{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "960cd706", "metadata": {}, "source": [ "# Thesis Code\n", "### Zachary Nathan, May 28 2023" ] }, { "attachments": {}, "cell_type": "markdown", "id": "88f10e56-68cd-4667-ad45-3fbeb34b738f", "metadata": {}, "source": [ "### Imports" ] }, { "cell_type": "code", "execution_count": 1, "id": "5a1d2d71-04cf-4a4a-a7ab-e55934ac37ea", "metadata": { "tags": [] }, "outputs": [], "source": [ "import warnings\n", "warnings.simplefilter(action='ignore', category=FutureWarning)\n", "\n", "import ee\n", "import utm\n", "import time\n", "import math\n", "import torch\n", "import gpytorch\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import gstools as gs\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "from typing import List, Tuple, Callable\n", "from sklearn import metrics\n", "from functools import reduce\n", "from itertools import combinations\n", "\n", "from gpytorch.means import ConstantMean\n", "from gpytorch.models import ExactGP, ApproximateGP\n", "from gpytorch.likelihoods import GaussianLikelihood\n", "from gpytorch.distributions import MultivariateNormal\n", "from gpytorch.kernels import ScaleKernel, MaternKernel\n", "from gpytorch.mlls import ExactMarginalLogLikelihood, VariationalELBO\n", "from gpytorch.variational import CholeskyVariationalDistribution, VariationalStrategy" ] }, { "cell_type": "code", "execution_count": 2, "id": "7d861b14-5b04-4937-a4c3-d6528e43fe58", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 3, "id": "5076a165", "metadata": {}, "outputs": [], "source": [ "np.random.seed(999)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "2bdf939c", "metadata": {}, "source": [ "## API code" ] }, { "attachments": {}, "cell_type": "markdown", "id": "350e0237-36ff-4542-97c4-b876456a3c91", "metadata": {}, "source": [ "### PredictiveSampler class with GPs" ] }, { "cell_type": "code", "execution_count": 4, "id": "cb3eb5e8", "metadata": {}, "outputs": [], "source": [ "class PredictiveSampler:\n", " \n", " def __init__(\n", " self,\n", " measurements: pd.DataFrame = None,\n", " grid_size: int = 400,\n", " extrapolate_factor: float = 0.0\n", " ) -> None:\n", " \n", " self.measurements: pd.DataFrame = measurements\n", " self.grid_size: int = grid_size\n", " self.extrapolate_factor: float = extrapolate_factor\n", "\n", " self.grid: pd.DataFrame = None\n", " self.x_min: float = -200.0\n", " self.x_max: float = 200.0\n", " self.y_min: float = -200.0\n", " self.y_max: float = 200.0\n", " self.xs: np.array = None\n", " self.ys: np.array = None\n", " \n", " self.generated_fields: List[str] = []\n", " self.predicted_fields: List[str] = []\n", " self.predicted_fields_var: List[str] = []\n", "\n", " self.cached_inducing_points: torch.tensor = None\n", " self.last_n_inducing_points: int = None\n", " \n", " self.init_grid()\n", " \n", " \n", " # create the 'grid' dataframe of x/y grid coordinate pairs, over the area covered by `points`\n", " def init_grid(self) -> None:\n", " \n", " # derive grid limits from `measurements`\n", " if self.measurements is not None:\n", " \n", " # find the bounds of `measurements`\n", " self.x_max, self.y_max = self.measurements[['x_pos', 'y_pos']].max().tolist()\n", " self.x_min, self.y_min = self.measurements[['x_pos', 'y_pos']].min().tolist()\n", "\n", " # extrapolate the grid beyond the bounds of `measurements` by `extrapolate_factor`,\n", " # where 0.0 leaves the bounds unchanged, or 0.5 adds 50%\n", " if self.extrapolate_factor != 0.0:\n", " x_mid = (self.x_max + self.x_min) / 2\n", " y_mid = (self.y_max + self.y_min) / 2\n", " self.x_max += (self.x_max - self.x_mid) * self.extrapolate_factor\n", " self.x_min += (self.x_min - self.x_mid) * self.extrapolate_factor\n", " self.y_max += (self.y_max - self.y_mid) * self.extrapolate_factor\n", " self.y_min += (self.y_min - self.y_mid) * self.extrapolate_factor\n", "\n", " # generate the coordinates with `grid_size` rows and `grid_size` columns\n", " self.xs = np.linspace(self.x_min, self.x_max, self.grid_size)\n", " self.ys = np.linspace(self.y_min, self.y_max, self.grid_size)\n", " mesh_xs, mesh_ys = np.meshgrid(self.xs, self.ys)\n", " coords = np.array([mesh_xs.flatten(), mesh_ys.flatten()]).T\n", " \n", " self.grid = pd.DataFrame(coords, columns=['x_pos', 'y_pos']).astype(np.float32)\n", " \n", " \n", " # helper function to calculate the grid's diagonal size\n", " def grid_diagonal(self) -> float:\n", " \n", " return np.sqrt(np.square(self.x_max - self.x_min) + np.square(self.y_max - self.y_min))\n", " \n", " \n", " # helper function to return all `measurements` field names\n", " def measurements_fields(self) -> List[str]:\n", " \n", " return [\n", " column for column in self.measurements.columns\n", " if column not in ('x_pos', 'y_pos', 'latitude', 'longitude')\n", " ]\n", " \n", " \n", " # create a scatter plot of measurements data for each field/column\n", " def plot_measurements(\n", " self, \n", " fields: List[str] = None,\n", " point_size: float = None,\n", " marker: str = 'o'\n", " ) -> None:\n", " \n", " if fields is None:\n", " fields = self.measurements_fields()\n", " \n", " for field in fields:\n", " if self.measurements is not None and field in self.measurements.columns:\n", "\n", " ax = sns.scatterplot(\n", " self.measurements,\n", " x='x_pos',\n", " y='y_pos',\n", " s=point_size,\n", " hue=field,\n", " edgecolor=None,\n", " palette='rocket',\n", " marker=marker\n", " )\n", "\n", " ax.set_title(f'Sensor measurements in field: {field}')\n", " ax.set_xlabel('x position (meters)')\n", " ax.set_ylabel('y position (meters)')\n", " ax.set_box_aspect(1)\n", " sns.move_legend(ax, 'upper left', bbox_to_anchor=(1, 1))\n", " plt.show()\n", " \n", " \n", " # generate spatial random fields using gstools and store them in the `grid` dataframe\n", " def generate_random_fields(\n", " self,\n", " n_fields: int = 1,\n", " name: str = 'random_field',\n", " len_scale: float = 1.0,\n", " common_basis_factor: float = 0.0,\n", " minmax: bool = False,\n", " heatmaps: bool = False\n", " ) -> None:\n", " \n", " # use a Matern covariance model, same as GPyTorch\n", " covar = gs.Matern(\n", " nu=1.5,\n", " dim=2,\n", " var=1.0,\n", " len_scale=len_scale * (self.grid_diagonal() / 5)\n", " )\n", " srf = gs.SRF(covar)\n", " srf.set_pos([self.xs, self.ys], 'structured')\n", "\n", " if common_basis_factor > 0.0:\n", " basis_field = srf(seed=np.random.randint(0, 2**30)).flatten()\n", " assert common_basis_factor <= 1.0\n", " \n", " # generate fields and add them to `grid`\n", " for i in range(n_fields):\n", "\n", " column_name = f'{name}_{i}' if n_fields > 1 else name\n", " field = srf(seed=np.random.randint(0, 2**30)).flatten()\n", "\n", " if common_basis_factor > 0.0:\n", " field = (field * (1.0 - common_basis_factor)) + (basis_field * common_basis_factor)\n", "\n", " if minmax:\n", " field = (field - field.min()) / (field.max() - field.min())\n", " \n", " self.grid[column_name] = field.astype(np.float32)\n", " self.generated_fields.append(column_name)\n", "\n", " if heatmaps:\n", " self.heatmap_field(column_name)\n", " \n", " \n", " # plot a heatmap of a field in `grid`\n", " def heatmap_field(\n", " self,\n", " column: str,\n", " override_data = None,\n", " n_ticks: int = 9,\n", " log: bool = False,\n", " points: pd.DataFrame = None,\n", " diff_column: str = None,\n", " title: str = None\n", " ) -> None:\n", " \n", " data = override_data if override_data is not None else self.grid\n", "\n", " # if plotting the difference between two columns, create a temporary column\n", " if diff_column:\n", " name = 'temporary_column'\n", " data[name] = np.abs(data[column] - data[diff_column])\n", " column = name\n", "\n", " # pivot the list of x/y coordinates into a matrix with columns for x and rows for y\n", " data = data.pivot(index='y_pos', columns='x_pos', values=column)\n", "\n", " # log transformation, if plotting the log as is typical for variance\n", " if log:\n", " data = np.log(data)\n", "\n", " if diff_column:\n", " self.grid.drop(name, axis=1, inplace=True)\n", "\n", " ax = sns.heatmap(\n", " data,\n", " vmin=data.to_numpy().flatten().min(),\n", " vmax=data.to_numpy().flatten().max()\n", " )\n", " ax.invert_yaxis()\n", "\n", " ax.set_xlabel('x position (meters)')\n", " ax.set_xticks(np.floor(np.linspace(0, len(self.xs) - 1, n_ticks)))\n", " ax.set_xticklabels(np.linspace(self.x_min, self.x_max, n_ticks, dtype=int), rotation=45)\n", "\n", " ax.set_ylabel('y position (meters)')\n", " ax.set_yticks(np.floor(np.linspace(1, len(self.ys), n_ticks)))\n", " ax.set_yticklabels(np.linspace(self.y_min, self.y_max, n_ticks, dtype=int))\n", "\n", " if title is None:\n", " title = 'GP field prediction: ' + column + (' (log variance)' if log else '')\n", " plt.title(title, y=1.02)\n", "\n", " # scatter points over the heatmap, coordinates must first be converted into heatmap units\n", " if points is not None:\n", " plt.scatter(\n", " (points.x_pos - self.x_min) * self.grid_size / (self.x_max - self.x_min),\n", " (points.y_pos - self.y_min) * self.grid_size / (self.y_max - self.y_min)\n", " )\n", " \n", " plt.show()\n", "\n", "\n", " def drop_field(self, field_name: str) -> None:\n", "\n", " if field_name in self.grid.columns:\n", " self.grid.drop(field_name, axis=1, inplace=True)\n", " \n", " \n", " def fields_root_mean_squared_error(self, field_1: str, field_2: str) -> float:\n", " \n", " if field_1 not in self.grid.columns or field_2 not in self.grid.columns:\n", " raise ValueError(f'fields \\'{field_1}\\' and \\'{field_2}\\' not found')\n", " \n", " return np.sqrt(metrics.mean_squared_error(self.grid[field_1], self.grid[field_2]))\n", " \n", " def fields_mean_absolute_error(self, field_1: str, field_2: str) -> float:\n", " \n", " if field_1 not in self.grid.columns or field_2 not in self.grid.columns:\n", " raise ValueError(f'fields \\'{field_1}\\' and \\'{field_2}\\' not found')\n", " \n", " return metrics.mean_absolute_error(self.grid[field_1], self.grid[field_2])\n", " \n", "\n", " def noisify_series(\n", " self,\n", " data: pd.Series, # input data to noisify\n", " noise_ratio: float, # standard devation multiple for Gaussian noise; 0.1 -> 10% of deviation is noise\n", " stat_source: str = None # source column (in self.grid) for calculating basis deviation\n", " ) -> pd.Series:\n", " \n", " stat_source = stat_source if stat_source is not None else data.name\n", " noise_sd = noise_ratio * self.grid[stat_source].std()\n", " noise = np.random.normal(0, noise_sd, data.size)\n", " return data + noise\n", " \n", "\n", " def simulate_lattice_samples(\n", " self,\n", " field_name: str,\n", " result_name: str = None,\n", " n_samples: int = 36,\n", " sample_noise_ratio: float = 0.01, # standard devation multiple for Gaussian noise; 0.1 -> 10% of deviation is noise\n", " spatial_noise_ratio: float = 0.01, # noise ratio for 'x_pos' and 'y_pos' as opposed to the simulated measurements\n", " pad_edges: bool = True,\n", " all_columns: bool = False,\n", " heatmap: bool = False\n", " ) -> pd.DataFrame:\n", "\n", " # number of rows for the lattice\n", " height = int(np.round(np.sqrt(n_samples)))\n", " remainder = n_samples - height ** 2\n", "\n", " # number of samples per row\n", " if remainder >= 0:\n", " row_counts = [height for _ in range(height)]\n", " else:\n", " row_counts = [height - 1 for _ in range(height)]\n", " remainder += height\n", " \n", " # remainder are evenly distributed among the middle rows if positive\n", " i = int((height - remainder) / 2)\n", " while remainder > 0:\n", " row_counts[i] += 1\n", " remainder -= 1\n", " i += 1\n", "\n", " # row numbers in the grid corresponding to the lattice\n", " row_size = len(self.xs)\n", " row_indices = np.linspace(0, len(self.ys) - 1, num=height).astype(int) \\\n", " if not pad_edges else \\\n", " np.linspace(0, len(self.ys) - 1, num=height * 2 + 1).astype(int)[1:-1:2]\n", "\n", " # grid indices using the row numbers and number of samples per row\n", " sample_indices = [\n", " y * row_size + x\n", " for i, y in enumerate(row_indices)\n", " for x in (\n", " np.linspace(0, row_size - 1, num=row_counts[i]).astype(int) \\\n", " if not pad_edges else \\\n", " np.linspace(0, row_size - 1, num=row_counts[i] * 2 + 1).astype(int)[1:-1:2]\n", " )\n", " ]\n", "\n", " # extract samples from the grid\n", " samples = self.grid.iloc[sample_indices].copy()\n", "\n", " # add noise by multiplying sample values by a 1-mean Gaussian with sd=noise_rato\n", " column_name = result_name if result_name is not None else f'{field_name}_sampled_{sample_noise_ratio}'\n", " \n", " samples[column_name] = self.noisify_series(\n", " samples[field_name],\n", " noise_ratio=sample_noise_ratio\n", " ).astype(np.float32)\n", "\n", " samples[['x_pos', 'y_pos']] = samples[['x_pos', 'y_pos']].apply(\n", " self.noisify_series,\n", " noise_ratio=spatial_noise_ratio\n", " ).astype(np.float32)\n", "\n", " if heatmap:\n", " self.heatmap_field(field_name, points=samples)\n", "\n", " if not all_columns:\n", " samples = samples[['x_pos', 'y_pos', column_name]]\n", "\n", " return samples.reset_index(drop=True)\n", "\n", "\n", " def simulate_lawnmower_sensors(\n", " self,\n", " field_names: List[str] = None,\n", " n_turns: int = 9,\n", " spacing: int = 5, # 1 means every point along with the path, 2 means every second, etc.\n", " sensor_noise_ratio: float = 0.01, # standard devation multiple for Gaussian noise; 0.1 -> 10% of deviation is noise\n", " spatial_noise_ratio: float = 0.01 # noise ratio for 'x_pos' and 'y_pos' as opposed to the simulated measurements\n", " ) -> pd.DataFrame:\n", " \n", " # lawnmower pattern (n_turns = 2):\n", " #\n", " # ***************\n", " # *\n", " # ***************\n", " # *\n", " # ***************\n", " #\n", " \n", " # row numbers in the grid corresponding to lawnmower rows\n", " row_size = len(self.xs)\n", " row_indices = np.linspace(0, len(self.ys) - 1, num=n_turns + 1).astype(int)\n", "\n", " # grid indices corresponding to the points along the lawnmower rows\n", " row_sample_indices = [[y * row_size + x for x in range(row_size)] for y in row_indices]\n", "\n", " # grid indices corresponding to the points along right turns, after even-numbered lawnmower rows\n", " right_turn_indices = [\n", " [(y + 1) * row_size - 1 for y in range(row_indices[i] + 1, row_indices[i + 1])]\n", " for i in range(0, n_turns, 2)\n", " ]\n", "\n", " # grid indices corresponding to the points along left turns, after odd-numbered lawnmower rows\n", " left_turn_indices = [\n", " [y * row_size for y in range(row_indices[i] + 1, row_indices[i + 1])]\n", " for i in range(1, n_turns, 2)\n", " ]\n", "\n", " # interleave rows (some reversed) and turns into a single list of indices\n", " lawnmower_indices = []\n", " for i, row in enumerate(row_sample_indices):\n", " if i % 2 == 0:\n", " lawnmower_indices += row\n", " if i < n_turns:\n", " lawnmower_indices += right_turn_indices[int(i / 2)]\n", " elif i % 2 == 1:\n", " lawnmower_indices += reversed(row)\n", " if i < n_turns:\n", " lawnmower_indices += left_turn_indices[int(i / 2)]\n", "\n", " # default to the randomly generated fields if names aren't specified\n", " field_names = field_names if field_names is not None else self.generated_fields\n", "\n", " # extract measurements from the grid\n", " measurements = self.grid.iloc[lawnmower_indices[::spacing]].copy()[['x_pos', 'y_pos', *field_names]]\n", "\n", " # add noise by multiplying sample values by a 1-mean Gaussian with sd=noise_rato\n", " measurements[field_names] = measurements[field_names].apply(\n", " self.noisify_series,\n", " noise_ratio=sensor_noise_ratio\n", " ).astype(np.float32)\n", "\n", " measurements[['x_pos', 'y_pos']] = measurements[['x_pos', 'y_pos']].apply(\n", " self.noisify_series,\n", " noise_ratio=spatial_noise_ratio\n", " ).astype(np.float32)\n", "\n", " return measurements.reset_index(drop=True)\n", " \n", " \n", " # select_points: Greedily select the optimal sampling points from a field, as measured by a fitness function\n", " #\n", " # grid: Pandas dataframe containing field predictions, as returned by `predict_field`\n", " # field_name: String column name of the field to be evaluated\n", " # fitness_function: Function of the form fitness(field, variance) that calculates fitness scores for the given field,\n", " # where minimum fitness is 0 and optimal points have the highest scores. See examples below.\n", " # distance_factor: Determines how close the selected points can get to one another. This parameter multiplies\n", " # the default factor, calculated according to the size of the field and `n_points`.\n", " # n_points: The number of points to be selected\n", " # heatmaps: Whether to print heatmaps of the fitness field after each point is selected.\n", " # Helpful when changing the `distance_factor` or `fitness_function`.\n", " #\n", " # return: A pandas dataframe with columns (`x_pos`, `y_pos`), as accepted by `xy_to_latlon` and `heatmap_field`\n", " #\n", " def select_points(\n", " self,\n", " field_name: str,\n", " fitness_function: Callable[[pd.Series, pd.Series], pd.Series],\n", " distance_factor: float = 1.0,\n", " n_points: int = 12,\n", " override_variance: str = None,\n", " all_columns: bool = False,\n", " heatmaps: bool = False\n", " ) -> pd.DataFrame:\n", "\n", " # extract relevant columns from the grid dataset\n", " variance = False\n", " columns = ['x_pos', 'y_pos', field_name]\n", "\n", " variance_name = f'{field_name}_var' if override_variance is None else override_variance\n", " if variance_name in self.grid.columns:\n", " variance = True\n", " columns.append(variance_name)\n", " data = self.grid[columns].copy()\n", "\n", " # calculate fitness of all points according to the specified function\n", " data['fitness'] = fitness_function(data[field_name], data[variance_name] if variance else None)\n", "\n", " # the 'distance factor' determines the how close the selected points can get to one another;\n", " # penalties are applied within a radius proportional to the field's diagonal divided by the number of points\n", " distance_factor *= self.grid_diagonal() / n_points\n", "\n", " # use a multiindex for quick access to coordinates\n", " data = data.set_index(['x_pos', 'y_pos'])\n", " all_points = data.index.to_frame().to_numpy()\n", "\n", " points = []\n", " for i in range(n_points):\n", " \n", " # select the next best point\n", " next_point = data.fitness.idxmax()\n", " points.append(next_point)\n", "\n", " # calculate distances and apply a fitness penalty to nearby points\n", " data['distance'] = np.sqrt(\n", " np.square(np.subtract(\n", " all_points, # vectorized for speed\n", " np.array(next_point)\n", " )).sum(axis=1) # (x - x`)^2 + (y - y`)^2\n", " )\n", " data.fitness *= 1 - np.exp(-data.distance / distance_factor)\n", "\n", " if heatmaps:\n", " self.heatmap_field('fitness', override_data=data.reset_index())\n", "\n", " samples = self.grid[self.grid[['x_pos', 'y_pos']].apply(tuple, axis=1).isin(points)]\n", " if not all_columns:\n", " samples = samples[['x_pos', 'y_pos', field_name]]\n", " \n", " return samples\n", " \n", " \n", " # fitness function for selecting maxima, transforms the field into [0,1]\n", " @staticmethod\n", " def maxima_fitness(field: pd.Series, variance: pd.Series) -> pd.Series:\n", "\n", " return (field - field.min()) / (field.max() - field.min())\n", "\n", "\n", " # fitness function for selecting minima, the opposite of maxima_fitness\n", " @staticmethod\n", " def minima_fitness(field: pd.Series, variance: pd.Series) -> pd.Series:\n", "\n", " return 1 - PredictiveSampler.maxima_fitness(field, variance)\n", "\n", "\n", " # fitness function for selecting points with the least information (highest variance)\n", " # transforms the field variance into [0,1] using a logarithmic scale\n", " @staticmethod\n", " def variance_fitness(field: pd.Series, variance: pd.Series) -> pd.Series:\n", "\n", " if variance is None:\n", " raise ValueError('field variance is required for the variance_fitness function')\n", "\n", " return PredictiveSampler.maxima_fitness(np.log(variance), None)\n", " \n", "\n", " # fitness function for selecting points with the most information, the opposite of variance_fitness\n", " @staticmethod\n", " def inverse_variance_fitness(field: pd.Series, variance: pd.Series) -> pd.Series:\n", "\n", " return 1 - PredictiveSampler.maxima_fitness(np.log(variance), None)\n", "\n", "\n", " # this example selects low-variance maxima; many such combinations are possible\n", " @staticmethod\n", " def combined_fitness(field: pd.Series, variance: pd.Series) -> pd.Series:\n", "\n", " return (\n", " PredictiveSampler.maxima_fitness(field, variance) *\n", " PredictiveSampler.inverse_variance_fitness(field, variance)\n", " )\n", " \n", " \n", " # the fitness function can be a random field, for selecting random points that are separated\n", " def random_fitness(\n", " self,\n", " field: pd.Series,\n", " variance: pd.Series\n", " ) -> pd.Series:\n", " \n", " self.generate_random_fields(name='random_fitness', len_scale=0.2, minmax=True)\n", " return self.grid['random_fitness'].copy()\n", " \n", " \n", " #################### GPyTorch ############################################################\n", " \n", " # convert a tensor of values to a tensor of z-scores, per column\n", " @staticmethod\n", " def standardize_tensor(data: torch.tensor) -> torch.tensor:\n", "\n", " means = data.mean(dim=0, keepdim=True)\n", " stds = data.std(dim=0, keepdim=True)\n", " return (data - means) / stds, means, stds\n", "\n", "\n", " # invert the standardize_tensor function using returned z-scores, means, and stds\n", " @staticmethod\n", " def inverse_standardize_tensor(\n", " data: torch.tensor,\n", " means: torch.tensor,\n", " stds: torch.tensor\n", " ) -> torch.tensor:\n", "\n", " return data * stds + means\n", "\n", "\n", " # adaptive inducing points selection, see https://arxiv.org/pdf/2107.10066.pdf\n", " @staticmethod\n", " def select_inducing_points(\n", " samples: torch.tensor,\n", " kernel: gpytorch.kernels.Kernel,\n", " threshold: float = 0.5,\n", " max_points: int = None,\n", " no_print: bool = False\n", " ) -> torch.tensor:\n", "\n", " # start with the first sample as the only inducing point\n", " inducing_points = samples[0]\n", " n_points = 1\n", "\n", " # check for each additional sample to determine the best inducing points\n", " for sample in samples[1:]:\n", " sample_tensor = sample if n_points == 1 else sample.repeat(n_points, 1)\n", "\n", " # d = max(kernel(sample, inducing_point) for inducing_point in inducing_points)\n", " # that is, the maximum output of the kernel for the sample with any inducing point\n", " d = kernel(sample_tensor, inducing_points).diag().max().item()\n", "\n", " if d < threshold:\n", " # add the current sample to the set of inducing points\n", " if n_points == 1:\n", " inducing_points = torch.stack([inducing_points, sample])\n", " else:\n", " inducing_points = torch.cat([inducing_points, sample.repeat(1, 1)], 0)\n", " n_points += 1\n", "\n", " if max_points and n_points > max_points:\n", " raise RuntimeError(f'maximum number of inducing points ({max_points}) exceeded with threshold {threshold:.3f}')\n", "\n", " if not no_print:\n", " print(f'selected {n_points} inducing points with threshold {threshold}')\n", "\n", " return inducing_points\n", "\n", "\n", " # select_inducing_points with different thresholds until the number of points falls within bounds\n", " def select_inducing_points_bounded(\n", " self,\n", " samples: torch.tensor,\n", " kernel: gpytorch.kernels.Kernel,\n", " min_points: int = 200,\n", " max_points: int = 300,\n", " no_print: bool = False\n", " ) -> torch.tensor:\n", " \n", " # use cached inducing points if they're still valid\n", " if self.cached_inducing_points is not None:\n", "\n", " # mask to select rows from `samples` that are present in the cache\n", " in_cache = torch.any(torch.all(torch.eq(samples[:, None], self.cached_inducing_points), dim=-1), dim=-1)\n", "\n", " # return the cached points if they're all in `samples` and within bounds\n", " if ((samples[in_cache].size() == self.cached_inducing_points.size())\n", " and (min_points <= len(samples[in_cache]) <= max_points)):\n", "\n", " print(f'using {len(samples[in_cache])} cached inducing points')\n", " return samples[in_cache]\n", " \n", "\n", " threshold = 0.5\n", " d_threshold = 0.1\n", " state = None # True if too few points selected, False if too many\n", " inducing_points = samples # return samples if len(samples) is in bounds\n", " i = 0\n", "\n", " # validate bounds\n", " if min_points > len(samples):\n", " raise ValueError(f'min_points ({min_points}) is greater than the number of samples ({len(samples)})')\n", " elif max_points < min_points:\n", " raise ValueError(f'max_points ({max_points}) is less than min_points ({min_points})')\n", "\n", " # iterate until a threshold is found that selects a number of inducing points within bounds\n", " while not min_points <= len(inducing_points) <= max_points:\n", " try:\n", " inducing_points = PredictiveSampler.select_inducing_points(\n", " samples,\n", " kernel,\n", " threshold=threshold,\n", " max_points=max_points,\n", " no_print=no_print\n", " )\n", "\n", " # too few points, raise the threshold\n", " if len(inducing_points) < min_points:\n", "\n", " # if there were too many points last time, raise the threshold by a smaller amount\n", " if state is True:\n", " d_threshold /= 2\n", " state = False\n", " threshold += d_threshold\n", "\n", " # too many points, lower the threshold\n", " except RuntimeError as e:\n", "\n", " if not no_print:\n", " print(e)\n", "\n", " # if there were too few points last time, lower the threshold by a smaller amount\n", " if state is False:\n", " d_threshold /= 2\n", " state = True\n", " threshold -= d_threshold\n", "\n", " if i > 30:\n", " print(f'maximum iterations reached, returning {len(inducing_points)} points')\n", " break\n", "\n", " i += 1\n", "\n", " return inducing_points\n", " \n", " \n", " class ExactGPModel(ExactGP):\n", " def __init__(self, X_train, y_train, likelihood, kernel):\n", " super(PredictiveSampler.ExactGPModel, self).__init__(X_train, y_train, likelihood)\n", " self.mean_module = ConstantMean()\n", " self.covar_module = kernel\n", "\n", " def forward(self, X):\n", " X_mean = self.mean_module(X)\n", " X_covar = self.covar_module(X)\n", " return MultivariateNormal(X_mean, X_covar)\n", " \n", " \n", " class ApproximateGPModel(ApproximateGP):\n", " def __init__(self, inducing_points, kernel):\n", " variational_distribution = CholeskyVariationalDistribution(inducing_points.size(-2))\n", " variational_strategy = VariationalStrategy(\n", " self, inducing_points, variational_distribution\n", " )\n", " super(PredictiveSampler.ApproximateGPModel, self).__init__(variational_strategy)\n", " self.mean_module = ConstantMean()\n", " self.covar_module = kernel\n", "\n", " def forward(self, X):\n", " X_mean = self.mean_module(X)\n", " X_covar = self.covar_module(X)\n", " return MultivariateNormal(X_mean, X_covar)\n", " \n", " \n", " # wrapper function for calling `predict_field` on all fields in `measurements` or specified `targets`\n", " def predict_measurements_fields(\n", " self,\n", " targets: List[str] = None,\n", " n_iterations: int = 200,\n", " n_inducing_point_bounds: Tuple[int, int] = (250, 300),\n", " heatmaps: bool = False,\n", " no_print: bool = False\n", " ) -> None:\n", " \n", " if targets is None:\n", " targets = self.measurements_fields()\n", " \n", " for target in targets:\n", "\n", " if not no_print:\n", " print(f'predicting field \\'{target}\\'')\n", " \n", " self.predict_field(\n", " self.measurements,\n", " target,\n", " ['x_pos', 'y_pos'],\n", " heatmaps=heatmaps,\n", " n_iterations=n_iterations,\n", " n_inducing_point_bounds=n_inducing_point_bounds,\n", " no_print=no_print\n", " )\n", " \n", " \n", " # predict_field: Use GPyTorch Gaussian process regression to predict a field over the grid space\n", " #\n", " # data: Pandas dataframe holding the training data (including `target` and `features`)\n", " # target: String column name of the field to be predicted\n", " # features: List of string column names to use as regression features\n", " # grid: Pandas dataframe of x/y coordinates covering the grid space, to which the predicted field will be added\n", " # is_sampling: False if predicting a sensor-measured field, True if predicting a sampled field.\n", " # If False, `features` is typically ['x_pos', 'y_pos'] for grid prediction.\n", " # If True, `features` is typically the other predicted fields ['a_pred', 'b_pred', ...]\n", " # result_name: Column name to store the prediction results in `grid`, defaults to `target`_pred\n", " #\n", " # return: `grid` input, with the new predicted fields as additional columns\n", " #\n", " def predict_field(\n", " self,\n", " source: pd.DataFrame,\n", " target: str,\n", " features: List[str],\n", " n_iterations: int = 200,\n", " n_inducing_point_bounds: Tuple[int, int] = (250, 300),\n", " is_sampling: bool = False,\n", " result_name: str = None,\n", " no_print: bool = False,\n", " heatmaps: bool = False\n", " ) -> None:\n", "\n", " # gpu acceleration for apple silicon\n", " # device = torch.device('mps')\n", " # not yet supported: https://github.com/cornellius-gp/gpytorch/issues/2209\n", " device = torch.device('cpu')\n", "\n", " # extract relevant rows and columns from the source data set\n", " row_mask = ~source[target].isnull()\n", " X_train = torch.tensor(source[row_mask][features].values, device=device)\n", " y_train = torch.tensor(source[row_mask][target].values, device=device)\n", " \n", " assert X_train.isnan().any().item() is False\n", " assert y_train.isnan().any().item() is False\n", " \n", " # standardize training data\n", " X_train, X_train_means, X_train_stds = self.standardize_tensor(X_train)\n", " y_train, y_train_means, y_train_stds = self.standardize_tensor(y_train)\n", "\n", " # define the GPyTorch model\n", " likelihood = GaussianLikelihood()\n", " kernel = ScaleKernel(MaternKernel(nu=1.5))\n", "\n", " # use an exact GP for sampling fields (relatively low numbers of samples)\n", " if is_sampling:\n", " model = self.ExactGPModel(X_train, y_train, likelihood, kernel)\n", "\n", " # use an approximate GP for sensor fields (relatively high numbers of data points)\n", " else:\n", " assert n_inducing_point_bounds[0] < n_inducing_point_bounds[1]\n", " inducing_points = self.select_inducing_points_bounded(\n", " X_train,\n", " kernel,\n", " min_points=n_inducing_point_bounds[0],\n", " max_points=n_inducing_point_bounds[1],\n", " no_print=no_print\n", " )\n", "\n", " self.cached_inducing_points = inducing_points\n", " self.last_n_inducing_points = inducing_points.size(0)\n", " model = self.ApproximateGPModel(inducing_points, kernel)\n", " \n", " # find optimal hyperparameters\n", " model.to(device)\n", " model.train()\n", " likelihood.train()\n", " \n", " # initialize torch optimizer and loss\n", " optimizer = torch.optim.Adam(model.parameters(), lr=0.025)\n", " if is_sampling:\n", " mll = ExactMarginalLogLikelihood(likelihood, model)\n", " else:\n", " mll = VariationalELBO(likelihood, model, num_data=inducing_points.size(0))\n", " \n", " # main training loop\n", " n_iterations = n_iterations\n", " for i in range(n_iterations):\n", " \n", " # if is_sampling:\n", " # X_train_sample = torch.distributions.Normal(X_train, X_train_stds).rsample()\n", "\n", " # refresh and regenerate output\n", " optimizer.zero_grad()\n", " output = model(X_train) # _sample if is_sampling else X_train)\n", "\n", " # calculate loss and backpropogate\n", " loss = -mll(output, y_train)\n", " loss.backward()\n", " if not no_print and (i == 0 or (i + 1) % (n_iterations / 10) == 0 or i + 1 == n_iterations):\n", " print(f'{i+1}/{n_iterations}: loss = {loss.item():3f}')\n", " optimizer.step()\n", "\n", " # print trained parameters\n", " if not no_print:\n", " for param, value in model.named_parameters():\n", " try:\n", " print(f'Parameter {param}: {value.item()}')\n", " except:\n", " print(f'Parameter {param}: {value.size()}')\n", "\n", " # enter evaluation/prediction mode\n", " model.eval()\n", " likelihood.eval()\n", "\n", " # make field predictions over the grid space\n", " with torch.no_grad(), gpytorch.settings.fast_pred_var():\n", " X_pred = torch.tensor(self.grid[features].values, device=device)\n", " X_pred, X_pred_means, X_pred_stds = self.standardize_tensor(X_pred)\n", " y_pred = likelihood(model(X_pred))\n", "\n", " # add field predictions (and variance) to the grid dataframe\n", " result_name = f'{target}_pred' if result_name is None else result_name\n", " y_pred_means = self.inverse_standardize_tensor(y_pred.mean, y_train_means, y_train_stds)\n", " self.grid[result_name] = pd.DataFrame(y_pred_means.numpy())\n", " self.predicted_fields.append(result_name)\n", " \n", " var_name = f'{result_name}_var'\n", " self.grid[var_name] = pd.DataFrame(y_pred.variance.numpy())\n", " self.predicted_fields_var.append(var_name)\n", "\n", " # plot heatmaps of predicted mean and variance over the grid space\n", " if heatmaps:\n", " self.heatmap_field(result_name)\n", " self.heatmap_field(var_name, log=True)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "496d2b1a-4e0a-436d-bd44-677b5eea13dd", "metadata": {}, "source": [ "### Helper functions" ] }, { "cell_type": "code", "execution_count": 5, "id": "cd8874cd-bcfd-4ecd-af96-7247702fbbcc", "metadata": {}, "outputs": [], "source": [ "# coordinate conversion between latitude/longitude and utm x/y, with memory\n", "class CoordinateConverter:\n", " \n", " zn = None # utm zone number\n", " zl = None # utm zone letter\n", " easting_midrange = None\n", " northing_midrange = None\n", "\n", " # convert latitude/longitude into x/y coordinates with utm\n", " def latlon_to_xy(\n", " self,\n", " data: pd.DataFrame,\n", " lat_column: str = 'latitude',\n", " lon_column: str = 'longitude'\n", " ) -> pd.DataFrame:\n", " \n", " easting, northing, self.zn, self.zl = utm.from_latlon(data[lat_column].to_numpy(), data[lon_column].to_numpy())\n", "\n", " # define the origin as the midrange for the first conversion\n", " if self.easting_midrange is None and self.northing_midrange is None:\n", " self.easting_midrange = (np.max(easting) + np.min(easting)) / 2\n", " self.northing_midrange = (np.max(northing) + np.min(northing)) / 2\n", " \n", " # x and y are distances from the midrange in meters, where north corresponds to positive y\n", " data['x_pos'] = easting - self.easting_midrange\n", " data['y_pos'] = northing - self.northing_midrange\n", " return data.astype(np.float32)\n", "\n", "\n", " # convert x/y coordinates back into latitude/longitude with utm\n", " def xy_to_latlon(\n", " self,\n", " data: pd.DataFrame,\n", " lat_column: str = 'latitude',\n", " lon_column: str = 'longitude'\n", " ) -> pd.DataFrame:\n", " \n", " if None in (self.zn, self.zl, self.easting_midrange, self.northing_midrange):\n", " raise ValueError('must convert lat/lon into utm first before converting back')\n", " \n", " # use the midrange from the first conversion as the origin reference point\n", " easting = data['x_pos'] + self.easting_midrange\n", " northing = data['y_pos'] + self.northing_midrange\n", " data[lat_column], data[lon_column] = utm.to_latlon(easting, northing, self.zn, self.zl)\n", " return data.astype(np.float32)" ] }, { "cell_type": "code", "execution_count": 6, "id": "62f71522-a26f-497f-8a28-e820d4405957", "metadata": { "tags": [] }, "outputs": [], "source": [ "# discard measurements that are too close (spatially) to the first and last points\n", "def discard_fringes(data: pd.DataFrame, min_dist: int = 15) -> pd.DataFrame:\n", "\n", " # index of the first point at least (min_dist) meters away from the very first point\n", " start = np.argmax(np.linalg.norm(\n", " data[['x_pos', 'y_pos']] - data[['x_pos', 'y_pos']].iloc[0], axis=1\n", " ) > min_dist)\n", "\n", " # index of the last point at least (min_dist) meters away from the very last point\n", " end = -np.argmax(np.linalg.norm(\n", " data[['x_pos', 'y_pos']].iloc[::-1] - data[['x_pos', 'y_pos']].iloc[-1], axis=1\n", " ) > min_dist) - 1\n", "\n", " # continue with a valid subset of data points\n", " return data[start:end]" ] }, { "cell_type": "code", "execution_count": 7, "id": "139574a5", "metadata": {}, "outputs": [], "source": [ "def discard_outliers(\n", " data: pd.DataFrame,\n", " limit: float = 3.0,\n", " columns: List[str] = []\n", ") -> pd.DataFrame:\n", " \n", " if not columns:\n", " columns = [c for c in data.columns if c not in ['latitude', 'longitude', 'x_pos', 'y_pos']]\n", "\n", " if not columns:\n", " print('no columns to modify')\n", " return data\n", "\n", " data[columns] = data[columns].where(\n", " np.abs((data[columns] - data[columns].mean()) / data[columns].std()) <= limit,\n", " np.NaN\n", " )\n", "\n", " return data\n", "\n", "def get_ee_dataset(\n", " dataset: str, # earthengine dataset name, like 'JAXA/GCOM-C/L3/OCEAN/SST/V3'\n", " bands: List[str], # band names to select from the dataset, like ['SST_AVE']\n", " area_of_interest: ee.Geometry.Polygon,\n", " start_date: ee.Date,\n", " end_date: ee.Date,\n", " min_count_per_pixel: int = 5, # satellite pixels with fewer data points are excluded\n", " has_offsets: bool = False, # whether the dataset has f'{band}_OFFSET' to transform data\n", " has_slopes: bool = False # whether the dataset has f'{band}_SLOPE' to transform data\n", ") -> pd.DataFrame:\n", "\n", " print(f'fetching bands {bands} from dataset {dataset}...')\n", "\n", " # initial API call\n", " collection = ee.ImageCollection(dataset)\\\n", " .select(bands)\\\n", " .filterDate(start_date, end_date)\\\n", " .filterBounds(area_of_interest)\n", "\n", " # extract constant properties the first image\n", " first = collection.first()\n", " projection = first.projection()\n", " \n", " offsets = [float(ee.Number(first.get(f'{band}_OFFSET')).getInfo()) if has_offsets else 0.0 for band in bands]\n", " slopes = [float(ee.Number(first.get(f'{band}_SLOPE')).getInfo()) if has_slopes else 1.0 for band in bands]\n", "\n", " # for results, take the mean over areas with sufficient data\n", " mask = collection.count().gte(min_count_per_pixel)\n", " image = collection.mean().clip(area_of_interest).updateMask(mask)\n", "\n", " # add lat/lon coordinates and take a sample from each pixel of data\n", " coords = image.addBands(ee.Image.pixelLonLat())\n", " arrs = coords.setDefaultProjection(projection).sample()\n", "\n", " # getInfo API call to retrieve coordinates and data\n", " lats = arrs.aggregate_array('latitude').getInfo()\n", " lons = arrs.aggregate_array('longitude').getInfo()\n", " data = [arrs.aggregate_array(band).getInfo() for band in bands]\n", "\n", " # apply transformations with slopes and offsets\n", " if has_offsets or has_slopes:\n", " data = [[point * slopes[i] + offsets[i] for point in band_data] for i, band_data in enumerate(data)]\n", "\n", " # convert to a pandas dataframe\n", " return pd.DataFrame(zip(lats, lons, *data), columns=['latitude', 'longitude', *bands])\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7c628a75", "metadata": {}, "source": [ "## Data demonstrations" ] }, { "cell_type": "code", "execution_count": 8, "id": "b073b5f5", "metadata": {}, "outputs": [], "source": [ "def demonstrate_with_data(\n", " sampler: PredictiveSampler,\n", " sensor_field_to_plot: str,\n", " sampling_field: str,\n", " n_inducing_point_bounds: Tuple[int, int] = (250, 300),\n", " n_samples: int = 24,\n", " sample_noise_ratio: float = 0.1,\n", " n_to_recommend: int = 12,\n", " fitness_function: Callable[[pd.Series, pd.Series], pd.Series] = PredictiveSampler.maxima_fitness,\n", " override_variance: bool = False\n", ") -> None:\n", "\n", " sampler.plot_measurements([sensor_field_to_plot])\n", " sampler.predict_measurements_fields(no_print=True, n_inducing_point_bounds=n_inducing_point_bounds)\n", "\n", " sampler.heatmap_field(\n", " f'{sensor_field_to_plot}_pred',\n", " title=f'Approximate GP prediction: {sensor_field_to_plot}' \n", " )\n", "\n", " samples_name = f'{sampling_field}_sampled'\n", " samples = sampler.simulate_lattice_samples(\n", " sampling_field,\n", " result_name=samples_name,\n", " n_samples=n_samples,\n", " sample_noise_ratio=sample_noise_ratio,\n", " all_columns=True\n", " )\n", " sampling_field_display_name = sampling_field[:-5] if sampling_field.endswith('_pred') else sampling_field\n", " sampler.heatmap_field(\n", " sampling_field,\n", " points=samples,\n", " title=f'Samples: {sampling_field_display_name}'\n", " )\n", "\n", " result_name = f'{samples_name}_pred'\n", " feature_fields = [field for field in sampler.predicted_fields if field != sampling_field]\n", " sampler.predict_field(\n", " samples,\n", " target=samples_name,\n", " features=['x_pos', 'y_pos'] + feature_fields,\n", " result_name=result_name,\n", " is_sampling=True,\n", " no_print=True\n", " )\n", " sampler.heatmap_field(\n", " result_name,\n", " title=f'Exact GP prediction: {sampling_field_display_name}'\n", " )\n", "\n", " recommended = sampler.select_points(\n", " result_name,\n", " fitness_function,\n", " n_points=n_to_recommend,\n", " override_variance=(f'{sensor_field_to_plot}_pred_var' if override_variance else None)\n", " )\n", " fitness_function_display_name = (\n", " fitness_function.__name__[:-8] if fitness_function.__name__.endswith('_fitness') else fitness_function.__name__\n", " )\n", " sampler.heatmap_field(\n", " result_name,\n", " points=recommended,\n", " title=f'Recommendations: {sampling_field_display_name} predicted - {fitness_function_display_name}'\n", " )\n" ] }, { "cell_type": "code", "execution_count": 9, "id": "bc160cd5", "metadata": {}, "outputs": [], "source": [ "def measurements_cross_validate(\n", " measurements: pd.DataFrame,\n", " test_fields: List[str] = None,\n", " n_samples_s: List[int] = [30],\n", " sample_noise_ratios: List[float] = [0.3]\n", ") -> pd.DataFrame:\n", " \n", " print('preliminary - predicting fields from measurements...')\n", " sampler = PredictiveSampler(measurements=measurements)\n", " sampler.predict_measurements_fields()\n", "\n", " if test_fields is None:\n", " test_fields = sampler.predicted_fields.copy()\n", "\n", " results = {\n", " 'result_name': [],\n", " 'target_field': [],\n", " 'rmse': [],\n", " 'mae': [],\n", " 'relative_rmse': [],\n", " 'relative_mae': [],\n", " 'n_feature_fields': [],\n", " 'feature_field_ids': [],\n", " 'n_samples': [],\n", " 'sample_noise_ratio': []\n", " }\n", "\n", " i = 0\n", " i_total = len(test_fields) * len(n_samples_s) * len(sample_noise_ratios) * (2 ** (len(test_fields) - 1))\n", " print(f'total number of tests will be {i_total}')\n", "\n", " for target_field in test_fields:\n", "\n", " print(f'testing field {target_field}...')\n", " target_field_mad = sampler.grid[target_field].mad()\n", " target_field_sd = sampler.grid[target_field].std()\n", " all_feature_fields = [field for field in test_fields if field != target_field]\n", "\n", " for n_samples in n_samples_s:\n", " for sample_noise_ratio in sample_noise_ratios:\n", "\n", " print(f'simulating samples with n_samples={n_samples} and sample_noise_ratio={sample_noise_ratio}...')\n", "\n", " samples_name = f'{target_field}-sampled_{n_samples}_{sample_noise_ratio}'\n", " samples = sampler.simulate_lattice_samples(\n", " field_name=target_field,\n", " result_name=samples_name,\n", " n_samples=n_samples,\n", " sample_noise_ratio=sample_noise_ratio,\n", " spatial_noise_ratio=sample_noise_ratio,\n", " all_columns=True\n", " )\n", "\n", " for k in range(len(test_fields)):\n", "\n", " print(f'predicting {target_field} with {k} feature fields...')\n", "\n", " for j, feature_subset in enumerate(combinations(all_feature_fields, k)):\n", "\n", " i += 1\n", " print(f'running prediction {i} of {i_total}')\n", "\n", " result_name = f'{target_field}_pred-from_{k}_{j}-with_{n_samples}_{sample_noise_ratio}'\n", " sampler.predict_field(\n", " samples,\n", " target_field,\n", " ['x_pos', 'y_pos'] + list(feature_subset),\n", " result_name=result_name,\n", " is_sampling=True\n", " )\n", "\n", " rmse = sampler.fields_root_mean_squared_error(target_field, result_name)\n", " mae = sampler.fields_mean_absolute_error(target_field, result_name)\n", "\n", " results['result_name'].append(result_name)\n", " results['target_field'].append(target_field[:-5] if target_field.endswith('_pred') else target_field)\n", " results['rmse'].append(rmse)\n", " results['mae'].append(mae)\n", " results['relative_rmse'].append(rmse / target_field_sd)\n", " results['relative_mae'].append(mae / target_field_mad)\n", " results['n_feature_fields'].append(len(feature_subset))\n", " results['feature_field_ids'].append(str(feature_subset))\n", " results['n_samples'].append(n_samples)\n", " results['sample_noise_ratio'].append(sample_noise_ratio)\n", "\n", " return pd.DataFrame(results)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7f5fc8b4", "metadata": {}, "source": [ "### Lake Sunapee dataset" ] }, { "cell_type": "code", "execution_count": 10, "id": "ff8def53", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['gps_msg.header.stamp.to_sec()', 'gps_msg.latitude',\n", " 'gps_msg.longitude', 'timed_compass_msg.header.stamp.to_sec()',\n", " 'timed_compass_msg.range', 'vfr_hud_msg.header.stamp.to_sec()',\n", " 'vfr_hud_msg.groundspeed', 'gps_velocity_msg.header.stamp.to_sec()',\n", " 'gps_velocity_msg.twist.linear.x', 'gps_velocity_msg.twist.linear.y',\n", " 'imu_msg.header.stamp.to_sec()', 'imu_msg.pose.pose.position.x',\n", " 'imu_msg.pose.pose.position.y', 'imu_msg.pose.pose.position.z',\n", " 'imu_msg.pose.pose.orientation.x', 'imu_msg.pose.pose.orientation.y',\n", " 'imu_msg.pose.pose.orientation.z', 'imu_msg.pose.pose.orientation.w',\n", " 'imu_msg.twist.twist.linear.x', 'imu_msg.twist.twist.linear.y',\n", " 'imu_msg.twist.twist.linear.z', 'imu_msg.twist.twist.angular.x',\n", " 'imu_msg.twist.twist.angular.y', 'imu_msg.twist.twist.angular.z',\n", " 'sonde_msg.header.stamp.to_sec()', 'yymmdd', 'hhmmss', 'battery_v',\n", " 'temperature_c', 'depth_m', 'cond_uS_cm', 'pH', 'spcond_mS_cm',\n", " 'spcond_Us_cm', 'chlorophyll_rfu', 'odo_pct_sat', 'odo_mg_l',\n", " 'turbidity_ntu', 'bga_pc_rfu', 'chlorophyll_ug_l', 'bga_pc_ug_l'],\n", " dtype='object')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ls_df = pd.read_csv('lake_sunapee_dataset.csv')\n", "ls_df.columns" ] }, { "cell_type": "code", "execution_count": 11, "id": "8c042ee0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 4202 entries, 0 to 4201\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 latitude 4202 non-null float32\n", " 1 longitude 4202 non-null float32\n", " 2 temperature_c 4202 non-null float32\n", " 3 pH 4202 non-null float32\n", " 4 odo_pct_sat 4202 non-null float32\n", " 5 cond_uS_cm 4202 non-null float32\n", "dtypes: float32(6)\n", "memory usage: 98.6 KB\n" ] } ], "source": [ "# select and rename relevant columns from the dataset\n", "ls_X = ls_df[[\n", " 'gps_msg.latitude',\n", " 'gps_msg.longitude',\n", " 'temperature_c',\n", " 'pH',\n", " 'odo_pct_sat',\n", " 'cond_uS_cm'\n", "]]\n", "\n", "ls_X = ls_X.astype(np.float32).rename(columns={\n", " 'gps_msg.latitude': 'latitude',\n", " 'gps_msg.longitude': 'longitude'\n", "})\n", "\n", "ls_X.info()" ] }, { "cell_type": "code", "execution_count": 12, "id": "5dc31b76", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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latitudelongitudetemperature_cpHodo_pct_satcond_uS_cmx_posy_pos
043.410038-72.03702515.6946.82103.1999970.07-178.468796-46.612698
143.410038-72.03702515.6946.85103.1900020.07-178.468796-46.612698
243.410038-72.03702515.6946.87103.1900020.07-178.468796-46.612698
343.410038-72.03702515.6956.85103.1900020.07-178.468796-46.612698
443.410038-72.03702515.6946.87103.1900020.07-178.468796-46.612698
\n", "
" ], "text/plain": [ " latitude longitude temperature_c pH odo_pct_sat cond_uS_cm \\\n", "0 43.410038 -72.037025 15.694 6.82 103.199997 0.07 \n", "1 43.410038 -72.037025 15.694 6.85 103.190002 0.07 \n", "2 43.410038 -72.037025 15.694 6.87 103.190002 0.07 \n", "3 43.410038 -72.037025 15.695 6.85 103.190002 0.07 \n", "4 43.410038 -72.037025 15.694 6.87 103.190002 0.07 \n", "\n", " x_pos y_pos \n", "0 -178.468796 -46.612698 \n", "1 -178.468796 -46.612698 \n", "2 -178.468796 -46.612698 \n", "3 -178.468796 -46.612698 \n", "4 -178.468796 -46.612698 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "converter = CoordinateConverter()\n", "ls_X = converter.latlon_to_xy(ls_X)\n", "ls_X.head()" ] }, { "cell_type": "code", "execution_count": 13, "id": "e9da110f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 2827 entries, 972 to 3798\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 latitude 2827 non-null float32\n", " 1 longitude 2827 non-null float32\n", " 2 temperature_c 2827 non-null float32\n", " 3 pH 2827 non-null float32\n", " 4 odo_pct_sat 2827 non-null float32\n", " 5 cond_uS_cm 2827 non-null float32\n", " 6 x_pos 2827 non-null float32\n", " 7 y_pos 2827 non-null float32\n", "dtypes: float32(8)\n", "memory usage: 88.5 KB\n" ] } ], "source": [ "ls_X = discard_fringes(ls_X)\n", "ls_X.info()" ] }, { "cell_type": "code", "execution_count": 14, "id": "bc10078c", "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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", 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", 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", 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iKMJ73/teAPJ96e/vLxzMssrfQV4be+65J772ta8BAP70pz8BkH+zY8aMsUBoyZIlmWyyTvWjttqG22plqLag/fnPf0Ycx5nyzTbbDBtssAHefPNNfPSjH8XMmTNx6aWXYsyYMfjxj3+Md7zjHfj4xz9ulJ958+bhoosuwmGHHYZPfepTeOWVV3DhhRcal4i2TTbZBGeeeSbOO+88rFq1Ch/72McwYcIEPPnkk3j55Zdx7rnnAgC22247/OxnP8Nll12Gd77znYiiKFfBufjii7F48WIcfvjhuOWWW/DBD34Q06ZNw8qVK/G///u/uP766zF27Fj09vZ27N6NGTMG3/jGN/DGG2/gXe96Fx588EHMnz8f+++/P9797ncXHv/Nb34T7373u/Ge97wHJ5xwAjbZZBOsWLECf/3rX/GLX/zCxKqccsopZuiA+fPnY8qUKfjhD3+I//3f/y08x3ve8x4ceeSRmD9/Pv71r3/hgAMOQF9fH/70pz9h/PjxOOmkkwDI+3399dfjhhtuwKabboqxY8diu+2287a5cOFC7LPPPpgzZw5OPfVUjBkzBpdeein+/Oc/40c/+lHuMAghu+aaa3Dsscfi+9//fm7c0FZbbYVPfepT+Pa3v40oirD//vvjueeew9lnn423vvWt+OxnPwtAKlinnnoq5s+fj0984hP4yEc+gn/84x8455xzMm6yz372s7jmmmswb948fOUrX8GMGTNw66234tJLL8UJJ5xQGe4mTZqEE044AX//+9+x5ZZb4rbbbsMVV1yBE044wbh0P/axj+HKK6/Epz/9aTz99NOYM2cOOOd4+OGHsfXWW+PQQw8FIN+Xe++9F7/4xS8wdepUrLPOOthqq60K+/ClL30JL7zwAvbee29svPHGeP311/HNb34Tvb292HPPPQHI8bd+9rOf4TOf+Qw+/OEP4x//+AfOO+88TJ06Fc8884zVXqv9qK22EWXDHMBd2wi0vGwykCyXI444QowfPz6TSnvjjTcKAOK///u/Tdn3v/99sdVWW4m+vj6x6aabioULF4rvfe97AoBYvHixdfw111wj3vWud4mxY8eKtddeW+y0005WxtKrr74qPvzhD4v11ltPMMZEmY9xkiTimmuuEfvss49Yf/31RU9Pj5gwYYLYeeedxdlnny1eeOEFq74vtb6sHX300WKttdYS/9//9/+J2bNni3HjxomJEyeKE044QbzxxhtWXThp1dQWL14sjj32WLHRRhuJ3t5escEGG4jdd99dzJ8/36r35JNPin322UeMHTtWTJw4URx33HHi5z//eanU+iRJxH//93+LbbfdVowZM0ZMmDBB7LbbbuIXv/iFqfPcc8+JuXPninXWWUcAMG34ssmEEOKBBx4Qe+21l1hrrbXEuHHjxK677mq1J0T6GdNDMmi75557Mv2uklqfJIn42te+JrbcckvR29sr1l9/fXHEEUeIf/zjH1Y9zrlYuHCheOtb3yrGjBkjtt9+e/GLX/xC7LnnnpnMueeff14cdthhYtKkSaK3t1dstdVW4utf/7pIkqSwP9T23HNP8fa3v13ce++9YtasWaKvr09MnTpVnHnmmZlsxlWrVokvfelLYostthBjxowRkyZNEnvttZd48MEHTZ3HHntM7LHHHmL8+PGZLLg8++Uvfyn2339/sdFGG4kxY8aIyZMni/e///3igQcesOp99atfFZtssono6+sTW2+9tbjiiivMkATUWu1HbbWNJGNCeEa9q6222lq2Y445Bj/5yU/wxhtvDHdXahtBNnv2bLz88sv485//PNxdqa222hyrY4Zqq6222mqrrbY12uqYodpqq622NixJEu+0MtoYY5lxt7plvhg/alEUdS1DrbbaRrPVbrLaaquttjZs9uzZuO+++4L7Z8yYgeeee25I+lIUoH700UcXZqnVVtuaaLUyVFtttdXWhn3nO9/xToyrzc2a7KYtWrQod383x3mqrbbRbLUyVFtttdVWW221rdFWO49rq6222mqrrbY12moYqq222mqrrbba1mirYai22mqrrbbaalujrYah2mqrrbbaaqttjbYRB0P3338/DjzwQEybNg2MMWtm82azidNOOw3bbbcd1lprLUybNg1HHXWUmUFa25IlS3DkkUdiww03xFprrYV3vOMd+MlPfjLEV1JbbbXVVltttY0GG3Ew9Oabb2KHHXbAJZdcktm3cuVKPProozj77LPx6KOP4mc/+xn+8pe/4AMf+IBV78gjj8TTTz+NW265BY8//jgOPvhgHHLIIWZG5tpqq6222mqrrTZtIzq1njGGm266Cf/xH/8RrLNo0SLsvPPOeP75582sz2uvvTYuu+wyHHnkkabepEmTcMEFF+C4447rdrdrq6222mqrrbZRZCNOGapqy5YtA2MM6623nil797vfjRtuuAGvvvoqOOe4/vrrMTAwgNmzZw9bP2urrbbaaquttpFpo3oE6v7+fpx++uk47LDDsO6665ryG264AYcccggmTZqEnp4ejB8/HjfddBM222yzYFsDAwMYGBiwyvr6+oZ09Njaaqutttpqq23obdTCULPZxKGHHgrOOS699FJr33/913/htddew69//Wusv/76uPnmm/GRj3wEDzzwALbbbjtvewsXLsS5555rlZ154G74rw/uLjfKTG5Ypk7B3EGl2wEA1qE+FdUJ9dl3nK/M7adbJ28/3eceF6pXZZ9vv68OAMYCk23m3b/CezsE4qzg2TLOc7eFSLL7aDtuWWiblvvq+Oprzz3PqeerQ9oWXHjL4Za77Vn7hPdYQe9VoE7pNriw65j9guzP1hWCHMeFU989nm6rdXJLzTopE3pdMLLN5KtbZrrPstukLtfrQtaT6zDrXJD6pvvpMbrcLdPbAKDfRbeOukxVh5TRtx20nexxbrm7DwD2+9f16KY1X/5bx9rqXX/TjrW1OtiojBlqNpv46Ec/ir/97W+4++67MWnSJLPv2Wefxeabb44///nPePvb327K3/e+92HzzTfH5Zdf7j2XTxni130Jfb2KF7sJFVXbAco/REcbDJXd1y0QKgtBrQJQpwC2yFzYoebCUQ4YtQVFAVDxw41TPw92ugVE3jZHGRBloMcHQbSMvJIyQcsEs2BInjst07dNw5C13UEYCgGS2UZqmTpknw+GyoBQ0T4O4P3dhqGlz3Ssrd7JW3SsrdXBRp0ypEHomWeewT333GOBECAzzgAgch4ojUYDPOcB4XOJreqtcHs68QBbEy0PDsqAkGtlVaVOQ1CovAh+uvW58bWrP/+0T4LbdTnZ5tzcAyESUu4cy7ls0912u8DpMbqfsOtz0oa+Du5pl3MJ6UL46wgOFjH54M/0kcmnID0OoTZVXedYpo4ROXWsNgCAq/NE8toYohSIaBtmvwKXiMkbZbUlwBiDiGCe6CxiEghytwUYWApE6j1gsBlXf0RcbtaXOJRG1Z0yxkvWp7egVD9QrR+1jS4bcTD0xhtv4K9//avZXrx4MR577DFMnDgR06ZNw4c//GE8+uij+OUvf4kkSbBkyRIAwMSJEzFmzBi87W1vw+abb47jjz8eF154ISZNmoSbb74Zd911F375y18O12UNn9Ev+3bqjFQLAU8bIFQagloBoE6qfmVNELCgpgGB1gtAVAaK6LH6EAo47raBFafMghsHoDSchIBI12kXiADn2BJABBgoCgIRvRmBOgwRBNUYMvtLApHpjwIgCHKvmb0NCkYO3HjASNaXbWoVJy23yzLbTFSGmU6Z77zdApoh48OhJtE1yEacm+zee+/FnDlzMuVHH300zjnnHMycOdN73D333GOyxZ555hmcfvrp+O1vf4s33ngDm2++OU499VQr1b6MrfreqXJlKOOFSrdV4YHZbv+76SarCjPtHFuwr2sQ1Km4oSgQs+QaT/L3l4kh8rnCfO6zsrFDdLvIbeatK/KP13WqusyAsNvMdZnRuh12mwl3HxfO/rDLTAhhb/vihULuMno7uP1K44eKXGXU3ZXZVvVadZMVxRG5brKq8UKdcpEBQ+Ame+mpjrXVO3XrjrW1OtiIg6GRZKVhqHTA8yiFIaA8EBXBUFk4KYKhqscFyjMA1Crg5dXNqw+Ug5xW1aK8X5IuNOXFEuXAUUtgFAqOrhJcnQdFnn52JZbIc3xlMPIdT4FGH09jicpCkQU86XYVIMoLpA7FDblB1OklstIw5AuedutViRfqVOB0CISAGoZGs404N1ltJU3wzrpTOuUq66bLrQhUOg1CZSGo0wDUyffV15Zxm5E+8CTsMqMuMRoXpPYz/TDNc5f54omo60wUrZNX7cKifbPa70AsETW3TXqRHtcYUxdu3GcA3Hgh6+bQfdr15nOdmf3aFWa7zRhHCkTaxSZ7Yj+xI8i4IR0/5O5XZn8chAGibB2P+4yl8DKU5lOFcuu3kEE2nCZqN1nXrIahobKyqlA3bCTFBFXtSxVVxndMGRAaKghqB4Daff+oWuGeS/AwGIWgyDzLU9hgrJGNKSoKmDbnpPsxvEAEpFDkxhIBTrsO7ORBkYYawIEinrZBgqsBOFBUEogiGOmDxhBJ8En3abPih4AUonKeu0ydwwcdbtyQrt+J53jZ4GhT39tG+/3Ia7+r5rqza+uY1TBUWzkTYuiArhVlxHdMJ0BouCCo0/AaCIy2+uAqRkVQ5Am4zlWJMsHPgXZbASK3vapARPtaRiWi97QsFLlqEqDghwBNSCXSQdQWMCEfiPS5AOggagNEBaoQtfQjICHMpwSldcP7Wqk3VJbnBqNWo8jqazUMFdlIUVTatW5llQ2V6lQ2lqegrC0Q6hQEtZNt1q4Ljf48t0DCcbtStSgIRbDLilQiCkQ+0KH9qApEXpdbARABYAosKqlEpp8loAgIqz1WKr1Dj45KlFGIaLaZPEkQiExGGjULjuirrQ75Mst8xiIBkFgha18HMsradbn5XF28hPsrz0Xm3pYhcafVbrKuWQ1Do9k6HTcE5MNNWXXIbaMb/aSWpwqVAaFW1aBOQVAeAHX6vvlcZG4fMjFCOVBUoBJ5gQgIg44+v+5THhABAdhR5zDw5UCLe51lVCLTIIqhiDbgcY1loSgFHwRiibzHmH0lgUi1kBlnqAVjkUIlpViFntFDoQC5WWR51s5ljwgMKcoUra1lq2FoTbJuqThDGZNURlXx1GkZhIYDggoAKDgtSEmzRpV21SDaryIoKqESWW6zPFUoA0SBfV4lKUf9MWxRUE8BkbwERyUy1+VAETVfTJF1YwDfoIuAAhxvgHVJlahVILLW89UhbdpVVkotCgRRd2rsoRD8+EadzrNWAqeHRRUCamWoi1bD0Ei0KnBRVXVp113WqjrUacsBn0ydUFko0Dp07DAqQe0CUF5bBo5KZ5NpKHLq+gKZqdusSBXS60CBKuTrXz7o5LrNnGsxUITQ9TvuM9dokKtXLVJlDXU+SGiTKfUUisIqUSkgAqQrrSwQdSiyWKpGGDExQa26yOz6ta3uNkQ/52sbljzTkJXJSMir47uWojZ949R00sqoQq2CEIsCrrOGH4SC9aN8Ncg5hrGGWbym22tlKToP7Q89xipvpGW0nq7jnM96H+gx9LoZOVeonrtu+ua4q9zPBK2nR7b21TXxREyCEb0ORq+PkSVwn/W56Pl6GulxpB0WRXZ5o5G2rY9R9VkUZeub/upzVYSRCOp4dQucV3NrmFDr6pVuF5wyYtnvDg1PZW24RrQeEcZ555YKdv/99+PAAw/EtGnTwBjDzTffbO0XQuCcc87BtGnTMG7cOMyePRtPPPGE2f/qq6/ipJNOwlZbbYXx48dj+vTpOPnkk7Fs2bLCc//zn//EEUccgUmTJmH8+PHYcccd8cgjj5Q+d1mrYWh1sG5Jp0ORxunreyeux30Ae/bJCiVAKHN8RQjytZtzTGkAascCcJQBozwoAtJ74daz6pQEInqcD4hom4H2c4GIReG67r3wQZHvHhSBUU9PPhhpkNEw09PwQo4FOHkA5QOiiIExRo7R6/Csp6+dtm6GDZYxn/A1qlxkAITgHVuq2JtvvokddtgBl1xyiXf/BRdcgIsuugiXXHIJFi1ahA033BD77LMPVqxYAQB48cUX8eKLL+LCCy/E448/jquuugp33HEHjjvuuNzzvvbaa9hjjz3Q29uL22+/HU8++SS+8Y1vYL311it97rJWj0CdY6u+d2q5h07ZB1PV1PSqD7xWvm3auT7f9bh1Q+DhK88rC/7Kz9/OVYVC/XH3mTodzA6r6g7Le59afcqEvhAdCLZijNzRnq2yxF+Hbqsya9Rqwe267nrePt/5dJaZez1ufassp757DDzZWe4PB+scBW0niV0vHa4Z1mjUQq3zdL8uM/WsMjJSNR2l2jNCteACiHUZyCsyrzwG3Ok5fFNz5E3LoUehpiNV+0agrjL6NN0HEM8ndH1dntZpd8Rpt+68f/0I3bSBZ3/fsbb6Ntu1peMYY7jpppvwH//xHwCkMjNt2jSccsopOO200wAAAwMDmDJlCr72ta/h+OOP97Zz44034ogjjsCbb76Jnh5/xM7pp5+O3/3ud3jggQe8+1s9t89qZWh1slYUlXZcZmXcZaEHiq/NVpWoIhDKq0vLtHUChIpcYr7iUH997Vh+ixaNtuHeD49aZPU9pBK5dQLHZFxyPlXId57QOj0fVWHccnrdVplTP+PushetFnldaWXcaVQxajSQcYVRd5jjIpP1bJWoZYWIWkl1qIyrTJan650wX8B0KJPMBaHCtq02R6YqJDvQOTfZwMAAli9fbi0DAwOVu7R48WIsWbIEc+fONWV9fX3Yc8898eCDDwaPW7ZsGdZdd90gCAHALbfcglmzZuEjH/kIJk+ejJ122glXXHFF2+f2WQ1DI9lagYORAERVrVW3WFkQcB+Gvn2hNrvsEjO7fFOD5EFQyHwP8rzF17YPeGgfQy4xFiHjNisCojwICvSjNBDJk2TLi1xnLhT57msVOGr0pHVNHJAbi0TcZxR+VH0DOxZgtQlEAILuMvKRyMQQddCGahzXIhdZ8Lgu9KUtE7xjy8KFCzFhwgRrWbhwYeUuLVmyBAAwZcoUq3zKlClmn2uvvPIKzjvvvELl5m9/+xsuu+wybLHFFvjVr36FT3/60zj55JNxzTXXtHzukNXZZENprYzi3EpWloaLKt9cwQwYTx13vwYifW1uPXoNNPutGxlnIfdYkSJklQfgp+CcQWvXJVYVuvKOca0RBWA0St9HUofRcj2wIm2Dp4ebbb2f7otkO/Zoyfo4dY7I0x7dl9e+a5xLsDBzd5Hr0G02yGfUPY6aO/I1rQtza+yyRoO025BuqIbaHzEADeLH4fJvqaHOxZlUYnQbXI3dw/So1KSO2pZuM11GjuECiBN533siMO0yi7mdXdbDgBjZVHvy50tHpIYac6iKUtLOGERVp+Uwx3kzy1Jr1T0GyNs9muyMM87A5z73Oausr6+v5faY82wTQmTKAGD58uWYN28ettlmG3z5y1/ObZNzjlmzZmHBggUAgJ122glPPPEELrvsMhx11FGVz51nHX4S1TaiTP8KqGpFSlFZlYhz/3pe0LQvrqMbNhQgVEUJCrXnddl5VB16vqo/38u4ywKKkdd9Zm2T/QEg9QZV+46x3GCe8+WoUKWVH/d+eF1mzL9odxddLHdYqhCxRkOqSD2NtNzKHutJz+WqRa5SVEUlAsopRAC87rKCjxh1leUZ82SVtWt5s9Rn6raZWj9sIMSTji19fX1Yd911raUVGNpwww0BIKPELF26NKPYrFixAvvttx/WXntt3HTTTejt7c1te+rUqdhmm22ssq233hp///vfK5+7yGoY6oRVcWe14lZqN6urFSgqSr9spU+txAl1IqMt5EqhZUAWhIpcYS0qM22DkO9coTinsktee3lQRK8n6BoLABEBkUoxRLQeLaPw4nPlVXWH0WsqAiQDPI18SLKyyxQYUZeZC0W0zRDwNBrkHPlAFHKZUTeZvA857jJapmKFfObGDem4Il96fTtWpBKVHT5pJM1OH7QOusk6ZTNnzsSGG26Iu+66y5QNDg7ivvvuw+67727Kli9fjrlz52LMmDG45ZZbMHbs2MK299hjDzz99NNW2V/+8hfMmDGj0rnLWO0mGy3WCZdSq+6zKm4z1xUYOr7Tg0WWBYfQMT4g8FmZ96DTgRV55w5BUOW2nWPo1BsAsoMcRlaZGWlaqOP0oVwf20jbjEgbeh1IB2b07JNurYJ+FG3rY6zjme64fX9zP/cF99LnevS5oXUfOaRbTXAy0COASN834j6LIrWzAcstpssiBsQJ0oEYyQCNPJKuKXly2Y6eABYwc5iZme65kADkTugawbjMtOnpOUSXZ4toZ4yhIhdZmXJg9LvHWrE33ngDf/3rX8324sWL8dhjj2HixImYPn06TjnlFCxYsABbbLEFtthiCyxYsADjx4/HYYcdBkAqQnPnzsXKlStx7bXXmoBtANhggw3QUK7ovffeGwcddBBOPPFEAMBnP/tZ7L777liwYAE++tGP4g9/+AO++93v4rvf/S4AgDFWeO6yVsNQkXUjrqXVGeA71ZeqUBSKFQr1Kw+IfPFDuiy0XdG8yotPFdLWKRAq0deWVaFSqlELqf/U6NONTr2h2xDkc8DJe0Pgw0zQakEJbCCibdBr49wGIlMPnrYqApHTT/e81uc1FBOk65b6GyTnAbKA5PubykCR/lvgMHRpxT7xLPTwCIhC+yT46CgfCVxkhGoDRgp8NAgpGGMROQ7kttLZXVj+XGWdtFb1pXZdZMNqnVDKW7A//vGPmDNnjtnWsUZHH300rrrqKnzxi1/EqlWr8JnPfAavvfYadtllF9x5551YZ511AACPPPIIHn74YQDA5ptvbrW9ePFibLLJJgCAZ599Fi+//LLZ9653vQs33XQTzjjjDHzlK1/BzJkzcfHFF+Pwww83dYrOXdbqcYZybNX3TpUrZb78qkJKO2kUnYazqsAROn/mgc3C+0Ouq7xYELeM1iXrVgxK0XkAGyJaUZhCx7lVOukey8BSSaAraxllwzPWEJCN8XLHEaLldDwibzkHOK82BlFOHzLbob6Htl3rhIvb1xfOVaB09p4IPU6QHmNI76fH+MYbSpLsvjhxtrmpIxJV15Src9Oxh2IBOt6QiInXJVHjBnFYYw7xxB5vKDTWUN44Q6Exhty0ehoz5I4tJMtVPU+QdNnA6SJV6MAlXR5n6M93FVcqaX3b7tOxtlYHq5WhTllV1aZVdUifC+gcFNl6d7nz+85dRSGi585Th/LO16JyZFkeCHXQJdbW3GKdAKGynxWTKUbfR24rRT6lxVFjMgqRbtMoRMiWq36a2e71Pq0UhdaruMjcvtPrDn2mtbXy90oz2DJtq1d9HVZddR8jpRJxmLnMLJVIu81cFUgw3bDZl86pFgFI1LaswzgrVoci2z3mvrVANjtsKGatB2wQ8lkVF1nVOkNqw6QMrQlWw9BotjLp8FWtLBiFgMwtDwFRWXjsZCp+RiVqA4QqQFguCBWdpwoItQNBvvouGPmgqCwQUYihT1Af3AABd1nOehEQucfRawpddyv3z2eWu8wDR4RvMp9xjhSITN0SQMQFqSf3yXgh1RcRcpex/NghB4pcVxmLkIkbYpFM/R8JLogiF1keaqyJsUJrktUwNJzWjjrkWqfVIqBcbFEeFIWAyK3TSqxQRoVqQyWqAkIVz9HJ2eYzVhHmWMm+CxcQKECYfSQguhUgioCi+KF0H/wxQ9Z6ARCB1HWvSe/LuXcdtUC8kCzz7OdOLFEJIJLjD0VpPS6VIDu2SM10b45Ng6nz1CG7r2qd6ZGIwnFDEorygYQxURgkTbPHWh1viFqoP1U1GJ/61GkT3Y5QX4OthqFOWivKRSeBSPeBWicDroEwDPiuPQREPheYD2bKuMrKWBWACZ2jU4Hc7VjZOCfnGspCkK++yHUzVQQi3TfzsK/oLgv5Z8oAkad9c02+e9hJCzUdgiKfSqSuyXKbhYAoAVhkQ48FR0oJyrjLIiHvOZQq5FGHoG8tyLrn9sptAZFkv9uYOm23zBcv5FpV0BkxqtBQRKavoVbDUBlr1z1TZJ0GImqdhqM8tcj75V4CiNw2XDhyQakTKpA7j5bbb7d+1dOUAaGi87XyXpFjvBBUpk3ymdFteKHIBSIg6w6jQARkVR0g4yKzAMbd9q1XBSLdD/d+5MVjtPN3Q5t1Y5X0ea2+I3s9ul4ZIFIuslCGmdddplWhHHVIwo+TXZYBIjtGiDF43WMRE1agc+EtLKEAhd49X+C0tlDg9EhUhWrrrtUw1GlrFZzcKS26Zb4v/Jb6WwBFVYCoSvB0kQLVSRsJapBpuIQqlAdCVe6PBxAYi2z3mQtEQNbtVaTOeN1lqKYOueDkmi+IWpeDnMu97rz2qlgmUNspN/1h2XqtAFGSWCqQjB+yg6UlAKlyRpSjPHWIvPpcZTRWyI0byguipupRxERpt1c78UejVhUC8j/rtbVlNQyVtSoP3HYezjS4cshmMSz5B+a7pmxgQLZN3y99QF5fLhDBXufkWKHlfrQELVZf3Wsr0V7b0FNFFSoCoRAEuedo5T7RbpCxc6z5xACiEjnHkYe6ARtv/BDIwx/pfn1cpr4LW9n+yvM7CmM77rGW/qbdz77ul3ptRABiu0/mPPSzz9NRpjmHFVjtAhFjUgniDEAC1tNQMJKQDuhyDsQA64FMqe9pyLnLlKrEeiJZrlWiSMYPQQ/eaN1eDUzZuKGQy0x3FyWyzkKxRL5yMwpBm6pQEQgNuSJUu8m6Zl34OV0bgM4QvBDZzJPhNM7TJWR64BH3ON+2GUCEO+Wkvq+tgnvrDTKkDzI3Fb0kCDHWMMuwm6efQRBikSeuqI2pOei5DNjqbY/7kaxb964I1tz9UeD6WrEoKteGrufra94S6rcHYM166PpYlN0XRUohYmbdmsJD/5BS5cyto9cB88qcbfrKMnXsy7FvjfCvd5gbfCpSO9lita3ZVsPQaDANRaMJjFwocusWAZFvvehXkSgGpVas4wBU9BAO7feNMO2rmwd3PuDxncet1woQuX0p6leOZeYuc9dD4FQEuhR2fIvViQDseDvsh0hvHzPHMn8dCjnWqVi4fT0vGZBdByQk6f6S8uyrs04O8YFR6BZROOqktfNXP2pUIQCdnKi1NttqGKpiVR+03fDvUjByl+GyIihy67rrLhC5x+VBkIakonvd4nvRcRUo+ACsUJ6nCuW510KqT66qQY6j+4uAKG+9jHXC9dmpdvMAqKzCVGSVoTZVh6w6PnUISNUhtW6rSelCwYoxWw2iM9gHFSLPJKwdTZbtQCo9UD5we8SZGfK7A0ttltUw1G0byoC3PFBqZalqIbXIpxL5+u7u90GOIOfo9B+088AZEe4wbTmqUCkQolakboSgyG077/whdQie+9oq+JS1dmClLAS1co6QCuo7F13PU4eo+8v0swV1KKQQIQeE3D4FZqcPlbdiVeKFfHe4k6rQCNLta2vBahiqaq3ATYk4lxFp7YCSF3g8X/6heKIQBA2RdUUR6qQq5IJI6DgXYvJcRb52KgRv5/abnquqdTpTsCx85YGQa2U/7yLw+W7VXHWIlhepQ0COeyzygpDrKqOmmyqKIyqyoq+X0O6yas+oVYUA+wdnu0ttltXZZENp3UoBHw5zv7FCI0wD9jX7ptcwmWQq7d5Kxeewssg6bd1+PzriQqkwZpEPXooCk0PlvjR0OvM8MSv13toRta/gdfqLu9v9CamgLgi522Xi6Ki5WZohiyJAjzekB1lMSLlgMAMxJkCaQs/knGU6zT6yxxwCyNtLyqhVffutiVg75BIrY6NGFardW12zGoZasXagxgcIq4PljZPkXnMZIKL7zDl45ss4TbnXGy1aKOOJWjfesxCoVFGFyoJQ1f67D1uTyh4Yedp3zFCb72ExVP0pC0G+MheEqhorGHtIW6TAh0Uwo1EzNRCjGTwzSeuZY/RAi3TQxXSddANy9ITOTNAanOOWTsnh21/RRdaODal7rFZ0umar2RN5CK3dD+XqKlXmudJCAdJFmWRlXWShYOp2f011KkjWtTKKjQs1eXE6oWM89RiLchfruFav3adoFbmTAmXWcAm+4PqQu7XMuUJWJtDUDUilf9eCfB7zyji3/2bcfbTfrXxn6AEd3RghIH1vvXFCbvyRJ24IKIwdSo+hKffZ/aHg6CpB03lTcAB+F1neHR0RGWS1DYnVylA71gm3F/1yWx3VIlcpcl1gvm/FMtN2FJ46ATO/bMvHtWRUoW69J0UBzEA591jomAAIlZ2nLOP20opPSB3yHRNI3/WOA8WTLHjkAU4eVOVBdStWdFwR5Of1y5c4kNdmu2YpP47bDMi6yiCzygRRh2CtI0sTZNLWTpnPZUbLqsYBhe6oNRDjSHKPmU6shj+gR4jVMDSSzP2gd+pB3M0/oKI++txnPiDyuctcEOLcdovxEudvx4YShPLOVdY9FlCRrGOKzks+K9a8ZJ22UJtuliDn1VUh2lbofKVjbXLa9LVdFA8E+AGobLvu8T6LSrrK6LrPVWb2E7eYjhsC/LFDxCyXWWD06SpWViEq4yLrhA1H9lg9a333bFRKEStWrMApp5yCGTNmYNy4cdh9992xaNEiq85TTz2FD3zgA5gwYQLWWWcd7Lrrrvj73//e+c50EzRGQ9ZA2XO5X+BFMRVu3bIPz1aMacjIGR25E5aXzeX0pbR7rBUQCg0qSPfRbufFJhVZqTGifEqR83kqWg/G4GThqvTfROhvibrGkjjdl8R2WaxekyR1gyVJWj8mx/rGgfH9XYWUpCJz5j5joc93wC1mrQPWk6Od4aSqmgsg9A6UdZFZx3j2A7V7bE20UakMfeITn8Cf//xn/OAHP8C0adNw7bXX4n3vex+efPJJbLTRRnj22Wfx7ne/G8cddxzOPfdcTJgwAU899RTGjh3bnQ65AcJrsuWpW65KFFKI9HE+dSjvvI3Aw51F5NUPPJWmieiUhc5TBYTKQFCV9HfhfJbV++HNFnMyy4IKEonlEiJJH/QahCjIEAgwv4LdWDB3nfQz1zWV178yFlJqdMxPXj8yfSl4clcBNvc8eea6x+iM9jSrTChFKFL7k9RFJlWgcBC1LK8anlUlLsiumzfvGM+p0w4I+d69Lv/sVCcZkrOskcaEGElzPBTbqlWrsM466+DnP/855s2bZ8p33HFHHHDAAZg/fz4OPfRQ9Pb24gc/+EF75/reqa0dWEORbd6HMcvudx/eepwUqlZosGn0pOsadBo9Fvww1gB6erIwRM/jqkI+labTVgQnbh9RoAhVAaEy1xRwKYkMtCRpfc7lfhdyfCDktuHUS8+XlAehshAUephUiQty4324c02+OqE2OmGk7wZMzH0TRH3S6wIQHCJO5LpWqxK5LeKErHMgTiASTrbVKwdELNSiBK0Y4DEAwcBjBp4w9TYzCM6sV50+n9kW8K5zwSAAK+2eg4CPQNBF1klVKA+EDl5yXfh96oCtuud/OtbWuDmf6Fhbq4ONuqd2HMdIkiSj8owbNw6//e1vwTnHrbfeii233BL77rsvJk+ejF122QU333xz9ZO16n6p6d22TtwPt41WYz48+yqBEHUx5S159V1rB4S81+MBoZCLzmfd9nVUBSFtPijKAyGfu8nnjnLr0CWObXeXdnklSbovoUtiL7qOW0+dVyQJRJKE+5WX0ebss0DINc/nLjgAo7sOmKk50vY65zYK/RzXIBQyC2wq/qTvJAjVtnrYqIOhddZZB7vtthvOO+88vPjii0iSBNdeey0efvhhvPTSS1i6dCneeOMNfPWrX8V+++2HO++8EwcddBAOPvhg3HfffcF2BwYGsHz5cmsZaMbtAdFogqKiuKNOX4/vG7BdNwaxUiNIhx76VWJsQlamft4Iz772aN8CAyoWTs1BzxWaqT7P3PfCVYWAfFUoBEK0SVcRylOHKOC4wOMDoBDwuGUUfGisTwiAmk0vIGnYEc0mRJxkFuMSdPdxYS1FgORzVaXvtf7ssHKf4Ux80NDGy7gDLlJVqIyVUYVK9aNknNCQfsuX/Z4eyu/y1cRGHQwBwA9+8AMIIbDRRhuhr68P3/rWt3DYYYeh0WiAqzf5gx/8ID772c9ixx13xOmnn44DDjgAl19+ebDNhQsXYsKECdby9dsXBeuXtuH+8HX6D6Mbf1CttON+qfvGTqHmush0sasKdWqMnTzzqTRFcULWvgoxRS5sheDHN39ZK9bmj4dc11hI6SmCoLzPPQWeUJBzBn7irPqTxBJ4KPg0m7KuBqUyiy8wW8OSA0gWLNH76Lu3IaNjCtFtd79V5msnfIo8c2OFCkOpcuKFWoGXPFXItWGLE7I64YHiVpfaLBuVAdSbbbYZ7rvvPrz55ptYvnw5pk6dikMOOQQzZ87E+uuvj56eHmyzzTbWMVtvvTV++9vfBts844wz8LnPfc4q4z/8L7mig3vbNfdLqZ0H7Ughe87bB4ai49tpn3mAJnIhIQBCvrY6ba1OgFrWleaeo0WzgqNdZSdUXlYVCoFQJr7I2fat637QbauPOeDgXovVpmdARMEliFjQ5nFVlflbNQHrZF0HOZt2Asfk9d97LjKuUG6fyHhCykIB02VMg09omo2y02+49Xzd0VffKVWodo+t/jYqYUjbWmuthbXWWguvvfYafvWrX+GCCy7AmDFj8K53vQtPP/20Vfcvf/kLZsyYEWyrr68PfX19VtmqXnJ7OgVE1EYK0AyH+abtyLu/blZY6LgioLG64AER97iuBVHnKzFVMse6AkK+QOTA51W4UETqtwVCrjLkc5Pluc9k5/z9D4GDD36s8gAAhc5b9m+cZlrqY8x4Qfr9JW3RzMtMW8P/vWKzc3vw47PQFRYNvtiqKlSlD121NfmZ0WUblTD0q1/9CkIIbLXVVvjrX/+KL3zhC9hqq63w8Y9/HADwhS98AYcccgje+973Ys6cObjjjjvwi1/8Avfee297J+4GENXmt7JqkJtlBgU5LtBoF5mCKW/QtNte8Jw5gBEYdTn3GAfEcuFmiBUhIF8Vys0gM/VbBCEKZCFActdLwIwxn2IUqG8AyPSJZGnp4znZ556LlgO24sMieW9cl1XmwUffW2efft+t6ys5JhEdZJH2r8r4fm0+o6tMuaGtFReZ99xtZI8NuY0A0F1dbVTC0LJly3DGGWfghRdewMSJE/GhD30I559/Pnp7ewEABx10EC6//HIsXLgQJ598Mrbaaiv89Kc/xbvf/e72T14DUXXLpHd70up92z71yOwj7q9QvJDPReY7V9GgglWgopUpNOi5g32rkGVWtR+ADXEEQrzp9O4Xcp57LGd/IQj51KBc11kBAOWpRT74oecBkElT1/t1gLOuA0BYKpTncWrN86XhiaX1KRglSfZvhk6NQa+xHasKQC2YTyXKxg2FU+pdq+IiC6lC9rEjGISAWhnqoo26cYaG0lb9z+fyK9RQ1Fq8T9EYQ272i+si0690DCEy7hBr9KZ1Gj1+VagMCBUBRdWR5dz23XsABTh5mWNDCEIAssqPruOqQkkzC0J6f9JsHYR8ClAeBBUBUI5SlHF/AcUAROHHpwiF4mtcZYhOokpT3SkUMUc5ygA0gSlz/sB90uMI6X6TsYbo+EN6nCHE3BprSMRCjTdExhlSybc8BkQixxkS1nhD6lUwJOrVlCvwSXjx+EIUdgyzghVmkbnlQGdVIc4YPvzSDwN7O2Orbv9Wx9oat//JHWtrdbBRqQyNGFvTVaJugBCtF2rfVYXI8cb95apCrnvMd17f+D20PNSXVs25vlKZYxgaEKo8wGI7IKQzp0JusaDbTGTr620gF5IyGViOslMEQEb5cVWhIkVImzUzPJeKDIsgwAGuoSgtB3jYfWbKS/yubVNZKAqe9omGRXVMeYWf5SEXWRlVKGTtgtCQWK0Mdc1qGGrX9F/2SIWi4epfnmuM7ncf7PQXsNl2VCFa7lu31KRsOn3wWADe7K5Omm/wO9ddlpNCPyJBSA8iWAWEKACF1KBQELUVn+NAUBkAstr0jSJdEoCswGlHFSoCIX3rtUssigAk0lXmgyKugAhI/0a4AiROyqmFHpxu33x9zus/L9jvpr8L+zU9rT2WkL+r4fGFaBfKzlofUoVGvHtMWx0z1DWrYahTFvqQtvNA7eQHv0xbZfsaUmzKKkH0XK7k3+L0G8Y1Zk3J0TDHZVxjedBRdJ1tmHf2eF+wN+1PJ11jZQFI1y0TKE0hKImz++M47BILQVER/ORAUW66u1c1ElbdIPTk1bOezDl/a9Z7xiDn+lLuMPP+6r8BlcYeMRlX5MYU+eKJXGtHSShUgfQ4RzBLus8ZONFJqzevykUmT5d1kaVdSV1krapC3QChIVOEauu61TDUbRtNJN+O26+bIOSqPi4UUTXIHOdRhLxtekCoSL3plGXUs/A9ahuEysQF6X3O5KmFIMSb/v0KdIIusTx3mAtCPggifS4NQAH3ViUAMm37AqfzAcIES2t1iEcQPVAqkIIcowKlqpAAB4OCJkGUoiiS1+Wm5JP311y7z9z++rYrjCvkhSKego9sUgNRcfdCFlKFyrjHRjUI1W6yrlkNQ7VVMx/0VHWJ0bIyIBR61QHTWvUxYBQImC4CobwYnk6ZFxodsCkCoSrmgyCgs2qQAR07iDrXJRbHmfYqQZAGINr/ongffQ9CQc9FAORtw4GFvIdVFBmlB1yARUzCTgypAhngIbATAiJAndcBorw+5PWt4CErhDD3QF4z0sVX34Uix4sYcpGVCZw2XfaoQsH+l3CjjXgQAkbXj+tRZl34tl99rNWRVldbqwpCLtzQMqPssNZAKCIg5M5M3yYIMRaF3VntLta9irIgVMbKHMOTsBpEQceK/Wmq+bTicmqQmZqiaYNQHEMkTQjVnlGJ9EJByC13priwpr7Q017ojCe6P1b76dQXcWJtW/OD0XrNJjAYy/q07mAMMRgDzZiUxxCDMstK6GOshfsXLuR+ztWrcjHFBOQoeLlw5oKZA7byPQ58X1lDCaSqlghCk6j20FVQJDgQiheS68UusiKjGWR62113VaGy7jHXRhwIDaPdf//9OPDAAzFt2jQwxjITnwshcM4552DatGkYN24cZs+ejSeeeMLsf/XVV3HSSSdhq622wvjx4zF9+nScfPLJWLZsWe55zznnHDDGrGXDDTe06hxzzDGZOrvuumvla6yVoQIT+hfcmmJVXGVFIGTKHeCgapDe9gU101crFkhue0EnSssy+03f8kEo9xrbNS9kVZySgxpP7OPdQR99LjG9XSY4eijUoDgurwRRFciKF3LAAbDhwVyjJzjarZspF875hPUqfLChTX93JELO/G6UITXIYhSpMq0GoYJCpPZHJJiajmQtO5f9zLig4xsSAEjvd2VXmT9eSJ6qnIvMVYUy+yuoQqZeBffYiAWhYXKTvfnmm9hhhx3w8Y9/HB/60Icy+y+44AJcdNFFuOqqq7Dlllti/vz52GefffD0009jnXXWwYsvvogXX3wRF154IbbZZhs8//zz+PSnP40XX3wRP/nJT3LP/fa3vx2//vWvzXajkf0BuN9+++HKK68022PGjKl8jTUMlbDRAkRayepKX92HcRkQKuMW02V5IOTGB1HQsfY1jNriBaEywcmh63OtEy60UAp/qE+h8/pGve62S0zXIROKFsYGJR4Y4jwd46YKBNF6gF890ffBBRmfq6wMAHGRgo8DRPatJ98Xen/EIKBASIORrADBmXw0FwGRTwXU8UMUiIAsYZR8iAbVImg4grk/bvB0UbxQFReZaxxZV1dVVSh4XYU1VJvDDUJAR91kAwMDGBgYsMp801IBwP7774/999/f3yUhcPHFF+Oss87CwQcfDAC4+uqrMWXKFFx33XU4/vjjse222+KnP/2pOWazzTbD+eefjyOOOAJxHKOnJ4wiPT09GTXItb6+vsI6Rdbhn72rr2Vmhx7GPhTNXF04s3Wnrcwgij63mN7vC4imZQ3bDWYyxyy3WMMGHwpYuj9lQMjnztLH0KVVC80c77SZ6VNZo0+kEi6xUiDkc4kR15blEnMX74zvjkuslDuMuMKoGyxJgGZsucAs91ds19ODCoo4ybrAYi5dYINx6jaLOUQzkUvCjdtL5Czgwi7T7jAujMuMxuBY8OVzmWkLAZ/ep99z11xFy23P3cftvnmNIyifGDDSPCo64yIzXStQhbxlAVWobJxQGRAabUEVCxcuxIQJE6xl4cKFldtZvHgxlixZgrlz55qyvr4+7LnnnnjwwQeDxy1btgzrrrtuLggBwDPPPINp06Zh5syZOPTQQ/G3v/0tU+fee+/F5MmTseWWW+KTn/wkli5dWvk6amWoonVVffGcpxtttt13ywVWAEJWueMW03VDypAHhDJqUGiEadqnKiDkWsvZdS3E/4T6UNaKXGJA62pQaMwgX7nPRUYUJEv5SbIuskIlKBRD43OB0diYIgWIxtMIYW+7SpClgPj/Vi11KEoflvovRkQA4/r9iiD0Pur+0u9rkTpEP0dUIXLhyL0ntE4AfrzB0+ZYueh4IZ+LLJRFptPoTVM5gdNVVKFMeZtxQiMKhDroJjvjjDPwuc99zirzqUJFtmTJEgDAlClTrPIpU6bg+eef9x7zyiuv4LzzzsPxxx+f2/Yuu+yCa665BltuuSX+9a9/Yf78+dh9993xxBNPYNKkSQCkavWRj3wEM2bMwOLFi3H22Wdjr732wiOPPFLpemoYatHoF2C7cDHUilNlt1/oAd1JEHLLAiBkTbURRX4Q8sURefrWERBqdTLUUIB2mX5Ry8R/EBAygbU27GT25U2lYZQk4uKiLjGf6ysYL+SJCyIusrYgyANFpVxgPgAyx1Mgcv5OMyqLfr/oWyMM0DDoeCGk0AMNREI1oICIQJRxl+mPGYkv8maXmXX3cxFSeDzxQvS9cCGooosslEXGLfeYDUUhy1OFuPPqc4+1Eic0okAI6CgMhVxirRpz7pUQIlMGAMuXL8e8efOwzTbb4Mtf/nJum9Q1t91222G33XbDZptthquvvtqA3CGHHGLqbLvttpg1axZmzJiBW2+91bjtylgNQx2w4XaftWItx0H5Hs5lQKhKfFAge8wLOmUyxzx9GzYQyoGgUhaKGeiUGtTumEFeOEqyECSECajuJASF0uBzY4B8AGQe3jYQpW9DjvsIeaoQA2T0UPpoZiI9OGpYwJNRh0IfFVcdCtXxbbvw2IZRF5lvoEW7PIWiIlWIdkuA5UIPNc+8sOo4p5732BEGQgBKUeMQm47VWbJkCaZOnWrKly5dmlGLVqxYgf322w9rr702brrpJjO5ellba621sN122+GZZ54J1pk6dSpmzJiRW8dnbWjytY12awvi3EkjhwKE3BT6spljZQKTq1rV2elDsUbtZqtpcABRg8rEBjkxPiJp2iDk218UFxQPZsubTX+afHOwfEwQifOx9vn2x9ybBk9T390YIBPbM8jJ5KPutr2AI1hu9jmKik9hsYKyQcrJdvb9dsty6nv22wNHcm8dHyxmxhfS18phuch8gdNc2O4yF5DKGJ2MFci6x1xAKhsn1AoICU87a6rNnDkTG264Ie666y5TNjg4iPvuuw+77767KVu+fDnmzp2LMWPG4JZbbsHYsWMrn2tgYABPPfWUBV2uvfLKK/jHP/6RW8dntTJUW75ZYFHw4B5KRYhAjrVfG3WPlb2+blgeeHnOXRrUiFzeFTXIlyXmqj5uqrwvLsioR7aLTMS6Hx1UgnwqEFV9Mg92jwJkbZN1c9/z3xahlCBAq0BSB2KpY0ypQo5CpM+h336tDqEBwR1XmTwRjKvM/Rxpd5klp3g67rrI1D1s1UVWNnBa72tFFQLst2C4QGjYrINusir2xhtv4K9//avZXrx4MR577DFMnDgR06dPxymnnIIFCxZgiy22wBZbbIEFCxZg/PjxOOywwwBIRWju3LlYuXIlrr32WixfvhzLly8HAGywwQYmXX7vvffGQQcdhBNPPBEAcOqpp+LAAw/E9OnTsXTpUsyfPx/Lly/H0Ucfbfp1zjnn4EMf+hCmTp2K5557DmeeeSbWX399HHTQQZWusYahkW6d+vAHHvotucuoKuRThKqMH1QGgoqCpX2uMY8iJLteEjb0AyJUn6azt+IuKwthgfffAiAgCzq6DlV6fHFB7lxirjuMApDrFnPiiDIp8nnxQFYMUefhxws+AEzsj3rAZ6CH3E5d39rOMfNRMa8EcNRiQ5BcBxf+YGoNNNRVhpzPGnWV+UAoc3/J/dIqm08V0kqZUcBgFh4DImHgMQNP5CK4Xo/kR4xHablg4OpVCIaEF4MQN1BpB1MXgVAnIWjEqEDDBEN//OMfMWfOHLOt43WOPvpoXHXVVfjiF7+IVatW4TOf+Qxee+017LLLLrjzzjuxzjrrAAAeeeQRPPzwwwCAzTff3Gp78eLF2GSTTQAAzz77LF5++WWz74UXXsDHPvYxvPzyy9hggw2w66674ve//z1mzJgBQI459Pjjj+Oaa67B66+/jqlTp2LOnDm44YYbzLnLGhNiBDohR4it/O5nh/6k3fywBx7AGRjyxdP4AqFpXSswmnUehKIIaPSGQcg6R4VBFXPuS+Bmhff5oKiiMgSEgU3QJzJ3ntJVs8QMyHiUIDdDjCo+XjgKq0DCAiSPCpTo0Zi7CEEe9UfQVwDG3ROAIet9CHGy8yeByF1n9mtPlL72RDLYNGJATwOImCxnkVqXZWCR2W/2mb9Rlu1YEISEdBtqlY4LM7yAcScmPvehCINQrCZZjSMDRlwoKBJAkkQWAGl1KOFRriKk3WMUekYqCH3kpR9WqF3dVv3w7I61Ne7w8zrW1upgtTKUZ/qB021XylDRPufea2l7UEnaJnWN0f2+oGbX8kCoSNEpUydk7v3Pe78pkLjnc0eDpvV9fQu9H0UyRDsg5LrE3CwxCkIhVciCoxJqkBVAXUENSpKuKUHpK0i9dN19q31viRuznDrC0m2p8PjfRsGJ+4wLoNGh4Trczrp+JiD9DBElKBQrVMU9xuPIuMfoLPSCABCQusmKxhdqBYSsW5Fpz3OO0aAIaSsjUdbWktUwVMY6DUXDJHWac3fqOlwFyU21D4FMSBXK3V/gHjPHemahJyYEL3aVhd4f9775wEi7z3xQVAGIcvtFIUhvF4BQdjwgG4QEdaNR8HHnEXOhx5RT1ScnJoiUd1sNqgRBzq11X6uYHCuItA8Y5xiDHIm61I8PLnK9YlUse6+FAtb0Qn2xQjQovEzQtAEfDqucEyWIglKRe8wXMK1uq1XmixEqAqFRBUHahvPZsZpbDUNVrIqCEDpmJFi7QJQXVO26x2h5WfdY5pgACFGroAoVKS9BWMp7/10FyAdFIZWItpsJhnXO6apBqk5XQShTFnCLJTGGPDYocfflQBBgwY/1iuyrO+moz9KBTFPeFbxYFVLDCnXEBPcEUZvziOx2CVVIusuqqUIpECnI4X4ASmc0KY4T0reKxgmNVBAagd/0tVWwGobasaEGnao/U/MAoRUgol8geaqQVR5VA6EQTHn7E5UH0grXWuimggImHxy1A0W6r95OEQiytkcoCOkZ2suAkE8t6pYaRF71bdSLLGDW7c0zFtH6wgKijlhV1zUX9jEKhDIz3VNVyLgjhfo88HTKEJ5VhXyxQpYqJBiSxO8eE446FAIhbaGAadCyDoLQqICgOsS3a1bD0Ei3dnzEeQ/dTNUc6b4sSFQBGee4YJxQGVXIZ+5TqVPgqs7tApMFRxSKANkPX/aZ+976Al+pOW4x04+cGKE8EKJuLWs9jrNlDvi0DEIZ99kQusWcV0sJciBI+AJQrLdK2H9eghkg0u0YdUi/tgpJ9O+yCJAcJcirwGVcZcIETdsQlLrKTAYZ19eausdoFlm+e4zAj8i6vNJtO06I1rHgqACEuglBQwpA1omH7cyrvdUwNBKtHQAKtdduvIrP8o6togoF22iE95d5spT9mV7lfvuqRpGBo4xilKcWAX7FyDpfkt1fEoSs0aL1fgI5mWk3fACl12mMUJFrLE8RGkEglAdBeR8JqQAxtS6sj1nu7w+OjrnGylhmBnorHojcb9+9pan0zj0Lucd09hhdp2n0oTghAJk4Id1zN2B6OEGoxpDV22oYGinWaQDytd8J/d6bKVZ1nKIC95gLSVQVKjI3o6sS6CTFdUIPOX06sr9QLSp7TnpcFRCirjWiJlmg5CpDeWUGkES6rftUBoTc+JV2rYMg5IMgN9OJMWHV0VDE9HhCgiGdWqOiacVHz2XmbJsTljRrctqMEsTJugObCoJc11hoTCGdRq8hR6fR++KEygZMlwWhUPp8GRAq+y6NOACqlaGuWQ1Dw23dhiD3XJ1UVKgVxAN5M79asVIxQoGMriLwKPNe+KpE/v0ajHLVIm2++x2CIL2tQcjqn0fxseo72+4+b5l+2GePt2Zzp4Bk6ncxayxg7YJQKN1bl7OWgSewXurY8j84/CBEgVUExxQy7jEyplBh9pgTJ+QbTyjh0ZCD0GoFQdqG8nmxhlkNQ8Nh7X6g835hF31puqDTUiB1B4CmSBWisUJlzAdwIfgJ3f9Sv7o894sepncRAAqqRUDaVok+eafd0Me6Za5qpMs0LNE6eZBEjlOdSK+LPmTTTqYAE7qeEAiVsRLusbJWBEI+IU/XYSzrHisaQstrETKqkDt4YiZTzPM3nnWJeeCzyD1GR5rm+YMrGmUoiQwImbghJ2C6VRCi20AWhDqtBo0GzBiNk4KPFqthaKisHQCq8gdA61bMRqk0+GIrQdWtDoxYNiuukkvMqVvl2MR58vmUIW9ZGlsEBDLSPOadegNAoXvMnD8ASrRNq11O6cA+zq1L93keyBlVKPdCS6hCJa1IFXJZUl6qH4T0dkuwA2RUIOa6wgA5+jSQfpZ9brKIDGia+zchHAAm7jE1ka1WhazJah1FSPBiEJJe0xSEEh4ZANLusrIgVCZ9vgiEqkLQaACg2obGahjKM98DMu9LqFMSZqfoPwRGrbjBgqnzLKDseMCnbKxQXuC0hh96DUVA4Xtw093CoyCVfO8ZawAJbDhkkcy4ch9comHVEfqrOA8svbDiqD0uCFUJmtZt8EAZPYdbrvvkfl7pw3g4rOSpacZYHggB9luv3WSZjwOT2WR6CU3HYdQg82ovzJ1qQ2/nXjN5D6gipKc7UXOPlZlugw9mFaGkmU6xoQOk6ZxjLgT51KAkZ64xfcstKGoRgELfnqsF+NQxQ12zGoaqWje/5LspgXIRBqJWXGVlrVOxQj5rUQmy4KcAlJyd8oVci3nHkiQN8I7s6tntRnreMuqQper4QSh4nC+jKNR2pyxiEhCHyyJUfvIxJtKYIEdozAMhFokgpwSBCPYrVYWYhiLArwq5yq37nZEDQtIV5sQIxaIQhFIlKAxCOj7InXg14VHLLjFfXNAaC0Ha6pihrlkNQyPB2oEgnn1A556nnTnIylpZAIpahKQy15yn/ngCkzPleWa5yVKQ1O8iC0KQs03Liswz2CI1ryrkWEYB68SvTBbBSz4sAiI+bE8iFiEd4yeo9AjIbDD124AAUVqHHOMETpssMsCrChkjEFSkCpkTUyCqMjxEJjssIeuynIKQbzb6kCLkzkLvBkpTEEoqusSK1KCqEFQjQ21VrYah4bSqEJT38HL3tTIwYScsd9wgx0VGj8nrr+qnEIl9XM79yDz482JkABse8qDIXB9J4TdwJMGoNBSFBmOkljPOUK4q1C2LPEpWxIJPHxYpdyBXcKRlG7XNQNyFpkw/4FKJh3Gk2Xlmv57ri6z7/qYigD4+BReAUYGyQATYbjMKQVQRMtsh91gJVSjtYzZWKDjFhms+EKKT3DoxQhYIDaYgxAdTEEqaUW6gdJJEZgwhOpZQQscTQhiEitQgn0usCILK/iUUjKdZyqI2fr+2ZXUAddeshqHhsE5CUNExmcynNtShvC/nPKBpNXDaYxRyKBjlxv2E4m7cMreu18h9pQqRBTwVoQjIgpHvOmj/SJk3aDrT7TagSV9raFuXAdIdM5wWIZ0MFX51SIKPTBaQnJ0CEWBDET0mXc+CkLcfBogYiRcqFysk2yDbvr8t63PhASFPsLQYTFoGIZ5E1mCKNEg64ZGJD0oE66gaRCGoFRWoE/ATanPIoaiOGeqa1TA0lDYUEORro1vxQEC+q6sdCNKqFQ2YBqz2guqPNl/2lVvXAxdWOTV6nY4aZLaLoIgGf1NgLeOiy1yPp89VYgryIMdVgPS1km0W8ezpdEA9VYNa+BiziLWuDvlUIqIO6dtvZ0+qFggUZfvkBE4TECoMmgZS4KGv6n65sUJeVciN+QPS75QWQYjGCHHtEssBIRogXdUt5qpB7UBQ3keqG/CTd65hU4lq66jVMDQUNhwQ5LZHv1x96lBZaLIGUcz51ukkgFVJn89TgYIp6iWVoYza5gEhHxTprsOjEoXGHSq6Jr3pU8S4oxRV+TxR6HGByOsii9Q1hqGnFVdZmbG0Ct1lEWx1CLa7DIABJheK/NehV1IoojDkusc0CPlfNQhlY4WsDLKQKgR0DoSaduo8jRPyxQdpt1hZNcjADdqDoNCneCjhJ3T+IQOiWhnqmtUw1E0bbghy2w5J7VRtqTLWUMjadYnpKTV86fMZt59zz3xxQEUQpAcRzAswtlShJDs1iAtCFHrIetB1VmaYgKqB32WUIlfxAfyKke9ecMAKno7INUQ5br+SFlSHyszcHXKXIQtEgA+K3M744obsYGkLhHocAOqJ8t1jbhB1nlEI0ttlQGiQKwgiwdJNDUD29BouCHEnfd6nBsUi3yVWFoKKVKCq8MM973iUA72t2JABUT1rfdeshqFOW6sBbmVBqEy9brrFunXukrDmvf5OAFARXGg4UH0RRhVywEg/t11lyLj81CmgYp4M5JFzuTAZcOFZ8Jb3uSiK5zH7HbdYRNrVCpDzaJLAEmVjiAD5YHfVHx7BAihWQR3SilBVdxkFIvX+CO6HIkBkbrdvuCzbFea+2iBE44SyqpCtAmVUIWr0fjiDWVYFIT6o4oMGU5eYVISybjGaLVZFDcqDoKoqUB4A+WCnyELHtANJw61Q1daeDeNTs3X75z//iSOOOAKTJk3C+PHjseOOO+KRRx7x1j3++OPBGMPFF19c/UR02PpO1PMey4sBhw6K106bljuoC78wSmaS5Voovidv4Um6OIMMZrbJ4IMiacrtJE7rJXGmrrXQur62uNOOb/BDdU1CJDaMUXCjCzUXhCrECJlBLoMVfHEqUXbbxAU5x+a5dKw2CAQU9Tli2XYdF1Nah9TvYWCZxQMuqizqSSEn6rEXmikWkTbKgpBUiVQ/e6IgCPnvled+uiCkxg6yQKiZQAwmEoIGOfgglyA0KEGINyUIJc3IWuI4QhLL1ziJjFtMrkdIlHssFnI9FgwJIiRgZokBuc6YyRBLFKgmUGoRY+BMlumF04XZi7l0sMzSSetGmx21vO+mqkttlo06Zei1117DHnvsgTlz5uD222/H5MmT8eyzz2K99dbL1L355pvx8MMPY9q0ae2fuBvwUOYD2c6HttvB09S6EUQdmnCV7tNWQgnKqEB5QdR5AdRu8LQ+PCLuL8BWibhbFhnVyxoyIPSelfkclAUjGt/kmk8B0vDjixcKttHml60Zp4gGQaubp11ajPkVIpXqn6cSmfdBvT+CvKVeI29JRhUy62HXWAaEehoZF1muKgSQz7IDQjR9fjDOjCzNBzmEig9KtCKkMsZofFAcN3LVID2AYiJYaSWIusJ8bjB6u11lpSqUuN/Q7SCNPnen3WltW51a3zUbdTD0ta99DW9961tx5ZVXmrJNNtkkU++f//wnTjzxRPzqV7/CvHnzhrCHJazbEOS2YwVPVwCksvVyh+AtYb7MMcs11kLKeREE5QVRh6CiIJUevACIdPq8C0cgsUTUdea7ZN/gka1+VvKe/qH0ebcsNOhipy1i6YNAgwIXASACgm4zDUo8hSILhIo+svpcORCUQg78IOSJFQpOu+G+ty4I6VGmB+N0ZOnBRKbMK9eYUYNUxpiOD3LdYnGcjQ1KaLaYJy7IhaA8V5gbIyT3kfWg47I1Cx1XBZK0A3fEWD0Cddds1LnJbrnlFsyaNQsf+chHMHnyZOy000644oorrDqccxx55JH4whe+gLe//e3D1NOADSUIFbWnHy7t/IHlKUKtWMhV5HWPkSXHHRZ0X/ncaUVuMrcebUeQc+pr4c5+AJkpNfT1ArbrzLHcaUTM/fNll+W8v1XdZqUBt3MPEO/ghEAaQ+S4zHLdZka1YWmQs3aF9cglnT8sXfQ+XS/TRgiEeqIsCPU00n6xKAUh57os0254wSHixJprLANCyjUmBgV4P1K32IAEIZ9brNlsIE5S11gzaaDJI8sl1hRhd1jMbFdYrNxgCbPdYzFxfcUs6+4SnqXTVrXtEe02q61jNuqUob/97W+47LLL8LnPfQ5nnnkm/vCHP+Dkk09GX18fjjrqKABSPerp6cHJJ59cut2BgQEMDAxYZUkzQV+vx0VT1ToBQK08XGjqO1WE8lwxpdWgnPiQomkyaD90fTqOUOG98ChCbiyNBR/cDx/cDySZtq1MMhB1KEIqS6h19SqYvM5UJeLpfuOKUllzjkoE5HxR52WUucHjzrUYMLSOybnXvvvhnl/Q+6kH/tOLE+Cr58fy7QOsB77ZBuAfVdp+QDEOoMEg9FhANIbPrEtViJYzXUbOk/fos6bVUP1wp9qwFB8mVSEdH0QhyMog80Em/bFCg6QFt2KDoFxiOm1exwZRl5iGIKMAKbeYjgmi8UAc0hWWIJ1XLIat/rjKj+0O0+v+4GiQOiEr+sas+lMrlOlFi/O6NGIUotpN1jUbdTDEOcesWbOwYMECAMBOO+2EJ554ApdddhmOOuooPPLII/jmN7+JRx99NJ0AsYQtXLgQ5557rlV25v7vwlnzdm6ns52p1+qvbCHCQNSOVVUTTH944Euf9KusSpUHQbqdovU8VxktT5x+Wy4yUsazr8ZtRq9P76duM9pemUEYi9x6RZBTZb8QwW3BhX0/OVf7K4AQhRaRbgtaXnRdyo3GGJOp9wSWmNpvxh7iUO9BWoayQ0rQdrUCpMozEESDvwMg5B1c0TMDfZlsMTc2iDdtJYjGBZmAaApCejoNE/AchqAiALLigjKxQO1bqI3Qt0+ZEaNDwy6k5xx+IBJlnym1VbZR5yabOnUqttlmG6ts6623xt///ncAwAMPPIClS5di+vTp6OnpQU9PD55//nl8/vOf98YWaTvjjDOwbNkyazl17jtb62SVaP3ch5Jo390QOp7+Gq9iHQrIzsBLmXvmcVsZt5LPXRZaD7nWyrjh3Pq0/467zHKbudfnus2AMJT57oG5kYE29HqVz6Fbnweuz+f+i5MUhGI9aawzY3oIhFQAsIl/UUuapck998+TvUncZm58TsaFZlxkOtMsMot3LCC9P0qz09Bj74M6thIIhVQhocEn8WeLOS4xDUJ8EEgGpEssHogQDzQQDzYQK1dYs9nAYJy6xAaTBgaVK6wpIjQRIUaEJhiaygXWZHK9qdYTxpQrDBgkLjLpMgMS4wZTbjHIJVGLzxVWdQl+jMni3c+ycGbd9py2a1u9bdQpQ3vssQeefvppq+wvf/kLZsyYAQA48sgj8b73vc/av+++++LII4/Exz/+8WC7fX196Ovrs8pWVnWRVaX2IhBq5VjvWD1EIWpHHSqKFynrHsvbVwQCykplhoXUoKLMM3MStZ0ZJZqUGSXI3bZfrcBq93ijEJGBJiu5Cj0w5bizDJAFgM1q19ovgttCQ48HhEyWk9kfgCBTRt1aDvRUMRJorZVh7ck06pGuo+DJqEPqfEGFyFWFdJkndikDQfKgfEVIdsb0g060amadd7LFTGwQTZl3FKGEq/ggpQbFSeoSS6DT420lKGZZFUiuww6SNooQuQTnkroxMap7Dt8p9J+fz1odJHHY1aHaTdY1G3Uw9NnPfha77747FixYgI9+9KP4wx/+gO9+97v47ne/CwCYNGkSJk2aZB3T29uLDTfcEFtttVW1k5UBh1Zky3bcYmXUEyDbb9dlljknbz0Fvsgy2WHyvmZSyoFsv53rDQ6S6AMbuh6CJNpWyDVFy53BE23wyYdBLxDp9n1AVNQXIF9VIupZXr8yqo8LPiZYXABx7Achrf7okZD1NlWJtKsnBEAet5hvtOmg+5sCirk+YdV3wQhACkfusaH2ybppm0KQ2s6oQaY8yrZnwas/PigTJB0LA0JJPzJuMR0cnSgVyBorSAVECxoMzZhxhcUeADJusTTMqqvuMPoX4LYdgiP33aN/bq6FgKjIXTasVjaMoLbKNupg6F3vehduuukmnHHGGfjKV76CmTNn4uKLL8bhhx/enRN22kfbKgi1ojoVKTFFsNeOihQy50FvAZE+p3tIaKTlKgHSRXUD586YBUEqtocCEcg6ffWlTEdOOy4Q5VnRpLMht1zRq15PNOTE1rZICPzEsV8NSmxAEq4yFOv+pfBjoMeKD/K7wQSy4MIYs+uXACM0WHreMvFCcEDMUoccCNLlVUDI4zoUGihjLgdSjKkalAZK86Z0iyXNdNBEnxrU1DCkBkqkEJQgVYHiAADRbSALPJ34tvSF5NFyen7ABpo8KFptgKi2rtiogyEAOOCAA3DAAQeUrv/cc891rzNVbKhAyD3OBO8G1CHiMkj70iGlKARUpDxXuaD1ad9oWUjtKXKZhdSUkFGANBBUAYg4cgKqHSACkBlsMjTQpO6359pz3WNK5THQkwdCSSwfzElsq0EUeAgE2WAk0oe6etALHWSdFyztfQ+UIuO6utTtNLDi+0x7gEdmk5VwPYTayoMgvW767AEh3VcgC0IkPgjELUbjg+hI0vGgVoQaZgRpA0PKJabT430QJF9TCKIA5MIP/SsRvq8U3y0M3FpqTIQhiHvKQPrmQlFZIBpVVrvJumajEoZGpXUThIokfh+Q5Kg+HZmsVTbkdY9l4mLyFCy3PVrerhoUgiDfe8FYtj+ue4yqPdZ++9V2lxGY0seYSVtbHGyyCISsqUIICBmlR20b9YensEPVoCTJhSCpAKUQRAFIxLq/ARCi98PcbwaogRMFVJyPhhAFPxYU+YDItONsl0jfl2VRZr8FQbIgo0wFY4Q8MVT0vlE1iI4mLd1iaXxQPNAgU2mkAdJaCcqMEaTgRwIRcYs5AEThRzhABPi3Q+Z7S6lFsMFKz43rgyBfW67KUxaIhnTW+Xat056K2ozVMDQU1mkQCv068LkJfOfKS7dvxzXGOdAoATmADUp596fowe9uFylA7rGmTsG3od6vocgXMF1BSRMiyQKRG4+UZ65SRq7HGk+IghAdUJJuO64wJLHtFtNqUJKkEGRcZQSKfDEuQshXkxkG9bDX3RP2usdS2CDQb0AIZmwhGqdjoIjDG+uTMVfpyatD+0TLqRpEXjMgRGOi8txi7mjSJFDaHUCx2WwYt1icRGgmDcQ8QlO5xJoFEBQzG4B88KNfQ38pZdLXaTvUIqe8CIzckD3ah04pRCFX2bAHUdfWFRv1quGINjduw2dVQMiXThw8t1O3zC+KojiVMsF7RUHI7kPcra/L6D76AHcDfem2W6bbo/toe5zDGr6A8/wFsOvSPvsUmJB7ylWk8tx2rrn1QyCkYYcu+li3XLu7khiIm0CzKd1iTbU+qF6bTQi1YGAQGBiEGBiE6G8CA02IgSbEykGgvwkxEIMPxBD9MXh/AtGfgK9USz8H7+dIVnLwlQK8XyBZqUZL9i7CLBIIJBik2VQymBixVJwkjEnIcN1x2TikyF5MOcssLHLS82mANB1EUR+fY4JzWNlidG6xpjPRaj9X1y8VITdtfnCgB81BmTI/GDdMuvyAiDCIBgZUWvwAYxhkDANR+tpkwEAENBkwyOSrXmIATch0+CaDSZuPA4uGqEy5swjYC5Aey51tc7+YDUd0n1vXDbYu8405amact4acaHOpYPfffz8OPPBATJs2DYwx3HzzzdZ+IQTOOeccTJs2DePGjcPs2bPxxBNPmP2vvvoqTjrpJGy11VYYP348pk+fjpNPPhnLli3LPe8555xjhsrQy4Ybbljp3GWtVoa6ZaXgoyIItdQP4iowbiphKxxuvU6bzz1GHzw+gHJhwy0PqUG6rIoaFHKXUaOTj+qZ210FzFWK6M9Ynn0VEey5yHwuRJ8FrqcwfZ4qQa5bzECRExuUJBKCXGUoMPYNFIwYOOFCrnNAqNPCYV3z9rrBJ0oO0Kyh1+X4QMKoQnLsH6UQabWoJ/1Vn1GJSrrPMq5id5tF/n1OPe9Aea5bjKpBMc8MpBiKD2o2G5ZbbDBpWGpQk9mKUMzUWECAUYESqgbp7jkuMut6sldj3xb3UuH86nZvq7B3uX82eh2QHxGqElmqENkuUogyfRotNkzZZG+++SZ22GEHfPzjH8eHPvShzP4LLrgAF110Ea666ipsueWWmD9/PvbZZx88/fTTWGeddfDiiy/ixRdfxIUXXohtttkGzz//PD796U/jxRdfxE9+8pPcc7/97W/Hr3/9a7PdaNixlEXnLms1DHXDhhqE6B9IaFj/PNCp4hqr6kYLBWJXVapC6knILZZXvwoEuftpELUFRKgWcK7ihDJApNsq0xcXgky7HgAKucU0BMVx2CXmQpGGIDonln6AKxCSCywI4jEAwRQIsRSGFATpbXobmQVEEoBYQ4DFMPOEiUiAcQeKOEsHRSSuswwQBT7PuSAUgiDftvW+EXVKZ9ZxAQzGcj1nktVkIBsfFA86EMTlwIkxIqnqsEjBUBaC1FuhxhXKwg+FIusSPJcVjAHyhID5jqXuNX2ID4raBaLVwjoYQO2bgso33h4A7L///th///297QghcPHFF+Oss87CwQcfDAC4+uqrMWXKFFx33XU4/vjjse222+KnP/2pOWazzTbD+eefjyOOOAJxHKOnJ4wiPT09GTWoyrnLWg1DeVYU+1Lmge5auxBU1ZVl4nKoIA37Ye4JrhaIwEJjTnIONEoMSGkpTwQayhynLQ9+QttllSD3WF8fMvfGqWcpRkin7iDzlIErFwwtY1GqEEHeJ1bm40QBiF5vWSXIiQsSyiVGAUiWJfIhraGHwo8O6qUP7RjywR0DImHgav4rwaFemXkVCoi4hiBPOpKGoIgpAGICLBKIGvQViBoCUY+QgBQJqRiZSVXlSNEighpZGhARM6NMM/oUjhQNqMESzTxlPrix4t2cOD2fO85KndduCp4CUH9slDQ+yM299KXMN/Vo0koN0kpQ0yhBKQA1GUOsXVtARhHSqhCQAhAnuk+Vbzcrzl1pMAlL1Ri634TfwQMvun4BSJkwrTTkzBtHRIGoSB0qC0+heKHRBl6+Kai+/OUv45xzzqnUzuLFi7FkyRLMnTvXlPX19WHPPffEgw8+GASSZcuWYd11180FIQB45plnMG3aNPT19WGXXXbBggULsOmmm7Z1bp/VMFTGWoEen7WbOt+KROr7uU37Q0emRgRE5Iuepn37js0zCkJusHQo1d7Xb7qvDPiUUYKKXHChfvlcffRV1ylj5t7CtGe5c0KHheZgy0uZz1OCms0UkpqxVH4UDInBWJXxdORjZ8A/EUvlIoUgCT2cABFPGLhg4EkkQ7Q4y4AQjU/XxphQMCTAmFSGGhFXEMQlCDUEoiSFJBYLRBqGepRi1KOgv0e50HgC1hNB6FggjlQpoo9ICkXmM8DS+06NRaniQ40OHeBAkM6qcwdQFDGMS0y7w6hLrBmnAdIDgkyfoabLGCQq0CBDVhEC7KwxieP2AIrhj6Bl+tOekHskf0rp/cxqz1WCMvtIHRdiXHgB8lUin4WCokeLdXJusjPOOAOf+9znrDKfKlRkS5YsAQBMmTLFKp8yZQqef/557zGvvPIKzjvvvEJY2WWXXXDNNddgyy23xL/+9S/Mnz8fu+++O5544glMmjSppXOHrIahobKqc4y5qlAIhEKyaWjcIJ97oMj1FVKCQsf54Ked7LEyapDebkUNyoCYc0/dqUx8sU90MtNAjJC9z4kzIu1p4NGDUXoHnfS5BUMuMZ0ST+OCCPQYNagZW+tWQK8nq0k/tHnMkDSzAJRwuZ4kkVSDBJDwSM3jGlaF5LUrEGL2eiPiCnwisy7VoXRdJAIRF4i47KNUi4RUgiLlPlP33Q9FjlIEAgrBYSfsYRCs4QIUANGAbp0+L2IB3p9Vg9yRpLVLbDBWWWI8wqBopBBEYChmacCzVoQ0BJmsMQJA+qOZjiVU/F1FIYcqIlSdAblzISjSrjEKOz4g0ubWAWwgcuvp6xptqk3QOugmC7nEWjV3ZHghRKYMAJYvX4558+Zhm222wZe//OXcNqlrbrvttsNuu+2GzTbbDFdffbUFcmXPnWc1DA2FVZ1eowwIFf1R+MYecoFI963MhyZP1WpE9nbevEuhSSndNulrGQjyHlcAQpZClHM/3bR6wAYYwO8OLAQi0oal8asHcAiC9LYve027xKgaREDIcosZ6CHrxCVmZTR5IEgH8/KEvBIA4npGdOUa42oaCA1A8mHscZERZYExgYaBIYFGFKGRcESRAG8wRFzI7YSlUJQIRLFAY4x0n0VcnkzEYSiyssMES+vwJAUj9T6HhgDIvFcEiNwhBtLsN5kl5t5TOpJ0U4FQM5ZxQbGQihB1i8kMMGaywBKWZoRRCIrV+N0cWh1SyhX5+OVZqgSlipl0b+nvE7teHhRVASKfouNTgsqoQ+3UD9lqA1stmI7nWbJkCaZOnWrKly5dmlFsVqxYgf322w9rr702brrpJvT29lY611prrYXtttsOzzzzTOVzF1kNQ922dkHIe1yFv7y8ARldcKGuMg5kR0B2wEeb6/Jx23ddZt5+BpSaoVCD3PfIfV+o+gOQWCtkgaho/rdcIIrsOu6x7rXkgVCcqkBet1gztmKDjBo0mBA1KH/EYw1AdA4sCkB0HiyhJgQVYGS8Glst0LcFSIGICYEICogglaEGU6pQEqGhXGdSFeLoIVDEE4FGr1SKtPvMC0VGIZI/EljEpFqUAFZsEVD81NNuMTq9iFGClGJkAsylm1HPKyahkmXcYpYiJBgG0ci4xXQ6fMJkOnysuu9CUKwAiMKPC0Qhs4OamfV+GTWJhaEoUvUiMEuRQkUg8gFMkTq02tgIHIF65syZ2HDDDXHXXXdhp512AgAMDg7ivvvuw9e+9jVTb/ny5dh3333R19eHW265BWPHjq18roGBATz11FN4z3veU+ncZayGoW5aJ0DIeoCH2/P5kq3B3rQaFFKHPIqOHIna+UoRJb9iXBWoTKxQVQii2+2qQXmuu0zckMgHoqA65N4P2N/YFJRC/fApQ657zAdCGnz0eEGxjBFCs5nGBmkI6o+z818N+FULCUMNNe0Ds6Z+0PCTKABKwDKznptLAwUhfRsEGkJCUCSABgQaCUPEgEYi0BNxCUdKLeppyLgkCkU8kaDkQpHlPosYRJzI2KIoBaTMmEEakGiZuQBhrVuDTFoDTqYQJGKAx3oARf+8Ym6m2CCijFtMjxFE1SAdJ+SDIA1AFpCAAI1jkaPJRJDKUAomKRj5oCgCnHOlQGQAqwCIXCvan6nviUEalTZMqfVvvPEG/vrXv5rtxYsX47HHHsPEiRMxffp0nHLKKViwYAG22GILbLHFFliwYAHGjx+Pww47DIBUhObOnYuVK1fi2muvxfLly7F8+XIAwAYbbGDS5ffee28cdNBBOPHEEwEAp556Kg488EBMnz4dS5cuxfz587F8+XIcffTRAKR7rOjcZa2GoW5YmeDiUu3kg1BRMJ3eb6DIB0QIQIrb31ZHqXZjk0J10k7nl1WFIF+bRRAUUobo9bQMRPqVuMf0dtEYQ3lxQm7GmAah5qAdH2Tgp0kAKJYDJVI1qJ97Z0OPVTaTOwlok86GjnTqB86QwhBLVSEKRa5FEDJsBwyMAZEQaADoEQIMDD0EjHp5ZNSihPPSUARGAq0jmYEmYhUP1MPSJ6w1kCIpy3xm7GhgF4assZYUBIlEAmazv2FcjXReMeoWa4pIDZ6YdYuZARKJGpRAmHWu1l0YArJAar8P0qhLDGQtowqB+ZUiohKl6pINREBWAbJub84+17qpCPkyydYEF9kf//hHzJkzx2zreJ2jjz4aV111Fb74xS9i1apV+MxnPoPXXnsNu+yyC+68804zzs8jjzyChx9+GACw+eabW20vXrwYm2yyCQDg2Wefxcsvv2z2vfDCC/jYxz6Gl19+GRtssAF23XVX/P73v8eMGTNMnaJzlzUmRNGTe821ld/8dLUDyt7KVuKEnP1VswoslcidQ0nvY2pdpRej0SMfDkyVNRrKFeRs0zIzJQFZ19uZa/YACy0fSjWo7P2MnGvSv4DpPaD7fPfHWzey26cZfbSP9JqqgJCVIdaEGBg0bjEx0LRHOx5Uo0E3mUrrzs59pTOaEsHMwzqBVCzKznsF+B/AkZAPPLreoxSiBgGjBgR6IdAAR4MJ9EbytachFaOeBnGf6QDrHhp0rVPyIV1okYYjtR6lUETXg2aBEH1NIUhwmKw7HXTe7O/JqEF0Oo0miCIUcIvRrLHYgJAfgqhKI5yHuw8kGMGPrHrHrDKqEll1HCCKyL60nnoV2ZR8/Vmwz22/AqmrzLfPHdzRvSa3jltP1s2HoUNe+mFmfyftjc99oGNtrX3RLR1ra3WwWhnKM/rgDMWCVM4SKwFCBfuDI9r6TIGPpRJZo1LnqEOcw4obcq/Vd+3UPVY1g6xTEORtowIE+aRo9zrcWChX5dHnrKIQubFDbh9pfBCNGSoDQjpGiMYHaTWoP1YQxCUEDaZTPujRjuO4IWNYyASggzzKjHRsxrYBS+NVNAQx/UAOx6cw9Z/iETSEfhAyNAA0BJMgxORrEwK9gqEhBJKESSgSzFKKoihSyhBHI47Q6OEm0FqPVWSpRQaGhHpFOjGs+Tjovyv6uSIfH56+cgeC6NADSRxhcKBhuRpjHmGQN9AUkTdbzHWLpTFCwlKGjIuMAJCGH6PQed4J+umXcJMGtHMCO+nxtpssUkpgqgRJFZW6qbhT340FKqMOuX9Oa4IVBu/X1rLVMFTWOiGgteIey+zKV4yy59Q/lVIoMiqRG9fjucZM3JAbRJ152FM4iLLnsBvPttNNNShz7wLKVFFffeMMmbgrpE+TvBihEBCBHO+e2wdCoRihPBAakK4yMRBD9CepW6xfxgZRNUhPADoYNzJuG/dBHasHtUnlJvErFIJoPLL94FWvVBliCojUaw/TQAQ0GNAjGBJIlagpGHqFQDOJ0Ms4GjySalHEwTlDFEXo6eESmuLIGquINeUrbwJRjwQj3zQg5E3JfkaIcKfhR7Kqhh8CQkmERL0ODPaAc5ZRg0LZYq5bTG7balCiUuf1q1Cv2eyx/DihbGyQUB/bMAD5gAj6fRf2x9wHPzS+ZzhBp6oqVNvothqGhsqC8TLl3WOVQcitS4EIyhUmOMDVU5nGuiACaDIZVUHKBlGnHc/pV56aw6tDkK+ue54CCCqcPd30k+zMAyJvzBUCQBR5PgPkWn0gpM/rBkvrCUBdEDKKUALen6STgCoQkhOApmpQM06DeENj2zQZMqMdUxCSaoA9uJ975427xShDUjHogXKVWUAkQajBgEHBMEa5zRIVdJ1otUgwCUXchqJGgyNqRGTcImGBUTrqNcw0ILJzgb85MqWInmpECAlAQgA8VuMrKQii2Xc+yEzIvaVuMQ1ARhnyqEHaNZbAhiD9Hrj3XkBYrjBAA41+X5gpUzcBkTomBEB6G+S9d9PqmXUue58+Lq3TGhStdqpRrQx1zWoYGgorC0I5VgqEQtBBpw6gwZ9Fc5aZlHlFRZyngy/mBVH7BiX02VCrQTkQVEZ+pnWYFYiu1bECIAJSd5juAwWikLlwSMcRohOtmvnFSNbYYJxVhAIg1FwlIag5qGZDV2qQnvJBp3QPsLDLpiiTCYB5OLvmxpvoOJGGgqMGGHogGb0HslzDkYQfhqQAihqJQG8j8ablR4yMZM00BNH1vM+GfmVmlG29zpNIvmXOGEw6AL0/aVgxV1QNklCUzihPU+dTEErVIH3PEw8EaYVIvwfOFZD3Qb9PzNqXurMkpkSmLRYEoExQNXGX6X5UgZVOD6CYFy9UeOxwcEnFWNHaylsNQ92yog9thTR6C4SqjkytH9qmXP75C/V1KBWifHXIcpW5aos3cyrKgoLP8iCoKgD5VKCy8JOXvaXNeRIKfZ1IJBgl6h7SeCHGYc9NJtJ7Rucn0/OZRVG67p6fqkLu9BpqIEWpABG3WDMGBgYhBgalGqTcYhqCkpVpbFCzX6pAgwM9Rgka5A0MqHTuAcYwEGkQSlWKJvSrKKVOAAXxQoAJymVQafRqu0G2ZUaZXO8VCo4E0CsYesDUugy07lVB172cy3qJDLruZWp6D6jxiyI9sKPwTgXCQqqQ/kwIZsEQVwNM6kEn3bGXEk9wdKzcYZb648QFyXUbgPR9jj3wQ1/Nx8njEo9YCjL0/aAQqxU7DVuRgiIKRG4MEcz7qdoh7jJXHSrrKvPFFPnMB1pljitykQ2be6xWhrpmNQx12sqQeysTsPqsIOMsU+YZZyh1mTlAZJ3DiQNy44ba6XcnQcinAlWBoLz3wN1HQE87FJgZrNKNKUJYJaLwSBjUex0+EFITr8rZ5FPXGB1DSAwmZjRpWw1KQWhwoAfNZgMDzYYCoQj9aGCARRhkKQQNRMCAB4KaSo3RD2b5sBRWzArU5boZTECasWQgCKkSEYEpIBJogMn4ICYDqscICQxaNUostUjGF8Uq6LrJGugVQmWiMTSFQCOJ0MOEVI0IGPmmAgEQBCI6x5qGIL2ecPkoTcj4S3rogQQMq6LImlg1owARpa3pACeNDdL33AdBGn7yHqUGkJh+L2zlRyjoAVGA9HvqApE7NpE+t2+fCztV1aKRYqOxz7WlVsNQnvnAxjPDe7U2S4BQiP59M2EXHePWCQ28mKmrH9gNWFll2lWWFzfkxr74lA56jiIQ6oAaVAmCiu4lVdvonGJaQaPNVQUiV03zDbKoFSbObdcYjRGKk3QMIQ1E/WogRRIfpBUhCkL9vIFBROhnVBFSEKRf1YO5CWFAKH1I2xCkH8Y0ZsV7W2maNUvVIA1HEoiYAaIeMAVCMAHVMXGlxZBQ1NSKkZD979UZacqVpsctYgqMGI/SKUAARAqANBj5jM61xoUaSsAz+nYCplyJap0x9JPZ5a3pNFBNDZKv/vuOgnuv7z9gQxGFIBr4rIEoBD7WvXHcZaPNQrPU23WGyGplqGtWw1BVa8dn28IH2bjIqoBQHsR5gMh81VF1yMQGidRV5s7V6osJ8mWP+RSXToFQqxBUBYAyAdAeF6QCGgNE7kS1JlvMA9MWKHnOrfurg6XppKs0kFoBkDXxKo0RGuTZ+CDlGhtoNjAQ92BAROhHhEEWYZVyiw2omBUJREKpQsKAkK0KKRAS8jXrIgvfZ6ZgB4DKKFPw44BRjwKi2ChFDL0KihIFRT2QriYdX2QUI8EUEKkAbKXraTDSI13L88upQCKm11U/HSCic63Ja2RqvEUJPEIBkIA9BpMegmAgys4npuOufO5HCps+Bc4Hn3n33XzUzEdQxQapgUVtIMoGW7vmxgvl1S7r7mrXfG6tULxQUX+GM4OsHhawe1bD0FBZ6GHbisITqp8HajTI1wUib79c+IrIa17ckAMBeX0pCnyuCkJVIcjrVgzcQ7dc30cgvZe6G4hsl5mvHZ8rzRdjpftLs8aEUof07POxrQxJF1k6vQbvTzKKUDwYSdfYYJotpkGon0UYiKRiod1iAwwYgFAwJJeYvMbgiAkAWSqFEN4sJut2mldmZpuWkBIhccAoIUpRQ8FRohUjJhWjXiFVlR7IjLNY2EHXTcbSjDSIDBilMASzbvoZEm4hgUevc+iBJ+XRGoT0qNxaDRpgdoaYb+BEnxpEgSgPgsr8fNPAw4ja4wJR9npTdUgHVFMFaU2xNe16V1erYajblgc3ZUeZDqlCRSDkxgvpei4QcfI1ptWhiLRJXWVV4oYyikrA/aNffbE/FUGoJQhy712R+ufCnwcuMy6zPHeZO84Qi5BRzEz6PBlLiAu/eyxOIGJuzTrP+wWSfpjU+eagXAabDfTHPejnjQwIrSIgNKhAaMCoQVyBUApBcuFIhBu7IswvWt+dpZ8ixhgikbrGEghZhhSMGko/6mESgBICRQ2lCMUKihqQKlDCmJV95kvRjzQQmW1hKRvaXeJTBtIRtdNJSDmj6yDTk9jDEISm0chTgyhsaiVOQ1CZgRXt+5+mxPuASBtVhzoBPfqcrViralLV40ZM4LS22k3WNasMQ8899xweeOABPPfcc1i5ciU22GAD7LTTTthtt91amoV2tbYqIJTZXfBAzgOhvEDqiGWByNt+CVdZKG6o7MjTvv5bcNQiCJWBoLIA5BuF3FV35IZ6cRQhKzC6DBDpYGoHEjUUGTjitntMKUSWe0xPsTEo1Izzao6xWM4xptPmB7nMaBr0gFA/UYQGwBFDvjYh0BRcxbPI10Rw9XDmSg3KwhBgP5xpvIkGISANoqZw1KPAqKEe1IlQgdWMWSpRA2lcUS+YBCGkcUW+FP0IKRiZcY6EDuBO50qjHwPrY2KuDWbeNWHWoZQhrRalrykM5Y8XRN1hrkssIcpbFbekvs/u3GLuuEN56lA71un28qbiyDt3WRdZkattSKyGoa5ZaRi67rrr8K1vfQt/+MMfMHnyZGy00UYYN24cXn31VTz77LMYO3YsDj/8cJx22mnWJGqj2orG4QkdU2TeGJoWj6vajr4mC4g86hAaNghYbVBQ8qg/RZO45rnH3PJWQagMBGVcUgX3zgUjn8tLn5trd1mJzw+dtoOaC0JJnO8eSxIg5ulYQhYIMUsVGozVwhsYRAP9KkbIB0KrGMegUoQkEHE0hVaHOBIRgiGlXhRkMqXKCwUhllWJ1LYJpGYMDUQqzicyLjRXJdLB1g0HirQLTU/50aPe1h7IB2tEoYjpPqZmUr/JW6zBh869RkfgNiAEGJXIjQsSQNAlJsi6qwb5ICjvGyMi9TT80J83PnVoKCwXYloAklbVnKLA6do9tnpZKRh6xzvegSiKcMwxx+DHP/4xpk+fbu0fGBjAQw89hOuvvx6zZs3CpZdeio985CNd6fCQW6dJvAQIeccVKvVwD7jTqNEssty4HpG6ykxmWIm4odBUH26/fIHPIUWnVRAqA0E+ACrjJqNpyFbcVGS5JK34IX2sTx1Sv74zfaNKkAqeNu4xzqV7LE6UEqSyx2LudY8lzchkjsWJnFtsQERYpbPGSIyQC0ID4BgkilATHLHwwZB81Q9p83DOAU0dIwSlvpgHsAAixgwcNdSeBECDRTJlnqhFMu4nH4oiEldEwSiCdo1JxShiOlYohSLAGYDapxAx6p5KwYgCkFwXpqzJwhCky8pAkA+AQvedqUl0gSz8AFl1qFtW5gwh6KgKI75ztaMKDYfVc5N1z0rB0HnnnYd58+YF9/f19WH27NmYPXs25s+fj8WLF3esg6uVVQWhIqsKQnqfC0QkVkiAg7lp9Fa8UIW4IReIQv0qM21GJ0AoD4KCgdPEvejWdSHGAqIADGbad9py92kQct1jCoTgxA1JV5nfPRYPKiDSgyqKhnKP2enzAwEQGhBSFRoAVy4yCUSJWtcZZNotRh/QuVkwIgUimlGmlSENRwm4BCKmR5pWLjARqQytyEAR0zDEqNvMhqMIwqhFESQYMaUYGQjSQITsx8D7dpJX102m46hSKBJGGaIDVPpS5X1xQSEICrkkgVR9E0KkEAobfqg6NBTmO1c34aPMtbWiCg2JglbDUNesFAzlgZBr66+/PtZff/2WO7RaWtEo0SErUoV8ZSHgot/iReMMadcZdZWpuKGM+eKGfApRXnq9t0297oGasiCU527znT83vd7ZR5U1F4jodRh3WUAdyhulm4IQHVyRAJCJFaJB0zGHiAVEDPAmM5Ouxso11lRxQgNgqSLEZDbTKgb0Q8YIuSA0qNxigyJBQlUhRxkSFIZM4HT43kZgFhBRd5nrMksgwIRUhhKlFiUKalJAikjAtQ1FTSeuyB3IUR4HFSNkz5Mm+0T7rd4m53o0sOh9Qr1SAEqnyUgHrNRl7nhBcQkIKnOf6f4IzACRzzU21OY7p+9eu+WmTNj1zKsWcH3nbFEVGjYQqq2rVjmA+tFHH0Vvby+22247AMDPf/5zXHnlldhmm21wzjnnYMyYMR3v5Ki1PIXG8+DNnXbDLfM9QPOy00IjUZu2SKwQPYa6ykCCqENxQz7XW2iwxaKynH2lQcinBhXd57z3zZ3nzQdEACx3WchcIKL3UPeDxA0JPa4QDZqmqtCgdpGlqlAyyJA0I8RxZLnHBtFAUwVM0/T5NGuMZ0BoUCQyTkhwxCJBUyQGgnScEAUieZvsGJbM7VQqjbxjjjqkACkyWJSCkVCKjVaLUjBSYwaBGUjSUERT860pPhwwiiAUBKXj5LgPV98D0ahCJl4oOx+bBiAaA+TGBFVRglwIKtKVhwp67HtXPN4QSuzvRABzVVVopLjHjFVwHNRWzSrD0PHHH4/TTz8d2223Hf72t7/h0EMPxUEHHYQbb7wRK1euxMUXX9yFbg6TlQlYrmpFEOTWyXX7FNRz2me+gRe589CmgzBS6OFc1SuIG6IZV754pLygZVfJCahCXhAKQVARABWpbhlLSEyQow3o67eAKEcd0v3SzSSe61eB0wZ84jide2xgUK4PDEKsHIQYiMFXxuArOeI3gHhVhMGVPRjo78HgQA/6B3uwKunBStHAShZhZRRhVQSsjICVDFjFBPrB0Q+OVeDoF4mBoAEkMkZIpK8JVYaEfEzLB3j6Km9rjipEXDVmSg7qMlMxQ7qcAlGDRWAi3e5Rj/cGixT4yP0m0Boq0NoCoHRQR0YgiU4FEll9A+lv1ij8yO0UUnyTprrgA1PPhh/qAnPBp8yAivp+ujqu6y4ra6F7VAQ9EViqupF2rHYFDar3q0K0vKwqVCaDLA+ERoIiVMcMdc8qw9Bf/vIX7LjjjgCAG2+8Ee9973tx3XXX4Xe/+x0OPfTQ1QuGOmmBD3HLIGQ3UqptC4qoi4zr36uR3xVm9Y8Xxw35Aqp97VQ14cBCqCyYgVYegtx7x+h1hKY1cYEw06Zn7KFQJhkJnhZc2O4yOrZQrMYSSngmeyxpRkhiO05oQKSTguqpNfT0GlINSl1jsXKL6WDpQRHL4GmRgJNYIQ1DPhASBT8ouAAYia1iYEhECj50XSh1SDAGJlI3j1aOBIQdT2SpRrYrTUMQAzMxRvrh3mOgy54zze8qS7dcFxWFGwouFISqqj8+ACo7zUY6hlBYIdFgY5UxF3bKIUBVVShzXrou/OVumQtCPisDQqH2qQ2La6yGoa5ZZRgSQoCrL+9f//rXOOCAAwAAb33rW/Hyyy93tnerg+V8eHNByNuW5wEeeKiXDsT2Bjk37PUycUP0AU9hwOf+KeoPtTLHeF1dJUCoQvA63WfBZCj+yqMOeUejpi422ncNQjprzGSQCdkX7SZr6mk4ZKwQ1zAUp+6xOInQTBpoChkzM+C4x5qgI0unGWMDShUaVC6xplGGEksRclUhoVxl8lKKv7wZeQilD+5I7ZMQBECqQAqELJUIMp5IMI1LDJxFJsaIgpFWhJgKvI4AE2Ok20tI0DZgw4B6R0nf7UeiDSl2mXGjOaNE63ghXTfP/ZW25QF4dYyr9LTiEqNwWGSuKuQDKuhyRxXK1MlRY3wxRIGp4jLHFMFM1cEV6xih1c8qw9CsWbMwf/58vO9978N9992Hyy67DACwePFiTJkypeMdHFZrZZwhemyOFYJQxXijKiAkOM+qQ25bOc51b9xQpo2KEFTSRFDdcVQhqywfhEpBKblPmfvnxl/lqEOmDxqOKBDRfrvB0zGdrZ6MKRRziIQDsYAYpEHTqSoUJxFiHqGJCE0WyQlWWTrzvAaiGEK5xbiJDUoByAYhCkRcCHCRmIDpKiAE2EBhwIcE+mr1qAiMOIQaE4iBC45Iucu4gqBE8EzgtXSdCfMwp4qReagLJ8vN+lj432fqGqQKkdxOFR6qCFUBoLx7G4Iin1V1kdH7pMGnHfMBlwtKrapCRUHTwT4VuMdCVxwNxbxhnfsqrc2xyjB08cUX4/DDD8fNN9+Ms846C5tvvjkA4Cc/+Ql23333jndw2K3DsqQXVPJAKBML08aDvQLYyQd+IwWjkMurE18A7cCSz4UY6pNzvyopc06KvRco8+DZNxCjlY5Pz8XT2CgaRO1kj+lUegNFcbEqRF1kgyyddV67ybQ6FCvgiQkIaddYVhlKrOyxoqBp15ggMETihWQbKRz5wMh+FQZaGoiMIkJT8t3Aa+1WY9CxQ3KGefPAJyMvUyACYEApz7i1bt8XvS9Rn8sq8BP6iykTD+RzR2WvTQ8vYLvIfOZThbzrOaqQjhUK9bMVVcit34k4oWEFIdQxQ920SjCUJAlee+013HfffZg4caK17+tf/zoaIZWgtrBaUwWEfPVCIBRSj9yHuW5Lz1YfFbyHJniaRB64cUOhVHPTj4rw44OFsse47kQfCBVllFE3Ygh4XHej1c8oe4xxr6k6VEXTIJTE8nzKLQYNR44qRGOFRFKsCpnMMaMQ2VNs6DghqQ4lRhGiylCTJ0YNSgQ3EOSOK1QmnoVCE1V+ABuOEuiHtANGjkpEQYgpMNKglECqQ9SFZtxjIG43pOMcURCgYyCpdzbX6CfVN/6Pjh9y75Vdt7zlxQNRCyk6RTFBvsDpVi1tJ7WyqlArQdP0HGmb1eKEvPWGCIRq665V+iw3Gg3su+++WLZsWWbf2LFj0dvb27GOheyyyy7D9ttvj3XXXRfrrrsudtttN9x+++0AgGazidNOOw3bbbcd1lprLUybNg1HHXUUXnzxxa73K2SC87AaVAaE3GPceuQ8uceG9uVthzK0vGnrPHXvDLX50ueB6iAkeLpQc8vcdjL3kIfVKR0QTfulj6EgpOOEYjUxq+CFqpCI01T6JGFIeFgVasJWhSwQUu4xM34QuBeEjDLEtbuMZ2OJhJD7nUUIYVLxjbsNgrjenPZ4ep5EZ7MpVYo7SlWTK3jjiVG3miJB7Gw3RYIBxwVoXpU6pocRMMMKwL5HA2ppllhikClMoOd0c+6VWjhgMs3K/jMfJf8nLwM5VPXyWVHgdChWqIwq5MIYzSDTbfvcXblusg66x8oGTA85CPEOLrVZVtlNplPqZ86c2Y3+FNrGG2+Mr371q8Y9d/XVV+ODH/wg/vSnP2HjjTfGo48+irPPPhs77LADXnvtNZxyyin4wAc+gD/+8Y+Vz5VJSa9wTK4VKRF5afR5D+VQ277z57nMaBB1YVvcHzdUpA7pOq1aXqB1jisyF4TKnNMdZ8h3njxXmTWrPfOfl8YLCQnN1phCVBVyBljkiVwS5SJLBMvGCqllkARNy3mx1IjS4JZ7LOaJBRoUPmS8EDcuMnkLimOGErIvnY5DxQkxZmarN2XKZZUIYalGqZtMKJUp60LjQpi4ogaiYBYaHe06VYhSJYhOIiv7hOw15Fieq8vnUiybJVbF/A95RuDFHzhdFCtUFoTsNrPuscjpI/OUu6pQ0bW24h5zbUSAEGo3WTeNibJRjsruvPNOnHbaaTjvvPPwzne+E2uttZa1f9111+1oB8vYxIkT8fWvfx3HHXdcZt+iRYuw88474/nnn8/MqVZkby48ulNdlFZmgL9OgpBv1GRnnUXKhcPUq95uNNJ9jYYsd16Z3tZlLErBxxdE7MbH+OYcE3RdKyQ6FoioJlTtseoI+76FVKE8EMq7b/Km+e+h3qfvI2P2/dD3WW8DJn7I+pJLYuUWUy6xphpnqNmEGBgEBpoQ/U1rXKFkpR5XqIGBVT0Y6O814wq9IRpYGTWwMmJYGQFvMuBNJrCKCawEx0ok6BcJ+tXrgIgxKGIMiARNLteNysLjjPJDY4VC7jHhgx/H3Bns09vvuqaYPX0HY5l98jWSYw3pOs6rjhnSx9AxjKw50lQfXDjy9buqhYAnb04x16z75oCavha9Ly8WSgaTy9o+VUjud8GpNVWIusMyU57AVnloeTtjCnUyTigEQgcvuc5b3il79aA9O9bWxJvu61hbq4NVVob2228/AMAHPvABe24b9WsrSZLQoR23JElw44034s0338Ruu+3mrbNs2TIwxrDeeusNWb8yFqL5MiDkq1sEQqHzVcmOK8goS/tEYl1U2FE6FYewgajbLjSfi4zubmG8Iau8lcxCVxmjsUJRZEMQdwBPjyVEs8hCqlAMJCSLLE4iNHmEpoiQaNcYSzPIYgavKmRcYd5A6dSVpcGHrgOwFCJ5Kb4fAORBRD4fiXpAuYpQIlKVyKhGSOFHII0XSoxOpDQfwU1cUYNFtmJE4op0FppvtGvdBwuOCGC4I2i3aiEwou2WgUrf/lAAtKsKZffZEJXd1xoImWsrcI+50ANP2UgBoXbip0pb7d7qmlWGoXvuuacb/ahkjz/+OHbbbTf09/dj7bXXxk033YRtttkmU6+/vx+nn346DjvssKFVrIqkzCIlwoWcToAQ3R8xG4y4gJ6oFdZzO5BRloGgIfkayFpZybgMjFaRnw3QuPfQ+erMwKBTJwS8cWzcY9DjC3ljhQRxkUWpiyyJkHCGWEQyVggyONiXQZaoWKEY6bQQTQpBoDCUWK4xCkJeN1mJbDKdyeXeNw1J1F2WB0YGiiD3+V1owgqyttxpeiBHAkKCMUCkwMCJ+qThKA35lhOwhlLtWzF9Xygk+YDLHUfIBoesO4tZqk/WPRYxloEPX9B0VRCC26awAaYIhGj22BoJQijnza+tNasMQ3vu2TmZrlXbaqut8Nhjj+H111/HT3/6Uxx99NG47777LCBqNps49NBDwTnHpZdeWtjmwMAABgYGrLJ4MEZfTwcz5LzxIQUg5KnrBaEqGVFWFW7HRHEFOvqyufBMy0Fe9TGZNgDvgIJDaWXudxWrpKx57gnN3gOQHexSnUO7+nTQtAZiVxUa5BCDQDIICUHNCHHcMBlksbCDpmOQmCENPuqVqkI6aNpShFT6fMK5iRFyQciFoLxpOGwTGYiwIImCjweMIsCCIjnOEHKgKDJxRD4oMgBE1CJarvGHMwogzPTbByxV/gL0vaAwScFIt192Ko28tHi3j6GgaRt27PaKQMhclwEqlIoTArIgROuWCZjuNggN08/A2rpglWEIAB544AF85zvfwd/+9jfceOON2GijjfCDH/wAM2fOxLvf/e5O9zFjY8aMMQHUs2bNwqJFi/DNb34T3/nOdwBIEProRz+KxYsX4+677y6lCi1cuBDnnnuuVXbGnO1x1t47lO9YGWz3ZokVBPXmxbuUDQK2VBDyJ+yqQ3T0aa0U6YBqE8MTARGH4FE6vURoJnY6oKATKFvafGPxhCxQLxPY3qoqVKoPHgWIzgsHIJ0bznGT6TR6PaZQsyljhgZjiIEmMBhD9McQ/Ry8XyDpB+L+BpqrGhgc6MHgYAMDzR70Jw2sQgP9LMKqiJk5yPqRzj/WT2KFBpCY0aYHRWwyrwZ5bOKEZPB0mt1lxQqBwJA14GC5eyuEByCoC00oSBCpa8psu/FCJMZIAw2NLYoEN/sST0wRQGKRSNo+PQeANKDaGRtJ1wtdS6gOBSrZnipn6fADDMyjBJE+k/PRYQKqKEIy0DwbMN1AjgoEPwi5MUKu8uPGDcEp98UI5WWZdRqChlsJylitDHXNKr+nP/3pT7Hvvvti3LhxePTRR42asmLFCixYsKDjHSxjQgjTDw1CzzzzDH79619j0qRJpdo444wzsGzZMms59b3b2OnWRUue+VLp3VT0KiBE23PPr/e5i9u2qptRmsi2H8C4/arXiaKRqQvI/Z3MwGh1dHBqQ5mdkbnPIi03qfVCBYpze/oN7SprJo57jMlBFj3jCsWMydggtSQAYpa6w8wiuEzphpyPTIhUGeJK+TFTbijoKQIhN91bp9K7i9nv++fU5eR8+pyc7lfHSPXKVa3sYQCo689NzafX5E45klHMQMdZkqqZqQeloJE6wumvXgBY6/Ke6I9Ktc8oDZoustDgij7X2HCCkM+NBnIMgvv8IORTo0Y8CKHa46idx9WaaJWVofnz5+Pyyy/HUUcdheuvv96U77777vjKV77S0c757Mwzz8T++++Pt771rVixYgWuv/563HvvvbjjjjsQxzE+/OEP49FHH8Uvf/lLJEmCJUuWAJAZZ2PGjAm229fXh76+PqvszXZcZLlj/eTEDOXFB/lcYlUUjoxikeP2oUqR6yrT+xuAmXzU9xWhFZG8uKIixaeKKjQSzR1iIHQtBCZNbJCBIOkWAxfyNRbWHGQyTkiOK5RwOd2EjBGSS6JcZBKCFBRBoKmhRz283Yd/OteYDR00NsgFIReAim+Pvw5j9mCMDIwEaUuz5hmG/ARyVRYJmAEItXstEgB0uJyqGwn9KuPAtHvOxA5plxuEKdNuPa7eXzlgI3FZUVcZ/XNzrtE8vBkzEBR5lJ+QFQVIl1GF5H0s5xobThCC0wZIuW+f3B8GIfs+Za0Vl9iQBAOM4q/CkW6VYejpp5/Ge9/73kz5uuuui9dff70Tfcq1f/3rXzjyyCPx0ksvYcKECdh+++1xxx13YJ999sFzzz2HW265BQCw4447Wsfdc889mD17drWTdVI1yBn7xlgVEMqBIN9YFMwN9KVBwAAEuPxqcwOp9ZPDdZX5AqmBrLuMXn8nA61ZNPQ/bzqhRLnmDgmg1CAdOE2Dpl1VSOiAaU8GWZMxAz46g0zHCjVB44IIAGnFBUSBUeoHLZfddT5zBIR8+8qafsC7WVPUTZQHReZjq0FH1yFlLhBBaNBREMIi82ei4YhCkbtustsIBFEoSy+ErhIAIq4+DUL6VSD/Ietzx1V1jwE2COnj3BihboEQdYEBEoTcsqECoVbUoCGBoNq6bpWfTlOnTsVf//rXTPlvf/tbbLrpph3pVJ5973vfw3PPPYeBgQEsXboUv/71r7HPPvsAADbZZJOgHF8ZhDph1P1hlXvcVtQt5gMh1y2WqSvM4jNrnw+ovH339cNxkdERlbMnzbrS3HOE9rVqVYGrFcBxxhkqbfTzYLnFRHq/PdljNGga1EWm5iCjGWSJYJYyNMhkGr3lFlMLzSATyLqEqDsMAIGQ1BVG0+ppHb1ecRgzvwuNbFP3my97jbrOdN+Fr0y7wbgzVpICQKstCoeedWsbznmJ68u9Dve6y1oGgDyqUJ754oRc6GFOWbpdHYQYbBCKhB+EmKgGQrode58wIET30+PS+2DbaACh4XKT3X///TjwwAMxbdo0MMZw88032/0SAueccw6mTZuGcePGYfbs2XjiiSfM/ldffRUnnXQSttpqK4wfPx7Tp0/HySef7J3NImQLFy4EYwynnHKKVX7MMcfIuECy7LrrrtUuEC3A0PHHH4//83/+Dx5++GEwxvDiiy/ihz/8IU499VR85jOfqdyB1cJ8D7kQAIUgSNeBhI8MCLn1HQjynscTM2Tq0zbVttAPZNonst+U6y8Nq8x5wIdAJ3R/qthwpPK3OsYQEI6TMvcxve9C3xuqEDmp9HwQamZ6qQzRDLKmTqdX8UKJihXSrrE0Tsh+gCceUHBdZLLLaZl1KSUe7qLE4rYhPOfW56NxRb5MNg0j+lgfELl1XSCi98KFIxeKrPM7AORCUahuWfMFZJdVhXxxQi4I9ZAyRo9pAYRg9mVVIr2v6mCKtJyCEJz99NzmPqEcCLnHUfO1MRQ2XDD05ptvYocddsAll1zi3X/BBRfgoosuwiWXXIJFixZhww03xD777IMVK1YAAF588UW8+OKLuPDCC/H444/jqquuwh133OEdKNlnixYtwne/+11sv/323v377bcfXnrpJbPcdttt1S4QLbjJvvjFL2LZsmWYM2cO+vv78d73vhd9fX049dRTceKJJ1buwIi2dtWKPMUkUC8435UHgoLncfvtyWQSXCUI+wIvzLZygzVkv8yYQ+AwmWEqzV4gAnNDrNzssg5ADFN99+9kYfDothXBUqhfFIR0Gj0ZaDFPFdIuMp4wcM5MvFBMQIhOvWEDke0ic11h1EUGwHKRhS8xoEoW3btAXXpHaRq5tQ5hXGccMJlX2gEkhJDuMdKaKRPyJJm6AiaOiLFIwY58ixn09B50nZk6APmTUueLVP90bBDdpn0tMrceBR9v/QpxQjbIZEGogdZAiMLNSIwPqhobtKa6xPbff3/sv//+3n1CCFx88cU466yzcPDBBwOQ02RNmTIF1113HY4//nhsu+22+OlPf2qO2WyzzXD++efjiCOOQBzH6OkJo8gbb7yBww8/HFdccQXmz5/vrdPX14cNN9ywjStsQRkCgPPPPx8vv/wy/vCHP+D3v/89/v3vf+O8885rqyOj3vKytwA/kjsusWDGWAiEQhlJmb45+2g7jhJkqUMe9aiSOkSvXffDe+865CJzjcQsZeaXo/FMRSBD9/um4mjFzHsi7PurFSEdNO0bYDFGGivEVaxQ0sgETuuxhdLAaQlCXJXFal1DkHCUDldBAfJdZNrsLLHWzacU+dapUWCz1onK5bZJlR1arhUi2ZcUEnXbdF3X8W23Y5mHd+Bx7FOF6DFunJDtAmNwlR/XJdYqCEU5ZdQtVgaEqHutyC1WpAZFQoxKEOqkMjQwMIDly5dbizvWXhlbvHgxlixZgrlz55qyvr4+7LnnnnjwwQeDxy1btgzrrrtuLggBwH/+539i3rx5eN/73hesc++992Ly5MnYcsst8clPfhJLly6tfB2Vv8mPPfZYrFixAuPHj8esWbOw8847Y+2118abb76JY489tnIHRrTluZzywAcIa5IZt1XAJeZ1YxEXlwtBZfpL6/uAyHWXmfppX9P2XMBSsUMhdxkFolZjhQIDRwIorzqFwKdqeVnzXS99v9R9F3Fi7p0VNO2oQtJFFikXmYoX4mpCVidwOgZ1k/ldZDSLzKTNExeZtjwXTice+uG2nW1Pn9wYIrdPbt9dF1peOQUiU6cEEFntOv2r6hZzB6R0wafIPQZk44TcgGkKPg0HjDLjC1UBIeEpQ1YNcuv62gCqxwYNpUss6uLfgTHBOrYsXLgQEyZMsJaFCxdW7pLO2J4yZYpVPmXKFLPPtVdeeQXnnXcejj/++Ny2r7/+ejz66KO5/dp///3xwx/+EHfffTe+8Y1vYNGiRdhrr70qg11lGLr66quxatWqTPmqVatwzTXXVG1u9bAih6wHmnIhSD8k9YOSxgX5oKalxYYsLxCZbbKurxdIYYdCkM9cIKL974T5QMgzKW3GXLiKWHbJq1/FfNBq3l9yf83YQgKIeVAV4nGEhMQL0cDp2IkX0mML+VxkckwhEn8TAASAPMyH2BXZztl8io//HNnyTFYcBazAunveVkHRHyRd0p1WIk6IgpA7+WoZEGpAxhU1lAutxwc9HrABqqtBuryV2CBqPjWoUxA0JCDUYfONrXfGGWe03J4bx0bd2dSWL1+OefPmYZtttsGXv/zlYHv/+Mc/8H/+z//Btddei7FjxwbrHXLIIZg3bx623XZbHHjggbj99tvxl7/8Bbfeemul/peOGVq+fLkJBlyxYoXVuSRJcNttt2Hy5MmVTj7irWqUmbZATEtmFGRf3I8noNpazxtzCPm/NpkJYmDquDSqQUD94ZvUelVHb6t1wdVXKFPH6yk6ENnjDpmmI1jj7AgehopW7re5FloWeUGLRZF8D3zHFJnHrZbrItNBJr5ywAYhDUckZgixnP7CVYVEwtJ4oTjNIKOB000FQu7YQtpFJhdBXkmQrydeaLSZjuMpa74vbXesHz3hayfP65rbB19LZVQheWx+nFAohT4bG+QHobLxQbSsSmzQaIgLGg4AavWR5DPf2HqtmI7VWbJkCaZOnWrKly5dmlGLVqxYgf3228/MKdrb2xts95FHHsHSpUvxzne+05QlSYL7778fl1xyCQYGBtBoZMcCnDp1KmbMmIFnnnmm0nWUhqH11lvPpK1tueWWmf2Mscx0Fqu9FTxQM/DjOyYHguzYoDAEWQCU0yehvgFYplsSZmwgYrDHHlJfbUxGmLCIKWgifYsYwCEfI0VABMA7NxdQXjEqM9ZQUZ2ybWjzAU7ewJWukfgvA0J6gEUVRC2UIuRThZKmGmk6jpAkMl7IGzgN20UmiItMD7QoQEZPRtblU9bkCD3dezBUxQsKJJ2cOFUbhZ52AIhOI6ItM0UHYwZmgu143GOyrXCckOve8o0l1ENVIqEhqNgtBoTVIHjqgdSjkFNGCbLvg23dgKDhVoAE7/znuV2bOXMmNtxwQ9x1113YaaedAACDg4O477778LWvfc3UW758Ofbdd1/09fXhlltuyVV7AGDvvffG448/bpV9/OMfx9ve9jacdtppXhACpAvuH//4hwVmZaw0DN1zzz0QQmCvvfbCT3/6U0ycONHsGzNmDGbMmIFp06ZVOvmIt7IKT5nj3LIi+AGybhUQ8PFBUQGc6YEXBSAf4HKCJzCdQhMxiChSZWq70ZDb9FxCDQZnohUZTMB0JN0/Aj02EAG2YhMFIKQsCPnUH10mSL+4vW6pQ/qayrq/CPRUCpx23msrSJ1mkMWJnIdsoAkxmMiJWNUcZPFKIBmIEA9EiAcjOQ9Zs4GBuAf9Qs5B1s8YBhjDAINcIDDA5GSsA+BmwMWm4NZAizS4OFF9tQKlcx4AjKWDIOp1q0zfgvJ3K207cD76KuuFyzLlZO4y3/4yFoItHxT5+kGBh/Zdl2dje5g5toEoqAgxxiyXV0O1GDE6rxizIKeBrDusVQii20UqULvwsyaAz0iyN954wxpfcPHixXjssccwceJETJ8+HaeccgoWLFiALbbYAltssQUWLFiA8ePH47DDDgMgFaG5c+di5cqVuPbaa03ANgBssMEGBmz23ntvHHTQQTjxxBOxzjrrYNttt7X6sdZaa2HSpEmm/I033sA555yDD33oQ5g6dSqee+45nHnmmVh//fVx0EEHVbrG0jCkZ6tfvHgxpk+fXvkLZDRaIfQA+epQCQCSxTkQpF5DEJSbYu+YIK4b+u6JiKpFjkqkvtVEnID1QPpeehqQeoNupyGPY+nXGRi3FSI6LYdWibSZ1P82NGAXjui2Vn9cIALKucwc5ScXhEIqkxuE7mSQ0QEWoV1jg9xMuyF09piamZ6m0jeRxgqlc5Ahk0GmM8SoqwxIgUeQbSDsctUjMMtbp6HHmT6DAJHcr25P+M5l6lplge8bF4SCoOK0mnVJOYpMpn61eLG8c/vOT+uGvll97biKUMg1RtUfF4Rcd1gRCDVEFoLSvpRTgfIgqKz6syYCUCfdZFXsj3/8I+bMmWO2P/e5zwEAjj76aFx11VX44he/iFWrVuEzn/kMXnvtNeyyyy648847sc466wCQLq+HH34YAMwk69oWL16MTTbZBADw7LPP4uWXXy7dr0ajgccffxzXXHMNXn/9dUydOhVz5szBDTfcYM5d1pioOkQshn/W+qGyN874ULpRJsYkzy3iqVMGggD1UKJg5IsXck5DIYm5bhzzTcXSfSpgmDH5ip5Gul+rQ6pMbkd2OYvkMYzJfbosimQbal2eS/vrcr6ehHtP0iBsQe8XDeymQco0k03Dh3PPcmO49D1xLANCZbLNQiCkMsiETp9vxkCcgK8YkCDUz8H7gaRfqkLN/gaa/XJ2+oFmD1Y1e9DP5ez0q6IIKyOGlRGwigErmcAqJrDSzFDP0S8SDKqZ6vXs9AMiQZPHaAo5S31TzVafiAQxTycwFUIEZ6rPzerqQLC1q+yY9QAIURDIndGeHM/A/PVNnchut8o6WEYVMud0zhNShfLihBosslxiWh1iAHpUO3QWeqoGuUqQiRnygFBPRTUoD4IsqCmAoCIVaLgBiPZ73r9+1FZbRfbP3fbqWFsbPXR3x9paHazazx2MzFnru2Y0+ypU7tZxs8qcOta0GVZml6euftCQSTrt4yBjdGLSLpnU07SjytI6+thsmwa8YhXEa2JahDUoYGaUZJ1N5skws1LuARtYfFb1AVoGSDxTaHjBJpRJ5qtfxoKKELdAyB5fKI0T0nOQUVUo1rFCgiFGZCtCAAmYlkqMXHSMEJkt3QEZmipOIYY+wH3GHAhx4aVVFdk9tl0Q8rbjicnJU4XKuMhCqpALQq65IOSzMgHTLgjRGCEXhKgSFAIhnS1WBEIRpKuB7td1aLaZLBPpovZFtD2yADCZYBqEaF3r/niOzd5nYS2tmOnzEAtJnRxnqDbbKn+761nrr7jiCisSfPfdd8ejjz7a0c4Nu+VBDxD+hDl1/QBUAoL0w5Eeq0DGABAFHwM5gSXWdTQgCVNuICrm6bkVFOUCkX6gW2UVgchd2jEKLCF4aSH2pzIIWe+/B4QckNQDLIqEOyNNIx1lWk/MSsYVSuEnDZ6OmT0fWQyBWKTZY2aaC7VdJWvMjXehSosuo9umroKTPDBy5xdyy3X7ZUDI1988QIo85/TF9mSuO2edtuVbp6qPzz3mU4XSfXQ/LPeYrSyloKTBxNQhAJQHQmXig+i+RqC+BUEEJijUVAWg4YCfoQag2obGRt2s9cNmeSjtKEeZQGbLneWJG6LuML1NY4K0CkS3AbvMtJlzDVFah6lYGaECp+XXo3xAsphDRAwQ6us0TiB6GpDD+TVU/FBDfgvGCdAjFQxTZkdNAypuKJNlZqoEQKNj4xDJa7Uyx0iskAYdX4xYSxCkTLhuOgPAGkhJnBBPp90QsYAYlPeUNyMzIWvC9cLQVPFCCUvnIdMjTrsTsWq9JwF3UuuLv9XdWCAA5gGs44VkDJHIHOObgV4fX8by4nqKQMh1g7mAxDwA4+6Tx/rdY5n+eNZd95h1TtjnNOsl3WPpNQIu9LhxQtoNpucbo+nz1msBCLnqEIUgOHXptrxGYcpA6sj7kVqRC6zok9NJl9dItJGYTba6WGUY0rPW64AnbUM1a/2Qmjfbyf/X0hEAouUO9Hi31Xq4D+o1srfN/F4RFBghhSK1znoUIOj0eh8QAQAaKRBxlpa5AdUuENH5ygqz89J4oVyzgqaZX2UKAJHc1bobzLVcENJzjxH1DTRwWqtCTWYrQs3ITMiqB1lsQgZOmzR69cqRush0xpgsEwSP1LZnmgrjyiGZYr77SWHJziKzy617E1D/vJOPOo8/X6B0yDWm6/sASR/n7rPhxXaPtRMn5AMhC9jI8RnVivYPWSUoLXfVHztg2j3WyiTLAaEesh5Sg6pCUAiAfH+BeYpPVRvpsFNkQzze6RpllWFIz1r//e9/H3rW+oceeginnnoqvvSlL3Wjj8NrrcAP4Acgsl4ZgixlyOmDBUS+a0hXJQuk30wsUg8tAkWsJ5JqhQqgFoBMvwdsIOI8hR+uH7tadYogH8vacoAIaF0dKhonyGSxMf972coAjAWWC0JCjTyu4oS0mzNVhXg60nTMjCoUxw2jCiU8QhNq6g0FQk2WZpC5LjIONdYQiRcCkFGGisYKihiTiYECavLTrDpkTaaqPh0+ZanIQhCkz0XruK46C0QCSlFZEMooRyVByNR34Itejw+EqFEVyPSFXJ9RgkxdClQp2ESgShG8IGTHFbUGQiEI8qlAeQDk+3SUAZ/RDjq1Da/Vs9bnGQWUwD67rCQA0f06Hsgqg1Um4rAiZDigCIi0ReRVP9kIFDEwAkKA6FFus54ILJYNp0Ck9uu2lZvMpOG7gzL6gAgIQ1GrbrIitckFKDrmUBsm3PffB0I6vkpnxZH5x4Q1/xhD0mRWvJBWhZrW1BvUPZbOSk8nYaVB0zpeqMrAiiFVCNAQJM9D3WWuStSKudDki8cpAqGgOlMRhPR6WRDywRftB80e87npfO4xe7+ur1UgeNLo8zLHFMQIDUfFIORLqc+6yLIQVARA7qcjD3zWdOCp3WTds8owBMhZ68866yw8+eST4Jxjm222wdprr93pvg27VVJ/3P00dqRojKCcmCCtBNmKEFqCIYsB6Lep/nYjEYpGJUKkXgERpY+hDBBF6okMII0rQjouURCImOyUdkmEIKaV9Af9EPepQz5FqQ0ostQg3V8HhIxbzIwnpAOmuQluF4MiVYU0BOn5x8zYQumI003GzISsRhkyMUIkaBrp+EKAcqGJVC0KWcQYEiGnpuAMBor0thAiA0TyNthTXJRJsfcpRj53GC33ucX0/k6AUDuuMX2OPBDSV0TdY3lp9HacEFGHGIUe5kCPXreBqEfoY/JBqAfFalAZCArGCXk+f1Wgh7UZJyRahPXhsBqGumctwRAAM2v9am1V4MfZLgVAQCEEATpzDGSfZx3hdW103DiWgSGk324aiHpSlQjg0n0Gbr46LCAClBqk9yrXmZ7Kw1JrbCCS/XF8eYELscYYCl1onhUBka6jrQQYlQUhMxu9EyeUuseESaU3MUJxOjO9VoWsOciQzkOWQCBmKQhplUiDkJluo42Hh3aVuaNOayACslCk61U5B7WqEKS3vUASgCQNQpXgp40YoaxbqxiE8tLoy8QJ2XOKufXaAyEXgqoAUAh82oWcslb1PKMJnmorb5VhqL+/H9/+9rdxzz33YOnSpeAOIKx+6fXl1B/AA0BkvcgVFowJ4jKrSG7DAiD3FYL8EvcxAumWPjdTKpAXioBUJdKddkawzgCRczqmRquWbfmBCFFE+sOCgFM03UhLVhhzxIJAlHGLycIwCJksMjdOSLvHJAzpMYV4EiGJo3RcIUcVMun0oPOQwcoi4yqlns4/pkecpvFDvnihCAyJcp2CqEKAelALCVY2ENmxQi3P2+U8cFwI0v2jZaEA6jwQSusNDwi5fckDoTJp9DROyJ1qgwKUzgxLVaJiEDJuMgeCAA1jWQgy6lAB/BQBSSCi0GstOtdL21BBms/qAOruWWUYOvbYY3HXXXfhwx/+MHbeeedKv/hGncXqId4K9ND9LvhkyvxuMPpqhjESjEAQM/VFEQgp06ILYxSGhCxnwsARU996rEft72FAD5PfSj0CooeDJZGJJ0KPABMSaliPUBDBIZQLzJQ1GjDjEEUqpohM3CoUHOVaFVXIdZUBWcDJAyIPCFWCIBoszQUwGBvXmBjkasoNDjEI8EEgGWBormogHozQbDYwMNiDZtxAf9JAv2hgEBFWRXIeslUR0M+y85DFEGoeMoEYHAm4hCM19xgnYBQyA0LqAUxdZQ0FPzrkDEgFQb1P3dhKsUneub0K4MfaLglA6Xr3Y4P0eihYOgJDQ4GYAQhGYSaFIDsOiKFByhvwp9DbZdI1prPGDCwJ82edgSArnd6jBGkAslQhJ4NMlhMYyrzL1WAnz3gLbXUbnjpptZuse1YZhm699Vbcdttt2GOPPbrRn5FlPrcXLaf789xfujxP/XFdXwEIEpzAkAeMZHn4kljKHfJV0DImwaeRQhEA9e1CfgKqdHuhLsKoRGrdKEJ0HCKuvu71OEQZlYilsUO+ecuAcDxRJxSjMrPXo0UQIsHS0kXmcY2pVHodMB3HDTMHWZOm0iv3WHaARZisMVcVSkTqKvNek5vtpR5dNHBaq0NaDQJgucz0w14rRdDlFX8sZYKmiUJUBoJ0X4PjDQ2jEhRqxwdCzGon3zVmzzGWghB1iWkQMipPCyDUcCAISEHIB0EagFw4yYOVItWlyEXltl0GdPQxowmKauu8VYahjTbaqPIEaKPVvABE1ksBkCrPqEBmnR4HLwTx2FaANBTJPupjmfWaZywSQKLAhwOAWldgpNlHcPWLz3zDCLJeAogAZNLudZkPiADpOpOdVKcJfEUNxXjyriLoiw3S23kgpIKlEfOMa0zDUDIIk0qv44TiJEIzacjRphGpwRU1FNGpN2SskE6n14vETpJJZl7Tz3ZRYLNWiNwyK3ha358AFFn3sEQMkQ+AgHIQpOu1ogYVrnuhKgxJpoz039eOdoul9f1jCUmIkUcXpdBTcKKDLFoDLpYEIQlMfjWIusFCEGTHDbX3wyXveB8o0XMXfWOMBiiiHoDaOmuVYegb3/gGTjvtNFx++eWYMWNGN/o0sqwTKpCqE3SFAV4I0tDDE1sBEsKGHxeITD8Ffaik/dereuwgCkIsksdFSh3iAmAN+cUnOGSQtPlCKgtECM90n0mDJyoRtZByY0GqZ39ZN43bdrdBaJDLzDHlHpPzj6mRpuPIZI/JoOnIzExPVSG93kQaK6TZWqpEPA2eFjYQAX4QYuqdYywChHQTa3WCqzfPHzydxg4BNtDQgO085SdYpwIEpf0dHjVI73fdYrSuCz4hEGoQeHJjhDT0mDaRKj503Y0RolljDdOGem0BhFwIKgKgTrrDXKPnaQeMRjIU1XOKdc8qw9CsWbPQ39+PTTfdFOPHj7fmJwOAV199tWOdG3YjGV6hWCCzz1vmW0fGFabLfe4woZQhDUBUEUrXU+VIds/364Eh0hSUMCt2SIKQrQ4JDkR64nmoX/rWN1kAiHQ8DhcAk2DQEhCZVUZunGMhEGp3Go9OgxAJljYp9IGJWHnCkCRkpGnIyVj1tBv5qlA62KJ2kXHAAiJziW38Qg8FTwP2A8QHRnltUrNS6itAkK430tQgWtfOCoN32x1U0awzCkape6zHlNhjCelBFa3yDOxk3WVVQIgqQWnskB+AWlWGXLgpcofp84TcapHnmFbqDLX5v9tr64RVhqGPfexj+Oc//4kFCxZgypQpq3cANfcMiAg4ri6/+wtIISgvHkjWgxeCbGWIABGBH/3HkZaF3w8O5SIDwMzIwQATzAtFsp565alClJoNRIjkQ99VhaxxiPTAjCCjV2sgArLxQmXigdqFn5yfW8G0eX3ePBDS2WMEhMSgJ05okJlxheI4zRxrKlUoBtS0G1INckecpoMtavXHrDvB0jp4uoxpd5g94rSEKxeIANhQJPxusuC5nLp5gdN5EKS3hys2SO7PqkG0bto+CPTAOo8OkrYCp52A6VT9sRUlRl9FCimMvPY4+9w6IRCSapL67hCpGuRCkA+K0vez3OeP/IzKtBOCoypQVEYBGolAVFt3rDIMPfjgg3jooYewww47dKM/I8pyJ0XtUDyQ3qchKAM+GoYcAKLwE3KTyW4SRQgwsUIAk4lW8okGxgQilU0WNTgYl/OXRQ1hVCKtEIWACJHtHrOACMiMQ5QBIsCjEiEtz1ycTy0iZVbMF1WOSHnAPZYbKK3bKwIhZ1BF7SLjg3IiVh0npFUh6iLTQdNyTKHInpAVVBWCFR+UQM5Qr//pLDKo/WUeQ3qgxZAxMAuIdNvtBE4DfgCi5VUhSB+TpwBVhSDffgpBhW0R8KExQ76sMZ8bLC9OiLrFQnFCND3eZJU56lDkAaEeIXLVoBAEeQdUzPlo0D9N99gQHFHQaRWKRgsQ1TFD3bPKMPS2t70Nq1at6kZfRp5VTY036yiEoJAKRCFIr/OEGQBy3WSuMqT3WZdhHhCmwMCPCaRmTI40LQQEj2TMkKMOAQVAFAlzNgNEEVMz1TMyuas2AkSCSZ+cVokYSwGmymSuvptQBoSsmLACt5heLwlCduaYMHOP6TghnjAJQSqDLOYRYiHnH9MZZINMjuakFaFUFUrnHrMDp9MsMkCDkHogmOyy8ioRQGOHhAVERYHTZWetDwVOl4EgvT2SXGKZtjTgZOCoGIR6iIJkUuvJtlF0CBD54oRcV5gZR8iCpGIQorFBdNsHQXnw45qvrv4zpG36wKgsFI3mQRPr1PruWWUY+upXv4rPf/7zOP/887HddttlYobWXXfdjnVu2M1yd4VcYN2DIL0/4ZENR1QZErYfueiXgw6kjpj8QmFMuswi7SZTUARwMJGqQ/RrxQdELIJUP9TNYNL/JqEAJEZIZZalpoEoghyEkQCR7HAWdHwutfQG2NvdBiE611gIhLRrjARM0zR6e6RpNRGrCppuEggaZKlbLIHAIBPWXGQpGMmxhdJMMljqUBljkHAaCZ66yvSDjrEMEEGdwxc4XQZ+fPWqQJDcHlqXGIWgvLo+NYiWFypCBIR8ShEj/UldWtodlrrLfAHTPXSfSI8tAiFXDXIhiEJNK3FCFtiQtlwwcqHI5z4rA0QjSf2pbXisMgztt99+AIC9997bKhcqRiBJEt9ho9K6NUZQGQhKklQJspQh0yUbiHSZ6XsgkwyQbjMDQkzI5C3GLCgSvIGowckXkf114QKR0LFIUDqRSpHXh1uuMz0GEbiissgPRIDtHtMPy7JZY50GIVcN0pCcqwjZKfRmuo04zR6jqfRxkk7E2mSRGldIzkyfKCBqMuoqI0HTgJqUFWnwNFWBAq4vM2VG+u55TccQuaNNCwd6ygZO+yCJWQ/B1iBIt1PKPdYCBMn9YQgybZljfGpQek+LQKhByn0DK1K3mAQYmm1mv5qJWYkSZMETDZCuAEIuBLkA5HFye03/ZQbdYPorIABFIZWoDOjk1RspsFSPQN09qwxD99xzTzf6MTItzyXmUYA67Q7T5QmPjAKkgch1j5lt33WI9AtcbuqHl7AVIibQUK4yGWcUGZVImp42g6utFIhElJ49VYkUELkZZsZd1jCDMvqBCOm5o6j8N0HeFCoeEPLONk+PaweEjCpEFKFBpQrF6bQbejLWmEv3mEylhwma1ouch8weV0irQjpo2sxOD3uiVqHW6ez1ZY2mzWdS6smDhypFpdp1f6FT91gJCNJtdNslFoIgX10KQfQctNwHXnmuMQpCbsB0K3FCfliyQSjSZR4Qom4xCkJ5afT2j7LU6A83eowLRi4UufFFeSqRCzOj1V1Wu8m6Z5VhaM899+xGP0amFalBHtdYCIR8gdFlIciFIUCt62564oZCxphAooKqmZAP3IiJVCESDI2IQzAG6SoDDPYIJoOrI/dLhqbdq2/e3AyzBtKU+xwgArJQRK0olqhb8UEahPQUGyR9noKQm0JPZ6M3wdJxw2SQNZOGzCADM4qQDpqOQdPp7QwyqgploAhOAHXFn5ZMu8qMEsBMXJCbPQZk4aaM+QBIn4uWFUGQbqusS6wqBIXasfqGfJeYfX4/CDWsfVkQcuccazVOyA6cFkQlEqrdMAhRt5irBlnu8wAAIaeO/h5z//JdKCoCok7aSFCFauuulYKhv//975g+fXrpRv/5z39io402arlTI8U6qQYZGMpxhwkBJElkqT9CyDgSIZgBIAuKdF+dLwHrS4Ls0t87+nimZjlngkEoKAKi9FVoJShCAxKSeGz/zmpEAI/JaNWx1rAFEBMQiuR1molddco9jzJABA6wyAdF5IK82WTOl28RBNFyX7YYKTcgpGaeLwIhPsglCOnMsWZkXGM6jZ66x8wAi8Q9RlUh6R6zxxUKqUIJ0rR610VmDbwYcIvpWejpfhosXZQ95nPJhTLMirLIfBCk2xvKuKBOQZBcJ/AD2y1WBoQ02FhApF1duj4FIP0qnLR6AkJym6pD1UAovX7HRVYCiKiLXx+fB0VlgGh1VIfqcYa6Z6Vg6F3vehc+8IEP4JOf/CR23nlnb51ly5bhxz/+Mb75zW/i+OOPx0knndTRjg6LEQiqCkDuQIncQI/8QPMkCrrBXPhJeCTjP8BU+JJ6CCEfiIypLwv3lxuDkF9+jHzRMYEGl24yHnEVv8wQJQK8wRBxgUbCESUMUUOg0cvlw7AhYSHiQDQGqbIyhqkAFqmm+CZ2RcRkHJFalxO4MrMPgBkfCRGz469z378S8EO38wDICprmsm4srz0PgjiZc0yDUHOwgSSWE7HGSYTBpIFB3sCACpruZwwDEZMTsKplkMnJWJtMyFcIDIKjCS4nZRVyPRZyUtZEcANEep3Ckvzc+IElC0FSHQJgRkawZh5nLNNWo8BVFsocs8vz4Ufva8UV1k34kfXgnANWvyJSt6H6TSHIAiQHgnyTr1LXWAP2IIqhFHqtCBnViIwjREGo4XGLUZeYC0EUfso+ul1g4mrsM21CpPeQw1aJfHFEISDqlg0VVNWp9d2zUjD01FNPYcGCBdhvv/3Q29uLWbNmYdq0aRg7dixee+01PPnkk3jiiScwa9YsfP3rX8f+++/f7X4PiVUBIQk/dkwQj1Pgoa4wrRJxwcBJdphPAUrUQgFIgxGQglC5AEHdhjSm21O/BgUjyhEA8FQh0uqQ/QrjMmNMyMBg6jKLhPTtgEuVhwuZvq/hwmSWNWQckVKGzDlI7FA65UfZUEwHgIB8CNLbRB0KxgZpEEpSOMqAkHaLOSBEY4QSTlxjInKCpv1xQlQJMutaCVKwIzPJYODH3A+Sal/WXaYDpBmLIAT3qkKADTGl2nVgyVV/9LmBMPjofZ1whZWBoFAskNUf61r8EES3GbKxQSamCK2BUNkUep9rzBcjlL4ffhBqB4Lc+rqFiImMWkSVoqF0WxWda7SpS7X5rRQMTZw4ERdeeCHmz5+P2267DQ888ACee+45rFq1Cuuvvz4OP/xw7Lvvvth222273d+htRIgxOOwO4yqQTQ9XrvCNPzouCAXgrQSlIAoQ2nXrD/CMnF1JuuMxH8IZKFI1mVAxNEAkHBZ2wUiFnHwRCs36leudplFUCAkpHsslu42eS6krz0RcoEICXTGmWyt4tegL27IB0F6f0gN0tvu9Bpc+EGIps+TgRVpjBB1jaUz0qcgpGODmhBmuwk6npAcYFFDj84k09BjXmGDkaviCMeNpk0HSGfKkSpBFGryAMsXVJ2nAunz67KqEOSuG/jICYpuFYKoGyzdD+u8+ngWOK8PhHTGmAtCFJRSF1jqGgvNOeZmjlV1jZUBIfddLnKRuW4f/b2gjy1yC4VcZqH4oU6D1FCDUJ1N1j2rFEA9duxYHHzwwTj44IO71Z8RZVVAiLrF0mDpNCZIl1GXmFaFEh55IYhDricKggwQaVkYttJTZMbFAfmllwAqGyyFItMgExJAPEAUMQbBgCRRX8NMQhGLpBoSAQp+IOdXjdVXhnJ9MZVVBi7hgfVERpIScSJdYoKlbjOtEgGy0/YkaSXeRH0D8iFIrua4xXRskC4jo0pbgdIKhPQs9FbGGAEhqQjJucea0KNNS5dYjDSNnqbP6zghrQoJwIoZclUhPf2Gb5b6EAS55qpDQPrgz5uE1TVXPSpSgYq2c6e8yNmXlx5fJjU+rZ9eF40Fcs8bgqC82KCsyyyFHq0CpbPNa5UoBSB3qg1T19Shc4ylZSDH+EAofS/zQahMnBCtZ6lA8ANRq+pQO66y0DmGSw2qY4a6ZxWeKqPPLr30UsycORNjx47FO9/5TjzwwAPVGmgDhOSEmzI2SE++mfDIDKoXm2057UKiRh1OBEMsGBIotUAtCRgSxhAztQ6WZhWp8qIlzUSS25wBiWovBgx4JVB9AjP9o0HdCZfXxJPIqGE8jkymlHQbqvsWS3ejcAFCT1PBuVRdVFCypcxoSOHcKDKmvOxCXXI8hRrTjgmG5nIAxViVJYkZOdpyi+kyHwgN2iBkTbHhjiVERpl2s8f03GNyQtZ0cEWqCulpN/QAizRo2qcKAXYcUNWJWjUYMBZZEKPhosxCj9djA+l/EWNGJSnabrAoXUdkYKTB0nXfvh69DRnTRNtosMjAUkPVilQ9t9ya9sIcp0eClvV6CMg0nPP2eOKDyoBQTwkQsgZRRBof5EIPdY/ZZenngoJQ+jlIYwuBLAhFemR7+tlRiRl0cS1zTM4+11jFz3LIysLVcLrFhPkubn+pzbbKqfWjxW644QaccsopuPTSS7HHHnvgO9/5Dvbff388+eSTpTPj2gEhGiSdJJFRgVw1iAZHx1oV0tv6lZE0egBcx2uQsiKLIMGHqfqRkL+WGAAwgUgwxNAjCAt5hOCQEdQ0fkfF7jAGJgQSLt1lQgilDgnwmIXdZVyAcdjxQ3EC0dNQeNdQ15Yz5lAVhi/IGhM0aLrALZaqRPCDUBwGoaRpu8ZikY4yHbOsi0wqQsJyl1EQoin1HBKauNm2VSEA1muZeCGtBoVcZRqIhMj/9DGPihdyhZXdrhIX5AZHV5lANT0uLafHmLrkHD5liJ7XVYPy4oOoG4zCkhUL5LxaGWTEPebGCVH3GMxx2UEV0/cp3Z+WZUGIWl5avZsxpo8vdIsRdagVq+Ii89Wt44NWX1ttYeiiiy7Ccccdh0984hMAgIsvvhi/+tWvcNlll2HhwoXlGvGAkNnW6zkgZNYJCOnYIK22JEhdYglSGEoglRuuEIECkIkbYrSr4T/SiETa6C/ChDELivSs5NIpbQMRY5Az20O9CoDz1EUWdJcxCQp6yjHtLtOPZb3OEAWBSKbYK3eZhiKu4ogK3z/yZezECxVCkOMWcwOlhYoVEoN2sHQZENIB03oSVj33WFO5x/To0vJVQk9TucZo0LRQbrFEcFsNclQhWt6O6Ye+m2lW9jht1rhCbUCQux6KC0of1gydgKCQK8wtC0EQyLoNQFkQcuGIgpBJqxeOKwwojBOq6h5j1nsuckGozNhCtG4IiELuMlMXWWBxU+3zLA9sRioI1TFD3bPVEoYGBwfxyCOP4PTTT7fK586diwcffLBSW970eSdYugiE6OCJNEOMqkFuXJBWgzgkuABaFQrHCvmCqGVsUPrlIqFHZKCoR6iAQwYvEKUnkV9BUhmCgh+p+Oh1HsNkl4lIApHpDIdShtL4IaMCcTXmERIVMxQBEUv3g0BQUexQ3kjTJSAIXKRp8zwFoHQgRWcwRQeEUjcpcY0lDTPvmC9gOqavSLPHfO4xrsFIUDUoXxUCYMYeKhsvBCCjDlG4cccpcsGHtuGrVylGyIWYCnFB3YQgC9LI9brgQ9ezQdB+FciUCQpFWRCyAMeBI8s9ptcrusfS+0Q/B/paWwMhesxwu22KFKNccBrCrtcxQ92z1RKGXn75ZSRJgilTpljlU6ZMwZIlS7zHDAwMYGBgwCrrjznGqK8xaxwhs04WYbvG7LR5mNgb7oBQSA0SgAVEtBwACaLONxo0DaRw5EJRzBgiDUEOEOkvaiEAob64OGfm1xpLmIEjwSUAaYVIJJBTekhfDlx3mYh5GkAdJ0BPA/rMVmq9VoM4ZJo+AAuOzAXbX8aZ8YW8rrJ8NUi7xbS6RUEoGQSZayyyBlTUI0zrFPrYEzAtJ2F1BleEMLPSuyDkC5rWqo+OHXJVISCFINdCgy4CqasMSKHEBagQ/NBjfHXbgSC9XsYlFnSpadBwIMj8nRDYynOF0fPpfhdBkNy21R8XfixliKg5KSjZIETXXTgKpdED7bnHXKsy2GImi4wGRwfUIV/dMlZV0XG/U0PH1zNjrF7WEgz95S9/wb333oulS5eCO2O5fOlLX+pIxzphbnaLnkzWZwsXLsS5555rlZ26yXScuskmShWiKfRpnJAQsEeSFmnqvOsac8cN0iDkxgbpuCC9bsodAKJfEqE/TD04XgKqDGmRhkkIUV+knLEUghQQ6UyzWBcTd1nCpWtMqmIRIpakShHTgdNSOWloTdtxl8lUeqIOxRJwpMtM9VwwSwUS1E2WR4MUjEpAkFGDDASptHmeVYO0IiQSO33eBSE7hZ55A6b1WEJufJAEITt7jDtB0xywBlj0qUJ5wOP9zBAliAKR3pfeUn85tZCLrLQyZEEJKzVekC9DrNMQlOcK8637IKiMW6wqCNF5yFw3WXqNnXePVR11ukx8UDfNGpaElJcBoeGEoOFW0FZnK3b4O3bFFVdgm222wZe+9CX85Cc/wU033WSWm2++uQtdrG7rr78+Go1GRgVaunRpRi3SdsYZZ2DZsmXWctL06cY9BmTjhNIRpgkk6ZR6TmKFCAQVgVDMmMrwku6SWGUXSWVIPigFYMpitWgXm7vE+lj1wBWkPGFpZlms96lzc9I/o14JKFULKfgR9csaVFKkbkQZdE7jr6hbCil4EEUGscrm8mR+yf2krrvE3N6fJOZ43abMCEvUIjPFstliyi022B4INQMgFDtxQjG0myzrGjPzjykw0i4xN5U+TxWiLrIqluf60otbX/9z6+l/9Di6bfaD2Rleal3v+//Z+/J4O4pq61V9LrlJyABhyMAYIQQChpkwjxImGdUHMisoGOYIKCgviQphEsEXQFEEERBkiPKJILwHCfB4zAQCMhvGJARIyEzCPV3fH9VVvau6qrr6DPeem/S6v/O73TV1dZ/TXavX3rWLkpw2RKm64pghJtJSIiRnh/lmhslZYG1JXUbqMKQz0lJ1J7ud1k1njdF8hnSWmIsIVVCcCMngi5L0hJjHXMgzj9Wy/Eaz4PMXKuI8DbQeEQKgxpNGfIrgsccew8EHH4whQ4aAMZYZ6znnGD9+PIYMGYJevXphzz33xKuvvqry586dizPOOAPDhw9H7969sf766+PMM8/E/Pnzg/swceJEMMZw9tlnFzp2KAqToV/84he4+OKLMXv2bEybNg0vvvii+rzwwguFO9AM9OjRA9tuuy0efvhhLf3hhx/GzjvvbK3T3t6Ofv36aZ/2SJpoCCFK7gbTPKZHmYZK16amI0uE5HR5n1lMkiBKgKTViRKfKks/GiGi5QxSFKttnRBxlcdIW4l/E1G61FTNOJ1qT82Hcqo9j1MiQRUiZX6SygwlRNJspaa4E2IjyZHtY+TL+nR1eRcJ4h1xstJ8nK44Lx2lpbP0lyxZZ4wEVJTO0hYi1MEjVJE6THcQh2kZS0j5CyF1ltZNY3qkaaoGUafpUFUo1F9IgpIbV55ZxiQ8NvVHEiG5bxIdqgZRpUdOo6dqUIVFWhmT8Mh6dOq8jwTpxIZphKtNK5/dpiTIJFSS4FByRAlRG2dqGQ05lZ4hWVrDQYScDtMFzGM+VUh8bwHEqQARKjL7rCh8E0pCVKHMWo/MTYTi5LnerEViWwGLFy/GlltuiUmTJlnzL7/8clx11VWYNGkSnn32WQwaNAj77rsvFi5cCACYOXMmZs6ciSuvvBLTp0/HzTffjAcffBAnnXRS0PGfffZZ3HDDDRg5cmThY4eisJls3rx5+Na3vlW0Wqdj7NixOO6447Dddtthp512wg033ID3338fp556angjjmn0cRIzRprHbA7TMp4QVYRk7CDpH2SSoA5KgBJCI9OBZN9hHcq89STliHeNMIUlz5uIiX3OU9MZ5wximj0AJpSgirRnqWsCZS6jztRJ66hGSRrx5ZEDTZw8cGMALObCRAYkpIelnWrjyTYDY7HqMJdtRgEc3uErJM1gutM0IWMdUq3iGoGTSpCMpSRjK1U7IlSrzEmC0lljwkdoWZSaxpYx6SMk/su1x5YnhEiuO1aFWHusmqRJIqT/jxMTmoxGnc4wc6lCctu3qGqIj5DPN4jm+0xhgN0nKNQx2mb2spnHbGawPBOYzwdI6z/ZjjLlTVObYRoj5jDVT7nNaXqWBLWZZXi64jxVhGzrjvmIkOproHmskYqQz4xWi79QbOzTNFc+kCVAXU14ukpzO+CAA5zLbHHOcfXVV+MnP/mJCsj8xz/+EQMHDsTtt9+OU045BVtssQXuueceVWejjTbCxRdfjGOPPRYdHR1oa3NTkUWLFuGYY47B7373O/ziF78ofOxQFFaGvvWtb+Ghhx4qWq3TceSRR+Lqq6/Gz372M2y11VZ47LHH8I9//AMbbLBBcBt0QhJVhuT4oMxjcp/rypAyJ6k3B12hkeqMUmksREhuSyLkModxywckH6QNrR1DJYrBVBqMPnAw9bDQzo9egzhVytQabcRcxkmnBdEgs7SI2Ywnpi5ejVMCk1F2qkgDKcZGemouk22YClA6M4xu67GDXETIpQZV45T8Sgd5SYS+ZHI/9Q+SpjE6e8ymCMlp9NJPyDZ7zGceoyiiClETl+sj4VKGTNMYVXmU8sPS7chQeDSVCHrARJ8KRM1jbVrZVAGSwRFtJjAaHLGC7DZVi9Jj6AqRmUf3K9D9eXxEqA1ZZchFhDJtFlCETISaxxptGgsx45gEJnRKPa1rbmtlAomQ+cxtJhppJlu2bBkWLFigfcxJRCGYMWMGZs+ejdGjR6u09vZ27LHHHt7Z2/Pnz0e/fv28RAgATjvtNBx00EH42te+1rBj21BYGdp4441x0UUX4amnnsJXv/pVrLLKKlr+mWeeWbTJpmHMmDEYM2ZM3e3INxE6hkjiI2Gax9QH4iaVREKSCkWOGNNJiYUIUTVIl3JTuKbVq3wzj5GHB0vLSpOZXIwz4unEdnnEmEPFHqowns6e4wyMc0KQuCBETPoJiWPxxHYnnKcFIUIbwDoA3iYVAznNXhyQJ0oRqvJBLC+K/gjSBn46hR6wKkHptq4GIbaQIKoKVUlUaUKEaBwhOWvMnEbfAX25DbEIa+o8LR2mY0BFmTb9hCRBskWatpnHQiNOM7BM3ZA6FKbyY0sz1RygsWqQqdwwQmyy6k3aU7pMBi0jt30qULqdHjdXGeJptGifGmTu+4hQG9d9hEyHaR+KzB5rVdBFrcU+tH29bArXWo82EtS9rogdtklD48aNw/jx4wu1I31zbbO333vvPWudzz77DD//+c9zlZs77rgDL7zwAp599tmGHduFwmTohhtuQJ8+fTB16lRMnTpVy2OMtRQZagRcvkJpvuE7lKMKAZT4UCWIORUhQN/mpB0faL4kOzGkQUsnRDINTLx9xglBiiFDICbmLVD5P5lazxkicOU7hEpCKlhChCKZhyQgI0fUlp4USxrn4IIQJUEWWZRuI+ap6S3KGbAp+SH7ThIUc0WAeOLoHXdAmUlNIlT9MllGJfnvI0LUWbqDpQRIziCT643ZoktTx2mbnxBVhcTp+QMrFiU5PuSZy0JMYnI/JGiia4YYJUGqPegmscg4fhESpBEqsm03nZkESS+v7RcwiznNZDZFCKk5yyRCIeYxis5WhTprplRs/AfCiVBXk6BGXqMLLrgAY8eO1dLa29trbi909vaCBQtw0EEHYcSIERg3bpyzvQ8++ABnnXUWHnroIfTs2bMhx/ahMBmaMWNG0SrdFikB0vdpWuE2CTkyzWNAlghRk5bMB9IbNqQbEVJyI49p2kdlvnYMIFWHGBInTaZKcM7ASVh9ZZ6JGWLGxKx9lZacSwdD1AYSZwjiV9iRPOENZQgJgUKUkJeQELOE/IhjcwshoooQlPlOqkGCEOn+QYoMFSRC0llaESCiAolZg0Z0acM8Rlekp+Yxnypk+goVgRz2KXmykR8JHwnS0gyiAzRHDfL5BflIkElw6lWBrGU4jHLpLLIQNciaR4iQdSV6DxEyUYvTdDOhnkU5JCC9vf2qkO15aSNCoSSoxmGgZjTyeO3t7XWRH4lBgwYBECrN4MGDVbpt9vbChQux//77o0+fPpg8eXLGskTx/PPPY86cOdh2221VWrVaxWOPPYZJkyZh2bJlhY6dh8I+QxSc+99EV0SYprJ0SnmYiYz64wDk5mMe27U8niznIEKmH5FZX9bjpIxJttL/7oePnGZvXgdAvxYqn6hn2hqqhhqjTFVkWns6m4yk5Xw48QWy+wOlM8Ti5dJ3yR1AMe5Ip813dFT05TWMJTbkorcdRA2is/zkMhvST2g5S+MJSROZNI+pKNPQgytSshOqCqnfgiSnAQSJkT8bgmeL2YhM4gtUj29Qhcwqs6lB1C/IXDBVzgjT/XsM/yK4fYHSqfC6/49enpRJZoilfkPpjLNGE6Ei78M2VaiuQaEAaokzJJ8rPtNX0LEt9UOJkO0Z21mQY0kjPo3C0KFDMWjQIG329vLlyzF16lRt9vaCBQswevRo9OjRA/fdd1+u2rPPPvtg+vTpmDZtmvpst912OOaYYzBt2jRUKpXgY4egpqCLt9xyC6644gq89dZbAIBNNtkE5513Ho477rhammtp2PyFGgHpKwRkyZFJVMwygF3qzRwj+a/MYtAVoGyfUhNZhahEwjyWzgjTzGaJ3xCAxGSWtpcxlSW2OWkuk35EDKlCJDUhBpYoQRDmsWSb56lC5MS5VQ1C5j+Ps2qQCpWQ+AfRWYNCDUpUIc40IkTXGxNqEIkuDWEm62BZPyFXlOmU+OiqEJLrRFUhlWZRg3zkx7UYq6sshc0viKb7ZorJfF/0aLN+nhqU5xeUpwTZlR6LmUvl6SpQJs0gKNnj6E7Rsk49RKiIeUz/LokSmLPsRqNBX55qDcYYqgqFEiHXM1dLK2iK6a5YtGgR3n77bbU/Y8YMTJs2DQMGDMD666+Ps88+G5dccgmGDRuGYcOG4ZJLLkHv3r1x9NFHAxCK0OjRo7FkyRLceuutymEbANZaay1UKmJU2WeffXD44Yfj9NNPR9++fbHFFlto/Vh11VWxxhprqHQZd8h37FAUJkNXXXUVLrroIpx++unYZZddwDnH//7v/+LUU0/Fp59+inPOOadok90OtdhthVksWy8mN6rrUeMyjYW+mWh+QoDmDwSklqeIHIuTcrb2KnSf+A0BUE7T1FQm0wCeOFQjWcdM+A8pQkSf+rTTIP8Bbep+hiBp5jG5DTsJUkQojYlkM4uJtcYiFTohjwgJgsPUjDGhFtn9hGLo/kEyyrRmEgtQhTIEqOCsMR8hskWYznOQBtAQs5jpEB1ChHwkSPTHT4JMU5jPFwhmGoelbJYEFVGDYObXQYQofKpQ6LIbzYLLRJYhOZ7uNIIIZRT4LiRARWbMNRLPPfcc9tprL7UvfY1OOOEE3HzzzTj//POxdOlSjBkzBvPmzcOoUaPw0EMPoW/fvgCEyevpp58GICZhUcyYMQMbbrghAOCdd97Bp59+WqhveccOBeMF7VxDhw7FhAkTcPzxx2vpf/zjHzF+/PgVyqdo1q57aQNkqhaI4IK2QdKMLyQHSvnpYOkq9MJfJI0xpMxg0JWhatIf05SmOwDaQW9byil8s1Mq6j9PpvMKNaiNc1SQflZhMSqMi08UoxKJ/1HE0dYWg8n9ChefthiMAVEbF7FL2rjwB2IJISJPfrnNIqPz8rxcZIhcFI0AAU4SlP1+023zO5aqkI0IVRkzltpIHaarzG4ekyYyGlPoC15NyJGYNdZBtuX0ejOuEI0jZPMXMmMKhQRjDFliI08Nkvt5i6oy0p7PSbooCZJtUvKTR4J8vj8hKlCanrZtI0Fyv83YD1WD6DFDiJDoV3YqPQ2wKK6zTOfqXLT9BjhPmwRHmb+oed0o6zKRUX+hoqqQSYSKkiDz7L8167ZMmUbikYH/0bC29v74Lw1ra0VAYWVo1qxZVlvczjvvjFmzZjWkUysSInC1anwoTBMZkN60tIxEo14WTAUpD+kKY5Y88oCn0+xhmMsArhQilpAfFiWtOlQhsS9VKMtJwE2AoPyW7ME0RVwk3SwmSa4kvF9KMuQhQnKZFOkrJImQaR6T5jDlNA3dabrDowopFc9ChPLAYJ+R5yJAso6trEaODKIjt2U532wxm+msHiLkI0GiP34S5CNFqv8eFSitm6RbSI9LDYIt36IGqWN4iFD6/WXNY3m+QnlPrpizwoTIRYS0tJw2bETIWUYe10wPJEImCeoicaZEkxEy5mnYeOON8Ze/ZBnlnXfeiWHDhjWkUysa6JsZkH/RC38pHjT7xpVhBKx5cRqLiS7RYaoxlKTEMsih4VxN1wWT6dT52faJl5P2qiyNGaRNk0+ny8v/In5Qlgh9Wa14iZBcWkUurSEdpqWJrCPHPCYXYlXbhBiZvkKA9CFykdHGfvOmGmQzi5mO0EBqFjPVHhsRipAsl2E4RbuIkM1BWjpWU+foilkX+lIYtgCJRRyi02UzzLXIUhJT4bRMEmQ9ITdtyKpBMsCijwgx+ImQ+r6QJUY05pDNV8gkOF01q8ylCtlgmzFWlAhpk0kYU0SIk4/WP+PTbLSiA/WKgsLK0IQJE3DkkUfisccewy677ALGGJ544gn8z//8j5UkrYhgjNf0Y5IPJKoUuZQjxsVbWzNvMI5wFSi3rUT9kU7UPGZgFRlfiINVhFqEmInYQbFQlWIwsBi6KiQdq6nJzOi3tQ+mKiQjXkNXgnQixrSlVeRCsyGmT5MILWdMmzn2JbJ+Qvo0ejl7jMYTQibStE8VCvpuHKVd6pBZhiLULCb3izhKN1sNClGCsmYzsl9QBcqkWdJDfIPS8ln/INofkwjZ/IRM85hEI1/AfPCpQkUdp22qkNUnyEjzESFVh+l5Zltdha4+/oqMwmToG9/4Bp5++mn86le/wl//+ldwzjFixAg888wz2HrrrZvRxy6FJD6MiRtD/pd5YvkADs5YsoYPwJkYYkQcHuGHIR+4ai0wLuqImVrEPMWRMYkxkk7NWDHJD/EZsuXZFKtGPBhlNGokMYdQhXCyrsSIOyKwiINxKCKEqvADEm+mjBChsGE/ExOKp/tyWRB9iRDh9xXzxAeMA9VqJEgRMYlVefIfZHmNhPzIyNJCCRI+YMslESJk6EvwZPmNdBFW+aGr08v1x0zzmFSJzFXpXb5C6jsINJflwUaAADsJarZvkJgeXx8ByiM/eTPBAP3ecREfmafXT8oSM1ebSZAcBEilkeU1fCRI5OumMZefkPie7L5CeQgxldmIjo0IaaYqiyrkMo/J0CXmtpaWQ4JsBMjnqpCWKVWWFQE1Ta3fdtttceuttza6Ly0LoVaIgZnHLBnImfJsFvuSCIkBnfFkYPe87Wgkh5Ag+XBSMQaTfZMo5REi25FDiU49tzfnCWkk6pCYgZb6DckT4RADg3gOJcQzAng1IaJ5YbbVMQ0yRAgQ3ackSKpAPCE+nEMpQTxRgUKIkJo1xrKmMakIyZhB0iFemsLkHw2waDOPSbNX0dXmTTRiGn1Efh0+3yCaXw8RqpDyPiJE1wyrlQSFzgQD3ETHR458PkHQ9rna1/pCTGJAGBECKSuuP01LyjbRDBZKhGx1fOYxcyq9uV0PEfL7a3Yd+SnNW81DEBlasGAB+vXrp7Z9kOVWBEjyo7arTP0HxBsUJ/vWNpIHEk8eVzHZlwpPhHT9L9tNL9O5sW9u+24T7aFoPPfoA5oZ5dTbanIGkbGfB82ROnGclhIYrzKw9Cmv9iWhMc1jzmNIwsONfaoISfOYXDdNzhxL9qUaFHPdJFblDFWkwRQlEeogREhzlka6LUxe4mFKnaWlo7T0M5ABFsV3zNOHOJc6EBRBknCtRG9DiDmMwhtLyCA+zSJCbSrfbhKr1KkG5ZGglLDoJKiICqTa49m0jLlMq8uz/bGYxNJj+omQzTTmundtCk+Iv5AkL7Ksz+TlCk2SdxTbVHqfnxDNF+lZwuNTg1pxWY7STNY8BJGh1VdfHbNmzcLaa6+N1VZbzbrmh1wLpFqtWlrovmARgDhrKkvNZ/WZymLGNHUILBnU5ZsM2daUJNgJkQmbGUy1Zebz9H/Ioo5A9o2ScwYwrv4DCTmJEg7kkLuk4qZMkDkkUzsmIT+iD3Q7S4KoSUyqQUoVSqKH5xEhGUeIzhhL1SCy4KpSh8jiq5rJK/mdECUIgLZNnaEloc5cA1omR/mhZEeqREHT6OsgQiFri0VgykHZRYQqYE6zWAUmaconQYCuvpgkqIgKZOZREuRTjSqqXJYEiTpZs1jaJ7IivSoTRoR8qlCt+kOe349JhOpVhWi+aR6jPkIhRCiPBLnuqkDxukSLI4gMPfLIIxgwYAAA4NFHH21qh1oJ0jxGt2sxlUnlxaYOIfEdkuoQkJIeeR/Sm9UkRDI9T0SxPdRpnvlAVemSxHH3MVzPgpgzRNQRihAiaQ5DnBBMQymi5jHpN2QzmWnLoyQKkNhOCVCap5OgmOtqEAeUWSzm8BIhZSJjaVBFqgzFFvNYqgzBqQoh+a/MYiQt1LzFmHBmj8By/YZCSBDQ9USokrRej1nMpgaFkqBQFQjImsJkeZjHIiRI7mukx1CDZNm0LZ0IZUhOABGi6OwZY7aYQi74VCFz22XiKkKEnAEYu5j4lMpQ8xBEhvbYYw+1PXToUKy33nrWVWI/+OCDxvauBcASVsKrWVOZUoGSwb4mdQjKakQUFZqW+g4BOiECsqTIhKn8mG+w6u2Vp+0yo6x2PaS5zPNQiMkSHRRUIQJ0UiSvJ62lSBBRiExCZPoK0bdKaiZTyhCHZhrjRAniiV9QBxdn6SJCHUz4IEgiRJWhWClBunksnTHmVoVEvy2BEhsgyoeaylwkCGgeEZJO0TYiVDHakgqQzSxGp8jXQ4JCZoKpNHltiKLjK49M+8XVIJHWGCJkm0rfrPE+JHK/TxXyzR4zt00/oTwi5CNBvhhvnY3SZ6h5KOxAPXToUGUyo5g7dy6GDh26wpnJJOisMkQcLGaJogEwLgf1YupQGxcDa6Q8jiGeqgYhUstlaPKtgI0UmXA9xDNTetV//UFr+gvBKG+DeKlN/KKSE5FO1bIiJUVAeqNLXyGbmcwMsmg+PCUBkts2EiS3qRoUA8JEhjRaeAw7EaJO0nI7NrZprCDqNE1VIfOhKp2l6bUxTV6+2EJ5kETHJEWuGWV5RMh0qLb5CMn2ixKhNlUuJUJ0QVVZx0wzyU8bIUu2CNFFSVBRFchMpwqPTDNJkKxjK+vyD4KxH+IjFOI03Si1yGce40ZayGKspipkM4+J/eJEyEaCbASoc3U0ga5WplZkFCZD0jfIxKJFi3JXoe12YDxZ9kGaxiC2q5L4AIgRrA4lAXggH3UdinQwZS6zEqKkOyYhArKkyHoasgz5bw33n/lvN5FR52lbiH4TmrkMSO/opNGqnHknkcOn6YPV5jytqUMWEiRnisVEDZJmMUFckjQGNxFiUFHCpZ+QJDMynpBuGsuqQrFhIpPExzSRiWuoU5jQoIo2U5mL/NA6qiy5111EyBZRGkCQs3StRMjmH+RVhgw1yGcOc5nCfCqQrbxMA+zERpaT9xqtR8tTNSjTl4JESJVzLKnR6LHWpgYVMY+ldZL/GtHxm8fMspQIucxiJhHS1SZLv0pyssIgmAzJhdkYY7jooovQu3dvlVetVvH0009jq622angHuxIyACDAlCM1IgYmlY7E65nJmDqReFBKdUg8eWIgjoQ8EkcZc5mcbsXVdpYQUYdq8IQgWW7CPCdq822WEqE2NRgkChCXSlCqCpkmsrw3S6kOMcZTQgSokUDzESrwGDb9hABYCZC5L01iVA3i0M1ikgyla8bZiRA1kcm3S0F80u10arxdFeJITWT0zRbQ1Zsg81biJ2TbD/EdkuXMNmk6NYvJ9HqIkM1HyCRCbYzUU/mU7LAksrNDGeI0nZwL9N9/KAkqogLp6VkSpPphmMTM8ibhsREhWxwhE3lEKBTcfHnxlDPhIkIhqpAtphAtq/IY3c8SGhsRcpEg8yy7mvyUMY2ah2Ay9OKLLwIQb6TTp09Hjx49VF6PHj2w5ZZb4txzz218D1sAUhECUt8hJE7UiMWDoVIBqtVE+q8kek6cNZdVJLFRd1lKiOQ2I4SIJYRIPojVzZiQogqgQhlFyBIizT/AeJjTgUASoTYzzaxj8TuwPVBpIDb58FTTb0knORAUWJH6CmkPVPUQTfMkAaL7kgSZapA0i3EI/yDuIUKS9JjkJjWbpXGBiqhC6rwshKWoScxFfEyi44NLDQIaR4T0fGJKK0CEKjCJkd0sZlODbI7RtZIgM02mi/JuEiTS832DtOMiTc+SoiwR8s0cM+9b8xdSj4ksjwiFpKf5pF3SS1MVspnHUuKjGwqtM8yYnQTlmcs6E7V/IyXyEEyG5Cyy73znO7jmmmtWqHhCLijflTg1lzEly3All/vMZZVIGrqEMlRNyrc5CBFT2+Jh3mE4VVcIKVLkh6c3acVxLi4SRIO8meaxNm5XhaiJzPYYo2+OSuziclDl2Ydf6BR6jQSJ/xmfIaICyXxKgkw1SCpBKj0hQDEhQpT0mLPGqHmMI1wV0s6LmsgMglQPJFkJNanZSBBN9xEhVa+OOELUWdpHhExzmFUZIkQorZv00VCDQklQrSoQLUtJkEx31Qs1i2l1mZ5Oy/pQVG9wqUMhTtKAfVAPUYVovty2mcd0MmP6DelEyKUG2Uxltv0SKwYK+wzddNNNzehHS4IG/Qs1l1UQo4ooeQDFqMaRUISoyQxA1SBE0mQWAQkRkoMiUwoRVYYYF1UpMUqOoEFTcIy3WUqElCLEeTK46ESoAuKLgHwTGZCqQ/pYXOyxa47jNvJjptPQ/iYJkmoQNYtJR2mhEqVESBIbahaTfkIx+a8THU7Ij/sacaQmMnVumXN316dmMAYxU8w1pd5Himz+f7UQIYYiihC8RCiqgwjZzGI2NcgkN80gQSYBEnkmmSmmBtn3w4hQET+hEFUolPgA4eaxtIx8mcmmyW2feQyQ92c4EfKRIO1YRZljA1ESseYhiAwdccQRuPnmm9GvXz8cccQR3rL33ntvQzrWEojMBwVX8YZ4nKgcVQbGYqKAAKwq8qtRBFblqCTLPTDGUIm4WviTA6iQuDYVRIjBsQpPTTYxOL7kTA26UgXSbmrywLDZtG0Pbc2EQEL8UzWoov7HShGSREiqQhHj2kPWVIIyN6/nGZt5IOYQIXM9I00RQpb8qDSaz1JliJKg1IFaxg3KKkIdkiwhdZqWq9KbK9R3JP9tJjI6iywElOzIbRsh0q4dshMfbKYzWoYSIJpXDwmKkF1eg8YQoo7SLhJkM5eZJjEVgyhABfKRn6LERytDfsBWYkTayCNAtrR6SZDZH1eZepBZmNWS51KEqNM0jTRtmz1mKkKUCJkzxiQJokqQSYBUXoupQ7Hl5aVEYxBEhvr3768ehP37929qh1oJLJKeQimoyQxgiOSgFjNEbWIR0qgSI0aECoSJTNxQyTYXek7EqqgmjtUs8WGJECfmG3FMaVIDEw8GeWOzxIQGOqAmnax4nmO2GSzUX0g+lNuQEp9QIuR6gIa8PdoEEJtfEE3n5j43Fmrk9A0wS4SkEsS1/SwRkg/NjM+QUoTs5jGb8gPob6BIyuj5/oGIEqGM0zQhROKacK2eDzYSROuZK86LcsWJEDOIEJPEhsky4URIqUJcEqB8JYjumxGi6yFBNvXHmV+jEqSnrRhEyF03+U96mfUL0vdpOiVCaXo+EfKRoKx5u8SKhCAyRE1jK5OZTCpDtRIizhiAOGHzwsNHPATS/yyJdxMxrkxq0qdF+gRFXA66yRsQIUYViBtfkiDXDUrfVk2JXpIgOShUINUhXhcRMuGy+mQemhbyQ88tbzVrHwky3yLziBA1jUlCpN42Qf2C3OYx6jidnkv+NZOkV7qp0en1NnUISAmRrJ9eU2MgtLxhukgQ3fc5SpuwESG5LUkPXV6DBlPsDCJETWMZxagOEmRTiWxtiHxzMdU0PduWnQhR1EOEGolQIlQ0phAtq/aN+znTF5pPmjKJUYwsCdJNcdl2OxslAWseCvsMLV26FJxzNbX+vffew+TJkzFixAiMHj264R3sSlBlKIQQ8QiIOwQh4nG6EKt4DsVgEQOrioc/JUBSJWKRGNIoKRJvSFEyGPFksE+JEZC+RfluFNtDnRIg6h/kI0FAPhHy+ev6iI+Zb5IfWt4mqbtIkCxvEqEOQ0avqvz0ISmJUEqAUhVI9pGqQiDHM1Ug0c/6H2c2dUiSFWkyE30jqpFHXreRIFonjwjRulQVEmk6EaK+QBEhQozUpTGEaiVCFbKdpwbVQ4JsKhDNt7Uh8vXfgZ30ZMuGzBgDaiNCjVKFfERIS3fOLkv+k566VCEbITHNYxmHauQTIdOZGrCTn842l5U+Q81DYTJ06KGH4ogjjsCpp56Kzz//HDvssAN69OiBTz/9FFdddRV+8IMfNKOfXQYbIUr9hsiTFEKyidqSvCSdMyjTGI+FCSOuRmBRFdVqlPE3ijlTx4qTGU8RYovvC1L/IU1xsD9g8qbo+khQcnY1qUESeWYvwHjwBBIgkZ71KZDbLjXI9sBUBIjUpQQIJA9avk6CMgTIfVkyiMBQ9dBa+duQZaUvkC2mEHMOe/bjqmNYSJA8NpAlQvVMn9cUIkjVKDt1PpQIydmWRdQguzpUnATZCBBtQ5TJ1gvxD9L61KJEKM/05SpTjyok0uz3daYcvb8tRCjjL0TquY5N0yNHfonugcLf3wsvvIDddtsNAHD33Xdj0KBBeO+993DLLbfg17/+dcM72KVInpyM/GdtZFt+KhxRW/KpiA+Lku22OEkT/ysVjra2KqIKR1tbLLYjjrZKrD6rVKpoi2KsEsVoi2K0sRirMI5VWCw+iNEDVbQhxirgaAfHKsmnB2L0SNJpGt1fBRxtiJP6sWq3wsSssQrjqERinwFqX5KjNOq0/UMR09ldxpR3Oe1dfmSaWEWepZGiARULSESOBjq4nP0VKYIoy8RI1glDOBGqWh6ULlUIkOqc/qCkw0neTLFiP8OEQKiZXRaiwrKzvMxp72abZhmzDa19CBJUjAghQ4Rc0+clEaIO1BkCJP/XSYQiLspSJUkLMQGu0qg6xSBIUBqQVM8DqQ/SroRvuns9RKgV4CJC9bzgqHrQSZFPFdL6RO/7AkSI03JMV4oyL0n0eP7uNASqTw34lNBRWBlasmQJ+vbtCwB46KGHcMQRRyCKIuy444547733Gt7BrgSLmFB/iO8QUMxsJlUiudp9XGUiEGMUq5XVpSqk1tKKRNBAQQqAKI6s08UB7nyY2GA+SNVDl6g96dt/VgWqZyKDawaYluaLM2I8JH1KkMzPTKOFnQhx1Y6DCBmqkPnmqUvwtQ1Qug+Q6FeUHFtzhGZMmdpkHc1EVtB52jXDzKYGiX3dRyjPYVozianyVF2iihFVigwCBH3WWD1EyKYGhSpBeaYw2kZazk6CfIoQtHLZ31SjHKZt5YqiViLkbM+4x9N0e9nce5vcy2Z7KlQG6bNrZpl5Tl2BMgJ181CYDG288cb461//isMPPxz//Oc/cc455wAA5syZs+IFYoxSUwMHT2IMESKU7LNYN5vR6fecwUqK5IKirCp8hiTBiZJ0HjNEEU/SuDOqsuhbijyp2hZfxFxfzCQ/ITGFALf/j28qvJYv23G8JVLSY9vXiBF5GMo838MyrZN9CNpUIZpP03zpeYhgX5aNOlJz8AwhksexkaKw4zLrNiVCdJp9KBGqZeaYSaS0uEINJEL6zDHeqSTItp89hjwuJTc5dRo4EywUIUTIWVeVdb/I1aoKOY9J7vE8IhTqN9SZ6GoytiKjMBn6z//8Txx99NE455xzsPfee2OnnXYCIFSirbfeuuEd7EqwiMzMoaQIABKCo7SgqBgp4gkpkj5DggQxpRZxLt6OecxQqTKiBqW+RWI7TQPyyRBgECKqFjn8gVzjqhbfiDPh9E2ULorQKfEiLylTBwmSx5IkSN93vzVmZHOiCtn+12sKSz3E0n2mgm7KGYVUCdIJkaxtI0VF4CJBaR9TgpOqRn4iZFWHLA7TjJRL9/X/ejDFfCJkpgM6EVLnaBChRpMgsw2XecxGhLQ2mD8/Wz5MFaoVvudMRoFpEVUohAiZ5jJ1LEMtKrHioTAZ+uY3v4ldd90Vs2bNwpZbbqnS99lnHxx++OEN7VyXw1CGgGQ/SsxiSRl5VzlJUYUDXJjchCqUKD1yP7nrqGLEKTmqyO2U+NgWKJUImbBkEhzzrdIlnesPwbQ/kW2ZDQOUCIXOCrOWke2QdDOomswPJULmg9AkSPS/iSIPyIgxVLmc8ZUOhLGNQSIlHNJcZhIiAEoloqRI7585OGfLaAO9hQQBKEyEfGYw6ifkc5imRMkkSdSnx0eEUuJjN4vlqUGNIEG2/TwiZDOPdTVC73FbeW3ihCrvV4XMfdcEkRC47lMfEbKRoK78VrpamVqRUZgMAcCgQYMwaNAgfPjhh2CMYZ111sEOO+zQ6L61BpInVRFSRM1nQD4xAhBMjmR7gEUdMu4UHymqxf+HcxGDSB4rfUCwlBAB3re/2PFADPUJMusBWTVIlnGF4s97Y1T9Y/YHqKka+ZD69WRNYPInQ8tK7TFmIEuyJO0YhAiwkyKoPNquDlvXTRIk65pmMdn3fCJE6yHXT0gSH5vDtCI6Mt0wealt+iHp0PbD1KBmkSBbnVCE+AoVBV1U2VcmD0WJUOYYFlXIXHYDMO5jhKtC8thUFXIRIZMEaSpRF9KhUplqHgqToTiO8Ytf/AK//OUvsWjRIgBA37598cMf/hA/+clPEEW2W7+bQmrTcfr66CVFdHQznE9MYsQqCUFSRIYnZIaLMpxsWwgSoJMdSoRcZITXeCdZSVckZp6lpIhlyJdLLdJULAcRCjWJ6fUoUbEToVBkHuwNeCOTapA+yMp4VFypQ1QNkuYynpi/ZD8idc1kf1NSpPqcIxGa5U0SBKAuIuTzE9JNXrpJzeYwreUnpKaNbMsyShWqgQjZTGL1kCBXmosIuVQhm69QoxFCdlywnY1zhXqtXvNVIZ95LIQIuUhQSUpWPBQmQz/5yU9w44034tJLL8Uuu+wCzjn+93//F+PHj8cXX3yBiy++uBn97BKwtuROIU8jqeQwMO0uZpKgyHxyt/BYH7k4vfsSwiP2OamT/tdIjKEOiW1DETLuVBs5ypTRyJSeRtUp2Z70bYqrERjnaiYc40K9kDPhXJAPNzNWkI0EhSpBIi9LgtL2sw86nx+Buh5av7MnJTkw/V+FrgrFCRGKACHLcVmGA4QQSUcz6S8ExgQVSg6ryLiK/ySVRb1fMTgqOfKfqRjZVq03CZDMCyFBtin02tT6pB2pBJn/1eLBSBUhagKj2z5HaUqCqOrjUoJCYgTRetnraofVF8iTVwSuVeRVPhrrN+Q6kjeavFZfJ0KuFyHzfiyiCtHldHxEyEWCbBMlMi9JZLszZIDWM5yuOChMhv74xz/i97//PQ455BCVtuWWW2KdddbBmDFjVigyBCDzC6dvzzajBItYOiJCKka65sqgEyTZIiUoOpkCqZ8lTBqhsrSVJjJrvlSkZDo31aoKT011MUNcBRCJWW6oxMoJOoqhzGRMLqoWcPeaik2jiBBtXyc04Q8V8zJqU+B5VjGKIIIm6j5BWVKUpmcJkXSLlucpVSJxTPmATvOAbD8qYBmCZMK3cCsz2rf5C4UQIbdpzK0ISdOYPD5VhCjhkfnNIEK1kCBfno8IFYFckhfQHjMZ2Exfcq8eUuT7RTWCCJll6H6eOmtbeyxbxk6EMvkGEbI9V2xtNxulz1DzUPh+nDt3LjbddNNM+qabboq5c+c2pFM+jB8/HptuuilWXXVVrL766vja176Gp59+WitzyimnYKONNkKvXr2w1lpr4dBDD8Xrr79e/GARSz8qLf2wiKWftigt25Z8IqEueT89kk8bQ9Qj/bAeUJ9IfnqmH2bsV3oDlZ7pp83Yr/QEKu3c8YlRaY8RrRKj0oOjrT1GZZUYlVU4KqvEWjBJM4ikjEfEGESgyWQ7IjPTavFnsD48GU3Ty9mIkGkaMx8kYT4/eflM+w8YDrtUWSHbgiRYVBZFMEyzUhrfhxkmJ6GuRKqM/FRYpMqbnwrLlqd/qn3GNJNYUSLkMo2l6dn/0NKStjg1aZHydRIhBlKuDiIUefJC4DMB+WKHaW04Qltkj1VcYfDVoYFVbX2x3cvZ9lmmrN1fz60KWfsGXRVyQfMvIkSIqzTjueL4lOi+KHz/brnllpg0aVImfdKkSdrssmZhk002waRJkzB9+nQ88cQT2HDDDTF69Gh88sknqsy2226Lm266Ca+99hr++c9/gnOO0aNHo1q1RXFxg2kkiFk+0MlRG8sQJCtJyiFFghhF6adnlOYnn6in8bGlEbLk/PQQRCnqAVR6CMIUrSI/ghxJYiRJUWWVOCVHCSGKKrEiRIocJf/F5UsXeLXBtfq02lbiWvYhG1vMQaEPppC3ObOpyEhj5H+klWEkXSdFPkJEfXJ03xs3KaJl6J+VJGWoj06ATBIUZfLDiZBJoKD1lZAdlac7TJv/zW3ZXq1ECNDVILqSvOmsXNQsJlGLCSzUvy3v95s3BT70U6T9ECJkizRtLQc/UbT2CbrZS2/bbh5zKUT0HCjhEQszZz/NRtzATwkdjOdp6QamTp2Kgw46COuvvz522mknMMbw5JNP4oMPPsA//vEPtVRHZ2HBggXo378//vu//xv77LOPtczLL7+MLbfcEm+//TY22mij8LZP2teazvNe1Xz5BX6FuccpcnyvDxMn2yKd/o+TpdvFdhLwsSOJph2L/3ESCymuRul2zJTvkFpmA0iDRiL1G9LXXdN9BXxT5wG3KpQpz2ib+n6oT0EV8kGYvjF2MK62q5Ar2XNUAXBtX9bT/8vV6OXq9h1IV7gXZke5nc4uQ1Jfpqu0GheCtfkLAYaaJcmdhQgBSEiWToTkf32hVeo/JJ2hRb6MJ6T5D/Gsw3QbsqoQLWtOnQ8hQuk5h6tBIfCRIbMN39R6X6wh2o5NiW3UIqwSeSQICCdCthAa2n2J/GjyatFllr1/qwH3NVWFtGeE7AchQdo5G9fg4ndvz1yXRuK36x7bsLZO+fDWhrW1IqCwMrTHHnvgzTffxOGHH47PP/8cc+fOxRFHHIE33nij04nQ8uXLccMNN6B///5OVWrx4sW46aabMHToUKy33nrFDuCYxqGpP8ZH1XN92sI/rEdU26dnRXy0tHQ7knmJ4kTVJ2mii6SZrk0oRtEqHKzCUekhzWWm2SwxkUVcM5fZ1KFaYXuLtKlCvvImit4AckCn9aS6keanbTNSVldQfApRqt6YKk0bUWhs6o/PNOb72Mxlkqy0yXSiRpmKkCJN1hhDdvMYvZ5Muz5pnnlNzetLlSATLiKUfm/NJ0JAjgnMU9b8/dJ3HF9QQroGYFqXWc1ZReBrw0eE9Db8xzBVoWx+lgjZFCBKeDJ5cBMh8ziyLZD8EMVsRcNjjz2Ggw8+GEOGDAFjDH/961+1fM45xo8fjyFDhqBXr17Yc8898eqrr6r8uXPn4owzzsDw4cPRu3dvrL/++jjzzDMxf/5873Gvv/56jBw5Ev369UO/fv2w00474YEHHtDKnHjiiZnn2Y477lj4HGuKMzRkyJAudZT++9//jqOOOgpLlizB4MGD8fDDD2PNNdfUylx33XU4//zzsXjxYmy66aZ4+OGH0aNHD2eby5Ytw7Jly/S0aoz2Ss5jz7i7mYNA1YVGtUn7ql7POLnrORBzsCT+EYuRRMoG0AFUIiDu0Nc0i6sMogGZKrZjAIxzVCKgGotTiAEgceyMAUScWZefCDoVX14dl0s7Cw41ytJ92Wc1MHNxzChJlVGgqdO0+C+jQ8vo0ul/JBGlpfoiVB/xhlyR+0zusyTeEH2Ap2/TFa0NP5hloKbkDUhVo4jUoURIlmVaPiF7SOvT8tQsCKSkhKZraUQJkkJHnnmMnp1OqLLXphlESII6Phcpq34fCWKePg7MNuldCMA5w6weQpTpq6UtF8HTHj8OVcjcrtVE5krPd8LOJ0K2fnYWGvjVFcLixYux5ZZb4jvf+Q6+8Y1vZPIvv/xyXHXVVbj55puxySab4Be/+AX23XdfvPHGG+jbty9mzpyJmTNn4sorr8SIESPw3nvv4dRTT8XMmTNx9913O4+77rrr4tJLL8XGG28MQEzgOvTQQ/Hiiy9i8803V+X2339/3HTTTWrfN9a7UNhMBgDz5s3DjTfeiNdeew2MMWy22Wb4zne+gwEDBhTugA+33XYbTjnlFLX/wAMPYLfddsPixYsxa9YsfPrpp/jd736HRx55BE8//TTWXnttVXb+/PmYM2cOZs2ahSuvvBIfffQR/vd//xc9e/a0Hmv8+PGYMGGClvbjrb+CC7YNN6s1HBYS5FxzykeYDMKmvnJCiLhBjrhYGl7MKOtI0jqE2Yx3CNMZr6bmsrjKEHcIE1lHR4S4Ksxj1WqkmcuqyaKzHMk28k1lNjOZ6S9kte/DyCPExmY6CzWVmZJ6OoXXbi7T07hW12cyA0mHkUbPld7CPr8F+vB2D/TEROYgQTKN7jPoqpAKjkhUH5tZrNap9LZ4Qi4yRGMIybMzVaFGzBgLhYsU+UxmIp+Y0Ji7rKt/jVq7zBXHzKdyAWHmMblvmsjzFlyuqnLhJrKqcS+DloNOhEJJ0MQmm8muW69xZrIxH9RmJmOMYfLkyTjssMMAiOfPkCFDcPbZZ+NHP/oRACEuDBw4EJdddpk2hlPcddddOPbYY7F48WK0tYXrMgMGDMAVV1yBk046CYBQhj7//POMWlUUhe/rqVOnYujQofj1r3+NefPmYe7cufj1r3+NoUOHYurUqXV1xsQhhxyCadOmqc92220HAFh11VWx8cYbY8cdd8SNN96ItrY23HjjjVrd/v37Y9iwYdh9991x99134/XXX8fkyZOdx7rgggswf/587TN2q6ENPR8vbCa1BFT+y5rdIvHJpFfST4+2tFxbBLZKBaxi/O9RSR2+lVN3YlbrESX7wmzG2oCoDWDUXJaYzFjEUamkDtXSXFaJYmU2k+YyxngyYOU/pM2AdyE/XDl4qAFQM4e429Icdbl93zT7iHSmBmY1QJM0GmPHNJlVErLQlpjM0rJZc5U06dVLOQAAmftJREFUoSnCwBgqZJaYbaaYNLHJjy2fmtgqlhlrupkrPReTCFFliZ4rkF43GOkhqpDcLqIKRYQouoiQiWYSIUAM8PJDkUsmyH4i4lrLusxD0nxmM6N5+5tTz3Y800fI5zBttmVrQ+zbiZDVfG7pE033qkdaGs+Ukend3YF62bJlWLBggfYxrSMhmDFjBmbPno3Ro0ertPb2duyxxx548sknnfXmz5+Pfv36BROharWKO+64A4sXL1ZrokpMmTIFa6+9NjbZZBN873vfw5w5cwqfR2Ez2WmnnYb/+I//wPXXX49KpaI6OWbMGJx22ml45ZVXCnfChb59+6Jv37655TjnuV9iXpn29na0t7draQvyTGSNgEfR0VQgs5w20y1y56m0ir6vadYxWMyFPSbmSDyewTtiEe8oYkAUAx0AICJt8+SQ0hQkIRQmKdin/6txBMaI2QzkwcOZ6HKy/ERqYmLqGPTByJA+zCLOvX5DNsieSXKTmriS02d6OZe5TO9r0ikm9tsgzVbS3CWvE9OPj/ThJM1mMtYnIAZ+SelicGUyi1T7adwjZU6D6IdEnpxv+5VTcxYtY5rFIqIemeYxWS6blvUZgpGW5mW3I9j7TKNLu84vz08o7453qWvmNQ59cthMXbQ+V9cmNZuJ/GTfMJvpZf39KUKIbLASLpPAWUxjtJypCmWOUUMXfbPIirRhmsZMhZa23R0xceLEjDVk3LhxGD9+fKF2Zs+eDQAYOHCglj5w4EC899571jqfffYZfv7znztVI4rp06djp512whdffIE+ffpg8uTJGDFihMo/4IAD8K1vfQsbbLABZsyYgYsuugh77703nn/++cyY7kNhMvTOO+/gnnvuUUQIACqVCsaOHYtbbrmlaHOFsHjxYlx88cU45JBDMHjwYHz22We47rrr8OGHH+Jb3/oWAODf//437rzzTowePRprrbUWPvroI1x22WXo1asXDjzwwGIHpKSi1pldeaDtGiSGc54SIvrUo6BEiKpJeX5GST6PuSBK6tUtIUYsOV5HnKy/FgGJczTv4EAyuLMIqC5PCVE6Ay5LiIBI8x9iif+QmFmWLCfBOaqOB6MgIUYwQnm+EA8lSmAEyRHlVT4hPz5CRGNn5hGiNkJIKCGS5IcZhCj1A5EERydIXP1PVqcHEHNRzkWMZL+gttPflUGDc0FNZTYSJI8i1SCZT0kP9SGS7fhUIUqeZBpIvmrDUPeoKpQ5lkUVMlFP5GcfySxCQHWirxOZEFIkbzmTFNnac/UhBL5zsobGKEiEqLlaP24Yi/EpPi5IE5mrro8IdQUJauQxL7jgAowdO1ZLK0IeTJguHNr4RbBgwQIcdNBBGDFiBMaNG5fb7vDhwzFt2jR8/vnnuOeee3DCCSdg6tSpihAdeeSRquwWW2yB7bbbDhtssAHuv/9+HHHEEcH9L0yGttlmG7z22msYPny4lv7aa69hq622KtpcIVQqFbz++uv44x//iE8//RRrrLEGtt9+ezz++OPKmapnz554/PHHcfXVV2PevHkYOHAgdt99dzz55JOaT1EQmkWAQo8XMTchUiN2nFWGTPjUJ9KeRowUKWKJlMMFMQK0xxogBtuUEEkKQbfN/3JTKEaVKAbiCLJ1BuqAHK4ONYMQSYQoRPKxHnEx1ZcSIhA1hyXnoitDKSnqgFR5RF6FfIWUGAF0IOGK9FCCJOuEIOuzQkmRrt5Qs5isaxIhm5O1TxWiyo/8b6ap9MBbM08V6iq4VBuTyJjlQkgR4CdGtj7UijwSRPvoKm/rk89Elu2DW/VxnaNvEeZMcFb1X1eKQo7TaDQysKPNGlILBg0aBEAoRIMHD1bpc+bMyahFCxcuxP77768UnlVWWSW3/R49eigH6u222w7PPvssrrnmGvz2t7+1lh88eDA22GADvPXWW4XOozAZOvPMM3HWWWfh7bffVtPXnnrqKVx77bW49NJL8fLLL6uyI0eOLNq8Fz179sS9997rLTNkyBD84x//aOhxncghSzXHCSJgEXmERSxZ0Cp5IJqrdkZMESNO6msjO7MrSWBi8dik40AcJfGHOFgcizbaBEHiHTFYh/jPO4RSxNoA3sEFKWrjiDsYql9GiKscUZWh+iVHNYrAqhysGiFmTC0ZUI0jsChGNYkxU4UY8FNNBZCEQsaWkb4CkjTIxbtiYraRl0aZoBShYKhwQpzkpTHS5NfHQNUsQlSSMqlzJlPblUThSv0ayAOdfD9xQvpSx3FBdCQxlG+uAFmzielv+9zIR3L9TIT+Gs3nbWRcU5MAyW2bj1AlQ4zSbRlgMTLrE6WHbsvvXvWL5If4CjUajRoATRUohR7CoQpKaMw8w9zGU/JH2wO870aF4XrEuZbYEXl6mqkImUvvmIdIiZFbNYqBzMwrn79Qtr7pNJ0lQp1FgFodQ4cOxaBBg/Dwww9j6623BiDC3kydOhWXXXaZKrdgwQLst99+aG9vx3333eeczJSHPJeXzz77DB988IFGzEJQmAx9+9vfBgCcf/751jzGUjWjaMTnloeH3DiJT60BGCPSLlFvKLnhSPKqVD2qJuVTUqQRIh7rhEgdj8ogEVABWBQnipGozwBlp5CTwukjDMhRib6UJ5akq2xBvgDxwK8kpibpQwTjSAwcEWfKZEZVBZMUcS1PNmC8VafjS9prQrqSS68UmpiUCVWKYojZLqnqlao5LsVItquIAUkj3YXRfVHWULVqBf2lUOJj7ptmMZqvt6erQzC2TbJj2zbruFDUDAS4iUnRa1hkSrjPx8enDLny0ny9D9TPKA9UgA5FXjRpUcaenmnLoc7k9sGh+NQKp7KU2e8cubGrCNiiRYvw9ttvq/0ZM2Zg2rRpGDBgANZff32cffbZuOSSSzBs2DAMGzYMl1xyCXr37o2jjz4agFCERo8ejSVLluDWW29VDtsAsNZaaym3m3322QeHH344Tj/9dADAhRdeiAMOOADrrbceFi5ciDvuuANTpkzBgw8+qPo1fvx4fOMb38DgwYPx7rvv4sILL8Saa66Jww8/vNA5FiZDM2bMKFql+6Io+cnqw2H1rMdONyl34VQFQmrm4hEDeDLjLObJaJ68MydEiMl6khA5/ZDkkzACIrK0aFsFiGMyCDeGEHHGlKlMvvUJlyWmyI1cBT69PCkhEvv6QN0MUiRMVFArsah+kny6z9TVcZMieRxKkiQpkl1xkSA3OUpZmjSzQcsLg0lmbCRI/GekT+5gixnFyVB6QkiRrNdsFBl06gslmq1vEh0A2l0m9k3io5e1+w3ZyKn9YoY/puzn7g0KaVGJbCQpE3SS+T28fHmNMC+lai5pt5NIUHq8rsFzzz2HvfbaS+1LX6MTTjgBN998M84//3wsXboUY8aMwbx58zBq1Cg89NBDagLU888/r9YQlSYviRkzZmDDDTcEIHySP/30U5X38ccf47jjjsOsWbPQv39/jBw5Eg8++CD23VesDlGpVDB9+nTccsst+PzzzzF48GDstddeuPPOO4MmX1HUFGdoZQFdjqMW8qPVCSBKTmgjg06C0hEpiYBNpuXrU/GjtIxsR7Iscw02W795ohJ1xEAcC/+hapK2PNZMZnw5wDuA6nKAVxNzGYlHVP0yEjGGqswah6iaRLmt8iTuEJdyuT0GEQDNBAZYHB+Jr4H1oUbq80watDR1bKY/zLmZT/aluYuay9L2uJZWhR5byOyvGWcoO+uFmEvIORYhQiZ0/yH5nxK2lCAxg/yYJjKphlGzVhp3COnSGsY24/qSHHlmspS8yX6I8/dFnA6BN6J0nYOujejlxUDSCaW/rKtcI5C3vqBZxmceE+n6Mju2KfWZe8xyf1bNdLOOcV/a7knbfSjTKa569w7X5WkIfrl+4+IM/fD9cjkOipoiUK8sKEqAnOTHWaZAZ4iswZSJDIQcJaoRIUtKLYqZUoq4JEUAEDkUItNJG0hVorYIvANAW+LFE9m9AYBUIapo6hC80++lQiRRJQqRND+ZjtUAhEoEOJWiiBOCkRAj5W8EskHqS78ip1KUDMTUNyFUKaqQ9qRaVFHnw9S2qR6JrqYkhJ6jzXyW5hGbHmr86al98/hZIkTLmgpRXvvMsd0MmA7JvjI2uB13a+y5bV2xzFIXaRmfYmSWpXXy1Kw8shTqCO2qYxKhbP3afqu1wqsqudSzTlaFgHC/vxLFUZKhEBQlQLb8RhIi7X9CjhQR0vczpKhNVEyHxsTHKI5SVYiqR/K8VJmEECWjAOuIwdssc5diHyHKEqFaCZGs7SJF4mhuYgQIciSJkc3hmiURsynJqRCSI0mRvGQ+85k8XnrGYoiQxCsGS9rIEiE5tT4lPWHkiOYBOkmiMB/u5sBqtmOLQUTVGBf5Ses3n+zYIN8NKEJNXUXJT5HBi7naMQgSJUe+AdlGemwmOFpeohbTn6td13pjNtMZvb70zIrGEisKhvqJRmcQlUbOJiuhoyRDPgSpOzrZsRGd7CrxyJQJRiTMHYwSonSUN4gQdFLUFoF1xG6VyEaIAD2N+hG1CW8U1hELwtXG4PMhqocQcQ7NqTpd4wtWUiTIhZsYUVXIVI1cxEiqRdSxmhn7khiZpAiwq0UVpDPQTN8iWcckQjbVCHCTo2wsohR6PKL8J60/BpHc18tRYqS2HSNHI/2BdD3SyLMQIlc5e9vZDFdzobe4s6/mscjv2aca2Y9hI7hSDW0c8kxmPiLkUoVq+Wl0lo9NZyk2XeUztDKgJEN5sKo8IYTHQYACCBE39rXJX8k2l+mUHJGPToSS7ZiLJTmo6aytkqpE9RAi2XfYnaqjGIl5qDghYkhnmTGWlODySHZSlPZGJ0ZU8RE90MmRnxglgwYTapH8OsQ+tH1JiipIfRdsxCkmdSQxqhpmNCCdou8zn+WRI/o9ifRi8Yiy5iwbMdLLN/pF1kdwXJC/78yipwU7l50ubu+ftW6IsuFw3zTPV+tHAdXINKnJtBAVyGU2C6mbJeDZ+i6fP1tbna2OSCW6xIqNwmToxBNPxHe/+13svvvuzehPayFDbBwkqAgBspAhk/x4yRDdt6hDPOKK/LCIifg/lBQhVqYzhgjoEGYy3lbRCZFECCGKIuVDBBiEKBYp1HclItfRF7FarK6d9oczDhmcUQT941ZSJAgMIStJr+RRKlz2Mx0ctRhE8nR5WgdAunCphRjR2EMZNYioRUCWBJlpETGjyWtmmtLUsT3mM5Mc6YEZRUmab0aqpg7XtmnyQJYEmaYzmVaUwKR9yCJm6XfoQsyYFmtIpRNSnIcQ9Scz0DtIT8hQWmWOq2ycB72WVfObqUM1MlGr2cztB6TDZhqzlbdd05p9sro5SkrWPBQmQzJewHrrrYfvfOc7OOGEE7DOOus0o29djrpIkIUQcSNNIz3kwZUhR1WdEPEq1EOPSRUIyKhDiERUaY0UxcKclYaoTUmRMpu1IXWsBvIJkeFUDdgVovQUbOoQ3U7+q6wYjDOlFjHOxPJpQIYUpUSIa4N8lhyJPsmjysGVkhgJZQYi5KgmYiTrgihG3LgCDOjgemBHBtJmQdVIlLCTI5D20qtBEaIYpMj6EBVtzU50bGoQd6TLNGbsyybT9LDBNE/9MQfqImqRC+Y5mSRJfPfcWl4zMTGd9JnkSJR3q1GNMMnY2uBGH9OyblUoNK3RaNR1aBRKhap5KEyG7rnnHnz22We49dZbcfPNN2PcuHH42te+hpNOOgmHHnpoUHjtbgWP+SuXBJHtDAFKHkxpuvFQDVWHeEqOJDGCixS1MY04KZUI0J2rO8Tq84rwSFDHaoMQqUCPEVc6gCJEcUqIWCwf3mGESL7oiv8xOE+W1WBcI0UVZT5Lj5wO8oIcydb1dP3ISjPxqEcMDBWeTr2tQCoR8thuYmRGr5bExmZKkyQtJnWkKS1UNRLn5zKfuQlSEdj9iLJ5tn0bXIQiYtlMae2NIS4w9QOS6hC9XiYpCj22fkzy4pJTVvaxCGQbpk+TpggRglQrORLHyHbO52RdDzKxhzxEyKYK1XJtIwgTeyNg+fmVWIFQk8/QGmusgbPOOgtnnXUWXnzxRfzhD3/Acccdhz59+uDYY4/FmDFjMGzYsEb3tfPhVX9oHpzbGglyECC171lFmht3NEvqSFLEktdf2U8WAVEbdFIEMdIK01YyzCdT47l0pDZnm7n8iGg8IhYly3HEIjBjR1UoTtKZuy19cLNYDtAw5P8sIWIsRlwVJEuEwxL/BQkySZF4VMlnp2opISiiVTtBkkekeZRsqGtuUY8qSbumaiTISUqMKsmAzbX9lOSAp8pR1ZYPu4rEjL4qEiIJAqlPyZFNHZJn6nK29oEOwD6TmexbHhQhcKTDYSqT11KqQ5QQ0fZ8XcgzfZm/2szxtfzazTkmeUnVQAGN9NA+esxqPmdsJO37TGJF4hOFrkSf5yekXW9LkzH832ct34D0E7K1S17VOl2paSWVakVDXQ7Us2bNwkMPPYSHHnoIlUoFBx54IF599VWMGDECl19+Oc4555xG9bNrkGMSs5nA5LaLBLkIkO5D5L99WUQiFEs+EktixISqw4FqzHVCFANoS1UiQCo6ialLPpZqcawG0nXUEv8jVR9plJtI7dn8NuIkKGTiM8TIduI/FHMm1hCzkCJxPVJiJBUjwFB4CEFKjmpEaSbXmmybsY1s5MiqGimfnpQwSSNiup+20yH3PSRIqkjh5jRxTJMYSXXIpgxpcZgCYLtWLpNZKFLlx20qA1GHInKNKSECkAmp4D9uGAGyqRu2OrbyNphE0fQJogTJRY4yvkcO1cjWZ1ucI9qvWqNt20mMXWGzqUKueqGgS+V4yyWdMfubR3w6SzUqlanmoTAZ+vLLL3HffffhpptuwkMPPYSRI0finHPOwTHHHKPCX99xxx34wQ9+0O3JUIYEGepPHgGiChCPdeKjSBFPy6THDbvZWcTJfwbGyHYEMMYRfwlEbVyZ0SQ5Ym1cfJIp8bxNECSe+AAxuf5ZWwXKjyg2H6UJIgaxmBlP1zODIEdQUbBj8USKYkQRkmjVST+Wi8Vc44qIUB1VuIpWHVc5qlVBcOIqA49FdGouTWTGtrimTG0DxoOWMzUyp0qc/vZNofk3UBOMeptNiRfIWzURCEV/WFpPmPaSAY2lpj6xDxGBm6hFkuyoMjw1q6m3Yp6WiUm/aaRdUTdd742aJNL+cTXF3qeA5MGnFNkgfZ10cpM2EHFBEjVTGS2XbFcTwhcl34lavQaCJIQihPBwS75ZN2/wMqf4V01uYpQXZh9J7tLyOhHlKl+0mRLvqlnWUJFsZIfBTeJqdUQXxzLLJf8d0eJdMYhU/YCvV6k6hBzRyRdmu4zUkfuctkNIUu0aYIlWQGEyNHjwYMRxjG9/+9t45plnsNVWW2XK7LffflhttdUa0L0uRpyjBBnmMOoPJAkPVYA0cmSQIJMcSdiIkSRBvCoIEI9ZohaJFzvxLOFKtYk7mDKjxeC6/1GU3sgcSM1dAFJ/n8SPiDpW5y197fMhSmmCKBrLwdCGGIyx1FzGAMa5IkVSJUq3xUVghBipljhDRS00i8xbcMxZdkYVKVIhhCTtKye+P+IqysVWNWduq7qjq0jS70gO5OpqsazZLGjqviWNRsGWZSqg6gvTiJGE7buxESQHXfbCpvr4IB3PAWQIEaCrRFRZCu5PhtxYyKFGkJDJt7cTdjzbtVDEBsQJnOll0zJMEZh6VCRZzkY8VB8KUgAriaHbOcvmdBYEWWLGPdD1U+xLM1nzUJgM/epXv8K3vvUt9OzZ01lm9dVXXyEWdC1MhAzlx6cGuUiQphA5fIh48jrImFRgeIYYMZ6azuR21CZeh3hMiIfUhaETIqHuxJofkSBBsZsQmVPuAd2HSJniCCGKOdCWms9sA4EKKh3FSiXykSKAOEBLXx5ChGzX1sxPj62nMaImyTayfkrcQ44SApIQUw6yFAcX+R2mzxF0YmRzxGby8pNzp47YjJM3WiZIUfqGS0MS5BMjIG0rD3lDJTfKyOvjUocUGXUQInl+ps9UiIIh4TTfEJJp5tvIkWs///gpKHmm+4BUwuzkyCRGAHTybyFGog3jG7OEJ3ARpKLIXCcPEbIGZLT8uOolC6YSJBGqDjUbnR1jaWVCYTJ03HHHNaMfrYs6iZBLDXKRIDpImzPKTPDEHCaIkEGMDFIUtQFxR+pYHXckxKMtOZ8OnRABiR9RxEXU6jYkZq3IT4iA5CAJFUjKJO/pmQjZ4heYKETIEiIW8awTdcwT85KdFInrmJIgwBgHuJEASnKMa2yka3vJNa+o4wiCJBWkiiQ7hByp8iDyvDGQS+ISQzhja7PUSDt06n6IWiTrV4y0ikUtUt+BIlY6MSr6TA6ZRUbDAgDIqjoBhEiRA6ISibbDelxE/bGRI40oBSpDNlCzFpD+XE11MUt+UrNWljgxgzj5VSNRznLdPGt7+wiy7/x9M/SaCUpo5D2m5+uO1C7i0wqqUYn6UEag9qHBRIiqQS4SRAlQ7BigNVSBiPEMMYKMKQQAUWoqiyC2NUIEJKRIjDSsgxAiQCzjkSyuyuOARV6pcw1xiGZxEuyxLR16zUegSYjSSxAn1yoGZ4kS5CBF8tpxahYjD3DzunKXKmQhTSnxSesCQIUlqpRBkDiHhRxRx2pDNeLpKttULaLEKE7MP4wXU4soAYIlTQZvBBkk7YvZGqpajYOANrCDfvd6+ACZL47tJ0RAlkBJ+Gaxhfj92MiRIkkOZchFAMyumHd6xhxLlCESZkxXw0h9UzWyXQdnJGsHMZLN2AiSGaA0BLZ2NLKpysl95ixTBNRvyO0LJQ5E833qkMhvvmxTEq7moSRDIYh1ktIIIuQiQbaBNqB7AJBGdk5GQDmWs5ghaouBWA4yDkIkjiqCJ8YAYmFSY8pkJsiPIjE+hYiqQ6JTkP5DHLFShnibnxBp152l/znnTlIEZImRfO6axMdGeNR1dVx/XWXiJF3/TllS2EWOlCcVT9UeRR1NtQjpFPHM1H3kq0U2UkTPJ48UAWRgJOcvBmE/OcobJOR5UwIkCaAkP0rRIGkmIVL1CSny+djQczP7Q8+PlrMpPzbyY/6iipo3qNID6OevnSNScuRTjRpBjOTxTLgIUhFkrlddrdkRMqNMkhuupdnVIRshajZKKtQ8lGTIA6oEAVCkSHOWRpYIpenhRMhFgoJmliVPqCoXqlAUp0qRfAWKOyKwiBNZOCVEgvAIM1hyVHXCyrzVljgfSYdqBBCiTD9TNiMWjk1UKOE1nEz31wkRyEOdR/K/IDo+UsQAjRipa0kXbSUkiYKqPTZww0yQNcVxQXpInuyTJEeMmNWYOkeeKENRQorEQ9f0LyqiFoWSIpf5zEeKqHlFf4P2/w7MGVTyCOmAL9QhkxBpA46FEAHQREnTVAb4A/C5/H5M9SeP/NTjP2T6CNE0wELwZD7Lqka0Pw0hRoCVHLkGaN+vwFUnc70cqlBRcpk+Wdz5NlOXqR6ZfkKdTYg6i3StjCjJkA/EJGaqQyIjO2tMlg8hQqYalJIj/U73mOiTBvS7VVOK5OiX3NWpOUJQGp6MNjGSmESx/pFECTHX/IeE0iPJDSFEFDZ1SJrL2qJktXuems06JClCWroDgKES8ThRhzykSFyWlBgBuilDkBW9v+q6O0gQYCdQJgmS5Wgel35DxHwXc6aCRlJiBB5rZjTt4UsIi6kW1UuK5NceGWkpuUlJkRwAQOoAxQcpmzmMmstsCpHNZCbrRSyrlNicj80+uPZNAuQjPy7zmHPgzyFrmhqGfHNYCDEyyU8eMfKvfWYfnKm6FwoXCRJ5+cqiDz6i4lKLmFGPqkNme5QQlei+KMlQDkx1iJrHMmuIUXJElWZz35juTdP02WTIpJlgUToAy9lk8q6MYSdEXP0XZEPEISLnmpAfxBZzWQSL/xBLCZGzn4nKEIvyLIbyH+Ididks+TVSUiRJEA0JIIgQEHcQiSFmYBWuSBHnTPjoSGLERb681vSKyuvLclb/dBIoQ20CdBJkpss05iBGKVkFYi68iqRyUoQUdUjna/L1yxOnQp6ZZ6aZAwIdDBpBiuS5yi7kESJZB0j7bCNFQNa/xoc8vx9TlTAJkq2MrT0TtmtlEh5AJz2yjEv1cREjjXwaZCyPGInz8KhGcBOkInARIdf1rwU2c5hIF9SGtk3VIaowmTGGipC/WlH6DDUPJRkKhGkaS9Oz5jE9j+n7FtOYSYRMIuXvl03nTl+FbYSIJ3YKnhATyWN4zEVku7T15L/FXAZA9x/yECLq5RoljyFjaQ8mZ6tFUDPMxOw1AB1I/ZvakmuXpJkqEQOUUgRAI0byusv+K4LiIEHemWSyjENtov5KSA+pkSORJsisfYkRKBNaUVIExtDG6zedaQQKdpVI7mlv0jmkyDSVUUJE24WFEMn2KfkxiZI56Pve2l3KkE/9ySNIZn2Rlz+QyetLfYVsypaN+NRKjMx65nkEESMIpdlK7HJO2/kbsRChorCpQr40ehyXOkTTOzvoYkmFmoeSDHmQ8RmSaRZVSOaZKhAAzTym2lB5diJEy4fMKotY6jCMiGsqkUmIqCMywAV5UCONNIvpn4y5LAay/kP5ClFKyqQ6lKpGyqG6A+Jp05YlRELpYYjaOCFChBRJlSy5hlItgtpPr3tW5TH6mmMuA+BWm+SbJPVXovWIQuRbYqQWUiRkPm41nRVViWKki8D6VCL5ZmwOND5S5CJEgK4SySFAWzbEohL5fGNCVIRGkR9KemzHtf2q0n6muRr5AcsQJB/xMfMzgz/57q0dQTFiJI6dJUeAm+y44FvWxEeuQ2CbQZb1C9LVoSjphJwskC4nlCVEJbovSjIUgHpUIdM8Zp01VpAIpcH+eKacIkUOQsQqyXEMc5noF6/JXIaoIjvhJkTJQrAi7hAZMqs8zYuSgT5K1k7rgE6IYiTKlegni9LvxkaKGFWLFDESh1WuweRaMzP8tHG9KSiRomqT/C7EsbL+SmqWmzSNJWYyPYp2baSoAxxRMr3fNJ0lXtuARSXqYH5CZKbF5JguQiTrSLimMZt+M3QAooSIms1UOVLXXGbCNWjbkOs4bZTLpBsqGc0z00MhFRxAXoN0ABb/mTWmkEsR8uWFmtEy5+K5xjZyVAtcRMim3uVB/j4lXGqQa1/+hm3+Q50xrR6o7bdUIgwlGfLBIEFUFcpzmnaZxwBo5jEXEQqZYp8x48hYNwAiNXpBPS1jAKgmZpNKjLgjQtQWC98biBubRbBPt08uCDWXqen2HVXwKFKkRhEiC5TvUPIYYRBmN9VmnEy/jxMfoQ7dhCcJkFSrePJffC+JQ3XMieKmk56MCdJlItNGbvcjl3Oky90niOLsd2dzlq9AVxJl4MiY/AbMNdhinpiMOEOVJw7WXFzJinxIc0GM6OwzIa4xmNPxqwkp4iotGSCY4sFIuHPGlBbDPePMRop8cV1Ma69GpJASA0oK6PprtJwc9CV8s77NbzaU8KTpZj1Cks223d0AkDXlMS0vuUe53OdaGUWGkpNl0K8HADJrMXutWFJJpYP4Wxn1AP0aS0LmOo88MpoHl/9VPc1SBZPBTvTpb1qdk0Mh6iyUClTzUJKhALiUIUBXe7J52XZovZr7Q+VpRtOZphbJpTmsbUilRP2HMpexSvI/x1wmOqCezkm7PCVERRClD3GlECEhP0hCE0qVCKlqkJ5PsugsuKYYCSUsWbstTs1nADVxZbtDr5vXgd1SxlSgpHkudeqGUoakgiTVvEpCIzhXEZkApNtCFWKIWNp3qhYBEWJwtBHzmXjIJz5EgKhAlKJaTGehKpEJHyGSCFWLoAYjppWjSol5bNq+dkyyXSsBMvNpntm2ifSckr6SX7cgJpyoQCz9DlR+qiBFsCtHeaqR2XegmDnNfh72612LH5GLTIY4q5v+bJRAZ/qrtrMO0jaTmXoGuE+nRDdASYaKwENgXANmSJwg36wxkzTZ/JFshMgcMKk6pJx8eXKTq/+pM7V5a3ObuSxiwqQDBuk/pD09c+MOpY8eFgMqrJkkNdJkligaQYRIrkVBc2kwSkARIwlKkGzwkSZVRjqmW9qU5MhFjGJVRpCiSiVWKlF2IVq7CU1YGwWblURSnT/niTksWTI38ScyTWdqcl6DCZHNYTUELrUoa4ZLvxjqgGx+o7avmH6lNl8fGwFykR+XKlT03CX5AShxYVqejxjFSEkRkJahpAiqXEpYzDytTy5SJDspy3mIkewfkE+ITZjt2LpRrwnJPWssS/BNk5ms02yUhKt5KMmQBy4naWf5gF+qzVfIVyakfZMQaXkWdUjOIlODc8S1cjy586nvEHUBcqpDyaNVKDrM8eRMYMun6hBARmODEEXpLDZKiFJFSBA1pQZFyXUAIUEGUTMJkg0hpElT7QhBknVNYoQoS4riagREHJFMY9AXoo3JIGaSXsYAni68Ko8eg6ON64SIKkRCOXITItugZhIikZ6dfk/LA2HqkAmqFslztykx5nDh8uUwFRub6UUSCFreRYB8xCjbKztkT+m1FP9TckTzbMRIvU+AEsJUQaOkCNBJJkheTaSIngRpg2bVS1gA4zuqg4GYpjKT/Ijt7O+Z/vbVdUf2O28GGnH9SthRkqEcuByn3eU74/2gMXCZylQ8H4epTD4NNHUoIVhp29JsFQg5u4w+UCIQlSMlRCIdOiEyRl/pK5T2QbYr6YGF/AT1t6C+b7MHkJHdRoqEGgZ9Edqk15E8f6ISVeMIEUsIkCTGijSkVyqEEJkkB9AJkS1IHU3jsJsXQuAaTLyLt0I3iZlfad4AZVNwihAgnyqUVTPcfTFCG+pER6Xp5MimGJlqkY8UJQcWaQ5SZMuT9ZTKY6hSatsgRubZF3lSWpUg0kAoSbD9Hl1EPVU27eay2CjfWU7UJZqDkgzViDwVoTtDqEQAfWxwqQRJgqQWhErKVKTSk5rLggmRFofIUIeQ+g+BEBwOTob5pI/IPmDdpAjZ0j4lC4kJMtdb0mjDHBGQKkZKacqQolgoQMp+kapE1H8oJUexMqeKB7SQkiIAIn6lnxDxHB8iyX/T9tNLJwkQkA4QLvNCrepQTAZx2yWlA3CRd3Nz8KfHKkKAzLKU9LgeE3RmnKwFpNdZEJg03yRHGWXIkgZWPyky82zmxzy1yEaM0l7UBqcjfh1t2tQhX5r24uDpUyPhI9Ql6kNJhgLQLOJj+pl0BWx+Q4zccNJUxozXb6UK2dSh2E2IeMY0FiXlA6CUImo2kya1xBwG+xunSYqE+Yyep5voyO+fOqdby1nJEqljGxFourIBMURxQnikCkZVImIqo+RImsXELKGE+LAwQkQVIm4QIslV8/yH6Bt1iLmsKPQYPDoxsg7ivrY0VSGfAMn0PAJUxExWNVKzKlBKkCg5ipL2TWWIpjWbFNFzlaDvPaHESKUHjPGNJEA+Mm6NRYR8f7h6Z82FYAV+B+9ylGSoBRGRKfJMDk5Q7iAZ1LlgtBXSb8gkQVmZAMZImd3OECAPGGNqQVarOgTdf6gIIRLnZSpFWWKUpifXPUcNcpGlLDniql31nZmkyCBEctaZqRJRU1k1jkBnmwHFCZGqy9NuZFShAEJETWh55rJafIfUpfKoRaF1YfSJEhkbMQolQNzY14+dhfnzEjPB0llK1NwpvquUAKXlGk+KXKQnlxQBJK6WrtzZygK1/Q6yJtEUoZN16W/f1jed+DR2gkAtKKfWNw8lGWow8tQeSnRUnYTkhChFecTHHJBdU+ttcE7FN0iQcqCmkoEKxEgqRZE+guYhz+maIDWVuQmR2rb8T9fHyKo5itx4rp02c8xClnisfxc6MTJIkYcQAdBUIpvZrBLFuYQofegzbbCWg2sb54oYqe2E3HBKenxMU55KQojyzAuNQC2Dg4sA0TyXChRKgLSBOaePabweptqgM8FouyCkSKpF9ZKitK86Kcpzps4jRYBfLXL9DnzvHm6zY7F0F9RvNJCodwUhKtEclGSoyXARHKr42GAjTbnHoitK55h0fKABpM1g0tTsZZrKMog9hKgQ6QFMdYg+eUwfIo0QwacSISVFgHqddJEbvV9uJclsgxIjGynKBtYhhAjImM1shIglAYUoIeKQig2DjKwozWlKE+DiGsRIIlYnhEiF1PQpRUBGHaJXxWcukzAdUF3kxvVr8d0htjqxtp0lO2a6TQXKI0AmYYKRnj0HpkqYPkMmMcr6CPHCpEhdY2kaRZYU0dhNDSFF0NUaqhjJfIlC5k5Lmu2xWStRyVOHAJ0QNRulLtQ8lGSogXCZsVR+ZB9UpUJgqkOSEOURJ3FsNxFqlBlNI0ZUW5amMkBXh8zXwtx5uQQBXplqdllM07KqkOynTSWi52YjRhK1ECTTzGYjRdJEl1GJEgYi0nkuIapEQDUGKCFiybR7SYhE+CWuHu7qwZ6QJZ7IQLFShTiq0GeYhfoP5ZnLirxJ+34tIYODjQDRurWQoDwCFOJEnUInQYAkSLoClI0dRElOGCnKkCSWqE8GKaLBG9U55JEeI5/ZyiCfGNnKS+RdS9pus5SaPILfTJRmsuahM8hsw/Haa6/hkEMOQf/+/dG3b1/suOOOeP/991X+nnvuCcaY9jnqqKMa2of8WUU6CSmi2tBBVZZljKsPbdNMc7XDIns5rY+m2qHFRCLpavTg+n8bqHM0nX1my89DJFSgjMok0xMw8RRPt5HdZ5H+HZr7YFz/WCDrZOqqfG58B+T48nuN0rIindRl5ncofg+McS1f/kZUHhPblUh4l6h0cERMqD4RAAaOtuR/xCVBAqIkSKNK4wC9jFFyeXy3gKwjvxWpSkBLS8uClMtcR89xTMSWj0jnGpnhWhmRxyGIhzSHyaVLOrR8rkhINSlTdezHADo4R2x8qsmHpnUkn9g4vtk27XM16VMMnvQRWh1Ozk3uV419VYZBLbGiX5/stZFls9fRnm8tQ74bzvSP7zu1wVbXWdaR7oP5u7WhQe+bLYvHHnsMBx98MIYMGQLGGP76179q+ZxzjB8/HkOGDEGvXr2w55574tVXX1X5c+fOxRlnnIHhw4ejd+/eWH/99XHmmWdi/vz53uNef/31GDlyJPr164d+/fphp512wgMPPFDo2KHodmTonXfewa677opNN90UU6ZMwUsvvYSLLroIPXv21Mp973vfw6xZs9Tnt7/9bc3HNAc6kzSIQc4gHsa+2VZEiIwsz5gxGEbpIBdZSJCEzJcfsz2TXLEI6rhpm+7z1ZA8ZdI1v8j/5MN5ui0+sZ30OIgQM6QsOwFiOglSREluQ9u27dvIjJPgmOTIQpLcbXLt+1T5yfcYVbj6DbFI7qffYVThiCpx8p3ZCVElihFFHBWyLQlRhfH0A/k/FtsJIaqAo42L/QhAhXNUAJVW4cK8VuFAG08Jkaibpst9SqKY3AdLyZT8GuV/npIiUS5sePERH/mpksG8CkFuOpL0aqKoiE+a1gGOL8n+l+D4ErHa7iDbVXB8yWN0cI4vE6LzJY/xJY+TtmLtU00+elraTjVp58uEIMl2bMe19bMjs43M/peW/So4OhjHcsbRwZCk265ZksbEpyo/qmzySfJjUoZ+DzEpS7/DKi0f8HH9DmDs07s1xB/I525JZ/FJdAYhcpHKWj5FsHjxYmy55ZaYNGmSNf/yyy/HVVddhUmTJuHZZ5/FoEGDsO+++2LhwoUAgJkzZ2LmzJm48sorMX36dNx888148MEHcdJJJ3mPu+666+LSSy/Fc889h+eeew577703Dj30UI3s5B07FIzzkLjJrYOjjjoKq6yyCv70pz85y+y5557YaqutcPXVV9d1rE/23UMpInKRVrlNF2qVy1jQxUDpYq1yX5aVbdBFO0UaUWKoxabAVAubwiD2U0JFyRBjQNQWq0GVRUgH42SQjtogSERbUrctISJtgqSwiAFtLCUtEUsJjY3I2EBUJvWTJEpSSrbg2bdty/bt+1qaY9+Vli1kP89s+1nFjZu/LZ6Wzewnvze1kGucLhAs06qyHE/LVTnJR7rAaxViwdcOQPxnTL3NVxNnW5WWDHpSRZC3hairp8NIS81SXMsH9IezGfMHRllVznKtQ2aKmcf1mcKo2cu2HXOunRdIGVcfbTDfP9Jp9NTYBbUQa6SV0bdpHV2RY161zrYP6MogJbGZvsn/PFvWPE+TaJh3Tr1v6eZ1dxEhm+DNPeX03xTP5F/03m0Fe1oMJ2/4zYa19ft3766pHmMMkydPxmGHHQZAKDNDhgzB2WefjR/96EcAgGXLlmHgwIG47LLLcMopp1jbueuuu3Dsscdi8eLFaGsL99gZMGAArrjiCpx00kk1H9uGbqUMxXGM+++/H5tssgn2228/rL322hg1alRGsgOA2267DWuuuSY233xznHvuuYVZYgjyFaOsOmQzl6UmE5dSwzNtm8fRlAcLEaJ9NlUFra0ijtfak4Rn1SGS52+nwDHNX6ztSWsrl8A0m2lpjn2Zlmsa9ZjT9P2sUkjNZvK7kWXpPq1nU4gkTJMZAKvJDJCDKSf/uTKZKdOZTONZ0xloWZ6a0mDJF9tukxmgK0RF4PIHshEhao5Ky3HddATdXEa3pXkrLcthmraomSnv06HVocfier+kac3XN1InJu3K/KpxjrF3n+vEV7t+Rt/kx2FGg6WMJBycfLRyxsf93bvLFSFCKxOWLVuGBQsWaJ9ly5YVbmfGjBmYPXs2Ro8erdLa29uxxx574Mknn3TWmz9/Pvr16xdMhKrVKu644w4sXrwYO+20U13HtqFbkaE5c+Zg0aJFuPTSS7H//vvjoYcewuGHH44jjjgCU6dOVeWOOeYY/PnPf8aUKVNw0UUX4Z577sERRxzhbdv6w4jjrKnEAe+AxyxpxFwmyqSEiJIaGykyP/Q4LiIkzWM+hPhBAalpLAh5fkU0vUi7gFNxyvgPAfZfekFCJNO916kGQqTSchzflXrn+R2aJIiR31fEuEY+UuLDFYGRvkJRMoREnBOSw0ldYgYjBMgkRHKf1hPbfkIEUg5GORtcipCZLwdnsa2TFlO5okRJK8t10qQTEZ0AFfnTCVI+KeogpCj1E8qek+4nRAkUtOOZZSlp6mBZUmSebygpynw8xMimBoaQJFv9kKCN9t9O68B5DWv4TJw4Ef3799c+EydOLNyn2bNnAwAGDhyopQ8cOFDlmfjss8/w85//PEi5mT59Ovr06YP29naceuqpmDx5MkaMGFHzsV1o6dlkt912m3ax7r//fgDAoYceinPOOQcAsNVWW+HJJ5/Eb37zG+yxxx4AhL+QxBZbbIFhw4Zhu+22wwsvvIBtttnGeqyJEydiwoQJWtq5Q9fH+RttaC2vLcJJAyMmc4WlMGLOFqPl5Wwi26wxvX1RLzTgoo0IpeV1JcGpEIXSZE8cIS5XR6dlmwQ5xV9DBP1Jluxrs/pIGXO2n232X1hnuNNkZi1uOY72/SffjTZ1P2CGGZJZQowJIhMnxeTARGeYVZO5eXSGmVqfiizZQafZV5ESGNuCrioPcK75BKSz2zjSr8M15V6WC4FLERLbXMu3EaEMaeK0HW5tR6aZfQhBZK3HtLz0ZyvSY7JKswyHANDgjFyV12eTybLymtM8Si4Z+R45eRjp369KpH3TT0EPp6XOw7hGxm0T8fDv2wWTBLm+kxDi1NXIi1lVBBdccAHGjh2rpbW3t9fcnunrmXn+J1iwYAEOOuggjBgxAuPGjcttd/jw4Zg2bRo+//xz3HPPPTjhhBMwdepURYiKHNuHliZDhxxyCEaNGqX211prLbS1tWkXAQA222wzPPHEE852ttlmG6yyyip46623nGTI9sNY+I2D1DYdsIK2k1diuiq8KJNOl3YRIgBJnj4I5gZc1FQinQhJ81gess7guVXscYZcUaldaCpRqpHUeOrW0mZNdQiJlvsgv6c8yKn1kNOvOVPmsmqy9ErEGGJOiJA2dZj6n6SDqCQr2Wn0WTKj6pOylNTIOqGECEY9CmpmEf+5li62KemojQjZ/Yx0wgIARVwyY3KDm+THR4ri9C2L5DON8CD5XumUe72shwDZSJIRo0jvaz4pMr+ntH1j3/Ez9zk3hy7b4VKEXKY0rUyNhLeV0N7eXhf5kRg0aBAAodIMHjxYpc+ZMyej2CxcuBD7778/+vTpg8mTJ2OVVVbJbb9Hjx7YeOONAQDbbbcdnn32WVxzzTX47W9/W+jYeWhpM1nfvn2x8cYbq0///v2x/fbb44033tDKvfnmm9hggw2c7bz66qv48ssvtYtlor29XU3fk5/2yOY8QolClnxk0j3mMnN6NZ01RmeMucxjNnMZrWcjQi5VyEaWzKnnXogRI/UbSqA5QzvrFizvQ+AvWjufIudZB0KIkI+w2vy7fNPtTZ8hWUeayxgz/YTkIKaby8R2feYyGGlq35iVY5rM6CmbDrtFYfqI6AOabhoD6iNCnKd+cyE+Q7QOt0yx95nPuOybUc80i+X5Eql2tDxox6ZlbKYzqb6FmM980+9h7JvmMNqG+bF9780iQp2NRprJGoWhQ4di0KBBePjhh1Xa8uXLMXXqVOy8884qbcGCBRg9ejR69OiB++67LzMDPBScc+XbFHrsELS0MmTDeeedhyOPPBK777479tprLzz44IP4f//v/2HKlCkAxNT72267DQceeCDWXHNN/Otf/8IPf/hDbL311thll11qOqbdjBGmDslAigCswRVNhQhIVSLRRqoUOftnDKCRQbJMIhR20r5BucbhyFiZXkurBxaJwGo2c5TNQz3KUi0wgzGKNMNsWkAdEnXEG75a8Z4EZBTbEOYwUx0i5jJpZoOhCtnMZZDlU2FBqT+mQhQR9SJPIaoFLlVI5pmDGyUIeUTIRoJgtBn200nLR2BpO8QEprdFzV1pPVMlirVyukqkK0F60MYQlUilEdOZnqefW0YpSk9D5JOvwXbNarh1Ndjq1kuEXOWahbiA0thILFq0CG+//bbanzFjBqZNm4YBAwZg/fXXx9lnn41LLrkEw4YNw7Bhw3DJJZegd+/eOProowEIRWj06NFYsmQJbr31VuWXCwiLT6Ui4uLvs88+OPzww3H66acDAC688EIccMABWG+99bBw4ULccccdmDJlCh588EEAwjyWd+xQdDsydPjhh+M3v/kNJk6ciDPPPBPDhw/HPffcg1133RWAkNT+53/+B9dccw0WLVqE9dZbDwcddBDGjRunLnityPXtsPj8aL5CRpqNEAGp2UyCms980BQADxFyqUJprBuz4YCLY4NcqDXQd8hlUijksG3C5ifUbBRcRqUIbMu7sAi5vkNy0JS/T0m4o+S3F0M3l0mCQ81lIct1ALURIkF+xJaPEMlBPJNvMaO5YKpCMo2qKRS1EqGsCc/ePxFd2jxiPimSa4iZaQCUL5FpNpPbkhCl/dVJU66ZzGU6S7ufS4ponmkSs029z7t9Q8mS+S34fIpaiQh15nFMPPfcc9hrr73UvnQpOeGEE3DzzTfj/PPPx9KlSzFmzBjMmzcPo0aNwkMPPYS+ffsCAJ5//nk8/fTTAKBMXhIzZszAhhtuCECIGZ9++qnK+/jjj3Hcccdh1qxZ6N+/P0aOHIkHH3wQ++67ryqTd+xQdLs4Q52JT/fbA0A6iIoYMEmmERdGbZN08T/Z57RcmiZhxiGibRSBZtryECGR7yFDjCNK4gohIv/bEmUoSv+rWEN0G2KbqkA+hzbrVHwjsGOanpcGo57ch32fpKn+5Oy70mqJNWTmyzhCtJz5+ykad4jGGyoSeygGRDpL/iONPaTSmCQTIq0juQxUjpd5rjS5D4hBJ5uW/GdpGdUG/Gl0n5qMqCpkkiGpCnGt3bQu3RffD4eNBBV1eGWEKChToTQPkhhDtGw2llBqTvTFJaLtM7KdLavnISANSAmNywSqnZuWpsPnHxTy2uGqnudY7SJCvnL/2eQ4Q8ducETD2rr1vXsb1taKgG6nDHU1lMJAZgwphScCRIyd7LpTerlUIQKyKpFI01dTdxEja0wcI25RLUTIFWunMIhM4PLwLxaTKDCtDjQsCGNgWZMI1Qpl9spRhwCmnuCM1BMT1JhmLhPDYpi5THvLN9Qhqgb50qhCpKfpCpF23qjffEKJjQ1mfh4RMp208yBJgaynq0WJoiK5vdV0FmY2E+XtztVpX7PO1TJPqk+5prPkmKT7FqWInJtFLVKw3BLyWhShmqGO1bWqQZ0hPHelv9KKjpIM+WCYWHy+QzZzGc3LrEyewDSbpWlpOZMY2eB04M4hQiFQS1kEIjO7zCBEQXCpQq0MC5GxE6naCI/pN6TNMitoBlQLuALKPy01eaTT7Klak2cug+yTw1zmI0SUaElClB4zS4jAdHMZSB2gdoLkUoUkpHkshAjZBi7b758x3cQnrrtOilKTZWp2lumyP2FmM1k+azYD6DXUzWaASXb8pjPt/B2kiF4zGOcPaxl60WyJYbAKupkybhJkL985aOTU+hI6SjKUBwshkuCxUIc00kNHAoCYidRrXZKu/6gZ0kGSVaQ6JPPCbwDbwqsmCRJpuiIk06DSipMgAMYI6Ni21bHsZ3yFMuYvy3XJM5EVRJAqVCMJyihQDhOrq74E9VWT+yHqEI09JE6DA3EkTKRIBlBqyEgWcAVLCFGSHkPMKmKcAQygh4+5VJ9SE1mF5ss+8+QOIUSpon75dHCXnYX6sVPSJAdz85dRj3qkm9bcRMhGgkzyY+tDZJSpgiqoqQ+XtnI98e0SZUXfUvKkpyVVUtUoEQeZKqe3n5Jg8vtI/jNC1ijhMn2oMulMTxfnrrct6lNiZLleyXk3CnnEB8gnP60al6hEOEoyVC9YlhBJkxmP7SoRNZGBqkGEIGllZJpxR/oCLtLtzJR+QoTSsrASoex/FkSQlDpkEqI8WAlOfr1gJ+s6X+GaTYSsxyzwMkhnIgJQM89CCFE1cdSPuGEicylE0E1mkKSMUQUnqWdwYZqfKh/kHYER5ciiEgG6yYzBTnhc5KheUJLj+kmFlDHzFPEgJmWlCGlKDkDNZ6lSpJMUmZYSHUF/QhysgfT6CejKkuwvjV1EzyFXMQIyqhEtZ16bFO5v07WES555qbsQoM5SoFZGlGQoBA5zmek/VIQQAXYTmUo39gE7+QH0uua+biaTaTphkkSoCGqeXu8DjTcUuoxHI54O1GfH015XEKE86D5petu2mWcAtIjUcPgP0ejUlJSI/gJg0jyWmszAkfEhshGiDPkxSBKH3oaNENlMZhJm2WZBU4AMVSiUCGXbFIhIG9SMJklRxnymhGdKWMJMZ4BpDvP7E0Frr4C5zEjX8ujDzUGMzGtkQu+DHXnfha12HgnqTD+e0meoeSjJkAd+H6HaCRHgUImQT4zcfc0SIJpOiZDajrLqUEYV8iHUhFYwArVV5THNX3UixGxW1LSWN2PMWobbiVKtfkUSGdMZUYfMY5r+Q2Z0alf8ITCRDo8PUahCpJb+ACEEDkIEta+bZBpJgDh0s5hrELIqCh4i5NOo6EwyzTzlUIlc/kQmIZKtmySJQxCiiJkKkkl27CoRMnVk38NIkT0P2gNMUwuNOiaKfO++p4itHXswR72VkqZ0b5RkKBSWp2wRQgRADfi6Q7TbNGYSozz4SJDIdxAhYh6znXew75Dm1EFMZQCyPlTQ00mdTJ7rKWcSJOd+QN+NcrkzyhwkJt1vDBGqJfCFzVSmL+khWEYt5jJXQEZFiDTVCE5CJPqZ7AOaeUymMdgJEUDVKihFSrsG1L8GLDNw1YI8Y1u+062/PnWapvVtKlEIIRJ1UxOZSYhEvm/GmW4Sy6pEgPztyDqyv2YZmp6a1dI8ez1ZxPQXQAaRPTkXXvNlAAFydKdpKB2om4eSDOXAtqinNyK1hRABgKkSAbAqRRI2n6H8vprmsuS/GZHaQoS0Og5iZPUXsik+RZylCaxEyJZfqzpkfeXLr9aZREgvk22zqGJkhnaIYmhEyVoHbnOZHFABIFVimCJEckHXXEIkimiEiNvKwE+IAOqz5FeH0r6KBqtelcYOu29J/u+xyCBmI0WmShRCiFhG8dHNXC4/IpkfZ8qK3om0MNNZWgagV9VOfLJmtGwZZMlR2q2a4Z52b284xJzWDJQ+Q81DSYYCEGIu08oZhEjk6SqRjxTJ8hTZqMP2m9QedFGvYyNC1tljPlIUCOsiro5yCtq2kZ+rAuWoSXAQD48qpBfsHCKUh6wzPc+0q0VEJ+qQuXirTR0KMZepfkjiAzJwBxAiQOfNpnlMlYGfENFLYSpCeYTHF7k6yqkfChsRsh3TdP6lM8FMlUj3I5Jt6gqOSYhkOy7HaiBrNpPtmkQnz3RGy4YSn9joY3pddFi/r6Jvjhb41ENXTklOVhyUZKgoyGtnKCEC7CqRSncEWpQwVSMKX9BFmh9EhGidDCmq/WHjI0TZ6fNZIlQPzKjT+rEK1AcKEyG72hPWhk0VsvfPJMk24m5f4wxAxpnaZy5zrm6f+A/ZHKqLEiIgS34iS5pJiFzmMmVKIyTJnJZtS0vrU8JotZZb4TW/OIZW6iQt4VKJ8vyIFFnhQJGYRBwwzGa6qcy20r3NdGaWBRyO0w7SYyNOtnL28vXB15LbYt855qtywYjmoSRDPliIjyvdSYgAq0oEuEmRRLrOmb+b/tXmsySI7mtEyEaKKCLHtg3GCBfk+OwgQoVVIQ+KqEJFZpbVMmOsKBEqYiKTfkN56pB3AWBSThEiUHUh36HaS4jkQZD+XGzkRyKUEFFzmSRB+nnpBIemuUiRJA+5fj85g1XIoOkiRTZCBCDfbOYgRAJ2PyKb2Uwc2+5LRPvrIkUyVhLgV4tofraMXs5WvlGohdA2G+VssuahJEMFEEKIgCw5sqlEol6WFGn5Baa7m8RFjzdE+kH2TSKkUIT0NAp5RKhQW7Jutj3bMYLgWTOukUSoWXCpQ3nO1NJcFgOgq9unZQWcDtWAkxAByDhWh8w0yy7/ka8Q2YiRzUQmgxC2AkxSZCNEAML8iOR7A1F78vyIgHCVKOmJ1l+7+hOiFpl17NdFR/PunzwC0pm/ltIs1zyUZCgPhi6eR4jotkZ+DJVIwuo4XSMBcTlQw2o2yxIhah7Tt4lZpYi5rOCUerGfbvpmljXbV8hnHtPrFyNCeXGIQlShepRyGteKOlP7zGXmch0u/yGbQ7WPEIk6WUIEIHemGSVEtsvhm00m+6gP3qkqFCUXpBp4oWlEZsZYw00Zmo8WMZsVJkRwzzSzmc1EGb9KZNt3kyLRc1rHpha56kjUYybLLvVR7LtqDZpcohkoyVAI6iBEchvIkqJMHrKERuSZfiHuW1IjUg4SpJUz9zPbTCtXGC5C5IklBAQSIQ+KqkKhREgvVx8RytR3EKFaYZrKaFwrn7ksoxYRdcjnP6TOgThUewkRoJvNHH5EkvC4SJQ027nMZep6JAfUHY9TJ2lTFZJmuFqcqEN9i4Csac22mDG9xgCg+wfpfkRFZ5oB1PSZmtJ8KhFQnBTJ80gaUWnZevrjRp+Kr9e1lbdB1gghP0W+7c5Wasqp9c1DSYZCYSFEQDLAEQ0/XNXh2uDIKjI5e6PnxhqymNNs5Ebrm48UmYqQY99OcpB9MvnIS4YgWEgQKef1E3KYxzQSYkkLIUKdRYLM/LyyNlAi7iNEkpHIYIyMJRZdLi9TMosoikVdQK1fFoOjjYkBUigjojzAtbXJGNJ1zFgShygGT9YlY9o6ZbIekn1zXTMAWtuxsc+QOvUyQBEiJAN6B1GKhBJEFTCRxiGVLa7UIelPBKKeqJhKhq9NYaXB8oW6yJFp4rOtcC/XOYuNW1USDamWUbMZknOqauRJXjeodHlccU2SW53Rcjqh5OrYel9oXki+PMc0L3vNXKTEtTxHI9AV/julz1DzUJKhIrC87mVUIqRlsqqPfZ+mFV0Ww+yLa9/mG+RTh+qCjRDZyhgoSoRs7TVDESrkSF3D1PtaUTjmUJ5CRPpum34fwT7DDFwQCxmYEUh9iPJUIlG2Nl8in0qkTGREIbIv6ZESKHG2uiN184bScFBHaQnTdOaabUZVIoASp4QIW0iRbAdJDVt6nlokyroUo/T4Wlte01i2XT0/C5Zps0QJN0oyVBR5hMhSJoQEuabUu+AiLj5CZCU9ToUoRxXKg+d62BBMhGx1bAoQjDQL6amFCOmqjZFXSwyiBqtCEjZ1SM/POlRTAuQ6FgMyJjMQIpTxIcojREDGlyiWxzEIkTiXZN/Mh0mICCfnIE7YwuxFVZy0rFSMUlJEzUc+A0otfkNFfYvodHpxzuGECEjVpHzTWdZM5kpX6k+GFKUKjkmKaFpyZqp/9Nx0ZM1qFKEEyUStZLerKFY5tb55KMmQB7aYLQDCCRHgJUU0zUw38/L66U0rrBAV9xPyBlf0KivGzZ1HhGpRibTj5aQFOkt3NhFqFDJrliXqUKNmmBUmRIBSiXKdq4FM1GpbeUF8BLGRfXYu9Aq7OqQGaOJInfocuU1lFPIYlCjVC1MlCiFEsnwxXyKd+CA5d8CuEhUhRbQNauKzqUUSeQ7V5vXV29XhM8e1OnLeKUvUgZIM1QoHIQLCSZFZtl4zlS8uUBFylG238QOzlwQBYURIa88sY2vLUt7bR7rdeUTI2pc6n9pUHXKZy2zLdVijVdN8QDOXFSVEHKl6U6tzdYYQqf+p0iNXt6eqkEsdorPiAOEfE+pIXYvfUC0wgy7KY9cz2wxwm81cKpE4Psjxk/oGKcq2paeJduxmNNl2Ws6tGpnHMuEjST40yoOgROuiJEP1wEJ0gBxSZJQvah7z1bMeyyybqxIVV4UkJEkJjjYtERJjyEuOsnVt7aXt2rdDHaa1tppAhGpVhbIr1ev98ZnLXMt12EiYbMc2w6wWQgRkCRFgmL14Mmhb/IhMQsQ9/kPSXJYSBUEM9IjKKRGKxIXNOFKbxEjWqXeKvW9pEBMhZrNQQpSeg1slEseQsCk/aV9NUiSX+BD5dgLkTtevS970+MhCeNQ18JAkH1pFkSlnkzUPJRnKgdNURuHwibGSIllewlMvGHlmMqOMmxxlHwi1qELBgRKDYwz50mzHt7WXLV/vzLHOUIRsdULr+WBbywzQzWWiHILNZbnHdBAiAHU7Vmd8hhz+QzZVSPY8Tx3Sz4VppjI3iTHd58hxDcLkU5RsUamBcEIk+5LnWG0SIgAaYXWbzgKVInHi5HoUI0bJWZNyTLtqDGHkSPY5bdH/zMojS52F0iG8eSjJUKPgcRJ2kiJZz4SPfOUQJe8SGma+iwi5jmGmhwRVtKFQjCFfWra+jwhRtCoRarSvkE8dKhp/yIcwc5mdEAnyku9YDehEB7ATosggRBzEfygxl/FE4aH/fepQej60g65rYY9s3Yi3eutSHTX4EYU4Vqs8h0pkms5g5JskUNSxq0WiTD4xypq53OY0dTxHmRCfovQo2e+uVQhSicagJEONhMNsJuFzlra2EwirklTIqTqACLlQhBDlkCCgQURIay+73Z2IUCMmjxQxl2W2CzhTh5nLHApRcrJex2px+HxCBLKtTGOC2PCkXdNclg70WXWoCqggk1DtuxypmxuNWsIMwgjoKlEoIaJl88xmQFYlkm2KNDspokqS5vtDro1uRtPJRygxspnTbN5FLnKUHg9Gvh3c6EtnoJxN1jyUZMiDEN8dK3JIEdAkXyF6bF+dHNNYSJ4Gc96zLc9aL93MOlRb0kOJUJ5JTCW2DhGyoZbnnsv8FVreF3uIljFjD5nwzzDLEiIkbfn8iDjspjBAJ0ScpsNu/jLNZdJBmgZulOoQAz3f2tWhRsOlEtU70wzIms3kcahKBOjEpQgpMvvtNqOZ9UHyihEjcR3IYeSxC5CjEGLUTJRmsuahJEPNRI5vkImaZ5M56uUpRhmyk3f8OKdMsK+QvmsjPK70eomQ2q4hqGIziVAR81gtprQi5jJR3q0OmdeByfaQqkOmlw1VGQA7IWLQCVG6D69jtUmIzHTdoZrmS/NYuDpkTrO3zTAzTWIeC7pCPYNcZqmOOmaa0bJ5KlEeKUJyNKgyJnmhx0tLh/gXNYsYwVE2zUvb7AqUDtTNQ1d9pysfIvJpcnvaIqxmeVWmk+3dMfkk4DHvGiLkgWsKfWcToWao4eZvInJEO6dLY/nKRIyLaNSMK0LEmCAPDBxRoiAxpASCKWUmaQc8mSnGk7LJT5VzRJzuG2W4bC/djgC1PIetjOgDM44v0uR/kcZIGlQaLQ+SHkEQA9m2fp30sjDqNwommTLNKTSfkpbYUl6W5ckfSLkYPM3nPDWf0ba0emn5vDJxkiI/gCBGsXGMmNS3nosjzzwH/Zrox4VR1kStRoMSrYtSGeoKNJiCOhUlp2JkeRiH9qnOp4DLHJbJc5EYDwmi6fXMGvPFEaqFBDnLuchRnUTIZypzzY50rV1mRqY21SGlCMHtPxRBDGhxQjJicFSgm5wYB7hsn0l1BZZ1zZCW4YlJi0FbowxEIWJEFULiKyQoDRf7YGkhmP9hDJdMtOVYr6yKFNTcBnl9Ar47ihAVgPqqZPxlyA/JpvzI+krtoISIEuLkP11hnl4ZunRiFZQAclJXN9PJfoBcH1nOPC+5HppIh2ojsh4HRn2uPdp8M9PksXymND3ekazTeYib8ZZUAkCpDHVbSPWnU4lQjZAKUIbsrAREiMesobPGQuuxwDXuXMqPasdYJJgqQpbF1VWbVCFS6YlKpKlCKi8tK1UgBqnEQFeJjDJUAVJtcbNsqhDpahBVi1haDqQOGFF15DGYNmCLa2NXh2pBqDmEKiAUPqXIVIls5i1feVnWphbJuj7FyKca5alLNtUoTgizu7493cwzz1UeD578zgZv4KeEjpIMdRNQ8pMbcLEIEfIgOF6Qo26GAAEFTWXZOt2NCNngD+LozGo6JIEyCZCZb8I0l2l5SE1mYt9OiCJSlprORBmdEAF2QgQgYzJT9SkhIv9lHdmuzVymjqfOl+n9yDF72UxljYaNFNlIijPPRhw0UkMJiZ1ohJKibBu62apR5jRfX22kyH1tdHQ1ISrRHJRmshZGI4Ivpm3VqkTIAdJfP5c4WWwERdQgV3qQf1BBItRVjtJ5RKhRMYiCAokCwavam/1mJF9eS0GImHByRjozCwCkw7X8+cayvMe5Wh5SOEJzVJVZCrrzNGkzdRgW+Rz67DLTmRrGNlP9SPtPzTqmqQyQpsDOGzzprDEJbVZZwZhEsk5IeUBeL92kZHO4lmXN6em0bhxYjnzdiDlX5jPtHFzn5kjPnivguvvMes1EScSah5IM+dDJRuG61ibrBFNXTcgjQUaZkgg58muZQRY4zd41hV61Y4lKbfbX9B2ifRD+Q3ZCJElQHiESadmFXlOikpIgSYiUL5GZRusAau0yGY9Irl/GE3IjB1w6s0ydH/F7EedrjzmUuebJgG6LRVTvjCHqDySRN+MshBDJ83P5Hsk6QD4pMsua/XaRomwfOaifD0PqV+OKXZSZTechRK2Gkgw1D638vbcOTI23wcg1feWh3m+x0edmGvAT+PyGeBxAhBzmsq4iQpx3f9NYUZimMpvvEJ1dJstEWn7yH9mZZnLbnG2Wlrf4EBnmMuqHlJlhRuqIMtTklfoMIfmvO/LSc7Cn+1D3bUp9ZMjHhVrNZi7Tkq0OPZbLF8c0g0nzWRETmlku1KeI9se8LrY0M91lLitJyYqHkgwVQRNIUb0r1TfsG6zn3GLjQxDmPG3vh0aQAsiPFkMoITYmyWokETLRLCLU6CU6fDD9hnzT7G37JlmiZTTCUyMhEvt+QqTKGMQISEmQ6TsU0XrQnaB1gpQ6TjOtTHO/Ix/p8REjly+Ryg+Ygi/SSZsOXyLb8cxHQohfUR7h8ZVJ+5Ecz/AlMs8thBC1EiiRrPdTBI899hgOPvhgDBkyBIwx/PWvf830a/z48RgyZAh69eqFPffcE6+++qrKnzt3Ls444wwMHz4cvXv3xvrrr48zzzwT8+fP9x534sSJ2H777dG3b1+svfbaOOyww/DGG29oZU488UQwxrTPjjvuWOj8gJIM1QbHwF8Lao5y3SyYxCbkY0GY83Qxs5iZTp2m84IpmrO6SiJUH0w1yKUOqW1mITweQuSLR6SOAZ0QqXSuExibOiTLqf7b9jOkKKsGmTGHmoEi06l9pEgr5yAkmTwPsclzyK6VFJnlQ0mRma8pOTUQItrXVgFV2er9FMHixYux5ZZbYtKkSdb8yy+/HFdddRUmTZqEZ599FoMGDcK+++6LhQsXAgBmzpyJmTNn4sorr8T06dNx880348EHH8RJJ53kPe7UqVNx2mmn4amnnsLDDz+Mjo4OjB49GosXL9bK7b///pg1a5b6/OMf/yh0fgDAeLnYiROfHrAHgED1pk5a2ejo0/ZjNHdgdfoVZciFO78ICcqU74TlNRpBhDqLBPn8hczzpH4+XKlq0tcj7ZMsx3nqOB1zZt1XZUn7su0YUDqO/NnECQ2S+UjKxOY+k2WTAZHR7TSvgyXHZkAHxM+jI+lPBxO+P3HyvyMZBkU6RweEv1AVwrepCq7SebIdA6hyMbBUIWc5cZUmzlE3D8k0cY40PTVR6d9L7Y/nyGSoyBK2zMKmmvnPyHOYDM16eXVt9f39cPUhW8aWryl4dKmXTHl3mrUt6G0BwK/fvRPNxA5D9mhYW8/MnFpTPcYYJk+ejMMOOwyA+P0OGTIEZ599Nn70ox8BAJYtW4aBAwfisssuwymnnGJt56677sKxxx6LxYsXo60tzH35k08+wdprr42pU6di9913ByCUoc8//zyjVhVFt1OGPv74Y5x44okYMmQIevfujf333x9vvfWWyn/33Xczkpn83HXXXTUdM6Ng2FCnUtQZCpFVrWlAe14VKE8J6kQilDGZNYkIuWILudoIabNVQM1ePnVITrUH0tllMh0IU4jUMc19YhKzmctoPaoOmf81k5p5nob/EG0zDyYx6CrYVKKsYlN8+r3Ic6tEsq7/uMXNZ2Y7pkpkyxdpWZiKktlXF7paOeAN/Fu2bBkWLFigfZYtW1a4TzNmzMDs2bMxevRoldbe3o499tgDTz75pLPe/Pnz0a9fv2AiJOsAwIABA7T0KVOmYO2118Ymm2yC733ve5gzZ07Bs+hmZIhzjsMOOwz//ve/8be//Q0vvvgiNthgA3zta19Tstl6662nyWWzZs3ChAkTsOqqq+KAAw6o7/hFSFEN5CaofdfxCh2HWz9FynpVIIsSlEeCbE7SMi9vuxExhHwmNVEeGRQNprgia7DUVyjK2aZli/oQZdchz4L6DgHET4j4C5l5dN/2DZrEyPQbcpEpue0CVYVM+J2j9Y8PtZjNnHmZeqRNi7mtEaTIeiyD0LnyTULkuxat5rFgQyN9hiZOnIj+/ftrn4kTJxbu0+zZswEAAwcO1NIHDhyo8kx89tln+PnPf+5UjVznPnbsWOy6667YYostVPoBBxyA2267DY888gh++ctf4tlnn8Xee+9dmNh1q6n1b731Fp566im88sor2HzzzQEA1113HdZee238+c9/xsknn4xKpYJBgwZp9SZPnowjjzwSffr0KXbAGFa6KAfOXNOWvLsKUs7g9htwLP24NYzWnieIzxyWl1+UBGXLNcY/SNTJL+NLt7VRtH5RFFm53gW6NIfZfzptX1/0NS1LyzCIAUmWNafcczAxBV4RFq4oDd2WU7ZpDCJzuj24MH/JqfZVVY/854KAyWnyrnhAdIq9Ond1NgHXEO7p9bXA1RJNt33zdLp5WkePSVQkHpE4jm7StE3Dl3VFvn5sXxva9H1tWn9ajvZf9s/2yKbT71lyLeS0+9DHpRmawIZm+YyZ/WgULrjgAowdO1ZLa29vr7k9UxGl4RsoFixYgIMOOggjRozAuHHjgts//fTT8fLLL+OJJ57Q0o888ki1vcUWW2C77bbDBhtsgPvvvx9HHHFEcPvdShmSTK9nz54qrVKpoEePHpkLJPH8889j2rRpuY5aTniUF6koNEstqkspatZrTgzvMazXpA5zWagalDpTN9ZRul4iZGujSP1a0AgiZIMtMrVpGpPQptUTcxnNA3QHaZGXOkm7lu4Igb6KuX6srIpjq28nFc2EpnZYFYzQdtxlbWYzLd9UchyO1fa6Rj8sClPRNvJUIp9CVISEmupQd1KLakV7ezv69eunfWohQ1J8MFWgOXPmZNSihQsXYv/990efPn0wefJkrLLKKkHHOOOMM3Dffffh0UcfxbrrrustO3jwYGywwQaa+0wIuhUZ2nTTTbHBBhvgggsuwLx587B8+XJceumlmD17NmbNmmWtc+ONN2KzzTbDzjvv7G3bZj/9ooPcCiYJcJiCcgmSrZ2cOy647dBj1fNx9Ef1y/LJK+NrT6snp8xbps1TEmReJ5449FrzknoagXKQoKwjdraur41MGU/9WkDPs5mwmbtomiRIeYSIkTXMRF4YIZLmMp/vkDwWXaYDSE1lgJ3wiPbd19DmtGvLy0ORN/wQU5ivnlnfnIpP/Uhk32xxgax5mbr6I802ndvXBkd2nTFa3uZLZPMTMvNU/eRa2GaXdQd01dR6H4YOHYpBgwbh4YcfVmnLly/H1KlTtXF3wYIFGD16NHr06IH77rtPEzV853v66afj3nvvxSOPPIKhQ4fm1vnss8/wwQcfYPDgwYXOo6XJ0G233YY+ffqoz1NPPYV77rkHb775JgYMGIDevXtjypQpOOCAA1CpVDL1ly5dittvvz1IFbLZT6+Z8b6fgOSQmULkJZAY2dquSUGq8RhFrkNRhUgnKY1RgoqsLxZKgmx1fW3Y6jZaCSpCghr9W7H5C9vSiihEIi2bHwrH8mpp/2x1Ch4jBBxunyAXmrUyua3VIkpRiJO0nl+/WmS2QQkaLUPrhV5vkxA10pzZLHTV1PpFixZh2rRpmDZtGgDhND1t2jS8//77YIzh7LPPxiWXXILJkyfjlVdewYknnojevXvj6KOPBiAUITkl/sYbb8SCBQswe/ZszJ49G9VqaoTeZ599tOn7p512Gm699Vbcfvvt6Nu3r6qzdOlS1a9zzz0X//d//4d3330XU6ZMwcEHH4w111wThx9+eKFzbGmfoUMOOQSjRo1S++ussw569eqFadOmYf78+Vi+fDnWWmstjBo1Ctttt12m/t13340lS5bg+OOPzz2WzX664PCDtH2vL4+8oxxPVDoABfsaSQQ+pTtjRhoAL2FzkiVPGe9+oF9QJq+JM8VcCCFBjUJnKEBFYVvWg/oIcc6sZVQeyG3k8B9S7SLx4yC+Q85+QfcbahbMAUb7GddIcJzmrpzBzKVSSb8ZrS3OC/kSUT8Q05fGrCvK6I8w06copB3ahvIBIn2R+bKe6UNkpvtg9rcE8Nxzz2GvvfZS+3KsPOGEE3DzzTfj/PPPx9KlSzFmzBjMmzcPo0aNwkMPPYS+ffsCEO4qTz/9NABg44031tqeMWMGNtxwQwDAO++8g08//VTlXX/99QCAPffcU6tz00034cQTT0SlUsH06dNxyy234PPPP8fgwYOx11574c4771THDkW3jzP01ltvYdNNN8UDDzygTe0DxAVcc801cffdd9fU9px99gDgJy+5K8gHoJELsjYcAaNHCAGylcvbd80SE/uevDpXm3eW68Lp8o0iPy7CbIszJMrLQRCZtJiaH7neDk3PxBgi8YfMdtK3dJaJP6TlQZpBmBFbSI85VE3yZUyhDgBVJvKrZL8KMchWYY81lMYYQpKexBbi4j9HGoMohhjw030OGWNI9N+MPWTMsCIX26rmFHyrdw3+GROhIecViUlkzbcQ2EwfLBKiL5ClNdilI3aQGQfITE8VSmYpk+67Yg3R9mW9a969w3KWjcPIQTs1rK2XZ/9fw9paEdDSypANd911F9Zaay2sv/76mD59Os466ywcdthhGSL09ttv47HHHqspEqUJn6oTpBZJBKhGzrZ87ZqoZRZaAXgVqE4kQWb+iqYGdZb641ukNQ8hi8Ga6lCt7TQbYdbsQBNMQDnbe2ijiZCsYyNEpkpURCECiqtENvHcNuPInLlmU4hsalWoOmRDrWpQZytIzTKhluiGZGjWrFkYO3YsPv74YwwePBjHH388Lrrooky5P/zhD1hnnXUyJKkIeBxOfoLMYPRp67mLCpMj33HqRLC/U0C9IiTIzPeRIKDziVCzSFAzCUEzzahySr3NDGbCV8ZlKjPz6oXb/JRPOGy+JaEmsXr8UuqZVm2b3i7607mESJQpZjZzkRgbyQsjPvpUe4qQ/pZYMdHtzWTNxMd77aG2azaVBeQDqPluq3uh1wSFBkqPw3hIehESJPbDTGJ5dUV5W/8apwbVQoI6QxHxfb8mMSliJqPlazWV5S3VYS7TEWomU9uJGayDmMdMs5lckkOUS81j0jSWms24vkQHD1uOgy7FYToBV8kNlc7wMr6jOoiQCZtK1NkmM1EmC187ruVAlPmqgLks1FRGt21mMrNOs81kmw8clV8oEK9+/HTD2loR0O2Uoa5CiKnMlheSD8BOMAKITtOdpnPaDyVA1rSiRGYFUoM60yRUKxFqJLxqUICaFALXafrSQyiGdVaUo2bR25GSnFpMID6S5PIVsgdBbL5CBAA2kxeFrx09yKK7bhF1SE9rfQWoNJM1DyUZ8oE+oMk04EYRI185AO4na6Pv2AJPcN/AGkSAgJIEdRLqJcrNWCOtHt8g3+lklBRm3+cs2440jXFLPfMYtC6N00P/623bY7oUEeSdy3XkUDmXaYzmm4QISElRowmRvQ0kfSRlChKivBlivujUNlOZq78hM9FKdF+UZCgU8gHO9AdQKDGy5bvK+coCaKhPUB7yBtRaCZCtXKNJkKhj619jiFAoWehsx+BQEtQINaazYU6xB4SJTN8n2yw/PXsMEDNXFlo7HoXIjJcTCtqirf3CcYs8pMhOWDqXEIlytREiMz9EHbLWJ+fpU5S6Gt0hFlJ3RUmGPLA6SzvUIlpeZeeQI1sZX1lf+XpQREEoYhYTGY0nQUFtlCTICxsR6urZXKEw/YUouGVbJxdGOyyr+JigEYxt7Yh9bt0223Eh1PzRDCfq7kiIXHVcsKlDjVB6Otu0VprJmoeSDAXAqf6Yg0cB1chWJq+sq3yzUIsqJDLyyYtI85MgoDFqUGeSoK52hg5BPYpQM0xnLhRdNzjWBs7UlEL/A27yI81lsSpjMW+RNE7qqbScwSqPNOWpQo2AnVR0D0Jkq2uay4qqQ9p5gpIl+3aeaa2ZKJWh5qEkQx6YD36xire9LItgJQFpW2E/YhZ1LuFxIbcP3nO1pQWoOzUoQKJe6PGKEaBmk5/O/p59JChLOunAVqwtH2zXi7aVVVz0gIuqHWMWGSU9Su0h/+Ussti2T/yFTBNZFZQcpeYvm78Q7YMt2GJ6DSih4kFv+z5iFOJ/ZIvlIxEpUpFNMwkRAM2cBNCV5/MJEW3b1oYoJ/uQbYe2UZQQxUk9lzrkMpW1stmsRONQkiEPzDhDdIAwV/DO9Q+yDR4s+xDLGyC7ZCo9UJj8iPRAhWglIUFdSXJrJUJdAZtfkEy3zewChCqUKjVZVUieoqkKUZLj8hNymchkWi0mskapQqGO2LZYPvRYPqWoyEyzPELkOl4e4QhRiHzt288rXx3y1Q+JhdRolGay5qEkQzlwmbpsqpGrnlk3LeS4eSwkydVuwxE4yBchQK7y3Y0EFSVAraDw5Sk4eedkiy9UpL6vH5p/j5EfaiLLzPBi9v9AqgrReq5ZZJIY6cQpXTbDNJHFKGYiKwInwaphYHSRonoJka+tWgmRz2RmIyKu8jZyE6IOZct1/dT70kzWPJRkqAD8M8fcqpFZ19VGWjhngPGQJS9qNW3k+g41lgC52uwOJKg7ECAJ+3dRq/lLP7YZiDEEPhOZK9CiOj6pbzpOp/XIPkOGSLlmkWUIV86UemoiMxFCYGpdyqMIQglKKCEq6kPkOl6thMgsH6o++RQdf16YklSi+6AkQx7QwYIVmlKfvYFCCZKtvWzF5sixoQO5NzqzSzFagUlQVxOgWvx3QoiQ67rVOyVf8xEyTXQFTQ2C2CSDIyFI1DeIxhai/j9aG1YSpM8io0qRy0SWJXTut3mbM3YIGrVogGsZDED362k1QmQ9FwdxsalDIWu1ZUiYxxTYmeBd/bBZgVGSoUCYgwdzBGEEXMEWwwiSrT0fmj3zLJcweI4RSoBcx2llEtTsZ1IzYwDV5u9Uu4nMVj7PRGbGDjIhHafT/bRdqfrQdCAlR2kdnikv04uYyMQ51DeLLKResxBKUlR5uGdTdQYhapQ61AhTmWmuazY64/ewsqIkQx541Z9A1chVX5RzP/BdRMnXx1pRKIJyQfLjqxNKgJxlG0iCOosAdWWgQ9851qMKOa+3YTrzwXZpfSYyVS/HcRqqHtknJjKTHBU1kbn63izUY2bzqRl5JMUWrVqpKHVOu7eVsbfjJ0S1qkMuR+psnt6+jxSW6H4oyVAgQokRkCVHZn1XO3r5rr/Ncn2FGjTDTLRVoGw3IUGtEuE510k6hwiF/hZNfyFfGXMbKGYiC3WcliYym+O0qotsbKFQE5lJikKn1LvQiKCKeflOxacFCVFRmM7U9ahDIIu3+hQhW36zUK6r3jyUZMgDOQgUnSlmGwxCCZKv3Uaj6CCfP6i60htDXoooSb52RL3azX8utAr5kQgjeuFEiZ5fs01kNLZQLY7TMXQCo9phRjmlEumkxjSRmX03TWRFo07L9EZNla7F9Gb1m3H4EXUVIarHXGaeVyPUIbMPIcduJEozWfNQkqEANGIavWvwsJEkV7udhUY4DjeTANXSjqjTWALUauQHKPLdFbuu7uOJ/65ZZKEmMl9sIVcd03Fa+gRRVUi0kZrKtPrIkiCOlKjoRCsbaBHQSZH7/Pz+Qq5LbpZttCqQR4oaQYhsx2wWITLL16sOZfOASKsnyjKSX6L7oiRDHshnj3lvFyVHoozrGP7BwkeWakUzAgb6SUjxeq1KglqFANUX+Trs2jZaFTJNZEUdp2nEaZUmj2H811QlppePwTNtZNUh3URG09V5tchber1qgYsUFSFEWnsFFz2thRC5zqOR6pB/plzXqEOlmax5KMlQAOjvz/bSk0eORBl3+17foRZd7DN/Rlbxuo1cL6xRBKgZ5KerFkQtQljDonCL/65rlBdoEbC/Tbscp7V6BRyn5XZm1lgBE1l2yrzN56g+f6GuhlVBCSREpmmpyJR723Hy+9qa6lCzUUagbh5KMuSBdUAImeVV2Pm5NX7ghWaV5XTZH4uouIrUbOWnkWtttQpqIaxmHZciZCNC1ERmms1iTsiLoQpxsIyvkCvIIjV5UYLjW4esg5YHR5Vsy7Y6EtqjCI0qk5rI0vzkPOAnOa041TpPYaHtKaJj+BFRJYluy5rUZAaItcxs65jRY+QdR/ZdbyNLiHyRqWNwRBw5a5bJOskq98Q8EGntccRgGtHqlDAILTJWrIgoyVBBBKlAjt+r68WnCAkJnXJftF1vOwGHLOKIW6T9WklQMwhQKxMfoH4y6yNCuXU9EaddM8h8vkIu2HyFZLpqM2nSpgKZ+y5ViM4UM2eRibbD7kO7j1DnDmi2CNkULnKU59/TLJWoXjTLmdpUhTghRLJsie6Lkgx5EGb+yt50zmCKnrslVCFu1pT7IuprkAmlCWY0Ua8kQPX8BkKVt8y0d89q81nfn2w6PaxvBlmmX4YqpOqQdul0ep+pTO5nTV5G/7RtnkkzCY5pInMhU68TTB4hxMu2crxEowiRebwis8x8/kN55rK0jcYFYjRJUJyklj5D3RslGSqA8GU27DeFT9Vp1d946MBbD/nJq1+vGawIAWoG+WmJmFE1kk9RN2seCz2GTxWywTSRZfItvkJAlvCIsjopcsUWStvQVSJX/1R5x5T6UH/8iLGW8gFxkaJGEKJGTLsvgmYFYszzH2o2yqn1zUNJhjzIc5wGCipDDYg43WjUMlAXca6ttY3OIkCNID+tQHZcqOV7yPMTomVcU+md0cgdvkI+UF8hleZQg/JMZFRJStvnjm15TlIdyidLjYTph8IYyygDPl+VWs1xNgKR8d/xqjC1ESIfvLPXUH/AQ5s6RP2JONzmPlMpKtE9UZKhQNgGlaI+QF5lqAUH1EY6VIe011kmsFoJUCt+RzbU+l2EmMZs5VxQxMhMt/XH4zitl9NNZCot0ESmt+P2FzLrtOKU+mYiRCXyBT2shRAVUYfyFB9bWdNU5lOHfOYyGZmakiC53WyUZrLmoSRDHrgiUKv8AgSJtudCZ6tDtQ7uofdjs9UfIGxgbtTCpK2KwoESayBCIU7TPlXItvRGXKDf1HFa7Kdv8WY5AJnYQlo7Btmx+QvVS3hWFMLkUolCCJHeTlhgRr8C1Fy/HNu5hpvLOgetZFZd0VCSoQA0wkk6xPzdagNww52qG7QOWDMIUKtde6A4ycltz3GORYhQyPpjWjmj3Sx50ZfeUGU9jtPm+mMyPa1rKWvQk+zx3LO+fM7TjQAjx+isKdpFUCshCiUvPnNZPb5DIcTKF/DRpg5Rc5k+FV9sl+i+KMmQB5wzZwToIgRJtJV/vDr8BQujnoE22Km6E8lP6PHS4zb2YrfqC1veedZChGz5RVUha189jtMi375tLr8B2MkRLSvTbf5CIc7T9YCBWcmXDfX6DTUKNrNZUUIUqg41Ey4Vh/oJudQh3+wySYiajdJM1jyUZCgHoYuuAv6BJ8QE1mq/86KEoZErwDda/amX/LTad5OHoiQICCdCvphCtKypCull8h2nZRsuExk9hukvZB7flW7mmWmNNEu0pOrjOL9QX51GESKf71BXwFSHbOYy03+oM+JQt9rvZ0VCSYZqQBGCpOoEDMad6TNUX6yaIiQkrFyrkJ/uRnokQs/XHUixGBGytZmnCtmCLOZFnNbaAnJjCoGUoWnZbfsX3QqDTaNIU54C5Y2ebUSD1vKaZNZqJsLWNnOrQ2mZ1Fxm+g+tKH5iKytKMuRByGr0qqxnoA5dbLXV/FaK+92El2206aumEAHd7NlVz+/Dd71DnKXNci7zWKgqVBShJjJTKRLb/qnz5rb9+MU6HWoKk7GGqN9QpkwXmspc5CZEyWllcxmF6xxd6pDNXNZZTtSlmax5KEMjeBBzpr8Vx8U+ql6yFlN3+xQ9Z/O6+T6h1ya99sz7McF5/icUecfurE8ofNfbdt3Na2a2I8vTcjKf5plEiK5BphQfWZc4TuetQ+ZafsNlIpN5rvhCtK5vJlkzfUDyVAqTXJj7oepLI0w3nNsja+txl9IAlLS8i4haj1OgbFEUvQ7pb0D/LdB0DiiH6phnF+dtBtSxGvApgsceewwHH3wwhgwZAsYY/vrXv2r5nHOMHz8eQ4YMQa9evbDnnnvi1VdfVflz587FGWecgeHDh6N3795Yf/31ceaZZ2L+/Pne406cOBHbb789+vbti7XXXhuHHXYY3njjjULHDkVJhgKQN6C7UJREdDbq7VvR6+IjO9m+FSMCtRId1/FqISFdidDfpeu6m9esyAKtWjuW+q4ZZKGQpEjVt5jBbCYy2/FtP41mmjfySA1Fvb+0ZvvZ5BEiF+zrszUHlCR2td9RM8Ab+FcEixcvxpZbbolJkyZZ8y+//HJcddVVmDRpEp599lkMGjQI++67LxYuXAgAmDlzJmbOnIkrr7wS06dPx80334wHH3wQJ510kve4U6dOxWmnnYannnoKDz/8MDo6OjB69GgsXrw4+NihYLzU3Zx4c7P9a6oXBZrFugtqWdG92VPba/3Vdhdy40It3wXg/j7yltAIjUAdogqJ9KwqJMtQZagq1SJGFaIkPfEXqpr/kzJylfqORBnqAFd5VfCkLFcr1dM0sao92eeyTAwZo0hGJpbLcYh+62uTyTQgJQOmWqLyyYXNOnf71RLz8V1kYdhaH/2mKmWqLpKEuIiJyqd1mEyzlHO0I8vSN/oiZbV8ZmlL1cnPky396b170Uys2nvDhrW1eMm7NdVjjGHy5Mk47LDDAIjf0ZAhQ3D22WfjRz/6EQBg2bJlGDhwIC677DKccsop1nbuuusuHHvssVi8eDHa2sI8dj755BOsvfbamDp1Knbfffeaj21DqQx5UETJoAgxE9U6qDUajehn0etUVH2p1cTVmSpP6Hde76cofN9HM4mQKqu1nXWKlmV8jtMAMumhw7h97bDWeFmxmW5833CI0mEr4zIR1erobJKoRpMtIP9ci5i9GjXLyyeUd9YvqpFmsmXLlmHBggXaZ9myZYX7NGPGDMyePRujR49Wae3t7dhjjz3w5JNPOuvNnz8f/fr1CyZCsg4ADBgwoK5j21CSoYII8W8JRWcNoI0YXGs971oISSsQn2aTlGYi77uxXVfzPPKIkAtWHyPHDLJQZM1s2e0wc5n7x9QogkQJRuggXI8DcSvO3LKhEdc3lyDVaCKrd0HYzoT0x2rEZ+LEiejfv7/2mThxYuE+zZ49GwAwcOBALX3gwIEqz8Rnn32Gn//854WUG845xo4di1133RVbbLFFzcd2oaXI0L333ov99tsPa665JhhjmDZtmpYf6oT1wgsvYN9998Vqq62GNdZYA9///vexaNGiwv0pOqiGOiW3GhrV70YQnxDy0wji053ITR6C/bAc19c83xAi5FKFtHa1Y1j64yFF1ESmpVv8hfLQ1TqQae4pMlAX8TnylWl0DByfOtSZBCFvANPNbrRefdfDHrG8e+GCCy7A/Pnztc8FF1xQc3uZNeEcs/QWLFiAgw46CCNGjMC4ceOC2z/99NPx8ssv489//nPNx/ahpcjQ4sWLscsuu+DSSy+15oc4Yc2cORNf+9rXsPHGG+Ppp5/Ggw8+iFdffRUnnnhizf1qpHNtV88Qq5eg1XMtuoL4rAhkh6KW7893rX1EyNcHWtc0j7lUIZfjtG0WmfW4tI6FFKlp9pbyLoQSqhAyUcsAq3xPNEWpYBstrCzV65Jq65/VvFhAFbL5Col0/zFaAY10oG5vb0e/fv20T3t7e+E+DRo0CAAySsycOXMyis3ChQux//77o0+fPpg8eTJWWWWVoGOcccYZuO+++/Doo49i3XXXrenYeWipOEPHHXccAODdd9+15m+xxRa455571P5GG22Eiy++GMceeyw6OjrQ1taGv//971hllVVw7bXXIorEz/vaa6/F1ltvjbfffhsbb7xxQ/ucNzh39uKr9aIRfjVd4dzcVQSnVdU+wP892K6XeS4+P6E8+FShohMoXX5EAFDr5W/0JE4zrlCUc4wicYHMsiF1bWVcsY9scYtaDTaCY3uTtzlNu8o2Cp0ZMbsVv6ehQ4di0KBBePjhh7H11lsDAJYvX46pU6fisssuU+UWLFiA/fbbD+3t7bjvvvvQs2fP3LY55zjjjDMwefJkTJkyBUOHDq3p2CFoKTJUC0wnrGXLlqFHjx6KCAFAr169AABPPPFEITJk+90VfZGqZ4CvlUh1xoypeu/JViM+rUxqiiDve3FduxAiZGuniCqktR/gN2ROqafpIWn1wiQ04onCUDWICaDHmKHkQhIQSU5CiYdoNRzdgdC4YJtJ5kKeKmQrlzeDzCxjm9G2smPRokV4++231f6MGTMwbdo0DBgwAOuvvz7OPvtsXHLJJRg2bBiGDRuGSy65BL1798bRRx8NQChCo0ePxpIlS3Drrbcqh20AWGuttVCpVAAA++yzDw4//HCcfvrpAIDTTjsNt99+O/72t7+hb9++SgHq378/evXqBcZY7rFD0a3JkM0Ja++998bYsWNxxRVX4KyzzsLixYtx4YUXAgBmzZpV9zHznjeNVJ27chp4o56rrUJ6VhSyY6LI9xSiBplt+vyEnMfRjknaDTSR0UCL3rZz8rV05s+PDJLjAwNDBC58mhpIQGQ0alf/VhZ1KMTHSpKXPPNYUSLk71eKriJMXfUdPffcc9hrr73U/tixYwEAJ5xwAm6++Wacf/75WLp0KcaMGYN58+Zh1KhReOihh9C3b18AwPPPP4+nn34aADKCxIwZM7DhhhsCAN555x18+umnKu/6668HAOy5555anZtuukm5vuQdOxRdFmfotttu00jMAw88gN122w2AMJMNHToUL774Irbaaitr/QULFmD06NFYffXVcd9992m2x9tvvx1jx47Fp59+ikqlgjPPPBN/+tOfMHbsWJx//vnW9pYtW5aZVvjvrf4D7ZXmulV1l5Xqve02gLQ1gvisqIQHqP27811Xnxpk1qVl81QhW1whIFWDXLGFTDJE4wvFYCqeEAeJJ8TyYwzJfRFDKPtfxg0y4wyp9CSekNz3xRqCzA+INwTSVnptTcdkaGVNmGm2x3mzYg/54g3ZY/jo/2UJUxlykSFfXKE885iLCGXa85CckHK3NjnOUFuPdRrWVsfyjxrW1oqALlOGDjnkEIwaNUrtr7NO+Jec54R19NFH4+ijj8bHH3+MVVddFYwxXHXVVRl7I8XEiRMxYcIELW3MahvjtAGbePtSr09Qi7yM5aJRKlV3Jz3d5fsqQoJEmrt+USJkPaYxsBSbWm+ZVVZjWyYiCCJFwQobqdJ6VtUlx1RG6xVRh6x9qFPhCTbjhS4HUnhGj06EirZd1E+oXiJUYgUCb0HMmDGDA+AvvvhiJm/+/Pl8xx135HvssQdfvHhxUHs33ngj7927N583b56zzBdffMHnz5+vPnPmzOE/+clP+BdffFHjWXQtvvjiCz5u3Lhu23+J8jxaByvCOXC+YpzHinAOnJfnUaJ10FLLccydOxfvv/8+Zs6ciYMOOgh33HEHhg8fjkGDBmHQoEFYuHAh9t13XyxZsgSTJ0/GqquuqupSJ6xJkyZh5513Rp8+ffDwww/jvPPOw6WXXoozzzwzuC8LFixA//79lYN2d0N3779EeR6tgxXhHIAV4zxWhHMAyvMo0TpoKQfq++67D9/5znfU/lFHHQUAGDduHMaPHx/shPXMM89g3LhxWLRoETbddFP89re/VdP2S5QoUaJEiRIlKFqKDJ144one4Ih77rlnkD37lltuaWCvSpQoUaJEiRIrMloqAnWJEiVKlChRokRnoyRDDrS3t2PcuHE1hSdvBXT3/kuU59E6WBHOAVgxzmNFOAegPI8SrYOWcqAuUaJEiRIlSpTobJTKUIkSJUqUKFFipUZJhkqUKFGiRIkSKzVKMlSiRIkSJUqUWKlRkqESJUqUKFGixEqNkgyVKFGiRDdFHNezMluJEiUkSjJUI8pJeF2D8rp3Pj788EO8+OKLXd2NEgZmzJiB3//+96hWq+V9UaJEnSjJUCA+++wzvP3223j22WcB1L86dFfgww8/xP33349bb70Vixcv7uruBGPZsmVYvnw5gOKrYLcSPv/8c7z99tv45JNPUK2aa6W3Jl599VXsvPPOuPXWWwGUSkSr4OWXX8aIESMwYcIEAN3zeeRDdz+Xzz77DJ988klXd6NEAZRkKACvvPIKDjjgABx++OHYa6+91IKv3Wlgnj59OnbddVeMHz8exx9/PL7+9a93iwH59ddfx9FHH429994bu+66K9577z0A3e9h+corr2D06NE4+OCDseWWWypy0cp46aWXsMMOO6CtrQ2333475syZgyjqvo+MGTNm4Fe/+hV++MMf4s477+zq7tSMl156CTvttBO++c1vYtVVV8Vll10GoHs9j2yQLzzLli0DY6zbEu9XX30Vo0aNwhNPPAGg+z2rVlZ03ydbJ+Ff//oXdtttN+yzzz647rrrcN111+GWW27B66+/3tVdC8Z7772Hr3/96zjppJPwwAMP4L333sNTTz2lbtZWxfTp07HLLrtgjTXWwLe+9S3EcYwjjzwSQPd6E37zzTex1157Ydddd8Wf/vQnHHTQQfjJT36CL774oqu75oQccM8++2w888wzWGONNfC73/0OnPNuc90ppk+fjt133x3/+Mc/8NRTT+Hoo4/GFVdc0dXdKoyXXnoJu+yyC8455xz86U9/wrbbbospU6ago6Ojq7tWF15//XV873vfUy8Mb7zxBqIo6naE6KWXXsLOO++MDz/8EJdffjnmz5/f7UnqSgNewolZs2bxrbfemv/oRz9SaR988AHfZ599+NNPP80feeQR/uWXX3ZhD8Nw00038V122YUvXLhQpR1wwAH89ttv59dccw2fNm0aX758eRf2MIt3332XjxgxQrv29957Lz/66KP54sWLu7BnxdDR0cG///3v82OOOUalzZkzh3/961/nb7zxBn///ff5vHnzOOecx3HcRb3U8dJLL/H29nZ+4YUXcs45r1ar/Jvf/CbffvvtVZlW6WsI3n33Xb7xxhvz888/n3d0dHDOOb/xxhv5oEGD+FtvvdXFvQvHO++8wxlj/Cc/+YlKe/zxxzljjN9zzz1d2LP68Morr/ABAwbwU089lf/whz/kBx54IB84cCCfNWtWV3etEKZNm8Z79erFL7jgAv7//t//41/5ylf4E088wTnn6ndXonVRkiEPPv/8c3722Wfz559/XqVNmDCB9+zZk2+xxRZ8jTXW4LvtthufMWNG13UyAL/4xS/4RhttxGfPns055/zKK6/klUqFH3TQQXz99dfnW221Fb/tttu6uJc67rjjDn7CCSfwOXPmqLQf/vCHfPDgwXzkyJF8iy224L///e/5okWLurCXYTjqqKP4SSedxJctW8Y55/yiiy7i7e3tfJNNNuFDhw7lxx57LH/nnXe6uJcpnnnmGX7RRRdxzgUR4pzz119/nffv359fd911Xdm1QojjmHd0dPBLL72U77///vzzzz9XedOnT+frrbcef/3117uwh8Vx4403qu2Ojg6+fPlyfvjhh/NvfOMbfMGCBV3Ys9owe/ZsPmrUKH7eeeeptBkzZvCRI0fyP//5z5zz7kG8n3vuOd7W1qaIahzHfMSIEfyb3/xmF/esRChKMmTB/Pnz1YPliy++UOl/+ctf+BprrMHvuece/v777/NPP/2UDx48mJ9xxhld1dUg/Pvf/+arr74632KLLfjXv/513qNHD/7Pf/5Tva0ceOCBfN9991UDX6tg2rRpavvXv/41Z4zxq6++mj/22GP81FNP5WuuuSZ/5ZVXurCHYfjBD37A11tvPT527Fh+6qmn8vb2dv7nP/+Zf/jhh/yPf/wj32677fgNN9zQ1d10Io5j/vnnn/PDDjuM/8d//Afv6OjoFgOU/H0/+uij/Mc//rGWV61W+dChQ/mjjz7aBT0rhmq1qj2HOOeaIn3dddfx/v37K2LXavexD1OmTOE77rijdq9zzvmuu+7Kx48f30W9Ko4LLriAn3POOZzz9Hd366238qFDh/LHHnusK7tWIhClz5CBf/3rXzjggAOUo+4qq6yi8gYOHIiHH34YRxxxBNZbbz2sscYa2GefffDRRx91VXetMO3sQ4cOxfPPP48f/vCH2H777XHAAQdg7733xpdffgkA+PrXv47Zs2djwYIFXdFdheXLl6Ojo0P1a8sttwQALFy4EHEc49FHH8VZZ52F3XbbDddffz0457j//vu7sstBuO6663DwwQejUqlg+vTp+PGPf4yjjjoK66yzDo4//ni0t7fjkUce6epuOsEYQ//+/XHcccfhrrvuwlNPPdXyfhAvvPAC9tprLyxatAh77rknJk6cCCB1ZmWMgTGmfmsA8D//8z8tNwPoX//6F0488UQceOCB+P73v4877rgDANDW1qb6/oMf/ACbbropxo8fD855t3JyHzlyJMaOHavudXlOAwYM6BYTPCQuvvhiXHXVVQCASqUCANhhhx2wbNkyPPbYYwBKR+pWR/e5azoB0mn0//7v/3DppZcCgPZg2X333bH11lur/Y6ODixdulTdyK2At956C+eeey6OPfZYjBkzRt2AQ4cOxYknnoi2tjZUq1W0tbWhZ8+eAMR5Dx06VO13BV577TWcfPLJ2H333fHjH/9Yi2vTt29f/OAHP8Aee+wBAKhWq/jwww8xfPhwjBw5squ6bMU777yDyy67DCeddBL+9re/YdGiRQCAa6+9FpdffjnWXXddrL322gCgHvbrrLMONtlkk5Z/WH7961/Hvvvui+uvvx5Lly7t6u448dJLL2H33XfH9ttvjz59+gAQA1Ecx2CMYfny5ViyZAmiKEK/fv0AABdeeCH23XdfjRx1NV5//XXsuuuu6NGjBw466CDMmDEDP/3pT3HGGWcAEC9qHR0d4Jzj61//Ol555RXMnDmzi3udj7lz52LOnDkAgNVXXx3f+ta3AIiXOPny2bt3b3XvAMBll12Gxx9/vPM768GSJUswd+5cLF26VL0c0Ht42LBhOP3003HNNdfg9ddfb/kXiJUeXaZJtRik89v555/Pr7vuOj5y5Ej+5ptvcs7dNuuf/vSnfJ111mkZJ8zp06fztdZaix999NH8qKOO4sOHD+c777yzVkY6XP7kJz/h9957Lx87diwfMGAAf/nll7uo16Lfq6++Oj/55JP5WWedxTfffHP+85//nHOeXnvTAfGiiy7iW2yxBf/www87vb8uvPzyy3zw4MF8//3353vuuSePooj/7W9/08occ8wxfJtttuEfffQRf/PNN/mECRP4mmuu2W18VyZOnMj79evXss6tL730El911VU1HxTOOV+6dKnarlarfPHixXyjjTbizz33HP/Zz37GV111Vf7MM890dned+OKLL/gxxxzDzzzzTJW2dOlSvuWWW3LGGD/66KO18vPmzeOMMXXftCreeecd/pWvfIVfdNFF/KOPPnKW+4//+A9+9tlnc87Fvc4Yy5jSuhKvvPIKP/DAA/lmm23GDz30UH7//fdbyz399NN8s80247/73e8456UjdSujJEOc82effZb37t1bzZ557733eL9+/fjPfvYza/lHH32Un3DCCXyttdbiL7zwQmd21YmPPvqIjxw5kp9//vmcc/HAf/rpp/kmm2zCp0yZosotXryYX3fddXz11VfnI0aM4Lvttht/6aWXuqrbfP78+XyvvfbSZo1NmDCBf/e73+VLlizJzNZ7/PHH+Xnnncf79evHX3zxxU7urRtvvfUWX2eddfhPf/pT5d/xjW98g//nf/6nVu7999/nm2++Oe/ZsycfMWIE33TTTVvqPFyQpHTu3Ll82223bclJA7NmzeKDBg3i++23H+dcDDxnnHEG32+//fjQoUP5z372M+1+3Wqrrfj222/Pe/TowZ999tmu6rYT++yzj/KbkWTu/PPP50cccQTfZptt+BVXXME5T/2HLr30Uv7aa691TWcDcf3113PGGN966635xRdfrJHqOI7VvXPooYfyX/ziF/zXv/41b29v1yaxdDVeffVVvvrqq/PTTjuN/+Y3v+G77LILP/bYY7Uy1G/r2GOP5RtuuGFnd7NEQbR1tTLV1ahWq/j5z3+Ok08+GRdffDGq1SrWX399jB07FnfccQeOOuooDBs2TJVfvHixkkWnTJmCESNGdGHvUzzxxBPo06cPTjvtNADCvDdixAh8+eWXmk9T79698YMf/ADf/OY3Ua1W0bt3b2Uq6ApUq1V89tln2nX89NNP8a9//Qtbb701ttlmG+y333444YQTMHfuXPzzn//E1KlT8cQTT+CrX/1ql/WbYvny5fjd736HQw89FBdeeCHa29sBAO3t7XjzzTdx0EEH4Wtf+xp23313bLvttnjhhRfwl7/8BUOGDMHw4cOxzjrrdPEZ5ENK/KutthqmTp2KVVddtYt7ZMdOO+2EDz74AH/729/wm9/8Bh0dHdhhhx3w1a9+FX/5y1/wyiuvYNy4cRgyZAhmzJiBJUuW4Pnnn2+Z3xIgTC1Lly7F8uXL8c4776CjowM9e/bERx99hDvvvBPjxo3DI488gn/84x8499xz0dYmHuM//OEP1XarYuedd8bxxx+PYcOG4dprr0Ucxzj99NOx2mqrgTGm7p3VVlsNF110Efr06YPHH38c22yzTRf3XGDp0qX4yU9+guOPPx5XX301AGDw4MH44x//iDlz5qB3797o06cPoijC8uXL0aNHD5x00kmYNm0aZs2ahcGDB3ftCZRwo6vZWCvANj374Ycf5gMGDOB//etfOec60//yyy812b0V8O677/Lf/OY3al/GDdphhx34H/7wh67qlhdxHPMPPviAb7311vyMM87g//znP/n48eN57969+X/913/xX//61/z73/8+32GHHdSb4dy5c/knn3zSxT3P4rnnnuP/+7//q/YnTJjAe/TowceMGcNPO+00vtFGG/Hjjz+ez58/vwt7ueJj5syZ/Pjjj+c9e/bk++67L//ss89U3uTJk/nAgQPVlO0777yzpWcjPvHEEzyKIr777rvz4447jq+66qr85JNP5pwL03KfPn3466+/3q1mj02bNo0PGzaMx3HMJ0yYwNdbbz1+9dVX88MPP1wp85xzfvbZZ/O2traW+36q1Srfbbfd+IQJE1TaueeeyzfccEO+7rrr8r333jszc3HBggX8448/7uyuliiIkgx5cOSRR/KRI0dqwQq7A+jDcffdd+dXX3212v/d737H33///a7olhO///3v+XbbbccPOuggPmjQIH7nnXeqvBdeeIGvueaaagDrDnj//ff5YYcdxu+//35lXvrLX/7C29ra+KuvvtrFvVvx8dFHH/ELL7xQTZun98OIESP4mDFjuqhnxfHMM8/wY489lp988sn82muvVel/+9vf+GabbabFTuouGD16tDKzXn755XzVVVfl/fv35//85z9VmX//+98t5Q/IufgdzZ8/n++333788MMP55MmTeIXXHAB79WrF7/pppv4Aw88wCdMmMC32WYb5SvYnYjqyo6VcjbZ/PnzvbNG5NT0b3/72/jiiy/UshWtFBredw40jP2XX36ppnqOGzcO3//+97FkyZJO66cPPJl5cdJJJ+HBBx/EH/7wB6yxxhoYNGiQKvOVr3wFX/nKV1pe/gfS81lnnXVw880348ADD1Tfw6BBg7D55pujb9++XdnFlQJDhgzB+eefj5133hmAuB8455g3bx7WWGMNbLvttl3cw3Bsv/32uOWWW/C73/0OY8aMUemPP/44Bg4c2NIzlFxT45cvX66mm7/xxhuoVCro1asXXnrpJTUbbujQoS1jPpbnIWcfTpgwAV988QWefPJJ3HvvvZg0aRJOPPFE7L///jjllFOUmV/WKdE9sNJ9U//617+w0UYb4bLLLnOSG/kDPuCAA9C3b19cd911WnpXI+QcZHpHRwcGDBiAq6++GldccQWee+45DB8+vDO764Sc5gyIuCmff/45AOEztHz5cnDOccUVV+Djjz/GqFGjurCn+ahWq2CMYcGCBVi6dCn69+8PII058ve//x0DBgzoUv+slQn9+/dHjx491D5jDL/61a8wa9Ys7L333l3Ys+KghGf69Ok47bTTcMMNN+Dqq69u2d/Tm2++iauvvhqzZs1SafLlbdSoUYiiCGeeeSYeeOABTJs2DWeeeSbGjx+PO+64o6XiC9nOY9SoUbj77rtxyy23YMCAASp8AyDiIw0fPlx9L7zFw2WUIOhSXaqT8dFHH/Ftt92Wb7755ry9vZ1ffPHFzmnzcgrkH/7wB77xxhvzuXPntkTU3SLnwLlYg2zNNdfkvXv3brkZM/Iaz5gxg2+44Yb8lVde4eeffz5va2vju+22Gx89ejQfPHhwy8zYc8E8j0ceeUTlffTRR/ynP/0pX2211fj06dO7qosrNf785z/zU045ha+++uot/1vy4YsvvuD33nsvP+qoo7p0Bmge3nrrLT5gwADOGOMXXHBBxsfvD3/4A2eM8cGDB2vPpMsuu0yFM2kF+M6jo6ODL1q0iI8aNYpfdNFFfN68eXzhwoX8oosu4oMHD+b//ve/u7DnJWrBSkOGqtUqv/322/k3vvENPn36dH7DDTfwKIpyycSMGTNaxnZdyznss88+nDHWco6IEu+99x5fa621+AknnKDSrr/+en7aaafxCRMmtEwMpzzI8/jud7+rvosXX3yR77///nyTTTbpFtPnV1S89NJL/KCDDmrZe6AIvvjii5Zej2/RokX8u9/9Lj/xxBP5pEmTOGOMn3feeRqReOONN/hPf/pTdU+0ol9NyHlwLpzwGWN8k0024aNGjeIbbLBBtybcKzNWGjLEuVhs8h//+Ifa/+1vf6vIBL0hW0EBciH0HKRa8dxzz7XsW0q1WuWXX345P+OMM1rygRgKeh7mb+fBBx9syZg8KxvkIrklmoslS5bwa6+9lt9xxx2c85QsmERi8eLFarsVn7eh58G5mPX3i1/8gv/mN78p7/VujJWKDFHIwddUV5YvX85vu+22Lo3IHArfOdx6663d4k14yZIl2n4rPhhDsKKcR4kS9cJUru644w7OGOPnnnsunzNnDudcPLta9SVNwncekhAtX768JUN9lCiO1p+i02BwzsEYU87Q3/ve9wAAp556KjjneO+993DXXXfhpZde6spuerEinINEr169tP1Wnh3jw4pyHiVK1AsZkLNarSKKIhx55JHgnOPoo48GYwxnn302rrzySrz33nv405/+hN69e3dxj+0IPY93331XnUd533dfrFRkqFqtolKpYOHChQCgpjl/73vfQxzH+MEPfoD+/fvjv//7v7H++ut3ZVedWBHOoUSJEis+KpWKWiD3qKOOAmMMxx13HO677z688847ePbZZ1uWCFGEnEerRmQvEY7WmCveCZAk4t1338XIkSPx3HPPqbzly5fjpZdeQv/+/fHkk0+2bBySFeEcSpQosfKAMQbGGDjnOPLII7Hbbrvhk08+wQsvvICtttqqq7sXjBXlPEq4sdIoQ5VKBe+//z522GEHHHzwwdhzzz1V3qOPPop77rkHDz/8MDbbbLOu62QOVoRzKFGixMoFxhiq1SrOO+88PProo5g2bVpLrQUXihXlPErYwThfOaJCxXGMX/7yl/jggw9wzTXXaLbdmTNnolKpYODAgV3Yw3ysCOdQokSJlQ/VahU333wztt12226tpKwo51Eii5WGDAFixWHT0bW7YUU4hxIlSqx8kBM/ujtWlPMooWOlIkMlSpQoUaJEiRImVhoH6hIlSpQoUaJECRtKMlSiRIkSJUqUWKlRkqESJUqUKFGixEqNkgyVKFGiRIkSJVZqlGSoRIkSJUqUKLFSoyRDJUqUKFGiRImVGiUZKlGiRIkSJUqs1CjJUIkSJUqUKFFipUZJhkqUKFGiRIkSKzVKMlSiRDfHiSeeiMMOO8xbZsqUKWCM4fPPP296fz777DOsvfbaePfdd5t+rM7C3//+d2y99daI47iru1KiRIkmoFyOo0SJbo758+eDc47VVlsNALDnnntiq622wtVXX63KLF++HHPnzsXAgQObvq7Sueeei3nz5uHGG29s6nGmTJmCvfbaC/PmzVPn3kxss802GDt2LI499timH6tEiRKdi1IZKlGim6N///65ZKBHjx4YNGhQ04nQ0qVLceONN+Lkk09u6nEaCc45Ojo6cst95zvfwX/91391Qo9KlCjR2SjJUIkSgfjkk08waNAgXHLJJSrt6aefRo8ePfDQQw9Z67z77rtgjOGOO+7AzjvvjJ49e2LzzTfHlClTtHJTp07FDjvsgPb2dgwePBg//vGPtQH67rvvxle/+lX06tULa6yxBr72ta9h8eLFAHQz2YknnoipU6fimmuuAWMMjDG8++67VjPZPffcg8033xzt7e3YcMMN8ctf/lLr04YbbohLLrkE3/3ud9G3b1+sv/76uOGGG7zX6IEHHkBbWxt22mknlSaP/c9//hNbb701evXqhb333htz5szBAw88gM022wz9+vXDt7/9bSxZskTV45zj8ssvx1e+8hX06tULW265Je6++251Xffaay8AwOqrrw7GGE488cTcemZ/tttuO7S3t+Pxxx/HSy+9hL322gt9+/ZFv379sO222+K5555T9Q455BA888wz+Pe//+29BiVKlOiG4CVKlAjG/fffz1dZZRX+7LPP8oULF/KNN96Yn3XWWc7yM2bM4AD4uuuuy++++27+r3/9i5988sm8b9++/NNPP+Wcc/7hhx/y3r178zFjxvDXXnuNT548ma+55pp83LhxnHPOZ86cydva2vhVV13FZ8yYwV9++WV+7bXX8oULF3LOOT/hhBP4oYceyjnn/PPPP+c77bQT/973vsdnzZrFZ82axTs6Ovijjz7KAfB58+Zxzjl/7rnneBRF/Gc/+xl/4403+E033cR79erFb7rpJtX3DTbYgA8YMIBfe+21/K233uITJ07kURTx1157zXm+Z511Ft9///21NHnsHXfckT/xxBP8hRde4BtvvDHfY489+OjRo/kLL7zAH3vsMb7GGmvwSy+9VNW78MIL+aabbsoffPBB/s477/CbbrqJt7e38ylTpvCOjg5+zz33cAD8jTfe4LNmzeKff/55bj3an5EjR/KHHnqIv/322/zTTz/lm2++OT/22GP5a6+9xt98803+l7/8hU+bNk07l7XXXpvffPPNzvMvUaJE90RJhkqUKIgxY8bwTTbZhB9zzDF8iy224EuXLnWWlWSIDvJffvklX3fddflll13GOReD9/Dhw3kcx6rMtddey/v06cOr1Sp//vnnOQD+7rvvWo9ByRDnnO+xxx4ZgmaSoaOPPprvu+++WpnzzjuPjxgxQu1vsMEG/Nhjj1X7cRzztddem19//fXO8z300EP5d7/7Xeux//u//1ulTZw4kQPg77zzjko75ZRT+H777cc553zRokW8Z8+e/Mknn9TaOumkk/i3/387dxfS1BvHAfx7dDtrtSFGq1GYLWq5Qa2BkrHuehl41xv2ciFoFIRdaEaEF7OXi6DAyhpBF0JQRAR1oQmGVBQnR4U3sSFialhQQqMItLL9uvj/PXhqm87+/Wvu+4GxnWfP73k5N/vxPM/Z7t1J55Rp3J07dwx17Hb7lImO3++XpqamtHWIKPtwm4woQ2fPnsX4+Dhu3ryJa9euYc6cOVPGTN42MplMKC0tRSwWAwDEYjGsX7/ecJ4nEAjg06dPGB4ehs/nw8aNG7F69Wrs3LkTV65cQTwe/6U5xGIxBAIBQ1kgEEBfXx++ffuml61Zs0b/rCgKnE4n3r17l7Ld0dHRlPdjcluLFi3C3LlzsXz5ckPZRNvRaBRjY2PYvHkzbDab/rp69Sr6+/tT9p9JXGlpqeG6vr4e+/btw6ZNm3D69Omk/VitVsNWHhHNDqY/PQCibPPy5Uu8efMGiUQCQ0NDhh/5TEwkPyLy08Fm+fchT0VRkJ+fj3v37kHTNHR2dqKlpQWNjY2IRCJwuVwz6jtdn5OZzeafxpzu8fIFCxakTNQmt6UoStq2J97b29uxZMkSQz2LxZKy/0zi5s2bZ7huamrCnj170N7ejo6ODoRCIdy4cQNbt27V67x//x4OhyNl/0SUnbgyRJSBL1++YO/evaisrMSpU6dQU1ODt2/fThnX3d2tfx4fH8fz589RUlICAPB6vdA0zZCMaJoGu92u/6ArioJAIIDjx4+jp6cHqqri9u3bSftSVdWwupOM1+vF48ePDWWapsHtdiM/P3/K+aTi9/sRjUZnHD/B6/XCYrHg1atXWLFiheFVVFQE4J95AjDMdTpx6bjdbtTV1aGzsxPbtm1Da2ur/t3Y2Bj6+/vh9/t/eX5E9HfhyhBRBhobG/HhwwdcuHABNpsNHR0dqKmpQVtbW9q4S5cuYeXKlfB4PGhubkY8Hkd1dTUA4ODBgzh37hwOHTqE2tpa9Pb2IhQKob6+Hnl5eYhEIujq6sKWLVuwcOFCRCIRjIyMwOPxJO1r2bJliEQiGBwchM1mw/z583+qc/jwYZSVleHkyZOorKzEkydPcPHiRYTD4V+6P8FgEMeOHUM8HkdhYeGM27Hb7WhoaEBdXR0SiQQ2bNiAjx8/QtM02Gw2VFVVobi4GIqioK2tDRUVFbBardOKS2Z0dBRHjhzBjh074HK5MDw8jKdPn2L79u16ne7ublgsFsOWJxHNEn/0xBJRFrl//76YTCZ59OiRXjY0NCQFBQUSDoeTxkwcoL5+/bqsW7dOVFUVj8cjXV1dhnoPHjyQsrIyUVVVnE6nHD16VL5+/SoiItFoVILBoDgcDrFYLOJ2u6WlpUWP/fEAdW9vr5SXl4vVahUAMjAwkPSw8a1bt8Tr9YrZbJalS5fKmTNnDGMqLi6W5uZmQ5nP59OfckulvLxcLl++bLhvP/bd2toqBQUFhrhQKCQ+n0+/TiQScv78eVm1apWYzWZxOBwSDAbl4cOHep0TJ06I0+kURVGkqqpqWnHJxvP582fZtWuXFBUViaqqsnjxYqmtrTUcjt+/f78cOHAg7dyJKDvxH6iJfqPBwUG4XC709PRg7dq1f3o4/4u7d++ioaEBL168QF7e7NiJHxkZQUlJCZ49ezbjc1pE9PfiNhkR/acqKirQ19eH169fT+ucTjYYGBhAOBxmIkQ0S3FliOg3ysWVISKibMNkiIiIiHLa7NjQJyIiIpohJkNERESU05gMERERUU5jMkREREQ5jckQERER5TQmQ0RERJTTmAwRERFRTmMyRERERDntO9ufOxORHUEeAAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ls_sampler = PredictiveSampler(measurements=ls_X)\n", "\n", "demonstrate_with_data(\n", " ls_sampler,\n", " sensor_field_to_plot='temperature_c',\n", " sampling_field='odo_pct_sat_pred',\n", " n_samples=20,\n", " sample_noise_ratio=0.1,\n", " n_to_recommend=6,\n", " fitness_function=PredictiveSampler.inverse_variance_fitness,\n", " override_variance=True\n", ")" ] }, { "cell_type": "code", "execution_count": 15, "id": "b3185620", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "preliminary - predicting fields from measurements...\n", "predicting field 'temperature_c'\n", "selected 40 inducing points with threshold 0.5\n", "selected 75 inducing points with threshold 0.6\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "selected 135 inducing points with threshold 0.6499999999999999\n", "selected 226 inducing points with threshold 0.6749999999999999\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "maximum number of inducing points (300) exceeded with threshold 0.688\n", "selected 226 inducing points with threshold 0.675\n", "selected 295 inducing points with threshold 0.68125\n", "1/200: loss = 1.956337\n", "20/200: loss = 1.094596\n", "40/200: loss = 1.006329\n", "60/200: loss = 0.993527\n", "80/200: loss = 0.990869\n", "100/200: loss = 0.990231\n", "120/200: loss = 0.990052\n", "140/200: loss = 0.989981\n", "160/200: loss = 0.989944\n", "180/200: loss = 0.989922\n", "200/200: loss = 0.989902\n", "Parameter variational_strategy.inducing_points: torch.Size([295, 2])\n", "Parameter variational_strategy._variational_distribution.variational_mean: torch.Size([295])\n", "Parameter variational_strategy._variational_distribution.chol_variational_covar: torch.Size([295, 295])\n", "Parameter mean_module.raw_constant: 0.2679172456264496\n", "Parameter covar_module.raw_outputscale: -0.2806068956851959\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.21588541567325592\n", "predicting field 'pH'\n", "selected 40 inducing points with threshold 0.5\n", "selected 75 inducing points with threshold 0.6\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "selected 135 inducing points with threshold 0.6499999999999999\n", "selected 226 inducing points with threshold 0.6749999999999999\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "maximum number of inducing points (300) exceeded with threshold 0.688\n", "selected 226 inducing points with threshold 0.675\n", "selected 295 inducing points with threshold 0.68125\n", "1/200: loss = 1.956766\n", "20/200: loss = 1.355541\n", "40/200: loss = 1.261156\n", "60/200: loss = 1.233349\n", "80/200: loss = 1.225221\n", "100/200: loss = 1.223057\n", "120/200: loss = 1.222348\n", "140/200: loss = 1.221956\n", "160/200: loss = 1.221687\n", "180/200: loss = 1.221597\n", "200/200: loss = 1.221283\n", "Parameter variational_strategy.inducing_points: torch.Size([295, 2])\n", "Parameter variational_strategy._variational_distribution.variational_mean: torch.Size([295])\n", "Parameter variational_strategy._variational_distribution.chol_variational_covar: torch.Size([295, 295])\n", "Parameter mean_module.raw_constant: -0.25222209095954895\n", "Parameter covar_module.raw_outputscale: -0.3826950490474701\n", "Parameter covar_module.base_kernel.raw_lengthscale: -0.7978715300559998\n", "predicting field 'odo_pct_sat'\n", "selected 40 inducing points with threshold 0.5\n", "selected 75 inducing points with threshold 0.6\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "selected 135 inducing points with threshold 0.6499999999999999\n", "selected 226 inducing points with threshold 0.6749999999999999\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "maximum number of inducing points (300) exceeded with threshold 0.688\n", "selected 226 inducing points with threshold 0.675\n", "selected 295 inducing points with threshold 0.68125\n", "1/200: loss = 1.957057\n", "20/200: loss = 1.101941\n", "40/200: loss = 1.025225\n", "60/200: loss = 1.013232\n", "80/200: loss = 1.010158\n", "100/200: loss = 1.008690\n", "120/200: loss = 1.007876\n", "140/200: loss = 1.007655\n", "160/200: loss = 1.007033\n", "180/200: loss = 1.006746\n", "200/200: loss = 1.006557\n", "Parameter variational_strategy.inducing_points: torch.Size([295, 2])\n", "Parameter variational_strategy._variational_distribution.variational_mean: torch.Size([295])\n", "Parameter variational_strategy._variational_distribution.chol_variational_covar: torch.Size([295, 295])\n", "Parameter mean_module.raw_constant: -0.12145940959453583\n", "Parameter covar_module.raw_outputscale: 0.10351917147636414\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.27005791664123535\n", "predicting field 'cond_uS_cm'\n", "selected 40 inducing points with threshold 0.5\n", "selected 75 inducing points with threshold 0.6\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "selected 135 inducing points with threshold 0.6499999999999999\n", "selected 226 inducing points with threshold 0.6749999999999999\n", "maximum number of inducing points (300) exceeded with threshold 0.700\n", "maximum number of inducing points (300) exceeded with threshold 0.688\n", "selected 226 inducing points with threshold 0.675\n", "selected 295 inducing points with threshold 0.68125\n", "1/200: loss = 1.956378\n", "20/200: loss = 1.097374\n", "40/200: loss = 1.028986\n", "60/200: loss = 1.018004\n", "80/200: loss = 1.015970\n", "100/200: loss = 1.015426\n", "120/200: loss = 1.015258\n", "140/200: loss = 1.015204\n", "160/200: loss = 1.015162\n", "180/200: loss = 1.015139\n", "200/200: loss = 1.015125\n", "Parameter variational_strategy.inducing_points: torch.Size([295, 2])\n", "Parameter variational_strategy._variational_distribution.variational_mean: torch.Size([295])\n", "Parameter variational_strategy._variational_distribution.chol_variational_covar: torch.Size([295, 295])\n", "Parameter mean_module.raw_constant: 0.23184220492839813\n", "Parameter covar_module.raw_outputscale: -0.33473604917526245\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.5307247042655945\n", "total number of tests will be 32\n", "testing field temperature_c_pred...\n", "simulating samples with n_samples=30 and sample_noise_ratio=0.3...\n", "predicting temperature_c_pred with 0 feature fields...\n", "running prediction 1 of 32\n", "1/200: loss = 1.269991\n", "20/200: loss = 1.171290\n", "40/200: loss = 1.115393\n", "60/200: loss = 1.092407\n", "80/200: loss = 1.087881\n", "100/200: loss = 1.087180\n", "120/200: loss = 1.086912\n", "140/200: loss = 1.086817\n", "160/200: loss = 1.086795\n", "180/200: loss = 1.086790\n", "200/200: loss = 1.086789\n", "Parameter likelihood.noise_covar.raw_noise: -1.5791255235671997\n", "Parameter mean_module.raw_constant: 0.11766010522842407\n", "Parameter covar_module.raw_outputscale: 0.31813329458236694\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.8166905045509338\n", "predicting temperature_c_pred with 1 feature fields...\n", "running prediction 2 of 32\n", "1/200: loss = 1.369170\n", "20/200: loss = 1.284686\n", "40/200: loss = 1.232579\n", "60/200: loss = 1.202564\n", "80/200: loss = 1.192222\n", "100/200: loss = 1.187960\n", "120/200: loss = 1.185483\n", "140/200: loss = 1.183966\n", "160/200: loss = 1.182982\n", "180/200: loss = 1.182322\n", "200/200: loss = 1.181870\n", "Parameter likelihood.noise_covar.raw_noise: -1.2108945846557617\n", "Parameter mean_module.raw_constant: 0.6371620297431946\n", "Parameter covar_module.raw_outputscale: 0.9929293394088745\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.3675694465637207\n", "running prediction 3 of 32\n", "1/200: loss = 1.343924\n", "20/200: loss = 1.246118\n", "40/200: loss = 1.176699\n", "60/200: loss = 1.133842\n", "80/200: loss = 1.118103\n", "100/200: loss = 1.114228\n", "120/200: loss = 1.113468\n", "140/200: loss = 1.113338\n", "160/200: loss = 1.113314\n", "180/200: loss = 1.113304\n", "200/200: loss = 1.113297\n", "Parameter likelihood.noise_covar.raw_noise: -1.8792232275009155\n", "Parameter mean_module.raw_constant: -0.2143741250038147\n", "Parameter covar_module.raw_outputscale: 0.9541317224502563\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.6202948093414307\n", "running prediction 4 of 32\n", "1/200: loss = 1.294291\n", "20/200: loss = 1.180651\n", "40/200: loss = 1.102575\n", "60/200: loss = 1.059808\n", "80/200: loss = 1.046996\n", "100/200: loss = 1.045022\n", "120/200: loss = 1.044835\n", "140/200: loss = 1.044762\n", "160/200: loss = 1.044687\n", "180/200: loss = 1.044617\n", "200/200: loss = 1.044551\n", "Parameter likelihood.noise_covar.raw_noise: -1.8068208694458008\n", "Parameter mean_module.raw_constant: 0.15590879321098328\n", "Parameter covar_module.raw_outputscale: 0.37123045325279236\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.3572710752487183\n", "predicting temperature_c_pred with 2 feature fields...\n", "running prediction 5 of 32\n", "1/200: loss = 1.389044\n", "20/200: loss = 1.314587\n", "40/200: loss = 1.258741\n", "60/200: loss = 1.212873\n", "80/200: loss = 1.191164\n", "100/200: loss = 1.183383\n", "120/200: loss = 1.179462\n", "140/200: loss = 1.176845\n", "160/200: loss = 1.175025\n", "180/200: loss = 1.173719\n", "200/200: loss = 1.172755\n", "Parameter likelihood.noise_covar.raw_noise: -1.5064857006072998\n", "Parameter mean_module.raw_constant: 0.425905704498291\n", "Parameter covar_module.raw_outputscale: 1.301388144493103\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.7629544734954834\n", "running prediction 6 of 32\n", "1/200: loss = 1.374164\n", "20/200: loss = 1.280521\n", "40/200: loss = 1.201961\n", "60/200: loss = 1.141048\n", "80/200: loss = 1.111281\n", "100/200: loss = 1.100410\n", "120/200: loss = 1.095915\n", "140/200: loss = 1.093110\n", "160/200: loss = 1.090874\n", "180/200: loss = 1.088990\n", "200/200: loss = 1.087387\n", "Parameter likelihood.noise_covar.raw_noise: -1.7223479747772217\n", "Parameter mean_module.raw_constant: 0.4508228600025177\n", "Parameter covar_module.raw_outputscale: 1.0526843070983887\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.766576051712036\n", "running prediction 7 of 32\n", "1/200: loss = 1.351642\n", "20/200: loss = 1.236145\n", "40/200: loss = 1.130153\n", "60/200: loss = 1.039300\n", "80/200: loss = 0.980357\n", "100/200: loss = 0.949429\n", "120/200: loss = 0.934823\n", "140/200: loss = 0.927746\n", "160/200: loss = 0.923790\n", "180/200: loss = 0.921109\n", "200/200: loss = 0.918976\n", "Parameter likelihood.noise_covar.raw_noise: -2.5231728553771973\n", "Parameter mean_module.raw_constant: -0.3804873526096344\n", "Parameter covar_module.raw_outputscale: 1.3874468803405762\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.988666296005249\n", "predicting temperature_c_pred with 3 feature fields...\n", "running prediction 8 of 32\n", "1/200: loss = 1.393119\n", "20/200: loss = 1.308982\n", "40/200: loss = 1.223505\n", "60/200: loss = 1.134128\n", "80/200: loss = 1.070643\n", "100/200: loss = 1.036185\n", "120/200: loss = 1.019331\n", "140/200: loss = 1.010251\n", "160/200: loss = 1.004206\n", "180/200: loss = 0.999512\n", "200/200: loss = 0.995638\n", "Parameter likelihood.noise_covar.raw_noise: -2.4331283569335938\n", "Parameter mean_module.raw_constant: 0.18586406111717224\n", "Parameter covar_module.raw_outputscale: 1.4782899618148804\n", "Parameter covar_module.base_kernel.raw_lengthscale: 3.4965081214904785\n", "testing field pH_pred...\n", "simulating samples with n_samples=30 and sample_noise_ratio=0.3...\n", "predicting pH_pred with 0 feature fields...\n", "running prediction 9 of 32\n", "1/200: loss = 1.424344\n", "20/200: loss = 1.404018\n", "40/200: loss = 1.397196\n", "60/200: loss = 1.396310\n", "80/200: loss = 1.395450\n", "100/200: loss = 1.394863\n", "120/200: loss = 1.394562\n", "140/200: loss = 1.394429\n", "160/200: loss = 1.394377\n", "180/200: loss = 1.394358\n", "200/200: loss = 1.394351\n", "Parameter likelihood.noise_covar.raw_noise: 0.15671570599079132\n", "Parameter mean_module.raw_constant: 0.05206689611077309\n", "Parameter covar_module.raw_outputscale: -1.5061663389205933\n", "Parameter covar_module.base_kernel.raw_lengthscale: -0.3542955219745636\n", "predicting pH_pred with 1 feature fields...\n", "running prediction 10 of 32\n", "1/200: loss = 1.433363\n", "20/200: loss = 1.414222\n", "40/200: loss = 1.409659\n", "60/200: loss = 1.407511\n", "80/200: loss = 1.406377\n", "100/200: loss = 1.405686\n", "120/200: loss = 1.405213\n", "140/200: loss = 1.404860\n", "160/200: loss = 1.404580\n", "180/200: loss = 1.404348\n", "200/200: loss = 1.404150\n", "Parameter likelihood.noise_covar.raw_noise: 0.2823842167854309\n", "Parameter mean_module.raw_constant: 0.054136842489242554\n", "Parameter covar_module.raw_outputscale: -1.9081966876983643\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.1960500031709671\n", "running prediction 11 of 32\n", "1/200: loss = 1.404655\n", "20/200: loss = 1.378757\n", "40/200: loss = 1.376560\n", "60/200: loss = 1.375593\n", "80/200: loss = 1.375076\n", "100/200: loss = 1.374918\n", "120/200: loss = 1.374895\n", "140/200: loss = 1.374895\n", "160/200: loss = 1.374895\n", "180/200: loss = 1.374895\n", "200/200: loss = 1.374895\n", "Parameter likelihood.noise_covar.raw_noise: -0.05147819221019745\n", "Parameter mean_module.raw_constant: 0.13832150399684906\n", "Parameter covar_module.raw_outputscale: -0.8822081089019775\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.867419421672821\n", "running prediction 12 of 32\n", "1/200: loss = 1.423149\n", "20/200: loss = 1.397449\n", "40/200: loss = 1.396945\n", "60/200: loss = 1.396653\n", "80/200: loss = 1.396642\n", "100/200: loss = 1.396639\n", "120/200: loss = 1.396634\n", "140/200: loss = 1.396631\n", "160/200: loss = 1.396627\n", "180/200: loss = 1.396623\n", "200/200: loss = 1.396620\n", "Parameter likelihood.noise_covar.raw_noise: -0.35814106464385986\n", "Parameter mean_module.raw_constant: 0.031030980870127678\n", "Parameter covar_module.raw_outputscale: -0.5702344179153442\n", "Parameter covar_module.base_kernel.raw_lengthscale: -0.6386606097221375\n", "predicting pH_pred with 2 feature fields...\n", "running prediction 13 of 32\n", "1/200: loss = 1.411949\n", "20/200: loss = 1.371205\n", "40/200: loss = 1.366256\n", "60/200: loss = 1.362596\n", "80/200: loss = 1.360489\n", "100/200: loss = 1.359129\n", "120/200: loss = 1.358177\n", "140/200: loss = 1.357483\n", "160/200: loss = 1.356956\n", "180/200: loss = 1.356542\n", "200/200: loss = 1.356207\n", "Parameter likelihood.noise_covar.raw_noise: -1.6787514686584473\n", "Parameter mean_module.raw_constant: 0.2361985296010971\n", "Parameter covar_module.raw_outputscale: 0.4896622896194458\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.5179041624069214\n", "running prediction 14 of 32\n", "1/200: loss = 1.428290\n", "20/200: loss = 1.405639\n", "40/200: loss = 1.402996\n", "60/200: loss = 1.401794\n", "80/200: loss = 1.401085\n", "100/200: loss = 1.400726\n", "120/200: loss = 1.400542\n", "140/200: loss = 1.400444\n", "160/200: loss = 1.400391\n", "180/200: loss = 1.400361\n", "200/200: loss = 1.400344\n", "Parameter likelihood.noise_covar.raw_noise: 0.10250987857580185\n", "Parameter mean_module.raw_constant: 0.07827507704496384\n", "Parameter covar_module.raw_outputscale: -1.2923513650894165\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.45456966757774353\n", "running prediction 15 of 32\n", "1/200: loss = 1.413445\n", "20/200: loss = 1.383484\n", "40/200: loss = 1.383402\n", "60/200: loss = 1.383274\n", "80/200: loss = 1.383179\n", "100/200: loss = 1.383116\n", "120/200: loss = 1.383066\n", "140/200: loss = 1.383030\n", "160/200: loss = 1.383006\n", "180/200: loss = 1.382990\n", "200/200: loss = 1.382982\n", "Parameter likelihood.noise_covar.raw_noise: -0.2146373838186264\n", "Parameter mean_module.raw_constant: 0.09560543298721313\n", "Parameter covar_module.raw_outputscale: -0.6791800856590271\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.6149923801422119\n", "predicting pH_pred with 3 feature fields...\n", "running prediction 16 of 32\n", "1/200: loss = 1.417379\n", "20/200: loss = 1.378300\n", "40/200: loss = 1.375122\n", "60/200: loss = 1.372988\n", "80/200: loss = 1.371912\n", "100/200: loss = 1.371118\n", "120/200: loss = 1.370485\n", "140/200: loss = 1.369975\n", "160/200: loss = 1.369557\n", "180/200: loss = 1.369205\n", "200/200: loss = 1.368904\n", "Parameter likelihood.noise_covar.raw_noise: -1.4233840703964233\n", "Parameter mean_module.raw_constant: 0.19364985823631287\n", "Parameter covar_module.raw_outputscale: 0.30671456456184387\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.5689029693603516\n", "testing field odo_pct_sat_pred...\n", "simulating samples with n_samples=30 and sample_noise_ratio=0.3...\n", "predicting odo_pct_sat_pred with 0 feature fields...\n", "running prediction 17 of 32\n", "1/200: loss = 1.247584\n", "20/200: loss = 1.154340\n", "40/200: loss = 1.102584\n", "60/200: loss = 1.072703\n", "80/200: loss = 1.059819\n", "100/200: loss = 1.055932\n", "120/200: loss = 1.055268\n", "140/200: loss = 1.055222\n", "160/200: loss = 1.055223\n", "180/200: loss = 1.055223\n", "200/200: loss = 1.055222\n", "Parameter likelihood.noise_covar.raw_noise: -1.847456693649292\n", "Parameter mean_module.raw_constant: 0.1293434351682663\n", "Parameter covar_module.raw_outputscale: 0.24810002744197845\n", "Parameter covar_module.base_kernel.raw_lengthscale: 0.5338035821914673\n", "predicting odo_pct_sat_pred with 1 feature fields...\n", "running prediction 18 of 32\n", "1/200: loss = 1.322157\n", "20/200: loss = 1.231746\n", "40/200: loss = 1.174924\n", "60/200: loss = 1.134179\n", "80/200: loss = 1.109552\n", "100/200: loss = 1.095553\n", "120/200: loss = 1.087841\n", "140/200: loss = 1.083650\n", "160/200: loss = 1.081354\n", "180/200: loss = 1.080065\n", "200/200: loss = 1.079319\n", "Parameter likelihood.noise_covar.raw_noise: -2.7566354274749756\n", "Parameter mean_module.raw_constant: 0.02679206244647503\n", "Parameter covar_module.raw_outputscale: 1.1903833150863647\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.3628007173538208\n", "running prediction 19 of 32\n", "1/200: loss = 1.294796\n", "20/200: loss = 1.180168\n", "40/200: loss = 1.103353\n", "60/200: loss = 1.056431\n", "80/200: loss = 1.035658\n", "100/200: loss = 1.027599\n", "120/200: loss = 1.023818\n", "140/200: loss = 1.021486\n", "160/200: loss = 1.019873\n", "180/200: loss = 1.018768\n", "200/200: loss = 1.018037\n", "Parameter likelihood.noise_covar.raw_noise: -2.4389967918395996\n", "Parameter mean_module.raw_constant: 0.08142650127410889\n", "Parameter covar_module.raw_outputscale: 0.4809510409832001\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.1749374866485596\n", "running prediction 20 of 32\n", "1/200: loss = 1.315183\n", "20/200: loss = 1.230235\n", "40/200: loss = 1.184015\n", "60/200: loss = 1.159354\n", "80/200: loss = 1.151775\n", "100/200: loss = 1.150643\n", "120/200: loss = 1.150605\n", "140/200: loss = 1.150603\n", "160/200: loss = 1.150601\n", "180/200: loss = 1.150601\n", "200/200: loss = 1.150600\n", "Parameter likelihood.noise_covar.raw_noise: -1.6175528764724731\n", "Parameter mean_module.raw_constant: 0.15801414847373962\n", "Parameter covar_module.raw_outputscale: 0.516364574432373\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.1353113651275635\n", "predicting odo_pct_sat_pred with 2 feature fields...\n", "running prediction 21 of 32\n", "1/200: loss = 1.354593\n", "20/200: loss = 1.253651\n", "40/200: loss = 1.177037\n", "60/200: loss = 1.119814\n", "80/200: loss = 1.090088\n", "100/200: loss = 1.078449\n", "120/200: loss = 1.074355\n", "140/200: loss = 1.072791\n", "160/200: loss = 1.072003\n", "180/200: loss = 1.071460\n", "200/200: loss = 1.071012\n", "Parameter likelihood.noise_covar.raw_noise: -2.487957239151001\n", "Parameter mean_module.raw_constant: -0.14626750349998474\n", "Parameter covar_module.raw_outputscale: 0.8715108633041382\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.8848199844360352\n", "running prediction 22 of 32\n", "1/200: loss = 1.339665\n", "20/200: loss = 1.248542\n", "40/200: loss = 1.183186\n", "60/200: loss = 1.128346\n", "80/200: loss = 1.091999\n", "100/200: loss = 1.072183\n", "120/200: loss = 1.062781\n", "140/200: loss = 1.058508\n", "160/200: loss = 1.056419\n", "180/200: loss = 1.055229\n", "200/200: loss = 1.054444\n", "Parameter likelihood.noise_covar.raw_noise: -2.4168059825897217\n", "Parameter mean_module.raw_constant: 0.06930019706487656\n", "Parameter covar_module.raw_outputscale: 1.7584794759750366\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.5564846992492676\n", "running prediction 23 of 32\n", "1/200: loss = 1.347624\n", "20/200: loss = 1.249121\n", "40/200: loss = 1.178682\n", "60/200: loss = 1.129561\n", "80/200: loss = 1.105148\n", "100/200: loss = 1.095494\n", "120/200: loss = 1.092007\n", "140/200: loss = 1.090744\n", "160/200: loss = 1.090251\n", "180/200: loss = 1.090031\n", "200/200: loss = 1.089917\n", "Parameter likelihood.noise_covar.raw_noise: -2.3282854557037354\n", "Parameter mean_module.raw_constant: 0.05825655907392502\n", "Parameter covar_module.raw_outputscale: 0.9114797711372375\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.8481965065002441\n", "predicting odo_pct_sat_pred with 3 feature fields...\n", "running prediction 24 of 32\n", "1/200: loss = 1.371829\n", "20/200: loss = 1.278099\n", "40/200: loss = 1.201373\n", "60/200: loss = 1.134533\n", "80/200: loss = 1.091443\n", "100/200: loss = 1.069552\n", "120/200: loss = 1.059861\n", "140/200: loss = 1.055660\n", "160/200: loss = 1.053644\n", "180/200: loss = 1.052471\n", "200/200: loss = 1.051641\n", "Parameter likelihood.noise_covar.raw_noise: -2.4177775382995605\n", "Parameter mean_module.raw_constant: -0.11226801574230194\n", "Parameter covar_module.raw_outputscale: 1.243133306503296\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.8109116554260254\n", "testing field cond_uS_cm_pred...\n", "simulating samples with n_samples=30 and sample_noise_ratio=0.3...\n", "predicting cond_uS_cm_pred with 0 feature fields...\n", "running prediction 25 of 32\n", "1/200: loss = 1.305825\n", "20/200: loss = 1.222868\n", "40/200: loss = 1.190988\n", "60/200: loss = 1.181069\n", "80/200: loss = 1.177421\n", "100/200: loss = 1.175701\n", "120/200: loss = 1.174852\n", "140/200: loss = 1.174396\n", "160/200: loss = 1.174145\n", "180/200: loss = 1.174005\n", "200/200: loss = 1.173927\n", "Parameter likelihood.noise_covar.raw_noise: -0.909345805644989\n", "Parameter mean_module.raw_constant: 0.3446035385131836\n", "Parameter covar_module.raw_outputscale: 0.6359384655952454\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.861341118812561\n", "predicting cond_uS_cm_pred with 1 feature fields...\n", "running prediction 26 of 32\n", "1/200: loss = 1.322586\n", "20/200: loss = 1.209725\n", "40/200: loss = 1.115456\n", "60/200: loss = 1.044110\n", "80/200: loss = 1.006698\n", "100/200: loss = 0.990439\n", "120/200: loss = 0.981518\n", "140/200: loss = 0.975291\n", "160/200: loss = 0.970691\n", "180/200: loss = 0.967183\n", "200/200: loss = 0.964432\n", "Parameter likelihood.noise_covar.raw_noise: -1.8006294965744019\n", "Parameter mean_module.raw_constant: 0.02039281837642193\n", "Parameter covar_module.raw_outputscale: 1.3131364583969116\n", "Parameter covar_module.base_kernel.raw_lengthscale: 3.051570415496826\n", "running prediction 27 of 32\n", "1/200: loss = 1.358050\n", "20/200: loss = 1.272072\n", "40/200: loss = 1.231673\n", "60/200: loss = 1.216346\n", "80/200: loss = 1.212663\n", "100/200: loss = 1.211198\n", "120/200: loss = 1.210538\n", "140/200: loss = 1.210224\n", "160/200: loss = 1.210068\n", "180/200: loss = 1.209990\n", "200/200: loss = 1.209952\n", "Parameter likelihood.noise_covar.raw_noise: -1.0144461393356323\n", "Parameter mean_module.raw_constant: 0.4100324511528015\n", "Parameter covar_module.raw_outputscale: 0.3876211941242218\n", "Parameter covar_module.base_kernel.raw_lengthscale: 1.8054382801055908\n", "running prediction 28 of 32\n", "1/200: loss = 1.366712\n", "20/200: loss = 1.286346\n", "40/200: loss = 1.237784\n", "60/200: loss = 1.212805\n", "80/200: loss = 1.204981\n", "100/200: loss = 1.201753\n", "120/200: loss = 1.199715\n", "140/200: loss = 1.198388\n", "160/200: loss = 1.197500\n", "180/200: loss = 1.196892\n", "200/200: loss = 1.196471\n", "Parameter likelihood.noise_covar.raw_noise: -1.1274884939193726\n", "Parameter mean_module.raw_constant: 0.11740819364786148\n", "Parameter covar_module.raw_outputscale: 0.9896557927131653\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.257213830947876\n", "predicting cond_uS_cm_pred with 2 feature fields...\n", "running prediction 29 of 32\n", "1/200: loss = 1.360573\n", "20/200: loss = 1.251663\n", "40/200: loss = 1.152542\n", "60/200: loss = 1.069070\n", "80/200: loss = 1.017911\n", "100/200: loss = 0.993410\n", "120/200: loss = 0.983124\n", "140/200: loss = 0.978786\n", "160/200: loss = 0.976702\n", "180/200: loss = 0.975478\n", "200/200: loss = 0.974609\n", "Parameter likelihood.noise_covar.raw_noise: -2.4629592895507812\n", "Parameter mean_module.raw_constant: 0.3435651361942291\n", "Parameter covar_module.raw_outputscale: 1.171710729598999\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.7451698780059814\n", "running prediction 30 of 32\n", "1/200: loss = 1.374260\n", "20/200: loss = 1.262484\n", "40/200: loss = 1.140541\n", "60/200: loss = 1.018493\n", "80/200: loss = 0.923994\n", "100/200: loss = 0.864074\n", "120/200: loss = 0.831450\n", "140/200: loss = 0.814285\n", "160/200: loss = 0.804065\n", "180/200: loss = 0.796777\n", "200/200: loss = 0.790966\n", "Parameter likelihood.noise_covar.raw_noise: -2.9020397663116455\n", "Parameter mean_module.raw_constant: -0.04715043678879738\n", "Parameter covar_module.raw_outputscale: 1.3930919170379639\n", "Parameter covar_module.base_kernel.raw_lengthscale: 3.576714515686035\n", "running prediction 31 of 32\n", "1/200: loss = 1.388363\n", "20/200: loss = 1.312699\n", "40/200: loss = 1.267665\n", "60/200: loss = 1.242643\n", "80/200: loss = 1.235088\n", "100/200: loss = 1.233047\n", "120/200: loss = 1.232054\n", "140/200: loss = 1.231453\n", "160/200: loss = 1.231094\n", "180/200: loss = 1.230876\n", "200/200: loss = 1.230743\n", "Parameter likelihood.noise_covar.raw_noise: -1.1958726644515991\n", "Parameter mean_module.raw_constant: 0.26017069816589355\n", "Parameter covar_module.raw_outputscale: 0.6430209279060364\n", "Parameter covar_module.base_kernel.raw_lengthscale: 2.0818777084350586\n", "predicting cond_uS_cm_pred with 3 feature fields...\n", "running prediction 32 of 32\n", "1/200: loss = 1.391732\n", "20/200: loss = 1.295548\n", "40/200: loss = 1.191355\n", "60/200: loss = 1.083852\n", "80/200: loss = 1.001934\n", "100/200: loss = 0.951303\n", "120/200: loss = 0.923967\n", "140/200: loss = 0.909429\n", "160/200: loss = 0.900743\n", "180/200: loss = 0.894615\n", "200/200: loss = 0.889746\n", "Parameter likelihood.noise_covar.raw_noise: -2.8574702739715576\n", "Parameter mean_module.raw_constant: 0.15501537919044495\n", "Parameter covar_module.raw_outputscale: 1.2575688362121582\n", "Parameter covar_module.base_kernel.raw_lengthscale: 3.5990302562713623\n", "\n", "RangeIndex: 32 entries, 0 to 31\n", "Data columns (total 10 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 result_name 32 non-null object \n", " 1 target_field 32 non-null object \n", " 2 rmse 32 non-null float32\n", " 3 mae 32 non-null float32\n", " 4 relative_rmse 32 non-null float32\n", " 5 relative_mae 32 non-null float32\n", " 6 n_feature_fields 32 non-null int64 \n", " 7 feature_field_ids 32 non-null object \n", " 8 n_samples 32 non-null int64 \n", " 9 sample_noise_ratio 32 non-null float64\n", "dtypes: float32(4), float64(1), int64(2), object(3)\n", "memory usage: 2.1+ KB\n" ] } ], "source": [ "# cross-validation results are slightly different than the figures\n", "# differences are not significant and do not affect the analysis\n", "# possibly caused by random seed mismatches, unsure exactly why\n", "ls_results_df = measurements_cross_validate(ls_X)\n", "ls_results_df.info()" ] }, { "cell_type": "code", "execution_count": 16, "id": "df24f32c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/homebrew/Caskroom/miniforge/base/envs/boost/lib/python3.8/site-packages/seaborn/regression.py:582: UserWarning: sharey is deprecated from the `lmplot` function signature. Please update your code to pass it using `facet_kws`.\n", " warnings.warn(msg, UserWarning)\n" ] }, { "data": { "text/plain": [ "Text(0.5, 1.2, 'Lake Sunapee: relative error vs. number of feature fields')" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = sns.lmplot(\n", " ls_results_df,\n", " x='n_feature_fields',\n", " y='relative_mae',\n", " hue='target_field',\n", " col='n_samples',\n", " row='sample_noise_ratio',\n", " x_jitter=0.2,\n", " sharey=False,\n", " ci=None,\n", " facet_kws={'legend_out': False}\n", ")\n", "\n", "sns.move_legend(ax, 'upper left', bbox_to_anchor=(0.18, 1.1), ncol=2)\n", "ax._legend.set_title('Predicted field')\n", "labels = ['Temperature', 'pH', 'Dissolved oxygen', 'Conductivity']\n", "for text, label in zip(ax._legend.texts, labels):\n", " text.set_text(label)\n", "\n", "plt.xlabel('Number of feature fields')\n", "plt.ylabel('Relative mean absolute error')\n", "plt.title('Lake Sunapee: relative error vs. number of feature fields', y=1.2)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "1440b5d7", "metadata": {}, "source": [ "### Lac Hertel dataset" ] }, { "cell_type": "code", "execution_count": 17, "id": "78b95643", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 4514 entries, 0 to 4513\n", "Data columns (total 16 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 %time 4514 non-null float64\n", " 1 field.header.seq 4514 non-null int64 \n", " 2 field.header.stamp 4514 non-null float64\n", " 3 field.stamp_sonde 4514 non-null float64\n", " 4 field.temp_c 4514 non-null float64\n", " 5 field.spcond_u 4514 non-null float64\n", " 6 field.sal 4514 non-null float64\n", " 7 field.ph 4514 non-null float64\n", " 8 field.orp 4514 non-null float64\n", " 9 field.depth_m 4514 non-null float64\n", " 10 field.turbidity_ntu 4514 non-null float64\n", " 11 field.turbidity_fnu 4514 non-null float64\n", " 12 field.odo_percsat 4514 non-null float64\n", " 13 field.odo_m 4514 non-null float64\n", " 14 field.latitude 4514 non-null float64\n", " 15 field.longitude 4514 non-null float64\n", "dtypes: float64(15), int64(1)\n", "memory usage: 564.4 KB\n" ] } ], "source": [ "lh_df = pd.read_csv('water_quality_dataset/water_quality_measurments.csv')\n", "lh_df.info()" ] }, { "cell_type": "code", "execution_count": 18, "id": "a23e113c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 4514 entries, 0 to 4513\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 latitude 4514 non-null float32\n", " 1 longitude 4514 non-null float32\n", " 2 temp_c 4514 non-null float32\n", " 3 ph 4514 non-null float32\n", " 4 odo_percsat 4514 non-null float32\n", " 5 spcond_u 4514 non-null float32\n", " 6 orp 4514 non-null float32\n", " 7 turbidity_ntu 4514 non-null float32\n", "dtypes: float32(8)\n", "memory usage: 141.2 KB\n" ] } ], "source": [ "lh_X = lh_df[[\n", " 'field.latitude',\n", " 'field.longitude',\n", " 'field.temp_c',\n", " 'field.ph',\n", " 'field.odo_percsat',\n", " 'field.spcond_u',\n", " 'field.orp',\n", " 'field.turbidity_ntu'\n", "]].astype(np.float32).rename(columns={\n", " 'field.latitude': 'latitude',\n", " 'field.longitude': 'longitude',\n", " 'field.temp_c': 'temp_c',\n", " 'field.ph': 'ph',\n", " 'field.odo_percsat': 'odo_percsat',\n", " 'field.spcond_u': 'spcond_u',\n", " 'field.orp': 'orp',\n", " 'field.turbidity_ntu': 'turbidity_ntu'\n", "})\n", "\n", "lh_X.info()" ] }, { "cell_type": "code", "execution_count": 19, "id": "7d2e3da2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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latitudelongitudetemp_cphodo_percsatspcond_uorpturbidity_ntux_posy_pos
85545.543907-73.15303024.72400110.24109.77999975.199997132.4199980.80-80.754349-61.620358
89645.543636-73.15292424.71100010.23109.33999675.129997133.4100040.75-72.614365-91.469398
297145.545189-73.15145124.87200010.19109.90000275.160004145.3200070.7438.59251483.707756
158045.545071-73.15250424.76499910.23110.13999975.150002137.7700040.76-43.22651368.896271
296545.545151-73.15145124.87700110.19109.87000375.059998145.3500060.7338.68767979.527542
\n", "
" ], "text/plain": [ " latitude longitude temp_c ph odo_percsat spcond_u \\\n", "855 45.543907 -73.153030 24.724001 10.24 109.779999 75.199997 \n", "896 45.543636 -73.152924 24.711000 10.23 109.339996 75.129997 \n", "2971 45.545189 -73.151451 24.872000 10.19 109.900002 75.160004 \n", "1580 45.545071 -73.152504 24.764999 10.23 110.139999 75.150002 \n", "2965 45.545151 -73.151451 24.877001 10.19 109.870003 75.059998 \n", "\n", " orp turbidity_ntu x_pos y_pos \n", "855 132.419998 0.80 -80.754349 -61.620358 \n", "896 133.410004 0.75 -72.614365 -91.469398 \n", "2971 145.320007 0.74 38.592514 83.707756 \n", "1580 137.770004 0.76 -43.226513 68.896271 \n", "2965 145.350006 0.73 38.687679 79.527542 " ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lh_converter = CoordinateConverter()\n", "lh_X = lh_converter.latlon_to_xy(lh_X)\n", "lh_X.sample(5)" ] }, { "cell_type": "code", "execution_count": 20, "id": "7e19eafc", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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