From fdcc25e2cc89675113301577f69539ae05d3652b Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 11:30:52 -0500 Subject: [PATCH 01/16] docs: convert readme to index in cli/basic-usage --- docs/cli/basic-usage/Readme.ipynb | 643 ------------------ .../basic-usage/Readme_files/Readme_19_1.png | Bin 0 -> 40985 bytes .../basic-usage/Readme_files/Readme_22_1.png | Bin 0 -> 41505 bytes .../basic-usage/Readme_files/Readme_24_1.png | Bin 0 -> 43082 bytes docs/cli/basic-usage/index.md | 414 +++++++++++ 5 files changed, 414 insertions(+), 643 deletions(-) delete mode 100644 docs/cli/basic-usage/Readme.ipynb create mode 100644 docs/cli/basic-usage/Readme_files/Readme_19_1.png create mode 100644 docs/cli/basic-usage/Readme_files/Readme_22_1.png create mode 100644 docs/cli/basic-usage/Readme_files/Readme_24_1.png create mode 100644 docs/cli/basic-usage/index.md diff --git a/docs/cli/basic-usage/Readme.ipynb b/docs/cli/basic-usage/Readme.ipynb deleted file mode 100644 index de71cfe0..00000000 --- a/docs/cli/basic-usage/Readme.ipynb +++ /dev/null @@ -1,643 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Basic usage\n", - "\n", - "The command line interface `python -m autora.workflow` allows us to load and save `States` and run arbitrary \n", - "functions on them." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "import numpy as np\r\n", - "import pandas as pd\r\n", - "from sklearn.linear_model import LinearRegression\r\n", - "\r\n", - "from autora.experimentalist.grid import grid_pool\r\n", - "from autora.state import StandardState, estimator_on_state, on_state\r\n", - "from autora.variable import Variable, VariableCollection\r\n", - "from sklearn.model_selection import GridSearchCV\r\n", - "from sklearn.pipeline import make_pipeline\r\n", - "from sklearn.preprocessing import PolynomialFeatures\r\n", - "\r\n", - "rng = np.random.default_rng()\r\n", - "\r\n", - "\r\n", - "def initial_state(_):\r\n", - " state = StandardState(\r\n", - " variables=VariableCollection(\r\n", - " independent_variables=[\r\n", - " Variable(name=\"x\", allowed_values=np.linspace(-10, +10, 1001))\r\n", - " ],\r\n", - " dependent_variables=[Variable(name=\"y\")],\r\n", - " covariates=[],\r\n", - " ),\r\n", - " conditions=None,\r\n", - " experiment_data=pd.DataFrame({\"x\": [], \"y\": []}),\r\n", - " models=[],\r\n", - " )\r\n", - " return state\r\n", - "\r\n", - "\r\n", - "@on_state(output=[\"conditions\"])\r\n", - "def experimentalist(variables):\r\n", - " conditions: pd.DataFrame = grid_pool(variables)\r\n", - " selected_conditions = conditions.sample(10, random_state=rng)\r\n", - " return selected_conditions\r\n", - "\r\n", - "\r\n", - "coefs = [2.0, 3.0, 1.0]\r\n", - "noise_std = 10.0\r\n", - "\r\n", - "\r\n", - "def ground_truth(x, coefs_=coefs):\r\n", - " return coefs_[0] * x**2.0 + coefs_[1] * x + coefs_[2]\r\n", - "\r\n", - "\r\n", - "@on_state(output=[\"experiment_data\"])\r\n", - "def experiment_runner(conditions, coefs_=coefs, noise_std_=noise_std, rng=rng):\r\n", - " experiment_data = conditions.assign(\r\n", - " y=(\r\n", - " ground_truth(conditions[\"x\"], coefs_=coefs_)\r\n", - " + rng.normal(0.0, noise_std_, size=conditions[\"x\"].shape)\r\n", - " )\r\n", - " )\r\n", - " return experiment_data\r\n", - "\r\n", - "\r\n", - "theorist = estimator_on_state(\r\n", - " GridSearchCV(\r\n", - " make_pipeline(PolynomialFeatures(), LinearRegression()),\r\n", - " param_grid={\"polynomialfeatures__degree\": [0, 1, 2, 3, 4]},\r\n", - " scoring=\"r2\",\r\n", - " )\r\n", - ")\r\n" - ] - } - ], - "source": [ - "%cat lib.py" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can run the pipeline of initialization, condition generation, experiment and theory building as follows.\n", - "\n", - "First we create an initial state file: " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!python -m autora.workflow lib.initial_state --out-path initial.pkl" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next we run the condition generation:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!python -m autora.workflow lib.experimentalist --in-path initial.pkl --out-path conditions.pkl" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We run the experiment:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!python -m autora.workflow lib.experiment_runner --in-path conditions.pkl --out-path experiment_data.pkl" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And then the theorist:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!python -m autora.workflow lib.theorist --in-path experiment_data.pkl --out-path model.pkl" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can interrogate the results by loading them into the current session." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "StandardState(variables=VariableCollection(independent_variables=[Variable(name='x', value_range=None, allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), units='', type=, variable_label='', rescale=1, is_covariate=False)], dependent_variables=[Variable(name='y', value_range=None, allowed_values=None, units='', type=, variable_label='', rescale=1, is_covariate=False)], covariates=[]), conditions= x\n", - "342 -3.16\n", - "869 7.38\n", - "732 4.64\n", - "387 -2.26\n", - "919 8.38\n", - "949 8.98\n", - "539 0.78\n", - "563 1.26\n", - "855 7.10\n", - "772 5.44, experiment_data= x y\n", - "0 -3.16 1.257587\n", - "1 7.38 153.259915\n", - "2 4.64 54.291348\n", - "3 -2.26 10.374509\n", - "4 8.38 155.483778\n", - "5 8.98 183.774472\n", - "6 0.78 3.154024\n", - "7 1.26 14.033608\n", - "8 7.10 103.032008\n", - "9 5.44 94.629911, models=[GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures',\n", - " PolynomialFeatures()),\n", - " ('linearregression',\n", - " LinearRegression())]),\n", - " param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]},\n", - " scoring='r2')])" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from autora.workflow.__main__ import load_state\n", - "s = load_state(\"model.pkl\")\n", - "s" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have three new fields in the state. The first is the conditions, a sample of ten values from between -10 and 10." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
x
342-3.16
8697.38
7324.64
387-2.26
9198.38
9498.98
5390.78
5631.26
8557.10
7725.44
\n", - "
" - ], - "text/plain": [ - " x\n", - "342 -3.16\n", - "869 7.38\n", - "732 4.64\n", - "387 -2.26\n", - "919 8.38\n", - "949 8.98\n", - "539 0.78\n", - "563 1.26\n", - "855 7.10\n", - "772 5.44" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s.conditions" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have experiment data corresponding to those conditions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
xy
0-3.161.257587
17.38153.259915
24.6454.291348
3-2.2610.374509
48.38155.483778
58.98183.774472
60.783.154024
71.2614.033608
87.10103.032008
95.4494.629911
\n", - "
" - ], - "text/plain": [ - " x y\n", - "0 -3.16 1.257587\n", - "1 7.38 153.259915\n", - "2 4.64 54.291348\n", - "3 -2.26 10.374509\n", - "4 8.38 155.483778\n", - "5 8.98 183.774472\n", - "6 0.78 3.154024\n", - "7 1.26 14.033608\n", - "8 7.10 103.032008\n", - "9 5.44 94.629911" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s.experiment_data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have a best-fit linear model." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures',\n",
-       "                                        PolynomialFeatures()),\n",
-       "                                       ('linearregression',\n",
-       "                                        LinearRegression())]),\n",
-       "             param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]},\n",
-       "             scoring='r2')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" - ], - "text/plain": [ - "GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures',\n", - " PolynomialFeatures()),\n", - " ('linearregression',\n", - " LinearRegression())]),\n", - " param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]},\n", - " scoring='r2')" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s.model" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "... which we can plot:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "from matplotlib import pyplot as plt\n", - "\n", - "from lib import ground_truth, noise_std\n", - "\n", - "def plot_results(state):\n", - " x = np.linspace(-10, 10, 100).reshape((-1, 1))\n", - " plt.plot(x, ground_truth(x), label=\"ground_truth\", c=\"orange\")\n", - " plt.fill_between(x.flatten(), ground_truth(x).flatten() + noise_std, ground_truth(x).flatten() - noise_std,\n", - " alpha=0.3, color=\"orange\")\n", - " \n", - " xi, yi = state.experiment_data[\"x\"], state.experiment_data[\"y\"]\n", - " plt.scatter(xi, yi, label=f\"observations\")\n", - " \n", - " plt.plot(x, state.model.predict(x), label=\"model\")\n", - " \n", - " plt.legend()\n", - "\n", - "plot_results(s)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If we run the experiment for another 3 cycles, we can get results closer to the ground truth. In this example, we overwrite the results file each time the CLI is called." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!cp \"model.pkl\" \"result.pkl\"\n", - "for i in range(3):\n", - " !python -m autora.workflow lib.experimentalist --in-path \"result.pkl\" --out-path \"result.pkl\"\n", - " !python -m autora.workflow lib.experiment_runner --in-path \"result.pkl\" --out-path \"result.pkl\"\n", - " !python -m autora.workflow lib.theorist --in-path \"result.pkl\" --out-path \"result.pkl\"\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAGdCAYAAAA44ojeAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAChjklEQVR4nOzdd3zU9f3A8df3LreyLntBgBC2DEEFI6goqHFQZ1XEWdSKaEVc1VoRR6mrzoq/2rrqqrYq4ogDBBWBMGRvCDN7XeYll7vv749PcuTIJSSQnffz8UhL7jvuczHjfZ/P+/N+a7qu6wghhBBCdCKGjh6AEEIIIcSRJEARQgghRKcjAYoQQgghOh0JUIQQQgjR6UiAIoQQQohORwIUIYQQQnQ6EqAIIYQQotORAEUIIYQQnU5ARw/gWHg8HjIzMwkJCUHTtI4ejhBCCCGaQdd1SktLSUhIwGBoeo6kSwYomZmZJCYmdvQwhBBCCHEMDhw4QO/evZs8p0UByrx58/jkk0/Ytm0bNpuN0047jaeeeorBgwd7z5k4cSJLly71ue73v/89r732mvfz/fv3M2PGDH744QeCg4O54YYbmDdvHgEBzRtOSEgIoF5gaGhoS16CEEIIITpISUkJiYmJ3r/jTWlRgLJ06VJmzpzJKaecQk1NDQ899BDnnnsuW7ZsISgoyHveLbfcwmOPPeb9PDAw0Ptvt9vNhRdeSFxcHL/88gtZWVlcf/31mEwm/vKXvzRrHHXLOqGhoRKgCCGEEF1Mc9IztONpFpiXl0dMTAxLly7ljDPOANQMyoknnsgLL7zg95qvv/6aiy66iMzMTGJjYwF47bXXeOCBB8jLy8NsNh/1eUtKSrDb7TgcDglQhBBCiC6iJX+/j2sXj8PhACAiIsLn8ffee4+oqCiGDx/Ogw8+SEVFhffY8uXLGTFihDc4ATjvvPMoKSlh8+bNfp+nqqqKkpISnw8hhBBCdF/HnCTr8XiYNWsW48ePZ/jw4d7Hr7nmGvr27UtCQgIbNmzggQceYPv27XzyyScAZGdn+wQngPfz7Oxsv881b9485s6de6xDFUIIIUQXc8wBysyZM9m0aRM///yzz+O33nqr998jRowgPj6eSZMmsXv3bpKTk4/puR588EFmz57t/bwuyaYpuq5TU1OD2+0+pucUPYPRaCQgIEC2qwshRCdzTAHKHXfcwRdffMGPP/541G1C48aNA2DXrl0kJycTFxdHenq6zzk5OTkAxMXF+b2HxWLBYrE0e3zV1dVkZWX5LC0J0ZjAwEDi4+Oblf8khBCifbQoQNF1nTvvvJNPP/2UJUuWkJSUdNRr1q1bB0B8fDwAKSkpPPnkk+Tm5hITEwPAd999R2hoKMOGDWvh8BvyeDxkZGRgNBpJSEjAbDbLu2Phl67rVFdXk5eXR0ZGBgMHDjxq4SAhhBDto0UBysyZM3n//fdZsGABISEh3pwRu92OzWZj9+7dvP/++1xwwQVERkayYcMG7r77bs444wxGjhwJwLnnnsuwYcO47rrrePrpp8nOzubhhx9m5syZLZolaUx1dTUej4fExESf7c1C+GOz2TCZTOzbt4/q6mqsVmtHD0kIIQQt3MUzf/58HA4HEydOJD4+3vvxn//8BwCz2cz333/Pueeey5AhQ7jnnnu4/PLLWbhwofceRqORL774AqPRSEpKCtdeey3XX3+9T92UVnlh8k5YNJN8rwghROfT4iWepiQmJjaoIutP3759+eqrr1ry1EIIIYToQeStoxBCCCE6HQlQxDF76623CAsL6+hh+NA0jc8++6yjhyGEEOI4SYAi2sWjjz7KiSee2GnvJ4QQonORAKULq66u7ughtDqXy9XRQxBCCNEJ9IwARdehprz9P1rYh7G0tJRp06YRFBREfHw8zz//PBMnTmTWrFkA9OvXj8cff5zrr7+e0NBQb9Xe//3vf5xwwglYLBb69evHc88953Nff8seYWFhvPXWWwDs3bsXTdP45JNPOOusswgMDGTUqFEsX77c55q33nqLPn36EBgYyKWXXkpBQUGzXtdbb73F3LlzWb9+PZqmoWma97k1TWP+/Pn85je/ISgoiCeffNLv0tFnn33mrWfT1P0A8vPzufTSSwkMDGTgwIF8/vnnzRqnEEKIWhWZUH6gQ4dwzKXuuxR3BXwU3P7Pe2UZBAQ1+/TZs2ezbNkyPv/8c2JjY3nkkUdYu3atz1LGs88+yyOPPMKcOXMAWLNmDVdeeSWPPvooV111Fb/88gu33347kZGR3HjjjS0a7p/+9CeeffZZBg4cyJ/+9CemTp3Krl27CAgIYOXKlUyfPp158+ZxySWXkJaW5h3D0Vx11VVs2rSJtLQ0vv/+e0DVzqnz6KOP8te//pUXXniBgIAAFi9efFz3mzt3Lk8//TTPPPMML7/8MtOmTWPfvn0NmloKIYTwQ/dA4Sowh0NQ021l2lLPCFC6gNLSUt5++23ef/99Jk2aBMCbb75JQkKCz3lnn30299xzj/fzadOmMWnSJP785z8DMGjQILZs2cIzzzzT4gDl3nvv5cILLwTUH/kTTjiBXbt2MWTIEF588UVSU1O5//77vc/zyy+/kJaWdtT72mw2goODCQgI8NvO4JprruGmm25q9jiPdr8bb7yRqVOnAvCXv/yFl156ifT0dFJTU5v9HEII0WM5c9TsiTm8Q4fRMwIUY6CazeiI522mPXv24HK5GDt2rPcxu93O4MGDfc47+eSTfT7funUrF198sc9j48eP54UXXsDtdmM0Gps9hrpqv3C4NUFubi5Dhgxh69atXHrppT7np6SkNCtAOZojX9Pxqv86goKCCA0NJTc3t1WfQwghuq3S3VCV39Gj6CEBiqa1aKmlMwsKavnr0DStQZE9f8moJpPJ5xpQvY3a2pGvyWAwNGu8jan/OkC9lvZ4HUII0eXVlEPpDqBlOZRtoWckyXYB/fv3x2QysWrVKu9jDoeDHTt2NHnd0KFDWbZsmc9jy5YtY9CgQd7Zk+joaLKysrzHd+7c2eJOz0OHDmXlypU+j61YsaLZ15vNZtxud7POjY6OprS0lPLycu9jdU0nj+V+QgghmqlsL1QXgsl+1FPbWs+YQekCQkJCuOGGG7jvvvuIiIggJiaGOXPmYDAYmuzGfM8993DKKafw+OOPc9VVV7F8+XJeeeUVXn31Ve85Z599Nq+88gopKSm43W4eeOCBBrMMR/OHP/yB8ePH8+yzz3LxxRfzzTfftGh5p1+/fmRkZLBu3Tp69+5NSEhIo80hx40bR2BgIA899BB/+MMfWLlypc8unZbeTwghRDN43FCyFQw28HR8yQeZQelE/va3v5GSksJFF13E5MmTGT9+PEOHDm2yw+6YMWP46KOP+PDDDxk+fDiPPPIIjz32mE+C7HPPPUdiYiKnn34611xzDffee2+LOz2feuqpvP7667z44ouMGjWKb7/9locffrjZ119++eWkpqZy1llnER0dzQcffNDouREREbz77rt89dVXjBgxgg8++IBHH330mO8nhBCiGZxZUHEIrDEdPRIANP1oHQA7oZKSEux2Ow6Hg9DQUJ9jTqeTjIwMkpKSmvzD3hWUl5fTq1cvnnvuOaZPn97Rw+m2utP3jBBCHLOcJVC4BkIGqUTZyDEQc0arPkVTf7+PJEs8ncivv/7Ktm3bGDt2LA6Hg8ceewygwS4dIYQQolW5SqB0J1iiO3okXrLE08k8++yzjBo1ismTJ1NeXs5PP/1EVFRURw/rqE444QSCg4P9frz33nsdPTwhhBBNKdsL1cVgCmNLPty6OJ5l+2s6dEgyg9KJjB49mjVr1nT0MI7JV1991ehW4NjY2HYejRBCiGbz1IBjMwQEg6bx7kaNbw8EY7K5GN+6ZapaRAIU0Sr69u3b0UMQQghxLCoOQmU2BPWhtBo+264DGtf23Q6c12HDkiUeIYQQoicr2Q4aYDDz6TaoqDEwwLKfU1nYocOSAEUIIYToqZz5UL4HLDHoOry7UW3svTbyK7TEjt2gIQGKEEII0VOV7QFXGZhCSc+EHUVGbJqTy+I2g31Ehw5NAhQhhBCiJ3I7VeVYUxgA725SD18SvoTQuDGqj10HkgBFCCGE6InK94EzDyxR5FVA2m718LVR30NEB27fqSUBShexZMkSNE2juLi4o4fSam688UYuueSSjh6GEEL0PLoHHFvBYAZDAB9tAZfHwOjAbZzQrw8YO76qtmwzFm1u7969JCUl8euvv3LiiSd6H3/xxRfpgp0WhBCi66vMhooDYI3F7YH3apNjr4v8EhJ+A53gV7MEKI1we3TSMwrJLXUSE2JlbFIERkPHrse1t+rqasxmc5vd327v+HbeQgjRI5XtAk81BASyOAMyy42EGx1c0DsHgpNVL54OJks8fqRtymLCU4uZ+voK7vpwHVNfX8GEpxaTtimrTZ+3qqqKP/zhD8TExGC1WpkwYQKrVq3yOWfZsmWMHDkSq9XKqaeeyqZNm7zH9u3bx5QpUwgPDycoKIgTTjiBr776ynt806ZNnH/++QQHBxMbG8t1111Hfn6+9/jEiRO54447mDVrFlFRUZx33nlcc801XHXVVT5jcLlcREVF8c477wCQlpbGhAkTCAsLIzIykosuuojduw9/cyclJQGqUq6maUycOBFouMRztNdft8y1aNEiTj75ZAIDAznttNPYvn2795z169dz1llnERISQmhoKCeddBKrV69u6X8KIYTovlwlULIDzJEAvLtRPXxlxPdYe53TgQPzJQHKEdI2ZTHj3bVkOZw+j2c7nMx4d22bBin3338///vf/3j77bdZu3YtAwYM4LzzzqOwsNB7zn333cdzzz3HqlWriI6OZsqUKd4S8zNnzqSqqooff/yRjRs38tRTTxEcHAxAcXExZ599NqNHj2b16tWkpaWRk5PDlVde6TOGt99+G7PZzLJly3jttdeYNm0aCxcupKyszHvON998Q0VFBZdeeimgui7Pnj2b1atXs2jRIgwGA5deeikejweA9PR0AL7//nuysrL45JNPjvn1A/zpT3/iueeeY/Xq1QQEBPC73/3Oe2zatGn07t2bVatWsWbNGv74xz9iMpmO6b+HEEJ0S+X7oLoIzOHsLYYf96vVgWtilkL0hI4dWz2yxFOP26Mzd+EWv0tvqvAvzF24hXOGxbX6ck95eTnz58/nrbfe4vzzzwfg9ddf57vvvuNf//oXp5xyCgBz5szhnHNUhPv222/Tu3dvPv30U6688kr279/P5ZdfzogRau96//79vfd/5ZVXGD16NH/5y1+8j73xxhskJiayY8cOBg0aBMDAgQN5+umnveckJycTFBTEp59+ynXXXQfA+++/z29+8xtCQkIAuPzyy31eyxtvvEF0dDRbtmxh+PDhREer7piRkZHExcUd0+u/7777vOc++eSTnHnmmQD88Y9/5MILL8TpdGK1Wtm/fz/33XcfQ4YM8b4eIYQQtTwuKN5U23fHwLubNHQ0Joaspm+f4WC0dPQIvWQGpZ70jMIGMyf16UCWw0l6RmGj5xyr3bt343K5GD9+vPcxk8nE2LFj2bp1q/exlJQU778jIiIYPHiw9/gf/vAHnnjiCcaPH8+cOXPYsGGD99z169fzww8/+HQZrvsjXn855qSTTvIZV0BAAFdeeaW3I3F5eTkLFixg2rRp3nN27tzJ1KlT6d+/P6GhofTr1w+A/fv3t/rrBxg5cqT33/Hx8QDk5uYCMHv2bG6++WYmT57MX//6V5/XJoQQPV7FAajMAmsMlS74aIt6S35D5BcQn9rBg/MlAUo9uaWNByfHcl57u/nmm9mzZw/XXXcdGzdu5OSTT+bll18GoKysjClTprBu3Tqfj507d3LGGWd47xEUFNTgvtOmTWPRokXk5uby2WefYbPZSE09/I08ZcoUCgsLef3111m5ciUrV64EVJJtW6i/ZKPVFhKqW0569NFH2bx5MxdeeCGLFy9m2LBhfPrpp20yDiGE6OzcHp3luwtYsO4Qy3fn4y7aBpoBDGYW7ICSagN9zFmcmVgDgb07erg+JECpJyakefu+m3teSyQnJ3tzP+q4XC5WrVrFsGHDvI+tWLHC+++ioiJ27NjB0KFDvY8lJiZy22238cknn3DPPffw+uuvAzBmzBg2b95Mv379GDBggM+Hv6CkvtNOO43ExET+85//8N577/Hb3/7WGyQUFBSwfft2Hn74YSZNmsTQoUMpKiryub5uJ5Db7T7u198cgwYN4u677+bbb7/lsssu480332zR9UII0R003PCxkglvukg7lICuw9u1k+zXRX6FodeRsycdv89YApR6xiZFEG+30lh2iQbE29WW49YWFBTEjBkzuO+++0hLS2PLli3ccsstVFRUMH36dO95jz32GIsWLWLTpk3ceOONREVFeXfCzJo1i2+++YaMjAzWrl3LDz/84A1eZs6cSWFhIVOnTmXVqlXs3r2bb775hptuuqnJwKHONddcw2uvvcZ3333ns7wTHh5OZGQk//jHP9i1axeLFy9m9uzZPtfGxMRgs9m8ibkOh+OYX39TKisrueOOO1iyZAn79u1j2bJlrFq1yieAE0KInqDRDR8VRmZ8F8jf18DWAgMWrYrfxq6FyHGHT9Ld6sMS1c6j9iUBSj1Gg8acKerd+pFBSt3nc6YMa7N6KH/961+5/PLLue666xgzZgy7du3im2++ITw83Oecu+66i5NOOons7GwWLlzoM0Mxc+ZMhg4dSmpqKoMGDeLVV18FICEhgWXLluF2uzn33HMZMWIEs2bNIiwsDIPh6N8G06ZNY8uWLfTq1csnT8RgMPDhhx+yZs0ahg8fzt13380zzzzjc21AQAAvvfQS//d//0dCQgIXX+y/Q2ZzXn9TjEYjBQUFXH/99QwaNIgrr7yS888/n7lz5zbreiGE6A6a3vCh/n69slr9/yVhSwhLnACa8fBJVYVgiYCgvu0w2sZpehcs5VlSUoLdbsfhcBAaGupzzOl0kpGRQVJSElbrsS3FpG3KYu7CLT6RZ7zdypwpw0gdHn9cYxedT2t8zwghRGexfHcBU19fcZSz1N7ULwbezfCzHgZzvTeCJdshKgVixjd69bFq6u/3kWSbsR+pw+M5Z1hcj68kK4QQoutp3kYOjZMCtzC8T5xvcFJTrvrwhCS32fiaSwKURhgNGinJkR09DCGEEKJFjraRQ8ODjoHrI7+EhAt9DzpzIbgfWGPbboDNJDkoQgghRDdytA0fOgaiAopIjT8IofU2Eehu1Z8ndDBoHb9iIAGKEEII0Y00teGjbvvw1IhvsCSe5xuIVOWDNbrDk2PrSIAihBBCdDOpw+OZf+0Y4oKP/DOvEUAN06J/gJgzfQ9VF0HoEJWD0glIDooQQgjRDaUOCeWcq7JIzzKRWxPGp9s0luzXSLX/QlziGDDaDp/sKlX9eYL7N37DdiYzKEIIIUR3VLYXY00hKUkhnJ4Iyw+ph2+K+hwSLvA915mrlnY6uDhbfRKgCCGEEN2NpwYcm8EYBJqRD7dAlVtjuG0XY3rZILBXvXNdgKfTJMfWkQBFCCGE6G4qDkDFIbDGUOOBdzeqh2+M/Byt10W+51blgTUGAhPbf5xNkAClB5o4cSKzZs1q9vlvvfUWYWFhbTYeIYQQrUjXwbFNzYYYzHy3BzLLDEQai7kobgdEjPE911UCocPAaO64MfshAYoQQgjRnThzoXwPWFSxtTc3qGWbayLTsPY+17fvjqsYTHYI6TzJsXUkQBFCCCG6k9JdUFMJpmC25EN6Zu3W4qhFEDfZ99yqfAgZAOawDhlqU3pEgKLrOhXVNe3+0dI+jBMnTuTOO+9k1qxZhIeHExsby+uvv055eTk33XQTISEhDBgwgK+//tp7zdKlSxk7diwWi4X4+Hj++Mc/UlNT4z1eXl7O9ddfT3BwMPHx8Tz33HMNnreqqop7772XXr16ERQUxLhx41iyZMkxf72FEEJ0EFcplG7z7sZ5u3b2RG0tHqW2EtdxO9VsSsjAjhjpUfWIOiiVLjfDHvmm3Z93y2PnEWhu2Zf47bff5v777yc9PZ3//Oc/zJgxg08//ZRLL72Uhx56iOeff57rrruO/fv3U1RUxAUXXMCNN97IO++8w7Zt27jllluwWq08+uijANx3330sXbqUBQsWEBMTw0MPPcTatWs58cQTvc95xx13sGXLFj788EMSEhL49NNPSU1NZePGjQwc2Dm/cYUQQvhRlgFVhRAyiKJK+Gy7elhtLZ7pe64zV+3msSW0/ziboUfMoHQlo0aN4uGHH2bgwIE8+OCDWK1WoqKiuOWWWxg4cCCPPPIIBQUFbNiwgVdffZXExEReeeUVhgwZwiWXXMLcuXN57rnn8Hg8lJWV8a9//Ytnn32WSZMmMWLECN5++22fGZb9+/fz5ptv8vHHH3P66aeTnJzMvffey4QJE3jzzTc78CshhBCiRdzVamtxQAhoBt7fXG9rcbzJt4S97gZ3JdiHgcHY+D07UI+YQbGZjGx57LwOed6WGjlypPffRqORyMhIRowY4X0sNlYlPeXm5rJ161ZSUlLQ6u1bHz9+PGVlZRw8eJCioiKqq6sZN26c93hERASDBw/2fr5x40bcbjeDBg3yGUdVVRWRkdLNWQghuozyfVCZBUH9cLnhnY3qb8P0qM/Qeh/RtbiqECwRnabvjj89IkDRNK3FSy0dxWQy+XyuaZrPY3XBiMfjaZXnKysrw2g0smbNGoxG34AqODi4kauEEEJ0KroHSraAFgAGE1/tgJxyjeiAQi6M2QqRd/meX10A0eMhIKhjxtsMXeOvtvBr6NCh/O9//0PXdW/gsmzZMkJCQujduzcRERGYTCZWrlxJnz59ACgqKmLHjh2ceaZqEjV69Gjcbje5ubmcfvrpHfZahBBCHIfKTCjbB9ZYdB3eWKf+JlwX+RXm3qlHbC0ug4BACE7uoME2j+SgdGG33347Bw4c4M4772Tbtm0sWLCAOXPmMHv2bAwGA8HBwUyfPp377ruPxYsXs2nTJm688UYMhsP/2QcNGsS0adO4/vrr+eSTT8jIyCA9PZ158+bx5ZdfduCrE0II0WyO7aC7ICCQtdmwPlfDrFVzTdQiiDvX99yqHAjqp6rHdmIyg9KF9erVi6+++or77ruPUaNGERERwfTp03n44Ye95zzzzDOUlZUxZcoUQkJCuOeee3A4HD73efPNN3niiSe45557OHToEFFRUZx66qlcdNFFRz6lEEKIzqaqAMp2eQuzvbFezZ5cEraEqF5jwBRy+FyPSy0HhQ7pVH13/NH0FhTrmDdvHp988gnbtm3DZrNx2mmn8dRTT/kkXTqdTu655x4+/PBDqqqqOO+883j11Ve9yZ2gdo7MmDGDH374geDgYG644QbmzZtHQEDz4qWSkhLsdjsOh4PQ0FCfY06nk4yMDJKSkrBarc19aaIHk+8ZIUSXlr8Scn+E0CEcKoUz3tFw6xpfD7yDoRPuhaA+h8+tzARTKPS5Agymxu/ZRpr6+32kFi3xLF26lJkzZ7JixQq+++47XC4X5557LuXl5d5z7r77bhYuXMjHH3/M0qVLyczM5LLLLvMed7vdXHjhhVRXV/PLL7/w9ttv89Zbb/HII4+08GUKIYQQPVxNudpabFa7Lt/ZqIKT04LXMzTe7huc6B5wOSB0aIcEJy3VohmUI+Xl5RETE8PSpUs544wzcDgcREdH8/7773PFFVcAsG3bNoYOHcry5cs59dRT+frrr7nooovIzMz0zqq89tprPPDAA+Tl5WE2H71ZkcygiNYk3zNCiC6reBNkfg0hA6moMXLqmxol1Rr/7PcYk1POg8hTDp9bVQB6DfS9Us2idIA2m0E5Ul0uQ0REBABr1qzB5XIxefLhWv9DhgyhT58+LF++HIDly5czYsQInyWf8847j5KSEjZv3uz3eaqqqigpKfH5EEIIIXo0jwuKN6ry9ZqRT7ZDSbVGX3MmZ0cfhIiTfM+vLlBl7TsoOGmpYw5QPB4Ps2bNYvz48QwfPhyA7OxszGYzYWFhPufGxsaSnZ3tPad+cFJ3vO6YP/PmzcNut3s/EhMTj3XYQgghRPdQvl8VZrPG4qm3tfiGqC8w9L4QtHp/4msqwGDutH13/DnmAGXmzJls2rSJDz/8sDXH49eDDz6Iw+Hwfhw4cOCo1xzHypXoYeR7RQjR5egelXuiGcFg4oe9sKdYI8RQxpVRP0HsJN/znTmqaqwtrkOGeyyOKUC54447+OKLL/jhhx/o3bu39/G4uDiqq6spLi72OT8nJ4e4uDjvOTk5OQ2O1x3zx2KxEBoa6vPRmLqqqxUVFS1+XaJnqvteObKKrxBCdFqVmVC2F6zq7+Y/a2dPron8huBeE1QhtjqeGpV7EjrUd1alk2tRHRRd17nzzjv59NNPWbJkCUlJST7HTzrpJEwmE4sWLeLyyy8HYPv27ezfv5+UlBQAUlJSePLJJ8nNzSUmRhWJ+e677wgNDWXYsGHH/YKMRiNhYWHk5uYCEBgY6NOrRog6uq5TUVFBbm4uYWFhDUr9CyFEp+XYqoKOgEA25cHyQxpG3NwQ+QUkPOF7blWeKspWf0dPF9CiAGXmzJm8//77LFiwgJCQEG/OiN1ux2azYbfbmT59OrNnzyYiIoLQ0FDuvPNOUlJSOPXUUwE499xzGTZsGNdddx1PP/002dnZPPzww8ycOROLxdIqL6puJqYuSBGiKWFhYY3O3gkhRKfjzFeF2ay1hdlqZ08uDPuJhPhksMUfPlfX1dbiiJPB2Dp/Y9tLiwKU+fPnAzBx4kSfx998801uvPFGAJ5//nkMBgOXX365T6G2OkajkS+++IIZM2aQkpJCUFAQN9xwA4899tjxvZJ6NE0jPj6emJgYXC5Xq91XdD8mk0lmToQQXUvpDtVPx9ab7DL4fKd6+Oaoz6DX73zPdRWDyQ4h/dt7lMftuOqgdJSW7KMWQgghOhu3Ryc9o5DcUicxIVbGJkVgNDQjHcFVCvs/AgxgieLp5RqvrtEYG7SJj0b9E0Y/51vCvmQHRJ4EsRPb6qW0SEv+fksvHiGEEKIdpW3KYu7CLWQ5nN7H4u1W5kwZRurw+CauBEp3qYJrIYOpcMF7m9TD06M+g16/8Q1OairA2LW2FtfXddJ5hRBCiC4ubVMWM95d6xOcAGQ7nMx4dy1pm7Iav9jtVFuLTWGgGfjfNnBUqcJsk6N2QvR43/O9W4uPEvR0UhKgCCGEEO3A7dGZu3AL/vIq6h6bu3ALbk8jmRdle8GZDZZoPDr8qzY5dnrUAoy9LvDtr+Nxge7qcluL6+uaoxZCCCG6mPSMwgYzJ/XpQJbDSXpGYcODnhpwbASDDQwBfJ8Bex0admMpV0T+BPGpvudX5akaKUF9W/dFtCMJUIQQQoh2kFvaeHBy1PMq9kP5Qe/W4n/8WluYLSKNwITxYAo5fG5d12L7CSoHpYuSAEUIIYRoBzEhzeuW3uA83QOOLSoB1mhhTRasztIwaS5uivocek3xPb+6CMwRXXJrcX0SoAghhBDtYGxSBPF2K41tJtZQu3nGJkX4HqjMhNI9YFXJrq/Xzp5cEraEmNgBENjb9/yqfAgd3GW6FjdGAhQhhBCiHRgNGnOmqJYuRwYpdZ/PmTKsYT2UemXt9xbDN3vUw7dEfwq9L/U9t6YMjLYuu7W4PglQhBBCiHaSOjye+deOIc7uu4wTZ7cy/9oxDeugOHNV7ZPa3JN/rtPQ0TgrZBWDoswqz8Tn/BwI7uc9vyuTQm1CCCFEO0odHs85w+KaV0m2ZBvUlENgbwoq4eOt6uFboz9hR+AlbN2pERMIYxPASLXKV7EP9S3Y1kVJgCKEEEK0M6NBIyU5sumTqouhZDtYogF4dyNUuTVG2HbS15zN6d+fjrt2ISQ+WGfO2FJSB/eGwK7VtbgxssQjhBBCdEYlO2p35ITjrIF3NqpZkVuiP+Vf+b/BzeFGp9llMGNxFGnZ/cDQPeYeJEARQgghOpuaclXW3hwJmsb/tkFBpUYvUw4Tgn/lw8LzfE7Xa9Ns5y4uabwSbRcjAYoQQgjR2ZTuVtuFLVG4PfDP2q3F06MX8FHhuZR7AhtcoqOR5ajyX4m2C5IARQghhOhM3E4o3qDqmGgGvtkDGbVl7S8LW8RbBVOavLy5FWs7OwlQhBBCiM6kbE9tU8AYdB1eW6tmT66P/JJFpWPJdkU1eXlzK9Z2dhKgCCGEEJ2FxwXFG8EYCIYAlh+CDbkaFq2KG6IW8ln5pWh++yE3UYm2i5IA5UhleyBnKejdI8lICCFEF1K2FyoOqU7EwPw1avbkyojviIruz7Rx/QAaBClNVqLtoiRAOVJNJZTtUtX4hBBCiPbicYNjIxhMYDCxKQ9+OqBhwM0tUZ9C78tITYb55+vEBfte2mgl2i6se2yWbm2VuapzpC2uo0cihBCip6jYD+X7waaa//1fbe7Jhfaf6RMZAmEjAUhNhnOSdNIzcsmtDiEm6QzG9o/pNjMndSRA8csDpdshbARYozt6MEIIIbo73aPqngAYLex3wJe71Ke/j/kfJF7hU77eqLlJiSmE+LEQ1vX77vgjSzz+GK3gKlM9EIQQQoi2VpkJpXvAqpZoXl+n4dE1Tg9ey/DwCohK8T2/Kl+VwA/u3wGDbR8SoDTGEqNaXFcXdfRIhBBCdGe6rtIK9BoICKSgEj7aog7NiPkv9L4ENKPv+dVFYB8GAQ0LtnUXEqA0xhwOrmLVqEkIIYRoK84cKN3p3bnz1nqNKrfGSNsOUsL2Qewk3/NdxWCyQ8iA9h9rO5IApTGaBuYotSboKuno0QghhOiuijdDTSVuYwiLMuCf69TDt8d8jNbrQjBafM+vyoXQweqNdDcmAUpTLJFQVQAlOzt6JEIIIbojZx6U7SAtK5EJ72hM/9JAZY1GsuUApwf/yqKqC3zPd5WB0aYClG5OApSmaAYwR4Bjk+osKYQQQrQmxxbSdhmY8V0QWWWHH54R/TEfFZ3Dzd/aSdtd7/yqbAjqD9buuXOnPglQjsYSBc5cmUURQgjRuqoKcBdvY+7q+Nq6sGobcS9TLheE/czreZcCMPcnDbcHcFepc8KG+Ww57q4kQDmSqxTclYc/14wqGcmxUVWZFUIIIVqDYxvph2rIKjdyuFg93Br9CV8Vn06mKwYdjawyjfRMVAPBwD7eQm7dnQQo9e16HX44V/Xiqc8ao7Ksy3Z1zLiEEEJ0L9XFULKFXJdvY79IYzFXhH/P/LwrfB7PLfeoGZSwE8BgpCeQAKU+SyTUlEL+z1BTcfhxzQgBIVC0HtzOjhufEEKI7qFkO1QXEWMP8nn4d9EL+KlsNLurEn0ejzEVgS0egpLac5QdSgKU+npfov7ju52Q9bXvMUsMVOZA6W6/lwohhBDN4ipRmy/MUYxN0Ai3qgyUYEM510V+yfzcw7MnGjrxwTpjI/IgfAQYzR016nYnAUp9mgGSb1b/PvhZbUJSLUOAqthXvAHc1R0yPCGEEN1AyQ5VwsISiUEDe22Zk+sjv2RjxQDWV6otxFpt6uycccUYA2MgOLmjRtwhJEA5UsIFYAoDlwNyFvkes8aqfgllezpkaEIIIbo4V5l6o2uOBM3Azwdgr0PDolVxU9TnvJp3pffUuGCYn+ohtVdmty9r7490Mz6SwQSxZ8HBT+HAJxB3rpo9qTtmtEHxeghJVp8LIYQQzVWyXTX6C1GzJC+vVrt3rolMIyo8ijsGjeDKSg8xgTA2AYyuQtAjIGRQR466Q8gMij+RY9XW4qpcyPvR95g1DioOQVlGx4xNCCFE11RTrkpWmCNAM7DyEKRnapg1F7dGfYKWeAUpiRoXD4KU3mA0AFV5EDoEzPaOHn27kwDlCG6PjguTSpgF2P9f0D2HTzCYwGBRsygeV4eMUQghRBdUskOVtrdEA/BK7ezJFeHfE2+3QdQ43/NdJWAK7hFl7f2RAKWeRVtzOO9fmfx7WzjEnw/GIKg8CAUrfE+0xUH5ASjb2yHjFEII0cXUlKvcE1MYaAbW5cBPBzSMuJkR81/o81tV0qI+ZzYEDwBrdIcMuaNJgFJPbmkVuwpc/N+mCJwEQsKF6sD+/4KuHz7RYFYfxevBU9MxgxVCCNF1lOxUbVNqg41XVqnZk0vCfyAxFIg5w/f8mgr1d8Y+rJ0H2nlIgFLP5WN6kxBqJKfSxMdbgV5T1DdI2S4o+tX3ZFs8lO+XXBQhhBBNq6lQb2hNYaAZ2ZwH3+/V0PAwM+Yj6H25n9mTLAhOUn9reigJUOoxBxiYcapKRJq/RqPaaIf4VHVw/0cyiyKEEKLlSnaq3JPa2ZNX16jZk4vsP9E/xAlxk3zPr6vBZT9B1efqoXruK2/Eb0cGE2tzkVmm8b9tQO9LQQuAki3g2Ox7ssyiCCGEaITbo7N8RyYL1mxjeX4Ubt3IrkL4qratm5o9ubRhyYrKTAjqoxoD9mBSB+UI1gADvx9eyGOrYvn7ao0rhkRiijtHlb7f/x8IG374ZINZfWMVr1dTcQb5cgohhIC0TVnMXbiFLIcTCAaCiQ/WSQwFHY1zQ5czJLQY4s/zvdDjAr0G7CN6TFPAxsgMypE0A1MHFhFl0zlYqvHpdiCxdn2weD2UbPM935YgsyhCCCG80jZlMePdtbXByWFZZZCeqf79h5gPoddvwGj1vdiZDYG9Ibhf+wy2E5MA5UiBvbAFhfH7kWUA/H2NRo05BmLOUsf3f+R7vncWZaPkogghRA/n9ujMXbgF3e9RDdCYHLKSE0KyVWuV+jw14K6AsBFSqRwJUBoyhYL9BKb1P0iEVWefQ2PhTqDPFYABCldD6S7fa6zxULFPZlGEEKKHS88obDBzcpgKW+6KfZ9DIRdBQBBuDyw/CAt2wPK9DtzmOJUyICRA8St0MIGBodw8ogKAl1dpuC0JEHO6On7kLIrRohJpZUePEEL0aLmljQUnABpnh6STZMlkg/k3pO2GCe9oTP3MwF3fGpj6VTQTPowibWtRu423M5MAxR9zONiHcP2Ag4RZdPYUa3yxC+hzJaCpyrLle32v8eaiSKdjIYToqWJCrI0cqZs9+YC3Cy5iZ0kIM77WyCrzPSu71M2Md9eStimrbQfaBUiA0pjQoQQHBnLzCBUNv7RKw21NhKjT1PH9H/uebzBLjx4hhOiG3B6d5bsLWLDuEMt3F+D2+M8wARibFEF8iAGtQRaKxsSQ1QywHGBhxcV8sLnuDM3nrLqr5i7c0uTz9AQSoDTGGg0hg7lhwH7CLDq7izS+2EntLAqQ97OaManPFl/bo0dmUYQQojtI25TFhKcWM/X1Fdz14Tqmvr6CCU8tbnSGw+ipYM6pxQD1gpTDuSf/LriQ84eEkl2uEmb90YEsh5P0jMLWfTFdjAQoTbEPJSTQwi0jVVW/F1dpuAOTIPJUQPezo6e203HRenBXt/94hRBCtJrGtgtnO5yNL8M4tpMaf5D5qR7iguse1DgjeA1DrXsZNPJi+oU17/mbzmfp/iRAaYo1FoIHcMPA/d5clIU7gb5Xq+N5P0HFAd9rvNVld7f7cIUQQrSOprYLN7oM4yr19txJHaDx/sU6Ru1w7om59/mcPSiMmMDmjaHxfJaeQQKUpmgahJ1AsNnILaPUjMhLqzRqAvsfnkXZ52cWJSAIitYd7qcghBCiS2l6u3AjyzAl26AqD6wxALy6VsOta5wevJaTQvZgSLwUgLEJEB+s+8lTUTQg3m5lbFJEa72cLqnFAcqPP/7IlClTSEhIQNM0PvvsM5/jN954I5qm+Xykpqb6nFNYWMi0adMIDQ0lLCyM6dOnU1Z2RCpzZ2FLgJBkbhh4gHCrmkX5fAfQ9yp1PO9HqDjoe401FioPySyKEEJ0Uc1dXvGe5yqB4g1gjgLNQEYxfFJbePzu2Pcg7jywqIDDaIA5p9elyPoGKXVZKXOmDMNo8J+j0lO0OEApLy9n1KhR/P3vf2/0nNTUVLKysrwfH3zwgc/xadOmsXnzZr777ju++OILfvzxR2699daWj749aAYIG06wSefWE9XunJdXadQEJkPkWFQuyn98rzGYwBgEhevA3bPXEIUQoitq7vKK9zzHFqgqAEsUUFs/S9c4K2QVY4J3Q+JlPtelJsP8Mw8RF+z7ZzjObmX+tWNIHR5//C+ii2txd7vzzz+f888/v8lzLBYLcXFxfo9t3bqVtLQ0Vq1axcknnwzAyy+/zAUXXMCzzz5LQkJCS4fU9gITIbg/1ydn8Pq6ZDIcGgt26FzeZyoUpEPuT9DnKtU/oY41Ts2glO5UZYuFEEJ0GWOTIoi3W8l2OP0uxGioYGJsUgRUF6l2J5YY0DR2F8FnO9R5d8e+pxoCWiJ9b+AqITXZwzlnnkR6VgC5pU5iQtT9evrMSZ02yUFZsmQJMTExDB48mBkzZlBQUOA9tnz5csLCwrzBCcDkyZMxGAysXLnS7/2qqqooKSnx+WhXmgHCRhBUbxblpVUarsBkiBgLePzs6AkAU4ja0VNT0b7jFUIIcVyMBo05U4YBDTcDN1iGKd4C1cVgVks4L63S8Ogak0NXMDJoHyRe0fAJKrMhZBDGwFhSkiO5+MRepCRHSnBST6sHKKmpqbzzzjssWrSIp556iqVLl3L++efjdrsByM7OJiYmxueagIAAIiIiyM7O9nvPefPmYbfbvR+JiYmtPeyjC+wDQX25PvkgUTbVo+eT7Rze0ZPbWC5KFpRsb/fhCiGEOD6pw+OZf+0Y4uy+yz0+yzBVBeDYpH7faxo7C1F5isCs2PchIdXP7EmZ6mIcNqydXknX1OIlnqO5+uqrvf8eMWIEI0eOJDk5mSVLljBp0qRjuueDDz7I7NmzvZ+XlJS0f5BiMELYSALL93LbaBdP/GLmpVUalwwegCViLBSmw77/wNB7Dl+jGcEUpradhQwEU3CjtxdCCNH5pA6P55xhcaRnFPpfhinepBJkbSo94YV0DR2N1NBlDA86CL0faXhTZxaEDVepAKJRbb7NuH///kRFRbFrl+oAHBcXR25urs85NTU1FBYWNpq3YrFYCA0N9fnoEEF9IbAP1yYfIjZI51CpxkdbgL5T1fG8HxtWl7XGgDNXJVAJIYTocowGzWcZBlCl71dtZfn23aoDMbAtH77cpQKXWbHvQ/z53p07XjVlqjWK/QRVykI0qs0DlIMHD1JQUEB8vMpITklJobi4mDVr1njPWbx4MR6Ph3HjxrX1cI6PIQDCRmI1VHPHSapr8curNJy25HrVZT/0vUYzqG1njo1Q7Wj/MQshhGg1PqXv/7eHqV/FMuHDcNJ2w9/SVcBxof1HhgRlNdi5A9TmngzwzriIxrU4QCkrK2PdunWsW7cOgIyMDNatW8f+/fspKyvjvvvuY8WKFezdu5dFixZx8cUXM2DAAM477zwAhg4dSmpqKrfccgvp6eksW7aMO+64g6uvvrpz7uA5UnA/CErkyn6H6BWik1uh8e5G6s2i/AxlGb7XWKKgqhAcm9t7tEIIIVpJo6Xvy+C2rzW+3aNhwMPdse9DwgVgDve9QU157Rvd4TJ70gwtDlBWr17N6NGjGT16NACzZ89m9OjRPPLIIxiNRjZs2MBvfvMbBg0axPTp0znppJP46aefsFgs3nu89957DBkyhEmTJnHBBRcwYcIE/vGPf7Teq2pLBhOEjcSCk7tOVrMo89dqlJuTIHqCOmefb90XNA0s0WqtsqpnN38SQoiuqOnS94eDjUvCf2BAYB709jd7kgXBA8DWq+0G2o20OEl24sSJ6HrjLaC/+eabo94jIiKC999/v6VP3XkE94eg3lzW5xCv2vuy16Hx1gadmUOvhrxlULACSndDSPLha8wRULpd7ZWPPbPjxi6EEKLFjlb6HjSMuJkV8z4kXAjmMN/DNRVq44TMnjSb9OI5FgYThI0iQHcy6xQ1i/KPXzVKAvpAzBnqnH1HBGCapjK2S7ZAZU47D1gIIcTxaE7p+6sjviHeWuI/98SZqd60BsrsSXNJgHKsamdRpvTOZGCEjqNK45/rNOhzNWCAwlVQssP3GnMYuMrVtuMmZqGEEEJ0LkcrfW/Wqrkz9j9k2y8G0xE7TWsqAFXwE03+7DaXfKWOldEMYaMweiqYXTuL8s91kE8viD1LnbPvvYbX2Xqpwm2Vh9pvrEIIIY7L2KQI4kMtjXYgvj7ySwINVSQM+U3Dg86s2tmT3g2PiUZJgHI8gvtDUCKpCZmMjNGpcGn8fY2m+vJoRij6teHOHVMweFxQtA50T4cMWwghRMsYDRpzJocBDTsQ2zQnM2I+Jjv8UozmIwpyuivV/8vsSYvJV+t41M6iaO4K7hunevS8txEO1cRB3DnqnIx/N1zOCewNpbugfG/7jlcIIcSxcTtJjdnJ/LPziDsiBrk5+jOCzRqDRlzU8LrKTFX3JLADWrR0cRKgHK/g/hDYiwlRWaT00qn2aLyYXjuLYjCrpNiitb7XGG2oPJV14KnpiFELIYRoCcd2qDhI6pAwfr5eZ8YYNQMeaizn5uhPsfS7ovZ3ez01FYAmsyfHSL5ix8tohvAT0TyV3lmU/26DXRWRqlAPwN53/cyi9ILyDCjb3c4DFkII0SKuMihep3qrGQKo0eHznWqr8O3RH2G3WSHh/IbXeXNPZPbkWEiA0hqCk8GWwJiwLCYn6Xh0jT/9oPF19RW4NZsKQvKX+15jMIPBCoVrwV3VMeMWQghxdI7N4MxRvdWA9zfBoVKNWFMhN0R9AX2uVL/T6/Pu3BkpsyfHSL5qrcFohvDRUFNBSnwNoLMyU2PG92G8kn0JAGU73wXd7XudLQEqDoFjW7sPWQghRDNUFULxBlUNXDNQVg2vrFazJ3fFvIfNZoe4yQ2v89Y9kZ07x0oClNYS3J+0nH488Ytvcd5/5l1CUU0IwTUH2bBxie81hgC1X754nZpCFEII0bkUb4TqYjCrLsb/WgcFlRpJlkx+G/E99JuminfWV1MBGCX35DjJV66VuDUTc38Jrt18driMcakniPl5VwAQlfcB7hqX74XWWDV1KI0EhRCic6nMBscWsMaDplFQCa//qn6/3xv7Nqag3oerh/tcd0hmT1qBBCitJD2jkKxSN/WDkzpv511IjiuCBFMu+7Z/63tQM4AlRk0hSiNBIYToHHQditarOiZmOwCvrtYoc2mMsO3ifPsvkHSdqnlVX00FaAGSe9IK5KvXSprq01CFlZdzrgYgoejDw4V76pgj1BRi8YY2HKEQQohmq9ivqn7bEgA4WAL/3qgO3R/3Fgb7YIg4peF1lZkQMlBmT1qBBCit5Gh9Gj4oPJe9VfFYPQ44uMD3oKapHwLHZqjIbMNRCiGEOCpPjdphiQcCggB4Pl2j2qNxWvB6JgSvg37XN+xKXFOmcgvDR0jH4lYgAUorGZsUQbzd6meBR3Fj5F/F16pPDn4K1Q7fE0yhartx0XopgS+EEB2pdBeU7QGbmgXZmg+f1G62vD/ubbSIkyBseMPrKjMhZJDquSaOmwQorcRo0JgzZRjgLwtFOWnEeFV51l0JBz5ueIKtF5TukBL4QgjRUdxO1UfNGAhGCwBPLdfQ0bjQ/iMnBu6ApGsbXucqAaMVwkfK7EkrkQClFaUOj2f+tWOIs/su9xg1HdDYV2KAfjeoBzO/Ameu7w0CAgENCn9VDQWFEEK0L8dWqDgItngAlh2AJfs0TJqb++PegejTVXHOIzmzIGQIWOPaecDdlwQorSx1eDw/P3A2H9x8Ci+e6+aD8w7x/Dlq8/E/ftXIt5yosrv1Gtj7XsMbBPaCsgwo2dG+AxdCiJ6u2qFmT8zhoBnx6DDvFzUbMi3iS/pa81TdE3/XGYPUso/MnrQaCVDagNGgkTIghovHjiQlvoKLkioYGaNT7tJ4cbUBkmpnUXKXNFzOMZjBFKJ+SGrK23voQgjRcxVvgKp8VfoBWLgDNuVpBBud3Bn7IcSf593V48OZDfahYItt5wF3bxKgtKWgPhAyEIMzkwdPU7Mo72+C3TUDIeo0QIeMfze8zhoLlVlQLMXbhBCiXVTmgGOTWqLRNKrc8MwKNRtyW9RHRFpc0OfqhtdVF6k3lXY/SbPiuEiA0pY0A4SPAkMAKXFlTOqn49Y1nlquQb/rAAMUroLiTUdcZ1R9H4rXQ1VBhwxdCCF6DF2HonXgqlDLO6iaJwdLNWJNRUyPXgC9LwVzWMPrnDlgHwbWqHYfdncnAUpbs/VS284q1SyKUdP5do9GenEviD9XnZPxpvpGr88cUbseur7hMSGEEK2nfC+UbFM5gICjCl5ZpWZPZse+g81ig94XN7yuulAFLfYT2m+sPYgEKG1N09S2M6OVASElXKV2IvPkzxqePlPBYIXSnZD3c8PrbAmqD0TlofYftxBC9AQeFxSuATRvUba/r9YortIYaD3I5eGLoO9UMNp8r9M9UJWrGgJaItp/3D2ABCjtwRavtp85s5g1VifIpLM+V+OLfeGQeJk6Z+87DbcWm0JAd6mKhh53+49bCCG6u5La2lO1pen3O+Ct9erQQ3H/xGWO5/PSc1h+ENz1a2hW5YMlSi3viDYhAUp7CR8JAcHEmIq4bYxasnl6uUZV/CVqzdOZo2qjHMmWWFvVcHf7jlcIIbo7VxkUroaAEDCYAFWUrdqjMT54PRNDVjNr5w384TszUz8zMOEdjbTdgO5Wyztho1QVcNEmJEBpL9ZoFWk7c7h5lE5skM7BUo13Nluh7zXqnP0fqV4O9Rktqjph4RqoqWx4XyGEEMemeIN6c1hbXG1NFny5S0ND5+H41/m1YjDflKR4T88ugxlfa6RtK1G7Le1DOmrkPYIEKG3E7dFZvruABesOsXx3AW6PrtYqzWHY9ELuGadmUV5erVEUNhkCE6GmFPb/t+HNbAlQcUA1ExRCCHH8nLlQvBEssaAZ0HV44meVGPvb8O8YatvLE1k3U795iV7777nLQ3GHnejNWRFtQwKUNpC2KYsJTy1m6usruOvDdUx9fQUTnlpM2g6nqiJblcvlgz0MjdIpqdJ4cVUAJN2oLj60EJx5vjfUjGCOUtvgqgrb++UIIUT3ouuqpYir1Jvg+sUu+DVHw2ao4t64f/Nl8XjWVgxteCkaWRUm0gui23vUPY4EKK0sbVMWM95dS5bD6fN4tsPJjHfXknYwBqwxGKtz+fMENYvy742wi5NVoR/dpRJmj2SJgupi9UMl246FEOLYebcVq8RYZw08VVvS/rbojwkzlvJU9o1N3iK3XLrOtzUJUFqR26Mzd+EW/IUPdY/N/XoP7tCR4CritF5uJiep4m1P/mKA/jepk3KXqq3H9WmaqqlSskUt9wghhGg5d7VKjK23rfjtDXVF2Yq5JfpT3im4kP3V8U3eJibE2uRxcfwkQGlF6RmFDWZO6tOBLIeT9MI4lVdSmc1Dp+kEGHR+2KextHAgxJylTt79r4YzJaZglT1euEa6HQshxLFwbIWyfd7Zk/wKeGW1mj25N/ZNbGYTH5dfheb3rabKSIm3WxmbJLVP2poEKK0ot7Tx4MTnvAodwkeDu4z+dhfXj1CPP7FMo6bPtaphYMkWyF/e8OLARCjdI92OhRCipaodULQGTHbvtuLnVmiUVmuMCNzD5eGL0fpcxd3jgwEaBCl1n8+ZMgyjQboWtzUJUFpRc6f8YkKsEDIQAvtAZSZ3naITZtHZWajxwe5o1fMBIOOthjMlBrOaSSlco/bwCyGEaJ6idaq/mVV1Hd6cBx9uUYceiX8Ngy0WEi4gNRnmn68TF+x7eVyomfnXjiF1eNPLP6J1SIDSisYmRRBvt9JYXO0zNWg0q1kU3YXdVMXdtduOn1+p4Yi5TPXicWZD5hcNb2SNU8eK1rfZaxFCiG6l4pBqzGpLAE1D1+GxnzR0NC4K+5lTgrZA0vXemZXUZPj5ep0PLvHw4umH+OByIz8/MFmCk3YkAUorMho05kxRZY+PDFLqPveZGgzuD8HJUHmQa06A5HCdQqfGy2sDod+16px9H4Gr5IibGVSQUrwBKrPa7PUIIUS34KlRibF6tbfy6zd7YGWmhsXg4o9x/4LQYRA13ucyowFSYoq5eJCblOGjMRrlT2Z7kq92K0sdHs/8a8cQZ/dd7omzWxtODRqMEH4iYMCkl/Fw7bbjtzbAbvNZEJQE7nLY90HDJzKHg7uyNmFW+vQIIUSjSndC6W7VOgS1rfjJZeqN4q1R/6O3OR+Sb1a7JevTdTVbbT8BbLHtPeoeL6CjB9AdpQ6P55xhcaRnFJJb6iQmRC3r+E2qCkxU5ZKLNnBW38Gc3Vdn8T6Nx5cF8NaE38HGP0Pm1xB/PgT1aXhtyQ6VzxI6uH1enBBCdCU15eqNnDFQtQ4B3lgPB0o0Ys0Obov+L8SeDSEDGl5bla/eDIaNaOdBC5AZlDZjNGikJEdy8Ym9SEmObDzjW9NqG04FQXURfz5dx2TQWbJPY7FjFESOAzywx8+2Y6NVtQAvWKV+CIUQQvgqXAeVmWBT/XZyy+HvtduKH4j9J0EmoN91Da/TPVBdoKp/m8Pbb7zCSwKUzsAWq6rIOnNIsuv8bpR6+PGfNKr73gRaABT9Wltc6Mhr41UeSvHG9h2zEEJ0dpVZKlfPGqdahqC6FZe7NEYF7eaSsCXQ5wpvuXsfzhywxkDYCe07ZuElAUpnETZS/ZBU5XPHKTpRgToZDo03dyRA74vVObv/2XDbsWYES4za0VOZ0/7jFkKIzshTo2aX3U7vDMiaLPjfttqGf/F/x2CNht6X+LnWpfr0RJwkDQE7kAQonYXZDmEnQnU+ISY3D6TUdjtepZEbeaX6AXNmwSE/244tEbXrrKslYVYIIaA2MXanytUD3B549MfabsURizgxcAf0v1HVljpSZSYEJULIoHYcsDiSBCidiX2otwT+5UNgVKxOmUvj6fRA6He9Omf/f6C6qOG1gYlQsr1hDx8hhOhpXKVQkA4Bwd7E2I+2wsY8jRBjFffHvul3WzGgZlz0GogYo+pViQ4jAUpnEhCofihqyjDo1Tx6uppF+e82jbX6WRA8ANwVsPe9htfWJcwWrpYKs0KInq1oXW0OiUqMdTjhmeVq9mRWzNtEmxww4BbvtmK3B5YfhAU7YPmeAtxBA1SdKtGhJEDpbEIGqh+MikOMjoMrhqgg5ZEfjbj736rOyf5O7ek/ki1eTU0WrWu/8QohRGdScag2MTZBFbUEnk/XKHRqDLRlcX3UlxB/niqSCaTthgnvaEz9zMBd3xqY+k0iE/5tJm2z5PR1NAlQOhuDCSJGAzrUVPDH03RCzDqb8jQ+ODgEYs5Ux3b/X8Ntx5oRrPHqh7PiUEeMXgghOo7HpRJjPdUqrw/Ylg//rt3kODf+ZUwmm7dSd9pumPG1RtYRk87ZJS5mvLuWtE1SqbsjSYDSGQX1hdAhUHGQqEC4p7ZPzzPLNQrjbwKDFUq2Qe6Shteaw8BTVftD6mp4XAghuivHVijbpRqxot7DzflRw61rXBC2gtOCN0C/aWAKxe2BuT/V9Sf2rVNV99Zv7sItuD1HvBEU7UYClM5IM6gS+KZAqC7i2hEwJFLHUaXxzJpI6HuVOm/Pm1BT0fB6WyKU7lJJs0II0RNUF6kcvAC7d2fOgh2q347V4OKhuP9Tb/7iUwFIz4SsMo2GndMUHchyOEnPKGynFyCOJAFKZ2WLBftIcGYToHl4/EwVxX+4BdYHXAy2XuAq9t+nx2hRDbEKV0N1cbsOWwgh2p2uQ8FqqCoAq+qZU1IFT9T227kz5kN6m/Mg+ffegm25ft7b+ZNb6myTIYujkwClMwsfAZYocOZySgJcNlhHR+ORn0x4+t+izjm0EMr3N7zWGgvOPChY0zBXRQghupOyPeDYAoG9vTtz/rZSI79Co78tj5uj/gfRp0PYcO8lMYHNu3VMiPXoJ4k2IQFKZ2YKhfAxaqbEU+NNmF2fq/Gf7DEQeSrggV3+EmYN6ofVsQnKMzpi9EII0fZqKlXNE82o6p4Am/PgndrE2MfiXsASYISkG30uG5sA8cE6Go2/gYu3q0avomNIgNLZ2YeqLsaVmcQEwayx6ofpqV80CuJvVmutjo2Qv6zhtQHB6oc2f6X6IRZCiO6meANUHFBvyACPDn9equHRNS4MX8GEkPXQ5yqwRvtcZjTAnNPU78VGWrlS6XLz3Zbsthy9aIIEKJ2d0aL6QeguqKnghpEwNEqnuEpj3tpYSLxcnbf7X+D2E4QE9lY/vMXr23fcQgjR1iqzVSNVS6w3t+S/W2FttkaQsZo/x81X+Xp1/cyOkBq/j/kXmrAHmvwed1TIduOOJAFKVxDcX/WEqDxIgAGenKimJf+7TWOl4QqVb1JdAPv+0/BazaiqKRb9qjp7CiFEd+BxqaWdmgpvN+KiSpj3S13F2HeJMxXAgN+r+lJHqiqAgFDOOWkM1gD/fwplu3HHkgClK9AMqgR+gNp2PCYOrq7tAP7wT2aq+/1efXJoAZTva3i9ORxqnOqHWWqjCCG6g+ItULpDbR2u9fRyjSKnxqDAbG6MWgDRE1TJhiPpbqjKhfBRpGcZyC6pavRpZLtxx2lxgPLjjz8yZcoUEhIS0DSNzz77zOe4rus88sgjxMfHY7PZmDx5Mjt3+jawKywsZNq0aYSGhhIWFsb06dMpK5P+MU2yxXm3HaN7eCBFJ9Kms7NQ458HTlYJs7obds73v2snqI9qJFi8pf3HLoQQramqAApXgSnMW/NkVSZ8sEXNnjwR/zymADP0n+7/+sps1Zg1bHiztxHLduP21+IApby8nFGjRvH3v//d7/Gnn36al156iddee42VK1cSFBTEeeedh9N5+D/utGnT2Lx5M9999x1ffPEFP/74I7feeuuxv4qeInxk7fbhHMKs8NB4FYi8tErjQMzvwWCBki2Q+0PDaw1m9cNcuEr9cAshRFeke1Sl7OpisMQAUO2GPy1RwclVkT8wNmgz9L0aLJENr3dXqaarEWMgIKjZ24hlu3H7a3GAcv755/PEE09w6aWXNjim6zovvPACDz/8MBdffDEjR47knXfeITMz0zvTsnXrVtLS0vjnP//JuHHjmDBhAi+//DIffvghmZmZx/2CujVTiEqYrSkBj4vLBsO4BB1njcajK6PQ+1ytztvzpmo3fiRLjNqynJ8OHne7Dl0IIVpFyQ4o2QqBid6aJ/9cBzsKNSJMlfwx9h+q1H3CFP/XVx48nNcHjE2KIN5ubXQnj4ZsN+4orZqDkpGRQXZ2NpMnT/Y+ZrfbGTduHMuXLwdg+fLlhIWFcfLJJ3vPmTx5MgaDgZUrV/q9b1VVFSUlJT4fPVboYAjqBxUH0TSVMGsy6Czaq5FWdYn6oXU5YO+/G16raeoHt2SrWrsVQoiuxFWicukMVpWTB+x3wIvpKrx4OO5VwgNKYcBtYAjwf71mgsiTvceNBo05U4YBDbcb130+Z8owjIbGQhjRVlo1QMnOVvvFY2NjfR6PjY31HsvOziYmJsbneEBAABEREd5zjjRv3jzsdrv3IzExsTWH3bUYTBBRG9zVlDEgAn4/Rn0656cASvrMVJ9kfaPeaRzJaIOAIPVDXu1onzELIcTx0nVVGdtZmz9S+9DDSzWq3BqnhW7n0rAfIHaST8VYn+srsyDsBLX1uJ7U4fHMv3YMcXbfZZw4u5X5144hdXh8m70s0Tg/IWbn8+CDDzJ79mzv5yUlJT07SAnqqwq4Fa2HkEHccTJ8uRMyHBpPbzmBJ+LOUnkou16F0c956wN4WePUDErBKog7W+0SEkKIzqxsjyrKZkv0/s76Yhf8uF/DbHDzeNzf0Ewh0P8m/9c7c9R25PDR3qWh+lKHx3POsDjSMwrJLXUSE6KWdWTmpOO06l+muLg4AHJycnwez8nJ8R6Li4sjNzfX53hNTQ2FhYXec45ksVgIDQ31+ejRNE3lopjDoCofawA8eZZKmH1vE6wJvEVVkS3bo3r1NLjeoJaCHJugdHf7jl0IIQC3R2f57gIWrDvE8t0FTdcZcZVB/grQAsCkytk7quCxn1TwcHvMxyRbD0H/36kWIUfyuNTSd/gYMNsbfRqjQSMlOZKLT+xFSnKkBCcdrFUDlKSkJOLi4li0aJH3sZKSElauXElKSgoAKSkpFBcXs2bNGu85ixcvxuPxMG7cuNYcTvdmiVA/bNUF4KnhtN7w26GqmeCDP4dQ3bf2XcTe98CZ2/D6gCC1s6dgpf+EWiGEaCNpm7KY8NRipr6+grs+XMfU11cw4anF/iu26joUroHKQxB4eGnmr8s08io0+tvymRH1IdiHQ+zZ/p+w4iAE9wX7sDZ6RaIttDhAKSsrY926daxbtw5QibHr1q1j//79aJrGrFmzeOKJJ/j888/ZuHEj119/PQkJCVxyySUADB06lNTUVG655RbS09NZtmwZd9xxB1dffTUJCQmt+dq6v7BhtX16DgHw0GmqNsqOQo1/ZJ4D9hPAUwW7XvNfG8XWS63JFqyWjsdCiHaRtimLGe+uJcvhW1ck2+H0X1a+fK9azrb18i5XLz94uObJXxOewWIEBt7ud+mGmnJAV7l7RnPrvyDRZlocoKxevZrRo0czevRoAGbPns3o0aN55JFHALj//vu58847ufXWWznllFMoKysjLS0Nq/Vw8tF7773HkCFDmDRpEhdccAETJkzgH//4Ryu9pB7EaFU/dHoN1FQQboNHJtTWRlmtsSfmLjUlWrjafzNBzQC23mpdt0yWeoQQbcvt0Zm7cIvf/sF+y8rXlNcu7Ri8SzfOGnjwBxWITIterGqeJF7mbRboe1NdzZ7Yh6ndj6JL0XS96711LikpwW6343A4JB9F90DWd6qjcchgdB1uWKjx436NcQk6H4x+D8OBD1W5+5P/7m1H7qN8v1qX7X2xqrUihBBtYPnuAqa+vuKo531wy6mk9I+AvJ9VgBIy0Dt78tQvGvPXasRayvhuwO8IDQqFk15WjVWP5MwDPCqAsUgdk86gJX+/ZftGV+ft0xMKVfne2ii2AJ2VmRoflF2lpkariyDjHf/3COwNlZmy1COEaFMtKitfvg+K1qktxbXByeY8+Mev6pzH454n1FgBg+7wH5x4XCpHL+IkCU66KAlQugNrNESMhqp88NSQGAr3nqoCjXm/BJCZcJc6LysNHH568WgGtXVPlnqEEG2o2WXlA3XIV8U965Z2ajzwx8Uabl3jgog1nGtfCbGTIWyk/5tUHITgfpIY24VJgNJdhI2oTZg9CMCNI2FMnE6ZS+PhtUPRY2qr++54BTzVDa83BasicPkrZFePEKJNNLusfMguFWAEHq539cY62JinEWqq4tHY51VvscZqnrhqm89GnOJ/dkV0CRKgdBdGK0Seojoa15RhNMDTZ+uYDTqL92ks8Nyq8lAqD8L+j/zfw9ZLLfXkp6vcFiGEaEXNKis/ORKjY4PPrp09RfDcSnXGn2JfJ8ZUDANu9Z8zp+vq95z9BFXUUnRZEqB0J0FJ6oey4hDoOgMi4A9j1VLP3F9s5Pe+Q5134H9QltHwem8Bt41QurMdBy6E6CmaLCt/9TBSozapwKQ2+PDo8MBiVc7+9LDtXBmeBhFjIWq8/yeoylU5J5Fj/G87Fl1Glyh1L5qprsJsxX71Q2qN5fej4ctdOlvzNeZsGsvf+5wG+b/Ajpdh9DMNy+AHBIPBoZZ6rLGqWq0QQrQiv2Xl+4VhzF0CRZkQMth77tsbYFWWRlBADfPi/ooWYIOBt/kPPjwu1WMsbpKaMRZdmsygdDeWCAg/CaqLwePCZIRnztYxajpf7tJIM96pqsiW7YKDn/u/hy1ebc/LXwked7sOXwjRMzQoK1++W83eBh7utbPPAU8vV4HIH+PeoLc5D5KuB0uU/5tW7IeQJNUQUHR5EqB0R/ZhENwfKg4AMDzmcMfjh38OprDXbeqTfe+pnJMjaQaVcOvYBCVb22nQQogeq7pY7doxWLy1muqWdiprNE6172Fa+EK1hB1/fiP3cKhE/8ix6v9FlycBSndkNEPkyWr5xlUCwF1jdQZF6ORXajyy9UwIG6V28+x4xX9CrNGmaqvkr6gtdiSEEG3A4z78e8Z2uN3Je5tgxSENm7GGp+OexGA0waA7/Xdf193gzFRbjv1VlBVdkgQo3VVQHwgfqfr06G4sRnh2klrq+WKXgS8D7gGDVc2SZH3t/x7WWPWuJH+FWtsVQojWVrwJijerHTe1wceBEvjrL2pp5/64d+hjyYF+1/kEMD4qs9Sx8NHtNWrRDiRA6c7Cx6gf2krVfGtkLNx+kjr051/CyU+4RX2y5y2ozG54vaapXxol21VFRyGEaE2VOVCYrpLxjWpXj0eHe7/XKHdpnBK6jxsiPoXQIdDrIv/3cFeCx6nKLJj8tPIQXZYEKN2ZKVj90HqcUFMBwJ2n6AyJ1Cl0avx5+znooSNUx+MdLzWy1GNRCWkFq1XhJCGEaA3uKrWj0FUK1hjvw29tgJWZGoHGGp6NfxyDIQAG/aHhjsM6FQcgZIjq1yO6FQlQuruQgRA6FCoPgK5jNsKzk3UCDDpf7zbwhem+w0s9mV/5v4clEnQX5P1S27pcCCGOU9GvULrLp8vw7iLVDBDgoYQ36WvJhn7XNJ5X4sxTpfAjT/afmyK6NPkv2t1phtqpzzCoUsmuw6PhjpNVAbc//xJOTvyt6tyMt73LQQ0E9oHyvVCwShoKCiGOT/k+KFyj8txqd9zUeGD297UF2cJ3MS1sAQQPgN6X+L+HxwXVhRBxsupHJrodCVB6AkukKuBWXeRNdp15EgyP1imu0nhg8+R6Sz0v+1/q0YyqoWDROijd0b7jF0J0H65SyF2mdu/UK6b2f2thfY5GiMnF07GPoxlMMHhWE0s7+yGkv9p6LLolCVB6CvsJ6oe5Yj8AJiM8f46O2aizZL+B9zwP1Fvq+dL/PUzB6pz85VBV2I6DF0J0C3VbiisPqZ2GtbbkwwvpamlnbsJrxJsLIOlan3N8VBepmimR41RZBdEtSYDSUxjN6ofZYFE/3MDACHggRS3XPJluJyNmpjo34+3GE2JtCVCVr5LbZOuxEKIlHJuheKNaMq6dGXHWwOzvNFwejXMjN3Np6DcQOgx6/cb/PXQ3OLMhfBQE9mrHwYv2JgFKTxLYCyJGgzMHPDUA3DQKTuutU1mjMXv9RGrCTlIF3Lb9zXuOD02DwH7g2AaFv7br8IUQXVhlNhSsVEmtAYHeh59dobGtQCPSXMWTMfPQjBYYfFfTu3YC+0jNkx5AApSeJvxEVduktgy+QYNnJumEmHV+zdF4reL+w716Dnzs/x5GC1iioXAVlO1tt6ELIbootxPyloGrTCXG1lp2AP65Ti3tPN3rWaJNxdD/JtUPzB9XqUrSjxoHAbZ2GLjoSBKg9DRGq/rh1jRvGfxeITD3DLXU88LaQDZG3KvO3fcfKN3p/z6WCJVMm7fMex8hhGhA19Xuv7Ld6s1RLYcT7vleBSfXxP7CpJDlEHZi4712dA9UHlQVsuttTRbdlwQoPVFgH7V+W1sGH+DSwXBBsk6NR+Ou1SdTEXE24IFtz6uCSo3dpzIT8pZL12MhhH+lO6BwLdh6ebcU6zo8tEQju1wjKaiEh6OfA2NQba8dzf99Kg+pHLiIkxo/R3QrEqD0RJqmfshtvaDikPehJyfqxAXp7CnWeDx7JpgjoPIgnj3vsPwgLNgByw+Cu24XsmZQ74iKN0Hxho57PUKIzsmZr2ZZDRaVe1Lrsx3w5S4No6bzfPxcAg1VMHBG4/VMaspUblzkODCFtNPgRUeTAKWnCghSSz16jVoXBsJt8LdzdDR0PthmIc32ZwAMWQt59ft13PWtgamfGZjwjkba7tr7GG2qlkHBSimFL4Q4zF0FeT+pXYP1mvwdKIFHlqoZkLsSFnBi4HaIPhNizvB/H90D5QfAPgJCkttj5KKTkAClJwtOVu3JKw96i7Od1ht+P0YdvmfFAP6e81sAnkt8nnCjA4DsMpjxdb0gxRqtfhnl/qSS2IQQPZuuQ0F6bSn7JO+STI0H7vpWo7RaY4w9i9sj3lC9vgb+vvF7VWaCLRaiTpFy9j2M/NfuyTRN9bCwxfvMfswepzM8WqfcpfFczrVsq+xDjKmIp3q/DOjo1BZU+kk7vNwT1FfdI+8X/9uThRA9hzfvJMGbdwLwYrrG2myNEFMNL8b/iQBNh8F3Q0AjXYhrKtQOoKhTfZaIRM8gAUpPZwpRP/z1lnrMRvjdKLWrx4OR6zMep9oTwLn2FUyN+AYAHY2sMo30zNr7aEYVpDg2QtH6jnglQojOwJmn8k6MVp+gYvlBeGW1+vdfer9KojlX9dkJG+H/PrpHVb4OGy6dinsoCVDEEUs9ajeOsd53Rm5NJPceuAuARxJeJ9ly4PCxinr3MdrAHKXyUaQ+ihA9T03l4bwT6+FaJkWVcPd3GjoaV8auZkrIt2rpp9+1jd+rMgusMRA5VpZ2eij5ry6OWOpRu3piAn1P+dwxkbTiU7EZqngh8VlMmsvveVgiVZCT9zNUF7f50IUQnYTuUX12jsg70XW4f7HaUtw/uIRHo+eBwQxD7/VZ/vFRUw7uSjW7a7a344sQnYkEKELxLvW4wFXG2ASID9YBvfYEjbsO3EehK4QRgbu5L+4d4oN1xib4uVdgH1XWOu9ncFe344sQQnSY4k1Q9CsEJvoEHu9ugu8yNMwGDy/FP6K2FCffqs7zR/dA+X619CNLOz2aBCjisOBkVQq/8gBGzc2c0+vSYVWQUqVbmJbxJAC3Rn/Ky6es9lkK8tIMqtKjY6uqIKnrfk4SQnQbFQdVl3OT3SfhdVMePP6z+i1yf++PGW7bBVHjIe6cxu9VeQgCEyBKlnZ6OvmvLw7TNIg4Wb2zqThAajLMP18nvl6C/VZnf17Kuw6Ak0ueh6oC//cyWtQadOFqKNneDoMXQnQIV4kqMeB2qpyRWqXVcEeaRrVbY3LUbqbb/616eA2a2XglWFeZ6pIeOU527QgJUMQRTMFqqQeg2kFqMvx8vc77F3sYFqVmQhZU/pYK62D1i2nb37yJtQ2Y7SqTP+9nlfAmhOhePC7IXaZmUOr12dF1ePAHjb0OjV6BlTwb8yc0zQBD7ml8S7HuhsoDqg1HyIB2egGiM5MARTQU1A/Cx4AzEzw1GA1wWiK8e7Eqhb+72MDDBY+ha1a1rXj/fxu/ly0Bakpri7iVtdtLEEK0MV2H/HRwbKpNijV6D723Gb7YqRGg6bzU63HCAsqg79VgH9b4/SoOgq23msWVXjsCCVCEP5oGkSdBcBJU7PM+HGGDF8/VMWo6n+wO4sOAx9SBfR+AY3Pj9wtKgvJ9qjaCFHETonso2aaWcK3xakm31qY8eOwnFWA80OdTTrJtUGXq+/y28XtVO1RybPSpahZXCCRAEY0xWiHqNNXkq16eybhecF+KWuqZs24om6xXAR7Y+pxa8vFHM6pZmeKN6heaJM0K0bVVHFJLt0abzzZgn7yT6D3cHPoGmMLUluJ6Myw+PC41WxtxknozI0QtCVBE4wJ7qfooVXmqk2itW0fD5CSdarfGjK3TcJgGQnU+bHvO29OnAaMVrLGQv1KSZoXoyqoduLN/ZPkBDwsOxHs7nOs63Pd9Xd6Jk2ejH0LTNJV3Yg5v/H4V+yC4v5q1laUdUU9ARw9AdHJho1SCa+lOCB4ImoZBg+cm6Vz4HzhQauCe3Cd4PeI6tKJfYf/H0Pcq//cyh4G7QlWaNIWqrYRCiK7DXU3a8p+Yu9RGVsXhXTbxwTopvXTS9miYDDqv9Jqr8k76XK2SXhvjzANjIESPV29ihKhHZlBE04xmiEpR9Q2cOd6H7Va1Bdls0Pn+QBD/8PxVHdj3QdO9eGwJqkpk7lK17iyE6Bp0D2krfmLG15BV4fveNqsMPtmuZj8e6fsfRts2qvYZjb1ZAdUB3VWoStnb4hs/T/RYEqCIo7NGqyClplR1F601IgbmnKHySZ7eNJBfTDcAHtj2bOP1UUDlo1Qcgtwf1S8pIUSn5y5Yz9xFpbVlG49citEAjbHBW7g2+F2VdzLknsbzTnQdKvZC6NDGmwWKHk8CFNE89qHqHVHFPp+6J9ecAJcN1nHrGnduvoLMgFHgcqggpbH6KJpR7RAq2aaqTzaWtyKE6BxKd5O+eS1ZFSYaBieK3VjK2/3+rKq/Dr236bwTZxaYI9UbH4NkGgj/JEARzaMZIGoc2HpBxeFuxpoGT07UGRalU+DUuG3/HJxaqNp2nPHvxu9nMENgbyhcA4W/tsMLEEIck8ocyF1KbkUjsyGAATcf9b8fm6GKLcHXqTczjXGV1TYCTAFLRBsMWHQXEqCI5jOFqGQ2DKqdei2bCf7vAp0wi86GfDOPlPxN7SQ++Ank/dL4/QKC1buovGWys0eIzshVArlLoNpBTHjjwcRfev2dwbYDpDlSKIm+rPH7eWpqq8WeCKGDW324onuRAEW0THA/tR3QmeOz9TgxFF4+T8eg6XyUEcf7+h/VgR0vqs6kjbFEqiJPuT+qSpJCiM7BXaV+Lsv3Q3ASYxM04oN1NHzrGP0mbAlXR35LRlUCzxbexdheTWwVrtinlncjx8qWYnFUEqCIlgsfo979lO31Kbp2eh+471T1+aNbxrNGu1BN5W6Zp3buNMaWoJJvc5ZAVWHbjl0IcXQet5rZdGz1lrE3GmDO6XpteKL+t7/5IC8kPkeFx8Jtex/i3gmB/jucQ+2WYpvqZhwQ2E4vRHRlEqCIljOa1VKPJQIqM30O3TYGLkjWcXk0btvxe7K0gap9+vYXmk6GDeoHldkqSGkqmBFCtC1dh8JVUPSr6mxer4z92f1gQDiARpChgs8Gzsag6TyVdwd3n92H1ORG7umuhOpC1aVY6h+JZpIARRwbSyREnwYep0+Je02DZybpDInUyas0cOvBeTj1IChYCQeaaCqoGSA4Gcp2Q86P4K5u/FwhRNsp3gj5K8ASAwFBPoce+0ljV5FGsMnDZwP/SKixgqzQKTxy+ZmNBye6R/XiChshW4pFi0iAIo5dyCCIGKNmSDwu78NBZnj9Qp1wq87GAiv3Fb+gVoL2vgcFqxq/nyFATSc7NtU2FvS/Tdnt0Vm+u4AF6w6xfHcBbo/09hGiVZTuVj12AkJU5ed63t8E727S0NB5sd8rDLTsgbCRxI/6XePLOgAV+1UhtugUMDS+E0iII8kGdHHsNE0luznzoXwvhAz0HkoMVZVmr10ACw/EM8T6J2banlT1UUY/q6aO/TFa1LGitRBgU1PC9ZLp0jZlMXfhFrIcTu9j8XYrc6YMI3W4VKMU4phVZqkdO2hgjfE59MtBeORH9XN4d99FTLJ9S7kxhi32+xmjGzE2lu9aVaDqHsWcrtpbCNECMoMijo/RqvJRTKHqF1w9p/aCubWVZp/deSrf1Vyh1qI3PQGu0sbvGRAEllg1zVyvbH7apixmvLvWJzgByHY4mfHuWtI2ZR15JyFEc1QVQPYi9XNp6+VzKKMYZnytUePROCtqN3eGvkCFx8IVWx/mtwvDmPCORtpuP/d0O1UT0cixENS3XV6G6F4kQBHHzxar8lFqyhsEHtOGw3UjdHQ0Zu28ga3uMaqK5NanG680C6qFe0BobY2UHbg9OnMXbsHfYk7dY3MXbpHlHiFaylWighNnTu2OncPTIY4qmP6FhqNKY2CIg/lx96FpcN+BWWx19gcgu0wFMD5Biu5Rs6qhJ6iaJ0IcAwlQROsIHVKbj3LQJx8F4JEJqtNpuUtj+t4/k+uOg+L1sOdNQLVqX34QFuzA27odUD2ADAGQs4T0rVsazJzUpwNZDifpGbJNWYhmqymH7MW1tU6SVbJ63SEP3JGmsadYIy7QxRsJd2M1VPNq7hV86Tjde55eW/p+7k/a4Z/div2qfEDMeCllL46ZBCiiddSVwg8ZAOUZPvVRTEaVj9I/TCez3MTNWc9T6bHAoc/ZuOFbJryjMfUzA3d9a2DqZwbfKWNbAniqyT3YRIfkenJLGw9ihBD1uKvUjrnSHRDcv0Fjv8d/0vjpgIYtwMNriXNItOTyreNUnsm+vsGtdDSyyjTSM6mXdzJB8k7EcZEARbQeoxWiT1dNwo6ojxJmhTcuUjt7NhSGcHf+83h0jSFF8+mnb/A5t8GUcWAfYsxN5KzUExNibdGQZUeQ6JE8NZD7s9oxF9QfDCafw2+sh7c3qpmR5/v/kxMtG9hSmcSsA/egN/FnI7e0GqryVXK75J2I4yQBimhd1miIngCeKqh2+BzqFwb/uEDHbNBJy+7DjP0PY9LczO87j/6Ww2XuG0wZaxpj+8cRH+hqUGa7jobazTM2qfnNx9I2ZTHhqcVMfX0Fd324jqmvr2DCU4sl2VZ0b3VVYot+hcA+PoXYANJ2q9kTgD/2/55U6+dUG8OYvvcRKjy2Jm8dY8yG8JGSdyJaRasHKI8++iiapvl8DBkyxHvc6XQyc+ZMIiMjCQ4O5vLLLycnJ6e1hyE6UshAiDhZJcO6q3wOnZIAT09SQcY3jnH8NesGwgLKeKPfXMKNhwManyljwGg0MOcM9UvzyCClLqVvzpRhGA3N6+8hO4JEj6R71O64glVqt84RJed/zYZZ32noaEzrs5XfB70Amgnj8D+BJaqJNwg68YEuxiZFq119Uu9EtII2mUE54YQTyMrK8n78/PPP3mN33303Cxcu5OOPP2bp0qVkZmZy2WVNdL8UXY+mQeQpYB+qMvmPKHF/yWBITVaPvZZ3BR8VTqafJYvX+v4Fs+abYJtbcfjfqQMMzD+vhrjAGp9z4uxW5l87ptl1UGRHkOiRdF0FJgUrVeE0U7DP4f0OuPlLDWeNxlmxucy1P6A29Ay+C6N9MHNOVz8PDd8gqM/npJRijDujQfVZIY5Vm6RXBwQEEBcX1+Bxh8PBv/71L95//33OPvtsAN58802GDh3KihUrOPXUU9tiOKIjGM0qH6XaocpcByf5HL5+OLU5JhoPHPwDvc05nBa8kXm9X+KeA7OpmxeJOaKnWOpAI+ckuUjfk0EufYnpPYaxAxKaPXMCkJ5R2OwdQSnJkc2+rxDHyu3RSc8oJLfUSUyIWqpsyff0Uek6FP4Keb+AJapB8mqxE25cqFFQqXFCeDmvRN1BgOaBvtdAzBkApCarZPe5P2lklR2+Ni5IZ87YbFLHTgBbw9/7QhyrNglQdu7cSUJCAlarlZSUFObNm0efPn1Ys2YNLpeLyZMne88dMmQIffr0Yfny5Y0GKFVVVVRVHV4qKCkp8Xue6GTMdvXLLfNLcOb6VKcc10v9YssuBx0DN2Q8xtcD7+Dy8B84WB3HCznXEBcMY/30FTMGmEgZEA9lWyHIAJ4IMDS9Nl5fc3f6yI4g0R7apTpy0QbI/1klsJvDfQ45a9TMyZ5ijYQgF28kzCLIWAGxk6HPVT7npibDOUk66Zk6uRUQY6thbMhOjDEpqtSAEK2o1Zd4xo0bx1tvvUVaWhrz588nIyOD008/ndLSUrKzszGbzYSFhflcExsbS3Z2dqP3nDdvHna73fuRmNhImXTR+QQlQtRp4HKA6/DbLqMBHj2jbqpYx6WbuGTX38ivsXNX7AdcHfENc07XG+/xYTCr3QeOLaoDsrv5wURzd/q0dEeQEC3VLrlQRRsgdykYg1WTz3pqPHDHNxqrszRCzB7e7PcIscYsCDsRBt7uU7StjtEAKb3h4oEeUuy7MYYNVdVi/ZwrxPFo9QDl/PPP57e//S0jR47kvPPO46uvvqK4uJiPPvromO/54IMP4nA4vB8HDhxoxRGLNhc2vLaI2wGfIm6pyfDa+bp3GafME8SFO16k3G3lyd6vkhrWRGNBULsPgpLAsRFyljZIyG3M2KQI4u1WGvt1eiw7goRoqXbJhSrepAL4gGC1w67+c+