irt8KK+IKEnFlxojr1taUS5curb4SAABdJlHPymZ2tSQn6YPOud855w5IunVGIgMAAB2LijgAvoK2lLFemXcws1hBRVyGRFyj/JMfBhID6o/nDxTTKhid5IRDTyi4/dJlL21TJOg2/hhx/UqWb03Z4yXizGtN6VXEbR/tntaUO3fubHcIAABETr0VcadIerVz7nczEQwAAJgdGCMOgK/WtpQSFXHNUpyI81tTcmIEOsm+1L6C21TYN9+mbZu05qo1Ou6K47TmqjXatG1Tu0OKBD8R12uFrSkLx4gr3Zpy4cBCJWLB+e+7xnfx2gUAoIvVm4gbkcR/wwAAoKJSB3kzLsNBdaBLFVTExcu3pZQYI65ZpiTi4owRh840mhwtuM3rt7k2bduk4duGtXNsp5ycdo7t1PBtwyTjJE14rSn7lCrfmtKviFO+Ii4ei2vJ4JLcsp2j3VEptmLFinaHAABA5NSbiLtZ0pCZPXcmginFzBab2Xoz+62ZjZvZo2Z2nZmdPM39zjOzT5rZvWa238yeNLPvm9nrq2z3oJm5KpcPTic2AAA6Xbnqt4k0VRhAN6qnIs5PxPkJPNRnf3p/bro4Ecfzik4ymipKxFFh31Trt66fktwcz4xr/db1bYooOvyKuB6XrKkirs9rTSl1Z3vKLVu2tDsEAAAip95E3EWSDkj6VzOr/B90E5jZcZJ+Jel9ko6SNCFpgYIWmTeZ2fkN7vcwSXdJ+pikoyVlJM2T9ApJ3zSzL9Swm6ckPVrmMtZIXAAAzBblzlbnLHagO9VTEUdryubwK+LmJOYwRhw61r5kYWtKWqs218jYSF3zu8l4Kp9Q6y1KxBVWxJVuTSlJy+Yuy03vGN0xQ5FGy7p169odAgAAkVNvIm5M0p9LeqGkX5nZeWb2B2Z2pJkdUe7SSGBmNiDpWkmHSLpT0vOcc/MlHSzps5JM0qfMbE2d+zVJV0k6UtKDkl7inBuSNCTpw5Kyks41s7Or7Op1zrnFZS5frCcmAABmG7/ybcA7S5iDv0B3qqcibnI8HYnKrelgjDjMFsWtKRlnq7kWDy6ua343mUjnK+ISrrA1ZcF3WUEiLlVYETfoVcSNdUdF3OWXX97uEAAAiJx6E3G/k3SFpEEFFWr/JOknkh4Il5W6bGswtnMkPV3SqKRTnXN3S5Jzbq9z7oOSrlGQjPt0nfs9XdKLFCTc/tQ5d1u433Hn3MWSPh+u9wkzq3y6LgAAKMmvfJvfNz8/n0Qc0JUabU1JRVzjGCMOswWtKWfWeSvOU9ziBfP64/06b8V5bYooOvyKuIRLVWhNWXqMOKmwNWW3VMQBAICp6k3EWQOXeu9j0pnh9ZXOuVKnDV0cXq8ws+c0sN//dc7dVWL5JZKcpMUKWlUCAIA6OOcKDpLN780n4qjCALqTn1CjNWVr+Im4/kR/QWtKxutEJyluTUkirrnWHrVWR80/Knc7ZjENnzistUetbWNU0eCPEZfIThRUxPknjRRUxFnQmtI5J6k7W1MCAICp6kqSOedijVzqDcrMhiStDG/eUGa1n0raE06fXMfuX15pv2HS7+7wJok4AADqlMqm5BQcfEjEEhrsGcwtowoD6E4NV8RlSMQ1qrgizk9wclIEOsmUijh+SzSd/5kw1DtEEi7kV7Ylskkl83m4ihVxkpTKBL+F/Yq47aPd0Zpy+/bueJwAANSj0Wq1mfZcBdV0Uj4pVsA5l5V0f3jzmFp2amaHKhhzrux+Q/fUsN9/NrPHzSxpZiNm9l0ze7NZUU8HAAC6TEEVRrxf/d7BCc5iB7qTf5C3WkUcrSmbw/+8HUgMFHwWk4hDJykeI47fEs2VyWYKKrXGUmNtjCZa/Iq4WHZcE7H8IbSC77KCMeKCRFwyEyTxFg4szI19umt8V1eMcbhly5Z2hwAAQORENRG3xJuuVLs/uWxJhXVmar/HS5ojaVzSIkl/Iumrkr5vZgfVGA8AALNOceUL4xIBSGaSuelqFXG0pmyOSmPEkYhDJ9mXKmpNyW+JphrZP6K0S+dup7NpqpFD415FXCab/x7rsYRi5h1O80506LPguZuspovH4loymD+0tHN050yFGxmnnXZau0MAACByEtPZ2Mz+QNIKSQvDWY9L2uqc+79pxjXoTVc6XWh/eD23hfu9RtIPJd3inHtSkszsCEl/KekDkl4m6RuS1pTbuZmtk7ROkhYtWqTNmzfXFj3QpUZHR3mfAB3k8dTj+Rtpac+Te3I37/zlnYpvq148zvsemF1+Pvrz3PSux3dNeX/77/l7D9ybm//oE4/yWdCgvQf25qbv/L87tXNf/uDv/b+9X5uf3NyGqIC8Wr/rnxx9suD2Aw8+oM17q2+H2tx/4P4p827cfKMG44Ml1u4uY+P55NuefbuksPAtoVjBa7cnuVsvCacnK+Ju+dGtOrg/SNYNpPIVc9/7yfd07MCxMxp3FJR6b/P7Hug+vO+BvIYScWb2Zkl/L2l5meW/k/S3zrmvNR5aNDnn3l9i3sOSPhQ+7n+T9EozW+Ocu7HMPjZI2iBJq1atcqtXr565gIFZYPPmzeJ9AnSO3zz1G+naYPqgwYP09IVP19YHtkqSjnr2UVr9rNVV98H7HphdHrv/MSk8lv70ZU/X6j9cXbDcf88PjgzmRnOeO38unwUNSv9XvsLl5JNO1uP3P67vbfmeJGnxYYu1etXqNkUGBGr9rk99tbA6a8GSBVM+Q9C4J379hPRY4bwTXnRCwdhm3Sp943elcNzj3v6EpOBzdaBnoPC1O75Xui2YnEzErXzhi3XEIXMkSTffdrN+/ZtfS5IWHLlAq4/2tp2lSr23+X0PdB/e90Be3a0pzewfJH1F0pEKxnHbIen/wsuOcN5Rkr5qZp9sMC6/KflA2bWC1pCSNFphnVbsd9IXJT0YTp9a57YAAMwK/tgtfYmi1pSM6wJ0peKWtZUwRtz0ZbKZgue8P9HPZzE6UiqbmjKmFq/f5vr9vt9Pmbc/tb/Emt0llckqkw2ScPGYFbVYLhrrdMoYcU7JTH58uaWD+aTm9rHtMxNwhFx22WXtDgEAgMipKxFnZi+X9BEFybb/lnS0c+5w59wfhpfDJT1H0tfCdT5iZqsbiMsfv63SaViTy2ptsj1T+5UkOeecpNvDm0fVsy0AALOFP3ZLf7xfA4mBkssAdA8/KdRbfACziJ+I8w98onb+Z+1AYkAxizFGHDrSaHLqubEk4pqrVCJuLD1WYs3uMp7KJ9L6EzFNZCuMdRrvkSxovZ6wrHqU0YQ3vpxfXbhjdIdmu3Xr1rU7BAAAIqfeiri/VFCX/3nn3JnOuV8Xr+Cc+41z7s2S/lVBMu59DcR1nybr/6WSzbPNLKYg6SdJ99SyU+fc45KeqLTf0DH17BcAAORNqcJIeAd/0xz8BbpRYSVBlYq4OBVx0+VXEE2eDEEiDp2oVCLuQKbScO+o1yP7Hpkyj4o4FSTS+nriBd9jvaW+x4qq4pLe9svmLstNd0MizszaHQIAAJFTbyLuDxUkyC6sYd1hSVlJJ9Z5H3LO7ZN0R3jzlWVWe5Gk+eH09+vY/c2V9mtmy5RP0tWzX1nwa+OF4c3f1bMtAACzRUFrynhha0oOngHdqdGKuHQ2XWFNlHMgNTUR15/oz80jEYdOsS+1b8o8TuppHuccibgyplbE5U8M6fM+T3O8ef1KKpVxudt+Rdz20dnfmhIAAExVbyLuaZL2OOeeqraic26XpD2SDmogLkm6Mrw+08yWlFj+wfB6i3Pu/gb2u8bMXlBi+QcUVPLtVD5pJymXaKvkHEnLw+lNdcQEAMCsUdCaMlHYmpKDZ0B3KqgkiNGacqbtT+cPovfHg4PDBWPE0SYYHYLWlDNrz8SekslO/zOkW42n8hVtAwlT0uVPDOmpUhHXZ4UVcQsHFioRS0iSdo3vmjLuIQAAmP3qTcTtkjTfzJ5WbcVwnfmSqibtyrhM0kOShiRdb2bHhPsdMrPPSHpduN5HS9y3Cy/DJfb7HUk/U/DYv21mLw636TOzv5b0/nC9C5xzxf/5f97M1pvZS80s9yvLzA43s4sUtOOUpJudc9+r/yEDAND5/GRbf7yfg78ACiqwqrWm9CvmaE3ZmFKtKScTchInRaBzlEoS8VuieUqNDydJYynGiPMr4gYTGSW987JLfo8VVcQlM/nt47G45vXMy91ee/Vabdo2e8/dPuWUU9odAgAAkZOoc/2fSDpd0t8pn7AqZ1hBsusndUclyTl3wMxOV9AecoWku81sr6S54X6dpI86526sc7/OzF4v6YeSjpT0EzMbldSv/PNxqXPu8hKbD0l6u4Jx77JmtkdSXNI8b51bJL2+npgAAJhN/ANkffG+gnZonMUOdKdGW1Mms1TENcL/HB4IqzQKxuukNSU6RMkx4qgmappHRqe2pZSoiJMKx4gbSmQ0kaqSiOspSsR522/atkm7J3bnbj9+4HEN3zYsSVp71NrmBR0R1113XbtDAAAgcuqtiPsXBW0b/9LM/svMnlu8gpmtMrOrJb1HQbLs840G55z7uaTnhfvYJqlP0pMK2j6+0jl3UYP7fUTS8ZI+Jek+BQm4fQpaUZ7hnDu3zKaXSrpE0m2SdihI3vVJ+r2kb0s6Q9IrwracAAB0JT/ZNpAYKKzC4OAv0JX8FpPVKuL8RFwqQ0VcI0qNEUd1MjrRaIrWlDOpXEUcY8RJE15F3FAirQmvIq7kCSVeK/Z+JQsSeeu3rldW2YLVxzPjWr91fRMjjo5TTz213SEAABA5dVXEOeduNrNPKWgH+SZJbzKzxyVtV5CUOlzSYLi6Sfqkc27zdAJ0zo1IOi+81LpNtbHc5JzbK+lj4aXW/f5U0k9rXR8AgG5U0IIu0Vd48JeDZ0BXojVla5VqTek/74y9h06xLzm1NSUn9TSPn4g7fOjw3G1aU0rjaa81ZbyG1pTeGHH9liqoiBsZGyl5H+Xmd7rrr7++3SEAABA59VbEyTn3t5LerKBCzSQdKukESc9V0DbSJP1W0hudc3/XvFABAEAn8JNtU1pTUoUBdCU/8VOtNWUilj9XMJVNyTk3Y3HNVtXGiOOkCHSKUq0pef02zyP78q0pn3Pwc3LTtP+UJlL5RNpgPKMJ73Tvkt9jPYUVcclMfvvFg4tL3ke5+QAAYPapOxEnSc65rznnnqVg7LZ3S/pIeHm3pBXOuWc7577RvDABAECnKBibqKg1JQfPgO5UT0VczGJKWD4Zl86mZyyu2apkRRxjxKEDlWpNmXZpqmWbxK+Ie/bTnp2bpiKusCJubjxdvSIuUX6MuPNWnFdwkokUnBxx3oqaGz8BAIAOV1drymLOubsk3dWUSAAAwKxQfMDdr4jj4C/QneqpiJOknniP0ukgAZfKptQT76myBXzVKuL4LEanKNWaUgpO7Onp5XNhOiYyE3ps/2OSghMgnnnQM3PL9qcZI27cr4iLZQrGiKvemrIwEbf2qLW6Y+QOXfWbqyQFn8sX/OEFWnvU2hmIvP2oZAcAYKqGKuIAAADK8Q8A98X7qIgDUFdFnCT1xPIH2BnPrH6lEnF+AnQ8Pc6BUnSEUhVxEsnkZtg+ul1OwefAksElmt87P7eMijhpIpWviBuIpQoScSVPKKlQESdJJy47MT+99MRZm4STpA0bNrQ7BAAAIqeuRJyZPdvMvmRmH6lh3Y+H6z6j8fAAAECnmUjnD471J/oL2qExRhzQnepNxPkHOWlBV79SibhELJFr+enkeF7REUqNEScxhlkz+OPDHTZ0mOb0zMnd3p+iIm7cS6TNiaWVqpaI8yri+pRUKlOYiBtMDOamZ3ui85xzzml3CAAARE69FXHvkPR2SU/UsO5YuO7b67wPAADQwfwD7v3x/sLWlGnOYAe6Ud2tKb2KOBJG9SuViJMYJw6dZ18q35oyZvnDF1TYT58/PtzhQ4drTsJLxNGaUuN+RZylqremLKiIS2miKBFHohMAgO5WbyLuVeH1tTWse6Ukk/Qndd4HAADoYP4B4P5Ef0FrygMZzmAHuhGtKVvLP4hekIiLk4hDZ/Er4g7pPyQ3TSJu+vyKuMOHDidRVMQfI64/lq7emrLCGHFSUSKORCcAAF2n3kTcEZL2Oecerbaic25E0l5JhzcSGAAA6EzFB9x7Yj25s9jT2bTS2XS7QgPQJvVWxNGacnrKVcQxZic6zb5kviJuwcCC3DStrqfPr4g7bO5hJIqKTKTzFXH9SilZV0Xc1ETcYE/3tKa89tpazt0HAKC71JuImyupnlG9naT5VdcCAACzRkFrykS/zIwqDKDLTacijkRc/fwkG60p0alS2VQu4RazmJ7W/7TcMhLJ01exNWVqv5yr59DP7FNQEWd1VsSVSsR10RhxK1eubHcIAABETr2JuBFJ88ysapVbuM58SY83EhjQapu2bdKaq9bouCuO05qr1mjTtk3tDgkAOpJ/cGyy+sI/EMzBM6C7OOeUzDY+RhytKetXU0UcFUWIOL8t5WDPYOFvCV6/05J12YLWlIcNHaZELJE7UcLJFXyOdKMJb4y4PquvIm7AkkpWGiNullccLlu2rN0hAAAQOfUm4n4UXn+ohnU/HF7fWud9AC23adsmXXDbBdo5tlNOTjvHdmr4tmGScQDQAP/g2OSBCirigO7lV7T5rWor6YlTETcd5RJxfhJ0Is1nMaLNT8QN9QypP0Fr1WZ5fP/juRMkDuo7SEO9Q5IK2yfO9mRRNRNeRVuvkgUVcSUTcVUq4nrjvUrEEpKCVu2cZAIAQHepNxH3b5JM0nvM7O/NbMqvDzPrM7N/kPQeBa0p/236YQIza/3W9VMODI9nxrV+6/o2RQQAncs/uDt50Mw/YMHBM6C71NuWUipqTZkhEVevWiriOCkCUbcvlR8fbm7v3MLfElTETUtxW8pJ/ufF/lR3J+LG/Yq4ojHiSlZ2e4nivhKJOKm7xokDAACFEvWs7Jz7mZldrKAi7qOSzjWzmyU9HK7ydEmrJR0c3v6cc+7HTYoVmDEjYyN1zQcAlOcfHJtMxNFOCuhefsKnlraUEmPETVe5RBxjxKGT+BVxc3vm0ua6ifxE3GFDh+WmSRTljafzibheV0tFXD4R16+prSklaU5ijvZM7JEUVBwenDt0NrucffbZ7Q4BAIDIqSsRJ0nOub8xsyckXSDpaZL+n4LKNymolpOkA5IudM59pilRAjNs8eBi7RzbWXI+AKB2mWwmd9DcZOqNBQfdqYgDupfffqvWijg/YUcirn4FiTivXRoVRegkfkXcUC+tKZvpkVFvfLi5+UTcnET3jGNWzXgqn0jrcSkl83m43O/bAn71sXV3RdyGDRvaHQIAAJFTb2tKSZJz7mIF1W/nSrpC0g3h5Ypw3hEk4dBJzltxnkxWMK8/3q/zVpzXpogAoDP5FRb9iX5ZePZwwcEzDv4CXWW6rSkZR6c+zrnaWlMyRhwirqAirnduwevXf42jfuVaU87pySfiZnOiqBYTXkVcj0tWb01ZS0Wc9/zO5tafK1eubHcIAABETt0VcZOcc09Kuiy8AB1t7VFrdckdl+iJA09IClqf/O2L/1Zrj1rb5sgAoLP4STb/gDsHf4Hu5SfSam1NSUVc45LZpLIuOACciCUKkpr+80prSkTdaKqwNaV/Ug+v3+l5ZF++Is5PxPkVW1TE5RNpiVpaU/onPShVsiKuoOJwFifitm7d2u4QAACInIYq4oDZKGb5t8Nrn/laknAA0AC/VZR/kMIfl4iKOKC7TLcijkRcfQ6kvGq4+EDBMlr7oZPsSxa1pozz+m0WPxHnjxHnV9D6nyXdaDyVr4grTsTVVBFXrTVlursrDgEA6DYNV8T5zKxP0qslPVtSUtJdkn7onHOVtgOixD8jjVYnANAYP8lWrh0aB8+A7uIn4mqtiEvE8v+m0JqyPuXaUkqFidBklucV0VbQmrKoIo6Teho3mhzVUxNPSQrGOjt0zqG5Zd0yhlktJrxEWjxb2Jqy5EklXtvJfivdmrJbnt8lS5a0OwQAACKnYiLOzA6W9FZJTtJlzrkp/62Z2UskfV1S8TftnWb2p8653xdvA0SNc66g9Ua3t+EAgEb5bScLWlNy8AzoWn4irdaKOFpTNq4gEddTVBHHSRHoIH5ryqHeoYLfEpw42Th/fLjDhg4r6AxT0Dqxy/8n9ivi4tlaWlPmX599ZSri/JMjZnNryh07drQ7BAAAIqdaa8o1kj4n6Q1lknCHSbpeQRLOii4rJH3XzJpSdQfMpAPpA7mxNCTacABAowrGiEswRhyAooq4WG0VcbSmbNyBTIWKOO9zmTG2EHV+a8q5PXNJJDfJI6Olx4eTuqdiqxYT3hhxscxEQUVc6daU/hhx1VtTzuZE5/DwcLtDAAAgcqol4lYrqIb7apnlH5M0P1zn45KWhrf/QlJK0jGSzmxGoMBMKv4RzBmWANAY/8CYPzYRY8QB3cuviKu1NWVBIi5DIq4eBWPEVWhNSSIDUVepIo5EcuOKK+J8c7z2irO5YquabNYVtJbMZsaVCRNxcYsVtE/OiffKKVin1zJKp9NTVumWROeFF17Y7hAAAIicaom4FeH1jcULzCwm6Y0KknBfds79g3NuxDm3zzl3qaR/UlAZ97pmBgzMhOIfwbP57DQAmEn+gbFyFXEc/AW6S8HnAq0pZ1ytY8SRyEDU+WPEFSfi+C3ROD8RV1wRR2vKgD8+XF8ippT3euv1ThQpYFZQFWclTjwreH67ONEJAEA3qpaIWyJpwjn32xLLjldQ/SZJl5dYfll4/YLGQgNapzgRR0UcADTGPzBWbow4Dv4C3aWgNWUjFXEk4upSayKO6mRE3b5U+daUfgtW1OeRfeVbU1IRF/DHh+vviSuZ9lssl0nESQXjxMXS43LOFSzuloo4AAAwVbVE3KGSyv36+oPweq+kn5ZY/pCC9pQLGwsNaJ3ifzK6+Z8OAJgO/8CufwDYP/jLyQ5Ad/FbU9ZaEecn4vztUV2lRJx/UgTPK6KuYIy43rlUxDVJQWvKuUWtKamIkySNp/OJuL5ETBP+GMgVTiixonHi0tnCRFxBonMWP7933HFHu0MAACByqiXikpIOMrMSDbBzibi7XPFpPpLCeaOSSm0LRErxj+DZ/KMYAGbSRLp0Czr/YDAVcUB3oTVla1ERh9liSmtKryLO/72B2qWyKY2MjUiSTKZlQ8sKllOxFZhI5VtT9vfElfS+h3orfY95yeJ+SyrptbiUaE0JAEA3q5aIe1DBOG8vKrHs5QrGh/tJqQ3D5N18SbsbDw9oDVpTAkBzjGdKt6YsOPjLWexAV/ErrxppTUnlVn0qVsSRyECHSGVTud8UMYtpTmJOQUUcrSkbs3N0pzIuqPY6dM6hU06O6JaKrWr8irj+npgmsjVWdhdVxBUn4rol0blq1ap2hwAAQORUS8RtVpCI+7iZ2eRMM/tTSU8Pb36vzLbHh/t/YHohAjOv+EfwRGZCmWymzNoAgHL8JJt/ALignRRVGEBXaaQiLhHLN9WgIq4+FSviEvnnn+pkRJlfDTfYMygzK3g9c1JPY/zx4Q4bOmzK8sFEPlHUzRVb40UVcRMFJ5TUWBGnpJKZCom49OxNxAEAgKmqJeL+VUF7yldK2mpmnzKzKyT9t4JquLudcz8qs+3a8Pr2pkQKzKBSZ6NRFQcA9St3wL2gCoODv0BX8d/ztVbE0Zqycf5vWP8kCInWlOgcBW0pe4YkBZWypuD84FQ2xYmTDfDHhzt86PApywe8iq5uTsRNpLwx4uJW0Jqyr+hztYBfEUdrSgAA4KmYiHPO/VrS+8KbL5D0N5LeIqlX0gFJZ5fazsxikt6uIFn3/WYFC8yUUj+Cu7kVBwA0qtwBYL8Kg7PYge7it5astSLOb02ZypCIq0etY8TRmhJRti+1Lzc9t3euJMnMCn5bcGJP/aol4rqldWI1414CbbBHmpDL3e6LV0jEFVXETRQn4nq6IxF3wQUXtDsEAAAip1pFnJxzGySdJOnrku4NL1+W9AfOuZ+V2eyPJO2S9DNJNzQnVGDmUBEHAM1RS0UcVRhAd2mkNSUVcY3zf8P61RcS1cnoHH5F3NyeublpP7nM/2v1e2TUa005d2pryv54v2IWHCZKZpNd+/k77lXEDcYzSuZHaqlc2d1T1JqyS8eIGx4ebncIAABETqL6KpJz7seSflzrTp1zt0hidFZ0jFL92WfzGWoAMFP8A7v+WesFY8RREQd0lWTB2Dq1taYsqIjr0gPBjWKMOMwGfkXcUO9QbpoTe6anWkWcmWlOYo5GU0EidH9qv+b3zW9ZfFHhJ+LmxtOa8BJxFU8o8cdHLjFGXF+8TzGLKeuyuUSn/303WyxdulQ7duxodxgAAERK1Yo4oBtQEQcAzeEn2fyDZQVVGLRDA7pKIxVx/oFJP5GH6iol4qiIQ6coqIjrzVfEcWJP45xzVRNxUmElbbf+T+y3lJwbTxdUxPXEKyTO/Io4S02piDMzDSbyVXGz9eTfnTt3tjsEAAAih0QcIMaIA4Bm8c9OL2hNmeAMdqBbTWTzCZ9aK+JoTdm4Sok4/3kdT4/LOScgiiYrsqTC1pT+bwt+T9Rn1/iu3OfD3J65ZSvdumUcs0omClpTFibi6qmISxVVxEk8vwAAdCsScYCoiAOAZvGr3fzkW8GBM85gB7pKKpNPpDVSEUcirj6VEnGJWEIJC0YncHI8t4isfcnSrSn91zS/J+pTXA1nXnLJ5yeKZvM4ZpWMp/IJtIFYpvbWlFXGiJOKEnGz9OTfFStWtDsEAAAih0QcoNI/gDk7DQDq55+dXi4Rl8wmlXVTD0wAmJ1oTdlalRJxUuE4cVQUIaoKWlP20JqyGfxE3GFDh5Vdz29NOVsTRdVMpL2KuFjhGHEVK7u9JFufJQtaXOb257WmnK2Jzi1btrQ7BAAAIodEHKDSSTcq4gCgfv5BMf+Au5kVjE3EwTOge/iJtFpbU/pj8FC1VZ+CRFxPiUScf2IESU5ElN+a0q+I47dE4x4ZfSQ3XW58OEka7Jn9iaJqCivi6mlNWVQRV6I1ZTc8v+vWrWt3CAAARA6JOEClfwB369l/ADAdfuWLf9Z68W1/PQCz23Qr4vzWlqiuWkUciYzm27Rtk9ZctUbHXXGc1ly1Rpu2bWp3SB2vXGtKKjob98i+fCKOirjKxr0x4ubEUnVUxBWOEVeqNaV/gsRsfX4vv/zydocAAEDkJNodABAFjBEHAM1R0JoyXpiI8w/Ak4gDuof/fq+5Io4x4hp2IJX/DVv8OSwVJjL4LJ6+Tds2afi24dz3386xnRq+bViStPaotW2MrLP5FXF+a0rGiGtc8Rhx5RSMYdalwzX4LSX7LdVgRVyqZCLOr4jr1ucXAIBuREUcul7WZRkjDgCapFxrSqmwIo6THYDu4bc/rLUizk/YkYirXSabUTKbf76LK5Olooo4Koqmbf3W9VOex/HMuNZvXd+miGYHf4y4sq0pef3WhURc7fyKuH4rrIir+D3mV8RZUklvrLlJ3TBGHAAAmIpEHLpeuYPBHCQGgPr51RXFLdH8g2dUYQDdY7qtKRnHrHbFbSljNvXfPT/JOZHms3i6RsZG6pqP2uxN7s1N+xVxnNTTmAPpA3riwBOSpIQltGjOorLrFoxhlu7ORNF4UUVcza0paxgjriDROUtbU27fvr3dIQAAEDkk4tD1yp2FNlt/FAPATHHOVayIKxjXhXZSQNfwE2mNtqZ0zjU9rtnIrxAqNT6cREVRsy0eXFzXfNSmoDVlr5eIY4zDhvjjwy2du1SJWPlRSgrGiKMiTn1KKZXPw6k3Nr0x4vxE3GytiNuyZUu7QwAAIHIaSsSZ2avN7N/N7Kdmdr+Zbatw+W2zgwaaqWwirkv/6QCARiWzSTkFB8sTsYTisXjB8oG4N64LB3+BruCcKxwjrtIBTE88Flfcgs8QJ6eMm9reC1P548OVS8T5J0VQbTh95604b8q8/nh/yfmoXdnWlAmq6xtRa1tKqSgR16Unp/pjxPUqXXtrSr8izpJKZqaeROK3ppytxxxOO+20docAAEDklD8NqgQz65H0dUmnT86qYTNOX0WklfvxS6sTAKiPf2a6n3SbREUc0H3S2XTFBH0lPbEeZTJBAi6ZSVas4EDAP2heNhHnHUTmpIjpe82Rr9FHfvSR3Ot8Xu88ffRFH9Xao9a2ObLOlcqmcq/NmMUKEkO0pmyMXxF32NBhFdfthoqtavyKuF7V0ZrSq4jrq6EirlsTnQAAdKN6/5v9G0mvVZBc2yTpGknbJfEfHDqW/89FwhJKu7QkfhQDQL0KxoFKTD1bmIO/QPdppBpuUk+8J/dZkcqmmhrXbFU8RlwpBeN1MkbctI2lxnJJOEk663lnkYSbJr8abrBnUOYlQWhN2Zi6KuK8RJFfZdtNJvxEnEsq2UhFnFIlE3EFY/B1aaITAIBuVG8i7kwFSbiPOOc+MwPxAC3nJ9wOGThEj+5/VBJnWAJAvSqNDycVHhTm4C/QHQoS9JUOXpZQPE4cqqslEeefKEFrv+nbk9xTcHu2tpprpYK2lD1DBcv8ijhO6qnd70fzibhqFXEFiaJ0dyaK/NaUPS7ZUEVcv5JKZqa2Ve6GRNxll13W7hAAAIiceseIWy4pK+lfmh8K0B7+j98FAwty0/wTDQD18Q+IlToAXFARx1nsQFfwxyCrePCyhIJEXIZEXC1qSsTxWdxUeyYKE3Gz9cB6K+1L7ctNz+2dW7CMis7GbN+3PTd92NwqrSn9MeK69H9ivzVlT4MVcQM2UbIizv9snq3P77p169odAgAAkVNvRdxuSX3OOUqFMGv4/ywvHFiYm6YiDgDq4x8QK3WQgrPYge4znYo4P3FHRVxt6k3EURE3fcWJONrbT59fETe3pygR548Rl+H/tVpkshk9MpofI65aa8puqNiqZjyVT6AliiriKn6XFVfEVWlNOVs/L8xMzrnqKwIA0EXqrYi7RdJ8M6v8y62JzGyxma03s9+a2biZPWpm15nZydPc7zwz+6SZ3Wtm+83sSTP7vpm9voF9vd/MXHh5cDpxofX8s9AOGTgkN00iDgDq4yfXSibiGNcF6DoFY8RNpyKORFxN6h4jjkTctFER13x+RdxQb2FrSv91zW+J2jy6/1Gls8E46If0H1IwBlwpBRVxszRRVM14Ol8Rl8gWVsRV/C4rHiMuMzUR5z+/fF4AANA96k3EfVLSuKR/nIFYpjCz4yT9StL7JB0laULSAkmnSLrJzM5vcL+HSbpL0sckHS0pI2mepFdI+qaZfaHOff19I3EgGvy+98WJuKyb+sMZAFCaf0Cs1AFg/yx2Dv4C3cFvTTmdMeL8/aA8PxHnf+b6GCOuuaZUxM3SVnOtVFARV9Saktaq9XtkX+3VcJIKEnUHUt15cuqEXxGXndBErP7WlH2WUiqVnrJKQUUcnxcAAHSNuhJxzrlfSXqtpFeb2ffMbLWZDVbZrCFmNiDpWkmHSLpT0vOcc/MlHSzps5JM0qfMbE2d+zVJV0k6UtKDkl7inBuSNCTpwwrGwDvXzM6ucZf/ImmupJ/VEweiwz8LbahniLMsAaBB1VrQFRw8ozUl0BVoTVnZNXdu10su+oGOPH+TXnLRD3TNndurb1QBY8S13p4krSmbbTRVW2tKEsm1+f2+3+emDxuqPD6cVFSxlR7ruhaDzrmCirhYNlXQmrJiRVwspmwsvzybmvoZ2w2tKU855ZR2hwAAQOTUlYgzs4yk/5E0X9IaSd+XtNfMMhUuU08Bqs05kp4uaVTSqc65uyXJObfXOfdBSdcoSMZ9us79ni7pRQoSbn/qnLst3O+4c+5iSZ8P1/uEmVXsn2NmpylITH5bwfOCDuSfhTanZ07h4Mmz9IcxAMyEgtaUCVpTAiisZJtOa8rZWBF3zZ3b9eFv/ULbdx+Qk7R99wF95OpfTisZV60yWaI1ZbPRmrL59iXzrSnn9c4rWOa/rhlKoDZ+Iq6WirieeE/u8zfrsl33OZHMZDWZe0zETLHMhFKqMREnKetXI5f4vVswzmH6gDLZzJR1Ot11113X7hAAAIiceltTWgOXeu9j0pnh9ZXOuVL/jV4cXq8ws+c0sN//dc7dVWL5JZKcpMUKWlWWZGZzJf2rpDFJ76/j/hEx/j/Lgz2Dhf/cdWkrDgBoBK0pARSbTkXcbB8j7uIb7lcyXdgG/UAqo4tvuL/hfdZSEecfRKY6efp2T+wuuE2ruemr1Jqy4KQeXr81eWS0vtaUUmHVVrcllye8z+X+nriUHi+oiKv2XZb1XqOxEom4mMUKqg5nY0L51FNPbXcIAABETqLO9Y+ckSiKmNmQpJXhzRvKrPZTSXsUVOedLKnW/1hfXmm/zrntZna3pOcpSMSVq3T7hKTDJZ3vnHvYvB9m6CyVEnFUxAFA7aq2pvSq5GbjQQcAU01k858LdVfExWd3Im7H7tKfg+Xm16KWRFzBSRFpToqYrr0Tewtu8//D9FVqTen/lqC6vjb1tqaUgvaUk0nm/en9OkSHVN5gFhlP5SvU+nticulxJeNeRVys8neZ6xmQwo9iy5T+PB/sGcx9VoylxqYknDvd9ddf3+4QAACInLoScc65h2YqkCLPlXK1/3eXiSVrZvdL+gNJx9SyUzM7VMr9giy539A9ChJxJfdrZidIep+keyX9Uy33jegqTsQVDE7NgWIAqJl/QMw/Y33SQDx/UJiKOKA7+C0lp1URl5l9ibilBw1oe4mk29KDSifQauEngWoZI85PlKIxxWPEdVv10EzwW1MO9Q4VLCt4/WYmlHVZxazRJjzdod7WlJIK/ifutirPiVS+Iq4vEVcyPS7Fg9u9sYSqnYTtvJMdrEyyeE7PnFyybizNZwYAAN0gqr9Yl3jTOyqsN7lsSYV1mrpfM4tJ2qDgp9hfOOdm31GBLuMn2xgjDgAaV22MOH8eVRhAd5hOa0q/gm42VsR9cM2zp8wb6InrQ6+qp+t+oYLftV7rM1/BGHF8Fk9b8RhxE5kJpbONDpMOqXJFXMxijHNYhz0Te3KJzYHEgA7pr62yrSAR12X/E0+k8xVxfT2xgs/JvirVcJIk73hCrMxnbEFrSobDAACgK9TbmrJAWGG2QtLCcNbjkrY65x6bZlyD3nSlXyWTvwhrreNvxn7fI2mVpK865zbXeL8FzGydpHWStGjRIm3e3NBu0CRP7H0iN/2rrb/S/t35fzRuv+t2JX+dLLUZWmh0dJT3CdABfvPUb3LTOx7aoc27Nxcs3za+LTf96K5HK76ved8jKm4fvV3X7b5OT2We0sHxg3XqQafqhXNf2O6wOsbde/NNKB4febzs+7rUe37XE7ty07+4+xfqf2hqpW0n60+7gttzEtJbnhvXQXt+o82bf1Nmq8p2PJ4/1/DX9/xa8d/Fp6zzu4nf5aYff6r83wS1eXzf41Pm3bj5Rs2JlU6EIq/cd/32J/JDxP/mV79R5oFMwfK4y7+uv3/L9zU3Prva+jXTwxMP56YPsoN0yy231LRdcl/+f+CfbPmJ9gzsqbD27PLgnvzrLT1+QHuyu6XB4NCZZazqZ+axB5Ka/LZKj+8ruX5qLH9yyY/v+LEe75/6OdLJbr755pKPm9/3QPfhfQ/kNZSIM7OXSvqkpD8qs/yHkv7WOffjacQWOWa2VMHj3iPpg43uxzm3QUFVnVatWuVWr17dlPjQmOGvD0vhSasvf8nLtfWOrfrl734pSTrqOUdp9TNWty02BDZv3izeJ0D03faz26RwqJxjnn2MVj93dcHyxbsW65+v+2dJUt9gX8X3Ne97RMGmbZv0jdu+kav2fCrzlL6x+xs65phjtPaotW2OrjNs+9U2aUswfdQRR2n1qtUl1yv1nv/Bj3+g2x+4XZL0jGc/Q6ufXXrbTjWyZ1z63+/nbp/9smfpr145tUquHpd/93IpLE5+8coX64RDT5iyzpJdS/RP1wXd9XsHe/msnQbnnA58Zer5nStetEKLBxe3IaLOUu67/rPf/qwU5oFOetFJeubBzyxYPnTVkMbGgnZ+K1+0Ukvm1togp/v8z+/+RxoJpo9efHTN7/drbr5G9z18nyTpmc99plYvr2272eCOB3dJP/mJJGnBwfMUS+YbSc3tH6z6HE48uEjad48kaSCWKbn+N7//TT3wyAOSpGcd8yytPqLyPjvNhg0btG7duinz+X0PdB/e90Be3a0pzezPJd2sIAlnkrKSHgsvmXDeyyRtNrNzGozLb5JdaZCEydMMRyus08z9/oukeZI+7pwbqfE+EXF+qw3GiAOAxvljxJVqQefP89tYAlG1fuv6Ka/V8cy41m9d36aIOo/fNs5vNVmL2d6act944WPac2D6j9H/7VpujDj/eaU15fTsT+9X2k1tQ9ltY2o1W0Fryt6p1W5+a0p+T1TWyPhwUvB/8aRua005XjRG3EQ2Xx3YW0OL5ViP15qyzDicg4nZ/fyec06jhwIBAJi96krEmdkJkv5VwfhoP5b0KklznXNLnHNLJA1JenW4LC7pX8Nt6uWP37a0wnqTy3bO9H7N7OWSXifpbklfNrO5/kVSb37V3Pxptf7EzMtkM1MOWBSMEcc/0QBQM/9gWH9iags5//N1vMzg9UCUjIyVPu+q3HxMlcrkk0v1jhHXE+vJ72c2JuImChM4e5uRiEtVT8SRxGie4vHhJo2lxkrOR21Gk/lE3FDv0JTl/m+M/8/eu8fJcZ113r/T97nP6DIjjSxZtny/xrJzdS5KnMSA42ACG17g3QV23zjwssRAMNjwbqIElgS8bNbJLhBnWWCBsDjBcew4wUlsKwmxk2BLtmQnli+yLGl0mYumZ3pm+l7n/aO6u55TXVVdt+7prn6+n48+qumurqnpqTld5/md3+/h+wlnTqycaGyfM3KO69fR8aPfrmfaIy6TjKFEP8cseiCbEUSIS9j0MKSLf/vt/WUYhmGYfsWrI+7DtdfcC2CPlPIbUsrGnYWUsiil/Dp0R9wXoYtxv+XjvJ4HUG+acLnVDkKIGIB6J/MfujmolHIOQL0hmOVxa1xmcdxzyeuyAHKmf3fWnt9BHvu/3ZwXs37Q1WeDiUHERExtnMyOOIZhGNdQZwUt9NZhRxzTa0wNTlk+zpFz7qGOuCBCXKkavZ69uYIqxIXtiLMahwG1kBzF97WTZItZy8ej6HDpFGWt3LhHMM/N6rCY7B6/jrh+TomhjrhMMo6SV0dcighxWhFSyqZ96PvLi38ZhmEYpj/wKsS9DbpA9ptSSs1up9pzv1Hbd4/Xk5JS5gA8WfvyXTa7vR7AWG37EZt9rHjM6bhCiG0wRDovx2V6ELr6rB6/odwU8ySaYRjGNbQY1iqakuPQmF7gl674pabHMvEMbtt9W+dPpkcJEk2ZjEfcEdfuaMpka0dc0catwbiDHXHhQ91wQ8khCCGa9qGOuH4TibziO5qSRCf22/VcKBNHXBwokvjZlEXigxkaTZlGCVWtWYiLevTnAw88sN6nwDAMwzBdh1chbjOArJSyZRSklPIkdOfYZh/nBQCfr/3/C0IIq+7Lv137/ykp5WEfx323EOJqi+d/C3qfu1MwRDtIKf9aSins/gH4WG3XV8njf+3hvJh1gK4+q98M0xgOntgxDMO4h8ZDWUVTKlFS1YLlCmGG6SaunbpW+XpjZiP2vmkvbjr/pnU6o96DOq44mlJlJWRHnJRSWRBhF02puJMrPBYHYalkLcRFsbBux/0HZnD9Jx/FeXc8hOs/+SjuPzAT6HhKLGWyOZYSMDni+iCa0u97XKqWcGb1DADdXTg95NSdQ6WfHVvFirHmfCihoUTEYFefY0nj+syghFK1eQ171IXOa6+9tvVODMMwDNNneBXilgGMCCGGWu1Y22e09ho/fBbAq9D7zn1FCHFZ7bgjQog/gd6vDQB+z+J7y9q/vRbH/TKA70P/2b8khHhD7TVpIcSHoTv5AOCjUkrOaok49Ka3Ptmg8Sf9NulgGIYJAnVWWEWixUQMqVjKcn+G6UbMsXN/9JY/YhHOI4EccVSIq0ZPiAs7mrKklaDVQksSsYTy/lHisTgSMb2VtYSMpMjZKZaL1lPdfplD3H9gBnfcdxAz2TwkgJlsHnfedyiQGJcr5xrbw6lhy33owp6o30vcf2AGd/p8j2dWZiBrHT+2DG5RXMatoI6tKApFTlBH3HC8giIR4lx9jpFFEAOiiFKlWYiLeo+4bdu2rfcpMAzDMEzX4VWI2w+979uHXOx7W23fp7yeFABIKfMAfhLAAoDdAJ4TQixBd9ndDj328s5aTzovx5UAfgbAKwDOA/CEECIHYAXAf4H+nvyFlPJzfs6b6S1WK83RlOyIYxiG8QddlW7XzL6fimdM75MtZJWv+6W4HiZBHHG04BlFsSjsaMp8mcRS2rjh6nDPznCw6xEXxcK6FXc9fFjppwUA+XIVdz3sJbBGhTrihpOthbioO+Luevgw8hbv8Z/88/MtX+s3lhIwLU7tI4cnABQqhhA3GK8EdMSVWwpx/fb+MgzDMEy/4lWIuwd6bOMfCCH+UAgxZt5BCLFVCPFfAXwculh2j9+Tk1I+A+AKAJ8GcARAGrow9xCAd0kpP+nzuCcAvAbAHwF4HkACQA56FOX7pZS/6vecmd5C6RGX4B5xDMMwQVAi0eKtexPxYgem21ksLipf90txPUyo4B4kmpIKelEhV1QdccWKpjgxvKL0h/MgxHHPTv/QHnH0861f5hAns9af43aPu4E64kZSraMpo34vYfseLxXw3775AuZy9n+/J3InGtvnjJzj6fv2czQlFZcHY6ojztXnWELtEVe0EOJoNGW/vb8MwzAM068kvOwspbxPCPG3AP4tgDsBfFgI8QyAGQAZADsAXAggCV2w+xsp5ZeCnKCU8jR0d91tHl7T3NG5eZ9lAL9f+xcYKeVeAHvDOBbTOehNb72hPTviGIZh/KEU3G0ccfRxdsQx3Y7Z7dIvxfUwoQJaoGjKSDriKk2PLefLyCTjvo5H71upm8UKKmTwWOwfKsRtHd6KV5ZeAdA/ov30+ABmLISi6XFnIdgJxRHnIpoy6o5Ou/cYAP7bN1/Enz32Mt77mmn8++vPw2XTo8rz1BHnWYjrY0dckTriYj6iKV30iIt6NOUHPvCB9T4FhmEYhuk6vDriAOCXoPdly0F3qL0OwE8B+HEAlwNI1Z67A8B/COUsGaZNUCGuHk3JPeIYhmH8oURT2qwY7qc4Kab3MUdTRrFY1m6COOKiHk25YiHEBYmn9OSI40URobBUMoS46aHpxna/zCFuv/FixGPqGtiBZBy333ix72OulA0hbiRp44ijMdcRd3TefuPFcFplXKpq+OJTJ/ATn/4Ofu6e7+EbPzyDqqb3haOOOK/RlLRHXL9cz3WKJkec52hKMv5mRMkymlJ5fyModN5zj+9gLIZhGIaJLJ4ccUCjx9onhRCfAfAu6P3bNteenoPeR+7rUsro3U0wkUPpEZfgHnEMwzBBUKIpbYrA1IUR9VXsTO9jjqbst2JkGFCRJxXz74iLZjRls+gWRIijxdxWQhyPxeFAHXFbhrY0tvtlrLjlmm34u+8dxZOvZhuP/cFPXo5brtnm+5i5ksdoymq052u3XLMNex94Dtna2DA1msbv3HgxUok4/vJfXsHTx7ONfZ84soAnjizg3I2DuHbHOL6de17PKgLw8kwa2On++0bdseUEjQjOiDIWiBLqyxHXqkdcBMeLa6+9Fk899dR6nwbDMAzDdBWehbg6UspVAPfX/jFMT6L0iEtyjziGYRi/VLUqKpru7hAQSgGd0k+r2JnehxbZAb4v8EOgaMp4/0VTdswRxz3iQoGOEdPDhiOOLvaLOuOD6t/1Gy/YFOh4nqMp+8BdXybRht/4rbdhNKOPjTdfPY39xxbxv/7lFXzt2dMNJ9yrC2t4dWEVwxfPN9x0n/n6IqYHZ1yLpP0dTWm83wNCdcS5WlBCHXF20ZSJaAud+/fvX+9TYBiGYZiuw080JcNEBrr6rC7AsSOOYRjGO9T1kklkIIR1kBIt/rILg+l2FguqIy6KxbJ2EySaMuo94toZTUmFCit4LA4HpUfc0NbGdhQdLnaYr9nZ5WDXE42mHE7aCHHx/hHiShUNqyXdoRWPCYyk1bXUu3dM4L///G5853fejl952y6MDejjpkjkIGL6GCMrg8gXU7jr4cOuv28/R1NSR5xZiHP1OZakQly5L6MpGYZhGIZphoU4pq+xcsRRIW6tvAY9jZVhGIZxQikAx+0LwHSMjXrxjOl9ssWs8jULcd4J5IijQlw1ekLccrf0iGNHnC+klGqPOOqI66OxIrtmEuJywa4nV9GUif6JVs3mjTF0fCBpu9BpenwAd/z4JXjizncAAGLJhcZzWnkDAOBk1v0iU/N7XNWqDntHCyrEpUUJReqIcxVNaeoR18IRF8Waw9atW1vvxDAMwzB9hm00pRDi0drmq1LKXzY95gUppbzBz8kxTLuxEuISsQRSsRRKWgkSEsVqseWqYoZhmH5Hcb0k7FcLK3FoVS7+Mt2NWYjrN1dAGBQ1/444WvCMpCMu5B5xvqMpNR6L/bBWWWtEMmfiGUxkJhrP9VOqhvmanQtRiLN1xPVRNOUSETrHBq1jvymDqQS2jQ/gjDzbeEwr6ULc9LjzuECJiRgGE4MNt9ZaZc1WGI0aNJoyjbJ3R1yidY+4eCyOTDyDQrUACYl8Ja+0yOh1Tp48ud6nwDAMwzBdh1OPuD21/5+3eMwL0Vraw0QK2r+BxkMMJgdRKuqrD9cqayzEhcRDRx7C3fvvxunV09gytAW37b4NN51/03qfFsMwIUBXpDs54mgBo58KlUzvUagUmq5Rjo/yDnXEcTSlQbmqoVBuLs4GEeKoINFKiKPjNDvi/EFjKUfTo5Hv+WRHUzRlQCGORlPaCT8D8f5x1y8SIW5i0J2r+PYbL8bvPvrlxtdaeSMGknHcfuPFnr73YJIIceX+EeIURxzKiiPOazRl2kaIA/T3t37/vFZZi5QQt3fvXuzdu3e9T4NhGIZhugonIe6Xa/8vWTzGMJFA6RFHJs8DiYHGKvi18ho2ZDZ0+tQix0NHHsLex/c2JhunVk9h7+N7AYDFOIaJALQQ5rR4gRaH2RHHdDNmNxzQX8X1MJBSKn/nQaIpqaAXBXIWsZTAOkVT8ljsCyrEjafHlUV9/TJWFMpVxT0EAHO5YMKYG0ccvX4jH025pkZTuuGWa7bh40+9gvpokp74Pn7mmtfilmu2efreQ8khzOfnAfTXQhS6SCIlyt6jKakjTtgLcUPJIZwt6M7F1fIqNg1s8nnG3cfHPvYxFuIYhmEYxoStECel/Bs3jzFML2MVTQmoohw7NsLh7v13N02UC9UC7t5/NwtxDBMBlGhKh9XC9Lmor2JnehtaZK/TL8X1sKjICjSpFyDjIo5EzGkNYDNRjqZcsRHiljskxFFHHI/F/qD94cbSY8p7nq/koUkNMRHtluxWwvHscniOuOEUR1NmPUZTAvoCyHLyqPFAfA1fOflpXHdkg6d5l7mPWb9QqBiOuJQseY+mpD3iYN0jDkDfumgZhmEYpl+J9syAYVpAJxRUiKMT6X5a/ddOTq+e9vQ4wzC9heKIc4imVIpnEV/FzvQ2i8XFpsd4cY43qIvNqxsOiHY05XLB+ufplCOO/j7YEecP6podS40hEUs0Pv8kZOQFIsBGiAsaTVnyGE0Z8XuJbN4YR91GU969/26YO4TUF0B6gUYl9tOcuEgccUkZ0BGHsqMjrk4/CZ0MwzAM0694EuKEEI8KIb7gYf9/EEI84v20GKYz0AkFnWjQbS66hcOWoS2eHmcYprdwG03JLgymV8gWsk2P8Yp1b7h1ytoR5WjKlaLhiBvJGE7BTglxylgccSGjXSwXlxvbY+kxAP0nXFC3Vp25AEJcWSs3rseYiCmOIUq/OuLcRlOGtQCyXx1bReKIS4ThiCM95yhRHi+efPLJ9T4FhmEYhuk6vDri9gC43sP+b6i9hmG6EjqhoBONfo3haCe3XnVr02OZeAa37b5tHc6GYZiwcR1NyX2JmB7ByhFXrBZR0awjBZlmAjvi4tF1xNEecedMGPedoQlxSfc94qImcnYKGl/bEOL6TLiwul7nV4rQNGmxd2uoG24oOQRBBBBKP8VcL1IhzmU05dTglOXjXhdAKkJRH82JaY84sxDn6rMsFkdV6AssYkKiUrG+3+238YJhGIZh+p12R1PGYc5EYJguoaJVGkXgmIgpK4fNPR6Y4Lxp+k3K1xsyG7D3TXu5PxzDRATqqGBHHBMFaOwcJWqr1ttJmI64cjVqQpzx85wzYdx3BhHilKQHGydRnX4SMtqFlRBHo+b6obBudb1WNImza/7EXSWWMmkdSwmoc7WoOzqXSDTluMtoyl+8/BebHvOzAFK5nivRv57rKI44reg9mhJAJWaMsVrJup4Q5WjK6667br1PgWEYhmG6jrYJcUKINIBJAMut9mWY9cDshqMrLqMcE7Fe5Eo55euPvOEjLMIxTISghVyngjv3iGN6BatoSiB6xbJ2ElSIowXPqDniaDTl5EgaiZh+H1ooa0oR2Av5sr9oSnYn+2OpRIS4lEU0ZR+MFVkbwW122d81lSsb84Xh1LDtfmYhWcrorv1dXPXuiHvd1tc1tqUEUtjoawFkP6bEVDWJclW/noQA4tUSSsSYmY65+yyrxowxVpZbC3H9INwzDMMwTL+TcHpSCLEDwE7TwykhxFsAWOdE6I+PA/g5ACkAjwc7RYZpD3QyQSfNgMkRZ3PjzHjDLMStlFds9mQYphehhVy3jriiTVQPw3QDVtGUABfLvBA4mjLWH9GUI5kkxgaSWFjV36+lfBmTI3HPx6QpDnSstYJGU/KiCH9Q12y/9ohbtnFwzuYKuAyjno9HHXHDSXshLh6LIxVLoaSVICFR0kq+xP5eIEve4wmXjjg676rmz8X54vdw0/lvcniFNf0mLANAgfRzyyTiEFXVEef2OqvG00D9V1eyfu9ozaGfHIcMwzAM0684CnEAfhnAR0yPTQDY5+LY9buV/+btlBimM9BCGl2NBqg3xf0wie4ELMQxTLShjjinAjAt/uarvNCB6V5o7ByFhTj3BHXExUUcAgISElVZRVWrIh7zLlB1I6oQl1CEuOV8GZMjzkKaFUqPuBaOOPr74EUR/lguGsEvjWjKRHSj5qywi1KdywV3xI2mnIW8TCKDUkn/mylUCpEV4paI63BswJ0jTpl3VQewVPa3kEFxxPXJnJgKcelkDKgUvfeIA1CNU0ec9WIHWoOI2uLfj370o+t9CgzDMAzTdbQS4rIAjpGvzwWgATjh8BoNehzlcwD+Ukr5WJATZJh2QVed0UkzoK7+4x5x4WAW3riQyTDRgjoqHKMp2RHH9AiLBcMRN5AYaNwP9EsxMgyCOuKEEEjFUw1Br6yVIyTEGYXxkUwCo6TA7rdPHB2HB5IehDiOpvSFVY84Oofoh3td6tbaNJzG/Ip+Lc36FOIUR5xDNCWg308s17pg5Cv5xu8gaiyueY+mpEKc1DK+x5Qo9zCzo1jRGtuZRByoFHw54jS6Xx9GU+7du3e9T4FhGIZhug5HIU5KeTeAu+tfCyE0AHNSyvPafWIM025cO+L6ZNLRbpZLartIdsQxTLRQHHFO0ZQJ7kvE9AY0dm7b8Da8lH0JQPSKZe2ECnF+3SrJWFIR4jLw7hTrRqwccXX8Fs29OOK4R1xwrHrERbmwbgW9Vi+cHG4IcX4dcXR+4BRNCfTH/UShXEW+5tBKxASG063WUesoQlzVvxCnCMt9Ep2oRFMGcMRpNB3CJv43yu/v9PQ0Tp48ud6nwTAMwzBdRczj/h8D8KftOBGG6TROPeJoDAc74sKBrnAFgNVStCYbDNPvKD3iHKIp6XM8vjLdDBXipoenG9u8QMc9QaMpAbVPHBX2ep2VIhHi0slwhLiyh2jKBDvigiCltO4R12dRfooQN2UIZ7M5f30HqYA0khpx3JcKcXQxUJSgPfjGB5MQRBByQnXEDaBQ1lCsVB1eYU2/Ra0CQKFsOOLSiThkJa844twKcZJcn8LOERfh9/fUqVPrfQoMwzAM03W4W1JVQ0r5sXadCMN0Gjo5bnLEJblHXNiYHXC0BwTDML0PLYLRAq+ZfljBzvQ+hUqhIRQnRAKTg5ON56JWLGsn9G/cTzQlACTjhkBV1vwJVN0IjaYcNjvi1rz/nFWtipKmC5UCwnFBBKAuiijYuDUYe/KVPCqaLqZm4pnGZxtd3NcPYwW9Vi+cMoSz2eUORFMmor+wR42ldD+Gmh1xgC6aTo54i/ZV5sR9cD0DUATLTDKGSqUILakLcQkRRyLmroRGhTjYCMX9Nl4wDMMwTL/j1RHHMJGBxsXQ1avmr6M6ses0StNw9EdcD8P0E7SQ6xRNSV0xUV3BzvQ+ZqcLjUiLWnxUOwkrmrJOtIQ4p2jKitVLHKH3q5lEpqVzRukRx/06PUP7w42mRxvbSk+tPljMRx1xF2w2xsm5lQ5EU/aBmJxdM8bQ8QF3/eEA0wJITX+fln2MK/3m8ARMjrhkHGVyr5p0KcIBgCQiZsxNNGXE5sa7d+9e71NgGIZhmK7DkyOujhDixwD8DIArAEwAcLorlFLKXX6+D8O0E+4R11nMQpw5qpJhmN7GdTRlIvqFM6b3oUX2icyEUoyMWrGsnSiOuJhPRxwV4qoRFeJCiKb00h8OMC2K4LHYM0p/uFosJYC+GiuklPbRlMtFSCldRynWoT2lvURTRlVMVh1x7oU4+j7Kqj4e+BlX+q3nIQAUFEdcHMU8iVj28DkmEq2FOCWaMmJC51NPPbXep8AwDMMwXYcnIU4IkQTwjwB+sv6Qi5dJryfFMJ2Ae8R1FnbEMUy0UaIpHZwviguj6q9QxzDtZrG42NgeT49zfJRPwnDE0UjLaDnijJ+l2RHXASGOe8QFQnHNpgwhrp+Ei9VSFRVNn