{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Deep Otello AI\n",
"\n",
"The game reversi is a very good game to apply deep learning methods to.\n",
"\n",
"Othello also known as reversi is a board game first published in 1883 by eiter Lewis Waterman or John W. Mollet in England (each one was denouncing the other as fraud).\n",
"It is a strickt turn based zero-sum game with a clear Markov chain and now hidden states like in card games with an unknown distribution of cards or unknown player allegiance.\n",
"There is like for the game go only one set of stones with two colors which is much easier to abstract than chess with its 6 unique pieces.\n",
"The game has a symmetrical game board wich allows to play with rotating the state around an axis to allow for a breaking of sequences or interesting ANN architectures, quadruple the data generation by simulation or interesting test cases where a symetry in turns should be observable if the AI reaches an \"objective\" policy."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Content\n",
"\n",
"* [The game rules](#the-game-rules) A short overview over the rules of the game.\n",
"* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations.\n",
"* [Initial design decisions](#initial-design-decisions) an explanation about some initial design decision and assumptions\n",
"* [Imports and dependencies](#imports-and-dependencies) explains what libraries where used"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The game rules\n",
"\n",
"Othello is played on a board with 8 x 8 fields for two player.\n",
"The board geometry is equal to a chess game.\n",
"The game is played with game stones that are black on one siede and white on the other.\n",
"\n",
"\n",
"\n",
"The player take turns.\n",
"A player places a stone with his or her color up on the game board.\n",
"The player can only place stones when he surrounds a number of stones with the opponents color with the new stone and already placed stones of his color.\n",
"Those surrounded stones can either be horizontally, vertically and/or diagonally be placed.\n",
"All stones thus surrounded will be flipped to be of the players color.\n",
"Turns are only possible if the player is also changing the color of the opponents stones. If a player can't act he is skipped.\n",
"The game ends if both players can't act. The player with the most stones wins.\n",
"If the score is counted in detail unclaimed fields go to the player with more stones of his or her color on the board.\n",
"The game begins with four stones places in the center of the game. Each player gets two. They are placed diagonally to each other.\n",
"\n",
"\n",
"\n",
"\n",
"## Some common Othello strategies\n",
"\n",
"As can be easily understood the placement of stones and on the bord is always a careful balance of attack and defence.\n",
"If the player occupies huge homogenous stretches on the board it can be attacked easier.\n",
"The boards corners provide safety from wich occupied territory is impossible to loos but since it is only possible to reach the corners if the enemy is forced to allow this or calculates the cost of giving a stable base to the enemy it is difficult to obtain.\n",
"There are some text on otello computer strategies which implement greedy algorithms for reversi based on a modified score to each field.\n",
"Those different values are score modifiers for a traditional greedy algorithm.\n",
"If a players stone has captured such a filed the score reached is multiplied by the modifier.\n",
"The total score is the score reached by the player subtracted with the score of the enemy.\n",
"The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initial design decisions\n",
"\n",
"At the beginning of this project I made some design decisions.\n",
"The first onw was that I do not want to use a gym library because it limits the data formats accessible.\n",
"I choose to implement the hole game as entry in a stack in numpy arrays to be able to accommodate interfacing with a neural network easier and to use scipy pattern recognition tools to implement some game mechanics for a fast simulation cycle.\n",
"I chose to ignore player colors as far as I could instead a player perspective was used. Which allowed to change the perspective with a flipping of the sign. (multiplying with -1).\n",
"The array format should also allow for data multiplication or the breaking of strikt sequences by flipping the game along one the for axis, (horizontal, vertical, transpose along both diagonals).\n",
"\n",
"I wanted to implement different agents as classes that act on those game stacks.\n",
"\n",
"Since computation time is critical all computational have results are saved.\n",
"The analysis of those is then repeated in real time. If a recalculation of such a section is required the save file can be deleted and the code should be executed again."
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The blackcellmagic extension is already loaded. To reload it, use:\n",
" %reload_ext blackcellmagic\n",
"The line_profiler extension is already loaded. To reload it, use:\n",
" %reload_ext line_profiler\n",
"The memory_profiler extension is already loaded. To reload it, use:\n",
" %reload_ext memory_profiler\n"
]
}
],
"source": [
"%load_ext blackcellmagic\n",
"%load_ext line_profiler\n",
"%load_ext memory_profiler"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Imports and dependencies\n",
"\n",
"The following direct dependencies where used for this project:\n",
"```toml\n",
"jupyter = \"^1.0.0\"\n",
"matplotlib = \"^3.6.3\"\n",
"numpy = \"^1.24.1\"\n",
"pytest = \"^7.2.1\"\n",
"python = \"3.10.*\"\n",
"scipy = \"^1.10.0\"\n",
"tqdm = \"^4.64.1\"\n",
"jupyterlab = \"^3.6.1\"\n",
"torchvision = \"^0.14.1\"\n",
"torchaudio = \"^0.13.1\"\n",
"```\n",
"* `Jupyter` and `jupyterlab` on pycharm was used as an IDE / Ipython was used to implement this code.\n",
"* `matplotlib` was used for visualisation and statistics.\n",
"* `numpy` was used for array support and mathematical functions\n",
"* `tqdm` was used for progress bars\n",
"* `scipy` contains fast pattern recognition tools for images. It was used to make an initial estimation about where possible turns should be.\n",
"* `torch` supplied the ANN functionalities."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"import pickle\n",
"import abc\n",
"import itertools\n",
"import os.path\n",
"from abc import ABC\n",
"from enum import Enum\n",
"from typing import Final\n",
"from IPython.display import clear_output, display\n",
"from pathlib import Path\n",
"import glob\n",
"import copy\n",
"from functools import lru_cache, wraps\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"from ipywidgets import interact\n",
"from scipy.ndimage import binary_dilation\n",
"from tqdm.notebook import tqdm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Constants\n",
"\n",
"Some general constants needed to be defined. Such as board game size and Player and Enemy representations. Also, directional offsets and the initial placement of blocks."
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n",
"PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n",
"ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1\n",
"EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples\n",
"IMPOSSIBLE: Final[np.ndarray] = np.array([-1, -1], dtype=int)\n",
"IMPOSSIBLE.setflags(write=False)\n",
"SIMULATE_TURNS: Final[int] = 70\n",
"VERIFY_POLICY: Final[bool] = False\n",
"TRAINING_RESULT_PATH: Final[Path] = Path(\"training_data\")\n",
"if not os.path.exists(TRAINING_RESULT_PATH):\n",
" os.mkdir(TRAINING_RESULT_PATH)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The directions array contains all the numerical offsets needed to move along one of the 8 directions in a 2 dimensional grid. This will allow an iteration over the game board.\n",
"\n",
"![8-directions.png](8-directions.png \"Offset in 8 directions\")"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])"
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"DIRECTIONS: Final[np.ndarray] = np.array(\n",
" [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0],\n",
" dtype=int,\n",
")\n",
"DIRECTIONS.setflags(write=False)\n",
"DIRECTIONS"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another constant needed is the initial start square at the center of the board."
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[-1, 1],\n [ 1, -1]])"
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"START_SQUARE: Final[np.ndarray] = np.array(\n",
" [[ENEMY, PLAYER], [PLAYER, ENEMY]], dtype=int\n",
")\n",
"START_SQUARE.setflags(write=False)\n",
"START_SQUARE"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating new boards\n",
"\n",
"The first function implemented and tested is a function to generate the starting environment as a stack of games.\n",
"As described above I simply placed a 2 by 2 square in the center of an empty stack of boards."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])"
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def get_new_games(number_of_games: int) -> np.ndarray:\n",
" \"\"\"Generates a stack of initialised game boards.\n",
"\n",
" Args:\n",
" number_of_games: The size of the board stack.\n",
"\n",
" Returns: The generates stack of games as a stack n x 8 x 8.\n",
"\n",
" \"\"\"\n",
" empty = np.zeros([number_of_games, BOARD_SIZE, BOARD_SIZE], dtype=int)\n",
" empty[:, 3:5, 3:5] = START_SQUARE\n",
" return empty\n",
"\n",
"\n",
"get_new_games(1)[0]"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"test_number_of_games = 3\n",
"assert get_new_games(test_number_of_games).shape == (\n",
" test_number_of_games,\n",
" BOARD_SIZE,\n",
" BOARD_SIZE,\n",
")\n",
"np.testing.assert_equal(\n",
" get_new_games(test_number_of_games).sum(axis=1),\n",
" np.zeros(\n",
" [\n",
" test_number_of_games,\n",
" 8,\n",
" ]\n",
" ),\n",
")\n",
"np.testing.assert_equal(\n",
" get_new_games(test_number_of_games).sum(axis=2),\n",
" np.zeros(\n",
" [\n",
" test_number_of_games,\n",
" 8,\n",
" ]\n",
" ),\n",
")\n",
"assert np.all(get_new_games(test_number_of_games)[:, 3:4, 3:4] != 0)\n",
"del test_number_of_games"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Visualisation tools\n",
"\n",
"In this section a visualisation help was implemented for debugging of the game and a proper display of the results.\n",
"For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole.\n",
"White stones represent the player, black stones the enemy. A single plot can be used as a subplot when the `ax` argument is used."
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
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\n"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def plot_othello_board(\n",
" board: np.ndarray | torch.Tensor,\n",
" action: np.ndarray | None = None,\n",
" score: float | None = None,\n",
" ax=None,\n",
") -> None:\n",
" \"\"\"Plots a single otello board.\n",
"\n",
" If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n",
" The image generated will be shown directly.\n",
"\n",
" Args:\n",
" board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n",
" action: The action taken on each board.\n",
" score: The score reached with the turn.\n",
" ax: If needed a matplotlib axis object can be defined that is used to place the board as a sublot into a bigger context.\n",
" \"\"\"\n",
" # convert a tensor into an array\n",
" if isinstance(board, torch.Tensor):\n",
" board = board.cpu().detach().numpy()\n",
"\n",
" # ensure the shape of the array fits\n",
" assert board.shape == (8, 8)\n",
" plot_all = False\n",
"\n",
" # create a figure if no axis is given\n",
" if ax is None:\n",
" fig_size = 3\n",
" plot_all = True\n",
" fig, ax = plt.subplots(figsize=(fig_size, fig_size))\n",
"\n",
" # set the background color\n",
" ax.set_facecolor(\"#0f6b28\")\n",
"\n",
" # plot the actions\n",
" if action is not None:\n",
" ax.scatter(action[0], action[1], s=350 if plot_all else 200, c=\"red\")\n",
"\n",
" # plot black and white stones\n",
" for x_pos, y_pos in itertools.product(range(BOARD_SIZE), range(BOARD_SIZE)):\n",
" if board[x_pos, y_pos] == ENEMY:\n",
" color = \"white\"\n",
" elif board[x_pos, y_pos] == PLAYER:\n",
" color = \"black\"\n",
" else:\n",
" continue\n",
" ax.scatter(x_pos, y_pos, s=280 if plot_all else 140, c=color)\n",
"\n",
" # plot the lines separating the fields\n",
" for x_pos in range(-1, 8):\n",
" ax.axhline(x_pos + 0.5, color=\"black\", lw=2)\n",
" ax.axvline(x_pos + 0.5, color=\"black\", lw=2)\n",
"\n",
" # define the size of the plot\n",
" ax.set_xlim(-0.5, 7.5)\n",
" ax.set_ylim(7.5, -0.5)\n",
"\n",
" # set the axis labels\n",
" ax.set_xticks(np.arange(8))\n",
" ax.set_xticklabels(list(\"ABCDEFGH\"))\n",
" ax.set_yticks(np.arange(8))\n",
" ax.set_yticklabels(list(\"12345678\"))\n",
"\n",
" # overrides the x_label text if a score should be plotted\n",
" if score is None:\n",
" ax.set_xlabel(\n",
" f\"W{np.sum(board == ENEMY)} / {np.sum(board == 0)} / B{np.sum(board == PLAYER)}\"\n",
" )\n",
" else:\n",
" ax.set_xlabel(f\"Score: {score}\")\n",
" if plot_all:\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
"\n",
"plot_othello_board(get_new_games(1)[0], action=np.array([3, 3]))"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
"PLOTS_PER_ROW = 4\n",
"\n",
"\n",
"def plot_othello_boards(\n",
" boards: np.ndarray,\n",
" actions: np.ndarray | None = None,\n",
" scores: np.ndarray | None = None,\n",
") -> None:\n",
" \"\"\"Plots multiple boards into subplots.\n",
"\n",
" The plots are shown directly.\n",
"\n",
" Args:\n",
" boards: Plots the boards given into subplots. The maximum number of boards accepted is 70.\n",
" actions: A list of actions taken on each of the boards.\n",
" scores: A list of scores reached at each board.\n",
" \"\"\"\n",
" # checking if the array input shapes do fit\n",
" assert len(boards.shape) == 3\n",
" assert boards.shape[1:] == (BOARD_SIZE, BOARD_SIZE)\n",
" assert boards.shape[0] < 70\n",
"\n",
" if actions is not None:\n",
" assert len(actions.shape) == 2\n",
" assert actions.shape[1] == 2\n",
" assert boards.shape[0] == actions.shape[0]\n",
"\n",
" if scores is not None:\n",
" assert len(scores.shape) == 1\n",
" assert boards.shape[0] == scores.shape[0]\n",
"\n",
" # plots the boards\n",
" rows = int(np.ceil(boards.shape[0] / PLOTS_PER_ROW))\n",
" fig, axs = plt.subplots(rows, PLOTS_PER_ROW, figsize=(12, 3 * rows))\n",
" for game_index, ax in enumerate(axs.flatten()):\n",
" if game_index >= boards.shape[0]:\n",
" fig.delaxes(ax)\n",
" else:\n",
" action = actions[game_index] if actions is not None else None\n",
" score = scores[game_index] if scores is not None else None\n",
" plot_othello_board(boards[game_index], action=action, score=score, ax=ax)\n",
" plt.tight_layout()\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [],
"source": [
"def drop_duplicate_boards(\n",
" boards: np.ndarray,\n",
" actions: np.ndarray | None,\n",
") -> tuple[np.ndarray, np.ndarray | None]:\n",
" \"\"\"Takes a sequence of boards and drops all boards that are unchanged.\n",
"\n",
" Args:\n",
" boards: A list of boards to be reduced.\n",
" actions: A list of actions to be reduced alongside the bords.\n",
"\n",
" Returns:\n",
" A sequence of boards where boards that where equal are dropped.\n",
" \"\"\"\n",
" non_duplicates = ~np.all(boards == np.roll(boards, axis=0, shift=1), axis=(1, 2))\n",
" return (\n",
" boards[non_duplicates],\n",
" np.roll(actions, axis=0, shift=1)[non_duplicates]\n",
" if actions is not None\n",
" else None,\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Hash Otello Boards\n",
"\n",
"A challenge for training any reinforcement learning algorithm is how to properly calibrate the exploration rate."
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"def hash_board(board: np.ndarray) -> int:\n",
" assert board.shape == (8, 8) or board.shape == (64,)\n",
" return hash(tuple(board.reshape(-1)))\n",
"\n",
"\n",
"def count_unique_boards(boards: np.ndarray) -> int:\n",
" return np.unique(\n",
" np.apply_along_axis(hash_board, axis=1, arr=boards.reshape(-1, 64))\n",
" ).size\n",
"\n",
"\n",
"a = count_unique_boards(np.random.randint(-1, 2, size=(10000, 8, 8)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Find possible actions to take\n",
"\n",
"The frist step in the implementation of an AI like this is to get an overview over the possible actions that can be taken in a situation.\n",
"Here was the design choice taken to first find fields that are empty and have at least one neighbouring enemy stone.\n",
"This was implemented with element wise check for a stone and a binary dilation marking all fields neighboring an enemy stone.\n",
"For that the `SURROUNDING` mask was used. Both aries are then element wise combined using and.\n",
"The resulting array contains all filed where a turn could potentially be made. Those are then check in detail.\n",
"The previous element wise operations on the numpy array increase the spead for this operation dramatically.\n",
"\n",
"The check for a possible turn is done in detail by following each direction step by step as long as there are enemy stones in that direction.\n",
"If the board end is reached or en empty filed before reaching a field occupied by the player that direction does not surround enemy stones.\n",
"If one direction surrounds enemy stone a turn is possible.\n",
"This detailed step is implemented as a recursion and need to go at leas one step to return True."
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": "array([[[1, 1, 1],\n [1, 0, 1],\n [1, 1, 1]]])"
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SURROUNDING: Final = np.array(\n",
" [[[1, 1, 1], [1, 0, 1], [1, 1, 1]]]\n",
") # defines the binary dilation mask to check if a field is next to an enemy stones\n",
"SURROUNDING"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Source https://gist.github.com/Susensio/61f4fee01150caaac1e10fc5f005eb75\n",
"def np_cache(*lru_args, array_argument_indexs=(0,), **lru_kwargs):\n",
" \"\"\"\n",
" LRU cache implementation for functions whose parameter at ``array_argument_index`` is a numpy array of dimensions <= 2\n",
"\n",
" Example:\n",
" >>> from sem_env.utils.cache import np_cache\n",
" >>> array = np.array([[1, 2, 3], [4, 5, 6]])\n",
" >>> @np_cache(maxsize=256)\n",
" ... def multiply(array, factor):\n",
" ... return factor * array\n",
" >>> multiply(array, 2)\n",
" >>> multiply(array, 2)\n",
" >>> multiply.cache_info()\n",
" CacheInfo(hits=1, misses=1, maxsize=256, currsize=1)\n",
" \"\"\"\n",
"\n",
" def decorator(function):\n",
" @wraps(function)\n",
" def wrapper(*args, **kwargs):\n",
" args = list(args)\n",
" for array_argument_index in array_argument_indexs:\n",
" np_array = args[array_argument_index]\n",
" if len(np_array.shape) > 2:\n",
" raise RuntimeError(\n",
" f\"np_cache is currently only supported for arrays of dim. less than 3 but got shape: {np_array.shape}\"\n",
" )\n",
" hashable_array = tuple(np_array.reshape(-1))\n",
"\n",
" args[array_argument_index] = hashable_array\n",
" return cached_wrapper(*args, **kwargs)\n",
"\n",
" @lru_cache(*lru_args, **lru_kwargs)\n",
" def cached_wrapper(*args, **kwargs):\n",
" args = list(args)\n",
" for array_argument_index in array_argument_indexs:\n",
" hashable_array = args[array_argument_index]\n",
" array = np.array(hashable_array).reshape(8, 8)\n",
" args[array_argument_index] = array\n",
" return function(*args, **kwargs)\n",
"\n",
" # copy lru_cache attributes over too\n",
" wrapper.cache_info = cached_wrapper.cache_info\n",
" wrapper.cache_clear = cached_wrapper.cache_clear\n",
" return wrapper\n",
"\n",
" return decorator"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"201 µs ± 15.8 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
]
},
{
"data": {
"text/plain": "array([[[False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, True, False, False, False, False],\n [False, False, True, False, False, False, False, False],\n [False, False, False, False, False, True, False, False],\n [False, False, False, False, True, False, False, False],\n [False, False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False, False]]])"
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def _recursive_steps(\n",
" board: np.ndarray,\n",
" rec_direction: np.ndarray,\n",
" rec_position: np.ndarray,\n",
" step_one: int = 0,\n",
") -> int:\n",
" \"\"\"Check if a player can place a stone on the board specified in the direction specified and direction specified.\n",
"\n",
" Args:\n",
" board: The board that should be checked for a playable action.\n",
" rec_direction: The direction that should be checked.\n",
" rec_position: The position that should be checked.\n",
" step_one: Defines if the call of this function is the firs or not. Should be kept to the default value for proper functionality.\n",
"\n",
" Returns:\n",
" True if a turn is possible for possition and direction on the board defined.\n",
" \"\"\"\n",
" rec_position = rec_position + rec_direction\n",
" if np.any((rec_position >= BOARD_SIZE) | (rec_position < 0)):\n",
" return 0\n",
" next_field = board[tuple(rec_position.tolist())]\n",
" if next_field == 0:\n",
" return 0\n",
" if next_field == -1:\n",
" return _recursive_steps(\n",
" board, rec_direction, rec_position, step_one=step_one + 1\n",
" )\n",
" if next_field == 1:\n",
" return step_one\n",
"\n",
"\n",
"@np_cache(maxsize=2000, array_argument_indexs=(0, 1))\n",
"def _get_possible_turns_for_board(board: np.ndarray, poss_turns: np.ndarray):\n",
" for idx, idy in itertools.product(range(BOARD_SIZE), range(BOARD_SIZE)):\n",
" # insear a cach step here\n",
" if poss_turns[idx, idy]:\n",
" position = idx, idy\n",
" poss_turns[idx, idy] = any(\n",
" _recursive_steps(board[:, :], direction, position) > 0\n",
" for direction in DIRECTIONS\n",
" )\n",
" return poss_turns\n",
"\n",
"\n",
"def get_possible_turns(boards: np.ndarray, tqdm_on: bool = False) -> np.ndarray:\n",
" \"\"\"Analyses a stack of boards.\n",
"\n",
" Args:\n",
" boards: A stack of boards to check.\n",
" tqdm_on: Uses tqdm to track the progress.\n",
"\n",
" Returns:\n",
" A stack of game boards containing boolean values showing where turns are possible for the player.\n",
" \"\"\"\n",
" assert len(boards.shape) == 3, \"The number fo input dimensions does not fit.\"\n",
" assert boards.shape[1:] == (\n",
" BOARD_SIZE,\n",
" BOARD_SIZE,\n",
" ), \"The input dimensions do not fit.\"\n",
"\n",
" poss_turns = boards == 0 # checks where fields are empty.\n",
" poss_turns &= binary_dilation(\n",
" boards == -1, SURROUNDING\n",
" ) # checks where fields are next to an enemy filed an empty\n",
" iterate_over = range(boards.shape[0])\n",
"\n",
" if tqdm_on:\n",
" iterate_over = tqdm(iterate_over, total=np.prod(boards.shape))\n",
" for game in iterate_over:\n",
" # insear a cach step here\n",
" poss_turns[game] = _get_possible_turns_for_board(boards[game], poss_turns[game])\n",
" return poss_turns\n",
"\n",
"\n",
"# some simple testing to ensure the function works after simple changes\n",
"# this testing is complete, its more of a smoke-test\n",
"test_array = get_new_games(3)\n",
"expected_result = np.zeros_like(test_array, dtype=bool)\n",
"expected_result[:, 4, 5] = expected_result[:, 2, 3] = True\n",
"expected_result[:, 5, 4] = expected_result[:, 3, 2] = True\n",
"np.testing.assert_equal(get_possible_turns(test_array), expected_result)\n",
"\n",
"\n",
"# with cach 6.56 ms\n",
"%timeit get_possible_turns(get_new_games(10)) # checks turn possibility evaluation time for 10 initial games\n",
"# %timeit get_possible_turns(get_new_games(EXAMPLE_STACK_SIZE)) # check turn possibility evaluation time for EXAMPLE_STACK_SIZE initial games\n",
"\n",
"# shows a singe game\n",
"get_possible_turns(get_new_games(3))[:1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Besides the ability to generate an array of possible turns there needs to be a functions that check if a given turn is possible.\n",
"On is needed for the action space validation. The other is for validating a players turn."
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"def move_possible(board: np.ndarray, move: np.ndarray) -> bool:\n",
" \"\"\"Checks if a turn is possible.\n",
"\n",
" Checks if a turn is possible. If no turn is possible to input array [-1, -1] is expected.\n",
"\n",
" Args:\n",
" board: A board where it should be checkt if a turn is possible.\n",
" move: The move that should be taken. Expected is the index of the filed where a stone should be placed [x, y]. If no placement is possible [-1, -1] is expected as an input.\n",
"\n",
" Returns:\n",
" True if the move is possible\n",
" \"\"\"\n",
" if np.all(move == -1):\n",
" return not np.any(get_possible_turns(np.reshape(board, (1, 8, 8))))\n",
" return any(\n",
" _recursive_steps(board[:, :], direction, move) > 0 for direction in DIRECTIONS\n",
" )\n",
"\n",
"\n",
"# Some testing for this function and the underlying recursive functions that are called.\n",
"assert move_possible(get_new_games(1)[0], np.array([2, 3])) is True\n",
"assert move_possible(get_new_games(1)[0], np.array([3, 2])) is True\n",
"assert move_possible(get_new_games(1)[0], np.array([2, 2])) is False\n",
"assert move_possible(np.zeros((8, 8)), np.array([3, 2])) is False\n",
"assert move_possible(np.ones((8, 8)) * 1, np.array([-1, -1])) is True\n",
"assert move_possible(np.ones((8, 8)) * -1, np.array([-1, -1])) is True\n",
"assert move_possible(np.ones((8, 8)) * 0, np.array([-1, -1])) is True"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"def moves_possible(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n",
" \"\"\"Checks if a stack of moves can be executed on a stack of boards.\n",
"\n",
" Args:\n",
" boards: A board where the next stone should be placed.\n",
" moves: A stack stones to be placed. Each move is formatted as an array in the form of [x, y] if no turn is possible the value [-1, -1] is expected.\n",
"\n",
" Returns:\n",
" An array marking for each and every game and move in the stack if the move can be executed.\n",
" \"\"\"\n",
" arr_moves_possible = np.zeros(boards.shape[0], dtype=bool)\n",
" for game in range(boards.shape[0]):\n",
" if np.all(\n",
" moves[game] == -1\n",
" ): # can be all or any. All should be faster since most times neither value will be -1.\n",
" arr_moves_possible[game] = not np.any(\n",
" get_possible_turns(np.reshape(boards[game], (1, 8, 8)))\n",
" )\n",
" else:\n",
" arr_moves_possible[game] = any(\n",
" _recursive_steps(boards[game, :, :], direction, moves[game]) > 0\n",
" for direction in DIRECTIONS\n",
" )\n",
" return arr_moves_possible\n",
"\n",
"\n",
"np.testing.assert_array_equal(\n",
" moves_possible(np.ones((3, 8, 8)) * 1, np.array([[-1, -1]] * 3)),\n",
" np.array([True] * 3),\n",
")\n",
"\n",
"np.testing.assert_array_equal(\n",
" moves_possible(get_new_games(3), np.array([[2, 3], [3, 2], [3, 2]])),\n",
" np.array([True] * 3),\n",
")\n",
"np.testing.assert_array_equal(\n",
" moves_possible(get_new_games(3), np.array([[2, 2], [1, 1], [0, 0]])),\n",
" np.array([False] * 3),\n",
")\n",
"np.testing.assert_array_equal(\n",
" moves_possible(np.ones((3, 8, 8)) * -1, np.array([[-1, -1]] * 3)),\n",
" np.array([True] * 3),\n",
")\n",
"np.testing.assert_array_equal(\n",
" moves_possible(np.zeros((3, 8, 8)), np.array([[-1, -1]] * 3)),\n",
" np.array([True] * 3),\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reword functions\n",
"\n",
"For any kind of reinforcement learning is a reword function needed.\n",
"For otello this would be the final score, the information who won or changes to the score.\n",
"A combination of those three would also be possible.\n",
"It is probably not be possible to weight the current score to high in a reword function since that would be to close to a classic greedy algorithm.\n",
"But some direct influence would increase the learning speed.\n",
"In the next section are all three reword functions implemented to be combined and weight later on as needed."
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"223 µs ± 13.6 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n",
"40.2 µs ± 1.93 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n",
"40.5 µs ± 1.39 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n"
]
}
],
"source": [
"def final_boards_evaluation(boards: np.ndarray) -> np.ndarray:\n",
" \"\"\"Evaluates the board at the end of the game.\n",
"\n",
" All unused fields are added to the score of the player that has more stones with his color up.\n",
" This score only applies to the end of the game.\n",
" Normally the score is represented by the number of stones each player has.\n",
" In this case the score was combined by building the difference.\n",
"\n",
" Args:\n",
" boards: A stack of game bords ot the end of the game.\n",
"\n",
" Returns:\n",
" the combined score for both player.\n",
" \"\"\"\n",
" score1, score2 = np.sum(boards == 1, axis=(1, 2)), np.sum(boards == -1, axis=(1, 2))\n",
" player_1_won = score1 > score2\n",
" player_2_won = score1 < score2\n",
" score1_final = 64 - score2[player_1_won]\n",
" score2_final = 64 - score1[player_2_won]\n",
" score = np.zeros(boards.shape[0])\n",
" score[player_1_won] = score1_final\n",
" score[player_2_won] = -score2_final\n",
" return score\n",
"\n",
"\n",
"def evaluate_boards(boards: np.ndarray) -> np.ndarray:\n",
" \"\"\"Counts the stones each player has on the board.\n",
"\n",
" Args:\n",
" boards: A stack of boards for evaluation.\n",
"\n",
" Returns:\n",
" the combined score for both player.\n",
" \"\"\"\n",
" return np.sum(boards, axis=(1, 2))\n",
"\n",
"\n",
"def evaluate_who_won(boards: np.ndarray) -> np.ndarray:\n",
" \"\"\"Checks who won or is winning a game.\n",
"\n",
" Args:\n",
" boards: A stack of boards for evaluation.\n",
"\n",
" Returns:\n",
" The information who won for both player. 1 meaning the player won, -1 means the opponent lost. 0 represents a patt.\n",
" \"\"\"\n",
" assert boards.shape[1:] == (8, 8)\n",
" return np.sign(np.sum(boards, axis=(1, 2)))\n",
"\n",
"\n",
"_boards = get_new_games(EXAMPLE_STACK_SIZE)\n",
"%timeit final_boards_evaluation(_boards)\n",
"%timeit evaluate_boards(_boards)\n",
"%timeit evaluate_who_won(_boards)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Execute a chosen action\n",
"\n",
"After an evaluation what turns are possible there needs to be a function that executes a turn.\n",
"This next sections does that."
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"class InvalidTurn(ValueError):\n",
" \"\"\"\n",
" This error is thrown if a given turn is not valid.\n",
" \"\"\""
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"111 ms ± 2.78 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
},
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def do_moves(boards: np.ndarray, moves: np.ndarray) -> np.ndarray:\n",
" \"\"\"Executes a single move on a stack o Othello boards.\n",
"\n",
" Args:\n",
" boards: A stack of Othello boards where the next stone should be placed.\n",
" moves: A stack of stone placement orders for the game. Formatted as coordinates in an array [x, y] of the place where the stone should be placed. Should contain [-1,-1] if no new placement is possible.\n",
"\n",
" Returns:\n",
" The new state of the board.\n",
" \"\"\"\n",
"\n",
" def _do_directional_move(\n",
" board: np.ndarray, rec_move: np.ndarray, rev_direction, step_one=True\n",
" ) -> bool:\n",
" \"\"\"Changes the color of enemy stones in one direction.\n",
"\n",
" This function works recursive. The argument step_one should always be used in its default value.\n",
"\n",
" Args:\n",
" board: A bord on which a stone was placed.\n",
" rec_move: The position on the board in x and y where this function is called from. Will be moved by recursive called.\n",
" rev_direction: The position where the stone was placed. Inside this recursion it will also be the last step that was checked.\n",
" step_one: Set to true if this is the first step in the recursion. False later on.\n",
"\n",
" Returns:\n",
" True if a stone could be flipped.\n",
" All changes are made on the view of the numpy array and therefore not included in the return value.\n",
" \"\"\"\n",
" rec_position = rec_move + rev_direction\n",
" if np.any((rec_position >= 8) | (rec_position < 0)):\n",
" return False\n",
" next_field = board[tuple(rec_position.tolist())]\n",
" if next_field == 0:\n",
" return False\n",
" if next_field == 1:\n",
" return not step_one\n",
" if next_field == -1:\n",
" if _do_directional_move(board, rec_position, rev_direction, step_one=False):\n",
" board[tuple(rec_position.tolist())] = 1\n",
" return True\n",
" return False\n",
"\n",
" def _do_move(_board: np.ndarray, move: np.ndarray) -> None:\n",
" \"\"\"Executes a turn on a board.\n",
"\n",
" Args:\n",
" _board: The game board on wich to place a stone.\n",
" move: The coordinates of a stone that should be placed. Should be formatted as an array of the form [x, y]. The value [-1, -1] is expected if no turn is possible.\n",
"\n",
" Returns:\n",
" All changes are made on the view of the numpy array.\n",
" \"\"\"\n",
" if np.all(move == -1):\n",
" if not move_possible(_board, move):\n",
" raise InvalidTurn(\"An action should be taken. A turn is possible.\")\n",
" return\n",
"\n",
" # noinspection PyTypeChecker\n",
" if _board[tuple(move.tolist())] != 0:\n",
" raise InvalidTurn(\"This turn is not possible.\")\n",
"\n",
" action = False\n",
" for direction in DIRECTIONS:\n",
" if _do_directional_move(_board, move, direction):\n",
" action = True\n",
" if not action:\n",
" raise InvalidTurn(\"This turn is not possible.\")\n",
"\n",
" # noinspection PyTypeChecker\n",
" _board[tuple(move.tolist())] = 1\n",
"\n",
" boards = boards.copy()\n",
" for game in range(boards.shape[0]):\n",
" _do_move(boards[game], moves[game])\n",
" return boards\n",
"\n",
"\n",
"%timeit do_moves(get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE))[0]\n",
"\n",
"plot_othello_board(\n",
" do_moves(\n",
" get_new_games(EXAMPLE_STACK_SIZE), np.array([[2, 3]] * EXAMPLE_STACK_SIZE)\n",
" )[0],\n",
" action=np.array([2, 3]),\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## An abstract reversi game policy\n",
"\n",
"For an easy use of policies an abstract class containing the policy generation / requests an action in an inherited instance of this class.\n",
"This class filters the policy to only propose valid actions. Inherited instance do not need to care about this. This super class also manges exploration and exploitation with the epsilon value."
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [],
"source": [
"class GamePolicy(ABC):\n",
" \"\"\"\n",
" A game policy. Proposes where to place a stone next.\n",
" \"\"\"\n",
"\n",
" def __init__(self, epsilon: float):\n",
" \"\"\"\n",
"\n",
" Args:\n",
" epsilon: the epsilon / greedy value. Should be between zero and one. Set the mixture of policy and exploration. One means only the policy is used. Zero means only random policies are used. All mixtures inbetween between are possible.\n",
" \"\"\"\n",
" if 0 > epsilon > 1:\n",
" raise ValueError(\"Epsilon should be between zero and one.\")\n",
" self._epsilon: float = epsilon\n",
"\n",
" @property\n",
" def epsilon(self):\n",
" return self._epsilon\n",
"\n",
" @property\n",
" @abc.abstractmethod\n",
" def policy_name(self) -> str:\n",
" \"\"\"The name of this policy\"\"\"\n",
" raise NotImplementedError()\n",
"\n",
" @abc.abstractmethod\n",
" def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n",
" \"\"\"The internal policy is an unfiltered policy. It should only be called from inside this function\n",
"\n",
" Args:\n",
" boards: A board where a policy should be calculated for.\n",
"\n",
" Returns:\n",
" The policy for this board. Should have the same size as the boards array.\n",
" \"\"\"\n",
" raise NotImplementedError()\n",
"\n",
" def get_policy(self, boards: np.ndarray) -> np.ndarray:\n",
" \"\"\"Calculates the policy that should be followed.\n",
"\n",
" Calculates the policy that should be followed.\n",
" This function does include the usage of epsilon to configure greediness and exploration.\n",
"\n",
" Args:\n",
" boards: A set of boards that show the environment where the policy should be calculated for.\n",
"\n",
" Returns:\n",
" A vector of indices. Should be formatted as an array of the form [x, y]. The value [-1, -1] is expected if no turn is possible.\n",
" \"\"\"\n",
" assert len(boards.shape) == 3\n",
" assert boards.shape[1:] == (BOARD_SIZE, BOARD_SIZE)\n",
"\n",
" if self.epsilon <= 0:\n",
" policies = np.random.rand(*boards.shape)\n",
" else:\n",
" policies = self._internal_policy(boards)\n",
" if self.epsilon < 1:\n",
" random_choices = self.epsilon <= np.random.rand((boards.shape[0]))\n",
" policies[random_choices] = np.random.rand(np.sum(random_choices), 8, 8)\n",
"\n",
" # todo talk to team about backpropagation of score and epsilon for greedy factor\n",
"\n",
" # todo possibly change this function to only validate the purpose turn and not all turns\n",
" possible_turns = get_possible_turns(boards)\n",
" policies[possible_turns == False] = -1.0\n",
" max_indices = [\n",
" np.unravel_index(policy.argmax(), policy.shape) for policy in policies\n",
" ]\n",
" policy_vector = np.array(max_indices, dtype=int)\n",
" no_turn_possible = np.all(policy_vector == 0, 1) & (policies[:, 0, 0] == -1.0)\n",
"\n",
" policy_vector[no_turn_possible, :] = IMPOSSIBLE\n",
" return policy_vector"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A first policy\n",
"\n",
"To quantify the quality of a game AI there needs to be some benchmarks.\n",
"The easiest benchmark is to play against a random player.\n",
"The easiest player to use as a benchmark is the random player.\n",
"For this and testing purpose the random policy was implemented."
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [],
"source": [
"class RandomPolicy(GamePolicy):\n",
" \"\"\"\n",
" A policy playing a random turn by setting epsilon to 0.\n",
" \"\"\"\n",
"\n",
" def __init__(self, epsilon: float = 0):\n",
" _ = epsilon\n",
" super().__init__(epsilon=0)\n",
"\n",
" @property\n",
" def policy_name(self) -> str:\n",
" return \"random\"\n",
"\n",
" def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n",
" pass\n",
"\n",
"\n",
"rnd_policy = RandomPolicy(1)\n",
"assert rnd_policy.policy_name == \"random\"\n",
"assert rnd_policy.epsilon == 0\n",
"\n",
"rnd_policy_result = rnd_policy.get_policy(get_new_games(10))\n",
"assert np.any((5 >= rnd_policy_result) & (rnd_policy_result >= 3))"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"class GreedyPolicy(GamePolicy):\n",
" \"\"\"\n",
" A policy playing always one of the strongest turns.\n",
" \"\"\"\n",
"\n",
" def __init__(self, epsilon: float = 1):\n",
" _ = epsilon\n",
" super().__init__(1)\n",
"\n",
" @property\n",
" def policy_name(self) -> str:\n",
" return \"greedy_policy\"\n",
"\n",
" def _internal_policy(self, boards: np.ndarray) -> np.ndarray:\n",
" policies = np.random.rand(*boards.shape)\n",
" poss_turns = boards == 0 # checks where fields are empty.\n",
" poss_turns &= binary_dilation(boards == -1, SURROUNDING)\n",
" for game, idx, idy in itertools.product(\n",
" range(boards.shape[0]), range(BOARD_SIZE), range(BOARD_SIZE)\n",
" ):\n",
"\n",
" if poss_turns[game, idx, idy]:\n",
" position = idx, idy\n",
" policies[game, idx, idy] += np.sum(\n",
" np.array(\n",
" list(\n",
" _recursive_steps(boards[game, :, :], direction, position)\n",
" for direction in DIRECTIONS\n",
" )\n",
" )\n",
" )\n",
" return policies"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Putting the game simulation together\n",
"Now it's time to bring all together for a proper simulation."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Playing a single turn\n",
"\n",
"The next function needed is used to request a policy, verify that the turn is legit and place a stone and turn enemy stones if possible."
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [],
"source": [
"def single_turn(\n",
" current_boards: np, policy: GamePolicy\n",
") -> tuple[np.ndarray, np.ndarray]:\n",
" \"\"\"Execute a single turn on a board.\n",
"\n",
" Places a new stone on the board. Turns captured enemy stones.\n",
"\n",
" Args:\n",
" current_boards: The current board before the game.\n",
" policy: The game policy to be used.\n",
"\n",
" Returns:\n",
" The new game board and the policy vector containing the index of the action used.\n",
" \"\"\"\n",
" policy_results = policy.get_policy(current_boards)\n",
"\n",
" # if the constant VERIFY_POLICY is set to true the policy is verified. Should be good though.\n",
" # todo deactivate the policy verification after some testing.\n",
" if VERIFY_POLICY:\n",
" assert np.all(moves_possible(current_boards, policy_results)), (\n",
" current_boards[(moves_possible(current_boards, policy_results) == False)],\n",
" policy_results[(moves_possible(current_boards, policy_results) == False)],\n",
" np.where(moves_possible(current_boards, policy_results) == False),\n",
" )\n",
" return do_moves(current_boards, policy_results), policy_results"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"%timeit single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))\n",
"VERIFY_POLICY = False # type: ignore\n",
"%timeit single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))\n",
"VERIFY_POLICY = True # type: ignore\n",
"_turn_result = single_turn(get_new_games(EXAMPLE_STACK_SIZE), RandomPolicy(1))\n",
"plot_othello_boards(_turn_result[0][:8], _turn_result[1][:8])\n",
"del _turn_result"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simulate a stack of games\n",
"This function will simulate a stack of games and return an array of policies and histories."
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
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lIzbk8/lQVlaG/Kvz0Sy7Va1DkiSkJaaitrkOamLLzV5ABiABUqK6Ty4yAzMwQ+QzJEp2lP6jFLm5uTCbzaoyaKW1o7TuA0D7a8EMzMAM+mSIdkexn5iBGZghlFjvJ6BnHMsyAzMwQzCl/WT8PaVkQD7jVbsoTjadZAZmYIaeliHJrn7ZSFO5HyL2OjADMzCDeBlE6ah4fx2YgRmYIViM99N3i8b+sSwzMAMzBFPYT8ZPSkmAlBS/s4XMwAzM0NUKVG1WHyo7qqf8xpUZmIEZulqJusUijv3EDMzADEErUbdYxPEcjxmYgRmCVqDsaYZPSkkOM1KmDlG1bKLVgfdmrsTEVbNUfUNFwyt7IZ/xQkq0IOUOZmAGZhAlg29ttart6kFtR2ndB4D214IZmIEZ9MkgSkexn5iBGZjhbLHeT0DPOJZlBmZghmBK+4k3OiciIiIiIiIiIsNxUoqIiIiIiIiIxOD3RzsBGcj4e0oREREREREREQEYXdOCGTvrcUW1C1l1rbA9OxYHTRJ2pdqwOdOB17OdKE9PiHZM0gknpYhimK+mBa4GF0pKSuCqPAVfigQzC5uIBMB+IiJR5fTPxsjMLKSlpWFS3jjsqN6FiiM7ox2LKO5cUN+KpZuO4cpjLngkYIcMFANoBJDslzH8WzfuPOVG0fZ6fNbXgTkFfXHAaYt2bN3FW0dxUoooxshePzx7GuCuqIO/1g0AWPjBwvafm9LssOekwjo0BZKFn9AlIuOwn4hIVAlWOyaPmYCi/JkYPeDi9seX374IAFB++BusKF2F4q0b0OJxRysmUdyYsvs0lm06jlafjJcBPCcDZV08L1cG5gGYcsyFz988gNkFfVE8LMXYsAaI547ipBRRDPHVt+LMu4cgN3pDPsdf64Zr03G0fFmLpJsGwhwHv00gouhjPxGRqC7KGIy3H3gBA3pnwi93fa+akf2ysHTGk/jN+Acwaend2F9TZXBKovgxZfdprPj4GHYDuAFAFULf7LoCwF0AHgPwoU/Gyo+rIUHGumHnGZRWf/HeUfw1JVGM8NW3omndQchNoU/4OpKbvGhadxC++ladkxFRvGM/EZGoLsoYjL/NfxOZzj6QJAlmk7nL55lNZkiShExnH/z9wTW4MH2QwUmJ4sOF9a1Ytuk4dgP4EYAj3z0e6tbmbY8fAXAFgD0Alm06jgt6yDEEOyrMSakTJ05g3rx5GDt2LK666iosWrQIbnfPunSMSESy148z7x4CWv2ArHQhAK2B5WRvfHyDBTuKyHjsJ2XYT0TGS7Da8fYDLyDZngSLWdkHRCxmC5LtSVg/50UkWO06JxQD+4mMtGTTMbh9Mm4A0ADAp3A533fPHweg1Sdj6aZjekU0DDsqQPGklCzLmDdvHlwuF15//XX86U9/wv/+7//i2Wef1TEeEQGAZ09D4CMxSk/42siA3OiFZ0+DLrlEwo4iig72U/fYT0TRMXnMBAzonan4ZK+NxWzBwPP7ofCS8TolEwf7iYw0+mQLrjzmQjECH9lTOiHVxvfdcsUArjzmwuialkhHNBQ7KkDxpNT+/ftRVlaGRYsWYejQobj00ksxb948/PWvf9UzHxEBcFfURXX5WMCOIooO9lP32E9E0VGUPzPk/Vm64/P7UJQ/M8KJxMN+IiPNqKyHRwKeg/r7CJkQWN4jATN21kcsWzSwowIUvxfS09PxwgsvIC0trdPjTU1NEQ9FRN/z1bS0f4uVWv5aN3wx/puE7rCjiIzHflKG/URkvJz+2Rg94OKQ92fpjtlkRu7AEcjpnx3hZGJhP5GRrqh2Ycd337Kn9sP7fgDbAOyQgcuPuSKWzWjsqO8pvk4sJSUFV111Vfu//X4/Vq1ahcsvvzysDUqShESrI6xl2jisCZ3+DlejJEFmBmaIsQyuhsiUraURcGQGb0OE/dAkSaqW6yjaHaV1HwDaXwtmYAajM+jdT0oydCcS+0FrR7GfmIEZjM8wMjNL9bo7GpE5DHtPHFSVoTvsp4B4OaZnBiCrrhXFqtYcbBeAwlOtQduJhf0A6N9RIuwHpf0kybIc7l0gAAB/+MMf8Prrr2PdunUYNmxYt8/3+XwoKyvD5MmTUVwcqbdieCZMmICTJ08iIyMDGzZsYAZmiIkMJSUlWLhwoeZtLViwAIWFhaoy6K2tF3Jzc2E2q/ttwdnYUczADPpn0LuflGQwQqQ7iv3EDMygf4a0tDQMGqT926mqqqpQW1urKoMR2E9ivA7MoCCD348xY8diBYB7I7CtPwMoArD1iy8A0/cfABN+P3xH744SYT8o7afw7qj1ncWLF+PVV1/Fn/70J0Vl1dEpVz0mrpqlZrNwWBOwdtoSTF0zFy5P+Jf61zbXtf/NDMwQKxlcladUZTvb8m2r8XLzRlUZuqN1PzS56lVtN5RodJTWfQBofy2YgRmMzqB3PynJ0J1I7IdIdhT7iRmYwZgMk/LGYfnti1Stu6OnSp/HO9s+UpWhO+yngHg5pmcG4KBJQrJf1TUxQVIAtJokTFzdeYorFvYDoH9HibAflPZT2JNSjz/+ON544w0sXrwY48aNC3dxyLKMZo+2y/1dnhZV62i7KIwZmCGWMvhStH+0DQC8yehyGyLth0iIdkep3Qdt22YGZoilDHr3k5IMSkViP2jFfmIGZjAuw47qXapzdVrP0V3sJ4U5on0cyQziZ9iVasPwb7Xdi7LNcACVvW1B24mF/QDo31Ei7YfuhHXT+6VLl+LNN9/Ef//3f+PGG28MOxQRhc+cngBTml3TOkxpdpjT1d+vIFawo4iMxX5Sjv1EZKyKIztRfvgb+Pzhful8gM/vQ9mhr7H9aGWEk4mH/URG2ZzpwEgJyIW2b9/LAzBCAj7vq+5eSSJgR31P8Xth3759WL58OWbNmoUxY8agpqam/Q8R6cuekxrV5WMBO4ooOthP3WM/EUXHitJVMEnqTn3NJjNWlK6KcCLxsJ/ISK9nO2GVgXnQ9u178wBY5cD6Yhk7KkDxx/f+/ve/w+fz4fnnn8fzzz/f6We7dkXm0jMi6pp1aApavqyF3OQFwrlKWwKkXhZYh6bolk0U7Cii6GA/dY/9RBQdxVs34DfjH0Cmsw8sZuV3LfH6vKiuP4GSr7q+111Pwn4iI5WnJ+Czvg5MOebCYwCOAAjnOiEzgP4AJgP4rK8D5TF+pTU7KkDxf3lRURGKior0zEJEIUgWE5JuGoimdQeBVr+yEz8JgC2wnGRRe4Fs7GBHEUUH+6l77Cei6GjxuPHzZffgb/PfRLI9SdFJn9fnRaP7DCYtvRstnsjc+0Zk7Ccy2pyCvvj8zQP4wCfjRwAaoGxiyozAzc0/BGAzS5hT0FfPmIZgRwX0/CNBoh7C7LSh15TBkHopm0uWelnQa8pgmJ02nZMRUbxjPxGRqPadPIhrF09Ddf0JAAh5/5a2x6vrT+DaxdOwv6bKsIxE8eSA04bZBX0xDMBmBK58AkJPTLQ93v+75w8FMLugLw70kGMIdpSKb98jougxO21Inn4hPHsa4K6og782eHbclGaHPScV1qEpcXEFAhGJgf1ERKLaX1OFsU/ciMJLxqMofyZyB44Ies72I5VYUboKJV9t7DFXHxCJqnhYCiTIWLbpOLb7ZBQDeA7Ati6eOxqBe0hNRuAKqVkFfVE8rGd99D/eO4qTUkQxRrKYYMt2wpbthK+mBZZGYHbedCzfthreZMTFt1gRkZjYT0QkqhaPG6u3rMfqLeuR0z8bIzKH4aH8+/FU6fP4uno3Ko7sjHZEoriybth52JrhwNJNx3DHMRdmSMAOGdiFwEf6UgBkARgpBW5q/mmmA3Ov6TlXSJ0tnjuKk1JEMcycngBHpgOFhYV4uXkjmj2uaEciIgLAfiIicVUc2Ym9Jw7inhE3451tH7GfiKLkgNOGGwsHYXRNC2bsrMflx1woPNUKm19Gq0lCZW8bXu7rwOvZzpi/qXk44q2jOClFRERERERERFFRnp6A8vQfAAASrQ68N/3PmLj63h4/GUMBvKEDEREREREREYnBxGmKeMJXm4iIiIiIiIiIDCfJsiwbsSGfz4eysjLkX52PZlnd3eIlSUJaYipqm+ugJrbc7AVkABIgJar75CIzMAMzRD5DomRH6T9KkZubC7PZrCqDVlo7Sus+ALS/FszADMygT4ZodxT7iRmYgRlCifV+AnrGsSwzMAMzBFPaT8bfU0oG5DNetYviZNNJZmAGZuhpGZLs6peNNJX7IWKvAzMwAzOIl0GUjor314EZmIEZgsV4P323aOwfyzIDMzBDMIX9ZPyklARISfE7W8gMzMAMXa1A1Wb1obKjespvXJmBGZihq5WoWyzi2E/MwAzMELQSdYtFHM/xmIEZmCFoBcqeZviklOQwI2XqEFXLJlodeG/mSkxcNUvVnfgbXtkL+YwXUqIFKXcwAzMwgygZfGurVW1XD2o7Sus+ALS/FszADMygTwZROor9xAzMwAxni/V+AnrGsSwzMAMzBFPaT7zRORERERERERERGY6TUkREREREREREZDhOShERERERERERkeE4KUUxKad/NibljUNaWhom5Y1DTv9swzP4alrgqjyFkpISuCpPwVfTYngGEfYDEXUmwrhkPxFRV0QYl8xARKHw+EWcDEYy/tv3iFRKsNoxecwEFOXPxOgBF7c/vvz2RQCA8sPfYEXpKhRv3YAWj1uXDLLXD8+eBrgr6uCvDWxj4QcL239uSrPDnpMK69AUSBZ95nxF2A9E1JkI45L9RERdEWFcMgMRhcLjF3EyRAsnpSgmXJQxGG8/8AIG9M6EX/Z3+ZyR/bKwdMaT+M34BzBp6d3YX1MV0Qy++lacefcQ5EZvyOf4a91wbTqOli9rkXTTQJidtohmEGE/EFFnIoxL9hMRdUWEcckMRBQKj1/EyRBN/PgeCe+ijMH42/w3kensA0mSYDaZu3ye2WSGJEnIdPbB3x9cgwvTB0Usg6++FU3rDkJuCl2YHclNXjStOwhffWvEMoiwH4ioMxHGJfuJiLoiwrhkBiIKhccv4mSItrAnpaqqqnD33XcjLy8PV199NV544QU9chEBCFzG+PYDLyDZngSLWdmFfRazBcn2JKyf8yISrHbNGWSvH2fePQS0+gFZ6UIAWgPLyd6uZ7vDIcJ+iAXsJzKSCOOS/RQ72E9kJBHGJTPEDvYTGY3HL+JkEEFYk1J+vx9FRUVITU3F22+/jcceewzPP/883nvvPb3yUZybPGYCBvTOVDxI21jMFgw8vx8KLxmvOYNnT0PgklKlhdlGBuRGLzx7GjRnEGE/iI79REYTYVyyn2ID+4mMJsK4ZIbYwH6iaODxizgZRBDWpFRtbS2ys7Px+9//HoMHD0Z+fj6uuOIKbN26Va98FOeK8meG/Fxtd3x+H4ryZ2rO4K6oi+rygBj7QXTsJzKaCOOS/RQb2E9kNBHGJTPEBvYTRQOPX8TJIIKwJqUyMjLw7LPPolevXpBlGVu3bsWXX36JsWPH6pWP4lhO/2yMHnBxyM/VdsdsMiN34AhNX6Hpq2lp/xYItfy1bk1fZyrCfogF7Ccykgjjkv0UO9hPZCQRxiUzxA72ExmNxy/iZBCF6m/fKygoQHV1Na655hqMGzdO8XKSJCHR6lC1TYc1odPf4WqUJMjMEDMZRmZmqVr32UZkDsPeEwdVZXA1uCKSwdIIODKDtxEr+6E7Wt8PTZKkarlQ1PYToH4/aN0HgPbXghmMy6D3uFSSQe9+UpJBhP3QnUi8HyLZUewnZtA7gwjjkhmUYT8FxMu5DTME8PxKnAzdMeocT5JlOdxPcgIAtm/fjtraWvz+97/H9ddfj4cffvicz/f5fCgrK8PkyZNRXFysZpOaTZgwASdPnkRGRgY2bNjADIJnSEtLw6BB2r9VoKqqCrW1taoylJSUYOHChZozLFiwAIWFhaoyiLAf9NbWC7m5uTCb1f22oKNw+wlgRzFDeBn0HpdKMujdT0oyiLAfjBDJjmI/MYPeGUQYl8xgHPaTGK8DMyjPwPMrcTLoTWk/qb5SatSoUQAAt9uN+fPn49e//jVsNlu3y51y1WPiqlmqtumwJmDttCWYumYuXJ7wL9erba5r/5sZxM8wKW8clt++SFW+jp4qfR7vbPtIVQZX5SnN2weA5dtW4+XmjaoyiLAfuqP1/dDkqle13VDU9hOgvqO07gNA+2vBDMZl0HtcKsmgdz8pySDCfuhOJN4Pkewo9hMzxEM/MYMy7KeAeDm3YYYAnl+Jk6E7Rp3jhTUpVVtbi7KyMlx33XXtjw0ZMgQejwdNTU3o3bt3t+uQZRnNHm2X7Lk8LarW0XZRGDPERoYd1bs0ZWtfz9FdXW5DSQZfSmQuifYmQ3UGEfaDUlrfD1pEop/asmjZD2r3Qdu2mSE2Mug9LpVk0LuflGQQYT8oFYn3g1rsJ2YwMoMI45IZwsN+Cujp5zbMEMDzK3EyKKX3OV5YNzo/cuQI5syZgxMnTrQ/tmPHDvTu3VtxYREpVXFkJ8oPfwOf36dqeZ/fh7JDX2P70UrVGczpCTCl2VUvDwCmNDvM6ervFSDCfogF7Ccykgjjkv0UO9hPZCQRxiUzxA72ExmNxy/iZBBFWJNSo0aNwogRI7BgwQLs3bsXpaWlWLx4Me677z698lGcW1G6CiYprLdpO7PJjBWlqzRnsOekRnV5QIz9IDr2ExlNhHHJfooN7CcymgjjkhliA/uJooHHL+JkEEFYe8BsNmP58uVwOByYNm0afve73+G2227D7bffrlc+inPFWzfg8KlqeH3esJbz+rw49O1RlHzV9X1SwmEdmgIp2QKEe6WpBEjJFliHpmjOIMJ+EB37iYwmwrhkP8UG9hMZTYRxyQyxgf1E0cDjF3EyiCDsabk+ffpg6dKl2Lp1Kz799FPcd999kCL8de5EbVo8bvx82T1odJ9RPFi9Pi8a3WcwaendaPG4NWeQLCYk3TQQsJmUF6cEwBZYTrKom/3uSIT9EAvYT2QkEcYl+yl2sJ/ISCKMS2aIHewnMhqPX8TJIALtryaRzvadPIhrF09DdX3gs+6hPnfb9nh1/Qlcu3ga9tdURSyD2WlDrymDIfVS9t0AUi8Lek0ZDLNT2TeWKCHCfiCizkQYl+wnIuqKCOOSGYgoFB6/iJMh2sL69j2iaNlfU4WxT9yIwkvGoyh/JnIHjgh6zvYjlVhRugolX23UZdbY7LQhefqF8OxpgLuiDv7a4G2Y0uyw56QGLkmNwAz+2UTYD0TUmQjjkv1ERF0RYVwyAxGFwuMXcTJEEyelKGa0eNxYvWU9Vm9Zj5z+2RiROQwP5d+Pp0qfx9fVu1FxZKfuGSSLCbZsJ2zZTvhqWmBpBGbnTcfybavhTYamb4FQSoT9QESdiTAu2U9E1BURxiUzEFEoPH4RJ0O0cFKKYlLFkZ3Ye+Ig7hlxM97Z9hGaPS7DM5jTE+DIdKCwsBAvN2+MSgYR9gMRdSbCuGQ/EVFXRBiXzEBEofD4RZwMRuI9pYiIiIiIiIiIyHCclCIiIiIiIiIiIsNxUoqIiIiIiIiIiAwnybIsG7Ehn8+HsrIy5F+dj2ZZ3d3iJUlCWmIqapvroCa23OwFZAASICWqu50WMzADM0Q+Q6JkR+k/SpGbmwuz2awqg1ZaO0rrPgC0vxbMwAzMoE+GaHcU+4kZmIEZQon1fgJ6xrEsMzADMwRT2k/G3+hcBuQzXrWL4mTTSWZgBmboaRmS7OqXjTSV+yFirwMzMAMziJdBlI6K99eBGZiBGYLFeD99t2jsH8syAzMwQzCF/WT8pJQESEnxO1vIDMzADF2tQNVm9aGyo3rKb1yZgRmYoauVqFss4thPzMAMzBC0EnWLRRzP8ZiBGZghaAXKnmb4pJTkMCNl6hBVyyZaHXhv5kpMXDVL1dciNryyF/IZL6REC1LuYAZmYAZRMvjWVqvarh7UdpTWfQBofy2YgRmYQZ8MonQU+4kZmIEZzhbr/QT0jGNZZmAGZgimtJ94o3MiIiIiIiIiIjIcJ6WIiIiIiIiIiMhwnJQiIooUvz/aCYiIiIiIiGKG8Tc6JyLqIUbXtGDGznpcUe1CVl0rbM+OxUGThF2pNmzOdOD1bCfK0xOiHZOIiIiIiEhInJQKQ07/bIzMzEJaWhom5Y3DjupdqDiykxmikMFX0wJXgwslJSVwVZ6CL0WC2eCTfxH2A0XHBfWtWLrpGK485oJHAnbIQDGARgDJfhnDv3XjzlNuFG2vx2d9HZhT0BcHnDZdM4kwJphBnAzsJ2ojwvuRGcTJIEI3iJCBxCHCuGAGZuiIHWU8Tkp1I8Fqx+QxE1CUPxOjB1zc/vjy2xcBAMoPf4MVpatQvHUDWjxuZtAxg+z1w7OnAe6KOvhrA9tY+MHC9p+b0uyw56TCOjQFkkWfT6aKsB8ouqbsPo1lm46j1SfjZQDPyUBZF8/LlYF5AKYcc+HzNw9gdkFfFA9LiWgWEcYEM4iTgf1EbUR4PzKDOBlE6AYRMpA4RBgXzMAMHbGjoouTUudwUcZgvP3ACxjQOxN+uet7xYzsl4WlM57Eb8Y/gElL78b+mipm0CGDr74VZ949BLnRG/I5/lo3XJuOo+XLWiTdNBDmCF+ZIsJ+oOiasvs0Vnx8DLsB3ACgCqFvzFcB4C4AjwH40Cdj5cfVkCBj3bDzIpJFhDHBDOJkYD9RGxHej8wgTgYRukGEDCQOEcYFMzBDR+yo6FM91VhUVISHHnooklmEclHGYPxt/pvIdPaBJEkwm8xdPs9sMkOSJGQ6++DvD67BhemDmCHCGXz1rWhadxByU+iy6khu8qJp3UH46lsjlkGE/UDhiXRHXVjfimWbjmM3gB8BOPLd46Fubd72+BEAVwDYA2DZpuO4IALvSxHGBDOIk4H9FHv0OoYS4f3IDOJkEKEbRMhA4dHzHE+EccEMzNARO0oMqial3n//fZSWlkY6izASrHa8/cALSLYnwWJWdjGZxWxBsj0J6+e8iASrnRkilEH2+nHm3UNAqx+QlS4EoDWwnOzV/m1oIuwHCo8eHbVk0zG4fTJuANAAwKdwOd93zx8HoNUnY+mmY5pyiDAmmEGcDOyn2KPXMZQI70dmECeDCN0gQgYKj57neCKMC2Zgho7YUeIIe1Kqvr4eTz/9NEaNGqVHHiFMHjMBA3pnKn5ztrGYLRh4fj8UXjKeGSKUwbOnIXA5p9KyaiMDcqMXnj0NmjOIsB9IOT06avTJFlx5zIViBD6yp3RCqo3vu+WKAVx5zIXRNS2qs4gwJphBnAzsp9ii5zGUCO9HZhAngwjdIEIGUk7vczwRxgUzMENH7ChxhD0p9Yc//AE/+9nPMGTIED3yCKEof2bIz5N2x+f3oSh/JjNEKIO7oi6qywNi7AdSTo+OmlFZD48EPAf1n3k2IbC8RwJm7KxXnUWEMcEM4mRgP8UWPY+hRHg/MoM4GUToBhEykHJ6n+OJMC6YgRk6YkeJI6zzq82bN+Nf//oXZs+erVeeqMvpn43RAy4O+XnS7phNZuQOHIGc/tnMoDGDr6al/RsY1PLXuuHTcFWKCPuBlNOro66odmHHd9+yp/ZiYT+AbQB2yMDlx1yq1iHCmGAGcTKwn2KLnsdQIrwfmUGcDCJ0gwgZSDm9z/FEGBfMwAwdsaPEovhaNbfbjUcffRSPPPIIEhISVG9QkiQkWh2qlnVYEzr9Ha5GSYLcTYaRmVmq1n22EZnDsPfEQWbQkMHVoO7E/WyWRsCRGbyNWNkP3TFiXOidoUmSVC3XkZ4dlVXXimKtAb+zC0DhqdYu93V3r4XeY4IZYiuD3v2kJEN3tHaDKBm0dpTex1AivB+ZQZwMInSDCBm6w34KMOIcT4RjemZgho54jmdMBqX9pHhSaunSpRg5ciSuuuoqVYHa9HY4UTxzpaZ1rJ22RNVyE1ZPwMmmk0hLTMV7ITKkpaVpidbuofz7cc+Im5lBQ4aSkhIs/GCh5gyz86ajsLBQVQYR9oNSeo4LvTNMfnuypu0COnaU3w/bs2PRqDFfmwYANr+M96b/GTB1vli1u9dC7zHBDLGVQe9+UpJBKbXdIEoGrR2l9zGUCO9HZhAngwjdIEIGpdhP+p/jiXBMzwzM0BHP8YzJoLSfFE9Kvf/++6itrUVeXh4AoLU18FWMH374IbZt26Y42ClXPSaumqX4+R05rAlYO20Jpq6ZC5cn/Mv1apvr2v8OlWFS3jgsv32RqnwdPVX6PN7Z9hEzaMjgqjylefsAsHzbarzcvFFVBhH2Q3eMGBd6Z2hy1avabkd6dtRBk4Rkf7h3YuxaCoBWk4SJq+8N+ll3r4XeY4IZYiuD3v2kJEN3tHaDKBm0dpTex1AivB+ZQZwMInSDCBm6w34KMOIcT4RjemZgho54jmdMBqX9pHhS6rXXXoPX623/9zPPPAMAmD9/fljBZFlGs0fbJXsuT4uqdciy3G2GHdW7NGVrX8/RXV1ugxmUZ/ClaP9IFwB4kxHT+0EpPceFURm00LOjdqXaMPxbbZ99bzMcQGVvm6r3g95jghliK4Pe/aQkg1Jqu0G0DGrpfQwlwvuRGcTJIEI3iJBBKfaT/ud4IhzTMwMzdMRzPGMzdEfxjc779euHQYMGtf9JSkpCUlISBg0aFHY4kVUc2Ynyw9/A5w/3S98DfH4fyg59je1HK5lBYwZzegJMaXbVywOAKc0Oc7r6z8eLsB9IGT07anOmAyMlIBfavn0vD8AICfi8r7rPdYswJphBnAzsp9ih9zGUCO9HZhAngwjdIEIGUsaIczwRxgUzMENH7CixqD2/6tFWlK6CSVK3a8wmM1aUrmKGCGWw56RGdXlAjP1A0fV6thNWGZgHbd++Nw+AVQ6sTy0RxgQziJOB/URtRHg/MoM4GUToBhEykDhEGBfMwAwdsaPEoXpS6qmnnsJTTz0VySzCKN66AYdPVcPr83b/5A68Pi8OfXsUJV91fQ8AZgifdWgKpGQLEO5VnhIgJVtgHZqiOYMI+4HCF8mOKk9PwGd9HZgCYBCAcL881vzdcpMBfNbXgXINv9kRYUwwgzgZ2E+xSY9jKBHej8wgTgYRukGEDBQ+vc7xRBgXzMAMHbGjxMErpbrQ4nHj58vuQaP7jOI3qdfnRaP7DCYtvRstHu33nmGGAMliQtJNAwGbSXlpSQBsgeUki/a3uAj7gaJvTkFf2MwSPkDgZuVKJ6bM3z3/QwA2s4Q5BX015RBhTDCDOBnYT9RGhPcjM4iTQYRuECEDiUOEccEMzNARO0ocnJQKYd/Jg7h28TRU158AgJCfN217vLr+BK5dPA37a6qYIcIZzE4bek0ZDKmXsvvyS70s6DVlMMxOW8QyiLAfKLoOOG2YXdAXwwBsBtD/u8dDlWjb4/2/e/5QALML+uJABN6XIowJZhAnA/uJ2ojwfmQGcTKI0A0iZCBxiDAumIEZOmJHiUHxt+/Fo/01VRj7xI0ovGQ8ivJnInfgiKDnbD9SiRWlq1Dy1UZdZkuZIcDstCF5+oXw7GmAu6IO/trgbZjS7LDnpAYuB43A7PnZRNgPFF3Fw1IgQcayTcex3SejGMBzALr6wuTRCNxDajICV0jNKuiL4mHaLzVuI8KYYAZxMrCfqI0I70dmECeDCN0gQgYShwjjghmYoSN2VPRxUqobLR43Vm9Zj9Vb1iOnfzZGZA7DQ/n346nS5/F19W5UHNnJDAZlkCwm2LKdsGU74atpgaURmJ03Hcu3rYY3GZq+gUEpEfYDRde6Yedha4YDSzcdwx3HXJghATtkYBeABgQ+qpcFYKQUuKn5p5kOzL0mMldInU2EMcEM4mRgP1EbEd6PzCBOBhG6QYQMJA4RxgUzMENH7Kjo4sf3wlBxZCfe2fYRamtr8c62j6Ly5mSGAHN6AhxZqSgsLIQjK9WQsjqbCPuBouOA04YbCwchf+pgvDzSCXOaHYUmCUUACk0SzGl2vDzSifypg/HTnw/SZULqbCKMCWYQJwP7idqI8H5kBnEyiNANImQgcYgwLpiBGTpiRxmPV0oREalUnp6A8vQfAAASrQ68N/3PmLj6XjR7XFFORkREREREJD5eKUVEFCkmVioREREREZFSPIMiIiIiIiIiIiLDSbIsy0ZsyOfzoaysDPlX56NZVnfHekmSkJaYitrmOqiJLTd7ARmABEiJ6j65yAzMwAyRz5Ao2VH6j1Lk5ubCbDaryqCV1o7Sug8A7a8FMzADM+iTIdodxX5iBmZghlBivZ+AnnEsywzMwAzBlPaT8feUkgH5jFftojjZdJIZmIEZelqGJLv6ZSNN5X6I2OvADMzADOJlEKWj4v11YAZmYIZgMd5P3y0a+8eyzMAMzBBMYT8ZPyklAVJS/M4WMgMzMENXK1C1WX2o7Kie8htXZmAGZuhqJeoWizj2EzMwAzMErUTdYhHHczxmYAZmCFqBsqcZPiklOcxImTpE1bKJVgfem7kSE1fNUvXtVg2v7IV8xgsp0YKUO5iBGZhBlAy+tdWqtqsHtR2ldR8A2l8LZmAGZtAngygdxX5iBmZghrPFej8BPeNYlhmYgRmCKe0n3uiciIiIiIiIiIgMx0kpIiIiIiIiIiIyHCeliIiIiIiIiIjIcJyUijE5/bMxKW8c0tLSMClvHHL6ZzNDlDIQUWcijEtmIKKuiDAumYGIQhFhbIqQwVfTAlflKZSUlMBVeQq+mhbDM5DxjP/2PQpbgtWOyWMmoCh/JkYPuLj98eW3LwIAlB/+BitKV6F46wa0eNzMoGMGIupMhHHJDETUFRHGJTMQUSgijE0RMshePzx7GuCuqIO/NrCNhR8sbP+5Kc0Oe04qrENTIFl4TU1PxFdVcBdlDMYXD7+PpTOexMh+WV0+Z2S/LCyd8SS+ePh9XJg+iBl0ykBEnYkwLpmBiLoiwrhkBiIKRYSxKUIGX30rGlfvh2vT8fYJqbP5a91wbTqOxtX74atvjXgGir6wJ6U+/vhjZGVldfozb948PbLFvYsyBuNv899EprMPJEmC2WTu8nlmkxmSJCHT2Qd/f3BNRAuDGSiWsJ+MI8K4ZAaKJewn44gwLpmBYgn7yVgijE0RMvjqW9G07iDkJq+i58tNXjStO8iJqR4o7EmpvXv34pprrsGnn37a/ueJJ57QI1tcS7Da8fYDLyDZngSLWdmnLC1mC5LtSVg/50UkWO3MEKEMFDvYT8YQYVwyA8Ua9pMxRBiXzECxhv1kHBHGpggZZK8fZ949BLT6AVnpQgBaA8vJXr/mDCSOsCel9u3bh2HDhiE9Pb39T0pKih7Z4trkMRMwoHem4qJoYzFbMPD8fii8ZDwzRCgDxQ72kzFEGJfMQLGG/WQMEcYlM1CsYT8ZR4SxKUIGz54GyI1e5RNSbWRAbvTCs6dBcwYSh6pJqcGDB+sQhToqyp8Jv6xuBtjn96EofyYzRCgDxQ72kzFEGJfMQLGG/WQMEcYlM1CsYT8ZR4SxKUIGd0VdVJcnsYQ1KSXLMg4cOIBPP/0U48aNw3XXXYdnnnkGra38XGck5fTPxugBF4f8bG93zCYzcgeO0PQ1nsxAsYb9ZAwRxiUzUKxhPxlDhHHJDBRr2E/GEWFsipDBV9MS8qbmSvlr3fDVtGhaB4kjrGv2qqur4XK5YLPZ8Oyzz+LIkSN44okn0NLSgocffljROiRJQqLVoSqsw5rQ6e9wNUoS5BjIMDKz628/CNeIzGHYe+IgM2jI0J14eU/qnaFJklQt11Ek+glQvx+07gNA+2thRAa9xyUzKM/QnXh5TxqRQWtHsZ/YT/GWoTvx8p40IkOs9xPQM45lY+XcRoQMrgZXRDJYGgFHZvA2YuX9EA8ZlPaTJMtyWJ/krK+vx3nnnQfpuw18+OGHePDBB7Ft2zaYzaFnXH0+H8rKyjB58mQUFxeHs8mImTBhAk6ePImMjAxs2LBB2AxpaWkYNEj7NxtUVVWhtraWGTRk0BszBLT1Qm5u7jl7pDtq+wlgRynNoPe4ZAblGYzADAGR6Cj2k/4ZRBiXzGAcZghgP4nxOsTKuY0IGUpKSrBw4ULNGRYsWIDCwkJVGfTGDAFK+ym8u5sBcDqdnf590UUXwe124/Tp0+jdu3e3y59y1WPiqlnhbhZAYIZu7bQlmLpmLlye8C/Xq22ua/9b5AyT8sZh+e2LVOXr6KnS5/HOto+YQUOG7sTLe1LvDE2uelXbPZvWfgLUd5TWfQBofy2MyKD3uGQG5Rm6Ey/vSSMyRKKj2E/sp3jK0J14eU8akSHW+wnoGceysXJuI0IGV+UpzdsHgOXbVuPl5o2qMnQnXt6TemdQ2k9hTUp98sknmD9/Pv7xj3/A4QhcArZz5044nU7FhSXLMpo92i7Zc3laVK2j7aIw0TPsqN6lKVv7eo7u6nIbzKA8g1I9/T1pVAYtItFPbVm07Ae1+6Bt26Jn0HtcMoPyDEr19PekkRnUYj8Zk0GEcckM4enp70kjM6glSj8BPeNYVvRzGxEy+FK037YDALzJ4DlejGToTlg3Os/Ly4PdbsfDDz+M/fv3o7S0FE8//TTuueeesANSaBVHdqL88Dfw+X2qlvf5fSg79DW2H61kBo0ZKHawn4whwrhkBoo17CdjiDAumYFiDfvJOCKMTREymNMTYEqzq14eAExpdpjT1d+LjcQS1qRUr1698OKLL+LUqVOYPHkyfve732HatGksLR2sKF0FkxTWy9PObDJjRekqZohQBooN7CfjiDAumYFiCfvJOCKMS2agWMJ+MpYIY1OEDPac1KguT2IJ+904dOhQvPzyy9i2bRs+/fRTzJkzp/2meBQ5xVs34PCpanh93rCW8/q8OPTtUZR8Ffz5Wmagno79ZAwRxiUzUKxhPxlDhHHJDBRr2E/GEWFsipDBOjQFUrIFCPdtJgFSsgXWoSmaM5A41E2Rku5aPG78fNk9aHSfUVwYXp8Xje4zmLT0brR43MwQoQxE1JkI45IZiKgrIoxLZiCiUEQYmyJkkCwmJN00ELCZlE9MSQBsgeUkC6cxehK+mgLbd/Igrl08DdX1JwAg5Gd/2x6vrj+BaxdPw/6aKmaIcAYi6kyEcckMRNQVEcYlMxBRKCKMTREymJ029JoyGFIvZd+9JvWyoNeUwTA7bRHLQGII69v3yHj7a6ow9okbUXjJeBTlz0TuwBFBz9l+pBIrSleh5KuNuvxmixmIqCsijEtmIKKuiDAumYGIQhFhbIqQwey0IXn6hfDsaYC7og7+2uBtmNLssOekBj7yxyukeiROSsWAFo8bq7esx+ot65HTPxsjMofhofz78VTp8/i6ejcqjuxkBoMyEFFnIoxLZiCirogwLpmBiEIRYWyKkEGymGDLdsKW7YSvpgWWRmB23nQs37Ya3mTwW/biACelYkzFkZ3Ye+Ig7hlxM97Z9hGaPS5miFIGIupMhHHJDETUFRHGJTMQUSgijE0RMpjTE+DIdKCwsBAvN29kR8UJXv9GRERERERERESG46QUEREREREREREZjpNSRERERERERERkOEmWZdmIDfl8PpSVlSH/6nw0y+ru3C9JEtISU1HbXAc1seVmLyADkAApUd3ttJiBGZgh8hkSJTtK/1GK3NxcmM1mVRm00tpRWvcBoP21YAZmYAZ9MkS7o9hPzMAMzBBKrPcT0DOOZZmBGZghmNJ+Mv5G5zIgn/GqXRQnm04yAzMwQ0/LkGRXv2ykqdwPEXsdmIEZmEG8DKJ0VLy/DszADMwQLMb76btFY/9YlhmYgRmCKewn4yelJEBKit/ZQmZgBmboagWqNqsPlR3VU37jygzMwAxdrUTdYhHHfmIGZmCGoJWoWyzieI7HDMzADEErUPY0wyelJIcZKVOHqFo20erAezNXYuKqWaq+HrLhlb2Qz3ghJVqQcgczMAMziJLBt7Za1Xb1oLajtO4DQPtrwQzMwAz6ZBClo9hPzMAMzHC2WO8noGccyzIDMzBDMKX9xBudExERERERERGR4TgpRer5/dFOQEREREREREQxyvh7SlHMGl3Tghk763FFtQtZda2wPTsWB00SdqXasDnTgdeznShPT4h2TCIiIiIiIiKKAZyUom5dUN+KpZuO4cpjLngkwDo6F7h+OJCcDFtjI0ZVVmJ4eRmKttfjs74OzCnoiwNOm66ZfDUtcDW4UFJSAlflKfhSJJg5IUYU93L6Z2NkZhbS0tIwKW8cdlTvQsWRnYZmYD8RUVfYT0QkMnYURQsnpeicpuw+jWWbjsNsswN33AHrvHlAXl7Q86zbtgHPPYfL1ryJz988gNkFfVE8LCWiWWSvH549DXBX1MFf6wYALPxgYfvPTWl22HNSYR2aAsnCT6YSxYsEqx2Tx0xAUf5MjB5wcfvjy29fBAAoP/wNVpSuQvHWDWjxuHXJwH4ioq6wn4hIZOwoEgEnpSikKbtPY8XHx4ChQ2H66CNg0KDQ95HKyQFeegmWRx+F6frrsfLjvZAgY92w8yKSxVffijPvHoLc6A35HH+tG65Nx9HyZS2SbhoIs85XaxFR9F2UMRhvP/ACBvTOhF/uup9G9svC0hlP4jfjH8CkpXdjf01VRDOwn4ioK+wnIhIZO4pEEfZUY2trKx577DH88Ic/xI9+9CP893//N2RZ1iMbRdGF9a1Ytul4YELq88+Bfv0ASQLM5q4XMJsDP+/XD6YtW4AhQ7Bs03FcUN+qOYuvvhVN6w5CbgpdVh3JTV40rTsIXwS2TbGF/RRfLsoYjL/NfxOZzj6QJAlmU9f9ZDaZIUkSMp198PcH1+DC9EERy8B+IqXYT/GF/USxhP0Uf9hRJJKwJ6WeeOIJ/POf/8SLL76IP/7xj1i7di3WrFmjRzaKoiWbjsFksweukEpOBqxWZQtarUByMkwffwyzzY6lm45pyiF7/Tjz7iGg1Q8o/f9GGUBrYDnZy28IjCfsp/iRYLXj7QdeQLI9CRazsot+LWYLku1JWD/nRSRY7ZozsJ8oHOyn+MF+oljDfoov7CgSTViTUvX19SguLsbjjz+OnJwcXHHFFbjrrrtQXl6uVz6KgtEnW3DlMRes024JfGRP6YRUG6sVGDwYlqnTcOUxF0bXtKjO4tnTELicM9xf1siA3OiFZ0+D6m1TbGE/xZfJYyZgQO9MxQdTbSxmCwae3w+Fl4zXnIH9REqxn+IL+4liCfsp/rCjSDRhvRO3bt2KXr16YezYse2PFRUVRTwURdeMyvrAt+zNmxe4h1Soj+ydi88HzJ0Lz19exYyd9ShP/4GqLO6KOlXLdVzelu3UtA6KDeyn+FKUPxN+2Q+zFH4/+fw+FOXPxOot6zVlYD+RUuyn+MJ+oljCfoo/7CgSTVhXSh0+fBj9+vXD+vXrccMNN+Daa6/FsmXL4A9182uKSVdUu2AdnRv4lj01E1JAYLkxY2AdnYvLj7lUrcJX09L+DQxq+Wvd8Gm4UotiB/spfuT0z8boAReHvP9Bd8wmM3IHjkBO/2zVGdhPFA72U/xgP1GsYT/FF3YUiSisK6Wam5tRVVWFN998E4sWLUJNTQ0eeeQROBwO3HXXXYrWIUkSEq0OVWEd1oROf4erUZIgM0O3GbLqWoHrh6tad/DKsjC8ojxoO0r2g6tB3WTW2SyNgCMzeBux8FrES4YmSVK1XEeR6CdA/X7Qug8A7a9FvGQYmZmlet0djcgchr0nDqrKoHc/KcnQnXh5PxiRQWtHsZ/iJwP7SZl4eT8YkSHW+wnoGceysZJB747iOR4zdKS0nyQ5jK9WWLFiBf74xz9i06ZN6NevHwDglVdewRtvvIEPP/zwnMv6fD6UlZVh8uTJKC4uVrrJiJowYQJOnjyJjIwMbNiwgRm6yuD3Y8zYscCsWcCKFdo3VlQErFyJrV98AZi+vzBPyX4oKSnBwoULNUdYsGABCgsLgx4X/rWIowxtvZCbmwuzyqvztPQTwI6KpQxpaWkYNEj7t79UVVWhtrZWVQa9+0lJBiMwQ4DWjmI/xU8G9pNxmCGA/STG6xArGfTuKJ7jMUNHSvsprCul0tPTYbfb2wsLAC644AIcO6b8G9ZOueoxcdWscDbbzmFNwNppSzB1zVy4POFfrlfbXNf+NzOEznDQJMHW2KgqW5CGBrSaJExcfW9YGQDAVXkqIhGWb1uNl5s3Bj0eC69FvGRoctWr2m5HkegnQH1Had0HgPbXIl4yTMobh+W3L1K17o6eKn0e72z7SFUGvftJSYbuxMv7wYgMWjuK/RQ/GdhPysTL+8GIDLHeT0DPOJaNlQx6dxTP8ZihI6X9FNak1OjRo+F2u3HgwAFccMEFAID9+/d3KrHuyLKMZo+2S/ZcnhZV62i7KIwZzp1hV6oNoyorNWVrV1mJyt62oO0o2Q++FO0f6QIAbzK63EYsvBbxlkGLSPRTWxYt+0HtPmjbNjN0n2FH9S7VuTqt5+iukBm7y6B3PynJoFRPfz8YmUEt9lP8ZGA/haenvx+MzKCWKP0E9IxjWdEz6N1RPMdjhq4ydCesG51feOGFuPrqq/Hb3/4WlZWV+OSTT7BixQrceuutYQckcW3OdMBTXgZs2xb4Fj01fD5g61Z4KsrxeV91n2E1pyfAlGZXt/3vmNLsMKer/5w+xQ72U/yoOLIT5Ye/gc+vrp98fh/KDn2N7UfVT76znygc7Kf4wX6iWMN+ii/sKBJRWJNSAPDMM89g4MCBuPXWW/Gb3/wGM2bMwG233aZHNoqS17OdsMoAnnuu032gwmI2A0uWwCoH1qeWPSdV9bKRWJ5iC/spfqwoXQWTpK6fzCYzVpSu0pyB/UThYD/FD/YTxRr2U3xhR5Fowvr4HgAkJyfj6aef1iMLCaI8PQGf9XXgsjVvwvLoo0C/foDVqnwFHg9w9Ci8a9dgS18HyjXMYluHpqDly1rITV4gnKuTJUDqZYF1aIrqbVPsYT/Fj+KtG/Cb8Q8g09kHFrPy/yvz+ryorj+Bkq+6vk9KONhPFA72U/xgP1GsYT/FF3YUiUblZTDU080p6Atfqxv+n/wEaGwMTDQp4fEAjY3wX389fK1uzCnoqymHZDEh6aaBgM0EKP34sQTAFlhOsvAtTtQTtXjc+Pmye9DoPgOvz6toGa/Pi0b3GUxaejdaPG7NGdhPRNQV9hMRiYwdRaLhq0ldOuC0YXZBX2DPHvgvuww4ejTwg1D3mGp7/OjRwPP37sXsgr444LRpzmJ22tBrymBIvZTN5Eu9LOg1ZTDMEdg2EYlr38mDuHbxNFTXnwCAkPdHaHu8uv4Erl08DftrqiKWgf1ERF1hPxGRyNhRJJKwP75H8aN4WAokyFi2aR/MF2fDMnUaMHcuMGZM8JPLyoAlS+Bduwa+VjdmX5+J4mGRu6zS7LQhefqF8OxpgLuiDv7a4Bl6U5od9pxUWIemcPacKE7sr6nC2CduROEl41GUPxO5A0cEPWf7kUqsKF2Fkq82RuS3e2djPxFRV9hPRCQydhSJgpNSdE7rhp2HrRkOLN10DFe++io8f3kV1tG5QFYWkJICNDQAu3bBU14Gqwx8nunA3GsuiMgVUmeTLCbYsp2wZTvhq2mBpRGYnTcdy7ethjcZ/AYGojjV4nFj9Zb1WL1lPXL6Z2NE5jA8lH8/nip9Hl9X70bFkZ26Z2A/EVFX2E9EJDJ2FImAk1LUrQNOG24sHITRNS2YsbMelx/ZieEV5bD5ZbSaJFT2tuHzkU68nu3UdFPzcJjTE+DIdKCwsBAvN29Es8dlyHaJSGwVR3Zi74mDuGfEzXhn20dR6Qb2ExF1hf1ERCJjR1G0cFKKFCtPT0B5+g8AAIlWB96b/mdMXH0vy4KIiIiIiIiIwsYPZZJ6Jr59iIiIiIiIiEgdzioQEREREREREZHhJFmWZSM25PP5UFZWhvyr89Esq7tzvyRJSEtMRW1zHdTElpu9gAxAAqREdZ9cZAZmYIbIZ0iU7Cj9Rylyc3NhNptVZdBKa0dp3QeA9teCGZiBGfTJEO2OYj8xAzMwQyix3k9AzziWZQZmYIZgSvvJ+HtKyYB8xqt2UZxsOskMzMAMPS1Dkl39spGmcj9E7HVgBmZgBvEyiNJR8f46MAMzMEOwGO+n7xaN/WNZZmAGZgimsJ+Mn5SSACkpfmcLmYEZmKGrFajarD5UdlRP+Y0rMzADM3S1EnWLRRz7iRmYgRmCVqJusYjjOR4zMAMzBK1A2dMMn5SSHGakTB2iatlEqwPvzVyJiatmqfrGt4ZX9kI+44WUaEHKHczADMwgSgbf2mpV29WD2o7Sug8A7a8FMzADM+iTQZSOYj8xAzMww9livZ+AnnEsywzMwAzBlPYTb3RORERERERERESG46QUEREREREREREZjpNSRERERERERERkOONvdE4UAb6aFrgaXCgpKYGr8hR8KRLM6QnRjkVExH4iImGxn4hIZOyo+MRJKYoZstcPz54GuCvq4K91AwAWfrCw/eemNDvsOamwDk2BZOFFgERkHPYTEYmK/UREImNHESelKCb46ltx5t1DkBu9IZ/jr3XDtek4Wr6sRdJNA2F22gxMSETxiv1ERKJiPxGRyNhRBIQ5KVVSUoLf/va3QY9LkoTKysqIhSLqyFffiqZ1B4FWv6Lny01eNK07iF5TBrO04gj7iaKB/URKsJ8oGthPpBQ7iqKBHUVtwpqUmjBhAq666qr2f3u9Xvz7v/87rr766kjnIgIQuJzzzLuHAmUlK10IQGtgueTpF/IyzzjBfiKjsZ9IKfYTGY39ROFgR5HR2FHUUViTUgkJCUhI+P5GY3/+858hyzLmz58f8WBEAODZ03DOyzlDkgG50QvPngbYsp0Rz0XiYT+R0dhPpBT7iYzGfqJwsKPIaOwo6kj19GJ9fT1WrlyJX/3qV7DZePkc6cNdURfV5Sk2sZ/ICOwnUoP9REZgP5Fa7CgyAjuKOlI9KfXGG28gIyMDN9xwQyTzELXz1bS0fwODWv5aN3w1LRFKRLGC/UR6Yz+RWuwn0hv7ibRgR5He2FF0NlXfvifLMt566y3cc889YS8rSRISrQ41m4XDmtDp73A1ShJkZoiZDK4Gl6p1n83SCDgyg7cRK/shHjI0SZKq5bqipZ8A9ftB6z4AtL8WzGBcBr37SUmG7sTLa2FEhkh1FPuJGdhPAfHyWhiRQZRjqHg/lmUG5Rl4jhc/GZT2kyTLstJbi7WrqKjArbfein/+858477zzFC3j8/lQVlaGyZMno7i4ONxNRsSECRNw8uRJZGRkYMOGDcwgeIaSkhIsXLhQ87YWLFiAwsJCVRn0xgwBbb2Qm5sLs9msaV1q+glgRzFDeBn07iclGYzADAGR6ij2EzMYkYH9FF8Zon0MxX5ihnAz8BwvfjIo7SdVV0p98sknuPTSS8M6oGpzylWPiatmqdksHNYErJ22BFPXzIXLE/7lerXNde1/M4P4GVyVp1RlO9vybavxcvNGVRm6Ey+vhd4Zmlz1qrbbFS39BKjvKK37AND+WjCDcRn07iclGboTL6+FERki1VHsJ2ZgPwXEy2thRAZRjqF4jscMSjPwHC9+MijtJ1WTUhUVFbjkkkvULApZltHs0XbJnsvTomodbReFMUNsZPClROZyZG8yutxGrOyHeMoQCVr6qS2Llv2gdh+0bZsZYiOD3v2kJINSPf21MDKDVuwnZjAiA/spPjNEAs/xmMGIDDzHi78M3VF1o/M9e/ZgyJAhahYlUsycngBTml3TOkxpdpjT1X9On2IP+4mMwH4iNdhPZAT2E6nFjiIjsKPobKompWpra5GSkhLpLERB7DmpUV2eYg/7iYzCfqJwsZ/IKOwnUoMdRUZhR1FHqj++R2QE69AUtHxZC7nJC4RzdbIESL0ssA7l/7HGG/YTGYX9ROFiP5FR2E+kBjuKjMKOoo5UXSlFZBTJYkLSTQMBmwlQ+vFjCYAtsJxk4VuciPTBfiIiUbGfiEhk7CjqiK8mCc/stKHXlMGQeim7sE/qZUGvKYNhdtp0TkZE8Y79RESiYj8RkcjYUdRG1cf3iIxmdtqQPP1CePY0wF1RB3+tO+g5pjQ77DmpsA5N4ew5ERmG/UREomI/EZHI2FEEcFKKYohkMcGW7YQt2wlfTQssjcDsvOlYvm01vMngNzAQUdSwn4hIVOwnIhIZO4o41UgxyZyeAEdWKgoLC+HISmVZEZEw2E9EJCr2ExGJjB0VnzgpRUREREREREREhuOkFBERERERERERGY6TUkREREREREREZDhJlmXZiA35fD6UlZUh/+p8NMvBd9VXQpIkpCWmora5Dmpiy81eQAYgAVKiunu8MwMzMEPkMyRKdpT+oxS5ubkwm82qMmiltaO07gNA+2vBDMzADPpkiHZHsZ+YgRmYIZRY7yegZxzLMgMzMEMwpf1k/LfvyYB8xqt2UZxsOskMzMAMPS1Dkl39spGmcj9E7HVgBmZgBvEyiNJR8f46MAMzMEOwGO+n7xaN/WNZZmAGZgimsJ+Mn5SSACkpfmcLmYEZmKGrFajarD5UdlRP+Y0rMzADM3S1EnWLRRz7iRmYgRmCVqJusYjjOR4zMAMzBK1A2dMMn5SSHGakTB2iatlEqwPvzVyJiatmodnjCnv5hlf2Qj7jhZRoQcodzMAMzCBKBt/aalXb1YPajtK6DwDtrwUzMAMz6JNBlI5iPzEDMzDD2WK9n4CecSzLDMzADMGU9hNvdE5ERERERERERIbjpBQRERERERERERmOk1JERERERERERGQ44290ThQBvpoWuBpcKCkpgavyFHwpEszpCdGORUTEfiIiYbGfiEhk7Kj4xEkpihmy1w/Pnga4K+rgr3UDABZ+sLD956Y0O+w5qbAOTYFk4UWARGQc9hMRiYr9REQiY0cRJ6UoJvjqW3Hm3UOQG70hn+OvdcO16ThavqxF0k0DYXbaDExIRPGK/UREomI/EZHI2FEEqLin1LFjx3DvvffikksuQUFBAV555RUdYhF9z1ffiqZ1ByE3hS6rjuQmL5rWHYSvvlXnZCQa9hMZjf1ESrGfyGjsJ1KK/UTRwI6iNmFPSv3iF79AYmIiSkpKsGDBAjz77LP4+OOP9chGBNnrx5l3DwGtfkBWuhCA1sBystevZzwSDPuJjMR+onCwn8hI7CcKB/uJjMaOoo7CmpQ6ffo0ysrKcP/992Pw4MG47rrrcNVVV2Hz5s165aM459nTELicU2lZtZEBudELz54GXXKReNhPZDT2EynFfiKjsZ9IKfYTRQM7ijoKa1IqISEBDocDJSUl8Hg82L9/P7766itkZ2frlY/inLuiLqrLU+xgP5HR2E+kFPuJjMZ+IqXYTxQN7CjqKKxJKbvdjkceeQRr1qzB6NGjMX78ePzbv/0bbr75Zr3yURzz1bS0fwODWv5aN3w1LRFKRCJjP5GR2E8UDvYTGYn9ROFgP5HR2FF0trC/fW/fvn245pprcOedd2LPnj14/PHHccUVV+Cmm25StLwkSUi0OsIOCgAOa0Knv8PVKEmQmSFmMrgaXKrWfTZLI+DIDN5GrOyHeMjQJEmqljub1n4C1O8HrfsA0P5aMINxGfTuJyUZuhMvr4URGSLRUewnZjAqA/spvjLEej8BPeNYlhmUZ+A5XvxkUNpPkizLij/JuXnzZvziF79AaWkpEhICwZ5//nm8++672Lhx4zmX9fl8KCsrw+TJk1FcXKx0kxE1YcIEnDx5EhkZGdiwYQMzCJ6hpKQECxcu1LytBQsWoLCwUFUGvTFDQFsv5Obmwmw2q1qHln4C2FHMEF4GvftJSQYjMEOA1o5iPzGDkRnYT/GVgf0kxuvADMoz8BwvfjIo7aewrpTasWMHBg0a1F5YAHDxxRfjf/7nfxSv45SrHhNXzQpns+0c1gSsnbYEU9fMhcsT/uV6tc117X8zg/gZXJWnVGU72/Jtq/Fyc/D/qcbKfoiHDE2uelXb7SgS/QSo7yit+wDQ/lowg3EZ9O4nJRm6Ey+vhREZtHYU+4kZjMzAfoqvDLHeT0DPOJZlBuUZeI4XPxmU9lNYk1IZGRmoqqpCa2srbDYbAGD//v3o37+/4nXIsoxmj7ZL9lyeFlXraLsojBliI4MvJTIf6fImo8ttxMp+iKcMWkSin9qyaNkPavdB27aZITYy6N1PSjIo1dNfCyMzqMV+YgYjM7Cf4jODWqL0E9AzjmWZged4zBCcoTth3ei8oKAAVqsVDz/8MA4cOIBNmzbhf/7nf3DbbbeFHZCoO+b0BJjS7JrWYUqzw5yu/nP6FDvYT2Qk9hOFg/1ERmI/UTjYT2Q0dhSdLaxJqeTkZLzyyiuoqanBlClTsGjRItx///2YNm2aXvkoztlzUqO6PMUO9hMZjf1ESrGfyGjsJ1KK/UTRwI6ijsL+9r0hQ4bg5Zdf1iMLURDr0BS0fFkLuckLhHN1sgRIvSywDk3RLRuJh/1ERmI/UTjYT2Qk9hOFg/1ERmNHUUdhXSlFZDTJYkLSTQMBmwlQ+vFjCYAtsJxk4VuciPTBfiIiUbGfiEhk7CjqiK8mCc/stKHXlMGQeim7sE/qZUGvKYNhdtp0TkZE8Y79RESiYj8RkcjYUdQm7I/vEUWD2WlD8vQL4dnTAHdFHfy17qDnmNLssOekwjo0hbPnRGQY9hMRiYr9REQiY0cRwEkpiiGSxQRbthO2bCd8NS2wNAKz86Zj+bbV8CaD38BARFHDfiIiUbGfiEhk7CjiVCPFJHN6AhxZqSgsLIQjK5VlRUTCYD8RkajYT0QkMnZUfOKkFBERERERERERGY6TUkREREREREREZDhOShERERERERERkeEkWZZlIzbk9XpRXl6O8RPGwyUH31VfCUmS0NvhxClXPdTEll0+QAYgAZLDzAzMwAyCZHBIdmzcsBGjR4+GxRKd71/Q2lFa9wGg/bVgBmZgBn0yRLuj2E/MwAzMEEqs9xPQM45lmYEZmCGY0n4yrLn8fj8AYOOGjUZtkohiTFtPRHPb7CgiCiVaHcV+IqLusJ+ISFTd9ZNhV0r5/X54vV6YTCZIkmTEJokoRsiyDL/fD4vFApMpOp8qZkcRUSjR7ij2ExGFwn4iIlEp7SfDJqWIiIiIiIiIiIja8EbnRERERERERERkOE5KERERERERERGR4TgpRUREREREREREhuOkFBERERERERERGY6TUkREREREREREZDhOShERERERERERkeE4KUVERERERERERIaLqUmpkpISZGVl4a233jJ0u1lZWZ3+XH755Xj44Ydx5swZQ3MAwOnTp/HUU0+hoKAAo0ePxvjx4/HKK6/A7/frvu2CgoL2fTB8+HDk5eXhlltuwSeffKL7trvKcPafLVu2RD3HrbfealiG5uZmPPvss7jhhhuQk5ODyy67DPPmzcOePXsM2X5BQQFKSkqCHi8pKUFBQYEhGUQT7x0V7/10do5odRT7if3UFfYT+4n99L1odhT7KRj7KXr9BIjRUSL007ly8BhK346y6LJWnbz//vsYOHAg3nnnHdx8882GbnvJkiXIy8uD3+/HsWPH8Mgjj+Dpp5/GY489ZliGuro6TJs2DRkZGXjyySfRv39/bN++HY8//jgOHz6M//zP/9Q9w4IFCzBhwgT4/X6cPn0a69evx7333osXXngBP/rRj3TffscMZzvvvPMM2f65clitVkO2febMGUyfPh3Nzc146KGHMHz4cNTV1eH111/HLbfcgvXr12PAgAGGZKHvxXNHsZ+Cc5zNyI5iP9HZ2E/sp445zhYv/QSwo0TEfopuPwFidJQI/RQqB4+h9BUzk1LffvstNm/ejIULF+Khhx7C4cOHDX1BzjvvPKSnpwMA+vTpg3vvvRePPfaYoZNSf/zjH2Gz2fDiiy/CbrcDAAYMGICEhATMnj0bM2fOxAUXXKBrhuTk5E774de//jVqamqwaNEivPfee7puu6sM0RTNHMuWLcO3336LDRs2ICUlBQDQr18/LFq0CMeOHcMrr7xi2P+JUUC8dxT7qesc0cJ+oo7YT+ynrnJES7QzsKPEwn6Kfj8BYnRUtLtBhBzx2k8x8/G9Dz74AMnJybjpppuQkZGBd955J6p5HA6HodtrbW3F+++/jxkzZrQXVptrrrkGr7zyCvr162dopjbTpk3D7t27UVVVFZXtxxu/34+3334bd955Z3tZdfT000/jwQcfjEKy+BbPHcV+ojbsJzGxn9hPFMCOEg/7Scx+AthRRovnfoqZSan3338fV199NUwmEwoKCrB+/XrIshyVLKdOncJrr72Gm266ybBtHjp0CM3NzRg1alTQzyRJwuWXXw6bzWZYno4uuugiAMDevXujsv14c+jQIZw6dQqXXnpplz/PyMhAQkKCwakonjuK/URt2E9iYj+xnyiAHSUe9pOY/QSwo4wWz/0UEx/fO3bsGL766ivceeedAICf/OQneOONN7B169aQL1qkzZo1C2azGbIsw+Vywel04ve//70h2waAhoYGAIHLCUXTlsmomwI++uijePzxxzs9lpmZiffff9+Q7Z8rx2effYbExERdt1tXVweg8+er//nPf+KBBx5o/7dR+6OrfeD1eoW49NZI8d5R7KfOROgo9hP7qQ37if3UUTz3EyBOR7GfAthP4vYTwHO8jngMpW9HxcSk1Pvvvw+73Y4f//jHAICxY8fivPPOw9tvv21YYT3xxBMYPXo0ZFlGXV0dVq1ahVtvvRXvvfcezj//fN2373Q6AQS+nUE0TU1NAIBevXoZsr158+bhJz/5SafHLBbj38pd5TDikt+2yznb/o8MAPLy8rB+/XoAwEcffYQ33nhD9xxA1/vAyO2LIt47iv3UmQgdxX5iP7VhPzkBsJ/axHM/AeJ0FPspgP3kBCBmPwE8x+uIx1D6bj9mJqVaWlowZsyY9sd8Ph8++OAD/Od//qchl7H16dMHgwYNAgAMHjwYI0aMwGWXXYaNGzdi5syZum9/4MCBSE5Oxtdff42cnJygn99///247bbbDP0Glza7du0CAAwdOtSQ7Z1//vntr0U0RSvHoEGD4HQ6sW3btvb3gsPhaM9ixCRpm672gZHbF0W8dxT7qTMROor9xH5qw35iP3UUz/0EiNNR7KcA9pO4/QTwHM9oovRT27aM7Cjh7yl14MABfPPNN3j44Yexfv369j9/+tOf0NTUhI8//jgquUwmE2RZhs/nM2R7FosFEyZMwOuvv47W1tZOP9u0aRM2bdqEjIwMQ7Kcrbi4GCNGjOiRX08pIovFgsmTJ+PVV19t/w1GRydOnIhCqvjFjmI/0ffYT2JhP7GfqDN2lDjYT2L3E8COMlo895PwV0q9//77cDqdmDZtWqcbvQ0bNgzLli3D+vXrMXHiRN1znD59GjU1NQACn6t96aWX4PP5UFBQoPu228ydOxc333wz7r77bsydOxc/+MEPsGXLFixevBi33347hgwZonuGxsZG1NTUtF/ium7dOmzYsAEvvfSS7ts+O8PZkpKSDLkfgQjmzp2LrVu34pZbbsGcOXMwYsQI1NXV4a233sK6devw05/+NNoR4wY7KoD9FJzjbPHSUewncbCfAthPwTnOFi/9BLCjRMF+ChChnwAxOor9FL/9FBOTUhMnTuzymwduvfVWPPnkkzhx4gT69Omja465c+e2/2+Hw4GRI0di5cqVhs4cp6en44033sCSJUswf/581NfXY+DAgZg3bx5uvfVWQzIsXLgQCxcuhCRJ6N27Ny6++GK88sorhn3uu2OGs/3Hf/wHZs+ebViOaHI4HHjttdfw6quvYvny5aiqqoLNZkNOTg6WLFmC6667LtoR4wY7KoD9FJzjbPHSUewncbCfAthPwTnOFi/9BLCjRMF+ChChnwAxOor9FL/9JMnR+s5NIiIiIiIiIiKKW8LfU4qIiIiIiIiIiHoeTkoREREREREREZHhOClFRERERERERESG46QUEREREREREREZjpNSRERERERERERkOE5KERERERERERGR4TgpRUREREREREREhuOkVA9UVFSE3/72t50e++tf/4qsrCwsWbKk0+PLly/Hz372s06PybKMu+66CyUlJZ0er6urw9y5c5GXl4eCggK888473WaZOXMmvvrqq3M+54UXXkBBQUGnx3bv3o2ZM2ciLy8P48aNw1//+tdut3XNNdfgxIkTQY8XFBQgKyur/c+ll16KefPm4dtvv+30vA8++ADjxo1Dbm4u7rrrLhw9erTbbRJR+NR01JYtWzqN445/qqurQ27rN7/5Dd57771z5tm4cSOysrLa/11SUtLldoYPH37O9YTqu9tuu63TevLy8nD33Xejqqqqy/W8++67uO2224Ief+WVV3DVVVchLy8PCxYsgMvlOmceIgqfXsdQAFBfX48f/ehHOHLkSLc51B4/nT59Gr/61a+Ql5eHf/u3f8Nf/vKXbrel5fgpVC+vX7++2+0SUfjUdtTp06cxf/58jB07FldddRX++Mc/wu/3n3Nbao6hAODjjz8O6oR58+adcz16H0MBwMMPPxy0j0gMnJTqgS699FJs376902NbtmxBRkYGtmzZ0unxsrIyjB07tv3ffr8fTzzxBD777LOg9f72t79FY2Mj1qxZg/vvvx8PP/wwKioqQuZwuVzYs2cPcnJyQj7n8OHDWLp0aafHWltbcd999+Hiiy/GO++8g1mzZuGhhx4K+m/qqKqqCgkJCejTp0+XP1+wYAE+/fRT/L//9//w2muv4fTp0/jNb37T/vOvvvoKv/rVr3DnnXeipKQENpsNv/zlL0Nuj4jUU9NReXl5+PTTTzv9ufTSS3HdddchMzMz5LY+//xzXH755SF/3tDQgCeffLLTYxMmTOi0nX/84x8YNGgQbr/99pDr6a7v7rrrLnz66af45JNPsHbtWjidTsyePRuyLAflfeSRR4KW//DDD7F06VL813/9F1599VWUl5dj8eLFIfMQkTp6HUOdPn0a9913X9AvxLqi9vgJAH71q1/hyJEjWLNmDRYsWIBnnnkGn3zyScj1aD1+OruX77nnHvTr1w/XXnttt/+dRBQ+tR312GOP4eTJk3j99dexePFivP32291OWqs5hgKAvXv34pprrunUDU888UTI9eh9DAUAK1euxFtvvRUyA0UXJ6V6oDFjxmDfvn04c+ZM+2NbtmzB3XffjbKyMrS0tLQ/Xl5e3l5WJ06cwL//+79j06ZNSElJ6bTOQ4cO4X//93/xxBNPYNiwYbj55ptx0003YfXq1SFz/Otf/0Jubi4sFkvI5zz66KPIzs7u9NjevXtx9OhR/Md//AcGDhyIKVOmYNiwYfjiiy9Crmfz5s244oorQv48OTkZ6enp6NOnD7Kzs/F//s//wSeffILGxkYAwEsvvYSbbroJt9xyCy688EL87ne/Q01NDU6dOhVynUSkjpqOstlsSE9Pb/+zZcsW7N69G48//njI7ezfv7997Ify9NNPY8CAAZ0eS0hI6LStd999F7IsY/78+SHX013fJSYmIj09HRkZGRg6dCgeeugh7N27F7t27Wp/ztKlSzFr1qygPADwl7/8Bf/+7/+Oa665Bjk5OXjsscdQXFzMq6WIIkyPY6h//etfKCwsRHNzs6IMao+fKisr8c9//hPPPPMMhg0bhhtuuAFTpkw55xVXWo+fOnZlS0sLXnvtNTzxxBNITk5W9N9KROFR21GlpaW48847MXToUFx++eX46U9/is2bN4fcjtpjKADYt28fhg0b1qkfzu7FjvQ8hmpqasK8efOwcuVK9O3bN2QGii5OSvVAo0aNgtVqxddffw0AOH78OKqrq3HzzTcjOTm5/eDkwIEDOH36NC699FIAwNdff42+ffuiuLg46GCivLwcffv2Rf/+/dsfGzNmDLZt2xYyR3cHOuvXr4fL5cKUKVM6PX7eeecBAN566y34/X5s27YN+/fvx8UXX6x6W2dzOByQJKn931988QWuv/769n8PGDAAmzZtQu/evRWvk4iUUdtRbTweD5599lncd9995xyjmzdvPudv+L744gt88cUXuO+++0I+p76+HitXrsSvfvUr2Gy2c24r3A4622effYYXX3wRP/nJTzo97vP5sH379k77ITc3Fx6PB5WVlYq3SUTd0+MY6tNPP8XkyZMVf2xE7fHTF198geHDh3c6KXvkkUfwH//xH6q3dbazj586eu6553DFFVfgRz/6keL1EVF41HaU0+nEu+++C5fLhRMnTuCTTz4JmtjuSMsx1L59+zB48GDF/016HkMdOXIEbrcbJSUlXU6gkRg4KdUD2Ww2jB49uv2jdZ9//jlGjhyJpKQk/PCHP2y/tLOsrAxDhw5FamoqgMC9A55++ukuT/JqamqQkZHR6bHzzz+/y3sQtDnXJZ+nTp3CM888g//6r/8KOrjp168ffvnLX+KZZ57ByJEjccstt+Cee+4JWVayLOPLL7/sdAn9uZw5cwYvvPACrr76aiQnJ6OhoQGnT5+Gz+fD3XffjSuvvBL333//Of/biEg9tR3VZuPGjWhsbMSMGTPOuZ3PP/88ZG+0trbiP//zP/HII48gISEh5DreeOMNZGRk4IYbbuh2W+c6eDt72//zP//Tfn+EjtvqqscaGhrgdrs7dbDFYoHT6cTx48cVbZOIlNHjGOoXv/gFZs+eDbPZrCiD2uOnw4cPo3///njxxRdRUFCAG264AW+++WbI7Wg9fuqouroaf/3rXzF79mxF6yIiddR21KOPPorNmzfjkksuwb/9278hIyMDc+bMCbkdtcdQsizjwIED+PTTTzFu3Dhcd911eOaZZ9Da2nrObel1DDV8+HD8+c9/7nRhBYmHk1I91KWXXtpeVlu2bMFll10GABg7dmynslJ6IOJyuYKuErDZbCELpr6+HidOnAi68V2bhQsX4uc//zmGDh0a9DOPx4P9+/dj2rRpeOutt/Db3/4WK1euDPqcdJvKykr07du3/Qqrrjz66KPIy8tDbm4uxowZgw8++AD33nsvALRfTv/EE09g4sSJeP7559Ha2op777232xsAEpE6Wjpq7dq1mDJlyjknk/x+P/71r3+F7Lhly5ZhxIgR+PGPfxxyHbIs46233sLMmTPP+d/SXd8BwJ///Gfk5eUhLy8Po0ePxgsvvIA5c+aEvOKgo7ZL8cPpYCJSL9LHUOHQcvzU3NyMf/7zn9i6dSv+7//9v5g1axYWLVqEDz/8sMt1aT1+6mjdunUYOXIkRo8erfC/lIjUUtNRBw4cwMiRI/HGG29g6dKl2LNnD1auXNnl+rUcQ1VXV7efNz777LPtN0t/+umnu1yX3sdQFBs4KdVDdbwJ3pYtW9pLZezYsdixYwdaW1tRVlaGH/7wh4rWZ7fbg05+WltbQ54Utm2zq7L45JNPUFZWhgceeKDLZdevX48dO3bg4YcfxogRI3DHHXdg4sSJIYtTySWf8+bNw/r16/HOO+/grbfewq233oq77roLe/bsaf/N5c0334xJkyYhJycHzzzzDHbv3o2ysrJzrpeI1FHbUd9++y3+9a9/4aabbjrn+r/55hsMGDCgy/ua7N69G2vXrsWCBQvOuY7t27fjxIkTuPHGG8/5vHP1XZtbbrkF69evx/r161FSUoJf/OIX+OUvf3nO+zm0sdvtANBlB3d1CTsRaRPpY6hwaDl+MpvN8Pl8eOaZZzBq1ChMnjwZU6dOxZo1a7p8vtbjp44+/PDDbnuZiCIj3I46ePAg/vCHP2DhwoXIzc3F9ddfj1//+tdYuXIlvF5v0Pq1HEP169cPW7ZswaJFi5CdnY3rr78eCxYswNq1a+Hz+YKer/cxFMWG0HdQpJiWl5eHkydPYvv27Th58iQuueQSAMDQoUORnJyML7/8Env37lX8W74+ffqgtra202O1tbUhb353rgOdDRs24Pjx4+0/93q98Hg8yMvLw8qVK/H1119j2LBhncopOzs75I06N2/ejDvuuOOc+c8//3wMGjSo/d+jRo1CaWkpSkpK8Ktf/QpWqxUXXnhh+89TU1P50RgiHantqE8++QT9+/c/52/UgHN30EcffYTTp0+330eu7SApLy8Pjz32WPuJ1SeffIJLL730nFcRdLetNuedd16nDsrOzsaXX36JN954o9tlnU4n7HY7amtrcdFFFwEI9GZ9ff05b0BKROpE+hgqHFqOnzIyMvCDH/wAiYmJ7ctccMEF+PTTT0NuS8vxU9u38B07dgx79+7lN+4RGSTcjvrmm2+Qmpra6TYAF198Mc6cOYPTp0/j/PPP77R+rcdQTqez0zIXXXQR3G43Tp8+HfQRZ72PoSg28EqpHioxMRHZ2dlYs2YNRo0a1f7bdEmS8MMf/hAlJSUYPHiw4ht55+bm4ujRo50mabZu3Yrc3Nwun3+ugpk/fz7ef//99hnvefPmISMjA+vXr8fIkSORkZGBvXv3dlrmwIEDXX4W2OPxoKKiAmPGjFH033E2n88Hi8WCESNGdLph8KlTp1BXV4d+/fqpWi8RnZvajqqoqGg/+DqXc92fYObMmdi4cWN7B7V9TfH69etRUFAQ9rbCvUFnG1mWu/yt4dlMJhNGjRqFrVu3tj9WVlYGi8WC4cOHh71dIjq3SB9DhUPL8dPo0aNx9OjR9m/GAwLfoNXVsUwkjp/atH0ZTmZmpqp1EVF4wu2ojIwM1NXV4dtvv21fx/79+5GYmNhlj2k5hvrkk09w2WWXdfp24J07d8LpdHa5Lb2PoSg2cFKqB/vhD3+I999/P+g3eWPHjsXf//73sC47HzBgAH784x/jwQcfRGVlJd566y389a9/7fJGw8ePH4fH4wn5DQdtv3Vr+3P++efDYrFg0KBBSEhIwMSJE3H48GEsXrwYhw4dwvr167F27VrcdtttQesqLy/HsGHDznlvGQBobGxETU0NampqcOTIESxZsgRVVVXtNy++88478dprr2Hjxo3Yt28fFixYgOzsbOTk5CjeR0QUHjUdtWfPHgwZMuSc621tbcWOHTtCTig5nc5OHdSnTx8AwKBBg9CrV6+wttVd37Vpbm5u76Bjx47h9ddfx+bNmzF+/PhzLtdm+vTpePHFF/G3v/0NFRUV+P3vf4+pU6fy43tEOonkMZRSWo+ffvSjH+GCCy7Ab37zG+zbtw8bNmxo/8jd2SJ1/AQEurLtKk4iMkY4HZWbm4uLLroIv/71r7Fnzx588cUXePrppzFz5sygj81pPYbKy8uD3W7Hww8/jP3796O0tBRPP/007rnnnqB1GXUMReLjx/d6sDFjxuCll15qv/ldm7Fjx8LlcoV92fnTTz+N3/3ud5g6dSrS09OxcOHCLidtuvsK0e4MGDAAL730Ep5++mmsXr0amZmZePLJJ3HVVVcFPVfptzUsXLgQCxcuBBC4P8uQIUPw7LPPthfuDTfcgIaGBixevBjffvstxo4di+XLl/MGekQ6UtNRtbW1SElJOed6y8rKMHz48PZ7MamlZFtK++6ll17CSy+9BACwWq0YNGgQHnnkEfz0pz9VlOXGG2/E0aNH8cgjj6C1tRU/+clP8OCDDypalojCF+ljKCW0Hj+ZzWasWLECjz76KAoLC5GamoqHHnqoy4/VRer4CQh0ZXcfcyaiyAqnoywWC1auXIknn3wSM2bMQGJiIn72s591+e17Wo+hevXqhRdffBELFy7E5MmTkZSU1P5N6mcz6hiKxCfJsixHOwQREREREREREcUXfnyPiIiIiIiIiIgMx0kpIiIiIiIiIiIyHCeliIiIiIiIiIjIcJyUIiIiIiIiIiIiw3FSioiIiIiIiIiIDMdJKSIiIiIiIiIiMhwnpYiIiIiIiIiIyHCclCIiIiIiIiIiIsNxUoqIiIiIiIiIiAzHSSkiIiIiIiIiIjIcJ6WIiIiIiIiIiMhwnJQiIiIiIiIiIiLDcVKKiIiIiIiIiIgMx0kpIiIiIiIiIiIyHCeliIiIiIiIiIjIcJyUIiIiIiIiIiIiw1mM2pDf74fX64XJZIIkSUZtlohigCzL8Pv9sFgsMJmiM1fOjiKiUKLdUewnIgqF/UREolLaT4ZNSnm9Xmzfvt2ozRFRDBo1ahRsNltUts2OIqLuRKuj2E9E1B32ExGJqrt+MmxSqm1mbPyE8XDJblXrkCQJvR1OnHLVQ5blsJeXXT5ABiABksPMDMzADIJkcEh2bNywMWpXSQHaO0rrPgC0vxbMwAzMoE+GaHcU+4kZmIEZQon1fgJ6xrEsMzADMwRT2k+GTUq1Xc7pkt0wT81UtY5EqwPFM1di4qpZaPa4wl6+4ZW9kM94ISVZkDJ1CDMwAzMIksG1thrA9z0RDVo7Sus+ALS/FszADMygT4ZodxT7iRmYgRlCifV+AnrGsSwzMAMzBFPaT7zRORERERERERERGY6TUkREREREREREZDhOShERERERERERkeE4KUVEmuT0z8akvHFIS0vDpLxxyOmfHe1IREQA2E9EJC72ExGJzMiOMuxG50TUcyRY7Zg8ZgKK8mdi9ICL2x9ffvsiAED54W+wonQVirduQItH3TexEBGpwX4iIlGxn4hIZNHqKF4pRURhuShjML54+H0snfEkRvbL6vI5I/tlYemMJ/HFw+/jwvRBBickonjFfiIiUbGfiEhk0ewoTkoRkWIXZQzG3+a/iUxnH0iSBLPJ3OXzzCYzJElCprMP/v7gGh5YEZHu2E9EJCr2ExGJLNodpXpSqrW1FT/96U+xZcuWiAQhIrElWO14+4EXkGxPgsWs7JO/FrMFyfYkrJ/zIhKsdp0Tfo/9RBRf2E9EJCr2ExGJTISOUjUp5Xa78ctf/hJ79uzRHICIYsPkMRMwoHem4rJqYzFbMPD8fii8ZLxOyTpjPxHFH/YTEYmK/UREIhOho8KelNq7dy+mTp2KQ4cOad44EcWOovyZ8Mt+Vcv6/D4U5c+McKJg7Cei+MR+IiJRsZ+ISGQidFTYk1JffPEFLrvsMqxZs0bzxokoNuT0z8boAReH/Hxxd8wmM3IHjtD9647ZT0Txh/1ERKJiPxGRyETpqPCu0QIwffp0TRuUJAmJVoeqZR3WhE5/h6tRkiAzAzMwQ9gZRmZ2/Q0M4RqROQx7TxwMerxJkiKyfq39BKh/LbS+DoD29wMzMEM8ZtC7n4DIdBT7iRmYIf4ysJ+UiZfjaWZgBtEyiHKOJ8myLKvdeFZWFv7yl7/gsssu6/a5Pp8PZWVlmDx5MoqLi9VuUpMJEybg5MmTyMjIwIYNG5iBGZhBYYa0tDQMGqT92xWqqqpQW1sb9HhbL+Tm5sJsVjdTf7Zw+glgRzEDM8RqBr37CYh8R7GfmIEZ4iMD+8kYsfBeYAZmEDGDKOd4YV8ppdUpVz0mrpqlalmHNQFrpy3B1DVz4fK0hL18bXNd+9/MwAzMoDzDpLxxWH77IlX5Onqq9Hm8s+2joMebXPWa1x0pajtK6+sAaH8/MAMzxGMGvfsJEKej2E/MwAyxlYH9pEy8HE8zAzOIlkGUczzDJ6VkWUazx6VpHS5Pi6p1tF0UxgzMwAzhZdhRvUtTtvb1HN3V5TY0XLAZcVpfC7WvQ9u2mYEZmCG8DHr3U8cM0Sby68AMzMAM7CeRj2WZgRmYIZgo53hh3+iciOJPxZGdKD/8DXx+n6rlfX4fyg59je1HKyOcjIjiHfuJiETFfiIikYnSUZyUIiJFVpSugklSVxlmkxkrSldFOBERUQD7iYhExX4iIpGJ0FGclCIiRYq3bsDhU9Xw+rxhLef1eXHo26Mo+WqjTsmIKN6xn4hIVOwnIhKZCB2laVJq165dir+ZgYhiW4vHjZ8vuweN7jOKS8vr86LRfQaTlt6NFo9b54SdsZ+I4gf7iYhExX4iIpGJ0FG8UoqIFNt38iCuXTwN1fUnACDk54/bHq+uP4FrF0/D/poqwzISUXxiPxGRqNhPRCSyaHeU4d++R0SxbX9NFcY+cSMKLxmPovyZyB04Iug5249UYkXpKpR8tdHw3/ARUfxiPxGRqNhPRCSyaHYUJ6WIKGwtHjdWb1mP1VvWI6d/NkZkDsND+ffjqdLn8XX1blQc2RntiEQUp9hPRCQq9hMRiSxaHcVJKSLSpOLITuw9cRD3jLgZ72z7CM0eV7QjEREBYD8RkbjYT0QkMiM7iveUIiIiIiIiIiIiw3FSioiIiIiIiIiIDMdJKSIiIiIiIiIiMpwky7JsxIZ8Ph/KysqQf3U+mmV1d2qXJAlpiamoba6DmthysxeQAUiAlKjudlrMwAzMEPkMiZIdpf8oRW5uLsxms6oMWmntKK37AND+WjADMzCDPhmi3VHsJ2ZgBmYIJdb7CegZx7LMwAzMEExpPxl/o3MZkM941S6Kk00nmYEZmKGnZUiyq1820lTuh4i9DszADMwgXgZROireXwdmYAZmCBbj/fTdorF/LMsMzMAMwRT2k/GTUhIgJcXvbCEzMAMzdLUCVZvVh8qO6im/cWUGZmCGrlaibrGIYz8xAzMwQ9BK1C0WcTzHYwZmYIagFSh7muGTUpLDjJSpQ1Qtm2h14L2ZKzFx1SxVX0nY8MpeyGe8kBItSLmDGZiBGUTJ4FtbrWq7elDbUVr3AaD9tWAGZmAGfTKI0lHsJ2ZgBmY4W6z3E9AzjmWZgRmYIZjSfuKNzomIiIiIiIiIyHCclCIiIiIiIiIiIsNxUoqIiIiIiIiIiAzHSSmKSb6aFrgqT6GkpASuylPw1bREO1JU5PTPxqS8cUhLS8OkvHHI6Z8d7UhEcY/9FMB+IhIP+ymA/UQkJnZUQLx1lPHfvkekkuz1w7OnAe6KOvhr3QCAhR8sbP+5Kc0Oe04qrENTIFl67nxrgtWOyWMmoCh/JkYPuLj98eW3LwIAlB/+BitKV6F46wa0eNzRikkUV9hPAewnIvGwnwLYT0RiYkcFxHNHcVKKYoKvvhVn3j0EudEb8jn+Wjdcm46j5ctaJN00EGanzcCExrgoYzDefuAFDOidCb/s7/I5I/tlYemMJ/Gb8Q9g0tK7sb+myuCURPGF/RTAfiISD/spgP1EJCZ2VEC8d1TPnWqkHsNX34qmdQchN4Uuq47kJi+a1h2Er75V52TGuihjMP42/01kOvtAkiSYTeYun2c2mSFJEjKdffD3B9fgwvRBBiclih/spwD2E5F42E8B7CciMbGjAthRYU5KnThxAvPmzcPYsWNx1VVXYdGiRXC7e9alYyQW2evHmXcPAa1+QFa6EIDWwHKyt+uZ5liTYLXj7QdeQLI9CRazsgscLWYLku1JWD/nRSRY7TonFAM7iozEfgpgPynDfiIjsZ8C2E/KsJ/IaOyoAHZUgOJJKVmWMW/ePLhcLrz++uv405/+hP/93//Fs88+q2M8ineePQ2ByzmVllUbGZAbvfDsadAll9Emj5mAAb0zFZdVG4vZgoHn90PhJeN1SiYOdhQZjf0UwH7qHvuJjMZ+CmA/dY/9RNHAjgpgRwUonpTav38/ysrKsGjRIgwdOhSXXnop5s2bh7/+9a965qM4566oi+ryoijKnxny88Xd8fl9KMqfGeFE4mFHkdHYTwHsp+6xn8ho7KcA9lP32E8UDeyoAHZUgOJJqfT0dLzwwgtIS0vr9HhTU1PEQxEBga8EbfsGBrX8te6Y/yrRnP7ZGD3g4pCfL+6O2WRG7sARPf6rRNlRZCT2UwD7SRn2ExmJ/RTAflKG/URGY0cFsKO+p/g6sZSUFFx11VXt//b7/Vi1ahUuv/zysDYoSRISrY6wlmnjsCZ0+jtcjZIEmRliJoOrwaVq3WezNAKOzOBtxMp+GJmZpWrdZxuROQx7TxxUlaE7WvdDkySpWq6jaHeU1n0AaH8tmMG4DHr3k5IM3TFiP+jdT0oydCcS+0FrR7GfmMHIDOynAPaTMtHuJyB+zm2YIYDneAE8x/ueJMtyuJ/kBAD84Q9/wOuvv45169Zh2LBh3T7f5/OhrKwMkydPRnFxsZpNajZhwgScPHkSGRkZ2LBhAzMInqGkpAQLFy7UvK0FCxagsLBQVQa9KcmQlpaGQYO0f7tCVVUVamtrVWXQW1sv5ObmwmxW99uCs7GjmEHPDHr3k5IMRugug979pCSDESLdUewnZtAzA/spgP2kDvuJGfTOwHO8AJ7jfS+8O2p9Z/HixXj11Vfxpz/9SVFZdXTKVY+Jq2ap2Swc1gSsnbYEU9fMhcsT/uV6tc117X8zg/gZXJWnVGU72/Jtq/Fy80ZVGbpjxH6YlDcOy29fpCpfR0+VPo93tn2kKkN3tO6HJle9qu2GEo2O0roPAO2vBTMYl0HvflKSoTtG7Ae9+0lJhu5EYj9EsqPYT8zAfmI/tWE/BcTLuQ0zBPAcL4DneN8Le1Lq8ccfxxtvvIHFixdj3Lhx4S4OWZbR7NF2yZ7L06JqHW0XhTFDbGTwpWj/SBcAeJPR5TZiZT/sqN6lKVv7eo7uEn4/REK0O0rtPmjbNjPERga9+0lJBqX03A9695OSDEpFYj9oxX5iBiMysJ8C2E/hiXY/AT3/3IYZAniOF8BzvO8pvtE5ACxduhRvvvkm/vu//xs33nhj2KGIwmFOT4Apza5pHaY0O8zp6j+nL4KKIztRfvgb+Pw+Vcv7/D6UHfoa249WRjiZeNhRZBT2UwD7STn2ExmF/RTAflKO/URGYkcFsKO+p3hSat++fVi+fDlmzZqFMWPGoKampv0PkV7sOalRXV4UK0pXwSSFNYfczmwyY0XpqggnEg87iozGfgpgP3WP/URGYz8FsJ+6x36iaGBHBbCjAhTvgb///e/w+Xx4/vnn8eMf/7jTHyK9WIemQEq2AOFe5SkBUrIF1qEpuuQyWvHWDTh8qhpenzes5bw+Lw59exQlX3V9T4iehB1FRmM/BbCfusd+IqOxnwLYT91jP1E0sKMC2FEBiielioqKsGvXri7/EOlFspiQdNNAwGZSXloSAFtgOcmibuZZNC0eN36+7B40us8oLi2vz4tG9xlMWno3WjxunRNGHzuKjMZ+CmA/dY/9REZjPwWwn7rHfqJoYEcFsKMCesarST2a2WlDrymDIfVSdl9+qZcFvaYMhtlp0zmZsfadPIhrF09Ddf0JAAj5+eO2x6vrT+DaxdOwv6bKsIxE8Yb9FMB+IhIP+ymA/UQkJnZUADtKxbfvEUWD2WlD8vQL4dnTAHdFHfy1wbPCpjQ77DmpgctBe8js+dn211Rh7BM3ovCS8SjKn4ncgSOCnrP9SCVWlK5CyVcbe8zsOZHI2E8B7Cci8bCfAthPRGJiRwXEe0dxUopihmQxwZbthC3bCV9NCyyNwOy86Vi+bTW8yYj5b2BQqsXjxuot67F6y3rk9M/GiMxheCj/fjxV+jy+rt6NiiM7ox2RKO6wnwLYT0TiYT8FsJ+IxMSOCojnjuqZU43U45nTE+DISkVhYSEcWalxU1ZnqziyE+9s+wi1tbV4Z9tHPbqsiGIF+ymA/UQkHvZTAPuJSEzsqIB46yhOShERERERERERkeE4KUVERERERERERIbjpBQRERERERERERlOkmVZNmJDPp8PZWVlyL86H82yurvFS5KEtMRU1DbXQU1sudkLyAAkQEpUd493ZmAGZoh8hkTJjtJ/lCI3Nxdms1lVBq20dpTWfQBofy2YgRmYQZ8M0e4o9hMzMAMzhBLr/QT0jGNZZmAGZgimtJ+M//Y9GZDPeNUuipNNJ5mBGZihp2VIsqtfNtJU7oeIvQ7MwAzMIF4GUToq3l8HZmAGZggW4/303aKxfyzLDMzADMEU9pPxk1ISICXF72whMzADM3S1AlWb1YfKjuopv3FlBmZghq5Wom6xiGM/MQMzMEPQStQtFnE8x2MGZmCGoBUoe5rhk1KSw4yUqUNULZtodeC9mSsxcdUsNHtcYS/f8MpeyGe8kBItSLmDGZiBGUTJ4FtbrWq7elDbUVr3AaD9tWAGZmAGfTKI0lHsJ2ZgBmY4W6z3E9AzjmWZgRmYIZjSfuKNzomIiIiIiIiIyHCclCL1/P5oJyAiIiIiIiKiGGX8PaUoZo2uacGMnfW4otqFrLpW2J4di4MmCbtSbdic6cDr2U6UpydEOyYRERERERERxQBOSlG3LqhvxdJNx3DlMRc8EmAdnQtcPxxIToatsRGjKisxvLwMRdvr8VlfB+YU9MUBp03XTDn9szEyMwtpaWmYlDcOO6p3oeLITl23yQxE4hNhTDCDOBmIRCLCmGAGcTIQiUaEcSFCBl9NC1wNLpSUlMBVeQq+FAlmgy+8EGE/GImTUnROU3afxrJNx2G22YE77oB13jwgLy/oedZt24DnnsNla97E528ewOyCvigelhLRLAlWOyaPmYCi/JkYPeDi9seX374IAFB++BusKF2F4q0b0OJxR3TbzEAkLhHGBDOIk4FIJCKMCWYQJwORaEQYFyJkkL1+ePY0wF1RB39tYBsLP1jY/nNTmh32nFRYh6ZAsuhzByQR9kO08J5SFNKU3aex4uNjsF44BJZvdgIvvQTk5HT95Jwc4KWXYPlmJ6wXXISVH1djyu7TEctyUcZgfPHw+1g640mM7JfV5XNG9svC0hlP4ouH38eF6YMitm1mIBKXCGOCGcTJQCQSEcYEM4iTgUg0IowLETL46lvRuHo/XJuOt09Inc1f64Zr03E0rt4PX31rxDOIsB+iiZNS1KUL61uxbNNxYOhQmD7/HOjXD5AkwGzuegGzOfDzfv1g2rIFGDIEyzYdxwURGLQXZQzG3+a/iUxnH0iSBLOp6wxmkxmSJCHT2Qd/f3BNRAcrMxCJR4QxwQziZCASiQhjghnEyUAkGhHGhQgZfPWtaFp3EHKTV9Hz5SYvmtYdjOjElAj7IdrCnpSqqqrC3Xffjby8PFx99dV44YUX9MhFUbZk0zGYbHaYPvoISE4GrFZlC1qtQHIyTB9/DLPNjqWbjmnKkWC14+0HXkCyPQkWs7JPm1rMFiTbk7B+zotIsNo1bZ8ZYgv7KX6IMCaYQZwMsYD9FD9EGBPMIE6GWMB+ii8ijAsRMsheP868ewho9QOy0oUAtAaWk73av4lehP0ggrAmpfx+P4qKipCamoq3334bjz32GJ5//nm89957euWjKBh9sgVXHnPBOu0WYNAg5RNSbaxWYPBgWKZOw5XHXBhd06I6y+QxEzCgd6biQdrGYrZg4Pn9UHjJeNXbZobYwn6KLyKMCWYQJ4Po2E/xRYQxwQziZBAd+yn+iDAuRMjg2dMAudGrfEKqjQzIjV549jRoziDCfhBBWJNStbW1yM7Oxu9//3sMHjwY+fn5uOKKK7B161a98lEUzKish0cCMG8e4Fc5A+zzAXPnwiMBM3bWq85SlD8TflldBp/fh6L8maq3zQyxhf0UX0QYE8wgTgbRsZ/iiwhjghnEySA69lP8EWFciJDBXVEX1eUBMfaDCMKalMrIyMCzzz6LXr16QZZlbN26FV9++SXGjh2rVz6KgiuqXbCOzg18y16oe0h1x2wGxoyBdXQuLj/mUrWKnP7ZGD3g4pCfq+02gsmM3IEjkNM/W9XyzBBb2E/xQ4QxwQziZIgF7Kf4IcKYYAZxMsQC9lN8EWFciJDBV9MS8qbmSvlr3fBp+ESQCPtBFOFdJ9ZBQUEBqqurcc0112DcuHGKl5MkCYlWh6ptOqwJnf4OV6MkQWaGbjNk1bUC1w9Xte7glWVheEV50HaU7IeRmV1/80C4RmQOw94TB4MeZwblGbqj9T3ZJEmqlgtFbT8B6veD1n0AaH8t4iWD3mOCGWIrQ3ci8Z6MZEexn3p2BhHGBDOIk6E77KeAeDi/EiWDCOcVImRwNai7aOJslkbAkRm8jVjZD90x6hxPkmU53E9RAgC2b9+O2tpa/P73v8f111+Phx9++JzP9/l8KCsrw+TJk1FcXKxmk5pNmDABJ0+eREZGBjZs2MAMXWXw+zFm7Fhg1ixgxQrtGysqAlauxNYvvgBM31+Yp2Q/pKWlYdAg7d8qUFVVhdra2qDHmUF5Br219UJubi7Maq/O6yDcfgLYUbGUQe8xwQyxlcEIkewo9lPPziDCmGAGcTIYgf0kxusQKxlEOK8QIUNJSQkWLlyoOcOCBQtQWFioKoMI+0FvSvtJ9ZVSo0aNAgC43W7Mnz8fv/71r2Gz2bpd7pSrHhNXzVK1TYc1AWunLcHUNXPh8oR/qVxtc13738wQOsNBkwRbY6OqbEEaGtBqkjBx9b1hZQCASXnjsPz2RZojPFX6PN7Z9lHQ48ygPEN3tL4nm1z1qrYbitp+AtR3lNZ9AGh/LeIlg95jghliK0N3IvGejGRHsZ96dgYRxgQziJOhO+yngHg4vxIlgwjnFSJkcFWe0rx9AFi+bTVebt6oKoMI+6E7Rp3jhTUpVVtbi7KyMlx33XXtjw0ZMgQejwdNTU3o3bt3t+uQZRnNHm2Xy7k8LarW0XZRGDOcO8OuVBtGVVZqytaushKVvW1B21GyH3ZU74pIhB1Hd3W5DWZQnkEpre9JLSLRT21ZtOwHtfugbdvM0H0GvccEM8RWBqUi8Z5Ui/0UPxlEGBPMIE4GpdhPAT35/EqUDCKcV4iQwZcSmY+9epMR0/tBKb3P8cK60fmRI0cwZ84cnDhxov2xHTt2oHfv3ooLi8S3OdMBT3kZsG1b4Fv01PD5gK1b4akox+d91X2GteLITpQf/gY+v7oMPr8PZYe+xvaj6ifYmCF2sJ/ihwhjghnEyRAL2E/xQ4QxwQziZIgF7Kf4IsK4ECGDOT0BpjS76uUBwJRmhzld/f3gRNgPoghrUmrUqFEYMWIEFixYgL1796K0tBSLFy/Gfffdp1c+ioLXs52wygCee67TfaDCYjYDS5bAKgfWp9aK0lUwSeoymE1mrChdpXrbzBBb2E/xRYQxwQziZBAd+ym+iDAmmEGcDKJjP8UfEcaFCBnsOalRXR4QYz+IIKw9YDabsXz5cjgcDkybNg2/+93vcNttt+H222/XKx9FQXl6Aj7r64B3zZtAVRXg8YS3Ao8HOHgQ3rVr8FlfB8o1zCAXb92Aw6eq4fV5w1rO6/Pi0LdHUfJV8Gd8maFnYj/FFxHGBDOIk0F07Kf4IsKYYAZxMoiO/RR/RBgXImSwDk2BlGwBwv0knwRIyRZYh6ZoziDCfhBB2NNyffr0wdKlS7F161Z8+umnuO+++yBF+OvcKfrmFPSFr9UN/09+AjQ2Kp+Y8niAxkb4r78evlY35hT01ZSjxePGz5fdg0b3GcWD1evzotF9BpOW3o0Wj1vT9pkhtrCf4ocIY4IZxMkQC9hP8UOEMcEM4mSIBeyn+CLCuBAhg2QxIemmgYDNpHxiSgJgCywnWVR+oqgDEfaDCLTvSeqRDjhtmF3QF9izB/7LLgOOHg38INQ9ptoeP3o08Py9ezG7oC8OOJV9Y8e57Dt5ENcunobq+sBn3UN97rbt8er6E7h28TTsr6nSvG1mIBKXCGOCGcTJQCQSEcYEM4iTgUg0IowLETKYnTb0mjIYUi9l3/8m9bKg15TBMEfgHLeNCPsh2sL69j2KL8XDUiBBxrJN+2C+OBuWqdOAuXOBMWOCn1xWBixZAu/aNfC1ujH7+kwUD9N+SWOb/TVVGPvEjSi8ZDyK8mcid+CIoOdsP1KJFaWrUPLVRl1mjZmBSDwijAlmECcDkUhEGBPMIE4GItGIMC5EyGB22pA8/UJ49jTAXVEHf23wNkxpdthzUgMf+YvAFVJnE2E/RBMnpeic1g07D1szHFi66RiufPVVeP7yKqyjc4GsLCAlBWhoAHbtgqe8DFYZ+DzTgbnXXBCRK6TO1uJxY/WW9Vi9ZT1y+mdjROYwPJR/P54qfR5fV+9GxZGdEd8mMxCJT4QxwQziZCASiQhjghnEyUAkGhHGhQgZJIsJtmwnbNlO+GpaYGkEZudNx/Jtq+FNhqZv2VNKhP0QLZyUom4dcNpwY+EgjK5pwYyd9bj8yE4MryiHzS+j1SShsrcNn4904vVsp6abmoej4shO7D1xEPeMuBnvbPsIzR6XIdtlBiKxiTAmmEGcDEQiEWFMMIM4GYhEI8K4ECGDOT0BjkwHCgsL8XLzxrjdD0bipBQpVp6egPL0HwAAEq0OvDf9z5i4+t4eP0iIiIiIiIiIKPJ4o3NSz8S3DxERERERERGpw1kFIiIiIiIiIiIyHCeliIiIiIiIiIjIcJIsy7IRG/L5fCgrK0P+1floltV9haEkSUhLTEVtcx3UxJabvYAMQAKkRHW302IGZmCGyGdIlOwo/UcpcnNzYTabVWXQSmtHad0HgPbXghmYgRn0yRDtjmI/MQMzMEMosd5PQM84lmUGZmCGYEr7yfgbncuAfMardlGcbDrJDMzADD0tQ5Jd/bKRpnI/ROx1YAZmYAbxMojSUfH+OjADMzBDsBjvp+8Wjf1jWWZgBmYIprCfjJ+UkgApKX5nC5mBGZihqxWo2qw+VHZUT/mNKzMwAzN0tRJ1i0Uc+4kZmIEZglaibrGI4zkeMzADMwStQNnTDJ+UkhxmpEwdomrZRKsD781ciYmrZqHZ4wp7+YZX9kI+44WUaEHKHczADMwgSgbf2mpV29WD2o7Sug8A7a8FMzADM+iTQZSOYj8xAzMww9livZ+AnnEsywzMwAzBlPYTb3RORERERERERESG46QUEREREREREZFI/P5oJzCE8feUIiIiIiIiIiKidqNrWjBjZz2uqHYhq64VtmfH4qBJwq5UGzZnOvB6thPl6QnRjhlxMTMp5atpgavBhZKSErgqT8GXIsFs8AvCDAE5/bMxMjMLaWlpmJQ3Djuqd6HiyE5DM3A/kEhEeD8yQ4AI45L7gUQiwvuRGQJEGJfMQKIRYWwyAzNEO8MF9a1YuukYrjzmgkcCdshAMYBGAMl+GcO/dePOU24Uba/HZ30dmFPQFwecNl0zGUnoSSnZ64dnTwPcFXXw17oBAAs/WNj+c1OaHfacVFiHpkCy6PNJRGYISLDaMXnMBBTlz8ToARe3P7789kUAgPLD32BF6SoUb92AFo9blwzcDyQSEd6PzBAgwrjkfiCRiPB+ZIYAEcYlM5BoRBibzMAMomSYsvs0lm06jlafjJcBPCcDZV08L1cG5gGYcsyFz988gNkFfVE8LCWiWaJF2EkpX30rzrx7CHKjN+Rz/LVuuDYdR8uXtUi6aSDMEZ4tZIaAizIG4+0HXsCA3pnwy11/rnVkvywsnfEkfjP+AUxaejf211RFNAP3A4lEhPcjMwSIMC65H0gkIrwfmSFAhHHJDCQaEcYmMzCDKBmm7D6NFR8fw24ANwCoQuibflcAuAvAYwA+9MlY+XE1JMhYN+y8iGSJJtXTfEVFRXjooYcimaWdr74VTesOQm4K/cboSG7yomndQfjqW5khwhkuyhiMv81/E5nOPpAkCWaTucvnmU1mSJKETGcf/P3BNbgwfVDEMnA/kBp6dZQI70dmCBBhXHI/kBrsp56fQYRxyQykBs/xmIEZjMlwYX0rlm06jt0AfgTgyHePh7q1edvjRwBcAWAPgGWbjuOCCO6PaFE1KfX++++jtLQ00lkABC6dO/PuIaDVD8hKFwLQGlhO9mq/Qz0zBCRY7Xj7gReQbE+CxazsojqL2YJkexLWz3kRCVa75gzcD6SGXh0lwvuRGQJEGJfcD6QG+6nnZxBhXDIDqcFzPGZgBuMyLNl0DG6fjBsANADwKVzO993zxwFo9clYuumYphwiCHtSqr6+Hk8//TRGjRqlRx549jQELp1T+sZoIwNyoxeePQ3MEKEMk8dMwIDemYoPJNpYzBYMPL8fCi8ZrzkD9wOFS8+OEuH9yAwBIoxL7gcKF/spPjKIMC6ZgcLFczxmYAbjMow+2YIrj7lQjMBH9pROSLXxfbdcMYArj7kwuqZFdRYRhD0p9Yc//AE/+9nPMGTIED3ywF1RF9XlmeF7RfkzQ372vzs+vw9F+TM1Z+B+oHDp2VEivB+ZIUCEccn9QOFiP8VHBhHGJTNQuHiOxwzMYNzyMyrr4ZGA56D+fkomBJb3SMCMnfWqs4ggrH2wefNm/Otf/8Ls2bN1CeOraWm/271a/lo3fBpmCpkhIKd/NkYPuDjkZ/+7YzaZkTtwBHL6Z6vOwP1A4dKzo0R4PzJDgAjjkvuBwsV+io8MIoxLZqBw8RyPGZjB2AxXVLuw47tv2VP7IUA/gG0AdsjA5cdcKtciBsXX07rdbjz66KN45JFHkJCQoHqDkiQh0ero8meuhsjsTEsj4MgM3kajJEFmBkUZRmZmRSTDiMxh2HvioKoM3A/KOKwJnf4OlwgZmiRJ1XId6d1Rer8fge5fC2YI0HtcKsnA/aCM1m4QJYPWjmI/xU8GEcYlMyjDfgrgOR4zMIPxGbLqWlEckQTALgCFp1qDthNL53iKJ6WWLl2KkSNH4qqrrlIVqE1vhxPFM1d2+bOSkhIs/GChpvUDwOy86SgsLAx6fMLqCTjZdBJpial4jxnOmSEtLU3z9gHgofz7cc+Im1Vl4H4Iz9ppS1QtJ0KGyW9P1rRdQP+O0vv9CHT/WjBDgN7jUkkG7ofwqO0GUTJo7Sj2U/xkEGFcMkN42E88x2MGZjA0g98P27Nj0ah56wENAGx+Ge9N/zNg+v6DcLF0jifJsqzo1l4FBQWora2F2Ry4DLe1NfDVgzabDdu2bet2eZ/Ph7KyMlwz4Vr0mn5hl89xVZ5C/QdVioKfi3P8YDiyUoMeP/HCDvibPDD1sqLPPSOZ4RwZJuWNw/LbF2nOcP9fHsI72z5SlYH7QRmHNQFrpy3B1DVz4fKEfwmpCBmaVu/H/274O3Jzc9s7Jlx6d5Te70eg+9eCGQL0HpdKMnA/KKO1G0TJoLWj2E/xk0GEcckMyrCfAniOxwzMYHyGg8+VodgvY7rmBMAbAApNEgbPyw0rgxJGneMpvlLqtddeg9frbf/3M888AwCYP39+WMFkWUazp+vL5Xwp2j/CAwDeZHS5jbb5N2boPsOO6l0RybDj6C7uB2jbD0q5PC2q1iFSBi307ii9349t22aG7jPoPS6VZOB+CI/abhAtg1rsp/jJIMK4ZIbwsJ94jscMzGB0hl2pNgz/Vts9rdoMB1DZ2xa0nVg6x1N8o/N+/fph0KBB7X+SkpKQlJSEQYMGhR0uFHN6Akxpdk3rMKXZYU5X/3loZgioOLIT5Ye/gc8f7hdUBvj8PpQd+hrbj1aqzsD9QOHQu6NEeD8yQ4AI45L7gcLBfoqfDCKMS2agcPAcjxmYwfgMmzMdGCkBudD27Xt5AEZIwOd91d0zShRq94Fu7DldXy5t1PLM8L0VpatgktS9RcwmM1aUrtKcgfuBRCLC+5EZAkQYl9wPJBIR3o/MECDCuGQGEo0IY5MZmEGUDK9nO2GVgXnQ9u178wBY5cD6YpnqSamnnnoKTz31VCSzAACsQ1MgJVuAcK+okwAp2QLr0BRmiFCG4q0bcPhUNbw+b/dP7sDr8+LQt0dR8tVGzRm4H0gtPTpKhPcjMwSIMC65H0gt9lPPziDCuGQGUovneMzADPpnKE9PwGd9HZgCYBCAcO8GZ/5uuckAPuvrQLmGq8ZEINyVUpLFhKSbBgI2k/I3iATAFlhOsmj/T2KGgBaPGz9fdg8a3WcUH1B4fV40us9g0tK70eLR/jlZ7gcSiQjvR2YIEGFccj+QSER4PzJDgAjjkhlINCKMTWZgBpEyzCnoC5tZwgcAUqB8Ysr83fM/BGAzS5hT0FdTDhEINykFAGanDb2mDIbUS9l92KVeFvSaMhhmp40ZIpxh38mDuHbxNFTXnwCAkPcGaHu8uv4Erl08DftrtH+bQRvuBxKJCO9HZggQYVxyP5BIRHg/MkOACOOSGUg0IoxNZmAGUTIccNowu6AvhgHYDKD/d4+HmqBpe7z/d88fCmB2QV8ciOD+iBbF375nNLPThuTpF8KzpwHuijr4a4N/W2JKs8Oekxq49C4Cs6XM0LX9NVUY+8SNKLxkPIryZyJ34Iig52w/UokVpatQ8tVGXX6zxf1AIhHh/cgMASKMS+4HEokI70dmCBBhXDIDiUaEsckMzCBKhuJhKZAgY9mm49juk1EM4DkA27p47mgE7iE1GYErpGYV9EXxMO0fYxSBsJNSQOCSOlu2E7ZsJ3w1LbA0ArPzpmP5ttXwJkPTHfeZITwtHjdWb1mP1VvWI6d/NkZkDsND+ffjqdLn8XX1blQc2al7Bu4HEokI70dmCBBhXHI/kEhEeD8yQ4AI45IZSDQijE1mYAZRMqwbdh62ZjiwdNMx3HHMhRkSsEMGdgFoQOCjelkARkqBm5p/munA3Gt6xhVSbYT8+F5XzOkJcGSlorCwEI6sVEPenMzQtYojO/HOto9QW1uLd7Z9FJUDCe4HEokI70dmCBBhXHI/kEhEeD8yQ4AI45IZSDQijE1mYIZoZzjgtOHGwkHInzoYL490wpxmR6FJQhGAQpMEc5odL490In/qYPz054N61IQUIPiVUkREREREREREPV15egLK038AAEi0OvDe9D9j4up70exxRTmZvmLmSikiIiIiIiIiorhgio/pmvj4ryQiIiIiIiIiIqFIsizLRmzI5/OhrKwM+Vfno1lW960akiQhLTEVtc11UBNbbvYCMgAJkBLVfXKRGZiBGSKfIVGyo/QfpcjNzYXZbFaVQSutHaV1HwDaXwtmYAZm0CdDtDuK/cQMzMAMocR6PwE941iWGZiBGYIp7Sfj7yklA/IZr9pFcbLpJDMwAzP0tAxJdvXLRprK/RCx14EZmIEZxMsgSkfF++vADMzADMFivJ++WzT2j2WZgRmYIZjCfjJ+UkoCpKT4nS1kBmZghq5WoGqz+lDZUT3lN67MwAzM0NVK1C0WcewnZmAGZghaibrFIo7neMzADMwQtAJlTzN8UkpymJEydYiqZROtDrw3cyUmrpql6g70Da/shXzGCynRgpQ7mIEZmEGUDL611aq2qwe1HaV1HwDaXwtmYAZm0CeDKB3FfmIGZmCGs8V6PwE941iWGZiBGYIp7Sfe6JyIiIiIiIiIiAzHSSkiIiIiIiIiIjIcJ6WIiIiIiIiIiMhwxt/onDTJ6Z+NkZlZSEtLw6S8cdhRvQsVR3bGXQZfTQtcDS6UlJTAVXkKvhQJ5vQEQzMQUWcijEtmIKKuiDAuefxERKGIMDbZURQtnJSKAQlWOyaPmYCi/8/evYdHUR/qA39nr9lAYsAklHAVgRDBXETxVk80ahWsFgOCAnq8gRWB01+LVTke1KpgxfZ45GILqNgiCpKAegTFlpqjFtEiSUAJgkC4hEsiCUnIZrOX+f2xJiZsws7O7sx+Z/f9PA8P7WZn5mVm53Xmm5nZ/CnI6XdB2+tL7poPACg79A2WlqxE0bYNaHa7YjaD7PHBvacervJa+Gr8y5j3wby2n5tS7bBn94B1SDIkCy8CJNKDCPslMxBRZ0TYL3n8RERdEWHfZEeRCDgoJbjz0wdi3UPL0a9nBnyyr9P3jOiTiUWTn8Ujox/C2EX3YV91Zcxl8Na14PS7ByE3eLp8j6/GBefmY2j+sgbdbukPc4otohmIqCMR9ktmIKLOiLBf8viJiLoiwr7JjiJRhDzU+NFHHyEzM7PDn1mzZmmRLe6dnz4Qf5v9FjJSekGSJJhN5k7fZzaZIUkSMlJ64e8Pr8agtAExlcFb14LGtQcgN3ZdVu3JjR40rj0Ab11LxDKQMbCf9CPCfskMZCTsJ/2IsF/y+ImMhP2kLxH2TXYUiSTkQam9e/fimmuuwaefftr255lnntEiW1xLsNqx7qHlSLJ3g8Ws7II2i9mCJHs3rJ/xChKs9pjIIHt8OP3uQaDFB8hKJwLQ4p9O9nQ+6k+xif2kDxH2S2Ygo2E/6UOE/ZLHT2Q07Cf9iLBvsqNINCEPSn333XcYOnQo0tLS2v4kJydrkS2ujRs5Bv16ZiguilYWswX9z+2DwotGx0QG9556/+WcSsuqlQzIDR6499SHnYGMg/2kDxH2S2Ygo2E/6UOE/ZLHT2Q07Cf9iLBvsqNINKoGpQYOHKhBFGpvWv6ULu/tDcbr82Ja/pSYyOAqr43q9GQs7Cd9iLBfMgMZDftJHyLslzx+IqNhP+lHhH2THUWiCWlQSpZl7N+/H59++iluuOEGXHfddXjhhRfQ0sL7OiMpu28Wcvpd0OW9vcGYTWbk9h+O7L5Zhs7grW5u+wYGtXw1Lnirm8OaBxkD+0kfIuyXzEBGw37Shwj7JY+fyGjYT/oRYd9kR5GIQrpmr6qqCk6nEzabDS+++CIOHz6MZ555Bs3NzXj88ccVzUOSJCRaHarCOqwJHf4OVYMkQTZAhhEZmarmfabhGUOx9/gBw2Zw1jsjksHSADgyApdhlM9DPGRolCRV07UXiX4C1K+HcNcBEP620COD1vslMyjPEEy8fCb1yBBuR7Gf4qeftD5+UpJBhPUQTLx8JvXIYPR+AmLjWNYo5zY8x1MmXj6TWmdQ2k+SLMsh3clZV1eHc845B9IPC/jwww/x8MMPY/v27TCbux5x9Xq9KC0txbhx41BUVBTKIiNmzJgxOHHiBNLT07FhwwZhM6SmpmLAgPC/2aCyshI1NTWGzVBcXIx58+aFnWHOnDkoLCxUlUFrzODX2gu5ubln7ZFg1PYTwI5SmkHr/ZIZlGfQAzP4RaKj2E/aZxBhv9T6+ElJBhHWgx6YwY/9JMZ2MMq5Dc/x9MEMfkr7KbSnmwFISUnp8P/PP/98uFwunDp1Cj179gw6/UlnHW5eOTXUxQLwj9CtmbgQE1bPhNMd+uV6NU21bX+LnGFs3g1Yctd8Vfnae67kZbyzfZNhMzgrToa9fABYsn0VXmvaqCpDMPHymdQ6Q6OzTtVyzxRuPwHqOyrcdQCEvy30yKD1fskMyjMEEy+fST0yRKKj2E/x0U9aHz8pySDCeggmXj6TemQwej8BsXEsa5RzG57jKRMvn0mtMyjtp5AGpT755BPMnj0bH3/8MRwO/yVgu3btQkpKiuLCkmUZTe7wLtlzuptVzaP1ojDRM+ys2h1Wtrb5HNnd6TKMksGbHP4tXQDgSYLqDErF+mdSrwzhiEQ/tWYJZz2oXQetyxY9g9b7JTMoz6BUrH8m9cygFvtJnwwi7JdaHz8pySDCelAq1j+TemZQS5R+AmLjWFb0cxue44Um1j+TemUIJqQHnefl5cFut+Pxxx/Hvn37UFJSgueffx73339/yAGpa+WHd6Hs0Dfw+ryqpvf6vCg9+DV2HKkwdAZzWgJMqXbV0wOAKdUOc5r6+/TJONhP+hBhv2QGMhr2kz5E2C95/ERGw37Sjwj7JjuKRBTSoFT37t3xyiuv4OTJkxg3bhz+8z//ExMnTmRpaWBpyUqYpJA2TxuzyYylJStjIoM9u0dUpyfjYD/pR4T9khnISNhP+hFhv+TxExkJ+0lfIuyb7CgSTcjPlBoyZAhee+01LbJQO0XbNuCR0Q8hI6UXLGblm8nj9aCq7jiKv+r8GQBGy2AdkozmL2sgN3qAUK5OlgCpuwXWIclhZyDjYD/pQ4T9khnIaNhP+hBhv+TxExkN+0k/Iuyb7CgSjbohUtJcs9uFWxffjwbXaXi8HkXTeLweNLhOY+yi+9DsdsVEBsliQrdb+gM2E6D09mMJgM0/nWThR5wo0kTYL5mBiDojwn7J4yci6ooI+yY7ikTDrSmw704cwLULJqKq7jgAdHnvb+vrVXXHce2CidhXXRlTGcwpNnQfPxBSd2Uj+VJ3C7qPHwhzii1iGYioIxH2S2Ygos6IsF/y+ImIuiLCvsmOIpGEfPse6WtfdSVGPXMTCi8ajWn5U5Dbf3jAe3YcrsDSkpUo/mpjREauRcxgTrEhadIguPfUw1VeC19N4DJMqXbYs3vAOiSZo+dEOhBhv2QGIuqMCPslj5+IqCsi7JvsKBIFB6UMoNntwqqt67Fq63pk983C8IyheDT/QTxX8jK+rvoW5Yd3xUUGyWKCLSsFtqwUeKubYWkApudNwpLtq+BJAr+BgSgKRNgvmYGIOiPCfsnjJyLqigj7JjuKRMChRoMpP7wL72zfhJqaGryzfZMuRSFiBnNaAhyZPVBYWAhHZg+WFZEARNgvmYGIOiPCfsnjJyLqigj7JjuKooWDUkREREREREREpDsOShERERERERERke44KEVERERERERERLqTZFmW9ViQ1+tFaWkp8q/OR5Os7sn9kiQhNbEHappqoSa23OQBZAASICWqe8Y7MzADM0Q+Q6JkR8nHJcjNzYXZbFaVIVzhdlS46wAIf1swAzMwgzYZot1R7CdmYAZm6IrR+wmIjWNZZmAGZgiktJ/0//Y9GZBPe9ROihONJ5iBGZgh1jJ0s6ufNtJUroeIbQdmYAZmEC+DKB0V79uBGZiBGQIZvJ9+mNT4x7LMwAzMEEhhP+k/KCUBUrf4HS1kBmZghs5moGqx2lDZUbHyG1dmYAZm6Gwm6iaLOPYTMzADMwTMRN1kEcdzPGZgBmYImIGyt+k+KCU5zEieMFjVtIlWB96bsgw3r5yKJrcz5OnrV+yFfNoDKdGC5LuZgRmYQZQM3jVVqparBbUdFe46AMLfFszADMygTQZROor9xAzMwAxnMno/AbFxLMsMzMAMgZT2Ex90TkREREREREREuuOgFBERRZbPF+0ERERERERkAPo/U4qIiGJKTnUzJu+qw+VVTmTWtsD24igcMEnY3cOGLRkOvJGVgrK0hGjHJCIiIiIiwXBQikKW3TcLIzIykZqairF5N2Bn1W6UH96lawZvdTOc9U4UFxfDWXES3mQJZp70EunqvLoWLNp8FFcedcItATtloAhAA4Akn4xh37twz0kXpu2ow2e9HZhR0Bv7U2yaZhKhG0TIQEQd8dhFnAxEFIgdJU4G0h8HpUiRBKsd40aOwbT8Kcjpd0Hb60vumg8AKDv0DZaWrETRtg1odrs0ySB7fHDvqYervBa+Gv8y5n0wr+3nplQ77Nk9YB2SDMnCO1OJtDT+21NYvPkYWrwyXgPwkgyUdvK+XBmYBWD8USc+f2s/phf0RtHQ5IhmEaEbRMhARB3x2EWcDEQUiB0lTgaKLg5KUVDnpw/EuoeWo1/PDPjkzp8VM6JPJhZNfhaPjH4IYxfdh33VlRHN4K1rwel3D0Ju8HT5Hl+NC87Nx9D8ZQ263dIfZo2vyCCKV+O/PYWlHx3FtwBuBFCJrh9QWA7gXgBPAfjQK2PZR1WQIGPt0HMikkWEbhAhAxF1xGMXcTIQUSB2lDgZKPpCHmpsaWnBU089hUsuuQRXXHEF/vjHP0KWZS2ykQDOTx+Iv81+CxkpvSBJEswmc6fvM5vMkCQJGSm98PeHV2NQ2oCIZfDWtaBx7QHIjV2XVXtyoweNaw/AW9cSsQxkDOwn7Q2qa8HizcfwLYArABz+4fWuHm3e+vphAJcD2ANg8eZjOC8C+6cI3SBCBjIG9pN+eOwiTgYyBvaTvthR4mQgMYQ8KPXMM8/gn//8J1555RX84Q9/wJo1a7B69WotslGUJVjtWPfQciTZu8FiVnZRncVsQZK9G9bPeAUJVnvYGWSPD6ffPQi0+ACl/22UAbT4p5M9/BaweMJ+0t7CzUfh8sq4EUA9AK/C6bw/vP8GAC1eGYs2Hw0rhwjdIEIGMg72kz547CJOBjIO9pN+2FHiZCBxhDQoVVdXh6KiIjz99NPIzs7G5ZdfjnvvvRdlZWVa5aMoGjdyDPr1zFBcmK0sZgv6n9sHhReNDjuDe0+9/3LOUH9ZIwNygwfuPfVhZyBjYD9pL+dEM6486kQR/LfsKR2QauX9YboiAFcedSKnull1FhG6QYQMZAzsJ/3w2EWcDGQM7Cd9saPEyUDiCGlv2LZtG7p3745Ro0a1vTZt2rSIhyIxTMufAp/sg1nq/JLSs/H6vJiWPwWrtq4PK4OrvDbs6W1ZKWHNg4yB/aS9yRV1cEv+h5qb0PUte2djAvASgMkSMHlXHcrSfqIqiwjdIEIGMgb2k3547CJOBjIG9pO+2FHiZCBxhHSl1KFDh9CnTx+sX78eN954I6699losXrwYPh8vn4s12X2zkNPvgi7vcQ7GbDIjt/9wZPfNUp3BW93c9g0MavlqXPCGcTUGGQf7SXuXVzmx84dv2VO7Vn0AtgPYKQOXHXWqmocI3SBCBjIO9pM+eOwiTgYyDvaTfthR4mQgsYR0pVRTUxMqKyvx1ltvYf78+aiursbcuXPhcDhw7733KpqHJElItDpUhXVYEzr8HaoGSYLMDIoyjMjIVDXvMw3PGIq9xw+oyuCsV3fCeiZLA+DICFyGUbZFPGRolCRV07UXiX4C1K+HcNcBEP620DpDZm0LilTPuaPdAApPtnT67wy2HrTuBqNkCCYePpN6ZQi3o9hP+mTQ+thFSQYRukGEDMHEy2dSjwxG7ycgNo5leX5lrAzBxMtnUusMSvtJkkP4aoWlS5fiD3/4AzZv3ow+ffoAAFasWIE333wTH3744Vmn9Xq9KC0txbhx41BUFKnTmtCMGTMGJ06cQHp6OjZs2MAMZ8mQmpqKAQPC/4aHyspK1NTUqMpQXFyMefPmhZ1hzpw5KCwsVJVBa8zg19oLubm5MJvV/fYonH4C2FFBM/h8GDlqFJYCeCACy/kzgGkAtn3xBWDqeNFusPWgdTcYJYMemMEv3I5iP+mTQetjFyUZROgGETLogRn82E9ibAeeXxkrg9aYwU9pP4V0pVRaWhrsdntbYQHAeeedh6NHlX+L0klnHW5eOTWUxbZxWBOwZuJCTFg9E0536Jfr1TTVtv3NDGfPMDbvBiy5a76qfO09V/Iy3tm+SVUGZ8XJsJcPAEu2r8JrTRtVZQgmXj4PWmdodNapWm57kegnQH1HhbsOgPC3hdYZDpgkJPki8xXRyQBaTBJuXhU4xBVsPWjdDUbJEEw8fCb1yhBuR7Gf9Mmg9bGLkgwidIMIGYKJl8+kHhmM3k9AbBzL8vzKWBmCiZfPpNYZlPZTSINSOTk5cLlc2L9/P8477zwAwL59+zqUWDCyLKPJHd4le053s6p5tF4UxgzBM+ys2h1Wtrb5HNnd6TKUZPAmh39LFwB4kqA6g1Kx/nnQK0M4ItFPrVnCWQ9q10HrskXOsLuHDcO+D+8ZAK2GAajoaVO1b2rdDUbJoFQsfyb1zqAW+0mfDFofuyjJIEI3iJBBqVj/TOqZQS1R+gmIjWNZnl8ZI4NSsf6Z1CtDMCE96HzQoEG4+uqr8dhjj6GiogKffPIJli5dijvuuCPkgCS28sO7UHboG3h9oX7pu5/X50Xpwa+x40iF6gzmtASYUu2qpwcAU6od5jT19+mTcbCftLclw4EREpCLEP/j0Y4JQB6A4RLweW9197eL0A0iZCDjYD/pg8cu4mQg42A/6YcdJU4GEkvI5xUvvPAC+vfvjzvuuAOPPPIIJk+ejDvvvFOLbBRlS0tWwiSpO/U0m8xYWrIy7Az27B5RnZ6Mhf2krTeyUmCVgVkI79v3ZgGwyv75qSVCN4iQgYyD/aQPHruIk4GMg/2kH3aUOBlIHCHdvgcASUlJeP7557XIQoIp2rYBj4x+CBkpvWAxK/+oeLweVNUdR/FXnT+HIBTWIclo/rIGcqMHCOXqZAmQultgHZIcdgYyDvaTtsrSEvBZbwfGH3XiKQCHAYTyuz4zgL4AxgH4rLcDZWH8hkuEbhAhAxkH+0kfPHYRJwMZB/tJP+wocTKQONTegUFxoNntwq2L70eD6zQ8Xo+iaTxeDxpcpzF20X1odof/7BnJYkK3W/oDNhOg9PZjCYDNP51k4UecKJJmFPSGzSzhA/gfVq70e37MP7z/QwA2s4QZBb3DyiFCN4iQgYg64rGLOBmIKBA7SpwMJA5uTTqr704cwLULJqKq7jgAdHkPdOvrVXXHce2CidhXXRmxDOYUG7qPHwipu7LfJkjdLeg+fiDMKbaIZSAiv/0pNkwv6I2hALbAf+UT0PV/TFpf7/vD+4cAmF7QG/sjsH+K0A0iZCCijnjsIk4GIgrEjhInA4kh5Nv3KP7sq67EqGduQuFFozEtfwpy+w8PeM+OwxVYWrISxV9tjMgI/pnMKTYkTRoE9556uMpr4asJXIYp1Q57dg9YhyRz9JxIQ0VDkyFBxuLNx7DDK6MIwEsAtnfy3hz4nyE1Dv4rpKYW9EbR0Mhdci1CN4iQgYg64rGLOBmIKBA7SpwMFH0clCJFmt0urNq6Hqu2rkd23ywMzxiKR/MfxHMlL+Prqm9RfniX5hkkiwm2rBTYslLgrW6GpQGYnjcJS7avgicJ/AYGIh2tHXoOtqU7sGjzUdx91InJErBTBnYDqIf/Vr1MACMk/0PNP81wYOY1kblC6kwidIMIGYioIx67iJOBiAKxo8TJQNHFoUYKWfnhXXhn+ybU1NTgne2bdCnMM5nTEuDI7IHCwkI4MnuwrIiiYH+KDTcVDkD+hIF4bUQKzKl2FJokTANQaJJgTrXjtREpyJ8wED+/dYAmA1JnEqEbRMhARB3x2EWcDEQUiB0lTgbSH6+UIiKisJSlJaAs7ScAgESrA+9N+jNuXvUAmtzOKCcjIiIiIiKR8UopIiKKLBP/00JERERERMHxzIGIiIiIiIiIiHQnybIs67Egr9eL0tJS5F+djyZZ3bcHSJKE1MQeqGmqhZrYcpMHkAFIgJSo7s5FZmAGZoh8hkTJjpKPS5Cbmwuz2awqQ7jC7ahw1wEQ/rZgBmZgBm0yRLuj2E/MwAzM0BWj9xMQG8eyzMAMzBBIaT/p/0wpGZBPe9ROihONJ5iBGZgh1jJ0s6ufNtJUroeIbQdmYAZmEC+DKB0V79uBGZiBGQIZvJ9+mNT4x7LMwAzMEEhhP+k/KCUBUrf4HS1kBmZghs5moGqx2lDZUbHyG1dmYAZm6Gwm6iaLOPYTMzADMwTMRN1kEcdzPGZgBmYImIGyt+k+KCU5zEieMFjVtIlWB96bsgw3r5yq6lud6lfshXzaAynRguS7mYEZmEGUDN41VaqWqwW1HRXuOgDC3xbMwAzMoE0GUTqK/cQMzMAMZzJ6PwGxcSzLDMzADIGU9hMfdE5ERERERERERLrjoBQRERERac/ni3YCIiIiEoz+z5QiIiIiopiXU92MybvqcHmVE5m1LbC9OAoHTBJ297BhS4YDb2SloCwtIdoxiYiIKIo4KEWG5K1uhrPeieLiYjgrTsKbLMHMA1siEgD7ieLdeXUtWLT5KK486oRbAqw5ucD1w4CkJNgaGnBhRQWGlZVi2o46fNbbgRkFvbE/xRbt2HGB/UQUKLtvFkZkZCI1NRVj827AzqrdKD+8K9qx4hI7Kj5xUIoMQ/b44N5TD1d5LXw1LgDAvA/mtf3clGqHPbsHrEOSIVl4ZyoR6Yf9ROQ3/ttTWLz5GMw2O3D33bDOmgXk5QW8z7p9O/DSS7h09Vv4/K39mF7QG0VDk6OQOPaxn4gCJVjtGDdyDKblT0FOvwvaXl9y13wAQNmhb7C0ZCWKtm1As9sVrZhxgR1FHJQiQ/DWteD0uwchN3i6fI+vxgXn5mNo/rIG3W7pDzN/60pEOmA/EfmN//YUln50FBgyBKZNm4ABA7p+jlR2NvDqq7A88QRM11+PZR/thQQZa4eeo2/oGMd+Igp0fvpArHtoOfr1zIBP7ryjRvTJxKLJz+KR0Q9h7KL7sK+6UueU8YEdRUCIg1LFxcV47LHHAl6XJAkVFRURC0XUnreuBY1rDwAtyh6QKjd60Lj2ALqPH8jSiiPsJ4oG9hMpEQ/9NKiuBYs3H/MPSH3+OZCUBEgSYDZ3PkHr6336wLR1K3yXXorFm7/DtnQHb+WLEPYTKRUPHdXq/PSB+Nvst5Bk7wZJkmCWOu8os8n/ekZKL/z94dW4dsFEDkxFGDuKWoU0KDVmzBhcddVVbf/f4/Hg3//933H11VdHOhcRAP/lnKffPegvK1npRABa/NMlTRrEyzzjBPuJ9MZ+IqXioZ8Wbj4Kk83uv0IqKQmwWpVNaLUCSUkwffQRzBdkYdHmo7ipcIC2YeMA+4lCEQ8dBfhv2Vv30HIk2bvBYlZ2GmwxW5Bk74b1M17BqGdu4q18EcKOovZC2pIJCQlIS0tr+/Puu+9ClmXMnj1bq3wU59x76v2Xcyotq1YyIDd44N5Tr0kuEg/7ifTGfiKlYr2fck4048qjTlgn3u6/ZU/pgFQrqxUYOBCWCRNx5VEncqqbtQkaR9hPFIpY76hW40aOQb+eGYoHpFpZzBb0P7cPCi8arVGy+MOOovZUDy/W1dVh2bJl+M1vfgObjZfPkTZc5bVRnZ6Mif1EemA/kRqx2E+TK+rglgDMmtX1M6SC8XqBmTPhloDJu+oiGS8usZ9IrVjsqFbT8qd0+QypYLw+L6blT4lwovjFjqL2VA9Kvfnmm0hPT8eNN94YyTxEbbzVzW3fwKCWr8YFL3/jGnfYT6Q19hOpFYv9dHmVE9acXP+37HX1DKlgzGZg5EhYc3Jx2VFnRPPFG/YThSMWOwoAsvtmIaffBW3PigqV2WRGbv/hyO6bFeFk8YcdRWdS9e17sizj7bffxv333x/ytJIkIdHqULNYOKwJHf4OVYMkQWYGw2Rw1kfmoNTSADgyApdhlPUQDxkaJUnVdJ0Jp58A9esh3HUAhL8tmEG/DFr3k5IMwcTLttAjQ6Q6Klb7KbO2Bbh+mOp5d5xZJoaVl3X67xThs2CEDOyn+MogyjGU6MeyIzIyVc37TMMzhmLv8QOqMgQTC8f0PMdjhvaU9pMky3Kod3KivLwcd9xxB/75z3/inHOUfXWv1+tFaWkpxo0bh6KiolAXGRFjxozBiRMnkJ6ejg0bNjCD4BmKi4sxb968sJc1Z84cFBYWqsqgNWbwa+2F3NxcmNX+lv0HavoJYEcxQ2gZtO4nJRn0wAx+keqomOwnnw8jR40Cpk4Fli4Nf0HTpgHLlmHbF18Apo4X9IvwWTBCBvZTfGWI9jGU0P3UTmpqKgYMCP9LFCorK1FTU6Mqg9aMkoHnePGTQWk/qbpS6pNPPsHFF18c0gFVq5POOty8cqqaxcJhTcCaiQsxYfVMON2hX65X01Tb9jcziJ/BWXFSVbYzLdm+Cq81bVSVIZh42RZaZ2h01qlabmfC6SdAfUeFuw6A8LcFM+iXQet+UpIhmHjZFnpkiFRHxWo/HTBJsDU0qJpvgPp6tJgk3LzqgZAyKBErn0f2EzO0J8oxlOjneGPzbsCSu+arytfecyUv453tm1RlCCYWjul5jscM7SntJ1WDUuXl5bjooovUTApZltHkDu+SPae7WdU8Wi8KYwZjZPAmR+ZyZE8SOl2GUdZDPGWIhHD6qTVLOOtB7TpoXTYzGCOD1v2kJINSsb4t9MwQrljtp909bLiwokJ1rg4qKlDR06bpf7dj5fPIfmKG9hkiIZbP8XZW7Q4rW9t8juzmeUWYGXiOF38ZglH1oPM9e/Zg8ODBaiYlUsyclgBTqj2seZhS7TCnqb9Pn4yH/UR6YD+RGrHaT1syHHCXlQLbt/u/RU8NrxfYtg3u8jJ83lvdsy/Ij/1EasVqRwFA+eFdKDv0Dbw+dR3l9XlRevBr7DgSoQH4OMaOojOpGpSqqalBcnJypLMQBbBn94jq9GQ87CfSC/uJQhWr/fRGVgqsMoCXXgp4DpRiZjOwcCGssn9+FB72E6kRqx3VamnJSpgkdR1lNpmxtGRlhBPFL3YUtadqrywvL8dVV10V6SxEAaxDkiElWYBQr/KUACnJAuuQ2P0PK3WO/UR6YT9RqGK1n8rSEvBZbwc8q98CKisBtzu0GbjdwIED8KxZjc96O1DG336Hjf1EasRqR7Uq2rYBh05WweP1hDSdx+vBwe+PoPirzp+xRqFjR1F7Kn+dRaQPyWJCt1v6AzaT8tKSANj800kWfsSJSBvsJ6IfzSjoDW+LC76f/QxoaFA+MOV2Aw0N8F1/PbwtLswo6K1t0DjBfiIK1Ox24dbF96PBdVrxwJTH60GD6zTGLroPzW6XxgnjBzuK2uPWJOGZU2zoPn4gpO7Knssvdbeg+/iBMKfYNE5GRPGO/UTktz/FhukFvYE9e+C79FLgyBH/D7p6xlTr60eO+N+/dy+mF/TGfu4bEcN+Igr03YkDuHbBRFTVHQeALp8x1fp6Vd1xXLtgIvZVV+qWMV6wo6iVqm/fI9KbOcWGpEmD4N5TD1d5LXw1gb+pMKXaYc/u4b8clKPnRKQT9hORX9HQZEiQsXjzdzBfkAXLhInAzJnAyJGBby4tBRYuhGfNanhbXJh+fQaKhvJ2jEhjPxEF2lddiVHP3ITCi0ZjWv4U5PYfHvCeHYcrsLRkJYq/2sgrpDTEjiKAg1JkIJLFBFtWCmxZKfBWN8PSAEzPm4Ql21fBkwR+AwMRRQ37ichv7dBzsC3dgUWbj+LK11+H+y+vw5qTC2RmAsnJQH09sHs33GWlsMrA5xkOzLzmPF4hpSH2E1GgZrcLq7aux6qt65HdNwvDM4bi0fwH8VzJy/i66luUH94V7Yhxgx1FHJQiQzKnJcCR4UBhYSFea9qIJrcz2pGIiACwn4j2p9hwU+EA5FQ3Y/KuOlx2eBeGlZfB5pPRYpJQ0dOGz0ek4I2sFD7UXGfsJ6JA5Yd3Ye/xA7h/+G14Z/sm7hdRxI6KTxyUIiIiIqKIK0tLQFnaTwAAiVYH3pv0Z9y86gGeZBAREVEb3pRJRERERNoz8bCTiIiIOuLRARERERERERER6U6SZVnWY0FerxelpaXIvzofTbK6bzCQJAmpiT1Q01QLNbHlJg8gA5AAKVHdnYvMwAzMEPkMiZIdJR+XIDc3F2azWVWGcIXbUeGuAyD8bcEMzMAM2mSIdkexn5iBGZihK0bvJyA2jmWZgRmYIZDSftL/mVIyIJ/2qJ0UJxpPMAMzMEOsZehmVz9tpKlcDxHbDszADMwgXgZROiretwMzMAMzBDJ4P/0wqfGPZZmBGZghkMJ+0n9QSgKkbvE7WsgMzMAMnc1A1WK1obKjYuU3rszADMzQ2UzUTRZx7CdmYAZmCJiJuskijud4zMAMzBAwA2Vv031QSnKYkTxhsKppE60OvDdlGW5eOVXVN7fUr9gL+bQHUqIFyXczAzMwgygZvGuqVC1XC2o7Ktx1AIS/LZiBGZhBmwyidBT7iRmYgRnOZPR+AmLjWJYZmIEZAintJz7onIiIiIiIiIiIdMdBKSIiIiIiIiIi0h0HpYiIiIiIiIiISHf6P+icKAK81c1w1jtRXFwMZ8VJeJMlmNMSoh2LiIj9RETCYj8RkcjYUfGJg1JkGLLHB/eeerjKa+GrcQEA5n0wr+3nplQ77Nk9YB2SDMnCiwCJSD/sJyISFfuJiETGjiIOSpEheOtacPrdg5AbPF2+x1fjgnPzMTR/WYNut/SHOcWmY0IiilfsJyISFfuJiETGjiJAxTOljh49igceeAAXXXQRCgoKsGLFCg1iEf3IW9eCxrUHIDd2XVbtyY0eNK49AG9di8bJSDTsJ9Ib+4mUYj+R3thPpBT7iaKBHUWtQh6U+tWvfoXExEQUFxdjzpw5ePHFF/HRRx9pkY0IsseH0+8eBFp8gKx0IgAt/ulkj0/LeCQY9hPpif1EoWA/kZ7YTxQK9hPpjR1F7YU0KHXq1CmUlpbiwQcfxMCBA3HdddfhqquuwpYtW7TKR3HOvafefzmn0rJqJQNygwfuPfWa5CLxsJ9Ib+wnUor9RHpjP5FS7CeKBnYUtRfSoFRCQgIcDgeKi4vhdruxb98+fPXVV8jKytIqH8U5V3ltVKcn42A/kd7YT6QU+4n0xn4ipdhPFA3sKGovpEEpu92OuXPnYvXq1cjJycHo0aPxb//2b7jtttu0ykdxzFvd3PYNDGr5alzwVjdHKBGJjP1EemI/USjYT6Qn9hOFgv1EemNH0ZlC/va97777Dtdccw3uuece7NmzB08//TQuv/xy3HLLLYqmlyQJiVZHyEEBwGFN6PB3qBokCTIzGCaDs96pat5nsjQAjozAZRhlPcRDhkZJUjXdmcLtJ0D9egh3HQDhbwtm0C+D1v2kJEMw8bIt9MgQiY5iPzGDXhnYT/GVwej9BMTGsSwzKM/Ac7z4yaC0nyRZlhXfybllyxb86le/QklJCRIS/MFefvllvPvuu9i4ceNZp/V6vSgtLcW4ceNQVFSkdJERNWbMGJw4cQLp6enYsGEDMwieobi4GPPmzQt7WXPmzEFhYaGqDFpjBr/WXsjNzYXZbFY1j3D6CWBHMUNoGbTuJyUZ9MAMfuF2FPuJGfTMwH6KrwzsJzG2AzMoz8BzvPjJoLSfQrpSaufOnRgwYEBbYQHABRdcgD/96U+K53HSWYebV04NZbFtHNYErJm4EBNWz4TTHfrlejVNtW1/M4P4GZwVJ1VlO9OS7avwWlPgf1SNsh7iIUOjs07VctuLRD8B6jsq3HUAhL8tmEG/DFr3k5IMwcTLttAjQ7gdxX5iBj0zsJ/iK4PR+wmIjWNZZlCeged48ZNBaT+FNCiVnp6OyspKtLS0wGazAQD27duHvn37Kp6HLMtocod3yZ7T3axqHq0XhTGDMTJ4kyNzS5cnCZ0uwyjrIZ4yhCMS/dSaJZz1oHYdtC6bGYyRQet+UpJBqVjfFnpmUIv9xAx6ZmA/xWcGtUTpJyA2jmWZged4zBCYIZiQHnReUFAAq9WKxx9/HPv378fmzZvxpz/9CXfeeWfIAYmCMaclwJRqD2seplQ7zGnq79Mn42A/kZ7YTxQK9hPpif1EoWA/kd7YUXSmkAalkpKSsGLFClRXV2P8+PGYP38+HnzwQUycOFGrfBTn7Nk9ojo9GQf7ifTGfiKl2E+kN/YTKcV+omhgR1F7IX/73uDBg/Haa69pkYUogHVIMpq/rIHc6AFCuTpZAqTuFliHJGuWjcTDfiI9sZ8oFOwn0hP7iULBfiK9saOovZCulCLSm2Qxodst/QGbCVB6+7EEwOafTrLwI05E2mA/EZGo2E9EJDJ2FLXHrUnCM6fY0H38QEjdlV3YJ3W3oPv4gTCn2DRORkTxjv1ERKJiPxGRyNhR1Crk2/eIosGcYkPSpEFw76mHq7wWvhpXwHtMqXbYs3vAOiSZo+dEpBv2ExGJiv1ERCJjRxHAQSkyEMligi0rBbasFHirm2FpAKbnTcKS7avgSQK/gYGIoob9RESiYj8RkcjYUcShRjIkc1oCHJk9UFhYCEdmD5YVEQmD/UREomI/EZHI2FHxiYNSRERERERERESkOw5KERERERERERGR7jgoRUREREREREREupNkWZb1WJDH40FZWRlGjxkNpxz4VH0lJElCT0cKTjrroCa27PQCMgAJkBxmZmAGZhAkg0OyY+OGjcjJyYHFEp3vXwi3o8JdB0D424IZmIEZtMkQ7Y5iPzEDMzBDV4zeT0BsHMsyAzMwQyCl/aRbc/l8PgDAxg0b9VokERlMa09Ec9nsKCLqSrQ6iv1ERMGwn4hIVMH6SbcrpXw+HzweD0wmEyRJ0mORRGQQsizD5/PBYrHAZIrOXcXsKCLqSrQ7iv1ERF1hPxGRqJT2k26DUkRERERERERERK34oHMiIiIiIiIiItIdB6WIiIiIiIiIiEh3HJQiIiIiIiIiIiLdcVCKiIiIiIiIiIh0x0EpIiIiIiIiIiLSHQeliIiIiIiIiIhIdxyUIiIiIiIiIiIi3RlqUKq4uBiZmZl4++23dV1uZmZmhz+XXXYZHn/8cZw+fVrXHABw6tQpPPfccygoKEBOTg5Gjx6NFStWwOfzab7sgoKCtnUwbNgw5OXl4fbbb8cnn3yi+bI7y3Dmn61bt0Y9xx133KFbhqamJrz44ou48cYbkZ2djUsvvRSzZs3Cnj17dFl+QUEBiouLA14vLi5GQUGBLhlEE+8dFe/9dGaOaHUU+4n91Bn2E/uJ/fSjaHYU+ykQ+yl6/QSI0VEi9NPZcvAYStuOsmgyV428//776N+/P9555x3cdtttui574cKFyMvLg8/nw9GjRzF37lw8//zzeOqpp3TLUFtbi4kTJyI9PR3PPvss+vbtix07duDpp5/GoUOH8F//9V+aZ5gzZw7GjBkDn8+HU6dOYf369XjggQewfPlyXHHFFZovv32GM51zzjm6LP9sOaxWqy7LPn36NCZNmoSmpiY8+uijGDZsGGpra/HGG2/g9ttvx/r169GvXz9dstCP4rmj2E+BOc6kZ0exn+hM7Cf2U/scZ4qXfgLYUSJiP0W3nwAxOkqEfuoqB4+htGWYQanvv/8eW7Zswbx58/Doo4/i0KFDum6Qc845B2lpaQCAXr164YEHHsBTTz2l66DUH/7wB9hsNrzyyiuw2+0AgH79+iEhIQHTp0/HlClTcN5552maISkpqcN6+O1vf4vq6mrMnz8f7733nqbL7ixDNEUzx+LFi/H9999jw4YNSE5OBgD06dMH8+fPx9GjR7FixQrd/iNGfvHeUeynznNEC/uJ2mM/sZ86yxEt0c7AjhIL+yn6/QSI0VHR7gYRcsRrPxnm9r0PPvgASUlJuOWWW5Ceno533nknqnkcDoeuy2tpacH777+PyZMntxVWq2uuuQYrVqxAnz59dM3UauLEifj2229RWVkZleXHG5/Ph3Xr1uGee+5pK6v2nn/+eTz88MNRSBbf4rmj2E/Uiv0kJvYT+4n82FHiYT+J2U8AO0pv8dxPhhmUev/993H11VfDZDKhoKAA69evhyzLUcly8uRJ/PWvf8Utt9yi2zIPHjyIpqYmXHjhhQE/kyQJl112GWw2m2552jv//PMBAHv37o3K8uPNwYMHcfLkSVx88cWd/jw9PR0JCQk6p6J47ij2E7ViP4mJ/cR+Ij92lHjYT2L2E8CO0ls895Mhbt87evQovvrqK9xzzz0AgJ/97Gd48803sW3bti43WqRNnToVZrMZsizD6XQiJSUFTz75pC7LBoD6+noA/ssJRdOaSa+HAj7xxBN4+umnO7yWkZGB999/X5flny3HZ599hsTERE2XW1tbC6Dj/dX//Oc/8dBDD7X9f73WR2frwOPxCHHprZ7ivaPYTx2J0FHsJ/ZTK/YT+6m9eO4nQJyOYj/5sZ/E7SeA53jt8RhK244yxKDU+++/D7vdjp/+9KcAgFGjRuGcc87BunXrdCusZ555Bjk5OZBlGbW1tVi5ciXuuOMOvPfeezj33HM1X35KSgoA/7cziKaxsREA0L17d12WN2vWLPzsZz/r8JrFov9HubMcelzy23o5Z+t/yAAgLy8P69evBwBs2rQJb775puY5gM7XgZ7LF0W8dxT7qSMROor9xH5qxX5KAcB+ahXP/QSI01HsJz/2UwoAMfsJ4DleezyG0nb5hhmUam5uxsiRI9te83q9+OCDD/Bf//VfulzG1qtXLwwYMAAAMHDgQAwfPhyXXnopNm7ciClTpmi+/P79+yMpKQlff/01srOzA37+4IMP4s4779T1G1xa7d69GwAwZMgQXZZ37rnntm2LaIpWjgEDBiAlJQXbt29v+yw4HI62LHoMkrbqbB3ouXxRxHtHsZ86EqGj2E/sp1bsJ/ZTe/HcT4A4HcV+8mM/idtPAM/x9CZKP7UuS8+OEv6ZUvv378c333yDxx9/HOvXr2/789///d9obGzERx99FJVcJpMJsizD6/XqsjyLxYIxY8bgjTfeQEtLS4efbd68GZs3b0Z6erouWc5UVFSE4cOHx+TXU4rIYrFg3LhxeP3119t+g9He8ePHo5AqfrGj2E/0I/aTWNhP7CfqiB0lDvaT2P0EsKP0Fs/9JPyVUu+//z5SUlIwceLEDg96Gzp0KBYvXoz169fj5ptv1jzHqVOnUF1dDcB/X+2rr74Kr9eLgoICzZfdaubMmbjttttw3333YebMmfjJT36CrVu3YsGCBbjrrrswePBgzTM0NDSgurq67RLXtWvXYsOGDXj11Vc1X/aZGc7UrVs3XZ5HIIKZM2di27ZtuP322zFjxgwMHz4ctbW1ePvtt7F27Vr8/Oc/j3bEuMGO8mM/BeY4U7x0FPtJHOwnP/ZTYI4zxUs/AewoUbCf/EToJ0CMjmI/xW8/GWJQ6uabb+70mwfuuOMOPPvsszh+/Dh69eqlaY6ZM2e2/W+Hw4ERI0Zg2bJluo4cp6Wl4c0338TChQsxe/Zs1NXVoX///pg1axbuuOMOXTLMmzcP8+bNgyRJ6NmzJy644AKsWLFCt/u+22c403/8x39g+vTpuuWIJofDgb/+9a94/fXXsWTJElRWVsJmsyE7OxsLFy7EddddF+2IcYMd5cd+CsxxpnjpKPaTONhPfuynwBxnipd+AthRomA/+YnQT4AYHcV+it9+kuRofecmERERERERERHFLeGfKUVERERERERERLGHg1JERERERERERKQ7DkoREREREREREZHuOChFRERERERERES646AUERERERERERHpjoNSRERERERERESkOw5KERERERERERGR7jgoFaOmTZuGxx57rMNr//u//4vMzEwsXLiww+tLlizBL37xiw6vybKMe++9F8XFxQHzrqurwxVXXIHDhw8HzTFlyhR89dVXZ33P8uXLUVBQ0OnPPB4PfvGLXwRk7sw111yD48ePB7xeUFCAzMzMtj8XX3wxZs2ahe+//77tPbIs45VXXkFBQQEuvvhiPPbYYzh9+nTQZRJR6NT206lTpzB79myMGjUKV111Ff7whz/A5/OddVmPPPII3nvvvbO+Z+PGjcjMzOzwWmVlJe677z7k5eXh6quvxvLly4P+u7pa1qOPPtqhg3JycnD77bejvLy80/n861//wrXXXtvhNa/XixdeeAFXXnkl8vLy8B//8R+oqakJmomIzk6r46XvvvsO9957Ly666CIUFBTgT3/6U9C+UnvMFMll3XnnnR36Ki8vD/fddx8qKys7nc+7776LO++8M+D1FStW4KqrrkJeXh7mzJkDp9N51jxEFJwRjp9atbS04Oc//zm2bt0a7J+l6fETAFx88cUd5pOZmcnzPMFwUCpGXXzxxdixY0eH17Zu3Yr09PSAcigtLcWoUaPa/r/P58MzzzyDzz77LGC+p06dwi9/+csOAzpdcTqd2LNnD7Kzs7t8z6FDh7Bo0aIuf/7qq6+ioqIi6LIqKyuRkJCAXr16dfrzOXPm4NNPP8X//d//4a9//StOnTqFRx55pO3nq1evxqJFi/DrX/8ab775Jo4fP47f/OY3QZdLRKFT209PPfUUTpw4gTfeeAMLFizAunXr8Je//OWsy/r8889x2WWXdfnz+vp6PPvssx1e8/l8mDZtGnr06IF169bhqaeewssvvxz04Oxsyxo9ejQ+/fRTfPrpp1i3bh1ycnLwwAMPBBwU7d69G//xH/8BWZY7vL506VJs2LABL774It5++22cOnUKv/3tb8+ah4iC0+J4yel0Ytq0aejVqxfWrl2LJ554Aq+//jrefPPNLnOoPWbSYln33nsvPv30U3zyySdYs2YNUlJSMH369IBe+vzzzzF37tyA6T/88EMsWrQIv/vd7/D666+jrKwMCxYs6DIPESkj+vFTK5fLhV//+tfYs2ePkn+WpsdPx48fR0NDA/72t7+1zefTTz9FYmKiomykDw5KxaiRI0fiu+++67DDbt26Fffddx9KS0vR3Nzc9npZWVlbaR0/fhz//u//js2bNyM5ObnDPP/1r3+hsLAQTU1NijL861//Qm5uLiwWS5fveeKJJ5CVldXpzyorK/GXv/wFgwcPDrqsLVu24PLLL+/y50lJSUhLS0OvXr2QlZWF//f//h8++eQTNDQ0AABWrlyJe+65Bz//+c8xZMgQPPfcc/j444+xb9++oMsmotCo7aeSkhLcc889GDJkCC677DL8/Oc/x5YtW7pczr59+9r2/a48//zz6NevX4fXampqkJWVhSeffBIDBw5Efn4+Lr/8cmzbtk31shISEpCWloa0tDQMGjQIDz/8MJqbm/H555+3veett97C7bffjnPPPTdgeq/Xi8ceewyXXHIJBg8ejDvvvPOseYhIGS2Ol7788kucOnUKTz31FAYNGoT8/HzcfffdZx3YVnvMpMWyEhMTkZaWhvT0dAwZMgSPPvoo9u7di927d7e9Z9GiRZg6dWpAfwLAX/7yF/z7v/87rrnmGmRnZ+Opp55CUVERr5YiCpPox08AsHfvXkyYMAEHDx5U9G/S+vjpu+++Q1paGvr169c2n7S0NEiSpCgf6YODUjHqwgsvhNVqxddffw0AOHbsGKqqqnDbbbchKSmp7ZLt/fv349SpU7j44osBAF9//TV69+6NoqIiJCUldZjnp59+inHjxim6lQ4IPlC0fv16OJ1OjB8/vtOfz507FzNnzkTPnj3DXtaZHA5HhzI6dOgQcnJy2v5/eno6evbsidLSUsXzJCJl1PZTSkoK3n33XTidThw/fhyffPJJl4PagL8XzvZbvi+++AJffPEFfvnLX3Z4PT09HS+++CK6d+8OWZaxbds2fPnllx2ukAh1WWeyWCyw2WwdXvu///s//P73v8fdd98d8P4ZM2bg+uuvBwB8//33ePvtt8+ah4iU0eJ4KSsrC4sXLw7YxxsbG7vMofaYSYtlncnhcAS89tlnn+GVV17Bz372sw6ve71e7Nixo209AUBubi7cbreiK9+JqGuiHz+1/uzSSy/F6tWrFf2btD5+2rt3L8477zzF86fo4KBUjLLZbMjJyWm75/bzzz/HiBEj0K1bN1xyySVtl3iWlpZiyJAh6NGjBwD/85eef/75TgeCfvWrX2H69Okwm82KMpztUsyTJ0/ihRdewO9+97tOR6qLiorgcrkwYcKEoMuRZTnoCWN7p0+fxvLly3H11Ve3HUiee+65HZ5H1dTUhFOnTqG2tlbRPIlIObX99MQTT2DLli246KKL8G//9m9IT0/HjBkzulzO559/3uWJV0tLC/7rv/4Lc+fORUJCQpfzKCgowKRJk5CXl4cbbrhB1bLO5PF48MYbb8BqtXboyCVLlgSc4J3ppZdewhVXXIGvvvoKjz76qKLlEVHXtDheSktLw6WXXtr2/5ubm7FmzZqznnipPWaK9LLO1NLSgj/96U9tz2Fp9eabb3Z63FVfXw+Xy4X09PS21ywWC1JSUnDs2DFFyySizhnh+GnSpEmYM2dOp4PZoS7rTGqOn7777js4nU7ceeed+OlPf4qpU6di//79ipZH+uGgVAy7+OKL20pr69atbQcto0aN6lBaWvy2va6uDsePH+/y4Xfz5s3DrbfeiiFDhgT87Pvvv8cf//jHLgeszlRRUYHevXvjnHPO6fI9TzzxBPLy8pCbm4uRI0figw8+wAMPPND28zFjxuDPf/4zvvvuO7hcLjz33HMAALfbHXT5RBQ6Nf20f/9+jBgxAm+++SYWLVqEPXv2YNmyZZ3O3+fz4V//+leX/bZ48WIMHz4cP/3pT8+a86WXXsKf/vQn7Nq1C/Pnz1e1LAB47733kJeXh7y8PGRnZ+N3v/sd7r//fnTr1u2syz/TL37xC6xduxaXX3457r333rNeDUFEymh5vOTz+fDoo4/i9OnTHY472gvnmCnSywKAP//5z219lZOTg+XLl2PGjBmKjslabx8680oGm82GlpaWoNMT0dkZ5fhJCT2On/bt24dTp07hwQcfxJIlS5CQkIC7776bx0+C4aBUDGv/MLytW7e27fCjRo3Czp070dLSgtLSUlxyySURX3br8jo7gPnkk09QWlqKhx56qNNpn332WRQWFmLo0KGKlqXkMvRZs2Zh/fr1eOedd/D222/jjjvuwL333tv2AL7p06djxIgRuOmmmzBy5EjYbDYMGzYM3bt3V5SBiEITaj8dOHAAv//97zFv3jzk5ubi+uuvx29/+1ssW7YMHo8nYP7ffPMN+vXrF3BbDQB8++23WLNmDebMmRM054UXXohrrrkGjz32GN56661OT6rOtqxWBQUFWL9+fdufJ598En/84x87/YbTsxkwYAAuvPBCPP/882hubsamTZtCmp6IAml1vOTxePDwww/j448/xpIlS7p8Zko4x0yRXFar22+/va2riouL8atf/Qq//vWvz/oMmlZ2ux0AArqypaVF8ZUTRNQ1oxw/KaHH8dMrr7yC9evX44orrkB2djZeeOEFuFwu/OMf/4jIv4Eio+unKZLh5eXl4cSJE9ixYwdOnDiBiy66CAAwZMgQJCUl4csvv8TevXs1uVLqbANFGzZswLFjx9p+7vF44Ha7kZeXh2XLluH9999HQkICVq5cCcD/W7ft27fjgw8+wPvvv9/psjq7h7i9c889FwMGDGj7/xdeeCFKSkpQXFyMRx55BImJifif//kfNDQ0QJIkdO/eHZdffjn69Omjcg0Q0dmE2k/ffPMNevTo0eGWkAsuuACnT5/GqVOnAh5uebYO2rRpE06dOtX2jCav19uW6amnnsIVV1yB0tJSXHfddW3TDB48GG63G42NjQG36ygZGO/WrVuHDho6dCh27dqFlStXorCw8KzTAsA//vEPXHDBBW3fMGq329GvXz/eYkwUAVocL7ndbvy///f/8Nlnn2Hp0qVt8+xMOMdMF198ccSW1eqcc87p0FdZWVn48ssv8eabbwadNiUlBXa7HTU1NTj//PPbMtfV1Z31oclEpIzIx0+33HJLSP8WPY6fbDZbhys37XY7+vbt2+GxLRR9HJSKYYmJicjKysLq1atx4YUXtv2GSpIkXHLJJSguLsbAgQMVPUg8VFu2bMF9993X6c9mz57d4cF4mzZtwl//+lf89a9/Ra9evQJ+8z979mzk5OTgnnvuCZiX2+1GeXk5Ro4cqSpna5k+//zzGDJkCG699VYAQHl5ORoaGpCXl6dqvkR0dqH2U3p6Ompra/H999+3HUDt27cPiYmJnXbY559/jvvvv7/TZU+ZMgU333xz2/8vKyvDww8/jPXr1+Pcc8/F3r17MWPGDJSUlLQNAu3cuRM9e/YMeVlnI8syfD6fovf+/ve/x6233tp2S05jYyMOHDjQdtJHROppcbw0d+5cfPbZZ20DR2cTzjFTJJd1NrIstx0znY3JZMKFF16Ibdu2td1WVFpaCovFgmHDhoW8XCLqSOTjp1BpffwkyzKuv/56TJ8+vW0Aq6mpCZWVlRg0aFDIyyXtcFAqxl1yySV46623cNddd3V4fdSoUXjhhRcwduzYiC/z2LFjcLvdnX5NKOC/aql9cZ177rmwWCxto+DtR8MB/1eBnnPOOZ1etVRWVoahQ4ee9UHFANDQ0IDq6moAgMvlwrp161BZWYkbb7wRgL+wFy1ahPPPPx8mkwkPP/ww7rjjDqSkpCj+dxNRaELpp9zcXJx//vn47W9/i0cffRS1tbV4/vnnMWXKlIDbUFpaWrBz584urxZISUnpsG+3Pny3tXsuvPBCDB8+HHPmzMFjjz2GI0eOYMGCBZ1+y0ywZbVqbm5u6yCfz4dt27bhvffew4MPPnjW6VpNnjwZCxcuxLBhw5CRkYE//vGP6N+/P/7t3/5N0fREdHaRPF767LPPUFxcjN/97ncYMGBA275vNpsDTgLDPWaK5LJaNTU1tc3H4/Fg8+bN2LJlCxYsWKDo3z9p0iTMnTsXQ4cORXp6Op588klMmDCBt+8RRYiox0+h0OP4SZIkXH311Vi4cCH69OmDnj174n/+53/wk5/8BPn5+SFnJu1wUCrGjRw5Eq+++mqHb2YB/KXldDo1u3UvlK/2DIfSb5CZN28e5s2bB8B/2ebgwYPx4osvthXhnXfeiSNHjmDq1KkwmUz4xS9+gdmzZ2uanSjehdJPFosFy5Ytw7PPPovJkycjMTERv/jFLzr99pjS0lIMGzas7dkmoTKbzViyZAmefvppTJw4EQ6HA3feeWfAwV8oy9q4cSM2btzY9m/5yU9+ggceeEDxbwgnT54Mp9OJJ598EidPnsSVV16Jl19+GSYTHw1JFAmRPF768MMPAfivYJo7d27b63369MHmzZs7vDfcYyYtlvXqq6/i1VdfBQBYrVYMGDAAc+fOxc9//nNFmW666SYcOXIEc+fORUtLC372s5/h4YcfVvpPIqIgRD1+CoVex08PP/wwLBYLfvOb36CxsRGXXXYZli5dqvjb5EkfkizLcrRDEBERERERERFRfOGvWImIiIiIiIiISHcclCIiIiIiIiIiIt1xUIqIiIiIiIiIiHTHQSkiIiIiIiIiItIdB6WIiIiIiIiIiEh3HJQiIiIiIiIiIiLdcVCKiIiIiIiIiIh0x0EpIiIiIiIiIiLSHQeliIiIiIiIiIhIdxyUIiIiIiIiIiIi3XFQioiIiIiIiIiIdMdBKSIiIiIiIiIi0h0HpYiIiIiIiIiISHcclCIiIiIiIiIiIt1xUIqIiIiIiIiIiHTHQSkiIiIiIiIiItKdRa8F+Xw+eDwemEwmSJKk12KJyABkWYbP54PFYoHJFJ2xcnYUEXUl2h3FfiKirrCfiEhUSvtJt0Epj8eDHTt26LU4IjKgCy+8EDabLSrLZkcRUTDR6ij2ExEFw34iIlEF6yfdBqVaR8ZGjxkNp+xSNQ9JktDTkYKTzjrIshzy9LLTC8gAJEBymJmBGZhBkAwOyY6NGzZG7SopIPyOCncdAOFvC2ZgBmbQJkO0O4r9xAzMwAxdMXo/AbFxLMsMzMAMgZT2k26DUq2XczplF8wTMlTNI9HqQNGUZbh55VQ0uZ0hT1+/Yi/k0x5I3SxInjCYGZiBGQTJ4FxTBeDHnoiGcDsq3HUAhL8tmIEZmEGbDNHuKPYTMzADM3TF6P0ExMaxLDMwAzMEUtpPfNA5ERERERERERHpjoNSRERERERERESkOw5KERERERERERGR7jgoRURhye6bhbF5NyA1NRVj825Adt+saEciIgLAfiIicbGfiEhkenaUbg86J6LYkWC1Y9zIMZiWPwU5/S5oe33JXfMBAGWHvsHSkpUo2rYBzW5138RCRKQG+4mIRMV+IiKRRaujeKUUEYXk/PSB+OLx97Fo8rMY0Sez0/eM6JOJRZOfxRePv49BaQN0TkhE8Yr9RESiYj8Rkcii2VEclCIixc5PH4i/zX4LGSm9IEkSzCZzp+8zm8yQJAkZKb3w94dX88CKiDTHfiIiUbGfiEhk0e4o1YNSLS0t+PnPf46tW7dGJAgRiS3Base6h5Yjyd4NFrOyO38tZguS7N2wfsYrSLDaNU74I/YTUXxhPxGRqNhPRCQyETpK1aCUy+XCr3/9a+zZsyfsAERkDONGjkG/nhmKy6qVxWxB/3P7oPCi0Rol64j9RBR/2E9EJCr2ExGJTISOCnlQau/evZgwYQIOHjwY9sKJyDim5U+BT/apmtbr82Ja/pQIJwrEfiKKT+wnIhIV+4mIRCZCR4U8KPXFF1/g0ksvxerVq8NeOBEZQ3bfLOT0u6DL+4uDMZvMyO0/XPOvO2Y/EcUf9hMRiYr9REQiE6WjQrtGC8CkSZPCWqAkSUi0OlRN67AmdPg7VA2SBJkZmIEZQs4wIqPzb2AI1fCModh7/EDA642SFJH5h9tPgPptEe52AML/PDADM8RjBq37CYhMR7GfmIEZ4i8D+0mZeDmeZgZmEC2DKOd4kizLstqFZ2Zm4i9/+QsuvfTSoO/1er0oLS3FuHHjUFRUpHaRYRkzZgxOnDiB9PR0bNiwgRmYgRkUZkhNTcWAAeF/u0JlZSVqamoCXm/thdzcXJjN6kbqzxRKPwHsKGZgBqNm0LqfgMh3FPuJGZghPjKwn/RhhM8CMzCDiBlEOccL+UqpcJ101uHmlVNVTeuwJmDNxIWYsHomnO7mkKevaapt+5sZmIEZlGcYm3cDltw1X1W+9p4reRnvbN8U8Hqjsy7seUeK2o4KdzsA4X8emIEZ4jGD1v0EiNNR7CdmYAZjZWA/KRMvx9PMwAyiZRDlHE/3QSlZltHkdoY1D6e7WdU8Wi8KYwZmYIbQMuys2h1Wtrb5HNnd6TLCuGAz4sLdFmq3Q+uymYEZmCG0DFr3U/sM0SbydmAGZmAG9pPIx7LMwAzMEEiUc7yQH3RORPGn/PAulB36Bl6fV9X0Xp8XpQe/xo4jFRFORkTxjv1ERKJiPxGRyETpKA5KEZEiS0tWwiSpqwyzyYylJSsjnIiIyI/9RESiYj8RkchE6CgOShGRIkXbNuDQySp4vJ6QpvN4PTj4/REUf7VRo2REFO/YT0QkKvYTEYlMhI4Ka1Bq9+7dir+ZgYiMrdntwq2L70eD67Ti0vJ4PWhwncbYRfeh2e3SOGFH7Cei+MF+IiJRsZ+ISGQidBSvlCIixb47cQDXLpiIqrrjANDl/cetr1fVHce1CyZiX3WlbhmJKD6xn4hIVOwnIhJZtDtK92/fIyJj21ddiVHP3ITCi0ZjWv4U5PYfHvCeHYcrsLRkJYq/2qj7b/iIKH6xn4hIVOwnIhJZNDuKg1JEFLJmtwurtq7Hqq3rkd03C8MzhuLR/AfxXMnL+LrqW5Qf3hXtiEQUp9hPRCQq9hMRiSxaHcVBKSIKS/nhXdh7/ADuH34b3tm+CU1uZ7QjEREBYD8RkbjYT0QkMj07is+UIiIiIiIiIiIi3XFQioiIiIiIiIiIdMdBKSIiIiIiIiIi0p0ky7Ksx4K8Xi9KS0uRf3U+mmR1T2qXJAmpiT1Q01QLNbHlJg8gA5AAKVHd47SYgRmYIfIZEiU7Sj4uQW5uLsxms6oM4Qq3o8JdB0D424IZmIEZtMkQ7Y5iPzEDMzBDV4zeT0BsHMsyAzMwQyCl/aT/g85lQD7tUTspTjSeYAZmYIZYy9DNrn7aSFO5HiK2HZiBGZhBvAyidFS8bwdmYAZmCGTwfvphUuMfyzIDMzBDIIX9pP+glARI3eJ3tJAZmIEZOpuBqsVqQ2VHxcpvXJmBGZihs5momyzi2E/MwAzMEDATdZNFHM/xmIEZmCFgBsrepvuglOQwI3nCYFXTJlodeG/KMty8cqqqrySsX7EX8mkPpEQLku9mBmZgBlEyeNdUqVquFtR2VLjrAAh/WzADMzCDNgJ6TkoAAQAASURBVBlE6Sj2EzMwAzOcyej9BMTGsSwzMAMzBFLaT3zQORERERERERER6Y6DUkREREREREREpDsOShERERERERERke44KEWG5K1uhrPiJIqLi+GsOAlvdXO0I0VFdt8sjM27AampqRibdwOy+2ZFOxJR3GM/+bGfiMTDfvJjPxGJiR3lF28dpf+37xGpJHt8cO+ph6u8Fr4aFwBg3gfz2n5uSrXDnt0D1iHJkCyxO96aYLVj3MgxmJY/BTn9Lmh7fcld8wEAZYe+wdKSlSjatgHNble0YhLFFfaTH/uJSDzsJz/2E5GY2FF+8dxRHJQiQ/DWteD0uwchN3i6fI+vxgXn5mNo/rIG3W7pD3OKTceE+jg/fSDWPbQc/XpmwCf7On3PiD6ZWDT5WTwy+iGMXXQf9lVX6pySKL6wn/zYT0TiYT/5sZ+IxMSO8ov3jordoUaKGd66FjSuPQC5seuyak9u9KBx7QF461o0Tqav89MH4m+z30JGSi9IkgSzydzp+8wmMyRJQkZKL/z94dUYlDZA56RE8YP95Md+IhIP+8mP/UQkJnaUHzsqxEGp48ePY9asWRg1ahSuuuoqzJ8/Hy5XbF06RmKRPT6cfvcg0OIDZKUTAWjxTyd7Oh9pNpoEqx3rHlqOJHs3WMzKLnC0mC1IsnfD+hmvIMFq1zihGNhRpCf2kx/7SRn2E+mJ/eTHflKG/UR6Y0f5saP8FA9KybKMWbNmwel04o033sB///d/4x//+AdefPFFDeNRvHPvqfdfzqm0rFrJgNzggXtPvSa59DZu5Bj065mhuKxaWcwW9D+3DwovGq1RMnGwo0hv7Cc/9lNw7CfSG/vJj/0UHPuJooEd5ceO8lM8KLVv3z6UlpZi/vz5GDJkCC6++GLMmjUL//u//6tlPopzrvLaqE4vimn5U7q8vzgYr8+LaflTIpxIPOwo0hv7yY/9FBz7ifTGfvJjPwXHfqJoYEf5saP8FA9KpaWlYfny5UhNTe3wemNjY8RDEQH+rwRt/QYGtXw1LsN/lWh23yzk9Lugy/uLgzGbzMjtPzzmv0qUHUV6Yj/5sZ+UYT+RnthPfuwnZdhPpDd2lB876keKrxNLTk7GVVdd1fb/fT4fVq5cicsuuyykBUqShESrI6RpWjmsCR3+DlWDJEFmBsNkcNY7Vc37TJYGwJERuAyjrIcRGZmq5n2m4RlDsff4AVUZggl3PTRKkqrp2ot2R4W7DoDwtwUz6JdB635SkiEYPdaD1v2kJEMwkVgP4XYU+4kZ9MzAfvJjPykT7X4C4ufchhn8eI7nx3O8H0myLId6JycA4Pe//z3eeOMNrF27FkOHDg36fq/Xi9LSUowbNw5FRUVqFhm2MWPG4MSJE0hPT8eGDRuYQfAMxcXFmDdvXtjLmjNnDgoLC1Vl0JqSDKmpqRgwIPxvV6isrERNTY2qDFpr7YXc3FyYzep+W3AmdhQzaJlB635SkkEPwTJo3U9KMugh0h3FfmIGLTOwn/zYT+qwn5hB6ww8x/PjOd6PQnui1g8WLFiA119/Hf/93/+tqKzaO+msw80rp6pZLBzWBKyZuBATVs+E0x365Xo1TbVtfzOD+BmcFSdVZTvTku2r8FrTRlUZgtFjPYzNuwFL7pqvKl97z5W8jHe2b1KVIZhw10Ojs07VcrsSjY4Kdx0A4W8LZtAvg9b9pCRDMHqsB637SUmGYCKxHiLZUewnZmA/sZ9asZ/84uXchhn8eI7nx3O8H4U8KPX000/jzTffxIIFC3DDDTeEOjlkWUaTO7xL9pzuZlXzaL0ojBmMkcGbHP4tXQDgSUKnyzDKethZtTusbG3zObJb+PUQCdHuKLXroHXZzGCMDFr3k5IMSmm5HrTuJyUZlIrEeggX+4kZ9MjAfvJjP4Um2v0ExP65DTP48RzPj+d4P1L8oHMAWLRoEd566y388Y9/xE033RRyKKJQmNMSYEq1hzUPU6od5jT19+mLoPzwLpQd+gZen1fV9F6fF6UHv8aOIxURTiYedhTphf3kx35Sjv1EemE/+bGflGM/kZ7YUX7sqB8pHpT67rvvsGTJEkydOhUjR45EdXV12x8irdize0R1elEsLVkJkxTSGHIbs8mMpSUrI5xIPOwo0hv7yY/9FBz7ifTGfvJjPwXHfqJoYEf5saP8FK+Bv//97/B6vXj55Zfx05/+tMMfIq1YhyRDSrIAoV7lKQFSkgXWIcma5NJb0bYNOHSyCh6vJ6TpPF4PDn5/BMVfdf5MiFjCjiK9sZ/82E/BsZ9Ib+wnP/ZTcOwnigZ2lB87yk/xoNS0adOwe/fuTv8QaUWymNDtlv6AzaS8tCQANv90kkXdyLNomt0u3Lr4fjS4TisuLY/XgwbXaYxddB+a3S6NE0YfO4r0xn7yYz8Fx34ivbGf/NhPwbGfKBrYUX7sKL/Y2JoU08wpNnQfPxBSd2XP5Ze6W9B9/ECYU2waJ9PXdycO4NoFE1FVdxwAurz/uPX1qrrjuHbBROyrrtQtI1G8YT/5sZ+IxMN+8mM/EYmJHeXHjlLx7XtE0WBOsSFp0iC499TDVV4LX03gqLAp1Q57dg//5aAxMnp+pn3VlRj1zE0ovGg0puVPQW7/4QHv2XG4AktLVqL4q40xM3pOJDL2kx/7iUg87Cc/9hORmNhRfvHeURyUIsOQLCbYslJgy0qBt7oZlgZget4kLNm+Cp4kGP4bGJRqdruwaut6rNq6Htl9szA8YygezX8Qz5W8jK+rvkX54V3RjkgUd9hPfuwnIvGwn/zYT0RiYkf5xXNHxeZQI8U8c1oCHJk9UFhYCEdmj7gpqzOVH96Fd7ZvQk1NDd7Zvimmy4rIKNhPfuwnIvGwn/zYT0RiYkf5xVtHcVCKiIiIiIiIiIh0x0EpIiIiIiIiIiLSHQeliIiIiIiIiIhIdxyUIiIiIiIiIiIi3UmyLMt6LMjr9aK0tBT5V+ejSVb3FYaSJCE1sQdqmmqhJrbc5AFkABIgJar74kFmYAZmiHyGRMmOko9LkJubC7PZrCpDuMLtqHDXARD+tmAGZmAGbTJEu6PYT8zADMzQFaP3ExAbx7LMwAzMEEhpP6lLFw4ZkE971E6KE40nmIEZmCHWMnSzq5820lSuh4htB2ZgBmYQL4MoHRXv24EZmIEZAhm8n36Y1PjHsszADMwQSGE/6T8oJQFSt/gdLWQGZmCGzmagarHaUNlRsfIbV2ZgBmbobCbqJos49hMzMAMzBMxE3WQRx3M8ZmAGZgiYgbK36T4oJTnMSJ4wWNW0iVYH3puyDDevnIomtzPk6etX7IV82gMp0YLku5mBGZhBlAzeNVWqlqsFtR0V7joAwt8WzMAMzKBNBlE6iv3EDMzADGcyej8BsXEsywzMwAyBlPYTH3RORERERERERES646AUERERERERERHpjoNSRERERERERESkOw5KUciy+2ZhbN4NSE1Nxdi8G5DdNysuM3irm+GsOIni4mI4K07CW92sewYR1gORSETYJ0TIwH4iEo8I+4QIGdhPRGISYb8QIQM7Sn/6f/seGVKC1Y5xI8dgWv4U5PS7oO31JXfNBwCUHfoGS0tWomjbBjS7XTGbQfb44N5TD1d5LXw1/mXM+2Be289NqXbYs3vAOiQZkkWbMV8R1gORSETYJ0TIwH4iEo8I+4QIGdhPRGISYb8QIQM7Kro4KEVBnZ8+EOseWo5+PTPgk32dvmdEn0wsmvwsHhn9EMYuug/7qitjLoO3rgWn3z0IucHT5Xt8NS44Nx9D85c16HZLf5hTbBHNIMJ6IBKJCPuECBnYT0TiEWGfECED+4lITCLsFyJkYEdFX8jDfJWVlbjvvvuQl5eHq6++GsuXL9ciFwni/PSB+Nvst5CR0guSJMFsMnf6PrPJDEmSkJHSC39/eDUGpQ2IqQzeuhY0rj0AubHrsmpPbvSgce0BeOtaIpZBhPUgOvZTfBFhnxAhA/vJGNhP8UWEfUKEDOwnY2A/xR8R9gsRMrCjxBDSoJTP58O0adPQo0cPrFu3Dk899RRefvllvPfee1rloyhKsNqx7qHlSLJ3g8Ws7KI6i9mCJHs3rJ/xChKs9pjIIHt8OP3uQaDFB8hKJwLQ4p9O9nQ+2h0KEdaD6NhP8UWEfUKEDOwnY2A/xRcR9gkRMrCfjIH9FH9E2C9EyMCOEkdIg1I1NTXIysrCk08+iYEDByI/Px+XX345tm3bplU+iqJxI8egX88MxTtIK4vZgv7n9kHhRaNjIoN7T73/ck6lZdVKBuQGD9x76sPOIMJ6EB37Kb6IsE+IkIH9ZAzsp/giwj4hQgb2kzGwn+KPCPuFCBnYUeIIaVAqPT0dL774Irp37w5ZlrFt2zZ8+eWXGDVqlFb5KIqm5U/p8p7WYLw+L6blT4mJDK7y2qhOD4ixHkTHfoovIuwTImRgPxkD+ym+iLBPiJCB/WQM7Kf4I8J+IUIGdpQ4VD86vqCgAJMmTUJeXh5uuOGGSGYiAWT3zUJOvwu6vKc1GLPJjNz+w8P6+koRMnirm9u+gUEtX40rrK8SFWE9GA37KbaJsE+IkIH9ZEzsp9gmwj4hQgb2kzGxn2KfCPuFCBnYUWJR/e17L730EmpqavDkk09i/vz5ePzxxxVNJ0kSEq0OVct0WBM6/B2qBkmCzAyKMozIyFQ17zMNzxiKvccPGDaDs94ZkQyWBsCREbgMo6yHYML9TDZKkqrpuqK2nwD16yHcdQCEvy3iJYPW+4RRMmjdT0oyiLAegonEZzKSHcV+iu0MIuwTImRgPynDfvKLl/MrETKIcF4hQgae4ymj1zmeJMtyqHdRdvDBBx9g9uzZ+Oqrr2Czdf3ViF6vF6WlpRg3bhyKiorCWaRqY8aMwYkTJ5Ceno4NGzYww1kypKamYsCA8J/oX1lZiZqaGsNmKC4uxrx588LOMGfOHBQWFqrKIMJ60FprL+Tm5sJsVvfbgs4o7SeAHWWkDFrvE0bJoHU/KckgwnrQgxYdxX6KzQwi7BMiZGA/6Yf9JMZ2MEoGEc4rRMjAczx9KO2nkK6UqqmpQWlpKa677rq21wYPHgy3243Gxkb07Nkz6DxOOutw88qpoSy2jcOagDUTF2LC6plwukO/VK6mqbbtb2Y4e4axeTdgyV3zVeVr77mSl/HO9k2GzeCsOBn28gFgyfZVeK1po6oMIqyHYML9TDY661Qtt71I9BOgvqPCXQdA+NsiXjJovU8YJYPW/aQkgwjrIZhIfCbD7Sj2U/xkEGGfECED+0kZ9pNfvJxfiZBBhPMKETLwHE8Zvc7xQhqUOnz4MGbMmIGSkhL06tULALBz50707NlTcWHJsowmd3iXyzndzarm0XpRGDMEz7CzandY2drmc2R3p8swSgZvcmQuifYkwdDrQalwP5PhiEQ/tWYJZz2oXQety2aG4Bm03ieMkkHrflKSQYT1oFQkPpNqsZ/iJ4MI+4QIGdhPoWE/+cX6+ZUIGUQ4rxAhA8/xQqP1OV5IDzq/8MILMXz4cMyZMwd79+5FSUkJFixYgF/+8pchBySxlR/ehbJD38Dr86qa3uvzovTg19hxpMLQGcxpCTCl2lVPDwCmVDvMaeqfFSDCejAC9lP8EGGfECED+8k42E/xQ4R9QoQM7CfjYD/FFxH2CxEysKPEEtKglNlsxpIlS+BwODBx4kT853/+J+68807cddddWuWjKFpashImSd0XNJpNZiwtWRkTGezZPaI6PSDGehAd+ym+iLBPiJCB/WQM7Kf4IsI+IUIG9pMxsJ/ijwj7hQgZ2FHiCHkN9OrVC4sWLcK2bdvw6aef4pe//CWkCH9zFomhaNsGHDpZBY/XE9J0Hq8HB78/guKvOn8GgNEyWIckQ0qyAKF+zCVASrLAOiQ57AwirAcjYD/FDxH2CREysJ+Mg/0UP0TYJ0TIwH4yDvZTfBFhvxAhAztKHOqG5SguNLtduHXx/WhwnVa8o3i8HjS4TmPsovvQ7HbFRAbJYkK3W/oDNpPy0pIA2PzTSZbwdzMR1gORSETYJ0TIwH4iEo8I+4QIGdhPRGISYb8QIQM7ShwclKKz+u7EAVy7YCKq6o4DQJf3vLa+XlV3HNcumIh91ZUxlcGcYkP38QMhdVf23QBSdwu6jx8Ic8rZv0Y3FCKsByKRiLBPiJCB/UQkHhH2CREysJ+IxCTCfiFCBnaUGEL69j2KT/uqKzHqmZtQeNFoTMufgtz+wwPes+NwBZaWrETxVxs1GbEVIYM5xYakSYPg3lMPV3ktfDWByzCl2mHP7uG/HDQCo+dnEmE9EIlEhH1ChAzsJyLxiLBPiJCB/UQkJhH2CxEysKOij4NSpEiz24VVW9dj1db1yO6bheEZQ/Fo/oN4ruRlfF31LcoP74qLDJLFBFtWCmxZKfBWN8PSAEzPm4Ql21fBk4SwvoFBKRHWA5FIRNgnRMjAfiISjwj7hAgZ2E9EYhJhvxAhAzsqujgoRSErP7wLe48fwP3Db8M72zehye2MywzmtAQ4MhwoLCzEa00b43Y9EIlEhH1ChAzsJyLxiLBPiJCB/UQkJhH2CxEysKP0x2dKERERERERERGR7jgoRUREREREREREuuOgFBERERERERER6U6SZVnWY0FerxelpaXIvzofTbK6p8VLkoTUxB6oaaqFmthykweQAUiAlKjucVrMwAzMEPkMiZIdJR+XIDc3F2azWVWGcIXbUeGuAyD8bcEMzMAM2mSIdkexn5iBGZihK0bvJyA2jmWZgRmYIZDSftL/QecyIJ/2qJ0UJxpPMAMzMEOsZehmVz9tpKlcDxHbDszADMwgXgZROiretwMzMAMzBDJ4P/0wqfGPZZmBGZghkMJ+0n9QSgKkbvE7WsgMzMAMnc1A1WK1obKjYuU3rszADMzQ2UzUTRZx7CdmYAZmCJiJuskijud4zMAMzBAwA2Vv031QSnKYkTxhsKppE60OvDdlGW5eOVXV1yLWr9gL+bQHUqIFyXczAzMwgygZvGuqVC1XC2o7Ktx1AIS/LZiBGZhBmwyidBT7iRmYgRnOZPR+AmLjWJYZmIEZAintJz7onIiIiIiIiIiIdMdBKSIiIiIiIiIi0h0HpYiIiIiIiIiISHf6P+hcJW91M5z1ThQXF8NZcRLeZAnmtARmYIaoZcjum4URGZlITU3F2LwbsLNqN8oP79I1gwjrgcTYDszADMxAnRFhOzCDOBl47CJOBvITYVswgzgZ2FHiZNCT0INSsscH9556uMpr4atxAQDmfTCv7eemVDvs2T1gHZIMyaLNRV/MwAztJVjtGDdyDKblT0FOvwvaXl9y13wAQNmhb7C0ZCWKtm1As9ulSQYR1gOJsR2YgRmYgTojwnZgBnEy8NhFnAzkJ8K2YAZxMrCjxMkQLcIOSnnrWnD63YOQGzxdvsdX44Jz8zE0f1mDbrf0hznFxgzMoFmG89MHYt1Dy9GvZwZ8sq/T94zok4lFk5/FI6MfwthF92FfdWVEM4iwHkiM7cAMzMAM1BkRtgMziJOBxy7iZCA/EbYFM4iTgR0lToZoUj3ENm3aNDz66KORzNLGW9eCxrUHIDd2vVHakxs9aFx7AN66FmZgBk0ynJ8+EH+b/RYyUnpBkiSYTeZO32c2mSFJEjJSeuHvD6/GoLQBEcsgwnowEq06SoTtwAzMwAzGxn5iBj0y8NhFnAxGwnM8ZtArAztKnAzRpmpQ6v3330dJSUmkswDwX7Z2+t2DQIsPkJVOBKDFP53s6XyElRmYQa0Eqx3rHlqOJHs3WMzKLi60mC1IsnfD+hmvIMFqDzuDCOvBSLTqKBG2AzMwAzMYG/uJGfTIwGMXcTIYCc/xmEGvDOwocTKIIORBqbq6Ojz//PO48MILtcgD9556/2VrSjdKKxmQGzxw76lnBmaIaIZxI8egX88MxYXZymK2oP+5fVB40eiwM4iwHoxCy44SYTswAzMwg3Gxn5hBrww8dhEng1HwHI8Z9MzAjhIngwhCHpT6/e9/j1/84hcYPHiwFnngKq+N6vTMwAxnmpY/pct7nIPx+ryYlj8l7AwirAej0LKjRNgOzMAMzGBc7Cdm0CsDj13EyWAUPMdjBj0zsKPEySCCkAaltmzZgn/961+YPn26JmG81c1tT5pXy1fjgre6mRmYISIZsvtmIaffBV3e4xyM2WRGbv/hyO6bpTqDCOvBKLTsKBG2AzMwAzMYF/uJGfTKwGMXcTIYBc/xmEHPDOwocTKIQvH1ci6XC0888QTmzp2LhIQE1QuUJAmJVkenP3PWO1XPtz1LA+DICFxGgyRBZgZmCCHDiIzMiGQYnjEUe48fUJVBhPUQjMOa0OHvUDVKkqrp2tO6o7TeDkDwbcEMzMAMoXdUuP0EhN9R7Cdm0DOD1scuSjKIsB5EyBBMPPQTIMaxLDOIk4HnV+JkCEavczzFg1KLFi3CiBEjcNVVV6kK1KqnIwVFU5Z1+rPi4mLM+2BeWPMHgOl5k1BYWBjw+phVY3Ci8QRSE3vgPWZgBgUZUlNTw14+ADya/yDuH36bqgwirAel1kxcqGq6cevGhbVcQPuO0no7AMG3BTMwAzOo7yi1/QSE31HsJ2bQM4PWxy5KMoiwHkTIoFQs9xMgxrEsM4iTgedX4mRQSutzPEmWZUWP1SooKEBNTQ3MZv9ldi0t/q8gtNls2L59e9DpvV4vSktLcc2Ya9F90qBO3+OsOIm6DyoVBT+blNED4cjsEfD68eU74Wt0w9Tdil73j2AGZgiaYWzeDVhy1/ywMzz4l0fxzvZNqjKIsB6CcVgTsGbiQkxYPRNOd+iXkDau2od/bPg7cnNz2zomVFp3lNbbAQi+LZiBGZgh9I4Kt5+A8DuK/cQMembQ+thFSQYR1oMIGYKJh34CxDiWZQZxMvD8SpwMweh1jqf4Sqm//vWv8Hg8bf//hRdeAADMnj07pGCyLKPJ3fmlat7k8G/hAQBPEjpdRuv4GzMwg9IMO6t2RyTDziO7Db0elHK6m1XNQ+HY+Flp3VFab4fWZTMDMzBDaBmUUttP7TOoxX5iBj0zaH3soiSDCOtBhAxKxXI/AWIcyzKDOBl4fiVOBqW0PsdTPCjVp0+fDv+/W7duAIABAwaEEOvszGkJMKXaw3rglynVDnOa+vuhmYEZ2is/vAtlh77BiD6Zqh7G5/V5seNwBXYcqVCdQYT1YARad5QI24EZmIEZjIn9xAx6ZuCxizgZjIDneMygdwZ2lDgZRBHSt+/pwZ7d+eWxek3PDMxwpqUlK2GS1O0qZpMZS0tWhp1BhPVAYmwHZmAGZqDOiLAdmEGcDDx2EScD+YmwLZhBnAzsKHEyiED1oNRzzz2H5557LpJZAADWIcmQkixAqFezSYCUZIF1SDIzMENEMxRt24BDJ6vg8XqCv7kdj9eDg98fQfFXG8POIMJ6MBotOkqE7cAMzMAMxsd+YgatM/DYRZwMRsNzPGbQIwM7SpwMIhDuSinJYkK3W/oDNpPyjSMBsPmnkyzh/5OYgRnaa3a7cOvi+9HgOq24OD1eDxpcpzF20X1odqu/JLOVCOuBxNgOzMAMzECdEWE7MIM4GXjsIk4G8hNhWzCDOBnYUeJkEIGQ/wpzig3dxw+E1F3ZI6+k7hZ0Hz8Q5hQbMzCDJhm+O3EA1y6YiKq64wD89zJ3pvX1qrrjuHbBROyrroxYBhHWA4mxHZiBGZiBOiPCdmAGcTLw2EWcDOQnwrZgBnEysKPEyRBtih90rjdzig1JkwbBvacervLaTh8AZkq1w57dw3/ZmwajhMzADO3tq67EqGduQuFFozEtfwpy+w8PeM+OwxVYWrISxV9tjMgI/plEWA8kxnZgBmZgBuqMCNuBGcTJwGMXcTKQnwjbghnEycCOEidDNAk7KAX4L2ezZaXAlpUCb3UzLA3A9LxJWLJ9FTxJ0OVJ88zADO01u11YtXU9Vm1dj+y+WRieMRSP5j+I50pextdV36L88C7NM4iwHkiM7cAMzMAM1BkRtgMziJOBxy7iZCA/EbYFM4iTgR0lToZoMcwQmzktAY7MHigsLIQjs0dUNgozMEN75Yd34Z3tm1BTU4N3tm/SpTDPJMJ6IDG2AzMwAzNQZ0TYDswgTgYeu4iTgfxE2BbMIE4GdpQ4GfRkmEEpIiIiIiIiIiKKHRyUIiIiIiIiIiIi3XFQioiIiIiIiIiIdCfJsizrsSCv14vS0lLkX52PJlndU/MlSUJqYg/UNNVCTWy5yQPIACRASlT3jHdmYAZmiHyGRMmOko9LkJubC7PZrCpDuMLtqHDXARD+tmAGZmAGbTJEu6PYT8zADMzQFaP3ExAbx7LMwAzMEEhpP+n/7XsyIJ/2qJ0UJxpPMAMzMEOsZehmVz9tpKlcDxHbDszADMwgXgZROiretwMzMAMzBDJ4P/0wqfGPZZmBGZghkMJ+0n9QSgKkbvE7WsgMzMAMnc1A1WK1obKjYuU3rszADMzQ2UzUTRZx7CdmYAZmCJiJuskijud4zMAMzBAwA2Vv031QSnKYkTxhsKppE60OvDdlGW5eORVNbmfI09ev2Av5tAdSogXJdzMDMzCDKBm8a6pULVcLajsq3HUAhL8tmIEZmEGbDKJ0FPuJGZiBGc5k9H4CYuNYlhmYgRkCKe0nPuiciIiIiIiIiIh0x0EpIiKiWOXzRTsBEREREVGX9H+mFBEREWkip7oZk3fV4fIqJzJrW2B7cRQOmCTs7mHDlgwH3shKQVlaQrRjEhEREREB4KCU4Xirm+Gsd6K4uBjOipPwJksw63yCkd03CyMyMpGamoqxeTdgZ9VulB/eFXcZiKgjEfopXjOcV9eCRZuP4sqjTrglYKcMFAFoAJDkkzHsexfuOenCtB11+Ky3AzMKemN/ik3TTEQiidduEDEDj+GIAomwbzKDHztKfxyUMgDZ44N7Tz1c5bXw1bgAAPM+mNf2c1OqHfbsHrAOSYZk0eaOzASrHeNGjsG0/CnI6XdB2+tL7poPACg79A2WlqxE0bYNaHa7YjYDEXUkQj/Fe4bx357C4s3H0OKV8RqAl2SgtJP35crALADjjzrx+Vv7Mb2gN4qGJkc0C5FI4r0bRMrAYziiQCLsm8zgx46KLg5KCc5b14LT7x6E3ODp8j2+Ghecm4+h+csadLulP8wR/u33+ekDse6h5ejXMwM+ufPnk4zok4lFk5/FI6MfwthF92FfdWXMZSCijkTop3jPMP7bU1j60VF8C+BGAJXo+mGR5QDuBfAUgA+9MpZ9VAUJMtYOPSciWYhEEu/dIFIGHsMRBRJh32QGP3ZU9IU81PjRRx8hMzOzw59Zs2ZpkS3ueeta0Lj2AOTGrnfS9uRGDxrXHoC3riViGc5PH4i/zX4LGSm9IEkSzCZzp+8zm8yQJAkZKb3w94dXY1DagJjKQMbAftKPCP0U7xkG1bVg8eZj+BbAFQAO//B6V482b339MIDLAewBsHjzMZwXwfVBXWM/6Sfeu0GkDDyGMwb2k75E2DeZwY8dJYaQB6X27t2La665Bp9++mnbn2eeeUaLbHFN9vhw+t2DQIsPkJVOBKDFP53sCf8blxKsdqx7aDmS7N1gMSu7qM5itiDJ3g3rZ7yCBKs9JjKQcbCf9CFCPzEDsHDzUbi8Mm4EUA/Aq3A67w/vvwFAi1fGos1Hw8pByrCf9BHt/ZIZfsRjOONgP+lHhH2TGfzYUeIIeVDqu+++w9ChQ5GWltb2JzmZz6SINPeeev9ljEp30lYyIDd44N5TH3aGcSPHoF/PDMU7aSuL2YL+5/ZB4UWjYyIDGQf7SR8i9FO8Z8g50YwrjzpRBP8te0oHpFp5f5iuCMCVR53IqW5WnYWUYT/pI967QaQMPIYzDvaTfkTYN5nBjx0lDlWDUgMHDtQgCrXnKq+N6vQAMC1/Spf31Qbj9XkxLX9KTGQg42A/6UOEfor3DJMr6uCWgJeg4j/kPzDBP71bAibvqlOdhZRhP+kj3rtBpAw8hjMO9pN+RNg3mcGPHSWOkI5lZVnG/v378emnn+KGG27AddddhxdeeAEtLXweRSR5q5vbvnlALV+NC94wfvOd3TcLOf0u6PK+2mDMJjNy+w9Hdt8sQ2cg42A/6UOEfmIG4PIqJ3b+8C17ai9g9wHYDmCnDFx21KlyLqQE+0kf0d4vmeFHPIYzDvaTfkTYN5nBjx0llpCuVauqqoLT6YTNZsOLL76Iw4cP45lnnkFzczMef/xxRfOQJAmJVoeqsA5rQoe/Q9UgSZANkMFZH5mTA0sD4MgIXIaSDCMyMiOSYXjGUOw9fsCwGYKJl8+k1hkaJUnVdO1Fop8A9esh3HUAhL8t9MigdT8xg7IMmbUtKIpIAmA3gMKTLZ3+O43wmdQjQ7gdxX5iP8VbBq2P4ZRkCCZW9guj9xMQG8eyRjnHYwY/nmfqk0FpP0myLId0J2ddXR3OOeccSD8s4MMPP8TDDz+M7du3w2zueqTR6/WitLQU48aNQ1FRpA6lQzNmzBicOHEC6enp2LBhg7AZiouLMW/evLCXNWfOHBQWFqrKkJqaigEDwv9WgcrKStTU1Bg2g9aYwa+1F3Jzc8/aI8Go7SeAHaU0g9b9xAwKMvh8GDlqFJYCeCDsBMCfAUwDsO2LLwBTxwuojfCZ1EMkOor9pH2GuO8GgTJofQynJIMeRMjAfhJjOxjlHI8Z/HieqQ+l/RTaU70ApKSkdPj/559/PlwuF06dOoWePXsGnf6ksw43r5wa6mIB+Efo1kxciAmrZ8LpDv1yvZqm2ra/Rc7grDipKtuZlmxfhdeaNqrKMDbvBiy5a37YGZ4reRnvbN9k2AzBxMtnUusMjc46Vcs9U7j9BKjvqHDXARD+ttAjg9b9xAzKMhwwSUjyhfp00M4lA2gxSbh5VeAQlxE+k3pkiERHsZ/YT/GUQetjOCUZgomV/cLo/QTExrGsUc7xmMGP55n6ZFDaTyENSn3yySeYPXs2Pv74Yzgc/kvAdu3ahZSUFMWFJcsymtzhXbLndDermkfrRWGiZ/Amh38rEwB4ktDpMpRk2Fm1OyIZdh7ZbegMSsX6Z1KvDOGIRD+1ZglnPahdB63LFj2D1v3EDMoy7O5hw7Dvw3seQ6thACp62jTtyVjZL9RiP+mTIdr7JTP8SOtjOCUZlIqV/UItUfoJiI1jWdHP8ZjBj+eZ+mYIJqQHnefl5cFut+Pxxx/Hvn37UFJSgueffx73339/yAGpa+a0BJhS7WHNw5RqhzlN/f3p5Yd3oezQN/D6Qv2icT+vz4vSg19jx5EKQ2cg42A/6UOEfmIGYEuGAyMkIBfhffteHoDhEvB5b3XPGiBl2E/6iPZ+yQw/4jGccbCf9CPCvskMfuwosYR0LNu9e3e88sorOHnyJMaNG4f//M//xMSJE1laGrBn94jq9ACwtGQlTJK60x2zyYylJStjIgMZA/tJPyL0U7xneCMrBVYZmIXwvn1vFgCr7J8faYf9pJ947waRMvAYzhjYT/oSYd9kBj92lDhCfqbUkCFD8Nprr2mRhdqxDklG85c1kBs9QChX5UqA1N0C65DksDMUbduAR0Y/hIyUXrCYlX9UPF4PquqOo/irzp9DYLQMZBzsJ32I0E/xnqEsLQGf9XZg/FEnngJwGEAov+szA+gLYByAz3o7UBbGbxtJGfaTPuK9G0TKwGM442A/6UeEfZMZ/NhR4lB71T9pTLKY0O2W/oDNBCi97VYCYPNPJ1nC37TNbhduXXw/Glyn4fF6FE3j8XrQ4DqNsYvuQ7M7/OediJCBiDoSoZ+YAZhR0Bs2s4QP4H9YudLvXDL/8P4PAdjMEmYU9A4rB5FIor1fMsOPeAxHFEiEfZMZ/NhR4uCglMDMKTZ0Hz8QUndlI7dSdwu6jx8Ic4otYhm+O3EA1y6YiKq64wDQ5X23ra9X1R3HtQsmYl91ZUxlIKKOROineM+wP8WG6QW9MRTAFvivfAK6/g976+t9f3j/EADTC3pjfwTXB5EI4r0bRMrAYziiQCLsm8zgx44SQ8i375G+zCk2JE0aBPeeerjKa+GrCRyRNaXaYc/uAeuQ5IiMGp9pX3UlRj1zEwovGo1p+VOQ2394wHt2HK7A0pKVKP5qoyajxiJkIKKOROineM9QNDQZEmQs3nwMO7wyigC8BGB7J+/Ngf8ZUuPgv0JqakFvFA0N//J3IhHFezeIlIHHcESBRNg3mcGPHRV9HJQyAMligi0rBbasFHirm2FpAKbnTcKS7avgSUJY3zygVLPbhVVb12PV1vXI7puF4RlD8Wj+g3iu5GV8XfUtyg/viosMRNSRCP0U7xnWDj0H29IdWLT5KO4+6sRkCdgpA7sB1MN/q14mgBGS/6Hmn2Y4MPMaXiFFsS/eu0GkDDyGIwokwr7JDH7sqOji7XsGY05LgCOzBwoLC+HI7KHLTnqm8sO78M72TaipqcE72zdFZScVIQMRdSRCP8Vrhv0pNtxUOAD5EwbitREpMKfaUWiSMA1AoUmCOdWO10akIH/CQPz81gEckKK4E6/dIGIGHsMRBRJh32QGP3aU/nilFBERUYwoS0tAWdpPAACJVgfem/Rn3LzqATS5nVFORkREREQUiFdKERERxSoT/zNPREREROLi0SoREREREREREelOkmVZ1mNBXq8XpaWlyL86H02yuifWS5KE1MQeqGmqhZrYcpMHkAFIgJSo7s5FZmAGZoh8hkTJjpKPS5Cbmwuz2awqQ7jC7ahw1wEQ/rZgBmZgBm0yRLuj2E/MwAzM0BWj9xMQG8eyzMAMzBBIaT/p/0wpGZBPe9ROihONJ5iBGZgh1jJ0s6ufNtJUroeIbQdmYAZmEC+DKB0V79uBGZiBGQIZvJ9+mNT4x7LMwAzMEEhhP+k/KCUBUrf4HS1kBmZghs5moGqx2lDZUbHyG1dmYAZm6Gwm6iaLOPYTMzADMwTMRN1kEcdzPGZgBmYImIGyt+k+KCU5zEieMFjVtIlWB96bsgw3r5yq6puE6lfshXzaAynRguS7mYEZmEGUDN41VaqWqwW1HRXuOgDC3xbMwAzMoE0GUTqK/cQMzMAMZzJ6PwGxcSzLDMzADIGU9hMfdE5ERERERERERLrjoBQREREREcUfny/aCYiI4p7+z5QiIiIiIiLSWU51MybvqsPlVU5k1rbA9uIoHDBJ2N3Dhi0ZDryRlYKytIRoxyQiiisclDKY7L5ZGJGRidTUVIzNuwE7q3aj/PCuuMvgrW6Gs96J4uJiOCtOwpsswcyDCKKoEqEbRMjAfiISjwjdIEKGeO2n8+pasGjzUVx51Am3BFhzcoHrhwFJSbA1NODCigoMKyvFtB11+Ky3AzMKemN/ii3asSmOsB/EySACET4PeuKglAEkWO0YN3IMpuVPQU6/C9peX3LXfABA2aFvsLRkJYq2bUCz2xWzGWSPD+499XCV18JX41/GvA/mtf3clGqHPbsHrEOSIVl4ZyqRHkToBhEysJ+IxCNCN4iQId77afy3p7B48zGYbXbg7rthnTULyMsLeJ91+3bgpZdw6eq38Plb+zG9oDeKhiZHITHFC/aDOBlEIMLnIVo4KCW489MHYt1Dy9GvZwZ8cuf3vY/ok4lFk5/FI6MfwthF92FfdWXMZfDWteD0uwchN3i6fI+vxgXn5mNo/rIG3W7pDzN/w0WkKRG6QYQM7Cci8YjQDSJkiPd+Gv/tKSz96CgwZAhMmzYBAwZ0/Ryp7Gzg1VdheeIJmK6/Hss+2gsJMtYOPUff0BQX2A/iZBCBCJ+HaAp5qLGlpQVPPfUULrnkElxxxRX44x//CFmWtcgW985PH4i/zX4LGSm9IEkSzCZzp+8zm8yQJAkZKb3w94dXY1DagJjK4K1rQePaA5Abuy6r9uRGDxrXHoC3riViGcgY2E/6EaEbRMjAfiKl2E/6EaEbRMgQ7/00qK4Fizcf8w9Iff450KcPIEmAufNtAbPZ//M+fWDauhUYPBiLNx/DeTGyPs6G/aQv9oM4GUQgwuch2kIelHrmmWfwz3/+E6+88gr+8Ic/YM2aNVi9erUW2eJagtWOdQ8tR5K9GyxmZRe0WcwWJNm7Yf2MV5BgtcdEBtnjw+l3DwItPkDpfxtlAC3+6WQPv1UlnrCf9CFCN4iQgf1EoWA/6UOEbhAhA/sJWLj5KEw2u/8KqaQkwGpVNqHVCiQlwfTRRzDb7Fi0+ai2QQXAftIP+0GcDCIQ4fMggpAGperq6lBUVISnn34a2dnZuPzyy3HvvfeirKxMq3xxa9zIMejXM0Pxh7OVxWxB/3P7oPCi0TGRwb2n3n85Z6i/rJEBucED9576sDOQMbCf9CNCN4iQgf1ESrGf9CNCN4iQId77KedEM6486oR14u3+W/aUDki1slqBgQNhmTARVx51Iqe6WZugAmA/6Yv9IE4GEYjweRBBSINS27ZtQ/fu3TFq1Ki216ZNm4b58+dHPFi8m5Y/pcv7SYPx+ryYlj8lJjK4ymujOj0ZB/tJPyJ0gwgZ2E+kFPtJPyJ0gwgZ4r2fJlfUwS0BmDWr62dIBeP1AjNnwi0Bk3fVRTKeUNhP+mI/iJNBBCJ8HkQQ0qDUoUOH0KdPH6xfvx433ngjrr32WixevBg+tWVPncrum4Wcfhd0eT9pMGaTGbn9hyO7b5ahM3irm9u+gUEtX40L3hj+7Rb9iP2kDxG6QYQM7CcKBftJHyJ0gwgZ2E/A5VVOWHNy/d+y19UzpIIxm4GRI2HNycVlR50RzScS9pN+2A/iZBCBCJ8HUYR0nVhTUxMqKyvx1ltvYf78+aiursbcuXPhcDhw7733KpqHJElItDpUhXVYEzr8HaoGSYJsgAwjMjJVzftMwzOGYu/xA4bN4KyPzAGApQFwZAQuwyifh3jI0ChJqqZrLxL9BKhfD+GuAyD8baFHBq27wSgZtO4nJRmCiZfPpB4Zwu0o9hP7Sc8M7Ccgs7YFuH6Y6nl3nFkmhpWXdfrvFGE9GL2fgNg4luX5lbEyBBMvn4dg9DrHk+QQvlph6dKl+MMf/oDNmzejT58+AIAVK1bgzTffxIcffnjWab1eL0pLSzFu3DgUFRUpXWREjRkzBidOnEB6ejo2bNggbIbU1FQMGBD+0/QrKytRU1Nj2AzFxcWYN29e2BnmzJmDwsJCVRm0xgx+rb2Qm5sLs8rfaIbTTwA7SmkGrbvBKBm07iclGfTADH7hdhT7SZ8MInSDCBnivp98PowcNQqYOhVYujT8BU2bBixbhm1ffAGYOt5kIsJ6YD+JsR14fmWsDFozyudBa0r7KaQrpdLS0mC329sKCwDOO+88HD2q/FspTjrrcPPKqaEsto3DmoA1ExdiwuqZcLpDv1yvpqm27W+RM4zNuwFL7gr/Pu7nSl7GO9s3GTaDs+Jk2MsHgCXbV+G1po2qMgQTL59JrTM0OutULbe9SPQToL6jwl0HQPjbQo8MWneDUTJo3U9KMgQTL59JPTKE21HsJ/aTnhnYT8ABkwRbQ4Oq+Qaor0eLScLNqx4IKYMS7Ce/WDiW5fmVsTIEEy+fh2D0OscLaVAqJycHLpcL+/fvx3nnnQcA2LdvX4cSC0aWZTS5w7tkz+luVjWP1ovCRM+ws2p3WNna5nNkd6fLMEoGb3L4t3QBgCcJqjMoFeufSb0yhCMS/dSaJZz1oHYdtC5b9Axad4NRMmjdT0oyKBXrn0k9M6jFftIngwjdIEIG9hOwu4cNF1ZUqM7VQUUFKnraND2WZD/5xcKxLM+vjJFBqVj/PCil9TleSA86HzRoEK6++mo89thjqKiowCeffIKlS5fijjvuCDkgda388C6UHfoGXp9X1fRenxelB7/GjiPq/2MsQgZzWgJMqXbV0wOAKdUOc5r6+/TJONhP+hChG0TIwH6iULCf9CFCN4iQgf0EbMlwwF1WCmzf7v8WPTW8XmDbNrjLy/B5b3XPYzEC9pN+2A/iZBCBCJ8HUYQ0KAUAL7zwAvr374877rgDjzzyCCZPnow777xTi2xxbWnJSpikkDcPAP+T+JeWrIyJDPbsHlGdnoyF/aQPEbpBhAzsJwoF+0kfInSDCBnivZ/eyEqBVQbw0ksBz4FSzGwGFi6EVfbPL5axn/TDfhAngwhE+DyIIOQ1kJSUhOeffx7bt2/HP//5T8yYMQNSBL45izoq2rYBh05WweP1hDSdx+vBwe+PoPirzp8BYLQM1iHJkJIsQKgfMQmQkiywDkkOOwMZB/tJHyJ0gwgZ2E8UCvaTPkToBhEyxHs/laUl4LPeDnhWvwVUVgJud2gzcLuBAwfgWbMan/V2oMzgV2QEw37SD/tBnAwiEOHzIAKVvzogrTW7Xbh18f1ocJ1W/CH1eD1ocJ3G2EX3odntiokMksWEbrf0B2wm5aUlAbD5p5Ms/IgTRZoI3SBCBvYTkXhE6AYRMrCfgBkFveFtccH3s58BDQ3KB6bcbqChAb7rr4e3xYUZBb21DUpxhf0gTgYRiPB5EEFsbM0Y9d2JA7h2wURU1R0HgC7vN219varuOK5dMBH7qitjKoM5xYbu4wdC6q7sufxSdwu6jx8Ic4otYhmIqCMRukGEDOwnIvGI0A0iZIj3ftqfYsP0gt7Anj3wXXopcOSI/wddPWOq9fUjR/zv37sX0wt6Y3+MrA8SB/tBnAwiEOHzEG0hffse6W9fdSVGPXMTCi8ajWn5U5Dbf3jAe3YcrsDSkpUo/mqjJqOlImQwp9iQNGkQ3Hvq4Sqvha8mcBmmVDvs2T38l4PGyOg5kchE6AYRMrCfiMQjQjeIkCHe+6loaDIkyFi8+TuYL8iCZcJEYOZMYOTIwDeXlgILF8KzZjW8LS5Mvz4DRUNj4xYhEg/7QZwMIhDh8xBNHJQygGa3C6u2rseqreuR3TcLwzOG4tH8B/Fcycv4uupblB/eFRcZJIsJtqwU2LJS4K1uhqUBmJ43CUu2r4InCYb/BgYiIxKhG0TIwH4iEo8I3SBChnjvp7VDz8G2dAcWbT6KK19/He6/vA5rTi6QmQkkJwP19cDu3XCXlcIqA59nODDzmvN4hRRpjv0gTgYRiPB5iBYOShlM+eFd2Hv8AO4ffhve2b4JTW5nXGYwpyXAkeFAYWEhXmvaGJUMRNSRCN0gQgb2E5F4ROgGETLEaz/tT7HhpsIByKluxuRddbjs8C4MKy+DzSejxSShoqcNn49IwRtZKTH/UHMSE/tBnAwiEOHzoCcOShERERERUcwrS0tAWdpPAACJVgfem/Rn3LzqgZg/4SMiElls3pRJRERERER0NiaeChERRRubmIiIiIiIiIiIdCfJsizrsSCv14vS0lLkX52PJlnd0+IlSUJqYg/UNNVCTWy5yQPIACRASlR35yIzMAMzRD5DomRHycclyM3NhdlsVpUhXOF2VLjrAAh/WzADMzCDNhmi3VHsJ2ZgBmboitH7CYiNY1lmYAZmCKS0n/R/ppQMyKc9aifFicYTzMAMzBBrGbrZ1U8baSrXQ8S2AzMwAzOIl0GUjor37cAMzMAMgQzeTz9MavxjWWZgBmYIpLCf9B+UkgCpW/yOFjIDMzBDZzNQtVhtqOyoWPmNKzMwAzN0NhN1k0Uc+4kZmIEZAmaibrKI4zkeMzADMwTMQNnbdB+UkhxmJE8YrGraRKsD701ZhptXTlX1LRn1K/ZCPu2BlGhB8t3MwAzMIEoG75oqVcvVgtqOCncdAOFvC2ZgBmbQJoMoHcV+YgZmYIYzGb2fgNg4lmUGZmCGQEr7iQ86JyIiIiIiIiIi3XFQyqh8vmgnICIiIiIiIiJSTf9nSpEqOdXNmLyrDpdXOZFZ2wLbi6NwwCRhdw8btmQ48EZWCsrSEqIdk4iIiIiIiIhIEQ5KhSC7bxZGZGQiNTUVY/NuwM6q3Sg/vEvTZZ5X14JFm4/iyqNOuCXAmpMLXD8MSEqCraEBF1ZUYFhZKabtqMNnvR2YUdAb+1NsmmYSgbe6Gc56J4qLi+GsOAlvsgQzB+UojkWjn0TMIAL2E1FHInSDCBlEwH4iCiRCP3Df9ON6iE8clAoiwWrHuJFjMC1/CnL6XdD2+pK75gMAyg59g6UlK1G0bQOa3a6ILnv8t6ewePMxmG124O67YZ01C8jLC3ifdft24KWXcOnqt/D5W/sxvaA3ioYmRzSLCGSPD+499XCV18JX41/X8z6Y1/ZzU6od9uwesA5JhmThnakU+6LZTyJlEAH7iagjEbpBhAwiYD8RBRKhH7hv+nE9EAelzuL89IFY99By9OuZAZ/c+TOcRvTJxKLJz+KR0Q9h7KL7sK+6MiLLHv/tKSz96CgwZAhMmzYBAwZ0/Ryp7Gzg1VdheeIJmK6/Hss+2gsJMtYOPSciWUTgrWvB6XcPQm7wdPkeX40Lzs3H0PxlDbrd0h/mOLhijOJXNPtJpAwiYD8RdSRCN4iQQQTsJ6JAIvQD900/rgcCQnzQeXFxMTIzMwP+DBs2TKt8UXN++kD8bfZbyEjpBUmSYDaZO32f2WSGJEnISOmFvz+8GoPSBoS97EF1LVi8+Zh/QOrzz4E+fQBJAsydZ4DZ7P95nz4wbd0KDB6MxZuP4by6lrCziMBb14LGtQcgN3ZdVu3JjR40rj0Ab4z8+0kZ9lMgLfpJpAwiYD+REuynQOwn7bGfSCl2VCAt+4H7ph/XA7UKaVBqzJgx+PTTT9v+fPzxxxgwYADuuusurfJFRYLVjnUPLUeSvRssZmUXk1nMFiTZu2H9jFeQYLWHtfyFm4/CZLP7r5BKSgKsVmUTWq1AUhJMH30Es82ORZuPhpVDBLLHh9PvHgRafICsdCIALf7pZA+/pTBesJ+6Fsl+EiWDCNhPpBT7qWvsJ22wnygU7KiuRbofuG/6cT1QeyENSiUkJCAtLa3tz7vvvgtZljF79myt8kXFuJFj0K9nhuKyamUxW9D/3D4ovGi06mXnnGjGlUedsE683X/LntIBqVZWKzBwICwTJuLKo07kVDerziIC9556/+WcSsuqlQzIDR6499RrkovEw346u0j0k0gZRMB+IqXYT2fHfoo89hOFgh11dpHsB+6bflwP1J7qJ4XV1dVh2bJl+M1vfgObLbbu65yWP6XL+4uD8fq8mJY/RfWyJ1fUwS0BmDWr62dIBQ3hBWbOhFsCJu+qU51FBK7y2qhOT8bEfupcuP0kUgYRsJ9IDfZT59hPkcV+IrXYUZ2LVD9w3/TjeqD2VA9Kvfnmm0hPT8eNN94YyTxRl903Czn9Lujy/uJgzCYzcvsPR3bfLFXTX17lhDUn1/8te109QypoCDMwciSsObm47KhT3TwE4K1ubvsGBrV8NS54DX61GIWO/dS5cPtJlAwiYD+RWuynzrGfIof9ROFgR3UuEv3AfdOP64HOpOrb92RZxttvv437778/5GklSUKi1aFmsXBYEzr8HaoGSYIcJMOIjExV8z7T8Iyh2Hv8QMgZMmtbgOsj9FDBzEwMKy8LWI6S9RCMHtvCWR+ZATVLA+DICFyGUdZDPGRolCRV03UmnH4C1K+HcNcBEHxbaN1PRskQjB7bQut+UpIhGD3WQ7xkiFRHsZ+CYz8Fx35ihvZEOYYS/Vg22ud4AM9tWnE9xE8Gpf0kybIc6p2cKC8vxx133IF//vOfOOeccxRN4/V6UVpainHjxqGoqCjURUbEmDFjcOLECaSnp2PDhg2dvic1NRUDBoT/7QqVlZWoqakJLYPPh5GjRgFTpwJLl4adAdOmAcuWYdsXXwCmHy+KU7IetKYkQ3FxMebNmxf2subMmYPCwkJVGbTGDH6tvZCbmwuz2isEf6CmnwBjdJTW/WSUDHoIlkHrflKSQQ/M4BepjmI/Bcd+Co79xAztRfsYygj9BET5HO8HPLfx43qInwxK+0nVlVKffPIJLr744pAOqFqddNbh5pVT1SwWDmsC1kxciAmrZ8LpDv1yvZqm2ra/u8owNu8GLLlrvqp87T1X8jLe2b4p5AwHTBJsDQ1hLx8AUF+PFpOEm1c9EFIGJfTYFs6Kk6qynWnJ9lV4rWmjqgzB6LEe4iFDo7NO1XI7E04/Aeo7Ktx1AATfFlr3k1EyBKPHttC6n5RkCEaP9RAvGSLVUeyn4NhPwbGfmKE9UY6heI7HcxulGbge4ieD0n5SNShVXl6Oiy66SM2kkGUZTe7wLtlzuptVzaP1orCzZdhZtTusbG3zObK702UEy7C7hw0XVlREJAMqKlDR0xawHCXrQSktt4U3OTKXI3uSoGpbhELL9RBPGSIhnH5qzRLOelC7DlqXfbYMWveTUTIopeW20LqflGRQSsv1EG8ZwsV+Co79FBz7iRk6yxAJPMcLTu05HsBzm1ZcD/GXIRhVDzrfs2cPBg8erGZS4ZUf3oWyQ9/A6/Oqmt7r86L04NfYcUTdwNKWDAfcZaXA9u3+b9FTFcILbNsGd3kZPu+t7v5REZjTEmBKtYc1D1OqHeY09ffpk/Gwn7oWbj+JkkEE7CdSg/3UNfZT5LCfSC12VNci0Q/cN/24HuhMqgalampqkJycHOkswlhashImSd0XE5pNZiwtWal62W9kpcAqA3jppQ7PgQothBlYuBBW2T8/I7Nn94jq9GQ87KeuhdtPImUQAfuJQsV+6hr7KbLYT6QGO6prkeoH7pt+XA/Unqq9sry8HFdddVWkswijaNsGHDpZBY/XE9J0Hq8HB78/guKvOr//XomytAR81tsBz+q3gMpKwO0ObQZuN3DgADxrVuOz3g6UGXwE2TokGVKSBQj1Kk8JkJIssA6J3f+wUufYT52LRD+JlEEE7CcKFfupc+ynyGM/kRrsqM5Fsh+4b/pxPVB7Ki/FiW3NbhduXXw/GlynFZeWx+tBg+s0xi66D81uV1jLn1HQG94WF3w/+xnQ0KB8YMrtBhoa4Lv+enhbXJhR0DusHCKQLCZ0u6U/YDMpLy0JgM0/nWThR5xiS7T7SZQMImA/EXUkQjeIkEEE7CeiQCL0A/dNP64Hao9bswvfnTiAaxdMRFXdcQDo8v7j1ter6o7j2gUTsa+6Muxl70+xYXpBb2DPHvguvRQ4cuSHhXVxD3Tr60eO+N+/dy+mF/TG/hRb2FlEYE6xofv4gZC6K3suv9Tdgu7jB8IcI/9+ojNFs59EyiAC9hNRRyJ0gwgZRMB+IgokQj9w3/TjeqBWqr59L17sq67EqGduQuFFozEtfwpy+w8PeM+OwxVYWrISxV9tjOhv14qGJkOCjMWbv4P5gixYJkwEZs4ERo4MfHNpKbBwITxrVsPb4sL06zNQNDS2Lmk0p9iQNGkQ3Hvq4Sqvha8mcF2bUu2wZ/fwXw7K0XOKcdHsJ5EyiID9RNSRCN0gQgYRsJ+IAonQD9w3/bgeCOCgVFDNbhdWbV2PVVvXI7tvFoZnDMWj+Q/iuZKX8XXVtyg/vEuzZa8deg62pTuwaPNRXPn663D/5XVYc3KBzEwgORmorwd274a7rBRWGfg8w4GZ15wXM1dInUmymGDLSoEtKwXe6mZYGoDpeZOwZPsqeJLAb2CguBPNfhIpgwjYT0QdidANImQQAfuJKJAI/cB904/rgTgoFYLyw7uw9/gB3D/8NryzfROa3E7Nl7k/xYabCgcgp7oZk3fV4bLDuzCsvAw2n4wWk4SKnjZ8PiIFb2SlGP6h5qEwpyXAkeFAYWEhXmvaqMu2IBJZNPpJxAwiYD8RdSRCN4iQQQTsJ6JAIvQD900/rof4xEEpgyhLS0BZ2k8AAIlWB96b9GfcvOoB7qhEREREREREZEi8KdOoTNx0RERERERERGRcHNkgIiIiIiIiIiLdSbIsy3osyOv1orS0FPlX56NJVvcNBpIkITWxB2qaaqEmttzkAWQAEiAlqrtzkRmYgRkinyFRsqPk4xLk5ubCbDaryhCucDsq3HUAhL8tmIEZmEGbDNHuKPYTMzADM3TF6P0ExMaxLDMwAzMEUtpP+j9TSgbk0x61k+JE4wlmYAZmiLUM3ezqp400leshYtuBGZiBGcTLIEpHxft2YAZmYIZABu+nHyY1/rEsMzADMwRS2E/6D0pJgNQtfkcLmYEZmKGzGaharDZUdlSs/MaVGZiBGTqbibrJIo79xAzMwAwBM1E3WcTxHI8ZmIEZAmag7G26D0pJDjOSJwxWNW2i1YH3pizDzSunqvrWufoVeyGf9kBKtCD5bmZgBmYQJYN3TZWq5WpBbUeFuw6A8LcFMzADM2iTQZSOYj8xAzMww5mM3k9AbBzLMgMzMEMgpf3EB50TEREREREREZHuOChFRERERERE8c3ni3YCorik/zOliIiIiIiIiKIop7oZk3fV4fIqJzJrW2B7cRQOmCTs7mHDlgwH3shKQVlaQrRjEsU8DkqRIXmrm+Gsd6K4uBjOipPwJksw8z8aRCQA9hMRiYr9RAScV9eCRZuP4sqjTrglYKcMFAFoAJDkkzHsexfuOenCtB11+Ky3AzMKemN/ii3aseMCOyo+cVCKDEP2+ODeUw9XeS18NS4AwLwP5rX93JRqhz27B6xDkiFZeGcqEemH/UREomI/Ef1o/LensHjzMbR4ZbwG4CUZKO3kfbkyMAvA+KNOfP7Wfkwv6I2iocn6ho0T7CjioBQZgreuBaffPQi5wdPle3w1Ljg3H0PzlzXodkt/mPkbDSLSAfuJiETFfiL60fhvT2HpR0fxLYAbAVSi6wcslwO4F8BTAD70ylj2URUkyFg79Byd0sYHdhQBfNA5GYC3rgWNaw9Abuy6rNqTGz1oXHsA3roWjZMRUbxjPxGRqNhPRD8aVNeCxZuP4VsAVwA4/MPrXT3avPX1wwAuB7AHwOLNx3Ae94+IYUdRq5AHpY4ePYoHHngAF110EQoKCrBixQoNYhH5yR4fTr97EGjxAbLSiQC0+KeTPfwWjXjCfiI9sZ8oFOwn0hP7iUIRD/20cPNRuLwybgRQD8CrcDrvD++/AUCLV8aizUe1ihhX2FHUXsi37/3qV79CRkYGiouLsXfvXsyePRt9+vTB9ddfr0U+inPuPfVnvZyzSzIgN3jg3lMPW1ZKxHORmNhPpCf2E4WC/UR6Yj9RKGK9n3JONOPKo068Bv8te6Hy/jBdEYC7jzqRU93Mb+ULEzuK2gvpSqlTp06htLQUDz74IAYOHIjrrrsOV111FbZs2aJVPopzrvLaqE5PxsF+Ir2xn0gp9hPpjf1ESsVDP02uqINbAl6C+mfXmOCf3i0Bk3fVRSxbvGJHUXsh7ZcJCQlwOBwoLi6G2+3Gvn378NVXXyErK0urfBTHvNXNbd/AoJavxgVvdXOEEpHI2E+kJ/YThYL9RHpiP1Eo4qGfLq9yYucP37Kn9qYvH4DtAHbKwGVHnRHLFo/YUXSmkG7fs9vtmDt3Lp5++mn85S9/gdfrRWFhIW677TbF85AkCYlWR8hBAcBhTejwd6gaJAkyMxgmg7M+MoVvaQAcGYHLMMp6iIcMjZKkarr2ItFPgPr1EO46AMLfFsygXwat+0lJhmDiZVvokSHcjmI/MYOeGdhP8ZXB6P0EaH8sm1nbgiJVcw60G0DhyZaA5YhwPG2UDDzHi58MSvtJkmVZ6aPFAAALFizA0aNHcc8992DPnj14+umn8dRTT+GWW24563RerxelpaUYN24ciooiVQuhGTNmDE6cOIH09HRs2LCBGQTPUFxcjHnz5oW9rDlz5qCwsFBVBq0xg19rL+Tm5sJsNquej9p+AthRzBBaBq37SUkGPTCDXyQ6iv3EDHplYD/FVwb2U5Dt4PNh5KhRWArggQgs688ApgHY9sUXgOnHm45E+CwYJQPP8eIng9J+CulKqS1btmDt2rX4/+zdeXwTZeI/8M8k6QktBdoi5SjKUcrRQy6vXbR4geJiQW5dVwQVgVUXFRFBFgUXvL5yqFyiiyBISxEBT9b+RAEVKYcCgkABW6CVFlqaHknm90dMbElLJpNk8iT5vF8vX+6mmcyHZ/p8nDxMJrm5uQgPD0f37t1x5swZvPnmm4pKCwDOGUsxcOVYV3ZrFxESjrXD5mPomokw1rh+uV5xRYn938wgfgbjwXOqsl1q0e5VeKdii6oMzgTLsfB2hnJjqar91uaJfgLUd5S7YwC4fyyYQbsM3u4nJRmcCZZjoUUGdzuK/cQMWmZgPwVXBn/vJ8D757LHdRKiLC5dh9GgaADVOgkDV9Vd4hLhfNpfMvA9XvBkUNpPLi1K7d+/H4mJiQgP//PyrS5duuCtt95S/BqyLKOixr1L9ow1lapew3ZRGDP4RwZztPsf6QIAUxTq3Ye/jEMwZXCHJ/rJlsWdcVA7BrZ9M4N/ZPB2PynJoFSgHwstM6jFfmIGLTOwn4Izg1qi9BPgvXPZQ01D0fl39+5hZNMZwMFmoQ77Eel8WvQMfI8XfBmccelG5/Hx8cjPz0d1dbX9saNHj6J169aupSNSQB8XDl1smFuvoYsNg55f2RoU2E+kJfYTuYL9RFpiP5ErgqGftidEoJsEpMG9b99LB9BVAna0VHd/HrJiR9GlXJqXGRkZCAkJwbRp03Ds2DFs3boVb731Fu69915v5aMgF5bS1Kfbk/9gP5HW2E+kFPuJtMZ+IqWCoZ/eT45BiAxMgnvfvjcJQIhsfT1yDzuKanNpUSoqKgorVqxAUVERhgwZgjlz5uCRRx7BsGHDvJWPglxIx2hIUQbA1as8JUCKMiCkY7RXcpF42E+kNfYTKcV+Iq2xn0ipYOinPXHh+KZlBIYASATg6u3g9X9sNxjANy0jsIdX6LiNHUW1uXRPKQDo0KED3nnnHW9kIXIgGXRodFdblK87DlRbACUfS5UAhFq3kwxqL9Ilf8R+Ii2xn8gV7CfSEvuJXBEM/TQhoyV2fHAMn5hlXAfgAgCzgu30sN7c/FMAoXoJEzJaejNm0GBHUW08miQ8fUwoGg9pB6mxsjVUqbEBjYe0gz4m1MvJiCjYsZ+ISFTsJ6I/HYsJxfiMlugEYDsA2x2zGnozbHu89R/P7whgfEZLHOP88Bh2FNm4fKUUkS/oY0IRNfIq1By+gKq9JbAUO36Dhi42DGEpTa2Xg3L1nIg0wn4iIlGxn4j+lNUpGhJkLNx6GvvMMrIAvAFgdz3PTYX1HlKDYb1CamxGS2R14kfGPI0dRQAXpciPSAYdQpNjEJocA3NRJQxlwPj0kVi0exVMUeA3MBCRz7CfiEhU7CeiP63r1AS74iOwYGsh7i80YpQE7JeBQ7B+pC8aQBKAbpL1pubbEiIw8SZeIeVN7CjiohT5JX1cOCISIpCZmYl3Kragosbo60hERADYT0QkLvYTkfWjfHdkJiK1qBKjDpTimkIjMs9VI9Qio1on4WCzULzTMgLvJ8fwpuYaY0cFJy5KERERERERUVDZExeOPXFXAAAiQyKwceTbGLjqIS6EEGmMH8okIiIiIiKi4KbjW2MiX+DMIyIiIiIiIiIizUmyLMta7MhkMmHPnj3oP6A/jLLjXfWVkCQJzSJicM5YCjWxZaMZkAFIgBShZwZmYAZBMkRIYdiyeQtSU1NhMPjmU8XudpS7YwC4fyyYgRmYwTsZfN1R7CdmYAZmaIi/9xMQGOeyzMAMzOBIaT9p1lwWiwUAsGXzFq12SUR+xtYTvtw3O4qIGuKrjmI/EZEz7CciEpWzftLsSimLxQKTyQSdTgdJkrTYJRH5CVmWYbFYYDAYoPPR5/nZUUTUEF93FPuJiBrCfiIiUSntJ80WpYiIiIiIiIiIiGx4o3MiIiIiIiIiItIcF6WIiIiIiIiIiEhzXJQiIiIiIiIiIiLNcVGKiIiIiIiIiIg0x0UpIiIiIiIiIiLSHBeliIiIiIiIiIhIc1yUIiIiIiIiIiIizfnVolR2djaSkpLw4YcfarrfpKSkOv9cc801mDZtGi5evKhpDgA4f/48XnrpJWRkZCA1NRX9+/fHihUrYLFYvL7vjIwM+xh07twZ6enpGD58OL7++muv77u+DJf+s3PnTp/nGDFihGYZKioq8Prrr+P2229HSkoK+vTpg0mTJuHw4cOa7D8jIwPZ2dkOj2dnZyMjI0OTDKIJ9o4K9n66NIevOor9xH6qD/uJ/cR++pMvO4r95Ij95Lt+AsToKBH66XI5eA7l3Y4yeOVVvWTTpk1o27YtNmzYgHvuuUfTfc+fPx/p6emwWCwoLCzE9OnTMXfuXMycOVOzDCUlJRg2bBji4+Px4osvonXr1ti3bx9mzZqFkydP4rnnnvN6hqlTp2LAgAGwWCw4f/48cnJy8NBDD2Hp0qW47rrrvL7/2hku1aRJE032f7kcISEhmuz74sWLGDlyJCoqKjBlyhR07twZJSUleP/99zF8+HDk5OSgTZs2mmShPwVzR7GfHHNcSsuOYj/RpdhP7KfaOS4VLP0EsKNExH7ybT8BYnSUCP3UUA6eQ3mX3yxK/f7779i+fTtmz56NKVOm4OTJk5oekCZNmiAuLg4A0KJFCzz00EOYOXOmpotSr7zyCkJDQ7Fs2TKEhYUBANq0aYPw8HCMHz8eo0ePxpVXXunVDFFRUXXG4amnnkJRURHmzJmDjRs3enXf9WXwJV/mWLhwIX7//Xds3rwZ0dHRAIBWrVphzpw5KCwsxIoVKzT7jxhZBXtHsZ/qz+Er7Ceqjf3Efqovh6/4OgM7SizsJ9/3EyBGR/m6G0TIEaz95Dcf3/vkk08QFRWFu+66C/Hx8diwYYNP80RERGi6v+rqamzatAmjRo2yF5bNTTfdhBUrVqBVq1aaZrIZNmwYfvnlF+Tn5/tk/8HGYrFg/fr1+Mc//mEvq9rmzp2LJ5980gfJglswdxT7iWzYT2JiP7GfyIodJR72k5j9BLCjtBbM/eQ3i1KbNm3CjTfeCJ1Oh4yMDOTk5ECWZZ9kOXfuHP773//irrvu0myfJ06cQEVFBbp37+7wM0mScM011yA0NFSzPLW1b98eAHDkyBGf7D/YnDhxAufOnUPPnj3r/Xl8fDzCw8M1TkXB3FHsJ7JhP4mJ/cR+Iit2lHjYT2L2E8CO0low95NffHyvsLAQP/74I/7xj38AAG699VasXr0au3btavCgedrYsWOh1+shyzKMRiNiYmLw/PPPa7JvALhw4QIA6+WEorFl0uqmgDNmzMCsWbPqPJaQkIBNmzZpsv/L5fjmm28QGRnp1f2WlJQAqPv56m+//RaPPvqo/f9rNR71jYHJZBLi0lstBXtHsZ/qEqGj2E/sJxv2E/uptmDuJ0CcjmI/WbGfxO0ngO/xauM5lHc7yi8WpTZt2oSwsDDccMMNAIDevXujSZMmWL9+vWaF9cILLyA1NRWyLKOkpAQrV67EiBEjsHHjRjRv3tzr+4+JiQFg/XYG0ZSXlwMAGjdurMn+Jk2ahFtvvbXOYwaD9r/K9eXQ4pJf2+Wctv+QAUB6ejpycnIAAJ999hlWr17t9RxA/WOg5f5FEewdxX6qS4SOYj+xn2zYTzEA2E82wdxPgDgdxX6yYj/FABCznwC+x6uN51De3b/fLEpVVlaiR48e9sfMZjM++eQTPPfcc5pcxtaiRQskJiYCANq1a4euXbuiT58+2LJlC0aPHu31/bdt2xZRUVH46aefkJKS4vDzRx55BPfee6+m3+Bic+jQIQBAx44dNdlf8+bN7cfCl3yVIzExETExMdi9e7f9dyEiIsKeRYtFUpv6xkDL/Ysi2DuK/VSXCB3FfmI/2bCf2E+1BXM/AeJ0FPvJiv0kbj8BfI+nNVH6ybYvLTtK+HtKHTt2DD///DOmTZuGnJwc+z+vvfYaysvL8fnnn/skl06ngyzLMJvNmuzPYDBgwIABeP/991FdXV3nZ1u3bsXWrVsRHx+vSZZLZWVloWvXrgH59ZQiMhgMGDx4MN59913732DUdubMGR+kCl7sKPYT/Yn9JBb2E/uJ6mJHiYP9JHY/AeworQVzPwl/pdSmTZsQExODYcOG1bnRW6dOnbBw4ULk5ORg4MCBXs9x/vx5FBUVAbB+rnb58uUwm83IyMjw+r5tJk6ciHvuuQdjxozBxIkTccUVV2Dnzp2YN28e7rvvPnTo0MHrGcrKylBUVGS/xHXdunXYvHkzli9f7vV9X5rhUo0aNdLkfgQimDhxInbt2oXhw4djwoQJ6Nq1K0pKSvDhhx9i3bp1uPPOO30dMWiwo6zYT445LhUsHcV+Egf7yYr95JjjUsHSTwA7ShTsJysR+gkQo6PYT8HbT36xKDVw4MB6v3lgxIgRePHFF3HmzBm0aNHCqzkmTpxo/98RERHo1q0blixZounKcVxcHFavXo358+dj8uTJKC0tRdu2bTFp0iSMGDFCkwyzZ8/G7NmzIUkSmjVrhi5dumDFihWafe67doZL/fOf/8T48eM1y+FLERER+O9//4t3330XixYtQn5+PkJDQ5GSkoL58+fj5ptv9nXEoMGOsmI/Oea4VLB0FPtJHOwnK/aTY45LBUs/AewoUbCfrEToJ0CMjmI/BW8/SbKvvnOTiIiIiIiIiIiClvD3lCIiIiIiIiIiosDDRSkiIiIiIiIiItIcF6WIiIiIiIiIiEhzXJQiIiIiIiIiIiLNcVGKiIiIiIiIiIg0x0UpIiIiIiIiIiLSHBeliIiIiIiIiIhIc1yUCgDjxo3DM888U+exjz/+GElJSZg/f36dxxctWoS//e1vdR6TZRkPPPAAsrOz6zz+66+/4oEHHsDVV1+NjIwMvPXWW7BYLJfNMnr0aPz444+Xfc7SpUuRkZFR57GSkhJMnDgR6enpyMjIwIYNGy77Gpfb17333oukpCT7P+np6RgzZgzy8/PrfZ2PPvoI9957b53Hqqur8Z///Ad//etf0atXLzz66KM4ffq000xEdHlq++rixYuYNm0arrnmGvz1r3/F4sWLne7rjTfewFtvvVXvz9555x3ceOONSE1NxZgxY3D8+HH7z2pqajBv3jzccMMNuOaaa/Cf//wHJpPpsvvKysrCc8895/B4dnZ2nT7q2rUrbr/9duTk5NT7OqWlpbjuuutw6tSpOo8fOnQII0aMQEpKCgYOHIgdO3Zc/g9PRIr4wzlURUUFpk2bhj59+qBXr1547rnncPHiRfvPCwsL8dBDD9n3tWLFCqd/bm+eQ9VW3zkfESnjrX7y5Puuy/XTpedAtn86d+6sal/u9tOpU6fqzZOUlITvv//e6RiQ93BRKgD07NkT+/btq/PYzp07ER8fj507d9Z5PC8vD71797b/f4vFghdeeAHffPNNnecZjUaMGzcOLVq0wLp16zBjxgy8++67WL16dYM5jEYjDh8+jJSUlAafc/LkSSxYsMDh8WeeeQZlZWVYs2YNHnnkEUybNg179+5Vva8HHngA27Ztw9dff421a9ciJiYG48ePhyzLdZ63Y8cOTJ8+3WH7N954A1988QVefvllrF69GiaTCRMmTHDYnohco7avnnvuOXz//fdYuHAhXn31VXzwwQd45513Lruv7du349prr3V4/KOPPsLChQsxc+ZMbNiwATExMXj44Yft8/uNN95ATk4OXnzxRSxbtgzbt2/HSy+9pGpfAHDFFVdg27Zt2LZtGz799FOMGzcO06ZNw+7du+s87/z583j44Yfx+++/13m8rKwMDzzwADp06ICNGzfilltuwYQJExyeR0Su84dzqNmzZ2P//v1YtmwZVqxYgb1799bppMceewyRkZHIzs7G1KlT8frrr+Pzzz9XtS/A/XMom4bO+YhIGW/0E+DZ912X66cBAwbYz3+2bduGr776ComJibjvvvtU7Qtwr59atmxZJ8+2bdtw5513onv37khLS2swE3kfF6UCQI8ePfDrr7/W+VuznTt3YsyYMcjLy0NlZaX98T179tgL68yZM/j73/+OrVu3Ijo6us5rfv/99zh//jxmzpyJq666Cn379sX999+PjRs3Npjjhx9+QFpaGgwGQ4PPmTFjBpKTk+s8duLECfzvf//DCy+8gE6dOuGee+7BXXfdhVWrVqneV2RkJOLi4hAfH4+OHTtiypQpOHLkCA4dOmR/zoIFCzB27Fi0adPGYfv169fj8ccfR+/evdGhQwfMmjUL+/bta3AlnoiUUdNX586dw6ZNmzBz5kz06NEDPXv2xOTJk7Fs2bIG93Px4kUcO3YM3bp1c/hZWVkZnnzySfTt2xft2rXD2LFjcezYMZw7dw6yLOP999/HE088gb59+6Jr166YOXMmPvjggzqZL7Vz505cc8019f5Mr9cjLi4OcXFxaN26NTIzM9GnTx988skn9uf88MMPyMzMREVFhcP269evR2RkJJ5//nkkJiZi0qRJSExMxP79+xvMQ0TK+MM5VEhICJ577jl069YNXbt2xeDBg7Fr1y4A1sXsvLw8PPLII2jXrh1uvvlm/OUvf8H27dtV7Qtw/xzKpr5zPiJSzhv95On3XZfrp/DwcPv5T1xcHD766CPIsozJkyer2hfgXj/VPh+Li4vDyZMn8emnn+I///kPQkJCGsxE3sdFqQDQvXt3hISE4KeffgIAnD59GgUFBbjnnnsQFRVlv/zx2LFjOH/+PHr27AkA+Omnn9CyZUtkZWUhKiqqzmsmJydj4cKFCA0NrfN4eXl5gzkud6UAAOTk5MBoNGLIkCF1Ht+zZw9atmyJ1q1b2x/r0aOHw1UEruzrUhEREQ6PffPNN1i2bBluvfXWOo9bLBbMmzcP1113ncM2ZWVlivdJRI7U9JXto2ypqan210lKSkJRUZHDx9xsfvjhB6Snp0Ov1zv8bNSoURg2bBgA65xetWoVOnbsiGbNmuHcuXO4ePGiw75qamoaXAQ6cuQImjZtimbNmikeh8jIyDr/f9u2bRg8eLDD5fgA8N1336Ffv351/ixZWVno27ev4v0RUf384RxqxowZ6NGjBwDrx08+/vhj+5vP8PBwREREIDs7GzU1NTh69Ch+/PHHyy4GefMcyqahcz4iUs4b/eTp912X66faSktLsWTJEvzrX/9y6Eal+6qPmn6yeeWVVzB06FC0b99e8f7IO7goFQBCQ0ORmppqv+xyx44d6NatGxo1aoRevXrZL+/My8tDx44d0bRpUwBARkYG5s6dW+8bqbi4OPTp08f+/ysrK7F27doGrwSw7behn587dw4vv/wy/v3vf0OSpDo/KyoqQnx8fJ3HmjdvjjNnzqja16Wqq6vx1ltv2T8zbLN69ep6S1On0+G6665DTEyM/bH33nsPTZs2rbM9EblOTV81b94cAOp0QmFhIQDrfRHqo+SkZt26dejZsyfWr1+P6dOnQ5IkNGnSBCEhIR7fV227du3Ct99+izvuuMP+2GOPPYbx48fXu4h28uRJNGvWDM899xyuv/56DB061P63kETkHn84h7J5+umn0a9fPxQXF+PRRx8FAISFhWH69OlYs2YNUlNT0b9/f/z1r3/FPffc49a+bFw9hwIuf85HRMp5o5+89b6rvn6qbfXq1YiPj8ftt99+2dfxdj/Z7Nq1C3l5eXjooYcU7Yu8i4tSAaJnz572wtq5c6f9ZKh37951CsvZBK2PxWLBlClTcPHixQYnbmlpKc6cOdPgos3s2bNx9913o2PHjg4/MxqNDivmoaGhqK6uVrUvAHj77beRnp6O9PR0pKamYunSpZgwYYKqk6MvvvgCy5cvd7qyT0TKuNpXrVq1QlpaGl588UWUlpaiqKjIfp+SmpqaevehZKHouuuuw/r16zF06FCMHz8eJ0+ehMFgwC233IJXX30Vp0+fRllZGf7zn//AYDCo3ldBQYG9j7p164aRI0fi+uuvR5cuXS6bz6aiogKLFy9GXFwclixZgl69emHMmDH2xTIico/o51A2Y8eOxZo1a9CqVSuMHTvWfuP0X3/9FTfddBPWrFmDOXPm4JNPPsFHH32kel/unkNd7pyPiFzj6X7yxvsuoOF+Aqw3XP/www8xevToy76Glu/x1q5di1tuuQUtWrRwaTvyDi5KBYjaN8LbuXOnvZh69+6N/fv3o7q6Gnl5eejVq5dLr2symfDkk0/iq6++wqJFixAXF1fv82z7rK8Qvv76a+Tl5dW7ag5Y/5bv0iKsrq5GeHi4y/uyGT58OHJycpCTk4Ps7Gw89thjeOKJJy57j4X6fPHFF3jssccwevToy/6tIxEpp6av5s6di7Nnz+Kaa67BgAED7N8w07hxY4fXP3fuHH7//Xenb4gSEhLQpUsXTJs2DS1btrR/I960adPQqFEj9O3bF3/9619x9dVXo0mTJvXuy2w248cff7RfMl+f+Ph4ex9t2LABCxcuxM8//1zvt/XVR6/XIzk5GZMmTUKXLl3w5JNPol27doq+LYeInBP5HKq2Dh06IC0tDa+99hoOHTqE77//Htu3b8e6deswe/ZsdO/eHZmZmRg3bhzefPNN1fty5xzK2TkfEbnG0/3kjfddQP39ZLNv3z6cOXOmzhXiavflifd4JpMJX375Je666y7F25B3NXxHavIr6enpOHv2LPbt24ezZ8/i6quvBgB07NgRUVFR+P7773HkyBGX/pavpqYGjz/+OL755hssXrzY/pr1udyVAps3b8bp06ftPzeZTKipqUF6ejqWLFmCFi1aoLi4uM42xcXFDZ68KbkCokmTJkhMTLT//+TkZHz//fdYvXq14o/ZbNq0CU899RSGDx+OqVOnKtqGiJxT01eJiYnYsGEDfv/9d0RFReHEiRPQ6XRISEhweP0dO3bU+ehMfT+Pj4/HVVddBQCQJAlXXXWV/eN5zZs3x3vvvYfS0lKEhYVBlmW88soraNWqlcNr/fTTT2jXrl29C1Y2BoOhTh+1b98elZWVmDx5Mp599tnLbgtYPwpky2rTrl07XilF5CEin0NVV1fjf//7H66//np7V8TGxiImJgYlJSU4efIkEhMT67yh7NKlC9566y2X92XjzjmUs3O+yy3gE5EjT/eTJ993Oesnm6+//ho9e/ZEkyZNLptNq/d4eXl5MJlMuP766xU9n7yPV0oFiMjISCQnJ2PNmjXo3r27/aZvkiShV69eyM7ORrt27Vy6Ee/06dPxzTffYMmSJU6L7nIlMnnyZGzatMm+qj1p0iT7lQPdunVDWloafvvtN5w+fdq+za5duxr8ak5X799iI8syzGazoudu374dTz31FEaNGqX4agYiUsbVvrJYLHjggQdw6NAhNG/eHKGhofjqq6/QpUuXehd0duzYcdmOWLJkCVasWGH//2azGQcPHrTf6PLJJ5/Etm3bEBMTg4iICOTm5qJ58+bo0KGDw2u500eyLNe5vL0haWlpdb5VBgCOHj1a7yIZEblO5HMonU6HKVOm4KuvvrI/VlBQgJKSErRv3x7x8fHIz8+vc+XD0aNH69zEWOm+LkfpOZSzcz4ico2n+8mT77uc9ZPN3r17L7swr2Rfl+PKezzAerP3rl27IiwszOV9kXdwUSqA9OrVC5s2bXI4+enduze+/PJLly47/+abb5CdnY0pU6YgMTERRUVFKCoqwrlz5xyee/r0adTU1DT4tcDNmzdHYmKi/Z/mzZvbrxwIDw9HmzZtcMMNN+DJJ5/EwYMH8eGHH+Ljjz/GqFGjXN6XTUVFhT1zYWEh3n//fWzfvh39+/d3+mc3mUyYOnUqevXqhbFjx9pfp6ioqMHPWxORa1zpK51Oh/DwcLzyyis4fvw4vvjiCyxcuBAPP/xwva/t7KRm5MiRyM7OxsaNG3H06FE8//zzqKysxKBBgwAAMTExeO211/DLL79g586dmDVrFsaNGwedzvE/mUpOoMxms71Dzp49ix9++AGLFi3CDTfc4PBVzfUZPnw4Dh06hPnz5yM/Px//93//h5MnT9o/wkhE7hP1HMpgMGDYsGF49dVX8cMPP2D//v14/PHH0a9fP3Ts2BEZGRkICQnBtGnTcOzYMWzduhVvvfUW7r33Xpf3ZePOOZSzcz4icp0n+8mT77uc9ZPN4cOH6/2LPVf2ZeNOP9XOw2/cEws/vhdAevTogeXLlzt8bKV3794wGo0uXXb+6aefArD+Td/06dPtj7dq1Qpbt26t89zt27cr/paEhsydOxfPPvsshg4diri4OMyePRspKSkOz1O6r+XLl2P58uUAgJCQECQmJmL69Om48847nW67f/9+FBQUoKCgADfccEOdn7333nuX/VgQESnjal/NnDkTzz33HO6++240b94c06ZNwy233OLwur/99hsAXPYqon79+uH555/HggULUFhYiLS0NCxfvhyNGjUCYP0mvJkzZ2LkyJGIjIzE/fffj/vvv9/hdaqrq3HgwIEG/3bR5vTp0/Yu0el0iImJwc0334zHH3/8stvZtGrVCkuXLsWLL76IxYsXo3379li8eDFvzknkQSKfQz3xxBOQJAmPPfYYKioqcOutt2LatGkAgKioKKxYsQIvvvgihgwZgmbNmuGRRx7BsGHDHF5Hi3MoIvI8T/YT4Nn3XZfrJ5vi4mKnfwmnZT8VFxcjOTlZ8fPJ+yRZlmVfhyAiIiIiIiIiouDCj+8REREREREREZHmuChFRERERERERESa46IUERERERERERFpjotSRERERERERESkOS5KERERERERERGR5rgoRUREREREREREmuOiFBERERERERERaY6LUkREREREREREpDkuShERERERERERkea4KEVERERERERERJrjohQREREREREREWmOi1JERERERERERKQ5LkoREREREREREZHmuChFRERERERERESa46IUERERERERERFpjotSRERERERERESkOYNWO7JYLDCZTNDpdJAkSavdEpEfkGUZFosFBoMBOp1v1srZUUTUEF93FPuJiBrCfiIiUSntJ80WpUwmE/bt26fV7ojID3Xv3h2hoaE+2Tc7ioic8VVHsZ+IyBn2ExGJylk/abYoZVsZ6z+gP4xylarXkCQJzSJicM5YClmWXd5eNpoBGYAESBF6ZmAGZhAkQ4QUhi2bt/jsKinA/Y5ydwwA948FMzADM3gng687iv3EDMzADA3x934CAuNclhmYgRkcKe0nzRalbJdzGuUq6IcmqHqNyJAIZI1egoErx6Kixujy9hdWHIF80QSpkQHRQzswAzMwgyAZjGsLAPzZE77gbke5OwaA+8eCGZiBGbyTwdcdxX5iBmZghob4ez8BgXEuywzMwAyOlPYTb3RORERERERERESa46IUERERERERERFpjotSRERERERERESkOS5KEZFbUlonY1D6bYiNjcWg9NuQ0jrZ15GIiACwn4hIXOwnIhKZlh2l2Y3OiShwhIeEYXCPARjXdzRS23SxP77ovjkAgD0nf8bi3JXI2rUZlTXqvomFiEgN9hMRiYr9REQi81VH8UopInJJ+/h2+G7aJiwY9SK6tUqq9zndWiVhwagX8d20TbgqLlHjhEQUrNhPRCQq9hMRicyXHcVFKSJSrH18O3wx+QMkxLSAJEnQ6/T1Pk+v00OSJCTEtMCXT67hiRUReR37iYhExX4iIpH5uqNUL0pVV1fjzjvvxM6dOz0ShIjEFh4ShvWPLkVUWCMY9Mo++WvQGxAV1gg5E5YhPCTMywn/xH4iCi7sJyISFfuJiEQmQkepWpSqqqrCE088gcOHD7sdgIj8w+AeA9CmWYLisrIx6A1o27wVMq/u76VkdbGfiIIP+4mIRMV+IiKRidBRLi9KHTlyBEOHDsWJEyfc3jkR+Y9xfUfDIltUbWu2mDGu72gPJ3LEfiIKTuwnIhIV+4mIRCZCR7m8KPXdd9+hT58+WLNmjds7JyL/kNI6GaltujT4+WJn9Do90tp29frXHbOfiIIP+4mIRMV+IiKRidJRrl2jBWDkyJFu7VCSJESGRKjaNiIkvM6/XVUmSZCZgRmYweUM3RLq/wYGV3VN6IQjZ447PF4uSR55fXf7CVB/LNw9DoD7vw/MwAzBmMHb/QR4pqPYT8zADMGXgf2kTLCcTzMDM4iWQZT3eJIsy7LanSclJeG9995Dnz59nD7XbDYjLy8PgwcPRlZWltpdumXAgAE4e/Ys4uPjsXnzZmZgBmZQmCE2NhaJie5/u0J+fj6Ki4sdHrf1QlpaGvR6dSv1l3KlnwB2FDMwg79m8HY/AZ7vKPYTMzBDcGRgP2nDH34XmIEZRMwgyns8l6+Uctc5YykGrhyratuIkHCsHTYfQ9dMhLGm0uXtiytK7P9mBmZgBuUZBqXfhkX3zVGVr7aXct/Eht2fOTxebix1+7U9RW1HuXscAPd/H5iBGYIxg7f7CRCno9hPzMAM/pWB/aRMsJxPMwMziJZBlPd4mi9KybKMihqjW69hrKlU9Rq2i8KYgRmYwbUM+wsOuZXN/jq/Hap3H25csOlx7h4LtcfBtm9mYAZmcC2Dt/updgZfE/k4MAMzMAP7SeRzWWZgBmZwJMp7PJdvdE5EwWfvqQPYc/JnmC1mVdubLWbknfgJ+3476OFkRBTs2E9EJCr2ExGJTJSO4qIUESmyOHcldJK6ytDr9Ficu9LDiYiIrNhPRCQq9hMRiUyEjuKiFBEpkrVrM06eK4DJbHJpO5PZhBO//4bsH7d4KRkRBTv2ExGJiv1ERCIToaPcWpQ6dOiQ4m9mICL/VllThbsXPoiyqouKS8tkNqGs6iIGLRiDypoqLyesi/1EFDzYT0QkKvYTEYlMhI7ilVJEpNivZ4+j37xhKCg9AwANfv7Y9nhB6Rn0mzcMR4vyNctIRMGJ/UREomI/EZHIfN1Rmn/7HhH5t6NF+ej9wh3IvLo/xvUdjbS2XR2es+/UQSzOXYnsH7do/jd8RBS82E9EJCr2ExGJzJcdxUUpInJZZU0VVu3MwaqdOUhpnYyuCZ0wpe8jeCn3TfxU8Av2njrg64hEFKTYT0QkKvYTEYnMVx3FRSkicsveUwdw5MxxPNj1HmzY/Rkqaoy+jkREBID9RETiYj8Rkci07CjeU4qIiIiIiIiIiDTHRSkiIiIiIiIiItIcF6WIiIiIiIiIiEhzkizLshY7MpvNyMvLQ98b+6JCVnendkmSEBvZFMUVJVATW64wATIACZAi1d1OixmYgRk8nyFSCkPuV7lIS0uDXq9XlcFd7naUu2MAuH8smIEZmME7GXzdUewnZmAGZmiIv/cTEBjnsszADMzgSGk/aX+jcxmQL5rUboqz5WeZgRmYIdAyNApTv62nqRwHjx0HZmAGZhAvgygdFezHgRmYgRkc+Xk//bGp/5/LMgMzMIMjhf2k/aKUBEiNgne1kBmYgRnqewFVu/UOlR0VKH/jygzMwAz1vYi6zTyO/cQMzMAMDi+ibjOP43s8ZmAGZnB4AWVP03xRSorQI3poB1XbRoZEYOPoJRi4cqyqryS8sOII5IsmSJEGRN/PDMzADKJkMK8tULVfb1DbUe6OAeD+sWAGZmAG72QQpaPYT8zADMxwKX/vJyAwzmWZgRmYwZHSfuKNzomIiIiIiIiISHNclCIiIiIiIiIiIs1xUYqIiIiIiIiIiDTHRSkiIiIiIiIiItIcF6XIL5mLKmE8eA7Z2dkwHjwHc1GlryP5RErrZAxKvw2xsbEYlH4bUlon+zoSUdBjP1mxn4jEw36yYj8RiYkdZRVsHaX5t+8RqSWbLKg5fAFVe0tgKa4CAMz+ZLb957rYMISlNEVIx2hIhsBdbw0PCcPgHgMwru9opLbpYn980X1zAAB7Tv6MxbkrkbVrMyprqnwVkyiosJ+s2E9E4mE/WbGfiMTEjrIK5o7iohT5BXNpNS5+dAJymanB51iKq2DcehqV3xej0V1toY8J1TChNtrHt8P6R5eiTbMEWGRLvc/p1ioJC0a9iKf7P4pBC8bgaFG+ximJggv7yYr9RCQe9pMV+4lITOwoq2DvKJeWGs+cOYNJkyahd+/e+Mtf/oI5c+agqiqwVulIPObSapSvOw65vOGyqk0uN6F83XGYS6u9nExb7ePb4YvJHyAhpgUkSYJep6/3eXqdHpIkISGmBb58cg2uikvUOKnvsKNIa+wnK/aTc+wn0hr7yYr95Bz7iXyBHWXFjnJhUUqWZUyaNAlGoxHvv/8+XnvtNfzvf//D66+/7sV4FOxkkwUXPzoBVFsAWelGAKqt28mm+lea/U14SBjWP7oUUWGNYNAru8DRoDcgKqwRciYsQ3hImJcT+h47irTGfrJiPznHfiKtsZ+s2E/OsZ/IF9hRVuwoK8WLUkePHkVeXh7mzJmDjh07omfPnpg0aRI+/vhjb+ajIFdz+IL1ck6lZWUjA3KZCTWHL3gll9YG9xiANs0SFJeVjUFvQNvmrZB5dX8vJRMHO4q0xn6yYj85x34irbGfrNhPzrGfyBfYUVbsKCvFi1JxcXFYunQpYmNj6zxeXl7u8VBENlV7S3y6vSjG9R3d4OeLnTFbzBjXd7SHE4mHHUVaYz9ZsZ+cYz+R1thPVuwn59hP5AvsKCt2lJXiRano6Gj85S9/sf9/i8WClStX4pprrvFKMCJzUaX9GxjUshRX+f1Xiaa0TkZqmy4Nfr7YGb1Oj7S2XQP+q0TZUaQl9pMV+0kZ9hNpif1kxX5Shv1EWmNHWbGj/qT62/fmzZuHn3/+GevWrXNpO0mSEBkSoWqfESHhdf7tqjJJgswMfpPBeMGo6rUvZSgDIhIc9+Ev49AtIUnVa1+qa0InHDlzXFUGZ9wdh3JJUrXd5WjdUe6OAeD+sWAG7TJ4u5+UZHBGi3Hwdj8pyeCMJ8bB0x3FfmIG9hP7CWA/2QTLextmsOJ7PCu+x/uTJMuyq5/kxLx58/DOO+/gtddew2233aZoG7PZjLy8PAwePBhZWVmu7tIjBgwYgLNnzyI+Ph6bN29mBsEzZGdnY/bs2W7va+rUqcjMzFSVwduUZIiNjUViovvfrpCfn4/i4mJVGbzN1gtpaWnQ69X9bUFt7Chm8HYGb/eTkgxacJbB2/2kJIMWPNlR7Cdm8HYG9pMV+8l17Cdm0CID3+NZ8T3en1y+UmrWrFlYvXo15s2bp7isajtnLMXAlWNd3g6wrtCtHTYfQ9dMhLHG9cv1iitK7P9mBvEzGA+eU5XtUot2r8I7FVtUZXBGi3EYlH4bFt03R1W+2l7KfRMbdn+mKoMz7o5DubFU1X7r46uOcncMAPePBTNol8Hb/aQkgzNajIO3+0lJBmc8MQ6e6ij2EzOwn6zYT1bsJ6tgeW/DDFZ8j2fF93h/cmlRasGCBfjggw/w6quv4vbbb3c5FGD92tGKGvcu2TPWVKp6DdtFYczgHxnM0Z65HNkUhXr34S/jsL/gkFvZ7K/z2yHhx8FdInSU2jGw7ZsZ/CODt/tJSQalvDkO3u4nJRmU8sQ4uIP9xAxaZWA/WbGflBOhn4DAf2/DDFZ8j2fF93h/Unyj819//RWLFi3C2LFj0aNHDxQVFdn/IfIGfVw4dLFhbr2GLjYM+jj1n9MXwd5TB7Dn5M8wW8yqtjdbzMg78RP2/XbQw8nEwo4iLbGfrNhPyrCfSEvsJyv2kzLsJ9IaO8qKHfUnxYtSX375JcxmM958803ccMMNdf4h8pawlKY+3V4Ui3NXQicpnq516HV6LM5d6eFE4mFHkdbYT1bsJ+fYT6Q19pMV+8k59hP5AjvKih1lpfjje+PGjcO4ceO8mYXIQUjHaFR+Xwy53AS4cnWyBEiNDQjpGO21bFrK2rUZT/d/FAkxLWDQK//UrclsQkHpGWT/WP89IQIJO4q0xn6yYj85x34irbGfrNhPzrGfyBfYUVbsKCt1y3JEGpEMOjS6qy0QqgOUfvxYAhBq3U4yBMaveGVNFe5e+CDKqi7CZDYp2sZkNqGs6iIGLRiDypoqLyckCj7sJyv2E5F42E9W7CciMbGjrNhRVoFxNCmg6WNC0XhIO0iNla0eS40NaDykHfQxoV5Opq1fzx5Hv3nDUFB6BgAa/Pyx7fGC0jPoN28Yjhbla5aRKNiwn6zYT0TiYT9ZsZ+IxMSOsmJHufjte0S+oo8JRdTIq1Bz+AKq9pbAUuy4KqyLDUNYSlOEdIwOmNXzSx0tykfvF+5A5tX9Ma7vaKS17erwnH2nDmJx7kpk/7glYFbPiUTGfrJiPxGJh/1kxX4iEhM7yirYO4qLUuQ3JIMOockxCE2OgbmoEoYyYHz6SCzavQqmKPj9NzAoVVlThVU7c7BqZw5SWieja0InTOn7CF7KfRM/FfyCvacO+DoiUdBhP1mxn4jEw36yYj8RiYkdZRXMHRWYS40U8PRx4YhIaorMzExEJDUNmrK61N5TB7Bh92coLi7Ght2fBXRZEfkL9pMV+4lIPOwnK/YTkZjYUVbB1lFclCIiIiIiIiIiIs1xUYqIiIiIiIiIiDTHRSkiIiIiIiIiItKcJMuyrMWOzGYz8vLy0PfGvqiQ1d0tXpIkxEY2RXFFCdTElitMgAxAAqRIdfd4ZwZmYAbPZ4iUwpD7VS7S0tKg1+tVZXCXux3l7hgA7h8LZmAGZvBOBl93FPuJGZiBGRri7/0EBMa5LDMwAzM4UtpP2n/7ngzIF01qN8XZ8rPMwAzMEGgZGoWp39bTVI6Dx44DMzADM4iXQZSOCvbjwAzMwAyO/Lyf/tjU/89lmYEZmMGRwn7SflFKAqRGwbtayAzMwAz1vYCq3XqHyo4KlL9xZQZmYIb6XkTdZh7HfmIGZmAGhxdRt5nH8T0eMzADMzi8gLKnab4oJUXoET20g6ptI0MisHH0EgxcORYVNUaXt7+w4gjkiyZIkQZE388MzMAMomQwry1QtV9vUNtR7o4B4P6xYAZmYAbvZBClo9hPzMAMzHApf+8nIDDOZZmBGZjBkdJ+4o3OiYiIiIiIiIhIc1yUIiIiIiIiIiIizXFRioiIiIiIiIiINMdFKXJZSutkDEq/DbGxsRiUfhtSWicHZQZzUSWMB88hOzsbxoPnYC6q1DyDCONAJBIR5oQIGdhPROIRYU6IkIH9RCQmEeaFCBnYUdrT/tv3yC+Fh4RhcI8BGNd3NFLbdLE/vui+OQCAPSd/xuLclcjatRmVNVUBm0E2WVBz+AKq9pbAUmzdx+xPZtt/rosNQ1hKU4R0jIZk8M6arwjjQCQSEeaECBnYT0TiEWFOiJCB/UQkJhHmhQgZ2FG+xUUpcqp9fDusf3Qp2jRLgEW21Pucbq2SsGDUi3i6/6MYtGAMjhblB1wGc2k1Ln50AnKZqcHnWIqrYNx6GpXfF6PRXW2hjwn1aAYRxoFIJCLMCREysJ+IxCPCnBAhA/uJSEwizAsRMrCjfM/lZb78/HyMGTMG6enpuPHGG7F06VJv5CJBtI9vhy8mf4CEmBaQJAl6nb7e5+l1ekiShISYFvjyyTW4Ki4xoDKYS6tRvu445PKGy6o2udyE8nXHYS6t9lgGEcZBdOyn4CLCnBAhA/vJP7CfgosIc0KEDOwn/8B+Cj4izAsRMrCjxODSopTFYsG4cePQtGlTrF+/HjNnzsSbb76JjRs3eisf+VB4SBjWP7oUUWGNYNAru6jOoDcgKqwRciYsQ3hIWEBkkE0WXPzoBFBtAWSlGwGotm4nm+pf7XaFCOMgOvZTcBFhToiQgf3kH9hPwUWEOSFCBvaTf2A/BR8R5oUIGdhR4nBpUaq4uBjJycl4/vnn0a5dO/Tt2xfXXnstdu3a5a185EODewxAm2YJiieIjUFvQNvmrZB5df+AyFBz+IL1ck6lZWUjA3KZCTWHL7idQYRxEB37KbiIMCdEyMB+8g/sp+AiwpwQIQP7yT+wn4KPCPNChAzsKHG4tCgVHx+P119/HY0bN4Ysy9i1axe+//579O7d21v5yIfG9R3d4GdanTFbzBjXd3RAZKjaW+LT7QExxkF07KfgIsKcECED+8k/sJ+CiwhzQoQM7Cf/wH4KPiLMCxEysKPEofrW8RkZGRg5ciTS09Nx2223eTITCSCldTJS23Rp8DOtzuh1eqS17erW11eKkMFcVGn/Bga1LMVVbn2VqAjj4G/YT4FNhDkhQgb2k39iPwU2EeaECBnYT/6J/RT4RJgXImRgR4lF9bfvvfHGGyguLsbzzz+POXPmYNq0aYq2kyQJkSERqvYZERJe59+uKpMkyMygKEO3hCRVr32prgmdcOTMcb/NYLxg9EgGQxkQkeC4D38ZB2fc/Z0slyRV2zVEbT8B6sfB3TEA3D8WwZLB23PCXzJ4u5+UZBBhHJzxxO+kJzuK/RTYGUSYEyJkYD8pw36yCpb3VyJkEOF9hQgZ+B5PGa3e40myLLv6Kco6PvnkE0yePBk//vgjQkMb/mpEs9mMvLw8DB48GFlZWe7sUrUBAwbg7NmziI+Px+bNm5nhMhliY2ORmOj+Hf3z8/NRXFzstxmys7Mxe/ZstzNMnToVmZmZqjKIMA7eZuuFtLQ06PXq/ragPkr7CWBH+VMGb88Jf8ng7X5SkkGEcdCCNzqK/RSYGUSYEyJkYD9ph/0kxnHwlwwivK8QIQPf42lDaT+5dKVUcXEx8vLycPPNN9sf69ChA2pqalBeXo5mzZo5fY1zxlIMXDnWld3aRYSEY+2w+Ri6ZiKMNa5fKldcUWL/NzNcPsOg9Nuw6L45qvLV9lLum9iw+zO/zWA8eM7t/QPAot2r8E7FFlUZRBgHZ9z9nSw3lqrab22e6CdAfUe5OwaA+8ciWDJ4e074SwZv95OSDCKMgzOe+J10t6PYT8GTQYQ5IUIG9pMy7CerYHl/JUIGEd5XiJCB7/GU0eo9nkuLUqdOncKECROQm5uLFi1aAAD279+PZs2aKS4sWZZRUePe5XLGmkpVr2G7KIwZnGfYX3DIrWz21/ntUL378JcM5mjPXBJtioJfj4NS7v5OusMT/WTL4s44qB0D276ZwXkGb88Jf8ng7X5SkkGEcVDKE7+TarGfgieDCHNChAzsJ9ewn6wC/f2VCBlEeF8hQga+x3ONt9/juXSj8+7du6Nr166YOnUqjhw5gtzcXMybNw8PP/ywywFJbHtPHcCekz/DbDGr2t5sMSPvxE/Y99tBv86gjwuHLjZM9fYAoIsNgz5O/b0CRBgHf8B+Ch4izAkRMrCf/Af7KXiIMCdEyMB+8h/sp+AiwrwQIQM7SiwuLUrp9XosWrQIERERGDZsGJ599lnce++9uO+++7yVj3xoce5K6CR1X9Co1+mxOHdlQGQIS2nq0+0BMcZBdOyn4CLCnBAhA/vJP7CfgosIc0KEDOwn/8B+Cj4izAsRMrCjxOHyCLRo0QILFizArl27sG3bNjz88MOQPPzNWSSGrF2bcfJcAUxmk0vbmcwmnPj9N2T/WP89APwtQ0jHaEhRBsDVX3MJkKIMCOkY7XYGEcbBH7CfgocIc0KEDOwn/8F+Ch4izAkRMrCf/Af7KbiIMC9EyMCOEoe6ZTkKCpU1Vbh74YMoq7qoeKKYzCaUVV3EoAVjUFlTFRAZJIMOje5qC4TqlJeWBCDUup1kcH+aiTAORCIRYU6IkIH9RCQeEeaECBnYT0RiEmFeiJCBHSUOLkrRZf169jj6zRuGgtIzANDgZ15tjxeUnkG/ecNwtCg/oDLoY0LReEg7SI2VfTeA1NiAxkPaQR9z+a/RdYUI40AkEhHmhAgZ2E9E4hFhToiQgf1EJCYR5oUIGdhRYnDp2/coOB0tykfvF+5A5tX9Ma7vaKS17erwnH2nDmJx7kpk/7jFKyu2ImTQx4QiauRVqDl8AVV7S2ApdtyHLjYMYSlNrZeDemD1/FIijAORSESYEyJkYD8RiUeEOSFCBvYTkZhEmBciZGBH+R4XpUiRypoqrNqZg1U7c5DSOhldEzphSt9H8FLum/ip4BfsPXUgKDJIBh1Ck2MQmhwDc1ElDGXA+PSRWLR7FUxRcOsbGJQSYRyIRCLCnBAhA/uJSDwizAkRMrCfiMQkwrwQIQM7yre4KEUu23vqAI6cOY4Hu96DDbs/Q0WNMSgz6OPCEZEQgczMTLxTsSVox4FIJCLMCREysJ+IxCPCnBAhA/uJSEwizAsRMrCjtMd7ShERERERERERkea4KEVERERERERERJrjohQREREREREREWlOkmVZ1mJHZrMZeXl56HtjX1TI6u4WL0kSYiOboriiBGpiyxUmQAYgAVKkuttpMQMzMIPnM0RKYcj9KhdpaWnQ6/WqMrjL3Y5ydwwA948FMzADM3gng687iv3EDMzADA3x934CAuNclhmYgRkcKe0n7W90LgPyRZPaTXG2/CwzMAMzBFqGRmHqt/U0lePgsePADMzADOJlEKWjgv04MAMzMIMjP++nPzb1/3NZZmAGZnCksJ+0X5SSAKlR8K4WMgMzMEN9L6Bqt96hsqMC5W9cmYEZmKG+F1G3mcexn5iBGZjB4UXUbeZxfI/HDMzADA4voOxpmi9KSRF6RA/toGrbyJAIbBy9BANXjlX1tYgXVhyBfNEEKdKA6PuZgRmYQZQM5rUFqvbrDWo7yt0xANw/FszADMzgnQyidBT7iRmYgRku5e/9BATGuSwzMAMzOFLaT7zRORERERERERERaY6LUkREREREREREpDkuShERERERERERkea0v9G5SuaiShgvGJGdnQ3jwXMwR0vQx4Uzgw8ypLRORreEJMTGxmJQ+m3YX3AIe08dCLoMIhwLETKQGMeBGaxE6AYRMohwLETIQGIcB2awEqEbmEGcDGQlwtxkBisR5gUzWInw+6AloRelZJMFNYcvoGpvCSzFVQCA2Z/Mtv9cFxuGsJSmCOkYDcngnYu+mMEqPCQMg3sMwLi+o5Hapov98UX3zQEA7Dn5MxbnrkTWrs2orKkK2AwiHAsRMpAYx4EZrEToBhEyiHAsRMhAYhwHZrASoRuYQZwMZCXC3GQGKxHmBTNYifD74CvCLkqZS6tx8aMTkMtMDT7HUlwF49bTqPy+GI3uagt9TCgzeCFD+/h2WP/oUrRplgCLbKn3Od1aJWHBqBfxdP9HMWjBGBwtyg+4DCIcCxEykBjHgRmsROgGETKIcCxEyEBiHAdmsBKhG5hBnAxkJcLcZAYrEeYFM1iJ8PvgS6qX2MaNG4cpU6Z4MoudubQa5euOQy5v+KDUJpebUL7uOMyl1czg4Qzt49vhi8kfICGmBSRJgl6nr/d5ep0ekiQhIaYFvnxyDa6KSwyoDCIcCxEy+BNvdZQIx4EZrEToBhEyiHAsRMjgT9hPgZ9BhG5gBnEy+BO+xwuODCLMC2awEuH3wddULUpt2rQJubm5ns4CwHrZ2sWPTgDVFkBWuhGAaut2sqn+1U1mcF14SBjWP7oUUWGNYNAru6jOoDcgKqwRciYsQ3hIWEBkEOFYiJDBn3iro0Q4DsxgJUI3iJBBhGMhQgZ/wn4K/AwidAMziJPBn/A9XnBkEGFeMIOVCL8PInB5Uaq0tBRz585F9+7dvZEHNYcvWC9bU3pQbGRALjOh5vAFZvBQhsE9BqBNswTFk9TGoDegbfNWyLy6f0BkEOFYiJDBX3izo0Q4DsxgJUI3iJBBhGMhQgZ/wX4KjgwidAMziJPBX/A9XvBkEGFeMIOVCL8PInB5Ueo///kP/va3v6FDhw7eyIOqvSU+3Z4Z/jSu7+gGP1frjNlixri+owMigwjHQoQM/sKbHSXCcWAGKxG6QYQMIhwLETL4C/ZTcGQQoRuYQZwM/oLv8YIngwjzghmsRPh9EIFLi1Lbt2/HDz/8gPHjx3sljLmo0n6nebUsxVUwF1Uyg5sZUlonI7VNlwY/V+uMXqdHWtuuSGmd7NcZRDgWImTwF97sKBGOAzNYidANImQQ4ViIkMFfsJ+CI4MI3cAM4mTwF3yPFzwZRJgXzGAlwu+DKBRfq1ZVVYUZM2Zg+vTpCA8PV71DSZIQGRJR78+MF4yqX7c2QxkQkeC4jzJJgswMijJ0S0jySIauCZ1w5Mxxv80gwrEQIYMzESHhdf7tqnJJUrVdbd7uKG8fB8D5sWAGK293g79kEOFYiJDBGXf7CXC/o9hPwZNBhG5gBnEyOBMM/QSIcS7LDFYivL9iBisRfh+c0eo9nuJFqQULFqBbt274y1/+oiqQTbOIGGSNXlLvz7KzszH7k9luvT4AjE8ficzMTIfHB6wagLPlZxEb2RQbmeGyGWJjY93ePwBM6fsIHux6j99mEOFYiJBBqbXD5qvabvD6wW7tF/B+R3n7OADOjwUzWHm7G/wlgwjHQoQMSqntJ8D9jmI/BU8GEbqBGcTJoFQg9xMgxrksM1iJ8P6KGaxE+H1Qytvv8SRZlhXdVisjIwPFxcXQ662XuFVXW7+CMDQ0FLt373a6vdlsRl5eHm4a0A+NR15V73OMB8+h9JN8RcEvJ6Z/O0QkNXV4/MzS/bCU10DXOAQtHuzGDJfJMCj9Niy6b47bGR55bwo27P7MbzOIcCxEyOBMREg41g6bj6FrJsJY4/olpOWrjuJ/m79EWlqavWNc5e2O8vZxAJwfC2aw8nY3+EsGEY6FCBmccbefAPc7iv0UPBlE6AZmECeDM8HQT4AY57LMYCXC+ytmsBLh98EZrd7jKb5S6r///S9MJpP9/7/88ssAgMmTJ7sUTJZlVNTUf6maOdr9j/AAgCkK9e7Dtv7GDM4z7C845JEM+3875NcZRDgWImRQylhTqeo1FK6NX5a3O8rbx8G2b2ZwnsHb3eAvGUQ4FiJkUEptP9XOoBb7KXgyiNANzCBOBqUCuZ8AMc5lmcFKhPdXzGAlwu+DUt5+j6f4RuetWrVCYmKi/Z9GjRqhUaNGSExMdDlcQ/Rx4dDFhrn1GrrYMOjj1H8emhms9p46gD0nf4bZYla1vdliRt6Jn7Dvt4N+nUGEYyFCBn/g7Y4S4Tgwg5UI3SBCBhGOhQgZ/AH7KXgyiNANzCBOBn/A93jBlUGEecEMViL8PojCpW/f00JYSv2XS2u1PTP8aXHuSugkdb8iep0ei3NXBkQGEY6FCBlIjOPADFYidIMIGUQ4FiJkIDGOAzNYidANzCBOBrISYW4yg5UI84IZrET4fRCB6kWpl156CS+99JInswAAQjpGQ4oyAK5ezSYBUpQBIR2jmcFDGbJ2bcbJcwUwmU3On1yLyWzCid9/Q/aPWwIigwjHQoQM/sYbHSXCcWAGKxG6QYQMIhwLETL4G/ZTYGcQoRuYQZwM/obv8QI/gwjzghmsRPh9EIFwV0pJBh0a3dUWCNUpPzgSgFDrdpLB/T8SM1hV1lTh7oUPoqzqouLJajKbUFZ1EYMWjEFlTVVAZBDhWIiQgcQ4DsxgJUI3iJBBhGMhQgYS4zgwg5UI3cAM4mQgKxHmJjNYiTAvmMFKhN8HEQj5p9DHhKLxkHaQGiu7D7vU2IDGQ9pBHxPKDB7O8OvZ4+g3bxgKSs8AQIOfu7U9XlB6Bv3mDcPRIve/SUCkDCIcCxEykBjHgRmsROgGETKIcCxEyEBiHAdmsBKhG5hBnAxkJcLcZAYrEeYFM1iJ8Pvga4q/fU9r+phQRI28CjWHL6BqbwksxY4rkbrYMISlNLVe9uaFVUJmsDpalI/eL9yBzKv7Y1zf0Uhr29XhOftOHcTi3JXI/nGLV/5WSYQMIhwLETKQGMeBGaxE6AYRMohwLETIQGIcB2awEqEbmEGcDGQlwtxkBisR5gUzWInw++BLwi5KAdbL2UKTYxCaHANzUSUMZcD49JFYtHsVTFHQ5E7zzGBVWVOFVTtzsGpnDlJaJ6NrQidM6fsIXsp9Ez8V/IK9pw4ERQYRjoUIGUiM48AMViJ0gwgZRDgWImQgMY4DM1iJ0A3MIE4GshJhbjKDlQjzghmsRPh98BW/WWLTx4UjIqkpMjMzEZHU1CcHhRms9p46gA27P0NxcTE27P7MJ/8RFyGDCMdChAwkxnFgBisRukGEDCIcCxEykBjHgRmsROgGZhAnA1mJMDeZwUqEecEMViL8PmjJbxaliIiIiIiIiIgocHBRioiIiIiIiIiINMdFKSIiIiIiIiIi0pwky7KsxY7MZjPy8vLQ98a+qJDV3bFekiTERjZFcUUJ1MSWK0yADEACpEh193hnBmZgBs9niJTCkPtVLtLS0qDX61VlcJe7HeXuGADuHwtmYAZm8E4GX3cU+4kZmIEZGuLv/QQExrksMzADMzhS2k/af/ueDMgXTWo3xdnys8zADMwQaBkahanf1tNUjoPHjgMzMAMziJdBlI4K9uPADMzADI78vJ/+2NT/z2WZgRmYwZHCftJ+UUoCpEbBu1rIDMzADPW9gKrdeofKjgqUv3FlBmZghvpeRN1mHsd+YgZmYAaHF1G3mcfxPR4zMAMzOLyAsqdpviglRegRPbSDqm0jQyKwcfQSDFw5FhU1Rpe3v7DiCOSLJkiRBkTfzwzMwAyiZDCvLVC1X29Q21HujgHg/rFgBmZgBu9kEKWj2E/MwAzMcCl/7ycgMM5lmYEZmMGR0n7ijc6JiIiIiIiIiEhzXJQiIiIiIqLgY7H4OgERkdg06Ent7ylFRERERESksdSiSow6UIprC4xIKqlG6Ou9cVwn4VDTUGxPiMD7yTHYExfu65hERD7ji57kopSfMRdVwnjBiOzsbBgPnoM5WoJe4/94prRORreEJMTGxmJQ+m3YX3AIe08d0DQDx4FIPJyXViKMgwgZiEQiwpwQoZ+CNcOVpdVYsLUQ1xcaUSMBIalpwC2dgagohJaVofvBg+i8Jw/j9pXim5YRmJDREsdiQr2aiag2ETqKGYI7w6U9uV8GsgCUAYiyyOj8exX+ca7KKz3JRSk/IJssqDl8AVV7S2AprgIAzP5ktv3nutgwhKU0RUjHaEgG73wiMzwkDIN7DMC4vqOR2qaL/fFF980BAOw5+TMW565E1q7NqKyp8koGjgOReDgvrUQYBxEyEIlEhDkhQj8Fe4Yhv5zHwq2noQ8NA+6/HyGTJgHp6Q7PC9m9G3jjDfRZ8wF2fHAM4zNaIqtTtEezENUmQkcxAzMAf/ZktVnGOwDekIG8ep6XJgOTAAwpNHq0J7koJThzaTUufnQCcpmpwedYiqtg3Hoald8Xo9FdbaH38N/stI9vh/WPLkWbZgmwyPV/prRbqyQsGPUinu7/KAYtGIOjRfkezcBxIBIP56WVCOMgQgYikYgwJ0Top2DPMOSX81j8eSHQsSN0n30GJCY2fH+UlBRg+XIYZsyA7pZbsOTzI5AgY12nJh7JQlSbCB3FDMwA/NmTvwC4HUA+Gr7x+F4ADwCYCeBTs4wlnxd4pCddXmL7/PPPkZSUVOefSZMmuRWC6mcurUb5uuOQyxv+5axNLjehfN1xmEurPZahfXw7fDH5AyTEtIAkSdDr9PU+T6/TQ5IkJMS0wJdPrsFVcYkey8BxIKXYT9rhvLQSYRxEyEDOsZ+0I8KcEKGfgj3DVaXVWLj1tHVBascOoFUrQJIAff0ZoNdbf96qFXQ7dwIdOmDh1tO4Mgi6kv2kLRE6ihmYAfizJ38BcB2AU3883tCtzW2PnwJwLYDDgEd60uVFqSNHjuCmm27Ctm3b7P+88MILboUgR7LJgosfnQCqLYCsdCMA1dbtZJP7d8kPDwnD+keXIiqsEQx6ZRfVGfQGRIU1Qs6EZQgPCXM7A8eBXMF+0gbnpZUI4yBCBlKG/aQNEeaECP3EDMD8rYXQhYZZr5CKigJCQpRtGBICREVB9/nn0IeGYcHWQrdy+AP2k3ZE6ChmYAab+VsLUWWWcTuACwDMCrcz//H82wBUm2W3e9LlRalff/0VnTp1QlxcnP2f6Gh+3trTag5fsF6+p/SX00YG5DITag5fcDvD4B4D0KZZguITCRuD3oC2zVsh8+r+bmfgOJAr2E/a4Ly0EmEcRMhAyrCftCHCnBChn4I9Q+rZSlxfaETIsOHWj+wpXZCyCQkB2rWDYegwXF9oRGpRpeos/oD9pB0ROooZmAH4syezYP3IntIFKRvzH9tlAW73pKpFqXbt2qneISlTtbfEp9sDwLi+oxv87L8zZosZ4/qOdjsDx4FcwX7SBuellQjjIEIGUob9pA0R5oQI/RTsGUYdLEWNBGDSpIbvIeU0hBmYOBE1EjDqQKnqLP6A/aQdETqKGZgB+LMn34CKRaE/6GDd3t2edGn/sizj2LFj2LZtG2677TbcfPPNePnll1FdHfiftdaSuajSfsd9tSzFVTC7sVqZ0joZqW26NPjZf2f0Oj3S2nZFSutk1Rk4DuQK9pM2OC+tRBgHETKQMuwnbYgwJ0ToJ2YAri0wIiQ1zfotew3dQ8ppCD3QowdCUtNwTaFR3Wv4AfaTdkToKGZgBptrC4zY/8e37Kn9EKAFwG4A+2W41ZMuXU9bUFAAo9GI0NBQvP766zh16hReeOEFVFZWYtq0aYpeQ5IkRIZEqAobERJe59+uKpMkyH6QwXjBM//hM5QBEQmO+1CSoVtCkkcydE3ohCNnjqvKwHFQJhDmRbkkqdquNk/0E6B+HNwdA8D9Y6FFBm/PSyUZvD0vlWQQYRxEyOBMoMwLdzuK/cR+cpU7/cQMQFJJNXBLZ49kQFISOu/dU++fU4R54e/9BATGuay/vLdhBmawSSqpRpZHEgCHAGSeq3bYj9J+kmRZdukTjKWlpWjSpAmkP3bw6aef4sknn8Tu3buhv8zfRJjNZuTl5WHw4MHIyvLUH981AwYMwNmzZxEfH4/NmzcLmyE7OxuzZ892e19Tp05FZmamqgyxsbFITHT/m0/y8/NRXFysKgPHQRsiZLD1Qlpa2mV7xBm1/QSwo5Rm8Pa8VJLB2/NSSQYRxkGEDFoQIYMnOor95P0MIswJEfop6DNYLOjRuzcwdiyweLHbGTBuHLBkCXZ99x2gq/shExHmBftJjOPgL+9tmIEZANh7cjGAh9xOALwNYBzg0JNK+8m1Ow8CiImJqfP/27dvj6qqKpw/fx7NmjVzuv05YykGrhzr6m4BWFeu1w6bj6FrJsJY4/plasUVJfZ/i5zBePCcqmyXWrR7Fd6p2KIqw6D027DovjluZ3gp901s2P2ZqgwcB2UCYV6UG0tV7fdS7vYToL6j3B0DwP1joUUGb89LJRm8PS+VZBBhHETI4EygzAtPdBT7if3kCnf6iRmA4zoJoWVlbu8fAHDhAqp1EgaucnzrJsK88Pd+AgLjXNZf3tswAzPYHNdJiLK4eof1+kUD9fak0n5yaVHq66+/xuTJk/HVV18hIsJ6adaBAwcQExOjuLBkWUZFjXuXqhlrKlW9hu2iMNEzmKPd/ygTAJiiUO8+lGTYX3DIIxn2/3ZIdQaOg2sCYV64wxP9ZMvizjioHQPbvkXP4O15qSSDt+elkgwijIMIGZQKlHmhFvtJmwwizAkR+okZgENNQ9H94EGPZMDBgzjYLNSr53HsJ6tAOJcV/b0NMzCDzaGmoej8u3v3tLLpDNTbk0r7yaUbnaenpyMsLAzTpk3D0aNHkZubi7lz5+LBBx905WXICX1cOHSxYW69hi42DPo49Z9P33vqAPac/Blmi6tfDmlltpiRd+In7PtN/QkBx4FcwX7SBuellQjjIEIGUob9pA0R5oQI/cQMwPaECNTsyQN277Z+i56qEGZg1y7U7N2DHS3V3afIH7CftCNCRzEDM9hsT4hANwlIg3vfvpcOoKsEt3rSpf03btwYy5Ytw7lz5zB48GA8++yzGDZsGEvLC8JSmvp0ewBYnLsSOkndr6hep8fi3JVuZ+A4kFLsJ+1wXlqJMA4iZCDn2E/aEWFOiNBPwZ7h/eQYhMgA3njD4T5QykPogfnzESJbXy9QsZ+0JUJHMQMzAH/25CS49+17kwC3e9Lllu7YsSPeeecd7N69G9u2bcOECRPsN8UjzwnpGA0pygC4OrQSIEUZENIx2u0MWbs24+S5ApjMJpe2M5lNOPH7b8j+sf77MbiC40CuYD9pg/PSSoRxECEDKcN+0oYIc0KEfgr2DHviwvFNywiY1nwA5OcDNTWuvUBNDXD8OExr1+CblhHYE+BXlLKftCNCRzEDMwB/9uQQAIkAXP2aBP0f2w0G3O5JtVdqkZdJBh0a3dUWCNUp/yWVAIRat5MM7h/aypoq3L3wQZRVXVR8QmEym1BWdRGDFoxBZY37n1HlOBCJh/PSSoRxECEDkUhEmBMi9BMzABMyWsJcXQXLrbcCZWXKF6ZqaoCyMlhuuQXm6ipMyGjpVg6i2kToKGZgBpsJGS0RqpfwCaw3K1e6MKX/4/mfAgjVS273JM9GBaaPCUXjIe0gNVZ2P3qpsQGNh7SDPibUYxl+PXsc/eYNQ0HpGQBo8N4AtscLSs+g37xhOFqU77EMHAci8XBeWokwDiJkIBKJCHNChH4K9gzHYkIxPqMlcPgwLH36AL/99sfOGrjHlO3x336zPv/IEYzPaIlj7EryMBE6ihmYAfizJzsB2A6g9R+PN7RIZHu89R/P7wh4pCdd+vY90p4+JhRRI69CzeELqNpbAkux498a6WLDEJbS1Hr5nxf+1vtoUT56v3AHMq/uj3F9RyOtbVeH5+w7dRCLc1ci+8ctXrkyiONAJB7OSysRxkGEDEQiEWFOiNBPwZ4hq1M0JMhYuPVX6LskwzB0GDBxItCjh+OT8/KA+fNhWrsG5uoqjL8lAVmd+BFn8g4ROooZmAGo3ZOnsc8sIwvAGwB21/PcVFjvITUY1iukxma09EhPclHKD0gGHUKTYxCaHANzUSUMZcD49JFYtHsVTFHQ5JuTKmuqsGpnDlbtzEFK62R0TeiEKX0fwUu5b+Kngl+w99QBr2fgOBCJh/PSSoRxECEDkUhEmBMi9FOwZ1jXqQl2xUdgwdZCXP/uu6h5712EpKYBSUlAdDRw4QJw6BBq9uQhRAZ2JERg4k1X8gop8joROooZmAGo25P3FxoxSgL2y8AhABdg/aheEoBukvWm5tsSIjDxJs9dScpFKT+jjwtHREIEMjMz8U7FFlTUGDXPsPfUARw5cxwPdr0HG3Z/5pMMHAci8XBeWokwDiJkIBKJCHNChH4K1gzHYkJxR2YiUosqMepAKa45dQCd9+5BqEVGtU7CwWah2NEtBu8nxwT8Tc1JTCJ0FDMEdwaHniw0IvNcdZ2efKdlhFd6kotSREREREQU8PbEhWNP3BUAgMiQCGwc+TYGrnqIC/dERH/wRU/yphJERERERBR8dHwrRER0WRr0JJuYiIiIiIiIiIg0J8myLGuxI7PZjLy8PPS9sS8qZHXfqiFJEmIjm6K4ogRqYssVJkAGIAFSpLpPLjIDMzCD5zNESmHI/SoXaWlp0Ov1qjK4y92OcncMAPePBTMwAzN4J4OvO4r9xAzMwAwN8fd+AgLjXJYZmIEZHCntJ+3vKSUD8kWT2k1xtvwsMzADMwRahkZh6rf1NJXj4LHjwAzMwAziZRClo4L9ODADMzCDIz/vpz829f9zWWZgBmZwpLCftF+UkgCpUfCuFjIDMzBDfS+garfeobKjAuVvXJmBGZihvhdRt5nHsZ+YgRmYweFF1G3mcXyPxwzMwAwOL6DsaZovSkkRekQP7aBq28iQCGwcvQQDV45Vdff3CyuOQL5oghRpQPT9zMAMzCBKBvPaAlX79Qa1HeXuGADuHwtmYAZm8E4GUTqK/cQMzMAMl/L3fgIC41yWGZiBGRwp7Sfe6JyIiIiIiIiIiDTHRSkiIiIiIiIiItIcF6WIiIiIiIiIiEhzXJTyMymtkzEo/TbExsZiUPptSGmdzAw+yiACjgOJxFxUCePBc8jOzobx4DmYiyo1zyDCnBBhHEQgwrEgshFhXoowJ0QYBxGIcCyIahNhboowL0QYBxGIcCy0pP2375HLwkPCMLjHAIzrOxqpbbrYH1903xwAwJ6TP2Nx7kpk7dqMypoqZvBiBhFwHEgkssmCmsMXULW3BJZi6+/b7E9m23+uiw1DWEpThHSMhmTwzt+DiDAnRBgHEYhwLIhsRJiXIswJEcZBBCIcC6LaRJibIswLEcZBBCIcC1/hopTg2se3w/pHl6JNswRYZEu9z+nWKgkLRr2Ip/s/ikELxuBoUT4zeCGDCDgOJBJzaTUufnQCcpmpwedYiqtg3Hoald8Xo9FdbaGPCfVoBhHmhAjjIAIRjgWRjQjzUoQ5IcI4iECEY0FUmwhzU4R5IcI4iECEY+FLLi81VldXY+bMmejVqxeuu+46vPrqq5Bl2RvZgl77+Hb4YvIHSIhpAUmSoNfp632eXqeHJElIiGmBL59cg6viEpnBwxlEwHFwjv2kHXNpNcrXHYdc3vBJRG1yuQnl647DXFrtsQwizAkRxkEEIhwL0bGftCPCvBRhTogwDiIQ4ViIjv2kLRHmpgjzQoRxEIEIx8LXXF6UeuGFF/Dtt99i2bJleOWVV7B27VqsWbPGG9mCWnhIGNY/uhRRYY1g0Cu7oM2gNyAqrBFyJixDeEgYM3gogwg4Dsqwn7Qhmyy4+NEJoNoCKD1nlQFUW7eTTfX/DZArRJgTIoyDCEQ4Fv6A/aQNEealCHNChHEQgQjHwh+wn7QjwtwUYV6IMA4iEOFYiMClRanS0lJkZWVh1qxZSElJwbXXXosHHngAe/bs8Va+oDW4xwC0aZag+JfTxqA3oG3zVsi8uj8zeCiDCDgOzrGftFNz+IL1MmtX/xJVBuQyE2oOX3A7gwhzQoRxEIEIx0J07CftiDAvRZgTIoyDCEQ4FqJjP2lLhLkpwrwQYRxEIMKxEIFLi1K7du1C48aN0bt3b/tj48aNw5w5czweLNiN6zu6wc+TOmO2mDGu72hm8FAGEXAcnGM/aadqb4lPtwfEmBMijIMIRDgWomM/aUeEeSnCnBBhHEQgwrEQHftJWyLMTRHmhQjjIAIRjoUIXFqUOnnyJFq1aoWcnBzcfvvt6NevHxYuXAiLJTAunxNFSutkpLbp0uDnSZ3R6/RIa9vVra+OZAZxcByUYT9pw1xUaf9mFLUsxVVufcWvCHNChHEQgQjHwh+wn7QhwrwUYU6IMA4iEOFY+AP2k3ZEmJsizAsRxkEEIhwLUbh0nVhFRQXy8/PxwQcfYM6cOSgqKsL06dMRERGBBx54QNFrSJKEyJAIVWEjQsLr/NtVZZIE2Q8ydEtIUvXal+qa0AlHzhxnBjcyOBMsvw/OuDsO5ZKkarvaPNFPgPpxcHcMAPePhRYZjBeMql+7NkMZEJFQ/5/RWQZvzwklGUQYB2e0+H0Q4Vg444lxcLej2E/sJ1exn5zzh2PhDPvJKlje43l7bvrL+woRxsEZvsez0uo9niS78NUKixcvxiuvvIKtW7eiVatWAIAVK1Zg9erV+PTTTy+7rdlsRl5eHgYPHoysrCylu/SoAQMG4OzZs4iPj8fmzZuFzRAbG4vERPfvpp+fn4/i4mJmcCODt3EcrGy9kJaWBr1e3d8WuNNPADtKaYbs7GzMnj3b7f1MnToVmZmZqjJ4e04oySDCOGjBH46FFtztKPaTNhlEmJcizAkRxkEL/nAstMB+EuM4KMng7bnpL+8rRBgHb/OXY+FtSvvJpSul4uLiEBYWZi8sALjyyitRWFio+DXOGUsxcOVYV3ZrFxESjrXD5mPomokw1rh+uV5xRYn93yJnGJR+Gxbd5/7nuF/KfRMbdn/GDG5kcCZYfh+ccXccyo2lqvZbmyf6CVDfUe6OAeD+sdAig/HgOVWve6lFu1fhnYotqjJ4e04oySDCODijxe+DCMfCGU+Mg7sdxX5iP7mK/eScPxwLZ9hPVsHyHs/bc9Nf3leIMA7O8D2elVbv8VxalEpNTUVVVRWOHTuGK6+8EgBw9OjROiXmjCzLqKhx75I9Y02lqtewXRQmeob9BYfcymZ/nd8O1bsPZlCeQalA/31Qyt1xcIcn+smWxZ1xUDsGtn2LnsEc7f5HLQHAFIUGMzrL4O05oSSDCOOglDd/H0Q4Fkp5YhzUYj9pk0GEeSnCnBBhHJRiP1mxn6wC/T2et+emv7yvEGEclOJ7PCtvv8dz6UbnV111FW688UY888wzOHjwIL7++mssXrwYI0aMcDkgNWzvqQPYc/JnmC1mVdubLWbknfgJ+347yAxuZhABx0EZ9pM29HHh0MWGufUautgw6OPU3z9DhDkhwjiIQIRj4Q/YT9oQYV6KMCdEGAcRiHAs/AH7STsizE0R5oUI4yACEY6FKFxalAKAl19+GW3btsWIESPw9NNPY9SoUbj33nu9kS2oLc5dCZ3k8uEBYL0T/+LclczgoQwi4Dgow37SRlhKU59uD4gxJ0QYBxGIcCz8AftJGyLMSxHmhAjjIAIRjoU/YD9pR4S5KcK8EGEcRCDCsRCByyMQFRWFuXPnYvfu3fj2228xYcIESB745iyqK2vXZpw8VwCT2eTSdiazCSd+/w3ZP9Z/DwBm8E8cB2XYT9oI6RgNKcoAuDq0EiBFGRDSMdrtDCLMCRHGQQQiHAt/wH7ShgjzUoQ5IcI4iECEY+EP2E/aEWFuijAvRBgHEYhwLESgblmOvK6ypgp3L3wQZVUXFf+SmswmlFVdxKAFY1BZU8UMHsogAo4DiUQy6NDorrZAqE75yYQEINS6nWRw/z89IswJEcZBBCIcCyIbEealCHNChHEQgQjHgqg2EeamCPNChHEQgQjHQgSBcTQD1K9nj6PfvGEoKD0DAA1+3tT2eEHpGfSbNwxHi/KZwcMZRMBxIJHoY0LReEg7SI2VfV+G1NiAxkPaQR8T6rEMIswJEcZBBCIcCyIbEealCHNChHEQgQjHgqg2EeamCPNChHEQgQjHwtdc+vY90t7Ronz0fuEOZF7dH+P6jkZa264Oz9l36iAW565E9o9bvLJaygzi4DiQSPQxoYgaeRVqDl9A1d4SWIodf990sWEIS2lqvUzbC3+rJcKcEGEcRCDCsSCyEWFeijAnRBgHEYhwLIhqE2FuijAvRBgHEYhwLHyJi1J+oLKmCqt25mDVzhyktE5G14ROmNL3EbyU+yZ+KvgFe08dYAaNMoiA40AikQw6hCbHIDQ5BuaiShjKgPHpI7Fo9yqYoqDJN6OIMCdEGAcRiHAsiGxEmJcizAkRxkEEIhwLotpEmJsizAsRxkEEIhwLXwnMpcYAtvfUAWzY/RmKi4uxYfdnPvnlZAZxcBxIJPq4cEQkNUVmZiYikpr65CRChDkhwjiIQIRjQWQjwrwUYU6IMA4iEOFYENUmwtwUYV6IMA4iEOFYaImLUkREREREREREpDkuShERERERERERkea4KEVERERERERERJqTZFmWtdiR2WxGXl4e+t7YFxWyurvFS5KE2MimKK4ogZrYcoUJkAFIgBSp7h7vzMAMzOD5DJFSGHK/ykVaWhr0er2qDO5yt6PcHQPA/WPBDMzADN7J4OuOYj8xAzMwQ0P8vZ+AwDiXZQZmYAZHSvtJ+2/fkwH5okntpjhbfpYZmIEZAi1DozD123qaynHw2HFgBmZgBvEyiNJRwX4cmIEZmMGRn/fTH5v6/7ksMzADMzhS2E/aL0pJgNQoeFcLmYEZmKG+F1C1W+9Q2VGB8jeuzMAMzFDfi6jbzOPYT8zADMzg8CLqNvM4vsdjBmZgBocXUPY0zRelpAg9ood2ULVtZEgENo5egoErx6Kixujy9hdWHIF80QQp0oDo+5mBGZhBlAzmtQWq9usNajvK3TEA3D8WzMAMzOCdDKJ0FPuJGZiBGS7l7/0EBMa5LDMwAzM4UtpPvNE5ERERERERERFpjotSpJ7F4usEREREREREROSntL+nFPmt1KJKjDpQimsLjEgqqUbo671xXCfhUNNQbE+IwPvJMdgTF+7rmERERERERETkB7go5YKU1snolpCE2NhYDEq/DfsLDmHvqQMBn+HK0mos2FqI6wuNqJGAkNQ04JbOQFQUQsvK0P3gQXTek4dx+0rxTcsITMhoiWMxoV7NZC6qhPGCEdnZ2TAePAdztAQ9F8QoiInQTyLMS2YgEg/7iRmIRMaOYgbyLS5KOREeEobBPQZgXN/RSG3Txf74ovvmAAD2nPwZi3NXImvXZlTWVAVchiG/nMfCraehDw0D7r8fIZMmAenpDs8L2b0beOMN9FnzAXZ8cAzjM1oiq1O0R7PIJgtqDl9A1d4SWIqtf87Zn8y2/1wXG4awlKYI6RgNycBPplLgE6GfRJiXzEAkHvYTMxCJjB3FDCQOLkpdRvv4dlj/6FK0aZYAi1z//ZO6tUrCglEv4un+j2LQgjE4WpQfMBmG/HIeiz8vBDp2hO6zz4DExIbvI5WSAixfDsOMGdDdcguWfH4EEmSs69TEI1nMpdW4+NEJyGWmBp9jKa6CcetpVH5fjEZ3tYXey1drEfmSCP0kwrxkBiLxsJ+YgUhk7ChmILFwqbEB7ePb4YvJHyAhpgUkSYJep6/3eXqdHpIkISGmBb58cg2uiksMiAxXlVZj4dbT1gWpHTuAVq0ASQL09WeAXm/9eatW0O3cCXTogIVbT+PK0mq3s5hLq1G+7jjk8obLqja53ITydcdh9sC+iUQkQj+JMC+ZgUg87CdmIBIZO4oZSDwuLUplZ2cjKSnJ4Z/OnTt7K59PhIeEYf2jSxEV1ggGvbKLyQx6A6LCGiFnwjKEh4T5fYb5WwuhCw2zXiEVFQWEhCjbMCQEiIqC7vPPoQ8Nw4KthW7lkE0WXPzoBFBtAWSlGwGotm4nm/gNgcGC/dQwT/eTCPOSGcifsJ8axn4K3AzkP9hRDWNHBW4GEodLi1IDBgzAtm3b7P989dVXSExMxH333eetfD4xuMcAtGmWoLisbAx6A9o2b4XMq/v7dYbUs5W4vtCIkGHDrR/ZU7ogZRMSArRrB8PQYbi+0IjUokrVWWoOX7Bezqm0rGxkQC4zoebwBdX7Jv/Cfro8T/aTCPOSGcifsJ8uj/0UmBnIf7CjLo8dFZgZSBwuLUqFh4cjLi7O/s9HH30EWZYxefJkb+XziXF9Rzf4+WJnzBYzxvUd7dcZRh0sRY0EYNKkhu8h5TSEGZg4ETUSMOpAqeosVXtLVG/rie3Jf7CfnPNUP4kwL5mB/An7yTn2U+BlIP/BjnKOHRV4GUgcqu8pVVpaiiVLluBf//oXQkMD52ZjKa2TkdqmS4OfL3ZGr9MjrW1XpLRO9tsM1xYYEZKaZv2WvYbuIeU0hB7o0QMhqWm4ptCo6iXMRZX2b2BQy1JcBbMbV2qRf2I/1c8T/STCvGQG8mfsp/qxnwIrA/kvdlT92FGBlYHEovrb91avXo34+HjcfvvtLm0nSRIiQyJU7TMiJLzOv11VJkmQnWTolpCk6rUv1TWhE46cOe6XGZJKqoFbPPQZ8qQkdN67x2E/SsbBeEHdYtalDGVARILjPpRkcEaL38lgyFAuSaq2a4jafgLUj4O7YwA4Pxbe7gYlGbw9L5lBeQZntPidDJYMnuwo9tPlsZ8CI4MzgdINImQQ5RxK9HNZX7+/AsR4b8MMygTC+ysRMijtJ0mWZVc/yQlZltGvXz88+OCDGDlypKJtzGYz8vLyMHjwYGRlZbm6S48YMGAAzp49i/j4eGzevLne58TGxiIx0f1vV8jPz0dxcbH/ZbBY0KN3b2DsWGDxYrczYNw4YMkS7PruO0D354V5SsYhOzsbs2fPdjvC1KlTkZmZ6fC4kgzexgxWtl5IS0uDXu3VeX9Q00+Af3SUt7tBSQZvz0tmUJ5BC8xg5amOYj85x34KjAxaYAYrX59D+UM/AWK8xxPhvQ0zaIMZrJT2k6orpfbt24czZ87gjjvucHnbc8ZSDFw5Vs1uERESjrXD5mPomokw1rh+uV5xRYn93w1lGJR+GxbdN0dVvtpeyn0TG3Z/5pcZjuskhJaVub1/AMCFC6jWSRi46iGXMgCA8eA5j0RYtHsV3qnY4vC4kgzOaPE7GQwZyo2lqvZbH3f6CVDfUe6OAeD8WHi7G5Rk8Pa8ZAblGZzR4ncyWDJ4qqPYT86xnwIjgzOB0g0iZBDlHIrv8fzjvQ0zKBMI769EyKC0n1QtSn399dfo2bMnmjRp4vK2siyjosa9S/aMNZWqXsN2UdjlMuwvOORWNvvr/Hao3n34Q4ZDTUPR/eBBj2TAwYM42CzUYT9KxsEc7ZnLkU1RUH0slPLm72QwZfAEd/rJlsWdcVA7BrZ9Xy6Dt7tBSQZvz0tmUJ5BKW/+TgZbBnexn5xjPwVGBqUCpRtEyOAJfI/nnDvv8UR4b8MMrgmE91ciZHBG1Y3O9+7di6uvvlrNpsLbe+oA9pz8GWaLWdX2ZosZeSd+wr7f1C/q+DrD9oQI1OzJA3bvtn6LnqoQZmDXLtTs3YMdLdV9hlUfFw5dbJi6/f9BFxsGfZz6z+mT/2E/NcwT/STCvGQG8lfsp4axnwIrA/kndlTD2FGBlYHEompR6vDhw+jQoYOnswhjce5K6CR1X0yo1+mxOHelX2d4PzkGITKAN96ocx8o10LogfnzESJbX0+tsJSmqrf1xPbkf9hPDfNUP4kwL5mB/BH7qWHsp8DLQP6HHdUwdlTgZSBxqJqVxcXFiI6O9nQWYWTt2oyT5wpgMptc2s5kNuHE778h+8f6P3/vLxn2xIXjm5YRMK35AMjPB2pqXHuBmhrg+HGY1q7BNy0jsMeNVeyQjtGQogyAq1d5SoAUZUBIx8D9PaX6sZ/q58l+EmFeMgP5I/ZT/dhPgZmB/A87qn7sqMDMQOJQ/fG9v/zlL57OIozKmircvfBBlFVdVFxaJrMJZVUXMWjBGFTWVPl9hgkZLWGuroLl1luBsjLlC1M1NUBZGSy33AJzdRUmZLR0K4dk0KHRXW2BUJ3y0pIAhFq3kwwqr/Qiv8V+cuTpfhJhXjID+SP2kyP2U+BmIP/DjnLEjgrcDCQOHs0G/Hr2OPrNG4aC0jMA0ODnj22PF5SeQb95w3C0KD8gMhyLCcX4jJbA4cOw9OkD/PbbHztr4HPYtsd/+836/CNHMD6jJY7FhLqdRR8TisZD2kFqrOy+/FJjAxoPaQe9B/ZNJCIR+kmEeckMROJhPzEDkcjYUcxA4lH17XvB4mhRPnq/cAcyr+6PcX1HI61tV4fn7Dt1EItzVyL7xy0eWT0XKUNWp2hIkLFw66/Qd0mGYegwYOJEoEcPxyfn5QHz58O0dg3M1VUYf0sCsjp57rJKfUwookZehZrDF1C1twSWYsc/py42DGEpTa2Xg3L1nAKcCP0kwrxkBiLxsJ+YgUhk7ChmILFwUcqJypoqrNqZg1U7c5DSOhldEzphSt9H8FLum/ip4BfsPXUgoDOs69QEu+IjsGBrIa5/913UvPcuQlLTgKQkIDoauHABOHQINXvyECIDOxIiMPGmKz1yhdSlJIMOockxCE2OgbmoEoYyYHz6SCzavQqmKPAbGCjoiNBPIsxLZiASD/uJGYhExo5iBhIHF6VcsPfUARw5cxwPdr0HG3Z/hooaY1BkOBYTijsyE5FaVIlRB0pxzakD6Lx3D0ItMqp1Eg42C8WObjF4PznGrZuau0IfF46IhAhkZmbinYotPjkWRCIRoZ9EmJfMQCQe9hMzEImMHcUM5FtclCLF9sSFY0/cFQCAyJAIbBz5NgaueohlQUREREREREQu44cyST0df32IiIiIiIiISB2uKhARERERERERkeYkWZZlLXZkNpuRl5eHvjf2RYWs7hsMJElCbGRTFFeUQE1sucIEyAAkQIpU98lFZmAGZvB8hkgpDLlf5SItLQ16vV5VBne521HujgHg/rFgBmZgBu9k8HVHsZ+YgRmYoSH+3k9AYJzLMgMzMIMjpf2k/T2lZEC+aFK7Kc6Wn2UGZmCGQMvQKEz9tp6mchw8dhyYgRmYQbwMonRUsB8HZmAGZnDk5/30x6b+fy7LDMzADI4U9pP2i1ISIDUK3tVCZmAGZqjvBVTt1jtUdlSg/I0rMzADM9T3Iuo28zj2EzMwAzM4vIi6zTyO7/GYgRmYweEFlD1N80UpKUKP6KEdVG0bGRKBjaOXYODKsaq+8e3CiiOQL5ogRRoQfT8zMAMziJLBvLZA1X69QW1HuTsGgPvHghmYgRm8k0GUjmI/MQMzMMOl/L2fgMA4l2UGZmAGR0r7iTc6JyIiIiIiIiIizXFRioiIPMti8XUCIiIiIiLyA9rfU4qIiAJKalElRh0oxbUFRiSVVCP09d44rpNwqGkotidE4P3kGOyJC/d1TCIiIiIiEgwXpVxgLqqE8YIR2dnZMB48B3O0BD3faPkEjwVRXb6YE1eWVmPB1kJcX2hEjQTsl4EsAGUAoiwyOv9ehX+cq8K4faX4pmUEJmS0xLGYUK9mEgH7iaguEeaECBlEwHEgciTCvBAhgwg4DsGJi1JOyCYLag5fQNXeEliKqwAAsz+Zbf+5LjYMYSlNEdIxGpKBn4b0Jh4Lorp8OSeG/HIeC7eeRrVZxjsA3pCBvHqelyYDkwAMKTRixwfHMD6jJbI6RXs0iwjYT0R1iTAnRMggAo4DkSMR5oUIGUTAcSAuSl2GubQaFz86AbnM1OBzLMVVMG49jcrvi9HorrbQB8FVAL7AY0FUly/nxJBfzmPx54X4BcDtAPLR8A0K9wJ4AMBMAJ+aZSz5vAASZKzr1MQjWUTAfiKqS4Q5IUIGEXAciByJMC9EyCACjgMBvNF5g8yl1ShfdxxyecMTpDa53ITydcdhLq32crLgw2NBVJcv58RVpdVYuPU0fgFwHYBTfzze0K3NbY+fAnAtgMMAFm49jSsDZH6yn4jqEmFOiJBBBBwHIkcizAsRMoiA40A2Li9KFRYW4qGHHsLVV1+NjIwMrFixwguxfEs2WXDxoxNAtQWQlW4EoNq6nWziN095Co8FuYL91NBG8NicmL+1EFVmGbcDuADArHA78x/Pvw1AtVnGgq2FbuUQga+PBfkX9lNDG8Gjc0KEDCLgOJArgqGfADHmhQgZRMBxoNpcXpR67LHHEBkZiezsbEydOhWvv/46Pv/8c29k85mawxeslxAqnSA2MiCXmVBz+IJXcgUjHgtyBfvpMjwwJ1LPVuL6QiOyYP3IntIFKRvzH9tlAbi+0IjUokrVWUTAfiJXsJ8uw4NzQoQMIuA4kCuCoZ8AMeaFCBlEwHGg2lxalDp//jzy8vLwyCOPoF27drj55pvxl7/8Bdu3b/dWPp+o2lvi0+3pTzwWpBT7yfvbjzpYihoJeAPqP/utg3X7GgkYdaBUdRYRsJ9IKfaTNtuLkkEEHAdSKlj6CRBjXoiQQQQcB6rNpfcV4eHhiIiIQHZ2NmpqanD06FH8+OOPSE5O9lY+zZmLKu13/VfLUlwFs59fASACHgtyBftJGXfmxLUFRuz/41v21F40bQGwG8B+Gbim0KjyVXzP18eC/Av7SRl354QIGUTAcSBXBEM/AWLMCxEyiIDjQJdy6dv3wsLCMH36dMyaNQvvvfcezGYzMjMzcc899yh+DUmSEBkS4XJQAIgICa/zb1eVSRJkJxmMFzzzJslQBkQkOO5DSQZntBgHETLwWARPhnJJUrVdbZ7oJ0D9OLg7BoDzY+HtOeEsQ1JJNbI8kgA4BCDzXHW9f053fyeD4VgoocU4BEsGdzuK/aScO3NChAzOBMuxcCZQukGEDP7eT0DwvK8QIYMzwXIsnAmE91ciZFDaT5Isyy59knPevHkoLCzEP/7xDxw+fBizZs3CzJkzcdddd112O7PZjLy8PAwePBhZWZ56W+OaAQMG4OzZs4iPj8fmzZvrfU52djZmz57t9r6mTp2KzMxMVRm8zV8y8FgETwZbL6SlpUGv16t+HbX9BPhHR3l7Tlw2g8WCHr17YzGAh9xOALwNYByAXd99B+jqXrQrwu+k0MdCQ8xg5YmOYj8p486cECGDFjgOzFAb+8l/3leIkMHbOA7MUJvSfnLpSqnt27dj3bp1yM3NRXh4OLp3744zZ87gzTffVFRaAHDOWIqBK8e6slu7iJBwrB02H0PXTISxxvXL9YorSuz/biiD8eA5VdkutWj3KrxTsUVVBme0GAcRMvBYBE+GcmOpqv3W5ol+AtR3lLtjADg/Ft6eE84yHNdJiLK4ekfK+kUDqNZJGLjKcYnL3d/JYDgWSmgxDsGSwd2OYj8p586cECGDM8FyLJwJlG4QIYO/9xMQPO8rRMjgTLAcC2cC4f2VCBmU9pNLi1L79+9HYmIiwsP/vHyrS5cueOuttxS/hizLqKhx75I9Y02lqtewXRR2uQzmaPc/RgQApijUuw8lGZTy5jiIkIHHIvgyuMMT/WTL4s44qB0D274vl8Hbc8JZhkNNQ9H5d/fuAWDTGcDBZqFenZuBfCxc4c1xCLYMarGflHNnToiQQalAPxZKBUo3iJBBLVH6CQj89xUiZFAq0I+FUoHw/kqEDM64dKPz+Ph45Ofno7q62v7Y0aNH0bp1a9fSCUwfFw5dbJhbr6GLDYM+Tv1nw8mKx4JcwX5Sxp05sT0hAt0kIA3uffteOoCuErCjpbrPt4vA18eC/Av7SRl354QIGUTAcSBXBEM/AWLMCxEyiIDjQJdy6X1FRkYGQkJCMG3aNBw7dgxbt27FW2+9hXvvvddb+XwiLKWpT7enP/FYkFLsJ+9v/35yDEJkYBLc+/a9SQBCZOvr+TP2EynFftJme1EyiIDjQEoFSz8BYswLETKIgONAtbm0KBUVFYUVK1agqKgIQ4YMwZw5c/DII49g2LBh3srnEyEdoyFFGQBXryyUACnKgJCO0V7JFYx4LEgp9pMTHpgTe+LC8U3LCAwBkAjA1dup6v/YbjCAb1pGYI+f/w0X+4mUYj854cE5IUIGEXAcSKlg6SdAjHkhQgYRcByoNpfuKQUAHTp0wDvvvOONLMKQDDo0uqstytcdB6otgJKPQkoAQq3bSQa1H2yhS/FYkCvYTw1tBI/NiQkZLbHjg2P4xCzjOgAXAJgVbKeH9ebmnwII1UuYkNHSrRwi8PWxIP/CfmpoI3h0ToiQQQQcB3JFMPQTIMa8ECGDCDgOVBuPZgP0MaFoPKQdpMbK1u2kxgY0HtIO+phQLycLPjwWRHX5ck4ciwnF+IyW6ARgOwDbHSca+o+J7fHWfzy/I4DxGS1xLEDmJ/uJqC4R5oQIGUTAcSByJMK8ECGDCDgOZOPylVLBRB8TiqiRV6Hm8AVU7S2BpdjxW6d0sWEIS2lqvQSRK7Zew2NBVJcv50RWp2hIkLFw62nsM8vIAvAGgN31PDcV1ntIDYb1CqmxGS2R1SmwLrlmPxHVJcKcECGDCDgORI5EmBciZBABx4EALko5JRl0CE2OQWhyDMxFlTCUAePTR2LR7lUwRYF3/dcQjwVRXb6cE+s6NcGu+Ags2FqI+wuNGCUB+2XgEKwf6YsGkASgm2S9qfm2hAhMvClwrpC6FPuJqC4R5oQIGUTAcSByJMK8ECGDCDgOxKVGF+jjwhGR1BSZmZmISGrKCeJDPBZEdfliThyLCcUdmYnoO7Qd3ukWA31sGDJ1EsYByNRJ0MeG4Z1uMeg7tB3uvDsxYBekLsV+IqpLhDkhQgYRcByIHIkwL0TIIAKOQ3DilVJEROSWPXHh2BN3BQAgMiQCG0e+jYGrHkJFjdHHyYiIiIiISGS8UoqIiDxLx/+0EBERERGRc3znQEREREREREREmpNkWZa12JHJZMKePXvQf0B/GGXHu+orIUkSmkXE4JyxFGpiy0YzIAOQAClCzwzMwAyCZIiQwrBl8xakpqbCYPDNp4rd7Sh3xwBw/1gwAzMwg3cy+Lqj2E/MwAzM0BB/7ycgMM5lmYEZmMGR0n7SrLksFgsAYMvmLVrtkoj8jK0nfLlvdhQRNcRXHcV+IiJn2E9EJCpn/aTZlVIWiwUmkwk6nQ6SJGmxSyLyE7Isw2KxwGAwQOej+xGxo4ioIb7uKPYTETWE/UREolLaT5otShEREREREREREdnwRudERERERERERKQ5LkoREREREREREZHmuChFRERERERERESa46IUERERERERERFpjotSRERERERERESkOS5KERERERERERGR5rgoRUREREREREREmvOrRans7GwkJSXhww8/1HS/SUlJdf655pprMG3aNFy8eFHTHABw/vx5vPTSS8jIyEBqair69++PFStWwGKxeH3fGRkZ9jHo3Lkz0tPTMXz4cHz99dde33d9GS79Z+fOnT7PMWLECM0yVFRU4PXXX8ftt9+OlJQU9OnTB5MmTcLhw4c12X9GRgays7MdHs/OzkZGRoYmGUQT7B0V7P10aQ5fdRT7if1UH/YT+4n99CdfdhT7yRH7yXf9BIjRUSL00+Vy8BzKux1l8MqresmmTZvQtm1bbNiwAffcc4+m+54/fz7S09NhsVhQWFiI6dOnY+7cuZg5c6ZmGUpKSjBs2DDEx8fjxRdfROvWrbFv3z7MmjULJ0+exHPPPef1DFOnTsWAAQNgsVhw/vx55OTk4KGHHsLSpUtx3XXXeX3/tTNcqkmTJprs/3I5QkJCNNn3xYsXMXLkSFRUVGDKlCno3LkzSkpK8P7772P48OHIyclBmzZtNMlCfwrmjmI/Oea4lJYdxX6iS7Gf2E+1c1wqWPoJYEeJiP3k234CxOgoEfqpoRw8h/Iuv1mU+v3337F9+3bMnj0bU6ZMwcmTJzU9IE2aNEFcXBwAoEWLFnjooYcwc+ZMTRelXnnlFYSGhmLZsmUICwsDALRp0wbh4eEYP348Ro8ejSuvvNKrGaKiouqMw1NPPYWioiLMmTMHGzdu9Oq+68vgS77MsXDhQvz+++/YvHkzoqOjAQCtWrXCnDlzUFhYiBUrVmj2HzGyCvaOYj/Vn8NX2E9UG/uJ/VRfDl/xdQZ2lFjYT77vJ0CMjvJ1N4iQI1j7yW8+vvfJJ58gKioKd911F+Lj47Fhwwaf5omIiNB0f9XV1di0aRNGjRplLyybm266CStWrECrVq00zWQzbNgw/PLLL8jPz/fJ/oONxWLB+vXr8Y9//MNeVrXNnTsXTz75pA+SBbdg7ij2E9mwn8TEfmI/kRU7SjzsJzH7CWBHaS2Y+8lvFqU2bdqEG2+8ETqdDhkZGcjJyYEsyz7Jcu7cOfz3v//FXXfdpdk+T5w4gYqKCnTv3t3hZ5Ik4ZprrkFoaKhmeWpr3749AODIkSM+2X+wOXHiBM6dO4eePXvW+/P4+HiEh4drnIqCuaPYT2TDfhIT+4n9RFbsKPGwn8TsJ4AdpbVg7ie/+PheYWEhfvzxR/zjH/8AANx6661YvXo1du3a1eBB87SxY8dCr9dDlmUYjUbExMTg+eef12TfAHDhwgUA1ssJRWPLpNVNAWfMmIFZs2bVeSwhIQGbNm3SZP+Xy/HNN98gMjLSq/stKSkBUPfz1d9++y0effRR+//XajzqGwOTySTEpbdaCvaOYj/VJUJHsZ/YTzbsJ/ZTbcHcT4A4HcV+smI/idtPAN/j1cZzKO92lF8sSm3atAlhYWG44YYbAAC9e/dGkyZNsH79es0K64UXXkBqaipkWUZJSQlWrlyJESNGYOPGjWjevLnX9x8TEwPA+u0MoikvLwcANG7cWJP9TZo0CbfeemudxwwG7X+V68uhxSW/tss5bf8hA4D09HTk5OQAAD777DOsXr3a6zmA+sdAy/2LItg7iv1UlwgdxX5iP9mwn2IAsJ9sgrmfAHE6iv1kxX6KASBmPwF8j1cbz6G8u3+/WZSqrKxEjx497I+ZzWZ88skneO655zS5jK1FixZITEwEALRr1w5du3ZFnz59sGXLFowePdrr+2/bti2ioqLw008/ISUlxeHnjzzyCO69915Nv8HF5tChQwCAjh07arK/5s2b24+FL/kqR2JiImJiYrB7927770JERIQ9ixaLpDb1jYGW+xdFsHcU+6kuETqK/cR+smE/sZ9qC+Z+AsTpKPaTFftJ3H4C+B5Pa6L0k21fWnaU8PeUOnbsGH7++WdMmzYNOTk59n9ee+01lJeX4/PPP/dJLp1OB1mWYTabNdmfwWDAgAED8P7776O6urrOz7Zu3YqtW7ciPj5ekyyXysrKQteuXQPy6ylFZDAYMHjwYLz77rv2v8Go7cyZMz5IFbzYUewn+hP7SSzsJ/YT1cWOEgf7Sex+AthRWgvmfhL+SqlNmzYhJiYGw4YNq3Ojt06dOmHhwoXIycnBwIEDvZ7j/PnzKCoqAmD9XO3y5cthNpuRkZHh9X3bTJw4Effccw/GjBmDiRMn4oorrsDOnTsxb9483HfffejQoYPXM5SVlaGoqMh+ieu6deuwefNmLF++3Ov7vjTDpRo1aqTJ/QhEMHHiROzatQvDhw/HhAkT0LVrV5SUlODDDz/EunXrcOedd/o6YtBgR1mxnxxzXCpYOor9JA72kxX7yTHHpYKlnwB2lCjYT1Yi9BMgRkexn4K3n/xiUWrgwIH1fvPAiBEj8OKLL+LMmTNo0aKFV3NMnDjR/r8jIiLQrVs3LFmyRNOV47i4OKxevRrz58/H5MmTUVpairZt22LSpEkYMWKEJhlmz56N2bNnQ5IkNGvWDF26dMGKFSs0+9x37QyX+uc//4nx48drlsOXIiIi8N///hfvvvsuFi1ahPz8fISGhiIlJQXz58/HzTff7OuIQYMdZcV+csxxqWDpKPaTONhPVuwnxxyXCpZ+AthRomA/WYnQT4AYHcV+Ct5+kmRffecmEREREREREREFLeHvKUVERERERERERIGHi1JERERERERERKQ5LkoREREREREREZHmuChFRERERERERESa46IUERERERERERFpjotSRERERERERESkOS5KERERERERERGR5rgoFQDGjRuHZ555ps5jH3/8MZKSkjB//vw6jy9atAh/+9vf6jwmyzIeeOABZGdn13n8/Pnz+Ne//oX09HT89a9/xXvvvec0y0033YQzZ844PP77779j0qRJ6NGjB66//nrMmzcPJpPJK/vKyMhAUlKS/Z+ePXti0qRJ+P333+t9nTfffBNTpkyp89iFCxfw7LPP4rrrrsM111yDKVOm4MKFC04zEZEjb3UUAJSWluK6667DqVOnnOYYPXo0fvzxR4fHKyoqMG3aNPTp0we9evXCc889h4sXL9p//vnnn9fplKSkJEyaNEnVvu699946r5Oeno4xY8YgPz+/3tf56KOPcO+999Z5rKqqCrNmzcK1116La6+9FtOnT0dFRYXTPz8ROQqEcygbk8mEv/3tbw65XdmXJ86haps5c6ZDhxGRcv5+DpWfn48xY8YgPT0dN954I5YuXep0X08//TQ2btzo8PiUKVPq9FNqaiqGDx+OvXv31nneV199hb/97W9IT0/HwIED8eWXX9b5+ccff4ybb74ZqampePTRR3Hu3Dmnmci7uCgVAHr27Il9+/bVeWznzp2Ij4/Hzp076zyel5eH3r172/+/xWLBCy+8gG+++cbhdf/1r3/h1KlTWLNmDaZOnYqXX34ZX3/9dYM58vPzER4ejhYtWjj8bPLkySgvL8eaNWvwf//3f9i0aVOdUvLkvgBg6tSp2LZtG/7f//t/+O9//4vz58/j6aefdnjexx9/XO/J24wZM3Dw4EEsXrwYy5Ytw6+//opp06Y1mIeIGuatjjp//jwefvjhBt8s1WY0GnH48GGkpKQ4/Gz27NnYv38/li1bhhUrVmDv3r146aWX7D8/cuQIbrrpJmzbts3+zwsvvKBqXwDwwAMPYNu2bfj666+xdu1axMTEYPz48ZBluc7zduzYgenTpztsv2DBAnz33XdYvHgx3n77bfzwww949dVXnY4BETkKhHMom+XLl+PgwYNO/8zePoey+fHHH7F69WqneYioYf58DmWxWDBu3Dg0bdoU69evx8yZM/Hmm2/Wu+BU244dO3DNNdfU+7P+/fvbz8XWr1+P1NRUPPTQQ/aFsIMHD2LChAkYPHgwcnJyMHz4cPzzn/+0d+PevXvx7LPPYsKECVizZg0uXLjgsOhH2uOiVADo0aMHfv311zqr0jt37sSYMWOQl5eHyspK++N79uyxl9WZM2fw97//HVu3bkV0dHSd1zx48CC+/fZbvPzyy+jUqRNuv/12DBkypN4Vcpvt27fj2muvdXi8uroazZs3x4wZM9ChQwf07NkTt912G3bt2uXxfdlERUUhLi4OLVq0QHJyMh5//HF8/fXXKCsrA2D928QZM2Zg6tSpaNOmTZ1tKyoq8Omnn2L69Ono1q0bunbtiqlTp+KLL75AVVVVg/skovp5o6N++OEHZGZmKr5C6IcffkBaWhoMBoPDz0JCQvDcc8/Z5/vgwYPt/QQAv/76Kzp16oS4uDj7P5fmUbovAIiMjERcXBzi4+PRsWNHTJkyBUeOHMGhQ4fsz1mwYAHGjh3r0E8AkJubi2HDhqF79+5ISUnBiBEjsGPHDkXjQER1+fs5lE1+fj7ee+89dOjQwemf2ZvnULVzT58+HWlpaU7zEFHD/Pkcqri4GMnJyXj++efRrl079O3bF9dee61Df9V29OhRewfVJzw83H4udtVVV+HJJ59EZWWl/Tzo448/xjXXXIP77rsPiYmJGDVqFPr06YMtW7YAAFauXIn+/ftj0KBB6Ny5M+bOnYvc3FycPHlS0ViQd3BRKgB0794dISEh+OmnnwAAp0+fRkFBAe655x5ERUXZT4KOHTuG8+fPo2fPngCAn376CS1btkRWVhaioqLqvOZ3332Hzp071znZmD59Ov75z382mKOhk5zQ0FC8/PLLSExMBAAcPnwYW7dutZemJ/fVkIiICEiSZP//FRUVOHToENauXYv09PQ6z9XpdHjrrbeQnJxc53Gz2VznPwhEpIw3Omrbtm0YPHiwoo+pAJfvjBkzZqBHjx4AgFOnTuHjjz+u8zeNv/76K9q1a6f4z6umny71zTffYNmyZbj11lsdfhYTE4NPP/0U58+fx/nz5/HZZ5859BURKePv51C1X3/ixIlo1qyZ0z+zN8+hbBYvXoykpCRcf/31ivdDRI78+RwqPj4er7/+Oho3bgxZlrFr1y58//33Dv116b4aukqqPgaDAaGhofb/f/fdd2Py5MkOz7Mtqu/Zs8c+RgDQsmVLJCQkYM+ePYr3SZ7HRakAEBoaitTUVPvnaXfs2IFu3bqhUaNG6NWrl/3Szry8PHTs2BFNmzYFYL1vwNy5c+s9gTl58iRat26NZcuWISMjA7fffjs++OCDBjPIsuy0ZADr55HvvPNOREVFYdSoUV7dl83FixexdOlS3HjjjfZSjo6OxgcffIDOnTs7PD88PBx//etf6xTce++9h6SkJEUne0RUlzc66rHHHsP48eOh1+sVZbjcpeA2Tz/9NPr164fi4mI8+uijAKx9c+zYMWzbtg233XYbbr75Zrz88suorq52a1821dXVeOutt+z3R7BZvXp1gx331FNP4dSpU+jTpw/69OmD8+fPY8aMGYr2R0R1+fs5FABkZWWhqqoKQ4cOdfrn9fY5FGBdyF+9ejU/EkPkAf58DlVbRkYGRo4cifT0dNx2222X3ZfSRXOTyYT3338fISEh9nzt27ev002HDx+us6h29uxZxMfH13md5s2b4/Tp04r2Sd7BRakA0bNnT3tZ7dy5E3369AEA9O7du05ZKT0JqaiowLfffotdu3bh//7v/zB27FjMmTMHn376ab3PP3jwIFq2bIkmTZpc9nWnTZuG9957DzU1NXjiiSe8tq8ZM2YgPT0daWlp6NGjBz755BM89NBDiv7sl1q5ciW2bNmCp556StX2ROT5jnJFaWkpzpw5U2fRpz5jx47FmjVr0KpVK4wdOxYWiwUFBQUwGo0IDQ3F66+/br/55ty5c1Xv6+2330Z6ejrS09ORmpqKpUuXYsKECXWuRLicEydOoGXLlnj33XexbNkyVFVV1bkHFhG5xp/PoX7//Xe8+uqr+Pe//62oQ7x9DiXLsv2qrdjYWEXbENHl+es5VG1vvPEG3nrrLRw4cABz5syp9zUsFgt++OGHy/45Nm7caD+HSklJwb///W88+OCDaNSokcNzz507h4kTJ+Lqq69Gv379AACVlZV1LjwArAt/l/vLRvI+LkoFiNo3wdu5c6d9Mvfu3Rv79+9HdXU18vLy0KtXL0Wvp9frYTab8fLLL6N79+4YPHgwhg4dijVr1tT7fKWXgnfu3Bl9+vTB7Nmz8b///Q+nTp3yyr4mTZqEnJwcbNiwAR9++CFGjBiBBx54AIcPH3b+h6/l/fffxwsvvIBnnnkGN9xwg0vbEtGfPN1RrrDtz9kbtg4dOiAtLQ2vvfYaDh06hO+//x6tWrXCzp07MWfOHCQnJ+OWW27B1KlTsXbtWpjNZlX7Gj58OHJycpCTk4Ps7Gw89thjeOKJJ7B9+3anf5by8nI8++yzePrpp9GnTx9cf/31mD17NrKysnD27Fnng0FEDvz5HOrFF19EZmYmOnXqpCibt8+h1qxZA7PZjGHDhinKQ0TO+es5VG3du3fHTTfdhGeeeQYffPBBvYtAP//8M9q0aePwccPaMjIy7OdQOTk5eP755/Hqq686fLtgcXEx/v73v0OWZbzxxhvQ6azLHmFhYQ77rq6urvdWCqQdLkoFiPT0dJw9exb79u3D2bNncfXVVwMAOnbsiKioKHz//fc4cuSI4hX0+Ph4XHHFFYiMjLQ/duWVV6KwsLDe51/uJKe8vBybN2+us2JuuxFnSUmJR/dl07x5cyQmJiIxMRHdu3fH1KlTER8fX+/XoTZk2bJl+Pe//40nn3wSf//73xVvR0SOPN1RrrhcZ1RXV+PTTz9FeXm5/bHY2FjExMSgpKQEgPUeTrVPxtq3b4+qqiqcP3/epX3ZNGnSxN5PycnJePjhh9GnTx9F31J19OhRVFRU1Lk0vUuXLrBYLLz0nEglfz6H2rRpE9577z37lQM//PAD3n77bdxxxx0u78vGnXOoTZs2Yf/+/bj66quRnp5u/4bQ9PR0FBQUON2eiBz56zlUcXExvvjiizrbdOjQATU1NXW2UbIvm0aNGtn7qVOnThgxYgQGDRqElStX2p9z5swZjBo1CtXV1XjvvffqfISxRYsWKC4urvOaxcXFDd5YnbTBRakAERkZieTkZKxZswbdu3e3r/ZKkoRevXohOzsb7dq1U3xPpNTUVPz222/2m8IB1jdDrVq1cnhuTU0N9u7da7/J3aWMRiMef/zxOjeQ++mnn6DX63HllVd6dF/O1HdlQ33Wr1+PuXPn4plnnsGYMWNU7YuI/uTpjnLF5U5ydDodpkyZgq+++sr+WEFBAUpKStC+fXt8/fXX6NOnD4xGo/3nBw4cQExMTL1ZXb2BsI0sy4r6yXYfhCNHjtgfO3r0KACgdevWLu+XiPz7HOqzzz7DRx99ZL9qoFu3bhg+fDgWL17s8r6cUdJRL7/8MjZt2mTPM3z4cHTr1g05OTkO93EhImX89Rzq1KlTmDBhAs6cOWP/+f79+9GsWbN6s7pyT87aZFm2L9xXVFTgwQcfhE6nw8qVK9GiRYs6z01NTa3z7X+FhYUoLCxEamqqy/slz+GiVADp1asXNm3a5LBK3rt3b3z55ZcuXdJ53XXX4corr8TTTz+NX3/9FZs3b7Zfwn2pPXv2oFOnTggPD6/3teLi4nDrrbdi1qxZ+Pnnn/HDDz/g2WefxejRo9G4cWOP7sumrKwMRUVFKCoqwqlTpzB//nzk5+fj9ttvd/pnLy0txb///W/cfffduOOOO+yvU1RUpHhRi4gcebKjlDp9+jRqamoa/Npyg8GAYcOG4dVXX8UPP/yA/fv34/HHH0e/fv3QsWNHpKenIywsDNOmTcPRo0eRm5uLuXPn4sEHH3R5XzYVFRX2TiksLMT777+P7du3o3///k7/PFdccQX+8pe/4LnnnsP+/fuxb98+PPfcc7jjjjv4RQxEbvDXcyjbFQO2f8LDw9GkSZN6F8C0OIdq0aJFnTxNmjRBeHg4EhMT6/06eSJSxh/Pobp3746uXbti6tSpOHLkCHJzczFv3jw8/PDDDq9VXV1tv8ryciorK+39dObMGWzevBkbN260n0O9/fbbOHHiBP7zn/8AgP25tr8kGDFihP2jyQcPHsRTTz2FG2+80em5G3kX/+sQQHr06IHly5fbb35n07t3bxiNRpcu6dTr9Vi8eDFmzJiBzMxMNG3aFFOmTLHfJK42Javas2fPxuzZs/GPf/wDADBo0CD861//8sq+au8PsH52uEOHDnj99dedFh1g/Sr2iooKrF+/HuvXr6/zsy+//JJXIxCp5MmOUkrJVws/8cQTkCQJjz32GCoqKnDrrbdi2rRpAIDGjRtj2bJlmD17NgYPHoxGjRph+PDh9S5KKf0a4+XLl2P58uUAgJCQECQmJmL69Om48847Ff2ZXnnlFbz00ksYN24cJElCv3798PTTTyvalojq56/nUK7Q4hyKiLzDH8+h9Ho9Fi1ahFmzZmHYsGGIiIjAvffei/vuu8/hdfLy8tC5c2eEhYVddn9btmzBli1bAFgXxa644go89NBD9vOyTz/9FJWVlbjnnnvqbHf33XfjpZdeQnp6Ov7973/jjTfewPnz53H99ddj1qxZiseEvEOSZVn2dQgiIiIiIiIiIgou/PgeERERERERERFpjotSRERERERERESkOS5KERERERERERGR5rgoRUREREREREREmuOiFBERERERERERaY6LUkREREREREREpDkuShERERERERERkea4KEVERERERERERJrjohQREREREREREWmOi1JERERERERERKQ5LkoREREREREREZHmuChFRERERERERESa46IUERERERERERFpjotSRERERERERESkOS5KERERERERERGR5rgoRUREREREREREmjNotSOLxQKTyQSdTgdJkrTaLRH5AVmWYbFYYDAYoNP5Zq2cHUVEDfF1R7GfiKgh7CciEpXSftJsUcpkMmHfvn1a7Y6I/FD37t0RGhrqk32zo4jIGV91FPuJiJxhPxGRqJz1k2aLUraVsf4D+sMoV6l6DUmS0CwiBueMpZBl2eXtZaMZkAFIgBShZwZmYAZBMkRIYdiyeYvPrpIC3O8od8cAcP9YMAMzMIN3Mvi6o9hPzMAMzNAQf+8nIDDOZZmBGZjBkdJ+0mxRynY5p1Gugn5ogqrXiAyJQNboJRi4ciwqaowub39hxRHIF02QGhkQPbQDMzADMwiSwbi2AMCfPeEL7naUu2MAuH8smIEZmME7GXzdUewnZmAGZmiIv/cTEBjnsszADMzgSGk/8UbnRERERERERESkOS5KERERERERERGR5rgoRUREREREREREmuOiFBG5JaV1Mgal34bY2FgMSr8NKa2TfR2JiAgA+4mIxMV+IiKRadlRmt3onIgCR3hIGAb3GIBxfUcjtU0X++OL7psDANhz8mcszl2JrF2bUVmj7ptYiIjUYD8RkajYT0QkMl91FK+UIiKXtI9vh++mbcKCUS+iW6ukep/TrVUSFox6Ed9N24Sr4hI1TkhEwYr9RESiYj8Rkch82VFclCIixdrHt8MXkz9AQkwLSJIEvU5f7/P0Oj0kSUJCTAt8+eQanlgRkdexn4hIVOwnIhKZrztK9aJUdXU17rzzTuzcudMjQYhIbOEhYVj/6FJEhTWC4f+zd+/xTdX3/8BfJ0mbXmgt2MIo1ylQK1BacahzfutwiuB0rCg4ROcU6kRgl69u6JyX6UBlF3+CsCF4G6IwKKgT1Cna73TKHFIKSpGLlEsRWmltS9M0l/P745jSkpacnCQn7ySv5+Phg63k5Lw8n/N5mfPpSWLV985fm9WGDHs61s9ajpQke4QTnsR+Ikos7Ccikor9RESSSegoQ4tSTqcTv/zlL7F79+6QAxBRbJg0egIG9MrVXVY+NqsNA8/sh5LzxkcoWWfsJ6LEw34iIqnYT0QkmYSOCnpRas+ePZg8eTIOHDgQ8s6JKHaUFk+DV/Ua2tbj9aC0eFqYE/ljPxElJvYTEUnFfiIiySR0VNCLUv/5z39wwQUXYNWqVSHvnIhiQ0H/fIwacG637y8OxGqxonDg8Ih/3TH7iSjxsJ+ISCr2ExFJJqWjgrtHC8DUqVND2qGiKEhLSjW0bWpSSqc/g9WkKFCZgRmYIegMI3K7/gaGYA3PHYY9R/f7/bxZUcLy/KH2E2B8LEIdByD084EZmCERM0S6n4DwdBT7iRmYIfEysJ/0SZTX08zADNIySLnGU1RVVY3uPC8vD88//zwuuOCCgI/1eDyoqKjApEmTsHbtWqO7DMmECRNw7Ngx9O7dGxs2bGAGZmAGnRmys7MxaFDo365QXV2Nuro6v5/7eqGwsBBWq7GV+lMF008AO4oZmCFWM0S6n4DwdxT7iRmYITEysJ/MEQvnAjMwg8QMUq7xgr5TKlTHHQ24esUMQ9umJqVg9ZSFmLxqNhyu1qC3r2upb/+TGZiBGfRnmFg0Dotvmm8oX0ePlC/By1vf9Pt5s6Mh5OcOF6MdFeo4AKGfD8zADImYIdL9BMjpKPYTMzBDbGVgP+mTKK+nmYEZpGWQco1n+qKUqqpocTlCeg6Hq9XQc/huCmMGZmCG4DLsqNkVUrb25zm8q8t9hHDDZtiFOhZGx8G3b2ZgBmYILkOk+6ljhmiTPA7MwAzMwH6S/FqWGZiBGfxJucYL+oPOiSjxVB7aiW0HP4XH6zG0vcfrQcWBT7D9cFWYkxFRomM/EZFU7CcikkxKR3FRioh0WVq+AhbFWGVYLVYsLV8R5kRERBr2ExFJxX4iIskkdBQXpYhIl7VbNuDg8Rq4Pe6gtnN73Djw5WGUfbwxQsmIKNGxn4hIKvYTEUkmoaNCWpTatWuX7m9mIKLY1upy4odPTkeT84Tu0nJ73GhynsDERbei1eWMcMLO2E9EiYP9RERSsZ+ISDIJHcU7pYhIt73H9uOyBVNQ03AUALp9/7Hv5zUNR3HZginYV1ttWkYiSkzsJyKSiv1ERJJFu6NM//Y9Iopt+2qrMebhq1By3niUFk9D4cDhfo/ZfqgKS8tXoOzjjab/ho+IEhf7iYikYj8RkWTR7CguShFR0FpdTqzcvB4rN69HQf98DM8dhrnFt+OR8iX4pOYzVB7aGe2IRJSg2E9EJBX7iYgki1ZHcVGKiEJSeWgn9hzdj+nDr8PLW99Ei8sR7UhERADYT0QkF/uJiCQzs6P4mVJERERERERERGQ6LkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZTlFVVTVjRx6PBxUVFSi+tBgtqrGvD1QUBdlpPVHXUg8jsdUWN6ACUAAlzdhnvDMDMzBD+DOkKXaUv1uOwsJCWK1WQxlCFWpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ/O/fU8F1BNuo5viWPMxZmAGZoi3DOl249uGm8HjELZxYAZmYAZ5GaR0VKKPAzMwAzP4i/F++nrT2H8tywzMwAz+dPaT+YtSCqCkJ+5qITMwAzN09QSGdhsZBjsqXn7jygzMwAxdPYmxzcKO/cQMzMAMfk9ibLOw4zUeMzADM/g9gb6Hmb4opaRakTl5iKFt05JS8eq0p3D1ihlocTmC3r7x2T1QT7ihpNmQeTMzMAMzSMngWV1jaL+RYLSjQj0GQOhjwQzMwAyRySClo9hPzMAMzHCqWO8nID5eyzIDMzCDP739xA86JyIiIiIiIiIi03FRioiIiIiIiIiITMdFKSIiIiIiIiIiMh0XpSgmeWpb4ag6jrKyMjiqjsNT2xrtSFFR0D8fE4vGITs7GxOLxqGgf360IxElPPaThv1EJA/7ScN+IpKJHaVJtI4y/9v3iAxS3V64djfCWVkPb50TADDv9Xntf2/JtsNe0BNJQzOh2OJ3vTUlyY5JoyegtHgaRg04t/3ni2+aDwDYdvBTLC1fgbVbNqDV5YxWTKKEwn7SsJ+I5GE/adhPRDKxozSJ3FFclKKY4Glow4lXDkBtcnf7GG+dE45NX6D1ozqkXzMQ1qxkExOa4+zeg7HujmUY0CsXXtXb5WNG9MvDoht+j1+PvwMTF92KfbXVJqckSizsJw37iUge9pOG/UQkEztKk+gdFdRS49GjRzFnzhyMGTMGl1xyCebPnw+nM75W6UgeT0Mbmtfsh9rcfVl1pDa70bxmPzwNbRFOZq6zew/GW3e+hNysPlAUBVaLtcvHWS1WKIqC3Kw+ePuuVTgrZ5DJSaOHHUVmYz9p2E+BsZ/IbOwnDfspMPYTRQM7SsOOCmJRSlVVzJkzBw6HAy+88AL+/Oc/45133sHjjz8ewXiU6FS3FydeOQC0eQFV70YA2rTtVHfXK82xJiXJjnV3LEOGPR02q74bHG1WGzLs6Vg/azlSkuwRThh97CgyG/tJw34KjP1EZmM/adhPgbGfKBrYURp2lEb3otS+fftQUVGB+fPnY+jQoTj//PMxZ84c/OMf/4hkPkpwrt2N2u2cesvKRwXUJjdcuxsjkstsk0ZPwIBeubrLysdmtWHgmf1Qct74CCWTgx1FZmM/adhPgbGfyGzsJw37KTD2E0UDO0rDjtLoXpTKycnBsmXLkJ2d3ennzc3NYQ9F5OOsrI/q9lKUFk/r9v3FgXi8HpQWTwtzInnYUWQ29pOG/RQY+4nMxn7SsJ8CYz9RNLCjNOwoje5FqczMTFxyySXt/9/r9WLFihW48MILIxKMyFPb2v4NDEZ565wx/1WiBf3zMWrAud2+vzgQq8WKwoHD4/6rRNlRZCb2k4b9pA/7iczEftKwn/RhP5HZ2FEadtRJhr99b8GCBfj000+xZs2aoLZTFAVpSamG9pmalNLpz2A1KQpUZoiZDI5Gh6HnPpWtCUjN9d9HrByHEbl5hp77VMNzh2HP0f2GMgQS6nFoVhRD252O2R0V6jEAQh8LZjAvQ6T7SU+GQMw4DpHuJz0ZAgnHcQh3R7GfmIH9xH4C2E8+iXJtwwwaXuNpeI13kqKqarDv5MSCBQvwzDPP4M9//jPGjRunaxuPx4OKigpMmjQJa9euDXaXYTFhwgQcO3YMvXv3xoYNG5hBeIaysjLMmzcv5H3dc889KCkpMZQh0vRkyM7OxqBBoX+7QnV1Nerq6gxliDRfLxQWFsJqNfbbgo7YUcwQ6QyR7ic9GcwQKEOk+0lPBjOEs6PYT8wQ6QzsJw37KXjsJ2YwIwOv8TS8xjsp6DulHnroIbz44otYsGCB7rLq6LijAVevmBH0doC2Qrd6ykJMXjUbDlfwt+vVtdS3/8kM8jM4qo4bynaqxVtX4pmWjYYyBGLGcZhYNA6Lb5pvKF9Hj5Qvwctb3zSUIZBQj0Ozo8HQfrsSrY4K9RgAoY8FM5iXIdL9pCdDIGYch0j3k54MgYTjOISro9hPzMB+0rCfNOwnTaJc2zCDhtd4Gl7jnRTUotSiRYvw0ksv4U9/+hOuvPLKoEMB2teOtrhCu2XP4Wo19By+m8KYITYyeDLDczuyOwNd7iNWjsOOml0hZWt/nsO7xB+HUEnoKKPHwLdvZoiNDJHuJz0Z9IrkcYh0P+nJoFc4jkMo2E/MYFYG9pOG/aSfhH4C4v/ahhk0vMbT8BrvJN0fdL53714sXrwYM2bMwOjRo1FbW9v+D1EkWHNSYMm2h/Qclmw7rDnG36cvQeWhndh28FN4vB5D23u8HlQc+ATbD1eFOZks7CgyE/tJw37Sh/1EZmI/adhP+rCfyGzsKA076iTdi1Jvv/02PB4PlixZgu985zud/iGKFHtBz6huL8XS8hWwKLqnaydWixVLy1eEOZE87CgyG/tJw34KjP1EZmM/adhPgbGfKBrYURp2lEb32/dKS0tRWloaySxEfpKGZqL1ozqozW4gmLuTFUDpYUPS0MyIZTPT2i0b8OvxdyA3qw9sVv3vunV73KhpOIqyj7v+TIh4wo4is7GfNOynwNhPZDb2k4b9FBj7iaKBHaVhR2mMLcsRmUSxWZB+zUAg2QLoffuxAiBZ206xxccp3upy4odPTkeT8wTcHreubdweN5qcJzBx0a1odTkjnJAo8bCfNOwnInnYTxr2E5FM7CgNO0oTH6NJcc2alYwe1w6G0kPf6rHSw4Ye1w6GNSs5wsnMtffYfly2YApqGo4CQLfvP/b9vKbhKC5bMAX7aqtNy0iUaNhPGvYTkTzsJw37iUgmdpSGHRXkt+8RRYs1KxkZU8+Ca3cjnJX18Nb5rwpbsu2wF/RE0tDMuFk9P9W+2mqMefgqlJw3HqXF01A4cLjfY7YfqsLS8hUo+3hj3KyeE0nGftKwn4jkYT9p2E9EMrGjNIneUVyUopih2CxIzs9Ccn4WPLWtsDUBM4umYvHWlXBnIOa/gUGvVpcTKzevx8rN61HQPx/Dc4dhbvHteKR8CT6p+QyVh3ZGOyJRwmE/adhPRPKwnzTsJyKZ2FGaRO6o+FxqpLhnzUlBal5PlJSUIDWvZ8KU1akqD+3Ey1vfRF1dHV7e+mZclxVRrGA/adhPRPKwnzTsJyKZ2FGaROsoLkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZTlFVVTVjRx6PBxUVFSi+tBgtqrFPi1cUBdlpPVHXUg8jsdUWN6ACUAAlzdhnvDMDMzBD+DOkKXaUv1uOwsJCWK1WQxlCFWpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ/O/fU8F1BNuo5viWPMxZmAGZoi3DOl249uGm8HjELZxYAZmYAZ5GaR0VKKPAzMwAzP4i/F++nrT2H8tywzMwAz+dPaT+YtSCqCkJ+5qITMwAzN09QSGdhsZBjsqXn7jygzMwAxdPYmxzcKO/cQMzMAMfk9ibLOw4zUeMzADM/g9gb6Hmb4opaRakTl5iKFt05JS8eq0p3D1ihlocTmC3r7x2T1QT7ihpNmQeTMzMAMzSMngWV1jaL+RYLSjQj0GQOhjwQzMwAyRySClo9hPzMAMzHCqWO8nID5eyzIDMzCDP739xA86JyIiIiIiIiIi03FRioiIiIiIiIiITMdFKSIiIiIiIiIiMh0XpShoBf3zMbFoHLKzszGxaBwK+ucnZAZPbSscVcdRVlYGR9VxeGpbTc8g4TgQSSJhTkjIwH4ikkfCnJCQgf1EJJOEeSEhAzvKfOZ/+x7FpJQkOyaNnoDS4mkYNeDc9p8vvmk+AGDbwU+xtHwF1m7ZgFaXM24zqG4vXLsb4aysh7dO28e81+e1/70l2w57QU8kDc2EYovMmq+E40AkiYQ5ISED+4lIHglzQkIG9hORTBLmhYQM7Kjo4qIUBXR278FYd8cyDOiVC6/q7fIxI/rlYdENv8evx9+BiYtuxb7a6rjL4Glow4lXDkBtcnf7GG+dE45NX6D1ozqkXzMQ1qzksGaQcByIJJEwJyRkYD8RySNhTkjIwH4ikknCvJCQgR0VfUEv81VXV+PWW29FUVERLr30UixbtiwSuUiIs3sPxlt3voTcrD5QFAVWi7XLx1ktViiKgtysPnj7rlU4K2dQXGXwNLShec1+qM3dl1VHarMbzWv2w9PQFrYMEo6DdOynxCJhTkjIwH6KDeynxCJhTkjIwH6KDeynxCNhXkjIwI6SIahFKa/Xi9LSUvTs2RPr1q3Dgw8+iCVLluDVV1+NVD6KopQkO9bdsQwZ9nTYrPpuqrNZbciwp2P9rOVISbLHRQbV7cWJVw4AbV5A1bsRgDZtO9Xd9Wp3MCQcB+nYT4lFwpyQkIH9FBvYT4lFwpyQkIH9FBvYT4lHwryQkIEdJUdQi1J1dXXIz8/HAw88gMGDB6O4uBgXXXQRtmzZEql8FEWTRk/AgF65uieIj81qw8Az+6HkvPFxkcG1u1G7nVNvWfmogNrkhmt3Y8gZJBwH6dhPiUXCnJCQgf0UG9hPiUXCnJCQgf0UG9hPiUfCvJCQgR0lR1CLUr1798bjjz+OHj16QFVVbNmyBR999BHGjBkTqXwURaXF07p9T2sgHq8HpcXT4iKDs7I+qtsDMo6DdOynxCJhTkjIwH6KDeynxCJhTkjIwH6KDeynxCNhXkjIwI6Sw/BHx48dOxZTp05FUVERxo0bF85MJEBB/3yMGnBut+9pDcRqsaJw4PCQvr5SQgZPbWv7NzAY5a1zhvRVohKOQ6xhP8U3CXNCQgb2U2xiP8U3CXNCQgb2U2xiP8U/CfNCQgZ2lCyGv33viSeeQF1dHR544AHMnz8f9957r67tFEVBWlKqoX2mJqV0+jNYTYoClRl0ZRiRm2fouU81PHcY9hzdH7MZHI2OsGSwNQGpuf77iJXjEEio52SzohjarjtG+wkwfhxCPQZA6GORKBkiPSdiJUOk+0lPBgnHIZBwnJPh7Cj2U3xnkDAnJGRgP+nDftIkyvWVhAwSriskZOA1nj5mXeMpqqoG+y7KTl5//XXceeed+Pjjj5Gc3P1XI3o8HlRUVGDSpElYu3ZtKLs0bMKECTh27Bh69+6NDRs2MMNpMmRnZ2PQoNA/0b+6uhp1dXUxm6GsrAzz5s0LOcM999yDkpISQxkkHIdI8/VCYWEhrFZjvy3oit5+AthRsZQh0nMiVjJEup/0ZJBwHMwQiY5iP8VnBglzQkIG9pN52E8yxiFWMki4rpCQgdd45tDbT0HdKVVXV4eKigp873vfa//ZkCFD4HK50NzcjF69egV8juOOBly9YkYwu22XmpSC1VMWYvKq2XC4gr9Vrq6lvv1PZjh9holF47D4pvmG8nX0SPkSvLz1zZjN4Kg6HvL+AWDx1pV4pmWjoQwSjkMgoZ6TzY4GQ/vtKBz9BBjvqFCPARD6WCRKhkjPiVjJEOl+0pNBwnEIJBznZKgdxX5KnAwS5oSEDOwnfdhPmkS5vpKQQcJ1hYQMvMbTx6xrvKAWpQ4dOoRZs2ahvLwcffr0AQDs2LEDvXr10l1YqqqixRXa7XIOV6uh5/DdFMYMgTPsqNkVUrb25zm8q8t9xEoGT2Z4bol2ZyCmj4NeoZ6ToQhHP/myhHIcjB4D376ZIXCGSM+JWMkQ6X7Sk0HCcdArHOekUeynxMkgYU5IyMB+Cg77SRPv11cSMki4rpCQgdd4wYn0NV5QH3Q+cuRIDB8+HPfccw/27NmD8vJyLFiwAD/96U+DDkiyVR7aiW0HP4XH6zG0vcfrQcWBT7D9cFVMZ7DmpMCSbTe8PQBYsu2w5hj/rAAJxyEWsJ8Sh4Q5ISED+yl2sJ8Sh4Q5ISED+yl2sJ8Si4R5ISEDO0qWoBalrFYrFi9ejNTUVEyZMgW/+c1vcOONN+Kmm26KVD6KoqXlK2BRjH1Bo9VixdLyFXGRwV7QM6rbAzKOg3Tsp8QiYU5IyMB+ig3sp8QiYU5IyMB+ig3sp8QjYV5IyMCOkiPoI9CnTx8sWrQIW7ZswXvvvYef/vSnUML8zVkkw9otG3DweA3cHndQ27k9bhz48jDKPu76MwBiLUPS0EwoGTYg2NNcAZQMG5KGZoacQcJxiAXsp8QhYU5IyMB+ih3sp8QhYU5IyMB+ih3sp8QiYV5IyMCOksPYshwlhFaXEz98cjqanCd0TxS3x40m5wlMXHQrWl3OuMig2CxIv2YgkGzRX1oKgGRtO8UW+jSTcByIJJEwJyRkYD8RySNhTkjIwH4ikknCvJCQgR0lBxel6LT2HtuPyxZMQU3DUQDo9j2vvp/XNBzFZQumYF9tdVxlsGYlo8e1g6H00PfdAEoPG3pcOxjWrNN/jW4wJBwHIkkkzAkJGdhPRPJImBMSMrCfiGSSMC8kZGBHyRDUt+9RYtpXW40xD1+FkvPGo7R4GgoHDvd7zPZDVVhavgJlH2+MyIqthAzWrGRkTD0Lrt2NcFbWw1vnvw9Lth32gp7a7aBhWD0/lYTjQCSJhDkhIQP7iUgeCXNCQgb2E5FMEuaFhAzsqOjjohTp0upyYuXm9Vi5eT0K+udjeO4wzC2+HY+UL8EnNZ+h8tDOhMig2CxIzs9Ccn4WPLWtsDUBM4umYvHWlXBnIKRvYNBLwnEgkkTCnJCQgf1EJI+EOSEhA/uJSCYJ80JCBnZUdHFRioJWeWgn9hzdj+nDr8PLW99Ei8uRkBmsOSlIzU1FSUkJnmnZmLDHgUgSCXNCQgb2E5E8EuaEhAzsJyKZJMwLCRnYUebjZ0oREREREREREZHpuChFRERERERERESm46IUERERERERERGZTlFVVTVjRx6PBxUVFSi+tBgtqrFPi1cUBdlpPVHXUg8jsdUWN6ACUAAlzdjHaTEDMzBD+DOkKXaUv1uOwsJCWK1WQxlCFWpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ/M/6FwF1BNuo5viWPMxZmAGZoi3DOl249uGm8HjELZxYAZmYAZ5GaR0VKKPAzMwAzP4i/F++nrT2H8tywzMwAz+dPaT+YtSCqCkJ+5qITMwAzN09QSGdhsZBjsqXn7jygzMwAxdPYmxzcKO/cQMzMAMfk9ibLOw4zUeMzADM/g9gb6Hmb4opaRakTl5iKFt05JS8eq0p3D1ihmGvhax8dk9UE+4oaTZkHkzMzADM0jJ4FldY2i/kWC0o0I9BkDoY8EMzMAMkckgpaPYT8zADMxwqljvJyA+XssyAzMwgz+9/cQPOiciIiIiIiIiItNxUYqIiIiIiIiIiEzHRSkiIiIiIiIiIjKd+R90bpCnthWORgfKysrgqDoOT6YCa04KM0QhQ0H/fIzIzUN2djYmFo3DjppdqDy0kxmikEHC+UAyxoEZNBLmpYQMEsZCQgaSMQ7MoJHQDRIycCyoIwnnAzNoJMwLCRk4FuYTvSilur1w7W6Es7Ie3jonAGDe6/Pa/96SbYe9oCeShmZCsUXmpi9m0KQk2TFp9ASUFk/DqAHntv988U3zAQDbDn6KpeUrsHbLBrS6nMwQwQwSzgeSMQ7MoJEwLyVkkDAWEjKQjHFgBo2EbpCQgWNBHUk4H5hBI2FeSMjAsYgusYtSnoY2nHjlANQmd7eP8dY54dj0BVo/qkP6NQNhzUpmhghkOLv3YKy7YxkG9MqFV/V2+ZgR/fKw6Ibf49fj78DERbdiX201M0Qgg4TzgWSMAzNoJMxLCRkkjIWEDCRjHJhBI6EbJGTgWFBHEs4HZtBImBcSMnAsos/wMl9paSnmzp0bziztPA1taF6zH2pz9ydGR2qzG81r9sPT0MYMYc5wdu/BeOvOl5Cb1QeKosBqsXb5OKvFCkVRkJvVB2/ftQpn5QxihjBnkHA+xJJIdZSEcWAGjYR5KSGDhLGQkCGWsJ/iP4OEbpCQgWMRe3iNlxgZJMwLCRk4FjIYWpR67bXXUF5eHu4sALRb5068cgBo8wKq3o0AtGnbqe6uVxaZIXgpSXasu2MZMuzpsFn13VRns9qQYU/H+lnLkZJkZ4YwZZBwPsSSSHWUhHFgBo2EeSkhg4SxkJAhlrCf4j+DhG6QkIFjEXt4jZcYGSTMCwkZOBZyBL0o1dDQgMceewwjR46MRB64djdqt87pPTF8VEBtcsO1u5EZwpRh0ugJGNArV/cE8bFZbRh4Zj+UnDeeGcKUQcL5ECuA/LOpAAEAAElEQVQi2VESxoEZNBLmpYQMEsZCQoZYwX5KjAwSukFCBo5FbOE1XuJkkDAvJGTgWMgR9KLUo48+ih/84AcYMmRIJPLAWVkf1e2Z4aTS4mndvqc1EI/Xg9LiacwQpgwSzodYEcmOkjAOzKCRMC8lZJAwFhIyxAr2U2JkkNANEjJwLGILr/ESJ4OEeSEhA8dCjqAWpT744AP897//xcyZMyMSxlPb2v5p90Z565zw1LYyQ4gZCvrnY9SAc7t9T2sgVosVhQOHo6B/PjOEmEHC+RArItlREsaBGTQS5qWEDBLGQkKGWMF+SowMErpBQgaORWzhNV7iZJAwLyRk4FjIovs+MafTifvvvx/33XcfUlJSDO9QURSkJaV2+XeORofh5+3I1gSk5vrvo0lRoDKDrgwjcvPCkmF47jDsObqfGULIIOF8CCQ1KaXTn8FqVhRD23UU6Y6K9DgAgceCGTSRnpexkkHCWEjIEEio/QSE3lHsp8TJIKEbJGTgWOiTCP0EyHgtywwaCdc2EjJwLPQx6xpP96LUokWLMGLECFxyySWGAvn0Ss3C2mlPdfl3ZWVlmPf6vJCeHwBmFk1FSUmJ388nrJyAY83HkJ3WE68yw2kzZGdnh7x/AJhbfDumD7+OGULIIOF80Gv1lIWGtpu0blJI+wUi31GRHgcg8FgwgybS8zJWMkgYCwkZ9DLaT0DoHcV+SpwMErpBQgaORXDiuZ8AGa9lmUEj4dpGQgaORXAifY2nqKqq66O9xo4di7q6Olit2u1lbW3a1yAmJydj69atAbf3eDyoqKjAdydchh5Tz+ryMY6q42h4vVpX8NPJGj8YqXk9/X5+dNkOeJtdsPRIQp/pI5jhNBkmFo3D4pvmh5zh9ufn4uWtbzJDCBkknA+BpCalYPWUhZi8ajYcruBvY21euQ/vbHgbhYWF7R0TrEh3VKTHAQg8FsygifS8jJUMEsZCQoZAQu0nIPSOYj8lTgYJ3SAhA8dCn0ToJ0DGa1lm0Ei4tpGQgWOhj1nXeLrvlPrb3/4Gt9vd/v//8Ic/AADuvPPOoIKpqooWV9e3y3kyQ38LDwC4M9DlPnzrb8wQOMOOml1hybDj8C5mCDGDhPNBL4er1dBz6FwbP61Id1Skx8G3b2YInCHS8zJWMkgYCwkZ9DLaTx0zGMV+SpwMErpBQgaORXDiuZ8AGa9lmUEj4dpGQgaORXAifY2n+4PO+/Xrh0GDBrX/k56ejvT0dAwaNCjocN2x5qTAkm0P6Tks2XZYc4y/H5oZNJWHdmLbwU/h8XoMbe/xelBx4BNsP1zFDCFmkHA+xIJId5SEcWAGjYR5KSGDhLGQkCEWsJ8SJ4OEbpCQgWMRO3iNl1gZJMwLCRk4FrIE9e17ZrAXdH2LrlnbM8NJS8tXwKIYO0WsFiuWlq9ghjBlkHA+kIxxYAaNhHkpIYOEsZCQgWSMAzNoJHSDhAwcC+pIwvnADBoJ80JCBo6FHIYXpR555BE88sgj4cwCAEgamgklwwYEe0edAigZNiQNzWSGMGVYu2UDDh6vgdvjDvzgDtweNw58eRhlH29khjBlkHA+xJpIdJSEcWAGjYR5KSGDhLGQkCHWsJ/iO4OEbpCQgWMRm3iNF/8ZJMwLCRk4FnKIu1NKsVmQfs1AINmi/wRRACRr2ym20P+VmEHT6nLih09OR5PzhO6J4va40eQ8gYmLbkWry8kMYcog4XwgGePADBoJ81JCBgljISEDyRgHZtBI6AYJGTgW1JGE84EZNBLmhYQMHAs5RL4StGYlo8e1g6H00Pc57EoPG3pcOxjWrGRmCHOGvcf247IFU1DTcBQAun3Pq+/nNQ1HcdmCKdhXG/q3GTBDZxLOB5IxDsygkTAvJWSQMBYSMpCMcWAGjYRukJCBY0EdSTgfmEEjYV5IyMCxkEH3t++ZzZqVjIypZ8G1uxHOynp46/xXAS3ZdtgLemq33kXgN63MoNlXW40xD1+FkvPGo7R4GgoHDvd7zPZDVVhavgJlH2+MyIotM2gknA8kYxyYQSNhXkrIIGEsJGQgGePADBoJ3SAhA8eCOpJwPjCDRsK8kJCBYxF9YhelAO2WuuT8LCTnZ8FT2wpbEzCzaCoWb10JdwZM+bYeZtC0upxYuXk9Vm5ej4L++RieOwxzi2/HI+VL8EnNZ6g8tJMZTMog4XwgGePADBoJ81JCBgljISEDyRgHZtBI6AYJGTgW1JGE84EZNBLmhYQMHIvoiplfU1pzUpCa1xMlJSVIzesZlRe2zKCpPLQTL299E3V1dXh565tRmSDMoJFwPpCMcWAGjYR5KSGDhLGQkIFkjAMzaCR0g4QMHAvqSML5wAwaCfNCQgaOhfliZlGKiIiIiIiIiIjiBxeliIiIiIiIiIjIdFyUIiIiIiIiIiIi0ymqqqpm7Mjj8aCiogLFlxajRTX2afGKoiA7rSfqWuphJLba4gZUAAqgpBn7jHdmYAZmCH+GNMWO8nfLUVhYCKvVaihDqELtqFCPARD6WDADMzBDZDJEu6PYT8zADMzQnVjvJyA+XssyAzMwgz+9/WT+t++pgHrCbXRTHGs+xgzMwAzxliHdbnzbcDN4HMI2DszADMwgL4OUjkr0cWAGZmAGfzHeT19vGvuvZZmBGZjBn85+Mn9RSgGU9MRdLWQGZmCGrp7A0G4jw2BHxctvXJmBGZihqycxtlnYsZ+YgRmYwe9JjG0WdrzGYwZmYAa/J9D3MNMXpZRUKzInDzG0bVpSKl6d9hSuXjEDLS5H0Ns3PrsH6gk3lDQbMm9mBmZgBikZPKtrDO03Eox2VKjHAAh9LJiBGZghMhmkdBT7iRmYgRlOFev9BMTHa1lmYAZm8Ke3n/hB50REREREREREZDouShERERERERERkem4KEVERERERERERKYz/4POKSSe2lY4Gh0oKyuDo+o4PJkKrDkpCZehoH8+RuTmITs7GxOLxmFHzS5UHtqZcBkkjIWEDCSDhHNBQgZ2AzOQPBLOBQkZ2E8aHgeSRsL5ICED56Ym0Y4DF6VigOr2wrW7Ec7KenjrnACAea/Pa/97S7Yd9oKeSBqaCcUWmZvfJGRISbJj0ugJKC2ehlEDzm3/+eKb5gMAth38FEvLV2Dtlg1odTnjNoOEsZCQgWSQcC5IyMBuYAaSR8K5ICED+0nD40DSSDgfJGTg3NQk8nHgopRwnoY2nHjlANQmd7eP8dY54dj0BVo/qkP6NQNhzUqOuwxn9x6MdXcsw4BeufCq3i4fM6JfHhbd8Hv8evwdmLjoVuyrrY67DBLGQkIGkkHCuSAhA7uBGUgeCeeChAzsJw2PA0kj4XyQkIFzU5PoxyHo5a1//vOfyMvL6/TPnDlzwhKGOvM0tKF5zX6ozd2fGB2pzW40r9kPT0NbXGU4u/dgvHXnS8jN6gNFUWC1WLt8nNVihaIoyM3qg7fvWoWzcgbFVQYJYyEhw+mwn8wj4VyQkIHdwAx6sZ/MI+FckJCB/aThcQiM/WQuCeeDhAycmxoeBwOLUnv27MF3v/tdvPfee+3/PPzww2EJQyepbi9OvHIAaPMCqt6NALRp26nurldYYy1DSpId6+5Yhgx7OmxWfTf22aw2ZNjTsX7WcqQk2eMig4SxkJAhEPaTOSScCxIysBuYIRjsJ3NIOBckZGA/aXgc9GE/mUfC+SAhA+emhsdBE/Si1N69ezFs2DDk5OS0/5OZmRlyEOrMtbtRu3VO74nhowJqkxuu3Y1xkWHS6AkY0CtX9yT1sVltGHhmP5ScNz4uMkgYCwkZAmE/mUPCuSAhA7uBGYLBfjKHhHNBQgb2k4bHQR/2k3kknA8SMnBuangcNIYWpQYPHhzyjun0nJX1Ud1eSobS4mndvq82EI/Xg9LiaXGRQcJYSMgQCPvJHBLOBQkZ2A3MEAz2kzkknAsSMrCfNDwO+rCfzCPhfJCQgXNTw+OgCWpRSlVVfP7553jvvfcwbtw4fO9738Mf/vAHtLWZ837nROGpbW3/tHujvHVOeGpbYzpDQf98jBpwbrfvqw3EarGicOBwFPTPj+kMEsZCQoZA2E/mkHAuSMjAbmCGYLCfzCHhXJCQgf2k4XHQh/1kHgnng4QMnJsaHoeTgrpPrKamBg6HA8nJyXj88cdx6NAhPPzww2htbcW9996r6zkURUFaUqqhsKlJKZ3+DFaTokCNgQyORoeh5z6VrQlIzfXfR6xkGJGbF5YMw3OHYc/R/TGbQcJYRDpDs6KE/Nzh6CfAeD+E2g1A6B1lRoZInwuxkiHS3aAng4TjkCgZQu0o9hP7ycwM7CdNohyHWO8ngNd4wZL8mp7XV/ozJMJx0NtPiqqqQb17sKGhAWeccQaUr3fwxhtv4K677sLWrVthtXa/yufxeFBRUYFJkyZh7dq1wewybCZMmIBjx46hd+/e2LBhg9gMZWVlmDdvXsj7uueee1BSUhKzGbKzszFo0KCQM1RXV6Ouri5mM0gYi0hn8PVCYWHhaXskEKP9BLCj9GaI9LkQKxki3Q16Mkg4DomSIRwdxX6KfIZEOR/ZT/oyJMpxYD/FRj8BifGantdX+jMkwnHQ20/BfaIWgKysrE7//+yzz4bT6cRXX32FXr16Bdz+uKMBV6+YEexuAWgr16unLMTkVbPhcAV/i1hdS337n5IzOKqOG8p2qsVbV+KZlo0xm2Fi0Tgsvml+yBkeKV+Cl7e+GbMZJIxFpDM0OxrC8vyh9hNgvKNC7QYg9I4yI0Okz4VYyRDpbtCTQcJxSJQM4ego9hP7yawM7CdNohyHWO8ngNd4wZL8mp7XV/ozJMJx0NtPQS1K/etf/8Kdd96Jd999F6mp2u1ZO3fuRFZWlu7CUlUVLa7QbhNzuFoNPYfvpjDpGTyZob+VCQDcGehyH7GSYUfNrrBk2HF4V0xnkDAWZmUIRTj6yZcllH4w2g2+fUvPEOlzIVYyRLob9GSQcBwSLYNR7CdzMiTa+ch+4nHomMEoKf0E8BpPr1h4Tc/rKx6HjhkCCeqDzouKimC323Hvvfdi3759KC8vx2OPPYbp06cH8zQUgDUnBZZse0jPYcm2w5pj/HMbJGSoPLQT2w5+Co/XY2h7j9eDigOfYPvhqpjOIGEsJGQIhP1kDgnngoQM7AZmCAb7yRwSzgUJGdhPGh4HfdhP5pFwPkjIwLmp4XHo8BzBPLhHjx5Yvnw5jh8/jkmTJuE3v/kNpkyZwtKKAHtBz6huLyXD0vIVsChBnabtrBYrlpaviIsMEsZCQobTYT+ZR8K5ICEDu4EZ9GI/mUfCuSAhA/tJw+MQGPvJXBLOBwkZODc1PA6aoI/A0KFD8cwzz2Dr1q147733MGvWrPYPxaPwSRqaCSXDBgR7aBVAybAhaWhmXGRYu2UDDh6vgdvjDmo7t8eNA18eRtnHXb//PtYySBgLCRkCYT+ZQ8K5ICEDu4EZgsF+MoeEc0FCBvaThsdBH/aTeSScDxIycG5qeBw0xpblKOIUmwXp1wwEki36TxAFQLK2nWILfWglZGh1OfHDJ6ejyXlC92R1e9xocp7AxEW3otXljIsMEsZCQgaSQcK5ICEDu4EZSB4J54KEDOwnDY8DSSPhfJCQgXNTw+OgYcsJZs1KRo9rB0Ppoe/z6JUeNvS4djCsWclxlWHvsf24bMEU1DQcBYBu33fr+3lNw1FctmAK9tVWx1UGCWMhIQPJIOFckJCB3cAMJI+Ec0FCBvaThseBpJFwPkjIwLmp4XEI8tv3yHzWrGRkTD0Lrt2NcFbWw1vnvxpqybbDXtBTu/UuAr9NkZBhX201xjx8FUrOG4/S4mkoHDjc7zHbD1VhafkKlH28MSyrxhIzSBgLCRlIBgnngoQM7AZmIHkknAsSMrCfNDwOJI2E80FCBs5NTaIfBy5KxQDFZkFyfhaS87PgqW2FrQmYWTQVi7euhDsDEf1GDkkZWl1OrNy8His3r0dB/3wMzx2GucW345HyJfik5jNUHtqZEBkkjIWEDCSDhHNBQgZ2AzOQPBLOBQkZ2E8aHgeSRsL5ICED56YmkY8Dl+BjjDUnBal5PVFSUoLUvJ5R+Y+XhAyVh3bi5a1voq6uDi9vfdOUSSoxg4SxkJCBZJBwLkjIwG5gBpJHwrkgIQP7ScPjQNJIOB8kZODc1CTaceCiFBERERERERERmY6LUkREREREREREZDouShERERERERERkekUVVVVM3bk8XhQUVGB4kuL0aIa+7R4RVGQndYTdS31MBJbbXEDKgAFUNKMfcY7MzADM4Q/Q5piR/m75SgsLITVajWUIVShdlSoxwAIfSyYgRmYITIZot1R7CdmYAZm6E6s9xMQH69lmYEZmMGf3n4y/9v3VEA94Ta6KY41H2MGZmCGeMuQbje+bbgZPA5hGwdmYAZmkJdBSkcl+jgwAzMwg78Y76evN43917LMwAzM4E9nP5m/KKUASnrirhYyAzMwQ1dPYGi3kWGwo+LlN67MwAzM0NWTGNss7NhPzMAMzOD3JMY2Czte4zEDMzCD3xPoe5jpi1JKqhWZk4cY2jYtKRWvTnsKV6+YgRaXI+jtG5/dA/WEG0qaDZk3MwMzMIOUDJ7VNYb2GwlGOyrUYwCEPhbMwAzMEJkMUjqK/cQMzMAMp4r1fgLi47UsMzADM/jT20/8oHMiIiIiIiIiIjIdF6WIQuX1RjsBERERERERUcwx/zOliGLcqNpW3LCzARfVOJBX34bkx8dgv0XBrp7J+CA3FS/kZ2FbTkq0YxIRERERERGJxkWpGOOpbYWj0YGysjI4qo7Dk6nAavICSEH/fIzIzUN2djYmFo3DjppdqDy0M+4zfLOhDYs2HcHFRxxwKUDSqELg8nOAjAwkNzVhZFUVztlWgdLtDXi/bypmje2Lz7OSI5pJwlgQ+bCfNBKOAzMQdSbhfGQ/aSQcBwkZiDqSMDeZQU6GROsoLkrFANXthWt3I5yV9fDWOQEA816f1/73lmw77AU9kTQ0E4otMu/ITEmyY9LoCSgtnoZRA85t//nim+YDALYd/BRLy1dg7ZYNaHU54y7DtZ99hSc3fQFrsh24+WYkzZkDFBX5PS5p61bgiSdwwaqX8OFLn2Pm2L5YOywzrFkkjAWRD/tJI+E4MANRZxLOR/aTRsJxkJCBqCMJc5MZ5GRI5I7iopRwnoY2nHjlANQmd7eP8dY54dj0BVo/qkP6NQNhDfPdOWf3Hox1dyzDgF658Kpdf37SiH55WHTD7/Hr8Xdg4qJbsa+2Om4yXPvZV1j6zyPA0KGwvPkmMGhQ958jVVAAPP00bPffD8vll+Opf+6BAhVrhp0RliwSxoLIh/2kkXAcmIGoMwnnI/tJI+E4SMhA1JGEuckMcjIkekcFvczX1taGBx98EN/61rfw7W9/G3/605+gqmoksiU8T0Mbmtfsh9rc/QTpSG12o3nNfnga2sKW4ezeg/HWnS8hN6sPFEWB1WLt8nFWixWKoiA3qw/evmsVzsoZFBcZzmpow5ObvtAWpD78EOjXD1AUwNp1Blit2t/36wfL5s3AkCF4ctMX+GYYxkTCWEjHfjIP+0kj4TgwQ2xgP5lHwvnIftJIOA4SMkjHfjKXhLnJDHIysKMMLEo9/PDD+Pe//43ly5fjj3/8I1avXo1Vq1ZFIltCU91enHjlANDmBfT+N0EF0KZtp7pD/0a4lCQ71t2xDBn2dNis+m6qs1ltyLCnY/2s5UhJssd8hoWbjsCSbNfukMrIAJKS9G2YlARkZMDyz3/CmmzHok1HQsoR7eMQK9hP5mA/aSQcB2aIHewnc0g4H9lPGgnHQUKGWMB+Mo+EuckMcjKwozRBLUo1NDRg7dq1eOihh1BQUICLLroIt9xyC7Zt2xapfAnLtbtRu4Uw2F9SqIDa5IZrd2PIGSaNnoABvXJ1TxAfm9WGgWf2Q8l542M6w6hjrbj4iANJU67X3rKnd0HKJykJGDwYtslTcPERB0bVthrOImEspGM/mYf9pJFwHJghNrCfzCPhfGQ/aSQcBwkZpGM/mUvC3GQGORnYUZqgFqW2bNmCHj16YMyYMe0/Ky0txfz588MeLNE5K+ujuj0AlBZP6/Y9rYF4vB6UFk+L6Qw3VDXApQCYM6f7z5AKGMIDzJ4NlwLcsLPBcBYJYyEd+8k87CeNhOPADLGB/WQeCecj+0kj4ThIyCAd+8lcEuYmM8jJwI7SBLUodfDgQfTr1w/r16/HlVdeicsuuwxPPvkkvEYv2KlLntrW9k/9N8pb54QnhDtzCvrnY9SAc7t9T2sgVosVhQOHo6B/fsxmuKjGgaRRhdq37HX3GVIBQ1iB0aORNKoQFx5xGHqKaB+HWMF+Mgf7SSPhODBD7GA/mUPC+ch+0kg4DhIyxAL2k3kkzE1mkJOBHXVSUPeJtbS0oLq6Gi+99BLmz5+P2tpa3HfffUhNTcUtt9yi6zkURUFaUqqhsKlJKZ3+DFaTokCNgQyORmOLF6eyNQGpuf770JNhRG5eWDIMzx2GPUf3x2SGvPo24PJzwpIBeXk4p3Kb335i4TjoEeq8aFYUQ9t1FI5+Aowfh1CPARD6WJiRIdL9pCdDpOeEngwSjgMz6BOOeRFqR7Gf2E/BivV+knAcJGQIhP2k4TVecEK5xmMGORl4jXdSUItSNpsNzc3N+OMf/4h+/foBAGpqavDiiy/qLq1eqVlYO+2pYHbrZ/WUhYa2m7ByAo41H0N2Wk+8KjhDWVkZ5r0+L5R4AICZRVNRUlJiKEN2dnbI+weAucW3Y/rw62Ivg9eL5MfHaB9uHg6ZmUj2qnh16l8By8kbFMUfhyAZnReT1k0Kab9AePoJCL2jjB4DIHxjEckMke4nPRkiPSf0ZJBwHJghOKHMi1A7iv1kTgYJ5yP7SSPhOEjIoBf7ScNrPH1CucZjBjkZeI13UlCLUjk5ObDb7e2FBQDf/OY3ceSI/m8WO+5owNUrZgSz23apSSlYPWUhJq+aDYcr+Fvl6lrq2/+UnMFRddxQtlMt3roSz7RsNJRhYtE4LL4p9PeSP1K+BC9vfTMmM+y3KEhuagp5/wCAxka0WRRcvfK2oDIA0T8OeoQ6L5odDYb221E4+gkw3lGhHgMg9LEwI0Ok+0lPhkjPCT0ZJBwHZtAnHPMi1I5iP7GfghXr/SThOEjIEAj7ScNrvOCEco3HDHIy8BrvpKAWpUaNGgWn04nPP/8c3/zmNwEA+/bt61RigaiqihZXaLfLOVythp5DVdWYyODJDP2tTADgzkCX+9CTYUfNrrBk2HF4V8xm2NUzGSOrqsKSAVVVqOqV7LefWDgOwQh1XoQiHP3kyxLKcTB6DHz7lp4h0v2kJ0Ok54SeDBKOAzMEJxzzwij2kzkZJJyP7CeNhOMgIYNe7CcNr/H0CeUajxnkZOA13klBfdD5WWedhUsvvRR33303qqqq8K9//QtLly7Fj370o6ADUvesOSmwZNtDeg5Lth3WHOPvT688tBPbDn4Kj9djaHuP14OKA59g+2HjizrRzvBBbipc2yqArVu1b9EzFMIDbNkCV+U2fNjX2Ht5o30cYgX7yRzsJ42E48AMsYP9ZA4J5yP7SSPhOEjIEAvYT+aRMDeZQU4GdtRJQS1KAcAf/vAHDBw4ED/60Y/w61//GjfccANuvPHGSGRLaPaCnlHdHgCWlq+ARQn6FAGgfRvA0vIVMZ3hhfwsJKkAnnii0+dABRfCCixciCRVez6jJIxFLGA/mYP9pJFwHJghdrCfzCHhfGQ/aSQcBwkZYgH7yTwS5iYzyMnAjtIEfQQyMjLw2GOPYevWrfj3v/+NWbNmQQnDN2dRZ0lDM6Fk2IBgD60CKBk2JA3NDDnD2i0bcPB4Ddwed1DbuT1uHPjyMMo+7vpzCGIlw7acFLzfNxXuVS8B1dWAyxXcE7hcwP79cK9ehff7pmJbCCvpEsYiFrCfzMF+0kg4DswQO9hP5pBwPrKfNBKOg4QMsYD9ZB4Jc5MZ5GRgR2kM3v5BkabYLEi/ZiCQbNE/URQAydp2ii30oW11OfHDJ6ejyXlC90Rxe9xocp7AxEW3otXljPkMs8b2hafNCe8VVwBNTfoXplwuoKkJ3ssvh6fNiVlj+4aUI9rHgagj9pNGwnFgBqLOJJyP7CeNhOMgIQNRRxLmJjPIycCO0vCVoGDWrGT0uHYwlB76Po9e6WFDj2sHw5qVHLYMe4/tx2ULpqCm4SgAdPueV9/PaxqO4rIFU7CvtjouMnyelYyZY/sCu3fDe8EFwOHDX++sm/f++n5++LD2+D17MHNsX3wehjGRMBZEPuwnjYTjwAxEnUk4H9lPGgnHQUIGoo4kzE1mkJOBHRXkt++R+axZyciYehZcuxvhrKyHt85/NdSSbYe9oKd2C2IEfuO8r7YaYx6+CiXnjUdp8TQUDhzu95jth6qwtHwFyj7eGJEV22hmWDssEwpUPLlpL6zn5sM2eQowezYwerT/gysqgIUL4V69Cp42J2Zenou1w8L31hQJY0Hkw37SSDgOzEDUmYTzkf2kkXAcJGQg6kjC3GQGORkSvaO4KBUDFJsFyflZSM7Pgqe2FbYmYGbRVCzeuhLuDJjyrUWtLidWbl6PlZvXo6B/PobnDsPc4tvxSPkSfFLzGSoP7YzrDGuGnYEtvVOxaNMRXPzcc3A9/xySRhUCeXlAZibQ2Ajs2gXXtgokqcCHuamY/d1vhuUOqVNJGAsiH/aTRsJxYAaiziScj+wnjYTjICEDUUcS5iYzyMmQyB3FRakYY81JQWpuKkpKSvBMy0a0uBymZ6g8tBN7ju7H9OHX4eWtbyZMhs+zknFVySCMqm3FDTsbcOGhnTinchuSvSraLAqqeiXjwxFZeCE/K6QPNQ+GhLEg8mE/aSQcB2Yg6kzC+ch+0kg4DhIyEHUkYW4yg5wMidZRXJQiCtK2nBRsy/kGACAtKRWvTv0rrl55W9yXBREREREREVE48QMdiEJl4TQiIiIiIiIiChavpomIiIiIiIiIyHSKqqqqGTvyeDyoqKhA8aXFaFGNfVq8oijITuuJupZ6GImttrgBFYACKGnG3rnIDMzADOHPkKbYUf5uOQoLC2G1Wg1lCFWoHRXqMQBCHwtmYAZmiEyGaHcU+4kZmIEZuhPr/QTEx2tZZmAGZvCnt5/M/0wpFVBPuI1uimPNx5iBGZgh3jKk241vG24Gj0PYxoEZmIEZ5GWQ0lGJPg7MwAzM4C/G++nrTWP/tSwzMAMz+NPZT+YvSimAkp64q4XMwAzM0NUTGNptZBjsqHj5jSszMAMzdPUkxjYLO/YTMzADM/g9ibHNwo7XeMzADMzg9wT6Hmb6opSSakXm5CGGtk1LSsWr057C1StmGPqms8Zn90A94YaSZkPmzczADMwgJYNndY2h/UaC0Y4K9RgAoY8FMzADM0Qmg5SOYj8xAzMww6livZ+A+HgtywzMwAz+9PYTP+iciIiIiIiIiIhMx0UpIiKieOX1RjsBEZFc7Egioqgz/zOliIiIKCJG1bbihp0NuKjGgbz6NiQ/Pgb7LQp29UzGB7mpeCE/C9tyUqIdk4goKtiRRETycFEqCAX98zEiNw/Z2dmYWDQOO2p2ofLQTlMzeGpb4Wh0oKysDI6q4/BkKrCa/B9PZiCSh/2U2Bm+2dCGRZuO4OIjDrgUYIcKrAXQBCDDq+KcL534yXEnSrc34P2+qZg1ti8+z0qOaCYiHwn9xAyJneHUjkwaVQhcfg6QkYHkpiaMrKrCOdsq2JEJKlHnhcQMifo67lQSxsJMXJQKICXJjkmjJ6C0eBpGDTi3/eeLb5oPANh28FMsLV+BtVs2oNXljEgG1e2Fa3cjnJX18NZp+5j3+rz2v7dk22Ev6ImkoZlQbJF5RyYzEMnDfmIGALj2s6/w5KYv0OZR8QyAJ1SgoovHFarAHADXHnHgw5c+x8yxfbF2WGZYsxD5SOgnZmAG4GRHWpPtwM03I2nOHKCoyO9xSVu3Ak88gQtWvcSOTACJPi8kZUj013E+EsYiWrgodRpn9x6MdXcsw4BeufCqXb/nfES/PCy64ff49fg7MHHRrdhXWx3WDJ6GNpx45QDUJne3j/HWOeHY9AVaP6pD+jUDYQ3zb3aYgUge9hMzANrF1tJ/HsFnAK4EUI3uPyyyEsAtAB4E8IZHxVP/rIECFWuGnRGWLEQ+EvqJGZgBONmRGDoUljffBAYN6v5zpAoKgKefhu3++2G5/HI89c897Mg4lejzQlKGRH8d5yNhLKKJt5N04+zeg/HWnS8hN6sPFEWB1WLt8nFWixWKoiA3qw/evmsVzsoZFLYMnoY2NK/ZD7W5+wnSkdrsRvOa/fA0tDFDmDMQScJ+YgYAOKuhDU9u+gKfAfg2gENf/7y7j+31/fwQgIsA7Abw5KYv8E12JYWRhH5iBmYATnYkhg6F5cMPgX79AEUBrF1ngNWq/X2/frBs3gwMGcKOjEOJPi8kZUj013E+EsYi2oJalCorK0NeXp7fP+ecc06k8kVFSpId6+5Yhgx7OmxWfTeT2aw2ZNjTsX7WcqQk2UPOoLq9OPHKAaDNC6h6NwLQpm2nukP/NhFmoFjCfuoe+yk+MyzcdAROj4orATQC8OjczvP148cBaPOoWLTpSEg5KDD2U/fC3U/MwAw+CzcdgSXZrt0hlZEBJCXp2zApCcjIgOWf/4Q12Z4QHcmO6l68zQspGaL9GkpKBgljIUFQi1ITJkzAe++91/7Pu+++i0GDBuGmm26KVL6omDR6Agb0ytV9YvjYrDYMPLMfSs4bH3IG1+5G7RZCvRPERwXUJjdcuxuZIUwZKDawn06P/RRfGUYda8XFRxxYC+0te3oXpHw8X2+3FsDFRxwYVdtqOAsFxn46vXD2EzMwA3CyI5OmXK+9ZU/vgpRPUhIweDBsk6ckREeyo04vXuaFpAyJ/jrOR8JYSBDUolRKSgpycnLa/3nllVegqiruvPPOSOWLitLiad2+lzMQj9eD0uJpIWdwVtZHdXtmoFjDfgqM/RQ/GW6oaoBLAZ6A8ffhW6Bt71KAG3Y2GM5CgbGfAgtXPzEDMwAnOxJz5nT/GVIBQ3iA2bMToiPZUYHFw7yQlCHRX8f5SBgLCQx/plRDQwOeeuop/O///i+Sk+PnA6UL+udj1IBzu30vZyBWixWFA4ejoH++4Qye2tb2T/03ylvnhCeE3+owA8Uy9lPX2E/xk+GiGgd2fP0te0ZvHvcC2ApghwpceMRh8FkoWOynroWjn5iBGXwuqnEgaVSh9i173X2GVMAQVmD0aCSNKkyojmRHdS0e5oWUDNF+DSUlg4SxkMLwt++9+OKL6N27N6688sqgtlMUBWlJqYb2mZqU0unPYDUpCtQAGUbk5hl67lMNzx2GPUf3G8rgaAzPf/hsTUBqrv8+mEF/hkDMOCcTIUOzohjarjtG+wkwfhxCPQZA4LGIdD/pyRDpeckM+jLk1bdhbVgSALsAlBxv6/LfM9R+MGNemJEhnB3Ffjq9UPqJGZjBJ6++Dbg8TJ+HlJeHcyq3ie1IKa+hpL+WlXCNxwwaCdd4EjJIGItAzLrGU1RVDfZdlFBVFZdddhmmT5+OqVOn6trG4/GgoqICkyZNwtq14XopHZwJEybg2LFj6N27NzZs2NDlY7KzszFoUOifZF9dXY26ujpDGcrKyjBv3ryQM9xzzz0oKSlhhhAyRBozaHy9UFhYCKvR32h+zUg/AbHRUZHuJz0ZIj0vmUFHBq8Xo8eMwVIAt4WcAPgrgFIAW/7zH8DS+QZqCf0gIUO4Oor9FFgo/cQMzACgvSMxYwawdGnIGVBaCjz1lNiOjPZrqFjoJ0DGNR4zaCRc40nIIGEsIk1vPxm6U2r79u04evQorrrqqqC3Pe5owNUrZhjZLVKTUrB6ykJMXjUbDlfwt8rVtdS3/9ldholF47D4pvmG8nX0SPkSvLz1TUMZHFXHQ94/ACzeuhLPtGxkhhAyBGLGOZkIGZodDYb225VQ+gkw3lGhHgMg8FhEup/0ZIj0vGQGfRn2WxRkeIP+nVKXMgG0WRRcvdJ/iSvUfjBjXpiRIVwdxX4KLJR+YgZm8NlvUZDc1BTy/gEAjY2iO1LKayhe4zGD3gwSrvEkZJAwFoGYdY1naFHqX//6F84//3ycccYZQW+rqipaXKHdLudwtRp6Dt9NYafLsKNmV0jZ2p/n8K4u96EngyczPLfhujPADCFm0CuS52QiZQiHUPrJlyWU42D0GPj2fboMke4nPRkiPS+ZQV+GXT2Tcc6XoX0Wgs85AKp6JUe0JyM5L8zMECr2U2Ch9BMzMIPPrp7JGFlVFZYMqKqKiY4MB17jBRbKNR4zaCRc40nIIGEs9Ir0NZ6hDzqvrKzEeeedZ2RT8SoP7cS2g5/C4w32C7Y1Hq8HFQc+wfbDxv9DaM1JgSXbbnh7ALBk22HNMf7+dGagWMV+6h77KX4yfJCbihEKUIjQvn2vCMBwBfiwr7HPGqDgsJ+6F45+YgZm8PkgNxWubRXA1q3at+gZCuEBtmyBq3JbwnQkO6p78TAvpGSI9msoKRkkjIUUhl7L7t69G0OGDAl3FjGWlq+ARTH2Mt9qsWJp+YqQM9gLekZ1e2agWMV+6h77KX4yvJCfhSQVmIPQvn1vDoAkVXs+ijz2U/fC1U/MwAzAyY7EE0/4fQ6U/hBWYOHChOpIdlT34mFeSMqQ6K/jfCSMhQSGjkBdXR0yMzPDnUWMtVs24ODxGrg97qC2c3vcOPDlYZR93PXngwQjaWgmlAwbEOydhQqgZNiQNDT08WEGikXsp66xn+Irw7acFLzfNxXXAhgEINiPtrV+vd0kAO/3TcU23lFqCvZT18LZT8zADMDJjnSvegmorgZcruCewOUC9u+He/WqhOpIdlTX4mVeSMqQ6K/jfCSMhQSG3753ySWXhDuLGK0uJ3745HQ0OU/oPkHcHjeanCcwcdGtaHWF/jkfis2C9GsGAskW/RNFAZCsbafYjL6hgxkotrGf/LGf4jPDrLF9kWxV8Dq0DyvXuzBl/frxbwBItiqYNbZvSDlIP/aTv3D3EzMwg8+ssX3haXPCe8UVQFOT/oUplwtoaoL38svhaXMmVEeyo/zF27yQkiHar6GkZJAwFhLwir0be4/tx2ULpqCm4SgAdPteT9/PaxqO4rIFU7CvtjpsGaxZyehx7WAoPfR9Hr3Sw4Ye1w6GNSuZGcKcgUgS9hMzAMDnWcmYObYvhgH4AED/r3/e3X/YfT/v//XjhwKYObYvPmdXUhhJ6CdmYAbgZEdi9254L7gAOHz465118/ktvp8fPqw9fs8edmQcSvR5ISlDor+O85EwFtFm6Nv3EsW+2mqMefgqlJw3HqXF01A4cLjfY7YfqsLS8hUo+3hjRFYqrVnJyJh6Fly7G+GsrIe3zn8flmw77AU9tVsQI3BnEDMQycN+YgYAWDssEwpUPLnpC2z3qFgL4AkAW7t47ChonyE1CdodUjPG9sXaYfH7Ng2KHgn9xAzMAHTsyL2wnpsP2+QpwOzZwOjR/g+uqAAWLoR79Sp42pyYeXkuOzJOJfq8kJQh0V/H+UgYi2jiolQArS4nVm5ej5Wb16Ogfz6G5w7D3OLb8Uj5EnxS8xkqD+2MeAbFZkFyfhaS87PgqW2FrQmYWTQVi7euhDsDpny7HDMQycN+YgYAWDPsDGzpnYpFm47g5iMO3KAAO1RgF4BGaG/VywMwQtE+1Py93FTM/i5/+0+RJaGfmIEZgM4defFzz8H1/HNIGlUI5OUBmZlAYyOwaxdc2yqQpAIf5qZi9ne/yY6Mc4k+LyRlSPTXcT4SxiJauCgVhMpDO7Hn6H5MH34dXt76JlpcDtMzWHNSkJqbipKSEjzTspEZopiBSBL2U2Jn+DwrGVeVDMKo2lbcsLMBFx5xoOR4G5K9KtosCqp6JeOZvql4IT8rYT6wl+SQ0E/MkNgZ/Dry0E6cU7mtU0d+OCKLHZmgEnVeSMyQqK/jTiVhLMzERSkiIqI4sS0nBdtyvgEASEtKxatT/4qrV94W9y9miIj0YEcSEcnDD94hIiKKVxb+Z56IqFvsSCKiqGMTExERERERERGR6RRVVVUzduTxeFBRUYHiS4vRohr7tHhFUZCd1hN1LfUwElttcQMqAAVQ0oy9c5EZmIEZwp8hTbGj/N1yFBYWwmq1GsoQqlA7KtRjAIQ+FszADMwQmQzR7ij2EzMwAzN0J9b7CYiP17LMwAzM4E9vP5n/mVIqoJ5wG90Ux5qPMQMzMEO8ZUi3G9823Aweh7CNAzMwAzPIyyCloxJ9HJiBGZjBX4z309ebxv5rWWZgBmbwp7OfzF+UUgAlPXFXC5mBGZihqycwtNvIMNhR8fIbV2ZgBmbo6kmMbRZ27CdmYAZm8HsSY5uFHa/xmIEZmMHvCfQ9zPRFKSXViszJQwxtm5aUilenPYWrV8ww9C0Zjc/ugXrCDSXNhsybmYEZmEFKBs/qGkP7jQSjHRXqMQBCHwtmYAZmiEwGKR3FfmIGZmCGU8V6PwHx8VqWGZiBGfzp7Sd+0DkREREREREREZmOi1JERERERERERD5eb7QTJAzzP1OKiIiIiIiIiEiIUbWtuGFnAy6qcSCvvg3Jj4/BfouCXT2T8UFuKl7Iz8K2nJRox4xLXJQKgqe2FY5GB8rKyuCoOg5PpgKrySemhAwS8DgQdSZhTkjIIAGPA1FnEuaEhAwS8DgQ+ZMwLyRkkCAax+GbDW1YtOkILj7igEsBdqjAWgBNADK8Ks750omfHHeidHsD3u+billj++LzrOSIZko0XJQKQHV74drdCGdlPbx1TgDAvNfntf+9JdsOe0FPJA3NhGKLzLshJWSQgMeBqDMJc0JCBgl4HIg6kzAnJGSQgMeByJ+EeSEhgwTRPA7XfvYVntz0Bdo8Kp4B8IQKVHTxuEIVmAPg2iMOfPjS55g5ti/WDssMa5ZExkWp0/A0tOHEKwegNrm7fYy3zgnHpi/Q+lEd0q8ZCGuYV00lZJCAx4GoMwlzQkIGCXgciDqTMCckZJCAx4HIn4R5ISGDBNE8Dtd+9hWW/vMIPgNwJYBqdP+B25UAbgHwIIA3PCqe+mcNFKhYM+yMsGRJdPG75BoiT0Mbmtfsh9rc/QTpSG12o3nNfnga2uIqgwQ8DkSdSZgTEjJIwONA1JmEOSEhgwQ8DkT+JMwLCRkkiOZxOKuhDU9u+gKfAfg2gENf/7y7jzb3/fwQgIsA7Abw5KYv8M04G5NoCXpR6siRI7jttttw3nnnYezYsXj22WcjECu6VLcXJ145ALR5AVXvRgDatO1Ud+if1C8hgwQ8DhQM9lN3G4H9FAE8DhQM9lN3G4H9FAE8DhSMROgnQMa8kJBBgmgfh4WbjsDpUXElgEYAHp3beb5+/DgAbR4VizYdCSkHaYJelPr5z3+OtLQ0lJWV4Z577sHjjz+Of/7zn5HIFjWu3Y3aLYR6J4iPCqhNbrh2N8ZFBgl4HCgY7KfTYD+FHY8DBYP9dBrsp7DjcaBgJEI/ATLmhYQMEkTzOIw61oqLjziwFtpb9vQuSPl4vt5uLYCLjzgwqrbVcBbSBLUo9dVXX6GiogK33347Bg8ejO9973u45JJL8MEHH0QqX1Q4K+ujur2UDBLwOJBe7CdztpeSQQIeB9KL/WTO9lIySMDjQHolSj8BMuaFhAwSRPM43FDVAJcCPAHjn2Vkgba9SwFu2NlgOAtpghqHlJQUpKamoqysDC6XC/v27cPHH3+M/Pz8SOUznae2tf1T/43y1jnhCWHFVEIGCXgcKBjsJ33YT+HB40DBYD/pw34KDx4HCkYi9BMgY15IyCBBtI/DRTUO7Pj6W/aMvgnQC2ArgB0qcOERh8FnIZ+gvn3Pbrfjvvvuw0MPPYTnn38eHo8HJSUluO6663Q/h6IoSEtKDTooAKQmpXT6M1hNigI1QAZHY3hOKlsTkJrrv49YyRBIooxFIGYch0TI0KwohrbrKBz9BBg/DqEeAyDwWER6TsRKhkASZSwCMeM4JEqGUDuK/aQf+ykwHgdm6CjW+wlInOsKCRkCSYSxyKtvw9qwJAB2ASg53ua3n1gZi0hn0NtPQS1KAcDevXvx3e9+Fz/5yU+we/duPPTQQ7joootwzTXX6Nq+V2oW1k57KtjddrJ6ykJD201YOQHHmo8hO60nXu0mQ1lZGea9Pi+UeACAmUVTUVJSErMZ9Ir3sdArkschETJMWjcppP36hNpPQOgdZfQYAIHHItJzIlYy6BXvY6FXJI9DomQIR0exn/RhPwXG48AMHcVLPwHxf10hIYNecTsWXi+SHx+DppD3rmkEkOxV8erUvwKWk29Ci5WxiHQGvf0U1KLUBx98gDVr1qC8vBwpKSkYOXIkjh49iiVLlugureOOBly9YkYwu22XmpSC1VMWYvKq2XC4gr9dr66lvv3P7jI4qo4bynaqxVtX4pmWjTGbIZBEGYtAzDgOiZCh2dFgaL8dhaOfAOMdFeoxAAKPRaTnRKxkCCRRxiIQM45DomQItaPYT/qxnwLjcWCGjmK9n4DEua6QkCGQRBiL/RYFGd5gP2G9a5kA2iwKrl55W1AZ9Eika7ygFqV27NiBQYMGISXl5O1b5557Lv7yl7/ofg5VVdHiCu2WPYer1dBzqKoaMIMnM/S3EQGAOwNd7iNWMugV72OhVySPQyJlCEU4+smXJZTjYPQY+PZ9ugyRnhOxkkGveB8LvSJ5HBItg1HsJ/3YT4HxODBDVxmMktJPQPxfV0jIoFc8j8Wunsk458vQPtPK5xwAVb2S/fYTK2NhVoZAgvqg8969e6O6uhptbW3tP9u3bx/69+8fXDrBrDkpsGTbQ3oOS7Yd1hzj7w2XkEECHgcKBvtJH/ZTePA4UDDYT/qwn8KDx4GCkQj9BMiYFxIySBDt4/BBbipGKEAhQvv2vSIAwxXgw77GPq+JTgpqHMaOHYukpCTce++9+Pzzz7Fp0yb85S9/wY033hipfFFhL+gZ1e2lZJCAx4H0Yj+Zs72UDBLwOJBe7CdztpeSQQIeB9IrUfoJkDEvJGSQIJrH4YX8LCSpwByE9u17cwAkqdrzUWiCWpTKyMjAs88+i9raWlx77bWYP38+br/9dkyZMiVS+aIiaWgmlAwbEOydhQqgZNiQNDQzLjJIwONAerGfAmA/hR2PA+nFfgqA/RR2PA6kV6L0EyBjXkjIIEE0j8O2nBS83zcV1wIYBMAa5PbWr7ebBOD9vqnYFuN3rkkQ9LfvDRkyBM8880wksoih2CxIv2YgmtfsB9q8gJ63QioAkrXtFJvRGwFlZZCAx4GCwX7qbiOwnyKAx4GCwX7qbiOwnyKAx4GCkQj9BMiYFxIySBDt4zBrbF98+NLneN2j4tvQvkXPo2M7K7QPN38DQLJVwayxfUPKQZr4OKsjwJqVjB7XDobSQ9+6ndLDhh7XDoY1KzmuMkjA40DUmYQ5ISGDBDwORJ1JmBMSMkjA40DkT8K8kJBBgmgeh8+zkjFzbF8MA/ABAN8nqHW3OOL7ef+vHz8UwMyxffF5nI1JtAR9p1QisWYlI2PqWXDtboSzsh7eOv9P6bdk22Ev6KndghiBlWsJGSTgcSDqTMKckJBBAh4Hos4kzAkJGSTgcSDyJ2FeSMggQTSPw9phmVCg4slNX2C7R8VaAE8A2NrFY0dB+wypSdDukJoxti/WDouPt1JKwEWpABSbBcn5WUjOz4KnthW2JmBm0VQs3roS7gyY8u0HEjJIwONA1JmEOSEhgwQ8DkSdSZgTEjJIwONA5E/CvJCQQYJoHoc1w87Alt6pWLTpCG4+4sANCrBDBXZBe0tfJoA8ACMU7UPN38tNxezv8g6pcIvPJdcIseakIDWvJ0pKSpCa1zMqRSEhgwQ8DkSdSZgTEjJIwONA1JmEOSEhgwQ8DkT+JMwLCRkkiMZx+DwrGVeVDELx5MF4ZkQWrNl2lFgUlAIosSiwZtvxzIgsFE8ejO//cBAXpCKAd0oRERERERERUcLalpOCbTnfAACkJaXi1al/xdUrb0OLyxHlZPGPd0oREREREREREflYuFRiFh5pIiIiIiIiIiIynaKqqmrGjtxuN7Zt24bxE8bDofp/qr4eiqKgV2oWjjsaYCS26vAAKgAFUFKtzMAMzCAkQ6pix8YNGzFq1CjYbNF5V3GoHRXqMQBCHwtmYAZmiEyGaHcU+4kZmIEZuhPr/QTEx2tZZmAGZvCnt59May6v1wsA2Lhho1m7JKIY4+uJaO6bHUVE3YlWR7GfiCgQ9hMRSRWon0y7U8rr9cLtdsNisUBRFDN2SUQxQlVVeL1e2Gw2WKL0/m12FBF1J9odxX4iou6wn4hIKr39ZNqiFBERERERERERkQ8/6JyIiIiIiIiIiEzHRSkiIiIiIiIiIjIdF6WIiIiIiIiIiMh0XJQiIiIiIiIiIiLTcVGKiIiIiIiIiIhMx0UpIiIiIiIiIiIyHReliIiIiIiIiIjIdDG1KFVWVoa8vDz8/e9/N3W/eXl5nf658MILce+99+LEiROm5gCAr776Co888gjGjh2LUaNGYfz48Xj22Wfh9Xojvu+xY8e2H4NzzjkHRUVFuP766/Gvf/0r4vvuKsOp/2zevDnqOX70ox+ZlqGlpQWPP/44rrzyShQUFOCCCy7AnDlzsHv3blP2P3bsWJSVlfn9vKysDGPHjjUlgzSJ3lGJ3k+n5ohWR7Gf2E9dYT+xn9hPJ0Wzo9hP/thP0esnQEZHSein0+Xga6jIdpQtIs8aIa+99hoGDhyIl19+Gdddd52p+164cCGKiorg9Xpx5MgR3HfffXjsscfw4IMPmpahvr4eU6ZMQe/evfH73/8e/fv3x/bt2/HQQw/h4MGD+O1vfxvxDPfccw8mTJgAr9eLr776CuvXr8dtt92GZcuW4dvf/nbE998xw6nOOOMMU/Z/uhxJSUmm7PvEiROYOnUqWlpaMHfuXJxzzjmor6/HCy+8gOuvvx7r16/HgAEDTMlCJyVyR7Gf/HOcysyOYj/RqdhP7KeOOU6VKP0EsKMkYj9Ft58AGR0loZ+6y8HXUJEVM4tSX375JT744APMmzcPc+fOxcGDB00dkDPOOAM5OTkAgD59+uC2227Dgw8+aOqi1B//+EckJydj+fLlsNvtAIABAwYgJSUFM2fOxLRp0/DNb34zohkyMjI6HYdf/epXqK2txfz58/Hqq69GdN9dZYimaOZ48skn8eWXX2LDhg3IzMwEAPTr1w/z58/HkSNH8Oyzz5r2HzHSJHpHsZ+6zhEt7CfqiP3EfuoqR7REOwM7Shb2U/T7CZDRUdHuBgk5ErWfYubte6+//joyMjJwzTXXoHfv3nj55Zejmic1NdXU/bW1teG1117DDTfc0F5YPt/97nfx7LPPol+/fqZm8pkyZQo+++wzVFdXR2X/icbr9WLdunX4yU9+0l5WHT322GO46667opAssSVyR7GfyIf9JBP7if1EGnaUPOwnmf0EsKPMlsj9FDOLUq+99houvfRSWCwWjB07FuvXr4eqqlHJcvz4cfztb3/DNddcY9o+Dxw4gJaWFowcOdLv7xRFwYUXXojk5GTT8nR09tlnAwD27NkTlf0nmgMHDuD48eM4//zzu/z73r17IyUlxeRUlMgdxX4iH/aTTOwn9hNp2FHysJ9k9hPAjjJbIvdTTLx978iRI/j444/xk5/8BABwxRVX4MUXX8SWLVu6HbRwmzFjBqxWK1RVhcPhQFZWFh544AFT9g0AjY2NALTbCaXxZTLrQwHvv/9+PPTQQ51+lpubi9dee82U/Z8ux/vvv4+0tLSI7re+vh5A5/dX//vf/8Ydd9zR/v/NOh5dHQO32y3i1lszJXpHsZ86k9BR7Cf2kw/7if3UUSL3EyCno9hPGvaT3H4CeI3XEV9DRbajYmJR6rXXXoPdbsd3vvMdAMCYMWNwxhlnYN26daYV1sMPP4xRo0ZBVVXU19djxYoV+NGPfoRXX30VZ555ZsT3n5WVBUD7dgZpmpubAQA9evQwZX9z5szBFVdc0elnNpv5p3JXOcy45dd3O6fvP2QAUFRUhPXr1wMA3nzzTbz44osRzwF0fQzM3L8Uid5R7KfOJHQU+4n95MN+ygLAfvJJ5H4C5HQU+0nDfsoCILOfAF7jdcTXUJHdf8wsSrW2tmL06NHtP/N4PHj99dfx29/+1pTb2Pr06YNBgwYBAAYPHozhw4fjggsuwMaNGzFt2rSI73/gwIHIyMjAJ598goKCAr+/v/3223HjjTea+g0uPrt27QIADB061JT9nXnmme1jEU3RyjFo0CBkZWVh69at7edCampqexYzFkl9ujoGZu5fikTvKPZTZxI6iv3EfvJhP7GfOkrkfgLkdBT7ScN+kttPAK/xzCaln3z7MrOjxH+m1Oeff45PP/0U9957L9avX9/+z5///Gc0Nzfjn//8Z1RyWSwWqKoKj8djyv5sNhsmTJiAF154AW1tbZ3+btOmTdi0aRN69+5tSpZTrV27FsOHD4/Lr6eUyGazYdKkSXjuuefaf4PR0dGjR6OQKnGxo9hPdBL7SRb2E/uJOmNHycF+kt1PADvKbIncT+LvlHrttdeQlZWFKVOmdPqgt2HDhuHJJ5/E+vXrcfXVV0c8x1dffYXa2loA2vtqn376aXg8HowdOzbi+/aZPXs2rrvuOtx6662YPXs2vvGNb2Dz5s1YsGABbrrpJgwZMiTiGZqamlBbW9t+i+uaNWuwYcMGPP300xHf96kZTpWenm7K5xFIMHv2bGzZsgXXX389Zs2aheHDh6O+vh5///vfsWbNGnz/+9+PdsSEwY7SsJ/8c5wqUTqK/SQH+0nDfvLPcapE6SeAHSUF+0kjoZ8AGR3FfkrcfoqJRamrr766y28e+NGPfoTf//73OHr0KPr06RPRHLNnz27/36mpqRgxYgSeeuopU1eOc3Jy8OKLL2LhwoW488470dDQgIEDB2LOnDn40Y9+ZEqGefPmYd68eVAUBb169cK5556LZ5991rT3fXfMcKqf/exnmDlzpmk5oik1NRV/+9vf8Nxzz2Hx4sWorq5GcnIyCgoKsHDhQnzve9+LdsSEwY7SsJ/8c5wqUTqK/SQH+0nDfvLPcapE6SeAHSUF+0kjoZ8AGR3FfkrcflLUaH3nJhERERERERERJSzxnylFRERERERERETxh4tSRERERERERERkOi5KERERERERERGR6bgoRUREREREREREpuOiFBERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjolQcKC0txd13393pZ//4xz+Ql5eHhQsXdvr54sWL8YMf/KDTz1RVxS233IKysrJOP3/22WeRl5fX6Z9HH330tFm++93v4ujRo34///LLLzFnzhyMHj0aF198MRYsWAC3293+93v37sUtt9yC8847D2PHjsVf/vIXeL3e0+5r2rRp+Pjjj/1+fuONN3bKXFRUhFtvvRXV1dVdPs8rr7yCG2+8sf3/Hzp0yO/f2/fPRx99dNpMROQvUh1VX1+P2bNno6ioCGPHjsXLL78cMEt3vdHS0oJ7770XF1xwAb71rW/ht7/9LU6cOOH3uLa2Nnz/+9/H5s2bA+7r17/+NV599VW/n8+dO7dTr4waNQrXX389KisrOz3u3XffxQ9+8AMUFRXh6quvxttvv93+dx6PB3/4wx9w8cUXo6ioCD/72c9QV1cXMBMRdRapfjpw4AB+8pOftM/fd999N2AWo/3kdDpxzz334Pzzz8d3vvMdPP300wH3FWo/+fz3v//FZZdd5vfz888/3+81VFedSkTdi4VrvMbGRvzmN7/Bt7/9bVx44YWYO3cuGhsb2/8+nF2o9xpv7dq1uPLKK1FUVITrrrsOW7Zs8fv3v+SSS1BUVIR77rkHDocjYCaKLC5KxYHzzz8f27dv7/SzzZs3o3fv3n4XThUVFRgzZkz7//d6vXj44Yfx/vvv+z3vnj17MHXqVLz33nvt/9xxxx3d5qiurkZKSgr69Onj93d33nknmpubsWrVKvy///f/8Nprr2HZsmUAAIfDgdLSUvTp0wdr1qzB/fffj+eeew4vvvhit/tyOBzYvXs3CgoKuvz7W265Be+99x7+9a9/YfXq1cjKysLMmTOhqmqnx3344Ye47777Ov2sb9++nf6d33vvPXz/+9/HyJEjUVhY2G0mIupapDrq7rvvRlNTE1atWoXbb78d9957b7cXTsDpe2PevHnYsWMHli9fjmeffRaVlZV45JFHOj3G6XTil7/8JXbv3q3r3/vDDz/EhRde2OXfjR8/vr1f1q1bh1GjRuG2225rv2irqqrCrFmzMGnSJKxfvx7XX389fvazn6GqqgoAsHTpUmzYsAGPP/44/v73v+Orr77Cr371K125iOikSPST0+nET37yE9jtdqxevRq33norfvGLX0Ssnx577DHs2LEDzz33HO6//34sWrQIr7/++mn/vUPpJ59du3bhZz/7md9rq6NHj6KpqQlvvfVWp9dSaWlpp81ERJ3FwjXe/fffj6qqKixduhTLly/H3r17ce+99wIIfxcCga/x/u///g+/+93vMHPmTKxfvx4XX3wxSktL2xfU3njjDSxatAi/+93v8Nxzz2Hbtm1YsGBBt3nIHFyUigOjR4/G3r17O71Y2Lx5M2699VZUVFSgtbW1/efbtm1rL6yjR4/ixz/+MTZt2oTMzEy/5927dy/OOecc5OTktP/To0ePbnN88MEHuOiii/x+3tbWhjPPPBP3338/hgwZgvPPPx/jxo1rX7X+6KOP8NVXX+HBBx/EWWedheLiYtx8881d/gbP57///S8KCwths9m6/Pu0tDTk5OSgd+/eGDp0KObOnYs9e/Zg165d7Y9ZtGgRZsyYgQEDBnTa1mq1dvp3PnjwIN544w08+uijSEpK6jYTEXUtEh114MABvPPOO3j44YcxbNgwXHfddbjmmmuwcuXKbnOcrjeSkpLw29/+FiNGjMDw4cMxadKkTr9Z27NnDyZPnowDBw7o+nfet28fMjIykJOT0+Xfp6SktHfMWWedhbvuugutra348MMPAWi/Cb3wwgtx0003YdCgQbjhhhtwwQUXYOPGjQC0O6XuvvtufOtb38KQIUNw4403+v0mkIgCi0Q/vfPOO6ivr8eCBQswdOhQTJw4Eddccw2effbZbnMY7aeWlhb8/e9/x29+8xsMHz4cl19+OaZPn44XXnih232F2k8A8NJLL+H666/HmWee6bf93r17kZOTgwEDBnR6PaUoSreZiMif9Gu8lpYWvPHGG7jvvvva++mee+7BW2+9BafTGfYuBAJf461bt659P4MGDcLPf/5zZGdno7y8HADw/PPP48c//jG++93voqCgAA8++CDWrl3Lu6WijItScWDkyJFISkrCJ598AgD44osvUFNTg+uuuw4ZGRnttz9+/vnn+Oqrr3D++ecDAD755BP07dsXa9euRUZGht/z7tu3D4MHD9ado7vCSk5Oxh/+8AcMGjQIALB7925s2rSpvTjz8/Px5JNPIjk5udN2zc3NQe+rO6mpqX4/e//997F8+XJcccUVp932j3/8IyZPnoyzzz5b9/6I6KRIdNS2bdvQt29f9O/fv/1no0ePxtatW7vNcbreuP/++zF69GgA2lt4//GPf3T6jeN//vMfXHDBBVi1apWuf+cPPvig27sQumKz2Tp14A9/+EPceeedfo9ramoCAMyaNQuXX345AO3t0X//+9875SUifSLRTwcPHsRZZ53V6ed5eXmoqKjoNofRfqqqqoLb7UZRUVH740ePHo1t27Z1+zEIofYToN2N8Oijj+Lmm2/2e/yePXvwzW9+U/fzE1HXpF/jWSwW/OUvf0F+fn6nn3s8Hpw4cSLsXdiVU6/xpk+fjp/85Cd+j2tqaoLH48H27dvbjxMAFBYWwuVytd+JTtHBRak4kJycjFGjRrXfCvnhhx9ixIgRSE9Px7e+9a322zsrKiowdOhQ9OzZEwAwduxYPPbYY+jVq5ffc9bV1aGhoQHr1q3D2LFjMX78eCxfvtzvFm0fVVXx0UcfBbwomjZtGr7//e8jIyMDN9xwAwAgJycHF1xwQftjWltbsXr16tO+YDrdbeenamtrw1/+8pf29x/7vPjiiwHzbtmyBRUVFbjtttt07YuI/EWio2pra9G7d+9OPzvzzDO7/LwDHz298etf/xqXXXYZ6urqOt3KPnXqVNxzzz1dLnB3ty+9L6rcbjdeeOEFJCUltec7++yzcc4557Q/Zvfu3V2+UHviiSfw7W9/Gx9//DHmzp2ra39EdFIk+ik7Oxu1tbWdXjN98cUXqK+v7zaH0X6qra1Fz549Oy0aZWdnw+l0oqGhodt9hdJPgPb5Nd39Um/v3r1wOBy48cYb8Z3vfAczZszA559/rmt/RHSS9Gu8lJQU/M///E+n/nn++eeRl5eHXr16RawLfbq6xhs+fHinBbf/+7//w/79+3HhhReisbERTqez0+tHm82GrKwsfPHFF7r2SZHBRak4cf7557cX1ubNm9sXecaMGdOpsPT+Jn3fvn0AtIu8JUuW4LbbbsOSJUvw3HPPdfn4qqoq9O3bF2ecccZpn/fee+/F888/D5fLhV/+8pd+f+/1ejF37lycOHGi24WghoYGHD16tNMC06n++te/oqioCEVFRRg1ahSWLVuGWbNmBX3r+OrVq3H55Zd3+R5qItIv3B3lcDj8fnOfnJyMtra2Lh+vpzcAYMaMGVi1ahX69euHGTNmBPzCha54vV7897//Pe2/y6uvvtreUQUFBfjd736H6dOnIz093e+xx48fx+zZs3Heeef5faDwD37wA6xZswYXXXQRbrnlltPeYUpEXQt3P/3P//wPmpqasHDhQrS1tWH79u1Ys2YNXC5Xl48PpZ+660IAXfZhuPupK/v27cNXX32F22+/HYsXL0ZKSgpuvvlm9hORAbFyjQcAK1aswMaNG9s/4zISXRjMNd6BAwdw99134+qrr8bw4cPb3+4YzOtHMgcXpeJExw/C27x5c3sxjRkzBjt27EBbWxsqKirwrW99S9fzjRkzBh9++CHuuusu5OXlYeLEiZg5c2a3Hz6u91bLc845BxdccAHmzZuHd955B4cOHWr/O7fbjbvuugvvvvsuFi9e3O1nHfj+/U63wHT99ddj/fr1WL9+PcrKyvDzn/8cv/zlL/HBBx8EzNgxz9tvv41rrrlG9zZE1LVwd5Tdbvd7AdHW1oaUlJQuH6+nNwBgyJAhKCwsxJ///Gfs2rXL0DdufvrppxgwYECXt8z7jB07tr2j1q9fjwceeAB/+tOf/L4hp66uDj/+8Y+hqiqeeOIJWCyd/7M9aNAgjBw5Eo899hhaW1vx5ptvBp2XKNGFu5/OPPNM/PnPf8aLL76IUaNG4Ze//CWmTZvW7aJOKP3UXRcC6LIPw9lP3Vm+fDnWr1+Pb3/72ygoKMAf/vCH9s+XIaLgxMo13gsvvICHH34Yd999N77zne8AiEwX6r3G+/zzz3HTTTdhwIABePjhhwForx0B/wX7trY23XfCU2R0/QliFHOKiopw7NgxbN++HceOHcN5550HABg6dCgyMjLw0UcfYc+ePUF95ojvFlCfs88+u9u3xnzwwQddfq4AoH021P/93//hyiuvbL+gGjJkCADtK9379+8Pl8uFX/ziF3j//fexdOnS9vzd7StQOZ5xxhntn2EFaJ9b9dFHH+HFF1/Ufct6RUUF3G43Lr74Yl2PJ6Luhbuj+vTpg7q6uk4/q6ur63Yx+3S90dbWhnfeeQcXX3xx+wd9ZmdnIysr67S3mHdHT0elp6d36qhhw4Zh586dWLFiBUpKSgBoH1R60003AdBuh+94G/4777yDc889t/0uTrvdjgEDBhjKS5ToIvEaqri4GP/+979RW1uL7OxsvPjii+jXr1+Xjw2ln/r06YP6+nq43e72Dwaura1FSkpKlx9wHK5+Op3k5OROdyLY7Xb079//tG+vJqKuSb7G81m+fDkee+wx/OpXv8KPf/zjTn8Xri700XONt3v3btx8880YMGAAli1b1r5An5WVBbvdjrq6uvbPCna73WhoaOj29SOZg3dKxYm0tDTk5+dj1apVGDlyZPtqr6Io+Na3voWysjIMHjy4y/cWd+Xvf/87xo0b1+k9wDt37sRZZ53l91iXy4XKysr2D+E8lcPhwC9+8Qts27at/WeffPIJrFZr+wdh3nfffXj//ffx1FNPBSzVYD8Az0dVVXg8Ht2P37ZtG4YPH96+qk5ExoW7owoLC3H48OFOnwGwZcsWFBYWdvn40/WGxWLB3Llz8e6777b/rKamBvX19Ya+4CCYz0PoSFXV9rcLtrS0YPr06bBYLFixYoXfW4gfffRRrF+/vv3/Nzc3Y//+/fxCBiIDwt1Pe/fubb/DsXfv3rBYLCgvL+/0+ZkdhdJP+fn5sNlsnT44eMuWLRg5cqTfnZVAePop0OO+973vdbqrqqWlBdXV1V2+hiSi05N8jQdo33b32GOP4e6778att97a6e/C2YWn0/Ea79ixY7jlllswaNAgLF++vNO3ClosFowcObLTtxVXVFTAZrN1+hxPMh8XpeLIt771Lbz22mt+izpjxozB22+/rfu2TgD49re/jdraWjz66KOorq7Ga6+9hqeeegrTp0/3e+y2bdswbNiwbt82k5OTgyuuuAIPPfQQPv30U/z3v//Fb37zG0ybNg09evTA+++/j7KyMsydOxeDBg1CbW0tamtrcfz4cb/n+uKLL+ByuTBgwIDT5m9paWl/niNHjuCFF17ABx98gPHjx+s+Brt37+YFHlEYhbOjBgwYgO985zu46667UFVVhb///e/4xz/+0f4FCh0F6g2bzYYpU6bgT3/6E/773/9ix44d+MUvfoHLLrsMQ4cODerfsa2tDTt27Djt3Z6A9oUOvo46evQoNmzYgFdffbW9o/7617/iwIEDePTRRwGg/bG+b9+74YYbsHz5cpSXl2P37t246667MHDgQPzP//xPUHmJSBPOfurXrx/27t2LJ554AgcPHsSTTz6JLVu24MYbb/R7bKj9lJqaiokTJ+KBBx5AZWUl3nrrLTz99NPtd1l2FK5+Oh1FUXDppZdi4cKF2Lx5M3bv3o1f/epX+MY3voHi4uKA2xORP6nXeA0NDfjd736HH/7wh7jqqqvae6O2thYejyesXegT6Brv0Ucfhdfrxe9///tOjz1x4gQA7Ytrli9fjrfeeguVlZV44IEHMHnyZL59L8r49r04Mnr0aDz99NN+q89jxoyBw+EI6rbOfv36YenSpViwYAFefPFFnHnmmbjzzjsxYcIEv8fq+a3bvHnzMG/evPav6Jw4cSL+93//FwDwxhtvANDulrrvvvs6Zdi0aVOn59H7NcZPP/00nn76aQBAUlISBg0ahPvuuw/f//73A27rU1dX5/cVp0RkXDg7CgAee+wx/OY3v8HkyZORk5ODefPmoaCgwO9xenrjl7/8JRRFwc9//nO0tLTgiiuuwL333htUHkD7jds555wT8A7LjRs3YuPGjQC0i85vfOMbuO2229pfFL7xxhtobW3Fdddd12m7H/7wh3jkkUdwww03wOFw4IEHHsDx48dx8cUXY8mSJV3eGUFEgYWzn1JSUrBo0SL87ne/w7PPPouhQ4di2bJlyM3N9XtsOPrp7rvvxgMPPIAf//jH6NGjB2bPnt3lN+OFq58Cueuuu2Cz2fC///u/aG5uxoUXXoilS5fCarXq2p6IOpN6jff++++jpaUF69atw7p16zr93dtvv43+/fuHtQuB01/jqaqKt956C62trbjyyis7bTdr1izMnj0bV111FQ4fPoz77rsPbW1tuOKKK3DXXXcF3C9FlqJ29/2PREREREREREREEcJfqRIRERERERERkem4KEVERERERERERKbjohQREREREREREZmOi1JERERERERERGQ6LkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZjotSRERERERERERkOi5KERERERERERGR6bgoRUREREREREREpuOiFBERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjohQREREREREREZnOZtaOvF4v3G43LBYLFEUxa7dEFANUVYXX64XNZoPFEp21cnYUEXUn2h3FfiKi7rCfiEgqvf1k2qKU2+3G9u3bzdodEcWgkSNHIjk5OSr7ZkcRUSDR6ij2ExEFwn4iIqkC9ZNpi1K+lbHxE8bDoToNPYeiKOiVmoXjjgaoqhr09qrDA6gAFEBJtTIDMzCDkAypih0bN2yM2l1SQOgdFeoxAEIfC2ZgBmaITIZodxT7iRmYgRm6E+v9BMTHa1lmYAZm8Ke3n0xblPLdzulQnbBOzjX0HGlJqVg77SlcvWIGWlyOoLdvfHYP1BNuKOk2ZE4ewgzMwAxCMjhW1wA42RPREGpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ37QORERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjohQRhaSgfz4mFo1DdnY2JhaNQ0H//GhHIiICwH4iIrnYT0QkmZkdZdq37xFR/EhJsmPS6AkoLZ6GUQPObf/54pvmAwC2HfwUS8tXYO2WDWh1Gft6YCIiI9hPRCQV+4mIJItWR/FOKSIKytm9B+M/976GRTf8HiP65XX5mBH98rDoht/jP/e+hrNyBpmckIgSFfuJiKRiPxGRZNHsKMOLUm1tbfj+97+PzZs3hy0MEcl2du/BeOvOl5Cb1QeKosBqsXb5OKvFCkVRkJvVB2/ftcr0F1bsJ6LEw34iIqnYT0QkWbQ7ytCilNPpxC9/+Uvs3r07LCGISL6UJDvW3bEMGfZ02Kz63vlrs9qQYU/H+lnLkZJkj3BCDfuJKPGwn4hIKvYTEUkmoaOCXpTas2cPJk+ejAMHDoS8cyKKHZNGT8CAXrm6y8rHZrVh4Jn9UHLe+AglO4n9RJSY2E9EJBX7iYgkk9BRQS9K/ec//8EFF1yAVatWhbxzIoodpcXT4FW9hrb1eD0oLZ4W5kT+2E9EiYn9RERSsZ+ISDIJHRX0t+9NnTo15J0SUWwp6J/f6RsYgmW1WFE4cDgK+uej8tDOMCbrjP1ElHjYT0QkFfuJiCST0lFBL0qFSlEUpCWlGto2NSml05/BalIUqMzADMwQdIYRuV1/A0OwhucOw56j+/1+3qwoYXn+cDA6FqGOAxD6+cAMzJCIGSLdT4CcjpI8DszADMzAfpL8WpYZmIEZ/Em5xlNUVVWN7jwvLw/PP/88LrjggoCP9Xg8qKiowKRJk7B27VqjuwzJhAkTcOzYMfTu3RsbNmxgBmZgBp0ZsrOzMWhQ6N+uUF1djbq6Or+f+3qhsLAQVmvX3/YQrGD6CWBHMQMzxGqGSPcTEP6OYj8xAzMkRgb2kzli4VxgBmaQmEHKNZ7pd0oddzTg6hUzDG2bmpSC1VMWYvKq2XC4WoPevq6lvv1PZmAGZtCfYWLROCy+ab6hfB09Ur4EL2990+/nzY6GkJ87XIx2VKjjAIR+PjADMyRihkj3EyCno9hPzMAMsZWB/aRPoryeZgZmkJZByjWe6YtSqqqixeUI6TkcrlZDz+G7KYwZmIEZgsuwo2ZXSNnan+fwri73EcINm2EX6lgYHQffvpmBGZghuAyR7qeOGaJN8jgwAzMwA/tJ8mtZZmAGZvAn5Rov6G/fI6LEU3loJ7Yd/BQer8fQ9h6vBxUHPsH2w1VhTkZEiY79RERSsZ+ISDIpHcVFKSLSZWn5ClgUY5VhtVixtHxFmBMREWnYT0QkFfuJiCST0FEhLUrt2rVL94fgEVFsW7tlAw4er4Hb4w5qO7fHjQNfHkbZxxsjlKxr7CeixMF+IiKp2E9EJJmEjuKdUkSkS6vLiR8+OR1NzhO6S8vtcaPJeQITF92KVpczwgmJKFGxn4hIKvYTEUkmoaO4KEVEuu09th+XLZiCmoajANDt+499P69pOIrLFkzBvtpq0zISUWJiPxGRVOwnIpIs2h1l+rfvEVFs21dbjTEPX4WS88ajtHgaCgcO93vM9kNVWFq+AmUfb+Rv+IjINOwnIpKK/UREkkWzo7goRURBa3U5sXLzeqzcvB4F/fMxPHcY5hbfjkfKl+CTms9QeWhntCMSUYJiPxGRVOwnIpIsWh3FRSkiCknloZ3Yc3Q/pg+/Di9vfRMtLke0IxERAWA/EZFc7CcikszMjuJnShERERERERERkem4KEVERERERERERKbjohQREREREREREZlOUVVVNWNHHo8HFRUVKL60GC2qsU9qVxQF2Wk9UddSDyOx1RY3oAJQACXN2MdpMQMzMEP4M6QpdpS/W47CwkJYrVZDGUIVakeFegyA0MeCGZiBGSKTIdodxX5iBmZghu7Eej8B8fFalhmYgRn86e0n8z/oXAXUE26jm+JY8zFmYAZmiLcM6Xbj24abweMQtnFgBmZgBnkZpHRUoo8DMzADM/iL8X76etPYfy3LDMzADP509pP5i1IKoKQn7mohMzADM3T1BIZ2GxkGOypefuPKDMzADF09ibHNwo79xAzMwAx+T2Jss7DjNR4zMAMz+D2BvoeZviilpFqROXmIoW3TklLx6rSncPWKGYa+krDx2T1QT7ihpNmQeTMzMAMzSMngWV1jaL+RYLSjQj0GQOhjwQzMwAyRySClo9hPzMAMzHCqWO8nID5eyzIDMzCDP739xA86JyIiIiIiIiIi03FRioiIiIiIiIiITMdFKSIiIiIiIiIiMh0XpSgmeWpb4ag6jrKyMjiqjsNT2xrtSFFR0D8fE4vGITs7GxOLxqGgf360IxElPPaThv1EJA/7ScN+IpKJHaVJtI4y/9v3iAxS3V64djfCWVkPb50TADDv9Xntf2/JtsNe0BNJQzOh2OJ3vTUlyY5JoyegtHgaRg04t/3ni2+aDwDYdvBTLC1fgbVbNqDV5YxWTKKEwn7SsJ+I5GE/adhPRDKxozSJ3FFclKKY4Glow4lXDkBtcnf7GG+dE45NX6D1ozqkXzMQ1qxkExOa4+zeg7HujmUY0CsXXtXb5WNG9MvDoht+j1+PvwMTF92KfbXVJqckSizsJw37iUge9pOG/UQkEztKk+gdFdRS49GjRzFnzhyMGTMGl1xyCebPnw+nM75W6UgeT0Mbmtfsh9rcfVl1pDa70bxmPzwNbRFOZq6zew/GW3e+hNysPlAUBVaLtcvHWS1WKIqC3Kw+ePuuVTgrZ5DJSaOHHUVmYz9p2E+BsZ/IbOwnDfspMPYTRQM7SsOOCmJRSlVVzJkzBw6HAy+88AL+/Oc/45133sHjjz8ewXiU6FS3FydeOQC0eQFV70YA2rTtVHfXK82xJiXJjnV3LEOGPR02q74bHG1WGzLs6Vg/azlSkuwRThh97CgyG/tJw34KjP1EZmM/adhPgbGfKBrYURp2lEb3otS+fftQUVGB+fPnY+jQoTj//PMxZ84c/OMf/4hkPkpwrt2N2u2cesvKRwXUJjdcuxsjkstsk0ZPwIBeubrLysdmtWHgmf1Qct74CCWTgx1FZmM/adhPgbGfyGzsJw37KTD2E0UDO0rDjtLoXpTKycnBsmXLkJ2d3ennzc3NYQ9F5OOsrI/q9lKUFk/r9v3FgXi8HpQWTwtzInnYUWQ29pOG/RQY+4nMxn7SsJ8CYz9RNLCjNOwoje5FqczMTFxyySXt/9/r9WLFihW48MILIxKMyFPb2v4NDEZ565wx/1WiBf3zMWrAud2+vzgQq8WKwoHD4/6rRNlRZCb2k4b9pA/7iczEftKwn/RhP5HZ2FEadtRJhr99b8GCBfj000+xZs2aoLZTFAVpSamG9pmalNLpz2A1KQpUZoiZDI5Gh6HnPpWtCUjN9d9HrByHEbl5hp77VMNzh2HP0f2GMgQS6nFoVhRD252O2R0V6jEAQh8LZjAvQ6T7SU+GQMw4DpHuJz0ZAgnHcQh3R7GfmIH9xH4C2E8+iXJtwwwaXuNpeI13kqKqarDv5MSCBQvwzDPP4M9//jPGjRunaxuPx4OKigpMmjQJa9euDXaXYTFhwgQcO3YMvXv3xoYNG5hBeIaysjLMmzcv5H3dc889KCkpMZQh0vRkyM7OxqBBoX+7QnV1Nerq6gxliDRfLxQWFsJqNfbbgo7YUcwQ6QyR7ic9GcwQKEOk+0lPBjOEs6PYT8wQ6QzsJw37KXjsJ2YwIwOv8TS8xjsp6DulHnroIbz44otYsGCB7rLq6LijAVevmBH0doC2Qrd6ykJMXjUbDlfwt+vVtdS3/8kM8jM4qo4bynaqxVtX4pmWjYYyBGLGcZhYNA6Lb5pvKF9Hj5Qvwctb3zSUIZBQj0Ozo8HQfrsSrY4K9RgAoY8FM5iXIdL9pCdDIGYch0j3k54MgYTjOISro9hPzMB+0rCfNOwnTaJc2zCDhtd4Gl7jnRTUotSiRYvw0ksv4U9/+hOuvPLKoEMB2teOtrhCu2XP4Wo19By+m8KYITYyeDLDczuyOwNd7iNWjsOOml0hZWt/nsO7xB+HUEnoKKPHwLdvZoiNDJHuJz0Z9IrkcYh0P+nJoFc4jkMo2E/MYFYG9pOG/aSfhH4C4v/ahhk0vMbT8BrvJN0fdL53714sXrwYM2bMwOjRo1FbW9v+D1EkWHNSYMm2h/Qclmw7rDnG36cvQeWhndh28FN4vB5D23u8HlQc+ATbD1eFOZks7CgyE/tJw37Sh/1EZmI/adhP+rCfyGzsKA076iTdi1Jvv/02PB4PlixZgu985zud/iGKFHtBz6huL8XS8hWwKLqnaydWixVLy1eEOZE87CgyG/tJw34KjP1EZmM/adhPgbGfKBrYURp2lEb32/dKS0tRWloaySxEfpKGZqL1ozqozW4gmLuTFUDpYUPS0MyIZTPT2i0b8OvxdyA3qw9sVv3vunV73KhpOIqyj7v+TIh4wo4is7GfNOynwNhPZDb2k4b9FBj7iaKBHaVhR2mMLcsRmUSxWZB+zUAg2QLoffuxAiBZ206xxccp3upy4odPTkeT8wTcHreubdweN5qcJzBx0a1odTkjnJAo8bCfNOwnInnYTxr2E5FM7CgNO0oTH6NJcc2alYwe1w6G0kPf6rHSw4Ye1w6GNSs5wsnMtffYfly2YApqGo4CQLfvP/b9vKbhKC5bMAX7aqtNy0iUaNhPGvYTkTzsJw37iUgmdpSGHRXkt+8RRYs1KxkZU8+Ca3cjnJX18Nb5rwpbsu2wF/RE0tDMuFk9P9W+2mqMefgqlJw3HqXF01A4cLjfY7YfqsLS8hUo+3hj3KyeE0nGftKwn4jkYT9p2E9EMrGjNIneUVyUopih2CxIzs9Ccn4WPLWtsDUBM4umYvHWlXBnIOa/gUGvVpcTKzevx8rN61HQPx/Dc4dhbvHteKR8CT6p+QyVh3ZGOyJRwmE/adhPRPKwnzTsJyKZ2FGaRO6o+FxqpLhnzUlBal5PlJSUIDWvZ8KU1akqD+3Ey1vfRF1dHV7e+mZclxVRrGA/adhPRPKwnzTsJyKZ2FGaROsoLkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZTlFVVTVjRx6PBxUVFSi+tBgtqrFPi1cUBdlpPVHXUg8jsdUWN6ACUAAlzdhnvDMDMzBD+DOkKXaUv1uOwsJCWK1WQxlCFWpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ/O/fU8F1BNuo5viWPMxZmAGZoi3DOl249uGm8HjELZxYAZmYAZ5GaR0VKKPAzMwAzP4i/F++nrT2H8tywzMwAz+dPaT+YtSCqCkJ+5qITMwAzN09QSGdhsZBjsqXn7jygzMwAxdPYmxzcKO/cQMzMAMfk9ibLOw4zUeMzADM/g9gb6Hmb4opaRakTl5iKFt05JS8eq0p3D1ihlocTmC3r7x2T1QT7ihpNmQeTMzMAMzSMngWV1jaL+RYLSjQj0GQOhjwQzMwAyRySClo9hPzMAMzHCqWO8nID5eyzIDMzCDP739xA86JyIiIiIiIiIi03FRioiIiIiIiIiITMdFKSIiIiIiIiIiMh0XpShoBf3zMbFoHLKzszGxaBwK+ucnZAZPbSscVcdRVlYGR9VxeGpbTc8g4TgQSSJhTkjIwH4ikkfCnJCQgf1EJJOEeSEhAzvKfOZ/+x7FpJQkOyaNnoDS4mkYNeDc9p8vvmk+AGDbwU+xtHwF1m7ZgFaXM24zqG4vXLsb4aysh7dO28e81+e1/70l2w57QU8kDc2EYovMmq+E40AkiYQ5ISED+4lIHglzQkIG9hORTBLmhYQM7Kjo4qIUBXR278FYd8cyDOiVC6/q7fIxI/rlYdENv8evx9+BiYtuxb7a6rjL4Glow4lXDkBtcnf7GG+dE45NX6D1ozqkXzMQ1qzksGaQcByIJJEwJyRkYD8RySNhTkjIwH4ikknCvJCQgR0VfUEv81VXV+PWW29FUVERLr30UixbtiwSuUiIs3sPxlt3voTcrD5QFAVWi7XLx1ktViiKgtysPnj7rlU4K2dQXGXwNLShec1+qM3dl1VHarMbzWv2w9PQFrYMEo6DdOynxCJhTkjIwH6KDeynxCJhTkjIwH6KDeynxCNhXkjIwI6SIahFKa/Xi9LSUvTs2RPr1q3Dgw8+iCVLluDVV1+NVD6KopQkO9bdsQwZ9nTYrPpuqrNZbciwp2P9rOVISbLHRQbV7cWJVw4AbV5A1bsRgDZtO9Xd9Wp3MCQcB+nYT4lFwpyQkIH9FBvYT4lFwpyQkIH9FBvYT4lHwryQkIEdJUdQi1J1dXXIz8/HAw88gMGDB6O4uBgXXXQRtmzZEql8FEWTRk/AgF65uieIj81qw8Az+6HkvPFxkcG1u1G7nVNvWfmogNrkhmt3Y8gZJBwH6dhPiUXCnJCQgf0UG9hPiUXCnJCQgf0UG9hPiUfCvJCQgR0lR1CLUr1798bjjz+OHj16QFVVbNmyBR999BHGjBkTqXwURaXF07p9T2sgHq8HpcXT4iKDs7I+qtsDMo6DdOynxCJhTkjIwH6KDeynxCJhTkjIwH6KDeynxCNhXkjIwI6Sw/BHx48dOxZTp05FUVERxo0bF85MJEBB/3yMGnBut+9pDcRqsaJw4PCQvr5SQgZPbWv7NzAY5a1zhvRVohKOQ6xhP8U3CXNCQgb2U2xiP8U3CXNCQgb2U2xiP8U/CfNCQgZ2lCyGv33viSeeQF1dHR544AHMnz8f9957r67tFEVBWlKqoX2mJqV0+jNYTYoClRl0ZRiRm2fouU81PHcY9hzdH7MZHI2OsGSwNQGpuf77iJXjEEio52SzohjarjtG+wkwfhxCPQZA6GORKBkiPSdiJUOk+0lPBgnHIZBwnJPh7Cj2U3xnkDAnJGRgP+nDftIkyvWVhAwSriskZOA1nj5mXeMpqqoG+y7KTl5//XXceeed+Pjjj5Gc3P1XI3o8HlRUVGDSpElYu3ZtKLs0bMKECTh27Bh69+6NDRs2MMNpMmRnZ2PQoNA/0b+6uhp1dXUxm6GsrAzz5s0LOcM999yDkpISQxkkHIdI8/VCYWEhrFZjvy3oit5+AthRsZQh0nMiVjJEup/0ZJBwHMwQiY5iP8VnBglzQkIG9pN52E8yxiFWMki4rpCQgdd45tDbT0HdKVVXV4eKigp873vfa//ZkCFD4HK50NzcjF69egV8juOOBly9YkYwu22XmpSC1VMWYvKq2XC4gr9Vrq6lvv1PZjh9holF47D4pvmG8nX0SPkSvLz1zZjN4Kg6HvL+AWDx1pV4pmWjoQwSjkMgoZ6TzY4GQ/vtKBz9BBjvqFCPARD6WCRKhkjPiVjJEOl+0pNBwnEIJBznZKgdxX5KnAwS5oSEDOwnfdhPmkS5vpKQQcJ1hYQMvMbTx6xrvKAWpQ4dOoRZs2ahvLwcffr0AQDs2LEDvXr10l1YqqqixRXa7XIOV6uh5/DdFMYMgTPsqNkVUrb25zm8q8t9xEoGT2Z4bol2ZyCmj4NeoZ6ToQhHP/myhHIcjB4D376ZIXCGSM+JWMkQ6X7Sk0HCcdArHOekUeynxMkgYU5IyMB+Cg77SRPv11cSMki4rpCQgdd4wYn0NV5QH3Q+cuRIDB8+HPfccw/27NmD8vJyLFiwAD/96U+DDkiyVR7aiW0HP4XH6zG0vcfrQcWBT7D9cFVMZ7DmpMCSbTe8PQBYsu2w5hj/rAAJxyEWsJ8Sh4Q5ISED+yl2sJ8Sh4Q5ISED+yl2sJ8Si4R5ISEDO0qWoBalrFYrFi9ejNTUVEyZMgW/+c1vcOONN+Kmm26KVD6KoqXlK2BRjH1Bo9VixdLyFXGRwV7QM6rbAzKOg3Tsp8QiYU5IyMB+ig3sp8QiYU5IyMB+ig3sp8QjYV5IyMCOkiPoI9CnTx8sWrQIW7ZswXvvvYef/vSnUML8zVkkw9otG3DweA3cHndQ27k9bhz48jDKPu76MwBiLUPS0EwoGTYg2NNcAZQMG5KGZoacQcJxiAXsp8QhYU5IyMB+ih3sp8QhYU5IyMB+ih3sp8QiYV5IyMCOksPYshwlhFaXEz98cjqanCd0TxS3x40m5wlMXHQrWl3OuMig2CxIv2YgkGzRX1oKgGRtO8UW+jSTcByIJJEwJyRkYD8RySNhTkjIwH4ikknCvJCQgR0lBxel6LT2HtuPyxZMQU3DUQDo9j2vvp/XNBzFZQumYF9tdVxlsGYlo8e1g6H00PfdAEoPG3pcOxjWrNN/jW4wJBwHIkkkzAkJGdhPRPJImBMSMrCfiGSSMC8kZGBHyRDUt+9RYtpXW40xD1+FkvPGo7R4GgoHDvd7zPZDVVhavgJlH2+MyIqthAzWrGRkTD0Lrt2NcFbWw1vnvw9Lth32gp7a7aBhWD0/lYTjQCSJhDkhIQP7iUgeCXNCQgb2E5FMEuaFhAzsqOjjohTp0upyYuXm9Vi5eT0K+udjeO4wzC2+HY+UL8EnNZ+h8tDOhMig2CxIzs9Ccn4WPLWtsDUBM4umYvHWlXBnIKRvYNBLwnEgkkTCnJCQgf1EJI+EOSEhA/uJSCYJ80JCBnZUdHFRioJWeWgn9hzdj+nDr8PLW99Ei8uRkBmsOSlIzU1FSUkJnmnZmLDHgUgSCXNCQgb2E5E8EuaEhAzsJyKZJMwLCRnYUebjZ0oREREREREREZHpuChFRERERERERESm46IUERERERERERGZTlFVVTVjRx6PBxUVFSi+tBgtqrFPi1cUBdlpPVHXUg8jsdUWN6ACUAAlzdjHaTEDMzBD+DOkKXaUv1uOwsJCWK1WQxlCFWpHhXoMgNDHghmYgRkikyHaHcV+YgZmYIbuxHo/AfHxWpYZmIEZ/OntJ/M/6FwF1BNuo5viWPMxZmAGZoi3DOl249uGm8HjELZxYAZmYAZ5GaR0VKKPAzMwAzP4i/F++nrT2H8tywzMwAz+dPaT+YtSCqCkJ+5qITMwAzN09QSGdhsZBjsqXn7jygzMwAxdPYmxzcKO/cQMzMAMfk9ibLOw4zUeMzADM/g9gb6Hmb4opaRakTl5iKFt05JS8eq0p3D1ihmGvhax8dk9UE+4oaTZkHkzMzADM0jJ4FldY2i/kWC0o0I9BkDoY8EMzMAMkckgpaPYT8zADMxwqljvJyA+XssyAzMwgz+9/cQPOiciIiIiIiIiItNxUYqIiIiIiIiIiEzHRSkiIiIiIiIiIjKd+R90bpCnthWORgfKysrgqDoOT6YCa04KM0QhQ0H/fIzIzUN2djYmFo3DjppdqDy0M+EycCzIR8K5wAwaCXNCQgaOBflIOBeYQSNhTkjIwLGgjiScD8ygkTAvJGTgWJhP9KKU6vbCtbsRzsp6eOucAIB5r89r/3tLth32gp5IGpoJxRaZm76YQZOSZMek0RNQWjwNowac2/7zxTfNBwBsO/gplpavwNotG9DqcsZtBo4F+Ug4F5hBI2FOSMjAsSAfCecCM2gkzAkJGTgW1JGE84EZNBLmhYQMHIvoErso5Wlow4lXDkBtcnf7GG+dE45NX6D1ozqkXzMQ1qxkZohAhrN7D8a6O5ZhQK9ceFVvl48Z0S8Pi274PX49/g5MXHQr9tVWx10GjgX5SDgXmEEjYU5IyMCxIB8J5wIzaCTMCQkZOBbUkYTzgRk0EuaFhAwci+gzvMxXWlqKuXPnhjNLO09DG5rX7Ifa3P2J0ZHa7Ebzmv3wNLQxQ5gznN17MN668yXkZvWBoiiwWqxdPs5qsUJRFORm9cHbd63CWTmD4ioDxyL2RKqjJJwLzKCRMCckZOBYxB72U/xnkDAnJGTgWMQeXuMlRgYJ80JCBo6FDIYWpV577TWUl5eHOwsA7da5E68cANq8gKp3IwBt2naqu+uVRWYIXkqSHevuWIYMezpsVn031dmsNmTY07F+1nKkJNnjIgPHIvZEqqMknAvMoJEwJyRk4FjEHvZT/GeQMCckZOBYxB5e4yVGBgnzQkIGjoUcQS9KNTQ04LHHHsPIkSMjkQeu3Y3arXN6TwwfFVCb3HDtbmSGMGWYNHoCBvTK1T1BfGxWGwae2Q8l542Piwwci9gSyY6ScC4wg0bCnJCQgWMRW9hPiZFBwpyQkIFjEVt4jZc4GSTMCwkZOBZyBL0o9eijj+IHP/gBhgwZEok8cFbWR3V7ZjiptHhat+9pDcTj9aC0eFpcZOBYxJZIdpSEc4EZNBLmhIQMHIvYwn5KjAwS5oSEDByL2MJrvMTJIGFeSMjAsZAjqEWpDz74AP/9738xc+bMiITx1La2f9q9Ud46Jzy1rcwQYoaC/vkYNeDcbt/TGojVYkXhwOEo6J8f0xk4FrElkh0l4VxgBo2EOSEhA8citrCfEiODhDkhIQPHIrbwGi9xMkiYFxIycCxk0X2fmNPpxP3334/77rsPKSkphneoKArSklK7/DtHo8Pw83ZkawJSc/330aQoUJlBV4YRuXlhyTA8dxj2HN0fsxk4FvqkJqV0+jNYzYpiaLuOIt1RkT4XgMBjwQyaSM+JWMnAsdAn1H4CQu8o9lPiZJAwJyRk4Fjokwj9BMh4Pc0MGgnXFRIycCz0MesaT/ei1KJFizBixAhccsklhgL59ErNwtppT3X5d2VlZZj3+ryQnh8AZhZNRUlJid/PJ6ycgGPNx5Cd1hOvMsNpM2RnZ4e8fwCYW3w7pg+/LmYzcCyCs3rKQkPbTVo3KaT9ApHvqEifC0DgsWAGTaTnRKxk4FgEx2g/AaF3FPspcTJImBMSMnAsghPP/QTIeD3NDBoJ1xUSMnAsghPpazxFVVVdH+01duxY1NXVwWrVbi9ra9O+BjE5ORlbt24NuL3H40FFRQW+O+Ey9Jh6VpePcVQdR8Pr1bqCn07W+MFIzevp9/Ojy3bA2+yCpUcS+kwfwQynyTCxaBwW3zQ/5Ay3Pz8XL299M2YzcCz0SU1KweopCzF51Ww4XMHfxtq8ch/e2fA2CgsL2zsmWJHuqEifC0DgsWAGTaTnRKxk4FjoE2o/AaF3FPspcTJImBMSMnAs9EmEfgJkvJ5mBo2E6woJGTgW+ph1jaf7Tqm//e1vcLvd7f//D3/4AwDgzjvvDCqYqqpocXV9u5wnM/S38ACAOwNd7sO3/sYMgTPsqNkVlgw7Du+K6Qwci+A4XK2GnkPn2vhpRbqjIn0u+PbNDIEzRHpOxEoGjkVwjPZTxwxGsZ8SJ4OEOSEhA8ciOPHcT4CM19PMoJFwXSEhA8ciOJG+xtP9Qef9+vXDoEGD2v9JT09Heno6Bg0aFHS47lhzUmDJtof0HJZsO6w5xt8PzQyaykM7se3gp/B4PYa293g9qDjwCbYfrorpDByL2BHpjpJwLjCDRsKckJCBYxE72E+Jk0HCnJCQgWMRO3iNl1gZJMwLCRk4FrIE9e17ZrAXdH2LrlnbM8NJS8tXwKIYO0WsFiuWlq+IiwwcC/KRcC4wg0bCnJCQgWNBPhLOBWbQSJgTEjJwLKgjCecDM2gkzAsJGTgWchhelHrkkUfwyCOPhDMLACBpaCaUDBsQ7B11CqBk2JA0NJMZwpRh7ZYNOHi8Bm6PO/CDO3B73Djw5WGUfbwxLjJwLGJTJDpKwrnADBoJc0JCBo5FbGI/xXcGCXNCQgaORWziNV78Z5AwLyRk4FjIIe5OKcVmQfo1A4Fki/4TRAGQrG2n2EL/V2IGTavLiR8+OR1NzhO6J4rb40aT8wQmLroVrS5nXGTgWJCPhHOBGTQS5oSEDBwL8pFwLjCDRsKckJCBY0EdSTgfmEEjYV5IyMCxkEPcohQAWLOS0ePawVB66PscdqWHDT2uHQxrVjIzhDnD3mP7cdmCKahpOAoA3b7n1ffzmoajuGzBFOyrDf3bDCRl4FiQj4RzgRk0EuaEhAwcC/KRcC4wg0bCnJCQgWNBHUk4H5hBI2FeSMjAsZBB97fvmc2alYyMqWfBtbsRzsp6eOv8VwEt2XbYC3pqt96FYaWSGbq2r7YaYx6+CiXnjUdp8TQUDhzu95jth6qwtHwFyj7eGJEVWwkZOBbkI+FcYAaNhDkhIQPHgnwknAvMoJEwJyRk4FhQRxLOB2bQSJgXEjJwLKJP7KIUoN1Sl5yfheT8LHhqW2FrAmYWTcXirSvhzkBIn3bPDMFpdTmxcvN6rNy8HgX98zE8dxjmFt+OR8qX4JOaz1B5aGdCZOBYkI+Ec4EZNBLmhIQMHAvykXAuMINGwpyQkIFjQR1JOB+YQSNhXkjIwLGILpFv3+uKNScFqXk9UVJSgtS8nqacGMzQtcpDO/Hy1jdRV1eHl7e+GZUJIiEDx4J8JJwLzKCRMCckZOBYkI+Ec4EZNBLmhIQMHAvqSML5wAwaCfNCQgaOhfliZlGKiIiIiIiIiIjiBxeliIiIiIiIiIjIdFyUIiIiIiIiIiIi0ymqqqpm7Mjj8aCiogLFlxajRTX2afGKoiA7rSfqWuphJLba4gZUAAqgpBn7jHdmYAZmCH+GNMWO8nfLUVhYCKvVaihDqELtqFCPARD6WDADMzBDZDJEu6PYT8zADMzQnVjvJyA+XssyAzMwgz+9/WT+t++pgHrCbXRTHGs+xgzMwAzxliHdbnzbcDN4HMI2DszADMwgL4OUjkr0cWAGZmAGfzHeT19vGvuvZZmBGZjBn85+Mn9RSgGU9MRdLWQGZmCGrp7A0G4jw2BHxctvXJmBGZihqycxtlnYsZ+YgRmYwe9JjG0WdrzGYwZmYAa/J9D3MNMXpZRUKzInDzG0bVpSKl6d9hSu/v/snXt8FPW99z+z1yyQGDCBEq4qECIYgiheWotirYLVYwNKBeqxKlgROKen9niptfVowXppfQSxRVHbIgglAfWIVitP84gibTEXUIJcwyUIiRCSkE2yl3n+GDYmJGFnZ3Znv7v7eb9evGg3O/N7+/1958PsL7Mzy2ehyeeNePv6V3dBPemH0sOBjNvpQAc6SHEIrK42NG4sMJpRZmsAmJ8LOtCBDrFxkJJRzCc60IEOp5Po+QQkx7ksHehAh87ozSfe6JwQQgghhBBCCCGEWA4XpQghJJkIBuNtQAiRCLOBEEIIIQKx/p5ShBBCosaYmmbM2F6Hy6q9yD3eCtez47HPpmBHbxc25XjwWl4myrPT4q1JCLEYZgMhhBBCEgEuSiUY+QPzMDonF1lZWbhp7LXYVr0DFQe3W+oQqGmGt96L4uJieCuPIZChwG7xiS3roME6pC7n1LVi8YbD+OZhL3wKsE0FigA0AEgPqhj5VQt+dKwFs7fW4aP+Hsyd2B97M10xdZLQCxIceFxqsA7x4fRscI4pAK4ZCaSnw9XQgAsqKzGyvMzSbJDQC3SQ4yDhuGQd5CBhLuhAh/ZIODZTzYGLUglAmtONKeMmY/aEmRgz6Py215fcthAAUH7gcywtWY6iLevR7GuJiYPqD8K3sx4tFccRrNXGWPDugraf27LccOf3hnN4BhRHbL4VyjposA5k6hcn8PyGL9EaUPEKgOdUoKyL9xWowHwAUw978cnrezFnYn8UjciIqouEXpDgwONSg3WIL6FssLvcwO23wzl/PjB2bKf3OUtLgeeewyWrXo9ZNkjoBTrIcZBwXLIOcpAwF3SgQ3skHJup7MBFKeGc13co1t77Egb1yUFQ7fp+EKMH5GLxjF/j/kn34qbFd2JPTVVUHQJ1rTj55n6oDf5u3xOsbYF3w5do/mctet44GPYo/9aVddBgHcjUL05g6fuH8QWA6wBUofubA1YAuAPAowD+GlDx4vvVUKBizYizouIioRckOPC41GAd4ksoGzB8OGzvvQcMGdL9faTy84GXX4bjl7+E7Zpr8OL7u6KaDRJ6gQ5yHCQcl6yDHCTMBR3o0B4Jx2aqO0S8vPX+++8jNze3w5/58+dHRYZ05Ly+Q/G3+15HTmY/KIoCu83e5fvsNjsURUFOZj988LNVODd7SNQcAnWtaFyzD2pj983ZHrXRj8Y1+xCoa42aA+ugwTqEJ9nz6dy6Vjy/4Ut8AeByAAdPvd7d7YtDrx8EcBmAnQCe3/AlzonCfEjoBQkOPC41WIfwxDKfQtmA4cNh++QTYMAAQFEAe9fzALtd+/mAAbBt3gwMGxa1bJDQC3SQ4yDhuGQdwmPV+ZOEuaADHdoj4dikg4FFqV27duGqq67Cxo0b2/48/vjjUZEhX5PmdGPtvS8h3d0TDru+C9ocdgfS3T2xbu4ypDndph1UfxAn39wPtAYBVe9GAFq17VS/+Sf9sA4arIM+kj2fFm04jJaAiusA1AMI6NwucOr91wJoDahYvOGwKQ8JvSDBgcelBuugj1jm06INh2FzubUrpNLTAadT34ZOJ5CeDtv778PucpvOBgm9QAc5DhKOS9ZBH1acP0mYCzrQoT0Sjk06aES8KLV7926MGDEC2dnZbX8yMqJ7HwICTBk3GYP65Og+SEM47A4MPnsACi+cZNrBt7Neu3xPb3OGUAG1wQ/fznrTDqyDBuugj2TOpzFHm/HNw14UQfvKnt4FqRCBU9sVAfjmYS/G1DQbdpHQCxIceFxqsA76iFU+hbLBOe0H2lf29C5IhXA6gaFD4bhlmulskNALdJDjIOG4ZB30YcX5k4S5oAMd2iPh2KSDhqFFqaFDh5oemJyZ2RNmdvu92nAEggHMnjDTtENLxfG4bg+wDiFYB30kcz7NqKyDTwGeg4HgPoUN2vY+BZixvc6wi4RekODA41KDddBHrPIplA2YP7/7e0iFIxAA5s0znQ0SeoEOchwkHJesgz6sOH+SMBd0oEN7JBybdNCI6LONqqrYu3cvNm7ciGuvvRbf+c538PTTT6O11ZrvO6cK+QPzMGbQ+d1+rzYcdpsdBYNHIX9gnmGHQE1z2x33jRKsbUHAxG9cWQcN1kEfyZ5Pl1V7se3UU/aMXiQbBFAKYJsKXHrYa2gfEnpBggOPSw3WQR+xzKfLqr1wjinQnrLX3T2kwmG3A+PGwTmmwHA2SOgFOshxkHBcsg76sOL8ScJc0IEO7ZFwbNLhayK6Xq66uhperxculwvPPvssDh48iMcffxzNzc14+OGHde1DURT0cHoMyXqcaR3+jpQGRYGaAA6jc3IN7ft0RuWMwK4j+ww5eOuNnZSejqMB8OR0HoN10O+QCnVoVBTT+45GPgHG88FsNgBnnovc460oMrznjuwAUHistcv/znD9EOteSBSHWB+XehxYBw0r6mA2o2KZT7nHW4FrRpry+3pnuRhZUW4oGyT0Ah3kODCfNFI9n0JIOJelAx3aI+EzXio46M0nRVXViL49WFdXh7POOgvKqQH++te/4mc/+xlKS0thP8Nv6AKBAMrKyjBlyhQUFUXro1VkTJ48GUePHkXfvn2xfv16sQ5ZWVkYMsT8UwWqqqpQW1tryKG4uBgLFiww7fDQQw+hsLDQkAProJEKdQjlQkFBwRlzJBxG8wkQnlHBIMaNH4+lAO6Owjh/ADAbwJZ//AOwdbxgNlw/xLoXEsUh1selHgfWQcOKOkQjo2KST6eyAbNmAUuXGvLqwOzZwIsvGsoGCb1ABzkOzCeNlM6ndkg4l6UDHdoj4TNeKjjozafI7iwGIDMzs8P/P++889DS0oITJ06gT58+Ybc/5q3DDctnRTosAO0KhNXTFuGWVfPg9UV+iVht0/G2vyU73DT2Wiy5baEhv/Y8UfIC3ih9z5CDt/KY6fEBYEnpCrzS9I4hB9ZBIxXq0Oiti8r+zeYTYDyjzGYDcOa52GdTkB6M9A6EXZMBoNWm4IYVnZe4wvVDrHshURxifVzqcWAdNKyoQzQyKlb5tM+mwNXQYNoPAFBfbzgbJPQCHeQ4MJ80Uj2fQkg4l6UDHdoj4TNeKjjozaeIFqU+/PBD3Hffffj73/8Oj0e7PGv79u3IzMzUHViqqqLJZ+4yMa+v2dA+QheFSXfYVr3DlFvbfg7t6HIMPQ6BDPNfpwIAfzoMO7AOGqlUBzNEI59CLmbywWg2hMbuzmFHbxdGfmXuO98hRgKo7OMy1A+x7oVEcYj1canHgXXQsLIORollPu3o7cIFlZWm/NqorDScDRJ6gQ5yHJhPGqmeTyEknMvSgQ7tkfAZL5UcwhHRjc7Hjh0Lt9uNhx9+GHv27EFJSQmefPJJ3HXXXZHshoSh4uB2lB/4HIFgpA991wgEAyjb/xm2HjJ+kmrPToMty214ewCwZblhzzZ+fx3WQYN10Eey59OmHA9GK0ABzD19byyAUQrwSX9j99WT0AsSHHhcarAO+ohlPm3K8cBXXgaUlmpP0TNCIABs2QJfRbnhbJDQC3SQ4yDhuGQd9GHF+ZOEuaADHdoj4dikQ7t9RPLmXr16YdmyZTh27BimTJmCn//855g2bVrSfOiTxNKS5bApxj562m12LC1ZbtrBnd87rtsDrEMI1iE8yZ5Pr+VlwqkC82Hu6XvzAThVbX9GkdALEhx4XGqwDuGJZT6FsgHPPdfpPlC6sduBRYtMZ4OEXqCDHAcJxyXrEB6rzp8kzAUd6NAeCccmHTQi7oThw4fjlVdeQWlpKTZu3Ii5c+e23RSPRI+iLetx4Fg1/AF/RNv5A37s/+oQij/t+nvnkeAcngEl3QFEOr0KoKQ74ByeYdqBddBgHfSRzPlUnp2Gj/p7MBXAEACR3srUfmq7KQA+6u9BuYnfaEjoBQkOPC41WAd9xCqfQtngX/U6UFUF+HyR7cDnA/btg3/1KtPZIKEX6CDHQcJxyTrow4rzJwlzQQc6tEfCsUkHDaPfAiExptnXgu8/fxcaWk7qPlj9AT8aWk7ipsV3otln/t4zisOGnjcOBlw2/U2qAHBp2ykO8+3FOmiwDgQA5k7sD5ddwbvQblaud2HKfur9fwXgsiuYO7G/KQ8JvSDBgcelBusQf+ZO7I9AawuC3/0u0NCgf2HK5wMaGhC85hoEWltMZ4OEXqCDHAcJxyXrIAcJc0EHOrRHwrFJB43kSLkkZffRfbj6qWmorjsCAN1+7zb0enXdEVz91DTsqamKmoM904VeU4dC6aXvnvhKLwd6TR0Ke6Yrag6sgwbrQPZmujBnYn+MALAJwMBTr3cX5KHXB556/3AAcyb2x94ozIeEXpDgwONSg3WIL6FswM6dCF5yCXDokPaD7u4xFXr90CHt/bt2RS0bJPQCHeQ4SDguWQc5SJgLOtChPRKOTTpE+PQ9Yj17aqow/vHrUXjhJMyeMBMFg0d1es/Wg5VYWrIcxZ++E5VV49OxZ7qQPv1c+HbWo6XiOIK1ncewZbnhzu+tXf4Xg9/osA4arAMpGpEBBSqe3/AltgZUFAF4DkBpF+8dA+0eUlOgXSE1a2J/FI2I3tcAJPSCBAcelxqsQ3z5Oht2w35+Hhy3TAPmzQPGjev85rIyYNEi+FevQqC1BXOuyYlqNkjoBTrIcZBwXLIOcpAwF3SgQ3skHJup7sBFqQSg2deCFZvXYcXmdcgfmIdROSPwwIR78ETJC/is+gtUHNwecwfFYYMrLxOuvEwEaprhaADmjJ2OJaUr4E9HTJ8KEoJ10GAdyJoRZ2FLXw8WbziM2w97MUMBtqnADgD10L6qlwtgtKLd1HxjjgfzrorOVRCnI6EXJDjwuNRgHeJL+2z45h//CN+f/gjnmAIgNxfIyADq64EdO+ArL4NTBT7J8WDeVefEJBsk9AId5DhIOC5ZBzlImAs60KE9Eo7NVHbgolSCUXFwO3Yd2Ye7Rt2MN0rfQ5PPa7mDPTsNnhwPCgsL8UrTO3FxYB00WIfUZW+mC9cXDsGYmmbM2F6HSw97UXisFa6gilabgso+LrzS34PX8jJN3bg4EiT0ggQHHpcarEN86JQNB7djZEV5h2z4ZHSmpdkgoRfoIMdBwnHJOshBwlzQgQ7tkXBsppoDF6UIISSBKc9OQ3n2NwAAPZwevDX9D7hhxd0pe3JLCNFgNhBCCCEkEUjOLysTQkiqYmOsE0K6gNlACCGEEIHwDIUQQgghhBBCCCGEWI6iqqpqxUCBQABlZWWYcOUENKnG7pqvKAqyevRGbdNxGNFWm/yACkABlB7GvrlIBzrQIfoOPRQ3Sv5egoKCAtjtdkMOZjGbUWZrAJifCzrQgQ6xcYh3RjGf6EAHOnRHoucTkBznsnSgAx06ozefrL+nlAqoJ/1GN8XRxqN0oAMdks2hp9v4ttHGYB2iNg90oAMd5DlIyahUnwc60IEOnUnwfDq1aeKfy9KBDnTojM58sn5RSgGUnqm7WkgHOtChqx0YGjY2GMyoZPmNKx3oQIeudmJss6jDfKIDHejQaSfGNos6/IxHBzrQodMO9L3N8kUpxWNHxi3DDG3bw+nBWzNfxA3LZxl6ekz9q7ugnvRD6eFAxu10oAMdpDgEVlcbGjcWGM0oszUAzM8FHehAh9g4SMko5hMd6ECH00n0fAKS41yWDnSgQ2f05hNvdE4IIYQQQgghhBBCLIeLUkYIBuNtQAghhBBCCCGEEBI7LFj7sP6eUgnImJpmzNheh8uqvcg93grXs+Oxz6ZgR28XNuV48FpeJsqz0+KtSQghhBBCCCGEEGKIeKx9cFHqDJxT14rFGw7jm4e98CmAc0wBcM1IID0droYGXFBZiZHlZZi9tQ4f9fdg7sT+2JvpiqlT/sA8jM7JRVZWFm4aey22Ve9AxcHtMR2TDnQg8gnUNMNb70VxcTG8lccQyFBgt3ixXIKDhGOCDnIciAwk9ALziQ7SHIgcJPSDhIyiQ2o7nL72sU0FigA0AEgPqhj5VQt+dKwlJmsfXJTqhqlfnMDzG76E3eUGbr8dzvnzgbFjO73PWVoKPPccLln1Oj55fS/mTOyPohEZUXVJc7oxZdxkzJ4wE2MGnd/2+pLbFgIAyg98jqUly1G0ZT2afS1RHZsOdCByUf1B+HbWo6XiOIK12lwveHdB289tWW6483vDOTwDiiM239aW4CDhmKCDHAciAwm9wHyigzQHIgcJ/SAho+hAB+DrtY/WgIpXADynAmVdvK9ABeYDmHrYG9W1Dy5KdcHUL05g6fuHgeHDYXvvPWDIkO6/S5mfD7z8Mhy//CVs11yDF9/fBQUq1ow4Kyou5/UdirX3voRBfXIQVLt2GD0gF4tn/Br3T7oXNy2+E3tqqqIyNh3oQOQSqGvFyTf3Q23wd/ueYG0LvBu+RPM/a9HzxsGwR/lKTgkOEo4JOshxIDKQ0AvMJzpIcyBykNAPEjKKDnQAvl77+ALAdQCq0P2NxysA3AHgUQB/Dah48f3qqKx98Ebnp3FuXSue3/CltiD1ySfAgAGAogB2e9cb2O3azwcMgG3zZmDYMDy/4UucU9dq2uW8vkPxt/teR05mPyiKArutawe7zQ5FUZCT2Q8f/GwVzs0eYnpsOtCByCVQ14rGNfugNnb/D1d71EY/GtfsQyAKuSTJQcIxQQc5DkQGEnqB+UQHaQ5EDhL6QUJG0YEOwNdrH18AuBzAwVOvd3dr89DrBwFcBmAnEJW1j4gXpVpbW/Hoo4/i4osvxuWXX47f/va3UFXVlIQkFm04DJvLrV0hlZ4OOJ36NnQ6gfR02N5/H3aXG4s3HDblkeZ0Y+29LyHd3RMOu74L2hx2B9LdPbFu7jKkOd2mxqcDHRKRZM8nQLu09+Sb+4HWIKD3P00F0Kptp/rNP0FDgoOEY4IOchwSgVTIJwm9wHyigzSHRCAV8gmQ0Q8SMooOdAixaMNhtARUXAegHkBA53aBU++/FkBrQDW99hHxotTjjz+Ojz/+GMuWLcMzzzyD1atXY9WqVaYkpDDmaDO+edgL57QfaF/Z07sgFcLpBIYOheOWafjmYS/G1DQbdpkybjIG9cnRHZghHHYHBp89AIUXTjI8Nh3okKgkcz6F8O2s1y7tjfRcUQXUBj98O+uTwkHCMUEHOQ6JQCrkk4ReYD7RQZpDIpAK+QTI6AcJGUUHOgBfr30UQfvKnt4FqRCBU9sVAabXPiJalKqrq0NRUREee+wx5Ofn47LLLsMdd9yB8vJywwKSmFFZB58CYP787u8hFY5AAJg3Dz4FmLG9zrDL7Akzu/2Oc1iFYACzJ8w0PDYd6JCIJHs+hWipOB7X7aU4SDgm6CDHQTqpkk8SeoH5RAdpDtJJlXwCZPSDhIyiAx2Ar9c+noPxezrZoG1vdu0jovG3bNmCXr16Yfz48W2vzZ49GwsXLjQsIInLqr1wjinQnrLX3T2kwmG3A+PGwTmmAJce9hraRf7APIwZdH6333EOq2Czo2DwKOQPzDO0PR3okIgkez4B2uNhQ0/jMEqwtgUBE7/JkOAg4ZiggxyHRCAV8klCLzCf6CDNIRFIhXwCZPSDhIyiAx1CXFbtxbZTT9kz+iXAIIBSANtUGF77ACJ8+t6BAwcwYMAArFu3Dr///e/h8/lQWFiIe+65BzabvvUtRVHQw+kxJOtxpnX4O1IaFAXqGRxyj7cC14w0tO/OO8vFyIryTuOEcwCA0Tm5UVEYlTMCu47s6/Q6HegQqUM4zB6bjYpiaLv2RCOfAON1MFsDIPxceOuNh317HA2AJ6fr/8ZEcIj1MUGHxHIIRzSOTbMZlQr5JKEXmE90kOYQDuaTRqw/4wEyzqdjnVF0oEMkDrnHW1EUFQNgB4DCY62dxtGbTxEtSjU1NaGqqgqvv/46Fi5ciJqaGjzyyCPweDy44447dO2jjycTRTNfjGTYTqyetsjQdpNXTMbRxqPI6tEbb53uEAzC9ex47ebm0SAjA66girem/wFoF+hndDhFVlZWVBQemHAP7hp1c6fX6UCHSB30YvTYnLJ2iqlxgejkE2A+o4zWAAg/F8XFxVjw7gLD+w8xZ+x0FBYWJqxDrI8JOiSWg17MHJtmMyoV8klCLzCf6CDNQS/MJ42YfMY7hYTz6VhnFB3ooNvh1NpHg+nRNeqBLtc+9OZTRItSDocDjY2NeOaZZzBgwAAAQHV1NVauXKk7tI5563DD8lmRDNuGx5mG1dMW4ZZV8+D1RX6ZWm3T8ba/u3LYZ1PgaojS1NTXo9Wm4IYVd0fkAAA3jb0WS24zf8nsEyUv4I3S9zq9Tgc6ROoQDrPHZqO3ztC47YlGPgHGM8psDYDwc+GtPGZov6ezpHQFXml6J2EdYn1M0CGxHMIRjWPTbEalQj5J6AXmEx2kOYSD+aQR6894gIzz6VhnFB3oEInDPpuC9GB0nrKZAXS59qE3nyJalMrOzobb7W4LLAA455xzcPiw/kcAqqqKJp+5S9W8vmZD+wg92rQ7hx29XbigstKUWxuVlajs4+o0TjgHANhWvSMqCtsO7ehyDDrQIVIHvZg9Ns0QjXwKuZipg9EahMY+k0Mgw/zXHAHAn45uHRPBIdbHBB0Sy0Ev0Tg2jZIK+SShF5hPdJDmoBfmk0asPuMBMs6nY51RdKBDJA47ersw8itz97QKMRI449pHOCK60fmYMWPQ0tKCvXv3tr22Z8+eDiGWyGzK8cBXXgaUlmpP0TNCIABs2QJfRTk+6W/se9UVB7ej/MDnCASNOQSCAZTt/wxbDxlfYKMDHRKNZM8nALBnp8GW5Ta1D1uWG/Zs4/eukOAg4ZiggxyHRCAV8klCLzCf6CDNIRFIhXwCZPSDhIyiAx1CbMrxYLQCFMDc0/fGAhilwPDaR2g/ujn33HNx5ZVX4sEHH0RlZSU+/PBDLF26FLfeeqthAUm8lpcJpwrguec6fBcyIux2YNEiOFVtf0ZZWrIcNsWYg91mx9KS5YbHpgMdEpFkz6cQ7vzecd1eioOEY4IOchykkyr5JKEXmE90kOYgnVTJJ0BGP0jIKDrQAfh67WM+zD19bz5geu0j4qPy6aefxuDBg3Hrrbfi/vvvx4wZM/DDH/7QsIAkyrPT8FF/D/yrXgeqqgCfL7Id+HzAvn3wr16Fj/p7UG5i5bRoy3ocOFYNf8Af0Xb+gB/7vzqE4k+7vhcCHeiQzCRzPoVwDs+Aku4AIr3iVwGUdAecwzOSwkHCMUEHOQ6JQCrkk4ReYD7RQZpDIpAK+QTI6AcJGUUHOgBfr31MBTAEgD3C7e2ntpsCmF77iHhRKj09HU8++SRKS0vx8ccfY+7cuVCi8Dh3Kcyd2B+B1hYEv/tdoKFB/8KUzwc0NCB4zTUItLZg7sT+pjyafS34/vN3oaHlpO7g9Af8aGg5iZsW34lmn/nvh9KBDolGsucTACgOG3reOBhw2fT/A6YAcGnbKQ6jF+jKcpBwTNBBjkMikAr5JKEXmE90kOaQCKRCPgEy+kFCRtGBDiHmTuwPl13Bu9BuVq53Ycp+6v1/BeCyK6bXPsxXMsnYm+nCnIn9gZ07EbzkEuDQIe0H3d1jKvT6oUPa+3ftwpyJ/bE302XaZffRfbj6qWmorjuiDdXNd6BDr1fXHcHVT03Dnpoq02PTgQ5ELvZMF3pNHQqll75nVSi9HOg1dSjsUcglSQ4Sjgk6yHEgMpDQC8wnOkhzIHKQ0A8SMooOdAC+XvsYAWATgIGnXu9ukSj0+sBT7x8ORGXtI6Kn76UKRSMyoEDF8xt2w35+Hhy3TAPmzQPGjev85rIyYNEi+FevQqC1BXOuyUHRCPOX8oXYU1OF8Y9fj8ILJ2H2hJkoGDyq03u2HqzE0pLlKP70nZj8RocOdCDysGe6kD79XPh21qOl4jiCtZ3n2pblhju/t3ZpcBR+myPRQcIxQQc5DkQGEnqB+UQHaQ5EDhL6QUJG0YEOQPu1jy+xNaCiCMBzAEq7eO8YaPeQmgLtCqlZE/tHZe2Di1LdsGbEWdjS14PFGw7jm3/8I3x/+iOcYwqA3FwgIwOorwd27ICvvAxOFfgkx4N5V50TlSukTqfZ14IVm9dhxeZ1yB+Yh1E5I/DAhHvwRMkL+Kz6C1Qc3B71MelAByIfxWGDKy8TrrxMBGqa4WgA5oydjiWlK+BPh6kngiSSg4Rjgg5yHIgMJPQC84kO0hyIHCT0g4SMogMdgI5rH7cf9mKGAmxTgR0A6qF9VS8XwGhFu6n5xhwP5l0VnW+HAVyUOiN7M124vnAIxtQ0Y8b2Olx6cDtGVpTDFVTRalNQ2ceFT0Zn4rW8TFM39oqEioPbsevIPtw16ma8UfoemnxeS8alAx2IbOzZafDkeFBYWIhXmt6JSy9IcJBwTNBBjgORgYReYD7RQZoDkYOEfpCQUXRIbYdOax+HvSg81tph7eOV/p6YrH1wUUoH5dlpKM/+BgCgh9ODt6b/ATesuJv/gBFCCCGEEEIIISQpiMfaB290bgQby0YIIYQQQgghhJAkxoK1D66uEEIIIYQQQgghhBDLUVRVVa0YKBAIoKysDBOunIAm1dgTDBRFQVaP3qhtOg4j2mqTH1ABKIDSw9g3F+lABzpE36GH4kbJ30tQUFAAu91uyMEsZjPKbA0A83NBBzrQITYO8c4o5hMd6ECH7kj0fAKS41yWDnSgQ2f05pP195RSAfWk3+imONp4lA50oEOyOfR0G9822hisQ9TmgQ50oIM8BykZlerzQAc60KEzCZ5PpzZN/HNZOtCBDp3RmU/WL0opgNIzdVcL6UAHOnS1A0PDxgaDGZUsv3GlAx3o0NVOjG0WdZhPdKADHTrtxNhmUYef8ehABzp02oG+t1m+KKV47Mi4ZZihbXs4PXhr5ou4YfksQ3d/r391F9STfig9HMi4nQ50oIMUh8DqakPjxgKjGWW2BoD5uaADHegQGwcpGcV8ogMd6HA6iZ5PQHKcy9KBDnTojN584o3OCSGEEEIIIYQQQojlcFGKEEIIIYQQQgghhFgOF6UIIYQQQgghhBBCiOVYf6PzBCZ/YB5G5+QiKysLN429Ftuqd6Di4HY6xMEhUNMMb70XxcXF8FYeQyBDgT07LeUcJMwFkQH7UUNCHeigIaEfiAzYjxoS6kAHDQn9QOTAntSQUAc6yHGwEi5KhSHN6caUcZMxe8JMjBl0ftvrS25bCAAoP/A5lpYsR9GW9Wj2tdAhhg6qPwjfznq0VBxHsFYbY8G7C9p+bstyw53fG87hGVAcsbkIUIKDhLkgMmA/akioAx00JPQDkQH7UUNCHeigIaEfiBzYkxoS6kAHOQ7xgotSZ+C8vkOx9t6XMKhPDoJqsMv3jB6Qi8Uzfo37J92LmxbfiT01VXSIgUOgrhUn39wPtcHf7XuCtS3wbvgSzf+sRc8bB8Oe6Uo6BwlzQWTAftSQUAc6aEjoByID9qOGhDrQQUNCPxA5sCc1JNSBDnIc4klyLbFFkfP6DsXf7nsdOZn9oCgK7DZ7l++z2+xQFAU5mf3wwc9W4dzsIXSIskOgrhWNa/ZBbez+IG2P2uhH45p9CNS1JpWDhLkgMmA/akioAx00JPQDkQH7UUNCHeigIaEfiBzYkxoS6kAHOQ7xJqJFqeLiYuTm5nb6M3LkyFj5xYU0pxtr730J6e6ecNj1XUzmsDuQ7u6JdXOXIc3ppkOUHFR/ECff3A+0BgFV70YAWrXtVH/Xv3lINAcJcyGdVMkn9qOGhDrQQUNCP0iH+XSmjZB0/SihDnTQkNAPiQAz6kwbIel6UkId6CDHQQIRLUpNnjwZGzdubPvz97//HUOGDMFtt90WK7+4MGXcZAzqk6M7KEI47A4MPnsACi+cRIcoOfh21muXMeo9SEOogNrgh29nfVI4SJgL6aRKPrEfNSTUgQ4aEvpBOsynMCRZP0qoAx00JPRDIsCMCkOS9aSEOtBBjoMEIlqUSktLQ3Z2dtufN998E6qq4r777ouVX1yYPWFmt9/tDUcgGMDsCTPpECWHlorjcd1eioOEuZBOquQT+1FDQh3ooCGhH6TDfLJme0BGP0qoAx00JPRDIsCMsmZ7QEZPSqgDHeQ4SMDwPaXq6urw4osv4qc//SlcruS5yVb+wDyMGXR+t9/tDYfdZkfB4FHIH5hHB5MOgZrmticPGCVY24JATXNCO0iYi0QjWfOJ/aghoQ500JDQD4kG86l7kqEfJdSBDhoS+iERYUZ1TzL0pIQ60EGOgxQMP31v5cqV6Nu3L6677rqItlMUBT2cHkNjepxpHf6OlAZFgRrGYXROrqF9n86onBHYdWQfHUw4eOu9UXFwNACenM5jJIqDhLkIh9ljs1FRDG3XHUbzCTBeB7M1AMLPRaz7UY9DrPtRj4OEOtBBQ0I/hCMax2Y0M4r5dGYSvR8l1IEOGhL6IRzS8glI3s94PKfXkFAHOshxCIdVn/EMLUqpqoq//OUvuOuuuyLeto8nE0UzXzQybBurpy0ytN3kFZNxtPEosnr0xlvdOGRlZZlRa+OBCffgrlE308GEQ3FxMRa8u8C0w5yx01FYWJiwDhLmQi9Gj80pa6eYGrc9ZvIJMJ9RRmsAhJ+LWPejHodY96MeBwl1oIOGhH7Qi5ljM1oZxXwKT6L3o4Q60EFDQj/oRUI+Acn9GY/n9BoS6kAHOQ56ifVnPEOLUlu3bsWRI0dw/fXXR7ztMW8dblg+y8iw8DjTsHraItyyah68vsgvU6ttOt72d3cON429FktuW2jIrz1PlLyAN0rfo4MJB2/lMdPjA8CS0hV4pemdhHWQMBfhMHtsNnrrDI3bFWbyCTCeUWZrAISfi1j3ox6HWPejHgcJdaCDhoR+CEc0js1oZRTzKTyJ3o8S6kAHDQn9EA5J+QQk92c8ntNrSKgDHeQ4hMOqz3iGFqU+/PBDXHTRRTjrrLMi3lZVVTT5zF2q5vU1G9qHqqphHbZV7zDl1rafQzu6HIMO+h0CGdG5HNmfjoR2kDAXejF7bEYDM/kUcjFTB6M1CI19JodY96Meh1j3ox4HCXWgg4aEftBLNI5NszCfwpPo/SihDnTQkNAPepGQT0Byf8bjOb2GhDrQQY6DXmL9Gc/Qjc4rKipw4YUXGtlUPBUHt6P8wOcIBAOGtg8EAyjb/xm2Hqqkg0kHe3YabFluw9sDgC3LDXu28e/pS3CQMBeJRDLnE/tRQ0Id6KAhoR8SCebTmUmGfpRQBzpoSOiHRIMZdWaSoScl1IEOchykYGhRaufOnRg2bFi0XcSwtGQ5bIqxBxPabXYsLVlOhyg5uPN7x3V7KQ4S5iJRSPZ8Yj9qSKgDHTQk9EOiwHyK7faAjH6UUAc6aEjoh0SCGRXb7QEZPSmhDnSQ4yABQ0dEbW0tMjIyou0ihqIt63HgWDX8AX9E2/kDfuz/6hCKP+36u+90iBzn8Awo6Q4g0qsbFUBJd8A53HyfSnCQMBeJQrLnE/tRQ0Id6KAhoR8SBeZTNyRZP0qoAx00JPRDIsGM6oYk60kJdaCDHAcJGP763hVXXBFtFzE0+1rw/efvQkPLSd2B4Q/40dByEjctvhPNvhY6RMlBcdjQ88bBgMum/2BVALi07RSHsd9ESHOQMBeJQrLnE/tRQ0Id6KAhoR8SBeZTVxsh6fpRQh3ooCGhHxIJZlRXGyHpelJCHeggx0ECyfFfEQN2H92Hq5+ahuq6IwDQ7Xd/Q69X1x3B1U9Nw56aKjpE2cGe6UKvqUOh9NJ3X36llwO9pg6FPdOVVA4S5oLIgP2oIaEOdNCQ0A9EBuxHDQl1oIOGhH4gcmBPakioAx3kOMQbQ0/fSxX21FRh/OPXo/DCSZg9YSYKBo/q9J6tByuxtGQ5ij99Jya/TaGDhj3ThfTp58K3sx4tFccRrO08hi3LDXd+b+0yyBisGktwkDAXRAbsRw0JdaCDhoR+IDJgP2pIqAMdNCT0A5EDe1JDQh3oIMchnnBRKgzNvhas2LwOKzavQ/7APIzKGYEHJtyDJ0pewGfVX6Di4HY6WOSgOGxw5WXClZeJQE0zHA3AnLHTsaR0BfzpsOTJAxIcJMwFkQH7UUNCHeigIaEfiAzYjxoS6kAHDQn9QOTAntSQUAc6yHGIF8m1xBZjKg5uxxul76G2thZvlL4Xl3+86KBhz06DJ7c3CgsL4cntHZeDVIKDhLkgMmA/akioAx00JPQDkQH7UUNCHeigIaEfiBzYkxoS6kAHOQ5WwkUpQgghhBBCCCGEEGI5XJQihBBCCCGEEEIIIZbDRSlCCCGEEEIIIYQQYjmKqqqqFQMFAgGUlZVhwpUT0KQae3qAoijI6tEbtU3HYURbbfIDKgAFUHoYu8c7HehAh+g79FDcKPl7CQoKCmC32w05mMVsRpmtAWB+LuhABzrExiHeGcV8ogMd6NAdiZ5PQHKcy9KBDnTojN58sv7peyqgnvQb3RRHG4/SgQ50SDaHnm7j20Ybg3WI2jzQgQ50kOcgJaNSfR7oQAc6dCbB8+nUpol/LksHOtChMzrzyfpFKQVQeqbuaiEd6ECHrnZgaNjYYDCjkuU3rnSgAx262omxzaIO84kOdKBDp50Y2yzq8DMeHehAh0470Pc2yxelFI8dGbcMM7RtD6cHb818ETcsn4Umnzfi7etf3QX1pB9KDwcybqcDHeggxSGwutrQuLHAaEaZrQFgfi7oQAc6xMZBSkYxn+hABzqcTqLnE5Ac57J0oAMdOqM3n3ijc0IIIYQQQgghhBBiOVyUIoQQQgghhBBCCCGWw0UpQgghhBBCCCGEEGI51t/oPIEJ1DTDW+9FcXExvJXHEMhQYM9OSzkHCUiogwQHQkJI6EcJDhKQUAcJDoSEkNCPEhwkIKEOEhwIaY+EnpTgIAEJdZDgkGpwUSoMqj8I3856tFQcR7C2BQCw4N0FbT+3Zbnhzu8N5/AMKI7YXHgmwUECEuogwYGQEBL6UYKDBCTUQYIDISEk9KMEBwlIqIMEB0LaI6EnJThIQEIdJDikMlyUOgOBulacfHM/1AZ/t+8J1rbAu+FLNP+zFj1vHAx7pivpHCQgoQ4SHAgJIaEfJThIQEIdJDgQEkJCP0pwkICEOkhwIKQ9EnpSgoMEJNRBgkOqw2W+bgjUtaJxzT6ojd03Z3vURj8a1+xDoK41qRwkIKEOEhwICSGhHyU4SEBCHSQ4EBJCQj9KcJCAhDpIcCCkPRJ6UoKDBCTUQYIDMbAodfjwYdx999248MILMXHiRLz66qsx0Iovqj+Ik2/uB1qDgKp3IwCt2naqP5gUDhKQUAcJDkQfzKfuNgKPiRggoQ4SHIg+mE/dbQQeEzFAQh0kOBB9pEI+ATJ6UoKDBCTUQYID0Yh4Ueo///M/0aNHDxQXF+Ohhx7Cs88+i/fffz8WbnHDt7Neu3xPb3OGUAG1wQ/fzvqkcJCAhDpIcCD6YD6dAR4TUUdCHSQ4EH0wn84Aj4moI6EOEhyIPlIhnwAZPSnBQQIS6iDBgWhEtCh14sQJlJWV4Z577sHQoUPxne98B1dccQU2bdoUK7+40FJxPK7bS3GQgIQ6SHAg4WE+WbO9FAcJSKiDBAcSHuaTNdtLcZCAhDpIcCDhSZV8AmT0pAQHCUiogwQHohHRolRaWho8Hg+Ki4vh8/mwZ88efPrpp8jLy4uVn+UEaprb7rhvlGBtCwI1zQntIAEJdZDgQPTBfNIHj4noIKEOEhyIPphP+uAxER0k1EGCA9FHKuQTIKMnJThIQEIdJDiQr4no6XtutxuPPPIIHnvsMfzpT39CIBBAYWEhbr75Zt37UBQFPZyeiEUBwONM6/B3pDQoCtQwDt56r6F9n46jAfDkdB4jURzCwbmwziEcVsxFrB0aFcXQdu2JRj4BxutgtgZA+LmIdT8mikM4OBfWOYTDirmwwsFsRjGf9MNjIjyJUAcJDuFgPmnEO58Afq6w0iEcnAvrHMKRSp/xIlqUAoDdu3fjqquuwo9+9CPs3LkTjz32GC677DLceOONurbv48lE0cwXIx22A6unLTK03eQVk3G08SiyevTGW904FBcXY8G7C8zoAQDmjJ2OwsLChHXQC+ci9g56ieVcxNphytoppsYNYTafAPMZZbQGQPi5iHU/JoqDXjgXsXfQSyznwgqHaGQU80kfPCbCkwh1kOCgF+aTjHwC+LnCCge9cC5i76CXVPiMF9Gi1KZNm7BmzRqUlJQgLS0NF1xwAY4cOYIXXnhBd2gd89bhhuWzIhm2DY8zDaunLcItq+bB64v8UrnapuNtf3fn4K08ZsjtdJaUrsArTe8krEM4OBfWOYTDirmItUOjt87QuO2JRj4BxjPKbA2A8HMR635MFIdwcC6scwiHFXNhhYPZjGI+6YfHRHgSoQ4SHMLBfNKIdz4B/FxhpUM4OBfWOYQjlT7jRbQotW3bNgwZMgRpaV9fvnX++efj97//ve59qKqKJp+5y+W8vmZD+1BVNaxDIMP814gAwJ+OLsdIFAe9cC5i76CXWM6FVQ5miEY+hVzM1MFoDUJjn8kh1v2YKA564VzE3kEvsZwLKx2MwnzSD4+J8CRCHSQ46IX5JCOfAH6usMJBL5yL2DvoJRU+40V0o/O+ffuiqqoKra2tba/t2bMHAwcOjMxOMPbsNNiy3Kb2Yctyw55t/LvhEhwkIKEOEhyIPphP+uAxER0k1EGCA9EH80kfPCaig4Q6SHAg+kiFfAJk9KQEBwlIqIMEB/I1ES1KTZw4EU6nEw8//DD27t2LDRs24Pe//z1++MMfxsovLrjze8d1eykOEpBQBwkOJDzMJ2u2l+IgAQl1kOBAwsN8smZ7KQ4SkFAHCQ4kPKmST4CMnpTgIAEJdZDgQDQiWpRKT0/Hq6++ipqaGkydOhULFy7EPffcg2nTpsXKLy44h2dASXcAkV7VpwBKugPO4RlJ4SABCXWQ4EDCw3wKA4+JqCOhDhIcSHiYT2HgMRF1JNRBggMJT6rkEyCjJyU4SEBCHSQ4EI2In743bNgwvPLKK7FwEYPisKHnjYPRuGYf0BoE9HwVUgHg0rZTHBGt9Yl1kICEOkhwIPpgPnW3EXhMxAAJdZDgQPTBfOpuI/CYiAES6iDBgegjFfIJkNGTEhwkIKEOEhyIBivZDfZMF3pNHQqll751O6WXA72mDoU905VUDhKQUAcJDoSEkNCPEhwkIKEOEhwICSGhHyU4SEBCHSQ4ENIeCT0pwUECEuogwYEYuFIqlbBnupA+/Vz4dtajpeI4grUtnd5jy3LDnd9bu/wvBqulEhwkIKEOEhwICSGhHyU4SEBCHSQ4EBJCQj9KcJCAhDpIcCCkPRJ6UoKDBCTUQYJDqsNFqTAoDhtceZlw5WUiUNMMRwMwZ+x0LCldAX86LLnjvgQHCUiogwQHQkJI6EcJDhKQUAcJDoSEkNCPEhwkIKEOEhwIaY+EnpTgIAEJdZDgkMpwmS8C7Nlp8OT2RmFhITy5vePSnBIcJCChDhIcCAkhoR8lOEhAQh0kOBASQkI/SnCQgIQ6SHAgpD0SelKCgwQk1EGCQ6rBRSlCCCGEEEIIIYQQYjlclCKEEEIIIYQQQgghlsNFKUIIIYQQQgghhBBiOYqqqqoVA/n9fpSXl2PS5Enwqp3vaK8HRVHQx5OJY946GNFWvQFABaAAisdOBzrQQYiDR3HjnfXvYMyYMXA44vP8BbMZZbYGgPm5oAMd6BAbh3hnFPOJDnSgQ3ckej4ByXEuSwc60KEzevPJsuQKBoMAgHfWv2PVkISQBCOUE/EcmxlFCOmOeGUU84kQEg7mEyFEKuHyybIrpYLBIPx+P2w2GxRFsWJIQkiCoKoqgsEgHA4HbLb4fKuYGUUI6Y54ZxTziRDSHcwnQohU9OaTZYtShBBCCCGEEEIIIYSE4I3OCSGEEEIIIYQQQojlcFGKEEIIIYQQQgghhFgOF6UIIYQQQgghhBBCiOVwUYoQQgghhBBCCCGEWA4XpQghhBBCCCGEEEKI5XBRihBCCCGEEEIIIYRYDhelCCGEEEIIIYQQQojlJNSiVHFxMXJzc/GXv/zF0nFzc3M7/Ln00kvx8MMP4+TJk5Z6AMCJEyfwxBNPYOLEiRgzZgwmTZqEV199FcFgMOZjT5w4sa0GI0eOxNixY/GDH/wAH374YczH7srh9D+bN2+Ou8ett95qmUNTUxOeffZZXHfddcjPz8cll1yC+fPnY+fOnZaMP3HiRBQXF3d6vbi4GBMnTrTEQRqpnlGpnk+ne8Qro5hPzKeuYD4xn5hPXxPPjGI+dYb5FL98AmRklIR8OpMHz6Fim1GOmOw1Rrz99tsYPHgw3njjDdx8882Wjr1o0SKMHTsWwWAQhw8fxiOPPIInn3wSjz76qGUOx48fx7Rp09C3b1/8+te/xsCBA7F161Y89thjOHDgAH7xi1/E3OGhhx7C5MmTEQwGceLECaxbtw533303XnrpJVx++eUxH7+9w+mcddZZlox/Jg+n02nJ2CdPnsT06dPR1NSEBx54ACNHjsTx48fx2muv4Qc/+AHWrVuHQYMGWeJCviaVM4r51NnjdKzMKOYTOR3mE/OpvcfppEo+AcwoiTCf4ptPgIyMkpBP3XnwHCq2JMyi1FdffYVNmzZhwYIFeOCBB3DgwAFLJ+Sss85CdnY2AKBfv364++678eijj1q6KPXMM8/A5XJh2bJlcLvdAIBBgwYhLS0Nc+bMwcyZM3HOOefE1CE9Pb1DHf77v/8bNTU1WLhwId56662Yjt2VQzyJp8fzzz+Pr776CuvXr0dGRgYAYMCAAVi4cCEOHz6MV1991bJ/xIhGqmcU86lrj3jBfCLtYT4xn7ryiBfxdmBGyYL5FP98AmRkVLyzQYJHquZTwnx9791330V6ejpuvPFG9O3bF2+88UZcfTwej6Xjtba24u2338aMGTPaAivEVVddhVdffRUDBgyw1CnEtGnT8MUXX6Cqqiou46cawWAQa9euxY9+9KO2sGrPk08+iZ/97GdxMEttUjmjmE8kBPNJJswn5hPRYEbJg/kkM58AZpTVpHI+Jcyi1Ntvv40rr7wSNpsNEydOxLp166Cqalxcjh07hj//+c+48cYbLRtz//79aGpqwgUXXNDpZ4qi4NJLL4XL5bLMpz3nnXceAGDXrl1xGT/V2L9/P44dO4aLLrqoy5/37dsXaWlpFluRVM4o5hMJwXySCfOJ+UQ0mFHyYD7JzCeAGWU1qZxPCfH1vcOHD+PTTz/Fj370IwDAd7/7XaxcuRJbtmzpdtKizaxZs2C326GqKrxeLzIzM/GrX/3KkrEBoL6+HoB2OaE0Qk5W3RTwl7/8JR577LEOr+Xk5ODtt9+2ZPwzeXz00Ufo0aNHTMc9fvw4gI7fr/74449x7733tv1/q+rRVQ38fr+IS2+tJNUzivnUEQkZxXxiPoVgPjGf2pPK+QTIySjmkwbzSW4+AfyM1x6eQ8U2oxJiUertt9+G2+3Gt771LQDA+PHjcdZZZ2Ht2rWWBdbjjz+OMWPGQFVVHD9+HMuXL8ett96Kt956C2effXbMx8/MzASgPZ1BGo2NjQCAXr16WTLe/Pnz8d3vfrfDaw6H9a3clYcVl/yGLucM/UMGAGPHjsW6desAAO+99x5WrlwZcw+g6xpYOb4UUj2jmE8dkZBRzCfmUwjmUyYA5lOIVM4nQE5GMZ80mE+ZAGTmE8DPeO3hOVRsx0+YRanm5maMGzeu7bVAIIB3330Xv/jFLyy5jK1fv34YMmQIAGDo0KEYNWoULrnkErzzzjuYOXNmzMcfPHgw0tPT8dlnnyE/P7/Tz++55x788Ic/tPQJLiF27NgBABg+fLgl45199tltcxFP4uUxZMgQZGZmorS0tK0XPB5Pm4sVi6QhuqqBleNLIdUzivnUEQkZxXxiPoVgPjGf2pPK+QTIySjmkwbzSW4+AfyMZzVS8ik0lpUZJf6eUnv37sXnn3+Ohx9+GOvWrWv787vf/Q6NjY14//334+Jls9mgqioCgYAl4zkcDkyePBmvvfYaWltbO/xsw4YN2LBhA/r27WuJy+kUFRVh1KhRSfl4Sok4HA5MmTIFf/zjH9t+g9GeI0eOxMEqdWFGMZ/I1zCfZMF8Yj6RjjCj5MB8kp1PADPKalI5n8RfKfX2228jMzMT06ZN63CjtxEjRuD555/HunXrcMMNN8Tc48SJE6ipqQGgfa/25ZdfRiAQwMSJE2M+doh58+bh5ptvxp133ol58+bhG9/4BjZv3oynnnoKt912G4YNGxZzh4aGBtTU1LRd4rpmzRqsX78eL7/8cszHPt3hdHr27GnJ/QgkMG/ePGzZsgU/+MEPMHfuXIwaNQrHjx/HX/7yF6xZswbf+9734q2YMjCjNJhPnT1OJ1UyivkkB+aTBvOps8fppEo+AcwoKTCfNCTkEyAjo5hPqZtPCbEodcMNN3T55IFbb70Vv/71r3HkyBH069cvph7z5s1r+98ejwejR4/Giy++aOnKcXZ2NlauXIlFixbhvvvuQ11dHQYPHoz58+fj1ltvtcRhwYIFWLBgARRFQZ8+fXD++efj1Vdftex73+0dTuc//uM/MGfOHMs84onH48Gf//xn/PGPf8SSJUtQVVUFl8uF/Px8LFq0CN/5znfirZgyMKM0mE+dPU4nVTKK+SQH5pMG86mzx+mkSj4BzCgpMJ80JOQTICOjmE+pm0+KGq9nbhJCCCGEEEIIIYSQlEX8PaUIIYQQQgghhBBCSPLBRSlCCCGEEEIIIYQQYjlclCKEEEIIIYQQQgghlsNFKUIIIYQQQgghhBBiOVyUIoQQQgghhBBCCCGWw0UpQgghhBBCCCGEEGI5XJQihBBCCCGEEEIIIZbDRSlCCCGEEEIIIYQQYjlclEoCZs+ejQcffLDDa//7v/+L3NxcLFq0qMPrS5Yswb/9278BAOrr6/Hzn/8cl19+OS699FI88MADqK+v77T/uro6XH755Th48GBYl5kzZ+LTTz/t9Hprayt+85vf4Nvf/jYuvvhi3Hvvvfjyyy/bfn748GHcfffduPDCCzFx4kS8+uqrhsf64Q9/iNzc3LY/Y8eOxZ133omqqqou9/Pmm2/ihz/8YYfXTpw40WEfubm5uOSSS8I6EUI6YzSjQqiqijvuuAPFxcUdXj9x4gR++tOfYuzYsfj2t7+NP/3pT2FdrrrqKhw5cqTT62fKw0WLFnXKg9zcXFx99dWGxpo4cWKH/Vx00UWYP38+vvrqqw7/zUuXLsXEiRNx4YUX4t///d+xa9euTvvqrjaEEH0kwzlUa2srHn30UVx88cW4/PLL8dvf/haqqhoay+w51MGDB7vMy9zcXPzzn/8MWwNCyNfE6vzp1Vdf7XR8/uY3vzmji5Hzp2iPFc3zJwB49NFHO30GJPGBi1JJwEUXXYStW7d2eG3z5s3o27cvNm/e3OH1srIyjB8/HgDwy1/+EpWVlVi6dCmWLVuG3bt34+GHH+7w/hMnTuDHP/5xh4O9O7xeL3bu3In8/PxOP3vuuefwt7/9DU8//TRWrlwJv9+PuXPntp00/ed//id69OiB4uJiPPTQQ3j22Wfx/vvvGxoLAO644w5s3LgRH374IVavXo3MzEzMmTOn00naJ598gkceeaTT9rt27UJmZiY2btzY9mf9+vVha0AI6YzRjAKAYDCIxx9/HB999FGn/f70pz/FwYMHsWrVKjz00EN4+umn8eGHH3brUVVVhbS0NPTr16/Tz86Uh6E8aZ8FmZmZuO222wyNBQAPPfQQNm7ciP/3//4f/vznP+PEiRO4//77237++uuv4+WXX8YvfvELFBUVYeDAgZg1axa8Xq+u2hBC9JEM51CPP/44Pv74YyxbtgzPPPMMVq9ejVWrVhkaCzB3DtW/f/8Oeblx40Z873vfwwUXXICCgoKwdSCEfE2szp927dqF6dOndzhO77333m49jJ4/RXssIDrnTwDw6aefYuXKld16EGvholQSMG7cOOzevRsnT55se23z5s248847UVZWhubm5rbXy8vLMX78eDQ1NeGvf/0rHnnkEYwePRqjRo3CQw89hL/97W9oaWkBAPzrX/9CYWEhmpqadHn861//QkFBARwOR6efrV27Fj/5yU8wfvx4DBs2DI899hi2bt2KqqoqnDhxAmVlZbjnnnswdOhQfOc738EVV1yBTZs2GRoLAHr06IHs7Gz07dsXw4cPxwMPPIBdu3Zhx44dbe9ZvHgxZs2ahUGDBnXafs+ePTjnnHOQnZ3d9ufss8/WVQdCSEeMZBQAHDlyBP/+7/+ODRs2ICMjo8M+Kysr8fHHH+Ppp5/GiBEjcN1112Hq1Kld/uY/xKZNm3DZZZd1ej1cHvbs2bNDFvzxj3/EsGHDzrgo1d1YIdLT05GdnY1+/fohLy8PP/nJT/Dhhx+ioaEBgJaZd9xxB6666iqcc845+NWvfoW6urq2/74z1YYQop9EP4eqq6tDUVERHnvsMeTn5+Oyyy7DHXfcgfLyckNjAebOoex2e4e8PHDgAP7617/iN7/5DZxOp65aEEI0YnH+BAC7d+/GyJEjOxyrvXr16tbD6PlTNMcKYfb8CdCuLn3kkUe4UC4ILkolARdccAGcTic+++wzAMCXX36J6upq3HzzzUhPT287CPfu3YsTJ07goosugs1mw+9//3vk5eV12FcgEGgLvo0bN2LKlCmdLg/tju5CJBgM4qmnnsLll1/e6WcNDQ1IS0uDx+NBcXExfD4f9uzZg08//bSTm56xusPj8XR67aOPPsKyZcvw3e9+t9PPdu3ahaFDh+rePyGke4xkFAB89tln6N+/P4qKipCent5hn//4xz8wcuTIDh+IHnnkEfzHf/xHtx7d5YaePAyxd+9eFBcX4/7774eiKBGP1R0ej6fD/v77v/8bN954Y9v/VxQFqqq2nXSdqTaEEP0k+jnUli1b0KtXrw5XSMyePRsLFy6MeKzuiPQcqj3PPPMMbrnlFpx33nm6xyOEaMTi/AnQfvkeyeccM+dP0RqrOyI9fwKApUuXIjc3F9/85jd1j0NiCxelkgCXy4UxY8agoqICgHY59ejRo9GzZ09cfPHFbZd3lpWVYfjw4ejduzfS0tLw7W9/Gy6Xq20/f/rTn5Cbm4s+ffoA0L5SN2fOHNjtdl0en3zyCS699NJOr9tsNlx++eXIzMzsMFbv3r2Rm5sLt9uNRx55BKtWrcKYMWMwadIkfPvb38bNN98c8Vhd0drait///vdt3z8OsXLlyg4nce3ZvXs3vvzyS0ydOhVXXHEFfvKTn+Do0aO6xiOEdMRIRgHavQOefPLJtkxqz4EDBzBw4EAsW7YMEydOxHXXXYfXX3+9WwdVVfHPf/6zy2NeTx6GWLZsGS699NJuv/YSbqyuOHnyJF566SVceeWVbSePF110Eb7xjW+0vecvf/kL/H4/xo0bB+DMtSGE6CfRz6EOHDiAAQMGYN26dbjuuutw9dVX4/nnn0cwGIx4rK4wcg4VYsuWLSgrK8Pdd9+tayxCSEdicf5UW1uLuro6rF27FhMnTsSkSZOwbNmybu9DZ+b8KZpjdYWR86fdu3dj5cqVne7VReJL19ftkoTjoosuaguszZs3t92Ue/z48fjf//1fAJ2/a9ye5cuX45133sFLL71kaPy6ujocOXKkwwlLd/ztb3/Dyy+/jEcffbQtxHbv3o2rrroKP/rRj7Bz50489thjuOyyyzqsdEcy1h/+8Ae8/PLLAIDm5maoqornnnvujFc2tGfPnj3o06cPHnzwQaiqit/97nf48Y9/jL/85S+6TzAJIV9jNqNOp6mpCR9//DH8fj/+z//5P/jiiy/wP//zP+jduzeuvfbaTu+vrKxE//79cdZZZ4Xdd3d52NjYiLfffhvPPvvsGbfXM9Yvf/lLPPbYY1BVFc3NzXA6nd3eqL28vBy/+c1vcOeddyI7OzusPyEkMhL5HKqpqQlVVVV4/fXXsXDhQtTU1OCRRx6Bx+PBHXfcYWgss+dQIVavXo1rrrmm23vDEELCE+3zpz179gAAzj77bLzwwgvYvn07Hn/8cdjtdtx+++2d3m/m/CkWY5k5f1JVFY888gjmzZuHrKyssP89xDq4KJUkXHTRRVi3bh0ALbAee+wxAFpgPfHEE2htbW27b9PpvPbaa3j88cfx4IMP4lvf+pah8Tdv3ozx48eHPWH529/+hv/8z//EzJkz266E2rRpE9asWYOSkhKkpaXhggsuwJEjR/DCCy90uSilZ6wf/OAHbU9TaGpqQklJCf7rv/4LL774oq5LQt9++20oioK0tDQA2k1Gv/Wtb6G8vBwXXnhh2O0JIR0xk1FdYbfbEQgE8PTTT6NHjx644IILUFlZiVWrVnW5KKX3cvAz5eGHH36ItLQ0XHHFFWfch56x5s+f3/a1l/r6erz11lu44447sHr1agwfPrztfaWlpZg1axa+/e1vn/GriYQQ4yTyOZTD4UBjYyOeeeYZDBgwAABQXV2NlStXdrkoZcU5FAD4/X588MEHePLJJ3W9nxDSNdE+fxo/fjw++eSTtquqcnNzcezYMaxcubLLhSIz50+xGMvM+dOqVasQCAQwbdq0sP89xFr49b0kYezYsTh69Ci2bt2Ko0ePti2cDB8+HOnp6fjnP/+JXbt2dVpFX7ZsGf7nf/4HP/vZz/Dv//7vhsfXEyJvv/02/uM//gPTpk3DQw891Pb6tm3bMGTIkLYFIAA4//zzUV1dbXiss846C0OGDMGQIUOQl5eHH//4x7jkkkt0P2XB4/F08Dn77LORmZnZ5eNJCSHhMZpR3dG3b1984xvfQI8ePdpeO+ecc3D48OEu368nN8Ll4YcffoirrroKNtuZ/+nUM9bZZ5/dllEXXHABHnroIfTt27fDY5s3b96MO+64A5deeimeeeaZsOMSQoyRyOdQ2dnZcLvdbQtSgPksNHsOBWhXbvj9ft6zhRCTRPv8CUDbIlGI8847r9vPOGbPn6I9lpnzp7fffhvbtm3DhRdeiLFjx+IPf/gD/vWvf2Hs2LHdfu4k1sAz3CShR48eyMvLw6pVq3DBBRe03ZRSURRcfPHFKC4uxtChQzt8t3jt2rV48skn8eCDD+LOO+80NX64ENm0aRP++7//GzNmzMAvfvGLDj/r27cvqqqq0Nra2vbanj17MHDgQENjdYeqqggEAmHf19jYiIsvvhiffPJJ22tHjhzB8ePHce6550Y8LiHEWEadiTFjxuDQoUMdbly5Z8+eDh/MQvh8PlRUVLTdT6Ar9ORhRUVF2Csl9Yx1JkIZ9cUXX+Cee+7BFVdcgWeffZZPrSIkhiTyOdSYMWPQ0tKCvXv3tr3WXRbqGas79J5DhSgvL8eoUaPgdrsjHosQ8jXRPn/6y1/+gmuvvbbDfZ22b9/e5Wccs+dP0R7rTOg5f3r66afx9ttvY926dVi3bh1+8IMfYPTo0Vi3bh369u1raFwSHbgolURcfPHFePvttzutlI8fPx4ffPABLr744rbX6urq8D//8z/4/ve/j+uvvx41NTVtfyI56QC0J0H4fL5OjwUO4ff78dBDD+Hiiy/GrFmzOozV2tqKiRMnwul04uGHH8bevXuxYcMG/P73v2+7dDySsUI0NTW1jXH48GG89tpr2LRpEyZNmhT2v6dXr14YN24cFi5ciIqKCnz22Wf4yU9+giuuuELX/R4IIV0TSUaF4/LLL8c555yD+++/H7t378b69evxl7/8Bbfeemun95aXl2PEiBEdrn5sj5489Pv92Lt3L4YNG3ZGr3BjhWhoaGgb4+DBg1i0aBGqqqpw3XXXAdCeJNi/f388+OCDOH78eNt72z/+mRASPRL1HOrcc8/FlVdeiQcffBCVlZX48MMPsXTp0i6z0IpzqBA7d+7kE/cIiRLRPn+qqanBb37zG1RVVeHtt9/Giy++iLvuuqvTe82eP0VzrBBmzp/69evXdpXVkCFDcNZZZyEtLQ1DhgyBw8G7GsUTVj+JGDduHF5++eW2G+CFGD9+PLxeb4cg++ijj9DU1IS1a9di7dq1Hd7/wQcfdHuVUlds2rTpjE9x2bZtG6qrq1FdXd3pfgt/+tOfcMkll+DVV1/Fr3/9a0ydOhV9+vTBPffc0+X3fcONFeLll19uu0mn0+nEkCFD8Mgjj+B73/uerv+m3/zmN3jiiScwe/ZstLa24uqrr8bDDz+sa1tCSNdEklHhsNvtWLp0KX75y1+isLAQvXv3xgMPPICrr76603vDPWlKTx7W1dXB7/cjIyPjjF56n2q1YMECLFiwAADgdrsxbNgwPPvss7jwwgtRU1OD0tJSAMCVV17ZYbuFCxeisLAw7P4JIZGRyOdQTz/9NB577DHceuut8Hg8mDFjRpe/2LPqHArQnvB1+mPiCSHGiOb504ABA7B06VI89dRTWLlyJc4++2zcd999mDx5cqf3RuP8KVpjheD5U3KiqN09k5EQQgghhBBCCCGEkBjBr+8RQgghhBBCCCGEEMvhohQhhBBCCCGEEEIIsRwuShFCCCGEEEIIIYQQy+GiFCGEEEIIIYQQQgixHC5KEUIIIYQQQgghhBDL4aIUIYQQQgghhBBCCLEcLkoRQgghhBBCCCGEEMvhohQhhBBCCCGEEEIIsRwuShFCCCGEEEIIIYQQy+GiFCGEEEIIIYQQQgixHC5KEUIIIYQQQgghhBDL4aIUIYQQQgghhBBCCLEcLkoRQgghhBBCCCGEEMvhohQhhBBCCCGEEEIIsRwuShFCCCGEEEIIIYQQy+GiFCGEEEIIIYQQQgixHIdVAwWDQfj9fthsNiiKYtWwhJAEQFVVBINBOBwO2GzxWStnRhFCuiPeGcV8IoR0B/OJECIVvflk2aKU3+/H1q1brRqOEJKAXHDBBXC5XHEZmxlFCAlHvDKK+UQICQfziRAilXD5ZNmiVGhlbNLkSfCqLYb2oSgK+ngyccxbB1VVI95e9QYAFYACKB47HehAByEOHsWNd9a/E7erpADzGWW2BoD5uaADHegQG4d4ZxTziQ50oEN3JHo+AclxLksHOtChM3rzybJFqdDlnF61BfZbcgzto4fTg6KZL+KG5bPQ5PNGvH39q7ugnvRD6elAxi3D6EAHOghx8K6uBvB1TsQDsxlltgaA+bmgAx3oEBuHeGcU84kOdKBDdyR6PgHJcS5LBzrQoTN684k3OieEEEIIIYQQQgghlsNFKUIIIYQQQgghhBBiOVyUIoQQQgghhBBCCCGWw0UpQogp8gfm4aax1yIrKws3jb0W+QPz4q1ECCEAmE+EELkwnwghkrEyoyy70TkhJHlIc7oxZdxkzJ4wE2MGnd/2+pLbFgIAyg98jqUly1G0ZT2afcaexEIIIUZgPhFCpMJ8IoRIJl4ZxSulCCERcV7fofjHw29j8YxfY/SA3C7fM3pALhbP+DX+8fDbODd7iMWGhJBUhflECJEK84kQIpl4ZpThRanW1lZ873vfw+bNm6MmQwiRzXl9h+Jv972OnMx+UBQFdpu9y/fZbXYoioKczH744GerLD+xYj4RknownwghUmE+EUIkE++MMrQo1dLSgv/6r//Czp07oyJBCJFPmtONtfe+hHR3Tzjs+r7567A7kO7uiXVzlyHN6Y6xoQbziZDUg/lECJEK84kQIhkJGRXxotSuXbtwyy23YP/+/aYHJ4QkDlPGTcagPjm6wyqEw+7A4LMHoPDCSTEy+xrmEyGpCfOJECIV5hMhRDISMiriRal//OMfuOSSS7Bq1SrTgxNCEofZE2YiqAYNbRsIBjB7wswoG3WG+URIasJ8IoRIhflECJGMhIyK+Ol706dPNz0oISSxyB+Y1+EJDJFit9lRMHgU8gfmoeLg9iiadYT5REjqwXwihEiF+UQIkYyUjIp4UcosiqKgh9NjaFuPM63D35HSoChQ6UAHOkTsMDqn6ycwRMqonBHYdWRfp9cbFSUq+48GRufC7DwA5vuBDnRIRYdY5xMgJ6MkzwMd6EAH5pPkc1k60IEOnZHyGU9RVVU1Onhubi7+9Kc/4ZJLLgn73kAggLKyMkyZMgVFRUVGhzTF5MmTcfToUfTt2xfr16+nAx3ooNMhKysLQ4aYf7pCVVUVamtrO70eyoWCggLY7V0/7SFSIskngBlFBzokqkOs8wmIfkYxn+hAh9RwYD5ZQyL0Ah3oINFBymc8y6+UOuatww3LZxna1uNMw+ppi3DLqnnw+poj3r626Xjb33SgAx30O9w09losuW2hIb/2PFHyAt4ofa/T643eOtP7jhZGM8rsPADm+4EOdEhFh1jnEyAno5hPdKBDYjkwn/SRKufTdKCDNAcpn/EsX5RSVRVNPq+pfXh9zYb2EboojA50oENkDtuqd5hya9vPoR1djmHigs2oY3YujM5DaGw60IEOkTnEOp/aO8QbyfNABzrQgfkk+VyWDnSgQ2ekfMaL+Ol7hJDUo+LgdpQf+ByBYMDQ9oFgAGX7P8PWQ5VRNiOEpDrMJ0KIVJhPhBDJSMkoLkoRQnSxtGQ5bIqxyLDb7FhasjzKRoQQosF8IoRIhflECJGMhIwytSi1Y8cO3TfBI4QkNkVb1uPAsWr4A/6ItvMH/Nj/1SEUf/pOjMy6hvlESOrAfCKESIX5RAiRjISM4pVShBBdNPta8P3n70JDy0ndoeUP+NHQchI3Lb4Tzb6WGBsSQlIV5hMhRCrMJ0KIZCRkFBelCCG62X10H65+ahqq644AQLffPw69Xl13BFc/NQ17aqoscySEpCbMJ0KIVJhPhBDJxDujLH/6HiEksdlTU4Xxj1+PwgsnYfaEmSgYPKrTe7YerMTSkuUo/vQd/oaPEGIZzCdCiFSYT4QQycQzo7goRQiJmGZfC1ZsXocVm9chf2AeRuWMwAMT7sETJS/gs+ovUHFwe7wVCSEpCvOJECIV5hMhRDLxyiguShFCTFFxcDt2HdmHu0bdjDdK30OTzxtvJUIIAcB8IoTIhflECJGMlRnFe0oRQgghhBBCCCGEEMvhohQhhBBCCCGEEEIIsRwuShFCCCGEEEIIIYQQy1FUVVWtGCgQCKCsrAwTrpyAJtXYndoVRUFWj96obToOI9pqkx9QASiA0sPY7bToQAc6RN+hh+JGyd9LUFBQALvdbsjBLGYzymwNAPNzQQc60CE2DvHOKOYTHehAh+5I9HwCkuNclg50oENn9OaT9Tc6VwH1pN/opjjaeJQOdKBDsjn0dBvfNtoYrEPU5oEOdKCDPAcpGZXq80AHOtChMwmeT6c2TfxzWTrQgQ6d0ZlP1i9KKYDSM3VXC+lABzp0tQNDw8YGgxmVLL9xpQMd6NDVToxtFnWYT3SgAx067cTYZlGHn/HoQAc6dNqBvrdZviileOzIuGWYoW17OD14a+aLuGH5LEOPJKx/dRfUk34oPRzIuJ0OdKCDFIfA6mpD48YCoxlltgaA+bmgAx3oEBsHKRnFfKIDHehwOomeT0BynMvSgQ506IzefOKNzgkhhBBCCCGEEEKI5XBRihBCCCGEEEIIIYRYDhelCCGEEEIIIYQQQojlcFGKJCSBmmZ4K4+huLgY3spjCNQ0x1spLuQPzMNNY69FVlYWbhp7LfIH5sVbiZCUh/mkwXwiRB7MJw3mEyEyYUZppFpGWf/0PUIMovqD8O2sR0vFcQRrWwAAC95d0PZzW5Yb7vzecA7PgOJI3vXWNKcbU8ZNxuwJMzFm0Pltry+5bSEAoPzA51hashxFW9aj2dcSL01CUgrmkwbziRB5MJ80mE+EyIQZpZHKGcVFKZIQBOpacfLN/VAb/N2+J1jbAu+GL9H8z1r0vHEw7JkuCw2t4by+Q7H23pcwqE8Ogmqwy/eMHpCLxTN+jfsn3YubFt+JPTVVFlsSklownzSYT4TIg/mkwXwiRCbMKI1Uz6iIlhqPHDmC+fPnY/z48bjiiiuwcOFCtLQk1yodkUegrhWNa/ZBbew+rNqjNvrRuGYfAnWtMTazlvP6DsXf7nsdOZn9oCgK7DZ7l++z2+xQFAU5mf3wwc9W4dzsIRabxg9mFLEa5pMG8yk8zCdiNcwnDeZTeJhPJB4wozSYUREsSqmqivnz58Pr9eK1117D7373O/zf//t/8eyzz8ZQj6Q6qj+Ik2/uB1qDgKp3IwCt2naqv+uV5kQjzenG2ntfQrq7Jxx2fRc4OuwOpLt7Yt3cZUhzumNsGH+YUcRqmE8azKfwMJ+I1TCfNJhP4WE+kXjAjNJgRmnoXpTas2cPysrKsHDhQgwfPhwXXXQR5s+fj//93/+NpR9JcXw767XLOfWGVQgVUBv88O2sj4mX1UwZNxmD+uToDqsQDrsDg88egMILJ8XITA7MKGI1zCcN5lN4mE/EaphPGsyn8DCfSDxgRmkwozR0L0plZ2fjpZdeQlZWVofXGxsboy5FSIiWiuNx3V4KsyfM7Pb7xeEIBAOYPWFmlI3kwYwiVsN80mA+hYf5RKyG+aTBfAoP84nEA2aUBjNKQ/eiVEZGBq644oq2/x8MBrF8+XJceumlMREjJFDT3PYEBqMEa1sS/lGi+QPzMGbQ+d1+vzgcdpsdBYNHJf2jRJlRxEqYTxrMJ30wn4iVMJ80mE/6YD4Rq2FGaTCjvsbw0/eeeuopfP7551izZk1E2ymKgh5Oj6ExPc60Dn9HSoOiQKVDwjh4672G9n06jgbAk9N5jESpw+icXEP7Pp1ROSOw68g+Qw7hMFuHRkUxtN2ZsDqjzNYAMD8XdLDOIdb5pMchHFbUIdb5pMchHNGoQ7QzivlEB+YT8wlgPoVIlc82dNDgZzwNfsb7GkVV1Ui/yYmnnnoKr7zyCn73u9/h2muv1bVNIBBAWVkZpkyZgqKiokiHjAqTJ0/G0aNH0bdvX6xfv54Owh2Ki4uxYMEC02M99NBDKCwsNOQQa/Q4ZGVlYcgQ809XqKqqQm1trSGHWBPKhYKCAtjtxn5b0B5mFB1i7RDrfNLjYAXhHGKdT3ocrCCaGcV8okOsHZhPGsynyGE+0cEKB37G0+BnvK+J+Eqpxx57DCtXrsRTTz2lO6zac8xbhxuWz4p4O0BboVs9bRFuWTUPXl/kl+vVNh1v+5sO8h28lccMuZ3OktIVeKXpHUMO4bCiDjeNvRZLbltoyK89T5S8gDdK3zPkEA6zdWj01hkatyvilVFmawCYnws6WOcQ63zS4xAOK+oQ63zS4xCOaNQhWhnFfKID80mD+aTBfNJIlc82dNDgZzwNfsb7mogWpRYvXozXX38dv/3tb3HddddFLAVojx1t8pm7ZM/raza0j9BFYXRIDIdARnQuR/ano8sxEqUO26p3mHJr28+hHeLrYBYJGWW0BqGx6ZAYDrHOJz0OeollHWKdT3oc9BKNOpiB+UQHqxyYTxrMJ/1IyCcg+T/b0EGDn/E0+Bnva3Tf6Hz37t1YsmQJZs2ahXHjxqGmpqbtDyGxwJ6dBluW29Q+bFlu2LONf09fAhUHt6P8wOcIBAOGtg8EAyjb/xm2HqqMspksmFHESphPGswnfTCfiJUwnzSYT/pgPhGrYUZpMKO+Rvei1AcffIBAIIAXXngB3/rWtzr8ISRWuPN7x3V7KSwtWQ6bovtw7YDdZsfSkuVRNpIHM4pYDfNJg/kUHuYTsRrmkwbzKTzMJxIPmFEazCgN3V/fmz17NmbPnh1LF0I64RyegeZ/1kJt9AORXJ2sAEovB5zDM2LmZiVFW9bj/kn3IiezHxx2/d+69Qf8qK47guJPu74nRDLBjCJWw3zSYD6Fh/lErIb5pMF8Cg/zicQDZpQGM0rD2LIcIRahOGzoeeNgwGUD9H79WAHg0rZTHMnR4s2+Fnz/+bvQ0HIS/oBf1zb+gB8NLSdx0+I70exribEhIakH80mD+USIPJhPGswnQmTCjNJgRmkkx2ySpMae6UKvqUOh9NK3eqz0cqDX1KGwZ7pibGYtu4/uw9VPTUN13REA6Pb7x6HXq+uO4OqnpmFPTZVljoSkGswnDeYTIfJgPmkwnwiRCTNKgxkV4dP3CIkX9kwX0qefC9/OerRUHEewtvOqsC3LDXd+bziHZyTN6vnp7KmpwvjHr0fhhZMwe8JMFAwe1ek9Ww9WYmnJchR/+k7SrJ4TIhnmkwbziRB5MJ80mE+EyIQZpZHqGcVFKZIwKA4bXHmZcOVlIlDTDEcDMGfsdCwpXQF/OhL+CQx6afa1YMXmdVixeR3yB+ZhVM4IPDDhHjxR8gI+q/4CFQe3x1uRkJSD+aTBfCJEHswnDeYTITJhRmmkckYl51IjSXrs2Wnw5PZGYWEhPLm9UyasTqfi4Ha8Ufoeamtr8Ubpe0kdVoQkCswnDeYTIfJgPmkwnwiRCTNKI9UyiotShBBCCCGEEEIIIcRyuChFCCGEEEIIIYQQQiyHi1KEEEIIIYQQQgghxHIUVVVVKwYKBAIoKyvDhCsnoEk1drd4RVGQ1aM3apuOw4i22uQHVAAKoPQwdo93OtCBDtF36KG4UfL3EhQUFMButxtyMIvZjDJbA8D8XNCBDnSIjUO8M4r5RAc60KE7Ej2fgOQ4l6UDHejQGb35ZP3T91RAPek3uimONh6lAx3okGwOPd3Gt402BusQtXmgAx3oIM9BSkal+jzQgQ506EyC59OpTRP/XJYOdKBDZ3Tmk/WLUgqg9Ezd1UI60IEOXe3A0LCxwWBGJctvXOlABzp0tRNjm0Ud5hMd6ECHTjsxtlnU4Wc8OtCBDp12oO9tli9KKR47Mm4ZZmjbHk4P3pr5Im5YPgtNPm/E29e/ugvqST+UHg5k3E4HOtBBikNgdbWhcWOB0YwyWwPA/FzQgQ50iI2DlIxiPtGBDnQ4nUTPJyA5zmXpQAc6dEZvPvFG54QQQgghhBBCCCHEcrgoRQghJLoEg/E2IIRIhNlACCGEkNOw/p5ShBBCkooxNc2Ysb0Ol1V7kXu8Fa5nx2OfTcGO3i5syvHgtbxMlGenxVuTEGIxzAZCCCGEhIOLUiRi8gfmYXROLrKysnDT2GuxrXoHKg5uTzmHQE0zvPVeFBcXw1t5DIEMBXaLT64l1IGkLufUtWLxhsP45mEvfAqwTQWKADQASA+qGPlVC350rAWzt9bho/4ezJ3YH3szXTF1knBc0kGD+ZS6nJ4NzjEFwDUjgfR0uBoacEFlJUaWl1maDRL6kQ50IDKR0A8SHHjuQId4wUUpoos0pxtTxk3G7AkzMWbQ+W2vL7ltIQCg/MDnWFqyHEVb1qPZ15K0Dqo/CN/OerRUHEewVhtjwbsL2n5uy3LDnd8bzuEZUByx+XashDoQMvWLE3h+w5doDah4BcBzKlDWxfsKVGA+gKmHvfjk9b2YM7E/ikZkRNVFwnFJBw3mEwllg93lBm6/Hc7584GxYzu9z1laCjz3HC5Z9XrMskFCP9KBDkQmEvpBggPPHeggAS5KkbCc13co1t77Egb1yUFQ7fp+EKMH5GLxjF/j/kn34qbFd2JPTVXSOQTqWnHyzf1QG/zdvidY2wLvhi/R/M9a9LxxMOxR/s2vhDoQMvWLE1j6/mF8AeA6AFXo/gaFFQDuAPAogL8GVLz4fjUUqFgz4qyouEg4LumgwXwioWzA8OGwvfceMGRI9/eRys8HXn4Zjl/+ErZrrsGL7++KajZI6Ec60IHIREI/SHDguQMdpBDxcmdVVRXuvPNOjB07FldeeSVeeumlWHgRIZzXdyj+dt/ryMnsB0VRYLfZu3yf3WaHoijIyeyHD362CudmD0kqh0BdKxrX7IPa2H1ot0dt9KNxzT4E6lqj5iChDtJhPsWec+ta8fyGL/EFgMsBHDz1ene3Lw69fhDAZQB2Anh+w5c4JwrHhoTjkg4azKfwJHs+hbIBw4fD9sknwIABgKIA9q57AXa79vMBA2DbvBkYNixq2SChH+lAh0Qi2fOpPRL6QYIDzx3oIImIFqWCwSBmz56N3r17Y+3atXj00Ufxwgsv4K233oqVH4kjaU431t77EtLdPeGw67uozmF3IN3dE+vmLkOa050UDqo/iJNv7gdag4CqdyMArdp2qt/804Yk1EE6zCdrWLThMFoCKq4DUA8goHO7wKn3XwugNaBi8YbDpjwkHJd00GA+hScV8mnRhsOwudzaFVLp6YDTqW9DpxNIT4ft/fdhd7lNZ4OEfqQDHRKJVMinEBL6QYIDzx3oII2IFqVqa2uRl5eHX/3qVxg6dCgmTJiAyy67DFu2bImVH4kjU8ZNxqA+OboPkBAOuwODzx6AwgsnJYWDb2e9dlmr3tAOoQJqgx++nfWmHSTUQTrMp9gz5mgzvnnYiyJoX9nTuyAVInBquyIA3zzsxZiaZsMuEo5LOmgwn8KT7PkUygbntB9oX9nTuyAVwukEhg6F45ZpprNBQj/SgQ6JRLLnU3sk9IMEB5470EEaES1K9e3bF88++yx69eoFVVWxZcsW/POf/8T48eNj5UfiyOwJM7v9Tms4AsEAZk+YmRQOLRXH47o9IKMO0mE+xZ4ZlXXwKcBzMPDd71PYoG3vU4AZ2+sMu0g4LumgwXwKT7LnUygbMH9+9/eQCkcgAMybZzobJPQjHeiQSCR7PrVHQj9IcOC5Ax2kYfgW+hMnTsT06dMxduxYXHvttdF0IgLIH5iHMYPO7/Y7reGw2+woGDwK+QPzEtohUNPc9iQKowRrWxAw8VtfCXVINJhPseGyai+2nXrKntELt4MASgFsU4FLD3sN7UPCcUkHDeZT5CRjPl1W7YVzTIH2lL3u7iEVDrsdGDcOzjEFhrNBQj/SgQ6JTDLmUwgJ/SDBgecOdJCI4afvPffcc6itrcWvfvUrLFy4EA8//LCu7RRFQQ+nx9CYHmdah78jpUFRoNJBl8PonFxD+z6dUTkjsOvIvoR18NYbOzE+HUcD4MnpPEai1CEcZnuyUVEMbdcdRvMJMF4HszUAzM9FrB1yj7eiyPCeO7IDQOGx1i7/O8PVIdbHJR30O8Q6n/Q4hCMax0U0MyoZ8yn3eCtwzUjD++64s1yMrCg3lA0S+pEOdIgE5pMGP9tY58DPNnSIBKs+4ymqqkb6bdIOvPvuu7jvvvvw6aefwuXq/hGRgUAAZWVlmDJlCoqKovWxJjImT56Mo0ePom/fvli/fj0dzuCQlZWFIUPM39G/qqoKtbW1CetQXFyMBQsWmHZ46KGHUFhYaMhBQh1iTSgXCgoKYDf6W/Yu0JtPADMqrEMwiHHjx2MpgLujMM4fAMwGsOUf/wBsHS/aDVeHWB+XdNDvEOt80uNgBbHIqKTJp1PZgFmzgKVLzQ80ezbw4ouGskFCP9KBDlbDfEqc82kJDvxsQwcr0ZtPEV0pVVtbi7KyMnznO99pe23YsGHw+XxobGxEnz59wu7jmLcONyyfFcmwbXicaVg9bRFuWTUPXl/klwzWNh1v+5sOZ3a4aey1WHLbQkN+7Xmi5AW8Ufpewjp4K4+ZHh8AlpSuwCtN7xhykFCHcJjtyUZvnaFx2xONfAKMZ5TZGgDm5yLWDvtsCtKDpn6P0UYGgFabghtWdF7iCleHWB+XdNDvEOt80uMQjmgcF2YzKtnzaZ9NgauhwdB+O1FfbzgbJPQjHegQCcwnDX62sc6Bn23oEAlWfcaLaFHq4MGDmDt3LkpKStCvXz8AwLZt29CnTx/dgaWqKpp85i4b9PqaDe0jdFEYHcI7bKveYcqtbT+HdnQ5RqI4BDKic0m0Px0JXQe9mO1JM0Qjn0IuZupgtAahsSU77OjtwsivzN2HIMRIAJV9XIZ6MtbHJR30O8Q6n/Q46CUax4VRkj2fdvR24YLKSsNeHaisNJwNEvqRDnQwAvNJg59tYu/AzzZ0MEKsP+NFdKPzCy64AKNGjcJDDz2EXbt2oaSkBE899RR+/OMfRyxIZFNxcDvKD3yOQDDSh75rBIIBlO3/DFsPGT9JleBgz06DLctteHsAsGW5Yc82fq8ACXVIBJhPsWdTjgejFaAA5p6+NxbAKAX4pL+x77dLOC7poMF80key59OmHA985WVAaan2FD0jBALAli3wVZQbzgYJ/UgHOiQayZ5PIST0gwQHnjvQQSIRfa6w2+1YsmQJPB4Ppk2bhp///Of44Q9/iNtuuy1WfiSOLC1ZDpti7KOn3WbH0pLlSeHgzu8d1+0BGXWQDvMp9ryWlwmnCsyHuafvzQfgVLX9GUXCcUkHDeZTeJI9n0LZgOee63QfKN3Y7cCiRaazQUI/0oEOiUSy51N7JPSDBAeeO9BBGhFXoF+/fli8eDG2bNmCjRs34sc//jGUKD85i8igaMt6HDhWDX/AH9F2/oAf+786hOJPu75HSaI5OIdnQEl3AJG2uQIo6Q44h2eYdpBQh0SA+RRbyrPT8FF/D6YCGAIg0tup2k9tNwXAR/09KDfxWzYJxyUdNJhP+kjmfAplg3/V60BVFeDzRbYDnw/Ytw/+1atMZ4OEfqQDHRKNZM6n9kjoBwkOPHeggzSMfgODpADNvhZ8//m70NByUveB4g/40dByEjctvhPNPvP3npHgoDhs6HnjYMBl0x/eCgCXtp3iMH+YSagDIQAwd2J/uOwK3oV2s3K9C1P2U+//KwCXXcHcif1NeUg4LumgwXwigJYNgdYWBL/7XaChQf/ClM8HNDQgeM01CLS2mM4GCf1IBzoQmUjoBwkOPHeggzS4KEXOyO6j+3D1U9NQXXcEALr9zmvo9eq6I7j6qWnYU1OVVA72TBd6TR0KpZe+ZwMovRzoNXUo7JlnfoxuJEioAyF7M12YM7E/RgDYBGDgqde7+8ck9PrAU+8fDmDOxP7YG4VjQ8JxSQcN5hMJZQN27kTwkkuAQ4e0H3R3j6nQ64cOae/ftStq2SChH+lAByITCf0gwYHnDnSQRERP3yOpyZ6aKox//HoUXjgJsyfMRMHgUZ3es/VgJZaWLEfxp+/EZMVWgoM904X06efCt7MeLRXHEaztPIYtyw13fm/tstgo/BbhdCTUgZCiERlQoOL5DV9ia0BFEYDnAJR28d4x0O4hNQXaFVKzJvZH0Qjzl32HkHBc0kGD+US+zobdsJ+fB8ct04B584Bx4zq/uawMWLQI/tWrEGhtwZxrcqKaDRL6kQ50IDKR0A8SHHjuQAcpcFGK6KLZ14IVm9dhxeZ1yB+Yh1E5I/DAhHvwRMkL+Kz6C1Qc3J4SDorDBldeJlx5mQjUNMPRAMwZOx1LSlfAnw5TT6LQi4Q6ELJmxFnY0teDxRsO4/bDXsxQgG0qsANAPbSv6uUCGK1oNzXfmOPBvKuicxXE6Ug4LumgwXwi7bPhm3/8I3x/+iOcYwqA3FwgIwOorwd27ICvvAxOFfgkx4N5V50Tk2yQ0I90oAORiYR+kODAcwc6SICLUiRiKg5ux64j+3DXqJvxRul7aPJ5U9LBnp0GT44HhYWFeKXpnZStA0ld9ma6cH3hEIypacaM7XW49LAXhcda4QqqaLUpqOzjwiv9PXgtL9PUjYsjQcJxSQcN5lPq0ikbDm7HyIryDtnwyehMS7NBQj/SgQ5EJhL6QYIDzx3oEC+4KEUIIcQU5dlpKM/+BgCgh9ODt6b/ATesuDvp/wElhJwZZgMhhBBCwsEbnRNCCIkuNv7TQgjpAmYDIYQQQk6DZweEEEIIIYQQQgghxHIUVVVVKwYKBAIoKyvDhCsnoEk1drd4RVGQ1aM3apuOw4i22uQHVAAKoPQw9s1FOtCBDtF36KG4UfL3EhQUFMButxtyMIvZjDJbA8D8XNCBDnSIjUO8M4r5RAc60KE7Ej2fgOQ4l6UDHejQGb35ZP09pVRAPek3uimONh6lAx3okGwOPd3Gt402BusQtXmgAx3oIM9BSkal+jzQgQ506EyC59OpTRP/XJYOdKBDZ3Tmk/WLUgqg9Ezd1UI60IEOXe3A0LCxwWBGJctvXOlABzp0tRNjm0Ud5hMd6ECHTjsxtlnU4Wc8OtCBDp12oO9tli9KKR47Mm4ZZmjbHk4P3pr5Im5YPsvQk1vqX90F9aQfSg8HMm6nAx3oIMUhsLra0LixwGhGma0BYH4u6EAHOsTGQUpGMZ/oQAc6nE6i5xOQHOeydKADHTqjN594o3NCCCGEEEIIIYQQYjlclCKEEEIIIYQQQgghlsNFKUIIIYQQQgghhBBiOdbf6NwggZpmeOu9KC4uhrfyGAIZCuzZaXSIg0P+wDyMzslFVlYWbhp7LbZV70DFwe0p58C5ICEk9AId5DhIOC5ZBxKCvSDHgXOhwTqQ9rAfNCTUQYID50JDQh2sRPSilOoPwrezHi0VxxGsbQEALHh3QdvPbVluuPN7wzk8A4ojNhd90UEjzenGlHGTMXvCTIwZdH7b60tuWwgAKD/wOZaWLEfRlvVo9rUkrQPngoSQ0At0kOMg4bhkHUgI9oIcB86FButA2sN+0JBQBwkOnAsNCXWIF2IXpQJ1rTj55n6oDf5u3xOsbYF3w5do/mctet44GPZMFx1i4HBe36FYe+9LGNQnB0E12OV7Rg/IxeIZv8b9k+7FTYvvxJ6aqqRz4FyQEBJ6gQ5yHCQcl6wDCcFekOPAudBgHUh72A8aEuogwYFzoSGhDvHE8DLf7Nmz8cADD0TTpY1AXSsa1+yD2th9Y7RHbfSjcc0+BOpa6RBlh/P6DsXf7nsdOZn9oCgK7DZ7l++z2+xQFAU5mf3wwc9W4dzsIUnlwLlIPGKVURJ6gQ5yHCQcl6xD4pHM+SShFyQ4cC40WIfEI9k/40noBwl1kODAudCQUId4Y2hR6u2330ZJSUm0XQBol86dfHM/0BoEVL0bAWjVtlP9Xa8s0iFy0pxurL33JaS7e8Jh13dRncPuQLq7J9bNXYY0pzspHDgXiUesMkpCL9BBjoOE45J1SDySOZ8k9IIEB86FBuuQeCT7ZzwJ/SChDhIcOBcaEuoggYgXperq6vDkk0/iggsuiIUPfDvrtUvn9DZGCBVQG/zw7aynQ5QcpoybjEF9cnQfICEcdgcGnz0AhRdOSgoHzkViEcuMktALdJDjIOG4ZB0Si2TPJwm9IMGBc6HBOiQWqfAZT0I/SKiDBAfOhYaEOkgg4kWp3/zmN/i3f/s3DBs2LBY+aKk4Htft6fA1syfM7PY7reEIBAOYPWFmUjhwLhKLWGaUhF6ggxwHCccl65BYJHs+SegFCQ6cCw3WIbFIhc94EvpBQh0kOHAuNCTUQQIRLUpt2rQJ//rXvzBnzpyYyARqmtvudm+UYG0LAjXNdDDpkD8wD2MGnd/td1rDYbfZUTB4FPIH5iW0A+cisYhlRknoBTrIcZBwXLIOiUWy55OEXpDgwLnQYB0Si1T4jCehHyTUQYID50JDQh2koPs6sZaWFvzyl7/EI488grS0NMMDKoqCHk5Plz/z1nsN77c9jgbAk9N5jAZFgUoHXQ6jc3Kj4jAqZwR2HdmXsA6cC314nGkd/o6URkUxtF17Yp1Rse4FIPxc0EGOQ6yPSz0OrIM+zOYTYD6jUiGfJPSCBAfOhQbroI9UyCeA59MhJNRBggPnQkNCHcJh1Wc83YtSixcvxujRo3HFFVcYEgrRx5OJopkvdvmz4uJiLHh3gan9A8CcsdNRWFjY6fXJKybjaONRZPXojbfocEaHrKws0+MDwAMT7sFdo25OWAfORWSsnrbI0HZT1k4xNS4Q+4yKdS8A4eeCDnIcYn1c6nFgHSLDaD4B5jMqFfJJQi9IcOBcaLAOkZHM+QTwfDqEhDpIcOBcaEiog15i/RlPUVVV1629Jk6ciNraWtjt2uVlra3aYxBdLhdKS0vDbh8IBFBWVoarJl+NXtPP7fI93spjqHu3Spf4mcicNBSe3N6dXj/y0jYEG32w9XKi312j6XAGh5vGXoslty007XDPnx7AG6XvJawD50IfHmcaVk9bhFtWzYPXF/llrI0r9uD/rv8ABQUFbRkTKbHOqFj3AhB+LuggxyHWx6UeB9ZBH2bzCTCfUamQTxJ6QYID50KDddBHKuQTwPPpEBLqIMGBc6EhoQ7hsOoznu4rpf785z/D7/e3/f+nn34aAHDfffdFJKaqKpp8XV8uF8gw/xUeAPCno8sxQutvdAjvsK16R1Qcth3akdAOnIvI8PqaDe1D59r4GYl1RsW6F0Jj0yExHGJ9XOpxYB0iw2g+tXcwSirkk4RekODAudBgHSIjmfMJ4Pl0CAl1kODAudCQUAe9xPoznu4bnQ8YMABDhgxp+9OzZ0/07NkTQ4YMiViuO+zZabBluU3tw5blhj3b+Peh6aBRcXA7yg98jkAwYGj7QDCAsv2fYeuhyoR24FwkDrHOKAm9QAc5DhKOS9YhcUiFfJLQCxIcOBcarEPikCqf8ST0g4Q6SHDgXGhIqIMUInr6nhW487u+RNeq7enwNUtLlsOmGGsRu82OpSXLk8KBc0FCSOgFOshxkHBcsg4kBHtBjgPnQoN1IO1hP2hIqIMEB86FhoQ6SMDwotQTTzyBJ554IpouAADn8Awo6Q4g0ivqFEBJd8A5PIMOUXIo2rIeB45Vwx/wh39zO/wBP/Z/dQjFn76TFA6ci8QkFhkloRfoIMdBwnHJOiQmyZpPEnpBggPnQoN1SEyS+TOehH6QUAcJDpwLDQl1kIC4K6UUhw09bxwMuGz6G0QB4NK2Uxzm/5PooNHsa8H3n78LDS0ndR8o/oAfDS0ncdPiO9Hsa0kKB84FCSGhF+ggx0HCcck6kBDsBTkOnAsN1oG0h/2gIaEOEhw4FxoS6iABcYtSAGDPdKHX1KFQeum7D7vSy4FeU4fCnumiQ5Qddh/dh6ufmobquiMA0O13XkOvV9cdwdVPTcOeGvNPM5DkwLkgIST0Ah3kOEg4LlkHEoK9IMeBc6HBOpD2sB80JNRBggPnQkNCHeKN7qfvWY0904X06efCt7MeLRXHEaztvApoy3LDnd9bu/QuCiuVdOiaPTVVGP/49Si8cBJmT5iJgsGjOr1n68FKLC1ZjuJP34nJiq0EB84FCSGhF+ggx0HCcck6kBDsBTkOnAsN1oG0h/2gIaEOEhw4FxoS6hBPxC5KAdolda68TLjyMhGoaYajAZgzdjqWlK6APx2m7nZPh8ho9rVgxeZ1WLF5HfIH5mFUzgg8MOEePFHyAj6r/gIVB7enhAPngoSQ0At0kOMg4bhkHUgI9oIcB86FButA2sN+0JBQBwkOnAsNCXWIFyK/vtcV9uw0eHJ7o7CwEJ7c3pY0Bh26puLgdrxR+h5qa2vxRul7cTlAJDhwLkgICb1ABzkOEo5L1oGEYC/IceBcaLAOpD3sBw0JdZDgwLnQkFAHK0mYRSlCCCGEEEIIIYQQkjxwUYoQQgghhBBCCCGEWA4XpQghhBBCCCGEEEKI5SiqqqpWDBQIBFBWVoYJV05Ak2rsbvGKoiCrR2/UNh2HEW21yQ+oABRA6WHsHu90oAMdou/QQ3Gj5O8lKCgogN1uN+RgFrMZZbYGgPm5oAMd6BAbh3hnFPOJDnSgQ3ckej4ByXEuSwc60KEzevPJ+qfvqYB60m90UxxtPEoHOtAh2Rx6uo1vG20M1iFq80AHOtBBnoOUjEr1eaADHejQmQTPp1ObJv65LB3oQIfO6Mwn6xelFEDpmbqrhXSgAx262oGhYWODwYxKlt+40oEOdOhqJ8Y2izrMJzrQgQ6ddmJss6jDz3h0oAMdOu1A39ssX5RSPHZk3DLM0LY9nB68NfNF3LB8Fpp83oi3r391F9STfig9HMi4nQ50oIMUh8DqakPjxgKjGWW2BoD5uaADHegQGwcpGcV8ogMd6HA6iZ5PQHKcy9KBDnTojN584o3OCSGEEEIIIYQQQojlcFGKEEIIIYQQQgghhFgOF6UIIYQQQgghhBBCiOUkzKJU/sA83DT2WmRlZeGmsdcif2AeHeiQ8g6BmmZ4K4+huLgY3spjCNQ0p6RDvJHQC3SQ4yDhmGAd5DjEGwm9QAc5DhKOCdZBjoMEJNRBgoOE40KCA+dCQ0IdrHSw/ul7EZDmdGPKuMmYPWEmxgw6v+31JbctBACUH/gcS0uWo2jLejT7WuhAh5RwUP1B+HbWo6XiOIK12hgL3l3Q9nNblhvu/N5wDs+A4ojNurMEh3gjoRfoIMdBwjHBOshxiDcSeoEOchwkHBOsgxwHCUiogwQHCceFBAfOhYaEOsTLQVENP380MgKBAMrKynDlpImw35IT9v3n9R2Ktfe+hEF9chBUg7Db7J33GQzApthw4Fg1blp8J/bUVJ1xn213oO+p7w70dKCDNIdAXStOvrkfaoM/7HuVdAd63jgY9kyXeIfA6mr8/Z0NKCgogN3eua5WEElGxaIXgMjmgg5yHGJxTETqwDrE1iHeGcV8ooNRBwnHJesQW4dEyicgec9lE/FzhQQHzsWp/QuoQzw/44lcgj+v71D87b7XkZPZD4qidNkYAGC32aEoCnIy++GDn63CudlD6ECHpHUI1LWicc0+qI3hgwIA1EY/GtfsQ6CuNakc4o2EXqCDHAcJxwTrIMch3kjoBTrIcZBwTLAOchwkIKEOEhwkHBcSHDgXGhLqEG+HiBel3n//feTm5nb4M3/+/KjIANqlc2vvfQnp7p5w2PV9u9BhdyDd3RPr5i5DmtNNBzoknYPqD+Lkm/uB1iCg99pGFUCrtp3qDyaFQziYT3Sw0kHCMcE6yHEIB/OJDlY6SDgmWAc5DuGIdT4BMuogwUHCcSHBgXOhIaEOEhwiXpTatWsXrrrqKmzcuLHtz+OPP25aJMSUcZMxqE+O7sYI4bA7MPjsASi8cBId6JB0Dr6d9dqllJF+2VYF1AY/fDvrk8IhHMwnOljpIOGYYB3kOISD+UQHKx0kHBOsgxyHcMQ6nwAZdZDgIOG4kODAudCQUAcJDhEvSu3evRsjRoxAdnZ225+MjAzTIiFmT5iJoGpstS0QDGD2hJl0oEPSObRUHI/r9lIcwsF8ooOVDhKOCdZBjkM4mE90sNJBwjHBOshxCEes8wmQUQcJDhKOCwkOnAsNCXWQ4GBoUWro0KGmB+6K/IF5GDPo/G6/yxkOu82OgsGjTD22kQ50kOYQqGlue/qBUYK1LaYe4ynBQQ/MJzpY5SDhmGAd5DjogflEB6scJBwTrIMcBz3EMp8AGXWQ4CDhuJDgwLnQkFAHCQ4AENG1aqqqYu/evdi4cSP+8Ic/IBAI4LrrrsP8+fPhcoV/OgQAKIqCHk5Plz8bnZMbiU63jMoZgV1H9nV6vUFRoNKBDgnm4K33RsXB0QB4cjqPIcGhUVFM7zsa+QR0X4dY9wIQfi7oIMch1seEHgfWwToHsxnFfKKDlQ4SjkvWwToH6fkEpMa5bKJ8rpDgwLnQkFAHKZ/xIlqUqq6uhtfrhcvlwrPPPouDBw/i8ccfR3NzMx5++GFd++jjyUTRzBe7/FlWVlYkOt3ywIR7cNeomzu9PnnFZBxtPIqsHr3xFh3okCAOxcXFWPDuAtMOc8ZOR2FhoUiHKWunmN53NPIJ6D6jYt0LQPi5oIMch1gfE3ocWAfrHMxmFPOJDlY6SDguWQfrHKTnE5Aa57KJ8rlCggPnQkNCHaR8xotoUWrAgAHYvHkzzjrrLCiKgry8PASDQfzsZz/Dgw8+CLs9/OVvx7x1uGH5rC5/dtPYa7HktoWRKHXJEyUv4I3S9zq9Xtt0vO1vOtAhURy8lcdMjw8AS0pX4JWmd0Q6NHrrTO87GvkEdJ9Rse4FIPxc0EGOQ6yPCT0OrIN1DmYzivlEBysdJByXrIN1DtLzCUiNc9lE+VwhwYFzoSGhDlI+40V2q3kAmZmZHf7/eeedh5aWFpw4cQJ9+vQJu72qqmjydX2Z2LbqHZHqdL2fQzu6HENVVTrQIeEcAhnmv9oGAP50iHcwi9l8Crl05RjrXgiNTYfEcIj1MaHHgXWw3sEMzCc6WOUg4bhkHax3MEMs8wlIrXNZ6Z8rJDhwLjQk1EHKZ7yIbnT+4Ycf4pJLLoHX+/WA27dvR2Zmpu7AOhMVB7ej/MDnCAQDhrYPBAMo2/8Zth6qpAMdksbBnp0GW5bb8PYAYMtyw56dltAO+uZM3AABAABJREFU4WA+0cFKBwnHBOsgxyEczCc6WOkg4ZhgHeQ4hCPW+QTIqIMEBwnHhQQHzoWGhDpIcAAiXJQaO3Ys3G43Hn74YezZswclJSV48skncdddd5mSaM/SkuWwKRE/FBCAdhf8pSXL6UCHpHNw5/eO6/ZSHM4E84kOVjtIOCZYBzkOZ4L5RAerHSQcE6yDHIczYUU+ATLqIMFBwnEhwYFzoSGhDhIcIpqFXr16YdmyZTh27BimTJmCn//855g2bVpUQ6toy3ocOFYNf8Af0Xb+gB/7vzqE4k+7/r41HeiQyA7O4RlQ0h1ApFdYKoCS7oBzeEZSOJwJ5hMdrHaQcEywDnIczgTziQ5WO0g4JlgHOQ5nwop8AmTUQYKDhONCggPnQkNCHSQ4RLw0OHz4cLzyyisoLS3Fxo0bMXfuXChReJx7iGZfC77//F1oaDmpu0H8AT8aWk7ipsV3otnXQgc6JJ2D4rCh542DAZdNf2AoAFzadorD2G8BpDmEg/lEBysdJBwTrIMch3Awn+hgpYOEY4J1kOMQjljnEyCjDhIcJBwXEhw4FxoS6iDBIfYpZ4DdR/fh6qemobruCAB0+13P0OvVdUdw9VPTsKemig50SFoHe6YLvaYOhdJL3/MJlF4O9Jo6FPZMV1I5xBsJvUAHOQ4SjgnWQY5DvJHQC3SQ4yDhmGAd5DhIQEIdJDhIOC4kOHAuNCTUId4OET99zyr21FRh/OPXo/DCSZg9YSYKBo/q9J6tByuxtGQ5ij99JyorlXSgg3QHe6YL6dPPhW9nPVoqjiNY23kMW5Yb7vze2qWYMfjtmgSHeCOhF+ggx0HCMcE6yHGINxJ6gQ5yHCQcE6yDHAcJSKiDBAcJx4UEB86FhoQ6xNNB7KIUoF1St2LzOqzYvA75A/MwKmcEHphwD54oeQGfVX+BioPb6UCHlHNQHDa48jLhystEoKYZjgZgztjpWFK6Av50xPQJLZIc4o2EXqCDHAcJxwTrIMch3kjoBTrIcZBwTLAOchwkIKEOEhwkHBcSHDgXGhLqEC+HhFmCrzi4HW+Uvofa2lq8UfqeJY1BBzpId7Bnp8GT2xuFhYXw5PaOy8mMBId4I6EX6CDHQcIxwTrIcYg3EnqBDnIcJBwTrIMcBwlIqIMEBwnHhQQHzoWGhDpY6ZAwi1KEEEIIIYQQQgghJHngohQhhBBCCCGEEEIIsRwuShFCCCGEEEIIIYQQy1FUVVWtGCgQCKCsrAwTrpyAJtXYHesVRUFWj96obToOI9pqkx9QASiA0sPYPd7pQAc6RN+hh+JGyd9LUFBQALvdbsjBLGYzymwNAPNzQQc60CE2DvHOKOYTHehAh+5I9HwCkuNclg50oENn9OaT9U/fUwH1pN/opjjaeJQOdKBDsjn0dBvfNtoYrEPU5oEOdKCDPAcpGZXq80AHOtChMwmeT6c2TfxzWTrQgQ6d0ZlP1i9KKYDSM3VXC+lABzp0tQNDw8YGgxmVLL9xpQMd6NDVToxtFnWYT3SgAx067cTYZlGHn/HoQAc6dNqBvrdZviileOzIuGWYoW17OD14a+aLuGH5LDT5vBFvX//qLqgn/VB6OJBxOx3oQAcpDoHV1YbGjQVGM8psDQDzc0EHOtAhNg5SMor5RAc60OF0Ej2fgOQ4l6UDHejQGb35xBudE0IIIYQQQgghhBDL4aIUIYQQQgghhJD4EQzG24AQEiesv6cUIYQQQgghhJCUZUxNM2Zsr8Nl1V7kHm+F69nx2GdTsKO3C5tyPHgtLxPl2Wnx1iSEWAAXpSIgf2AeRufkIisrCzeNvRbbqneg4uB2Sx0CNc3w1ntRXFwMb+UxBDIU2C0ObDrIcWBPkhDsBTpIc2BPkhDsBTpIc2BPxo9z6lqxeMNhfPOwFz4F2KYCRQAaAKQHVYz8qgU/OtaC2Vvr8FF/D+ZO7I+9ma6YOkmYCzrQoT2pllFclApDmtONKeMmY/aEmRgz6Py215fcthAAUH7gcywtWY6iLevR7GuJiYPqD8K3sx4tFccRrNXGWPDugraf27LccOf3hnN4BhRHbL6RSQc5DuxJEoK9QAdpDuxJEoK9QAdpDuzJ+DP1ixN4fsOXaA2oeAXAcypQ1sX7ClRgPoCph7345PW9mDOxP4pGZETVRcJc0IEO7UnljOKi1Bk4r+9QrL33JQzqk4Og2vX3nEcPyMXiGb/G/ZPuxU2L78SemqqoOgTqWnHyzf1QG/zdvidY2wLvhi/R/M9a9LxxMOxR/m0CHeQ4sCdJCPYCHaQ5sCdJCPYCHaQ5sCfjz9QvTmDp+4fxBYDrAFSh+5sbVwC4A8CjAP4aUPHi+9VQoGLNiLOi4iJhLuhAh/akekYl3xJ8lDiv71D87b7XkZPZD4qiwG6zd/k+u80ORVGQk9kPH/xsFc7NHhI1h0BdKxrX7IPa2H1jtEdt9KNxzT4E6lrpkIQO7EkSgr1AB2kO7EkSgr1AB2kO7Mn4c25dK57f8CW+AHA5gIOnXu/u1uah1w8CuAzATgDPb/gS50ShHhLmgg50aA8zysCiVGtrKx599FFcfPHFuPzyy/Hb3/4WqqpGRUYKaU431t77EtLdPeGw67uYzGF3IN3dE+vmLkOa023aQfUHcfLN/UBrENBbXhVAq7ad6jf/BAs6yHFgT+qD+dQ1ydgLdJDjwJ7UB/Opa5KxF+ggx4E9qY9Y59OiDYfRElBxHYB6AAGd2wVOvf9aAK0BFYs3HDblIWEu6ECH9jCjNCJelHr88cfx8ccfY9myZXjmmWewevVqrFq1yrSIJKaMm4xBfXJ0N0YIh92BwWcPQOGFk0w7+HbWa5fORfrvgQqoDX74dtbTIYkc2JP6YD51T7L1Ah3kOLAn9cF86p5k6wU6yHFgT+ojlvk05mgzvnnYiyJoX9nTuyAVInBquyIA3zzsxZiaZsMuEuaCDnRoDzNKI6JFqbq6OhQVFeGxxx5Dfn4+LrvsMtxxxx0oLy83LSKJ2RNmdvtdznAEggHMnjDTtENLxfG4bk8HWQ7syfAwn8KTTL1ABzkO7MnwMJ/Ck0y9QAc5DuzJ8MQ6n2ZU1sGnAM/B+H1jbNC29ynAjO11hl0kzAUd6NAeZpRGREtyW7ZsQa9evTB+/Pi212bPnm1aQhL5A/M63O0+Uuw2OwoGj0L+wDzDj20M1DS33e3eKMHaFgRqmg0/tpEOchzYk/pgPoUnWXqBDnIc2JP6YD6FJ1l6gQ5yHNiT+oh1Pl1W7cU2teun7OklCKAUwDYVuPSw19A+JMwFHejQHmbU10S0KHXgwAEMGDAA69atw+9//3v4fD4UFhbinnvugc2mb+1bURT0cHoMyXqcaR3+jpQGRYEaxmF0Tq6hfZ/OqJwR2HVknyEHb72xsD0dRwPgyek8Bh0SyyEVerJRUUzvOxr5BBjPKLP5BISfi1j3gh6HWPcCHRLLIVV60mxGMZ/0I70X6JA4DqnSk9LzKfd4K4pMGX7NDgCFx1o7jSPhXJYOdIjUgZ/x2m0fyWBNTU2oqqrC66+/joULF6KmpgaPPPIIPB4P7rjjDl376OPJRNHMFyMZthOrpy0ytN3kFZNxtPEosnr0xlvdOGRlZZlRa+OBCffgrlE3G3IoLi7GgncXmHaYM3Y6CgsL6ZDgDqnQk1PWTjG972jkE2A+o4zmExB+LmLdC3ocYt0LdEgsh1TpSbMZxXzSj/ReoEPiOKRKT4rOp2AQrmfHo8GU4dfUA3AFVbw1/Q9AuwUzCeeydKBDpA78jPc1ES1KORwONDY24plnnsGAAQMAANXV1Vi5cqXu0DrmrcMNy2dFMmwbHmcaVk9bhFtWzYPXF/lN7mqbjrf93Z3DTWOvxZLbFhrya88TJS/gjdL3DDl4K4+ZHh8AlpSuwCtN79AhwR1SoScbvXWm9x2NfAKMZ5TZfALCz0Wse0GPQ6x7gQ6J5ZAqPWk2o5hP+pHeC3RIHIdU6Unp+bTPpiA9GOkdlLsmA0CrTcENK+7u8LqEc1k60CFSB37G+5qIFqWys7PhdrvbAgsAzjnnHBw+rP/xnKqqosln7jIxr6/Z0D5CjzY9k8O26h2m3Nr2c2hHl2PocQhkmP8qEwD400GHJHBIpZ40QzTyKeRiJqOM5lNo7DM5xLoX9DjEuhfokFgOqdaTRmE+6SdReoEO8h1SrSeNEut82tHbhZFfmbtnTYiRACr7uDqNI+lclg500OvAz3hfE9FDEMaMGYOWlhbs3bu37bU9e/Z0CLFEp+LgdpQf+ByBYKQPLNUIBAMo2/8Zth6qNOxgz06DLctteHsAsGW5Td1sjA5yHNiT+mA+hSdZeoEOchzYk/pgPoUnWXqBDnIc2JP6iHU+bcrxYLQCFMDc0/fGAhilAJ/0N3ZvYglzQQc6tIcZ1W4fkbz53HPPxZVXXokHH3wQlZWV+PDDD7F06VLceuutpiSksbRkOWyKsdi02+xYWrLctIM7v3dct6eDLAf2ZHiYT+FJpl6ggxwH9mR4mE/hSaZeoIMcB/ZkeGKdT6/lZcKpAvOhPUXPCEFo2ztVbX9GkTAXdKBDe5hRGhFX4Omnn8bgwYNx66234v7778eMGTPwwx/+0LSIJIq2rMeBY9XwB/wRbecP+LH/q0Mo/rTr73xHgnN4BpR0BxDpFXUKoKQ74ByeQYckcmBP6oP51D3J1gt0kOPAntQH86l7kq0X6CDHgT2pj1jmU3l2Gj7q78FUAEMA2CPc3n5quykAPurvQbmJKzIkzAUd6NAeZpRGxItS6enpePLJJ1FaWoqPP/4Yc+fOhRKFx7lLotnXgu8/fxcaWk7qbhB/wI+GlpO4afGdaPaZ/9604rCh542DAZdNf4MoAFzadorD6AWydJDowJ7UB/Opa5KxF+ggx4E9qQ/mU9ckYy/QQY4De1Ifsc6nuRP7w2VX8C60m5XrXZiyn3r/XwG47ArmTuxvykPCXNCBDu1hRmnEPuUSlN1H9+Hqp6ahuu4IAHT7Xc/Q69V1R3D1U9Owp6Yqag72TBd6TR0KpZe++9ErvRzoNXUo7JkuOiShA3uShGAv0EGaA3uShGAv0EGaA3sy/uzNdGHOxP4YAWATgIGnXu/ug2jo9YGn3j8cwJyJ/bE3CvWQMBd0oEN7mFERPn0v1dhTU4Xxj1+PwgsnYfaEmSgYPKrTe7YerMTSkuUo/vSdqKxUno4904X06efCt7MeLRXHEaztPIYtyw13fm/t0rsY/DaFDnIc2JMkBHuBDtIc2JMkBHuBDtIc2JPxp2hEBhSoeH7Dl9gaUFEE4DkApV28dwy0e0hNgXaF1KyJ/VE0InpfY5QwF3SgQ3tSPaO4KBWGZl8LVmxehxWb1yF/YB5G5YzAAxPuwRMlL+Cz6i9QcXB7zB0Uhw2uvEy48jIRqGmGowGYM3Y6lpSugD8dMX0iBx3kObAnSQj2Ah2kObAnSQj2Ah2kObAn48+aEWdhS18PFm84jNsPezFDAbapwA4A9dC+qpcLYLSi3dR8Y44H866KzhVSpyNhLuhAh/akckYl1xJ8jKk4uB1vlL6H2tpavFH6niWNcTr27DR4cnujsLAQntzecfnHiw5yHNiTJAR7gQ7SHNiTJAR7gQ7SHNiT8WNvpgvXFw7BhFuG4pXRmbBnuVFoUzAbQKFNgT3LjVdGZ2LCLUPxve8PicmC1OlImAs60KE9qZZRvFKKEEIIIYQQQohllGenoTz7GwCAHk4P3pr+B9yw4m40+bxxNiOEWA2vlCKEEEIIIYQQEj9s/FhKSKrCo58QQgghhBBCCCGEWI6iqqpqxUCBQABlZWWYcOUENKnG7havKAqyevRGbdNxGNFWm/yACkABlB7GvrlIBzrQIfoOPRQ3Sv5egoKCAtjtdkMOZjGbUWZrAJifCzrQgQ6xcYh3RjGf6EAHOnRHoucTkBznsnSgAx06ozefrL+nlAqoJ/1GN8XRxqN0oAMdks2hp9v4ttHGYB2iNg90oAMd5DlIyahUnwc60IEOnUnwfDq1aeKfy9KBDnTojM58sn5RSgGUnqm7WkgHOtChqx0YGjY2GMyoZPmNKx3oQIeudmJss6jDfKIDHejQaSfGNos6/IxHBzrQodMO9L3N8kUpxWNHxi3DDG3bw+nBWzNfxA3LZxl6MkP9q7ugnvRD6eFAxu10oAMdpDgEVlcbGjcWGM0oszUAzM8FHehAh9g4SMko5hMd6ECH00n0fAKS41yWDnSgQ2f05hNvdE4IIYQQQgghhBBCLIeLUoSQ6BAMxtuAEEIIIYQQQkgCYf09pQghScGYmmbM2F6Hy6q9yD3eCtez47HPpmBHbxc25XjwWl4myrPT4q1JCCGEEEIIIUQoXJSKgEBNM7z1XhQXF8NbeQyBDAV2iz905w/Mw+icXGRlZeGmsddiW/UOVBzcTgc6WOZwTl0rFm84jG8e9sKnAM4xBcA1I4H0dLgaGnBBZSVGlpdh9tY6fNTfg7kT+2NvpiumToT5RAc6SHUgzCc60EGqA9FgRtGBDvF14KJUGFR/EL6d9WipOI5gbQsAYMG7C9p+bstyw53fG87hGVAcsfk2ZJrTjSnjJmP2hJkYM+j8tteX3LYQAFB+4HMsLVmOoi3r0exroQMdYuYw9YsTeH7Dl7C73MDtt8M5fz4wdmyn9zlLS4HnnsMlq17HJ6/vxZyJ/VE0IiOqLoT5RAc6SHUgzCc60EGqA9FgRtGBDnIcFNXw80cjIxAIoKysDFdOmgj7LTmG9hG1O9D31HcH+kBdK06+uR9qgz/se5V0B3reOBj2MFeEROpwXt+hWHvvSxjUJwdBNQi7zd7ZMxiATbHhwLFq3LT4TuypqaIDHaLuMPWLE1j6/mFg+HDY3nsPGDJEu4+UvbMDAgHAZgOqqhC85hpg1y7MvqY/1ow4q8t9B1ZX4+/vbEBBQQHsXe3PAsxmVFSf4qOjH2KRT5E6xKIf6UAHiQ7xzijmU+QOydyPdKBDh20SPJ8AfsZLxc8VdEgNB735xBudd0OgrhWNa/ZBbQwfVgCgNvrRuGYfAnWtUXM4r+9Q/O2+15GT2Q+KonTZGABgt9mhKApyMvvhg5+twrnZQ+hAh6g6nFvXiuc3fKktSH3yCTBgAKAoXS9IAdrrigIMGADb5s3AsGF4fsOXOCeKx0cqw3yiAx1kOhDmEx3oINWBaDCj6EAHeQ4RLUoVFxcjNze305+RI0dGRUYKqj+Ik2/uB1qDgN7ryFQArdp2qt/8U8jSnG6svfclpLt7wmHX9y1Lh92BdHdPrJu7DGlONx3oEDWHRRsOw+Zya1dIpacDTqe+DZ1OID0dtvffh93lxuINh015nAnm05k2AvOJDnSIscOZYD6daSMwn+hAhxg7hIMZdaaNwIyiAx1i7BDRotTkyZOxcePGtj9///vfMWTIENx2222mRSTh21mvXc4Z6RcbVUBt8MO3s960w5RxkzGoT47uxgjhsDsw+OwBKLxwEh3oEBWHMUeb8c3DXjin/UD7yp7eBakQTicwdCgct0zDNw97Maam2bDLmWA+hYH5RAc6xNThTDCfwsB8ogMdYuoQDmZUGJhRdKBDTB0iWpRKS0tDdnZ2258333wTqqrivvvuMy0iiZaK43HdHgBmT5iJoGpsNT4QDGD2hJl0oENUHGZU1sGnAJg/X7uHlCGJADBvHnwKMGN7nWGXM8F8smZ7gMcEHegQKcwna7YHZPQCHeggzSEczChrtgdk9AMd6CDNwfA9perq6vDiiy/ipz/9KVyu5Hnce6Cmue0JDEYJ1rYgYOJqkPyBeRgz6Pxuv8sZDrvNjoLBo5A/MI8OdDDtcFm1F84xBdpT9ozeQNNuB8aNg3NMAS49bOwmu5HAfOoe5hMd6BB9h0hgPnUP84kOdIi+Q6Qwo7qHGUUHOkTfAQAiu0arHStXrkTfvn1x3XXXRbSdoijo4fQYGtPjTOvwd6Q0KArUMA7e+uh8YHY0AJ6czmPocRidkxsVh1E5I7DryD460MGUQ+7xVuCaKN1TIDcXIyvKO43TqCjR2f8pjOYTYDyjzOYTEH4uYp1Pehxi3Y90oINEh2hmFPPpzDCf6ECHyByknEPxM578c3o60MFqB735pKiqGum3aqGqKq6++mrcddddmD59uq5tQo8LnTJlCoqKiiIdMipMnjwZR48eRd++fbF+/fou31NcXIwFCxaYHuuhhx5CYWGhIYesrCwMGWL+TvZVVVWora2lAx2MOwSDGDd+PDBrFrB0qWkHzJ4NvPgitvzjH4Dt6ws1Q7kQjccZG8knIDEyKtb5pMch1v1IBzpIdIhWRjGfwsN8ogMdInOI9zlUIuQTwM94dKBDPBz05pOhK6W2bt2KI0eO4Prrr49422PeOtywfJaRYeFxpmH1tEW4ZdU8eH2RXzpZ23S87e/uHLyVxwy5nc6S0hV4pekdQw43jb0WS25baNrhiZIX8Ebpe3SggymHfTYFroYG0+MDAOrr0WpTcMOKuzu83Oiti87+YS6fAOMZZTafgPBzEet80uMQ636kAx0kOkQro5hP4WE+0YEOkTlIOYfiZzz55/R0oIPVDnrzydCi1IcffoiLLroIZ511VsTbqqqKJp+5yye9vmZD+whdFHYmh0BGdC6B9aejyzH0OGyr3hEVh22HdtCBDqYddvR24YLKyqg4oLISlX1cncYxcMFmt5jJp5CLmYwymk+hsc/kEOt80uMQ636kAx0kO5iF+RQe5hMd6GDMIRrwM154+BmPDnSI3CEchm50XlFRgQsvvNDIpuKxZ6fBluU2tQ9blhv2bOP3bag4uB3lBz5HIBgwtH0gGEDZ/s+w9ZDxhQQ60CHEphwPfOVlQGmp9hQ9QxIBYMsW+CrK8Ul/Y/cb0Avz6cwwn+hAh+g76IX5dGaYT3SgQ/QdIoEZdWaYUXSgQ/QdAIOLUjt37sSwYcNMDSwZd37vuG4PAEtLlsOmGHs4ot1mx9KS5XSgQ1QcXsvLhFMF8NxzHe4DFZmEHVi0CE5V218sYT7FdnuAxwQd6GAU5lNstwdk9AId6CDNQS/MqNhuD8joBzrQQZqDodFra2uRkZFhenCpOIdnQEl3AJFe5akASroDzuHma1O0ZT0OHKuGP+CPaDt/wI/9Xx1C8add34+BDnSIlPLsNHzU3wP/qteBqirA54tsBz4fsG8f/KtX4aP+HpSb+A2THphP3cB8ogMdYuqgB+ZTNzCf6ECHmDrohRnVDcwoOtAhpg6Gv753xRVXmB5cKorDhp43DgZcNv2hpQBwadspDoNXk7Sj2deC7z9/FxpaTupuEH/Aj4aWk7hp8Z1o9rXQgQ5Rc5g7sT8CrS0Ifve7QEOD/oUpnw9oaEDwmmsQaG3B3In9TXnogfnU1UZgPtGBDjF20APzqauNwHyiAx1i7KAXZlRXG4EZRQc6xNjB/JGVpNgzXeg1dSiUXvruBa/0cqDX1KGwZ7qi5rD76D5c/dQ0VNcdAYBuv+sZer267giufmoa9tRU0YEOUXXYm+nCnIn9gZ07EbzkEuDQoVODdfP949Drhw5p79+1C3Mm9sfeKB4fqQzziQ50kOlAmE90oINUB/L/2bvz8KbKvH3g90nSDWgpWMpQVhdaSqGLIOA2aB0XUFyKCkL1dQMHBMbXn47III4jAsLoeAmisigqgiCUKgIOKq/MyACjQFkUEGSXrZWW7kuS8/sjJrakaU62k2+a+3NdXIxpTs7N8zy55+Q0ObFhRzEDM8jL4NW374ULY3wkYkdcgroDpajZVQxrkfNZQENCFKLS29jeDuqHs+cXOlR4FP2m3oqcywdh9MBcZHZJc7rP7hP7MG/jYuRtXxeQ36YwAzMAwMrkOChQ8caGn2DsmQrTvcOA8eOBPn2c71xQAMyeDfPyZbDU1mDsjUlYmdx83w4eDOwnZmAGmRmI/cQMzCA1A9mwo5iBGWRl4EkpNxSTAZGp8YhMjYelsBqmMmBs1gjM3bEE5lj49A0MWlXX1WDJ1nws2ZqP9E6pSEtKxsSBYzBj45v4/uSP2HViLzMwgy4ZViS3xrbEGMzZcApXv/ce6t5/DxEZmUBKChAXB5SWAvv3o25nASJUYEtSDMZffzHfIRUg7CdmYAaZGYj9xAzMIDUD2bCjmIEZ5GTgSSkPGNtFIyYpBjk5OXi3ch0q66p0z7DrxF4cPHMEj6bdg092rGcGZtA9w+H4SNya0xUZhdUYubcEA07sRY9dOxFpVVFrULCvbSS29IrHh6nxAb+oOf2G/cQMzCAzA7GfmIEZpGYgG3YUMzBDcDPwpBQReWVnu2jsbPc7AECLiBisHvE2hix5jAdVREREREREpAkvdE5E/mFgnRAREREREZF2fBVJRERERERERES6U1RVVfXYkcViQUFBAQZeNxCVqndXalcUBQkt2qCoshjexFYrzYAKQAGUFt59cpEZmIEZ/J+hhRKFjV9vRGZmJoxGo1cZfOVrR/k6BoDvc8EMzMAMgckQ7I5iPzEDMzCDK6HeT0DzOJZlBmZgBmda+0n/a0qpgFph9nZTnC0/ywzMwAzNLUPLKO+39Tcvx8Fv88AMzMAM8jJI6ahwnwdmYAZmcBbi/fTrpqF/LMsMzMAMzjT2k/4npRRAaRm+ZwuZgRmYobEH8Gq3geFlRzWX37gyAzMwQ2MP4t1mfsd+YgZmYAanB/FuM7/jazxmYAZmcHoAbXfT/aSUEmNE3L2XebVti4gYrM6djyGLR3n1DV+liw5CrTBDaWFC3IPMwAzMICWDZflJr/YbCN52lK9jAPg+F8zADMwQmAxSOor9xAzMwAwXCvV+AprHsSwzMAMzONPaT7zQORERERERERER6Y4npYiIiIiIiIiISHc8KUVERERERERERLrT/0LnIcxSWI2q0irk5eWhat85WOIUGNtFh10GCSSMg4QMRHYS1qOEDBJIGAcJGYjsJKxHCRkkkDAOEjIQ1SdhTUrIIIGEcZCQIdzwpJQbqtmKugOlqNlVDGtRDQBg2ufTHD83JEQhKr0NIrrHQTEF5o1nEjJIIGEcJGQgspOwHiVkkEDCOEjIQGQnYT1KyCCBhHGQkIGoPglrUkIGCSSMg4QM4YwnpZpgKalFxafHoJaZXd7HWlSDqg2nUf1tEVre3gXG+Mhml0ECCeMgIQORnYT1KCGDBBLGQUIGIjsJ61FCBgkkjIOEDET1SViTEjJIIGEcJGQIdzzN54KlpBblK45ALXe9OOtTy80oX3EElpLaZpVBAgnjICEDkZ2E9SghgwQSxkFCBiI7CetRQgYJJIyDhAxE9UlYkxIySCBhHCRkIC9OSp06dQqPPfYYLr/8cmRnZ2PRokUBiBVcqtmKik+PAbVWQNW6EYBa23aq2dosMkggYRwkZCBt2E+uNgKfEwEgYRwkZCBt2E+uNgKfEwEgYRwkZCBtwqGfABlrUkIGCSSMg4QMZOPxSaknnngCLVq0QF5eHiZNmoTXXnsNX3zxRSCyBU3dgVLb2/e0Lk47FVDLzKg7UNosMkggYRwkZCBt2E9N4HPC7ySMg4QMpA37qQl8TvidhHGQkIG0CYd+AmSsSQkZJJAwDhIykI1HJ6XOnz+PgoICjBkzBt26dcMf/vAHXHvttdi8eXOg8gVFza7ioG4vJYMEEsZBQgZyj/2kz/ZSMkggYRwkZCD32E/6bC8lgwQSxkFCBnIvXPoJkLEmJWSQQMI4SMhANh6dlIqOjkZMTAzy8vJQV1eHQ4cOYfv27UhNTQ1UPt1ZCqsdV9z3lrWoBpbC6pDOIIGEcZCQgbRhP2nD54R/SBgHCRlIG/aTNnxO+IeEcZCQgbQJh34CZKxJCRkkkDAOEjLQbzz69r2oqChMmTIFL774It5//31YLBbk5OTgnnvu0fwYiqKgRUSMx0EBICYiusHfnipTFKhuMlSVVnn12BcylQExSc77CJUM7nAu9Mvgjh5zEegM5Yri1Xb1+aOfAO/HwdcxANzPRaDXY6hkcIdzoV8Gd/SYCz0y+NpR7Cft+JxwLxTGQUIGd9hPNsHuJ4CvK/TM4A7nQr8M7oTTazyPTkoBwE8//YTrr78eDz30EA4cOIAXX3wRV155JW6//XZN27eNicfK3Pme7raB5cNme7Xd4CWDcbb8LBJatMFqFxny8vIw7fNpvsQDAIzNGoGcnJyQzaAV5yLwGbQK5FwEOsPQVUN92q+dr/0E+N5R3o4B4H4uAr0eQyWDVpyLwGfQKpBzoUcGf3QU+0kbPifcC4VxkJBBK/aTjH4C+LpCjwxacS4Cn0GrcHiN59FJqc2bN2PFihXYuHEjoqOj0bt3b5w5cwZvvvmm5tI6V1WCIYtHebJbh5iIaCwfNhv3LhuPqjrP3ypXVFns+NtVhqp957zKdqG5O5bg3cp1IZvBHc6Ffhnc0WMuAp2hvKrEq/3W549+ArzvKF/HAHA/F4Fej6GSwR3OhX4Z3NFjLvTI4GtHsZ+043PCvVAYBwkZ3GE/2QS7nwC+rtAzgzucC/0yuBNOr/E8Oim1Z88edO3aFdHRv719q2fPnnjrrbc0P4aqqqis8+3tclV11V49hqqqbjNY4nz/GBEAmGPR6D5CJYNWnIvAZ9AqkHOhVwZf+KOf7Fl8GQdvx8C+76YyBHo9hkoGrTgXgc+gVSDnQs8M3mI/acfnhHuhMA4SMmjFfpLRTwBfV+iRQSvOReAzaBUOr/E8utB5YmIijh49itraWsdthw4dQqdOnTxLJ5ixXTQMCVE+PYYhIQrGdt5/NlxCBgkkjIOEDKQN+0kbPif8Q8I4SMhA2rCftOFzwj8kjIOEDKRNOPQTIGNNSsgggYRxkJCBfuPRSans7GxERERg8uTJOHz4MDZs2IC33noL999/f6DyBUVUepugbi8lgwQSxkFCBnKP/aTP9lIySCBhHCRkIPfYT/psLyWDBBLGQUIGci9c+gmQsSYlZJBAwjhIyEA2Hp2Uio2NxaJFi1BYWIi7774b06dPx5gxYzBs2LBA5QuKiO5xUGJNgKfv6lMAJdaEiO5xzSKDBBLGQUIGco/95AafE34nYRwkZCD32E9u8DnhdxLGQUIGci9c+gmQsSYlZJBAwjhIyEA2Hn/73mWXXYZ33303EFnEUEwGtLy9C8pXHAFqrYCWj0IqACJt2ykmj871ic0ggYRxkJCBtGE/udoIfE4EgIRxkJCBtGE/udoIfE4EgIRxkJCBtAmHfgJkrEkJGSSQMA4SMpANR9IFY3wkWt3dDUorbeftlFYmtLq7G4zxkc0qgwQSxkFCBiI7CetRQgYJJIyDhAxEdhLWo4QMEkgYBwkZiOqTsCYlZJBAwjhIyEBevFMqnBjjIxE74hLUHShFza5iWItqnO5jSIhCVHob29v/AnC2VEIGCSSMg4QMRHYS1qOEDBJIGAcJGYjsJKxHCRkkkDAOEjIQ1SdhTUrIIIGEcZCQIdzxpJQbismAyNR4RKbGw1JYDVMZMDZrBObuWAJzLHS54r6EDBJIGAcJGYjsJKxHCRkkkDAOEjIQ2UlYjxIySCBhHCRkIKpPwpqUkEECCeMgIUM442k+DxjbRSMmpQ1ycnIQk9ImKItTQgYJJIyDhAxEdhLWo4QMEkgYBwkZiOwkrEcJGSSQMA4SMhDVJ2FNSsgggYRxkJAh3PCkFBERERERERER6Y4npYiIiIiIiIiISHc8KUVERERERERERLpTVFVV9diR2WzGzp07MWjwIFSpzle010JRFLSNice5qhJ4E1utsgAqAAVQYozMwAzMICRDjBKFdWvXISMjAyZTcL5/wdeO8nUMAN/nghmYgRkCkyHYHcV+YgZmYAZXQr2fgOZxLMsMzMAMzrT2k27NZbVaAQDr1q7Ta5dEFGLsPRHMfbOjiMiVYHUU+4mI3GE/EZFU7vpJt3dKWa1WmM1mGAwGKIqixy6JKESoqgqr1QqTyQSDITifKmZHEZErwe4o9hMRucJ+IiKptPaTbieliIiIiIiIiIiI7HihcyIiIiIiIiIi0h1PShERERERERERke54UoqIiIiIiIiIiHTHk1JERERERERERKQ7npQiIiIiIiIiIiLd8aQUERERERERERHpjieliIiIiIiIiIhIdyF1UiovLw8pKSn4+OOPdd1vSkpKgz8DBgzA5MmTUVFRoWsOADh//jxmzJiB7OxsZGRkYNCgQVi0aBGsVmvA952dne0Ygx49eiArKwvDhw/Hv//974Dvu7EMF/7ZunVr0HPcd999umWorKzEa6+9hltuuQXp6eno378/JkyYgAMHDuiy/+zsbOTl5TndnpeXh+zsbF0ySBPuHRXu/XRhjmB1FPuJ/dQY9hP7if30m2B2FPvJGfspeP0EyOgoCf3UVA4eQwW2o0wBedQAWbNmDbp06YJPPvkE99xzj677nj17NrKysmC1WnHq1ClMmTIFM2fOxAsvvKBbhuLiYgwbNgyJiYl46aWX0KlTJ+zevRsvvvgijh8/jueeey7gGSZNmoTBgwfDarXi/PnzyM/Px2OPPYYFCxbgqquuCvj+62e4UOvWrXXZf1M5IiIidNl3RUUFRowYgcrKSkycOBE9evRAcXExPvzwQwwfPhz5+fno3LmzLlnoN+HcUewn5xwX0rOj2E90IfYT+6l+jguFSz8B7CiJ2E/B7SdARkdJ6CdXOXgMFVghc1Lql19+webNmzFt2jRMnDgRx48f13VCWrdujXbt2gEA2rdvj8ceewwvvPCCrielXnnlFURGRmLhwoWIiooCAHTu3BnR0dEYO3YscnNzcfHFFwc0Q2xsbINx+POf/4zCwkJMnz4dq1evDui+G8sQTMHM8cYbb+CXX37B2rVrERcXBwDo2LEjpk+fjlOnTmHRokW6/Z8Y2YR7R7GfGs8RLOwnqo/9xH5qLEewBDsDO0oW9lPw+wmQ0VHB7gYJOcK1n0Lm43uff/45YmNjcfvttyMxMRGffPJJUPPExMTour/a2lqsWbMGI0eOdBSW3fXXX49FixahY8eOumayGzZsGH788UccPXo0KPsPN1arFatWrcJDDz3kKKv6Zs6ciaeffjoIycJbOHcU+4ns2E8ysZ/YT2TDjpKH/SSznwB2lN7CuZ9C5qTUmjVrcN1118FgMCA7Oxv5+flQVTUoWc6dO4cPPvgAt99+u277PHbsGCorK9G7d2+nnymKggEDBiAyMlK3PPVdeumlAICDBw8GZf/h5tixYzh37hz69u3b6M8TExMRHR2tcyoK545iP5Ed+0km9hP7iWzYUfKwn2T2E8CO0ls491NIfHzv1KlT2L59Ox566CEAwE033YSlS5di27ZtLifN30aNGgWj0QhVVVFVVYX4+Hj89a9/1WXfAFBaWgrA9nZCaeyZ9Loo4PPPP48XX3yxwW1JSUlYs2aNLvtvKsemTZvQokWLgO63uLgYQMPPV//nP//B448/7vhvvcajsTEwm80i3nqrp3DvKPZTQxI6iv3EfrJjP7Gf6gvnfgLkdBT7yYb9JLefAL7Gq4/HUIHtqJA4KbVmzRpERUXhmmuuAQD069cPrVu3xqpVq3QrrKlTpyIjIwOqqqK4uBiLFy/Gfffdh9WrV+Oiiy4K+P7j4+MB2L6dQZry8nIAQKtWrXTZ34QJE3DTTTc1uM1k0n8pN5ZDj7f82t/Oaf8/MgDIyspCfn4+AGD9+vVYunRpwHMAjY+BnvuXItw7iv3UkISOYj+xn+zYT/EA2E924dxPgJyOYj/ZsJ/iAcjsJ4Cv8erjMVRg9x8yJ6Wqq6vRp08fx20WiwWff/45nnvuOV3exta+fXt07doVANCtWzekpaWhf//+WLduHXJzcwO+/y5duiA2Nhbff/890tPTnX4+ZswY3H///bp+g4vd/v37AQDdu3fXZX8XXXSRYy6CKVg5unbtivj4eOzYscOxFmJiYhxZ9DhJatfYGOi5fynCvaPYTw1J6Cj2E/vJjv3EfqovnPsJkNNR7Ccb9pPcfgL4Gk9vUvrJvi89O0r8NaUOHz6MH374AZMnT0Z+fr7jzz/+8Q+Ul5fjiy++CEoug8EAVVVhsVh02Z/JZMLgwYPx4Ycfora2tsHPNmzYgA0bNiAxMVGXLBdauXIl0tLSmuXXU0pkMpkwdOhQvPfee47fYNR35syZIKQKX+wo9hP9hv0kC/uJ/UQNsaPkYD/J7ieAHaW3cO4n8e+UWrNmDeLj4zFs2LAGF3pLTk7GG2+8gfz8fAwZMiTgOc6fP4/CwkIAts/VvvPOO7BYLMjOzg74vu3Gjx+Pe+65B4888gjGjx+P3/3ud9i6dStmzZqFBx54AJdddlnAM5SVlaGwsNDxFtcVK1Zg7dq1eOeddwK+7wszXKhly5a6XI9AgvHjx2Pbtm0YPnw4xo0bh7S0NBQXF+Pjjz/GihUrcNtttwU7YthgR9mwn5xzXChcOor9JAf7yYb95JzjQuHSTwA7Sgr2k42EfgJkdBT7KXz7KSROSg0ZMqTRbx6477778NJLL+HMmTNo3759QHOMHz/e8b9jYmLQq1cvzJ8/X9czx+3atcPSpUsxe/ZsPPXUUygpKUGXLl0wYcIE3HfffbpkmDZtGqZNmwZFUdC2bVv07NkTixYt0u1z3/UzXOhPf/oTxo4dq1uOYIqJicEHH3yA9957D3PnzsXRo0cRGRmJ9PR0zJ49G3/4wx+CHTFssKNs2E/OOS4ULh3FfpKD/WTDfnLOcaFw6SeAHSUF+8lGQj8BMjqK/RS+/aSowfrOTSIiIiIiIiIiClvirylFRERERERERETND09KERERERERERGR7nhSioiIiIiIiIiIdMeTUkREREREREREpDuelCIiIiIiIiIiIt3xpBQREREREREREemOJ6WIiIiIiIiIiEh3PClFRERERERERES640mpZmD06NF49tlnG9z22WefISUlBbNnz25w+9y5c3HHHXcAAEpLS/GXv/wFV111FQYMGICJEyeitLTUcd+ffvoJDz/8MC6//HJkZ2fjrbfegtVqbTJLbm4utm/f7nR7bW0tXn75Zfz+97/HFVdcgccffxynT592+e+ZOHGi23+3q33df//9SElJcfzJysrCI488gqNHjzb6OJ9++inuv//+BrfV1NTgxRdfxJVXXokrr7wSU6ZMQWVlpdtMROTM246yU1UVDz/8MPLy8hrc/uOPPyI3NxdZWVm4+eab8dlnn7nNcv311+PMmTNOt7vrw927d2P48OHIyMjAzTffjPz8fLf78rWjVq5ciVtuuQVZWVm45557sG3bNsfPKisrMXnyZPTv3x9XXHEFnnvuOVRUVLjNREQNBeoYatGiRQ2e5ykpKXj55ZebzOJtP/nzeM3XY6gTJ044/bvtf7799tsmMxFRQ4Hqp+LiYowfPx5ZWVnIzs7GJ5984jaLr6/xamtrcdttt2Hr1q1u9/XMM89g9erVTrdPnDixQadkZGRg+PDh2LVrV4P7ff3117jjjjuQlZWFIUOG4KuvvnL8zGKx4O9//zuuvvpqZGVl4U9/+hOKiorcZqLA4kmpZqBv377YvXt3g9u2bt2KxMREpyd+QUEB+vXrBwB4/vnnsW/fPsybNw8LFy7ETz/9hMmTJwMAqqqqMHr0aLRv3x4rVqzA888/j/feew9Lly51maOqqgoHDhxAenq6089ef/11fPnll/j73/+OpUuXwmw2Y9y4cVBVtcH91qxZg40bN7r9Nze1LwB4+OGH8c033+Df//43li9fjvj4eIwdO9Zpf1u2bMGUKVOctp8zZw7++9//Yt68eXj77bfx3Xff4dVXX3Wbi4icedtRAGC1WjF16lRs2rSpwf1qa2vxxz/+ET179sQnn3yCUaNGYeLEiU77qe/o0aOIjo5G+/btnX7WVB+WlZVh1KhRyMrKwmeffYbHH38ckydPbnCS6EK+dtS//vUv/O1vf8PYsWORn5+Pq6++GqNHj3a8YJ02bRr27NmDhQsXYtGiRdi1axdmzJjhMg8RNS4Qx1AAcPDgQYwYMQLffPON48/jjz/uMoe3/eTv4zXAt2OoDh06NPg3f/PNN7jtttvQu3dvZGZmusxERM4C1U/PPvssysrKsGzZMowZMwaTJ092OrFTn6+v8WpqavDkk0/iwIEDmv7dW7ZswYABAxr92aBBgxzdsmrVKmRkZOCxxx5z/GJu3759GDduHIYOHYr8/HwMHz4cf/rTn7Bv3z4AwLx587B27Vq89tpr+Pjjj3H+/Hn8+c9/1pSLAkilkPfdd9+pPXr0UMvLyx233Xjjjeq7776rpqWlqVVVVY7b+/Xrp65fv16tqKhQU1NT1YKCAsfPtm/frqampqrV1dXqxo0b1T59+qg1NTWOn7/11lvqsGHDXOb417/+pY4ePbrRn1111VXqmjVrHP995swZNTk5WT18+LDjtuLiYvX3v/+9OnToUPWZZ55p8t/c1L5yc3PV119/vcFtZ8+eVZOTk9W9e/c6bps9e7baq1cv9bbbblNzc3Mb3H/IkCHqBx984Pjv999/X7311lubzEREjfOmo1RVVU+fPq3m5uaq1113ndq3b1915cqVjvt9//33anJycoPHvOuuu9QFCxa4zLF06VL1hRdecLrdXR/u379fffrpp1Wr1er4+Z133qnOmzfP5b587agnnnhCnTJlSoP73HTTTeqyZctUVVXVv/71r+p3333n+Nl7772nDho0yGUeImpcII6hVFVVhw8frn700Ueac3jbT/4+XvPHMVR927ZtU9PS0tSDBw+6vA8RNS4Q/XT06FE1OTlZPX78uOPnkyZNavK1ly+v8Q4cOKDefvvt6pAhQ9Tk5GR1y5YtTf6bf/rpJ5evuZ555hmnnHV1dWpmZqb65ZdfqqqqqrNmzVIfeeSRBvd5+OGH1VdffVVVVVt32Y8zVVVVv/zySzU9Pb3JTBR4fKdUM9C7d29ERETg+++/BwCcPn0aJ0+exD333IPY2FjHWy0PHz6M8+fPo2/fvjAYDHjrrbeQmpra4LEsFgsqKiqQmpqKN954A5GRkQ1+Xl5e7jLH5s2bceWVVzrdbrVaMWvWLFx11VVOPysrK3P875dffhl33HEHLrvsMrf/Zlf7ciUmJsbptk2bNmHhwoW46aabnH4WHx+Pf/7znzh//jzOnz+P9evXO40VEWnjTUcBwPfff48OHTpg5cqViI2NbfCYrVu3BgB8/PHHsFqt2LFjBw4dOoSePXu6zOGqN9z1YXJyMmbOnAlFUWC1WrFhwwYcPnwYV1xxhcf7cuXCjnr00Ufx0EMPOd3P3pnPP/88+vTpA8D2cZnPPvuswTvMiEibQBxDAcChQ4fQrVs3zTm87Sd/Hq+54ukxVH2vvPIK7r33Xlx66aWa90dENoHop507d6JDhw7o1KmT42d9+vTBjh07XObw5TXef//7X/Tv3x/Lli3T9G/evHmzy3dJNcZkMjXov7vuugtPPfWUyzzjxo3DjTfeCAD45Zdf8PHHH/P4SQCelGoGIiMjkZGR4Xjb5ZYtW9CrVy+0bNkSV1xxhePtnQUFBejevTvatGmD6Oho/P73v2/wJH7//feRkpKCtm3bol27dujfv7/jZ9XV1Vi+fHmTJeHqrZYGgwFXXXUV4uPjG+yrTZs2SElJAWAroO+++w5jx47V9G9u6m2dF6qtrcVbb73l+Pyx3dKlS12W0J///GecOHEC/fv3R//+/XH+/Hk8//zzmvZHRA1501EAkJ2djZkzZ6Jt27ZOj9mxY0c8+eST+Pvf/45evXph+PDhePTRR12+0FJVFd9++22jz3l3fWhXW1uL9PR0jBkzBnfccUeTH0XxtaPS0tIavKD917/+hSNHjjg95jPPPIMbbrgBRUVFTX40iIgaF4hjqKKiIpSUlGDVqlXIzs7GoEGDsHDhQqePv9n50k/+PF5rjDfHUHbbtm1DQUEBHnvsMU37IqKGAtFPhYWFSExMbLCfiy66qNHr2dn58hpvxIgRmDRpUqMnt13tS+tJc7PZjA8//BARERGOfJdeeil69OjhuM+BAwcaPan2+uuv46qrrsL27ds1XcuYAssU7ADkH3379nUU1tatWx0HKP369XNc/PfCa7XUt3jxYqxbtw4LFixw+pnVasXEiRNRUVHh8sCipKQEZ86caXDA4sqXX36Jd955By+88AIiIyNRU1OD559/HlOmTEF0dLTb7bXs6+2338Y777wDwHaApqoqXn/9dSiK4vbxAeDYsWPo0KEDZsyYAbPZjL/97W+YMWMGpk6dqml7ImrI1466UF1dHQ4dOoRhw4YhJycH3377Lf7xj3/giiuuaPACzW7fvn3o0KGD4x1WTWmqD5ctW4ZDhw7hb3/7G7p169bou5n83VHHjh3Ds88+iyFDhiAtLa3Bz0aNGoX77rsPr7zyCkaNGoW8vDwYDPx9E5En/H0MdejQIQC2F3pvvvkm9u7di6lTp8JoNOLBBx902t5f/eSv4zVfj6Hsli9fjhtvvLHR62QRkTb+7qeqqiqnd1ZGRkaitra20e19eY3nKavViu+++w7Tpk1zeZ/Vq1fjn//8JwDbtaosFgueffZZtGzZ0um+586dw/jx43H55ZfjhhtuaPCzO+64A9dffz0WLFiAhx9+GGvWrEGrVq08zkz+wSPXZqL+hfC2bt3qKKZ+/fphz549qK2tRUFBQaMfN/nwww8xdepUPPvss7jmmmsa/MxsNuPpp5/G119/jblz56Jdu3aN7t++T3cHLF9++SWeeOIJ5Obm4p577gFgu6h4r169cO2112r6t2rZ1/Dhw5Gfn4/8/Hzk5eXhiSeewJNPPonNmze7ffzy8nL85S9/wTPPPIP+/fvj6quvxrRp07By5UqcPXtWU0YiasiXjmpMfn4+9uzZg8mTJyMtLQ0PPvgghgwZgvnz5zd6f60fV2mqDyMjI5GWloYhQ4bgj3/8Iz744INGH8OfHXX48GE88MAD6Ny5c6MnxS+77DJkZmbiH//4B/bv389vtyLygr+Pofr164ctW7bg6aefRkpKCu68806MHTvW5cXH/dFP/jxe8+UYqn6er776CrfffrvmbYjImb/7KSoqyukEVG1trcs3BvjyGs9TP/zwAzp37ux0yYb6srOzHf2Un5+Pv/71r3j11VedvqG5qKgI//M//+M4qX7hL+y6du2K3r17Y+bMmaiursb69eu9ykz+wXdKNRNZWVk4e/Ysdu/ejbNnz+Lyyy8HAHTv3h2xsbH49ttvcfDgQaez6AsXLsTMmTPx5z//Gf/zP//T4Gd1dXX43//9X2zatAnz5s1zPGZjtBxQrVmzBn/+858xfPhwTJo0qcHtRUVFyMrKAgBHUf7zn/9s9PPNWvbVunVrdO3a1fHfqamp+Pbbb7F06VK32x46dAiVlZUN3vrZs2dPWK1WnD592uktr0Tknrcd5cr333+P5OTkBgdJqampjX5dMWDrjcbeoVCfqz48fvw4jhw50uDE+WWXXYbi4mKX+/JHRx04cAAPPvggOnfujAULFjgOGGtra/F///d/uPrqqx2/1UtISEB8fLzLTETkWiCOoewfQ7a79NJLXX48xpd+Avx/vObLMZRdQUEBzGYzrr76ak33J6LG+buf2rdvj6Kiogb3LSoqcnki25fXeJ7Ssq+WLVs26Kfk5GTs3bsXixcvRk5ODgDgzJkzeOCBBwDYPk5Y/1IM//d//4eePXs63sEZFRWFzp078/gpyPhOqWaiRYsWSE1NxbJly9C7d2/H53YVRcEVV1yBvLw8dOvWrcGTctWqVZg5cyaeffZZPPLII06POWXKFGzatAnz5893+0LRXYls3rwZf/7znzFy5Eg899xzDX72wQcfYPXq1Y4z3tnZ2Y6z4N7syxVVVWGxWNzez37S6eDBg47b7G/Fr39RQCLSzpuOakpiYmKD5yhge1dRY8/Ruro67Nq1y3Fh8MY01Ye7du3C//7v/6K6utpx2549e3DJJZc0+lj+6KizZ8/i4YcfRteuXbFw4cIGbyk3GAyYOHEivv76a8dtJ0+eRHFxMS8mTOQFfx9Dffzxx7j55psbXENq7969jXaGr/0E+Pd4zRWtx1B2O3fuRFpaGqKiojzeFxH9xt/9lJmZiZ9//hmnT5923LZt2zaX18n05TWepzy53l19qqrCarUCACorK/Hoo4/CYDBg8eLFTh8ffvnllxu8xiwvL8eRI0d4/BRkPCnVjFxxxRVYs2aN0wFJv3798NVXXzV4W2dJSQn+9re/4a677sKtt96KwsJCxx+LxYJNmzYhLy8PEydORNeuXR0/O3funNN+T58+jbq6OnTu3LnRXGazGZMmTcIVV1yBUaNGNdhXbW0tOnbsiK5duzr+tGzZ0uksuNZ92VVWVjr2cerUKXz44YfYvHkzBg0a5HYcf/e73+Haa6/Fc889hz179mD37t147rnncOutt2p+wUxEzjzpKHeGDBmC48ePY9asWTh27Bjy8/OxfPly3H///U733blzJ5KTk12+Nd1dH1533XWIjY3FlClTcPjwYaxevRoLFizAmDFjnB7LXx318ssvw2q14qWXXmpw34qKCphMJgwbNgyvvvoqvvvuO+zZswf/+7//ixtuuAHdu3fXPIZE9Bt/HkNdddVVKCwsxMsvv4yjR49izZo1mD9/Ph599FGn/fraT/48XrPz5RjK7sCBA3yRR+Qn/uynzp0745prrsHTTz+Nffv24eOPP8Znn32GkSNHOu3X19d4nqitrcWePXuafKcnYLvOnX0fZ86cwdq1a7F69WpHP7399ts4duwYXn75ZQBw3Nf+7XsjR47EwoULsXHjRhw4cABPP/00unTpgt///vce5SX/4sf3mpE+ffrgnXfecbrIb79+/VBVVdWgyDZt2oTKykqsWrUKq1atanD/r776ynEBuSlTpmDKlCmOn3Xs2BEbNmxocH93X925Z88enDx5EidPnnS6BsL777/f6EWJXdH6NaHvvPOO4yKdERER6Nq1K6ZMmYLbbrtN035eeeUVzJgxA6NHj4aiKLjhhhvwzDPPaM5JRM486Sh3OnfujHfeeQczZ87EkiVLkJSUhJdeeqnRa9O5+82buz7s1KkTFixYgBdffBE5OTlo06YNJk2ahD/84Q9Oj+WPjlJVFV9++SWqq6txyy23NNhu3LhxGD9+PJ588kkoioInnngClZWVuOmmmzB58mS3+yWixvnzGKpTp06YN28eZs2ahaVLl+Kiiy7CU089hcGDBzvt19d+8ufxmp2vx1CA7eNAF34lPRF5x9/9NHPmTPzlL3/Bvffei3bt2mHatGlIT0932q+er/EKCgrQo0cPt++uXLduHdatWwcAMJlM+N3vfofHHnvMcdL/n//8J6qrq52ua3XXXXdhxowZGDlyJKqqqvDXv/4V586dw9VXX40333yTXxITZIrq6vtpiYiIiIiIiIiIAoSnBImIiIiIiIiISHc8KUVERERERERERLrjSSkiIiIiIiIiItIdT0oREREREREREZHueFKKiIiIiIiIiIh0x5NSRERERERERESkO56UIiIiIiIiIiIi3fGkFBERERERERER6Y4npYiIiIiIiIiISHc8KUVERERERERERLrjSSkiIiIiIiIiItIdT0oREREREREREZHueFKKiIiIiIiIiIh0x5NSRERERERERESkO56UIiIiIiIiIiIi3fGkFBERERERERER6c6k146sVivMZjMMBgMURdFrt0QUAlRVhdVqhclkgsEQnHPl7CgiciXYHcV+IiJX2E9EJJXWftLtpJTZbMbu3bv12h0RhaDevXsjMjIyKPtmRxGRO8HqKPYTEbnDfiIiqdz1k24npexnxgYNHoQqtcarx1AUBW1j4nGuqgSqqnq8vVplAVQACqDEGJmBGZhBSIYYJQrr1q4L2rukAN87ytcxAHyfC2ZgBmYITIZgdxT7iRmYgRlcCfV+AprHsSwzMAMzONPaT7qdlLK/nbNKrYHx3iSvHqNFRAxW5s7HkMWjUFlX5fH2pYsOQq0wQ2lpQty9lzEDMzCDkAxVy08C+K0ngsHXjvJ1DADf54IZmIEZApMh2B3FfmIGZmAGV0K9n4DmcSzLDMzADM609hMvdE5ERERERERERLrjSSkiIiIiIiIiIjurNdgJwoZuH98jIiIiIiIiIpImo7AaI/eW4MqTVUgprkXka/1wxKBgf5tIbE6KwYep8djZLjrYMZslnpQiIp+kd0pFr6QUJCQk4M6sm7Hn5H7sOrE32LGIiNhPRCQW+4lIhotLajFnwylcfaoKdQqwRwVWAigDEGtV0eOXGjx0rgajd5dgU4cYjMvugMPxwfm2cD3p2VE8KUVEHouOiMLQPoMxemAuMjr3dNw+94HpAICdx3/AvI2LsXLbWlTXefdNLERE3mA/EZFU7CciWe7+8Tze2HAatRYV7wJ4XQUKGrlfpgpMAHD3qSps+egwxmZ3wMrkOH3D6iBYHcVrShGRRy5N7Ib/Tl6DOSNfQq+OKY3ep1fHFMwZ+RL+O3kNLmnXVeeERBSu2E9EJBX7iUiWu388j3lfnMJhi4reAB4GsMvFfXf9+vPeAI5YVMz/4iTu/vG8XlF1EcyO8vqkVG1tLW677TZs3brVb2GISLZLE7vhy6c+QlJ8eyiKAqPB2Oj9jAYjFEVBUnx7fPX0Mt0PrNhPROGH/UREUrGfiGS5pKQWb2w4jR8BXAXgxK+3u7q0uf32EwCuBHAAwBsbTuPiktrABtVJsDvKq5NSNTU1ePLJJ3HgwAG/hCAi+aIjorDq8QWIjWoJk1HbJ39NRhNio1oif9xCREdEBTihDfuJKPywn4hIKvYTkTyzN5xCjUXFLQBKAVg0bmf59f43A6i1qJiz4VSgIupGQkd5fFLq4MGDuPfee3Hs2DGfd05EoWNon8Ho3DZJc1nZmYwmdLmoI3IuHxSgZL9hPxGFJ/YTEUnFfiKSJeNsNa4+VYWVAI5C+wkpO8uv260EcPWpKmQUVvs7oq4kdJTHJ6X++9//on///li2bJnPOyei0DF6YC6sqqs3tTbNYrVg9MBcPydyxn4iCk/sJyKSiv1EJMvIfSWoU4DX4f21jAywbV+nACP3lvgtWzBI6CiPv31vxIgRPu+UiEJLeqfUBt/A4CmjwYjMLmlI75Qa0K87Zj8RhR/2ExFJxX4ikufKk1XY4+Jb9rSyAtgBYI8KDDhV5Z9gQSClozw+KeUrRVHQIiLGq21jIqIb/O2pMkWBygzMwAweZ+iV1Pg3MHgqLSkZB88ccbq9XFH88vj+4O1c+DoPgO/rgRmYIRwzBLqfADkdJXkemIEZmIH9JPlYlhmYwS6luBYrvXpkZ/sB5JyrddpPKIwDIOc1nqKqqurtzlNSUvD++++jf//+bu9rsVhQUFCAoUOHYuVKfy0DzwwePBhnz55FYmIi1q5dywzMwAwaMyQkJKBrV9+/XeHo0aMoKipyut3eC5mZmTAaG/+2B0950k8AO4oZmCFUMwS6nwD/dxT7iRmYITwysJ/0EQprgRmEZLBa0adfP8wD8Jgf9vU2gNEAtv33v4Dhtw8Dih+HX0l5jaf7O6XOVZVgyOJRXm0bExGN5cNm495l41FV5/kFxYoqix1/MwMzMIP2DHdm3Yy5D0z3Kl99Mza+iU92rHe6vbyqxOfH9hdvO8rXeQB8Xw/MwAzhmCHQ/QTI6Sj2EzMwQ2hlYD9pEy7H08wgI8MRg4JYq9fvy2kgDkCtQcGQJQ1PcYXCOAByXuPpflJKVVVU1vn2ucuqumqvHsP+pjBmYAZm8CzDnpP7fcrmeJyf9ze6Dx/esOl3vs6Ft/Ng3zczMAMzeJYh0P1UP0OwSZ4HZmAGZmA/ST6WZQZmsNvfJhI9fqnxKZtdDwD72kY67ScUxgGQ8xrP2wvOE1EY2XViL3Ye/wEWq6dfmmpjsVpQcOx77P55n5+TEVG4Yz8RkVTsJyJ5NifFoJcCZMK3b9/LApCmAFs6eHfNKAmkdBRPShGRJvM2LoZB8a4yjAYj5m1c7OdEREQ27Ccikor9RCTLh6nxiFCBCbB9i543rLBtH6HaHi+USegon05K7d+/X/NF8IgotK3cthbHz52E2WL2aDuzxYxjv/yMvO3rApSscewnovDBfiIiqdhPRLLsbBeNTR1icDeArgA8/XoA46/bDQWwqUMMdrbz/hs8JZDQUXynFBFpUl1Xg7veeBRlNRWaS8tsMaOspgJ3znkE1XX++ew2EdGF2E9EJBX7iUiecdkdEGlU8DlsFyvXemLK+Ov9/wkg0qhgXHaHQEXUjYSO4kkpItLsp7NHcMOsYThZcgYAXH7+2H77yZIzuGHWMBwqPKpbRiIKT+wnIpKK/UQky+H4SIzN7oBkAJsBdPr1dlcnR+y3d/r1/t0BjM3ugMPxkYENqpNgd5Tu375HRKHtUOFR9Jt6K3IuH4TRA3OR2SXN6T67T+zDvI2Lkbd9HX/DR0S6YT8RkVTsJyJZVibHQYGKNzacxm6LipUAXgewo5H7ZsB2DamhsL1DalR2B6xMjtMzbsAFs6N4UoqIPFZdV4MlW/OxZGs+0julIi0pGRMHjsGMjW/i+5M/YteJvcGOSERhiv1ERFKxn4hkWZHcGtsSYzBnwyk8eKoKIxVgjwrsB1AK20f1UgD0UmwXNf8mKQbjr28+75C6ULA6iieliMgnu07sxcEzR/Bo2j34ZMd6VNZVBTsSEREA9hMRycV+IpLhcHwkbs3piozCaozcW4IBp6qQc64WkVYVtQYF+9pG4t0OMfgwNT7kL2ruCT07iieliIiIiIiIiChs7WwXjZ3tfgcAaBERg9Uj3saQJY/xhLEOeKFzIiIiIiIiIiI7A0+V6IUjTUREREREREREulNUVVX12JHFYkFBQQEGXjcQlap3V2pXFAUJLdqgqLIY3sRWK82ACkABlBbefXKRGZiBGfyfoYUShY1fb0RmZiaMRqNXGXzla0f5OgaA73PBDMzADIHJEOyOYj8xAzMwgyuh3k9A8ziWZQZmYAZnWvtJ/2tKqYBaYfZ2U5wtP8sMzMAMzS1Dyyjvt/U3L8fBb/PADMzADPIySOmocJ8HZmAGZnAW4v3066ahfyzLDMzADM409pP+J6UUQGkZvmcLmYEZmKGxB/Bqt4HhZUc1l9+4MgMzMENjD+LdZn7HfmIGZmAGpwfxbjO/42s8ZmAGZnB6AG130/2klBJjRNy9l3m1bYuIGKzOnY8hi0d5dRX80kUHoVaYobQwIe5BZmAGZpCSwbL8pFf7DQRvO8rXMQB8nwtmYAZmCEwGKR3FfmIGZmCGC4V6PwHN41iWGZiBGZxp7Sde6JyIiIiIiIiIiHTHk1JERERERKQvqzXYCYiISAD9rylFRERERERhJaOwGiP3luDKk1VIKa5F5Gv9cMSgYH+bSGxOisGHqfHY2S462DGJiEhnPClFIclSWI2q0irk5eWhat85WOIUGMPwQCa9Uyp6JaUgISEBd2bdjD0n92PXib3BjkUU1thPNuwnInmC0U8Xl9RizoZTuPpUFeoUICIjE7ixBxAbi8iyMvTetw89dhZg9O4SbOoQg3HZHXA4PjKgmdhPRDJJOIZiBv3xpBSFDNVsRd2BUtTsKoa1qAYAMO3zaY6fGxKiEJXeBhHd46CYmu8nU6MjojC0z2CMHpiLjM49HbfPfWA6AGDn8R8wb+NirNy2FtV1NcGKSRRW2E827CcieYLZT3f/eB5vbDgNY2QU8OCDiJgwAcjKcrpfxI4dwOuvo/+yj7Dlo8MYm90BK5Pj/JqF/UQkk4RjKGYILp6UopBgKalFxafHoJaZXd7HWlSDqg2nUf1tEVre3gXGAP+WLRguTeyGVY8vQOe2SbCqjV+LoVfHFMwZ+RKeGfQ47pzzCA4VHtU5JVF4YT/ZsJ+I5AlmP93943nM++IU0L07DOvXA127ur6OVHo68M47MD3/PAw33oj5XxyEAhUrklv7JQv7iUgmCcdQzBB8Hp1iO3PmDCZMmIB+/frh2muvxfTp01FTw98kUGBZSmpRvuII1HLXT9L61HIzylccgaWkNsDJ9HVpYjd8+dRHSIpvD0VRYDQYG72f0WCEoihIim+Pr55ehkvaddU5afCwo0hv7Ccb9pN77CfSWzD76ZKSWryx4bTthNSWLUDHjoCiAMbGuwFGo+3nHTvCsHUrcNlleGPDaVzshyzsJ/fYTxQMEo6hmEEGzSelVFXFhAkTUFVVhQ8//BD/+Mc/8H//93947bXXAhiPwp1qtqLi02NArRVQtW4EoNa2nWpuHt/sEh0RhVWPL0BsVEuYjNre4GgymhAb1RL54xYiOiIqwAmDjx1FemM/2bCf3GM/kd6C3U+zN5yCITLK9g6p2FggIkLbhhERQGwsDF98AWNkFOZsOOVTDvaTe+wnCoZgdxQzyKL5pNShQ4dQUFCA6dOno3v37ujbty8mTJiAzz77LJD5KMzVHSi1vY1R65PUTgXUMjPqDpQGJJfehvYZjM5tkzQfUNmZjCZ0uagjci4fFKBkcrCjSG/sJxv2k3vsJ9JbMPsp42w1rj5VhYhhw20f2dN6QsouIgLo1g2me4fh6lNVyCis9joL+8k99hMFg4RjKGaQQ/NJqXbt2mHBggVISEhocHt5ebnfQxHZ1ewqDur2UowemOvyGgjuWKwWjB6Y6+dE8rCjSG/sJxv2k3vsJ9JbMPtp5L4S1CkAJkxwfQ0pdywWYPx41CnAyL0lXmdhP7nHfqJgkHAMxQxyaD4pFRcXh2uvvdbx31arFYsXL8aAAQMCEozIUljt+OYBb1mLamDx4TdsEqR3SkVG554ur4HgjtFgRGaXNKR3SvVzMlnYUaQn9pMN+0kb9hPpKdj9dOXJKkRkZNq+Zc/VNaTcMRqBPn0QkZGJAaeqvHoI9pM27CfSW7A7ihnk8frb92bNmoUffvgBK1as8Gg7RVHQIiLGq33GREQ3+NtTZYoClRlCJkNVqXcHIRcylQExSc77CJVx6JWU4tVjXygtKRkHzxzxKoM7vo5DuaJ4tV1T9O4oX8cA8H0umEG/DIHuJy0Z3NFjHALdT1oyuOOPcfB3R7GfmKE591NKcS1wYw+/ZEBKCnrs2tnov5P9ZBPq/QSEz2sbZrCR8BqPGbTR6zWeoqqqp59gxKxZs/Duu+/iH//4B26++WZN21gsFhQUFGDo0KFYuXKlp7v0i8GDB+Ps2bNITEzE2rVrmUF4hry8PEybNs3nfU2aNAk5OTleZQg0LRkSEhLQtavv3wBz9OhRFBUVeZUh0Oy9kJmZCaO3v1Wthx3FDIHOEOh+0pJBD+4yBLqftGTQgz87iv3EDIHOENR+slrRp18/YNQoYN48nzNg9Ghg/nxs++9/AUPDD3iwn2zYTzLmgRm0Z5DwGo8Z9KG1nzx+p9SLL76IpUuXYtasWZrLqr5zVSUYsniUx9sBtjN0y4fNxr3LxqOqzvO3qRVVFjv+Zgb5Gar2nfMq24Xm7liCdyvXeZXBHT3G4c6smzH3gele5atvxsY38cmO9V5lcMfXcSivKvFqv40JVkf5OgaA73PBDPplCHQ/acngjh7jEOh+0pLBHX+Mg786iv3EDOHQT0cMCiLLyvySAaWlqDUoGLLkMY8yAOwnT/E1HjPolUHCazxm0Eav13genZSaM2cOPvroI7z66qu45ZZbPA4F2L52tLLOt7eqVdVVe/UY9jeFMUNoZLDE+eftyOZYNLqPUBmHPSf3+5TN8Tg/7xc/Dr6S0FHejoF938wQGhkC3U9aMmgVyHEIdD9pyaCVP8bBF+wnZtArQ7D7aX+bSPTet88vGbBvH/a1jfTq+IX9pJ2EfgKa/2sbZrCR8BqPGTwT6Nd4mi90/tNPP2Hu3LkYNWoU+vTpg8LCQscfokAwtouGISHKp8cwJETB2M77z+lLsOvEXuw8/gMsVotX21usFhQc+x67f/bTAaJQ7CjSE/vJhv2kDfuJ9BTsftqcFIO6nQXAjh22b9HzhsUCbNuGul07saWDd9dCYT9pw34ivQW7o5hBHs0npb766itYLBa8+eabuOaaaxr8IQqUqPQ2Qd1einkbF8OgaH66NmA0GDFv42I/J5KHHUV6Yz/ZsJ/cYz+R3oLZTx+mxiNCBfD6607XgdLMaARmz0aEans8b7Gf3GM/UTBIOIZiBjk0t/To0aOxf//+Rv8QBUpE9zgosSbA03c3KoASa0JE97iA5NLbym1rcfzcSZgtZo+2M1vMOPbLz8jb3vg1IZoTdhTpjf1kw35yj/1EegtmP+1sF41NHWJgXvYRcPQoUFfn2QPU1QFHjsC8fBk2dYjBTh/eBcB+co/9RMEg4RiKGeTw8tcXRPpQTAa0vL0LEGnQ/mRVAETatlNMzWOJV9fV4K43HkVZTYXmAyuzxYyymgrcOecRVNfVBDghUfhhP9mwn4jkCXY/jcvuAEttDaw33QSUlWk/MVVXB5SVwXrjjbDU1mBcdgefcrCfiGQKdkcxgyzN419BzZoxPhKt7u4GpZW26/IrrUxodXc3GOMjA5xMXz+dPYIbZg3DyZIzAODyGgn220+WnMENs4bhUOFR3TIShRv2kw37iUieYPbT4fhIjM3uABw4AGv//sDPP9t+4OoaU/bbf/7Zdv+DBzE2uwMO+yEL+4lIJgnHUMwgg0ffvkcULMb4SMSOuAR1B0pRs6sY1iLn31wZEqIQld7G9jbIZnLW+EKHCo+i39RbkXP5IIwemIvMLmlO99l9Yh/mbVyMvO3r+Bs+Ih2wn2zYT0TyBLOfVibHQYGKNzb8BGPPVJjuHQaMHw/06eN854ICYPZsmJcvg6W2BmNvTMLKZP99LIX9RCSThGMoZgg+npSikKGYDIhMjUdkajwshdUwlQFjs0Zg7o4lMMeiWXzzgBbVdTVYsjUfS7bmI71TKtKSkjFx4BjM2Pgmvj/5I3ad2BvsiERhh/1kw34ikieY/bQiuTW2JcZgzoZTuPq991D3/nuIyMgEUlKAuDigtBTYvx91OwsQoQJbkmIw/vqL/fIOqQuxn4hkknAMxQzBxZNSFJKM7aIRkxSDnJwcvFu5DpV1VcGOFBS7TuzFwTNH8GjaPfhkx/qwHQciSdhPNuwnInmC0U+H4yNxa05XZBRWY+TeEgw4sRc9du1EpFVFrUHBvraR2NIrHh+mxvt0UXNPsJ+IZJJwDMUM+uNJKSIiIiIiCqid7aKxs93vAAAtImKwesTbGLLksWb/YouIiJrWvD6MSERERERE8hn4MoSIiHhSioiIiIiIiIiIgkBRVVXVY0cWiwUFBQUYeN1AVKrefaOFoihIaNEGRZXF8Ca2WmkGVAAKoLTw7pOLzMAMzOD/DC2UKGz8eiMyMzNhNBq9yuArXzvK1zEAfJ8LZmAGZghMhmB3FPuJGZiBGVwJ9X4CmsexLDMwAzM409pP+l9TSgXUCrO3m+Js+VlmYAZmaG4ZWkZ5v62/eTkOfpsHZmAGZpCXQUpHhfs8MAMzMIOzEO+nXzcN/WNZZmAGZnCmsZ/0PymlAErL8D1byAzMwAyNPYBXuw0MLzuqufzGlRmYgRkaexDvNvM79hMzMAMzOD2Id5v5HV/jMQMzMIPTA2i7m+4npZQYI+LuvcyrbVtExGB17nwMWTzKq2/qKF10EGqFGUoLE+IeZAZmYAYpGSzLT3q130DwtqN8HQPA97lgBmZghsBkkNJR7CdmYAZmuFCo9xPQPI5lmYEZmMGZ1n7ihc6JiIiIiIiIiEh3PClFREREzZvVGuwERERERNQI/a8pRURERBRAGYXVGLm3BFeerEJKcS0iX+uHIwYF+9tEYnNSDD5MjcfOdtHBjklEREQU9nhSygPpnVLRKykFCQkJuDPrZuw5uR+7TuwNuwyWwmpUlVYhLy8PVfvOwRKnwKjzwb2EcWAGkkTCWpCQQUI/MUPwMlxcUos5G07h6lNVqFOAPSqwEkAZgFirih6/1OChczUYvbsEmzrEYFx2BxyOjwxoJpLRDRIySHheShgHZrCRsB7IRsJ6kJBBwprkONiE2zjwpJQb0RFRGNpnMEYPzEVG556O2+c+MB0AsPP4D5i3cTFWbluL6rqaZptBNVtRd6AUNbuKYS2y7WPa59McPzckRCEqvQ0iusdBMQXmU6ESxoEZSBIJa0FCBgn9xAzBz3D3j+fxxobTqLWoeBfA6ypQ0Mj9MlVgAoC7T1Vhy0eHMTa7A1Ymx/k1C8noBgkZJDwvJYwDM9hIWA9kI2E9SMggYU1yHGzCeRx4UqoJlyZ2w6rHF6Bz2yRY1cavR9GrYwrmjHwJzwx6HHfOeQSHCo82uwyWklpUfHoMapnZ5X2sRTWo2nAa1d8WoeXtXWD082+eJYwDM5AkEtaChAwS+okZgp/h7h/PY94Xp/AjgFsAHIXri2buAvAwgBcA/NOiYv4XJ6FAxYrk1n7JQjK6QUIGCc9LCePADDYS1gPZSFgPEjJIWJMcB5twHwePT28dPXoUjzzyCLKysnDddddhwYIFfgkizaWJ3fDlUx8hKb49FEWB0WBs9H5GgxGKoiApvj2+enoZLmnXtVllsJTUonzFEajlrhdnfWq5GeUrjsBSUuu3DBLGgRlCA/upoea+HiX0EzMEP8MlJbV4Y8Np/AjgKgAnfr3d1aXN7befAHAlgAMA3thwGhf7cTwaw35qiP3UEI+fmncGCeuhKeHST4CM9SAhg4Q1yXGw4Th4eFLKarVi9OjRaNOmDVatWoUXXngBb775JlavXu2XMFJER0Rh1eMLEBvVEiajtjeTmYwmxEa1RP64hYiOiGoWGVSzFRWfHgNqrYCqdSMAtbbtVLPv33YkYRyYITSwn1xrjutRQj8xg4wMszecQo1FxS0ASgFYNG5n+fX+NwOotaiYs+GUTzmawn5yjf1k3wg8fmqmGSSsh6aESz8BMtaDhAwS1iTHwYbjYOPRSamioiKkpqbir3/9K7p164aBAwfiyiuvxLZt23wOIsnQPoPRuW2S5oVhZzKa0OWijsi5fFCzyFB3oNT29j2ti9NOBdQyM+oOlPqcQcI4MENoYD81rbmtRwn9xAzBz5BxthpXn6rCStg+sqf1hJSd5dftVgK4+lQVMgqrvc7SFPZT09hPv+LxU7PMIGE9NCVc+gmQsR4kZJCwJjkONhwHG49OSiUmJuK1115Dq1atoKoqtm3bhm+//Rb9+vXzOYgkowfmuvwspzsWqwWjB+Y2iww1u4qDuj0gYxyYITSwn9xrTutRQj8xQ/AzjNxXgjoFeB1eXI/gVwbYtq9TgJF7S7zO0hT2k3vsJ/9tD8gYB2awkbAemhIu/QTIWA8SMkhYkxwHG46DjdeXTM/OzsaIESOQlZWFm2++2ecgUqR3SkVG554uP8vpjtFgRGaXNKR3Sg3pDJbCascV971lLaqBxYffOksYB2YITeynxjWX9Sihn5hBRoYrT1Zhz6/fsuftm8etAHYA2KMCA05Vefko2rGfGsd++g2Pn5pPBgnrwRPNtZ8AGetBQgYJa5LjYMNx+I3X3773+uuvo6ioCH/9618xffp0TJ48WdN2iqKgRUSMV/uMiYhu8LenyhQFqpsMvZJSvHrsC6UlJePgmSMhm6Gq1D8H5qYyICbJeR+hMg7MoI2vz81yRfFqO1e87SfA+3HwdQwA93MR6LUQKhkC3U/MEDoZUoprsdIvCYD9AHLO1Tb67/RnR7GfmsZ+svHleSlhHJjBRo/1EOr9BPA1np4Z+BrPhuNgE+hx0NpPiqqqnn56sIHPP/8cTz31FLZv347ISNdfCWixWFBQUIChQ4di5Up/HUJ6ZvDgwTh79iwSExOxdu3aRu+TkJCArl19v5L90aNHUVRUFLIZ8vLyMG3aNJ8zTJo0CTk5OV5lkDAOzKAPey9kZmbCaPTutwWN0dpPQGh0VKDXQqhkCHQ/MUOIZLBa0adfP8wD8JjPCYC3AYwGsO2//wUMDd9IHoiOYj81jv1k48vzUsI4MIONHuuB/RQ6x9MSMvA1ng3HwSbQ46C1nzx6p1RRUREKCgrwhz/8wXHbZZddhrq6OpSXl6Nt27ZuH+NcVQmGLB7lyW4dYiKisXzYbNy7bDyq6jx/i1hRZbHjb1cZ7sy6GXMfmO5VvvpmbHwTn+xYH7IZqvad83n/ADB3xxK8W7nOqwwSxoEZtPH1uVleVeLVfuvzRz8B3neUr2MAuJ+LQK+FUMkQ6H5ihtDJcMSgINbq0+/WHOIA1BoUDFnifIrL145iP2nHfrLx5XkpYRyYwUaP9RDq/QTwNZ6eGfgaz4bjYBPocdDaTx6dlDpx4gTGjRuHjRs3on379gCAPXv2oG3btpoLS1VVVNb59jaxqrpqrx7D/qawpjLsObnfp2yOx/l5f6P7CJUMljj/vBXYHIuQHgdm8Iyvz01f+KOf7Fl8GQdvx8C+76YyBHothEqGQPcTM4ROhv1tItHjF9+uhWDXA8C+tpFN9qS32E/asZ9sfHleShgHZrDRcz14S0o/AXyNp0cGvsaz4TjY6DUO7nh0ofPevXsjLS0NkyZNwsGDB7Fx40bMmjULf/zjHz15GNF2ndiLncd/gMXq6RdL21isFhQc+x67f94X0hmM7aJhSIjyensAMCREwdjO++tXSBgHZggd7Cf3mst6lNBPzCAjw+akGPRSgEz49u17WQDSFGBLB++uh+IO+8k99tNvePzUfDJIWA/uhEM/ATLWg4QMEtYkx8GG41DvMTy5s9FoxNy5cxETE4Nhw4bhL3/5C+6//3488MADPoWQZt7GxTAo3h3eGg1GzNu4uFlkiEpvE9TtARnjwAyhgf3kXnNajxL6iRmCn+HD1HhEqMAE+PbtexMARKi2xwsE9pN77Cf/bQ/IGAdmsJGwHpoSLv0EyFgPEjJIWJMcBxuOg43HI9C+fXvMmTMH27ZtwzfffIM//vGPUPz8zVnBtnLbWhw/dxJmi9mj7cwWM4798jPytjf+me9QyxDRPQ5KrAnwdHoVQIk1IaJ7nM8ZJIwDM4QO9pNrzW09SugnZgh+hp3torGpQwzuBtAVgKeX+DX+ut1QAJs6xGBnAN+NwH5yjf30Kx4/NcsMEtaDO+HQT4CM9SAhg4Q1yXGw4TjYePtu92atuq4Gd73xKMpqKjQvELPFjLKaCtw55xFU1/l+fQsJGRSTAS1v7wJEGrQvUgVApG07xeT78pIwDsxAkkhYCxIySOgnZpCRYVx2B0QaFXwO28XKtZ6YMv56/38CiDQqGJfdwaccJKMbJGQI9nMCkDEOzGAjYT2QjYT1ICGDhDXJcbDhONiw5Vz46ewR3DBrGE6WnAEAl5/1tN9+suQMbpg1DIcKjzarDMb4SLS6uxuUVtquia+0MqHV3d1gjG/662M9IWEcmIEkkbAWJGSQ0E/MEPwMh+MjMTa7A5IBbAbQ6dfbXR3g2G/v9Ov9uwMYm90Bh/04HuFMQjdIyCDheSlhHJjBRsJ6IBsJ60FCBglrkuNgw3Hw8Nv3ws2hwqPoN/VW5Fw+CKMH5iKzS5rTfXaf2Id5Gxcjb/u6gLwbRUIGY3wkYkdcgroDpajZVQxrkfM+DAlRiEpvY3v7XwB+oyNhHJiBJJGwFiRkkNBPzBD8DCuT46BAxRsbTmO3RcVKAK8D2NHIfTNgu4bUUNjeITUquwNWJgf+4zHhREI3SMgg4XkpYRyYwUbCeiAbCetBQgYJa5LjYBPu48CTUm5U19VgydZ8LNmaj/ROqUhLSsbEgWMwY+Ob+P7kj9h1Ym9YZFBMBkSmxiMyNR6WwmqYyoCxWSMwd8cSmGMR0G8FsZMwDsxAkkhYCxIySOgnZgh+hhXJrbEtMQZzNpzCg6eqMFIB9qjAfgClsH1ULwVAL8V2UfNvkmIw/nq+QypQJHSDhAwSnpcSxoEZbCSsB7KRsB4kZJCwJjkONuE8Djwp5YFdJ/bi4JkjeDTtHnyyYz0q66rCMoOxXTRikmKQk5ODdyvXhe04MANJImEtSMggoZ+YIXgZDsdH4tacrsgorMbIvSUYcKoKOedqEWlVUWtQsK9tJN7tEIMPU+MDelFzakhCN0jIIOF5KWEcmMFGwnogGwnrQUIGCWuS42ATbuPAk1JERETUrOxsF42d7X4HAGgREYPVI97GkCWP8UUfERERkTD8sDIRERE1bwYe7hARERFJxKM0IiIiIiIiIiLSnaKqqqrHjiwWCwoKCjDwuoGoVL27WryiKEho0QZFlcXwJrZaaQZUAAqgtPDuk4vMwAzM4P8MLZQobPx6IzIzM2E0Gr3K4CtfO8rXMQB8nwtmYAZmCEyGYHcU+4kZmIEZXAn1fgKax7EsMzADMzjT2k/6X1NKBdQKs7eb4mz5WWZgBmZobhlaRnm/rb95OQ5+mwdmYAZmkJdBSkeF+zwwAzMwg7MQ76dfNw39Y1lmYAZmcKaxn/Q/KaUASsvwPVvIDMzADI09gFe7DQwvO6q5/MaVGZiBGRp7EO828zv2EzMwAzM4PYh3m/kdX+MxAzMwg9MDaLub7iellBgj4u69zKttW0TEYHXufAxZPMqrb9ApXXQQaoUZSgsT4h5kBmZgBikZLMtPerXfQPC2o3wdA8D3uWAGZmCGwGSQ0lHsJ2ZgBma4UKj3E9A8jmWZgRmYwZnWfuKFzomIiIiIiIiISHc8KUVE/mG1BjsBERERERERhRD9rylFRM1CRmE1Ru4twZUnq5BSXIvI1/rhiEHB/jaR2JwUgw9T47GzXXSwYxIREREREZFQIXNSylJYjarSKuTl5aFq3zlY4hQYdX7Bm94pFb2SUpCQkIA7s27GnpP7sevEXl0zSBgHCRk4FzbBGIeLS2oxZ8MpXH2qCnUKEJGRCdzYA4iNRWRZGXrv24ceOwswencJNnWIwbjsDjgcHxnQTMEWrmvhQhLGQUIGzoWcDBLmItg4DzYcB2aoj+tBDs6FDcdBTgYJcyEhg55zIfqklGq2ou5AKWp2FcNaVAMAmPb5NMfPDQlRiEpvg4jucVBMgfkkYnREFIb2GYzRA3OR0bmn4/a5D0wHAOw8/gPmbVyMldvWorquJiAZJIyDhAycC5tgjsPdP57HGxtOwxgZBTz4ICImTACyspzuF7FjB/D66+i/7CNs+egwxmZ3wMrkOL9mCbZwXwt2EsZBQgbOhZwMEuYi2DgPNhwHZqiP60EOzoUNx0FOBglzISFDsOZCUb3+/lHPWCwWFBQU4LpB2TDem+T+/iW1qPj0GNQys9v7KrEmtLy9C4xu3o3huAJ9S21XoL80sRtWPb4AndsmwapaYTQYnXNaLTAoBhw/dxJ3znkEhwqP+jWDhHGQkIFzYRPMcbj7x/OY98UpoHt3GNavB7p2tV1HyuicARYLYDAAR4/CeuONwMGDGH1jB6xIbt3oY1uWn8TX6zYgMzMTxsYeTweedFQg1gLg2XoIxFrwNIOEcZCQgXMhJ0Og5iLYHcV+8jwDx4EZGjx+M14PodRPAI+nHY/PcRCTQcJcSMgQiLnQ2k9en2IbPXo0Jk6c6O3mTbKU1KJ8xRGo5e4nBQDUcjPKVxyBpaTWbxkuTeyGL5/6CEnx7aEoSqOTAgBGgxGKoiApvj2+enoZLmnX1W8ZJIyDhAycC5tgjsMlJbV4Y8Np2wmpLVuAjh0BRWn8hBRgu11RgI4dYdi6FbjsMryx4TQu9uN4uBOojgr3tWAnYRwkZOBcyMkgYS60Yj81/+eEhHFgBhuuB8/wNZ4N16QN+6EhHkMFZi68Oim1Zs0abNy40S8BLqSaraj49BhQawW0vodLBVBr2041+/4NYNERUVj1+ALERrWEyajtE44mowmxUS2RP24hoiOifM4gYRwkZOBc2AR7HGZvOAVDZJTtHVKxsUBEhLYNIyKA2FgYvvgCxsgozNlwyqccWgWqo7gWbCSMg4QMnAs5GSTMhVbsp4aa43NCwjgwgw3Xg2f4Gs8Z16QN+8G+EXgMBf/PhccnpUpKSjBz5kz07t3b5503pu5Aqe1ta55+qFAF1DIz6g6U+pxhaJ/B6Nw2SfOk2JmMJnS5qCNyLh/kcwYJ4yAhA+fCJpjjkHG2GlefqkLEsOG2j+xpPSFlFxEBdOsG073DcPWpKmQUVnudRYtAdlS4rwU7CeMgIQPnQk4GCXOhBfupcc3tOSFhHJjBhutBO77Gc41r0ob98CseQwHw71x4fFLq5Zdfxh133IHLLnP/uURv1OwqDur2ADB6YC6sqndnHS1WC0YPzPU5g4RxkJCBc2ETzHEYua8EdQqACRNs15DyKoQFGD8edQowcm+J11m0CGRHhftasJMwDhIycC7kZJAwF1qwn1xrTs8JCePADDZcD9rxNV7TuCZt2A/+215KBglz4dFJqc2bN+O7777D2LFjfd5xYyyF1Y4rzXvLWlQDiw/vxEjvlIqMzj1dfo7SHaPBiMwuaUjvlOp1BgnjICED58Im2ONw5ckqRGRk2r5lz9sLaBqNQJ8+iMjIxIBTVd49hgaB7CiuBRsJ4yAhA+dCTgYJc6EF+6lpzeU5IWEcmMGG60E7vsZzj2vShv3wGx5D+a+jNL9Hq6amBs8//zymTJmC6Ohor3eoKApaRMQ0+rOqUv+8WDWVATFJzvsoUxSobjL0SkrxS4a0pGQcPHPEqwwSxkFCBs6FTbDHIaW4Frixh18yICUFPXbtdNpPuaL4/NCB7qhArwXA/VwEei1oySBhHCRk4FzIyaDHXPjaUewn7UL9OSFhHJjBJlzWg/R+Ang8bcdxkJNBwlxIyBDoudDaT5pPSs2ZMwe9evXCtddeqzlcY9rGxGNl7vxGf5aXl4dpn0/z6fEBYGzWCOTk5DjdPnjJYJwtP4uEFm2w2kWGhIQEn/cPABMHjsGjafd4lUHCOEjIwLmwCeo4WK2IfK2f7eLm/hAXh0iritUj3gYMv71Rc+iqoT4/dKA7KtBrAXC/HgK9FrRkkDAOEjJwLuRk0GMufO0o9pN2of6ckDAOzGATLutBej8BPJ624zjIySBhLiRkCPRcaO0nzSel1qxZg6KiImRlZQEAamttX0H4z3/+Ezt27ND6MDhXVYIhi0c1+rOqfec0P05T5u5Ygncr1zndXlRZ7PjbVYY7s27G3Aem+5xhxsY38cmO9V5lkDAOEjJwLmyCPQ5HDAoiy8p83j8AoLQUtQYFQ5Y81uDm8qoSnx860B0V6LUAuJ+LQK8FLRkkjIOEDJwLORn0mAtfO4r9pF2oPyckjAMz2ITLepDeTwCPp+04DnIySJgLCRkCPRda+0nzSakPPvgAZrPZ8d9///vfAQBPPfWU1ocAAKiqisq6xt+qZonz/SM8AGCORaP7UFXVbYY9J/f7JcOen/d7nUHCOEjIwLmwCfY47G8Tid779vklA/btw762kU77sWfwRaA7KtBrwb7vpjIEei1oySBhHCRk4FzIyaDnXHiL/aRdqD8nJIwDM9iE23rwFl/jeYavK359HB/GQUIGCXMhIYNec+GO5gudd+zYEV27dnX8admyJVq2bImuXbtqT+uGsV00DAlRPj2GISEKxnbefx5614m92Hn8B1isFq+2t1gtKDj2PXb/7P2LeAnjICED58Im2OOwOSkGdTsLgB07bN+i51UIC7BtG+p27cSWDo1/ptlXge4orgUbCeMgIQPnQk4GCXPhDvvJvebynJAwDsxgw/WgDV/jacM1acN++A2PofzXUR59+54eotLbBHV7AJi3cTEMindDYzQYMW/jYp8zSBgHCRk4FzbBHIcPU+MRoQJ4/fUG14HyLIQRmD0bEart8UJVuK8FOwnjICED50JOBglzEWycBxuOAzPUx/UgB+fChuMgJ4OEuZCQQcJceH1SasaMGZgxY4bPAS4U0T0OSqwJ8PTdbAqgxJoQ0T3O5wwrt63F8XMnYbaY3d+5HrPFjGO//Iy87Y1/7twTEsZBQgbOhU0wx2Fnu2hs6hAD87KPgKNHgbo6zx6grg44cgTm5cuwqUMMdvpwNt8TgeiocF8LdhLGQUIGzoWcDBLmwhPsp4aa23NCwjgwgw3Xg+f4Gs8Z16QN++FXPIYC4N+5EPdOKcVkQMvbuwCRBu2TowCItG2nmHz/J1XX1eCuNx5FWU2F5skxW8woq6nAnXMeQXVdjc8ZJIyDhAycC5tgj8O47A6w1NbAetNNQFmZ9hNTdXVAWRmsN94IS20NxmV38ClHsHEt2EgYBwkZOBdyMkiYi2DjPNhwHJihPq4HOTgXNhwHORkkzIWEDBLmQtxJKQAwxkei1d3doLTSdh12pZUJre7uBmN8pN8y/HT2CG6YNQwnS84AgMvPWdpvP1lyBjfMGoZDhUf9lkHCOEjIwLmwCeY4HI6PxNjsDsCBA7D27w/8/POvO3Px+WP77T//bLv/wYMYm90Bh/04HsES7mvBTsI4SMjAuZCTQcJcBBvnwYbjwAz1cT3Iwbmw4TjIySBhLiRkCPZcaP72Pb0Z4yMRO+IS1B0oRc2uYliLnM/AGRKiEJXexva2Nz+cJbzQocKj6Df1VuRcPgijB+Yis0ua0312n9iHeRsXI2/7uoD8JkPCOEjIwLmwCeY4rEyOgwIVb2z4CcaeqTDdOwwYPx7o08f5zgUFwOzZMC9fBkttDcbemISVyb6/vVSKcF8LdhLGQUIGzoWcDBLmItg4DzYcB2aoj+tBDs6FDcdBTgYJcyEhQzDnQuxJKcD2drbI1HhEpsbDUlgNUxkwNmsE5u5YAnMsfLrSvFbVdTVYsjUfS7bmI71TKtKSkjFx4BjM2Pgmvj/5I3ad2BvwDBLGQUIGzoVNMMdhRXJrbEuMwZwNp3D1e++h7v33EJGRCaSkAHFxQGkpsH8/6nYWIEIFtiTFYPz1FzeLd0hdKNzXgp2EcZCQgXMhJ4OEuQg2zoMNx4EZ6uN6kINzYcNxkJNBwlxIyBCsuRD58b3GGNtFIyalDXJychCT0kaXSbnQrhN78cmO9SgqKsInO9YH5f84JIyDhAycC5tgjMPh+EjcmtMVA+/thnd7xWPXib2o/Xg5MH8+aj9ejl0n9uLdXvEYeG833HZX12Z5QupC4boWLiRhHCRk4FzIySBhLoKN82DDcWCG+rge5OBc2HAc5GSQMBcSMug5F6LfKUVEcu1sF42d7X4HAGgREYPVI97GkCWPobKuKsjJiIiIiIiIKBSEzDuliEg4A+uEiIiIiIiItOOrSCIiIiIiIiIi0p2iqqqqx44sFgsKCgow8LqBqFS9u1K7oihIaNEGRZXF8Ca2WmkGVAAKoLTw7pOLzMAMzOD/DC2UKGz8eiMyMzNhNBq9yuArXzvK1zEAfJ8LZmAGZghMhmB3FPuJGZiBGVwJ9X4CmsexLDMwAzM409pP+l9TSgXUCrO3m+Js+VlmYAZmaG4ZWkZ5v62/eTkOfpsHZmAGZpCXQUpHhfs8MAMzMIOzEO+nXzcN/WNZZmAGZnCmsZ/0PymlAErL8D1byAzMwAyNPYBXuw0MLzuqufzGlRmYgRkaexDvNvM79hMzMAMzOD2Id5v5HV/jMQMzMIPTA2i7m+4npZQYI+LuvcyrbVtExGB17nwMWTzKq2/4Kl10EGqFGUoLE+IeZAZmYAYpGSzLT3q130DwtqN8HQPA97lgBmZghsBkkNJR7CdmYAZmuFCo9xPQPI5lmYEZmMGZ1n7ihc6JiIiIiIiIiEh3PClFRERERERERES640kpIiIiIiIiIiLSXciclLIUVqNq3znk5eWhat85WAqrwzJDeqdU3Jl1MxISEnBn1s1I75Qalhk4F8wgiYT1KCGDhLUgIYOEuZCQQcJcSMgQbBLWgoQMEtaChAycC2aQRsKalJBBwnqQkEHCXEjIIGEu9Myg/7fveUA1W1F3oBQ1u4phLaoBAEz7fJrj54aEKESlt0FE9zgopsCcX5OQIToiCkP7DMbogbnI6NzTcfvcB6YDAHYe/wHzNi7Gym1rUV1X02wzcC6YQRIJ61FCBglrQUIGCXMhIYOEuZCQIdgkrAUJGSSsBQkZOBfMII2ENSkhg4T1ICGDhLmQkEHCXAQrg6J6/f2jnrFYLCgoKMB1g7JhvDfJ/f1LalHx6TGoZWa391ViTWh5excY4yObvJ/jCvQttV2BXkKGSxO7YdXjC9C5bRKsqhVGg9E5p9UCg2LA8XMnceecR3Co8Gizy8C5aN4ZLMtP4ut1G5CZmQmj0fnx9OBJRwViPQKezYWEDIFYC6GYQcJcSMggYS4ClSHYHcV+8jxDc16PnAtmaLBNCPUTIOOYXkKG5npMH4pzISGDhLkI5ms8kR/fs5TUonzFEajl7hcGAKjlZpSvOAJLSW2zynBpYjd8+dRHSIpvD0VRGl0YAGA0GKEoCpLi2+Orp5fhknZdm1UGzgUzSCJhPUrIIGEtSMggYS4kZJAwFxIyBJuEtSAhg4S1ICED54IZpJGwJiVkkLAeJGSQMBcSMkiYi2Bn8Pik1BdffIGUlJQGfyZMmOCXMIDtrXMVnx4Daq2A1vdwqQBqbdupZmuzyBAdEYVVjy9AbFRLmIzaPmVpMpoQG9US+eMWIjoiqllk4FwwgyfYT/pkkLAWJGSQMBcSMkiYCwkZ3GE/6ZNBwlqQkIFzwQyeCHQ/ATLWpIQMEtaDhAwS5kJCBglzISGDxyelDh48iOuvvx7ffPON48/UqVN9DmJXd6DU9tY5Tz9UqAJqmRl1B0qbRYahfQajc9skzQvDzmQ0octFHZFz+aBmkYFzwQyeYD/pk0HCWpCQQcJcSMggYS4kZHCH/aRPBglrQUIGzgUzeCLQ/QTIWJMSMkhYDxIySJgLCRkkzIWEDB6flPrpp5+QnJyMdu3aOf7ExcX5HMSuZldxULeXkmH0wFxYVe/OvlqsFowemNssMnAumMET7Cd9MkhYCxIySJgLCRkkzIWEDO6wn/TJIGEtSMjAuWAGTwS6nwAZa1JCBgnrQUIGCXMhIYOEuZCQwauTUt26dfN5x42xFFY7rnbvLWtRjU9f2yghQ3qnVGR07unys5zuGA1GZHZJ8+lrGyVk4Fwwg6fYT4HPIGEtSMggYS4kZJAwFxIyaMF+CnwGCWtBQgbOBTN4KpD9BMhYkxIySFgPEjJImAsJGSTMhYQMAODRe7RUVcXhw4fxzTff4O2334bFYsEtt9yCCRMmIDLS/Td1AICiKGgREdPoz6pKqzyJ45KpDIhJct5HmaJADYEMvZJS/JIhLSkZB88cCdkMnIvwyVCuKD4/tj/6CXA9DoFej4D7uZCQIdBrIVQySJgLCRkkzIUeGXztKPaTPhnCZT1yLpihPun9BMg4ppeQIRyO6UNlLiRkkDAXUl7jeXRS6uTJk6iqqkJkZCRee+01nDhxAlOnTkV1dTUmT56s6THaxsRjZe78Rn+Wl5eHaZ9P8yRSo8ZmjUBOTo7T7YOXDMbZ8rNIaNEGqwVnSEhI8Hn/ADBx4Bg8mnZPyGbgXIRPhqGrhvr82P7oJ8B1RwV6PQLu50JChkCvhVDJIGEuJGSQMBd6ZPC1o9hP+mQIl/XIuWCG+qT3EyDjmF5ChnA4pg+VuZCQQcJcSHmN59FJqY4dO2Lr1q1o3bo1FEVBamoqrFYrnn76aTz77LMwGt2/7etcVQmGLB7V6M+q9p3zJI5Lc3cswbuV65xuL6osdvwtOcOdWTdj7gPTfc4wY+Ob+GTH+pDNwLkInwzlVSU+P7Y/+glw3VGBXo+A+7mQkCHQayFUMkiYCwkZJMyFHhl87Sj2kz4ZwmU9ci6YoT7p/QTIOKaXkCEcjulDZS4kZJAwF1Je43l2iXUA8fHxDf770ksvRU1NDc6fP4+2bdu63V5VVVTWNf52OUuc7x/hAQBzLBrdh6qqIZFhz8n9fsmw5+f9IZ2BcxF+GXzlaz/ZszSWMdDr0b5v6RkCvRZCJYOEuZCQQcJc6JnBF+ynwGcIt/XIuWCG+hl8Ech+AmQc00vIEE7H9NLnQkIGCXMh5TWeRxc6//e//43+/fujquq3He7duxfx8fGaC6spxnbRMCRE+fQYhoQoGNtFh3SGXSf2YufxH2CxWrza3mK1oODY99j9876QzsC5YAZPsJ/0ySBhLUjIIGEuJGSQMBcSMrjDftIng4S1ICED54IZPBHofgJkrEkJGSSsBwkZJMyFhAwS5kJCBsDDk1JZWVmIiorC5MmTcejQIWzcuBEzZ87Eo48+6lOI+qLS2wR1eykZ5m1cDIPi8ZcjArBdBX/exsXNIgPnghm0Yj/pl0HCWpCQQcJcSMggYS4kZGgK+0m/DBLWgoQMnAtm0EqPfgJkrEkJGSSsBwkZJMyFhAwS5kJCBo/23qpVKyxcuBDnzp3D0KFD8Ze//AXDhg3za2lFdI+DEmsCPH1HnQIosSZEdI9rFhlWbluL4+dOwmwxe7Sd2WLGsV9+Rt72xq8BEGoZOBfMoBX7Sb8MEtaChAwS5kJCBglzISFDU9hP+mWQsBYkZOBcMINWevQTIGNNSsggYT1IyCBhLiRkkDAXEjJ4fEqse/fuePfdd7Fjxw588803GDduHBQ/fJ27nWIyoOXtXYBIg/YFogCItG2nmLw7yyctQ3VdDe5641GU1VRoXiBmixllNRW4c84jqK6raRYZOBfM4An2kz4ZJKwFCRkkzIWEDBLmQkIGd9hP+mSQsBYkZOBcMIMnAt1PgIw1KSGDhPUgIYOEuZCQQcJcSMjg+0gGgDE+Eq3u7gallbbrsCutTGh1dzcY4yObVYafzh7BDbOG4WTJGQBw+VlP++0nS87ghlnDcKjwaLPKwLlgBkkkrEcJGSSsBQkZJMyFhAwS5kJChmCTsBYkZJCwFiRk4FwwgzQS1qSEDBLWg4QMEuZCQgYJcxHsDB5/+55ejPGRiB1xCeoOlKJmVzGsRc5n4AwJUYhKb2N7650fzlRKzHCo8Cj6Tb0VOZcPwuiBucjskuZ0n90n9mHexsXI274uIL9NkZCBc8EMkkhYjxIySFgLEjJImAsJGSTMhYQMwSZhLUjIIGEtSMjAuWAGaSSsSQkZJKwHCRkkzIWEDBLmIpgZxJ6UAmxvqYtMjUdkajwshdUwlQFjs0Zg7o4lMMfCp6vdh1KG6roaLNmajyVb85HeKRVpScmYOHAMZmx8E9+f/BG7TuwNiwycC2aQRMJ6lJBBwlqQkEHCXEjIIGEuJGQINglrQUIGCWtBQgbOBTNII2FNSsggYT1IyCBhLiRkkDAXwcog8uN7jTG2i0ZMShvk5OQgJqWNLgtDYoZdJ/bikx3rUVRUhE92rA/K/3lJyMC5YAZJJKxHCRkkrAUJGSTMhYQMEuZCQoZgk7AWJGSQsBYkZOBcMIM0EtakhAwS1oOEDBLmQkIGCXOhZ4aQOSlFRERERERERETNB09KERERERERERGR7nhSioiIiIiIiIiIdKeoqqrqsSOLxYKCggIMvG4gKlXvrtSuKAoSWrRBUWUxvImtVpoBFYACKC28u8Y7MzADM/g/QwslChu/3ojMzEwYjUavMvjK147ydQwA3+eCGZiBGQKTIdgdxX5iBmZgBldCvZ+A5nEsywzMwAzOtPaT/t++pwJqhdnbTXG2/CwzMAMzNLcMLaO839bfvBwHv80DMzADM8jLIKWjwn0emIEZmMFZiPfTr5uG/rEsMzADMzjT2E/6n5RSAKVl+J4tZAZmYIbGHsCr3QaGlx3VXH7jygzMwAyNPYh3m/kd+4kZmIEZnB7Eu838jq/xmIEZmMHpAbTdTfeTUkqMEXH3XubVti0iYrA6dz6GLB6Fyroqj7cvXXQQaoUZSgsT4h5kBmZgBikZLMtPerXfQPC2o3wdA8D3uWAGZmCGwGSQ0lHsJ2ZgBma4UKj3E9A8jmWZgRmYwZnWfuKFzomIiIiIiIiISHc8KUVERERERERERLrjSSkiIiIiIiIiItKd/hc695KlsBpVpVXIy8tD1b5zsMQpMLaLZgZmCFqG9E6p6JWUgoSEBNyZdTP2nNyPXSf2MkMQMgSbhPXIDMxQn4TnJTPIIGE9MgMz1CfheckMckhYk8zADNIySOgHPTOIPimlmq2oO1CKml3FsBbVAACmfT7N8XNDQhSi0tsgonscFFNg3vTFDMxQX3REFIb2GYzRA3OR0bmn4/a5D0wHAOw8/gPmbVyMldvWorquhhkCmCHYJKxHZmCG+iQ8L5lBBgnrkRmYoT4Jz0tmkEPCmmQGZpCWQUI/BCuD2JNSlpJaVHx6DGqZ2eV9rEU1qNpwGtXfFqHl7V1gjI9kBmYIWIZLE7th1eML0LltEqyqtdH79OqYgjkjX8Izgx7HnXMewaHCo8wQgAzBJmE9MgMz1CfheckMMkhYj8zADPVJeF4ygxwS1iQzMIO0DBL6IZgZRF5TylJSi/IVR6CWu14Y9anlZpSvOAJLSS0zMENAMlya2A1fPvURkuLbQ1EUGA3GRu9nNBihKAqS4tvjq6eX4ZJ2XZnBzxmCTcJ6ZAZmqE/C85IZZJCwHpmBGeqT8LxkBjkkrElmYAZpGST0Q7AzeHxSqra2Fi+88AKuuOIKXHXVVXj11VehqqpfwgC2t85VfHoMqLUCWh9WBVBr2041N35WjxmYwVvREVFY9fgCxEa1hMmo7c2FJqMJsVEtkT9uIaIjopjBTxncYT8xQ7hlkPC8ZAZt2E/MEG4ZJDwvmUGbQPcTIGNNMgMzSMsgoR8kZPD4pNTUqVPxn//8BwsXLsQrr7yC5cuXY9myZT4Hsas7UGp765ynPagCapkZdQdKmYEZ/JphaJ/B6Nw2SfOT1M5kNKHLRR2Rc/kgZvBTBnfYT8wQbhkkPC+ZQRv2EzOEWwYJz0tm0CbQ/QTIWJPMwAzSMkjoBwkZPDopVVJSgpUrV+LFF19Eeno6rrzySjz88MPYuXOnz0HsanYVB3V7ZmCGC40emOvyc7XuWKwWjB6Yywx+ytAU9hMzhGMGCc9LZnCP/cQM4ZhBwvOSGdzTo58AGWuSGZhBWgYJ/SAhg0cnpbZt24ZWrVqhX79+jttGjx6N6dOn+xwEsH39ov1q996yFtXAUljNDMzglwzpnVKR0bmny8/VumM0GJHZJQ3pnVKZwccM7rCfmCHcMkh4XjKDNuwnZgi3DBKel8ygTaD7CZCxJpmBGaRlkNAPEjIAHn773vHjx9GxY0fk5+fjrbfeQl1dHXJycjBmzBgYDNrObymKghYRMY3+rKq0ypM4LpnKgJgk532UKQpUZmAGDzL0SkrxS4a0pGQcPHOEGVxkKFcUnx/bH/0EuB6HQK9HwP1cMAMz1Bfo5yUz/MbXjmI/MUO4ZQiXbpCQQXo/ATKO6ZmBGaRl4Gu833h0UqqyshJHjx7FRx99hOnTp6OwsBBTpkxBTEwMHn74YU2P0TYmHitz5zf6s7y8PEz7fJonkRo1NmsEcnJynG4fvGQwzpafRUKLNljNDMygIUNCQoLP+weAiQPH4NG0e5jBRYahq4b6/Nj+6CfAdUcFej0C7ueCGZihvkA/L5nhN752FPuJGcItQ7h0g4QM0vsJkHFMzwzMIC0DX+P9xqOTUiaTCeXl5XjllVfQsWNHAMDJkyexdOlSzaV1rqoEQxaPavRnVfvOeRLHpbk7luDdynVOtxdVFjv+ZgZm0JLhzqybMfcB39++PGPjm/hkx3pmcJGhvKrE58f2Rz8Brjsq0OsRcD8XzMAM9QX6eckMv/G1o9hPzBBuGcKlGyRkkN5PgIxjemZgBmkZ+BrvNx6dlGrXrh2ioqIchQUAF198MU6dOqX5MVRVRWVd42+Xs8T5/hEeADDHotF92L/alBmYQWuGPSf3+yXDnp/3M4OGDL7wRz/ZszSWMdDr0b5vZmAGrRkC/bxkBucM3mI/MUO4ZQi3bpCQwVuB7idAxjE9MzCDtAx8jfcbjy50npGRgZqaGhw+fNhx26FDhxqUmC+M7aJhSIjy6TEMCVEwtotmBmbwS4ZdJ/Zi5/EfYLFavNreYrWg4Nj32P3zPmbwMYM77CdmCLcMEp6XzKAN+4kZwi2DhOclM2gT6H4CZKxJZmAGaRkk9IOEDICHJ6UuueQSXHfddXj22Wexb98+/Pvf/8a8efNw3333+RSivqj0NkHdnhmY4ULzNi6GQfHoqeJgNBgxb+NiZvBThqawn5ghHDNIeF4yg3vsJ2YIxwwSnpfM4J4e/QTIWJPMwAzSMkjoBwkZPN773//+d3Tp0gX33XcfnnnmGYwcORL333+/z0HsIrrHQYk1AZ6+o04BlFgTIrrHMQMz+DXDym1rcfzcSZgtZo+2M1vMOPbLz8jb3vj1GJjB/9hPzBBuGSQ8L5lBG/YTM4RbBgnPS2bQJtD9BMhYk8zADNIySOgHCRk8PikVGxuLmTNnYseOHfjPf/6DcePGQfHD17nbKSYDWt7eBYg0aF8gCoBI23aKybuzfMzADK5U19XgrjceRVlNheYnq9liRllNBe6c8wiq62qYwU8Z3GE/MUO4ZZDwvGQGbdhPzBBuGSQ8L5lBm0D3EyBjTTIDM0jLIKEfJGTwfSQDwBgfiVZ3d4PSStt12JVWJrS6uxuM8ZHMwAwByfDT2SO4YdYwnCw5AwAuP3drv/1kyRncMGsYDhUeZQY/Zwg2CeuRGZihPgnPS2aQQcJ6ZAZmqE/C85IZ5JCwJpmBGaRlkNAPwc7g0bfv6ckYH4nYEZeg7kApanYVw1rkfAbOkBCFqPQ2trfe+eFMJTMwQ1MOFR5Fv6m3IufyQRg9MBeZXdKc7rP7xD7M27gYedvXBeQ3W8wgg4T1yAzMUJ+E5yUzyCBhPTIDM9Qn4XnJDHJIWJPMwAzSMkjoh2BmEHtSCrC9pS4yNR6RqfGwFFbDVAaMzRqBuTuWwBwLn652zwzM4I3quhos2ZqPJVvzkd4pFWlJyZg4cAxmbHwT35/8EbtO7GUGnTIEm4T1yAzMUJ+E5yUzyCBhPTIDM9Qn4XnJDHJIWJPMwAzSMkjoh2BlEPnxvcYY20UjJqUNcnJyEJPSRpeFwQzM0JRdJ/bikx3rUVRUhE92rA/KgQQzyCBhPTIDM9Qn4XnJDDJIWI/MwAz1SXheMoMcEtYkMzCDtAwS+kHPDCFzUoqIiIiIiIiIiJoPnpQiIiIiIiIiIiLd8aQUERERERERERHpTlFVVdVjRxaLBQUFBRh43UBUqt5dqV1RFCS0aIOiymJ4E1utNAMqAAVQWnh3jXdmYAZm8H+GFkoUNn69EZmZmTAajV5l8JWvHeXrGAC+zwUzMAMzBCZDsDuK/cQMzMAMroR6PwHN41iWGZiBGZxp7Sf9v31PBdQKs7eb4mz5WWZgBmZobhlaRnm/rb95OQ5+mwdmYAZmkJdBSkeF+zwwAzMwg7MQ76dfNw39Y1lmYAZmcKaxn/Q/KaUASsvwPVvIDMzADI09gFe7DQwvO6q5/MaVGZiBGRp7EO828zv2EzMwAzM4PYh3m/kdX+MxAzMwg9MDaLub7iellBgj4u69zKttW0TEYHXufAxZPAqVdVUeb1+66CDUCjOUFibEPcgMzMAMUjJYlp/0ar+B4G1H+ToGgO9zwQzMwAyBySClo9hPzMAMzHChUO8noHkcyzIDMzCDM639xAudExERERERERGR7nhSioiIiIiIiIiIdMeTUkREREREREREpDuelPKApbAaVfvOIS8vD1X7zsFSWK17hvROqbgz62YkJCTgzqybkd4plRmYIewzEPuJGZhBagZiPzEDM0jNQDbsKGaoj+tB/wz6f/teiFHNVtQdKEXNrmJYi2oAANM+n+b4uSEhClHpbRDRPQ6KKTDn+KIjojC0z2CMHpiLjM49HbfPfWA6AGDn8R8wb+NirNy2FtV1NczADGGRgdhPzMAMUjMQ+4kZmEFqBrJhRzFDfVwPwc2gqF5//6hnLBYLCgoKcN2gbBjvTfLqMfx2BfqW2q5AbympRcWnx6CWmd3eV4k1oeXtXWCMj/RrhksTu2HV4wvQuW0SrKoVRoPROafVAoNiwPFzJ3HnnEdwqPAoMzBDSGWwLD+Jr9dtQGZmJoxG58fTg68d5ddv8dEwF4HoJ08zBGItMAMzSMwQ7I5iP3meoTmvR2ZghgbbhHg/AXyN15yO6UMxA9dD4DJo7Sd+fM8FS0ktylccgVrufnECgFpuRvmKI7CU1Potw6WJ3fDlUx8hKb49FEVpdGEAgNFghKIoSIpvj6+eXoZL2nVlBmZothmI/cQMzCA1A7GfmIEZpGYgG3YUM9TH9SAjg0cnpfLy8pCSkuL0p0ePHn4JI4VqtqLi02NArRXQ+j4yFUCtbTvVbPU5Q3REFFY9vgCxUS1hMmr7lKXJaEJsVEvkj1uI6IgoZmCGZpehKeynpjYC+4kZmCHAGZrCfmpqI7CfmIEZApzBHXZUUxuBHdVMM3A9yMng0UmpwYMH45tvvnH8+frrr9G1a1c88MADPgeRpO5Aqe3te55+sFEF1DIz6g6U+pxhaJ/B6Nw2SfPCsDMZTehyUUfkXD6IGZih2WVoCvvJDfYTMzBDQDM0hf3kBvuJGZghoBncYUe5wY5qlhm4HuRk8OikVHR0NNq1a+f48+mnn0JVVTz11FM+B5GkZldxULcHgNEDc2FVvTv7arFaMHpgLjMwQ7PL0BT2kz7bAzLWAjMwg7QMTWE/6bM9IGMtMAMzSMvgDjtKn+0BGeuBGWy4HuRk8PqaUiUlJZg/fz7+3//7f4iMdH9xylBhKax2XHHfW9aiGp++OjK9UyoyOvd0+VlOd4wGIzK7pPn0tY3MwAzSMniC/eQa+4kZmMH/GTzBfnKN/cQMzOD/DJ5iR7nGjmo+Gbge5GQAAM/eo1XP0qVLkZiYiFtuucWj7RRFQYuIGK/2GRMR3eBvT5UpClQ3GapKvftWmguZyoCYJOd9aMnQKynFLxnSkpJx8MwRZmAG8RnKFcUvj2/nbT8B3neUr/0EuJ+LQPeTlgyBXgvMwAwSM/izo9hPTWM/MQMzeJZByjEUX+MF/3iaGbRn4HrQJ4PWflJUVfX0U5RQVRU33HADHn30UYwYMULTNvavCx06dChWrlzp6S79YvDgwTh79iwSExOxdu3aRu+Tl5eHadOm+byvSZMmIScnx6sMCQkJ6NrV9yvZHz16FEVFRczADOIz2HvBH19n7E0/AaHRUYHuJy0ZAr0WmIEZJGbwV0exn9xjPzEDM3iWIdjHUKHQTwBf4zFDQ1wP+mTQ2k9evVNq9+7dOHPmDG699VaPtz1XVYIhi0d5s1vERERj+bDZuHfZeFTVef5WuaLKYsffrjJU7TvnVbYLzd2xBO9WrvMqw51ZN2PuA9N9zjBj45v4ZMd6ZmAG8RnKq0p8fmw7X/oJ8L6jfO0nwP1cBLqftGQI9FpgBmaQmMFfHcV+co/9xAzM4FkGKcdQfI0X/ONpZtCegetBnwxa+8mrk1L//ve/0bdvX7Ru3drjbVVVRWWdb2+Xq6qr9uox7G8KayqDJc4/b4E1x6LRfWjJsOfkfr9k2PPzfmZghpDK4A++9JM9iy8d5W0/2ffdVIZA95OWDIFeC8zADJIz+Ir95B77iRmYwbsM/sDXeO7xNV7zyMD1oG8Gd7y60PmuXbtw+eWXe7OpeMZ20TAkRPn0GIaEKBjbeX/dhl0n9mLn8R9gsVq82t5itaDg2PfY/fM+ZmCGZpNBK/ZT09hPzMAM/s+gFfupaewnZmAG/2fwBDuqaeyo5pOB60FOBsDLk1IHDhzAZZdd5tOOJYtKbxPU7QFg3sbFMCjefTmi0WDEvI2LmYEZml0GLdhPgd0ekLEWmIEZpGXQgv0U2O0BGWuBGZhBWgat2FGB3R6QsR6YwYbrQU4Gr/ZeVFSEuLg4n3cuVUT3OCixJsDTd/UpgBJrQkR338dm5ba1OH7uJMwWs0fbmS1mHPvlZ+Rtb/x6DMzADKGcQQv2kwvsJ2ZghoBm0IL95AL7iRmYIaAZtGJHucCOapYZuB7kZPD643vXXnutzzuXSjEZ0PL2LkCkQfsiVQBE2rZTTN6daayvuq4Gd73xKMpqKjQvELPFjLKaCtw55xFU19UwAzM0uwxasJ8a2wjsJ2ZghgBn0IL91NhGYD8xAzMEOINW7KjGNgI7qplm4HqQk8H3kWymjPGRaHV3NyittF0LXmllQqu7u8EYH+m3DD+dPYIbZg3DyZIzAODys57220+WnMENs4bhUOFRZmCGZpuB2E/MwAxSMxD7iRmYQWoGsmFHMUN9XA8yMnj17XvhwhgfidgRl6DuQClqdhXDWuR8FtCQEIWo9Da2t//54WzphQ4VHkW/qbci5/JBGD0wF5ld0pzus/vEPszbuBh529cF5LcpzMAM0jIQ+4kZmEFqBmI/MQMzSM1ANuwoZqiP6yH4GXhSyg3FZEBkajwiU+NhKayGqQwYmzUCc3csgTkWPl1xX6vquhos2ZqPJVvzkd4pFWlJyZg4cAxmbHwT35/8EbtO7GUGZgi7DMR+YgZmkJqB2E/MwAxSM5ANO4oZ6uN6CG4GnpTygLFdNGKSYpCTk4N3K9ehsq5K9wy7TuzFwTNH8GjaPfhkx3pmYAZmIADsJ2ZgBqkZiP3EDMwgNQPZsKOYoT6uB/0z8JpSRERERERERESkO56UIiIiIiIiIiIi3fGkFBERERERERER6U5RVVXVY0cWiwUFBQUYeN1AVKreXaldURQktGiDospieBNbrTQDKgAFUFp4dzktZmAGZvB/hhZKFDZ+vRGZmZkwGo1eZfCVrx3l6xgAvs8FMzADMwQmQ7A7iv3EDMzADK6Eej8BzeNYlhmYgRmcae0n/S90rgJqhdnbTXG2/CwzMAMzNLcMLaO839bfvBwHv80DMzADM8jLIKWjwn0emIEZmMFZiPfTr5uG/rEsMzADMzjT2E/6n5RSAKVl+J4tZAZmYIbGHsCr3QaGlx3VXH7jygzMwAyNPYh3m/kd+4kZmIEZnB7Eu838jq/xmIEZmMHpAbTdTfeTUkqMEXH3XubVti0iYrA6dz6GLB7l1VcSli46CLXCDKWFCXEPMgMzMIOUDJblJ73abyB421G+jgHg+1wwAzMwQ2AySOko9hMzMAMzXCjU+wloHseyzMAMzOBMaz/xQudERERERERERKQ7npQiIiIiIiIiIiLd8aQUERERERERERHpTv8LnYcwS2E1qkqrkJeXh6p952CJU2BsFx12GSSQMA4SMhDZSViPEjJIIGEcJGQgspOwHiVkkEDCOEjIQFSfhDUpIYMEEsZBQoZww5NSbqhmK+oOlKJmVzGsRTUAgGmfT3P83JAQhaj0NojoHgfFFJg3nknIIIGEcZCQgchOwnqUkEECCeMgIQORnYT1KCGDBBLGQUIGovokrEkJGSSQMA4SMoQznpRqgqWkFhWfHoNaZnZ5H2tRDao2nEb1t0VoeXsXGOMjm10GCSSMg4QMRHYS1qOEDBJIGAcJGYjsJKxHCRkkkDAOEjIQ1SdhTUrIIIGEcZCQIdzxNJ8LlpJalK84ArXc9eKsTy03o3zFEVhKaptVBgkkjIOEDER2EtajhAwSSBgHCRmI7CSsRwkZJJAwDhIyENUnYU1KyCCBhHGQkIG8OCl16tQpPPbYY7j88suRnZ2NRYsWBSBWcKlmKyo+PQbUWgFV60YAam3bqWZrs8gggYRxkJCBtGE/udoIfE4EgIRxkJCBtGE/udoIfE4EgIRxkJCBtAmHfgJkrEkJGSSQMA4SMpCNxyelnnjiCbRo0QJ5eXmYNGkSXnvtNXzxxReByBY0dQdKbW/f07o47VRALTOj7kBps8gggYRxkJCBtGE/NYHPCb+TMA4SMpA27Kcm8DnhdxLGQUIG0iYc+gmQsSYlZJBAwjhIyEA2Hp2UOn/+PAoKCjBmzBh069YNf/jDH3Dttddi8+bNgcoXFDW7ioO6vZQMEkgYBwkZyD32kz7bS8kggYRxkJCB3GM/6bO9lAwSSBgHCRnIvXDpJ0DGmpSQQQIJ4yAhA9l4dFIqOjoaMTExyMvLQ11dHQ4dOoTt27cjNTU1UPl0Zymsdlxx31vWohpYCqtDOoMEEsZBQgbShv2kDZ8T/iFhHCRkIG3YT9rwOeEfEsZBQgbSJhz6CZCxJiVkkEDCOEjIQL/x6Nv3oqKiMGXKFLz44ot4//33YbFYkJOTg3vuuUfzYyiKghYRMR4HBYCYiOgGf3uqTFGguslQVVrl1WNfyFQGxCQ57yNUMrjDudAvgzt6zEWgM5Qrilfb1eePfgK8HwdfxwBwPxeBXo+hksEdzoV+GdzRYy70yOBrR7GftONzwr1QGAcJGdxhP9kEu58Avq7QM4M7nAv9MrgTTq/xPDopBQA//fQTrr/+ejz00EM4cOAAXnzxRVx55ZW4/fbbNW3fNiYeK3Pne7rbBpYPm+3VdoOXDMbZ8rNIaNEGq11kyMvLw7TPp/kSDwAwNmsEcnJyQjaDVpyLwGfQKpBzEegMQ1cN9Wm/dr72E+B7R3k7BoD7uQj0egyVDFpxLgKfQatAzoUeGfzRUewnbficcC8UxkFCBq3YTzL6CeDrCj0yaMW5CHwGrcLhNZ5HJ6U2b96MFStWYOPGjYiOjkbv3r1x5swZvPnmm5pL61xVCYYsHuXJbh1iIqKxfNhs3LtsPKrqPH+rXFFlseNvVxmq9p3zKtuF5u5Ygncr14VsBnc4F/plcEePuQh0hvKqEq/2W58/+gnwvqN8HQPA/VwEej2GSgZ3OBf6ZXBHj7nQI4OvHcV+0o7PCfdCYRwkZHCH/WQT7H4C+LpCzwzucC70y+BOOL3G8+ik1J49e9C1a1dER//29q2ePXvirbfe0vwYqqqiss63t8tV1VV79RiqqrrNYInz/WNEAGCORaP7CJUMWnEuAp9Bq0DOhV4ZfOGPfrJn8WUcvB0D+76byhDo9RgqGbTiXAQ+g1aBnAs9M3iL/aQdnxPuhcI4SMigFftJRj8BfF2hRwatOBeBz6BVOLzG8+hC54mJiTh69Chqa2sdtx06dAidOnXyLJ1gxnbRMCRE+fQYhoQoGNt5/9lwCRkkkDAOEjKQNuwnbfic8A8J4yAhA2nDftKGzwn/kDAOEjKQNuHQT4CMNSkhgwQSxkFCBvqNRyelsrOzERERgcmTJ+Pw4cPYsGED3nrrLdx///2ByhcUUeltgrq9lAwSSBgHCRnIPfaTPttLySCBhHGQkIHcYz/ps72UDBJIGAcJGci9cOknQMaalJBBAgnjICED2Xh0Uio2NhaLFi1CYWEh7r77bkyfPh1jxozBsGHDApUvKCK6x0GJNQGevqtPAZRYEyK6xzWLDBJIGAcJGcg99pMbfE74nYRxkJCB3GM/ucHnhN9JGAcJGci9cOknQMaalJBBAgnjICED2Xj87XuXXXYZ3n333UBkEUMxGdDy9i4oX3EEqLUCWj4KqQCItG2nmDw61yc2gwQSxkFCBtKG/eRqI/A5EQASxkFCBtKG/eRqI/A5EQASxkFCBtImHPoJkLEmJWSQQMI4SMhANhxJF4zxkWh1dzcorbSdt1NamdDq7m4wxkc2qwwSSBgHCRmI7CSsRwkZJJAwDhIyENlJWI8SMkggYRwkZCCqT8KalJBBAgnjICEDefFOqXBijI9E7IhLUHegFDW7imEtqnG6jyEhClHpbWxv/wvA2VIJGSSQMA4SMhDZSViPEjJIIGEcJGQgspOwHiVkkEDCOEjIQFSfhDUpIYMEEsZBQoZwx5NSbigmAyJT4xGZGg9LYTVMZcDYrBGYu2MJzLHQ5Yr7EjJIIGEcJGQgspOwHiVkkEDCOEjIQGQnYT1KyCCBhHGQkIGoPglrUkIGCSSMg4QM4Yyn+TxgbBeNmJQ2yMnJQUxKm6AsTgkZJJAwDhIyENlJWI8SMkggYRwkZCCyk7AeJWSQQMI4SMhAVJ+ENSkhgwQSxkFChnDDk1JERERERERERKQ7npQiIiIiIiIiIiLd8aQUERERERERERHpTlFVVdVjR2azGTt37sSgwYNQpTpf0V4LRVHQNiYe56pK4E1stcoCqAAUQIkxMgMzMIOQDDFKFNatXYeMjAyYTMH5/gVfO8rXMQB8nwtmYAZmCEyGYHcU+4kZmIEZXAn1fgKax7EsMzADMzjT2k+6NZfVagUArFu7Tq9dElGIsfdEMPfNjiIiV4LVUewnInKH/UREUrnrJ93eKWW1WmE2m2EwGKAoih67JKIQoaoqrFYrTCYTDIbgfKqYHUVErgS7o9hPROQK+4mIpNLaT7qdlCIiIiIiIiIiIrLjhc6JiIiIiIiIiEh3PClFRERERERERES640kpIiIiIiIiIiLSHU9KERERERERERGR7nhSioiIiIiIiIiIdMeTUkREREREREREpDuelCIiIiIiIiIiIt2F1EmpvLw8pKSk4OOPP9Z1vykpKQ3+DBgwAJMnT0ZFRYWuOQDg/PnzmDFjBrKzs5GRkYFBgwZh0aJFsFqtAd93dna2Ywx69OiBrKwsDB8+HP/+978Dvu/GMlz4Z+vWrUHPcd999+mWobKyEq+99hpuueUWpKeno3///pgwYQIOHDigy/6zs7ORl5fndHteXh6ys7N1ySBNuHdUuPfThTmC1VHsJ/ZTY9hP7Cf202+C2VHsJ2fsp+D1EyCjoyT0U1M5eAwV2I4yBeRRA2TNmjXo0qULPvnkE9xzzz267nv27NnIysqC1WrFqVOnMGXKFMycORMvvPCCbhmKi4sxbNgwJCYm4qWXXkKnTp2we/duvPjiizh+/Diee+65gGeYNGkSBg8eDKvVivPnzyM/Px+PPfYYFixYgKuuuirg+6+f4UKtW7fWZf9N5YiIiNBl3xUVFRgxYgQqKysxceJE9OjRA8XFxfjwww8xfPhw5Ofno3Pnzrpkod+Ec0exn5xzXEjPjmI/0YXYT+yn+jkuFC79BLCjJGI/BbefABkdJaGfXOXgMVRghcxJqV9++QWbN2/GtGnTMHHiRBw/flzXCWndujXatWsHAGjfvj0ee+wxvPDCC7qelHrllVcQGRmJhQsXIioqCgDQuXNnREdHY+zYscjNzcXFF18c0AyxsbENxuHPf/4zCgsLMX36dKxevTqg+24sQzAFM8cbb7yBX375BWvXrkVcXBwAoGPHjpg+fTpOnTqFRYsW6fZ/YmQT7h3Ffmo8R7Cwn6g+9hP7qbEcwRLsDOwoWdhPwe8nQEZHBbsbJOQI134KmY/vff7554iNjcXtt9+OxMREfPLJJ0HNExMTo+v+amtrsWbNGowcOdJRWHbXX389Fi1ahI4dO+qayW7YsGH48ccfcfTo0aDsP9xYrVasWrUKDz30kKOs6ps5cyaefvrpICQLb+HcUewnsmM/ycR+Yj+RDTtKHvaTzH4C2FF6C+d+CpmTUmvWrMF1110Hg8GA7Oxs5OfnQ1XVoGQ5d+4cPvjgA9x+++267fPYsWOorKxE7969nX6mKAoGDBiAyMhI3fLUd+mllwIADh48GJT9h5tjx47h3Llz6Nu3b6M/T0xMRHR0tM6pKJw7iv1EduwnmdhP7CeyYUfJw36S2U8AO0pv4dxPIfHxvVOnTmH79u146KGHAAA33XQTli5dim3btrmcNH8bNWoUjEYjVFVFVVUV4uPj8de//lWXfQNAaWkpANvbCaWxZ9LrooDPP/88XnzxxQa3JSUlYc2aNbrsv6kcmzZtQosWLQK63+LiYgANP1/9n//8B48//rjjv/Uaj8bGwGw2i3jrrZ7CvaPYTw1J6Cj2E/vJjv3EfqovnPsJkNNR7Ccb9pPcfgL4Gq8+HkMFtqNC4qTUmjVrEBUVhWuuuQYA0K9fP7Ru3RqrVq3SrbCmTp2KjIwMqKqK4uJiLF68GPfddx9Wr16Niy66KOD7j4+PB2D7dgZpysvLAQCtWrXSZX8TJkzATTfd1OA2k0n/pdxYDj3e8mt/O6f9/8gAICsrC/n5+QCA9evXY+nSpQHPATQ+BnruX4pw7yj2U0MSOor9xH6yYz/FA2A/2YVzPwFyOor9ZMN+igcgs58Avsarj8dQgd1/yJyUqq6uRp8+fRy3WSwWfP7553juued0eRtb+/bt0bVrVwBAt27dkJaWhv79+2PdunXIzc0N+P67dOmC2NhYfP/990hPT3f6+ZgxY3D//ffr+g0udvv37wcAdO/eXZf9XXTRRY65CKZg5ejatSvi4+OxY8cOx1qIiYlxZNHjJKldY2Og5/6lCPeOYj81JKGj2E/sJzv2E/upvnDuJ0BOR7GfbNhPcvsJ4Gs8vUnpJ/u+9Owo8deUOnz4MH744QdMnjwZ+fn5jj//+Mc/UF5eji+++CIouQwGA1RVhcVi0WV/JpMJgwcPxocffoja2toGP9uwYQM2bNiAxMREXbJcaOXKlUhLS2uWX08pkclkwtChQ/Hee+85foNR35kzZ4KQKnyxo9hP9Bv2kyzsJ/YTNcSOkoP9JLufAHaU3sK5n8S/U2rNmjWIj4/HsGHDGlzoLTk5GW+88Qby8/MxZMiQgOc4f/48CgsLAdg+V/vOO+/AYrEgOzs74Pu2Gz9+PO655x488sgjGD9+PH73u99h69atmDVrFh544AFcdtllAc9QVlaGwsJCx1tcV6xYgbVr1+Kdd94J+L4vzHChli1b6nI9AgnGjx+Pbdu2Yfjw4Rg3bhzS0tJQXFyMjz/+GCtWrMBtt90W7Ihhgx1lw35yznGhcOko9pMc7Ccb9pNzjguFSz8B7Cgp2E82EvoJkNFR7Kfw7aeQOCk1ZMiQRr954L777sNLL72EM2fOoH379gHNMX78eMf/jomJQa9evTB//nxdzxy3a9cOS5cuxezZs/HUU0+hpKQEXbp0wYQJE3DffffpkmHatGmYNm0aFEVB27Zt0bNnTyxatEi3z33Xz3ChP/3pTxg7dqxuOYIpJiYGH3zwAd577z3MnTsXR48eRWRkJNLT0zF79mz84Q9/CHbEsMGOsmE/Oee4ULh0FPtJDvaTDfvJOceFwqWfAHaUFOwnGwn9BMjoKPZT+PaTogbrOzeJiIiIiIiIiChsib+mFBERERERERERNT88KUVERERERERERLrjSSkiIiIiIiIiItIdT0oREREREREREZHueFKKiIiIiIiIiIh0x5NSRERERERERESkO56UIiIiIiIiIiIi3fGkFBERERERERER6Y4npZqB0aNH49lnn21w22effYaUlBTMnj27we1z587FHXfcAQAoLS3FX/7yF1x11VUYMGAAJk6ciNLSUsd9Fy1ahJSUlAZ/Xn755SazXH/99Thz5ozT7e72VVxcjPHjxyMrKwvZ2dn45JNP3P67c3NzsX37dqfb77///gaZs7Ky8Mgjj+Do0aONPs6nn36K+++/v8FtdXV1mDVrFq655hoMGDAAL7/8Msxms9tMROQsUB3lz96ob/LkyU65fvnlF0yYMAF9+/bFjTfeiLy8PLf7euaZZ7B69Wqn2ydOnNigozIyMjB8+HDs2rWrwf2+/vpr3HHHHcjKysKQIUPw1VdfNfh53759nTq6oqLCbS4i+k0g+mn27NlOz82UlBTccMMNTWZxdQxlp6oqHn74Yaf++fHHH5Gbm4usrCzcfPPN+Oyzz9z+u13tKzs7u0Hmvn37YsKECfjll18afZw333wTEydObHBbRUUFJk+ejAEDBuD3v/895s2b5zYPETkL9eOnvLy8RruwR48eXu1L62u8lStX4pZbbkFWVhbuuecebNu2DQBw4sSJRvOkpKTg22+/dTsGFDg8KdUM9O3bF7t3725w29atW5GYmIitW7c2uL2goAD9+vUDADz//PPYt28f5s2bh4ULF+Knn37C5MmTHfc9ePAgRowYgW+++cbx5/HHH3eZ4+jRo4iOjkb79u2dfuZuX88++yzKysqwbNkyjBkzBpMnT3Z6gVZfVVUVDhw4gPT09EZ//vDDD+Obb77Bv//9byxfvhzx8fEYO3YsVFVtcL8tW7ZgypQpTtu//vrryM/Px0svvYSFCxdi8+bNmDFjhss8RORaoDrK370BAPPnz8fHH3/c4DZVVfH444/j9OnTeP/99zFp0iTMmDED69evb/LfvWXLFgwYMKDRnw0aNMjRq6tWrUJGRgYee+wxx0mlffv2Ydy4cRg6dCjy8/MxfPhw/OlPf8K+ffsAAGfOnEFZWRm+/PLLBh3dokWLJjMRUUOB6Cf7MYj9z9q1axEfH48HHnjAZY6mjqEAwGq1YurUqdi0aVOD22tra/HHP/4RPXv2xCeffIJRo0Zh4sSJTv8mT/Y1adIkfPPNN/jXv/6FDz74AOfPn8czzzzjdL/PPvvM6YUxADz33HP49ttv8cYbb+DVV1/FRx99hHfffddlHiJqXKgfPw0ePLhBF3799dfo2rVrk13o62u8f/3rX/jb3/6GsWPHIj8/H1dffTVGjx6NM2fOoEOHDg3yfPPNN7jtttvQu3dvZGZmusxEOlAp5H333Xdqjx491PLycsdtN954o/ruu++qaWlpalVVleP2fv36qevXr1crKirU1NRUtaCgwPGz7du3q6mpqWp1dbWqqqo6fPhw9aOPPtKcY+nSpeoLL7zgdLu7fR09elRNTk5Wjx8/7vj5pEmT1Geeecblvv71r3+po0ePbvRnubm56uuvv97gtrNnz6rJycnq3r17HbfNnj1b7dWrl3rbbbepubm5jtutVqualZWlrlixwnFbQUGBmpaW1mCMiUibQHSUv3ujrKxMHT9+vHrFFVeoAwcObNAhu3btUpOTk9Vjx445bnv77bfVe++91+W+fvrpJ/XWW29t9GfPPPOMU866ujo1MzNT/fLLL1VVVdVZs2apjzzySIP7PPzww+qrr76qqqqqbtq0Sb366qtd7p+ItAnUMVR9zz33nDpixAjVarW6zOHqGEpVVfX06dNqbm6uet1116l9+/ZVV65c6fjZ999/ryYnJzfIf9ddd6kLFizwal/XX399g8dXVVXdsWOHmpycrJaWlqqqauurKVOmqL1791ZvuummBn32yy+/qMnJyermzZsdt61Zs4Z9ReSFUD9+utBbb72l/uEPf1Bramq82peW13hPPPGEOmXKlAb3uemmm9Rly5Y5Pd62bdvUtLQ09eDBgy7zkD74TqlmoHfv3oiIiMD3338PADh9+jROnjyJe+65B7GxsY63Px4+fBjnz59H3759YTAY8NZbbyE1NbXBY1ksFsdv6g8dOoRu3bppzrF582ZceeWVTre729fOnTvRoUMHdOrUyfGzPn36YMeOHR7vy5WYmBin2zZt2oSFCxfipptuanD7uXPnUFFRgYyMDMdtKSkpqKurw549ezTvk4hsAtFR/u6NEydOoKamBnl5eejcuXODnx0/fhxt27ZtcHtKSgr27NmDuro6l/ty9S6pxphMJkRGRjr++6677sJTTz3ldL+ysjIAtneyXnzxxZofn4gaF6hjKLvDhw8jLy8PzzzzDBRFcZmjqX76/vvv0aFDB6xcuRKxsbENfta6dWsAwMcffwyr1YodO3bg0KFD6Nmzp1f7akxMTEyD7JWVldi/fz+WL1+OrKysBvc9ceIEADgdQxUWFjp+RkTahPrxU30lJSWYP38+/t//+38Njnc82VdjLnyN9+ijj+Khhx5yup/9+Km+V155Bffeey8uvfRSzfujwOBJqWYgMjISGRkZjrddbtmyBb169ULLli1xxRVXON7eWVBQgO7du6NNmzaIjo7G73//+wal8P777yMlJQVt27ZFUVERSkpKsGrVKmRnZ2PQoEFYuHCh08ff7FRVxbfffut422h97vZVWFiIxMTEBttcdNFFTV5XoamPxVyotrYWb731luMzw3ZLly5tNG/r1q0RERHRYP+nTp0CYPsMNhF5JhAd5e/e6NGjB95+++0GB2l2CQkJKCsrQ1VVleO206dPw2w2N3qQY9+X1oMqs9mMDz/8EBEREY58l156aYNrLhw4cKDBgdpPP/2Eqqoq3H///bjmmmswatQoHD58WNP+iOg3gein+hYuXIgBAwY0+bGXpo6hANt1nmbOnOn02ADQsWNHPPnkk/j73/+OXr16Yfjw4Xj00Udd9o+7fV2ooqICCxYswHXXXec4IRYXF4ePPvqo0evCXHTRRQDAYygiPwj146f6li5disTERNxyyy1N3s/X13hpaWkN3lTxr3/9C0eOHHF6zG3btqGgoACPPfaYpn1RYJmCHYD8o2/fvo7C2rp1K/r37w8A6Nevn+OCl/U/a3yhxYsXY926dViwYAEA27ukAFtJvfnmm9i7dy+mTp0Ko9GIBx980Gn7ffv2oUOHDo7f2DXlwn1VVVU5nTGPjIxEbW1to9uXlJTgzJkzDU4wXejtt9/GO++8AwCorq6Gqqp4/fXXm/wtpZ3JZMKNN96IV199FZdeeilatmyJl19+GSaTyeW7Ioioaf7uqED0hisZGRlITEzEiy++iMmTJ6OwsNBxfZTGOsFqteK7777DtGnTXD7m6tWr8c9//hMAUFNTA4vFgmeffRYtW7Z0uu+5c+cwfvx4XH755Y4LJR86dAjnz5/Hk08+iVatWmH+/Pl48MEHsWbNGrRq1crjfyNROPN3P9mVl5djzZo1eO2115rcvyfHUBeqq6vDoUOHMGzYMOTk5ODbb7/FP/7xD1xxxRWOf4en+3r++efx4osvQlVVVFdXIyIiAu+//76mPB07dkRmZiZeeuklzJo1C3V1dZgzZ44jKxF5JpSPn+xUVcXHH3+MRx99tMn7+fs13rFjx/Dss89iyJAhSEtLa/Cz5cuX48Ybb3R5bT3SF98p1UzUvxDe1q1bHcXUr18/7NmzB7W1tSgoKMAVV1zhtO2HH36IqVOn4tlnn8U111zj2G7Lli14+umnkZKSgjvvvBNjx47F0qVLG92/1rdaNravqKgopyKsra1FdHR0o49h//c1dYJp+PDhyM/PR35+PvLy8vDEE0/gySefxObNm91mBGzfHtGyZUsMHDgQv//973H55ZejdevWfLFH5CV/d1QgesOVqKgovPbaa9iyZQv69OmD/8/evYdHUZ79A//O7iabAIkBEpBwFIEQgZCIxVMtiloEi8WgoIDWiqAi8uvbalVqPVQFC1Z9BbEFUWsRRSGgFPBQafOqRWqREFCCHMMhCIkkJCGbZA/z+2PMStgkOzu7O3vv7vdzXVy2yc7ON89z753ZJ7MzkydPxk033QQALfaEr7/+Gj179vT5mM3pRo4c6e1Ra9aswWOPPYZnn33W565aFRUV+MUvfuE96LJYtF/bS5cuxZo1a3DJJZcgJycHzzzzDBoaGvDPf/4z4J+PKN6Fuj81+eSTT5CUlITLLruszf0H+nGV061ZswY7duzAww8/jEGDBuG2227D2LFjsWTJEsP7mjVrFtasWYN3330X77zzDm6++Wbcfvvt2L17t65M8+bNw/Hjx3HRRRdhzJgx3juC8RiKKHDRfPzUZPv27Th27BiuvfbaNh8Xyvd4+/fvx6233oqePXviySefbPY9l8uFjz/+GNddd53hn4lCi2dKxYi8vDwcP34c27dvx/Hjx3H++ecDAPr374+UlBR88cUX2LNnj88