jwpyUa32domI06/xrwPIONG9X24GF/PHqBtfK9Kpcl5vQGO4GEaA1tvs04LCyMQYMGsWvXLuLi4qiurqa4uNjnnJycHL85K3UsFguhoaE+H6IL0QwQdarqfly+xydpNjUZlt+o89wkD0EmnZyaKG7LehaXx6DK4ZfsaPredUFK8fpmz6QYDRpzpgxTQztyqLX/35IdQUIci5bkQh2T4s2Q84NKWj0iOAH420qN/2zRMGg6Lw96h7EBP4A5EobPabC7p4HKbFX3KPbMBl2PhWgtbR6glJWVsXv3buLj4znppJMwmUwsWrTIe3z79u3s37+flJSUth6K6Eh1v8yscSpptv4hA1w+FP59sU6gSeenwn7MznkCt9sFmx9rUPTN771bGKSkDo9n/rVjiLP7LuO0dEeQEMeqTXOhijdDzmIwBjboTAzwzgZ4ebUKwJ8Y9BXnmT5W5w5/RCXRNsVVAu5yVe8osHfLxyZEM7V6kuy9997LlClT6Nu3L5mZmcyZMwej0cjUqVOx2+1Mnz6d2bNnExERQWhoKHfeeScpKSmyg6cnMIdDzJmQ+ZV6B3ZExv+YOPi/83V+9wV8mTecUMMf+UvMX9A2Pgqj/gqWJpZcvEHKBjV3HXeWeqwJqcPjOWdYXNvunhCiEW2WC1W3rGO0+Q1OFmyHOT+q7/G7k1dwjWU+aCY44eEGu+0acFepNwxRKWAf1rJxCdFCrT6DcvDgQaZOncrgwYO58soriYyMZMWKFURHqynG559/nosuuojLL7+cM844g7i4OD755JPWHoborIIS1Tsvd3mDSrMAp/eBF87V0dD5IOc0nsmfAc5s2DTHJ8nWL6O1NnF2I2T/ADWVRx2O0aCRkhzJxSf2IiU5UoIT0W5aPRdK16FwnWr+Z7SBNbbBKd/ugdnfq0Js1/Xdxh8CnwAMMPQelSvW5P3dqs+WfZgkxYp2oem63uWqUZWUlGC323E4HJKP0hXpuqrHkP8LBPXzO9PxwWZ48AcVPz/U+wNujXhPbWMc8dhRZ0ZwV6lcF/sJEDtRCkeJTqtuFw/gkyxb96e/2cuN3jonP0FAiN+ck2UH4KaFGtUejcsSD/Bs2O0YNF3t1olPPfr9y3apJZ2E88EU0rwXKMQRWvL3W3rxiPanaRA1FuzD1TsyT02DU6aeAPenqGTavxycyr+LLoWSbbDlrz47gfwyWmpnUjZD9vfgal6jQSHaW6vkQukeVSE2dymY7H6DkzVZcMtXKjg5r1cuT4fdoYKTvtccPTgBqDiglmhjJ0pwItpNmxRqE+KoDCa1PdFdrmY7ggeo3T71zBgDZdU6r67R+POB6VhwciVfw/YXYMjsBu3hfRgt6p4lO1QAFDdJdhuITum4cqE8bihcdbhC7BFF2AA258FNX2hUuDROjy3ipfDbCNDckHBRg0Jsfjnz1JuK2DP95rQI0VYkQBEdxxQMMRNV0qyfcviaBvedquOsgTfWazxw4HYsWhUXU7vGPnBm0+vgBpMKUsp2Q9a3KkixSOl60fnU5UK1iMelApOC1SrfxGxvcMq2fLh2gUZJlcZJUWX8X/RtWAzVEDsJkm8+eh6JqwRqHBBzNgT3b9n4hDhOssQjOpY1CmLPUjMelQ2rCWsa/HmCzrThOjoasw/czdeO8ZD9Lex+Xa2NN8UQACEDoPwAZKb5fQ4huhy3U+3UKUgHW4Lf4GRnIUxboFHk1BgZUcEbcbcRaChXlZ0H3dFgxtLvc1Rmqs7k4SPa5nUI0QQJUETHC0pU24/dlVBd1OCwpsHjZ+pcMUTHrWvcuf8BvnOMg8wvIOOtowcpmlEFKVW5kJUG5fvb5nUI0R5qyiF7ERT9CoF9GnQlBthVBFM/U83/hkc4+Xev27EbilWwMeSeppdHQc3OlGdA2AhVZPFowYwQbUC+60TnEDpY/SJ05qlfwEcwaPDU2Tq/GahToxu4ff+fSHOkwMFPYd8HR7+/ZoCgZJUwm/k1lGxvgxchRBurdkDWN6oHVVB/vxVfdxfB1E818is0hkU4ebf37di1fLCPgKEPqKXPpuhulRcWMkA1+zza+UK0EQlQROegaRBxEkSepHYM+OmrYzTA385RQYpLN3DH/gf52nEa7P8Q9jej15OmqW3NAFnfqZoRXW+XveipKnNUvlbpHghO9tv/Zk8RXPOZRl6FxpDwKt7rfQdh5Kot+if86eg9c3S9tsdOL4g9++gl74VoQxKgiM7DYFTr4/bh6h2cn+3EAbVByiWD1EzKHfv/yBfFE2Dvu80LUkCt2RsDVZ+SgpV+tzkL0amU7YWsr1UOVcgAv7MaOwrgyk81cso1BodV8V7vOwknWwUnwx9tXrBRcQBMoSovTHa9iQ4mu3hE52I0Q+wZ4KlU7xRDBjRYLw8wwHOTdQwafLLdwF0H7setG7iYd1VNiL5XH/15rNFgMEPez6pCbfR4CLC10YsS4hjpOpRshdwf1Zbi4GS/O28258F1CzQKnRrDIqp4t/edRJAJIYObH5w4c9RSaOxZDdpQCNERJEARnU9AkJpedldBWYbfX8pGAzwzSQUp/91m4O4D91KlW7iS92uDlKlH30Jptqt3okVroaZMFaGSd42is/C4oXAN5C9XM35Bvfyetj4HrvtcbSUeFeXk7YQ7CCNbdQ8f8WjzgpOqQpX7FTf56P14hGgnEqCIzskcpuqWZH4NFfsO547UYzTA05N0TAb4YIuB+w/eRanbxnQ+BDzQd9rRg5SAQFUrpXSX2kUUOxFs0slYdLCaSlXjpGidmu3zU4ANYHUW3Pi5RplL46ToCt5MuJ1QPR9CBtYGJ81o8+AqgeoCtZNOGgCKTkRyUETnZY1R080GC1Qc9HuKQYO/nKVzy4kq2fXxrFt5Kedq9H0fNW8LMqhZlJABaoo78yso2SnJs6LjVBepnTpFa1Tvm0aCkyX7VBG2MpfGqbFlvBP/exWchA5VPasCGm4/bqCmHJxZEDkOIkZLA0DRqUiAIjq3oD4QdzagN1pkTdPgofE6s8ep3j1/y7mWv2T9Dv3Ap7Brvto2eTSaUW3bdFerWZuCdEmeFe2v/AAc+lI15gse0OjyzOc74OYvNZw1GmfGO3gz9maCKIKwkc2fOXE7VVJs+EkQNU5qnYhOR5Z4ROcXMgA81ZD1PVQV+C1Xr2nwh1MgyOTh8Z8NvJ5/GcXuEObxMgE1lTD4LlVVtimapt6xVheprrAuR23yrHRDFm1M94Bjq0radldB8MBGA4Z/b4RHlmroaPymbz7Pht6GGacqwjb0gaNvJYZ6hdhGqu/xo/1sCNEB5LtSdA32YeoXd84S9Yu7kWnvG0dCTrmH13/V+LjoHApqwnhF/yuB7goYen/zfnmbw8FoVev/Lodam5cmaaKtuJ2QvxIK16plmUaSVHUdXl4Nf1upApfrk/fzaOCdGDQ3RKXAkHubV1TN41I5V/Yh6nvbaG7NVyNEq5E5PdF1hJ8I0adBVZ5K7DtC2m6Y8I7GP341oKPW0heXnsI1e+ZRmLsdNj0GNRXNey6jTb2LLT8AhxaCY5vkpYjWV1WgekQVrFQN/xrZ3lvjgT8v1bzByV2DtzA38HYVnMScpYLv5gQnuhvK9kDogNpCbLK1XnReEqCIrkPTIPIUiByrEvtcZd5DabthxtcaWWVHXqSzrmIQl+9+lgN5ObD+QbWlsjkMASoPwFOjevjk/aTe7QrRGkp3w6Ev1P8HDwBTiN/TKlzw+6803t2koaHz6LDl3G25X+Wz9r5ELV8epbeO2wPLD3pYsCGX5Y4k3DGT/PbwEaIz0XS9670tLCkpwW6343A4CA0N7ejhiPbmqYG8ZVCwCgJ74zYEMeGduuDE3y4EHdCIDijiX/3mMjK8RCUSBvZu/nO6SlRn15CBED1BdWEW4li4q1V9k8LVKrCw9W5090xeBUz/QmNDrobFqPPiCV+Qyv+pg0k3QuJlR326tN0w90eNrPLDzxFvtzJnyjBSh8uWetG+WvL3W2ZQRNdjCFCJfRGqb0/6gSqyyjT8Byd4H8+rCefKPU/xTW5/WPcAlGxr/nOaQlXBuLI9cOhz1Wyw68X2oqM581XJ+ryfwRQGgYmNBie7iuDSj1VwEm7VeX/EP2uDEwMM+kOzg5MZX2tkHdF/M9vhZMa7a0nblHX8r0mINiIBiuiaDAEQMwHCR5NbXNCsS4ZG6jg9Fm7b9xD/yJqMvv5htfbf7Oc0qan4uq3IuUv9dl4WogHdo/KYDn0OJbsguH+TVYt/PgCX/VfjYKlG31A3nwx5nJM8C1R7hhMeVBVfj8LtUTMnKoz2DYLqQuu5C7fg9kigLTonCVBE12UwQcwZxMT0bdbpfxqvc90IHR0Df8mazkMHbsW16Sk4+FnzZ0M0DQJ7gSVW1Uo59IVKpBWiMa4yyFmq8pg8LrVMaGh858y/N8INtaXrR0c7+V/SLJI86WrGZdQ8VVStGdIz9dplHf8zNDqQ5XCSntHMnCwh2plsMxZdm9HM2BMnEv/NIrLLdO/unfo0dOKCIaU3jE/USQrTefwnjQ8KU9lbFc/f3U8RUXEIBvy++fUgTMEQMAjK96kgJeIktctItmyKOrquao3krYDKg2BLbDIx1eWGx37W+PdG9T18ab8C5tnvxKqXqKWg4Y+onT7NfO7cwlzg6DkmuaWS+C06J5lBEV2e0WRlzm9GAmqXQ311n885XcdoUBMgvxsFr1+oE2TSWV4+iik7n2dzxg7YNFc1DWwuzaim6o02tdyT+QVUZLbiKxNdVk2lyjM5+AVUF6rGfU0EJ8VOuHGhCk40dO4ftoW/hdykghP7CBj1VIuCE8r3EBPajCaBQEyItXn3FaKdSYAiuoXUkYnMv2YkccG+MyhxwTD/fJ3UZN/zJyfBp1fo9LPrHHLFcvmuZ/l8rx1+vR8qDrXsyS2RKoG2fJ/KMchPV0XlRM+j67XfBwtVF2JLJAT1bXIb8OY8mPKRxrKDGoEBOv934hfcHnA/muZRtUpGPNr8LcG6B8r3gDmcsaMnEm+3Npk6Hm+3MjYpooUvUoj2IduMRbfidlWRvm4JubkZxIRFMTbRgrGJMNzhhD98q7F0v/o1/vvo/3Jfr/8RMOxuVTq8paoKVCG54GTV3ySw1zG+EtHluEpVNdjiDSpQCUw86pLhJ9vgwR80qtwafULcvJb8IsM8iwED9L8Jev2m+Q38dA+U7VZVj+Mmgy2OtE1ZzHh3LUf+kq+74/xrx8hWY9GuWvL3W3JQRLdiNFlIGXMW5Bqh6Ffw9AZD4+8+7VZ44yKdZ1bAa2s1/i/vCtZXDOKlqmeIGXghJP62ZR1eLZFqS3LFfjiYrXqdRIyWfj7dme6B0p2qLk9lJth6qe+BJlS74YmfNd6pzTeZ2KucF2Puw+7eD8YgGHqvymtq9hjctcFJHMSf49OawR5oorjC5XN6WKCJeZeNkOBEdGqyxCO6H6MZYs9UVWcrD/kti+9zugH+eJrOK+d5CDLprCgfyYU7X2T5pvWw9SlwV7bs+Q0mNYMSEAL5v8CBT2vrpniO40WJTsmZB1nfwaGv1AxKyOCjBieHSuHqTw8HJ38Yuos3Iq9TwYmtF4x+puXBSekusCVAQqo3OKmbPTkyOAEo8vOYEJ2NLPGI7stTA/krVK0TS0yTdSfq7CqC27/W2FGoYcDNPXHvMqPPCgwnPABBfVo+Bt0NlVngcULIEIgYA7ZmJjuKzqumAoo31jaULFXLOQFHT0r9dg/ct0jDUaURYtZ5YdjnTPK8rg5GjIUhs1TDwObyuFTxwKA+auaktomm26Mz4anFZDn879DRgDi7lZ8fOBujoQUzhEIcJ1niEQJqK86epmY08n9RwYIlsslLBoTDZ7/VeXgJfLLdyDPZN5BefgJPlz3GocipVEVOYmwCTea1+NCMqqS+uxJKtkLFXrUrI3zkUd9pi07I44ayXVCwWs3OWWIgNOGol1W54a+/aLy5XgUDo6KqebnPPPrUrAIM0G8aJF6uOnU3l7tKJcSGDIDYSWC2ew+lZxQ2GpyAbw2UlOSmfyaE6CiyxCO6N82glnqizwCXA5y5R70k0ATPTdZ56mwPJoPO0tKTuXDHczgOLGP/6peZ9O8q0nY3fr1qzAYLdqj/d3tQW5FDBqr8gvxf4MAnULhedvt0FboO5fsh80s49KVaNgwZdNSAF2BvMVzx38PByc2DDvJxrxtVcGKyw4i50Oe3LQxOKlVwYh8G8ef5BCfQ/NomUgNFdGYygyK6P82gllYMZtWRuOLgURsFahrYLeDyAOjk14Rz095HuTHyc16KeZB7F88C+jTYvpy2G+b+pNX2BlLig3XmnF671dkcrv4oOXMh+zso3aYKvAX3VzM9ovOpzIai9SqPCA8E9gGj5aiX6Tq8v1klw1bWaIRZdJ4btpBJ7n+oKYzQITD0frC0sPFkTZn6Hg4/EWLOAGPDOibNrW0iNVBEZyYBiugZNA3CR0CADXKWQFkGBPVrdIeO26MCjdqLvY+/VfAbVpSP4KneL7F4/Vmc0+8CjEZ1vK4x25FJXdll6nFvPRbNALY49e67MktVog3qq/7gBCWBofGaGaIdOfPBsRkcW1TOSWCvZu/Gyi2HBxZr/LBPfW+kxFXyXPzjJLg3ABokXgF9pza/cnGd6mJw5kDk2MPLl36MTYog3m4l2+Fs8P0Ih3NQpAaK6MxkiUf0LCED1E4Hs13lEuhuv6elZ+K3Q7KGh23OJH67+2mM7hIKVj8J1UXegMZ/Yzb1+dyfNLXcU8dgUsmNQf1UoHJwoapGW7ZH5TqIjuHMU71zDvxXbR0OCIHQQc0OTtJ2Q+oHKjgxG3UeHrGR92KmqeDEHAEjHoOk61oenDjzoLpANcmMntDkjJvRoDFnyjCgYSeeus/nTBkmCbKiU5MZFNHzBPaGhAsge5HanulneSW3wv+lOgZAp4YAXsiZxneOXTxb9gxa70vIKju10afU0cgqUw3cUo5cXTKYVZDiroKyvVC6R82ohI2A4H6y9NMedF0tu5VsU8nMrjJVWt7W/EJ7+RXw6E8aX+xUf/SHRrh4od/fGVzzvToh4mQYdFeDfJFmja3yEKCryrJhI5pVmyd1eDzzrx3D3IVbfBJm4+xW5kwZJjVQRKcn24xFz1XtUD10SrZBYF+fbaLLD8LUz5qeYDTgxoMRk+bijpj/EGfK5y9Z03G4Qxq95sVzPVw86CjjcleBM0ttIQ3sDWHD1dJPgK0lr040h+7BXXaA9K1byC3IIcZSwdg+IRitYc2/hQ6f7YC5P2oUV2kYNZ1bB2Uwy/onLHopGCyqKmz8+S0r+lc7PsozwBQCMRMhJPmolxzJ7dFJzygkt9RJTIha1pGZE9FRZJuxEM1htkP8uWAMhOJ1YIn11koZm6CSW7PLaLRDclSggZExbr7fa+L5nGtJthzgqd4v8r+iyXxX4n82JaY5/duMFjWj4nGBMxsOfQ3WKAgdqv5ANWPniDgKtxPK95O2dgtzf4SsChMQDRyR1HwUh0rh4SWHc02GRrh4OukNRrgWHk6EHTxLFVFrqboaJ7Z4iDtb/f8xMBo02UosuiSZQRHCUwOFqyF/pQpWbHHA4aRX8A1S6jJN5p+vc15/WLgTHvvRQ75TxftXhn/LibbtPJtzPYVuu/eauGD4+Xq9+TVU6uhuqMqH6iL1Tjo4WeVE2BLAYJJ3yM2l6+rrWJYBJVtJ2+5kxtJeDfKG6v/3bSxIqXbDP9fBy6vUDh2zQeeuIdu41TwXk6cMtABV26T3JU02CmxUTQVU7KutcXKWtwCbEF1dS/5+S4AiBKg/Xo4tkPezWmIJ6gua4ejbhms5nHDnNx5+PKCClAijgztiPmSrsx//K5qMjqHJP3jNVu2Aqly1E8gSTVp2P+b+UEFWSfXh8XWiHINOETzVVKgO1aU7VC2TmjLcxjAmfBRPVjk0TCNtOqBcdgD+vFRjT7G6bmxsJX9JeIkB7p/UCaFDYOAdx1Z5GFQg6sxVu7qix8vSnuhWJEAR4liV74fcH9XSSlASGMy4PWpXT26FWqJpqpLs31fDq6tclLtVnYwTrLu4NupbEoekMmFIv2Makt/np5q07WXMWBTpZwZA6ehOtWmbshokaLZb8OSuVnk8ZXtVE72qIrV92xIDppBm5RgBfHCJx5vUfLAE/rr8cBJslE3noUE/can+HBpuVYwv6QaIT21Z0bX6KjNVgBx1qurHI1vORTcjAYoQx6O6CHJ/UsmztkQwtaA3CuB0wZPLdD7Z6qbcbQbgIvuPPDj6IL2GTGlRZ+PGZnD+PEHn8Z/VziD/MwAQF2rm5wcmYWzxmtLxq2tUd+QvlzYNntxOVVSt4pDK3ajKB3S1tdcc5rPUsmAH3PXt0b8uL57r4ex+8OpqjX+th2q3hkHTuS75ELODn8TuOaBOjBwHA37f8qJrdXQ3lO9VfXhizlBVh1uaUCtEFyABihDHy+1UOSmFa8AUBtboFt8ivwKeW+bkw+02dDTMWjU3xnzLjJMthPebeNTcBN/Cb745Ev7qrfjzwcUuUob0UzMH1uh22bJ8LI3qjmkpSPeowmVV+aqyavle9TmoPkfmiEZfb3NnUH43ysOCHRoFlWosp8ZV8nD8Pxju/k6dYI2D5Omq0d+xBhQ1FVCxXy0rxpx+zMmwQnQFEqAI0Rp0DxRthILl9fJSWj7lvikPHvuhjPRc9b0aYijjtl6Luem0vgRGj/B7jdsDE95pfIZEbRE5+h/EF8/M4+K++arWijlMbVu2xqqdQJbINglYlu8uYOrrK4563ge3nEpKcmTzl4J0j+qBU12ocjTK90FVofoDbzCqQNJkb1YBtLqvb2O7tEDHqIFbV8f622t4sN9XTPb8E03zqK9n4m8h8VL172NVVaACrPCREHVai2frhOhqJEARojVVHFRLPhUHVZBibHnSoq7Dkr1unvqpgm0lamdPdEAhM/quYOqpg7CF9/c5v7nv8I/mvYs9jE9EBViuEvWh16g/qqZQsMWqWQCzvfYPfGjLK5weYcG6Q9z14bqjnvfi1SdiCTA0vRT0234qsbgqXy3d1JRATbmKz0zBarzGoGOavWhsl1b94C/c6mFWcjrXBDyHSa9Uh6PGQ//fHdOs2uGn8EDFATXuyFNVQqzkm4geQOqgCNGaAntDr4sg7xco3lg7+9CyXANNg7OSjJzZL4TPt5bz3HI3ByojeGz3Bby6r4hb+v7AtacNIsiuKpc2Vsn2mBktYIw+/Ee1LmAp3QXFm9UAjTa1zdoSDuYoMIeqnAhjoNpJYrCC8eizBc1tQBcVZOLejzf47RWjQgSduV/u5JzLd2E0GNVYAuxgjfcmobo9kH6oeQnMR0pNVluJH/1RI7u8/hENW4DO7QO2cJPlWYL1vNqaJsOg/41ql87xcDvVcpQtXpWsD+53fPcTopuSAEWI5jCFQNxksERDwUqVhHkMSz4GDS4ZZuOCwfDfDUW8ukbjoDOcebsn8dreEm7qt5xrx/UlJvAYCnv5kV/ZyIG6gKW2OBm6R/3hrCmHikwo3Q11oYNmUoGJwayCFFNIbTBjUZ10Dabar4PqXTQ2AuJDjGSXuhtpVKcTF6xD1vdklTRe9l1HI6vCRHrp4IbtAWhG5+ijqHJDkROs9X4LWo06Nydv4xbb37DrWepLEJgISdcfX56J90nzVT8d+3DV7K+lZe+F6EFkiUeIlio/AHnLVGLjMezyqc/lhs825vPqGiMZlarap0Wr4rL4Lewsj2SNI7HRHIlmJcnW2yZ7THQddBd4qtXWXU917ec1KqjB3XA4OqTtD2bGkl61nx65fALTTyjDZtJ4Zd3Rv3b+2gM0lUAMTRdZK6yED7fAW+s1civUtXaLzg19t3Kj7UUi9EPqRGsc9LlSFUo7lmJr9elulTNjNEPEOJVzcpxLaUJ0RZKDIkRbqymH/HQoXq9mFWwJx/XuusYDX27I5vV1sKns8OzJCNtOXB4j26qSqPtDXPdH2G5VBeIaK8V/zJVrW4m/GQ6DpuPRW/Z1OjLIOloCcWOvfWMuvL1B4/OdarswQHyQm+mJ6Uw1v0oQRepEaxz0uQpiJx5/YALgKoXK2vyl6PFqyVCIHkpyUIRoawFBEHsm/9/evUdFdZ1/A//ODMwMCDPcGZCLiIoXFDWGKeTNpZFErU207bLG2tZam4vFNAmu/KJdv0g1q9WqK6a1rmjXm2jfZd8mmpVqbVL9aarmNRLwWiNeMQgiN4Fwvwwz53n/2DA4MjMwOAzn4PNZa5bOmX0O+7AZ5mFfno3AWKAmD2i+JjYc1PRv/kWvy6mBeVNNeDYNKPi6HP/7VAuO1CTjq7axAMSE2mj/Olxvi0NYkA65j4ogZfm/VF3Ljnv3IuQ+OnTBCSDmeDyVRCgoJxwuBt7/jwpSrz+Hug+4DjTS7xntKiiHQ9DT+4o9O0dPjgI+KQI+KFThXFXPOZPD27Ak+t94Vv0etOquLLyB8UD8D4Cox70TmJAkJlaTVeRJCZ/hUQ4cxh50HKAwNlAqNWBIEfNSar4Uid38gsUy3gH2pqhUgDnZBHMycLOqCv+noAoflyXjjjUMd6xhUEPC+IBbsLQFIislDO/Ooa5eip5rmILQ73kYg02jFgFGzpHu78e93xcVRJDiOGTlLsjq7wTi3/w/FYq/ASySuK6/mjB3ZDl+avwA01RHe5ooJE3smRM63XvJ0awtYpVOQAwQkQEEjebEa4x5iId4GPMGyQY0XgZqC0SejsCEAS1Hdqa9rRmHzl/B/71mQH5TzwqSQHUHno6rw3cnhULnr0Vdu+crWXxhIEum3U129fR6OlUHnjKewX/Hvg+TX6U4qPIXK2ji5ongwVtIEunqpQ7AOBmISBeTihljAHiIhzHfU2uAkFQxF6UmH2i8JJbF6k0D35eliz4gCPMyZmDet2y4UXwW+wqbsL9iHEotMdhXGoN9pUCwXzueGNmCrHEGNHdqYNR56b68oL89HitmSBgb1neQlR4rAhjXSewANSRMCijC8siPMMd40t550ew3EkEJs4HoJ70fOHQ2Am23xc9A+EyxE/F9tj1jDzIOUBjzJl0YEPO02Mm27rTYQTdgpMOHoSebDzpQaZA8eipWjgZy2mtx/ur/YP81Nf5Z+xBqrKE4UKLHgRLAT2VDelQLHhkViEcS1EiNFHNchkpUYP/KPRIHtyuOiICyJuB4KRAZCIdhLUAEJWN1pVgQdhg/Dv8UenUnAKDFpsehxgzsqXsKJapUnPiWl3uYJOtdSdfMYpM/zgjL2H3jIR7GBoulAag7K5K7AUBgHA4W+99X7o5eiCA1XMb5oms4fNMPR75Jw/WORIciwf6dMMdKMMf5Y2o0kBoJBAz+ljx2faWVd7XqRiKgqA7ILwdOlatwqqL35FiduhMpuq/xXNghfD/0qD0osZIanzdNx776b+Nwgxlt1DN5+b6XXncj6sprUgOMGAVEmMXQHs81YcwlXmbMmFwQiXwptQU4WFiL5cfjBpS7o39fywY0XMLNmxdwvJTwRf1YfNkyGY02x7/mNSrC+DAb0kwajA8njAsHxoUBYd6ZMuO0h+hwsfO08t33/s5ThDFhwOUa4OIdFQrvAJdqgJZOxw97PxVhamgNngg+iye0BzFRXwS1SlyjE1oca5iG/2k047NGM+pszpOgOcur4jFrs0i9rw0BQqcBIZMGvIKLsQeJYgKUbdu2YdOmTaisrERaWhq2bt2K9PT0Ps/jAIUpja2zHf9r41FUNNngSe6OASMJaC6GrfY0CksrcLI6FGdbx+N86zhUW8OdnhIRIGF0qApxwUCcAYgLJsQGAxEBIngJ0QPaPlbfOst9YhpB+K8MQmMH8MdTKtS197ym1RBG+APftDvvddBrbJhurED6iItI9/8CUwMvIVDd0VNAFwGETAXCH0Z+6zQs/Eff40n31YMidYqlwwBgnAiETRfDeoyxflHEJNkPP/wQOTk52L59O8xmM9555x3MmjULV69eRVRU1FBVi7FBUVDagoomCa4mdd6du8Mrww8qNRCcDE1wMqaMAqZ0NgINF0H1H6GiugznawJxoW0Mrrcn4lpHAm5ZTKhpU6OmDSjouUivywb5E4J1gF4D6PxEmvjuoKWmFfi6vndVKluAnCPOoy6LTQVLVzLaEP8OjBtRjdSA60j1u4DUgGsYrSuDn0rqOcHfCBini6XBoVO79uUR9ZwhieGyvoaS7s2r0i9kA9oqxPLhoFFA2IyurQ54OIexwTJkPShmsxkPP/ww/vSnPwEAJElCfHw8Xn75ZaxatcqhbEdHBzo6ev5qamxsRHx8PPegMMXo9w6/3hh+6I/OZqDpqtgssPkGWhpuoagxECWWGJRZolBmiUaZJQrlnZH4xmrAN7ZgSLi/5GV6VQfiAhoQ7f8Nov3uIEZTgSTtLSTpyjFadxuhfk2OJ2gCRPK04BTAME5s0qeLchsUuNqheMDDaCQBHXcAyzdidU7YdLE6R+3DSTyMDSOy70GxWCw4c+YMVq9ebT+mVquRlZWFvLy8XuXXr1+PtWvX+rKKjHlVf3f4jQqwwidvS/8gsdok7CEAwAgAaZYGpLXeEmnZW8uAtnzRa9BRC8nWgUbbCNRajWiRAtBOOnRI/miXtOggLdQgqFUS/FQ2aCDBX9WJYE0rgjUtCFaLf7snsDpSi2Ea/Six03JAnOiZGJEgEuB5uEy3e4fi+05eZ58AWyt2rzZliQDJz0sTdRhjfRqSAKWmpgY2mw3R0dEOx6Ojo3HlypVe5VevXo2cnBz78+4eFMaUIj0pDDFGPSob2l3s8AuYgiSkB38NtOiBAJPYPdiXtEbxCEl1PE4Eta0VIR21COmoBayNYqjD2gLYWgFrC0rqbSi4TVCrbPCDGJK53RllD2A6JC0abCPwnQkGTI83AH4GMcFUF+6dtPJ3uTvFvsdLuUkCOmq7ApMwIOoxwDgB8OeeWsZ8TRF5UHQ6HXQ6GWWeYsxDGrUKuc9MxPLdZ+3J3bt1D0TkPjsNmvixQMNXYudblZ8YVtAM8c++SiX2kPEbIXo2nCgvA17P7zsCmBkuAT6YU6pRu8+p0gvZ7gpMwsV+PMbxHJgwNoSGJECJiIiARqNBVVWVw/GqqiqYTKahqBJjg252agze/fF0rD1wCRUN7fbjJqMeuc9MxOzUGHEgeAzQchOovwC0lIpjumhZJ//qzu46KBNUB5PUCbRXiWXD+kgg6gkOTBiTiSEJULRaLR566CF89tlnmD9/PgAxSfazzz7DihUrhqJKjPnE7NQYPDXRhILiOlQ3tSMqWI/0pDBo1Hd9qKv9RJAyIknkUGm4JAKWtttivoY2VHYp1DVqMcdDzrsrO7C2AO3VYqfhgBgg6lGxJ49fP9PeMsYG3ZAN8eTk5GDJkiWYMWMG0tPT8c4776ClpQVLly4dqiox5hMatQoZyc5zkThQa4CgJJGltL1arLhpuiLS5/sFiWBFRsnBvDZBdbCQDeioE5s5agLEcmHDBPEvr8phTHaGLEBZuHAh7ty5gzVr1qCyshJTp07FwYMHe02cZeyBp1IBAdHiETpF9KY0XBErbCSLmDOhDfX6ZNOBuK8JqoOls0msyJE6AV0oEJkpekv00ZzHhDEZ41T3jCmRZAPaK4Hmr4Gm6yJPBzRi5Ym/UXZDQD5naxOTXq3NorcpcCQQPE5M8uVhHMaGjOzzoDDG7pNaAwSOhE0fi4L60aiur0SU3x2ka8qg6bguVgBpw8RkTxn0rAw6IjGvpPMb8a9GD+hNorckME58L7i3hDFF4QCFMYU6eLGi14qgGEMicrOmYXbcHZFsrflr8eHtbxA5TjTDKNGY1Al0NoqHZBHLoPXRQHCyCE70UdyTxJiCcYDCmAIdvFiB5bvP9kr6VtlowfKPK/Huj6dj9vjHxBLa1nIxb6W9GrC1ix4V/2DAL1gELErpWZAsXb0kTWIIR+0nAi9DiuglCTBxTwljwwgHKIwpjE0irD1wyWlGWoJI/Lb2wCU8NfFJaIKSxEog6VsiCVlHrQhaWm51TRxtEydpArqSsQUCav3Qf8hLFsDaKgIRawsAG6DyF7lgRowEAhNF3hKZrWRijHkPByiMKUxBcZ3DsM69CEBFQzsKiut6ljOrNWLIQx8lUrdLNrHc1lIvHu0VXcHLHUDqgD3UUetEAKD2F6n31Voxv+V+AxiyAZJVfC1bhwhIpA6AOgFSia/nFyh6egwpIhjRhooHBySMPRA4QGFMYaqbXAcn/S6n1ogPfX1kzzGbRcznsDaLR2djV/r3eoAsgKVFBBJkFeW7u2uI7prroUJP8n4Se9vc9bSniEYEOt1Bjz6qKwAxiqEn/2AxfKOkISjGmFdxgMKYwvR7Z+R+lrPTaAFNBIAIx+NEXT0d7T0PqVP0dkidImCRrCIYAYneETFuJOaJqP0AqLv+r3V8aALEQ/0ArDRijHmEAxTGFKZfOyMbRQp9r1CpxLAKD60wxnyI1+AxpjDdOyMDcLItn+i7eHPuRMf9fRhjTGE4QGFMgbp3RjYZnfdqvPXJJRy8WOHjWjHGmPdwgMKYQs1OjcGbcyc4fa2yoR3Ld5/lIIUxplgcoDCmUDaJ8NYnl52+1j03Ze2BS7BJ8t5uyyYR8m7UYv/528i7USv7+jLGfIMnyTKmUAPKhyIzTtP1G/XIfWYiZqfGDGHNGGNDjXtQGFMor+RDGULd6frvDbJ4eIoxBnCAwphiDVo+FB/oK10/oIzhKcbY4OEAhTGF6s6H4moxsQpiuMRr+VC8yJPhKcbYg4kDFMYUyl0+lO7nuc/IMx+K0oenGGODjwMUxhTMVT4Uk1GPd388XbYTTZU8PMUY8w1excOYws1OjcFTE00oKK5DdVM7ooLFsI4ce066+TxdP2NMcThAYWwY0KhVsl1K7Ez38NTy3WfFhsh3vSb34SnGmG/wEA9jbEgodXiKMeYb3IPCGBsyShyeYoz5BgcojLEhpbThKcaYb/AQD2OMMcZkhwMUxhhjjMkOByiMMcYYkx0OUBhjjDEmOxygMMYYY0x2OEBhjDHGmOxwgMIYY4wx2eEAhTHGGGOywwEKY4wxxmRHkZlkicTWYo2NjUNcE8YYY4z1V/fndvfnuDuKDFCampoAAPHx8UNcE8YYY4x5qqmpCUaj0W0ZFfUnjJEZSZJQXl6O4OBgqFTe3VSssbER8fHxuHXrFgwGg1evLQd8f8o33O+R70/5hvs9Dvf7AwbvHokITU1NiI2NhVrtfpaJIntQ1Go14uLiBvVrGAyGYfuDB/D9DQfD/R75/pRvuN/jcL8/YHDusa+ek248SZYxxhhjssMBCmOMMcZkhwOUe+h0OuTm5kKn0w11VQYF35/yDfd75PtTvuF+j8P9/gB53KMiJ8kyxhhjbHjjHhTGGGOMyQ4HKIwxxhiTHQ5QGGOMMSY7HKAwxhhjTHY4QGGMMcaY7DxwAcpvf/tbZGZmIjAwECEhIU7LlJaWYu7cuQgMDERUVBRef/11WK1Wt9etq6vD4sWLYTAYEBISgmXLlqG5uXkQ7sAzx44dg0qlcvo4deqUy/OeeOKJXuVfeuklH9a8/0aNGtWrrhs2bHB7Tnt7O7KzsxEeHo6goCD84Ac/QFVVlY9q3H83b97EsmXLkJSUhICAACQnJyM3NxcWi8XteXJvv23btmHUqFHQ6/Uwm80oKChwW37v3r0YP3489Ho9Jk+ejE8//dRHNfXc+vXr8fDDDyM4OBhRUVGYP38+rl696vacXbt29WovvV7voxp75je/+U2vuo4fP97tOUpqP2e/T1QqFbKzs52WV0Lbff7553jmmWcQGxsLlUqFffv2ObxORFizZg1iYmIQEBCArKwsXL9+vc/revo+9tQDF6BYLBYsWLAAy5cvd/q6zWbD3LlzYbFYcPLkSfzlL3/Brl27sGbNGrfXXbx4MQoLC3H48GH885//xOeff44XXnhhMG7BI5mZmaioqHB4/OIXv0BSUhJmzJjh9tznn3/e4byNGzf6qNaeW7dunUNdX375ZbflX3vtNRw4cAB79+7F8ePHUV5eju9///s+qm3/XblyBZIkYceOHSgsLMSWLVuwfft2/PrXv+7zXLm234cffoicnBzk5ubi7NmzSEtLw6xZs1BdXe20/MmTJ7Fo0SIsW7YM586dw/z58zF//nxcvHjRxzXvn+PHjyM7OxtffvklDh8+jM7OTjz99NNoaWlxe57BYHBor5KSEh/V2HOTJk1yqOuJEydcllVa+506dcrh3g4fPgwAWLBggctz5N52LS0tSEtLw7Zt25y+vnHjRvzxj3/E9u3bkZ+fjxEjRmDWrFlob293eU1P38cDQg+onTt3ktFo7HX8008/JbVaTZWVlfZj7777LhkMBuro6HB6rUuXLhEAOnXqlP3Yv/71L1KpVHT79m2v1/1+WCwWioyMpHXr1rkt9/jjj9Mrr7zim0rdp8TERNqyZUu/y9fX15O/vz/t3bvXfuzy5csEgPLy8gahht61ceNGSkpKcltGzu2Xnp5O2dnZ9uc2m41iY2Np/fr1Tsv/8Ic/pLlz5zocM5vN9OKLLw5qPb2lurqaANDx48ddlnH1+0iOcnNzKS0trd/lld5+r7zyCiUnJ5MkSU5fV1LbEREBoL///e/255Ikkclkok2bNtmP1dfXk06no7/97W8ur+Pp+3ggHrgelL7k5eVh8uTJiI6Oth+bNWsWGhsbUVhY6PKckJAQhx6JrKwsqNVq5OfnD3qdPfGPf/wDtbW1WLp0aZ9l//rXvyIiIgKpqalYvXo1WltbfVDDgdmwYQPCw8Mxbdo0bNq0ye2Q3JkzZ9DZ2YmsrCz7sfHjxyMhIQF5eXm+qO59aWhoQFhYWJ/l5Nh+FosFZ86ccfjeq9VqZGVlufze5+XlOZQHxHtSCW0FiPYC0GebNTc3IzExEfHx8Zg3b57L3zdycP36dcTGxmL06NFYvHgxSktLXZZVcvtZLBbs3r0bP//5z6FSqVyWU1Lb3au4uBiVlZUObWQ0GmE2m1220UDexwOhyN2MB1NlZaVDcALA/ryystLlOVFRUQ7H/Pz8EBYW5vKcofLee+9h1qxZfe4G/aMf/QiJiYmIjY3FhQsX8MYbb+Dq1av4+OOPfVTT/vvVr36F6dOnIywsDCdPnsTq1atRUVGBt99+22n5yspKaLXaXnOQoqOjZdde9yoqKsLWrVuxefNmt+Xk2n41NTWw2WxO32NXrlxxeo6r96Tc2woAJEnCq6++ikceeQSpqakuy6WkpOD999/HlClT0NDQgM2bNyMzMxOFhYWDvnO7p8xmM3bt2oWUlBRUVFRg7dq1ePTRR3Hx4kUEBwf3Kq/k9tu3bx/q6+vxs5/9zGUZJbWdM93t4EkbDeR9PBDDIkBZtWoVfv/737stc/ny5T4ncinJQO65rKwMhw4dwp49e/q8/t3zZyZPnoyYmBjMnDkTN27cQHJy8sAr3k+e3F9OTo792JQpU6DVavHiiy9i/fr1st0rYyDtd/v2bcyePRsLFizA888/7/bcoW4/JmRnZ+PixYtu52gAQEZGBjIyMuzPMzMzMWHCBOzYsQNvvfXWYFfTI3PmzLH/f8qUKTCbzUhMTMSePXuwbNmyIayZ97333nuYM2cOYmNjXZZRUtspzbAIUFauXOk2wgWA0aNH9+taJpOp10zk7tUdJpPJ5Tn3TgyyWq2oq6tzec79Gsg979y5E+Hh4Xj22Wc9/npmsxmA+AveFx9w99OmZrMZVqsVN2/eREpKSq/XTSYTLBYL6uvrHXpRqqqqBq297uXp/ZWXl+Pb3/42MjMz8ec//9njr+fr9nMlIiICGo2m14opd997k8nkUXm5WLFihX3CvKd/Sfv7+2PatGkoKioapNp5T0hICMaNG+eyrkptv5KSEhw5csTjXkcltR3Q87lWVVWFmJgY+/GqqipMnTrV6TkDeR8PiNdmsyhMX5Nkq6qq7Md27NhBBoOB2tvbnV6re5Ls6dOn7ccOHTokq0mykiRRUlISrVy5ckDnnzhxggDQf/7zHy/XzPt2795NarWa6urqnL7ePUn2o48+sh+7cuWKbCfJlpWV0dixY+m5554jq9U6oGvIqf3S09NpxYoV9uc2m41GjhzpdpLsd7/7XYdjGRkZsp1kKUkSZWdnU2xsLF27dm1A17BarZSSkkKvvfaal2vnfU1NTRQaGkp/+MMfnL6utPbrlpubSyaTiTo7Oz06T+5tBxeTZDdv3mw/1tDQ0K9Jsp68jwdUV69dSSFKSkro3LlztHbtWgoKCqJz587RuXPnqKmpiYjED1dqaio9/fTTdP78eTp48CBFRkbS6tWr7dfIz8+nlJQUKisrsx+bPXs2TZs2jfLz8+nEiRM0duxYWrRokc/vz5UjR44QALp8+XKv18rKyiglJYXy8/OJiKioqIjWrVtHp0+fpuLiYtq/fz+NHj2aHnvsMV9Xu08nT56kLVu20Pnz5+nGjRu0e/duioyMpJ/+9Kf2MvfeHxHRSy+9RAkJCfTvf/+bTp8+TRkZGZSRkTEUt+BWWVkZjRkzhmbOnEllZWVUUVFhf9xdRknt98EHH5BOp6Ndu3bRpUuX6IUXXqCQkBD7yrmf/OQntGrVKnv5L774gvz8/Gjz5s10+fJlys3NJX9/f/rqq6+G6hbcWr58ORmNRjp27JhDe7W2ttrL3HuPa9eupUOHDtGNGzfozJkz9Nxzz5Fer6fCwsKhuAW3Vq5cSceOHaPi4mL64osvKCsriyIiIqi6upqIlN9+ROLDNiEhgd54441erymx7ZqamuyfdQDo7bffpnPnzlFJSQkREW3YsIFCQkJo//79dOHCBZo3bx4lJSVRW1ub/RpPPvkkbd261f68r/exNzxwAcqSJUsIQK/H0aNH7WVu3rxJc+bMoYCAAIqIiKCVK1c6RNFHjx4lAFRcXGw/VltbS4sWLaKgoCAyGAy0dOlSe9AjB4sWLaLMzEynrxUXFzt8D0pLS+mxxx6jsLAw0ul0NGbMGHr99depoaHBhzXunzNnzpDZbCaj0Uh6vZ4mTJhAv/vd7xx6u+69PyKitrY2+uUvf0mhoaEUGBhI3/ve9xw+9OVi586dTn9e7+78VGL7bd26lRISEkir1VJ6ejp9+eWX9tcef/xxWrJkiUP5PXv20Lhx40ir1dKkSZPok08+8XGN+89Ve+3cudNe5t57fPXVV+3fj+joaPrOd75DZ8+e9X3l+2HhwoUUExNDWq2WRo4cSQsXLqSioiL760pvPyLRAw6Arl692us1JbZd92fWvY/u+5Akid58802Kjo4mnU5HM2fO7HXviYmJlJub63DM3fvYG1RERN4bMGKMMcYYu3+cB4UxxhhjssMBCmOMMcZkhwMUxhhjjMkOByiMMcYYkx0OUBhjjDEmOxygMMYYY0x2OEBhjDHGmOxwgMIYY4wx2eEAhTHGGGOywwEKY4wxxmSHAxTGGGOMyc7/B3iY7rhBYHxbAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "state_after_three_more_cycles = load_state(\"result.pkl\")\n", - "plot_results(state_after_three_more_cycles)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can continue to run for as long as we like, e.g. another 10 cycles:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "!cp \"result.pkl\" \"result-10.pkl\"\n", - "for i in range(10):\n", - " !python -m autora.workflow lib.experimentalist --in-path \"result-10.pkl\" --out-path \"result-10.pkl\"\n", - " !python -m autora.workflow lib.experiment_runner --in-path \"result-10.pkl\" --out-path \"result-10.pkl\"\n", - " !python -m autora.workflow lib.theorist --in-path \"result-10.pkl\" --out-path \"result-10.pkl\"\n", - "\n", - "state_after_ten_more_cycles = load_state(\"result-10.pkl\")\n", - "\n", - "plot_results(state_after_ten_more_cycles)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/docs/cli/basic-usage/Readme_files/Readme_19_1.png b/docs/cli/basic-usage/Readme_files/Readme_19_1.png new file mode 100644 index 0000000000000000000000000000000000000000..b725bff142472cc49beaf13535b1ab40bc6a1291 GIT binary patch literal 40985 zcmZ_0byU^O7d3tXDWwD?q?PWHZk6svT1vV*1*HXqOLt2PJal)1fOL0v_dEA_zQ5mE z?;o#AmVlSJ^O-rb&))l-Aw*GL0{!{x=MV@4T}twUG6Vuo3xU9;p&)_pG`rl|fq!_N zK59Ct*qS=I8akLjvUB8PVX^-IU%+hZ zV8%kHyWtB4LA8_Aa)dxI4PhT}zl8J6A&~SysSl#6ZYlcGV{Xsc`c3C1#m9 zm2UK2EQ{BV%k?ZHqpEg37ue$MVU-*IK$ieJ-%5=@q6J?< zcbzyzl)xvd`Pp!xuov)=pew>&IkEG_FAIE9ATNP{3w}V_neTN5Eo`vylf7*?V${f< z_tMhOGcz*@0!K$X{vCrOAy3NCkRl``M3Yf&@Mi+kaqrv6gcuqHuJ>YMg9!-)XM-Fg zoUZ%RE6#%_J!H1`aCG1OqA=?=a`riCr6cD2>Y zR=V$H{Zo=>!vIr_s;_QUAZ*nN4tIj# zp?hU5X)G=G(Ix|NqYbV{;*qIb)~_L+m-~i)GDJIjdMZ6GEXs_=#>e4;BO|ZefB5-9 z;Njsvaf**~7X13vdf-yCEih53S)zV_fA7>#4+4;#>A9lp_)igvzObi~vVLG^6=KH`vNJ!Y(-3|Zy%jlc-_I3hZ2jdq(N80Z0yafdXdUY() z?v2F5LIIOJP&-y#vZ+vgB_|GvmkoEQW7>({UQ3k~tEi|#=x z3WBk}e$jGS&vp)RFAduFkn~KK8^I-Tm|?t?h**!7VO|NLNh4=s`q6OIoV-`sP})^V z+3Y4j8XX<|`%?)eHTCMzQQ1*MtU{i-vYwti2qP&eDKtX%oSk-2aO`G3hE)@CpNl=s zT9(;^=yW_@7G-X}{#U=6!p<0zz!_u;J)(R^Dm36|S`D@>3k6mYAI#YrL)t zVWi+CfsfBnSp4g`ymco&DQW2}{T3g+3k|4+q?8mYG6u0hs~_C-!DR$#1XxOKrWw=u zRjRb^^PTaaT$y+-_f(&U+mnka{hD>{nuKN?^`Ts027m%L+xn*eo&<3Ef4#lD-7CW( zC0!itIQ~q4l@=4mq$yHh6G;sCp{@{t0B)25!r0! zdDM$FSDc4I1j;Wpd!s&oz6#cknxDTxYh({R;?`GWQiHYb9|VD44GAWe=2+46d~Qs9 z?&g-TiHQgGpKdkMWh7t^cfnlIU5XqP8{0KwmM*8Li1j`YZRKo4*mja97CZ~7;9C(k zxnHz4Pmy?Bq0Jj{+M3N?yy?D=ykU4utNH0ZpC4{7^m^_OY<-R9YwhpB;>|mb2o`JC zM1VokU$8Vr4JC6sK0RE4?_Rkz8E}Imx6ox>v(O!gPDH@xM0>V1lAo0Y@26IzZa<-> zVgGP3RcY9PBrkCCfz;=E#Z>po{{{2%q_(Ze-(N~Od3n)EN&SfUI*Je14_8YgVA4aI zL&tD<1i=8w3(zW&d#KG;By-_f|VLerV=c~sYZ#^>&0+SC@6=u&8~t*NVzYjYi!Awfu8C@j2u@va1wot?d~ML|tJmmZ+Wm(dF% zX!A0o) zjkI{xjFsM&-#-{%ES=M1x;~pvx)CYgx%&ykU%J7j%Y;iKs--RwnHBVmHgI%5H!gzR zZdt^Ni^y`aIMa5i8M3~$RcSfJ905=pX@rRF^Rt0?maBT(o6`+65cA1dbanKE4Jri<%rwFbW>D?2 z{|n9X&xkCI$M7so=gJpsG^tM5u&=;c0mOFfA#weiZ1Sc52lry{U?RuO+|pxrqFGvB z&63Yt@qG+EIKeb@bRpL~bs69&NNClbuUPdG8kFZ;$6=_KMs%(kz3Y+fKkB;?(u0g~9bai!|?@ol}r+I`HmDU$#2aQ`h z=cg0qLis)q%St|CS-o7A4f+*=HD?#v_VY`nO?RR70|1Hr>GA*&w9)D5BLSE~D6L=x zXWHJvmgC?RmFP#*XBR&qxdA)a3N$Ke!Pb}iGhlbmz|y=VAz2vhuo(NLl#POldUA6D z$b{?pF@W87-MUDK{Cpn|rCz0q?tGw@O=zum-sAHikXQ#GX=BG=r=z38A1MxaU>KD6 zTZJqN>GbH^f;_lTi&p@{_O>Yi^W($LLq%+$WSbmwZ->`ig)u&liV7=QAqZUgX;l%* z^J-T&CftA7V?kOm4=R0VD;~YR**%Kq6DrZs?jJ+*e+lJ<>LGjY5?r<2%`7Lyg?1gu zyOOr?*?@oPsH%dR16Dsfd4@yHmlb(hDWndhlS+Q4FaI%5!Jp>ROR2Mc3$H0*aPBOoXERA^G#6^75@ergQPCeLPq(R7`o*##RB zx6OJdjshhoC-nDkR%*GV&eCOFC zJKC8F20iYPH(TnXg_~-=-jtOZPp%37wv(|)_E{2sx*730AC+hXt5dAslGYZ040{F# z2ZzGQx`)d-cW{C=D^1ba*w|9+y9p<#Hp>86>+kQ^thORd=C<7ge3pii@|j;_qkuf$ z4kawQ!K}2vP2r1(DG=oz`K{op>nx-tXk*$C1hjD4^)U;AfeW$hX@KU``{OH1?I z?N`F>)O!IY``hK<6CR6Rc-Lnb>FQoPf&2z!71I3l=&7uta&x^F8F_t!Fz-C2D{%2w zrC7HCPgq#E6b!uEgU6^T0`OQ1%y)0HWR1o5<^@;sLGYt6zzJ=3xtS89@(IeGJa3xx z>_|B6HQm6uA2Wy>TU*I~iRtP3N9AK<%8ql@)~4p>J1=$bl85L_pZJ?O?_fOa=45CS znoZKI@bTlvydhJLC4knucYt9Hb#{I@1MHL4_x?lzhjq#GsA;#Sva)ihwN>N{5CLwv zan7D_LZe0Brw5_3r$6s86CF1PPwJ1B+XAQ!4(IE}IpxL$9e#a~yez&HqfaI2)BMIq#rJGucG;A?RCmOnsK0@W%8iFOiG$1d$sy zuOXKDGbyV6NyWnaxQ2;-I%z5)df$hih0K>cA8p1i7g0sQGUCA9Iz9 za##%akolhPvI}@!AMYONnvCU0>8+ifovq!Ujg%cq0xTRfOZV>fM|@EjIn(6H4M>OC za_iS`-@lKx`1(SkV`8))ZV>cvm3d_uhp71=~08A`KA-QoAQoK2v{6t>!&y>$ni{<;xj}s!!@0Om@yzegU z`>5i7yPug-E2Iqqridw`r1a7(#U6=>%j)=c8cYb}S)Ge_{s94dx~_o7G3qrYgomRE zJ)En+BOoMl+v;7c!CueH%iDOnTU7k1DiknCxM<@!JPVc?g4hrpwE?NCC0}9f8k>!O z#^u+7$b1aedw+TX&SuSy0m!=py>#wnh_CUGx7q+dYU*3w>QE%wDq~zO;uPXOdnUFo ze=>IGBk2LVdS^Mw>agCsd#7Hiqvg%d%^k1X;KKH~GkEt72^-rVDjF z?+Y~uwR}qNWQq0;Ao>Bwn3uQ5ub_Wj2HAT4N^4J8#-xzB@#56~UE%NzB3rEh6yf^N>X z0KmQm!8rgJ&%i4UozXALiW^yB%&V~)dWNG}AN2x2@gHC}@0vDB# z&?9VQxKa`x81lL_e)aJh_12oNDzfDrmL-qnmjH}`*F%O85^$_Jz+{`G+V+E zK*`y9jDkn%-qu#n($k~s<4L41Y&gJd+&f2F*wl++_xG)s0i}fP=gn672wi?kI|8P_ zpJLcvYBR{i9CWG08ZG3G)e(?qn$Gw*KTkQ95?-9$-t`lmWR8C<=HCg$HTVO<~EeW%~%DuuThiMclVBGP(-g7flLH-0$dFPp6s zJd3`-Pq(0}7ix_irEMX=`6%sELqTk?cwPyY!welkJu3`|d2s(tE43J{@2u0q9BEnL zNw)bzewq92npP_Gy?AEKw4&Bz`6oUFmr9uFX4Qq9Ay8v_nPZ2Ed+@Wr{Dek>?DCcx z0Ve%*y1D+BLkQ;DLoA*(>Y@n&!v39F**eNNEab*l74ds&&bl1mH>11=UJv47mqIrV6r^ z>JIz!yZz-$```b*3D_3lZb_ZzwUGFa@HuOIms;*ePR>5v(^X7)7Fbg6P;B1b!Y!HM z(06UH|2323-6xj+z4^}uwCB}dnHuwY6#i#R zI!gd$AX}!jX#YxVQ^BDDOrXUlc6lSkka~2~d)5<*J_gA}=KG(okmP+2GXvb*+>(Dt z0FukVAxAq;C&L@pANpoT*e{>hA6aDD4uY}X;VN}{9NTkVG7~tD>Xi2LU&GUxXFPKo zGR<&zm_RD|AZ|mGqTIB8mX3}@I=+0pXo7YioD+bwm;4`tbyca=NP@dX9GG%X&cO?P zhqW3J-;i?L=Hh;xwDa;^j|(=;0ij8;gXf;NL*QO;!U2HL+0}Idutymr9snAmU%t=+ zY}^EHVu6s^&RDK&Dqk$H$ADRKJ)r+62J-*K8qgLx9y__f#fplGY6bR`+R&`{#s5>W7dLjM2^xqk!_=>lM^RU*_$xW4LDO9jc3Da2}TiyKor10K!&;Q zTXZxw2AR+xFlJyfak|$2EpYwVpFk>fzg`I{Dsu&BS?RQ+40G0+?+*EaY1IxSMN{(@ zuwq6+Uop4=(FQUz4zLkP0lP4|I$V%=uq^{~PJMM0R6%?k8C5n=L17s?FE8-%uuv`G zAW2F+JY#qYrAFd>mCm`2(EX_9;L*EAkSCt}DeeI$l88G3$TlKBkVayF?h6NO2Id4q z4x6s@U{(*z#lzS45=|HKc3b(557fg-M^H?3bUTUbd|T7iq6~1%{(S)8Zt&a~n-oAZH$YrH@F$L&v_kjzC)32*@ zJuNLlC8b$LB^bksejja#t$8E-);_pvQJw({pWAsbFD^lgB zo8MS)r7?R4-IAo5**1b`CZRPrpov-8Y%1(5>_i(Cod-j@Si|vHs+nmd{whh)J{e9eh-B@<6F>1J9#d-)b7GA-qjZGN3aNf|t`6 zp3FdIMnrSG2)*>)yfBuSk?ip zoww^ihso#>p}X+A!-hz0n>xg>E-^_-6b)VHS0Fj_3*R3jz})TA0hS)+BAJapneVlJ z8^FPgM>5}gHek*c>op}wka~~5vAAU0rOHFLFjV;I}$u?-ELt~VT=`An%AimY(v+=IZ)8i zH-L3VB`mzO$5+;L`5IIBp0#GtgCPi$jGB)x3Ftw`+nxNHD;1C#oGIz0GYt5zB_`+N zZ>zi_QdCKTRX5U7X3P8*n`m6Xs?Z0zQ+gWmYl@1(VFU%--+KY;yOGq9FBMP~HlTI) zT|AM0C^}Q!f^4^YdRo)AQbys#N}x_RR(&dMhu^V%NA7?f^nCgH>2%|V=au3M&+BKZY-xOibm#X8s;0&VvB{p_@-By~6he!PsTVG#a zip#7yFmPXjS0B_Y9jZO3!fFvisveT3a)qZ-vN*~Njwm<^h#g|hIE!=CuDTr6SYk-d zgPPhIAL07Pa%Jic>-RM49H@Z(+P>kyW;RS58WvU*S$DIUe6t$Hat+89tYQTIq&N=q zPDK8%9t0#5tR4i@h;D#z)dA+BeWV3@Z^4gk@~F~<)p+<;0jmfGCqX=PV>gp{wDyE( zk+f^InfCAGp7EFCQS~wF)c)Dqo6`49ou1YN^tJ~S2qb)bg#JYl0Bk%vIWZ8aR$^e| zF=&(;17_?6Xf3Qx1ze;wP%8p1#K?P0!A=+g0sR!&(&D=($p3HNE?WGg!>}w_kRli& z2xmpX!?0ZSBbxXwXmp0akVe&&<8Uy79y!;7Thchk7`;rp1|xo;Yk#J)D3VafiwCF) z6Hq^b6l<3I1InhV@d5GwSwz}B*|lL}9{9@W-b8i62@zU^)5=9^@@L?&)+B#+b&%0k z4J!+gMg}F@)Q14$l-=X}3uJ6;36p1hh$)_st9K&f}!q4Ee)g z1SqJZL;%<07}$ALn{Hn9pd{8eGE(*ks{jV{sK#lp{-n2%CXP}^mcW4o2!=O~1K*o*|>B~*VM07berz|vwoQ(>Z)YQMI& zM#sWJ!@@FRiAN)I13ag+~4SDGKOClimlw;>_LYjV;Ud6^ABQ_hVzdUE3)PxFrwtW+Iyr z(*IrFl2#tc`WS}t;)M|qZY3uvg$SvI6!msGN6r z0nASzeeFBYxmk_6(ef11FE5o=j^*k@X~GZ>;=XvrqmyTn{m1TgTj@A7lUb5ut-w>pQ*b=QEfkdW}N8H>%O zljc>lBJSWo!olpQ#zWtOs;OGw>cPPZMZYx}Q#=prps}%Rz#`HE1ZdZ&M4dt3=Y|TT zU?yNglLMcAfVm+YsJG+ov=B`7A~k(409?*2CW(N3!c|q{X$+-(AVYvtvKsKGLPlc@ z?0ffCxy@eLnR~4?s|&ba<#Pv(*Q;T$4|LM;GJWCZ$J@O)FH3M5rQvY*<46QVWBEVn zB1V;~+R#YHOleH2aUl{b%0F!zpzJKcAqeu#h5?od-KE$0u2_ozpJjO{^ME0X{|znh z_X_1!N4)2Hrf|6A*FTx>oR#ab{&P%Av+T-njm`kqk>k!$FO@v!BS8!BeY99+Lyy=~ zY1<}+MtJ2MBYSr`piq=iP1fxF2ub2#HW@RL?sBPZlteI=w zUbz2zz5go0vTT4~LeiabbJPf`W83GoiyufPHUTI0q|hsIp+l z&R72fgJ}zwHC(E`@KD3=-&ANBgSfc|-cLpJb^Pve>I2#4Kf<1>YyKSf0NJxd&xLML zJ8WqN{`&?}z#Cbgm?-K>8gJSBkV3W{3iJk`cYoGW|rlZ@Q+oZ)p$>aI&^qX zSSWW;D>`u$2{RI?i64pm z)|XYTjcb17tM~2q#jXiV(>?2v{Qb|b7`gnv7wKPN>W$=veo(y@6a!Q?%k3{m@}m#p z?$Bki_djCyKEvE@6|Esn6@}U6eA%lAib=a_2~5uUgK1uIt^zZM$GdlO%W+hOjIuL?e|FLS_ih6Rz8Eati`Tt`_wYjOi;OhU9i#EogM##uhfBn>&P-p+IIlGr?X^nb6F z#&~bf{;XSLDYkmg@*WMd1^0(ZL#59T9Grl^@c2bB4zrFq*5dyyTqWH!b82YG*VC#w zDcQCf$UV*8pt!;ityA^I_U!ln)Qs8cpkI5_qRGLyZ|4%@XJ0LNVO&|8^YiIHrP_pjcaE<|uD(=7`Nt73~zod%{KP@8vYrGADq}_BPA9+P8(rh)SNI_8+Zhw8xEsRGo z=LwKKcX2zIr!XUdk|J4R8Fi=ZpK)fNo_U*vcUrJ{k&aJ%@l)2Y$2Mk!i!1`gA0P(u z>E;nP>XfOf`!f|b9NTp~K0c#Z3BHm~bqh+3XG!aA97R2NH^!C!eRh{!j<&$cl7uTK zTLLKi!u(&f1&o$tsNx%plB0UPOK6(pCr)}gZ?4k02$)HgWW_~M%OA|xou`*=I2@Hf zBH-%lxK}(0I4R0q2*ENi)2o93P!b{3aa^M46QnT3^OXL4?Gfqa-eDZGa*4Yw{0tj; z>KW%kaP#f$=W8j%mgoQyL2TGb`r3o&p4|2tEl}-{VIXkO#G&CTv9WfzwbNi&BxdF3 z2K(9(!3CXZ1SUDH3%&?L^W1Ei+2#8rLeZpCFa_^6ekaL$}R^u}W;;W$n}qB-Xv z#92dfW#bWd4lC_K2mT{PHP#JW-_q#lTM&>Fsjx&^p83mt*WH}&Op1 zd(q09-wtn{6jbEs)=gi0|I^l7Hud9+-x%%_ZST_a()I{an8k8P?aN;~(8`jt+5Dbt z03^1?^P<$}k!^#E)G;`I6=*1g&)}3u*yk^E;G|XHvy4OXMa-07qU?86a6PZnX!xQJkvl^9tgKy|Z2`AMY=!&}z{8ULLpEXY!gL?G=Q*4HjnzvfKZ#av8O#|2As6@-J&1amPohq(cJ-C z#a81N+n#V4pqj3f(=ZX|8k6DUhy(Z4AUPlIBQUG`7JQQ|{PW@GH)6lfcy!CSj=04Q znN+=Z$1r9p;|TkV*rHf)y2X4{djdlO(&w(C?rG->1rFC7t>1d-8XKGNnIqf&`4F?y z6g3~y%7b#a#I|+-0UqGwmJZ53ljq1dzNfHhWbAhJ7yX`aU`VT8DJn50vsiE=GL8gr zx-UqD2}EAi^uwkhO~I`J$0Hu_F2ksM9u6GXp;crA=9sx4q1dMFiO8AO*R*xCX`vW| zXNEqr*ZIA%M$J^sCe5P%nT!_Kw;xfr zG=iYO=d6W5VH!6tbY1RRDH0}Z5SxaY2cjQVczwYz|035MXjQa(V z#yt}Uw|_7mO#4$fNd}?UWqS)@MdfnUqrGw#d8AWVW`QNJ#88J$mC z#SMI8|123=OB80!z`*H{3d0gH|2T#5?|te6Lr#&CE*64S-?ueImpK~cNbsb+bGw2K zu>QDrc|54n%8h0U?7lFN=?_Cz=-gmSnCLP7#FArJVtByzeFik$ICiraP--U&>eYkCoAdoQwlN~LpL>5UnYU8f`6B_L{QeN3;4<(qQAq;~ z^aNTCT0tl{y{IH;D{Bx1XKa;s+Fv$Y%B@M*Il)Hie&`dWQ+S!6=%~M9qjkzwERgPi zXEVN><3o+JTEIA{jK#PeNM7 zZ#`X=m$s6|(|>q%yvgB74!pk>78W7}!kl9ctX)wKm5f2VQD7tL6ok?vhTW?@Mp(z< z63BTgLNhu_cg_7`86!DqK|P!a9Dj_hh@+=8)0paLeA-AjHs!?-pm_vH=Orm0rEZ?n zOE;3$^oX@#&<>bCmBY?fqb$y8wPXoSOGeTirZ;?oRaNS+#@%~X*1BAa%g$KjYCDuY z_y2a1S(}!?Ct6>b%7X9NWi*mP!O|qJkPiLBhOOj?^4c=o;eyYaIpb`S{8o`glSW9-Iz`%C zcEk%na3$tJvyN*U<1H|JF-#Hn5(id03^mazsjoWKD7!>D0-XmF_zA%wtI*8Nt?Jnz z3GO7td>kE9t6;w^*(9U8!r!-ADu+!eCBFQ?R$un|od*{JUT``?{LDI**r8fhDV6Qx?8=02r5VR$S zyy^76Hb7s!YFXKGLRRlEHfJAv`rDq~T*>-0*F5Oa(cWHSj;>#WJPPT;50i5_QpNQ| zeuL`R%7U9xFhMvyai2}8#N{h-7XdmBRkxIrsGa34M!wa`tQ_MfPz%J`*Ug)VnWlQ< zn}266^|lmzQIk`>3LLZwcuT`}g;W`S^M)`sZ58mqe4Myncn21bX@E3wN#fb4iav z3n}^%m>J`zFQ7Wm^R9~6+CqG>Rdc&zoSpQj28=f}QznDhW5@_es!IV8d>kLm;nhiQY_M7m2zmQN*G- z22}nA32-OqN3t2l2%+8I&S>GJ7l>WhU^5s zCtG1Jnc#OFCKzjkP;vcTJQrO6aUq9FMBO!KakX+1>Gy33HqE9;ZpKr$Me3RHQUJvR zpq!y%yO~oxJHR?|TGO}W{dAmk$L<4f#`iQJoSL(Wl?5+%n23l~XP3)3~ z5o{H^HKta@BccUL`LK#5@Kgx`+d%8w?!`5*WFmkeNd`ROGd^liUPF9=hlPhH4)ixn znST73dfqipik|ttsfHNgTnHbHVci;<2%UxhY&`i9mhuZ_EDlelFYJZP6a?&!eR%{Q z1>(yge!}wX_R}lPMpQfnL^-M^dGoH_lEra>XR03lc*wNCR}TmNF|dcr+l)Z>oP>pi z#YGRWllLyJVKuILX9iez-~YS=9mk<}Ol01k_Tf>?&?>VJ`)pXAS@W0g!aj#ZZKQ{; zUJ~Vl9HTx868!F(*HD^q*|%up$7Dx5^I>xA_p*55aY38tobET*?>mDun@aJIexIFo z;ds+5U$QbSb~%D>4_L^!k5h9yw_U34QA_t9Nm@Iv+R zvZm!{Lc;VIMU|kZz&DKOb(*>5q`SLE`NICq;;&iWizVd;V?H`oaAOU_H0F4A+>bsr?MTH&UVH@Yy4 z2^XU&&va-?6LM6}m2*&pHKAHrF?Ix^uYn2y73i|OEq}$JjzvnUN0I^=OcNvu>uLvm zX%N_%) z&87+tlVYPnkFn0A?xhfhNz&<+zXg%Jj1aq<-8P9Q)*-_{8z zn^d@+d?xk1w~u4i1*@0hKgaY+YkX`h_{Wb6zMhehNYEcJHs%$7>MYxRHKj(5{*2`9>{f`AQii0JVKheuaD$@XI`^N!nB?aB1H=!WT+8 z7Kk3ZAOd5e;qKWu*F(K->NFeIdVvK=f~fmyj>?BfwDVmr5`A+zt&OaT`x-^7n0IA^ zj@hE0XT1KqITsE(fF(gO2lQXVkqZf>0e`*Bh@PIlx3ABf)s~8!+z<5gltp5^{EP2@ zcb)L@=fy|%I5G23fEuH*&PxAsjruo5UB^vmPN7#6{_3NhvqIN z8yVjTg)sjbLV&&x!uXk*DktV|OgWOk23oTOfF-KoJqQeLzn(S2*?-Kf1yiz(PGWvd z=^~M83_WB9P&hnaHYdlYs;FQNRgYH#4D+q8<->f;J(J?^A1%51(%;QDuA8ZQ&P$ym zIMBtAWH7QVRKpOUSy^vD`*$m7_kc)BOMeDYNJ&GZqN>^n9OU8tScaJvU*Rx(mQ8T+ z!1#E%Z7`ML=X&tVw+Y;~q@exp9jt>CR3%{TQ#zm&lIo(StX2PJ=4t3c&NnwoaS?fYxZ#5|6LcUM8^--AQ^a5qnsW5cpi zBS4MZvv=-I8A6rk;ks?l;6kU7xdy!5B`X1;?q156DheTaGP7#TrxZ%hc2pXJB=oD7 zu;PDmqqwm#C2;@bWm=rKUh<*9ubJTGUUKTTyr6JxauPZ8OuMQ#7J)j|4lZGgrh3uA zgiMFDN+u{IPSWMY-IEHxl3R|?D!cacyRkSn^j(-$jh&P@0<#=;M>a!#f(gEHr$bK}^?@(XR#7NvtkfC7`=X zekEk86b`<@q!d_?&6?OYDX#0YJglR zvBn;o0%ENUpaWJ1eDkI92+(Z97l=JyXh-6D>!q&=>XwR+%d>l;)@SYyE&}iYzfO(W z`8xk2+GrbJ$I-V9!-3=K*sC6zRO?(XWpKdLnaDgKT9w>aXgUhn`0^b+CeLrfInL@< zmoj}E?;jj~()JwkFg}~WVpxR%z2L=qml?oi)6`3lHwUp_*PvTL3^f~2nN9F=2 zi7$TjL9upZYrhZ2Jbsnkns{nzeYzPoALY(hZ|n} zFSEIAy@|M>7vnWzRzx@wZ3z{*bezZTP*ymoc}eE4UG1ggPrrEXDg_@00%y2G7m0Vz zWV3Ts-_du`v{??rRIZP9Up+=U|0YQ=Bvu)BH`v^7EQvTf$4y~D`EsI;R(Mi>xIntL ze}Ozi6ZSko?ShI9(+x)D=E~Jaf}~Qhfqql6->yHsn`0GJZXIWv_2jRxU_)2@6eIY$ zUHq>?Fgg*^%NPhI@fQQU+%IIfG*ttvpe5v8W|pdhf>q`s;-mxjvFVsW^Z-sUy2IHM z_1{E6x`Al;G{X)>2?+$~!?1}^gNewjWK-ei9!8`!-jzQ%cEE| zY>s@3d@4nrXz3EuYwEna!KMr90<4(UD$DWKJH<{DqO7E;k>x-so4bMy0M3CmlNVGK zrwer z+wx8uPWuO_xY;DZ>WX@+RFSvj*dD1AH8GD2L%9}buDz;8huyavjNmwYQWzDYd%&6= z*gMqak2_gH>mzKuddBbLtj|_trtpu2mG&P!ONyGD{~ zqnzKQ&M!W>Jg{H+wE3a(w)p2~=>`^pHIZ(UrxnsCXdZvD7@>D5C>{(#S21)AhT^`pDmk7s-8X=IlKMP+Rq;aE7W;qywliXfZV1;bJ`)TaFPq8agNNe*x4N+>}IhVS{JHC)id z(X)#Dz!C>6!vcNMrB&p|m+Y^!uGqlXOe$*7A+=@QF;chn9vx|cud>f&Huq7zchmP| zYXY(=o|E30N{rJGha4+mTS3h{m&iC?_#^u@Jc|}C_SF-S zHR)_A_;1o5%|izzkv-!7(XYB=P0x?)Z0$hkA=2EHP3zs4g8LAT(9(KI;)n^>l?gAb z4Z$n|X?g7;NUNa*U3%y)XrTI^3dWf{^{(Hoego?+{TdgJYG`4_F`Kr5V|=jau^^4q zHq92?(3=Zj5U^VsiKgXmnW7fI+EaU)ALE=kz~Rej5}(Tklkd3}TG3(E%DXsxuwt-L zAi|Y$43FAKtKh4oeTieNJ6;@R-Q#>C;aBv5o;1lis<#Mu6}qEBwDahqO-+YBW)~DL zxHMQcOv{%ztGnr21%9EQg9(n*SUy&P8@XQBXN`v6W*(;FKDF`}&1Fa?G0B=L_3sU5 z5xlFUC6w{9Wy07+N951Y466b77*?AaRavd4RGos2sbC!pzdUJ36cT*=GJ{8j;urom z44bmiOSjh<*I2KxTT2`%;dX784k`0%8!uXQt$ zhS4AOxGA_;NwF1T=A_D|M!3tbWwr)WoRv{QLzL>81Gg&IRai;$z`@ss7MAYL_BthD zHj{a_ixJ0osYj_!x8KvV*0s_IP;ogDtiBl>55pw85i{*i!iJM9l0MtI-!D85&IK`x z+dvJOP-ZXPGBUoE+E->TLJBCdi5HW?A7ZMSQd1v!#m8sZ>RZmJP5>) zr3q0cN&$Sgr{-hOaJELu1)a`O8*(`XQ|j@mG#%A^7fpBExO}WJM*oMazn~hHd9x4X#l{q*aX9#O#(_UKbaFlx$k-<{>Oj6{xgbygX_RMi@6gMJJHguV2-p^C8Kn;^~P&)p5q)F@v z{|zk~`x<$%#J5x*%RsWdxBo{62Cf+nNRC`T2`k*pkbtSV+ch ziHbN~ECjt+*-@(?I%5g3eaUvNv$VxG-pcm;zln<@K=Fc6F1J|n(U6yCj$9pSYjT`h zL>0*jeki-*AsV!9M0dtkin|>CHHnN}5NLkh09IT<*+H@T74qe25?q~cqLkG4SUOQ{ zUR&8;8pp~d0@|T<-y_X?;21!4+dOkgZhz?S<4SlxOGiO!WTs&ukp0ZhUS!oXMn2lcpfQ(ZN!%Q*){j*vMq~}!AJFY3ht?EY-DOb zM8ZWbFfx|>qcbg_r@f!quJ>lL%eBz)j(V5pO3Xn#!sE2EDeq?eMfbVY)l_L@dg!^` znr&}ojQ=)M|9uHCO&Z#1#E(*XbD?1aE06si@ftl|?SEd<+%WfV4njOr?$OmrfL?mb zO34frCT0;NJiPN__&%&|Gm9^Tci)jI&~xXbO>i!#Z*%lyEB7*U7XD6Tg_QQMkf3w{ zX}21AC5;b7MOE!sWf8h^DAW0g!dmxN28zR++bs|J9PUroJY|Xa6ZSx7icO{RB={(a z=HNq5{<@YBqdof|9i<$n)dJBj8_yl|c4sEO*MD# z@mj%Tb}=A?1&3#yeaTra#hiU_m0(dmKurz^G?W=@by6XjB-G~e&%S%yI8Nb(vR*^S z%}bw)W?a0sIcP7+JB=gb7jc@S&4Hxnr{|^Qb^F>>h=5gt{CFgRP-AYFv_>OOyp6e% zy_dd67f-kod}2^lb5yGq04Dyt2P0&q_#`BO`hJNfx!}vtENwLw3K@$^g!7qHR$d=x z&Q7#Vk24`2s`4q9R0hl}PwYXQvD~oDVk*8pe6k5d-$BZZ`+RtCK{kWFBhzOHd;^mM zwfs!Dex>@oe}2LeP?B=1<-k?VVHZh)9z8Q*4pl0|^3 z+qFT3WXT9Z#y3_<6}W3`tf5h&%`(df=lbNR~3>G0>I2M_RZaQFjD?e+aahiX{#riZ63%l=z zXESPY8UfTN186ap7$FR6N&lYiVs_G3R-#Eev`SM+OK>5xJlCGFL0%QTEYGy?BoG z9(vGUOc&7)-tquaS^vhhZV+QiD%^V=KcE;pKok!7#%Ldzb=zWTE_9%xRT#d;2o2o7 zLf1cARJ#&9?&8ut+yTYrf3k`qNqU37v7Son2%K+JPd5BE?7igH4*n|)YREJ#evqJ+ zZ>tCwBUi4yEcTZceJ&c{q6D)q5$-_@w_U6{vHw*KXsI!3N~a|R2^0{~WncHn2H=2P%)Dt9jP^*|(ciVp4# zx{BCUo8N#}x_%OM(*SXHFRc|1PeDmtPr>B)DkQhIHUW0M7<8ZBdfkINddskT>t&6n z&x_Pc-hfuMI>)V5r^)**W^g01M7yQ}{K|^v`%{@XChhKbQ#y|8BUw0vbNnd`W*Cs= zLxpNZ)yYt8ueaSIBC-#w*5qAtjE_+*gcWg9zVoY?J{Y~a8oqe2D|XMv-?mA)r`-z{ zpP$nQAlx9GR1-f&A1Ce4q6QcGHs|Y{Uc909)5j{$9AX%poL^Jj`#*G@WmHvB`|as2 z0ckiO-3=loqSAHfZjg|a?p8z&-KEkUQqmz^f^97imI7i1AocVYq;|HzGoWW=+$hXewRRfJ_Zw+7XpX~i_L8AWu2ofV4eao=k5pv}A0BstRUrT#aO%3Lu#E$G| zPlnD!NRiAKuLiZVX}V&JcZzHEfhZ@>CcloGWQyEIi!iWowDs#T3Q~H+m_b~p1&8}S zH7sF4!}*w^bJs9w=Cn*c-qPR@13f$YkGsi+B~DHH8zsf4nR zK12_gvFdcTk%uP=`2Ep+EB;0vqyJCbh$8wQ87ftHP6kzPa`R_5SJq>c0)SX{U?7;{ zej1auF`^zG5458U_3@w7Fln?`{|J`n!@uV%;6o-DpIZ50?l86$inP@&rGN*^nMf7B zfD4`PuS6Ozy3BKfABA9!5^W!bO0`}1`Rn3ch7IsFss#vHEd4|AZ(U>3(M?&A@mx~y+|pX(THNRe@s}nJqX-Xh zw}8q?4M}36NAln@A57i-0O2W3gL#!ySg(o0rJk}IM}$OMyl?YQMf`+3=}WT8-ai4& zag$~|=BmWj(TBgHq||5{D^Xz~s1^!U0({6zLUUpJnU^5K5^nmK;X4NJ{0Vq{Ye3}mF@p!N z2ageY1Tx@O2jc5vD$?p~XOhFXHRBQL^T;jf?(UxQb;#@yFM!c92?VyJ{t~;nJIGgg zSN`$1`b+sxZ{1oeX&*^5D1zL#UtCG~Z6r%LD(rp%rzMIi5c>vUc+nbKYwAlGEn(z^ zSk%$7q}ea%gvJb0N&2Z|yT%Wc-Ug~_7_srWGkH6F|9?3JyFL5i*4m+A6|KB+lOkU+ z^%aQ90)4dGp+Zi=8^kXjJ@7zq;{yx^w#QZK@xQZ+=Z!Fn^<}qZ2~q?GaLo^1uWRY; z9DDRZRlJn%-uG(xD22^RXJ3wJS6vP&%8%$dS=Eg^&SOLe*lcw*oTh$nj&(F7@EwAI zLxWpY(4aYws0*dFh<{+A4K8y}5>@aDBEgFvwb{|O=Hau&Wghb~|0k4j%M}kpavHp$ zyu6(5!imD$ETM!kjxBqilDZ{#d{tp=FN{x(w&|RTU_iixpqta2rc%A_;Oe(mNnyU? z1UmvWt-WEZ`x5qav4h2u0)8<4)*T}f94%(&C@|VxOIA}SNjmQgeTDyFnIX%YjAOUD zs<1__JDMLZzmk2>@)z2X{jq-5q_FpQo9jT-oY>hEac_`qv)|F9ZsbiFBA?r~b5PTt z8(y%do9$hvW)c`e@yH` zy651zW~HOuI_g5eMfNA)B>yK0D67TN_w|@>$;M6DwJ}uL8nZuj!Y0Qs?aGsQX&7`I zH;Y$!xSSXkxl=jU!Tq{=y%whxTKq+zt+cs~WB)n7MK7J|LHK;J`+oPqMm-&N-jT)O zwdU|fsJ$*4EaRWgrjDC8*niXzMfAGdTg*~RfN$T}WRD795X5QWvJ3s9x!9~?1 z-I~~!ZgL>37uci%k^9y)(vbnBxwG=wH4vzD!OrAY0!8ea8IvQ(W7#Oq6{@XCe%oB8 zIuj}S1xyua&A>o5AA#M0Z6!)yI#=%W$Y;BaLgmC@mMN=n`C1WEikt>ewa2J$|j)_Gu zZ;|FN!E&%Z{TumTkrnQz&2jQOPuE|F4i8TB%Zt8Lt5Oo@NA;n`m8aWsSMu%`I>^ls zh-cy-A{OP~uIwA5CS1kPPQ&pM=KI{8ZB0-e<2-rGe3Tx03%G+9Uzq9R^9$9?BLBBgJ zh?AVB3-sS5QZIiEVZS-OlubDU`$eJldyn>1qX)7s=d2_q`d-(;$2y#7 z#_#1fPQI|p1gL$^R(yZGGl5JXOiA_K0_(%58q$?BaOW zWM<^a;L76l+swY!XCV^IJxG&(O>=cbv(UO zbG<3ud3m{?+t-VWp=I-iqBhyvmy;CGzkc(G$F$VB=vQ*==Mr}sDp=TTUH{%z{LsqU zi`TN`F-%k_7llhbPV-%B|21-gvYDzPhDYWLq`+R10}~lN_I3YIys%0%LMzUDI5vJv zoov3gUy_bR64H|PPq7y4Gku8tzg4gk7r{r1e^6sVNi?Rk!Wu;`T zz1^hhhRKgk*>vX`18kY@T$f|a(I48vPvix7>-52GkN<>+3I6zc^8T6e`N>*z)c3Y` z>zCkfU!(Tdi3dt&3ma@M(co{05axR7eGQ0#7H_f5=+4>|aFdb98y*!L;s7(U7qWQ9 zmY2?w>YLFRd}B8GT!UACG{D`-2R}YknTlj^qxTej<^172LrGunxPrnZssbpeX-Mou zX5jGlBGb&Ad4RD%q(I zE48670^a@T1@9C><(pUMwk&6AVW74|vF0r21WiIdM?q+vMLx7o%*!mW$|H)^YqYZ- zJM56`yl~4%HF51rXMf-O`~CKVJ+o!Ku9w5T=j|QGZ3BP&bkd>ZPi(zXzRzaZVb!JA zup3d6u}K%vD`XaVTN4vrAad)rT`Cs?XG!?FL-;Kkqp7aZemO~0kN*EA{7t?#<$reODt>$DO5*$;i*|lrZp!Smc5-CV_`_3V}_`Nqr;f@3Ave{rSBj zMWS8^TZthhuE7>T=xM}}+WrgQ$$N17*11xbU?TKuPK`v_#z<7iqLiNGIKvV8;=Ddu%fk zw;X4VZp11T#a;gDO7y8z-R4#kMQ8$;^gE`Tj%U=09r?u5A9~K?rVM0{oXio}T@035*@|_DJcYPCc*73g(9Gc({P) z0G+Q`_d|Zru4m3^Omjb$Z4LysqXjMqsWasE>gE;`th?C`va8?EB47u>Qhs?t@-~r& zJC$G!aTlLHf~u%GHol#bFXJmofS0|i7^*`%NBRsA$*cZhZsv545x#7N;N6!PN(BA3k4!OFJ%bRCDpkIGkevBSfA* z-Z35ak|FTm_hlr&OMjt}#a>fNLOIiUlmZ=)XqhoFY3RR;k24LJ93Rn)W8PADgXt+x zXPdSsq#+&*C{um4%s5t?D=hMc4&?#XcfS)m>%#`1u%>R0_X*w#;y!-Hz1*@$sijX> z?8Cr5spz0%EqKV-Lcz(hc1C-uYuq9Pp`>5Il^tX50w;xQwsvA=JX%-x#3EDxMMFFs z4DfN%>}cp}4J-p-O{BZ<10ftPvKO!Yw-w?xU@r~996RN${!_C?u1kOZi-!4%BUMs? zFas*T;SiTPxpHr!qmzlGQkIaHiVhPdH-ggve1s6im;E``K?MDV1i7&^X7R{-M-SdA zQ}=uSRZkq`C1al$*c9~(_-EZx0&z|Mt4s;33UV}@RxKKCx$ryO(;eQZfwEp7I-f6x zCNiv(uEdap;Aq6(Cb+as#15BJ?e8fv#D~^zC44NcNOGr@rJLNvHdM2i`8jZ@zyIXK zRsES`jwa(e(a$&Oby1){lju*}^bYA8tqYdM`VCj}=3z{?AXwLgz`AA@Z?lkb2Bm)k zh+Ue*3QL~~sF1!j!C|6 zL6g%ZTU)aJelLO%N?-xKpW_p^nmYS*gc9qDmfGK&=lWzix8S3jP^~3@#*vTCr`@+4 zXEF=Dg}=~AvNyTl_p-^7J6f&JSr1GohWNgxR}d9hv5xp>14olRdk#LiYFeK=_(`Lf zxi|vF$=@uv37n~M_{UKnlI}I(NXUl!y(}$7KfLkin#S5g9pUgo-*BL{2G=6K;Sk>Z z1$x+BS$#_@Rx6JbgC5OKZnen3Uq#DbbC0(?ecZ6_sMP%$L-Ad9RS5v?CU9}QU;*G>Jc0K0r}yu zA!vx2@y`4H^4z=nb9CikR;YTeXPhpgXqJO#c(+-6YC?vasuQtPJha%A zbu=Q%vRZ$XM!J=#{A%uz^q~cbPcKMwI-&;=IFcrgeKM`(X}Crp|C>0okXrSsM=%M0 z8+CHuQ~n!dr(JZ)*?8yBHw$TcJK)RXZEl%3iyU+MwrjdNtUt|lb5wQbyIC2C^d2{` z1!Sw!HgG%O-`d1>1o?&-ePs&BHaFv3z`I$FU5mK=`V#_EVMNb!h~(NY)B_)d@cY9* zPZX&MxG?cA6w+yoV^9bWDxGr~c-YG+MCRPIo=R*Vf_y0G%V|e@+1po6^Pa5`I1$xw$QAOMoJ^j1 zCCXJXa)p?Cr{8Xnsk_LXx3cwKw2^g&3;DKG+oxuJ$@<#lo}dD*$<=DDP;;)s z7p~^a%h@2Uy4EhokB~JaGDadY?SpK%!_i}!s#bSVUk@~u3}sWcW>C z1f#FO$qeepOad&Sd)Tf@w~Ea6K2&0s1QK}O*^7N=27K(4B63zXiEt_81e%p-udWhN zi1FQ~9v?O==bfHO#s@*JQN;R*3*M^U=^gLeAI%fCN8T;#)EePT!)%j9kEqwgVEc}{ z_P@Q-l9U{h76cajSJO63u|e%w0ex{_0$zj7)>|W^$P4Lzw5gez#fTI+rwIOFIt*p^ z1^zR^+e(B-)K95t{eGDxYu+gnVjc=i8-@Soa!Tk5VHTT*zWJ-Z#9e_aLE|Md@m7gD z%~)O-Pad8y0?!NSYd`J79H<$aZ{OmH5l)Q8XIUgmZxVn{fqHQ1= zi+Cs~ezb9=E2b>M+|XSbPu7N0ILr2IkK^-b9%P+_Vn)qsyFN-zCv>XZS03-8UPLS? z!SR&X!4)K7&FOL)hh|7@)K-#)NEObv@ZK%KqijP7V`LNCk`$)VmCxyUBj|UUz>A>Q0)m!by*(Uok7lrj8EW*^8|&-h1U25v9>3Uzi9V5EIwvqX&*L-*LHL~cHx0*JbEh2 zvqr{RQzb9>_|&YXV%~uo5(5H^d!ggodl}VPL3^_2J@P&N(hAR=nWb*2+7p76a3^ID zSud?{6Y_%@BlI4(Ub`-$bbdv*5@;99%b41}rZL)9JX}-jpW>Bp6ldf)9_RR_6 zvXi<#INd`C3iQ3KnsQ*gf1p;;=;>_?%A}`D74{+-%hlLqBpVLYAWfyWZm^31d=YD<}YZ`o<|@-BBnfZ{c#WH-BDT)-$`7J z9@0}Vu8Wl>S6R|4lV^77t4VJNJq;wL*7>$mI$DjFJNuSjSIv*i&L8}}9hFWw%kSuH zktpAGm*?#%w9(_#qJDy_N^I^EadLspY(jQ)Uc8>Yiu*@$3_QvP+TN?UeI9wc`B-EV?^%-D2E>-X(*}yW~e|!t5Q0GBG;pOgZXyw10yk zG^~w%*<+1A=(2g^v@h%yOguqfQyi`KW%`X;@e@EbK-i3m+{&7;xH&do-dl+`)^Au8 zwr}9LNT9O!tdDL(e!GMjj_Wcdu%to2aMbbaa8Dku{&61VH)g_bG<^|Xp~b41tyYh+ z*Aw-o-ujh)nnXJ2yu%swMhgtE%<50R>eV#vd~KyibJ?Hc9oDc;fYLKaN&4AXRFZYl z5a1Vz4Mpr;x|w&(OD=S)H0h7^RoL!2_aU%`Eys*?)TUvzG8=xOB>JO|)tUFeGBE~< zE~`Z`bJD1yv=+2)xY)J*ZJY|na@wTb_fTdLwCT!+VFVV=)y+;EuzVxkLnsqk(Hpc9 z^%(i8e9CXISYbwaYC1p$NETHg?;u|zEILZLU2WUd)1v>yjbUabhxdv9`|8?XmGEx$ zjq~UNii$j>#CaIM1;v~j%3?|)bV(7W;W)C0A?4?sdjI$lQOK9l$myqS6a0kr8tKcv zib;hmeIrNoZrnp~didv3OJZ$VF1{4-><);c3^D56)dyw(Fo(1eh#?$Sim&JYq)hwmHE6unuWTGRT z5TNp+Da7L<-6`Jt{gi7f{si-@kY0Mb5T03rzaX6@TKZd|R}Y#u{$br>5n39pSAx#+ z$khxt_4ETNj^=CUf{A{BiIvgNAf}_EdqkJy7C@vL-6pM&ZcA_1#^rEe_>47`QG@q2 zX{Fz)H;rk1f9%b$ii|n2`hHe|t09?fP;09vTH%(Uu!c3!nv*wB7J}HZt--xk5x>Rf z_EYS&-y3L|*=tYJoJbO%7x7TuBJ`fy5!eI84Ipziz63r&!lJC<@ z{4C$!et9M+SbM#;m2DU4y6Af{?0fu+)ECg&9@|K5N=$qg=!*-iOb0nw&0HGbGewp5K*x+MUb&;J;+mXRze?@;k6r zn+RKQptccUeEgeucC>?*y6t((5Fd}OL6h7@?cTyte`6FVcusa8sudjnQ%Zhv`a)^A zlR{XXB9d(qYmVXN@yQ9jghcB#{fieAfdFWAe|H#g0@`c10`NSq%{YUR&%WRzHy)5j zXGx^hWazktMgl6*OAmDRRM^!@ zt3p_NGtWMs;;P9DmR$x8MVg@ca2z^@^s-}DEecL_9lq6|*;0&n4-4Fm+nDn|K}-?G zFp~JiAklqOeN4y14GH+@MI`gGFX!AxqIlje9>Efj>i`-5k>mb|0d}cokShN#9252b z!!hCh-z*&dqy$<|=uuCiIwt0kxh52Ey6wd7q+}TFEH0H;+kY)=_FIAU1FDP9p(KNI z1+RYxK?;Vhokdf%R=Q@fGb3wEoz9#L%9+`!QNxK$s>oH>>-Z984H|7VBz>B=<=L2^ zMCwR8Bc@H<;B0O|uL}Dy2_NQ@p40JWqRAaS@t2RRKmeJ30i?5akh^38 zkalyJcoHE0{}!}nEQ$?;vvbQU&Q_Eh7Qpjw@V^G9?>eGJh-HqTA_v6)$@ zHMN8InDOiM+RA+F$dL*2?DJZ^nF2>@g4pz6PQIOep4Fx6Ar7n?CNW3r{UgR(SN`?U~1 zFzCk{coQ*S%y246`DG_K`>lZN+~~02afvso>=gxo0L^zf#G>VVDPoCz8>lvs_xwBb zea`TI;&gys`{<(qIM`0BnkvuZzdOAi2McmQEq-i>u=}-8%jqC@Nz8ZZ9fFZjb@Eog zJFD!B_UCeGZlaXg@C%yN%A2n*kMTMx?BntKO9l;<+t`xg%qiwt90UiKZz{h}Sn$F2;drL1pmEG`U( z6j@nwG$=ve5akFwYBPY&wy?G)0!;);b!#5Ebbw%vAO?CM>2Q!dqIdzq{E@}>*h#?- zU%Iwx86rwhFgU#2I{%B__^{of#$`L|{!6w685F5W3?E+KCs6&n9nx^b%X8|TDkXCH ziFTWl)cUt+GVU&{zX_#c(wh;Y2|%;;FEwPkM~NfN{EUdvpI(` z6L&BNPAoTbSunxo#o%9WSTopE=ozQA~YaU>-!uRes`JAFunCpV(4Ey>nB+8G{&n>TBjy*$%dQF3Nw4uQyYe_U?o&xDs>x)-zYg ze*fD*WD(~;ePRxq&efSbcpNU@A;tw%crT|_ZYU)C&Eh?*=#VKY1hC_p_^$miKE_IB z=pQ5(*C=5|B@3Safc)TS-Jy}6pmqDo5E_AFrjnJ2ZOgga?BSl7@81vkLu^KQ&8%B& zBd=S>aoA16{GKtv)*3V)($ajIYv2>SH{x|!vfq5vb%$4>Hihp47>u~OCBo`T-7 z8B?^yi7#mQo@5=rlv7b}*t%j0Eu?stO$4WC`IRnHD2|y-T_U!mkSw8SqD{V~fx!Ts40 z7VBXf{`-T!oGLda6odjQaqGm{4E53p2^f{e_yWR*HogEf;UxJ}NX$yE7=AE%72{y% ztqN|nJnq}K)3fq8aSW|nPa796eE+$1+h3py(uGOc(14{wjB0{0*V4c6M+ZodQX*XPlDms@*AtBf`eTC&*A#W9 zqNno?7r4h8XV^u=+uvsJZhzgB; z&{ii5*s2-EhT5CP*{9bi7msKq2s~i2PA(}Dxd_Q>n+2};-#WDy9+dG5{$4NRSE4%C z+p?$#r&duj?DQYgRC2^GpQ|ETP_g1KyZ-{-TgnO0OR7=9>U7I->r0m{@8$AO>D$$^ zv*(7mD1_mt-wNdEtN-39aWB4Bj=`!4*Muv$w~RI461LH9Gso2zSq&Hzjr6P~S@~~E z%9m@IJj>n>wQCh(aiz>ySY97qP79riW^@S%dk@oOYM?RJ?QA6v*ipb6;Cr|5DK4g5 z1O0LM&&x_X!|bFgoy()07xNR1r;;VCPC^8}I`#yvr2?cJbJM4#vZo)&{3%Uh)0mr# zZH;2gYNh*3SQfBZmtWd=f6h*ZzV9)_OO=%B86_aVMf`p1!N2gMF9(pZrc}4(?JE}5 zI6b}-^9!&ubhynZ;a)TqmkB6QJp7{JzB2hwm#jkflk`~UX0Hv6SIDGB`M!th;_=@^Cb;4boZjFsb`?yc;5umpjvy7m(p} zIo?vf_`hs%bA(>{wOWxo&qs#Rvb$Cg8=?pfE<08Z?HD4~dsvw+Al7C@nb5eV4${Q@N z%s80vD&BhsN9gCLE?t$2w8@`Hs))Q+w()oR%as@$p%zc)^6h*^?GZFoEPV>Y+gy{R z>1tTQb5SrbINf0*aj?m$ah458r9MsoeVZmoVcCWv@zBPFn%%?U`9)+xf-4#6O>U@H zok*f>;tRceR(>Yd<-XFleJ0iNWq^!h(vOJTl-)0>EU3%#bHqzz*ETr5u!slFJ&dg^ z#wGU(MpiKYNwXkNGO@Vpbp*=Mfgosc^em|w3xB$`C3-rE`ATAjmkJ!8U4QiaglK;f z#SC8twWNCl(JUMPn7@aCE3Gm0YCFo$)1MHty5%lxKx-J@KQReg@!#tge0~#vmd=Os zY>(+M!xEm3=r%H_r*qfyEP`nVVZ7ZGfavqbDJ$ z%He05PSAd1?S8cWx;&APSJ{0pAy3fJivIjL*_Cxsd|V?=o#gLZOG-Q1P@JL+mj`)w zBG$<{@bypPwhKE=!HU}23UNAr$lW$x=81=m2&R%5Z#ADnOy}1Go7~>sHhKkxZzruV zSOjuJT%!v4MFT`ESpQaUOG#*6xC(d-#WS=_2h5HpI+m8T;m%g}3AlGNu*f<5jG^p< z9L9QRk+|xs%{CQ~Zw0NlgyJNb{5uk^{{Cuktz-)7q61fg*GnJ0tPDFoCu!JoWo;K? z>{y>TQAB(DM}&LBZsrPSC8#0Zw0nOTM_G|YJ}%SQnc1d{XmT5{>tCRD@id%=N;SJ2 zzeakmm9!5M^U3~nB2CJP+Ml!SS)<9gYbb|ph{*&|-!5a5h_1g6RJsr_ly9>#fx1m` zzsBmw<4jtVkf&yyKyFN5IZ9p`3LK+r_<}%lKf6-SNV1UMG25lMRILA#W@SZ2u*HpV zG$!0`^eRAt+?%2un}Q-7vGe9<$r@YZx(g|-0NqyS zsL;QD!}@if$neb}NNuVt3#gQb3GVRWrv#W%nqJ_%D<}UsD;XL%)RT9IVY965;0TfR zZ%iy{<-43ln|DmyPY(Y(qI$j?l9u^mbo9)rE8&Hx zzc`ofxX9@zU-1=}e*w-X^{B~INvXXJ@fKb(MO?4I24AL@ZbIN{tJ+Vj)d`)3sOQZ62rdVqfZTr*H#ttOUir zYWBAa{Pr^xiI&IZylpym{&ArH9ZvOC*E?ls$t%r(zrg0gLfVBq5} z$f%&+-Xvdt>H?SjwNjh`X-P}}godznTD73KUD%Kr${A`KEj+{N~czR^Fxwc1xH!q6}JMzOyl~548u;r2gAYWAFnvj z7G7ABP18tXC}^t30rg3aRjJG%+~#eJ*-z6^$=nOfmlgb`D;vYhvBuVNVRlSRt18;q1N#z z5-rUk;on)P9`OF#ieb!D1J&c+ObnQ5i3E zI1H&pZ`_*TOwjZMyi~8%Z_$k^hg zSInVr#PSMV4$~!5Y5Sfn(sGKy<2wplhhIk}R29vGllRiB9tF!4Jx$E3T2AL>=82N< zo)0x%0F!ZV7KU_%qi*2tP-tZ5z=}l%8gsEaSntm;=GCzqK=2FH`Fd=58@$d5%Ee82 zv_8|JRzln2M~5@z5J5a|o+b!RRg}sHR|YhIuVv(78*qm?vxq)SfOi>;^pMGCMIEcw z>Yq9r&?O2yvvFFhM+0!(((rz2e#P>v6?zA!rybF4QU~5wKbMh;T*u=Oq(g`%-++^l zchswb&rK4uom-T7S^WS+CFaxNN!W$VZVe>~s$pZ!OZ8&3oE;A>dk4$lzkHCoU7)}D zZk&ZZA~3s3B=|J=X7{s?CBLoM0wzcws%qm)IVVSj6n7Hf6}5+#`u*qr!+lwq%*X!ep@LuVV84 z0YygPe-=3U{ZY0};9Rhr`05K-Bt^m(S-f#P-&N&5Co@PN(H0fYQsrZ!KcL?%qlxih z^TWAKV4~HCTEucW>kvE;H@_)xkUMx$9A{E9-A`in;DpJ6gFF$c;?dEfkoVg-C%YfH zH#I}JQ)bBIr|E;J(~Dt;={U?w9~$P@R~9t@&%^IFI2Z z5(hi2{lQc^N%SjG1a%5ot$Q5H@deg5|6buhE3A9fW7>3ECC1{M z;ohU`d5a$v5Y!3W zen@-J1%f(ZzRUt$hq6Kn%`C44c6@nvhac?rigi*7EMvt<*&f!;py2vELmR98kcr7@ zdY$801||FQlZYRC!Ksp6<)pde1;#u$Er{P>B0r_HhzFx01yzxr_Of7zbsCVmtv@!F zU|xS8hobSog7L9@Dc>Otuzx*|m_u&)W+i;jP#SE2QmSnm&#(UC$(Cbm#oCsvLRb=$ ze!9bUzd5XAPrkI)O=CJ2Ft*)@6E%<4JE@x+;RyMdY8^rcqD!6RYLq-k<}FLq!U{HN ziqoVAaTP?H9qsH4?awL7k!D?NaYM&U<8I%taT-|l*iMd$#Nc0W z2Cu37hHx8b;=n0xG}T3lt_r`ukyPqWk}u&fapxHeeD$%k(|7@@e6XH zdT_qt7`6->*t&MULJ2#wy|RCE@U|!wnuMy8GdeqV_-$&tYmF^|{Am}P2zs;{bZ>Yk z;B@++NKyS>3EQK_X$_G^=ZUx`hQNU~W8^pm|9~|v2m8kafRFx)j z5ZN`oz!sFmzT+w^#qvSv{{y1;Dp(NqU-No%l%Tb{EFgiW(Xp1K0F328TxKc)16os~ zk33pIR8&Xh52yTZ-*gDyO$5YLgxqwDQCgmV7i`Fcf7@~Hk5ie!z}T)pUDoR~WJ=V> zc7N&2haGQk(3DFGN3UdJ5#-?wa(1rdH9UY}3pM&A^>2qzel#|G1L7VrtvaoBy@RE4 zGe`84cDi*x^gm`WELI89YA*ig$;I2Gam*!+gcv)lsg^VRR{p}dT5f(vmOM5T>`-f2 z7P`nipata^+r|0UmUD(x?PZ{v#H#SJjt69wpSsvhZm8C#(8y_UO3+@t%G)-nT0MuE zPle>6EKbv@XLGJpqzsNjdC{u2{;UD|4PRgZN?jg^io?-f*Y2b&KIPJ4CXG|md23IgxKA26$*bYrtD%sxBQUz%pBhde4!F9CW$4zcmTZT28FvPG04W-&Wi;6T z1Xij|Bzv*@jX^H=i>O-tlM)Ao$6qv_6e4nac2ZmV{2vl+x0TC==jGic8bzC6w;@}L zFJ1tq=Q?W5;nmn~eOWa_jT5)nQM{C`+A!anS5BxGO3LO-fqa85E6-%J-<%v72}b*Ch6`zrD@m>+TfW$mY)I@PAg0s0w3Q}&olRESIuj^Fz8%-=m{ z?nv$wuiS#DHmJAa?V*PF2dsFS;5$sC zpU|3DFiHT1{{c?JD&cUCG66IS4fGG zNVCIc$MNLhfjX>ZhY&i%sNvrtNui3cKSa(?HHhZgI2snio%`NfgX|l&HjwzzpuxvO@6L7G{iGLKlY$nJYkohZF2nv3p)Cp zhEw7VQe6qQ@1Oo^m1Gn8!xf|NeG5 zLy14Lkx1%$rFf97IkJ%R#%X17fLb@u90#YF@D)1s;)#25KcSjQGspHj73#?lu;MBIc|6(vsf95>)&U%`0~+8sT ze;~`VuRkyd^{rP|F=4-z_LOE7&Zp!{>K{tt*E~3Zg|=>iP5Sq25kB$i8Vp)ntk=q8 zKLv|{ar;dX_{s+kJ&ma+zonl|fOOfV1H;dQiZw6p4$1rYM+ijnS+91qQ$dx!0tfzx;?9dR&7A5F;@Hhi}jv6ed=zS8KF;LIw zTe@Kn4!oX@>=ubr%{nymz3aEJOl{-{=RHeN=}Z7F>;XreXFL4Shpk`1PgiQyl5b0j z?}^T8B$p+V%Jo|}mC1e}P{p0X_a_m2VEyVw*J5+$FE0~6gqCM$(!k`~w)%XgpgZu9Lld}ekscvqa`-)B(J2&Gz z(08QhTw4uG#16b1CbDI*0~wJasGy@{2+X5%wKI)$a)uUD3t)>=(`IB_<<$s5a}>TL z`ERU&oK%0UrEjSg5RWJ2vZ|zb1gm1(3$S0r;Df%9j^`AU!#4;>rA)5qowHp^(YtGR z8FtLAJ@bPpe;=@u{#4i{jUs?PjM=UXy0uT?#>I(S11@U+XlGwhku7^qYZZS6mHDD* zlQh21agDFoLeS2W-v3M#V=7e$Q}K{1m-p8l{#-`i4xH3H);ayWEyspsbsXr>w(viP zwmXFgp|E%pMqArmPNfgD_2@!Y?QzIx%gkym>R1+6wtC#ptyB70L+Jj5G64w2vrhi3%@TWs;Bp&0$c78rHGpC!n;+$yynMwB;)c_b0ptB zj+xP;PwN7`xcqKVg!}-Fm~P~PbvX^@0p-TId{~jB7XY6MS&TUG1u=m zqLj+^+tt+b>fUyDbJZ%WJJFSj;S9#%CNWAoWCp;tTUHV};*7^v2%~M_CnI;I^UcBh zUCHB;w6&Yp8@$cg{1L}%TTbI+J@rnI*lK&$MhG9mH)~l4L*Ao3nPu{~B2i>Kt=-cE zDwHM-yR$@oLWq5}$q%{m2~d)rN#43Em*{3f9Q^Y-p7j%tM7h?tGJfiDl0i7EW)qdX z&E#VWgT5X;Q&3r>=K5S#Z>XPFrNm=OuJi>?1XfG7YhfFTb?=2>s(4^HrC=J(Y<^}f z62Bel+p>U=XCAc6>!a)67vgm^#VC060<7bk6s?qQkv5h^%rZvOSSCMm5#>C#SrWTi zkI&7^;|0C)9)Z@No%7tf7pRVKegCFWhri`uVHyXSzE2r*I?Na_6h_B3(XAe00?t^h z!4~7@vhe;GSu$$m@8*hcdppN4;(4ZNiZ)`eh!VE`yy!xTR;%74kkF!-ueBO^LqD(> zlYrjjVxkb<(StJ+hxn%ader6v$Iu=wXp)jjhVPGy`owZJ@gcuW9;vD%=bEmdH`_9d z=;}oP)AHtM&Yx1_%k@ILu0WKxBOk7oOr>dEBHd}ViphVz4us#|9J+4jC4>Ir6_4nN zM|y_D?UA%Qa8KCV+kfA(1@$-zkKc4w;x$2k%-(4oW)z=@Rq~@x<+i73gb1?6810EV zK4a>$P({JPy5MQgl5=#W#M~&6``}17$6dj+*h#^FsBrmiyN8nRs4xxf1-r$kO;toH zwoqwQG&!$IQPT6Rp!rfsBcL<j2^=r`P=X`W|dr}eRphc)n@a)a&~{|FHW0HYv<&k~Ef`3MOC zbbbRQ3eZ_m_$ayUHt)Bq;7c{bVF1}53UITG?-e{dSQ4NsBdfC*i0YnFY|NZ`IR^c; z{FiA?>vbq&1cn{WlPRRmJ1k6rfl7S?6ciLQ{0}CzGG=p~8(rKe6QOZfps!v+Lryp9 zm1T?}mPj7F@c>7~kWMJRBbJ8^t*0j~>Pr}1tb~>9g0e0i`;zgMGeYFK+{8<65)5h% zxxyzzv>#Y>Zs%HmmNzK|(|2L5np?ab$p2rRoo76o?c2wtiY`=#s!^-<-fETJv1-(& zMo?{y)~XQ{NlOW;6h+M#ty(c^@0M0mdqnI}G)6^@*yMlae)T+W{?F(0&vNDFo^9b1y5PGxcsFn4W5t@4llzm> zo|td)QHK0EGJY|c7EdxpN3b^^^AGfnx)x{3yN=&{qnme~mpeM&0?Ky8O&b`)>OkY4 zG8GbvV7K~w>U>Po+wE{Fk*W>f$vI=N~^%lKk&w>PbDQ#SJy&BHmpqB z+gl1y2L*WapiV`&Id)hBX13E$iAzk&-5%Sr)A*`gY_GKs>5~m1s13~pEB7x^v6h`G z%|uQ(tLJq^YrXCnmoVj_xz0R0Vl``VKHib38+EN4wcEzL__CKktHK~BWPOjWf0Ch2 zjXI-e#XRaWpVz}d!g8$enTl=`UQf}_r?j+5*n5^fZ5QMkJwiWuKIka6)^9SzjVF0& zdv+3x*&$HqvAz!S+43MCpxWhsq{S2^r=>;9IQMSrtv{=ueO7;zt*oSU@PT`HZO3HI2Uk$=q zMDGL*M{xf?7eByxtk=I@2~o)1Htb++h`%xr(Sh>6xpU$^0KZc(M6J~9=2$1JuFYt~ z`GDFz|7xmqHN2}~ha?HhVcA9=dwgk7@axy0&9K9V!q0F#{6<$N4k304bLrMmqp)+U z?77~TnBn6Jggm zFAknPSeZ(|aBK#e6>IHkw&Bj!jpN$K{dB950ZI_h0_**~ab3KH7*V@Si&@he_k=0W z+(6#haBb@8$~qgndzGTLpS%U{2h3XSH;28?tI^xE{3%qX32Bb<#2U7hf`6bn>G4#2 zLPBS0!ysZ}Vvs`{Yiozkq-?*6s;Vm#(mR5J~$u+zJJ5Nc4b9M<#qa3O*f3*Oe?r zjaI_80HJ!T*3gjFZT`fw{Fe#L=)X0J67&+my9`Oqp{xdL_=Eh>lE;+F#cT~yd1kG! zjQfKZLAdl`v*m*q5p^!eUNn}jP9ts(9)2~Owc$@o3G;dG5MS1oOBdhun}G9^rPHpVO{!dinKC4myCb#i>lwR zctE3eylwh)yy|REPfzM?gxYk_YH28ka}+;Y7%cK@M#pT__FK2m*i=__0u4G(tNCD= z2+_wDNziG(ef_$Y%`3D>YZ3aPXc6+D;E7v}9nUYbUFe)fusZy5zqf_K+Vl_x{OjPE zRcXD9BXn5uF}?sPZc-}mo>@B5>qxN7_0HQ5G(rhNm5!?oi#N7#PqKH0n#&MWEQ!NQ zEK@FG(lWXM4Z|pQ&y;gZmxyMie8$U1FeX=a>MOZkPIrxLY;W}A(AH*{EX%~K>)l8x zCKReZ&>pfsiCm3#d$htv{|IaD^S*pu#CX&JdFKjd`|ZkAO?~-U4@;k9MK|2c)HPh1 z^7p!Fhervu%mH?8D6e~wtUT^_PyHekVW+!=5?ha;i5Ed>*ftmQ^hY&8MsT~+N~=iX z<#Sj*ucKm#yHJDtNlvmc7l{(mtWNS`4a(IGgUbv& z{Ox%kYhI>dn_^xtK#XxSGs0`)oc}4XEDPuPNEPvEddyzn6JtzYp0#GvR8eAaU#T?` z{O}vf<(9>IigM= zdr>Hqjt^)y6Vuz@lIq+%JUl&)$U9IdG_9TL6$*utjf9*7uyI!g>MP*4L3Yp(C^Y{T zsKEbqqkyQT3^Nmzy0&)bX+k)-Jfe6V1TV2O@{3YmiEM{Zu+^!v8K7k2PXHWRV)3M3 zR_VGSOP-WkHe+mTEFf>ZGAv-jJ%RiBa`Ey~0|LfbQRc2sFq`vMEq@ipx_)fFYQ@67 zV_|9ze|`$`cqy{$+`AVE<7`UNwW>ick%A_{B6T|Ov=U9$J>+C`*yj(!!nBeljtq9B z4R5r;_ZCS1bjEh3^1}1^{)_>if)nr2+BsR|W?9&KwNOgStIJ`=J_(j$*L#l<@HMtZIc7anf{ z)b-d-|3nqx$?fwIe8hd!e5cGYfIi;9cA z|ITV0ZDo@?C?x^1`a{v^iwOYsAuA_G^Yr$?KwNxgW^5y|L1d{OP({4j0w-$R*$QkU zJ%C^pB=8t}FZ7b^F@R`90VXpCr5^y{ePDDHagn*yz>T$rqFZ0Ph6pw1<>^_M6^ zVQzjExD^pVk#KIf&~!dyYwlL?o+Qx71F`3vvj9ZCw7mQ;&$+j^7frY?nv6UsDl6jz z9ZUrL4aOgNr%)XtLGu_F{qfiJ$4*_3ft(F|CFnzHZCIL3MlMvv# zzXSot-u1TBuvHMRe@gughw|^4UBJnSHY`X4aFjPe)1KiIYsm`>567AUefoU?0J}`( zWN&^xv5*a*cKMY3|FHNU)YQmFy?&i^e7JkKiyIz3Lj{n@oMG&5FzypIy8izD{j%1W zR*S}YUA7EJM3}i<8 zc*QCw)}%eBn;Z)mcMqN)ZFKSp2xteZ%^*A53yDxD)sGqS37qVl-6tTQ{;x10xdl`R zEbq;N+sCf`tKmVMaUBNum(od_o6ox6%g_}T7M_HF9=fBgO$R0vovMJixHwuf7tG9{ z<{LmX&MAvvbTrRNZd>e1p*R}cLnnY94>d8lw7I!yWNjUd!C<_9%>8&e)o>MXsjL7U z9vtb$&}9q4A|eArLt(#uJs`ILKnu5w%;m+!#rd~WY=hI&Z^FaFxrbaUP9{ARz=hN; zyP!Bgl?n@8@9OHJ9;9B$x)9lL$}9xJQrU}vHAk0}hyuO8SukPPw+XS#!JzHH_;rGl zSGgNb*tX8gvA=507U5CL_I#K4jS;cejy^vWVLD}3hQTm^A%^%pthP2bGLm%Rh+R;- z5mjz0>Ln_tpg?z8fa)kaJv|*XosW;t!5#`ded*FAT2<%VCcsk$^LZdXMl6(|JfmS@ z!8|xL zdWX*r_;ogTBgP&IgH5BCpZWM~fHSiLakAdU)3Xz3OB$P*g|DovNZGT{Hpg09O6XX#-PJQ<;a_7%%ArX$4u?*|rzdqqUwh@py7D`TZ@Q-&|s1^c3wl zpvei0tIXzWMpMDXiE_s<#LQ&9kE1N>2FQDP0Q};#%;=z-B>2WJO`!9~(v>37+0J;I zeS0zrbK3;0eJ^0l(IK)_=<@Q5uU@@6>C@EIOjUg@Pcb(3Cz~lwnLY8M_bWTdB=A@; za7Zu%{!G*|0)vv-mJ!>MVjp^4FIiM0DChv~`n8bwwI~0Kk-Wzwi|kh#BruZntJd=A zrS|t0S_U}e)7|@hFzYM}8v$O6Ki_He)f@8)Z4sv$0SpXPhB#j3CO-!~NHy&FcYXue z_*O|wP!KSfzJR=mx9RB<>vcVk!zR|WY;0`QMege9b*19)q&s5vPENcn+aDxyK7Bev zNl*Aeo({mzI3y$_I7qS_#HOCxX|5f6%KZT!O zmwLS@@u{9(3}Oaj*Vyr(0tM{bU+a*}hjE;@i8JuoHi&^=0%<=uAv05qO~HeGU|;(U zI}_C=Mb|IMNB#h0uZRRS!!Wk>(z6>ahLxZP?2iw7Gj8RL8CKHM(@O(_dEin`WXJr* z>m^p}B8tJf-x}IX{)}IJXX8=N=OQpx7P9sPa(M3idASMfAYn^aS2rrZprDHktS^&Y z`}~HEhX;o8#wstPae&~ZcvDRc7P{LwLm!|rxl$H4<#8>&hhJ4yl{>S5)X>hA`4G%8 z;tYOzTCK#eGH0@r_vh*-J0bmHJYLV-{2j2by88OB&CJbp!C#8(3{1x4dSHMSz}uvh zIJE;Ea6A#yH8e~f95f-z0bKXwt(tRmHG!{!rdY+ zvUN{*wu({ZfBg7yrXnJO7TeSF4qU{Uuly*eX8@B zYup^FL1zAcM!7jdw%=wb!wo5YiN#_!LE7C+_V0tuD3r?1s8hoG_d=AeSlru~H?gu3 z1T*}yaX1=O=^;qBsq~t=+0@)_3huX+f1bLp6>1>KpAY9sqiXMj%=Spj6mWESAx3F%T6?nTYkLt^78bzswu4#n+TL`5tyNvWwU6;`5^k9$}V{dqK$Z@?Xp zI2;Z~6U-=XTgSCK=@SRcE(-fFVR@*a3wW4(Yin!ssq=G%B_&BZco+5??mMMA(HZE+cR$l;K! z{da+^fUo3Z9Rq`RWuc_vXTLh4Hu{bvOROp=34HO$X)RYI~=(Rs;H|Uj^ t-VQu>1jiJp@4O=8|MT?nUynT}oJ&eK^X4?0KU0B^uBIUrbI0N3e*inn>+=8r literal 0 HcmV?d00001 diff --git a/docs/cli/basic-usage/Readme_files/Readme_22_1.png b/docs/cli/basic-usage/Readme_files/Readme_22_1.png new file mode 100644 index 0000000000000000000000000000000000000000..0e987da3410c5eabad98478536f299477fa098db GIT binary patch literal 41505 zcmZ_01yB{<7d3hb=@KL*rBO<{OG)XLZlt?QKtL%e>6Vu625IT;mhNtN=lc79Z{B<} z&l!fxm3!_v`|Q2;+H3F2R|Pot;t&`O!Lvj}r2ggsgHf&5>OmE+in>#t#Ir1_yTmQemz+~%S z#!RoX;R_Z)wv*I!gg`J2pkFZgLV2Gckjx0FcOoioDf^4AUK1A&Z70)LOtlqEo+5r& zHE1HwDD&y^?G?;aJ2fZ1nZMVb{Ps-TbVGYAt2pl}_XBJ~yBsNc-P3ri@ zqoYW9hrhklRNqst&Q2s{4*3opS=YVOhwsjOEE`JpkSGGNM4es*MUeVoi6T*SMo|er z2jAc2QNnzKKEX?ZtN?xkX>>=@?-h6uA}0a+;@@j{u`{4A&Ki$`yoWwWl@pf0T+wjj zCwj{jmtR;bZvVy3}SBK zqow9#{=D}vf12FSuK&i!&(v7IGV;h1@p#Awuo7RiU+_Z9)RNDHO6w1^PGBEJL(8vhJ?Vx(vZRIm! zZ-0M>6(`w+yNtAS+57=FF~+|e2w}>i_HB){#EQYZ>{U*`v<$;W-DC|p4E3gkz{kzKpuhTwSh_RX39Xzey)!F{ORqHT^ z?GpdyP^#xIFXunKP0XT z?f80L?U6!{ZWGp`>)qjS`qL#kRJ61>`1leY9u31h;2)&3tLvsYxXZBJu$=K4I}bsLR*{g+WLBO+!GaWQtv7{;Zf&QzN4lXd7+0`YMCG3V`H5rET@XK5QV+G z_#yQ4^!zt}WBzV#V&mYzwYe^POPHI}bp)YXt{%TUb>lZSHr8h+g1WF3XMdy7YJAC_ zin@9XxL$E_1UN(tev4IdVB3Ri;K0Bd?oSU_nq~Sh6ciLoDbE`hBL+>4t_~NQo*wVC z?b@Hc6Bn;A=s-AZxw9GKUPlv;AVzMh-%9H*Gw7&0Y}j+V-O1}48rob9CNtd}NMuZ+ z{`A4wnS(SkxU=(J`oW;+wNd3POX7$9`P#_cU5j68mJ*m!NEGml3teo!k6y$Wh&Z%z zRDyy_cPHsj_lS_n*@3HN-(l!Ge5Vkr15RFdf7-8EXP0?JDxMw1+;R<@Jt`?JjWVt4 z$vCa&+bq8rtLAQSDyP97<5dbSd24))IxQDOENA|!J^AGp@0;DC(vPPTzySicMgA6N z|BEgF6`ib}d&RX#sHl6}2G=9(;lqM=zp{gYVb-{%{9esZSK693GNNERx%BjKe|-D~Vd$ZVVeBuFedUjTSJ|=?< zR$giQ?DcrFHAs{PK=UJRqJmF`Sg_qd&SB#V*JoZY79NK^O$g!PIquG9E6pmcX5R`v z-8%vtaQ_=6q0#74Jgn4RIV{*u8Oi@Ug~t)1QE7^th_guG?onKL{SPu9x;zGM_6G2paZb z{xdY@*88{Pxw1yU1<;c|qEG}Li(Lt?GOz@TDU4g2%qa~cDKz+vjVUep+*vRAK6%r~ zCc(EQ+qOuFiuw<`14D6MEjUJAoq-!={WM1Pc)ukC$6`K0USl=;n{AkXd=0X(=%de~H)i_@WfhYno;$+z71_M$WRdksChHEM8#6tb*^~=QE)^|8Y1$WCvDMRJ0DH z+q$EcyO59&avGW-9>-067J{VxZm(g1E4x4RdB@l5k&ct9>g8TH4!Z6exVqjKsz*Ff zKPYWFMFF5&w`fBOvK~Sun#5VK(EaC=^`5i+%3+6-F8s4WuH`Co_dLB;AAr7PHjBI- zSBJ8al9Jhj6g}ZDCG_>lp()$;w*`d?Tr|#OC$B!lM3J3$ zkC(NrQPI)A-{b3a{_Tq)6!PH*2e+>1I80zQx&}UfecXXbDCor<$$yFzDR7w}@4pYQ zL&DJTRbILe@3gifI!Lv)p?m`A9=ioikGFeG*K46+L>%92TOWP|llj!mPV4#HZ2Zj4 zb(qpLdrm?!h)Cu&vR(iD`SYf`!$z-*N%b%SR)0*vYd;Ax@AHIz;76FEsbG)vi*@}HfPbf=q9TF0moLY?3J-$p z!KVpWfkc2Gyjqri9(A%yAH_&UaG`-a&E(FK*Gckiz}VL?Qh_86%PFUGmWV!eJ@3hF zwUwEf85h!U0D`7x6MjZ)@bCe-Cx_zUwwUln74-zm4JL&j-@(2ZWdP)3{$B#Hf5U(w zYQhPBky%9~I9~!sG<~^+Sqvh5ma`qs{CrlHwu*FR&6&)O=zlD9 zyCCI8p#|{`>o#vwqoVbGGw12+s?LbT3=n6~+@c(J0HaQrASyK+Nb+9XDk-LajWfXe zT`-31KUSMX>%gbFp`lCwIkHj0)WdEG9I0b1jMPE=-|AogTzzK4e53eRRd~+k;<#FI zS?nF6&2j-Xj5L0^aUV9jY<68;U3T!8g-z3mI8*)K=m^pvEYWlR21H`5c6|gf2$?lZ zd{5hUn{~=aDJB75OJR)_8=kcdAiq@9)F&X7Ijnu9^&s;F{=eg&iU*FnS2Pgx4NgD2 z>)`X1MT}8t=sh;J4_xYsdL=wvxSgld7#m6-qcb*+p^23eytr6TNl$exAO!=aj>(J5 zHb>VkOW@p;aR;#S9PscJ+;DIE!vkNEXpitA`p2j;r(w{@@caC<{$u!CIW+P17Ul5P zjzn2cuRSmiFQ$gRNH)C|P)DKrRm{%LPW|eSi7W=NMQX*TJZ7^MCSk-p*hQ0n3i8ta zazA}Y;eKvj*XdX_tyeoxZ9e)+PVmMU77mW*plW=k#k=t;}24r(Ya rk}rl4R{W5EqjT*fBy`mH2RDNrr|V!+ezAlE^lNgZH4l^T)^G$$osAV251D{3LYN*xN-Sm$P?uMPv?h= z$*M(a<)(u~kJmjyhHn!ic3Oi$Q7E%DY;jQA@rM3IBVZ@b-X}zt+qn35Or(68I z6bBTDila*4-Q~RPc%!SW;KR9cNzTS`oZ>(Fu_H5AZC+w!5R&VOyWG zmmoVqpfuN8w;yl;5ho{hP}muOTIZca(P0AMO`voj8Q*IK*{f+w5M=oj_svAe{Yj+n zUqC-Pcbp8XKhC!L3SBL_l7ZBI(gFpaYJMiVC6#&Cp0>thb|-e4pkKMR>8tuxPUlF? z#t1oS=V8AQ*k~_ygnx8Md59ZiZxI(QHoC3@QXvH3lQpKVbEe#Aw!yjRsysIK#ZfEe zt5*d4Ze>^3WRJ&)X>M!C-H~L&fbY$e83bG{0KYx!z!bW6A}qP1)b-`r{23#6N~kU@ z3;|RyrF0C6BK zP@fZyNZaF}>)Cj-nGEPE=CqD0$xAMqzreRP!KEQ&{Q4C}ubd0b(dm(?e69}Ngl29> zfU{4mv_R?NXx4l1)~B;(=?0avlClE#;ru3lUZ9|&x<6b@Yt}nZzg91SSBbXP%5OE! zp2Wj0)ROZ!AC;JGa%Tfnlp++L*%VmB3*5K$TMQ7i`wOJ08;z(MWrtY(u3PI&a|lT= zXr_4ke$f_i-UFH`i5hU9oB2HI1gV4zXlZ`B-?b!r>dF95@pKg0twEB@F8YON+H z@A-Xql$G_$Wq+m}@TKNRY8o1cdF$GfKH79UKw^$>_e$YdOa}-!ZI?c@`aBS@==%)^ zw`TlofeI6#9D6)Ve>w)7^<;keaq1=2ix)4-yzg8{eXb1v_w58r(laoe*07_fN;>ANWA>-t`+Uiq zj;f?3X&u&pjrHiJd5>jVJEr0C6`^x}^2hoV9`O7yLN+J`la!Hx61@e7enybES-fwZ zj@$v6Aqd4|Gz515tr7sDy1V`!Na6^!ZMg{o&Iyi?=G9a7anzjE$+D09wpcTjE1+=W>5maJn00 zh|1Zfuk{$g>j`?k$_%exL-Ads!WbDy2}U4c{Q6k^ht>~AG$bu!6rBuL+|&!dcX_&P z3KkBp_}g-K$(LUHVEM7d-45)@q3lbj>xl<+r_k>%-bRT?FK#*JqFGjY(D^>>>D7bC zt_P(u0h=jWqsze>*e(S>|H4*E<6%Q+j2!P*pjF^8X>YTMu{v&k2*MzdwyENq3Z_ol(x0ey14hsxyFkS2$`GDv7fGdpCo{0g0HvVDrV}a>#H0lPWkNFGpII%M#LWSy0j_! zY*;A0-f@d_&jYwFM$*!8=A%z@#m9#yY6BT0nG{IU$+48`7yYk(87&7abKRdj@ZW4` zDk=Fd+Vrg2VG$ASIu7hOMMp)6C@Ep9?UgfjLDTi&Z$`l=v!=yADfAtZB&5FDM);}n zmR`ev0GpM2xx#=PZXa7Yu{6PqurzpFNs8du%;ir#Pr>lau$#-{qTFKl=qk!Mxty$^ zW1YuLLp!pR>NS*Yd|DF62#L^qVJ0$5kQ0T zu=f!)QDPkd5uf)cTLS}8y)k(mDeA~HjOK0p2B~=HpyCjhLlrt1FG3dVH_31zq|6J> z=i4@u>9kHP<|M6#+RfG5(P|^c)Q2jg+Da$>FzAS~%T#^XxzN zrzNYOM77rlSmrR&_Zd_l-2Lykd^%ic*#7O$Riy^sNS1nI4z?(YkVV*S@JUVW=9>rym6|YssCiq zZ5sv*;Vz1@ZiV&Fu3Uw|wqf_g#nbOww$wI0b0EOt%=@Oueuv~BCIKZAIGx4ijcxM< z9uO$3IidNbSaQ0(Ty`*sV8E*u@ohiaJEG8fIvd1yVJ8C9s<4?IZRUq{tatw-v#H#U znO>M0D&^H&T=^!+maoRkE(ND+k0Oc)KDZ$5@b{HF|EK0Q#Ej`EC?n_U*ZdXpFg=)B z%YTo>HG8#C=!HZG*(}2#v{3eV=a;p|i#y42@Hjdq7zQ+!zkqu|b(X;3U?^(?)Km_n z8?Hqs93X0;5wQ4y+G5Uga4biL5L6dl6xr(nx}byrsbAjCjs@f$eh_8o zX;32RdDI-Q+w1`{LuZ}+IzWa#R^R3?fNWr?)5qGJ9d^4nx?H}qW+ct2!Jf9~o3xVd zZHpk-QM?G@rHfL9(zT}*fFH`;n`ZZjKyeNel+`FM9kDZd7yTL1wHK?Qqq#^$6 zl>m)mwXCcx=q?Dj?Z~0EC%_G>nX=EIaEb$&1zIl$p%MP3j@SMTR4Dhu`mJL({@A#< zlTzP@P{1620CAPouoDR?wxkpO0H-|LOtw8e=^=9jnKC9NWuWY7-L^Vt%*pAd?mr6%lgTq+GeZ zdj}tYh}zwS5w1xZ9C5Mhetff zMyu-zvEDpS%{__`5_ly%%3j6k^e4oUooo!btfCdLRx!obT{0QEXIQY*8x_QJY4JVQ%jl4%1ZTuVD&7}efD@LXOKVc-f!;E&$ z$iEp*22i~Y5rcRI8d&o+)^9Y*{D5Ere(_u^^RYvj($`qE&j6sHsD;WfS5sr z9Uv0haT5z(xdY#E2Q?}532vutENG<$R1j^a(f1O9IiRc`$}NQaadAhjY%bRwOw-1$ z3C!0uYJ1^utsN=Di1-C#N5$Lqe)Jsg#U8XTlkRnj49?zRT4_J`DenZ7LN`=8ys2`) zxk;e`R#;dFZCtnk$)ve2HNzzW8q;Jx*PmBb^lj=^5jF>tC4_~~)^h%Tv=R`|gWjLA z5Mz!ADc;5ZXvKE$4IH5$X86LkG-|g;q=(rQkco5nB||WHxOf0wneMzE7A?2?XjVMw z_Rjk!9^(lV1rpiJDh#_&TJ8?{w3+b1!I?HTHkKTray{S_y+Cvx0I=6LFz^=;xHD4M z#zk$n)i0nQ02L;WL1A+?rDc24OBq>pYyxUbECFrV`niu*YK=_Gv-$op`R9) zQ?^O%c*vd1gW+izC$k7+DZ#ru2j~OV=2;J81Ll7xA#n!q&9Mtt9a3gJ&k1|>0 zK|ZU)ZZZ+|B+=9U6+w*hP(ZITM!J?N!~^}jS!poK$&WKxghxq-Nel!o#B%Ca`-TIn z`|0Y(Cs6%l%BKqgp`6%nqd%SvKu$V!`q>a)B)9~?i}$bG!L@;2)5#6A58%NbiTaJJ z@bn@nO1?%+s#;vnk;Y7dEHEU-Yq*q2!Q_CCj{8%A5rzUkDJDpPhWFPeXk>!Ket@wJ zn6iOXD7e+#-5s5pdLWSJW2fZWbeJFnnphn+wVpztITPtT1Em&M3N3oLrj^}m1+~@J zLHW!q=Pg)O9=>aq3~l;{RlwzVHX$aUc>LU8b(=KKGmEfYe=WGVEKh^7Q=vOfQAlK;YWXacr_kaTV~JRh=bH$6VJM#k z+8;BB7&3qqwO1!~b=&~)=$V)P`1r!MF1@yp&f&-0U@PH6OUPg=>jUavW`9+GnYA#JXF|LC8hCA7)r563oscx&M|Y?uqUTdDpIO8EU!%*Pkj?aabhM~~0v6YT z9ULf-W=@);J=kR_L9;R;fk2x{y=YP0Nr)y!%2X~8OGjo0V^Y3nDtZ6ywO5|U^=AHX z#`KZburqEz9|pz4yk~6BLEUbKQ|yoZY&_tWyf14dXa%yrFDTKnQmBD)O`n~elB8V~ z;mNTUx(cj1k|Z!I$IA@8(oV$~^kWF#l6INpk)p z`9OSH>RCHb+x$Q%zI%L4QvxsTTHtR<5l~>)?wLH%F`g|Lpxb(aE@#2eHd9@LH$Ck< z<_;)H2osaFG9KHK&K^z*#Q2|h#rP??f~a-oKt(H5)*yrMdYRKsrQo+!Oty>Yx!dwt zvsP#%HfWOk$9NCg4n`9j?NA?28FopN!2=t4%0zq<&-O(0ALjhL_eGpME*=xGVa-g( z2c_%wpAUB(v_kjxlKz>YA>scLLOKG{i0rK31JKc6ywYJjNr+sG=+)mn!k-khY^iS) z5YdZxYhAssqWrJb?ebk~&dttY;*8-^>_+5hYR&ilqgDdrtMInK6MYmOFB_d{!#iXK z#GKIobXjvmR*J#BA4@Czi*ON)3@}sX2C{g+hQ?SvG1&k@?;(34&Y6lvAaG1TU$w8Kbb9DtB1@Qo!J3)Bx(7U&WWl5Xk4yYN zm6!z7L5{ikKbRyC=$+Gt6W{(a5Qz0KIk>{>;PRa4sD0;)(#(7zP@9VuR>Ra-T_^az zV@31wr`=3PPz)V5hT)jizI~cwMc>Qdc2qrxnOlhQEg2sf<$i698;~`?Fxo#1w{R8uMvn!MM3ns?>9c&$x_Drwr~ar$;op zP*4eKm<`P+DIs13wUta(*RfV~QbHM(I5nSz>)*ijU!Pq$3pJy(vV=DDZd%(1SH<&Y zO<0WVUwoQk`0;7v|)P@P&LMo#K}su2;%5ocD$!14Fp==go+B{yw3Znee4 z^r;Ek8vnlulhN7OL$&!YjEZ#v$HQ~QUE|sK$BL``4(!`V8jDCBOvQHA+0=`lWJ_AO9TxZ)ohsEXJKOsjU-wubX>>nUR@bt23SqE8E z!aPc{)UgLjlh?p{A(w0R0Y;PrAM{zu=`nqHGYr}W85Pq-kNPELgKoC=I-lL?&Y4rs zG5zwi`e9=oS6}G(ld&XQ0$f{GUj7W`#$9`E($j;U^MMQVbvf45#oggGr40WgLGcQMvH%uz(=}>|$T^;Eg+I)7_3~CnIpi>P z`;U)NLZm?;G3dp$VID5S1Xz<{XRvo;XMfaI$9F!Lgu04ZL&+G*IS~@l&kStAxh#yq zkQ?Un7I^mTqnpY1`eX<&=%_W$_|TUTW0V+9=7XVyK=ao_#B_^0i}hzy9^nkN-IDVd zO204vY=<2B9<~jXfY|d>w^+Wd7l4OxPq` zykY~Ahxqg-s}R*|*fs9+XfAB5jT~%jt~mmWgr8B&?i+e=wknz)yfGKTgcBVsO_N}< zwC4}3WVopvgUfSL^EyZOg;q$rm{W)Kj(H&1Bf7Dl4QVI72a{Bz4TUIn__jueyVr9K zWfm{(nU$IF10M$V+~Z+cu4vI~5$)6q9DfJhSn(W|0N05wda)1}EHoX)K-gEVsG10! zvH2Ka^l~TIqL+cop-w|!f#?BQ4>w&d_ca1Z_^-F&=O0wy+S>$|L~RyR;pr|8JV<=F z)i2fxhKaH(e)YRJ57a?#hIz6}q2h~nysc5Iq!FunpzrW~(`zr%VaBU`!q_sLHvONp zK$Z}cp_+&leH>O$w!gL?M1rAEs3Kh$ig=k0eBuxwhYJ34Bg|9xYu8cK>jEqG#v*KQ z(nwa^&y1x0(Q}TmB+{_4w;p;~kL!)8-!H07&5K!#UvHkXCjV`XHNl@*0~%{efFO(IeY30)DV<7*W4etRqX+UU_1x zDakeGYNAd*A$^ykTHUmk+43mTiA^xN9lqSGy!U+>rB054zZmb{?(ID1~_Dv|t z2=JIf?cTf5s{{@V1`H8R@t!bQfHTu7$|cfj36#QYWv5s_%`6f)@N31r{eQSUqyI{T zkLe$~q|Xjfb;sg`AGnMl^=^!TY#`Z0Mxe$>Cp?>Z(i;&7mS;(5(^ssdBUKL$Q-mUy zN`+WlP3=3lW9ftaKHSx19NSuv3GU@H9cq1)!{;Uk4`3Q6?Y)*G_mN)Wy{8s;XF6s# zc|JeVv)5koRb3)CFm&_t6zea5Pj^kk7A@c?6PP1RZM4ZFvWL|rK0njjKGRYi%Mvu> zgvW$fIt8QEXG{4h$=iIwZA8(&U(Q8JffxP#Ww-6|$-jh5a8zH7tZT1bd7L!>xcI1Z z?7oV%vPD3+x>~_(jLdIea@H3iJRMi}NhlYt-GaYT5$D_`{gj3`j67nnEU5CvI(xJ} z>ncxhNzO9S-A-N^Yw^b(#cM++6J?7E6l~3*1ZOq{artO+)ET!@*QjZvS@pN$FK7aA4n zM7D=kFGcMpLL!q}yO|z`uWdVRB@l2d9iudJPg<>ok7Ptp{h}FHX7)WR2C|^I7C4_> z=_NsfI%Q?#?(@QCvA0C@y0E4=IZ2?t%AoJtpASg8*+g)c`bvl!NK+8FRx;gQqawqb zJB#qwLGKK|@kzwBEI*MUz4W;@4$$;A!Yx%-wnw;e0HNepC94VTxxER-K|=8Via8~P z_KYOlQ7oQ~s)}H3_^f$k9kv-^pVH%la$9#V+Mg(PIAuh<=O*Jk8igl2F68Ad-eqnA zu~ugS%Rk5~p-O1e|5}~Z?R^HCCg0Nv9v^}eFf*rZ+srSTXA;prH&fK<-J#Xs06&xb z++6nT%gJ4o3FO{8Ts)iy!Ei{a=gRl5XNxPIN%miG_;;9Fm)l^6&lZmq(MJ-9E242k zD^xAxZuvP@O8m;6D-{qUD-gZ?;{O1jdm$tlsA`rjX0$4oF^ua6gQ70B!?bMq>qMbk z-c%7>N3hH=ofV6tLjsD{;WzJeF$#PUVJsWWH$q6LE^VjH7z>-+ac{{%?tAUT^7(V- z0)G~)U%dLKI!0tH#|B=Xzi+;cW?_Fak%$D1cyrLodPWN&G7J70W87yPaKrWUAPAZX z9tPTUmWdK>RoQU_!(LfiDmI4Kvc*8U$Q-$6g6$ss0s=LiE?-!Bm7{JuQfCzWso3!J zEL9)P&Uo9$=p_vpCTgy~0!0z;7eLc}Ws zrdR~;TX*O8NwhLzeS@wpud@0>w85=k4Mm$w3uAxJ&f%e{l?a_8px&U(=l2`l#!&W_ z8L5LeDBrItlUNIe@$}}iCH@(ePjWuC3-tKeE-r8vE>?MSTUz{)&I% zA^WM}?H7)to8%$0okuF+Pv1E3{1NRs+8&m)W54iyZc#519m$`r9%z}}Iiy`SAO!=olg`Zh&!m`4u$Oy-kEqa9^G3-x>k1LiMQNK=DaN3mrJ zY15Aw(Mx^FrWbzY$XH~*?)sD!*~yn|z_`Ub%jOiOf-aapU`VwW3_gI_B;j#(!MlC7 z^mVQ!H_D{k8!s>vbep2Aq0tKzJm?76n>S%Q<9W(zF7Fr|%?xDxz8l*RxcS)?CB47# zLL9kbaOOXf$mibn4ClaO!0dYi8XHcEgF3n=X8)srgM64K{cXD51M2h=Ev#TW6D+B!t~6{W?;tg9t=j>o~KMqs6eN`$jH2o zKM$XP8N71$GgGL_)pEUt>T`c0Vbgpu^&_%Hz#IYTrCgcR))da)!yFTC(?ScAr4F=LL0Q8 z1B=!M1hoOEZVzT5!DzCmOz^}dEDlAT&@`>t@oj_gTVf(qmu>AOGlmyG#SZ01wiqUb zG9x(T1~Xz0RZK#Gqc{;7#k>ls)#`KMeqib}&(}8ug`Wz3feY;qf)REX{B|?G33u0? zmOLWZkFUIKR~RTbW;=My(%yNfLF#kl3`Hj%JZ=Z1QaSrXpy~@ND=Qi)e*#bu6ciLz z1Zu!s+wb4Mo7$1vz+@RK0opI^`mv*j|09Q)t0%$y7ROSt#oNeHB`Rq%4k18wyWihN zhA4;3jVddTwycBfXRjTG5YD3<1cS~6$E6WOzXS_rtJGw;nTyAcw~1oJ)LGt|1J*uz zjLc9;VT{$?rlAx~S%2NB`;$sS+D=Kn2$8O!pa6`Z@V)t16#^ZW&yk6D0K=#2E{!m~ zLqjw)G~HWCV4m~Ut5@L1OV44T9Rs1JnGDRr7YpoXqwd3rc-ITwkSlUdW^ctD5HF3! z%xf@7wRaa_y0!$2N*Wd0IH9wJp1}mjR1QicYA{e}8`84*^s9_6ealQMqmCfn#v9VRY z-wjzrXCz_!uN>yh@#XIgH-Wk0(MbKM4d1-T?Pz&w8}Y=@%O-4pkz14c1r1)=F1r>V z(1x3z7?E2k2KGPAUfk*d!~MiIwq_7m{o;g952q>+NcX-IzwN|MqS@&5F^=1haj+gIV`zCWI~18d({ISj5Tmo>hQi ze3Z)0IqF}jDdlKc%rx>z#U=SvI2~6+! zgK4nV9Qj3e_^aTICGDv#tkSu=is{UgDTLHSvC^O>6NNHZX;(4H(^boX=L!uv2XT=C zmFwM1AmMaHsNIr6$usVmAeA=KCd+aM2d>3>;6NIC^7$GM9(3QYgk9h6z2FEvjnw0i zhP@RYAlyyymVnn!%6(fSQzL95$A_r_KDKjWF1K@6MA<^I^l?q-sxz@*sS4rGzLcYs zpTjQ;GsWEVA!Gf(h-~Tg^gZ@%M-F|z->M1~9alt-1a*HVYu0H@GoeKylf-Lp+o{5O zwo4)7d1i$1=X|o33=q|09NEWx&Umk!h`3QSgKQQLh6EkH(9>b(@AAwc0y3$UN6kUg zvmOP%t>c2{Y=42fj_9BHiL@rh816#eB6unTi>^wAb|c#nF!T$s>Lv8Zui{{1{Qh@h z3a<)~6T`wr3+z4tE}46KYA#N9TfI6&qRir^tx$#GBp-~X1^8q?RB@vThC%1UnrEkF zGZduZyH^U^q(pIOcs=>lzb_Tqr@rSlF_dL~h;sNc&*QwQ_BqC6r^o`&Zc3Ohm-Z0y zK6*}LhL`PKggP)+xjmm$_-x;OdD};KUTQ>heq5yI2iQ|SpA5^cX%HTd$IoV@p z5SOkzV$FmiD{B5cA1k;tZ%WYR3pHdZ`Z<$T-7-yJozEZVyi%|eq6m#cp&4Z3{M)~8GG-ID^0(5Yr z3KcNhmRuhOvd;Za(dgzEhv0ykJo>8SEuC(jM-d@x{^;siszuT9!6=zQttQ3lebBVK zqrCCuUkyMhiTq>Qf3zi(y`iDqadQe6ddN6&zQC>HNJbGojla`1VhLzR`C{3wGs(IR zR<(DE7+e`pY@YPH;%d)S3fEAk;Ckl`<6WZCI=**yxIjq%Z<7|q?O>Cm3d$nVUg#N> zZ@!>xSwY6XJ-P93PltpUiK%6bJ|9Zp`1gX|* zaZ61Sh1Qt$FKh#MfvK6gpFSc!izAZy@xkZiiNJYs?l;#db!8X=>Z`xped;A~bsRX3 zzQ`quUM_WE_64*dH}2{Xthg(fL!$VjFH;&E&UE4MfTuVX3?TI2m30T?Dk>nCJ{9`3 zF2B6v%*|K|E(*TWc9k@h|M(f6u9yml_rH|5E&^hBZMSqJBVPN%D>L2I`0jZsu=!Do z%Th>FiU8Orb|U#URm4kU$_FVenWA(26jpYy=5@#X-6^%uT~$x^nK?|f=NQW0qG{=* z-EoC4aq*5N2;`aD9UWghcM~WlUKpMPaS~?&S;e$yrnJy!9vi}~0sFL+kFiL0g@KvDd^;Y438~bbSO(aOiAK$Ecq9K66UDtM%ky}6p+hdyFYt^9$&Cv|<;d2IG z5n=ryZh|`5bJ_MEk3DGMO9OnSx%Q>Cm2(|XJ0v7~*3`&hq+b()dZKA@*X*-|z0qI2 zuIWN~3?Gz9jAfh;nHG(JyVHMW4#XlUaKev0fJshzHk*W*K4DYSBy?z96%s>k<<_ys zz(!&GeYc(_A{kh%(|ja>&4gfu8TCESr%pFj_bDA@L_r%j|6=^u!|&MF;64=>eD8fXx>IT(>>rYn@79+-Z;z|m z4^i?|k{cswtk1c(EyjaQzHxTr7ZS4LBwO%8VNToI3^>C$x#zJsI}!4k?5$17uV}m= znz_^McnN>$Ux7w9JK6$=4<^-0<}yv?2Uar(PqtZ(@Ht+-Wn7cF{dlIbh~qm=7%)*0 zIgnOGgsd>)kLi>v>A4!Wp z^PbzlCXTqaeuZADw=f!YaGV>T;9sUL5Z+OArf)4yu6HD&UuNouT5rL)+G1x^XF!YaS#O9hFU>S$@nKWiMPf9zfxE z>7X?s@$RGc$kuMqv?_i9SDcHGROMP7z>Od5aDkDqVi0r)(QA4^19_aJaD zO8nPkCA7^{yve>zi>ZnPqv?RQE}Bkomh(!XLO)-A5-p+(hoS8I50Sc%X69#(8XbEn zJV4)_%6B1iaRu6)R^^4#{1C(Bn{SHaH!hLl9`?*3Lh7k8C%L!crNhLEjie1NtE@n+ zDbDj^jnm`rR#& z*X)Q7y%sN7RM@rPTM()1T_ngw4UN%rbIR2@J6C)w#TUCHV)jp+CJ|d_V~!d=SPK`H z=4u-O)Y6PcA)FL2(w@j<$T01l3E%3h!#-BHd(?}o-cwr)jwfbYWE1!O(9oK+bN!c+ z8u-)+Uz7y-VX-7YRAYR!PFE7X1#@`uPm9RdDS_ zX+W*aJY|miiO;dlJyy=@`%t@5xGSet<`Ktk$^%(}F2)5RVDp7ucm75;0c2BNb zfQO@ombSGlo>#q$nAq0p_4G}(AgpCNzThN;#mUTlarsocI%tKgU@y#p0}$N) zKBZov>G_-T48jp-w>7gkg1h!Rq z(1!vM!gP1)!|vKnowEF90#63ZYueXA-Q!N^x)D znh4X6P?}#UM47+a0IBFIYp*aTq-Y{}<+h9InnR+)G=FWW&iBmZ#BE9q&DxEgNE4T4 z3^i-sb3z~jiVOesNo9U??3}sPbo4>>8W$FXU#tX0jyGrUfO{QI!6vZcwiomM6EEaRq5K$&=#y&%Rd_WJ#rPqIK&qg_gs8RDlAZ{c+YqR6%ct` ztEIz=Ym2WB(4F7UeygXxRbHa6`~EO_BD+LG(>eFo-u@oA!22D-FX*OnyW{`Vncv)T z>Pm@&VtG681WrCPdF54ha;qsDK37S$(PS1|JH$M{zT$ z2C5|2rL2`H4q3e3m(8o<+&_|EYqbcIsjB7Yl7N-yYO79GI=7loNPbHMG=@F8;7>;? zL<*IE$j%+EE;P{Z!|T;sI$mpgN4H412uzceQ%Isvh48`UsAg?T%{*4kG7M><1H|Cy zt#;SqdH@XQm;LLVqGgLT;Qcd{qGR4Y5Yhn7!QKg*(72{%;h2ujYUZD`ADT~|!H};P zgA*WBCP~q2XI~yeDOXySb75IDkjs( z@!C%C^@;Vz&1wxPP~l^ZRR;Dw@~b zZwZ&VTn(5#+2^9aA<2X)-<6tR7%J!XFMvPSt`sPKE%&IdJ>BE-)Hlfu>RMTgw14s+ zF~H(j+IpJ}qh$E4-tBvG>}obE(T2RKXLPB{YZ=fizPIebGP}|_{938?QVyLc49n-0 ze%sIZ6T5?&^;*t0n=?(USolMSnJbYF+PA?0jTM{*YPaX$9kZofMR#l_dEu*zulr1P z!`F%xpR#Lt$Ur-$k$P|3nM2E32*#@XKwy`YIU^f!gal;l|CQmiKVEArG`7G#Sgz=+N|_lTqlK+%a$4^c##l54GVH754HvN>=RM z+r)ZYpQN)F-Yvm@guHn8sHMH#Yq_pUDt*#@Nm2<;;1Z|Fpgv5L_c17=0XM#pUHsX> zW^@_#$QFuiy(ifaaap(U4Dtb==_;6RH+#;h^zdC}!?A~+SMf71Ax1ctE0yq3=p;|$ z)2!WmxhcF%7?6n)#~%T44;kuJ&Nhu-lsiJ}O?q>^Tr(Hsd*a)pA0D(6e_cP7b9??S zg$f;p?>jtQ>X%sz16omMK?)i!%%2l3e7ZSNFWqx)VH{1{DTL-D7@t?~{VJk1P(z}~ z;AC~l`!fl*K;ceGuUb83PjE4Nx>d#*lDw+*2$pAb4q@APi9RsF)sdFZ>=65%LIF=Fa zRZq)~s}^g9srETh2toF)>Q@X(U;%8bd>=ZCKP=mm{2mQJ13lslufEm9;)g8YmR*6e za*BEYujB_xB_LwO<~r6GU!}vGxmOc6EG~`J2Ik)-6SJ(~9n~1tBK{x?e8#7LlLosW z0;iJ7Fq%mvykjMbP)HW`O)M-T;B`63c-`G{;ZWbB+`*1eG^4JpEMBo?>j?^& znOCyU=Vav+!L5c*lb@z@vOudcvG<;c$MQ{Mh(`Xungp`1a2~B`tSkSXJF_Dz@V*Q{ zekBgaJE3yiGwvihz?*!^F38OdZ#bmV(S%`O>(W0>zqx(NwxUY^O&JoY9`aB#vfI(N(GISQhsBE&n~`< zP$<}c&lj%CtC1gO>*qjOw}lPBm97yvj1HPk>S$9|y%XEDaMK1H<#mr5-FyyFdDc?L z;Ef`Xv9+;k{Kx&dgj+x9qjVj7t{0lTpuH?sR=t|C1)n6S6Od?n{^CF!__`!pKK6C4 za6Z%8+;bKxr5?qclYu13ZO=Gf+u>vd<Y`8zv2KLmADDg=xR3PPg1xX zF}bpqS@)!D`?#hIBRL!hn$tn4<1a{h9k``H3nvesJOZGhnMvrgJ4riJoD6rj`wzHX zzID&05Vg^2bXOQIm-Bke717H<3&`2N5d)B|xzrM|b_*aa7wsl0D?O8+xSX$N+Z6Li zJ|n-mTJpE9_gR|1iP74%ilGS2j)8!WQIo;^ptIX_kcQRf)R2%^k4pdGcDtN4#8ZX! z=ZdRoiU@UxpH5?(MIHRjl7^THft4B9&&|zzj*m4;l&zxKt&EY$*^h{$d15nmN7SsJ z2OFI~gj{UXeua`bGgFi=$E+5)oyzO72|DRTC+YjFSndofpLHIwP0@FQC(Dulu<;t6 z1It`mFsKgV4CaH`i{!JF)Va=?o;BSzZ2iEWFTI&wCPP5Cn<%{Xb7*amcxjdqNJ_J_ z!G%oSafzMq?Z3)*gLew_*iqJO)hvr6!oRovTCIj@-wo#U&AFujKyaAr2B$)-VA~6c z#PHQE1oIh8Xy5~z-!FjtT_%2~ZOY!3GCpzCCH}EqX~*Gg@yC7*akDw#a;d4KS+^qF zO!);XK~XI1(s^~#MoV)Vl1Gc3*Zn_43(;ssxrU0YX7!s z8Cchde=koG>KRnO@o;_^i1~$`F(8NnKTXUDlzOtB$pxcM+J+FX;!9mXe=K z{nRLHl(UKwXRD+GxqBQx{y3OlNRRhW$m0x;vGw zLzjRwNOw1qf`oKP9a^MYq)U+Q?(XJY-1qZ*-#gy_WDGg%v)9^tUF({2{+2^=enu+V zXP(tu*_10e{jO=Z2oAh<|D}>!RT(IwzrXS@pC$Sv%#$D5rzVFU-~nO!iw;Hb^`CVW zq{S>RKY)2WRx*R$Js9{nTEKogvUYFbBe6=~4b!&D1H&7%%BgP@6hRMm0k>Q3N~X7OO+oH1I5ZUJ_3LiXj$~j;cw|%f+2v73n&;(CAw@S< zP+hIOmW8aSfm+>2>^gkaW=&TVYxPE}Isc&t^#96=p)hEg0Stq>XQmKZ?@FnmOu?5= zf(0-f=UInOxBWH~DO@)0)paiiT-PqAR$=m+o6~`5`vjnG7LHCp-ZAwVYXFcP(TPl& zI3Q8sv6T@9%-kY}Kx&!>(YYm`D^f%66GV~6Yihu^*sE&$l1b%ldT_Zy^1Jl-uRC6N z^Do&o(ZQn*qkwqkxI2kXYYelCPQ7~B2YX-x)%@Y5p1;3qT=@q^`5;t;S*4>7@>PVD z+k)e~h3M^9j0!i+;)0TwCKMD!Gjri!fbOgv{GVlqvp={>_B;8>+`I*Q{O_8N;eh{^ z70?sdfC#Xj;kHQ0!SPSv-*bRqY;5d$OXR7q-eD~T1dE^P62R+C3Ftt;tJ=t=7A~7o z#sC`|Ie^qzk3ec3-JQpj_xDb(Y3HB4Okw3re|RS2R0_yq3THWVbaf_1w<^S z(mm-R3!rgP$tT{kU6Mn`eSW`sn$jc_OrJuIQuqSYJ6mVE*iajuL;AARpyz0nt1EW` zozkVSS=}5+FOUo*15@qI=|*r!hyyUw0`d?Tcch>IaHnruK7$Yg4GoPjxsb-T5y~zy z9`Yz>BC9p~_S@N#uNp29w>d6+Mn`SL1|^oe$aSVAI!$<>xBLf^>$roik(huCyjYPt zjLq)6hmha!vLD-RjZlvLTFe4_6Iyzr|3?X`BcAdRHt%PR3hfpr7}e0>673t-xa%@8 zF#(R7=;#Zwf&bBU+(8fx`1lu{VmJYqXWzByikgkBiYsiPhCm)$g?N7A8yf|juZXk{ z|5hQ4?Cqd>mZ?wPq9sY6MUX$mg@nO@MHWyI{+x`tKnUlw(?nG7{&vc7LFb7IL+rN3 zD#jwj6}T z4k8UlTi_N63A{($EkUctD+`Mgn|EOMZombKoziE%0J_y-RS)_mgOJe?k3D#I?X_`q z*$&2V0o?--(heUkwTWfyHjUyqa!dm_4S>QMMg$a^YBbSWAs4&h#x3j8@;Kvb9_bVw9?MEeWZ{-b|J0J>b2rG9MhHQ4h;7fbAEsrWUe%xV4j znAm0EU(SMAX@sUdVQnHRe5a>utA@JXR{CKmvx~lcd;_FovaMVBNPGn`#o{>ba z@bQ5|p6G}VWGuVaPFU^c>nBMRugoHpMQkPzmy1_^EgsM1K)){siG(RH)LrWTS-fih zK6iZUPf=4{Xq5jHtOIsQ)WG+fay)MQtnoJq>-CIJX|k>qcRe!I?()AX59pV`c6Ybj ztQg=tW#qh_JN^Fhf^s@cVt?i_t8$eB;R^AtlG{@%m-$&v{{Q78<%lW(J23%CZHv_I zQtfJYkP*2Ck?)y$2Wo&25&{G;J;y#87<5wpZ$NjpYuI=__U|9ykr2AgJ0OFI6Bqa& zWjC{pZIvHud^|B>kN;Xix%*?pqy0=X;V*I9)exHu&J2mWCgsZdUY91t^oWPMegzEz z!lQDUffZfNH*+iJh8nHj6*|MU7pE+m??l||H~S26GdqkCkQNW!c0yAfMKv3|q@DKK zC`Qe6NU}=}T2e>zWH>;E2L@oMo>iu2+73)Tu(3Zo>>B_hh;QSY8a)#eH8V3t$%Xyt zCPmFd4VvfBYvfF7r&V;a z<{RyR%1<8Ui`5x`1!=fTcsjI|In48J(@8$?se;x3Gn1_mn5tmlSBtiM><5Z}oX7e% zXF>dN*#8Q6osPdF0(#gVo&IaPb`TOk3rR50h=#E{|-Q;|2a+_Y@x=?$Yj`x^<}b{xeHi{ zHU+PHDt6O*)-vhFwP1q|kIB>B^%!N|t-e83Yy>8(MtEyZ$*54M_wjff0oqk26fWAM z4I%EkeKP+$CJYi^&l3xz8W*Mi+`*!mPaE(qy_#J@dr7WVg2z2wM0WaXf#F=~)`qB6 z36wTJp3>Awf|q^c3FbmTy{sP`U8ImAgwh^O{ZT&sdB3t!BQa`XRdRRejwm>RQNe>) zLS=u$WU3j9ovXmvRO;Q!f@g$4R_=Du%|D$|_|gixIy$`t`CQd)m053gOuu zjEa-(j4#b3nVHK^H1+KxXZt_%y%Y@o$ScdY$MeurWk#&ukFoblos)9R7wd&3^RK}J zC^f{$B*KT2XA(40o*^W4JTL3gon>rD*R75YZ+DT!QMk8zl@9dbaaCt+@bPqFA9llj zu3~TV!&5C|nM|mT%p2OQU$shPxGnoBCxH_DGi+V7a$_|qGE49_L+V>5zYA8?JnrK5 zAKcf++sEz3km1Mk$^$*ZOr)14lvd48bVdCTKDw_a_n!q`>q{roySz&+F8^)Q<$EDv z6}@qlw=$s5uY1O|X+t!ybeE2F)7Bo7{PCOvV_+E>A*drK$+NTys#6Bq?Nn`_Hts?` z4(h{60c~R1>u`?P2$CeNEQ)cq`uOFwQBXkL4VJJV%Y?~WyZBVL*ZQd-_{fulf+B(n zjqF(aZ5nJoJjrIoZ+JNNo@22X+M9F`7?gF_7RGE~J2GI1`n-}GqKtBI(t~-VJG6*I zc34wA0;}{+GoY7zZ85u!4=cVLS?=3Yn#O)u+?xq(WoHj?$7C))V$YK^V#2TrZrb;( zh52C?R8HCMCiol`rzcQbA|=}IO(W3g&RPBy4<{>W)H;}D(`v3s-A!_3wB}T-Ir^w` zEnX8$>gP*+WnU!u)LXUtB$W)>*lwnr66<|dH{B4pc6}2UB&qFnO)J5l7xE~?`L1XC z?p=Q3rK1H_CF>PM%&velXWPCeeDBrmTEEcem1fjMiIG+nTDX?^$B45dTj0UXaB5+B zP+d3X0rCw`AMB_XAj;$@hY@M(E~24QB1J= z9sb=@L_RA!;cadDcHTFh|9s2vcb`(dl+VvC=AuD6_m+ZULn4|vh?ESNq6&$8$|>dX zC(%}#u`*#^ZBz7amgzW+vBXruVB7h3kLu~lUNf+#xc_a+{jXDO{UmVp-x;(X{(7b> ztHHKs6mFwOj59b}-Fw{eZRb#{_pFh=f!vhCBc9Nld%-!g0-BV8J-JRj?XcRQZXq2CR0hoXA z#huB^ReSXdT#v??3NHPuKl;Q-hxc{;tBTDdlxKC-n~k27EHw9qMja zgRuwGj7u_#RSj8EkHMQ%V zFLtaf&Fy|$|4Dm6v7?jaunZfH)jbLauY{p1MWWK!}1?*m!rv$&- z(NUWf@bj!4bmJP^qADj=#Lt=TRbl7Skfi0f=jpJQXAn9}w(lQt>XAh|QS&%iZu4OC zqkBGdKM6VW@K#fLze2dQ>gkBQ1TK6foaq--(m@=^f?P23oM?)BWop`aY+etNR=*Wh z5$9_khP-016oT4)m#2|J+G_WXL$LL=K5@S)RsT>18?YFbrJqw(CQ3b~*OkC__BZM^ zfw$(rCRez-_d^L}qHy0bY40T=b3ba)Tg8IRX?KECTzrQ{-OE-VJ6k+4z4xEUq+e*| z=GfzXJFuou1I+;4&&pjZ+JWG>8Dn{fr zzPh?dGv5HCR!xM-^WSp76wM(WJ`1abiWUt0u<ztf9orR~(D2Fc1VbHZ-cwF4M%wLoR6lW2p9LGq{9?sqo*g})UI%F9_-Uagx z>LYrH6zd0Fq~4R#2goEr3FDe@UfUZlyM_zn8V?`)kuSh+Ah!#{iO0{Gtmh_x&;s2H zMU8_#CM?g$>WoQZu+<@LHSdCX%skVD$&~ZXw9kY0-)B!bacQCGA}aGG+<5#EKMgXu zY2^}Pp0*5kZ;s;Sqmd79HS&Jxm_!Lh&QUKax3nTXww`!F%mSHT=PG`6ycCMMpE~U0 zRJf?D?7AED9V9E{5Y#E0&p*){uCXcEmxwA3FZ66f-`*a7t$zDKpm`p5Tyuf?2>)p= zAp~0}jOXZ0N17Ylv2kPftW7kw8pgZsrwAB@unso~QEL5gYsPWR>>@Rvq;Sa*pw26q zqp678UnF@BN?$L~*Oc@Gecj_AE1bn`Z@9#hkG@8N`ET%JaQ4nZ8t(@$xA^F7j5`e& ztM>1Or;1S;S=q)nVnEZmy)yJ{lg;JRyqG~HUU?F3l!3Hj60>A{@dCxypORqJr zpGdR2+)TE&&T6M{sU~`TpT>?0&jHD5O+>EsPeowQ&7Kw;^nHrnYJ zI&>`0qy$P)yyvTkBkoL$hYU$}N?4#55%voXB~_ zihgDh^ZAXAq8Y)+w(JT`|EiNeVK0*^U88H_IBr)k_f+QTj*&X!PNSvyeK($rPto-N z<#~kVJFJS4vuDMu*zdhthVSsb2wvx#iN98VOhVf;x`?!#TWXG|!ALn^Ob|ITPdug# z-Zl_q0n3q@^6tgVs0-MgM7Ll@8w4Z@5}(m=4#7wqT6)V>9ftP9LosA}{arm_bAd@- ziu2Vt*6$vF4qQPl0t|Z{s%Eb$#*ntA>Gn><*c@w(nlkq%KjOAzW>_m(>&W`VnmIX8 zO0wyP-2-SgRN)JkCss=xVe549%j})z@jZv%aQ)dw6Gr5d*AI-Cfn{~6U5N$)a3I?! zl8W?|PRt%heg90D+R3qJa2fG@A}ERZOgx z7-aU<8`v9u(b@f8ZAYJ0stHRreVeXxdLqLC)&9O3y^EjvW(aMx2124LS0|k|!flk* zoUko4PjZWt@_RgK)sy2bsDin4i5=oSIjAL>QI#dv;Jk`&=^-A_1dB3Vna=e$8CG@O zQDy(^Q;>jCW8*bE_pcDxU`ngv+EnAsLbm&%r1jN)rZ=!yFEIaj38e4w&tLiIFGeJo z=aGy5<4klj#{7Kmi+4v+-}gg?)3~%o*NQ$jXi+n? zIFDUgq@eRxoTrwYD&Fdq#TyW>4T4~mWUS_Agz?%bZIq`< zAX6fgCordm@(3xcNTxl-x>oGEQ<0Pu#|dBOt1XY$+dh$`>lDqprk@;jADOd)JTJW- zJg9v-UjU{^LO)5bzO0=Tbv30wED!lb8+lsJ7v_$sVjhlYhr|hPIC)q(Nn&&@XON~0 z-{c4>GUY~xW_U8Ep*|kLWw1sLhkA3we!EvVcq4p`y8bYB{Qws@(Nxs@>1VYJP!b_< z4RYYUAn(4`@yF2fA)})f{s*5beMD>N$(@IlRY_MSN=}fjPkpWzz#9FMw->1){ri2b z`hu73m4UEQPxg-Yx0gM4x8xH6r0<}^KccH7p;Sr@B2d|QunKkP=lik@TuIpDnBa1P z7c!^!9>D{x4XUP$ubealZshf1*R+9x4PN4sbAdW>2_C3Hz_M@*nKZ_J>=|8%8vi+lq3rII0qVW4$fqCsWZ+t7fDq-L`K6q zp0@6}k9BP~6z|>$%Y^j&w)G-kT|^Cd6iAmiNHR{_H6y{ER(vPv{OS2`aimVD#?rts za`<2_a3it2pLFoxw3|Ee`uQsW>T`REpQ;#&v5TBI!}#8kG3BNBFJ}EPV3|EH*|jmK zhk1zwVWfEe!HNC%R=OV*WMKC6o|3dbHq6%#uOJyns<*~QlrD!dGA zs7W--TJT_8n$XLc%;gb+Eg$PXBE&{W(&8G@tFZB%EqDu*)=4^E*j`uO?k;DSg! z=qM$f)bT_wsV_com9^9anm%T(4tK;MeTEwoh>OfWoM^3A#zo&PCg?L@Ae1t7Si zy;a!bb@~RO+Xmp#?-_Yra;jq0PmDnJFSOHz8Zao$4w?hX4%whz)+Y;zD>z?3L%c*S zY@@%C)(i1F;oEgA87nTBfPZ}5AfwdjhvWw0nkyc}WOV+cjA2Z93<=GXH8Bbgx^cM5 zv9wStDmc-}j_3tpK9y0^ZEO0z3j3tt|f z-lBu<44>Y`d`FDeS3Un{NP9$Wr>Z>%bc|PYX`A!d zE;!)be5{Rj&5@QEOmyMgp?yNrl40wfj&j6U#=+PZ^(Esm4P&I(^KD`#Z9RTt*E{~9 z%`bN=k-9OEcXc4HSiRs7@d`~oA(!^>6DRQMfJ6pLdP z!o#8};Klta)ZXp!4EUufrOtK=KOgheb$oL$A~zmXST7yN1v}o+xKA>1+g}B_;_j+v z+3?57(P^_fKbMBp@j$+aL=`e1j;h^yd}Ng z(P8jJSqvua7M!eG=ofNly%hN@`JacseI&pb+B>2Y2$YQd;Wd6(9|*Ck8-7W%^HIW4t{+`?-ev+Taw%m z$?+5mvS=cwZXXe=H`9#LbRDjjis8`*MJht;+ljKAR`)eF4Fw8jT$D|pN7q>&krt5& zvcjoWIkNJAS$`vk0c1w)s)oTDk!IWFa34%SC1CM)lB&6;xzmSzT85sT~X?-Hx2KX62w@1 zB6fsAtKe}`g`D8xGF7JcNyPw$aj3NdyQlwP6nHD%)Qx|T57&X(^j)2+?C`&OMDu9# zr-6!{T2&5lhoV(pGMk_kjFiquQeg zquaT3Cr(nrjj9ZIvVhtTr%{p!s6x-!Ex z0)ePQNDUaDDNtUS+oprA7X!>^a`v0I>V+gzau3D>EXbtrJf?!(Q}9R2r^n>HTBJQM z_@=P&(M=xC@i>rD-V!=OzZT) z!M~4Uiis`7SgZ?RrWPqazepXkrr40e0_eKwJ4&_{3UGuKe0jbQj zY2of`%Jlp1&Z9TL1~qQE?C8IDJjap;OD2?O2i5AyPpdbbTI#K+a?;#K)+0T^a8jHi zK05ixTC#u~!wiN0*>uw(3BJTHXPG!`<_VStWhr6`HwJ(((9@{Z!Y!;PWao_RmO`{uO;UMmx z5CMZ9^R^p(ixu%ilaeN4%1u~-@$FSF9h11<_u39VCwC4si0)iG-wFfN!s`jY zdi1GM%>J-d_}h1I*aNO^4l#|~TKRnFs706H2S_FUZ-8O#Kcn9RRdC7yxRPOGRwV9i zc@W1#a`&h~YtJG$$J_cYtg(gZCrLBP-35U=bc7tySGo=K&`NUDc*gHP6C6RZczdqy z9dJc}lVynTzigqW5>6bmdO+8@WNlzudxTd5>sGv`Ko+V*N;5ZlrEN<3ar&6ztq#CU)*i z+oTtex>A#0HyDbqZNm6OphqW737YoNpM))Fc~@4DnhuBnx`YQ^1-ykPe>$L!ikAro zIUX;IJs&&*j?QQ}?PrRJiZTVELO|SR=zfNAKEvBVqBosmm^TQ>^Uu`nNwU!G(mXxjF?~p+#x!o92_I-mAxU}sDG#PpMDl}P?!WMD@6I!Q8gm__#c(ao%Oz33osb&?@ zURmL;7NOJD2#xBOn+XIW7cB^13=+V9n&1a`vg@;e9W8rD8pF;@e52ldq=OY70_NRJ z8Ub~fS3DnFiNh6l>K$_g?dbJf>c#h8N=?IXZ*?dbTBz4^D#kLe<{!_Y{GE@pR|yig z@#Q-kPx~^>@v!*|WmE%{#H2m1(AjVyW2IS+*QrQX8BlO* zZ}x9*87Tox6>Nwm>loixz2EU1y&2ySuL9;s_Xm|v z_lD=TTIdtl0;utyg+0k4N)W6_u${OOu0GFP2lFZdk`;dv7n<>iDhF92MhU7l(Y;6D z@UInqexhou`Jt(pleh=weP8{uXr3-?7)to;dl=J#8y`%{Mv^+UgK>uU$hv_`%cka( z^19h7>*EB3DjmcQbuTUGH4`(C7ezi>Gkr} z16qI&kuwd_Gz39SL~ZCPREGD)tzxc<_zR?xZ9TIfSw?JV_?x-tGz!G@#G)e#+g7x7 zPjU;JU+aO&d9&ECU53@-czlMxjj%{9kGS6FDeJw{kM<6wk4wlhZEa@$*`|rCX*XOT z;T?oeDM?)7DmuvnMTRK*wc#1M;dhKHah)=8hDz~z)Lk7+*LYXP`sZL3<&P9>+a=<^ zW*6nU6P&#f|Me1l(XDJtYzG|4%pb1k*E=O9ob5})Dq>&cckQ!joO zuF+A`&pi;#FMm~q}oxE#H1SV~hyX2NJr^G(ta z7uxla4|~dp>r>ny3gNAqAX(ksuug&7_-VKqc6d8lA$CTmulduDW)B| zWY{kaFUau$k>P21}<;1&1=T;xr=h$Pc zztiOK6>GWAtQAHsztgj&A;a5PKL{2;q1JW5B0sS>3rv8DC*I-l+-yI%2V2lR-_$;m zg54y53dOs_+=>|o}b$8e^CfizH{=d)GL9P zHe-ES&XuXMkhLEc8L0E5f;>R}HqI`XZvJkmA(j*eykj2?DW56z4 zO@bm3%ojyTM=*OnMXUT9LVBT2a_;p-ET}C#-)SI%apvNrRM&%H%j(>Roa^%o_9E?X zaj;fj1kRY~XBhgbbJu`;nZYk*t$vgy9hg9Kr~a~*J-NHM>QgiBlNVlkFeXH(1dhl~ z#4fvlBwZVu50gq-4qkM$7&J-v>p+ywjXRr1$5i3pa?S~Vbx-l4kl#Q2+FXCY=2EoE07oSzfeD1q4kI`bcOj&Xcg?I>VR;;;M$x;za*~D7 zoasl{b%?!r!Vb%o$a>8Jfz&dj7A#h2;1`!yvdGw;mO4wkww1r~Hz|>w1vBBeT^c^r z?{lzBlGV1weZgnpkX+7$HDcjuQW~dp*2-L%}dH%uQ?05 zAx&z@lCOM1qb|W&D5Hg9kWATq0dZhyKaS}Z@#V_Sn;gSW&iu{gwW*TQM9M9M#DzEH z#geDc63HwA6ZSgLByBxEd{PsV?J0>@s*dqQG_$C?79jF&qPe3_Kd6qC=hzi59b}mT zk2VqL8j1TaMYsKD#ch7p7&se%30yAmkK*)II7tc4o!+NK3CpIB-BU!`pJWVvRF@lL zCm;DH!F%vkK8n@k|Kvl5WyES%%k#WmfB3O@fHq1b>(-g`Zu|)u3y?XM{xRwu-&Jrf zF8s*JIoqz>n73^(+^D{6m1H&~%dd->gCD^1)T*RR-iUcK&z5k1dHgb$<3DCC=C}WA z)&dZTgYA{@%gy3|X9NHmoYxvR0^3SPgH3x@*pJU^6~YmR(%P?C*k)5V`b%qo%5Bv0iyhqxQRr0XjjqMDym^z|5I_$2Oja& zPclA@zZO`pWTHz?J4arAu44zLQPr@4B+t>-=ehzk=%-9jlp}mzLO(0r1~7u&$UQQh zJNZZn>Q=vy(usndpVk%3Hyi6mr&MuBNBvJB`)#KQo65be%iKJ^Gf3ZUb5_SIq=1NM zB)X z+o|ZV*c`CGWfFAt{+7yxO7HRty|$aX!hY&ajcR@TSaZ3wzr|TxeBD^q+aUMgYVbN2 zb|LRH1=9zUrir57F98ziCk&JPpt)vLEWM=6lZEb)o*?)_-76Fq=;wy9zYkP6=oq6e zF#>nR_ZnW*EnmLRX6B~@i_+95R>P- z7u>Px{xmKKQ7_B%MtNk46La2l5m=V^%Q=YaFk zVa6?|^J*YvK2Ma=_y@Fq9`|(7SZHc9x_Bc?3ra6l98i$%TW>BX^d z-Z*r$a?m?;us(TbjGHc<(b07jYHpub?~yomIo_0;-*{J$`nCWASIvGO^H;`zTJNlW zwq7MosSU}IyuF$w9`ClF91Sa;Ub61nLHL{Vp=j!q4a=qzOK&Qt*jjN$H|k{} zT+^!?+qtUt?USoYV=DlZu9HEZ{8Flf1gaIoQke=tDFdauAeW=$$WvF|&w_EJYq1#o!xF6SZ9 zg~_h$Dq$hh`4Kcm@=#T%bwrfmNBI_PbbQ!hsiYAVhw|_Ok{Ta7FD(7(SqgSW^xKp0 z!vQt;8z%KKTsip!7rNbj#=yC@$!V1$KvNZRIAYHmK|`k#gc0-65k^|TNYq|-5bwnf zCxEXtqZRlvTv7n{g=doc+gr#0AFPa$?1L-TeBJv_mHd~+lO7+Zx8zTo%Q2;+LMW@% zJKHx;>(x)%vxTiTf7C`4faoshz?$;iAN?Km2X6N)a$e%R97K*_aS}T1)t7KqOv9N4 zW}K&fDjk6|Kl|j6f;-LICOq6xL4DZEF~bvQ;0vdeEYzLTTdXdnXlw(guvv5cHwyZr zwFyVIR=mrghKbsHU1iBKQn7a}^ryaZrOwc>wlM|gN>MVTVWpzYqPf8U5k4;$>d`PF zcspJShyM37(HnzueixqPCRv(4q3Hh8AB<|fu=34caTBHcf5!OsZN0z`DEaiy!^bm} zo#dH20+S4%-XPQR<}bpC!lcKp4Hj+C@Yq;FgME(^FXmg5r`_c5=SPfVt~|aiR)a_{ zT#KIEyp(mnN+3b+1Mdx&+v$|+4P5V>@ftBV?kLaXc+c~7xX}rn$Nlk*KC|haEOmDD z4FzGII#dut?2UhRhBy4(s$)i1WCTBvBb{vBAkh82pQTlWmvS}(`b?t;xGD{Fvx%?u ztII0Hh*m_?%*&@R+v`)oPX88V8rV*q48C~8dEt-1-EvO1rq>d0KK_`vL{bG>;%2%* z)5Hu(`6E4_6Xl%%{Xzj+GvbvdhfwZW@nC4~1!F7<7Q!WL-bPXK4u5kS=wxe5S^#!m zCUI@theN+2hN!=ktmnR!zba2m6~5n+VT!yo9)>aL ze+IbrL^A!)%A&_%_{HMjhgyX^5asNG*j z(xU#%RZAdzHF}0{85;b8!t3j7=8m}sP2KOOe10U+!cZ84-tXORG5UhKm*_f2a=nZK zHKT>&qrHr381t$zdiv}skhs)msfmI(FETKFkfO$nSegS@|*MVFmoXP5N<{79V&NuvV{ zkh2QX&iN2sZyd8Vpap*_fmGNc1#OX5|n)$Y74>4I`D50v3jLxNx+q%i~Nao;Fj*KCj-G-D5K5&4KvfN zrhsriNBb){HeAX#H$}-LegAiZfAZ^h+))*9Y7_R*$6AT|1|#&~RTra(i%D6+wCs4@ z>H&*i5{~NG0bkkdT9>R>Z_=$l)RH_;)zh}zK5xxcKW>@=zK6M}*Iaq44gnm*m_8Vj z^eCjzM^P@5t#DqnIHC?6F8-WOY%MF+M?luVLh3!&ZDDv}a zZ%9t#v>U~{^$z9l?e1wM!P4k{m^(D>9y7o=4c&dZvVHr$*tJt+s$-yJ9Fw$KY^$7d zu6{xgKcNu)7Yy)(UePFUquHn{Agb?|lsPyi)xo4;>+3&*_Wh|4ibM=zm;oG9#~5|@ zMe54-T&Oi)y8RXpnXh1W;5U@KAOT}x(~@fPC#KY>n4CTl_aTh~f2dv!ZZD34j;qM# zqq3OBhl`aHmt2w{#g~E;>P46n`2y<9390P!-K@0Uuaq?SIOVBr`Lp$a&9qtFM5(IL z&c=qu?}K{;>|xe8YL0}_GHH*72Z1`p?jWS8F}G)6EOYz0Q?{y=coYU22V=6zI0S?B zLROkeb|E^smeBb9CC$!~61{Itkc=qY(x!UuU0s~8AM79Bx0w*dFKrd3{yO+HsP$^c z97%L%Te0Su`v1nFR`+qLj4ifcl2Ps_1R(rJOmXQPEPXhY%J=D6xQasP__MW^(6h}YRzUo>@ z)|zY{v}NaxgaK#ancaeUTcl;GyI4WqTZ)!Yc}o@ZwQe)}M?tZzldOqhiYE>jY<#QD zEo9n{HYcfLCneVEZtL%oxiK>56+vme8rQ#2)Q{|3Q!_=fSv~&K2zmbEV6=?|Fnd<^ zeUEpoqW#Lktm;C={xz`NU{?oa{W;{zR*WJ+hWA}M&9!!M=J|F6@o_gER)&P>rYbW@ z;y<4>)-!OR&c_g9-Tn$`a{KiXRU2HU?&f;u0k<>fpbi&LxA#C)0(0TO{+SYqiVIJ<%8;3V0yvq{r0(Vn6JUCo}`IcxXIB~AIudt8OH zq6+iX&y**s7e^)#NH$#Q@mFjYok;V&;B6}~KXbVtBQg|%d1e64-LhIZgZ^K2?@XZBOHRr2tOy}*RyH)eyxQmjKa?^NS+kZNv}Ud!f4_h_O!nO(%O+pSBt?zy0$ zJtjc&y7_82(;Lv}pI^&M*eLU`QpynaMV@{E!zCxkOf?{)qcrf9+Iw486O{~SjDp#U zpj~}VZn#y6DAVLdVoUWxT>Mgr$t%-DPJ>H*8S0YXlAb%up$D)Q(p%ekMUE0*aZ4|J zU+6^h^U!@>dp);Qxu?A=hn<4*VT#-^GveyQ8AOEi&VFLQBLCA-$hH_LW5SadMPNJz z)Q#8J_D_pPHbO_ZH_vv7s0kCHvxQP6t3R)q_us~vMpIXfl0=x%^i9suddWMJI^(-T zCnoikTn@Il7>haEnJ9{`fUnI| z8jMxfuDi$O$TVK#8aa&NQ|Fj>AVqa9u`6j!a^9edCo7O-Y<;m~m&jqlDe;Fl(aAAg z&Qjc2Dn5uxQWsca?w#okD$MX~Pb$-OySqT&+getowUdZB9TqP4wrh=Ms zi>Wk=rB6$=sfkv$st=aXO)i{c9clwM6e^wo`!;lrEsv*ZR$g`vR$lb2HU+;6IgjO78L+lrdPd9Dq`U5duS5)i5{LUSy6r1jXiIVj6bR;ZDi%+p=sudz( zjac=VoMT6X2aNP#5`X{QeGw9nQHp^RW`Gl>S6|VCjPNCN&Q-p-U2@lWAp5mj{3twsW5{R3*&iV7x4H<>d@HY>L>BbU+pmuIS0t*;^$?gP8n7hx|8 ziq!r2W)Pg%?W>_^PlefNyUz68QJX zgCIyD?=`IS@Ylnmo|YwiJju9KUegVh-rXaF)unq8yf1CAZ{zFB+frHGO!<7R?qU9^ z%Xp>Izfsu#j?2H`)i+woY@DblijMsi79o1`k9Cwsc$hoE8B!k-rvZ}H3(3rw_F!0M z8P|fAGQzN7!;YsGGf`i)5wv(w7v#*Cl1?|e5b>=FDgCA`CT;JJ6mkU%3a%IDp8OEx zO!mwUzn)gC1jBsZqEmb(i`C7DbH14s}+ML}cM8;(Ho`87LEiRFa365au!#)hx8+kPP->1E?tUc~yiyou< zJUC*g)dAadE#$n;+;FyaT_d8`@>RGeKD9z7SnQa}1ZTAR1lVW4ru%9Se@%<=82#uB z%b`od;#ane6ZB-%h(U6kwRU*ieKLCD;(FA+!?r5T;Z@EBLAZ9MPZFN$FUSb-!ewyA z-$%c4(hHSUH+t$9!a=TMiV64sNxSUMfK7-J_K{f>fyTroUklrnKm_yYm8T0GOmgPQVfMa5R!l6hhvr_bYh^UzGBj44=uK04i<}n;(O1P2W$`HVwBCMRvkxM)9p~`4 zX-zh8qu%YeR)vouK$J}B`b###^>L8Kz-%x@4?Dt}p$3sxODl4tXAS9FQ=XsU01~I( z@1Zn&`{r-QQV&|*Gwg)X+&yiZT#Uc3S&7HwiK4LRqFx|(hroVZ{La4iD{R}o>g?C) z!qwxjS}@zk_6?%tRZ={(Bba0>|0Km8EH4qfk5(2KnJB`Mbia_vz@E`2#(Y(DlL@+ z-kVyxg)isl=fWdvFd+=lW!0ol)@v&2oHNTG4r5@cQ7u?P%Pu+5^iv%(rn`~yD5|EIJw4~P1D`}m-c ztf>sL?^_wZsIeAd>}y11&Aw+HyJRO>QubY;LDpU*{nfBOuD#~N^LW#ja!M`ZK$vfI8RF0NVb zRZ1tZ3F^3WQbV#^TzYe(hDuB%&$KRfbEt-H{3Cj*Hou6#jYo0&#+RZYRymZfh`i5JQt)8m9Ioc{HExUH~vBTe3*gQOkXQ=pQg7!sC6Nzd1bJ|2!{iLz* z4fTW8@Ud_gXthXGzQ+2Uu6asmc|vJdp<(OcGQ&X*SKLBf$Mct4-zvY~vLl-o?%7=^ z&{vvFd|yo)a66{9OTtcG@W}^eqBzIdez_tEgcoryI9Sdy^!Q&+bD^u68U-94bmr{r z>Z$@7a0TL@S8=qR7-;Bf%FvU7wRe-EHOJ&;EbfIBFnYdBX!^q)j@TqaKH;u8an!~BnusA{?eJT%WaYo~cPxgeh?Ax@d(B@LJ> zPE+QC;f=wgE+hJv`+r8L&QOk-B{`;&j_AOjs-HQ&s$b<48{@1nzH(|L?a0~ncs$NZ zTO?9SjPgN3SgSw{+#tc4g&oAVz1?a49jKULrLIuDE!_Q`_$Jt@-^*E%yd@N2H1(?ykhDqp$yfENJCq1tIUOL%c8!azfpV?lVpWn&1$vrv(u~CA zvc|fbV6(PfrR(1)=*yNlW_vm-IIkFsE6?BDOXON9GLTSmSeFsgR&M>Se~awrjy}y6 z1S#CPl{8J9a~<~SHp$Px4x zq##T4=BQQ)ZDO-xo{z7V}LKg)GB&`mMun zzh9o(qSEUA94gnlb0bS!`q^_{rMTGGaMj|w#>N@wop ztK>Z|U8BJsF7g+%6Faau2KC|$pdRsNtmuT)r^nlVbbKgqzCN@C7i2V|NE^FUZxUyZ zK2hgfzeKAAO^f5Yq*rey#vZiF6?{15kfjLziv&X)0*C+_ypZ|4NF(u>cuP5{(Pxpr z;YKnIJi?|a`z7LzWBwr(l?0U+65NO-J*Q?~(#*ygn~vwwMt(wLQqHhG<)Ky)*_uWO zcHE|XAsouNu3syV@>uZ)MxvK|?gh=x($bPu|4Y6sm@PR_yVwEp=>?^w7d2nqWP2wJ z`@;y#$=pBWlX_dvCA@$)wY0w7tg6}RBlq_e{KYt{`>Oq2ZPIsrYhKW-RxoDYaVG8Y zwnksrxrG|A*7AEUs`RkglWS|XB?`#J7u3~V0kHPZT~QQB?Hv2fh;joGlF{D`@ca8^ z|2$$4apg_Ok}RY-II;T?(TuwEE~@kcqUuX3oWw$q{2Bp zk%&L2h_VfCK=ZL#j_cI-Q&v)NaA8cdto~NiB;?6UFQ=omyKH@<_j%&xUV(V;R+<^v zh2&@290`#pqZRK_D(UlVB`yO6Yt1(wK%CG$cDl^_Rn%~97^-BCbqA$Nx2j###4D~7 ze5<+X8SMT7BpMbC52!7gh%bODb9;X%v-X>1OLeV2cG+3LdeGm|`3EgHnl*OmsdRjd z9m8P3!KjjF9i`5`{%l%LR-{*WcNQsIn`y*y>+qq*$%84!uH6)oovoB|+ry*2o-5No zyX%FFjPNrZh8i_tn1P#wg%K`tfD$MN((N zNZ1$6>z}5DNf}%&Ls$!TnOdw=6EBc5-p5>dU2SKR7)VFFwbos)Ty)J)JEhWnWm&5D zji5})N-3K!${c(KO`6iRvp)@Pv16}UbPcj8t%u8x>2Ih&3J#gx;>OKjoy(zQ&^nTr z#=&CdF_h{hwBc|PgE-U*lVDH~wGcOS^m#l51#hA}{cR;{E$esL;N4=v&GMhIbRi*j z!?5i8Usr0R6Vx1RO-^t@;iBQC_b*(rySCig>Jq#4W~1<)?r!K6xEacg+@^o(v_x;p! zxvf&GxS=F*7zUU-@1M8|0;Hn#4CNc_NZO-JfK>eh?C^~2YVXyu$Fe-E_o+fqdT)Db zsOYN2dxK*qe!U257j*Xz>ugjvlvP6GMxIULF*)$XTCURi|Gg>^ z)@v67dIGgg?572duwG~y8%V`%6Jh+az>uIp%MUyaG-PdpkrNxHh=T%zncQzy?uL0wRqHx`PzX% zVk$G@rJki_GGIGb7-8m&s%mQ)z_rc38`r7HqfAg@6v1HwGPB#M+q%ck@$$4dJQ?{m zdmN>P?vKX8FkKext5QT!#)P@oCy$7kst&GU<%or+eT zTeYaXG86YNr z7?x|mBG{z=Po|RdBpL7s!<&P01#WS1dM++5ox$|XOdAlpDXFPdjEt^Yh7o)L|GjCV zy0Q}e`*VV|IF$a%l}P)+%)*wIK>Dpul7KiKrBUjAa@%)3eQ+-i$SYYcKMq>s(jI8T33C@O(HHN|;0OvVG#Q)fT;B0c>XK)>(` z2mtvjrt1lxv4P$moy4RZaDhfP4#cy+2?`2&nul&<+MxjCz8@sdubY<$@VsMcQU|jq z2OB$o(R4hwZ$kn3o4Ap_w`^ZO%&}Y%6d6NBRT|sc&ANAg;+^oV`D>4Paj@YCHkl{w0(FZ z=tSXgjEt$kRP;Ka3PXSfoBzqjZ%@#(Ek4$@rk=Y?h|}d;VO{SnT5EtPR?~z90H#n~ zzU+1M*ZOoX|GWphVVull8DK5$-o*o6maeF%@C-Qp&D5!6U~mPTmlh6Z!4;T=wj@@W zlZu~t=1uOo$`+47y4$q;7>ShvRA>kixAl2vu@C54Cj%}#Ug4eFxkZcj#h1L+U_Jyz zMSC*E%xgmMey1lBom+d4S{mnLI6`AV3I}}XH^AAbYigo_7?z%e1-AYalu6V&j&cKF z3iZlRF8cI%4;FS7{HQHpv`=a~f3YuxM^=^Q6-$!BY4KTs-;m7ywht)Vw9fMFr5``OfsBAT zvB>l~z^f;F`}hcniB-=pXJA56ZM#%_0s?8g2%X0!1~Uu{Bn6%4gzdwXm%OR{c17CR z(o-qppgTI{#hnDK$4%7Y8a{xNy_r3|g9u9BUFwfbPHyDLmU6ky!pf>|YP!0c16bBT zMjH5J#klj*$_iajt~@a3DOp29gXzboPWkrdVCn%#i4-80OxuH`%*@S0^w1GgHP&R^ zXf(`i`X4|X@5jEF1rYg>sVU-}@U@`(JX~BPfq{V?6`D6RtgWu@`|=&IzG?eTPfzKuU;ncUYOFEHZEN5~igDOa6&Ta)*Xyn>P|aV4`e zRNyGu4N6<$)z||s06X6tEG;SdMZnGXfl`Q(k&*Ck*)lwml8ivdFRH_*wH%zv{jk%~ zpiari$jAyi-4L)ps^+!x`~C$A3Y;)%>2RjWgJXSTW9LIY;j29}Uqi0s9QGH2m1ZeK zjvmde^svGCTIe}`zE#WzR5K|EcnkF_ZM9TYQOD4-b?3<=PukAr_8f>|5fH+Ov~n5u zStW1p-A^JI-MrbyIy%XONzk)`apxW2wKl++>*hpkIkEm=(R|I5XT5w~^b^3GZ6D4S zx-0VAIXEnWkng_Y2vJg1C6|zp*c_IWl!O6f(dJ|=nFnC7S(*Ic@%i($_B?DLT?j;I zbuFzP(2p9|sXDHz*EmoVg3OY1pam<(B2(XBM(A4&r5=zCT$Ap;7!DNfa2sa)X>TXA zmbS*(_|y8A@8EQ(>&&VvDl2^ghX^cRIfw{wxT52@rmC8NgtrBB5S4Y zy@p#S2y{2@c=s$?s_}s`^Szb_#>UaW(0Jm(P%9TczIKN!kb^FE;>ia=t;cD0mG9nd z_W5m2-UWJ`(=#)OJ02t@v9%Tcq^^s-}Z`xjD(%-aon2t ziuc>bXgdSlul4nu4vakFusB7bj-%CkIo?&EKQkj^bh6fVtz{*Tr*a%#;PT}y0i5BS zK>f^sK8yDL{XX5NEEDyGdr)Q^u@PNOZ_f=KD zgC&QZ_%b|P4%UFMh{y+yYVkz`B4*w=a=f>) z24=1v)JqXJf_(7R(V+wm!@)4Bd8=IoXgcnLjWb&(UqKt#C_Ob5cD3o(gNF~9lb9u+ zKN-qF*xTD1>FZmE&044;u(&P?ju#+01M`gnX5DHulVt%2!1#fd{L>|YdgpOrj=KXoTLi(+ssl%HZ(R)56&V}TqfR^ zD#y@{f{lI^luYf<`V6O9qRIiNudw-I6H#9i?B>N_kSAcd0=35k5YH>XJ`j zEzQLhfeBblvP22hVnG7CnePi(#Wu~CfqBqJATBX5xJ}kX02-kqP``Y-(0%a@C>P}8 z5J~p-h=*hxW zM%7Z-`5;D*9=R$$FgMpsxGq)%aybbob^X&d1LOz~1@SjuziO4Et}!vm2GfCXzgFAF zUR+Zn{(TLUlz)W=5e_Ea78Z8JNNwdyIt;y-a^)``RS#;<cr1&-w0~mYFFeg zYHXA~0XY-`RNh^MLe=N-7~Bno{bd`FpXh{HZf~6$+2Dx?Mj(HzUO8?M6a)`BUVe2r z0g#PeW_5OP%E$7^!x13Y3tGRIAktRTbQN~IlJLXENbGFO56eFoWbnbb33fhZb=C1? z$iG9`VL0y~WEpS0&>el1kx|*KIuk4;1gPmPDJtT|Z)kWZa*vYHhJ&nfdP9n@(E{i2 zvpr=C|AIG;SV9}0oXnrAqXx#b>AMYfp!DqQ4bQK0_(@hH6%`DtxDD~l(i)aS@txb7mPLka1UmJ(39k?!sgq@=sMq>)BaK)Sm-1eBBp>F#bkv;6kn=ZBYw zYrQe^#2wFsDauQrqY$D%AP{sZ$@j_-2rL~00+WG+0Di-@_W2L^i`z*|(@DkF)XDXO zg9$|LgOi<=t&^375xI+rgQJD54LdU@GaDnhxs#KfBM%FU_5Xc<+19~~gS(M{R2}dSYQEx6f{V^7glvkKUi}2Qr(>DJYCM9PA!e+j~DW*#O^NlN1{WK zRD6-FE~aZ~En~l2T=q_ULAh@FlXvj6cCz+NvtsG{7dS9*A6~HfF;bMy{ot63AN=Y4 zw{egvK6Mawj(q$6_Wj_Z$&nD7ZM$k$}a4e))nMD;s>_dCn;7#nrQPl+Yew z8yjX}VPU%PiG^fJ=tnUW)e^(QQH+d@$9LyRDY+@(5*8PA*VfiN?%AN%v`2|1;qCAA zhg(=IP=Oh$HW|J->A}2R4JA7{KVNS>A6YLd$Ta$0s5Ihj`s-`o-Q~Vs^!@Fq??^Z< zL;5lqzefVKOw!3_vH=!8{*Par%Rj*t-r)1NaD%7tyMhf24CFn>g5GFcW@vagEF!|u zC%WM~xD&XNRUS_F&fXeK{AJUrKR%j4C8`&t-n`ttq#J?~$u zhJ~h!37INQMz8ZVJDN@;u}AL7+^HPrU@!ud?z@^1$E6V_)nSFNBSZUd8a8 zAx%w9jaU;95JVDjju50nex`B8oSiwi9RE2yb>G|Dqhn!ly~P51**mwN5dV<`1Mzy% z5p%LYftHnZ{PyN@#$a@%D=;i7%4DWo?_p1)!)UqP+v{dE6tc0s-2zYRcYgoy;1x4k zXEnz*F)<;3sT>U5yb$h9h{^86_m3tfRrc%R$pgMuHCfz$`D_-sjEsy@_&qu1=H}3d zI1Umr_rFMxuD0JFIr=Ooe4Ko#re(8dbURg;rFsw70jDw71{g zd7Pb{>E>=#Rv^dPba?c;IFExy1BXeu~c;; zsiwBKzt8P{M#as|9f{AHv(zmN*49J305;*fO!C>Zj%}60rgT6+Ksq<2X$^s(pkQ@P zjr)FCL*quA3=$@$8Cc~-&*Qdq->2J1GC@+m2$uGgpdfgg)>H9JpF4}Q^KtFM?ePLAKZd(Trgo} zr+0y6^t{JvPXA@Pe<%aZQpAfGh?v^9Z^hdkJaeH{IXMA+5qQ|opF{U)l>eHz#`M=( zrsoli;g47fzT1uXMW;zQctk|rk}IE+F2qO@-j@aj1|et!-8G{E`wsdFlcW?B6s=eD zmJnhAFMKg2Xmx2i=|(-hzBcO)LjL&iVJ8$6?)! zq>RjZ%W=D?5)O`-y+A__9iu^e`Y=mJx}P7!=kNWpXFAW_&3a76rPVwSnUIpw3k`jD z>ZhkC5E21@K|ql-%Y(O%Dt7#~r&*!jO`qH>m^)jt+SZxr`^WNi*YmN}rQ?=k0S@c= zUf;j>206L8?gv!^vsK2S!>avRPZzYLo(HVTDk?Cu?cTgIx{l~Ef=^sC`kqY7Ugzi? z51TB=n3&s1IySq%H=njRJ608Z@31MwBUd;(ZqXxNGOdA>#z#Y_x0>s=ZdmFEm9cRx zoIz4S!Bt<>v%Kv}ySlm>{A(M82BdbLTaMKC!T#xHK=3TNHzWlzIg@py* zu-@$%isv;&>Jo6+#c zBVw+`4DMvFqymeGXuo<{3{S83@p}3A!3SL9XC{Bz^3zoVB$Ajrj^Fd@$q@p( zjClk1D>^cDY}@L3X6F9f+B9vxe95E@-%0j#f~fDd`V15eDJiMl6Gsrx9cnt+QJFVE zS9>PVXgjWmGQH?OcNzO88d^DLMMX``O~#(~E0XZtkV%K*2=~C|eVgZXwcV;n@<6^q z)`-E=8Qy^luSZ*Z&&-(WA>LOVY@C-b**q@Hua1_66E*aAt9>0D9716eu4;Yc3Q9Kj zk&uwcxwulgyStgaF+hi~RQo8Zr(|m&CWx$v^Ib)S$y-ZEXxkt(ht5XqijO*%FiJex zSZLq+_mXx8O@{o;xBbif&3(vW-9_&{$TfC-QC!snM4n{PIg&exxB~*iow0BDQR4MB zOM6~FKh;(H{(a(zA!0X0OXIM1aJQPwmjjDD!R>)XKp>^BpXqq-4~NLJwCnyeh1F`V zx^J`UR~o15jT;#m*@25^=v7o?WFFYW;^Noa#&UAB3Y%V_xbYO8z4@K&H@A=J7iQ;O3>+k|5kP4(MwxOIqvxDGs1tZo9T5X1r0PdHa54@K0No` z@5$-+x=!O_tv72CRJ63l4GXtZ6+W9BLt~jON6ittlLhAmf{$UrsCZ{{W?9akJj_6z zZ)|K-I&RA&U=T|xD#p%i#i|s@_kjv;@b_+J(RoG>`VJrR-_V&JqCSIo78geo`cnt5P#zrpFk@P`mn}oyU8{3s11#7wvP{-Eob{4dbc!37b zcej&EBJc#loran^7?q_p_Qwy&KR)-?755>*!KYhkwr9HqS!|#;LVpR8?Nmh|3vB1r zci)y|0$Y5|1e?_(bXG=>jt~NcGD?1iipRhf|D5_6m`cpo{|g5I%y5}g*U^!Ym&Z6g zJ+=0!%t9_MF2;Xj2pJW)XKYw<(Xllc(b~7VOMM~oS>;P+;y@gyYjzIoFG?CYUu~bB zkIGoa^7roZcMmpl;)-{%wjGa24a+`h2M1Oz2eVykeGxE=>bp=>r`LC+D0Od}q+szkmP!;>x7X667pA0)ofG-F3&` zrG;d$Bi#`{)3MHm_AN-#-zxd@Su&+^Q}cW1#ZfJU%6@$tcDT@RePxm!ry%(FdtZ5F zXJ?1BoebvZz!dPbo2w0R?gSd=0n z>fVu^`D;9$o)mmFhfD^ATRgG@{X6S=uT|lSq8>3!Goeu0O&DvMWccx%kLiD~^-<0G z#obq8<$@Ww=Y^_qYPnHg6Bgjowdjjbu{>Hy!~enI_r7ZGNLGn?k!QxYUWv%U5|u^b zA@`)4q0MfLrYgxytVfK4!ce$;N9oCwaQw^|34%9J!l;9XEF^8kJUL1rHj#(wSr%9N z-_-;^xE6lgN>J2Pl1XTfrP`#rTloO7x>-e%*bBkRD_KicfjfV`Klcr!(6RGc_oxtM~ucTmc+6Yr81rn@~Tb7@cp`wgEw4jM*aYR?#)Z9J)vPSG208a9VTnNVIu=szEAEWo${yv%Jo|?n;gIH z&>oGOI=T4CHjRt^Y$arn!f(4-onHzThebD}E1-5$t?eD=j1K79Aoh0a&(nUjEsy9R zQH;2_gi6mB^V@VG`-KMt42ANZ+dY@AzJ>H4Vg!aCkamnrf5eSJ+|_db>Gp{vLjTXt zrQ?H-8am6bHqTi;koG zAUNOH{^2X{c=CW&qhw1^=E3hyz-J+`nVBPz1nfx2$P|2h>BGz|kp~A`WJfnQZbBsq zC3GkNaKP5mXEKyG=JZtj1^XeQgfm^PH_W}A9@x<#xSiojdVh5YNEHBE_N&2oSU5QE z0eDo&m;JC%Z=La205ZHr+*CenxHg&>@xB-lV%L)rt(JI*jFnwG@fL0Rj*NX-dl)3C zlV$ALm?-9H7b4lo-F`)l@c>2$CfP`<`#BxG#gXsHN+9OhLCt8j^S=5kN=mItL;srI zhl%epMI|Ncp!sdxA9rj6vh?cBo9BMj)ojeoJFjTuzV_BzFMuXrke%&kS>DvYNvQAp z=Ww*|7iuLuB<&~@KT^qY3R1!&zEyhEv8%gYS;0npgO zdR8Ii?CjWnP(az*$|vw}(xc+@22I~v zoCtFK9N;eFw}cA2%c3A$5DpUy$&81-_1e%(C=T_lOI(eq)hXn=X`6fE%a-IP*MGuv z#AehJSW;0_>pR;Vb_ZZAMbK9O!qV};W;tED3La(^?Cdl0ckdFL9JgV$->}-P2npQn zP?k4s5k`~p4^3$p{A#pchv4%#6`ntU2YwY#Be#a>dlPtG<@ocJ0+77@?PfAI4i0=LxZ>fN_7fnVppOn_@_S0k z%2Kf@>(sv_C5`Sg;{HDK7iq}c(GttC{{3W0dR)x1bD0E z;Svt;l0UcGDfne>iXT2uK(3cu$pjyF6;j#FFnk}@$@KKo0Em~6I{na_B1h_pD?t!G zr@;$P;$o9F-9XqP?KdGJ!TavYNn#-SZdbu~2!N}`(|)4cr~6}&I*vE{27gh6OiZXz zUoskQk7O_#fG1f2FwZrUlDyN~Vh%JStri!i;NW1dhtq+Z+uJX3achh1hF!4I($a2V zPv)vkP<869U}~urj>a5@#Fc6dn(}w^KwV5t-i6rg@VG^o0sb z?GskP@wIeha|^#17e`m09|CJRp6%LJI#fay-*PhuTXJ*PD?jw4H<8I%aS-V=*ichY zbluKw{YuO5WoBYB`TO(;ibemermik=$4wv0KRWUE>E0bY5KIc6J6ntEu_=HoXk-G5 zo5L!K6BF*+84}>b$L;sbP)cxn8smF_h7}$WG1p*A79(&+S7SB`iXLl1Qc^SVaxK;m zz=^N+k3WB*lyEq1yFLQ|!*NPY;}pOOmpwNC9*JsoPfkbWLSYmWwx|#&Ij*KKU{(sS zbvgvEeUOomK>%6eqcu0=8Vd53M7=zP@9gC)qeRCkN;`jx<}^Wz(Qy zSQix)tw!@6tw8(Rk1v!~^R;1RIt|V6c7Otsx#^s&D#EDRq^+!MQ(`I|o){O>$Lu2K zrnxE~&L`WxkI{Fu1jRFZhCYvZ>}XmCk)D5i9IWdDrG|m`JI+6Dl<~9*TY&s{ftnN) z64HF&2%?wWWC#cFYOT6YiNi>J;GGBnKnCvx{*Pvzma31ufZZLxrHlMtf-M z2nq_yo~-+8TnVz}>R_(N4+c*6?7b5Y$#LsB#zKQF&`-VqBA;xQ>E6Go2}l#beVu^U za010ktI=+izT>HW=h6f0chhcu8a}rJ6_m%FZ;#S4F_no9paMZAyX+ZRb~fZMZ(*#D zY>Alj<5d!P<&Z@mAB)cC&C@fhEB`oW{mWvP6<(z&gvhw`R zB_AmP7n}sfGU=sYZQle47c>tBuq2Ebca08d05@8)Bf^nACatkXELWQtPB>-|2fz1 z;W>}YfAFk#4zQfN5UjZM&_LK_5~i(%a4s(#qKJ_w=cR`F=K&H|9`^M~|H-2xc5?i# z>EBrq5OW)j5WFFD+Ar#7>JwqU=;Ab|1-@HHcJ$Ln(Apdih~|fX4_{P1&qCuQwB31?OhqvVYT)TB`bStW>L}5vY_r zt$!^m+QcO#B^&f&z^kdOmu<`Yh{4IUhg0wmgkD&=Sr6M=6@P(O;aFC;9IU!cto&Ff zawm)%fGu=9NyO5{K=2QyjtE&_E-H;D;TKpd+Ht8`UCv8NCwvRyN3&d%5EiDk)Ff01`O+t0sr^tH&H3T*VuI76O-ZBGt zy5eGGz2&iWgN(x-F3V}gqtl6?pwyrv zGcS+I%iB9FENm6%zWLw2bv3ntPo~*4hjn%e0U;5JEtWDH%FCk>N!>sOB0PWoyz_UF z$}K30^0&tTfWE)pmmDR5gcf`Mj=5e?2qtvX-rkdXGzu^1H>F*z8ufT^zvg4b^vxQ1 z#O-*x+vmF&6a8pvdIqXf^~XW1f54&jOxovh-{2giJ+%2dT<+t-K+#cpC5EnEL_~a3g1UdD2DQkC2W5;QTk7Y}pI5FHY@t`+yP7q|!NaSuoMG1Y*rf)FI+S4(@O!+~ z(6xUC6>aVhYPg6oUNbNNIHz$lnf26rFjqssX+vDm@zgwwGz|K@J5U1Mfg+g7?MMSi z+`2y^sbPO4LF?UKN!tx4G^?2oL9{3m?5LC;5>=*&ULKV=;gI)Ry`mQ=y=T6_xr}&$ zBbb}Xukdp}ar?0JbbWyLZ|TfF(51{k0Ua60$*seP2R-~?sU;amj0rFIrwbIa`{W7K6-tR{r>5xUW}fbz?`bsvX{dp0OKNR` zd!`#_f~y+&yQW2azr@(p9J%UKgq=936moj8e)==6ds%OH@nFJp=rS@t?J|kyj&FL3 zDe010qKFemmrI!!mzKV-n5pr;ce(JG@q7Jd>|7VZD!^Ux&;HNJVkws zUf^Q@DWu2zEzsItBA^q(3t3pu-(MeZ2cR-T3@7rWW)EFZP*K5hn^v^F1nXNs1Fg8C zgg+LWzjlY%y@K_wd{@YKqD2L1hgmz)TpP)fJw)^$(oJ2J7 zAV62peguUtKn|f`XOA}-PCD)Q`&fZzkO9^sdP3uXc23#9A_fz)RL#vuj#&)dGzYDZ zQ7~4>qh5Vlz@3~il2`c54%OrD&Y$)JjzOd$0;^6x7^pT3O$%u30-wUB<&cBa`$B13 zV3hA1Eio~XQM1wyr2i2Rh)UHT|P-2$XUz(5T(^iVAe&m@O?Wo1j(}sYf$vRR;lb z5eEv6P5Z5B5|d6y*I1QXQEMx4&0OTvCu%OPSrZ)q=DpY3E-gzV zP)gzL%?}lUK`Qf9v|SO#@Ly@t8stM2^wD>!{?44K)GyCo;|fvyER2eyMf5t>)m~Ip z<2VmO4;Z+Rwwut(__`(qgy7q!x*2__bO$IJ)T9E26SP{mL9L3NoCt{Zogq{t{L`9h zF`0h~uqZ&Qr0q9rs6eYu<+6XJAaG07aW_@r1~58M1ay9d|1$$h*bw)^>1!>%zmk<^ zLi|+sy>AM`pkWEsn&SD}TH1<}gbejKD-~u@%@p+&6F{G5tvI%RrmioVUF?jb5x)H# z8Hok~njt=?P5N-cD3k%Su$WyREs4 zAV_~}Z9Bg;2=x!sevMQ#a$SFN1G3Kh4rOPYPiLJta>|UFum{8?GfC*7I}D0CUcC&3 zz3^{i-+DON>RA_LIQUgN?J9#ra|7|!eCEODvGGNsQoC%V0wigjr>q&#W!RI9k2+9n zh^Jttm$G++&E8i84kHlfPQ2(O&*J0I;Lsq~Ahi6MpIMQOxsxU~$H)C0vI&LB@d^T~ zz<2lv`1HsC(@WIL%gcns#HIrSMMb|pBl{y2Ma7l+Hj6Y`;DiA;q{Yj9Qq{Sxxw(0= zLgqq2PLQFjwP%|Iap|j0h~52JsnNR!GR4F zk7Ig9M&Nj&_`S27eojm*Do4aN+;;iueFDd!tVxQ{)=yxM&!v?NaK|RuI%zz^9tntZ!y^nM z0^+$!;_@I?lENPiOW*~W`d%?qghx(rUCcJQOBe39*R#F(I-2smkIA_>&dOjsRoV#} ztOmyaM#<^a84^kFrD6HWUD>vr@Ew78F=LxJKEjtUV=di z{ySPrr))fB>{-hb5fab|0AZli<(18gX4XyLYDUhz-wS|O##+!aQL$ItZ^O>3OBrNo zI9QqnNrdumBx7)_i8HonUMGA|Kv_gsnH?h!8BfTe&;W?WhUS! zO&~!Z3x~I<>u6h{*_ZdbQ?e%`yvxk%B*Pc{)Otlc7h5k(Q89se0#_Zznzf?|`5l_h zy&nZFE9@yt-{R^&#Q;H?i%dqR4zZ<2W=m}IL*XyPWl2c!zS@(wkPf=%LdvT#0;$mu z>Jr?u*Ls-ND1H+)XU!XR7x4ea7(SE6rmC#5l}&y{+0e2a{7G-Wykid8zs^2~%iy>@ z?P_S!JcL0z8#Ei~wVx%K{}J}`Pow;{6CGsF_&?z9A@m{mdL?h^u{cI#%6@yoC=})I z&xudj40-vfpp| z6+9PbL_yQJYK1ZTbp}!x6ZhXeDd@vk89P3(y{y@%3+b~uYwc~US1j?K$SHjkWE+Mw z@~!DGvgW48>^sMPO~9nfK=r$$D++{8gIr`M^x|*PX!58_)juGb7sC3Ml|Fun^O!iV z6^uax!1HDB2Fx34$W9ThiQ=+y{!I*9SWaWeGl<@ygdA;(Jrey##+J zi;S5=o@xfV@Z9H-BvaZK!3adcR5#1CSY zrSF|4{coSz^Uf5FRfNi3WQztnOGHA_iDJcsMc=1|X3+=F&i^-bGp@m9rFg}^^OzwA zBl!1QBxT(y{653&H&e;9P@Mqp|GDY+x*<`;O454Ip*t=%VY`Bp%hze5(oxX&x`IVL+7#gn+YTk(5Ogm@mhvRRVXsoZKfqzhuI=~bgR z4Z!}ezmgsuqO{&*K6~v2DJ%7s&6ZBDB1T%1P|^vDOcf7@bzE2D$Wk2S(uMIbh@+J^ zn?Kp9IjWI{O?X*L7Q4Qoh6ZQVX=*gmdDaPi6Ev65p@@BqlSMqlv3#4afst`TJZJcR z7`%dMM(|<_`7>P?{x12U8zQnOL7E=hYb~j=r*FX%Kx@s9lFAmo%>Sy5qjKy(61>hd?{lJYZj{@B)Gde@Jd~LNyb(AKuA{1si(RnRtbPtT^^+wpPuPFQ4Qc ze^ULYQ7x4W1yEU!KQ+^juw3ibybsODy`2BiCZ!=^s_&@fsj9}{Zz~T8EC{eRLqt~e z18!Gxc}!W6P-fj#Y0(JOlf15VR$2U5sX*#-k-neR*L>zkUush|u8tti4v&7k#c-&H zl|6P^>}e+BEC8ajt)MNf$zVeQ=$q3js;{N|V0WBRfE(sF&HY>3 z4mQ@~L#I|lzb;sgQOo^&u4zTd#Gb4!fhI2%R#Lyeq>7ci5Koe9A;|#8!P7Ze*aY$a zsVY4ImdF!o+++>#-Dh*udGE=77ym>7Z(8teQ_g7GHCf376-sqHpg*7 zq&rO54u5`+wl*=8y1H1SyCCDj-!hdSX9Hp@=2HpUQJ4d?Cq=h-D&DP``rmDJCZ3b-T*Vm+sm z>#pB}48GtArk)f5@NSTyi2uyM?yaG#(0oX~=JY$EFZ%o-pS7!bRga4xoA-o7k75vQ zos49*I-aW;9S+Cibok7U*{%f*u35KuX=z>Ln;_w_AAj8F+oXXV)bxrqwxe{EvVkY^ z`kdBoeXwG%R`0$3_v?4tOrDoin5f515xC&x3-Zi1zW`()L+@$!x^u^{(x>7Xaa1m? zPV`iD9Tg#2U%$dAG8Iqxl$qR;)MrTqGDn5>NC9CG0;l5)4}40ND2+KM60;b-g-pkL zkliUTy7;J}61q0+?UG&uS!fTOk6$6$UA!_9e+HR(?<4B8NHv2!Kh%Xk%Q7_Y34}?+ zndnNa)$Nrarmr#Q;@K>7i{IAsG=NTbpnHfg>yy-p-{SxKhE&cB|rg@v|KRV+wP_PVenDqR+zCQ$!qs zR0W9UodO=7J_F4%?*miZx0M{r0T{e8G;{osnH$1}t?KDzS#glQ2qCgY=YXqiJk$yk zi{CA^N2y~Iv7h}io8EwI@RpY-xXC5dK%<3aaQBY+J;hRsQY0c&#PGvXfp1g1O~yvJJCWrr z(;Fh4K6~Qz15*xfW_vR*_NvO~b^e$T744Rh8n*l z3E#Y#^R+!Mmoxc1Iw)%3-N;!EWbXH5U*hn4&WLD?uQ)vxZOVeFOVrd!t%>;w3=riN2OlGv`NkG>lwvkHnP}g8PQ|%uk>n{mi8h^ z@WzY|(Qo<)U9+A=cvPCe?HG03U`^u}7*0P?o|1ZlKF*L3qZ?L)#M&QC3OvTD###Tu zFQulzwJ|?P%(lCyN}O@+8rd7a*&%d0?0&rY8XAv->Oo={2Z$>O;Ktv zO0khV<33j$XFDmqXu$cF3=O-Imz*6BrG#S0klMoUnYW?WsGc1e4JBPBd<<+Z!JZ7v z=Zl#n5;#7C%Fn33uO&%m@zedLPc>PE=3Lpr0ib)-Y_IFzuh(3cI@sZ6F{F+Dd@eZ} zLSReBc&9nAl(nyUVL`?ICydA)N28cMC&QzK`!lQ zYN2{DrxC%$xr*+EW)*5+rL$teI7DUM#wWVlUXMy;|~jooGqpI|+P zh^)k!Hat&+SV&*m3ad6|kOu=~+`qE0Dtj6AS;WfDefj;qm(cbCSGdvs>c8CAn?I0W zEG)uQkWy0`~xsM!mGHa@KCor{bJfx7zg9RJM?cry+HY$QP&LNWSQjOh05 z=8loVsGI~JM3+&eT4Da*G$4)UET z-yDfJx{W6*a=p?)P&P`9bx)N;O`hu9j#ZV+@yNziNL-4Mp=RjEY{t}a=r)+Kl%4u^ z)EhPV#u^dpH7$_{%*|%x%#bjQqo9Kme9;P%_gInCy0@h{vYc(?*y(sX zbAI*Z+VJONo|))8LU5}znIR-rLe>tsC^^O%0}eE4E_SCvUiB5IKq@}}$ z1*oa18TDIJfYl7fL>mw57Ya+Q5{DKMLH(}Uc% z4yFEEX8GVWCV-lQ-Us@nUAgbe$$o{Nia@#J;|z8Y0Wz-O7YVoL+vhFIkI@VjtrPnK zK(7H4&D$F0=I7}Pf7(2OCbv!Y_XZJ6xS0SU9y)Njnc@0}f|K+5x4sysxvd)}4vuQQ zY7}Lxa>!lgNwe8LO#C#mIuyqzT{UAf)TV?Ku~1Wg5**%6Fh;hT7yVvH0q;i?LcEcq zv`W<{BAdPUA@93Z6^*vBN_xP_X5r%^R^Q_Q`3^P!Y~|(cU|QfT#!twryaY<;>Y{ z6@@CFM~|)1te7PmL~=pFEbwf}#%Ks|A3l5lQk^H?_WwzAjg95)R-7axf7t0T*h;X% z-X?+kbPF9_X6up$8#J*)v^!LW$_N+Uv%0LW^AP`6e&{(E||8XvyOa5W{rQgSu>{A zsnC@cItms*JPcD$!HjAc@PL4~4d!QwBKkx=eE2pj01hxDBqSJCY4T-j^{gf3cNK5zv0Kh1E+yJHP0zfzc0K}8JhST@E+aOR zKXDyQ9sGXkV?2(f@N(m!UC~fzXl?7T=K$%mW#n>N%R=}J%)7DoagUT9JGkko&25Sc z!14hD(=;^VMD^10^7*Bukw8l3z1C{5Apw)~MJfd@*PBk^Gpqc65t2r0zOc#ek305o zG3|Mm+p)Szv>h%g6cnyFlf;%f;(^L2=b=u@o~b>Mlg#OOjTj1g&0F?A$khBg3s2pg z-)F}iKb*MG#AL1d1bp>EB0OSSd&ReZfg}z5Byc{!$tMfUEsSLFLdQ`V86#_J-GSte`sxo>85})^|F%ZnsM9hXbt#*y!PUFBOnB3~t)Jgp{bP3S3u^RLp& z4ef_ND}sRVq-@4@!zIzO+e&+ieC5m1p9}J`*B-4KdBjU@Er2JpOP_^SAb@ChI zezYerQR2E(vS%dMLa7ieu+}mQ-;e9A|7z4HtqBdJuawD3@-2H0eC0zT#_)k_zBU@g3NJ1;TjZGm zdizgPcJ-3Pm6esu4oE0^v^P?n*oaNPN!^=s=fcWeH;XYg=B5*g=Wo%*JT5+N72~|z zeu2xMo;Qd$_#^DONV+gvb%fT%*%rr@-I&wp-@%I*sdT5N{jHEsg-m{p3>4Y-8aY>L z;D}3-segfpSx_u8b1oePO=Fq;+vCw^5mjV1BVyzG(r_s)!TH48sn#|kDK zyYlzb!ds~+UXi4`!)bu{x2>yNQ|^-gAj-vaz(}eD->*&yhd$+pA=2;vimZi%+E=AO z`ZzZ#=dCKQgi?U_>UMlxQCbI%ZVc15_4WD#g3zr%;i*2M0kr7kyo0~E)XW#?Hhi{H z9UDcZkh$q&XRW`!GuUa`#p^ zUps30j7udarhW@Sf%xED;o_xxe!Cz13|t_ojy5s^XHF<=)3G6JA?Fb9aWRxul>iu=HF!Yht(dxWKEnv6h~*aQ2#*HiJ$gk5 zTKMW~_JUsPjXY{xfPOSvmAfSQIYf}g)Erk8+paSI#5rz`xDoJki=8!0<6a2N{=$}8 zAfCrhH|M5{?!QuE$!d*TcqOnkh>mfd5d(u-*YDMj(qAJhHcOf+(Ya5Fch-rNV(_YA_^Kz58h*9sPibhhtLqTjjKgQz3|Xc688OI11E_n5W+f0Kg$K03hy>MX_oe)mZ2imC$GE2VT7tH9N{H=BK-S!oZoYjDj(xf1LId$BeirzqS;&!uD#92Yr(I655|1K<6w$qD< zxr$$hC>X>$?iAP3Tbw?q4x}&sE)00ve>(!i_=sVj{-jQ=W-kWO?#3TrA zO?d#}RIlVRrBykx#5q@l^k*q*`eNl_CNz?Qwu*?!S1{6e7GGN~#KpkmOPd!D@0E#g z+mth+@tfIwpaRkRvw&wTS|h*P6Q#mLH(QlVAw|5VDN-$&_w)*P$JQyq*2ADL34V7! zOktik?I@QHg!pF3$;I#6DOzGMafs#-v47pxJbveb62HX>d3_~=>;*an)0H;e(sVA5rx#{B~8)6Q2y+(w2!*56HxfjwzlAjZ+ zVM5Nn>?x45LtI3)&<73xq@)>AoR3MN#MsbC57Js_qTTf?o=hWG8X@u}dQ#Rn{1Fk{ zBAvm$!SovjZZ#}0a>PUZ2G|=Vehj3>7qSb@^S@JbE(HmW2LWK3`odNnEm|>dB-`9d_j#$ zXxGLEuGYj1)J<80Mi#C665pbefrKMpjr(U7gS4gg0vEj3)}SOe%TIlv`zt&QWA(A7 zXOgJSD{dioGK|!RmAO*$F(@sPl)uhC`mz zxt(kB$({+f&qoVvI(?nmgn<&_7#2<-Gto=H<}iW&5&k>vO`p)1dEqZdfxMY6TT^r2 z$G@+e6Vk~hmXco*1q#&(4`SH4*@%O~e`{|OIHxl|*<)*}VfqgK7BBZDxTiOm)|c$J zPhSeZyD0{LDL6pbiK{yUk6?CT4}8iYBE&dx~*=D!`oIlf2B!=9pVmu%E{gRJA|2poEIiehCFSr4BHV9Of44$% zEjxt{(3!S=i_JtYbSY%e-`M=G1$lyp~T;*ud#DhZF%bq zH@}XJy63N$ZrlGGvICO#W*%Au!uigh#s?o!amD5^;8T9l`#F?B`{M_5|B)iaN8+0x z^DnNsN~?C(0UQZ8szu6tXvk;I9`0Q z`eGS9KboFeZgad|*P0vVa6EA{QKsCjAb%t-a`ukF(~}0b^S5*=haPRwixmnt;lnAn zEmbY-3w6yvJwB|fsquKr8R{!iS{19CrcPH_G-x>>sp&x)gDb@YX#fYG@=a_y!yIB5ccBf>puq^yn+5RBb{ z+)kX$iO}sz+=JpPg;T31^hKga+hpT9QcMrFm>ElNkB=auMVz#uQ-q$5GNx_n6`%aw z`HvGuEYEeR)yg9X(~nQJ-1VcMXHbKB{E3%mCa+8&h~JHGR=VyzLv|&hP?r$gfb~o1 z!>-8dg=3d!5l^awWB)zlrAu(Kd#zMWbCsV2#M;OX=VbM+W=17x+ah5rgG#z*KQ7O~gil;tZWG{|h( z%gt`z(EXyM1~6!YopP7Uk+uT}08-eVuUvL@c2^pJ4_a}7^ ze{wD6`SENs)~@;DJLvQO=P|pL(CYa8#kBea1wqVVyn{h z-d;brpuMt@^Fq1}wbvh$(1WV=6e$VT!K=|oz$IA0)sX^sb!Aj-Y)3uwuHh52?|LW7v*WC^ZtUy@KONL> zT$I(o)WNytNdyAVEh&q91kR^@1aPaLa+P4ZK;(lMlala!Y}P>Gyr4WovTieKfCRV3 zg&zhb2hirNuS}d(;+?IVsF^vj9G&DR8E3HZGpBubl-ROrnSG7KOlM z=rYw&aCX{KOc}#O_@|IaNB2gRqa^6Gli19PUq4wjZeOy2864f;v8-@4h5DeGjb zJz@|n1mZDj1F^FLi2$?x!$;C8W%ZJ=1P2q9IuPm7%8ks7B)JnpT4f@pHtY7`q+YqT zxcu*)wK*PwaG2pDtQ|M;EE`6WltSn0P;2?+Nq%G;u+DO6SBh?h`WxClC4RVbL5=>NB6=JP!+sn*3Rf(ow z$*lRJx{gPRW4DcDI`OD5_RNzaIon{llT!ws<6^B{Rg%DY99Wf+4%>AYzsHx>p_=44 ziwQjQo@dDerjJ=Y3f&02Xts>e!FBM-2HE#MIv&mYV``~3qoYY zJFGxKDdhFfrwvVsn)RIWw-4V9Suy+C%cuwI^K4~PnC573O@p65>gSo|&Qkzov;v5E@>Eh&HpQ8m15GC|NFN43%^KmDvorSZIv0LOW9c z7$Mjxsb0doiWm=}k#W81{SHRL8mf3zq2#>j93GgJB*)Kny>nPuIbJ4g#WcqF*j47z zL45VlJ2LGg8RC%h%z7d@ab9|tt{;s$Gu|;q6Z}1+@NU?+fKH&?5oUZzaHOq#==NfS zDes7dY1i&P7^baQlbrTlRDa0c>B7ld{8$*-l>2Jll%C%2IG* z0Qb)E>&lCaFkVl*uM>EV$Ln^Ff~aGwmdc%-=`r;q{+=bEyJ9is5*bE9Z=I#+mv;-; zqYt3LLpzwe`b>1^?ezRrAi}eEu_&wNa@2GCF9(-*8NH?->GGcp%H`{A!nhhB3uM zpH>56RpQ@qU>n!a!0}HoSQS_ho4u6%tzC7vi#;K2s zSp@{ywB4F6NePh>q$LIE?(XhXO1isSLQ)#(6zT5n?(UH8ls&xf_wR4-lmA3K;u&V1 zm|6E)*BwZ7e8f#%a_YsC<^FPm2S!4#A{5X$xZaMC5#qGEMNVs}pQRxdMK-*%2n$+> zm2X<+Q3Ifp`^-o~HntXjdX@KlW8=`Rl&VkPHM;&d{s3I~tNI2gS- zCmwR$;jDc2G`GT~=5nlP{MBjKtR~S)OhFVb_cccr1n+{zgk`AcBkxaYjU zMZnFWduO#ivCha-6X`Y`T;*ArX&U=b9>jl?SYsM~Ed|sBPjy8P+>c*k6HCzPw7Td_ zsTN_Ud#ms(aCGMkNn3lmfEzO*)d)f790vDUhf+ptH@WJV~JA&XNym@QW=hdq<5g_~S?*HSVfVj#0x&QFb z5g}rAdP``(b`Ae%0@+6Ip&{b^E+vOhKpMd>W^aTUWFKyt>c?c7S*(D$1;GF zfe2(69uo7&Ms99yEUT2cAB^tC7}ddlH@!--W{ap3yow#Kv4CNb_CF_TL#MRk@_%IS zmy^Q+G-?WK^`!jKM1;D^dhMU8uDNi3W^e=SXI`NDOkw+z{HRx=Fk*7~OBJ`>(>yo^ zkU*UL<7S>DMNy_w`O$#02tM_O8hZqRBhi*-BRLWQutwZIBE`L9R zmpx%jxamyDL5zdzu%tk*1BWmhQP_g3|fZrIM-`k>|LX2KG9bGeek zw?4F86s7qHXp**9@bEZxgL`e@-)|^wD!UK(l>Ta$(D?|c7Dgdb!+`n*XGs$L+L2-3uOymwoeEr0JVyZ|dF?Y?-AL9myN{+-hi#z$+ap~&LSJiNQ% z7S{q;y@q$i7vo+@QZ?qSOJI}~iiDcEhxbgU5q9&J`7*3w2Oe(^+`lc3UP0@jkrG{V z{#LWdo(S?$(&8X<6V8YJ|4L1kDMdv97~;MD;&@%}2n6ZQ^p}zg@Rje15B{%}r`e;_ zELfxH1ja@AW5pg_g|+fm-);}^<`h{XZ@+Kh1QvfsQ!PJxe>POHX++Zv?Bx3{$WC++6YY0j-&-E*Q1*y&j%#6 zz+c@Mo)~ZI;SN#JdTB%v_~0Ehk-p@sp@tGo=0Zw(wbbZxb8;?hpY83L?$!YQQC60A z@blb`^}r#_(aby<8MhyKGs{q` zZxllx3xutpAww=OxHeb!G61PqHnhk*zT5);LQK=eG2j24q)foxpu{J_t)Q}=$~_}O z<`wzmRcI9zt$ti4oJY7ig4OkSp)9d9jA9oe*DZ{fVCC)&n2RSaaYS6?osS;(MhF&LqQPmj>n2yJ#Z3LOO7l`7k0Gmk>xmsOyv>GB`~Y##Ygqo<=}2?e z2+R+tTn2*d5kyREEHw>{5r`X%cml*gaOb-I!BnA+D~AbPqYydW6V(dRr`f`m+YeWV zW%$y+Tav@V1aH#7iVdW1(CJ@9%L6HPnT&@f3hYyi0K1_6;XhJ(y5?@ZVR4Zm!-A-& zEHzCO8rdfM$WqKSyh;nFRY$>G9V?JpsZx%-*k2NKN!VxlvU@vf6b*{``7R)y#o=xe*xum_4L?vW2-^@Z^bKhhS3k2=4Ip@ z{Aoqgq8hg6y-iwGP*ZvhC>9Hz@X<-0sU4&#pb5;{tXD-A@>S1^QeIVb!xV9UlG%<*!Gqx83%`v{l-2dW`Nb(;fDGLnHG7nGvhUzi zVY$dk-*hUtdm~d%!nW$c{E|mO3i@$;6eu4<3uahP|P!dkjP1ewHG<}WgsDb3-VdN zNZF@oomnScL*=bD*4pqEF$ER5&teZX|5M$n*4xQ8HhxnHHl&0Lv;5E~xVJJxG+j~8 zAMHh9V$w^=Bh8*qhn)#zykklnNravE_S|O|YvoAI#HpAQa%0u@GfTgJuNC7PCZ#;y z5DzS4-pwJ0#g_Wbfd4L?l(fr}--NgI^Igx|g60lEyy|Z6^*}!hj?-m$4>x`(Tnoa~ zswFi%BSex0A(MdtljCJ6-OrPCVa0iY5aAsYh(sPA(MEw2Hcr)uS#q;Z`d~YhzFi{! zwS!0*2Wi6FS86hWf&ZlAG@m3{J@cQK7Cr*IUS0=A-wg}tTylM4(?GfIC|yK3xP@~& zKW{&&AVnQQJ}%en|5nPsfBl*2OB{8u|3Nn`0o=<&Z#iZz$Wjhdl%vbr&XP|~69o*h z+UK{%ZjIIeqr)6m+aai_zv0%auze~P>@Qc!T-SDD;SqoDG|KRD37t}K34herxi`P> z$Lim3qdzgE)71GE^x#r_#{JqPv3*2Cz|Gf~T)Ug5zo`?N^UZoh#!Pa|vbislT3~kb z!~1ayGJX#KT(X|uXKHWGu8$^N{x*azeO!JB2^JXV^!Tf{&a#AarqH+>i4^nInM8Q@ zKwjgHV|}l*Q5=sz5_lY#EH{g%*7q>tdK#up9N(JNrQgvAQdaRBl zO_f^u&+W^aJ$#Vdqm99OCoBCM?QYwVsB*rTz>BKDL!L9Z*GToWu_Y(p$_UzXf4 z8QZfT=d{*GPFzl>1<22*>Z)Gi2=^UjnV;VHiJCpI>?AxoH492qhY{ATo-?cz)P3K+ zs6L`6U@h(a@tO5DpyBI*wBN5id}Ekx+N@c#`GZWCp)YDa^Zr$OEs5d33?+u1wXYE` z{Iw_xU|@qPsPn_(Q<(bL)v1Ki!TD@gRkh^?^YUn|JdnO`d`N5p0Dy$k5)TkG3@o5Y{-u`Fm^6E>~RfF|492 z|6JCRz^N2N|48E0-qP8w4mo{ftRqy+a8-Zp7N5siPwhxPK8S94h%9y?C^t z)l167gxYgVKL%6OeEtynkUrFS5}ukCFBheZJIS77Ho#L>D<1FP-#$>0`IQX@*$I)C z-~;!i2z0d*&n~Q2@0C*4G8ArpGPkAHUJh$U(J+ioVdnB~AJ*tRtpk%X;k1{l*0Kt> zUCTQQv{{=f`k=RmWFwRrMprmx`7uydV5QWQAjp$6nOas@OkFPA`-X1X_0&3*vY&&k z*8I~)4ay+J=mPX$diX~ls@6UVu<=TZ%H9)$g-Uq~P4cLHlvw+7;j_|jhDXy9)jwOM zF?UN?El99pjrnoN;K@q-Ju5KIre6%96gQZct$MpjarCsO_VM|>)gwyg9#0x{h%}tKCe^BF3n4y>8wZ8IOx>gb zdr-Nng53fLxEtrcmm$$g%rY0O^v&CDme|RsEOZg8Dcf<8*LPh;WH3xV-M!&iq~^55 z>c)j~q|{+0?-tC=c<0;jL3S?7w5^T!-Dv1*I1h&o3FSE=78awA%H!6?n9ivK%E#)b?$ePLz7_XUHUnz^EZ;;TD_>3=k3uGFEb%_FI^ zr8Ak$u82?ER+OB zJ`Z@6%h&5kS%oLJ$~%I8)8XX4uL-=7!rVpP6%m6WX&j_*@JdvD(n6cL(V zkl4Z9qV4&H<1~vv#r^H_h6s>(@A*e|q9*XW+H`6?5oUqiqzm8Qs`-(kii;%sQxu$$ zW>kk#FJUa$$6%i;_|pi#5VBp0MxppzcR_?v^YfoB;R#dbr_S@2o+M3mGVWzAhHHEw zMBWyQ#ZHg#)mj(AsdqrMHJPwC(x_nBIP6~(pD zfZuilN50&397JMwkfW3rDA3c8lx*KyF3|tkISpt_ZoMLrR{^`n_<7ChIn@M9#r_(+ zP$sMk;|{pExjUbX$>$ogi<8lY%3wO2biq?qT> UYl%<~5*X}iUaI1Iy%4V+U3f}1Qz<`aox!o<58O>70t%(R-&@37T(nt*myevnhP3;N zzczj^yhPw~??;g210PEeUD>L(F82c;c1gt&)`4UuPFx^Lx?2P@^|58hH)D^zHcu>3 z6(61PON!hxwIK^&e+3jT6V`-^DCd+KR}(Z3+c}>o!%c?HXJ4~ROCmWX^`kR`o2M^zXn5XU)oT z;Vx#S!Z(^pAb3S`k7%+YQKGfd|5MRr!{X>^Ltqe}O!^)Jm)n^n^8701dB%;e9+Hy= zC~Ihew~cSqm>=decx!{=3>I!=go;@`(nu+-GK8*wuG8=)hUS6TGZwUxpgD~0H2q-h*X?1uwAUKxeTK* zM3Jz{sBw^qFs}D$>eFu8k0tMujC(kzH~0wCTCP@8?t2^7r(VC3xi9}JqGLF9is_ItJJkw% z^6*@K-6yy=n zN^BuGts>O>5Brs>p12hV$=rOyjV>VJBArSHqp6Fhz}c)9@u6~|ZkIthG%voRA&<~M(vL>}xHd|E$#oiHqu z3R5_ew?`JFtYg8#dWwaidJja-; ziI~XCBbXYYj2*_*o;zubxw2=F;jzUhjp3%8PTP(6Li z|9VU9FI2yl#Ly3HzNJhSh+Ut%BV~R0^zeGftyOJ)TcNk=RDL({Rz7C3ru|$L$S$Rl z;S-B5a01W!rFNLXG8m=z@<*JeF5a~_3>ohpYsbdcZvjhsVd+^>!vIq(h6wl&}1RFjVgLEQ7R9>p|_C`Ig!ev;Nn3w4aJSd&JXrX-BU$A7hZv!Wb_ zT!bu$+$!*n@1?taJE8<~El{9J%P)GEda?c>V2=X59-{O79Z09K#9uz~Q92p%bcYAeHYSyNpgbhiGx>Fpx2FYnIIju-o65R$^u<>%<;l57q&-dHI z6@kZ4YPW_^es@tPmDL?gnQw8Wkj}%DD5I5fp^$ukNlQ@pq-T8!`RprSK`7aB^gWR{ zV2|KsAJe*8i=VnTR$=T-bO-4Vha4PzwjyU#MK>i_l%E@^Ur_x=JrxRKOTjlcSOV=7KZMw%Uvi~s;rFez9}YO#qof3 zR8&z7(cS&s*)JnpD7G-K5Ufyswp(X%cXh_)svp#<)l8PZ5UXiW8?vvzr~jR7ybNH< zIpt2WWv*_61Y~~o>KOW8J+5+N`%knDY!o(~iv&qwu(3f3Wm4$9Qp8(8_yW`vDV3kb zG;v;16Va!v=5NiSa=U*KHy;=tH=CkUcQ&O?>OxY-Tf^tTbHT-Fq2yG_)UO&O!(5b^NssR#-4n#5!Qdm6co znfhr7?{+XZ$`ih$!lOFSqCUjEL*ebY-CAspN-aPwm_sAklwgn~JM!kMb6|`5#}Y(* z6@8BglKO6vP{(cd8uWO5X&tNJ*tS&hZ?7 zaW1ffrx127=$mmn#Pw?f?&Gr0Q&_2Fu*S9~9&oWE51}_}Fq!vMx82dY?0)3dM-GUx z5a<7~1ZlV~UnF~AE z#8k$aH<)b7W&(0s4hR_sG17_Y@nV1``!WQz;(lNZYu7D{hcL};f&6uc;Doam!h&-? z(zmL__$i{_wtWRUuEFrPno(4Jz*~kdjj)t5SZ#)^n7>e0K*Wjl>*`K9wm@n z8$dnQH8LJI@&9qw;D7n`##09F_5qtj_%5!p)d}6X>_exn+WOO05X5OjP}Z>gecGTs zy{mojk}u-;^g$SjH{INaDorsW?v%pcmHfeFioF;9>Fc}m&KH|1BqO}sRsaB?2eU3= zj05M2BFjJcrN43}CW%zyJSz!25tB`@NUkbw2_@H$Up^zUo}ZJi6;D-;aHi+0dBYd& zQWNl7tXm;im3*(zqrt5&y^YGa7kQbI9Ai#4xFcD+)|F zxbq?D(zeCb$c)hkJ!^CB{FyAzZ7*%D+LZUzO>ur@eM^mE$87<7<|r!Bt*Awjf@_RX zbd;f6b~dd+1RsOJGHJ{`F`C}8)bVRt!e z^-u^bLxNv^N!l5gJN+tnJ2LJ0ug7Ui%YtWR>C<*5S+~@_`?xf?AM!!V4Hw5ZL}CgM z$4M;FcOS)or8<28&%gVx|DaPXiP5uw@LkpS$_YV}lQv_K=)FV&6!|&@t&eXQu^dEe zbxIshV^!o;^Nsvgy{y7-LmnbmqZWF4MGZuFrm)TWk0AZi04d`oIS+A@btki$59A^k zjdejNtZ`~W6o`R?OJkxdZ5x^Vw#h_P{oiuD;Jrxh#O&{x{HmoMo4F=CYx7HUB)Z!QoN_TMVru+sWPnWB;1eI$s_G? ziFwAqh608k!RpSkVI{Hs3lfK>8H@aQ!07-x{I}urS3F(d0eKASuRxNk+dqfcKI?ra zrht`L29R)EwX-ubFC?Rm&Q3&RJRa@^6|fOs2p6w`OBraMzdF_ z-&JMWPL`Emay@_Q{5<+|m$W8Q3x?$qaRK27WRoH4TE+aE?e&QMr{^8?EovK5yR&TZ+aY;mo*8Hw|-iT#%PHKk7E3U}C4(!z=V z1B&0Zr@0-h+u)sMk`F7`dGvR7Xt3KtfFGYV#ayQ8Br4$iA;Y^juIr}F0b)ycy|i{^ zBP*O9Y7KyeKmV7q<=DF&LhsZo(&>7YLNHLoqZZ{z(IoQ&%2l<%{7`>EP|!XW5=K#d{NK?&zP$BsjX{f}a#@M`g^Y08JVDiMvM0+U|(_zD64( zj+?fra~FF<8C2T-8$wfY+J~<#66~+FImbVZI9*8I;B#Le)v9`!p@b{ZzpleTcjO(@ zRshG}1oXwO*O@WNadMIq$fx$+t8X@x9i@Ei*4iKe;t)^~0coic;MV~8uIu_}v3&k3 zD9`uSpX`lizx`y24r;o(;9cFod2o=Nj|AHBG;UUizyo)Lcau3mtBZZ`B5UG4j#9|= zPQn9U0Uf|#I>8(72zp@$Bq>Xplg#3D+pLm;;M!2~x$zF1^-lPCp*j=^^-Sjl{x>qT zDBpo*^h{_m+`WZ#d}|4FrjV8#u_DsMW52A3HOwMU*WdfN+)c6%D1Sw^9+sl@{RL(l z4r7^+cY2Cn5=($Gr3Wn`06!*1E_7-tmyf*>=Xi%T3Mi8=@M%EMerc`(IuS71??`|6 z@S$&Xv=?+%iH=53Gy*I%z>>Og8vzVG1J;x@JzHB_9nbl!Sm3l*x9v1GT##~k72+Rq z(e{PhQ;!bRb=5D+Bi(2Bs0uBSOq5Y)P$=4S=oU4!yy%&soq<|@r7Nhln_bHL`*@s_ zcySSpB3bp2fU4lDvtD#Ea@NC@IKA>dJ(V`vJ^$$y_xoF+?=`7)0xIhIx}!qb&g~(3 zZnO))4|&e7&fXzV!GZ7Dhl?P0URQ>mpFJoh50aH9j~5`*m;~DD07&mn^UX@&K?k6bC$$B>A(@MQsL-EyI7eb4S?;L&( zL`s=~I87RVmxce}UMg;=RfK9$PpiP({C5S>mJ`GawE#H`pdhzi0*`52iGUV4FfgDk zs(^%q#JyAU>FnyNdsfX0@;)msptfdCC9tY2<+c2BF)>v^z+E9Xrx1C^rvSAUjxM!s zq57jifydrw#!h$?vrQ;G|G0{tbe{1yJ}Zt}+57a>q|{}Ku>zNIR-=I*7ExgJ%q5C- z{bD!p>RidOl>gxFy9cyJxgbv7_VWBXwpEBNdrBA4TRU{46;}Im%}E8whQ=l)n3$NI zanwqnIS*i_&(wQ@9!dnDLlwAdj$5$CrGP7@kEX1Xhkd+&3e-K+q4an30~3GY^>t+$ z#m)QInK?4viLB&5LmWj^P>Y+fEKfR_c{%?(s^Nb|^@sliEsrXyQF*4bw0JFAr5D18 z#2Wb-ngsJ?HpX<(kOtlzTX^Jj?n*u6*Tgm{6&m*`#0y{>bWQ;8!T>2*XWRJ7P&dU+aBK=Fl2cUE*OuSK zzc#;4U4pMdP;@e*!J&QQw=(5B@tDj-PtbF@{#~clO%Q>hp_ET%vMO?A)WSy5Bv{X* z=y$O^iL~{0#7{GI3OYwE%Uz%Wvecu0N8Sk-(Md#4n*sv`G|-oEfu1X208$=wdTPUJ zy&`R#!`gNGf@1}pvTOmW^dCZDx%vyWvhkit_}#=h+XhbdfPt@9lWic{c#q=sEb>|c z8cjioIc2?ywYhZa6VZ8VKu|I&yclVge-4HJo`TGiS<_ROV*_Uec;(5K-es(yNskjb zS8}cWWx!%3QahcUJ~j8i>!hIbi|%q7u?{XGpkw@=qdpFerJ^!gXRZt!1z`G0RB77V z(`PTjTRM;Blg_3ZSn&eE+sI&3=D64ibqmLK*!zjf62UO}j<`$*GrYex&8JrvUM0AV zI{`%7Y43NPk90Rd`8YP2GOL$mTMUxE6<_Av6JffQ!wknfL=bTq2W3%_Bfhsulpi>? z3`A41d)qN}lRflcgsb+J5p)>?$KCyI(gvNyhz`7Bc{dG3?)R*Iv%6Y| zQ!177oT*&A++o8z_59iwnD?xaIfoSeRcSx;Gk!HnVQ0N^l<>xz{;3i|r;R3RpVHnR zi(kD4_(r=M>D!N8ACKTEA%HFJo_f5Jj2(jq!0Cmf&eWqnj0qfY)aQJwHkAr&o@;uh zVk-;%DSNejzQ@DuJdJSaHu}VyO2Aq$MA59zF2#ERDSJV$5@KaH5N}NAL^Z#lO)?{e z!Ro_jt>9u%>@;Em$J-l)`J_L0M3iryjPwBqyorB)%PBy*gjOQ9*`sb1CCRkUSOvRS zqU~!@f=&L6R=k731(`9en&(zkw_`AVFz(yey&9y-oqbFD?KnzBKdmDAL@ent7#G`T4w;KmxUeVF21Yv^~G zL!V0AO0!V~4ud1KD!s%vO8m1{3{fhJH@40_;skpd1hpxvbhr@{y3tt+Ki}gwmIV&o zlOg?iY|LK`Md#_(eHDnG=|Fjla=CDewicmtIyb9Hd>*~c;*}Kr%7_T2+Y^TAAEAE9 z9H-wjd+$SxKe!O2ExIG*oJD5K)aTe`$hW-)+g?Y{iPCu8l@jg>Hm4^>My`+Ee3><~ zj_Tt=V>XvHf-#@H7z z>Rz>Od`FSMHjRJ_SA*22gR=e5@XYdZ7AlRtNt*Hhpl_Ojt+zVlxB6>#Wy2fi3=-|z z5~7h8EN6D_6SKWp>dcv{e0hCEDLRh;*!;3lAqB|zo>I$ue!GNbO(=1){DT^;SBN42 zFA`xiPiA>{O2c7vYjod&3PX(qgFOB>wN|wFt?kaRP1xU}JpL4IL-(A)+C6G;v$P212ZvnzhL0e(^dA|Nue|mIc#C(G za%=r(i;%Zk*FPd7av*NI&B@zdwFGR?X}&K-Z_X(ky#6<|bIl#7=!$!;YQbaU7vxR| z3+Y1h%4-rg6{y&xUOWf*akf#li+YqrY1dpMPcN4wSze))50M>zh}K|EZ!$mWo>s2< z9zUcVk3X6LbHM8L@Wjz%XZoq;`Dph{DtOY$EtLAT1Fwx8DX3D}apKCBF4myu4@^!x zp!1Q|%0}%*h6iP<`J6Y)-vS+!-9|kHTl@LS^P+0R664)P%6EK)p4{ryM>KIH8sZ+l zm`8K}M8B|!ZLLdMAbokt8aVdGsHFtuSU2f2$;r%x`T4V$)UnKvxr zA{{8;3TOmQ3f?=W*9i7DXJ&~uc!Z||)Zw1JY_9WYHFN&y;g;pz?~9Rg4DQ=ig2QXD zm~h@8RgMi`y)~cQq|{_i!ug9-r)JO`@3z~!G$$j(%KomosDp6-R5|F{$xCdCOWXW! zvTNg{IN$5Bzuj{KKU;9$n?%Pr9Pg{uU}uGk6Jm|;rplhAtEAN0jn>%z&fZlVBuQ^H zWaJG(T{c!1 zM>5KI$zYszhK#ZprlG-o{G!Yq_5eyDjtxJCFLA?Vfup)vjmH z-Rk|7w{m}mnZCNd&QKn=7-T(qp{d*Ek&T8~O`gRwYKqJbY2VN}!9O~A+S{Bj{%B<$ zw|>XAo1?IfU?V|Q%f+3#pj&)3hnNP1p`=qZaPU8;2A?V9*Uh5ffuVG@%)(hSeTYOC z=eW`S%i&4+w*ik83(fG1i;}wdnE&@rD$QEe4D?c(ukD;BGB_j+iY96uRk~2xCc%xo zYA(!D0`2YZ;2z^$R<*tC*yGK`>?>*y=-O=OGC#lz_Lw1VaB47++!NguVtJ}c8X|+P zE5ky=1f=~xd{-CzncJ4uy64 z;@l_^qSs*3?$=Oub%tg0s9Do%l7=Yoa+0&aGl%1k2s9MY!YkQp-{bV&U)lP~WG~oi zqSg&@ts-K7)kxmtmFsVSL8vZUa^v5Iv7oaPs)GJer`U!9tfJ6;-;I zX275@LJ$VEzANbRdTPh)N(zsKg~LL})ydNAeR&TQ+})Oa6aBY$Phy`R#?K>pGDb2> zPi;T(>o%|+86|#5&I+Hx;!pYGqJ2>cwz*M!V}7yn&GEHCe}mp;!(V)zUuJJ=ihrR8 z7fF}%_t?VIIAg~cMD!A|G!7H-3SPoigo&lP5}<$@HkLK)v+tZEU2#-K02`4rajE~O!DSu;W)UzrZqgL9x zxECs`;A)#bK;CI!0{M7}8JL9^2-zd38|D3N-Drn@No8b>Aen|v$X@Vnl%nv_xm8eC z<)Q|JWr1J4;;Z^4y9SsMD^CA}xi@)NNB!KYv$CM6_#Sj}8dgY_w`twlg!-ylF12K{!{9t$)xuFG6v7NP@K~K>A5x>2TT*RkcRe z9ybi%`Ofh6wwU<%1B7CbnN%oUDV#8^ucpoUjWzbU=C<3emW9Uo4(dc@&T-UUBN=!U zlN{hek|B%II#R#t>o*3cDrak)kzz)9SA1u?Fo~|2?ohBGiW&*Mt}~v0;)qy?lau*X zgT?VlF2#<@9hNNT#RHhI~A`&Q{cF-LpJWX$ovJ)xJGIygE(xoIeO2|802E|8w_; zqQYjwCo)YfWRi@7Dobx1Uj~>8iR4q?!N@eJrcb}EGw$hba`u874>Ckm4y-)Y!PknM z0sO!oTlIRqht}Q?shM<+s02lH67iq=8Uf-&0jx=nG2TV z%EqjsBl3IY)_kiRe*GYWSmoF)UzdJ)VlOdxN?F!)2Q8K0blnnp-F8-`=iV+8T=r8$ zWj4-$(LH3KtX1)DRG028EA^Ut0-9IY>36kGpFu8N0(nRN&o!!7b4>8f8G%!ha4yRD@TREhQ4vot*|nqvy&vMe}j1lr8IBmIe_x~00}<~eo!%eZ0Wk@u(| z)o@HT{p)H5!0zU-OjZl>Jl@Jp%H~>1iy)4xfxdeqvYgqfXDl9gQ#(SQNwYeWmFxA= zN2G(mno#XRG6~&EK7IlL03Zh{q(9wg)>c$%_HX~g+iSLPh?}ZW`847l>A&YC!(-F- zq*u^v7Ip29A1|+@WV1mnJ|5{|nBB3cVKWVn)H{IvQctzHh1OD`WS~1e$lSU&n^D`@Z z%8Fu1zUSxbSrwiYH;C%|-z8PC45ALOjY8dryPc(z!RUBv4P;A(tkoPxKY@itmlMxM z&vo+hiEc9`0p19ph(|(F@zfBbt1#J=0|jKwH^$S)1W@pOL%AY1MrvFZqV^>#9So$a+YuYESZo2O z=aG0TE2W#E8lpQr7VQ!F`>EGhgo}}$HstqXA2V-wu4ZRZ8Y(-?taU@8nIB#aBN4ecJ{;!C!9l@%xE!8pHo%kM0V4M z<|bupJIwXAOWC!|;v>ARIEU&>{V)@Whij8_GQVENKS07$8^JNL35b39)k&Ax$G$S7 z@`-`O%V3OIIux?!G3jy>Bd1hZ+biLpK0(PQT>bikFs7~wHgAST1w01>nYae9S@7r*{?qm$}~dK zCxE7bC@=i1G|i-ZQ{>}n9X1BQF32iB-RPqg215dc6fVmQ0R1 zkgUI0&9P@Tc8&y=pD zIlm+hV(=cEzrb28S0~xQZ*8o3Z=+$31F1I2=FPJ}^N#uWW z=SsJ&v@QUga38w>V}z(0@;-qyx#!mH2{`2y@N!)W}p82tTBtVPBlW zuiTG+Vz5q2(cdpG42;~-C|Qjc0iHr?E;@amA?@j0i{JK*NY8hWUabm0OJv){%5A+b zTkFWpSt#FIeOV~D+q)XxwPJYguh)|x5x(c2qD3$_xy^eiRsqfUzDqgfg$oh3*Xl8( zIW5!7M?E0Bqx(kYivmL6H2OOHjrUJ^`EAz&F@f9(6UK0c`p9uDKEv+61|`Mf9l!7p zrc@O65l&A7R<>2EZbeUCK?+rk$1ZrVm*YuepmU2p_?VYCj>pTg6;4dXMN-m<8O8)V zKK(h(Df9}h_4t-Iw!e88Nq2UIrA|=ZQP!$F=b-(d@z#Q~F9V*Zw}6Td_liL1$#6L` z^gx|~FKb8u-JSO~Z6PFBH~(^OwHjSVBF{zmIgd@?k~SpOx8-NR)~N@G3GdsU-rl7* z4mUW6v))F>dC<||z?`T2P(zs3Ds+I!?DQ>DoLwKpMc-N%NK;6;M#Rg5r3w7AzV{Ga zD{3J<$Nn^lErTeR-%(UcomO+Xbv{!QR_R)Hf1oqi*6}5HdvSfEwrZ_Qt#H?1u-Jq9 zTzEVko}h1fQs$#HafMz*Taw}gLC>#tfExufsp$R)GlCG zgCj7Hs`R+LbzsFwdjq})sl@0z!G*+WdQWdz^0(FdLLPw5E`OS;ykFR1?v5?hyg$BO ziZY#pTx5LbA+EK$rr0VxS-u~cmouHy<3hU0&i%K#qviF{?Y=M9U8m2Rw*+sYNYkf_ z8fyf~CcPqo)m2{e(!<=1ULK%NLRQF@gG8Rmid_Os3lFHUyh>$CVY>WB;2VXcOb^8| zNK_W<+2TQmVLC|%K5za>#nb&z7Y1e>79Q?! z&a_BpTpd0)BDa``uL(-Ui%V#`Kf;nu0aofa8ooCResf}9uU6V?>nL|5UBSn1anlZ7 zx#MBS>LP|^fyo{PypZw1nZFR^+bNMf1gpLmh|=72E@wD%hX63S>lSys(e~*EYhW@Q zEFmgRu=l{zxOI$1e4kN$EB_hFjjn!asZ{M^KesZ!fhUAQc_N81hj>yzvG2G5vOp>LpvPF7vP&@%bv7g zyDT_FOuaMEybI-37awnKHdqlp7Cx>+(LqjY`SQZX??L>)LXoplzWu4bXyQ{I4Nqsy z$Z(7Q_hgHu$>aRP!PHKkzqwI#OpSnnRnv_bSAK&bT^mvw1jeqTTa|1`Wzsj`?oB_~ z1n1!^TRQRa3`3sRV$hLG(;k;cw(0%N2_9N75S>F;+PKzh@3@x5q-1AX-*5uz+1#Js zv+ZAl1YRNNBel zJuf!i?BxwK>8-6Eeo9=4SxLcJQ2c?*^69pYZ55B=Y#=59)*RS%#0d#{SpRSG$bQl zo6mCszID+l-wSE{D$WApf`u_RpHKpc5&TcOq0b`f9unos&jOJC6rYHh`J?9cLR5Dk z+b6d6c$#U|!wvq$-nF$C(mLrGUsgQ+mdU6*TQlH>X1$x;6;O1VPuIIl=15BWa8G;e zmI)&%fCv)^Dd5JRqMs7*VfdyzgCAME*n({2faZ$dk|(=uq3M^sE15YYV>nXk6Sh1J z=jp>9!`as*9ARN{XrX7nqaKX9xph~UzR&MjrBXf-V5dTKtsn=WoVhUc{1PF^WZVgu zG=NWoyK^=sWw>`44fcTG&lR${kNuJ8ff1Ep)fSv@c2d{cvXixGnO7YBjQ?lhT&iLjtNmHyX?wdyp-0t?4PEmCq|N#6k6ZAy$-{yWr}05JSwsrjgey^U;W_Xd4Mz z2r@C`6A=_fh;Bd+8Gyk;>SA$wq=Kju@0!tt{$T;>8B{f&u~7c^Z$wUnqr*9BjF5%CPC zG-?eX(S{}CBm0c&G%mDraIptU?*;*nhd5j0aZ)^1<*_+W@u|y`BKkv(XqCPJiEo)_ zgzP8-ygoU%yW*DXy$m`iwJs|97-l>HNs2H_{hrYaKkc& z7D>4B{g6UwdKD*bI4|hQ)^aHYDTQPJx4?dv~-YVgI-LySM0! zJxn~>Xt_gq)xNY>T+nrgmziw~dSA-+%VOLdZzvpJsfG=bi>PaFxN&9QOuvn-yy-#1 zH8nV~d}X9U8pEwMi_AqqM(@~yQPx7vhExwx*FqMm-NF;q9(ED;_p$d8-?^S2L=Px? zUv9tE|Jza}5suE-x7POMC`8Qp9W^W2_80QXV+hb-l?=*_qUJTDVF!n2uSn} z=wd|<6;Akbtk_NP+bCUz+dhc7zFO>l8LjTFga#!=_%v@{_TT4h!HuA7mUHy))S;L( z@QEa_Q+?H{(>zP#c1jkHkO|?X$jyUVin2Wo|3&q7e{i)alo9{iHB59ucFe;x}Ce3Rkzqdff779RsCbnwPWW1K_3@53yMzT*oF1 zeC&8N5S^rj0=avme-gysL$n%pN!>paHSK;?XJwF6>7Ex83L`4&z=&O1o2Zdk@z{3s zo^a$r37Ab2TLB-+Ev0g# z(?1d9Hn)YWDON=Yt;GGwSihIKhogR5eIojnyDp)yCBt%7>+F6l#6+r3ah~Lm>vzyi zP}kF`wa+1ntd>-!^)kApk0O$^3D&wFXEt`7ULmWI)eoc0_Ehx}o6T`0q5i4by=Qjy z5SF3MWB5D};V=BHJ z7o;mQF6UT_T~S&Vn*&xD8?{F~ryr5om7d$G*9$?!)M5G-gMMf827Xpv;dTuBC{v$860uuf`-# zlS$q11wv`MXjVd@U#&aJLY&UO^l*4jB?k+KA3t)8jwC-ck{EoA_1igrYnYksv`rX2 z>|v-K#T)qk?X_)jY(jkp)`p}BhQT*XR-37^@6--0XxU?7m8QLKfJS-W(7Q91@E{CQ za!U>xy9UocL1*b)EDbjYB zTpqXMHYI2XUv|SfPX=kC^V?1V7wc%e=hP#+T9 z*F7s=xx}Jb`gbLrQc2`?Vo-0D!tMX&9rfVu(;=;g}kr(LNu2qH{w27X0{@BDkR$Di!t!F47ix8r60i8>&JgjM1d zri%e_;8@TXz0m9eJ_6ZNX{RbXR%>AT1>CkcP`;HTZEVz(i(^MJ5{)<$h|90!eYWpx z-fzQ$KxK&)6%{>zBy`qe+YV? zb0=~dSc@>@pgX&`XaE)z$D5C2>=nRXZ5)iIhE9!sYSPr}cEW)hE`MZcoI27E)@`=f zdT}Ii4N*oh&Luh@G=F5PciZxhPS&*a_My^zM z?y!QUyUgmVa6*+tDDQ_3%c`JEUHp(>%rJF-dVhtF3^gC!F!9Ev*=v}jtfZ9H#j@U0 zL1{FjxxbQ;;}qj;00NmZeAW*s(Q?659;!AGw8utvu7779M25nBLHu z@sdOJ;z7dj7{0~eZOTC;k6h-sd&*SXFqa|2@1pb+*^F?PD zM^gQRG>+2YEP0b-OH%%5w*uLQ(LfKarw=sw!tkwwRA=zhM(tG2Hn?9moV+f)!n-#m{_9aeyeWSPXq62J0w<{zPS__Guq z11*y=U-$9vIV~HEs9Yq5daCnM5%5x}_))xv=l{-Q^J8#_EzWvQy80$u^+=}h;#;2U z&R%E}KO$gfHMpHSTMvCryWuIT{DxI|_baQFT3b=GS`;~)pSWN#-@o$Lud21O{rPH4 z=e?tT57iTM9|x=>i+RXnY?g@Aa6^T`-@1UGDqiVvQBl!O)GIBm4rA^U`B>OCym6~H zv^(g{LiU=;=v=fG>_pFs@^5m7zb_{Dxv%ko4`S0evliX*36^kb+Tz5eX|dxh7t{4O zmLTFP?EdoTVx$3qjZldg<)oI_-ePh6gT8*x+dgPQZ*B*9th%~hcxf+ZW@ZgJIehsU zKll37WiGaCsrFhAwL>=$tOx~EO6W1n{k~@l?m895l76HgDrt|IRXpAFc=wtXmwj_X zp^sF$@l_I>3wYBoQwIYk@%)+ZsmsrfZ@4d6j?Q$C{(Fr>g59{!SAo)O@#a~nZABdm z=*Kn7Ov6VV`CjF)yI&pZm$t;4mo#Tn4&r8O%s88M+Q?MkswqF?CvZCru%3s9Y)78iZ^bvOyv0ON+-R=i(MtShF^{@h6fdh(3DT=HxIlk!_6`kH`6+>UWt$Ru<VD3$;8L#wzR9`m8AA=eD5MlpS7 z7MVe@X!tr6NY5@}UZ|hU7!9i;ZQrr=jnIU)bR^}7nWp;2`nG5ZBTAFj4Lv$0KIw1& zp8fFt(gY^I0}-am4Yj-%D1~Mx3e8}~Vwn|0FerFh-(0lLiSiA$34drV6Y#)iZcTyy zfHeyPi;(;4o0r+~nl4(%70MfTmm*%1jXG|gW_8a)2V z((%EvZT|V2Pa%#$^lS&?xfl%ZbAP-2WevUT`|;8xvt-!RF(rj67_)V9EogJ-C+q%p zFRZ!?Wansds_S}%^2@5MT`vMEG!bby$u_y3ly+K(<905!hjs~^FYY}TgGw^^XVzZD zCdG*_ZpiSA&M;yzrvHF&_)B3Gbo!4==BEunm3slbF~4MR?02 zvOO=ENDM71&3a4*&XXq_DKS`3k=(PYn&)UArU})t5x7=7ZJE%*eEB3!ET+E-TPqCo zTfzr+Rgs$*mfJA91A0!qW-_CR75$Z}3m$TFCy&UFN;_?=8C!3b>f#fb? z2y@n_Kl-A0F^JR0FH~Zh2*R35s9r298KI*+niXqx{`exbkG&u_lz-0|l9d#ap}8`C z5E;tAD&%FVlc&Za!{ZjY`k#T>knkl~BPcQGdu{~B{$xbeu@hBF|J{X(K>o&iNh<`A z#_KqG&MTy{Fk+%XIdA=HucawD#4tyw@1Zmu2nJ971X=!f^Mc&?(mN|pih-cmL#Sp| z%|j=o^4ovx)MF40;gs<66juAW6BTL(!{hkxQ*w%<(~3G(#6fSc$fTxCG~sYO*&w8h zs4R|2iuF&*kA8QV$|wD|jwHcH|49$*n1E0nhNn&*doVkdpVnqhgVII)Qq+;TU9=x$ ze1NNDQ+Ya#MH)YO>ElUh>hnI-12k?MikUUKeD_|qM+dP&OWK33ndzW!p)$23*0;LC z)&u)?_ZYFq2$UVim(k%wfI~X_D|fSE_9JxFI<^FT-0_2iz5d3J15(qS+3vg61F1w< z{?ak4`_xldm*8;8nG>kUAl2*A@Xg&&Cw#A`lVZY)4lJqnj_%Gn96X`zLD#1@SJ*v% zcO6mbe>Wo-h)gqu-BN;oFjEX{qC@VUOW909HF(eEy|Ya4LxujoKY+hh`jT08y^N@A z>yQ?WfP+a80aMolGacFobs)?%0^WYtA2{=m5VZckH9$*IOjMZFE2*rk{PO%ioivuT z&rL2lxuZWr0K5pqAEdkV(WBVp(E9{x0L;AxMh5WdCIH zze(c1tEJlz)%@eF)@!sWt^H3HCQW9x=Y zZ?9jPt+j!_?Sop@>fL4U-vTh~N0zG0@Z=(3XrD+ zOB>bDAUKpJL;`9RH{_3=NNSqd=f%HJ8XsDZ0e(z4-nBc7*uMOJ4$1|!L=r3&07fh# zCIOwbAIT7F0Kl!-pQAX4!s(ji;D|E=ifL0uoey!v9g+)X16W?4`Ek{ZZ$VB1OSPU z@&LVYfR=Jv?fxLn*(loVzTflj;<(c9)^}&R5`%_@Ci$5eZtCaH3x@d}I*e|AuSVm_matTWx7 zEM-bpmEYanRo!F zr~b4+aFY@n8(WRnsrAeTP$!F1%FO~)p3_n3!mb}7>XMR@T=Apz+GYBRg@uLoBZnKP z!J(lX@Py1|yyhTRQdZ6(W7ifGyRC1(eyZ|Cd|^)q6vtxMCljrDsz!xnWz3KodVhaED=X_}_^M$-NXR`ISy@lf5xTh% zTmH3!l`gk0t@Jp3KYqAg%utY$PNx$oEcGKS*%8)U5Zbwt!ovGteif9IIswn3{>@nr zU78q@{KJP2FyVKs<|7%A#~UNfq5?5@y_rtrsdyaqvw+<({R|2PyD0-*UCIc#Yy;}8 zQ!n7}jkeht-qA=#dUu{Z6}jv&PC+zdq&+W{fguS6g@ro@D=UtMh6ZQ(78jlO0a~7F z`d=r3O?g^R%)2{KR_+FBaEIg1xmJKzp6^tTTo&XUT^~mKbpyB=F&SB~&lSpKYdp80 zq@?>Uh@5z5kKxqn?Q&zYiHk4p&lWd-`t$(!#65uHbVg>h*BPm(5O9!(PweYBIaN;B z==-o-x0XT>q_U#7|BjP+tsXpk_Dnw`2~bNCN&JJF_C!cZOJiu4>IDN2CnY00y&T?M z1c0$l5EWuUqk#b>j@RJ7hx5*Os%e4&0A&<rr`BrGejwY(G{LQ-}dY!(oeSMYw|^dJV@uXo{v(2Iyr1LeB94Iv>Rn2__M$#SFUDMMswefU;_ z)kNOR&22K=G$tV-I6j`#cCm%hWqoL?_tV89h>!l@JOdm)_D3k-r(1wI0+ThIg3FD1 z1^pXP5HwpDH0Bl@lBp}()z#hH*^%+|6dIqHpfMDH;d6ifQBYo9zb#u>RP?tN^>=vg(xAnI z*nQp!+u7Oq;O1%{dF|`7;9J(+-Hj;J6fQ}2KAWM&zgIqdMgg#C6)MSRC@!l6rC_JE zp06MsNK)DmAtokX_|t^%n~*nHEU~W1%sKMI|S06^Nw8v zs^we#XASb+{GT6x^GJR4T1(4Jqz*_(j&HsDIXSt0VmPT-6-r1`MKjmt(`=;jiA*;3 z#mkpghpXSkntb;cTQU88FSl6el7`Os?Pg^H>D3Jk(kG@$p>@;IA{8PiZb)Zh=`o}CEvNN?SM&NZLmtb<%Shx zXLl8E|7+b{e)DOkNUPYkmx_w&t;(mw_@)#Z*V+A4_s?@l%~^Z)^IaB%P#Sd+H^ z#P;p8lrV+M-h|j#$(MP`Url?X#_H_mSnmQd*sE%m2jM<9KmVnyZ1Ap*p&@M~wLlau z9-bAL0bbi_?o>V-?JrX!31GS(K!jcY#&_9}k&(q`WT=8m$jE5Ecp(MW#C+*cLJbfy z>=v35LI`P;>KDCij40-^fn$$>)o*LM(o|DVPw6wiT^7)Q_1dZIwcU7EPDeb(Ga@Pt zV%!NpXHR^U4rLV)`CL_9eU*)CucfIu>N;g0AIGAW2b`*?q@+fyDT72|_Y9!YN5eLrDHDDel9C3d#!<0 zPtIki44P+ERXw`|muC|YNCMHkps6V}488q2EQf9mFbR8YwAP2*55fGAEbYSyw37*%#4iGR|Sy+0vY|PBe+`e>xm2+$IwL>nDO&z!7eYfB`H5Sg*rT{cT zeRSSmP zh;D12t}uB&;a6@TB7sqPJz1iAXUH7wVm2P0IMn`<0}{yi+GqFD`OWYB`|(*|0xVdH zrP>n(8rhrMFCtJc9Z~(kaNyH9#@w%k(dmi zZ3mrNjb=&$rA{IZz$CqUig1u%EW~~YNf-B-U8zObiflV*pM}=a0?!)cYF9oyJj@xh zv^@IVPw1+qsQ497bT^yswe_}T(lZ_{_!Hli71O`gME|el%Ky9IIle{n_D@MGrsmIs PfRCcAs!W-bap3;|SQ5Lp literal 0 HcmV?d00001 diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md new file mode 100644 index 00000000..c635fd83 --- /dev/null +++ b/docs/cli/basic-usage/index.md @@ -0,0 +1,414 @@ +# Basic usage + +The command line interface allows us to load and save `States` and run arbitrary functions on them. + +## Setup + +To use the command line, we first define a file containing the functions we want to run on the State. + +```python title="lib.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/main/docs/cli/basic-usage/lib/python/lib.py" +``` + +We can run the pipeline of initialization, condition generation, experiment and theory building as follows. + +First we create an initial state file: + +```shell +python -m autora.workflow lib.initial_state --out-path initial.pkl +``` + +Next we run the condition generation: + + +```shell +python -m autora.workflow lib.experimentalist --in-path initial.pkl --out-path conditions.pkl +``` + +We run the experiment: + + +```shell +python -m autora.workflow lib.experiment_runner --in-path conditions.pkl --out-path experiment_data.pkl +``` + +And then the theorist: + + +```shell +python -m autora.workflow lib.theorist --in-path experiment_data.pkl --out-path model.pkl +``` + +We can interrogate the results by loading them into the current session. + + +```python +from autora.workflow.__main__ import load_state +s = load_state("model.pkl") +``` + +`s` is the following object: +```python +StandardState( + variables=VariableCollection( + independent_variables=[ + Variable(name='x', + value_range=None, + allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), + units='', + type=, + variable_label='', + rescale=1, + is_covariate=False) + ], + dependent_variables=[ + Variable(name='y', + value_range=None, + allowed_values=None, + units='', + type=, + variable_label='', + rescale=1, + is_covariate=False) + ], + covariates=[] + ), + conditions= x + 342 -3.16 + 869 7.38 + 732 4.64 + 387 -2.26 + 919 8.38 + 949 8.98 + 539 0.78 + 563 1.26 + 855 7.10 + 772 5.44, + experiment_data= x y + 0 -3.16 1.257587 + 1 7.38 153.259915 + 2 4.64 54.291348 + 3 -2.26 10.374509 + 4 8.38 155.483778 + 5 8.98 183.774472 + 6 0.78 3.154024 + 7 1.26 14.033608 + 8 7.10 103.032008 + 9 5.44 94.629911, + models=[ + GridSearchCV( + estimator=Pipeline(steps=[ + ('polynomialfeatures', PolynomialFeatures()), + ('linearregression', LinearRegression())]), + param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]}, scoring='r2')] +) +``` + + StandardState(variables=VariableCollection(independent_variables=[Variable(name='x', value_range=None, allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), units='', type=, variable_label='', rescale=1, is_covariate=False)], dependent_variables=[Variable(name='y', value_range=None, allowed_values=None, units='', type=, variable_label='', rescale=1, is_covariate=False)], covariates=[]), conditions= x + 342 -3.16 + 869 7.38 + 732 4.64 + 387 -2.26 + 919 8.38 + 949 8.98 + 539 0.78 + 563 1.26 + 855 7.10 + 772 5.44, experiment_data= x y + 0 -3.16 1.257587 + 1 7.38 153.259915 + 2 4.64 54.291348 + 3 -2.26 10.374509 + 4 8.38 155.483778 + 5 8.98 183.774472 + 6 0.78 3.154024 + 7 1.26 14.033608 + 8 7.10 103.032008 + 9 5.44 94.629911, models=[GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures', + PolynomialFeatures()), + ('linearregression', + LinearRegression())]), + param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]}, + scoring='r2')]) + + + +We have three new fields in the state. The first is the conditions, a sample of ten values from between -10 and 10. + + +```python +s.conditions +``` + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
x
342-3.16
8697.38
7324.64
387-2.26
9198.38
9498.98
5390.78
5631.26
8557.10
7725.44
+
+ + + +We have experiment data corresponding to those conditions: + + +```python +s.experiment_data +``` + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
xy
0-3.161.257587
17.38153.259915
24.6454.291348
3-2.2610.374509
48.38155.483778
58.98183.774472
60.783.154024
71.2614.033608
87.10103.032008
95.4494.629911
+
+ + + +We have a best-fit linear model. + + +```python +s.model +``` + + + + +
GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures',
+                                        PolynomialFeatures()),
+                                       ('linearregression',
+                                        LinearRegression())]),
+             param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]},
+             scoring='r2')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
+ + + +... which we can plot: + + +```python +import numpy as np +from matplotlib import pyplot as plt + +from lib import ground_truth, noise_std + +def plot_results(state): + x = np.linspace(-10, 10, 100).reshape((-1, 1)) + plt.plot(x, ground_truth(x), label="ground_truth", c="orange") + plt.fill_between(x.flatten(), ground_truth(x).flatten() + noise_std, ground_truth(x).flatten() - noise_std, + alpha=0.3, color="orange") + + xi, yi = state.experiment_data["x"], state.experiment_data["y"] + plt.scatter(xi, yi, label=f"observations") + + plt.plot(x, state.model.predict(x), label="model") + + plt.legend() + +plot_results(s) +``` + + /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names + warnings.warn( + + + + +![png](Readme_files/Readme_19_1.png) + + + +If we run the experiment for another 3 cycles, we can get results closer to the ground truth. In this example, we overwrite the results file each time the CLI is called. + + +```python +!cp "model.pkl" "result.pkl" +for i in range(3): + !python -m autora.workflow lib.experimentalist --in-path "result.pkl" --out-path "result.pkl" + !python -m autora.workflow lib.experiment_runner --in-path "result.pkl" --out-path "result.pkl" + !python -m autora.workflow lib.theorist --in-path "result.pkl" --out-path "result.pkl" + +``` + + +```python +state_after_three_more_cycles = load_state("result.pkl") +plot_results(state_after_three_more_cycles) +``` + + /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names + warnings.warn( + + + + +![png](Readme_files/Readme_22_1.png) + + + +We can continue to run for as long as we like, e.g. another 10 cycles: + + +```python +!cp "result.pkl" "result-10.pkl" +for i in range(10): + !python -m autora.workflow lib.experimentalist --in-path "result-10.pkl" --out-path "result-10.pkl" + !python -m autora.workflow lib.experiment_runner --in-path "result-10.pkl" --out-path "result-10.pkl" + !python -m autora.workflow lib.theorist --in-path "result-10.pkl" --out-path "result-10.pkl" + +state_after_ten_more_cycles = load_state("result-10.pkl") + +plot_results(state_after_ten_more_cycles) +``` + + /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names + warnings.warn( + + + + +![png](Readme_files/Readme_24_1.png) + + From c7e50972e6a63abce2ad6b736030b9aaa75f6cd5 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 11:30:55 -0500 Subject: [PATCH 02/16] docs: convert readme to index in cli/basic-usage --- mkdocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mkdocs.yml b/mkdocs.yml index e16c828a..7b6d30e6 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -28,7 +28,7 @@ nav: - Cycle: - Functional: 'cycle/Linear and Cyclical Workflows using Functions and States.ipynb' - "Command Line Interface": - - "Basic Usage": "cli/basic-usage/Readme.ipynb" + - "Home": "cli/basic-usage/index.md" - "Using Cylc": "cli/cylc-pip/README.md" - "Using Cylc and Slurm": "cli/cylc-slurm-pip/README.md" From 10df3e49cb024934dc6bc6164a71a85e86b56cb1 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 13:31:30 -0500 Subject: [PATCH 03/16] docs: ignore pickle files in current directory --- docs/cli/basic-usage/.gitignore | 1 + 1 file changed, 1 insertion(+) create mode 100644 docs/cli/basic-usage/.gitignore diff --git a/docs/cli/basic-usage/.gitignore b/docs/cli/basic-usage/.gitignore new file mode 100644 index 00000000..13974321 --- /dev/null +++ b/docs/cli/basic-usage/.gitignore @@ -0,0 +1 @@ +*.pkl From e32b4f172f8b4e347c9f141b35cd8fa2af50382c Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 13:43:09 -0500 Subject: [PATCH 04/16] docs: update basic-usage --- .../basic-usage/Readme_files/Readme_24_1.png | Bin 43082 -> 0 bytes .../after-four-cycles.png} | Bin .../after-one-cycle.png} | Bin docs/cli/basic-usage/index.md | 424 ++++-------------- docs/cli/basic-usage/plot.py | 45 ++ 5 files changed, 138 insertions(+), 331 deletions(-) delete mode 100644 docs/cli/basic-usage/Readme_files/Readme_24_1.png rename docs/cli/basic-usage/{Readme_files/Readme_22_1.png => img/after-four-cycles.png} (100%) rename docs/cli/basic-usage/{Readme_files/Readme_19_1.png => img/after-one-cycle.png} (100%) create mode 100644 docs/cli/basic-usage/plot.py diff --git a/docs/cli/basic-usage/Readme_files/Readme_24_1.png b/docs/cli/basic-usage/Readme_files/Readme_24_1.png deleted file mode 100644 index 8c263d41050d92e6eab11704c33ed129a986814f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 43082 zcmYIvWmuI>xb7mPLka1UmJ(39k?!sgq@=sMq>)BaK)Sm-1eBBp>F#bkv;6kn=ZBYw zYrQe^#2wFsDauQrqY$D%AP{sZ$@j_-2rL~00+WG+0Di-@_W2L^i`z*|(@DkF)XDXO zg9$|LgOi<=t&^375xI+rgQJD54LdU@GaDnhxs#KfBM%FU_5Xc<+19~~gS(M{R2}dSYQEx6f{V^7glvkKUi}2Qr(>DJYCM9PA!e+j~DW*#O^NlN1{WK zRD6-FE~aZ~En~l2T=q_ULAh@FlXvj6cCz+NvtsG{7dS9*A6~HfF;bMy{ot63AN=Y4 zw{egvK6Mawj(q$6_Wj_Z$&nD7ZM$k$}a4e))nMD;s>_dCn;7#nrQPl+Yew z8yjX}VPU%PiG^fJ=tnUW)e^(QQH+d@$9LyRDY+@(5*8PA*VfiN?%AN%v`2|1;qCAA zhg(=IP=Oh$HW|J->A}2R4JA7{KVNS>A6YLd$Ta$0s5Ihj`s-`o-Q~Vs^!@Fq??^Z< zL;5lqzefVKOw!3_vH=!8{*Par%Rj*t-r)1NaD%7tyMhf24CFn>g5GFcW@vagEF!|u zC%WM~xD&XNRUS_F&fXeK{AJUrKR%j4C8`&t-n`ttq#J?~$u zhJ~h!37INQMz8ZVJDN@;u}AL7+^HPrU@!ud?z@^1$E6V_)nSFNBSZUd8a8 zAx%w9jaU;95JVDjju50nex`B8oSiwi9RE2yb>G|Dqhn!ly~P51**mwN5dV<`1Mzy% z5p%LYftHnZ{PyN@#$a@%D=;i7%4DWo?_p1)!)UqP+v{dE6tc0s-2zYRcYgoy;1x4k zXEnz*F)<;3sT>U5yb$h9h{^86_m3tfRrc%R$pgMuHCfz$`D_-sjEsy@_&qu1=H}3d zI1Umr_rFMxuD0JFIr=Ooe4Ko#re(8dbURg;rFsw70jDw71{g zd7Pb{>E>=#Rv^dPba?c;IFExy1BXeu~c;; zsiwBKzt8P{M#as|9f{AHv(zmN*49J305;*fO!C>Zj%}60rgT6+Ksq<2X$^s(pkQ@P zjr)FCL*quA3=$@$8Cc~-&*Qdq->2J1GC@+m2$uGgpdfgg)>H9JpF4}Q^KtFM?ePLAKZd(Trgo} zr+0y6^t{JvPXA@Pe<%aZQpAfGh?v^9Z^hdkJaeH{IXMA+5qQ|opF{U)l>eHz#`M=( zrsoli;g47fzT1uXMW;zQctk|rk}IE+F2qO@-j@aj1|et!-8G{E`wsdFlcW?B6s=eD zmJnhAFMKg2Xmx2i=|(-hzBcO)LjL&iVJ8$6?)! zq>RjZ%W=D?5)O`-y+A__9iu^e`Y=mJx}P7!=kNWpXFAW_&3a76rPVwSnUIpw3k`jD z>ZhkC5E21@K|ql-%Y(O%Dt7#~r&*!jO`qH>m^)jt+SZxr`^WNi*YmN}rQ?=k0S@c= zUf;j>206L8?gv!^vsK2S!>avRPZzYLo(HVTDk?Cu?cTgIx{l~Ef=^sC`kqY7Ugzi? z51TB=n3&s1IySq%H=njRJ608Z@31MwBUd;(ZqXxNGOdA>#z#Y_x0>s=ZdmFEm9cRx zoIz4S!Bt<>v%Kv}ySlm>{A(M82BdbLTaMKC!T#xHK=3TNHzWlzIg@py* zu-@$%isv;&>Jo6+#c zBVw+`4DMvFqymeGXuo<{3{S83@p}3A!3SL9XC{Bz^3zoVB$Ajrj^Fd@$q@p( zjClk1D>^cDY}@L3X6F9f+B9vxe95E@-%0j#f~fDd`V15eDJiMl6Gsrx9cnt+QJFVE zS9>PVXgjWmGQH?OcNzO88d^DLMMX``O~#(~E0XZtkV%K*2=~C|eVgZXwcV;n@<6^q z)`-E=8Qy^luSZ*Z&&-(WA>LOVY@C-b**q@Hua1_66E*aAt9>0D9716eu4;Yc3Q9Kj zk&uwcxwulgyStgaF+hi~RQo8Zr(|m&CWx$v^Ib)S$y-ZEXxkt(ht5XqijO*%FiJex zSZLq+_mXx8O@{o;xBbif&3(vW-9_&{$TfC-QC!snM4n{PIg&exxB~*iow0BDQR4MB zOM6~FKh;(H{(a(zA!0X0OXIM1aJQPwmjjDD!R>)XKp>^BpXqq-4~NLJwCnyeh1F`V zx^J`UR~o15jT;#m*@25^=v7o?WFFYW;^Noa#&UAB3Y%V_xbYO8z4@K&H@A=J7iQ;O3>+k|5kP4(MwxOIqvxDGs1tZo9T5X1r0PdHa54@K0No` z@5$-+x=!O_tv72CRJ63l4GXtZ6+W9BLt~jON6ittlLhAmf{$UrsCZ{{W?9akJj_6z zZ)|K-I&RA&U=T|xD#p%i#i|s@_kjv;@b_+J(RoG>`VJrR-_V&JqCSIo78geo`cnt5P#zrpFk@P`mn}oyU8{3s11#7wvP{-Eob{4dbc!37b zcej&EBJc#loran^7?q_p_Qwy&KR)-?755>*!KYhkwr9HqS!|#;LVpR8?Nmh|3vB1r zci)y|0$Y5|1e?_(bXG=>jt~NcGD?1iipRhf|D5_6m`cpo{|g5I%y5}g*U^!Ym&Z6g zJ+=0!%t9_MF2;Xj2pJW)XKYw<(Xllc(b~7VOMM~oS>;P+;y@gyYjzIoFG?CYUu~bB zkIGoa^7roZcMmpl;)-{%wjGa24a+`h2M1Oz2eVykeGxE=>bp=>r`LC+D0Od}q+szkmP!;>x7X667pA0)ofG-F3&` zrG;d$Bi#`{)3MHm_AN-#-zxd@Su&+^Q}cW1#ZfJU%6@$tcDT@RePxm!ry%(FdtZ5F zXJ?1BoebvZz!dPbo2w0R?gSd=0n z>fVu^`D;9$o)mmFhfD^ATRgG@{X6S=uT|lSq8>3!Goeu0O&DvMWccx%kLiD~^-<0G z#obq8<$@Ww=Y^_qYPnHg6Bgjowdjjbu{>Hy!~enI_r7ZGNLGn?k!QxYUWv%U5|u^b zA@`)4q0MfLrYgxytVfK4!ce$;N9oCwaQw^|34%9J!l;9XEF^8kJUL1rHj#(wSr%9N z-_-;^xE6lgN>J2Pl1XTfrP`#rTloO7x>-e%*bBkRD_KicfjfV`Klcr!(6RGc_oxtM~ucTmc+6Yr81rn@~Tb7@cp`wgEw4jM*aYR?#)Z9J)vPSG208a9VTnNVIu=szEAEWo${yv%Jo|?n;gIH z&>oGOI=T4CHjRt^Y$arn!f(4-onHzThebD}E1-5$t?eD=j1K79Aoh0a&(nUjEsy9R zQH;2_gi6mB^V@VG`-KMt42ANZ+dY@AzJ>H4Vg!aCkamnrf5eSJ+|_db>Gp{vLjTXt zrQ?H-8am6bHqTi;koG zAUNOH{^2X{c=CW&qhw1^=E3hyz-J+`nVBPz1nfx2$P|2h>BGz|kp~A`WJfnQZbBsq zC3GkNaKP5mXEKyG=JZtj1^XeQgfm^PH_W}A9@x<#xSiojdVh5YNEHBE_N&2oSU5QE z0eDo&m;JC%Z=La205ZHr+*CenxHg&>@xB-lV%L)rt(JI*jFnwG@fL0Rj*NX-dl)3C zlV$ALm?-9H7b4lo-F`)l@c>2$CfP`<`#BxG#gXsHN+9OhLCt8j^S=5kN=mItL;srI zhl%epMI|Ncp!sdxA9rj6vh?cBo9BMj)ojeoJFjTuzV_BzFMuXrke%&kS>DvYNvQAp z=Ww*|7iuLuB<&~@KT^qY3R1!&zEyhEv8%gYS;0npgO zdR8Ii?CjWnP(az*$|vw}(xc+@22I~v zoCtFK9N;eFw}cA2%c3A$5DpUy$&81-_1e%(C=T_lOI(eq)hXn=X`6fE%a-IP*MGuv z#AehJSW;0_>pR;Vb_ZZAMbK9O!qV};W;tED3La(^?Cdl0ckdFL9JgV$->}-P2npQn zP?k4s5k`~p4^3$p{A#pchv4%#6`ntU2YwY#Be#a>dlPtG<@ocJ0+77@?PfAI4i0=LxZ>fN_7fnVppOn_@_S0k z%2Kf@>(sv_C5`Sg;{HDK7iq}c(GttC{{3W0dR)x1bD0E z;Svt;l0UcGDfne>iXT2uK(3cu$pjyF6;j#FFnk}@$@KKo0Em~6I{na_B1h_pD?t!G zr@;$P;$o9F-9XqP?KdGJ!TavYNn#-SZdbu~2!N}`(|)4cr~6}&I*vE{27gh6OiZXz zUoskQk7O_#fG1f2FwZrUlDyN~Vh%JStri!i;NW1dhtq+Z+uJX3achh1hF!4I($a2V zPv)vkP<869U}~urj>a5@#Fc6dn(}w^KwV5t-i6rg@VG^o0sb z?GskP@wIeha|^#17e`m09|CJRp6%LJI#fay-*PhuTXJ*PD?jw4H<8I%aS-V=*ichY zbluKw{YuO5WoBYB`TO(;ibemermik=$4wv0KRWUE>E0bY5KIc6J6ntEu_=HoXk-G5 zo5L!K6BF*+84}>b$L;sbP)cxn8smF_h7}$WG1p*A79(&+S7SB`iXLl1Qc^SVaxK;m zz=^N+k3WB*lyEq1yFLQ|!*NPY;}pOOmpwNC9*JsoPfkbWLSYmWwx|#&Ij*KKU{(sS zbvgvEeUOomK>%6eqcu0=8Vd53M7=zP@9gC)qeRCkN;`jx<}^Wz(Qy zSQix)tw!@6tw8(Rk1v!~^R;1RIt|V6c7Otsx#^s&D#EDRq^+!MQ(`I|o){O>$Lu2K zrnxE~&L`WxkI{Fu1jRFZhCYvZ>}XmCk)D5i9IWdDrG|m`JI+6Dl<~9*TY&s{ftnN) z64HF&2%?wWWC#cFYOT6YiNi>J;GGBnKnCvx{*Pvzma31ufZZLxrHlMtf-M z2nq_yo~-+8TnVz}>R_(N4+c*6?7b5Y$#LsB#zKQF&`-VqBA;xQ>E6Go2}l#beVu^U za010ktI=+izT>HW=h6f0chhcu8a}rJ6_m%FZ;#S4F_no9paMZAyX+ZRb~fZMZ(*#D zY>Alj<5d!P<&Z@mAB)cC&C@fhEB`oW{mWvP6<(z&gvhw`R zB_AmP7n}sfGU=sYZQle47c>tBuq2Ebca08d05@8)Bf^nACatkXELWQtPB>-|2fz1 z;W>}YfAFk#4zQfN5UjZM&_LK_5~i(%a4s(#qKJ_w=cR`F=K&H|9`^M~|H-2xc5?i# z>EBrq5OW)j5WFFD+Ar#7>JwqU=;Ab|1-@HHcJ$Ln(Apdih~|fX4_{P1&qCuQwB31?OhqvVYT)TB`bStW>L}5vY_r zt$!^m+QcO#B^&f&z^kdOmu<`Yh{4IUhg0wmgkD&=Sr6M=6@P(O;aFC;9IU!cto&Ff zawm)%fGu=9NyO5{K=2QyjtE&_E-H;D;TKpd+Ht8`UCv8NCwvRyN3&d%5EiDk)Ff01`O+t0sr^tH&H3T*VuI76O-ZBGt zy5eGGz2&iWgN(x-F3V}gqtl6?pwyrv zGcS+I%iB9FENm6%zWLw2bv3ntPo~*4hjn%e0U;5JEtWDH%FCk>N!>sOB0PWoyz_UF z$}K30^0&tTfWE)pmmDR5gcf`Mj=5e?2qtvX-rkdXGzu^1H>F*z8ufT^zvg4b^vxQ1 z#O-*x+vmF&6a8pvdIqXf^~XW1f54&jOxovh-{2giJ+%2dT<+t-K+#cpC5EnEL_~a3g1UdD2DQkC2W5;QTk7Y}pI5FHY@t`+yP7q|!NaSuoMG1Y*rf)FI+S4(@O!+~ z(6xUC6>aVhYPg6oUNbNNIHz$lnf26rFjqssX+vDm@zgwwGz|K@J5U1Mfg+g7?MMSi z+`2y^sbPO4LF?UKN!tx4G^?2oL9{3m?5LC;5>=*&ULKV=;gI)Ry`mQ=y=T6_xr}&$ zBbb}Xukdp}ar?0JbbWyLZ|TfF(51{k0Ua60$*seP2R-~?sU;amj0rFIrwbIa`{W7K6-tR{r>5xUW}fbz?`bsvX{dp0OKNR` zd!`#_f~y+&yQW2azr@(p9J%UKgq=936moj8e)==6ds%OH@nFJp=rS@t?J|kyj&FL3 zDe010qKFemmrI!!mzKV-n5pr;ce(JG@q7Jd>|7VZD!^Ux&;HNJVkws zUf^Q@DWu2zEzsItBA^q(3t3pu-(MeZ2cR-T3@7rWW)EFZP*K5hn^v^F1nXNs1Fg8C zgg+LWzjlY%y@K_wd{@YKqD2L1hgmz)TpP)fJw)^$(oJ2J7 zAV62peguUtKn|f`XOA}-PCD)Q`&fZzkO9^sdP3uXc23#9A_fz)RL#vuj#&)dGzYDZ zQ7~4>qh5Vlz@3~il2`c54%OrD&Y$)JjzOd$0;^6x7^pT3O$%u30-wUB<&cBa`$B13 zV3hA1Eio~XQM1wyr2i2Rh)UHT|P-2$XUz(5T(^iVAe&m@O?Wo1j(}sYf$vRR;lb z5eEv6P5Z5B5|d6y*I1QXQEMx4&0OTvCu%OPSrZ)q=DpY3E-gzV zP)gzL%?}lUK`Qf9v|SO#@Ly@t8stM2^wD>!{?44K)GyCo;|fvyER2eyMf5t>)m~Ip z<2VmO4;Z+Rwwut(__`(qgy7q!x*2__bO$IJ)T9E26SP{mL9L3NoCt{Zogq{t{L`9h zF`0h~uqZ&Qr0q9rs6eYu<+6XJAaG07aW_@r1~58M1ay9d|1$$h*bw)^>1!>%zmk<^ zLi|+sy>AM`pkWEsn&SD}TH1<}gbejKD-~u@%@p+&6F{G5tvI%RrmioVUF?jb5x)H# z8Hok~njt=?P5N-cD3k%Su$WyREs4 zAV_~}Z9Bg;2=x!sevMQ#a$SFN1G3Kh4rOPYPiLJta>|UFum{8?GfC*7I}D0CUcC&3 zz3^{i-+DON>RA_LIQUgN?J9#ra|7|!eCEODvGGNsQoC%V0wigjr>q&#W!RI9k2+9n zh^Jttm$G++&E8i84kHlfPQ2(O&*J0I;Lsq~Ahi6MpIMQOxsxU~$H)C0vI&LB@d^T~ zz<2lv`1HsC(@WIL%gcns#HIrSMMb|pBl{y2Ma7l+Hj6Y`;DiA;q{Yj9Qq{Sxxw(0= zLgqq2PLQFjwP%|Iap|j0h~52JsnNR!GR4F zk7Ig9M&Nj&_`S27eojm*Do4aN+;;iueFDd!tVxQ{)=yxM&!v?NaK|RuI%zz^9tntZ!y^nM z0^+$!;_@I?lENPiOW*~W`d%?qghx(rUCcJQOBe39*R#F(I-2smkIA_>&dOjsRoV#} ztOmyaM#<^a84^kFrD6HWUD>vr@Ew78F=LxJKEjtUV=di z{ySPrr))fB>{-hb5fab|0AZli<(18gX4XyLYDUhz-wS|O##+!aQL$ItZ^O>3OBrNo zI9QqnNrdumBx7)_i8HonUMGA|Kv_gsnH?h!8BfTe&;W?WhUS! zO&~!Z3x~I<>u6h{*_ZdbQ?e%`yvxk%B*Pc{)Otlc7h5k(Q89se0#_Zznzf?|`5l_h zy&nZFE9@yt-{R^&#Q;H?i%dqR4zZ<2W=m}IL*XyPWl2c!zS@(wkPf=%LdvT#0;$mu z>Jr?u*Ls-ND1H+)XU!XR7x4ea7(SE6rmC#5l}&y{+0e2a{7G-Wykid8zs^2~%iy>@ z?P_S!JcL0z8#Ei~wVx%K{}J}`Pow;{6CGsF_&?z9A@m{mdL?h^u{cI#%6@yoC=})I z&xudj40-vfpp| z6+9PbL_yQJYK1ZTbp}!x6ZhXeDd@vk89P3(y{y@%3+b~uYwc~US1j?K$SHjkWE+Mw z@~!DGvgW48>^sMPO~9nfK=r$$D++{8gIr`M^x|*PX!58_)juGb7sC3Ml|Fun^O!iV z6^uax!1HDB2Fx34$W9ThiQ=+y{!I*9SWaWeGl<@ygdA;(Jrey##+J zi;S5=o@xfV@Z9H-BvaZK!3adcR5#1CSY zrSF|4{coSz^Uf5FRfNi3WQztnOGHA_iDJcsMc=1|X3+=F&i^-bGp@m9rFg}^^OzwA zBl!1QBxT(y{653&H&e;9P@Mqp|GDY+x*<`;O454Ip*t=%VY`Bp%hze5(oxX&x`IVL+7#gn+YTk(5Ogm@mhvRRVXsoZKfqzhuI=~bgR z4Z!}ezmgsuqO{&*K6~v2DJ%7s&6ZBDB1T%1P|^vDOcf7@bzE2D$Wk2S(uMIbh@+J^ zn?Kp9IjWI{O?X*L7Q4Qoh6ZQVX=*gmdDaPi6Ev65p@@BqlSMqlv3#4afst`TJZJcR z7`%dMM(|<_`7>P?{x12U8zQnOL7E=hYb~j=r*FX%Kx@s9lFAmo%>Sy5qjKy(61>hd?{lJYZj{@B)Gde@Jd~LNyb(AKuA{1si(RnRtbPtT^^+wpPuPFQ4Qc ze^ULYQ7x4W1yEU!KQ+^juw3ibybsODy`2BiCZ!=^s_&@fsj9}{Zz~T8EC{eRLqt~e z18!Gxc}!W6P-fj#Y0(JOlf15VR$2U5sX*#-k-neR*L>zkUush|u8tti4v&7k#c-&H zl|6P^>}e+BEC8ajt)MNf$zVeQ=$q3js;{N|V0WBRfE(sF&HY>3 z4mQ@~L#I|lzb;sgQOo^&u4zTd#Gb4!fhI2%R#Lyeq>7ci5Koe9A;|#8!P7Ze*aY$a zsVY4ImdF!o+++>#-Dh*udGE=77ym>7Z(8teQ_g7GHCf376-sqHpg*7 zq&rO54u5`+wl*=8y1H1SyCCDj-!hdSX9Hp@=2HpUQJ4d?Cq=h-D&DP``rmDJCZ3b-T*Vm+sm z>#pB}48GtArk)f5@NSTyi2uyM?yaG#(0oX~=JY$EFZ%o-pS7!bRga4xoA-o7k75vQ zos49*I-aW;9S+Cibok7U*{%f*u35KuX=z>Ln;_w_AAj8F+oXXV)bxrqwxe{EvVkY^ z`kdBoeXwG%R`0$3_v?4tOrDoin5f515xC&x3-Zi1zW`()L+@$!x^u^{(x>7Xaa1m? zPV`iD9Tg#2U%$dAG8Iqxl$qR;)MrTqGDn5>NC9CG0;l5)4}40ND2+KM60;b-g-pkL zkliUTy7;J}61q0+?UG&uS!fTOk6$6$UA!_9e+HR(?<4B8NHv2!Kh%Xk%Q7_Y34}?+ zndnNa)$Nrarmr#Q;@K>7i{IAsG=NTbpnHfg>yy-p-{SxKhE&cB|rg@v|KRV+wP_PVenDqR+zCQ$!qs zR0W9UodO=7J_F4%?*miZx0M{r0T{e8G;{osnH$1}t?KDzS#glQ2qCgY=YXqiJk$yk zi{CA^N2y~Iv7h}io8EwI@RpY-xXC5dK%<3aaQBY+J;hRsQY0c&#PGvXfp1g1O~yvJJCWrr z(;Fh4K6~Qz15*xfW_vR*_NvO~b^e$T744Rh8n*l z3E#Y#^R+!Mmoxc1Iw)%3-N;!EWbXH5U*hn4&WLD?uQ)vxZOVeFOVrd!t%>;w3=riN2OlGv`NkG>lwvkHnP}g8PQ|%uk>n{mi8h^ z@WzY|(Qo<)U9+A=cvPCe?HG03U`^u}7*0P?o|1ZlKF*L3qZ?L)#M&QC3OvTD###Tu zFQulzwJ|?P%(lCyN}O@+8rd7a*&%d0?0&rY8XAv->Oo={2Z$>O;Ktv zO0khV<33j$XFDmqXu$cF3=O-Imz*6BrG#S0klMoUnYW?WsGc1e4JBPBd<<+Z!JZ7v z=Zl#n5;#7C%Fn33uO&%m@zedLPc>PE=3Lpr0ib)-Y_IFzuh(3cI@sZ6F{F+Dd@eZ} zLSReBc&9nAl(nyUVL`?ICydA)N28cMC&QzK`!lQ zYN2{DrxC%$xr*+EW)*5+rL$teI7DUM#wWVlUXMy;|~jooGqpI|+P zh^)k!Hat&+SV&*m3ad6|kOu=~+`qE0Dtj6AS;WfDefj;qm(cbCSGdvs>c8CAn?I0W zEG)uQkWy0`~xsM!mGHa@KCor{bJfx7zg9RJM?cry+HY$QP&LNWSQjOh05 z=8loVsGI~JM3+&eT4Da*G$4)UET z-yDfJx{W6*a=p?)P&P`9bx)N;O`hu9j#ZV+@yNziNL-4Mp=RjEY{t}a=r)+Kl%4u^ z)EhPV#u^dpH7$_{%*|%x%#bjQqo9Kme9;P%_gInCy0@h{vYc(?*y(sX zbAI*Z+VJONo|))8LU5}znIR-rLe>tsC^^O%0}eE4E_SCvUiB5IKq@}}$ z1*oa18TDIJfYl7fL>mw57Ya+Q5{DKMLH(}Uc% z4yFEEX8GVWCV-lQ-Us@nUAgbe$$o{Nia@#J;|z8Y0Wz-O7YVoL+vhFIkI@VjtrPnK zK(7H4&D$F0=I7}Pf7(2OCbv!Y_XZJ6xS0SU9y)Njnc@0}f|K+5x4sysxvd)}4vuQQ zY7}Lxa>!lgNwe8LO#C#mIuyqzT{UAf)TV?Ku~1Wg5**%6Fh;hT7yVvH0q;i?LcEcq zv`W<{BAdPUA@93Z6^*vBN_xP_X5r%^R^Q_Q`3^P!Y~|(cU|QfT#!twryaY<;>Y{ z6@@CFM~|)1te7PmL~=pFEbwf}#%Ks|A3l5lQk^H?_WwzAjg95)R-7axf7t0T*h;X% z-X?+kbPF9_X6up$8#J*)v^!LW$_N+Uv%0LW^AP`6e&{(E||8XvyOa5W{rQgSu>{A zsnC@cItms*JPcD$!HjAc@PL4~4d!QwBKkx=eE2pj01hxDBqSJCY4T-j^{gf3cNK5zv0Kh1E+yJHP0zfzc0K}8JhST@E+aOR zKXDyQ9sGXkV?2(f@N(m!UC~fzXl?7T=K$%mW#n>N%R=}J%)7DoagUT9JGkko&25Sc z!14hD(=;^VMD^10^7*Bukw8l3z1C{5Apw)~MJfd@*PBk^Gpqc65t2r0zOc#ek305o zG3|Mm+p)Szv>h%g6cnyFlf;%f;(^L2=b=u@o~b>Mlg#OOjTj1g&0F?A$khBg3s2pg z-)F}iKb*MG#AL1d1bp>EB0OSSd&ReZfg}z5Byc{!$tMfUEsSLFLdQ`V86#_J-GSte`sxo>85})^|F%ZnsM9hXbt#*y!PUFBOnB3~t)Jgp{bP3S3u^RLp& z4ef_ND}sRVq-@4@!zIzO+e&+ieC5m1p9}J`*B-4KdBjU@Er2JpOP_^SAb@ChI zezYerQR2E(vS%dMLa7ieu+}mQ-;e9A|7z4HtqBdJuawD3@-2H0eC0zT#_)k_zBU@g3NJ1;TjZGm zdizgPcJ-3Pm6esu4oE0^v^P?n*oaNPN!^=s=fcWeH;XYg=B5*g=Wo%*JT5+N72~|z zeu2xMo;Qd$_#^DONV+gvb%fT%*%rr@-I&wp-@%I*sdT5N{jHEsg-m{p3>4Y-8aY>L z;D}3-segfpSx_u8b1oePO=Fq;+vCw^5mjV1BVyzG(r_s)!TH48sn#|kDK zyYlzb!ds~+UXi4`!)bu{x2>yNQ|^-gAj-vaz(}eD->*&yhd$+pA=2;vimZi%+E=AO z`ZzZ#=dCKQgi?U_>UMlxQCbI%ZVc15_4WD#g3zr%;i*2M0kr7kyo0~E)XW#?Hhi{H z9UDcZkh$q&XRW`!GuUa`#p^ zUps30j7udarhW@Sf%xED;o_xxe!Cz13|t_ojy5s^XHF<=)3G6JA?Fb9aWRxul>iu=HF!Yht(dxWKEnv6h~*aQ2#*HiJ$gk5 zTKMW~_JUsPjXY{xfPOSvmAfSQIYf}g)Erk8+paSI#5rz`xDoJki=8!0<6a2N{=$}8 zAfCrhH|M5{?!QuE$!d*TcqOnkh>mfd5d(u-*YDMj(qAJhHcOf+(Ya5Fch-rNV(_YA_^Kz58h*9sPibhhtLqTjjKgQz3|Xc688OI11E_n5W+f0Kg$K03hy>MX_oe)mZ2imC$GE2VT7tH9N{H=BK-S!oZoYjDj(xf1LId$BeirzqS;&!uD#92Yr(I655|1K<6w$qD< zxr$$hC>X>$?iAP3Tbw?q4x}&sE)00ve>(!i_=sVj{-jQ=W-kWO?#3TrA zO?d#}RIlVRrBykx#5q@l^k*q*`eNl_CNz?Qwu*?!S1{6e7GGN~#KpkmOPd!D@0E#g z+mth+@tfIwpaRkRvw&wTS|h*P6Q#mLH(QlVAw|5VDN-$&_w)*P$JQyq*2ADL34V7! zOktik?I@QHg!pF3$;I#6DOzGMafs#-v47pxJbveb62HX>d3_~=>;*an)0H;e(sVA5rx#{B~8)6Q2y+(w2!*56HxfjwzlAjZ+ zVM5Nn>?x45LtI3)&<73xq@)>AoR3MN#MsbC57Js_qTTf?o=hWG8X@u}dQ#Rn{1Fk{ zBAvm$!SovjZZ#}0a>PUZ2G|=Vehj3>7qSb@^S@JbE(HmW2LWK3`odNnEm|>dB-`9d_j#$ zXxGLEuGYj1)J<80Mi#C665pbefrKMpjr(U7gS4gg0vEj3)}SOe%TIlv`zt&QWA(A7 zXOgJSD{dioGK|!RmAO*$F(@sPl)uhC`mz zxt(kB$({+f&qoVvI(?nmgn<&_7#2<-Gto=H<}iW&5&k>vO`p)1dEqZdfxMY6TT^r2 z$G@+e6Vk~hmXco*1q#&(4`SH4*@%O~e`{|OIHxl|*<)*}VfqgK7BBZDxTiOm)|c$J zPhSeZyD0{LDL6pbiK{yUk6?CT4}8iYBE&dx~*=D!`oIlf2B!=9pVmu%E{gRJA|2poEIiehCFSr4BHV9Of44$% zEjxt{(3!S=i_JtYbSY%e-`M=G1$lyp~T;*ud#DhZF%bq zH@}XJy63N$ZrlGGvICO#W*%Au!uigh#s?o!amD5^;8T9l`#F?B`{M_5|B)iaN8+0x z^DnNsN~?C(0UQZ8szu6tXvk;I9`0Q z`eGS9KboFeZgad|*P0vVa6EA{QKsCjAb%t-a`ukF(~}0b^S5*=haPRwixmnt;lnAn zEmbY-3w6yvJwB|fsquKr8R{!iS{19CrcPH_G-x>>sp&x)gDb@YX#fYG@=a_y!yIB5ccBf>puq^yn+5RBb{ z+)kX$iO}sz+=JpPg;T31^hKga+hpT9QcMrFm>ElNkB=auMVz#uQ-q$5GNx_n6`%aw z`HvGuEYEeR)yg9X(~nQJ-1VcMXHbKB{E3%mCa+8&h~JHGR=VyzLv|&hP?r$gfb~o1 z!>-8dg=3d!5l^awWB)zlrAu(Kd#zMWbCsV2#M;OX=VbM+W=17x+ah5rgG#z*KQ7O~gil;tZWG{|h( z%gt`z(EXyM1~6!YopP7Uk+uT}08-eVuUvL@c2^pJ4_a}7^ ze{wD6`SENs)~@;DJLvQO=P|pL(CYa8#kBea1wqVVyn{h z-d;brpuMt@^Fq1}wbvh$(1WV=6e$VT!K=|oz$IA0)sX^sb!Aj-Y)3uwuHh52?|LW7v*WC^ZtUy@KONL> zT$I(o)WNytNdyAVEh&q91kR^@1aPaLa+P4ZK;(lMlala!Y}P>Gyr4WovTieKfCRV3 zg&zhb2hirNuS}d(;+?IVsF^vj9G&DR8E3HZGpBubl-ROrnSG7KOlM z=rYw&aCX{KOc}#O_@|IaNB2gRqa^6Gli19PUq4wjZeOy2864f;v8-@4h5DeGjb zJz@|n1mZDj1F^FLi2$?x!$;C8W%ZJ=1P2q9IuPm7%8ks7B)JnpT4f@pHtY7`q+YqT zxcu*)wK*PwaG2pDtQ|M;EE`6WltSn0P;2?+Nq%G;u+DO6SBh?h`WxClC4RVbL5=>NB6=JP!+sn*3Rf(ow z$*lRJx{gPRW4DcDI`OD5_RNzaIon{llT!ws<6^B{Rg%DY99Wf+4%>AYzsHx>p_=44 ziwQjQo@dDerjJ=Y3f&02Xts>e!FBM-2HE#MIv&mYV``~3qoYY zJFGxKDdhFfrwvVsn)RIWw-4V9Suy+C%cuwI^K4~PnC573O@p65>gSo|&Qkzov;v5E@>Eh&HpQ8m15GC|NFN43%^KmDvorSZIv0LOW9c z7$Mjxsb0doiWm=}k#W81{SHRL8mf3zq2#>j93GgJB*)Kny>nPuIbJ4g#WcqF*j47z zL45VlJ2LGg8RC%h%z7d@ab9|tt{;s$Gu|;q6Z}1+@NU?+fKH&?5oUZzaHOq#==NfS zDes7dY1i&P7^baQlbrTlRDa0c>B7ld{8$*-l>2Jll%C%2IG* z0Qb)E>&lCaFkVl*uM>EV$Ln^Ff~aGwmdc%-=`r;q{+=bEyJ9is5*bE9Z=I#+mv;-; zqYt3LLpzwe`b>1^?ezRrAi}eEu_&wNa@2GCF9(-*8NH?->GGcp%H`{A!nhhB3uM zpH>56RpQ@qU>n!a!0}HoSQS_ho4u6%tzC7vi#;K2s zSp@{ywB4F6NePh>q$LIE?(XhXO1isSLQ)#(6zT5n?(UH8ls&xf_wR4-lmA3K;u&V1 zm|6E)*BwZ7e8f#%a_YsC<^FPm2S!4#A{5X$xZaMC5#qGEMNVs}pQRxdMK-*%2n$+> zm2X<+Q3Ifp`^-o~HntXjdX@KlW8=`Rl&VkPHM;&d{s3I~tNI2gS- zCmwR$;jDc2G`GT~=5nlP{MBjKtR~S)OhFVb_cccr1n+{zgk`AcBkxaYjU zMZnFWduO#ivCha-6X`Y`T;*ArX&U=b9>jl?SYsM~Ed|sBPjy8P+>c*k6HCzPw7Td_ zsTN_Ud#ms(aCGMkNn3lmfEzO*)d)f790vDUhf+ptH@WJV~JA&XNym@QW=hdq<5g_~S?*HSVfVj#0x&QFb z5g}rAdP``(b`Ae%0@+6Ip&{b^E+vOhKpMd>W^aTUWFKyt>c?c7S*(D$1;GF zfe2(69uo7&Ms99yEUT2cAB^tC7}ddlH@!--W{ap3yow#Kv4CNb_CF_TL#MRk@_%IS zmy^Q+G-?WK^`!jKM1;D^dhMU8uDNi3W^e=SXI`NDOkw+z{HRx=Fk*7~OBJ`>(>yo^ zkU*UL<7S>DMNy_w`O$#02tM_O8hZqRBhi*-BRLWQutwZIBE`L9R zmpx%jxamyDL5zdzu%tk*1BWmhQP_g3|fZrIM-`k>|LX2KG9bGeek zw?4F86s7qHXp**9@bEZxgL`e@-)|^wD!UK(l>Ta$(D?|c7Dgdb!+`n*XGs$L+L2-3uOymwoeEr0JVyZ|dF?Y?-AL9myN{+-hi#z$+ap~&LSJiNQ% z7S{q;y@q$i7vo+@QZ?qSOJI}~iiDcEhxbgU5q9&J`7*3w2Oe(^+`lc3UP0@jkrG{V z{#LWdo(S?$(&8X<6V8YJ|4L1kDMdv97~;MD;&@%}2n6ZQ^p}zg@Rje15B{%}r`e;_ zELfxH1ja@AW5pg_g|+fm-);}^<`h{XZ@+Kh1QvfsQ!PJxe>POHX++Zv?Bx3{$WC++6YY0j-&-E*Q1*y&j%#6 zz+c@Mo)~ZI;SN#JdTB%v_~0Ehk-p@sp@tGo=0Zw(wbbZxb8;?hpY83L?$!YQQC60A z@blb`^}r#_(aby<8MhyKGs{q` zZxllx3xutpAww=OxHeb!G61PqHnhk*zT5);LQK=eG2j24q)foxpu{J_t)Q}=$~_}O z<`wzmRcI9zt$ti4oJY7ig4OkSp)9d9jA9oe*DZ{fVCC)&n2RSaaYS6?osS;(MhF&LqQPmj>n2yJ#Z3LOO7l`7k0Gmk>xmsOyv>GB`~Y##Ygqo<=}2?e z2+R+tTn2*d5kyREEHw>{5r`X%cml*gaOb-I!BnA+D~AbPqYydW6V(dRr`f`m+YeWV zW%$y+Tav@V1aH#7iVdW1(CJ@9%L6HPnT&@f3hYyi0K1_6;XhJ(y5?@ZVR4Zm!-A-& zEHzCO8rdfM$WqKSyh;nFRY$>G9V?JpsZx%-*k2NKN!VxlvU@vf6b*{``7R)y#o=
xe*xum_4L?vW2-^@Z^bKhhS3k2=4Ip@ z{Aoqgq8hg6y-iwGP*ZvhC>9Hz@X<-0sU4&#pb5;{tXD-A@>S1^QeIVb!xV9UlG%<*!Gqx83%`v{l-2dW`Nb(;fDGLnHG7nGvhUzi zVY$dk-*hUtdm~d%!nW$c{E|mO3i@$;6eu4<3uahP|P!dkjP1ewHG<}WgsDb3-VdN zNZF@oomnScL*=bD*4pqEF$ER5&teZX|5M$n*4xQ8HhxnHHl&0Lv;5E~xVJJxG+j~8 zAMHh9V$w^=Bh8*qhn)#zykklnNravE_S|O|YvoAI#HpAQa%0u@GfTgJuNC7PCZ#;y z5DzS4-pwJ0#g_Wbfd4L?l(fr}--NgI^Igx|g60lEyy|Z6^*}!hj?-m$4>x`(Tnoa~ zswFi%BSex0A(MdtljCJ6-OrPCVa0iY5aAsYh(sPA(MEw2Hcr)uS#q;Z`d~YhzFi{! zwS!0*2Wi6FS86hWf&ZlAG@m3{J@cQK7Cr*IUS0=A-wg}tTylM4(?GfIC|yK3xP@~& zKW{&&AVnQQJ}%en|5nPsfBl*2OB{8u|3Nn`0o=<&Z#iZz$Wjhdl%vbr&XP|~69o*h z+UK{%ZjIIeqr)6m+aai_zv0%auze~P>@Qc!T-SDD;SqoDG|KRD37t}K34herxi`P> z$Lim3qdzgE)71GE^x#r_#{JqPv3*2Cz|Gf~T)Ug5zo`?N^UZoh#!Pa|vbislT3~kb z!~1ayGJX#KT(X|uXKHWGu8$^N{x*azeO!JB2^JXV^!Tf{&a#AarqH+>i4^nInM8Q@ zKwjgHV|}l*Q5=sz5_lY#EH{g%*7q>tdK#up9N(JNrQgvAQdaRBl zO_f^u&+W^aJ$#Vdqm99OCoBCM?QYwVsB*rTz>BKDL!L9Z*GToWu_Y(p$_UzXf4 z8QZfT=d{*GPFzl>1<22*>Z)Gi2=^UjnV;VHiJCpI>?AxoH492qhY{ATo-?cz)P3K+ zs6L`6U@h(a@tO5DpyBI*wBN5id}Ekx+N@c#`GZWCp)YDa^Zr$OEs5d33?+u1wXYE` z{Iw_xU|@qPsPn_(Q<(bL)v1Ki!TD@gRkh^?^YUn|JdnO`d`N5p0Dy$k5)TkG3@o5Y{-u`Fm^6E>~RfF|492 z|6JCRz^N2N|48E0-qP8w4mo{ftRqy+a8-Zp7N5siPwhxPK8S94h%9y?C^t z)l167gxYgVKL%6OeEtynkUrFS5}ukCFBheZJIS77Ho#L>D<1FP-#$>0`IQX@*$I)C z-~;!i2z0d*&n~Q2@0C*4G8ArpGPkAHUJh$U(J+ioVdnB~AJ*tRtpk%X;k1{l*0Kt> zUCTQQv{{=f`k=RmWFwRrMprmx`7uydV5QWQAjp$6nOas@OkFPA`-X1X_0&3*vY&&k z*8I~)4ay+J=mPX$diX~ls@6UVu<=TZ%H9)$g-Uq~P4cLHlvw+7;j_|jhDXy9)jwOM zF?UN?El99pjrnoN;K@q-Ju5KIre6%96gQZct$MpjarCsO_VM|>)gwyg9#0x{h%}tKCe^BF3n4y>8wZ8IOx>gb zdr-Nng53fLxEtrcmm$$g%rY0O^v&CDme|RsEOZg8Dcf<8*LPh;WH3xV-M!&iq~^55 z>c)j~q|{+0?-tC=c<0;jL3S?7w5^T!-Dv1*I1h&o3FSE=78awA%H!6?n9ivK%E#)b?$ePLz7_XUHUnz^EZ;;TD_>3=k3uGFEb%_FI^ zr8Ak$u82?ER+OB zJ`Z@6%h&5kS%oLJ$~%I8)8XX4uL-=7!rVpP6%m6WX&j_*@JdvD(n6cL(V zkl4Z9qV4&H<1~vv#r^H_h6s>(@A*e|q9*XW+H`6?5oUqiqzm8Qs`-(kii;%sQxu$$ zW>kk#FJUa$$6%i;_|pi#5VBp0MxppzcR_?v^YfoB;R#dbr_S@2o+M3mGVWzAhHHEw zMBWyQ#ZHg#)mj(AsdqrMHJPwC(x_nBIP6~(pD zfZuilN50&397JMwkfW3rDA3c8lx*KyF3|tkISpt_ZoMLrR{^`n_<7ChIn@M9#r_(+ zP$sMk;|{pExjUbX$>$ogi<8lY%3wO2biq?qT> UYl%<~5*X}iUaI1Iy%4V+U3f}1Qz<`aox!o<58O>70t%(R-&@37T(nt*myevnhP3;N zzczj^yhPw~??;g210PEeUD>L(F82c;c1gt&)`4UuPFx^Lx?2P@^|58hH)D^zHcu>3 z6(61PON!hxwIK^&e+3jT6V`-^DCd+KR}(Z3+c}>o!%c?HXJ4~ROCmWX^`kR`o2M^zXn5XU)oT z;Vx#S!Z(^pAb3S`k7%+YQKGfd|5MRr!{X>^Ltqe}O!^)Jm)n^n^8701dB%;e9+Hy= zC~Ihew~cSqm>=decx!{=3>I!=go;@`(nu+-GK8*wuG8=)hUS6TGZwUxpgD~0H2q-h*X?1uwAUKxeTK* zM3Jz{sBw^qFs}D$>eFu8k0tMujC(kzH~0wCTCP@8?t2^7r(VC3xi9}JqGLF9is_ItJJkw% z^6*@K-6yy=n zN^BuGts>O>5Brs>p12hV$=rOyjV>VJBArSHqp6Fhz}c)9@u6~|ZkIthG%voRA&<~M(vL>}xHd|E$#oiHqu z3R5_ew?`JFtYg8#dWwaidJja-; ziI~XCBbXYYj2*_*o;zubxw2=F;jzUhjp3%8PTP(6Li z|9VU9FI2yl#Ly3HzNJhSh+Ut%BV~R0^zeGftyOJ)TcNk=RDL({Rz7C3ru|$L$S$Rl z;S-B5a01W!rFNLXG8m=z@<*JeF5a~_3>ohpYsbdcZvjhsVd+^>!vIq(h6wl&}1RFjVgLEQ7R9>p|_C`Ig!ev;Nn3w4aJSd&JXrX-BU$A7hZv!Wb_ zT!bu$+$!*n@1?taJE8<~El{9J%P)GEda?c>V2=X59-{O79Z09K#9uz~Q92p%bcYAeHYSyNpgbhiGx>Fpx2FYnIIju-o65R$^u<>%<;l57q&-dHI z6@kZ4YPW_^es@tPmDL?gnQw8Wkj}%DD5I5fp^$ukNlQ@pq-T8!`RprSK`7aB^gWR{ zV2|KsAJe*8i=VnTR$=T-bO-4Vha4PzwjyU#MK>i_l%E@^Ur_x=JrxRKOTjlcSOV=7KZMw%Uvi~s;rFez9}YO#qof3 zR8&z7(cS&s*)JnpD7G-K5Ufyswp(X%cXh_)svp#<)l8PZ5UXiW8?vvzr~jR7ybNH< zIpt2WWv*_61Y~~o>KOW8J+5+N`%knDY!o(~iv&qwu(3f3Wm4$9Qp8(8_yW`vDV3kb zG;v;16Va!v=5NiSa=U*KHy;=tH=CkUcQ&O?>OxY-Tf^tTbHT-Fq2yG_)UO&O!(5b^NssR#-4n#5!Qdm6co znfhr7?{+XZ$`ih$!lOFSqCUjEL*ebY-CAspN-aPwm_sAklwgn~JM!kMb6|`5#}Y(* z6@8BglKO6vP{(cd8uWO5X&tNJ*tS&hZ?7 zaW1ffrx127=$mmn#Pw?f?&Gr0Q&_2Fu*S9~9&oWE51}_}Fq!vMx82dY?0)3dM-GUx z5a<7~1ZlV~UnF~AE z#8k$aH<)b7W&(0s4hR_sG17_Y@nV1``!WQz;(lNZYu7D{hcL};f&6uc;Doam!h&-? z(zmL__$i{_wtWRUuEFrPno(4Jz*~kdjj)t5SZ#)^n7>e0K*Wjl>*`K9wm@n z8$dnQH8LJI@&9qw;D7n`##09F_5qtj_%5!p)d}6X>_exn+WOO05X5OjP}Z>gecGTs zy{mojk}u-;^g$SjH{INaDorsW?v%pcmHfeFioF;9>Fc}m&KH|1BqO}sRsaB?2eU3= zj05M2BFjJcrN43}CW%zyJSz!25tB`@NUkbw2_@H$Up^zUo}ZJi6;D-;aHi+0dBYd& zQWNl7tXm;im3*(zqrt5&y^YGa7kQbI9Ai#4xFcD+)|F zxbq?D(zeCb$c)hkJ!^CB{FyAzZ7*%D+LZUzO>ur@eM^mE$87<7<|r!Bt*Awjf@_RX zbd;f6b~dd+1RsOJGHJ{`F`C}8)bVRt!e z^-u^bLxNv^N!l5gJN+tnJ2LJ0ug7Ui%YtWR>C<*5S+~@_`?xf?AM!!V4Hw5ZL}CgM z$4M;FcOS)or8<28&%gVx|DaPXiP5uw@LkpS$_YV}lQv_K=)FV&6!|&@t&eXQu^dEe zbxIshV^!o;^Nsvgy{y7-LmnbmqZWF4MGZuFrm)TWk0AZi04d`oIS+A@btki$59A^k zjdejNtZ`~W6o`R?OJkxdZ5x^Vw#h_P{oiuD;Jrxh#O&{x{HmoMo4F=CYx7HUB)Z!QoN_TMVru+sWPnWB;1eI$s_G? ziFwAqh608k!RpSkVI{Hs3lfK>8H@aQ!07-x{I}urS3F(d0eKASuRxNk+dqfcKI?ra zrht`L29R)EwX-ubFC?Rm&Q3&RJRa@^6|fOs2p6w`OBraMzdF_ z-&JMWPL`Emay@_Q{5<+|m$W8Q3x?$qaRK27WRoH4TE+aE?e&QMr{^8?EovK5yR&TZ+aY;mo*8Hw|-iT#%PHKk7E3U}C4(!z=V z1B&0Zr@0-h+u)sMk`F7`dGvR7Xt3KtfFGYV#ayQ8Br4$iA;Y^juIr}F0b)ycy|i{^ zBP*O9Y7KyeKmV7q<=DF&LhsZo(&>7YLNHLoqZZ{z(IoQ&%2l<%{7`>EP|!XW5=K#d{NK?&zP$BsjX{f}a#@M`g^Y08JVDiMvM0+U|(_zD64( zj+?fra~FF<8C2T-8$wfY+J~<#66~+FImbVZI9*8I;B#Le)v9`!p@b{ZzpleTcjO(@ zRshG}1oXwO*O@WNadMIq$fx$+t8X@x9i@Ei*4iKe;t)^~0coic;MV~8uIu_}v3&k3 zD9`uSpX`lizx`y24r;o(;9cFod2o=Nj|AHBG;UUizyo)Lcau3mtBZZ`B5UG4j#9|= zPQn9U0Uf|#I>8(72zp@$Bq>Xplg#3D+pLm;;M!2~x$zF1^-lPCp*j=^^-Sjl{x>qT zDBpo*^h{_m+`WZ#d}|4FrjV8#u_DsMW52A3HOwMU*WdfN+)c6%D1Sw^9+sl@{RL(l z4r7^+cY2Cn5=($Gr3Wn`06!*1E_7-tmyf*>=Xi%T3Mi8=@M%EMerc`(IuS71??`|6 z@S$&Xv=?+%iH=53Gy*I%z>>Og8vzVG1J;x@JzHB_9nbl!Sm3l*x9v1GT##~k72+Rq z(e{PhQ;!bRb=5D+Bi(2Bs0uBSOq5Y)P$=4S=oU4!yy%&soq<|@r7Nhln_bHL`*@s_ zcySSpB3bp2fU4lDvtD#Ea@NC@IKA>dJ(V`vJ^$$y_xoF+?=`7)0xIhIx}!qb&g~(3 zZnO))4|&e7&fXzV!GZ7Dhl?P0URQ>mpFJoh50aH9j~5`*m;~DD07&mn^UX@&K?k6bC$$B>A(@MQsL-EyI7eb4S?;L&( zL`s=~I87RVmxce}UMg;=RfK9$PpiP({C5S>mJ`GawE#H`pdhzi0*`52iGUV4FfgDk zs(^%q#JyAU>FnyNdsfX0@;)msptfdCC9tY2<+c2BF)>v^z+E9Xrx1C^rvSAUjxM!s zq57jifydrw#!h$?vrQ;G|G0{tbe{1yJ}Zt}+57a>q|{}Ku>zNIR-=I*7ExgJ%q5C- z{bD!p>RidOl>gxFy9cyJxgbv7_VWBXwpEBNdrBA4TRU{46;}Im%}E8whQ=l)n3$NI zanwqnIS*i_&(wQ@9!dnDLlwAdj$5$CrGP7@kEX1Xhkd+&3e-K+q4an30~3GY^>t+$ z#m)QInK?4viLB&5LmWj^P>Y+fEKfR_c{%?(s^Nb|^@sliEsrXyQF*4bw0JFAr5D18 z#2Wb-ngsJ?HpX<(kOtlzTX^Jj?n*u6*Tgm{6&m*`#0y{>bWQ;8!T>2*XWRJ7P&dU+aBK=Fl2cUE*OuSK zzc#;4U4pMdP;@e*!J&QQw=(5B@tDj-PtbF@{#~clO%Q>hp_ET%vMO?A)WSy5Bv{X* z=y$O^iL~{0#7{GI3OYwE%Uz%Wvecu0N8Sk-(Md#4n*sv`G|-oEfu1X208$=wdTPUJ zy&`R#!`gNGf@1}pvTOmW^dCZDx%vyWvhkit_}#=h+XhbdfPt@9lWic{c#q=sEb>|c z8cjioIc2?ywYhZa6VZ8VKu|I&yclVge-4HJo`TGiS<_ROV*_Uec;(5K-es(yNskjb zS8}cWWx!%3QahcUJ~j8i>!hIbi|%q7u?{XGpkw@=qdpFerJ^!gXRZt!1z`G0RB77V z(`PTjTRM;Blg_3ZSn&eE+sI&3=D64ibqmLK*!zjf62UO}j<`$*GrYex&8JrvUM0AV zI{`%7Y43NPk90Rd`8YP2GOL$mTMUxE6<_Av6JffQ!wknfL=bTq2W3%_Bfhsulpi>? z3`A41d)qN}lRflcgsb+J5p)>?$KCyI(gvNyhz`7Bc{dG3?)R*Iv%6Y| zQ!177oT*&A++o8z_59iwnD?xaIfoSeRcSx;Gk!HnVQ0N^l<>xz{;3i|r;R3RpVHnR zi(kD4_(r=M>D!N8ACKTEA%HFJo_f5Jj2(jq!0Cmf&eWqnj0qfY)aQJwHkAr&o@;uh zVk-;%DSNejzQ@DuJdJSaHu}VyO2Aq$MA59zF2#ERDSJV$5@KaH5N}NAL^Z#lO)?{e z!Ro_jt>9u%>@;Em$J-l)`J_L0M3iryjPwBqyorB)%PBy*gjOQ9*`sb1CCRkUSOvRS zqU~!@f=&L6R=k731(`9en&(zkw_`AVFz(yey&9y-oqbFD?KnzBKdmDAL@ent7#G`T4w;KmxUeVF21Yv^~G zL!V0AO0!V~4ud1KD!s%vO8m1{3{fhJH@40_;skpd1hpxvbhr@{y3tt+Ki}gwmIV&o zlOg?iY|LK`Md#_(eHDnG=|Fjla=CDewicmtIyb9Hd>*~c;*}Kr%7_T2+Y^TAAEAE9 z9H-wjd+$SxKe!O2ExIG*oJD5K)aTe`$hW-)+g?Y{iPCu8l@jg>Hm4^>My`+Ee3><~ zj_Tt=V>XvHf-#@H7z z>Rz>Od`FSMHjRJ_SA*22gR=e5@XYdZ7AlRtNt*Hhpl_Ojt+zVlxB6>#Wy2fi3=-|z z5~7h8EN6D_6SKWp>dcv{e0hCEDLRh;*!;3lAqB|zo>I$ue!GNbO(=1){DT^;SBN42 zFA`xiPiA>{O2c7vYjod&3PX(qgFOB>wN|wFt?kaRP1xU}JpL4IL-(A)+C6G;v$P212ZvnzhL0e(^dA|Nue|mIc#C(G za%=r(i;%Zk*FPd7av*NI&B@zdwFGR?X}&K-Z_X(ky#6<|bIl#7=!$!;YQbaU7vxR| z3+Y1h%4-rg6{y&xUOWf*akf#li+YqrY1dpMPcN4wSze))50M>zh}K|EZ!$mWo>s2< z9zUcVk3X6LbHM8L@Wjz%XZoq;`Dph{DtOY$EtLAT1Fwx8DX3D}apKCBF4myu4@^!x zp!1Q|%0}%*h6iP<`J6Y)-vS+!-9|kHTl@LS^P+0R664)P%6EK)p4{ryM>KIH8sZ+l zm`8K}M8B|!ZLLdMAbokt8aVdGsHFtuSU2f2$;r%x`T4V$)UnKvxr zA{{8;3TOmQ3f?=W*9i7DXJ&~uc!Z||)Zw1JY_9WYHFN&y;g;pz?~9Rg4DQ=ig2QXD zm~h@8RgMi`y)~cQq|{_i!ug9-r)JO`@3z~!G$$j(%KomosDp6-R5|F{$xCdCOWXW! zvTNg{IN$5Bzuj{KKU;9$n?%Pr9Pg{uU}uGk6Jm|;rplhAtEAN0jn>%z&fZlVBuQ^H zWaJG(T{c!1 zM>5KI$zYszhK#ZprlG-o{G!Yq_5eyDjtxJCFLA?Vfup)vjmH z-Rk|7w{m}mnZCNd&QKn=7-T(qp{d*Ek&T8~O`gRwYKqJbY2VN}!9O~A+S{Bj{%B<$ zw|>XAo1?IfU?V|Q%f+3#pj&)3hnNP1p`=qZaPU8;2A?V9*Uh5ffuVG@%)(hSeTYOC z=eW`S%i&4+w*ik83(fG1i;}wdnE&@rD$QEe4D?c(ukD;BGB_j+iY96uRk~2xCc%xo zYA(!D0`2YZ;2z^$R<*tC*yGK`>?>*y=-O=OGC#lz_Lw1VaB47++!NguVtJ}c8X|+P zE5ky=1f=~xd{-CzncJ4uy64 z;@l_^qSs*3?$=Oub%tg0s9Do%l7=Yoa+0&aGl%1k2s9MY!YkQp-{bV&U)lP~WG~oi zqSg&@ts-K7)kxmtmFsVSL8vZUa^v5Iv7oaPs)GJer`U!9tfJ6;-;I zX275@LJ$VEzANbRdTPh)N(zsKg~LL})ydNAeR&TQ+})Oa6aBY$Phy`R#?K>pGDb2> zPi;T(>o%|+86|#5&I+Hx;!pYGqJ2>cwz*M!V}7yn&GEHCe}mp;!(V)zUuJJ=ihrR8 z7fF}%_t?VIIAg~cMD!A|G!7H-3SPoigo&lP5}<$@HkLK)v+tZEU2#-K02`4rajE~O!DSu;W)UzrZqgL9x zxECs`;A)#bK;CI!0{M7}8JL9^2-zd38|D3N-Drn@No8b>Aen|v$X@Vnl%nv_xm8eC z<)Q|JWr1J4;;Z^4y9SsMD^CA}xi@)NNB!KYv$CM6_#Sj}8dgY_w`twlg!-ylF12K{!{9t$)xuFG6v7NP@K~K>A5x>2TT*RkcRe z9ybi%`Ofh6wwU<%1B7CbnN%oUDV#8^ucpoUjWzbU=C<3emW9Uo4(dc@&T-UUBN=!U zlN{hek|B%II#R#t>o*3cDrak)kzz)9SA1u?Fo~|2?ohBGiW&*Mt}~v0;)qy?lau*X zgT?VlF2#<@9hNNT#RHhI~A`&Q{cF-LpJWX$ovJ)xJGIygE(xoIeO2|802E|8w_; zqQYjwCo)YfWRi@7Dobx1Uj~>8iR4q?!N@eJrcb}EGw$hba`u874>Ckm4y-)Y!PknM z0sO!oTlIRqht}Q?shM<+s02lH67iq=8Uf-&0jx=nG2TV z%EqjsBl3IY)_kiRe*GYWSmoF)UzdJ)VlOdxN?F!)2Q8K0blnnp-F8-`=iV+8T=r8$ zWj4-$(LH3KtX1)DRG028EA^Ut0-9IY>36kGpFu8N0(nRN&o!!7b4>8f8G%!ha4yRD@TREhQ4vot*|nqvy&vMe}j1lr8IBmIe_x~00}<~eo!%eZ0Wk@u(| z)o@HT{p)H5!0zU-OjZl>Jl@Jp%H~>1iy)4xfxdeqvYgqfXDl9gQ#(SQNwYeWmFxA= zN2G(mno#XRG6~&EK7IlL03Zh{q(9wg)>c$%_HX~g+iSLPh?}ZW`847l>A&YC!(-F- zq*u^v7Ip29A1|+@WV1mnJ|5{|nBB3cVKWVn)H{IvQctzHh1OD`WS~1e$lSU&n^D`@Z z%8Fu1zUSxbSrwiYH;C%|-z8PC45ALOjY8dryPc(z!RUBv4P;A(tkoPxKY@itmlMxM z&vo+hiEc9`0p19ph(|(F@zfBbt1#J=0|jKwH^$S)1W@pOL%AY1MrvFZqV^>#9So$a+YuYESZo2O z=aG0TE2W#E8lpQr7VQ!F`>EGhgo}}$HstqXA2V-wu4ZRZ8Y(-?taU@8nIB#aBN4ecJ{;!C!9l@%xE!8pHo%kM0V4M z<|bupJIwXAOWC!|;v>ARIEU&>{V)@Whij8_GQVENKS07$8^JNL35b39)k&Ax$G$S7 z@`-`O%V3OIIux?!G3jy>Bd1hZ+biLpK0(PQT>bikFs7~wHgAST1w01>nYae9S@7r*{?qm$}~dK zCxE7bC@=i1G|i-ZQ{>}n9X1BQF32iB-RPqg215dc6fVmQ0R1 zkgUI0&9P@Tc8&y=pD zIlm+hV(=cEzrb28S0~xQZ*8o3Z=+$31F1I2=FPJ}^N#uWW z=SsJ&v@QUga38w>V}z(0@;-qyx#!mH2{`2y@N!)W}p82tTBtVPBlW zuiTG+Vz5q2(cdpG42;~-C|Qjc0iHr?E;@amA?@j0i{JK*NY8hWUabm0OJv){%5A+b zTkFWpSt#FIeOV~D+q)XxwPJYguh)|x5x(c2qD3$_xy^eiRsqfUzDqgfg$oh3*Xl8( zIW5!7M?E0Bqx(kYivmL6H2OOHjrUJ^`EAz&F@f9(6UK0c`p9uDKEv+61|`Mf9l!7p zrc@O65l&A7R<>2EZbeUCK?+rk$1ZrVm*YuepmU2p_?VYCj>pTg6;4dXMN-m<8O8)V zKK(h(Df9}h_4t-Iw!e88Nq2UIrA|=ZQP!$F=b-(d@z#Q~F9V*Zw}6Td_liL1$#6L` z^gx|~FKb8u-JSO~Z6PFBH~(^OwHjSVBF{zmIgd@?k~SpOx8-NR)~N@G3GdsU-rl7* z4mUW6v))F>dC<||z?`T2P(zs3Ds+I!?DQ>DoLwKpMc-N%NK;6;M#Rg5r3w7AzV{Ga zD{3J<$Nn^lErTeR-%(UcomO+Xbv{!QR_R)Hf1oqi*6}5HdvSfEwrZ_Qt#H?1u-Jq9 zTzEVko}h1fQs$#HafMz*Taw}gLC>#tfExufsp$R)GlCG zgCj7Hs`R+LbzsFwdjq})sl@0z!G*+WdQWdz^0(FdLLPw5E`OS;ykFR1?v5?hyg$BO ziZY#pTx5LbA+EK$rr0VxS-u~cmouHy<3hU0&i%K#qviF{?Y=M9U8m2Rw*+sYNYkf_ z8fyf~CcPqo)m2{e(!<=1ULK%NLRQF@gG8Rmid_Os3lFHUyh>$CVY>WB;2VXcOb^8| zNK_W<+2TQmVLC|%K5za>#nb&z7Y1e>79Q?! z&a_BpTpd0)BDa``uL(-Ui%V#`Kf;nu0aofa8ooCResf}9uU6V?>nL|5UBSn1anlZ7 zx#MBS>LP|^fyo{PypZw1nZFR^+bNMf1gpLmh|=72E@wD%hX63S>lSys(e~*EYhW@Q zEFmgRu=l{zxOI$1e4kN$EB_hFjjn!asZ{M^KesZ!fhUAQc_N81hj>yzvG2G5vOp>LpvPF7vP&@%bv7g zyDT_FOuaMEybI-37awnKHdqlp7Cx>+(LqjY`SQZX??L>)LXoplzWu4bXyQ{I4Nqsy z$Z(7Q_hgHu$>aRP!PHKkzqwI#OpSnnRnv_bSAK&bT^mvw1jeqTTa|1`Wzsj`?oB_~ z1n1!^TRQRa3`3sRV$hLG(;k;cw(0%N2_9N75S>F;+PKzh@3@x5q-1AX-*5uz+1#Js zv+ZAl1YRNNBel zJuf!i?BxwK>8-6Eeo9=4SxLcJQ2c?*^69pYZ55B=Y#=59)*RS%#0d#{SpRSG$bQl zo6mCszID+l-wSE{D$WApf`u_RpHKpc5&TcOq0b`f9unos&jOJC6rYHh`J?9cLR5Dk z+b6d6c$#U|!wvq$-nF$C(mLrGUsgQ+mdU6*TQlH>X1$x;6;O1VPuIIl=15BWa8G;e zmI)&%fCv)^Dd5JRqMs7*VfdyzgCAME*n({2faZ$dk|(=uq3M^sE15YYV>nXk6Sh1J z=jp>9!`as*9ARN{XrX7nqaKX9xph~UzR&MjrBXf-V5dTKtsn=WoVhUc{1PF^WZVgu zG=NWoyK^=sWw>`44fcTG&lR${kNuJ8ff1Ep)fSv@c2d{cvXixGnO7YBjQ?lhT&iLjtNmHyX?wdyp-0t?4PEmCq|N#6k6ZAy$-{yWr}05JSwsrjgey^U;W_Xd4Mz z2r@C`6A=_fh;Bd+8Gyk;>SA$wq=Kju@0!tt{$T;>8B{f&u~7c^Z$wUnqr*9BjF5%CPC zG-?eX(S{}CBm0c&G%mDraIptU?*;*nhd5j0aZ)^1<*_+W@u|y`BKkv(XqCPJiEo)_ zgzP8-ygoU%yW*DXy$m`iwJs|97-l>HNs2H_{hrYaKkc& z7D>4B{g6UwdKD*bI4|hQ)^aHYDTQPJx4?dv~-YVgI-LySM0! zJxn~>Xt_gq)xNY>T+nrgmziw~dSA-+%VOLdZzvpJsfG=bi>PaFxN&9QOuvn-yy-#1 zH8nV~d}X9U8pEwMi_AqqM(@~yQPx7vhExwx*FqMm-NF;q9(ED;_p$d8-?^S2L=Px? zUv9tE|Jza}5suE-x7POMC`8Qp9W^W2_80QXV+hb-l?=*_qUJTDVF!n2uSn} z=wd|<6;Akbtk_NP+bCUz+dhc7zFO>l8LjTFga#!=_%v@{_TT4h!HuA7mUHy))S;L( z@QEa_Q+?H{(>zP#c1jkHkO|?X$jyUVin2Wo|3&q7e{i)alo9{iHB59ucFe;x}Ce3Rkzqdff779RsCbnwPWW1K_3@53yMzT*oF1 zeC&8N5S^rj0=avme-gysL$n%pN!>paHSK;?XJwF6>7Ex83L`4&z=&O1o2Zdk@z{3s zo^a$r37Ab2TLB-+Ev0g# z(?1d9Hn)YWDON=Yt;GGwSihIKhogR5eIojnyDp)yCBt%7>+F6l#6+r3ah~Lm>vzyi zP}kF`wa+1ntd>-!^)kApk0O$^3D&wFXEt`7ULmWI)eoc0_Ehx}o6T`0q5i4by=Qjy z5SF3MWB5D};V=BHJ z7o;mQF6UT_T~S&Vn*&xD8?{F~ryr5om7d$G*9$?!)M5G-gMMf827Xpv;dTuBC{v$860uuf`-# zlS$q11wv`MXjVd@U#&aJLY&UO^l*4jB?k+KA3t)8jwC-ck{EoA_1igrYnYksv`rX2 z>|v-K#T)qk?X_)jY(jkp)`p}BhQT*XR-37^@6--0XxU?7m8QLKfJS-W(7Q91@E{CQ za!U>xy9UocL1*b)EDbjYB zTpqXMHYI2XUv|SfPX=kC^V?1V7wc%e=hP#+T9 z*F7s=xx}Jb`gbLrQc2`?Vo-0D!tMX&9rfVu(;=;g}kr(LNu2qH{w27X0{@BDkR$Di!t!F47ix8r60i8>&JgjM1d zri%e_;8@TXz0m9eJ_6ZNX{RbXR%>AT1>CkcP`;HTZEVz(i(^MJ5{)<$h|90!eYWpx z-fzQ$KxK&)6%{>zBy`qe+YV? zb0=~dSc@>@pgX&`XaE)z$D5C2>=nRXZ5)iIhE9!sYSPr}cEW)hE`MZcoI27E)@`=f zdT}Ii4N*oh&Luh@G=F5PciZxhPS&*a_My^zM z?y!QUyUgmVa6*+tDDQ_3%c`JEUHp(>%rJF-dVhtF3^gC!F!9Ev*=v}jtfZ9H#j@U0 zL1{FjxxbQ;;}qj;00NmZeAW*s(Q?659;!AGw8utvu7779M25nBLHu z@sdOJ;z7dj7{0~eZOTC;k6h-sd&*SXFqa|2@1pb+*^F?PD zM^gQRG>+2YEP0b-OH%%5w*uLQ(LfKarw=sw!tkwwRA=zhM(tG2Hn?9moV+f)!n-#m{_9aeyeWSPXq62J0w<{zPS__Guq z11*y=U-$9vIV~HEs9Yq5daCnM5%5x}_))xv=l{-Q^J8#_EzWvQy80$u^+=}h;#;2U z&R%E}KO$gfHMpHSTMvCryWuIT{DxI|_baQFT3b=GS`;~)pSWN#-@o$Lud21O{rPH4 z=e?tT57iTM9|x=>i+RXnY?g@Aa6^T`-@1UGDqiVvQBl!O)GIBm4rA^U`B>OCym6~H zv^(g{LiU=;=v=fG>_pFs@^5m7zb_{Dxv%ko4`S0evliX*36^kb+Tz5eX|dxh7t{4O zmLTFP?EdoTVx$3qjZldg<)oI_-ePh6gT8*x+dgPQZ*B*9th%~hcxf+ZW@ZgJIehsU zKll37WiGaCsrFhAwL>=$tOx~EO6W1n{k~@l?m895l76HgDrt|IRXpAFc=wtXmwj_X zp^sF$@l_I>3wYBoQwIYk@%)+ZsmsrfZ@4d6j?Q$C{(Fr>g59{!SAo)O@#a~nZABdm z=*Kn7Ov6VV`CjF)yI&pZm$t;4mo#Tn4&r8O%s88M+Q?MkswqF?CvZCru%3s9Y)78iZ^bvOyv0ON+-R=i(MtShF^{@h6fdh(3DT=HxIlk!_6`kH`6+>UWt$Ru<VD3$;8L#wzR9`m8AA=eD5MlpS7 z7MVe@X!tr6NY5@}UZ|hU7!9i;ZQrr=jnIU)bR^}7nWp;2`nG5ZBTAFj4Lv$0KIw1& zp8fFt(gY^I0}-am4Yj-%D1~Mx3e8}~Vwn|0FerFh-(0lLiSiA$34drV6Y#)iZcTyy zfHeyPi;(;4o0r+~nl4(%70MfTmm*%1jXG|gW_8a)2V z((%EvZT|V2Pa%#$^lS&?xfl%ZbAP-2WevUT`|;8xvt-!RF(rj67_)V9EogJ-C+q%p zFRZ!?Wansds_S}%^2@5MT`vMEG!bby$u_y3ly+K(<905!hjs~^FYY}TgGw^^XVzZD zCdG*_ZpiSA&M;yzrvHF&_)B3Gbo!4==BEunm3slbF~4MR?02 zvOO=ENDM71&3a4*&XXq_DKS`3k=(PYn&)UArU})t5x7=7ZJE%*eEB3!ET+E-TPqCo zTfzr+Rgs$*mfJA91A0!qW-_CR75$Z}3m$TFCy&UFN;_?=8C!3b>f#fb? z2y@n_Kl-A0F^JR0FH~Zh2*R35s9r298KI*+niXqx{`exbkG&u_lz-0|l9d#ap}8`C z5E;tAD&%FVlc&Za!{ZjY`k#T>knkl~BPcQGdu{~B{$xbeu@hBF|J{X(K>o&iNh<`A z#_KqG&MTy{Fk+%XIdA=HucawD#4tyw@1Zmu2nJ971X=!f^Mc&?(mN|pih-cmL#Sp| z%|j=o^4ovx)MF40;gs<66juAW6BTL(!{hkxQ*w%<(~3G(#6fSc$fTxCG~sYO*&w8h zs4R|2iuF&*kA8QV$|wD|jwHcH|49$*n1E0nhNn&*doVkdpVnqhgVII)Qq+;TU9=x$ ze1NNDQ+Ya#MH)YO>ElUh>hnI-12k?MikUUKeD_|qM+dP&OWK33ndzW!p)$23*0;LC z)&u)?_ZYFq2$UVim(k%wfI~X_D|fSE_9JxFI<^FT-0_2iz5d3J15(qS+3vg61F1w< z{?ak4`_xldm*8;8nG>kUAl2*A@Xg&&Cw#A`lVZY)4lJqnj_%Gn96X`zLD#1@SJ*v% zcO6mbe>Wo-h)gqu-BN;oFjEX{qC@VUOW909HF(eEy|Ya4LxujoKY+hh`jT08y^N@A z>yQ?WfP+a80aMolGacFobs)?%0^WYtA2{=m5VZckH9$*IOjMZFE2*rk{PO%ioivuT z&rL2lxuZWr0K5pqAEdkV(WBVp(E9{x0L;AxMh5WdCIH zze(c1tEJlz)%@eF)@!sWt^H3HCQW9x=Y zZ?9jPt+j!_?Sop@>fL4U-vTh~N0zG0@Z=(3XrD+ zOB>bDAUKpJL;`9RH{_3=NNSqd=f%HJ8XsDZ0e(z4-nBc7*uMOJ4$1|!L=r3&07fh# zCIOwbAIT7F0Kl!-pQAX4!s(ji;D|E=ifL0uoey!v9g+)X16W?4`Ek{ZZ$VB1OSPU z@&LVYfR=Jv?fxLn*(loVzTflj;<(c9)^}&R5`%_@Ci$5eZtCaH3x@d}I*e|AuSVm_matTWx7 zEM-bpmEYanRo!F zr~b4+aFY@n8(WRnsrAeTP$!F1%FO~)p3_n3!mb}7>XMR@T=Apz+GYBRg@uLoBZnKP z!J(lX@Py1|yyhTRQdZ6(W7ifGyRC1(eyZ|Cd|^)q6vtxMCljrDsz!xnWz3KodVhaED=X_}_^M$-NXR`ISy@lf5xTh% zTmH3!l`gk0t@Jp3KYqAg%utY$PNx$oEcGKS*%8)U5Zbwt!ovGteif9IIswn3{>@nr zU78q@{KJP2FyVKs<|7%A#~UNfq5?5@y_rtrsdyaqvw+<({R|2PyD0-*UCIc#Yy;}8 zQ!n7}jkeht-qA=#dUu{Z6}jv&PC+zdq&+W{fguS6g@ro@D=UtMh6ZQ(78jlO0a~7F z`d=r3O?g^R%)2{KR_+FBaEIg1xmJKzp6^tTTo&XUT^~mKbpyB=F&SB~&lSpKYdp80 zq@?>Uh@5z5kKxqn?Q&zYiHk4p&lWd-`t$(!#65uHbVg>h*BPm(5O9!(PweYBIaN;B z==-o-x0XT>q_U#7|BjP+tsXpk_Dnw`2~bNCN&JJF_C!cZOJiu4>IDN2CnY00y&T?M z1c0$l5EWuUqk#b>j@RJ7hx5*Os%e4&0A&<rr`BrGejwY(G{LQ-}dY!(oeSMYw|^dJV@uXo{v(2Iyr1LeB94Iv>Rn2__M$#SFUDMMswefU;_ z)kNOR&22K=G$tV-I6j`#cCm%hWqoL?_tV89h>!l@JOdm)_D3k-r(1wI0+ThIg3FD1 z1^pXP5HwpDH0Bl@lBp}()z#hH*^%+|6dIqHpfMDH;d6ifQBYo9zb#u>RP?tN^>=vg(xAnI z*nQp!+u7Oq;O1%{dF|`7;9J(+-Hj;J6fQ}2KAWM&zgIqdMgg#C6)MSRC@!l6rC_JE zp06MsNK)DmAtokX_|t^%n~*nHEU~W1%sKMI|S06^Nw8v zs^we#XASb+{GT6x^GJR4T1(4Jqz*_(j&HsDIXSt0VmPT-6-r1`MKjmt(`=;jiA*;3 z#mkpghpXSkntb;cTQU88FSl6el7`Os?Pg^H>D3Jk(kG@$p>@;IA{8PiZb)Zh=`o}CEvNN?SM&NZLmtb<%Shx zXLl8E|7+b{e)DOkNUPYkmx_w&t;(mw_@)#Z*V+A4_s?@l%~^Z)^IaB%P#Sd+H^ z#P;p8lrV+M-h|j#$(MP`Url?X#_H_mSnmQd*sE%m2jM<9KmVnyZ1Ap*p&@M~wLlau z9-bAL0bbi_?o>V-?JrX!31GS(K!jcY#&_9}k&(q`WT=8m$jE5Ecp(MW#C+*cLJbfy z>=v35LI`P;>KDCij40-^fn$$>)o*LM(o|DVPw6wiT^7)Q_1dZIwcU7EPDeb(Ga@Pt zV%!NpXHR^U4rLV)`CL_9eU*)CucfIu>N;g0AIGAW2b`*?q@+fyDT72|_Y9!YN5eLrDHDDel9C3d#!<0 zPtIki44P+ERXw`|muC|YNCMHkps6V}488q2EQf9mFbR8YwAP2*55fGAEbYSyw37*%#4iGR|Sy+0vY|PBe+`e>xm2+$IwL>nDO&z!7eYfB`H5Sg*rT{cT zeRSSmP zh;D12t}uB&;a6@TB7sqPJz1iAXUH7wVm2P0IMn`<0}{yi+GqFD`OWYB`|(*|0xVdH zrP>n(8rhrMFCtJc9Z~(kaNyH9#@w%k(dmi zZ3mrNjb=&$rA{IZz$CqUig1u%EW~~YNf-B-U8zObiflV*pM}=a0?!)cYF9oyJj@xh zv^@IVPw1+qsQ497bT^yswe_}T(lZ_{_!Hli71O`gME|el%Ky9IIle{n_D@MGrsmIs PfRCcAs!W-bap3;|SQ5Lp diff --git a/docs/cli/basic-usage/Readme_files/Readme_22_1.png b/docs/cli/basic-usage/img/after-four-cycles.png similarity index 100% rename from docs/cli/basic-usage/Readme_files/Readme_22_1.png rename to docs/cli/basic-usage/img/after-four-cycles.png diff --git a/docs/cli/basic-usage/Readme_files/Readme_19_1.png b/docs/cli/basic-usage/img/after-one-cycle.png similarity index 100% rename from docs/cli/basic-usage/Readme_files/Readme_19_1.png rename to docs/cli/basic-usage/img/after-one-cycle.png diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index c635fd83..7f7a8d40 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -7,7 +7,7 @@ The command line interface allows us to load and save `States` and run arbitrary To use the command line, we first define a file containing the functions we want to run on the State. ```python title="lib.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/main/docs/cli/basic-usage/lib/python/lib.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/feat/reintegrate-workflow/docs/cli/basic-usage/lib.py" ``` We can run the pipeline of initialization, condition generation, experiment and theory building as follows. @@ -43,297 +43,90 @@ We can interrogate the results by loading them into the current session. ```python +#!/usr/bin/env python from autora.workflow.__main__ import load_state -s = load_state("model.pkl") +state = load_state("model.pkl") +print(state) +# state = +# StandardState( +# variables=VariableCollection( +# independent_variables=[ +# Variable(name='x', +# value_range=None, +# allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), +# units='', +# type=, +# variable_label='', +# rescale=1, +# is_covariate=False) +# ], +# dependent_variables=[ +# Variable(name='y', +# value_range=None, +# allowed_values=None, +# units='', +# type=, +# variable_label='', +# rescale=1, +# is_covariate=False) +# ], +# covariates=[] +# ), +# conditions= x +# 342 -3.16 +# 869 7.38 +# 732 4.64 +# 387 -2.26 +# 919 8.38 +# 949 8.98 +# 539 0.78 +# 563 1.26 +# 855 7.10 +# 772 5.44, +# experiment_data= x y +# 0 -3.16 1.257587 +# 1 7.38 153.259915 +# 2 4.64 54.291348 +# 3 -2.26 10.374509 +# 4 8.38 155.483778 +# 5 8.98 183.774472 +# 6 0.78 3.154024 +# 7 1.26 14.033608 +# 8 7.10 103.032008 +# 9 5.44 94.629911, +# models=[ +# GridSearchCV( +# estimator=Pipeline(steps=[ +# ('polynomialfeatures', PolynomialFeatures()), +# ('linearregression', LinearRegression())]), +# param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]}, +# scoring='r2' +# ) +# ] +# ) ``` -`s` is the following object: +`state` is the following object which, once loaded, can be treated like any other `State` object: ```python -StandardState( - variables=VariableCollection( - independent_variables=[ - Variable(name='x', - value_range=None, - allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), - units='', - type=, - variable_label='', - rescale=1, - is_covariate=False) - ], - dependent_variables=[ - Variable(name='y', - value_range=None, - allowed_values=None, - units='', - type=, - variable_label='', - rescale=1, - is_covariate=False) - ], - covariates=[] - ), - conditions= x - 342 -3.16 - 869 7.38 - 732 4.64 - 387 -2.26 - 919 8.38 - 949 8.98 - 539 0.78 - 563 1.26 - 855 7.10 - 772 5.44, - experiment_data= x y - 0 -3.16 1.257587 - 1 7.38 153.259915 - 2 4.64 54.291348 - 3 -2.26 10.374509 - 4 8.38 155.483778 - 5 8.98 183.774472 - 6 0.78 3.154024 - 7 1.26 14.033608 - 8 7.10 103.032008 - 9 5.44 94.629911, - models=[ - GridSearchCV( - estimator=Pipeline(steps=[ - ('polynomialfeatures', PolynomialFeatures()), - ('linearregression', LinearRegression())]), - param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]}, scoring='r2')] -) ``` - StandardState(variables=VariableCollection(independent_variables=[Variable(name='x', value_range=None, allowed_values=array([-10. , -9.98, -9.96, ..., 9.96, 9.98, 10. ]), units='', type=, variable_label='', rescale=1, is_covariate=False)], dependent_variables=[Variable(name='y', value_range=None, allowed_values=None, units='', type=, variable_label='', rescale=1, is_covariate=False)], covariates=[]), conditions= x - 342 -3.16 - 869 7.38 - 732 4.64 - 387 -2.26 - 919 8.38 - 949 8.98 - 539 0.78 - 563 1.26 - 855 7.10 - 772 5.44, experiment_data= x y - 0 -3.16 1.257587 - 1 7.38 153.259915 - 2 4.64 54.291348 - 3 -2.26 10.374509 - 4 8.38 155.483778 - 5 8.98 183.774472 - 6 0.78 3.154024 - 7 1.26 14.033608 - 8 7.10 103.032008 - 9 5.44 94.629911, models=[GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures', - PolynomialFeatures()), - ('linearregression', - LinearRegression())]), - param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]}, - scoring='r2')]) - - - -We have three new fields in the state. The first is the conditions, a sample of ten values from between -10 and 10. - -```python -s.conditions -``` - - - - -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
x
342-3.16
8697.38
7324.64
387-2.26
9198.38
9498.98
5390.78
5631.26
8557.10
7725.44
-
- - - -We have experiment data corresponding to those conditions: - - -```python -s.experiment_data -``` - - - - -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
xy
0-3.161.257587
17.38153.259915
24.6454.291348
3-2.2610.374509
48.38155.483778
58.98183.774472
60.783.154024
71.2614.033608
87.10103.032008
95.4494.629911
-
- - - -We have a best-fit linear model. - - -```python -s.model -``` - - - - -
GridSearchCV(estimator=Pipeline(steps=[('polynomialfeatures',
-                                        PolynomialFeatures()),
-                                       ('linearregression',
-                                        LinearRegression())]),
-             param_grid={'polynomialfeatures__degree': [0, 1, 2, 3, 4]},
-             scoring='r2')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
+For instance, we can plot the results: +```python title="plot.py" +# TODO: replace with snippet -... which we can plot: - - -```python +#!/usr/bin/env python import numpy as np from matplotlib import pyplot as plt +import typer + +from autora.workflow.__main__ import load_state from lib import ground_truth, noise_std + def plot_results(state): x = np.linspace(-10, 10, 100).reshape((-1, 1)) plt.plot(x, ground_truth(x), label="ground_truth", c="orange") @@ -343,72 +136,41 @@ def plot_results(state): xi, yi = state.experiment_data["x"], state.experiment_data["y"] plt.scatter(xi, yi, label=f"observations") - plt.plot(x, state.model.predict(x), label="model") + plt.plot(x, state.models[-1].predict(x), label="model") plt.legend() + plt.show() -plot_results(s) -``` - - /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names - warnings.warn( - - - - -![png](Readme_files/Readme_19_1.png) - - - -If we run the experiment for another 3 cycles, we can get results closer to the ground truth. In this example, we overwrite the results file each time the CLI is called. - - -```python -!cp "model.pkl" "result.pkl" -for i in range(3): - !python -m autora.workflow lib.experimentalist --in-path "result.pkl" --out-path "result.pkl" - !python -m autora.workflow lib.experiment_runner --in-path "result.pkl" --out-path "result.pkl" - !python -m autora.workflow lib.theorist --in-path "result.pkl" --out-path "result.pkl" +def main(filename: str): + state = load_state(filename) # load from the first + plot_results(state) +if __name__ == "__main__": + typer.run(main) ``` - - -```python -state_after_three_more_cycles = load_state("result.pkl") -plot_results(state_after_three_more_cycles) + +```shell +python plot.py model.pkl ``` - /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names - warnings.warn( - +![png](img/after-one-cycle.png) - -![png](Readme_files/Readme_22_1.png) - - - -We can continue to run for as long as we like, e.g. another 10 cycles: +If we instead run the experiment for 4 cycles, we can get results closer to the ground truth. +```shell +set -x # echo each command -```python -!cp "result.pkl" "result-10.pkl" -for i in range(10): - !python -m autora.workflow lib.experimentalist --in-path "result-10.pkl" --out-path "result-10.pkl" - !python -m autora.workflow lib.experiment_runner --in-path "result-10.pkl" --out-path "result-10.pkl" - !python -m autora.workflow lib.theorist --in-path "result-10.pkl" --out-path "result-10.pkl" +python -m autora.workflow lib.initial_state --out-path "result.pkl" -state_after_ten_more_cycles = load_state("result-10.pkl") +for i in {1..4} +do + python -m autora.workflow lib.experimentalist --in-path "result.pkl" --out-path "result.pkl" + python -m autora.workflow lib.experiment_runner --in-path "result.pkl" --out-path "result.pkl" + python -m autora.workflow lib.theorist --in-path "result.pkl" --out-path "result.pkl" +done -plot_results(state_after_ten_more_cycles) +python plot.py result.pkl ``` - /Users/jholla10/Developer/autora-workflow/.venv/lib/python3.8/site-packages/sklearn/base.py:464: UserWarning: X does not have valid feature names, but PolynomialFeatures was fitted with feature names - warnings.warn( - - - - -![png](Readme_files/Readme_24_1.png) - - +![png](img/after-four-cycles.png) diff --git a/docs/cli/basic-usage/plot.py b/docs/cli/basic-usage/plot.py new file mode 100644 index 00000000..94e7784c --- /dev/null +++ b/docs/cli/basic-usage/plot.py @@ -0,0 +1,45 @@ +#!/usr/bin/env python +import pathlib + +import numpy as np +import pandas as pd +import typer +from lib import ground_truth, noise_std +from matplotlib import pyplot as plt +from sklearn.model_selection import GridSearchCV + +from autora.state import StandardState +from autora.workflow.__main__ import load_state + + +def plot_results(state: StandardState): + x = np.linspace(-10, 10, 100).reshape((-1, 1)) + plt.plot(x, ground_truth(x), label="ground_truth", c="orange") + plt.fill_between( + x.flatten(), + ground_truth(x).flatten() + noise_std, + ground_truth(x).flatten() - noise_std, + alpha=0.3, + color="orange", + ) + + assert isinstance(state.experiment_data, pd.DataFrame) + + xi, yi = state.experiment_data["x"], state.experiment_data["y"] + plt.scatter(xi, yi, label="observations") + + assert isinstance(state.models[-1], GridSearchCV) + plt.plot(x, state.models[-1].predict(x), label="model") + + plt.legend() + plt.show() + + +def main(filename: pathlib.Path): + state = load_state(filename) + assert isinstance(state, StandardState) + plot_results(state) + + +if __name__ == "__main__": + typer.run(main) From b02bbc5fa47f3d036ff5a335e3f00bb6e6f70844 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 13:53:02 -0500 Subject: [PATCH 05/16] docs: update basic-usage --- docs/cli/basic-usage/index.md | 35 ++--------------------------------- docs/cli/basic-usage/plot.py | 1 - 2 files changed, 2 insertions(+), 34 deletions(-) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index 7f7a8d40..daefd597 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -7,7 +7,7 @@ The command line interface allows us to load and save `States` and run arbitrary To use the command line, we first define a file containing the functions we want to run on the State. ```python title="lib.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/feat/reintegrate-workflow/docs/cli/basic-usage/lib.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/lib.py" ``` We can run the pipeline of initialization, condition generation, experiment and theory building as follows. @@ -115,38 +115,7 @@ For instance, we can plot the results: ```python title="plot.py" -# TODO: replace with snippet - -#!/usr/bin/env python -import numpy as np -from matplotlib import pyplot as plt -import typer - -from autora.workflow.__main__ import load_state - -from lib import ground_truth, noise_std - - -def plot_results(state): - x = np.linspace(-10, 10, 100).reshape((-1, 1)) - plt.plot(x, ground_truth(x), label="ground_truth", c="orange") - plt.fill_between(x.flatten(), ground_truth(x).flatten() + noise_std, ground_truth(x).flatten() - noise_std, - alpha=0.3, color="orange") - - xi, yi = state.experiment_data["x"], state.experiment_data["y"] - plt.scatter(xi, yi, label=f"observations") - - plt.plot(x, state.models[-1].predict(x), label="model") - - plt.legend() - plt.show() - -def main(filename: str): - state = load_state(filename) # load from the first - plot_results(state) - -if __name__ == "__main__": - typer.run(main) +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/plot.py" ``` ```shell diff --git a/docs/cli/basic-usage/plot.py b/docs/cli/basic-usage/plot.py index 94e7784c..03717360 100644 --- a/docs/cli/basic-usage/plot.py +++ b/docs/cli/basic-usage/plot.py @@ -24,7 +24,6 @@ def plot_results(state: StandardState): ) assert isinstance(state.experiment_data, pd.DataFrame) - xi, yi = state.experiment_data["x"], state.experiment_data["y"] plt.scatter(xi, yi, label="observations") From 90b92de81a85b4fcabfbd8ec90f7efc7a28289cd Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 13:59:12 -0500 Subject: [PATCH 06/16] docs: add labels to plot --- .../cli/basic-usage/img/after-four-cycles.png | Bin 41505 -> 42902 bytes docs/cli/basic-usage/img/after-one-cycle.png | Bin 40985 -> 41682 bytes docs/cli/basic-usage/plot.py | 3 +++ 3 files changed, 3 insertions(+) diff --git a/docs/cli/basic-usage/img/after-four-cycles.png b/docs/cli/basic-usage/img/after-four-cycles.png index 0e987da3410c5eabad98478536f299477fa098db..75d36d2945b3a11bba3d41087596f16b72f6a8fd 100644 GIT binary patch literal 42902 zcmeEu^;=b4(DtE0y1PUg0R^N>N+hKlq`SK%L>fdux};OOLj(i_q#F*>-CgfG&+~lo zH+|-~%BLI4CMI_=IP4VGaD? zca_p|Rdq0T^?2`W22ptL>S*iWYHMXo<8J2cV&!1Z#m>jh$wp)8>gwnsz`16L$kXa#{3BFIXLt9hpHEqeG)oZojIPhTEW;hV%b?PR;JkJv{aAkxi1Ql!!%`m) z^5mb-Ui|;RymtM6-v|Zu2VycC?k%!%a&$B_5QXu%X2E|P0bYNanT6#k0|Rn!j!jIc zEX0#&Y;5dPbhO>BJ~6$r~GDfZOwFJBx?j)^e(WYL$qPR8C^;EoPa@f{Gmoo;T9Pg`7MMA=DnQyUe_97 z7?9~Q?d~8XbiU1W7e|4NyX%pFjlYo`=F9DVSJ&6-4K4fi^PYFdeWd~QT5OZcEqd(i zO>20$xw%){g;{Tulr}fg9C`-_BN?-NtJSk&Vc{TYGv=y4J>QIP!73=2_URMq6nMlJ zW>p9eJfHOh)5CFW0JrB5@3L=qezL(^9UZdx_;^U`#hi`M6*Sn?!eVuQ-*2w(IUCzg z>pJ6_SyM!1V3#eLwfmNYZy&zT+CoA?LOdw~4%;qK(a}w2s@@Bo{gL>Rl%$b0-{?fw z9fn*KGh)zTv03{8iyuiZZGL~_pykkf?3*kG`Kz*aO+8l^Q30d;L z-7nMn9#m&Do%t$uBm@l~!son(>UVoV&%zS%^QUC&tCW-!h@_Mhk7sNcmG`GmbYhK1 zy}IaDTKk5yZ{MCpNz=V}@xs%`$76d@I@hVWA|WGVs6T;md%2?{3K77Ur4!{#$b?&l z;6Y>Xi0ETFb--QxQkzfKMJlDBI|PT45>rf1k0Ri9e)-qHz|*Hs;R6#{HStJDe#OyB zkhO-*+V}5q76WAB{UYa*UxCjp<&AgMfXMjNFZbg93l^e7wKZ zuD2zHgM*v2xhT_MZEtU<5cd9Zxg3zCU1N?*MmA8P-_p35>GSoa*%LbHCeUJ9e?a=$-u(dBgmgXyS-MJXn+X$K9No9s*!OUlS- z2Kb$g%0R%|pWa_CyBzlrb6NhOIcU2ysA#{jPU0{$@Waj<{S`sT3ik15Pmj}TG_UjN z5UE}@abR;#&ZiA|H5(+!wVPd;J(m4=k&uw=789*g z3y!Zhvs`)zHEZ28f#ZGh2H(xb>6kEy749v1mp8Y65BqeA1}>Y=23X5(G1Pq1k#DXU z9Tq&1@et(+RW-Gr3r#M^r>ArR0;$A?zVXGXh0d3Y9teL*H8~z`raNGZ!zUrp%5XUz zR}wYb`jhi@$lUvUrw5&*73yTDFn$HhB@_de^xbt^1p?cG0xRE(Squ5JSD2AKKYqp2 z%{Dsa_3_9hv**jiQfaXfRkWVGb#`${J8Mm1*B|)X6FJ-D!kAi+W2JL$Vw2kYnO?4O zuX^z4^mNrB;FcVGkDiI?*D95v@3GYR$7t0>Y#K(!FxJXeyvUx{j}Q0PCxaYm6G|W= zj?NEU{V#_#G^l^s?pCu{=%ZN3?gnJMZ`uTYTK&Eox&7`$PNPDvzu9efrroba zCT%k-ATyp$=Hzrl^z;{9Y?a;otBSS@or;bJZ}-EcA(%1gVuk+V;_yrwKAaGPpcZl8 zo9POKL-@*Nfu&f8A2^i8%jK{nWZ!Y`4*Q>4t8vf2;f$%S%exgVF+PWF$vF~XpEENR zy}bpd^*!{@uluNcqQDD$UTpC=O9Uh@=Ny?cl2&~g9ju;WpL*uaw( z;?QcA9E?PeByL9Ha@CbawwX$hXYzhvHB53h($ngV-vhPOTNs)Q=S^QG*-I zRGXm-d!Io%&1;;t{?Hc4r;Kg61*2e_cYnmB>U(8712cPxTv}*YSVCr|f#1W?N;gO- zneQHvv8jG<45bOj*v-`z_fPxy`0#p3z7!Hl&&_@M_U+q};O>&oK^<%UAacnzoOhow ztjDXHGX9!Qo4lRujlHth7PFmquSoa|QT7Cx9-5?Uzw&T<$oTA82*`^>&vin&jQGr& zs$tIPGRz;=@o-+L=dtK!yU-Y~Y2Xza0Jd+^4(2KbUh9N^|NeDs(u1X_bLoD?&0)bq zQ;^1l9`8=|{IA!2Z}%G%bRISHH7gCC(bIo7>BDOFI8+o96U)ngWRU+F*kimh67ay~ zvE;>=#_LegP`oaGz!-v)+a4mk&1TRZ>zcN>>RE*yRb9aAoXDqJjjTLzdfD-q(b&kx z-gc%^pp-TIO*Vl<$dgk6X0|3O|x8asvl8@ z={?C~d9%G!5-v?hL}Xm21E>Pxu`*wi5s*MW*30c~UMn{EPlDg?-k0xxrRo{nhW(vI@4_Hi}Xib~~EOLQ%!u7^d z#}1jV9`{kBKmp1*tY)Ht6v2j|doSB*V zJ$Q0RXx(E+CxD*6hlk71X|VOvQ;YboQQt9_ZmD${mb>?S7S5sng_>Ptake#TJ6~U3 z-f|oXvqE%%b$C>i?fMdUe@l5uvGJr9$*Vyvbvck)U0H;EE^K$%VgD6$+$Qm<{wD5y z&G;X4M9d7P$b{p?Hr+M{{SP6Nuxw`OCLP?HJ1YSxN;8!&#Xuv@NC+SOHT?WxbX-^|bYZ7oJdkRj6aiHseTSfeLjFyOsexW3YN~SN@Q|^5Ows$4%i={5~I9$5BI~|E4 z<0-kh0?rqrCQ0!6Q~mMeuo{GYNBiTfnl`n_z2NyH?Pg$CX|(rL6EMSETSUZ@);3*s z>@SlnJ-wkgxzB-v7#?bjcO+vKVaV=j$93rYQ48dN>#zF>90fO>cWs4I2dgQI!H>wn z#S=R9_4V}yugwfeNlEDHYWG@y!fdr!q)Zwn`72K2pQygRzF+yAp88zu6^nTM{fTBi zlBwY6$O*6#gHqs2WyeGF%^lzwU-?}a9v&VfrKO$66?o$l5>);C0jpU6gmA&{axo+{ z^o2<;hCM+0ik1U`SP?!7EI?5`H#0mSZ{EByI$7&SL_&fQDnPdfM)PD!=PwTy$(0io zxfNjSNbH^&IxhTJVs)fms`0{pfsc&{9ndaz6l|(8`x=)`#R7#iX)!U#hYug3CLx=bD8^LKS116!j&@Tu{JV*7qBh&2KOE&vvI{Nx979l9M$THvmL#!s2r< z>3K+47#A?m4xTMK5nFa^YdYY+)jpT@nO+;DfFQ#$F)=}d(AkY(p|aSV7!rc`l8dVe z6cfTXM;G%Bpq3Z{;N-bqHx0|(gUK9)jg1V96AjD$a#mK%0AuMP^z`&>dW~`5#j33* zSul_hV4vDIl+dMo{fgQN2&obv2w8qpM-|ltLIHstck3LjM?cWP;|LS_e>(V|rtP@6 zY!2sxTElj>I@E5y{T>Fw2d|;%H;L$7i=F*oC#9WJ7{k~>+{X64V zX$mN=X+s)^dfM74?GDQ#ZDnP9#EZ9Si&oy1D4JWsyT0cocQ@u9bF=Op;ypb*&B@8h z4@*9W>eQu0MSo0;jn6Ey{4^d{!l+%v9sw6F9ogL2*a1xXMuyt&+ir6Os5$fk_P+O# zwLTg?-e}$fPI$qW^!alx!cA8&iktrQIY2Z+YGLnM8S=31oUqW)?Zehn#q;m{E*o1g zPLwx7FDR&sat0U?xZSR-tgJvb$TuTY`}R%iME5Z88#|qLYrE;_0){eN+$gPVAN#Nq za2OZ}@!KBDkG?3csJZvU1&O+M+j)1D>QU$L8v4ZVe9o*n^CZ9G@G7#RBdj98cJdrQ zYv*QZ(@oezw?_1$c&Vf12`QXyn4Wz`&)_AG7Wwy`nZN6|I;H|wTcdfv#TgV*)%<>g z$`cTjnt;cL9TO)fr^)58kPuEsXy?u;EX^qi9U}swVmz8FwKrE++PpuUA$Sd}b#!@I z`9Q{PseEptNh;`GCetC$fDg*&=b)yf%9g%Odam0G=y&Nng@`YRzKuVCM!+K=Y)_UF zL;CyshaT?Wq@zgQ-TS$^aznJWwIMM7S$?=^kk1myD9rMoTWtafA@F%$bw9fk{?@*^ zO6-8M!}fB?V{EI~tAJWgG{}6;&u>Cwb{EnkyJF2lipDAid3JMSfLQCsPzv@c@Gky5 zSZpEXwWoNz+Z2UkVrMtM*qhy(`QE*{3&@Fl%FFy47^ylx5cD|E((&TwHHF|FsK;D(cwmNp1{)eG>1CJ=R` zfPP$GUsFwM?mu&H(zCd~OEU)SZNX(k*ca4CdTx{It>;s^7Orgop)}YVhIxG^X?p4J zSta755(CN0y1T~8_XVb<-auxsq!6#TZCbciHaGk3u1}jDA8usq-x&y&C*|h@d+Fyf%Cd29c zFd)d2i9G@6cCrgX@5=}6L>LtUP8JQSW^egNWE2#9fXM+5r_?Y`zcX2?-RPLpSBHy> zdv$Z8;UEO)OUKo9)?00DQh-*1urvtxlM$e-;O0GaVnnY$RoI^9;IDo8Fu7;0;=#fj zpr-NgDQUC=RF+19-0dEyqZ-t;(!(}lwUc3h66mZQgF?XyR`A+4Z!`2pk#>Xn>I%FC z8Wz@tr3;An7w&snFJHdYYWHpGL!Ae&17mx~$Hy2XoPjVd3iyMG5mp-`Lx;16ha*0T}~2XH#jm@jC^kjmS=;(@I)gPL9Yz zeqO?H(8V=ivN(4VK;AnQwrg>tD@^Aj{@_s8()u)M-D6&ZOG2{cG;H6H@a2mnaPQ+| z{?qv8f5@U{d1%o+wi+P;dy^B!ad&RO`w=N0m--Hl*QlfK_*nMjJ)P;j+z}i`++F;Y zj7C=D8VH*W(fs`N#~Y7uBo%_=UJT8JskQ}p5Wa+;QS8BvH1Cf#`Bd$VjPOo_8tnm) zB3CW)3(99B_B0ck7AkB;BWiSkf5Z+%N%O3kRi0E(Mp6?ENlE0sksqKd{iP@wn0moO zMwUha<3MvS^ewJq2*gY@L^(+V&vX(+eNC+Ang`TbNL)P0-RfNuAXOP$WZZvmKGwVO z!uVH>Imhr?OP)ZslXd{*g5s|$#f+%T?b${la<&(l;yISD{^MyH$Eydy1pFA1x4Ti% z$j-dMd63p%T325MiABs|V^j(ZWD{Mt2GsMlm6JR`Yo|Lc>Y_}93w`fz#@S(Q5I*KY-&%pAvp=puEmyc-9^xqNcgZTRL$M@C}N@EMLk@m1fe3cP6)@2z6hofy9WnMs~&v+i4( zQyDjQ?<9-)6WgQcq#^2ZN%&5UZ@U8dgu@z-W9M8P1@{01@QH||jg6mrEI6T@ZjNlG z+ElCnR5b(WrssRy15@1qBz{g!9RNBAOf8-P>X2L#+e$R=5;UAKv#5O;C~G6BJT_WD z)?4-V=~|t8J#)E1EXQ{;sa_`(7PsKQ<791rNAVMqr&t zso+2~F(znFQ5@&H@X)7n>gF^w9;&d86`swhPhF(O2u|?Gd1(GSp`MpXov3k6a&2#wRBq1kz4WffWWB_ov!g zZYtj+aVo#FcW>q7ynxu}35*HLFK~oLKwWCPIsTlG;I&)c@J3OQfkE2ursc5x7O-h3 zkWv2jGiKSwJi>HAok-yXI>zytgn7&a@y*Ze0(+(D{1GWgsT$+;%_m{D50=mIAQ8yX zBrkGrd;q{%S~9`(X%Qk)QZzA;v2QOA8QIyf%BQGLL1_)L{068I);2d)-@WSs3UA5C z|DrQlpoEDYT!*DPs(U654n}V7+S#lufCEGtu3tG~zQXZ!poFOHeHbI)yb}A#JyK8D z#6lSb7Qh44wx@<1bhlJlPB$N)A2nJG3=R&iS}2SQ#i%3s*f-qn31}8KHj)7Ov)*o= zlT7$_7Zj#!FkL7&kuTy8I`*;D=aM6*9x=+Xc8$%ag+cu)<5OlRL(f1Qq#y>CzZtLP z%8b}Yg=r;#{6tjjPJUPcq#Fnx*?ZSdkSHo) zvgAP+bpgeSL7Ffzc;-;{8sEHPl2i4}r;g;|v#)wH?Xnq>0NJK8k&;M`!tL+<-QQQE zNv79{f=Z{HmIC_MnecdNbngI*T&>H?Dh+vfeukJi$YE=Uv%Z?iPQtu zTR|I^fS(hj_ocs*hp6o&#{*_FB~9z**hx90dWCJD9(rh&%SBL))d@)sNes5$sFxo*i1={xr= zrE$zgFtFyv_96O0u^G8)ecES+(E0UUQxv21M~kCPHl$$fM1TBp#eYGaJ2sb&ASvne z90)awGgPk3%--<^m}OALe#D1!C; z&L>UH&An@76%{vtD%xfI9dn)-WD@sw)#MN2+uu&dLZ64^PP70CWrh(F5X6G_z`fQO&F;41z#QqzM$WkVIqC zBWRcHTy1zbKI6%v$MSbj8@4|__&lYfBjvFsfH5(zqb?LLP}v<_T-YbI4=~t_5}f!v z4cYqh_Hzzf28ZIAl#GcnFYovI$6}Wk$(~d9ZUn*o*mt+J3Wi93#AP76B?FAaczE!g zAm$zUC_v%T);t7+Wl&t9kn`Fj8m;z51J$jyx!`#xAnQzQY^DGfF+~(X-U$s2r80~z zW=Ye~(eZXyQglTFT@1+i02GZ@vZZiWxsjR@A&W|_^1Y^;D4dy z8>wHPh2ong97S54Ejl0E$+`j^;{`JMMx+mB?THXNK|=&pj9_1uC1m< z0Q!zpm!)&`dXok0HM3E(w)W1C+zPO+4-kkcuw)V{@%3XH8X9EmOo5Z(u-Gbl#yOkt z4Puu{Xoi-3aHb5B3C`D5(A7tgp$$n#=-tq^;P7w4B8BWU4^w(9bb&6)FsNYOfXx#g zj-?bN;^5!_*Ftw|(S{F}R^Tm~<_%E%Ii}hI?ZoJmu`Rtn9 z3h?gi+SQ1GpkwAu5dcznBd7=AJVAuNAi;p)$Cu<}E+CizsXaiwfrl&_)>XYe-NYv* z4$I1-hIPz=!8~n*Va?p!RThz$QtpJrSwC&R*Obizm->H-!X; zL;m@OX*f!3ya5JJ7c~YqHRD8S9QBhv=USnpGvnx=wF3!+UM$Bh`^@i0H=aRYBu6sA z%&c%i(A{TE2EsPfR92wR3~u@y=TBu_Gh^zT|MEd}-dEHiF38#B-tXFnpQ9)CWzVVf z{e*tJHd|aaP`PZN1U-;{@LAP0B&(wl; z?{62EFaEo4dS)qwtq*4^LX(fL0&>&*50Sz@W-B#!=zmy(e@Ja^ldx8+y|ygAooD|~ zxgKZb$1+PXilOPC5HkrJLA$w5UrT6>WOCB|bP`6-<@Wcsu}d3qD#z%^dNn5U;~O#( zSlUZZokv3Q>9UlbmiKK{QrI3wzlEnn5Jooqfr7sf6`S+&T&|tvnxWWm?m5~&Ms%_^ zW6a?u^=}RN>x%ea9oD-oFoOjVAo060 z?I62vd1guZ(ED=BJ;lPuf|?O*5bdM>2$%yBm%$j<}GE_U6p{Z!k-3~U+5Gn zg?`9a=ZMQ&Q-`INFaKS|Xk%_LlntR0(k=o|j}>jOfzf-rubvlBr`p;`S#nY7R`t!_ zYV*Hs?1q6yl|cMyU*dSjG-5!cIo5|G+06aH8dlYgGt2$V2(D-U7GY!>u81rXF-v*Z zabFAGcMhqGm(rRiSws*oV#d6#!h*~5m_OI%4*$0XDjLy#QZEc8#7OOxNh~%jK(eKu zD@4s*6`t2bjzB!K3LcK&qW|~4JFFrFuL7?^R9AwOu#38Vt01yzR)vurcS=Yq7`r?Mglqz-%??89VDc z%6(v=%F4nIvJJrC&M+TV-hhy@p9C+-?sjZXsw{#6Ms_Z8??DmW#xfGRP;QO+5f(Z+ z3+z?<$iciMt#6n^+?ZJ)t?Z`st{u6GK4EhZJf>np0X(48aruxDP}}Vqz_R??0mav{ z)o(Xn4{a@bJR?43zru1QeOE|+d zaj-lv+A-NjTdGDkq17q%K8)74+T!*^k25UD@DTU{A1knfgyG>ZbnxDNNtgmzx@InX z-M!we0r<76dnihmdV%|+3fKK@X`H%e-*B1efM$Fto~X}tgS%3X_Gd^HWh$2lQJ^~W zgK1N4_A{in3GR8vL4@S0;zdvWVi|rFo@W*!s`P$2bSt z0>!@;$&}o5h*;LZUCp0@FMp|G%;>1(Kvdf}Z({XLx$B^MW;;LMD-2ltC^I2dP=wGC z7M#(f(=R3-Tx&L(_DXW!JfZn{t}YHDwng2J%3N(A1r9$0t%`@1`F^G;;TVfAsb3!x zgG2UF=87y}cA&RFo4F`~R=(^RY!RdkEV+As;MHW|)1Vp+(FqG;crPhK|LDB`X|TM; z^IGH#d3d`>bfCwOx_jNe2!^-E=meDNblw}BkQn05W;HG{d;6^vwT^ZNuX-}vv)#!Z zeZnCbpsPN6!3=t^88jxe9@4&I0jFrOrvhZ#Jp$ojF%1eR;7+dW70ygENCp~p1=v?c z4Q~Zs(HjX0Bg>!LR_;QpibqBBni2(BQxgya_upv5QwH`KKMegSy1bIOD#UCU6c~j% zfiU?SML@0EpEYEC8n%c=eW+O@&nxZl0s1|2pY>#deFY+WKQ;<$-bf-|L5|F0bR3+t zkI0@X@So4em$};lSsSP0%Y4ogOcLKNBY0?9H~R_eZ%H3BE<3G&k!lCXI=}U1rKS&367b>+l;8wVK;wGbew2(W&U2AZWZ)8@^x8@-~eAg%uTI;@~ znr~gVu>4ZE<_;_|gox|_!CGsaO(l=QC7#BIudwbZh zLx@rAXmc;GGxzn~6Hlb@L_NsBNMK+Q2e>J*RKAn#sah4ilTrgmIF&1XY}x6CsHn}I zM_7E+X9F>js&LCvARc1V`fHsPJHVQ$TlPGW-w>qhE?OJm+uu~fJFW)$a%u}zezyoT z#Fo8V2>*p@BxuHMd3MNy`Wx4?$xe^3^$B&JqDHZ_bVkZDMq0-8p*`b!CGUAxPyDvA@1~;E1N}VL5b9zjr1SGJv$VvdTIFU% zSxH`G@?pX@>}8|J-I!+3n@hdFC{3^I3tPWF+E@yEaTVfipqg18Bn4Jf41#7!N&!U` zk}4eheItw9t^i^Cm0-B6SNSwAxC3Pnh=yZJ_QCo+v(*(fy^XIsE~1qEe=V)}{6DHx zP-!xDWF2T&^_59#_f#Bp3iUOcKE0p z^Rm--hlNJH{~HLPPyY=KltY#JnLb`GTi!XyU@co*!a+Bj+zR~NC|R5*x3c;HuVK>x z*^TmpCXLPn2IK+nR61CJ+cmdbBmmiDJFK&GCl6edD z-q^?cl`}z61U1~fZfj-kIS3|k664Cw==f6ve}-H|FTV1V5uedB<*1Lng<-I;rUYg? zmwvEDe@RfCC#kT%^fLE@W3~`FJW7x@GLZls8bt6(mLo>IDx4?H212aryN4=M9fsp~ zvMenv;HB6PU2T4h952g#V2xus6k?~)@i?m_iE4+L0+#W{q5^fxyNd99c(RX6vmHqB z4W4x7-@8sNm*I;tRaIA*IH$R40=Kz!F5y`rD*y83i8_L(1~$30Nycp63C7Vbf=K-H zS*g*FAh%VreYf5Z&C8zpet<)S(n$?+uvRiWA$v(plWLW&-8@Xp%a1;!d|f+P*wuVsViK0?PzjJX`m46D6^RTimnAs|w`^5y)m}%N|iR6YwW!1{r z*lWsmwe>x*Am}5pN3EUvkVUkq_bM0V2?+s<7rz-_Bl%unjI1W+1x|ZC@9Hb65tT8q zQ71LZvQ%IFerEdb;%-&qu|sb^QA4|LbX`Rne+&&0tK-vFM#xc6EK8t~4B&H7Kpw*A&n8 zK$S-L=@u4wH+||fOaSrcV(+YJJAk)9L&QW0)&wA1%K+Y5P>%Opw(No_yFfh_e#zF0 zGSDHm`1b+i>gPW%>}p1cWHgVm@hLT$qB(8E0{H&PB1LA`4f*L5X&6A*~%K z1EnWonz8T&_0AR`0&0t&q>(|6umEHg*4U5O$9%c$TvqGi>E4NYNZbtK$AHh@(*+#@ zBN-#kVkI+s!Nv@pzV2ZpIX2?k$2VV;nEB1fmMMybEUJq#^pJdn5@f-|@7BVT%hFL% z7p%(Y7G)AaRil}Q65XdA;Baz;ip;^N}J(|BY5{xzO^{6VOBM08+(6 z`7IBFq(eAD@D!oe!bXXon4$PR>DgwUW>6w~N0o2xD-O8-op%lgCZ}%x+)`ZJqSjddLW>#KJO)Yry z;&55%^=o+DdfWF4jZToe)2v5R(58S*oq=W`w@+4DXnmN1r&Z~oprDdq(ZKETLK9AsnN}|s zUDpOHd7?U^Kk_IaFHhjaLoGLK%>le+_ zAE(KSrY~{v@Lo$xOG`8$!sbza{CFK(sX;tr_kU#{!MY6*Q zU34ZdSU``L{6d*G7^w>g6y8=%+89QLdYDAjDHVSkL3XIZvR@yLxX4yT4xBa&5Kh*2 zCxx|EBUmepdLjs6y<}jGea3_zTof+7bn>cuJ|*a7Cysyl~#VkN>86Jb-P&931|J? zUdn&yMILFhVSnfc-L3b-KoUBh?b4Z6n?|+I69MsONjjMqkZJR{&?mZazQ+o8HN=F; zVN!0RXSVYg{Beb!jj1_;9T$=*Yi2LcWl4ow^kH51N#bUoz2v0SM`&jr)dZ+B|s%2A||c@Ly}-L7)}i6=YsBgH2nN2 zAhZuU9{pe0&HV(ECE9h?gvo~f{P#EKCZJ&s!JrcQ3Y^5gW&af(KK^Xgdjwc-9&DQ5 z?IN6>CX|MUQty2!zd5(WWoaYBl@EMWJ_YL^EtlLWp7s~Yz8G&6Ct5N<&c-SdYUmmj z{Ve)dbXF6N)8gw!%GIoT1u}fl$70{=T)CaN#}nNKdowWB1Z$E6f+6Xb-e;Duh839O zZ*kxMTRq5b0=hvkGy-M9z;ea0l5^YIZzfaEW1)h~t^ z$4;-pV@swVhNvJf>PlOhSUdLvvsa8bpEg%u@xwE*TuYYRDV$5gS&S|kTYPk*gD5?I zTPe}GusDOmi0eQ|9`EYSYhs&^9{@iZ7gU~0g4c-(5{5D%A7-bT^z^-v744m_?}yyE zt7S}|S7TJUqC6UuPbrLwxc$NvdnY@t_V()!2`C#-9w2Cae*8&ZNT)yAq2%+={Q2OV zz$nck}$_XIN{B z3qO05d<M6uv%7D&V4$Nac+;5Ja`2oYIgB(>v* zSeho5tfI-#t~91xi}uDDtQ|F~e;gXV^Jst#&tYbM0v^OL3OG9Eu*y+MVs!2m({+l^ zHK(SXXKVSvR+cb6+oI`pEaVwv?~1$JnK2nxQ;Hd=kXvHm^RbT`di{spqUH7_2(jgp zp0?%I2$@Y;B?c@+9LtR3FrYL@%r8yJ^3DsOK5{?E|FSKDfi|8pmN&(}n9mY`7!Aqe zeGTY8saCVNm?54LL7YL^JHnZ^3?F8b=eJwy85&;lba|3~lb8=BTmQ{AvAO~EL^44= z`k`si=G7w{0c8%i52Kum+HAwMiQCBC@P+(QbWmV>`Mlw%Jz$2UmVkyxYou((RNys) z@;XqK)YK>2^!(IttL~n1&7D=S=8l^ zehowi!j|c!WgLzgUgU9=u^{)As45gEFS=Lyo(vC{h6ARsRBYKZ&7d`Qt!cWnZgCRw zi=HkIOmK9Nmz$K_AJ~tmXw%*85+M-jgGOgYsJYQyT#lqJg=L-e&D+IxAcjVzb!$MN zW{&t)qr!8Z3&?fkp1y~1$RjZPqoeQ3*?JS47hp&vPdkLG*eJERBVISW&F(leF(;bf zU~{2S>w*Vye=7ZGz?PcZUP%dUOB0NggP&f>n{{f$T;PX1MY>GCms^o$~9$}4)MkAjKRnNN@(t#Fh}eY&Z@QE7oSl;vY1QzYohGi`eC%=QcIif z1KqkX>d{n+Acmg(j3-_a<;3h)l@F|rd|%n@#_UG@WuI;h_f`@gOLR9D$>4>Dw)L}w zqM}E|riu^Tgn99L5Q#n`_p#ZciRy-B9IZ?g(^CMRoDpI$ztL-{yva@tacV0k$+%`|11B>-UF2^65#`S*IL$Ii;-((BE%j()X)NU^~LLoRHuDyL*RH2Za&)|;iU}3DVg#l$VvyYC$)c+tS3?LOp6w5GcuKs2%8J@6fvWgnynXA#G=N#$7%Rr}F+ zo>(4Lh*0tRvgLiouF7-8iS%dM+_XK^LH~FkUjJ3w^#SW|p=2=&9Y_f}S$36g|59*P zZG1iWxO(`#w3gZ?qSt7`^?^@=v98Ff0ru(raI0DEcT?uEm8m8JT4NX3e_5)rD7v5%%_p)pk6)CRSjC zGqNz}6#w&v2VTqPdA7OHT+zxIZ&vo}%UFJvI9PuH@yul$Oy3 zVD(H2VC$jtL#Li|yvmu~9nKD~Wmf-+2n7GI&fuslxfaC96Q`?iU`meNk=9#QMthJ9 z25$SLWD0(Vo#)A$$)NW$?*sxlRYj00#D2*0T;~AcAmY8R6=%Ay z%`crscDWVu>6jK!@{7x-4M9=#gd#NVv8JTYz9=!hI}_8&&}D{d@Fe}am_%N{E1nxo zpP_6V1u)pDxjKyxe={|RzC}$k+$w?s=V{i$VegSK@Y&!4v_zRh#ap#h5x4=eA?lYK?Ldh{TNbm726yZB7q`8X7x=1F5t99&CCbA$V zXkml7vRBte_cqTLvyZBDz5$8y@7`=pXFa*^Q(?LGM2fKAlN7a=Yo+P9Vi}{N4fyFj zI6^w*=obZph1fQBye#o%4F!Bi)hk66?^|tJ;zWZWO^CJcnz0RFS-V z$eVBjbzoW*(`I80SkivfStenUO~AGR?p%Ot22$_~$s;<7jz&P35VMct*L?w*SHCP(lbtOR!$F}YJa zaJPPOa-Ak#k9HwI6;={;H0zXI0y01lAc##!0 zGtq!6vUJ*M@+?I!mCsv@!UWdDYiV&P&AC-|5=~_IG6pCad;I(y6DMUM<)ms$%=1)) zs9>Wl1uVjKx z6)&enRPH2a;9?O!k)`3(3zabeC1>h8T< z=bDYDj;fU1j5V=|e&Cmb1kYWU_UktAfphV?u7l4Ts=zVMDc?7v1RFSYwBLjVO$4Tw z$^Av&BDr%=rv=hEc)(mfhfh2DpX1PaR@Eify8uWVg~?TtSEhI}M_LI34P!$->7)fS z%c-W2vwbh0(jRTAvxZpK%zhQ|6S%*<+yv8s&v?{#2I|SDXszGo4j07e_9El$=nsTP zkciB;Rz7%(1}C%NCwH_h*&BoRNE8}tzw*fxd|+>6)iQ8GK(X^j^xVDkcP$?km7yj1 zy%XGAP-opBwK-V=2L)3S;?~wIumMdldz1@~`u$GlPk6jP4B(@Pnc9me8e|nyc+U4k z?Zfd~B95=3(rq|x>ArC5+q*l4yZAXGT^qb{d^)JKhy+wYxhCi1?O>v#jJn7%?aF6v z5_0!GDyGiejn}7nU6#O0?ftiEi@&7a|GjHS`{`w4x8Nu1KoVS zSB^FwvTDWNAD9P^_t*;wjDUA_qcBaH#`ASzdH8XQ~AdywO$(dd{FCH8S{|?Ul zfCC0UfI2s$vA8oQ-(FJHSgNI~$TSBMvkOIDIcQ0wRIC?R<_J?S<@%VH9YGgPFGAQsl$1;!U)r=;G3 znV{>n1f@nWJ`8@v!zvi%*|+Z+Yt!=}%FZjeVop8 z(q>V5sW=@@F3gEYC@F{R8WyF&)4}OnQ!rWxj!gv6a8@ylj)KF>s860)!=4?R4*ar`6Kub^&boGhu1l{Rlj>AJV<9)gxn*KEr&J!vxz5ZN-K^Mj zGa)*1pkGX6O!sTZ8#835~Mj`9-46q4kM~X8Wg9_no&GR7~BwD5+T3$XAVjy*VWrJ626_ ze&=PF#({SNCM{^6lo&O5-=9Sv3mJIhjZH{5Tbv&J$hUzpk9PN(YVM=R&_Fnlqes`@ zK$yr1)RQP)-n5>ymOp`quC_+<)q8~Y#jIE-X)!He_w?x$gWo|gsyI_K$@XT^ zyCZw7eT%)Gv~q3!ixEcZaPa0-s;pCDDbGw-UYDi)qJJd26uj6d-!fAbR+oC}aBqUZ zAXZmz0;d2T``-4?(D+TopAvHsH`A$X*(nnQp9Yt1{D?vEklix5o0-?>-?rSk4^Apj z(kZ34;s)9vOFYKu*bOL7m30&4BBjhVBjozYy*cdtyN)2sQG886zF&Dd{|?!oFXuGc z4sZVAKJ+`T>h7WQ={|Cgj9SpvAE)wp&?dG-my%JpJ8LEsbtR_oK?q!*%eYIo>;0Qw zGevZ*vs(a%T4)^Er1g z;{4!IWQz($Qh{FaYcaRLUV&)DWgAU7HE0p%2bYZc*rsUIXn2`EQRCUSl3%9Vquzc* z`bmg^x#Hje4>L%^^Q?wIhyylZsZzTe$Uof$&hPs_;(!Ap8dY)% zD^s&qD=Zv8oaFQUyxNawRU$D#vvA>6iAG+8?@@J8-L%SyLM=QRL@F2@)_v2!)9$V$ zLszP1Vs3c;`dt3zIUiQXJJIJDfevgl7rYcSAaz+NC!t*nc2aDAKc-t@@;zSk@ob8m z(c+GJq#{QY^QERVtQ?ST#=5|$!a`X7HFems^%+dDU=FZY&-F%!FS`BkU3{kQx_ZCb zM&sjmFU=6i5}28`6|V_XXOSA@@_#xf1vZ(>$ozQcc^$T@hx--Msn2|gK$d+v#U33} zGV*hM)(9)%vqP>r7;qvZ!2MGjvM3C{QgOUguu_ZQFeuJykB<5JhUhdK9& zefGYt&%S=qS~{jzhdP*kbu=cs zY4M7COYTFWaQU#NhG+hqt*mzg(tAe8IJ+Zb`BdvJ;D;WK?Z!yvFbMc@Jgv&g#C&q= zu#B3|=Ac`xL#6=c-*A@}x}Q;(-C@c3+ceCz_}#Q+c&c{lN4V|cw%f-*o%eQI0OD@)qk%D}3Q$|^~?)Q>7 zjo8!S4Oc?}y_q6D|JM(E9&x}spDpMx?)*wZF$b=5AP-*$vP-7}WZj7P_d5%eLsdsF zP^kmV$6a!H<~P5?IH)sy2hf$fgYT){XLC@QLjLiAJ5&^pT6_hff$Ip0gKj4hzh9SH zfv$71Q%eGG&rwV@vvn5K$CnYuo_wC2>}i9I?_ctd>8Bz-$7O6e9kOx*mp^S>xv`Vu zc-Au6wqGTCmUH6>N?H!mc4s7i;(QmABss@Or6>C@`QB&Z6Z_Uh&Beq-nQ=bxTck&2 z^D3@n!p*m@U+)y_?!efA0`$tU@$pu`Rbw1-eX_R%&jC8oI|pEIf({uQ5ICptJCL(z zWCK}!QBBOT=Kr#0`Cj4)C(k=2wNRs81{8?;x;FGGT=B_Y(ybm_j93V6<-o99omy$) z2&E1vV_PNNO>r27v*&*&wcsMJ!n?~in=8L8!lf7WPVIHl8tPzME>5j|HD&uB<^`ic z1~&G?bm0>GDaht_=>TUQkV{8^LeW3?3e_~OFknGJt^R-2kn+zs0Nkg#dUUP)do7{X zfcke)iH1cHslFu@Tic(I&VEYtCpnXFJ>C)?rA9HJ&QhiY?mL^8AgFaJ8`Js?wmqLZ zWt{wv=NgBol3%`S`ec6NW%w-I1|$o{e+b2xnS_(nDIhjhCA39v-)0Z+F)=Zfk62q- z0qy#V+u}bZCGCYG#ye7zUU|di)923{KL#v?r3Ertu{RG+=qeUsOBisecZ7;12S0t> zrynX-7q)vn*>5py)4+W<6T{0gLkKg3D%vI*Q7=oYct&ms;dD4PVZtAWHE*(nXc9XS2PYr?q`WTi zX_N+~+B_;!TFkl5=-m_M5Y!FB=5{6nPhaNTF{^~Qa4vY!LT9Pcd6b|L_<;DhI8+AS zagT{7yu5Xn#z5)}jIwlFS?VmnmOAM~4cyN-`1pU%cgFCUQ#vJ&F%^b9o8REv@F*pq z-iTbWsTa{Z`O3uFpy#mmUr{O3DAIr&*Y8*PnresC&&>axi0Y@~vP`~9eRIwm;DHY! z=6Q-@Q#>YiwSd?n<`s%nN3T{$HE_)UAW{u%vTVl^sMhbCut4Yx0h(jr8#f2e#7QT; zD$|6y-!?swI2DUqghNd<=mb!|Ti9=wbOaW&Zc&sU+x4{T`VyVax5@Sh=tk1KtgFb2 znl-S`@`1ytH(!W-uKHC%-)pyzyN(m1UMJMWA_FHPZ*0BG>p9L;M{z3RN%}xy>zh`V zLIVc@z%p=k`Y1+hMcFw6+7dhP_4Xyw0$(qhCXEEBL`k{3^Q0HK0W;Du@Q562q?+BC z-JLrxY(ThO=7UT0|E)hI`#@eRr(<^K>t269a(wgUb3lwvDXk;_(ydc$bpy2f>Koi`z| ztax!>Sz`*mxLhHRdfXT;)^_6uq7<}$0*^o5V@}z-M?7&BHv;Lns9A-RyO~Xw*I{pn zO1}kbWL8<0`NvFpv8p@{mgW5L!-=7#b5cROD^_oM;#+)Y8A$!ThiD zoxIadE9J9I)>gJ}kLH3EEWVNuY~4H+MV|^IrmdQy03iX5TZ2E^lu_>{Et1&7`c^W_Z>}&_fwhweKtNaj0%#n#Y zEf5FZbf{9{yljfqEc@$EQN+)lT4>w}o{q6kLCNa}^^~tXHUy0$d+(Hu+L;H{=ICYK zAl_B6hnFmD*%PO`ru{v8YAM86Ap=>tX95!3}}kgx0`V+q}$Te}^4*P@`}ccoK>_U5mm zdV+xXIYszcoNsM4FXl_oSO~7RjAdR z%K}KB95PLzTV%U~iS7qI!^ifr9zI5~HcTM8qrzm0jMq8gd3xkP=y1?fD$E=)+!VES z)ZxVU;3idpss+aUnp*A0!k!yIKnWVH1;h|Los{aQW_Dn*Q6`V-YX z#VYn8C8AAFFq&=#|5b0=z~Pw^)@D2uo|bL^F^GK*z-e|uomx92)nZ>PW%_fu(gc)) z;H+Nag%>dl9?&mm2e0%73O(+3|AsXu0Bt|xopRK%!MZ8f{`pCmC&Ev-x6Egt2Tk+i z@xIg9LvLFe9KKyq;g;c;>35{ql;|keFRIU^GsQqu{2iC7(EW1qC$amqknjSkr#9_M z`+GmM2LW{}THj0K8UKRiG#!P`p~RS?c&cNX4&$}8p&g92 z2;U2C;9ws~NubaBlC-3Ws1&~1@fWI;@A2Gk zodS?*>c~KBdUDo#*llgy&i6QisM59WX7fciz2soAW_rAH?NKU8llIOiC4Ih!$?wdN zR+U0HF5P1q3E7ytvGTjQ2KxGR>e7v#MdBrezNoh`+WTE89XRg6uyZ0u@rVUW?hj zQ|vz*G1tuxHNAnw6@2I`+CC5XwZ}@^Ki864rX{K1b{$|xZQx(ZQr&#(Bxf*P(+ z{^Z>YCSR?agJLBZ+j&d8k>Zona7!1yK%#uAcIk=A<=XhE?FQmJUJp{4Q~3tdk*C!+ z7xh)S2awk8RCobLZnd$cY~-+0zC#1TE9DQHYqc&CM8#n9I6;4-*>XK7dVI6MMG9(f z?^}kD7wfd!ROJk}TX!q3Qru|^iC%f6w_Q)1r!%%tw(0v*soJwDq?5g))#f7Aln5B% ziA*uGwm2rZCxf@xM=!TbP1x(FA&fu# zR(eoAiI^7q<4TJ4Wm!C>n zL=o_D-UoHG^Ny2(IT#F2!6?XpF8~`*8jMa`u-(W3kgi^Q-yEBkh%lp1SUedeyG63E z4X&m*6(-=TwSxs#P77b-in>mOzq?d`vujmE>S)o;{U-?M=X(m1PHRQog7RF_?4i1@V;>r7Oo-?8~@ z5b1jde7xzFAmgkj3$>oco0Q~LZsVg?E|WC?X*1wiZPx^5x6>DM?fg(?m5%vPpM+^D z%Dm)V{B^{{1x!rcl15zhW`_=}%^{%5wo~*vg@~km*~#Jj9$L@@IoAw`q*uROb(*-i z@}zaK%(`kGRAi@B_P3DBCo2Az8e6+Vv0ei>&>PoiCe58C>+YGRRa)|tlrC>zY-Rbg z&9G1p9zQjkrwNfFm-f_ZrEw?uB#6T(v%z$7Ts?mX|EsyanUx_mryx;n-_pXyFjs1Dsd6Yx6A`N`Y;0RPh#@x7V)IQn}i z;G8xhzCk`d@&5Zah0V=D27fW7)S^-P@bJU$ zI$+nU-YWTtl3&H9V5qOe^XQr$;?hi>oMzuUqOukBtJPM`T)$=EoNn8Oaqsa&%jH8d1_%ZXdm^C=a2 z85Qk|RsJM>@8l$0iBXnfy-c&)%&+qWn|A6P4%RJ7Yea`>oo{eX*~!&`Rn|;v%8GI_ zqigPlMB7smS&8&h z1#Ok~m4k9Rr2;X7my<95?B$3~k>N77Qi5M>6_2Rw@k1}2PDlZgDDI7>4ff`6K0Lpt z;;s(48v_<|cDZ{(bmCc>bRr;+yrbzOwm!++OsKv5x8$SV;T`sidLq*s;^+6Y^+W4s zm_%;(`?>}nWzl{l|D$HuA7C2Noz_B~$MHFYekfO-)G46r0pTZ0qeI|$o<&PFVsTrd ztJOXwxi^}1c(X{k`H@Exr-*LHQh(_(jp2UHYK)u* zB8m0?3Whc6eZU+&{Q@U4h>^MR#-`LXF<7t)4KXg@-DR55<;lD|828m~!*VTP3uY$r z^aq4GZ8w1ryEq$Da$7nhp7Qhft z;O5ZYv&8TSPJUCAuMf(^TWqVa6twVsj6s&|-g3twQ=83KQsiKP+GY z#;QL<{^5abVV_on&(!|n|G7`tmWB*w@aTNCUOA%9wRNJV8f??>-iIVB8my*koClDp zPiz9_6+?9CcV`h!)AobLz9Y}e3Rk2_!-rzVbgc@kA4`RU-$3f6;%h;>Kfj;DIKp)X z&y^m@0=X^qO*^3qJ5Td8ZJnu`1!>E)+lp6zwMU@Z+H3lr%y%zRfmd?I_W%d2Z41vS zmQ&Q{6E1G*rfDxx<6GBdKi3rgKu)kguim#A9--kPURiJCRFW19*DaX!e0Q?U2%sLJ z)xJ=m$SNM^Y%WUqPVjnqCn5e3+uhSK@18y&VxWd0qOzlgq4681316SH^DL`9^>Yu8 z;N?>9zBM7#0i$kOMotRP`vo?F*?2=%kSM!$K<$&6o7A$Ny9wj`TTcoOleOBL6P?aS zMXidQ+}aXtIS=`RAy;?E=`>vIz2uiv(yY_1_6U#fZ1()9;L*WV}Us1VjrAKxv+`Y|}- zH1E@eZ-zO21}gJb$?`jGz@QdjidV?%iOm#R>)w!2r4Iu{J( zsH~A418LB2jr8tK7Jqk#^PWISn)pMO#M86%{lz2Rd92YrJ9g*G zALd}gi^M)poRiUJf%hGBObGMTcZHk#A_GsPZ(nX2H_rI?bi)JQCm);hmAh-U80Btj z{xhRjm31cj;RE#TsImKaDmFW^lWZ4Pc0WR>mXoDl{xmQZ5<&}AVBWd1R+k@MUC2h{Yj*ev z#u+sqgDl;ax8#(6%GP+5e#ba)Q$$(2t0T&rJ<)t@B@|$6;m6WDfm@hnp2Wv z$sp>%U7(QWLo?C0&#Ij&7tQI#oLX(ks@@&Z^bLh?Ee(8sLa}B! zc7fCvj`*_ESP{BvSvKXeEksvr>}&!(b`p zahJ#364Zp9GrpyQLnZQrxTlhf-aknn$|`9261zVyrwWS>mk1@C6&t$q#yQ>^Es zQ`v>jlOl8QdRvXcqqgVoKH&9$Mu&led`bVAV4?lNx^C7Dqp;yH@gLP-$X3l+S7X)T zl^<65LbsvAC)Gg_9E3A;hQT30nQ)(G+?6JP{6XNowz&+60OkBWfk`atE+aEuT->m$yw$ zRC!^e6S({;W{_E6%~305J~eO)-QZ&9u30lc=#+S=Pp@IZR)0!69grhv7tJiacR+pgseVvUf56 zhhTn23;mBfwn)>VSERHj3fN{7zYE|>vy}ZZ(KqZE56Ldz1tpOF-+lY)$f%wIvNC*Q zOZ-LiUqDyI;G*!_%Lv;I_ODVMb;%B%zqRn@w_QGC=Lx&T?o=UDx}o1sh}Nd~D``J_ ze2>NC@D};B_Xz!so*_o$cF*0sFdF4Lfoj8*W1H^XkX4cVuJZUS`XS)m{+EthxoX?z z!4k<5zAz_n(tUc@h1#CU9}_v@Du|pdO_nffE%hY%C?V;mvltH) zWIcxRk;kN^8Eiv%M)E#a!r8;;{7ZAa%T9m+9BGD@VB%fUAC-gy`xrwk4K`S%^ONYL z8gq^ERBFuSGAS+>tI49Is6CNj(lNNukXV3}VG+oDK7KZ8&lri-gjPGvyLd~C2o`=3 zQ4X=lTjHRL3r;?BU-J{YQif!=Y1-;qp(S`V4U!WJl7`c~pk$SuzMIew_z0x?%Ayt? z_t8992(WuMyl#-C-NXqOyTLZZ5*PA%XEy}73CcZZwW`FJeo~YWMQp3!Q(h)|A;Num zW{w~|5il0Oj_27pP<~_k(?B#_Vf+TWs|UxKgMPF>NJRsLt1DaK-4pLdBx4Ehs@{H- zK@3Py{>P40W|Lp6LiKI8|Kf}(dC0mNjpfwr`=Jba(7=nk(Sw7!8Wo)I-EtnL<^n(x z!V6Rc+)1F-HnsoK0KO_q=^ObBJ&?~~8Sue4=v#*`j}aIPX>KLDCCoSFL0rq1N9Ja6 zHDqHGWx%JloJW=;O)G)Oa9YIaBus#F5{GAZkDaDJs4qC7^Q;uJIH8zQMBK;c{>n<7VD!e8QnAR#d?h@24ANS!)o8nqnvPq-ej)R z!5?!iC-&;dq#>alqnQcjTr&M7SM_Ty0T;A{&BSM*2+ILf)HtH8al9HB;S)nT-aekmlxm~5rwM|X732N8kEV8 z(|Vzc0xL7=a-(#AmlnN9vfq>_3M->&MA}o%`WGxYWe%fL>(K)!RD5g~f04+XrUUQh z4LAw#}@ps<|o(*IH?uy=co4(QhTVR;F|m$I2jJbA+yXEzI?(1}81yOW0k$qhpz0|r zuY`SBjI-IIfws_9H+P?eLWsWpG9DXAkU3jD>%09C_M2YXe$f68P5z=ek6!sbe8#UI zOIbsIK%13$e;SO&SjX^x_*39M+r)g1$47eXKf>b6yX7uEn1ixCFRpIu=*e{ErC&l| z{%NgXB7?XXQ92DtS7iphQ+8;Zemb@v_R_Qi=BTl2HwNU6S$gL!QpQ9;7 zlc{daY=Rb}t{MG=#mSeW%Td3QOm>*Lhu#>y5&vqtX&d|ToZ1a!iHV)W@M`0PZg?_i{kfbg=c)QHeZ}15-w|r@;G1KwjAJ zM?<*-$4xoQAN>H3Wr3&fj&^%zcLb#<2q=+#S#jkGy8OG-7=cNU2RcOnHhm4^DkU{l z$G~9w@bRqBP_FVfjK5G9LV~^J6YlQax?HoQ*Z2yQO?1t)bCs!OKA8Hy6^*?Wui@Vl z{5=kLE1qXq1#(VGN7~`qQd!+d_AIh*R{fIq&%c=TqT6qbeAyHQFStRhsmfYH=Yh&r z=s^$5K&u2}dMun&`Gu}vQ0FwJ)a+lwxE)`}3SxeDD>O}kacQK4W z@6HKw*;|DqEuOG0AfQ`cUW1r2{T5?)mxJ zn~*~>djD-k$LB^T`pSd$Q*p0OzkonXsF^lpz+!io9O7bP)3vnz5`-~-7KJ~U%-!g_ zD7=)fnJp~|m$bA#d27{gJh}ZshOw1TKT7#TyZZIlp3aot>4WB1=UqAH3$J2I zN6SArZrgR`9ec)mEj1WhYi1XE-(dZ9>Ske--5Rq;>uLpqN6BRlQAm8i2wKVj)EW2@ zodvkH=gl_NaX%fIxwuBxR6H3_t|wPr16rvQ?7Bu>&qoTW7cnVtqLTZ)qq*iUHjg%}tc{{ZCjSBZ%>pjPVZ=l4%Z_ZT3` z9|6lA5O6%-E40%}FCvdIiqWmaa%}!Q*Rrs3>PAiNEIt5_<A zch?k~>mdU4kldrd%M;Drn}XpgV%vi8n{V@=`OBSu7_i#!rsHh=huW+{2OIoQW*4BFZ1$AgMXGqyf#Qo#smnd`cb$4qvS@J1^|j3>@Pe!QahVfM}q zkIy3s#YA38mx$LJ(=ha$osnX8TGim4{h!}&NeQBe34YZxg#ulM6_|^loktRopL_rt zG_X3#`Zg<19|HNGJLoIo4ot|r)`O&XO`i7ZMrNC*^Ps*MWda2G8u?0jldMrFBrukP zr$47X{6>i)GmdEN^i_T{aCtP$p0LX5uX#%kWA@MG9oeKK%QUD6V9)47qZ19wmrI>* z*FPouByGla#U`^9Wiy`x$8WiA#qNm{`x9`i>++eT4xYkw|HC$9-bE3~3-3s((Jo9Z zNj@Igh#uItvm%XnV^gfEzc2428`xzelnTmNj|b_emgc+iJT)EgRo-=hP?yCk^JBlN>wOk#^VQ3ebc|#v5^$F!xv-&WQcRh2cq7cZ+By|S8t#pMiy?c9sQ&0 zS7wrnaFIjMuBX_VHg5|3L*e8csdm8oJk>MCu3Yc4&Uaq40+E3UO`CSU3NKFxez0le zI=v~Qe8?1*_p}7}#=R+2qe&hZl+VS5a}on`fZ0yYU5-zyb0aWh%|2XW0eaC5i=91r z+MPoTPXqVa-7&rs=9jed%SB1&ov-t3;#wDtyS4I0{aH4aH6QvcearZvLu1#q<1RfPh+291WNu;`{M_YD%lTfJGe5XW_ z8BE$^g7QrP`l_rS&#Jq1J8+(`{{@lXT-O+ZYVi%NhD2*LjUE9*X&w!CXJMdc0#QwI z0M0Wts7O$oN!d;yo*Vi4wGm*AY3|-WEG`qM7`sf7j>iOsEq(k*eNLi{bW{6gZuhN3 zymQ!b(fHERGQrJt?m_MgkL{%U;dvx(DKeXHfTWRqL4yWa_+V+Up&T<=7m@I%Q%()< zhV5t)t2Fk>eIyP77z0RAC)9glkEMJvYb!zEQEV&c26f~C>4zGxhdD0uZkJayV6DGI zSSXtP1SnKSVN!79eC|!T;-xtbsM||3Q|s8ne4w$|=e2aoT=+1~^aHARYp?s|@`zy> zTTrB$?!Y{#x8{v+qL8k}W1M2e5b#WwoCGvz>rdG5b$QgaS-uF4e4}$&<2uLsU~g-- zxf{HzZam~w`LE@A^w?I-loFCWCU;VqO`=D8;sdJ{5kQ4W1(agbhMw8BN1IGf`dU_Y zDQhzs|2C{2+%)Jtyw+$6>_I7HVepMF`^%Ui9tlX!sI0P1-T9L=YWB71?yyJ%L}TR7 zP=eTLp5=0wlgtG?p-(*|BtmJDkV7TnugfRC-+!lp0JV8u7~pGa9e3|NcQzWBZqxn< zXKt)*bRl@-|Ff%dt1Ruhz1ndOB#)9^H#jLH>C}A_mT_8Vu*)SZ}K8b zhRh=m1YOBX`2$d{p%qKf>C}8T{=X#K^&Pi{*11J%E9f`=kOqsC8b$mrx0eV0=XdD8 zQkcSm#f+8*un~dxPYdp_NC0&|$h1gV|3|mbvr}E; z=Ae&OV*OXsnD_RkBadROO96_Z-+tN2DcY7HvP1;{?WkADN)`iubi;(tN%z|FgEyV%Z*8=~@M7bZ4ShtfoSkxUDhuBQZjQ1ZBecas~cHvYjn z^Jqws*T2Sm^HI1y$J)x5)T8dVnz(F^$hCKnAH{|{kuLb}wC*bF^qBF8Iz$|Pv9 z0O_54h)x>GRhqz-uJKaax#KN-9EXcEd0(5!XF9TC?bp+2i@)~mY>ExIG{7Fv`6KjF zNC-@A1+Y#9$!<;A&eF@ZiDLtOlE+#E^Ap zx_6^z3^Hf(y=zp3X|j%5AC%UpJupWV>vbKlV*a3yb$u=d;d9t{ztc(SR>O5f%Rw1H z$h?#^Znn*)|I0L7UVrL5rHPsGMLIGC$4xjLlhKmV^TGQpbp4;Db2LMlA{UtA4-PRc ziULo!u3R_z)K53~R%!rHLZJF;CYHO6UV~*RYC*W@SbV<)ClvRXIMrP_jK*kNT~FbMfq<11;Mx(?~lx!1qIt z0-;0>UN_UH_46kl=&0s=yrO@a0>wAse|cGwwRVOYZpRHh@}9ies2CdoRn~;no`^}2 zw{>ypjpXH}zavYE`3SV((RobEOGNoiQF2?*#{q}XD zDh;v!W#8BW8+U6+&Y&mfrcH>jbZj)pK+Eb-wf}SNHV#xxFwTrasO~k3oO{k+ss5dl zs~PWi(X$I2eNWX;W*i2T1g{1bP@O66p{RY2nVRsH)*bh%{vA_arTeQP^k&D0?mxNW zC&v!_5vfwexjp@oIctI9NQ~aBGpu-VwX{>9y%H)Kp1oT2d5@xd$ zrcrnkb&H_dEIGyE9#LD2EoQ}XS?*-BXF^OcSG8|eblnpwGmx-h}n`rN3&t z-yWJ7AU-G-J0b=?~5hyn_DF@!UtPc4XX~>iHn#8N6D(HA4UluStmE_QT5x;BRC2c zM zbm0gFejPayAzVhw$LmP+O;`Sh)7bea(Q;k-F@SCKIk@kJ@`n4C>Qn-$z^P5Im!8Kb zSK*V;N*u_Pu>uNf!*`5(vB_~XAX1{9rp)jl*Uw_o#{_D%P&{gJ#l4@6j{W*5`oA7YGrT#GUU++%WA=0Oz zoucSOl~b%9FaVURE7;PBk0XfgJ}Xa9QL`A)6XMS=ity6p6}`t8Oyzg`;hrSpaN=Y6 zj*nD9xqlx)UfCy^&Ko4?CKU4of7!wqKd-%&zC#Yqd^&8aA`m?pr}~V?7i0NjPBwGI zhJ$`x?O)#4altqS4>GIIs1a{w!vf-#t9md16`}c91kGAKLFq=s0CCG9f3kxqb2IUG zxk{8GQ;w~s6+J|{9^j^c&^1_WB3)7~qL!~#StDd1q_%2Pw!fl%ZcA%3DhQ0*UV|cS4#G@3RELMRUkxz&O zgHVkFW<1+lua096{dx^fkGlo}X5R07DWvaydI&D1J7&qQq~ulOYzmYFl0k9uM&r$C>J6OF6GK*q@%a>-A2HYVBR2a(IOv;7{*)3S$pa5@NX8@ z0*Aw;rT)5%97m)^^s?4Y#5>}=p#cyv4?T8ekX5$~^yNkbSIR$Su>+JpeN0~q5+I>8 zzTcU_dA0BjvXpF<0#e_`Ya7pC^;OCX36G&X%JDyLxzi(ah)NJy@76yAB<8Kv*vecA zBsE~h2eU;Xo`g%ZkDad_;Df4 zRH29w{(2f}^813hO#i0c*NDCHovNZqrF&~j0kvZ4rnl6MvtY~T+A@Wl@y$7rOf3Dt zyu*;T$^D7_{QKtx(^-G3NxvL?gOOI1K8PwySDTT=7E{={!bJ@Cn-vfbJ+osyBw@aT zwrK?ep=uryDi?L$=~a1{5Un-x5@+Yjl4Z`uehufUt^2#QBJN|E1pUTrnB}W~+0yX> zBA!5Mr^^vtV-p|z67zzdjzs<4XIK+S$zwI|dLrP^>~+3R*u2h^fYw6&$p*{iEa+X# zL(}fL`?&epLUj!RiPEg!OYm=)6%SZsMIPCk4~IK4Q53(2y-ZAbMC@ynvG@}= zgY7YeuoOmUG_y15y*#pkt0qU(dwCn^Z@RF*QU#;y2%YmWCh_`y$-U~TV(CbPe`l$I zZ|#Sj9qhkGOc1ywkIf-E3{VF zC`-)ld;y*AM3aN(>U5WFMIfen2lTFkAr2-n8mFL{5?>rGbtiLH4A$or%(dg4+E{z8 z<n_Lp4p0K0(_UJ9iVPWsR9xCw9T zSoF>-t9HI?BtuV%j?u<=YnzfZKZX{+sk10hNPL5g=xrtSDz14;Xu5ra+VNl)8eu9R zy~l5RYVj!#GFZomG(NGA370@5f+0i?wUrAFlTH3fD7i_rqlVDm@HtfdmG=)Wv1*FC zd-c)Gl>qBV&nDq&t;~pfUJtK?>f}@s<}~@#CTn zr?4#)Zu4U+;j`i7^hLTST~40IP!jWBDW3?jh)AYtUk8CP6&OYit!MpbrLcFCF(*W( zqn}XcffgDxm@67@ykZcKXclKQ7d(l}z7{$trswmvDZ9ladFh!=*BHI{@m5oa{aFpy z`iS{2ZyVZYBPcNhJuJ{7|F_E;^&z0t+7=pRCl-dru=CKk_3bx@`C|27wd&;qDBDiZ zCxS1lFqhw!JVx?u-YfFvl#wa^QF^$pL47+{HRYA{&W3^US@eZN>s!;}RmJ~;dafOF z?8}u^2Oap%(MJCjJho5m>hkup!Cp}3u={*{5&`dVhYtRJ_eS@CV!7gY9W?ReI>+$0 z6|D+~S9@4Yc-Yb*fAUWDyMNWireXmp1KL<*11=&R_43_zrmTPItMMXFrE+j4O79y@ zU?(7?<2|rcm_oi6Q_x!h;XpKtB`+$sE&Q=*&TRD|2=7MpTne{vbCd!j#qTIWNN zcZGrpHeu}GJ2qvMowZ?NZc&3nNs;S}EakCJL&mg)rD|^wJFp27se8VBzT>E_ z!zA{m62WT6u&AUeVj|u>h^Wn{QVSAxsvHQ@CYfuXxDy1^+BtjfHz~+{6!y06X~?l> zM=naLm&)fbWZky?_y(7MOzh>$_`WdQhc!M>JApk%>7Zzrf6^weNM>}DH`p1NB0-1@D7|Fs%_8Pf>`eeGbpkIi$RD*hU&E^r<5D2NiNYG6URP7t(*f!3-ma^JD=2JXX*9 zGPLmUZ5B+P_wOwe{sl=IGIyJJfoQ24-urp;`nw4}w$^yho6p=_YiJ38;TV=7A2BEl z?9@r81dncsfTXc*Pc_G;oST}Dd`K@$b>X(?9~oJJr6a^mWWwfCvYF%#?yBXOA~Rx;~2w&kA*)D-RIhu;`aM60Mv>R^?_^jCXd+t&#DO%+bw?~lfG@8VN*wq=zS zfV|*Ko3eDE(;!swM#;hWDfcM2w5}JM$gdO!;Y;Bq{;xBooFduaS7rowVE);?c7oXfb+YpN=8I-*eB? zW`CJ{(EG^CQ`8!0WO?yWh4$c-2mQq z?lpxbCD+>!muX*1mYFOzNy>Yl>Yl13B>pN^k<#&U33x7e)GdOJiX|l(a`4K|2k%zI z_;FGkDrlh6D7FKy8PLF(D=zJ{@aeeWEn1cSD@?|7T17`tu0e0NFuF?~8A_xS1}wtV%{75y4qD z=8`++@%Q@K$Bi%~lh#`P_3{+7%l!Gy`!@Brk*ypHCdmiWRw%dPFus8%5z3B{_9~N< zxkCAiIKuKLPz4lUj0lb9+2299g@otkob5Mt^77V%eKV3-ZGF4O;t*ATq0DnhHO4hP zdUVWrzs*-!<+`LLW6o0f=eMVSL`BPvkTmB$HaxsPNu<588Bqur%GvF;F~|ll%guu- zv_q7id0~`)`>yh9zv9Uyn_kCz@`~9`^1ueKZoL}v8e$9z2KI1NRAtrBq=dZy8=gF0M6nFU`TC>x3@R)dq8a0(;pL2)h)4c8V|=K{*5TQxaanjz zmq7|Gu9BWwL@qf>=p#msXbQsTrCT9zBh}oKbqL-r& zLlKaZmWxwxaHEH&{p?Dcn-qN~hA_aNp$Xmg9}?6;B;@($m9O`>BW>ym&JH!jgMu3h3KEl>c`7=G`=Mg7$GlM4MZC=sy-RgK9$l% zL9vijyiY8wr^foDNSZ&cbwyM&wR~sd1sY|z?&y4iB)acNHwMIyqDwII$ht7-#r9zaDNZLzWA&vFJSJz*i(QPQ;6UPsu(p%yxh*(4jN;sE#f0DT(_sq) z9KM*M&TTO!pyZM(i8oioC4LW~lo88WLW`&!$*H(!$EI!A*(!RHz5N%qC}tViXReGs z6JTn6<-OTp1M4H8nCCUY*h29yk*ruJVQ{H?5k~-7-9jssz(Vyu4|dRlZg$!6&oEi( zj%3H!C9Pd&pyX2E8exyB-PLL#^s<`A&&-b?;s9vN#+4UfPlE;&) zMiF}H0qcq^R2H*|M_2vQn$lh2jJkM5?z`4Z$nxFDEaa56+ersqKLJJ}GPQwHY^FUl z5W2(0b;`l7-B#>)BKbv#e@w)t5f}9phxUKxB_|(^rW-Nqca*<2WU40xO6url!PngH z22JJSYj7debvDd&Pupp2*?+Up#uMG!VnBnWk+U?rg%67RrI3-f4dTBjgH#w2&~X#! z|LpFfRG=3eF|0{^QH1z)-dDb1Xo}qb-bRLg${I_m)%~vUfgL*r^%3;Lh#uB9>H{gW zf<6@5XBrLrq6bp~!j9iD*b}9My5%Row!N%1->ZJkV!#Hy9nQOjj6#AKk^)J%R$nY# zZu6(2e82@G&#a^NSJm_0e@8x;DNjDZ^xPOjhw+J6>&pH!h;s-W=d8Emm6@zdl$LFb z9A1~hhRQ+UFAXhweKgFQPTdG8qIPf9m^bbyrQaG9D`_CaBFQX(?(62P$zJbMxvMeG}g7>=;Vy8|<%JL?+|b%vEzz1syH?u}&Ol z)OZu{iUzhhD&oBGnb1*ZtlFgyX!{|>U#48bJoqcN;%PXV?ZcN_-6Un_B!y8pjZF0rUFp_HO zT57Q_$QI#LkjqGV25RC)%v?u$O+VR+!Ih1`usM&gHro793}NGY{***4j=f)VjUkfB z!IY>vF6gTv6VB2v?=9OsIT+Dl^O)qJ#ev9T;F1@hdg!2kWC~m6*yLW!#`}Dw8j~kH z{j)ZbSfqCBX$@ED{ZNyR>h90-g*!tt=@ijd-u`q_S24Tqsy$y847$JS7}B6Q-JCYR z$Vj2fSxb<6+)rt*sW$Cjr>{1d4lzrC++LW*(E8a?h|-*d3k`HNq+)LtHv7V5byS+N z{7CFXt4=@WhasBE%!j7M-+xeU7*zQRu;wvrcq;1(zPC1zZIa+nyRO(G%;@)9kW+sK z-+KL@C5cjLgw)Qju1JYkI-|`4UJ3V;VmvablK((G>w~PDfqERpw7{}f8oP6qI2Gwp zj8i^`XL7%-aMMvac#^2^RX85^=poFi#&Rxz&Y*M1qi&1lc;q2dXZOZ;$7^x?v!Lfa zYaU38&geqZ&zXA0Sb^Sz=g3S#v&;yO6ha90C?1bIM5Py(JOSmQ@we){(&d{UOGd@} zIM`_NrdaXkZpHrF99!D%C*cNPFn+{2gfiMN6Z0>ul`+XuF#Y%KxhBZL-n%ZGmC-mt--43tR)zPiZOhSk#_5*xc2AkzE zejSEXW`uuBCTSB)-d_FopM@3?UU83giAa}DFJC%9Sh@Mx5H9JyZUkYv%A~jqb`lr8 zA`-}giDX0P+06CDt9L)+#<8Dfr+zbmOw~}eMa`YWgBIAaq$tWeVQUnjE`y<#6rSg` zl+B~LyPk{dg3E)Cmg63EZybh}mUEMViN4Lm-}OcN(Wl~7KEi=UD<)jcH!uPLHP`F=l{`jZEdRK6mNV2^%e~+2!vVb@ zI;+st^-(txvhXY>%7yORK7#PxN0*>Pk@dE1nZM+fT#4D~aH5)Yh|}J;?~%^o34V6B z{gexnPNJDu8{ht|`(ESgezv9dsFm{IW(YFMf`lM)Elbe{Pthj(LLq&Sw~Ge7Dtx)C zNrSr3poLZmK|^Z{%c`Rpajp-S8^ zzFJc($>I+>&W+_214WHHHo0XuC9tuTbBtw8ZV+p*7n&AtuD7vcrV&3&yN{)s=*8YQ zMVk&i`N@tH&;o_$7Qoclt7No1t@<`(lK_d!CVLIWH?%x} z#6(r~OX#_uONh5a}C4F1d0kL8w6nf;1arE22mG~uTd>llZiFS@l3ic@J`TT41 zswiyD0Oe;ty;peoZy6zyM6$(bIIn5<^*K%7*kDi(=hZg`Fa>aEgYSPB7Dg@M}Bl^daDSz~mANCo4 z`apt5zlHCN|9@&b?|7=;{*NCcN_I)Mh$J%(+3Q$eWRL7EI~j#zl~4*Lqs%hm*km3v zdlN!tnGv$%828(KKkmPO|J=XxpX1~6xjxr;kIVIbzWi8M|7n_HSxJ9dMTT$Umw)W| z!LpC5>A*N{;g-9e$-NA6J2KgVbN7oYW`woLs@~^l6cON)1&cM7&<)GJ?2xrIVx_dY zLP~-EQz4{9Ygede-bRx1W4zw2iHvC$haoXNA@?J691^+Tq~qMXAiI5z)r-_R_6DM3 z?VDp(dEt`6^^cLXNx=b)mv58#y*IN<@7m8RcY3Ofu`CuX&)3l@)qSN>F;XFIA4T-h zKDWne{<^IDmLx?w?eSkCvccdQQ<|N)HRlv8h1NE)k^{oS5ZfDd*fX7<{p!MbypMdu zY&V(!DTl}$?>7f@Jjs?lcVi!v)Kuh|teLkPIMH!kEA&oCtNuDVV?phpUE?jN<_ zA7y%rqgE56&#IO-!m;QVp>8}$%3dWujwkvF8bPY_;+b5hx!*62%uk7hrm7kfzdBIWWqF<5b0(Ie5-^S^yxQu z91(xe`=za$UiZru1z)rLr%^jQUcg$r)Gu=?iI5!&AaVVB6Adm)rBoD8 zzkQ@OB%V8tY{#QsEE+XzJ3>PojLF~*enYMiE1t1paaH8Xc~$KN66V~)%X|7UD=+F) z&pp~bh+2EejrBx?mo;MYUk~Zo3rQ9P8I0V&nKn&Inv{9_6|<71JFe#ZssE~=-mpnB zj+zbs_3qpS(vuGU&6Bluy!2LUxd#sf&e-)lCKWx^L4b|V!C=08D=?9gCYF&E&O{m_ zXu_Fv-`sZ+f5Xg&TtxQb52N#LhaztT*9-+0Oz)Q9ec--I`qIOem+76FO=ef=Ir!H< z!FC2>PaI*fUMiz6R87ZaB3tA^Fg!7CK z6rG7cjyuGncxmCc@ffn{q?Y9EH<4>1Jd|ZRAIE;H1xD_>%P^laH83E;PDR1lEg#(6 z&z}#r=2a7xghfR&s;kEj{53Q*(&As|Xuit`{_Cu_?Yv+WxA65{aC&HczwIv#*?Cks z9=F1n9^r7RL6haNSow8h-Q2F)kyM?er5grv>3!*e75VI>z1S@}_TZR7Cz6zy!GZ}{ zVeLpWve^;?f@`Xc#oZwTddTk+7m4bk2&5u9I^78xQ;iw|rJ&D52U=NIq{LHm%;uGW!aXhlkTt7 zgNnV-g5~A=S4oN9zJ2?7!a_&q383Z^mh#Q8S3nusZ7;&i;JGe4mbmZ)eE!c68;pPugO;66HLPhVxu9 zrU|dAW70lEo`m|4L3Hrefc(kpj*q#rqdG){ZTKGB!4bkEJsPNCwIdOP@H_Q0tYK+c zSxNu`siENGBLcjXwJpZ7aniDPr?~9M#HLKn*W?TY!;AQF7P$v&`0|V)mNKLdm*u+; z>zE|?((;6UCY(NRiHwx&XIUoQqt`1o96v9)r`SJwc^%o8JOA$dMgFDF8@R>HUM@v2d4FFKJqyh2j4Pk-M4tKg9*%m@pul)Dq zS%-=A>DNRW880TX9TsrmF8=TVNZq**MeoKFdAYWZzG!SWGq==5t^n&i-KVB4g+$XW zeFje@@DF9GIN46;M)6n?`Q~-sU1RyF#ICAy-=YyAy8l2u!ZhLH@MTQX<;6s4cV<4< zy>iYwBe)_S3(}_ zEnOc)p~y)Q&vP7lqEz37YZ%a%tB&U*waj z&D!sza!w=UHi??=!m&J|3y$=aRFN!=;NQM|2nl zVy`@KpEZ7hnzAjxqgT^YD(15|=DUIv^ps8PB46p9>WlGC?k#O0A%HT#a(VvxB; zJgh3nH2NpQ=+HV?jz|hi`JCBG!}DS1DlTwcA|w*Vt59m3MvO6x)O_*FATc1Y87cJ+ z5p*IHPH0cZJIvRsk-v^mifh!H1629YsMPq8PU$_xAnTw z{^lRnGA_C%((&S+N3Vd2P&$&}y<%Nz1c@vG<1sDVJeYP!pj>d4o&GD_nnjk4{=Q#E zSLV64&+BC-#!1Gm-k8oYovdu#k`am9Vfs$;P9=H41xbSGc(QE*1eA7q8dc)#mgn($ z*b#FANNZ8nmO!p zS~H6d!6Yj?*?SDQHLBMvRxrQ{k;Hpa;}Mtze^5su5J)7Fz?2&9xKbF8^XU$lWD!K{$ho@mB3N(UbPQIL zN1;&Dn1TY3$8C|NwUJ$JNo%%XaeN;Jha*CtJ(K%1w7cRtIy?+lUs&o(QF#3Lagp@C zW#cNtA>W?!{4QAlEe^SL=yw;TWnvQ9(t=vvJsD?+qLXD=-t~LQC|0Uz!7eFz^zq2L za`wL$ht)?O)B6TU%@w_CxN<@VrizN{K#(XHnt}=p!<%Kb6G=MLLIz#&0mWaJYU@92 zST`t{&kQ^&v0yKXMmNc^{^wG<|D)>~@wVU~I=hh2rKYAPV7qzw_JCx137oJeBqnAT z5xGJk{g)LEs3-KBXlsWgx!2SE`0)d-YXL^9wxQuDvEgir8P*3np?Z>>@y_gCZC+sw zW@z)#l((Twd@W8Xnt3WWUsL+P7JNJsX*Gh;zbcKsBd?&~alAX40ZuLLpUHrOg99Vr z-T`rx^77?SL7O(#TemJ=iOlNWCh|Y7`}5`ERX|MP6A-*kO^pK5?jzqL(0mtgo4f-@ ztF6Cg0%G3PL?&)nVs*5r9gbg9UAYnl;UWY?q@V7ltZXF%y!H_$ud%T)kh^3*a34G4 z&AkC9XKN%Ka)w!E4>z9Q{nU)n&ogC~xxBJ5q$$%H9du*^5Igx#LqF>Fr=9n!B4%GJ zGs}S-5*(EmaG#b$1E`BRZFFKo@FppOIHJ|MiA;1d7`stFu`uU@Wm1dh34!n6T=<`r zydrCW4L+WKtz3hiKI_5uXcjlgrZ_P0|r z@T+FlT7B#dP5B|=+M})RJAp@cK-^rccIT_w-(L5?xy{KY;~@9C-7DZ>pXTTDpbr)j z5^vj)fY^HQ*RMJW?Hl7|#N7$}?J&k3fB#sW^<#HDZ!@UP99GY#uECS?3<|!~2jGf9 zMaQVXpeId+Wp{ViER~j-dAhI=4w(;Wa;(4W=ELTj`N{xFu(BQeCqXa)G5Kd~1(Spi z0^wHmgQ#+ebnh^)sHpwzOdrZqU#(tl_Ta2lU(IWS)MhebdV5A`FH)V~`7E zuRPWzJbs2EV(R?&_v9}4kLqelaooIl(~Mat5fDlF_ez~cxR*A3ux20#WCyiIe9@=B zG=sQd>>VrlrKHT(Yq$HPc^%xjczJ0MXEe9U_9~o-u#ugeT_?P9O~8>>p$ye)Kn-gG z1d{!Ib~PHEGs1%Kg}If|;QXF*b8~ZRXGl|GUteGU`M68G==9^}we80^sceHD1i21q zgSBR=#zI}e(qyG&6aMh<@a*5sIk$c&gKOiZspX5Jb|llSl6Uk<0<>xtEre*U95+~)gd$H#}iK4D!-WxSRt;RG14 zDwifjVZptmN0PvE*P?$OX4cfuYinyWM>D+Kbto}GiP+S%rwl`9(D~;@5B7UHkXR{lV|l)FoNRUZt3To)D=03%mr#sp@VRZ42gm1%e0U%ddIs0J}_?BU^o zouvrg-iP?Da;c@Qtzv?fk}^0ahYRM|TSIeS5EJKV1erCgw$@Zy74~s|RvK_0S+-tL$ z<%IImjk{j{rpCtfC$Mg+m*0aPHECy7nDQIg`K~@re ztEiS5OooDykx zY&sC({U1Qp_wY6p^h@Fc^%_y+)`elg=xOs;#RBpMItk-_g_4l6HFJ zP-Icmu-c#U@8m4(E_)%?Z)0w5u1-8qz^Klz+*2U2@*Zo(V1(mP_K%%kLjig<(=>E+ z&(-+rhFyKbtzn$r2{{ydF5N9ETU01GF<$wQnMruz!iBzL4i1h)ac@kwr{5N=W>SQ| zwz@hgkRJUOs&C)E{Rez<#^=w&(7P6{)0j|6y0P-nc@pHq)!S_{pvF>l`d z-1USt!6@Z-Ig*xt{VDZcJ=lWz#l@fTCT<=Ff3+|T6=$tK^Vs)FTk^KUjE}Q2Gg+mj zna9V+`+|$Ivx&sS#M~UZmtl5)zq+i=b+Q6p{vo)gdzEe}pb+{9s-Y1F zA=Cb&5~=TH4$+ePlb#RfJE%anFb>q=%wSCCznQpuGY@SZqEPEKt9*1wr?=>%&Gv_X zX62y&VqU&{8B!I>M|1gd$5@Gt-TGv;4m?s(QL(RJO;92CWE#D#A(+%#>bq@!u$bgN zA0@FK)6t=_)PXZ`t5#$V{A;zeX@TB+Mo3850hWaQ#@*x?@alr}uO0%BGo*&Fa=jks z29b0O1Zw4Zd0}BhOM*;A?o&11TZ76hs%~zDjN)D@XJmiivc8>bkEUqhc)Zg{K+yr? z2TFjN^?!d}d?)Ijic(fqb9Bs&AYD6jwyK=48_v<*8c?9{_H*I-X5s2uunqgtsR4WU z#L$0>lf^uhP^eV&mMVCow*@AZUCZ@>U-iJidawp65O7@=7dK{pJd0OiT+r7pb1;7ij}JzfV!=H}+u{aFw&x$VE_0_uj;W#c?H?NM>WENCrE zULLNbWy*7T;F_wYW&#LKp1nK>|8-x|l)MJJP<=My=4lZsHZ~cPp8Zm{UB(11kdw!+ z7Gev{w2($F-#>RQES0aFUV~-sI$5Qy^opK?Ggj5U_dN%0Z_QI$#G#MzUWv6Lc5Vht zTs6cqt+uy2?Gns5Pfzw6aMdkSbA^R4?dK)4=XR%pPLKQc+4%VGUg0T= zXId2udsmX1EtmQN{P%u`blS@M`0OF#Uq<9S^5C^(`zTW3IuT~q9d89<2jJqGhjVpH zyngANIamTSVYZLvXK7x}Q~f*xE6Ao21#O6;n5AAo=-B8YLg7^s5#dJ$`QS%#dIkn4 zm_{W_JR%P#XZiwx5K)Z^3RU+a0NNqm(c7yC^@PG2VDL|5X~QFOMg<8}P{Uymm4iB> zfcJ`CW>%IJ>@VN(+u^ddu_3Ox4}Tnn$4aHmaF+9&?Wm%m9`ZaHSu4zC;5CQ9*Ouv# zN~mGyF+z3Je6jN=pUYS=UQyj1{g>wE52LG_-<^wo0OGqDv?}flw6e3UAbSx1PTlD2 d|36dNQx=@rU$>XvlWP$0QB}N)DwMZ;@-Gd1;p_ka literal 41505 zcmZ_01yB{<7d3hb=@KL*rBO<{OG)XLZlt?QKtL%e>6Vu625IT;mhNtN=lc79Z{B<} z&l!fxm3!_v`|Q2;+H3F2R|Pot;t&`O!Lvj}r2ggsgHf&5>OmE+in>#t#Ir1_yTmQemz+~%S z#!RoX;R_Z)wv*I!gg`J2pkFZgLV2Gckjx0FcOoioDf^4AUK1A&Z70)LOtlqEo+5r& zHE1HwDD&y^?G?;aJ2fZ1nZMVb{Ps-TbVGYAt2pl}_XBJ~yBsNc-P3ri@ zqoYW9hrhklRNqst&Q2s{4*3opS=YVOhwsjOEE`JpkSGGNM4es*MUeVoi6T*SMo|er z2jAc2QNnzKKEX?ZtN?xkX>>=@?-h6uA}0a+;@@j{u`{4A&Ki$`yoWwWl@pf0T+wjj zCwj{jmtR;bZvVy3}SBK zqow9#{=D}vf12FSuK&i!&(v7IGV;h1@p#Awuo7RiU+_Z9)RNDHO6w1^PGBEJL(8vhJ?Vx(vZRIm! zZ-0M>6(`w+yNtAS+57=FF~+|e2w}>i_HB){#EQYZ>{U*`v<$;W-DC|p4E3gkz{kzKpuhTwSh_RX39Xzey)!F{ORqHT^ z?GpdyP^#xIFXunKP0XT z?f80L?U6!{ZWGp`>)qjS`qL#kRJ61>`1leY9u31h;2)&3tLvsYxXZBJu$=K4I}bsLR*{g+WLBO+!GaWQtv7{;Zf&QzN4lXd7+0`YMCG3V`H5rET@XK5QV+G z_#yQ4^!zt}WBzV#V&mYzwYe^POPHI}bp)YXt{%TUb>lZSHr8h+g1WF3XMdy7YJAC_ zin@9XxL$E_1UN(tev4IdVB3Ri;K0Bd?oSU_nq~Sh6ciLoDbE`hBL+>4t_~NQo*wVC z?b@Hc6Bn;A=s-AZxw9GKUPlv;AVzMh-%9H*Gw7&0Y}j+V-O1}48rob9CNtd}NMuZ+ z{`A4wnS(SkxU=(J`oW;+wNd3POX7$9`P#_cU5j68mJ*m!NEGml3teo!k6y$Wh&Z%z zRDyy_cPHsj_lS_n*@3HN-(l!Ge5Vkr15RFdf7-8EXP0?JDxMw1+;R<@Jt`?JjWVt4 z$vCa&+bq8rtLAQSDyP97<5dbSd24))IxQDOENA|!J^AGp@0;DC(vPPTzySicMgA6N z|BEgF6`ib}d&RX#sHl6}2G=9(;lqM=zp{gYVb-{%{9esZSK693GNNERx%BjKe|-D~Vd$ZVVeBuFedUjTSJ|=?< zR$giQ?DcrFHAs{PK=UJRqJmF`Sg_qd&SB#V*JoZY79NK^O$g!PIquG9E6pmcX5R`v z-8%vtaQ_=6q0#74Jgn4RIV{*u8Oi@Ug~t)1QE7^th_guG?onKL{SPu9x;zGM_6G2paZb z{xdY@*88{Pxw1yU1<;c|qEG}Li(Lt?GOz@TDU4g2%qa~cDKz+vjVUep+*vRAK6%r~ zCc(EQ+qOuFiuw<`14D6MEjUJAoq-!={WM1Pc)ukC$6`K0USl=;n{AkXd=0X(=%de~H)i_@WfhYno;$+z71_M$WRdksChHEM8#6tb*^~=QE)^|8Y1$WCvDMRJ0DH z+q$EcyO59&avGW-9>-067J{VxZm(g1E4x4RdB@l5k&ct9>g8TH4!Z6exVqjKsz*Ff zKPYWFMFF5&w`fBOvK~Sun#5VK(EaC=^`5i+%3+6-F8s4WuH`Co_dLB;AAr7PHjBI- zSBJ8al9Jhj6g}ZDCG_>lp()$;w*`d?Tr|#OC$B!lM3J3$ zkC(NrQPI)A-{b3a{_Tq)6!PH*2e+>1I80zQx&}UfecXXbDCor<$$yFzDR7w}@4pYQ zL&DJTRbILe@3gifI!Lv)p?m`A9=ioikGFeG*K46+L>%92TOWP|llj!mPV4#HZ2Zj4 zb(qpLdrm?!h)Cu&vR(iD`SYf`!$z-*N%b%SR)0*vYd;Ax@AHIz;76FEsbG)vi*@}HfPbf=q9TF0moLY?3J-$p z!KVpWfkc2Gyjqri9(A%yAH_&UaG`-a&E(FK*Gckiz}VL?Qh_86%PFUGmWV!eJ@3hF zwUwEf85h!U0D`7x6MjZ)@bCe-Cx_zUwwUln74-zm4JL&j-@(2ZWdP)3{$B#Hf5U(w zYQhPBky%9~I9~!sG<~^+Sqvh5ma`qs{CrlHwu*FR&6&)O=zlD9 zyCCI8p#|{`>o#vwqoVbGGw12+s?LbT3=n6~+@c(J0HaQrASyK+Nb+9XDk-LajWfXe zT`-31KUSMX>%gbFp`lCwIkHj0)WdEG9I0b1jMPE=-|AogTzzK4e53eRRd~+k;<#FI zS?nF6&2j-Xj5L0^aUV9jY<68;U3T!8g-z3mI8*)K=m^pvEYWlR21H`5c6|gf2$?lZ zd{5hUn{~=aDJB75OJR)_8=kcdAiq@9)F&X7Ijnu9^&s;F{=eg&iU*FnS2Pgx4NgD2 z>)`X1MT}8t=sh;J4_xYsdL=wvxSgld7#m6-qcb*+p^23eytr6TNl$exAO!=aj>(J5 zHb>VkOW@p;aR;#S9PscJ+;DIE!vkNEXpitA`p2j;r(w{@@caC<{$u!CIW+P17Ul5P zjzn2cuRSmiFQ$gRNH)C|P)DKrRm{%LPW|eSi7W=NMQX*TJZ7^MCSk-p*hQ0n3i8ta zazA}Y;eKvj*XdX_tyeoxZ9e)+PVmMU77mW*plW=k#k=t;}24r(Ya rk}rl4R{W5EqjT*fBy`mH2RDNrr|V!+ezAlE^lNgZH4l^T)^G$$osAV251D{3LYN*xN-Sm$P?uMPv?h= z$*M(a<)(u~kJmjyhHn!ic3Oi$Q7E%DY;jQA@rM3IBVZ@b-X}zt+qn35Or(68I z6bBTDila*4-Q~RPc%!SW;KR9cNzTS`oZ>(Fu_H5AZC+w!5R&VOyWG zmmoVqpfuN8w;yl;5ho{hP}muOTIZca(P0AMO`voj8Q*IK*{f+w5M=oj_svAe{Yj+n zUqC-Pcbp8XKhC!L3SBL_l7ZBI(gFpaYJMiVC6#&Cp0>thb|-e4pkKMR>8tuxPUlF? z#t1oS=V8AQ*k~_ygnx8Md59ZiZxI(QHoC3@QXvH3lQpKVbEe#Aw!yjRsysIK#ZfEe zt5*d4Ze>^3WRJ&)X>M!C-H~L&fbY$e83bG{0KYx!z!bW6A}qP1)b-`r{23#6N~kU@ z3;|RyrF0C6BK zP@fZyNZaF}>)Cj-nGEPE=CqD0$xAMqzreRP!KEQ&{Q4C}ubd0b(dm(?e69}Ngl29> zfU{4mv_R?NXx4l1)~B;(=?0avlClE#;ru3lUZ9|&x<6b@Yt}nZzg91SSBbXP%5OE! zp2Wj0)ROZ!AC;JGa%Tfnlp++L*%VmB3*5K$TMQ7i`wOJ08;z(MWrtY(u3PI&a|lT= zXr_4ke$f_i-UFH`i5hU9oB2HI1gV4zXlZ`B-?b!r>dF95@pKg0twEB@F8YON+H z@A-Xql$G_$Wq+m}@TKNRY8o1cdF$GfKH79UKw^$>_e$YdOa}-!ZI?c@`aBS@==%)^ zw`TlofeI6#9D6)Ve>w)7^<;keaq1=2ix)4-yzg8{eXb1v_w58r(laoe*07_fN;>ANWA>-t`+Uiq zj;f?3X&u&pjrHiJd5>jVJEr0C6`^x}^2hoV9`O7yLN+J`la!Hx61@e7enybES-fwZ zj@$v6Aqd4|Gz515tr7sDy1V`!Na6^!ZMg{o&Iyi?=G9a7anzjE$+D09wpcTjE1+=W>5maJn00 zh|1Zfuk{$g>j`?k$_%exL-Ads!WbDy2}U4c{Q6k^ht>~AG$bu!6rBuL+|&!dcX_&P z3KkBp_}g-K$(LUHVEM7d-45)@q3lbj>xl<+r_k>%-bRT?FK#*JqFGjY(D^>>>D7bC zt_P(u0h=jWqsze>*e(S>|H4*E<6%Q+j2!P*pjF^8X>YTMu{v&k2*MzdwyENq3Z_ol(x0ey14hsxyFkS2$`GDv7fGdpCo{0g0HvVDrV}a>#H0lPWkNFGpII%M#LWSy0j_! zY*;A0-f@d_&jYwFM$*!8=A%z@#m9#yY6BT0nG{IU$+48`7yYk(87&7abKRdj@ZW4` zDk=Fd+Vrg2VG$ASIu7hOMMp)6C@Ep9?UgfjLDTi&Z$`l=v!=yADfAtZB&5FDM);}n zmR`ev0GpM2xx#=PZXa7Yu{6PqurzpFNs8du%;ir#Pr>lau$#-{qTFKl=qk!Mxty$^ zW1YuLLp!pR>NS*Yd|DF62#L^qVJ0$5kQ0T zu=f!)QDPkd5uf)cTLS}8y)k(mDeA~HjOK0p2B~=HpyCjhLlrt1FG3dVH_31zq|6J> z=i4@u>9kHP<|M6#+RfG5(P|^c)Q2jg+Da$>FzAS~%T#^XxzN zrzNYOM77rlSmrR&_Zd_l-2Lykd^%ic*#7O$Riy^sNS1nI4z?(YkVV*S@JUVW=9>rym6|YssCiq zZ5sv*;Vz1@ZiV&Fu3Uw|wqf_g#nbOww$wI0b0EOt%=@Oueuv~BCIKZAIGx4ijcxM< z9uO$3IidNbSaQ0(Ty`*sV8E*u@ohiaJEG8fIvd1yVJ8C9s<4?IZRUq{tatw-v#H#U znO>M0D&^H&T=^!+maoRkE(ND+k0Oc)KDZ$5@b{HF|EK0Q#Ej`EC?n_U*ZdXpFg=)B z%YTo>HG8#C=!HZG*(}2#v{3eV=a;p|i#y42@Hjdq7zQ+!zkqu|b(X;3U?^(?)Km_n z8?Hqs93X0;5wQ4y+G5Uga4biL5L6dl6xr(nx}byrsbAjCjs@f$eh_8o zX;32RdDI-Q+w1`{LuZ}+IzWa#R^R3?fNWr?)5qGJ9d^4nx?H}qW+ct2!Jf9~o3xVd zZHpk-QM?G@rHfL9(zT}*fFH`;n`ZZjKyeNel+`FM9kDZd7yTL1wHK?Qqq#^$6 zl>m)mwXCcx=q?Dj?Z~0EC%_G>nX=EIaEb$&1zIl$p%MP3j@SMTR4Dhu`mJL({@A#< zlTzP@P{1620CAPouoDR?wxkpO0H-|LOtw8e=^=9jnKC9NWuWY7-L^Vt%*pAd?mr6%lgTq+GeZ zdj}tYh}zwS5w1xZ9C5Mhetff zMyu-zvEDpS%{__`5_ly%%3j6k^e4oUooo!btfCdLRx!obT{0QEXIQY*8x_QJY4JVQ%jl4%1ZTuVD&7}efD@LXOKVc-f!;E&$ z$iEp*22i~Y5rcRI8d&o+)^9Y*{D5Ere(_u^^RYvj($`qE&j6sHsD;WfS5sr z9Uv0haT5z(xdY#E2Q?}532vutENG<$R1j^a(f1O9IiRc`$}NQaadAhjY%bRwOw-1$ z3C!0uYJ1^utsN=Di1-C#N5$Lqe)Jsg#U8XTlkRnj49?zRT4_J`DenZ7LN`=8ys2`) zxk;e`R#;dFZCtnk$)ve2HNzzW8q;Jx*PmBb^lj=^5jF>tC4_~~)^h%Tv=R`|gWjLA z5Mz!ADc;5ZXvKE$4IH5$X86LkG-|g;q=(rQkco5nB||WHxOf0wneMzE7A?2?XjVMw z_Rjk!9^(lV1rpiJDh#_&TJ8?{w3+b1!I?HTHkKTray{S_y+Cvx0I=6LFz^=;xHD4M z#zk$n)i0nQ02L;WL1A+?rDc24OBq>pYyxUbECFrV`niu*YK=_Gv-$op`R9) zQ?^O%c*vd1gW+izC$k7+DZ#ru2j~OV=2;J81Ll7xA#n!q&9Mtt9a3gJ&k1|>0 zK|ZU)ZZZ+|B+=9U6+w*hP(ZITM!J?N!~^}jS!poK$&WKxghxq-Nel!o#B%Ca`-TIn z`|0Y(Cs6%l%BKqgp`6%nqd%SvKu$V!`q>a)B)9~?i}$bG!L@;2)5#6A58%NbiTaJJ z@bn@nO1?%+s#;vnk;Y7dEHEU-Yq*q2!Q_CCj{8%A5rzUkDJDpPhWFPeXk>!Ket@wJ zn6iOXD7e+#-5s5pdLWSJW2fZWbeJFnnphn+wVpztITPtT1Em&M3N3oLrj^}m1+~@J zLHW!q=Pg)O9=>aq3~l;{RlwzVHX$aUc>LU8b(=KKGmEfYe=WGVEKh^7Q=vOfQAlK;YWXacr_kaTV~JRh=bH$6VJM#k z+8;BB7&3qqwO1!~b=&~)=$V)P`1r!MF1@yp&f&-0U@PH6OUPg=>jUavW`9+GnYA#JXF|LC8hCA7)r563oscx&M|Y?uqUTdDpIO8EU!%*Pkj?aabhM~~0v6YT z9ULf-W=@);J=kR_L9;R;fk2x{y=YP0Nr)y!%2X~8OGjo0V^Y3nDtZ6ywO5|U^=AHX z#`KZburqEz9|pz4yk~6BLEUbKQ|yoZY&_tWyf14dXa%yrFDTKnQmBD)O`n~elB8V~ z;mNTUx(cj1k|Z!I$IA@8(oV$~^kWF#l6INpk)p z`9OSH>RCHb+x$Q%zI%L4QvxsTTHtR<5l~>)?wLH%F`g|Lpxb(aE@#2eHd9@LH$Ck< z<_;)H2osaFG9KHK&K^z*#Q2|h#rP??f~a-oKt(H5)*yrMdYRKsrQo+!Oty>Yx!dwt zvsP#%HfWOk$9NCg4n`9j?NA?28FopN!2=t4%0zq<&-O(0ALjhL_eGpME*=xGVa-g( z2c_%wpAUB(v_kjxlKz>YA>scLLOKG{i0rK31JKc6ywYJjNr+sG=+)mn!k-khY^iS) z5YdZxYhAssqWrJb?ebk~&dttY;*8-^>_+5hYR&ilqgDdrtMInK6MYmOFB_d{!#iXK z#GKIobXjvmR*J#BA4@Czi*ON)3@}sX2C{g+hQ?SvG1&k@?;(34&Y6lvAaG1TU$w8Kbb9DtB1@Qo!J3)Bx(7U&WWl5Xk4yYN zm6!z7L5{ikKbRyC=$+Gt6W{(a5Qz0KIk>{>;PRa4sD0;)(#(7zP@9VuR>Ra-T_^az zV@31wr`=3PPz)V5hT)jizI~cwMc>Qdc2qrxnOlhQEg2sf<$i698;~`?Fxo#1w{R8uMvn!MM3ns?>9c&$x_Drwr~ar$;op zP*4eKm<`P+DIs13wUta(*RfV~QbHM(I5nSz>)*ijU!Pq$3pJy(vV=DDZd%(1SH<&Y zO<0WVUwoQk`0;7v|)P@P&LMo#K}su2;%5ocD$!14Fp==go+B{yw3Znee4 z^r;Ek8vnlulhN7OL$&!YjEZ#v$HQ~QUE|sK$BL``4(!`V8jDCBOvQHA+0=`lWJ_AO9TxZ)ohsEXJKOsjU-wubX>>nUR@bt23SqE8E z!aPc{)UgLjlh?p{A(w0R0Y;PrAM{zu=`nqHGYr}W85Pq-kNPELgKoC=I-lL?&Y4rs zG5zwi`e9=oS6}G(ld&XQ0$f{GUj7W`#$9`E($j;U^MMQVbvf45#oggGr40WgLGcQMvH%uz(=}>|$T^;Eg+I)7_3~CnIpi>P z`;U)NLZm?;G3dp$VID5S1Xz<{XRvo;XMfaI$9F!Lgu04ZL&+G*IS~@l&kStAxh#yq zkQ?Un7I^mTqnpY1`eX<&=%_W$_|TUTW0V+9=7XVyK=ao_#B_^0i}hzy9^nkN-IDVd zO204vY=<2B9<~jXfY|d>w^+Wd7l4OxPq` zykY~Ahxqg-s}R*|*fs9+XfAB5jT~%jt~mmWgr8B&?i+e=wknz)yfGKTgcBVsO_N}< zwC4}3WVopvgUfSL^EyZOg;q$rm{W)Kj(H&1Bf7Dl4QVI72a{Bz4TUIn__jueyVr9K zWfm{(nU$IF10M$V+~Z+cu4vI~5$)6q9DfJhSn(W|0N05wda)1}EHoX)K-gEVsG10! zvH2Ka^l~TIqL+cop-w|!f#?BQ4>w&d_ca1Z_^-F&=O0wy+S>$|L~RyR;pr|8JV<=F z)i2fxhKaH(e)YRJ57a?#hIz6}q2h~nysc5Iq!FunpzrW~(`zr%VaBU`!q_sLHvONp zK$Z}cp_+&leH>O$w!gL?M1rAEs3Kh$ig=k0eBuxwhYJ34Bg|9xYu8cK>jEqG#v*KQ z(nwa^&y1x0(Q}TmB+{_4w;p;~kL!)8-!H07&5K!#UvHkXCjV`XHNl@*0~%{efFO(IeY30)DV<7*W4etRqX+UU_1x zDakeGYNAd*A$^ykTHUmk+43mTiA^xN9lqSGy!U+>rB054zZmb{?(ID1~_Dv|t z2=JIf?cTf5s{{@V1`H8R@t!bQfHTu7$|cfj36#QYWv5s_%`6f)@N31r{eQSUqyI{T zkLe$~q|Xjfb;sg`AGnMl^=^!TY#`Z0Mxe$>Cp?>Z(i;&7mS;(5(^ssdBUKL$Q-mUy zN`+WlP3=3lW9ftaKHSx19NSuv3GU@H9cq1)!{;Uk4`3Q6?Y)*G_mN)Wy{8s;XF6s# zc|JeVv)5koRb3)CFm&_t6zea5Pj^kk7A@c?6PP1RZM4ZFvWL|rK0njjKGRYi%Mvu> zgvW$fIt8QEXG{4h$=iIwZA8(&U(Q8JffxP#Ww-6|$-jh5a8zH7tZT1bd7L!>xcI1Z z?7oV%vPD3+x>~_(jLdIea@H3iJRMi}NhlYt-GaYT5$D_`{gj3`j67nnEU5CvI(xJ} z>ncxhNzO9S-A-N^Yw^b(#cM++6J?7E6l~3*1ZOq{artO+)ET!@*QjZvS@pN$FK7aA4n zM7D=kFGcMpLL!q}yO|z`uWdVRB@l2d9iudJPg<>ok7Ptp{h}FHX7)WR2C|^I7C4_> z=_NsfI%Q?#?(@QCvA0C@y0E4=IZ2?t%AoJtpASg8*+g)c`bvl!NK+8FRx;gQqawqb zJB#qwLGKK|@kzwBEI*MUz4W;@4$$;A!Yx%-wnw;e0HNepC94VTxxER-K|=8Via8~P z_KYOlQ7oQ~s)}H3_^f$k9kv-^pVH%la$9#V+Mg(PIAuh<=O*Jk8igl2F68Ad-eqnA zu~ugS%Rk5~p-O1e|5}~Z?R^HCCg0Nv9v^}eFf*rZ+srSTXA;prH&fK<-J#Xs06&xb z++6nT%gJ4o3FO{8Ts)iy!Ei{a=gRl5XNxPIN%miG_;;9Fm)l^6&lZmq(MJ-9E242k zD^xAxZuvP@O8m;6D-{qUD-gZ?;{O1jdm$tlsA`rjX0$4oF^ua6gQ70B!?bMq>qMbk z-c%7>N3hH=ofV6tLjsD{;WzJeF$#PUVJsWWH$q6LE^VjH7z>-+ac{{%?tAUT^7(V- z0)G~)U%dLKI!0tH#|B=Xzi+;cW?_Fak%$D1cyrLodPWN&G7J70W87yPaKrWUAPAZX z9tPTUmWdK>RoQU_!(LfiDmI4Kvc*8U$Q-$6g6$ss0s=LiE?-!Bm7{JuQfCzWso3!J zEL9)P&Uo9$=p_vpCTgy~0!0z;7eLc}Ws zrdR~;TX*O8NwhLzeS@wpud@0>w85=k4Mm$w3uAxJ&f%e{l?a_8px&U(=l2`l#!&W_ z8L5LeDBrItlUNIe@$}}iCH@(ePjWuC3-tKeE-r8vE>?MSTUz{)&I% zA^WM}?H7)to8%$0okuF+Pv1E3{1NRs+8&m)W54iyZc#519m$`r9%z}}Iiy`SAO!=olg`Zh&!m`4u$Oy-kEqa9^G3-x>k1LiMQNK=DaN3mrJ zY15Aw(Mx^FrWbzY$XH~*?)sD!*~yn|z_`Ub%jOiOf-aapU`VwW3_gI_B;j#(!MlC7 z^mVQ!H_D{k8!s>vbep2Aq0tKzJm?76n>S%Q<9W(zF7Fr|%?xDxz8l*RxcS)?CB47# zLL9kbaOOXf$mibn4ClaO!0dYi8XHcEgF3n=X8)srgM64K{cXD51M2h=Ev#TW6D+B!t~6{W?;tg9t=j>o~KMqs6eN`$jH2o zKM$XP8N71$GgGL_)pEUt>T`c0Vbgpu^&_%Hz#IYTrCgcR))da)!yFTC(?ScAr4F=LL0Q8 z1B=!M1hoOEZVzT5!DzCmOz^}dEDlAT&@`>t@oj_gTVf(qmu>AOGlmyG#SZ01wiqUb zG9x(T1~Xz0RZK#Gqc{;7#k>ls)#`KMeqib}&(}8ug`Wz3feY;qf)REX{B|?G33u0? zmOLWZkFUIKR~RTbW;=My(%yNfLF#kl3`Hj%JZ=Z1QaSrXpy~@ND=Qi)e*#bu6ciLz z1Zu!s+wb4Mo7$1vz+@RK0opI^`mv*j|09Q)t0%$y7ROSt#oNeHB`Rq%4k18wyWihN zhA4;3jVddTwycBfXRjTG5YD3<1cS~6$E6WOzXS_rtJGw;nTyAcw~1oJ)LGt|1J*uz zjLc9;VT{$?rlAx~S%2NB`;$sS+D=Kn2$8O!pa6`Z@V)t16#^ZW&yk6D0K=#2E{!m~ zLqjw)G~HWCV4m~Ut5@L1OV44T9Rs1JnGDRr7YpoXqwd3rc-ITwkSlUdW^ctD5HF3! z%xf@7wRaa_y0!$2N*Wd0IH9wJp1}mjR1QicYA{e}8`84*^s9_6ealQMqmCfn#v9VRY z-wjzrXCz_!uN>yh@#XIgH-Wk0(MbKM4d1-T?Pz&w8}Y=@%O-4pkz14c1r1)=F1r>V z(1x3z7?E2k2KGPAUfk*d!~MiIwq_7m{o;g952q>+NcX-IzwN|MqS@&5F^=1haj+gIV`zCWI~18d({ISj5Tmo>hQi ze3Z)0IqF}jDdlKc%rx>z#U=SvI2~6+! zgK4nV9Qj3e_^aTICGDv#tkSu=is{UgDTLHSvC^O>6NNHZX;(4H(^boX=L!uv2XT=C zmFwM1AmMaHsNIr6$usVmAeA=KCd+aM2d>3>;6NIC^7$GM9(3QYgk9h6z2FEvjnw0i zhP@RYAlyyymVnn!%6(fSQzL95$A_r_KDKjWF1K@6MA<^I^l?q-sxz@*sS4rGzLcYs zpTjQ;GsWEVA!Gf(h-~Tg^gZ@%M-F|z->M1~9alt-1a*HVYu0H@GoeKylf-Lp+o{5O zwo4)7d1i$1=X|o33=q|09NEWx&Umk!h`3QSgKQQLh6EkH(9>b(@AAwc0y3$UN6kUg zvmOP%t>c2{Y=42fj_9BHiL@rh816#eB6unTi>^wAb|c#nF!T$s>Lv8Zui{{1{Qh@h z3a<)~6T`wr3+z4tE}46KYA#N9TfI6&qRir^tx$#GBp-~X1^8q?RB@vThC%1UnrEkF zGZduZyH^U^q(pIOcs=>lzb_Tqr@rSlF_dL~h;sNc&*QwQ_BqC6r^o`&Zc3Ohm-Z0y zK6*}LhL`PKggP)+xjmm$_-x;OdD};KUTQ>heq5yI2iQ|SpA5^cX%HTd$IoV@p z5SOkzV$FmiD{B5cA1k;tZ%WYR3pHdZ`Z<$T-7-yJozEZVyi%|eq6m#cp&4Z3{M)~8GG-ID^0(5Yr z3KcNhmRuhOvd;Za(dgzEhv0ykJo>8SEuC(jM-d@x{^;siszuT9!6=zQttQ3lebBVK zqrCCuUkyMhiTq>Qf3zi(y`iDqadQe6ddN6&zQC>HNJbGojla`1VhLzR`C{3wGs(IR zR<(DE7+e`pY@YPH;%d)S3fEAk;Ckl`<6WZCI=**yxIjq%Z<7|q?O>Cm3d$nVUg#N> zZ@!>xSwY6XJ-P93PltpUiK%6bJ|9Zp`1gX|* zaZ61Sh1Qt$FKh#MfvK6gpFSc!izAZy@xkZiiNJYs?l;#db!8X=>Z`xped;A~bsRX3 zzQ`quUM_WE_64*dH}2{Xthg(fL!$VjFH;&E&UE4MfTuVX3?TI2m30T?Dk>nCJ{9`3 zF2B6v%*|K|E(*TWc9k@h|M(f6u9yml_rH|5E&^hBZMSqJBVPN%D>L2I`0jZsu=!Do z%Th>FiU8Orb|U#URm4kU$_FVenWA(26jpYy=5@#X-6^%uT~$x^nK?|f=NQW0qG{=* z-EoC4aq*5N2;`aD9UWghcM~WlUKpMPaS~?&S;e$yrnJy!9vi}~0sFL+kFiL0g@KvDd^;Y438~bbSO(aOiAK$Ecq9K66UDtM%ky}6p+hdyFYt^9$&Cv|<;d2IG z5n=ryZh|`5bJ_MEk3DGMO9OnSx%Q>Cm2(|XJ0v7~*3`&hq+b()dZKA@*X*-|z0qI2 zuIWN~3?Gz9jAfh;nHG(JyVHMW4#XlUaKev0fJshzHk*W*K4DYSBy?z96%s>k<<_ys zz(!&GeYc(_A{kh%(|ja>&4gfu8TCESr%pFj_bDA@L_r%j|6=^u!|&MF;64=>eD8fXx>IT(>>rYn@79+-Z;z|m z4^i?|k{cswtk1c(EyjaQzHxTr7ZS4LBwO%8VNToI3^>C$x#zJsI}!4k?5$17uV}m= znz_^McnN>$Ux7w9JK6$=4<^-0<}yv?2Uar(PqtZ(@Ht+-Wn7cF{dlIbh~qm=7%)*0 zIgnOGgsd>)kLi>v>A4!Wp z^PbzlCXTqaeuZADw=f!YaGV>T;9sUL5Z+OArf)4yu6HD&UuNouT5rL)+G1x^XF!YaS#O9hFU>S$@nKWiMPf9zfxE z>7X?s@$RGc$kuMqv?_i9SDcHGROMP7z>Od5aDkDqVi0r)(QA4^19_aJaD zO8nPkCA7^{yve>zi>ZnPqv?RQE}Bkomh(!XLO)-A5-p+(hoS8I50Sc%X69#(8XbEn zJV4)_%6B1iaRu6)R^^4#{1C(Bn{SHaH!hLl9`?*3Lh7k8C%L!crNhLEjie1NtE@n+ zDbDj^jnm`rR#& z*X)Q7y%sN7RM@rPTM()1T_ngw4UN%rbIR2@J6C)w#TUCHV)jp+CJ|d_V~!d=SPK`H z=4u-O)Y6PcA)FL2(w@j<$T01l3E%3h!#-BHd(?}o-cwr)jwfbYWE1!O(9oK+bN!c+ z8u-)+Uz7y-VX-7YRAYR!PFE7X1#@`uPm9RdDS_ zX+W*aJY|miiO;dlJyy=@`%t@5xGSet<`Ktk$^%(}F2)5RVDp7ucm75;0c2BNb zfQO@ombSGlo>#q$nAq0p_4G}(AgpCNzThN;#mUTlarsocI%tKgU@y#p0}$N) zKBZov>G_-T48jp-w>7gkg1h!Rq z(1!vM!gP1)!|vKnowEF90#63ZYueXA-Q!N^x)D znh4X6P?}#UM47+a0IBFIYp*aTq-Y{}<+h9InnR+)G=FWW&iBmZ#BE9q&DxEgNE4T4 z3^i-sb3z~jiVOesNo9U??3}sPbo4>>8W$FXU#tX0jyGrUfO{QI!6vZcwiomM6EEaRq5K$&=#y&%Rd_WJ#rPqIK&qg_gs8RDlAZ{c+YqR6%ct` ztEIz=Ym2WB(4F7UeygXxRbHa6`~EO_BD+LG(>eFo-u@oA!22D-FX*OnyW{`Vncv)T z>Pm@&VtG681WrCPdF54ha;qsDK37S$(PS1|JH$M{zT$ z2C5|2rL2`H4q3e3m(8o<+&_|EYqbcIsjB7Yl7N-yYO79GI=7loNPbHMG=@F8;7>;? zL<*IE$j%+EE;P{Z!|T;sI$mpgN4H412uzceQ%Isvh48`UsAg?T%{*4kG7M><1H|Cy zt#;SqdH@XQm;LLVqGgLT;Qcd{qGR4Y5Yhn7!QKg*(72{%;h2ujYUZD`ADT~|!H};P zgA*WBCP~q2XI~yeDOXySb75IDkjs( z@!C%C^@;Vz&1wxPP~l^ZRR;Dw@~b zZwZ&VTn(5#+2^9aA<2X)-<6tR7%J!XFMvPSt`sPKE%&IdJ>BE-)Hlfu>RMTgw14s+ zF~H(j+IpJ}qh$E4-tBvG>}obE(T2RKXLPB{YZ=fizPIebGP}|_{938?QVyLc49n-0 ze%sIZ6T5?&^;*t0n=?(USolMSnJbYF+PA?0jTM{*YPaX$9kZofMR#l_dEu*zulr1P z!`F%xpR#Lt$Ur-$k$P|3nM2E32*#@XKwy`YIU^f!gal;l|CQmiKVEArG`7G#Sgz=+N|_lTqlK+%a$4^c##l54GVH754HvN>=RM z+r)ZYpQN)F-Yvm@guHn8sHMH#Yq_pUDt*#@Nm2<;;1Z|Fpgv5L_c17=0XM#pUHsX> zW^@_#$QFuiy(ifaaap(U4Dtb==_;6RH+#;h^zdC}!?A~+SMf71Ax1ctE0yq3=p;|$ z)2!WmxhcF%7?6n)#~%T44;kuJ&Nhu-lsiJ}O?q>^Tr(Hsd*a)pA0D(6e_cP7b9??S zg$f;p?>jtQ>X%sz16omMK?)i!%%2l3e7ZSNFWqx)VH{1{DTL-D7@t?~{VJk1P(z}~ z;AC~l`!fl*K;ceGuUb83PjE4Nx>d#*lDw+*2$pAb4q@APi9RsF)sdFZ>=65%LIF=Fa zRZq)~s}^g9srETh2toF)>Q@X(U;%8bd>=ZCKP=mm{2mQJ13lslufEm9;)g8YmR*6e za*BEYujB_xB_LwO<~r6GU!}vGxmOc6EG~`J2Ik)-6SJ(~9n~1tBK{x?e8#7LlLosW z0;iJ7Fq%mvykjMbP)HW`O)M-T;B`63c-`G{;ZWbB+`*1eG^4JpEMBo?>j?^& znOCyU=Vav+!L5c*lb@z@vOudcvG<;c$MQ{Mh(`Xungp`1a2~B`tSkSXJF_Dz@V*Q{ zekBgaJE3yiGwvihz?*!^F38OdZ#bmV(S%`O>(W0>zqx(NwxUY^O&JoY9`aB#vfI(N(GISQhsBE&n~`< zP$<}c&lj%CtC1gO>*qjOw}lPBm97yvj1HPk>S$9|y%XEDaMK1H<#mr5-FyyFdDc?L z;Ef`Xv9+;k{Kx&dgj+x9qjVj7t{0lTpuH?sR=t|C1)n6S6Od?n{^CF!__`!pKK6C4 za6Z%8+;bKxr5?qclYu13ZO=Gf+u>vd<Y`8zv2KLmADDg=xR3PPg1xX zF}bpqS@)!D`?#hIBRL!hn$tn4<1a{h9k``H3nvesJOZGhnMvrgJ4riJoD6rj`wzHX zzID&05Vg^2bXOQIm-Bke717H<3&`2N5d)B|xzrM|b_*aa7wsl0D?O8+xSX$N+Z6Li zJ|n-mTJpE9_gR|1iP74%ilGS2j)8!WQIo;^ptIX_kcQRf)R2%^k4pdGcDtN4#8ZX! z=ZdRoiU@UxpH5?(MIHRjl7^THft4B9&&|zzj*m4;l&zxKt&EY$*^h{$d15nmN7SsJ z2OFI~gj{UXeua`bGgFi=$E+5)oyzO72|DRTC+YjFSndofpLHIwP0@FQC(Dulu<;t6 z1It`mFsKgV4CaH`i{!JF)Va=?o;BSzZ2iEWFTI&wCPP5Cn<%{Xb7*amcxjdqNJ_J_ z!G%oSafzMq?Z3)*gLew_*iqJO)hvr6!oRovTCIj@-wo#U&AFujKyaAr2B$)-VA~6c z#PHQE1oIh8Xy5~z-!FjtT_%2~ZOY!3GCpzCCH}EqX~*Gg@yC7*akDw#a;d4KS+^qF zO!);XK~XI1(s^~#MoV)Vl1Gc3*Zn_43(;ssxrU0YX7!s z8Cchde=koG>KRnO@o;_^i1~$`F(8NnKTXUDlzOtB$pxcM+J+FX;!9mXe=K z{nRLHl(UKwXRD+GxqBQx{y3OlNRRhW$m0x;vGw zLzjRwNOw1qf`oKP9a^MYq)U+Q?(XJY-1qZ*-#gy_WDGg%v)9^tUF({2{+2^=enu+V zXP(tu*_10e{jO=Z2oAh<|D}>!RT(IwzrXS@pC$Sv%#$D5rzVFU-~nO!iw;Hb^`CVW zq{S>RKY)2WRx*R$Js9{nTEKogvUYFbBe6=~4b!&D1H&7%%BgP@6hRMm0k>Q3N~X7OO+oH1I5ZUJ_3LiXj$~j;cw|%f+2v73n&;(CAw@S< zP+hIOmW8aSfm+>2>^gkaW=&TVYxPE}Isc&t^#96=p)hEg0Stq>XQmKZ?@FnmOu?5= zf(0-f=UInOxBWH~DO@)0)paiiT-PqAR$=m+o6~`5`vjnG7LHCp-ZAwVYXFcP(TPl& zI3Q8sv6T@9%-kY}Kx&!>(YYm`D^f%66GV~6Yihu^*sE&$l1b%ldT_Zy^1Jl-uRC6N z^Do&o(ZQn*qkwqkxI2kXYYelCPQ7~B2YX-x)%@Y5p1;3qT=@q^`5;t;S*4>7@>PVD z+k)e~h3M^9j0!i+;)0TwCKMD!Gjri!fbOgv{GVlqvp={>_B;8>+`I*Q{O_8N;eh{^ z70?sdfC#Xj;kHQ0!SPSv-*bRqY;5d$OXR7q-eD~T1dE^P62R+C3Ftt;tJ=t=7A~7o z#sC`|Ie^qzk3ec3-JQpj_xDb(Y3HB4Okw3re|RS2R0_yq3THWVbaf_1w<^S z(mm-R3!rgP$tT{kU6Mn`eSW`sn$jc_OrJuIQuqSYJ6mVE*iajuL;AARpyz0nt1EW` zozkVSS=}5+FOUo*15@qI=|*r!hyyUw0`d?Tcch>IaHnruK7$Yg4GoPjxsb-T5y~zy z9`Yz>BC9p~_S@N#uNp29w>d6+Mn`SL1|^oe$aSVAI!$<>xBLf^>$roik(huCyjYPt zjLq)6hmha!vLD-RjZlvLTFe4_6Iyzr|3?X`BcAdRHt%PR3hfpr7}e0>673t-xa%@8 zF#(R7=;#Zwf&bBU+(8fx`1lu{VmJYqXWzByikgkBiYsiPhCm)$g?N7A8yf|juZXk{ z|5hQ4?Cqd>mZ?wPq9sY6MUX$mg@nO@MHWyI{+x`tKnUlw(?nG7{&vc7LFb7IL+rN3 zD#jwj6}T z4k8UlTi_N63A{($EkUctD+`Mgn|EOMZombKoziE%0J_y-RS)_mgOJe?k3D#I?X_`q z*$&2V0o?--(heUkwTWfyHjUyqa!dm_4S>QMMg$a^YBbSWAs4&h#x3j8@;Kvb9_bVw9?MEeWZ{-b|J0J>b2rG9MhHQ4h;7fbAEsrWUe%xV4j znAm0EU(SMAX@sUdVQnHRe5a>utA@JXR{CKmvx~lcd;_FovaMVBNPGn`#o{>ba z@bQ5|p6G}VWGuVaPFU^c>nBMRugoHpMQkPzmy1_^EgsM1K)){siG(RH)LrWTS-fih zK6iZUPf=4{Xq5jHtOIsQ)WG+fay)MQtnoJq>-CIJX|k>qcRe!I?()AX59pV`c6Ybj ztQg=tW#qh_JN^Fhf^s@cVt?i_t8$eB;R^AtlG{@%m-$&v{{Q78<%lW(J23%CZHv_I zQtfJYkP*2Ck?)y$2Wo&25&{G;J;y#87<5wpZ$NjpYuI=__U|9ykr2AgJ0OFI6Bqa& zWjC{pZIvHud^|B>kN;Xix%*?pqy0=X;V*I9)exHu&J2mWCgsZdUY91t^oWPMegzEz z!lQDUffZfNH*+iJh8nHj6*|MU7pE+m??l||H~S26GdqkCkQNW!c0yAfMKv3|q@DKK zC`Qe6NU}=}T2e>zWH>;E2L@oMo>iu2+73)Tu(3Zo>>B_hh;QSY8a)#eH8V3t$%Xyt zCPmFd4VvfBYvfF7r&V;a z<{RyR%1<8Ui`5x`1!=fTcsjI|In48J(@8$?se;x3Gn1_mn5tmlSBtiM><5Z}oX7e% zXF>dN*#8Q6osPdF0(#gVo&IaPb`TOk3rR50h=#E{|-Q;|2a+_Y@x=?$Yj`x^<}b{xeHi{ zHU+PHDt6O*)-vhFwP1q|kIB>B^%!N|t-e83Yy>8(MtEyZ$*54M_wjff0oqk26fWAM z4I%EkeKP+$CJYi^&l3xz8W*Mi+`*!mPaE(qy_#J@dr7WVg2z2wM0WaXf#F=~)`qB6 z36wTJp3>Awf|q^c3FbmTy{sP`U8ImAgwh^O{ZT&sdB3t!BQa`XRdRRejwm>RQNe>) zLS=u$WU3j9ovXmvRO;Q!f@g$4R_=Du%|D$|_|gixIy$`t`CQd)m053gOuu zjEa-(j4#b3nVHK^H1+KxXZt_%y%Y@o$ScdY$MeurWk#&ukFoblos)9R7wd&3^RK}J zC^f{$B*KT2XA(40o*^W4JTL3gon>rD*R75YZ+DT!QMk8zl@9dbaaCt+@bPqFA9llj zu3~TV!&5C|nM|mT%p2OQU$shPxGnoBCxH_DGi+V7a$_|qGE49_L+V>5zYA8?JnrK5 zAKcf++sEz3km1Mk$^$*ZOr)14lvd48bVdCTKDw_a_n!q`>q{roySz&+F8^)Q<$EDv z6}@qlw=$s5uY1O|X+t!ybeE2F)7Bo7{PCOvV_+E>A*drK$+NTys#6Bq?Nn`_Hts?` z4(h{60c~R1>u`?P2$CeNEQ)cq`uOFwQBXkL4VJJV%Y?~WyZBVL*ZQd-_{fulf+B(n zjqF(aZ5nJoJjrIoZ+JNNo@22X+M9F`7?gF_7RGE~J2GI1`n-}GqKtBI(t~-VJG6*I zc34wA0;}{+GoY7zZ85u!4=cVLS?=3Yn#O)u+?xq(WoHj?$7C))V$YK^V#2TrZrb;( zh52C?R8HCMCiol`rzcQbA|=}IO(W3g&RPBy4<{>W)H;}D(`v3s-A!_3wB}T-Ir^w` zEnX8$>gP*+WnU!u)LXUtB$W)>*lwnr66<|dH{B4pc6}2UB&qFnO)J5l7xE~?`L1XC z?p=Q3rK1H_CF>PM%&velXWPCeeDBrmTEEcem1fjMiIG+nTDX?^$B45dTj0UXaB5+B zP+d3X0rCw`AMB_XAj;$@hY@M(E~24QB1J= z9sb=@L_RA!;cadDcHTFh|9s2vcb`(dl+VvC=AuD6_m+ZULn4|vh?ESNq6&$8$|>dX zC(%}#u`*#^ZBz7amgzW+vBXruVB7h3kLu~lUNf+#xc_a+{jXDO{UmVp-x;(X{(7b> ztHHKs6mFwOj59b}-Fw{eZRb#{_pFh=f!vhCBc9Nld%-!g0-BV8J-JRj?XcRQZXq2CR0hoXA z#huB^ReSXdT#v??3NHPuKl;Q-hxc{;tBTDdlxKC-n~k27EHw9qMja zgRuwGj7u_#RSj8EkHMQ%V zFLtaf&Fy|$|4Dm6v7?jaunZfH)jbLauY{p1MWWK!}1?*m!rv$&- z(NUWf@bj!4bmJP^qADj=#Lt=TRbl7Skfi0f=jpJQXAn9}w(lQt>XAh|QS&%iZu4OC zqkBGdKM6VW@K#fLze2dQ>gkBQ1TK6foaq--(m@=^f?P23oM?)BWop`aY+etNR=*Wh z5$9_khP-016oT4)m#2|J+G_WXL$LL=K5@S)RsT>18?YFbrJqw(CQ3b~*OkC__BZM^ zfw$(rCRez-_d^L}qHy0bY40T=b3ba)Tg8IRX?KECTzrQ{-OE-VJ6k+4z4xEUq+e*| z=GfzXJFuou1I+;4&&pjZ+JWG>8Dn{fr zzPh?dGv5HCR!xM-^WSp76wM(WJ`1abiWUt0u<ztf9orR~(D2Fc1VbHZ-cwF4M%wLoR6lW2p9LGq{9?sqo*g})UI%F9_-Uagx z>LYrH6zd0Fq~4R#2goEr3FDe@UfUZlyM_zn8V?`)kuSh+Ah!#{iO0{Gtmh_x&;s2H zMU8_#CM?g$>WoQZu+<@LHSdCX%skVD$&~ZXw9kY0-)B!bacQCGA}aGG+<5#EKMgXu zY2^}Pp0*5kZ;s;Sqmd79HS&Jxm_!Lh&QUKax3nTXww`!F%mSHT=PG`6ycCMMpE~U0 zRJf?D?7AED9V9E{5Y#E0&p*){uCXcEmxwA3FZ66f-`*a7t$zDKpm`p5Tyuf?2>)p= zAp~0}jOXZ0N17Ylv2kPftW7kw8pgZsrwAB@unso~QEL5gYsPWR>>@Rvq;Sa*pw26q zqp678UnF@BN?$L~*Oc@Gecj_AE1bn`Z@9#hkG@8N`ET%JaQ4nZ8t(@$xA^F7j5`e& ztM>1Or;1S;S=q)nVnEZmy)yJ{lg;JRyqG~HUU?F3l!3Hj60>A{@dCxypORqJr zpGdR2+)TE&&T6M{sU~`TpT>?0&jHD5O+>EsPeowQ&7Kw;^nHrnYJ zI&>`0qy$P)yyvTkBkoL$hYU$}N?4#55%voXB~_ zihgDh^ZAXAq8Y)+w(JT`|EiNeVK0*^U88H_IBr)k_f+QTj*&X!PNSvyeK($rPto-N z<#~kVJFJS4vuDMu*zdhthVSsb2wvx#iN98VOhVf;x`?!#TWXG|!ALn^Ob|ITPdug# z-Zl_q0n3q@^6tgVs0-MgM7Ll@8w4Z@5}(m=4#7wqT6)V>9ftP9LosA}{arm_bAd@- ziu2Vt*6$vF4qQPl0t|Z{s%Eb$#*ntA>Gn><*c@w(nlkq%KjOAzW>_m(>&W`VnmIX8 zO0wyP-2-SgRN)JkCss=xVe549%j})z@jZv%aQ)dw6Gr5d*AI-Cfn{~6U5N$)a3I?! zl8W?|PRt%heg90D+R3qJa2fG@A}ERZOgx z7-aU<8`v9u(b@f8ZAYJ0stHRreVeXxdLqLC)&9O3y^EjvW(aMx2124LS0|k|!flk* zoUko4PjZWt@_RgK)sy2bsDin4i5=oSIjAL>QI#dv;Jk`&=^-A_1dB3Vna=e$8CG@O zQDy(^Q;>jCW8*bE_pcDxU`ngv+EnAsLbm&%r1jN)rZ=!yFEIaj38e4w&tLiIFGeJo z=aGy5<4klj#{7Kmi+4v+-}gg?)3~%o*NQ$jXi+n? zIFDUgq@eRxoTrwYD&Fdq#TyW>4T4~mWUS_Agz?%bZIq`< zAX6fgCordm@(3xcNTxl-x>oGEQ<0Pu#|dBOt1XY$+dh$`>lDqprk@;jADOd)JTJW- zJg9v-UjU{^LO)5bzO0=Tbv30wED!lb8+lsJ7v_$sVjhlYhr|hPIC)q(Nn&&@XON~0 z-{c4>GUY~xW_U8Ep*|kLWw1sLhkA3we!EvVcq4p`y8bYB{Qws@(Nxs@>1VYJP!b_< z4RYYUAn(4`@yF2fA)})f{s*5beMD>N$(@IlRY_MSN=}fjPkpWzz#9FMw->1){ri2b z`hu73m4UEQPxg-Yx0gM4x8xH6r0<}^KccH7p;Sr@B2d|QunKkP=lik@TuIpDnBa1P z7c!^!9>D{x4XUP$ubealZshf1*R+9x4PN4sbAdW>2_C3Hz_M@*nKZ_J>=|8%8vi+lq3rII0qVW4$fqCsWZ+t7fDq-L`K6q zp0@6}k9BP~6z|>$%Y^j&w)G-kT|^Cd6iAmiNHR{_H6y{ER(vPv{OS2`aimVD#?rts za`<2_a3it2pLFoxw3|Ee`uQsW>T`REpQ;#&v5TBI!}#8kG3BNBFJ}EPV3|EH*|jmK zhk1zwVWfEe!HNC%R=OV*WMKC6o|3dbHq6%#uOJyns<*~QlrD!dGA zs7W--TJT_8n$XLc%;gb+Eg$PXBE&{W(&8G@tFZB%EqDu*)=4^E*j`uO?
k;DSg! z=qM$f)bT_wsV_com9^9anm%T(4tK;MeTEwoh>OfWoM^3A#zo&PCg?L@Ae1t7Si zy;a!bb@~RO+Xmp#?-_Yra;jq0PmDnJFSOHz8Zao$4w?hX4%whz)+Y;zD>z?3L%c*S zY@@%C)(i1F;oEgA87nTBfPZ}5AfwdjhvWw0nkyc}WOV+cjA2Z93<=GXH8Bbgx^cM5 zv9wStDmc-}j_3tpK9y0^ZEO0z3j3tt|f z-lBu<44>Y`d`FDeS3Un{NP9$Wr>Z>%bc|PYX`A!d zE;!)be5{Rj&5@QEOmyMgp?yNrl40wfj&j6U#=+PZ^(Esm4P&I(^KD`#Z9RTt*E{~9 z%`bN=k-9OEcXc4HSiRs7@d`~oA(!^>6DRQMfJ6pLdP z!o#8};Klta)ZXp!4EUufrOtK=KOgheb$oL$A~zmXST7yN1v}o+xKA>1+g}B_;_j+v z+3?57(P^_fKbMBp@j$+aL=`e1j;h^yd}Ng z(P8jJSqvua7M!eG=ofNly%hN@`JacseI&pb+B>2Y2$YQd;Wd6(9|*Ck8-7W%^HIW4t{+`?-ev+Taw%m z$?+5mvS=cwZXXe=H`9#LbRDjjis8`*MJht;+ljKAR`)eF4Fw8jT$D|pN7q>&krt5& zvcjoWIkNJAS$`vk0c1w)s)oTDk!IWFa34%SC1CM)lB&6;xzmSzT85sT~X?-Hx2KX62w@1 zB6fsAtKe}`g`D8xGF7JcNyPw$aj3NdyQlwP6nHD%)Qx|T57&X(^j)2+?C`&OMDu9# zr-6!{T2&5lhoV(pGMk_kjFiquQeg zquaT3Cr(nrjj9ZIvVhtTr%{p!s6x-!Ex z0)ePQNDUaDDNtUS+oprA7X!>^a`v0I>V+gzau3D>EXbtrJf?!(Q}9R2r^n>HTBJQM z_@=P&(M=xC@i>rD-V!=OzZT) z!M~4Uiis`7SgZ?RrWPqazepXkrr40e0_eKwJ4&_{3UGuKe0jbQj zY2of`%Jlp1&Z9TL1~qQE?C8IDJjap;OD2?O2i5AyPpdbbTI#K+a?;#K)+0T^a8jHi zK05ixTC#u~!wiN0*>uw(3BJTHXPG!`<_VStWhr6`HwJ(((9@{Z!Y!;PWao_RmO`{uO;UMmx z5CMZ9^R^p(ixu%ilaeN4%1u~-@$FSF9h11<_u39VCwC4si0)iG-wFfN!s`jY zdi1GM%>J-d_}h1I*aNO^4l#|~TKRnFs706H2S_FUZ-8O#Kcn9RRdC7yxRPOGRwV9i zc@W1#a`&h~YtJG$$J_cYtg(gZCrLBP-35U=bc7tySGo=K&`NUDc*gHP6C6RZczdqy z9dJc}lVynTzigqW5>6bmdO+8@WNlzudxTd5>sGv`Ko+V*N;5ZlrEN<3ar&6ztq#CU)*i z+oTtex>A#0HyDbqZNm6OphqW737YoNpM))Fc~@4DnhuBnx`YQ^1-ykPe>$L!ikAro zIUX;IJs&&*j?QQ}?PrRJiZTVELO|SR=zfNAKEvBVqBosmm^TQ>^Uu`nNwU!G(mXxjF?~p+#x!o92_I-mAxU}sDG#PpMDl}P?!WMD@6I!Q8gm__#c(ao%Oz33osb&?@ zURmL;7NOJD2#xBOn+XIW7cB^13=+V9n&1a`vg@;e9W8rD8pF;@e52ldq=OY70_NRJ z8Ub~fS3DnFiNh6l>K$_g?dbJf>c#h8N=?IXZ*?dbTBz4^D#kLe<{!_Y{GE@pR|yig z@#Q-kPx~^>@v!*|WmE%{#H2m1(AjVyW2IS+*QrQX8BlO* zZ}x9*87Tox6>Nwm>loixz2EU1y&2ySuL9;s_Xm|v z_lD=TTIdtl0;utyg+0k4N)W6_u${OOu0GFP2lFZdk`;dv7n<>iDhF92MhU7l(Y;6D z@UInqexhou`Jt(pleh=weP8{uXr3-?7)to;dl=J#8y`%{Mv^+UgK>uU$hv_`%cka( z^19h7>*EB3DjmcQbuTUGH4`(C7ezi>Gkr} z16qI&kuwd_Gz39SL~ZCPREGD)tzxc<_zR?xZ9TIfSw?JV_?x-tGz!G@#G)e#+g7x7 zPjU;JU+aO&d9&ECU53@-czlMxjj%{9kGS6FDeJw{kM<6wk4wlhZEa@$*`|rCX*XOT z;T?oeDM?)7DmuvnMTRK*wc#1M;dhKHah)=8hDz~z)Lk7+*LYXP`sZL3<&P9>+a=<^ zW*6nU6P&#f|Me1l(XDJtYzG|4%pb1k*E=O9ob5})Dq>&cckQ!joO zuF+A`&pi;#FMm~q}oxE#H1SV~hyX2NJr^G(ta z7uxla4|~dp>r>ny3gNAqAX(ksuug&7_-VKqc6d8lA$CTmulduDW)B| zWY{kaFUau$k>P21}<;1&1=T;xr=h$Pc zztiOK6>GWAtQAHsztgj&A;a5PKL{2;q1JW5B0sS>3rv8DC*I-l+-yI%2V2lR-_$;m zg54y53dOs_+=>|o}b$8e^CfizH{=d)GL9P zHe-ES&XuXMkhLEc8L0E5f;>R}HqI`XZvJkmA(j*eykj2?DW56z4 zO@bm3%ojyTM=*OnMXUT9LVBT2a_;p-ET}C#-)SI%apvNrRM&%H%j(>Roa^%o_9E?X zaj;fj1kRY~XBhgbbJu`;nZYk*t$vgy9hg9Kr~a~*J-NHM>QgiBlNVlkFeXH(1dhl~ z#4fvlBwZVu50gq-4qkM$7&J-v>p+ywjXRr1$5i3pa?S~Vbx-l4kl#Q2+FXCY=2EoE07oSzfeD1q4kI`bcOj&Xcg?I>VR;;;M$x;za*~D7 zoasl{b%?!r!Vb%o$a>8Jfz&dj7A#h2;1`!yvdGw;mO4wkww1r~Hz|>w1vBBeT^c^r z?{lzBlGV1weZgnpkX+7$HDcjuQW~dp*2-L%}dH%uQ?05 zAx&z@lCOM1qb|W&D5Hg9kWATq0dZhyKaS}Z@#V_Sn;gSW&iu{gwW*TQM9M9M#DzEH z#geDc63HwA6ZSgLByBxEd{PsV?J0>@s*dqQG_$C?79jF&qPe3_Kd6qC=hzi59b}mT zk2VqL8j1TaMYsKD#ch7p7&se%30yAmkK*)II7tc4o!+NK3CpIB-BU!`pJWVvRF@lL zCm;DH!F%vkK8n@k|Kvl5WyES%%k#WmfB3O@fHq1b>(-g`Zu|)u3y?XM{xRwu-&Jrf zF8s*JIoqz>n73^(+^D{6m1H&~%dd->gCD^1)T*RR-iUcK&z5k1dHgb$<3DCC=C}WA z)&dZTgYA{@%gy3|X9NHmoYxvR0^3SPgH3x@*pJU^6~YmR(%P?C*k)5V`b%qo%5Bv0iyhqxQRr0XjjqMDym^z|5I_$2Oja& zPclA@zZO`pWTHz?J4arAu44zLQPr@4B+t>-=ehzk=%-9jlp}mzLO(0r1~7u&$UQQh zJNZZn>Q=vy(usndpVk%3Hyi6mr&MuBNBvJB`)#KQo65be%iKJ^Gf3ZUb5_SIq=1NM zB)X z+o|ZV*c`CGWfFAt{+7yxO7HRty|$aX!hY&ajcR@TSaZ3wzr|TxeBD^q+aUMgYVbN2 zb|LRH1=9zUrir57F98ziCk&JPpt)vLEWM=6lZEb)o*?)_-76Fq=;wy9zYkP6=oq6e zF#>nR_ZnW*EnmLRX6B~@i_+95R>P- z7u>Px{xmKKQ7_B%MtNk46La2l5m=V^%Q=YaFk zVa6?|^J*YvK2Ma=_y@Fq9`|(7SZHc9x_Bc?3ra6l98i$%TW>BX^d z-Z*r$a?m?;us(TbjGHc<(b07jYHpub?~yomIo_0;-*{J$`nCWASIvGO^H;`zTJNlW zwq7MosSU}IyuF$w9`ClF91Sa;Ub61nLHL{Vp=j!q4a=qzOK&Qt*jjN$H|k{} zT+^!?+qtUt?USoYV=DlZu9HEZ{8Flf1gaIoQke=tDFdauAeW=$$WvF|&w_EJYq1#o!xF6SZ9 zg~_h$Dq$hh`4Kcm@=#T%bwrfmNBI_PbbQ!hsiYAVhw|_Ok{Ta7FD(7(SqgSW^xKp0 z!vQt;8z%KKTsip!7rNbj#=yC@$!V1$KvNZRIAYHmK|`k#gc0-65k^|TNYq|-5bwnf zCxEXtqZRlvTv7n{g=doc+gr#0AFPa$?1L-TeBJv_mHd~+lO7+Zx8zTo%Q2;+LMW@% zJKHx;>(x)%vxTiTf7C`4faoshz?$;iAN?Km2X6N)a$e%R97K*_aS}T1)t7KqOv9N4 zW}K&fDjk6|Kl|j6f;-LICOq6xL4DZEF~bvQ;0vdeEYzLTTdXdnXlw(guvv5cHwyZr zwFyVIR=mrghKbsHU1iBKQn7a}^ryaZrOwc>wlM|gN>MVTVWpzYqPf8U5k4;$>d`PF zcspJShyM37(HnzueixqPCRv(4q3Hh8AB<|fu=34caTBHcf5!OsZN0z`DEaiy!^bm} zo#dH20+S4%-XPQR<}bpC!lcKp4Hj+C@Yq;FgME(^FXmg5r`_c5=SPfVt~|aiR)a_{ zT#KIEyp(mnN+3b+1Mdx&+v$|+4P5V>@ftBV?kLaXc+c~7xX}rn$Nlk*KC|haEOmDD z4FzGII#dut?2UhRhBy4(s$)i1WCTBvBb{vBAkh82pQTlWmvS}(`b?t;xGD{Fvx%?u ztII0Hh*m_?%*&@R+v`)oPX88V8rV*q48C~8dEt-1-EvO1rq>d0KK_`vL{bG>;%2%* z)5Hu(`6E4_6Xl%%{Xzj+GvbvdhfwZW@nC4~1!F7<7Q!WL-bPXK4u5kS=wxe5S^#!m zCUI@theN+2hN!=ktmnR!zba2m6~5n+VT!yo9)>aL ze+IbrL^A!)%A&_%_{HMjhgyX^5asNG*j z(xU#%RZAdzHF}0{85;b8!t3j7=8m}sP2KOOe10U+!cZ84-tXORG5UhKm*_f2a=nZK zHKT>&qrHr381t$zdiv}skhs)msfmI(FETKFkfO$nSegS@|*MVFmoXP5N<{79V&NuvV{ zkh2QX&iN2sZyd8Vpap*_fmGNc1#OX5|n)$Y74>4I`D50v3jLxNx+q%i~Nao;Fj*KCj-G-D5K5&4KvfN zrhsriNBb){HeAX#H$}-LegAiZfAZ^h+))*9Y7_R*$6AT|1|#&~RTra(i%D6+wCs4@ z>H&*i5{~NG0bkkdT9>R>Z_=$l)RH_;)zh}zK5xxcKW>@=zK6M}*Iaq44gnm*m_8Vj z^eCjzM^P@5t#DqnIHC?6F8-WOY%MF+M?luVLh3!&ZDDv}a zZ%9t#v>U~{^$z9l?e1wM!P4k{m^(D>9y7o=4c&dZvVHr$*tJt+s$-yJ9Fw$KY^$7d zu6{xgKcNu)7Yy)(UePFUquHn{Agb?|lsPyi)xo4;>+3&*_Wh|4ibM=zm;oG9#~5|@ zMe54-T&Oi)y8RXpnXh1W;5U@KAOT}x(~@fPC#KY>n4CTl_aTh~f2dv!ZZD34j;qM# zqq3OBhl`aHmt2w{#g~E;>P46n`2y<9390P!-K@0Uuaq?SIOVBr`Lp$a&9qtFM5(IL z&c=qu?}K{;>|xe8YL0}_GHH*72Z1`p?jWS8F}G)6EOYz0Q?{y=coYU22V=6zI0S?B zLROkeb|E^smeBb9CC$!~61{Itkc=qY(x!UuU0s~8AM79Bx0w*dFKrd3{yO+HsP$^c z97%L%Te0Su`v1nFR`+qLj4ifcl2Ps_1R(rJOmXQPEPXhY%J=D6xQasP__MW^(6h}YRzUo>@ z)|zY{v}NaxgaK#ancaeUTcl;GyI4WqTZ)!Yc}o@ZwQe)}M?tZzldOqhiYE>jY<#QD zEo9n{HYcfLCneVEZtL%oxiK>56+vme8rQ#2)Q{|3Q!_=fSv~&K2zmbEV6=?|Fnd<^ zeUEpoqW#Lktm;C={xz`NU{?oa{W;{zR*WJ+hWA}M&9!!M=J|F6@o_gER)&P>rYbW@ z;y<4>)-!OR&c_g9-Tn$`a{KiXRU2HU?&f;u0k<>fpbi&LxA#C)0(0TO{+SYqiVIJ<%8;3V0yvq{r0(Vn6JUCo}`IcxXIB~AIudt8OH zq6+iX&y**s7e^)#NH$#Q@mFjYok;V&;B6}~KXbVtBQg|%d1e64-LhIZgZ^K2?@XZBOHRr2tOy}*RyH)eyxQmjKa?^NS+kZNv}Ud!f4_h_O!nO(%O+pSBt?zy0$ zJtjc&y7_82(;Lv}pI^&M*eLU`QpynaMV@{E!zCxkOf?{)qcrf9+Iw486O{~SjDp#U zpj~}VZn#y6DAVLdVoUWxT>Mgr$t%-DPJ>H*8S0YXlAb%up$D)Q(p%ekMUE0*aZ4|J zU+6^h^U!@>dp);Qxu?A=hn<4*VT#-^GveyQ8AOEi&VFLQBLCA-$hH_LW5SadMPNJz z)Q#8J_D_pPHbO_ZH_vv7s0kCHvxQP6t3R)q_us~vMpIXfl0=x%^i9suddWMJI^(-T zCnoikTn@Il7>haEnJ9{`fUnI| z8jMxfuDi$O$TVK#8aa&NQ|Fj>AVqa9u`6j!a^9edCo7O-Y<;m~m&jqlDe;Fl(aAAg z&Qjc2Dn5uxQWsca?w#okD$MX~Pb$-OySqT&+getowUdZB9TqP4wrh=Ms zi>Wk=rB6$=sfkv$st=aXO)i{c9clwM6e^wo`!;lrEsv*ZR$g`vR$lb2HU+;6IgjO78L+lrdPd9Dq`U5duS5)i5{LUSy6r1jXiIVj6bR;ZDi%+p=sudz( zjac=VoMT6X2aNP#5`X{QeGw9nQHp^RW`Gl>S6|VCjPNCN&Q-p-U2@lWAp5mj{3twsW5{R3*&iV7x4H<>d@HY>L>BbU+pmuIS0t*;^$?gP8n7hx|8 ziq!r2W)Pg%?W>_^PlefNyUz68QJX zgCIyD?=`IS@Ylnmo|YwiJju9KUegVh-rXaF)unq8yf1CAZ{zFB+frHGO!<7R?qU9^ z%Xp>Izfsu#j?2H`)i+woY@DblijMsi79o1`k9Cwsc$hoE8B!k-rvZ}H3(3rw_F!0M z8P|fAGQzN7!;YsGGf`i)5wv(w7v#*Cl1?|e5b>=FDgCA`CT;JJ6mkU%3a%IDp8OEx zO!mwUzn)gC1jBsZqEmb(i`C7DbH14s}+ML}cM8;(Ho`87LEiRFa365au!#)hx8+kPP->1E?tUc~yiyou< zJUC*g)dAadE#$n;+;FyaT_d8`@>RGeKD9z7SnQa}1ZTAR1lVW4ru%9Se@%<=82#uB z%b`od;#ane6ZB-%h(U6kwRU*ieKLCD;(FA+!?r5T;Z@EBLAZ9MPZFN$FUSb-!ewyA z-$%c4(hHSUH+t$9!a=TMiV64sNxSUMfK7-J_K{f>fyTroUklrnKm_yYm8T0GOmgPQVfMa5R!l6hhvr_bYh^UzGBj44=uK04i<}n;(O1P2W$`HVwBCMRvkxM)9p~`4 zX-zh8qu%YeR)vouK$J}B`b###^>L8Kz-%x@4?Dt}p$3sxODl4tXAS9FQ=XsU01~I( z@1Zn&`{r-QQV&|*Gwg)X+&yiZT#Uc3S&7HwiK4LRqFx|(hroVZ{La4iD{R}o>g?C) z!qwxjS}@zk_6?%tRZ={(Bba0>|0Km8EH4qfk5(2KnJB`Mbia_vz@E`2#(Y(DlL@+ z-kVyxg)isl=fWdvFd+=lW!0ol)@v&2oHNTG4r5@cQ7u?P%Pu+5^iv%(rn`~yD5|EIJw4~P1D`}m-c ztf>sL?^_wZsIeAd>}y11&Aw+HyJRO>QubY;LDpU*{nfBOuD#~N^LW#ja!M`ZK$vfI8RF0NVb zRZ1tZ3F^3WQbV#^TzYe(hDuB%&$KRfbEt-H{3Cj*Hou6#jYo0&#+RZYRymZfh`i5JQt)8m9Ioc{HExUH~vBTe3*gQOkXQ=pQg7!sC6Nzd1bJ|2!{iLz* z4fTW8@Ud_gXthXGzQ+2Uu6asmc|vJdp<(OcGQ&X*SKLBf$Mct4-zvY~vLl-o?%7=^ z&{vvFd|yo)a66{9OTtcG@W}^eqBzIdez_tEgcoryI9Sdy^!Q&+bD^u68U-94bmr{r z>Z$@7a0TL@S8=qR7-;Bf%FvU7wRe-EHOJ&;EbfIBFnYdBX!^q)j@TqaKH;u8an!~BnusA{?eJT%WaYo~cPxgeh?Ax@d(B@LJ> zPE+QC;f=wgE+hJv`+r8L&QOk-B{`;&j_AOjs-HQ&s$b<48{@1nzH(|L?a0~ncs$NZ zTO?9SjPgN3SgSw{+#tc4g&oAVz1?a49jKULrLIuDE!_Q`_$Jt@-^*E%yd@N2H1(?ykhDqp$yfENJCq1tIUOL%c8!azfpV?lVpWn&1$vrv(u~CA zvc|fbV6(PfrR(1)=*yNlW_vm-IIkFsE6?BDOXON9GLTSmSeFsgR&M>Se~awrjy}y6 z1S#CPl{8J9a~<~SHp$Px4x zq##T4=BQQ)ZDO-xo{z7V}LKg)GB&`mMun zzh9o(qSEUA94gnlb0bS!`q^_{rMTGGaMj|w#>N@wop ztK>Z|U8BJsF7g+%6Faau2KC|$pdRsNtmuT)r^nlVbbKgqzCN@C7i2V|NE^FUZxUyZ zK2hgfzeKAAO^f5Yq*rey#vZiF6?{15kfjLziv&X)0*C+_ypZ|4NF(u>cuP5{(Pxpr z;YKnIJi?|a`z7LzWBwr(l?0U+65NO-J*Q?~(#*ygn~vwwMt(wLQqHhG<)Ky)*_uWO zcHE|XAsouNu3syV@>uZ)MxvK|?gh=x($bPu|4Y6sm@PR_yVwEp=>?^w7d2nqWP2wJ z`@;y#$=pBWlX_dvCA@$)wY0w7tg6}RBlq_e{KYt{`>Oq2ZPIsrYhKW-RxoDYaVG8Y zwnksrxrG|A*7AEUs`RkglWS|XB?`#J7u3~V0kHPZT~QQB?Hv2fh;joGlF{D`@ca8^ z|2$$4apg_Ok}RY-II;T?(TuwEE~@kcqUuX3oWw$q{2Bp zk%&L2h_VfCK=ZL#j_cI-Q&v)NaA8cdto~NiB;?6UFQ=omyKH@<_j%&xUV(V;R+<^v zh2&@290`#pqZRK_D(UlVB`yO6Yt1(wK%CG$cDl^_Rn%~97^-BCbqA$Nx2j###4D~7 ze5<+X8SMT7BpMbC52!7gh%bODb9;X%v-X>1OLeV2cG+3LdeGm|`3EgHnl*OmsdRjd z9m8P3!KjjF9i`5`{%l%LR-{*WcNQsIn`y*y>+qq*$%84!uH6)oovoB|+ry*2o-5No zyX%FFjPNrZh8i_tn1P#wg%K`tfD$MN((N zNZ1$6>z}5DNf}%&Ls$!TnOdw=6EBc5-p5>dU2SKR7)VFFwbos)Ty)J)JEhWnWm&5D zji5})N-3K!${c(KO`6iRvp)@Pv16}UbPcj8t%u8x>2Ih&3J#gx;>OKjoy(zQ&^nTr z#=&CdF_h{hwBc|PgE-U*lVDH~wGcOS^m#l51#hA}{cR;{E$esL;N4=v&GMhIbRi*j z!?5i8Usr0R6Vx1RO-^t@;iBQC_b*(rySCig>Jq#4W~1<)?r!K6xEacg+@^o(v_x;p! zxvf&GxS=F*7zUU-@1M8|0;Hn#4CNc_NZO-JfK>eh?C^~2YVXyu$Fe-E_o+fqdT)Db zsOYN2dxK*qe!U257j*Xz>ugjvlvP6GMxIULF*)$XTCURi|Gg>^ z)@v67dIGgg?572duwG~y8%V`%6Jh+az>uIp%MUyaG-PdpkrNxHh=T%zncQzy?uL0wRqHx`PzX% zVk$G@rJki_GGIGb7-8m&s%mQ)z_rc38`r7HqfAg@6v1HwGPB#M+q%ck@$$4dJQ?{m zdmN>P?vKX8FkKext5QT!#)P@oCy$7kst&GU<%or+eT zTeYaXG86YNr z7?x|mBG{z=Po|RdBpL7s!<&P01#WS1dM++5ox$|XOdAlpDXFPdjEt^Yh7o)L|GjCV zy0Q}e`*VV|IF$a%l}P)+%)*wIK>Dpul7KiKrBUjAa@%)3eQ+-i$SYYcKMq>s(jI8T33C@O(HHN|;0OvVG#Q)fT;B0c>XK)>(` z2mtvjrt1lxv4P$moy4RZaDhfP4#cy+2?`2&nul&<+MxjCz8@sdubY<$@VsMcQU|jq z2OB$o(R4hwZ$kn3o4Ap_w`^ZO%&}Y%6d6NBRT|sc&ANAg;+^oV`D>4Paj@YCHkl{w0(FZ z=tSXgjEt$kRP;Ka3PXSfoBzqjZ%@#(Ek4$@rk=Y?h|}d;VO{SnT5EtPR?~z90H#n~ zzU+1M*ZOoX|GWphVVull8DK5$-o*o6maeF%@C-Qp&D5!6U~mPTmlh6Z!4;T=wj@@W zlZu~t=1uOo$`+47y4$q;7>ShvRA>kixAl2vu@C54Cj%}#Ug4eFxkZcj#h1L+U_Jyz zMSC*E%xgmMey1lBom+d4S{mnLI6`AV3I}}XH^AAbYigo_7?z%e1-AYalu6V&j&cKF z3iZlRF8cI%4;FS7{HQHpv`=a~f3YuxM^=^Q6-$!BY4KTs-;m7ywht)Vw9fMFr5``OfsBAT zvB>l~z^f;F`}hcniB-=pXJA56ZM#%_0s?8g2%X0!1~Uu{Bn6%4gzdwXm%OR{c17CR z(o-qppgTI{#hnDK$4%7Y8a{xNy_r3|g9u9BUFwfbPHyDLmU6ky!pf>|YP!0c16bBT zMjH5J#klj*$_iajt~@a3DOp29gXzboPWkrdVCn%#i4-80OxuH`%*@S0^w1GgHP&R^ zXf(`i`X4|X@5jEF1rYg>sVU-}@U@`(JX~BPfq{V?6`D6RtgWu@`|=&IzG?eTPfzKuU;ncUYOFEHZEN5~igDOa6&Ta)*Xyn>P|aV4`e zRNyGu4N6<$)z||s06X6tEG;SdMZnGXfl`Q(k&*Ck*)lwml8ivdFRH_*wH%zv{jk%~ zpiari$jAyi-4L)ps^+!x`~C$A3Y;)%>2RjWgJXSTW9LIY;j29}Uqi0s9QGH2m1ZeK zjvmde^svGCTIe}`zE#WzR5K|EcnkF_ZM9TYQOD4-b?3<=PukAr_8f>|5fH+Ov~n5u zStW1p-A^JI-MrbyIy%XONzk)`apxW2wKl++>*hpkIkEm=(R|I5XT5w~^b^3GZ6D4S zx-0VAIXEnWkng_Y2vJg1C6|zp*c_IWl!O6f(dJ|=nFnC7S(*Ic@%i($_B?DLT?j;I zbuFzP(2p9|sXDHz*EmoVg3OY1pam<(B2(XBM(A4&r5=zCT$Ap;7!DNfa2sa)X>TXA zmbS*(_|y8A@8EQ(>&&VvDl2^ghX^cRIfw{wxT52@rmC8NgtrBB5S4Y zy@p#S2y{2@c=s$?s_}s`^Szb_#>UaW(0Jm(P%9TczIKN!kb^FE;>ia=t;cD0mG9nd z_W5m2-UWJ`(=#)OJ02t@v9%Tcq^^s-}Z`xjD(%-aon2t ziuc>bXgdSlul4nu4vakFusB7bj-%CkIo?&EKQkj^bh6fVtz{*Tr*a%#;PT}y0i5BS zK>f^sK8yDL{XX5NEEDyGdr)Q^u@PNOZ_f=KD zgC&QZ_%b|P4%UFMh{y+yYVkz`B4*w=a=f>) z24=1v)JqXJf_(7R(V+wm!@)4Bd8=IoXgcnLjWb&(UqKt#C_Ob5cD3o(gNF~9lb9u+ zKN-qF*xTD1>FZmE&044;u(&P?ju#+01M`gnX5DHulVt%2!1#fd{L>|YdgpOrj=KXoTLi(+ssl%HZ(R)56&V}TqfR^ zD#y@{f{lI^luYf<`V6O9qRIiNudw-I6H#9i?B>N_kSAcd0=35k5YH>XJ`j zEzQLhfeBblvP22hVnG7CnePi(#Wu~CfqBqJATBX5xJ}kX02-kqP``Y-(0%a@C>P}8 z5J~p-h=*hxW zM%7Z-`5;D*9=R$$FgMpsxGq)%aybbob^X&d1LOz~1@SjuziO4Et}!vm2GfCXzgFAF zUR+Zn{(TLUlz)W=5e_Ea78Z8JNNwdyIt;y-a^)``RS#;<cr1&-w0~mYFFeg zYHXA~0XY-`RNh^MLe=N-7~Bno{bd`FpXh{HZf~6$+2Dx?Mj(HzUO8?M6a)`BUVe2r z0g#PeW_5OP%E$7^!x13Y3tGRIAktRTbQN~IlJLXENbGFO56eFoWbnbb33fhZb=C1? z$iG9`VL0y~WEpS0&>el1kx|*KIuk4;1gPmPDJtT|Z)kWZa*vYHhJ&nfdP9n@(E{i2 zvpr=C|AIG;SV9}0oXnrAqXx#b>AMYfp!DqQ4bQK0_(@hH6%`DtxDD~l(i)aS@t>FyYMfMJI7 z%>M0ju5&(|zu=q?UR&pS=bh($p0)0E-}hSY{-CL@M1)U+4}n04o+~T7gh0@PAP}?_ zTx{@(@WjFf_>Z`oqQ0B9qm`Sdxr-&_g}IxPouixGyEjZ8mM*UE936ys#d!I-nQYwL zoLnXN`0W3$3wRw}toej%8_K~=@SKzlTp5J-W{a|O9qURei=o_>a# zQ{5-aQ#G3%)(4NqmdFKz_~o&Ezg5&|=RMK<&iU)*C1?0cc8Z@~)RywIETsRC4XQKw zvZ=or5Mnq@sXS>9d|GGc{Yd?dA;UKO8rO8umsRRv9dtryOd#bYK64o9Gu#P_H1tKt z|NdJ02tx4;mpN?5{Qv*U{}(oaJJ>;1Z|lTsaA=76;Y0LZe)L5;R3v;0c^Q3r>he-s zTOi%X#x!j&gu#2`p8KShQrYpb)2D=lyfJCGU4!NDgDzKfu~kg0tHr9eBZ)58%Y)f3 z>XL^~?vs%fkdcv1+BYp0XQ^A4&nJHRG_@hT@mREF=!Jtzvf)g#rKM%VbEDt)-G>;u z!wDz_t;gu%q;G7Dcqs#sXSwMj_B5Fy_7AzaM?9B=XN-C=NS>~=G1AcN&3m*hW(C~r zK4N35e>+6x;_BLRdpcbEy7KAiAWP+YB?Sdch=GBD!ax5sPPCDOXjbs$j%KQBg-FYTmN|$ zrMO3|tl`?~;^Ennp1->S?|OYI+m2de3>{kfJ-Zx;g8?uwE9m_$!sw=TXb$GCo0e73Q<=?q)+6tW)6l0VwCjT=~J77`+_pH+MR zo)d&X68GyTsvL?S9%g4}3F*W%ebB=}*0k}aV;2|6?oH{LZvNz|e#FHUqsrHj0ybaM zz~H%$kHmJ4FR$maf77xHRLb|#34|Hy>A!#f-n;kA!w2hIyGRVWf*0g~7W8Qb9N|27mtiF=%#LmCG&B$d&fH zn9{SKs<68FOD43IpbV`ceHIn>XyU`a2TH<%mbY_i;(I7u@Z}4}BB4x#`SB22E@mq= z>bUCx=u7?dhb<1I30O!Rp5cKIqL)LLb?$p_Ym2cMCbI1&fw71QJ}p>OhOlR_^YK|v zR~UqahbJZ_eb?5I>i@u&Gq}*=incS~#7821#gu9qAfA|**!h*~4!(RxCG98H)6;W) zIG@Uv>-QV#ok{y3HZE?fVa5c*40g0g715)_=->C8EnC6HhW(3Dyw&dSqJVhs!-koi z#WvCW{QNB6qZW$$_Z#;7J3t&S1l}PkjN2ac^79k+!sfuU+@6iQP8(R?d+^{#FNw^; z!LL*BLu-aL&UxDyf4c%@Q2P&V15PYqTpC`XbBL;TbD5Yy^v^k*bUbbkNrey#F2g+B zChck9f{!5b&i-h~oDB1IU1gv3k!$e#oZAE-F7%K$GhKB)7w>tSSI~J|cOFhxn~tM4 z&h+j^uPdmu0ePC*rNzi=HN0~j1R*18)%!Em+k55J(repoAirByLJ0Jm z9Oz53J!tB!MhlvouSoA4!4Z<^c4B<3!&r=VC{ryC-mP2EISznuN*QUQeXh~Xer;kh zwqM;fHt*Oq%2ASqzH=K5;3r@^+wXK}!Dqj+6Ao^+mZGh`S{;bsf`nody#aY~i+~1h zgK&OYxV7XlZ;!&>AmReB&@li4RDy4DHDnM^gsetZGy-puq3)l#4ZgQ~pAp}*Gcz-X zMMhfG>Syr4Jcn3Qou+j38d|e)d^@?S+mmAWI;nz`7`(%*bG#$&bLsM1{P?Kb6#?); zpMi~{GHkGi)Mv$|dhOS9lDy-3+Zo<0bvE+HYR88lq2C;@^aO0vgMt(Q6Lnk~sU2Y0 zZ-S!m5`K9YX@t{K^_pNZ^@xj|{kTKj*mzqanN35waNF_uI?Sz*rZc{#hW{Z8i$7Ez zm$^^wm1QW4%&*Fw#zLGLmUMY{MtRHf-8`2{UvS&9TeORzbg-}nS|mq(BT<%o&B{J*lhGu4c`<)1!r>HTi= zbc7suNX|FfuV1alJDxbpM-p3}tn~-LAMlxstWsR7ef@oz) zlO`aG10Ftnh=P=6#O3^l*jQEpfkaBV!C?;n%9pR5wd0YtT4;7|2Lay>KWh6( zB@hDgKN5$*tJ@K65G)i0soKSAt4XT7tBvyxEKkmVMU=3;$mj#8+XwP?bZ6qrH30n< z@NGlH6)1qY)IwIMtV>Kt=$3@G|5IG9jfBuY$j{fe@1WMAb=g6v4LVEi1fByM_hEYzWCJW4_@5f>{r{( z)`jDdKQ?Qc_g)Fcfr!Bm>M<4s0n#p-%o1xd@MB@MvMy#2qQzKEvHIjlxO0NzzXc_( zZ(snY)c{A>@5--BDuvtoaM#dRItMj z^J{=4uhpiKQc@;+D(^kRbyntt?esG?77tx0&L=@M-M9eTz;h!9#hQ*dp5UiQD63J) z3-Uvih#*kraPN6diECyP^x$2e5cfrEy&|^xcB3KDnr3c=V)Scxnkl5i7Z;-oPn*g;nZ0! ze#Q&}_YA|Oizhh9>?YIdx?+JDB7_{!skXWsDru7;nsiB61P{!pu#1X{f*n*cTTXv+ ziEn4QqAwBx36uU67R*9o_hAVxZe~i7#^mu#Hgh@~u(Sz_|4Jze$bWpKUZ1}MJIQkY zUO4GP*`JMYJ!I)VB8DDEZUW6#*OLuY%yUrx@bKSvCCO@OX&qiJfMpTqHBN$O&AjPf z54(k4c+_ztZ8QWi7lvA-qKhPBuG~hYKOb>_KYVwW^ED%b26;6gla!VgHEOlqydGz< z`SVl2Hmb;Iefh_{em3pNJ2F}kyJPzKdTSB@hmQpW1VB|40H@k{v&Xf30vH6p>y{cg z;^!(VYjwlC7I#QQ=Q>-C*F(_-Ck#LqS*4|OcK?*PqF{D4obsljXV;C4k#U^Xu^p`& zz_Hj-^LkWV++$weIH57IP{4+6#>NK+A#O$Fz5HS)edNK#^4&PTckaC_%Yk=NO7!j& zpit7ejtJN-woZAD%{ADH?-nLUMMW_Q3MQSb57fV(`YMko0g-l8`9@T1xO)%r(B#`Q zJ#@V2@V{Ts=e`}Oqj#&@Ekzi`!RJYgZhs3p_;?agc76M}j=aP;6WM6o-$(9h1g-_% z!5OQ&kP=9Xeon&^dTO;|!#Swsv z)&?Make5we_ZS$6W#7Hy0F_=472{K1bw)Bp;{hQ>73VIIcI3@ICKgt$*U1|buT?Co z(Tx7>+(30j#c*hrW9N0m*RPyoQZOS35D6`tpAGdJ-rq;E0U{*dvFb^~p~%6^R!yGN`Vr2DtzP z;wIa(|Gr*n{kU|S4%C!m6CQXBe*1dt`gEA@{t6rx7Zs&h-EsLk#@_ZoS%wdI44Wy| zoDI8-Du>saWfkKobC(4#9jR41!k5Nw)XHKt*mb_Oj+)-c&OmdX`9LI@o0OdIwli%U zYMLCD5xI`7UFtvuzn28*2$DLFanl?K-3P zPJW~qxUL1ZTCfi`=l&y}5jw*g)Bhcd(x}_eu>)&o zsT1&+6i~>n$7VqV23sJ2xVc~f(cb9~N3ZdOE{O!*LB9MGdum@&SP0S7)P!{NG%b9G z2EZgyWy>O7Y74dmAQQ4VkER2_3M%O@EI8=#e)rhj9<$xtL~- z%oMGhW41AWqrUHPIM;8PYW(BoVqbi(^vl&u7ZOWWQ4tG;1-8=_CvEo2o!Q_CmSA+| z=H@SQJOSG z&m0q*P7;YO1N8xPXCf$$*^B{K!REaYCqRQWsY(J;KU~HU5p7I*@B&e=kZ_m1q@GUP zO*y~%kq>@)y|o7suJcWX)R1$sJBnXPW}Oi$0u1tZh3<)EtLs)7q2!q#{4Q(0w4!mbw4%QOcfcm3TJf~y-Lc(Cvxs8` z7lT8KN6F`9klUS16{V$7AW~fb4R-y>QNr)Gqp6~za?4=al=Sz|gYg9J7%LZw?R+*W zdUgm@)spx238-xhzt_V_3+BHLp7SE3CSftU&+KbW2+2h61&NAM*>N}4*8jcV9pPb0 z2Jv|I;a;PN6jT$ytuv5gu0T2pIW9dFv7hS$u7kXe&i#7p@yl#jHwMWu0=8Ul-iuw; zeyXyzzV6TUZhI_ySajJ>-pcAR3cX~IS6}$VvV^RO`}_Ni{7(8Sj9QXVx^q-?8O43+ z`T5IH01Xn0k3SIU*R{HwmPWOYUPEHOm?}X=R?fhXR z0!dQX+M0n94WQoDSdTNHNaN2>TnO~HpwQJWG%WQqY7ub;`h5v}oQ?jNYd*$YF)nyk z)94B36DRvaP-YLp9>48NBD3tZS#3ruRG3XmxHr#ReFqq`GxB=db=ERfz+pkmUq@EJ}!%kF1nGg55%+a@x_nJ+$~f`+K*+4gELJ56pG*G7ZVc50*r)=jGt@$G0ts^ zYMCOji7ZNjo<~MNTMDETBb~E^Z65#+r$DdTB;f2^?J+sD6V6+%S8WAMjRn86QIxQN z`BwD5SxvXjSp{5?1gMcL|I1m_6ZhGPXuo>Zx0z}>2Iz4!5Ikw(u8(2Mfq~@=e1I3d zo-%RTkaueDgbqd~nVx$@k0D^w*#1~gSt~;}a5=DM7zm5rMsKd7ydO?Z{I*5)w{HuV z1tNRpz-duaQ~$M#T+$YGl;@r4Dhp($L1Ii{g^!y`#8I=nB(C2qs2Be|9s_tio{HR9 zs%9toclfS<`dxSh$@yBm7Rk%aun*NVDKj+f0q=>~)N=6h-`UT7{Fl+~q8$`keNet}nRV@^>ix1$Hug0P9~>-NUij@eq4|`l3Vt z7edjzxzy90Nj@uDswL({Bge(%G-or_f(mTu#bVDea2{jAGVj3n zGtHoYE{k%&zU7`8YZ?}4cLbRbzFCH(`NhZ}+e~1{>_62XOPd2oDd^K0FPX?7(Lv&X z1f@%QI+TwG0>c4tC5NUJxW z|H?9$r8?kh#+c|@X2;%fGae=q{KtZyw>Dz6;|`}m4w=%xI|uNzmzHbBCkIIn$Ra{(q9Dy81Md7})NUs0+_ z0nixbRjtucQMdp*yJt)T4}C|zhZCgpo1+7BrLeHjX*=6<&85X}fD14hV2$FDkgx%> z53rTGq5bK}Nt7=!QLe`aY^O9a=Z6FjxObwOxWQvoq9XL@rnO5&t_s$gC`e97zHIr- zAzZFvwD%nbMHr0em8~xw9z-(XW%SqAdXdX1FC!PG!3wg0*Qr~f-xDjkGLl$=0rCXb!zv2Al9gjU6B{;8|S3>XvS*BqgFiJi!XSzIZVf*Dj` z@GtGi9JK<)f(n?(j;1ePl0mSrud%9we1i9zfdD{nfKazsR--E`Iy;s;L8m-(D1 z8AF#jcBcwiAIV06C|3q$GLN)8{RN2{$>2T%XZchhS(Q0e0DLb*Dt^HAZS2|C($a1_ zk$T{Vjac1XMnpz74cUU!*?}-L9U+7wCub0&cMK`y-vyc8@aw2wIn_(M?dCm;daBMD z=*EBDwHQp;E4GpUx5{kiSN<(D@J^m%lYo$t&qNJ)`M_1^`|;yV!)pUTXgYlN4~|$_ zS?%TpuMwomISEi0}O-@RAB<306??DYCLBY zP>V4VncMCNBHCsUumb6OG65)a46raG5aTFr^VZ6$?oB^Fga5f!C&)QSrzF_i$U?hv z;+v74n}DI$P8%WO6l5B*9A3SK*A~;=57q7=nAtglh>p@*O+8a~oH~3i*2=3p*MMJP zeZDgR9vXNEcFPaRg1YVy&{wZsIc=p|lij=5Q`xi>z32e*&CxUU{}jpK69wq&Cx7_m zJs|fApC^m0e-x6q;Q>aA7@e@9W^KLn1%Yf8Ox5rAb2DOdOJchvN3(i%UaD6nG8&q0 z?DF*LainOn1_snX+X7And@)3vI2|!Cb%q89yRGW6O2Z4v6F@O6F#Owvj{o4<2C4sY zA_-R&76sjfBkl`}v8SPYo>WFpN<#+J1(*-Cg3)lzh9>SlZ9;K0FAanjbbrKMw`%NW1-Hg?ME{D0%s0WbATp5Qy^IBUC%) z(c{M`D>+UE=>;sp>h@E7$1a2jO3vm{QlSW!!qY92ge8S&t-9<(5}{X_koNvP#VbY-`{L2Dk)+7=3h7X`dfsbIzTC1*D_NV zaBH$+Sxt)l)72S2jPmEsCqW2OaSG7m3UPa9jJ!jFC;>ej3_vp-+PbDe=PexM324^U zy?)wMW%nAGs%=fGZvLQ!1bOju1&>*wM6Z)PYt!taSi7u2v=r`31F7~Um&wgpWnz|4 z0pNsg>_Tjo{r~KMZO!LqWvSWQ^8nW=pd;w|`Wkd1;bR81Z^D<)rYgy*Bui@l*8?-0 z5&<0}H@7DMs3Bny5jQ^z@g@=m*7Iv>5`O*Cp zAPI_+qtNNyp1;T+#@UqH@Tv*Jt{O$(DL~7684diL#CREG8V~{riHWP8ez#XA`jxt! zcSzqcnL9s7qr>9Qr4HZpr{01PV0v$@Mlu%X!lDh@nF%uRTWc!RjIfspu#~<&1<)_fd|I-T1ES>iJqrOi zrEO=q-G3G{^-^z&Y_KLN_EuN=IK&o@O`*roPx6-*VK6kqHME>pZYjLf5NW_FAX#2( z9|GW}{ueqZu?ETU+2a861K2*&!otF8xzgFdbXx9o9kmiN^*g}=3`Pp<)njh%k6cyF zA;4eG8=bcm$+UDxMcG?LoT?>(cxAaE{hfU0;~VeH@YnY36HMQcG8Tw+XmBW~l`(QY zK$~L4=$@`f`!;L$6t>`s`ooj+r$mDh7N!R zm>8FbcBn?Ckkfs}HSdt@tSm4P+(IEql>9n-&`)F11*YuR#!%DSw>7La#d3S8s@NNQ zlYCo^>2Fx$vi|3giapt!@6jQecJf~~AjTp%_ox;Mx>@QHg3lyTQDd)Ck3LPrrNH~w zf}QXgb77w^u)Uog$|T8ojXNAPXuhG>oho^rUyi-Km%`su8~m=?=0EGzrsFhQ(~wY3 z;HJ|>KF(9xzgno9-^=z(@UVr`tGdj@6ZI%Ms^-gRtLOjYw$sitA^t4-U-nd6?pKCo zpw}qKem@a2ItIFI=O?owX$CfP2l|ZF1owZ7kpMuQNCJFh_@#eUV6hsGE5E5-WWoE; z6sP|4Zx5qrupd7UpPv1XIfrU9EW)kp_Go1{8M-FzyffyT(&^06a@Ts*c8xW;` zi%s)ayV3=M#*G_)_m04mJ{wHFANC0RCs)gICb83@t+%KwxM@rYKb-knIrdZwgCNdO)rBvF3W7=PJ% zPhO8?Y(l<^Xd6FTUGaaagHC@|#7QSe_~kN8jJ7a9oSZOJZ-$1QQ2pT0O7<0z0&yZ( zZ`%LXYm;72_frH8+d4FTnM=UGDs~`z9NhHe7#i_FPC0rKak%lH=o$X$`9$Tmf(fqO zk?lg0R?*&e?`sye{2Il;dGt z9=D2K3{UlP@rPIx9ywAn{dcWiBHomDESXGTF>nuX<+S`d$Xz%I*W@Xzi=d%{J!Y}E z%C3t0|Ls@tQ->PIU++xS9(0Ur;lfk*4o$4lkAKoE!bNTMc^a8$6_gj3t7QMT4Nr6$ z^wYjiXwOYa8_j9w#QajbTm%=z01( zgeTY`8stq*sf6D6o$X(EDom=Glljs8Hv{zp#LEZ2Bde%iGnJXPQUL{%UmibIULtL3 zs;us;7-R_g=>-EE^96d4nW+<Fe5ok39{!)-Onj%Mc0?a$ zNZsCQBmZwJzJRTaBjofDX}KJ&8^l7weJ{aHu!z_z5YXJiD8XzN{&q*%3@&1n131~B zwC`vPt>7)FXcg&3^2E@O^bJ$DtpxqDnwQXsmG0#K?rK?ZH0TPZg~Y5)|hA6H9Ay_Bf!^ zqY$H)2K`)hrd4LRwiCp zF4JLYHtRdWBxs9PHcj23%Q|0-^og*vl5UE)l7MSSAi`BeSJ`BG`%YA)?7v^uNi3uE z!4%yYorj5c_KmMnbI%bN#t?n4h>p40d}hOk`+`J2xqlUyj>(zAbkDe>UxYh+wp*m# z*+Q|LxTosu#w1(6Zt5JXI0xanjwRVd-Kro+D2dKUEvwFp18Ok~`qyxu14E=gtQ$+- zeSA5Fz>-QIJhWu#!a5IpI`5<5Qd8@Vk}^%-M+5FFS>IuzmcCz8&sRmB6t>-aZG|+r0Vj<2h8+Amo9PEpj?ELe4uqoDnBX{hy z5HHKvU_)xP=X!+kgW<<$$g(#IsVrz_*58n5`d*JIsv+Hn!80?oLFgHbM;&KhE}Et4 zRKTwFF_(^oM`xRSUeB1X%7Y#yvYNRf_u4#He%pg{{f;EeThg;FN>>IJ+`dRit~1IzZ&oiPb5@`O;639EkT6<5Hc2T6#$NvIN(=cqEp;%(n*N&r7%2trbm5w{qk)@_{k)49 zQFuPtiVfr@u+RQ&4j&0HC>4myH7Iymxvwb?K5{ev+J4xPeR1ytb0xu^N_kerAh*Ln z1Q19&B0n2L>d`|Az}}1^RK*@VOS*OQ?GItYZ7Og zJ{0y#SOKSr7nhse^P6igit~Fn6lpfjcI`!e(X2*dDNEv{;+UL*l~{emi77!ZPzn++ zU7zQg1JycPN0XxO1!i|Ul%TvJ@ zFr;?g15Ue)E9Y$HMM>Gpxi{QdlpFK%`1Za3!Kqd>sYW6%+zO9C^NXS(>Z}N&gZtLe z774EYKL6Q9+DhSVb^a)Ps!%`Ya5a^_4P#CLJXm(tJlf@jkJt?VzW-06SpXXEwu6S&_7RefxP|&I z%|&LuWZ}N3lWg@UG`*Aozk$r z4r3DKQf6ngJy4n1)oFhmvs6Oy_D%!fD8`70$(14uIeI{Xu=6JUP4L|Zr*xt~3LL*q zpT=ZYR2BXp{6|w;AmPYPb(86pvuh9y8^{ao^1oO*;-D6(Oz$9y&6K6GD+I6XGNsQW zPk5bl_WQ;k+sbBe&!vK3d>!h>7eW1d{LlPsZpgr{B)H_JeOzQFK}YjfA`uvknwa&@ zYK4v4osn$q`P{uM4i-*I4G?zX3gy_1zIQL&CqD{A0BYc+qC(4OOfgh8zK`5}ZEWt% z;N3)%@7sp}Vwyko#K_p~Ts5NNvYk^fpOe+Z^^bjx!+-}p1&!5?J8`(q@zP`e zn~U|QE8O9w_atm67L!ofq7VE945a{sbh1wMZ}dT=a`n<_>(V^I)zS?oesqjvO+H|J z5AdVOI`kr>ph>lhiwVpFJN0FQzVl|yEBI4Vt|#_B*x)j+h31$U=ett{=tq~1@35ON611xy(jN|m z{hK`#<%<58*|e{1ypq)KWp;7u&ft-V0Nav2TYSbRt}5%j2ZKq-SI>R@TcqdgoxMOA z@q>di`>}~}O=E8+utEyR%jSBcjj=X#4N3`+zbme@=<6Xt+xWb)=9;UM18z`L=`a#Z zL%$#z9*JmhU*kRqZrluk%$`0Avt=u2&2~4<^RN8)asg|f(fy>Qt2Ld-gIcr!J4s4a zN#2}H_;3Rrqq)FSZcfJG);+mS#B=j#>W=bm3QR3|$<~I45EM96+#?kxe18dtYDg;0 zSbuYbz#lIkQ6tP{KNeI>_XScu=L1cJbLCII`45x(c5IfbFjes=e*_S8cM$~ad)|15 z-rt%tG7gk})WBlMiLQX&UB&b!@93hOr*fH+j^sJp{$a;ON6=%8Ew63#&boq>uV15y z?MeY+1OdGu4pCDkc*ts`_c4S14zK4iTRB%`O@&J#)U7_h`JGX0C%Lc@3EKw;4b*ML z)HMd})5x%aht-YATAuG0=?F{5$oDKP_-nqFojc=ZqYdH#Q(xzE6`VFHdKMF=uBDJZ z-16jzOLiRb#}(b(x+lDsLd26d>~dOkf(4K!9R=cPuApoppYvxgnNGYq7R`9``d{Tz z9`{?aihV7j1l8UL6S^Ryd6N;GLv!9!$cHPcSKrdgCzHZ>C^gH(sqYMRRzIHf8SYHS zn0A|}ZG8)AwwZW11{%Gn>1@JK4e9GX=+!4ZlMld>Z34Zyt88r}qmc@O`lyc|A4y1L z%+_0LYfXH>U^Ns}ILA@SxkH{W@8kmJF3xDOO%$Bsq!{q&14(Knv^xUiC~g{dN1*i4 zdu-i6;-Hps$E$%?if>Af9yOoXDAov><}&8oi+T_P*-b(-v$SLdGn!j1+c~x;S>T5g zGBfwvI?l!<0|uJp`+BO3n+q;Z83}_D66_hhq#dfn@IXWDh~cvlq#u@Xz9_x zoA`3Oj~U}IPPT(h7nd$%EeHlfFmlN0=+sTPO@xNGoA%+$`Ay~l96ZASZ ztLj4fL`O&a4SeP`R&jIthMM~Zb6dbv-W*PCy2=7ZM9Qa6*NYM<=D%H^q$u6JocXXr zBCw7|@)j}PG;bBW|6|vr+d7c9&p>;&_7IhK08NfJ=BZbcM%MXKo0k{+M>+yoS@ zozEHjh_lIO(@H*)2+`)+;{(n`xaX+8VrhwT2}KMQX%Kdd?EYu86-7$pJ_GCQ{=q~R z)Nt0-S_~iRSU`VAtYEtXbY8$1eW#(WuI~JkE6p_SoB52A2T#Xt5L&%V?;o*Kz75=% zr++iGcncZlUE=Ei5`SXx+g~^=yXxV63X-9c<9?67I`2v8E1K=XLgpT3!^Uau)fC5c z?|w!zvp@}SfWatwNw=!@jg7bX`1rSD&Mih@zNksek@UR%JFuv_3}wSCcf12)&(JSh zH19?b58m%Zw)4^BIWtFhSXxON^Zxszm9LJbTFekWcUc$OA-~6aV?PCY``!hJ>fTew z!&H>t$SWRa^9f_P2eGoY290Y4m1q+>0Wj65qN-}p;nM)k0^=5F@dLemAILGLMy7>u zcJCWjsc0U72W4S)p<*vFU3WuA; zMr>$bzh^sO7l&NCZ!;c(v4BiQ^gLtfB!zn{D^-i>C@APGK6jawt4b_ zPf`9jw_)SQ#Wv3~Fvs9}IcqIs)(t7v$R+Lu!f*uF@5Qmn{ z2S4KIhk=hCI%{VIx^7wS(*}ezPoe;L2?gAGfstc2@KS;Q_z4(&5&$-}y7(pq>OB)+ zev6raNekJIB6(}P30Jgi4+K$-`ne6Fa!lK>>zomn;P)ajPY<)r){+<08Mk)~qA3*^ zgeW;g$^DxEt1>Y`FuB?jbdN)$nEF3`3C{3~q9Sa(l5H?@Lyvf=g4KG@Sm*z2j$C$+ z;JE2_FOj%GY;0@3ws;BKH8ZO9@UOB;jboIShOe85vR4Xt?Va0e<{E>=Z3@o9BGs~CL|{k#cSsM3%1 zu;0RF_!6?vWoo}pdXLXk3RqlKU-uCN&~3&i(G05S-A7C=H96ZeW>eKiSm#?UdZU5a9@VnHMXq<=`<)mseC~{jHFFFMOwUBW8&$?D#wRSvpn->! z!tCF<4HQNWRes1U?K*5JN9bZkzFzflE!o0obCk0?|ZoPpmH*+^C`n=8xClv7B$f(k>jr#qHOu z;PdaAO8=tijGiM8z4aVL|G+67swM`2_+w7>&mUsTZ^MoIbA3k_>w{*&CVK^e8p+<# z^aP6i%%pUBCocRcoPPE-*q_Lshe2zmJ#@vCu9NR3;jk0kzxJY04II3TAC3?N`xyED zs586?hM@(w$Wercph2l2#KaiU-TS9V6fDVo`u`kvltjzUpibH>61`b174f2Xckz8CN#a-OTP1DYic!9v85(T?N z=96I3ed8TMNgO$eVi)0}l$9qMtSFPswZ;)msWWhj4Q#cmGwELWwQsMNVpNN6$;S^2 zc#l;ffQkx%MP(+uHO4Az)p9f$5i^EQXcHLRogEU3^fJaz%Pn{5O}^C1nEH2N&irG7 z?8XFg&d82HFnhruZA)=3ku54J8&D+ozIko!-p;otM8i<3V2)0}eGW zwaR-1G#nw|>l4vty=5f`h4@ob{)b^eOf4pk&J*m|JfY;bB2*y0xI_=wnYS129VK_; zTZt)O{0p=8FtY&c@mpylrpk=GQ%E3wYCF{JXeLizIeo}>Kd*Ey&oO1~mU-tZV}6I* zkqmPNGg$3gDpKKRZ20cFS5T;=s^fORdaB^oh#dbTb*-Z(XSs}`Ap?s&v0!#*LSfe@ zyMvj%F(9|(!DVN4)1Sc5#rq?H0aG1;u59cT5!#dxkQmMoa7KE}9Hg^qd}inD{@PVH zb#g&NL57d_OuF@Es42GW_Xno|540K4f?US>yecujZd~xz+@~i~PahlZqDh&eB8=9_ z5-07@fAmOaCX})O3w6f`G_79uGA6z7yV}mwymIL1PB1YL2&j{9zi&_al;)WF~yTV|y}p zw0onu-ohebkyjQFthVLTLlMGe|D+?VTQgfyNx>PyHtA7$O9o&m!g)?W|)Fc6fmT)cO-S>4P?ur1ly3F`HT>kcLj=t537Pin0 z$B#$Ms8s>rBfr{0$G+ai!Zc?2%P&7vEwP+3lP4zT7`23)j}I^1`%Y{JUNJkDb%;b7 z+Tl$FR_}}9yVH9Hb*7%!c7Aa5piU#~w@*$v5>5fp7X<_%$FrBrE~H{KqgaH`BR1ao zNS+a8`*iPb;YBkgzj;>`n>&Nt^Hc-aOk3|5@zpLHR-NAg1$N@3)2nlRWaF!C%-c~? zD$!4kEvbZ|IeGSl#92>W_JE{f{oL-m+2Ri(YdF2t+glJ}-KBEY`%A+=5i z7#fY1Toe#EC2f33ln1rEO|h@B%auzoaQ=ho2+b|0dGkXBnk)8*408FXbC1az2@kc% zpD_T7?8@64?j99ax#yr`$Bw^M{>j$e2OU*<%il^(9?S>_($1ZUtOWo4a;!kS?(7I% z-ek$w!}M|R)R#~I@hA2KbxU`ykkOtOzG#2OF;vA~9fpU5cP=_JJB{i~ox}UqUT0aR z)6c#E+!{$2ZnnI_b3MIMXH-joANYITpKtTbz9#<{(?jKx$P<+r%uBKJ1(~vIF5*PY zAgNd$>WA2(qXag1k>_U@mq$&ApWUMj7$?lpi<@%oZC>=vwvtsH041_HiXsDyH+`;} z@<&9^$HO=#!_L>C!*0-J=m5tX`Cowpy*IL6{|q!5xDkK_KXLB}`ploL_ceb~h>88d zdwjQA=jvmob0hMVTrRa&2g`GbJP&}!T+T^wFq-1WWkA5%wZl#1Z+)_Skzniq%26{Q zACGHXo`W5*12ZCKiw&A1 zyF)zJc9%f24y`x~nj-Y1`{Ijc`r4XB#@GH|P1%|ooxPOg_znq&@kK<_OW4Xo3A_Uu zhbnEwD%O77NTfm&(=dB!rs8C=^mejGzPHJXLb(#mrBxBu}d~K?iz9b+mfrUB` zMZZt|5Qt185>}*NumLCbc!8MRgs9j|>gMIZ`q%1_6c1u?VS(FR82mCj`ThfP%?^@> zH*z+)#Ey+S(jW_l3jPTa#(y7!fDJGb+zUP5tCNCW18lp!)~Dz0Y~o2doDWRg_yyk0 z5!*|Wjx4-^j%QX!dRA&Bco5&|J815Uq$PY6YvF69qr)#y3Lc^hiikOShTfgSEv8F? zHA8WO;}U^Jt+#i$;4N{lY(|TNza#hi7eZuXjY1$fs-XKc6pga^d+7D%c%FMe31(l? z{Jd-2Y4fE2!cW-V5r}bqE5jTY1Y*m0(g~qdYSndz+_^{U`(!0}@$N$MykrQ!KL3iB z>!am<-~@R(sN+v~JB#EWvjw?=4bW_M)l^K0{qGT6KfRZWa08-3cH9qV(z#WFT<=LI7* zJc{v+lVv>N2l3|s@wf-;PPIP=PZjzR9G8v-gLefprZ?V&i@gF9nV@albK=9^oL{q) z;1|8Lbdj;lfAWId?L+g0qKLFXr`${d%G(s&3|=!mM^DIOzq9aNnv(Bc#c=9>v6|Q~ zA=dte;{3z28GMm>CaaXd74|-JFps(8#xG!T5p6nUBi1y|YK9+D_d>J%dy^zH1=1;n z827GoGK8)DOIC}Oi zn3xDs-MohXfampOA|JUp!D#)bMwsktJu{4U*&$Pr4;RfVz@7@r zAnCzBxXc-r%Y>hNGd}xqEkYEB(a6u+LMU}<52{5##*WYgBQy5~XSChz@Pchxc8VpQ zKyJaiZ-1K{8BsG8&<+>_m`k$+&VwI#om(t>EL0}g#`GS>#V-Z-s=EMHs`D0oN2vEe zwZeh{hPhf&!B5LI#u)qyP4E_I6bR7PD#!J2d_OVLtM?95-fcAh@%E1G^xdwFW)hOn zu+{uFHqWU*yLT)e1ZL$?ukC`DfjsE5nokKbJC_uTU=Sy$Zimb5ND zq0*Db{yCq6iAino-HIbt{>pwcakD@(#7xS}9KO9iLpfbm_33}qC1Wr4XN2tj@`IU^ zGFf5OFxX6ge>n}&cqaERC}&4DB7NDY=Y+%Q1`_^#WmU1Ew9cM>1}LMQ5x`+~|1m!K zvbtxi!SmL~wW2tCpt@hcuU&_+3$E|@+gb??lWoVZ^4Ygq5H;EAY^YbNQNw;ae@aLg z{f^O4Z-If?RMb2!n1G4{qw=|^Q5Kd=RvJMACJ(}ui86eeXepY4e?nZQ?^aJ+&!`j= zo}ainP{~vn;EY8R+tvYwrouo;QTaPis4@{baOt1#3k!Lp)iJgjoa=V%i6reWeRLio zY5gH5(>`|RxH#shS{|c2C557@Ws3&9xYY|@mC^?lZ`4GZq(jG-&nV z$M>7Pm-4a0?bO)kT{Qf8PWPVd?5f6xl@IJ3;!xsf8GdX0@*3oOw)VA0_6=*H)?Dh` z%fIl>r6XVJ+#|xR8NX1?@->ZQ0EgRqCcT5q^mA_~T-|ISSCiTriOI>m;B_t3i|ZLu zY{2y#85xPQ`)o79@2yIdo_VIzPPN?yVXT3Ii);gepTD{G;QYd+h^`3I3lk> z7vY{BD@8T7YiW+@;;)>h9%HOkL|L@dhk?&KOI_mY_n)uss1a7FMA74XPADGdQJ~%V z1vv(zOubh1?i;Gnz4tSUySyb_G8p!KInqM%?do~Sx9>AxHu-jSAopjK@$2^q+nnwf<5Oie>l|NCA(Hvn|mnxCK`3~P1A$<0YybSYUhBXzb z(Cd<*GM*Ee2Xr{^w)YN=t8Xf)kfWMZ>3Qs)8Qw05^qd|ZW?ulKBQG8M!xb2se6FlQ zUu3q;6@;@E&pb~x78o!QiS(=ZZY4L~aVh5R{y13}5=$us8f68RjS3w%BZWYfo;aP?a7*_qLqdg88n!pUx2ULO3`Xvji! z|4--00aU8Qhf(1?vgRYPW9yCq7+1m3O%41CN=86Eks$BPysykL7l!96{48P3lJJ&0 zHuA4;jsN9j=%sIPQtZQjx!oZcC=YIAIu`f2bw58k>-WIG=$F!Ne`jiRKj?Y&t#JB1 zROgGGn46uZU_jPB(Ujf{LZ$%*={~k{e*%Q@@@2CT3dawLvMJvh!jKYXDm*$fut)<>l z|0)lMn|^6J>zd&pX@AMG0$V@VJZ2eYDf?+yRzC;k(L8nPrrVBL`UAV_2`}5ro8V(> z+4lK%bB?6c70ru=8rgGXH4&iw6oL08+=dOjTM$|wwud)V_VUfaair4=z{8B<5=PV6I^<@{ZQnMx~=OFJ)>SYI+L;7*LDI64NbM*bgcy=7RH zLEE;y=q>^2Qjn6CX3>a(bax4&ba$tqfRajgH_{y

#dmf0nH4e5YO^j1V|eR-Q+!CN4$MeSYju za))b~+DQ_+?L&Ib!K+F>`#cIGK)`9D;Th*$Z?_X2fu*s#q3K^PZ(uEx+o5=N%P~b= z#>_AH7C+p-_SAh^-e1c2KIKZJi{N?mPqiwALRqlGR8*|%I4mx`#F1FQPiLW{zZLYY z5e(95LeFx1adn)m^M3WJVTR8^#y;YO9wx9~!gA!Ig^q{$UMnf}apQ_#t`m2xDX{J} z!D-di)iJTK%(f?sZI{~@_tREa%^$*`Z{ISGjg373AEKgOx;e;cWEYDFySgb)tdAbX zyWyE_gc@;O(=;El$f>88t9TJ|am^EK%!^cwf${{Otv2f|H1uTLB#vtEif(c*0wz01 zJhCy?ho^IPRe4l?t>_Ihl8!!8=BiDv%5r%auP~a2etExd9GK_(QBJjLi6f zI`I%E_PcVW#*f%f0~yC^r?r>B^E?7lj$PnaH3A#5=r)I|9Z&A5Ed1v{Hl9pj7|*b3 zowQ2S88*RqehehTh)n)$Z%WAr#H4dd9cQ-F0tV+?_l(^#Xt9tG9{eihHEOC_WGDQY zt8z$9?ie7ylnUjPHFz*~4}atPPbd?ZB2%d~6b=DpC;q|u2?C_4AOQ`$_YQIK@oPJ* z3$0#!Al11BQeRf9y&tJP7MyN&Ozu}fx)f|}g(1sIWF#cHA)T9FWq^7#$#-)0C;4{# zXBt1@vphCxdt!nc+n}8Pc}DgshjDga86QDt{m#9sDLMaFr8k?WGA!Yms(V5guR-wz zy3n+*KpM=;%j-?L$W#M}&PIJCX0CDFQiuE>)#e2dj}rFNiZu$&dB1@~rC0Qbk%oqh zp5C|R^8P5w3V7>_hOFF?KGV-PE^=q97)>1D^IYz# zC@37!3=IuE{vLiOQ}9*dQEnWc;t5jPW*MR z8a<-$?_ik6ZD^EI5N6n-hW6udz0t9~6^0`1Y1xxrq z)tvshR+`I^4{hg5OgQyr+-cC#o(E}cC2nr788?fzQ+`8d|0i7Lk<7-}bVJhE z(bnHa`qm<{coWCBlw62N1VJ(1=~>ME1qbH0B?9H`Tt{!*J-tUkZ2GKCpo5&AtnTe^ z;)WlZCjf0fCWWF>^MB>fSo8A8UAi6ph;3u^9#&#&g&VyF7ggR&w|RDWB4^M zw}0T#%}4whU_p+G!Un079w7Wc+72uL9t0$i$a=U_L_IhOpeKZxerFU9C>apcW(G7V z5V61r1eB47Jk>)9_YmR&an7cdaH>W`PV_4!yG=5Kx?yg5_vff`TUuS8Pt!My2*2XZ zWnMx5-K~*!S@o?haElwHqF5S;R4jtiDoe?k^j7nx%N=RuIF1A^Uxok7Asp=)2|654 z`%O_xUSkOat$K~yAUI_~BBr+g#N7E_h~kVCX$(9&$kOuwIS430IR8mjgIqcgmwg}? z6Pb6t57{yR3L1I{h=61?SS5O_N==L&vhe?Zf>2;u_+ISCl6Qw>Wv!>1yo125 zAUL(PFBAr5u+s>mc3-*c)`kfY%CNrfb#MGH3uMSwQYSG3vim$_^u@h}LRWJ~pdU)F zQt(Q^8BK{(&-;DKf6sXu->PE84!;Ua&`9;~0bLWxxejXV$5Iy%=y_B2qQeeXgH-if z0{;w+Wt{xKmIoIDw4CId(82;tG5$Dz+Sy0n#o7>_&bNC2`jkUlqKLCrf$s77o~I`e zspDK5Q?H;F?t_-P@`d=+Bd(#Luj<1!C(Ak4Jos%$8tJ7wx9H3-@a{@#76esH^RS5LlvHMWg=w3-fzcj9@wrW82|WLnc#_tfy4eqtVx_uHJPE% z8;l?i4y6KtfTo0x#L}o4E!yXIO(iFq$>9mXG+cqsQp28`i8MU~KDcGi`kpeET;cLe zHHp0UKZ(S5XeY#Yf|O+~>h|93jg+d5gLmsl7$G$QKU&o}v_l589U=+TY`O4O`=;z! ziJ3z&TgUN4_Dys%3;MAiZ_6ge2I-$FfDRj8d!zQdsn}1LV*|i`{?~YzyozbNx9D@9 z$~cZx0#&^PoQyGpAG08j9pobd^u9;38BV|G0*h>&U@UP|Qb=j*rI%03GNh13dP2`m zIQhO}riD)YwOMKEGsN?WAd7z&1uht22-Ju19-%Cb5Hqw?+CfFZZPY$TPqGVIaCoSR zXvNjw=!RdZx+AFAP6Zt)K={fvZ~U`rJDzkZ#TCaqa?>%SXy5|HgR?4!TPPrMHKiF9 zb1;|qrTpj7+$Ykm(xBctBN8U>)-M9XbWkZAg@Hi0`|$f&dftD2scu@b24)!aL>^8dNJT!7i zc6;82HRg`G1rMdtsz8KbU^~XYwa5MRN_E!e%|gQyq_ZK_D#9ETPs8SEhjJqo zi}z*rdo}!D%g1Uj8ydbN{QB8*cD8XnKXh5n@x-G0%Sg24|wb7(T9N$R0oU8!gmOm1Dam zar?ILW;``5r935|*iU4E`jcfX5su`v=5|-M`8YK6Ji_?h_U`V;jw_aN&+3ZEK4QQ` zr@(Avo?fO)I`Ry}FIGtjCx=HXk37lBg&C}#S8k;L`tJLn6U#8a_;m??j?#l&Ex)5i z$RNT4%Fb)-sPL4-D}vnqxf9Q2MS3Cd@)m9jmb0m1wNIk8NwmLtzSU~QMZ;nE8_~aY zd#yfwGwQJ9(VURano_n-IN9_8UAV}Sf1)^!O1yoxbpuv4D|C&D;uH6KK1(;D`T4qiFb7%fUSBd9sJ9gl< z3#$jm>#V<^&d?eY#1>yfSFG(aN;K&>=$T<+k%cpXVF}ozZ=>(!7BpGqaDUF2fyy#_ z#?_J0ovRKz`r>^ZW4WdIxFTL3j7q&mI!+(^sb=C&tV|^LcFYO|OuA0dGrmh<#blp( zE$mux{{Jb;d!6=~cq<)Kp5G7}0n=KJMQFheHpA5Q_x-LN392%+=48ix4F3rG%rXRN zHjokzXSW%lni>Xwd3M1pH`$|{?U*#!5p3T&yd46~!A@EC?cZXpv$%m1C}CQ6g_~M> zjdyF(n|8nK?%i?5(7`Ct^l-bXWO86pdnv^lJT>cdd+^Sj#Wa!&bylMEYK>%}>vP?abjQl?%9&Bl4Upl_e|{ zKlu0URp_{Wy^4FWRNkDB*(%ea94oa3tBgT*-o@8``?$eoBFq|e+M{Afg~^{_2!L12 zZQ6Niia%wU0_sVRiwX;p_e4>C8_#HO^T|j!Q2OuiKQscig`<}A$|K-;WhvM?T%C%$ zM=`CcoZ%2_)txzl`bqA1pJ5Nu*v;yKsrE4T-<}hCywJ7vXM*_#uVp>#gy#mTiMygC zkMnfUP+EU5ed=qmIlW2W93KM0i%Y`z9BN4oeVNC^T7|-F!BAWAWNo9%h9p}W`dU0` z2hHE+WZ;0OxnX2LegoFsL*Q+*D$Bqr`u?pySxkxUe6qX#-OV52XLy`c#UY&%9E!O) z)>I_-f7Lk1q+Q)M=1&(o;$EbG%c?f2l-l*LVmeknCA~?oB(&8Q^N%uD=X!+&u$bR1 zAgpQv09#QH7bVP50;>Y@Q|~%siiNC*k$!Gd7@ml{>D=Sl^QPq$QD*k>r>Ck1G94#l zJ^YEkaaqABUFJu=_hcst?({)Hzv8s?k|5;Y>!!~UNrW=7O{wzG?C)2?{0CzmD37YiAEwFl_e_FZ# z`xS=Z0lj_(C9?lCgpj$MF=g?>OQ65$R5H+c)=o-b94cE)V#ZG&neL%NDX!ZsdH%82 z_}tIVxXTWK68qbcC~ZG)T8Gv|YSgA+=@Y1vU#>=sdO7XRL#`je76NR}@&m(kH)YeVyL z^Qhwqq55+I4ui=jn;Px^OpwuVkcfwJ_gBMAPU|k@mDL$T1%yVlvdPN&lpu=M6L6v& zoCoF_e!Z;Gvx@qn%icd-PR$CK2uM|zp+q!RhKLrCx!Us~p5xW&cGXsFHa^jUUFpa_ z{naKIo||#tZ%ih2yBqDyWcU&Za_xn5!-BJ;C~m3J3dKZlq$V*j_h%kP3%F5PL}G!2 zGe%c(CJ-Rzgw6N{Nv!IWwL>_>FL&qI1zOD(dU|aKgp>NZ#Z-<^#M=da)eFAKguwD| zbfd#}mk&Ez*)t;hs$n)NsBn1~b0Kteve4C-``wC-Fb4+^*<5Ki=_6B%;_C!- zp5dEz?w=~OZ~MhvhA(G>p4%sX?Bsq}L8f{U8~dnKRzehU4qR1X0>kp0@>LNRmla7((lSp`EIToPRD3Y1NBcf-cg|o3}-Y+%y2B7sa zMZ!Mm)F~B)^QgAg&ULq@88-`NNpGTHkL?O$yH$3ul9zo^iuEz9+Mt6KcaaKzZ`ygM zy7EFuL=F^`pEKF%f-T&>vuW_*yb49Ef_ar5JBNN4e^Szxw0Usaq94#x$uaHXMOk(M zeTG*-Q`oS7!y4R*U7JBLIbKymn6u*|x*af*%6^LOjih%eP!)RkX2YoL4__pv`pueV z*xV$d$RJvPBEX8PiBSZUG&@kI2#oDxq69)yZWykC#Q zw{9g20-;Dmt9k#{dN~Ikn*2!waDD8ib8X3%8%tSvS~WizF43(Y>FucZgrhvJ{CX28 z?J8(#(0Y8Qo|<_MFBzBV@MMYl-nBrQt40pa6;AGJTYmg#&C+T&j1*U-iy--vb6gWj z?aLyxOC3pzmO(jtl(!tU{K@)umlpPI>Twcjq0|`Lq9T1Lg0|$?b-!J>?$Rp&B5Dkg zr_IQcwO{n3LDNDh z^U1ELp$p!UOQ|VUWiU?~_7Q=Q(rQU)upEpnBF^gQ7HRz+6AcGKd|yawCY6*(U%NWD z6*U^39;UGM)k#f;!Q1n?!6*{)FzEgmRM_}2AwhzO-Lly4d466nRJnU{Isg2w@@StG zz}O1TJgJH!%&|FY1jeZiTIhbI@RV@#Ie{(}e?-S^$#E-KRe2cO$C_e%F=Gz#Z}tCH zuSmP%gQfIOCBIA;R=?!Y3(2h}aXjstaQ&60ttiu4^Dg6%>h|#Xmsp#u)f4SI)*Gbv!?L#aJ zuQ!~_z30C&2NLcjQewY{^{dvqX@Y|bXTH)QUJyD;D6_iR=FU`+FnY zvK$&k!{UP40AG;P{wAd#x>_Bdc>lyKKg+qY;*`DAUycBr{tzNy#+d)p^7$@dj~|{L zfUFU>NAv6I*Zu)h&&sEuX3Yh>aY(p+AI;oNQ<$h-pPg7l)ls0&D6i>)_ zQlN{uf6Xzed(zNty4NkVV4u(YWroC~lM3KMh;$Oq&wpS_Pozo|T1nXYVFzl}mwMUS z(LwG+LUZ=;agoUyOVhG&Rq>;AE zfLinBja;PMp+-^{U#j;GX%`w!m)0WBz7(btLX5Kwk-G{R$VfC8xpqlXBN2ZFOU$YAc>!G{JH(rj^ zVus0dj`>~Pt9PpHMka=D)gpm%cF5)Z$KEpP*}_03D8X)~qrbj4iOi3rGPvv>>7ee|$$zjKY*JzpGDMFj5exb) zdmL|s3O3fqq+MMeUd%ue#EIB-J3Q&=QVw^NJp_r@1mpT;N6+~iHE>i+5W=muwrmjsY_csb7mnW(E+pNLq5BT)8w6stY9rS^>x_L_KX+usI33qLkE843 zBvd15LEL!EO%8A7*rVj^D&O}oo)_hjN~a)Qm6Sj5GVYg1_Wkt@@k#ob^QO!DtCyR7 ze=7!q?9hkZ=C2X8xYFMI0Wtk(26y-s&hFosorc1{K@5czoc3T=e=7gx)?)S2Ox=h{ zGk9ZyeP_m!SEl=|5poGz%cTo03i_Q?C3zXg^l7lxtyss&D^IKMz-6`cETq9BKe!b6 zhzt=OOZbF)0sq#rjICuujt=szQhM$&TjWObuqaC3mKL}rg;mRE?cI(Oqw`&QfK&`XE-vOZ)QQ~YzU zI~N6o=%$m*3NTTW`RsfzJwdwia9xJ8parm9V$3U+Glp-AbWHywaGF7!@Kh6@tP(JI z3qAZEvLvMHH3CB>#uqf`zsKf%mLqZ!{Ua*rFbYp~grMj%0d@tQh(Z_4$2VmWDF6p9 z!`en(dZA-9*FWir7NN62JA3vVa__X%ucLRU+cuCv+(Ri*DE|%*0K0ge&i}ZSb|rn7 z03+P=_F_N_Cksnr%zzXZZtZfYY#WP%psD3GEL1!S$Y8;2Av+ydIRcF!Tr}2|Q-=FE z#{z^RqpNMPOy5%vcr~$^P2|Fg&4S>9V(o5XkaOBf^33t!%PHZj%SSO|dZ?j<;4j&C z+fD>5aG1eHY(}sT{a738GIYL%*%6lu3_HdW`qq9!tfXkHp3gbooLSTCwbJZ%1eg_W*;oP#!as zP#pZMJtl8d+1QhU@b}pz@{Z5<7(8H_kCmg1hxduaKe$TYYOQBy;yos1geaJ#F+x8P z+Eq^D0~6-=g={~4@k(o^fBwYDyiRL(0X3!1BPSi9`&>m$Zch?h++fVCCZX2S-~(zS ze`W-x!EWF&l8z?s#+}~`vZK!t)f=q){6k_SU<-8Fr1)m$P_T4fSBC>&0XN20 ztI2PcqF}-3cSrt*n#17{?|kk*w@Y1rPfI2$2Omb`COfga3%Vv;=8gdN++p7X$boPt z=`NM#t3N^GZH;WEYdx@v)!ULGFUt{f$Q_Rsk63ot@gnKfkm)P+7Jie+in4k1zz2GI zxY@;GI4;Gi=$@lc3ScujIXM9;xeLI0#b*Wt_Mtp1=OMEnn;R;=8Tx%bQN|L(JNUXaG*9l03T=zV)7$k!m8^m<9a@U7sJuk(`y_;UGN`1k8eh zGalCfHRjiE-+pNY;3Y2N7ci8^oQAKImGJ?{%@|_9{?~Ar1=Az%NUYAlWT;kJ zX4nAdTA%*O)0ytzJ`e1k( zE8U6K+2XRnpv+mk1wn6fc{}uukye^yULlt(^S#i=>U>&z(=r2x#HR^BfURvlb%+3> zld$ldM|5l~MyGwlG2p--#0K1iJYd2B1^5`yHfz8w9Dw`z7^WR9U{QmZy$vd(#V^>x2PMVojBEEg)?_{6tKPtUtLr}=PJVrt`b+R(LOiz z)Yr9r5^Al$n!fIJ&s&ur$ke*wavTs^cCWS`wZ2`}&sxgQC$4vRuJK*(5NF9NU?q+l z?fGvdToUQYt!X6K+3q}0XY)-u{D;5uN4NR75&pk`Bhmi_9HC4Zj?tEViSraoDTlF~ zh`z{`5R=gOLXA&Vg5l^htpqWQKfubQy{F-$eEV6531v@M8RJuc!H3nMVZuchwN?d_ zUkQahOJ50%^taGiZYY9RPxjv_{!2BT?{M@iGfciF@nM&F6|33m+1zdQe$#ikwZpL8z@FQErE`24aB=C}Ckpoza$9wJD{lhnWVv>^LZ0kQ%v~8&6Txit zYVX?ac3ccmtD}z6e*J@x0l&bOiiC5#&A+RfBU2|GBbBym&B;Z6C8Uh)^%Gz#-KL0Y zjI;W4-gv^cl2YBgkV?3k_5GT5ieorUc%lLNVUh&^4mC*j~TtRd@qkaV~wRn8F{~&sS4z%-Z(Z)tU8o(Ogi*DG!*|$7u1(` zG4ehN>382J1u4sdjB_&PI6Q0V5R1MHt{dlF8|5b$$J94`qLU@qqyj z0-6Q486yBTTjpSAFHJY#`1@&~42}|hIu+k*V4h-nz(L4EXt+_ef|PzgGGrTESjhU4 zktM1GkMn-mw1XYJY)m9wF4tIw0ab+g-O{-?k9G)`rV@*w?VYHm<)QvSSZkGv%7oWH z#y+0+9AX6`7{NJi@B$c%G!7QC(pii4jGo(bi1ujI1i|r$&t7Y(O2DzuOS(=ih0x(I{i* zZuHLxn)r@dKo1?(s{etq^ocOtP%8%iE-jJp?{z2KDgd>~q&ml0NN~4}G^{KCDM(>mmfqa4^~gJJX(LeI;o&LI zT)kT}cy*q$;Jsu5`UW&y$M(S28m?aBdgut){6wUrfISAV)fGRDaJ-g-{h~AWJ+eNo zH7$3Z!B5UQh2wY^_YY!QRy<57K}6ndjRYuQu8tpr*NewR8N4&L#TJisG%(F>38=FY zDLDBh6D;=Y0 z**m1e9|Ql6?Y#S^JWClKyauWgr$hV)n4^a{Hm*v2fSv1WOfpO*@+mM(A)117T3_dc zbg4PQT&{8+T9SC3DE#ygIRiog{OVHtizulb)^|=Au7S(9Iux zOR#-Na?1DHsul5nKO8TYI;vYllEBms7*X%7t4o>DD}e7mQy%Luk&f&EvJGOcd)#dU z@@_7OEQ}l-_a-Dm6j2<8N3cEh8P8A6bo0rI#+uPSxtQNu0k>M+&R46m$T zhjnGv;!ZCsy15D0o{J4{4jT7Huq}xh=xn}EYI&(r9tqVSStA92WgXG$2qOG7A`%n?)lB>XZsbNb~(DICnY9&Ck(wrpgVxslgExJ`+1a%V#EH@ zuof@;UTfsAlr`}5{Nj|F5`7_{b#HAk&W7>1;&mXRYF6Lij{vkZ)rych-P6(+m0{L{)bdgxM_2mbQ z=!#0;!o5ouEh*ifK_Ljk3M-ro)dv%>I|Mex34XKPwfP0|GBni3vR{Lf~i}@ zxzjXex=xjKeme{H80lOCLM(tb`EJ#<6QnL4^pq(8iA+w_1(T_Q{#fp|s<*Fj^vrA`<4eeXy+T1z6ht=}0ekNu! z9@dQ1Y@yM&24}WyC_tP|c2#v7!)M}7y zY+$wr;*nz*j@f*zzf22*w&#Xx-xzDuk$#Ax1ix-_Y{m@9SMFGsi~A!+z?j{CK){+pb zyQ#n|Gbx@gN6;$Z>=SH=(!*_v{y5AuF!eGxCGC6=V6p*?upRByP5%&^>*(P{A9lLL zj8Ai_H#W_y|4;y&D6xe>2>+1^s*NH=b{L@@FcUD~_dY7%dRb4hNbJe|k+~C=3PEx1 z2v6q{#6upL#E}8yH63631DD4lv!BRe<+&pJu+xuW2uvWN=l8Z#bYBNCoxoxTzD2mq z<1EyjyNfqu!VC_aI?YT*KhAP607BU8qrZ8VU>62oX>S*5zx4R)W_T{!4h+tmjv8V= zIxn0lh=nXuc5t*6MSRUd%^6bK!F^#S=#6jY8L+tam5<M^fkoXMZ#(=plI34y_ zQo{Ju2j`CIV%=^G1Q#<#{4tZI!7?mr`1-Q?#u`|0qYK#!tf<$Wez+S+bFK(QQcpf} z01Yt5hZm~9a_dSE)^Y_CMn+P%0-gJuh!D7!4#rGjB$hx=$2*ok6nR5Gf2TXFp1LiC zFboiq5QIg$T?*+~wzM)a+<2y4DatST8Z~p5dF*WO?Og}o8Z2$BrpH$0IHM9tHP`Qd z^us?A(jgT(qW6E)`{_e`1AVA9jbauRy=?L$VG_eB)hgAI`P!GX7dPw0&F61-CgSdC zSdufIB6iiPzpv00vgOzv{1plDA^XPS- zDE?7(C6%$S*8N-}m~F75P2RntYWXk$Y%Hz*N#++_1&2*GSsw^`KSeZRech9b#DCV| zBu$Oo6F6Ia6|9v$-@M@Wnz>8WAu1&pt!m?ShnZ145&()Uh)EF;-MfT+ynam42t}|x zT|qg`iA&>h+tp(DtM8VPv9Hr?tRiKtbO0|usCFBA;$M60ww`sG8p={1Zu}$`%9EP{Gml`iu>n^>@qgz+J%OpuI&b@T z=nqa$AI|tfhKOhjU`oPG<5STwk2`Y8;b1|tG%#Bx^Cq=lr%z8pWW^qL{<*Judo18z zyXLSiLQGDWdja#6>j=rmJZa1_XO_he$|LTgUU^~$M4@n1rVP?~Bus?IozSkFW^%A^i{&PDw)?c?%7hX+_! z_3uH+sY~MzlPXRN5VJF9`--js{Bm*Ec>hdrrJTx3w{Tz;Qg)sRWCFd;8q>Q%iHQ?e z?4aHqv4GNVjA@Aj8`2SLxgrZksI?%N@=lD;8Jd}&0#j8ZzwX9-&MyY;D>clhDVbk3 z`=dP$cyG4R=+Y}6To83sY3JEpTyAskh8YNXUP)Ljlc~0%i|VKO)GNW$ zZFkKH-ckJdaekD1Du1lIqy;gA>L32Y4cj%Zq&=t-25m=NF&TKdRSb()P!zL zwXgWO3O7un2ATPpo>+iv%~QJRg>1MvKR5kj@w?CFvcWk;e_=VXc;XeJ`JC_T%%*y} zzoA?_>FZnD#-NED)ZCb?B|-DJM_e2FvTW6U*F1vr9)l1)WSnyDmzs*M*3c@~Cu-N-A8DndOuYuhM{7vqcjid7?k+fwj5p z5Wid&Tkc&>BKO?J4xN4Ex)D0=7I)iJu|zLxG3Dh=dU?krLWrYeW8^Op81=@T^BMzQ z(easyG#9JZ)AQ1`Z~tfA(GPZyot35aV#2S^DGrjDW7D|#dDD~s@BI(!Qb%1MGqMX_ z>441G>DlOyRneptO3=BF(m?{56m;+O6^|(SF5)5FyEc83xLIj zZ$y-o{xwdQZ;~vg_Lpn4kd%)$G4@<--z1i6-QY-Y-G7((*Zz&yL#VBLvDG=eD{i_V zw``#lK3MQ(;&px)f^q$d0|`d-g&@v4DOVLEDCTAwBWMtBJ~N`#;q|sa8B^&hvX1=A+&a{qmq+I z4|MlPJ-PYB2l@h(1&QeX4l)-FPG>GBXq>{;B9&z;mLEZAi7p`@9}8ojvMI`UF`x!v z*N6u$I&5E86Py0xFg@&8z59+a<8P^|Ye`6y=Yy>B-qY_?D0^`J_>m8ZZ0t0toa_k9 zX@_)EZs-*IxJo=?nyPF;)7~dUqMW=p`HU5kCNcZFhnWJy&1{FA(Il(wVLctw?l~?rpa@{u z5nwyt77hm{U1jC}z6@a zxsV}x+Y?tpPtCPxce{@nR3OxSNX+njZPYs)*&1B0wRi7J+;ny|?giX3dr%j0zL&pB z)Jx8`jsi(VJ0GFd=gHhPxRKm-=PvKVPjC4kLL${saOH+CP1EVtbR)xAMoe>+PD%7$UdYiZa&xqm!X_4(2wdNF?DQ{ zNYWPK?-``dRK}>kwZHpLm4s`VD>E|HVy{WsKx5PMcQBSkVJmcVlhEOS8An_e&OGCQ z1&NLH4eVtoW*vXXjx;;JvI&vQr{4)!>SLf?Y~elm^XwRz{lm&08hWPf#L5`Yd+(rE z@y66TOq%aPnA8DWf^v-2rluJh1uh>8F&QzDL64)heDG24>GgEcGAB4htWJq6#&P^O zof4yT);iqE*}phWdavm%{qcwP@%jrKX3IK(qg?R;7o!Y`*QZaKF`N7qpI9@9C_AS8 ziFmvuZ_;U?AxeJYXuQAN`Rn?`w=>G%ht; z?_(l}ZswxhkNeLBohJ%hicUg#8QLQ&tCA|Igh zU8a&c+quj#8@|4>DM@h+3_eN<>F5!zR4n~7)7C$ixlOx%fZJBm@*_HGo275WMw|Dx z=ao2nMkIxx;Agh=T^#dQ_!0?lrybZxQeH^M=%kEI1mP1H(BE@%^`5$^m`-v-eK#xY zZ!PSwn!_CjaV4duBdYdByn|k&+*-imm)R<)3b|E%8|BW?IS1@de8crdXmEDRnGfFu zU<)rJnxc?0XugtCs7Tp{GwXiLH&ouaNNNNzeVR*pu(XzKFdO zqhOG`*J5rfhU9@O8(s zs-rY@{i?JqEP{-xwM`8}p?D=KLRm9yp&<?zy6wP2{jPGUC;%?sR&Qm)C*faM!-H%8xL7@_(O zPZJafKMa?r^pIiF^6s0x#jx%xv5MD}PZ*jh!FLGplwC(*{QF5= zwb__p#~i`1BBRwzTQ82sk9H+I{wJut_WLkdsdKl+5T3Cf4y`4Cg)CBYA})LfhgD({)IJp0fs&&}xhPU9KlbvYsB=)dU>BSk zdW^6%OVxI85$BGXJ1)%y%{KMuOKMI}GcVzhO1%7^7Jb3dbMGZwjwcyry9ugwnv}Kb zjY%^caeF_BpN!-ZrvLA2+s$FaI0_i;lG2q(uiRH9Ef2IC39cpKrayH>_`HvA3No>e zXz_o+Qd&;11Qx98m>Fm=hq^t~Kodnlw2St@~UDX_nw9(EHF5$@oC1g&O0S>v6|7Y zDCFDASM_`FJ)~n{zauR2>;VifR~#{AC?n0+5;C7xF%n~V|GNoR7*2VIISx>^aj!e- zggm~-7QHi)h~T;-U+{b9vT*%zU0ZSjR%t9_m3k ziDUKUsLPC-Fi;0W^b&K4{Y0@{GvsaR@MGp#=$C9F`jZ@JSnfwRno`n%7 zxeu;jBv&XD{VnxziB}fNA^j!oYUO;J1UZQOh4HFRG}a*5cfR9IWh<`m@Dh0g%2{hJ zF?6lV4)suT53N zixwQ6{Jlk&^_>hp`E39DB*)u!g2MB9G~tbd1vbwBVxdGV6asj^??`!1eLU|!WTW?+ zj#C_Gk+kLT8@KMOQRzC;|9*EOq3Yh4)i7r00_F7ifsVQM+wPcq$+>5cvq{Ed(>;D) z9f6=tZ{!iGe`Z~@A?6X{0`xDP06>Wkomz;{)yGs0pF~s2JTe-~i790<|EdkN4i_4# zT#e=!S@6r`>mfNZO(kwwni_dNLnX&2j-rE9Cw=voV!sx!FU~)NoC~mhfL;aMBpjGD zmhLCxQu&1&XE`+{jF*1Fqqnc|ufTtE{8X0y*MEzfY+x7Lh#Optkl-SeWUY5FlI?BR zd0qb)r7F*yBzD7i0Dw&W3)@{{B37^t0&G_9rvdW_Az2mhX*E38mEPKpgnf7(>-_$0 zoPiphYC$MFFcGJWjg%iRG!33aS@z_ibZ3z-wos6i#+zZtdBpTF?orY#2oJf&7Fc9* zj%=1dHjv|$lFw>iZr6C**?O?Hw*G|ODyi;_-Agcsm9K3k5Tpp%3gxByyzLpJExc0) z7N_2|(}14|698Qp&zU*;z$WiSE|g}khhy$TP2+I_xfBWy&Rd6O z4N|3@g@8}$==3CUs?%l%mdKCp?m(aNsG`w1VKrxkkaXdw`)f0FWJGfqv7E&)Snk7b zM7s3-7d9@tZjY;jzGE;xemN2Fqf2EA%MwI1$SFL^cO_h}7)N@)sPgU`?YP_Dwrd)1 z<8)!!hM`AG6*z|ezeC6Z_`x@uaDKlQT6MaRb|Mge&AfFJ6LIOVzxF(0+tz5B<1qAT zfH*@l;eUS;a`)Oaj!ab2R$@VR8v#3c3C^^)9!{h17RR5@mqhW|j%66WSR#+I(cyAb%I=LI$$^LMA&6^_ViDU1!oI?7uLqv4KX#Z#d)+&g(bE<|5&f-k9 zm2DClJ*rGUrk-wInKwGP5(!CcI<0h5?^UQ!x`=$;_J;hnQvAqRB;VDI%;QJJKO%{0 zmy>$zv7rC1ZkR<;i{6QjAk=p{7BtB4LC8>avOZdZspHSmkbSwBfsnDhI z;{I$8$}+ffM|W|pH)~YUvfuz%CS$!esx0f~8m}jX${8>9Y|^aDf0tWZxTRUcb&A~| zm5XdQOn=;Z6LtG6{n=j=m-4A6A1P57(D{vnWig8)1EUtWd_+4W{?tTP8ImQrEmwYf z7x!+Y)(1brQX=CxZKO+nd4P3rzr=@*`u6GX;B|jnSLEo|oE25%ZsHx6{TvC#Uz>x;M2=n~%1EJU>_t#?iC%QUrTT>_{#ER& zcpoH#kVkSzRzHy`34-M4PN<7Qg*n-y6nXRl7kFW}(r6JK7?huPB}yZ1|Cl-*NabxG zWu4I=_1;ip`t?ek3+tB|G=B?$685?%mDH<#`Fm z9OM7K2|UpPtE?*$$LkjmqzhS5PUve53ddcGEM9}90E}N@S2Eg?f-&V1*`Qt%JEodrez&F(JVcpdDuAAZI-O>c-e zSvCtc;R_k%%AJ;Z-zGZJ_r-BIM##^Q86@Iz`(#lA!7KSc(*n-`FTeA*;WyZfPo9Ox z68ChMxE%&qss?}9 zZ8%znpv7LKcjdrjUQKNbbfQB@R3Zc4H|F`1EHhwr`5V9bwB73RDxT=#hRyM$CU}82 ztFHcd^6e*OQw1SzrZ=XB+}r|$ktZ&Ho?As@v6P@=mj>%BO_x+`OZ{56EZ6_@5$$gn1N+O<7!bpE1x zV|~Iw{)wh{5O|L#Rs;>>DOfuw;;MR<^FUf1`AQYXb=slb&~h+qb?XB!n8ZxUX~up|CuEE~~3MB3yHUBgIj9UB4>sMkI|3 z&z>|v-R2rBo)-0z(+_EX+ZnI`i|NEds#`+EZFu|W07enG&r)%~w9Vx2-{J*H0nZIU z-Y~#t;DdCUSJR7#Jltm9+w8XE-I~!Mx&HO}Gm1}I@S(s__SXJR9EkW0zUM{<6ocQL z7)oV7G*c!FR`mF;p~X4|Uh)$fCVAF2d5HK^Z@-Q-LTA~^0zZFZ)?adi z^i?F+kgPQW8z?akkdf;G^)1o$?SDt}7*Pt^smdFubg*Q+!2Mdtn{u&wS2iIrY!8O@P0r=?)fRXopC&J@RWX{Tj zT>Sj?e&u_uR{d!QSt8e*mN4&2b{q0Ctd^wJ4#*)t;f)! zUq1M2>(*2_BMUg)X*e{X?h~_)rOO9$@9@GDSt(|vJQ`@)4 z526s2770ZJLO_9w^eVjtupq?(ib$xUw9rA2qKHI_6h-t32yz7k=_0*&K|v5{(wm@2 z30-<1{8sLr_urd&^X9$GFidiibIvYn?X}OW_5BFWGL|tT#L?=5B?Hk*OG_+M4Gj$* zpu8+uaLd(I&)GS5o>Ey^shua(nYOZeK_I=X5%}DmzQ#Gbu zQyse$CYJN(S8^*l7cS~9$GMu`vS-mKHF_kF5MbMD4&>9-*;0yUiG28)dB|f^(cL{jJfrXDc9V)uTh#uciN81q1L+gug~)9q3G%b ze~%xGvP{esEnavu$m}4BD&d`%@BNJKT6*re_AVld_*e(u5D7V&JTVNQEe1$ceG3a7 zqylwZRrMHXWKXZ~O)B7@Ae$S2P`eEc<4T zWm?Xe(cgWSUrph%L=iR1ll@hXKZ??8UJPTZ)Ws$QeK^36mq!gNBKt#oa?R~#x?a<8 zi$~bmi=6u;Dufo`dqz~O$bc#7<%R;L{B12yYy>N7U?{*ma~Gj+tZAoZHhz3lw87LRZ{Z|H*%!2 zK3mP<(9tpO`ct~2*eiQAmhxQ}aNULPCWpOxI4Wy!`>k`5x+i`KD=RGU9i0C3*>zq% zz_Blm)ck->0ImFJkkzEAl`_awD$DI6nkaOi`6Gfkipuc`ZBj36>9LK2NkS+6Ij!CA zFT?&h4qTT1h|m5fqz4KNp?LXI@&UJ}7a60OJ(o}aR!AF{?YMB@*){uM?NTF#M`8uz zSn=oAetye;qn$}KeM48uk4knK8I1LVww`wFF3zm&0Xxm=kOG2E0?+)JM&Gp zSxB&~0f{47MzzqJTwVO*xZtZ`o62B8cq!37Cy|=lV9vl>PdO&!A-snt+gkq*hkwk> z9V(Z_?MKq`^S^#pzzGVz8g-%!yHR-k444qcwAxyJgbi|afBwmaMw=3P`ucPW`c$iU zjM7nlED$`~7Nu2J^HQl)6U@i-_Ur#RteciK0URnRU(?&wc?*N`7p;gwLsQ!eYl_7| zyCV0sf`ZgR*(dEn#ngy9ZI6(6HauR)fMwQs+PgAvC1&KoyjRdhz_9_1KEHyp_<1tc zk8jKQN2-k!8jX%WMw>)<{LdTQ2+Ku_JWjyecQ}=P&2LGwrdW>EjOxE{UmGF2+EZ={ zl%wwd({Jwk|A+qTIAaw!uK-x_`lcpEIy$=RPb)kp5B+L;!HC6TK~>5INZ!)V4M#MH zK0XSZQdUeUMiHT*h&Z8^mzkM4tm9s-a=@x6MsH^2)a{kOM##aN4Om~Xy{>ao%r@Y3vd1A@{jS!$?!9eg~uUfRQFPM z?Et7t-T3m1E+ixbZX72e!5khQK4Miu9IG`7nw*?ez$+|NjqOo4Qf5_ycQ)M$JQAt& zmDIpjqKCS=yQ{<(5AFKxY}_}x1l;~u#EiZ1=3fRgYJ3=~pO;7F3Z zKD&IIvaKQfkS^^pHxq;Sl|n?SZpSkz77*T$^v%i;Mh8gY&7m>s0}#lx0V?W<#v%ys zc#Qvjz}~@O9J1>_K(_Gm--o4`^x3x|dH4X}yBFPeR+8%QmX^GLZ5W*|Z3p0M1R030 zD)`ccs`D=teX_|di6^Th_FjzbFknM=WLS7lg#scw9cH1i=I$z6&-)EYt7=r#$9qa+ zci6ckE$hFgs22GxTJ5Zt)y*#tjt_>=L_5t2tYSdvC|Skl(8Wx{4|4-0rk5}GIBX>+ z^NL%%L$xMJHO+Kq#Xo)e;N3g;nw<-4G{w-sxG(X*`bZ5#K&qQX81 z=;-Qx1X6vagp$`U!(}LPU^@SrK~z!EY;L%sq;JyM$>~1W6HKeZl#{?&M(}QK3j*Id zilFnwfXQAdA(u>%l94e5Qv6V@(u+1hF|o72X0K>nq22jMK+&iqpF4Z@h*a(7L|Sh* zIwvP*KjJahFH_|(w=2PuFDonC2pgY(>!XPjV-$`Cm6y5kh1;g+O68s5o^94pTF$-e z*fnuZuyfpd*P$D#<`*vty|c)J$w;-?xV^otk?9K#Bh%B%iw28^5|^Q`ZK>+Ve0+S$ z-N)~ZIPcrHPbE70b!Mi{>kBw3DPjkCmd|)l~wh zy#eA%yp(opX#q{mx`uWuxSWDQ&qBL~l2V!OZLM07>#qxt)qVoF2U1Lo9`KPtiH^8I zY;*UR={f;JX9M{2E7kro`IZ&7Wp7Vzy!>EYuew+rM%bC)0#E9uY)-CIO?>hs4LqeT zc4jRA>|gs3=#(smx@isZH zOd8PY(Y(sVL!Rv#6meTSJ6ggvpo=GZ%n5onHaO~9K?t+y`M|}#I;sNyoh5Ck%D{<; zFoJeg69~Klxa5&!tNEo%S{a?*m5lOgYIpkA`bL2FL)*H724KyQXG7_p+duLB@MPc| z*!FcRyG3>7VM>c_k#$ebW&i2)2wG29O-}syu?&~t03k7b=)m{Hu}7e&YFX}{-n8*X z4%%ijRvSc$js54spxdXm(kyf;gsQf)yQ`Y$*F&WbW!2b3fG4!M)gIzj7M;5`HZr)K zE*13c<%UeD9Wt#&?#*k!?rk=?wPG-sRsW3QlQYIIz~bCDmu%+7>gt-N>V8u{f~UmE z${s1X(Wc|!A@eEvX!l;^#s$J)86d)kDj@M+H>2}AWZ*Y~^N*M})8Cz`bMDKx0T%R? zLTkFz5bBm&fsgMVIxaQ!(eJ5tzrYY)1kl(*P(HLCboT5aVZ&#kG`AB1D*!{)pFxU# z3zkE5BF3rFQ0W3FBHKOcE(oesusi?qC)TWS{`#5{m7OhG-O4 z2Z`oauQYGxK%+ZvowztO+d(3ss``e5e&l`zIai<35od-RP1mnqzTn;6rGr-*~@A)$BY&Yi3#AwfZFX>OB?7rSjRAfo8mu}yXhawR}H z4u9aB3@m-$r9!sOy(AE`Deb9oacutn{@xZIBO~n^5D*woMuc&kH0$RKTl2x3&NH(E zhPy2n9#t}GC2lX>O$@A$Yl z1le5eHU>xGf~|hk+oyOK7x(=6L#XA@$}`*8T7%J{NBF2(Oqq9AXMmHHcHxc6`PQ;C zr%#7k2v4k1+vbTl#~?NevFhXIAdf)JDFLYg@bBRVxoe5P!E?5>aAtPk;S?_ zjYs_Ik>%y(8k!LUE}tsArj|e?nnj11uOL004&?m&q3Q(OT;lek5%_V`;lmB!FSor@ za@Pp3)my+Uocyo4kHZCd2QR$j~$Y_%{qho=Nhk23|fiuhaCFe0EH%xGF@Wkp& zH|_6LZ7og7`Lq2Ib`c|tvD)(eQ(nKKVeb=%VrJ$5BQ8@nu(C=8qvCRKaCq+p@Gx|D z=6QA~zk<>%_K8}`0y{v9oLZyaV38eQVg*)D#8CdJz5xUW`bN$ z$9dw!iHQbQO$_kRIAb-or%lYO3}At`o%)(G0pgdh%FC}*0~k$EUjCB!)#668UkmF8 zagFDsYL465+BRmr3>K@UZac>(CyRr+U`pqGH;8;5f|H2^sm_PR#j+l|+de}cj-cmW z=QkE)ezVk~h&ZOPJYO~z$z|oQy?_7yezQ?ckk_;YcGCM5V6KHPt*&B*%7|Pbn+VW% z-RvGGkA-1nM}-ghNrd35(`x}9;AL5YdcJ+LKk4O1QFI#?Wx;BQM@B{If#TxkKzpz- zgj9{;hq;nF@AKzfEz##y54iN?$rBQ+VLIUaBf%0NEI4uBeV*!Ur}#q8&@kG6t;bwd z{a56!Ie|c=yrmcLo$JRLz0{D9B-DcbqHXI_2|)n?Et(qm1T5~h)SWFsNl7DlC8eR% z9|oG+@%=S{W%HEO(I$H=y_U$;O7AyF$IRwjNxO>!fV4giS9pb&m6d_kD%!dCEm}XL zbA8kCWsopJN=P^|RB^4$?V(;2=Rr+P&Ghb>#$tz77wt*+Lg3}aCnR)D+QBgK1v8lE zTcTl*vQdW)9kIwWi{?``1L1Hps2gLki3t?Z)FgnHUMQi{4gY1nk!jcvi7A_78 zZa^Z1n~fsu&YBBKOPg$NZj!Q619Egt6fEs;-0-(PFSs(xN%JAW5q-hpLR(?D@UIB0)8x|W&6I+FO0o8mFCAsh=Y1)=oBcN zt*lre@a^il;AkE}Y92qe?=;?`KTN8oT89m7V)Um$z EA9i;B*Z=?k literal 40985 zcmZ_0byU^O7d3tXDWwD?q?PWHZk6svT1vV*1*HXqOLt2PJal)1fOL0v_dEA_zQ5mE z?;o#AmVlSJ^O-rb&))l-Aw*GL0{!{x=MV@4T}twUG6Vuo3xU9;p&)_pG`rl|fq!_N zK59Ct*qS=I8akLjvUB8PVX^-IU%+hZ zV8%kHyWtB4LA8_Aa)dxI4PhT}zl8J6A&~SysSl#6ZYlcGV{Xsc`c3C1#m9 zm2UK2EQ{BV%k?ZHqpEg37ue$MVU-*IK$ieJ-%5=@q6J?< zcbzyzl)xvd`Pp!xuov)=pew>&IkEG_FAIE9ATNP{3w}V_neTN5Eo`vylf7*?V${f< z_tMhOGcz*@0!K$X{vCrOAy3NCkRl``M3Yf&@Mi+kaqrv6gcuqHuJ>YMg9!-)XM-Fg zoUZ%RE6#%_J!H1`aCG1OqA=?=a`riCr6cD2>Y zR=V$H{Zo=>!vIr_s;_QUAZ*nN4tIj# zp?hU5X)G=G(Ix|NqYbV{;*qIb)~_L+m-~i)GDJIjdMZ6GEXs_=#>e4;BO|ZefB5-9 z;Njsvaf**~7X13vdf-yCEih53S)zV_fA7>#4+4;#>A9lp_)igvzObi~vVLG^6=KH`vNJ!Y(-3|Zy%jlc-_I3hZ2jdq(N80Z0yafdXdUY() z?v2F5LIIOJP&-y#vZ+vgB_|GvmkoEQW7>({UQ3k~tEi|#=x z3WBk}e$jGS&vp)RFAduFkn~KK8^I-Tm|?t?h**!7VO|NLNh4=s`q6OIoV-`sP})^V z+3Y4j8XX<|`%?)eHTCMzQQ1*MtU{i-vYwti2qP&eDKtX%oSk-2aO`G3hE)@CpNl=s zT9(;^=yW_@7G-X}{#U=6!p<0zz!_u;J)(R^Dm36|S`D@>3k6mYAI#YrL)t zVWi+CfsfBnSp4g`ymco&DQW2}{T3g+3k|4+q?8mYG6u0hs~_C-!DR$#1XxOKrWw=u zRjRb^^PTaaT$y+-_f(&U+mnka{hD>{nuKN?^`Ts027m%L+xn*eo&<3Ef4#lD-7CW( zC0!itIQ~q4l@=4mq$yHh6G;sCp{@{t0B)25!r0! zdDM$FSDc4I1j;Wpd!s&oz6#cknxDTxYh({R;?`GWQiHYb9|VD44GAWe=2+46d~Qs9 z?&g-TiHQgGpKdkMWh7t^cfnlIU5XqP8{0KwmM*8Li1j`YZRKo4*mja97CZ~7;9C(k zxnHz4Pmy?Bq0Jj{+M3N?yy?D=ykU4utNH0ZpC4{7^m^_OY<-R9YwhpB;>|mb2o`JC zM1VokU$8Vr4JC6sK0RE4?_Rkz8E}Imx6ox>v(O!gPDH@xM0>V1lAo0Y@26IzZa<-> zVgGP3RcY9PBrkCCfz;=E#Z>po{{{2%q_(Ze-(N~Od3n)EN&SfUI*Je14_8YgVA4aI zL&tD<1i=8w3(zW&d#KG;By-_f|VLerV=c~sYZ#^>&0+SC@6=u&8~t*NVzYjYi!Awfu8C@j2u@va1wot?d~ML|tJmmZ+Wm(dF% zX!A0o) zjkI{xjFsM&-#-{%ES=M1x;~pvx)CYgx%&ykU%J7j%Y;iKs--RwnHBVmHgI%5H!gzR zZdt^Ni^y`aIMa5i8M3~$RcSfJ905=pX@rRF^Rt0?maBT(o6`+65cA1dbanKE4Jri<%rwFbW>D?2 z{|n9X&xkCI$M7so=gJpsG^tM5u&=;c0mOFfA#weiZ1Sc52lry{U?RuO+|pxrqFGvB z&63Yt@qG+EIKeb@bRpL~bs69&NNClbuUPdG8kFZ;$6=_KMs%(kz3Y+fKkB;?(u0g~9bai!|?@ol}r+I`HmDU$#2aQ`h z=cg0qLis)q%St|CS-o7A4f+*=HD?#v_VY`nO?RR70|1Hr>GA*&w9)D5BLSE~D6L=x zXWHJvmgC?RmFP#*XBR&qxdA)a3N$Ke!Pb}iGhlbmz|y=VAz2vhuo(NLl#POldUA6D z$b{?pF@W87-MUDK{Cpn|rCz0q?tGw@O=zum-sAHikXQ#GX=BG=r=z38A1MxaU>KD6 zTZJqN>GbH^f;_lTi&p@{_O>Yi^W($LLq%+$WSbmwZ->`ig)u&liV7=QAqZUgX;l%* z^J-T&CftA7V?kOm4=R0VD;~YR**%Kq6DrZs?jJ+*e+lJ<>LGjY5?r<2%`7Lyg?1gu zyOOr?*?@oPsH%dR16Dsfd4@yHmlb(hDWndhlS+Q4FaI%5!Jp>ROR2Mc3$H0*aPBOoXERA^G#6^75@ergQPCeLPq(R7`o*##RB zx6OJdjshhoC-nDkR%*GV&eCOFC zJKC8F20iYPH(TnXg_~-=-jtOZPp%37wv(|)_E{2sx*730AC+hXt5dAslGYZ040{F# z2ZzGQx`)d-cW{C=D^1ba*w|9+y9p<#Hp>86>+kQ^thORd=C<7ge3pii@|j;_qkuf$ z4kawQ!K}2vP2r1(DG=oz`K{op>nx-tXk*$C1hjD4^)U;AfeW$hX@KU``{OH1?I z?N`F>)O!IY``hK<6CR6Rc-Lnb>FQoPf&2z!71I3l=&7uta&x^F8F_t!Fz-C2D{%2w zrC7HCPgq#E6b!uEgU6^T0`OQ1%y)0HWR1o5<^@;sLGYt6zzJ=3xtS89@(IeGJa3xx z>_|B6HQm6uA2Wy>TU*I~iRtP3N9AK<%8ql@)~4p>J1=$bl85L_pZJ?O?_fOa=45CS znoZKI@bTlvydhJLC4knucYt9Hb#{I@1MHL4_x?lzhjq#GsA;#Sva)ihwN>N{5CLwv zan7D_LZe0Brw5_3r$6s86CF1PPwJ1B+XAQ!4(IE}IpxL$9e#a~yez&HqfaI2)BMIq#rJGucG;A?RCmOnsK0@W%8iFOiG$1d$sy zuOXKDGbyV6NyWnaxQ2;-I%z5)df$hih0K>cA8p1i7g0sQGUCA9Iz9 za##%akolhPvI}@!AMYONnvCU0>8+ifovq!Ujg%cq0xTRfOZV>fM|@EjIn(6H4M>OC za_iS`-@lKx`1(SkV`8))ZV>cvm3d_uhp71=~08A`KA-QoAQoK2v{6t>!&y>$ni{<;xj}s!!@0Om@yzegU z`>5i7yPug-E2Iqqridw`r1a7(#U6=>%j)=c8cYb}S)Ge_{s94dx~_o7G3qrYgomRE zJ)En+BOoMl+v;7c!CueH%iDOnTU7k1DiknCxM<@!JPVc?g4hrpwE?NCC0}9f8k>!O z#^u+7$b1aedw+TX&SuSy0m!=py>#wnh_CUGx7q+dYU*3w>QE%wDq~zO;uPXOdnUFo ze=>IGBk2LVdS^Mw>agCsd#7Hiqvg%d%^k1X;KKH~GkEt72^-rVDjF z?+Y~uwR}qNWQq0;Ao>Bwn3uQ5ub_Wj2HAT4N^4J8#-xzB@#56~UE%NzB3rEh6yf^N>X z0KmQm!8rgJ&%i4UozXALiW^yB%&V~)dWNG}AN2x2@gHC}@0vDB# z&?9VQxKa`x81lL_e)aJh_12oNDzfDrmL-qnmjH}`*F%O85^$_Jz+{`G+V+E zK*`y9jDkn%-qu#n($k~s<4L41Y&gJd+&f2F*wl++_xG)s0i}fP=gn672wi?kI|8P_ zpJLcvYBR{i9CWG08ZG3G)e(?qn$Gw*KTkQ95?-9$-t`lmWR8C<=HCg$HTVO<~EeW%~%DuuThiMclVBGP(-g7flLH-0$dFPp6s zJd3`-Pq(0}7ix_irEMX=`6%sELqTk?cwPyY!welkJu3`|d2s(tE43J{@2u0q9BEnL zNw)bzewq92npP_Gy?AEKw4&Bz`6oUFmr9uFX4Qq9Ay8v_nPZ2Ed+@Wr{Dek>?DCcx z0Ve%*y1D+BLkQ;DLoA*(>Y@n&!v39F**eNNEab*l74ds&&bl1mH>11=UJv47mqIrV6r^ z>JIz!yZz-$```b*3D_3lZb_ZzwUGFa@HuOIms;*ePR>5v(^X7)7Fbg6P;B1b!Y!HM z(06UH|2323-6xj+z4^}uwCB}dnHuwY6#i#R zI!gd$AX}!jX#YxVQ^BDDOrXUlc6lSkka~2~d)5<*J_gA}=KG(okmP+2GXvb*+>(Dt z0FukVAxAq;C&L@pANpoT*e{>hA6aDD4uY}X;VN}{9NTkVG7~tD>Xi2LU&GUxXFPKo zGR<&zm_RD|AZ|mGqTIB8mX3}@I=+0pXo7YioD+bwm;4`tbyca=NP@dX9GG%X&cO?P zhqW3J-;i?L=Hh;xwDa;^j|(=;0ij8;gXf;NL*QO;!U2HL+0}Idutymr9snAmU%t=+ zY}^EHVu6s^&RDK&Dqk$H$ADRKJ)r+62J-*K8qgLx9y__f#fplGY6bR`+R&`{#s5>W7dLjM2^xqk!_=>lM^RU*_$xW4LDO9jc3Da2}TiyKor10K!&;Q zTXZxw2AR+xFlJyfak|$2EpYwVpFk>fzg`I{Dsu&BS?RQ+40G0+?+*EaY1IxSMN{(@ zuwq6+Uop4=(FQUz4zLkP0lP4|I$V%=uq^{~PJMM0R6%?k8C5n=L17s?FE8-%uuv`G zAW2F+JY#qYrAFd>mCm`2(EX_9;L*EAkSCt}DeeI$l88G3$TlKBkVayF?h6NO2Id4q z4x6s@U{(*z#lzS45=|HKc3b(557fg-M^H?3bUTUbd|T7iq6~1%{(S)8Zt&a~n-oAZH$YrH@F$L&v_kjzC)32*@ zJuNLlC8b$LB^bksejja#t$8E-);_pvQJw({pWAsbFD^lgB zo8MS)r7?R4-IAo5**1b`CZRPrpov-8Y%1(5>_i(Cod-j@Si|vHs+nmd{whh)J{e9eh-B@<6F>1J9#d-)b7GA-qjZGN3aNf|t`6 zp3FdIMnrSG2)*>)yfBuSk?ip zoww^ihso#>p}X+A!-hz0n>xg>E-^_-6b)VHS0Fj_3*R3jz})TA0hS)+BAJapneVlJ z8^FPgM>5}gHek*c>op}wka~~5vAAU0rOHFLFjV;I}$u?-ELt~VT=`An%AimY(v+=IZ)8i zH-L3VB`mzO$5+;L`5IIBp0#GtgCPi$jGB)x3Ftw`+nxNHD;1C#oGIz0GYt5zB_`+N zZ>zi_QdCKTRX5U7X3P8*n`m6Xs?Z0zQ+gWmYl@1(VFU%--+KY;yOGq9FBMP~HlTI) zT|AM0C^}Q!f^4^YdRo)AQbys#N}x_RR(&dMhu^V%NA7?f^nCgH>2%|V=au3M&+BKZY-xOibm#X8s;0&VvB{p_@-By~6he!PsTVG#a zip#7yFmPXjS0B_Y9jZO3!fFvisveT3a)qZ-vN*~Njwm<^h#g|hIE!=CuDTr6SYk-d zgPPhIAL07Pa%Jic>-RM49H@Z(+P>kyW;RS58WvU*S$DIUe6t$Hat+89tYQTIq&N=q zPDK8%9t0#5tR4i@h;D#z)dA+BeWV3@Z^4gk@~F~<)p+<;0jmfGCqX=PV>gp{wDyE( zk+f^InfCAGp7EFCQS~wF)c)Dqo6`49ou1YN^tJ~S2qb)bg#JYl0Bk%vIWZ8aR$^e| zF=&(;17_?6Xf3Qx1ze;wP%8p1#K?P0!A=+g0sR!&(&D=($p3HNE?WGg!>}w_kRli& z2xmpX!?0ZSBbxXwXmp0akVe&&<8Uy79y!;7Thchk7`;rp1|xo;Yk#J)D3VafiwCF) z6Hq^b6l<3I1InhV@d5GwSwz}B*|lL}9{9@W-b8i62@zU^)5=9^@@L?&)+B#+b&%0k z4J!+gMg}F@)Q14$l-=X}3uJ6;36p1hh$)_st9K&f}!q4Ee)g z1SqJZL;%<07}$ALn{Hn9pd{8eGE(*ks{jV{sK#lp{-n2%CXP}^mcW4o2!=O~1K*o*|>B~*VM07berz|vwoQ(>Z)YQMI& zM#sWJ!@@FRiAN)I13ag+~4SDGKOClimlw;>_LYjV;Ud6^ABQ_hVzdUE3)PxFrwtW+Iyr z(*IrFl2#tc`WS}t;)M|qZY3uvg$SvI6!msGN6r z0nASzeeFBYxmk_6(ef11FE5o=j^*k@X~GZ>;=XvrqmyTn{m1TgTj@A7lUb5ut-w>pQ*b=QEfkdW}N8H>%O zljc>lBJSWo!olpQ#zWtOs;OGw>cPPZMZYx}Q#=prps}%Rz#`HE1ZdZ&M4dt3=Y|TT zU?yNglLMcAfVm+YsJG+ov=B`7A~k(409?*2CW(N3!c|q{X$+-(AVYvtvKsKGLPlc@ z?0ffCxy@eLnR~4?s|&ba<#Pv(*Q;T$4|LM;GJWCZ$J@O)FH3M5rQvY*<46QVWBEVn zB1V;~+R#YHOleH2aUl{b%0F!zpzJKcAqeu#h5?od-KE$0u2_ozpJjO{^ME0X{|znh z_X_1!N4)2Hrf|6A*FTx>oR#ab{&P%Av+T-njm`kqk>k!$FO@v!BS8!BeY99+Lyy=~ zY1<}+MtJ2MBYSr`piq=iP1fxF2ub2#HW@RL?sBPZlteI=w zUbz2zz5go0vTT4~LeiabbJPf`W83GoiyufPHUTI0q|hsIp+l z&R72fgJ}zwHC(E`@KD3=-&ANBgSfc|-cLpJb^Pve>I2#4Kf<1>YyKSf0NJxd&xLML zJ8WqN{`&?}z#Cbgm?-K>8gJSBkV3W{3iJk`cYoGW|rlZ@Q+oZ)p$>aI&^qX zSSWW;D>`u$2{RI?i64pm z)|XYTjcb17tM~2q#jXiV(>?2v{Qb|b7`gnv7wKPN>W$=veo(y@6a!Q?%k3{m@}m#p z?$Bki_djCyKEvE@6|Esn6@}U6eA%lAib=a_2~5uUgK1uIt^zZM$GdlO%W+hOjIuL?e|FLS_ih6Rz8Eati`Tt`_wYjOi;OhU9i#EogM##uhfBn>&P-p+IIlGr?X^nb6F z#&~bf{;XSLDYkmg@*WMd1^0(ZL#59T9Grl^@c2bB4zrFq*5dyyTqWH!b82YG*VC#w zDcQCf$UV*8pt!;ityA^I_U!ln)Qs8cpkI5_qRGLyZ|4%@XJ0LNVO&|8^YiIHrP_pjcaE<|uD(=7`Nt73~zod%{KP@8vYrGADq}_BPA9+P8(rh)SNI_8+Zhw8xEsRGo z=LwKKcX2zIr!XUdk|J4R8Fi=ZpK)fNo_U*vcUrJ{k&aJ%@l)2Y$2Mk!i!1`gA0P(u z>E;nP>XfOf`!f|b9NTp~K0c#Z3BHm~bqh+3XG!aA97R2NH^!C!eRh{!j<&$cl7uTK zTLLKi!u(&f1&o$tsNx%plB0UPOK6(pCr)}gZ?4k02$)HgWW_~M%OA|xou`*=I2@Hf zBH-%lxK}(0I4R0q2*ENi)2o93P!b{3aa^M46QnT3^OXL4?Gfqa-eDZGa*4Yw{0tj; z>KW%kaP#f$=W8j%mgoQyL2TGb`r3o&p4|2tEl}-{VIXkO#G&CTv9WfzwbNi&BxdF3 z2K(9(!3CXZ1SUDH3%&?L^W1Ei+2#8rLeZpCFa_^6ekaL$}R^u}W;;W$n}qB-Xv z#92dfW#bWd4lC_K2mT{PHP#JW-_q#lTM&>Fsjx&^p83mt*WH}&Op1 zd(q09-wtn{6jbEs)=gi0|I^l7Hud9+-x%%_ZST_a()I{an8k8P?aN;~(8`jt+5Dbt z03^1?^P<$}k!^#E)G;`I6=*1g&)}3u*yk^E;G|XHvy4OXMa-07qU?86a6PZnX!xQJkvl^9tgKy|Z2`AMY=!&}z{8ULLpEXY!gL?G=Q*4HjnzvfKZ#av8O#|2As6@-J&1amPohq(cJ-C z#a81N+n#V4pqj3f(=ZX|8k6DUhy(Z4AUPlIBQUG`7JQQ|{PW@GH)6lfcy!CSj=04Q znN+=Z$1r9p;|TkV*rHf)y2X4{djdlO(&w(C?rG->1rFC7t>1d-8XKGNnIqf&`4F?y z6g3~y%7b#a#I|+-0UqGwmJZ53ljq1dzNfHhWbAhJ7yX`aU`VT8DJn50vsiE=GL8gr zx-UqD2}EAi^uwkhO~I`J$0Hu_F2ksM9u6GXp;crA=9sx4q1dMFiO8AO*R*xCX`vW| zXNEqr*ZIA%M$J^sCe5P%nT!_Kw;xfr zG=iYO=d6W5VH!6tbY1RRDH0}Z5SxaY2cjQVczwYz|035MXjQa(V z#yt}Uw|_7mO#4$fNd}?UWqS)@MdfnUqrGw#d8AWVW`QNJ#88J$mC z#SMI8|123=OB80!z`*H{3d0gH|2T#5?|te6Lr#&CE*64S-?ueImpK~cNbsb+bGw2K zu>QDrc|54n%8h0U?7lFN=?_Cz=-gmSnCLP7#FArJVtByzeFik$ICiraP--U&>eYkCoAdoQwlN~LpL>5UnYU8f`6B_L{QeN3;4<(qQAq;~ z^aNTCT0tl{y{IH;D{Bx1XKa;s+Fv$Y%B@M*Il)Hie&`dWQ+S!6=%~M9qjkzwERgPi zXEVN><3o+JTEIA{jK#PeNM7 zZ#`X=m$s6|(|>q%yvgB74!pk>78W7}!kl9ctX)wKm5f2VQD7tL6ok?vhTW?@Mp(z< z63BTgLNhu_cg_7`86!DqK|P!a9Dj_hh@+=8)0paLeA-AjHs!?-pm_vH=Orm0rEZ?n zOE;3$^oX@#&<>bCmBY?fqb$y8wPXoSOGeTirZ;?oRaNS+#@%~X*1BAa%g$KjYCDuY z_y2a1S(}!?Ct6>b%7X9NWi*mP!O|qJkPiLBhOOj?^4c=o;eyYaIpb`S{8o`glSW9-Iz`%C zcEk%na3$tJvyN*U<1H|JF-#Hn5(id03^mazsjoWKD7!>D0-XmF_zA%wtI*8Nt?Jnz z3GO7td>kE9t6;w^*(9U8!r!-ADu+!eCBFQ?R$un|od*{JUT``?{LDI**r8fhDV6Qx?8=02r5VR$S zyy^76Hb7s!YFXKGLRRlEHfJAv`rDq~T*>-0*F5Oa(cWHSj;>#WJPPT;50i5_QpNQ| zeuL`R%7U9xFhMvyai2}8#N{h-7XdmBRkxIrsGa34M!wa`tQ_MfPz%J`*Ug)VnWlQ< zn}266^|lmzQIk`>3LLZwcuT`}g;W`S^M)`sZ58mqe4Myncn21bX@E3wN#fb4iav z3n}^%m>J`zFQ7Wm^R9~6+CqG>Rdc&zoSpQj28=f}QznDhW5@_es!IV8d>kLm;nhiQY_M7m2zmQN*G- z22}nA32-OqN3t2l2%+8I&S>GJ7l>WhU^5s zCtG1Jnc#OFCKzjkP;vcTJQrO6aUq9FMBO!KakX+1>Gy33HqE9;ZpKr$Me3RHQUJvR zpq!y%yO~oxJHR?|TGO}W{dAmk$L<4f#`iQJoSL(Wl?5+%n23l~XP3)3~ z5o{H^HKta@BccUL`LK#5@Kgx`+d%8w?!`5*WFmkeNd`ROGd^liUPF9=hlPhH4)ixn znST73dfqipik|ttsfHNgTnHbHVci;<2%UxhY&`i9mhuZ_EDlelFYJZP6a?&!eR%{Q z1>(yge!}wX_R}lPMpQfnL^-M^dGoH_lEra>XR03lc*wNCR}TmNF|dcr+l)Z>oP>pi z#YGRWllLyJVKuILX9iez-~YS=9mk<}Ol01k_Tf>?&?>VJ`)pXAS@W0g!aj#ZZKQ{; zUJ~Vl9HTx868!F(*HD^q*|%up$7Dx5^I>xA_p*55aY38tobET*?>mDun@aJIexIFo z;ds+5U$QbSb~%D>4_L^!k5h9yw_U34QA_t9Nm@Iv+R zvZm!{Lc;VIMU|kZz&DKOb(*>5q`SLE`NICq;;&iWizVd;V?H`oaAOU_H0F4A+>bsr?MTH&UVH@Yy4 z2^XU&&va-?6LM6}m2*&pHKAHrF?Ix^uYn2y73i|OEq}$JjzvnUN0I^=OcNvu>uLvm zX%N_%) z&87+tlVYPnkFn0A?xhfhNz&<+zXg%Jj1aq<-8P9Q)*-_{8z zn^d@+d?xk1w~u4i1*@0hKgaY+YkX`h_{Wb6zMhehNYEcJHs%$7>MYxRHKj(5{*2`9>{f`AQii0JVKheuaD$@XI`^N!nB?aB1H=!WT+8 z7Kk3ZAOd5e;qKWu*F(K->NFeIdVvK=f~fmyj>?BfwDVmr5`A+zt&OaT`x-^7n0IA^ zj@hE0XT1KqITsE(fF(gO2lQXVkqZf>0e`*Bh@PIlx3ABf)s~8!+z<5gltp5^{EP2@ zcb)L@=fy|%I5G23fEuH*&PxAsjruo5UB^vmPN7#6{_3NhvqIN z8yVjTg)sjbLV&&x!uXk*DktV|OgWOk23oTOfF-KoJqQeLzn(S2*?-Kf1yiz(PGWvd z=^~M83_WB9P&hnaHYdlYs;FQNRgYH#4D+q8<->f;J(J?^A1%51(%;QDuA8ZQ&P$ym zIMBtAWH7QVRKpOUSy^vD`*$m7_kc)BOMeDYNJ&GZqN>^n9OU8tScaJvU*Rx(mQ8T+ z!1#E%Z7`ML=X&tVw+Y;~q@exp9jt>CR3%{TQ#zm&lIo(StX2PJ=4t3c&NnwoaS?fYxZ#5|6LcUM8^--AQ^a5qnsW5cpi zBS4MZvv=-I8A6rk;ks?l;6kU7xdy!5B`X1;?q156DheTaGP7#TrxZ%hc2pXJB=oD7 zu;PDmqqwm#C2;@bWm=rKUh<*9ubJTGUUKTTyr6JxauPZ8OuMQ#7J)j|4lZGgrh3uA zgiMFDN+u{IPSWMY-IEHxl3R|?D!cacyRkSn^j(-$jh&P@0<#=;M>a!#f(gEHr$bK}^?@(XR#7NvtkfC7`=X zekEk86b`<@q!d_?&6?OYDX#0YJglR zvBn;o0%ENUpaWJ1eDkI92+(Z97l=JyXh-6D>!q&=>XwR+%d>l;)@SYyE&}iYzfO(W z`8xk2+GrbJ$I-V9!-3=K*sC6zRO?(XWpKdLnaDgKT9w>aXgUhn`0^b+CeLrfInL@< zmoj}E?;jj~()JwkFg}~WVpxR%z2L=qml?oi)6`3lHwUp_*PvTL3^f~2nN9F=2 zi7$TjL9upZYrhZ2Jbsnkns{nzeYzPoALY(hZ|n} zFSEIAy@|M>7vnWzRzx@wZ3z{*bezZTP*ymoc}eE4UG1ggPrrEXDg_@00%y2G7m0Vz zWV3Ts-_du`v{??rRIZP9Up+=U|0YQ=Bvu)BH`v^7EQvTf$4y~D`EsI;R(Mi>xIntL ze}Ozi6ZSko?ShI9(+x)D=E~Jaf}~Qhfqql6->yHsn`0GJZXIWv_2jRxU_)2@6eIY$ zUHq>?Fgg*^%NPhI@fQQU+%IIfG*ttvpe5v8W|pdhf>q`s;-mxjvFVsW^Z-sUy2IHM z_1{E6x`Al;G{X)>2?+$~!?1}^gNewjWK-ei9!8`!-jzQ%cEE| zY>s@3d@4nrXz3EuYwEna!KMr90<4(UD$DWKJH<{DqO7E;k>x-so4bMy0M3CmlNVGK zrwer z+wx8uPWuO_xY;DZ>WX@+RFSvj*dD1AH8GD2L%9}buDz;8huyavjNmwYQWzDYd%&6= z*gMqak2_gH>mzKuddBbLtj|_trtpu2mG&P!ONyGD{~ zqnzKQ&M!W>Jg{H+wE3a(w)p2~=>`^pHIZ(UrxnsCXdZvD7@>D5C>{(#S21)AhT^`pDmk7s-8X=IlKMP+Rq;aE7W;qywliXfZV1;bJ`)TaFPq8agNNe*x4N+>}IhVS{JHC)id z(X)#Dz!C>6!vcNMrB&p|m+Y^!uGqlXOe$*7A+=@QF;chn9vx|cud>f&Huq7zchmP| zYXY(=o|E30N{rJGha4+mTS3h{m&iC?_#^u@Jc|}C_SF-S zHR)_A_;1o5%|izzkv-!7(XYB=P0x?)Z0$hkA=2EHP3zs4g8LAT(9(KI;)n^>l?gAb z4Z$n|X?g7;NUNa*U3%y)XrTI^3dWf{^{(Hoego?+{TdgJYG`4_F`Kr5V|=jau^^4q zHq92?(3=Zj5U^VsiKgXmnW7fI+EaU)ALE=kz~Rej5}(Tklkd3}TG3(E%DXsxuwt-L zAi|Y$43FAKtKh4oeTieNJ6;@R-Q#>C;aBv5o;1lis<#Mu6}qEBwDahqO-+YBW)~DL zxHMQcOv{%ztGnr21%9EQg9(n*SUy&P8@XQBXN`v6W*(;FKDF`}&1Fa?G0B=L_3sU5 z5xlFUC6w{9Wy07+N951Y466b77*?AaRavd4RGos2sbC!pzdUJ36cT*=GJ{8j;urom z44bmiOSjh<*I2KxTT2`%;dX784k`0%8!uXQt$ zhS4AOxGA_;NwF1T=A_D|M!3tbWwr)WoRv{QLzL>81Gg&IRai;$z`@ss7MAYL_BthD zHj{a_ixJ0osYj_!x8KvV*0s_IP;ogDtiBl>55pw85i{*i!iJM9l0MtI-!D85&IK`x z+dvJOP-ZXPGBUoE+E->TLJBCdi5HW?A7ZMSQd1v!#m8sZ>RZmJP5>) zr3q0cN&$Sgr{-hOaJELu1)a`O8*(`XQ|j@mG#%A^7fpBExO}WJM*oMazn~hHd9x4X#l{q*aX9#O#(_UKbaFlx$k-<{>Oj6{xgbygX_RMi@6gMJJHguV2-p^C8Kn;^~P&)p5q)F@v z{|zk~`x<$%#J5x*%RsWdxBo{62Cf+nNRC`T2`k*pkbtSV+ch ziHbN~ECjt+*-@(?I%5g3eaUvNv$VxG-pcm;zln<@K=Fc6F1J|n(U6yCj$9pSYjT`h zL>0*jeki-*AsV!9M0dtkin|>CHHnN}5NLkh09IT<*+H@T74qe25?q~cqLkG4SUOQ{ zUR&8;8pp~d0@|T<-y_X?;21!4+dOkgZhz?S<4SlxOGiO!WTs&ukp0ZhUS!oXMn2lcpfQ(ZN!%Q*){j*vMq~}!AJFY3ht?EY-DOb zM8ZWbFfx|>qcbg_r@f!quJ>lL%eBz)j(V5pO3Xn#!sE2EDeq?eMfbVY)l_L@dg!^` znr&}ojQ=)M|9uHCO&Z#1#E(*XbD?1aE06si@ftl|?SEd<+%WfV4njOr?$OmrfL?mb zO34frCT0;NJiPN__&%&|Gm9^Tci)jI&~xXbO>i!#Z*%lyEB7*U7XD6Tg_QQMkf3w{ zX}21AC5;b7MOE!sWf8h^DAW0g!dmxN28zR++bs|J9PUroJY|Xa6ZSx7icO{RB={(a z=HNq5{<@YBqdof|9i<$n)dJBj8_yl|c4sEO*MD# z@mj%Tb}=A?1&3#yeaTra#hiU_m0(dmKurz^G?W=@by6XjB-G~e&%S%yI8Nb(vR*^S z%}bw)W?a0sIcP7+JB=gb7jc@S&4Hxnr{|^Qb^F>>h=5gt{CFgRP-AYFv_>OOyp6e% zy_dd67f-kod}2^lb5yGq04Dyt2P0&q_#`BO`hJNfx!}vtENwLw3K@$^g!7qHR$d=x z&Q7#Vk24`2s`4q9R0hl}PwYXQvD~oDVk*8pe6k5d-$BZZ`+RtCK{kWFBhzOHd;^mM zwfs!Dex>@oe}2LeP?B=1<-k?VVHZh)9z8Q*4pl0|^3 z+qFT3WXT9Z#y3_<6}W3`tf5h&%`(df=lbNR~3>G0>I2M_RZaQFjD?e+aahiX{#riZ63%l=z zXESPY8UfTN186ap7$FR6N&lYiVs_G3R-#Eev`SM+OK>5xJlCGFL0%QTEYGy?BoG z9(vGUOc&7)-tquaS^vhhZV+QiD%^V=KcE;pKok!7#%Ldzb=zWTE_9%xRT#d;2o2o7 zLf1cARJ#&9?&8ut+yTYrf3k`qNqU37v7Son2%K+JPd5BE?7igH4*n|)YREJ#evqJ+ zZ>tCwBUi4yEcTZceJ&c{q6D)q5$-_@w_U6{vHw*KXsI!3N~a|R2^0{~WncHn2H=2P%)Dt9jP^*|(ciVp4# zx{BCUo8N#}x_%OM(*SXHFRc|1PeDmtPr>B)DkQhIHUW0M7<8ZBdfkINddskT>t&6n z&x_Pc-hfuMI>)V5r^)**W^g01M7yQ}{K|^v`%{@XChhKbQ#y|8BUw0vbNnd`W*Cs= zLxpNZ)yYt8ueaSIBC-#w*5qAtjE_+*gcWg9zVoY?J{Y~a8oqe2D|XMv-?mA)r`-z{ zpP$nQAlx9GR1-f&A1Ce4q6QcGHs|Y{Uc909)5j{$9AX%poL^Jj`#*G@WmHvB`|as2 z0ckiO-3=loqSAHfZjg|a?p8z&-KEkUQqmz^f^97imI7i1AocVYq;|HzGoWW=+$hXewRRfJ_Zw+7XpX~i_L8AWu2ofV4eao=k5pv}A0BstRUrT#aO%3Lu#E$G| zPlnD!NRiAKuLiZVX}V&JcZzHEfhZ@>CcloGWQyEIi!iWowDs#T3Q~H+m_b~p1&8}S zH7sF4!}*w^bJs9w=Cn*c-qPR@13f$YkGsi+B~DHH8zsf4nR zK12_gvFdcTk%uP=`2Ep+EB;0vqyJCbh$8wQ87ftHP6kzPa`R_5SJq>c0)SX{U?7;{ zej1auF`^zG5458U_3@w7Fln?`{|J`n!@uV%;6o-DpIZ50?l86$inP@&rGN*^nMf7B zfD4`PuS6Ozy3BKfABA9!5^W!bO0`}1`Rn3ch7IsFss#vHEd4|AZ(U>3(M?&A@mx~y+|pX(THNRe@s}nJqX-Xh zw}8q?4M}36NAln@A57i-0O2W3gL#!ySg(o0rJk}IM}$OMyl?YQMf`+3=}WT8-ai4& zag$~|=BmWj(TBgHq||5{D^Xz~s1^!U0({6zLUUpJnU^5K5^nmK;X4NJ{0Vq{Ye3}mF@p!N z2ageY1Tx@O2jc5vD$?p~XOhFXHRBQL^T;jf?(UxQb;#@yFM!c92?VyJ{t~;nJIGgg zSN`$1`b+sxZ{1oeX&*^5D1zL#UtCG~Z6r%LD(rp%rzMIi5c>vUc+nbKYwAlGEn(z^ zSk%$7q}ea%gvJb0N&2Z|yT%Wc-Ug~_7_srWGkH6F|9?3JyFL5i*4m+A6|KB+lOkU+ z^%aQ90)4dGp+Zi=8^kXjJ@7zq;{yx^w#QZK@xQZ+=Z!Fn^<}qZ2~q?GaLo^1uWRY; z9DDRZRlJn%-uG(xD22^RXJ3wJS6vP&%8%$dS=Eg^&SOLe*lcw*oTh$nj&(F7@EwAI zLxWpY(4aYws0*dFh<{+A4K8y}5>@aDBEgFvwb{|O=Hau&Wghb~|0k4j%M}kpavHp$ zyu6(5!imD$ETM!kjxBqilDZ{#d{tp=FN{x(w&|RTU_iixpqta2rc%A_;Oe(mNnyU? z1UmvWt-WEZ`x5qav4h2u0)8<4)*T}f94%(&C@|VxOIA}SNjmQgeTDyFnIX%YjAOUD zs<1__JDMLZzmk2>@)z2X{jq-5q_FpQo9jT-oY>hEac_`qv)|F9ZsbiFBA?r~b5PTt z8(y%do9$hvW)c`e@yH` zy651zW~HOuI_g5eMfNA)B>yK0D67TN_w|@>$;M6DwJ}uL8nZuj!Y0Qs?aGsQX&7`I zH;Y$!xSSXkxl=jU!Tq{=y%whxTKq+zt+cs~WB)n7MK7J|LHK;J`+oPqMm-&N-jT)O zwdU|fsJ$*4EaRWgrjDC8*niXzMfAGdTg*~RfN$T}WRD795X5QWvJ3s9x!9~?1 z-I~~!ZgL>37uci%k^9y)(vbnBxwG=wH4vzD!OrAY0!8ea8IvQ(W7#Oq6{@XCe%oB8 zIuj}S1xyua&A>o5AA#M0Z6!)yI#=%W$Y;BaLgmC@mMN=n`C1WEikt>ewa2J$|j)_Gu zZ;|FN!E&%Z{TumTkrnQz&2jQOPuE|F4i8TB%Zt8Lt5Oo@NA;n`m8aWsSMu%`I>^ls zh-cy-A{OP~uIwA5CS1kPPQ&pM=KI{8ZB0-e<2-rGe3Tx03%G+9Uzq9R^9$9?BLBBgJ zh?AVB3-sS5QZIiEVZS-OlubDU`$eJldyn>1qX)7s=d2_q`d-(;$2y#7 z#_#1fPQI|p1gL$^R(yZGGl5JXOiA_K0_(%58q$?BaOW zWM<^a;L76l+swY!XCV^IJxG&(O>=cbv(UO zbG<3ud3m{?+t-VWp=I-iqBhyvmy;CGzkc(G$F$VB=vQ*==Mr}sDp=TTUH{%z{LsqU zi`TN`F-%k_7llhbPV-%B|21-gvYDzPhDYWLq`+R10}~lN_I3YIys%0%LMzUDI5vJv zoov3gUy_bR64H|PPq7y4Gku8tzg4gk7r{r1e^6sVNi?Rk!Wu;`T zz1^hhhRKgk*>vX`18kY@T$f|a(I48vPvix7>-52GkN<>+3I6zc^8T6e`N>*z)c3Y` z>zCkfU!(Tdi3dt&3ma@M(co{05axR7eGQ0#7H_f5=+4>|aFdb98y*!L;s7(U7qWQ9 zmY2?w>YLFRd}B8GT!UACG{D`-2R}YknTlj^qxTej<^172LrGunxPrnZssbpeX-Mou zX5jGlBGb&Ad4RD%q(I zE48670^a@T1@9C><(pUMwk&6AVW74|vF0r21WiIdM?q+vMLx7o%*!mW$|H)^YqYZ- zJM56`yl~4%HF51rXMf-O`~CKVJ+o!Ku9w5T=j|QGZ3BP&bkd>ZPi(zXzRzaZVb!JA zup3d6u}K%vD`XaVTN4vrAad)rT`Cs?XG!?FL-;Kkqp7aZemO~0kN*EA{7t?#<$reODt>$DO5*$;i*|lrZp!Smc5-CV_`_3V}_`Nqr;f@3Ave{rSBj zMWS8^TZthhuE7>T=xM}}+WrgQ$$N17*11xbU?TKuPK`v_#z<7iqLiNGIKvV8;=Ddu%fk zw;X4VZp11T#a;gDO7y8z-R4#kMQ8$;^gE`Tj%U=09r?u5A9~K?rVM0{oXio}T@035*@|_DJcYPCc*73g(9Gc({P) z0G+Q`_d|Zru4m3^Omjb$Z4LysqXjMqsWasE>gE;`th?C`va8?EB47u>Qhs?t@-~r& zJC$G!aTlLHf~u%GHol#bFXJmofS0|i7^*`%NBRsA$*cZhZsv545x#7N;N6!PN(BA3k4!OFJ%bRCDpkIGkevBSfA* z-Z35ak|FTm_hlr&OMjt}#a>fNLOIiUlmZ=)XqhoFY3RR;k24LJ93Rn)W8PADgXt+x zXPdSsq#+&*C{um4%s5t?D=hMc4&?#XcfS)m>%#`1u%>R0_X*w#;y!-Hz1*@$sijX> z?8Cr5spz0%EqKV-Lcz(hc1C-uYuq9Pp`>5Il^tX50w;xQwsvA=JX%-x#3EDxMMFFs z4DfN%>}cp}4J-p-O{BZ<10ftPvKO!Yw-w?xU@r~996RN${!_C?u1kOZi-!4%BUMs? zFas*T;SiTPxpHr!qmzlGQkIaHiVhPdH-ggve1s6im;E``K?MDV1i7&^X7R{-M-SdA zQ}=uSRZkq`C1al$*c9~(_-EZx0&z|Mt4s;33UV}@RxKKCx$ryO(;eQZfwEp7I-f6x zCNiv(uEdap;Aq6(Cb+as#15BJ?e8fv#D~^zC44NcNOGr@rJLNvHdM2i`8jZ@zyIXK zRsES`jwa(e(a$&Oby1){lju*}^bYA8tqYdM`VCj}=3z{?AXwLgz`AA@Z?lkb2Bm)k zh+Ue*3QL~~sF1!j!C|6 zL6g%ZTU)aJelLO%N?-xKpW_p^nmYS*gc9qDmfGK&=lWzix8S3jP^~3@#*vTCr`@+4 zXEF=Dg}=~AvNyTl_p-^7J6f&JSr1GohWNgxR}d9hv5xp>14olRdk#LiYFeK=_(`Lf zxi|vF$=@uv37n~M_{UKnlI}I(NXUl!y(}$7KfLkin#S5g9pUgo-*BL{2G=6K;Sk>Z z1$x+BS$#_@Rx6JbgC5OKZnen3Uq#DbbC0(?ecZ6_sMP%$L-Ad9RS5v?CU9}QU;*G>Jc0K0r}yu zA!vx2@y`4H^4z=nb9CikR;YTeXPhpgXqJO#c(+-6YC?vasuQtPJha%A zbu=Q%vRZ$XM!J=#{A%uz^q~cbPcKMwI-&;=IFcrgeKM`(X}Crp|C>0okXrSsM=%M0 z8+CHuQ~n!dr(JZ)*?8yBHw$TcJK)RXZEl%3iyU+MwrjdNtUt|lb5wQbyIC2C^d2{` z1!Sw!HgG%O-`d1>1o?&-ePs&BHaFv3z`I$FU5mK=`V#_EVMNb!h~(NY)B_)d@cY9* zPZX&MxG?cA6w+yoV^9bWDxGr~c-YG+MCRPIo=R*Vf_y0G%V|e@+1po6^Pa5`I1$xw$QAOMoJ^j1 zCCXJXa)p?Cr{8Xnsk_LXx3cwKw2^g&3;DKG+oxuJ$@<#lo}dD*$<=DDP;;)s z7p~^a%h@2Uy4EhokB~JaGDadY?SpK%!_i}!s#bSVUk@~u3}sWcW>C z1f#FO$qeepOad&Sd)Tf@w~Ea6K2&0s1QK}O*^7N=27K(4B63zXiEt_81e%p-udWhN zi1FQ~9v?O==bfHO#s@*JQN;R*3*M^U=^gLeAI%fCN8T;#)EePT!)%j9kEqwgVEc}{ z_P@Q-l9U{h76cajSJO63u|e%w0ex{_0$zj7)>|W^$P4Lzw5gez#fTI+rwIOFIt*p^ z1^zR^+e(B-)K95t{eGDxYu+gnVjc=i8-@Soa!Tk5VHTT*zWJ-Z#9e_aLE|Md@m7gD z%~)O-Pad8y0?!NSYd`J79H<$aZ{OmH5l)Q8XIUgmZxVn{fqHQ1= zi+Cs~ezb9=E2b>M+|XSbPu7N0ILr2IkK^-b9%P+_Vn)qsyFN-zCv>XZS03-8UPLS? z!SR&X!4)K7&FOL)hh|7@)K-#)NEObv@ZK%KqijP7V`LNCk`$)VmCxyUBj|UUz>A>Q0)m!by*(Uok7lrj8EW*^8|&-h1U25v9>3Uzi9V5EIwvqX&*L-*LHL~cHx0*JbEh2 zvqr{RQzb9>_|&YXV%~uo5(5H^d!ggodl}VPL3^_2J@P&N(hAR=nWb*2+7p76a3^ID zSud?{6Y_%@BlI4(Ub`-$bbdv*5@;99%b41}rZL)9JX}-jpW>Bp6ldf)9_RR_6 zvXi<#INd`C3iQ3KnsQ*gf1p;;=;>_?%A}`D74{+-%hlLqBpVLYAWfyWZm^31d=YD<}YZ`o<|@-BBnfZ{c#WH-BDT)-$`7J z9@0}Vu8Wl>S6R|4lV^77t4VJNJq;wL*7>$mI$DjFJNuSjSIv*i&L8}}9hFWw%kSuH zktpAGm*?#%w9(_#qJDy_N^I^EadLspY(jQ)Uc8>Yiu*@$3_QvP+TN?UeI9wc`B-EV?^%-D2E>-X(*}yW~e|!t5Q0GBG;pOgZXyw10yk zG^~w%*<+1A=(2g^v@h%yOguqfQyi`KW%`X;@e@EbK-i3m+{&7;xH&do-dl+`)^Au8 zwr}9LNT9O!tdDL(e!GMjj_Wcdu%to2aMbbaa8Dku{&61VH)g_bG<^|Xp~b41tyYh+ z*Aw-o-ujh)nnXJ2yu%swMhgtE%<50R>eV#vd~KyibJ?Hc9oDc;fYLKaN&4AXRFZYl z5a1Vz4Mpr;x|w&(OD=S)H0h7^RoL!2_aU%`Eys*?)TUvzG8=xOB>JO|)tUFeGBE~< zE~`Z`bJD1yv=+2)xY)J*ZJY|na@wTb_fTdLwCT!+VFVV=)y+;EuzVxkLnsqk(Hpc9 z^%(i8e9CXISYbwaYC1p$NETHg?;u|zEILZLU2WUd)1v>yjbUabhxdv9`|8?XmGEx$ zjq~UNii$j>#CaIM1;v~j%3?|)bV(7W;W)C0A?4?sdjI$lQOK9l$myqS6a0kr8tKcv zib;hmeIrNoZrnp~didv3OJZ$VF1{4-><);c3^D56)dyw(Fo(1eh#?$Sim&JYq)hwmHE6unuWTGRT z5TNp+Da7L<-6`Jt{gi7f{si-@kY0Mb5T03rzaX6@TKZd|R}Y#u{$br>5n39pSAx#+ z$khxt_4ETNj^=CUf{A{BiIvgNAf}_EdqkJy7C@vL-6pM&ZcA_1#^rEe_>47`QG@q2 zX{Fz)H;rk1f9%b$ii|n2`hHe|t09?fP;09vTH%(Uu!c3!nv*wB7J}HZt--xk5x>Rf z_EYS&-y3L|*=tYJoJbO%7x7TuBJ`fy5!eI84Ipziz63r&!lJC<@ z{4C$!et9M+SbM#;m2DU4y6Af{?0fu+)ECg&9@|K5N=$qg=!*-iOb0nw&0HGbGewp5K*x+MUb&;J;+mXRze?@;k6r zn+RKQptccUeEgeucC>?*y6t((5Fd}OL6h7@?cTyte`6FVcusa8sudjnQ%Zhv`a)^A zlR{XXB9d(qYmVXN@yQ9jghcB#{fieAfdFWAe|H#g0@`c10`NSq%{YUR&%WRzHy)5j zXGx^hWazktMgl6*OAmDRRM^!@ zt3p_NGtWMs;;P9DmR$x8MVg@ca2z^@^s-}DEecL_9lq6|*;0&n4-4Fm+nDn|K}-?G zFp~JiAklqOeN4y14GH+@MI`gGFX!AxqIlje9>Efj>i`-5k>mb|0d}cokShN#9252b z!!hCh-z*&dqy$<|=uuCiIwt0kxh52Ey6wd7q+}TFEH0H;+kY)=_FIAU1FDP9p(KNI z1+RYxK?;Vhokdf%R=Q@fGb3wEoz9#L%9+`!QNxK$s>oH>>-Z984H|7VBz>B=<=L2^ zMCwR8Bc@H<;B0O|uL}Dy2_NQ@p40JWqRAaS@t2RRKmeJ30i?5akh^38 zkalyJcoHE0{}!}nEQ$?;vvbQU&Q_Eh7Qpjw@V^G9?>eGJh-HqTA_v6)$@ zHMN8InDOiM+RA+F$dL*2?DJZ^nF2>@g4pz6PQIOep4Fx6Ar7n?CNW3r{UgR(SN`?U~1 zFzCk{coQ*S%y246`DG_K`>lZN+~~02afvso>=gxo0L^zf#G>VVDPoCz8>lvs_xwBb zea`TI;&gys`{<(qIM`0BnkvuZzdOAi2McmQEq-i>u=}-8%jqC@Nz8ZZ9fFZjb@Eog zJFD!B_UCeGZlaXg@C%yN%A2n*kMTMx?BntKO9l;<+t`xg%qiwt90UiKZz{h}Sn$F2;drL1pmEG`U( z6j@nwG$=ve5akFwYBPY&wy?G)0!;);b!#5Ebbw%vAO?CM>2Q!dqIdzq{E@}>*h#?- zU%Iwx86rwhFgU#2I{%B__^{of#$`L|{!6w685F5W3?E+KCs6&n9nx^b%X8|TDkXCH ziFTWl)cUt+GVU&{zX_#c(wh;Y2|%;;FEwPkM~NfN{EUdvpI(` z6L&BNPAoTbSunxo#o%9WSTopE=ozQA~YaU>-!uRes`JAFunCpV(4Ey>nB+8G{&n>TBjy*$%dQF3Nw4uQyYe_U?o&xDs>x)-zYg ze*fD*WD(~;ePRxq&efSbcpNU@A;tw%crT|_ZYU)C&Eh?*=#VKY1hC_p_^$miKE_IB z=pQ5(*C=5|B@3Safc)TS-Jy}6pmqDo5E_AFrjnJ2ZOgga?BSl7@81vkLu^KQ&8%B& zBd=S>aoA16{GKtv)*3V)($ajIYv2>SH{x|!vfq5vb%$4>Hihp47>u~OCBo`T-7 z8B?^yi7#mQo@5=rlv7b}*t%j0Eu?stO$4WC`IRnHD2|y-T_U!mkSw8SqD{V~fx!Ts40 z7VBXf{`-T!oGLda6odjQaqGm{4E53p2^f{e_yWR*HogEf;UxJ}NX$yE7=AE%72{y% ztqN|nJnq}K)3fq8aSW|nPa796eE+$1+h3py(uGOc(14{wjB0{0*V4c6M+ZodQX*XPlDms@*AtBf`eTC&*A#W9 zqNno?7r4h8XV^u=+uvsJZhzgB; z&{ii5*s2-EhT5CP*{9bi7msKq2s~i2PA(}Dxd_Q>n+2};-#WDy9+dG5{$4NRSE4%C z+p?$#r&duj?DQYgRC2^GpQ|ETP_g1KyZ-{-TgnO0OR7=9>U7I->r0m{@8$AO>D$$^ zv*(7mD1_mt-wNdEtN-39aWB4Bj=`!4*Muv$w~RI461LH9Gso2zSq&Hzjr6P~S@~~E z%9m@IJj>n>wQCh(aiz>ySY97qP79riW^@S%dk@oOYM?RJ?QA6v*ipb6;Cr|5DK4g5 z1O0LM&&x_X!|bFgoy()07xNR1r;;VCPC^8}I`#yvr2?cJbJM4#vZo)&{3%Uh)0mr# zZH;2gYNh*3SQfBZmtWd=f6h*ZzV9)_OO=%B86_aVMf`p1!N2gMF9(pZrc}4(?JE}5 zI6b}-^9!&ubhynZ;a)TqmkB6QJp7{JzB2hwm#jkflk`~UX0Hv6SIDGB`M!th;_=@^Cb;4boZjFsb`?yc;5umpjvy7m(p} zIo?vf_`hs%bA(>{wOWxo&qs#Rvb$Cg8=?pfE<08Z?HD4~dsvw+Al7C@nb5eV4${Q@N z%s80vD&BhsN9gCLE?t$2w8@`Hs))Q+w()oR%as@$p%zc)^6h*^?GZFoEPV>Y+gy{R z>1tTQb5SrbINf0*aj?m$ah458r9MsoeVZmoVcCWv@zBPFn%%?U`9)+xf-4#6O>U@H zok*f>;tRceR(>Yd<-XFleJ0iNWq^!h(vOJTl-)0>EU3%#bHqzz*ETr5u!slFJ&dg^ z#wGU(MpiKYNwXkNGO@Vpbp*=Mfgosc^em|w3xB$`C3-rE`ATAjmkJ!8U4QiaglK;f z#SC8twWNCl(JUMPn7@aCE3Gm0YCFo$)1MHty5%lxKx-J@KQReg@!#tge0~#vmd=Os zY>(+M!xEm3=r%H_r*qfyEP`nVVZ7ZGfavqbDJ$ z%He05PSAd1?S8cWx;&APSJ{0pAy3fJivIjL*_Cxsd|V?=o#gLZOG-Q1P@JL+mj`)w zBG$<{@bypPwhKE=!HU}23UNAr$lW$x=81=m2&R%5Z#ADnOy}1Go7~>sHhKkxZzruV zSOjuJT%!v4MFT`ESpQaUOG#*6xC(d-#WS=_2h5HpI+m8T;m%g}3AlGNu*f<5jG^p< z9L9QRk+|xs%{CQ~Zw0NlgyJNb{5uk^{{Cuktz-)7q61fg*GnJ0tPDFoCu!JoWo;K? z>{y>TQAB(DM}&LBZsrPSC8#0Zw0nOTM_G|YJ}%SQnc1d{XmT5{>tCRD@id%=N;SJ2 zzeakmm9!5M^U3~nB2CJP+Ml!SS)<9gYbb|ph{*&|-!5a5h_1g6RJsr_ly9>#fx1m` zzsBmw<4jtVkf&yyKyFN5IZ9p`3LK+r_<}%lKf6-SNV1UMG25lMRILA#W@SZ2u*HpV zG$!0`^eRAt+?%2un}Q-7vGe9<$r@YZx(g|-0NqyS zsL;QD!}@if$neb}NNuVt3#gQb3GVRWrv#W%nqJ_%D<}UsD;XL%)RT9IVY965;0TfR zZ%iy{<-43ln|DmyPY(Y(qI$j?l9u^mbo9)rE8&Hx zzc`ofxX9@zU-1=}e*w-X^{B~INvXXJ@fKb(MO?4I24AL@ZbIN{tJ+Vj)d`)3sOQZ62rdVqfZTr*H#ttOUir zYWBAa{Pr^xiI&IZylpym{&ArH9ZvOC*E?ls$t%r(zrg0gLfVBq5} z$f%&+-Xvdt>H?SjwNjh`X-P}}godznTD73KUD%Kr${A`KEj+{N~czR^Fxwc1xH!q6}JMzOyl~548u;r2gAYWAFnvj z7G7ABP18tXC}^t30rg3aRjJG%+~#eJ*-z6^$=nOfmlgb`D;vYhvBuVNVRlSRt18;q1N#z z5-rUk;on)P9`OF#ieb!D1J&c+ObnQ5i3E zI1H&pZ`_*TOwjZMyi~8%Z_$k^hg zSInVr#PSMV4$~!5Y5Sfn(sGKy<2wplhhIk}R29vGllRiB9tF!4Jx$E3T2AL>=82N< zo)0x%0F!ZV7KU_%qi*2tP-tZ5z=}l%8gsEaSntm;=GCzqK=2FH`Fd=58@$d5%Ee82 zv_8|JRzln2M~5@z5J5a|o+b!RRg}sHR|YhIuVv(78*qm?vxq)SfOi>;^pMGCMIEcw z>Yq9r&?O2yvvFFhM+0!(((rz2e#P>v6?zA!rybF4QU~5wKbMh;T*u=Oq(g`%-++^l zchswb&rK4uom-T7S^WS+CFaxNN!W$VZVe>~s$pZ!OZ8&3oE;A>dk4$lzkHCoU7)}D zZk&ZZA~3s3B=|J=X7{s?CBLoM0wzcws%qm)IVVSj6n7Hf6}5+#`u*qr!+lwq%*X!ep@LuVV84 z0YygPe-=3U{ZY0};9Rhr`05K-Bt^m(S-f#P-&N&5Co@PN(H0fYQsrZ!KcL?%qlxih z^TWAKV4~HCTEucW>kvE;H@_)xkUMx$9A{E9-A`in;DpJ6gFF$c;?dEfkoVg-C%YfH zH#I}JQ)bBIr|E;J(~Dt;={U?w9~$P@R~9t@&%^IFI2Z z5(hi2{lQc^N%SjG1a%5ot$Q5H@deg5|6buhE3A9fW7>3ECC1{M z;ohU`d5a$v5Y!3W zen@-J1%f(ZzRUt$hq6Kn%`C44c6@nvhac?rigi*7EMvt<*&f!;py2vELmR98kcr7@ zdY$801||FQlZYRC!Ksp6<)pde1;#u$Er{P>B0r_HhzFx01yzxr_Of7zbsCVmtv@!F zU|xS8hobSog7L9@Dc>Otuzx*|m_u&)W+i;jP#SE2QmSnm&#(UC$(Cbm#oCsvLRb=$ ze!9bUzd5XAPrkI)O=CJ2Ft*)@6E%<4JE@x+;RyMdY8^rcqD!6RYLq-k<}FLq!U{HN ziqoVAaTP?H9qsH4?awL7k!D?NaYM&U<8I%taT-|l*iMd$#Nc0W z2Cu37hHx8b;=n0xG}T3lt_r`ukyPqWk}u&fapxHeeD$%k(|7@@e6XH zdT_qt7`6->*t&MULJ2#wy|RCE@U|!wnuMy8GdeqV_-$&tYmF^|{Am}P2zs;{bZ>Yk z;B@++NKyS>3EQK_X$_G^=ZUx`hQNU~W8^pm|9~|v2m8kafRFx)j z5ZN`oz!sFmzT+w^#qvSv{{y1;Dp(NqU-No%l%Tb{EFgiW(Xp1K0F328TxKc)16os~ zk33pIR8&Xh52yTZ-*gDyO$5YLgxqwDQCgmV7i`Fcf7@~Hk5ie!z}T)pUDoR~WJ=V> zc7N&2haGQk(3DFGN3UdJ5#-?wa(1rdH9UY}3pM&A^>2qzel#|G1L7VrtvaoBy@RE4 zGe`84cDi*x^gm`WELI89YA*ig$;I2Gam*!+gcv)lsg^VRR{p}dT5f(vmOM5T>`-f2 z7P`nipata^+r|0UmUD(x?PZ{v#H#SJjt69wpSsvhZm8C#(8y_UO3+@t%G)-nT0MuE zPle>6EKbv@XLGJpqzsNjdC{u2{;UD|4PRgZN?jg^io?-f*Y2b&KIPJ4CXG|md23IgxKA26$*bYrtD%sxBQUz%pBhde4!F9CW$4zcmTZT28FvPG04W-&Wi;6T z1Xij|Bzv*@jX^H=i>O-tlM)Ao$6qv_6e4nac2ZmV{2vl+x0TC==jGic8bzC6w;@}L zFJ1tq=Q?W5;nmn~eOWa_jT5)nQM{C`+A!anS5BxGO3LO-fqa85E6-%J-<%v72}b*Ch6`zrD@m>+TfW$mY)I@PAg0s0w3Q}&olRESIuj^Fz8%-=m{ z?nv$wuiS#DHmJAa?V*PF2dsFS;5$sC zpU|3DFiHT1{{c?JD&cUCG66IS4fGG zNVCIc$MNLhfjX>ZhY&i%sNvrtNui3cKSa(?HHhZgI2snio%`NfgX|l&HjwzzpuxvO@6L7G{iGLKlY$nJYkohZF2nv3p)Cp zhEw7VQe6qQ@1Oo^m1Gn8!xf|NeG5 zLy14Lkx1%$rFf97IkJ%R#%X17fLb@u90#YF@D)1s;)#25KcSjQGspHj73#?lu;MBIc|6(vsf95>)&U%`0~+8sT ze;~`VuRkyd^{rP|F=4-z_LOE7&Zp!{>K{tt*E~3Zg|=>iP5Sq25kB$i8Vp)ntk=q8 zKLv|{ar;dX_{s+kJ&ma+zonl|fOOfV1H;dQiZw6p4$1rYM+ijnS+91qQ$dx!0tfzx;?9dR&7A5F;@Hhi}jv6ed=zS8KF;LIw zTe@Kn4!oX@>=ubr%{nymz3aEJOl{-{=RHeN=}Z7F>;XreXFL4Shpk`1PgiQyl5b0j z?}^T8B$p+V%Jo|}mC1e}P{p0X_a_m2VEyVw*J5+$FE0~6gqCM$(!k`~w)%XgpgZu9Lld}ekscvqa`-)B(J2&Gz z(08QhTw4uG#16b1CbDI*0~wJasGy@{2+X5%wKI)$a)uUD3t)>=(`IB_<<$s5a}>TL z`ERU&oK%0UrEjSg5RWJ2vZ|zb1gm1(3$S0r;Df%9j^`AU!#4;>rA)5qowHp^(YtGR z8FtLAJ@bPpe;=@u{#4i{jUs?PjM=UXy0uT?#>I(S11@U+XlGwhku7^qYZZS6mHDD* zlQh21agDFoLeS2W-v3M#V=7e$Q}K{1m-p8l{#-`i4xH3H);ayWEyspsbsXr>w(viP zwmXFgp|E%pMqArmPNfgD_2@!Y?QzIx%gkym>R1+6wtC#ptyB70L+Jj5G64w2vrhi3%@TWs;Bp&0$c78rHGpC!n;+$yynMwB;)c_b0ptB zj+xP;PwN7`xcqKVg!}-Fm~P~PbvX^@0p-TId{~jB7XY6MS&TUG1u=m zqLj+^+tt+b>fUyDbJZ%WJJFSj;S9#%CNWAoWCp;tTUHV};*7^v2%~M_CnI;I^UcBh zUCHB;w6&Yp8@$cg{1L}%TTbI+J@rnI*lK&$MhG9mH)~l4L*Ao3nPu{~B2i>Kt=-cE zDwHM-yR$@oLWq5}$q%{m2~d)rN#43Em*{3f9Q^Y-p7j%tM7h?tGJfiDl0i7EW)qdX z&E#VWgT5X;Q&3r>=K5S#Z>XPFrNm=OuJi>?1XfG7YhfFTb?=2>s(4^HrC=J(Y<^}f z62Bel+p>U=XCAc6>!a)67vgm^#VC060<7bk6s?qQkv5h^%rZvOSSCMm5#>C#SrWTi zkI&7^;|0C)9)Z@No%7tf7pRVKegCFWhri`uVHyXSzE2r*I?Na_6h_B3(XAe00?t^h z!4~7@vhe;GSu$$m@8*hcdppN4;(4ZNiZ)`eh!VE`yy!xTR;%74kkF!-ueBO^LqD(> zlYrjjVxkb<(StJ+hxn%ader6v$Iu=wXp)jjhVPGy`owZJ@gcuW9;vD%=bEmdH`_9d z=;}oP)AHtM&Yx1_%k@ILu0WKxBOk7oOr>dEBHd}ViphVz4us#|9J+4jC4>Ir6_4nN zM|y_D?UA%Qa8KCV+kfA(1@$-zkKc4w;x$2k%-(4oW)z=@Rq~@x<+i73gb1?6810EV zK4a>$P({JPy5MQgl5=#W#M~&6``}17$6dj+*h#^FsBrmiyN8nRs4xxf1-r$kO;toH zwoqwQG&!$IQPT6Rp!rfsBcL<j2^=r`P=X`W|dr}eRphc)n@a)a&~{|FHW0HYv<&k~Ef`3MOC zbbbRQ3eZ_m_$ayUHt)Bq;7c{bVF1}53UITG?-e{dSQ4NsBdfC*i0YnFY|NZ`IR^c; z{FiA?>vbq&1cn{WlPRRmJ1k6rfl7S?6ciLQ{0}CzGG=p~8(rKe6QOZfps!v+Lryp9 zm1T?}mPj7F@c>7~kWMJRBbJ8^t*0j~>Pr}1tb~>9g0e0i`;zgMGeYFK+{8<65)5h% zxxyzzv>#Y>Zs%HmmNzK|(|2L5np?ab$p2rRoo76o?c2wtiY`=#s!^-<-fETJv1-(& zMo?{y)~XQ{NlOW;6h+M#ty(c^@0M0mdqnI}G)6^@*yMlae)T+W{?F(0&vNDFo^9b1y5PGxcsFn4W5t@4llzm> zo|td)QHK0EGJY|c7EdxpN3b^^^AGfnx)x{3yN=&{qnme~mpeM&0?Ky8O&b`)>OkY4 zG8GbvV7K~w>U>Po+wE{Fk*W>f$vI=N~^%lKk&w>PbDQ#SJy&BHmpqB z+gl1y2L*WapiV`&Id)hBX13E$iAzk&-5%Sr)A*`gY_GKs>5~m1s13~pEB7x^v6h`G z%|uQ(tLJq^YrXCnmoVj_xz0R0Vl``VKHib38+EN4wcEzL__CKktHK~BWPOjWf0Ch2 zjXI-e#XRaWpVz}d!g8$enTl=`UQf}_r?j+5*n5^fZ5QMkJwiWuKIka6)^9SzjVF0& zdv+3x*&$HqvAz!S+43MCpxWhsq{S2^r=>;9IQMSrtv{=ueO7;zt*oSU@PT`HZO3HI2Uk$=q zMDGL*M{xf?7eByxtk=I@2~o)1Htb++h`%xr(Sh>6xpU$^0KZc(M6J~9=2$1JuFYt~ z`GDFz|7xmqHN2}~ha?HhVcA9=dwgk7@axy0&9K9V!q0F#{6<$N4k304bLrMmqp)+U z?77~TnBn6Jggm zFAknPSeZ(|aBK#e6>IHkw&Bj!jpN$K{dB950ZI_h0_**~ab3KH7*V@Si&@he_k=0W z+(6#haBb@8$~qgndzGTLpS%U{2h3XSH;28?tI^xE{3%qX32Bb<#2U7hf`6bn>G4#2 zLPBS0!ysZ}Vvs`{Yiozkq-?*6s;Vm#(mR5J~$u+zJJ5Nc4b9M<#qa3O*f3*Oe?r zjaI_80HJ!T*3gjFZT`fw{Fe#L=)X0J67&+my9`Oqp{xdL_=Eh>lE;+F#cT~yd1kG! zjQfKZLAdl`v*m*q5p^!eUNn}jP9ts(9)2~Owc$@o3G;dG5MS1oOBdhun}G9^rPHpVO{!dinKC4myCb#i>lwR zctE3eylwh)yy|REPfzM?gxYk_YH28ka}+;Y7%cK@M#pT__FK2m*i=__0u4G(tNCD= z2+_wDNziG(ef_$Y%`3D>YZ3aPXc6+D;E7v}9nUYbUFe)fusZy5zqf_K+Vl_x{OjPE zRcXD9BXn5uF}?sPZc-}mo>@B5>qxN7_0HQ5G(rhNm5!?oi#N7#PqKH0n#&MWEQ!NQ zEK@FG(lWXM4Z|pQ&y;gZmxyMie8$U1FeX=a>MOZkPIrxLY;W}A(AH*{EX%~K>)l8x zCKReZ&>pfsiCm3#d$htv{|IaD^S*pu#CX&JdFKjd`|ZkAO?~-U4@;k9MK|2c)HPh1 z^7p!Fhervu%mH?8D6e~wtUT^_PyHekVW+!=5?ha;i5Ed>*ftmQ^hY&8MsT~+N~=iX z<#Sj*ucKm#yHJDtNlvmc7l{(mtWNS`4a(IGgUbv& z{Ox%kYhI>dn_^xtK#XxSGs0`)oc}4XEDPuPNEPvEddyzn6JtzYp0#GvR8eAaU#T?` z{O}vf<(9>IigM= zdr>Hqjt^)y6Vuz@lIq+%JUl&)$U9IdG_9TL6$*utjf9*7uyI!g>MP*4L3Yp(C^Y{T zsKEbqqkyQT3^Nmzy0&)bX+k)-Jfe6V1TV2O@{3YmiEM{Zu+^!v8K7k2PXHWRV)3M3 zR_VGSOP-WkHe+mTEFf>ZGAv-jJ%RiBa`Ey~0|LfbQRc2sFq`vMEq@ipx_)fFYQ@67 zV_|9ze|`$`cqy{$+`AVE<7`UNwW>ick%A_{B6T|Ov=U9$J>+C`*yj(!!nBeljtq9B z4R5r;_ZCS1bjEh3^1}1^{)_>if)nr2+BsR|W?9&KwNOgStIJ`=J_(j$*L#l<@HMtZIc7anf{ z)b-d-|3nqx$?fwIe8hd!e5cGYfIi;9cA z|ITV0ZDo@?C?x^1`a{v^iwOYsAuA_G^Yr$?KwNxgW^5y|L1d{OP({4j0w-$R*$QkU zJ%C^pB=8t}FZ7b^F@R`90VXpCr5^y{ePDDHagn*yz>T$rqFZ0Ph6pw1<>^_M6^ zVQzjExD^pVk#KIf&~!dyYwlL?o+Qx71F`3vvj9ZCw7mQ;&$+j^7frY?nv6UsDl6jz z9ZUrL4aOgNr%)XtLGu_F{qfiJ$4*_3ft(F|CFnzHZCIL3MlMvv# zzXSot-u1TBuvHMRe@gughw|^4UBJnSHY`X4aFjPe)1KiIYsm`>567AUefoU?0J}`( zWN&^xv5*a*cKMY3|FHNU)YQmFy?&i^e7JkKiyIz3Lj{n@oMG&5FzypIy8izD{j%1W zR*S}YUA7EJM3}i<8 zc*QCw)}%eBn;Z)mcMqN)ZFKSp2xteZ%^*A53yDxD)sGqS37qVl-6tTQ{;x10xdl`R zEbq;N+sCf`tKmVMaUBNum(od_o6ox6%g_}T7M_HF9=fBgO$R0vovMJixHwuf7tG9{ z<{LmX&MAvvbTrRNZd>e1p*R}cLnnY94>d8lw7I!yWNjUd!C<_9%>8&e)o>MXsjL7U z9vtb$&}9q4A|eArLt(#uJs`ILKnu5w%;m+!#rd~WY=hI&Z^FaFxrbaUP9{ARz=hN; zyP!Bgl?n@8@9OHJ9;9B$x)9lL$}9xJQrU}vHAk0}hyuO8SukPPw+XS#!JzHH_;rGl zSGgNb*tX8gvA=507U5CL_I#K4jS;cejy^vWVLD}3hQTm^A%^%pthP2bGLm%Rh+R;- z5mjz0>Ln_tpg?z8fa)kaJv|*XosW;t!5#`ded*FAT2<%VCcsk$^LZdXMl6(|JfmS@ z!8|xL zdWX*r_;ogTBgP&IgH5BCpZWM~fHSiLakAdU)3Xz3OB$P*g|DovNZGT{Hpg09O6XX#-PJQ<;a_7%%ArX$4u?*|rzdqqUwh@py7D`TZ@Q-&|s1^c3wl zpvei0tIXzWMpMDXiE_s<#LQ&9kE1N>2FQDP0Q};#%;=z-B>2WJO`!9~(v>37+0J;I zeS0zrbK3;0eJ^0l(IK)_=<@Q5uU@@6>C@EIOjUg@Pcb(3Cz~lwnLY8M_bWTdB=A@; za7Zu%{!G*|0)vv-mJ!>MVjp^4FIiM0DChv~`n8bwwI~0Kk-Wzwi|kh#BruZntJd=A zrS|t0S_U}e)7|@hFzYM}8v$O6Ki_He)f@8)Z4sv$0SpXPhB#j3CO-!~NHy&FcYXue z_*O|wP!KSfzJR=mx9RB<>vcVk!zR|WY;0`QMege9b*19)q&s5vPENcn+aDxyK7Bev zNl*Aeo({mzI3y$_I7qS_#HOCxX|5f6%KZT!O zmwLS@@u{9(3}Oaj*Vyr(0tM{bU+a*}hjE;@i8JuoHi&^=0%<=uAv05qO~HeGU|;(U zI}_C=Mb|IMNB#h0uZRRS!!Wk>(z6>ahLxZP?2iw7Gj8RL8CKHM(@O(_dEin`WXJr* z>m^p}B8tJf-x}IX{)}IJXX8=N=OQpx7P9sPa(M3idASMfAYn^aS2rrZprDHktS^&Y z`}~HEhX;o8#wstPae&~ZcvDRc7P{LwLm!|rxl$H4<#8>&hhJ4yl{>S5)X>hA`4G%8 z;tYOzTCK#eGH0@r_vh*-J0bmHJYLV-{2j2by88OB&CJbp!C#8(3{1x4dSHMSz}uvh zIJE;Ea6A#yH8e~f95f-z0bKXwt(tRmHG!{!rdY+ zvUN{*wu({ZfBg7yrXnJO7TeSF4qU{Uuly*eX8@B zYup^FL1zAcM!7jdw%=wb!wo5YiN#_!LE7C+_V0tuD3r?1s8hoG_d=AeSlru~H?gu3 z1T*}yaX1=O=^;qBsq~t=+0@)_3huX+f1bLp6>1>KpAY9sqiXMj%=Spj6mWESAx3F%T6?nTYkLt^78bzswu4#n+TL`5tyNvWwU6;`5^k9$}V{dqK$Z@?Xp zI2;Z~6U-=XTgSCK=@SRcE(-fFVR@*a3wW4(Yin!ssq=G%B_&BZco+5??mMMA(HZE+cR$l;K! z{da+^fUo3Z9Rq`RWuc_vXTLh4Hu{bvOROp=34HO$X)RYI~=(Rs;H|Uj^ t-VQu>1jiJp@4O=8|MT?nUynT}oJ&eK^X4?0KU0B^uBIUrbI0N3e*inn>+=8r diff --git a/docs/cli/basic-usage/plot.py b/docs/cli/basic-usage/plot.py index 03717360..42e25ca2 100644 --- a/docs/cli/basic-usage/plot.py +++ b/docs/cli/basic-usage/plot.py @@ -30,6 +30,9 @@ def plot_results(state: StandardState): assert isinstance(state.models[-1], GridSearchCV) plt.plot(x, state.models[-1].predict(x), label="model") + plt.xlabel("x") + plt.ylabel("y") + plt.legend() plt.show() From 645e838a3384c8ff5803e477cdc5b8498ffe20d9 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 13:59:31 -0500 Subject: [PATCH 07/16] docs: fix broken bits on readme --- docs/cli/basic-usage/index.md | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index daefd597..9ff33dc7 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -106,14 +106,9 @@ print(state) # ) ``` -`state` is the following object which, once loaded, can be treated like any other `State` object: -```python -``` - - +`state` is the following object which, once loaded, can be treated like any other `State` object. For instance, we can plot the results: - ```python title="plot.py" --8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/plot.py" ``` From 6aa50e024b3fa2e91b3ec8c3a3221c6f0ba68d74 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:02:15 -0500 Subject: [PATCH 08/16] docs: rename CLI basic usage page --- mkdocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mkdocs.yml b/mkdocs.yml index 7b6d30e6..421da751 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -28,7 +28,7 @@ nav: - Cycle: - Functional: 'cycle/Linear and Cyclical Workflows using Functions and States.ipynb' - "Command Line Interface": - - "Home": "cli/basic-usage/index.md" + - "Basic Usage": "cli/basic-usage/index.md" - "Using Cylc": "cli/cylc-pip/README.md" - "Using Cylc and Slurm": "cli/cylc-slurm-pip/README.md" From 68f7bac105b574c4eff5d85526a24a2fae3963ee Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:21:46 -0500 Subject: [PATCH 09/16] docs: restructure basic-usage directory --- docs/cli/basic-usage/example/__init__.py | 0 docs/cli/basic-usage/{ => example}/lib.py | 0 docs/cli/basic-usage/{ => example}/plot.py | 3 ++- docs/cli/basic-usage/index.md | 8 ++++---- 4 files changed, 6 insertions(+), 5 deletions(-) create mode 100644 docs/cli/basic-usage/example/__init__.py rename docs/cli/basic-usage/{ => example}/lib.py (100%) rename docs/cli/basic-usage/{ => example}/plot.py (96%) diff --git a/docs/cli/basic-usage/example/__init__.py b/docs/cli/basic-usage/example/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/docs/cli/basic-usage/lib.py b/docs/cli/basic-usage/example/lib.py similarity index 100% rename from docs/cli/basic-usage/lib.py rename to docs/cli/basic-usage/example/lib.py diff --git a/docs/cli/basic-usage/plot.py b/docs/cli/basic-usage/example/plot.py similarity index 96% rename from docs/cli/basic-usage/plot.py rename to docs/cli/basic-usage/example/plot.py index 42e25ca2..4ccb4f48 100644 --- a/docs/cli/basic-usage/plot.py +++ b/docs/cli/basic-usage/example/plot.py @@ -4,13 +4,14 @@ import numpy as np import pandas as pd import typer -from lib import ground_truth, noise_std from matplotlib import pyplot as plt from sklearn.model_selection import GridSearchCV from autora.state import StandardState from autora.workflow.__main__ import load_state +from .lib import ground_truth, noise_std + def plot_results(state: StandardState): x = np.linspace(-10, 10, 100).reshape((-1, 1)) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index 9ff33dc7..9320b85d 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -6,8 +6,8 @@ The command line interface allows us to load and save `States` and run arbitrary To use the command line, we first define a file containing the functions we want to run on the State. -```python title="lib.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/lib.py" +```python title="example/lib.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/lib.py" ``` We can run the pipeline of initialization, condition generation, experiment and theory building as follows. @@ -109,8 +109,8 @@ print(state) `state` is the following object which, once loaded, can be treated like any other `State` object. For instance, we can plot the results: -```python title="plot.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/plot.py" +```python title="example/plot.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/plot.py" ``` ```shell From 2d66293fba106b44dbef7a75cb0fc832f6704de8 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:26:25 -0500 Subject: [PATCH 10/16] docs: update script examples --- docs/cli/basic-usage/example/__init__.py | 1 + docs/cli/basic-usage/index.md | 20 ++++++++++---------- 2 files changed, 11 insertions(+), 10 deletions(-) diff --git a/docs/cli/basic-usage/example/__init__.py b/docs/cli/basic-usage/example/__init__.py index e69de29b..afea99a8 100644 --- a/docs/cli/basic-usage/example/__init__.py +++ b/docs/cli/basic-usage/example/__init__.py @@ -0,0 +1 @@ +# This file is required to allow plot to import from lib diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index 9320b85d..37ff540f 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -15,28 +15,28 @@ We can run the pipeline of initialization, condition generation, experiment and First we create an initial state file: ```shell -python -m autora.workflow lib.initial_state --out-path initial.pkl +python -m autora.workflow example.lib.initial_state --out-path initial.pkl ``` Next we run the condition generation: ```shell -python -m autora.workflow lib.experimentalist --in-path initial.pkl --out-path conditions.pkl +python -m autora.workflow example.lib.experimentalist --in-path initial.pkl --out-path conditions.pkl ``` We run the experiment: ```shell -python -m autora.workflow lib.experiment_runner --in-path conditions.pkl --out-path experiment_data.pkl +python -m autora.workflow example.lib.experiment_runner --in-path conditions.pkl --out-path experiment_data.pkl ``` And then the theorist: ```shell -python -m autora.workflow lib.theorist --in-path experiment_data.pkl --out-path model.pkl +python -m autora.workflow example.lib.theorist --in-path experiment_data.pkl --out-path model.pkl ``` We can interrogate the results by loading them into the current session. @@ -114,7 +114,7 @@ For instance, we can plot the results: ``` ```shell -python plot.py model.pkl +python -m example.plot model.pkl ``` @@ -125,16 +125,16 @@ If we instead run the experiment for 4 cycles, we can get results closer to the ```shell set -x # echo each command -python -m autora.workflow lib.initial_state --out-path "result.pkl" +python -m autora.workflow example.lib.initial_state --out-path "result.pkl" for i in {1..4} do - python -m autora.workflow lib.experimentalist --in-path "result.pkl" --out-path "result.pkl" - python -m autora.workflow lib.experiment_runner --in-path "result.pkl" --out-path "result.pkl" - python -m autora.workflow lib.theorist --in-path "result.pkl" --out-path "result.pkl" + python -m autora.workflow example.lib.experimentalist --in-path "result.pkl" --out-path "result.pkl" + python -m autora.workflow example.lib.experiment_runner --in-path "result.pkl" --out-path "result.pkl" + python -m autora.workflow example.lib.theorist --in-path "result.pkl" --out-path "result.pkl" done -python plot.py result.pkl +python example.plot result.pkl ``` ![png](img/after-four-cycles.png) From 1db28b899aa7e893fef43a97cc245f0ef0bb918b Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:28:39 -0500 Subject: [PATCH 11/16] docs: add note to create library as a package --- docs/cli/basic-usage/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index 37ff540f..abb405fa 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -4,7 +4,7 @@ The command line interface allows us to load and save `States` and run arbitrary ## Setup -To use the command line, we first define a file containing the functions we want to run on the State. +To use the command line, we first define a package `example` containing the functions we want to run on the State: ```python title="example/lib.py" --8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/lib.py" From 569a8462d794c7b1f56358ed6eb4c978021a5d81 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:29:27 -0500 Subject: [PATCH 12/16] docs: add note to include an empty __init__.py file --- docs/cli/basic-usage/index.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/index.md index abb405fa..f4efed31 100644 --- a/docs/cli/basic-usage/index.md +++ b/docs/cli/basic-usage/index.md @@ -6,6 +6,11 @@ The command line interface allows us to load and save `States` and run arbitrary To use the command line, we first define a package `example` containing the functions we want to run on the State: +```python title="example/__init__.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/__init__.py" +``` + + ```python title="example/lib.py" --8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/lib.py" ``` From 3b39b7388a9e4c39e759071062c27f5de74f0522 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:30:02 -0500 Subject: [PATCH 13/16] docs: update comment in __init__.py --- docs/cli/basic-usage/example/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/cli/basic-usage/example/__init__.py b/docs/cli/basic-usage/example/__init__.py index afea99a8..9fe79be5 100644 --- a/docs/cli/basic-usage/example/__init__.py +++ b/docs/cli/basic-usage/example/__init__.py @@ -1 +1 @@ -# This file is required to allow plot to import from lib +# This __init__.py file is required to allow `plot` to import from `.lib` From 32e6bab44572b153b29428ccf22b8977733c1e35 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 14:33:02 -0500 Subject: [PATCH 14/16] docs: rename README --- docs/cli/basic-usage/{index.md => README.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename docs/cli/basic-usage/{index.md => README.md} (100%) diff --git a/docs/cli/basic-usage/index.md b/docs/cli/basic-usage/README.md similarity index 100% rename from docs/cli/basic-usage/index.md rename to docs/cli/basic-usage/README.md From 1e15432cd07a170e88ca56484753f47100fd7915 Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 16:41:20 -0500 Subject: [PATCH 15/16] docs: rename index to README.md --- mkdocs.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mkdocs.yml b/mkdocs.yml index 421da751..5aee1786 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -28,7 +28,7 @@ nav: - Cycle: - Functional: 'cycle/Linear and Cyclical Workflows using Functions and States.ipynb' - "Command Line Interface": - - "Basic Usage": "cli/basic-usage/index.md" + - "Basic Usage": "cli/basic-usage/README.md" - "Using Cylc": "cli/cylc-pip/README.md" - "Using Cylc and Slurm": "cli/cylc-slurm-pip/README.md" From c9c479b098a12d607dc4cddccdb910679b245e3c Mon Sep 17 00:00:00 2001 From: John Gerrard Holland Date: Fri, 1 Dec 2023 16:41:47 -0500 Subject: [PATCH 16/16] docs: use main branch for documentation --- docs/cli/basic-usage/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/cli/basic-usage/README.md b/docs/cli/basic-usage/README.md index f4efed31..0470d14b 100644 --- a/docs/cli/basic-usage/README.md +++ b/docs/cli/basic-usage/README.md @@ -7,12 +7,12 @@ The command line interface allows us to load and save `States` and run arbitrary To use the command line, we first define a package `example` containing the functions we want to run on the State: ```python title="example/__init__.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/__init__.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/main/docs/cli/basic-usage/example/__init__.py" ``` ```python title="example/lib.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/lib.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/main/docs/cli/basic-usage/example/lib.py" ``` We can run the pipeline of initialization, condition generation, experiment and theory building as follows. @@ -115,7 +115,7 @@ print(state) For instance, we can plot the results: ```python title="example/plot.py" ---8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/docs/update-workflow-docs/docs/cli/basic-usage/example/plot.py" +--8<-- "https://raw.githubusercontent.com/AutoResearch/autora-core/main/docs/cli/basic-usage/example/plot.py" ``` ```shell