+oPJOPYOJRCOhFDsaIhX65ipVjBSMa9eASYoik9OOLy1WjO15byxBHnN5qy4YjzPq4on30RE4rsKCo94mIokvtbTxHLxBEXtxljozxe3HrrrbjnnnvW+zQYhmEYpqvw6oj7XQC3QBfXHgJwP4AZALyMkuk5HB1x5MaZhbhwMPeIM3/NMExvQx0VTkXgRCyBRCyBilaBJjWUtbLv3lEM0y6yhWxjezw93ndxc2ERSo844oijwl4vI6XEStFwxA1nEhjtsBBHRYyovK+dhLpmx9Pjje1+ivKj1+nYQBJCCEyOpnH8rH4tzuaK3oU4Mj/w4oiLatR1ljrivERTEkEzkCMuEV2hyI6iyRFX0sqoB0ClPXyOiaRxfcZdRFNGbZHP5z73ORbiGIZhGMaEVyHuF6CLcHdKKf+kDefDMB3DSYhTJtERuyleL9gRxzDRhsZCtXK+DMQHkNP0MaFQLbAQx3Qd1O0ynhnvq7i5MKFCHPeIM1grVVEzEiGTjCEZjymOOD/OlUDRlJUCu5M9QoU4JZoywoV1M0r/slps4uRIxhDilovYtdnZ1WaGzhc89YiLqBDnN5oyV252xPkR4uj1nC/n+2KcKJSJEJeIoaiVYAhx9tHrZoQLR5zZcdgP7y/DMAzD9DMxj/vvBKAB+Ez4p8IwnYWuUjVHU9ICBjviwqGpR1x5BVJyci3DRAWl4J5wLrjT56NaPGN6GxpNOZGeiHR8VDuhTiu/gnsUoymV/nA1x1DQaEp6X+tGiIvH4kjE9DWZEjIy722noD24RtOjjW3FPRtxIY5ep3VH5+SI8fk+t+I98pQ64oZTLYQ42iMurHjVg/cCn7oC2Duu/3/w3nCO65MwoilR9S/EpeKpxjhRkZW+GCcKNJoyGUOJ9CZNtbi/pYiUMQ4nNOvrMxlLNvqnVmWVY4IZhmEYJuJ4FeKyAHJSSlYmmJ5HccQlHBxxtdVpTDDMUZQVrYKSxlFIDBMVFDdG3LkITFexUycdw3QLNJpyLD3WVy6XMOFoSmtWimp/OAAYG+xsNCVgchTZRKcx1ihjRMraEbdaibZov2yKpgSAzUSIm132fk3RSEUv0ZShLJw8eC/wwIeApeMApP7/gx9aVzFucdW7I05KqQjFQRxxAPrOEa5EU8brjjgdL464WLK1EAeYxowIvb8zMzPrfQoMwzAM03V4FeK+BWBMCLG9HSfDMJ3EKZoyGU82Vv9VZbUvVv+1k1K1ZLnCz+ySYximd/HiiFOKZ1Ve28N0HzSaciIzwT3ifFJSCpg+oynj0YumXKaOuHRNiAvoiKPuYrdCHBVHeVGEN5ZK1j3i+qmnllX/MsURl/N2TZW1ckMQjomYIgBZQa/zUNz1j3wcMAt65bz++DqRJY64CZeOuGK1iIqmjzFxkQSk/rvxK8T12+cfdcQNJoAijAW5XhxxibRx/ToJcVF9f5966qn1PgWGYRiG6Tq8CnF/CKAA4I/bcC4M01GchDhAndzx6vdg2AluUS9QMEw/QYW4TIsVw7Qgz8VfphtResSluUecX7hHnDUrFtGUQ6k44jG9N1C+XEWpolm+1g52xHUWNz3i6j21osqShSNucsS4pmY9CnHUDTeUHGrZK0vpcxjG9bt0wtvjHYCKnVSsd4LOuwbiRrynn96TQP854miPuMFYGSVyHXr5HIuTaMqktL8+o1pzeO9737vep8AwDMMwXYcnIU5K+SyAWwD8mBDia0KIPUKIZgWDYXoAeqNr7hEHqJMO7hMXDDshzhxXyTBMbyKlVMbJVoUK6ojj4i/TjSwW7HvERalQ1m7C6BEXxWhK2iNuuOaIE0JgtBZTCXh3r/gR4qh7OSrvbaewE+LMPbWiHMNOr9F6bOLmURJNmfP2+a7EUiadYykB071EGI64sXO8Pd4BFNehy2hKOu8aShpCnO9oyj6LZi6SRRBD8YoixNX7ubkhThxxSYdxgHvQMgzDMEz/4EmIE0JUAfwzgDEA7wbwCIBlIUTV4V/F8aAMs07Q6AcrR5wy6YhQTMR6YCe4rZZ4ssEwUYAWGpOxJOKxuOP+igsjjOIZw4SM2REX1eiodhOGI44KePW4tV4nV2juEQcEi6dkR1xnoULcaGpUea5fhPuspSPOfzRlrmwISK36wwFtuH5v+AgAkwsvOVB7fH3wE01J38dhFuI8ozriKihSIc7DgpIEccSlZP9FUzIMwzAM04zXaErh45/X78EwHYGuOLPqQUCLGOyICwZtGE5hRxzDRAMqprWKpQTUVexW/SMZZr1RhLjMuNrXsJJHVatavIoxQ/++w3DERSaastgcTQl0XojjmGD/2PWIA/onyo9eo6O1a3fzCHXE+Y+mHE4NO+ypE3qPuKverwtvdWIJ4OZP64+vA4VytdGvLBkXGEw5L3KqQx1xY2lDJA4jmrIfhCLaI24gXvUfTUkccWmUUKlaxw1Hdbz47Gc/u96nwDAMwzBdR6L1LgrnteUsGKbDlKvlRjEnLuKWN9XKpKMPVv+1EzqxpkRpssEw/YwixCVaC3F0zOWFDky3UagUGtdlQiQwnByGEAKDicFGEXKtsubKsdHv0LjDMHrERSU+cZlGUxJH3CgR4rwWzYNGU7Ijzj1SSttoSqB/ouaWlWhKXWjfOJRGTACa1GMVi5Uq0gmXAhJ1xLmIplR6xIUhxGlVoEzuSeIp4Mp/E/y4PlFjKVMte+bVoULceMYQ4vw64vrNsVWoGAttMqKMJZ+OOJBxeECUUK5KWP0pRNVxeOutt673KTAMwzBM1+FJiJNSvtquE2GYTqK44ZKDlhMbdsSFh53zjR1xDBMNvMbPsSOO6WaoG24sPda4RxhKDhlCXJmFODeEHU0ZGUccEeJG2xFNmWRHXDvJV/KNazEdTzctQOmXPtNUKKpfu/GYwKbhdMMNN5cr4pyJ5uQRK7w64kLvN1tYAiCNr8trwOocMDwZ/Ng+oLGU4wPu+sMBqhA3kRmDEICUwGqpinJVQzLuLbAoqo4tO4rUESfKvh1xSBrXZwYllCoaBixcjVEVOoUQkFK23pFhGIZh+giOjWT6ktWKMYmw6g8HcI+4MKETQko/TOYYph+gBTA3jjgaX8lCHNNtUKfLRGaisU3vC+h9BGMPdbBxNKUB7RE3nA5JiCsHjKbksdg1ihsuNdb0vDJWRPhed8miRxwATI76i6ekC/RobzM7Qo+mzC82P7a4fuuQF1epI86fEDeaGsFoxr/TFuifnod1ioojTu0R50mII9dnBiUUq9aR1v0mdDIMwzBMP+NbiBNCTAkhflYI8dtCiPXrYMwwPqA3uUMJayGOHXHhQSeEtKBmJ9AxDNNbeO0RR+PQeHxluo3FolGMpb2fOLLaO2E44qIYTZkrtLlHXNydEMeLIvxB+8ONkh5cdaLqcDFDr1Hq2JocMa6rOQ9CHJ0XuHEc0+u3fULc0eDH9ckSdcQNul/IYH4f6bhCY3HdQh22/SAUFcqGYJZGSRHiPC0oIY64tCijVLHuEddvQifDMAzD9DOehTghREYI8ecAjgH4PIA/BvBR0z7jQohFIURFCHFBOKfKMOFBb3JtHXFccAsNOiHcMrSlsd0PkzmG6QeUYnuidbGdFom5+Mt0G9lCtrFNhTgulnknFCEuHj1H3EqRCnFtiKb00SOOx2L3UEccHSPq9IPDRdMklomzk/Y33Dzs0xG33tGUa2ebH8seDX5cnyg94nxGU5qFOD994uii1X5YPFUkgllGVPxHU5occXZCXFQdtO95z3vW+xQYhmEYpuvwJMQJIRIAvgrgVgBlAI8BaLq7llJmAXyudvyfDXyWDBMy5h5xVrAjLjxo1MzWoa2WjzMM07sEccSFsoqdYUKE9ogbz4w3tqkQF6ViWTsJO5oyOo44Ek0ZlhBX9d4jLnRHUZ+gRFOm+zOaMleooN7+aSSdQDxmiBU0mnJu2f11lSsbApKbaEoqxIUyV+u2aMo1n9GU9H1MDQcW4vrheqa0wxGXQQmlqo0Ql4hmO4wHH3xwvU+BYRiGYboOr464/wBgD4AXAVwppXwngCWbff+x9v87/J0aw7QPJZqSe8S1neXScmNbccSVoj+ZY5h+gK5Ed7NamO7DxV+m26DRlBNp0iMuwT3ivBKGI44WPqPiiKPRlKPr6YjjHnG+oGJ9KyEuqov5lP5wJpFocsSfIy5INGUo12/ewhG3jtGU2RCiKUdTo8GFuIgKRXYUyoZglkRZccR5E+KM983JERdVt/3NN9+83qfAMAzDMF2HVyHu3wKQAH5dSvlKi32fAVAFcJmfE2OYduJGiGNHXHjQqJmpwSnjcXbEMUwkUBxxidaOODq+cvGX6TZoNCUtsisLdCJULGsnYTviKpr3/kbdSI5EUw6nQ+oRVw4mxIUS7dcn0AVmY6lmIY5G+UXVQURFojFTbOJm0iPOdzSlC0ec2V0v6xY9v1g54rLr54jLrvp0xJkEzdEBQ+z3FU3ZZ27wYsVwxKVMQpynBSXxJKq1cltCaCiXrP8Wovr+fuUrX1nvU2AYhmGYrsOrEHc5dHHtsVY7Sikr0N1yG3ycF8O0Fbqaj67yo3CPuPBQoimHjWjKKE02GKafoWKaGyGOHXFMN0PdLhMZwxEX1VXr7aKiVVCVekEzJmJIiESLV1gT9WhK2iOO9tla7nSPuAovinBLq2jKfhgrFEecSYhToim9CHFkvuDGEZeMJZGI6X8/VVkNLtRb9YhbmgGq6+PEpWLnhAdHnFnQDDKuAP23CIU64lJaCUVDh/O8oKQkjL+FSsH6vVOiP9ltzzAMwzCRxqsQlwGQr4lsbhgAwBU2puugkwg3PeL6IYajndCVmVsGjWhKdsQxTDSgYpqb1cJUrGMXBtNtKD3i0uONbS6WeYOKZul4GoK4CrwQtWjKclVrFHpjAhhMxRvPcTRlb8A94tTr0+zW2jxMoyk99IgreesRB6jxlLRPoi+sHHGyCiydCHZcn2Rpj7gB/464MHvE9UNKDO0Rl0RJdcTFvEUsl6kQV7J+73jxL8MwDMP0D16FuFMAhoUQLV1uQoiroQtx65fnwDA2eO0R1w+TjnZCJ4Rbh9gRxzBRg4ppbhxxtHDGjjim21gsWPeI64e4uTAJI5YSUB1xURDiVgo0ljKhCJS015aXgrmU0pcQF3qPrT7BS4+4qC7moyJRczSlIT7Mr5RQ1dxFRtIFesMpl0IcuecI7Oq06hEHrFs8pfIee4mmLDv0iFsL1iMu6p99UkoUSS+3uFZCMeYzmhJAWRiffdWS9VgQVQdt4KhYhmEYhokgXoW4fbX/f8nFvnuh95P7hsfvwTAK9x+YwfWffBTn3fEQrv/ko7j/wEzgY3rtERelm+JOI6W0jaak0SkMw/QuSjRl3IUQl+DiL9O9ULeLnSOO7wtaQ/+2vboIKFGLpswRIW4koxbXh1MJ1Gu+a6UqylUNbihWi5DQi540rq8VSo+tiLqT2zGPUBxxFj3i+sHhQoXiUZMQl0nGG+JPVZM4u+ru75bOC9xEUwIhL+yhjriNFxjbi+skxPmIpixr5YYoHxdxDCQGFCFuuRCsR1xUheU6VIRLxWOIVYsoksUSXheVlMlnn2bniIuo2/6ee+5Z71NgGIZhmK7DqxD3p9DFtY8IId5ptYMQYqsQ4u8A/CSAEoC7g50i08/cf2AGd953CDPZPCSAmWwed953KPAk2muPOHbE+WetsgZN6pOagcQABhODjQJRSStFoqjGMP0OXYXuKpqSRknx+Mp0GYtFoxg7nhlvbLMQ543QHHHxaDnickXr/nAAEIsJRdRw64rz44YDTI64CPaIa9c8Yrm03Nhu1SMuqg4i2mtsfKD573tyxFufuLJWbojBMRGznZ+ZoQt7AkdT0h5xW19jbC8eDXZcnyjRlC4dcUp/uNQwhBDBoyn7yBFXJP3h0skYUCmo0ZQeHXEVF0JcVB1xH/zgB9f7FBiGYRim6/AkxEkpnwPwGwBGATwshHgGwDgACCHuE0I8CT2K8uegC3a/IqU8FuYJM/3FXQ8fRp7ktANAvlzFXQ8fDnRcz464iK/+ayfmfg9CCKXvA/eJY5jehxaB3URTcl8iplspVAqN6zkhEsrnlRJNGaFV6+1CccR5LF5SohZNqTrimp1rformXsfgOlQgjeJY3K55RKsecf3gIHKKpgSAyVFvfeIUAak2X3BDuI64rLE9fY2xvQ7RlPlSteHOSiViGEjGW7xCR+kPl9RdhUGFODonzlfyjQWWUaRQMcaLdCIOVII54twIcalYCgmhfxaUtTLK1d7/nGMYhmEYxhqvjjhIKf87gPcBOA7gSgBpAALALQB2A0gAOAHgFinl34R2pkxfcjJrfcNq97hbuEdc51CEuFq/B2WlcImLmQzT63A0JRMVzL2faDE4qqvW20VRM/62Q+sRF4EC5YpDNCUQXIhz6yQCTCJGBKMp2zGPkFK2FOL6wUFEr00rIW7zMBXiWn/O+4mlBEK8n6hWgMbvVQBbrzKeW4doShpLOT6QdC1MKkJc7X0czQQT4uKxeJMYF1WoIy4TgiOuSsZYafO+CSEwkDTe36iOGQzDMAzD+BDiAEBKeT+A8wG8E8BHAPw5gM8C+DiAHwewS0r5YBgnKITYIoS4WwjxshCiIIQ4I4R4UAhxQ8Djjgoh/lAI8SMhxJoQYkEI8YgQ4mccXpMSQvyKEOJ/CSH2CyFOCiFKQojl2tefEEJstXs9453pcet4HbvH3UILaLZCXB/0d+gE1PFWnxCyI45hogUt4NKeQ3YoUVIRLugwvQctsE9kJpTn+iFuLkxoNGUQRxwV8SLhiCPRlMPp8B1xXqIp6Xgdxajwdswj8pU8Spr+XqViKcvFJ/0QY0uvTavYxMlR431xE02ZK6sJGm4J7X6ikDW2B8aBifOMr9chmnJx1XssJaC+j/V5V1BHHNA/vdOpIy6TjAOVUkAhzthf2jjigGi6aB944IH1PgWGYRiG6Tp8CXEAIKXUpJSPSin/UEr5a1LKX5VS7pVSPiylrLQ+QmuEEFcBeBbAh6ALf0UAmwC8B8A3hBB3+DzuOQCeBvD7AC4BUIUet/kOAF8QQvyZzUs3QBcdfxnANQAmAawAGK59fQeAHwkh3u7nvJhmbr/x4qYojnQihttvvDjQcWkBjU6WKXRlGheK/WMVkUInGyzEMUzvQ+OgBuKtC5xKXyJ2xDFdhNIfLj2uPEfvC6JSKGsnHE1pTatoStojbrmDPeKi6Ii7/caLkYqrTqKg8wjaH248PW7pVFIW80V0rMi2cMTRHnGzyx6jKVPuhTh6vQeKpqT94QY2AKPTQH3sWZsHip2dryiOuEH3jmJLRxz5/eQKFVQ16fl8+mUhSqFMhTjdEUejKWnPUjdo1BFXdhDiEtF7f6+99tr1PgWGYRiG6To8CXFCiH8nhPg3HvZ/nxDi33k/LUAIMQDgAQAbARwAcIWUcgzABIA/hR6H+UdCiHd7PK4A8EUA5wE4CuB6KeUIgBEAvwNAA/CrQogPWLy8AOC/QY/m3AYgJaXcACAD4CcAPA9gDLqYN+7lvBhrbrlmGz7xviuRSRiX6s+/fjtuuWZboOPS3i52jrhULIW40EXAslaORPFnPbCaENIJdlQmG0zv8dCRh/DuL74bV/3NVXj3F9+Nh448tN6n1LMoBXcXjji6T+CeLgwTIlniijALcbRQFmVHQFhQh5XX4iWFCnFRcG3lPERTtluIU/p1VqK3KOKWa7Y1zRl++fqdgeYR1DU7mh613GcgMYCY0OcuxWoRFS2UNapdxXKraEoixM2teHPE1RfuuYFew4HE5LyxCAMDE0AsDoxvNx7Ldrbt/RLpwTdu8f7aYTXviscERoj7NlfwPqftB3EZQKMvH2D0iAviiKNCHBzud+nC4KjMjbdtC1avYRiGYZgo4tUR99fQhSi3/CmA/+Xxe9T5IIBzoTvObpZSPgcAUsplKeVvA7gfuhj3CY/H/UkAr4cuuP2UlPLx2nELUsq7AHy6tt/HhRDK8jMpZVZK+ZtSyi9JKU9KqXcqllKWpJRfg+7UA3Tx8GaP58XYcMs12/BTu89pfL1zo/tVknYoPeIS1kKcEKJv8vDbSaseceyIY9aDh448hL2P78Wp1VOQkDi1egp7H9/LYpxPqJjmpkiRjCUbCx2qssoLHZiugfaIG8+MK8/1iyMgLMJyxEUumrKFI66T0ZQ01i+KjjgA2LFBTb7YtTnYPKJVfzhAn0NEXbhQesRZRVOOGNfW7LK3HnFeHHHKNRxkYU+eOOIGN+j/j59rPNbheMrFNZ/RlCXriE/VaetdGO6XHqmtHHFeP8skuT7h4IhT4mwjOF4wDMMwDKPjJ5rSXadg//vX+YXa/5+XUs5YPH9X7f/dQggv+SL1435TSvm0xfP/BYAEsAV6VKVrpJQvA6gvp5v28lrGmalR46b3jIt4EyeklMiTG2E7RxzAfeLCwKpHHF3pulriYibTee7ef3dT0bFQLeDu/Xev0xn1NvS9dFsEpsWzKDoxmN6ERlNOpNUecUqPnMoaNKmBsYcKcVRM80rUHHErpEfcegtx9PcS1Zjg+RX1mgk6j6Bi/VjKWogDoj2HKFc1rBR1MScmgOFU83VMHXGzLnrE0fmCpx5x8bCEOJMjDgAmdhqPZV/1f2wf0GjKCZ/RlKOLx4BPXQHsHcd9pVvx3ti/APDXJ65fopkLZeNzPZOIQ6sUUKbRlDH/0ZQxh+uTHfcMwzAM0x/47hHnknHocY6eEEKMAKiHSj9ss9v3ANSXJN7g4fD1/m2Wx62Jfs/VvvQkxAkhLoEenQkAr3h5LePMFGn4fcbFqkonSloJlVobw0Qs4RiXxH3igkN7aTR6xKWMyQaNomGYTnF69bSnxxlnqJDmdrVwaHFSDBMiNJrS7HaJx+LslPcAFc3YEWdAHXHD6XV2xMWjvyBiYVUV4k4HFOKWSoYjzuyapUQxaq4OjaUcHUgiFmtedzs5SoW4AqR07ktmFanoBqVHXJB7CXOPOACYoI64zgpxNJrSynFoh/I+/ugrwNJxABJT2hw+mfyfeG/sX3wJcf0iFFFHXDoZQ4kmPsSSlj0hnaCOOOFwfUZxvPjAB6w6vTAMwzBMf9M2IU4I8T7o/dKO+nj5pTCcdM9Z7VCLhTxc+/Iyl+c0CT020va4NX7o9rhCiJgQYqsQ4mcBfKX28DEAD7o5J8YdU6bJXBCUWEoHNxzQP3n47cQqaoaudI3KZIPpLbYMbfH0OOMMLX7Rwq4TSvGM+8QxXQJ1u0xkJpqej7LLJWzCiqakDoSoCXGtesS1W4hTesRViy3Fkl5kwdSf7PRSMMFRiaZ0csQloztW0OvSrn/ZSDqhR/tBdxnlis5xiFZR9m5QFvWE7Yhb12hKf444JYmkoo4fg6KE30nc60uIi6JQZAXtEZdJxJUFCqmYD2d3wqUjjkZ/RqTmcM8996z3KTAMwzBM1+EoxAkhbhNCHKn/qz28mT5m8e8VIcRZAF+AHvH4JR/ntZVsn3TYr/7cVod92nJcIcT/FEJIANXa/v8HwC4ATwN4p5SSl0mHCO0zEDRSxk1/uDrKyneHXHfGHirE1Ve4Kj3iStwjjuk8t+2+rSleJhPP4Lbdt63TGfU2tPhFIyedCK14xjAhovSIS483Pd8vxcgwoI64sKIpy9XeF+JW2t0jLuleiIvH4kjE9HOQkJEQOs0shBxNuVw0kh5G06O2+yk9JSvRGiuytD+cjRAnhFDmb3Mt4il9R1OG1efQqkfcekZTrrUWO62gSSTDWnN88rRY8OeIi6BQZIXqiIujRK6ptJ/PMTIex/rMEXfttde23olhGIZh+ozm2Z/KOICd5GsJIG56zI4ygH8A8Ac+zouqI07qR/0u0O3depjHXQJwBkAKRhzl0wB+XUr5otNJCCFuBXArAExNTWHfvn1OuzMAlorGCt2ZsyuB3rMTpRONbVmSjsfKLxuXyfcPfB8rAywaeeXomaPG9vNHse/YPpxYMX4HL594ueXvc2Ul2O+cYcwMYQi7B3bj+6vfbzx208hNGDo2hH3H9q3fifUoq0WjaPCv3/tXDMYGHfbWKZNC0OM/eBwn0ieU5/nvnlkPjs8fb2wfee4ItJfUQqYsGPcj3/7et3E0fbRTp9ZzPL/0fGP79InT2Le6z3F/u7956tKqyAoefexRxES70/Xbx6kF497y8LNPo3Asrjx/dMkoBM/MZV2Ngy8svmAc/9VT2Jdt/Zo6CZlABbo4+M1vfdPV+N1LnFpUi9rH55cDfbb8aP5Hje0zR89g34L1sfJLxu/5Bwd+gMLh6Cw4OThniMnVvP1ndVozfuavf/v7uHRjvGmf+t/9kbkjjceOv3Qc+05ZH9PM8RwZs48daTnO2HHZq4cxWdv+4SunMLu2D4nyMt5ce6w6fwTfeewxwGM0oV+OnjKun6Mv/BD7Fg477G1wYta4lxq1EOJOyo048NzzmM4faXrOibnFucb2cy88h32z+zy9vld47qhxbzp/5iSW8ytArUWGLDvXDawoLWRxVW27uLJo+/rZ7Gxj+0cv/ch2XOkl9u/fb/nz8v09w/Qf/HfPMAathLi/BrCvti0APArgLICfdniNBmAZwItSysgul5JSfhjAhwFACDEK4CcAfBLAd4QQfyql/G2H194D4B4AuO666+SePXvaf8I9jqZJ/Na3voaqJrFaBt5w/VuQSTZP5tyw/8x+4JS+PTk+Caf3/4F9D+BHr+oT7l2X7sKenfb7Mtb8z6/+z0anyDdd+ybsntqN6qtV/N2+vwMADG8YdvwdAMC+ffta7sMwXjn8zGF8/2lDiPv5t/48Lpq4aB3PqHep/G1FX6oD4J1ve6cr98tffe2vcHxWL6Bd/prLce2UunKW/+6Z9eATX/wEUDPQ3PDGG7B9dLvy/F997a8ahc5Lr74Ur93y2k6fYs9w6MAhIKtvX3j+hdhz9R7H/Z3+5pN/m2y4td781jcHctitN9r3HkV9PeDbr38jdmxUha/jZ9ew94nH9H3jaVfj4Hee+I4++wJw2UWXYc+lrV9TZ+gfh1Ao6Ddqr33Da7F5cLPr13Y7VU1i5eGvKo8tlyTe/Ja3IhH3J+Z+6dEvATVt73VXvQ57zt1jud9Xv/1VPPvKswCA8y4+D3t2We/Xi2QPzABPPQ0AOO+cKezZc43lfv944im8mNV7707vugR7XrOtaZ/63/3nv/75xlLY1139OrzlnLe4Opfll5fxj//yjwCADZMbsOcte7z9MHVe/a9ATWu67NrrcdkFewApgX8dAUo5xLUC9rz2CmC4M38ff3TgWwD0BaB73vRaXLrV3n1J+cwDnwFq5sMRkxC3JlP4k8r7Mb11B/bsucTT+bx06CV8ff/XAQCT2yex59o9nl7fKzz32EvA87rouWvnuRCG7o7RoVHP96WHcs8CNY1tOBXD9TavP/7D43joXx8CAGzethl7Xuft+3QrVu8X398zTP/Bf/cMY+AoxEkpXwXQyGEQQhwDcEZK+a02nxddujgAIGezX33m6tamZD6uHZ6OK6VcBvB/hBDfgd5f7sNCiO9KKf3EcjIWxGICkyNpnFrSCwWzy8WmwoVbvPSI42jK4Fj1fBhKkbieiMRvML0HjaAD1Lgpxj0VrYKKpq+Oj4lYU+SnHRxNyXQji0WjT9B4ZrzpeSWeK2J9n8KGRlMG6REH6PGUdSGuVC31tBC3QnplDVtEU452sEccYBqLg0T7dSHZtRI0U9s7TQJzK0VsHfP2PtVZKrnrERflsWJJiaa0LydMjhjXlpdoynqUvRtCu35pNGW9R5wQejzlmUP619lXOybEKdGUg+6jKZXe3ESIK8cHcUf+l/CA9mb8nJ8ecX3SH7VIoikzyRhK1TIA3RHn53MnljLGmbhm/zegRNlGZG68davb7jEMwzAM0z94WgoopdwppXx9u06GQPu3TTvsV3/u1DofFwAgpZyB0RPv33t5LdOayVHSJy7nf6JF+zR4EeKinIffTuiEcDSlr+akvR/oxJthOslScUn5mvbVYNxTrBqFhXQ8DeEytim0vi4MExLFarEhaCREwrJPURT7uLQL89gQBFoA7eU+ZlJKRYiz6hE3kk400u9WihVUqs3xcmboGOqlRxwApBPG76ZYcRZLeo2F1ZLl46eX/H/m0HuHsbS9EKcIFxGbQyy56BEHqHO32RZCnLJwz0OPODpXC7SoJ581tus94gBg4lxje/Go/+N7QEqpCHETg+4FIPo+Ukfc4sZr8ICmB20uF3wIccn+EOIKFeM9yyTjKGp0QYm7HsgUKsQlNIcecYno3VucPHmy9U4MwzAM02d4EuKEEEeEEN/zsP93hBAvez8tPI9GyBUutzl2DMDFtS9/6OagUso5APNOx61xmZfjmpip/b/Lx2sZB6bIqsogjdbp5IHe9FpBJx10tTHjnly5eWJNJ9hRmWwwvQdd1Q6wEOcXWvjKeChS0H3ZEcd0A9lCtrE9lh6zFJUVl0vEiuthQx1xQR1s1Gnby0JcvlxFtWbRyiRjSFrEI8ZiAqMZ4+ddLlSa9jFDr8VW97Zm6FhcdHBs9CLzK9Y/z5ll/z+nWyEuig6XOopba8D+b3uzT0dcPUHDDcq9RJBFPWsWjjgAGO+8EJcvV1GqCfDpRMx1OwZNaur7SOygI2tGL71lH464fvnsKxBHXDoOlKQx/qYSQYU4+78BReiMyPu7d+/e9T4FhmEYhuk6vIbj7wSww8P+59Re4wkpZQ7Ak7Uv32Wz2+sB1Gc/j3g4/GNOxxVCbIMh0nk5bp3zav+zzSdkpqgjLsAE2m80ZZRX/7WLslZuCJgCojHJoBNsunKTYToJR1OGAy18ZTwUKRQXRjVaxV+mN6FjwkRmwnKfKK5abxdhOuKoEEcFvl4jR0S14bS9k2jMYzwljU8PEk0ZOUfcivW14ndBn5TSlxAXlcJ6HdeOOCLEzbZIM6EJGl6iKRV3vd9FPZUiUB/PRRxIk35sEzuN7eyr6ASLPmMpV8urkLW1zEOIgcp3mdWTiEMXmdxG3lL65bOvWDYccUPxKopkQY6fz7E4EdiSmv1nVxSjbD/2sY+t9ykwDMMwTNfhr0u1e5IAWuepWPP52v+/IISwCpj+7dr/T0kpD/s47ruFEFdbPP9bAAT0WMrH6BNCCMeeekKICwHcUvvyOx7OiXHB1CiZzIXkiGslxNFJBzvivLNaMiZqw6lhxIQ+5ER5lTDTO5ijKal7k3EPLdx6KVLQVew8vjLdgNIfLj1uuU+/xHOFARXigjriohJNmSORcKMWsZR1PAtxQXrEJaLbI87OEXfa5zyiUC2gVCump2IpRxd4lBfz0Wty1EGIo464WYdFlGWt3Lj2YiLmydVJhTjf9xJ5Y+zHwARA3dBKNGVnhLjsmiHY+I6llKqjW8gKtooFAP6EuCgLy5RCxXDEDcbKihAXtEdcUjo44vpE6GQYhmGYfqdtQpwQYhTAJIDFVvva8FkArwIYAfAVIcRlteOOCCH+BMD7avv9nsX3lrV/ey2O+2UA34f+s39JCPGG2mvSQogPA/iN2n4flVKaly19WgjxaSHEm4QQjbt+IcS4EOKXAHwLwACAHIBP+fiZGQeUHnEBhDjaI44W1Kygk2guFHtHmRAmjdWtmXgGcaGv0yxWiyhXe7eoxvQu7IgLB7+OOLovO+KYboCOCXZCHC8kcQ91rqVjwRxxiZghWvW2EOfcH65OJ4U4JZoywo646TEyj/DZI87shnPqiRrlsWIpb7yvTo6tyRF3PeKoG244Oey61ywQUsw1FeJofzhgXaIpl9bcOQ7N2PWHq3OuOKMf34cQF2VhmUKjKQdEBaWAjrhE2qg1pByEuCg64hiGYRiGaaaVw+sqAK8xPTwghPh3Ti8DMA5dKIsD+Fc/JyalzAshfhJ6PORuAM8JIZYBDEMX0SSA35NSft3jcaUQ4mcAfBt6jOQTQogVABkY78dfSCk/Z/HyQQC/CODXAWhCiCUYP2+d0wD+jZTyhJfzYloTVjSl3x5xUV791y6ow4jGzAghMJQcavTkWi2vYjw+3unTY/qYqlZtEt64R5w/qIjmqUdcIrrFX6Y3oT3ixjPjlvsMJfrDFRAGYUZTKo64Hl68o0RTdokQR9/bqC2KWFg1fp7LpsdwsibA+XXEuY2lBNQ5RtTGCrfRlBuHUojHBKqaxFK+jEK5atnvzG8sJRDSoh67/nAAME66ciydAKoVIO5YQgmM32hKRYirNI8b54pZfBd6jzhNk4jF3Aue/SIUFSuGgDkQqyAX0BFHhbhk0xpvgyjWHJ588snWOzEMwzBMn9HqLvKnAHzE9NgogL9ycWwBoATgEz7OCwAgpXxGCHEFgDsBvAfANgALAH4A4FNSSj893CClPCGEeA2A34UuGO6E7mJ7GsCfSym/YPPSTwL4EYB3ALgAwBT0+M0zAJ4F8BCA/yWlXLJ5PRMAJZqyRZ8BJ7z0iFOiKcvsiPMKnRCaG68PJ4cbwsdKecW26Mkw7SBXyjX6aNRhIc4ftABMI85aQQvz+SqPr4x37j8wg7sePoyT2Tymxwdw+40X45Zrtvk+Ho2mnEjb9IhLcnyUW6gjLmg0Je0R18uOuJUiccQ59IgbXSdHXPSiKY1r8LLpUXzzR7ojyG+yhhchLtqOOHdCXCwmsGk41VhAOb9SxDkTzYsg6cK94eRw0/NOhNIjTommNDniUoPA8BSwcgaQVWB5Ro2rbAPZfAjRlBYLFnYlZoEqoElgpVTBaMa9yKd89lWidT1TwnbEJTPG+5bmaEqGYRiG6XtaCXFHoTvH6rwNQBnAEw6v0QAsA3gOwN967N/WhJTyNIDbav/cvqbl8i4p5TKA36/9c3vc5wE8D+CP3b6GCY8pGm8SwBHnRYjjaMpgOK1wHUoNAbVfBU84mE5jjqUEOJrSL9TN5sURR8dXdsQxXrn/wAzuvO8Q8rWi2Uw2jzvvOwQAvsU46oizK7Jzjzj3KNGUAR1xVIijx+01aI84t4645Q72iOvl99aKBdIj7vLp0ca232SNpRIR4lLuhbiojRVZD46tyZFM4/2ezVkLcUo0ZcqbEDcQJ3M1v4t68g6OOECPp1zRRVwsHm2/EEejKb044srO0ZTnxeca28v5sjchLtEfn32FsvG+pUU5uBBHoylhP74OJAYQEzFoUkOxWkRFqyiRzL3IddddByll6x0ZhmEYpo9w/HSXUv4NgL+pfy2E0ACclVK+vd0nxjBmxgeTSMVjKFU15IoVrBYrGEp7v0FVoilb9IiLYkxEJ6EOI9ojDlBXvK6UV8AwncRSiGNHnC/8xs/RfaPmwmDaz10PH26IcHXy5SrueviwfyGOjAsTGWtHnFJc5/sCR4qaMTYEdcQp0ZQ97IhrR4+4ilZpvCcCwnOxOJQeW13KwqpR+N61eRipRAylioaVYgUrxQqGPc4jvDjiBpKkp1aExopCudqI70vGBQYsoiYpm0dIoomNAKoISElv0ZSJWKIhYFS0ij8Bw6lHHABM7ARO/EDfzr7q7dg+yK6F4YirCUrxFFAT2HeI2cbzS/kyzrH+mLMkHU8jLuKoyirKWhnlahnJuHshr1eg0ZRplFEky7v9/LzUEZdxiKYUQmAwMdiYE69V1jCaGrXdn2EYhmGY3iTmcf9fBvAbXl4ghOA7CCYUhBDqZM6h6bcT7IjrHFRgM69wjXJkD9P90GJaHRbi/EHHRhoR1QpFiItY8ZdpPyez1p/Jdo+7gQpx4+lxy31ojzj+7HKmXY646Ahx9kVdRYhbc/55zWOwEO77PgHq7yZyPeJINOXm4TS2kH7Tp5e8f+7QMaJlNGVEx4plUyxlq+ttkszd5mxaCwRxxAkhFDHZ1zWs9Igbb36eOuAWOyHEEcehQ/SnGaUlgKwJStO7G49Na6eBWiy7m8hbSl0oqhMlcZlSJAt8MiE44lLpAWi1sKaUqABa1XbffnEdMgzDMEw/40mIk1L+jZTy3lb7CZ0fE0L8A4CTvs+OYUzQPnF++zvQXHs6SbaCb4iD4RRNSVe80okjw3QCjqYMD1r08h1NGbHiL9N+pset4/fsHnfDYsFwRdgJcdwjzj1+3bJWRCeakvaIC8cRFySWElCjKaPkTi6Uq42efMm4wOhAIvA8gt4ntBLiohpjm3XZH67OpItFlMrCPY894gB1EZCvhZNOPeIAPZqyzuJR78f3yKKH6E8KnU+N1h1xW64EaosfB+UaJqDv4yby1kxUr2kK7RGXQgnFgEJcIh5DEcbvsFqyf9+i9v5+9KMfXe9TYBiGYZiuw6sjzhEhxOVCiD8BcALAQwB+FoD/igjDmJgiK1l9C3HsiOsYTtGUQ6lorhRmegMrIa6kldiZ5QOl2J7wGU3J7zvjkdtvvBiJmOrEyCRjuP3Gi30fkzplJ9IcTRkUKpgFjaakkWC97IhbKRrnHlY0JR0/fQlx1BEXoX6dNJZy41AaQojA8wilR1wrIc7kHtJkc8+uXmTJoxC3mbznczZCnDJfSHmLpgTU697X/USrHnETO43tDkRTLuWNa3fcbzRlvUfcyBZgw3mNx8+txVN6dcQB/bEQpUCiKVOyrAhxqZj3zzEhBAog0coF+/uGqKXF7N27d71PgWEYhmG6jsBCnBBioxDi14UQTwI4CODDALYCqAB4GMAHg34PhqlDJ9B2fQZawT3iOgdd4WqeWHOPOGY9sYqmBDie0g9KLJoHRxxdwR4lFwbTGW65Zhtes10thP/Wuy7y3R8OABaLxBGXGbfcJ2or1ttJuxxxvSzEUUfccEhCXGBHXET7dS6sGNffxmG9EK5EU/oR4miPuJSzEBePxYMLRF0IjUoNzREXIJoSCGFhTz5rbFv2iFvHaEoPjjjFWUiFOCIk7hBnAPgT4miSTFTnxUWTIy5oNCUAlIQhxJWK7hxxNMGnV5menl7vU2AYhmGYrsNjJ2MdIUQCwM0AfhHAj9eOI6CHjn8FwBcAPCiltK50MoxPJgNGykgplYlDK0dcJp6BgICERLFaRFWrIh5zbkrOGCi9Chx6xNEJOOOfh448hLv3343Tq6exZWgLbtt9G246/6b1Pq2uxMoRB+ixU5ODk509mXXi/gMzuOvhwziZzWN6fAC333ixLxFDiab00COOinZRKVAynSWTVG9jL592Low7UawWG4JGQiRs49HMLhcppeeeXP0CR1M246tHnAchjl6fbqFjcS+/t2Zof7iNw/r1t2WMOOLa3CMO0IXR+u9ntbzacgFgL0CjKd24tdT+3jY94kKMpgzeI87CETe6DYglAK0CrM4CpVUg5TyHDIISTTng3oWlOAs1vRcchs1CHDvinKCOuCQqqiPOp7O7SBxxFSdHHBU6I7DQ59SpU+t9CgzDMAzTdXhyxAkhrhNCfAbAKQBfBPBe6CLcd8hu/1ZK+XcswjHtYGqETKBtVlU6UagWGtEw6XgaiZizFi2E4HjKADj1iKMT7ahO5jrJQ0cewt7H9+LU6ilISJxaPYW9j+/FQ0ceWu9T60pshbg+ccTdf2AGv/tPBzGTzUMCmMnmced9h3D/gRnPx6IimpdiO42x5B5xjB/mV9TrZibr/zM6W8g2tsfSY7biWiKWaFznmtT4vsCGqlZFRdNFJwHR8n6rFbQA2tOOuCIV4tw54lr1cqILzLhHnAEdHzYN6dfPVJiOOBdCXNSi5gDv0ZSKI84mzUSJVPQRTUnF5Lb0iIvFgbHtxtfZY96/h0uklKZoSp894myjKf074qKeFFOuaqjWBMyYAOLVYkiOOON1FbeOuIiMFwzDMAzDqLQU4oQQW4UQvyOEeA7A9wH8GoCNAJ4FcAeAnVLKPW09S4apEbS3A72pdbtqmBY1ojjpaCeOPeKoI46jKQNz9/67mwpohWoBd++/e53OqLuhxTTqtOgXIe6uhw+jWFH71eTLVdz18GHPx6LXnZci8ECcFzkwwTD3GzoZRIgj4vxExro/XB3uE9eakqb2hwvqGqTjdF3g60VyBdIjLm0vxI1kEqi/ZblipVEctiJoNCUVMSLbI264WYg74yPifrlo3COMp8db7m920EYBKuCMuukRR4S4+ZWi5bWsRFP6cMQpEaB+xORWPeKAjsVTrpaqKFf19yiTjCGTdJ/EYtsjbsIQ4nbEdEfcct77OKpczxFwbJmh98WZZByiWlQccWFEU7oV4qLw/u7evXu9T4FhGIZhug5HIU4I8TCAYwA+AeBSAMcB/DGAq6SUV0sp/0RKebz9p8kwOlOjdFWl94mWl/5wVvtxsdgbStSMKZqSfs2r/oJzevW0p8f7HVp03z5irHKmRYwoYydY+BEyaOGWHXFMp6hUNZxdU2P0TmX9u3mU/nAtCuzKAp0IFMvaAY049BvnRem3aMpYTChCnZMrLswecVEai9UecbVoyoAL+pZKxiKe0dRoy/0j6Ygj4+64CyEunYg3XF2aBM6uNv/9OvWUdkOgHnHlPFB/TTxlHzk5ToW4o96+hwey5P2dcBH9SVEETU3T4zQHNrQlmjKKn30F0h8uk4wDlUIo0ZQlYYw71ZL9fXbUevA99dRT630KDMMwDNN1tHLEvau2z+cBvFVKuVNKeaeU8tn2nxrDNDNpWskqpf0KYSvoJLhVf7g6XHDzj1M0JTviwmXL0BZPj/c7dkJcvzjipseti7V2jztBV59Tca0VSk+XCLkwmM5wdrUE8y3AyaVwHHGthLgoFtfDJsz+cEB0oilXiBA37BBNCQBjg+76xClCXDKYEBelaEqlR1wtmpL2mp7NWbuz7MhX8o3rOhlLuhI9o7iYz2s0JWCKp7ToE6f0lA7YI87zNaz0h9sA2Ll3iZiFbPsccdk17+8voEdaNjnihrcAsRgwvgMQurNuqziLNEq+hLioCUVmFCEuEQMqRZRDEOLKMeN1VQdHXNTuLW699db1PgWGYRiG6Trc9oj7SQAfFEL8mBDCfT4Cw4TMaCaBTFK/bPPlqtJrww1+hDgawxGVSXQnaJoQmoQ4GlVJBTvGH7ftvk1xDAB63NRtu29bpzPqbmg0pSLEFftDiPutd13Y9NhAMo7bb7zY87Ho6nMaN9kKpadLlcdWxhuzFn1iA0VTkh5x45lxx305mrI1YQtx9POtV4W4clVDvlbojQlgKOU8paJFeEchrhzQEUfdyUEWRRy8F/jUFcDecf3/g/f6P1YIzBPn1aaaIy6TjGOiJnBWNam45lph7g/nJm6VziGiUFgH/Alxm0dUAdRMUEecEk3p1RGn9IdziCXuUDQlFeK89IfLV/KoSH1enNE0pABgZEp/Mp4Exs5p7LtdzLbsPWlF1HuYFcpGNGXawhHn97OsEjNeV3VY1Bu19/dzn/vcep8CwzAMw3QdrYS4nwLwZQBpAL8A4CEAp4QQnxFCvKndJ8cwZoQQSn8Hr/GUtGDmNpqSe8T5o1AtNCaEqViqafIylIrWqr/15qbzb8I7d7xTeezO192Jm86/aZ3OqHuhq9oTsYTiGuwXR9z1F2xWvk4lYvjE+67ELdds83wspeDuwRGXjCUhoBc4KlrFf9+nLiv+Mp1hzqKAfjJb8OyUr0OjKSfSzj3iolYsc+L+AzO4/pOP4rw7HsL1n3wU9x+YcfW6sKMp6TF6NZpylSweG04nWgo5roU4skiMLnBwi9IjTvMpxB28F3jwQ8DScQBS///BD63reDyfo9GUxvVD5xGnPcwjqBDnpj8cED2HCwBk896FoskR4z2fs+jN55Sg4QbFEedZiCOOuMEN9vuN7zS22xlNmfcXTam0A6g7PUe2GjsQR9+54ow/R1zEF6EUK4YjLl1zxJVCcMRVhHFvrDlEU0bRQcswDMMwjIqjECel/LKU8n0ApgHcBuAAgE0Afg3Ad4QQR4QQfyiEuLz9p8owOlMjajylFxRHXMKlI45vin2hxMykmmNmaPQMR1OGw9TQlPL1m7bxegkrzMU02uelX4S4eZOIMTWa9iXCAWoMlJcisBBCjaf005uoC4u/TGeYt3BV5MtVxU3gBbPbxQnqcolyZPX9B2Zwxz8dxEw2DwlgJpvHnfcdciXGhe2IS8SMGMdedcS57Q9Xx48QF7hHnF9H3CMf13ttUcp5/fF1YmG1uUccoApxXuYR9P7ATX84IJo9tcKOpqzKauM+Ii7iga/hYNGUTo64ncZ29lU0ZSOHhF9HXFMsJQAMk3nBhvMamzvELJbyZc8LV6LeroE64qx6xPl2xJF7Y0chLoIOWoZhGIZhVFxFU0opF6SUn5FSXgfgCgD/BcBpADsB3AngINl9R9gnyTAU2t/Ba6N17hHXOejqVquCBRXieLIRDmcLZ5WvaWGZMWgS4tJEiOuTaMo5k4hxMltAparZ7O0MXX1OhTU3UOHO8yp2oCuLv0xnsHLEAf77xC0WiCMu4+yIi6LLxYq7Hj6MQkUdF/LlKu56+HDL14btiKPRlL3qiFsuGAX2kRb94YDOCXGB+mvVWTrh7fE2I6W07BEHAFt8OuJoH8lWYn0dpbBeicZYsRwwmtJ8/5HXjOt3KDnkKvLTTDBHnMtoysENQH1hYWlFFfBCJLtmXLfjHhxxlkLcCOkTPaEKcRVNYq1kOMDcoDjiIjgnLpbNjriSIsT5/SzTiIAny/bXZ9TuLWZm3DnoGYZhGKafcNsjroGU8odSyt8BsB3AjwP4AoD6HbUA8IwQYr8Q4v8TQlwa3qkyjI7flawA94jrJHTlsFXj9YHEQCOWLl/J+4+lYxrQQjKgFo0YA3MxrR8dcWYRo6pJTwVJShDnS2BHXJcVf5nOYS7m1jmZ9Xcd03GhVexc1OO56tj13HPTiy9sRxwtgPaqI25FccS1FuJGXQpxVDwbSAZ0xPkZhwGl/5Srx9vMcr6CSi2ebzid0N0tNabGyDxiyV80pVshjo4VefOiET+scxSzlFJxbI26dcTRtgIOQpyfWEpA7U8bKJrSSYgTQnXFtSmeUnHEuXx/ARdCHHHEnSvOAFAXB7ghisIypVhpdsSViC7sv0ccWaTmMA5E7d7iqaeeWu9TYBiGYZiuw7MQV0dKqUkpH5ZS/l8AtgD4FQCPQxfjXgPgYwCeFUL8MIwTZZg6U6P28SatoKv33PaIU2JlInBT3CmUXgUW0ZRCCHbFhYxZiGNHnDXmgns/CnHmaEoAOH7WX5FQccR57E+kxEn5ccR1WfGX6RzzxO0ymDKK7Kd8OuK8CHH9Eh81PW4t6tg9TqGCTtiOuF4V4mg05XDamyNu2ckRV+6CaMobPgLETaJBIq0/vg7MK7GU6vXn1xHnp0dcqP0kuyCKea1UbQicmWRMETid2DxM527qNVbQjN+B1cI9NwRydVJHnFOPOAAYP9fYzh719n1cshhqNCV1xO1sbO4QswCcBX4rou6IKxBHXCYZCy2aUnHEOSzqjVrs9Xvf+971PgWGYRiG6Tp8C3EUKeWylPIeKeWbAVwE4D8DOAZdlLs4jO/BMHWoI27WoyOOCml+oinZEeceN43Xh1LRiuBYb8zRlOyIs8ZcTKMr2/s1mhIATiz6m/QrPeK8RlMGjUS74SOAMBUC4+tX/GU6xxxZiHPFNuNveMaFW8uKbCHb2J5IO0dTRrHvkxW333gxzCFxA8k4br+x9a09jY9Mx4I74hQhrtqbQtxKsft7xBWqBc99owAAV70fuODd6mO7f1F/fB2wi6UE1AV9XiLul0rBHHGBHURdEMXspz8coLYVMC+izEvjZ7JauOcGei/hea625jKaEgAmiBC3+Kq37+OSpXyY0ZSkRxyJptwu5iCgYcljT9WoL04tVGg0ZRyoFFEKJZqSOuLsx5xQhXuGYRiGYbqSUIQ4ipTyJSnlf5JSngfgBgD/O+zvwfQ3kyM0mtJ/jzi66syJqK1O6xTUWWQnxNGVr9RBx/hjsag64vrF3eUVjqZU3UR1ji/6EzCog8JzNGXQHnFXvR8YmW5+bJ2Kv0znoGLy1ecYRXG/0ZR0/BzPjDvuG7X4KDtuuWYbknFVivvozZfilmu2tXwtR1M2kyMxcMNd1CMuHosjETPOx/f7axYxRqet9+sACyvUEadef2rEvfvxgi7Usep9bEWoc4guiGJWYxPdixKTpEfc7HJREXuVaMqkv2jKQPcSSo+4Fo64bo6mLFsJcVuNHTKjwOBGAEBalLEFi54dcVGfExfLNJoyBlnJqz3iYv6EOEmEYuEgFPfLvQXDMAzD9DOhC3EUKeVjUspfbuf3YPoPZSWrx2hKPz3i2BHnDyqs2U2sFSGuxEJcENbKa03XJ3V4MAZmIW4gMYCE0IuQhWpBcXJElTmLsdOPI05KGcgRl06oTgzPlPPAyin1seEp632ZSEHF5Ku3jze2T/lwxBWrxcb4mRCJlvFo/RJNuVKsoFRV3VGXTbtzAtFxlKMpdZY99ojzI8S5XWRmRhEy/IzFALA8o37dJseQG+ZXjetvk0mI20J6xJ320CPOfO/ghlDds10QxezXETecTmCgFmNZrGjIEXeoEk0ZgiPOc59Dtz3iAFM0ZXuu78W1MBxxUk8LGNyk7mSKp/QsxEXcDa5GU8ZRqRQha0JcQsQRj7mLYjWjCnEOjriI3Vt89rOfXe9TYBiGYZiuo61CHMO0g0llJWvRU4QO94jrHHRCaDexptGU7IgLhtkNB6gxSoyBOZpSCIHRdH+54qwccSd89IgraaTYHkshJrzdVgzEjYUOvnoTnT4EaBX1sewx78dheopipdooIMZjApdtNf5+T/oQ4uiihbH0GIQwBzKqKHFzESiW2TFr4RY6Mufu5w3bEUeFuF5dLEGjKUdDjKak96Z+HHFASH3ilk+qX7dJqHADdcRtMvWI2zCYajg9lwsV5EtVuMFPj7hQHS5WUczJgY5GMdPrcNSDECeEUOMpSWsB6ogLpUdcEEdcqx5xHYmmNN7jiSA94oYngZjpnozEU+6InQkkxAWOWu1CChXqiIujRK6lVMz978KMTLpzxNH3N1/JQ5Oa7b69wK233rrep8AwDMMwXQcLcUzPMZxOYCilT0RLFc3TJIJOGnw54sy9GRhblAmhi2jKKBczO8FiwUKIK7IQZ4XVqnYlnrIP+sTNr4TTI44WvKi7zS2BHXEz+5sfYyEu8syb+j9Njxuf06eXC6hUvRWv6JgwkWnhiED/LNCZtegleWTO3aIZKsSF4YiLXDRlunuiKYEQ+nUCzULcOjrinHrExWJCibk/7TKe0k+PuFAdLle9X40aBIB3/UFHo5jV/mXehInNxJlI+8Qp0ZQ284VWUEdnvuq1R5xPR9zScUBzJ+K6RUqpRFOOBRHiRrY077TBEOLOFWewHDCa0lc/yS6GOuLSiZi6oCSAECfIuBxzWOgQE7FIJfG0WtTEMAzDMP0IC3FMTzJlcsW5RYmmTLgT4pRJR4QLbmHjVYiLuiPu/gMzuP6Tj+K8Ox7C9Z98FPcfmGn9Ig+cLZxteoyFOGto0b2+qr2f+sSVKlqj0BMTQH2efGq5gFLFm4BBhThaCHNL4B5xM081P7Z03PtxmJ6C9ofbPJJGJhlvxM9p0lpAckLpD+fC6aK4XCIYz1XH6n18ed6dmEBda2E74npViFvpQDSlXyGOCp2+HHGFZYDc9wGoCRXr4+hYWLXvEQeYYu7dCnHknmos5U6IC909a45xn7oi+DE94DeaEoDiiKNjuOKICyGa0tO9hJSmHnEthLjUIDA0qW9rleY41oCsFCuoaLq4NZiKI51wH4VIe8QNaxowbCHETahCnFdHXCKWaIznErLnhSIzRbMjLqwFJcQRF2ux0CFq8ZQMwzAMw6iwEMf0JJM+JtCAWjBz7YhLRmdlWiehwppd1IxSoChFd7Jx/4EZ3HnfIcxk85AAZrJ53HnfoVDFOHbEuccqXoqKxVEX4miBcsNQGlM1Z4CUwKklb2McXS3stT+c+TW+XBgnLRxxyyeBSm9G1zHumM/R2Dn9fmB63LiWvMZTWonzTvRLoayroinjvR9NmSNCnBtH3AiJr8wVKqhq1u4Tem/qZxwG1EURnntsAUDuVPNj1RKwctrX+QRFcc0ONxfQaZ84X0KcD0dc4MV8xRxg7v179kiwY3pEcWt5FeKIC5FGUxYk6RHnN5rS7/VbWgHqwn5iQI/6bEUb4ynp+zvu8f2lCyBH7RxxpEfcdjGr9K10S6hxq11GsyMupAUl5LqKa87jTb9EXzMMwzBMv8JCHNOTqI4498VbekPrukccO+J8sUJW7fa7I+6uhw8jX1bja/LlKu56+HBo38PKEUeLy4xBy2jKiAtx8zmjsLB5JI1zJowCwXGPfeJoAdhPkSJQX6J8Flh4Sd+OJYDBTbUnJLB8wvO5ML3D3IrqiAOA6THjOj655E3UpT3ixjPjLffvl0LZnIUj7pX5FWg2ghBF6R8ZQjQldcRVzH0he4Sc4ohrXWSPx4TinKPRlnWklIoDKJQecX6EODtn0DrFU6o94qwccSSa0sV4UagUGu9LMpZ0/T6b3bOBovyyFm7vDgtx1EHlOZpyhDjiVqwdcb6jKYkA7WnRpJf+cHWImIXFo+6/lwvUWEpv46b3aMpZz444QB1jouYIL5QNR1w6GUdR+RzzL8TRaMp4i/E1SkLne97znvU+BYZhGIbpOliIY3oSOoH2EkGlRFP66BEXtQlHO6Fiht3Eul+KmXbuDK+uDScsHXGlpcj1bwhKVasqPeAaQly6f3rEza0YRcdNwyls32AsNvDaJ05xxPmJpqTFM699XU4eMLanrgA2XmB8zX3iIo05mhKA0ifO69hKoykn0q17xEWpUOaE1f1VoazhlIsFUO2MpuxZR1zRWzQl0DqeslgtQkL/nE/GkkjE3B3XTOB+neb+cHWy6yTErdr3iAOALVSIc3E9m91wbnsfJePJxrVblVVFoPaMVezyOgpx3h1xpEccec8LWnBHHJ2reYqm9NIfrg7tExfy9Z0lPfgmPAqddAHksCaB4anmnYa3QKuNxxNiBeXV5rlDK6L8+VesGIsmM4kYSlXjek