q+tKlSzFv3jz89re/xS9+8Ytm3+vYsWOz/3/uuee2emrnpk2bWjyDSs++unbtioqKimaPraioQEZGRqv78ndAddZZZ6F3797e/5+dnY0vvvgCb775pq4Dv86dO+P1119HVVUV7HY7VFXFn/70J3Tv3t3vtkTkK9Q9Khx9oy05OTnYuHEjysvL0bFjR3z22Wfo2LFji2c26dlX+/btm/WoAQMGYOfOnVi2bBny8/MBaB9/abpDzeuvv97sozuJiYnN/tJpt9vRo0ePNk+/J6KWheMYCtAWpa644grvYnJr9BxDtearr77CgAEDmr2Jy87ObvXW7Xr21blz52b9aciQISgsLPReG8uf3r17491338V3332HlJQUHDx4EBaLBZmZmfp+KCLyivbjJ0DrhRdccIHfs0FD9R5v9+7duO2229CzZ0+8/PLLPgtuRUVFcLlcuPTSSw3+RBRqPFMqRrRr1w7Z2dlYsWIFhgwZ4r3om6Io+NGPfoSCggL06dOn2Zua1atXY968eXjooYcwderUZs/3zjvvYNSoUc2uIbVz50707dvXZ99OpxPFxcUYNmxYq/na2ldubi6OHDmCb7/91vu1LVu2tHprTqPNUVVVuN1uXY+9//778emnnyItLQ3JyckoLCxE586d0a9fv4D3S0Sh71Fm9Q1AO5385ptvRmVlJTIyMmCz2fCvf/2r1VPlA7kewulUVYXH4wGgXUj4jjvugMViwbJly5qdXq6qKq666qpmZ1XV1dWhtLS0xR5NRG0LdX9qUlxc7H0D2Ro9x1Bt6dKlC/bs2dPsa/v372/x+i7B7kvPMZTH48Htt9+OXbt2oXPnzkhMTMS//vUvnHfeeTxTisiAaD5+aqKnFwazr9Pf4x0/fhy33347evfujaVLl7bYd7Zt24ZBgwbBbrcHvC8KDy5KxZAf/ehHWLdunc8bpeHDh+Pjjz9udlpnVVUV/vCHP+D666/Htddei/Lycu8/t9uNSy65BOXl5fjjH/+I0tJSrFu3DkuWLGnxs8Dbtm3DgAEDWj3t09++evbsiR//+Me4//77UVJSgnfeeQd///vfMXnyZJ/n+vbbb+F0Otu8uwOgvUFr2sfRo0fxxhtvYNOmTRg9erSeoURaWhqee+45fPPNN9i8eTOeeOIJTJ8+3e9fO4modaHsUeHoG61JS0tDXV0d5s+fj0OHDuGdd97BqlWrWuyHjY2N2LFjh9+Dr/r6eu/Pc+zYMaxfvx5r16719qi//OUvOHjwIP74xz8CgPexNTU1UBQFl19+ORYsWIDNmzdj9+7d+O1vf4uzzz4bI0aMMPQzEsW7UPYnQPt4yP79+/3+McvfMZQ/Y8eOxaFDhzB//nwcPHgQa9aswdtvv41bbrnF8L5qamq8P8/hw4exYMEClJaW+r1AMaDdcTkpKQl/+tOfcODAAfzjH//Aiy++iLvuusvQz0dE0Xv81GT37t1+e2Go3uP98Y9/hMfjwVNPPdXssaffGXX37t28454w/PheDBk2bBheeeUVnwtbDh8+HA6Ho1kj++yzz1BXV4fVq1dj9erVzR7/8ccfo0ePHli8eDHmz5+PN998E507d8Z9992HMWPG+OzX31kBevY1b948/O53v8OECROQkZGBOXPmtHinGr23WX/llVe8F8FLSEhA79698cgjj+BnP/uZ320B4Fe/+hUef/xxTJo0Ce3atcNtt91m+NR6ItKEukeFum+05bnnnsOjjz6KsWPHokePHvjf//3fFvdVVFSEgQMH+v3r24YNG7BhwwYA2s0Vzj77bNx5553eha4PPvgA9fX1uPHGG5ttd/311+Ppp5/G/fffD5vNht/85jeora3FRRddhMWLF8NqtQb1cxLFq1D3p6qqKrhcLqSmpra5X6NnVjbp2bMnXnnlFcybNw/Lly9HZmYmnnrqqRavY6V3X3PmzPHeqMFut6Nfv354/vnndZ3pAACPP/44fv/73+P6669H586d8fDDD+Pqq68O7AcjIq9oPn4CtI8H+uuFoXiPp6oq/vGPf6C+vt5nEX3mzJm49957vXmys7MN/jQUDop6+ueziIiIiIiIiIiITMDPIhERERERERERkem4KEVERERERERERKbjohQREREREREREZmOi1JERERERERERGQ6LkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZjotSRERERERERERkOi5KERERERERERGR6bgoRUREREREREREpuOiFBERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjohQREREREREREZmOi1JERERERERERGQ6m1k78ng8cLlcsFgsUBTFrN0SURRQVRUejwc2mw0WS2TWytmjiKg1ke5R7E9E1Br2JyKSSm9/Mm1RyuVyYfv27Wbtjoii0JAhQ5CYmBiRfbNHEZE/kepR7E9E5A/7ExFJ5a8/mbYo1bQyNnrMaDjUBkPPoSgKOiWn4YSjCqqqBry96nADKgAFUJKtzMAMzCAkQ7Jix4b1GyJ2lhQQfI8KdgyA4OeCGZiBGcKTIdI9iv2JGZiBGVoT7f0JiI1jWWZgBmbwpbc/mbYo1XQ6p0NtgHVCpqHnaJeQjFVTlmDssmmoczoC3r76tT1QT7mgtLchdUI/ZmAGZhCSwfF2GYAf+kQkBNujgh0DIPi5YAZmYIbwZIh0j2J/YgZmYIbWRHt/AmLjWJYZmIEZfOntT7zQORERERERERERmY6LUmScxxPpBEREREREREQUpUz7+B5Fv6Hl9Zi8swoXlzmQVdmIxOeH44BFwa6OidiUmYw3stOwLSMp0jGJiIiIiIiIKApwUYr8OqeqEQs3HsWlRx1wKkDC0Fzg6oFASgoSa2owpKQEA7cVYfr2KnzWLRkzR3bD/rTI3EHNTO7yejiqHSgoKICj5ATcqQqscbgol9MjG4Mzs5Ceno5xeaOwo2wXig/vjHQsilOsRw37k4b1QJKwHjXsTxrWA0nDmtSwR2nMrAcuSlGbbvjmJF7c+C2siXbgttuQMGsWkJfn87iErVuBF17AhSvewudv7ceMkd2wakBqBBKHl+rywLm7Gg3FlfBUaHcYmfP+HO/3Lel22HM6IqF/KhRb7H46NinBjvHDxmD6iCkY2vM879cX3ToXALDt0NdYXLgMq7asR73T2J1YiPRiPWrYnzSsB5KE9ahhf9KwHkga1qSGPUoTqXrgohS16oZvTmLxR0eB/v1h+fBDoHfv1q8jlZMDvPIKbI8+CsvVV2PJR3ugQMXKAWeZGzqM3FWNOPXeQag1rlYf46logGPjt6j/ogLtr+sFawyeMXZulz5Yfc/L6NkpEx615XoY3D0LCyc/hQdG34NxC6diX3mpySkpXrAeNexPGtYDScJ61LA/aVgPJA1rUsMepYlkPRhe5mtsbMTPfvYzbN68OSRBSJa+VY14ceO32oLU558D3bsDigJYrS1vYLVq3+/eHZbNm4F+/fDixm9xTlWjucHDxF3ViNqVB6DWtt6sTqfWulC78gDcMfLzNzm3Sx/84763kJnWFYqiwGppuR6sFisURUFmWld8fP8K9M3obWpO9qf4EC31GG7sT5poqQf2p/gQLfUYbuxPmmipB/an+BEtNRlu7FGaSNeDoUWphoYG/PrXv8bu3btDEoLkWbDxKCyJdu0MqZQUICFB34YJCUBKCiwffQRroh0LNx4Nb1ATqC4PTr13EGj0AKrejQA0atuprti4S2FSgh2r73kZKfb2sFn1nWRps9qQYm+PNTOXIinBHuaEGvan+BAt9Rhu7E+aaKkH9qf4EC31GG7sT5poqQf2p/gRLTUZbuxRGgn1EPCi1J49ezBhwgQcPHgw6J2TTEOP1+PSow4kTLxJ+8ie3gWpJgkJQJ8+sE2YiEuPOjC0vD48QU3i3F2tnc6pt1k1UQG1xgXn7uqw5DLb+GFj0LNTpu5m1cRmtaFX5+7IP390mJL9gP0pfkRDPZqB/UkTDfXA/hQ/oqEezcD+pImGemB/ii/RUJNmYI/SSKiHgBel/vOf/+DCCy/EihUrgt45yTS5pApOBcCsWa1fQ8oftxu49144FWDyzqpQxjNdQ3FlRLeXYvqIKa1+vtgft8eN6SOmhDiRL/an+BEN9WgG9idNNNQD+1P8iIZ6NAP7kyYa6oH9Kb5EQ02agT1KI6EeAr7Q+aRJk4LeKcl2cZkDCUNzW7zLnm5WKzBsGBKG5uKiKL6VqLu83nsHBqM8FQ1wl9dH9a1Ec3pkN7sDQ6CsFityew1CTo/ssN5alv0pPkRLPYYb+5MmWuqB/Sk+REs9hhv7kyZa6oH9KX5ES02GG3uURko9mH73PUVR0C4h2dC2yQlJzf4bqBpFgcoMfjNkVTYCVw809Ny+T5aFgcXbfPYTDeMAAI5qh6HnPpOtBkjO9N1HtIzD4MwsQ899pkGZA7Dn2AGfr9cqSkiePxSMzkWw8wAEXw/xkiHc9agngz9mjEO4+5OeDP7ESj1I6VGS54EZNOxPGvYnDfuTPvHw/kpKhnDXZLSMA9/jaaS8x1NUVQ30U5ReWVlZeP3113HhhRf6fazb7UZRURHGjx+PVatWGd1lUMaMGYPjx4+jS5cuWL9+PTO0lMHjwbDhw4Fp04DFi4Pf2fTpwJIl2PKf/wCWHz4tKn4cvldQUIA5c+YEva/Zs2cjPz/fUIZw05MhPT0dvXsHf3eF0tJSVFRU+Hy9qS/k5ubC2todHgMUSH8C2KOiKUO461FPBjP4yxDu/qQngxkk1EOoexT7U+xmYH/SsD9p2J/MEQ21ICVDuGsyWsaB7/E0Ut7jmX6m1AlHFcYum2Zo2+SEJLw9cQEmrLgXDmfgF8+uqKv0/pcZWs9wwKIgsabGUDYf1dVotCgYu/zOgDLoYcZcOEpOGMp2pkVbl+PVug2GMvhjxjiMyxuFRbfONZTvdE8XvoR3t37o8/VaR1XQzx0qRntUsPMABF8P8ZIh3PWoJ4M/ZoxDuPuTngz+xEo9SOlR7E/yM7A/adifNOxP+sTD+yspGcJdk9EyDnyPp5HyHs/0RSlVVVHnDO50OYez3tBzNJ0UxgxtZ9jVMRFDSkqCyuZVUoKSTok++4mGcQAAd2poTol2paDFfUTLOOwo2xVUNu/zHNnV5jhIEOxcGJ2Hpn0zg/8M4a5HPRn0Cuc4hLs/6cmgV6zUQ6RJngdm0LA/adifNOxPgYnl91dSMph1TC99HPgeTyPlPV7Ad9+j2LcpMxnObUXA1q3aXfSMcLuBLVvgLN6Gz7sZ+xytBNaMJFjS7UE9hyXdHtUXwAOA4sM7se3Q13B7jNWD2+NG0cGvsP1IiBY7Ka6xHjXsTxrWA0nCetSwP2lYDyQNa1LDHqWRUg9clCIfb2SnIUEF8MILza4DFRCrFViwAAmq9nzRzJ7TMaLbS7G4cBksirF6sFqsWFy4LMSJKJ6xHjXsTxrWA0nCetSwP2lYDyQNa1LDHqWRUA9BLUrt2rVL90XwKHpsy0jCZ92S4VrxFlBaCjidgT2B0wkcOADX2yvwWbdkbIvyFeSE/qlQUmxAoGd5KoCSYkNC/9Sw5DLbqi3rcehEGVxuV0DbudwuHPzuCAq+bPmaEOHC/hTboq0ew4X9SRNt9cD+FNuirR7Dhf1JE231wP4U+6KtJsOFPUojoR54phS1aObIbnA3NsDz058CNTX6F6acTqCmBp6rr4a7sQEzR3YLb1ATKDYL2l/XC0i06G9aCoBEbTvFFhsvs3pnA65/8Q7UNJzS3bRcbhdqGk5h3MKpqHc2hDkhxRPWo4b9ScN6IElYjxr2Jw3rgaRhTWrYozQS6iE2RpJCbn9aImaM7Abs3g3PhRcCR45o32jtGlNNXz9yRHv8nj2YMbIb9qclmhM4zKxpiehwQx8oHfTdG0DpYEOHG/rAGiM/f5O9xw/gyvkTUVZ1DABa/fxx09fLqo7hyvkTsa+81LSMFD9Yjxr2Jw3rgSRhPWrYnzSsB5KGNalhj9JEuh5Mv/seRY9VA1KhQMWLG/fCel42bBMmAvfeCwwb5vvgoiJgwQK43l4Bd2MDZlydiVUDYuOUxibWtESkTOoL5+5qNBRXwlPhuypsSbfDntNROx00RlbPz7SvvBTDn7wW+eePxvQRU5Dba5DPY7YfLsHiwmUo+HJDzPw1hWRiPWrYnzSsB5KE9ahhf9KwHkga1qSGPUoTyXrgohS1aeWAs7ClSzIWbjyKS//6Vzhf/ysShuYCWVlAaipQXQ3s2gXntiIkqMDnmcm494pzYuYMqTMpNgsSs9OQmJ0Gd3k9bDXAjLxJWLR1OVwpiPo7MOhV72zA8s1rsHzzGuT0yMagzAF4cMTdeLrwJXxV9g2KD++MdESKI6xHDfuThvVAkrAeNexPGtYDScOa1LBHaSJVD1yUIr/2pyXi2vzeGFpej8k7q3DR4Z0YWLwNiR4VjRYFJZ0S8fngNLyRnRb1FzUPhDUjCcmZycjPz8erdRtQ53REOlJEFB/eiT3HDuCOQTfi3a0fxu04kAysRw37k4b1QJKwHjXsTxrWA0nDmtSwR2nMrAcuSpFu2zKSsC3jbABAu4RkrJ30F4xdfmfcvlCJiIiIiIiIyLjY/EAkmcPC8iEiIiIiIiIiY7iqQEREREREREREplNUVVXN2JHb7UZRURFGXD4CdaqxK7UrioL0dh1RUVcJI7HVOhegAlAApZ2xTy4yAzMwQ+gztFPsKPxXIXJzc2G1Wg1lCFawPSrYMQCCnwtmYAZmCE+GSPco9idmYAZmaE209ycgNo5lmYEZmMGX3v5k/jWlVEA95TK6KY7XHmcGZmCGWMvQ3m5821AzOA4hmwdmYAZmkJdBSo+K93lgBmZgBl9R3p++3zT6j2WZgRmYwZfO/mT+opQCKO3jd7WQGZiBGVp6AkO7DQ+DPSpW/uLKDMzADC09ibHNQo79iRmYgRl8nsTYZiHH93jMwAzM4PME+h5m+qKUkmxF6oR+hrZtl5CMtVOWYOyyaYbu+Fb92h6op1xQ2tmQehszMAMzSMngfrvM0H7DwWiPCnYMgODnghmYgRnCk0FKj2J/YgZmYIYzRXt/AmLjWJYZmIEZfOntT7zQORERERERERERmY6LUkRERERERJHg8UQ6ARFRRJl/TSkiIiIiIqI4NLS8HpN3VuHiMgeyKhuR+PxwHLAo2NUxEZsyk/FGdhq2ZSRFOiYRkWm4KEVRKadHNgZnZiE9PR3j8kZhR9kuFB/eaWoGd3k9HNUOFBQUwFFyAu5UBVaTDyIkZCCi5tif5GQgouYk9Kd4zXBOVSMWbjyKS4864FSAhKG5wNUDgZQUJNbUYEhJCQZuK8L07VX4rFsyZo7shv1piWHNRCRNvPaHeM/ARSmKGkkJdowfNgbTR0zB0J7neb++6Na5AIBth77G4sJlWLVlPeqdDWHJoLo8cO6uRkNxJTwV2j7mvD/H+31Luh32nI5I6J8KxRaeT8dKyEBEzbE/yclARM1J6E/xnuGGb07ixY3fwppoB267DQmzZgF5eT6PS9i6FXjhBVy44i18/tZ+zBjZDasGpIY0C5E08d4fmIGLUhQlzu3SB6vveRk9O2XCo7b82fvB3bOwcPJTeGD0PRi3cCr2lZeGNIO7qhGn3jsItcbV6mM8FQ1wbPwW9V9UoP11vWAN8V+4JGQgoubYn+RkIKLmJPSneM9wwzcnsfijo0D//rB8+CHQu3fr15HKyQFeeQW2Rx+F5eqrseSjPVCgYuWAs0KShUiaeO8PzKAJ6M+Ux44dw6xZszB8+HBcdtllmDt3LhoawrNKR9Tk3C598I/73kJmWlcoigKrxdri46wWKxRFQWZaV3x8/wr0zegdsgzuqkbUrjwAtbb1N1unU2tdqF15AO6qxpjKIB17FJmN/UlOBunYn8hsEvpTvGfoW9WIFzd+qy1Iff450L07oCiAteUMsFq173fvDsvmzUC/fnhx47c4J8y9kv2JIiHe+wMz/ED3opSqqpg1axYcDgfeeOMNPPfcc/jnP/+J559/PiRBiFqSlGDH6nteRoq9PWxWfSf22aw2pNjbY83MpUhKsAedQXV5cOq9g0CjB1D1bgSgUdtOdQV/VxUJGaRjjyKzsT/JySAd+xOZTUJ/YgZgwcajsCTatTOkUlKAhAR9GyYkACkpsHz0EayJdizceDSoHG1hf6JIiPRrkxlkZdC9KLVv3z4UFRVh7ty56N+/Py644ALMmjULf//734MOQdSa8cPGoGenTN0vkCY2qw29OndH/vmjg87g3F2tfRxF75utJiqg1rjg3F0dExmkY48is7E/yckgHfsTmU1Cf4r3DEOP1+PSow4kTLxJ+8ie3gWpJgkJQJ8+sE2YiEuPOjC0vN5wlrawP1EkxHt/YIbmdC9KZWRk4OWXX0Z6enqzr9fW1gYdgqg100dMafUzrf64PW5MHzEl6AwNxZUR3V5KBunYo8hs7E9yMkjH/kRmk9Cf4j3D5JIqOBUAs2a1fg0pvyHcwL33wqkAk3dWGc7SFvYnioR47w/M0JzuRanU1FRcdtll3v/v8XiwbNkyXHTRRUGHIGpJTo9sDO15XqufafXHarEit9cg5PTINpzBXV7vvYOUUZ6KBriD+OuWhAzRgD2KzMT+JCdDNGB/IjNJ6E/MAFxc5kDC0FztLnutXUPKbwgrMGwYEobm4qKjDmPP4Qf7E5kt0q9NZpCVAQji7nvz58/H119/jZUrVwa0naIoaJeQbGifyQlJzf4bqBpFgcoMUZNhcGaWoec+06DMAdhz7IChDI7q0BwA2GqA5EzffURLBn+CrYdaRTG0XVvM7lHBjgEQ/Fwwg3kZwt2f9GQId2+Ilgz+hKIeQt2j2J+YIdb7EzMAWZWNwNUDQ5IBWVkYWLytxZ8z2vsTED/vbZhBI+E9HjOYk0Fvf1JUVQ30KhCYP38+Xn31VTz33HMYNWqUrm3cbjeKioowfvx4rFq1KtBdhsSYMWNw/PhxdOnSBevXr2cG4RnS09PRu3fwV/QvLS1FRUWFoQwFBQWYM2dO0Blmz56N/Pz8qM0Qbk19ITc3F1ajf008DXsUM4Q7Q7j7k54M4e4N0ZLBDKHsUexPzBDuDBL6U9xn8HgwbPhwYNo0YPHioDNg+nRgyRJs+c9/AEvzD7qwP0XH65IZfiDhPR4zmJNBb38K+EypJ554Am+++Sbmz5+vu1md7oSjCmOXTQt4O0BbsX174gJMWHEvHM7AT/WvqKv0/pcZ5GcYlzcKi26dayjf6Z4ufAnvbv3QUAZHyYmg9w8Ai7Yux6t1G6I2gz/B1kOto8rQflsSqR4V7BgAwc8FM5iXIdz9SU+GcPeGaMngTyjqIVQ9iv2JGeKlPzEDcMCiILGmJuj9AwCqq9FoUTB2+Z0+34r2/gTEz3sbZtBIeI/HDOZk0NufAlqUWrhwId566y08++yzuOaaawLZ1EtVVdQ5gzvd3+GsN/QcTSeFMUN0ZNhRtiuobN7nObKrxX3oyeBODc0p0a4URHUGvYKth2BJ6FFGx6Bp38wQHRnC3Z/0ZAh3b4iWDHqFoh6Cwf7EDGZlkNCfmAHY1TERQ0pKQpIBJSUo6ZTY5nFcMCT0JyD239swg0bCezxmMDeDP7ovdL53714sWrQI06ZNw7Bhw1BeXu79RxQOxYd3Ytuhr+H2uA1t7/a4UXTwK2w/YvyAwJqRBEu63fD2AGBJt8OaYfzaERIyRAP2KDIT+5OcDNGA/YnMJKE/MQOwKTMZzm1FwNat2l30DIVwA1u2wFm8DZ93M3aNIH/Yn8hskX5tMoOsDEAAi1Iff/wx3G43XnrpJfz4xz9u9o8oXBYXLoNF0V2mzVgtViwuXBZ0BntOx4huLyWDdOxRZDb2JzkZpGN/IrNJ6E/xnuGN7DQkqABeeMHnOlD6Q1iBBQuQoGrPFw7sTxQJ8d4fmKE53XufPn06du3a1eI/onBZtWU9Dp0og8vtCmg7l9uFg98dQcGXLV+jJBAJ/VOhpNiAQD+logBKig0J/VNjIoN07FFkNvYnORmkY38is0noT/GeYVtGEj7rlgzXireA0lLA6QzsCZxO4MABuN5egc+6JWNbmM4oZX+iSIj3/sAMzRlcticyR72zAde/eAdqGk7pfqG43C7UNJzCuIVTUe9sCDqDYrOg/XW9gESL/jddCoBEbTvFFvzLTEIGImqO/UlOBiJqTkJ/YgZg5shucDc2wPPTnwI1NfoXppxOoKYGnquvhruxATNHdgsqB5E0kX5tMoOsDDwSJPH2Hj+AK+dPRFnVMQBo9TOvTV8vqzqGK+dPxL7y0pBlsKYlosMNfaB00HdvAKWDDR1u6ANrWmJMZSCi5tif5GQgouYk9Kd4z7A/LREzRnYDdu+G58ILgSNHvt9ZK9dvafr6kSPa4/fswYyR3bCfvZJiULz3B2b4QUB33yOKlH3lpRj+5LXIP380po+Ygtxeg3wes/1wCRYXLkPBlxtCsmJ7JmtaIlIm9YVzdzUaiivhqfDdhyXdDntOR+3jLGH467+EDETUHPuTnAxE1JyE/hTvGVYNSIUCFS9u3AvredmwTZgI3HsvMGyY74OLioAFC+B6ewXcjQ2YcXUmVg2I/Y84U/yK9/7ADBouSlHUqHc2YPnmNVi+eQ1yemRjUOYAPDjibjxd+BK+KvsGxYd3hj2DYrMgMTsNidlpcJfXw1YDzMibhEVbl8OVAlPuICUhAxE1x/4kJwMRNSehP8V7hpUDzsKWLslYuPEoLv3rX+F8/a9IGJoLZGUBqalAdTWwaxec24qQoAKfZybj3ivO4RlSFBfivT8wAxelKEoVH96JPccO4I5BN+LdrR+izukwPYM1IwnJmcnIz8/Hq3Ub4jYDETXH/iQnAxE1J6E/xWuG/WmJuDa/N4aW12PyzipcdHgnBhZvQ6JHRaNFQUmnRHw+OA1vZKeF7aLmRNLFa3+I9wxclCIiIiIiIjLBtowkbMs4GwDQLiEZayf9BWOX38mFeyKKW7ygAxERERERUSRY+HaMiOIbuyAREREREREREZlOUVVVNWNHbrcbRUVFGHH5CNSpxq7UrigK0tt1REVdJYzEVutcgApAAZR2xj65yAzMwAyhz9BOsaPwX4XIzc2F1Wo1lCFYwfaoYMcACH4umIEZmCE8GSLdo9ifmIEZmKE10d6fgNg4lmUGZmAGX3r7k/nXlFIB9ZTL6KY4XnucGZiBGWItQ3u78W1DzeA4hGwemIEZmEFeBik9Kt7ngRmYgRl8RXl/+n7T6D+WZQZmYAZfOvuT+YtSCqC0j9/VQmZgBmZo6QkM7TY8DPaoWPmLKzMwAzO09CTGNgs59idmYAZm8HkSY5uFHN/jMQMzMIPPE+h7mOmLUkqyFakT+hnatl1CMtZOWYKxy6YZukNF9Wt7oJ5yQWlnQ+ptzMAMzCAlg/vtMkP7DQejPSrYMQCCnwtmYAZmCE8GKT2K/YkZmIEZzhTt/QmIjWNZZmAGZvCltz/xQudERERERERERGQ6LkoREREREREREZHpuChFRERERERERESm46JUAHJ6ZGNc3iikp6djXN4o5PTIjssM7vJ6OEpOoKCgAI6SE3CX15ueQcI4MINGQj2QjFqQkEFCPUoYBwkZJMyFhAwkox4lZJBQjxLGgRnkZCCNhLmQkIE9ihkilcH8u+9FmaQEO8YPG4PpI6ZgaM/zvF9fdOtcAMC2Q19jceEyrNqyHvXOhpjNoLo8cO6uRkNxJTwV2j7mvD/H+31Luh32nI5I6J8KxRaetU4J48AMGgn1QDJqQUIGCfUoYRwkZJAwFxIykIx6lJBBQj1KGAdmkJOBNBLmQkIG9ihmkJCBi1JtOLdLH6y+52X07JQJj+pp8TGDu2dh4eSn8MDoezBu4VTsKy+NuQzuqkaceu8g1BpXq4/xVDTAsfFb1H9RgfbX9YI1LTGkGSSMAzNoJNQDyagFCRkk1KOEcZCQQcJcSMhAMupRQgYJ9ShhHJhBTgbSSJgLCRnYo5hBSoaAlztLS0sxdepU5OXl4fLLL8fLL78ckiDSnNulD/5x31vITOsKRVFgtVhbfJzVYoWiKMhM64qP71+Bvhm9YyqDu6oRtSsPQK1tvVmdTq11oXblAbirGkOWQcI4MINGQj20hf2pOdZjc+xPsT0XEjK0hf2pOb4mmmN/YoZwZ2hLvPQnQMZcSMjAHsUMkjIEtCjl8Xgwffp0dOzYEatXr8bjjz+Ol156CWvXrg1JGCmSEuxYfc/LSLG3h82q72Qym9WGFHt7rJm5FEkJ9pjIoLo8OPXeQaDRA6h6NwLQqG2nulpeYQ2EhHFgBo2EemgL+1PrWI9NG4H9KQwZJMyFhAxtYX9qHV8TTRuB/YkZwpahLfHSnwAZcyEhA3sUM0jLENCiVEVFBbKzs/HYY4+hT58+GDFiBC6++GJs2bIl6CCSjB82Bj07ZeqelCY2qw29OndH/vmjYyKDc3e1djqn3mbVRAXUGhecu6uDziBhHJhBI6Ee2sL+1DbW4/fYn0KeQcJcSMjQFvantvE18T32J2YIU4a2xEt/AmTMhYQM7FHMIC1DQItSXbp0wfPPP48OHTpAVVVs2bIFX3zxBYYPHx50EEmmj5jS6uco/XF73Jg+YkpMZGgorozo9oCMcWAGjYR6aAv7k3+sx9BtD8gYBwkZJMyFhAxtYX/yj6+J0G0PyBgHZpCToS3x0p8AGXMhIQN7FDNIy2D4EvojR47EpEmTkJeXh1GjRgUdRIqcHtkY2vO8Vj9H6Y/VYkVur0FB3TJRQgZ3eb33DgxGeSoagrqVqIRxYAaNhHoIBPtTy1iPP2B/ip25kJAhEOxPLeNr4gfsT8wQygyBiNX+BMiYCwkZ2KOYQVoGIIi7773wwguoqKjAY489hrlz5+Lhhx/WtZ2iKGiXkGxon8kJSc3+G6gaRYHqJ8PgzCxDz32mQZkDsOfYgajN4Kh2hCSDrQZIzvTdR7SMAzNowl0PtYoSkudvYrQ/AcZ7VLD9CfA/F+GuhWjJEO561JNBwjhIyCBhLszIEMoexf7UNr4mNOxPzKA3Q7T3J4Dv8czMwPd4zGBmBr39SVFVNdBPkzbz/vvv47777sOXX36JxMTWbxHpdrtRVFSE8ePHY9WqVcHs0rAxY8bg+PHj6NKlC9avX9/iY9LT09G7d/BXkS8tLUVFRUXUZigoKMCcOXOCzjB79mzk5+cbyiBhHJhBE+56aOoLubm5sFqNrdS3RG9/AqKjR4W7FqIlQ7jrUU8GCeMgIYOEuTAjQzh6FPtTy/ia0LA/MYPeDOxP0XM8LSED3+Mxg5kZ9PangM6UqqioQFFREa666irv1/r16wen04na2lp06tTJ73OccFRh7LJpgezWKzkhCW9PXIAJK+6Fwxn4KYMVdZXe/7aWYVzeKCy6da6hfKd7uvAlvLv1w6jN4Cg5EfT+AWDR1uV4tW6DoQwSxoEZNOGuh1pHVdDPHYr+BBjvUcH2J8D/XIS7FqIlQ7jrUU8GCeMgIYOEuTAjQ7A9iv1JP74mNOxPzKA3Q7T3J4Dv8czMwPd4zGBmBr39KaBFqcOHD2PmzJkoLCxE165dAQA7duxAp06ddDcsVVVR5wzutEGHs97QczSdFNZWhh1lu4LK5n2eI7ta3Ee0ZHCnhuZUYFcKonocmEFjVj0EIxT9qSlLMD3KaH9q2ndbGcJdC9GSIdz1qCeDhHGQkEHCXJiZwSj2J/34mtCwPzFDoBmMktKfAL7HMyMD3+MxQyQy+BPQhc6HDBmCQYMGYfbs2dizZw8KCwsxf/583HXXXYE8jWjFh3di26Gv4fa4DW3v9rhRdPArbD9SEtUZrBlJsKTbDW8PAJZ0O6wZxq9fIWEcmEEjoR78YX/yj/X4A/an2JkLCRn8YX/yj6+JH7A/MUMoM/gTD/0JkDEXEjKwRzGDtAxAgItSVqsVixYtQnJyMiZOnIjf/e53uOWWW3DrrbcGFUKaxYXLYFGM3ZjQarFiceGymMhgz+kY0e0BGePADBoJ9dAW9if/WI+h2x6QMQ4SMkiYCwkZ2sL+5B9fE6HbHpAxDswgJ0Ob+4iT/gTImAsJGdijmEFahoD33rVrVyxcuBBbtmzBp59+irvuugtKiO+cFWmrtqzHoRNlcLldAW3ncrtw8LsjKPiy5WsARFuGhP6pUFJsQKDTqwBKig0J/VODziBhHJhBI6Ee/GF/ah3r8XvsTyHPIGEuJGTwh/2pdXxNfI/9iRnClMGfeOhPgIy5kJCBPYoZpGUwtiQW4+qdDbj+xTtQ03BK9+S43C7UNJzCuIVTUe9siIkMis2C9tf1AhIt+puWAiBR206xBV9eEsaBGTQS6oFk1IKEDBLqUcI4SMggYS4kZCAZ9Sghg4R6lDAOzCAnA2kkzIWEDOxRzCAtA4/CWrH3+AFcOX8iyqqOAUCrn7Ns+npZ1TFcOX8i9pWXxlQGa1oiOtzQB0oHfdfEVzrY0OGGPrCmtX372EBIGAdm0EioB5JRCxIySKhHCeMgIYOEuZCQgWTUo4QMEupRwjgwg5wMpJEwFxIysEcxg6QMAd19L97sKy/F8CevRf75ozF9xBTk9hrk85jth0uwuHAZCr7cEJa/ZEjIYE1LRMqkvnDurkZDcSU8Fb77sKTbYc/pqJ0OGoa/OEsYB2bQSKgHklELEjJIqEcJ4yAhg4S5kJCBZNSjhAwS6lHCODCDnAykkTAXEjKwRzGDlAxclPKj3tmA5ZvXYPnmNcjpkY1BmQPw4Ii78XThS/iq7BsUH94ZFxkUmwWJ2WlIzE6Du7wethpgRt4kLNq6HK4UhPWuRU0kjAMzaCTUA8moBQkZJNSjhHGQkEHCXEjIQDLqUUIGCfUoYRyYQU4G0kiYCwkZ2KOYQUIGLkoFoPjwTuw5dgB3DLoR7279EHVOR1xmsGYkITkzGfn5+Xi1bkPcjgMzaCTUA8moBQkZJNSjhHGQkEHCXEjIQDLqUUIGCfUoYRyYQU4G0kiYCwkZ2KOYIVIZeN46ERERERERERGZjotSRERERERERERkOi5KERERERERERGR6RRVVVUzduR2u1FUVIQRl49AnWrsSu2KoiC9XUdU1FXCSGy1zgWoABRAaWfsclrMwAzMEPoM7RQ7Cv9ViNzcXFitVkMZghVsjwp2DIDg54IZmIEZwpMh0j2K/YkZmIEZWhPt/QmIjWNZZmAGZvCltz+Zf6FzFVBPuYxuiuO1x5mBGZgh1jK0txvfNtQMjkPI5oEZmIEZ5GWQ0qPifR6YgRmYwVeU96fvN43+Y1lmYAZm8KWzP5m/KKUASvv4XS1kBmZghpaewNBuw8Ngj4qVv7gyAzMwQ0tPYmyzkGN/YgZmYAafJzG2WcjxPR4zMAMz+DyBvoeZviilJFuROqGfoW3bJSRj7ZQlGLtsmqFbEla/tgfqKReUdjak3sYMzMAMUjK43y4ztN9wMNqjgh0DIPi5YAZmYIbwZJDSo9ifmIEZmOFM0d6fgNg4lmUGZmAGX3r7Ey90TkREREREREREpuOiFBERERERERERmY6LUkREREREREREZLqoWZRyl9fDUXICBQUFcJScgLu83vQMOT2yMS5vFNLT0zEubxRyemSbnoHjICcD50JOhkhjLWg4DnIySJgLCRkkzEWkcR40HAdmOB3rQQ7OhUbCOEjIIGEuJGSIt7kw/+57AVBdHjh3V6OhuBKeigYAwJz353i/b0m3w57TEQn9U6HYwrO+lpRgx/hhYzB9xBQM7Xme9+uLbp0LANh26GssLlyGVVvWo97ZEJYMHAc5GTgXcjJEGmtBw3GQk0HCXEjIIGEuIo3zoOE4MMPpWA9ycC40EsZBQgYJcyEhQzzPhaIavv9oYNxuN4qKinD56JGwTsj0//iqRpx67yDUGpffxyopNrS/rhesaYltPs57Bfr2+q5Af26XPlh9z8vo2SkTHtUDq8Xqm9PjhkWx4NCJMoxbOBX7yktDmoHjICcD5yJ8Gdxvl+FfGzYiNzcXVqvv85khkB4VjloAApuLcMxDoBk4DnIySJgLCRnCNReR7lHsT4Fn4DgwQ7Pnj+F6iKb+BPB42vv8AsZBQgYJcyEhQ6zOhd7+JPLje+6qRtSuPAC11v+kAIBa60LtygNwVzWGLMO5XfrgH/e9hcy0rlAUpcVJAQCrxQpFUZCZ1hUf378CfTN6hywDx0FOBs6FnAyRxlrQcBzkZJAwFxIySJiLSOM8aDgOzHA61oMcnAuNhHGQkEHCXEjIwLkIYlFq+vTpePDBB0MS4nSqy4NT7x0EGj2A3nO4VACN2naqyxN0hqQEO1bf8zJS7O1hs+r7hKPNakOKvT3WzFyKpAR70Bk4DnIycC7kZAhEOHoUa0HDcZCTQcJcSMggYS4Cwf70g1h8TUgYB2bQsB4Cx/d4zcViTUrIIGEuJGTgXGgMLUqtW7cOhYWFQe+8Jc7d1dppa4F+qFAF1BoXnLurg84wftgY9OyUqXtSmtisNvTq3B35548OOgPHQU4GzoWcDHqFq0exFjQcBzkZJMyFhAwS5kIv9idfsfaakDAOzKBhPQSG7/FaFms1KSGDhLmQkIFzoQl4Uaqqqgrz5s3DkCFDgt55SxqKKyO6PQBMHzEFHtXYqqPb48b0EVOCzsBxkJOBcyEngx7h7FGsBQ3HQU4GCXMhIYOEudCD/al1sfSakDAOzKBhPejH93hti6WalJBBwlxIyMC50AS8KPXHP/4RP//5z9Gvn/+LZQXKXV7vvdK8UZ6KhqBumZjTIxtDe57X6uco/bFarMjtNSioWyZyHORk4FzIyaBXuHoUa0HDcZCTQcJcSMggYS70Yn9qXay8JiSMAzNoWA+B4Xu8tsVKTUrIIGEuJGTgXPwgoHO0Nm3ahP/+979Yu3YtHnvsMUM7VBQF7RKSW/yeo9ph6DnPZKsBkjN991GjKFD9ZBicmRWSDIMyB2DPsQOGMnAc5GTgXJiToVZRQvL84exR4a4FwP9chHse9GTgOMjJIGEuJGQwYy5C0aPYn/SJ9teEhHFgBk281IP0/gTweLqJhHGQkEHCXEjIEA9zobc/6V6UamhowKOPPopHHnkESUlJugOeqVNyGlZNWdLi9woKCjDn/TmGn7vJjLxJyM/P9/n6mOVjcLz2ONLbdcTaVjKkp6cHvX8AeHDE3bhj0I2GMnAc5GTgXJiTYfzq8UE/d7h7VLhrAfA/F+GeBz0ZOA5yMkiYCwkZzJiLYHsU+5N+0f6akDAOzKCJl3qQ3p8AHk83kTAOEjJImAsJGeJhLvT2J92LUgsXLsTgwYNx2WWX6U/XghOOKoxdNq3F7zlKTgT13E0WbV2OV+s2+Hy9oq7S+9/WMozLG4VFt84NOsPThS/h3a0fGsrAcZCTgXNhToZaR1XQzx3uHhXuWgD8z0W450FPBo6DnAwS5kJCBjPmItgexf6kX7S/JiSMAzNo4qUepPcngMfTTSSMg4QMEuZCQoZ4mAu9/Un3otS6detQUVGBvLw8AEBjYyMA4IMPPsDWrVv1Pg1UVUWds+VT1dypofkIjysFLe5DVVW/GXaU7QpJhh1HdhnOwHGQk4FzYW6GYIS7R4W7Fpr23VaGcM+DngwcBzkZJMyFhAxmzoVR7E/6RftrQsI4MIMm3urBKL7HC0y0v6+QkEHCXEjIEE9z4Y/uRam//e1vcLlc3v//zDPPAADuu+8+vU/hlzUjCZZ0e1AX/LKk22HNMH7qafHhndh26GsM7p5l6IJfbo8b2w+XYPuREsMZOA5yMnAu5GTwJ9w9irWg4TjIySBhLiRkkDAX/rA/+RcrrwkJ48AMGtaDPnyPp0+s1KSEDBLmQkIGzsUPdN99r3v37ujdu7f3X/v27dG+fXv07t07qABnsud0jOj2ALC4cBksSsA3JgSgXYF+ceGyoDNwHORk4FzIydAWM3oUa0HDcZCTQcJcSMggYS7awv7kXyy9JiSMAzNoWA/+8T2ePrFUkxIySJgLCRk4Fxpjew+jhP6pUFJsQKBnsymAkmJDQv/UoDOs2rIeh06UweV2+X/waVxuFw5+dwQFX7b8ufNAcBzkZOBcyMkQaawFDcdBTgYJcyEhg4S5iDTOg4bjwAynYz3IwbnQSBgHCRkkzIWEDJwLjeFFqaeffhpPP/100AHOpNgsaH9dLyDRon9yFACJ2naKLfh1tnpnA65/8Q7UNJzSPTkutws1DacwbuFU1DuNn4LXhOMgJwPnQk6GQISjR7EWNBwHORkkzIWEDBLmIhDsTz+IxdeEhHFgBg3rIXB8j9dcLNakhAwS5kJCBs6FRtyZUgBgTUtEhxv6QOmg75JXSgcbOtzQB9a0xJBl2Hv8AK6cPxFlVccAaJ+XbEnT18uqjuHK+ROxr7w0ZBk4DnIycC7kZIg01oKG4yAng4S5kJBBwlxEGudBw3FghtOxHuTgXGgkjIOEDBLmQkIGzkUAFzo3mzUtESmT+sK5uxoNxZUtXgDMkm6HPaejdtpbCFYJz7SvvBTDn7wW+eePxvQRU5Dba5DPY7YfLsHiwmUo+HJDWP6SwXGQk4FzISdDpLEWNBwHORkkzIWEDBLmItI4DxqOAzOcjvUgB+dCI2EcJGSQMBcSMsT7XIhdlAK009kSs9OQmJ0Gd3k9bDXAjLxJWLR1OVwpCOpK83rVOxuwfPMaLN+8Bjk9sjEocwAeHHE3ni58CV+VfYPiwzvDnoHjICcD50JOhkhjLWg4DnIySJgLCRkkzEWkcR40HAdmOB3rQQ7OhUbCOEjIIGEuJGSI57kQ+fG9llgzkpCc1RH5+flIzupoyqScqfjwTry79UNUVFTg3a0fRuQXB8dBTgbOhZwMkcZa0HAc5GSQMBcSMkiYi0jjPGg4DsxwOtaDHJwLjYRxkJBBwlxIyBBvcxE1i1JERERERERERBQ7uChFRERERERERESm46IUERERERERERGZTlFVVTVjR263G0VFRRhx+QjUqcau1K4oCtLbdURFXSWMxFbrXIAKQAGUdsau8c4MzMAMoc/QTrGj8F+FyM3NhdVqNZQhWMH2qGDHAAh+LpiBGZghPBki3aPYn5iBGZihNdHen4DYOJZlBmZgBl96+5P5d99TAfWUy+imOF57nBmYgRliLUN7u/FtQ83gOIRsHpiBGZhBXgYpPSre54EZmIEZfEV5f/p+0+g/lmUGZmAGXzr7k/mLUgqgtI/f1UJmYAZmaOkJDO02PAz2qFj5iyszMAMztPQkxjYLOfYnZmAGZvB5EmObhRzf4zEDMzCDzxPoe5jpi1JKshWpE/oZ2rZdQjLWTlmCscumoc7pCHj76tf2QD3lgtLOhtTbmIEZmEFKBvfbZYb2Gw5Ge1SwYwAEPxfMwAzMEJ4MUnoU+xMzMAMznCna+xMQG8eyzMAMzOBLb3/ihc6JiIiIiIiIiMh0XJQiIiIiIiIiIiLTcVGKiIiIiIiIiIhMZ/6Fzg1yl9fDUe1AQUEBHCUn4E5VYM1IirsMOT2yMTgzC+np6RiXNwo7ynah+PDOuMsgYS4kZJAwFxIyRJqEWpCQQUItSMggYS6YQSOhHiJNwjxIyCChFphBI6EeJGSQMBcSSJgLCRkk1APHQSNhHCRkMHMuRC9KqS4PnLur0VBcCU9FAwBgzvtzvN+3pNthz+mIhP6pUGzhOelLQoakBDvGDxuD6SOmYGjP87xfX3TrXADAtkNfY3HhMqzash71zoaYzSBhLiRkkDAXEjJEmoRakJBBQi1IyCBhLphBI6EeIk3CPEjIIKEWmEEjoR4kZJAwFxJImAsJGSTUA8dBI2EcJGSI1FyIXZRyVzXi1HsHoda4Wn2Mp6IBjo3fov6LCrS/rhesaYkxl+HcLn2w+p6X0bNTJjyqp8XHDO6ehYWTn8IDo+/BuIVTsa+8NOYySJgLCRkkzIWEDJEmoRYkZJBQCxIySJgLZtBIqIdIkzAPEjJIqAVm0EioBwkZJMyFBBLmQkIGCfXAcdBIGAcJGSI5FyKvKeWuakTtygNQa1uflNOptS7UrjwAd1VjTGU4t0sf/OO+t5CZ1hWKosBqsbb4OKvFCkVRkJnWFR/fvwJ9M3rHVAYJcyEhg4S5kJAh0iTUgoQMEmpBQgYJc8EMGgn1EGkS5kFCBgm1wAwaCfUgIYOEuZBAwlxIyCChHjgOGgnjICFDpOci4EWpjz76CFlZWc3+zZo1KyRhAO20tVPvHQQaPYCqdyMAjdp2qqvlVb1oy5CUYMfqe15Gir09bFZ9J7TZrDak2NtjzcylSEqwx0QGCXMhIYOEuZCQwR/2J3MySKgFCRkkzAUzaCTUgz/sT+ZkkFALzKCRUA8SMkiYC3/C3Z8AGXMhIYOEeuA4aCSMg4QMEuYi4EWpPXv24IorrsCnn37q/ffkk08GHaSJc3e1dtqa3klpogJqjQvO3dUxkWH8sDHo2SlTd2E0sVlt6NW5O/LPHx0TGSTMhYQMEuZCQgZ/2J/MySChFiRkkDAXzKCRUA/+sD+Zk0FCLTCDRkI9SMggYS78CXd/AmTMhYQMEuqB46CRMA4SMkiYi4AXpfbu3YsBAwYgIyPD+y81NTXoIE0aiisjur2UDNNHTGn1s5z+uD1uTB8xJSYySJgLCRkkzIWEDP6wP5mTQUItSMggYS6YQSOhHvxhfzIng4RaYAaNhHqQkEHCXPgT7v4EyJgLCRkk1APHQSNhHCRkkDAXhhal+vTpE/SOW+Iur/dead4oT0UD3OX1UZ0hp0c2hvY8r9XPcvpjtViR22sQcnpkR3UGCXMhIYOEuZCQQQ/2p/BnkFALEjJImAtm0EioBz3Yn8KfQUItMINGQj1IyCBhLvQIZ38CZMyFhAwS6oHjoJEwDhIySJgLIMC776mqiv379+PTTz/FX/7yF7jdblxzzTWYNWsWEhP1Xf1dURS0S0hu8XuOakcgcVplqwGSM333UaMoUKMgw+DMrJBkGJQ5AHuOHYjaDBLmQkIGCXMR7gy1ihL0c4eiPwGtj0O4awHwPxcSMoS7FqIlg4S5YAaNGfUQbI9ifzIng4TewAwaCfUgIQP7k0bC8bSEDBKO6TkOGgnjICGDlPd4AS1KlZWVweFwIDExEc8//zwOHz6MJ598EvX19Xj44Yd1PUen5DSsmrKkxe8VFBRgzvtzAonUohl5k5Cfn+/z9THLx+B47XGkt+uItYIzpKenB71/AHhwxN24Y9CNUZtBwlxIyCBhLsKdYfzq8UE/dyj6E9B6jwp3LQD+50JChnDXQrRkkDAXzKAxox6C7VHsT+ZkkNAbmEEjoR4kZGB/0kg4npaQQcIxPcdBI2EcJGSQ8h5PUVU1oMtqVVVV4ayzzoLy/arXBx98gPvvvx9bt26F1dr6aV9utxtFRUW4YsyV6DCpb4uPcZScQNX7pYHEaVHa6D5Izuro8/VjL++Ap9YJS4cEdL1jsNgM4/JGYdGtc4POcPfrD+LdrR9GbQYJcyEhg4S5CHeG2uX78M/1HyM3N7fNPuKP0f4E+O9R4a4FwP9cSMgQ7lqIlgwS5oIZNGbUQyh6FPtT+DNI6A3MoJFQDxIysD9pJBxPS8gg4Zie46CRMA4SMkh5jxfYJdYBpKWlNfv/5557LhoaGnDy5El06tTJ7/aqqqLO2fKpau7U4D/CAwCuFLS4j6b1N+kZdpTtCkmGHUd2RXUGCXMhIYOEuTArQ7CC7U9NWVrKGO5aaNq39AzhroVoySBhLphBY2Y9BIP9KfwZJPQGZtBIqAcJGdifNBKOpyVkkHBMz3HQSBgHCRmkvMcL6ELnn3zyCS688EI4HD/scOfOnUhLS9PdsNpizUiCJd0e1HNY0u2wZiRFdYbiwzux7dDXcHvchrZ3e9woOvgVth8pieoMEuZCQgYJcyEhgz/sT+ZkkFALEjJImAtm0EioB3/Yn8zJIKEWmEEjoR4kZJAwF/6Euz8BMuZCQgYJ9cBx0EgYBwkZJMwFEOCiVF5eHux2Ox5++GHs27cPhYWFmDdvHu64446gQpzOntPy6bFmbS8lw+LCZbAoAd8cEYB2FfzFhctiIoOEuZCQQcJcSMjQFvYn8zJIqAUJGSTMBTNoJNRDW9ifzMsgoRaYQSOhHiRkkDAXbTGjPwEy5kJCBgn1wHHQSBgHCRkkzEVAe+/QoQOWLl2KEydOYPz48fjd736HiRMnhrRpJfRPhZJiAwI9m00BlBQbEvqnxkSGVVvW49CJMrjcroC2c7ldOPjdERR8uSEmMkiYCwkZJMyFhAxtYX8yL4OEWpCQQcJcMINGQj20hf3JvAwSaoEZNBLqQUIGCXPRFjP6EyBjLiRkkFAPHAeNhHGQkEHCXAS8JNa/f3+8+uqr2Lp1Kz799FPMnDnTe1G8UFBsFrS/rheQaNE/OQqARG07xWZslU9ahnpnA65/8Q7UNJzSXSAutws1DacwbuFU1DsbYiKDhLmQkEHCXEjI4A/7kzkZJNSChAwS5oIZNBLqwR/2J3MySKgFZtBIqAcJGSTMhT/h7k+AjLmQkEFCPXAcNBLGQUIGCXMR/E8RBta0RHS4oQ+UDvquw650sKHDDX1gTUuMqQx7jx/AlfMnoqzqGAC0+lnPpq+XVR3DlfMnYl95aUxlkDAXEjJImAsJGSJNQi1IyCChFiRkkDAXzKCRUA+RJmEeJGSQUAvMoJFQDxIySJgLCSTMhYQMEuqB46CRMA4SMkR6LgK++55ZrGmJSJnUF87d1WgoroSnwncFzpJuhz2no3baWwhWCSVm2FdeiuFPXov880dj+ogpyO01yOcx2w+XYHHhMhR8uSEsf02RkEHCXEjIIGEuJGSINAm1ICGDhFqQkEHCXDCDRkI9RJqEeZCQQUItMINGQj1IyCBhLiSQMBcSMkioB46DRsI4SMgQybkQuygFaKezJWanITE7De7yethqgBl5k7Bo63K4UhDUleajKUO9swHLN6/B8s1rkNMjG4MyB+DBEXfj6cKX8FXZNyg+vDMuMkiYCwkZJMyFhAyRJqEWJGSQUAsSMkiYC2bQSKiHSJMwDxIySKgFZtBIqAcJGSTMhQQS5kJCBgn1wHHQSBgHCRkiNRciP77XEmtGEpKzOiI/Px/JWR1NmRSJGYoP78S7Wz9ERUUF3t36YUR+eUnIIGEuJGSQMBcSMkSahFqQkEFCLUjIIGEumEEjoR4iTcI8SMggoRaYQSOhHiRkkDAXEkiYCwkZJNQDx0EjYRwkZDBzLqJmUYqIiIiIiIiIiGIHF6WIiIiIiIiIiMh0XJQiIiIiIiIiIiLTKaqqqmbsyO12o6ioCCMuH4E61diV2hVFQXq7jqioq4SR2GqdC1ABKIDSztg13pmBGZgh9BnaKXYU/qsQubm5sFqthjIEK9geFewYAMHPBTMwAzOEJ0OkexT7EzMwAzO0Jtr7ExAbx7LMwAzM4EtvfzL/7nsqoJ5yGd0Ux2uPMwMzMEOsZWhvN75tqBkch5DNAzMwAzPIyyClR8X7PDADMzCDryjvT99vGv3HsszADMzgS2d/Mn9RSgGU9vG7WsgMzMAMLT2Bod2Gh8EeFSt/cWUGZmCGlp7E2GYhx/7EDMzADD5PYmyzkON7PGZgBmbweQJ9DzN9UUpJtiJ1Qj9D27ZLSMbaKUswdtk01DkdAW9f/doeqKdcUNrZkHobMzADM0jJ4H67zNB+w8Fojwp2DIDg54IZmIEZwpNBSo9if2IGZmCGM0V7fwJi41iWGZiBGXzp7U+80DkREREREREREZmOi1JERERERERERGQ6LkoREREREREREZHpzL/QuUHu8no4qh0oKCiAo+QE3KkKrBlJzMAMcZ0hp0c2BmdmIT09HePyRmFH2S4UH94ZdxkiTUItMAMzMIMv9icZ88AMGgn1KGEcmEEjoR4kkDAXzMAMzODLzB4lelFKdXng3F2NhuJKeCoaAABz3p/j/b4l3Q57Tkck9E+FYgvPSV/MwAzSMiQl2DF+2BhMHzEFQ3ue5/36olvnAgC2HbYPCYYAAQAASURBVPoaiwuXYdWW9ah3NsRshkiTUAvMwAzM4Iv9ScY8MINGQj1KGAdm0EioBwkkzAUzMAMz+IpUjxK7KOWuasSp9w5CrXG1+hhPRQMcG79F/RcVaH9dL1jTEpmBGWI6w7ld+mD1PS+jZ6dMeFRPi48Z3D0LCyc/hQdG34NxC6diX3lpzGWINAm1wAzMwAy+2J9kzAMzaCTUo4RxYAaNhHqQQMJcMAMzMIOvSPYokdeUclc1onblAai1rU/K6dRaF2pXHoC7qpEZmCFmM5zbpQ/+cd9byEzrCkVRYLVYW3yc1WKFoijITOuKj+9fgb4ZvWMqQ6RJqAVmYAZm8MX+JGMemEEjoR4ljAMzaCTUgwQS5oIZmIEZfEW6RwW8KNXY2IjHH38cP/rRj3DJJZfg2WefhaqqIQkDaKetnXrvINDoAfQ+rQqgUdtOdbW8qscMzBDNGZIS7Fh9z8tIsbeHzarvBEeb1YYUe3usmbkUSQn2mMjgD/sTMzBDfGZgf5IxD8ygkVCPEsaBGTQS6sGfcPcnQMZcMAMzMIMvCT0q4EWpJ598Ev/+97+xdOlS/OlPf8Lbb7+NFStWBB2kiXN3tXbaWqB9UAXUGhecu6uZgRliLsP4YWPQs1Om7kbRxGa1oVfn7sg/f3RMZPCH/YkZmCE+M7A/yZgHZtBIqEcJ48AMGgn14E+4+xMgYy6YgRmYwZeEHhXQolRVVRVWrVqFJ554Ajk5Obj44otx++23Y9u2bUEHadJQXBnR7ZmBGSRmmD5iSquf7fXH7XFj+ogpMZGhLexPzMAM8ZuB/UnGPDCDRkI9ShgHZtBIqIe2mNGfABlzwQzMwAy+JPSogBaltmzZgg4dOmD48OHer02fPh1z584NOgig3fqw6UrzRnkqGuAur2cGZoiZDDk9sjG053mtfrbXH6vFitxeg5DTIzuqM/jD/sQMzBCfGdifZMwDM2gk1KOEcWAGjYR68Cfc/QmQMRfMwAzM4EtKjwroHK1Dhw6he/fuWLNmDf785z/D6XQiPz8fd999NywWfetbiqKgXUJyi99zVDsCidMqWw2QnOm7jxpFgcoMzBBlGQZnZoUkw6DMAdhz7IDIDLWKEvRzh6I/Aa2PQ7hrAfA/F8zADMzg+5hw9ycg+B7F/hQ/Gcyox2gYB2bQsD9pJBxPMwMzMIMvKe/xAlqUqqurQ2lpKd566y3MnTsX5eXleOSRR5CcnIzbb79d13N0Sk7DqilLWvxeQUEB5rw/J5BILZqRNwn5+fk+Xx+zfAyO1x5HeruOWMsMzBAlGdLT04PePwA8OOJu3DHoRpEZxq8eH/Rzh6I/Aa33qHDXAuB/LpiBGZjBN0O4+xMQfI9if4qfDGbUYzSMAzNo2J80Eo6nmYEZmMGXlPd4AS1K2Ww21NbW4k9/+hO6d+8OACgrK8Obb76pu2mdcFRh7LJpLX7PUXIikDitWrR1OV6t2+Dz9Yq6Su9/mYEZoiXDuLxRWHRr8KdQP134Et7d+qHIDLWOqqCfOxT9CWi9R4W7FgD/c8EMzMAMvhnC3Z+A4HsU+1P8ZDCjHqNhHJhBw/6kkXA8zQzMwAy+pLzHC2hRKiMjA3a73duwAOCcc87B0aNHdT+Hqqqoc7Z8qpo7NfiP8ACAKwUt7qPp1qbMwAzRlGFH2a6QZNhxZJf4DMEIRX9qytJSxnDXQtO+mYEZmCGwDOHuT6dnMIr9KX4ymFmPkseBGTTsTxoJx9PMwAzM4EvKe7yALnQ+dOhQNDQ0YP/+/d6v7du3r1kTC4Y1IwmWdHtQz2FJt8OakcQMzBAzGYoP78S2Q1/D7XEb2t7tcaPo4FfYfqQkqjP4w/7EDMwQnxnYn2TMAzNoJNSjhHFgBo2EevAn3P0JkDEXzMAMzOBLSo8KaFGqb9++uPzyy/HQQw+hpKQEn3zyCRYvXoybb745qBCns+d0jOj2zMAMEjMsLlwGixLQy9XLarFiceGymMjQFvYnZmCG+M3A/iRjHphBI6EeJYwDM2gk1ENbzOhPgIy5YAZmYAZfEnpUwHt/5pln0KtXL9x888144IEHMHnyZNxyyy1BB2mS0D8VSooNCPRsNgVQUmxI6J/KDMwQcxlWbVmPQyfK4HK7AtrO5Xbh4HdHUPBly9dCiLYM/rA/MQMzxGcG9icZ88AMGgn1KGEcmEEjoR78CXd/AmTMBTMwAzP4ktCjAl6USklJwbx587B161b8+9//xsyZM6GE4HbuTRSbBe2v6wUkWvRPjgIgUdtOsRlb5WMGZpCcod7ZgOtfvAM1Dad0NwyX24WahlMYt3Aq6p0NMZHBH/YnZmCG+MzA/iRjHphBI6EeJYwDM2gk1IM/4e5PgIy5YAZmYAZfEnpU8D9FGFjTEtHhhj5QOui7DrvSwYYON/SBNS2RGZghZjPsPX4AV86fiLKqYwDQ6md/m75eVnUMV86fiH3lpTGVIdIk1AIzMAMz+GJ/kjEPzKCRUI8SxoEZNBLqQQIJc8EMzMAMviLdowK6+56ZrGmJSJnUF87d1WgoroSnwncFzpJuhz2no3baWwhWCZmBGaRn2FdeiuFPXov880dj+ogpyO01yOcx2w+XYHHhMhR8uSEsf12TkCHSJNQCMzADM/hif5IxD8ygkVCPEsaBGTQS6kECCXPBDMzADL4i2aPELkoB2ulsidlpSMxOg7u8HrYaYEbeJCzauhyuFAR1pXlmYIZozVDvbMDyzWuwfPMa5PTIxqDMAXhwxN14uvAlfFX2DYoP74yLDJEmoRaYgRmYwRf7k4x5YAaNhHqUMA7MoJFQDxJImAtmYAZm8BWpHiXy43stsWYkITmrI/Lz85Gc1dGUSWEGZpCeofjwTry79UNUVFTg3a0fRuRgRkKGSJNQC8zADMzgi/1Jxjwwg0ZCPUoYB2bQSKgHCSTMBTMwAzP4MrNHRc2iFBERERERERERxQ4uShERERERERERkem4KEVERERERERERKZTVFVVzdiR2+1GUVERRlw+AnWqsSu1K4qC9HYdUVFXCSOx1ToXoAJQAKWdsWu8MwMzMEPoM7RT7Cj8VyFyc3NhtVoNZQhWsD0q2DEAgp8LZmAGZghPhkj3KPYnZmAGZmhNtPcnIDaOZZmBGZjBl97+ZP7d91RAPeUyuimO1x5nBmZghljL0N5ufNtQMzgOIZsHZmAGZpCXQUqPivd5YAZmYAZfUd6fvt80+o9lmYEZmMGXzv5k/qKUAijt43e1kBmYgRlaegJDuw0Pgz0qVv7iygzMwAwtPYmxzUKO/YkZmIEZfJ7E2GYhx/d4zMAMzODzBPoeZvqilJJsReqEfoa2bZeQjLVTlmDssmmoczoC3r76tT1QT7mgtLMh9TZmYAZmkJLB/XaZof2Gg9EeFewYAMHPBTMwAzOEJ4OUHsX+xAzMwAxnivb+BMTGsSwzMAMz+NLbn3ihcyIiIiIiIiIiMh0XpYiIiIiIiIiIyHRclCIiIiIiIiIiItNxUSoA7vJ6OEpOoKCgAI6SE3CX15ueIadHNsbljUJ6ejrG5Y1CTo9sZohQBtaDnAzEemSG5iTUg4QMEuaCWAvM0JyEepCQQcJckEZCPTADM0jLYGaPMv/ue1FGdXng3F2NhuJKeCoaAABz3p/j/b4l3Q57Tkck9E+FYgvPGl9Sgh3jh43B9BFTMLTned6vL7p1LgBg26GvsbhwGVZtWY96ZwMzhDED60FOBmI9MkNzEupBQgYJc0GsBWZoTkI9SMggYS5II6EemIEZpGWIVI/iolQb3FWNOPXeQag1rlYf46logGPjt6j/ogLtr+sFa1piSDOc26UPVt/zMnp2yoRH9bT4mMHds7Bw8lN4YPQ9GLdwKvaVlzJDGDKwHuRkINYjMzQnoR4kZJAwF8RaYIbmJNSDhAwS5oI0EuqBGZhBWoZI9ih+fK8V7qpG1K48ALW29cI4nVrrQu3KA3BXNYYsw7ld+uAf972FzLSuUBQFVou1xcdZLVYoioLMtK74+P4V6JvRmxlCnIH1ICcDsR6ZoTkJ9SAhg4S5INYCMzQnoR4kZJAwF6SRUA/MwAzSMkS6RwW0KFVQUICsrCyffwMHDgxJGClUlwen3jsINHoAVe9GABq17VRXyyuLgUhKsGP1PS8jxd4eNqu+E9psVhtS7O2xZuZSJCXYmSFEGVgPcjK0hf2prY3AeozRDBLqQUIGCXPRFvantjZCzNUCM2gk1IOEDBLmwh/2qLY2QszVJDMww+kk9KiAFqXGjBmDTz/91PvvX//6F3r37o1bb7016CCSOHdXa6fO6S2MJiqg1rjg3F0ddIbxw8agZ6dM3YXRxGa1oVfn7sg/fzQzhCgD60FOhrawP/nBeozJDBLqQUIGCXPRFvYnP2KsFphBI6EeJGSQMBf+sEf5EWM1yQzMcDoJPSqgRamkpCRkZGR4/7333ntQVRX33Xdf0EEkaSiujOj2ADB9xJRWP8vpj9vjxvQRU5ghRBlYD3IytIX9yZztARm1wAwaCfUgIYOEuWgL+5M52wMyaoEZNBLqQUIGCXPhD3uUOdszAzNIzCChRxm+plRVVRWWLFmC3/zmN0hMDO1FtiLJXV7vvdq9UZ6KhqBu25jTIxtDe57X6mc5/bFarMjtNSio2zYyg4b1ICdDINifWsd6jJ0MEupBQgYJcxEI9qfWxUItMINGQj1IyCBhLgLFHtW6WKhJZmCG00npUYbvvvfmm2+iS5cuuOaaawLaTlEUtEtINrTP5ISkZv8NVI2iQPWTwVHtMPTcZ7LVAMmZvvvQk2FwZlZIMgzKHIA9xw4wQxAZWA/mZKhVlJA8fxOj/Qkw3qOC7U+A/7kIdz3qyRDuWmAG/Rkk1IOEDGbMRSh7FPtT26TXAjPoyyChHiRkiLb+BPA9nj/BHNMzAzNIyyDlPZ6hRSlVVfHOO+/gjjvuCHjbTslpWDVliZHder09cYGh7cYsH4PjtceR3q4j1raSoaCgAHPenxNMPADAjLxJyM/PN5QhPT096P0DwIMj7sYdg25khiAysB7MyTB+9fiQPD8QXH8Cgu9RRvsT4H8uwl2PejKEuxaYQX8GCfUgIYMZcxGqHsX+5J/0WmAGfRkk1IOEDNHUnwC+x9MjmGN6ZmAGaRmkvMcztCi1fft2HDt2DNdee23A255wVGHssmlGdovkhCS8PXEBJqy4Fw5n4KepVdRVev/bWgZHyQlD2c60aOtyvFq3wVCGcXmjsOjWuUFneLrwJby79UNmCCID68GcDLWOqqCfu0kw/Qkw3qOC7U+A/7kIdz3qyRDuWmAG/Rkk1IOEDGbMRah6FPuTf9JrgRn0ZZBQDxIyRFN/AvgeT49gjumZgRmkZZDyHs/QotQnn3yCCy64AGeddVbA26qqijpncKeqOZz1hp5DVVW/GdypoTkF1pWCFvehJ8OOsl0hybDjyC5mCDID68HcDKEQTH9qyhJMjzLan5r23VaGcNejngzhrgVm0J9BQj1IyGDmXASL/cm/aKkFZpBfDxIyRFN/AvgeT49gjumZgRmkZZDyHs/Qhc6Li4tx/vnnG9lUPGtGEizp9qCew5JuhzXD+HUbig/vxLZDX8PtcRva3u1xo+jgV9h+pIQZgszAepCTQS/2p7axHmMng4R6kJBBwlzoxf7UtlioBWbQSKgHCRkkzEUg2KPaFgs1yQzMcDopPcrQotTu3bvRr1+/oHYsmT2nY0S3B4DFhctgUYzdHNFqsWJx4TJmCFEG1oOcDHqwP4V3e0BGLTCDRkI9SMggYS70YH8K7/aAjFpgBo2EepCQQcJc6MUeFd7tmYEZJGaQ0KMM7b2iogKpqalB71yqhP6pUFJsQKBn1CmAkmJDQv/gx2bVlvU4dKIMLrcroO1cbhcOfncEBV+2/Nl3Zggc60FOBj3Yn1rBeozJDBLqQUIGCXOhB/tTK2KsFphBI6EeJGSQMBd6sUe1IsZqkhmY4XQSepThj+9ddtllQe9cKsVmQfvregGJFv0FogBI1LZTbMZWGk9X72zA9S/egZqGU7oLxOV2oabhFMYtnIp6ZwMzhCgD60FOBj3Yn1raCKzHGM0goR4kZJAwF3qwP7W0EWKuFphBI6EeJGSQMBd6sUe1tBFiriaZgRlOJ6FHBf9TxChrWiI63NAHSgd914JXOtjQ4YY+sKYlhizD3uMHcOX8iSirOgYArX7Ws+nrZVXHcOX8idhXXsoMIc7AepCTgViPzNCchHqQkEHCXBBrgRmak1APEjJImAvSSKgHZmAGaRki3aMM3X0vXljTEpEyqS+cu6vRUFwJT4XvKqAl3Q57Tkft1LsQrFSeaV95KYY/eS3yzx+N6SOmILfXIJ/HbD9cgsWFy1Dw5Yaw/DWFGTSsBzkZiPXIDM1JqAcJGSTMBbEWmKE5CfUgIYOEuSCNhHpgBmaQliGSPYqLUn4oNgsSs9OQmJ0Gd3k9bDXAjLxJWLR1OVwpCOpq93rVOxuwfPMaLN+8Bjk9sjEocwAeHHE3ni58CV+VfYPiwzuZwaQMrAc5GYj1yAzNSagHCRkkzAWxFpihOQn1ICGDhLkgjYR6YAZmkJYhUj2KH98LgDUjCclZHZGfn4/krI6mFMaZig/vxLtbP0RFRQXe3fphRH55MYOG9SAnA7EemaE5CfUgIYOEuSDWAjM0J6EeJGSQMBekkVAPzMAM0jKY2aO4KEVERERERERERKbjohQREREREREREZmOi1JERERERERERGQ6RVVV1Ywdud1uFBUVYcTlI1CnGrtSu6IoSG/XERV1lTASW61zASoABVDaGbvGOzMwAzOEPkM7xY7CfxUiNzcXVqvVUIZgBdujgh0DIPi5YAZmYIbwZIh0j2J/YgZmYIbWRHt/AmLjWJYZmIEZfOntT+bffU8F1FMuo5vieO1xZmAGZoi1DO3txrcNNYPjELJ5YAZmYAZ5GaT0qHifB2ZgBmbwFeX96ftNo/9YlhmYgRl86exP5i9KKYDSPn5XC5mBGZihpScwtNvwMNijYuUvrszADMzQ0pMY2yzk2J+YgRmYwedJjG0WcnyPxwzMwAw+T6DvYaYvSinJVqRO6Gdo23YJyVg7ZQnGLpuGOqcj4O2rX9sD9ZQLSjsbUm9jBmZgBikZ3G+XGdpvOBjtUcGOARD8XDADMzBDeDJI6VHsT8zADMxwpmjvT0BsHMsyAzMwgy+9/YkXOiciIiIiIiIiItNxUYqIiIjCx+OJdAIiIiLSi7+3yWTmX1OKiIiIYtbQ8npM3lmFi8scyKpsROLzw3HAomBXx0RsykzGG9lp2JaRFOmYREREBP7epsjjolQA3OX1cFQ7UFBQAEfJCbhTFVhNfoFKyCCBhHGQkIGoiYR6lJBBAgnjEIkM51Q1YuHGo7j0qANOBdihAqsA1ABI8agY+F0DfnmiAdO3V+GzbsmYObIb9qclhjUTyRCvrwmJJIwDM5A0EuqBv7c18ToXEjOYiYtSfqguD5y7q9FQXAlPRQMAYM77c7zft6TbYc/piIT+qVBs4fk0pIQMEkgYBwkZiJpIqEcJGSSQMA6RzHDDNyfx4sZv0ehW8SqAF1SgqIXH5arALAA3HHXg87f2Y8bIblg1IDWkWUiGeH9NSCJhHJiBpJFQD/y9rYn3uZCUIVK4KNUGd1UjTr13EGqNq9XHeCoa4Nj4Leq/qED763rBGuLVYwkZJJAwDhIyEDWRUI8SMkggYRwimeGGb05i8UdH8Q2AawCUovULVhYDuB3A4wA+cKtY8lEZFKhYOeCskGQhGeL9NSGJhHFgBpJGQj3w97Ym3udCUoZIiq0lthByVzWiduUBqLWtF8bp1FoXalcegLuqMaYySCBhHCRkIGoioR4lZJBAwjhEMkPfqka8uPFbfAPgEgCHv/96a5dIbfr6YQAXA9gN4MWN3+KcGKuLeBbvrwlJJIwDM5A0EuqBv7c18T4XkjJEWsCLUkePHsWdd96J888/HyNHjsRrr70WhliRpbo8OPXeQaDRA6h6NwLQqG2nuoK/Y4GEDBJIGAcJGUgf9qfWNgJfE2EgYRwinWHBxqNocKu4BkA1ALfO7dzfP34UgEa3ioUbjwaVIxqwP7W2EWLqNSGFhHFghugRD/0JkFEPkc4g5fd2pMeBGWQJeFHqV7/6Fdq1a4eCggLMnj0bzz//PD766KNwZIsY5+5q7dQ5vYXRRAXUGhecu6tjIoMEEsZBQgbSh/2pDXxNhJyEcYhkhqHH63HpUQdWQTv1X++BbRP399utAnDpUQeGltcbzhIN2J/aECOvCUkkjAMzRI946E+AjHrg721NvM+FpAwSBLQodfLkSRQVFeHuu+9Gnz59cNVVV+Gyyy7Dpk2bwpUvIhqKKyO6vZQMEkgYBwkZyD/2J3O2l5JBAgnjEMkMk0uq4FSAF2D8WgAWaNs7FWDyzirDWaRjfzJneykZJJAwDswQHeKlPwEy6oG/tzXxPheSMkgQUD0mJSUhOTkZBQUFcDqd2LdvH7788ktkZ2eHK5/p3OX13qvdG+WpaIA7iJVjCRkkkDAOEjKQPuxP+vA1ERoSxiHSGS4uc2DH93frMXryuAfAVmi3ob7oqMPgs8jH/qRPtL8mpJAwDswQPeKhPwEy6iHSGaT83o70ODCDPAHdfc9ut+ORRx7BE088gddffx1utxv5+fm48cYbdT+Hoihol5AccFAASE5IavbfQNUoClQ/GRzVoTkottUAyZm++4iWDP5wLszL4I8ZcxHuDLWKYmi704WiPwHGxyHYMQD8z0W46zFaMvjDuTAnQ1ZlI1aFJAGwC0D+icYWf04J9RBsj2J/0i+aXxN6cC7iK4M/7E8avq8wJ4MZv7ejYRyYQT+z3uMFtCgFAHv37sUVV1yBX/7yl9i9ezeeeOIJXHzxxbjuuut0bd8pOQ2rpiwJdLfNvD1xgaHtxiwfg+O1x5HeriPWtpKhoKAAc96fE0w8AMCMvEnIz8+P2gx6cS7Cn0GvcM5FuDOMXz0+qP02CbY/AcH3KKNjAPifi3DXY7Rk0ItzEcYMHg8Snx+OmqD3rqkGkOhRsXbSXwBL85O4JdRDKHoU+5M+UfuaCBDnIj4y6MX+pOH7ijBmMOn3tvhxYAZDwv0eL6BFqU2bNmHlypUoLCxEUlIShgwZgmPHjuGll17S3bROOKowdtm0QHbrlZyQhLcnLsCEFffC4Qz8NLWKukrvf1vL4Cg5YSjbmRZtXY5X6zZEbQZ/OBfmZfDHjLkId4ZaR5Wh/Z4uFP0JMN6jgh0DwP9chLseoyWDP5wLczIcsChI8QR6Zc6WpQJotCgYu/zOgDLoEYp6CLZHsT/pF82vCT04F/GVwR/2Jw3fV5iTwYzf29EwDsygn1nv8QJalNqxYwd69+6NpKQfTt8677zz8Oc//1n3c6iqijpncKeqOZz1hp5DVVW/GdypwX+MCABcKWhxH9GSQS/ORfgz6BXOuTArQzBC0Z+asgQzDkbHoGnfbWUIdz1GSwa9OBfhzbCrYyIGfhfctRCaDARQ0ikxrH0yFPVgFPuTftH8mggE5yI+MujF/qTh+4rwZjDj93Y0jAMzBC7c7/ECutB5ly5dUFpaisbGRu/X9u3bhx49egSWTjBrRhIs6fagnsOSboc1w/hnwyVkkEDCOEjIQPqwP+nD10RoSBiHSGfYlJmMwQqQi+Du4pMHYJACfN7N2PUOogH7kz7R/pqQQsI4MEP0iIf+BMioh0hnkPJ7O9LjwAzyBFSPI0eOREJCAh5++GHs378fGzduxJ///Gfccsst4coXEfacjhHdXkoGCSSMg4QM5B/7kznbS8kggYRxiGSGN7LTkKACsxDcXXxmAUhQteeLVexP5mwvJYMEEsaBGaJDvPQnQEY98Pe2Jt7nQlIGCQJalEpJScFrr72G8vJy3HDDDZg7dy7uvvtuTJw4MVz5IiKhfyqUFBsQ6Bl1CqCk2JDQPzUmMkggYRwkZCD/2J/84Gsi5CSMQyQzbMtIwmfdknEDgN4ArAFub/1+u/EAPuuWjG0x8Je+1rA/+REjrwlJJIwDM0SHeOlPgIx64O9tTbzPhaQMEgR85l6/fv3w6quvYsuWLfjoo49w2223QQnB7dwlUWwWtL+uF5Bo0V8gCoBEbTvFZvSESFkZJJAwDhIykD7sT61tBL4mwkDCOEQ6w8yR3ZBoVfA+tIue6j3AtX7/+A8AJFoVzBzZLagc0YD9qbWNEFOvCSkkjAMzRI946E+AjHqIdAYpv7cjPQ7MIEts/BRhYE1LRIcb+kDpoO9a8EoHGzrc0AfWtMSYyiCBhHGQkIGoiYR6lJBBAgnjEMkM+9MSMWNkNwwAsAlA0xVIWju4aPp6j+8f3x/AjJHdsD/G6iKexftrQhIJ48AMJI2EeuDvbU28z4WkDJEW0N334o01LREpk/rCubsaDcWV8FT43q3Akm6HPaejdupdGFYqJWSQQMI4SMhA1ERCPUrIIIGEcYhkhlUDUqFAxYsbv8V2t4pVAF4AsLWFxw6Fdi2K8dD+0jptZDesGhAbp57TD+L9NSGJhHFgBpJGQj3w97Ym3udCUoZI4qKUH4rNgsTsNCRmp8FdXg9bDTAjbxIWbV0OVwpMudq9hAwSSBgHCRmImkioRwkZJJAwDpHMsHLAWdjSJRkLNx7FbUcdmKwAO1RgF4BqaKf8ZwEYrGgXR/00Mxn3XsEzpGJZvL8mJJEwDsxA0kioB/7e1sT7XEjKECmxtcQWZtaMJCRndUR+fj6SszpGpDAkZJBAwjhIyEDUREI9SsgggYRxiESG/WmJuDa/N0ZM6INXB6fBmm5HvkXBdAD5FgXWdDteHZyGERP64GfX9+aCVByJ19eERBLGgRlIGgn1wN/bmnidC4kZzMQzpYiIiChktmUkYVvG2QCAdgnJWDvpLxi7/E7UOR0RTkZERERn4u9tijSeKUVEREThY+GhBhERUdTg720yGSuOiIiIiIiIiIhMp6iqqpqxI5fLhW3btmH0mNFwqL5Xk9dDURR0Sk7DCUcVjMRWHW5ABaAASrKVGZiBGYRkSFbs2LB+A4YOHQqbLTKfKg62RwU7BkDwc8EMzMAM4ckQ6R7F/sQMzMAMrYn2/gTExrEsMzADM/jS259M61wejwcAsGH9BrN2SURRpqlPRHLf7FFE1JpI9Sj2JyLyh/2JiKTy159MO1PK4/HA5XLBYrFAURQzdklEUUJVVXg8HthsNlgi9Dl29igiak2kexT7ExG1hv2JiKTS259MW5QiIiIiIiIiIiJqwgudExERERERERGR6bgoRUREREREREREpuOiFBERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjohQREREREREREZkuqhalCgoKkJWVhXfeecfU/WZlZTX7d9FFF+Hhhx/GqVOnTM0BACdPnsTTTz+NkSNHYujQoRg9ejRee+01eDyesO975MiR3jEYOHAg8vLycNNNN+GTTz4J+75bynDmv82bN0c8x80332xahrq6Ojz//PO45pprkJOTgwsvvBCzZs3C7t27Tdn/yJEjUVBQ4PP1goICjBw50pQM0sR7j4r3/nRmjkj1KPYn9qeWsD+xP7E//SCSPYr9yRf7U+T6EyCjR0noT23l4DFUeHuULSzPGibr1q1Dr1698O677+LGG280dd8LFixAXl4ePB4Pjh49ikceeQTz5s3D448/blqGyspKTJw4EV26dMFTTz2FHj16YPv27XjiiSdw6NAh/P73vw97htmzZ2PMmDHweDw4efIk1qxZgzvvvBMvv/wyLrnkkrDv//QMZzrrrLNM2X9bORISEkzZ96lTpzBp0iTU1dXhwQcfxMCBA1FZWYk33ngDN910E9asWYOePXuakoV+EM89iv3JN8eZzOxR7E90JvYn9qfTc5wpXvoTwB4lEftTZPsTIKNHSehPreXgMVR4Rc2i1HfffYdNmzZhzpw5ePDBB3Ho0CFTJ+Sss85CRkYGAKBr166488478fjjj5u6KPWnP/0JiYmJWLp0Kex2OwCgZ8+eSEpKwowZMzBlyhScc845Yc2QkpLSbBx++9vfory8HHPnzsXatWvDuu+WMkRSJHO8+OKL+O6777B+/XqkpqYCALp37465c+fi6NGjeO2110z7JUaaeO9R7E8t54gU9ic6HfsT+1NLOSIl0hnYo2Rhf4p8fwJk9KhI9wYJOeK1P0XNx/fef/99pKSk4LrrrkOXLl3w7rvvRjRPcnKyqftrbGzEunXrMHnyZG/DanLFFVfgtddeQ/fu3U3N1GTixIn45ptvUFpaGpH9xxuPx4PVq1fjl7/8pbdZnW7evHm4//77I5AsvsVzj2J/oibsTzKxP7E/kYY9Sh72J5n9CWCPMls896eoWZRat24dLr/8clgsFowcORJr1qyBqqoRyXLixAn87W9/w3XXXWfaPg8ePIi6ujoMGTLE53uKouCiiy5CYmKiaXlOd+655wIA9uzZE5H9x5uDBw/ixIkTuOCCC1r8fpcuXZCUlGRyKornHsX+RE3Yn2Rif2J/Ig17lDzsTzL7E8AeZbZ47k9R8fG9o0eP4ssvv8Qvf/lLAMBPf/pTvPnmm9iyZUurkxZq06ZNg9VqhaqqcDgcSEtLw2OPPWbKvgGguroagHY6oTRNmcy6KOCjjz6KJ554otnXMjMzsW7dOlP231aOzz77DO3atQvrfisrKwE0/3z1v//9b9xzzz3e/2/WeLQ0Bi6XS8Spt2aK9x7F/tSchB7F/sT+1IT9if3pdPHcnwA5PYr9ScP+JLc/AXyPdzoeQ4W3R0XFotS6detgt9vx4x//GAAwfPhwnHXWWVi9erVpDevJJ5/E0KFDoaoqKisrsWzZMtx8881Yu3YtOnfuHPb9p6WlAdDuziBNbW0tAKBDhw6m7G/WrFn46U9/2uxrNpv5pdxSDjNO+W06nbPpFxkA5OXlYc2aNQCADz/8EG+++WbYcwAtj4GZ+5ci3nsU+1NzEnoU+xP7UxP2pzQA7E9N4rk/AXJ6FPuThv0pDYDM/gTwPd7peAwV3v1HzaJUfX09hg0b5v2a2+3G+++/j9///vemnMbWtWtX9O7dGwDQp08fDBo0CBdeeCE2bNiAKVOmhH3/vXr1QkpKCr766ivk5OT4fP/uu+/GLbfcYuodXJrs2rULANC/f39T9te5c2fvXERSpHL07t0baWlp2Lp1q7cWkpOTvVnMWCRt0tIYmLl/KeK9R7E/NSehR7E/sT81YX9ifzpdPPcnQE6PYn/SsD/J7U8A3+OZTUp/atqXmT1K/DWl9u/fj6+//hoPP/ww1qxZ4/333HPPoba2Fh999FFEclksFqiqCrfbbcr+bDYbxowZgzfeeAONjY3Nvrdx40Zs3LgRXbp0MSXLmVatWoVBgwbF5O0pJbLZbBg/fjz++te/ev+Ccbpjx45FIFX8Yo9if6IfsD/Jwv7E/kTNsUfJwf4kuz8B7FFmi+f+JP5MqXXr1iEtLQ0TJ05sdqG3AQMG4MUXX8SaNWswduzYsOc4efIkysvLAWifq33llVfgdrsxcuTIsO+7yb333osbb7wRU6dOxb333ouzzz4bmzdvxvz583HrrbeiX79+Yc9QU1OD8vJy7ymuK1euxPr16/HKK6+Efd9nZjhT+/btTbkegQT33nsvtmzZgptuugkzZ87EoEGDUFlZiXfeeQcrV67Ez372s0hHjBvsURr2J98cZ4qXHsX+JAf7k4b9yTfHmeKlPwHsUVKwP2kk9CdARo9if4rf/hQVi1Jjx45t8c4DN998M5566ikcO3YMXbt2DWuOe++91/u/k5OTMXjwYCxZssTUleOMjAy8+eabWLBgAe677z5UVVWhV69emDVrFm6++WZTMsyZMwdz5syBoijo1KkTzjvvPLz22mumfe779Axn+n//7/9hxowZpuWIpOTkZPztb3/DX//6VyxatAilpaVITExETk4OFixYgKuuuirSEeMGe5SG/ck3x5nipUexP8nB/qRhf/LNcaZ46U8Ae5QU7E8aCf0JkNGj2J/itz8paqTuuUlERERERERERHFL/DWliIiIiIiIiIgo9nBRioiIiIiIiIiITMdFKSIiIiIiIiIiMh0XpYiIiIiIiIiIyHRclCIiIiIiIiIiItNxUYqIiIiIiIiIiEzHRSkiIiIiIiIiIjIdF6WIiIiIiIiIiMh0XJSKAdOnT8dDDz3U7Gt///vfkZWVhQULFjT7+qJFi/Dzn/8cAFBdXY3f/e53uOSSS3DRRRfhwQcfRHV1tc/zu1wu/PznP/d5rpZcccUVOHbsWKvfV1UVt99+OwoKCpp9/eTJk/jNb36DvLw8/OQnP8Hrr79ueF8jR45EVlaW998FF1yAWbNm4bvvvmuWY/HixRg5ciTOP/98/OIXv8CePXta3M/jjz+OW265xW8eImqZ0R7VpLW+cfDgQfzyl79EXl4exo4di3/9619+s0yZMgVffvllm495+OGHfXJ99NFHzfpKVlYWZs2aZWhft9xyS7PnycvLw9SpU1FaWtrsca+++iouv/xyDB06FFOnTsWBAweaff+1117DZZddhry8PMyePRsOh6PNPETkKxzHUAsWLPDpF1lZWbjyyivbzGL0GKpJKI7XQnEM9d1332HWrFkYNmwYLr30UsyfPx8ul8tvJiJqLtzv8aqqqnDJJZfg8OHDfrMYPX4qLS3F1KlTkZeXh8svvxwvv/yy33098MADWLt2rc/XH3zwwWb9aejQobjppptQXFzc7HHvvfceRo0ahZycnBa///e//x1XXXUVhg4dinvuuQcnTpzwm4nCi4tSMeCCCy7A9u3bm31t8+bN6NKlCzZv3tzs60VFRRg+fDgA4NFHH0VJSQkWL16MpUuXYu/evXj44Yd9nv+VV15BSUmJ3xylpaVISkpC165dW/y+x+PBk08+ic8++8zne7/5zW9w+PBhrFixArNnz8YzzzyDTz75xPC+Zs+ejU8//RT/93//h7/97W84efIkHnjgAe/333rrLbzyyiv4/e9/j1WrVqFHjx6YNm2az5u6L7/8Em+++abfn52IWme0RwGt942Ghgb88pe/hN1ux9tvv42pU6fif/7nf3wOPE7ncDiwe/du5OTktPqYJUuW4J133vH5+p49e3DFFVfg008/9f578sknDe/r9ttvx6effopPPvkEb7/9NtLS0jBjxgyoqgpAO6B68cUX8fjjj+Pdd99FWloa7rrrLu/3P/jgAyxcuBB/+MMf8Ne//hXbtm3D/PnzW81DRC0LxzFU0+u76d/69euRlpaGW2+9tdUcwRxDNQnV8Vqwx1D33XcfamtrsWLFCvzv//4v1q1bp+uNKBE1F873eCdPnsRdd93VbMG5NUaPnzweD6ZPn46OHTti9erVePzxx/HSSy+1uOB0us8//xwXXXRRi98bPXq0t7euXr0aQ4cOxZ133olTp04BAP773//id7/7HWbMmIF169YhLy8P06ZN836/uLgYv/vd7zBz5kysWLEC1dXVPgt/ZD4uSsWAYcOGYe/evd4XG6A1rKlTp6KoqAj19fXer2/btg3Dhw9HXV0dPvjgAzzyyCMYPHgwBg0ahNmzZ+Mf//gHGhoavI8vLS3F66+/jn79+vnNsWnTJlx88cUtfu/YsWP4xS9+gY0bNyI1NbXZ90pKSvDvf/8bzzzzDAYMGIBrrrkGN9xwQ5ur8W3tCwBSUlKQkZGBrl27Ijs7G//zP/+DTz75BDU1NQCA1atX4/bbb8cVV1yBc845B4899hiqqqqa7bOxsRGPPPIIcnNz/f7sRNQ6Iz0KaLtv/POf/0RlZSXmz5+P/v37Y9y4cbjuuuvw2muvtZrjv//9L3Jzc2Gz2Xy+V1tbi1mzZmHJkiXo1q2bz/f37t2LAQMGICMjw/vvzEx69wUA7dq1Q0ZGBrp06YL+/fvjwQcfxJ49e7Br1y4AQE1NDe6//36MGDECffr0wbRp07B//37vX/Nef/11/OIXv8AVV1yBnJwcPP7441i1ahXPliIKUDiOodq3b9+sV/z1r39Fv3792lyUMnoM1SRUx2tAcMdQjY2N6Ny5Mx599FH069cPF1xwAUaNGoUtW7b4zUVEzYXrPd5///tf5Ofno66uTlcOo8dPFRUVyM7OxmOPPYY+ffpgxIgRuPjii9vsB/v27fP2oJYkJSV5e2vfvn1x//33o76+Hp9//jkAoLy8HDNmzMDPf/5z9OzZE/fccw+qqqqwd+9eAMCyZcswevRojBs3DgMHDsS8efNQWFiIQ4cO6RoLCg8uSsWAIUOGICEhAV999RUA4Ntvv0VZWRluvPFGpKSkeBda9u/fj5MnT+KCCy6AxWLBn//8Z2RnZzd7Lrfb3azxPfLII7j33nvRqVMnvznaOsj56quv0K1bN6xatQopKSnNvvef//wHAwcORM+ePZvt9//9v/9naF8tSU5OhqIo3v//29/+Ftddd533/yuKAlVVvQdcALB48WJkZWXh0ksv1b0fIvJlpEcBbfeNQ4cOoW/fvs2+npWVhaKiolZztNU3Dh8+jIaGBhQUFDTrRU327t2LPn366P6ZjfSo002ePBkTJ04EoC1QLV++HP3790enTp3gdruxfft27zgBQG5uLpxOp66zJIjoB+E8hmrarqCgAA888ECz45AzGT2GahKq47WWBHIMlZiYiGeeeQa9e/cGAOzevRsbN25sdgYsEekTrv706aefYvz48bo+6gsYP37q0qULnn/+eXTo0AGqqmLLli344osv2uwHmzZtavUsqZbYbDYkJiZ6///o0aNx9913AwDq6+vx2muvoXPnzjj33HMBaIt3px8/devWDZmZmdi2bZvufVLocVEqBiQmJmLo0KHej618/vnnGDx4MNq3b48f/ehH3tM7i4qK0L9/f3Ts2BFJSUn4yU9+0uxF/PrrryMrK8t7QLNq1So0NDRgwoQJfjOoqtpmkxk5ciTmzZvX4sHSoUOH0KNHDyxduhQjR47ENddcg7feesvwvs506tQpvPzyy7j88su9B3MXXHABzj77bO9j3nnnHbhcLgwbNgyA9gb0zTff5OmcRCFgpEcBbfeN9PR0lJeXez/OBmgHa5WVla3maOt08IEDB+Ivf/kLevTo4fM9VVWxf/9+fPrppxg1ahSuuuoqPPPMM2hsbDS0rzM1Njbiz3/+s/caCadbuXIlLrjgAqxevRqPPPIIFEVBdXU1Ghoa0KVLF+/jbDYb0tLS8O233+raJxFpwnUM1WTp0qW46KKL2vzYSzDHUEBoj9fOZOQYqsmUKVPws5/9DCkpKZg8ebKu/RHRD8LVn371q19hxowZsFqtunIYPX463ciRIzFp0iTk5eVh1KhRbe5L76K5y+XCG2+8gYSEBJ98mzZtQl5eHhYuXIjZs2ejffv2AIDjx483O34CgM6dO/P4KcJa/lwBRZ0LLrjA27A2b96MCy+8EAAwfPhw/P3vfwfge62W0y1btgwbNmzwfub/u+++w7PPPotXX321zb/sNSkpKUG3bt1w1llnBZy9rq4O//73v+FyufC///u/+Oabb/CHP/wBHTt2bLFp6dnXo48+iieeeAKqqqK+vh4JCQmtXjx927Zt+OMf/4ipU6ciIyMDqqp6/+KYnp4e8M9DRL6C7VFn+slPfoInnngCCxYswF133YVdu3Zh5cqVcDqdLT6+qqoKx44d81n00aOsrAwOhwOJiYl4/vnncfjwYTz55JOor69v8Tp8evb1l7/8Ba+88goA7S95qqrihRde8Om3l1xyCVavXo1Vq1ZhxowZWL16tff0+dMPOJv+f1sLZUTUslAfQzWpra3FunXr8Pzzz7e5/2COocJxvBbMMdTpHn74YZw8eRJPPvkkfv3rX+PPf/5zYD8cEYWtP+kVzPHT6V544QVUVFTgsccew9y5c1s8fvJ4PPjvf/+LOXPmtPo8a9euxQcffABAu76o2+3GQw895F10atK/f38UFBTgn//8Jx588EH06NEDubm5qK+v5/GTQDxTKkacfiG8zZs3exvT8OHDsWPHDjQ2NqKoqAg/+tGPfLZ944038OSTT+Khhx7Cj3/8YwDAU089hfz8fAwYMEDX/gM9Ffx0VqsVbrcbzzzzDIYMGYLx48djwoQJWLFiheF9zZo1C2vWrMG7776Ld955BzfffDNuv/127N69u9njtm7diqlTp+InP/mJ9+OCK1asgNvt9n50hoiCF0yPaknnzp3x3HPP4c0338TQoUPx61//GlOmTPE5KGnStE89b9rO1L17d2zevBlz585FdnY2rr76asyePRtvv/023G63oX3ddNNNWLNmDdasWYOCggL86le/wq9//Wts2rSp2eMyMzNx3nnn4eGHH0a3bt2wZs0a2O12APA5gGpsbPT5GCAR+RfqY6gmn3zyCZKSknDZZZe1uf9gjqHCcbwWzDHU6QYOHIgLL7wQc+bMwT//+U9dd/gioubC1Z/0Cub46XRDhgzBFVdcgYceeghvvfVWi4tAX3/9NXr27Nnqx5QB7YyrpuOnNWvW4LHHHsOzzz7rc1fS9PR0ZGdnY8aMGbj00ku9n8Kx2+08fhKIZ0rFiLy8PBw/fhzbt2/H8ePHcf755wPQVolTUlLwxRdfYM+ePT6r6EuXLsW8efPw29/+Fr/4xS+8X1+3bh2SkpKwbNkyANpf8rdu3Yr3338f69at89n/pk2bcNtttxnK3qVLF5x99tlo166d92vnnHMOPv300xYfr2dfnTt39l7PANAaYWFhofe6DoDWZO+66y5ceuml+NOf/gSLRVujXbduHXbs2OEdQ6fTCbfbjby8PKxbtw6ZmZmGfk6ieGa0R7VlxIgR+Pe//43y8nKkp6fjzTffRPfu3Vt8bDBv+gAgLS2t2f8/99xz0dDQgJMnT/p8pEbPvs4666xmPSo7OxtffPEF3nzzTVx88cX4/PPP0aVLF/Tt2xeAds2Wvn37orKyEmlpabDb7aioqPBeI8HlcqGqqqrVC4MSUetCfQzV5JNPPsEVV1zhPb5oTTDHUOE4XgvmGKq2thb/93//h2uuucb7taaLr1dWVvr9iA8RNReu/qRXMMdPFRUVKCoqwlVXXeX9Wr9+/eB0OlFbW2vo+Kl9+/bN+tOAAQOwc+dOLFu2DPn5+SguLobVasWgQYO8jzn33HO9Fzrv2rUrKioqfHLy+CmyeKZUjGjXrh2ys7OxYsUKDBkyxLvaqygKfvSjH6GgoAB9+vRp9uJfvXo15s2bh4ceeghTp05t9nwffvgh3nvvPe8q9ODBg3HTTTdh8eLFPvt2Op0oLi72uZaAXkOHDsWRI0eaXWR83759Lb65DHZfTWc1fPPNN7j77rtx2WWX4fnnn0dCQoL3Mc888wzWrVvn/dlvuukmDB48GGvWrPH5DDIR6WOkR7Vl7969+MUvfgFVVdGlSxdYLBYUFhZ6T2s/UzAHVZ988gkuvPDCZne227lzJ9LS0lrMa3Rfqqp6e9SSJUua3UnQ7XajpKQE5557LiwWC4YMGdLs7jVFRUWw2WwYOHBgwPslinehPoZqUlxc7H0D2Zpgj2vMPF7TcwzlcDjwP//zP80uGvzVV1/BarXinHPOMbRfongWrv6kVzDHT4cPH8bMmTNx7Ngx79d27NiBTp06tXj8FMj1OE+nqio8Hg8A7Vqczz77bLPvf/XVV94/8g0dOrTZ8dPRo0dx9OhRDB06NOD9UuhwUSqG/OhHP8K6det8VsqHDx+Ojz/+uNlpnVVVVfjDH/6A66+/Htdeey3Ky8u9/9xuN3r37t3sX1JSEs4666wWF4q2bduGAQMGICkpyVDuSy65BOeccw4eeOAB7N27F+vXr/eeLm50XzU1Nd6f5/Dhw1iwYAFKS0txzTXXANDuUtOtWzc89NBDqKys9D62vr4eXbt2bfazn3XWWUhKSkLv3r1bvb07EfkXSI/yp3v37ti7dy9eeOEFHDp0CC+++CK2bNmCW265xeex3377LZxOZ4t31dMjLy8PdrsdDz/8MPbt24fCwkLMmzcPd9xxh+F91dXVefvO0aNH8cYbb2DTpk0YPXo0AGDSpEkoKCjA2rVrsW/fPjz22GOor6/HuHHjvN9funQp/vGPf6C4uBiPPfYYJkyYwNPPiQwK5TEUoJ29uH//fu9ZQq0J9hgqHMdrwRxDZWRk4Kc//SmeeOIJfP311/jvf/+L3/3ud5gyZQo6dOhg6Gckineh7k96BXv8NGTIEAwaNAizZ8/Gnj17UFhYiPnz5+Ouu+7yeWxjY2OzT6q0pr6+3vvzHDt2DOvXr8fatWu9x08TJ07E559/jr/+9a84cOAAXnjhBRQXF3vPEL355pu9H00uKSnBb3/7W1x++eWGf0YKDb7DjiHDhg3DK6+84nOmwPDhw+FwOJo1ss8++wx1dXVYvXo1Vq9e3ezxH3/8cUCnVxtd1W5itVqxePFiPProo8jPz0fHjh3x4IMP4sorrzS8rzlz5ngvkme329GvXz88//zzOP/881FeXo6tW7cCAC6//PJm282dOxf5+fmGfxYial0gPcqfpKQkLFy4EH/4wx/w2muvoX///nj55Zdb/HhtoLcXPlOHDh2wdOlSzJkzB+PHj0f79u1x0003tbgopXdfr7zyivdC5wkJCejduzceeeQR/OxnPwMAXHnllXjsscewcOFCHD16FLm5uXjllVe818y69tprceTIETzyyCNobGzET3/6U9x///2Gf0aieBfqY6iqqiq4XC6kpqa2ud9gj6ECYdYxVNP2v/zlLwEA48aNw29+85vQ/jBEcSRS7/GCPX6yWq1YtGgRnnjiCUycOBHJycm45ZZbcOutt/o8tqioCAMHDvReN7M1GzZswIYNGwBodx4+++yzceedd3qPyQYNGoSFCxfi2WefxZ/+9Cf0798fS5cuRdeuXQFof2j8wx/+gBdeeAEnT57EpZdeiieeeMLwz0ihoain30+biIiIiIiIiIjIBPz4HhERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKbjohQREREREREREZmOi1JERERERERERGQ6LkoREREREREREZHpuChFRERERERERESm46IUERERERERERGZjotSRERERERERERkOi5KERERERERERGR6bgoRUREREREREREpuOiFBERERERERERmY6LUkREREREREREZDouShERERERERERkem4KEVERERERERERKazmbUjj8cDl8sFi8UCRVHM2i0RRQFVVeHxeGCz2WCxRGatnD2KiFoT6R7F/kRErWF/IiKp9PYn0xalXC4Xtm/fbtbuiCgKDRkyBImJiRHZN3sUEfkTqR7F/kRE/rA/EZFU/vqTaYtSTStjo8eMhkNtMPQciqKgU3IaTjiqoKpqwNurDjegAlAAJdnKDMzADEIyJCt2bFi/IWJnSQHB96hgxwAIfi6YgRmYITwZIt2j2J+YgRmYoTXR3p+A2DiWZQZmYAZfevuTaYtSTadzOtQGWCdkGnqOdgnJWDVlCcYum4Y6pyPg7atf2wP1lAtKextSJ/RjBmZgBiEZHG+XAfihT0RCsD0q2DEAgp8LZmAGZghPhkj3KPYnZmAGZmhNtPcnIDaOZZmBGZjBl97+xAudExERERERERGR6bgoRUREREREREQyeDyRTkAmMu3je0REREREREREpxtaXo/JO6twcZkDWZWNSHx+OA5YFOzqmIhNmcl4IzsN2zKSIh2TwoSLUhSwnB7ZGJyZhfT0dIzLG4UdZbtQfHhnpGOZzl1eD0e1AwUFBXCUnIA7VYE1Dpsl64EkYT1q2J80rAeShPWoYX/SsB5ImkjU5DlVjVi48SguPeqAUwF2qMAqADUAUjwqBn7XgF+eaMD07VX4rFsyZo7shv1p4b3LJHuUxsx64KIU6ZKUYMf4YWMwfcQUDO15nvfri26dCwDYduhrLC5chlVb1qPeaezOG9FAdXng3F2NhuJKeCq0n3PO+3O837ek22HP6YiE/qlQbLH76VjWA0nCetSwP2lYDyQJ61HD/qRhPZA0kazJG745iRc3fotGt4pXAbygAkUtPC5XBWYBuOGoA5+/tR8zRnbDqgGpIc3CHqWJVD1wUYr8OrdLH6y+52X07JQJj9ry53sHd8/CwslP4YHR92DcwqnYV15qcsrwc1c14tR7B6HWuFp9jKeiAY6N36L+iwq0v64XrGFeyY8E1gNJwnrUsD9pWA8kCetRw/6kYT2QNJGsyRu+OYnFHx3FNwCuAVCK1i92XQzgdgCPA/jArWLJR2VQoGLlgLNCkoU9ShPJejC8zNfY2Iif/exn2Lx5c0iCkEzndumDf9z3FjLTukJRFFgt1hYfZ7VYoSgKMtO64uP7V6BvRm+Tk4aXu6oRtSsPQK1tvVmdTq11oXblAbirGsOczFzRUg/sT/EhWuox3NifNNFSD+xP8SFa6jHc2J800VIP7E/xI5I12beqES9u/BbfALgEwOHvv97apc2bvn4YwMUAdgN4ceO3OCcEfYI9ShPpHmVoUaqhoQG//vWvsXv37pCEIJmSEuxYfc/LSLG3h82q76Q6m9WGFHt7rJm5FEkJ9jAnNIfq8uDUeweBRg+g6t0IQKO2neqKjbtHREs9sD/Fh2ipx3Bjf9JESz2wP8WHaKnHcGN/0kRLPbA/xY9I1+SCjUfR4FZxDYBqAG6d27m/f/woAI1uFQs3Hg0qB3uUJtL1ABhYlNqzZw8mTJiAgwcPBr1zkm38sDHo2SlTd3E2sVlt6NW5O/LPHx2mZOZy7q7WTufU26yaqIBa44Jzd3VYcpktGuqB/Sl+REM9moH9SRMN9cD+FD+ioR7NwP6kiYZ6YH+KL5GsyaHH63HpUQdWQfvInt4FqSbu77dbBeDSow4MLa83nIU9SiOhRwW8KPWf//wHF154IVasWBH0zkm26SOmtPp5Un/cHjemj5gS4kSR0VBcGdHtpYiGemB/ih/RUI9mYH/SREM9sD/Fj2ioRzOwP2mioR7Yn+JLJGtyckkVnArwAoxfR8gCbXunAkzeWWU4C3uURkKPCvhC55MmTQp6pyRfTo/sZlfcD5TVYkVur0HI6ZEd1be3dZfXe+/AYJSnogHu8vqovpVotNQD+1N8iJZ6DDf2J0201AP7U3yIlnoMN/YnTbTUA/tT/Ih0TV5c5sCOVu6yp5cHwFYAO1TgoqMOQ8/BHqWJdD00Mf3ue4qioF1CsqFtkxOSmv03UDWKApUZdGUYnJll6LnPNChzAPYcO2Aogz9mjIOj2lijO5OtBkjO9N1HtIxDuOuhVlFC8vyhYHQugp0HIPh6iJcM4a5HPRn8MWMcwt2f9GTwJ1bqQUqPkjwPzKBhf9KwP2nYn/SJl/dXEjJE+j1eVmUjVoUkAbALQP6JRp/98D2e/gxS3uMpqqoG+ilKr6ysLLz++uu48MIL/T7W7XajqKgI48ePx6pVoSrFwIwZMwbHjx9Hly5dsH79emZoI0N6ejp69w7+avqlpaWoqKgwlCHc9GQoKCjAnDlzgt7X7NmzkZ+fbyhDuEmoh6a+kJubC6u15bs9BCqQ/gSwR0VThnDXo54MZvCXIdz9SU8GM0ioh1D3KPan2M3A/qRhf9KwP5kjGmpBSoaIvsfzeDBs+HAsBnBn0AmAvwCYDmDLf/4DWH74MCDf4+nPIOU9nulnSp1wVGHssmmGtk1OSMLbExdgwop74XAGflGzirpK73+Zoe0M4/JGYdGtcw3lO93ThS/h3a0fGsrgjxnj4Cg5YSjbmRZtXY5X6zYYyuBPLNRDraMq6OcOFaM9Kth5AIKvh3jJEO561JPBHzPGIdz9SU8Gf2KlHqT0KPYn+RnYnzTsTxr2J33i5f2VhAyRfo93wKIgxWP4nJhmUgE0WhSMXd58iYvv8fRnkPIez/RFKVVVUecM7nQ5h7Pe0HM0nRTGDP4z7CjbFVQ27/Mc2dXiPqJlHNypoTkl2pWCqB4Hs+pBgmDnwug8NO2bGfxnCHc96smgVzjHIdz9SU8GvWKlHiJN8jwwg4b9ScP+pGF/Ckysv7+SkCHS7/F2dUzEwO+Cu5ZTk4EASjol+uyH7/H0Z5DyHs/oRe8pxhUf3olth76G2xPojTo1bo8bRQe/wvYjJSFOZi5rRhIs6fagnsOSbo/qC+ABrAeShfWoYX/SsB5IEtajhv1Jw3ogaSJdk5sykzFYAXIR3N338gAMUoDPuxm7XhN7lCbS9dCEi1LUqsWFy2BRjJWI1WLF4sJlIU4UGfacjhHdXgrWA0nCetSwP2lYDyQJ61HD/qRhPZA0kazJN7LTkKACs6DdRc8ID7TtE1Tt+Yxij9JI6FFBLUrt2rVL90XwKPqs2rIeh06UweV2BbSdy+3Cwe+OoODLlq8BEG0S+qdCSbEBgZ7lqQBKig0J/VPDksts0VYP7E+xLdrqMVzYnzTRVg/sT7Et2uoxXNifNNFWD+xPsS+SNbktIwmfdUvGDQB6Awj00vzW77cbD+CzbsnYFsSZSuxRGgk9imdKUavqnQ24/sU7UNNwSneRutwu1DScwriFU1HvDM3nhSNNsVnQ/rpeQKJFf9NSACRq2ym22HiZsR5IEtajhv1Jw3ogSViPGvYnDeuBpIl0Tc4c2Q2JVgXvQ7tYud6FKev3j/8AQKJVwcyR3YLKwR6liXQ9AFyUIj/2Hj+AK+dPRFnVMQBo9fOmTV8vqzqGK+dPxL7yUtMymsGalogON/SB0kHfvQGUDjZ0uKEPrGmJYU5mLtYDScJ61LA/aVgPJAnrUcP+pGE9kDSRrMn9aYmYMbIbBgDYBKDH919vbWGi6es9vn98fwAzRnbD/hD0CfYoTaR7lOl336Pos6+8FMOfvBb554/G9BFTkNtrkM9jth8uweLCZSj4ckPM/kXHmpaIlEl94dxdjYbiSngqfH9OS7od9pyO2umgMbJ6fibWA0nCetSwP2lYDyQJ61HD/qRhPZA0kazJVQNSoUDFixu/xXa3ilUAXgCwtYXHDoV2Danx0M6QmjayG1YNCN1H59ijNJGsBy5KkS71zgYs37wGyzevQU6PbAzKHIAHR9yNpwtfwldl36D48M5IRzSFYrMgMTsNidlpcJfXw1YDzMibhEVbl8OVgqi/A4NerAeShPWoYX/SsB5IEtajhv1Jw3ogaSJZkysHnIUtXZKxcONR3HbUgckKsEMFdgGohvZRvSwAgxXtouafZibj3itCc4bUmdijNJGqBy5KUcCKD+/EnmMHcMegG/Hu1g9R53REOlJEWDOSkJyZjPz8fLxatyFux4H1QJKwHjXsTxrWA0nCetSwP2lYDyRNJGpyf1oirs3vjaHl9Zi8swoXHXUg/0QjEj0qGi0KSjol4tVuyXgjOy2oi5oHgj1KY2Y9cFGKiIiIiIiIiCJiW0YStmWcDQBol5CMtZP+grHL74zbBaF4E5sfiCQiIiIiIiKi6GPhMkU84WwTEREREREREZHpFFVVVTN25Ha7UVRUhBGXj0CdauxK7YqiIL1dR1TUVcJIbLXOBagAFEBpZ+yTi8zADMwQ+gztFDsK/1WI3NxcWK1WQxmCFWyPCnYMgODnghmYgRnCkyHSPYr9iRmYgRlaE+39CYiNY1lmYAZm8KW3P5l/TSkVUE+5jG6K47XHmYEZmCHWMrS3G9821AyOQ8jmgRmYgRnkZZDSo+J9HpiBGZjBV5T3p+83jf5jWWZgBmbwpbM/mb8opQBK+/hdLWQGZmCGlp7A0G7Dw2CPipW/uDIDMzBDS09ibLOQY39iBmZgBp8nMbZZyPE9HjMwAzP4PIG+h5m+KKUkW5E6oZ+hbdslJGPtlCUYu2yaoSvxV7+2B+opF5R2NqTexgzMwAxSMrjfLjO033Aw2qOCHQMg+LlgBmZghvBkkNKj2J+YgRmY4UzR3p+A2DiWZQZmYAZfevsTL3RORERERERERESm46IUERERUazzeCKdgIiIiMiH+deUIiIiIqKwGlpej8k7q3BxmQNZlY1IfH44DlgU7OqYiE2ZyXgjOw3bMpIiHZOIiIjiHBelKCrl9MjG4MwspKenY1zeKOwo24XiwzuZIU4zEEki4TXBDHIymO2cqkYs3HgUlx51wKkACUNzgasHAikpSKypwZCSEgzcVoTp26vwWbdkzBzZDfvTEiMdm0wi4TXBDHIySMBxoNO5y+vhqHagoKAAjpITcKcqsJr8BxQJNRlvGbgoRVEjKcGO8cPGYPqIKRja8zzv1xfdOhcAsO3Q11hcuAyrtqxHvbOBGWI8A5EkEl4TzCAnQ6Tc8M1JvLjxW1gT7cBttyFh1iwgL8/ncQlbtwIvvIALV7yFz9/ajxkju2HVgNQIJCYzSHhNMIOcDBJwHOh0qssD5+5qNBRXwlOhzfec9+d4v29Jt8Oe0xEJ/VOh2MJz9SEJNRnPGXhNKYoK53bpg/88vA4LJz+Fwd2zWnzM4O5ZWDj5Kfzn4XXom9GbGWI4A5EkEl4TzCAnQ6Tc8M1JLP7oKBL69oPt653AK68AOTktPzgnB3jlFdi+3omEc87Fko/KcMM3J80NTKaQ8JpgBjkZJOA40OncVY2oWb4Pjo3fehekzuSpaIBj47eoWb4P7qrGkGeQUJPxniGgRaljx45h1qxZGD58OC677DLMnTsXDQ1cvabwOrdLH/zjvreQmdYViqLAarG2+DirxQpFUZCZ1hUf378ipC8UZpCToS3sUWQ2Ca8JZpCToS3h7E99qxrx4sZvgf79Yfn8c6B7d0BRAGvLYwCrVft+9+6wbN4M9OuHFzd+i3PCcLBPkSPhNcEMcjK0xazjJ+njQOZyVzWiduUBqLUuXY9Xa12oXXkgpAtTEmqSGQJYlFJVFbNmzYLD4cAbb7yB5557Dv/85z/x/PPPhyQIUUuSEuxYfc/LSLG3h82q79OmNqsNKfb2WDNzKZIS7MwQQxnawh5FZpPwmmAGORnaEu7+tGDjUVgS7bB8+CGQkgIkJOjbMCEBSEmB5aOPYE20Y+HGoyHJQ5En4TXBDHIytMWs4yfp40DmUl0enHrvINDoAVS9GwFo1LZTXcHfUVZCTTKDRvei1L59+1BUVIS5c+eif//+uOCCCzBr1iz8/e9/DzoEUWvGDxuDnp0ydb9AmtisNvTq3B35549mhhjK0Bb2KDKbhNcEM8jJ0JZw9qehx+tx6VEHEibeBPTurX9BqklCAtCnD2wTJuLSow4MLa8POhNFnoTXBDPIydAWs46fpI8Dmcu5uxpqjUv/glQTFVBrXHDurg46g4SaZAaN7kWpjIwMvPzyy0hPT2/29dra2qBDELVm+ogp8KjGVsLdHjemj5jCDDGUoS3sUWQ2Ca8JZpCToS3h7E+TS6rgVADMmgV4DP7l2O0G7r0XTgWYvLMq6EwUeRJeE8wgJ0NbzDp+kj4OZK6G4sqIbg/IqElm0OhelEpNTcVll13m/f8ejwfLli3DRRddFHQIopbk9MjG0J7ntfqZVn+sFityew1CTo9sZoiBDP6wR5GZJLwmmEFOBn/C2Z8uLnMgYWiudpe91q4h5Y/VCgwbhoShubjoqCPoTBRZEl4TzCAngz9mHD9FwziQedzl9a1e1FwvT0UD3EGc2SuhJpnhB4Gdo3Wa+fPn4+uvv8bKlSsD2k5RFLRLSDa0z+SEpGb/DVSNokBlhqjJMDiz5av+B2pQ5gDsOXaAGQRnqFWUkDz/6czuUcG+JoDgX5vMYF6GcL8mmEFWhlD3qFD2p6zKRuDqgaEJlpWFgcXbWhznaHhdMoMmXl6XzKCR3J+aSDiW9Sde3l9JyOCoDs0fP2w1QHKmsd9XEmoyHjLo7U+KqqqBfpIT8+fPx6uvvornnnsOo0aN0rWN2+1GUVERxo8fj1WrVgW6y5AYM2YMjh8/ji5dumD9+vXMIDxDeno6evcO/or+paWlqKioYAbBGZr6Qm5uLqxG/9J/GvYoZgh3hnC/JphBVoZQ9qiQ9iePB8OGDwemTQMWLw4qFwBg+nRgyRJs+c9/AEvzk+mj4XXJDJp4eV0yg0ZsfzqNhGPZcGMG/RkKCgowZ86coPc1e/Zs5OfnG8ogoSbjIYPe/hTwmVJPPPEE3nzzTcyfP193szrdCUcVxi6bFvB2gLZi+/bEBZiw4l44nIGfrldRV+n9LzPIzzAubxQW3TrXUL7TPV34Et7d+iEzCM5Q66gK+rmbRKpHBfuaAIJ/bTKDeRnC/ZpgBlkZQtWjwtGfDlgUJNbUhCQfqqvRaFEwdvmdPt+KhtclM2ji5XXJDBrJ/amJhGNZf+Ll/ZWEDI6SE4aynWnR1uV4tW6DoQwSajIeMujtTwEtSi1cuBBvvfUWnn32WVxzzTWBbOqlqirqnMGdsudw1ht6jqaTwpghOjLsKNsVVDbv8xzZ1eI+mEFehmBJ6FFGXxNN+2aG6MgQ7tcEM8jMEIxw9addHRMxpKQk6HwAgJISlHRKNPy7Qo9Y7w0SMsTb65IZ5PanJhKOZfWK9fdXEjK4U0PzkVNXCsS/t2EGff1J94XO9+7di0WLFmHatGkYNmwYysvLvf+IwqH48E5sO/Q13B63oe3dHjeKDn6F7UeMH6wzg5wM/rBHkZkkvCaYQU4Gf8LZnzZlJsO5rQjYulW7i54RbjewZQucxdvweTdj1yEhOSS8JphBTgZ/zDh+ioZxIPNYM5JgSbcH9RyWdDusGcavzSehJpnhB7oXpT7++GO43W689NJL+PGPf9zsH1G4LC5cBouiu0ybsVqsWFy4jBliKENb2KPIbBJeE8wgJ0Nbwtmf3shOQ4IK4IUXfK4DpZvVCixYgARVez6KfhJeE8wgJ0NbzDp+kj4OZC57TseIbg/IqElm0Oje+/Tp07Fr164W/xGFy6ot63HoRBlcbldA27ncLhz87ggKvvT9nDEzRG+GtrBHkdkkvCaYQU6GtoSzP23LSMJn3ZLhWvEWUFoKOJ2BPYHTCRw4ANfbK/BZt2RsC+IvzySHhNcEM8jJ0Bazjp+kjwOZK6F/KpQUGxDoJ/kUQEmxIaF/atAZJNQkM2gM/kmNyBz1zgZc/+IdqGk4pfuF4nK7UNNwCuMWTkW9s4EZYigDkSQSXhPMICdDJM0c2Q3uxgZ4fvpToKZG/8KU0wnU1MBz9dVwNzZg5shu4Q1KppHwmmAGORkk4DjQ6RSbBe2v6wUkWvQvTCkAErXtFFvwyxgSapIZNFyUIvH2Hj+AK+dPRFnVMQBo9TOvTV8vqzqGK+dPxL7yUmaIwQxEkkh4TTCDnAyRsj8tETNGdgN274bnwguBI0e0b7R2jammrx85oj1+zx7MGNkN+9MSzQlMppDwmmAGORkk4DjQ6axpiehwQx8oHfTde03pYEOHG/rAGsLfVRJqkhkCvPse/X/2zj08ivLs/9/Z3WRzIDFgAiUcq0CIQEjEotZaFGsRLIpBxSJaD4CKQPv21RYttVoVVFrrTzlUDh5axBMJIAU8UvPWVqliQkABQc4EIZHEJGST7GF+f4wbE3aT3Z3dmb03+/1cFxftZmfmw30/z9eZJ7OzJFrsqzyIkY9cicJzx2L6qCnI7zvE5z3bj+zC0pKVKP50kyG/TaGDHAdCJCFhTtBBjkO0KBqUDgUqFm3+EtZzcmG7fhIwaxYwYoTvm8vKgGeegeu1V+FubsKMy7NRNCj8j0IQeUiYE3SQ4yAB1oG0xpqRiLTJZ8G5pxZN5dXwVPn225Jphz2vq/aRvwjcIXU6EsZkvDtwUYrEDI3OJqzashartqxFXu9cDMkehDmj7sJjJUvwWcUXKD+ykw5x5ECIJCTMCTrIcYgWqwedga3dk7Fw8zFc9OKLcP7tRSQMzwdycoD0dKC2Fti9G85tZUhQgY+ykzHr0u/zDqlOjoQ5QQc5DhJgHUhrFJsFibkZSMzNgLuyEbY6YEbBZCwuXQVXGsL6lr1gkTAm49mBi1IkJik/shN7jx/A1CHXYV3p22hwOugQxw6ESELCnKCDHAez2Z+RiCsL+2F4ZSNu3FmDC47sxODybUj0qGi2KNjVLREfDc3AS7kZfKh5HCJhTtBBjoMEWAfSGmtWEpKzk1FYWIjnGzbF7dyMNwcuShFCCCGEdDK2ZSVhW9b3AAApCclYP/lZjF91By/4CCGEECIKPuicEEIIIaSzY+EpHyGEEELkwTMUQgghhBBCCCGEEGI6iqqqqhkHcrvdKCsrw6hLRqFB1fekdkVRkJnSFVUN1dCjrTa4ABWAAigp+j65SAc60CHyDimKHSXvlyA/Px9Wq1WXQ7iEm1Hh1gAIvxd0oAMdjHGIdkYxn+hABzq0R6znE9A5zmXpQAc6+BJsPpn/TCkVUE+59G6KE/Un6EAHOnQ2h1S7/m0jjc46RKwPdKADHeQ5SMmoeO8DHehAB19iPJ++3TT2z2XpQAc6+BJkPpm/KKUASmr8rhbSgQ508LcDXYc1Bp0Z1Vl+40oHOtDB3070bRZxmE90oAMdfHaib7OIw2s8OtCBDj47CO5tpi9KKclWpF8/QNe2KQnJWD9lGcavnKbr22NqX9gL9ZQLSooN6bfQgQ50kOLgfq1C13GNQG9GhVsDIPxe0IEOdDDGQUpGMZ/oQAc6nE6s5xPQOc5l6UAHOvgSbD7xQeeEEEIIIYQQQgghxHS4KEUIIZHC44m2ASGEEEIIIYTEDOY/U4oQQjoJwysbcePOGlxY4UBOdTMSnxqJAxYFu7sm4sPsZLyUm4FtWUnR1iSEEEIIIYQQkXBRKgTyeudiaHYOMjMzMaFgDHZU7Eb5kZ1x5+CubISj1oHi4mI4dp2EO12B1eQLbwl1oIMcB7P5fk0zFm4+houOOeBUgB0qUASgDkCaR8Xgr5tw68kmTN9eg3/3TMbM0T2xPyPRUCcJ85IOGhLmBB3kOEQbCTWQ4CAhGyQ4SOgFHeQ4SEBCHSQ4SMgHOmhIGA/x5sBFqQAkJdgxccQ4TB81BcP7nNPy+uKb5wMAth3+HEtLVqJo60Y0Ops6rYPq8sC5pxZN5dXwVGnHmPfmvJafWzLtsOd1RcLAdCg2Yz4VKqEOdJDjEC2u/eIbLNr8FZrdKp4H8LQKlPl5X74KzAZw7TEHPnplP2aM7omiQekRdZEwL+mgIWFO0EGOQ7SRUAMJDhKyQYKDhF7QQY6DBCTUQYKDhHygg4aE8RDPDoqq+/tHQ8PtdqOsrAyXjB0N6/XZuvYRsSfQpwb3BPqzu/fHmruXo0+3bHhUD6wWq8973B43LIoFh09WYMLC27Gv8mCnc3DXNOPUG4eg1rkCvldJsyH1qr6wBrgrJBbrQAfjHNyvVeD9TZuRn58Pq9V3f2YQTEZd+8U3WPrOMXwB4AoAB6E9mM/fk6S8r/cD8BaAgQCmX94Tqwed0a5DKL0wYl7SQZ+DEXOCDrIcop1RoZxDdeY+xFo2SHCQ0As6GOsQS/kEdN5z2Vi8vqKDhoTx0Fkdgs2nkJcaDx48iNtvvx0FBQW45JJLsHz58lB3EROc3b0/3r3nFWRn9ICiKH6bAgBWixWKoiA7owfeu/dVnJXVr1M5uGuaUb/6ANT6wEEBAGq9C/WrD8Bd0xwxBwl1oIMch44wMp/OqmnGos1f4QsAPwRw5NvX23u0uff1IwAuBLAHwKLNX+H7EZgbEuYlHTQkzAk6yHHoCDPOnyTUQIKDhGyQ4CChF3SQ49ARZl3fSaiDBAcJ+UAHDQnjgQ4hLkp5PB5Mnz4dXbt2xZo1a/DQQw9hyZIlWL9+fURkpJCUYMeau5cjzZ4KmzW4TzjarDak2VOxduYKJCXYO4WD6vLg1BuHgGYPEOz9dCqAZm071RX+N5FJqAMd5Dh0hNH59MzmY2hyq7gCQC0Ad5Dbub99/xgAzW4VCzcfC8tDwrykg4aEOUEHOQ4dYcb5k4QaSHCQkA0SHCT0gg5yHDrCrOs7CXWQ4CAhH+igIWE80EEjpEWpqqoq5Obm4sEHH0T//v0xatQoXHjhhdi6dWvYIpKYOGIc+nTLDropXmxWG/qe2QuF547tFA7OPbXarZShfsBTBdQ6F5x7asN2kFAHOshx6Agj82n4iUZcdMyBImgf2Qt2QcqL+9vtigBcdMyB4ZWNul0kzEs6aEiYE3SQ49ARZpw/SaiBBAcJ2SDBQUIv6CDHoSPMur6TUAcJDhLygQ4aEsYDHTRCWpTq3r07nnrqKXTp0gWqqmLr1q34+OOPMXLkyLBFJDF91BR4VH2rr26PG9NHTekUDk3l1VHdHpBRBzrIcegII/Ppxl01cCrA09DxmedvsUDb3qkAN+6s0e0iYV7SQUPCnKCDHIeOMOP8SUINJDhIyAYJDhJ6QQc5Dh1h1vWdhDpIcJCQD3TQkDAe6KCh+/H1o0ePxuTJk1FQUIAxY8aELSKFvN65GN7nnHY/RxkIq8WK/L5DkNc7N6Yd3JWNLd9+oBdPVRPcYdwRIqEOdJDjEAqRzqcLKxzY8e237Om9WdgDoBTADhW44FjoX9QAyJiXdNCQMCfoIMchFIw4f5JQAwkOErJBgoOEXtBBjkMoGHV9J6EOEhwk5AMdNCSMBzp8R2j3aLXi6aefRlVVFR588EHMnz8fc+fODWo7RVGQkpCs65jJCUlt/g6VOkWBGsBhaHaOrn2fzpDsQdh7/EDMOjhq9V00n46tDkjO9j1GrNSBDuY41CtKRPbvRW8+Af7rkFPdjKIIue0GUHiy2W+tA/XC6HlJh+AdjJ4TdJDlEMmMinQ+AfHTh1jIBgkOEnpBB/McpOcTEB/nsrFyfUUHDQnjIR4cgs0nRVXVUD/J2YY333wT99xzDz799FMkJrb/9YzerwudOHEiiooidXkXGuPGjcOJEyfQvXt3bNy40e97MjMz0a9f+E+RP3jwIKqqqmLWobi4GPPmzQvb4f7770dhYaEuBwl1oIM5Dt5ciPTXGQebT0AHGeXxYMTIkVgK4I4IOD0LYDqArf/9L2Bpe7NqoF4YPS/pELyD0XOCDrIcjMioiOTTt8RLH2IhGyQ4SOgFHcxzkJ5PQHycy8bK9RUdNCSMh3hwCDafQrpTqqqqCmVlZfjJT37S8tqAAQPgdDpRX1+Pbt26BdzHSUcNxq+cFsphW0hOSMJrk57B9a/OgsMZ+u16VQ3VLX+35zChYAwW3zxfl19rHitZgnWlb8esg2PXybCPDwCLS1fh+YZNuhwk1IEO5jjUO2rC3nck8gnwn1EHLArSPGGt37eQDqDZomD8Kt8lrkC9MHpe0iF4B6PnBB1kOYSbUUbmExA/fYiFbJDgIKEXdDDPQXo+AfFxLhsr11d00JAwHuLBIdh8CmlR6siRI5g5cyZKSkrQo0cPAMCOHTvQrVu3oANLVVU0OMO7Zc/hbNS1D+9NYR057KjYHZZby36O7vZ7jFhxcKdH5lZgVxpiug50MNchHCKRT16X0x13d03E4K/D++y7l8EAdnVL1NULo+clHYJ3MHpO0EGmg16MzCcg/vogORskOEjoBR3Md9CL0fkExNe5rPTrKzpoSBgP8eQQiJAedD5s2DAMGTIE999/P/bu3YuSkhIsWLAAd955Zyi7EU35kZ3YdvhzuD2hfum7htvjRtmhz7D96K6YdrBmJcGSade9PQBYMu2wZul7/hcgow50kOMQCCPz6cPsZAxVgHyE9+17BQCGKMBHPfU9V0/CvKSDhoQ5QQc5DoEw+vxJQg0kOEjIBgkOEnpBBzkOgTDj+k5CHSQ4SMgHOmhIGA90+I6Qrq+sVisWL16M5ORkTJo0Cb/73e9w00034eabbw5LQhpLS1bCoui79LRarFhasrJTONjzukZ1e0BGHeggx6HDYxiYTy/lZiBBBWYjvG/fmw0gQdX2pxcJ85IOGhLmBB3kOHR4DBPOnyTUQIKDhGyQ4CChF3SQ49DhMUy6vpNQBwkOEvKBDhoSxgMdNEI+eo8ePbBw4UJs3boVH3zwAe68804oEf7mrGhTtHUjDp+sgMvtCmk7l9uFQ18fRfGn/p8BEGsOCQPToaTZgFDbqwBKmg0JA9PDdpBQBzrIcQiEUfm0LSsJ/+6ZjGsB9AMQ6mNErd9uNxHAv3smY1sYv9mRMC/poCFhTtBBjkMgjD5/klADCQ4SskGCg4Re0EGOQyDMuL6TUAcJDhLygQ4aEsYDHTT0fhKlU9PobMI1i6airulU0M1xuV2oazqFCQtvR6Mz/GfPSHBQbBakXtUXSLQEHxgKgERtO8UW/vCSUAc6yHGIJjNH90SiVcGb0B5WHuzClPXb978FINGqYObonmF5SJiXdNCQMCfoIMch2kiogQQHCdkgwUFCL+ggx0ECEuogwUFCPtBBQ8J4oIMGF6Xa4csTB3DZgkmoqDkOAO1+ztL7ekXNcVy2YBL2VR7sVA7WjER0ubY/lC7BPRNf6WJDl2v7w5rR8dfHhoKEOtBBjkO02J+RiBmje2IQgA8B9P729fZC1Pt672/fPxDAjNE9sT8Cc0PCvKSDhoQ5QQc5DtFGQg0kOEjIBgkOEnpBBzkOEpBQBwkOEvKBDhoSxgMdQvz2vXhjX+VBjHzkShSeOxbTR01Bft8hPu/ZfmQXlpasRPGnmwz5TYYEB2tGItImnwXnnlo0lVfDU+V7DEumHfa8rtqtmBFYuT4dCXWggxyHaFE0KB0KVCza/BW2u1UUAXgaQKmf9w6H9gypidDukJo2uieKBoV/q7EXCfOSDhoS5gQd5DhEGwk1kOAgIRskOEjoBR3kOEhAQh0kOEjIBzpoSBgP8e7ARakANDqbsGrLWqzashZ5vXMxJHsQ5oy6C4+VLMFnFV+g/MjOuHBQbBYk5mYgMTcD7spG2OqAGQWTsbh0FVxpCOvbD4JFQh3oIMchWqwedAa2dk/Gws3HcMsxB25UgB0qsBtALbSP6uUAGKpoDzX/IDsZsy6NzB1SpyNhXtJBQ8KcoIMch2gjoQYSHCRkgwQHCb2ggxwHCUiogwQHCflABw0J4yGeHbgoFQLlR3Zi7/EDmDrkOqwrfRsNTkdcOlizkpCcnYzCwkI837ApbutABzkOZrM/IxFXFvbD8MpG3LizBhccc6DwZDMSPSqaLQp2dUvE8z2T8VJuRlgPNQ8FCfOSDhoS5gQd5DhEGwk1kOAgIRskOEjoBR3kOEhAQh0kOEjIBzpoSBgP8ebARSlCCNHJtqwkbMv6HgAgJSEZ6yc/i/Gr7ojbE0tCCCGEEEIICQU+6JwQQiKFhZFKCCGEEEIIIcHCKyhCCCGEEEIIIYQQYjqKqqqqGQdyu90oKyvDqEtGoUHV96R2RVGQmdIVVQ3V0KOtNrgAFYACKCn6PrlIBzrQIfIOKYodJe+XID8/H1arVZdDuISbUeHWAAi/F3SgAx2McYh2RjGf6EAHOrRHrOcT0DnOZelABzr4Emw+mf9MKRVQT7n0booT9SfoQAc6dDaHVLv+bSONzjpErA90oAMd5DlIyah47wMd6EAHX2I8n77dNPbPZelABzr4EmQ+mb8opQBKavyuFtKBDnTwtwNdhzUGnRnVWX7jSgc60MHfTvRtFnGYT3SgAx18dqJvs4jDazw60IEOPjsI7m2mL0opyVakXz9A17YpCclYP2UZxq+cpuvbrWpf2Av1lAtKig3pt9CBDnSQ4uB+rULXcY1Ab0aFWwMg/F7QgQ50MMZBSkYxn+hABzqcTqznE9A5zmXpQAc6+BJsPvFB54QQQgghhBBCCCHEdLgoRQghhBBCCCGEEEJMh4tShBBCCCGEEEIIIcR0YmZRyl3ZCMeukyguLoZj10m4KxtNd8jrnYsJBWOQmZmJCQVjkNc713QHCXWQ4CChFxIc2AsZSOgDHeQ4SJgTEhzYCxlIqAHHggbrIMeBvZCDhDpwPGhIqIMEB/ZCw8w6mP/teyGgujxw7qlFU3k1PFVNAIB5b85r+bkl0w57XlckDEyHYjNmfS0pwY6JI8Zh+qgpGN7nnJbXF988HwCw7fDnWFqyEkVbN6LR2WSIg4Q6SHCQ0AsJDuyFDCT0gQ5yHCTMCQkO7IUMJNSAY0GDdZDjwF7IQUIdOB40JNRBggN7oRGtOiiq7u8fDQ23242ysjJcMnY0rNdnB35/TTNOvXEIap0r4HuVNBtSr+oLa0Zih+9reQJ9anBPoD+7e3+suXs5+nTLhkf1wGqx+np63LAoFhw+WYEJC2/HvsqDEXWQUAcJDhJ6IcGhs/bC/VoF3t+0Gfn5+bBaffdnBqFklBF9AELrBR3kOBgxJ2LRoTP3ItoZFUo+cSxosA4aEuogwaEz9yKW8gng+bQX1kGOA3uhEc1rPJEf33PXNKN+9QGo9YGbAgBqvQv1qw/AXdMcMYezu/fHu/e8guyMHlAUxW9TAMBqsUJRFGRn9MB7976Ks7L6RcxBQh0kOEjohQQH9kIGEvpABzkOEuaEBAf2QgYSasCxoME6yHFgL+QgoQ4cDxoS6iDBgb3QiHYddC9KTZ8+HXPmzImIRGtUlwen3jgENHuAYO/hUgE0a9upLk/YDkkJdqy5eznS7KmwWYP7hKPNakOaPRVrZ65AUoI9bAcJdZDgIKEXEhzYi9AxIqMk9IEOchwkzAkJDuxF6BiRTxJqwLGgwTrIcWAvQseoazwJdeB40JBQBwkO7IWGhDroWpTasGEDSkpKwj64P5x7arXb1kL9UKEKqHUuOPfUhu0wccQ49OmWHXRTvNisNvQ9sxcKzx0btoOEOkhwkNALCQ7sRWgYlVES+kAHOQ4S5oQEB/YiNIzKJwk14FjQYB3kOLAXoWHkNZ6EOnA8aEiogwQH9kJDQh1CXpSqqanBE088gWHDhoV9cH80lVdHdXsAmD5qCjyqvlVHt8eN6aOmhO0goQ4SHCT0QoIDexE8RmaUhD7QQY6DhDkhwYG9CB4j80lCDTgWNFgHOQ7sRfAYfY0noQ4cDxoS6iDBgb3QkFCHkBelHn/8cVx99dUYMCDww7JCxV3Z2PKkeb14qprC+srEvN65GN7nnHY/RxkIq8WK/L5DwvrKRAl1kOAgoRcSHNiL0DAqoyT0gQ5yHCTMCQkO7EVoGJVPEmrAsaDBOshxYC9Cw8hrPAl14HjQkFAHCQ7shYaEOgBASPdoffjhh/jkk0+wfv16PPjgg7oOqCgKUhKS/f7MUevQtc/TsdUBydm+x6hTFKgBHIZm50TEYUj2IOw9fkCXg4Q6SHCQ0AsJDvHQi3pFicj+jcwoo/sABO4FHeQ4GD0nYsUhXnoRiYwyMp84FjRYBw0JdZDgEC+9kJ5PAM+nvbAOchzYCw0p13hBL0o1NTXhD3/4Ax544AEkJSUFLXg63ZIzUDRlmd+fFRcXY96b83Tv28uMgskoLCz0eX3cqnE4UX8CmSldsb4dh8zMzLCPDwBzRt2FqUOu0+UgoQ4SHCT0QoJDPPRi4pqJYe/b6Iwyug9A4F7QQY6D0XMiVhzipRfhZpTR+cSxoME6aEiogwSHeOmF9HwCeD7thXWQ48BeaEi5xgt6UWrhwoUYOnQoLr744uDt/HDSUYPxK6f5/Zlj18mw9u1lcekqPN+wyef1qobqlr/bc5hQMAaLb54ftsNjJUuwrvRtXQ4S6iDBQUIvJDjEQy/qHTVh79vojDK6D0DgXtBBjoPRcyJWHOKlF+FmlNH5xLGgwTpoSKiDBId46YX0fAJ4Pu2FdZDjwF5oSLnGC3pRasOGDaiqqkJBQQEAoLm5GQDw1ltvobS0NNjdQFVVNDj936rmTo/MR3hcafB7DFVVAzrsqNgdEYcdR3frdpBQBwkOEnohwSGeehEORmeU0X3wHpsOseFg9JyIFYd464VejM4njgUN1kFDQh0kOMRbL/RixjUez6c1WAc5DuyFhpRrvKAXpf7+97/D5XK1/P8//elPAIB77rkn2F0ExJqVBEumPawHflky7bBm6b/1tPzITmw7/DmG9srR9cAvt8eN7Ud2YfvRXbodJNRBgoOEXkhwYC+Cw+iMktAHOshxkDAnJDiwF8FhdD5JqAHHggbrIMeBvQgOM67xJNSB40FDQh0kOLAXGhLqAITw7Xu9evVCv379Wv6kpqYiNTUV/fr1C0vgdOx5XaO6PQAsLVkJixLyFxMC0J5Av7RkZdgOEuogwUFCLyQ4sBeBMSOjJPSBDnIcJMwJCQ7sRWDMyCcJNeBY0GAd5DiwF4Ex6xpPQh04HjQk1EGCA3uhIaEO+o5uIAkD06Gk2YBQ72ZTACXNhoSB6WE7FG3diMMnK+ByuwK/uRUutwuHvj6K4k/9f+48FCTUQYKDhF5IcGAvZCChD3SQ4yBhTkhwYC9kIKEGHAsarIMcB/ZCDhLqwPGgIaEOEhzYCw0JddC9KPXYY4/hscceC1vgdBSbBalX9QUSLcE3RwGQqG2n2MJfZ2t0NuGaRVNR13Qq6Oa43C7UNZ3ChIW3o9Gp/xY8LxLqIMFBQi8kOLAXoWNERknoAx3kOEiYExIc2IvQMSKfJNSAY0GDdZDjwF6EjlHXeBLqwPGgIaEOEhzYCw0JdRB3pxQAWDMS0eXa/lC6BPfIK6WLDV2u7Q9rRmLEHL48cQCXLZiEiprjALTPS/rD+3pFzXFctmAS9lUejJiDhDpIcJDQCwkO7IUMJPSBDnIcJMwJCQ7shQwk1IBjQYN1kOPAXshBQh04HjQk1EGCA3uhEe06BP2gc7OxZiQibfJZcO6pRVN5td8HgFky7bDnddVue4vAKuHp7Ks8iJGPXInCc8di+qgpyO87xOc924/swtKSlSj+dJMhv8mQUAcJDhJ6IcGBvZCBhD7QQY6DhDkhwYG9kIGEGnAsaLAOchzYCzlIqAPHg4aEOkhwYC80olkHsYtSgHY7W2JuBhJzM+CubIStDphRMBmLS1fBlYawnjQfLI3OJqzashartqxFXu9cDMkehDmj7sJjJUvwWcUXKD+y03AHCXWQ4CChFxIc2AsZSOgDHeQ4SJgTEhzYCxlIqAHHggbrIMeBvZCDhDpwPGhIqIMEB/ZCI1p1EPnxPX9Ys5KQnNMVhYWFSM7pakpTTqf8yE6sK30bVVVVWFf6dlT+wyGhDhIcJPRCggN7IQMJfaCDHAcJc0KCA3shAwk14FjQYB3kOLAXcpBQB44HDQl1kODAXmiYWYeYWZQihBBCCCGEEEIIIZ0HLkoRQgghhBBCCCGEENPhohQhhBBCCCGEEEIIMR1FVVXVjAO53W6UlZVh1CWj0KDqe1K7oijITOmKqoZq6NFWG1yACkABlBR9z3inAx3oEHmHFMWOkvdLkJ+fD6vVqsshXMLNqHBrAITfCzrQgQ7GOEQ7o5hPdKADHdoj1vMJ6BznsnSgAx18CTafzP/2PRVQT7n0booT9SfoQAc6dDaHVLv+bSONzjpErA90oAMd5DlIyah47wMd6EAHX2I8n77dNPbPZelABzr4EmQ+mb8opQBKavyuFtKBDnTwtwNdhzUGnRnVWX7jSgc60MHfTvRtFnGYT3SgAx18dqJvs4jDazw60IEOPjsI7m2mL0opyVakXz9A17YpCclYP2UZxq+chganI+Tta1/YC/WUC0qKDem30IEOdJDi4H6tQtdxjUBvRoVbAyD8XtCBDnQwxkFKRjGf6EAHOpxOrOcT0DnOZelABzr4Emw+8UHnhBBCCCGEEEIIIcR0uChFCCGEEEIIIYQQQkyHi1KEEEIIIYQQQgghxHTMf9C5TtyVjXDUOlBcXAzHrpNwpyuwZiXFnUNe71wMzc5BZmYmJhSMwY6K3Sg/stNUB9ZBQ0IdJDhI6EW0kdAHOshxkDAnJNRBgoOEXkQbCTWQMBYkOEjohQQHCb2Q4CChFxKQUAcJ40GCA3tBh9aYOR5EL0qpLg+ce2rRVF4NT1UTAGDem/Nafm7JtMOe1xUJA9Oh2Iy56UuCQ1KCHRNHjMP0UVMwvM85La8vvnk+AGDb4c+xtGQlirZuRKOzyRAH1kFDQh0kOEjoRbSR0Ac6yHGQMCck1EGCg4ReRBsJNZAwFiQ4SOiFBAcJvZDgIKEXEpBQBwnjQYIDe0GH1kRrPIhdlHLXNOPUG4eg1rnafY+nqgmOzV+h8eMqpF7VF9aMxE7ncHb3/lhz93L06ZYNj+rx+56hvXKw8MZH8duxd2PCwtuxr/JgRB1YBw0JdZDgIKEX0UZCH+ggx0HCnJBQBwkOEnoRbSTUQMJYkOAgoRcSHCT0QoKDhF5IQEIdJIwHCQ7sBR1aE83xIPKZUu6aZtSvPgC1vv2mtEatd6F+9QG4a5o7lcPZ3fvj3XteQXZGDyiKAqvF6vd9VosViqIgO6MH3rv3VZyV1S9iDqyDhoQ6SHCQ0ItoI6EPdJDjIGFOSKiDBAcJvYg2EmogYSxIcJDQCwkOEnohwUFCLyQgoQ4SxoMEB/aCDq2J9ngIeVHqnXfeQU5OTps/s2fPjogMoN22duqNQ0CzB1CD3QhAs7ad6vK/qhdrDkkJdqy5eznS7KmwWYO7oc1mtSHNnoq1M1cgKcEetgProCGhDhIcJPQiEMwnOpjpIGFOSKiDBAcJvQiE0fkkoQYSxoIEBwm9kOAgoRcSHCT0IhBG5xMgow4SxoMEB/aCDq2RMB5CXpTau3cvLr30UnzwwQctfx555JGwRbw499Rqt60F2xQvKqDWueDcU9spHCaOGIc+3bKDHhhebFYb+p7ZC4Xnjg3bgXXQkFAHCQ4SehEI5hMdzHSQMCck1EGCg4ReBMLofJJQAwljQYKDhF5IcJDQCwkOEnoRCKPzCZBRBwnjQYIDe0GH1kgYDyEvSn355ZcYNGgQsrKyWv6kp6eHLeKlqbw6qttLcZg+akq7n+UMhNvjxvRRU8J2YB00JNRBgoOEXgSC+UQHMx0kzAkJdZDgIKEXgTA6nyTUQMJYkOAgoRcSHCT0QoKDhF4Ewuh8AmTUQcJ4kODAXtChNRLGg65Fqf79+4d9YH+4KxtbnjSvF09VE9yVjTHtkNc7F8P7nNPuZzkDYbVYkd93CPJ65+p2YB00JNRBgoOEXgQD84kOZjlImBMS6iDBQUIvgsHIfJJQAwljQYKDhF5IcJDQCwkOEnoRDEbmEyCjDhLGgwQH9oIOrZEwHoAQv31PVVXs378fH3zwAZ599lm43W5cccUVmD17NhITg3v6u6IoSElI9vszR60jFJ12sdUBydm+x6hTFKgx4DA0OyciDkOyB2Hv8QO6HFgHDQl1kOBgdC/qFSXsfUcin4D262B0H4DAvaCDHAej50QwDhLqIMHBjF6Em1FG5xPHoxwHCb2Q4CChFxIcmE8aPKeX48Be0KE1Uq7xQlqUqqiogMPhQGJiIp566ikcOXIEjzzyCBobGzF37tyg9tEtOQNFU5b5/VlxcTHmvTkvFCW/zCiYjMLCQp/Xx60ahxP1J5CZ0hXrBTtkZmaGfXwAmDPqLkwdcp0uB9ZBQ0IdJDgY3YuJayaGve9I5BPQfkYZ3QcgcC/oIMfB6DkRjIOEOkhwMKMX4WaU0fnE8SjHQUIvJDhI6IUEB+aTBs/p5TiwF3RojZRrPEVV1ZAeq1VTU4MzzjgDyrerXm+99RbuvfdelJaWwmpt/7Yvt9uNsrIyXDruMnSZfJbf9zh2nUTNmwdD0fFLxtj+SM7p6vP68eU74Kl3wtIlAT2mDhXrMKFgDBbfPD9sh7v+NgfrSt/W5cA6aEiogwQHo3tRv2of/rnxPeTn53eYI4HQm09A4Iwyug9A4F7QQY6D0XMiGAcJdZDgYEYvIpFRRuYTx6McBwm9kOAgoRcSHJhPGjynl+PAXtChNVKu8UJ7xDqAjIyMNv//7LPPRlNTE7755ht069Yt4PaqqqLB6f9WNXd6+B/hAQBXGvwew7v+Jt1hR8XuiDjsOLqbdUDs10GCg1m9CJdw88nr4s/R6D54j02H2HAwek4E4yChDhIczOxFOBiZTxyPchwk9EKCg4ReSHBgPmnwnF6OA3tBh9ZIucYL6UHn//rXv3D++efD4fjugDt37kRGRkbQgdUR1qwkWDLtYe3DkmmHNSspph3Kj+zEtsOfw+1x69re7XGj7NBn2H50l24H1kFDQh0kOEjoRSCYT3Qw00HCnJBQBwkOEnoRCKPzSUINJIwFCQ4SeiHBQUIvJDhI6EUgjM4nQEYdJIwHCQ7sBR1aI2E8ACEuShUUFMBut2Pu3LnYt28fSkpK8MQTT2Dq1KlhSbTGnuf/9liztpfisLRkJSxKyF+OCEB7Cv7SkpVhO7AOGhLqIMFBQi86gvlEB7MdJMwJCXWQ4CChFx1hRj5JqIGEsSDBQUIvJDhI6IUEBwm96Agz8gmQUQcJ40GCA3tBh9ZIGA8hHb1Lly5YsWIFTp48iYkTJ+J3v/sdJk2aFNHQShiYDiXNBoR6N5sCKGk2JAxM7xQORVs34vDJCrjcrpC2c7ldOPT1URR/uilsB9ZBQ0IdJDhI6EVHMJ/oYLaDhDkhoQ4SHCT0oiPMyCcJNZAwFiQ4SOiFBAcJvZDgIKEXHWFGPgEy6iBhPEhwYC/o0BoJ4yHkJbGBAwfi+eefR2lpKT744APMnDmz5aF4kUCxWZB6VV8g0RJ8cxQAidp2ik3fKp80h0ZnE65ZNBV1TaeCHiAutwt1TacwYeHtaHQ2he3AOmhIqIMEBwm9CATziQ5mOkiYExLqIMFBQi8CYXQ+SaiBhLEgwUFCLyQ4SOiFBAcJvQiE0fkEyKiDhPEgwYG9oENrJIyH8P8VBmDNSESXa/tD6RLcc9iVLjZ0ubY/rBmJncrhyxMHcNmCSaioOQ4A7X7W0/t6Rc1xXLZgEvZVHoyYA+ugIaEOEhwk9CLaSOgDHeQ4SJgTEuogwUFCL6KNhBpIGAsSHCT0QoKDhF5IcJDQCwlIqIOE8SDBgb2gQ2uiPR5C/vY9s7BmJCJt8llw7qlFU3k1PFW+K3CWTDvseV21294isEoo0WFf5UGMfORKFJ47FtNHTUF+3yE+79l+ZBeWlqxE8aebDPltCuugIaEOEhwk9CLaSOgDHeQ4SJgTEuogwUFCL6KNhBpIGAsSHCT0QoKDhF5IcJDQCwlIqIOE8SDBgb2gQ2uiOR7ELkoB2u1sibkZSMzNgLuyEbY6YEbBZCwuXQVXGsJ60nwsOTQ6m7Bqy1qs2rIWeb1zMSR7EOaMuguPlSzBZxVfoPzITsMdWAcNCXWQ4CChF9FGQh/oIMdBwpyQUAcJDhJ6EW0k1EDCWJDgIKEXEhwk9EKCg4ReSEBCHSSMBwkO7AUdWhOt8SDy43v+sGYlITmnKwoLC5Gc09WUpkh0KD+yE+tK30ZVVRXWlb4dlf94sQ4aEuogwUFCL6KNhD7QQY6DhDkhoQ4SHCT0ItpIqIGEsSDBQUIvJDhI6IUEBwm9kICEOkgYDxIc2As6tMbM8RAzi1KEEEIIIYQQQgghpPPARSlCCCGEEEIIIYQQYjpclCKEEEIIIYQQQgghpqOoqqqacSC3242ysjKMumQUGlR9T2pXFAWZKV1R1VANPdpqgwtQASiAkqLvGe90oAMdIu+QothR8n4J8vPzYbVadTmES7gZFW4NgPB7QQc60MEYh2hnFPOJDnSgQ3vEej4BneNclg50oIMvweaT+d++pwLqKZfeTXGi/gQd6ECHzuaQate/baTRWYeI9YEOdKCDPAcpGRXvfaADHejgS4zn07ebxv65LB3oQAdfgswn8xelFEBJjd/VQjrQgQ7+dqDrsMagM6M6y29c6UAHOvjbib7NIg7ziQ50oIPPTvRtFnF4jUcHOtDBZwfBvc30RSkl2Yr06wfo2jYlIRnrpyzD+JXT0OB0hLx97Qt7oZ5yQUmxIf0WOtCBDlIc3K9V6DquEejNqHBrAITfCzrQgQ7GOEjJKOYTHehAh9OJ9XwCOse5LB3oQAdfgs0nPuicEEIIIYQQQgghhJgOF6UIIYQQQgghhBBCiOlwUYoQQgghhBBCCCGEmI75DzrXibuyEY5aB4qLi+HYdRLudAXWrCRTHfJ652Jodg4yMzMxoWAMdlTsRvmRnaY6SKgDHejQGgnzItqwDxoS6kAHOrRGwryINhJqIMFBwniU4MBeyHGQ0AsJSKiDBAcJY5IOdGiNmfNC9KKU6vLAuacWTeXV8FQ1AQDmvTmv5eeWTDvseV2RMDAdis2Ym76SEuyYOGIcpo+aguF9zml5ffHN8wEA2w5/jqUlK1G0dSManU2GOEioAx3o0BoJ8yLasA8aEupABzq0RsK8iDYSaiDBQcJ4lODAXshxkNALCUiogwQHCWOSDnRoTbTmhdhFKXdNM069cQhqnavd93iqmuDY/BUaP65C6lV9Yc1IjKjD2d37Y83dy9GnWzY8qsfve4b2ysHCGx/Fb8fejQkLb8e+yoMRdZBQBzrQoTUS5kW0YR80JNSBDnRojYR5EW0k1ECCg4TxKMGBvZDjIKEXEpBQBwkOEsYkHejQmmjOC5HPlHLXNKN+9QGo9e03pTVqvQv1qw/AXdMcMYezu/fHu/e8guyMHlAUBVaL1e/7rBYrFEVBdkYPvHfvqzgrq1/EHCTUgQ50aI2EeRFt2AcNCXWgAx1aI2FeRBsJNZDgIGE8SnBgL+Q4SOiFBCTUQYKDhDFJBzq0JtrzIuRFqebmZjz00EP4wQ9+gB/+8Id48sknoapqRGQA7ba1U28cApo9QLC7VQE0a9upLv+reqGQlGDHmruXI82eCps1uJvJbFYb0uypWDtzBZIS7GE7SKgDHejQGgnzIhDMJ/8wn+jQ2R0kzItAGJ1PEmogwUHCeJTgwF7IcZDQi0AYnU+AjDpIcJAwJulAh9ZImBchL0o98sgj+M9//oMVK1bgz3/+M1577TW8+uqrYYt4ce6p1W5bCzUHVUCtc8G5pzZsh4kjxqFPt+ygm+LFZrWh75m9UHju2LAdJNSBDnRojYR5EQjmU/swn+jQmR0kzItAGJ1PEmogwUHCeJTgwF7IcZDQi0AYnU+AjDpIcJAwJulAh9ZImBchLUrV1NSgqKgIDz/8MPLy8nDhhRfitttuw7Zt28IW8dJUXh3V7QFg+qgp7X6OMhBujxvTR00J20FCHehAh9ZImBcdwXwKDPOJDp3VQcK86Agz8klCDSQ4SBiPEhzYCzkOEnrREWbkEyCjDhIcJIxJOtChNRLmRUiLUlu3bkWXLl0wcuTIltemT5+O+fPnhy0CaF996H3SvF48VU1wVzbq3j6vdy6G9zmn3c9RBsJqsSK/7xDk9c7V7SChDnSgQ2skzItAMJ8Cw3yiQ2d0kDAvAmF0PkmogQQHCeNRggN7IcdBQi8CYXQ+ATLqIMFBwpikAx1aI2FeACF++97hw4fRq1cvrF27Fn/961/hdDpRWFiIu+66CxZLcOtbiqIgJSHZ788ctY5QdNrFVgckZ/seo05RoAZwGJqdExGHIdmDsPf4AV0OEupABzq0xuh5Ua8oYe87EvkEtF8Ho/sABO6F0X0IxkFCHehAh9aYMS/CzSij80lCNkhwkDAeJTiwF3IcmE8aEq6vJDhIOKenAx1aI+UaL6RFqYaGBhw8eBCvvPIK5s+fj8rKSjzwwANITk7GbbfdFtQ+uiVnoGjKMr8/Ky4uxrw354Wi5JcZBZNRWFjo8/q4VeNwov4EMlO6Yn07DpmZmWEfHwDmjLoLU4dcp8tBQh3oQIfWGD0vJq6ZGPa+I5FPQPsZZXQfgMC9MLoPwThIqAMd6NAaM+ZFuBlldD5JyAYJDhLGowQH9kKOA/NJQ8L1lQQHCef0dKBDa6Rc44W0KGWz2VBfX48///nP6NWrFwCgoqICL7/8ctChddJRg/Erp/n9mWPXyVB02mVx6So837DJ5/WqhuqWv9tzmFAwBotvDv921cdKlmBd6du6HCTUgQ50aI3R86LeURP2viORT0D7GWV0H4DAvTC6D8E4SKgDHejQGjPmRbgZZXQ+ScgGCQ4SxqMEB/ZCjgPzSUPC9ZUEBwnn9HSgQ2ukXOOFtCiVlZUFu93eElgA8P3vfx/Hjh0Leh+qqqLB6f9WNXd6+B/hAQBXGvwew/vVph057KjYHRGHHUd363aQUAc60KE1Zs2LcIhEPnld/Dka3QfvsTtyMLoPwThIqAMd6NAaM+eFXozOJwnZIMFBwniU4MBeyHFgPmlIuL6S4CDhnJ4OdGiNlGu8kB50Pnz4cDQ1NWH//v0tr+3bt69NiIWDNSsJlkx7WPuwZNphzUrSvX35kZ3YdvhzuD1uXdu7PW6UHfoM24/u0u0goQ50oENrJMyLQDCfAsN8okNndJAwLwJhdD5JqIEEBwnjUYIDeyHHQUIvAmF0PgEy6iDBQcKYpAMdWiNhXgAhLkqdddZZuOSSS3Dfffdh165d+Ne//oWlS5fi5z//eVgSrbHndY3q9gCwtGQlLEpIpWnBarFiacnKsB0k1IEOdGiNhHnREcynwDCf6NBZHSTMi44wI58k1ECCg4TxKMGBvZDjIKEXHWFGPgEy6iDBQcKYpAMdWiNhXoR89D/96U/o27cvfv7zn+O3v/0tbrzxRtx0001hi3hJGJgOJc0GhHo3mwIoaTYkDEwP26Fo60YcPlkBl9sV0nYutwuHvj6K4k/9f+48FCTUgQ50aI2EeREI5lP7MJ/o0JkdJMyLQBidTxJqIMFBwniU4MBeyHGQ0ItAGJ1PgIw6SHCQMCbpQIfWSJgXIS9KpaWl4YknnkBpaSn+85//YObMmVAi8HXuXhSbBalX9QUSLcE3RwGQqG2n2PSt8rWm0dmEaxZNRV3TqaCb43K7UNd0ChMW3o5GZ1PYDhLqQAc6tEbCvAgE88k/zCc6dHYHCfMiEEbnk4QaSHCQMB4lOLAXchwk9CIQRucTIKMOEhwkjEk60KE1EuZF+P8KA7BmJKLLtf2hdAnuOexKFxu6XNsf1ozEiDl8eeIALlswCRU1xwGg3c9Zel+vqDmOyxZMwr7KgxFzkFAHOtChNRLmRbRhHzQk1IEOdGiNhHkRbSTUQIKDhPEowYG9kOMgoRcSkFAHCQ4SxiQd6NCaaM+LkL59z0ysGYlIm3wWnHtq0VReDU+V7wqcJdMOe15X7ba3CKwSns6+yoMY+ciVKDx3LKaPmoL8vkN83rP9yC4sLVmJ4k83