/7dBsDgEgZ12dCc65bRKnu8OCDD673KTAMwzBM18FCHNOT0MmcW0ecJjVlwkCdbk5Q5xxHU7qHOtxsHXGp/nDE0QKxm8f9YOWIq2iVyE2Sg5Ir5RpFy+HkcKNA1reOuGGTIy6AEEcLuW5R4qS8OuJof7htu4HxHcbXLMRFmnnqiAshmtJr5JzilA/qculi6P1VjOgOR+Zaf14Xw+qtY3GMXu0RRx1tYQlxYfSHAwKOxYC9ELcOjrhyVe2DOm7hLPKarLFU8t4frg6dRwRadGb1ubaOQtyoRyGOOuJmbXrE+XXEUbHfkxDnpT9cnU5FU3oU4podcVubd4rFUB417pWG1rynB5g//6JEkTjiMomY4ohL+1hsVidGxoCEB0dcry9Svfnmm9f7FBiGYRim62AhjulJ/ERTmqN74jF3DbBpYYOFOPfQCaHdClclmtLcgD5C3H7jxUoREwAGknHcfuPFoX0PKyEO4D5xZqxiKYH+EuLMsX7bJ6gjzn80ZdAecZ7j0Kgjbtu1LMT1EdQRt8nSEefN0UMdxROZ1sVYs8vFV5RfD0CL5ZdPG+Olmz5x7XTE9a4Q5y2aEuicEBc8mpIIcZsvMbbXwRG3SNxwG4ZSiJtvwGCeR7T+ef30h6szlAipsG4pxL2iN3jtEEo0ZZAecW0U4kpaCZrUHPYm5H044toaTWlcu1YCsh2laqnhZE1IiQEpgRELRxwAOb7T+B4FH0JcWMJyuzl4L/CpK4C94/r/B+9t+RLaI24gIUFHhpSPxWZ1Ymn3jjhznG0v85WvfGW9T4FhGIZhug4W4piexOsEGjD1h3PphgPUVcL5St795K6PqWpV5f12JcRF2BF3yzXblIiZeEzgE++7Erdcsy2072EVTQmwEGeGCnHj6fHGdl9FU1IRw+yIO9vZaEpaPPO80IE64qbNjjiLCC8mMijRlDVH3NYx/444u3HBiSjHc9Wh8XFv3LWxse3VEcfRlHovtxUSTTmc7i5HnOIoChpNueMNxvY6OOLoYpONQ9bX3hYyXrjpERdEiKPCRaDCulU0ZXFJjVdsM4GiKUdJjzgyhhdk8GhKIYS/eEo/PeLaGU255k/oNLvhBAAMW/SIAxDfdH5je1PJxsnqQE989h28F3jwQ7W/Gan//+CHWopxBRJNOSDKKBMNP4izO0GiKZPSuW6hCJ2VLhY6GYZhGIbxBQtxTE8yRSZzsy4dcYoQl3QvxMVjcaXA7CnypE+hotpQcsjWfTiUik78hhNSSqyWjMldPCbw3qunQ/0etMfR1KCxCpYWmBm1mKYIcX3kiKOxfptGzD3ivAkYdDz0U2z37YhbPgnkTunbySFg88XsiOsj5k2uTgDYRh1xS+0X4uiCnih+fhXKVSzXHFyJmMDuHYZb5Mh865+XoylV8uUqqpruXEonYkgl3E3BOibEEbdH4GjKHW8yttfBEbewQvrDDVtfe8o8IleApjm7ykIT4oIIF8oCE6IQnH3Z/zG9nsKafyFuw2AKiZo7cSlfbriPwnDEAepiINdi8pqPaMrRbYCozWtWzgCl8MSoRZ/RlHTeNaxpgIgBQ5st901sNIS4aXlacYG5oSd6mH3994Gy6T6gnAce+bjjy2g05UCsgiLpBRlkQUk8bYwBLYW4CEd/MgzDMAzDQhzTo5jjTVpNoAF1VRldzeeG0CbRfYKb/nBA/zjilgsVFMjkrlTRlEJyGNBoyvPGzmts074mDEdTAub+WhlsGcs0olNnc0VPRRla7PJTBPa9yGFmv7E9/RogFmchro+wcsRtGk4jGdcv5OxaGWuliuVrrcgWso3tibS7YmxoLpcuxeycvWDS+Lxej2jKRMxwkJW1cs/15VvxEUsJrFOPOF/RlDPG9o7Xq49XOyucLqwSR9yw9bU3mEo0+vSVqxJn15xdlkF6xNFoytAccdOvMbY71CdO0ySWC/6FuFhMYNOw6oora2WUpX7MuIiHJib7csQNuHTExRPA+Hbj6xDvN7J5f9GUTf3hhjbr52mB2GDMEc4Vs1i2GFec6GpHXH4R+MpvASuz1s8vOUdxniaLeD7yT08pQlwwR5xxv5CSJcc42ShFU/ba5zTDMAzDdAIW4pieZCAVx2htAl3RWk+gAfVm1ks0JWDqE2deYcc0Qfu9OcXMKA2pS9FzFNSxcm2e8Bid5kS+km8U45KxJLYNG5GXSwUW4iiuoikjLsSp/bVSSMZj2DpmjHEzHq5N6pwI6ojzFIdGYym37db/HzvHeCx3Eqj0XnydHx468hDe/cV346q/uQrv/uK78dCRh9b7lNrKWqnScBin4jGMDuj3ArGYUOLmvPSJo47i8cy4q9d0dTEyBGZzxvs3OZrGjg2DjV5bM9k88iVnwT5sR1xMxJAQRmG5orkXWruBZUWIcxdLCQCjXoS45Dr1iCsXjF5bIg6MbQdGtupfS61l8TtsFEfckP21t8VDv2m7RTxuCKWnVrmgu68A3e107vXGcx0S4nLFSkM/GE4nkIh7LyPUHcyAvvCHzheGkkMQormfn1t8OeL89IgD2hZPueQzmpLet45oEhixjqUEAEwQIS52xnJccaIr3eBSAk//A/CZ64An/9J+P3qfaOL+AzOYIfcNudVVlEJyxKWSCRQl+X06CMU904PPBffcc896nwLDMAzDdB0sxDE9y5SHCTSg3sx6dcQpMRwRLLiFjTIhZEec0pS+zozHCEAnaH+4icyEUiRiR5yKq2jKiPeImydFyvrqdL994mixK+2jkb1vF8ZJ6oirCXGJtFr8pQ6NiPLQkYew9/G9OLV6ChISp1ZPYe/jeyMtxs3njOt380haKdxOE0H5lMt4ymK12BAzEiLhukeRspCkx4tlVtD+u5MjaaQSMewgMbavtIinpI64MIQ4AEjGjUJmr8VT5oiTyK8QZ+VcofekXheZURQ3kdcecTkSSzmyteZQbl8frVaon3EOQtyY+3kEvS/wKsSFMlbQz7ORaT2OuU6HhLilALGUdSZHqCOuoAhxQWIpAXSuRxwATJDrO8Q+iItr/hxxyvuoabb94fQD70Ctixy2YgHLK96uya5zbM3+CPjrm4D7fwVYmydPmETd5ABww0dsD/MnDz8P6t9Ko6w64mL+P8dSiRgKIH8zDot6qYO213vEffCDH1zvU2AYhmGYroOFOKZnoUKcldBhJogQR1en0dXHjDVuJ9bmyM+q5q1PQa9gVeDx2ovLCSrEbchsUAQm7hGnYtfnpV+iKYuVamP1czwmMFEr9PjtE0eLXQNx724MX1FSmgbMHDC+3natsd1n8ZR377+7qWheqBZw9/671+mM2s/civHzmovsSp84l85OGks5lh5z7cjoSldAiFAn92Ttfuv8Tca905F558UzVFgPI5oS0B3fdXpNiFsp+nPEtYymJAVdurDBK4ojzmuPONofbrTW/7ZNQoUbFlZaR1MC6jzi9JLzzxykR1woi/momDm+Hdiwy/i6U0JcPgQhbpQKcUXkykakottFEHYoDnu39xNrPh1xEzuN7cWj7l/Xgix5jyc89IhriqYcmbLfOZnBYnwTACAuJIoL3v4+u8axVVoFvvFR4C/eDLz6XePx0W3A+/8WeOvtxmPxFHDzp4Gr3m95qEK52uSiT6McniMuHkMB5H7FpSOuK4ROhmEYhmFChYU4pmehkzmr6D8z7IjrHG4n1jERi3y8F6A6C+rMZMP7WRcKC43tibTJEVdkRxzFLppyKDmEuIgD0MX2XivyuoVGdm0YSjWi5hRH3KL7a1Mptgd0xLl2YZw9AtSv68FNqvhGt2k/nYhyevW0p8ejgNIfbkS95raOG9fTjMtoSjomTGTcF2KjXiyjC5zqLpbzNxMhrkWfuLY44ogQR4/fC+RINOVwOkQhLqQecbTI7NkRZyXEraMjbmHVezTl6RbzCKVHXABHnO+xIks+z8Z3ABvON77uISFus6nHtxJlnwomxCnXcDt7xAEdiaYcCyTEbXXc/2xqurEtPV4/dBHKus3bnn8I+B+vB77734B6TLGIA2/6deDXfgBc9l7gml8w9h/abCvCzeWK+L/u+V7T42mUUIyF0yMulRAoSPJ6B0dc1O8tGIZhGKbfcT8TZJguQ42mbL16V+kRl/QW30MnHdwjrjXKhLBF1MxQcqghkq6UVgJH03QjVo64dkVTbhjYoBSJoh6z6BW7aEohBEZSI42i/HJxGRsHNnb47NrPPHEKbCJOge0TwR1xgXvEuS2cmfvDUQdTnznipgancHqtWXTbMuQQS9XjzK2o0ZSUaeKIO+XSEaf0hyNjQiuivohEFeJqjrjNRqH8yFznHXG0ENpriyVWlB5x7gvsnRLi6KIIzyInjU1sCHFkLO5aR5zx3JklDz3iUgGEOL9jBV1YMrZd7wGWGAAqeV1MWjvrLVrRB9m8cV2EEU05u6w64kaSwe7/ffWc9dsjTnHEhXN9SykVR9z4gHvhR1kAqWnAsIMjDsDywHYg/wwAIJY96uk81yUl5uC9wCMf1/tNJtLNjrIdbwRu+lNg6nLjMRrPmTutpynE1DXoL83m8Et/9a+W971poUZTBnPExZF36YhTomx7PJrygQceWO9TYBiGYZiugx1xTM8yRSZzrnrEVdgR1ym8CHF04h3VPnFzFtGp7YqmnEhPKEUijqZUUYppGbWYRq9Veg1HCTs3kRJN6bNHnJ8isK84NNofjsZSAn0nxN286+amxzLxDG7bfds6nE1noNfwJlORnfaIO+myR5ydS7YVkY+mtHLEKdGUzj8zR1OqLJMecWE64pQxOBnAERekR9zyKWPbKppyHXvEbXYZTXkm18IRFyCaMpSxQnHEbdcXoFBX3OIr/o7rAXr9jXtwa1HofcdsrqDcawV1xNF4bFcLezTN5IgLEE0ppd2erskVK6hq+nGGUnGkEu7LNPR9HNU0Xah1YG1oe2M7teztXqnj/VEP3gs8+KGaGC1VEWtwI/CTfwb80ldVEQ4AkhnD5Sirpv5xwOMvz+N9f/Z4Yz4WE8D7dm/DtvEBCADTQyK8aMqEKZqy7CDEJUJw0HYJ1157beudGIZhGKbPYEcc07MEccTRm1w3cI84b3hpvj6U6vCEbh2wdMRl85BSuu5H5MTZorGid0NGdcTROCXGuejeD33iVEecURSg0ZReRGIqnvkpUlDxznXxlzripnerz40ZxaV+EOLMi0rS8TT2vmkvbjr/pnU6o/bjFE05rfSIcxlNSXrEjWfGXZ9Hx4uRHUbtEVePpqSOuFXHz7B2RFPS4/RyNOWo3x5xaxaOuHL4jjjvPeKsHHHr0yNOSomFVeqIc4imHKM94pzHC5ou4EWwB0IaK8yOOADYcB4w+5y+vXCkeWFKyITSI04R4kzRlGH2iHNzP1FcBqSmb6eGgYSHcWpwI5AcAsqrQCmnC3oBHYnZVSp0ehsz1WhK2VKIK40ai5aGVr3FeCvRlJ0Qih75uHWUY2oI+I9POr/vI1sN1+PySWB4EgDwxadO4I5/OohKTfgcTMXxmZ+7BjdcSpyEz5XxR48Yn2/JuL9rHrAQ4hxqCV3Tgy8Etm3bBhmCSM0wDMMwUYIdcUzPMkmEuNkWK1kB9WbWazQlLW6wENca6mxrNbGmz0fVEWe10nqtVEXWoqjmh7N5VYijRSLuEadiF00J9IsQZx3rNzWaQTKuFxwWVktYLVaaXmsFLXbRQq5bPPd0qZaBUweNr7eZhDilb0v0hbhD84eUr7ePbI+0CAeoYrLZ7TJNesSdrC12aAWNppxIc4+4OtQRV1/4tGk4hZGaiLRSrFi6veuwI05lpegvmpKKdrliBZqmXtPt6BFHf3euUHrEbTP+r/VdxeqsY0+kMFkrVVEo6+JKJhnDYCpuu+8WZUGf/edPoVJofNYlYgnP7zN1KvqeQ5h7xAEd7xNHheBRv0Icec/ncqZoyoDR9PQadvU+K7GUHkU0IVTX5+JRb6+3gEZ/enUcNvWIG3YW4rTxnY3tscIJT99LEYoqq7pj7VNXAHvH9f8P3uvpeC1Zsjm/0lpr8ZMKkrnTkFLiv379MH77C880RLjJkTTu/eAbVREOACpFlGLhOeKKkvxOHcbDUHpKdoj7D8zg+k8+ivPueAjXf/JR3H9gpvWLGIZhGKbPYSGO6VmU3g4uoinD6hHX7TfF3QAVMdz0iKsTRSFOSqk4NreN+3MeOaEUkjMTqiOuuMSrEWuYi2n07xoARtNEiItobz3FTUREjHhMKG6iGZf9tWjBlq5GdwstbJS0ErT66nQ7zjwH1L/n+A5gaJP6/Ng5xvbyjC7crRPtLlBIKXFw7qDy2JnVM6F+j25EiaY0OeJGMkmM1GL/ihUNZ1dbu6b8Rs4p9wURi6wukfdOCGDjUKq2LRRX3Mtz1qv1NakpQlkqFo4jjgpxveeIYCO4egABAABJREFUI9GUHhxxiXisEWUppeqsA9ojxHmPpqRCXM0RF0+o43GHFkYskMUmG4fSjqkDG4fTiNcK7YtrZRTKVcv9lDEiNeY5yYCmcPhyuFQrquuw/r52WogLI5qS3HfMrxSRK5KFe0GjKRMeoymVWMpx79/QHE8ZELo4z7sQZ9yzDmuy4fyyI7bRuHY2lE55itZUohNX59TYyKXj+tdhinF0HHHzOGV0a2OzvDSD3/jHp/HpR19qPHbJlhHc/2vX44ptFp/91WKIPeLM0ZTuHHHdfG9x/4EZ3HHfQT3hBfq84c77DrEYxzAMwzAtYCGO6Vmom2MuV2zk6tuh9IjzGE3JjjhveImmpI641VJvR3BYsZyvoFTRxYXhdAIXTRk/70w2nAkW7RG3IbMBqXiqcc1WZTWSAqcflP5wFsW0fnDEzSnRlGpRYfuEMfk/7rJPHC12+SlSCCEUJ13L4plTfzhA7wlSXwkuNbVA3EHuPzCDO+871NYCxZm1M5jLzymP5cq5yC8WsROT61BB+VSLuDnA1GMz494RF+VoSuo63DiURiJuTBd2KX3irD9blFjKWCqUCGZAjQbrbUect84ATn3iQhPiSI84T9GU1TKwQhYAUCfOROfjKedX6WecswAcjwllDJm1ibmnEd9e+8MBIThccif1HlcAMLQZqDvs1lGI8xtNmUrEMFETmTQJzK8Z722Y0ZSuXJ1rRIjzEyupOPCDX9+La9QR5zGakkQsj6ZHgRYxioOjm7As9Xu+tCwAK7Ouvxd1eK4VFptFpXJej5MMizf/ZvNjyQHgho+0fu2IIcTd/62n8OWnjXvCt120GV/4lTcq9wwKFVWICxKxnIwLRYjTnIQ40yKfbl1MedfDhxvu4zr5chV3PXy48fUHPvCBTp8WwzAMw3Q9LMQxPUs6EVcmcwsrzpMuWigz99VpRa+sTusWlObrLSbWUXfE0VjKydE0ziFiR1iOuLMFI16nXkg2u+IY51hKoD+EuHmH/lp++sQp0ZQ+HHGAqQDcqnjm1B+uzrjR+2S94invevgw8iZ3hblAEZRn5p6xfPzMWnRdcVJKNZpyxEqIM65DN85Op76RTvRSfJRXaCzlpOk9Pn8zEeJsHHHtiKUEejuakjrZ6g43t4x2QIhTesRpHoS4lTMAaoXioUm1z1bIQoUbFEechVBvZor0ibOKEQda3zu0oinKzytWsZRAx4U46tjyK8QB6rh9Nm+8t/QezA9KjzjPjjgfQlzIQrPiOPT4/ubINToysLnl/qODSbwqiWtu8RXX30v57IONSGQXJ+mHtOm6GNsO3Pxp4Kr3O77s/gMzuOtx416+smSIcD//+h34y1+8zjkmuFJAKSRHnBACJWG8vlq0v2dIxBKN76VJrWsXAJ+0ub+ij99zzz2dOh2GYRiG6RlYiGN6mimlv4Nz4YAWyrwKcbS4EbWCWzugglqriTWNoomaqwBQY1MnR9LY5kPsaAUV4jZk9GKC0ieuxEIcYHLEWaxq74toSidH3AbvjjjqnPDTI878upbFs5kWjjigK4Q4NwWKoByaO2T5eJSFuFyxgmLNYTyQjGPIQtDYSla3u3m/wxDifBXXu5jZZXUBCYVGUx6Zc+GIC+AiMKMIcesYO+uH5YK/HnEAMDZgXOdtc8TFfTrirGIp61AhLoToPjcsKG7O1tfeFnJ9n7Zx0NL7gVGzKOACJcrPzxxiiQhxY9uN7dFtQP33tjYPFNp7r6cKRf7/ridHjM/8bIEs3AsYTUnvJbz3iHPvhm4QcjTl4qr/aMoV8hk0PDTlsKfO2EASr0qyn4fzz8QziAm9hFSMxWDZUdhNbKRbXvqGsf32/w/4zWddiXB33ncIL6wZf3tTQhdef+8nLsF/vuUKxeltSaWAIjFzB/0sqwjj9ZWS8/WpiJ1dugDYztlNHYbXXmtzn84wDMMwfQwLcUxPM+my0TqgijxBesR168q0boK6iVpNrKljLpKOOCIQT41mlB5xbvtwOVGoFBrXZCKWaLyfYyniiGtzcaZXaFVw7zdHnDm2K6gjjjrbvKCsYnfqTVRcAeae17dFDNh6tfV+46RQuU5CnF3UkW0Ekg8OzRtC3EjSiACeXXMfMdVrzDk4Outs8xhNmSWRXhNp98XYKC/QOePWETffWUccLYT2miNuhfSIG21TNKW576kXXI/DZmjvstFt6nMT6+CIW/XmiNviYh5hjrX2ihLl52esUBxx5PMtFgM2nGd8fda9q8kPYURTAuqY4iVBoxWer+F8d0VTZvPGtTvhIZqyqlWxUhtzhZQYJnGMdowNJHGMCnEerh0hhBqfGDNFD8fT7mIj3aBpwEuPGF9f+E5XL6unEpyWxu91Sixiw2ASt751l7u45EoxNEccAJRixuu1kvM40O33F1JKpBLNZcSBZBy333hx4+v9+/c37cMwDMMw/Q4LcUxPM0Umc3aRMnWCRFMqN8RdujKtm/DbI46+LirMkutyajSjiB0zITjilP5w6Q2NyaUSTcmOOACmeKnMeNPzURfiipVqw5URj4mmQg+NTT2+6L1HXBiOOMdoylPP6H3fAGDzJUDapmjXBY6422+8GMm4WuhJxoVSoAhCWSvjuYXnGl/v2b6nsX1mNbqOOKdo1TpbSdScm8UOi0VjDLUaF+yIco+4uWX1c4uyc+MQ6rXJ42fXUKyoEaxAhxxxPSbEKdGUAYS45YK9EOc3HhgwOeLc9NdqnBB1xJkEgPHO94ibc1hsYgVd0GfniAuzR5yvsWKJfI6N7VCf62A8ZVhC3GbiQlwjTq5W84VWKPcSblydawEdccq9xnFAax4LvbDkM/qTLmIc1iRiLoS44XQCJ2BEU1YXvF07ihAnTOWk89/W0rHmmlNP625PQO+PuMVmAZaJuhv+jDR+r1NiEYtrHj43KgWlR1xQIa4sjOuz6sER1433FweOZzFPYoABfYHJJ953JW65ZpvNqxiGYRiGAViIY3ocT9GUFf/RlNRBx444Z4rVIkqafnOeEImWxfmhVLR7xM0uq84CNZoyuKirxFKSHhe0WERXc/cznqIpIyjE0UnzxqEUYqZVzNt9OOJowTaMHnGO0ZQnycpau/5wQFcIcbdcsw3vvkyNh7ru3InQChQvLr7YeO+nh6Zx6cZLG89FOZpSjVa1LrJT1+GpFkJcsVo0HMUi4cmR0QvRUX5x6hGXScYbrkNNAscWmn/2TvSIo2JfL5ALFE1p74ij117XRVMqjrjOjMWqI85NNCXtEWf9cwftEUej/EpaybuIbOeIAzomxFWqGlaK+jUshH0snRtoNGW+SiIVQ3TE5atuoikD9ohLD+viEABoZfVvwQeLa8a1O+7BEacIcVIDRra0fI0QAvNJ4+9V83jtKL3TzY64MK/Dl75pbO+6QXeBtqBYqSJRWwi1gFFUpb69SSxjx5iH67ZSVIS4wNGUZIyVPR5Ned/+5h6AP3Pt9qZ73K1bW4vCDMMwDNNvsBDH9DRTZFXlrEM0ZVWrBuqj0e0REd2EEjOTGm4Z/0En3t246i8oSo+40Qw2D6eRrsV5LBcqTavbvUKFOBqrpjjiiuyIAzxGU0awR5waS9lcHN88YlybS/myq2szbEecY5zUzFPG9jYnIY4Uf5fWR4gDgFFTD51SVYZ27INzBxvbV22+ClODhugXaSHOYzTlyayzU57GUo6lx9zFVdWghciofXbNKu9z89817RP38lzzz87RlCqVqoZ8WXfLCAEMJuOeXu8kxNExOCwhrlAtQEqX45UixJkWGgxPAXVxpJBtew8zwNwjzkU0JXHQnrFzxBWDOeKaovy8ziOoiDlmFuJoNGX7hDja43A0k2xayOMFOnaXpfFeBHbE0WjKVv1mgeA94oBQ4ymz5G97wkOPODrvGqm6E+IAYClj9HETHh2rihAnYvriqLp4tPASMP+ip+PZ8iLpD3eBu1jKjz34Q5Rr91tVxDEP42/2997qQXCtFFAO0RFXpdGUZWchjo4X3XZ/UaxU8eAzp5oeX1htXshw8mQwcZphGIZhoggLcUxP47ZHHF1NNpgYbKxMdQv3iHOPl1hKoB96xJGIr5E0hBBqn7iA8ZQ0Vm0iYxQSqNDEQpxOq1XtUY+mbCViCCFUx+ZZ52uzolVQkXpxLiZiSMT8rZB3XTybIY44JyFuzCguYWkGqFbs920jZsfrC2dy7ovbLaD94a7cdCWmhogQF+VoSlJk3zxsLfxOjWYa0YlncgWUq5rt8ag4T8dPN6RiKSSEfs1XtErPObScoJHKk6PNY8X5m2ifuObP7XZFU9IxxpcQd/Be4FNXAHvH9f8P3hvauTlRdxIBeiScVxHDbY+4IEJcPBb39/46OeKEUB3KHYinXFjx5oijyRqnbeYR9N6BOue9oAgXXoQ4TQOWiPtknRxxWcWt5T+WEqAu2yo06MeNi3ig6xcwLepxJcQF7BEHqK7PgNc3jab08h4rQpymAcPuhLjS4BaUpL4oIJGf0/vwukQRimICuPyngF1vN3Y4/FXXx7Jl7Sww82TtCwHsekfLl3zxqRP4/PcN4XpsIKH0ibtxh9WrbKiUVEdcLNhnWZVcn7KVEOd3vOgAj/5otulzCFDvz+rs3bu3A2fEMAzDML1F1wtxQogtQoi7hRAvCyEKQogzQogHhRA3BDzuqBDiD4UQPxJCrAkhFoQQjwghfsbhNQkhxI8LIT4jhHhSCLEkhCgJIU4JIR4QQtwS5JwY77iNpqQ3sV5jKQHuEecFr43XlRz8Unet+gsD6iyoX6/bQuwTd5as6N2QMSabVFRiIU6HoymdHXEAsN1DnzglljKe8eQmopidGJaszhurzeNpYPJy+wMmB3QnBgDIKpBbnxW55v5kuUKlZYSyW5wccbNrs6F8j25E6f80Yl0USyVi2Fy7vqV0XqTTyiXrhBCiq4tlQTBHKps5fzMR4iwccfV4aqB9jjjPwufBe4EH/iOwdByA1P9/8EMdEeNyJjeRV0ZthLiKVmkIZgIi8Hvt2p1McXLEAaE6htxAXRl2n3MU6og7vWztBFR6xKW8O+KAAFFzq3NA/bM2M6b/o3RIiAurPxxgjCkiblxjQ8kh3/cQdeiiHld9DoP2iAOAiZ3G9uJRf8eov9xnNCW9Xx3R3DvihgczOCE3kxM46vp7DpGxYi0WAy65Cbj4J4wdng9BiDvymNEXeNu1wNBGx92fO7mE3/+SsUjpPVdtxdMfeTeuvvQSYycv94OVAkohRlOqQpzz+NrN0ZT/tH+msX3DJUafwflc82fyxz72sY6cE8MwDMP0El0txAkhrgLwLIAPATgfQBHAJgDvAfANIcQdPo97DoCnAfw+gEsAVAGMAngHgC8IIf7M5qV/DuCrAP4jgGsBDAAoANgC4GYAXxJCfEEIEWyGwrhGiabM2d/UrpJm4H6EOO4R555c2RDiqBhkR5QdcVJKtaBZu17PoUJcix5GrThbtBbiFEdciYU4oHXRfTg5DAF90r1aXkVFWx8nVbtQhDgbEeMcD33i6Fjotz8coC50sO1NdPKAsb31KiDRoiBC47vWoU+clNJSZH/hTM5ib28sFZdwdPkoAN0hdOnGS7FxYGPD6b1QWEC52juxfV5QXJ0ORfZpl/GU1FHsp/eTEk9ZicZCkqomVeehlRC3yfjcPjLX/LlNi+BhOuJojzjPjrhHPg6Yx5dyXn+8zVAhbjjt3TlMhY9lIoiY3XBBhQzPfeI0DciRiLIRi35AITqGWlHVJM6SHnETLsSM4XQCQyndFVSqaMiuNV9XQXvEAQGi5pZIf7gxCzvP6DlA/e9i5YwnV5MXQhXi6osoY8bYHDSWEjD1iHMzVwvaIw4ITWjWNOn7PV4pUiFOGguRWjA6kMQxSfb1IMQNFo17mdXRaWDjLuCiG4F64szx7+sLqILw0iPGdotYyqW1Mn717/ajWNGFuwsnh/HHP32VPiZSYTJ32v33N/WIC7rQQaOv79FoyoWVIvYdNhZ7feCtxkIAq2hKhmEYhmGa6VohTggxAOABABsBHABwhZRyDMAEgD8FIAD8kRDi3R6PKwB8EcB5AI4CuF5KOQJgBMDvANAA/KoQ4gMWL08COAng4wCuAZCWUo4C2Abgf9T2+RkA/9nLOTH+2TScbkRQza+UbCOo6Ep1P9En5h5xYcWLRRFzj7hWDKWII66LJhthkF0ro1S7JkfSCQym9AIcjaY0x9d5ZbFgHU1JHV9UgOoV7j8wg+s/+SjOu+MhXP/JR3H/gZnWL2pBq2JaTMSUa5bGrEYBNyLG9g3EEXfWvSMuSIFCccTZxUnR/nDTDrGUdWgc2joIcXMrxUZBiBKGEPfs/LON7YsnLkY6nkYylsSmzKbG47P5aLri5knsnF2POACYHjcKsicdFjvQHnHjmXHP5zOUiN7n18JKEVrtFmdiMIl0ormfmeKIm7dwxFXb44gLJMTReD83j4dIjvTbHMkEE+KWHIS4oCgxwW4ccWvzQP33kBkHUoPN+yhjcXuFuOxaqXHtjg0kkUq4m+ZO0T5xFov6gvaIAwI4XOjnlzmWEgDiCZPY+YqPs2tNmELccDqBwVRcccS5SdBoxUDc+Btoef1qVbVnodlp6JaQhOZcodK4dofTCSTj7ks0uRVDDB+Jp1ovVKoxNpDEq9JwNHm5dgZzRgT22pZaQsHQJmD762uPSuCFh10frwlNA176pvH1he9y2FXit+59Gsdq96xDqTj+/P++FkP1RQ90gQBdONCKSiFUIU7SBWstolOVtJguurd44JmTqNQu1GvPncC15xrzzrOrJVQ1ro8wDMMwTCu6VogD8EEA5wJYAXCzlPI5AJBSLkspfxvA/dDFuE94PO5PAng9dMHtp6SUj9eOW5BS3gXg07X9Pi6EMN/J/hmA86WUH5VSPi1raoyU8qSU8j8C+Ovafr9WExKZNpOMx5Rm7Fb55IB6E+vHEZeIJRrZ8BLSXeRJn+K1R5y5kKlJazG1F6GxlLTPzrYQHXF2QhwVmpaLvRWzeP+BGdxx30HMZPOQ0N+jO+87FFiMc1NMi3KfODcihhdHHHVMhCbE2RXPlP5w17Y+6DoLcXaRsy+eCS7ummMp60wOGgW1qMZTKtGUTo64MeKIW3IQ4miPuLT3aDKluB6RaErlc2vE2um6ZTSDgaQu0GXXyooLCWifI44ey7Pr084lQntKtgnaI66bhTj6/rpyxC2Tz2SrWEpAdQy12RG3sOqtP1ydLbRP3FJ7hLhwHHEWQhwAbNhlbLcpnjJMIQ7Q70EEccS5WbjXinTCxaKexg5LAGqiQWZMFzT9EFI0ZTbvvwdfbsVweY0k3M9xxwaSOEaFuLMuhTitisFF47rMb77IeO7iHze2g/SJO3NId3gCultx+hrbXf9s30t45Hnjnueuf3M1Lpgk15MixLl3xFUrBVRqQpyA8N0HuY4k0ZSixfWpxF53UTTlfSSW8n27tyEZjzWuV02q8aoA8OSTT4JhGIZhGJVuFuJ+ofb/56WUVtXXu2r/7xZCXOzjuN+UUj5t8fx/gX5nvgV6VGUDKeUPpJROM9O/rv0/COBSD+fEBIDGU9r13wkqxAHde1McBmG6j2i8pJsVrvFYvFGgkJCRKWYCam8i2s/wHNKHK3CPuIIRTbkxY/RPoP3Oes0Rd9fDh1Eoq4JsvlzFXQ8f9n1MTWqKsNaPQtycxx5xrdya+Wo4RWD6WsvimZSqI26bV0fccfv92gQVMWnh/YXZ4I64g/OGEHflpisb21NDhtBwZvUMoobmIjKxzlYlmtKdEOenwB7FHnE05psuIKHEYgLnbaJ94lSBuSsdcZe91+KAA8ANHwl4Vq1Roil99IhzJcQlQ3DEkUKxqwVnSn+4aet9qGOozY44N31Qrdii9JtWP4MKlUJjgUhCJBRBzQu+x4pWjjigI33iltbCFeImR9IQcfI5mQwhmtLL9RtGfzhAjwYVNdfwyumWkYN20EhUz0JcfqGxPZJ2/z6O+Y2mPPEkhkrGNbw6SGI9aZ+4lx8FWvRCs4W64Xa9A4g1O7MB4DsvzuFPv/FC4+sPvOU8/MSVpohcKsTRMasFJXI/mo4lA0f/UkecaBGdSseZbrm3eOFMDodm9EUJqXgM77lSH/PpWGu3IJphGIZhGIOuFOKEECPQe7ABgF2uwfcA1Jco3uDh8G93Om5N9Huu9uU7rPZxYIFsW98xMqEz5TCBrkOFODoZ9gItFkepT9z9B2Zw532HQnMfKU3DXfZ8iGqfOHo9TpKisRpNGZ4Qp0RTpoyi8nJpuaechnaFc6eCeitypVzjPRhODisFXQoVMHvNSdiK+VxrEcPsiHOK4W2HI86yeLZ0XI9AA4D0mLr6346Q+rb4hf5dv/WizY3tl86sBIo2llLi0PyhxtdXb766sT01SIS4tegJcUv5ciMSaSSTQCZpf5u1jURTnnLqEWfjKHaL4nKJSI842tfUSexU4inn1J89rNhaM3TcpmKfK8zF9uQgcPOngaveH8KZOZML6IgbNfWI02p/B2E74lqOxWYUIc6iPxxgGouP6Qsr2sQCcX1v8uCIm1QccerPbV7A47cY79s9SxeSjFv0iAM6IsRl8/6FIismRzJKj7gwHHHmHnGOn7Vh9IcDdCfdGHGD+lz4Q51EbnobUhQhLuP+Z9GjKakQ59IRd/ghDJI5xRqdE2+6ENh4gb5dXgNe+bbr81F4sXUs5Uw2jw/9w4HGkPK68zbgd3/skuYdffaIK5F73JTNnMELkozRsR6MpqRuuHdeNomx2jiwcci4Xudz6ufydddd15mTYxiGYZgeoiuFOOhusvpM5zmrHaSUGoC6PeIyNwcVQkxC7zlne9waP/RyXMLbav+XAbzgtCMTHtQRN2sjxNFJr29HXBeuTguDux4+jHy5qjwWxH3kNZoSiG6fOBrxRQXjqdEMEjF9iFtYLSFfqja91i12heRkPNm41jWpKb37up3pceuCot3jbnDrfOl3R9yGoRQGU7rAsVKsKKu0zdAYSRoJ5ZWWfYmU/nCvAWIubl3WO5oya3xGXLN9HKO14nuuWMEpi+gztxzLHWvEpI2nx7F9xHBI0GjKlkLcwXuBT10B7B3X/z94r+9z6hT0+rXrcViHjhVO8b90XLDqG9mKbiyWBcVNNCUAnL/ZKJy/PK8uoOlINKVXR9zsj9SvJy/riAgHmHrEpb0Lccl4DEO1cVmTwEpJF/byxH1D+2P5RYn2c9MjThHibKIpByaA+gKX8hqwOh/gDJ1ZIGMEja1vxRYyjzhtmkeEEUsJBBDtXUVTUiGu+3vEARbRlCH0iIuJmHsxOR+SIw4IJZ4yyPubI4vGRgY2OuypMjaQxHFpLBRC9hhQrdi/oM7zX8UQ6QXWdD0HjafMZ4Hj3ze+3tW83rpYqeL//fv9WKzdo06OpPHff/4aJKx66/mMpizSe9wQPsdkkjjiWix06LbY66om8aUDRj/Vn95tRDpvIgt2FlbZEccwDMMwrehWIY4uq3TKEKg/Z7MMs2PHhRBiGMAdtS/vk1IuOe3PhActFNlGU5JJwpCH/HxKVB1xYbuPqODjdmIdVUccFYbpiut4TGArcWz47RNXqBQaMamJWKIp2kdxxfWQu+v2Gy+Gec15OhHD7Td6SSFWcVtwj6oQVyhXG/FoiZjAuE2hRwjhuk8cjZEMUgSmcVKW0ZRKLKWL/nCAGuG1POOuuBQi9H07Z2IQF00Zf5svnPEvitP+cFdsukJxZ7iOpjx4L/DlX6sVeKX+/4Mf6noxTukP5+DUAoCttEdcG4W4KEZTqpHK9u/zLgdHXFdGU849r34doJ+TV2g0pR9HHGCKp6wVn8N2xCnRfq56xLmIphSiYw5l3z3ixoyf27ygLywhzldhXUqXjrjzjO2Fl32cXWuyYUdTjqYh4sZ77XbhXiuUnrNOriPqiBsM4IgDQrm+F8m169VxqLQEIPcBrRgbSCKPDGbluP6AVgGWTzi+BvMvAgsvYkAjjjjz9UzjKQ9/DdA8JnK88i1A1hYobn0NMLy5aZc/+MoP8czxLAB9TvU/fmG3/cKRwQ1AXUgrLgEld0J4iXzGhLGgRJD44HjVed7XbW77x1+eb9RYNg6llKSHTcQRR+/TGIZhGIaxJljX2fZBlRKnO5X6nZ/bZXTtOi4A/AWAcwAswxDkLBFC3ArgVgCYmprCvn37PHwbxszSaeNG+ZkXjmJf+lTTPj/M/rCxPTszi32r+zx/nyJZafvEk0/g7MBZh717hw0ZgYVCc3zLhozwdW0enT3a2D724jHsm2l9jBKJE3r8ycexOLCoPL+ystKTfyfPHjGKAAvHX8a+fcYEfQjG9fTVb30PV232PhyfrRjX4JAYwre+9S3l+XjZiG579IlHcW76XPQCoxZxQm/YIjC+9CL27XvR1zGfXXu2sa2tarbX09KiUXR7+vmnMXlq0nK/XmM+bxRChpPAt7/9Ldt9BzTjuv3nf/lXLGyxvjYPrB5obC+dXfL9N/rKirGC/9WZVxvHqf/dv+a5xzBee/7ZxRTmXX6fNyXHkCovAVoFT3zjSyhmmos57eKFE0Zh6syR5zBMhMB/fvwZ4JS/QubXzn6tsT26Mqq856cKxmffi6dftP19vOGJ30PGHOtXzqPw0O/he2e793p/4iQRU/PO15smJRIxoKIBy4UKvvbNxzCQaI6UO501Vscffvowzia9fa4vLBqRYM++8Cz2nbE/p17hh68Yf/9zps8tyuKS4eR+9tVZ5ffx4qIxTp949QT2ZffBDa0+619aeck47skTrsccoZXx1vmX1AUea/P4zje/iqrPnl9eOHzE+Lw/ffwo9u3zHv0d14y/2Uf/5QmcOxrH/pX9jceWzy4Hvk9aPmssPtl/aD/EEecYxquPPYe6l+iZo/NYXLb+/pdXB1EffX/43a9idqo9C64OvWC8z2dPvop9+9z1g5rJGtfySyfnlffxmbVnGtvlXNn3e3ySiJaHXzmMfUutj5Mor+DNtcVt1VgK3/nBIV3YNCG0Ct6KGAQ0IHcS337kYWghCuAAcOy0MW1+5fAPsW/ef89eAFg4UUY8Y7jV/+7Zv0PxZBGvHX5toOPGqsYa48f+5TFMJKzdbucc/wFqAYo4cXYNLwX429mR1VD3JB4/+B28vHah52M8/ZLx9700dwr79i047K1ytphrNMSYnc27vkaP1sbwV+UkJkVWP499X0Z24mrb12w/dh92ARgk9+nHTh9Tv6es4vrECJKVHLByGk995S+RG3X/nlz8/P9urIQ+mroIR00/z3dnyvi7Q8b79f6Lklg9ehD7jtof8/XJcQxUZwEA3//ml5EftFk4QNhaWAGgC8TVYjXw+Hp6nsxtS2uOx3ulaNwXn144ve5z4M8eNO4Ldm/S8N3vGJGjuXnjd3Hghy9hX9X4u/7FX/xFy3Pv1Xk9wzD+4b97hjHoViGupxBC3AHgFwBIAB+QUh512l9KeQ+AewDguuuuk3v27Gn3KUaa6o/O4K+fexIAIIYmsGfP65r2+f4Pvt/oKHj5hZdjz+V7PH+fLz7yRbx4Qi8uXXj5hdizw/sxupH/NDaDD9/7DKpkUpVOxPCffvIq7LnGJmrIgb/+579uyNxvuOYNeP3W17d8zZcf+zIOH9Mn9bsu3YU9O/coz+/btw+9+Hdy9w+/CyALANjzht143XnGqtsHZ5/B82f1lacbd1yIPa/3LpI9t/AcUKvnbRnd0vQe/f3X/x7HT+mrqXddsQtv3vZmz99jPTiZzUM+/Kjy2PT0NuzZc6XvYy6/vAzM6dvnbT0Pe966x3K/lw69hG/u13tTbNq2CXuus96v13j6eBb41ncBANs2jmDPnrfY7vvY0rN4Zk4vvo9Nn4c9b7Xuybb44iJQSxnbvnU79rx5j69zKxwt4O+/9ff699s01riO9+3bhz1vfQvwXaMgccWNv2jvvDDz4gUNN90bL5kGdl7v6/y8IqXE4iMPA9CLXLe8863QDpzAvhP6ghBtZBJ79tgXupz4i6/8RWP7va99L67fZvxM5y+fj09/6dMAgEKiYD9m7rOOhssU57t6nH3pO0eAg3q84GXnb8eePZc77n/Ok4/h6IIuiF5w5XW4cKrZcZH/e6O4/GNv+zHProzDzxzGN5/Wx4up7VPYs3uPp9d3I596zvjcevsbduO1O63dIivFCvY+obdbni8Ab37LWxuxYN//wff1ZWkALrngEtf3XK0+64tHi0BtDcHE5gn31+uZ54BvN7sy3nLFDmDLFe6OEYD7Tx8AjulCzDVXXIo9157T4hXNTB9+AsdzulB84WVX400XbMLcC3PAE/rzO7ftxJ437Ql0nl//ztdx4Ii+wGLXxbuw54IWxztoLDi4+s0/Dkxear1f4WFgXo+au2x6CJe9Jdh52vH5Y08C0N3Ab7zmCuy50l2wycVLefzB9/R7jlUtoVxXZ18827h32DW9y/fn3NwLc7j/ifsBABu2bHD3uzp1ENA/thHfsBN73v52+30Pndvo8fXWK7YDU167KzjziQPfBqCLgm9742tx2fSo8wta8OR3/wHxFw1hPS/zuDd7Ly677DLcdP5Nvo879qUxZJezAIBrXnsNdo7ttN7x0e8CNfPgORdciXOCfPYdmgde0e9htp/4Mrbn9gM3fMRT9O2+5eeAl44CAK6+5ALsecv5zi8g/PFRY2y75jVvw45L9rh63bGFNex94jEck1N4ba2jxmu2jwJO971/+UcAgCHichscG2wei7M3A898HgBw7fAZYM8HXJ0TpASe+tXGlztv+A/YueMNja9/dGoZf/vIdxtf33TVVvzRz13Tunfjy+cBx3Uh7vWX7QB2tp4P/ehfje3xEQ+fNzY8lXuyMZakUHY83rbFbfivD/xXAEBiILGu92YrxQp+9RGjZ99t730DrthmuINPDR7DfS/qvYsHN0wp97d2592r83qGYfzDf/cMY9Ct0ZTUg++UtVJfxup2aWXoxxVCfBDAJ2pfflhK2d3ZThGERlHY9oirhNsjLkrRlLdcsw3T42qcx/t2b8MtPkQ4wGePuAj22QGAWRKVao74ovF/Mw7xf07Y9YerQ6PWaLxSt2MVh3jg2KLFnu7JFrKN7X6MpqRxMZtbxPpt32CMdcfP2l+btP9KkFg0JQ7N3Ddj/gWgPiYMb3EvwgFqjBfts9Nmzq6WGn03h9MJjA4kTNGU/twghUoBh88aLoQrNqkCAu0RN7c2h6pm03ty2Mb1NuZdHOgkXq5hQI2ntIr/LVaLjc/yhEj46lHUbX1cwmCORio7vM/D6UTjc61clThOxm36d9wV0ZTm/nB1OhRPuVIMOZqy1k9K6REXQjQl7RHXMppSSiBHEihGHEQvGt232KloSvfX3abhdMNoNr9SQqliiAyhRVMmfIwVbvrD1VH6xB3xcGbuyOaN93bMY3SiFQ+d+EsIoYrjhWoBd++/O9Bxlahrpz6HYfaIm39J/dpH3HN2jUZTeotBzEnjs35k3P2ivvqYckwj9wSLDj0GV2aB4z8AAAxKQ/iynLcpfeK+1vy8HbM/BHI192hmDNh2HQDg/gMzeOMnHsGP3/0dFMr6dbNr8xD++Kevai3CAcDIFmPbZZ+4InEhpxI2sZceECljjE5oRX0MtYHGXq93NOXXDp1q3NNePDWCy00i/EYSTTm/on5uTE97uGdnGIZhmD6hW4U4miXi9Alef645i7ADxxVC/FsAf1b7cq+U8lMuz4MJESpwnLER4ugkwa8QN0Cy3amwFwWWC2r/pKGUf7Ms7VVg7llmx3Aqej3ipJSYzdGCpjqJ2+ayD5cTZwtGIcFKiKNFI9oLqds5frb57+uFMzmlmOkV1z3i0tEU4ujkeFOLAqXaI85+rKP9V4IU2zOkwNHU08VPf7g6VIjLHrPfL2TU/nADEELgwiljjHtpdgXSoQBjx/Nnn0dF6n8DO0d3NhWFM4lM47GKrCjjg8IVP938WHJAX8HfxcyRa3iziyL79LhxHZ9aar43oOL8WHrMXTHPhFIsi8AiEiml8j7b9typcf4m47o+Mmd8dlMhLozeOnUUIa7qQYgz94er0yEhjt5jDYcpxLWzR5x5UYSZQhaoC0rJIb1obsdEh3rEkWvXS4+4ZDymfC7Sv4GwhDhfYwX93BpfXyGufs0BsO0x64WFwqzl46dX3YkkdlAxuWM94g78TfNj5TzwyMddHyJL3t8JD0KnrFaxQj66hiesEwysGMkkIATwqiR95ZzGxBf+GXr4DzA0ZSRUWM6Jd73D6Mt25ln3AvyL3zAdI4H7D8zgzvsONn2Ov/+6czCcdjmejpCyz7KLyFpNQ0ka43Y6HlyISyZSKEs9Q1RAAuaIcAIV7tf73uK+/UaU8vt2b2u6V6I9e+liCAA4dcptiY5hGIZh+oduFeKeR/1OD7DMHhJCxABcXPvyh1b7mJFSzqERpGV93Br1PA/b4woh/g2Av4L+Hv6plPJjbs6BCZ+Nw2nEaveEi2tlFCvNLgB6Ezvosx+I4ogr+xNOupHsWkmZYAPA4TM538ej4gUV2JygTgTqqOtlFtfKKFf1YWw0k8BAKq48f864s1vD1fcgjriNmY1NzyvurmLviEpWwqQmgYMnsr6P6baY1qvvWSvmc16EOOKIcxCJ6WrzQEKc0wr2GaMHErZd4+3AihDXvuKvGfr3XBc1Nw+nMV4rrq0UKzhpIQy14uDcwcb2VZuvstxnatAoqM2uWRc6lYItAKRHgJs/7SlGaz2gjrhNI62L7NTpfdJijKXivNVCBjfQ4noUFujQz62RdPPnlpnzNxvFwiNzxn1WiRQYw3TEUVHPtyOOFJA7JcTliBA3mvEnYnRCiKO/q5ZCHC1mj05b9i5rQF06bVwUMU/6DW8a8nbdbRk1xovTZHym48RYKoAjjrpn3Y4VWeKIo59nVmwkAkzIQlyhXG24kBIxgcEW44Ibtgxt8fS4Wwbixt+BY3rJWoiOuGUbsWHphOtDZNeI0OlBiMvnZlCt/e0NaBLJtHtndywmMJJO4JgkjrizDo444mwb3HVDY9vS4ZkeBs57m/H1C//s7qReMiIQccE7AQB3PXwY+XJztPD/fsLDWOLVEVctokjGtFQi+IKSVCKGAshxHGoJdLzIl/O+Fm+FwYnFNTxxRO9XGBNoTss5eC+u+sKbcST98/iX1IdwzeI3LI7CMAzDMAylK4U4KWUOwJO1L99ls9vrAdRnRI94OPxjTscVQmyDIdJZHlcIcTOAv4feGvkvpJS/7eH7MyETjwklporGAdahkwRaOPMCLXJEoeBW59WF5p/l8Gl/QpwmNUX09CXERcQRR92Zk6PNKymp2OE3mrKVI446v3rJEUddWJmk8TH19PGs72MqxTS3QlyEHHGKm6hVNCW5Nk8srtkWAEKLpiSOuKY4tECOuM4Uf83Q63dbTXAXQuCiSRpP6X2MPThPhLhNrYW402s2xSbzavAL3tX1IhxgiqYcbr06nTriTmYtHHEuXbJO+Iqb62LUz63WQsb5m4kjbt7aEdd10ZQX/5ix3bFoSuNcQ42mDFuIo24ip1g/oFmIc0JZFHEcsIvNDUChXG245hMxgdEBb+/zFLlPo38H9D5gzMn11wK6mM99NCX53BprIcS10RG3TBbrjQ0kfbmHzXzwqg82PZYUady2+7ZAx1XuJ5zEZCWaMqAjzi7W2UPcs99oyuXFlxvbIz7KOmODSRwzO+Ks7vlKa8DLjzW+HLzoJxrbttezEk/51dYnU8wBx75nfF0T4qwW0jg9bgmNzs3ZCKeUSgElcp2nY8E/x5qEOAfHZjKeRCKmj2EVWUFJs3fPtZP7DxhuuDdfuFkZJ3HwXuCB/4hE7gRiAjgnNo/frfwZJIlk3b17dydPl2EYhmF6gq4U4mp8vvb/LwghrBoP1MWvp6SUhy2eb3XcdwshrrZ4/rcACOixlI+ZnxRCvAvAFwAkAfwNgP/Xw/dm2gS9MaRxgHXCiKakAl6UesQdXWiOvJjNFbG46v2mf628Bk3qqxYHEgNK0cyJoVT3RHCEBS3kmPvDAcCWsUxjAfmZXEHpSeIWL9GUS6Xe6RF3nAgZN1xiFAgOHMv6PiZ1xPVjjzg1mtK5yDM2mGwUiwtlTXEZUMKKpqSvpcXfWLUEnHnO2HHaoyOO9tRZt2hK43ODxlO+6EOIOzR3qLF95eYrLfehfeJsHXFmIa5DYkRQ5j2IyYBZiGv+zF4sGo5i30JcxPqbzubcx1ICqiPuZRtHXJjRlPRYJYdYL4VygfQ9EsCFNxrPrYMjznWUmgnal6sj0ZStesQtGwXalkJcehgY3KRva2V3hXCPqP3hUp7FInqfRh1xips+gCPOXzQldcR5iaZ0cDX5gKZmhNEfDgBm543PKikBrTSOwqn3obz0mkDHdYy6ptBoyoHxQN8TN3wEMM93PMY9Z31Gf64sG6674Zj3sWVsIIl5jGJV1q7/4rL63tQ58hhQH282X4LBqcsaT61VbBZsUSHu6L8A+azzyRz5lj4+AMCWKxsuNvpZTrF73BKvjriK6ogLY0FJMh5DQbpzxAHrf38hpVRiKX96t8kN98jHANPnxKAoQX7TCIl66qmnwDAMwzCMSjcLcZ8F8CqAEQBfEUJcBgBCiBEhxJ8AeF9tv98zv1AIIWv/9loc98sAvg/9Z/+SEOINtdekhRAfBvAbtf0+KqVUZvlCiOsB3A8gDeD/APj3cr2yAhgFWjA6Y+GIC6VHHHXERWDle51jFo44wF88pZ/+cEA0HXG0oDllUdBMJWKNKCQpgVNL3sVdGk25IdO8ord3HXHGe3Hz1UaB78CxrO94Ftc94qIqxOWMjzM3/bXOMbnirKCiWSZAI3slmpIUzoZWXzGKMht2eY+PooXLpRNtcWFYMWPqEVfnoinqiPM2zs3n53FyVRfQMvEMLpy40HK/qSFDuD6zesb6YLSADvSEEFfVJM6aCu2tmB4j0ZQW4yvtETeeGfd1XkpxvRIBIc6jI26X0iPO+Pm7yhE3/wJQWyCEiZ3A5CXGc9lXAc37IhgvSCmx0iM94qjQ2doRR8S0VkIcoPaJc9svygNKfziPsZSAGk1JF1KF1SPOVzTlEhHixloIceM7ABEzXlf2Hn9sexomR1wY/NX3n2xsV1cvxurLd2Bt8Wrc9bCXtbXN0PHGOZoyxB5xV70fuP5DxtexhKe456omfb/HOSLEjcS834fp30uorjgrIfd54mi7+MeRjCWRiunjRVVWrd2Ho9PGAiqtosZOWmERSwkAt994Mcyy+kAyjttvvBiuoWNUzkWPOJMQF8aCEi+OOMCnizZEnj6exZF5/XN9OJ3Auy8zxcbaRK8Kco956623tu38GIZhGKZX6VohTkqZB/CTABYA7AbwnBBiCUAWwO3Qe8jdKaX8usfjSgA/A+AVAOcBeEIIkQOwAuC/QH9P/kJK+TmLl/8BgPpd0TsBnBRCnLb597Mef2QmAHQlK51A16GTXt+OuERUHXHGe5OMG5MOP/GUfvrDAervJDJCXItoSsCIrQP8xVO2EuJo0ahX+p1VqprSkP2tF23CSM1BML9S9N1Pz2005UjKEEtWSisNh2ev4yWaEgC2EwHJrk8cdUwEEuLoCnZS/B1dfsnYyWssJQCkhogLo+JuFXQIUCF5G3kfL5z074ij/eEu23iZrdt4y6BRKDmzZifEmYpQ+bNAobsdswurRWg1DX5iMIlkvPXt61Yyvp5aKkDTVBFf6RGX9tcjKGrRlKojrvU4sW1iAKmE/ruYXyliuaAXk9vliPMlxM09b2xPXqr3RKyPC9VSW9xZlEJZQ6V27aUSMaQT/vprjXZAiFMccS17xHlwxAFt79m5sOJNqDczNWYtxLm9d2gFnUO4creUVoE1vTcTYgnV0WNFIk2iEGWo7zHtXxaWEJctG5/HWsm4f/UUN2gB/TuwFZOrZaBU+wwWMSDA77XBWz6s/54A/X6DCEmtyBXKjTTIkUwCCRefb43Xrhjv44iP1gv1npWvKvGUJiFOq6o93i6+CYDLHqkXGxGWtMdcE1KahDijg8g7Lp0E/fSeHsvgE++7srlfmRNmR1yrRX2VIsohO+LSiRgKIH8/Xe6Io264n7hyi9ozVspmF2iN0pDxefC5z1mV0xiGYRimv+laIQ4ApJTPALgCwKcBHIHuRFsA8BCAd0kpP+nzuCcAvAbAHwF4HkACQA56FOX7pZS/avNS+n5tAjDl8C/4jJhxjdrbwdkRRyfDXohqj7hjZ4335o27NjW2n/chxK2UiCMu5c8Rt1rqfVcBoF6HdgVNWqQ/4UOIU6IpLQrJSjRlsbsL7XVOLRVQrRUtN4+kMZhK4Ort443n/cZTuo2mjMfijetRQiJX8tcvsduYJwX2TW1wxIUVTUnFvZHcC8ZO23z2mVCKv+2Pp5RSKu+XGk1pjIkvzq40CUNOHJonsZSbrGMpARfRlFI2C3FAWxwqYaL0h3MhEAH6Cu560bhU0ZToOiCcArtSiIyAEDfnMZoyHhPYudF4D+quOHrt/ea+38RDRx4K5fyScaPw5zqakvaH21xzw03sNB5rgyhEyRUMEWPUpxsOUAWQZQshLshiiDq0R1xrIY72iHNREB9vryNOjV8O5og7bdcjLkA0JZ1D5Cv51ot8aCzl6DYg5kLAbVOfuCWfsYlODA8b92Ra2RDiPMUNWuAqXpVGL2bGgVgI5ZDUELCVdLw48a+uX0qFznGP0Z+5tbnGtpd5V536uHJMGvcOTY644z8A1ub17eGpxsIoV+Iyjad88Ru6CGrF3GHDAZoeBba/rvHUszPGtXLZ1lE8fucN3kQ4QF+AUV8gWikAxBFvSaUQviMu7tER50bobBPFShUPPGOM8e/bbep3eOQxI7GCsCZT+NFlv9Hms2MYhmGY3qarhTgAkFKellLeJqXcJaXMSCknpZTvkVI+4vAaUfu312GfZSnl70spL5VSDkgpN0gp3yGl/ILDa/aQY7f699fBfnLGC9QRN2tyxFW0SqOgEBMx36uGo9sjzri5f/dlxorIFwJGU/a7I07tEWddIKOxdSd8rAL20iOuV6IpaX+4uivrmh3jjcf8CHGFSqEhGiVEoqUrNmrxlIVyFbmiHo2WiAlXK9q3byCOuLPW1yaNkaTFL6+YHXH1+NHR5ReNnfw44oCOC3FL+TJWS3oE5mAqjglSVNs0nGp8vVaqenJ3UkfcVZuvst1vapBEU1o54gpZo88LxbwCvsugfQq9FNm30nhK0/tNHcVW46cbfPV96mJoj1030ZQAcL4ST7mCh448pFx78/l57H18byhiXCiOOMAUk3g08Hk5UR97AWAk41/EaBVN6XeRGcVbjzgqxHmMpmyHI45G1w55L5pvGWte0FesFhvvsZt7ByfisXiTGOcIjaWkn2NOdECIC8sRd+6U8fPLmiPOc9ygBfR+Il+1eY+V/nD+xn5Ltr/B2D72hOuXLa4Z1+7EoLdrN1dYaGyP+Oh1ainEmcfEw2TsvujHGsKlq4UoU1cYsarFJeDVx633o264898GkEUXB08YQtxV5wRwL45sNbZbJSS0K5rSQ4+49YymfOz52cbf/bbxAbxupyl15bufbnpNTmZwR/n/waGNNzY9xzAMwzCMQdcLcQzjBhr9dyanCnFmN5zXBu51otgjbrVYaayAT8YF3n6JMRF74XTOcz8uKlp46hFHRLsoFDMBU484m4LmtnFjkuU1mrJYLTZWSCZEQhGP6tDHcqUcqh3qkRWEE0p/Lf39eQ1xxD193KKJfAvMzpdWY8BoOlpC3JzJDReLtR4D3TjiqGMiiBsjJmKNXiON4xaWMJivxeLEEsAWexeYIx0W4pRYyvEB5VoTQphcce4WO1S1Kp6df7bxtaMQZ+oR1zSGW7nhgK7vE+fHEQeo8b/mPpxuXbJOZOIZxGp9mUpayb041KWoTm53f9PnbzbEiSNzq7h7/92QUK+7QrWAu/ffHfj8FCHOzllhppUjrt1CHO0Plw7HEdeuaErFndzKEUf7LI24iabsYI84H4442sv39JK+IIRGeo+mR33PH+p4iqekn1frLMRl2yDElcR8Y1srbwQA/OEtl3t3OplQFvbYOY7WjEVsgfvDUXZQIe57rl8W5P3NkVjpkcFNDntaU4+8dYympJGSl9zU2HS1QFUI1RVnF0/50jeMbRJLCQCHFCFu3Pr1bqDxlHb3QnUqBZRCjqb02iMuUDTlwXuBT10B7B3X/z94r6eX/xOJpXzf7m3qvOHUQd0RZ+Jb2mvwgPZmJYFjZmamaT+GYRiG6XdYiGMiAZ1Az5qiKaloNugjP7/x2gj2iDt2Vo1Qmx7LNCaBuWLFcz+uMKIp6TF6GaVHnE1BU42m9Cbumt0cVgWiRCzREER7JWbxBLkm664sKsQ9e3IZxYo3QdFrwV1xxPVIbz0nlMiuEXereqkjzi42lRa5ghYpmiLRTh4wnpy8DEj6LDK3uS+RGVVIbj7ni6aMse6FM+7GuiNLRxqi++aBzYrrzcxwcrhRkC9UC81CchSEOC+OuHFj7J3JqkWvxaIxhvoV4oQQkeoT58sRt5k44uZXcHrV2mlg97gXqCvBlehZWjOubREDNl2kb3dUiDPOcySsaMpCBVLK8HvE2fTrbKK4YvSVjKeAwY2tD67EgYa/KCJoj7jRgQQySX1anK+5yMPqD1eHFtZbjhXUEVd3FLWiTULcMhWKPDq2rKhqVZxcMT6L6j3iAoksNair01aIa5cjjgpxM/uBVq7SGlniiBv36ogjKSIjQ5MOe1rTMppy7gVgodavNzkInPe2xlP0s89RKFKEuK8292crrqhOOVN/vYMz2cZ2Zx1xxpdhRVMWqRDXrh5xB+8FHvxQbQyR+v8Pfsi1GHd2tYTHnjfipZtiKR//jLE9ajw3KfS/KzrneOqpp9yfN8MwDMP0CSzEMZGAOo7OmKIpaa56kFiZgaSHSJke4dUF48b+3I26W/DiLYaA5jWekgo9QaIpvTrxug1Nk4ojzq6gSQv1XkXPBRJH4xSrRt1dS6Xu7xNn5YjbOJzGubU+RKWKhh+d8nZdei2mRS2aksb6uRUxqCNuZjFv2c+MFmqD9icaiJvG15n9xpN++8MB6+CIs+4PV+eiKe/jqzmW0smVIYRwjqdcJquTM+PGdpcLcaqY7F6Io/2GTpnG2CzpEWPVY9Mt9N6gl4U4KaWykMmut6kZsyOO9imkbBnaYvm4FzxHU86/ANTdeRPnAcnaONVBIW6lQKMp/QtxyXgMgym9T1hVk1gpVkIX4mix2TGaMnfK2B7Z6q7H1tg5AGpj1/IMUHHZ488l86veP+coQgilT9yZpYKyiCdIf7g6SpRtpZUjjkZTrq8QF3Y05em106jIWly2HAVqcX0vzgZfiEfvRWxdnXniiBsI0RE3PAls2KVvV4vAyaddvYz2iJvw0iNOSuTIHHdkaKvDztbUf58zchOq9bJQ7iRQrt3f0VjKXe8wxlB46GF27pv1vm+AviBq9ofq80f/Baj3/Jy8DBgzXJFnV0uNePRUPKbcQ3mGOuLoGGZFFzjifPemf+TjzSJfOa8/7oIHnp5BpXbPv3vHOM7bRGon2ePAs/9kfH3DRxqbU9CFOLoo4r3vfa/782YYhmGYPoGFOCYSTAymkIzrN8zLhQryJcMxQ1eR0dV7XlGy2jvcNLld0P5wOzfq783FZJLz/GmPQlzZ2N8qKtGORCzRmHBIyJ4XOs+ulRqTmLGBJDLJuOV+amxaAZWq5vp7UEfchox9IYE6PXqhTxwV4rYTIYO64g4c8xZP6dkRF/FoSjcMpxONglCpqinCch0lmjJAjzjAwhE3Q1bR+u0PB6hCHHUYtAklmtLCEXfhJImmdOmIOzR/qLF95abWEZ3meEoF6og7903GdpcLcX4dcXSMPWmKplQccVSU9Eig+KguYrlQQbGifwYNJOOuYxR3kR5xr8yv4v0X/WzTPpl4Brftvi3wOVIhrlQttV60Q2Mp6/3hgHWMpgwmYpjjKUN3xMVdOuKooD/qMkowkSa95GTo47EaTenPvUL7+Z5eLiiLl/y6Zimeej75ccRNnIeG2Jk9FprYSR1bYQhxJ3InGtvjSUMc8dOb2ozSI85uLtEuRxxgiqd01yeOCnHjXt7ftbPIkXU5I26cqSbqv88KEliIk0UU9QSB579qPEZiKQEPn32JlOpyO/xV9XklllJ1wx2aMf4GL906glQiQOmK9rJ0IcQV2yHESfL79eCI87TIZ+mEt8dN3HeAxlKa3HDf+3NA1mosO98CXPITjaemxCIAqSycYhiGYRimGRbimEgQiwkl/o/GKyk94gJEUypN1lvcPPcKrxIhbscG/b1RHHFehTjqiEu6d8QBza64Xoa6Cuz6wwFAJhnHplrBqKpJnLEQO+wwR1PaQR1gVJDqVo4rjiLjb+4apU9c1tMxqQDppuAe7WhK98UE6ug6bhGdSotcQR1xTX1daDTldABHHC1gZo8Dmnux2w/U2doqmvKl2RVLp6GZZ+aeaWw79YerQx1xs2uz6pNUiNvxRmM7ewzo4h6SfnvEbR2jrmPjvqBYLTau34RIeP68oijxXK1cLl3MnCmW0m0/rLHBJDYO6Z9jxYqGjalzlee3Dm3F3jftxU3n32T1ck/EY3HEhb6wRUKiKltcs3M2QtzoNr33JACsnNEjLNtErhiOIw5QRZDsWkmJ3gu7R1yp6iDi0HFk1IMLp41RwWo0pb+iuSLELRWaesQFRXEQtSqsKz3iXApxyYwhjEotNLGTOuLGvTi2bKBC3NYhQ8gNwxFH3fUd7xEH+OoTpwidXqIpV04jR9yoXloC1BklY8pMjDjGzr4CrMwCJ/5V/1rEgAtvVF7rqXf6xYZgo/SJkxJ40UGIO5FtbAeOLlUccS2iKaslRYgLK5qyIz3iBsatH6dCpA0vnsnhYK0nXyoew81Xkdfks8D+vzG+ftOHgPQIUEvAyYgyxrCKhdVw3c4MwzAMEzVYiGMiw6QST2kU7drVI67X4xMBNZpy5yb957tki39HnN8ecYCpT1yPC3FnaEHTpj9cnW2mCEC3nC0YhQQnR1wvCXGliobTtWhZIdRYuWt2GGLjgWNZT8dV4qX6MJrSr5tI7RPXXGShjrigq4UVJ0ZuxnBcJAeBzZf4P3B62OhfpJWBleB9qpywilalbBxON0SLfLlq23+vzmp5FS9nXwYAxEQMl2+8vOU5OEdTkgL6pouAoc36tlZRXS5dhiIme7iGp0mPOBpNSWMpx9JjrkUnK3yvWu8y6H3TVIvPLTM0nvL5eaPIfssFt+DrP/P1UES4Op7iKWefN7bpOBKLd6x/ZFg94gC1aD6/ugJZi91MxVKIx6yd915w3SNOEeJaF3cbjBORdjG891xKiYVV4ogb8lc03zJGoimXC23tEedYWK+UiFAglD5MLdlwnrG98LK3E7Qh7GjK4zlDINw1YVwTL7l0iTtB3fW213BbHXFkgcvx77la/JPN+4ymzJ3CChHi/Cwoob9PpU/c4tGaYFab6+54IzCkOu6Uz75WSTEXvhOoLaLAzFPG9b3wsjH+pobV9w9oiEIAcGWQ/nCAqUdcF0RTlp2FOF9JPLnTQMnmuNQJbsH9B2bwU39m9Oq7dOswxuj1+OT/Aurz/M2XAhe+S98mAueUWMQ8mXN89rOfdXfeDMMwDNNHsBDHRAZaOKJ94ugK9SA94pLxJBK1FdQVWXHXn6TLoY64c2vRlBeSaMqX51ZQ9hCXSKMpvQpxSoGi1LuuAgCYJdefXX+4OueMO4sddlAhzqm/Ee1r0u1C3MlsvtHDfctoRomguXTraOPrY2fXlBiqViiOODfRlBET4kJxxJ1tFoxoD6Ggjjha5Cg+83+MJ7QK8Nx9gY7dyT5x9G+YxiJSLiSuuFZRXM/NP9cotl8wfoGrxSSuhbjRrR2N6AvC3Io/R9zUaAYxYRyjVItepGOCk6PYDVHpEUeTBDa3+Nwycz6Np1w0BF16LYZFMq7GUzpi54gDOnbt50LqEQeoRfP5VWPsoNdgEJRx2K6/FmAaR1xGUwIAEV3CFD+XCxWUq/o4OZxO2MaBt4I64s4sF0PvEedauFg+gYYAMrJVj/ZzSxv6xIUtxJ1YMcT6KyeN8z0y723OYYWyqMfOcaT0iAtZiNt4gbH4J78ILLzY8iVKNKUnIe4MlokQ56UlQB36+zxS2Ww8sfiKGiFJHW01PEWtDkyocdgv/LP+P42lPO9tTdc6FeKuCizEeXDEVYqKEBeKIy4RQ0FSIc75PfPliPvnO4Bq7X49Zvq8efW7wKuPN78Gugh3530HsUIc3D86tYL76zGVlSLw/b8wXvCmX9dXTAKKwDklFpErVlAo6271W2+91d15MwzDMP8/e98d5kZ5bn9Gfbu2eHft3XXvDReKwRQDCRBMC5eQ3hNyc1MIySUXcu8lDilwQ/IjkE4qaYQaUxxw6MUG2+Cy7nVt7663V61WXfP7Y6T53k+akaZpvTZznsePZ6TRSDsaffPNe95zjo13EWwizsZpgzpOEadsTWkmIw7QacMxzhGJJ+TMHEFgNmoVRW5MSnUFxxIijvZqJ8XMWFOeVoo4zpoynyKOWKfpUMRxGXE5wuY5RVx0fBNxvJqILyx6XA4snMSKDHrsKfUScZREPu2sKXVk5zRVqpPEoihy3eamFXFUibH/GfZEIgo8/VWg+RHjO+fsKQtHxA2FYnLR3etyqB7r2aTZ4UB3biKuubdZXtZiSwkAtcWsqz03EddwShBx0XhSLlQ6BKBKh9rF7XTIqmRRZHMDvWNCLnDFslPYmpJaKtfqIDsBXhHXMcLOOZpXaBU0K+IiI+z3LjilAjnFGJ37IxwRZ11GXN8omydZYUsJZBBxca1E3MlXxFmRDwdIDUBpFDojLmdhfZBYSmq1pUzDYiJOFMWCKuJmVk1BlU8q6McSItcgaAT0t6BJEWe1NaUgAE36cuKoNaV/rK0pSXPAgRgh4rp2A0deYetzFYg4t8bzOQ0le8pDL7DHZl7Kbd49HJZdMnxuB2ZOMG4hDSBDEdeZ2447IyPO4xh7a0pdVrYAcOBfwO5/sPWPPQ6sGQLmXsUee/pritmR96zfj1CMJ8GjiSTuWb9fWml+RLJxBqTjuOgDbENyXOsFieRO21OacRuwYcOGDRs2TlfYRJyN0wa15Aa6m9gicEScCUUckG1PeSqjtZ+pjyZVFMHrYh3Esw3aU5qxpjTshT8OQZUFdXkKmpRwovlS+cARcV71QgItHlE7tvEImkPWpGDrZ9SeUrc1pff0UsRRa0o9BfZcijiqlvA4PHAI5qYTXBe7mNERHwsBL95pfOdjZEHXnkEkqxUgqOr4YB4rruYeQsTVaCPiKPnRFSREXGQESP8WnB6pa/8UIOKo5VxViRdOh77CDrWnTI+xAxE2fpom4lynhzVlNzdO6LWmZAXS/kiPvFwQRRwh4uLJuPqGvfvZcvUMwJUx9o2VIi7CSIxSr3WKuP4QGzvo+GkGlIgLJ8LqFuzUxrZMBxHHKeKsa4qgmURGbSkBoL6Cb+jTO3fIB66wnksRR7PdKk4uEReKJWS1odflMKw2pKAZcU1lTZhUyuYPB/OoxPMhK29WCaMFtKYEdOfEUWtKvx6iM9CJEXI9LPXoJ6pcToc8Lh1LEmvKo68zomjCPP68SkGXNSUAzLmCLR95BQj2AUffYI+lrQ5T2NnOfn8LJ1XA5TRZtnJ5gXTjopgAgr3q22Yo4gpjTZn7nk+XNWU0CKz7Bls/4yPA9FXS8vt+KOe4oXc/sPH+rJefULn/PDEYkuxVN/6UPXjOv/PKRaI0rMWg9DY6Ms9t2LBhw4aNdxtsIs7GaQPeUobdfFmVEQdkKOK0+rWPUxzvz86HS2MOIeLyWadRUEWc7ow4cgNJ93MqgiriavMp4jhrSmMZcbms1U4tRRz7TWUq4gBg6WS/vLytdSDreTWYsaY81c9FAOgdYUVKPflaXEbcID/ecflwmQVuA+CKZw6FqclQW/ZjWkFVGFRpYDE4W0oFIjmN2bXarClFUeSJOI2KOFVrSpqJUj5J6tw/BYg4LuNQp1ILACaSMTZdbKJNCX6f3/BnAwyoAsYpug0S9gCviAsm+uTlQhBx1CIspzWlWj5cGqe4NeVgyHpFnNPhlC3YASCaVDm+mWOJVvgLY01Ji77VOq5xmaAEdOcQT8TRBh2j0GzlN44UcdQ20Qo13FBkSG5w8jl9qCmqQUMJIzwOdptzxODIZFVrSkrEWayIA/icMw1E3EDQmCIuMnwCkdR8ySU4DBPy6e+Vy4ijmPM+xYd1WVMC0rk5IWURHA8DL32XkX01c/imKVicD5eG1py4TEWcRdaUEZDfUB5FnK4G1Zd/AAylmhuKqoDLvseeq2gALv5vtv7aPVljg1qMwiR/EXBwPWts8ZQBZ36a34hcA+oE6bfVqyM+wIYNGzZs2Hi3wSbibJw2oIUjVWtKs4o49+mjiDvay26aJlfxx2WuUUVczLgijlpTnsrFTIDPiKvLlxFHCvZ6FHGUiKvyabSmHOcZcVR11ViVTWQsafLLyztah5BIqnTrZ4D+3e+2jLhQNCFnPridgq5CWoOffQcnBsOIk+wWOv4VOc0XgbnimZKSrKLR+M7HKCOO/n6ViOQ0qDXloe4R1fO4I9iBvrBEapS6SzGtYpqmz1Hpq5SL6YFogBXIqIolnev0LiDiaLNDx1C2NWWujE0tOG2IOO66pa+gO7mqGK6UMiPpGGT7KbAiLqc1Za58OODUJ+Ii7FyziogDeHWdYk5cPAIEU6pHwQGU6viOyycB6e8v2COpOCxAb5A2mxgvmNPzvnckgkGLFXGaC+umFHHkOjF4DEjkUI1qALWl1JVfpgKaD9dY1ghBEDCpjJUj9DT/KYFr6lG1pixgRhwATDwDSH+OgZaceWSJpIhhMkbomaMFRhiRVO4qNmwDWJ56zxEUI650PzF3teLruGufVltmanH5zh/Z8sz3ZG3a3DYoL5vOh0tDa05cIRRxTj4jTsyjiNM8XpzYDrz1C7Z++Q+Akmp+m7NvAuoXScvxMLDuPwGieF4wMbvRoMjtxK2XzwE2EAXd8k8CvozvghzTNBHXl2oAvOqqq2DDhg0bNmzY4GETcTZOG9AbaJp1YiURdzplxB3rI4q4ap70oIXi/RqJuFgyJhfnHYKD65TUAvrdnE4ZcfksvhoyrCmTGsklaq2mWRE3zom4fIq4Bn+RXIgficRxuEfbeUKL7u82a0o+H86rq1BT5HHKCrpEUpSzOoDCKuIimZ/RXQRceofxnY8REZcr45CissQjH9dIPInWfuVrCc2HW1CzQLP9p0NwcARI92i3tEBzndJd4acAEWc04zCNdOYpwMhSvWNCLlBrylO5QYdTxOVpIMmE2+nA5KpiwBGG4JT243V6LSEvst5LKxGnVxGnZsNoEoEw+4xWZsQFIqQZwm0dEZc3J46qSErrAacOctHh5JsqLBqPuYy4EuPXI4/LIVtbJkVggCpnLciI02zlR49LhkooLzwl0vcCAMk4T+oZgNX5cNSWsrFUOhcaSti17ZBJRRyXEaekOIqFgfT9m8MFePXnquWFywM0LGfrOVRxw+T4lvtcuqyXA6PMBrjMY1yxSXPiQqUZ51tpPTBpmeLruLiGPKSSDJoTBzLmzuKJOFEUOWvKxY1+bfvPh3KqiDuhvl2GIs4KIk4QBMQdbD6SjGq3plSdWyTiwNM3A2lL92kXAWd8KHs7pwu46j4Aqb/p8ItyntxoNI63j/EuIw3+Itx1/SJcN6EDOL5RetDhAlZ8MXvfRGVYl8qI60mNyU8//XTOv9GGDRs2bNh4N8Im4mycNqDKI86aMm6dNeXplBF3jBR/p2QQcTMmlMo3g8f7RzEazd9RS/PhSt2lujszqTXlqawqSCZF+QYEyF/QLPW65OJGNJ7UZOcRSUTkY+QSXJyCKxO0eDTeibhWQmQoZcQJgoClRBW37Xh+e8qkmOTINC2FYarmDEQDSGZmlp1C6Mkg4vSC2lNSxSItcFlRoOAy4lJjhwhIaoCr7wcW32h859Taa6hVyrsoADhrSn/uwvjsOjbeqVlxGcmHS6O2mFlMMSKOKuJSVkJlE6W8OAAY7QPC4494LoQ1Jc3YzNXIoAWnoyJOrzUlINlTOlzsGlNXXGdYoZELmq0pewgRVzs/+3lfBZC2JY2HgZGu7G0sQFqRDFiriAtEydxWZ+NTLuRVFFFCX48tZRqUWBqwxp6yj9gvV5tQxAF8Ux83d/BYkBHn0jhWmCHiACkTMQ2T9pRWW1O2Bhgx2FgmEXE0I+5IT5BT33NofgS4dyGwxi/93/xI1iZ5cw45W8pKyaK5ENCYEzcwasyWEqKIkRCzAS410fRAv9d45qGvmQUo2YXDYLb3pGVASYYFprsYmHwe91DHUFi2VS/1ujCt2lwjrQzOmjKXIi7KKeKssKYEgDiZ6+ZTxGmaW2x+AOjYLi07vcBV96qf043LgbM+x9afuw0ID+Ef29plVeaU6mIc+cGV2HDbJbhuaQOw4T62/cIblN0pOEXcIAA2Jl999dU5/0YbNmzYsGHj3QibiLNx2qCiyA2PSzqlg8SOjSrXaOe6EZxOGXHH+igRxx8Xn9vJqeQOdOXvUKVEnF5bSoC3pjyVFXF9wahsNecvdsPryh9sT9UzbRrsKWkR2e/z5yx20uLReCbiwrGEXHB3OgRMrFBWEi6hOXHHB/PulxJppe5STk2hBrfDLRfMkmLylC6u0+wcI2oiap1KiSaqiLPCFo2q6sKCAHjL8dqFjwO37DJHwgFSx3s6ByYRLVjBnbemzF0Yp6pjNSuunT075WWt+XBpKObEcQX0lDWlw5mhGLQut8kqcEScATKZs6YclIgFvXa1uWCoGDnOEIzEEYwmAEiqICMF9+kTSiG4CRFXYr0tJaBRERceZkogh5snJijGQBFKrSlLveaIuHLyvQQJEWelNWVeRRw3jkzMfj4fKq3PiesLWpMRB5CmPiGOSEIa052C07SjBpBhb69WhE8m+KYJI7bM1J7SJBE3zCnizJMRnCIuRcQVuwXUpwjQaCLJNQrKaH4EePqrqd+1KP3/9FezyDiXwyVbMyfFZPYYUeh8uDRoTlyrOhE3SI5vpR7rz9AAAkjIq2UWEHHXON5AxcAu/snWTYqEJ8Cfz5rviR0OYM4V/GNiEtj7FPcQzYdb2FAOhw6lYE5w1pTaM+KsaDgDgATZj2lrysFW4CWSBXfRN9WvdWlc+r9MMTvSBfHF7+KPG47KT3/i3KnsWPcdBvYSRdt5X1HeJyE3J2AQDrCm0meeeSb357Fhw4YNGzbehbCJOBunDQRBUFTF0cmraUXcaZIRF0/wdmiZijgAmFvPVFYHNNhTDsdY5zAl1bSCu+GwKDfkZICqMevy2FKmQQvF7QP5zyut+XCARIoKKSuSQCyAeNJcXkihQEmMiRU+uJzKl6elTUy9sr11MO9+jVrQnS72lFQRZ0RN1ERIYqpYtFoRR3Pmwg4BmL4KosNc0ZoDVcUVyJ6yjVN05i6Mz6KKOAUiLpaIYW8/y7haVLNI12fJT8QRJUslKdqOQ3vKXqJ2MXIOT1JSxBFrX0uJOK05OeMM3RlkpxEl2/SaEggZirhCgBJxqoq4nv1suXom4FQpcHNEnPUkdCIpYjRFcAoCUOKxThFHm8wKRsQpZcQpEfp64CdEnEXHnI4RNSXmyKL6VBOQ4GTHt8JbYYm6U5PCJdApWUoCQHG1ZDWpF1XT2bJJIs5ya0qSEddUxq7L+a6JePFOIJO4iIWkxzNA5xNZ92qFzodLo/EsyDaAHc1ARLnBcJAo4ir0KOJGujBMlGpGGiDl9019r990PQKHmHGPkIgqHmPARBOKN8PFIx7OIlX5fDi/9n3nA1XEDWsn4qxSxCUcZA6jZJ1K4HV6ZUvyWDKGWIKQyqII/PM/gfRxnzAPOO+r+T+ArwK44i62vuW3KO7ZDgAo8TjxgTMJ8f/mzyHbh864FKhfqLxPl1cmtV1CEtUY0uTuYsOGDRs2bLxbYRNxNk4rUOJDJuJIYczOiJPQMRRGPKXamlDmRbFCcWhOPbup26eBiLMVcRK6A8TeS2PODs2Ja9NAxOmxVXM6nNz3MV5JJUoM58rXWtxYgXSz5v6uAGf7pQTDRByx+xyOjM9jpgW9AVKgNKAUUFPEUcsyKzLi6D4iggDMeq/pfXKgqi+TmTlKGInEZQsvj9OR91jzirjs8e7AwAG5CN5Q2oDqompdn4daU3YFcyjigHGfE2dWEVdZ7IY3pZYPROIYDscwSLKfKr0mrSmN5OSMM3C2lDrz4dKYPqEUDvcYEHFODYq4HkZio1YhHy6NAp/7I1QN53GZVnVQIoQSDIUi4gpiTUmPuVWKuBErFXEpIs7Bjq9VWYfUlUOVtKfXp4om5W3ywUIibjBEiCKrM+LKWNF/Vi27Jh5UcuEYast+TOVxLnM2k0ymirjiAiriivzMEldMAO1vK25GrT91KeICnRgh44kVRNwkoVd5A5VjbziuYffa7McySFU+H87CrFHN1pQRxMhwbZUiLknOzSxiOQOCIHBjBqc63PMkcOA5tn71fVI2oRYseD8wU8rkEyDiB+7fwYkEbljeiPJ0jmmwF9j+V/aalXlIPi4nboCzC7Zhw4YNGzZs8LCJOBunFWi2Q/ewdPNlpTVl1k2HhryC8YijfawAMFVBDQfwheL9XfmJiECUkXU0700rLLP3OsnfSfq8A/jzMRco2dE+mJ/g5RRx3vyFBFpEGq/2lG158uHSKPG65HNTFIHmPKo4oxZ0HBE3TslLLeg1q4gjGXFtJCOOs6Z0mi8C+0RW8QgLglwksAx+6+3QKKiStaGyKG/BfVYtGyMP94zIdrZpNPcaz4cDeFtAZUUcKUaNdyLO5DksCEKWPSUl6P3pnDCDOB0y4qgiTquSOxPTJ5RAcLGxciwUcapEXDfJh5swT31nBT73h8Ps85nNhwN4IiRCSDJLiTjaFKGoiKNZkyYVcZZZU1qXEZe2SHSV75Afawu0Yd2Rdab2C/DzXNVmvkFCxPlPPhFHFXF+PUSRAmLJGDqCTIXUUMrOH5qbekApN1XNBlXBupPLOcxUHY2OkSIO0JQTR4k4vx6iM9CJAFXEuU0Qcanv9YRYo7KBsj0qPc6heAiJZEJxuyzQMYQiRfiJoshZUy5u8GvbrxZwRJy6Ik6MhwqiiEuSjLh8ijhAZX4RHgKe/S+20ZmfASafo/1DCAJw5Y/kz7LAcQyfcq7HJ8+byrbZ/Bv2+eoXA9Muyr3Pcp6IS997ZGU02rBhw4YNGzZsIs7G6YXaAltTcoq4E+8AT+XPKxiPOJojHy6NuUQRt78zv0KNEnGUxNAKSt4FYvkVeIrQmCFRSHQRIq5WY9HYlDWlhowLSkCNVyKudYAq4nL/TpdOZsWTbXmIOEsUcacwEdfDZcRZqIiLW6uI85FiYbjIb0xpkQtcDpr11pRtA9oUnfLHKfbIpFIknsTxjEyc5h5CxOnMhwMUrCljYWA01e0uOIFSQpKMcyKO5hwaIeIAYKKfFb+O9Q/JneUuwWXISpnidMiI67JAEVdd4oHHy8ZKr1AYtQlHxCXGuSKOKLbLfObVRB6XA0VuKXdWFKzN6UzDRwrFeTPiylTIkVygGXED5sfiWCIpkxkOAajUY++ngLoKH1zl2+CpfpW9RzKGNRvXmCbjuEwtVSKOkJMVk5W3yYdMu2GtBIkChkLsHDariOsY6ZAze2uLazmVUV5ryolLsh8TnMCld2Q9TPd70qwpAT4nTpWIM2pNmUHEWaCI+2H8RkSEjPHfXaR4jAHAITiMqeLUcg9Tj7f2h2QCuKLIzTWEmUbJBCBl94jRXiCurNyKxyMQU0ScS3DKFpFmIZKxWtBJxMljxgvfAUZSar7SOuDSb+v/IFXT8HLdp+TVWz2PYbpnUFqJjgKbH2DbrrxZIu9ygWTv1QmD6B+V8tIfeOCBHC+yYcOGDRs23p2wiTgbpxU4RVyqeEcLY2atKbmMuKNvAJk3HSp5BeMNx4kibkqVMunRVFUMn1saInpHIpz1jxI4RZyBwiZ9jeGMOB0ZEoVCF7Gm1K6IM2FNqcFWjeadjVcijv7d+YiMpZP98vK244M5t6UWdLoUcd7TxJpyxBwRN8nvk++/O4bDiMalIhq1LKOFW6Pwdu2WlyMlKl3ZZlBwIo4o4vzaikacAiCj8Lizd6e8vGiCvnw4gCfiuke7+c7vsnrA4WTr45iIC0UTCKTIDLdTMFwInlTBvpMj/V3yshXZT5zKJX5qWlZTwl5rA0kmBEGAx8vO43DIHMGpBqpMGO+KuAC1prRAEQcQMsTB/vaTlxFnoGGiZAKQ/ryRId4q0AAGiBquqsQDp0n7z7oyH7wT1kNw8ORVOBHGfVvvM7VvSlqMxkeV1SLUmtJvkIjzlUvHGZAyvtQUSBrAEUUmiThqS0nz4QBgJrGmPNIbRDyRZE+GBoCW17N36KsAFt+Y9TD9PWTZq9LzreBEHFEptW0BEtlW6oMh49aUlIgz4kSSRnnqe30qeT5+V/m1lCWqIP1/9f2KxzgNjijSev279A6J4KMghN8OLh/OmnxGGU4XUMKsu2VCKwMR2mzmMN9EkYZIVIRaiLgsO9vWzcDbv2cbvO+Hkg2qTgTCMXyj/UIcSEqqVJ8YZiq77X9lhHXFZGD+dfl3yFlT9kMUgf5gFF/4whd0fzYbNmzYsGHjdIdNxNk4rVCXoYiLJWJyocYpOE17vPM30Wr5Dio5BuMInCKuRpmcdDqEDHvK3Co1mut20jLidGRIFAo0a6dOo7KAEk/tg6G8Vh4DEe0ZcUCGIi46Tok4oghqUiGH01ja5JeXt7cO5DxenAWdDiLuVMjV0wKztn5el1O2qhNFoGNIIpyoUoLaExmCKMLXzhRgoSIL80DSKDAR1z6onUhOg8/EYePrYHgQx4YlVYTb4ca8qhxEggpqimsgQCpe9YX6EKN/c2bxnCpUBo+bUk9YjUwi2WhBbhIhR48PshwcLeNnPnDzglM0O7abI+KM/55FJ7u+DAXNNT6pIa81ZWgQCKTIIqeHt+nLREWjpKoBpNfE8hdG9SBgsTUlwMgQwcEIEtNjMAFn65dJYiTiwAgjsg0p4gSBH48HzNlT9pIsouoS8+rs+gofBPeg4nOdwRyZUhrgdrrl8zchJpSJTiusKQHL7CmHCVFUYdKasm2E5MOV8qqoiiK3PGeOZqrEN/8GSDf7Vc9iRG6oHxjOthfkMuIyVZ3UmrKQGXGARGSl7VujI0DXrqxNOGtKE0ScEScS+bVErbvecSFwyy5gzaD0fw4SDjCoCF98o0TwqRB+BcuHS4PanKrkxNHfptciW0oAgF4ijh7fyDDw9M0AUvc8s68A5l9r6GM8/k4bBiPAt2KfZQ/uewbY+zTw5s/ZY+f+h0Re5gMl4iDdo/bmaeC1YcOGDRs23q2wiTgbpxVotkn3cCTLltJsVx3tsgyp7UvNcmMc4ZiGjDgAmEOJuM7cRBxVxBkh4jJv5gz5yqt1t47hd9LN2ahpK45VFLlR4pGKgaPRBHdjroR+Yq1T5dOQEedhN7JUITaeoEcRN2NCKcq80o1h70g0p4qQKgDfjdaUnK2fAUUcwOfEtaZy4miB1nSIfe8B+EhxN+K2rqgso4IUNAdbgWRSfVsDaNNhrZoGbXQ40MWaD6gabm7VXEPZJG6HGzVFkrJQhIie/oPsyUwizlsGFKdUiIloztyUsYZZIjmNScSasn2YEXF6yHk1FLmKZNIznAgjnsxWPYx3dBMl9wSD1pSheAgxSOexKDrQ1e/M8wpjoL+HaELBVqxnP1uunpW7iOh08/MDi0l6q60pAaJKEtjfbqUijh7fLBIj2A2IKaK+uAYwOlZXWpcT1xdkn9FsPhyQUiXF/YrP1ZfUKz6uB3mJC6qIqzj5RBxVbJlVxLUG2N+WqYgDMppT0jlxkRHgrV+wjS68FWhYxtbbNmfth6r0T6oiThDy5sQNEMWhX5c1ZZfl1pQAnwmoBZkqT81YfKMq4ddMFHGLrMyHS0NDTlyUEHEeh3VEnNPlQSKViewQ44oqSYoiohwMPfpJoHuPtOLwAFf+KL9lpAKSSREPvimNu2+Lc3Gw4f3syYc/Bgy0SMuuImDpx7XtlFPESb+xvhFl208bNmzYsGHj3Q6biLNxWqGWWAF2BcKSjUMKZm0pgQwLDofSz0cALv4f0+9TSCSTItdpOqVK/bjMqTdGxBmxpnQ73XJBPyEmsm+etcDnV9ixer5BIdBlQBEnCAIadNhT9kd0EnGEgBqPirhgJI6+lL2U2ynktfR0OAQsofaUOXLijCriOCLuFLWmHI3GEYxKRVOP04HyImOKDKWcOJoRZ9qa8tAL8ImMGIsoFdfNwlfOxodEBAj2WLp7zppSoyJOzZqSs6Ws0W9LmUZtMbNf6h4khdgyBTu5cWpPaTbjMA2qiOsKsvHTCiJOEATetlprTs44QreBbNOsfYx2y8tirBwtvYU5DnkVcVw+nAY1aQHP/WFqTem1RhFXrqCIK1RGXNY8zKwtZRp+mhNnkoijijgTY0QagiCgePRqZPaC+Zw+3LzsZtP7z2llK4oWKuJmsGUTRNyQhUQctaZsLMtukFPMiXv794w8q5wKLPw3oOls9qJWBSKOqI6yM+IoEVdgRRzA58S1ZhNx9Pj69RzfQAcCxIb1pBFxWnIPdSCZFLGrnc25C6KII3lm6oo4Nq6YbjYj8LidCIMQe3nmCxxxz43HInD8TUOf4dUDPWjpleojZT4XJt3wQ0CpRpKMAfv/qW2n5JjWC0wR99RTTxn6jDZs2LBhw8bpDJuIs3FaIdOakmaNUZ91oyhykABwQQC8ft5rHiIwam2B12p0ByIIx6Sit7/YndNqhiPiCmxNCRi0OEnjxDZgQKHYcOGtea1VrEIiKXKFYz0KDkp2tA/mvpnlMuI0WKtxRNw4zIijtn6T/EWaMl6oPeW24+oZM5R4NJoRR0nmUwm9AVZIqCn1GFYENxFiqTVFxFHbHtO2aAefh49UPQtGZBTQnrJdh6IzjVlEEXekh2XiNPcwm87FExYb/kw0J66TFEAVC+inABFnVNEJ8ERcd3y7vLzxxEasO7LO8H7ToKoA3deucQCq5NaabZqJriBTtSbjFTjSa9BiOg/yEnHdlIibm3+HBTz3RwgRV34KZsRlKQ5p1pgZIs5CRRy1P6susUa50uQ+DxDZ9bKuuA5rzluD1dNXm943/a6yiIvRPlaY95QpN5dpRdU0ttxnjIhLJkXemtJCRZwiEZepiIuFgI0/ZRucf4ukcG0i2WtKRBwlkzPt/8ZSEQfwn/X4W8hkeA0p4kQRCPCKOCMNkGnQ73U4HNflSGK1NfOR3qCsJK4p9WJiRQEcEqgijjYXEESS7HvxuCwk4pwOnojLY4dMaxejdA6fjBnOP//9hhZ5+UNnNaGkshZQ+huTce3vQY5pLSHili9fbugz2rBhw4YNG6czbCLOxmmFUq8LxSmLv3AsiZ4g66qzRBG37xl5edThAD70Z+DWg7zi6qXvA/0tCq8eH6C2lFOqcx8Tak15oDOAZFL95oxTxBkMDedy4qI6i3ibHlB+PG25NgboC0aQPkRVJR54XdqtuRr8OhRxYROKuHFIxFFbvyaNtn6cIu74oOp29O81rIg7Ra0pqa1fjQlbP14RJ52blCwz1S0cDQLHNsBLCj+KuTlWgCPizBV/KUajvKJTa8YWl4mTSOJY/yieOfwMNp7YKG/TF+oz/LnqShgR1zVKcp1OISKu1yprygppfHWVb0O06G358dH4KNZsXGOajONULqdYTlw4lpBVEC6HgCo99mgE9BwTYxVoGwghHLM+b9DtZEVjRWtKSsRNOLmKOJoRZ5UiTikjjhbDzcJLCrLZijhi42aVIs5kU0R67AWkhhMrUFEehOCQrkklLj9e+MALlpBwQB5FHD0W/iZDtnMyLLCmDETi8py2xOOE22m8bCCKIpcRp2RNyavER4Ctf5bsUAEpa+2MD0vLjWexF3VsBzIsVLmMuMz5xFhmxAFA3QKJVAUkG8SMuQe1oq/UmhEXGQbiIcsy4jwuB4rc0v1KIinKTgpaYKqBUgE72wfl5cWNFaYjJRTBWVMqK+KiCfa9eM26PhC4XQ5dirjiIdb8EMxsUjSQf36oO4DXD0r23A4B+MS5U6UnQioNjVrfo7QWEKTzsVoIwIMYekeiaGho0P0ZbdiwYcOGjdMdNhFn47SCIPC2dieGB+Vlap9hCO1bUbT5t/LqaEk1MO1CaeW8rwJ1C6XleAh45pasrsfxgmN91JYy9zGZUOaVbwyD0QSnXMoEJeKM3hAavqEL9gK7Hmfrc69iyye2GfosRmDG3kurNWU0EZWPjUtwaVIfUgKKWjWOF6RzxwDtaqIlTayTec+JYUTiyoUD+ve+2zLiKIlhxtavkcuIs1gR1/I6kIjCR0j+rA52q2Bh8ZfiBBkXJ1ZoU3SmQXPiHt6zFmveXAMR7Fj8dNtPDZNEnDVlhBRZyhUKI5SMGEeNJLw1pfEie5HHicpiN7wT1kMQ+HzAcCKM+7beZ3jfAD+/ONUUcZn2nw4d5y8FR8TFKyCK/HwjJ5ofAe5diIteuQ64d6G0roL81pT72LIma0pqk3g0//Y6EAjTjDiLibgCZcRRNVFWRlwhFHGmrSlpRpw1yhVfEcuRLHea+DsVkFM9S69LZvLhAF4RN9BiKBfVSjXcYGRQ/nuLXcWo9Gar0agi7njPIMQNZFxeeTNT7ZTUMOvNRBTo2MHtR9WaUhTHXhHncPJWmsc3yYvxRFIeIwRBR45kijyyKiMOMG5PyVlT6smIU0FzG2ueW9RQAFtKIH9GnCgiWkhFnEgVcSr3e4kY8NztKN7H5n/BzEgMA/nnf9x4VF5+z7w6NKXrAGr70voeDidQypq/aoVB7h7Ehg0bNmzYsMFgE3E2TjtQAqQjwCb0pjqGIyPA459FMemQC3mImszpBq6+X+4Gw5GXgR1/N/5+BcRRooibWp37mAiCoDknzmxGHMAr6QIxHXaAWx+Ucp8AYNIy4KzPsefGkIij+XC1Ou29KAGVi/Ckaji/zw+HkH8Yr/CcQoq4PORwGlUlHvn8jSaS2HNCmSwzrIjznvpEnFW2fk0KijhaoDWVEXfoeWkfpHHBUD6kFhTImrLVgC1lGrTw+HTr77O6982QRNSasovkpZ5Kijje6tdcV/okfxEE96Dic51B5a54rcipchnn6A7Q65bxcYIew2RMuuYc6dGgbG9+BHj6q8BQKwSIwFCrtK5CxnFEXCKjYDzaD4ykCEGXjz+v1VBIa8oIJeLMERlpVKSzPguUEUcVzrkz4kwoHTKbIkw0rvXSjDiLrCnhZnmHPnFijg31I2fD2RDNh5sMUyiqZBlo8bAy4ZAHXD6cQaVsGpm2lEpKp4pit3wPt1p8FcJwSo1TMgFY9gl+Yy4nbhP3lKo1ZWyU3Ss4vYDZBk2toDlxJNeLHt9yn1t7E0+gE3GwrHIBgulmU46IG9VBxFlsTUmJuILkwwH5M+KScdCZmMfKjDiXAxHkIeKGTwB/XA289QuUkCa1EP3NGMg/HxqN4fF3WDPFp1ZOZU9eeoe0Twq970GOay0GuCYJGzZs2LBhwwaDTcTZOO1AFXHdIxZZUz77TaD/CIrIhDir2Na4HDjni2x9/e3AyPjLizvWzz735DzWlABvT5krJ86KjDhK4NF8v5xIxIEtv2frZ98ETFrC1rt2Z9nWFApdRBFXp1cRp9GaUm8+HMATUOORVDKiiAOAJVxO3GDW85FERO6GdgkuXWMAp4iLjL9jpgWcIq7MeBFtYoVPLhBJGZMJhBLEmtJot7AoAgclIo5aU4bjYV0ZJZrhJwoDC4m4NhNEHLXiGkkoXy+MkkT1Jawo0iWSwlqZQmF5nBJxVllTApJaUYz5FZ+jx8oITuWMODNKbm4/o4y8EOMpIq5Xw7F48c7sYmQspJpN43GysSxLEUfVcDWzpC79fKikyqGjlroZcNaUViniirOtKQtFxGXZ+lEiTmkc0YoiP5BWqMdDwEh3zs1zoRCKuLDAxlwxVptjS/3gFESZxMUgJeJMKuIA0/aU1DZRJoANoi2Q25YyjVl1pXAigf9wPsUePPfL2SRBLiKOKOI4MjlTDVcI20MlTM7IiUthMGTAlhIAAp2cOqrUU6qpKS8Xysn3a1QRF4ybu/bFE0nsPkEUcYUi4mgzkhJBHQ8jSs4NU/brGfC6HAiDfNeZDhBHXgF+dYF8TheLTMka9JUBECS17NX3684/f/jt4wil7KLn1pfh3OnV7MnFN0r7rGgy/h5l7LjWCQPoHYni85//vK7PaMOGDRs2bLwbYBNxNk471JGO7r5RVkA33C248zFg+1+lfZAJcUjJ1/2S/2ZdrKEB4LnbjL1nAXFMhyIOAObUM0JCTREniiKX6WYFEUeJvZzYvw5Id80W1wALr5dusNMFiGQM6Npl6PPoBVUW1OlWxLHvon1AvauUy4fzasu3oOqu8WhN2TbI/l49RMbSyYyI3N46mPX8YJg9VuHVlzVBVYTD0eHCEEMFhlXWlC6nA/XkfG4fDFmjiOs7JOeluDylcDmkQpAIUdlyziyowoAqD0yinRBxDX5915lZpNHBmVAm1o2SRJw1pTNFSJRMAFwKpGz5JCCtNBrtBSI6FMkFBJdzaDL/qcHvQ6Tnsiyexef04eZlN5va96lsTdlNVId6ldwU1JoyGZeuOYe1KOLUMmhUHs9pTak3Hw6Q5gvpa2QsKFldW4RCWlPCwf72okySwgRoY0Vua0qT2T+V1mR2UkWcVRlxQzH2d4ZHq3NsqR+cgiizoY9el8xaUwKmibghC60paT5cY6m63d2s2jJc5XgTUx2p8cTnB876bPaGjZSI28wR6KqKuALmw63d1o6Vd7+Eabetw8q7X8LabeS30rAcSM1v0LNX/hwc0alHcTjSiWGinjOTDye/v1FrSnI+h9RsFjXiUM8IwjHpPntihU9z3q5uFFUC6YaOyLDkekMRjyBCbhdo84dZeFwq1pTJJPDaj4A/v1+agwGA4ETJghvkTYOzLwfWDAK37NJNwiWSIh7cyMbZT6+cmn1PtPhGad8G34Mq4uoESRH3wAMq+e02bNiwYcPGuxg2EWfjtAMlQAZCrJhoSBE3cAx45uvyqmfhjXLXYSwZyy4CeUqAq+5l67seAw6s1/++BYIoijjWSzLitCji6hk5pkbEheIhxEWp4OR1eg3ftNDvSDMRt/k3bHn5p1iGxKSl7PH2rYY+j15QRZxei6+aUg+8LuncGg7HMRxWvhHmiDiftkJCmadMPm+DsWBhSA4ToIo4aoOYD0sn++Xlba3ZQeOUdNRjSwkAbqdbVhkkxMQpZzcHZNr6mevobcrIibMkIy6lhgMATF/FF88KYU9ZkaGIs4hcpdaquq0piSIu1H0ZBPCFETMkEUfEuZxIAuq5Tg4nT1SazG2yAqIoWnoOT/QXIRGczYkgJpZMxJrz1mD19NWm9k2vXYpNOuMYnKWyiWPcFSQZcSlryie2tmcXpSk6d6mrUlSyaSgRF01E+Se5fLi5+T80IL1/gXLiOCLOa5U1pRtAAoIgKRscggMeh3WFYi4jjiriRJFXj5SbtGyk9pQGxxtRFNEXtF4R1x1miunhYWtzxDgb25yKOJPWlIClRJy/yDprypyKuNpifMn1JHtgxX8AXoXmvtp5QLrpb6SLU7lrVsRZhLXb2vHNx5rRPhiCCKlZ6fYndrJxz1MCTDyDvaBtCwBgcJSNX/oUcV0YoYo4g3EAFOWEiBvWQcQZzvZWwJjkwwGpQD7S4DTSxT8fjyDqKIwizuN0IEytKeNh6bz8+4eBl74LpBt+S2qBTz6FkoWMiDNzH/L8ni459qCy2I1rl5hspFACUUnXpxRxy5cvt/59bNiwYcOGjVMcNhFn47QDLdYNkS433URcIg488XkgnTFVORXC6h/z3X9KBbeZ7wEWf4itP/P1caMuGBiNIZDKLCn2ODV1D88mio3DPSOIxrMD3ylpZuaGkGbEabqh69oNHH1dWhacwJmfYc9NWsaWT2w3/Jn0oJsraOojJwRB4Owp21XsKY1YUzoEB9cxO55y4obDMbnY43E5dCm35taXw5MiL1v7Q1nB4PTvrPDqv6mnys5T0Z6SVwqYKyQ0ZuTE0bHPsCLuECHiZr6HL55l2vVYgSI/4EvboYWBoDXWwWasKct9bkyskP7uyOBSeB3sGNQW15oiiYpcRfJ5HxcE9DscuVUs48yeMhhNyN3xPrcDpV5ziiIpI441MsypnIN/3fAv0yQccIpbU1JFnEEFQiwRQ1+4DwAgwAExzsbOrKJ0Gp07gQevZoVHDoJqNk1Oa0ojijigYOd+IMI+n5WKOFfFO/K6KIr4Z8s/Ldk3kMOacrQPSBOf3gplckQP6DEfPGpoF6NkjPC6HCjxaLAizYOhyBAGo9I8S0y60DtYjGTSOkV8TvXsELFMHgeKuMEQm0NU6CGKFECtKRvL1BVx50TexGyHNFaMogg45yblDR1OoPFM8gZb5EVq1crNJUJEEWchEffdZ/YgmuDHsVAsgXvW72cPNK1gy6mcOKqI8+tRHAY6ECBEnFEXEgrDijh3DoWnTjS3DcrLBcuHS4Na61LLXQCIhxEpkDWlx+VAiBJxrZuAX18EHHiOPTb5PODfXwemns+dy2Yy+P64sUVe/vDZk+Fzmx8rs0Az4oQBRBNJbN06No2wNmzYsGHDxqkEm4izcdqBKuICURNE3Gv3sNwBwQn82+8AX7m2SfHlPwCKU3Y2w23Ai9/V994FwlFiSzmlukSTVV+Zzy0TRPGkiBaFzJdAlBGNZm4IdSviNhPLi3lXARWkyEwVcSe2Gf5MetDFWVPqv3FrqMxPxFFFnFYiDuCJqPFEKrVl5MM5tIbVQ7qhpV2z2zNy4swo4oCMnLhxmK2XD1bma1GlYusAr4gzVKSIjgJHN7D1me/hC8CFynWkKgOLcuLSXcYA/xvWCtme0hFCOCnty+v04vkbnjdNElFVXJfLqa6IA8YdEUfVcDWlXl3Wskpo8Pvg8PTJ67lUGXphpSpgrMETccbGie4QyfhKlAHgi3xZRemOZuDBa1hh3OkDSiaA0R0ir1ggyGlNySniDBJxBkkhJYwUwJpyc88L8NWz/CwRItZsXIN1R9ZZsn9VNRFnS5ljHNEKqogzOBb3ZTSbmB0jAKBliBWsk9EaJJICeoPWXY9Ux4rwkPQPAJxeyUbYLKpnsOX+FvXtVGClNSVVxKkScaKIqbt/Ia/+OXkZErnmbio5cXQuwRNx1ivi9ncG0BeMKj53gswNMJkScVJO3ABRxPl1WVN2FZSIU3PkUEKJy7pr306iiFvc6De1r7ygRFwgI4c3HuGIOKutKWuEQfbAG/fy1rznfQX45FPy9c+KucXejmG8dUS61jodAj62YkqeVxgEUUnXIdulxIYNGzZs2LAhwSbibJx2oEQcJcpox3peHNsIvPZDtn7xt+TOS9r9p2pBVVINXHE3W9/8ANC6RXnbMYTefLg05tSzm7x9ndmEhFVEHFXTBaN5bjhCA0DzI2z97C/wz088A0jbvPXsBfLtzwJ0E2tKvRlxAK+mocV9ioEIu7nRak0J8ETceMqJ42399Oc4Lm3yy8uZ9pQcEefzQy9OdSIuk8gwA3putg2EzFtTHn0dSO9jwlzA38Q1OYQSBbL344q/5u0Xw7GEfJydDoHL0tOK2bXSuJdJEqXtZM2grrhOXu5yufjiUybGMRFnlkgGgIkVRWNCxJ1qNrackttAAwnA21LGo8p5RXJRumMH8CdCwnkrgE//E7j1EE5Meh97wZbfKe7H7VSxpgz2MpWru5j/redDAc59URQ5a8pSi4i4P+z5JQRHnHssnAjjvq33WbJ/1YYIqhoxa0sJZNiBGhuLezlbSmuK5TwRJzUydA1ZR8SpZsRxtpRNgMOCW/RMRZxOO+Zhi4i4SCKC7lGJrHcIDkwqUSFyDz4PV/dOAEBI9OCB6BXcHDELHBG3WV5UJZMtzojrDoTxmT+q39v5qYqQEnHtW4F4hLf+1GVN2YnhcaKIo/mUZq590XgSezvYvWRBrSmBDCKug38uHka0QIq4ud3PYblwKPsJpw/44F+Ay74HkGucFXOLP2xgY9oVC+sxya+/YUwTOGtK6bdWU1untrUNGzZs2LDxroVNxNk47UA7usMJNmnVrIgLDQCPf57ZJU29ADj/FvlpThGXa1K86AOSTSUAQASe+goQV+6aHCsc62Ofd7JBIu5AV7bNJiXizFhT6lLEbfsrkCZa6xYCU87jn/eWAhPmSMtiUrLBKiDiiSSnQDJCfFBrSrXig5GMOACo8LCb2vFkTdlKlH9NBtRES2hOXIYizqw1JUfEjSMVoRYEI3GMRqUMIY/TgXKTReCmKmJN2T/KdZkbIuIO8raUQI4CsJXIzIkzCUqY15f74HLqn1al7X8LQRJRIq7b6TylrCk5Is6C7KfaMi+cHjZ+1pdYl5FilX3UyUCPBdaUXaOMiPNCWWkyyV8k2UQ/eA1TpngrgE/8A2iUcmQ4Im7fM9lKBeRQxFFbyprZ+ogM7ty3Jh8xEk8inrI09Lgc8LqssQLrGs0+JgDQGVR+XC84NRGniKNEnNWKOGPHnCriqkssIuKGCREXkVRpn/zDZvWcQ53grPzoWDFEiDgrbCkBSfWVtmOOBbOzsPKAWieaIeJOjJyAmNK71hfXc2S6DFGUnEhS+FviUvShAge6ctwLNBBrys6dcsOdujWldYq4UDSBzz34tmrTHCDFATy5PXXelNYCVSmFYiICnNhuwpqyk8uIO5lEXM7MQx040BWQ7T2bqopQadHvWRVUcT2GirgzD/8ULkHBjrm4Eph3dfbDJm2v+4NRrN3Oxu7PrJyqex+aQYi42pTq708vjI0jjQ0bNmzYsHEqwSbibJx2KPG6UJbKkhEFdpOuiYgTReCZWyQ7SUC6UXv/r6UsghS4jLhYDtWGIABX3Quk37dnL7DhJ5r/jkKAEnFTq7Vbdc4hOXH7O7OJOEqaWaaIy3XDkUwAW37D1s++STremaD2lO2F9anvC0aRjhGpLvHI2WV6QBVhqoo4AxlxAG/NOBQdP0ScaUXcZHYMdrQOIkGyXExbU3pPXUVcpi2lWcuuTEUcLdAa6hY+9AJbnvXerP1wBWArwVlTtqpvpxHtJvLh0phVl1LEuXvlxyaXTVbbXBd4RdypZU3JNTZYoIhzOR3wFrHxs0SwrlP7VLWmjCWSsq2aIEBTbqwSqCLuzMZpcDv58abI7cT3zokDf7oWCA9KD/oqgE+sBRqWy9sFS6cAk8+VVpJxYOufst5LlYgzaksJAJXT2LJF5z61dyszmW9IUV+ibNmp9rheqGbEcUScBSS2n5BNQ23SvE4n+kaoIs4a1QqviJOIuP5gVDnn0ABUFS6ZijgrIAimcuKssqaktpSqTSZHXwfaJFVbXHDjgbhky3ywO0fGdpGfZUGKCdmGnubWqhNxxhVxyaSIrz28Dc0pK0WHANx04TQ0+IsgAHARi/VbHt6Op3ekfjucPeWbnDWlZuIpEgBiwfGTEedSIZZ1YgeXD+c3vB/N4BRx2RlxhVLElYRVGiYUmk4A80TnQ5uPy9nuixoqsGyyOQI6J4oqJVtdAGVCCCUI4YGf/F/h3s+GDRs2bNg4RWETcTZOS6TtlQQHu0nPS8Q1PwL8cBqw+x/ssWt+yueOQYciDpCKvpf+L1t/7R6gZ7/69gXGMS4jzqg1ZW5FnCkizsOIOLrPLBx8nhXLfH5JfaiEScvYcoFz4ro4ey9jqoKxyogbT4q4NqqIq9JPZEyq8Mkq2GA0gUPdjBR+N2fE8epM8928deU+ubjeF4wiTBRrtOilCX2HgYFUsdNdIhfeVbvYrYTFGXFtHBGnn0gGWEYcVcRNLreIiCshRJzTlUcRl6FQSSp0bY8hrFbEAQDc7BgLiRpr9olTl4ijx7i6xGtI0Qnwirjzps7Aly+ZKa+7HAJ+ebGAizd9jpBwfuATTwINy5CFsz7Hlt/5I5DgbRipOiGWUFHETZir7w+oaIJsZT3UZol7QaAA+XAAcPOymwGR/558Tp/0uAWgCmd1Is4CRZynhOWgJeN8Bp1G0Gwuq6wpjw4dlZfTijhAIefQIFQVLkPkelRhzfgPwDIiTpd1YgbaAm3ysmo+HFHDHWm8Dl2QiLKDuRRxANB0FltO5cR5XSpNPRYp4u5+bh/W72Zj3neuWYBvXTkfG267BC13r8amb12K2akGm6QIfO3h7Xh2Z0dWTpwhojMgvW+AkH1lbvNEXLlRIs6tYrWqE1w+XKFtKQHeXldBEVcoIi5UpNIwUaH8u/C5fBBS16ZwIoyEjoaFWCKJP7/J1MafXjnVkhxNVQgCpzSsFQax9vfWWCbbsGHDhg0bpxNsIs7GaQk5n4sQcbTIm4XmRyTrSHqTJjgBBcWbpow4irNvYh3fiSjw1FdPWoGTKuKm6FDETZ9QAmfqpq9tIISRCF8YK0hGXK5i5uYH2PKyjwMelQI4VcQVmIjj8+GM3bTx1pT5FXHVvmrN+x6vRFxrvzlFnCAIWMrZU7LjY6k15SlGxPUEWIHSbD4cIOWfsVyJBBKiNAY4BSdcDp1FZmpLOf0iIFU0U1ViWAnLiTh2/jYYVMSVel1SJ30BiLhaHyskd7ucubOdfBVMJZCIZuemjDGszogbjY0iIUi/Y1F0IhwyX7xM41TNiOvmbCmNH2NKxNUV1+ELF86Q5wwLcAgXbf48EE6Nx2kSjl6fKeZdDRSnSNLhduDgeu7pgijiXB5SCBV5m0CDGOGIOOMkRiZWT18Nl8jUPGXuSqw5bw1WT19tyf7VFXGEKCuzgIgDeHtKA5agnPLbgutcLBHj1FtpRVwaJ3LYEGqFKmlfCEUcYIqIs8qakh5TJSKufGgv0PKatCI4MXrml+XnciriAKDpHPJGkqKuyEnyZul9mgUZcX/ddAwPvMaO42fPn4aPnzuV26a61Iu/fm4FZqbyXxNJEV95aBtej7IGBbS+hcEgIwn9xRqJ5NR1ebwo4kpc1jShNBMiblHjGBBxeTLiqDUlveaYxf6FX8eomPFdu4uAS+9Q3N4hOPQ1AKewdls7zv7+C+hMNYmWep1YvdiCbM98UMiJs2HDhg0bNmzwsIk4G6clonGpY0xwalTEvXgnkKnAEBPS4xnQnQXjcErKunSxuvUt4M5K4N6FEgE4RgiEY3L3sMflwEQdqi2vy4npNez4ZebEUWtKMxlx9LWqGXG9B4HDL6ZWBL57PhP1C9lx7zvICoEFQFeAKOIMFjTryn2ypU1fMIpQlO98jCai8nFxCk5dN9+UiKJKsZMJURQ55Z+RjDgAWNLEOptpThz9O2lGnlZw1pSnWEZcz4i1JAYANKWJUgcr0nidBmwvD2XnwwG8EkNTk4MRZBJxoqi+rQZQC1mj1pQAMLO2lFfEWWVN6WDffZfbLalQcmEc2VOazdzMBC0Gi9FKdA1Zl9lqiT1X8yPSvGCNf8zmB92cktsaIq62uBY+txMzJpTgDOEQ/uy+C0L62ltUCXzyKWDSEvWdubxSg00aW37HPa1IxImiOUUckHHut6huphVUEVdqoTWlKIpICmx+dMu8X1pGwgE5sjqtVsQB2SpcrUj9Vu54ZyXe8HwV1zjesEQR1xpoRUKU5l3JqB/IKJhP8hsf49NQbeYrREYcYIqIG7bImrJtJLcibsqxR9nK4g9iysz58uqh7hEkkzmu05lEnCiqqzpNWlO+eqAHdzy5W15/z7w6fOtKZdJ/QpkXf/vcOfK9Uzwp4jNPDyDqrZQ/S3nwqLx9pVbF4UhaEVc4Im54jBVx4VgC+8l95cKxUMRlZsTRuWAiWjBFXN+0a3Fb7HNoS9ZAhCD91q++H1h8o+pr9Cru125rx+1P7MQAIdLDsSSe3WlNjmhOkGavWgzk2NCGDRs2bNh498Im4mycdli7rR3bW6WiD7WmfHVfjkL6UJvmxykRp7lYXLcAmHVZxr5bgae/OmZkHFXDTa4qhsOhr3hO7SkPZNhTUkUctZfUixKPhpuNzSQbbs77+OJZJtxFfGd8xw7Dny0fujhFnDFrSqdDwEQ/e21mThxVw/m9fjgE7UM4JaLGiyJuKBRDIKWuLHI7UWUwnJ0q4ra3DrL9k7/zXWdNGbCWxAAY0SQI7OaeFrw0IRYCjr7B1lP5cJn7KpgirsgPpEnpeAgI9ubcPB/aLMiIA4BpExxwuKTiugMuLtvNDOri7Lvqcjoh5iMexxERZzWZTO3RkrEqnBiyjuylxUhDqoC0Kn+oFbIiawzmB5Yp4khGXF1JHdD8CB4b+RTWeu5AuZCaexRVAp94Cph4Rv4dLv80ZKvIwy9KdrYpUGvKaCJFpgZ7gFCq+95dYozI4NRZR/W/PgMBmhFnoTVl92g3koJEoIoJH5Jx65SdQHZWpyiKUpG6EEScEUVc8yPSb2OoFQJENDp6cbf7t5jbvT7/a/OA5sMhVss953M7cOvlc0y/h6o1JVVo+0++NWU8kZTnZ4JgTtVJx96m0ozfZscOVPe/k1oRgAu+jsoSj2ypHY4lVR0iAADVM5nNZKgf6DvMzSX4jDii0NFpTbmvcxhf+utWOYd4YUM57v/wEln5q4Tach/+9vkVmJqKAoglgNdCM+TnZ4V3ycv+ovGliMs7V0jB4/TIrgjxZJyNyTqwp2NYPq7TJ5Sg3EIFsSq8ZUD6fjUe5knaDEUcveaYhcflwFPJ83F+9H58vHE9cMuunCQcoF9xf8/6/QjF+EbOeFK0xFo3L4girk4YwCW3/S7HxjZs2LBhw8a7EzYRZ+O0wz3r9yOeFAGInDXlz19UIdsAoFjF4k/Bs91w919Hc/ZjsZCi6q4Q4Gwpq/RbAM6pU8+Jo0QcJS/0IlMRl3UjGAkA2//G1s/+fP6djpE9ZbcFGXFApj0lf37RfLgqnd28lIgaL0RcJolhNLtgcWMF0rWQA90BuQDKZcT5/Lr3e0oTcRZnxAFAU1W2Ik53PtzRN5j6uGYOV3Ck+yoYEQdYak9Jf6ONfmMZcQBQ6WcKFy9q4XQ4TX2uNMpGB1GUskIOCUAglsfmq2oaWz7ZRJxFJFEaxwPsu05Gq9E+aF0OoWlrSiVV/hjMDygRZ7SBJJ6MozfECO3aw68DT30Z5Yl+pId0EQDO+wowcbG2nVZO4ZuX3vmDvKioiKNquNq5gMPA7Y3FJHQgUhhrysNDjJRMRmo55Z0VcDp4u+FoMgpEhoE0aeQqMpWvxYFTxGkYixNx4NlvZtnGFwtRzNj5Y9Mfp2WYEXErp8yXHQoA4KYLp+O6pTkyNjWCGyvS6tlYSCKTAckWn9rmmQUl4jp2aFbbDlNrVa8rJ+GUC6Ioon2E2ZpyirjmR4DfXc7WG5YDNbMAALNqSfNfV47rliAAjWez9bbN3FxCJuJE0XBGXPdwGJ/949uyLf/ECh9+98mzUOzJT7DXV/jw0E0rMDk1f9qUmC0/tygpjVsOQQdZn8ozG7GYiPO5nfC4pH3GEiLCMe0RCmYV4WOeD5cGZ09J1GIFzIhLH2MAiMa1HWO9TjxqFrpWWOvmBVEa1gsDnL2tDRs2bNiwYUOCTcTZOO0gTzSFOARBmuSKohMdgzkmgxMUulxVPNsNKeIA9SD6oVYgXsCicwpH+1jnrZ58uDSoIm5/LkWcCWtKj9MjF9niybhUAKLY8Xcg/V41s4HpF+ff6aRlbLl9q+HPlg9cQdNE0ZjmpOVSxFV59RFxXEZcdHwQcTQfrskAOZxGsceFOfUSaSaKUtZEUkxy5Jlpa8pTjIjj87WME8MUnSkFEVXEeV06z3WaD0fUcJn7Kpg1JcDn7+ixQ8tAJJ6Qf/cOQSq4GYWvmP22E1Fj2TVKEAInUBdnndFUuaSIcaKIE0WxoNaUyVgVOiwsSqmqXLRChyrfSvRYYKncF+qT7fyqfFXwvvyDrDmNAABv/yH7xblw1mfZ8ra/yOQLJeJk9QXNh5ugMx8uDauJOC4jzjpFHFVtJaK1umzktCKLyMhUwxlsmskCVcTlGouTSWDXE8AvVvBkCoF75ITi43pwZJApxt4zcxGuOYMp/6q0Znjlgdfpld0MosmoRCbT33l5A+C07nzBkVf4dY1qW5oTVqHVNlEBfeE++Xpe5iljc9G0Cphe67t2yp9rVh27lzjYrWJVn0bTWWy5dRNcDhecgtTMEhfj0jGOBIBk6jfpLgbc2q7Xo9E4Pvent+X5eInHid9/6ixdjQsTK4rw0E0r0FhZhLeT7H5zuXAAgKRG0+xSkrKmHKZEnNsaVazhnDhqnRjXf/3j8+H8ul9vGJw9JcmJy1DEFYqIiyS0EXF6rSnVrjdWWOvmf3NiTSkMYOv9/17497Rhw4YNGzZOMdhEnI3TDumJJrWlRMKrPgFNxPkiTh7PdsOdfwrqOhm/fQ/QU1jLiONUEVdtQBFXr96dSvPczHZmcqq4KLn5FkVg8wNs/eybtBWDxkgR11UARVx7hh1Pf4Qp4ip9+jrSOSJunCrizCDTnjIQDSApSje5Je4SuJ36C0mcIu4Uy4izWhG3dls7Hnk7VSwkirhwROc0QiUfDjhJijiay6MTHYNhOVakvtzHFVj0Ii50y8ujI37NndJ5MXwCdQlCxI2eGkTcUCiGWEI6uKVeF4o85hWCHBEXrcaJwZBm+618yMx9So89mkELghS55g0WgFoqGyXs6TlVV1ynSh6KeknFme9hv9XQALB7LQBwY7mqIs4ILD73RwpExFGyKBmp1VUw1wpaeI4monwjmVW2lAA/FitZU4oicOBfwAMXAo99Wsr6VUOFebUaJTmnVUzD/ElsDrDrhDVzAEEQUOLKUMVxtpQW5sMByqpaDWpbel5ptk1UAB13G0tT45koSsrGTBVwPCJ/rlnEheNgLkUckJETtwWCIPBW1/FIhi2ltmaXRFLELQ9vl4kihwD87KPLMG+ifuePBn8RHvr8CvSXz0NYlMawqY4uTMAAhsNxrN2m0qyZiZRyK0CIOysUcYBxIs6sIq65bVBeXtx4shRx6kScpdaUTv2KOEUVrQraBkYxGs1WSRe5nZZY6+ZFhjUlIGUA2rBhw4YNGzYYbCLOxmmHWy+fgyK3g7OlhOhVn4AefxMY7ZOWyyYCd/Tn9Gw3rIi79A5JZaeEzmbg1xcBW37HB0ZbCF4Rp5+Ia6osRnGqGNoXjHKKG6qIM3tDqNr5d+RloFfqHoWnDDjjQ9p2WDsfSBeVBo8BwT5Tn08NfEac8e7JBkJIZeZi9IesIeKoZePJRCux9WuqNK6IA4ClTX55+Z71+3HF/c/J60by4YBT3ZqSqUlrLLD1u2f9fkRSRQNBYDf53cM6CIe+wyyjxl0CTDmPe1o118VqWGRNSX+fDSaJ5M4QIyni0Wq09BpQVSkh0IFaoojrHu3OsTHGDRHHKzqt6UanBWExWo1gNIHz7n5JewE0BxyCw/jcAJDyTrMgABf/t7kPlgfdVBFn8LqVRcSV1ChuFyvVSeA4nKmsuBTelrJmFK0pLVfEHTM9F6MZcaVeC4m4IULERQtDxHFjcSIMDJMitZVEXEUT5CzAQAevpDz6BvD7y4G/fQDo3Mked/oAB388o3BBuPTbpj6KKIqcNeW0imlYSGzydltExAEZFvexUb4hxEi+YS4YVNsOjrI5BCVo9ILLhytrAnoPAn+8SlXZmP5cs2p1KOImLQPSmcnde4DwEK/qTIQN2VLe/exerN/NxrfvXLsQF8+pzfGK3GiqKsafbjofu4SZ8mNnOg4gkRRx+xM7tV2LAp0QwVtTmsnmpignDQOGFXE6FeHBSByHelL5uAKwYJJ+ktMwVBVxEURJn6eVijgvadiKaVTEcYr7PIrD7z6zB2l+z+UQIEAige+6fpEl1rp5QYk4SL852hhow4YNGzZs2LCJOBunIa5b2oC7rl8Mr4fdRJR5StQnoHufZstzr8qbLWI4I27xjZLKLl14qGgEFn+QkUTxELDu68BDHwaCvTl3ZQQ0I26qAWtKh0PgOlSpKs5KIo7eUHJ5Rpt/w5aXfEQK2tYClweoX8jWO6xXxcUTSfQFpRsNQTBno0aVYVnWlBFiTenTZ19X6i6VrXpC8ZChQHWrYaUirj/I3+h1BRlpSUlIPci0prRKPTMWsJrI4LIlHOzciUR1KJUOvcCWp10IZNha0mLHqUDEtQ+SfDiTRPLxYZpfVpM7E0cPhttRl2DEaV5ryvIGVuQOdgNRiwhBneixWNEZS8bQGWQZMMmYNH52DIW1F0DzwJQ9ZVxpPBatswBUQTdpIDFqTUnPqbqSOmDaRVnbjIoevDPzK/p3vvTjQJp4a9sCdOzgibhETCLMuvew1xhVxJXUSA0CgJSJpkYUaARvTWldRhxHxEUm4NldnZacvxR0LI7EI9nWlFbB5ZHGHACACAy2Shbif34/8MfVQOsmsm0RcP4twDf2Atf9EgnSKNOFGtXmOa3oCfXIv9sydxmqfdWcIu5gVwCRuDXKDnofEYwFpb87DasVcWqq2jxqW86a0iIirnGgDfjlecCxN9RfkPpcs8n9xqHuESSTOeZf3lKgLj3PF4H2dzgyORQPAaNEEVecm4hbu60dS77zL/zmdUbMfvb8afj4iik5XqUNU6pLsNPBmgXOckhuKKFYAves1+CMMtKFUUFAMnVtKHIVcZmOZmBUEUevdze/fDPWHVmn+bW7TwzLPQ+zass05e5ZBjqWcRlxhbOmdBtQxGUR9yp4eX83Rxw//IUVaLl7NTbcdsnYkHAAR27WCYOoWPlh9I2c/PtNGzZs2LBhYzzBJuJsnJa4bmkDPrKCTQadULFcSiZ5Im7e1Xn3zXW9x3R2vS++UVLbrRkEbtkNXP8AcNPLkmorjQPPAr84Fzj4gupu9CIcS6AzZZ3odAiG1RtzSGbDPpITR60pzXZmUmvKYKoI7At1AfufZRudfZO+nRbYnrJ3JCrfSFaXeLgbLb1o9JOMuAxFHJcRp5OIEwRh3NlTtlFFnImMOAB48E3e1kpwsn0bVcR5nV75BjyejBc2t8xCBCNxhFJWMB6XA2UWqDGotS/NiKPFrrzg8uHek/U0HVvDifFPxFlJJGfaJua14tKK4YyMuHzWlA5nfru4MYDVRHLHSIecY5aMlQMiKzhqLoDmgRlVAFpeY8uzLmPLG+4rmEo+keRz+Iwe5yxFHIEIoC1Zg9tin8NzwgX6d146AVhwHVvf8jvOJiyWjEkF1HDqeuYtJ8SOTghChiquRXVTLRiJWG9NORQZQn9YIhTEpBtirBKReNIyMjkNjohLRDKsKS0u6FKniF+sAH5zMXD4JfaYwy3N+W7eDrxnDVBcBSy+EVuveR4RUTquTeg0nQGcaUspCALKfW5MTs1N4kkRB7vyKLM0grOmjGdYU1qtiFNy43B6FDOwKYYtyoij17amI68DchOYkKVspNncVSUeVJdIv/VQLJHVmJaFprPJm27OzjnUqIhbu60d33y8GYPk73cIwAIDdpRqeDXMFHHLHQfk5RP5/sZoEIgMI0Dz4SyypQSMEXHrjqzjlKT94X6s2bhGMxlHbSkXjaUtJZChiKNEXATRQllTugpjTRmOJbDmqd3y+geWN2L5FOvyhjXDWypdhwF4hRimnn+NrYizYcOGDRs2MmATcTZOW0ypYUqNYFilCHJiGxBIdfoWVQJTVubdL+16t6QwX7cA+PxLwDkk0DjYDfz134BnbwNi5gvSx/vZxL3BX2SYKJpTz25E93dKNj2JZIIrOtICgxFwGXEpgm/SiX9CKukBmHEpUDNT4ZU5MGkZW263nojj8uEM5uykUV/hQzr6oSsQ5m7U0gU4QL81JcBbLZ5sIk4URbT2W0dkdAzyvxNKxBlVxAGnpj0lV1wv9UKwQFUjWf6mxlQHKzDPravWtoNYCDj6OlufmU3EZakwCoVMIs4g0cFZU6plkGrAaGwUPaEeAIAoOiHGKnDAioKvKALDJ1CrJyMOGBf2lBwRZ0JhnEYm0ZmJvAVQDdCT48Jh4CgwlCrEu0uAa3/BlFnde4CD/zL92ZTQF4wgLTKpLHbD6zKWw8cRcSV1QMd2ef2d9z6K86P346nk+cat/c78LFve+SickREIKTvDhJhAopsVHzFhjjkVoYXn/jC1prSIiONtKWuQvo2zikxOg1MnJ8K8Io7mKplF8yPMrhgAkqT4LziAJR8DvvIOcOU9WTmKnYlyrEuuYA9Q1wQDoETc1Iqp8jK1ytvVbs28KUsRR60p6fXJCqTdOKiLxMQz8ioIB0ctUMSN9qPt2KvyamMsNXeYtAz4wmvAdb8EKpogqmRzz+TsKfXkxG3iM+ISkQwiTp2guGf9/iyCJCkCP37+gMor9KOjbDGSojROLRCOohjS/FU1yzyNFFk0TIg4Okc1CyNE3H1b78vKRA0nwrhv632aXp/O3wPGOB8O4McyOsaNFRGn1ZrSnd+a8oHXjsjON+U+F257n0FluBUgY/W+n/+7TcTZsGHDhg0bGbCJOBunLWrIvUko4kL3sAKhtfcptjxnNeDMXyyhqg1d1pS54C4C3vd/wEcfA0pI/sCmXwL3LwV+NBtY4wfuXSgVLnSC2lIayYdLYw6xitmfKhRzajh3KZwOY8W8NEo8GaqC6CgmdhB1oF41HFBwRRwl4szkwwHSTVpduVRAEEWgY4gViDkizqufiKPKsJOdE9cfjMqqrTKvy5T1EZBdwLBCEQfw3canChFHSQwr8uGAtOXvIlQWuwGB2czMqPFr28GxDUDabrJ6Fl/wTiEr06VQ8PmlnEkAiI2yjFCdaOcUccbHVT67rBKAEwfyFR21IDwIxEZRFyfWlKcIEcdlHFpMxImx7CJs3gKoBhi2rW4hBPXkFZIK7EySjfbGT0x/NiXwtpTGG0g4a0pXKdB3SFpxuNA09yz5ub0dw7nt5dQweQVzDYiNQmh+hFfFdRFbygkmi48WnvtUEVduERF3ePCwvJyM8FlVVpDJaXhdGU0RhbKmfPFOQFSwe3QVAf+xCbju50Clsh1g30gED8aJenTX46Zs3TMVcWlQIs6qnLgsq7nBAhJxgERufWY9W+/cyVSkKjBlTSmK0r3Kz85CW4TNWxsFH/C+e4DPvQBMXCy7hLy6aq1iNvdszg4/T3MKVcS1vc3NJ0LxkGZFnNrvyMrf1xevWIZOSJ/BJSTxqvdruMGzUT3LPI0UEcflw7nNuZBQ0O95WCMRRy2ftTyeiZ3tlIjza3qNZcihiCuUNaUhRZwrt9q+tX8UP3/5kLx+6xVzUW3BvMkwyHGNjAxx8zkbNmzYsGHDhk3E2TiNEU2Sm6akB+8cy8j7EEXdtpQAfwNtuVXdrPcCX9wIzL6CPRY4AYx0ARClrtmnv6qbjDvWxybupoi4enZTfLArgGRS5PLhrAgM5xRxR18D7p0Pdzx1A15cIx0jvZgwB0h/b4ET/A2XBegixEeaRDMDqq6hxX7OmjJHR68aOGvK6MlVxLVSNVFlkWnV1q2Xz4HbyfYhuKwh4jhFXOTUIOJ4RZx1nbzXLW3AP/5jJQSiiNNcoKBWuyq/YdrBXtCMOEGwxJ6SWquaUXQeD/D5cIDUPGE6j2i4AwA4a8ru0e78rxsHRJzV1pT0GAvxGu65IrczfwFUAwxnxFGl6LSUfeOK/2DZaMc3Asc3Zb/OJLoDRMltooGEkru1IySHacI81Fb55Yy/YDSBo306jksaggCcRVRxb/+Oz4nr3cueq50HU+DOfXO2rDQjrtRrTUYcr4jjiTgryOQ0KIkRSUSYcwRgrTXlUJvy4/EwMGF2zpf2BaPYIc7E9uR06YFEBNj6oOGPokrENbB50+4T1sybOPVsdLhwx5eibgFQv0hajoeBPU/m3JwScX4tRFzzI1Kz4Bo/8P064InPIxTqQ49LIqFdAOpvegM45ybJAlkDZhE7/Ly2oP4prJExMgxfkl33wvFwRkac+vxZrXnJyt/Xdc4NqHewc2mCMIwfOn+J6w5+S7ov7dkPJBSIsBHp3iXgYHNdK60pyw0o4upL6nU9TjEUiqGlV7omuBwC5tZb97doAlXEjXQB6XMmHi6cIq4AGXHfeXo3Iql9LWwox0fOLgCZrwcZqmlbEWfDhg0bNmzwGPdEnCAI9YIg3CcIwmFBEMKCIHQJgvC0IAiXmtxvuSAI3xMEYa8gCKOCIPQJgvCiIAg35HndYkEQ/l0QhN8JgtAsCEJcEARREIS/m/k8NqwHLYSJSW82EdezD+hPdRd7SoHpqzTtl1PE6bGf0orSCcCH/w6s/rHy87GQ1EWsA7T4NbXauHXkhDKvnNkwGk2gbSDEKeKsuCHkcnZ2P8Z3sYaHpK5nvXA4JSueNCxWxfVw1pTmi8a0qN+mRsR5zRFxJ5tUsjIfDpBIom+8lxXuHFZZU3pPPWtKq0kMislVxfC5WYErkdBYYD5E8uEUbCkBhVyiQoIWAv96g+7mhlgiKeduAsBEv3EC/vgwI4k84gQAUn7XBf/3srncp5SKpSqZRFqPMxQZyt9AMh6IOAuyyyioIu7GM5Zwz33nmgW4bqn54rehjDhR5PPhpl0o/V/RwKtDNvzE9OfLBFXEGT3GSTHJkbt1/YS8mrQEgiBg/iRKZBgcQxd/UJqnAUDPPtBRJ9ZDLOMsJeKOmtpVgFhTWpURxxFxRBHncgiWkMlpcGNxZJjNwxwuoGSCZe+DikZ9jxOkVRYPxi9nD275PZCIq7wiN2jOlZoibm9HAAkjqs4McKR9oANIW/uV1gFu881cqlj8Iba8I/dt66AeRVzzI1KT4FArABFIWUu3u9h5P7GsCa5KfQTBrFrS/JdPJS4InCrOF2X3JuGE9oy4lTOyrYutataQ8eKdcGQoQR1iAtizFnj4Y8DPzwa+Xw/89EzgoY8AL6wBtv8N2PZXALw1ZaEy4rQq4m5edjNH3AOA2+HGzctuzvva3UQNN6e+DD63OUcV3XB5mU2pmGCK2kIq4py8NaWowRo9FxH3wp4uvLBXugYLAvDdaxfC6TDX2GgahIhrqK+2FXE2bNiwYcNGBsY1EScIwmIAuwB8FcB0ABEANQCuAvC8IAi3GdxvI4DtAP4bwFwACQDlAC4B8KggCL/I8fI/AfglgM8AWARgjGeNNrQik4h7O5OIo2q4WZdpvvm1PCNOCYIAnPU5ACqTabUuYhXw1pTmMtyoVcy+zmFOEVfmNn9DyCniMi2LkjHdJKSMAtpTdlGLLysUcZSIS9nhRBNRBGLSsXYKTo4g0gpKSJ1sa0or8+HS+NwF0+FN275YZE15KmbE9Vhs60fhcAiYUM6mDkNaehH6W5hdnbtYNYuTNjkUbGwFpKJhN7GzG+3TrTTuHArL+Vp15V7D+VoAr9YKjbICYXcggtuf2GmcjBuWXucAUCuw8yCvKm4cEHG91F7VgnO4LcCumTcuWcplD82ss8bai1O5aLWm7DsMBCTlIrzlQD1pGFlJCpn7/wl077PgUzJ0k2Ns1JpyIDyAWCrXq8xThuIuktc2aQkAi6z9vGUcMekmGZLRvoNsuwnjh4gbIYo4q4i4lkFGFhULzCJyUUOFJWRyGpw6mViPomwS4LDw1vHSOyRrdgp3kfR4HvSlyPp1yRWIpBuThtuk34pOjMZGZSs9l+BCU1mT/FxtmU8mqkOxhKzgMQNurBghDg0VTQpbW4hFH5Cy9wDJLjqH6lOXNeWLd0pNghloLWJjKz2mWkEVcYe6R/Jb21IiLsRInnA8DISIIi6Ho0Qwyt93NPiLcNf1iyz9fWm6h0vGgb6DwP51wBv3Amu/CBx+EQBvTVkW0KBy1wgjGXGrp6/GmvPWcPducyrnYPX01Xlfu6PtJNpSpkHVW2llagEVcQ6HwLl3aMmJ46wpSUZcOJbAd55h19wPndWEpZP1xxaYwboj63DZY5dh8YOLcdljl2HdkXXcMb3rsxfJY7UNGzZs2LBhQ8K4JeIEQSgC8BSAagDbACwURbECQCWAH0NiKH4gCMJl6ntR3K8A4DEA0wAcBbBSFMUyAGUAvgkgCeCLgiB8XmUXMUgk3m8BfAHAepXtbJxkcIHGSS92nxhCOEZusGg+nEZbSqBAGXFqMNEtTGFVRhzA21Pu7wzwRJzFirgRpYKPThJSxqRlbLl9q7F9qKCLWHxZY03JvqO0NSVVw/m9fjgE/cM3JaSGIifXmpK39TOviAMAl9MhW9tYlRFHiTh6ro9nUBsYq4k4AKguY0WE/hEN6oBDxJZy6gWqTQ9jpoh78U6pyEWhU2ncauH5SxVxiSjfjR+KJXDP+v3GdkxynepIkUwXETd4DEhqs0+yElYq4kRR5Ii4xrJGnhxqt2YsNKSWP0rUcFPO43NqJ8wB5lzJ1jfeb/IT8ujmrlvGjjG1pawrruObXFLNLzwRZ+JYn8nsKd1RVvSPpVX5vgo+88cIqGXtUJuyPZwGJJKiXNAXBKDEY56IG42N4kRQ+k07BSf++LH3yc8NjFqrOODG4iAZL8onKmxtAotvBK6+P0VACdL/V9+flRWmhL6g9DdH4Ubv7A+zJzY/oPtjHB0+Ki83ljVy1qeAhedwCpwijh5ff4GJuLI6YAYxlMnRfEIVURXFeYg4lXl5G9h1trFU330LIM1fqogLR3u+nLamc+RFX5Blv2pVxCWTIrYcZYTdC1+/EBtuu8RaEg5Qv4fzlErfTx5CNkCJuNYtln0sI9aUgETG/eXKv8jrBwYOaJov72wflJcXNxp3rjAFhZy4eDyMeIqIc0CAS7CmkSINvfaUaoq4X75yWG5q9Be7cevlJjNSdWLdkXW4Y+Md6Ah2QISIjmAH1mxcg3VRNi946J9v2taUNmzYsGHDRgbGLREHieSaAmAEwNWiKO4GAFEUh0VR/E8AayGRcXfp3O+1AM6BRLi9XxTFjan9hkVRvAdAutJxpyAISi1QK0RRXCqK4udFUXwAgLVhUzYsA52sikkvYgkRzenuu/4WKawcAJxeXbljPpcPQkqpFklEkEgm8rzCBJS6hZ0eTd3CacQSSe7mdbJJG0COiOsKcNaUlmTEkX0oEnE6SUgZmYo4DXYgWkEVcUYLmhS8NaV0Hg9EWBGh0mes47HCM44UccRys8kiRRwA2QZNcDIi3hQRZ1tTZsFPfua9w3mKCM2PAP/6H7aeI5vF6xojIk6NzNdB8tPsxgaT2TFKGXEUJ/IVH9UwzJR0tT523NPKD1X4KlihMh6Wc2nGComkyHVQV5vMOewJ9UiFWEjEeoW3AgutsEvMgCFryhaaD3dh9vMrv8aWmx8BhkxYlWaAWlMaVcR1EbVUna8a6E9ZJzpcQO0CAMACcqz3nBjWZMWliPqFQNMKAICb7COWVi5MmCexXmbg9rFufjFhuPFnJELy4TwuOCywCqNkUVNZExZMqpKVFUf7RnUVzvOBEnHhUUZooHySwtYmsfhG4JZdwJpB6X8NJBwAboyILfkkIKRUyUdfB7r2qLxKGWr5cGlYPV5whfUQOb5+fdaNhnAGtad8SHEuvHZbOw50MSJl05G+rG04lGTbOQJAW4lfXm4sMzZ3p+rlQ915cuImLpGzNYtCg/LDWjPi9ncFMDgq/Y5qSj2YMcEatXQW1JSgV90LfPwJ6XfwrRPATa8C1/8WuPBWblOOiAtZ11RnRBGXxgz/DMytkoigaDKKF469kOcVYPfkkFS9JwW0uSClTo+SjGKvw206wzoTHhf7/mKJ/NdDpbnFsb4gfvnqYfnxb14+Vyatxwr3bb0P0QTfBBJOhHHfiZfl9We3daDPtqa0YcOGDRs2OIxnIu6jqf//JoqiUuXhntT/ywRB0GPcnt7vC6Iobld4/kcARAD1kKwqOYhipleejfGKTGtKACwnbt8zbMMZl0i2RxrhEBycbU9BLdTS3cL08zWcpblQAUgF43SmxcQKn2kP/lyKOGpNYhR0H8HMmx+NlkWKqJoOpK0ZR3uNK+sU0EOUBUYLmhTUmjJNovaHWRGhyqdOZuQClxF3kkmlQijiAGB+qnNdsCojjlpTnuRcPa0otCKOnuIdgzkuic2PAE99VSJz0tj9D9Uu/DGzprRAaUyzG81Yq4biIaZQEx0QY/6sbSYZJfrSlocA6kpY1zdVManiJNpTDoxGZdvPiiK3KdtPgM+HS9ujLWhgv+tdFihcAANEnChKpEEaUy/I3mbyOcDkc6XlZAx4K5dzuj5w1pQWKOLqqVN77XxZ+TqlqhilXklR0BeMco0runGWpIrzKBFxtRapASw492k+XKlFtpSHB1nRdXrFdHhdTm4+ZpWyE8hQxFFLv3KLlUEmQIu7lROnA3OJFd6W3+jaVz4izmpFHGdNSZuiCm1NCUjHKe1e0X8YaHube3rttnbc/kQzqAvkD9fvz22RrNQc5i5Ca+0sedWINSUAzCb2lJQcVITbJ+dBe8kYIVlT5lfEvUUIx3OmVVtOwMjQogT1lEj2vos/AFzyP9y5ESCKqjIT89tMmCHiAGD1NPYbXHdkXc5t+0Yi8jzK43JwY9mYglpTDqeJOHaNstKWMg23GUVcfBSiKGLNU7vl157RWIEPnjUGY0cGOoIdio93Rvq59f7RKOIaLDht2LBhw4aNdwvGJREnCEIZgOWpVTXrx7cApO+GLlXZRgkX59pvivRLG25nEXE2Th1whTCZiEtNDmk+nA5byjTGJCcujcU3Ah9fy9a7d+uySzrax46DWTUcwGfEtfQGMRhm5AQlLYyCy4hLdX2KgC7LIkU4HMAkkr9zwhp7ylgiKQdRC4LURWsWVGHTMRRGPJHkiDjDirhxkhEniiKnKGqsslARNzGbiHu3ZcTxRJz1RQSPm5FvwyFegcfhxTuBzPExHla1gBwza0qlbnQAWHmL5l3wRJzxcZWSRFXeevjcvAWYz+XArZfr6TUioNaUpAia15oSOKlEnNWKTkUijihc9ncGNBXD8oHOCzTZVvfsA4I90nJRJVC3UHk7qop75498QdkEuodpA4kF1pRRQrin8uEAKRMnPS4DJomM+dcCxdVwgxBxIIo4K2AJEVeAfDhCFk33TwcALGrwy481W0nEUXVyeJA9UQhFnAGEYwkEUqpDl0NAeZELOOcLbIMdfweIIiof8hNxvCLOsKozBc6akp5jOTLbLIO7CFhwLVtv/jv39N3P7kMoxo+H4VhS3SL5+FtSlpkMRiy1CWyuYFQRN6uW3XMczKeIA2R7Sh9HxIUAeh6rEHGbjrB59jnTjTW8aYZeJSiZtwQIQVi24N8s+0hmibj3TXuf7BizuXMzp5jOxE4yXs2fWM6RU2MKzpoyRcQl2RzE6yjAHNqlk4hz8daUz+/pwsv7pbmDIADfvW4hnBaorvWCfi6K+uI6bt0hJtBvsX2yDRs2bNiwcSpjXBJxAOYB6TtrmRTjIIpiEkD6rmC+lp0KglALKXNOdb8ppD1NNO3XxvhEpjUlICnixOEOoHWT9ITgBOa8T+nlOZHZnVZwNCwHylM3seFBoOW1nJtT0Hy4qdUlObbUhlKvS1aAxJMi2obYjasV1pQlHqIqcDiAeVfj1VVP6rIsUkWmPaUFoEXjmlIvXBbcTPrcTlnJlEiK6ApEuIw4KxRxJzMjricQQSR181lR5Ea5L0/+iA7Mm1gGwRGD4JCKCE7BxXWf68WpRsSJolhwa0papEDSo15Y12kBSZXGYaqisxpcNzrB4FHNu2gfZONqgwlFXOswI4nmTZiGu69fLNvNAcAnzp1iPJ+GWlNWzpSXcxXHZIwXIs4CRWcWEdf8CCp+tRRHfB/FG56v4n3i6/mVFhpA5wWaFHHUlnLKSqlZRAmzLmMkU3QE2PJbE59SgiiKXA6fJdaUI8S+jl5rwZTKgElrP5cXWPpxuAkPEh2HijhqTVlm0fXtyNAReXl6hUTE0VylnW3WXdN9TnY+RKgSnKpHTiL6g6yoW13qkZRLU1ZKSkwAiI0C2/+meX8twwpEXPMjwL0LgTV+NP3pbHzQ9yYAYHA0lj+rLA84RZxATuYtv8mZ22YZziCZerseB1IKoHXNHegcVr72qlokv/7/2PKSj8rEUnLRDWgPsGuQkYw4AJhFFHEHtYzTTWcBAIqIpC8cGQLEFOHhKQOc2b9JURSxmeTDnTNN2W7zpIHMWwJOpj4um3mZZW9R7HHClSJ0IvEkn6ueA2u3tWPl3S9hxXffhiMizTVEiHju6HOqr3lkC7suH+wK5FZcFhJlpLkglREXIXaLboVzxSw4Ii6R/xhnqu2/8zSz3v3I2ZOxuNFv6efTglgyJpOuFD6nDzcv/xpQLP1+2r9eimoM2/aUNmzYsGHDBsF4JeLond4J1a3Yc1rvDAu1XxvjEJQgK01NYgdGY+h95wm20dSVOTOL1DBmFmppCILUCZ7GnrWaX0qJuMnV1lgAziUWIh3DjCAq85i3FikdYTfCIw4BuOAbpvcpY9IyttxujSKuixQtrMiHS4OzpxwIcUScUUUcVYadTCKOy4ezUA0HAMUeFyZPYOul7nJT9kJcRtwpYE0ZjCYQTnWze10O2RLOSlCSTBTd6oV1nRaQbocbzlTOT0JMIFFIJ+h0N/oH/8Ie2/JbINir6eVWWVPSfLgpZRLp9pGzWU5QqdEifmQECKd+404P6v0z5KfGuzUlp+i0QhFHyM6moU7g6a8CQ61wQESjoxd3u3+LwBbtRXs1cMX1mIYGnaOkoWbaRerbORzAypvZ+lu/AmLm5h0DozE5m6bM60KRx5j9J1VX1vWz44yJS7jtqLXfLrPKrTM/nWFNmVoYV4o4Yk1p0RisRMTRXKXm9kFL3gfIyIgj9uPjxZqSFnWrS1KfVRCAs29iG235DZDMrzZJJBM4NsSUaNMqpklkWGqcAEQIQ624U3gA1zjeAGA+J44j7amSJYdi3FJMPg+oSF1nQgMI7noWX/v7Nnzpb+rzYkWL5M5dwMG0wYzAqXe7R7sRTUrfU6W30nCjXqYiLq8asfFsABmKODp3K1aePx/sHpEJ3spiN2bVFigfzgxS85ZA45nyQ1bcd6UhCAKnihsO51fFSVamO9E+GIIIYKRvsfzcw3ufxPrdnXj8nTb86c2j+MUrh3DP+n34+O824dldLHs2GE3g9id2Wk7GrTuyDpc9dhkWP7gYlz12mbJdJqeIkz5TlDgy0LHQKnhIw2ZEryIuPorB6m/DVb4NlcVu444JJvHmiTcRjPMNRw44sOa8NVg9fbVMcL5zIoE6YYCb19mwYcOGDRvvdlhfobMGVL6Qq9qQrnRonS0Xar+6IAjCTQBuAoC6ujq88sorhXibdz16hnrk5Uk+t+xjGtj8d6Tr9Adcc3HCwPGPjbKbkw2bN6DT15lja2tQHmlCmkaKNf8DG0uvg+jIXzx75wArmge7juKVV8xno/kirAhyrLcD6WiY4weP45UTr5jad+2+e4HU/X7A6cErB4YwMjJiye/EF4pgRWo5fvxtvPHyy1LxxgTe6WKd785o0LLfsyfGvrfnN76DY75d8nrv8V68MqD/fcJJts/+UP9JG3vePMGOmTdu3TFLo8LVjzSdm4y6Te3/RJT1bHQOdo778boryG7qS10iXn31Vcvfo7OXjHdJF17efggLhOxxZVLN5Zg9xKt3Eg4v9k/6ALpVjqMbbiQgEXADgYHCH2+xBGeWTEFp8BgQG8Wxh7+JlumfyPmSRFLk1AGHm7eg1WlsHNnUt0lejnRF8Morr8AVYNeXl3ccxmKn/uJU0Wgbzkkth9yVOLLrqPxc62Br3uPqHxjCktTy0NEd2Gbge6jtehXTj/wZ3kgvIt4aHJn+cXTX5SCcUnirhV1fIoPdps+B3R3MAKFu62NZJFaxEMWs5h/hFb85IudgiNmzneg5kftzi0msPPgK0iXPzb0+jObYXkhOwDneGvgivcBoLw48sgYnGvSr+dNoDdBxImH4GLf0MiVR7aB0niYFF17f3wfxINtnaJiR6u8cUf9OtV7rRVcZAOl3EhMEiBCwd90v0V2/Su+fkIXyoQF5rhU4vhPvGDg2m8g1LjRs/lqbEHmyqK25DT2OHsSTIlwCEBeB1v4QnvnXyyj1mLcoOxZg7zUaYXaAb+45jsiRMWg+y4PmHnZ8HWTe5UhMxLmuErjjQaD/CJr/cS/6q5er7EVCb6xXJozKneXYunErVrz5LfgyxgmvGMG33X/Gusi5+OfGZnh79hn67O7oIELtD8utsKMC3xMrDrXh1TGYZ0yrOAdThqRGkE3/+CnWRr6uuq3HAayenD1OzNvzY6RN6HpqVmD37hNI97IeCh+StysXy3P+BnL97kVRRIkbCMaA0WgCTzz3MqqLcvcRr/DWwCuy76+946i8HIi7FX/TLxxj193pZUm89pr1cyer0D3EGiD2bN+Dfnd/jq31wS2y4/DCqxsxqTT3sf7uK6MIxRjpGQ8sgph8EoIjjtbgQXzx4WeRjNbmfd9QLIHvPrkD/qGDebfVgi0jW/BQ/0OIpf6ejmAH/veN/8WePXtwVulZ8naeSB/OSy1H+49h4yuvoDoaAiCpgmPhuOXz0EiInZtvbX4bPf7c9/JbRrZw6w7PIHwTn8AypwvbN1tvnakFf+z5Y9ZjSSQRPxLHK8dfwaKYB9UArvl7CJ+7vR+vb9mBRDsrO1p1X2/Dho1TB/bv3oYNhvFKxJ3WEEXxAQAPAMCZZ54prlq16uR+oNMU33v0e+k6DVYtnI29nQOowAimhFhRbvbVt2C2gcyLv/3rb2jpkApQcxbNwfkN51vymXMieSFw6H4gcALueAAXTXUC01flfdl333kFgNS1duUFZ2Eh6aA2iiF/O545sh0AEHWwgsiKJSuwsmGliR23Ifz6BmCyJEYddTqxatUqvPLKK7DkdyKKwM7bgdE+uBJBrFo8Gaiekf91OdD65lFgm3ROzZ82CatWLc79Ao14c3QvtnRKHfDl9VPhE3xAqh62YvEKrJqySvc+RVHE7X+5HfFkHDExhhXnr+DsAMcKu18+BDRLzsLLZk/GqlXWugC/EB5ES0r043ZWmjp3uoJduOuxuwAAcVfcmvOwgNhytB94XbLQappQgVWrTPweVfCbdb8BUs2tYtKDrphH+bhsbQUOk/WKJjgvvQPzF9+o6vtc/HAxwmGJMPaUqOzXatTeCTz6SQDAlM71mPKhH+VUSrcPhpD810sAJDvayy69WHXbfPjz+j/Lv+tLll2CCxsvRF3HMH63S7It7Iy4jR2DI68Cm6XFotoZuPqSq7Hmz2sgQkQgEcDKC1fC7cihthuYCuy4AwBQkRzQ/xmaHwHe+IWk8ADgi/Rg/qFfYv68eXktht8Y2QPsl66vS+fNxKpV5sbo//n7/8jLM0b7FLepSvaZPteqe6rxs3/+DADgLs3zvXU0A6+mlEYlE3D2lR/P3xRS9A1g/e0AgNk9z2L2h74POI1N41870ANskE6QqXVVWLVqRZ5XZEMURXzzb9+U1+sS0lzAUb8AF13yXm7bWCKJ721aj2giib6wiCVnnwd/cXYBUeu1/vHOaiCSUi8IAgSImH/4V5g/f755C+vAXGDbbQCAsrix86LtrWNAs9Q8M2NyA1atWmTqIx0ZPILkcYk8nVgyEZdfcrn83II9b2BHypayYtpCXDBrguI+9GDkyAiQck6Ni2liXMC5771O0dZvrNH7Thvwzg4AwKzJ9Vi1agl7Mv5p4E3pd7g4/BawKrerwmttr8k+KHMmzMGqiy4CXulR3LZaCOAN783YFLwaq5Z/i1fT5P3QB4GNPwV2/B1HhQTQJN17jGZkOwkVjWNy3QvPqQd+/SgA4Hxsgx8BDKIM/7asEWdO9eNnLx3GicEQJvmLcOvlc7ItkvsOA6++Ia9OuP4urCKWtAMHB4DUPGx+w3ysunCV6mfJ97tfsP9N2TayavpCrJqTh9jpuRA+YotYQpTVZbWTFd/r0b9uBSBlhF119hysWpmdFThe8O2Hvw2kbr3ec/57UFNUY9m+63ZvQOfoIABgzqIlWD5FfS60uaUffeE3+QeTPsRH5sJdLo1/roptiPZcrvDqbPSHRcvO/e8/9n2ZhEsjJsbwfPh53HrVrezBRBx4ywGISXhiw1h1/rnYvok1qlRV1Fj+e/z5vo1oGZJcThYuXoJzpue2Qf3BYz/IekxwxNBa/BJWrbrN0s+mBcFYELc+zI5hTVENekOSm0Tl3Epc2HghMPQY0P8OAKBOGEBt03SsumC6/BrL7utt2LBxysD+3duwwTBerSmp1j2X51Naq68hvbmg+7UxDkGtoc5skoid9zi2wplSW6DxLMPB89RWZkysKQHJnmr+NWx999q8L0kkRbT2s883xTJrSmYzNRJjPxPTGXEb7oc3EYMrZSkTFeOIEq9+0xAEy3PiuobN5+wogbOmHMywpvQas6YUBAEVnpOfE9faz36bjZXWnJMUNRWMHI5EzNnKUNufU8Gasjcjs7AQCCdIhozoQmt/CEOjChZGh19ky+/9rqacR5pNlFYpFBzzrmHZQtERuYirhjbu/DVnrUqtKSeXSVZhs2pL4U1liHQMhY1Z+gwT9+3yiXA73Kgukoo9IkT0juax4CxvlDJUAWCkC4jqzEJ98U6ZhJMRC2myXeOsKUvNdXsPR4flcc7r9GJCSZ3idh1iNRLJPJZneaDLmvIoyYeber42ZfayTwA+v7Q8eEyXRXUmqKVyrUFL5eHosDz/KRJcKEsfvwxbSgBwOx2YXc/mB3tMWvu5Ax3ysjzyaDy/8qK0Dkg3qIQHgdBAzs2VEAjTjDjzPY9KtpRpLCI5cc0W5cTRcTicPjdL68YFCQfwY0R1ScYYceZnIMeMH3xeIoxyoGWI5MOVTwWe/9+c208U+nHd4IPAvQuARz4pZTbnsks8/hbw0EeAn50FbH0QSERQTLYPUkWcuwi49I6c728FtrcO4sq/dmJbUsrz8ggJfLBoC371seX48Y1n4MNnT8GG2y5By92rseG2S5RzSjfez3LXpl+clQvZNsJU8kbz4dKYSXLiDnVpuDVvOhtFxJY0TMfjouz5syiK2NTCmjTGXT5cBgLELtZKa0oAnDXlUEjZmrI7EMYtD2/Hjb9+U/H5+PASebm8ZieuPWMiPnrOZHzhwun4xntno6JIeUxUtD81iM6gslNN1uNOlzS2pRHoQEQkrh2uAlhTchlx+a0pO1T+FrXHC40Xj78o3wfM9M/Ee6ewxpt9/SmlMKmv1AoDXCatDRs2bNiw8W7HeCXiaH5bLqYk/VxHjm3GYr82xhlEUeS8y8+ZOhEuh4ArnMTeYd7VhvdPM+I0ZcFYBZoTt/dpIJk7Q6lzOCxP8qtLPCgzmjeUgWk1JXJEc1xkf3+Z28QN4UgPsPVBCABKyA00JfosgeVEHM2Is5CIIzekbQMhDERYMbDKpz/XMI0KLyHioieHiLMqX0sN5cWMwAmMekwV2ItcRXA5pKJBNBnl8tHGI2iBckJZYSxrMjPiAGD3iYxzKZkADr/M1mdcomnfVKGZ2c1cMDgcwIWkQ3rTA8CoutWTVedvOB6Wi0JOwYmGUqnY6XI6MG8ia3bYaSRTa5jYWaYKIrXFTEWQNyfO6QL8TWx98Jj6tkoYUrFAVnucoIc7h80VwVoDLLessbQRjoU3ZG0TFx34v9iNONJj7lpDG3TyzgtaCBE37UJtb+At5TOwNvwkNwGQA90B2kBi7BjTc6gOTnlOkFmQT2PBRHbtMZux5SbEcIySmBrOr7wQhIycOJ3nPoCRCBu7yizIiDs8yMikaRW8Umdxg19e3mkREUdzkaLp41s+fmKzNx1hjQSPvN3KZ0tVzwBmpQvDIrDldzn3xRFx3Ycl1ZoCRIcLwyIZ75NxiQx/8Grg5+cAm34NvPNH4N6FwBo/8MPpwH1Lgd9fDuxfJ32WFErqmEJy1OkAIAAVTcDV95tXdCpg7bZ2rLz7JUy7bR0WfXs93v/zDTjSG8TjiQvkbf6zfhuuWKhR4TfcAWwnuZoKWc507G0qa8p6Xg9mk7y2A12BHFum3/BsPiOOZIYrqd0P9wTRm8odrChycznY4w2RRASxpDS+eBweyzPMchFx8UQSv3+jBZf+6FX8I0eemzu8AD6n9J1F0ItPXSrg++9fhNuvnIevXDoL37lmIYrcvB1jkdtpWd7ZowceVX2uvkThHKfK1oFjiJBriqfAGXHRHBlxwUgcf9zQgmRMxclGTCl6xxjPHH5GXr5q+lWYV8VsvWUiLnVMf32VD3UY5HI9bdiwYcOGjXc7xisRtw/sjmWB0gaCIDgApGdse7TsVBTFHgDpuzfF/aaQds3StF8b4w/hRBjJVKemx+FBqdeH5ZM8uNDRzDaae5Xh/dPg5DFTxAFA0zmsc2+0Fzi2Mefmx/oYGWmVGg4A/rmTcNROVpTfcMBEIfOtn8sKilKB3QgGo0G1VxjDpGVsuV09mF4rrChoKoEqxd441ItjgywTotJnTBEHAH6vX14+aYq4AVYUaaqyXhGXENg5E48VoaXX+DkkCALKPYwUGY6Ob1VcDzkfJ4yFIi4p/VZ3ZRJxJ7ZJahIAKK0H6nJdchloUWnMiDhAanKoSU0pogHgrV+qbtpO8uEaTBBx7SOskDWxZCLcRG2yiFgI7zJSXOcUcRLBV1fMur7zEnFABhlxVN/7u1WOS0V+ZQR3DltIxEnF4OyilwhgQ3JR9jmsE5SIo41AWUjEgWMb2PpUjUQcAJzzBSDdCNS5Ezj8ks5PKaEnYF7J3RUkRFyUdLtPWqK4/YIGNo5mEfc64SHHmiPiNJxfmmDm3AeviCu1WhHn5xVx1G7cEGmvANoQISviyhVUUScBa7e147UDTL00HI7j9id28mTc2V9gy9v+AuSYR3JE3D5mZ4iJS1Lnk0SSCdf9Ep+e8Hd8JfplbErO5XfSux949pvA0zcDQ60ARGC0Dxg4wm8363LgU+tQ9Dn2uw0JApLf7tekGDeCtdvacfsTO9E+GIIIIBCJyzfYLzlXIiFI56e74x3JPlML3vwZkHaraDxLUvVmoD3Avo/GMnO/y1l1jBg72K3hPqN+MbwO1ogUjhDyTkER99YRdj6dNbUKjgy70PEEqoYz7UKiAKpWo04Hm1v6cdVP38Cdz+xBIMLGtysX1ePbV89Hg78IAqQmwruuX4rV05kd5boj67j3uG5pA+66flHGaxYpKy91Ynv3dvxgU7aVIyDNL29ednP2E2WkyWDgKGs+ACwnOoEMRZwCEXdiMIS7nt2Lc+96EWue3oNI9+UQkwqNtIKIL734Jdyx4Q7uvCgkuke7samTZRuvnr4ac6vYeLi3b6+0kDqmNy33oF7oN+bsYMOGDRs2bJymGJdEnCiKAQBvp1bfq7LZOQDSd58vqmyjhHSLvuJ+BUFoACPp9OzXxjhCMMZuutN2UR8o3wuvIN1UdBfPNJUNxini4mOoiHM4JRu1NPY8mXPzY33ss02pLsmxpT7cs36/fCMvOFhR+pcvnVB+QT6EBoDNv5VXS0uYcqOgiriOHXlVhflQKEXctuPUDisOpI6zAAenatOLci8rhp4MIi6RFHGCEhkWWtGkMRgZlJfFRDH2dJgjzzgibpzbU/aQrtMaC4lhikiC3VCnFXG72jOOCyUIZlyizXoP/NgaFcewg9bhBC5ieVfY9CtVS7o2QiSbsVY9NsyUNpPLJVtKND8C3LsQd24/H294voprHG8YVMRRIk5SxHFEXLCARNzgcckmMBNOjybbtV5yDpslk9sCxB6trBE48gp7MlXEdAtJfML1L+zOPId1gjbojMZGIaqp1Tp3AOlxpGyivrlISQ2w7ONsfcNP9H9QSNZiaRi1puQUceHUddrpYTavGVgwiRJxJhVxk5bLyzIRZ6Wtn4VEnBVOBJQsyrSmnFXHrGzbB0Pos6DgSYvPkTQpYdDK3Wr88Ll9SGT8tkKxBO5Zv589MOMSoCr1u4oMAc0Pq+6PI+JiKeJh5nuAz/4LuGU3sGZQJsnmNFTj6eR5+GD0Djx85sPAmZ+Vx5GcWPox4D82AR99BJh6PhwO55g5a9yzfj9Csex5rsfpwMNfWw3nnCvYgzmOk4zRfuDtP7D1C76heH2n1pRmFXGzqDVl94j62JqG042iGqauCtG5blG2Im5TC1PAr5hu3HFiLECbwejc1CpQRdxwOI7uQBhfT9lQ7utkZM/0CSX482fPxi8+uhyfXjkty8p09fTV8rbrj66XVXxpXLe0Ib/9qU50j3bjllduQTwpjb/1xfVcFu77Z76f+1wyOEXc0QxFnPXOEh4XUwNSa8odrYP46kPbcMEPX8avXz2C4dR1JD68FOGO65GM+iGKQDJegmSCjdH/OPQPXP/U9XjzhLJVqJV4tuVZudH5rPqzUF9Sj5n+mbJzSNtIm0QKpog44TvDqBUGbEWcDRs2bNiwQTAuibgU0p4XHxUEQckP5T9T/78jiuJ+hefz7fcyQRDOUHj+65DCBTrASDsbpxjoTW26S/28KFOPvepYYWr/JyUjLg3OnvKpnETS0QIp4mQiRYhBcEjvL4pOdAzGc7wqBzb/VlKhAEDNHJSUsYKP5URc+UTW/RgLau8AVgFVxNUZLGgq4acvHZKXBRcp0iSK4RCMD91UEUcJq7FC13AYsYRURKku8aDEAtuuTFCCUUwUm1ZfUPLSVsTx1pRpRVzWMT5E+lhmXqp53ydNEQcAC94P1MyWliPDwFu/UtzMKmvKLLVW8yPA018FhlohQESjoxd3u3+Licee1r9zzpoypYgj+Wjdo92Zr8iGUTLizV+A2rDJaDwrr+IjlkiiPygVbAQBqMrMf9IJ7hh7qyQVGSDl311xl/zcJ5zP42CbBnIyB1wOl5ytJUJUnxtQW8qpF2gmqWWc+2WW39fymiFld7cF2aYcEZdIzUNq5wMqmTpz68vlP/VwzwhCUeNNMO4JrAM/JhTA1s9SIs7cNS4pJnMScW6nA/MnmbSyzQAdh2VFXPPD0hh1EhGNJ3FiSNkemjb4wOEAzv48W9/8G0Ub14HwgGz77UsmUR9PSL/JD/5F8TymZPJrw7XAVf8P+MY+YPWPc3xqAbj250Atr6LjMiUL2NDHHReCWCIpORKc8SH24I6HgaS6VR4AYPMD0twZkH7vsy7P2iQYC6I/LJFbboebs0U2ggmlXpkgGonE0aFyDlD4SFYlzfzKVMSJoohNRBG3Yvq7Nx8O4DOc73/xIC64+yU8QdSmRW4n/uuKuXju5gtxwawJqvtZXrdcbv4ZjAxiY3tuBxeziCaiuOWVW9AbkoyPKrwV+MMVf8DnFn1O3kZUmpcAALnnHAtFXMcgO8bffnI3vvP0bnzgVxtx7c834KkdJzg7/anVxfi3ZQ1whZYjePg2jOy7G8GD/4vksduxsOIiebvOYCduev4mfO+t7xWU2KfqxqumS85CbqcbM/0z5cf39e/jVIZ1woCtiLNhw4YNGzYIxjMR92sAxwCUAXhGEIT5ACAIQpkgCD8EcH1qu29lvlAQBDH1b43Cfp8EsAnS3/4PQRBWpF7jFQThGwC+ltru26KY3Y4vCEKxIAg16X8A0jM0D31cEATr/SJsaMZzLcxepmu0C+sO/AP1Xa/Kj/15aDFiGgKS1XDSMuIAYMp5QEnq5mekC2jdpLrpcaKIm2qhIi4dqC04SFZUwodJfgNkX2QEeOsXbP2Cr3N2K1TdaBm4nDjj9pTROCsaOwSg2kLigxZPBCcjI+Mxc99jhYdkxJ0ERVyh8+GAbCJuj0n1Be06Hiv7F6OgN7uFUMSJosgp4pwpG9kjvUEE03ZF4SGgLZ3HKQDTL9a8fy8pfo6pIg6QVHE0K+6tXwKhwazNqDVlowlF5/Hh4/LylPIpwIt3ZinJioUoPh/7i36VS4DYB6cKImNiTTnaD2x9kK1f9F9suWd/XgUy7ZquLvHA5TQ3TaXHuGmE5P41ngmc8RHEyyWlRqUwgtkdTyFpIk8SyMiJUyuuHzWQD0dROQVYeD1bN6CK4yyVjSriiKqyPp76XlXy4QCgxOvCtBrp+pUUgX2dxsdlqlKIXvZd6239/FPYst58RACBsHUZcR3BDtkOuNJbqWhNvZjaU1qQE8cp4tJF6fCQ1Chwksi4WCKJrzykPl+blDkWL/kIkCa7uvcAR9/Ies3Rd1h+3NRYHI7Gs4EP/13VWnfhJHac5XmFtww463MSGawEFbtUqqAtyDw3hfIiZUWmfLxmXcbIqaHjwPEchElkRFKLp3H+LRLpmQGqRG4obTDVPAZIFuGziSpOS06cr4GpZsO02SEjI+5o36g8Hpb5XJg3sRzrjqzDZY9dhsUPLsZlj12WZa14MjESZfcDpW5rSw1rt7Xj2V2d8no8KSKSYNfEKxfV48VvXIQvrprB2SsqwSE4cOW0K+X1Qh/DH2z6AZp7muX3vufCe9BY1oilteyatK1bJRc8QxFHiTiPw1pF3Npt7djWysbowVAMf9hwFFuO8g4MK6ZX4TefOBMvfWMVfnzjEtx9/WLeyvO6FXjoup/hnovu4RosH97/MG54+gZs7TIfvZCJw4OHsbdfsp70ODx4z5T3yM9Re8p9/fuAkhqIqYahKmEEgRENSlYbNmzYsGHjXYJxS8SJohgCcC2APgDLAOwWBGEIwCCAWyG1W98uiuK/dO5XBHADgBYA0wC8KQhCAMAIgB9BOia/EkXxNyq7+CaAHvIv3Ur4/ozHf6bnc9mwDuuOrMOvm38tr8eTcazZ9F0865EmgC3JOjTHGkwV509aRhyQsqe8mq3nsKc8Soi4yRYq4m69fI4UtO2kyhifsaDtd/4IhFIFUv9kYOENXKew5Yo4IIOIU7kx04AeSnqUeuG0MFeCFpUEFyvSeARzVjR+n19eHoqeDCKO2PoVIB8OyLCmjEtEnJkbwFMpI64345y0GpSE8zq9mDlBOjaiCOxNW4AeeRUQ04X5JUCJ9g7zIic778dcEQcAC67nLc02P8A9nWWtaoJMPh5gJNHkssnAUJvidpOEPuzSc72KR4Bgj7QsOORcUUrEaVPETWPLWom4Lb8F0s0pdQslIi5tNTzaSwhaZVh9/lJF3ORuon6evgpwuuA878vyQx8Tn0FrnzmiPW9xPREDjhH7qGkXGHujlSTnZs+TwBo/cO9CTSSJKIqcpbLRbFN6DtXFUyS8Sj5cGgsIkWHGnpLajWVanlkCk4q4kYh11pRHBtXz4dJY1OiXl5stUMT5Qmwf1KYNsZDUMDDGiCWSuPnv27B+t3IDQZHbmT3/9FXwaq+MsRy716LlrXvl1WmuUuBjjwFedXJjTn2ZPM9r6Q1y3zMuvSObwMthlzoWirhQNIGkgsKNO14ur3TdS2PHQ+o73Pogs2z2T+FfR0DHXbP5cGnMrGXqr0MacuJ8jefIyyFKBGYo4jZl5MM9d/SfWLNxDTqCHRAhoiPYgTUb14wbMq6Qirh71u+XHSsoXA5BtqHMIrxzgNpAvtz6csEI50cPPIrHDz4ur399+ddx7qRzAQCLJyyGM0UIHRw4qDyH5zLiWgpqTXnP+v2c4o3C5RDw/qUNeOYr5+PvN52L986vk/MK1aw8r5h6Bf5x7T+wqmmVvJ/WQCs++dwnseKvKywlk+k+Lmq6iLs3yiLiHE4IpXW4arbUiOJP9stWmzZs2LBhw8a7HeOWiAMAURR3AFgI4H4ARyCpz/oArAPwXlEU7za43zYASwD8AMA+AC4AAUhWlDeKovhF0x/exknDfVvvQzTJKynCyRjuq/QDANYnzwYg4O1jyvk/WlBEbrbHNCMuDWpPuedJRSsZURRxjFhTWqmISwdtF/vYcS51l+r3+I+FgY0/ZesrvwY4XVyXZzBaCEXcMrZswNYrjULlwwES2ZnuOBWc7BjMq1Vy6tUOeuM0FBmSM6n0FHLNoLW/8Io4PiOuBH3BKKcA0YtThYgTRZG3piyAIo7aUnqdXixoYMdmV7oAfJjYUs7QbksJ8Iq4ghTY88Hp4lVxb/4cCLPvvDvAW6sWe4yrXTi1VnkTUKE8fp4Qq9mx1QKqhiutl/4mgLMHM6SIy0dmR0d5tcTKm6XGkTnvY4/ty10MsvL8jSQiMlnkEByYdHwze3L6KgCAsOzjCDikYuYURzf63n48cze6QIvrikXH9q3M1q1iMn+M9aB+EVC7gDwgAkOtmhRLw+E4InFpzlDkdqLUoGKLnkO1ifyKOMC6nLjCE3FUEXdcd5YstaYsNWlNeWSIEHEVKkQcUcTpGisyEQsBr90D7x+YkiWSaZ2q0jBQKMQTSdzy8Hb8cydT6lw8pwYNfh9Th1y/SHn+Se0p961jn/3AeuDxz6LFxb6baYs+KpF3OeBzOzFzApuf7qX5s4tvlOxRK5oA5LdLHQtnjT+/dRSBiHTuOgSoH68zPsyWdz+pnPEZj2TM12+Wry2ZoIo4s/lwaehWxBElYpg2yWVkxL3F2VJW4b6t98kKVPn1iTDu23qf3o9cENA5qNVEnJqNaSIp5rShVMOcqjmyZWE4EcZLx1/K8wr92N69HT/Y9AN5/cppV+IT8z8hr5e4SzCnSiKdRYjY0b0jeydUERcaKKg1pdoxBoA3/usS3PvBJVjYkHscykRNUQ3uv/h+fP/876PMzc6JYDxoGZmcFJOKtpRpzKuaJy+nVXMon4inPyw1J9XBtqe0YcOGDRs20hjXRBwAiKLYKYrizaIozhBF0SeKYq0oileJovhijtcIqX9rcmwzLIrif4uiOE8UxSJRFKtEUbxEFMVH83yeNWT/uf59yvhfbcMMOoOdyo+nwpGfS5wFANhqgojjFHFKN6yFxpTz2c1koENRZdA7EsVoKoOlzOdCZbG5ruxMXLe0AV+6hN3oxuMGblZ2/A0YSX1fpfXAko9Ki4SIK7girnOnpFIwgG6OiLP2Zu26pQ34/nULAfDWlAvrJ6m9RBMqvMSasns38JSUSaWnkGsGVBHXVFkYRVymNSUAUwpYLiMuMn6JuJEIK7D73A6UeJx5XqEftEDlc/o4hcuuE8MSWXOIFFt05MOl95nGmFtTprHoA0BVquAdHgQ2M4V1+4A1arhoIoqOoESYOQQHGksbgcUfyt5OdOKH8Rv12c0Nn2DL5Wy8yCTikmIee+YiP5BW0MbDkhVyLmz/KzCaKmpWNEmZewAwl3XFY9+6nISelRmH7YF2ORNmoq8G7oGUxaC7GGg4U1r2lKC5/gb5NRN3PZCfcMwBTuWiVFw/+hpbNqqGSyOooGrUoFjqCRA1XLkXgt6MuhSoNWVdPAE4PcCEeTlewRNxe0xkd7qdbD4TTRRgnPCUMCVnMs5nLmoAZ005BkTcjAklkksBgI6hMLoDYcXtVCGKwO5/AD87G3jpe/CSBqgsIk7FarEQSCRFfOPRHXimmTUXfHrlVPz+U2djw22XZqlDslA7T8p8AySV9tu/Bw6/DDz8cSAZR4uHnUfTauZr+kwcmZxJei6+UbJJXTOY1y41L2lvEiOROH75ymF5/TvXLlQ/Xo1nMiV4NKDcMLHj76zJo7ROnq8roW2EEXGNpdacL7OIIu6gBkWcx+FB+syNCQJkKp0o4kRRxKYWZll8zrRq9XtIlcfHGvSeyGoiTk3tpkcFlwmqirNaVdg92o1bXrkF8aTU+DC3ai7WnLcm65q2rJY1XyraU5bz91WRAhJxaseywV+E+grjDZ2CIOCaGdfgiWufUPzMZsnkbd3bcCIozS0rvBW4oIGfv8ypmgMh9Ys7MnhEcs8om4irH5LmQXXCAGc9bsOGDRs2bLybMe6JOBs29KK+pF758XgCsZJ67BClQsbbx/oN29VxnawnQxHndAHzSDeagj0lVcNNqS42XGzLhaYats9gyM1lJ+VFIg688RO2ft5XALd0E1Jwa8qSaskGEwASEaB7r6HddHPqDWsVcQDwgTObsGJ6FWdNWeWryvGK/KBZAoO9+4BMa9UCW0+1UmvKAijikmKSs9wUE9J77OkwQcSdIoq4XnKTW1NqvMCeC9Sa0ufyYeGkDEVc3yEpZwYAPGVA41m69u9zsd/RSbGmBKTx9YL/ZOtv/hyISB34VmUcto20MZKoZKJkfzTal7XdfrEJTyXPx049KhcVIq7YXSyfy/FkHANhDc0oWi36EnFeLXHul4E0WTLtIpbV1H8Y6D2gupseCzMOOXs0Bxmfp6wEXMxuKrjkM4iI0medGNwDHNtg+D3zquVbTObDUQR7lR/Po1jqHmbHuM7gdSsYCyIQk34TblFEZTIJ1C3gjqsSKHG/rzOAuMGs3oIr4gDD9pSiKGZYU5ok4gbzE3Eup4MjiHSp4k5sB/5wJfDop+Sx20fmxmGHA/JaDqtFq5FIirj10R14cjsbzz557hTccdV8fde2c77All//MfDn90vzPgAtXvZ7nVYxLfOViljQkNF8YhB5SXuT+MMbLRgYlX4bDf4ifPDMHMo0QeBVcTv+zj+fTPBZlOd+SZ6vK4GOvYVQxB3qyp83JQgCfAIbJyRyRZAaTNKfsz+EjiGJtC71urBgUjlqimoU96d2bznWKKQ1pRw7QKBo+6oDNCfuzY430RtSuW7pRDQRxS2v3CLvz+/14ycX/4S7P0+D5sRt7VZwQSmqlBpJUiikNWUhjjFFfUm9anOKGTL5mSPPyMuXT7mca4YBpPFscrl0X50QEzg0cAgoq8czB6RrYb1gK+Js2LBhw4aNNGwizsZph68s/UrWY75kEjcPDMI5/2qUeKVJdddwRB9xRFDsPokZcWnMv44t73kyq4uf5sNNsdCWkiKSJF28SR9e3d+j/cW7HgMGUwqFokpg+afkp0o9RBEXLQARB2TkxBmzp+wqoCIujXOn13DWlGaJOE4Rp0Z0FNB6ihIZTQXIiAtEA7LSx+MoguQ8bFIRZ5aIGyP7z0LbUgIZ1pQuL+aT4u/B7hHEDjzPNp52ISNjNIJ28p40RRwgKRn8KXu60ACwWYqNpdeMRhOKztbhjEJlPArsWZu13QyhA15E0T4YwkBQ4/FQIeIAC+wp1bBnLT+eL/s4e87tA2ZewtZz2FNaqYjjisERUuiefhG33ezpM/B44nx5Xdx4v+H3LHHlULnEI0DrJrY+1aQiTk2ZlEexxDWQGLxu0XOnLh6X+uDz2FICQFWJB5NSXf+ReBKHe4wpgSgRVxBFHGCYiIvEk7J9rcfpgNdlXJksiiKviFPJiAOARY3s2t6sRUEb6AKe/BLwwCrg+Eb2eFEVHKt/zB9jIb/VopVIJkX81+PNeGIbUyJ+bMVkrLlmgf4Gk0gQAH2N9N1EfX60OVP23xDkInI+WGWvSu8jgnFrFXFDozE88Do7b25+zyzZ6lwV9Hs9/KJ0fqSxZy3Qn9qfrwI48zM5d0WtKa3KiJtQ5kV5itQOROLoHM6v+qSNESFBkD67g/0e32phzS/Lp1TC5XRged1yxX1dO+NaxcfHGoUk4tKxAw3+ovy2rxoxqXSSrEhLikmsP7reks/6g00/QHNPMwDJVeCei+5BQ6ny51xWxxRxu3p3ZV8zBIGzpyykNWUhjnEm1EhjNZI5H6KJKPe9UZUjBc2J29u/l8veq7WJOBs2bNiwYUOGTcTZOO0wu3I2tz4xIWJNbz9WB0fhmH8Nlk72y8+9Y9Ce8qQr4gCpyJ22DRtuA9rf4Z4+ThVxBSA8AJ4kExNFeGW/glWWEpJJ4PX/x9ZX/AfgZeQblxFXoHBvnohTsCrRgC6qLLA4Iy6N82ZWQ3Cx41zpq8yxdX5QRdyQSr4H3EWm7NnUEE8k5e5jQLoBtRrUlrLC45eXd5uwQTNlTbnj78CTXx4T+096k1tjksRQQ6Y1ZZnPjWk1EvmQSIoI7SVEHCVfNGJcKOIAiUC8kKjiNv4UiIxw1qpmzt9jw8fk5cllk4EjL0uEHwCUN8rWmMVCBOc4JMWuZlVcDiKurqROXqbWgqrQQkaIIq+WOPsmydqPYi5RcO//p+rbUUWcWTKZI+IGyDFJ5cOlMbmqGH9zXoukKBXfhAPrge59ht4zp8qlbYtk8QlI369KJqBmXHqHNFZTCM68iiVqW1hr8Bhn2VICwMQlml47n6jijI7LVKWQtiWzHAaJOJoPZ1YN1xfuk5s/il3FqCuuU92W5sQpWtnShpC7JwM/WQRs+wvSxBQcLmDFl4CvbgPO+hxXgA7fdiyv1aJVSCZFfOsfO/HYO4zM+fDZk3HnNQuNqbxf/h6A7PnMcV8RkpCadiaVTlJU0iiBaz7pCiAST+TYWh3U4t5qRdxvXj8in4fTakpwvZYif+UUSS0MAGJSapYDpPH99XvZdmffBHjVCaBEMoETI2y8VSNH9EIQBMyqI/aUXfmb9LxkPA47BMl2k8y9+Hy4agBQVWy9cPyFk5Nbm4FCEnGARBRtuO2S/LavOmC1PeUj+x/B4wdZnuvXl38dKyauUN2+pqhGmmdBcnXY07cneyNCGkXIMGO1Ig4ozDGmuHnZzZzNexrFruL8luQKeL3tdfm8ayhtwJLaJYrbUSJuX/8+7pjWCQOca4cNGzZs2LDxboZNxNk47bClk+WlXVZ7Fv51vBWrg6NSptrk87BsMiMy3j5qjIg76RlxgFQopsXNDDUFVcRNLZAiLm1NBQBi0oeNh/sQjWuY5O97BujdLy17yoCzP889XfCMOACYxDokjRNxhVfEndHoh4tYUybi5r5Lqu4acggK5SkAsVHg1f8z9T5K6BgKI5GU3nFCmRc+t/UZZoORQXm5prgSTod0R320b5SzC9MD3Yq46Kik+ln7JWDtF2UbLBkFsv8cCyIuEuetKQGmEPAghuITRFkxQ18+HMBnxJ1UIg6QrLoqUiqJUD+w5beWWVMeDxyXlyeXTwZ2PsaeXHg9MPsKefVix3YAeog4kmdVzhd46otZp3T3qIbGCS1kxJGXpaxNAHAVAWd/IXubWZdJJBEgEVIBZYukvURh8r11e7CWKGL0gh7jptHUsSuuAWoXcNs5HAKKJ83FC0lyTXjzpzACTuWS2URipS0lIJEiV98PlExgj4lJoEFZ0ZEGbSCpNWhNySniEikiQoMiDrBGUTSerSkN5cOpqKZbhlrkTaZXTGdElML2i4kijhsrIiPAhp/yDSHhIf66NOty4D/eAq74gWzdR4m4SOY1rEAQRRH/8+Qu/H0LI9FvPLMR379uIRwOg1bLKgr/FmJhPbViqubdlfvcmJxqbosnRU2EkBLoWGElEdc3EsHvN7Dz5mvvmQWXU+Pt/hkkp3THQ9L/B58HulLju7sYOOeLOXfROdqJuCjNtWqKari/0yyoPeWBrkCOLSX44qzwHxEEyWKTNEJtOkLy4aZXIRANYHv3dvmxh1Y/JBO0hwYP4cHdD5r9E0yDI+Lc1hNxhcDlUy+HyyGNhTt7d3KNSHqxrXsb7tp8l7y+evpqfGL+J/K+Lq89JSGNCqmIGwusnr4aa85bg4klE+XcNgA4FjiGtYfW6t4ftaW8ctqVcAjK48m8KpYRKyni6iF+W7re18NWxNmwYcOGDRtp2EScjdMOmzs3y8tnR0j31dwrAacLZ05lRJxRRRx3A32yFHEAsOA6tpxhT3msn1pTFkYRR28IxYQPI5F4/mMqisDrP2LrZ32WC08HgBKipiiYIm7iGWy5azcQy29zkwlqo2a0oJkPHpcDPh/7bEe7zOV+FbmK4HFIHZ5RQUBYEADBAUBgOU4A8MpdwPa/mXqvTNB8uKYC5MMBPBFX6fNj5gRWuNlnMCdOExE30gNs/TPw0IeBH04H/v4RYPtfpMK4Egpg/zkm1pREEZcuUCxMKTGWOw7AlSCKnyptmTsUVBF3Uq0pAanZ4YKvs/WNP0VfPxvfTFlTErXW5KI63q5x0Q0ScZXCJY5tAETtuU9jbU1Jsz6XfVzK4MxEcRUw5Ty2vv/ZrE3WbmtHSy8b73tHorj9iZ2GyThqj9YUT5Hw0y4EHNlT34WTKvBAnNgtNT+iShbmAm3SybKbO0qIOLO2lGksvhG49RDZnwi8+sOcL+nmrlsWKeKcXqB2Xo5XMBjOMiOgKoXxZk1JFXGlWoi45kckcoCqpp/6CrDhPhxpe1PebHrRBMke8M2fS8/T7Z/8Eqa/9jXc4X0IP3H/DPeF/xfx+5YDP2gE7moAnv+f7IYQQFLBfexx4KOPADWzuKfoWDwWRJwoirjjyd342yZGoP/bskbcff1i4yQcoGrV2lLGxqlp5fquVQsbzJ/DVD1r5Tz3V68exmhUIsfn1JXh6sWT8ryCYP61QPp779wJdO4C3iDuFcs+qTy+E3C2lKXW2FKmEYoy9eH/e/5A3muDj+RohtLkSqoRqm1gVLaaLvY4saihAm91vCWTiPOq5mFhzUJ8ecmX5X38asevOFvpk4FCK+IKgQpvBc5vYPbPRlRx646sw6WPXopPPPsJWQU9t2ouvn3utzUpZak95bYuhebL04iIAyQy7l83/AvNn2zGZxd+Vn78x2//GH2h7DxiNQxFhvBq26vy+lXTr1LdliriDg4cRKK0Dg+8I12fa4UB9NlEnA0bNmzYsAHAJuJsnGZIikm808UsGs9q28WenHcNAGBJkx/pe/p9ncOGVDLUwuakZcQBwLSLgHTm1+BxTtl1jFpTFkgRx1lTJqWb91cP5MmJO/wi0LFDWnb5pND3DIyJIq7ID1TPlJaTcYmM0wmqiKstkCIOAEQHOwZ72vTbilAIgsDnxDkcwIXfBNYMArcdA6ZfzDZ+6ivAkVdMvR8FryYqDDnMWVN6KyxRX3BEXLCLKRF+PAd49NPA7y4DfjQLeOrLku2eljGB5FFYBdptOqHUejsdgM+IS6vXFqas5i5yNLMNDajhAL7oMR5soLDko1I2EgCM9uLC4aflpxrMKOKGiSKurwVIF2JrZgP1iyWLsFRW5hRHN2YIJ6yxpiTWdpYQcSe2AS2pIo3gVBzPZcy5ki0r2FP+33P7shS6oVgC96zfn/9zZiCRTKBthBBxsdR1PsOWMo2FDeV4W5yDrcnUNSERBTb9Wvf7qlpTRkeBVtYkZBkRl8Yl/8OWdz4C9BxQ3bTbgusWr4iLA/ULNedBLiAWins6hiEasEEez4o4Oqcs82o4Ji/eKZEDFPEw8PwdOLyRkSDTmv8B3L8UWP8tZnGaRiIKx67H8BnhaVzn3IhznXvgGjgkWfHlQjIBzHyP4lOcIi5euALq2m3tWHn3i5h2+z/x57eYUub9SxvwwxtMknCAsoWruwgtDYvl1WkV+oi4BZy9qrF5Bc2TtKqhr2s4jD+9yY7hLe+dre/4+Sr4cfqftwLHU2Swww2c92Xl1xFwlsBlTdrfOw/WbmvHP3ey5ojRaCJvo0YRUcSFqYpnqI1Twy2fUgm304HX21izxAWN0hj9kXkfkZU+kUQE39v0PUNjllU4FYk4INueUs8xXHdkHb698dtZKv5rZlyj2VKWKuK29WzLtmgkc/IIIeLcOnOOxyO+cMYXZIvY4egwfvT2j/K8guGFY8ySdX71/Jw5pdVF1agtkpq9QvEQjgkxfOEZ6VplW1PasGHDhg0bDDYRZ+O0wv7+/bJipcbrx7TelD2Lp0wirQCU+dyYUy8V1pMisP34oO73ofZpoXjIkOe6JXB5JKVfGnueBCAFtQ+OShNnn9thuOs9H+gNIVJEXM6cuOZHgIc+wtYnnweU1mZtVqhO4SxwOXEKViU5EIknMJA6xk6HgOqSwhzjWCKGqCgdA1EU8E5L2HQRoMLBSJohlwc48zPSitMN3PgnZt2WjAMPfwLo3mvq/dKgRFxTVeEVcX6vn8tz2WOUiMvMiEsrEQKdwO4ngNZNyMqgqZkDnH8LcNHt2UVAQCqAjvZnP24CPQF2k1swa0qijMi0pryQEnEzjRFx40oRB0hj7Pm3yKufdTwFHyLwF7tR6jWW/xRLxHAiKJFlAgQ0HmTdxlh4AyAI0vsS0uhix3a0DYQwEMxzTBJxYIQQbKTLG8jIiNNCxFU0MkvJQEc2YbDhPra84P08eZEJeq068ioQ4UkCmh9JcWJQf7NL12iX3DVflUiiJD1mqhBxUmFdwK/jpNv77d9lfcZ8ULWba90EpAmjmjlAmXrWlyFMXsHIbzEpKZpVQJWzRrNNaUG0Pp7QnA8HAJMqfPAXS8XNQDiO1n793++YEHFlE4G08m60Dwhru35Qa0pNirghdYXNEQ/7O6fHDP6dTi/7DWdCRS0GjI015dpt7bj9iWa0D/K//WVNfvzoA2fI1tKmkLZwrWgCIEj/X30/Whxs3q6XiJvPNfgYU8TltLHNgXVH1uGyxy7D4gcX47LHLuPURT9/+RAiKXv4hQ3luHyBgXHmjA+z5ePEavqMD+Y8X9LgFHFl1ini7lm/H9EEf6+Vr1HDS5SzYXouVTRm5cOJoog32t+QH7ugQSLiXA4Xvn3ut2U7vo0nNuLZlmxF91iBRgKcSkTcqsZV8r3d8cBx7OrdlecVEpJiEj/Y9APFMejPe/6s+f2nlk9FpVdyXxmKDHG2vwBOO0UcRZGrCP+74n/l9WeOPION1EY+B6gtZS41XBpzq5kqbu8II8lLhTCCgUFN72nDhg0bNmyc7rCJOBunFagt5VkD3cwZvXYu4GYFp+VT/PLy28f0F8OdDidHxoUzu5PHEvOvY8spe8pj/UQNV1VivqNYBfSG0ClKRYV9nQFOKSaj+REpo4TeTB3fyAWnp8Ep4qIFUsQBGUScvpy47mGqPvJaUzBSwECEWeGJiWKcGIzgeL+57umKECsoDs5YxReFfeWSTVX6pjQyBPz1A4Zs2jLRRj53oRRxWUTcRELEGbSmLHYVw5kqZIYdAhSpEMEhEcuXfQ/4ylbgy5uB96wBLr6NLwKmEeyW7CsNWKKqoYcq4sbQmrKyxINFFWHMd0id+KLDBUw9X/H1+TCuMuLSWPoxOWttgjCMvd5PYz3+Q3Hs0oL2kXa5eaOueAK8h19kTy66gS3PvlxelOwpgV35ir7BbkBM2XcV1wAu/jzgrCmDGog4p5svvg4yJR/6j8jNHwCAlV/Nva/KqUDdQmk5EQEOsb+7dyQCtRF0kl8/ac+pMtIERuVUoHKK4vYzJpTA63Lg+eSZaEmmxsPwkGQ3qwNcEwm1pqS2lFbkwynh4v9my7ufUFV5W2JNSRVx8YTmfDhAUmUvMElkUJVCwawpHQ7AT86XQW25Rq8QV4A3Dvbmts/r2Q+onfkOF1q8bDycXlQnncNqpJqnFHvmfw3fiP47Pha9Hf898QHgmy3A/3QB7/+VoioMl96h+tFoUwQd963EPev3IxTLbmTrDIStnVMtvhG4ZZek/L9lF8RFH+AK8foVcez83dsRkLNv9cCIxf26I+uwZuMadAQ7IEJER7ADazauwboj69A2MIqHNrPx+RuXzdFk2ZeFGZdIzYuZWPk1TS+nSmQriTi1hoxcjRq+mjnycjh9LFLn/aYWkg83rQr7B/ajJyT9diu8FVhUs0h+fkHNAnxkLmsi/L8t/8e5L4wlTlVFnM/lw6WTWYPWupb89pQtQy341HOfUrWE7wxqvy8RBCF3Tlw5I+IipxkRBwArG1bifdPeJ69/763v5a1ddIx04O2utwEADsHBvV4N1J5y3wBPkrt1fF82bNiwYcPG6QybiLNxWuHtzrfl5TNHCYHTsYMrmp45pUpePuVz4mZczG6aB1qAzp042sc+z+QC5cMB/A3hvDpW4H11v4I95Yt3ZmeUxMPS4xmgxcyCWVMCwCSWGaCbiKPFzALaUg6ECREXlwjKNw9r9/fPQqATFSPs+xmadXH2NhWNwEceka3xMNQK/O1GIGLuu+AUcWNkTUk71/d3BhBL6FevCoLA21M6FS6d/3kQ+MyzwHlfAapn8M/RIuAHHoRceD3+JrD2i0DSGkVtLzknC6WI46wpSaH2+gp2w93jXwJ4jRWI6D7HDRHn8nLkiSAAdckexJ/8iiEy7niAFUunCD7JBhGQyAx67pCcuLMc+1GG0fz2lDlsKYFsa0pN6lo1i76NP2MZiDMu4XM31aBiT/nzlw9l2VICQJHbiVsvn6PwTG5wRFw8ty0lALicDsybWI4kHPhdgnzGt34BJLSfh9RujlO5tFAizmJbyjQalwOzSaHs5R9kbfLw5uOcdeLL+3Io2HOAkri1iQQwaYmu15u19hsTRRyg255y7bZ2PP4OIyJCsRz2eZER4OGPI0tNDQDuIgSuvhfdqUuN2+FG45feAW7eoU6qXXUvfBffiseTF+KN5CKs76mCWFQpDVgqqjAsvlH1b6E5fIWyplQjUToGC9vc1j3aLc/byz3lqPblzj3LRG2ZT252CcUSaOnVPzeieZKcejYH7tt6XxYpGk6Ecd/W+/DTFw8hlpDOpeVTKrFq9gTdnwmAROJn2msLTs1z5EJZU6o1ZNTlmH/7qtj1NCw45PO+Y8rVckObz+3A4kY/Z0t53qTz4HTwhPeXl35ZbmTpD/fj3nfuNfy3GEUsGZPjEByCgzuHTgVQRdWzLc/KqvVMxJIx/Hbnb3HDUzdgW7f6eVdfos/iPWdOnIoijo6Dpzq+edY3ZfK2NdCKB5ofyLk9JUvPnXguaopq8r5H2sYVAPb278WTX2HkZ2msF+FYQullNmzYsGHDxrsKNhFn47RBIpng8uHODpGb1USUI3yWT6mUl7cdHzTUzcrlxGXadY0lXF5gDim+7VmLY72sADi1gEQcVaudN411virmxA21ZT+m8niRq0hWIEUSETk83XJMXCwpmQCgZx8Q1W4PxOXslBmz99KC/jDr2hUTUpH3zSMmiLgtv4M/wY7nYHGl8nYTFwMf+CPrvu/YATz+Wcn6ziBaB6gibmysKf3FHjSkCjjRRBKHe4yRiRwR58i4dFY0ASX5b1ABAAuuAy77Llvf/QTw4ncMfSYKURTHRBHHWVMS9dq54g55udl3puH9032OC2vKFEYPvJL1mCsRxuiz6ooSNXCFyiBpBFl4A79hWb1s+ecWEjjfsRO78hJxpOCfUvFRlHvK5WtXKB7S1uhAyYj+lIpkpAfY/lf2uEa1BGdPeWA9kIihtX8Uf32LkZNVJR4IABr8Rbjr+kW4bmn235EPvCIuNWal7KnVsLBB+o0/mrgIIbdfenColVf95QFt0JHnBZEA0M7mJphiTC2qCRd/iy3vewY4sV1eXbutHXc8xavkvvWPXbkVWwqIJCKyUtspiqgW3MCEuXlexcO0Im6siDhKwj75pbzE+53P7JHJkDQU7fNEEXjmFqA39bjgBkrrwFknNi6RN59SPgUuR8rmMgepNrW6BGUpy9zekShv95qhCstFwgH8WFwoRVxViXKR24gKVg+ODB2Rl6dVTDOkHFtoMn/WiAW7mgKoM9iJx7ayufQ3LpttTA0HSPdKmQSJmFBsmlMCZ01Zap0i7tbL56DIna0GnVylfo9D79PC1/5UPu9pPtyyyZXwuBx4vZ3kwzVkN0uUuEvwrXPY+Pr4wcextUufpb1ZBMk9Sqm71Ph3fJJwdv3ZmFAkEcT94X5s6tiUtc3evr34yLqP4L6t9yGalOaAAgS4BN7m1+f04eZlN+t6/5yKOJWMuNNFEQcANUU1+Pryr8vrf9j1BxwaOKS4rSiKeOYws6WkGX+5wCni+vdh+fyZ8nodBrgsaxs2bNiwYePdCpuIs3HaYN/APtkqsTYex5R4xo0kIXwaK4tkS6aRSBwHuvTlwAD8Dd5JVcQBwPxr2fLutXj9AOtyf+TtNt2FNq2g1pQXz54sL79+sAfxTOWRtxSKUMicEASBK1JEkgWauHtKWAFRTAIdzbm3J6D2m7k6cs1CkYg73GcsJy4WBt7+PSrId6Nm+QIAmPVeYPWP2fqB54Dn/ksqIupENJ5EZ+qYCULhCm2ZRBwAzKP2lEZz4khhiiPi8th7KeLcLwNnfZ6tb/gJsOV3hj5XGoFIHNFUNkyR24kSg/ll+UAVcd607WEyienDzBZ4fXiB4f17iZXiuFHEAfCFlAugao/nwrFhZnE3uT9NGAnAwuuzNyb2lJc6t5lWxAmCoN+eUkkVtOlXkqIZkMhCrXaLE5cwgjA8CBx/E/c+f0DO/lk+pRLv/M970HL3amy47RJDJByQqYhLnUf5iLiUSisCD14qu449seE+zWOeYu7T8beYXWjdQqBEn/pGFyYuBuZdw9ZJVtw96/fL+VFp5MtYUkJ3kM0vJiQScNYtlCxMdWCBSRKDqhRiOhSLutD8CHBsA1sPDwFPf1WRjAvHEvjftbvQr5LhmKX8evv3wE6yn2vvB/7zAEeSUbJoesV0/vUqpJrDIWBBAzu2zW3G7fNoAbpQ9p/lRdnXKaMqWD0wY0uZhllVJ53jar2HqC5SHju8qJIbCs+bUY3zZmhsDFKCjqa5rE0iQ/Kc0uf0aVLQaMV1Sxtw1/WL0OAv4sxctxwbUCXz6TlMyeRNLayZ7Zxp1RiKDGFHj9RMJEDAyoaVivu7dPKluLiJuUjc+eadhRt/FHCq2lKm4XQ4ccW0K+R1mm8Yjofxk3d+gg+v+zD29e+TH59fPR+PXv0ovnf+9zCxZCIECJhYMhFrzlujmRxKY17VPLnBoH2knZ//eMtkF5DIaaqIA4DrZ10vE5JxMY4737pTMed+/8B+HB46DECqd1Bb0VxoKG2Qz82hyBAav/io/Fy90I/ekfHTYGfDhg0bNmycLNhEnI3TBls6tsjLZ4YV8mYI4SMIAqeKe9uAPSW1BAll2riMNWZeymwE+w9juJURSkOhmLo1kgkkxSSniFvSUI/6cukGZzgcx/bWQbZxPKJsv5eDxKA5caFkAY8vlxOnvbu1i9gA1pUXThFHrSndkG5uugMRHOnVrt6TsetxYLQXFUlmDZI35+LMT/Nqly2/Bd78ue63PjEYkmvZ9eU+eFyFufzQvydNxJkt+iI8jPIBVtgf9pRAq72XIgQBeN//8TZy//xPSSFkEJwtZVnhCgecNWVaMdHZDE9EIox7xXL8s7fGkMoYAIqcjKAdL4q4aDyJE0nlAqja47lArSknp/PLpp6vSJxhFiPiLnJsR1t/EIOjOY4LR8RNVNwk054yLzKJuMgIsOU37LHzvyad01ogCJw9Zf87/8A/trNr039dMdeSLv8sRVz94rwEGC2s/zp8CeBi5zdaXtX0vpw1ZTojruU1tkGh8uEoVt0O2f72wHNAm2TZbSRjSQmdo4x8lvLhluj+iNNqSmV1S3cggp6AvmabMVHEvXgnkLnvWChLGbS3YxhX//QN/Pkt9Qw5rvHkxDbgudvY+rJPAEs+kvWaI4OEiPNPz3peDYsb/fLyzvZBza/LRKEz4t4+2o+WXkZAmVXB6oE1RJw5VSe9h9CqiKv2Ko9hg10r5OVvXDZb92fhoNAcl/Nxgsx8OKsVW9ctbcCG2y5By92rcclcqaFEFIG7/rlPsTmNO4fJ3OUtoohbMb0KG09slMmIRTWLUOVj8QWZ+NY53/r/7J13eFRl+obvb2bSK6EkoffeQRS7oNi7Ym/rWld/uqu7uu6qWNa+tl37rq5dERELKiCKBaWH3jsECIT0PuX7/XEmZ84kM8lMMmnw3teVK3PqnJk59Xu+53nN325L4RbeWvNW4z5UGBQ5ffev1pSGtoRVPJu7cy7lrnKW5izl4i8v5r+r/4vb22klxh7DXWPu4v0z3mdA2gDO7H0msy+azcprVjL7otlhi3Bg1BYd3nG4OVwr9tIbT1l1iDriwIg0feCoB0yHddb+LD7d9Gmt+axuuAndJ/h1MqoLpZSfK85Kusr3e1YRBEEQhMMVEeKEQ4ZF+3yODL9YSggo+FiFuGUNEOLiolqHI664wsnczUWsThhvjjvd5h/30ZBe7/VR5ixDe2ubxDniiLJHcYKlJsU8a524dV9CdUODshOKiJEQ7WvQrNBNWC/EKsTNug+eGxpS3af9RZYacU0UAwj+jriuyb7v99dw68RpbbhYgBSLKGp1kAVl4oMwxOLWmf03eKo3TEkN+fuy1odrqlhK8P88yTFGQ4W1TlyDHHHzHie5yrf9RWc+FXK8V1Bsdrjov779T3vgk+vCrlVYzXRLLNW+woomc8FaG2TNRq4tc81xP3uGUVql2dYQoZjW54jLLankiv8s4CnXZMq0v8CpNXwYFcDFVg+7inwiUffq2MShFwaeufMoSDCO+46qiOFqa91isp8QF7gx2yrE7S8LoUZYTSFu2duGOwigXS9/B1YoWOIpPetmmg2oEwZ2Ylyv4A2goaK19hPiujpd0LtuNxxA/4xEHDajAW5lnoOqYZf5Js5/MaT39nO5VNd92m6pD9ezierDWUkf7O+u/OEfAMQGiHWD8N3JVvE23eXyv4aGiN2mGJjpc3SEK2RYhbimcmvV5wzSWvPW/G2c+9J8Nu33dUqy1dAe/Bxe5fkw9WpfXciMYXD6UwHfpk5HXB0M6+ITlFdlN8wBDv4N0E1RI+7VH7eYry8e07XRLthw2FZkEeKSG++IW51dFHZKQcAY2zpYvG8xGwoC38c7EjYDmpMGdGRMj0aeQyc+ELgGYQjO/6aKpQzEX08faB5rv2zODRiJb+3YU33vsr+owrw/iXbYGNEtlV+yfzHnO7Zr3dHBGQkZ3D7qdnP4tRWvsbNoZx1LRA5r58e26IgDGJw2mJ7JPQHj2Xnc++O49ttr2V603ZxnbPpYpp8znWuHXuuL5I0QocRTHqrRlNX0bdeX64ZcZw4/t/Q5cstzzWG3x83X23w1fM/sFZ7oGUyI66TyOVgqQpwgCIIgiBAnHBK4PC6WWerDHVFR6e3NHlzw8XfE5REuzVUjbkZWNsc88T297p3JMU98zydLdvHLplye+nY95700n5EPz+H6t5fw7xxfHNwZtkW11hNur/f68ItIiTIeCE8c4BOK/B6Kl1h6jJ54b0gihtURV+FpQiGurMZvX7graPyUlf3F1mjKJnTEVfpE4v4dfA6XBeEKcTt/M5wdQCq+B9t6HXEANhuc9wp094m9lB0EdMjfl7U+XLd2TVe3MJAjbrA1mnJvmA1me1fCwldJtoiXRZGqWRidAJd9DCneWFdnKXxwCRSE16gzIyub137yNdo63bpJXLAQpEbc5u/NcT+5jd7GDXEIgH+jR5PWfgqBNXsKOfff81m8PZ8vPMdyr/P37Pa0N52dSsEF3cMTHJ0eJ3tKfGJZV5cLbA7/eGErNhv0PcUcnGBfXnc8ZT3RlIBfNKXV3RSUmkKc1RF79O2GqBwOPY4Fr0jewZ3DILUTpeAvp0Umji6/Mt90mMR7PLT3eKD3ifUuF+Ow0z/dIg71uArTWbZlLuxbXe86rI3rZc4yKC8w6muCUY+0x9GhfozGceJfffVPt3zP+oWzKHe6a83WkBhAa5xXuttt1jEMl8Y4lf2iKZvqPBHMAWSzc3DnOq7732Ie+nKtXyTw4xcM458XjzDj8/wcXh4PfHaL7/wekwwXv11b9PDSUCFueFeLELe7oGEx1gSP9YsEG3OK+W6drxPATSeE/vkiQSQccd3S4kiKNXwyhoIAAKKRSURBVO6lCsudZId5j+0XY+sqrfN30lrz7JJnzeFz+pzDh2d+iPKenxyJG3AkruVPp0TgHFpHDcL68OsAkdS0Qly/9CQuHeeLxH/s63W1IvEDOeIWbPPd84/qlkq0Q/kJcYHqw9XksoGXMbj9YACqPFU8vODhBh9n4WB97rI+I7UllFL0S+0XcFq0LZr7j7qf/576X7ondw84T2MZ3Wm0+ToUR9yhFk1ZzY3Db6R7kvEdF1cV89RiX4eQRfsWcaDceIZPi01jfOfxAdcRjEFpg8zXg0/tY75OVwUSTSkIgiAIiBAnHCKsy11DqdeVlu5y0S22PdxZd1H6IZ1TiPHG4+3KK2d/UXgNDdZYmaZyxM3Iyuav01eRXVCOBrILyvnztJVc+d+FvDxvC8t3FZgRcPM8IyjTRsNJP1s2fZV/b+5I1+Sy1oer7pl5dN8O2L1dVFdlFxpxUwc2wA7vQ66yw6irQlq/1VnQpELcsndqjwsQP1UTa424Tk1ZI67c12gworOvp/iCrWHWiVvwivkypdeJ5uuQhDiAqFi49ANDNKhJCN/XbosQ11SOuEp3pRkT61AOs6Gia7s4khvSYObxwMw/gfb4C3F11dULl6R0uHIaxHobT0ty4P2LjQb8EHl61gacbv99oSlcsFCjRpw9BiqLYdcCc9wvnmFAAyNA8e/g0JLRlF+v2stFr/xm7itKAcMu5pL4N/i9825zvj47pkJ+8Ei6muwr2YfLK+R2crmI0xr6ngzxdbgY+k8yX55kq6dOXJFFfA3miEsI0xEX1w5ivPunq9z3HgkdA0bq1YsjGt3P95lOsS3l/JFdGJgRmaitmrGUyh7t34mgDoZa6mstLW4Hg872Tfzt3/UuX6txfft8w+0KRjxmXGpI29FoOvSD4ZeYg1VzHjFfx0XZGhUDmFO43Xyd7lG+OqthYnUUhetUbpZoykDOIACPC/ubJ1O5aZ45akjnZL68/VguG9ed80d3NePz/Bxev74IG7/xrefcl6B9HwJR6a4ku8Q4zhSKHsk9Qt7s7mnx5vUuv8zp50YPBz9HnDuyLgarG27S4HT6dmo+d0+ps9Q87zlsDrokNcyBp5RqlJgcZYsi2mY08nu0p06xc9aOWaw+aHQEiLZFc9vI2xjaYSgdtM/pm9rta/qkh1erMShBahDWh58jromFOIA7T+5HQrTREWRjTgnTlvo/91j34ep7w4VbLfXherdn7cG1ZvJEWmyaKbDVhd1m58HxD2LzdnZYuHchX239qp6lGk9brxFXTXU9vpqkxqYyecBk83ttCoZ3HG6uf2P+Rr/vtDrOu8riaq4+Rg81Yh2x/P2ov5vD32z7xhSkrfvy6b1OD9uVaHXEdb6um/k6Q+WFHUMtCIIgCIciIsQJhwSLF75gvh5XXom64HVI7FjHEr5IkmqWhhlP6eeIa6IacU/P2hCwF7sVpYzGw6uPH0RJ9wnmeKsrriG93uvDr2emtz5dSlwUY7r7nIY/bzrg74YbeEbQukU18XPENWU0ZVEQ11AdhelnZGX7RVEt2xl+tGmoWB1xQzO60C7eaGg5WFrFxpySYIv5U7AT1vserJKH+yLXQhbiwBALPEH2xzq+LzDE7mq6pjWNI876WZJjks36JEqphsVTZr0Du43ak8na92QeUSEOoOMAr8jpbUQ7sB4+vhJcoQlRwYTFSLtgIUA05bafwWMIS0UpAzlAKgCr6xKL6iDKFmX28nfjxuWJkPswRDwezbNzNnLr+8vMc29SjIM3rzmCFy8bzfx7J/Lff/wduh3pXcAJ8x4Pef07in2inS+W8qK6F+ozAa2MhpDhtm3s2bUt8HxaQ/Fe33BS4HOt1RE3beM0Jk2bxMytM4O/v1LQLoAQcORNQd089bEq8Rjz9amOJfzxlEbWNbLgJ8S5XNB1nOE+DYGhlli/NXuK4Jg7fBNXfFhvHG+txvXtltpyzVEfzsoJf/FGQcNw1yrG29YQG2Vjzp9OaFQM4P58n4iSntQV7A2LDmtMjS2rS6HJoilrOIN0XBpujO8zlRLejXqcK+1zuOG4Xky/9Wj6dqrDobL9F//OKuNvg8HBI123F243a1Z1Sezi5+ypD6UUw6yuuAaei60xwdYOGI0lu6CcL5b7nLs3nxhYjGwqtluE5O5J3f1E3XCxiskN6XwSMMq2Bk63kxeX+aJxrxh0BZmJmSzdkc/WjcfjcRnrqOQgr698PextiCRWIa5bUrc65owMnZJiuekE3/7z7JyNlFb67hmsz2mmI84ixB3VO42fd/uig4/tcmzIItDg9oO5YtAV5vDTi5+moKIg7M8QDtZ7z7YsxFW7rWqNLws8PpIkRicyoJ3xPOzRHlYe8NVUJykTDVTafPvAoeqIAxjfeTxn9T7LHH50waMUVBQwd6cvbt46PVR6pfQyRfBf7llAgff77EQ+B0tEiBMEQRAEEeKEts/uJSzK9j1IHdHt+JBiqMA/njJcIc6vvkMTCXF1NaRfPb4Hr145mqz7T+Gr24/jvjMG0elIX6/Vc6MXNarXe30Eq1VwgiWecv663bDiA99CY3yZ9PXRbI64YPFTUXHgrt3TfkZWNvdOX4nVjPbYzHVNVpMrv8K3X7aPS2N8n/bm8G9bcgMtUptFb/hcGb1OIDXTF80SUo04K8G+ryDum2qawxFn/SzVsZTVDM60uC/2htBgVpoLcx40B5N7+0TuosoIC3EAPY814j+r2f4zPNqx3hp8B0sqa9UkqibSLljwrxUUa4/1qw+n+k40X6/OLmxQVJNSyq/ROdJOjLoorXRxy/tLeXHuJnNcrw4JfPaHYzhpoE+8Qik4eYpveMVHkLM2pPew1pLp4XKBIw4GnF73QrEp6O5HmYN9ixZQWB7ABVR20Fd7KiYFYgILA5vzN/sN7y3dy5Rfp9QtxtXsEW2PgSN+X/d2B8Ht0TywNpMqbYgaQ9R2utnCjNqtg5qOuFDvB8BfHFqdXQhdx0JaX8sc9cfx+sVTbvdFnjW7EJfWm0pLnbu7HJ9wy/F96NrIaOAcS7RqRoeGueEA+qcnmTX5th8so7gidGdbszjigBnuYzim8kV6VbxPv8KXuKDyQXJ0KgAO5eHRqLf4m/4PMcoTfCXFOTDtd6C9nVi6Hel//giANTqxT2r4QtWwLqnm65W7GybEmdHDRFbs/M/PW3F5kxyO7JXGaEvnrebAGvnZ0FjKavzE5AYInrWibAMwdeNU85yWHJ3M9cOuB+C5ORvBE0/lft/14+21b/t9vuZmd0nzOuIAfn9cL9K9qRT7iyt542ff5695L3GguJItB7z14ew2RndvF3YspZXbRt5GRoJRVyy/Mp9Jn05i+NvD6+/c0kCycnxRijM2z2iS92gOqr+zUMdHmqB14pIysF5NopSjSd15rYG7x95NijfxILskmxvn3GhGe/dM7smQ9kPqWjwgDpvDjB+t2FHB6nhj/dHKTWVh04utgiAIgtDaObTvLoRDn4pCnNOuY1mMr8faESdOCXnxsX514hruiAv2AN1YqutP1KRLahwPnzuU04Zmkhpv6a3Xb5LRsAv00TvZFnsF82P+j/Ps8yO+bX7RlFEWIa6/T4hL2PwFVHgbJ9r1hN4nhbz+ZqsRN/EBXPYAvc2dZRS/eQHfLd/M279u54lv1nPnR1n8ZdpKKpz+jW7lTk+TxAACHKzwNVC3i23H+N4+Ie7XUOrEVZXCsrd9w0fdYj50ARRWhSmYBIvrSsowohwDMCMrm+W7CszhdaEIYQ0gUH24agaHGyE15wGo7t2c2oOkIT7XUsQdcdUMvxgGn+c/ro5Gf601f/tsNZ4AP19TuGDB3xEX44iBzT4hLnHIJFK9js2iCleDI9GsDcCRdGLUxa68Mi585VdmrfHVvzquXwdm3HpMYKdLj6ON8y0AGr5/NLT38ROJnIYIF0Qws2Lrf6r5eoItK3Cjr18sZeD6cACfbPyk1rgKdwUvLHshwNwY+96+lf7jtBs2zalzm4Mxfdlulu/3sMBjiQDb8E3wBcJkd5GlTpHLBb1PqGNufwZlJlNdHmbLgRLKq9y+84AVZznMui+gQ9jP5XLQe11QdrCIqc3FS+7zTcFzrG0jt3Tb3uh15lT59r1OGaPrmLNuYqPsfsfWur3FdcztT3MIcTWjwV0ezQrdl3MqH2V7tMXBueS/8O75tevNArhd8On1RuQwQHx7uOgtsNftwmpofbhqrHXiGupObooacfmlVXy0yHd83tLMbjiITH24amo5aMPET4gLEHFfUlXCayteM4dvGHYDP6wtYeyjc/hls9ERy104moHtjEhol8fFYwsea5Z6ZTX5fPPnZpwq4O80akLiox3cNcl3r/Paj1vNUgM17yUWWerDjeiWQpm7kFW5qwCwKVvYtbDio+K5b9x95nC5qxyNDq1zS5jM3DqTebvnmcMlzpKIv0dzccfoO/x+GzB+qztG3xFkicgyKt0nxPnViUvKpNJSHy6mnvP0oUD7uPbcNeYuc3hd3jrzdb/UfmaySLgMbO/rpLMuIdV8bSvdG2BuQRAEQTi8ECFOaLtoDV/9kbXl+yj3xh5kxnWkSxi1NKw9cdfsKaSinhhIK9YacU3hiCssc1Lpqr09dTawxyRCJ2sP9fp77zeUYLUKBmcm0yHRaMA51z3bt8CYa8EW+imnOu4SmlaIm+E+hnuqfs9uTwc8Gkq1r/EpKfsn0qdfyL+/mM+rP25hxvI9VLkDi01NEQPo9DjN79mmbKREp/g54hZuy8MTSIWxsuIjixjaC/qdSqwj1nwIdnlc4e2/fnFdFrKXwPe168RVOwitm/n0rA1N4iC0OuKsYiP491yvN5pyx6+w/H3f8BnPkBzfwRxsMiEOIHtp7XHOcph9f63RX6zYw7dr9pnD7ROim9QFC/7CWGxpLuR7GzWj4lHdxzO0cwQagC2RaM3hiFuw9SDnvjSf9ft857Trj+3FW9ceQUp8HQ0xEx/wvd4wE3YtCj6vF6sjrrvTBcMuDm0jLULcsbbVrNkVwA1b5HMq1SXEBasLt690X8DxzH3YjB818bjqrQsZiAqn23ByALM9Y30T1keuvs6ufJ+jsRtR0Dl0sSg+2kGfjsa1x6Nh3b4iw2kYiNID8Oxg+OZe2L2Eapu0X524artqlzEQ07xRYuv3FfHvZZV85Pa5eaN/ehwa0Ujv9DjJ1YbwpbSmY/djG7WN/tF+oZ8vrDVrXB6XGeMYSYJFg1fEpdPj7nkw5ALfyO0/wxsTjJq4VuY9ZkwDQMGF/4GU+s/LWwp88Z8NEYuGWQSilbsLGiTMNIUz+e3ftpvf6aDMZL+OW83F9qLt5uvGCnG9OySYtab3FVWEHbtmfY6odqFYeWvNW2Y8eWZCJgmVJ/DX6SvJLfE5FG02OxM63OKrV7ZvId9si1zHhlCYuXUmjyx4xG/cPxb8o9lEogtHd2VghnF+LXe6ee474xpjvZcod5ezcJulPlyv9szPno/GODZGdBxR674xFE7qflItUQnq6dwSJm6Pm0cXPIpb+5+PIvkezcmZvc9kytFTyEzIRKHITMhkytFTOLP3mc3y/qM7+e4JVh5YibM6/aSGEBddVRbxZ+fWyHl9z6Nncs9a43/K/qnBx/CgtEEAOFIdbIj1HR+OspxgiwiCIAjCYYMIcULbJes9WP0piy03eEd0Hh9W7612CdH06Wj0Xne6dVgRPn6OuAA9WRvL6z9vodJlPCA6bCr0Bvb8nbXHOcsb1GhaF0v3+QSDmdtmmjfrNpvihP4dGaR2MMbmbRC1RcHIK8Naf3PViHvq2/V86jyaY6tepHflBwypfJNnnT730zDbdj6NfpBequ5efE0RA2itN5Eak4rdZqdPx0Q6JhmNC4XlzrpjFrWGhb7e1Bx5kymGJsf4hKmw4ymHT4Y/roYHC+CIG3zjf3nOvyYg8NSs9bUchBVN5CCsK5qyT8dEou3GZ88uKKewLIiLwu2Er/7kGx50NvSfRHK07/tqUiEuWK29kn3eiFHjnJBTVMH9M1abky8/sjtL7z+lUbWfQsHaIBu7Z7lvQs/jwBHjH+0XZt0nc73N4IibkZXNMU98T897Z3Lp6wvIKzUaNqPtNp66aDj3nzUYh72eW6SMYf713b57qF6RY2e+b7/vbosFS5xnnXToT3GcEfWVpMop3/Jz7XlCdMSFHQsVbJ+spy5kIN5bsIM9hcZvuiTG4hDbMR/KC8JeXyCsYme3zDFh1zAbWjNuLlgcLxjH5cJX4D8T4YUR8N1DJFjqSZZVx1oldAiygqZBa82UL9bg0fCS61yq8ArKe5bBxm8bvN7cA+vQ3nus9h4PUZ0G17NE3fhHgYZ+XlVK+bnimqKWZLDONUXlTlR0Alz0Jpz0d9+E/G3wn5Nho7cD0sZZ8PM/fdNPvBf6TCAU/BxxqeE74rq2i/NzJ+/MC/8e1eqIs0YSN5SyKhf/+3W7OXzzCb0b7LZoDH6OuOTGCXEOu42BmWG67S1Y3bM1hbgDZQd4d+275vDto27n+TlbKa9xP+X2aN77ycnlAy83xz2z5Bm/+Pim5oVlL9QSa5tTJLLbFPedMcgc/njxLjbsK65VI27hVp8j7qje7fnZUtYg3FhKK8GE6qCdW8LgQNkBbphzAyXOwL9nJN6jJTiz95nMvmg2K69ZyeyLZjebCAdGndyuicZ1vdJdydo8b7T4jvlUWbLeYzzuJunI2tpQSgXsCFDprmzwMTwwzegUPPD5gWx0+M5ZCZUHcAXp0CoIgiAIhwsixAltkwMb4Ju/ALA41tdYcETGEWGvqqF14pqyRlxuSSVvzd9uDj97ycjQG9jLA8QjQYMaTYMxc+tMvtv5nTlc6iz1i0g5YUBHLrf7IusYfA4khtfz2dpAUe5pmhp8gNko7EPxovsC7nHegNt7iuxuO8DXCQ/z34maW07oY/aArqapYgDzKny/ZbsYYz9VSnGUJZ7SWni+Flu+h1xvw390Eoz0FZa3ClXWSMewUApOewL6n+YbN/MuM7KuyuVhT0FgIaUpHIR1RVNGO2z0S/eJu2v2BvnMv70EB7zRLFEJxufDX7hskhpx1dTV6P/13fDBJejiHO75dCVFFUbjc7e0OL9GqKbEKozF7Fzsm+AVlIZ0sTriGvY9WRu1rp99fcR71RuRcyvJrrEPJsbY+fDGI5k8tluQJQNw0n2++mk7fvGrmVcTl8fFbosbrVvf08HSY79OlKKi18nmYMa+n2rP4+eIC36duGP0HUTbov3G1RkLFWyfrGtfDUBRhZN//+CrT3fpxCOhszciyuNqcNSllTJnGQfdhujg0JqMXiEKnRaGdK6xDweK47U5IKpGpGjBDvjlWeL3rDBHmY64zXObtTHv61X7WOBtdM61tad0+DW+iT/8I2iMcH3k7P7NfJ1uiw1b5KyJX42tMIX7po6nbJ8YHXC82elGKTjhzzD5Xai+H6wsgg8uhse7wQe+mr30mQDH/zmk93V5XOwo2mEONySaUilVwxUX/jU+0tGUHy/eRYG3A0y3tDjOHJbZ6HWGS83vtmdKz0avc0i4sdcW/GJsa3Toe3nFy+azxYB2Azil++lk13E/9YeRf6BjnHGffaD8AC8tfymsbWkMwcSg5hSJju/fkeO9DkuPhse/WefXqafUWcGGHMP17rApRnRL4tc9v5rTj+vacCEuWCcWu81eqyZrOCzcu5CLv7yYxfsWB52nueqqHWqMTve54szaez885h9N6dFN0pG1NZJbHrjmeEOP4X7t+mFTNnI+y2G7p5wy7/faiXzyyiJXc1QQBEEQ2iIixAltD2eFUfjeWYYTyIrzNZCNyxgX9urG9kgzXy/dEUTECoA1UibSNeJe/mELZVVGBMnAjCTOCqfBIkKNpnXxwrIX6oxIOa57rF9duuIhV4X9Hs0RTVlU4SRYh+xfks7AftmHZs29OFchExf+nnt6b+PJC4fTJTWuyWMA/YS4WJ9gfLQlnrLOOnELX/W9HnUFxPoajKwRPGE74qzYHXDhfyFzhDGs3fDJtVTuWs4t7wWIWfTS1A7CQBFD9cZTFuyEH5/0DZ/0V/O4aTZHXMAafJaddNMsKv91FGzyxb4+fdEIEmMa1yAeKtYG2didC30T+hiCx9AaDevhRqLN3DrT78E/tzw34nVQjMi52kJEQoyDMZbrQUi07wOjLSLHdw8FFTn2FWfj8sZgdXS5iB9+aVhvlTLc12N8bNUiiipqiA9+Qlzwa0Z1LFR1lBnABf0uCN4jPdA+GRXnH80ZAq//uNVsiO/aLo7Lj+wBAyzvuaHxv/EuSyN7F5cLR4gOJCtDutRwdfrF8Srj/3mvwL074Mrphtvbcr5JsOzzpdVxzO7KZmvMK69y84+Za83hq8f3oN2ke3xi0b5VsP7LBq173z6fyJgeE+axEgBr7c7N+0tw1he1bCHa7hPKqtyRbdjTWgc8pwbsdDP4HPjdLP+4Zr/OGgoGngU2e0jvnV2SbQqLHeM6+kV/h4O1TtyqBsQE+zniGhlN6XR7eOMnn8vvxuN61+84bgL2lOyJyHdrxS+OOUwxOVit6a0FW/ls02fm8E3Dbuf6t5cEXU/n1DgSoxO5e+zd5rgP13/IhrymqV1ck/Zx7QOOb26R6L4zBlLd92HehgOsyfZ1tiks9zl+hndNYUvROrPzVse4jgxo1/DOdIFqnoEh/F4681LeX/d+WPdCbo+bV1e8yo1zbvSrE+1Q/uek5qyrdqgxqpOvTtyy/cuMF4W7qbJGU1b/ZhHsyNpaCTspoR7iHHH0Su7Fgc8PoIGN0UbHmQyVT26xCHGCIAjC4Y0IcULbY879kGNEsq2OS6S8ugRLYhc6JwaP4wrG6BqOuFAflqwP0JF0xO0pKOe9hb7GxLsmDcBmC6IWBSJgQz7Q7cgIbJ1Bfb1f2239giRlfCdbPJn8UNk/7Pew9hRuqmjK13/cGjBJzmxsG3AaXPsVxHsbGVzl8NHlnOeZw/x7JzR5DGB+hc+hmRbra/Qcb3HELdqWFzjmI3ezRaxRMO5Gv8kp0b7Go8KqBjriqolJhMun+hoiq0oofesC1q5fF3D2pnIQrspdZb5+a/VbtcSbwZYIqYCRnt/cC9WNYZ2GwJE3m5MSohJM4aLcVd4kDgwgcKP/uS/BUX8wZ4mtyuN/0U/zkOMtbhyf6eeQbGr8oikrvTXVUrsbghTQs30CCdFGg3NuSRX7i8NrwH1h2QtmzZZqIh1xFcyNub+ogY3NJ/zFFOzZtxLWfhZwtp2bfPtjN48NeoZXXyu6z/FUYDSO97btY/O65f4zhOiIAzi7z9ncNPwm37YVB4g0ribQPnn2i8b4ENlfXMF/f/FFwt01qT/RDhsMtAhxm+ZAIyPwdu/0RY111XboGP55xuqI25hTTJXL44vjnVJg/B8+2eiE0HcinPcS3L0RLnkfhpxPvEWILbf29GimxrxXftxiOr3TEqK58+T+kNgJxllihKdeDc8NCdull5O30XydntT4zj1JsVH0aG8IhC6PJrs4dKdeUzriftiwn+0HfcJIvZ1uMofDDT+APZCLThuxzSGytcASS9kAN1w1w7qkmq9XNcARF8kacV8s32Puk+0Tork4HNdxBPGLpWxkfbhqwqo/W4Ngjrjnlz1vdnYb2eEInp4B8zcH7nRlvZ86vdfpZodEtzbqijVF/cSatI+tfQ/SEiLRwIxkLhrjOy+9Nm+X+bqkyvf9HlkjlvLYLsc2Kia1Zs2z5Ohk7Mq4D6p0V/LEoie4de6tQV1HVg6WH+SW727hpeUvmb9dWmwab0x6g0ePfbTF6qodaljrxGXtzzKe/VO6UmXp+BZT/YAYwY6srZVAYnJjj+GB7X0169dHG9fGTiqfg6VNX/tZEARBEFozIsQJbYv1M2HR6+bg4mG+B5CGxFIC9OmYYNbSyC9zsjW3dk56IKzRlJGsEfev7zcZDX/AiG6pnDyoU3grMBtNazw4rJ4GWe9HZButn92K2XPOUifsA/dE5m08EPZ7+NWIawJH3P4i/4bhdvFRgRvbuo6F382G1B7GsPbAl3cY0VNTUuG5oU0WOZZf6RPirI64Hu3jyUwxHphKKl2sDtT4s8hSG67/qaZQUo3VMVZY0UghDiApA674BO2NcEzzHOTN6KdIpIxTBnWiS2pskzoIZ26dyfIDy83hwqrCWk6qwZYG9loNZhu+8XfknPUs2H0NvTZl8+s9X1xVHLmNr0nNRv9RV8Bpj+G54jPybD5B9hrHHO7ddbPhcGkGZm6d6VdHYm68V3zqM4Fqa6nNpmpE+4W3bzV1xFWF0409SMeGBrs0kzLgKJ9oy/f/MGoN1mDnFl/0Yvfk7iE7ZEyiYtmSNNYcrFj7jf90PyGu/k4p5/Y913z9655f6/6OAwlRYfCvuZspd/pc3ueO8B7/nQZBu57G66oS2Bag9l0Y7LJEJ3ZLyCSo5bkOUuKi6J5mXOOcbs3GnBCO9ahYGHQWXPw/P7e86YiDZmnM25VXxqs/bjGH/3LqAFLivOex1J7+MxfuDrv+TU6pbx9Lbx+ZzhRWIWNHUcsLcR6P5ulZPsHx2qN7htbpJrFjwOMeCEuEbWx9uGqGdfU/D3vCcBtC5GrEeTya137y7ZPXHdOT2Kgwz30RoimEuAEZSeY1ZVtuKSWVodcr9DtXeK+tWfuz+GHXD+b49WuPZ2OOrz7YGUMzgt5PKaX425F/w+GNS15+YDmfb/68wZ8tFJbvX84GS+3TlhaJ/nTKAOK8+9fmHN9+axWTj+yVxs+7LfXhGhFLWY215tn8y+Yz7exp9G/n64T4S/YvXPD5BczbNS/oOpbmLGXyl5P5ba/vOjY2fSzTzp7GUZlHtWhdtUONXim9zAj7gsoCthVtg4kPUBnlE6Oi0A1y/7dFaorJkTiGB6X5IvPXxxhCXLrKJ7dEhDhBEATh8EaEOKHtUJgNn/tcIQw8i0V2X6NNQ2IpwXhwHdM9/DpxwSJlGsP23FKmLvE12Pzl1AEN66U5fDL8cQ38bR/0OMY3/ovbYf3XjdrGSnclOkCDjtlzLnsZ7F1uzKujmOY+np825obdCNTUQtyL328yG4YHZSaz9O+nBG9s69AXfv+dL34RvNFTGgp3NVkx74Plvh7QVkecUsrPFfdbzXjKikJY/oFv2OLsqsZPiGusI656PYl9uT/2XpzaaAQZZNvF15n/4Y0rRzL/3olN6iB8YdkLtXp+13RSDcr0CWmb95dQ4f39qSqFr//iW3DUldD9qFrv4RdP2ZR14oLwzv5eTCx7jFlunxhjy90Ab0yAX//d4LpPoTBz60ym/DrFb9yjHdKYmRBvxlJW4xftF2aduGAxODH2GNwed8Bp4fDEN+txBTgXNdqlecwdEOs9pvK2QNZ7/tOdFezMXW0O9uhSe/8KheJuvqjFtOx5vglahy3EdUnswpGZhlPaoz18uaVhcYX1sT23lA8X+Rx395w20OfyViqi8ZS7LFFs3ToObfB6hlr24XBrlyX09DXqmjXimqkx7x8z15kdeYZ1SfF3Hv3ybO0Fwql/U7yPHEs0bXrHIY3ZVBOrcL8jDEdcU0VTfrVqL+u8jum4KDt/OKlv6AtHIBrcT4hrhCOuc0os7ROM76i40sX2g6F1MqsmUjXivl+/3xSSEqLtXHVUzwavq7FsK4q8EBcbZadvR9/96rpAbvsgWB1xpc5StNb8c8k/zXG6eBQHDhp1zxw2xbOTR/DylWPqvJ/qndqbawb74pKfW/pcw+sAh8C/s/5tvj6z95ktLhJlpMRyw/HGcaM9PrHejXGOsNsUvdI9rMszEhscysFRmQ27HtdF33Z9+fDMD/1+i/zKfG7//nYe+e0RvyQVj/bw31X/5fpZ17O/3FdH9oZhN/DGpDfoGB9ejW2hfpRSjOw00hzOysmC4ZOpGn+rOS7GHhO2+78tE2mhd2DaQPpMMTqBrpNoSkEQBEEwESFOaP2snGpEKD03GMq9IllyV6rO/CcrDvjqlTTUEQcwpqdFiNsemhBn7ckaqWjK57/biNvbSDy+d3uO6duhcSuMioPLPoSMYcawdsO062D7/LqXq4PZ22dT5jaER5uy1e45t+RNc945tvEUkkhuSWXgKMA6aMpoyu25pXy0yBdZ85fTQoj/TOwE184ER2ztaU1UzDuYIw7gKEuduN+21hDist433CUAHQdB7xNrrbu6JygQkUaagyWVXPbGAt7L6cm9Tl8EWvf8BfDVHwmYARpBQnFS1YxB27zf+x399DQUeoWCuHZwcuDfstnqxAVg64ESnvh2Pfkkc5Pzj8zq/VdfzSd3Fcz+GzyW0WQuzReWvVCrMbbCZuOFtFTofYLf+MbUzAlWa6XCXcGDvz7YqJitHzce4H+/bjeHU+OCuGAbQlw7OOZOy5s9aZwXqtk8h13Kt+3dGijEJQ47w3zdp2wFVMeDVhRCtVsxKh5iU0Na3/l9zzdff7b5syaJMfvnnI2m+DmuVxonDqjRqDjQ95nY8E3DBWVnObss0V/duoUX/WnF39UZ5rWri08oL1W2BkV5NoRfNuXy7Rrf+W7KOYP93Z/BXFmhurX2LGe/w1ejKD0xjNq1dWCtE7czDEdctesHIueIc7o9PDvbJ+b+7tiedEyKqWOJGkSgnmKkoimVUn6uuHDrxEUqmtLq0Lz8yO6kxEfVMXfT4ueIS46MEAc1O5+E/j37JWs4y/h+5/fmc4322CnNOQWApBgHb/9uHBeMDk3QvXH4jWQmGMdnfmV+RKOdrSzcu5CF+4xasXZl59YRt9azRPNw0/G96ZAYA9p3jlA2J+BhaJcUsnIXmONHdhoZkVqBgYi2R3P3EXfz+imv0ynOl24ydeNUzvj0DE6aehLD3x7OuPfH+cWRpsak8srJr/B/o//P7zwnRBZrPGV1nbhKSye8mF4nHTYiXFMwMM0XTbkpOhon0IFCDpaE1ylEEARBEA41RIgTWjcrpxpuo5oNRSMvY1VZttkw3C2pW6OKglsdcR8v2cUxT3zPjKzsOpexOuJ2Fu9k0rRJtWpShcOGfcV8vsLnaLg7UjW0YlPgyunQztvo4KqADy9tcJzdxxs+Nl/fNvI2/55zFYWw+lNz+qZuvgeYH8OMp7Q+GEfaEffM7A1mw/CRvdI4sX+IvU1jkoLXMGqC+j9rc9ear19e/rLf/nW0RYhbvC3PdEHgcfvHUh55U8B4NqsjrqCyoFHbub+ogktfX2CKrZ96jmdFH4sLL+td+PmfQZaODFZh3ErN84K1Tlzx4g/gmQH+9XtOeRgSAtdcaykhzu3R3PXJCiqcxm88MCOZEy//M9z0M2SO9M3oqqSpXJpBhU67w+cE8zK0i294TZiNv9Z4HPD/XT/f8jkP//Zwg8SivNIq7v7E13Hj5EHpZD1Qhwu2IRx5MyR697fivX4xyqyaxs4oXwN09+TuDXqLvn0HsNZjxORG4aJs/VxjgtUNlxR6JOPE7hPNc+2u4l0szVnaoO0KxursQr60XNfuPX1gbZd3t6Mgzuv4Ld4Le7Ia9ma7FrLL4but7ZY+smHrwT8uMVwx2c8tf+QNDYryDBen28NDX64xhy8Y1YUxPdL8ZwrqytKwJnBdQz/2LifH4YsUTI9Pb8CW1sb6Xe8s9pidkerDL5oyWCRkmExbutusDZcc6+DG4/vUs0QNGllPUWvt59pqTDQlwHDLuTjcOnGRiKZcvD2PJd6UiSi74vpjG/d5GktTRFOCv3C/Jow6cdbrW1FVEc8ve94cduYfhXamkZkSyye3jA+rY158VDz3jLvHHJ62cRqrLY7sSKC19nPDndf3vAZf1yJNQoyDP53SH7D5ueJQLo5qgljK+hjfeTyfnvMpp/Q4xRyXW5FLbnkuGu0ndI/sOJJPzv6EY7s0vCOJEBqjOo0yXy/L8QpxHt9vER2w5qcQKikxKWyZYnTEcCrF1qgobEpTmZ/TwlsmCIIgCC2LCHFC62buw/6ugmpWfMTifYvNwYbGUlazM88/WjK7oJy/Tl9VpxhnLfQNsLd0b62aVOHw7JwNpmlowsBOjOnRru4FwiGxE1z1GSR6G84qi+DdCyBva93L1WDdwXVmb12HzcEF/S7wn2HlVKiO6ew0hJ4jTzQnzduwn3CIc8ShvEWzq3QVLk/odTfqYtXuQr5audccvidQw3BdBGvMtEf73CkRYObWmWZ0DhhimXX/6tounm5pRoNvudPNyt0Fxvf/TH/I324s5IiD4ZcEXL9ViGtMzGJ2QTmTX/uNTV53mU3BMxePYMSVT8CIy3wzfv8ITElpErdWSVVJQEdErIoy4lK1huJ9sGsR5zl+5Vb7DN6PeoQjl98HJRaBSdnAHtz9kBzTMtGUr/+0laydBYART/XPySOIcdiNyNTr5xgCcU0i7NIM1tEhw5FQa1yfjgnEeAWRPYUVHAyzHkR1PM6/evyL3y7/ze888+mmT3l84ePoMByWWmvum76KA8XGdnRIjOHJC4c1LPa3LqLj4QRLxOnPz0J5AVQW4974LbuifD3bG9pgGRtlZ0Wc73pXssp7vSkOL5bSXJ8jljN6+RxpMzbPaNB2BWJGVjYXvvKrOTy0czKjuwe4rtkd0P8033AD4ymdW75nr8Wx1TWp4TXZrA3r6/YWhSwOgb+bO1Kx1fXx7m87zHNwQrSde04fWHumQG6taqb9DlZ8VOd7uLOXccDuE+I6xYdZvzYInZJiTddZlduosxUK1kbSSDjiKpxuXvhukzl884l9fPX1wqER9RRzynLMWmFJ0Um0jw3cKSRUhnVNNV+vDLNTRCSiKV+Z53PDnT+qCxkpARIFmom8ijyz01GcI470hMgIyeAvJocjxFnPFd/v/J7tRdsB0O4Yqg5OYGBGEp/degwDM5KDrCE4E7pN4Lguhsik0Vz1zVUMf3t4ozsNVvNL9i9mXd4oWxQ3Db+p0euMJJPHdqVfp0SwCHHK5sTlcfLbHl8NturvqKlJjU3lnyf8k4ePfth8tqlJQlQCb572ZqM6lgqhM6T9EPM8t7tkN/vL9vvFHMfU8TwghE91nTi/+1VBEARBOAwRIU5o3dQRpWQV4sZmjA08X4g8b2l8qabc6ebpWRsCzG3w+srXa42rWZMqVFbsKmDWGl8Psbsm9a9j7gaS1stwxlULMKX74d3zDYEiRKxuuEk9JtE+ztJIpDUsecs3PPY6juvva6hbtrOAwvLQG8uUUn514qobpxrLU7PWm69PHZIeuGG4LoI1ZrorDXGzvKBxG+jl+WXPo/Fv/K25f1nrxOX+9p7hgirzRbPhccL6rwKuPyW68Y64nQfLmPzqb6aDwG5TvHDpKC4a09Vw5Jz9InSo4exsArfWjM0zqPJ4639ojdKaTKeLKfv3ceanf4R/ZMA/B8B/T+HU9X/nL1FTOca+Dhs1nFXaYwiGQWgJR9z6fUU8N2ejOXzHxH5+IgGOaKgsCbxwBF2ak3pMqjUu1uPhjgFX1BrvsNsYlNmwhsma2JSNB456gLN7n22O+2jDRzy1+KmQxbhPlu72i+x7+qLhtE9sogaW0Vf73McVBfDrv2D9THJw4vQKf+1j2/s1wIbLwc4nmq8Tdn4foD5ceO6+8/v54ilnb59NSVWQ/SkMPlq0g7s/WUGly3eMbdpfErxzizWesoF1TPdu+wG39zvuFJXsF60XLh2TYshINpavcHrYeiD076Rm3aemJrekkue+850jbp/Yj/TkAJ+9plsrqbPPwak98NnNsPR/Qd8nL2cFLu/3mxqV1KjvtyYdEnyi2sWv/lpvIgHUcMRFQIh797cd7CsyBKeOSTFce3TPRq8zXGrWh2tsZ4FhNdzJ4QjK1kbohtTgW7+viO/XGx2wlCJ8d2GEsbrheib3xKYi9whsjVfdlFNMpSu0eqYrdvo6GlrFzqqDJ3Fs7x58cvP4BouXSin+Ou6v2DHEc5fHhUY3utMgGJ1b/pX1L3P4ov4XkRmhqNpI4bDbOGlAR7S2OuKcfLDiZ4qdRqe5jIQM+qaGUQOykSil/K63NSlzlvmd14SmJcoexbAOw8zhrP1Zfu5EccRFlvXeOnH2IAkbgiAIgnC4IEKc0LoJ4j6qTOnK8v3LzeEj0hteHw5gT0HgGm/BxkNoNalC5RlLTZIzh2X6N7RHkoyhcPnHvjpn+dvhvQtDEo+Kqor8HtwvHXip/wy7FsF+bzRWVDwMn0yHxBiGe2uUuD2a+ZtzCYeE6Mg2aM7fnMvPm4xtsCn4c0PiP2s2Zlpj+XYvgnfOgdKDQRcPlVD2r/GWeMoxm/9V2z3qcQV1RVkdcYVV4fWUn5GVzbh/fMfxT/9AtvcYibbbeOWK0Zw9wuLGcUT7atVZiaBby+1x896698zhvx7MZ+X2XczevYczS0qhNMeIYw2VOsQra1xqcwhxVS4Pd01dQZXbEDNGdE3hlhMDNGYGc2naHBFzaa7P8wnYVAudRZWcOSZwTZjGRPvVxG6z88gxj3B6z9PNce+te4/nlj1Xrxi342ApD33hi+y78qjunDQwMk6egNijYMLffcMLXoZFb7DT0Xg3XDUp/caTp41OCglVubB3RQ0hLnRHHMDgtMH0b2d0/qhwV/DN9m8avG07D5bx0Jdr+Ov01Wb8bzWVLk/wzi19JviuSwfWwcEtgecLRnk+u/J9HWq6pTY+dq6h+3CCxSVa5mpaR9yMrGyOf+oHiisMx3iHxGiuO6Zn8AWsbq271sHNv0D6UO9EDV/eAQtfq71c0V5yKvLMwUjVh6v+DNVuPoD8Mme9iQTg30jaEKHISnGFk5fnbTaHb5/Ql/jo5q/NZBWL+qQ2XrhKT44x3YalVW625YYuKFuF1gp3RVguZIDXfvSJipMGp9O3U2Idczc9TRVLCZBco/7sxn31f88zsrJ58+fazhCPM5mzekzmzWuPICm2caJMt+RuxAXoONbQToPVzN0510xsiLHHcMOwG+pZomWYuWqvnyMOmxN3rC9p4rgux0XeGR8CQRMGxAnX7FjjKbP2Z4kjLsJcc+c15ut10cY1O6YsvIQcQRAEQTjUECFOaN0EKXy/ctw1pgOmR3KPRkfMdE4NHNfUPjF4b7hIPUgt3HrQTxz64ylN4Iaz0mM8XPw2KG/EVM5q+PCywBGgFr7Y/IXZY7d/u/6M7DjSf4Ylb/peD73QFKhOsNRf+3FDeHXirI64EmfjXBpaa5781icmXDymG307NbBAu7Ux896dcPrTvml7V8DbZ0FxwzPwK1wVQXtrW/ev8b19NUM6uII82AQRllJjUn2zVIbeyDwjK5t7Pl3J/mL/uMHrju3JpCEB9v2iIBEkhbugPD/k9w3GvF3zyC4xGmyT3W7ODlYEPK4dZI5ADzqb99TZFOggjqSgdZRqOOKaMJpyRlY2xzzxPf3//o3pJot22Pjn5BE47AH2i2AuTY8Tpl4DjayftO7gOhbuWwgYjsNZu/cYQmd8D7DZAy7jVyeuEY64auw2O/847h9+NVbeWv0WLy1/KegyLreHP368nNIqw53Qu2MCfztjcKO3pV6GXADp3l7WzjLIXuJXH65bUrfGrb5rGvM8I30jNs2GIotoEaYQp5Tyi/+csWlGWMtrrVm49SA3vrOEE575gbfmbydYk33Qzi3RCdD7JN/wv0aHF2O77Wd2WeqXdYtAQ/sQyz68OjuMuk9RvrpPTRlNWX0uLqvyuW+Kyl18syqMzkCJHeGaL/1rTX7zF/jlef/5ataHi2CD8dOzNtQSbetLJIDIOuL+8/M28suMdXRtF8elR7RMrautBf6OuMailPKrE7cyjDpxNmXz+46r77lDYXd+GV9YakPefELLuuGgaYU4qBlPWff3vHl/CQ98vhpXVO0OB7aC0/jnxWOJCnStbwDBOrE1pNMgGJ2frNfdywZeRsf4EOssNzN7Cir8HHFKVeFI9J1XWqoO2x2j7yDW7u90jLXHGlHqQrMyOn20+XpZzjI/R5wIcY3niUefMF9viInGAyRUHQi7Y4cgCIIgHEqIECe0boIUvl+c4GtEPyKjcW44MJxRcVG1G5SLy51s2BfYURLoQQrg0gGXBpg7MFprPzfcBaO7Nk+v4QGnwbmWBuydv8KTPWFKasDGT621XyzlpQMv9e9FWpYHaz7zDY/9nfnyxAEWIW5jeDffkYz4+nrVPrMRKsZh485T+jVqfX4ceSOc8y+orvuwfy387wworD9eKxBTN0zFoz21xtd8UM9IiaV3hwTOs/0SfGVBhCU/R1xlYUi/i9ujeeDz1X5xc9V8tWJvgCWCvz8Arx0Pe7Lqfd+gVBbzzs/3m4MXF5cQX/NzJKYbYuk92+Gmn1CXvMesrrfzgPMaynQNoT0qzhC1guBXI66JHHEzsrL56/RVptOwmjOGZgQXjmueJ+Mscatb5sIX/weNeOh9e+3b5utJpWV0ro7d2rciqFAy1OLqXRNmbaJgRNmiePK4Jzmx24nmuNdWvsarK14NOP/L87awzFJb7/lLRhIXHVg4jCg2W639aKe1PlxS4xr5B2Uk+wlx7vXfNMoRB3BmrzPNRveVuSvZnL+5niUMx+ZnWbs5+9+/cMnrC5i9Nqfe3SxYpxfAEIWshBNju+1Hvxp8jRU7wahpV83qMPZhqxDXlNGUT367vta5uMpdh+swGPFpcM0X0O1I37jvHoR5T/rOG3uy2GcV4uIjV1+rIYkEEDkhLq+0iv/87BPA/nhyf6IdLfN4tKXQJ8xESiwa1tV3Ll4V5rnYeo9bEYaz/D8/bzNjMMf3bs+ocCPA62Hm1plMmjYp5JpnM7fO9LuHzbO4OyOFNcmiZucTj0eTtTOfJ79dz4R/zuPkZ3+kLHoxMR3n+s2nNVRU6Yi6tIJ1DmxoB8Zvt3/L5gLj+hDviOd3Q39XzxItR+fUOD9HnC06F3usIUA6bA6OyjyqRbbrzN5nMuXoKWQmZKJQZCZkMuXoKZzZ+8wW2Z7DmREdR5g1+zbkb6CgosCcJtGUjWd0v9G0izHO/yU2G9kOBx11HmWRKfsuCIIgCG2S5s9dEYRwGT65VrH7xd9eZ74elzGu0W9x3iijps7Tszawp6AcpcCjodKtufatRXx26zG16jRUPzA9t/Q5csp87qcZW2ZwycBLQqoB9OPGAyzebriCouyKOyZGUByqj5GXQdlBmP03Y7i6kaW68RPM733B3gVmEfnEqETO7FXjYXHFh0aNNDB61nfx9TAc0TWV5FgHRRUu9hVVsCGnOOTC836OuEbULXK6PX6C57VH9yQzpY4G4YYw+mpwxMFnN4F2w8HN8NZpcPUXRn2+EClzlvHf1f81h5OjkymuKiYjIYM7Rt9R60H9+varuKT4VQK229QhLEXbo4lzxFHuKset3ZQ6S0mMDi4C7zxYxl2fLKeoIvDTU9BG04kPGPtTIMdlwU747yQ47XEYez2BP0QQ9ixnzfRrWZZkiEIOrbmsqEajd1QcTHrUPz4UGJyZzGubjgUnPJI4nZSqHEMwnPhArXONleaoEff0rA2UO2vXl1m0vZ6Gw5rnyR8ehx+9PVFXfGCIMxPvD7xsHewr3ce32741h68ptHRMcDuNiNEA31n/jEQcNoXLo9l+sIyiCifJjYzZAqOmxz9P+Cd3/HAHv2QbAvRLy18iyhbF9cOuN+dbvquAF+b6ogr/eEp/hndNbfT7h0xFASibUXsL/KIpeyT3aNSq46LtZLc/BlfhyziUB9veLEiyNLY2QIhLjU3lpG4nMXvHbAA+2/wZfz7iz+b0GVnZ5vUxIyWWUd1SWbIjv5YzFuD4/h0ZlJnEO79up9zpE4rioux1xwFv/q72OGc5fPtXGHqRIXAGY+s8djkiLMRZnERr9xTh8WhstvrPUdZrf1NFU7rcHvYWBhZG6hOwAhKbYtSQ/fBS2P6zMW7eY+Aqh4kPwp7l5Nh9328khbjOqXG1Oh4ApMbXfb6IslvcWo2Ipnz5h82ma7Zfp0TzfrAlsLq2IuGIA/86cavCcMQBfh2CLvjiAv405k91igUzsrJ58tv1fvvmzYHilBvBjM0zeHTBo6ZzZW/pXu6ffz+rclcxqtMotNZ4tAcPHrTWLMtZxudbPvcTa6dvms6IjiMiKnxY68S9u2AHc9flcPbIzpRUuJizNqfWuTKm4yyUzf9+SimIS/8OCN4hKFzuGH0HU36d4leDDqBTXCc82hNWrTyXx8XLy182h68afBXtYiMrskaSP586gL8t8IkpjmRfTPXY9LF+nSaamzN7nynCWysgKTqJ/u36syF/Ax7t8as/L464xrN3717OSjuL3/b+BsC66CjSK/PJrhRHnCAIgnD4IkKc0OaocFWw4sAKc3hs+tiIrPe8UV3MBpi1e4qY/NpvlFS62FtYwXX/W8wnN48nMcb/kKl+kNqQt4Erv76SCncF2wq3MeXXKTx1/FN19mqt6Ya79IjudEtr5ofCo28zGutr1pGqruHlbWC39iQ+p885/g+vWsOSt3zDY30iKRgF04/r35GZKw3H1LwNB0IW4qwNmo2Jppy6ZBfbcg2RJjnWEbjOViQYfjE4YmDa74xYwIKd8NYZhtugQ2gi64frPzR7a2ckZDDz/JnBe2VunM1lOx/CpozGslzVgQ5JMYY7JgRhKSUmhXKX0QBaUFkQUIjTWjN1yS4e/nKt2VgZiKBOl+r3n/uwEZOZ0hUGngnLP4DKInBXwcy7YOcCOOt5iKnHEao1LHwVZt/Pu+2TAWMfmRTdifQz74Efn/S9T5DPX91g9oXnWIozz+et60IT85tDiAvWiL63IIw6dwAn3mvEFWa9awz//Iwh0Bxxfd3L1eC9te/h1sbvPra8giFVNRq8g0Sfxjjs9E9PYu1e43tau6eIo3q3DzhvuETbo3n+pOe5fe7t5sP988ue5/llz5OZkMnNw2/jX18km46MsT3aNX802tyHTREO8HdrJTdeJOrZtQtLC/pzpFqPQkOxxZGa3DAh4fx+55tC3Fdbv+LO0XcSZY8yXZrVAvHewgr2FvrHmsU4bFwwugu/O6YX/dIN5+agjGRTvOucGsefTx1Qt8hRFMRVW5YLL42Do26GEZcZMZZWCnfDwc3s6uITIyMhxGWmxJKWEE1eaRXFlS525ZfRo339HWziHU3riNNa86Cl7mFN6nQd1kVMIlw+FT6+ArZ8b4z75TnjfmBPFjnx1mjKyAlxfz51gN/+VU1ppYstB0ro0zHwNSESjri9heW8s2CHOXzXpAHYQxBbm4KCigLz2h9rj6VzYviCeiCG1YgJdrk9gSOOazBz60w/IXl/2X6m/DoFIKCAUPM8AUZGQF5JbbG+5vu8sOwF9pXuIyMhgz+M/AOj00eTXZLNnpI97C7ebb7OLsnmQHntiHOnx8n7697n/XXv1/u5ACrdlbyw7IWICiG78vxF9z2FFX518qzERdmxRRUEnKYdgcc3lOrP+MKyF9hb6jvHrsxdyfPLnudPY/4U8rq+3PIlO4t3AoaAcfWQqyO6rZHmvFFdeG9bezYUGw6+qERfPP1xXY5rqc0SWhmjOo1iQ77xPL7moO/aKo64yDCw/UDzXn19TDSTSgpYVyVCnCAIgnD4ItGUQptjxYEVZqNLr5ReTVKbYHDnZF6+YjQOb4PMur1F3Pr+Mpzu2pF8AAPSBnD/eJ/b5Nvt3/LB+g/qfI9vV+8z687EOGzcNqFvhLY+TCqDCFyFu2DLD+wr2csPu34wR18y4BL/+bb/Age9zpPoJMO5UIOG1olLivZF8TVUiCurcvHCdz5nzM0n9iE1vgkfrgafA5d+AA6vg7J4D7x1OuQEbzitpqSqhLfW+ETNG4ffGPxBcOs8+PhKbNo4FrZ4Mjmr6hHKb1tl1K774+o6RTioUSeuqnZP+dySSm54Zyn3fLrKFOEUmMdFNfU6Xaw19f64Gk5/Em6c56ujBbDqE3hjAuxfH2wtUHrQqGf47b3kKA+zEnwN3ldP+heMvsr/fYJ8fmstl2qhKBT8oimboEbc+n1FQU2BYTeuK2UIm/0m+cZ9fTesrzvCy0pxRQHT1vnOY9cWBvjMdUSPDu3SsGi/UIixx/DChBfolezvNt1bupeHf3uIXVWGWy4xxsFzl4xs/sZ1i0DpgYi7tYZ1SeYH98jaE2xREN+h9vgQGJ853nQ65VXk8dPunwB47Ot1AV2aAJ2SYrh7Un9+++tEHr9guCnCgdEIOv/eCWx74kzm3zuhfqdRXTG2BzcZgv2zg2DOA1Cwyzdt649oYHeEv2OllN+5ItQ6cX6OOGdZxGuhvPbTVt5fuDPgtHrPxfURHQ+XfQQDzvCNW/gqlO5nv71poinPG9WFxy8YRhfvOa76WK1ya259bxnlQTqA7C3xiQrPLH6m3njCQLw4dxNV3njPEV1TOHVI5D5XuGwt9Ik2PVN6huVUqotOybFkJBv3I+VON1sOhCYOv7DsBXSNao8V7gqeX/p8wPkDubk18MzsjUHf46P1H3H//PvZW7oXjWZv6V7+Pv/vnDH9DG6YfQMP/vogb6x6g6+3fc3yA8sDinANpaE10oIRTHSrpl18FBeP6cp/rh5L1gOnkJmYGXC+zAjWX6zmzN5nMvui2ay8eqXfPfxbq9/io/UfhbSOKncVr6x4xRy+bsh1fp2TWiu92lscezZfR6Jju7ZMfTih9WGtE2c954kQ13hGjx7NoLRB5vC66GgyVB6FIsQJgiAIhzEixAltDmtsxBHpja8PF4zj+3fksQt8QsFPGw/w989WB21UO6fPOVzc/2Jz+JnFz7B8//KA87o9mn/O8TVOXHN0T9KTa9ebaxbqavx89zw++eQCM57oyIwj6Z1aIy5pyZu+18MnB3Q0nWgR4pbsyKOkMrRweL8acVUNcxa8NX+7GQmUnhzDdUdHpu5KnfSfZDgLqre/9AD852R4pn/QOnwA7617j8JKQ7DoktiF8/qeF3j9OxcYglR1NJNK54qq+9jnTmHpjvyQNzMl2lInrsJfKJmzNodTn/uJ79b5Yld7d0xgxh+O4ZmLR9AlNQ4FdEmN4/ELhoUf59W+D/x+jhHpWU3uBnjjpMA1obb/Aq8eCxu/AeCj5ERcXtVqdKfRDOkwJOS37tUhkdgo4/KXU1RJbj099qtpSkfcsp35XPLaAjwBTi8Nbly3O+Di/0FnbyOD9hhuzV2L6l82fwfTPzyLUq/Q27PKyXHlNVx59dTUG1rDiRFpqqNVa+Kmiph0o1F+yjlDmt9pDH7n1f12O5XeWMV2Hh2RxsthXVP43jOq9oTkzLojHOvAbrNzbt9zzeH31nzCHR9lBYyfrOaXeyZw24R+pCVEoMFq4gPGPmXF5gBrLdaKQpj/ArwwAj651ohg/fpuDtjtVHg/d1J0kl8NzMZgrfu0ek9oYnK0PRqHzRAFXdpFlafhsYk1+XLFHp74xtdZYXT3VLqkxjbuXFwTRwxMfgcGn+c3OsdaI253I2p7BqBatP3faQl8cdsxZo22DTnF/H1G7fuumVtnsmz/MnO4sKqQKb9OCUuM25ZbytQlPsH8z6cOjGhtrnCxCnGRqg9XTUPqxAUTqvaV7eP6Wdfz5uo32ZC3Aa01LrcnYLwo+Lu88yvymb19No8ueJRzZ5zLPxb+o1H1/azE2mM5pccpnNrzVE7veTpn9DqDs3qfRZwjcCeWYLXTGkpdkbAf33gUi/92Mk9fPIKTB6cTG2UPWGe6Zh3gSKOU4q/j/sqJXU80xz2+6HF+2PlD8IW8fLrpU9NR1y6mHVcMuqKpNjOiBIoX7JLYpVYnHuHwZVSnAPdSSDRlJFi6dCkD0waaw+ujo0lVpZTVfJ4QBEEQhMMIiaYU2hx+Qlxm0wlxAJPHdmN3fjkvemsNfbxkF93S4rhtQuCYwXvG3cOag2tYe3AtLu3irh/v4pOzPyEtNs1vvs+XZ7N5v+HwSoxxNH9smpU6ang5gU89hWAzGuAuSRlsRANWN1aVHIB1X/oWqBFLWU2n5FgGZSazbm8RTrdm6IOz6BJCVJlfjbgGOOLyS6t4dd4Wc/iOif2Ji7bXsUQE6X0CXDUd3r/YiGB0lhl/ELAOX2FlIe+secdc/JYRt/hFb5lkLzPWWb2upM581O0F9i0zGrN+3ZLLsf1Cc8RYHV7VjriSShePfLmWj5fs8pv3mvE9uPf0QcRF2xnRLTUydXSi4uCcf0H38fDVn4x6RM4ymH4DZL0HB7cY8YoxScZ36KVcKT5p1wG8ItGVg68M623tNsXAjGSW7yoAjNjE4/vX76y1CijFVcV1zBkeP286wI3vLDXdBDF2RVJcFAdLqkKL9KuL6ARDFP7vKZC/zagF+cFkuH5O4LhUrWH5Bzi/uYf30pMMIQS4RrXDdsqtsOj1eqM/q/ETMSLsiKvGWp/Tis1RQp/BX3LioCOb5H3rxXJe3WmJpeweAacWwODMFDbTld26A11Vrm9CUuPi7M7rex6vr3wdgMX7f6V08wlAYOGwS2qcKZhEhEAxthMfgAGnG1G2C14x9mEw6nCu+cxcdFeMr8Gsm72eeNswaKirM94Rb4r1Zc6yiDToLd6ex11TfbHcR/ZK453rxxHjaIJrmj0KLvwvbJoNzjI0+NeIm/8yjLs18u+Lcd54+Jwh3Dt9FQCfLtvNuF7tuOSI7uY8Lyx7wYzMrabCXRFW3OCzczaa8bVH92kf8nWzqbAKcX1SIntPOKxLCnPWGufKVbsLuGhMHR2wvGQkZPhFGVpZtG8Ri/Yt4rmlz9E+tgOukv44knqAvZyY9vNQUQVoZyqVuSeRFtuOxxeuZHHOYjblbwq4vkCM6jSKLold/P46J3Zmac5SHl3wqF/Ns1h7LFOOnhLwt5+5dWatGmlNIXgFq3XYJTWOIwPEMlsjI6tjOQPVAY40dpudJ49/kutnXc/qg6vxaA9/+ekvvHXaWwztMDTgMuWucvO6AHD9sOtbtL5aOMQ6andyPK7LcS0quguti4yEDLokdiG7JNtvvDjiGs+NN97Iq6+9anacy3XYybXbUBWhdxoVBEEQhEMNEeKENkW5q5yVuSvN4aZ0xFXzx5P7sTu/jOnLjBv0Z2ZvpEu7OM4fVbshI8Yew7MnPsvkLydTVFXE/rL9/OWnv/Daya9h94pZTreH5y1Ridcf2ysyboKGEqjxc/wfIHcjc9d/wkFvI18nl4sTv30IVn9t1J/qMxGWv2fUQgPoOg4yhgV5E+icGss6SwxgdkE5f/U2tAUTGfwccQ2otfPyvM0Ue913vTskMHls/Y1PEaX7UXD15/CfiX71ogBvHb6HzO//7TVvU+w0xJ2eyT0DN8bkrIH3LvCJUgkd4ZovGLQvEZYZ7oDfth4MefOs0ZQFlQUs3p7Hn6YuZ1eerzEpPTmGpy8aEZJQ1WBGXg6ZI2Dq1XDQqOXBth99060xkHFpfHn0NRRu/RQwejZP6DYh7Lcc3NkixO0NTYhLik5CodBoSpwluD1u87huKN+s2sv/fZSF0200CLdPiObt343zc5M1msSOcOWn8N9JRr2t8nxjP7r+O0iyRLGV5sKXd8D6r5idEM8+b9Rfmi2Gs6+eA9GJcMz/hfy2gzKTsCnwaNhyoISyKhfx0ZG97airsXi/ns85n5/DnaPv5MJ+Fzb6twoLy3l1p8fX4NA9PXDP63CJi7bTt1MSPxwcyVWO73wT9q0wHKX1xNIGYltuKf+aexB3aW/sCVtRShOVsoyqgyeav6P5/o2NQAzG8MmBt/3Im+CI3xvC0IKXYdtPfpOtNfi6F+yJ2OYMtYjJa/cUobUOqQE3ISrBFOJKnaW0i21XzxJ1s+VACTe8s4Qqbzx2n44JvH7V2KYR4aqxO8wOOgU2G1XeyMhEj4eEwuy6lmw0lxzRjUXb88z7rgc+X8OwLqlmfc9gbq1g54KarN1TxJcrfPvJ3U2xL4fJ1gKfEFcreaCRWB1xK0MUlO8YfUctAav6+mflYEUuOHKJ6/qrXz8tFV1AbOZnlCv4oI7E6UBkJmTyzunvBJzWNakrDpsjZAGruQSvQLUO6ztPVteZbm7io+L598R/c8XXV5Bdkk2Fu4I/zP0D753xXsBY36kbppJbbnT46BTXqXZEfSsmkCPyuK5SH07wZ1SnUbWEOHHENZ433niD119/nQHtBrD8wHLAiKd0VOa17IYJgiAIQgsi0ZRCm2L5/uW4PIaw0ielD+3javcyjTRKKZ64YDhH9/G911+mreTXzbkB5++S2IUnjnsChdEasXDvQl5e8TJgFLM/4tHv2Okt6h4XZeP3x7WCeJSaNbyOugXOeo6PBvoeVi8qLiEKYPdieO9CeGEUzH3Et470uqMBV3hFDyvlTjdPz9oQdJkthT4326ebPg0rdiq7oJy3f9thDv/51AE47C1wyusy2nAZBaJwN8y+n/zdC3l/3fvm6FtG3GJGm5nkboJ3zjVEFIC4dobI16EfR/ZqbzZ+rdxdGHL0pzW+7cGvFnPxq7/5iXBnDc9k1p3HN60IV036ELjhBxhyfvB57DF4bv6Z9w76IskuH3h5gwSWwZmWOnEhxibalI3EaJ/bprGuuKmLd/GHD5aZIlznlFim3jw+siJcNe37eONSvb3YC3bC+xdBpfczbJwFL4+H9V+hgbdTfN/PpcOvJyY6fJdRfLSDjolGQ4ZHw/FPzWNGVmQb8I9Juwrt8XeOau0TSoqrinlkwSNc+fWVrDlYf53GiOI9r+488S5zVLfkyDjiwIj+LKNGQ5Gz3HDiBYp3DcL23FLumrqCk5/9kelZ2VQV+Dq4JHfMYvot43l28sjGx9E2FpvdcMdd8yXcPN9vkl8NvvLIuVW7p8WTFGOs+2BpFfuKQotTamwnEiu5JZVc99ZiCsqMTi8dEqP533XjSIkP4JiONN6IVb9YSper7kjrCKCU4tHzhtI/3TjvVLo83Pr+UooqjO+grljB27+/nT0ldYuxz8z23XecMjid0d0bJ5RGAqsjrndKhIU4yzUla2cBRz8xt95z8Zm9z2TK0VPITMhEochMyOTx4x5n7sVzefjoR+gbfyza7e+KqqlR1xx2KAcjO47khmE38Popr/Pw0Q83KJ7RrHl2zUpmXzS7XjEr3PkbgrXWYYueJ0OkfVx7Xjn5FfM+MK8ij1u/u5WCigK/+Uqdpfx31X/N4RuH3xjQZdZaqbmt0bZojsho+k6cQtsiUDylCHGRo2Y8ZWxl6J1GBUEQBOFQQxxxQpvCL5ayGR+koh02Xr1qDBe/8hsbcopxujU3vbeUaTcfzYCMpFrzH9f1OG4cfiOvrXwNgNdXvs7KLSl8v6yDGYUE4HRr5q7b3yof1Dfmb2TpwdUAOJSdC3ufAyumgttb76Zgm/8CKz6CHkcHdWIcLAlcJydYXY2ZW2fy5RZf7GW5q5wpv04BCKkR5fk5G6lyGe6BEd1SOW1oZOuBhEVKVyOOMhC/vshb696hLNUQPvom9+S0Xqf5z5O/Hd4+x6g1BxCTDFd9Zoqf7RKiGZhhRH+6PZrF2/M4aUCnejdr+37fa2UrM1/HOhRPXjSCc0c2834ZmwwXveUXOeeHu4r5xdvYVmjsewlRCVzQ74IGvdWQzj6haU2ItZ/AiKesFuCKqopIjU1t0Pu/8dNW/vH1OnO4d4cE3v39kXRJDVzPJiJ0HWPUjPvwMiPab99KeLoPuPxrgC2OjWFdjOHSjbHHcOmASxv0djOyssm1HPe5JZXc8+lKtNacP7rxDflbDpTwyY8dqYi5gJiOs3xxaAdOpX1cO9r3mMmuYuO4W31wNZfPvJxLBlzCbaNui0idtlDZWbTTfN09qXsdc4bHsC4pTFq9oPYEZ7nhcK7DFTcjK5vHv1lHTlHt+m+u4iHYdBweVU6lykHHbuO8UWNa13UqYyikdDPPq1ZHXDdH7WtyQ7HZFIM6J7Nom9F7e3V2EZkp9R+j1ti2QHUMQ6W8ys3v315i6bxj57/XHNF8dQ+9Eas5dt99S7qHOmtDRor4aAcvXzGGc//9C6VVbrYfLOOeaSt5+YrRAd1a1czbNY+Fexdy84ibuWrwVbUinpdsz+P79cbFTym4e1LLu+HKnGWmm8+u7BE9TwD8sikXBaaXbU9BRb2JBBDYsVVQVsUXv3Qma8NZwBnYYneTnLYFd8qsoOv53dDfMS5jHKM6jaoVaRhtj272eMam4rxRXVrXebIeeqX04l8T/sXvZ/2eKk8V24u2838//B+vn/K6KWC9v+598iuNDmCdEzo3+J6rpagpphyReUTQuoHC4cvoTqNrjZNoysgxqP0g8/W6mGj6lYojThAEQTh8EUec0KZoKSEOIDk2ireuO4L0ZOOhrrjCxSWv/cpRj82l170zOeaJ75mRlU2F082ibXnYCyeRgs8l9lvRv/HY/XuAuTy6TkdYSzJ1g89RMaH7RDqd8xL833IYd2PgBVzext8gdA4iMCgFX6zYg67hGnth2Qs4q2MvvVTXgKmPTTnFfLpstzl8z2kDWrYexMQHjHpoAci12/gw2ec2unXLMmwfXQFrvzDqIv1zILwwAoq9PfyjEuCKadDZv/em1bG5YEvdPQ3X7ini/hmr+SqrwByn7D4hLjU+uvlFOHNDlNHAHoiUrry79l1z8Py+5/s51MJhYEYy3qQ1tuaWUlYVmovQKuBUR8+Fg9aap2et9xPhhnROZurN45tWhKum/6lw9vO+4RoiHNFJvD3oRHPw3D7nNjhW7+lZG3DXOK4rXR7+PG0lz3+3kS0Hwq/7WOF0MyMrm0te+42J//yRkko3rqJRlG65l5L1T1C65V5cRaPYn9OTz879jFtG3EK0zWhM8WgPH67/kHM+O4dHFjzCpGmTGP72cCZNmxSW2zZcdhb7hLgeyT0itt5hXVLIVEGO9cLdgccDb83fxl2frAgowh3XrwOf3nwCFw44yxz32aYgwnhLYzmv7rY44rqOvCaibzO0AbUO4x0+saGhjji3R3Pnx1lmhK5NwYuXjWJEt9QGra9BDJ8MZ79ITpLPFZ3eeVyDok8bQt9OiTx+4XBz+JvV+3hr/vZabq30+HS/qPJyVznPLX2OyV9OZmnOUnP8Z8t2c/kbC83hMd1TA3amam62Ffk6NnVL6kaUPbJux6dnbaCmL7/c6ebRmWvNDkuhsGJXAWe++As/bPB2CsLG2IyRzLr2UTITMgMuk5mQyR/H/JFjuhwTsK5Yc7jVhOCM6jSKx4973EzxyNqfxX2/3IdHeyisLOR/q/9nznvziJsjvm82NdbIV4C0mLQgcwqHM71Te9fqoCWOuMaTnW04r/0dcVEkuqRGnCAIgnD4IkKc0GYoc5axOne1OTw2Y2yzb0Pn1DjevPYIEqKNmKaCchf7iirQGFGIf5y6nEH3f8vk137jyW83kb3xAjxOoxFP2cuJ6/I+KH9xKZgjrCUpqSrxc6NdOtDriEnpAmc8DQQRtepo/P3zqQOIi6odIejR8H8fZnHFfxayeb+vYb6uGjA1RTsrM7KyOftfv5j1jAZkJHF0nw5B528WvI2ZhsDkFZrOew0un8p/e4+mwmacigdWVjGxpAQ2fA1Tr4IZt0BxjZo3R94E3Y+s9Rbje/uEuF8DCHEllS4+XLSTc//9C2e8+DPvLtiBxxIrpey+/TBQA32zEki4jIpj09E389ve3wAjJvKKQVc0+C3iou306mDEx2kNG/aFFmeXHGMR4irDE+LcHs3fZ6zmpR98kavjeqXx4Y1H0SGxGR/4R19tuCoDsDUhiZ8KDJFQobhq8FUNfptg5zaXR/P8d5uY+M8fOeOFn3ll3hZ25ZUFnLeaTTnFPPzlWo56fC53frychdvq7k3bOTWOGHsMt468lennTufozkeb0w5WHGTqhqnGuQTN3tK9TPl1SpOIcVprdhX53LCB6u80lMGdk9lDkHNbgOjAA8WVPPTlGh76cq2fM7uaDonRvHv9kYzpkebnepi9Y3aj4xWbBMt51c8RN7Lh+2wghnbxHSsvzN1kdrqpi0hEU/5j5jpmrckxhx88ewinDE6vY4kmYvhk9h3l64CT3u2oZn37c0Z05qqjfAL2Y1+vY9nOfD8B57uLv+PN097k3dPfpX+7/ua8mws2c+2313L//Pt5b9Ea/vLpSrPOHsCq7KKIx+U2BL/6cBGOpYTg5+LckipGPTyb37+9mHd+28623NKA91daa975bTsXvfor2ZZ13XRCbz644UjSk404yYbETAotz6Sek7h77N3m8Jwdc/jnkn/61S7ukdyDs/uc3VKb2CBmbp3Jt9u/9Rs3e8fsJu14I7RNbMpWK55SHHGNZ+lSoyNM39S+2L3NjruioogjcHkPQRAEQTgckGhKoc2wfP9yXNpwrfRN7UtabMv0ahzSOYWXrxzDNW8uqjWtZvuFdidQvvsK4nu+hlJu7HHZxKR/SeU+XyNnMKdYS/LV1q8ocxkN431S+jA2vYboGSxqsY66MdVxPU/P2sCegnJS46NwuT0UVxqF7X/dcpDTX/iJG47rzW0T+pKRkGFGNdXk7h/v5qGjH/JzQxWUVfHPORv5YMFOPxfO9txSZmRlt3xc0PDJtVwE+0r3MXVhgTn8B0c6NgILkCarPoGTH6w1elzvNGzKEDbX7CmksNxJcqyDlbsL+WjxTr5YvofSKrf/Qn5CnE8IafF9svp7mvuwIe6mdIWJD/Beia/G14RuE+ia1Lh4w5RYX8/ua99azEPnDKl3P2mII25GVjZPfbuePYX+MWoTBnbi5StGExtAoG5yKgMLj+/YKwDjuDqx24n0TOnZ4LfonBrn12gbiLV7i1i7t4gnv13P6O6pnD2iM3YFr/20jeyCctr9NJvU+Ci25dYW6uw2xaCMJDbmlPg1rsdF2fnzqb64uR7JPXj15FeZs2MOTy5+kv1l+2utq8JdwWMLH6N7UncGpA2IWAPMgfIDZnxeSkyKX13GxhIf7eD5uKu5s/zfxCtL9G9UnF90YGGZk9d/3sKbv2yn3OkOsCYDa3zwkPZD6Jval80Fmyl3lTNr+6zWGUk2fDJFA0+j4MNjAKP+T6f4+mN5wyGnRl247IJy/jxtBRtzirnhuN60S6i9rzRWiHtr/jbenO9zSf3+2F5cc3TPsNcTKXLKfIJgenzzi4F/P2sQK3YXsHJ3IS6P5rb3lzHz/46r9d2P7DSSj8/6mPfXvc9Ly18yY0FnbJ6Bds/G1nEICQmb/GJsn54V0+L3B3O2zzFfL9q3iJlbZ0bUGVbXubi0ys136/bz3TrjvNgtLY7j+nXk+H4dyS+r5MW5m9lb49qVFOvg2ckj/YTh6u09VGImDzeuGnwVe0r3mPWK31n7jt/0W0fcWrt2cSsnULJGpbuSF5a9IPulUItRnUbx4+4fzeHb597OXWPvkn2lEZxzzjlorYm2R9M3IZMNpUbHl7LoPMqr3MRFt8DzjyAIgiC0MG3rjlo4rFm0zyd8jcsY14JbAif071jn9L6dEhnVLZXRPdoxuvvxLMlL4YnFjwMQ3W4RUamL0M5UdN7p/HlSZGO0GovWmo/Wf2QOXzLwktqxjt66MTgtDTs1Gn8DUbN+RlGFk+fmbOTtX7fj0UbNvJfnbeHz5Xs48+hr+Gzn8wFrwMzeMZt1eeu5aeBDbNuTzI8bD7BiVwEBTB5Uujw8PWtDize0BeKNlW9Q5TEav4d1GMYJZ7wPeVthxYfw09OBFwriOkyOjaJLahy78svxaBj/+FxS46JqiT8A0XYbpw3NIDE5mi+9nRKrhbiaIkaLUUO4zKvI46tPnjSHG+PUAkMcW2mJmSssd4ZUM6egosB8/eiCR3Frd50P6TOysrl3+koqnP7xX6O7p/LaVWOIsreQMT2AmJ5rs/FFok9AuHbItY16iz+fOoC/Tl/lJ/7ERtm4ZGw3cooq+X7Dfr9YtGU7C1i2s8BvHfllTvLL/BvSuqTGcdm4blw8thvpybHMyMo2Bf7OqXH8+dQBtX5DpRSTek7imC7HcNQHgR09RVVFXP715UTZohiUNoihHYYyrOMwhncYTrekbny97euwG5l3FO0wX0e67hNAbq9zuXdFBX9xTKWL7SDKK1ozfDJlVS7emr+d137cQlFF/dGrVgFeKcX5fc/n6SXGeWj6pumtU4gDsw4gQNekrthUZI+pdxfsqDWu+lr18rwtZKbEMjgzmcGdk83/+/J9+/Vj36xAlYwL+Ro0a80+Hv5qrTl8+tAM7jtjUB1LND1W8bolhLgYh52XLh/NmS/+TFGFiz2FFfxx6nLevOYIbDb/+xOHzcEFfS6nqmgYb617nmJ7FmBc46Lb+eLNVXQBsZnT2b8XYEIzfhp/Plz3IfN2zzOHS5wlYdXDDYVA52K7TZEc66h1ft2VV84HC3fywcKdNVcDQNfUWD64YTzd2weOmZRG67aJUoo/j/0zWTlZrM1b6z8NhVsH78TRWgmWrBFsvHB4U+Hyf146UH4g4ufiw5mBqf1MIS4/poTcksrmq3crCIIgCK0IEeKENoO1PlxLC3FgNAYH6mGcmRLLd386wW9c//TL+HrbTFbmrgSMMlgqugB75icUx3RD6ytbtoaZhSU5S9hSaETnxTniOLt3gCiaII6lcOvGJMdG8eDZQ7hoTFfun7HabITPLijn9a9T6dH9EipjvsBjz8fmbke3pO7sLF8BwK7infxt4Q1U7jsXZ+FYgsZl0jrjP7NLspm+ebo5fNvI24x9oH0fmPB3Q4wLJLoFcR3OyMr267VeVuWmrIYDrm+nRC49ohsXjO5KWkI0ueW5fOktBajsZXQJImK0BqZumGqKlkPaD6kVIRMuT8/agKuGcltdM+ecEZ1rNe6CEXO0bP8yc7iwqrDOh/SVuwu477NVtUQ4gH1FFS0nwkFAMf2jdu1wes9DwzoMa/R3XNMFW1MkK65wMmdtDl+s2MMvm3Jr/R41OX1oBpeN686xfTv4/T41Bf66SIhKIDMhM6jbFsDpcbIyd6Vxvl5vjIuzx1HpqcSjjd+yOs4S6m6gsYpE3ZMjL8QN7ZLCw1nH8kXVsVwwugvPTh5JpcvNB/O38dIPm8m1uNwABmYkcWy/Dry/YAflzuAuQoCz+pzFc8uew+VxseLACrYWbKV3auRj8xqL9TuOZPRnNXsLandm8JteWMHewgrmrveJVdEdi4nxpoYWVpZw9ycrmL8ll+P7dSQ5LorkWIf3fxRJsQ5io+zMyMrmHzPXcaDEFw08unsqz10yMuD5qDnxc8QltEA8JtAtLZ5nJ4/k9+8sAWDehgO8PG8zt03oB4DL7WH+loNMX7abWWv2ec+7l2BPHEFs+ufYomvXpFE2J3Hps4G/N+MnMThQdoA3V7/Je+veqzWtuh5upBp/g52Lzx3Zme0Hy/h50wF+2niA37YcrO2cr4FHE1CEE9o+dpudvIrasc8azb+y/tXmoimDJWtkJGS0wNYIrZ0ZW2bUGhfpc/HhzKCOI/g8ex4Ae2Kc5BZXiBAnCIIgHJaIECe0CUqdpaw5aMTSKRRj0se08BYF7mEcF2XnntMG1ppXKRUwDs2tXTy1+CneWPkGgzsMZmj7oQxpP4QhHYaY8Vozt85s1qifjzd8bL4+u/fZfvGPfgSIWmwoQzqnMO3mo5m2dDePf7PO7KG9Y+cgwOcEWAM4kgcTm/Epyl6FsrmI7fwp9vhtVOWch13F4HTXbsxv8ajFALy24jVcHsOlMrrTaMZ3Hu8/w8QHw3IdBhKWqrlgdBcuG9edsT3a+Qm+KdG+mDx7VAU/33NixN0kkaDKXeXn0rxycOOF67pq5kx89kcuH9edi8Z09Ys+e2HZC7V6hVe4K3hq8VOc0esMlFKUVrr4fPkePli0g9XZwaMr62vcb3JqiOnlKV35uF08uI3v5Zoh10Skc0BdIllSbBQXjO7KBaO7kldaxber93HfZ6sCzquAV66MzHn/jtF3MOXXKX5uW4fNwZC0IeRV5vkJO9WUu2vvLxXuCh7+7WHsNjujO40OGIm4s8jnKmkKR9zQLr5jePqybL73xssVlPu7XHp1SOCPp/TnrGGZ2GyKoZ1T6nURpsWmcVK3k5izw4jNm7F5Bn8a+6eQt625rl27i30dFppCiAsW6xdlVyil/FydJh5LzUdbJS6P5pMlu/lkSWBHs11BzUuXwjh3t0h0rQWttZ+DpCUccdWcPDidm0/ow6s/Gp2Fnpm9kWdmbyQxxoFCm1HXVnTpQEbbx7GcWwOuUzvy2Va4jV4pvZp026upFuA+2fgJle7g9Vgj7doJdi7u1SGBXh0SuHp8T6pcHpbtzOfnTQf8aplaqRlTKRxaWEV3K23RRRboWi91C4Vg5JQeOvt+a+G1114zXw9MH2m+3hxtpyA/D3q0TJkRQRAEQWhJRIgT2gTLcpaZDeD92/UnNTa1ZTeI+t0eNQn2cAuQX5nP/Oz5zM+eb47rFNeJ9nHt2ZS/yayNF6oLo6EcKDvA3B1zzeHJAyIjtIWCzaaYfEQ3ThmcztOzNwSNRXIVjaC0ojNxXd7DHmt8p1Gpy+jXvYCzM+7lua8La4mjrSJq0cLOop18seULc/i2UbfVFj3CdB0GE5YU8OzkkQGnRdmjSIhKoNRZikd7KHGW+NVAay18s+0bDlYcBIzj4tQepzZ6nXXVzNmWW8o/vl7H07M3cOawTK44sjtjerQL+jCeV5HHJV9cTVrVOfyyOpmSyvBiAFsMi5j+xfqPKVj4KABdErswsfvEZt2UtIRoLj+yOy/9sDng7xLJ76u+Wkb5Ffmszl3NqtxVrMxdyerc1RRWFgZcV5mrjD//+GfA+N7GpI9hVKdRjO40mrUH15r1dgByyyNfnH7bgRK/4ZoCXOeUWO44uR8Xju6Kw+LADNVFeF7f80wh7vMtn3P76NuJskXVs5Qhwj3464Om0NCU166mdsQF63Tz+AXDOGt4JltzS1m3t4i1e4x6hz9vykV7fAK+sgUXW6pxa3AkZxHTcZZf/bJX5sVx5VE9I/6ZwqHEWWLWWou1x7b4NeLuSf2ZvWYfW3N9tfcCnXMHZiRx4eiunDuyM52SY5k0LbgT9rzPz+Os3mdx0/CbmsS5CqELcNW0hGsn2mHjqN7tOap3e2Zk7Wnyc7HQ+jiUXGRSt1AIh0Np328t3HjjjebrAWm+jspbo6MoPrgN6NsCWyUIgiAILUurF+KUUhnAX4GzgC5AIbAIeF5rPbeuZetZbzLwF+BCoAdQDiwHXtFaTwth+YuBW4ARQBywA/gUeFJrXdzQ7RJqM3PrTB5Z8Ig53CGuQwtujT/hRKIFu8FXKDS1nUz7y/ezv7y2i67CXcFjCx+ja1JXBqYNJMYeU2uehjJt0zRT9BvdaTQD0ppfwGqXEM1j5w/jw4U7A3wrBnefdCxH9Tmdz3b+m8+9USLbi7byn7I7uPSk25m9qEtI4mhL8cqKV0xh+ciMIzki44jAM4bhOgwmLNXXaJYSnUKp02jQLKwobPFG1pporXl37bvm8GWDLiPKXr8QUB/BauY4FFR6rSlVLg+fZWXzWVY2/dMTSerUgSLXgYDrW1ewHFiOu1N/bAcm4anoSrTDxvAuyazKLqLSVXcMYEvi9rh5Z+075vBVg6/CYWuZ24Ngokekv6+6ahm1i23HcV2P47iuxwHGPjjxk4kcKA/821eTXZJNdkm2n8hu5fPNnzMmfUxEGwFf/H5zwPE2BX8/czCXH9m9UY6qozsfTae4Tuwv309eRR4/7/6ZCd0D19PKLc9l8b7FLNy7kBmbZwR0jz679Nk2J8TV1+mmf3oS/dOTOHekMXzME3PJjfF1vIlKWYK7vDvRFWM5cUBHiiqcFJaXUVhVTHFVEaXOYkhYTXS7X1E24ztrLfXLwN8lkJ6Q3uIx2g67rVbscjU2Bb87phcXjO7K4M7+17JA7phqPNrDF1u+YObWmZzT5xxuHH4jXZMCx0CHS10C3OD2gzki/Qg+3vBxq3PtNNe5WGhdHGouMqlbKITKobbvtwaUUmhtPFMlRifS2W1jj92DSyl2560ETmnZDTwEae4kJUEQBCF8WrUQp5QaDnwPtPeOKgI6YIhyZyql7tNaP9GA9XYFfgKqc2hKgGSM1o4JSqlXtNaBM2yM5V8HbvAOuoAKYCDwN+AypdRxWus94W6XUJuZW2fWuiletG8RM7fObHM3FcFu8B8Y/wDDOw5nTe4aVh9czZrcNazLW2f2QA9EUVURV359JQ6bgwHtBjC0w1CGdxzOsA7D6JHcg2+2fRP2TZjT42TaBp8GfenASxv/oRtBMGGpS2ocfzjJ6EE3pvsjjEkfzWMLH6PCXUG5q5xpu54ivls8SZnlJCRkEJVyB4aG3zrYUrCFmVtnmsO3jbotIuttaKNZSkwKe0qN01VhVSHdiHxDdmNYvG8xG/I3AMbxcnH/iyOy3mCN65OGpPPVir28v3AHK3b7XFAbc0pwlE8gNnM6yuZzHWltAzxUt007EjfiSNxIn4SjeOCYPzI6czAzsrJDds62BPN2z2NnseFATYpO4vy+57fYtlh/l+yC8lZRt1ApxV1j76p1/o62RXNMl2MocZaw6sCqgA38Vqo8VRGvNRLMCas1/O7YxkftOWwOzul7Dv9Z9R8A7vjhDjITMrlj9B0c1/U4luxbwqJ9i1i4dyGbCwKLglb2l+3nzh/u5KL+F3F056MjEoXb1EIchNfpZtK4PXyyw1dLUtmdxHaeSqJjFmscNoqii3A5fA6uYF1plM1JbOdP+MtPRfRv19/8S4/3iWHN0eBiFZb3luxtFfdfOUWBjzWt4e9nDQ44LZA75vy+57PiwArm7zHSCNzazWebP+PLLV9yXr/zuHHYjWQmZoa1bdbfJN4RT4W7opYoPbj9YG4dcSvHdz0epRSD2g9qdQ1n4aY+CIcG4iITDldk3296EogCjA4p/yv9gB5bB8r320hcHhe7i3eztXArX2/9mu92fmfec+wt3cuDvz4INE2SkiAIgtAwVHUvldaGUioOWIfhVssCrtJar/E62R4A7gI0cJrWenYY61XAb8CRwHbgCq31r0qpWOB24AnABtyotX4jwPK3AC8DHuAe4F9a60ql1NHAB97tna+1PjaU7Rk7dqxesmRJqJt/2DFp2qSALrLMhExmXxTyz95qCLXRzO1xs61wG9fOujZoJFowYuwxON1OPPgcONG2aG4ffTsX9ruQxKjEWj3aZ26dyZOLniS/Mh+ABEcCP1/6c0ScRw1lRlZ20Diwmg1BG/M3cte8u9hetL3Wehw2B1cPvpqrBl/VKtyUd827i9k7jH33mC7H8OrJr0Zs3Q0RfM6bcR5bCo1aMGmxafzliL+0qpv12+fezrzd8wCY3H8y94+/v9nee9XuQj5YtIPPl+8xHRiB4uPc5T2I6zgXe8oysPg4FYrTe53O4PaDeX/d+632wf7qb64ma38WANcPvZ47x9zZshvkZd68eZx44oktvRkmdZ2/nW4na/PWkpWTxbL9y/hh1w8B16FQrLxmZcS26Zgnvg/aYWH+vZFxUr295m2eWfKM37hgTu5w6JzQmQv7X8j5fc+nY3zHBq1jxuYZ3D/fd0549JhHObfvuY3arsYS7L4lUiRFJ9G/XX+ibdEsyVmC0+PrGBBjj+FvR/6Nc/ueG1DkrO8exOlxUuYso9xVTpmzjNk7ZvPqilf9hKRYeyxTjp7SJOewUI/5SO/3WfuzeGn5Syzcu9BvvEIR54ij3FVOenw6vxv6O8Z3Hk+ps9T35yqlzFlGqbOU5fuX8+PuH2sJb9XUFOAEQWh913pBECKD1RE3c+tM/vbTX3Er372jQ0Xz6LEPR/5+YuXUkEs7NCfhdp6yzp8en85F/S+ia1JXthZuZVvhNrYWbGVH8Q6z5nwwHMrBdUOvY2L3iQxuP1juP4QWQa71wuGGUmqp1npswGmtWIi7E3gOw602UGudXWP6Z8B5wDKt9Zgw1nse8BmGkDZGa728xvTngDuBfUAPrXWVZVoMsBPoBDyntf5TjWVHAUsxyjKdo7X+sr7tESGuboa/PTxgY1+kGzNbK4EcgQ6bg6Hth5Jfmc+Ooh1hrzPKFkW72HakxaaRFptGmbOMVbmr/BqOHMrBo8c+2uJiQbWwFIozptRZyokfn1inKyUtNo1+7fr5uQv6pPbhux3fNfjGOBxhZUPeBi768iJz+MMzP2Roh6H1LtdUzNw6k/t+uQ+P9om2TdnIGi47inZw9mdnm+eAL877gl4pjXf5hEtxhZMZy/dw/4zVQedZdv8pFDh389Lyl0yhNRit6TtecWAFV359JWCcW2ZdOItO8Z1aeKsM2vINe3N1Igmnw0JDCVVYctgcDO8wnKMyj8KlXbyz5h2/83Ew8c6u7JzY7UQu7n8xeRV5/CvrX7XOrR7t4UDZAfaU7iG7JJu9JXv5bc9vLM1Z6tfppDUcW8HuW6xE2aJIjk4mOSaZpOgkNuRtCKluWDhE26KJdcQSa48lxhFDpauSA+UH/LZNoYw4YgVlzjI/Ua8umqozVKjHfFPt94v3Leal5S+xNGdpg9cRCIfNwfMnPi8CnCAEoC1f6wVBCM7ZZ5/Nl18azWHHfjCRQmftkhsKGyf3mMjwDsMZ3nE4g9oPIs5hKasQSFQbdA44y4y/qjJwloKz3Hi9eQ4seRPcVb51OGJg4oMw6kqISYaaHZLn3c8LWz9jnw0yPHBH7/M588RHqAvrMh09cHnXiQwffiWFlYUUVhZSUFlg/i+oLGBrwVZ2Fu+sdX+YFJVEfFQ8NmVDoVBKoVCUOcvIr8xvdKe3mmQmZDKh+wQmdp/IqE6jWqwUgXD4Idd64XCjrQpxi4GxwOta65sCTD8amO8dHKi13hDiej8BLgJma61PDTC9C7ALQ0w7XWv9rWXamcBXGJaHbjXFQe88szECrz/WWteb7SdCXN0cao64hlCX6FNYWcjq3NWsyl1l/B1YZbraGktr+o5DvXCH0gBaE4VxM25dzq7sHN/1eIa0H0K0PZpoezRRtiii7dGszl3N9E3T/Roso23R3DT8JiZ0n0CUPYoom+XPOzxr+ywe+u0hs7F1UNogpp49NaxtjTTBjq94Rzx/GPkHuid3p3tSd7okdfGrRdiYHn2hCpczt87k4d8epsxVBsCA1AFMO7fe8p1NyjFPzCW7oLbQW9OFsT5vPf/O+jc/7v4x6LqibdGc3+98eqX0oldyL3qm9CQjIQObsjX4+2rIMlahf3Sn0bx9+tt1LtOctOUb9kCdKJpKJGrq6NO6zqtD2w9lXOY4jsw4kpGdRhIfFW9OC7RPDmo/iGkbp/HFli8Cur1rinU2bKTGpFLsLG5xkShUgp1XO8Z15OOzPiY5JrlWbddg+8u1Q66lU0InNuZtZGP+Rjblb6LY2fJliJuqM1Q4x3xT7fdaaxbtW8Qt390S8j5XH4dL5zFBaAht+VovCEJoDPvfMAihH4od6E8sw7WDEWWlHKzI44PkJPY57GS43NyRX8CZpWV1rmNmQjwvtEs1l7mhoJAxlZUctNs56IgiLzaRg9HxHIyKZi0VrFdutFWc05ooZTNFKm3+abQGl3YZTr9W0rGmU3wneqX0YtWBVeZzcyi0i2nHid1OJDk6mVk7ZpFTmtOkHZKFwxu51guHG21OiFNKJQGFGJfrC7XW0wPMYwPygBTgD1rrl0Ncdy5Gzbm7tNbPBplnFTAUeFpr/RfL+GcwIjFXaa2HB1n2LuAZ4IDWul5bgQhxddOcjZmHAlprTv7kZPaX1+5xZld2ou3Rddaes9KaGo5CvXAHawCNskXhsDlC/uzNQbQ9moePboI4jjAIVbhUKDISMuiW1A2tNVn7s3BpXwxGlC2KC/tdyPCOw3F5XLi1G7fHjUu7WHlgJbO3z/ab36EcHNvlWHql9sLj8eDBg0f7/rYVbmNpzlI/l2a0LZqHj2nZ7ytcF8by/cu56purQl5/rD2W1JhU9pfv93MpOmwOTup6Et2Tu1PuKjf/ylxGhNze4r1kl2bXcrr0SelDj5QeJEQlEOeIIyEqgYSoBOId8Wwu2MwXW77wF5RbwT5ppa3fsB8qD6rBzqvp8el8d/F3DVpnpbuSOTvmMG3jtIi7j1r62tXQ+5ZQ9hetNTllOWzM38i9P90bcVHOruzEO+KJi4oj3hHP7pLdASOPWtoR1xzUdX0clDaI+Kh445zqSDBfT980nRJnSa35W1ocFoTWTGs67gVBiBxWR9zE/wxhf1Tj6wIrrenscpHq8ZhXaG1R+ApsNvY57P7C2iHG74b+jt4pvemd0pteKb1IjE4EjPvIB37+O1X47tuicTB50KUUVRXxw64fKK6q/75RoRjeYTj90/obz41R8cQ7jPucDXkbmLbhE1xYntFx8PBxdScpvfjJn/i8cBYHHIqOLs25KafyfxcHbIpt8DLN8R6H0nYdSp9Ftqt1btfhTlsU4sYB1YUagrrdlFILgXHAS1rr20JYbycgxzt4mtZ6VpD5PgYmAzO11mdZxn8NnA58pLW+LMiypwNfewc7aq1z69omEeLq51BpzGwu6msELHeVk1+RT15FHnkVedz3y30BnQmtqeEo1If0uj776b1OJ7s4m435G82/TQWbGhTvGSla+jtu6lpGkaalvy8I34Uh33HDkca51kFTd4jZWrCVaZum8e7ad+ucr11MOzondqZzYme6JHZh+qbpFFUV1ZqvNezDzXHfUt/1rspdRaW7kgpXBRXuCq799lpyy2vfknaK68S0c6YRHxVPtC3aLzqxuTtDtaZjviGJDNJ5TBDCpzUd94IgRA5rjbgvn+7Mwx3aUWHziXGxHg835heSqj2sjIlhVUw0W6KjW2pzG4/WnFhWTqrHQ4rHQwpRJMW2JzGxM09UbqPQVrt+bCpxvDT+eTQaj9Ze153mjoV3UUjtFJY04vn4pPcCvv22Xz5m3+5XeSXN5yC8Ja+YjK430+vYS3B5XKwsWMMvuQuZf2AheVWRSVGqpnNcJqlRybSLTiElKoXUaONv7eYfme/ehNPmu7+M8Xg41z6ac4+6JeC6Pl/wCp+7l1Fp2V/qWibc+Ztrmda6XYfSZ5HtapntivV4uCpRxLi6aItC3LnADO9gstY6YNcNS5246VrrC0NY7whguXdwuNZ6VZD5quvE+dWfU0plASOBZ7XWdzXmPaoRIU5oCsJpBGwLDUfhPKSH2wB6yiensK9sX63xiVGJXDrwUqrcVVS5q3B6nFS5q5izY07AOnQOm4MeST2M+TxVON1OnB7jL5gTrzU6N6JsUZzS4xQSoxLZVbyLncU72Vu618+h1VK09PfVEAJ9xzH2GC4ZcAkd4jqwvWg72wq3sb1we8RiZRtDa/qOpXGu9dAcwtIp005hX2ntc3HHuI58df5XfrGX1dvU2q9dTU1zXOubszNUazrm28L3JQiHAq3puBcEIXJYhbiyJwfyg63QLzLyjvwCTqm0sbbP71l7wMnqXBd5HsiNLSU/roD97VdELv5Rg6u8B8oVT7Q7hji3gyS3jbIOCyi013bqdXK6uXVnF2JwEUMVMcpJLE5icHF3Nxf7omrXVst0upi9e0/At5+ZEM+UDmm1hMgpuXkBozbDnT9cPMCqmGiuzExvNRGbgiC0LTo5Pcz9/ZqW3oxWS1sU4i4H3vcORmmta+fiGPO9D1xOkHpvAea31pXrp7XeHGS+fwD3ARu11gMs4zcC/YB/aK3/HmTZfsBG7+DRWuvfAsxzI3AjQHp6+piPPvqovk0XhCZlccliviz4knx3Pu3s7Tg79WyOSDyipTfLpKSkhMTExCZZ9+KSxXyY9yFO7Yvoi1JRXJZ2WcDvINz5AR7Y/QD57toiSzt7Ox7u+nAEPkXDCeW3d2kXea48DrgO8Hbu25R7aguLUSqKkfEjsWHDpmzYsWNTNhaWLKRSV9aaP07FcXLKydiwoZQy/qOMGmkFMynz1H7IaA3fV0MI9fgqdZfyjz3/oNhTu+9JrIrl5JSTiVbRxKgYom3e/yqat3PfDrhMoi2RS9IuoUJXUOmppFJXUuGpoFJXsqBkAVW6qtYyrek7bsrjXmh9NOTc2tqvXa2N1v59tbZjvrV/X4JwKNDajntBECLDSSedxA8//ABAp5wf6bv+30Rbnj2qVDSbB97G/vQTAKh0a9YddLN8v5vlB9w4uk2hMqr2M2e0K4b8Xb/Hv+ic8Tqu6/+wRdV+JvJUpVK65d5a48elfMS2jGW1BK9e+0azqPDSgJ8r2DJn57RjSGkKfdReeqs9JCv/ba9Zu66+enfhzt8QJnXtzN4AomKq280f8gsptSnKlI0ym6LUZuObhHi/zy0IwuGL0poXe/67pTej1XLSSSeJEOedv1UIcVbEEScI9dPUvWXD7cHekPkPFedGuJ+lIZ/9UPq+wqW5vq+28B1LL/nDD3ETHd7IMS8Ihx9y3AvCYcLKqTD3YXThblRKV5j4AAyfHHBWrTWjn3sST7uP8FgiHW0eO+V7L6KDGh9wuVz9G9GZ01E2X6cu7Ymiau8FAZfJKapgTPJHHOy4zKx91P7AaJYWXUp6cmzA9whpGa1Jo4AeOpseOptbnW+TqGon6ri0jVyVVmt8B52HQ9VOowk2f0OXWRRfziMda0eG3n8gn3FlcSHPf9fBAnpXxlFgVxTaFAV2RYEd8u2KOYn2gOKdTWvauwO3RR+0KzwBnHrBlgl3/uZaprVuV0OWke2S7aqJOOLqpi5HXO3uD62DUsvrOCBYVdHqnKLaldFDW28wgq23evlQlg1nuwRBaEHO7H1mWI29DZkfOCQamMP9LA357IfS9xUuzfV9Hc7fsdB6CffcKgiCIAiCILQ+Xn/9dW688UbfiOGTYfhkfgxBfFdK8eBJV3HfbA8q7RtUVAHamYo773SeOv2aoPW5Z2QN5L7ZNr9ldB3LzMjK5q/T7ZRvNtxvRcCeKDv/nDysjvcIf5nFX/Rh6NK/E6d8jsByHc3qMY9yxDk3BZj/tbDmb+gymV+8xn3rH+WVtERLXbkSMgc+SEaAZYLN33XgA0HfI+OTP/Fuyaxa4l1d9aVeDHOZcOdvrmVa63YdSp9FtqvltuvclHq9UEIQWqsj7ghgkXdwoNZ6Q5D5FgLjgJe01reFsN6OwH7v4Gla61lB5vsYmAzM1FqfZRk/EzgD+EhrfVmQZU8HvvYOdtRa59a1TeKIE4T6kd6ygnD4Ice9IBxeyDEvCIcfctwLwqGJtUaclXCO+RlZ2Tw9awN7CsrpnBrHn08dEFTsaugyzfEeYAhl3ZY9TSedy37VgV2j/xxUvGrI/M21TEPe48VP/sTnhbNMB+G5KcEb/Ru6THO8x6G0XYfSZ5Htap3bdbjTFmvEJQGFGGHPF2qtpweYxwbkASnAH7TWL4e47gNAB+AurXXAPUcptQoYCjyttf6LZfzTwN3AKq318CDL3gU8AxzQWneqb3tEiBOE+pGHdEE4/JDjXhAOL+SYF4TDDznuBeHQJBJCnCAIhwZy3AuHG3UJca2y0qbWuhioVqdOCTLbkRgiHMDcMFb/Q13rVUp1AYYEWW/1skOUUplB1j+pAdskCIIgCIIgCIIgCIIgCIIgCIIgHGK0SiHOywfe/1cEEb3u9v5fGiy6sp71TlJKjQgw/U8YTry9+IS3auZiRFvagLtqLuhd38newffD2CZBEARBEARBEARBEARBaNN88cUXLb0JgiAIgtDqaM1C3GvADiAJ+EopNRiM2Eql1FPABd757qu5oFJKe/+mBFjv58BCjM/+mVLqKO8yMd5YyTu98z2ota6yLqi1rgSq1/lHpdRdSqkY7/Ljgc+8652vtf6qQZ9aEARBEARBEARBEARBENogY8aMaelNEARBEIRWh6OlNyAYWutypdS5GC600cAapVQRkIghdmngPq317DDXq5VSFwE/Ab2A35RSJUAsvu/jVa31G0GWf0UpNQq4AaMW3ONKqUrvdgFsBSaHs02CIAiCIAiCIAiCIAiC0Nbp0qVLwBpxgiAIgnA405odcWitVwBDgRcxBK4Y4CAwEzhFa/1EA9e7GxgJPAasxxDgijGiKCdrrW+pZ/kbgUu885d4l18P/AMYqbXe05DtEgRBEARBEARBEARBEARBEARBEA4dWq0jrhqt9T7gDu9fqMuoEOYpAv7m/WvIdk0FpjZkWUEQBEEQBEEQBEEQBEEQBEEQBOHQp1U74gRBEARBEARBEARBEARBaBvccMMNLb0JgiAIgtDqECFOEARBEARBEARBEARBEIRG8/rrr7f0JgiCIAhCq0OEOEEQBEEQBEEQBEEQBEEQGs2YMWNaehMEQRAEodUhQpwgCIIgCIIgCIIgCIIgCI1m2bJlLb0JgiAIgtDqECFOEARBEARBEARBEARBEARBEARBEJoAEeIEQRAEQRAEQRAEQRAEQWg0mZmZLb0JgiAIgtDqECFOEARBEARBEARBEARBEIRGs2fPnpbeBEEQBEFodYgQJwiCIAiCIAiCIAiCIAhCo5kyZUpLb4IgCIIgtDpEiBMEQRAEQRAEQRAEQRAEodE89NBDLb0JgiAIgtDqECFOEARBEARBEARBEARBEARBEARBEJoAEeIEQRAEQRAEQRAEQRAEQRAEQRAEoQkQIU4QBEEQBEEQBEEQBEEQhEazZMmSlt4EQRAEQWh1iBAnCIIgCIIgCIIgCIIgCIIgCIIgCE2ACHGCIAiCIAiCIAiCIAiCIDSasWPHtvQmCIIgCEKrQ4Q4QRAEQRAEQRAEQRAEQRAEQRAEQWgCRIgTBEEQBEEQBEEQBEEQBEEQBEEQhCZAaa1behsOa5RSB4AdLb0dgtDK6QDktvRGCILQrMhxLwiHF3LMC8Lhhxz3gnB4Ice8IBx+yHEvHG700Fp3DDRBhDhBEFo9SqklWmsJmheEwwg57gXh8EKOeUE4/JDjXhAOL+SYF4TDDznuBcGHRFMKgiAIgiAIgiAIgiAIgiAIgiAIQhMgQpwgCIIgCIIgCIIgCIIgCIIgCIIgNAEixAmC0BZ4vaU3QBCEZkeOe0E4vJBjXhAOP+S4F4TDCznmBeHwQ457QfAiNeIEQRAEQRAEQRAEQRAEQRAEQRAEoQkQR5wgCIIgCIIgCIIgCIIgCIIgCIIgNAEixAmCIAiCIAiCIAiCIAiCIAiCIAhCEyBCnCAIrRal1PlKqa+UUnuVUk6lVLFSarlS6gmlVHo9y9qUUjcqpX5TShV4l81SSv1ZKRXdXJ9BEITwUUp18R7nq5RSRUqpEqXUJqXUB0qpc+tYTo57QWjDKKXsSqklSint/ZtSz/xyzAtCG0Ip1VEpdZNS6hOl1BalVIVSqlQptU4p9W+lVN8Q1iHHvSC0IZRSGUqpFyzHfI5S6kul1MSW3jZBEMJDKdVdKXWn9xjeqZSq9F6HV3if3zPrWT5aKfUXb7teifc6/pv3uq6a63MIQkshNeIEQWh1KKVswDvAFZbRxUA8YPcO5wGnaa0XB1g+CpgBnOEdVQW4gTjv8GJggta6JOIbLwhCo1BKXQz8F0jyjioDNJDgHZ6rtT45wHJy3AtCG0cpdSfwnGXUQ1rrKUHmlWNeENoYSikn4LCMKgGivX8AFcDvtNYfBllejntBaEMopYYD3wPtvaOKgEQMU4AG7tNaP9FCmycIQhgopboBOwCrYFaE8Zxe3U6XD1yotf4hwPLJGOeDMd5RZRj3BNX3AF8B52utXZHfekFoHYgjThCE1sgN+ES454F0rXUyEAucBuwE0oAPvaJdTR7FeECvAK7FEPASgLMxBLwjgNeabvMFQWgISqkzgA8xRLg3gYFa6wStdSLQAbgQ+DrI4nLcC0IbRinVFXgE4wE/J4RF5JgXhLaHA/gJuAbI1FonYRy7xwLLMe713/E23gdCjntBaCMopeKALzBEuCxgqNY6BWgH/BOjMf8xpdSklttKQRDCoFpsmwlcDKR5j+l4jGvzNozje4ZSKiPA8m9giHB5GNftRO+y12Jc188CHmrC7ReEFkcccYIgtDqUUj8CxwPfa61rRVYopU4EqnvYjNJaL7dMywC2AzHAHVrrF2ssey5GT1oNjNRar4z4BxAEIWy8PeTWA5nAY1rrv4WxrBz3gtDGUUp9BpwHnAu8CPQgiCNOjnlBaJsopY7XWv8UZFpHYDXQCfif1vq6GtPluBeENoTF5V6C0bkuu8b06uv+Mq31mForEAShVaGUSgF6aq1XBJk+EEN0jwWmaK0fskwbBSzzDp6rtf6ixrJ3YHTCL/e+x/7IfwJBaHnEEScIQmukuv5bVpDpSy2vE2pMuxDjAb0QeL3mglrrz4GNGD3wLm/cZgqCEEGuwxDhdgNTwlxWjntBaMMopc7BaIz7quaDeRDkmBeENkgwEc477QA+13ugRnk57gWhbVGdcPNBTRHOy9Pe/6OVUgOaaZsEQWggWuvCYCKcd/p6YIF3sOZ1vPq6vCHIvf7rGNf3OOCCxm6rILRWRIgTBKE1st37f1SQ6dUX9UpgbY1pJ3n//6S1rgiy/Gzv/wkN2jpBEJqC6of1aVprZ5jLynEvCG0UpVQC8G+MHrC3h7iYHPOCcGhy0PvfHmCaHPeC0EZQSiXhe2afFWS2BRgN7wC1UnAEQWiTBLuOV1/DZxMArXU58LN3UK7hwiGLCHGCILRG3vD+n6CUek4p1QlAKeVQSp0KvO2d/rDWOr/GsoO9/9fUsf5q8W6QUkrVMZ8gCM2AUioWGOkdzFJKDVRKfaiU2q+UqlBKbVVKvaKU6hlkFXLcC0Lb5RGgG0Yk7fYQl5FjXhAOTU7w/l8dYJoc94LQdhiE4U6FIMes1toDbPAODg40jyAIbQellAM4xju42jJeAQO9g6Fcw+V8IByyiBAnCEKrQ2v9KfA3wA3cCeQopYowCrh+CxQD12mtHwuweKb3/5463qJ6WqL3TxCElqUnEOV93R8jP/5SjOhZJ9ALuBlY4a0RWRM57gWhDeKtF/F/GHFyT4WxqBzzgnCI4a3xNtY7+FaAWeS4F4S2Q6bldSjHbGYd8wiC0Db4A5ABePB1ngdIxldSRs4HwmGNCHGCILRWHgeuBUq9w0n47O0JQAelVKBzWPUFvryOdZdZXstDuiC0PKmW138F8oFTgUStdRJGz7qNGDfxnyil0mosL8e9ILQxvNfw1zCu7bdpravCWFyOeUE4hFBKdcFX9+0LrfW3AWaT414Q2g7WOu6hHLNyvApCG0YpNRyjDQ/g31prawkZOR8IghcR4gRBiAhKqQeUUq4G/v2jxrqSgC+Bd4EfgCMxGuB7YrhikjGKO7/frB9SEAQ/Injc22q8vlprPVtrrQG01r8CF2H0rusA/L7ZPqQgCCaRvNZj9Jo9ApiqtZ7TAh9HEIQQiPBxH2j9icAMoBOwA7i+iT+SIAiCIAgRQimViXEdjwOWAve06AYJQitGhDhBECKFDaNXe0P/rDwLnAl8p7U+W2u9SGtdrLXeobV+DbgA0MClSqnTayxb7aCLq2Nb4y2vS8L6lIIgWInUcW89DtdorefWfCOt9SrgO+9gzYLuctwLQvMQkWNeKdUZeBQjavqPDdgOOeYFofmI5D2+H94asZ9jRFIeAE7VWucGmV2Oe0FoO5RaXodyzMrxKghtEG9SzWyMUhKbgDO11hU1ZpPzgSB4ESFOEISIoLWeorVWDfy7t3o9Sqlk4Drv4PNB3utHjBpSAOfWmFydK925js2tnlaitS4O64MKgmASqeMe/6z4DTXfJ8C0bjXGy3EvCM1ABI/5xzHc7U8BRUqpROsfoLzzRVvGWZFjXhCaiQge934opaKBacAEoACYpLWu6x5AjntBaDtY7+1DOWb3NuG2CILQBCilUoBZwFBgJ3Cy1jonwKxF+MQ4OR8IhzUixAmC0Nroh6/37LY65tvq/d+zxvjqLOohdSw72Pt/XVhbJghCk+Dt/R7opj3oIjWG5bgXhLZFD+//RzBccTX/unun/9Uyzooc84LQhlFKOYAPMRIwSoAztNbL61lMjntBaDusx3e/HvCY9daKHeAdXBtoHkEQWidKqQTgawxH+z4MEW5noHm95Saqr8uhXMPlfCAcsogQJwhCa8Njed096Fy+RryajXM/eP8f5427CcQp3v+14u8EQWgxqmMnB9Qxz0Dv/+01xstxLwiHF3LMC0Ibxdv4/jZG1Hw5cI7W+rcQFpXjXhDaCF5H6hLv4ClBZjsSSPG+lmNWENoISqk44EvgaOAghgi3qZ7Fqq/hAc8H3uv6cd5BOR8IhywixAmC0NrYAFR6X98QaAal1GhgtHdwYY3J073LpwK/D7Ds2RgN/RqjJ64gCK2Dd7z/hyilTq45USk1DF9tuK9rTJbjXhDaEFrrE+uKswN2eGd9yDLOihzzgtAGUUop4HXgcqAKuEBr/UPdS5nIcS8IbYsPvP+vUEplBph+t/f/0npiaQVBaCV4Y6WnAyfhi5VeE8Ki1dflgUqpswJMvwFDmC8HPovApgpCq0SEOEEQWhVa6zKMXrIAFyil3lBKdQOjl4xS6lxgBuDAyJr+X43l9wEveAefUkpdpZSye5c/A3jLO+1DrfXKpvwsgiCEjtZ6NjDHO/i2UuoUb4MdSqnxGHVkbBiRtW/VWFaOe0E4jJBjXhDaLM8B1wMuYLLW+ttQF5TjXhDaHK9hdKxJAr5SSg0GUEolKaWewnDFAtzXQtsnCEIYeK+5HwCnYSRTna61XhbKslrrLGCqd/B/3us2Sim7Uupq4EnvtOe01vsju+WC0HpQRlSrIAhC60EplQh8AxxrGV0KxOHrQFAMXORtvK+5fBSGWHeGd1Ql4AbivcOLgYlSxF0QWhdKqfYYsRXDvKPKMI7dJO/wHuBUrfXqAMvKcS8IhwhKqe0YEdQPaa2nBJlHjnlBaEMopbrjc7s6gby65tdaZwRYhxz3gtCGUEqNwIiZa+8dVQQkYjzTa+A+rfUTLbR5giCEgVLqeOBH72AFUFjH7Lu01kfUWD4Z+B4Y4x1VBtiBGO/wV8D5WmtXxDZaEFoZ4ogTBKHVobUuAU4EfgfMBg5gXJzLgdUYvWmHBRLhvMs7gbOBm4EFGA/pGlgO3AMcKw/ogtD60FofBI7AOE6zMGpGOoA1wGPA8EAinHdZOe4F4TBCjnlBaHNY2x6igPR6/mohx70gtC201iuAocCLwFaMZ/qDwEzgFBHhBKFNYb2Ox1L3NbxjzYW11kUYdeXuBVZgXL8rMa7nN2HUjBURTjikEUecIAiCIAiCIAiCIAiCIAiCIAiCIDQB4ogTBEEQBEEQBEEQBEEQBEEQBEEQhCZAhDhBEARBEARBEARBEARBEARBEARBaAJEiBMEQRAEQRAEQRAEQRAEQRAEQRCEJkCEOEEQBEEQBEEQBEEQBEEQBEEQBEFoAkSIEwRBEARBEARBEARBEARBEARBEIQmQIQ4QRAEQRAEQRAEQRAEQRAEQRAEQWgCRIgTBEEQBEEQBEEQBEEQBEEQBEEQhCZAhDhBEARBEARBEARBEARBEARBEARBaAJEiBMEQRAEQRAEoVlRSk1RSmml1P9a4L3/533vKc393s2FUupa72ec19LbIjQepdR27+9p/evZ0tvVkiilRgb4Tua19HYJgiAIgiAIQiAcLb0BgiAIgiAIgiC0DF4h7JoAk0qAncCPwL+01uuac7saglIqFbgTQGs9pSW3pbHU8buEQq8IbkqrQynVFfgDMAnoC8QBucA+YCUwD5iltd5bY7lrgZ7ADK318mbb4MiSD1R5X7utE7zC3LYAy5QChcBuYCnwHfCl1trZdJvZLDiBHO/rOCC5BbdFEARBEARBEOrk/9u79zC7qvqM499XyIUYkoBEAqKiFoQKKIo8ilRCrUIARaMgdwHvghLBC9qqSKVQRBEURVFA0ShIqdBawkUlIuBTtOFukCoBRe6BYAiEQN7+sdbOHE7OzJxJzjADfT/Pc5599lp777X23uvwPJkfv7USiIuIiIiIiGXAwvpdwHrA39bPuyXtZ/vHI9W5Lk0BPle/HzXAcXcCN1OCN6PVIvqCDK1aAw6d6qEEaBZR7vH23ndt5Eh6M/ADYO2W4gcp734DYGtKAPMkalC2xYHADsAC4Jph7OZwmmn7si6Oaw3YjQWmARsC2wIfBO6SdJjtc4all08B2zdS7qsJsp4xoh2KiIiIiBhApqaMiIiIiIgrbU+rn/WB8cAMStBiLHCGpKkj2cFesf0p25vZ/tpI96U/tg9reR8rPsBhLcesVF8/f7L97/UeDxjB2+gpSS8GzqEE4X4L7AZMsL2O7QmUbLeDgUuA5SPVz1FiZst4WBcYA2wBHA7cRglgnf1Mnp41IiIiImI0SSAuIiIiIiKexPYy23OAfWvRs4G3j2CXIt5HCRDfBUy3/VPbjzSVtm+zfYbtNwGfHqlOjka2l9u+0faJlIDcf9Sqz0naZQS7FhERERHx/0ICcRERERER0Z+rKOvFQZmmciWSxko6VNLlkhZKWirpNkmnS9p8qA1K2kjSxyTNkXSLpCWSHpI0T9Ln61pw7edcRsv6WJLc9jmqpe7MDmX71rK7JK0xQN9eW49bJmm9DvVb1Pu+VdKjkh6UdIWkD0gaM9RnsaokHVj7eVmHugW1brqkDSSdKulPkh6R9DtJH5X0rJbj96jv9sH6Hn4qaYtB2p8q6VhJ10taLOlhSTdIOkbSuqt4W1vW7Vzbiwc60PajLX05UJIp01JCye5sHRsLOvR/yGO6dVxJGl/H6vz6XO+R9ENJm67arfdOfXb70Pd7Obr9GEnrSfqQpPPrPfy1vsObJH1Z0oYdzjmg5TfU7xIYknasxy2RNLmlfKykwyRdWcfaMkl3S7pW0imSXtuD24+IiIiIGBFZIy4iIiIiIgaiul0pQCVpA+BC4OW1aDnwMPAC4CBgb0n72j5vCO19hb7su8cogcApwCvqZ19J023/ueWchZQ135rgWPv6aQMGboCfAEuA9YE3ABf3c9zedXux7SetMSfpUMraZE0QazEwEdiuft4paVfbSwbpy1PlRcAPKdMUPkSZvnAz4MvAi4EPSzoO+CRl3bkllGkhdwG2k7St7VvaLyppe+B8oAm4PUYZFy+rn/0lvdH2zavY7+cN8fhHKOOhmaLxoVrWuLf14B6M6XHAL4DXUO79UWAqsBfwFkkzbP9yiPfQU7YXSzqJ8lt7laSXtr2PI4Ej6vfHKc9sMrB5/ewn6R9sX9dyzo+Bkym/oRn0Zd21O7huz7O9CKAG7i6mL1hqyjqHzwGeC2xVv1+1SjccERERETHCkhEXERERERH92Y4yLSXAH1sraobX+ZSAxc/qseNtTwI2pPyRfzxwlqSXDKHN3wEfATYF1rL9nHqd6cDVwEuAb7aeYHsm8OqW/fZ1004YqEHbDwMX1N29Ox1TM+X2rLuz2+reCnyVErD5BDDV9trABGBn4Jba/xMH6sdT7ERKVtTLbU8GJgGfqXWHSPo0ZU2xWcDk+l63BG6mBEaPab+gpBdSAjDrAt8ANgHWooyhLSnBlucD5w2UediP39Tt9pIO6fZ822fX9fWurEXt6++tGDc9GtMfpASODgAm1me7NfA/lPFwjqR1ur7r4XNhy/e/a6u7nTK951b0/QbHAdsAF1ECi7MlNUF66jShze/ioE4NSpoEzKy7p7dU7UMJwi0B9qeu/VfbfCFwKHDtEO8vIiIiImLUSCAuIiIiIiKeRNIYSTsB369Fy4Cz2w57FyX4dTkww/ZVtpcB2L7T9kcpAbMJwEe7bdv2Z2x/1fYttpfXsmW251KCWvcCMyRtvOp32FETRHibpPEd6nekZPssoWTQASsCdF+pu3vY/mKTLWf7MdsXUTKElgAH14yr0WA5sEuT1WR7ie0vAD+nZEEeA3zB9kk1UIntG4D31vPfImls2zWPoQTpjrP9Idv/W9cnW17PfTNwHWWa07cNsb9fB+6p378G3CFptqRZkraTNG6I1+ukF2N6MvA+22e1nHsNsBNwP2UMHdKDvq6uW4Cl9fuLWitsn2z7WNvX2368lj1h+7fA7sBNlOzG17dd87S63U3S1A5t7kV5drdSsgYbr6nb79n+fjO1aG3zdtun2D521W4zIiIiImLkJRAXERERERHb1bWd7pJ0N2U6vTnAxpSAzfvbpoKEErQAOKkJOHTwg7p9Yy86aXshJbNJlGylXppDmeJyMmX6xXZNptwFTWCqmk7J2rmhBt1WYvsPwK8pSwNM71F/V9epth/sUH5p3T5Gmaay3RWU8TEO+JumUNIEYA/KeOl0HrYfA86tu0MaE7bvpmRNNZlt61PeyYm1Tw/UwFzHtQy71IsxfRttGZMANTjbZHK+Y5V72CO2DTxYd7tet8/2UuCSuvu6trp5lMy/McB+HU5vMuXOrO03Hqrb0RKkjoiIiIjoqawRFxERERERYyiBjXYLgZ1s/6a1sK7ptG3d/aakU/q5bjN94POH0hlJ2wIfoATbNqJvesxWGw7lmoOxvUzSucD7KFPlrVgDrGZbNVPqtQdZmoDgJpLuGqCJyXU7pGcxjK7vp7zJOltge6W19Wwvl3Qf5b20TrH4KmAsZX2v61tmLWy3Vt0O+TnYng+8TtI2wG6UZ/9Kyvpha1ECczMl7Wf73P6vtLIejum5bUGmJ9VRpnzcQtLYGpgclSRtRpkS8vWUgPxE+taLbHT6DX6bkr14EC1TsUranJL5thw4s+2cCylrEe4u6YJaP9f2/at5GxERERERo0ICcRERERERMdf2dFgRdNoM+CdK5s53JE23/UDL8etSgi5QgiCDWWvwQwpJHwOOp++P/k8AD1AytKAEtMbTOTi3umZTAnG7Slrb9l9r+QzKlIsLKZlzrZosnnF0Dma2m9CDfvbCnf2UPzFIfesxY1rKmucghvgcJF1N58DWCZ3W96uB4RXBYUlbU7LZDqG8h+9KusL2QPfQrldj+o4Bzmnq1qAEMe/urmu9V9d3m1J3F7bV7QV8j773uxxYRN9UlhMpv79Ov8HZwAnAlpJeVaezBDi4bi+1fXvrCbbnSvos8FnK9KVvrv2YD/wU+KbtW1bhNiMiIiIiRoVMTRkRERERESvYXmr7WmBP4CJgK/qm1Gu0/jtia9sa7NNN25JeBvwrJZjzNco6VONsr2t7mu1p9E1t2NU1h+iXwJ8pgb6ZLeXNtJTndpiysHkW53fzHGwfNQz9Hg2a57Coy+cwveXcqZTgXftnYjcN255nexZ9Ux9OoKxHtir9hx6O6VFsE0rQEuCPTWFd2+00ShDubGAbYLztdVp+g02m20rPwPYi4Md196B6zTWB/WvZ6Z06Y/ufgU2BT1H+u/MQ5X8IOAK4SdIBq3abEREREREjL4G4iIiIiIhYSZ1e7yOU7Kc9JO3QUn0/fVlRL+hhs2+n/BvlItsftn2T7Sfajukm22qV1Hv+Ud3dG0DSRGqGDh3W/qIvq6mXz+HpqHkOkyRNHvDINrY37lHQcjbwSP2+6RDP7dWYHmjK1KauyfIcSTNavl/eVj4RuAnYx/ZvOwSfB/sNfrtu96kZtrvUcxYCP+nvJNu32j7O9s6UDMUdKcHxNYGvS3ruIO1GRERERIxKCcRFRERERERHtn9PyYoBOKalfBl9UwPOaD9vNWxUt/M6VUp6NmWdqU6Wtxy3OtlKTbDtDfUP/7tTpiH8MyUo0O6qut1K0vNWo92nu98Aj1OypHYeiQ7YXk5fIK59/bVmfHQcGz0c0zt0UXfDSK4PV4PLs+ru1fV33mh+g9fV59l+roC/H+j6tn8FzKdMv/lW+jIVZ9te2t95bdd4wvZllLUAl1Gmwdymm3MjIiIiIkabBOIiIiIiImIgzRpdr5M0vaX8zLo9UNLLB7qApHW6bGtR3W7ZT/0/Amv3U/dQy/cpXba3EtvzKEGENYE9gH1q1Y9qxly7nwF/oqz79cWBrj2E5/C0U9fT+7e6e7Sk/t4TktaswaCuSdpe0vhBjmkyqQCuaatuxseUAS5xZt2uzpjeWNLe7YWS1qWsPwh9Uzc+5epznw1sDJiyLlur5je4RT8B7fcCL+miqSYr7nBg1/r9O/30aWyn8uox+jIVxw1wXERERETEqJVAXERERERE9KsGpi6tu//UUvUd4NeU9dR+Lum9kiY1lZKmSdpX0lzgsC6bu6Rud5X0KUkT6rWmSvoiZf2o+/vp54PAX+ruQZ2OGYImK+79wBvbytrbXQYcSglq7C3pJ5Je0dRLGiNpG0nHA7euZr9GuyMp0w9uClwpaWdJY6BkUknaRNLhlEDnULObZgELJJ1Qg3JrNRWSNpB0JHBOLfoLfWsJNm6s25kDTJ3ZizG9CDitHrdmPW8ryrpnU4F7gK93d8u9UZ/95pJmAdfTN9XqZ23PaTv8UspY3gI4WdKUeo1Jkj4OnEI/v8E236ME0balrDc3z/Y1/R0r6QxJO7UGcCVtDHyX8j4e4clTaEZEREREPG0kEBcREREREYM5vm7fIOk1sCIAtTtwBSUL6VvAA5Lul7QYuBP4PvB6yh/2B2X7YuC8uvsvwGJJCynrj32MEij5zwEu0WThfEnSYkkL6mdWd7e5QhN025ISRJhfA5L99fsC4N2UwMPuwDxJSyTdTwkgXA18HBjS2mlPN7YXUKal/AslkHMh8LCk+4BHgd8DX6JkVHU1Jloso6wzdgQlIPOwpAckPVrbO5aSLXkHsFvN0Gt1FuX9bA/cJ+mOOjZ+1dL/XozpbwA31OMWS1oEXEsJPC4B9rA93OvDnSfprvpZSHl2NwEnUjLh7gT2tP2F9hNt3wx8pe4eSrn/Byhr2h1PyQA9dbAO2L4XuKCl6PQBDh8PHAjMARbV9/owJXD9TkpG3Ptt3zdYuxERERERo1ECcRERERERMSDbl9C3bttnWsrvoax7tS/wX8C99E0dOZ+SFbMncNwQmnsnJbPqd5QAgiiBkXfZfs8g5x4NfBK4rp73wvqZMoT2sf0H4L9bijpmw7WdcwbwUkoQ40ZK8GASJXvoMuBztf4ZzfbVwGaU93AlsJjy/JdQ1mA7GdjB9twhXnp/4E2UqVIvp2SWPbvW3UnJpjwM2KxT0NT2fEp24xxK1to0ytjYqO241R3TS4HplLF4GzC2XuNHwCttd1pnsNfWoQQt16cEue6lBINPBWYCL7Dd7/SYtg+nTKM5j3I/a9TvsyjTTD7eZT+aoPpS4AcDHHck8AnKu/kj5ZmtAfwBOIPy3M7qss2IiIiIiFFHnZc5iIiIiIiIiIhuSDoTeBfwedtH9fjaCyhBwx1tX9bLaw8nSacB7wHOtr3XMLZzICVgN9f29OFqJyIiIiJiVSUjLiIiIiIiIiJ6pq7D1wTfvjWSfYmIiIiIGGlrjnQHIiIiIiIiImJQv5DUfH9RXZNv1JE0FvgyMBG4zvbPh6GNV9A3XW5ERERExKiWQFxERERERETE6HUvZa23Vk+MREcGIukdlDX81qOs32fgiGFqbhlwd1vZwmFqKyIiIiJitSQQFxERERERETFK2X71SPehSxMpa9ktpWSrHW370uFoyPaNwLThuHZERERERK/J9kj3ISIiIiIiIiIiIiIiIuIZ51kj3YGIiIiIiIiIiIiIiIiIZ6IE4iIiIiIiIiIiIiIiIiKGQQJxEREREREREREREREREcMggbiIiIiIiIiIiIiIiIiIYZBAXERERERERERERERERMQwSCAuIiIiIiIiIiIiIiIiYhj8H2gUcqikOvqpAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tft_vis.display_sample_wise_attention_scores(attention_scores=validation_outputs['attention_scores'],\n",
" observation_index=chosen_idx,\n",
" horizons=[1,5,10],\n",
" unit='Days')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And that's it! \n",
"Enjoy using ``tft_torch``"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 4
}