GfKbDAl1oAMdWiNhXkQb9kFDQh3oQIfWSJgX0UZCDSQ4SBiPEhzYCzkOEnohAQl1kOAgYUzSgQ6tiea8ELsoBWi3syXmZiAxNwPuykbY6oAZBZOxuHQVXGkI60nzwdLobMKqLWuxasta5PXOxZDsQZgz6i48VrIEn1V8gfIjOw13kFAHOtChNRLmRbRhHzQk1IEOdGiNhHkRbSTUQIKDhPEowYG9kOMgoRcSkFAHCQ4SxiQd6NCaaM0LkR/f84c1KwnJOV1RWFiI5JyupjTldMqP7MS60rdRVVWFdaVvR+U/HBLqQAc6tEbCvIg27IOGhDrQgQ6tkTAvoo2EGkhwkDAeJTiwF3IcJPRCAhLqIMFBwpikAx1aY+a8iJlFKUIIIYQQQgghhBDSeeCiFCGEEEIIIYQQQggxHS5KEUIIIYQQQgghhBDTUVRVVc04kNvtRllZGUZdMgoNqr4ntSuKgsyUrqhqqIYebbXBBagAFEBJ0feMdzrQgQ6Rd0hR7Ch5vwT5+fmwWq26HMIl3IwKtwZA+L2gAx3oYIxDtDOK+UQHOtChPWI9n4DOcS5LBzrQwZdg88n8b99TAfWUS++mOFF/gg50oENnc0i169820uisQ8T6QAc60EGeg5SMivc+0IEOdPAlxvPp201j/1yWDnSggy9B5pP5i1IKoKTG72ohHehAB3870HVYY9CZUZ3lN650oAMd/O1E32YRh/lEBzrQwWcn+jaLOLzGowMd6OCzg+DeZvqilJJsRfr1A3Rtm5KQjPVTlmH8ymlocDpC3r72hb1QT7mgpNiQfgsd6EAHKQ7u1yp0HdcI9GZUuDUAwu8FHehAB2McpGQU84kOdKDD6cR6PgGd41yWDnSggy/B5hMfdE4IIYQQQgghhBBCTCf2FqU8nmgbEEIIIYQQQgghhJAwMf+ZUiEyvLIRN+6swYUVDuRUNyPxqZE4YFGwu2siPsxOxku5GdiWlRRtTUIIIYQQQgghhBASAmIXpb5f04yFm4/homMOOBUgYXg+cPlgIC0NiXV1GLZrFwZvK8P07TX4d89kzBzdE/szEg11yuudi6HZOcjMzMSEgjHYUbEb5Ud2GnpMOtCBDvKRUAM60IEOMh2ijYQa0IEOdJDpIAEJdaCDHAd3ZSMctQ4UFxfDsesk3OkKrCbfgCKhDvHmIHJR6tovvsGizV/BmmgHbrkFCbNnAwUFPu9LKC0Fnn4a57/6Cj56ZT9mjO6JokHpEXVJSrBj4ohxmD5qCob3Oafl9cU3zwcAbDv8OZaWrETR1o1odDZF9Nh0oAMd5CKhBnSgAx1kOkQbCTWgAx3oINNBAhLqQAc5DqrLA+eeWjSVV8NTpR1j3pvzWn5uybTDntcVCQPTodiMefqQhDrEs4Oi6v7+0dBwu90oKyvDJWNHw3p9drvvu/aLb7D0nWPAwIGwvP020K+f9hwpq9XfTgGLBTh4EJ7LLwf27sX0y3ti9aAz/O675Qn0qcE9gf7s7v2x5u7l6NMtGx7VA6vF18HtccOiWHD4ZAUmLLwd+yoPdrhPOtCBDr64X6vA+5s2Iz8/H1Z/c90Egs0owJgaAKH1gg50oIN5DtHOKOYTHehAh/aIpXwCOu+5LB30ObhrmnHqjUNQ61wB36uk2ZB6VV9YA3w6Khbr0Fkdgs0nUQ86P6umGYs2f6UtSH30EdCrF6Ao/hekAO11RQF69YJlyxZgwAAs2vwVvl/THLbL2d374917XkF2Rg8oiuK3KQBgtVihKAqyM3rgvXtfxVlZ/cI+Nh3oQAe5SKgBHehAB5kO0UZCDehABzrIdJCAhDrQQY6Du6YZ9asPQK0PvCAFAGq9C/WrD8AdgWt9LxLqQIcQF6WKi4uRk5Pj82fw4MERkXlm8zFYEu3aHVJpaUBCQnAbJiQAaWmwvPMOrIl2LNx8LCyPpAQ71ty9HGn2VNiswX3C0Wa1Ic2eirUzVyApwR7W8elABzqEjtH5BMioAR3oQAeZDh3BfKIDHeggNZ8AZhQdzHdQXR6ceuMQ0OwBgv3clgqgWdtOdXnCdpBQBzpohLQoNW7cOHzwwQctf95//33069cPN998c9giw0804qJjDiRMukH7yF6wC1JeEhKA/v1hu34SLjrmwPDKRt0uE0eMQ59u2UE3xYvNakPfM3uh8Nyxuo9NBzrQQR9G5pMXCTWgAx3oINOhI5hPdKADHaTmE8CMooP5Ds49tdpH9kJ9kJAKqHUuOPfUhu0goQ500AhpUSopKQlZWVktf9544w2oqop77rknbJEbd9XAqQCYPVt7hpQe3G5g1iw4FeDGnTW6XaaPmgKPqs/B7XFj+qgpuo9NBzrQQR9G5pMXCTWgAx3oINOhI5hPdKADHaLpEAhmFB3Mdmgqr47q9oCMOtBBQ/czpWpqarBs2TL87//+LxITO37YWDBcWOFAwvB87Vv29D6kz2oFRoxAwvB8XHDMoWsXeb1zMbzPOe1+jjKggsWK/L5DkNc7V9f2dKADHcIn0vkEyKgBHehAB5kOocB8ogMd6GCmQ6gwo+hgtIO7srHlW/b04qlqgjuMT0ZJqAMdviO0e7Ra8fLLL6N79+644oorQtpOURSkJCT7vJ5T3QxcHqHPLefkYHD5Np/j1CkK1A4cAGBodk5EFIZkD8Le4wd8XqcDHejg61CvKBHZvxe9+QS0XwejawAE7gUd6ECH6DhEMqOYT3SgAx0i6SDlHCrez2XpELyDo1bfzSOnY6sDkrN9jxErdYgHh2DzSVFVNdRPckJVVVx22WWYOnUqJk+eHNQ23q8LnThxIoqKitr+0OPBiJEjgWnTgKVLQ9XxZfp0YNkybP3vfwHLdzeDjRs3DidOnED37t2xceNGv5tmZmaiX7/wnyJ/8OBBVFVV+bxOBzrQwdfBmwuR+DpjPfkEBMgoGF8DIHAv6EAHOkTHIVIZxXyiAx3oEGmHaJ9DBconID7OZekQvENxcTHmzZsXtsP999+PwsJCXQ4S6hAPDsHmk647pbZv347jx4/jyiuvDHnbk44ajF85zef1AxYFiXV1enR8qa1Fs0XB+FV3tHm5qqG65W9/DgAwoWAMFt88P2yFx0qWYF3p2z6v04EOdPB1qHfUhL1vL+HkE9B+RhldAyBwL+hABzpExyFSGcV8ogMd6BBpBynnUO3lExAf57J0CN7Bsetk2McHgMWlq/B8wyZdDhLqEA8OweaTrkWpf/3rXzjvvPNwxhlnhLytqqpocPresre7ayKG7dqlR8eXXbuwq1uiz3G8N4W15wAAOyp2R0Rhx9Hdfo9BBzrQoX2HSBBOPnld/DkaXQPvselABzrIdQgX5hMd6EAHoxwigRHXeEB8ncvSIbCDOz0yHzl1pSGm6xBPDoHQ9aDz8vJynHvuuXo2bZcPs5Ph3FYGlJZq36KnB7cb2LoVzvJt+Kin/89NBqL8yE5sO/w53B59Dm6PG2WHPsP2o/oX2OhABzrox4h8AmTUgA50oINMh2BhPtGBDnQw2yEUmFF0MMPBmpUES6Zd9/YAYMm0w5qVpHt7CXWgw3foWpTas2cPBgwYENaBT+el3AwkqACefrrNc6BCwmoFnnkGCaq2P70sLVkJi6LPwWqxYmnJSt3HpgMd6BAeRuSTFwk1oAMd6CDTIRiYT3SgAx2i4RAszCg6mOVgz+sa1e0BGXWgg4auo1dVVSE9PT3sg7dmW1YS/t0zGa5XXwEOHgScztB24HQCBw7A9dqr+HfPZGwLY+W0aOtGHD5ZAZfbFdJ2LrcLh74+iuJPfT/bSgc60CF8h2AwIp+8SKgBHehAB5kOwcB8ogMd6BANh2BhRtHBLIeEgelQ0mxAqJ/kUwAlzYaEgeGPUwl1oIOG7o/vXXzxxWEf/HRmju4Jd3MTPD/9KVBXF/zClNMJ1NXBc/nlcDc3YebonmF5NDqbcM2iqahrOhV0c1xuF+qaTmHCwtvR6GwK6/h0oAMd9GNUPgEyakAHOtBBpkMwMJ/oQAc6RMMhWJhRdDDLQbFZkHpVXyDREvzClAIgUdtOsen8ZFUrJNSBDhrhdzOC7M9IxIzRPYE9e+A5/3zg6FHtB+09Y8r7+tGj2vv37sWM0T2xPyMxbJcvTxzAZQsmoaLmuHaodj5n6X29ouY4LlswCfsqD4Z9bDrQgQ5ykVADOtCBDjIdoo2EGtCBDnSQ6SABCXWggxwHa0YiulzbH0qX4L57TeliQ5dr+8MagWt9LxLqQAed375nJEWD0qFAxaLNX8J6Ti5s108CZs0CRozwfXNZGfDMM3C99irczU2YcXk2igZF7pbTfZUHMfKRK1F47lhMHzUF+X2H+Lxn+5FdWFqyEsWfbjLkNxl0oAMd5CGhBnSgAx1kOkQbCTWgAx3oINNBAhLqQAc5DtaMRKRNPgvOPbVoKq+Gp8r3GJZMO+x5XbWP/EXgDqnTkVCHeHdQ1Eh+j2gHuN1ulJWV4ZKxo2G9Pjvg+79f04yFm4/homMOOBUgYXg+kJMDpKcDtbXA7t1wbitDggp8kJ2MWZcGvkOq9oW9UE+5oKTakH5L6A/xy+udiyHZgzBn1F14rGQJPqv4AuVHdoa0DzrQgQ6+uF+rwPubNiM/Px9WqzVkh0gQaka1JhI1AMLrBR3oQAfjHKKdUcwnOtCBDu0Ry/kEdJ5zWTpExsFd2QhbHTCjYDIWl66CKw0hf8teZ6hDZ3EINp/E3SnlZX9GIq4s7IfhlY24cWcNLjiyE4PLtyHRo6LZomBXt0R8NDQDL+VmhPVQ81AoP7ITe48fwNQh12Fd6dtocDpMOS4d6EAH2UioAR3oQAeZDtFGQg3oQAc6yHSQgIQ60EGOgzUrCcnZySgsLMTzDZvitg7x5iB2UcrLtqwkbMv6HgAgJSEZ6yc/i/Gr7ojb4CaEEEIIIYQQQgjpDIh60HlQWGJPmRBCCCGEEEIIIYS0hSs8hBBCCCGEEEIIIcR0TH/Q+ahLRqFB1fekdkVRkJnSFVUN1dCjrTa4ABWAAigp+j65SAc60CHyDimKHSXvl4h40LnejAq3BkD4vaADHehgjEO0M4r5RAc60KE9Yj2fgM5xLksHOtDBl2DzyfxnSqmAesqld1OcqD9BBzrQobM5pNr1bxtpdNYhYn2gAx3oIM9BSkbFex/oQAc6+BLj+fTtprF/LksHOtDBlyDzyfxFKQVQUuN3tZAOdKCDvx3oOqwx6MyozvIbVzrQgQ7+dqJvs4jDfKIDHejgsxN9m0UcXuPRgQ508NlBcG8zfVFKSbYi/foBurZNSUjG+inLMH7lNF3fvlf7wl6op1xQUmxIv4UOdKCDFAf3axW6jmsEejMq3BoA4feCDnSggzEOUjKK+UQHOtDhdGI9n4DOcS5LBzrQwZdg84kPOieEEEIIIYQQQgghpsNFKUIIIYQQQgghhBBiOlyUIoQQQgghhBBCCCGmY/6DzmMYd2UjHLUOFBcXw7HrJNzpCqxZSXSgQ1w7EBlIGAt0oIM0ByIDCWOBDnSQ5kDkIGE80IEO0hzMhItSAVBdHjj31KKpvBqeqiYAwLw357X83JJphz2vKxIGpkOxGXPjGR3oIM2ByEDCWKADHaQ5EBlIGAt0oIM0ByIHCeOBDnSQ5hAtuCjVAe6aZpx64xDUOle77/FUNcGx+Ss0flyF1Kv6wpqRSAc6dGoHIgMJY4EOdJDmQGQgYSzQgQ7SHIgcJIwHOtBBmkM06VxLbBHEXdOM+tUHoNa3PzBao9a7UL/6ANw1zXSgQ6d1IDKQMBboQAdpDkQGEsYCHeggzYHIQcJ4oAMdpDlEm5AXpY4dO4Y77rgD5557LkaPHo0XXnjBAK3ooro8OPXGIaDZA6jBbgSgWdtOdXnoQIdO5xALMJ/a2widbjzSgQ6xBvOpvY3Q6cYjHegQa8RDPgEyxgMd6CDNQQIhL0r96le/QkpKCoqLi3H//ffjqaeewjvvvGOEW9Rw7qnVbp0LdmB4UQG1zgXnnlo60KHTOcQCzKcO6GTjkQ50iDWYTx3QycYjHegQa8RDPgEyxgMd6CDNQQIhLUp98803KCsrw1133YX+/fvjJz/5CS6++GJ8+OGHRvlFhaby6qhuTwc6SHSQDvPJnO3pQAeJDtJhPpmzPR3oINFBOvGST4CM8UAHOkhzkEBIi1JJSUlITk5GcXExnE4n9u3bh08//RS5ublG+ZmOu7Kx5Wn3evFUNcFd2UgHOnQah1iA+RQcnWE80oEOsQbzKTg6w3ikAx1ijXjIJ0DGeKADHaQ5SCGkb9+z2+144IEH8PDDD+Nvf/sb3G43CgsLcd111wW9D0VRkJKQHLIoACQnJLX5O1TqFAVqAAdHrUPXvk/HVgckZ/segw50iEWHQIQ7N+sVRdd2rYlEPgH66xBuDYDAvTB6LNCBDrHoEIhIzM1wM4r5FDyxPh7pQIdQYD5p8BqPDnSIjkMgzLrGC2lRCgC+/PJLXHrppbj11luxZ88ePPzww7jwwgtx1VVXBbV9t+QMFE1ZFuph2/DapGd0bTdu1TicqD+BzJSuWN+OQ3FxMea9OS8cPQDAjILJKCwspAMdOoVDsOidmxPXTAzruF7CzScg/IzSWwMgcC+MHgt0oEMsOgRLOHMzEhnFfAqOWB+PdKCDHphPGrzGowMdzHUIFqOv8UJalPrwww+xevVqlJSUICkpCcOGDcPx48exZMmSoEPrpKMG41dOC+WwLSQnJOG1Sc/g+ldnweEM/Ta1qobqlr/bc3DsOqnL7XQWl67C8w2b6ECHTuEQiHDnZr2jRtdxWxOJfAL0Z1S4NQAC98LosUAHOsSiQyAiMTfDzSjmU/DE+nikAx1CgfmkwWs8OtAhOg6BMOsaL6RFqR07dqBfv35ISvru9q1zzjkHf/3rX4Peh6qqaHCGd6uaw9moax+qqgZ0cKeH/zEiAHClwe8x6ECHWHQIlnDnZjhEIp+8LuHUQW8NvMfuyMHosUAHOsSiQ7BEYm7qhfkUPLE+HulABz0wnzR4jUcHOpjrECxGX+OF9KDz7t274+DBg2hubm55bd++fejdu3dodoKxZiXBkmkPax+WTDusWfo/G04HOkhziAWYT8HRGcYjHegQazCfgqMzjEc60CHWiId8AmSMBzrQQZqDFEJalBo9ejQSEhIwd+5c7N+/H5s3b8Zf//pX3HTTTUb5RQV7Xteobk8HOkh0kA7zyZzt6UAHiQ7SYT6Zsz0d6CDRQTrxkk+AjPFABzpIc5BASItSaWlpeOGFF1BZWYlrr70W8+fPx1133YVJkyYZ5RcVEgamQ0mzAaHeUacASpoNCQPT6UCHTucgHeZTADrZeKQDHWIJ5lMAOtl4pAMdYol4ySdAxnigAx2kOUggpEUpABgwYACef/55bN26Fe+88w5uueUWKBH4OndJKDYLUq/qCyRagh8gCoBEbTvFFnJZ6UAH8Q6xAPOpvY3Q6cYjHegQazCf2tsInW480oEOsUY85BMgYzzQgQ7SHCTQOf4VBmDNSESXa/tD6RLcs+CVLjZ0ubY/rBmJdKBDp3UgMpAwFuhAB2kORAYSxgId6CDNgchBwnigAx2kOUSbkL59L96wZiQibfJZcO6pRVN5NTxVTT7vsWTaYc/rqt16Z8BKJR3oIM2ByEDCWKADHaQ5EBlIGAt0oIM0ByIHCeOBDnSQ5hBNuCgVAMVmQWJuBhJzM+CubIStDphRMBmLS1fBlQZTnnZPBzpIcyAykDAW6EAHaQ5EBhLGAh3oIM2ByEHCeKADHaQ5RIvOtcRmMNasJCTndEVhYSGSc7pGZWDQgQ7SHIgMJIwFOtBBmgORgYSxQAc6SHMgcpAwHuhAB2kOZsJFKUIIIYQQQgghhBBiOlyUIoQQQgghhBBCCCGmw0UpQgghhBBCCCGEEGI6XJQihBBCCCGEEEIIIaajqKqqmnEgl8uFbdu2Yey4sXCovl9xGAyKoqBbcgZOOmqgR1t1uAEVgAIoyVY60IEOQhySFTs2bdyE4cOHw2aLzpeChptR4dYACL8XdKADHYxxiHZGMZ/oQAc6tEes5xPQOc5l6UAHOvgSbD6ZllwejwcAsGnjJrMOSQiJMbw5Ec1jM6MIIe0RrYxiPhFCAsF8IoRIJVA+mXanlMfjgcvlgsVigaIoZhySEBIjqKoKj8cDm80GiyU6nypmRhFC2iPaGcV8IoS0B/OJECKVYPPJtEUpQgghhBBCCCGEEEK88EHnhBBCCCGEEEIIIcR0uChFCCGEEEIIIYQQQkyHi1KEEEIIIYQQQgghxHS4KEUIIYQQQgghhBBCTIeLUoQQQgghhBBCCCHEdLgoRQghhBBCCCGEEEJMJ6YWpYqLi5GTk4PXX3/d1OPm5OS0+XPBBRdg7ty5OHXqlKkeAPDNN9/gsccew+jRozF8+HCMHTsWL7zwAjwej+HHHj16dEsNBg8ejIKCAtxwww3417/+Zfix/Tmc/mfLli1R9/j5z39umkNDQwOeeuopXHHFFcjLy8P555+P2bNnY8+ePaYcf/To0SguLvZ5vbi4GKNHjzbFQRrxnlHxnk+ne0Qro5hPzCd/MJ+YT8yn74hmRjGffGE+RS+fABkZJSGfOvLgOZSxGWUzZK8GsWHDBvTt2xfr1q3DddddZ+qxn3nmGRQUFMDj8eDYsWN44IEH8MQTT+Chhx4yzaG6uhqTJk1C9+7d8eijj6J3797Yvn07Hn74YRw+fBi///3vDXe4//77MW7cOHg8HnzzzTdYu3Yt7rjjDixfvhw//OEPDT9+a4fTOeOMM0w5fkceCQkJphz71KlTmDx5MhoaGjBnzhwMHjwY1dXVeOmll3DDDTdg7dq16NOnjyku5DviOaOYT74ep2NmRjGfyOkwn5hPrT1OJ17yCWBGSYT5FN18AmRklIR8as+D51DGEjOLUl9//TU+/PBDzJs3D3PmzMHhw4dNbcgZZ5yBrKwsAECPHj1wxx134KGHHjJ1UerPf/4zEhMTsWLFCtjtdgBAnz59kJSUhBkzZmDKlCn4/ve/b6hDWlpamzr85je/QWVlJebPn4/169cbemx/DtEkmh6LFi3C119/jY0bNyI9PR0A0KtXL8yfPx/Hjh3DCy+8YNp/xIhGvGcU88m/R7RgPpHWMJ+YT/48okW0HZhRsmA+RT+fABkZFe1skOARr/kUMx/fe/PNN5GWloarrroK3bt3x7p166Lqk5ycbOrxmpubsWHDBtx4440tgeXl0ksvxQsvvIBevXqZ6uRl0qRJ+OKLL3Dw4MGoHD/e8Hg8WLNmDW699daWsGrNE088gXvvvTcKZvFNPGcU84l4YT7JhPnEfCIazCh5MJ9k5hPAjDKbeM6nmFmU2rBhAy655BJYLBaMHj0aa9euhaqqUXE5efIk/v73v+Oqq64y7ZiHDh1CQ0MDhg0b5vMzRVFwwQUXIDEx0TSf1px99tkAgL1790bl+PHGoUOHcPLkSZx33nl+f969e3ckJSWZbEXiOaOYT8QL80kmzCfmE9FgRsmD+SQznwBmlNnEcz7FxMf3jh07hk8//RS33norAOCnP/0pXn75ZWzdurXdpkWaadOmwWq1QlVVOBwOZGRk4MEHHzTl2ABQW1sLQLudUBpeJ7MeCviHP/wBDz/8cJvXsrOzsWHDBlOO35HHv//9b6SkpBh63OrqagBtP1/9n//8B3fffXfL/zerHv5q4HK5RNx6aybxnlHMp7ZIyCjmE/PJC/OJ+dSaeM4nQE5GMZ80mE9y8wngNV5reA5lbEbFxKLUhg0bYLfb8aMf/QgAMHLkSJxxxhlYs2aNaYH1yCOPYPjw4VBVFdXV1Vi5ciV+/vOfY/369TjzzDMNP35GRgYA7dsZpFFfXw8A6NKliynHmz17Nn7605+2ec1mM38o+/Mw45Zf7+2c3v+QAUBBQQHWrl0LAHj77bfx8ssvG+4B+K+BmceXQrxnFPOpLRIyivnEfPLCfMoAwHzyEs/5BMjJKOaTBvMpA4DMfAJ4jdcankMZe/yYWZRqbGzEiBEjWl5zu91488038fvf/96U29h69OiBfv36AQD69++PIUOG4Pzzz8emTZswZcoUw4/ft29fpKWl4bPPPkNeXp7Pz++66y7cdNNNpn6Di5fdu3cDAAYOHGjK8c4888yWXkSTaHn069cPGRkZKC0tbRkLycnJLS5mLJJ68VcDM48vhXjPKOZTWyRkFPOJ+eSF+cR8ak085xMgJ6OYTxrMJ7n5BPAaz2yk5JP3WGZmlPhnSu3fvx+ff/455s6di7Vr17b8+ctf/oL6+nq88847UfGyWCxQVRVut9uU49lsNowbNw4vvfQSmpub2/xs8+bN2Lx5M7p3726Ky+kUFRVhyJAhnfLrKSVis9kwceJEvPjiiy2/wWjN8ePHo2AVvzCjmE/kO5hPsmA+MZ9IW5hRcmA+yc4ngBllNvGcT+LvlNqwYQMyMjIwadKkNg96GzRoEBYtWoS1a9di/Pjxhnt88803qKysBKB9rva5556D2+3G6NGjDT+2l1mzZuG6667D7bffjlmzZuF73/setmzZggULFuDmm2/GgAEDDHeoq6tDZWVlyy2uq1evxsaNG/Hcc88ZfuzTHU4nNTXVlOcRSGDWrFnYunUrbrjhBsycORNDhgxBdXU1Xn/9daxevRo/+9nPoq0YNzCjNJhPvh6nEy8ZxXySA/NJg/nk63E68ZJPADNKCswnDQn5BMjIKOZT/OZTTCxKjR8/3u83D/z85z/Ho48+iuPHj6NHjx6GesyaNavlfycnJ2Po0KFYtmyZqSvHWVlZePnll/HMM8/gnnvuQU1NDfr27YvZs2fj5z//uSkO8+bNw7x586AoCrp164ZzzjkHL7zwgmmf+27tcDq//OUvMWPGDNM8oklycjL+/ve/48UXX8TixYtx8OBBJCYmIi8vD8888wx+8pOfRFsxbmBGaTCffD1OJ14yivkkB+aTBvPJ1+N04iWfAGaUFJhPGhLyCZCRUcyn+M0nRY3Wd24SQgghhBBCCCGEkLhF/DOlCCGEEEIIIYQQQkjng4tShBBCCCGEEEIIIcR0uChFCCGEEEIIIYQQQkyHi1KEEEIIIYQQQgghxHS4KEUIIYQQQgghhBBCTIeLUoQQQgghhBBCCCHEdLgoRQghhBBCCCGEEEJMh4tShBBCCCGEEEIIIcR0uCjVCZg+fTruu+++Nq/94x//QE5ODp555pk2ry9evBhXX301AKC2tha/+93v8MMf/hAXXHAB5syZg9ra2pb3Hjp0CLfeeisKCgowfvx4vP/++wFdpkyZgk8//bTD98ydO9fH6/jx45g9ezZGjhyJiy++GPPnz0dTU1OH+/ntb3+L9evX+7w+Z84c5OTktPwZPnw4brjhBpSXl7d53/vvv4+rr7665d/33nvvtfzM7XbjT3/6Ey666CIUFBTgl7/8JaqqqgL98wkhfjAqo1544YU2cz0nJwePP/54hy6XXnopjh8/3u7PVVXFbbfdhuLiYp+f1dTU4Ic//CGOHDkS8N/cXhbedNNNbXwLCgpw++234+DBg23eV1RUhCuuuAIFBQW47rrrsHXr1pafNTU14eGHH8aFF16ICy+8EA888AAaGhoCOhFCfNGbT19//TVmz56NESNG4KKLLsKCBQvgcrl89u9yuXD11Vf77MsfevOpuroas2bNQkFBAUaPHo1169YFPJaRGQVo+XzxxRejoKAA999/PxwOR0AnQkjHGHU+9cUXX2DKlCkoKCjAmDFj8I9//COgS3t5derUKcydOxcXXHABfvzjH2Pp0qUB9/X000/jr3/9q8/rzzzzTJs8GjZsGK6++mqUlJS0eV9ZWRluuOGGFv/XX3+95WejR4/2OVfMycnBwoULA3oR8+CiVCfgvPPOw/bt29u8tmXLFnTv3h1btmxp83pZWRlGjhwJAPjDH/6AXbt2YenSpVixYgW+/PJLzJ07F4B20XPrrbfCbrfjtddew+23347/+Z//8VnYaY3D4cCePXuQl5fX7nuWLVvWJigA7SRr9uzZcDgceOmll/CXv/wF//znP/HUU091+O/+6KOPcMEFF/j92dixY/HBBx/ggw8+wJo1azB8+HDccccdOHXqFABg165dmDlzJiZOnIi1a9fihhtuwC9/+Uvs2rULALB06VJs3LgRTz31FF5//XV88803+M1vftOhDyHEP0ZkFADs3bsXkydPbpnrH3zwAe6+++52PQ4ePIikpCT06NHD7889Hg8eeeQR/Pvf//b52TfffIM777wTX3/9dcB/b6AsvO222/DBBx/gX//6F1577TVkZGRgxowZUFUVAPB///d/+OMf/4gZM2Zg7dq1uOiiizB9+vSWk7+FCxfiv//9L5YuXYpnn30Wn3zyCZ588smAXoQQX/Tm0z333IP6+nq8+uqr+H//7/9hw4YNWL58uc/+n3vuuZZzi44IJ5/uu+8+1NXV4dVXX8Vdd92FuXPnhnW+Fm5GvfXWW1i4cCH++Mc/4sUXX8S2bduwYMGCgDUghHSMEedTzc3NuPPOO3HOOedg3bp1mDZtGubMmeNznNZ0lFe///3v8fHHH2PRokV48skn8corr+D555/v8N/14Ycf4sILL/T7s4KCgpZzvA0bNuBnP/sZZs2a1fILwsrKSkybNg0jR47EmjVrMHv2bDz88MMtN1OsXr26zXni73//e6SlpeGaa67p0ImYCxelOgEjRozAl19+2bLgAmgBdfvtt6OsrAyNjY0tr2/btg0jR45EQ0MD3nrrLTzwwAMYOnQohgwZgvvvvx/vvvsumpqa8M9//hPV1dVYsGABBg4ciAkTJuCqq67CCy+80K7HJ598gvz8fNhsNp+f1dfXY/bs2Vi2bBl69uzZ5mf79u1DWVkZ5s+fj4EDB+K8887D7NmzO1yl37dvH9LS0pCVleX350lJScjKykJWVhbOOuss3HvvvWhsbMRHH30EQPutwgUXXICbb74Z/fr1w4033ojzzz8fmzZtAqDdKXXffffhBz/4AQYMGICbbrrJ57eAhJDgMCKjAODLL7/E4MGDW+Z6VlYWunTp0q5HRyc9x48fxy9+8Qts3rwZ6enpbX72ySefoLCwMOi7kTrKQgBISUlBVlYWunfvjoEDB2LOnDnYu3cvdu/eDQBYs2ZNS+b269cPv/rVr5CZmdnym8GSkhJMmjQJw4YNQ15eHn7+85+3ZBshJDT05FNzczPOPPNM/OEPf8CAAQNw3nnnYcyYMT7nCQcPHsTf/vY3DBgwIKCH3nw6dOgQ/vnPf+KRRx7BoEGDcN111+Gqq67CqlWr2j2W0Rn1t7/9Db/4xS9w6aWXIi8vDw899BCKiop4txQhYWLE+dTevXtx9OhR/PKXv0Tfvn1x7bXXYtCgQfjvf//brkd7eXXy5Els2LABDz30EEaMGIHzzjsP99xzD1asWNHuvk6dOoX9+/dj6NChfn+ekJDQco7Xt29fTJs2DdnZ2di8eTMA4N1330VmZiZ+/etfo3///rjyyisxYcKElk/TdOvWrWX7pKQkLFq0CL/97W/Rq1evjotNTIWLUp2AYcOGISEhAZ999hkA4KuvvkJFRQWuu+46pKWltdyevX//fnzzzTc477zzYLFY8Ne//hW5ublt9uV2u3Hq1CkcPnwYZ511FtLS0lp+lpOTg7KysnY9OjqhOnLkCJqamlBcXIw+ffq0+VlWVhaWL1+OzMzMNq/X19d3eKz27pLyh81mQ2JiYsv/v+aaa3DPPff4vK+urg4AMHPmTFx++eUAtFv0X3/99ZbfNhBCQsOIjAK0xen+/fsH7dFRRn322Wfo2bMnioqK2uQeAHzwwQeYOHFiUB+/CXQcfyQnJ7f5/1OnTsWtt97q8z5vPmVkZOCtt97CN998g2+++QZvv/22T50IIcGhJ58SExPxpz/9Cf369QMA7NmzB5s3b/Y5T3jggQcwa9YsdOvWLaCH3nzatm0bevbsid69e7e8NmLECJSWluo6lj9CySi3243t27fjvPPOa3k9Pz8fTqczqDvGCCHtY8T51BlnnAEAeP311+HxeFBaWop9+/bhnHPOadejvQzx3r00fPjwltdycnJQWVnZ7qMPPvnkExQUFMBqtQZdh5SUlJb/7X3sy+n4u45csWIFsrKyMHHixKCPRcyBi1KdgMTERAwfPrzlVu2PPvoIQ4cORWpqKn7wgx+03M5ZVlaGgQMHomvXrkhKSsKPf/zjNgs1f/vb35CTk4Nu3bohMzMTlZWVLbdqA1rwVVdXt+vR0cfpBg8ejGeffbbNSZOX9PR0XHzxxS3/3+PxYOXKlR0uOn300UdBn1C5XC689NJLSEhIaNnn2WefjcGDB7e8Z8+ePX4D9umnn8YPf/hDfPrpp5gzZ05QxyOEtMWIjKqqqkJNTQ3WrFmD0aNHY+zYsVixYkWbzGqNqqr4+OOP211cHj16NJ544gm/F4+/+tWvMGPGjKBPmDrKwtNpbm7GX//615ZnHADAkCFD2iy2/d///R8OHDjQss/f/OY3OHLkCM4//3ycf/75+Oabb/CHP/whqOMRQtqiJ59aM2XKFPzsZz9DWloabrzxxpbXi4qK0NTUhOuvvz6gQzj5VFlZie7du7d57cwzz+zw2VRGZlRtbS2ampraONlsNmRkZOCrr74K6piEEP8YcT7Vq1cv/PrXv8af/vQnDB06FDfccAOmTp3a7nVWR3l15plnAkCb/Dl27BgAtHsNGcoiuaqqePfdd3HgwIGWmwd69+6N/Pz8lvd8/fXX2LBhg88+HQ4HVq5ciTvvvBMWC5dApMGOdBLOO++8loDasmULzj//fADAyJEj2wRUeyc8K1euxKZNm1qem/TjH/8YdXV1eOaZZ9Dc3Izt27dj9erVcDqdfrevqanB8ePHW05YwmHBggX4/PPP8T//8z9+f+7xePDJJ590eOfS+vXrUVBQgIKCAuTl5eGPf/wjpk6ditTUVJ/3njx5ErNmzcK5556Lyy67rM3Prr76aqxevRoXXnghbrvttg7v3iKEtE+kM2rfvn0AtBOgJUuW4I477sCSJUvw4osv+t1+165d6NmzZ8tvBI0imCx89tlnW/Jp+PDhWL58OWbOnAlFUXzee+jQIdx3330YP348hgwZ0vJaz5498eKLL2LFihVoamrCY489Zti/iZDOTjj5NHfuXPztb3+D0+nEr3/9awDaRdGTTz6JP/7xj37n9emEk08Oh6PNxSagXbg2Nzf7fb/RGeX9+FAoToSQ4In0+ZTT6cS+ffswadIkvP7667jvvvuwbNkyn2dUeekor3r16oX8/Hw8+uijqKmpQWVlZcsDxdu7hgy0KOW9k6qgoABDhw7F3XffjYkTJ/o8DgYAGhsbMWvWLGRmZmLSpEltfrZx40akpKTgpz/9abvHItGDi1KdhNYPvtuyZUtLEI0cORI7duxAc3MzysrK8IMf/MBn25deegmPPPII7rvvPvzoRz8CoF3o/eUvf8HLL7+M4cOH49e//jWmTJnid1Gn9TGDOfnqiAULFuDFF1/EggULMGjQIL/v+fzzz9GnTx+fW9hbM3r0aKxdu7blz4MPPognn3zS5xtrqqqq8Itf/AKqquLpp5/2WTnv168fhg0bhieeeAKNjY14++23w/r3ERKvRDqjRo4ciY8++gj33nsvcnJyMGHCBMyYMQMvv/yy3+OH+nEVvQSThTfccENLNhUXF+NXv/oVfv3rX+PDDz9s8779+/fj5ptvRp8+ffDII48A0G5H/93vfoff/va3OP/883HRRRdh3rx5KCoqwokTJwz9txHSWQknnwYPHozzzz8f8+bNwz//+U8cOXIEjz76KAoLC9s9jzmdcPLJbrf7LPY0NzcjKSnJ7/uNzii73d7icLrT6R8DJISETqTPp9auXYsdO3Zg7ty5GDJkCG655RaMHz8ey5Yt83v8QHn1xBNP4MSJE7jgggswbty4lm8A9PfMz5MnT+Lrr7/GwIED293f0KFDW/Jo3bp1+NOf/oQ33njD59vzTp06hTvuuAMHDhzAs88+65M3b731FsaNG9fus/RIdGFXOgkFBQU4ceIEtm/fjhMnTuDcc88FAAwcOBBpaWn4+OOPsXfvXp9V8xUrVuCJJ57Ab37zG/ziF79o87NRo0bhP//5DyorK5GZmYmXX3653YfCReKC7+GHH8bLL7+MBQsWYMyYMe2+L5hjpaamtjzrAQAGDRqEnTt3YuXKlSgsLASg3Vp68803A9BuY219W/w///lPnHPOOS3fKmG329GnT58OP75ICGkfIzLq9I/RnH322e1+ZOXDDz/ELbfcErl/UDsEk09nnHFGm3zKzc3Fxx9/jJdffrll2z179uCWW25Bnz59sHz58pYLzH379qGhoaHNx4/POecceDwefPXVVz4f4yGEBCbUfKqvr8f//d//4Yorrmj5ZZb3YebV1dXYsGEDkpKSsHLlSgDab+9LS0vx5ptvYsOGDT7HDyefevTogaqqqjavVVVVtftFMEZnVEZGBux2O6qqqnD22WcD0B6jUFNT064TISR4In0+9dlnn2HQoEFtFqpzc3Nbnk91OoHyql+/fli3bh2+/vprpKWl4dChQ7BYLMjOzvZ570cffdRyp1d7JCUltcmjAQMGoKKiAs899xxmzpwJQMvkqVOn4tChQ3jxxRd9njfa3NyM//73v5g+fXqHxyLRg3dKdRJSUlKQm5uLV199FcOGDWtZHVYUBT/4wQ9QXFyM/v37t1l4WbNmDZ544gncd999uP3229vs78svv2y5g6h79+6wWCwoKSlpNzjCXZRauHAhXnnlFTz55JO48sorO3xvKM9CaI2qqvB4PACAhoYGTJ06FRaLBStXrvT5StPHH38ca9eubfn/9fX1OHDgQMsJFiEkNCKdUa+//jrGjBnT5hlSO3fuxFlnneVzbKfTifLycowYMcKgf9136M1CVVXhdrsBACdOnMBtt92Gfv36YcWKFW1+u+hddNq7d2/La96PMvp7Zh8hJDCh5pPD4cD//M//YNu2bS37+Oyzz2C1WvH9738fb7/9Nt54442W3+57n9OydOlSn2OHm0/5+fk4evRom+c1bd26tc0zVlpjdEZZLBYMGzaszTcRlpWVwWaztVlMJ4ToI9LnU927d29zTgFod0H6O6cIlFcejwe33XYbdu/ejTPPPBOJiYl4//33cc455/i9UyqUZwS3pvU1ncfjwcyZM3HkyBH8/e9/93vX1e7du+FyuZCXlxfysYg5cFGqE/GDH/wAGzZs8FkZHzlyJN577702t3HW1NTgj3/8I6655hpceeWVqKysbPnjdrvRq1cvfPnll3j66adx+PBhLFq0CFu3bsVNN93kc9yvvvoKTqfT51v1guXLL7/E4sWLMW3aNIwYMaKNy+k0Nzdjx44dLb8VaI/GxsaWfRw/fhwbN27E+vXrMXbsWADa8xIOHTqExx9/HABa3uv9dqsbb7wRK1asQElJCfbs2YN7770Xffv2xY9//GNd/0ZCSGQz6oc//CEqKyvx+OOP4+DBg9iwYQOWLVuGqVOn+hx327ZtGDRoULsfZ4kUwWZhQ0NDy7/l2LFjeOmll/Dhhx+25NPjjz8Oj8eDRx99tM17T506he9973u4+OKL8fvf/x47duzA9u3b8fvf/x5XXnllUN/wRQjxTyj5lJWVhZ/+9Kd4+OGH8fnnn+OTTz7B7373O0yZMgVdunRBv3792vxJSkrCGWec4fdu83DzqU+fPvjRj36Ee++9F7t27cLrr7+Of/zjH20euu7FjIwCgMmTJ2PFihV49913UV5ejgcffBDXX389P75HSISI5PnU+PHjcfjwYSxYsACHDh3C2rVr8dprr/m95guUVxaLBUlJSfjzn/+MAwcO4N1338WiRYtw5513+n1/MIvkTqezxffEiRP417/+hb/97W8tebR69Wps2bIFjzzyCNLT01veW1NT07KPPXv2oHfv3j7PuiNy4Mf3OhEjRozAc88953M308iRI+FwONoE17///W80NDRgzZo1WLNmTZv3v/fee+jduzcWLlyIP/7xj3jhhRcwcOBALF++3O+tlx9++KGuO5daH8/tdmPJkiVYsmRJm5/t3r27zf8vKyvD4MGDW55Z0B6bNm3Cpk2bAGjf+vK9730Pd9xxR8sF61tvvYXGxkZcd911bba75ppr8Nhjj+HGG2+Ew+HAgw8+iJMnT+Kiiy7CkiVL+G0NhIRBpDNq6dKlWLBgAV5++WWceeaZuOeeezBu3Dif4+q9uzJUgs3C5557Ds899xwAICEhAf369cMDDzyAn/3sZy3fLNPY2IgrrriizXYzZ87ErFmz8Oc//xmPPfYYpk+fDkVRcNlll+G3v/2tIf8mQuKFUPIJAObNm4d58+bh1ltvBQBMmDAB//u//xvycSORT0888QR+97vf4frrr0dWVhbmzZvn944AszLqyiuvxNGjR/HAAw+gubkZP/3pT3HvvfeG9W8khHxHJM+n+vTpg+eeew5PPPEEVq1ahezsbDz66KNtvhndSzB59dBDD+H3v/89rrnmGpx55pmYO3duyzfltebo0aMA0O6jYbyUlpa2PP/KYrEgKysLV199NWbPng1Au6bzeDy44447fGrx97//HYD2kWajv+iGhIeitvf92YQQQgghhBBCCCGEGARv+yCEEEIIIYQQQgghpsNFKUIIIYQQQgghhBBiOlyUIoQQQgghhBBCCCGmw0UpQgghhBBCCCGEEGI6XJQihBBCCCGEEEIIIabDRSlCCCGEEEIIIYQQYjpclCKEEEIIIYQQQgghpsNFKUIIIYQQQgghhBBiOlyUIoQQQgghhBBCCCGmw0UpQgghhBBCCCGEEGI6XJQihBBCCCGEEEIIIabDRSlCCCGEEEIIIYQQYjpclCKEEEIIIYQQQgghpsNFKUIIIYQQQgghhBBiOlyUIoQQQgghhBBCCCGmw0UpQgghhBBCCCGEEGI6NrMO5PF44HK5YLFYoCiKWYclhMQAqqrC4/HAZrPBYonOWjkzihDSHtHOKOYTIaQ9mE+EEKkEm0+mLUq5XC5s377drMMRQmKQYcOGITExMSrHZkYRQgIRrYxiPhFCAsF8IoRIJVA+mbYo5V0ZGztuLBxqk659KIqCbskZOOmogaqqIW+vOtyACkABlGQrHehAByEOyYodmzZuitpdUkD4GRVuDYDwe0EHOtDBGIdoZxTziQ50oEN7xHo+AZ3jXJYOdKCDL8Hmk2mLUt7bOR1qE6zXZ+vaR0pCMoqmLMP4ldPQ4HSEvH3tC3uhnnJBSbUh/foBdKADHYQ4OF6rAPBdTkSDcDMq3BoA4feCDnSggzEO0c4o5hMd6ECH9oj1fAI6x7ksHehAB1+CzSc+6JwQQgghhBBCCCGEmA4XpQghhBBiHB5PtA0IIYQQQohQTPv4HiGEEEI6P8MrG3HjzhpcWOFATnUzEp8aiQMWBbu7JuLD7GS8lJuBbVlJ0dYkhBBCCCEC4KIUCZm83rkYmp2DzMxMTCgYgx0Vu1F+ZKepDu7KRjhqHSguLoZj10m40xVYTb7IkeAgAQnjgRAvEsajhGyIhsP3a5qxcPMxXHTMAacC7FCBIgB1ANI8KgZ/3YRbTzZh+vYa/LtnMmaO7on9GcZ+U5SE8UCIFwnjMV7zSaKDhPFASGskjEkJc5MOGmaOBy5KkaBISrBj4ohxmD5qCob3Oafl9cU3zwcAbDv8OZaWrETR1o1odOr75o1AqC4PnHtq0VReDU+Vdox5b85r+bkl0w57XlckDEyHYjPmk6kSHCQgYTwQ4kXCeJSQDdF0uPaLb7Bo81dodqt4HsDTKlDm5335KjAbwLXHHPjolf2YMbonigalR9RFwnggxIuE8Rjv+STJQcJ4IKQ1EsakhLlJB41ojQcuSpGAnN29P9bcvRx9umXDo/p/NsjQXjlYeOOj+O3YuzFh4e3YV3kwog7ummaceuMQ1DpXu+/xVDXBsfkrNH5chdSr+sIa4d/AS3CQgITxQIgXCeNRQjZE0+HaL77B0neO4QsAVwA4iPYfWFkO4DYADwF4y61i2TsVUKBi9aAzIuIiYTwQ4kXCeIz3fJLkIGE8ENIaCWNSwtykg0Y0x4PuJbbm5mb87Gc/w5YtWyIiQmRydvf+ePeeV5Cd0QOKosBqsfp9n9VihaIoyM7ogffufRVnZfWLmIO7phn1qw9ArW9/krZGrXehfvUBuGuaO5WDBCSMh2BgPsUHEsajhGyIpsNZNc1YtPkrfAHghwCOfPt6e482975+BMCFAPYAWLT5K3w/Ai4SxkMwMJ/iAwnjMd7zSZKDhPEQDMyn+EHCmJQwN+mgEe3xoGtRqqmpCb/+9a+xZ8+eiEgQmSQl2LHm7uVIs6fCZg3upjqb1YY0eyrWzlyBpAR72A6qy4NTbxwCmj2AGuxGAJq17VRX+N/6JMFBAhLGQzAwn+IDCeNRQjZE2+GZzcfQ5FZxBYBaAO4gt3N/+/4xAJrdKhZuPhaWh4TxEAzMp/hAwniMdjbQ4TskjIdgYD7FDxLGpIS5SQcNCeMh5EWpvXv34vrrr8ehQ4fCPjiRzcQR49CnW3bQg9OLzWpD3zN7ofDcsWE7OPfUarcxBjtJvaiAWueCc09tp3CQgITxEAjmU/wgYTxKyIZoOgw/0YiLjjlQBO0je8EuSHlxf7tdEYCLjjkwvLJRt4uE8RAI5lP8IGE8xns+SXKQMB4CwXyKLySMSQlzkw4aEsZDyItS//3vf3H++efj1VdfDfvgRDbTR01p9/OkgXB73Jg+akrYDk3l1VHdXoqDBCSMh0Awn+IHCeNRQjZE0+HGXTVwKsDT0P8sAAu07Z0KcOPOGt0uEsZDIJhP8YOE8Rjv+STJQcJ4CATzKb6QMCYlzE06aEgYDyE/6Hzy5MlhH5TIJ693bpsn7oeK1WJFft8hyOudq/urI92VjS3fPKAXT1UT3JWNur9CU4KDBCSMh2BgPsUHEsajhGyItsOFFQ7saOdb9oI+PoBSADtU4IJjDl37kDAegoH5FB9IGI/RzgY6fIeE8RAMzKf4QcKYlDA36aAhYTwAUfj2PUVRkJKQrGvb5ISkNn+HSp2iQKVDUA5Ds3N07ft0hmQPwt7jB3Q5OGr1XaCcjq0OSM72PUasOASiM4yHekWJyP4jgd5ehNsHIPzxEC8ORo/HYByMzoZYcMipbkZRRAyA3QAKTzb7/XdKGA9SMkryvKSDBvOJDq1hPgVHvFxfSXDgNR4dWiPlGs/0RaluyRkomrIsrH28NukZXduNWzUOJ+pPIDOlK9bToUOHzMzMcNRamDPqLkwdcp0uh+LiYsx7c17YDjMKJqOwsDBmHYIllsfDxDUTI7L/SBBuRuntAxC58dDZHYwej8E4GJ0N4h08HiQ+NRJ1YR9doxZAokfF+snPApa2HwaUMB6kZBTzSb4D84kOrWE+hUZnv76S4MBrPDq0Rso1numLUicdNRi/cpqubZMTkvDapGdw/auz4HCG/kDUqobqlr/p0LHDhIIxWHzzfF1+rXmsZAnWlb6ty8Gx62TYxweAxaWr8HzDpph1CERnGA/1jpqw9x0p9GZUuH0Awh8P8eJg9HgMxsHobIgFhwMWBWmeUJ/M6Z90AM0WBeNX3RGSA2DOeJCSUcwn+Q7MJzq0hvkUHPFyfSXBgdd4dGiNlGs80xelVFVFgzO8W9UczkZd+1BVlQ5BOuyo2B2WW8t+ju72e4xgHNzpkbkd2ZWGmHYIls4wHiQQbi/09sF7bDoEdjB6PAbjYHQ2xILD7q6JGPx1eM9C8DIYwK5uibpy0szxEG0kz0s6aDCf6NAa5lNodPbrKwkOvMajQ2ukXOPp/cIc0skpP7IT2w5/Drcn1C/51nB73Cg79Bm2H92l28GalQRLpl339gBgybSH9YBxCQ4SkDAeCPEiYTxKyIZoO3yYnYyhCpCP8L59rwDAEAX4qKe+Z3BIGA+EeJEwHqOdDXT4DgnjgZDWSBiTEuYmHTQkjAeAi1KkA5aWrIRF0TdErBYrlpasDNvBntc1qttLcZCAhPFAiBcJ41FCNkTT4aXcDCSowGxo36KnBw+07RNUbX96kTAeCPEiYTzGez5JcpAwHghpjYQxKWFu0kFDwngIa1Fq9+7dOP/888OWIDIp2roRh09WwOV2hbSdy+3Coa+PovhT/5+/D4WEgelQ0mxAqHc3KoCSZkPCwPRO4SABCeMhFJhPnRsJ41FCNkTTYVtWEv7dMxnXAugHwBri9tZvt5sI4N89k7EtjN/0SRgPocB86txIGI/xnk+SHCSMh1BgPnV+JIxJCXOTDhoSxgPvlCLt0uhswjWLpqKu6VTQg9TldqGu6RQmLLwdjc7wnzWi2CxIvaovkGgJfrIqABK17RRb+ENcgoMEJIwHQrxIGI8SsiHaDjNH90SiVcGb0B5WHuzClPXb978FINGqYObonmF5SBgPhHiRMB6jnQ10+A4J44GQ1kgYkxLmJh00JIyHznG1TAzjyxMHcNmCSaioOQ4A7X7e1Pt6Rc1xXLZgEvZVHoyYgzUjEV2u7Q+lS3DP5Ve62NDl2v6wZiR2KgcJSBgPhHiRMB4lZEM0HfZnJGLG6J4YBOBDAL2/fb29kwvv672/ff9AADNG98T+CLhIGA+EeJEwHuM9nyQ5SBgPhLRGwpiUMDfpoBHt8WD6t++R2GNf5UGMfORKFJ47FtNHTUF+3yE+79l+ZBeWlqxE8aebDPmNjjUjEWmTz4JzTy2ayqvhqfI9hiXTDnteV+02SAPuTpLgIAEJ44EQLxLGo4RsiKZD0aB0KFCxaPNX2O5WUQTgaQClft47HNozpCZCu0Nq2uieKBoUuY84SxgPhHiRMB7jPZ8kOUgYD4S0RsKYlDA36aARzfHARSkSFI3OJqzashartqxFXu9cDMkehDmj7sJjJUvwWcUXKD+y03AHxWZBYm4GEnMz4K5shK0OmFEwGYtLV8GVBlO+4U6CgwQkjAdCvEgYjxKyIZoOqwedga3dk7Fw8zHccsyBGxVghwrsBlAL7aN6OQCGKtpDzT/ITsasSyNzh9TpSBgPhHiRMB7jPZ8kOUgYD4S0RsKYlDA36aARrfHQOW/lIIZSfmQn1pW+jaqqKqwrfTsq/wG1ZiUhOacrCgsLkZzTNSqLQRIcJCBhPBDiRcJ4lJAN0XDYn5GIKwv7YdT1/fH80AxYM+0otCiYDqDQosCaacfzQzMw6vr++Nk1/QxZkDodCeOBEC8SxmO85pNEBwnjgZDWSBiTEuYmHTTMHA+8U4oQQgghEWNbVhK2ZX0PAJCSkIz1k5/F+FV3oMHpiLIZIYQQQgiRBu+UIoQQQohxWHiqQQghhBBC/MMzRUIIIYQQQgghhBBiOoqqqqoZB3K73SgrK8OoS0ahQdX3pHZFUZCZ0hVVDdXQo602uAAVgAIoKfo+uUgHOtAh8g4pih0l75cgPz8fVqtVl0O4hJtR4dYACL8XdKADHYxxiHZGMZ/oQAc6tEes5xPQOc5l6UAHOvgSbD6Z/0wpFVBPufRuihP1J+hABzp0NodUu/5tI43OOkSsD3SgAx3kOUjJqHjvAx3oQAdfYjyfvt009s9l6UAHOvgSZD6ZvyilAEpq/K4W0oEOdPC3A12HNQadGdVZfuNKBzrQwd9O9G0WcZhPdKADHXx2om+ziMNrPDrQgQ4+OwjubaYvSinJVqRfP0DXtikJyVg/ZRnGr5ym61t8al/YC/WUC0qKDem30IEOdJDi4H6tQtdxjUBvRoVbAyD8XtCBDnQwxkFKRjGf6EAHOpxOrOcT0DnOZelABzr4Emw+8UHnhBBCCCGEEEIIIcR0uChF9OPxRNuAEEIIISR4eO5CCGkP5gMhUcH8Z0qRmGV4ZSNu3FmDCyscyKluRuJTI3HAomB310R8mJ2Ml3IzsC0rKdqahBBCCCEAeO5CCGkf5gMhMoiZRam83rkYmp2DzMxMTCgYgx0Vu1F+ZGe0teKC79c0Y+HmY7jomANOBUgYng9cPhhIS0NiXR2G7dqFwdvKMH17Df7dMxkzR/fE/oxEQ50kjAc6yHGINqyBHCT0QoKDu7IRjloHiouL4dh1Eu50BVaTT6wlOEjoRbSJ1xqcfu6yQwWKANQBSPOoGPx1E2492WTquYuEOUEHOQ7xOjdPJxp14LUNHeggy0H0olRSgh0TR4zD9FFTMLzPOS2vL755PgBg2+HPsbRkJYq2bkSjsylamp2aa7/4Bos2fwVroh245RYkzJ4NFBT4vC+htBR4+mmc/+or+OiV/ZgxuieKBqVH1EXCeKCDHIdowxrIQUIvJDioLg+ce2rRVF4NT5V2jHlvzmv5uSXTDnteVyQMTIdiM+bT+xIcJPQi2sR7DbznLs1uFc8DeFoFyvy8L18FZgO49pjDsHMXCXOCDnIc4n1ueolmHXhtQwc6yHMQ+0yps7v3x3/nbsDCGx/F0F45ft8ztFcOFt74KP47dwPOyupnsmHn59ovvsHSd44h4awBsH2+E3juOSAvz/+b8/KA556D7fOdSPj+2Vj2TgWu/eKbiLlIGA90kOMQbVgDOUjohQQHd00z6lbtg2PzVy0XW6fjqWqCY/NXqFu1D+6a5k7pIKEX0Sbea+A9d9nvVjEMwG0Aytt5b/m3Px8G4IBbjfi5i4Q5QQc5DvE+N71Esw68tqEDHWQ6hLQodfz4ccyePRsjR47ExRdfjPnz56OpKfKrdGd3749373kF2Rk9oCgKrBar3/dZLVYoioLsjB54795XO214R4OzapqxaPNXwMCBsHz0EdCrF6AogNV/L2C1aj/v1QuWLVuAAQOwaPNX+H4E/qMuYTzQQY5DR5iRUdJrEE9I6IUEB3dNM+pXH4Ba7wrq/Wq9C/WrD0T0okuCg4RedATzyXi85y5fAPghgCPfvt7eo4u9rx8BcCGAPUDEzl0kzAk6yHGQPjfj4RqP1zZ0oINch6AXpVRVxezZs+FwOPDSSy/hL3/5C/75z3/iqaeeioiIl6QEO9bcvRxp9lTYrMF9utBmtSHNnoq1M1cgKcEeUZ945ZnNx2BJtMPy9ttAWhqQkBDchgkJQFoaLO+8A2uiHQs3HwvLQ8J4oIMch44wI6Ok1yCekNALCQ6qy4NTbxwCmj2AGuxGAJq17VRX+N80JMFBQi86gvlkDs9sPoYmt4orANQCcAe5nfvb948B0OxWwz53kTAn6CDHQfrcjJdrPF7b0IEOch2CXpTat28fysrKMH/+fAwcOBDnnXceZs+ejX/84x9hS7Rm4ohx6NMtO+iCeLFZbeh7Zi8Unjs2oj7xyPATjbjomAMJk24A+vULPrS9JCQA/fvDdv0kXHTMgeGVjbpdJIwHOshx6AgzMkp6DeIJCb2Q4ODcUwu1zhX8xZYXFVDrXHDuqe0UDhJ60RHMJ+PxnrsUATiI4BekvLi/3a4ICPvcRcKcoIMcB+lzMx6u8XhtQwc6yHYIelEqKysLy5cvR2ZmZpvX6+vrw5ZozfRRU+BR9f1Wwu1xY/qoKRH1iUdu3FUDpwJg9mzAo/M3RG43MGsWnApw484a3S4SxgMd5Dh0hBkZJb0G8YSEXkhwaCqvjur2Uhwk9KIjmE/G4z13eRr6H5hqgbZ9uOcuEuYEHeQ4SJ+b8XCNx2sbOtBBtkPQ/91OT0/HxRdf3PL/PR4PVq5ciQsuuCBsCS95vXMxvM857X6GMRBWixX5fYcgr3duxJzikQsrHNpXoxYUtP8560BYrcCIEUgYno8Ljjl07ULCeKCDHIdAGJ1RsVCDeEFCLyQ4uCsb231gb7B4qprgDuM3vhIcJPQiEMwn47mwwoEd337Lnt4PXHkAlALYoUL3uYuEOUEHOQ6xMDfj4RqP1zZ0oINcBwAI7R6tVixYsACff/45Vq9eHdJ2iqIgJSHZ78+GZvt/ynuoDMkehL3HD/i8XqcoUAM4BCI5IanN36ESCw451c3A5YN17dt3ZzkYXL7N5zjB1EHCeKCDOQ71ihKR/bcm0hlldA2A8PMh3GyIFQcJvZDg4KjVd1J8OrY6IDnbf69jwcGMXkQ6o5hP+ujIIae6GUW699yW3QAKTzb7/XfGwpyggxwH5pNGtM9leW1DBzrIvsZTVFUN9VPWWLBgAZ5//nn85S9/wZgxY4Laxu12o6ysDBMnTkRRkf/ThszMTPTrF/4T3A8ePIiqqiqf18eNG4cTJ06ge/fu2LhxY9jH0YN4B48HI0aOBKZNA5YuDf9g06cDy5Zh63//C1i+uzEvmDpIGA90MMfBmwv5+fmw6v0NViuMyCijawDEQD4IcZDQCwkOxcXFmDdvXtgO999/PwoLC2PWwYxeRDKjmE/6adfh23OXpQDuiMBxngUwHfA5d+nQ4VskzAk6yHFgPmlE9VyW1zZ0oIP4a7yQ75R6+OGH8fLLL2PBggVBh1VrTjpqMH7lNL8/m1AwBotvnh/yPk/nsZIlWFf6ts/rVQ3VLX+35xCI5IQkvDbpGVz/6iw4nKHfzhsLDgcsChLr6nS5+VBbi2aLgvGr2p4mBlMHCeOBDuY41Dtqwt63F6MyyugaAOHnQ7jZECsOEnohwcGx62TYxweAxaWr8HzDpph1MKMXkcoo5pNx2XDAoiDNE/LvWf2SDvg9dwnkAMiYE3SQ48B80oj2uSyvbehAB9nXeCEtSi1cuBCvvPIKnnzySVxxxRWhbNqCqqpocPq/nXZHxW5d+/TZz9Hdfo/hvSmsI4dgcTgbde0jFhx2d03EsF27wnJrYdcu7OqW6HOcYOogYTzQwVyHcDEyo4yugffYHTkEi95siBUHCb2Q4OBOj8xHNlxpiGkHM3sRDswnDaOyYXfXRAz+OrznB3kZDPg9dwnkAMiYE3SQ48B80oj2uSyvbehAB9nXeEE/6PzLL7/E4sWLMW3aNIwYMQKVlZUtfyJF+ZGd2Hb4c7g9oX6Rr4bb40bZoc+w/WiEQidO+TA7Gc5tZUBpqfZNE3pwu4GtW+Es34aPeup7dpaE8UAHOQ6BMDqjYqEG8YKEXkhwsGYlwZJp1709AFgy7bBm6X/GjwQHCb0IBPPJeD7MTsZQBchHeN++VwBgiALd5y4S5gQd5DjEwtyMh2s8XtvQgQ5yHYAQ/rv93nvvwe12Y8mSJfjRj37U5k8kWVqyEhZF3+mE1WLF0pKVEfWJR17KzUCCCuDpp32epRA0VivwzDNIULX96UXCeKCDHIeOMCOjpNcgnpDQCwkO9ryuUd1eioOEXnQE88l4vOcusxHet+/NBsI+d5EwJ+ggx0H63IyHazxe29CBDrIdgj769OnTsXv3br9/IknR1o04fLICLrcrpO1cbhcOfX0UxZ/6/8w3CZ5tWUn4d89kuF59BTh4EHA6Q9uB0wkcOADXa6/i3z2TsS2M3zBJGA90kOPQEWZklPQaxBMSeiHBIWFgOpQ0GxDqp1QUQEmzIWFgeqdwkNCLjmA+GY/33OVaAP0AhPq4Z+u3200Ewj53kTAn6CDHQfrcjIdrPF7b0IEOsh303uFsGI3OJlyzaCrqmk4FXRiX24W6plOYsPB2NDoj8zyBeGfm6J5wNzfB89OfAnV1wYe30wnU1cFz+eVwNzdh5uieYXlIGA90kOMQbVgDOUjohQQHxWZB6lV9gURL8BddCoBEbTvFFv5pgAQHCb2INqyBdu6SaFXwJrSHlQe7MGX99v1vAUi0KmGfu0iYE3SQ48C5qRHtOvDahg50kOsgblEKAL48cQCXLZiEiprjANDuZxy9r1fUHMdlCyZhX+VB0xw7O/szEjFjdE9gzx54zj8fOHpU+0F7n8P2vn70qPb+vXsxY3RP7M9IDNtFwniggxyHaMMayEFCLyQ4WDMS0eXa/lC6BPfdJUoXG7pc2x/WCOSzJAcJvYg28V4D77nLIAAfAuj97evtnex6X+/97fsHAhE7d5EwJ+ggxyHe56aXaNaB1zZ0oINch5C+fc9M9lUexMhHrkThuWMxfdQU5Pcd4vOe7Ud2YWnJShR/uqnT/BZBEkWD0qFAxaLNX8J6Ti5s108CZs0CRozwfXNZGfDMM3C99irczU2YcXk2igaFf8uzFwnjgQ5yHKINayAHCb2Q4GDNSETa5LPg3FOLpvJqeKp8j2HJtMOe11X7OEsEfvsv0UFCL6JNvNfgu3OXr7DdraIIwNMASv28dzi0Z0hNhHaH1LTRPSN67iJhTtBBjkO8z00v0awDr23oQAeZDmIXpQDtVrJVW9Zi1Za1yOudiyHZgzBn1F14rGQJPqv4AuVHdkZbsdOzetAZ2No9GQs3H8NFL74I599eRMLwfCAnB0hPB2prgd274dxWhgQV+Cg7GbMu/X5EfotwOhLGAx3kOEQb1kAOEnohwUGxWZCYm4HE3Ay4KxthqwNmFEzG4tJVcKUhrG+QiiUHCb2INvFeg9bnLrccc+BGBdihArsB1EL7qF4OgKGK9lDzD7KTMevSyNwBcToS5gQd5DjE+9z0Es068NqGDnSQ5yB6Uao15Ud2Yu/xA5g65DqsK30bDU5HtJXihv0ZibiysB+GVzbixp01uODITgwu34ZEj4pmi4Jd3RLx0dAMvJSbEdaD/0JBwniggxyHaMMayEFCLyQ4WLOSkJydjMLCQjzfsCluHST0ItrEaw18zl2OOVB4srnNucvzPZNNPXeRMCfoIMchXufm6USjDry2oQMdZDnEzKIUiT7bspKwLet7AICUhGSsn/wsxq+6I27/I0oIIYQQ2fDchRDSHswHQmQg8kHnJEawcPgQQgghJIbguQshpD2YD4REBc48QgghhBBCCCGEEGI6iqqqqhkHcrvdKCsrw6hLRqFB1fekdkVRkJnSFVUN1dCjrTa4ABWAAigp+j65SAc60CHyDimKHSXvlyA/Px9Wq1WXQ7iEm1Hh1gAIvxd0oAMdjHGIdkYxn+hABzq0R6znE9A5zmXpQAc6+BJsPpn/TCkVUE+59G6KE/Un6EAHOnQ2h1S7/m0jjc46RKwPdKADHeQ5SMmoeO8DHehAB19iPJ++3TT2z2XpQAc6+BJkPpm/KKUASmr8rhbSgQ508LcDXYc1Bp0Z1Vl+40oHOtDB3070bRZxmE90oAMdfHaib7OIw2s8OtCBDj47CO5tpi9KKclWpF8/QNe2KQnJWD9lGcavnKbrWxFqX9gL9ZQLSooN6bfQgQ50kOLgfq1C13GNQG9GhVsDIPxe0IEOdDDGQUpGMZ/oQAc6nE6s5xPQOc5l6UAHOvgSbD7xQeeEEEIIIYQQQgghxHS4KEUIIYQQQgghhBBCTIeLUoQQQgghhBBCCCHEdGJmUSqvdy4mFIxBZmYmJhSMQV7vXDrQgQ50EIGEGtBBjoO7shGOXSdRXFwMx66TcFc2mu7AOmhIqEO0kVADCQ4SxiMdNDgeNCTUQQIS6kAHDQnzQoIDe6FhZh3M//a9EEhKsGPiiHGYPmoKhvc5p+X1xTfPBwBsO/w5lpasRNHWjWh0NtGBDnSII4doI6EGdJDjoLo8cO6pRVN5NTxV2jHmvTmv5eeWTDvseV2RMDAdis2Y3wexDhoS6hBtJNRAgoOE8UgHDY4HDQl1kICEOtBBQ8K8kODAXmhEqw6Kqvv7R0PD7XajrKwMl4wdDev12QHff3b3/lhz93L06ZYNj+qB1WL13afHDYtiweGTFZiw8HbsqzzY4T5bnkCfGtwT6OlABzqY4+B+rQLvb9qM/Px8WK2++zODUDLKiBoAofWCDnIc3DXNOPXGIah1roD7VdJsSL2qL6wZiRF1YB00jKpDtDOK+RS6g4TxSAcNjgcN5pNGZz2XjUUHI+ZFLDqwFxrRvMYT+fG9s7v3x7v3vILsjB5QFMVvQQDAarFCURRkZ/TAe/e+irOy+tGBDnTo5A7RRkIN6CDHwV3TjPrVB6DWBz6JAAC13oX61QfgrmmOmAProCGhDtFGQg0kOEgYj3TQ4HjQkFAHCUioAx00JMwLCQ7shUa06xDyotTBgwdx++23o6CgAJdccgmWL18eEREvSQl2rLl7OdLsqbBZg/t0oc1qQ5o9FWtnrkBSgp0OdKBDJ3UIBPOJDmY6qC4PTr1xCGj2AMHec6wCaNa2U12esB1YBw0JdQgE88kcBwnjkQ4aHA8aEuoQCKPzCZBRBzpoSJgXEhzYCw0JdQhpUcrj8WD69Ono2rUr1qxZg4ceeghLlizB+vXrwxbxMnHEOPTplh10QbzYrDb0PbMXCs8dSwc60KGTOnQE84kOZjs499Rqt1mH+iF4FVDrXHDuqQ3bgXXQkFCHjmA+mecgYTzSQYPjQUNCHTrCjHwCZNSBDhoS5oUEB/ZCQ0IdQlqUqqqqQm5uLh588EH0798fo0aNwoUXXoitW7eGLeJl+qgp8Kj6VvzcHjemj5pCBzrQoZM6dATziQ5mOzSVV0d1e4B18CKhDh3BfDLPQcJ4pIMGx4OGhDp0hBn5BMioAx00JMwLCQ7shYaEOoS0KNW9e3c89dRT6NKlC1RVxdatW/Hxxx9j5MiRYYsA2tcODu9zTrufYQyE1WJFft8hYX1dIR3oQAeZDoFgPtHBTAd3ZWPLN6PoxVPVFNZX/LIOGhLqEAjmkzkOEsYjHTQ4HjQk1CEQRucTIKMOdNCQMC8kOLAXGhLqAACh3aPVitGjR6OiogKXXnopxowZE/R2iqIgJSHZ78+GZufo1WnDkOxB2Hv8gM/rdYoClQ50oIM4h3pFicj+vejNJ6D9OhhdAyBwL+ggx8FR64iIg60OSM72P+9Yh+AczKhDJDOK+WScg4TxSAcNjgcN5pNGPJzLxoqD0fMiVhzYCw0p13iKqqqhfoIRALB9+3ZUVVXhwQcfxOWXX465c+d2+H7v14VOnDgRRUVFft+TmZmJfv3Cf4L7wYMHUVVV5fP6uHHjcOLECXTv3h0bN26kAx3oIMTBmwuR+jrjUPMJCJxRRtcACNwLOshxKC4uxrx588J2uP/++1FYWKjLgXXQMKMOkcwo5pNxDhLGIx00OB40mE8a8XAuGysORs+LWHFgLzSkXOPpvlNq2LBhAICmpibcc889+M1vfoPExMSA25101GD8yml+fzahYAwW3zxfr1ILj5UswbrSt31er2qobvmbDnSggxyHekdN2Ptujd58AtrPKKNrAATuBR3kODh2nQz7+ACwuHQVnm/YpMuBddAwow6RzCjmk3EOEsYjHTQ4HjSYTxrxcC4bKw5Gz4tYcWAvNKRc44W0KFVVVYWysjL85Cc/aXltwIABcDqdqK+vR7du3QLuQ1VVNDj936q2o2J3KDrtsuPobr/H8N4URgc60EGmQzhEIp+8Lv4cja6B99h0iA0Hd3pkPi7hSgPrgNipg16YT+Y4SBiPdNDgeNBgPmnE07msdAej50WsOLAXGlKu8UJ60PmRI0cwc+ZMHD9+/DuBHTvQrVu3oAOrI8qP7MS2w5/D7XHr2t7tcaPs0GfYfnQXHehAh07mEAjmEx3MdLBmJcGSade9PQBYMu2wZiXp3p510JBQh0Awn8xxkDAe6aDB8aAhoQ6BMDqfABl1oIOGhHkhwYG90JBQByDERalhw4ZhyJAhuP/++7F3716UlJRgwYIFuPPOO8OSaM3SkpWwKCFptWC1WLG0ZCUd6ECHTurQEcwnOpjtYM/rGtXtAdbBi4Q6dATzyTwHCeORDhocDxoS6tARZuQTIKMOdNCQMC8kOLAXGhLqENLRrVYrFi9ejOTkZEyaNAm/+93vcNNNN+Hmm28OW8RL0daNOHyyAi63K6TtXG4XDn19FMWf+v/MNx3oQIfYd+gI5hMdzHZIGJgOJc0GhHr3tQIoaTYkDEwP24F10JBQh45gPpnnIGE80kGD40FDQh06wox8AmTUgQ4aEuaFBAf2QkNCHUJeEuvRowcWLlyIrVu34oMPPsCdd94JJYJfRdrobMI1i6airulU0IVxuV2oazqFCQtvR6OziQ50oEMndQgE84kOZjooNgtSr+oLJFqCP5lQACRq2yk2fb+Vag3roCGhDoFgPpnjIGE80kGD40FDQh0CYXQ+ATLqQAcNCfNCggN7oSGhDuH/KwzgyxMHcNmCSaio0T7b3N5nHL2vV9Qcx2ULJmFf5UE60IEOndwh2kioAR3kOFgzEtHl2v5QugT3vSFKFxu6XNsf1ozgvs0oGFgHDQl1iDYSaiDBQcJ4pIMGx4OGhDpIQEId6KAhYV5IcGAvNKJdh5C+fc9M9lUexMhHrkThuWMxfdQU5Pcd4vOe7Ud2YWnJShR/usmQ3yLQgQ50kOkQbSTUgA5yHKwZiUibfBace2rRVF4NT5XvMSyZdtjzumq3aUfgt1qnwzpoSKhDtJFQAwkOEsYjHTQ4HjQk1EECEupABw0J80KCA3uhEc06iF2UArRbyVZtWYtVW9Yir3cuhmQPwpxRd+GxkiX4rOILlB/ZSQc60CFOHaKNhBrQQY6DYrMgMTcDibkZcFc2wlYHzCiYjMWlq+BKQ1jfjBIsrIOGhDpEGwk1kOAgYTzSQYPjQUNCHSQgoQ500JAwLyQ4sBca0aqDyI/v+aP8yE6sK30bVVVVWFf6dlRCmw50oINMh2gjoQZ0kONgzUpCck5XFBYWIjmnqyknEafDOmhIqEO0kVADCQ4SxiMdNDgeNCTUQQIS6kAHDQnzQoIDe6FhZh1iZlGKEEIIIYQQQgghhHQeuChFCCGEEEIIIYQQQkyHi1KEEEIIIYQQQgghxHQUVVVVMw7kdrtRVlaGUZeMQoOq70ntiqIgM6UrqhqqoUdbbXABKgAFUFL0PeOdDnSgQ+QdUhQ7St4vQX5+PqxWqy6HcAk3o8KtARB+L+hABzoY4xDtjGI+0YEOdGiPWM8noHOcy9KBDnTwJdh8Mv/b91RAPeXSuylO1J+gAx3o0NkcUu36t400OusQsT7QgQ50kOcgJaPivQ90oAMdfInxfPp209g/l6UDHejgS5D5ZP6ilAIoqfG7WkgHOtDB3w50HdYYdGZUZ/mNKx3oQAd/O9G3WcRhPtGBDnTw2Ym+zSIOr/HoQAc6+OwguLeZviilJFuRfv0AXdumJCRj/ZRlGL9yGhqcjpC3r31hL9RTLigpNqTfQgc60EGKg/u1Cl3HNQK9GRVuDYDwe0EHOtDBGAcpGcV8ogMd6HA6sZ5PQOc4l6UDHejgS7D5xAedE0IIIYQQQgghhBDT4aIUIYQQQgghhBBCCDEdLkoRQgghhBBCCCGEENOJmUWpvN65mFAwBpmZmZhQMAZ5vXPpEMcO7spGOHadRHFxMRy7TsJd2Wi6A+ugIaEO0UZCDeigIWFOSHBgLzQk1CHaSKiBBAcJ45EOGhwPGhLqIAEJdZDgwDGpwTpoxFsdzP/2vRBISrBj4ohxmD5qCob3Oafl9cU3zwcAbDv8OZaWrETR1o1odDbRoZM7qC4PnHtq0VReDU+Vdox5b85r+bkl0w57XlckDEyHYjNmvZV10JBQh2gjoQZ00JAwJyQ4sBcaEuoQbSTUQIKDhPFIBw2OBw0JdZCAhDpIcOCY1GAdNOK5Doqq+/tHQ8PtdqOsrAyXjB0N6/XZAd9/dvf+WHP3cvTplg2P6oHVYvXdp8cNi2LB4ZMVmLDwduyrPNjhPlueQJ8a3BPo6SDHwV3TjFNvHIJa5wr4XiXNhtSr+sKakRhRB9ZBw4g6uF+rwPubNiM/Px9Wq+/+zCCUjDKiBkBovaDDt/s3YE7EogN7oWFUHaKdUcyn0B0kjEc6aHA8aDCfNCScT0tw6Kzn9KyDPofOWodg80nkx/fO7t4f797zCrIzekBRFL8FAQCrxQpFUZCd0QPv3fsqzsrqR4dO6OCuaUb96gNQ6wNPUgBQ612oX30A7prmiDmwDhoS6hBtJNSADhoS5oQEB/ZCQ0Idoo2EGkhwkDAe6aDB8aAhoQ4SkFAHCQ4ckxqsgwbrEMai1PTp0zFnzpyISLQmKcGONXcvR5o9FTZrcJ8utFltSLOnYu3MFUhKsNOhEzmoLg9OvXEIaPYAwd7TpwJo1rZTXZ6wHVgHDQl1CAUjMkpCDeigIWFOSHBgLzQk1CEUmE/GOUgYj3TQ4HjQkFCHUOA1nrEOHJMarIMG66Cha1Fqw4YNKCkpCfvg/pg4Yhz6dMsOuiBebFYb+p7ZC4XnjqVDJ3Jw7qnVbmMM9UOmKqDWueDcUxu2A+ugIaEOwWJURkmoAR00JMwJCQ7shYaEOgQL88lYBwnjkQ4aHA8aEuoQLLzGM96BY1KDddBgHTRCXpSqqanBE088gWHDhoV9cH9MHzUFHlXfip/b48b0UVPo0Ikcmsqro7o9wDp4kVCHYDAyoyTUgA4aEuaEBAf2QkNCHYKB+WS8g4TxSAcNjgcNCXUIBl7jmePAManBOmiwDhohL0o9/vjjuPrqqzFgQOCHZYVKXu9cDO9zTrufYQyE1WJFft8hYX1dIR3kOLgrG1u+eUAvnqqmsL5Ck3XQkFCHYDEqoyTUgA4aEuaEBAf2QkNCHYKF+WSsg4TxSAcNjgcNCXUIFl7jGe/AManBOmiwDt8R0j1aH374IT755BOsX78eDz74oK4DKoqClIRkvz8bmp2ja5+nMyR7EPYeP+Dzep2iQKVDzDg4ah0RcbDVAcnZvsdgHYJ3MLoO9YoSkf0bmVFG1wAI3As6aBg9J2LFgb3QMKMOkcgo5pPxDhLGIx00OB40mE8aEs6nJTjEwzk96xC8QzzUIdh8CnpRqqmpCX/4wx/wwAMPICkpKWjB0+mWnIGiKcv8/iwzM1P3flszZ9RdmDrkOp/Xx60ahxP1J5CZ0hXr6SDeobi4GPPenBe2w4yCySgsLNTlwDpoGF2HiWsmhr1vozPK6BoAgXtBBw2j50SsOLAXGmbUIdyMYj6Z4yBhPNJBg+NBg/mkIeF8WoJDPJzTsw7BO8RDHYLNp6AXpRYuXIihQ4fi4osvDt7ODycdNRi/cprfn00oGIPFN88Pa/8A8FjJEqwrfdvn9aqG6pa/6SDfwbHrZNjHB4DFpavwfMMmXQ6sg4bRdah31IS9b6MzyugaAIF7QQcNo+dErDiwFxpm1CHcjGI+meMgYTzSQYPjQYP5pCHhfFqCQzyc07MOwTvEQx2CzaegF6U2bNiAqqoqFBQUAACam5sBAG+99RZKS0uD3Q1UVUWD0/+tajsqdge9n47YcXS332OoqkqHGHJwp0fmI12uNLAOiI06hIPRGWV0DbzHpkNgB6PnRKw4sBcaZtZBL8wncxwkjEc6aHA8aDCfNCScT0twiKdzetaBdWjtEIigF6X+/ve/w+Vytfz/P/3pTwCAe+65J9hdBKT8yE5sO/w5hvbK0fWwLbfHje1HdmH70V106AQO1qwkWDLtYT0AzpJphzVL/63IrIOGhDoEwuiMklADOmhImBMSHNgLDQl1CATzyRwHCeORDhocDxoS6hAIXuOZ58AxqcE6aLAO3xH0t+/16tUL/fr1a/mTmpqK1NRU9OvXLyyB01lashIWJeQvBQSgPf19aclKOnQiB3te16huD7AOXiTUoSPMyCgJNaCDhoQ5IcGBvdCQUIeOYD6Z5yBhPNJBg+NBQ0IdOoLXeOY6cExqsA4arIOGvqMbSNHWjTh8sgIutyvwm1vhcrtw6OujKP7U/2e+6RCbDgkD06Gk2YBQ725UACXNhoSB6WE7sA4aEuoQbSTUgA4aEuaEBAf2QkNCHaKNhBpIcJAwHumgwfGgIaEOEpBQBwkOHJMarIMG66Che1Hqsccew2OPPRa2wOk0OptwzaKpqGs6FXRhXG4X6ppOYcLC29Ho1H/7Gx3kOSg2C1Kv6gskWoKfrAqARG07xRb+uivroCGhDqFgREZJqAEdNCTMCQkO7IWGhDqEAvPJOAcJ45EOGhwPGhLqEAq8xjPWgWNSg3XQYB00xN0pBQBfnjiAyxZMQkXNcQDaZxX94X29ouY4LlswCfsqD9KhEzpYMxLR5dr+ULoE9wg0pYsNXa7tD2tGYsQcWAcNCXWINhJqQAcNCXNCggN7oSGhDtFGQg0kOEgYj3TQ4HjQkFAHCUiogwQHjkkN1kGDdQjhQedms6/yIEY+ciUKzx2L6aOmIL/vEJ/3bD+yC0tLVqL4002G/BaBDnIcrBmJSJt8Fpx7atFUXu33gXCWTDvseV212yAjsGp8OqyDhoQ6RBsJNaCDhoQ5IcGBvdCQUIdoI6EGEhwkjEc6aHA8aEiogwQk1EGCA8ekBuugEe91ELsoBWi3kq3ashartqxFXu9cDMkehDmj7sJjJUvwWcUXKD+ykw5x5KDYLEjMzUBibgbclY2w1QEzCiZjcekquNIQ1jcPBAvroCGhDtFGQg3ooCFhTkhwYC80JNQh2kiogQQHCeORDhocDxoS6iABCXWQ4MAxqcE6aMRzHUR+fM8f5Ud2Yl3p26iqqsK60rejEtp0kONgzUpCck5XFBYWIjmnqymT9HRYBw0JdYg2EmpABw0Jc0KCA3uhIaEO0UZCDSQ4SBiPdNDgeNCQUAcJSKiDBAeOSQ3WQSPe6hAzi1KEEEIIIYQQQgghpPPARSlCCCGEEEIIIYQQYjpclCKEEEIIIYQQQgghpqOoqqqacSC3242ysjKMumQUGlR9T2pXFAWZKV1R1VANPdpqgwtQASiAkqLvGe90oAMdIu+QothR8n4J8vPzYbVadTmES7gZFW4NgPB7QQc60MEYh2hnFPOJDnSgQ3vEej4BneNclg50oIMvweaT+d++pwLqKZfeTXGi/gQd6ECHzuaQate/baTRWYeI9YEOdKCDPAcpGRXvfaADHejgS4zn07ebxv65LB3oQAdfgswn8xelFEBJjd/VQjrQgQ7+dqDrsMagM6M6y29c6UAHOvjbib7NIg7ziQ50oIPPTvRtFnF4jUcHOtDBZwfBvc30RSkl2Yr06wfo2jYlIRnrpyzD+JXT0OB0hLx97Qt7oZ5yQUmxIf0WOtCBDlIc3K9V6DquEejNqHBrAITfCzrQgQ7GOEjJKOYTHehAh9OJ9XwCOse5LB3oQAdfgs0nPuicEEIIIYQQQgghhJgOF6UIIYQQQgghhBBCiOlwUYoQQgghhBBCCCGEmI75DzrXSV7vXAzNzkFmZiYmFIzBjordKD+y01QHd2UjHLUOFBcXw7HrJNzpCqxZSXHnwF7QoTUSxkO0kVADCWNBggN7QYfWSBgP0UZCDSSMBQkO7AUdWiNhPEhAQh0kjAcJDhJ6IcFBQi8kOJjZC9GLUkkJdkwcMQ7TR03B8D7ntLy++Ob5AIBthz/H0pKVKNq6EY3OJkMcVJcHzj21aCqvhqdKO8a8N+e1/NySaYc9rysSBqZDsRlz45kEB/aCDq2RMB6ijYQaSBgLEhzYCzq0RsJ4iDYSaiBhLEhwYC/o0BoJ40ECEuogYTxIcJDQCwkOEnohwSFavRC7KHV29/7/n713j4+ivve4P7O7yeZuwASP4arcRCAkoqi1FsW2FBTEgFIRfdoqWBQ55zlH67W2PSpYqT0+imBBKraINwioBaxWal7aKq2YEFTAcAeDkJjE3DaX3Z3njzExYTfZ2Zmd2e/uft6vFy/azc7Mm+/vOx9nfpkLNt7+LAb2zYNf9Qf9zpj+I7Hshkdw95TbMWPZzThQdTiiDr66NjS9fgRqg7fH7/irW+HZ9iVa/l2N9OmD4MxOjjsHjgUduiKhH6KNhBpI6AUJDhwLOnRFQj9EGwk1kNALEhw4FnToioR+kICEOkjoBwkOEsZCgoOEsZDgEM2xEPlMqaH9huBvd76EvOwzoCgKnA5n0O85HU4oioK87DPwzl0v4+zcwRFz8NW1oXH9IaiNPTdGV9RGLxrXH4Kvri2uHDgWdOiKhH6INhJqIKEXJDhwLOjQFQn9EG0k1EBCL0hw4FjQoSsS+kECEuogoR8kOEgYCwkOEsZCgkO0xyLsSam3334bI0eO7PZn0aJFEZEBtEvGNt7+LDLd6XA59V3I5XK6kOlOx6aFq5GS5DbtoHr9aHr9CNDmB1S9CwFo05ZTvcFnFmPNgWNBh65I6IdQMJ96WgjsR3As4tlBQj+EgvnU00JgP4JjEc8OEvohFFbnEyCjDhL6QYKDhLGQ4CBhLCQ4SBiLsCel9u3bh8svvxzvv/9+55+HH37YtEgHM8dPxcC+eboL0oHL6cKg0/uj6Lwpph3aK+q1S+f0NkYHKqA2eNFeUR8XDhwLOnRFQj+EgvnUC+xHAByLeHWQ0A+hYD71AvsRAMciXh0k9EMorM4nQEYdJPSDBAcJYyHBQcJYSHCQMBZhT0rt378fI0aMQG5ubuefrKws0yIdzJ84t8d7GEPh8/swf+Jc0w6t5bVRXV6KA8eCDl2R0A+hYD5Zv7wUB44FHboioR9CwXyyfnkpDhwLOnRFQj+Ewup8AmTUQUI/SHCQMBYSHCSMhQQHCWNhaFJqyJAhpjccjPwBozBu4Lk93sMYCqfDiYJBo5E/YJRhB19VS+fT7o3ir26Fr6olph04FnToioR+0APzKTTsR45FvDlI6Ac9MJ9Cw37kWMSbg4R+0IOV+QTIqIOEfpDgIGEsJDhIGAsJDhLGAgjz7XuqquLgwYN4//338Yc//AE+nw8/+tGPsGjRIiQn63v6u6IoSEtKDfqzMXkjw9HpkdF5I7DvxKGAzxsUBWoIB0+9JyIOrgYgNS9wG7HiwLGgQ1es7odGRTG97kjkE9BzHayuARB6LKzuhVhx4FjQoSt29IPZjGI+6Yf9qMGxiA8H5pMGzyvkOEgYCwkOEsZCgoOUc7ywJqUqKyvh8XiQnJyMJ554AseOHcPDDz+MlpYWPPDAA7rW0Tc1Gxvmrgr6s5ycnHB0euSeiQtwy+hrAz6fum4qTjaeRE5aH7zRg0NxcTEWv7nYtMNthXNQVFQUsw4cCzp0xep+mLlxpul1RyKfgJ4zyuoaAKHHwupeiBUHjgUdumJHP5jNKOaTftiPGhyL+HBgPmnwvEKOg4SxkOAgYSwkOEg5x1NUVQ3rsVp1dXU47bTToHwz6/XXv/4Vd911F0pLS+F09nzZl8/nQ1lZGS6fegUy5pwd9DszCidj+U1LwtEJyoI/3YPXSt8K+PzEs5/A39gOR0YSzrhlTNBlPXtqUPfmYdMO2VOGIHVkn5h14FjQoStW90PjugP4+5Z3UFBQ0GuOhMJoPgGhM8rqGgChx8LqXogVB44FHbpiRz9EIqOYT/pgP2pwLOLDgfmkwfMKOQ4SxkKCg4SxkOAg5RwvvEesA8jOzu72/4cOHYrW1lZ8/fXX6Nu3b8jlVVVFc3vwS9U+qdwbrk7w9XyxN+g2OubfenPwZZm/jQgAvJmIaQeOBR26Ylc/mMVsPnW4BHO0ugYd2+7NwepeiBUHjgUdumJnP5iB+aQP9uM36+FYxIUD80mD5xVyHCSMhQQHCWMhwUHKOV5YDzp/7733cOGFF8Lj+XaDu3fvRnZ2tu7A6o3yY7ux8+hn8Pl9hpb3+X0oO/Ipdn2xx7CDMzcFjhy34eUBwJHjhjM3JaYdOBZ06IqEfggF80kf7EeORbw5SOiHUDCf9MF+5FjEm4OEfgiF1fkEyKiDhH6Q4CBhLCQ4SBgLCQ4SxgIIc1KqsLAQbrcbDzzwAA4cOICSkhI89thjuOWWW0xJdGVlyVo4lLBfCghAe/r7ypK1ph3c+cEv0bVreSkOHAs6dEVCP/QG88me5aU4cCzo0BUJ/dAbzCd7lpfiwLGgQ1ck9ENv2JFPgIw6SOgHCQ4SxkKCg4SxkOAgYSzC2npGRgZWr16NmpoazJw5E/fffz9mz54d0dDasGMLjtZUwuvzhrWc1+fFka++QPHHW007JA3PgpLpAsK9ok4BlEwXkoZnxYUDx4IOXZHQD73BfAoB+xEAxyJeHST0Q28wn0LAfgTAsYhXBwn90Bt25BMgow4S+kGCg4SxkOAgYSwkOEgYi7CnxIYPH47nnnsOpaWleP/997Fw4cLOh+JFgpb2Vlzz9C1oaG3SXRivz4uG1ibMWHYzWtpbTTsoLgfSpw8Ckh36G0QBkKwtp7iMzTRKc+BY0KErEvohFMynnhYC+xEci3h2kNAPoWA+9bQQ2I/gWMSzg4R+CIXV+QTIqIOEfpDgIGEsJDhIGAsJDhLGwvy/wgL2nzyEK5bORmXdCQDo8R7Hjs8r607giqWzcaDqcMQcnNnJyJg1BEqGvmfBKxkuZMwaAmd2clw5cCzo0BUJ/RBtJNRAQi9IcOBY0KErEvoh2kiogYRekODAsaBDVyT0gwQk1EFCP0hwkDAWEhwkjIUEh2iPRdhv37OLA1WHMeHhK1F03hTMnzgXBYNGB3xn17E9WFmyFsUfb7XktwjO7GRkzjkb7RX1aC2vhb86cBuOHDfc+X20S+8iMFMp0YFjQYeuSOiHaCOhBhJ6QYIDx4IOXZHQD9FGQg0k9IIEB44FHboioR8kIKEOEvpBgoNgk9iGAAD//UlEQVSEsZDgIGEsJDhEcyzETkoB2qVk67Zvwrrtm5A/YBRG543APRMX4NGSFfi08nOUH9ttuYPiciB5VDaSR2XDV9UCVwNwW+EcLC9dB28mTD3tPpYcOBZ06IqEfog2EmogoRckOHAs6NAVCf0QbSTUQEIvSHDgWNChKxL6QQIS6iChHyQ4SBgLCQ4SxkKCQ7TGQuTte8EoP7Ybr5W+herqarxW+lZUQtuZm4LUkX1QVFSE1JF9bGkMiQ4cCzp0RUI/RBsJNZDQCxIcOBZ06IqEfog2EmogoRckOHAs6NAVCf0gAQl1kNAPEhwkjIUEBwljIcHBzrGImUkpQgghhBBCCCGEEBI/cFKKEEIIIYQQQgghhNgOJ6UIIYQQQgghhBBCiO0oqqqqdmzI5/OhrKwMEy+biGbV2JPaFUVBTlofVDfXwoi22uwFVAAKoKQZe8Y7HehAh8g7pClulLxbgoKCAjidTkMOZjGbUWZrAJgfCzrQgQ7WOEQ7o5hPdKADHXoi1vMJiI9jWTrQgQ6B6M0n+9++pwJqk9foojjZeJIOdKBDvDmku40vG2kM1iFi40AHOtBBnoOUjEr0caADHegQSIzn0zeLxv6xLB3oQIdAdOaT/ZNSCqCkJ+5sIR3oQIdgKzC0WWswmFHx8htXOtCBDsFWYmyxiMN8ogMd6BCwEmOLRRye49GBDnQIWIG+r9k+KaWkOpF13TBDy6YlpeKNuaswbe08NLd7wl6+fs0+qE1eKGkuZP2EDnSggxQH3yuVhrZrBUYzymwNAPNjQQc60MEaBykZxXyiAx3ocCqxnk9AfBzL0oEOdAhEbz7xQeeEEEIIIYQQQgghxHY4KUUIIYQQQgghhBBCbIeTUoQQQgghhBBCCCHEdux/0LlB8geMwpi8kcjJycGMwsn4pHIvyo/tTjgHX1ULPPUeFBcXw7OnBr4sBc7cFDrQIWoOEvaLaCOhBhIcJPQjHejQFQn7RbSRUAMJDhL6kQ506IqE/UICEuogwUFCT9JBg/2gYWcdRE9KpSS5MXP8VMyfOBfjBp7b+fnym5YAAHYe/QwrS9Ziw44taGlvjVsH1etHe0U9Wstr4a/WtrH4zcWdP3fkuOHO74Ok4VlQXNZc/EYHOnRFwn4RbSTUQIKDhH6kAx26ImG/iDYSaiDBQUI/0oEOXZGwX0hAQh0kOEjoSTposB80olUHsZNSQ/sNwcbbn8XAvnnwq/6g3xnTfySW3fAI7p5yO2YsuxkHqg7HnYOvrg1Nrx+B2uDt8Tv+6lZ4tn2Jln9XI336IDizk+lAB8scJOwX0UZCDSQ4SOhHOtChKxL2i2gjoQYSHCT0Ix3o0BUJ+4UEJNRBgoOEnqSDBvtBI5p1EPlMqaH9huBvd76EvOwzoCgKnA5n0O85HU4oioK87DPwzl0v4+zcwXHl4KtrQ+P6Q1Abe27OrqiNXjSuPwRfXRsd6GCJg4T9ItpIqIEEBwn9SAc6dEXCfhFtJNRAgoOEfqQDHboiYb+QgIQ6SHCQ0JN00GA/aES7DmFPSrW1teE3v/kNLrjgAnznO9/B73//e6iqGhEZQLtkbOPtzyLTnQ6XU9+FXC6nC5nudGxauBopSe64cFC9fjS9fgRo8wN6y6sCaNOWU73BZzfpQAejSNgvQsF8ssdBQj/SgQ5dkbBfhIL5ZI+DhH6kAx26ImG/CIXV+QTIqIMEBwk9SQcN9oOGhDqEPSn18MMP45///CdWr16Nxx9/HK+88gpefvll0yIdzBw/FQP75ukuSAcupwuDTu+PovOmxIVDe0W9dvleuP89UAG1wYv2ino60CGiDhL2i1Awn+xxkNCPdKBDVyTsF6FgPtnjIKEf6UCHrkjYL0JhdT4BMuogwUFCT9JBg/2gIaEOYU1K1dXVYcOGDXjooYeQn5+Piy++GD/72c+wc+dO0yIdzJ84t8d7GEPh8/swf+LcuHBoLa+N6vJ0oMOpSNgveoP5ZJ+DhH6kAx26ImG/6A3mk30OEvqRDnToioT9ojfsyCdARh0kOEjoSTposB80JNQhrEmpHTt2ICMjAxMmTOj8bP78+ViyZIlpEUB77eC4gef2eA9jKJwOJwoGjUb+gFEx7eCraul84r5R/NWt8FW10IEOEXGQsF+Egvlkj4OEfqQDHboiYb8IBfPJHgcJ/UgHOnRFwn4RCqvzCZBRBwkOEnqSDhrsBw0JdQDCfPve0aNH0b9/f2zatAnPPPMM2tvbUVRUhAULFsDh0De/pSgK0pJSg/5sTN7IcHR6ZHTeCOw7cSjg8wZFgRoDDp56T0QcXA1Aal7gNuhAh3AdrN4vGhXF9LojkU9Az3WwugZA6LGQ4GB1P9KBDuE62LFfmM0o5pM9DhL6kQ506ArzSUPC+ZUEBwnH9HTQYD9oSDnHC2tSqrm5GYcPH8ZLL72EJUuWoKqqCg8++CBSU1Pxs5/9TNc6+qZmY8PcVUF/lpOTE45Oj9wzcQFuGX1twOdT103FycaTyEnrgzcEOxQXF2Pxm4tNO9xWOAdFRUV0oINpB6v3i5kbZ5pedyTyCeg5o6yuARB6LCQ4WN2PdKBDuA527BdmM4r5ZI+DhH6kAx26wnzSkHB+JcFBwjE9HTTYDxpSzvHCmpRyuVxobGzE448/jv79+wMAKisr8eKLL+oOrRpPHaatnRf0ZzMKJ2P5TeYvFX20ZAVeK30r4PPq5trOvyU7ePbUmN4+ACwvXYfnmrfSgQ6mHazeLxo9dabXHYl8AnrOKKtrAIQeCwkOVvcjHegQroMd+4XZjGI+2eMgoR/pQIeuMJ80JJxfSXCQcExPBw32g4aUc7ywJqVyc3Phdrs7AwsAzjrrLBw/flz3OlRVRXN78EvVPqncG45Oj3zyxd6g2+h4tal0B1+W+VuZAMCbCTrQISIOdu0XZohEPnW4BHO0ugYd25buYHU/0oEO4TrYuV8Yhflkj4OEfqQDHbrCfNKQcH4lwUHCMT0dNNgPGlLO8cJ60Pm4cePQ2tqKgwcPdn524MCBbiFmhvJju7Hz6Gfw+X2Glvf5fSg78il2fbEnph2cuSlw5LgNLw8Ajhw3nLkpdKBDRBwk7BehYD7Z4yChH+lAh65I2C9CwXyyx0FCP9KBDl2RsF+Ewup8AmTUQYKDhJ6kgwb7QUNCHYAwJ6XOPvtsXHbZZbj33nuxZ88evPfee1i5ciWuv/56UxJdWVmyFg4lLK1OnA4nVpasjQsHd36fqC5PBzqcioT9ojeYT/Y5SOhHOtChKxL2i95gPtnnIKEf6UCHrkjYL3rDjnwCZNRBgoOEnqSDBvtBQ0Idwt767373OwwaNAjXX3897r77btxwww248cYbTYt0sGHHFhytqYTX5w1rOa/PiyNffYHij4Pf8x1rDknDs6BkuoBwr+pTACXThaThWXSgQ0QdJOwXoWA+2eMgoR/pQIeuSNgvQsF8ssdBQj/SgQ5dkbBfhMLqfAJk1EGCg4SepIMG+0FDQh3CnpTKzMzEY489htLSUvzzn//EwoULoUTgde4dtLS34pqnb0FDa5Puwnh9XjS0NmHGspvR0t4aFw6Ky4H06YOAZIf+JlUAJGvLKS5js510oENPSNgvQsF8ssdBQj/SgQ5dkbBfhIL5ZI+DhH6kAx26ImG/CIXV+QTIqIMEBwk9SQcN9oOGhDqY/1dYwP6Th3DF0tmorDsBAD3e49jxeWXdCVyxdDYOVB2OKwdndjIyZg2BkqHvefRKhgsZs4bAmZ1MBzpY4iBhv4g2EmogwUFCP9KBDl2RsF9EGwk1kOAgoR/pQIeuSNgvJCChDhIcJPQkHTTYDxrRrkNYb9+zkwNVhzHh4StRdN4UzJ84FwWDRgd8Z9exPVhZshbFH2+15LcIEhyc2cnInHM22ivq0VpeC3914DYcOW648/tol/9FYLaUDnToDQn7RbSRUAMJDhL6kQ506IqE/SLaSKiBBAcJ/UgHOnRFwn4hAQl1kOAgoSfpoMF+0IhmHcROSgHapWTrtm/Cuu2bkD9gFEbnjcA9Exfg0ZIV+LTyc5Qf250QDorLgeRR2UgelQ1fVQtcDcBthXOwvHQdvJkw9cR9OtDBCBL2i2gjoQYSHCT0Ix3o0BUJ+0W0kVADCQ4S+pEOdOiKhP1CAhLqIMFBQk/SQYP9oBGtOoi8fS8Y5cd247XSt1BdXY3XSt+KSmhLcHDmpiB1ZB8UFRUhdWQfW5qTDnToDQn7RbSRUAMJDhL6kQ506IqE/SLaSKiBBAcJ/UgHOnRFwn4hAQl1kOAgoSfpoMF+0LCzDjEzKUUIIYQQQgghhBBC4gdOShFCCCGEEEIIIYQQ2+GkFCGEEEIIIYQQQgixHUVVVdWODfl8PpSVlWHiZRPRrBp7UruiKMhJ64Pq5loY0VabvYAKQAGUNGPPeKcDHegQeYc0xY2Sd0tQUFAAp9NpyMEsZjPKbA0A82NBBzrQwRqHaGcU84kOdKBDT8R6PgHxcSxLBzrQIRC9+WT/2/dUQG3yGl0UJxtP0oEOdIg3h3S38WUjjcE6RGwc6EAHOshzkJJRiT4OdKADHQKJ8Xz6ZtHYP5alAx3oEIjOfLJ/UkoBlPTEnS2kAx3oEGwFhjZrDQYzKl5+40oHOtAh2EqMLRZxmE90oAMdAlZibLGIw3M8OtCBDgEr0Pc12yellFQnsq4bZmjZtKRUvDF3FaatnYfmdk/Yy9ev2Qe1yQslzYWsn9CBDnSQ4uB7pdLQdq3AaEaZrQFgfizoQAc6WOMgJaOYT3SgAx1OJdbzCYiPY1k60IEOgejNJz7onBBCCCGEEEIIIYTYDielCCGEEEIIIYQQQojtcFKKEEIIIYQQQgghhNhOzExK5Q8YhRmFk5GTk4MZhZORP2AUHRLYwVfVAs+eGhQXF8Ozpwa+qhbbHSTUgQ4ykFADOshxYD7RQRISakAHOQ7MJzpIQ0Id6CDHgRmVmA72v30vDFKS3Jg5firmT5yLcQPP7fx8+U1LAAA7j36GlSVrsWHHFrS0t9Ihzh1Urx/tFfVoLa+Fv1rbxuI3F3f+3JHjhju/D5KGZ0FxWTPfKqEOdJCBhBrQQY4D84kOkpBQAzrIcWA+0UEaEupABzkOzCg6KKrh94+Gh8/nQ1lZGS6bMgnO6/JCfn9ovyHYePuzGNg3D37VD6fDGbhOvw8OxYGjNZWYsexmHKg63Os6O59An67vCfR0kOPgq2tD0+tHoDZ4Q35XyXQhffogOLOTI+ogoQ7x6uB7pRLvbt2GgoICOJ2B67ODcDLKihoA4Y0FHeQ4WJFP4TpIqEM8O0Q7o5hPdDDqwHyKf4dYyicgfo9l6WDMged48e2gN59E3r43tN8Q/O3Ol5CXfQYURQlaEABwOpxQFAV52Wfgnbtextm5g+kQhw6+ujY0rj8EtTF0WAGA2uhF4/pD8NW1RcxBQh3oIAMJNaCDHAfmEx0kIaEGdJDjwHyigzQk1IEOchyYUXToIKxJqeLiYowcOTLgzznnnBMRGUC7ZGzj7c8i050Ol1Pf3YUupwuZ7nRsWrgaKUluOsSRg+r1o+n1I0CbH9B7TZ8KoE1bTvX6TTtIqAMdQsN8ooPdDswnOuiF+UQHux2YT3QIB2YUHex2YEbRoSthTUpNnToV77//fuefd999F4MHD8ZNN91kWqSDmeOnYmDfPN0F6cDldGHQ6f1RdN4UOsSRQ3tFvXY5Z7g3maqA2uBFe0W9aQcJdaBDaJhPdLDbgflEB70wn+hgtwPziQ7hwIyig90OzCg6dCWsSamUlBTk5uZ2/nn99dehqiruvPNO0yIdzJ84F37V2Mynz+/D/Ilz6RBHDq3ltVFdHpBRBzqEhvlEB7sdmE900AvziQ52OzCf6BAOzCg62O3AjKJDVww/U6qurg6rVq3C//zP/yA5OfQDEfWQP2AUxg08t8d7GEPhdDhRMGi0qdcV0kGOg6+qpfMNDEbxV7eaepWohDrQIXyYT3Sw2oH5RAejMJ/oYLUD84kOZmBG0cFqB2YUHU4lvGu0uvDiiy+iX79++NGPfhTWcoqiIC0pNejPxuSNNKrTjdF5I7DvxKGAzxsUBSodYsbBU++JiIOrAUjNC9xGrNQhERwaFSUi6+/AaD4BPdfB6hoAoceCDnIcrM4nPQ4S6pAoDpHMKOYTHax2YD4lloOUY6hEP5alg34HnuMljoPefFJUVQ33Tk6oqoorrrgCt9xyC+bMmaNrmY7Xhc6cORMbNmwI+p2cnBwMHmz+Ce6HDx9GdXV1wOdTp07FyZMn0a9fP2zZsoUOwh2Ki4uxePFi0w733XcfioqKDDlIqEMiOHTkQiReZ2wkn4DQGWV1DYDQY0EHOQ5W55MeBwl1SBSHSGUU84kOdjgwnxLLIdrHUDzHo0O4DjzHSxwHvflk6EqpXbt24cSJE7jyyivDXrbGU4dpa+cF/dmMwslYftMSI0rdeLRkBV4rfSvg8+rm2s6/6SDfwbOnxvT2AWB56To817zVkIOEOiSCQ6OnzvS6OzCTT0DPGWV1DYDQY0EHOQ5W55MeBwl1SBSHSGUU84kOdjgwnxLLQcoxFM/x6KDXged4ieOgN58MTUq99957OP/883HaaaeFvayqqmhuD37J3ieVe43oBK7ni71Bt9FxURgdYsPBlxWZy5G9mYjpOiSSQyQwk08dLsEcra5Bx7bpEBsOVueTHgcJdUg0B7Mwn+hghwPzKTEdIgHP8ehghwPP8RLPIRSGHnReXl6O8847z8iiva/32G7sPPoZfH6foeV9fh/KjnyKXV/soUMcODhzU+DIcRteHgAcOW44c1MMLy+hDnQID+YTHexwYD7RwQjMJzrY4cB8ooNRmFF0sMOBGUWHUzE0KVVRUYFhw4aZ2nBPrCxZC4di7KWATocTK0vW0iGOHNz5faK6PCCjDnTQD/OJDnY5MJ/oEC7MJzrY5cB8ooMRmFF0sMuBGUWHrhjaenV1NbKyskxvPBgbdmzB0ZpKeH3esJbz+rw48tUXKP44+L3vdIhNh6ThWVAyXUC4V3kqgJLpQtJw830qoQ500A/ziQ52OTCf6BAuzCc62OXAfKKDEZhRdLDLgRlFh64Yvn3v0ksvNb3xYLS0t+Kap29BQ2uT7sJ4fV40tDZhxrKb0dLeSoc4clBcDqRPHwQkO/SHlgIgWVtOcRmb9e2KhDrQQT/MJzrY5cB8okO4MJ/oYJcD84kORmBG0cEuB2YUHbpifjQtYP/JQ7hi6WxU1p0AgB7vcez4vLLuBK5YOhsHqg7TIQ4dnNnJyJg1BEqGvufyKxkuZMwaAmd2csQcJNSBDjKQUAM6yHFgPtFBEhJqQAc5DswnOkhDQh3oIMeBGUWHDgy9fc8ODlQdxoSHr0TReVMwf+JcFAwaHfCdXcf2YGXJWhR/vNWS3yLQQY6DMzsZmXPORntFPVrLa+GvDtyGI8cNd34f7XLQCMyen4qEOtBBBhJqQAc5DswnOkhCQg3oIMeB+UQHaUioAx3kODCj6AAAihrJ94j2gs/nQ1lZGS6bMgnO6/LCXj5/wCiMzhuBeyYuwKMlK/Bp5ecoP7Y7rHXUr9kHtckLJd2FrJ+E/xA/Oshx8FW1wNUA3FY4B8tL18GbibDfwBAPdYgXB98rlXh36zYUFBTA6XSG7RAJzGRUJGoAmBsLOshxiEQ+mXWQUId4coh2RjGf6BApB+ZT/DnEcj4B8XMsS4fIOPAcL74c9OaT2CulTqX82G7sO3EIt4y+Fq+VvoXmdg8dEtjBmZuC1LxUFBUV4bnmrQlbBzrIQEIN6CDHgflEB0lIqAEd5Dgwn+ggDQl1oIMcB2ZUYjqIfKYUIYQQQgghhBBCCIlvOClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHZsf9D5xMsmolk19qR2RVGQk9YH1c21MKKtNnsBFYACKGnGHqdFBzrQIfIOaYobJe+WiHjQudGMMlsDwPxY0IEOdLDGIdoZxXyiAx3o0BOxnk9AfBzL0oEOdAhEbz7Z/6BzFVCbvEYXxcnGk3SgAx3izSHdbXzZSGOwDhEbBzrQgQ7yHKRkVKKPAx3oQIdAYjyfvlk09o9l6UAHOgSiM5/sn5RSACU9cWcL6UAHOgRbgaHNWoPBjIqX37jSgQ50CLYSY4tFHOYTHehAh4CVGFss4vAcjw50oEPACvR9zfZJKSXViazrhhlaNi0pFW/MXYVpa+cZeiVh/Zp9UJu8UNJcyPoJHehABykOvlcqDW3XCoxmlNkaAObHgg50oIM1DlIyivlEBzrQ4VRiPZ+A+DiWpQMd6BCI3nzig84JIYQQQgghhBBCiO1wUooQQgghhBBCCCGE2A4npQghhBBCCCGEEEKI7XBSihBCCCGEEEIIIYTYjv1v34thfFUt8NR7UFxcDM+eGviyFDhzU+hAh4R2IDKQ0At0oIM0ByIDCb1ABzpIcyBykNAPdKCDNAc74aRUCFSvH+0V9Wgtr4W/uhUAsPjNxZ0/d+S44c7vg6ThWVBc1lx4Rgc6SHMgMpDQC3SggzQHIgMJvUAHOkhzIHKQ0A90oIM0h2jBSale8NW1oen1I1AbvD1+x1/dCs+2L9Hy72qkTx8EZ3YyHegQ1w5EBhJ6gQ50kOZAZCChF+hAB2kORA4S+oEOdJDmEE3CnmI7fvw4br31Vpx33nmYNGkS1qxZY4FW9PHVtaFx/SGojT03RlfURi8a1x+Cr66NDnSIWwfpMJ+CE6/9SAc6xBLMp+DEaz/SgQ6xRKLkEyCjH+hAB2kO0SbsSan/+q//QlpaGoqLi3HffffhiSeewNtvv22FW9RQvX40vX4EaPMDqt6FALRpy6lePx3oEHcOsQDzqaeFEHf9SAc6xBrMp54WQtz1Ix3oEGskQj4BMvqBDnSQ5iCBsCalvv76a5SVlWHBggUYMmQIvv/97+PSSy/FBx98YJVfVGivqNcundPbGB2ogNrgRXtFPR3oEHcO0mE+hSDO+pEOdIglmE8hiLN+pAMdYolEySdARj/QgQ7SHCQQ1qRUSkoKUlNTUVxcjPb2dhw4cAAff/wxRo0aZZVfVGgtr43q8nSgg0QH6TCf7FmeDnSQ6CAd5pM9y9OBDhIdpJMo+QTI6Ac60EGagwTCmpRyu9148MEH8fLLL2PcuHGYMmUKvve97+Haa6+1ys92fFUtnU+7N4q/uhW+qhY60CFuHGIB5pM+4qEf6UCHWIP5pI946Ec60CHWSIR8AmT0Ax3oIM1BCmG/fW///v24/PLL8dOf/hQVFRV46KGHcPHFF2P69Om6llcUBWlJqWGLAkBqUkq3v8OlQVGghnDw1HsMrftUXA1Aal7gNuhAh1h0CIXZfbNRUQwtdypm8wkwXgezNQBCj4XVvUAHOsSiQygisW9GIqOYT/qI9X6kAx3CgfmkwXM8OtAhOg6hsOscL6xJqQ8++ADr169HSUkJUlJSMHbsWJw4cQIrVqzQHVp9U7OxYe6qcDYbwCuznzK03NR1U3Gy8SRy0vrgjR4ciouLsfjNxWb0AAC3Fc5BUVERHegQFw56Mbpvztw409R2gcjkE2A+o4zWAAg9Flb3Ah3oEIsOejGzb5rNKOaTfmK9H+lAByMwnzR4jkcHOtjroBerz/HCmpT65JNPMHjwYKSkfDtTdu655+KZZ57RvY4aTx2mrZ0XzmY7SU1KwSuzn8J1L98BT3v4l6lVN9d2/t2Tg2dPjSG3U1leug7PNW+lAx3iwiEUZvfNRk+doe12JRL5BBjPKLM1AEKPhdW9QAc6xKJDKCKxb5rNKOaTfmK9H+lAh3BgPmnwHI8OdIiOQyjsOscLa1KqX79+OHz4MNra2pCcnAwAOHDgAAYMGKB7Haqqornd3KVqnvYWQ+tQVTWkgy8rMrcReTMRdBt0oEMsOujF7L5phkjkU4eLmToYrUHHtntzsLoX6ECHWHTQSyT2TaMwn/QT6/1IBzoYgfmkwXM8OtDBXge9WH2OF9aDzidNmoSkpCQ88MADOHjwILZt24ZnnnkGN954Y9iCUnHmpsCR4za1DkeOG85c4/eG04EO0hxiAeaTPuKhH+lAh1iD+aSPeOhHOtAh1kiEfAJk9AMd6CDNQQphTUplZmZizZo1qKqqwqxZs7BkyRIsWLAAs2fPtsovKrjz+0R1eTrQQaKDdJhP9ixPBzpIdJAO88me5elAB4kO0kmUfAJk9AMd6CDNQQJhv31v2LBheO6556xwEUPS8Cy0/LsaaqMXCOeKWAVQMlxIGp5FBzrEnUMswHzqhTjrRzrQIdZgPvVCnPUjHegQayRCPgEy+oEOdJDmIIGwrpRKFBSXA+nTBwHJDkDvrZ4KgGRtOcVlvqx0oIM0ByIDCb1ABzpIcyAykNALdKCDNAciBwn9QAc6SHOQQHz8KyzAmZ2MjFlDoGTou5hMyXAhY9YQOLOT6UCHuHUgMpDQC3SggzQHIgMJvUAHOkhzIHKQ0A90oIM0h2gT9u17iYQzOxmZc85Ge0U9Wstr4a9uDfiOI8cNd34fJA3PsmSmkg50kOZAZCChF+hAB2kORAYSeoEOdJDmQOQgoR/oQAdpDtGEk1IhUFwOJI/KRvKobPiqWuBqAG4rnIPlpevgzYQtT7unAx2kORAZSOgFOtBBmgORgYReoAMdpDkQOUjoBzrQQZpDtIivKTaLceamIHVkHxQVFSF1ZJ+oNAYd6CDNgchAQi/QgQ7SHIgMJPQCHeggzYHIQUI/0IEO0hzshJNShBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHYUVVVVOzbk9Xqxc+dOTJk6BR418GnyelAUBX1Ts1HjqYMRbdXjA1QACqCkOulABzoIcUhV3Ni6ZSvGjRsHlys6718wm1FmawCYHws60IEO1jhEO6OYT3SgAx16ItbzCYiPY1k60IEOgejNJ9uSy+/3AwC2btlq1yYJITFGR05Ec9vMKEJIT0Qro5hPhJBQMJ8IIVIJlU+2XSnl9/vh9XrhcDigKIodmySExAiqqsLv98PlcsHhiM5dxcwoQkhPRDujmE+EkJ5gPhFCpKI3n2yblCKEEEIIIYQQQgghpAM+6JwQQgghhBBCCCGE2A4npQghhBBCCCGEEEKI7XBSihBCCCGEEEIIIYTYDielCCGEEEIIIYQQQojtcFKKEEIIIYQQQgghhNgOJ6UIIYQQQgghhBBCiO3E1KRUcXExRo4ciVdffdXW7Y4cObLbn4suuggPPPAAmpqabPUAgK+//hqPPvooJk2ahHHjxmHKlClYs2YN/H6/5dueNGlSZw3OOeccFBYW4sc//jHee+89y7cdzOHUP9u3b4+6x/XXX2+bQ3NzM5544gn86Ec/Qn5+Pi688EIsWrQIFRUVtmx/0qRJKC4uDvi8uLgYkyZNssVBGomeUYmeT6d6RCujmE/Mp2Awn5hPzKdviWZGMZ8CYT5FL58AGRklIZ968+AxlLUZ5bJkrRaxefNmDBo0CK+99hquvfZaW7f91FNPobCwEH6/H8ePH8eDDz6Ixx57DL/5zW9sc6itrcXs2bPRr18/PPLIIxgwYAB27dqFhx56CEePHsUvf/lLyx3uu+8+TJ06FX6/H19//TU2bdqEW2+9Fc8++yy+853vWL79rg6nctppp9my/d48kpKSbNl2U1MT5syZg+bmZtxzzz0455xzUFtbixdeeAE//vGPsWnTJgwcONAWF/ItiZxRzKdAj1OxM6OYT+RUmE/Mp64ep5Io+QQwoyTCfIpuPgEyMkpCPvXkwWMoa4mZSamvvvoKH3zwARYvXox77rkHR48etXVATjvtNOTm5gIAzjjjDNx66634zW9+Y+uk1OOPP47k5GSsXr0abrcbADBw4ECkpKTgtttuw9y5c3HWWWdZ6pCZmdmtDr/4xS9QVVWFJUuW4I033rB028Ecokk0PZ5++ml89dVX2LJlC7KysgAA/fv3x5IlS3D8+HGsWbPGtv+IEY1EzyjmU3CPaMF8Il1hPjGfgnlEi2g7MKNkwXyKfj4BMjIq2tkgwSNR8ylmbt978803kZmZienTp6Nfv3547bXXouqTmppq6/ba2tqwefNm3HDDDZ2B1cHll1+ONWvWoH///rY6dTB79mx8/vnnOHz4cFS2n2j4/X5s3LgRP/3pTzvDqiuPPfYY7rrrriiYJTaJnFHMJ9IB80kmzCfmE9FgRsmD+SQznwBmlN0kcj7FzKTU5s2bcdlll8HhcGDSpEnYtGkTVFWNiktNTQ3+/Oc/Y/r06bZt88iRI2hubsbYsWMDfqYoCi666CIkJyfb5tOVoUOHAgD27dsXle0nGkeOHEFNTQ3OP//8oD/v168fUlJSbLYiiZxRzCfSAfNJJswn5hPRYEbJg/kkM58AZpTdJHI+xcTte8ePH8fHH3+Mn/70pwCAH/7wh3jxxRexY8eOHgct0sybNw9OpxOqqsLj8SA7Oxu//vWvbdk2ANTX1wPQLieURoeTXQ8F/NWvfoWHHnqo22d5eXnYvHmzLdvvzeMf//gH0tLSLN1ubW0tgO73V//zn//E7bff3vn/7apHsBp4vV4Rl97aSaJnFPOpOxIyivnEfOqA+cR86koi5xMgJ6OYTxrMJ7n5BPAcrys8hrI2o2JiUmrz5s1wu9347ne/CwCYMGECTjvtNGzcuNG2wHr44Ycxbtw4qKqK2tparF27Ftdffz3eeOMNnH766ZZvPzs7G4D2dgZpNDY2AgAyMjJs2d6iRYvwwx/+sNtnLpf9rRzMw45Lfjsu5+z4DxkAFBYWYtOmTQCAt956Cy+++KLlHkDwGti5fSkkekYxn7ojIaOYT8ynDphP2QCYTx0kcj4BcjKK+aTBfMoGIDOfAJ7jdYXHUNZuP2YmpVpaWjB+/PjOz3w+H95880388pe/tOUytjPOOAODBw8GAAwZMgSjR4/GhRdeiK1bt2Lu3LmWb3/QoEHIzMzEp59+ivz8/ICfL1iwADfeeKOtb3DpYO/evQCA4cOH27K9008/vXMsokm0PAYPHozs7GyUlpZ29kJqamqnix2TpB0Eq4Gd25dComcU86k7EjKK+cR86oD5xHzqSiLnEyAno5hPGswnufkE8BzPbqTkU8e27Mwo8c+UOnjwID777DM88MAD2LRpU+ef//u//0NjYyPefvvtqHg5HA6oqgqfz2fL9lwuF6ZOnYoXXngBbW1t3X62bds2bNu2Df369bPF5VQ2bNiA0aNHx+XrKSXicrkwc+ZMPP/8852/wejKiRMnomCVuDCjmE/kW5hPsmA+MZ9Id5hRcmA+yc4ngBllN4mcT+KvlNq8eTOys7Mxe/bsbg96GzFiBJ5++mls2rQJ06ZNs9zj66+/RlVVFQDtvto//vGP8Pl8mDRpkuXb7uCOO+7Atddei5tvvhl33HEH/uM//gPbt2/H0qVLcdNNN2HYsGGWOzQ0NKCqqqrzEtf169djy5Yt+OMf/2j5tk91OJX09HRbnkcggTvuuAM7duzAj3/8YyxcuBCjR49GbW0tXn31Vaxfvx5XXXVVtBUTBmaUBvMp0ONUEiWjmE9yYD5pMJ8CPU4lUfIJYEZJgfmkISGfABkZxXxK3HyKiUmpadOmBX3zwPXXX49HHnkEJ06cwBlnnGGpxx133NH5v1NTUzFmzBisWrXK1pnj3NxcvPjii3jqqadw5513oq6uDoMGDcKiRYtw/fXX2+KwePFiLF68GIqioG/fvjj33HOxZs0a2+777upwKv/5n/+J2267zTaPaJKamoo///nPeP7557F8+XIcPnwYycnJyM/Px1NPPYXvf//70VZMGJhRGsynQI9TSZSMYj7JgfmkwXwK9DiVRMkngBklBeaThoR8AmRkFPMpcfNJUaP1zk1CCCGEEEIIIYQQkrCIf6YUIYQQQgghhBBCCIk/OClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHY4KUUIIYQQQgghhBBCbIeTUoQQQgghhBBCCCHEdjgpRQghhBBCCCGEEEJsh5NShBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmyHk1JxyPz583Hvvfd2++wvf/kLRo4ciaeeeqrb58uXL8fVV18NAPjqq6+waNEijB8/HpdccgmWLl0Kr9fb+d01a9Zg5MiR3f789re/7dXl8ssvx4kTJwI+//rrr3HnnXdiwoQJuPTSS/H444/D7/f3uq67774bb7zxRsDn99xzTzencePG4cc//jHKy8u7fe/dd9/F1VdfjcLCQkybNg3vvPNO0O2sWLEC99xzT68uhBDjWJVRtbW1uOOOO1BYWIhJkybhtddeC+kyd+5cfPzxx90+O3bsWEDWdfz597//3eO6nnzySTzzzDMBnz/11FPd1jF27FhcffXVKCkp6fa9srIy/PjHP0ZhYSEmT56MV199tfNnkyZNCuqzbNmykP9GQoh+jOZTfX097r//fnznO9/BRRddhHvuuQf19fWd343kMZSqqnjyySfxne98BxMmTMAvf/lLtLa29rous8dQr7/+OiZPnoz8/PyAn/t8Pvzud7/DJZdcgsLCQvznf/4nqqure/UhhIRPLJzjffbZZwHrKioq6nVddp3jbd26FSNHjuzVhUQHTkrFIeeffz527drV7bPt27ejX79+2L59e7fPy8rKMGHCBADAnXfeicbGRrz88sv4//6//w+bN2/Gs88+2/ndffv2Yc6cOXj//fc7/9x+++09ehw+fBgpKSk444wzAn72m9/8BidPnsQLL7yApUuXYuPGjfjTn/7U67/rww8/xEUXXRT0Z1OmTOl02rhxI8aNG4dbb70VTU1NAIA9e/Zg4cKFmDlzJjZt2oQf//jH+M///E/s2bOn23r+8pe/BIQ6ISSyWJVR9957LxoaGvDyyy9jwYIFeOCBBwIOXLri8XhQUVGB/Pz8bp+feeaZ3XLu/fffx1VXXYWxY8eioKCgx/V98MEHuPjii4P+rLCwsHNdmzdvxlVXXYU77rgDx44dAwBUVVVh3rx5mDBhAjZu3IhFixbhoYcewrvvvgsAWL9+fTefX/7yl8jMzMQ111zTow8hJHyM5tOvfvUr7NmzBytXrsTq1auxf/9+PPDAA53fjeQx1KpVq7Bu3To8/vjjePbZZ/Hhhx+GnKA2cwz10Ucf4f7778dtt92GzZs3o7CwEPPmzev8+cqVK7FlyxY88cQTePXVV/H111/jF7/4Ra8+hJDwiYVzvH379mHUqFHd1rV69epe/112nOPV19fjkUce6dWDRA9OSsUh48ePx/79+zt3VkALrJtvvhllZWVoaWnp/Hznzp2YMGEC2tracPrpp+NXv/oVhg0bhvPPPx+TJ0/Gjh07Or+7f/9+nHPOOcjNze38k5GR0aNHbydoJSUl+OlPf4rhw4fjoosuwlVXXYUPPvigx3UdOHAAmZmZyM3NDfrzlJSUTqezzz4bd911F1paWvDhhx8C0CabLrroItx0000YPHgwbrjhBlx44YXYunUrAMDr9eJXv/oV7rvvPgwcOLBHD0KIeazIqCNHjuDvf/87Hn74YYwYMQLXXnstpk+fjnXr1vXo8dFHH6GgoAAul6vb506ns1vOHT16FH/961/x29/+FklJSUHX1dTUhIMHD2LMmDFBf56UlNS5vkGDBmHevHnIy8vDtm3bAAB/+9vfkJOTg//+7//GkCFDcOWVV2LGjBmdvzns27dv5/IpKSl4+umncffdd6N///46Kk4I0YuRfGpubsZf//pXPPjggxgzZgxGjx6N++67D3/72986r2CK1DGUz+fDc889h7vvvhsXX3wx8vPzcccdd+DTTz/tcV1mj6Gqqqpw22234eqrr8bAgQNx++23o66uDvv37+90uvfee3HBBRdg2LBhuPHGG7sdPxJCIkMsnOPt378fQ4cO7bauPn369Lguq8/xOnjsscd4jicYTkrFIWPHjkVSUlLnAcqXX36JyspKXHvttcjMzOy8VeXgwYP4+uuvcf755yM5ORm/+93vMHjwYABARUUFtm3b1jnDDmihMWTIEN0evQVWdnY2Xn/9dXg8Hpw4cQLvvfceRo0a1eu6eppBD4bL5UJycnLn/7/mmmtw5513BnyvoaEBANDc3Iy9e/filVdeQWFhoe7tEELCx4qM2rlzJ84880wMGDCgczvjx49HaWlpjx69ZVRXHn/8cVx33XUYOnRoj9/56KOPUFhYCKfTGboA35CWltb5vy+99FIsWbIk4DuNjY0Bn61evRq5ubmYOXOm7m0RQvRhJJ8cDgeeeeaZgOMYn8/XefIYqWOoiooK1NbW4vvf/37nZ9OnT8cf//jHXtdl5hhqypQpWLBgAQCgpaUFa9aswemnn96ZiQsXLsQPfvADANptQq+++mq340dCSGSIhXO8/fv3h70uK8/xAOBf//oX/vWvf+HnP/+57u0Qe+GkVBySnJyMcePGdd628uGHH2LMmDFIT0/HBRdc0Hl5Z1lZGYYPHx4wez137lxcddVVyMzMxA033AAAqK6uRl1dHTZu3IhJkyZhypQpWL16NVRVDeqgqir+/e9/93hQ8qtf/QoffPABzjvvPHzve99Dv379sHDhwh7/TR9++KGuk0dAu+rphRdeQFJSUmfIDR06FOecc07ndyoqKroFalZWFl566aVu3yGEWIMVGVVVVYV+/fp1+97pp58e9HkHHfR2uXgHO3bsQFlZGW699dZev6d3ggvQ8vFvf/sbDh061HkiN2DAgG63Bn711VfYvHlzwDo9Hg/Wrl2Ln//853A4+J9wQiKNkXxKSUnB9773vW4nSn/6058wcuRI9O3bN6LHUMeOHcNpp52Gjz/+GDNmzMDEiRPxyCOPoK2trcd/k9ljqA4++OADFBYWYtmyZbjvvvuQnp7e7ecdz7n6+OOP+WxOQiwgFs7x9u/fj927d2PatGm47LLL8OCDDwb9BVsHVp/jtbW14Ze//CUefPBBpKSk6NoOsR8e0cYp559/fmdgbd++HRdeeCEAYMKECd0CK1igPPDAA/jTn/6E9vZ2/Pd//zcAbQYd0E7yVqxYgVtvvRUrVqzA888/H3T7e/bswZlnnonTTjst6M87bnN58cUXsWzZMlRUVGDVqlVBv+v3+/HRRx/1+lu3N954A4WFhSgsLER+fj7+93//F7fcckvAARMA1NTU4I477sB5552HK664osd1EkKsI9IZ5fF4up0QAtrBW08nanV1dThx4kTIB16+8sor+MEPfhD0uQldCTUp1XElVWFhIcaMGYPbb78dM2fOxJlnnhnw3ZaWFtxxxx3IycnB7Nmzu/1sy5YtSEtLww9/+MNefQghxjGTTwCwdu1abN26tfO5SpE8hmpqakJLSwsef/xx3H333Vi8eDH+/ve/9/hQ4kgeQw0fPhzFxcVYtGgR7rnnHpSVlXX7+dVXX43169fj4osvxs9+9rNeT0QJIcaQfI7X3t6Oo0ePor29HYsXL8YjjzyCjz/+GHfddVfQddlxjvf0009j9OjR+O53v9vjNogAVBKXvP/+++pll12mqqqqXn755er777+vqqqq7t27Vx09erTa2tqqTp8+Xd26dWuP6ygvL1dHjBihHj16VFVVVa2pqen289WrV6s//OEPgy67evVqdenSpUF/dvDgQXXUqFHqiRMnOj977bXX1MLCQrW9vT3g+7t27VKvvfbaHj3vvvtudeHCheqhQ4fUQ4cOqXv37lXXrVunjh07Vt2wYUO371ZVValXXXWV+sMf/lD96quvelzf3Xff3eP2CCHmiXRGrVq1KiAn3n33XbWwsDDosm+++ab6X//1X706tre3q+PHj1ffeeedXr/31VdfqZdcckmPP3/yySfVWbNmdWZURUWF+vrrr6sTJkxQn3rqqW7fbWxsVG+66Sb14osvVg8ePBiwrnnz5qlLlizp1YcQYg4z+bR27Vp15MiR6po1a7p9HqljqL/85S/qiBEj1O3bt3d+9vbbb6tjx45VfT5fwPcjeQzVlfnz5/d4rNTS0qJOmDCh1+UJIcaQfI6nqqra0NCgtrW1df7/Xbt2qSNGjFC//PLLgO9afY63d+9e9aKLLlKrqqpUVVXVDz/8UB0xYkSP2yPRg1dKxSmFhYU4efIkdu3ahZMnT+K8884DoP2WKzMzE//+97+xb9++zpnpxsZGbNmyBX6/v3Mdw4YNA6C9Zh1AwCWgQ4cO7fHWmN6uGvjss8/Qp0+fbrfanHvuuWhqasLXX38d1ro6SE9Px+DBgzF48GCMGDEC119/PWbMmIG1a9d2fufEiRO44YYb0NbWhj/96U/o27dvr+skhFhHpDPqjDPOCHgFeXV1dY8PztSTK2VlZfB6vbjkkkt6/d6HH37Y+ZvKnkhJSenMqGHDhmHatGn42c9+hj//+c+d32lsbMTNN9+MiooKPP/88wHPZGhra8O//vWvbs+SIYREnnDzqYPVq1fjf//3f3HXXXfh//l//p9uP4vUMVRHpp199tmdn5111llobW1FTU1NWOvqINQxVHl5ecCD1IcOHdp5fPj3v/+927/F7XZj4MCBnT8nhEQOyed4AJCRkdHtpTAdz54Ltj6rz/HeeustfP311/jBD37Q+dZQQKvh66+/3ut2ib1wUipOSUtLw6hRo/Dyyy9j7NixSE1NBQAoioILLrgAxcXFGDJkSOdO6/F48P/+v/8vdu7c2bmOTz/9FE6nE2eddRZeffVVTJ48udv9xbt37+52UNRBe3s7ysvLMX78+KBu/fr1Q21tLb766qvOzw4cOIC0tLSgE0V6nvsSDFVVOwO4ubkZt9xyCxwOB9auXRvyVhxCiLVEOqMKCgrwxRdf4Msvv+z8+Y4dO7o9p6kreg6Edu7cidGjR8Ptdvf6vXCeh9CVrhnl9/uxcOFCHDt2DH/+858xfPjwgO/v3bsXXq8X+fn5YW+LEKKfcPMJADZu3IjHHnsM9957L26++eZu64vkMdS5556LpKSkbq87379/P9LT05GdnR3w/UgcQ61fvx6///3vu/38008/7fT/7W9/i02bNnX+rLGxEYcOHer15RCEEGNIPsfbt28fCgsLcfTo0W7rcrlcnQ9a74rV53hz587F1q1bsWnTJmzatAkPP/wwAGDTpk2YNGlS2Nsl1sFJqTjmggsuwObNmwN+kzdhwgS88847uOCCCzo/y83NxQ9/+EM89NBD+Oyzz/DRRx/h/vvvx9y5c5GRkYHvfOc7qKqqwm9/+1scPnwYmzdvxqpVq3DLLbcEbHfnzp0YMWJEjw+TKygowNChQ/GLX/wCFRUV+Ne//oXHHnsMc+fOhaIo3b7b1taGTz75pPO3AD3R0tKCqqoqVFVV4cSJE9iyZQveeOMNTJkyBQDwhz/8AUeOHOl85kLHd7u+mYEQYi+RzKiBAwfiu9/9Lu666y7s2bMHr776Kv7yl790PsizK19++SXa29tDvhq4oqJC10mVngmu9vb2ztw5efIk3nvvPfzpT3/qzKj169dj+/btePjhh5GVldX53bq6um4+AwYMCHh2FiEk8oSTT3V1dfjf//1fXHPNNbjyyis799+qqir4fL6IHkNlZGTguuuuw0MPPYSysjKUlpbid7/7Ha699lq4XK5u343UMdTs2bPx4Ycf4vnnn8ehQ4fw5JNPory8HD/5yU8AADfccANWr16NkpISVFRU4K677sKgQYPwve99L2SdCSHhI/Uc7+yzz8bgwYPxy1/+Ep9//jk++ugj/PKXv8S1114b8AwqO87xsrOzO6+yGjx4cOeE1eDBg5GRkRGiysROXKG/QmKV8ePH449//GPAbSUTJkyAx+MJCLLFixdj8eLF+OlPfwoAmDFjBv7nf/4HANC/f3+sXLkSS5cuxYsvvojTTz8dd955J6ZOnRqw3VCz3i6XC6tWrcIjjzyCG264AWlpabj66quDvn2vrKwM55xzTsgrFbZu3YqtW7d2rv8//uM/cOutt3YG6l//+le0tLTg2muv7bbcNddcg0cffbTXdRNCrCGSGQUAjz32GO6//35cd911yM3NxeLFi4NeVaT39cPV1dUBr3g/lS+++AKAlpG9UVpa2vmQTYfDgdzcXFx99dVYtGgRAC2j/H5/wFv+JkyY0HmLX3V1dY8vjyCERJZw8ukf//gHmpubsXHjRmzcuLHb99955x0MGDAgYsdQAHDPPfdg6dKlmD9/PlRVxfTp07tlYQeROoYaPXo0li1bht///vd4/PHHMXz4cKxevbrzBO+GG26Ax+PBr3/9a9TU1OCSSy7BihUr+IZQQixC6jmew+HAihUrOs/xHA4Hpk2b1vnSh67wHI90RVHVHt73SAghhBBCCCGEEEKIRfBXGIQQQgghhBBCCCHEdjgpRQghhBBCCCGEEEJsh5NShBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHY4KUUIIYQQQgghhBBCbIeTUoQQQgghhBBCCCHEdjgpRQghhBBCCCGEEEJsh5NShBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHY4KUUIIYQQQgghhBBCbIeTUoQQQgghhBBCCCHEdjgpRQghhBBCCCGEEEJsh5NShBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmzHZdeG/H4/vF4vHA4HFEWxa7OEkBhAVVX4/X64XC44HNGZK2dGEUJ6ItoZxXwihPQE84kQIhW9+WTbpJTX68WuXbvs2hwhJAYZO3YskpOTo7JtZhQhJBTRyijmEyEkFMwnQohUQuWTbZNSHTNjU6ZOgUdtNbQORVHQNzUbNZ46qKoa9vKqxweoABRASXXSgQ50EOKQqrixdcvWqF0lBZjPKLM1AMyPBR3oQAdrHKKdUcwnOtCBDj0R6/kExMexLB3oQIdA9OaTbZNSHZdzetRWOK/LM7SOtKRUbJi7CtPWzkNzuyfs5evX7IPa5IWS7kLWdcPoQAc6CHHwvFIJ4NuciAZmM8psDQDzY0EHOtDBGodoZxTziQ50oENPxHo+AfFxLEsHOtAhEL35xAedE0IIIYQQQgghhBDb4aRUrOL3R9uAECIRZgMhhBBCYg0evxCSsNh2+x4xx7iqFtywuw4XV3owsrYNyU9MwCGHgr19kvFBXipeGJWNnbkp0dYkhNgMs4EQQgghsQaPXwghHXBSSjhn1bVh2bbjuOS4B+0K8IkKbADQACDTr+Kcr1rx05pWzN9Vh3+cmYqFk87EwWxr37zhq2qBp96D4uJiePbUwJelwGnzfzToIMchf8AojMkbiZycHMwonIxPKvei/NhuWx0SkVOzIWlcAfCDc4DMTCQ3NGDsnj04Z2eZrdkgoRfoQAdpDkTGONCBDnSQgcRzGwljQQc6JLIDJ6UEM+vzr/H0ti/R5lPxHIAnVaAsyPcKVGARgFnHPfjwpYO4bdKZ2DAiK6IuqteP9op6tJbXwl+tvVlj8ZuLO3/uyHHDnd8HScOzoLisuSuUDnIcUpLcmDl+KuZPnItxA8/t/Hz5TUsAADuPfoaVJWuxYccWtLQbexML6ZmObHAmu4Gf/ARJixYBhYUB30sqLQWefBIXvvySZdkgoRfoQAdpDkTGONCBDnSQhaRzGwljQQc60EGDz5QSyqzPv8bKt4/joE/FWAA/A1Dew3fLv/n5WACHfCpWvV2JWZ9/HTEXX10bGtYdgGfbl52TIKfir26FZ9uXaFh3AL66tohtmw7yHIb2G4J/PbAZy254BGP6jwz6nTH9R2LZDY/gXw9sxtm5gyPukMh0ZEPS2cPg+mw38Mc/Avn5wb+cnw/88Y9wfbYbSWcNjXg2SOgFOtBBmgORMQ50oAMdZCHp3EbCWNCBDnT4FsOTUm1tbbjqqquwffv2iMkQjbPr2vD0ti/xOYDvADj2zec9Pf6v4/NjAC4GUAHg6W1f4qwITEj46trQuP4Q1Eavru+rjV40rj8U0ckQOshxGNpvCP5250vIyz4DiqLA6XAG/Z7T4YSiKMjLPgPv3PWy7QdW8ZpPHdmA4cPh+PBDoH9/QFEAZ/BxgNOp/bx/fzi2bweGDYtYNkjoBTrQQZqDHuI1nzqQMA50oAMdjGFVPkk6t5EwFnSgAx26Y2hSqrW1Ff/93/+NioqKiEiQ7jy17ThafSp+BKAegE/ncr5vvj8ZQJtPxbJtx015qF4/ml4/ArT5AVXvQgDatOVUr/m3aNBBjkNKkhsbb38Wme50uJz67vx1OV3IdKdj08LVSElym3bQQzzn01PbjsOR7IbjrbeAzEwgKUnfgklJQGYmHG+/DWey23Q2SOgFOtBBmoMe4jmfABnjQAc60MEYVuaTlHMbCWNBBzrQIZCwJ6X27duH6667DkeOHDG9cRLIuJMtuOS4BxsAHIb+0O7A981yGwBcctyDcVUthl3aK+qhNnj1T4J0oAJqgxftFfWGt00HeQ4zx0/FwL55usOqA5fThUGn90fReVNMO4QinvOpIxuSZv8YGDxY/4RUB0lJwJAhcF0323Q2SOgFOtBBmkMo4jmfOpAwDnSgAx3Cx8p8knRuI2Es6EAHOgQS9qTUv/71L1x44YV4+eWXTW+cBHLDnjq0K8CTMH5vpQPa8u0KcMPuOsMureW1hpeNxPJ0kOUwf+Jc+FVjV1z5/D7MnzjXtEMo4jmfOrIBixYBfoNXvvl8wB13mM4GCb1ABzpIcwhFPOdTBxLGgQ50oEP4WJlPks5tJIwFHehAh0DCzoY5c+bgvvvuQ2pqqumNk0AurvTgk2/eRGH0his/gFJor1i96LjH0Dp8VS09Pkhbt0d1K3wmfptBBzkO+QNGYdzAc3u8vzgUTocTBYNGI3/AKMMOeojnfLq40oOkcQXaW/Z6eoZUKJxOYPx4JI0rMJwNEnqBDnSQ5qCHeM4nQMY40IEOdDCGlfkk5dxGwljQgQ50CE5412hFAEVRkJZkLPBSk1K6/R0uDYoCVbjDyNo2bDC05kD2AiiqaQvYjp46eOqNBf6puBqA1LzAbdAhthzG5AV/A0O4jM4bgX0nDgV83qgoEVl/JDCaD2azAeh9LEbWtgE/OMfwuruvbCTOKd8Z9N8Zqh+s7gU60EGig5SMkppPQOL0Ah3oIM1Bej5JObexeizoQAc6BDrozSdFVdVwn1LTyciRI/GnP/0JF154Ycjv+nw+lJWVYebMmdiwIVLRFB5Tp07FyZMn0a9fP2zZskWeg9+P8RMmYCWAWyOwrT8AmA9gx7/+BTi+vShOTx2Ki4uxePFi0w733XcfioqKAj6nQ2w55OTkYPBg829XOHz4MKqrqwM+78iFgoICOI1eBXQK4eQTIDyjvskGzJsHrFxpfkPz5wOrVgVkQ68O32B1L9CBDhIdIp1RcZVP35AovUAHOkhzEJ1Pgs5trB4LOtCBDsbP8Wy/UqrGU4dpa+cZWjY1KQWvzH4K1718Bzzt4d+KVN1c2/m3VIdDDgWZfsPzhN3IAtDmUDBtXff/DOipg2dPTUQclpeuw3PNWwM+p0NsOcwonIzlNy0x7fBoyQq8VvpWwOeNnjrT644URjPKbDYAvY/FIYeC5IYGQ+sNoL4+aDaEcgCs7wU60EGig5SMkppPQOL0Ah3oIM1Bej5JObexeizoQAc6GD/Hs31SSlVVNLebux3J095iaB0dF4VJdtjbJxnnfGXu+UEdnANgT9/kgO3oqYMvKzKXAnszEXQbdIgth08q90bE4ZMv9vbqIAGz+WA0Gzq23ZPD3j7JGLtnj2GvbuzZEzQbQjkA1vcCHegg2SHaSM0nIPF6gQ50kOYQbaSf29h1LEsHOtAh0CEURl+CQCzig7xUjFGAAph7Q0UhgNEK8OGZxp6d5cxNgSPHbdDgG48cN5y5xp9fQQc5DuXHdmPn0c/g84f7Il8Nn9+HsiOfYtcXEZpUSUA+yEtF+84yoLRUe4ueEXw+YMcOtJfvNJwNEnqBDnSQ5kBkjAMd6EAHeUg5t5EwFnSgAx2Cw0kpYbwwKhtJKrAI5t5QsQhAkqqtzyju/D6Gl43E8nSQ5bCyZC0cirHIcDqcWFmy1rRDItORDXjyyYDnQOnG6QSeesp0NkjoBTrQQZoDkTEOdKADHWQh6dxGwljQgQ50CMTUpNTevXt1PwSP6GNnbgr+cWYqZgEYDCDcxxU6v1luJoB/nJmKnSaujkkangUl0wWEe/eYAiiZLiQNzzK8bTrIc9iwYwuO1lTC6/OGtZzX58WRr75A8ceBz7OyknjLp45s8L78EnD4MNDeHt4K2tuBQ4fgfeVl09kgoRfoQAdpDuEQb/nUgYRxoAMd6GCOSOeTpHMbCWNBBzrQIRBeKSWQhZPORLJTwZvQHuinN7yd33z/rwCSnQoWTjrTlIficiB9+iAg2aF/MkQBkKwtp7jMtxcd5Di0tLfimqdvQUNrk+7Q8vq8aGhtwoxlN6OlPTLPE0hkFk46E762Vvh/+EOgoUH/xFR7O9DQAP8PfgBfW6vpbJDQC3SggzQHImMc6EAHOshDyrmNhLGgAx3oEAgnpQRyMDsZt006EyMAfABgwDef9zRYHZ8P+Ob7wwHcNulMHMxONu3izE5GxqwhUDL0PRNfyXAhY9YQOCOwbTrIc9h/8hCuWDoblXUnAKDH+487Pq+sO4Erls7GgarDEXNIZDqyARUV8F94IfDFF9oPenrGVMfnX3yhfX/fvohlg4ReoAMdpDkQGeNABzrQQRaSzm0kjAUd6ECH7tj+9j2ijw0jsqBAxdPbvsQun4oNAJ4EUBrku+Og3Wc9E9pvEeZNOhMbRpi/XasDZ3YyMuecjfaKerSW18JfHTgb6shxw53fR7vNLAJX5dBBrsOBqsOY8PCVKDpvCuZPnIuCQaMDvrPr2B6sLFmL4o+3xsVv+CTxbTbsh/PcUXBdNxu44w5g/PjAL5eVAU89Be8rL8PX1orbfpAX0WyQ0At0oIM0ByJjHOhABzrIQtK5jYSxoAMd6PAtnJQSzPoRp2FHv1Qs23YcPznuwQ0K8IkK7AVQD+1y1pEAxijag//ez0vFHZdH5rcIp6K4HEgelY3kUdnwVbXA1QDcVjgHy0vXwZsJU292o0PsObS0t2Ld9k1Yt30T8geMwui8Ebhn4gI8WrICn1Z+jvJjuy13SGS6ZsMlzz+P9j89j6RxBcDIkUBWFlBfD+zdi/adZUhSgQ/zUnHH5WdZkg0SeoEOdJDmQGSMAx3oQAdZSDq3kTAWdKADHTQ4KSWcg9nJuLJoMMZVteCG3XW46LgHRTVtSParaHMo2NM3Gc+dmYoXRmWbevBfODhzU5Cal4qioiI817wVze0eW7ZLB5kO5cd2Y9+JQ7hl9LV4rfStqDgkIgHZcGw3zinf2S0bPhyTbWs2SOgFOtBBmgORMQ50oAMdZCDx3EbCWNCBDonswEmpGGFnbgp25v4HACAtKRVvzPkDpq27NWH+A0YICQ6zgRBCCCGxBo9fCCEd8EHnsYqDQ0cICQKzgRBCCCGxBo9fCElYuPcTQgghhBBCCCGEENtRVFVV7diQz+dDWVkZJl42Ec2qsSe1K4qCnLQ+qG6uhRFttdkLqAAUQEkzduciHehAh8g7pClulLxbgoKCAjidTkMOZjGbUWZrAJgfCzrQgQ7WOEQ7o5hPdKADHXoi1vMJiI9jWTrQgQ6B6M0n+58ppQJqk9foojjZeJIOdKBDvDmku40vG2kM1iFi40AHOtBBnoOUjEr0caADHegQSIzn0zeLxv6xLB3oQIdAdOaT/ZNSCqCkJ+5sIR3oQIdgKzC0WWswmFHx8htXOtCBDsFWYmyxiMN8ogMd6BCwEmOLRRye49GBDnQIWIG+r9k+KaWkOpF13TBDy6YlpeKNuaswbe08Q29mqF+zD2qTF0qaC1k/oQMd6CDFwfdKpaHtWoHRjDJbA8D8WNCBDnSwxkFKRjGf6EAHOpxKrOcTEB/HsnSgAx0C0ZtPfNA5IYQQQgghhBBCCLEdTkoRQgghhBBCCCGEENvhpBQhhBBCCCGEEEIIsZ2YmZTKHzAKMwonIycnBzMKJyN/wKiEdPBVtcCzpwbFxcXw7KmBr6olIR0kjAUd5DhEGwk1oIMG84kO0hyijYQa0EGD+UQHaQ4SkFAH7psarAMdouVg/9v3wiAlyY2Z46di/sS5GDfw3M7Pl9+0BACw8+hnWFmyFht2bEFLe2vcOqheP9or6tFaXgt/tbaNxW8u7vy5I8cNd34fJA3PguKyZp5RgoOEsaCDHIdoI6EGdNBgPtFBmkO0kVADOmgwn+ggzUECEurAfVODdaCDBAdFNfz+0fDw+XwoKyvDZVMmwXldXsjvD+03BBtvfxYD++bBr/rhdDgD1+n3waE4cLSmEjOW3YwDVYd7XWfnE+jT9T2BXoKDr64NTa8fgdrgDfldJdOF9OmD4MxOjjsHCWNBB+scfK9U4t2t21BQUACnM3B9dhBORllRAyC8saDDN+u3IJ/CdZBQBzpY6xDtjGI+xaYD84kOdjjEUj4BMo5leW7zzfpZBzpY7KA3n0Tevje03xD87c6XkJd9BhRFCVoQAHA6nFAUBXnZZ+Cdu17G2bmD48rBV9eGxvWHoDaGDgoAUBu9aFx/CL66trhykDAWdJDjEG0k1IAOGswnOkhziDYSakAHDeYTHaQ5SEBCHbhvarAOdJDkENak1IkTJ7Bo0SJMmDABl156KZYsWYLW1sheOpaS5MbG259FpjsdLqe+uwtdThcy3enYtHA1UpLcceGgev1oev0I0OYH9F7LpgJo05ZTvf64cJAwFnSQ4xAKqzNKQg3ooMF8ooM0h1AwnxLHgflEB2kOoUiUczzumxqsAx2kOeielFJVFYsWLYLH48ELL7yA//u//8Pf//53PPHEE6YlujJz/FQM7JunuyAduJwuDDq9P4rOmxIXDu0V9dqllOHeXKkCaoMX7RX1ceEgYSzoIMehN+zIKAk1oIMG84kO0hx6g/mUWA7MJzpIc+iNRDrH476pwTrQQZqD7kmpAwcOoKysDEuWLMHw4cNx/vnnY9GiRfjLX/5iWqIr8yfOhV81Nvvq8/swf+LcuHBoLa+N6vJSHCSMBR3kOPSGHRkloQZ00GA+0UGaQ28wnxLLgflEB2kOvZFI53jcNzVYBzpIc9A9KZWbm4tnn30WOTk53T5vbGw0LdFB/oBRGDfw3B7vYQyF0+FEwaDRpl5XKMHBV9XS+fYDo/irW029xlOCg4SxoIMch1BYnVESakAHDeYTHaQ5hIL5lDgOzCc6SHMIRaKc43Hf1GAd6CDNAQB0X6OVlZWFSy+9tPP/+/1+rF27FhdddFFYG1QUBWlJqUF/NiZvZFjr6onReSOw78ShgM8bFAVqDDh46j0RcXA1AKl5gduIFQcJY0EHexwaFcX0uq3OKKtrAIQeCzpoWJ1Pehwk1IEO9jmYzSjmU+I4MJ/oYLeD9HwCZBzL8txGg3Wgg50OevNJUVU13LtJAQC//e1v8cILL2D9+vUYMWJEyO93vC505syZ2LBhQ9Dv5OTkYPBg809wP3z4MKqrqwM+nzp1Kk6ePIl+/fphy5YtYh2Ki4uxePFi0w733XcfioqKYtZBwljQwR6HjlyI5OuMI51RVtcACD0WdNCwOp/0OEioAx3sc4h0RjGf4teB+UQHux2k5xMg41iW5zYarAMd7HTQm0/hPc3qG5YuXYrnn38e//d//6crrLpS46nDtLXzgv5sRuFkLL9piRGlbjxasgKvlb4V8Hl1c23n35IdPHtqTG8fAJaXrsNzzVtj1kHCWNDBHodGT53pdXfFioyyugZA6LGgg4bV+aTHQUId6GCfQyQzivkU3w7MJzrY7SA9nwAZx7I8t9FgHehgp4PefAp7Uuqhhx7Ciy++iKVLl2Ly5MnhLg5VVdHcHvyywU8q94a9vqDr+WJv0G10XBQm3cGXZf5WJgDwZiKmHSSMBR3sdYgEVmWU1TXo2DYdQjtYnU96HCTUgQ72O5iF+RT/DswnOkTLwSzxfo7HcxsN1oEO0XAIhe4HnQPAsmXL8NJLL+H3v/89rrzyynAW1UX5sd3YefQz+Pw+Q8v7/D6UHfkUu77YE9MOztwUOHLchpcHAEeOG87clJh2kDAWdJDjoAcrM0pCDeigwXyigzQHPTCfEsOB+UQHaQ56SIRzPO6bGqwDHaQ5AGFMSu3fvx/Lly/HvHnzMH78eFRVVXX+iSQrS9bCoYQ1V9aJ0+HEypK1ceHgzu8T1eWlOEgYCzrIcegNOzJKQg3ooMF8ooM0h95gPiWWA/OJDtIceiORzvG4b2qwDnSQ5qB76++88w58Ph9WrFiB7373u93+RJINO7bgaE0lvD5vWMt5fV4c+eoLFH8c/P77WHNIGp4FJdMFhHuFpQIomS4kDc+KCwcJY0EHOQ69YUdGSagBHTSYT3SQ5tAbzKfEcmA+0UGaQ28k0jke900N1oEO0hx0T0rNnz8fe/fuDfonkrS0t+Kap29BQ2uT7sJ4fV40tDZhxrKb0dLeGhcOisuB9OmDgGSH/sBQACRryykuY7Od0hwkjAUd5Dj0hh0ZJaEGdNBgPtFBmkNvMJ8Sy4H5RAdpDr2RSOd43Dc1WAc6SHMw31EWsP/kIVyxdDYq604AQI/3OHZ8Xll3AlcsnY0DVYfjysGZnYyMWUOgZOh7Hr2S4ULGrCFwZifHlYOEsaCDHIdoI6EGdNBgPtFBmkO0kVADOmgwn+ggzUECEurAfVODdaCDJIew375nFweqDmPCw1ei6LwpmD9xLgoGjQ74zq5je7CyZC2KP95qyW8RJDg4s5OROedstFfUo7W8Fv7qwG04ctxw5/fRLsWMwMy1RAcJY0EHOQ7RRkIN6KDBfKKDNIdoI6EGdNBgPtFBmoMEJNSB+6YG60AHKQ6KGsl3sfeCz+dDWVkZLpsyCc7r8sJePn/AKIzOG4F7Ji7AoyUr8Gnl5yg/tjusddSv2Qe1yQsl3YWsnwyLSQdfVQtcDcBthXOwvHQdvJkI++0H8eAgYSzoEDkH3yuVeHfrNhQUFMDpdIbtEAnMZFQkagCYGws6aEQin8w6SKgDHSLrEO2MYj7FhwPziQ5WOMRyPgEyjmV5bqPBOtAh0g5680nslVKnUn5sN/adOIRbRl+L10rfQnO7JyEdnLkpSM1LRVFREZ5r3pqwDhLGgg5yHKKNhBrQQYP5RAdpDtFGQg3ooMF8ooM0BwlIqAP3TQ3WgQ7RchD5TClCCCGEEEIIIYQQEt9wUooQQgghhBBCCCGE2A4npQghhBBCCCGEEEKI7dj+oPOJl01Es2rsSe2KoiAnrQ+qm2thRFtt9gIqAAVQ0ow9TosOdKBD5B3SFDdK3i0R8aBzoxlltgaA+bGgAx3oYI1DtDOK+UQHOtChJ2I9n4D4OJalAx3oEIjefLL/QecqoDZ5jS6Kk40n6UAHOsSbQ7rb+LKRxmAdIjYOdKADHeQ5SMmoRB8HOtCBDoHEeD59s2jsH8vSgQ50CERnPtk/KaUASnrizhbSgQ50CLYCQ5u1BoMZFS+/caUDHegQbCXGFos4zCc60IEOASsxtljE4TkeHehAh4AV6Pua7ZNSSqoTWdcNM7RsWlIq3pi7CtPWzjP0SsL6NfugNnmhpLmQ9RM60IEOUhx8r1Qa2q4VGM0oszUAzI8FHehAB2scpGQU84kOdKDDqcR6PgHxcSxLBzrQIRC9+cQHnRNCCCGEEEIIIYQQ2+GkFCGEEEIIIYQQQgixHU5KEUIIIYQQQgghhBDbiZlJqfwBozCjcDJycnIwo3Ay8geMSkgHX1ULPHtqUFxcDM+eGviqWugQJQf2g4aEOkQbCTWQ4MB+1GAdNFgHGUiogQQH9qMG66DBOshBQh0kOLAnNVgHjUSrg/1v3wuDlCQ3Zo6fivkT52LcwHM7P19+0xIAwM6jn2FlyVps2LEFLe2tceugev1or6hHa3kt/NXaNha/ubjz544cN9z5fZA0PAuKy5p5RjposB80JNQh2kiogQQH9qMG66DBOshAQg0kOLAfNVgHDdZBDhLqIMGBPanBOmgkch0U1fD7R8PD5/OhrKwMl02ZBOd1eSG/P7TfEGy8/VkM7JsHv+qH0+EMXKffB4fiwNGaSsxYdjMOVB3udZ2dT6BP1/cEegkOvro2NL1+BGqDN+R3lUwX0qcPgjM7mQ4WOLAfNKyog++VSry7dRsKCgrgdAauzw7CySgragCENxYSHKzox3AdWAcN1kHDqjpEO6OYT+E7xHM/sg7hO8RzHWIpnwAZx9MSHOL1mJ51MOYQr3XQm08ib98b2m8I/nbnS8jLPgOKogQtCAA4HU4oioK87DPwzl0v4+zcwXHl4KtrQ+P6Q1AbQzcnAKiNXjSuPwRfXRsdIuzAftCQUIdoI6EGEhzYjxqsgwbrIAMJNZDgwH7UYB00WAc5SKiDBAf2pAbroME6GJiUOnz4MG6++WYUFhbisssuw7PPPhsRkQ5SktzYePuzyHSnw+XUd3ehy+lCpjsdmxauRkqSOy4cVK8fTa8fAdr8gN5r2VQAbdpyqtdPhwg5sB80JNQhFMwnexzYjxqsgwbroA/mkz0O7EcN1kGDddCH1fkEyKiDBAf2pAbroME6aIQ1KeX3+zF//nz06dMHGzduxG9+8xusWLECb7zxhmmRDmaOn4qBffN0F6QDl9OFQaf3R9F5U+LCob2iXrt8L9ybK1VAbfCivaKeDhFyYD9oSKhDbzCf7HNgP2qwDhqsQ2iYT/Y5sB81WAcN1iE0duQTIKMOEhzYkxqsgwbroBHWpFR1dTVGjRqFX//61xgyZAgmTpyIiy++GDt27DAt0sH8iXPhV43N+Pn8PsyfODcuHFrLa6O6PB2+hf2gIaEOvcF8ss+B/ajBOmiwDqFhPtnnwH7UYB00WIfQ2JFPgIw6SHBgT2qwDhqsg0ZYk1L9+vXDE088gYyMDKiqih07duDf//43JkyYYFoE0F47OG7guT3ewxgKp8OJgkGjTb2uUIKDr6ql84n7RvFXt5p6dSQdNNgPGhLqEArmkz0O7EcN1kGDddAH88keB/ajBuugwTrow+p8AmTUQYIDe1KDddBgHb4lvGu0ujBp0iRUVlbi8ssvx+TJk3UvpygK0pJSg/5sTN5IozrdGJ03AvtOHAr4vEFRoMaAg6feExEHVwOQmhe4DTrod2A/aFhdh0ZFicj6OzCaT0DPdbC6BkDosZDgYHU/6nFgHTRYBw076hDJjGI+WeeQKP3IOuhzSJQ6SM8nQMbxtASHRDimZx30OyRCHfTmk6Kqarh3MAIAdu3aherqavz617/GD37wAzzwwAO9fr/jdaEzZ87Ehg0bgn4nJycHgwebf4L74cOHUV1dHfD51KlTcfLkSfTr1w9btmwR61BcXIzFixebdrjvvvtQVFREBxMO7AcNq+vQkQuRep1xuPkEhM4oq2sAhB4LCQ5W96MeB9ZBg3XQsKMOkcwo5pN1DonSj6yDPodEqYP0fAJkHE9LcEiEY3rWQb9DItRBbz4ZvlJq7NixAIDW1lbceeed+MUvfoHk5OSQy9V46jBt7bygP5tROBnLb1piVKmTR0tW4LXStwI+r26u7fxbsoNnT43p7QPA8tJ1eK55Kx1MOLAfNKyuQ6OnzvS6u2I0n4CeM8rqGgChx0KCg9X9qMeBddBgHTTsqEMkM4r5ZJ1DovQj66DPIVHqID2fABnH0xIcEuGYnnXQ75AIddCbT2FNSlVXV6OsrAzf//73Oz8bNmwY2tvb0djYiL59+4Zch6qqaG4PfqnaJ5V7w9HpkU++2Bt0Gx0XhUl38GVF5jJcbyboYNKB/aBhVx3MEIl86nAJ5mh1DTq2Ld3B6n7U48A6aLAOGnbWwSjMJ3scEq0fWQfWoauDUazOJ0DG8bQEh0Q6pmcdWIeuDqEI60Hnx44dw8KFC3HixIlvBT75BH379tUdWL1Rfmw3dh79DD6/z9DyPr8PZUc+xa4v9sS0gzM3BY4ct+HlAcCR44YzN4UOJh3YDxoS6hAK5pM9DuxHDdZBg3XQB/PJHgf2owbroME66MPqfAJk1EGCA3tSg3XQYB2+JaxJqbFjx2L06NG47777sG/fPpSUlGDp0qX4+c9/bkqiKytL1sKhhKXVidPhxMqStXHh4M7vE9Xl6fAt7AcNCXXoDeaTfQ7sRw3WQYN1CA3zyT4H9qMG66DBOoTGjnwCZNRBggN7UoN10GAdNMLautPpxPLly5GamorZs2fj/vvvx4033oibbrrJtEgHG3ZswdGaSnh93rCW8/q8OPLVFyj+OPg937HmkDQ8C0qmCwj3qj4FUDJdSBqeRYcIObAfNCTUoTeYT/Y5sB81WAcN1iE0zCf7HNiPGqyDBusQGjvyCZBRBwkO7EkN1kGDddAIe0rsjDPOwLJly7Bjxw68//77+PnPfw4lgq8ibWlvxTVP34KG1ibdhfH6vGhobcKMZTejpb01LhwUlwPp0wcByQ79TaoASNaWU1zGZjvpEAj7QUNCHULBfLLHgf2owTposA76YD7Z48B+1GAdNFgHfVidT4CMOkhwYE9qsA4arIOG+X+FBew/eQhXLJ2Nyjrt3uae7nHs+Lyy7gSuWDobB6oOx5WDMzsZGbOGQMnQ9zx6JcOFjFlD4MzW95YMOuiH/aAhoQ7RRkINJDiwHzVYBw3WQQYSaiDBgf2owTposA5ykFAHCQ7sSQ3WQYN1CPPte3ZyoOowJjx8JYrOm4L5E+eiYNDogO/sOrYHK0vWovjjrZb8FkGCgzM7GZlzzkZ7RT1ay2vhrw7chiPHDXd+H+3yvwjMltIhOOwHDQl1iDYSaiDBgf2owTposA4ykFADCQ7sRw3WQYN1kIOEOkhwYE9qsA4aiV4HsZNSgHYp2brtm7Bu+ybkDxiF0XkjcM/EBXi0ZAU+rfwc5cd2J4SD4nIgeVQ2kkdlw1fVAlcDcFvhHCwvXQdvJkw9cZ8O4cF+0JBQh2gjoQYSHNiPGqyDBusgAwk1kODAftRgHTRYBzlIqIMEB/akBuugkch1EHn7XjDKj+3Ga6Vvobq6Gq+VvhWV0Jbg4MxNQerIPigqKkLqyD62NCcdgsN+0JBQh2gjoQYSHNiPGqyDBusgAwk1kODAftRgHTRYBzlIqIMEB/akBuugkWh1iJlJKUIIIYQQQgghhBASP3BSihBCCCGEEEIIIYTYDielCCGEEEIIIYQQQojtKKqqqnZsyOfzoaysDBMvm4hm1diT2hVFQU5aH1Q318KIttrsBVQACqCkGXvGOx3oQIfIO6QpbpS8W4KCggI4nU5DDmYxm1FmawCYHws60IEO1jhEO6OYT3SgAx16ItbzCYiPY1k60IEOgejNJ/vfvqcCapPX6KI42XiSDnSgQ7w5pLuNLxtpDNYhYuNABzrQQZ6DlIxK9HGgAx3oEEiM59M3i8b+sSwd6ECHQHTmk/2TUgqgpCfubCEd6ECHYCswtFlrMJhR8fIbVzrQgQ7BVmJssYjDfKIDHegQsBJji0UcnuPRgQ50CFiBvq/ZPimlpDqRdd0wQ8umJaXijbmrMG3tPDS3e8Jevn7NPqhNXihpLmT9hA50oIMUB98rlYa2awVGM8psDQDzY0EHOtDBGgcpGcV8ogMd6HAqsZ5PQHwcy9KBDnQIRG8+8UHnhBBCCCGEEEIIIcR2OClFCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHZiZlIqf8AozCicjJycHMwonIz8AaMS0sFX1QLPnhoUFxfDs6cGvqoW2x1YBw3WQUNCHaKNhBpIcGA/0qEr7AcZSKiBBAcJ/SjBQcJYSHDgWMhBQh0kOEjoSQkOEsZCgkOijYX9b98Lg5QkN2aOn4r5E+di3MBzOz9fftMSAMDOo59hZclabNixBS3trXHroHr9aK+oR2t5LfzV2jYWv7m48+eOHDfc+X2QNDwLisuaeUbWQYN10JBQh2gjoQYSHNiPdOgK+0EGEmogwUFCP0pwkDAWEhw4FnKQUAcJDhJ6UoKDhLGQ4JDIY6Goht8/Gh4+nw9lZWW4bMokOK/LC/n9of2GYOPtz2Jg3zz4VT+cDmfgOv0+OBQHjtZUYsaym3Gg6nCv6+x8An26vifQS3Dw1bWh6fUjUBu8Ib+rZLqQPn0QnNnJEXVgHTRYBw0r6uB7pRLvbt2GgoICOJ2B67ODcDLKihoA4Y2FBAcr+jFcBwl1oMM364/jfoh2RjGfwneQ0I8SHCSMhQSHeB6LWMonQMbxtAQHCcf0EhwkjIUEh3gdC735JPL2vaH9huBvd76EvOwzoChK0IIAgNPhhKIoyMs+A+/c9TLOzh0cVw6+ujY0rj8EtTF0cwKA2uhF4/pD8NW1RcyBddBgHTQk1CHaSKiBBAf2Ix26wn6QgYQaSHCQ0I8SHCSMhQQHjoUcJNRBgoOEnpTgIGEsJDhwLExMSs2fPx/33HNPRCS6kpLkxsbbn0WmOx0up767C11OFzLd6di0cDVSktxx4aB6/Wh6/QjQ5gf0XsumAmjTllO9ftMOrIMG66AhoQ7hYEVGSaiBBAf2Ix26wn4IH+aTdQ4S+lGCg4SxkODAsQgfnuNZ6yChJyU4SBgLCQ4cCw1Dk1KbN29GSUmJ6Y0HY+b4qRjYN093QTpwOV0YdHp/FJ03JS4c2ivqtcv3wr25UgXUBi/aK+pNO7AOGqyDhoQ66MWqjJJQAwkO7Ec6dIX9EB7MJ2sdJPSjBAcJYyHBgWMRHjzHs95BQk9KcJAwFhIcOBYaYU9K1dXV4bHHHsPYsWNNbzwY8yfOhV81NuPn8/swf+LcuHBoLa+N6vIA69AB66AhoQ56sDKjJNRAggP7kQ5dYT/oh/lkvYOEfpTgIGEsJDhwLPTDczx7HCT0pAQHCWMhwYFjoRH2pNRvf/tbXH311Rg2LPTDssIlf8AojBt4bo/3MIbC6XCiYNBoU68rlODgq2rpfOK+UfzVraZeHck6aLAOGhLqoBerMkpCDSQ4sB/p0BX2Q3gwn6x1kNCPEhwkjIUEB45FePAcz3oHCT0pwUHCWEhw4Fh8S1jXaH3wwQf46KOP8MYbb+DXv/61oQ0qioK0pNSgPxuTN9LQOk9ldN4I7DtxKODzBkWBGgMOnnpPRBxcDUBqXuA2WAf9DqyDhtV1aFSUiKzfyoyyugZA6LGQ4GB1P+pxkFAHOmgkSj9EIqOYT9Y7SOhHCQ4SxkKCQ6KMhfR8AmQcT0twkHBML8FBwlhIcEiEsdCbT7onpVpbW/GrX/0KDz74IFJSUnQLnkrf1GxsmLsq6M9ycnIMr7cr90xcgFtGXxvw+dR1U3Gy8SRy0vrgDcEOxcXFWPzmYtMOtxXOQVFRkSEH1kGDddCwug4zN840vW6rM8rqGgChx0KCg9X9qMdBQh3ooJEo/WA2o5hP9jhI6EcJDhLGQoJDooyF9HwCZBxPS3CQcEwvwUHCWEhwSISx0JtPuielli1bhjFjxuDSSy/VbxeEGk8dpq2dF/RnMwonY/lNS0ytHwAeLVmB10rfCvi8urm282/JDp49Naa3DwDLS9fhueathhxYBw3WQcPqOjR66kyv2+qMsroGQOixkOBgdT/qcZBQBzpoJEo/mM0o5pM9DhL6UYKDhLGQ4JAoYyE9nwAZx9MSHCQc00twkDAWEhwSYSz05pPuSanNmzejuroahYWFAIC2tjYAwF//+leUlpbqXQ1UVUVze/BL1T6p3Kt7Pb3xyRd7g25DVdWYcPBlReZWJm8mWAewDh3EQh3MYHVGWV2Djm1Ld7C6H/U4SKgDHTQSrR+Mwnyyx0FCP0pwkDAWEhwSbSyMwnM8+xwkHNNLcJAwFhIcEmksQqF7UurPf/4zvF5v5///3e9+BwC488479a4iJOXHdmPn0c8wpv9IQw/b8vl92HVsD3Z9sSemHZy5KXDkuE09+MyR44Yz1/gluKyDBuugIaEOobA6oyTUQIID+5EOXWE/6IP5ZI+DhH6U4CBhLCQ4cCz0wXM8+xwk9KQEBwljIcGBY/Etut++179/fwwePLjzT3p6OtLT0zF48GBTAqeysmQtHErYLwUEoD39fWXJ2rhwcOf3ieryAOvQAeugIaEOvWFHRkmogQQH9iMdusJ+CA3zyT4HCf0owUHCWEhw4FiEhud49jpI6EkJDhLGQoIDx0LD2NYtZMOOLThaUwmvzxv6y13w+rw48tUXKP44+D3fseaQNDwLSqYLCPeqPgVQMl1IGp5l2oF10GAdNCTUIdpIqIEEB/YjHbrCfpCBhBpIcJDQjxIcJIyFBAeOhRwk1EGCg4SelOAgYSwkOHAsNAxPSj366KN49NFHTQucSkt7K655+hY0tDbpLozX50VDaxNmLLsZLe3GL3+T5KC4HEifPghIduhvUgVAsrac4jI/38g6aLAOGhLqEA5WZJSEGkhwYD/SoSvsh/BhPlnnIKEfJThIGAsJDhyL8OE5nrUOEnpSgoOEsZDgwLHQEHelFADsP3kIVyydjcq6EwC0exWD0fF5Zd0JXLF0Ng5UHY4rB2d2MjJmDYGSoe/RX0qGCxmzhsCZnRwxB9ZBg3XQkFCHaCOhBhIc2I906Ar7QQYSaiDBQUI/SnCQMBYSHDgWcpBQBwkOEnpSgoOEsZDgwLEI40HndnOg6jAmPHwlis6bgvkT56Jg0OiA7+w6tgcrS9ai+OOtlvwWQYKDMzsZmXPORntFPVrLa4M+CM2R44Y7v492+V8EZktPhXXQYB00JNQh2kiogQQH9iMdusJ+kIGEGkhwkNCPEhwkjIUEB46FHCTUQYKDhJ6U4CBhLCQ4JPpYiJ2UArRLydZt34R12zchf8AojM4bgXsmLsCjJSvwaeXnKD+2OyEcFJcDyaOykTwqG76qFrgagNsK52B56Tp4M2Hqift6YR00WAcNCXWINhJqIMGB/UiHrrAfZCChBhIcJPSjBAcJYyHBgWMhBwl1kOAgoSclOEgYCwkOiTwWIm/fC0b5sd14rfQtVFdX47XSt6IS2hIcnLkpSB3ZB0VFRUgd2ceW5jwV1kGDddCQUIdoI6EGEhzYj3ToCvtBBhJqIMFBQj9KcJAwFhIcOBZykFAHCQ4SelKCg4SxkOCQaGMRM5NShBBCCCGEEEIIISR+4KQUIYQQQgghhBBCCLEdTkoRQgghhBBCCCGEENtRVFVV7diQz+dDWVkZJl42Ec2qsSe1K4qCnLQ+qG6uhRFttdkLqAAUQEkz9ox3OtCBDpF3SFPcKHm3BAUFBXA6nYYczGI2o8zWADA/FnSgAx2scYh2RjGf6EAHOvRErOcTEB/HsnSgAx0C0ZtP9r99TwXUJq/RRXGy8SQd6ECHeHNIdxtfNtIYrEPExoEOdKCDPAcpGZXo40AHOtAhkBjPp28Wjf1jWTrQgQ6B6Mwn+yelFEBJT9zZQjrQgQ7BVmBos9ZgMKPi5TeudKADHYKtxNhiEYf5RAc60CFgJcYWizg8x6MDHegQsAJ9X7N9UkpJdSLrumGGlk1LSsUbc1dh2tp5aG73hL18/Zp9UJu8UNJcyPoJHehABykOvlcqDW3XCoxmlNkaAObHgg50oIM1DlIyivlEBzrQ4VRiPZ+A+DiWpQMd6BCI3nzig84JIYQQQgghhBBCiO1wUooQQgghhBBCCCGE2A4npQghhBBCCCGEEEKI7cTMpFT+gFGYUTgZOTk5mFE4GfkDRtnu4KtqgWdPDYqLi+HZUwNfVUtCOkgYCwkOEsZCgoOEsYg2EmogoRckOEgYCzposB9kIKEGEnpBggPHQoN10JBQBwlIqIOEfpDgwLHQYB007KyD/W/fC4OUJDdmjp+K+RPnYtzAczs/X37TEgDAzqOfYWXJWmzYsQUt7a2WOKheP9or6tFaXgt/tbaNxW8u7vy5I8cNd34fJA3PguKyZo5PgoOEsZDgIGEsJDhIGItoI6EGEnpBgoOEsaCDBvtBBhJqIKEXJDhwLDRYBw0JdZCAhDpI6AcJDhwLDdZBI1p1UFTD7x8ND5/Ph7KyMlw2ZRKc1+WF/P7QfkOw8fZnMbBvHvyqH06HM3Cdfh8cigNHayoxY9nNOFB1uNd1dj6BPl3fE+h9dW1oev0I1AZvyO8qmS6kTx8EZ3Zy3DlIGAsJDhLGQoKDFWPhe6US727dhoKCAjidgeuzg3AyyooaAOGNhRW9EIsOEsaCDt+sP477IdoZxXyKTQeOhQbroMF80uAxvRwHjoUG66ARzXM8kbfvDe03BH+78yXkZZ8BRVGCFgQAnA4nFEVBXvYZeOeul3F27uCIOfjq2tC4/hDUxtCNAQBqoxeN6w/BV9cWVw4SxkKCg4SxkOAgYSyijYQaSOgFCQ4SxoIOGuwHGUiogYRekODAsdBgHTQk1EECEuogoR8kOHAsNFgHjWjXIexJqbfffhsjR47s9mfRokURkQG0S8Y23v4sMt3pcDn13V3ocrqQ6U7HpoWrkZLkNu2gev1oev0I0OYH9F5HpgJo05ZTvf64cJAwFhIcJIyFBAcJYxEK5lNPC4H9iPjMJwkO7Ad9MJ96WgjMJ8TnWLAOGhLqEAqr8wmQUQcJ/SDBgWOhwTpoSKhD2JNS+/btw+WXX47333+/88/DDz9sWqSDmeOnYmDfPN0F6cDldGHQ6f1RdN4U0w7tFfXapXPh3tioAmqDF+0V9XHhIGEsJDhIGAsJDhLGIhTMp15gPwKIv3yS4MB+0AfzqReYTwDibyxYBw0JdQiF1fkEyKiDhH6Q4MCx0GAdNCTUIexJqf3792PEiBHIzc3t/JOVlWVapIP5E+fCrxqb8fP5fZg/ca5ph9by2qguL8VBwlhIcJAwFhIcJIxFKJhP1i8vxUHCWNBBg/2gD+aT9ctLceBYaLAOGhLqEAqr8wmQUQcJ/SDBgWOhwTpoSKiDoUmpIUOGmN5wMPIHjMK4gef2eA9jKJwOJwoGjTb1ukJfVUvn0+6N4q9uNfXaRgkOEsZCgoOEsZDgIGEs9MB8Cg37MX7ySYID+0E/zKfQMJ/iZyxYBw0JddCDlfkEyKiDhH6Q4MCx0GAdNCTUAQDCukZLVVUcPHgQ77//Pv7whz/A5/PhRz/6ERYtWoTk5NBvqAAARVGQlpQa9Gdj8kaGo9Mjo/NGYN+JQwGfNygK1BAOnnpPRBxcDUBqXuA2YsVBwlhIcJAwFhIcrB6LRkUxve5I5BPQcx2srgEQeiys7oVYcZAwFnTQSJR+MJtRzCf9MJ80Yn0sWAcN5pMGj+nlOHAsNFgHDSnneGFNSlVWVsLj8SA5ORlPPPEEjh07hocffhgtLS144IEHdK2jb2o2NsxdFfRnOTk54ej0yD0TF+CW0dcGfD513VScbDyJnLQ+eKMHh+LiYix+c7Fph9sK56CoqChmHSSMhQQHCWMhwcHqsZi5cabpdUcin4CeM8rqGgChx8LqXogVBwljQQeNROkHsxnFfNIP80kj1seCddBgPmnwmF6OA8dCg3XQkHKOF9akVP/+/bF9+3acdtppUBQFo0aNgt/vx1133YV7770XTmfoy75qPHWYtnZe0J/NKJyM5TctCUcpKI+WrMBrpW8FfF7dXNv5d08Onj01prcPAMtL1+G55q0x6yBhLCQ4SBgLCQ5Wj0Wjp870uiORT0DPGWV1DYDQY2F1L8SKg4SxoINGovSD2YxiPumH+aQR62PBOmgwnzR4TC/HgWOhwTpoSDnHC+8R6wCys7O7/f+hQ4eitbUVX3/9Nfr27RtyeVVV0dwe/FK1Tyr3hqsTfD1f7A26DVVVQzr4sszfRgQA3kzEtIOEsZDgIGEsJDjYNRZmMZtPHS7BHK2uQce2e3OwuhdixUHCWNBBI9H6wQzMJ30wn75ZT4yPBeugwXzS4DG9HAeOhQbroCHlHC+sB52/9957uPDCC+HxfLvB3bt3Izs7W3dg9Ub5sd3YefQz+Pw+Q8v7/D6UHfkUu77YY9jBmZsCR47b8PIA4Mhxw5mbEtMOEsZCgoOEsZDgIGEsQsF80gf7MX7ySYID+0EfzCd9MJ/iZyxYBw0JdQiF1fkEyKiDhH6Q4MCx0GAdNCTUAQhzUqqwsBButxsPPPAADhw4gJKSEjz22GO45ZZbTEl0ZWXJWjiUsF8KCEB7+vvKkrWmHdz5faK6vBQHCWMhwUHCWEhwkDAWvcF8smd5KQ4SxoIOGuyH0DCf7FleigPHQoN10JBQh96wI58AGXWQ0A8SHDgWGqyDhoQ6hLX1jIwMrF69GjU1NZg5cybuv/9+zJ49O6KhtWHHFhytqYTX5w1rOa/PiyNffYHij4Pf8x0OScOzoGS6gHCvqFMAJdOFpOFZceEgYSwkOEgYCwkOEsaiN5hPIWA/Aoi/fJLgwH4IDfMpBMwnAPE3FqyDhoQ69IYd+QTIqIOEfpDgwLHQYB00JNQh7Cmx4cOH47nnnkNpaSnef/99LFy4EEoEXufeQUt7K655+hY0tDbpLozX50VDaxNmLLsZLe2tph0UlwPp0wcByQ79DaIASNaWU1zGZhqlOUgYCwkOEsZCgoOEsQgF86mnhcB+RHzmkwQH9oM+mE89LQTmE+JzLFgHDQl1CIXV+QTIqIOEfpDgwLHQYB00JNTB/L/CAvafPIQrls5GZd0JAOjxHseOzyvrTuCKpbNxoOpwxByc2cnImDUESoa+Z8ErGS5kzBoCZ3ZyXDlIGAsJDhLGQoKDhLGINhJqIKEXJDhIGAs6aLAfZCChBhJ6QYIDx0KDddCQUAcJSKiDhH6Q4MCx0GAdNKJdh7DfvmcXB6oOY8LDV6LovCmYP3EuCgaNDvjOrmN7sLJkLYo/3mrJbxGc2cnInHM22ivq0VpeC3914DYcOW648/tol95FYKZSooOEsZDgIGEsJDhIGItoI6EGEnpBgoOEsaCDBvtBBhJqIKEXJDhwLDRYBw0JdZCAhDpI6AcJDhwLDdZBI5p1EDspBWiXkq3bvgnrtm9C/oBRGJ03AvdMXIBHS1bg08rPUX5st+UOisuB5FHZSB6VDV9VC1wNwG2Fc7C8dB28mTD1tPtYcpAwFhIcJIyFBAcJYxFtJNRAQi9IcJAwFnTQYD/IQEINJPSCBAeOhQbroCGhDhKQUAcJ/SDBgWOhwTpoRKsOIm/fC0b5sd14rfQtVFdX47XSt6IS2s7cFKSO7IOioiKkjuxjS2NIdJAwFhIcJIyFBAcJYxFtJNRAQi9IcJAwFnTQYD/IQEINJPSCBAeOhQbroCGhDhKQUAcJ/SDBgWOhwTpo2FmHmJmUIoQQQgghhBBCCCHxAyelCCGEEEIIIYQQQojtcFKKEEIIIYQQQgghhNiOoqqqaseGfD4fysrKMPGyiWhWjT2pXVEU5KT1QXVzLYxoq81eQAWgAEqasWe804EOdIi8Q5riRsm7JSgoKIDT6TTkYBazGWW2BoD5saADHehgjUO0M4r5RAc60KEnYj2fgPg4lqUDHegQiN58sv/teyqgNnmNLoqTjSfpQAc6xJtDutv4spHGYB0iNg50oAMd5DlIyahEHwc60IEOgcR4Pn2zaOwfy9KBDnQIRGc+2T8ppQBKeuLOFtKBDnQItgJDm7UGgxkVL79xpQMd6BBsJcYWizjMJzrQgQ4BKzG2WMThOR4d6ECHgBXo+5rtk1JKqhNZ1w0ztGxaUiremLsK09bOQ3O7J+zl69fsg9rkhZLmQtZP6EAHOkhx8L1SaWi7VmA0o8zWADA/FnSgAx2scZCSUcwnOtCBDqcS6/kExMexLB3oQIdA9OYTH3ROCCGEEEIIIYQQQmyHk1KEEEIIIYQQQgghxHY4KUUIIYQQQgghhBBCbCdmJqXyB4zCjMLJyMnJwYzCycgfMCohHXxVLfDsqUFxcTE8e2rgq2qhQ5Qc2A8aEuoQbSTUQIKDhH6kg4aEfqCDDCTUQIKDhP2SDnIcJPSkBAcJSKiDBAcJ+wUd5DhI6Ek7Hex/+14YpCS5MXP8VMyfOBfjBp7b+fnym5YAAHYe/QwrS9Ziw44taGlvjVsH1etHe0U9Wstr4a/WtrH4zcWdP3fkuOHO74Ok4VlQXNbMM9JBg/2gIaEO0UZCDSQ4SOhHOmhI6Ac6yEBCDSQ4SNgv6SDHQUJPSnCQgIQ6SHCQsF/QQY6DhJ6MloOiGn7/aHj4fD6UlZXhsimT4LwuL+T3h/Ybgo23P4uBffPgV/1wOpyB6/T74FAcOFpTiRnLbsaBqsO9rrPzCfTp+p5AL8HBV9eGptePQG3whvyukulC+vRBcGYn08ECB/aDhhV18L1SiXe3bkNBQQGczsD12UE4GWVFDYDwxkKCgxX9SAdjDhL6IZ4dop1RzKfwHSTsl3SQ4yChJ5lPGhKOpyU4SDimp4McBwk9Gc1zPJG37w3tNwR/u/Ml5GWfAUVRghYEAJwOJxRFQV72GXjnrpdxdu7guHLw1bWhcf0hqI2hdxAAUBu9aFx/CL66NjpE2IH9oCGhDtFGQg0kOEjoRzpoSOgHOshAQg0kOEjYL+kgx0FCT0pwkICEOkhwkLBf0EGOg4SejLZD2JNSbW1t+M1vfoMLLrgA3/nOd/D73/8ekbzYKiXJjY23P4tMdzpcTn13F7qcLmS607Fp4WqkJLnjwkH1+tH0+hGgzQ/oLa8KoE1bTvX66RAhB/aDhoQ6hIL5ZI+DhH6kg4aEfqCDPphP9jhI2C/pIMdBQk9KcAiF1fkEyKiDBAcJ+wUd5DhI6EkJDmFPSj388MP45z//idWrV+Pxxx/HK6+8gpdfftm0SAczx0/FwL55ugvSgcvpwqDT+6PovClx4dBeUa9dQhjufw9UQG3wor2ing4RcmA/aEioQyiYT/Y4SOhHOmhI6Ac66IP5ZI+DhP2SDnIcJPSkBIdQWJ1PgIw6SHCQsF/QQY6DhJ6U4BDWpFRdXR02bNiAhx56CPn5+bj44ovxs5/9DDt37jQt0sH8iXPhV43NOvr8PsyfODcuHFrLa6O6PB2+hf2gIaEOvcF8ss9BQj/SQUNCP9AhNMwn+xwk7Jd0kOMgoSclOPSGHfkEyKiDBAcJ+wUd5DhI6EkJDmFNSu3YsQMZGRmYMGFC52fz58/HkiVLTIsA2msHxw08t8d7GEPhdDhRMGi0qdcVSnDwVbV0PvXfKP7qVlOvr6SDBvtBQ0IdQsF8ssdBQj/SQUNCP9BBH8wnexwk7Jd0kOMgoSclOITC6nwCZNRBgoOE/YIOchwk9KQEBwAI6xqto0ePon///ti0aROeeeYZtLe3o6ioCAsWLIDDoW9+S1EUpCWlBv3ZmLyR4ej0yOi8Edh34lDA5w2KAjUGHDz1nog4uBqA1LzAbdBBvwP7QcPqOjQqiul1RyKfgJ7rYHUNgNBjIcHB6n6kg34HCf2QKA5mM4r5ZI+DhP2SDnIcJPQk80lDwvG0BAcJx/R0kOMgoSelnOOFNSnV3NyMw4cP46WXXsKSJUtQVVWFBx98EKmpqfjZz36max19U7OxYe6qoD/LyckJR6dH7pm4ALeMvjbg86nrpuJk40nkpPXBG4IdiouLsfjNxaYdbiucg6KiIjqYcGA/aFhdh5kbZ5pedyTyCeg5o6yuARB6LCQ4WN2PdNDvIKEfEsXBbEYxn+xxkLBf0kGOg4SeZD5pSDieluAg4ZieDnIcJPSklHO8sCalXC4XGhsb8fjjj6N///4AgMrKSrz44ou6Q6vGU4dpa+cF/dmMwslYfpP5S0UfLVmB10rfCvi8urm282/JDp49Naa3DwDLS9fhueatdDDhwH7QsLoOjZ460+uORD4BPWeU1TUAQo+FBAer+5EO+h0k9EOiOJjNKOaTPQ4S9ks6yHGQ0JPMJw0Jx9MSHCQc09NBjoOEnpRyjhfWpFRubi7cbndnYAHAWWedhePHj+teh6qqaG4PfrncJ5V7w9HpkU++2Bt0Gx2vNpXu4MsyfysTAHgzQQeTDuwHDbvqYIZI5FOHSzBHq2vQsW3pDlb3Ix30O0joh0RzMArzyR4HCfslHeQ4SOhJ5pOGhONpCQ4SjunpIMdBQk9KOccL60Hn48aNQ2trKw4ePNj52YEDB7qFmBnKj+3GzqOfwef3GVre5/eh7Min2PXFnph2cOamwJHjNrw8ADhy3HDmptDBpAP7QUNCHULBfLLHQUI/0kFDQj/QQR/MJ3scJOyXdJDjIKEnJTiEwup8AmTUQYKDhP2CDnIcJPSkBAcgzEmps88+G5dddhnuvfde7NmzB++99x5WrlyJ66+/3pREV1aWrIVDCUurE6fDiZUla+PCwZ3fJ6rL0+Fb2A8aEurQG8wn+xwk9CMdNCT0Ax1Cw3yyz0HCfkkHOQ4SelKCQ2/YkU+AjDpIcJCwX9BBjoOEnpTgEPbWf/e732HQoEG4/vrrcffdd+OGG27AjTfeaFqkgw07tuBoTSW8Pm9Yy3l9Xhz56gsUfxz8vvNYc0gangUl0wWEe2WhAiiZLiQNz6JDhBzYDxoS6hAK5pM9DhL6kQ4aEvqBDvpgPtnjIGG/pIMcBwk9KcEhFFbnEyCjDhIcJOwXdJDjIKEnJTiEPSmVmZmJxx57DKWlpfjnP/+JhQsXQonA69w7aGlvxTVP34KG1ibdhfH6vGhobcKMZTejpb01LhwUlwPp0wcByQ79O4oCIFlbTnEZm+2kQyDsBw0JdQgF88keBwn9SAcNCf1AB30wn+xxkLBf0kGOg4SelOAQCqvzCZBRBwkOEvYLOshxkNCTEhzMV9IC9p88hCuWzkZl3QkA6PEex47PK+tO4Iqls3Gg6nBcOTizk5ExawiUDH3Po1cyXMiYNQTO7GQ6RNiB/aAhoQ7RRkINJDhI6Ec6aEjoBzrIQEINJDhI2C/pIMdBQk9KcJCAhDpIcJCwX9BBjoOEnoy2Q1hv37OTA1WHMeHhK1F03hTMnzgXBYNGB3xn17E9WFmyFsUfb7XktwgSHJzZycicczbaK+rRWl4Lf3XgNhw5brjz+2iXIEZgxpYOwWE/aEioQ7SRUAMJDhL6kQ4aEvqBDjKQUAMJDhL2SzrIcZDQkxIcJCChDhIcJOwXdJDjIKEno+kgdlIK0C4lW7d9E9Zt34T8AaMwOm8E7pm4AI+WrMCnlZ+j/NjuhHBQXA4kj8pG8qhs+Kpa4GoAbiucg+Wl6+DNhKmn/tMhPNgPGhLqEG0k1ECCg4R+pIOGhH6ggwwk1ECCg4T9kg5yHCT0pAQHCUiogwQHCfsFHeQ4SOjJaDmIvH0vGOXHduO10rdQXV2N10rfikpoS3Bw5qYgdWQfFBUVIXVkH1t2EDoEh/2gIaEO0UZCDSQ4SOhHOmhI6Ac6yEBCDSQ4SNgv6SDHQUJPSnCQgIQ6SHCQsF/QQY6DhJ600yFmJqUIIYQQQgghhBBCSPzASSlCCCGEEEIIIYQQYjuclCKEEEIIIYQQQgghtqOoqqrasSGfz4eysjJMvGwimlVjT2pXFAU5aX1Q3VwLI9pqsxdQASiAkmbsGe90oAMdIu+QprhR8m4JCgoK4HQ6DTmYxWxGma0BYH4s6EAHOljjEO2MYj7RgQ506IlYzycgPo5l6UAHOgSiN5/sf/ueCqhNXqOL4mTjSTrQgQ7x5pDuNr5spDFYh4iNAx3oQAd5DlIyKtHHgQ50oEMgMZ5P3ywa+8eydKADHQLRmU/2T0opgJKeuLOFdKADHYKtwNBmrcFgRsXLb1zpQAc6BFuJscUiDvOJDnSgQ8BKjC0WcXiORwc60CFgBfq+ZvuklJLqRNZ1wwwtm5aUijfmrsK0tfPQ3O4Je/n6NfugNnmhpLmQ9RM60IEOUhx8r1Qa2q4VGM0oszUAzI8FHehAB2scpGQU84kOdKDDqcR6PgHxcSxLBzrQIRC9+cQHnRNCCCGEEEIIIYQQ2+GkFCGEEEIIIYQQQgixHU5KEUIIIYQQQgghhBDb4aQUIYQQQgghhBBCCLGdmJmUyh8wCjMKJyMnJwczCicjf8AoOiSwg6+qBZ49NSguLoZnTw18VS22O0ioAx1kIKEGdJDjwHyigyQk1IAOchyYTxqsgxwk1IEOchy4b2okWh1sf/teOKQkuTFz/FTMnzgX4wae2/n58puWAAB2Hv0MK0vWYsOOLWhpb6VDnDuoXj/aK+rRWl4Lf7W2jcVvLu78uSPHDXd+HyQNz4Lisma+VUId6CADCTWggxwH5hMdJCGhBnSQ48B80mAd5CChDnSQ48B9UyOR66CoqqpGbG294PP5UFZWhsumTILzuryQ3x/abwg23v4sBvbNg1/1w+lwBq7T74NDceBoTSVmLLsZB6oO97rOztciput7LSId5Dj46trQ9PoRqA3ekN9VMl1Inz4IzuzkiDpIqEO8OvheqcS7W7ehoKAATmfg+uwgnIyyogZAeGNBBzkOVuRTuA4S6hDPDtHOKOYTHYw6MJ++WX8c1yGW8gmI32NZOhhz4DneN+uP0zrozaewptiKi4sxcuTIgD/nnHNOOKsJydB+Q/C3O19CXvYZUBQlaEEAwOlwQlEU5GWfgXfuehln5w6mQxw6+Ora0Lj+ENTG0DspAKiNXjSuPwRfXVvEHCTUgQ69w3yiA/MpscdCgkNPMJ/owHxiHaJdh95gRtGB+ybrEM06hDUpNXXqVLz//vudf959910MHjwYN910U0RkAO2SsY23P4tMdzpcTn13F7qcLmS607Fp4WqkJLnpEEcOqtePptePAG1+QO81fSqANm051es37SChDnQIDfOJDnY7MJ/ooBfmEx3sdmA+abAO+mBG0cFuB+6bGqyDRliTUikpKcjNze388/rrr0NVVdx5552mRTqYOX4qBvbN012QDlxOFwad3h9F502hQxw5tFfUa5cxhnuTqQqoDV60V9SbdpBQBzqEhvlEB7sdmE900AvziQ52OzCfNFgHfTCj6GC3A/dNDdZBw/ATsurq6rBq1Sr8z//8D5KTQ99zrZf5E+fCrxqb8fP5fZg/cS4d4sihtbw2qssDMupAh/BgPtHBDgfmEx2MwHyigx0OzCcN1iF8mFF0sMOB+6YG66BheFLqxRdfRL9+/fCjH/3ItEQH+QNGYdzAc3u8hzEUTocTBYNGm3pdIR3kOPiqWjrfPGAUf3WrqVdoSqgDHcKH+UQHqx2YT3QwCvOJDlY7MJ80WAdjMKPoYLUD900N1uFbwrtG6xtUVcWrr76KW265JexlFUVBWlJq0J+NyRtpRCeA0XkjsO/EoYDPGxQFKh1ixsFT74mIg6sBSM0L3Eas1CERHBoVJSLrB8zlE9BzHayuARB6LOggx8HqfNLjIKEOieIQqYxiPtHBDgfmk0ai1EHKMVSiH8vSQb8Dz/E0EqEOevNJUVU13DsYUV5ejuuvvx7//Oc/cdppp+lapuN1oTNnzsSGDRuCficnJweDB5t/gvvhw4dRXV0d8PnUqVNx8uRJ9OvXD1u2bKGDcIfi4mIsXrzYtMN9992HoqIiQw4S6pAIDh25EInXGRvJJyB0RlldAyD0WNBBjoPV+aTHQUIdEsUhUhnFfKKDHQ7MJ41EqUO0j6F4jkeHcB14jqeRCHXQm0+GrpR67733cP7554d1QNVBjacO09bOC/qzGYWTsfymJUaUuvFoyQq8VvpWwOfVzbWdf9NBvoNnT43p7QPA8tJ1eK55qyEHCXVIBIdGT53pdXdgJp+AnjPK6hoAoceCDnIcrM4nPQ4S6pAoDpHKKOYTHexwYD5pJEodpBxD8RyPDnodeI6nkQh10JtPhialysvLcd555xlZFKqqork9+KVqn1TuNbTOgPV8sTfoNjouCqNDbDj4siJzObI3EzFdh0RyiARm8qnDJZij1TXo2DYdYsPB6nzS4yChDonmYBbmEx3scGA+aSRaHSIBz/HoYIcDz/E0EqkOoTD0oPOKigoMGzbMyKK9Un5sN3Ye/Qw+v8/Q8j6/D2VHPsWuL/bQIQ4cnLkpcOS4DS8PAI4cN5y5KYaXl1AHOoQH84kOdjgwn+hgBOYTHexwYD5psA7hw4yigx0O3Dc1WIdvMTQpVV1djaysLFMb7omVJWvhUIy9FNDpcGJlyVo6xJGDO79PVJcHZNSBDvphPtHBLgfmEx3ChflEB7scmE8arEN4MKPoYJcD900N1kHD0NbLy8tx6aWXmt54MDbs2IKjNZXw+rxhLef1eXHkqy9Q/HHwe77pEJsOScOzoGS6gHCvblQAJdOFpOHm/8MqoQ500A/ziQ52OTCf6BAuzCc62OXAfNJgHcKDGUUHuxy4b2qwDhrGpsQspKW9Fdc8fQsaWpt0F8br86KhtQkzlt2MlvZWOsSRg+JyIH36ICDZoX9nVQAka8spLvMtLqEOdJCBhBrQQY4D84kOkpBQAzrIcWA+abAOcpBQBzrIceC+qcE6aIiblAKA/ScP4Yqls1FZdwIAerzHsePzyroTuGLpbByoOkyHOHRwZicjY9YQKBn6nsuvZLiQMWsInNnJEXOQUAc6yEBCDeggx4H5RAdJSKgBHeQ4MJ80WAc5SKgDHeQ4cN/UYB0Mvn3PDg5UHcaEh69E0XlTMH/iXBQMGh3wnV3H9mBlyVoUf7zVkt8i0EGOgzM7GZlzzkZ7RT1ay2vhrw7chiPHDXd+H+0yyAjMGp+KhDrQQQYSakAHOQ7MJzpIQkIN6CDHgfmkwTrIQUId6CDHgfumRqLXQVEj+R7RXvD5fCgrK8NlUybBeV1e2MvnDxiF0XkjcM/EBXi0ZAU+rfwc5cd2h7WO+jX7oDZ5oaS7kPWT8N8sQQc5Dr6qFrgagNsK52B56Tp4MxH2mwfioQ7x4uB7pRLvbt2GgoICOJ3OsB0igZmMikQNAHNjQQc5DpHIJ7MOEuoQTw7RzijmEx0i5cB80oinOsRyPgHxcyxLh8g48BxPI17qoDefxF4pdSrlx3Zj34lDuGX0tXit9C00t3vokMAOztwUpOaloqioCM81b03YOtBBBhJqQAc5DswnOkhCQg3oIMeB+aTBOshBQh3oIMeB+6ZGotVB5DOlCCGEEEIIIYQQQkh8w0kpQgghhBBCCCGEEGI7nJQihBBCCCGEEEIIIbZj+4POJ142Ec2qsSe1K4qCnLQ+qG6uhRFttdkLqAAUQEkz9jgtOtCBDpF3SFPcKHm3RMSDzo1mlNkaAObHgg50oIM1DtHOKOYTHehAh56I9XwC4uNYlg50oEMgevPJ/gedq4Da5DW6KE42nqQDHegQbw7pbuPLRhqDdYjYONCBDnSQ5yAloxJ9HOhABzoEEuP59M2isX8sSwc60CEQnflk/6SUAijpiTtbSAc60CHYCgxt1hoMZlS8/MaVDnSgQ7CVGFss4jCf6EAHOgSsxNhiEYfneHSgAx0CVqDva7ZPSimpTmRdN8zQsmlJqXhj7ipMWzvP0CsJ69fsg9rkhZLmQtZP6EAHOkhx8L1SaWi7VmA0o8zWADA/FnSgAx2scZCSUcwnOtCBDqcS6/kExMexLB3oQIdA9OYTH3ROCCGEEEIIIYQQQmyHk1KEEEIIIYQQEg38/mgbEEJIVLH/mVKEEEIIIYQQkoCMq2rBDbvrcHGlByNr25D8xAQccijY2ycZH+Sl4oVR2diZmxJtTUIIsQ1OSoWBr6oFnnoPiouL4dlTA1+WAqfN/9GgAx2kORAZSOgFOtBBmgORgYReoAMdou1wVl0blm07jkuOe9CuAJ+owAYADQAy/SrO+aoVP61pxfxddfjHmalYOOlMHMxOttSJaCRqT9KBDlIcOCkVAtXrR3tFPVrLa+GvbgUALH5zcefPHTluuPP7IGl4FhSXNXdD0oEO0hyIDCT0Ah3oIM2ByEBCL9CBDlIcZn3+NZ7e9iXafCqeA/CkCpQF+V6BCiwCMOu4Bx++dBC3TToTG0ZkRdSFaCR6T9KBDpIcOCnVC766NjS9fgRqg7fH7/irW+HZ9iVa/l2N9OmD4IzwbzToQAdpDkQGEnqBDnSQ5kBkIKEX6EAHKQ6zPv8aK98+js8B/AjAYfT8UN9yAD8D8BsAf/WpWPV2JRSoWD/itIi4EI1E70k60EGaQ9jTW8ePH8ett96K8847D5MmTcKaNWsiIiINX10bGtcfgtrY86B0RW30onH9Ifjq2uhAh7h1kA7zKTjx2o90oEMswXwKTrz2Ix3oAABn17Xh6W1f4nMA3wFw7JvPe3q0ecfnxwBcDKACwNPbvsRZFmdlouQTwJ6kAx0kOoQ9KfVf//VfSEtLQ3FxMe677z488cQTePvttyMiIwXV60fT60eANj+g6l0IQJu2nOo1/xYNOtBBmkMswHzqaSHEXT/SgQ6xBvOpp4UQd/1IBzp08NS242j1qfgRgHoAPp3L+b75/mQAbT4Vy7YdN+URikTIJyD6/UAHOtAhOGFNSn399dcoKyvDggULMGTIEHz/+9/HpZdeig8++MC0iCTaK+q1y9b0DkoHKqA2eNFeUU8HOsSdg3SYTyGIs36kAx1iCeZTCOKsH+lABwAYd7IFlxz3YAO0W/b0Tkh14PtmuQ0ALjnuwbiqFsMuvZEo+QSwJ+lAB6kOYU1KpaSkIDU1FcXFxWhvb8eBAwfw8ccfY9SoUaZFJNFaXhvV5elAB4kO0mE+2bM8Hegg0UE6zCd7lqcDHSQ53LCnDu0K8CQM3JryDQ5oy7crwA276wy79Eai5BPAnqQDHaQ6hJWRbrcbDz74IF5++WWMGzcOU6ZMwfe+9z1ce+21pkWk4Ktq6XzSvFH81a3wmfhtBh3oIM0hFmA+6SMe+pEOdIg1mE/6iId+pAMdOri40oNPVO0te0ZvbvEDKAXwiQpcdNxjcC29kwj5BES/H+hABzr0TNhv39u/fz8uv/xy/PSnP0VFRQUeeughXHzxxZg+fbqu5RVFQVpSatiiAJCalNLt73BpUBSoIRw89ZEJfFcDkJoXuA060CEWHUJhdt9sVBRDy52K2XwCjNfBbA2A0GNhdS/QgQ6x6BCKSOybkcgo5pM+Yr0f6UCHDkbWtmFDRAyAvQCKatqC/jtjPZ8AnuPRgQ7x6qA3n8KalPrggw+wfv16lJSUICUlBWPHjsWJEyewYsUK3aHVNzUbG+auCmezAbwy+ylDy01dNxUnG08iJ60P3ujBobi4GIvfXGxGDwBwW+EcFBUV0YEOceGgF6P75syNM01tF4hMPgHmM8poDYDQY2F1L9CBDrHooBcz+6bZjGI+6SfW+5EOdAAA+P1IfmICGkxvXaMeQLJfxRtz/gA4ut/oEi/5BPAcjw50iDcHvfkU1qTUJ598gsGDByMl5dtZ7HPPPRfPPPOM7nXUeOowbe28cDbbSWpSCl6Z/RSue/kOeNrDv0Ssurm28++eHDx7agy5ncry0nV4rnkrHegQFw6hMLtvNnrqDG23K5HIJ8B4RpmtARB6LKzuBTrQIRYdQhGJfdNsRjGf9BPr/UgHOnRwyKEg0x/uk4ODkwWgzaFg2rpbA34W6/kE8ByPDnSIVwe9+RTWpFS/fv1w+PBhtLW1ITk5GQBw4MABDBgwQPc6VFVFc7u5y8Q87S2G1qGqakgHX1ZkbiPyZiLoNuhAh1h00IvZfdMMkcinDhczdTBag45t9+ZgdS/QgQ6x6KCXSOybRmE+6SfW+5EOdOhgb59knPOVuWe1dHAOgD19k3s9jjOKlHwCeI5HBzrEq0MownrQ+aRJk5CUlIQHHngABw8exLZt2/DMM8/gxhtvDGc1onHmpsCR4za1DkeOG85c489toAMdpDnEAswnfcRDP9KBDrEG80kf8dCPdKBDBx/kpWKMAhTA3Nv3CgGMVoAPzzT2vKZQJEI+AdHvBzrQgQ69rCOcL2dmZmLNmjWoqqrCrFmzsGTJEixYsACzZ882JSENd36fqC5PBzpIdJAO88me5elAB4kO0mE+2bM8HeggyeGFUdlIUoFFMPf2vUUAklRtfVaQKPkEsCfpQAepDmG/fW/YsGF47rnnTG9YMknDs9Dy72qojV4gnCtiFUDJcCFpeBYd6BB3DrEA86kX4qwf6UCHWIP51Atx1o90oAMA7MxNwT/OTMWs4x78BsAxAL4wlncCGABgJoB/nJmKnRZeUZoI+QSwJ+lAB6kORq8mjWsUlwPp0wcByQ5A722WCoBkbTnFZb6sdKCDNAciAwm9QAc6SHMgMpDQC3SggySHhZPORLJTwZvQHlbu1Lmc85vv/xVAslPBwklnmvIgGtHuBzrQgQ7B4ZFgDzizk5ExawiUDH0XkykZLmTMGgJndjId6BC3DkQGEnqBDnSQ5kBkIKEX6EAHKQ4Hs5Nx26QzMQLAB9CufAJ6PgHr+HzAN98fDuC2SWfiILMyYiR6T9KBDhIdwr59L5FwZicjc87ZaK+oR2t5LfzVgW/QcOS44c7vg6ThWZb8tpcOdJDmQGQgoRfoQAdpDkQGEnqBDnSQ4rBhRBYUqHh625fY5VOxAcCTAEqDfHcctGdIzYR2hdS8SWdiw4jEuMXZThK9J+lAB2kOnJQKgeJyIHlUNpJHZcNX1QJXA3Bb4RwsL10HbyZseWMQHeggzYHIQEIv0IEO0hyIDCT0Ah3oIMVh/YjTsKNfKpZtO46fHPfgBgX4RAX2AqiHdqveSABjFO2h5u/npeKOy3mFlJUkek/SgQ6SHPhryjBw5qYgdWQfFBUVIXVkn6gcXNOBDtIciAwk9AId6CDNgchAQi/QgQ7RdjiYnYwriwZj4nVD8NyYbDhz3ChyKJgPoMihwJnjxnNjsjHxuiG46prBnJCykf+/vXuPj6K+9z/+nuzmTmKAJNRwrQIRgZAIorValFoRFKRBRTFarYKKQi9HPYrUS6HBA/bUc1RsARUVsSiEIAJqlcpPKtKKhACKgtwNQgKJEHLd3fn9sc0eQhKS3Wwmk83r+XjkYZmdme873wnfZj585zvt9WeSDGSwSwZmSgEAAACABbYkRWlL0g8kSTHh0Vo54S8avfhulVWXt3IyAGgdzJQCAAAAgNYQxu0YgPaNURAAAAAAAACWM0zTNK1oyOVyacuWLRo5aqTKzboruTeFYRjqFJ2gY+UlCiS2We6WTEmGZEQ7yEAGMtgkQ7QRqTWr12jQoEFyOlvnqeLmjlHN7QOp+deCDGQgQ8tkaO0xivGJDGQgQ0Pa+vgkhcbvsmQgAxnqaur4ZNnI5fF4JElrVq+xqkkAbUzNONGabTNGAWhIa41RjE8AGsP4BMCuGhufLJsp5fF45HK5FBYWJsMwrGgSQBthmqY8Ho+cTqfCWmltBcYoAA1p7TGK8QlAQxifANhVU8cny4pSAAAAAAAAQA0WOgcAAAAAAIDlKEoBAAAAAADAchSlAAAAAAAAYDmKUgAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALNemilI5OTlKTU3VW2+9ZWm7qamptb4uvvhiTZ8+XSdPnrQ0hyR9//33euqppzR8+HANGjRII0eO1MKFC+XxeFq87eHDh/v64LzzzlNGRoZuuukmffzxxy3edn0ZTv/auHFjq+e4+eabLctQVlamZ555RldffbXS0tJ00UUXaerUqdq5c6cl7Q8fPlw5OTl1tufk5Gj48OGWZLCb9j5Gtffx6fQcrTVGMT4xPtWH8YnxifHp/7TmGMX4VBfjU+uNT5I9xig7jE9nysHvUC07Rjlb5KwtZNWqVerRo4dWrFihG264wdK2n332WWVkZMjj8ejQoUN67LHHNHv2bD355JOWZSguLtb48eOVnJysP/zhD+rWrZu2bt2qGTNm6MCBA/rd737X4hmmTZumUaNGyePx6Pvvv1dubq7uvvtuLViwQJdcckmLt39qhtOdddZZlrR/phzh4eGWtH3y5ElNmDBBZWVlevjhh3XeeeepuLhYr7/+um666Sbl5uaqe/fulmTB/2nPYxTjU90cp7NyjGJ8wukYnxifTs1xuvYyPkmMUXbE+NS645NkjzHKDuNTQzn4HapltZmi1NGjR7VhwwZlZ2fr4Ycf1oEDByy9IGeddZaSkpIkSV26dNHdd9+tJ5980tKi1B//+EdFREToxRdfVGRkpCSpe/fuioqK0uTJk5WVlaUf/vCHLZohLi6uVj889NBDKiws1KxZs7Ry5coWbbu+DK2pNXM8//zzOnr0qFavXq34+HhJUteuXTVr1iwdOnRICxcutOz/xODV3scoxqf6c7QWxiecivGJ8am+HK2ltTMwRtkL41Prj0+SPcao1h4b7JCjvY5PbebxvXfffVdxcXEaM2aMkpOTtWLFilbNEx0dbWl7VVVVWrVqlW655RbfgFXjiiuu0MKFC9W1a1dLM9UYP368vv76a+3bt69V2m9vPB6Pli9frjvuuMM3WJ1q9uzZevDBB1shWfvWnscoxifUYHyyJ8Ynxid4MUbZD+OTPccniTHKau15fGozRalVq1bp8ssvV1hYmIYPH67c3FyZptkqWY4dO6bXXntNY8aMsazN/fv3q6ysTAMHDqzzmWEYuvjiixUREWFZnlOde+65kqRdu3a1Svvtzf79+3Xs2DENGTKk3s+Tk5MVFRVlcSq05zGK8Qk1GJ/sifGJ8QlejFH2w/hkz/FJYoyyWnsen9rE43uHDh3S559/rjvuuEOSdNVVV+mNN97Qpk2bGrxowTZx4kQ5HA6Zpqny8nIlJCToiSeesKRtSTp+/Lgk73RCu6nJZNWigI8//rhmzJhRa1tKSopWrVplSftnyvGPf/xDMTExLdpucXGxpNrPV3/yySe67777fH+2qj/q6wOXy2WLqbdWau9jFONTbXYYoxifGJ9qMD4xPp2qPY9Pkn3GKMYnL8Yn+45PEvd4p+J3qJYdo9pEUWrVqlWKjIzUpZdeKkkaOnSozjrrLC1fvtyyAWvmzJkaNGiQTNNUcXGxFi1apJtvvlkrV65U586dW7z9hIQESd63M9hNaWmpJKlDhw6WtDd16lRdddVVtbY5ndb/KNeXw4opvzXTOWv+j0ySMjIylJubK0l6//339cYbb7R4Dqn+PrCyfbto72MU41NtdhijGJ8Yn2owPiVIYnyq0Z7HJ8k+YxTjkxfjU4Ike45PEvd4p+J3qJZtv80UpSoqKjR48GDfNrfbrXfffVe/+93vLJnG1qVLF/Xs2VOS1KtXL/Xv318XXXSR1qxZo6ysrBZvv0ePHoqLi9P27duVlpZW5/N7771Xt956q6VvcKnx1VdfSZL69OljSXudO3f2XYvW1Fo5evbsqYSEBG3evNn3sxAdHe3LYkWRtEZ9fWBl+3bR3scoxqfa7DBGMT4xPtVgfGJ8OlV7Hp8k+4xRjE9ejE/2HZ8k7vGsZpfxqaYtK8co268ptWfPHn3xxReaPn26cnNzfV9/+tOfVFpaqr/97W+tkissLEymacrtdlvSntPp1KhRo/T666+rqqqq1mdr167V2rVrlZycbEmW0y1btkz9+/cPyddT2pHT6dS4ceP0yiuv+P4F41SHDx9uhVTtF2MU4xP+D+OTvTA+MT6hNsYo+2B8svf4JDFGWa09j0+2nym1atUqJSQkaPz48bUWeuvbt6+ef/555ebmavTo0S2e4/vvv1dhYaEk73O1L730ktxut4YPH97ibdeYMmWKbrjhBt15552aMmWKfvCDH2jjxo2aM2eObrvtNvXu3bvFM5w4cUKFhYW+Ka5Lly7V6tWr9dJLL7V426dnOF1sbKwl6xHYwZQpU7Rp0ybddNNNuv/++9W/f38VFxfrrbfe0tKlS3Xttde2dsR2gzHKi/Gpbo7TtZcxivHJPhifvBif6uY4XXsZnyTGKLtgfPKyw/gk2WOMYnxqv+NTmyhKjR49ut43D9x88836wx/+oMOHD6tLly4tmmPKlCm+/x0dHa0BAwZo/vz5llaOk5KS9MYbb+jZZ5/VAw88oJKSEvXo0UNTp07VzTffbEmG7OxsZWdnyzAMderUSeeff74WLlxo2XPfp2Y43a9+9StNnjzZshytKTo6Wq+99ppeeeUVzZ07V/v27VNERITS0tL07LPP6sorr2ztiO0GY5QX41PdHKdrL2MU45N9MD55MT7VzXG69jI+SYxRdsH45GWH8UmyxxjF+NR+xyfDbK13bgIAAAAAAKDdsv2aUgAAAAAAAAg9FKUAAAAAAABgOYpSAAAAAAAAsBxFKQAAAAAAAFiOohQAAAAAAAAsR1EKAAAAAAAAlqMoBQAAAAAAAMtRlAIAAAAAAIDlKEqFoEmTJumRRx6pte2dd95Ramqqnn322Vrb586dq+uuu06SdPToUU2dOlWDBw/Wj3/8Y82ZM0cul6vO+UtKSnTJJZfo4MGDjWbJysrS559/fsZ9FixYoOHDhzd6rv/93//Vn//85zrbn332WaWmpvq+Bg4cqOuuu07r1q2rtV9eXp5uuukmZWRkaMSIEXrrrbdqfZ6bm6sRI0boggsu0H333afCwsJGMwHwT6Dj06mefPJJ3XrrrbW2Nfb3uz5XXHGFDh8+XGd7U8fCUzV3fKqxb98+paWl1dnO+ARYo6V+h/r666+VlZXlG6PeeeedRrM0NEYdP35cjz76qC655BJdfPHFevjhh3X8+PEznqulf4eqsWXLFvXr169JvyMC8E9LjE+njwE1Xz/96U/PmKWh8amGaZr65S9/qZycnEa/r5Yen/75z3/quuuu06BBg3TjjTdqx44djWaCtShKhaAhQ4Zo69attbZt3LhRycnJ2rhxY63teXl5Gjp0qCTpgQceUGlpqZYsWaL/+Z//0apVq7RgwYJa+3///fe65557dPTo0UZzlJeXa+fOnfXeYNU4cOCAnnvuuSZ9Xxs2bNCPfvSjej/LyMjQ+vXrtX79eq1atUrXXnutpkyZ4vulqLCwUBMnTtTQoUO1fPlyTZ06VTNmzNBHH30kSfr44481bdo03XrrrXrrrbcUExOjiRMnyuPxNCkbgKYJdHyq8fnnn+uNN96ota2xv9/12bdvn6KiotSlS5c6nzVlLDxdc8anGocOHdLdd9+tysrKWtsZnwDrtMTvUFVVVbrnnnt0/vnna8WKFZo4caIefvjhOu2c6kxj1OOPP64dO3Zo3rx5evHFF/XNN99o+vTpZ/y+WvJ3qBrV1dWaPn06YxPQQlpifPrlL3/p+/u/fv16rV69WgkJCbrtttsazHGm8UmSPB6PZs6cqX/84x9N+r5acnw6cOCAJk6cqJ/97GdasWKFUlNTNXnyZFVVVTUpG6xBUSoEDR48WN98841Onjzp27Zx40bdeeedysvLU0VFhW/7li1bNHToUFVVValz5856/PHH1bt3bw0ZMkQjRozQpk2bfPt+9tlnyszMVFlZWZNyfPbZZ0pPT5fT6Wxwn8cff1z9+vVr9FwnT57Unj17NGDAgHo/Dw8PV1JSkpKSktSjRw9NnDhRKSkpWrt2rSTpgw8+UGJion7729+qV69euuaaazR27FitXLlSkrRo0SKNHj1aWVlZOvfcczVjxgwdOnSoyYMpgKYJZHyqUVVVpccee0zp6em1ztnY3+/6NPQLUFPGwtM1d3yq+R4yMzMVERFR53jGJ8A6LfE71K5du/Ttt9/qV7/6lXr06KHrr79effv21T//+c8GczQ0RpWVlem9997TY489pgEDBqh///6aNm2aPvjggzoF7Rot/TtUjQULFqhDhw4Nfk8AmqclxqfY2Fjf3/+kpCS98sor6t279xmLUmcqIh0+fFi/+MUvtHbtWsXHxzf6PVlxj5eWlqb7779fvXr10rRp0xQWFqbdu3c3mg3WoSgVggYOHKjw8HBt375dkvTdd9+poKBAN9xwg+Li4nyP0+3Zs0fff/+9hgwZooiICD399NPq2bOnJGnnzp1au3ZtrRvC9evXa9y4cXWmhzbkTAOW5H0cpby8XNdff32j5/rss8+UkZEhh8PRpLYlKSYmxve/L7vsMs2aNavOPqWlpZK8VfRTZ3RFRUWpR48eysvLa3J7ABoXyPhUY968eUpNTdWPf/zjWuds7O93fRoan5oyFp6uueOTJH300Uf61a9+pUcffbTOvoxPgHVa4neos846S5L01ltvyePxaPPmzdq9e7fOP//8BnM0NEaFhYXpz3/+c51/0HO73bVuVE/V0r9DSd7+eP311/Xwww83uQ0A/mmpe7wae/bsUU5Ojv7zP/9ThmE0mONM93jbt2/X2WefrWXLlikuLq7R76mlx6d//vOfuuqqq3zbo6Oj9cEHH+i8885rcntoeRSlQlBERIQGDRqk/Px8SdKnn36qAQMGKDY2VhdeeKFvemdeXp769Omjjh071jo+KytL1157reLi4nTLLbf4tv/617/W5MmTmzxofPrpp7r44ovr/ezYsWN6+umn9fvf//6Mg16NxgpcpzJNUx988IH27t2rn/3sZ5Kkbt261ZpdcfToUa1atcp3zs6dO+vIkSO+zz0ejw4fPqzi4uImtQmgaQIdn7755hu98cYbddZSkBr/+3060zT1r3/964yFJqnhsfB0zR2fJGnmzJm66aab6j2G8QmwTkv8DtW1a1f99re/1dNPP60BAwbopptu0l133RXQGBUVFaWf/OQntWZVvvrqq0pNTVWnTp3qPV9L/w5lmqYee+wxTZkyRZ07d25SOwD811L3eDVefPFFXXzxxWdceqWx36GGDx+u2bNnNzgena6lx6cDBw4oKipKU6dO1SWXXKLbbrtNu3btalJ7sA5FqRA1ZMgQ34C1ceNGXXTRRZKkoUOH1hqw6htQpk+frldffVXV1dX67W9/G1D7JSUlOnz4sFJTU+v9PDs7Wz//+c/Vp0+fJp2vsQGrpsqekZGhAQMG6L777tO4ceN09tln19m3oqJCU6ZMUWJiosaPHy9JGjVqlN544w1t3rxZ1dXV+vOf/6yjR4+qurq6SfkANJ2/49OpNzyJiYlnPHd9f79Pt2PHDp199tm+2QsNaepYGMzxqT6MT4C1gv07VHV1tXbv3q3x48frrbfe0iOPPKL58+fXWQOmRlPHKMn7aMqaNWv00EMPNbhPS/8OtXTpUlVXV+vGG29sNC+A5mmpe7zS0lKtWrWqzotkTufP+NQULT0+lZWV6emnn9aFF16o+fPn6+yzz9btt9/e4MxStA6KUiHq1IXwNm7c6BuYhg4dqm3btqmqqkp5eXm68MIL6xx73nnn6aKLLlJ2drb+/ve/B/QGlZo265sF9fHHHysvL0/33Xdfk8517NgxHT169IwFrAEDBig3N1e5ublasWKFnn76ab399tt1FlE/efKk7r77bu3du1d/+ctfFB0dLUm68cYbdc011+iWW27RoEGDtHPnTv3kJz9hbQSgBfg7Pi1ZskRut7vBIlONhv5+n66p/yrXlLEwmONTQxifAGsF+3eo3Nxcbdu2TdOnT1f//v11++23a/To0Zo/f3697Td1jHr99dc1c+ZMPfLII7r00kvr3aelf4cqLCzUn/70pybPfAfQPC11j/fxxx8rKipKl1122Rnb92dmU2OsuMdzOBwaPny4br31VvXv318zZsyQx+Opta4nWl/DK1CjTcvIyNCRI0e0detWHTlyRBdccIEkqU+fPoqLi9O//vUv7dq1yzeQlZaW6v/9v/+nq6++WmFh3lpl7969JUnFxcXq1q2bX+2facBavXq1vvvuO9/nLpdL1dXVysjI0Pz582utISN5p6bW/CtAQ6KionzPStdkLygo0EsvvaT777/f9z3edddd2r9/v1555RX16tXLt7/D4dDjjz+uhx56SJWVlUpISND1119fZ+0aAM3n7/i0atUqbdu2zbdfdXW13G63MjIytGrVKqWkpJzx7/fpNmzYoNtvv73ez/wdC4M1Pp0J4xNgrWD/DrV9+3b17du3VtGmX79+vvVfTnemMarGiy++qNmzZ+uhhx7SL37xiwb3a+nfodavX6/i4mLfPxqYpilJuvbaa3XPPffonnvuOWPbAPzTUvd4H3/8sa644grfPg1pyvjUVFbc4yUlJemHP/yh788RERHq2rWrDh06FJTvAcFBUSpExcTEqF+/flqyZIkGDhzoqxYbhqELL7xQOTk56tWrl+953/Lycv3mN7/R2WefrYyMDEneheocDketv8hNtWHDBt155531fvbAAw/U+iXl/fff12uvvabXXnut3leLfvrppwFV5E3T9L2W2OPx6P7779fBgwf12muv6dxzz62178KFC1VVVaVJkyYpOjpaR44c0Zdffqns7Gy/2wVwZv6OT08//XStN8q89tpr2rJli55++mklJyc3+vf7VNXV1crPz9fgwYPr/dzfsTAY41NjGJ8AawX7d6jk5OQ6b/Dcs2dPvf/g19gYJUnLly/X7Nmz9cgjjzR6c9jSv0P97Gc/890US943b916662aN2+e+vbt63e7AM6spe7x8vPzGx1PmjI++cOKe7z09HR99dVXvj9XVVXpwIEDfk+4QMvi8b0QduGFF2rVqlV1nikeOnSoPvzww1rTOpOSknTVVVdpxowZ+uKLL/TZZ5/p0UcfVVZWlt+PiHz33Xeqrq5W9+7d6/28c+fO6tmzp++rc+fOcjqd6tmzp6Kiours35RpotXV1SosLFRhYaGOHDmijz/+WK+++qpGjhwpybvewcaNGzVz5kzFx8f79i0pKZHkXSRv/vz5+vTTT7Vz505NnTpVw4YN4xcqoIX4Mz516dKl1phx1lln+f7lzOl0Nvr3+1RbtmxR37596x1rJP/HwmCMT41hfAKsF8zfoUaPHq0DBw5ozpw52r9/v3Jzc/Xmm2/Wu3ZLY2NUSUmJfv/73+vnP/+5rrnmGt/YUlhYKLfbXWf/lv4dqkOHDrXG55SUFElSSkqKEhISztgugMAE+x7P5XJpz549vhlUDWlsfPKXFfd4v/jFL/Tee+9p8eLF2rt3r37/+98rMjJSl19+eVC+BwQHM6VC2ODBg/XSSy/VmRY5dOhQlZeX1xnIsrOzlZ2drTvuuEOSNHbsWP3Hf/yH3+1u2LChwbfu+evbb7+V5H1zzZls3rzZt55CWFiYkpKSdN1112nq1KmSpPfee08ej0d33313reOGDh2q1157TVdeeaW++eYbPfDAA6qsrNSVV15Z76vZAQSHv+PTmTT29/tUZ3oraI2mjoXBGp8aw/gEWC+Yv0N1795dL730kmbPnq3FixcrJSVFf/jDH+pdu6WxMeof//iHysrKtHz5ci1fvrzWZx9++GGtf/236ncoANYK9j1eSUmJXC6X4uPjz9huU36HaiqrxqdBgwbpmWee0dNPP61Zs2ZpwIABWrBggWJiYoLyfSA4DLPm4W8AAAAAAADAIjy+BwAAAAAAAMtRlAIAAAAAAIDlKEoBAAAAAADAchSlAAAAAAAAYDmKUgAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALEdRCgAAAAAAAJajKAUAAAAAAADLUZQCAAAAAACA5ShKAQAAAAAAwHIUpQAAAAAAAGA5ilIAAAAAAACwHEUpAAAAAAAAWI6iFAAAAAAAACxHUQoAAAAAAACWc1rVkMfjkcvlUlhYmAzDsKpZAG2AaZryeDxyOp0KC6NWDgAAAADtgWVFKZfLpa1bt1rVHIA2aODAgYqIiGjtGAAAAAAAC1hWlKqZ/TBy1EiVm5UBncMwDHWKTtCx8hKZpun38Wa5WzIlGZIR7SADGchgkwzRRqTWrF7DLCkAAAAAaEcsK0rVPLJXblbKcWNKQOeICY/Wsqz5Gr1oosqqy/0+/vjCXTJPumTEOhV/Y28ykIEMNslQ/maBJPFoLwAAAAC0I0xLAAAAAAAAgOUoSgEAAAAAAMByFKUAAAAAAABguTZTlHIXVqh8xzHl5OSofMcxuQsrLM+Q1q2fxmaMUGJiosZmjFBat35kIAMZbJABAAAAAND2WLbQeSBMl0fVO4+rMr9YniLvG/uy3832fR6WGKnItI4K7xMvw9ky9bWo8EiNGzxKk4ZlaVD3833b5942S5K05cAXmrdukZZtWq2K6sDeKkgGMpABAAAAANDeGGYg728PgNvtVl5eni4fObxJb99zl1Tp5Nv7ZZ5wNbqvEedU7JgeciREnHG/Wm8Zu73xt4ydm9xLy+9boO6dUuQxPXKEOerm9LgVZoTpwLECjX3uTu0u3EcGMpDBzwzuNwv00Zq1Sk9Pl8NR93wAAAAAgNAT8PSiqqoqXXvttdq4cWMw80jyFqRKl+6VWdp4QUqSzFKXSpfulbukKmgZzk3upQ8e+KtSErrIMIx6b7wlyRHmkGEYSknoog8fXKJzknqSgQxkaMEMAAAAAIDQEFBRqrKyUr/97W+1c+fOYOeR6fLo5Nv7pSqP1NQ5XKakKu9xpsvT7AxR4ZFaft8CxUXGyulo2hOOTodTcZGxyr3/RUWFR5KBDGRogQwAAAAAgNDhd1Fq165duvHGG7V///6WyKPqnce9j+z5+1ChKZknXKreebzZGcYNHqXunVKafONdw+lwqkfnrsq8YCQZyECGFsgAAAAAAAgdfhel/vnPf+qiiy7SkiVLWiKPKvOLW/V4SZo0LEseM7AZV26PW5OGZZGBDGRogQwAAAAAgNDhd1FqwoQJmjZtmqKjo4Mexl1Y4XvLXqA8RZVyF1YEfHxat34a1P38BtfKaYwjzKH0Hv2V1q0fGchAhiBmAAAAAACEFv+ewwkCwzAUE15/Qav8eHlQ2nCekKJT6rZxwjBkNpJhQEpqUDL0T+mrXYf3koEMZGhChlLDCMr5AQAAAABth2Gapr+rN/mkpqbq1Vdf1UUXXdTovm63W3l5eRo3bpyWLVtW7z45OTnKzs4ONI7PtGnTlJmZWWf7qFGjdOTIESUnJ2v16tX1HpuYmKiePZv/prB9+/apqKiIDGQgQxMy1IwL6enpcjgCm40FAAAAAGhbLJ8pday8RKMXTaz3s/Idx4LSxtzNi/Vy2Zo624vKin3/bSjD2IwRmnvbrGZneGrdC1qx+X0ykIEMTchQWl7S7HMDAAAAANoWy4tSpmmqrLr+x/Tc8cF5hMcVp3rbqJkUdqYM2wq+CkqGbd9+RQYykMHPDAAAAACA9sPvhc5bkiMpSmGJkc06R1hipBxJUQEfn3/wS2058IXcHndAx7s9buXt366t3+4gAxnIEMQMAAAAAIDQYquilCRFpnVs1eMlad66RQozAusaR5hD89YtIgMZyNACGQAAAAAAoaNZRamvvvqqSYuc+yO8T7yMOKfk75N8hmTEORXeJ77ZGZZtWq0Dxwrkcrv8Os7ldmn/0W+V83nd9azIQAYyND8DAAAAACB02G6mlOEMU+yYHlJEWNMLU4akCO9xhrP531JFdaV+/vxdOlF5ssk34C63SycqT2rsc3eqorqSDGQgQwtkAAAAAACEDtsVpSTJkRChDtf3ktGhaeuwGx2c6nB9LzkSIoKW4Zsje/XTOeNVUHJYkhpcS6dme0HJYf10znjtLtxHBjKQoQUzAAAAAABCg+Vv32sqR0KE4iaco+qdx1WZXyxPUd1ZFmGJkYpM6+h95C8IM6ROt7twn4bOvEaZF4zUpGFZSu/Rv84+Ww/u0Lx1i5Tz+ZoWmQlCBjKQAQAAAAAQigzTonexu91u5eXl6fKRw+W4McX/4wsr5DwhTc6YoLmbF8sVJ7/fsnd84S6ZJ10yYp2Kv7233xnSuvVT/5S+enjYvXpq3QvaXvC18g9+SQYykKGZGdxvFuijNWuVnp4uh8PhdwYAAAAAQNtj25lSp3MkRSk6JVqZmZl6uWyNyqrLLc+Qf/BL7Tq8V3f1v0ErNr9PBjKQwSYZAAAAAABtjy3XlAIAAAAAAEBooygFAAAAAAAAy1GUAgAAAAAAgOUsX+h82OXDVGYG9jYuwzCUGNNRRWXFCiS2WeaSTEmGZMQEtpwWGchAhuBniDEite6jdSx0DgAAAADtiPULnZuSedIV6KE6UnqEDGQgQ6hliI0M/FgAAAAAQJtkfVHKkIzY9jsjhAxkIEN9JwioWQAAAABAG2Z5UcqIdij+xt4BHRsTHq2VWfM1etHEgF47f3zhLpknXTJinIq/nQxkIINdMrjfLAioXQAAAABA28VC5wAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALNdmilLuwgqV7zimnJwcle84JndhRbvMkNatn8ZmjFBiYqLGZoxQWrd+lmegH8hgtwwAAAAAgLbH+rfv+cF0eVS987gq84vlKaqUJGW/m+37PCwxUpFpHRXeJ16Gs2Xqa3bIEBUeqXGDR2nSsCwN6n6+b/vc22ZJkrYc+ELz1i3Ssk2rVVFd2SIZ6Acy2C0DAAAAAKBtM8yA3t/uP7fbrby8PF0+crgcN6Y0vn9JlU6+vV/mCVej+xpxTsWO6SFHQsQZ9/O9ZSy2aW8Zs0OGc5N7afl9C9S9U4o8pkeOMEfdnB63wowwHThWoLHP3andhfuCmoF+IENLZ3C/WaCP1qxVenq6HI665wMAAAAAhB5bPr7nLqlS6dK9MksbL4JIklnqUunSvXKXVIVUhnOTe+mDB/6qlIQuMgyj3pt/SXKEOWQYhlISuujDB5fonKSeQctAP5DBbhkAAAAAAKHBr6LU4cOHNXXqVA0dOlSXXXaZZs2apcrK4D6aY7o8Ovn2fqnKIzV1Dpcpqcp7nOnyhESGqPBILb9vgeIiY+V0NO0pS6fDqbjIWOXe/6KiwiObnYF+IIPdMgAAAAAAQkeTi1KmaWrq1KkqLy/X66+/rj/96U/6+9//rmeeeSaogap3Hvc+JubvQ4WmZJ5wqXrn8ZDIMG7wKHXvlNLkm/8aTodTPTp3VeYFI5udgX4gg90yAAAAAABCR5OLUrt371ZeXp5mzZqlPn36aMiQIZo6dareeeedoAaqzC9u1ePtkmHSsCx5zMBmGrk9bk0altXsDPQDGeyWAQAAAAAQOppclEpKStKCBQuUmJhYa3tpaWnQwrgLK3xvdguUp6hS7sKKNp0hrVs/Dep+foPr9TTGEeZQeo/+SuvWL+AM9AMZ7JYBAAAAABBamvwcTnx8vC677DLfnz0ejxYtWqSLL77YrwYNw1BMeHS9n5UfL/frXA1xnpCiU+q2ccIwZLaBDANSUoOSoX9KX+06vDegDPQDGazMUGoYQTk/AAAAAKDtMEzT9HfFIEnSf/3Xf+n111/X0qVL1bdv30b3d7vdysvL07hx47Rs2bJ698nJyVF2dnYgcWqZNm2aMjMz62wfNWqUjhw5ouTkZK1evdq2GRITE9WzZ/PfVrZv3z4VFRUFlIF+IIOVGWrGhfT0dDkcgc3GAgAAAAC0Lf6tWPxvc+bM0SuvvKI//elPTSpInepYeYlGL5pY72flO44FEqeOuZsX6+WyNXW2F5UV+/5r5wxjM0Zo7m2zmp3hqXUvaMXm9wPKQD+QwcoMpeUlzT43AAAAAKBt8bsoNWPGDL3xxhuaM2eORowY4XeDpmmqrLr+R8Pc8cF5hMcVp3rbqJkUZvcM2wq+CkqGbd9+RT+oef1ABmszAAAAAADajyYvdC5Jzz33nP7617/qv//7v3XNNdcEPYwjKUphiZHNOkdYYqQcSVFtOkP+wS+15cAXcnvcAR3v9riVt3+7tn67I+AM9AMZ7JYBAAAAABBamlyU+uabbzR37lxNnDhRgwcPVmFhoe8rmCLTOrbq8XbJMG/dIoUZftUMfRxhDs1bt6jZGegHMtgtAwAAAAAgdDT5DvPDDz+U2+3WCy+8oEsvvbTWVzCF94mXEeeU/H16zJCMOKfC+8SHRIZlm1brwLECudwuv45zuV3af/Rb5Xxedx0nf9EPZLBbBgAAAABA6GhyUWrSpEn66quv6v0KJsMZptgxPaSIsKYXQwxJEd7jDGdgMznslqGiulI/f/4unag82eQigMvt0onKkxr73J2qqK5sdgb6gQx2ywAAAAAACB3Nrxq0AEdChDpc30tGh6atw250cKrD9b3kSIgIqQzfHNmrn84Zr4KSw5LU4Ho+NdsLSg7rp3PGa3fhvqBloB/IYLcMAAAAAIDQ4Pfb96ziSIhQ3IRzVL3zuCrzi+UpqjvLIiwxUpFpHb2PmQVhVo4dM+wu3KehM69R5gUjNWlYltJ79K+zz9aDOzRv3SLlfL6mRWaj0A9ksFsGAAAAAEDbZ9uilOR9fCyiX4Ii+iXIXVgh5wlpcsYEzd28WK44NevNbm0pQ0V1pRZvzNXijblK69ZP/VP66uFh9+qpdS9oe8HXyj/4ZYtnoB/IYLcMAAAAAIC2zZaP79XHkRSl6NSOyszMVHRqR0uKIHbMkH/wS63Y/L6Kioq0YvP7rXLzTz+QwW4ZAAAAAABtT5spSgEAAAAAACB0UJQCAAAAAACA5ShKAQAAAAAAwHKGaZqmFQ253W7l5eVp2OXDVGYG9jYuwzCUGNNRRWXFCiS2WeaSTEmGZMQEtsY7GchAhuBniDEite6jdUpPT5fD4QgoAwAAAACgbbH+7XumZJ50BXqojpQeIQMZyBBqGWIjAz8WAAAAANAmWV+UMiQjtv3OCCEDGchQ3wkCahYAAAAA0IZZXpQyoh2Kv7F3QMfGhEdrZdZ8jV40UWXV5X4ff3zhLpknXTJinIq/nQxkIINdMrjfLAioXQAAAABA28VC5wAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALNdmilLuwgqV7zimnJwcle84JndhheUZ0rr109iMEUpMTNTYjBFK69bP8gz0gxf94EU/AAAAAADaKuvfvucH0+VR9c7jqswvlqeoUpKU/W627/OwxEhFpnVUeJ94Gc6Wqa9FhUdq3OBRmjQsS4O6n+/bPve2WZKkLQe+0Lx1i7Rs02pVVFe2SAb6wYt+8KIfAAAAAAChwDADen+7/9xut/Ly8nT5yOFy3JjS+P4lVTr59n6ZJ1yN7mvEORU7poccCRFn3M/3lrHYpr1l7NzkXlp+3wJ175Qij+mRI8xRN6fHrTAjTAeOFWjsc3dqd+G+oGagH/59fvrBe/4Q7Qf3mwX6aM1apaeny+Goez4AAAAAQOix5eN77pIqlS7dK7O08RtvSTJLXSpdulfukqqgZTg3uZc+eOCvSknoIsMw6r3xliRHmEOGYSgloYs+fHCJzknqGbQM9IMX/eBFPwAAAAAAQonfRal9+/bpzjvvVEZGhi6//HItWLAgqIFMl0cn394vVXmkps7hMiVVeY8zXZ5mZ4gKj9Ty+xYoLjJWTkfTnnB0OpyKi4xV7v0vKio8stkZ6Acv+sGLfgAAAAAAhBq/ilIej0eTJk1Sx44dtXz5cj355JN64YUXtHLlyqAFqt553Ptokr8PFZqSecKl6p3Hm51h3OBR6t4ppck33jWcDqd6dO6qzAtGNjsD/eBFP3jRDwAAAACAUONXUaqoqEj9+vXTE088oV69emnYsGH60Y9+pE2bNgUtUGV+caseL0mThmXJYwY2s8TtcWvSsKxmZ6AfvOgHL/oBAAAAABBq/CpKJScn65lnnlGHDh1kmqY2bdqkf/3rXxo6dGhQwrgLK3xvEwuUp6hS7sKKgI9P69ZPg7qf3+BaOY1xhDmU3qO/0rr1CzgD/eBFP3jRDwAAAACAUOTfczinGD58uAoKCnTFFVdoxIgRTT7OMAzFhEfX+1n58fJA49TiPCFFp9Rt44RhyGwkw4CU1KBk6J/SV7sO7w0oA/3gRT94tYd+KDWMoJwfAAAAANB2GKZp+rtKjSRp69atKioq0hNPPKGf/exnmj59+hn3d7vdysvL07hx47Rs2bJ698nJyVF2dnYgcWqZNm2aMjMz62wfNWqUjhw5ouTkZK1evbreYxMTE9WzZ/PfFLZv3z4VFRUFlIF+8KIfvNpDP9SMC+np6XI4ApuNBQAAAABoWwKeKTVw4EBJUmVlpR544AE99NBDioiIaPS4Y+UlGr1oYr2fle84FmicWuZuXqyXy9bU2V5UVuz7b0MZxmaM0NzbZjU7w1PrXtCKze8HlIF+8KIfvNpDP5SWlzT73AAAAACAtsWvolRRUZHy8vJ05ZVX+rb17t1b1dXVKi0tVadOnRo9h2maKquu/3Ekd3xwHuFxxaneNmomhZ0pw7aCr4KSYdu3XwWcgX7woh+82lM/AAAAAADaD78WOj948KDuv/9+HT582Ldt27Zt6tSpU5MKUo1xJEUpLDGyWecIS4yUIykq4OPzD36pLQe+kNvjDuh4t8etvP3btfXbHQFnoB+86Acv+gEAAAAAEIr8KkoNHDhQ/fv317Rp07Rr1y6tW7dOc+bM0T333BO0QJFpHVv1eEmat26Rwgy/usbHEebQvHWLmp2BfvCiH7zoBwAAAABAqPHrDtPhcGju3LmKjo7W+PHj9eijj+rWW2/VbbfdFrRA4X3iZcQ5JX+fWDIkI86p8D7xzc6wbNNqHThWIJfb5ddxLrdL+49+q5zP667b4y/6wYt+8KIfAAAAAAChxu9pD126dNFzzz2nTZs2af369brnnntkBPF17oYzTLFjekgRYU2/ATckRXiPM5yBzeQ4VUV1pX7+/F06UXmyyTfgLrdLJypPauxzd6qiurLZGegHL/rBi34AAAAAAISa5t+ptgBHQoQ6XN9LRoemrcNudHCqw/W95Eho/O1/TfXNkb366ZzxKijxrp/V0Fo6NdsLSg7rp3PGa3fhvqBloB+86Acv+gEAAAAAEEr8evuelRwJEYqbcI6qdx5XZX6xPEV1Z1mEJUYqMq2j99GmIMwEOd3uwn0aOvMaZV4wUpOGZSm9R/86+2w9uEPz1i1SzudrWmQmCP3gRT940Q8AAAAAgFBh26KU5H1kKaJfgiL6JchdWCHnCWlyxgTN3bxYrjg1621iTVVRXanFG3O1eGOu0rr1U/+Uvnp42L16at0L2l7wtfIPftniGegHL/rBi34AAAAAAIQCWz6+Vx9HUpSiUzsqMzNT0akdLbnxPl3+wS+1YvP7Kioq0orN77fKjTf94EU/eNEPAAAAAIC2qs0UpQAAAAAAABA6KEoBAAAAAADAchSlAAAAAAAAYDnDNE3Tiobcbrfy8vI07PJhKjMDexuXYRhKjOmoorJiBRLbLHNJpiRDMmICW+OdDGQgQ/AzxBiRWvfROqWnp8vhcASUAQAAAADQtlj/9j1TMk+6Aj1UR0qPkIEMZAi1DLGRgR8LAAAAAGiTrC9KGZIR235nhJCBDGSo7wQBNQsAAAAAaMMsL0oZ0Q7F39g7oGNjwqO1Mmu+Ri+aqLLqcr+PP75wl8yTLhkxTsXfTgYykMEuGdxvFgTULgAAAACg7WKhcwAAAAAAAFiOohQAAAAAAAAsR1EKAAAAAAAAlmszRSl3YYXKdxxTTk6Oyncck7uwwvIMad36aWzGCCUmJmpsxgildetneQY79IMdMtjhWtghA9cCAAAAANBWWf/2PT+YLo+qdx5XZX6xPEWVkqTsd7N9n4clRioyraPC+8TLcLZMfS0qPFLjBo/SpGFZGtT9fN/2ubfNkiRtOfCF5q1bpGWbVquiurJFMtihH+yQwQ7Xwg4ZuBYAAAAAgFBgmAG9v91/brdbeXl5unzkcDluTGl8/5IqnXx7v8wTrkb3NeKcih3TQ46EiDPu53vLWGzT3jJ2bnIvLb9vgbp3SpHH9MgR5qib0+NWmBGmA8cKNPa5O7W7cF9QM9ihH+yQwQ7Xwg4ZQvVauN8s0Edr1io9PV0OR93zAQAAAABCjy0f33OXVKl06V6ZpY3feEuSWepS6dK9cpdUBS3Ducm99MEDf1VKQhcZhlHvjbckOcIcMgxDKQld9OGDS3ROUs+gZbBDP9ghgx2uhR0ycC0AAAAAAKEk4KLUpEmT9PDDDwcziyTvo0kn394vVXmkps7hMiVVeY8zXZ5mZ4gKj9Ty+xYoLjJWTkfTnnB0OpyKi4xV7v0vKio8stkZ7NAPdshgh2thhwxcCwAAAABAqAmoKLVq1SqtW7cu2FkkSdU7j3sfTfL3oUJTMk+4VL3zeLMzjBs8St07pTT5xruG0+FUj85dlXnByGZnsEM/2CGDHa6FHTJwLQAAAAAAocbvolRJSYlmz56tgQMHtkQeVeYXt+rxkjRpWJY8ZmAzS9wetyYNy2p2Bjv0gx0y2OFa2CED1wIAAAAAEGr8Lkr913/9l6677jr17t34gsj+chdW+N4mFihPUaXchRUBH5/WrZ8GdT+/wbVyGuMIcyi9R3+ldesXcAY79IMdMtjhWtghA9cCAAAAABCK/HoOZ8OGDfrss8+0cuVKPfHEEwE1aBiGYsKj6/2s/Hh5QOc8nfOEFJ1St40ThiGzkQwDUlKDkqF/Sl/tOrw3oAx26Ac7ZLDDtbBDhvZwLUoNIyjnBwAAAAC0HU0uSlVWVurxxx/XY489pqioqIAb7BSdoGVZ8+v9LCcnR9nvZgd87hqTMyYoMzOzzvZRi0fpSOkRJcZ01MoGMiQmJja7fUl6eNi9uqv/DQFlsEM/2CGDHa6FHTK0h2sxbvm4oJwfAAAAANB2NLko9dxzz2nAgAG67LLLmtXgsfISjV40sd7Pyncca9a5a8zdvFgvl62ps72orNj334YyjM0Yobm3zWp2hqfWvaAVm98PKIMd+sEOGexwLeyQoT1ci9LykmafGwAAAADQtjS5KLVq1SoVFRUpIyNDklRVVSVJeu+997R58+YmN2iapsqq638cyR0fnEd4XHGqtw3TNBvNsK3gq6Bk2PbtVwFnsEM/2CGDHa6FHTK0p2sBAAAAAGg/mlyUeu211+RyuXx/fvrppyVJDzzwQNDCOJKiFJYY2axFncMSI+VICvzxwvyDX2rLgS80oGtqQIs6uz1ubT24Q1u/3RFwBjv0gx0y2OFa2CED1wIAAAAAEIqa/Pa9rl27qmfPnr6v2NhYxcbGqmfPnkENFJnWsVWPl6R56xYpzPD7xYSSvG8Zm7duUbMz2KEf7JDBDtfCDhm4FgAAAACAUBPYHWYLCu8TLyPOKfn7xJIhGXFOhfeJb3aGZZtW68CxArncrsZ3PoXL7dL+o98q5/O66/b4yw79YIcMdrgWdsjAtQAAAAAAhJqAi1JPPfWUnnrqqWBmkSQZzjDFjukhRYQ1/QbckBThPc5wNr/OVlFdqZ8/f5dOVJ5s8g24y+3SicqTGvvcnaqoDvwxqxp26Ac7ZLDDtbBDBq4FAAAAACDU2G6mlCQ5EiLU4fpeMjo0bckro4NTHa7vJUdCRNAyfHNkr346Z7wKSg5L8q6JU5+a7QUlh/XTOeO1u3Bf0DLYoR/skMEO18IOGbgWAAAAAIBQ0uSFzq3mSIhQ3IRzVL3zuCrzi+td5DksMVKRaR29jzYFYSbI6XYX7tPQmdco84KRmjQsS+k9+tfZZ+vBHZq3bpFyPl/TIjNB7NAPdshgh2thhwxcCwAAAABAqLBtUUryPrIU0S9BEf0S5C6skPOENDljguZuXixXnJr1NrGmqqiu1OKNuVq8MVdp3fqpf0pfPTzsXj217gVtL/ha+Qe/bPEMdugHO2Sww7WwQwauBQAAAAAgFNjy8b36OJKiFJ3aUZmZmYpO7WjJjffp8g9+qRWb31dRUZFWbH6/VW687dAPdshgh2thhwxcCwAAAABAW9VmilIAAAAAAAAIHRSlAAAAAAAAYDmKUgAAAAAAALCcYZqmaUVDbrdbeXl5Gnb5MJWZgb2NyzAMJcZ0VFFZsQKJbZa5JFOSIRkxga3xTgYykCH4GWKMSK37aJ3S09PlcDgCygAAAAAAaFusf/ueKZknXYEeqiOlR8hABjKEWobYyMCPBQAAAAC0SdYXpQzJiG2/M0LIQAYy1HeCgJoFAAAAALRhlheljGiH4m/sHdCxMeHRWpk1X6MXTVRZdbnfxx9fuEvmSZeMGKfibycDGchglwzuNwsCahcAAAAA0Hax0DkAAAAAAAAsR1EKAAAAAAAAlqMoBQAAAAAAAMtZv9B5gNyFFSo/Xq6cnByV7zgmd7whR1IUGVohQ1q3fhqQkqrExESNzRihbQVfKf/gl5ZmoB+86AcAAAAAQFtl66KU6fKoeudxVeYXy1NUKUnKfjfb93lYYqQi0zoqvE+8DGfLTPoig1dUeKTGDR6lScOyNKj7+b7tc2+bJUnacuALzVu3SMs2rVZFdWWLZKAfvOgHAAAAAEAosG1Ryl1SpZNv75d5wtXgPp6iSpWv/U4V/ypS7JgeciREkKEFMpyb3EvL71ug7p1S5DE99e4zoGuqnrvlD/rPkfdp7HN3anfhvqBmoB+86AcAAAAAQKiw5ZpS7pIqlS7dK7O04RvvU5mlLpUu3St3SRUZgpzh3ORe+uCBvyoloYsMw5AjzFHvfo4whwzDUEpCF3344BKdk9QzaBnoBy/6AQAAAAAQSvwuSv3tb39Tampqra+pU6cGLZDp8ujk2/ulKo9kNvUgSVXe40xX/TM3yOC/qPBILb9vgeIiY+V0NG1SndPhVFxkrHLvf1FR4ZHNzkA/eNEPAAAAAIBQ43dRateuXbriiiu0fv1639fMmTODFqh653Hvo0lNvfGuYUrmCZeqdx4nQ5AyjBs8St07pTS5AFHD6XCqR+euyrxgZLMz0A9e9AMAAAAAINT4XZT65ptv1LdvXyUlJfm+4uPjgxaoMr+4VY8nw/+ZNCyrwTWDGuP2uDVpWFazM9APXvQDAAAAACDUBFSU6tWrVwtE8b7evuZtYoHyFFXKXVhBhmZmSOvWT4O6n9/gmkGNcYQ5lN6jv9K69Qs4A/3gRT8AAAAAAEKRX8/hmKapPXv2aP369frLX/4it9utq6++WlOnTlVERNPe8GUYhmLCo+v9rPx4uT9xGuQ8IUWn1G3jhGHIJEOTMgxISQ1Khv4pfbXr8N6AMtAPXu2hH0oNIyjnBwAAAAC0HX4VpQoKClReXq6IiAg988wzOnjwoGbOnKmKigpNnz69SefoFJ2gZVnz6/0sJydH2e9m+xOpXpMzJigzM7PO9lGLR+lI6RElxnTUSjKcMUNiYmKz25ekh4fdq7v63xBQBvrBqz30w7jl44JyfgAAAABA22GYpunX0sklJSU666yzZPx7ZsN7772nBx98UJs3b5bD0fCjPW63W3l5ebpi1E/VYcI59e5TvuOYSt7d50+ceiWM7KXo1I51th9esE2e0mqFdQhXl7sGkOEMGcZmjNDc22Y1O8O9rz6sFZvfDygD/eDVHvqhdPFu/X31h0pPTz/jOAIAAAAACB3+vUZLUkJCQq0/n3vuuaqsrNT333+vTp06NXq8aZoqq67/cSR3fHAe4XHFqd42aupvZGg8w7aCr4KSYdu3X9EPoh9852mkHwAAAAAA7YdfC51//PHHuuiii1Re/n83lV9++aUSEhKaVJBqjCMpSmGJkc06R1hipBxJUWRoZob8g19qy4Ev5Pa4Azre7XErb/92bf12R8AZ6Acv+gEAAAAAEIr8KkplZGQoMjJS06dP1+7du7Vu3TrNnj1bd911V9ACRabVfbzIyuPJ8H/mrVukMMPvFzRK8r5tbd66Rc3OQD940Q8AAAAAgFDj1x1mhw4d9OKLL+rYsWMaN26cHn30UY0fPz6oRanwPvEy4pySv08sGZIR51R4n3gyBCnDsk2rdeBYgVxul1/Hudwu7T/6rXI+X9PsDPSDF/0AAAAAAAg1fk976NOnj15++WVt3rxZ69ev1/333+9b9DwYDGeYYsf0kCLCmn4DbkiK8B5nOAObyUGGuiqqK/Xz5+/SicqTTS5EuNwunag8qbHP3amK6spmZ6AfvOgHAAAAAECoaf6dagtwJESow/W9ZHRo2jrsRgenOlzfS46ECDIEOcM3R/bqp3PGq6DksCQ1uKZQzfaCksP66Zzx2l3Y/LfF1aAfvOgHAAAAAEAo8fvte1ZxJEQobsI5qt55XJX5xfIU1Z1lEZYYqci0jt5Hm4IwE4QM9dtduE9DZ16jzAtGatKwLKX36F9nn60Hd2jeukXK+XxNi8yIoR+86AcAAAAAQKiwbVFK8j6yFNEvQRH9EuQurJDzhDQ5Y4Lmbl4sV5ya9TYxMvinorpSizfmavHGXKV166f+KX318LB79dS6F7S94GvlH/yyxTPQD170AwAAAAAgFNjy8b36OJKiFJ3aUZmZmYpO7WjJjTcZ6pd/8Eut2Py+ioqKtGLz+61SgKAfvOgHAAAAAEBb1WaKUgAAAAAAAAgdFKUAAAAAAABgOYpSAAAAAAAAsJxhmqZpRUNut1t5eXkadvkwlZmBvY3LMAwlxnRUUVmxAoltlrkkU5IhGTGBrfFOBjKQIfgZYoxIrftondLT0+VwOALKAAAAAABoW6x/+54pmSddgR6qI6VHyEAGMoRahtjIwI8FAAAAALRJ1helDMmIbb8zQshABjLUd4KAmgUAAAAAtGGWF6WMaIfib+wd0LEx4dFamTVfoxdNVFl1ud/HH1+4S+ZJl4wYp+JvJwMZyGCXDO43CwJqFwAAAADQdrHQOQAAAAAAACxHUQoAAAAAAACWoygFAAAAAAAAy1m/0HmA3IUVKj9erpycHJXvOCZ3vCFHUpSlGdK69dOAlFQlJiZqbMYIbSv4SvkHv7Q0gx36gQz2yWCHn0k7ZAAAAAAAtD22LkqZLo+qdx5XZX6xPEWVkqTsd7N9n4clRioyraPC+8TLcLbMpK+o8EiNGzxKk4ZlaVD3833b5942S5K05cAXmrdukZZtWq2K6soWyWCHfiCDfTLY4WfSDhkAAAAAAG2bbYtS7pIqnXx7v8wTrgb38RRVqnztd6r4V5Fix/SQIyEiqBnOTe6l5fctUPdOKfKYnnr3GdA1Vc/d8gf958j7NPa5O7W7cF9QM9ihH8hgnwx2+Jm0QwYAAAAAQNtnyzWl3CVVKl26V2Zpwzf/pzJLXSpdulfukqqgZTg3uZc+eOCvSknoIsMw5Ahz1LufI8whwzCUktBFHz64ROck9QxaBjv0Axnsk8EOP5N2yAAAAAAACA1+F6Wqqqr05JNP6sILL9Qll1yi//7v/5ZpmkELZLo8Ovn2fqnKIzX1tKakKu9xpqv+mRv+iAqP1PL7FiguMlZOR9MmkzkdTsVFxir3/hcVFR7Z7Ax26Acy2CeDHX4m7ZABAAAAABA6/C5KzZw5U5988olefPFF/fGPf9Sbb76pJUuWBC1Q9c7j3sej/K1zmZJ5wqXqncebnWHc4FHq3imlyTfeNZwOp3p07qrMC0Y2O4Md+oEM9slgh59JO2QAAAAAAIQOv4pSJSUlWrZsmWbMmKG0tDT96Ec/0i9/+Utt2bIlaIEq84tb9XhJmjQsq8G1chrj9rg1aVhWszPYoR/IYJ8MdviZtEMGAAAAAEDo8KsotWnTJnXo0EFDhw71bZs0aZJmzZoVlDDuwgrfG80C5SmqlLuwIuDj07r106Du5ze4Vk5jHGEOpffor7Ru/QLOYId+IIN9MtjhZ9IOGQAAAAAAocWv53AOHDigrl27Kjc3V3/+859VXV2tzMxM3XvvvQoLa1p9yzAMxYRH1/tZ+fFyf+I0yHlCik6p28YJw5DZSIYBKalBydA/pa92Hd4bUAY79AMZ7JPBDj+TLZ2h1DCCcn4AAAAAQNvhV1GqrKxM+/bt01//+lfNmjVLhYWFeuyxxxQdHa1f/vKXTTpHp+gELcuaX+9nOTk5yn43259I9ZqcMUGZmZl1to9aPEpHSo8oMaajVjaQITExsdntS9LDw+7VXf1vCCiDHfqBDPbJYIefyZbOMG75uKCcHwAAAADQdvhVlHI6nSotLdUf//hHde3aVZJUUFCgN954o8lFqWPlJRq9aGK9n5XvOOZPnAbN3bxYL5etqbO9qKzY99+GMozNGKG5tzX/ccSn1r2gFZvfDyiDHfqBDPbJYIefyZbOUFpe0uxzAwAAAADaFr+KUklJSYqMjPQVpCTphz/8oQ4dOtTkc5imqbLq+h+JcscH5xEeV5zqbcM0zUYzbCv4KigZtn37VcAZ7NAPZLBPBjv8TFqVAQAAAADQfvi10PmgQYNUWVmpPXv2+Lbt3r27VpGqORxJUQpLjGzWOcISI+VIigr4+PyDX2rLgS/k9rgDOt7tcStv/3Zt/XZHwBns0A9ksE8GO/xM2iEDAAAAACC0+FWUOuecc3T55ZfrkUce0Y4dO/Txxx9r3rx5uvnmm4MWKDKtY6seL0nz1i1SmOFX1/g4whyat25RszPYoR/IYJ8MdviZtEMGAAAAAEDo8PsO8+mnn1aPHj1088036z//8z91yy236NZbbw1aoPA+8TLinJK/T00ZkhHnVHif+GZnWLZptQ4cK5DL7fLrOJfbpf1Hv1XO53XXDvKXHfqBDPbJYIefSTtkAAAAAACEDr+LUnFxcZo9e7Y2b96sTz75RPfff7+MIL7O3XCGKXZMDykirOlFAENShPc4wxnYTI5TVVRX6ufP36UTlSebfAPucrt0ovKkxj53pyqqK5udwQ79QAb7ZLDDz6QdMgAAAAAAQkfz75ZbgCMhQh2u7yWjQ9PWYTc6ONXh+l5yJEQELcM3R/bqp3PGq6DksCQ1uJZOzfaCksP66Zzx2l24L2gZ7NAPZLBPBjv8TNohAwAAAAAgNPj19j0rORIiFDfhHFXvPK7K/GJ5iurOsghLjFRkWkfv41VBmI1yut2F+zR05jXKvGCkJg3LUnqP/nX22Xpwh+atW6Scz9e0yEwQO/QDGeyTwQ4/k3bIAAAAAABo+2xblJK8j01F9EtQRL8EuQsr5DwhTc6YoLmbF8sVp2a90aypKqortXhjrhZvzFVat37qn9JXDw+7V0+te0HbC75W/sEvWzyDHfqBDPbJYIefSTtkAAAAAAC0bbZ8fK8+jqQoRad2VGZmpqJTO1py83+6/INfasXm91VUVKQVm99vlRtvO/QDGeyTwQ4/k3bIAAAAAABoe9pMUQoAAAAAAAChg6IUAAAAAAAALEdRCgAAAAAAAJajKAUAAAAAAADLGaZpmlY05Ha7lZeXp2GXD1OZGdgr4g3DUGJMRxWVFSuQ2GaZSzIlGZIRE9iLB8lABjIEP0OMEal1H61Tenq6HA5HQBkAAAAAAG1LYHegzWFK5klXoIfqSOkRMpCBDKGWITYy8GMBAAAAAG2S9UUpQzJi2++MEDKQgQz1nSCgZgEAAAAAbZjlRSkj2qH4G3sHdGxMeLRWZs3X6EUTVVZd7vfxxxfuknnSJSPGqfjbyUAGMtglg/vNgoDaBQAAAAC0XSx0DgAAAAAAAMtRlAIAAAAAAIDlKEoBAAAAAADAcm2mKOUurFD5jmPKyclR+Y5jchdWtMsMad36aWzGCCUmJmpsxgildevXLjNwLbzoBwAAAABAW2X92/f8YLo8qt55XJX5xfIUVUqSst/N9n0elhipyLSOCu8TL8PZMvU1O2SICo/UuMGjNGlYlgZ1P9+3fe5tsyRJWw58oXnrFmnZptWqqK4M2QxcCy/6AQAAAAAQCgwzoPe3+8/tdisvL0+Xjxwux40pje9fUqWTb++XecLV6L5GnFOxY3rIkRBxxv18bxmLbdpbxuyQ4dzkXlp+3wJ175Qij+mRI8xRN6fHrTAjTAeOFWjsc3dqd+G+kMvAtfj3+UO0H9xvFuijNWuVnp4uh6Pu+QAAAAAAocevaRQ5OTlKTU2t83XeeecFNZS7pEqlS/fKLG38xluSzFKXSpfulbukKqQynJvcSx888FelJHSRYRj13vxLkiPMIcMwlJLQRR8+uETnJPUMqQxcCy/6AQAAAAAQSvwqSo0aNUrr16/3fX300Ufq2bOnbrvttqAFMl0enXx7v1TlkZo6h8uUVOU9znR5QiJDVHiklt+3QHGRsXI6mvaUpdPhVFxkrHLvf1FR4ZEhkYFr4UU/AAAAAABCjV9FqaioKCUlJfm+3n77bZmmqQceeCBogap3Hvc+muTvQ4WmZJ5wqXrn8ZDIMG7wKHXvlNLkm/8aTodTPTp3VeYFI0MiA9fCi34AAAAAAISagFdBLikp0fz58/Uf//Efiog485o1/qjML27V4+2SYdKwLHnMwGa3uD1uTRqWFRIZuBZe9AMAAAAAINQEXJR64403lJycrKuvvjpoYdyFFb63iQXKU1Qpd2FFm86Q1q2fBnU/v8H1ehrjCHMovUd/pXXr16YzcC286AcAAAAAQCjy7zmcfzNNU2+99Zbuuusuv481DEMx4dH1flZ+vDyQOHU4T0jRKXXbOGEYMttAhgEpqUHJ0D+lr3Yd3ttmM3AtvNpDP5QaRlDODwAAAABoOwIqSm3dulWHDx/WNddc4/exnaITtCxrfr2f5eTkKPvd7EAi1TI5Y4IyMzPrbB+1eJSOlB5RYkxHrbRxhsTExGa3L0kPD7tXd/W/oc1m4Fp4tYd+GLd8XFDODwAAAABoOwIqSn388ccaMmSIzjrrLL+PPVZeotGLJtb7WfmOY4HEqWPu5sV6uWxNne1FZcW+/9o5w9iMEZp726xmZ3hq3Qtasfn9NpuBa+HVHvqhtLyk2ecGAAAAALQtARWl8vPzdcEFFwTUoGmaKquu/3Ekd3xwHuFxxaneNkzTbBMZthV8FZQM2779qk1n4Fp4tad+AAAAAAC0HwEtdL5z50717t072FnkSIpSWGJks84RlhgpR1JUm86Qf/BLbTnwhdwed0DHuz1u5e3frq3f7mjTGbgWXvQDAAAAACAUBVSUKioqUnx8fLCzSJIi0zq26vF2yTBv3SKFGYG9HNER5tC8dYtCIgPXwot+AAAAAACEmoDuMPPz83XZZZcFO4skKbxPvIw4p+TvE0uGZMQ5Fd6n+cUyO2RYtmm1DhwrkMvt8us4l9ul/Ue/Vc7nddcOaosZuBZe9AMAAAAAINQENu2hBRnOMMWO6SFFhDX9BtyQFOE9znA2/1uyQ4aK6kr9/Pm7dKLyZJOLAC63SycqT2rsc3eqoroyJDJwLbzoBwAAAABAqLFdUUqSHAkR6nB9LxkdmrYOu9HBqQ7X95IjISKkMnxzZK9+Ome8CkoOS1KD6/nUbC8oOayfzhmv3YX7QioD18KLfgAAAAAAhJKA3r5nBUdChOImnKPqncdVmV8sT1HdWRZhiZGKTOvofbQpCDNB7Jhhd+E+DZ15jTIvGKlJw7KU3qN/nX22HtyheesWKefzNS0yG8UOGbgWXvQDAAAAACBU2LYoJXkfWYrol6CIfglyF1bIeUKanDFBczcvlitOzXqbWFvKUFFdqcUbc7V4Y67SuvVT/5S+enjYvXpq3QvaXvC18g9+2S4ycC286AcAAAAAQCiw5eN79XEkRSk6taMyMzMVndrRkhtvO2bIP/ilVmx+X0VFRVqx+f1Wufm3QwauhRf9AAAAAABoq9pMUQoAAAAAAAChg6IUAAAAAAAALEdRCgAAAAAAAJYzTNM0rWjI7XYrLy9Pwy4fpjIzsLdxGYahxJiOKiorViCxzTKXZEoyJCMmsDXeyUAGMgQ/Q4wRqXUfrVN6erocDkdAGQAAAAAAbYv1b98zJfOkK9BDdaT0CBnIQIZQyxAbGfixAAAAAIA2yfqilCEZse13RggZyECG+k4QULMAAAAAgDbM8qKUEe1Q/I29Azo2JjxaK7Pma/SiiSqrLvf7+OMLd8k86ZIR41T87WQgAxnsksH9ZkFA7QIAAAAA2i4WOgcAAAAAAIDl2l5RyuNp7QQAAAAAAABoJuvXlPLToMIK3fJliX5UUK7U4ipFPDNUe8MMfdUxQhtSovV6vwRtSYpq7ZgAAAAAAADwg22LUj8sqdJzaw/px4fKVW1I20xpmaQTkuI8ps47Wqk7jlVq0tYS/ePsaN0//GztSYho0UzuwgqVHy9XTk6OyncckzvekMPighgZyEAGAAAAAEAosGVR6vqvv9fza79TldvUy5L+15Ty6tkv3ZSmSrr+ULk+/eseTR5+tpb1jQ9qFtPlUfXO46rML5anqFKSlP1utu/zsMRIRaZ1VHifeBnOlnkakgxkIAMAAAAAINTYrih1/dffa97fDulrSVdL2qeGF77Kl/RLSU9Kes9tav7fCmTI1NK+ZwUli7ukSiff3i/zhKvBfTxFlSpf+50q/lWk2DE95AjybC0ykIEMAAAAAIBQ5PcUhkOHDunuu+/WBRdcoOHDh2vhwoVBC3NOSZWeX/udvpZ0iaSD/97e0NLmNdsPSvqRpJ2Snl/7nX5YUtXsLO6SKpUu3SuztOEb71OZpS6VLt0rdxDaJgMZyAAAAAAACHV+F6V+/etfKyYmRjk5OZo2bZqeeeYZ/e1vfwtKmGfXHlKl29TVko5LcjfxOPe/9x8hqcpt6rm1h5qVw3R5dPLt/VKVRzKbepCkKu9xpqv5bwgkAxnIAAAAAAAIZX4Vpb7//nvl5eXp3nvvVa9evXTllVfqsssu04YNG5odZNCRCv34ULmWyfvIXlMLUjXc/z5umaQfHyrXoMKKgLNU7zzufTSpqTfeNUzJPOFS9c7jAbdNBjKQAQAAAADQHvhVlIqKilJ0dLRycnJUXV2t3bt36/PPP1e/fv2aHeSWHSWqNqT/9TfUKcLkPb7akG75siTgLJX5xQEfG4zjyUAGMgAAAAAAQp1f9Z/IyEg99thjWrJkiQYNGqSRI0fqJz/5iW644YZmB/lRQbm2/fste4E+5OORtFnSNlO6+FB5QOdwF1b43iYWKE9RpdzNmKlFBjKQAQAAAAAQ6vx++94333yjK664QnfccYd27typGTNm6Ec/+pHGjBnTpOMNw1BMeHSd7anFVVrmb5gGfCUp81hVnXZOGIbMM2SQpPLjgRWzTuc8IUWn1G2DDGQgQ902Sg0jKOcHAAAAALQdfhWlNmzYoKVLl2rdunWKiorSwIEDdfjwYb3wwgtNLkp1ik7Qsqz5tTd6PIp4ZqhO+BPmDI5LivCYWjnhL1LY/00GG7V4lI6UHlFiTEetPD3Dv+Xk5Cj73exmZ5icMUGZmZl1tpOBDGSom2Hc8nHNPjcAAAAAoG3xqyi1bds29ezZU1FRUb5t559/vv785z83+RzHyks0etHEOtv3hhmK8/i7gnL94iVVhRkavfjuWtuLyop9/60vgySV7zgWlAxzNy/Wy2Vr6mwnAxnIUDdDaXlJUM4PAAAAAGg7/CpKJScna9++faqqqlJERIQkaffu3erWrVuTz2Gapsqq6z4K9FXHCJ13tHlr1tQ4T9KOThF12jFN84wZJMkdH5zHiFxxqrcNMpCBDA1nAAAAAAC0H34tdD58+HCFh4dr+vTp2rNnj9auXas///nPuvXWW5sdZENKtAYYUrq/oU4RJilDUn9D+vTs+tfGaYwjKUphiZEBJvh3jsRIOZKiGt+RDGQgAwAAAACgnfKr/hMXF6eFCxeqsLBQ119/vWbNmqV7771X48ePb3aQ1/slKNyUpqp5b9+bKinc9J4vUJFpHQM+NhjHk4EMZAAAAAAAhDq/JyX17t1bL7/8sjZt2qS//e1vuv3222UE4c1ZW5Ki9I+zo3W9pJ6SHH4e7/j3ceMk/ePsaG1pxoyM8D7xMuKckr/fliEZcU6F94kPuG0ykIEMAAAAAID2INAn5VrE/cPPVoTD0LvyLlbe1MKU49/7vycpwmHo/uFnNyuH4QxT7JgeUkRY02/ADUkR3uMMZ/O7lQxkIAMAAAAAIJTZ6i5xT0KEJg8/W30lbZBUs3x6QyFrtnf79/59JE0efrb2JEQ0O4sjIUIdru8lo0PT1oI3OjjV4fpecgShbTKQgQwAAAAAgFDn19v3rLCsb7wMmXp+7Xfa6ja1TNL/Stpcz76D5F1Dapy8M6QmDj9by/oG7xEhR0KE4iaco+qdx1WZXyxPUd23A4YlRioyraP30aYWmAlCBjKQAQAAAAAQimxXlJKkpX3P0qbkaD239pBuP1SuWwxpmyl9Jem4vI/qpUoaYHgXNV+fEq0pVwRnhtTpDGeYIvolKKJfgtyFFXKekCZnTNDczYvlipMlbxMjAxnIAAAAAAAINbadwrAnIULXZPbUsBt76eUBCXIkRiozzNAkSZlhhhyJkXp5QIKG3dhL1/68Z4sUpE7nSIpSdGpHZWZmKjq1Y6vceJOBDGQAAAAAAIQCW86UOtWWpChtSfqBJCkmPForJ/xFoxffrbLq8lZOBgAAAAAAgEDZdqZUg8LaXmQAAAAAAADURoUHAAAAAAAAljNM0zStaMjlcmnLli0aOWqkys26b+tqCsMw1Ck6QcfKSxRIbLPcLZmSDMmIdpCBDGSwSYZoI1JrVq/RoEGD5HTa/qliAAAAAEAQWHb35/F4JElrVq+xqkkAbUzNOAEAAAAACH2WzZTyeDxyuVwKCwuTYRhWNAmgjTBNUx6PR06nU2GsGwcAAAAA7YJlRSkAAAAAAACgBlMSAAAAAAAAYDmKUgAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALEdRCgAAAAAAAJajKAUAAAAAAADLtamiVE5OjlJTU/XWW29Z2m5qamqtr4svvljTp0/XyZMnLc0hSd9//72eeuopDR8+XIMGDdLIkSO1cOFCeTyeFm97+PDhvj4477zzlJGRoZtuukkff/xxi7ddX4bTvzZu3NjqOW6++WbLMpSVlemZZ57R1VdfrbS0NF100UWaOnWqdu7caUn7w4cPV05OTp3tOTk5Gj58uCUZAAAAAABtl7O1A/hj1apV6tGjh1asWKEbbrjB0rafffZZZWRkyOPx6NChQ3rsscc0e/ZsPfnkk5ZlKC4u1vjx45WcnKw//OEP6tatm7Zu3aoZM2bowIED+t3vftfiGaZNm6ZRo0bJ4/Ho+++/V25uru6++24tWLBAl1xySYu3f2qG05111lmWtH+mHOHh4Za0ffLkSU2YMEFlZWV6+OGHdd5556m4uFivv/66brrpJuXm5qp79+6WZAEAAAAAIBBtpih19OhRbdiwQdnZ2Xr44Yd14MABS2+6zzrrLCUlJUmSunTporvvvltPPvmkpUWpP/7xj4qIiNCLL76oyMhISVL37t0VFRWlyZMnKysrSz/84Q9bNENcXFytfnjooYdUWFioWbNmaeXKlS3adn0ZWlNr5nj++ed19OhRrV69WvHx8ZKkrl27atasWTp06JAWLlxoSZESAAAAAIBAtZnH9959913FxcVpzJgxSk5O1ooVK1o1T3R0tKXtVVVVadWqVbrlllt8BakaV1xxhRYuXKiuXbtamqnG+PHj9fXXX2vfvn2t0n574/F4tHz5ct1xxx2+gtSpZs+erQcffLAVkgEAAAAA0HRtpii1atUqXX755QoLC9Pw4cOVm5sr0zRbJcuxY8f02muvacyYMZa1uX//fpWVlWngwIF1PjMMQxdffLEiIiIsy3Oqc889V5K0a9euVmm/vdm/f7+OHTumIUOG1Pt5cnKyoqKiLE4FAAAAAIB/2sTje4cOHdLnn3+uO+64Q5J01VVX6Y033tCmTZsavDEPtokTJ8rhcMg0TZWXlyshIUFPPPGEJW1L0vHjxyV5Hxmzm5pMVi38/vjjj2vGjBm1tqWkpGjVqlWWtH+mHP/4xz8UExPTou0WFxdLqr2G1ieffKL77rvP92er+qO+PnC5XLZ4vBIAAAAAYG9toii1atUqRUZG6tJLL5UkDR06VGeddZaWL19uWVFq5syZGjRokEzTVHFxsRYtWqSbb75ZK1euVOfOnVu8/YSEBEnet+/ZTWlpqSSpQ4cOlrQ3depUXXXVVbW2OZ3W/yjXl8OKxzprHtmrKVRKUkZGhnJzcyVJ77//vt54440WzyHV3wdWtg8AAAAAaLvaTFGqoqJCgwcP9m1zu91699139bvf/c6SR5W6dOminj17SpJ69eql/v3766KLLtKaNWuUlZXV4u336NFDcXFx2r59u9LS0up8fu+99+rWW2+17A14p/rqq68kSX369LGkvc6dO/uuRWtqrRw9e/ZUQkKCNm/e7PtZiI6O9mWxokhao74+sLJ9AAAAAEDbZfs1pfbs2aMvvvhC06dPV25uru/rT3/6k0pLS/W3v/2tVXKFhYXJNE253W5L2nM6nRo1apRef/11VVVV1fps7dq1Wrt2rZKTky3Jcrply5apf//+lr4NsT1zOp0aN26cXnnlFd8stVMdPny4FVIBAAAAAOAf28+UWrVqlRISEjR+/PhaC3n37dtXzz//vHJzczV69OgWz/H999+rsLBQknftpJdeeklut1vDhw9v8bZrTJkyRTfccIPuvPNOTZkyRT/4wQ+0ceNGzZkzR7fddpt69+7d4hlOnDihwsJC32OMS5cu1erVq/XSSy+1eNunZzhdbGxsi6/nZBdTpkzRpk2bdNNNN+n+++9X//79VVxcrLfeektLly7Vtdde29oRAQAAAAA4ozZRlBo9enS9b5a7+eab9Yc//EGHDx9Wly5dWjTHlClTfP87OjpaAwYM0Pz58y2dHZSUlKQ33nhDzz77rB544AGVlJSoR48emjp1qm6++WZLMmRnZys7O1uGYahTp046//zztXDhQsvW9jo1w+l+9atfafLkyZblaE3R0dF67bXX9Morr2ju3Lnat2+fIiIilJaWpmeffVZXXnlla0cEAAAAAOCMDNM0zdYOAQAAAAAAgPbF9mtKAQAAAAAAIPRQlAIAAAAAAIDlKEoBAAAAAADAchSlAAAAAAAAYDmKUgAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALEdRCgAAAAAAAJajKBWCJk2apEceeaTWtnfeeUepqal69tlna22fO3eurrvuOknS0aNHNXXqVA0ePFg//vGPNWfOHLlcLt++xcXFmjJlijIyMjR8+HCtWLGi0SxZWVn6/PPP6/1s4cKFuuyyy5SRkaFp06apvLz8jOdatmyZfve739XZnpOTo9TUVN9X//79dfXVVys3N7fWflu3btVNN92kQYMGacSIEXU+r3Hw4EFlZGRo48aNjX5/AAAAAAAgMBSlQtCQIUO0devWWts2btyo5OTkOoWWvLw8DR06VJL0wAMPqLS0VEuWLNH//M//aNWqVVqwYIFv30ceeUQnTpzQkiVLdO+992r69OnKz89vMEd5ebl27typtLS0Op+99957eu655/T73/9er7zyirZs2aI5c+ac8fvasGGDfvSjH9X72Q9+8AOtX79e69ev13vvvadJkyZp+vTp2rx5syTpxIkTmjhxojIyMvTOO+/ovvvu0/Tp07Vp06Y653riiSdUVlZ2xiwAAAAAAKB5KEqFoMGDB+ubb77RyZMnfds2btyoO++8U3l5eaqoqPBt37Jli4YOHaqqqip17txZjz/+uHr37q0hQ4ZoxIgRvqLN/v379fe//10zZ85U3759dcMNN2jMmDFavHhxgzk+++wzpaeny+l01vns1Vdf1S9+8QtdccUVSktL05NPPqlly5adcbbUxo0bdfHFF9f7mcPhUFJSkpKSktStWzdlZmbqoosu0rvvvitJOnTokH7yk5/ooYceUvfu3TVmzBj16dOnziyut99+u1a/AQAAAACAlkFRKgQNHDhQ4eHh2r59uyTpu+++U0FBgW644QbFxcX5CjF79uzR999/ryFDhigiIkJPP/20evbsKUnauXOn1q5d65tFtWXLFp199tnq1q2br53Bgwf7ZiLVp6GZTW63W1u3btWQIUN829LT01VdXa0dO3bUe65du3apY8eO6tSpU5P7ISYmxve/+/btq9mzZ8swDHk8Hq1du1Z79uzRhRde6NunuLhYc+bM0e9///smtwEAAAAAAAJDUSoERUREaNCgQb5H6z799FMNGDBAsbGxuvDCC32P8OXl5alPnz7q2LFjreOzsrJ07bXXKi4uTrfccoskqbCwUMnJybX269y5sw4fPtxgjk8//bTemU3Hjx9XZWVlrfM5nU4lJCTou+++q/dcZ3p0rz6bNm3SJ598omuuuabW9qqqKqWlpenee+/Vddddp/T0dN9nTz31lH7+85+rT58+TW4HAAAAAAAEhqJUiBoyZIivKLVx40ZddNFFkqShQ4fWKkrVzIQ61fTp0/Xqq6+qurpav/3tbyV514eKiIiotV9ERISqqqrqbb+kpESHDx9Wampqnc9qHh/053yNFaUKCgqUkZGhjIwMDRgwQBMmTNCPf/xjnX/++XX2XbJkiZ5++mmtXr1aL7/8siTpk08+0aZNmzR58uQG2wAAAAAAAMFDUSpEnbrY+caNG33Fp6FDh2rbtm2qqqpSXl5ercfXapx33nm66KKLlJ2drb///e86ePCgIiMj6xSMqqqqFBUVVW/7NW0ahlHns8jISN/xp58vOjq6zv5ut1uff/55rcf9TpecnKzc3Fzl5uZqxYoVev755/XFF1/UeVtfRESE+vfvr9GjR+uee+7Ra6+9poqKCj322GN6/PHHG/x+AAAAAABAcFGUClEZGRk6cuSItm7dqiNHjuiCCy6QJPXp00dxcXH617/+pV27dvmKVaWlpVq9erU8Ho/vHL1795bkXWupS5cuKioqqtVGUVGRkpKS6m3/TDObEhISFBkZWet8LpdLJSUl9Z5v+/bt6tWrlzp06NDg9+t0OtWzZ0/17NlT5557rq688kr9+te/1vLly1VaWqoDBw7o448/rnVM7969VVxcrPz8fB04cEBTp071zbaSpIkTJ+qxxx5rsE0AAAAAABC4uq9FQ0iIiYlRv379tGTJEg0cONA3A8kwDF144YXKyclRr169fAuHl5eX6ze/+Y3OPvtsX1Fm+/btcjgc+uEPf6iEhAR9++23+u677/SDH/xAknfdplPXZDrVhg0bdOedd9b7WVhYmAYOHKhNmzb5HivMy8uT0+nUeeedV++5/FlPqoZpmjJNUx6PR/n5+Xr88ce1fv1632yobdu26ZxzzlFaWpref//9WsdeddVVmjlzpn784x/73S4AAAAAAGgcM6VC2IUXXqhVq1bVWTdq6NCh+vDDD2s9upeUlKSrrrpKM2bM0BdffKHPPvtMjz76qLKystShQwd1795dl156qR588EHt2LFDb731lt555x3fQuin+u6771RdXa3u3bs3mG3ChAl68cUX9cEHHyg/P19PPPGEbrzxxnof32tKUcrtdquwsFCFhYU6cuSIPvvsM82dO1eXXnqp4uPjdfnllysuLk6PPfaY9uzZo5UrV2rBggW69957FRUV5ZtlVfMlSV26dFHnzp3P2C4AAAAAAAgMM6VC2ODBg/XSSy/5ZiPVGDp0qMrLy+sUq7Kzs5Wdna077rhDkjR27Fj9x3/8h+/z2bNn69FHH9WNN96opKQkZWdnKy0trU67GzZsqPete6e65ppr9O233+qxxx5TVVWVrrrqKj344IN19quqqtKXX37Z4IysGt99950uvfRSSd6ZWAkJCbryyiv1m9/8RpIUGxurBQsWaMaMGcrMzFTHjh01bdo0XXnllWc8LwAAAAAAaBmGaZpma4cAAAAAAABA+8LjewAAAAAAALAcRSkAAAAAAABYjqIUAAAAAAAALEdRCgAAAAAAAJajKAUAAAAAAADLUZQCAAAAAACA5ShKAQAAAAAAwHIUpQAAAAAAAGA5ilIAAAAAAACwHEUpAAAAAAAAWI6iFAAAAAAAACxHUQoAAAAAAACW+//n6sbPA7zXGgAAAABJRU5ErkJggg==\n"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"board, action = simulate_game(1, (GreedyPolicy(0), GreedyPolicy(0)))\n",
"\n",
"plot_othello_boards(\n",
" *drop_duplicate_boards(board.reshape(-1, 8, 8), action.reshape(-1, 2))\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Statistical examination of the natural action space and result\n",
"As for many project some evaluation of the project is in order.\n",
"\n",
"1. What is the expected distribution of scores\n",
"2. What is the expected distribution of possible actions\n",
"\n",
" a. over time\n",
" \n",
" b. ober space\n",
"\n",
"The easiest and robustest way to analyse this is when analyzing randomly played games."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For this purpose we played a sample of 10k games and saved them for later analysis."
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "((70, 10000, 8, 8), (70, 10000, 2))"
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"if not os.path.exists(\"rnd_history.npy\") and not os.path.exists(\"rnd_action.npy\"):\n",
" simulation_results = simulate_game(\n",
" 10_000, (RandomPolicy(1), RandomPolicy(1)), tqdm_on=True\n",
" )\n",
" _board_history, _action_history = simulation_results\n",
" np.save(\"rnd_history.npy\", np.astpye.astype(np.int8))\n",
" np.save(\"rnd_action.npy\", _action_history.astype(np.int8))\n",
"else:\n",
" _board_history = np.load(\"rnd_history.npy\")\n",
" _action_history = np.load(\"rnd_action.npy\")\n",
"_board_history.shape, _action_history.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For those 10k games the possible actions where evaluated and saved for each and every turn in the game."
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "(70, 10000, 8, 8)"
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"if not os.path.exists(\"turn_possible.npy\"):\n",
" __board_history = _board_history.copy()\n",
" __board_history[1::2] = __board_history[1::2] * -1\n",
"\n",
" _poss_turns = get_possible_turns(\n",
" __board_history.reshape((-1, 8, 8)), tqdm_on=True\n",
" ).reshape((SIMULATE_TURNS, -1, 8, 8))\n",
" np.save(\"turn_possible.npy\", _poss_turns)\n",
" del __board_history\n",
"_poss_turns = np.load(\"turn_possible.npy\")\n",
"_poss_turns.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Those possible turms then where counted for all games in the history stack."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The action space size can be drawn into a histogram by turn and a curve over the mean action space size.\n",
"This can be used to analyse in which area of the game that cant be solved absolutely."
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "interactive(children=(IntSlider(value=34, description='turn', max=69), Output()), _dom_classes=('widget-intera…",
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "a13cb900bf9441bab6cb50c0ea6cc58d"
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"count_poss_turns = np.sum(_poss_turns, axis=(2, 3))\n",
"mean_possibility_count = np.mean(count_poss_turns, axis=1)\n",
"std_possibility_count = np.std(count_poss_turns, axis=1)\n",
"cum_prod = count_poss_turns\n",
"\n",
"\n",
"@interact(turn=(0, 69))\n",
"def poss_turn_count(turn):\n",
" fig, axes = plt.subplots(2, 2, figsize=(15, 8))\n",
" ax1, ax2, ax3, ax4 = axes.flatten()\n",
" _mean_possibility_count = mean_possibility_count.copy()\n",
" _std_possibility_count = std_possibility_count.copy()\n",
" _mean_possibility_count[_mean_possibility_count <= 1] = 1\n",
" _std_possibility_count[_std_possibility_count <= 1] = 1\n",
" # np.cumprod(_mean_possibility_count[::-1], axis=0)[::-1]\n",
" # todo what happens here=\n",
" fig.suptitle(\n",
" f\"Action space size analysis\\nThe total size is estimated to be around {np.prod(_mean_possibility_count):.4g}\"\n",
" )\n",
" ax1.hist(count_poss_turns[turn], density=True)\n",
" ax1.set_title(f\"Histogram of the action space size for turn {turn}\")\n",
" ax1.set_xlabel(\"Action space size\")\n",
" ax1.set_ylabel(\"Action space size probability\")\n",
" ax2.set_title(f\"Mean size of the action space per turn\")\n",
" ax2.set_xlabel(\"Turn\")\n",
" ax2.set_ylabel(\"Average possible moves\")\n",
"\n",
" ax2.errorbar(\n",
" range(70),\n",
" mean_possibility_count,\n",
" yerr=std_possibility_count,\n",
" label=\"Mean action space size with error bars\",\n",
" )\n",
" ax2.scatter(turn, mean_possibility_count[turn], marker=\"x\")\n",
" ax2.legend()\n",
"\n",
" ax4.plot(\n",
" range(70),\n",
" np.cumprod(_mean_possibility_count[::-1], axis=0)[::-1],\n",
" # yerr=np.cumprod(_std_possibility_count[::-1], axis=0)[::-1],\n",
" )\n",
" ax4.scatter(\n",
" turn,\n",
" np.cumprod(_mean_possibility_count[::-1], axis=0)[::-1][turn],\n",
" marker=\"x\",\n",
" )\n",
" ax4.set_yscale(\"log\", base=10)\n",
" ax4.set_xlabel(\"Turn\")\n",
" ax4.set_ylabel(\"Mean remaining total action space size\")\n",
" fig.delaxes(ax3)\n",
" fig.tight_layout()\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It is interesting to see that the action space for the first player (white) is much smaller than for the second player."
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": " Total mean action-space\nwhite 5.687159e+18\nblack 3.753117e+20",
"text/html": "
![\"Startaufstellung.png\"](\"Startaufstellung.png\"/)
\n",
"\n",
"## Some common Othello strategies\n",
"\n",
"As can be easily understood the placement of stones and on the bord is always a careful balance of attack and defence.\n",
"If the player occupies huge homogenous stretches on the board it can be attacked easier.\n",
"The boards corners provide safety from wich occupied territory is impossible to loos but since it is only possible to reach the corners if the enemy is forced to allow this or calculates the cost of giving a stable base to the enemy it is difficult to obtain.\n",
"There are some text on otello computer strategies which implement greedy algorithms for reversi based on a modified score to each field.\n",
"Those different values are score modifiers for a traditional greedy algorithm.\n",
"If a players stone has captured such a filed the score reached is multiplied by the modifier.\n",
"The total score is the score reached by the player subtracted with the score of the enemy.\n",
"The scores change in the course of the game and converges against one. This gives some indications of what to expect from an Othello AI.\n",
"\n",
"![\"ComputerPossitionScore\"](\"computer-score.png\"/)
\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initial design decisions\n",
"\n",
"At the beginning of this project I made some design decisions.\n",
"The first onw was that I do not want to use a gym library because it limits the data formats accessible.\n",
"I choose to implement the hole game as entry in a stack in numpy arrays to be able to accommodate interfacing with a neural network easier and to use scipy pattern recognition tools to implement some game mechanics for a fast simulation cycle.\n",
"I chose to ignore player colors as far as I could instead a player perspective was used. Which allowed to change the perspective with a flipping of the sign. (multiplying with -1).\n",
"The array format should also allow for data multiplication or the breaking of strikt sequences by flipping the game along one the for axis, (horizontal, vertical, transpose along both diagonals).\n",
"\n",
"I wanted to implement different agents as classes that act on those game stacks.\n",
"\n",
"Since computation time is critical all computational have results are saved.\n",
"The analysis of those is then repeated in real time. If a recalculation of such a section is required the save file can be deleted and the code should be executed again."
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The blackcellmagic extension is already loaded. To reload it, use:\n",
" %reload_ext blackcellmagic\n",
"The line_profiler extension is already loaded. To reload it, use:\n",
" %reload_ext line_profiler\n",
"The memory_profiler extension is already loaded. To reload it, use:\n",
" %reload_ext memory_profiler\n"
]
}
],
"source": [
"%load_ext blackcellmagic\n",
"%load_ext line_profiler\n",
"%load_ext memory_profiler"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Imports and dependencies\n",
"\n",
"The following direct dependencies where used for this project:\n",
"```toml\n",
"jupyter = \"^1.0.0\"\n",
"matplotlib = \"^3.6.3\"\n",
"numpy = \"^1.24.1\"\n",
"pytest = \"^7.2.1\"\n",
"python = \"3.10.*\"\n",
"scipy = \"^1.10.0\"\n",
"tqdm = \"^4.64.1\"\n",
"jupyterlab = \"^3.6.1\"\n",
"torchvision = \"^0.14.1\"\n",
"torchaudio = \"^0.13.1\"\n",
"```\n",
"* `Jupyter` and `jupyterlab` on pycharm was used as an IDE / Ipython was used to implement this code.\n",
"* `matplotlib` was used for visualisation and statistics.\n",
"* `numpy` was used for array support and mathematical functions\n",
"* `tqdm` was used for progress bars\n",
"* `scipy` contains fast pattern recognition tools for images. It was used to make an initial estimation about where possible turns should be.\n",
"* `torch` supplied the ANN functionalities."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"import pickle\n",
"import abc\n",
"import itertools\n",
"import os.path\n",
"from abc import ABC\n",
"from enum import Enum\n",
"from typing import Final\n",
"from IPython.display import clear_output, display\n",
"from pathlib import Path\n",
"import glob\n",
"import copy\n",
"from functools import lru_cache, wraps\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"from ipywidgets import interact\n",
"from scipy.ndimage import binary_dilation\n",
"from tqdm.notebook import tqdm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Constants\n",
"\n",
"Some general constants needed to be defined. Such as board game size and Player and Enemy representations. Also, directional offsets and the initial placement of blocks."
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"BOARD_SIZE: Final[int] = 8 # defines the board side length as 8\n",
"PLAYER: Final[int] = 1 # defines the number symbolising the player as 1\n",
"ENEMY: Final[int] = -1 # defines the number symbolising the enemy as -1\n",
"EXAMPLE_STACK_SIZE: Final[int] = 1000 # defines the game stack size for examples\n",
"IMPOSSIBLE: Final[np.ndarray] = np.array([-1, -1], dtype=int)\n",
"IMPOSSIBLE.setflags(write=False)\n",
"SIMULATE_TURNS: Final[int] = 70\n",
"VERIFY_POLICY: Final[bool] = False\n",
"TRAINING_RESULT_PATH: Final[Path] = Path(\"training_data\")\n",
"if not os.path.exists(TRAINING_RESULT_PATH):\n",
" os.mkdir(TRAINING_RESULT_PATH)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The directions array contains all the numerical offsets needed to move along one of the 8 directions in a 2 dimensional grid. This will allow an iteration over the game board.\n",
"\n",
"![8-directions.png](8-directions.png \"Offset in 8 directions\")"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[-1, -1],\n [-1, 0],\n [-1, 1],\n [ 0, -1],\n [ 0, 1],\n [ 1, -1],\n [ 1, 0],\n [ 1, 1]])"
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"DIRECTIONS: Final[np.ndarray] = np.array(\n",
" [[i, j] for i in range(-1, 2) for j in range(-1, 2) if j != 0 or i != 0],\n",
" dtype=int,\n",
")\n",
"DIRECTIONS.setflags(write=False)\n",
"DIRECTIONS"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another constant needed is the initial start square at the center of the board."
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[-1, 1],\n [ 1, -1]])"
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"START_SQUARE: Final[np.ndarray] = np.array(\n",
" [[ENEMY, PLAYER], [PLAYER, ENEMY]], dtype=int\n",
")\n",
"START_SQUARE.setflags(write=False)\n",
"START_SQUARE"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating new boards\n",
"\n",
"The first function implemented and tested is a function to generate the starting environment as a stack of games.\n",
"As described above I simply placed a 2 by 2 square in the center of an empty stack of boards."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "array([[ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, -1, 1, 0, 0, 0],\n [ 0, 0, 0, 1, -1, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0],\n [ 0, 0, 0, 0, 0, 0, 0, 0]])"
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def get_new_games(number_of_games: int) -> np.ndarray:\n",
" \"\"\"Generates a stack of initialised game boards.\n",
"\n",
" Args:\n",
" number_of_games: The size of the board stack.\n",
"\n",
" Returns: The generates stack of games as a stack n x 8 x 8.\n",
"\n",
" \"\"\"\n",
" empty = np.zeros([number_of_games, BOARD_SIZE, BOARD_SIZE], dtype=int)\n",
" empty[:, 3:5, 3:5] = START_SQUARE\n",
" return empty\n",
"\n",
"\n",
"get_new_games(1)[0]"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"test_number_of_games = 3\n",
"assert get_new_games(test_number_of_games).shape == (\n",
" test_number_of_games,\n",
" BOARD_SIZE,\n",
" BOARD_SIZE,\n",
")\n",
"np.testing.assert_equal(\n",
" get_new_games(test_number_of_games).sum(axis=1),\n",
" np.zeros(\n",
" [\n",
" test_number_of_games,\n",
" 8,\n",
" ]\n",
" ),\n",
")\n",
"np.testing.assert_equal(\n",
" get_new_games(test_number_of_games).sum(axis=2),\n",
" np.zeros(\n",
" [\n",
" test_number_of_games,\n",
" 8,\n",
" ]\n",
" ),\n",
")\n",
"assert np.all(get_new_games(test_number_of_games)[:, 3:4, 3:4] != 0)\n",
"del test_number_of_games"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Visualisation tools\n",
"\n",
"In this section a visualisation help was implemented for debugging of the game and a proper display of the results.\n",
"For this visualisation ChatGPT was used as a prompted code generator that was later reviewed and refactored by hand to integrate seamlessly into the project as a whole.\n",
"White stones represent the player, black stones the enemy. A single plot can be used as a subplot when the `ax` argument is used."
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "