{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Table of Contents\n",
"1. [Introduction](#intro)\n",
"2. [Conceptual Background](#theory)\n",
"3. [Our Model on the Life-Cycle of Human Capital](#our)\n",
"4. [Dynamic Programming](#dynamic)\n",
"5. [Model Solution](#solution)\n",
"6. [Simulation of the Life of an Agent](#simulation)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Introduction\n",
"In this tutorial, we are going to apply previous ideas as well as introduce new concepts in order to analyze a particular economic question: How do people make decisions about the timing of education and work over their life-time, and how do macroeconomic forces – such as the interest rate or wage growth – affect this decision? To help us approach this problem, we are going to build a **life-cycle model with human capital accumulation** and solve it with Python using an optimization method called **dynamic programming**. \n",
"\n",
"Consequently, this tutorial is structured around two main objectives: Firstly, readers unacquainted with the lingo of economic theory will gain some understanding of how economists go about actually designing a theoretical answer to a particular research question, and how programming can aid in this process. Secondly, readers who already have a passing familiarity with economics will get introduced to a powerful solution technique that helped revolutionize the discipline, but that also finds many applications outside of the social sciences."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Conceptual Background\n",
"Before opening our discussions of our life-cycle model with human capital, however, it is worth pausing in order to reflect on a few points that might need some clarification. For example, it might not be intuitively obious to everyone what the point of economic modelling is in the first place, or even what it is exactly that we mean when we speak of a *model*. Additionally, the notions of both a *life-cycle* as well as *human capital* are seldomly encountered outside of economics textbooks. In order to motivate and facilitate our subsequent exposition, this section is therefore devoted to addressing some these conceptual issues. \n",
"\n",
"*(Note: Readers only interested in the code, or who already have a background in economics, should feel free to skip this section; no information is stated here that is essential to understanding the code itself.)*\n",
"\n",
"## The Use of Models in Economics\n",
"The economy as we observe today is a highly complex phenomenon: It emerges from the interaction of all the 7.5 billion people who inhibit our planet, the vast number of firms employing them to produce the goods and services they consume, as well as the various governments of all levels that act both as regulators and market participants. Attempting to make sense of the aggregate behaviour of such a large-scale system driven by many micro-decisions might seem discouraging, if not futile. At the same time, however, there are also many empirical observations about the economy and human decision making that are quite stable over space and time: For example, as a good becomes more expensive, people generally buy less of it; stock returns are for the most part unpredictable; most people acquire their education when they are young and work when they are older, and so on. This fact suggests that, even if we are unable to offer an explanation for every single phenomena of economic life, there *do* exist underlying relationships that we can try to understand with the goal of informing our policy as well as individual decisions. \n",
"\n",
"Economists use models in order to make sense of such *stylized facts* about the world. Broadly, a model can be understood as \n",
">[...] a human-made **(abstract) simplification of (observational) reality** that is used to understand, define,\n",
"quantify, visualize, or simulate a part or feature of reality.\n",
"\n",
"This is a point worth repeating: A model is by design a simplification of reality, but under no circumstance is it a perfect image of reality itself. For even if it were possible to devise such a model that perfectly represents reality – which it is not – the inherent complexity of such a model would render it useless to a decision maker who wishes to inform a very narrow question. *(To illustrate this point, the Argentinian author Jorge Louis Borges (1899 – 1986) in his short-story \"Del rigor en la ciencia\" [(1946)](https://kwarc.info/teaching/TDM/Borges.pdf) imagined an empire in which cartography was perfected to such an extent that the map (or \"model\") of the empire was as large as its whole territory – only to be abandoned as a useless relic by latter generations!)* Instead, a model is supposed to be sufficiently rich in its structure that it captures the essential mechanism(s) that need to be taken into account in order to understand a particular phenomenon, but not more. Consequently, the simplifications and assumptions that underpin a model should also be evaluated in this light. \n",
"\n",
"In economics, models usually take the form of mathematical equations that describe, and optimally have testable implications about, relationships between economic variables. However, economic models can also be designed to articulate decision problems that are not obviously related to the subject matter of economics. For example, while the model of the [Federal Reserve Bank of New York (2013)](https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr647.pdf) focuses on the classical problem of macroeconomic forecasting and policy analysis that most people would intuitively associate with economics, [Becker and Murphy (1988)](https://www.journals.uchicago.edu/doi/abs/10.1086/261558) develop a model which rationalizes addictive behaviour among individuals. This variety stems from economics as a discipline being first and foremost an \"apparatus of the mind, a technique of thinking\" that is not defined by a particular subject domain, as the famous economist John Maynard Keynes (1883 – 1946) [once put it](https://opentextbc.ca/principlesofeconomics/chapter/1-3-how-economists-use-theories-and-models-to-understand-economic-issues/). In other words, it is *how* economists model problems that make economics a distinct discipline. \n",
"\n",
"Consequently, countless number of economic models have been written so far, and there are possibly just as many ways to classify them, depending on the particular modelling choices one wishes to contrast. One possible (non-exhaustive) classification that is useful in our context emphasizes the incorporation of *time* into a model: \n",
"* **Static** models do not incorporate a time dimension into their structure.\n",
"* **Dynamic** models do incorporate a time dimension, usually by introducing difference or differential equations into the mathematical equations that describe the model. They can be further grouped into *Infinite Horizon*, *Overlapping Generations* and *Life-cycle* models. \n",
"\n",
"The distinction that is introduced here is that some economic models – namely, dynamic ones – are better suited to describe the behaviour of variables over time, instead of merely suggesting static cause-and-effect relationships between variables without describing the dynamic process by which these relationships play out. For example, while a static model might tell us that a positive interest rate shock of $X\\%$ will decrease economic output by $Y\\%$ at some indeterminate point in time, a dynamic model would illustrate how economic output evolves quarter-by-quarter until the effect of the interest rate increase peters out. (The former type of analysis is also called *comparative statics* in economics-speak, as an aside.) Understanding the dynamic structure of a relationship or decision process can be useful in many contexts: For example, projecting out the dynamic impact of a particular policy intervention is of immeasurable value to a politican, to whom it obviously makes a huge difference whether a policy will work in one or only in ten years. \n",
"\n",
"This benefit of a richer structure, however, comes at the cost of less tractability, as dynamic models have the drawback of being mathematically more involved and require more sophisticated solution techniques. To solve and simulate such models, in fact, programming methods are often used. \n",
"\n",
"## Some Terminology: Human Capital and the Life-Cycle\n",
"An important component of any economic model is the assortment of hypothetical agents that populate the model. These agents – such as individuals, firms, governments, or even entire countries – are postulated to work toward achieving a particular objective, such as maximizing profits in the case of firms. They are endowed with resources and take actions that are in some sense \"optimal\" for fulfilling this objective, subject to constraints on the information, resources and abilities they have. All these properties of the agents are expressed through the equations and assumptions that describe a model. \n",
"\n",
"In the model that we are going to analyze, the objective of our agent will be to maximize the discounted sum of her earnings over the whole **life-cycle**. By specifying that the agent optimizes over her life-cycle, we emphasize that the agent is aware that her actions in the present will have repercussions for her future and *finite* life, and that she takes this fact into account when making decisions. Furthermore, this circumstance will result in a behavioural pattern that is connected to what we, the physical embodiment of what our imaginary agent is supposed to represent, would recognize as the agent's life stages. \n",
" \n",
"\n",
"Additionally, our agent will be endowed with time, and her feasible actions that she will be able to choose from in any given period is to allocate this time to one of two activities: Going to school or renting out her labour to a firm. While the former increases her **human capital** and thereby enhances the agent's *future* earnings potential, the latter brings in earnings *immediately*; a situation that generates a trade-off that our agent will have to resolve in light of her desire to maximize the totality his discounted earnings.\n",
"\n",
"To better appreciate why schooling increases future earnings potential, we might briefly consider the following definition of human capital as\n",
"\n",
">*Any stock of knowledge or characteristics the worker has (either innate or acquired) that contributes to his or her productivity.*\n",
"\n",
"In other words, human capital can be best understood as all those *personal* attributes that make a person productive at work, such as particular technical skills, cognitive ability, physical qualities or character traits. In an economic model of production, human capital is usually treated as an input to a production process, similar to physical capital such as machines or buildings. Unlike its physical counterpart, however, human capital is specific to the person who possesses it and cannot be transferred. Furthmore, the process by which human capital is formed is more nebulous and less straightforward compared to the case of, say, a specific machine. One common assumption that we will also make, however, is to assume that at least *some* components of human capital can be acquired through schooling. Therefore, agents are assumed to be able to affect their productivity through their schooling and training decisions, which in turn influences the wage employers are willing to pay. (An opposing argument that is sometimes made, on the other hand, is that schooling is merely a tool that people use to *signal* the skills they already possess. In this interpretation, schooling does not make people more productive.)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Our Model on the Life-Cycle of Human Capital\n",
"\n",
"After this brief detour to the world of economic modelling, we are going to introduce our own model. Remember that its purpose is to try to explain why people allocate their life-time between education and work the way they do. For example, why is it that people usually go to university immediately after they complete school, when they might also decide to work for a few decades first? And how might this pattern change, for example, if the growth rate of wages were to increase?\n",
"\n",
"In order to analyze such questions, our model studies the behaviour of a single hypothetical person. Intuitively, this person can spend time at school in order to increase her future income, but at the cost of foregoing her current income. *(Note: We adopt the convention of labelling the agent as female, although this distinction is irrelevant.)* This is a decision that of course we all face in our lives. What the model captures, however, is that this is a decision that we have to make not only in our youth, but in *all* years of our life, as we are *always* free to change our employment status (well, we can at least try to!). Our agent's objective will be to maximize her discounted life-time income. \n",
"\n",
"This latter point might not be strictly true for how people behave in the real world; after all, there are many other factors that people value in their life other than just how much money they make. For example, having a career that is meaningful and/or leaves time for leisure is probably just as important to most people, if not even more so. However, introducing such subtleties would make our model more complicated than it already is, so we simply \"assume them away\". If we were to believe such factors to be crucial to understanding the question at hand, however, we might want to extend our basic model to take them into account. \n",
"\n",
"A more formal description of our model is the following: \n",
"\n",
"## Model Description\n",
"\n",
"1. Time evolves discretely, *(Action only occurs at distinct, separate points in time.)*\n",
"* The agent is alive for *J* periods (or \"years\"), where $J$ is a natural number larger than 0. *(With respect to the previous point, action occurs exactly at each of these periods. Also, sometimes we will use the more common $T$ instead of $J$, but the meaning will be the same.)* \n",
"* In each period, the agent is endowed with one unit of time. \n",
"* The unit of time can be allocated to one of two activities: (a) full-time school or (b) full-time work. The agent's decision is denoted by a dichotome variable $s$: $s=1$ indicates the agent allocates her time to schooling, $s=0$ indicates the agent going to work. \n",
"* When in school ($s=1$), the agent accumulates human capital, whose value in period $j$ is denoted by $h_j$. \n",
"* When working ($s = 0$), agents rent out their human capital at the wage $w_j$, such that her total earnings for that period amount to $w_j \\cdot h_j$\n",
"* The agent discounts future earnings by discount factor of $\\frac{1}{1+r}$, where $r > 0$ is the interest rate. *(By discounting, we mean that she prefers to receive income in the present rather than in the future, for a given nominal income. The larger the discount factor, the strong is her preference towards the presence. There is a mathematical arbitrage argument that can be applied to demonstrate why income is more valuable the sooner it occurs; however, it should also make intuitive sense that such preferences are innate to people.)*\n",
"* The agent's goal is to maximize her discounted sum of life-time earnings. \n",
"* The wage rate $w_j$ increases exogenously over time according to the formula: $$w_j=(1+\\gamma)^{j-1}, \\quad \\gamma \\geq 0$$ where $\\gamma$ is a parameter that regulates the magnitude of the growth rate. \n",
"* Human capital grows from period-to-period according to the formula: $$h_{t+1}=h_t+(h_t \\cdot s)^\\alpha, \\quad \\alpha \\in (0,1)$$ where $\\alpha$ determines the magnitude of the growth rate of human capital allocation. *(Note that when the agent goes to work $(s=0)$, human capital remains flat: $h_{t+1}=h_t$.)*\n",
"* The value of being alive in period $J+1$ is zero. \n",
"\n",
"This completely describes, or formalizes, our model. In the following, we are going to *solve* it; that is, determine the sequence of schooling decisions that our hypothetical agent should make in order achieve her objective of maximizing her discounted life-time income. This should give us some insight into how the agent – and, maybe, *real* people – trade-off current income versus future income potential. \n",
"\n",
"Before doing so, however, we briefly want to spend some time visualizing the wage and human capital functions under points (9) and (10). This should help facilitate their economic interpretation and, of course, serve as an opportunity to refresh and extend our knowledge of Python's plotting capabilities.\n",
"\n",
"## Wage Function\n",
"First, we plot the wage function $$w_j=(1+\\gamma)^{j-1}$$ for different values of $\\gamma$. The two key points to take away in terms of economic intuition are that: \n",
"\n",
"* For any *given* value of $\\gamma$, the wage increases exponentially over time. \n",
"* Across *different* values for $\\gamma$, the wage increases in $\\gamma$ for any given time period.\n",
"\n",
"This smoothly increasing function is intended to be a reflection of how the economy-wide wage level evolves in the real world. \n",
"\n",
"The below code produces our plots:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAFlCAYAAADRdSCHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xd4FcXewPHv7inpEHqTIlWK9JKGVEWRGkRB5SKIeBXBK1Ug9CJV5IWrgl28iihFuLYrKpIACb1Jb0IgJJRAklNyztmd94/Igc2GopJQnM/z+DwmM7s7Own5nemKEEIgSZIkSdJtQ73VBZAkSZIkyUgGZ0mSJEm6zcjgLEmSJEm3GRmcJUmSJOk2I4OzJEmSJN1mZHCWJEmSpNuMDM75qEaNGnTs2JHOnTsb/ktOTr7VRZNukvnz57N69WoAXn31Vd57773rXpOSkkKHDh3o3Lkz27Ztuynl+O677+jVqxcAc+fOZcWKFQAsW7aMli1b8uyzz+bLc68lLi6O3bt335R79erVi+++++6m3OvP+Kt199lnn7Fw4cI/dE2vXr1o3bo18+fPB2DBggU8/PDDPPjgg8ybN4+rrYK9Wr7z58/Tr18/2rdvT4cOHdi6dav/mjVr1tCxY0fatWvHoEGDyMrKyvPeO3bsoFu3bjzyyCP07t2btLS0P5wvNjaW9u3b+/8evvvuuwC4XC6GDBnCI488Qrt27fz/rubMmUPLli15/vnn/1D93fGElG+qV68uzp07d6uLIeWjp59+Wnz77bdCCCFGjBgh3n333etes3z5ctG7d++bWo5vv/1WPP3006bv9+rVS6xYsSLfnnstrVq1Ejt37rwp97qynm+Fgq47IYzvvGbNGtG5c2fhcDiE2+0WTz31lPj6669N11wr36BBg8Rbb70lhBBiz549IiYmRjidTnHu3DkREREhjh49KoQQYsaMGWLcuHGme2dnZ4sHHnhAbN68WQghxH/+8x/Rr1+/P5TP4XCIRo0aCY/HY7pu+vTpIi4uTgghxMmTJ0VMTIxISUkRQgixdOlS0b9//xuuu7uBbDnfIsuXL6dt27Y4HA6cTiePPPKIv7Xz+eef06FDBzp16kTfvn05evQokPPJ9/nnn+eRRx6hZ8+eDBo0iHnz5gFw+PBh+vbtS2xsLJ07d+bLL78EICkpiR49ejBs2DC6dOlChw4d2LJlCwCZmZkMHTqUDh060LFjR2bMmIHP5wNyWv3nz5/3l/fS1w6Hg0GDBtG5c2e6du1KXFwcuq4b3u3DDz9k2LBhAHi9Xho2bMjSpUsB2Lx5M927d0fXdSZPnkz37t1p3749jzzyiL9cf+Y9c9u5cyexsbF07NiRAQMG0LVrV5KSkkhKSqJTp0706NGDjh074vF48qzvvXv30qJFC//9nn32WUaMGAGAx+OhWbNmfPTRR+zevZsZM2bwww8/ALBt2zZ69OhB27ZteeGFF3A6nYZyJSYm8sYbb7Br1y5/S/dqP+9XX32Vf/7znzz66KPMnDnT9I5z586lbdu2PPbYY/7nX7ruvffeY+rUqezatYu5c+fy4Ycfmp77008/0b17d7p06UKPHj38LcJ58+bx7LPP0rFjR4YOHQrAW2+9RdeuXencuTMvvvgiqampQE7rbvbs2Tz11FO0bt2a0aNHo+s6c+bMIS0tjaFDh7Jjxw5DuXv06MH333/v/3rmzJnMnDkTp9PJ8OHDeeKJJ2jXrh2xsbEcOXLEcG1ycjINGjS46tdffPEFsbGxdOnShWeeeYbDhw8DOb93jz32GLGxscTGxhqef6W8fhZ5/cwu2bx5Mw899JD/a6fTSbNmzThz5owh37x585g4cSIArVu3Zt68eTz55JO0atWKN954I8+yXOmHH36gQ4cOBAcHExAQQGxsLCtXrrzhfD6fjzVr1vD4448DULNmTSpVqkR8fDwJCQncf//9VKpUCYCePXuyatUqU8t8165dhIaG0qhRIwAee+wxNmzYQHp6+g3n27lzJ8HBwfTr14+OHTsydepU3G43AKtXr6Z79+4AlC1blujoaL799tvr1s3dSgbnfNa7d29Dl/aAAQMA6Nq1K/Xq1WPmzJlMnjyZxo0b06VLFzZs2MC7777Lxx9/zMqVK+nQoQMDBgxACMHkyZOpWrUq3377LXPnzvV3S/l8PgYNGsSQIUNYtmwZn3zyCe+//z7bt28HcgJV3759WbFiBbGxscyZMweAyZMnEx4ezqpVq1i6dCn79+/n/fffv+b7/PDDDzgcDr766it/YDxx4oQhz0MPPURCQgK6rrNlyxaCg4NZv349kBMQHnroIXbs2EFaWhqff/4533zzDV27duWdd97xl+vPvOclPp+PgQMH8vLLL7Nq1Sp69erF3r17/ekHDx5k9uzZrFq1ii1btuRZ3/fddx9Wq5UDBw7gdrs5cuQIiYmJAGzYsIG6devSu3dv6tSpw/Dhw3nwwQcBSE1N5YMPPuD7778nNTWV//3vf4ayRUREMGjQIBo3bsyiRYuu+fMGcLvdfP311/4PO5esXr2a//3vf6xYsYLFixfn2Q05atQof/meeeYZw3OPHTvGnDlzWLhwIStWrGDSpEkMHDjQ/2Hi5MmTLF++nFmzZrFixQoOHDjAF198wVdffUWLFi2Ii4vzP+f48eMsWrSIlStXsnbtWjZu3Mgrr7xCyZIlmTVrFvXq1TOUq3v37ixbtgwATdNYuXIl3bt3Z+3atRQqVIjPP/+c77//njp16vCf//wnj9/CvG3cuJEVK1bwn//8hxUrVtCvXz9eeuklICc49unTh2XLljF16lT/z/JKV/tZNGvWzFB3V2rcuDFWq5WNGzcC8M0339CsWTNKlChxzbI6nU4+/fRTFi9ezPvvv2/6N5RbSkoKZcqU8X9dunRp/wekG8mXnp6OrusULVrUn1aqVClOnz7N6dOnKV26tOGarKwsHA6H4d6589ntdooWLWoqx7XyORwOmjVrxty5c/nyyy9JSUlh9uzZeZb9Uvn+rqy3ugB3u48++sjwD+JKEyZMoHPnzgQGBvr/WMXHx9O+fXv/NbGxsUyZMoXk5GR++eUXli9fDkDJkiV5+OGHATh27BjHjx9n1KhR/nu73W727NlDlSpVKFu2LDVr1gSgVq1a/nusXbuWzz77DEVRsNvt9OjRg48++oj+/ftf9X0aNWrEnDlz6NWrF1FRUfTu3ZuKFSsa8pQtW5YyZcqwe/du4uPj6d+/PwsXLkQIwU8//cTChQupUKEChQsXZvHixZw4cYKkpCRCQkIA/tR71q9f3/+9AwcOAPhbvhEREVSrVs2fXqZMGcqVK3fd+n7wwQdZu3Yt1apVIyIigv3793Pw4EF+/PFHQ2vpSm3btiUoKAiAatWqGXof8nKt51+q77xs2LCBBx98kNDQUAC6detmChzXsm7dOtLS0njmmWf831MUhePHjwNQv359rNacPw8///wzu3btolu3bgDouo7L5fJf16pVK1RVJTQ0lIoVK3Lx4sVrPrt9+/bMmDGDM2fOsGfPHipVquT/r3z58ixatIjffvuNjRs3GlrF17NmzRp+++03evTo4f9eRkYGFy5c4JFHHmHixIn89NNPREVFMXjwYNP11/tZXM3jjz/O0qVLadq0KV9++SUDBw68blnbtGkD5ASgYsWKcfHiRcqXL3/V/EIIFEUxfK2q5rbV1fLpum74/qU0i8WSZxpguv+17nGj+dq0aeN/d4Dnn3+egQMHMnr0aFPZ8yrD34kMzrfQuXPnyM7OxuPxkJaWRvny5U1dxJDzi+3z+bBarYaupku/uJqmERYWxldffeVPO3v2LGFhYWzfvp3AwED/9xVF8d8j9z8iXdf93dpX8ng8/v8vX748P/zwA0lJSSQmJtKnTx8mTpxI69atDde0bduWtWvXsm7dOhYsWMB///tfvvnmGwIDA6lQoQJr1qxhypQp9OnThzZt2lC5cmV/N92fec8rWSwWU5fclX9AgoODDe+c26X6btu2LXPnziUtLY3o6GiKFStGQkICa9eu5ZVXXjFdd6nsl1xZ11dzrefnLmte+S7J/QfyenRdJzIy0tClmpKSQsmSJfnhhx9MddSvXz+efPJJIOf34coAfLXfr6sJCgqiXbt2/Pe//2Xbtm3+rsxPP/2UJUuW8NRTT9GxY0fCw8NNgTH3/b1er6GcnTt39vcy6LpOWloahQsXpkePHrRq1Yp169YRHx/P/Pnz+e677wgICDBcn9uVP4ur6dKlC2+99Rbbt2/n3LlzREVFXTM/YHjujdRZmTJlDJOq0tLSDK3T6+UrVqwYQgguXLhAeHi4P61UqVKEhoYahh5SU1MpXLiw6Xcv9729Xi8XLlygVKlSN5zvp59+IiwsjCZNmgA59Xvp38yl64oXL+4v33333XfNermb/X0/ltxiXq+XwYMH8/LLL/PSSy/xyiuv4PV6ad68Od98842/xbV06VLCw8OpWLEiLVq08Hclp6ens3r1ahRF4d577yUwMNAftC7NLL3eTNmYmBg++eQThBB4PB6WLFni/8NStGhRdu3aBcB///tf/zWffvopI0eOJCYmhmHDhhETE8OePXtM937ooYdYtWoVuq5TqlQpoqOjmTlzpr/FuW7dOlq1asWTTz5JnTp1WL16NZqmAfzl96xSpQp2u521a9cCOd36Bw4cyLN1cK36btiwISdOnGDNmjVERUURHR3NRx99RKVKlShSpAiQExSv98f7Wq71/Gt54IEH+O6778jIyEDXdcMHlhsRGRnJunXr/GOyv/zyC506dfKP/10pJiaGL7/80t91PnfuXIYPH37dZ1yrbh5//HGWL1/O1q1badeuHQAJCQl07dqV7t27c++99/LTTz/5fycuKVSoEF6vl0OHDgHw9ddfG8r59ddf+wPDZ599Ru/evYGcce69e/cSGxvLpEmTyMjIMI0L/9mfRXh4OM2bN2fw4MF07949z9+zv6pNmzasXLkSp9OJx+Nh2bJltG3b9obzWa1WWrZsyZIlSwDYt28fhw8fplmzZsTExLBjxw6OHTsGwOLFiw2t20vq1avHhQsX/MNMS5cupX79+hQqVOiG850+fZrp06fjdrvRNI0PP/yQ9u3b+8v++eefAzld4/Hx8bRq1ermVOAdSLac81nv3r1NXTODBw8mMTGR4sWL+1sNq1evZs6cOf7xwd69e/vHiBYsWICqqowcOZK4uDh/q6Js2bIEBgZit9t58803mTJlCu+++y4+n4+XX36ZRo0akZSUdNWyxcXFMXnyZDp27Oj/YPDPf/7TnzZx4kQKFSpEVFSUfwytS5cubNy4kfbt2xMUFESZMmVMk2QAqlatiqIoREZGAjl/ON98803/H+IePXowZMgQOnbsiM/nIzo6mv/973/ouv6n3vNKVquVefPmMW7cOF5//XUqVapE8eLFCQwMNHTHAkRHR1+1viEnCO7atYuiRYvSqFEjLl68aOjSbt26Na+//rqhBfdHXO/5V9OiRQv2799Pt27dKFSoEPfdd59pYs61VK1alYkTJzJ48GB/6+Wtt97yDy1cqXv37qSmpvL444+jKAplypRh2rRp133Ggw8+yLBhwxg/fjwxMTGGtDp16mCxWHj44Yf9rci+ffsyduxY/wez+vXr+4coLgkLC2PYsGE899xzFC1a1D/kATm/Y8899xx9+/ZFURRCQ0OZP38+iqIwdOhQpk6dyhtvvIGiKLz00kvcc889hnv/2Z8F5HzY+Oabb/xd/zdb69atOXDgAN27d8fr9dKmTRu6dOkC5HwI2b17N1OmTLlmvnHjxhEXF0eHDh1QFIUZM2b4e51ee+01Bg0ahNfrpUKFCkyfPh3ImdwVFxfHV199hc1mY/78+UycOBGXy0V4eLg/X2pqqn/4qlSpUlfN16NHD06cOEHXrl3RNI1mzZr55+EMHDiQ8ePH8+ijj6JpGsOGDaNChQr5Up93hAKZEy7dFJ988onYunWrECJnuUK3bt3EmjVrbnGpbr6b8Z7Tpk0TZ86cEUIIcerUKdGkSRNx8eLFm15WSRJCiBMnToj69evf1Hve6uVjl7z00ku3ugh/y6VUsuV8B6latSqTJk1C13W8Xi8PP/ywYbnP3eJmvGe5cuV45pln/OPXkydPNnW/SdLtbsaMGRw6dMg/67ygpaam5ltvwI2aM2cOX331FTVq1Lil5ShoihDXmYkgSZIkSVKBkhPCJEmSJOk2I4OzJEmSJN1mZHCWJEmSpNvMbTMh7MyZzBvOW6RIMOnpzutnlG4KWd8FS9Z3wZN1XrBkfecoUSLsqml3ZMvZav1juyFJf42s74Il67vgyTovWLK+r++ODM6SJEmSdDeTwVmSJEmSbjMyOEuSJEnSbUYGZ0mSJEm6zcjgLEmSJEm3GRmcJUmSJOk2I4OzJEmSJN1mbptNSO5WCQlr+fDDd7FYLDz6aCc6depqSE9OPsGUKeNRFIXKlaswePAIVFXl/fcXsmFDAhaLlUGDBlOrVp2r5pUkSZLuLvIvez7y+XzMm/c6r78+n/nzF7Jy5XLOnTtryDNv3us899wLvPnmuwghiI//hf3797F9+1YWLvyI8eOn8vrrM66aV5IkSbr73DEt54ULbaxdm1Ncux08nqC/fM8HHvDRv7/3qukvv/wiAwe+QtWq1dixYxvLl3/J+PFTrijTm+zcud1wzZw5/8ZmswFw7NhRypUr7z9HuG7deuzYsZ3Wrdv68+/fv48GDRoBEBERxcaNSVSoUJEmTSJQFIXSpUujaT7S09PzzNuiRau/XA+SJEnS7eWOCc63wqOPduL777+hatWX+eabVTz6aEdDev/+L17zeofDQWhoqP/r4OAQHI4sQx4hBIqiGNIdjiwKFw43XZdXXkmSJCn/7bSmEiLsVNGKFMjz7pjg3L+/19/KLVEijDNnXPn+zBYtWvLxx+/Rp08/9u79lREj4gzp12s5h4SE4HQ6/GlOpzFYA4Yx40vpISGheVwXlmdeSZIkKX8dUdMZHvojDXyleS2rdYE8844JzrdCQEAg9eo1YNasabRo0do0+ep6LedKle4lOfkEGRkXCQoKZvv2bfTs2cuQp1q1GmzdupmGDRuTmLiehg0bU65ced566//o2bMXaWlp6LogPDw8z7ySJElS/tERzAlJQkPQ1X1fgT1XBufraN++E//8Zx+WLPnqD19rtVp56aVXGDx4ILqu8+ijnShRoiRHjx5h6dIlDB36Ki+99C9mzJjCggX/pmLFSrRs2QaLxULduvV5/vk+CCEYPHgEQJ55JUmSpPyzKuAA+yznaOmtSFNf2QJ7riKEEAX2tGv4I+c553Rr33j+v6pTp3asXPl9gT3vdlPQ9f13J+u74Mk6L1h3Sn2fUZw8W2gVFhTez+hIEfHXJyJf6a47z1mSJEmS8tubwZtxKT76uRrc9MB8PTI434C/c6tZkiTp72iDLZkE2wnq+ErwiKdqgT9fBmdJkiRJuoITL/8XtBErCv9yNkNFKfAyyOAsSZIkSVf4MGgHZ1UXPdx1qKgXviVlkMFZkiRJkn6333KOFQH7KaeH0dNd+5aVQwZnSZIkSQI0dOYEJyKAV5zNsGO5ZWWR65zz2Z89lWrEiFfIyLiIxWIlICCQ2bP/T55KJUmSlI+WBuzjsOUC7TyVqecrdUvLIoNzPrp0KtU773xMUFAQL7zwLNHRzSlWrLg/z6WTpho2bMzMmVOJj/+FFi1acfJkMosWLfHvpX2tvJIkSdJfc1rN4uOgnRQSAfR3NbzVxblzgvPCoK2stR0HwI4VTyHfX77nA94K1/wh3KpTqe6/vy6ZmZmMGPEKmZmZPP30M0RHN5enUkmSJOUDgeD/gjaSjca/XE0pJAJMeX6yHiNcBNJQK10gZbpjgvOtcKtOpfJ6vfTo8TTdu/cgMzODF154llq1astTqSRJkvLBGttvbLKl0NBXmjaee03pWy2neS1wPc20sjR0yeBs0N/V0N/KLVEijDMZ+b/12606lapYseJ06dINq9VKkSJFqVatBseP/yZPpZIkSbrJMpVs3gzegg2Vl51NUXKtaXbgZXZgEioK/8iuW2DlumOC861wq06l2rQpiWXLljBz5lycTidHjx6mYsV75alUkiRJN9mbQVu4oLh51lWfsrp5r+t3AraRpjh40lOb6nrRAiuXDM7XcatOpdq4MZH+/Z9BVVX69x9AeHi4PJVKkiTpJkq0nmS1/SjVtKJ0z65pSt9sSeFr2yEq6+E87alToGXLt1OpvF4vr776KidPnkRVVSZNmkSVKlWuml+eSnX7ulNOkLlbyPoueLLOC9btUN9Ziofnwv7LBdXNmxntuVcPN6bjoX/IN5xXXMx3tqNqPrSab8mpVL/88gs+n4/FixczYMAA3njjjfx6lCRJkiT9IW8HbeGs6uIp9/2mwAywMGAbZxQnT3rq5Etgvp58C8733nsvmqah6zpZWVlYrXduD/rfudUsSZJ0t9lkPcX39iNU0cLpkccWnRstp/jWdpgqehF6emrdghLmY7d2SkoKL774Ik6nk/T0dN5++20aNrz6mmKfT8NqvXVbpUmSJEl3PwceHudLzuJkEV2pTjFDeqbI5gltGedwssjShepKsavcKX/lW3P2ww8/JCYmhiFDhpCSkkLv3r1ZtWoVAQHmxd0A6enOG7737TBe8Xci67tgyfoueLLOC9atrO83gpM4ac/gKXcdirjtnMFYjlkBiZyyZfAPz/0U8ZjTb6ZrjTnnW3AuVKiQf71v4cKF8fl8aJqWX4+TJEmSpGvaak3ha/shKmmFecptnn2dZDnF97Yjv3dn37oTqSAfg/MzzzzDqFGjePLJJ/F6vbzyyisEBwfn1+MkSZIk6aqceJkTnIQKDHVGYst14lQm2cwJTMKKynB3BNZbfGhjvgXnkJAQ5s6dm1+3lyRJkqQb9l7Qdk6rDnq4a1NDM48jvxW4lXOKi2c8damsFzGlZ5CNFZVgbAVRXHmesyRJknR322lNZWXAASrohejlvt+UvsGSzA/Wo1TTi/JEHrOzz+Ckb+A3TLMnFkRxARmcJUmSpLuYGx+zghNzurMdkdjz6M5+I3ATVlSG5dGdrSOYaU/iItk01coUWLllcJYkSZLuWh8E7SBFzaJbdk1qasUNaQLBnMCNnFdc/MOT92YkX1j3sU1NJUIvy6Pa1Xe5vNlkcJYkSZLuSrssaSwP2Ec5PYzeLvOJUqutx4i3nqC2ViLP7uyDynk+tO6kiAhkiMd8YlV+ksFZkiRJuus48TIjZD0KOd3ZAbnmP59WspgXuJkgbLzqjkTNFXhd+Jhq34APwXBvM8IJLMDSy+AsSZIk3YXeDt7CadXB4+5a1NFKGNJ0BNMCN+DCy0B3Y0qLUNP1C2zbSFYyifVVp7FecGPNl8jgLEmSJN1VNtiS+dZ+mCpaOP9wm7uzF9v38KvlDA/4KtDWV8mUvk5N5mvLYSqLcJ711SuAEpvJ4CxJkiTdNdIVF7ODE7GiMsIRbdps5IB6no/tOykmgviXu4lpHPksTl63b8SGykiPeXZ3QZHBWZIkSborCARzgjdyUcnmWVd90+xrNz5eC1yPhmC4O5IwjGc96Ahm2JPIwMM/vQ2oJAoXZPENZHCWJEmS7grf24+wwZZMPV8pYrPvM6UvDNhGsppBrPc+GmqlTelLLfv9y6Y6alULoshXJYOzJEmSdMc7rWbxZtBmgoWVYQ7z7OskyylW2Q5SSS/Ms9nmceRDSjrv23YQTgCDC3jZVF5kcJYkSZLuaDqC6cHrcSk+BrqaUEqEGNLTFTezAnPGoV91R5nGkd34mGpfjw/BME8ERfJYNnWMi5zGka/vcSUZnCVJkqQ72pKAPey2nqG5tzxtPPca0gSC1wOSuKC46Ztdjyp5HGqxwLaNE0omXX3VaZrHsqlDpPOidTXzLFvz7R1yk8FZkiRJumMdtqTzUdAOiohA/uVsZuqO/sZ2mETrSepppejmNY9Dx6sn+K/lMPeKwvTLY9lUFh4mWjfgRaOzXnDj0DI4S5IkSXckDxrTgtfhQzDUEUkhYZx9naxk8FbAVkKFneHuCNM4dIqSxWz7RgKwMMpj7u4WCGZbNpNCFj31mjQV8uALSZIkSbqmD4N2cMxykQ7Z1WjqK2tI86AxJWg92fgYlN2EkrnGob1oTLatx4GXgd5GeS6bWqYeJEFJpq4oQW+9dr6+S24yOEuSJEl3nJ3WVL4M2EtZPZT+rgam9HcCtnNIPc/D3iq08lU0pb9r3cEB9TxttUq00yqb0n9VzvKOuoNwAhmlRWAp4HApg7MkSZJ0R8lQsnkteB0KMMIRRRA2Q/oGSzIrbPupoBfmxexGpuvXqckssx6ggijEIG9jU/pFspls2YAARmsRFCMon97k6mRwliRJku4YAsHs4ETOqi7+4a5LrVyHWqQpDmYGJmLDwmh3NEF5nEY1y56EHQtxnihTuo5guiWJs7jordemviiZ7++UFxmcJUmSpDvGKvtB1tuSqesrSU93HUOahs7UwPVkKh5ezG5E5Vzbd14aZ876fZz5XmFMB1is7mWTcpomojQ99Jr5+i7XIoOzJEmSdEc4oqbzdvAWCgk7rzqiTbOvP7bv8p829ai3iun696w72a+ep41WiXbavab07UoaH6m/UpwgRmjNTPcvSDI4S5IkSbc9Nz6mhCbgRWeoM5ISItiQvtVyms/seygtQnnFbd5+c4N6kqXW/dwjwhjkbWRKP4eLKZZEFCBOi6RwrkMxCpoMzpIkSdJt7+3gLRxXM+icXZ1I7z2GtHTFzbTA9ajAaFc0odgN6amKg5n2JGyojPFEE5xrApmGzlRLIhdw85xej9qieH6/znXJ4CxJkiTd1n6x/cbX9kNU0cLp72poSNMRzAjcQLripm92fe7TixnSfehMsa0nEw8DvI2onMc480fqr+xUzhAtyhGrVzOlO/DyMj8zj20398WuQQZnSZIk6baVqmYxJzgpZxcvR4xpF68vbHvZbEmhiVaWx/LYnvN96072qudorVWkfR7rmTcop/hM3UsZQhiqNTF1d+sIprGJPZw3tcjzkwzOkiRJ0m1JQ2dq8Docipe/wLkvAAAgAElEQVSXnE2ooBt38dqjnuWDgB0UFUF5bs+5QT3JF9Z9lBNhvOxtbAq8J8hgmiUJGxbG+qLyDL6L2EsiKTSgBP+g4GZvy+AsSZIk3ZY+DtzFHutZWnor0s5jbPVmks3UoHXowEh3FOHCeMzjSSWT6fbE38eZo0zjzE68jLeux4mXwVojqmI+rSqek3zCXkoTTBzNCnSXMBmcJUmSpNvOdutpPgvcTWk9hJcdxtnXAsGswCRSFQdPeWpTXytluNaFjwn2BBx4ecXbhCrCGHh1BDMsGzlOBl31arQVlUzPP8JFZrCJQCxMIIpCBTx723r9LH/OsmXLWL58OQDZ2dns3buXdevWUahQofx6pCRJknQXuKi4mRayHgUY6TDPvl5i28t6azJ1tZI87TFuRCIQvGHbxFHlIh21qjyYx3rmxepe1iknqStK0F83HxOZQTbjWI8bjbFEUBnzoRj5Ld+Cc2xsLLGxsQBMmDCBbt26ycAsSZIkXZOOYFZwIucUF8+66pu259xhSeX938eZ49wxpq7mrywH+cnyGzX1YrzgNR+IsVFJ4cPfNxqJ0yKx5rpeQ2cySZzGyVPcR3PK3fyXvAH53q29a9cuDh06xBNPPJHfj5IkSZLucEsC9pBoO0kDX2kez65lSDurOJkcmHPgxRhXDEVyjTPvUs/wtm0b4QQwxhONLdfM7lNk8ZolCSsq433RFMF4PcBCdrGNM0RQhn9Qy5ReUPKt5XzJggULGDBgwHXzFSkSjNVquW6+S0qUCPsrxZL+IFnfBUvWd8GTdV6w8qrvraSwiF2UIYzZtnYUDbp8GpRP6IzU1pCFlyFqJK2CjBPEzgon07OTsKAy2/4gtcKM49BO4WWq60fcusbYgGhibOZjJL/2HGal8wjV1CLMDmtFiFJwS6dyy9fgnJGRwZEjR4iIiLhu3vR05w3ft0SJMM6cyfwrRZP+AFnfBUvWd8GTdV6w8qrv84qLIYW+x6doDM+MRNN8nOFynrcDtrLZdooHfBVo665oSPOhM9z+M6lqFv299amQGWpIFwimWBLZr5yjo16VSFdpQzrAPs4znnUEYmEUTXBmZ+MkO59qIMe1PhDma7f2pk2biIqKys9HSJIkSXc4DZ0pIQmkK26eczWkTq5x5rXW4yy17eMevRBD3M1M65XfsW5nl3qGB7TyPKbVMN3/C/UAvygnqC2K80IeE8DO4WI8G9DQGUVT7sEcNH1CRwjxF9/0xuVrcD569Cj33HPP9TNKkiRJf1sfBu5kpzWNaO89dMs27vJ1QslgVmASgVgZ525uWq/8k+U3llkPUEEUYojXfODFViWV99SdFCWIsVqUaRzag8ZEEjmHm2e5nyaUNpXvrHDRV1vNa/rmm/TG15ev3dr9+vXLz9tLkiRJd7hEWzKLA3+ljB7KUEekIbg68TIhKB4XXka6o6iUa4ewo8oFXrdtJAgr4zwxpsB9GgdTLBtQURirRVI01wQwgeB1trKH87SmPN0x76vtFD7GaImk4KCzYt7+M7/ITUgkSZKkW+K0msX04PXYUBnneMCwnlkgeCNwI7+pF+nsrU5rXyXDtVl4mGBfRzYawzzNqCCMS3WdeBljSSADDwO0BnmeNPUp+/iR49SkKEMwHyOpC8Fr+iYOcYFHlIrEKuYzovOLDM6SJElSgfOgMTEknizFy0BnE6poxl28VtoO8rP1N2ppxXk+27heWUcw3Z7ISSWTJ3w1aa6XN6W/ZknimHKRTnpVOghzUF3DCT5kD6UIZgKRpgM1hBD8W99JojhNI6Ukg9T6KIpiuk9+kcFZkiRJKnBvB23hoOU8D3kq87DHGDz3qGd5O2ArhUUgce4Y0zjxB9adJKqnaKiXoo/vftO931N3kqicooEoxYt6fVP6Xs4zg80EYWUSUXmud14mDrNSHKEShYhTm2JVCjZcyuAsSZIkFajvOMSqgIPcq4Uz0Gk8pvG84mJSUAI6glHuKEqIYMO1P1mOsdi6l7IilDhPlGmHsO+VoyxR91OOMMZokab0VByMZT0aOnE04948tuZcp59igb6LogQy2RJJqGIz5clvMjhLkiRJBeaYeoEpxBMkrIx1NCfwinnJHjQmBMZzVnHSJ7seDTXjzOn9yjlm2TYSjJWJnuaE5TqMYpdyhjcsWwjFzmRfDGG59uR24CWO9VwgmxepR9M8ZmbvE+eZqm8mAAuTLZGUUoJNeQqCDM6SJElSgXDiZVJozuzrIc4I7tEvT+ISCOYHbGaP5SytfBV5wms8O/kcLsbZE/ChM8oTRUVhbPGexsF4y3p0BGO0SNNaZQ2dKSRxjAw6UZnOVDWV77RwMEZLxIfOaLUJ1ZTwm/j2f4wMzpIkSVK+0xFMD1nPcTWDntShhde4feYq20G+tR2mil6Ewbk2GvGgMc4ezznFRT9fPZrpZQ3XXp6Znc1LWgMaCuPWnQBvsZNNpNKEUryIeSOSLOFhtLYhp1Wt3k+EWuYmvfmfI4OzJEmSlO8+DdzNelsydX0leRnjls47LWm8GbCFwiKQCa4HDF3dAsHrtk3sV8/TRqtEd59xk5LcM7M7CnOL+CsO8RWHqUQhRtPMNA7tFTrj9SSOk0msUoXOasEtmboaGZwlSZKkfLXBlszHgTspqQczxtHccExjquJgQmA8AGPdMZQSIYZrv7Du40fLMWroRRnsbWJai3y9mdkbOc2b7CCcACYTRUiujUqEELyhb2OHOEuUUobnVfPsbyEEy32HWa+l/Ok6+KNkcJYkSZLyzQk1g2nB63KOaXS0IPyKYx7d+BgXtJYMJZsB2Y2pq5U0XJuknuJd6w6KiSAmeJqb1iJfb2b2US4ymZyTqiYQSSmMgR/gQ30v/xPHqU44I9XGqHmsZf7Yt583fbv5QTvxV6riD5HBWZIkScoXWXgYG7oGp+JjiDOCalpRf5pAMDswicNqOo96q9LBa+yOPq5kMNW+HisqEzwxFCPIkL5bOXvNmdlncDGKBFz4GEZjalHMVL6v9MN8KvZThhAmWyIJVMw7Wi/3HeYTbT9llGBestX9K9Xxh8jgLEmSJN10lyaAJauZdMu+jzaeew3pn9v3sMb6G7W1EgzINm6dmUk2Y+3xOPEx1NuUGsIYWJPJZJwl4aozs7PwMIoEzuKmH3VohXEHMYBf9JP8W99JOAFMs0RRRDFvRPKjdoI3fbspQgDTbVEUyyNPfpHBWZIkSbrpFgXuItF2kga+0jznMm6/maAf5337ToqLYMa5mxt2APOhM8m+npNKJj18NWmtVTJcewE3o6zxZODhX1oj08xsDxrj2OBfMvU41U1l266fYZq+mUCsTLVEUVYJNeVJ1E4z07uNEKxMs0dSRjV3iecnGZwlSZKkm2qd7QSfBO6itB5CnCPGMBZ8QslgtP5zzhi0qzlFrhiDFgj+z7aZbWoqEXpZ+viM3cjZaIy1rCOFLHrqNXlEGE+J0hHMZDM7OUs0ZRlAfdMEssPiAuP0RADGq83yXMu8Sz/HRO8mLChMtkdQWTXvIpbfZHCWJEmSbppj6gWmB6/HjoXxjhYUEpd38cokm7FBa3HgZbC7KTV0Y3f159Z9fGs5QhVRhJGeSNQrAquOYJolib3KOdqIivTR65ie/R67WUMytSnGSJoaroecTUZGautx4WO42oiGaknTPY7oFxnjSURHMNbWlDqqeay6IMjgLEmSJN0UWYqH8aFrcSk+hjoiDCdN+dCZGJRAsppBL+V+2vqMY9C/qMd5z7qD4iKIydnNTWczL1B3kKAkU1eUYLDW2NQiXsEhlnCAewhlIpEE5JrZfUFk86q2nnSyeUGtSyv1HlP5T+kOXvVswIGP4baGNLOYNzMpKDI4S5IkSX+ZjuC14HWcVDN5wl2LVt5K/jSBYG7AJrZbUon03cNAtanh2l+Vs0y3JxKElSmeFhTHuJ/1cvUgy9QDVKAQ47Vo05KqeE7yJjsoQgCvEUOhXHtuO4WP0dp6TpJFD6U6XfPYZOSccPOqNyd4D7DeT2uLOXgXJBmcJUmSpL/svaBtbLSdorGvDH3dxs1Altj28t3vW3OOdEcZ1hKnKFmMC4hHQxDniaayMI4Br1NO8pa6nXACmeJrbloytYuzvMbGnMldxFA611pmr9CZpCdxgAs8pFSgr1rLVPZM4WGkZz0pwkkvaw26WCub8hQ0GZwlSZKkv+Rb+yGWBOylnB7GKEe0Yaw3wXqC9wJ2UFwEM8nVgqArtubMJJtR9l+4SDYveRvRVDfuZ71POcdUSyJ2LEz2mQPvb2QwjpzDLsYSQVWMgV0Xgtn6VjaLNJoppXlFbYCSa5MRl/AxxpPEUZFJJ8u99LLUML2fEIJV3mMk+lL/dB39UTI4S5IkSX/aDmsqc4M3EibsTM5qSdgVE8AOqOd5LTBnctgk1wOGs5m9aIy3ryNZyaS77z46asZNSFLIIs6ScwpVnBZBDYoa0s/hYjTryMTLYBrRGOP4sBCCt/Vd/ChOUJOixKlNsCrGkOcRGuO8SfwqztNKLccA6/2m4C2E4F3PXv4vexffeY//pbr6I2RwliRJkv6UZDWDCSFrUYDxjgcMR0CmKQ7GBP2CF53Rriiq6lfsDiZyDrPYqaYRo91DP5/xlKhMPIyyxnORbAZoDYgQxlOocjYZWUcqTvpQm4cwnnAF8LG+j+XiMBUJy3P3L6/QmejdxDb9LJFqaYbbGpq27hRC8L5nH0u8h7lHCWVQgHnf7fwig7MkSZL0h2Uq2cSFriFT8fCysxl1fZdbrk68jA1ay3nFxfPZDYjUjJOr3tO2s9pyjOp6UUZ4Iwzd4DlrmRNIJpPH9Rp0ynXKlAsfo1nHES7Skcr0xNwN/YV+kE/EPsoQwnRLDIUU4zi1JnSmejeTpKfSWC1JnK2xqVUN8JFnP4u9hyinhDAzKJKiqtwhTJIkSbpN+dCZGBLPSTWTx7Nr8rDn8uxnHcHUoHUcVtPp4K1KrNcYPH+0HONt31ZKiWAme4zHQ2roTLZsYLdylpaiPM/qxk1IvGhMIpE9nKc15Xkpj01GvtaPslDfTXGCmGGJNm25qQvBDO9WEvQU6qrFGGdrgl0xzv4GWOQ5wH+8BymjBDMzKJLiBRiYQQZnSZIk6Q8QCOYHb2K7NZUo7z08m2trzgUB20iynKKRVoYB2cb1yNvVVGbZNuYcVuFpQRGMu4PNUbeQqJyioSjFcK2paROSGWxmE6k0pRTDaGzaZORnPZm5+nYKYWe6JZrSinECmS4Eb/i285N+klpKESbZIvI87OJTz0E+9uyn9O+BuYQaZMqT38ylkiRJkqSrWBawj6/th6iiFeFVR5QhQK60HWCZbR8V9cLEuaIN5zYfVtIZa48HBDNsrakkChnu+566i+/Vo1QXRRmnRRn22xYI5rOdNSRTh2KMIcJwb4BEPYXp+maCsTHdEk0FxXgYhhCCf/t28a12nGpKYabYIwnOIzAv9hziA88+SilBzAqKpJQabMpTEGTLWZIkSbohG2zJLAjaSlERyKSslgRdsYtXkuUU/w7YQrgIZLKrBaFXrEc+rWQx0v4LbnwM90bQ1FLOcN8v1P18ru6jHGFM0WJMu4N9wK+s4ghVKMwkogxd4ZBzkMVEfSNWVCZbIqmaa79sIQTv+vawUjtKJSWMafYoQhXjMwC+8BzmPc9eSihBzLyFgRlkcJYkSZJuwGFLOlND1mHDwsSsloZlUfvUc0wKSsg5e9n1AKXF5VOeLuDmVfsvpCtuXvA2pJVmnFn9g3KMheoOihHEdN8DhGMc2/2SA3zGfsoSwmvEGII+wF5xnjH6BgQwQY2gjmLeC3uRtp8l2iHuUUKZYY82TRADWOY5wkLPHoorgcwMKvhTqHKTwVmSJEm6pvOKizEha3Dj41VHFDW0ywHwpJLJ6KA1eNGIc0VTSy/uT3PiZbR9rf/4x66a8fjGROUUsyybCMPONN8DlMq1ych3HGMBuyhGINNpbhijBjgiLjJaW48HndFqExrlcZDFYt9BFvn2U0YJZoY9iiJKgCnPV56jvOX5laJKADODIimXR2AWQtxYZd0k+RqcFyxYwBNPPEFsbCxffPFFfj5KkiRJygdOvMSFruGM6qSPux7NvRX8aemKm5HBP5OhZDMwu4lhyVTOuczrOKCe50GtEn1zHf/4q3KWSZYNWFGZpMVQCeOxjOs4yRy2EIaNaTQ37Q6WLLIYoeVsQjJMbUiMalwLDbDUd5j3fHsoQSAzbFGUUMwTu1Z4jjLfs5vw3wPzPar5bOc03cULWQm84dx1Y5V2E+RbcE5KSmLbtm189tlnLFq0iNOnT+fXoyRJkqR84ENnckg8By3naeepTE93bX+aEy+jg9aQomTxlKcOHbyX1yPrCGbZNrJZPU1TvQyDvU0Ns7YPa+n+3b/GalHUFsUNz91GGpPZiB0LU4mhEsbJY6dEFsO0BC6QzUC1Hm3VCuT2he8Qb/t2U4xAZtijKZ1Ha3iJ5zD/9uymyO+BuYIaZspzSnMwOHMDh7UMyhTgGHS+zdZOSEigevXqDBgwgKysLIYPH55fj5IkSZJuMoHgjeAkNtlSaOItw7+czfwB1ofOpKAEDqrnaeetTG+Pcees96w7+NFyjPv0YsR5jLO2U3EwzL2WLDyM0JrSTBj30/6Vc4xlPQATiOS+XNt2nhYOhmoJnMXFc2odOqnmQyqW+A7yjm8PxQlkpj06z9bwp56DfODZ5x9jzivPMS2TEVlJnBfZ9AmszuMBBXcgRr4F5/T0dE6dOsXbb79NcnIyL7zwAt99951p39JLihQJxmo1LwS/mhIlzJ9wpPwj67tgyfoueLLOjRayhR85xv2UYq6tPcHBObObhRBM0NeyXaTRQqnElMA2WAtdDr6f+nazzHeAKkoR3ra3J/yKTUDO6y7GutZzRjgZFhJBT3ttwzP3+M4yLmsDOjAruCUt7cYWcYqWxagLiaQrHl4JaUTvYOP1AB9n7eGDzH2UtYeyoFgbylvNS6oWZvzKIvdBygeE8XbJVpSzmgPzvux0Rp7eRIbFy4iiDelZuLopT37Kt+AcHh5O5cqVsdvtVK5cmYCAAM6fP0+xYuaZdADp6c4bvneJEmGcOZN5s4oqXYes74Il67vgyTo3+tZ+iDeDN1FaD2FMZjQO4caBG4D37TtYYd9Hdb0YQ5xNScfhv+4ny2/MsG2gqAhkgicGr/ByBi+Qs1/2UMsajigXeDa4Hg9drMAZLtf5YS4wlLU48TKSptS+WMSQniacDNHiOY2TPmot2jsqcMZh/Jl97jvIu7+3mKfamxGYjuEeQgje8+zjc+8hyijBvGZvij1dGPIA/OpLZ1TWRlz4eCXoftp6yuTL78e1PhDm25hzo0aNiI+PRwhBamoqLpeL8PDw618oSZIk3TJJ1pO8EZxEIWHntazWFBGXJ1GttB3gM/uvlNXDmJzr+MdNagozbYkEY+U1T0tKictjvA68vGpZyxHlAp30qrxkb2R45lEuMpx4HHgZRmNaUt6Qfka4GKolcBon/1Br8qRq3k97se+APzDPtsdQLlc3tRCCtz17+Pz3vbJnB0XluY55q/csI7ISyUZjZHADHgkwj2cXhHxrObdq1YpNmzbx2GOPIYRg7NixWCw33m0tSZIkFaz9lnNMCo3HgsrErJaGU6YSrCeYH7CFwiKQ11wtKSIud1fvUtMYb09AQWGS5wEqi8sNMRc+xlgSOKCc5yG9EgN045nKJ8hkOPFk4OEVGtI21wlTZ4WLYVoCKTh4SqlBL/U+U7k/8x3gfd9eShDILHsMZVXztp3zPbtZ5T1GRTWM6YERFMtjr+wN3lQmOrYAMC6kEZG2UqY8BSVft++Uk8AkSZLuDClqJnGhOeuVxzoeoLZWwp+2y5LG1MD1BGBhiqsFZcXl7tgDynni7GvR0BnvaU5d/fJaYw8a4y3r2KWcoaUozxC9iWG7z1NkMYy1XCCbl6hHe+41lOm8cDNMS+AkWfRUatBbrWkq96e+A3zg20tJgphljzZtHqILwRvZO/nWd5x71TCmB0ZSRDWvdf7Zc4rpzu1YUZgY0oSGtuKmPAVJ7q0tSZL0N3dRcTMy9GcuKG4GOpsQ7b3crXxQPU9c0C/o6Ix3taCGfnne0DHlIiMD1uBGY6Qnkgj98lpjHzqTLBvYqqQSIcoyQmtmCMypOBjGWs7h5nnupzPGoyHTfw/MyWTxuFKNPmpN04Ti//j286FvHyUJYnYey6V0IZiZvZ3VvmSqqoWZHhSR5+5g32Wf4HXXToKwMiW0CXWsRU15CpoMzpIkSX9jbnyMCf2Fk2omPdy16OS5PCv5hJLByKA1uPDxqjuSptrl4JuiZDHC/jMZeBjibUpL/fLYrI5guiXJf8LUGC3SsJwqTXcwjHjScNGH2jyGcSb0BZHNMC2B42TSTalKP7W2ITALIfhE28/Hvv2U+r3FnDswe4TGNPc24rUUaqjhTAuKyHM/7SXuw7zj3kchxca0kGZUsxY25XEJHwuy9lHJGkqXoEo3Xrl/gQzOkiRJf1M+dKaEJLDXcpY2nkr0cdf3p6UqDkYE/8RFxc3L2U1p7avkTzuDk+H2nzmvuPmntwEPa5fX/+oIXlc3s0Y5QR1RnPFaNPYrTpg6j5uRWetyxpC5jycxjiGnCzfDtXX8RiZdlSo8r9YxBeZ3fXtYoh3KOdLRFmUKzC7hY4J7M1u0M9RVizExqAkhuQKzEIJ33ftYkn2E4kogr4U2pZLFPHv6gp5N3MUt7Pdd5NHA8qb0/CKDsyRJ0t+QjmBW8AYSbSdp4CvNEGeEv9s5XXEzIugnzihOns2ub9j96wJuRgT8zGnFQW9fHbppl2dOCwT/Vrf5j36crDU3zOhOx81w1nJSd/A41elNLUOZzgoXw7V1nCCTzkplXlDvNwRmXQjm+3aySjv2+yEW5i05s4SX0a4k9ujpNLOUZExgYwIU42RkTejMdu7kB+9J7lFDmBbajFJ5nNl8SnMy8uImTmlO2gaUY0BoLVOe/CKDsyRJ0t+MQPBm0GZ+tB/jPq0Y47Me8J+fnIWHkUE/53Rze2rRw3s5IGXh4dWAXzihZPKYrwZP+Wob7vmuupOV6iHuFYWZpj1AyBVHP57HzTDWcpxMnrbX4h/e+wxbeqYJJ8O0BE7hoLtSjedydWVrQme2dzs/6CeorBRiWh6HWKTr2Yx0J3JYz6CVtRzDA+pjVYwrht1CY4pjK4m+NGpYCjMlpCmFVfM49H7vRUZf3MxF4aFncBX6BFe76iZa+UEGZ0mSpL+ZRYG7+CrgAJW0wkzNauU/P9mFj9FBazisptPBW5W+nnr+a1z4GG1fy2ElnfZaFfr76vuDq0DwoforS9T9lCOM6VoLwq442vEsLoaxlmSyiKUqQ4KacNaR5U8/LRwM+30d85NKDZ7JNfnLK3SmebewVj9FDSWc1+yRhOWa2JWqOxnhSuSkcNDBWpGBAfej5gqmmbqHMY7N/Kql08hanLEhjQhWzGFwo+cMkzK24RE6g0Jr0zGo4Nc6y+AsSZL0N7I8YB+LAndRWg/htazWhImc1qcHjQlB8eyxnKWVryIDs5v4g68HjXH2ePaoZ2mlVeBlb2NTYP5U3UMZQpnpa2E42vHM74H5JFk8RjX6Y+yqTv79EIuzuHhGrclTudYxe4TGRO8mkvRU6irFmGSPMAXU43omI1yJnBVuetiq0td+n6mVe0Z3MSprI8f0LFrZyjIsuB42xbwP13fuZOZk7saCwthCDYgOuDVrnWVwliRJ+ptYbT/Cm0FbKCICmZ7VhuIiZ4csDZ3XAtezxZJCM60sw92R/vFnDxqT7OvYpqYSoZdluPfy2HTuwDzb15ISXN51Kw0nQ1lLCg6eoDrPUsfQlf2byGCYlkA62fRTa/OEapy17RQ+xnmT2K6fpbFaknG2JgTmCswHtQu86koiAw/97DV5wm5ckgWQrGXxatZGUoWLzvaKvBhU29SqFkLwH+dhPnIeJEyxMalwI2rbivyF2v5rZHCWJEn6G9hgS2Zm8AZChY1pma0pq+fMTNYRzAnYSIL1BHW1koxxxfiXPXl/D8yJ6ika6qUYc8UJU9cLzKk4GfZ7YO5JDfpQ2xCYj4iLDNfWcZFsXlTr0lWtYihvlvAw2pPIHpFOtFqGUbZG2HNN7NqpnWOMK2cP7H8F1OVRm3F3MYD9vguMcmwkQ3jpE1idngFVTa1qTej8X9YevnGfoLQaxNTCjSmfx2EYBUkGZ0mSpLvcDmsqk0LisWFhclYrKus5LUKB4O2ArXxvO0J1vRgTXS0I+D0s+NCZbF9PonqKBnopJnqa+5dECQQfqLv5TN2bZ2A+/fsGI6dx8jQ1+Qc1DYF5n/c8Q7V4MvHyslqfDqpxZ7CLIpsRng0cFhdpo97DMFsDLLm6oBN9qUx0b0YgGBXQiJa2suS22XuGiY4tZKPxr6D7eTSPfbJdwsfUjB0ketKoYi3E1MKNKZrHDmIFTQZnSZKku9h+yznGhKxBIBif1cK/LadA8I59O8tt+6moF2aqq4V/drUPnSm29axXT1L/98B8KWhfGZjLEsqsXIE5hSyGspY0XPyDmvTKtVxqrzjP2ItJZOFlqNqQdqqxtZsmXIz0rOe4yOJRS0UGWeuZuqC/8x5nTvZO/p+9846vqr7///Occ1dubnZC2CtA2JCwwhSpbW2rtnW332pbd9VKHcjeU0BUsKK2jlpn62jV+lUrgjJkjxASVkICmWTffc8953x+f9x8Ey43Fn/fSmq/Pc+/hPu5N58c8vCV93q9LcgscoxhrKUT5/Nh6AyPBfJRkJnnzGWyrUvMmTo9yHz3Pk5qbnKtaSxMzMUpx8pitRZgVVM+2bYkfpUY6+19MTDF2cTExOT/KGVyM3NcnxKSNOb6JjNai0SXAsHztnz+bCuiu5HI6sA0kloWWWgYrLB+wTalnOFGJ5aqk3F8RWGuaPHKrm1x/nXDmRkAACAASURBVDrfYOSgUcsCYye6JJglj2aaHG3qUWZ4mK3uoJYg1yhZ3GmJdQZ7NXyCF9VjJGJjadxYBivRdWEhBC8FT/ByKFI7XhI/ul07zmLNzbzmfdQZQS53dGe6a0jM2BXAYbWRRY0HcRsqYx0ZMa9fLExxNjExMfk/SJXsYZZrE25J5X7/OKaE21K6L9kO87rtCN2MBNYEppHashZSx2CV9Qu2KmcYbmSwTJ3ylYU5sl3qc+oIcitDuZHotY47jCqWGbsRwOrEKQxzR4tqkdHAXHUnHsLcZhnM9Uq/GAOSDaHDvK+VkSnFsTIujx7nrYUMC4N1/nw+CVfQRY5jRfxYuiuxteOdobMs9xwkKHRui8/m+rg+7c4wf+iv4InmQgwE9yUO5sp40yHMxMTExOR/SY3sZYZrE3VygDsCOXxfbetgftlWwMu2AroIF2sC0R3bq6w7+Uw5wzAjg6XqlFZ3rwsJczFNzGQrzajcwTCuO88r++/GadYa+7Ehs0jOY5q9J7V4Wl/fo9ewOLyHMDoPWkZyuSU61R0SOiuC+9mhV5MlJ7LcMS5m5aNXhFni28cBrZ5sJYml8WPa3T71l0ApG71HW0elJts7x5wxhOBZz3He8pWSIFmZnzKCHHtazLmLyZeK80033fQP3VBeeumli3IhExMTE5P/PbWSnxmuTdTIPm4JjOC6UFvN93XbEf5gy6ezcLHG/y0yWoTZQLDauostymmGGOksU6e0GpMIBM/Jh3lDPtquMB+hnrlsw4/GfeRwJX2j7vO2cZKNxmESsLJMmcBgKTrF/KlezurwfmQkFlnHMl6Jrg17hMr8wB6OGA3kKOksdIyO8cmuNQLM9e7hlOFhvCWTOfE5ONqx7HzKW8S7wdMkyzaWJo5ioDWZ8/EZGiua8tkdqqWHJZ6lKTl0s8THnLvYfKk4//rXv+7Ie5iYmJiY/JPUSwFmJHxClezlpuAwfhIa2vran6xFPGc7RIZwssY/jUwREZz/EeZPlTIGG+msUC9pFWajxSv7Xfkk3UhgjXZJlDDvp4YFfEEYnZmM4Vu0pc6FELxkHOVlcZRUHKxSJtJHSoy67ztaMU9pBcRjYYltHMPl6B3KNYafOYFdnBZeLrV0Y4Z9ZIxxSLHuZp53D3UiyFW2XtzTzgyz39BY7jnIbrWW3oqLZUmjyVTa8dLW/CxoPECZ5mW0PZ25ycNxybGbrDqCLxXnsWPHtv73vn37OH78ONdccw2HDh1izJgxHXI5ExMTE5OvRmOLMFfIHn4SHMJNwWGtr71lPcrv7AdIF07W+r9FZxGpw+oYrLXuZpNSyiAjLUaYH5X38LFcSm+RxGo92vlrB5UsZRcACxnPBNpGmQwheMrI56+ihC7E84gykS5SW/QphOD5cCGv6SdIwc5K23iy5OhVjSW6mznBXdSLINda+3K7bXCM6P7PqFQAnTscg7jWHls7PqsHmO/eR4nmYbQtnbkJI9sV3EOhBhY3HsQjwvw4vhd3JgyIGd/qSC5Yc/7DH/7AJ598wtmzZ7n88stZsGAB1157LbfeemtH3M/ExMTE5AI0S0Eedm3ijOzmutAgfhkc0TpX/FfrcZ627ydVxLHGP42uImI+orU0f32mnGFgizCfO0q1StnFZ9IZBohUVuqTSaStfvsJZaxhLzYUFjOeXNosLjVhsNbYzyZxhj4kslKZSJrUJuqGEKxw7+HP+gm6SE4esU6gy3krHw/pdSwM7MGHxp22wVxrizYogcio1OOBw8hIzHPmcIktds75WLiZBe59NBghrnD04F7X4HYF92/+cjY0FwLwm6Qh/MDZ/Ss/+4vFBX8teOedd3juueeIi4sjJSWFN998k7feeqsj7mZiYmJicgE8UoiZrk2UKs38KJTN7YGcVmF+33qSJ+17SRYO1gSm0V1E0soqOkts21ubv1apU3G1LKpQ0Vms7OCzln3Mq/VLooT5PYpZzV6cWFnF5ChhDgmdxcYuNokzDCaVR5XJUcIcEjpLw3t4x3+SLCmJJ2xTYoT5k3A5swI7CaEz254bI8yGEDwbKOLRQD5OycIjrnHtCvOnwUrub9pJoxHizviB3OcaEiPMYWGwvrmQx5uPRD4rdXS7wiyE4ItALUWh5q/0b/J1cMHIWZZlbLa27R92ux1FUf7BO0xMTExMOgIvKrNcn1KsNHFlqD93B0ZFRcxP2veSJBysCXyLnkYkbRxEY7FtG3vlanKMTBarbTuXA2gsVLZzQKohV2SySJ8YtY/5dY7xHAUkY2cVk8iiraHKK8Is1HeSTx2jpE4slMcRd44PdrMIsUDdRaFoZJyjM7P13KjGLiEEL6nHeTl8HBdWFjhGk2OJrkH7hcZK3wF2amfpLsezLH4M3ZRocTeE4AX/cV73l+CULCxMyGGcPdakpEEPsbTpEAVqI30sCSxKGUlXizPmXEjorG88yse+SvIcGSzNGPmV/33+GS4ozmPHjuWRRx4hEAjwySef8MYbb5CXl9cRdzMxMTEx+RL8hJmTsJnjSgOXq1ncG2jbIvWm9SjP2PeTLBysDkyjd4sw+wkz37aVfPks44yuLFAntlpyelGZp2zjiFRHnujKfH18lF3n8xzhdY6RQRyrmUx3ElrvUisCzNV3cAo3U6RuzJJHRzVuVRo+5oS/oEL4uFTuxiOpU2iu87e+rgqddaFDbNIq6Cw5WRY3ll5y2+cD1BgBFnj3UGJ4yLGkMd+ZS8J5e5h9hsYqT8SKs6viZEniKHq145FdpDaxuPEQ9UaQSxydeTBpCHHtOINVan6W1OVTHPYwwJbIvSnZMWcuFhcU54cffpg//elPZGdn85e//IVLLrmEG2+8sSPuZmJiYmLSDn7CzHNtpkip4zK1D/f7x7VuinrNdoTnbYdIE3Gs8X+LHi2pbC8qc22fUyjXMUnvzpzweKwt4usmxCzlc05IjUwVPZipj2tdcGEg2MAB3ucUXYlnNVPIPKdju1S4maPvoJYAV0l9uUceHtW4VWg0MF+NbI26UenPLy2DohZYuIXKosAeDhsNDJJTWOyInU8u0hpZ4NtLk1C50taTu+Ni3bwqdB8LmvdzWveSa01jXmIOCe00fv23v5z1zUUYCG5LGMD18b3bHRveGahlVX0BPqHxg/hu3J2SHbN442JyQXFetWoVV111lSnIJiYmJt8AvKjMdW2m0FLH1HAvZvgj6x0Fgpdsh3nZVkAnER/V/OUmxCz7Fk5IjUzTe/FweBxKi/g2EGSm8hmlUjPfNfrwgDE6al3kCnaznUqySGIFk0g9p2M7X9SxUN+JlzC3ykO4QeofJXTb9EpWhPehYzDdMoIrLL2jvpdyw8u8wG4qhI8pli48bM/Bfp4AblYrWeM/hI7BPXGD+aEtVkz3q3Usc0c6ra+O680d8dnt1pc3uo/ynv8MCZKVOSnDGW2PTptDJC3+oruY19ynsEoyM1KH8J342Jr2xeaC4tyzZ0+WL19Oc3MzV155JVdeeSXdu//rO9lMTExM/tPwSCFmuzZzTKnnW2rvKGF+znaIN2yFEecv/7da55gbCTLTvplTUjPf1fvwQHhsq/hW4WWm5XOq8PJDox93Gzmtr3lRWcAODlPPCDJYxHhctEWinxkVrDIiW6FmyqO4TI7e+PSOVsxGrQA7Cgus48hTop24Duv1LAzswUOYG639+KVtYFTELYTgj6ET/DF4gjgUFsWPYaw1unYshOCvwTI2eo8iAw8mDONyR6w+NeghljQe5Ei4ib4t9eUu7dSXm3SVFfWHORBqoIsljoVpI8iyJcSc6wgkIYT4Kgerqqr44IMPePfdd4mPj+fVV1/9Wi9SW+u58KEWMjIS/r/Om/xzmM+7YzGfd8fz7/DM3VKIh12bKFYa+Y7alwf9ea3CvNG+n3esx1q8stucv2rxM9O+mTOShyv1ftwbHtUqvsU0MdvyOY0E+YkxiF8aQ1tr1rUEmMM2SnFzCd15mNGt9WeIuH49bRzGgYWF8jhGyW2iaQjBM1oBb+slpGBnmS2PAXK0E9deZz3zz+5EIPiNfTiXW6OFPSR01voPsSVcRWc5jqXxY+itRItkWBhs8B7hv4PlJMs2FiXmMsQa7dcN0fXlqY7OPPAl9eWiUDNL6/Op1YPkOdJ5OG1ou2nxr5OMjC8X/q/kre3xeNi+fTvbt29H13UmTpz4tV3OxMTExOQf0ygFmOn6lFNKE99X+zHdH4l+DQRP2vfynvUEvYwkVp+zxKJK8jLTtpkqyce1WjZ3aCNbxTdfqmW+sg0/Ye4xcviR0b/1a5XhZjbbqCXAD8nibka0CrohBL83jvBn0WIeokwgS2oT3pDQWRXexzajip6Si+XWPDrL0eYjL4dP8GrwJHZkFjhGk2uJ3vRUawRY5NvHcb2ZIUoKi+JHkXxeDbpOD7LUfYBCrYl+lkQWJ+bS6TzHLyEEfwuU89vmoxgIbk8YwHXt1JeFELzvK+epxmMYwC+TsrgxoU+M4UlHc0FxvuuuuygsLOTb3/4206dPZ8SIER1xLxMTExMTIpacM12bKFOauSo0gHsCo1uFeZ19Fx9ZS8gyUlgVuJTklrWPJVITs2xbaJSC/Ewbws1aW1S8XapguRKJWmfreUwTbVHrEeqZz3Y8hLmFIdxIduv7VKGzxtjPFlFODxJYoYyn8zmuX00ixMKWUanhUhqLbGNJkNq6qYNCY23oEJ9plfS0JzLflkvv8zqyC7QGFvv20SRULrN2437nsJgmrMPhBpa6D9JohJhq78KDCcNifLQDhsYT7iI2BSpJlK3MSR7BqHYWV/gMjccbC9niryFRtjI3bRi5jvYXXBwPuYmXLXSzxqbDLwYXFOfrr7+eKVOmYLGYC6xMTExMOpJayd9qyXl1aCB3BXKRkNAxWOPYySZLKQOMNFb5p5LQYhRyWK5lvu1zfIS5O5zLj/W2DVEfSCU8oezDhsJCfSKjRVsdeCdVLGUnGgYPMYrv0rv1Na8Is8jYySFRxxBSWaqMjxLeUsPN/PAuqoWfS+VuPGTNiRLVWiPAguAeThrNDJFT2ZA5Fb0hHPW9vh8q47eBIxgIfhU3mB+f1/j1P/Xlp71HEcBd8QO5Oi42Ej6j+VjSeJBSzctAaxLzUka066N9UnWztP4wlZqfwbYk5qQNI9MSe04VBs83FPOW+zRj4tJY0fkbMuecm5vLokWLOH36NOvXr+eRRx5h1qxZJCUlXeit/OhHPyIhIfKbUffu3Vm5cuU/f2MTExOT/wBqJF/rEosbgoO5NRhJS6voLHVsY6elgsF6OssDbe5eO+UKlti2YyCYFc7jW3pvIDKn/JpcxAtyAYnYWK5PZqBoixA/pJTH2IcFmcVMII+2zVDVwsc8/QvK8DBR6spseXRUR/VuvYZl4T0E0LnJks1NSnaUYBbqjSwM7qFJhPiupQf32YeRqjioJSLOYWHwVOAI76unSZSszHXmkmuN7qIOCp3HPQVsClWSLNuYn5DDcFv0diuAzwPVrG0+QkBoXOXsyV2J2TGLMoQQvOcrZ2PjcTQMrk/oxS+T+sWMZgGUh/0sO1tAseqhm9XJbamxNqIXiwuK84IFC5g4cSL5+fk4nU46derEjBkzePbZZ//h+0KhEAB//OMfv56bmpiYmPyHUCV7Wtc+/iw4jJuDw5CQ8BFmQdxn5CtnydE7sygwuXVRxd+VU6y17o4IrDqJcUZk/MdAsFE+yF/kE3TCySptCj2IzD4LBK9xjBc4ElnpyEQG0ybahaKBhfpOmgjxYymLu+RhrbVYIQRv6yU8qxWgIDPHOopLlehO6b+Hz7AulB+Jhm1D+LE1ejFFoxFiiW8fBXojfeUEFsePprMSnTau0v0sdu+nWPMw0JLMgsQcMpToXc6aMPid5zhv+8pwSAqzk4czLS569SSA1wizrqGQrYGzJMpWHk4dwbi42HEqIQQfe6t4sv44QaHzXVdX7k7rj7OdRrKLxQW/Unl5OTfccAOvvfYaNpuN+++/n6uuuuqCH3z06FECgQC33HILmqbxwAMPMHJkx6QDTExMTP5dKZfdzHB9Qp0c4BfB4fxXy3apJinI7LgtnJQbmKT1YHZwQmsH9VvKMZ62HsCFlaXqFIYakSarMDprlD1slk7TSySyUp/SuvIxjM4THOAjyuhEHCuZRE/aVjpuNspZY+xDR/BreQRXyW17mjVh8KSWz9/0MlKws9g2lkFyWyRrCMHv1SL+HC7GhZW5jlxGW6LHoI5pTSzy7aNOBLnE2oUHncOj7D4Bdqu1rHIfwiPC/MDRg7tdg2Jq0LV6kGWNhygMN9HT4mJ+8gh6W2NdwY6rbpbV51OlBRhqT2ZO6jAyLI6Yc15D44m6o2zx1eCULcxJH8qlrsyYcxebC4qzoih4PJ7W33ZKS0uR5Quv0XI4HNx6661cd911lJaWcvvtt/Phhx9+ae06JcWJxfLV3Vf+UQu6ydeP+bw7FvN5dzzfhGd+jDoe5lOaCPEA47nZOgISoFp4malv5jRurpUGM8cxCTlBQgjBRm0fz+uH6IyLJ23fpV9CRCT9IszDwc3s1CvJlTvzeNxlJEqRurTHUFng38IerZrhSgaPxU8jTY7UW4UQPO8vYKM/H6diZVXiZCacs1jCbYSY37iNvXoNgx1pPJY6hcxz/K29hsqc+i/YIarJciTzWPpkelqjn+0H3lKWhfYRVgzuTxnJzUnRqXBDCF5oOMrTvkKsFpnFncbww6Q+Mc9rt/cscyv20ihCfD+1F/O65OBUojVGCMGf6k/xeEMBYQS3dx3IXZkD291Ole9tYF7pASpVP7lJ6SzrnUtXe8c0gJ3PBeecP//8c9atW0dVVRWjRo3i4MGDrFixgqlTp/7DD1ZVFcMwcDgiv5lce+21bNiwgS5dYlMNYM45f5Mxn3fHYj7vjueb8MwPW84yL34zAUnj1/4xXKlGGrlOy83MjNtMneTnBnUwt6qRdZAGgvXWvfxNKaaLcLFandq6p7kWP/OVbRRLTeSJrszV83C0xGLV+JjLdk7jYTxdmM3Y1uUWqtBZZxxgkzhDJk6WKuPpI7VF02cMD/PDu6gQPibInZllHRUV7ZYbXhYE9nBGeBmjdGKOIxfXOcstNGHwu+BR3tXLsGsyc+JzYoxFPEaY1Z58dqpnyZAdLEzMJdsa3eNkCMEr3hL+6C1GQeKuxGyucvaIaQ7ztKSxtwXOkiTbmJk6hDHtpLENIXi9uYw/NJYggJ8k9+Lm5L4oF3mc6p+ac54yZQpDhw4lPz8fXddZsmQJ6emx39z5vPnmmxw/fpxFixZRU1OD1+slIyPjgu8zMTEx+U9jp6WCJa7PMRDM9k3k0nBvAI7J9cyJ24JbCnFbaCQ3hAcDEVvNVdadbFXOkCWSWRmaSkqLrWYJTcy1bKWOAFcYWdxr5LRadR6lgfnsoIkQV9OPOxneOsPsFiqL9J0cpp6BpLBEySPlnHWP+/Valob34CXc6pF97izwHu0sK4P78RDmGmtf7rANjnq93giy3Lefw3oj/eOSmRM3gu5KdPr5WLiZZe4DVBsBRlrTmJs4ot0Z51VNhzmkNpChOJifPIJBtmiTE4DDoUZW1RdwVg8y3J7C7LShpCuxaeyzWpBHagvJDzaSrtiZlTGEEXGxZiYdzZeK85NPPtnu3xcVFQFw7733/sMPvvbaa5k9ezY/+clPkCSJFStWmONYJiYmJufxqbWU1fE7UJBZ7J3COK0bAAeUahbGbSWExgPBcXxPi3QKewix0LaNw3Itw40MFquTW7u190rVLFF2EEDjNmM41xttc8rbqGAlu9EwuJcR/JB+rXc4IzzM07+gEh+XSN2YIY9q7cgWQvCufoqntMPISMy05nKZ0qP1vYYQvB4+yYvqURRkHrKP5LvWttcB8rV6lvn20yhUJls7s6rrRPz1wdbXhRC8GzzN096j6Bj8zNmPm5z9YoxAdgfrWN18mGZDZby9EzOSY128dGHwsvsUr7pPAXBzYl9+mtin3TT2p95q1tcfw2doTHBm8GD6IBKVWFcwTRj8rbmSztY4xsW3Pwf9dXPR1NJms/Hoo49erI83MTEx+bfnXdtxnnTuwSmsLPVOZZgeSfFut5xhmWM7APOCk5isRcSuWvIyx/YZZyQPU/QezAzntTaFfSid4nFlLzIyc/XxTBWR9wgEb3KC33EYO0rMqNRBo5Ylxi48hPmplM3P5baIWBU667V8PtJPk4SNRbaxDJXbxMknwqwOHmSHXk265GCRYwzZSlsUK4TgzdApfh+MBHV3OQZxtb0P8bIVPxFx9hkaj3kP81momkTJxuzEEYy2RWdnNWHwguckf/KdwoLMPYmD+GE7aexqLcDK+sMUqs1kKg5mpQ1jqD02qvboYdbXH2OLrwaHpHB/+kC+5+ra7naq0pCP1TVFnAh5mOTK+NeL84UiYxMTExOT/x0CwauOAl505JMsHKzyTiNLj6RSP7Ce5An7HmwoLA5MIVePGIUclxqYa/+MJkJcq2Vzuzay1Vv7RfkIr8qFJGBjsT6RYSJSQtQx+C2HeI8S0nCwjIn0IyJWQgjeFSU8ZUQi4oflUXz7nOUVtSLAYnU3x0QT/aUkFtnG0UlqM+koMzwsCuylXHgZoaQx1z4qatWjT4RZ689nW7iaVMnOvPgchlmiha1Yc7PUfZAK3cdQawpzEkbGjElVawFWNOVTFG6iq+JkXsoI+lsTOZ/N/moebyjCLzSmOjOZnjIIVzve2PsDDaypLaRODzHInsTMjMHtun4ZQvCnxtP8oeEUmhB8O6Ezd2f0izl3sTDzzCYmJiYdiIHgmbj9vG0/SqYRzyrvNLobiQgEf7Ad5hVbAYnCzvLAVAYaETHbKVeyzLYdFZ17wrn8qMX1K4zOo8peNklldCGeFdoUuhNpMvISZgW72EMNfUliGRPJICKuYWHwpHGID0QpSdhZqIxlmNQWrRYY9SxWd9OEymVyD35jHRFlPLJVq2JN8CABNK6zZnGrLbr7+ZTuYbFvHxWGj+FKKnPjc0iV20RXCMEHgTM86S0kjMH1cX34ZfyAGCOQrYEa1jUfwSvCTHN0YXrS4JhZY7+h8WTjUf7ur8IhKcxIHcK3nV1iouCQofN8YzFvu88gI/GLlL7cmNS73aavM6qfNTVFFAXdJCs2HuiUzXjXhXutvk5McTYxMTHpIHQM1jl38bGthJ5GIqs8kQ1SGgbrHLv4u+UUXYSLFf6pdBeR6PB95SQbrPtQkFigTmSSEUlXe1BZpGwnX6plkEhjiT6R5JamsAq8LGAHp/EwhkzmMa7VrKRRBFms7+IIDWSRxGIlj0ypLXJ8Xyvlt1qLcYhlKD9W+rYKnSEEz6tHeSN8EgcKc+2jmGqN3nW8Sa3gMX8+IQyut/flFkf0buWA0FhYs5d3vadIkKwsSMghzx7dsa0KnWfcx3nXfxqbpPBg0lC+Gxebdj4aamZFw2GqtAADbInMTh1Kd2s851Mc8rCy9ghlYR/drU5mZQwh2x4bfRtC8E5TOc/VlxAWBlNdnfh1pwHt1qEvNl9JnP1+P6dPnyY7O5tAIIDT+a+Z+zIxMTH5dyWIxvL4bey0VjBAT2WF91KShAMfYZbEbWW/Uk22kcbSwCWkCAcCwQuWw7xmKSQRO0tDkxksItFbFV7mWbZxGjeTRHdm6eOwt9Se91PDMiI15Gvoxx3ndGQfF40s1HdRR4CpUncelHNwSG1jVE9ph/mbXkYiVuZbxzBSaZuwaRYhlgf3c0Cvo5sUz0LHaPoobQKnCp1nAkW8q5YRh8ICZy6TbdGjsyWah+Xug1RKAbItScxPzInxvS4Ne1nVlE+x5qGXxcW8dkxFdGHwhqeUl5pLMBDcmNCbm5OyYqw6DSH4U/Np/tBYgobBlQnduSO1Hw451lOjUg2w9mwRhwPNJCpWZmUMYkpCp5hzHcUFxfmLL75gwYIF6LrOG2+8wRVXXMGjjz7KpEmTOuJ+JiYmJv/2NElB5ru2cFSpJ0frzCLvFJxYqZP8zIv7jGK5kTytG3OCE4nDEklXW3ezSSmjq3CxQr2EbiKSrs6XalmsbMeNytXGAO40RrTWnt+lmKc4hIzMg4zi8nOWV3xqnGGtsR8Ng1vlIdwg9W+NROtFkCXqbgpFI1lSIousY6NWPR7Xm1gS3EuNCJCnZDLTkRM1v1yp+1jmP8AJvZnesouF8aOixqSEELzX0o0dxuBn6QP4KX2ixFQIwbv+MzzjOUZYGPzA2Z27EgfGbJyq1Pw8Ul9AodpMmmLn4dQh7W6SKg/7WVNbSGGomRTFxkPpgxnrjD1nCMH7zZX8rq6YoNCZGJ/O9E7ZpFhsMWc7kguK87p163j11Ve5/fbbycjI4JVXXuGBBx4wxdnExMTkK1Ape5jt+pRK2cu31N486M/DikKp3MycuM3USn6uCPfj3tBoFGS8qCyybeOQfJZBRhpL1Mmt6eoPpBLWK/sAmK6P4goRGa8Ko/NbDvE3TpGMnUWMZ0iLR7YhBM8bR3hDnMCJhQXyOPLktm1UhUYDi9XdNBDiUrkbD1hHtkbTQgje08rYGDqCjsHNtmz+y9o/asRpi1rJOn8+AXS+a+vOPXFDooxJ3IbKWs9hvlDPkihZmZ8wkqs69YsyfWnUQ6xtPsLuUG1kdWPycCY6oi0zhRD8zVfBM00Rv+upzkzuSxkUM0plCMFf3OU811iMKnQmx3dielo2SUqs2FaoftadPUZ+oAmXbGFWp0FMS8hst2tbNQwAbF/BIfPr4ILibBhGlHlIv34d161mYmJi8u/MUaWOea4tNEshbgwO4ZZgxN3rkFLDwrjIWsdb1RHcoA5GQqJC8jDP9jnlkocJRjdmq+NxYEHH4Fk5n7fl4yRgY6E+gREiknJtIsRSdpJPXaSGzAQyW/yzvSLMSmMPu0UN3XCxWBlHrxbHLyEEf9VP8YxWgIHgDssQrlWyWoXJLzQeCx1i59C/5wAAIABJREFUi1ZJIjZmOXIYc44/dkjobAwU8jf1NA4UZjpHcJktevFFvtrASs8h6owgw62pzEoYEdONvStYy9rmApoMlVxbGjOSY81CGvQQ6xoK2RWswyVbmJ0yjGnxnTmfqnCAtXWF5AebSJStzEgfxNR2fLENIXir6Qwv1p9CFQZ58WlM75RNusXe7tkPmqr4fc0pcl0pLOg++IL/7l8HFxTnzp07s3nzZiRJwu1288orr9C1a9cLvc3ExMTkP5qd1nKWxW8jjM5959hxbraUsdrxBQAzg+O5TIt4Rh+Sz7LYtg0PKtdpA7lNi6SrvaisUHayR6qmJ4ks1SbRlUjKuIRmFrKDavxMphszGN1qxVkq3CzSd1GBl9FSJ+bIY1p3MPuFxmPhg2wxKkjCxhzraHLPqS+X6G6WBPdSIXwMkVOZ68glQ26rDZ/WvSz37afE8NBXTmBufC49z0lj68LgZX8xr/qLAfhl/ABujOsbFXGHhM6zLU1fFmTuSszmx85eMcYjW/01PN5YhNsIk2NPZUbqkJiFFYYQvO+p4HcNJwkKnQnODH6TPpCUdqLlUyEvj549yrGgh0TFykMZA5nq6vSlM86PV53giL8Zp2zh0sSOc7m8oDgvWbKE5cuXU1VVxWWXXUZeXh5LlizpiLuZmJiY/Fvyvu0EG5y7saCwyHcJ48PdEQjesBbxnP0gTqwsDExunWH+QClmvXUvEvBgeCyX65ENUBV4mG/ZzhncjBGdmaPntbqB7aCSVewhgMZNDOJnDGpt/NpslPOosZ8QOtdL/blVHtIqeqWGmyXhiP/1YCmFebYxZEhtSy8+0s6wPnQ4MuJkzeKXtoFRI06fqOU84S8giM4Vtp7cFTc4asyqRg+wynOIgnAjmXIcsxNHMMQabYd5PNjEjLqdlGleellczE4eRtZ5s8teI8xvG4/xib8KqyRzT3I2V7l6xIh3dTjAo3VFHAw2kiBbuT99IJfGx6amw8LgtYYyXmssQxOCaQmZ/Cq9H8nt1JZVw+CVujL+VF+OJgwmJ2Zwd2YW6dbYyPpicUFxTktLY926dR1xFxMTE5N/awSCFx35vOqIzCov9V7CYD2DMDqP2/fwsbWEdOFkeeAS+hopkZlnywHethwnERsL1UkMNyKp44PSWZYoO/Cgco0xgDtaGr8MBC9TxB8pwo7CAvKYTMTyUxMGvzMKeFsUE4eF+fJYpsjdWu/3qV7OY+GDBNG5WunL7ZYhrcIbEBobQof5u1ZOAlbmO0Yx3tKWOg4IjScDR/hYLceJhbnOHKbaorOoW0PVrPMU4BVhptg7c79raJQRiCEEb/vKeKmuhIAW5ipnT+5IHBAl7gCHgg2sbjjCWT1If1sis1KH0vO8ESkhBH/zVPJsw0kCQiPPmc5v0gaS1k5q+ljQzaM1Rzml+ki32LkvY8CXzi0f8DXyRNUJKtQAGVY793XuT15Cx7iCncsFxfk73/kOuq63/lmSJBwOB3379mXmzJl069btH7zbxMTE5D8DDYN1zp383XaKLoaLFd5L6W4k0iwFWezYxmHlLAOMNBYHJpMunPgIs8K2g91yFT1FIkvVyXRt6ch+XyrmSWU/EhIP6KP5nohE0h5UVrGb3dTQGSeLGE9Wi+NXvQiyTN9NAfX0JIGFyjh6SpHPU4XO01oB7+mlxKEw3zqGKUqbsJYZHpYG91FmeBggJzPfMYrOctvIbInuZrnvAKcNL/2VJOY5c+h6zppIv6Gx0VfEh8FybMjc7xrK9xzdo6LXai3AmuYC8tUGOjmczHENI88RnSb2GxrPNZ/kXW/EKORniX35r8Q+MeYk1eEA6+qOciDYQLxs4eG0wVzm6hwTLQcNnT82lPJm4xkMBN9P7Mrt6Vm4lFjpa9bCPFNTzN+ba5CRuDq1Oz/P6BWzgrKj+Epbqbp37861114LwLvvvsvhw4eZNm0ac+fO5cUXX7zYdzQxMTH5RuOVVJbGb2W/pZoBeirLvFNJEXGUyc3Mj/uMKsnLZK0HDwcjDV7Vkpd5ts8pk9yMNjozV52ACxthdDbKh3hPPkkidhbqExjeYsVZQhOL2EkVPkaTyWzGkEgkSswXdSzVd9NEiEukbjwg5+Js6ZiuEX6Wqns4JproLSWw0DqW7nJbffiTcDlPhPIJovMjax/usA1uHXESQvCOWsrvA5ERqKvtfbjVkY3tnEj3SLiRRzz5VOl+siwJzEoYQW9L2ypEIQQfBirY6D5GQGiMt3died+x6I3hqGd4KNjA2oZCqvUAPS3xPJQ6hEH22FWRf3GX83xjMSGhMyYujfvTB8bUoAH2+hpYX3uMqnCQzhYHD2QOJMcZu21KCMGm5rNsrCnGrYfJcrh4oMsABsT9a/d7X1Cc9+3bx7x581r//NOf/pSrr76alStX8tRTT13Uy5mYmJh806mUPcxzbeGM7CYv3I05vonEYWWvUsWyuG34CPNTdQg/VyNmIAVyLQtt23AT4sfaAO7URqIgU0+ApcoXHJHq6COSWKJPojOR6PRTTvMo+1Ax+AnZ/IIhkdlmIXhLFPM7owCAu+RhXC21dVzv1mtYFd6HhzDfkrsz3TqidczJLzTWhw6zSSuPpMAdo5hiaYumG4wga/357NFqSZSsLHDmkmdt63zWhMEf/Sd53V+CQHBDXF9+Ht8/ana5Xg/xWPMRdoVqcUoWZiQN5dtxXUm1OKglIs7nR8s3JPTm5qS+Ub8AAJSqXtbVHaUo1ExiS215Wju15UZN5em6k3zqiUTA1yb34Oa0PsS1YzxSGvKxoeok+f4m7LLCnZlZ/Di120Xf4/xVuKA4y7LM1q1bmTx5MgBbt27FZrNRV1eHpmkX/YImJiYm31QOW86yKP4z3JLK1aGB3BnIRUbir9bjPGXfF1mxeE5H9kdKCY9b9yIQTA+P5go9Mpp6RKpjifIFDQSYKnrwgD6GOCxoGDzLYd7hJHFYWMw4JhARUL/QeNTYz+eighTszD/HH1sTBi9oRfxJP4kFiemWEfxA6dUqZMf0JpYH91El/GTLycx15NLlHNORneEa1vrzaRYqoy3pzHCOiPLGPqN5WeXJ57jWTKYcx8MJwxluS416NlsC1axvLsQjwuTY0ngweUiMG9hXiZbDwuCNpjJeaS5FEwZT4zO5O21ATCe2EIKP3NU8W3cSj6ExwJ7A/Z2y6eeIjYD9usYrdad5q6EcXQjyEtK4J7MfnW2xETjATncDz1eXMiw+iV93y/qSn4avlwuK88qVK5k1axYPPfQQAD179mTVqlW88cYb3HLLLRf9giYmJibfRD62lfCYcycCmO4fyxVqf3QMNtj38a71OEnCweLAZIYYGWgYbLQe4F3lBAnYmK9OJMfIRCB4XyrhKeUABoI7jRFcYwxAQqKBIMvYyWHq6UUCCxlPj5alFqXCzVJ9N6fxMJQ05iljSZMiwlJt+FgR3keRaKSL5GSedQwD5Ehd2hCCP4eLeUE9GrG9tPbj57bs1ppuSOg822LBaUHiV3GD+ZGtd2uH9P84fT3jPYqKwWX2btzjit7+5DHCrG8uZEuwGpukcG/iIK50RndZ+3WNDY1HW6PlGxN6c1M70fKxkJtH64o4pXpJU+xMT89mvDN2nOmM6ufxFjOROFnh7oz+/DCpW0xntxCCbZ46NtYUUxsOkWl1cE/nfoz/koav8lCAjZUl7PY0IgOXp8bOTF8sJCGE+CoHm5ubURQFl8t14cP/C851i7kQGRkJ/1/nTf45zOfdsZjPu+P5/3nmBoIXHAd53VGIS1iZ75tMrtYFLyrL47azV6mit5HE0sAldBYuGgmy1Ladw3ItvUUSi9VJdBUJqOisl/fzkXyKROzM0/PIEZH/+R+hnqXspJ4gk+nGQ4zCiTUSHYrTbDAOoaJztZTF7fLQVnHdqlfyaPgAPjSmyd24zzqC+BabzQYjyCOhg+zXa0mR7Myy55BriZ5tXuE7QJnhpZfsYk58Dn3P8c5uMEKs9Rxmj1pLgmTlNwlDmWKPNgLZHazj0eYCGowQg6zJPJw8lO6W6C7rQ8EG1vuOc9rvoaclnhmpQxh4XrQcNHReairhreZII9cPErpxW2o/XOdtpFINg9cb28ajxsenc29GfzpZYyPgSjXAk9Un2eNtwCLJXJfWnZ+m92zXZ9uv67x69jRv1VWiCcFIVxL3dM2it+Pr3SuRkfHlde0LRs4HDx7kmWeewe/3I4TAMAwqKyv59NNPv9ZLmpiYmHzTCRBmdfwXbLOeoavhYpn3UnoYiZyR3CyM+5wzspuxelfmBCYSj5WjUj2LbduokwJcovfggfBYnFg5i5/Fyg6OSw30Fyks1CeQSTwCwV8p5hkiW6FuZxjX0R8JKVIjNg6ySZzBhZXZ8mgmyZEU97nd2HYUHrSM5LtKz7bas3aW1aEDNAuVsUonZjhGkixFmskMIXgndIrfB4+iIbjK1os74gZFr4gMVfO45whuoTLKms5DCcOiXLy8Rpin3cf4KFCBBZlbEvpzfXzvqG1UXiPM75tO8DdfBTaL8qXR8t5APevrjlGlBehiieOB9EGMjItt5Mr3N/F47THOqH7SLXbuyejPJFdsVK0aBq/Xn+b1ujOEhUFOfAq/7tyPHvZYoRVCsKmplt9VldKgqWTa7NzZpQ+TEtPaNSm5mFxQnOfMmcOtt97KO++8w0033cTHH3/M4MEdY19mYmJi8k2hVvKzwLWFk0ojw7VOLPRNIVHY2alUsDJuB37CXB0eyJ2hHGQkPlRKWG/di47gNm0E12sDkZDIl2pZouygmRDfFr2Zro/CjoKXMI+yl21URly7GEsukUi6RDSzVN9NOV6ySWGeMobOUiQiPW14WB7eS4lw00dKYK51DL3kthGq59SjvB0uwYLMr2xD+LG1T6vQ1BoBHvXns0+rI1my8ZBzBOOsbRadbkPlSW8hm0NVWJG5xzWIqxzRLl47g2d5vLmIeiNIliWRGclDYgxFtvvPsr7pKA16iN5WF8uzxtDJFy0/DVqIpxtOsNkXaeS6LqknNyf3jYlsG7QQz9YVs8lTgwRcldSNW9L7Ei/HytkuTz1P1RRTqQZItdi4KzOLqYkZ7Qrtcb+H31aWUOj3YJUkbs7syfUZ3bC3E1l3BBcUZ5vNxjXXXENFRQWJiYmsXr2aK6+8siPuZmJiYvKN4ITSwHzXFuqlAN9V+zLdPxYFmVdsBfzBdhgLcmvjVxidJ60HeE85SQI25qjjGW10QSB4Uz7G7+R8JOBeI4erjH5ISJygkaXsogofw0lnNmNJJy5itCFKecrIJ4zBtVI/bpGHYJVkhBB8rJ9hg5ZPCJ0rlN7cZRnaGvGWGh5WBQ9QbDTTXXIxz5FLlhJJHwsh+DRcyQZ/AT40xloyeMg5ghS5zcBjR6iGx7wRz+tBlmRmJAyjh6WtrOk2VJ5yH2VToAoLMr9siZYt53VrP9l4lG2Bs5EzSVlcl9Cbrs4kan2RMoIhBB94KnmusRivESbbnsj9aQPJskenfHUheK+5ghfqS/AbOv3tCUzvNIBsR+xe5go1wMbqYnZ561tnlm/O6EV8OzPLjWGVF2vK+O+GGgQwOSmNO7v0IfNLmsM6iguKs91up6mpiT59+nDo0CHGjx8fZUpiYmJi8n+ZzdZS1sbvJIzO7YEcrgsNIoDGcscOtlvO0EnEsygwmf5GKo0EWWLbRoEcGYda1FJf9qKyRtnDDqmCZBws0MczTGS0rnncSD5ay5jUzxmMgoxPhHncOMgW0eLYJY9lvBzZj+wTYTaE89lklBOPhRnW0VyiRAyhDCH4S/gUv1eLCGNwuaUnd9vbNkU1GSGeCBSwLVxNHAq/iRvG9209WqNJjxHmt95CNoUqsSJzW3w218X1iYqWPw9Us8FdRJOhkm1N4qGkoVE7l4UQfOir5Nnm43gNjaH2ZO5PGRzj8nVK9fJ43VEKQ83ESRbuTcvmyoTYRq7CQDPra49THPLiki3clzGAHyR1jTnn1zVeqz/Dmy22m8OdydzTOYu+jtheKdUweLuuklfPniFg6PRyOLmna19yXMnt/hyohoEEWL8pW6l+8YtfcP/997Nhwwauu+463nvvPYYOHdoRdzMxMTH5l2EgeC7uAH+yFxEnLMzzRzyyyyU3i+K2UiY3M1zvxPzgJJKFgyKpniXn1JcfDI8jDgvHaWCp5Quq8TFcZDBXH08qDnyEeZz9bKGcRGzMZAxjiTRYnRRNLNV3U4mPwaQyRxlDphSpkRYY9TwS3k+18DNQSmGudVTr7uVaI8Ca0EEO6HUkYmOuYzgTLV1av6cvwjWs8+fTJFSGKSnMcI6ki9JWe90ZOstj3khD1wBLEjMShkUZijTqITa4i9garMEqydyeMIBr4ntF1ZYrwn4eayzkUKiROEnhvpRB/CA+WnCDhsZzDcX8ubkMHcHk+E7cnTogZitUs67y+7oSPnRXAfCdxM7clpYVs2tZCMFmdy3P1pRQr4XIsNq5MzOLKQnpMSlsIQSfN9fz++pTVKshEhULt3btyw/SOsc4kQEEdJ13ait5vbqC0YnJLOg78Cv89PzzfKk4V1ZW0rVrV773ve9x+eWXI0kSb731FqWlpQwc2DGXMzExMflX4JFCLIvfxn5LNd2MBBZ7L6GXkcQupZKVcdvxtdSX7wiNjMw1K8d52noAA1rrywDvScU8pRyIRMXGIH5uDEFBppgmlhLZGDWENOYyjoyWNPZfRQnPGgWRxRNSf34pD8YiyRHTD+0Yr+vHAfiJ0p+bLW1LKTaHK1gfOoyXMHlKJg/Y29LUPhFmY6CQj9RyLEjc4RjENfa2aNhrhNnoK+LjYAUWJG6JH8D1cX1aRVcIweZgNb91R7ZDDbWl8GDSkKhObE0YvOk5zUvuYsLCIM+RwX0pse5de/z1PHO2mDKfh04WB79OyybPGe1zbQjBf7ureK6uGI+h0ccWz687DWBYXGxUWxz08mT1SQr8zVglmZ9l9OKGtB7tdmEf83t4uuoUBT43FknimvSu/CyzZ7t2nroQfFR/lj9UnaYhrJJosTIt9RuwleqGG27A6XQyadIkJkyYQF5eHvHx8WYzmImJyf9pSuRGFrk+p0r2Mi7clVm+SOf1q7YjvGjLj6ov+wnzmHUPW5TTJGFnjjqeXKMzfsI8ruxjs3Q6EhXr4xgrInXn9ynhKQ4RxuAGBvALhmBBplEEWWPsZ4+oiSzBkEcxTo5E0uWGl1XhfRwTTXSWnDxszWWYHJnN9QiVDaECNmsVOFD4jX0437e0dWofDNexxn+IsyJIPyWRmc6R9FbaouHdai2PeQqoM4L0syQyI2E4fc+Jlmu0ABvcRewK1WKXFO5JHMRV580tHwk18URjEafCXpJlG/emDmRKXPQaxrNakI31J9jmP4vNauG6pJ7clNw3xrnraNDNk7XHORb0ECcr3JXejx8md4uJat1amBdqS/mgsQoDwcSEdO7KzGrXSKQ2HOK5qlI2NdUCMCExldu79KG7PS7mrBCCnc2NPFdZRlnQj02W+Wnn7lyf2a3dmvXF4ku/0tatWzl9+jR79+7lk08+Ye3ataSmpjJhwgQmTpzIyJEjO+ySJiYmJh3BZ9Yy1sR/QQidnwaH8vPgcAJoLHFsY5vlDBnCyaLAFAYYqZRITSyxbadC8jDESGeuOoEMnJyimSWWHZTjYbBIY64+nk448aLyBAfYQqSGvIA88oiknHca1aw19tNMiNFSJ2bIo0iVHAgh+EAvY6NWQAidy+Qe3GMdhqtldnm/Vsua0EHqRJBBcgozHTl0a0lxB4TGC4FjvKOWIgM/s/fnvxz9WkWu2VDZ6C1iU6gSBYmfO/tzo7Nv6+uGELzjL+NFT2RHco4tjfuTBtPF0pYG97SMR33gqwDg+/HduC25PwnnmJKEhcFbzWd4uekUIaEz2J7Eov65pPiixbZBC/F8/Sk+aklhT3V14o6MfmScl+oOGwZ/bazklboyvLpGT7uTuzP7McoVO24V0HX+XFfBG7XlqIZBliOeu7r2YeSX1JWLfB5+X1FGvrcZWZL4XlomN3fpQbqt41ZF/g9f2YTE7XazadMmnn/+eU6dOkVBQcHXehHThOSbi/m8OxbzeXc8aRkuVnu28rqjkDhhYYZ/PJPDPSmRG1ni2EaF7GG43ol5wUmkCAcfK6d4wroXFZ3rtIHcog3HgszHUilPKPtQ0bnGGMBtRuTvj1DPSnZTgz9SQ2YcmTgjjlxGAe+KyKjTbfIQfixlIUsSTSLEuvBBvjCqcWFlunUEU1uavoJC43n1KO+ET6EgcbMtmxusWa1p6IPhOtYF8qkyAnSX45npHMlAS0SQhBBsDlXxlLeIZqEywJLEAwlDybK0dT2fDLtZ13yEE2E3ibKVXyUO5FuOLq2RsBCCT/xVPNN0gmZDpbfVxfSUQQy1R4ve/kADG+qPUR72k6TYuD0li2+7upDZKbH1ZzwsDP7SVM4fG0oJGDp9bS7uyejPcGf0Zwkh2OGp59mzJVSqAVyKhZ+l9+KHqV1jompdCD5sqOGlmtM0aCopFiu3dO7Nd1I6xTSRAVQEAzxfdZrPG+sAyEtK5dauvegd9/WajpzP/8qERNM09u3bx9atW9m2bRvBYJAJEyYwffp08vLyLspFTUxMTDoajxRiKdv43FFGV8PFYu8l9DaS+chSwhOOPYTRuV4dxC3qCDQMHrXu5kOlhHiszFXHM8HoTgCNx+V9fCSfIh4rs/VxTBLd0TH4I4W8TBEANzGI/2IgCjIlopkV+h7K8NCLBGYro8mSIoK0W69hbfgAjYQYIafzsDWXTlIkBXtEb2BN8CAVwkd3ycUsRw7ZSuR9fqHxu0AR76unkYHr7X252dG2L/msHmCDt5Cd6llsyNwRP5Cr49oaugKG9v/Ye+/wuOoz7f9zzplepNFImlG1ZEmW3I0NBtOdQCBgqjHGgA2mmZpCEpZkd1+y+6b8NhveTYfQqwEbbKoBU0wAAwZjG/cqWX1GmtHMSNPnlO/vjxGyhZyyGyDJXvP5i+vykWQdz3XdPM9zP/fDY4lWViU7MBCcbq/ihqIWiuVDBqxONcmvorvZlo1ilRSuLZ7ARe5xowQypGW4J3KAt4d3ls8rqmGppwG3cqiiBvgoOcDdoQN0qyncwy7ss4urxhyeaM0kuLuvla3JGDIS53uruaKsjiLT6O8nhODDeJT7g+10ZFJYZZnLfbUsLK/BoYydQQ+oOZYHunh5oA9dCFocbpZV1zHdXTzm2S+bPyrOs2fPZtasWZx55pn89re/paam5sv8exUoUKDAF06bEuXfne/QT4rZaiU/SJ2IRSjcad3AWnNegP9P+kSO12voluL82PIerVKMRlHCD3MnUilcHCDKj00b6CFOkyjh/+jHU4WLPlL8B/n7yj7sfJ9jmUYZhhCsFge439iJisF5UgPL5Px+ckpo3K/t5EW9HRMS15kms0BpQpYkskLnoeFAEYD55gausrRgG16R2qiG+GVqG/0iQ53s4jbHDFpMhzK112S6uC+5h7TQmWH28h33NKoOc2p/lAnzm6H8EYpKxcG3iyczy3ooczordJ4YOsjKoXY0BHNs5dxS0oLfdGhuqwmD1UNdPBY9SEboTLIW843SZiZYR+8id2WS/KR3GxuS+T3k84qrWVo6fox4R7QcD/UfZG2sD4HgWJeXZf4G6qyjV7Igb/a6N3CQbckhZOBsr58l/nGUmce2pOOayoq+Hp4NBcgZBtVWO0urxnGq58hJYGld5/VwiBqbnVnFX45w/1FxXrRoER988AGrVq0iGAxy4oknMnPmTOQvacerQIECBb5I1lpa+ZXjI1QMrmMWC5ITCUgJfuRYT6scpcnwckf6JCqFi3flLu60fEgKjXl6IzepszAjs0rex/1yfkf5IqOZq41pWFB4m25+wSaSaJxCNd9mFm4sRESGnxub+Fj0U4SFO+RZzBneXd5mhLlT3UJApKiT3PzAfDSNcl4IDq+WqyUn37XNYJoybAgzctyT2c3aXDcKEoutE7jU1jgSi9mlJfhFYgfb1ShOycR3XFP5uq1mRISiepbfD+1lXSaAgsQiVwOLXQ2j4js/Sof5bWwPAS1NuWLjlpIWTrD7Dn+dbE5HuGtgHx1qkiLZzM2lzZzhqhx98MLQeDLSwfPtvaRVjel2DzeXT6DBOnoPOWvorIr08FS4M7+DbHVyg7+BY1yjL18BBLIZHuxr5w+x4ZZ0kZdrKuqPmIP96VrUyr5ekrpGmdnK4poaziz1HXGNKqPrvBTqZ0Wgl5iqclKJ90sT5z87c+7v72f9+vWsX7+e7du309zczEknncSll176Z7/5wMAA8+fP58EHH6Sx8U+f2SrMnP9+KbzvL5fC+/5iyaLxG8dG1lracAozt6dO4DzPJFZHd3GnbQMpVOapTdyUPRqB4B7zJ7yoHMCKwq3qbE7T64mS4efKR2yUgniwcZs+m2NFJSlU7mIra+nAhsLNHMWZ1CEh8bbRw6+NTxgiN8r0lRU6D2q7eFZvQwIWKhNYYmrBIilkhc7DuT2sGq6WL/xMtfyB2scvU9uJiCyNShG3OWbQOHysQhUGz6QP8ljyACoGJ1r83OKaPJKJbQjBmlQ3D8b3kxAqE83F3Fo8hQbzoTloQEtxV3QfGzKhfNKWexxLihpwHBaV2aumuCdygPdTISQk5rmruLqkcVQV/Olq1MMDB4npOaodTpYW1XOqa3SUpiEE6wb7eSjUTr+aoUgxs9RXz9meyjGt7iFNZXl/Fy8MBNCEoNnuYlnleGa4xoqnahi8PNDH44EuYppKkcnMIn8155VXHDGeM2sYrOnv46lAL1FVxa7IXOSv5KKKSlymz8+x/VcdvvD5fJxzzjnU1dWxefNmnn/+ebZu3fpnxVlVVe644w5str9tBFqBAgUKfEq3PMSPne/SqsRo0ku4I3ky5YaTX+gbeMS2FSumkTWpdmnH0zKlAAAgAElEQVSQn1jep10aZLwo5p9zJ1AvivlYCvIz5SNiZDhaVPBP+rF4sbGPKD/lI3pI0ISHf+FYanDnV52MrbwlujEjc5M8nfOlBmRJYpcR4T/VzSMV8T+ZZzFZzleHh1fLVZKT7x1WLceMLHend7FO7cWExFW2ZhZaG0eqv+1qhF/Fd9Kh51ebvumawsmHXZDamxvk10O72acO4pRMY846ZoXOiqF2noq3owqD6dYSbva00GA5JCYpQ+PJWAfPDHWiCYNpNg83eZtp+kzs5uZUhN+HDnAwl8QqyVzpHc+NEyYTj6RGPbcpEeW+/jZaMwnMkszC0louLRu7g5zSdVaHe3g61EPK0KmwWLm6op5Ti8vGmL0MIVgXDfFIbxfBXAa7rLC4opYF/qojrkXlDINXQv08GehhIJcX5Uurqri4ogr35yjKfwl/9Ke9+eabbN68mU2bNtHd3c2MGTOYM2cOv/jFL5gwYcKf/cY/+9nPWLRoEffee+/n+hcuUKBAgf8J75o7udPxASlJY16uiZtSxxCTMnzX/gb7RJQao4gfZk6mzijiJeUAd5k352fC+gSuV49CAu6Tt7JS3osJmWXDt5cFguXs5jF2oyNYSDNLmYwZhY+MPv7L2MwAGSZSwj8pR1MruckJncfUvazU9yOA+UoDV5kmYZNMZIXOI7m9rFLbEIhRs2UhBGtz3dyb2U1cqLQoxXzPMWNkb3nIyHFfci+vZroBmGer5Rpny8hqU9xQeSi+n5dS3QgEp9mrWOZuxqvk57JCCN5Ph/h9bB9BPU2pYuV6TzNz7f6RCtcQgnXJIPdFWonoWcoVG9d5m5jrHL3X3JlLcl+4lQ3JASTgzKJKlpaOp8xkxaYofNobas0kuK+vjU3JKBISpxX7uaq8fky2dc4wWBMJsry/i0FNpdhk5saKcZzjrcTymXGrIQTvxAZ4LNBFZyaFSZK50FfFpf5qSsyj08UgX1m/Gg7xRG8P4VwOqyxzSWUVF1dUUmw2j3n+y+CPivPy5cuZM2cO//zP/8zUqVP/W7Pm1atX4/V6Ofnkk/9icS4pcWAy/eXXP/5UO6DA50/hfX+5FN7354eGwa/5kCfYjg0TP+U0zjZP4C17Oz8y3mWILGdIDfyr42Q0h8GP1fWsM9opwsoPzSdzqlJHpzHIv2beYZcxwHjJw09tpzJJKaNDH+SO1Hvs1MP4JSf/5jiRY82VpAyVXyY3szpzAJMs8U3nLK60T0aRZPaoEX4Y+4BWaZBaaxE/LJ7DLGt+fvtxpo+fRD+mSySosxVxh/dYZlrzqVSdapyfhjfzsdqP3WTi9pJZXFI0AVmS8vvQ8U5+EdpGTM8xyenlB76ZTLfnK20hBGsGO/lV306iepYmZzHfr5jB0c5DiVed2QR39u7g/Xg/Jlnial8L1/pacBxWYe5MRrmzeyfbk1EsisxNVZO4wt+I7bA296CW456efTzT34Eh4NiScr4zbjITnaPbzXqRibs79/NyqAch4IQyH9+qm0iLa7R5zBCCl/t6uaejlUAmjUMxcXN9M5dX1+H4TDUrhOAPoRD3HGzlQCKBLElcNK6Wa+sbqLSPDRzJ6QYv9gZ46GA7wXQGq6JwVVM9S+rr8FrHiviXyV+85/zf4fLLL0eSJCRJYvfu3dTX13P33XdTXv7Ho88KM+e/Xwrv+8ul8L4/P0JSih8732WXKUytUcQdiZOpNFzcY93Ci+b9WFC4KXs0VxYfxVuRNv4/8wZCUorpRjnfzx1PGXZelg7ye+UTMmh8TdRziz4TGyZepJV72U4Og9MYx83MwI2F7SLMf+qbCJJiPEXcrhxNo+QhJ3Se0PbxlL4fHcG5Sj3XmqbgkEzERY57s7t5VetERuJC83iWDlfLqjBYmW1leSY/O55j8nGLYyp+OS82nVqCXyV2sk2NYJUUrnA0Md9+6DrUQTXOb4Z2sz2XX31a4mpkvrMO82HrU08MHeSZeAcaglk2Lzd7Jo46UjGgZXkg2srriXxAyKlOP9eVNOI3HxK8nGHw4mAPj0faSRgaVWY7y8oaOcE5Ot86oWu8mOnjsc42VGHQYHNxrW88xzhLRj0nhOD9oQgP9eWTusySxHmllVzqq6X4SCtUQ1EeCXRxIJUX5a+WlLOksoaqI6SAZYfb1ysCvYRzOcyyxDnlfhZVVeE9QmUNEMhksCsKns+xkv6rZs7/E5YvXz7y30uWLOHf/u3f/qQwFyhQoMDnzUZTL//hfJ8hKctctY5bk8fRL6e4xbGWdnmQ8YaHf86cyDijiPv1T7jbsgmAK7WpXKZNYZAsdyjvsUHqHdld/qqoI0Saf2cDm+nHjZnbmc0p1JATOvcY21klDiAhsUhqZok8EYuksNOI8F/qFjpFgnJsfM88i1lKef4Ig9bLb7I7iIksjXIRt1pnjOwt79Ai/DK1nQ4jgVeycot9CieZK5AkKS/2qVZWpA6iYTDH4uMW12T8Sl6MkobG44lWVg/vLJ9o83NjUcvInxtCsC4V5P7B/QzoWXyKjRs9LZxoP2TSShs6Tw92sHKwk6zQabS4uck7gen2Q2lchhD8IdHPQ+E2gloGl2zihrImzvNUj/wPAOQd2M9Felkx0EVaMvAoZq7y1XN6sX/MrHhLIsaDwQ72pOLIwNe9fpb4xuH7TFKXEIJN8RiPBLrYk4wjIfGVknIWV9Yw7ghu7Yyus2ZYlKOqilWWWVBRycWVlX9UlHcMxVnRE2BDJMaxJcX8ZHLLf+dj+D/my51wFyhQoMAXjIrOQ/atPG3djQmJb6Rmc06uiZfNbdxl3YSKzrnqBK7PziQmZbnNso5d2gBlws4P1OOZapSzXurmF8omhshylPBxm34s5dh5k05+w5b8DWT8fIejKcXOLhHh/+mb6SRONS5uU2YxRSrN7y2r23lOb0MA5ynjucY0GYdkImSk+XV2Oxv0PszIXGOZyAJz3tSVMFQeyOzhpVwnAOdaxnG1feJIbOdHuRC/S+yiV09RJtu4xTWZEyz5ma8hBK+ne7k/vo+YkaNScXBz0USOsx0qkHZmY9wd28ve3BBmSebyovEsco8fORZhCMFriQAPR9sY0LN4FAs3eiZwlnv0mcbNqQj3h9vYn41jkiTme2q43FtP0WFObU0YvBoL8niokwEti0sxcUtdM6ebS8c4pbcnB3k42Mm25CCQv6281F83RmiFEHySGOTRQBc7EkMAnOQp5YrKWsbbx+5Ap3SdF/v7eCYYIDbsvl5UWcVFFZVHrISFEGyMDfJUd4DtQ/ku1mS3i8W11X/Zh/Bz4AsX58cee+yL/hEFChQoAOTd2D91vsd+JUK14eZfkidRoTv5ke091pu6cAsL/5I9gRO0Gt5Q2vmteRMpNM6QG7ghOwMZmZ/LH/Ga3I4ZhRuNo7jAmECcHD/iQ95l+LgEszibejJC525jG8+KVgRwvtTANXL+dvImvZ9falsJihQ1kovvmI9imlyKIQQvqu3cl91NGo3pSim3WqdTI7vy0Zq5Xn6f3kVEZKmTXXzbMY2ppryDO6inuCuxmw9y/fnVJns9VzomjKw27ckN8tuh3exVB7FKCktdTSxw1R9KCNMyPDC4n3WpIABzHX6uLZ4wKkhkSzrCPZEDtObiWCSFyzz1XFJcN2p9qi2b4P5wKxtTEQC+6vZzVel4Kg5rcxtC8PZQiIdD7fTm0lgkmUVl41hYWkNDhXfU6GZPKs7DwQ42JWIAzHaXcKV/HC2O0W1fIQSb44M8HjwkynOKvVxZWUuTY+zN5oSm8UJ/H6uCAYY0DYeicFlVNRdVVIxJF4N87Oc74QgregK0JvNu8tklxVxaXcXUItcRA0q+KAqVc4ECBf5X8IaljV/bN5KWNM7INXBz6hja5Bg3OF+lX0oyXfdxe+Z4rMLE/zW/x3qlGzsmvqsey2LXdNZJB/lP5SP6SDJBlHC7fhx1FLGeHn7FFmJkmUIpt3MMlbj4xAjxX8YWAiSpxsV3lZlMk8qIixw/Vzfzmt6FTP604+LhveUOI84vMtvYaURwYuI71hl83VSLJEl06gl+m97BFm0AMzJX2Zq52NqIWZLzq02pNp5KtaFiMN3s5WbXJBqG87AjepYH4vt5LZ0/QDHXVsF1RS34hnea04bGyngHK+Pt5IRBs6WIGz0to7KwO3NJ7oseYEMqH+ZxuquSq0saRp187FMzPDxwkDfjQQQw01HCtaUNNNsOmbiEEGxMRnmw/yCtmQSKJHFuSRWXl42j9DNpXQfSCR7p62TDUF7kZ7qKudJfxxTnaFOYEIKNQzEeD3axO5kX9TnFXhZX1NDiHDu3jaoqz/YFeL6vj5Su41IUrqiu4UJ/xRH3lHOGwWv9YVb2BAhkssiSxNwyL4tqqmh0frH52n+MgjgXKFDgH5oUKr92fMSblnbswsQPkidwilrHE5adLLfkD/QsyU1jcW4qH8tB7rR8SFTKMNUo43Z1Dl5h51e5j3lE2Y4EXG5MZrExmQQqP+ZD3qYbEzLXMJWFNJMWGr80trBGtCMjsVCawBXyJKySwrt6L79WtxIjR6NUzG3mmTTKxWSExgPZ3TyjtqIhOFmp5GbrVEplG2mh8UT6AM9k29AQHGsq52b7FKoUJ0IIPsj2cVdiN0EjjVe2cr1zIl+x5o9QqMLguWQnjyVaSQuNRpObm4omMt2ar7QNIXhreK4c1rN4FSvXFDdxuuNQcldMz/Fo9CBr4j0YCKbbPFzvnUDzYZGbcV3lqWgnz8a68yYui4tryxo4xuEdVU3uSA3yYP9BtqcGR9airiivo8oy2pTVmozzi47drB8cAGCas4il/jqmfyZA5FOj12OBLvalEgCc4CllSUXNESvlvmyWp4O9vBIKkTMMis0mrq6s5Ty//4h7zXFV46W+fp4N9BHNqZhkiXkVPhZWVVBl/9tmdBTEuUCBAv+w7FUG+KlzPb1ygmbdy78kT0IXgm85XmefPEC5cPCDzAk06V5+a97Ei8oBTEhcq83gYm0ircT4P8p7dKsJKnFyu34ck4SXP9DNb8mneU3Cy3c5mjqK+NAI8kvjE8KkGU8R31Vm0SKVEBJpfpfbzntGID8/Nk3mYiV/JWqD1sfvsjsIihQ+yc4t1qkcb6pACMH6XJC70zvpFxl8ko2b7FM4wZzfKe7Rk/wusZuNuRAKEhfbx7PY0TTSXv4oE+bu+B66tXxc5nXuycxz1IyI7vZslHtj+9mTG8QsyVxaNJ5F7vqRr08ZGqsHu1g52ElaaFSbHSwraeJ4xyF3dcrQeC7WzcpoF0lDo9xk5arSBk5zjzZx7U3HeSTUzsZEvgKe4yrlKl89DbbRAtqeSbG8v5P3klFUVWeiw81S/zhmuTxjnNofDEZ4LNjNgWFRPtlTyuUVtTQ6xs6Uu9JpVgR6eWMghC7AZ7GwsLKKM8vKsR3h4EVfJsuqQJBX+kJkdAO7orCwupL5VX5KLUc2hoWyOWyyjNv85chmQZwLFCjwD4eBYJV1Nw/aP0FDsDA7iSvT03nV3MY91i3k0DlNG88tmaPpkuLcaF1LjxSnXhTz/dwcakURD8s7WCHvwUCwyDSZy9ITSaPx72zgPXoxI3M905jPBBJC5T+Mj3lTdGFCZok8kUulFmRgldbKI9pu0uhMl0q51XwUNbKLPiPFXZmdvK8HUZC4xNzE5ZYJ2CVTXnjTO9mohTAhscjayGW2JuySibTQeDLZxtPDLuyZ5lJudk2mzpQXunY1wb3xvWzMhvNHIxzjWOpuGgka6VaT3De4n/fTIQBOsfu5zjOBiuG5siYMXon38mgsH6VZrFi4xtPCPPeh04s5w2DNUC9PRDqI6TmKFDPLyho5v7hmVOBHaybBw6F2NsTzFfB0h4erfPVMdYyugNvSSZ7o7+KdwTACmOrxcImniuPcJWPiO9+Ohnmqr4e2dBIJibklZVxWUXNEo9eBZJInAz28G4kggFqbjUVV1XzVW4rpCNkc+xNJVvYEeGcgiiEEZVYLS2r9nO0vP2K7WwjBllicZ3v6+DAyyHHeYn409c+HcH0eFMS5QIEC/1CEpBT/z/kBm0xBPMLG7cnjqdc9/ND+Lh8rAdzCwj9lj+dErYblpp08YdqFQHCxNpGl2jQOMshNyut0SEP4cfId/RjOsDbyZHwnd7OVOCrTKeNWZlEtXLwlurnb2E6MLM14+K4yiwapmL1GlF+oW2kVg7gx813TNM5QxmEgWJE7wOO5fWTQmSZ7+aZtOvWym6zQeTSzj6cyragYzDSVcot9KuMUF4YQvJHp4YHkPsJGhjLZxg2uiZxiya9ORfUsjyZaeTnVjYFgpqWUG4paRrKwo3qWx4baWJPIt6cnW4pZ5mlmivXQHed3Uv08GGmjV0thkxSWeMazoHjcSDWtC8HrQ0EeixykX8tilxWWeOu5qKQW52GGsIOZJI+G2lkfz8+nJ9uLWOqrZ6azZNS/VWs6weP9XSPt6wl2F0v8tZzbUEc4nBh5TjUM3oiEWNHXQ082PbKnfGlFzZibykIItgwN8XSwl48H867uCU4nl1ZWcWKJd8xa1qfO66d7gnwymDeRjXfaWVhVyallXsxHEPGsbvBm/wCre/roSGbyv2ORk4W1FWOe/aIoiHOBAgX+YXjL3M5vHBuJSzlmq5XcljqebUqIZY6XiUs5jtEr+W7mOIbIcYv1dVqlKD7h4J/UOUwySnlU3snT8l4MBOcaTVxrTCOJxreT63ibLmwo3MIMzqWRoEjyA+N9Nol+LChcK09hgdREGp3fqNt4UT+IAM5QallmmkKxZGW7PsCvs9tpN+IUYeEW6zTOMOXP7b6bC3BvJj87LpWsXG+fzFxzfna8S41yd2IPe7QYZmQudTRyqaMBu2QiJ3RWJzp5ItFGWmjUmpwsc7dwnDXffs4YOqsTHTw11E5a6FSbHFxbPGHUvvIn6Sj3RQ+wLzuEMnxfebFnPCVKvoVrCMG7iRAPDxykW01hlmQu8tSyqGQcHtNht5yzKR4LdfD2UAiBoMXu5sry+jEBIvvTCR7v6+T9YaNXs93FEv+4kUr502czhs4r4T5W9vUSVrOYJImzy/ws9FVTbRs9p9aF4J3IACuDAQ4kkwBMdxdxaVUVRxcVj3FS5wyDdaEBVgeCHEymAZjpKeLiqkqO8RQd0XkdyuZ4sTfEmkA/Q6qOIsFXfV4urPYzsWhs5f5FUhDnAgUK/N0Tl7L8xr6RtywdWFH4Zmo2c3N1/M62mTdNB7Gg8M3sbM5Ux/OUaQ9PmHaiIzhTH88N6kw6pCFuML1OF0NU4uS7+mymiXLWcJD72U5OM5hJeX5vWdhZIfbxmLEHFYPZkp9vyDOowMHbRi93q9uJkKVWcvFt8wymy2VEjSx3Zj9hrdYFwNmmcVxjnUSRZKFNH+Lu9C4+0QZQkFhgHc8SWzMOyUS/nuaB5F7WZfPJW3OtlVzrzAeFCCF4Kx3ggfh++vQ0RbKZa9yTmOeowSTJGEKwNtnDI4OthPVs/s+LJzDPVT3Snm7Nxnkg2srGdL5ynev0s7SkgWpzvhoVQrAxFeGhgYMcyMaRkTi7qIrFpfWUmw45q7uzKR4Pd/LWYD8Ggkabi6Xl9RznGm0I25uK83h/14j7epLDzWJ/LbNdo8U7oak8GexmVX8vg5qKRZaZ76tiga+K8s8EjaR1ndfCIZ4JBghms8gSnOL1srCiihbXWFNYTFV5MdjPC4F+YqqKLEl8pbyUi6sqmOA6ssDuGUrybE8fb4ci6AKKzAqXjqvk3Kpyyv9GMZ4FcS5QoMDfNZtMAe50fEBYTjNRL+X25AmEpBTXO18hJKVoNkr5fvp4suh80/oGrVKMMmHnVvVYZhg+HpZ3sEreB8AFxgSuNqYRJMmt/IFdRHBg4l/sczhRrWCniPCv+gd0EMeDlZvk6cyVqgmKFP+ibWCj0Y8ZmaWmiVysNCEjsSrXxqO5vaTQaJCL+KZ1GlMUL3Ejx2/SO3gp14EBzDaVc6N9MrWKi4zQeTS5nxWpNnIYTDAVcaNrEtPMeZf1rlyMe4b2skuNYULmYmc9l7kacMnmvIM5HebBwf20qfkLTovc9VxSVI9reO7cmUvyaOwgbyf7ADjKVsK13iZahh3YQgg2paI8GjnI7ky+1TvX5ePK0vHUWA61kTuzKZ44TJTHW51cUV7Pie7SUWK7LTHIk6EuPo7n95SnONwsOYLRK6rmeDYU4JVdIWKZLE7FxGUVNVxYXjUmDCSmqrzQ38fzfUGGNA2zLHGuz89FFZVUH+HaYXsqzareIG+GBlANA6cpb/I6r9KH32od83zOMHgnFOW5nn72xvOVeJ3TxvxqP6f5SrEqf/k9iS+CgjgXKFDg75IMGvfbt/C8dR8KEksz0zkv08yD1q28ZD6AjMSS3DQuzk1khWkPT5l2oSM4S29gmXoUbdIg15teo4c41bj5rn4MzcLLcnazkn3oCE6hmpuYQZW5mJ/pH7JGtANwjjSea+T8ZanH9L08pe1HxWCWXM43TdOpll1s1kLcldtJhxHHjZlbLFM5x1wHwAvZdh7O7CMuVKplJzfaJ3Oc2YcQgjczPdw/PFf2ylaucTZzurUaWZLo0ZI8FD/A25l8SMjJNj/XupupMuUFc0c2xoOD+9mejSEBX3NUsrS4Cd/wLnJQTfNY7CBvJIIYCJqtRVxV0sDRtnyFK4RgSzrKowPt7Mzk57UnOMu4orSexsNOPbZnkywPdY60r8dbnVxWNo5TispHZrpCCDYmojzZ382OZF7gpzuLWOwfx1HO0W3mnkyap/t7eS3Sj2oYlDvsXFNVxznlFWNOQnZn0qwOBlkbzq9DuU0Ki6uqOc9fQYl5bKb2xtggq3v72BTL/z6VNivzqyo4w1eG4whO7U9b1y8HQgyqGpIEc0qLuaDax6w/0u7OGQYbwoNU2600ur+cveeCOBcoUODvjr3KAD9zvk+XPEStUcT3kycQJzcSKFJnFHNbZg4I+Kb1DdqlQXzCwa3qbFqMUu6Vt/GK3IaExEVGM0uNqexigGW8Ti9JfNj5BjM5TlTwB9HDN6Pv0i+S1FPEt5WjmIyXD4wgd2v5FSgvVq43T+UrcjV9Is2/pz9mvR5AAuaZ6rjK2kKxZGWrNsBdqZ20GXHsKCyzTeICaz1mSWa7GuGexB72aoMjc+VF9gYcsilv5kq08XKqCx1Bi7mY64tamGbJG6zacnEeGmxlQybvwJ5jK+dqTxPjzfm2bljL8kSsnVfivWgY1JtdLC1p4ITD1qK2pWI8EjnItnS+up3jLOUK73gm2A6JclsmwfJwJ+8OhRHD7evFZXWc4C4dEWVDCNYPDfBEfxet6XzFOafIy6LymjHhIXuTcVb09bA+FkEgqLDYuNhfxeUtjaPuOQsh2B6P83QwwIexKALwWy0sqMivQ9k/I7JpXefN0ADPBfroSOXnydOL3VxUWcEcr+eIprDtgwme6+3nvXAUQ4DbrLCwtoJzq8qpsI2trAG6khnW9IZ5LTBAXNU4trSYnxzV9Jd9iP9KCuJcoECBvxs0DJ607WC5bQc6gguzLVySnsIj1m28Ym5FRuKy3BQuzk1ihWk3K035Vahz9EauUWewUQpytelVYmRoEB6+bRxNlXDxK7bwBp3IwHyauJLJhESa24332CJCOAwz1wwbvg5vYStILFSauNzUgoLEY+o+nsrlr0NNkb3cYp1Kk1JMr57kl5kdrFeD+dvFlhqusU2kRLbSqSW4L7mXDbl+AE61VnCts4UKxUHK0Hg0foBnkh35XWPFydXuJk625Xedg1qahwdbWZcKIIBpVg/XFE8YcWAP6jmeGuzg+aF8OEiVycGVJeOZ6zy0h7w9HeORgYNsHRblYx2lXFFaT8thqV4HMgkeD3Xw3rD7utnuZnFZHXMOmylrwmBdLMST/d10Z9NIwFxPGYvKa2i0H5r9CiH4OB5jRV8PW+P5arbJ4WKhr4pTSspQJGnknrNmGLwTjfBMMMD+YZPXRJeLBRWVnFTiRfmMyAYzWV4I9vFqX5i4pmGSJE4rL+WiPzJPTus6b/ZFeKG3f8QU1uiyc36Vj6/4vEfcgVYNg/dCMV7qCbM1mk8jK7aYuKSuggtrfX/pR/mvpiDOBQoU+LugVYnyc8f7tCoxygw7t6WORxOCW5xrCUspGgwP38vMIYPGN62v0yXFqRBOblVnU2W4+amygY1SEDMK1xrTmW9M4C26+VfeZ4gcTXi4lVnUCDfLjT2sEgfQERwr+bnDewLGgMYj2h6e0Q+gIZgpl3GLaTq1kov1epB7sjvpE2m8kpXrLJM5zVRNQqjcnd7FC9l2NASTFQ832afQYvIQNbL8Kr6DlzP51adp5hKuc05kktmDJgxeGE72ihk5PLKF69yTOcuRN3NF9SyPDx3k5UQ3GoJGs5uri5uYbcvPehO6yjNDXawe7CItNMoVG4tL6jnDVTliBtuWivF4tJ0tqSgAxzi8LPHWM9l+aAd5Z2qQp8JdbEjkDWMT7UUsKa9j9mHu67Su81q0j6fDPfTlsiiSxJklfhb5aqg57ByjJgzeiQ6wsq9npKI+usjDQl81M92j29xDqsqKQC/P9QUJ53LIEpxU4mVBRSVT3GPztD8ZjPNcsI8NkRiGEHjMZhbXVjHP76PsCIatjmSaFwMhXu8Lk9IMZAlOLS/h/GrfH83IDqSzrOkJszYwQCynAjCjxM051WWcWO454srVF0lBnAsUKPA3RUVnuW0HT9mGHda5Bhanp/G4ZQdrzW0ow7Plc3KNPGLeyctKKxJwnj6BpepUXpHbucP0Plk0Zgk/39KPJofB91nPNsLYULiB6ZwvGnhXBLjD2MAAGSpwcJM8nePwsy0X4WfZjYTJUI6NG83TOEmu5IAxyPcyH7DNGMCExEJzI5dbmjEjszp7kOXZA8SFSoVs51rbRE4xV5JB5/HkAVam20gLnRrFyXXOFo635Kuut9NBHozvp1dPYVIZiJAAACAASURBVJdMXOFq4iJn/rBE3FBZOdjKc4kuMkKn0mRnaVETcx35Sjihq6we6mL1UD6xy6NYuKq4mXlF1VgkOX8YIhVheaRjpH0901HCFd7xTB0WZSEEm5JRngx3sS31qYGrmCVldcxyHjJwDWoqzw8EeD7cy5CuYZFlLiirZEFZNX7LIUNWQtN4eaCP50IBQrl8LvVXSspZ6K8aE7HZnUnzXF+QdVsjxLMqNlnmAn8F8/0VVH7G5HWk1nWzy8mFlX5OKfOOCkOB4Yo3HOPFQD/bYvkdaq/FzPw6P2dXHtl1rRoGH4QHebknzKZIfm7uNpu4aJyfeVVl1Dr/dhGeBXEuUKDA34x9ygB3OjZwUIlRbji4NXUcuhB82/E6A1KaRqOE72WOo5sE19vWEiNLvSjm1txsFCFzm/I2rVKMIqzcqh/NcaKSx9nNsxzAAOZQyS0cRVpo/MD4gE9ECDMyi6WJLJKb6RFJbtc+YEcsAgguU5q51DSBhND4efYT3tC6EcAcxc/11slUS07Wq0Huy+whYKRwYmKZbRLnW+swIfNKpptHUvuJGNl8NeycyFm2GhQkNmYHeDixn/3q8K6xYxyLXQ2UKFYShsojg62sineQFjpexcqyogl83Zm/ifxZUS5WLFznbeJcdw12WUEIwUfJAZZH2tk17L6e7fByubeeKcOibAjBe/EwT4a72J/Jt2tnu7xcWjaOaYclegWyGZ4J9/BqtC9vyFJMLPbXcn5pFZ7DLjkFsxlWhwK8Gu4jbejYZIXzyytZ4KuiwnpI1IQQbBoa5Lm+IB/FYgigymXnEl8l88p9Y5K5etMZXurrH2ldK8OrUBdU+pnkco6pevsyWdYEwrwSDBHLaQAc5XFzXpWP40uLj5gU1pXM8EpvmNeCAwwOf80Uj4tzqso4xV8yRvj/FhTEuUCBAl86OXQes21npW0nBjAv18SC9CQetm7jbVMnJmSW5qYzV63jbvMWPpTzcZpXa9M5S2tgubybF5QDGAjOMOpZZkxnEyGu4XUiZKjEyU3MYLoo53FjD6uHW9hzpApulKdhx8zd2nZe0fNrTnPtNSyVW/BKNp5W21iRO0AWnQa5iOstk5llKmePFuM76Q/YoUdRkLjAUs8S2wTckpn3c/08lNxHh57AgsxljkYuGTZ7bctGeDhxgO25fHt5rq2Cpe4mqk1OUobGE0NtPB3vIGFoeGQLVxY3co6rBqukkNBVnhxq/5Oi/H4izPJIO/uyw9eanKUs9h6aKWvCYN1gP08NdNGVTSEhcUpROYtKa5lgP9RC3p9OsDLUzTuxMAbgt1hZUFbNmSX+UYasnYkhVvX38t5gJB+BabZyeWUt80r9o4Q2peu8GQ7xXH8fnel85TvZ5cpXys11RAeSI88aQvBRNMYLwX42RvNz6mKzmctrqzjnCK1rQwg+jg7xYm8/H0UGMQS4TArza3ycU+mj1jG24s3qBu/2R3m5N8z24cq6yGxifq2Ps6rKqHfZx3wNQCSr8mYgyh+CUWZ53VzTXPWXfMT/agriXKBAgS+V3UqYO50f0CkPUWE4+VbqOIJSkm84XiMh5Zikl/Ht7Gy2SP3cYF1LBo2jDD/fVI9mH1GWmV4jSoZq3HxLn0WJsPMjPmIr+ar4CiZxsWjmPRHgauP1US3soyUfz+ltLNf2kUJjnOTietNUzipp5KnAbh7M7SEsMngkKzdbpnKmqZagkeInyc38Qc0HhZxo9nOtbSI1iotPcgM8kNzHHi2GjMTXbTVc4ZhAuWJjb26QhxIH2JTNm6zmWH1c5W6iwewmbWisGGpnZbydIUPFPRwgcr6rBrtsIqGrrBjq+KOibAjB2/F+noh00JZLIAEnu8q53Fs3shKVNnReiwVZOdBNv5rJz4o9FVxSWkut9VAIyaZEjJWhbrYk8qLYaHOysLyaUz3lI4YsXQjeiw2wqr+XXcMnGxvtTi72V3NqSenInBvyFfXzfX28Euonqet501ZpGRf6K0ZCQz6tZmOqyqt9IV4KhujLZgGY7HZxfqWfk0rHVrChbI61wTCvBMP0Z3IANLsdnFvlY255yRENXq3xFC/3hnkzGCGp6QDM9BZxVlUpJ5Z7jlgl53SDDaEhXu+N8FF4CEOASZY42e8Z8+wXhSSEEF/aT/sTHH54+89RXu7+bz1f4K+j8L6/XP63vu8MGo/at7HKuhsDOC/bzBnZBn5v3cwOJYQDM9dkZzBRK+OXlo3sl6IUYeEGdSaNegm/U7awTQphRuFyYxLzjAZWso/VDFfFVHATM4iJHHfp29hDFDMyi+RmFjKBj0U/92o7CYgUbsxcaZrIPKWe3UaUh6V9bEuFMSOzwNzIIksTWaHzeGY/a3Kd6AialWKut09iuqmUveogDyb3slnNG6lOtlaw1DGBcSYX7WqChxMHeC+TDwCZaSllqbuJyRYPWaHzUqKbp4baiRk5nJKJBe46LnSPwymbGNRzrBrs4vl4N6lhUV5YPG5ElFVh8MZQkBXRTnrUNDISc90+Li2po96adyvHtBwvRHt5PtLLkK5ikWTOKqnk4tIa/OZ8RZkz8s7rVeEe2jP5laajXMVcUl7D0YcFh8Q1lZcH+nkxFKAvlxfPOcVeFviqmO46tBP8ad718/1BNsTyq0oes5lzfX7O8fnwmg9VvkII+syCh3cd5O2BCJohsCoyp5eXcW6Fb8z9ZEMIPooMsiYQGqmS7YrMV31ezqosp8U91qUdVzXW9UVYGxhg/1D+9/NazZxZWcpZVWVU2seuTgkh2DeU5rXeCG8FosTVvJA3F9s5o8rLVypKKLJ8vvVsefnYW9SfUhDnAn+Wwvv+cvnf+L43mnr5teMjgnKSSsPFt1LHskMO8ZRlFxoGJ2m1XJmdxkumVl4cblefptdzpTqVF+RWVsv7MBDMEVXcpB/FHqLcw7ZDVTEzaBIlPGDs5E2Rj9A8VarmOnkqCaFyl7adbUY+PvM8ZTxLTC1ERJYHsnv4QA9iMimcQgVXWybiksw8kznIM9k2MuhUyQ6W2lo41VxJt57koeQ+1ufywjvLXMrVzhZazMX0aEkeS7SyLh1EIJhk9nCVu4mZ1lIyhs6aZDcrhtqJGjnsksJ89zgWuOtwyWYGtCxPD3byUryHrNDHiHLK0Hh5MMCqWBdhLZ9Bfbq7gktKxo0kevXm0jwz0M2rsSCqMHArZs4rqeJ8bxUlw/nYg5rKiwMBnh8IENNUZGCup5yLyqpodhwSio50iudCAV6PhMgaOlZZ4Wvecub7qqg9LPM6oWm8Hg7xQn8f3Zn8gYgJTifz/RWc4i0dVZWmdJ11oQFeCvbTkcuiqTo1dhvnVfj4mq9szOw5lM3xajDMK4EQoWzePT3B7WBeZTlfKffiMI2ukg0h2ByJszYQ5r3QIKphIEsSx5YWcXZVGceWFY9ZzQIIZXKsC0R5vTdKRyL/O3gsJr5WVcLXqryMdx+53f158KfEudDWLlCgwBdGVEpzt30Tb1k6kIGF2UnMzFXyW+smuuUhyoSDb2SOIYXGbda3iJGlWri5RZ1FXKjcanqLAdJU4ORmfSYlwsbP+JidDOSNXUziAtHIC+IgPzE+JotOEx5uUqZRjYuHtN2s1Tvzpi7ZzzLTFGyYuC+7m7VaFwaCKbKX7/uOwTto4qVcJ8sz+xkSKh7JwjLbJM6y1DJgZPmvxA5ez+QvPrWYirnG2cJMSyk9WpKfx3bwRro3nzttcrPU3cRx1nLSQmfFUDvPxDuIDYvyInc9F7vrKFIsBNU0D0baeDXRiyoMyhQr1xQ3cpa7CpusMKSrrBzo5PlYN3FDwyYpXOSp5aKS2pHs673pOCsHulg/FMZA4DfbWFBaw5meCuxyXsA6MylWh3t5LdqHKgRORWFheTXnl1bhG86yNoTgo6Eoz4UCbBrKu7j9FivnlddyVqkP92FmsLZUihf6g7wZDpMxjJHW9bk+P5Ndo1eV9ieSrOkLsS40QFrXkSWJ06p9nF7sYWbx6EQuzTD4MDLIq8HwqCp5XmUZZ1eW03yEKrk3lWVtYIDXAgOEs/lWd63TxpmVpXytohSv1Tzma1Kaznv9g7zeG+GTSAIx3LY+pcLDGVVejil1o8hjhfzLpCDOBQoU+NwxELxqaeV++xbiUo4WvZRrU0fxpqmDH9jfQkLiArWFr+TquN+8le1yCAsKV2nTOE6r4h5lG1vkPswoLDGmcIZRz+Ps5jU6EMCJVHGdmMo+MciNxluESOPByi3yDE6iilVaKz/QN5BFp05yc4NpKhPlElbkDrBaPUgOnXGSi2utkzhW9rFZjXJbfCtBI40dhaW2Zi60jidlaNyd2M3LmW40DOoUF1c5mznB4qNXT40S5TqTi8WuRk6x+UkLnafieVEeMlQckonLisZzkWscRYqFbjXFPZEDvJkIoiOoNNm5pLiOr7krsUgy/WqGhwbaWDPYS1YYFClmrvDWc76nhiLFjCEEH8YHWDnQPbIO1WhzcUlpLacU5WfFQgi2JGKsCvXwYTxvRquwWJk/bPL6NNoypeu8NtDPc6EAPdnhtC1XMReUV3KC51AQiGYYvBuN8FJ/H9vi+c6Oz2LhMp+fr5f7RkVrpnWdt8IR1gT72ZfIG7/KrRYWVlfwdV85k2pKR3WHOlNp1gYHeK0vPOK4bh6ukuceoUpOaTrv9kd5LRBhWyz/fewmhbOryzizspRJRWNd3YYQbB6I80Ygyvq+QbK6AcBkj4PTq7zMrfDgNh9ZEg/GM6wPDjKhyM4cf9ERn/m8KYhzgQIFPlc65EF+5fiQ7aYQdmHipvTRKIbC/7WtJy7laDRKuD4zkw1yL7da38RAcIJRzZXqVNZKHdxseiMfDiIquU6fzgaCLOMN0mg0UMyNTMcmTPynvpldRDAhs0hq5mJpAn8werhKe4MYOTxYuN40hdPlGl7WuvhpejNxVEolG1dapvI1pZqNepgbE+vpSiXBEMy3jucyaxM6gkeS+3kx3YmKQYVsZ4mzidOt1QT1NHcO7hwlype7GjjVVkFKaCwfauPZRBdxQ8Ulm7iiqIEL3eNwyWZas3F+M7CPt5P9CATjzE4u9dTxFWcFiiTRlk3wTLSLtxJ9aEJQZrJylaeWs4ursMsKWUPnpWgvz0Z66MzmZ6lHO0tYWFrLzOEd5Yyh82okxHMDvSPz5MkONwvKqzmx6FAMZ3s6xYvhIK8P9JM2dMyyzJmlPi4sr6LRcahC7ctmeSXUzyuhfiJqvr08s6iIC/wVHOcpGdUqbkumeCnYzxuHVclzvB7m+X0cW1I8KlYzpem8E47yajDMzsG8e9ptVrig2sfXK8podI2dPX8SjfNaYID1odiIuE4vcXNWZSkn+jxjYj4BWofSvBGIsC4QJZLNC3+lw8LplV5Oqyyh2nnk6M7eZJY/BAZZ1xujI55vd59SWfyliXNh5lzgz1J4318u/6jvO4fOk7adPGXbgYbgBLWGszKNPGbdyT55ADtmrshOpdiwcb9pKxEpQ6VwcZM6k7DI8JCygyGyVOJkmT4DIeA+dhAgSREWrmIKM4WPh43d/EF0A3CSVMV10hRaxRAPaLvoEUlsKCw0NXGh3MgGvY+Hc3voE2mcmFhkaeJ803h26FEezuxlnz6IBJzvaWCBUYcVhZWpgzyf7iCHgU+2cbmjiTNs1fTrGZ5ItPH6sCiPM7lYPCzKcUNldaKT5+NdJIWGWzazwD2O813jcEgKWzMxVgx28PHw6cZGi5vLPfWc6ChHArakozwd7eLjVP7UYq3FwULPOE4r8mOWZCJajucjPbwUDTCkq5gkmVOLyrm4tIZGW94B3ZfL8OJAgJcjfcT1/H7wKcWlXFBaxeThzGtdCN6PRXg+HBiJ1iwzWzmnzM+8soqRy1CGEHw0GGNNfx8fDcYwBDgUhTPKyjnP56fWfmgOm9R03goP8EpfaKRKLrVYOMtfxln+cnyHXYQSQrA7nuTdoThr2gOkdQNJyt9Z/npFGSeWjXVPd6cyvBYY4I1ghNCwQ7vCbuVrFV6+Vll6RHNXMJ3lrUCMdYEo7cNzZJdZ4VS/h9OrSpjiGVtZA4TSKm8HYrwViLEvlu8imBWJY8vdfKXKw/G+Iiyf47WqgiGswF9F4X1/ufwjvu/NpgC/cWykW45TZti5Kn0Uu+QwL5tbEQi+qtVzRq6BJ0272Crnzy5eqk1mol7K/fJ22qQYdkxcZkxipuHnfnbwCSEUJM6nkfNFE88brbwgDqJh0IyHZcpUZCFzv7qTXSKKDMxT6lmstLDHiPFwbs//z957xUhyn9mev4iMNJHeRma59t577w3ZTSfKixzpajR3BwMs9n0wwLws7mKFxeLuLgYXmLsXuDPSSBo5kpLouslmG7Z31d777uquqvTeR8R/HyI7q1tNzWqGZI8uUAfgS2Wk6T+r8sT5vvOdj7tmGQWZr9gn8aZjOneNMv9Yv85lwyrzbrAn+J5rBjNiEf5+6CK/rd+nIQyisos33VPZ4eonadT5eeVuVyk/ScoZo8lb5ft8WO0YuWQH3/RN5FVvPy7JxpFaml8U73Oj2dna5Ary7cAklqthDKxxqF8XhrjdtJTjAjXIN0MDrHBbCvd2o8Lb2YfsL6XROyavV0I9vBbqJWp3IoTgUq3EbzLDHClmMQG/ovBKuIdXIglidou48u0WH2aSvJ9JkmlbrutFvgCvRZ8uXWdbLXZnUnyYSpFqdUaVPB5e1eJsDEe6ylQIwZVyhV3JNAeyOZqGZb5aFvTzclxjZTj4lKJON1vsTWb5KJnlYa2BYpcJ2xRejEd5MREh/nuLJ8ptnQOpPHtGslwtWoSvKjY2aiFe6AkzL/BsBGexpXMwWWDvcJ7LBes5iiyxIupnW2+IldHPJtZ8s83h0RIHhgtczFcRAmQJlkZ9bOoNsibux2t/VpF/ERgn53F8Loyf9/PF/0jnnZZq/Ff3IAftD5CAV5sz6Nd9/NRxmZLUZKIZ4AfNhQzKo3xgu42JYKXZyzfbs/itfIvDkqWAXzQn85o5jXe5zR6sYJAVxPkLMY/TIsXPzRtUaZPAzV/Ic5kk/PzIuMpR01qtuE7u4S9ss0mKOv/Yus4N05o73qL08X3HTLJmkx81rnNOt5TrKkXjz9WZaJLKW/W7vK8/pNRqEpadvOmeyk5XPw/1Gj+v3OFgI/kMKT/Sa/yyfI+91RF0BDGbi2/5JrLDY61+3FMe4delBzxqW6Efa9xRvh2YyGxXgKqps6s4wjuFIdJ6ExmJ9d4Y3wgNMMvlt1RrJcfbuYecq1r95H6Hm69H+tgWiOPqlLcPFDL8JjvczbGe6vLw1Wgvm4MxHLIV5Xm5Wubd9CiHChl0IVBlG9sjGq9FE0xUrbKxKQRnS0XeT6U4VshhCHDJMlujUV6OxZnuGStxF9ptPkll2ZVK86ATqZlwOdmhxXhBiz4VkdnqxGnuSWYYzFuzwnZZYm00yHdmTWAyylNl7pZpcjJTZG8yx/FMEd0UyJLEkrCP7YkIa2JBXL9HrnXd4Fi6xL6RPKczJQwBkgQLQl629oRYFw98Zh+52NI5NFrk4EiR89kKZocFF4Q9bOoNsj4RIOj88ru+4+Q8js+F8fN+vvgf4bzbGLztvMbP1Es00JllRHi1MYP37De51ilhv9mcg82U+Wf7FSq06Rc+/qK9gJsUeEu+QRuDOSLCD4z5nCHF29ykhckk/PxPYh5l0eYfzCukqePDzp/Js1ghNH5h3uITYwgTmCuF+Uv7XEwh+FHzOhfMztyxrYfvO2fSNA1+1LjBKd1atbhMifJ910zissrbtXu827DiMjWnm68rE3lZHeBOu8w/V+5yvGltkZqq+HjTO4V1rji32mV+XrrLkXoKAQwoHr7tn8QWd4KmMHm/9Ih3Sg/IGy0USWabJ8G3ghMYsHtIthv8rviQD4rD1EwDpySzw9/DN0IDJOwqFUPn48Iov8sPM9yyiG+xJ8TXw30s94aRJYmRZoP3cyPs6pSuZWBNIMLXor3Mc/s7SzF09ubSvJ8Z5V7d6jlPdLl5LZZgW1jrGsEyrRYfZ9LsTqcY6QSATHG7eSWmsSUaxdPZs2wKwelCkY9SGY5m8+hCoMgS68IhdsZjLAr4n9rxfK1c5eNklgOpHJVO6Mdsv4cX4lE2aSG8itL9HTeF4HKxwt7RHJ+m8lQ6s8WTvCrbEmG2JsLPpIO1DJPBbJn9o3mOpkrd3vM0v8qWnhCbEkFirmdztEstncOjJT4dKXDuCUKeHXKzIRFgY0+QmPqssxsgWWtxIllhit/FvMgXt895nJzH8bkwft7PF3/q5z2ojPBfOiVsv3DyRmMuQ5TYZb+DQLBJn8jydi+/UK4wJJXxYOe77bm4TIWf2K6So04Ulf9ozKcqdH7CVYq0COPi+2IOMeHmv5uXuY219/ir0lRekCbwrnGPDw1r+9MkyccPlNlEhIsft29wyrCIdIVN4weOWZhC8NPGLY7p1jzyAluYP1dn0iu5+VX9Lu/XH9DCJCQ7+ZY6mT/vn82RkWF+VrnD2ZZF8HPsQd70TmG5I8LFVoGfl+8x2LAem+Hw8x3fJNaqGim9wW9KQ+wqj1AXOqqk8Kq/j6/6B4jYHFxplHi7MMSRijXqFLQ5+Gqwj1cDffhsdh40a/wu94g9RSuj2i7JbAlofDXcx1SXF1MITpXzvJsd4VTZ2nXsVxReCiV4JZIg7nBZARq1Cu9lRjmQz9I0rWSudcEIr0QT3cAQQwhOFvJ8mE5zsmiFhThkmY3hMK9ocWZ7xsrFD+sNPkql+SQ9NqI00a3yUjzGtlgU/xOKNNlosi+V45Nklgc1q8cbcdrZHo+wPR5hgvvpWeGK08avrjxg32iOZKePHHHa2ZoIszUeZorvaQI0TMHZXJkDowUOJwtUdYuQe9wOtvSE2JwIMdH7bGRnuaVzJFni05EiZzMVjA7dzQy62dgTYEMiQNz9LJED3C83OTJS4tBwiVtF62ZpVdzHf1o18f/3b+SPxTg5j+NzYfy8ny/+VM87JVX5r+5BDtmHkIGXmtMI6irvOK9To80EM8A3WrM4LD/kpDyCjMROYwrzdY2fy1e5L5VwYONb5kwGTD//xFUeUUFF4dvMYI6I8DPzOueFFXe5VRrgm9I09huP+I1xhxYmPZKbP1dmMwk/P2nd4LBhRWoutEX4gWMWNiHz08ZNTugWWc+xBfm+a4yUdzce0sYkJrv4tnsKO5x9nG8VeMd4wGDJUteLHRHe9E5hnj3A4UaaX5fvc6Nl9YwXOkO84Z/MEmeYa80Sb5UecLiaxkQQsTl53T/AK/4+XJLMwUqat/ND3czrqU4vXw8OsNGroUgSJys5fpt7xGDV6n9HFSevhXt5KdhDQLFT0tvszid5PzvKSMsivNluH69FetgQiOKQZSvYI5/mg0ySWzWrb51wuHg5GufFiEaok8w10miwK5Pi40yabGcd4jSPh5diGpvDkW4ASM0w+DST46NUmssl6/U8io1N0QgvalFmPbF4oqobHMrk2ZPMcrFYRjxRtt4ej7Is5H+qbJ1qtDiQzLMvmeN+wwohURUb62NBtibCLAr5nrreFIJL+SoHRvMcTBa7CyqiLjubEkE2JULM8KvP9J4LTZ0jySKHRoucy1S7hDw9oLKxJ8jGngCJzyBkIQQ3Cg0Oj5Q4PFLiYcWqJtgkicUxD2t7/GzqDeB1fHH953FyHsfnwvh5P1/8qZ13C4N3nNf4qXqRJgaz9SjrmwO8b7/NsFzGJxx8qzWbjGjwvmJFaS4y4+xsT2GXfJdzUgoZiRfMSawye3mLm1wiaxm4mMJ60cc75m2OC6t/vFyK84Y0k/Nmhl/rt6ihE8XFnykzmUGQX+q3OKhbpDxLDvIDxyycKPy0cYPTukXs820hvuuaQUJS+UX9Dnsaj9ARJGSV77inssXZw9Fmil9V7nFHL6MoNpbZIrzhncxkxctH1WHeLj9g1KgjAWtVjW/6JjLLEeBILc3bxSEuNzvzxQ4f3wgMsNETp24afFAc5nfFR2T1JhKw2hPl68EB5qsBqqbBR53S9UindD3fHeD1cB9rfVFk4Hq9wnvZEfYX0rSFwCHLbAnGeC3Sw3TVcmbfrFX4MJNkby5N3bRGllYHwrwcjbPUF0SWJKvnm8+xK53ibMm6uXDbbGyNRNkZ07q9ZFMILpTK7E6mOZzL0+w4qBcF/OzQYqwNh3B2er2GEJzOFfkkleVIpkC7UxteEPSyVYuwIRZ6Kumr2NI5mLaWRjyeR7ZJEuv7o6wJeFkdfbqPbArB1WKNg6MFDiYLZBrWjUTAobAhEWRzIsjcoOcpEgfINtocSZY4NFrkwhMl6xlBlfUJSyH3fsbIlGEKLmarHBktc2S4RLrzfg5ZZkXcy9oeP6vivi+UkJ/Evws5G4bB3/7t33L37l1sNhs//OEPmTBhwh+8fpyc/3Qxft7PF38q5y0QHLM/5P9VzzAsVwgIJ681ZnBRTnPOlkRG4qX2NMK6ym/sNyjTokd4+FZ7NhelDPukBwAsFwl2GlP4hCGOMgzAanp4VUzhE3OI/cJayziPCH8mz+SeWebn+k1KtPDj4A1lOvOI8Mv27a5Sni4H+J5jBh5h56fNm5ztGL0WKhG+55qOHwe/rN1hf3MEE0GfzcOb7imstmt80hjh7ep9koaVTb3BFed/njAPCjq/qQzxfuUhZbONXZLZ4enla94JhG1OPq6M8E5xiBHdItUVaoRvBCawyBXibqvK7wqP+KQ8SkuYqLKNnf4eXg/202NXud2o8G5umL2lFM3PKF3XDIO9hRQfZEe53bAMXr0OF69GengxZKVzVQyd/bk0H2ZTXZUctTt5KRpnR0Qj5rDc2zeqVT7KpNmfzVAxrB7ufJ+PnTGN9aFwdznEw3qDT9IZ9qazjDYsldjjcvKCFmW7FiXeGYESQnCzUmNvKsu+VK4bEtKnOtkej7A1HiHxhNu6phscVIqs5wAAIABJREFUyxTYn8xzOlvqKtcFQR+bEiE2xEJM6wt1f8dFh5A/HS1wKFnoEqTXbmOtFmBzT4hFIe8ziV3pepvDo5ZCvtRxWQPMCblZlwiwPvHZCrmmGwymqhwZKXEyWe5maHvtNlbGfazv9bM05sWlfPlrI/9dyPmTTz5h7969/PCHP+TEiRP86Ec/4u///u//4PXj5Pyni/Hzfr74UzjvO7Y8f68Ock5JIgPbW1MQBnxiv4eJYKnRw8J2nA9ttxmVqnix81V9BlVT5z35Dm0MpoogXzdnMCjS7MOK0JxDmK+J6Zw10+wW9zEQTCXAd+WZjBp1fmncpEALNwrfVKaxmChvte92SXmGHOR79uk4hY2ftW5zvkPKizukLAmZX9bucLxllbUn2ry86Z7KIiXCe/Uhfld9QFm0cUg2dqh9fNMzibYw2WWO8tv0PdrCxC/b+Yp3gNe8AzRMg3fLD9lVHqHSIezt3h6+5h+gz65ypJLh3eIjLtQtFZ1QXLwe7GdHoAc7MgdLad7LD3OlbinXuN3FK6EednZK1zdqZT7IjbKvkKZhml2D18vhBEu8QSTgUrXMh5kkBwsZWp286JX+EC9F4yz3WyEghXabvdkMu9Mp7nXWM4bsdrZHo7wY1ZjQmUsut3UOZHN8kspwpWwRvGqzsT4S4kUtyjz/WGn5Ya3BvlSOfaksj+oWefvtNjbFwmyLR5jlGytxP3Zaf5rKczRTpNUxaU31udkSD7MpHkJ7wqQVjXo5eCvJwWSBg6NjhOxRZFZrATYmgiwJ+54ZfRqqNLsl68dzyJIE80Ie1icCrEsEPtPUlW/qHBspc3S0xJl0lbZpfb6oy86aHj9rEj4WRj0onxHZ2TJMzqdrDCYrzI26Wd/3xYWQ/Ltka2/bto1NmzYBMDw8TDQa/bLeahzjGMcXhLxU58fqBXY5bmECS9s9TNaD7FbuULG36DN9bG9P5oj0iH9QLqAg8Zo+nYDp5LfyLcpyixhuvmHM4KGo8H9xBh3BFAJ8Q0zntlnk/xCDtDHpw8ufSTMpmC3+rnWRPE1UbLxhm85SSeM37bv82LgBwEw5yHftMzCEyc8at7lmWGS4XInxpnMaFVPnHyo3udS2+rdzlCBvuKcyIHt4p/aA/1y4QksY+CQ73/NO5TX3AHfaFf5L/honGhkUxUbM5uSbvolsU3u40Srz/2Sucaw2ZuL6XnAyr/r7QcAHxWHeLw2T1S3SWuoO83qwjxXuCKl2k39OP2B3YZSS0UZCYoU3zKuhXlZ4wzRMk/2FNB/kRrlZtwhSszv5TizOi+E4UbuTfLvFW6lhdmWTPGxYJNTjdPFSJM72iEbE7kA3TU4W8uzOpDlRyGMILBNYKMyLsRjLA9ascds0OZrNsyed4Xi+0B1RWhoMsF2LsCYc6s4v51ptDqRy7E1luVG2nN4OWWKTFmKLFmFZyI+9ExLSNk0Gs0UOJC1Crnec2X1uF1viITbHwwx4xkxaj0vWh5MFjh+v8LBjsnIrMtt6Q2yMB1kSeZqQhRDcKjU4NFrkaLLUTeqSJVgc9bIuEWBdwv9MfrYQgvvlJseTZY6NlLmaryOwdOhkn4vVPT7W9viZHnD9wTCSk6MVToxUOJuq0ujcbOSbxhdKzv8SvvSe81//9V+zZ88e/u7v/o5169b9wet03UBRvpy6/jjGMY5/GS0MfsEl/jtnqdJikgiyVkxgv3mPYSp4cfA6M7hjFjlqWrPJ2+TJTCPMO+0bpEQNL3besM+hbhj8unWdJgb9so8/c8zhUbvCW82bNIRBXHbzF+651A2Dn1SvkjUbuCU73/HMYImi8evqLT6tW+XveY4w/9E/h5Le4sfF69xpWwp0k7uP/xCYyaNWjR/nr3OrE/KxzpPgz8MzUZD5WfYWe0tWcEiP3c13I9N40d/Pp6VR/jlzm9sNqzqxwB3iu7FprPZqfJwf5hfpu9zsKN3Z7gBvaFPYGkhwo17mV8l77MmNoAuB22bjtegA39QmMuDycCSf5q3RBxwtpBECAnY7X9H6+XpiAr1OlauVEr8bfcSu5Ag1Q0eWJNaFY3y9p5/V4SgCwZFMlvdGhjmUTaObnX6zpvF6bx9LgiFkSeJGqcwHI6PsGh4l9zgoxOfjtb4edvTECTocVjhJocSuRyk+Hk5R6MRuTvV6eLk/zo7eOFonWava1tk3kmH3wxSn0gVMBDISK7UQO/s1NvVEcHf6yLppcipVZM/DNPuHs5Tbj+MwnWzvj7G9P8qs4Jjj2xSCs+kSe4eyHHiUI9VR4B7Fxsa+MNsGoqxKBJ8iZFMIzqXKHHiYY/9QjpGq9W90yBKre4NsGQizvi+E//fmkHXT5FyywsGhAgeH8jwsW+8lSxILNS+bJoTYOBCk3/+sq9sUgsupKoeHihweKnI9W+s+NjHgYt1AgHUTAixOeLu7qL9sPBdDWDqd5lvf+hYffPABbvdnz4iNl7X/dDF+3s8Xz/O8BYIj9iH+m3qWEbmCTzjY2JrINSnLLTmPgsy29mTapsl+2wNMBPPNGIv0OHvlBwxTwYGNV8wpOE0773KbKjoRXHxNTCNvtnhf3KWBQQQX35CmYZjwtnG7q5Rft01hJiF+p9/jrGEZuubIIb5tn0baqPNW6y6jZh0Z2GLv43XnJK61i7xVe/xzic3OHr6hTmJEb/BW9R5X2h2zluLjW97JzLUH2VV9xHuVh5TMNjYkNrjj3X7yAZHhl8N3KJltqw/t0XjdP8Bku4dPKyneKw5zs+O6nujw8JVAH1v9cSqGzu7CKLvyo2Q6KnqO6ufVUC8b/DGapsG+QppduWS3lxy1O9gZTrAjFEdzOLlXr/FxLsWebIqCbpHoZNXDzojGtnAMn2In22qxL5vhk2yGOzWLOPyKwuZIhB1RjWkdc9dQvc7edJZ96SwjnT5y0G5nSyzCC1qUKW7L3Vw3DI5ni3yaznEyV+wau2b7PV1jV8hhqVFDCM7nyxxM5TmUKlDqEHLU6WCDFmRTPMwsv7tLyLopOJcrczhZ5Eiq2O1R++w2VmsB1msBXpzVSzFX7f4eNgyTwXSZo8kSx1MlSi1LhbsVmVWan3WJAMtiXtTfE3CVlsGpVIVjoyVOpSrdOWnVZmOp5mFNws+KuJfAZwSKlJo6p5NVTiYrnB6tUOy8pyJLLIi6WZnwsrLHR5/3s0etvgj8u5S1f/vb35JMJvmrv/orVNX6hbB9Rij5OMYxjn8fXLdl+W/qGS4oKWxIbGpNpCCavG+7BcAavR+/4WSf7QEtm8EE4We13sdJRvmJfAUbEjvNKQRMJx9yjxItfNj5rphNwzT4ibhOA4MwLr4rzcIwBb/Sbz9Vvp6Aj3fb9/m5eRuAxbYoX7VP5l67wv9du0hBtLAj85pjItvsfRxtpfibwmnKom393DWBl10TONvK8r/mzzNqdOZRnTG+7pmEGxvvVIb4P2uX0RH4ZDvf8U3iVU8/j/Q6vyw84GgtjazIuJF5IzCJV/19VA2D94qWwatmGshIrPFEeT3Yz3xXgFPVPP/7w2ucquQwsZK3Xgn18nKohylODxeqRf7zw5scKmZoC4FNkljrj7AzHGe5L0TNMNifz/BRNsX1mkX6PpvCa7EedkQ0pqkemqbJ0UKeTzIZBktWvrUiSawNhXghapWt7bJMttXi7eFR9qaz3OxkW7tsMltjEbbEIiwJ+FFkmZZpcixbYH86x7Hs2FamiR4Xm2NhtmhjOdW6KTidLXEwledIeoyQgw47r/XH2BQPMzcw5ppuGiZnsiUOp4ocSxW7JqugQ+Hl/gjrE0EWhrzdnq7DJpNvtjmRKnMkWWIwU6ZtWDcIYZfCyxPCrIkHWBz1dMvoYJWrH1ZaHE+WOZEscylb6xrOYi47W/qDrIp7WRj1PNOvNoXgZr7BydEKp5IVrufqmJ3Hwi6FHZOCrEp4Wax5cH9JcZ3/GnxpyrlWq/E3f/M3ZDIZdF3nL//yL9m2bdsfvH5cOf/pYvy8ny++7PN+JJf5B/UcB+2Wm3qBruHW7ZxULGfzHCPKgO7nkO2hNcYkVNYbA1wVOa5JOSQkNoh+NMPDx9ynSAsPCi+JyRimxC5xjzo6IZy8Lk2laRq8Z9yjTBsVG6/ZJpMQHt7V73HXtP6da2wJdigDXNLzvN98QA0dNwqvOSeyxBbjk+Yj9jWG0RH4JQdfUSewyqGxvz7Kh7WH1ISOXZJ5Ue3jVfcA99tV3q0Mcakz7jSgePiabwKrXTEO1VK8W3rEULsTe+nw8f2B6cxreTlVz/FBcbhr8IooTl7y97Az0IspBLsLo+x+QiXPVH28HOxhoz9GzTT4OJ9idy7ZnUvuc7rYGU7wQlAjoNg5Wy7ycTbFoWKWdsfctdQX5MWIxupAGEWSuFAusTeb4dNclnqHQGd5vWyPRNkUieBX7FR0nSPZPHszWc4XraStx9nWW2NRVoetDU26aXKmUOZAKsfRbIFqpy/cqzrZFAuzSQsz2WOZxdqmydmOQj6aLnZL1iGHnXVakA1aiAVBb5eQK22dE2mLkE9nyt2+bNRlZ60WYEM8yLzQ02NPQ5Umx1IlzhbrDI4Uug7riT4Xq+N+1sb9zAioT8d6GiYXszWLkEfLjNRa3cdmBFXWJPysSniZ4n+2f1xq6gymqpwYrTCYrFLobKWSgbkRN8sTXlYkvEwJOD+z95yt65xNVjk9WuN8qsbafi//y5L4H/Nn9kdhfM55HJ8L4+f9fPFlnXdeqvNT1yU+cN7EQDDFCNLX9nNCGaaFwYDpZ5Ye5bg8TJkWfpxs0AcYEmXOS1ZAx0rRQ5/hYx8PKdDEjcIOMQlhwm7xgDo6QZy8Kk22MqSN+9Qx8GHnNdtkvMLBe+37DIuqVY5WelljS3CslWJ/exgDQVBy8FXHJCbIPt6vDzHYtkrdfTYP33BNotfm5sPaIw51Mq9DspPXPRNY7bSI94PqI3KGRZ7LXBG+6p1AWHbwfnmYvZVRGsKwtjp5NF719ROS7Rw0c7w1fI+iYZWVl7hDvBroY6ka4nQ1z+7CKKcqeQQCt6ywNaDxcqiHAYebo6UsH+dTDJbzmHQStwJRdobjzHP7udeo8Ukuzd5cmmzbIpY+p8qOiMbWcIyo3cGdeo192Qz7slkynT6y5nCwNRpleyTGgKpapehcgQPZHCc7xi6AOT4vW2IRNkbDBO12q/daKPNpOs/RbJ5SR8XGnHY2aWE2xcJM91pl6JZpMpgtcShd4Fim0C0LR5x21sUsk9bcwBghZxptjqWLHE4WOZ8r0xG79HmcrNMCrNUCzAy4u9cbpuByvtopV5d5VLX+v9jtNmZ2CHlN3E//780gZxttTiYrnEiWOZOqUjeeLlevjPtYEfcSdj1tBDNMwbV8ndPJKqdGK9zI13lMcCGnwoqEl+UJL0s1z2fOLjd0kwvpGmdGawyOVrlXanYfCzoV/sO8CK9OC/1Rf29/DMbJeRyfC+Pn/XzxRZ93nTZvu67xK+cV6pJO3PQwtR3mnG2UGjphobKgrXFRSpOVGqgorNX7SYsG5yVrJGmBiDHRDHBIDFOgiYrCC2IiLdNkr3hIC4MgTnZKEymabfYYQ7QxCeHkVdskTBPe1x9QEE0UZF5Q+pkjhTnQHu4Gh0yQvXzVOQnZlPhd4wF39I5hyx7mK64JVA2D39WGuK1bZq3Jio+vuScQt7n5sPqQQ7UUBgK3pLDD08sOTx93WxXeLT3qBobEFRev+PrY7ElwtVFiV2mYM7U8imLDLWRe9Cd42d9LWwh250f5pJjsEvYs1c/LoR42+KIMNet8lE9xoJCmbFhqbJbbxwshjc3BGG3TZF8+w55sqruYwmtT2BSKsi0cY47HR6rTR96bzXC/M/7ksdnYEI6wNRJlvs+HLgSDhSL7MzmO5fJddTrZo7IpEmFzLEyPy4VumpwtlDmYznMkm++WlUMOhfXREJu1CHP8loqt6QYnskWOpAuczJa6LuvHPeQN8RCzO9cKIXhQbXIsVeRousjVwphRarpfZV08wBotyETPmPKstA1OpcscT5Y4lR6bI3baZJbFvKzS/Lw8uxejs8oRLFK9mq9zMlnmZKrC7Y6TGyziXxn3sjLhY37E/VSZGyxn9enRCqeTVc6kqt0bDJskMTeisjQ+po5/P7zkcan7bLLG4GiNS5la96bHLsssiKksSXhYGnczOfjs8z8vxsl5HJ8L4+f9fPFFnbeOyW7Hbf5JvUBeauAXDma2o1yXcpSkJj7hYIEe5zYFRqUqdmRWG30UzBYXOkp5vogxwfRzVIx0esUKm0U/DdPkoBhGx0RDZQsDpEWDA8YjDARxVF60TaBgtPlYH6KBgRuFncoEYpLKntZDbhsd8rWFedHRz8N2jV3NhxTMlmXKcibY4uzlaqvIB7WHlDo/X+PSeEntJ91u8G71IbfbHaOW3cPr3gnMtAfYXx3lo/IIJdMi1uVqhFf9fSRsKh+VRtlTtsacAOa5Arw5YSrTWipHK1k+KoxytePW9tvsbAvE2RFMELDZ2VNIsSef4n7DIqmQYmd7SGN7KE6Pw8nRQo5PcmlOlwuYnV7zcn+IF8IaKwMhGqbBwVyOvdkMl8rW51YkiVXBEFsiEVYGrbnlc8US+9NZDufyT5SiXWyKhNkcizDJrf5BQg477KyLBtkYs1YrypJEsaVzLFPgSLrAYK7cnfPtUZ2s14KsjQWZ1SFkUwguF6ocTRU5li511a4swbyQl3VagDVagLg6ZpR6WG1yPFniRLrMxexYZGbUZWd13M8qzc+iyFgfOBbzceNhnlPJMqdSFU4/YeZSJIkFUQ8r4l5Wxn30e59W1Q3d5GLGmjseTD2tbuNuO8viXpbHPSzSPHh+r3cshOBhuc3ZZJUzSatU/fh9AaYGXSxNuFka9zAvpn6hu5s/C+PkPI7PhfHzfr74vOdtIvjUfp8fqxd4JJdxYGN2O8oDSuQ7yniBrjEkKgxLFWxILDN6qJo6lyRLxc4VUXpMLydFkhItVBTWiz6qps4xMWqlbuFltZTggVHhpGkp7AHJyyapjyGjykHD6mFHJRc7lQkIU2J3a4iMaCADG+w9LLXFONfK8WnTWr3olezsdPUzQwlwqJ7icKd07ZPsvOTuZ7EjzIl6lj21YSqmbpG1GuNlbz+ldpsPK8Ocb1izzn7Zzgu+HrZ7EtxqVthVHOFSo2g9ZrPzgi/BDn+CkmFwsJVj1+gjmqaBhMQyb4gdwQRLPEFOlQvszac41SlbK5LEGn+EF0IaS7xBLlRK7M2lOVzIUjetL/oZbi/bwxqbQlHsssSxfJ792SyDpYK11hCY7/OzLRplfSiMarNxvlji00yOw7n8U47ox4Q83eOmLQRn8iUOZfIcyxaeIeRNWpi5fouQU40WxzIFDqcKXChUMDtf9ZO9KutiQdbFgkz2dtzbusFgtszRVJET6VK3FO6yySyL+lijBVgZ9eN3WB7ilmFyMVflRLrMiVSJ4erTfeBVmlWunuIb6wM/VsenUxUuFBtcTJa6z9FUOyviPlZoXhbGPLifcGWbQnC32OR00uobX8rWuu5yhyyxMOZhecLLsriHfq/jmd7x477xmWSNs8kamXq7+1jCY2dx3MPiuJvFmpug61mPtCkEdwstLqXqTA87mRNTn7nm34pxch7H58L4eT9f/FvPWyA4bn/Ej1znuWOz9hnP0MNkzAYZuYYDG3P1GKOiyohk9XwXG3EapsFlyUrami0iRE03gyJFDR0fdlaJHvJmi9PCIuDJ+FlIjOtGnqvCKhfPkoIskmJc14ucNS2CnyT72GjrJak32Nd+RAsTFza2O/row8vB5ihXdOv5E2xeXnYNgICPa8Pc7pS0pyg+XnH340Tho+owF5oW8QZlBzu9fSx1RjhZy7K7PNxVyQtcIV729hJXXOwtp9hXTlI1LbJb4g7xkr+XKQ4vB0pp9hSTjLTqKIqNqGRnRzDBtkCc0VaTPfkUh4oZah3Cna56eTGksSkQZbTVZF8+w/58hnz7cY/YyZZQjK3hGD1OFycKFiGfKOa7ZDLN42FTOMKWSISw3cH5YomD2TyHsrkxR7TdzvpIiM2xCHN9XhqGyel8kUOZPCeyxa5JLOK0sy4aYmMsxFy/Fwm4W21wNF3gaKbAzdJYCXpWwMO6mKWQ+93WnG+q0eJEusTxdJGz2Ur3M4adCqtjAVZrARaHvV31mG20Odkh4zOZCvXOZihVkVkS9bJS87Mi5iPyRB84VW9zOmkp4zPpSrcK4LQrzAo4WaFZveOJvqcNWZl6mzOpKmeSVQZTY0YugKkBF0vjHpZqHuZF3c+o21LT4HyqxrnOfw+eUNZ+h43FcQ+LNDdLE256PmNMyhSCO/km55N1zqfqXErVKXfGrFb2evjfNvc985x/K8bJeRyfC+Pn/Xzxrz1vgeCMMso/que5brNIdpoepiyaJKUaNmRmGREyZoOkVEUCFhgaddPkhpQDYLoIETbdnBUpWpgEcbJEaIwada7QuYYg00SQ82aGYWF98a+QNAYkH6f1NPdNK+1qoRxhvhzhajvPoGF9nrikss3RhzDh48YwGdPqN650xFhl17jTqrC3MUJN6N3S9XpnnDvNMrtrIxRNiwAXO8Ps8PRimhIfVYY593sqeZ0a41qjzEelEe62rF5vRHHyoj/BJo/GjUaFjwtJLtSsmwKnbGOdL8obk6dgFtvsK6bZl0+Taltf6DG7g61Bja0hDTsSe/Np9uUyPGpaPVGfTWFDKMrWcJQZqpezpRIHclmOFnJdEp2gqmwOR9gUidDjdP2LhLwpGmae30etM4d8KJPn1BNzyAmXg/WxEGsjVl9YAJcLFY6kCxzNFBmtj21SWhjysTYWZHU0QMzlwBSCG6Uax1IlTqRL3C6P9XUneV2s1gKs0fzM8FuGLsMUXCnUOJUuczJV5nZp7Ppej4OVmp9Vmo95obFy9WNn9eNS9eNEL4CE28Eyzcsyzcv2WQlqxbGbh2rbsIxYqSpnU1Xul8cINexSWKp5WBa3xpxCv6dua22Ti2mLiM8ma9wpNLtpYC6bzLyYyuL4H+4bG6bgVr7JhWSdC6kaF1N1qm2z+3jCY2dhXGVB3M3qPg8+5/hWqj+IcbJ4vhg/7+eLf815X1RS/Mh1ngtKCoFgkhGkarbJSHUkJKYZIUpmi6RUQwLmGFGqps49ySopzhBhvKaDCyKDjiCCizkiwj2jzBAW2S4gQky4OW2kKNJGQWKN3IPbtHPMSFIULWxIrLbFSeDheDvFQ9Mixnm2EEuUGEOtKodaSXRMVMnGdmcfCdnN8UaaCy2LYCOyix3uXmKSypF6itONLALwyXZe9PQyzx7kTCPP/kqS8hMqeae3Fwcy+8pJjlezGAirj+uJst0Xxy5s7C2lOFzO0Oyo4AXuINuDcRaoAU6U8xyu57mQtz6HKtvYEIiyLRSjx+7icDHH/lymO4/skGXWBMJsCcVY6PVzqVLh01yWo/lcd9FEj9PJpkiETeEo/U4n50plDmXzHH2iZP2YkDdGw8z3+8i12hzLFjiaLXCuUO4akya4XayLhlgfCzHVo1I3TAZzJY5nihzPFLuvpyo2Vkb8rI4GWRHx47Ur1HSDM9kyx9MWIT8OBFFkiUVhL6tiflbG/CQ68825ZptTqTKn0mUGM0/0gWWJeWEPqzQfK7Uxd7UQgnvlJmfSVv/3fKZKq9PPdsgyC6Melmtelse99HnGSs7BsIdDN9IddVzh2hMzx06bzIKomyWah6VxD5P8T6vqum5yJVPnfMrqGV/LNjA7ZKzIEnMiKovjbhZpbmaGVey2p8m4ZZjcyDW5mKxzMVXnUrrerQIA9HjtLNBUFsXdzI+rxD3PZnV/URgn53F8Loyf9/PFH3Pe121ZfqSe57QygkDQZ/hpmAa5DilPMYIURYsM1srDGUaEstliWLJIc6YIYzcVrogsJhDHzSQzwE2zSI4GMhJL0bALmUEjQ7Nj6FopxWmaJieNlBXqgZ21th6EgCPtUSpCR0FinT1BHDenW5luiXrA5mGjs8faQVwfofBYDTsirHbGSLebfFIbId/5+RxHgK3uHnRTsKcyyq2W9TpBm4MXvD3McwS52Ciwp5SkYFjPmeLw8oI/wXSnj1OVPHuLSdIdFdzjUNkW0Fjni3KrXmVfPs3ZSsEaf7LbWOTysy2kMVv1crJU4NN8louVEgJrhnixL8DWUIyV/hDXqlUO5rIceYKQow4HG8JhNoejTHKpnC4WOZzNczw/Nl8ccthZFw6xIRpmgd/Ho3qTI5k8R7IFrpXGErOmet2sjwZZFw0x0aOSarS6ZHw2X+oSd9hpZ000yOpYgEUhHw5Z5mG1wYl0iZOZMhfyle61QYfCypifVTE/SyI+3IrtKXV8Kl3m1hMuaU21szzmY4XmY1HE2+0D55s6Z9OWMh5MVck1x3q4E30ulmlelmte5kfGSs6mENwpNjmbqnIuVeVqsUm5s+xCBmaFVRZrHpZoHmaHVexPlKobHTI+l6pxIV3jeraB3qEtGYlZERcLNTeL427mRNXuessnn3810+Biqs75ZI2rmUa3EgHQ73MwX1NZoKksiKton0HGQgiGy22CLgWP44sziY2T8zg+F8bP+/niXzrva7YMP3Vd5IR9GIEgblhJUkXJIqBJRpC8aFKkiYzE5KdIWmKGCNEyBHexlHM/XjTTwzUzTw0dl7CxQIpSNw0umlY5O4bKXClM0mhw1bTUZb/kZb4cZlSvc7ZTug5KDtYpCdomHG6OUu2UqFc5Ykyx+bneLHG6lUV0jF9b1R6ikotTjWy3l+yVFbaoPUy2e7lYL3KolqItTGQkVrgjbHBrlHWdfZUk1zvZ2D5ZYbMvzip3hHuNGntLKW43OhuXZBsb/TE2+zWqus7+YobjpRztztfeLLePzcEoL04Y4NDQCPtzGc5ViphCICEx3+tnUyjCSn+Ie/UGBzsl67L+NCFvCEV1jAGxAAAgAElEQVSYqKqcyhc5lM1zslDoJnBpTgfrImHWRULM9nq4WalxNFvgSKbAUG1skcP8gI+10SBrIkFiTgc3yzWOdQj5dnmsBDzV52ZlJMDqWIAZPje6KTifr3AyU+JkusTwEyEd0/wqK6J+Vj9Rrk7WWpzKlDmdLnM2U6HWUY2KLDE/7GF5zMfymI+JXkuxNg2Ty7kag6kKg+nqU2NOAYfC0pg1N7w45u1uhBJCMFRucS5tlanPp2td8xrAtIiHuUEnSzUP82NuvE+4qh+T8fl0jQupOtey9afIeHrYxUJNZaHmZl7Ujdv+bM/5cnpMFd/MNrvPl4ApQSfzOkQ8P6YSUp81gTV0kxuZJldSDS6nG1xJNSg1DVYNePhPW3s+60/z34Rxch7H58L4eT9ffNZ5X7al+ZnrIqfsllIOmyptU1DB+iLuN/zkzAY1SceGxEQzQM5sUqCJDYkpZpCS2SaJ9cU6lQBOQ+G6KGAgCOBguggxatZ4KCwFN10KEBcebhpFksJ63gI5QhSVy+0cSWERyyxbkOlygPutKhd0i9BDspP1jjjClDjSSJEzO4la9gDLHFEKeouD9VS3PL3QGWKVK0ZJb7O/mmK0szO5z+7mBU8PAdnBiWqWk52ytYzEUneITV4Nw4QDpTTnqtbSBpsksdwbZotfQ0XhcCnL4VKGakfhDjhVtgZjrPCFud+o8Wk+y7l6iUan5DvL42NTKMpqf4j79TqH8jmOF/KfScgJh5Pj+QJHc3nOFMcUba/qYn04xPpIiImqyrlimWPZAseyBfKd93HIEsvDAdZGg6wMB1EkibP5MicyRU5mi2Q7ilSRJRaFfKyKBlgVCRBXnYzWm5zKlDmZKXE2W+neCKiKzNKIj5UxP8sifqIuOw3D5Hy2wul0hdOZMg8rY/3cHreDZTEfy2Lerjo2heBmocHZdIUz6SqXcrXu6JUiScyPeFiqeVmmeZjsd3V7uKPVFufSNc6lLXWcbYyZuDTVzmLNw6KYm0Wah9kTwt3f8Vrb5FLG6vVeSNe4kXtaGU8LOVmouS0yjqnPjEclK+0uEV9K17lfHLs5sUkS08JOFmoq8zWVuTH1M3vG6arOlQ4JX041uJVtdsfBABJeO3M0F6/M8DM/Me7W/oMYJ4vni/Hzfr548rwvKil+4rrIWWUUgSBkqrRMgyrWKsIew0tWNGhhYkemx/CREjUaGCjITDD9ZMwmJVpIwFQRpG0I7mO9fhw3PcLDHaNEiTYyME+KoJg2Lho52pg4sbFIjoCQONPO0sbEgcwKRcMpbAy2st0S9TwlxGSbj6FWjXNti6g9ksI6V5yg5OBsI8+NlqXaQ7KDTe4EfsnBmXqOiw3LpOWSbGzwaMyw+7nbrHCwkqbccVtPdXrZ7NUIyU5OV/IcKWdoCYs45qh+Ngc04oqL0+UCB4uZ7iKJqN3BlmCMlb4wI40Gh4rWWNNjEpgTCrJaDbDCH+JBvcGRfI4TxXzX1BV1OFgfCrMhHCFoUziWL3Akl+dKudKNoJzicbM2HGJdJERQUTiZL3E0U2AwX6TVIW2/XWFVJMDaSJAlIT/ZZpsT2RInMkUuPNFn9tsVVkYDrI4GWBr2W7Ge+QqnMmVOZUoMVccIdoLXyYqo1TueG/RgkyTulBoMZioMZspcyle7udUuRWZR2MuymJdlMR99HidCCB5VW5xNVzmTrnA+U31K5U71u1gS87Io5mFBxINLsZRqstbmQrrKuXSNC+kqo7Wx8nbQqXSJeHHMQ4/HPhZS0jIYasPBm1kupGrcyje7PeMnyXhBzCLjJ5O8nhxrutwh43Rt7CbApcjMjrqYH1OZp6nMirhQf09Ztw3BrZyliq+mG1xJN0hXx15DkS1Cn6O5mKu5mKO5iLq/nDUU4+Q8js+F8fN+vojGvOzN3+afXBe4oKQwEQRMJ3VTR8cqt0YNN1lhGWEc2IgZbkZEDROBC4WE6WHErNHskPZE4SdrNMnTBAGTJT9O08ZNs4gBuFGYQZCi2e7mXSckN5MlH0m9wZ3uz1Rm2kJk2w0udcagfJKd5Y4YsilxqpntOqvn2IPMUAJk9AYnGtlueXqZK8I0u5/hZp2j9QwtYRHBIleIJa4wVcPgYCXNSNtSz2Gbgy2+OP2Kmxv1CofKGcqdAJE+h8oWv8YEh5urtQoHixkyndEmv6Kw3h9lpS9Eod3mcCHHmfIYIU9RPWwIRljqC1J2Srx37xGni4VuP7LH6WR9OMzaYBgbkkXI2Tz3atbnkiSY5/OxJhxiTThI0xQczxY4ni1wtVztkvYEt4vVkSCrI0GmeVUuF6ucyBQ5kS3xqDbmZn5crl4Z9TPT52ak3uqS8fl8hZYx5kBeFPGyrKOQE6qTdL3NYKbMmUyFM5kKxdYTo0d+V0cd+5gTtPrA6Xqb85kqZ9NVzmUqpJ6Y/Y2rDpbErDL14piHYGejU7re5nyqyvlMjfPpWneVI1gbp+bH3CyKWer4SRNXtq5zMV3jYrrOpXSNu8UWNkW21gRLEjPCLhZ0yHhuVH2qTF1rm1zLNLpEfDXTeMq8FXDamBezVPE8TWVqyNldrvEYmZrO1VSjq4xv5prdmxWAgMvG7JhFxHNjLmZEnTiVZ/vKtbaJS5G+0JSwcXIex+fC+Hk/HwgEg8oI74Suc6o9jIFJwHRRNdsIQEIiZLjIigYSEk5s+AwXaWGZvrw48BtOhkUVkHCjoJluhs0aLUwUITMJPxVTZ7QzChVHJYqb+0aFimgjAbPkEE5T4bpeoI6BDMyxhfAJB1daBYqiE2epBOmV3Txq1bmuW+EePsnOcmcURcgMNnJkOxnXA4qHpc4wuik4XsuS6fy8V3Gz1t25vpbnRmcto0OSWeeJMsPpZ7TZ5GA5TU63yCCsONjojzHZ4WGoUedgKUuyZb2e12ZjrT/KMl+Qmm5wuJDj7BOEPFX1sCEUYa7Hz/1anSP5POfLRSSbjK6bTFRV1oXCrAoGKbZ0TuSLHMsXyDSt97bLMkuDftaEQywO+LlfrXMiV+RkrkiyYV0jSzAv4GV1JMiqsLU56lS2yMlsiXP5cjcu02WTWRz2szISYEXEbwWR5MoMZsuczj694GGS18XyqI9lUT/zgh50IbiQrTKYqXAmU+bBE6XqiMvOkqiXpVEvS6JeQk47pZbOuUzV6gFnqk+Vtn12GwujHpbEvCyJeejtuKqT1RYXOkR8IfM0GXsUmfkdIl4U8zC5E40phGC40raIOGP1jJ98nl2WmR1xsXZKiMmqzOyI2lXiQghStU55OWPNF9/JNxmjYsu8NU9TmRtzMS+m0uezP+XkbuomN7NNrqabXE03uJZ5WhXLksSUsIM5MRezYy7mxFz0+JRngktahuBWpsn1dJPrmRbX000eFttsnOzhb7dqz/zt/lsxTs7j+FwYP+8vFyaCg/YH/MJ1mdu2PEIBtaVQFTo2ISEh4TUcFIRl8nILO3bTRkG0kJAICieSKZMXTSQgJFyows6waRGwWyjE8TBq1KhjIHWUM6bEXbOMADwoTJb8lA29O68ckhxMkwOUdL1Lvl7JzjwlhGHChVaeprASteY7gmiSylCrxvW2Vbb2SAorXFE8kp0r9SJ32tbrumWFNWqUsM3JjXqZC/UiZqePvMQdYq4zQMUwOFrOMtJ6PE9sZ50vwlSn9/9j7816ZNvScr1njDG76LvM1fftbtZuqtlVVME5xxLHOrItbCFKWMLixpYvStz6CiTkC+w/wT+wVPaxDIIDByiMQGWqatfuV9/3KzP6dnZj+OKbERmxcu06wN7UKSCHFMrIzIiZkXPlime+7/d+3+BZHPPXo95q56eSNny73ubdapNplvODYY+PJqPVRKzzpQr/qtnhQqnCndmcv+73uD7dS0ZfrFT4r04d4xw+T+YJf9Pr8+PBaLXZQs3z+EarwbfaLc6WS3w0mPD/9Qa83x+t7OqKZ3ivXeeb7SZfada4P13ww+6IH3ZH3J+u9QeXQ95rizp+q1nl7njBj7pjfrw75upwyjJEXPY0X+3UeG+rzntbNZqBx9X+jJ90p7y/O+b6YL6qiYZG806nUgBZglzTzPLx7pQPuzM+2Jlwe7Sn0EvG8FanzFe2xXI+W49QwLNpyoe7YlF/vDvbsKnLnuatrTLvbFd4Z7vMhWa06oW+M4j5ZFdU8Se7c3prteaKb7iyVRJ1u13mUivCN4rt7RpPno243Y/5dGfOZ7tzPttZsDvftJcvtUOuFBb1G1slGtGexe2c4/Eo5dqugPjqzoI7vWSjVtyMDK9tiyJ+41DExU64z+bOreN+P+V6AeNrOzH3eglr4pqyr7m4FfCrb9b5xTMVvqx1AOeD9YXWwfn+x1kJOX8S3OH/iD7jqZ6QqpxaHjI3OaRSf/OtYWFzHNBwIYm1xC7HAh1XYmYz4qLmesiVWeSWEQk4RYeI0Bme2BkKRQmP41TYyWOGTtTMMVWh5nweZNMVuC+YBiXncSsdMSss5wtenTYh95MZz63A5rApcclrMMtyPkr6pM7KWMqwxVFd4mmy4ON4iMNhUHyt1OaoV+JFEvOjmTwe4I2ozpWoKXsIT/o8iOWiItKGb1c7nAkr9JKUvxn1VsNBStrwzXqLt8oNJlnGD4Z9rk73/kZfr9T4dqPNkSDi5nTKX/f7PF7sJaPfqdX5drPFqajMzemMD2dTfrzTXwH9WCni260m32g1UcD7/TF/2xtwe7IH2lPliF/oNPlmu0Hb9/nJYMwPX1LHgdG826zxja06X2/XMUrx4wLGP+nt9RFrBZcbZb7eqfO1rRqXaiXuT2Le7074YHfCR73pKvSlFVxqlPlKoY5fb5ZJrOOT7oyPdqd8sDvl9nCv99fXmjfbAuN3tipcbpYwCu6PEwliFUDeXYNqzTdc2SrzznaZt7fKnC9gPEst17pzgfGuJKnXbeZW5PHWVom3D5W5slXaGPrRm2dc3V3w2c6cu9OcDx6NN1qampHhza0Sb2xHvLld4mI73Jj+NVjkXNtZcH03Xn1cTu4CgfnFTsjr2xGvbYe8vhVxuLqpiq1zPByk3NiNub6TcHM35lY3WZUMAHyjON8OuLwd8tp2yKXtgBMN/0vf9AIO4HywvuA6ON9f7pqS8gfhTb4XXaWv5sQqp5IHzFyG5zSR55PEOc4hSWobMXYp2ikc0LZR0QusUEDHluhZsf+UgyNUGNuUsUvBwbYqEVqPx4WS9tGcUlWmec6zArR15XOCKoM84UkuX2uqgLOmziTPuJWOcThCZXjda+KjubYYMnbyhn7CK3POrzHPLB8s9sD7WljnjF9lnGa8P++vZk+fCsq8U2qhLHw4HXE/FiXrK803qm1OB2VGWcYPRv1VDbmsDd+qtzkfVRlnKX87HKx2fNJK2p6+WW9R0R5XJxN+MBgwSEX9hVrzXqPJN5pNKsrw0WjC3/YHPF3sbWF4qVTiW+0Wr1erPJkt+FF/xI/7IybZ3iCOd5s1vtlu8HajxvN5wo96I37cG2/Ujo+XI77RqfNep87ZSomrwxnvd8e83x1vtDkdLvkrGL/TqjBIcj7sTvlJd8KH3QmjNfCcrkW8W6jjt9syqvPT3owPCxjfGqwN4lCK11tl3t6q8O5WmdfbZTyluDVYFACX3ZfWj18PDG9vlXl7u8LbW+WVTb0zS/l0V5Ttp7vzjfAWwKl6KMq4UMdHiuBXmoui/qyoE1/dXfBsuqfEA99wsuLxxrZY1G9ulzhc2QNpnFlu9RKuFdb0tZ2YZ5O95wMcrfm8thXx+rYA+Vw72IC5dY4no4wbuzE3dmJu7ibc7MbM073XrxWcbQVc3BIYX94OOdMK9g0ucc6xM81pRPqV9eh/6DqA88H6QuvgfH85q6/m/J/hdf6f8AYTlZCQE1hDbsEBkfNY2JzIeCyynJoNGNsMD41GUbI+Y5uiUQQYStanb2OM0wQYGi5kx84BhXZwRFUY5SkTl4GDtoqoOJ8n+Ywch3Iy01pbzYN0Qg7SdmXqGKe5k4xJiorfGa9Ki5An6ZznuYCoqQMu+XWcg6vzkfwc4LhX5mJQI7GOj2YDJkXS+rAX8Vapge8Mn05HPEiKiwWl+XqlxfGgzCjN+OG4T79IWVeN4Vv1Dsf8iF6a8bfD3qq+7CnN1+oN3q40wMHH4zE/Hu2Numz6Pt9sNLlSrRHnjveHI94fDFfbLpaN4WvNBt9oNTizVedvHuzyw96QW5O9nuJDUcB7rTpfbzVo+h6fDKb8sDfis+HecI+SZ3i3VeO9tljVgyTjxwWMb43mK6u65GneaVf5WqfG1zs1DIoPelM+7E74SXeyYQdvRT5fKWrG73aqhFrzSVds6o9eUsaeUlxulXhnS5TxG60yADf6cz7pzvloZ8pnvU2Fu13yeXtL+oTf2ipzqhZgHdwZxHxagPiz7pwXa9b2Mrx1ZbvElS0Jb9VDI+CaiSq+1hV7+UZvc9BHPTC8viU13te3SvzS5S2mxfjO3DruDRKu7cTc6IoivttPVi4GQD00XN4KeW074rWtiMtb4YbFbZ3j8TDj5m7Mjd1Xg1gBp5o+l7ZDLm+FXNwKON8J9sE2yx0PBil3ugk3dxJudRPu7CZMEssvni3zv/67g5rz564DWPxs18H5/mLrrh7wvegqfxbcIyYjw4JVeFaTKEvZ+ixsju+MQNr4LOIMB5SdT2wtOEWGo+VC5taSOYt10CIksY55AeCqCihZjx0roTHtFEdUmXGeMnLSftXAp03E82yxsq23dUSbiGfpYmV5t3XICV1hmKfcT0WhBkpzyW8QoLm9mDAs+pTbJuBiUMdZAfWy9WnLhLxZamCs4uZ8wsOihuwrzVcqTQ57EcM048eTwaoPue55vFdtseWFPI9jfjwarPZMrhiP9+pNzkYV5pnl/dGQG2v149OlEr/QbHHYD9iJU340GHFzsvf946WIX2g1uVStME1zPhiM+clgxBxHlloZU1mv8o12g/OVMs/nMT/pT/hJf8wgkd9VKcWFWomvt+t8tVXDV4aPBxM+6E34eC1VbRS80azwlU6Nr3ZqtAOPT/szPuhO+LA75dmaim6GHu92qrzTqfCVTpWK0Xzcm/NRd8rHu1PujPbmRS9h/HangHG7TJJbPu1KCOuT7oyb/b1eYYCTtZC3OiXeKmB8uBIwinM+64oqvtpdcK07X124ADRCjzc6EW9ulXhzq8SldkRgNLPUcrO3WCnia7uLjQsLDZxthbyxFfHGVonXtqJVcEvUbMqzVPO3twdc311wq5eQrP1c3ygutkMub4k9/drWZmhraU3f6ibc2I259TkgPtHwubQVcHEr5NJWyPmtYN/AklliudNLuLObcmtXQHyvl2ykuRWKYw2PC1sB//XrVb564qDP+XPXASx+tuvgfP/91zJ5/b3oGj/ynpIgdePcOgJrSLEC41xUc+AMiZWvWQ+i1GNqM/kcR82GjGyK5zQOR92FDG2CRuOco03E2GZiJztoqJDQGV7kcxQaDRylzNxaunmMQhFhOGbKTLKc59kcpRSRMpwyVRLruB9PcEre6M56VarK53Eyp1uMyqxpnwtBFe00t+Z7oG4an9fCBsYpbs+nPEtFaftK8065SdsL6CYpH02Gq0ldh/yQd6sNysrj8WLOB5PRavDFlh/yXl2etxun/Gg0oFuA0ijZevHtap1AaW5NZvx4MGKcFTOkleKtRo2vNhrUjeHBLOZH/SH3p3s29KEo4L84sc05L8A4xcfDCe/3xjxas6rboc/X2nW+3q6xFYbcGc95vzvmo96E6ZoiPV2N+FoB48ORz63Rgg+6Ez7qTjfS1zXf8HanwrsdUcaRVnzam/Nxd8bH3elG+trXmtcLZfx2p8zlZonuIuPT7pxPuzM+6c55uLZRhFGKC82IK51C4XbKNELDvWHMZ7uLFZAfT/ZeD8DpwqJ+o7gdr/o44N4g4XpXVPG13QX3BpsJ6k7J47WOKNrXtyIutiPKvvxdPp9kXO+Kmr3Rjbm5u2CaWjzPkGU5WinOtgIudfZgfLoZrNqh0tzxYJAUSjjh1m7M7V5CnG2C+GTT5+JWyMVO8EoQL23p27sJd7oJt3YTbndTno42rXJPK852Ai50As5v+VzYCjjbDih/iSM719cBnA/WF1oH5/vvvhJy/jy4x/fCq9wzA6Yqw3OKrIByhgMLvvVIyCk5Uc2B8yQ4ZQ0YRZ46fKexFpwTxVHGx1pH4hw4CDEEzjCyKcaJ9d0iZGAlaeqco1lA+nm2KCrUcEyXsVbxPJ0X8FWcMGW00zxKZsVlBBwzZRoqYDeL2cnkzT9ShnN+FeM09+LpSiE3jM/5oIq2irvz2QrgJW14o1SnpnxeJDHXZpPVG/vpsMSFUhXPKW7NZqv6McCZUpkr5TqBMtybzfhoPF4pwbrn8fVGgyNBRJxbPh5OuLGmjrfDgPeaDU6VSiS546PhmA8H4809gJs1vtKs0/R9nkwXXF3E/OT5YGWlRkbzTqvGu60ap8qR9Pj2xX4erPUQHy0HvNuu8pV2jePlkPvjmA97+5Vx1TdcaVd4p13h7XYFTyk+68/5pIDxep9xZDSvt8orGJ+th9wbJXzanfFpd85n3RnDtXpxydO80RYQX+nIZg9Jbgs1LDB+ObhV9gyvdUTZvt6JeL1TouprXkwzrnUXXC9uN3oxi7XnBUZxuS0gXsJ4u+wX1nbOzd0F17ux2MvdmFG89zoBTtQFnl8/2+Bo4LjQCVetVPNUVOztrijYW92Yu710VT4AqRGfaQk8L26FnO+INb0O4iRz3O8LfO925Xh3uinjl15LLTSc3/JXxzi/FXCq6eO9vFFG5njYT7nfS7lwKOBU68vbCOMAzgfrC62D8/2fXkO14A/Cm/z78AY9NWeiEjyr0VbLSEmrSZ0jsoYEh7EKbTUZblVrDp0n2zWaiEGcEDhDjqPifCY2xXcC94YLV7XnzLmVtb1wkrYOMDQI6OcCaYujrUJC5/E8XYAStb6tI0rO41k6Jy2A3NYhbR3Sy5JVX3GgNKf8CsZpHi1mTAsrvGF8zvgVnFPcne2Bumo8LkU1AgyPFwsexnsJ54ulCseDElkOV6djukXYy1OKK9U6x/wSmXVcnUx4uFgb0FEu80a1RqgMz+cxHwzHK3VslOJKvcYbtSqh0jycLvhgOF6NvwQ4WynxtVado1HIJLF8Mpzw8WC8snED33CuHPHVVp3TlUhGSg6mfNibsLvYO04r9Phqu8Y77QpHSiFPpykf9SZ80pvxfL4fxu92pAac5/BZb84nvRmf9maM1gBf9z2udMq81SnzVqdCO/S43p+vQHxjsNgA1HbJ581OiTc6YlGfqATcH8dS7+3O+Wx3sdFbDNIf/EZnTxWfroutfaMXc31XasTXugsGiz2AaeB0M+RyJ+JyJ+S1TsSZZohR8GIqQaubvZhbXQHxcLEJv6NVn0tbIRcLVXyhE6ymfQXVEj+43uPmbryC8eNRytqviaelJ/ni1h6Mz7YDggKezjm6s5w7XakP3ykg/HCQbtSrAY41BMIXtgLOtX3ObwVsVcxmkttKgOxuN+VuN+VeN+VeL+XxIFu9rvdORfzv/+02X9Y6gPPB+kLr4Hx//rplevz78Dp/HtxjRspMpSirCHOPWFmM1RircU4UamYtofWLMJiHtdIyhVNgFcoptNGoTIIpBk3uLBEeuYXcOZRTGBSR8xgXVneOWNvTPCusYkWApkFAL5NYl0NS2VXls5vGK0u5ojw6OmKYpQyyBKUUvtIc98poq3iczFftWk3jc8wrk+aOe/PpCuotL+BkUEZZxb35jGFRI/aV4rVyjYb2GWcZV6eT1ZaCdc/njUqNqvLoJxmfTsYsiu+FWvN2rc4hPyS1juvjKfdnazsmhQHvNuq0PJ9ZJrC9u9ZP3Aw8vtKscbpcAqu4NZnxYX/CON2D4qlKxLutGmcqJarVEj982OWj/oTnayq2HhjeaVV5q1VlK/TpzlM+7s/4qDdlEGcbj7tSqOKL9RLT1HK1N+fT3oyr/fnKogeZM/1Wp8KVTpnXWyXSzHGtv+Cz7oyrvflGf7EGLrRKvNEuCVzbJZxTXO3NxWbuzrnZjzeOX/VFFb/ekfGVr7VLaAU3e7Go4UIRP59uWrqHKz6XOwLj1zoRF9oRJU/xbJJxsxtv3F5WxIcrha3clsTzxXZIPZI53c/HGbe6CbcLVXy7G9OPHdm6kve1WMnF7UIn4HRrz95epJb7/XQF4Lu9hLvddN/rKPmas20B8dlOwLmOv8+WttbxYpKv4HuvJyB+0M82as0AlUBs7jMdjzNtn2+fK7Fd/fJGeR7A+WB9oXVwvjdXhuWv/Af83+F1PvF2mKmUzFmcEygnyoKFKPeIVY6xBm3VGqAhsh4xlsh5JNau6tCR9cg06EzaqCLnMS9s7wxL1fmMbYaPJnOyZWNmHbGVIR7KQVOFjPKU3DpQMkmsoXz6WUrmJFZUUoa2ChlnGaM8RSkB/lGvBE7xNF6s7O2mCdg2IYvM8mghVjjAYT9i2wtll6v5bAX7mvE4F1Xw0DxfxDxaU84noxInghIKxYPpnEfxXq30RBRxvlwhRPNikfLpeLKCTqA1b9drHA1DlIO70wVXx9OVovS14u1GlXOVMr7SPJvFfDSYriZ7AWxHAV9p1ThZjtAo7o4XfFzA2PM1WWqlFtyucqVZoe57dOcZn/VnfNrfnDfdjjzebld5q1XmSDlksMi42pca8L3xXnhLoThXD3mzU+FKu8zxSsDuPOPT7oyr3TnX+/PVIBOQWvQbhSp+s1PiWCXg7lCger234FpvwTBeD18pzjZD3uhEvNYp8XqnRCsy3B0UNd6e2MyPxptKuhGaQhFHXGoLkBuR4dEw5VZvD8K3ewmTZBOAR6o+FzshlzrhCsj1yJDkjnu9hDu9IuFcwHiW2o3nt0qGt05UOV6BC52QC52AIzUPrdRKvd7rCYDvdBPu9lKeDLPVOZNiPbwAACAASURBVF2uo3VfQLwVcK4tNeLDVQ+t95T1i0nO/QK+93ty3Af9lEW6eSzfKM60/RWEz3R8znb8fer6y14HcD5YX2gdnG9ZfTXnD8Nb/EF4kxdqylDFKCepa+sAp1BFCjvHYS1E1iemSGJbUE7hnMJZCIq6c+g8YmuJnCEmp+6FjOOMsPi8is/CWozTWOfw0XjWSGAMQ+YsTRUyzTOslTSxcYqGChiuQTpA09QBozRjYfMVkLdMhLWwk8Qry7tjAhrFY3eTePUGdSwoUVM+ozTjabK2u1EQseUFsqnGfMZ8DarnSxVq2mea5tyczVbKOdKay5UqTc9nkVmuj2ervmSAM+US58plAqXpximfDCerjSiUko0mLtXKlJRhkGR8MpjwYrEHoUbg8XazxslShAYeTWM+Gcw2bOqab7jSqvCNE23SaUZ3kXK1P+PqcLahoo6UA660K7zZLFM2hhezlKv9OZ/1Zhs16NBoXmuVuNKucLkZ4WvF/VHCtd6ca69QxWcaEa8Xqvh8I2KW5Nzox2Iz9xY8eSm0daTic7ldkrpvJ+JkLeDxOJUWpG7Mrf6CB8NkA2NlT3OpsKYFxhHNSPNgmHGrG3OrF3O7JyBery8DHK8HXOwEXGiLPX2xE1INtNjJBYjvFCB+ONy0pbWCkw1fwNkJON+RGnGrZNjaqnLjwZC7BXzv9fY+Ji+p11poONv2OdP2OdcJONcJON3yV2p4HcL3e9kKxg/66UaCG8DTcKrlc7oA8Jm2z+m2x9H6HtShUNfjnAf9jIe9jIf9lIf9jG+fK/FrX63yZa0DOB+sL7T+pZ/v66bL/xVe4y+DB4xVLDtCFSo5xqKtIrCGBIsubGwcOFQBaE8AbT2sk/pzjluB3ALaKaxTEuwyGpdK+5RzS6BDhGGW5/gYUmepqYA4tysg48S2HmUZygEFfOsqYJTtQdpD0dYhcW4ZZOlqJvKWFxLh0U2Slb1slKhpD81OkqzanYxSnAhKlJVhmGY8iffqw1t+wNGghLPwZBHTWwPuiSjiSBCinOLZPOHhfO95Ld/nYrVMRXtMs5zroxnDNRv6eCnkYlXgOEst10czns7XZ0R7vNWsciQK0E7zdBbz6WATns1AFO+pSoivNLvzlM/6Mx7OU5JCGSsF52oRb7YrnCyHaBRPpimf9WbcHMw3WpS2In9lT29HAYvUcmOw4Gpvzu3BZjtTPTC83i7xWrvE5VaJyGjuDxNu9KXme3ewOeCj6psCwiVea0ecqgd05zm3emJL3+oJiNdxWvI0F9shF9sRlzohl9oR9VBzry+K+Fahhu8PNsdcaqU43Qy40A640BE1fK4d4hvFg36yB+Ke2NOjxSbES77Uh5cgvtAJOdPyCT3NJLbc7y/hKwB+PLbsvqTmPa041RIb+kxbVPG5zl5t2FrH83EB4X7KgwLEnwfh402fM22PU21RwafbPscbHmYNwvPU8rif8aCf8agA8YOegPhli1srxXe+WuV//lcNvqx1AOeD9YXWv8TzPSPlL4J7/GF4i+umy0jFpIhFraykp5WV8ZopDqwitBLoUk6+njuHdprcOiLrscCuEti+k4CY5zQ46UfOnZPWqcLWTp2j5DzmVrZtjK2lqnwSa3EWNBI2q+IzziUVbpHhHFU8hktIozBK0dABkywjyS1KCfC3vBCsopvsvVFGytDxQtLc8SKOhVbIhK5Dfoi18GwRr7Zq9JTmRBhR0h7jJOPRfLF6TsUYTkclAmUYpxn3pouNmdAXymXqnk+cW+5P5nTXQNoJfC5Uy1SMYZE5bo9nq80lQOZZv9moshUGKAfPZgmfDWcbqeRO5HOlWeFw5INTPJsmfDaYb6hn3yjePdzgbORT9z2ZbjWMudrfVNkaaVF6o13mdDXEU4oXs4xrPbGn1ydueUpxrimq+HIroh54DOYZN/oxN/sLbr1UJw6M5kIz5HI74nI74kQtYJ5abvYSbvUX3OjGPB5vKuLI01xshVwsrOkLrZDAqBWI7/Slvvv0pclagdGcbwecb4ecbwdc7IScbvgMYye13ALCd1+hhgGO1jxRsO2A8wWQD9c8kkyGd9xbg/C9Xrqx8cRynd4qcayqCggHnG37nGhIUjrLZaDIg0KtiiJOeTjISLL9ED7RFPW7VMOnWgLhZeraWsfOJBf4Lm+FGt6d5PteW+gpTrZ9TrU8TrY9TrYE8MebHoH35VrcB3A+WF9o/Us633dMnz8IbvIfg7v09YKRiqX1KfdIyVFOEeTeSiV7ViYkOSfK1beezJh2miCXOrJxmtwVgHaifHOL2NbOEjhD5hyh0yycpeYFTOKUCJ/Y5pSUR5JbdNEuleMoO4+JzQmdJL4DZErYOJN6dA6ESlPC21PSyNV/U4vinqTSZ5o7R9MElJQ8dp6J5e0QNV1ShlGaMUzTlb3d9AI6hY39dLEXLtMKjocRNSNW9cPpYu17ipOliLbvk1t4OovZWUtUN3yPs5USFeMRZzl3x4tVPzOIMr5cK9P0fayDZ9OEG+P5RpL5RCXkUr1EzZMA3cNJzPXhfMOubYYebzbLnCjU8yjOebDI+eT5aEPpNgOP19tlLjQiKp4hTi13R/E+exrgSNlfKeJWaEhzmbZ1owBxvDZkwyjFmUbIa22xmA9XfKnb9yX9fLu/H6hlT4u13BYQn24GWAt3+6Jkb/Vi7vaSjVnTIJO1zheW9BLIrUhzf5CJldwXCN/tp0yTz1fDZ1tBAdEAT8PD4vn3+wLi+/2UZ6P9deGtisfpltjHZwoIn2z6nD7e4MGTIQ/7olQf9AXGD/opTwYZL4lWfKM41RIAny7Aebrtc7S+B+FpbFcAftTPeDTIeNRPedTPNvqiV6+tajjZ8jnRWgJYYLxVMRsWd5I5ng4zng5yzm55HG4cBMI+d/1LgsXPw/rnfr5jMv4yeMAfBjf52HvBWCUsyDBWo61M5jJWo3MBoba6UMx2pZjjFawVqoCxc3vBL89pMlu0TTlLWChn+TwnKurOJSQQZjJJdntOWk/smq0dYUicJVQG7TTzPCdAkzhHVXsop5isIO2IlEcJI3B1CgrV3PYCsNBLMzQCY19pOl5AliO15qI32ijFIT/EIPXfZe3X4ej4AS1PgPt8nqy+B3AkCml7Ps7BziJldw3GVc9wqhxR1oZFZnkwXTBaC101AoF1zXikFh5PFzxcaxHSCs7XShwvhwRas8gsd0bxxnaIIHOpL9ZL1Dwjqn+acG2w2NjzOPQ9Tld8LjdLNAMPUDyfJNwcLLg/2hy6UQ8Ml1uiiJuhh3PwdJJxq7/gZn9zv2GN4nQj4FI74kIzpB35ZLnj3jDhdl8CW/2XWpDqQQHUQhVvlz0mseVePylgHPNwmG7Y0grFsbrPhXbAuZbUdk81AqZxzv1BVgBYQLwz3fx5WsGxur8C8bkCos1I82iYc7+XcH+wCeGXW5UakRHl2hIInynuV0PNYG552BcALz8+mzoedTf/nQDKgVjbp1o+pwo1fLrlc7gmwExzAeXjFXyzFZD7s/0qOPAUJ1veHoQLJXy86W0kuJPM8WSQ8aSf83iQ8bifrz5/Mc5Xe3N/41zI//Zr7X0/5x+6DuB8sL7Q+ud6vu/pAX8U3uZPgju80FNGKsY58HNTqF8l97EoqyVRXbQy+dZgnUBTFbBOivqzv6wpFxZ2VChkz0l4K3JeoZg1qRXreuEsAYbMOkrGJ8nkDcF3msQWqhpLRYnt6hx4aBInVndcWN1GKWJraegAax3TLCdQoswjZShrwyjNpYVLKTJnaRifUBkGidSlZcyi1IBLyjBJLeM0K1SzI9KGbT/EWdiN042Rj03fp+P74KC7SBmswbZsNMdKESWtmaeWR7N447nt0Of48vuZ48F4wXDt+ZHRXKiVaAU+CsUwTrk5XDBbg2HJ01xqlDgUBfhKM00sd0YLHr4E7EMlAfFW5OMphfM9Pnoy5s5ws6c40IqLrRIXmxGt0EMBu7OMW/2Y24NNRaxRnKwHXGxFnG8GVHwjE66GKXf6oohnLwWutsse51uiiE83fErGMJjn3B2IIr7bjzd6j0Hs7HMtUbPn2yHn2gGh0TwdZdzrJ9zrp9zrJzx6hSXdLps9FVzUd7crZi9Q1d+7vUoJ10MjIaplqKot4axqID//0WDPjl5+nMSbvzPAkWbAkeoSxF4BY592WdoOdyYCyUcbKjjj+Sjfd2GgUByuG060vJUKXt5fV8HT2PJ0IMd9Osh53M94MhAI7473v0aArZrmWNPjWNNwvOXxixcjTrb/CSvnNE357d/+bR4/fkySJHz3u9/ll3/5l3/qcw7g/PO7/jmd7ykp3w/u8cfhbT4xO4xUzExleLlGWbGMvdyAg9yBZzVYqeWaYqhI5qTGvB4CW9aOrXM4iwwUccuENQWQ8zUF7bNwOSHyBh5R2OEojNbY1OE5RewcJeWxyC0hEh6zzlHCY5pn0v+MwLqiJEhlnEYrRWItdeNjLUyzHL94vqcUNe0zz3MWWY5RkgIPtaFufJLcMkhyTAFjjaLtBxg0/TgjXtnesjFF2w9QQC9Omay1zZQ9zeEwxEczzXKezeINu/JwFLAVBhgUoyTn0SRm3X1shx7HyxFlo0lyeD5NNnZ1AjheCThRDil7YiXvzFLujDbruSVjuNSMOFQOCJUiyR2Pxgm3h3tw9TwDueVsI+R8M6IRGJRTDBc5twcxd4fJxjE1ijONgAutiONVn0BrkiWIBzEPhi8FrpDpWOdbIedbIe2SAavYmebcHcTc6SU8Gu0fnnGkWijaVsjZlk89NMySorZbQPjBIN0XXir7mjPLcFVLlPB22dCb21WI6uFAIPxisr8m3IiMALiA8OmWTMYyyvFwsKzfynEeDTKeDvdb0UbBsaao1lNNqduebHmcaPqcOV7n+v3hSgE/7mcrGD8Z7g9jATTLhhNNUb1L+B4vPg88CTUOZpYng5ynBXSfrH0czvYDWCnYrhmONgXuR5uG402PYy3D0Yah9FJ/9Lrd/WWsnzmcv/e973Ht2jV+53d+h36/z6/+6q/y/e9//6c+5wDOP7/rn/r5djg+MTv8cXib7wf36Ko5I5XgnAA3tw7tFMYKOI0zBYQFvL4TG1nUs0fmio0rnEY5tYJ16ERZ62WrFB6JzTFo+dxJqMtbKmREQfsFsANkaIPSCp0rkkJVx0id2lmHdRAUtemS8sBBnEtgLHViS4dF7TlALPHUOepGBp5MsowAjSts7KaR3YiGSYpBSyuVg7YfoJ1imORkywAZ0v7UWinjvXAZOCJj2A4CdAHb3iJZ1ai1UhyOAmqeh7Py3N5av65ScLwc0vJlD65JkvNgEm/sbFT2NKeqEQ3fQ6EYLXLuj2Om2Z6yNEpxth5yuBRQMgLM7izj9nBTpS/bmE7XAqq+oVaJeNKdc28Y82CUbKSmPaU43ZDAVSv08LRinlgeDFNu9+ONTR8AQqNWED5a8QmNJskcj0Ypd/sJ9wb7e3/LvuZsawnhgEYo/0bPRhn3C4jeHyT7aqe+UZxu+pxpBQLjlk81NMxiy8OhAPT+QCA6mO+3fdtlw+lWwMmmt1LBR2oes9RJvXZQ1HAHcv/llDZALdSiWJt+YSGLEj5SM0wSx6MCvE8G8vHxIGNnCqOX6vYA5UCvgHu8uaeCjzc9qpEmyx0vRjlPh8VtCeB+xtNhzjzZjzOj4XBDoHu0aTjW9Djeko9HGmYV8rLW0Ztang1zng1yng9FaT8b5jwf5LwY5fyXb5X4X/6b+r6f8Q9dP3M4T6dTnHNUq1X6/T7f+c53+LM/+7Of+pwDOP/8rn+q57un5vxJcIc/Dm9zy/QYqYSYDM8abO7AKUyRqqawsLM123oJXQl9iYVtrEYXQFZW4bu952MVgZPar3YK7TTGKhLnME6mf/ksAS1ALi0VdtF2ZdAE2jDLslVCO8LDOSfWNB7zXBQ3KFJrqWhR1srJZK9Fbikbg3GKSSb1aFCkTpQ0DsapKGkUpNbR9HwMinGyZ3nnzhFpTb2oJ/dj2R9aKSWbcXge9QK2vTglzuwKxr7WbIc+UVFPfjFPWXd0y57mUBRQMoYkc7yYpxthJq3gaDmkHXp4iA3+dJJs2NwAx8oBh8sBZSPnc7DIuTdKXrKbZVem49WAiq+xVjGOLQ9G8WqP4eVGDJHRnG+FnKgGlH0DFsZxzv1Ryr3B5sUCwFZJbOmTdTm2cjBcWO4PRdX25pvg1kpxoqjvnm4GNCMjFzPznAfDjPv9lIfD5BWtQYpTTV9A3A44XvcIjSLOHI+HuYSpBikP++m+XmWF4kjd41TTX9VzTzY8SoFmMLNiGQ8kOPVwkPJinO+zw7WCow2Pk4USPrH6KOHGp8N8BeAnQ1HWTwYZ83Q/zANPcf5wiU7JiRJu7anhZkkzjd0GeJ8NRf0+LQD58msDCH3F8abhaGFBLyF8rGk4VDcYvVTWjmdL4C4hPMqLY1vSVwTHANpVzZGG4Ve+WuLfXvlnsCvVZDLhu9/9Lr/+67/Or/zKr/zUx2ZZLtbSwTpYX2Al5PwV9/lDbvIX7h595oxJ0MVozMw6fCtAcQ48Z8gLUHvOFBtNgG8NzgqgjDMYK3BTVq9qwzgZ9mGcFsvTCayVU6S2gPzyc2fRxRaOntPE1soAESu29fJNXzlwVnaHmtucUBmyXGAfYJjZnJKW15nljkjLhDGNItKGSZoTKkl1L2xO1fhoFOMkI1TSL7rILU3fxzhRuBqFpmjdMoaa8YhzxzDO8IqNMTLnaAU+ZeOxyCy9eYLRe0Mgar5HI/BRTtFfZEySbAVqBWxHIfVAzvsozngxSzcmL7VDj+1SQLSE9SSlu3hpvGQ54HAloOwZcuvozzIejOKNoRVawdlGxOFKQMk35BkMFjl3+vN9ox5bkcfFTolOySc0SkJw05Rb3QW7s02o+lpxrh1xvh3RiDx8rUhS2f7wdnfBk1HCy++kh2s+F7YizrVl+pZRinnieDRIuNONuduNiV8CqW8Up9sh5zpyO1T1V0r90SDlXjfmXjfh8SDZB6nAU5xqBZzdCjnTCTnTDmhXjLSQDTMe9BLudxMe9BIe9FKSbD842xWPM1sBp9oBpztyO9ny8bXi6TDjUS/lYS/hUT/lYVfuvzxtC4p2pE7AqY7PiZbPqeX9tk+rbHg+zHncT3ncS3ncyzbuj16h8AG2ah7H2x7H23KcE22f422PE22fdlUuoHuTnKf9TG6DjCc9uf+k+Fr8itcK0Chrjrd9jrU9jrW81cfjHZ8jTUPo/+PsSvXT1j8anJ8+fcpv/dZv8Ru/8Rt85zvf+U8+/kA5//yun/fz7XB8Znb50/AOf+7f45meMFbJypa21qGd9Cfnzm2Adwlq68CzUgfMncOzUoNeprM9p6Wm5pBe56ImjWU1/SsvpoQF6BXknRM72y0fXwS5tJUwl18o6BABjgVC4xEnkspezsn2XGFzK0PukLq1NsSZxVcC/YVzlLVcDMyynEhJcCW2lqrx0E4xSXICpVFFcKxiDKHSzDJLmostbnHSXuVJWGqS5CS5wxTWtnXQCjxCZVjkluEiQyu9+rcItaYVyHPnqaW/yDdiRb5WbEdiO6eZYxDnGz3CIJtBbJd8IqOxuSji57N0IzXtacXxSkAr9PC1Js0d/XnGo/ErksxVn6MVn7IvFy7z1PF0nPB4nMm/d6GcQUJapxshrcgQak1uYbjIeThMi80ZXhGSagWcrEswyiixsZ+NRYk+Hm26BlC0BjWkpnu87lMJNEYpZonlyVCe92iQ7bugAKhHhpNNnxMNsY+3Kx5GQ5w6no6KINUg4/EgZfoKm7fkK1GqTVHAJ5oeh6oevoHhvEgtD6WO/HiQ8WyUk72iBlzyNceahmMNUb7HitvRhkEDz0eFRVy0IT0t1OrOOEcbvTFbe3lOjjal1nukaTja2FPBRxoegYGdseXFSI7zYmQL+1nU709TvvWS5nDDcLghCvhI03C4YTjSMBxq6FVyO8kcOyPLi2HOzsiyM8qLzy2745x/80bI//CvKq/8Gf+Q9TNXzru7u/zmb/4mv/u7v8u3vvWtv9NzDuD887t+Xs/3Mz3hT4M7/Elwh1umz0jFLMhlfKYV23k5BGQ5PETAK+0v1hZAdorcOrziMRkWY43Uo91SVWsoACwjO/fsbL2mnpe9yKaAqVeAOkAX2zgugS316qQYx5nlAmhnwRqFzmUv26hQyWmRtk5yscQ9FAtrCQsYLzJLSWucW0JXLjrmmaWkDI41SKOYJBmeMngKeZ1KUTUemXWMk5xAKZRSpM4RKE3d84radAZWyVSxIojWDHxCLUAaJBksJ5YVqxNKCtlaAfE0yfe+76DiGzqhJ7XZ3DFa5PRfglJkNIdKPtXAoB3EmePFLGP4iscdrwbUQ0OgRQ2P4pxHo3SjxQkk2X26EdCKPDq1iOk0YZpYno0zHo82AQ9Q8TVnWgFHqj5lT6MUpBnsTnMeDlKeTzJefjMt+YpTzYDTTZ9WyciOSg7GC8uTUcbDQcbz8f7WJK0UR+tSxxUAG3wtKfrh3IqFPMw+tw7saTjW8DjWKCDc8miXBZqzxPJsaHk6Euv52TBnZ7I/BQ1STz7alOMcbUho6ljD0IgM89TxfJQXAN68vTwsZPW3UNjDF46Vqfu51H2bhiN1QzVU7E4sLwo4Ph+J7bz8fGeck+//VQFRvuvwPdwwHK4bDjfla+VA/o91x3L8PeguISxfG84+H4eVUPFrv1DiN//1P2E4/97v/R5/9Ed/xLlz51Zf+/3f/32iKPrc5xzA+ed3/Tyd77GK+X/9B/zH4C5/6z9hrGImpBincPmeAs7sZrp6HcK+Nbi1+1hpKfJWQTCxkZczs/dqzZrMWnBa6rVW7alnpAUkL+Zne0j9MStgLna2KgJjcsEQIBtixM7iK01mIUTjacMszQiUtFoFaEyhjAMl4bLcSjgrs5A5R0mLHYxDrHDnyKyjbATucWaJtEB6kVuqnsFDM8tynJXdoyxSf677UuedpjlZLoEoCojXPI+SKdRknKOLGrQoakcj8CgbU0BRUrdLEDsnteZG4OErTZJb+vOMjdkXTiDYirwV0MexZXeW8fL7cjvyaEceZU/O/SyxvJhmjF8apmGU4mjVp1PyiIwCFHHq2JlkPJ0IGNeVc9nXnG4GtEseJU/+HePM0Z1mPBxmjF7RGtQsGU41fA5VvUI9Q5bDYJbzaCQK9OVaMEgq+mShYLcqUkfGwSJ1PBvnPCnU66sAbBQcaXgcXyrXuvTuKuT5L0Y5T0d5AeCM8SteN8gwjqMFyI8VirVV1pJBWDieFUr16TCTYw5yZq9Q5ADVUHGkCFodLZTp8lYONIOpwHHufG49mvJ8JMGrF6OcwfTVr08paFeW8JXbobouPsrngQfd8R5kd1f390Dcm9h9pYfl8j3Yrstxt+uaQw3Ddl3L1xqaQ3VNOfzyre2DPueD9YXWf+7zPSflB/5j/jy4x1/5DxioWCZ3OUQNW8R2tqCtQluxiD0n9rW1opZF+QqoV1a227OyjdOrxLYq1DBW1Ioq1HNuZRqYKQJfWTENbKmel4EynPQoL+GOBQ+zFxBDXnfASwraOkqeh80csbUEqvi9irBXtkxsK02cC7g9FLEV29lXikXm8FAESr7ugIo2pNaRZGI7gyjsSOuV6o0zR6BFESa5IzCayhKQidS1l9Z2mjvqQWH75ogt7UTx4eSCoeZ7VD2NQuzt4SLf3FzAQTM01HyDQZFk0F9kxC9ZqIHWdEoelcKSjlPLYGH3qWYFbJW9Aux7kOrNcnam+b6e3WpgOFrzqIeGdqGcF6ljd5LxZJzts6K1gqM1mUpVDzS+ka0+F6lldyo14Zf3NAYIjOJE0+d43aNV9gg9Vfy+jt5MbOwnw1f3A68D+FjDo1MxeEqhVQHgcS6hqdGre4ChsIsL5SsfPZpljV8Mo+lO7JoCFgCPF6/GQugrjtTFaj7cEMV7pOGxVdN4WjFdyEXBi5EtPu7Bd73eu34x5BnFobpegXb9/uGGplnWjOeOnXEB3pFdwXd3DbyvCorJ8aVfebu+BO4edLfrhq2aplGWv8vRTNT17tjSHVu6I0t37NgdW3pjy79+M+C//6V/BoGwv886gPPP7/rPcb4zLD/ynvLnwV3+IrjPrpoxUrIxgMpV0YNsVva1sZIaNU4StrmVUJe1FLOsi/trdeblLGtRzks4K7IiPCa9y1Lf1U7hrdqZJJntId+3DlGfLB9PkdZWRbJb+mKX9jaFBe4htnmI2NGpdYWCVZhidnZqBeTLMFuo5MIicQJZZ5f1Z7HPk+K+QqzuQBXwdg4FlLScp0UmlrguQKyQWdXWwjSVOran5PWJYjbSy5s5ponF12Jt2+L81HxDychrmCRWXnehmK0TsDUDUYZ5rpgmlmkxPnS5nJOtDGu+hKey3DGKLeM437DJcaI4m6Gh5JmVfd+f5a9Uh43Q0Cl7VAOx8fN8qbJzhotln/NeDbQSaI7VPBqRISrs6yyD0SLn2SinO9vfF6yVJKKP1TyaJUPoKQnSZY7hwvJsJCr4VWMk1y3oQzWPsq/wtPy9LJbW8UhahWbJq9Vls2w4toRv3VAviQ0OjnmCQHIFy5xJ/Oq3/cBTHF23hRuGwzVDJZSLnVls2RkLgHfGOS+Wqnf2+aq0Fony3C6OuV3XXD5VJXQJjbKco97UrUFXlO8SwIPp5x97Cd6t2iZ4t9buN0owS0RZd8eOXgHeJYB7xW137F5ZW18u31N859sR/+Mvlz/3MX/fdQDng/WF1s/qfFscn3gv+Av/Pv8hvM1TNWGkErJi8lZmkelbVhSztmLr+s5sWNrWAlatephVkcTOrQOnMU7vPb5Qx7l1mMJmtg5cYUOrAtwrJV3Y4dopTKF6MyvqeammcyfTwdzy+IW9bZD+Zw9RXFmhoK0VJUyhqiMjc5x9xFrMrCSiPSU12VDJ15f7tcSJOwAAIABJREFUAIuKlsf7SpEWwCxpmWK2tLQ1rJ5TNgLpeWbleEouIjLrqHqiZBeZI82tqGnk4sAhYzd9LW0866B2To5f9TVlY+QCIbVMEotRe3Xo3Eq9txYYfCXHHS8s88zug3XF1zRCQ2jkQmSeWgZzu29bQYBWyaMRGiJPLmaSzDGOHbvT7JWtQdsVAWnZ09QqAZOJ1Jx3JzndV4yCBDhU9ThcE+s68mT7zyx3TGKBqNSP9z+v5CuONeS5tVALvBXkGUxiy4uxBKZeNYISJP18pC7q93DdoxJqAiPDVbMc+oX6XQL4VQlqgMhXe9CtGw7XNfXIII0yinkB353xWiBqbD8XWp5RbBeq9FABw8MNw3ZNUQnEoZks9kC4M5KP40TzeDdmPP9pMGQDukv1u1XTbBWfexr6U0dvLIq3OxG125usKd+J+9ygGMjfQrum6SxvxbE7xc/p1BSdmqYaqS99b+cDOB+sL7T+Mc/3Esh/6d/nT4O7PNIjRiohIV8NAvFyAa5azrougJznrFRz5mT+tSps6aUiFnt7CdW9PmVrKVqh9Cpp7RX2dL76nrzJy+cUSlls8uVz1epYIKlqCY5lTlLCximZW13Y6BSQNkVQLC9UNVZ2d8JCrhTaFhOJUEWozJHBqg5tnNjWmXWkTurPzkGSQ6RFsSdF+CwqEsdpLmpbA6mVl1zSGgfM08IK14rcKZICypGR404Ti1ZSm6a4MDDItoammLo1ifdAjZP6tacV9RWEC1Wd76nqpQVe9Q3VQOMpOS+zxDKOLS+/FWqlaIaGSiA2ap7La+/P8n02NIgKbkWaSiAXFHnuWKSOwdzSX2vZWbdZtyoSnqr4ulCfkGQwWVheTPJX1n8BWmXNkZpHI9KUirqztYo4s4xmop67U/tK69koJVZu3bBVEaUaaCkh5DmM5naVVN4dv/p3Ban5ChwFkq2yJjAareTvb7oQhfiisIN3x58PcoBWZQ+8h+pS421XNL4HOPndBmuqd6lId8c56X6DYbUaVY9G5AqFa+hU9wDcqcmFR5o7ehNRur2JwLc32VO6fxfotqp6E7wFaNdv9RJMY+iNHYOJ/Kz+xDKYCPT7E0t/4hhMLf/23YD/6d8d2Nqfuw7g/LNdX/b5Xgfyfwju8FiPGal4NZs6cw6Ty5u0sRpnBaDrQS+1UtJmoxXKOYct9kleBrT8Igy2Ae0imGUKuC5VtFqDs+fUSjEqK2qVJYytWqWybTG2UzmpJeriZyk0zjp8JVZ7Zh26CHT5K9UtljJOVJCHxmjNIs3FVi5sbY89ZRrovVBYqOWCIV1T0csea3mcwFsjn2e5BMUE0vK83ELJFCM/MyvHNfL9xDpy66h4As7MOmaJxdNKgmIImLUSUHuFHT1NJZy2VMxL+7viaype8bNzGfCxHHqyXLmFyFPUQlP8fhLIGsXSKvOyejFKAlkVX4DtHMwTx2hhX2kDK6BVNivb2lMQhj6DccJ44did5PtGUYLYz4drMiijXFwcKCDNHNNYpkvJAI/9T1YoSSrXDY2SoVRY18pBmiumsUDtxfjVYyaXaxmM2q4ZmmVR78v9ifMchjMntvBEVO+rJmYt18puXqrRmpaLHiPnKC2Ot1uo3e5Earyjn6J2lYJmRa+OJwp3r67rG/k/FZQi7jyarsHWyf2JpT+xn5vKhj2l214Db7u6Cd1WVf5tRnPojwW0/amlP3b0C/j2JgLjwcT91J8HEPgyiOS/+1bAd37p84PNf991AOeD9YXWl3G+l0D+/hLIZsSQhIx8pUZ1oZAFyFLXXYW7rEx2Ii+CV9btpbGt1ItVYWOv39eFjb1Sv07qxvkajJc9yZ7bS3SrlXLWhR0ualdbyIvA1xLGFIlp5fQKzs6pDaUsIz1VoZRZU+ICLVOA2EPhe4Y8dbLfcwFl5aQGvFSkGlGo6ZrNnRcgDrQkjJNcati+0lin/v/2vj3YsqOq+7d6P8459zUzIYnfF0LEAAmPGAP6BbCKh8pXkbJCImrpHw5VilRBUSIlKCqTGCuBEIqytMIfWqlSv4pSSGEMQR5BAhI0hkgoAoGQREhinmQmM5mZe89r7939/bHW6u69z7l37oR53Jn0r2rmnrMfvbt779O/9VtrdW92fROhEJKuhKRzYpKuGod+bnzi2bhyKAyraevIu5IXC3GrNw7jqUWeMcFByN45YKlgxaauaC3LRK5t6xyWexkGuYFxTAarU4uqhiccQKafwWGll2FB1GxjHSaVw8Exu97nuRu3D1iN9zI2pKYNx1/3jxpMOqpOY84rfYPtAyapImPybCyT/f5hg71DtyH5nrKQYaln0I/ixtOKY7VPrVrsXuUM+HkoJDHqtOUMKwODQaFkxsQ7mvIKV5tRvMt9VaJMjCt9QpFzQp/mRRwYihtYY6+HIMVByQToXb7yd6EUQ0OewafXnLiaI6W7alsu7NhT4dufE56zREy8ywY7lvgap8i2lQHXv7EO+4fA06Jo96067F9jgn96jbcdGDrYTRLu9iXCdiH37Ysk1ybs0L9LBhk5HBgBpywRsuzIubYTOSf8SHim/T1Fg2/mP8RXyofwxfIBPG5WcYAmqB0neDgLUMMDeNZwfNQ0miFNyBomVZ9dLetZO8uraOXWsPtY4ss+1hy5qguJKdfWIQfPY7ZOksQQYshkmXwh2d1KtLofjtUriVJ2ltVFJjFlnf+spK5KnaO1sg3Ey4ZKfDYD/Lrbcfy5l3MM3Vn49bKtXK+gUOfGsZu5kX0lBRVtHdATFTltAgk3VkjbMEk31mFac0ZxQWw8TBsHA377EU8jAk/9ygwycFurhl3W/Zz7qWocRpVDJq5vEjd21TgMcoNBwe50dkNbVA0vRhLi0FznpdL4hUIa5zCasFI3UcwakOltRFjpGwxyVrHWOUwrnkM8rmYVNsDtXOkbLBSEXs5TY5rGwVGO3funczOmAVb2OxYMVgZcP433NkK+q2MmuvWmGAHsIj51KcNyn1g5i9HAZTgcGLGa27O6fowX4AU1ThNi3DYw6JckfcnP9bTmrGOOuzZ4atVu6GLOMyapU0WNnrqSYWVAKDMCdxGJSzwozr0HLSvR1Y2TqABgeUA4ZYnJVlXt889YRG7H6BcEI8Q+qSz2rwFPrzlPvEq2T69arI03vAwAYKEH7BCS3bHE19qufxeZcLctAL3cYFJZHBhyXz296rB/jf89vWZxYI23HRjytpEk0L3mJwtcvjMlhK2LRM7HFofT30NU+K/iMXypfBBfLh7EU2aEgzT17zeGBdCwKmZiJlnFiwnayXzlTBK/MsvZzbpICPzUKYKVcjLH2c7WhgSvWtzBWrZzkJdHsFLl+DLHcq1McyJH4gp3rJIdtZW0zF1uHMH5Y4xXV0BQ0yTeACfKN0eIPWucWbf76wrhOJ+tre5gnmvsRInzMiI8ENeWSU6NgdIwgerCJZlkXdfymsnSEIyo9KkQbClu50ktpE0GcKzCayHX3HBfjSqONZeG3eC1dagafrnAIDeibIDR1AKgVrKYGg1LBatZzYJem1q+ByYQsJVrLwhZFzKAV43D2sRiXKGVZAbwPSbihTMWCoNC3LO1BSZThwNjh6qer7L7ZYaFHFjsiatY6lzX3OYDQ4vV2dcPeyz2mLwXRTWr4rVNiFfvG7p15/IC4q5dynDKEmG5zwZNmcNPX6tr9hbsV+I9BOlyeeL6XTLYvhjUuCHIQjzsTdi3FmKr+1bthu5wgFXuKUtKgOJiXiIs9gllpp4PNkZXx2B1O2QX8tOrDsPK4Mm91SHdycYAKwvkyXa7XHP7IvnPCz02noiA0QTYv2qxX0j1wFogXf5nN6WqtY3bFsO/7UuEn395gVe+uDj0yZtEIueEHwmH6u+naYzbi0fxhfIHuK14GPtojDWq5GURDiTxYxK3NFkjBG2YoB2/hclZVqGmIVghbRJyzPTVjZaXzwxkzOWoO9uIy1vnHWtsNofxc6LVvQ2wknNKeJGLW8lZ49ZGXdjRMWEbq3oA4sZmwub2i6KGHCvXJKh61gQqHsgcCLkxaGqL3HCdvLKW4zhzO5B9ZXkAN2AiYkJWNyOEtMnHEQn8YgoDrp8maCnJT2pWzqVhklIFDBAGOde3bpgoMmOE8IWoJYa+UBhvUExrcZFnxGt1U6gXgbBYEkqZl6wuZDUU2rFoJvdlIdDcE7bFaAoMJw6GZhWzdZztvCTnFUIcTcPXWRtzIl2zjgLsFYTlHmFRsqxzw/e8sbxk5nDisG+4cXJSryA8Z9Fgqc9u4DInyHojvEiMliOx0UPGXIV0ty0w4fYKQmEkL1GMttGE3b97V3k60to6c5fjcrctaiyXsGPRYHnAdS1ziA8ouNgPqGtZSHDfmsVkuuElAAD9EvixU0oslA22LfJ1ti8Rti8aLA+ALOO+Uff76kiIdtgmW1W10w3c+zGWFwgrC0y0K4uEbYtM8isdAh6U7DGY1sDqCDgo110dOVzwwgwvPPPIvQMikXPCj4Rufzs4PGT24z+LR/D58vv4dv4k9tMEY6r9sphkCU6I2DWAkSlORtQy6b5IOZPlqUtW3NSBjPk4Tdpyul1iwnUjKjaaOpXFCtoRMvBiGo1XyfB1zWTJzUDETMwk5KpvizIOTKKiYPVFFgArJAh58/uiDCDXI6IQnwZ8W0xE0CQkXzcORcYv4yAI6UrCWaygnWOC1QVPasm+Lgh+mdCCWEU72W8du3U5Hs1u9dyEtut8516mpMf1KTONdzvUQuZFRujJgiV1AyFqVvEGgAVJ8hlPIyrFhatzd1Xx+4Qx6ziD3AGLJaGXGWTchZhWzruLldwVjbRrqUcY5CYoVgdMphzrnTYI2eERnGOX7lLPYPtSATSNzN123KYpK97RdL6LHGClvjIwWOyxq7qUBC2SXIKqZpI8MLQ4eAi3bJEz6a4MDAYleQWeicqtRYWPJhZPr2FTCpcIWFkwXuUuDwi9nOupngprHZqGX+RxYKgxXFa6ow28BXG9t0dkp0S72CcUGcfSFdY6DCeApRKPPTluk+7QYXKI9igGPSbTZVHVnmAXDFYWCSsLQL8kn9zmHGFtzEQb/zswdDg4ZAPgwJrDwZHDeIM2X/iSDB94W8rWXheJnI8tTjttGY/v3u8Tur5Q/gAPZftxkKaoYL27msmYgJpjn6iFPBojipkHZ2M5pkqOXdscX2ZShihjXuiDV/xylvyqXErMYXqU80trNhZ+JS5WzA5GXM+QAVenMTkb3NU6RaqxjmPZ3tXMA7WqYeMQbQvuawDsYhdlkfnzWWXo1KJM3NHxdicknQGB+IlAkjCVkZEEskDCOlg7J7FGwGd+N5YHQxJFXRjy5G8tkyIBKDKWWdOay2NSDUaAdZyxnckUnInGkw0rx0bIomocD/aZLFdq4ZW3HuvAx2pm+kCyqg3x2tST2qERwleyVoOibhx6RZt4nVOlyc9nl7CdEGOZsQoaFEz0mrBUVcBw6jCeOh/L7iYoWcdzgpd6EUlKGVXNrvzRxGF1bFE3GycILfYISwPiOHdpUBgOA6gXZlo7TCrg4Mhi/xAbKnCAFe7KAsdRl3qEQU/iw+KuBthoqWpx5w+B/Ws85Wk6+wrlGeQZsH2JiW7bIpPfoCQUOROxGh/WcVhiPHU4OIIQXVC2G7UjLzLU8vrPXknYtkBCqoF0ty0SlgecyKYkq/d/PAUORKS6OopJFzg4cqg3cPl3MegB2xYJSwvkFfbyAqvt5QWux8oi4byfyLCymBLC1kUi52ODAzTBf+WP4avbHsYX6u9jtxliSDUaWE6IcgRXU1DJXhUbuIYVsSdsywRITZug4YjVtCdjzsomq3Fbktc9iutYE66iZTtJ18O2SryigCURixeKEGKOVv0KxMxE14gCzxDUKatm4oixfLeeUCMSZ1aNFDJ55RzIWbdrBnJweRuCJ3o/XQui7sRlDRdUsGbdOgdxf8tNkylmhuBd0pxIJslXEmesLROhTj1S13ZOnKADyyq5boDCwLuQ64aJqcg0nsz3pbZs/BSZqHMSl3vNU7dyEx3vgqrODCeeaWZ0LQlq04pj0Hnk2lZFq8TZzyW2K4lQdc2qfFrzuaajdrXvyhxMlEK6ANArcgxHNSZC3FXtZs6PQQQs9ckr3Nyom1q8ADUr/rUxsDZx665wpShyJqjFHqFfsrrNs/DsWHmmx1NgPGESPzg89BQggLOSty8SVhZYOfdLXgmskNiwNxgt3+/RxOKgJEodGDLxbSZGCwRFuyJku22BDZNeQSgLNgQNEVZW+jhwcIymAcYTJtODkYpV0t2MclcYAywNmFCXBkqwTLgrSrQDNgYyE2YEOAuMK2B16LA24sS31aHDqnxeG8nnkcP/vTDHWy8uN1+pQ2Ajcs6P2FUSTnhYOPx3thf/XjyML5Q/wN35blbHroE1PMC4WuPGGawQshVCVoUMcVtbJy7rBkLUAJwR17aQexRf5hhtO4lL5zlrTFkXE4ElWXErTKUyurCH1elLrKZtIy5oeTlFbfm9yZl815dgGMdHaT0aybaWyU+wunqY5TnMQJgypdOdGMF9DcsDNsCJXjoQKvGzemaCgbi2DRGayiKT+cxW9hGk3S4kj8EBlRPylLnSmaga3e4cMLGsMDOJVZfSj+OpJIXJ8p+TmtVkkRnkYMPANsCkYnLsZQYDw8Q7qZjoi4wNhNLoohvipTBAmXGc1jleDWtUcW/kxmAg7vNm6jARlWyIyW65x/FpKwbCZOrQWCbBngFQE8Y1MJL72VhW3v3CYGlBjB1IYlzD7ayEtF1FWKuANb5LAACTNZhOLQalKNyFoO4d2NOhhDuccLsPVoSDvow2+zrw1KPFHivQMockYknegXVoGjZCxlNgdWSx5ynCnnXKi7E8YNJ5zjKTXq/QmDBg5N40YhixWx3Yv+bw8BMOk3WW/+yCiY4J7sxTDVYW2GgopB2Zgfc6WCszCxqH4Zg80T7yuMP3Rpxl3TVO8qJBXc2vy6DHRHrGqQZLg0jBDggLPSZXQ7w6GcC/LOd4RbjRBFgdBlLdtx94+HGuw+rIYW2TBk2MzACLC5zsdiRV86GQlPOzHAdpgq/nj+Pm8vv4avEwfmjWMKQKVl4H6CyYcBt1T5vwOVLJnOQFH0fW73AGqFnxkiwmQjKH2Tk+nsR1TaKI9bOR+DOUpEWhZpIhbYXcWcEyEevymJrcpcpXibiRhChdetM5h7phqs1k4pMObvFxiAlVMq81TsyGhBP6lxW/1AUuSU/k6VzOicjZx68B9iQQrzcMSepyNmQmkyhv63iN75z4Ok4SxkxE8tY6NE6Tw0KbVAUTAfoazMYiqD/HhGbALs44EU1VcmY4ASkoZFXxHMvMxCioGyEiC1GD5F3ljcSqDVGkktmYaZ1XEHpZGIydJDxNKzYCcqNkEcU2HSd41ZZVdq8IWcRqIHEM12E8BTKTwdlmbmzZSd8VGbBQalmELAt5A1Y8B5MamEzY5b2ZpR7zjBV4v0fo5axoWTGHpEF1fTORs4obrbM29jws9JlkF/usmns5oShYOfspal6dO3FVwxPa6ogV5eGgV4qC7TO5Lg4ISwO+l3kG7NjWx2g4gZGpWtBnq+H7sRap1rWREOsYGB9GuxVFwYbGktRhUT4vDoDFvoQc+kC/x88Hx+KlXuD+GE2A4Rh4+bkGLzrryL2dKrm1EzwsHO7NnsJX5bWL3853Y5UmHDuGkLEloAbQZDL1KWOirTN2Tzdou7DFDQ2fAKZkTMG9bQE4JeKIoC1AzoAaVpDwpAx51aKo24b8qxc1U9vY9tKYnMgFaCauXzhEEpG8olYXtRCEknfs3tbsaiVTvYYnbE/A8C6/TEgb0o9KmiSEq9muiBW4LCxi1HUNICODuuZ1rHU6lUEYsMkFNQcEQtXPchVPqOpaD9NnxO0rBO0NEiHpQshV+wxOiduXHIjXhePZC8BqzQrZ5zqtJnLNqnLp5XHCjpB1zfdNCT43ADRpSc61FugVrOByQzAmtKuqWdHDOU/a3Xi0lmOI1W2ZAwv9HE3NlpvOqVdCnEwxQ/5tOL+e9qBsu6WVwAFpf+N8HccTznjf7HrNg5640UsmuZaKNeEZcGK48HVEzQ7dhtOu5l8PolyZvHo5oVcAubZN1TOCIVpreGEKT6xMsm2DIo45b4TMMJkuRmQaSBUoSzYy1Ig0+iOKfpuTKpDrcMzqem3kZJuT7fp72hgXvszgA+88Nm7tRM7PAvyQ1vCfxSP4Qvl93F48hr00woT4/bituccNcTKXV8dCyo0RUlbFrNuEgH3il6rhTFR0rIiNJIGZkBjmTDhHyVziyqqiIcrZyJQi57okHZbN9NOcLDwpK9kCus61uK0befWjEmocz+0Qc7wGdqbU54KqcS64izX2q4lrQKS0CT6xK3ZrKzmz8xsgMrANL5uZEdeXEI5RpeFfwiHEb52uHKaOeBn0pf5AyFpuGiatTI7VkrlevABILoMdgdewbqwSXnAbQzwYcTKaxnudbGN3MpNILotlOFH+jag1gqhGEwyGpnGSdMaeg0zK4FcyB+PBZ+Fn5N3HmrwVSJtj0bYJ5cRkmxcGVdV48gcgJCvlZdKnLKbYJV1zuZrd210opQsHyZjPgYWexrw53myIXdJsIYsh0rABNJ6yYh5PDs+lagyw0Odr9UugLLg9eR7c0ppApsZnXXN/TyuH0YQwFPW6mUSyedePyXRR3NJlAWzf1sNkPEWWBcNHm6/Pa639OyUMhdxjgh2Ow716JnUb9KR/+iSfCQtS10Ff+477Lc/4nJ8932DHSlLO6yKR88YYosI38ydwc/kDfKV8CP9jDmBEtbiqeVCHJaACYCNV3IgLWom4VlKOjvNxZSZp8qqY/GpfJCt6ke26soVodMqUi1WzbAeX6zYiZf8dnoD9tCtoBjXHSp2f2hRc3TydKkxx0jmreqxX0SC/SAmTr4nIF/49zRkZIdZAvM6RKGN1gbf3c9uhW1uqlMigacJ1AT5H1bXwg4QG2MhQd7azShJBscG3kedRZ7Jgg1+TXIgsDDnUIs/cwJ/TWKCpHYwJJKxGhbZLCS4XV7QaFFZcpg6BrNUVr3H7WB2XObwbXDPbNWlJE7Zi0jZEcHD+fO8tyRBINoojK8lWjYOFwXRiPfnTHKJ1CGUC8IlVpWQw55n2noYAwFOUJBt7Oj00gcdXs44Vsipl7g/pE3W9st3JBpUYM7XExsdTVozPhMCKgklKY7y9ApKtHVRz5g2t0EFW7k/TaHyemEhFqeo86Lww68ac10OWKZmyFyH+u9Dn+uUZexSMIWTEzykRvLdJ8z2qSo0eTkgbjTmvYeg/szEwnoT7DQCveYXB5W8/cqlaKSHsJMcUDb6T78YXiwfw5eJB3JfvxZAq8Ovl3TrKOJPPFAjX70NHKVNE0m1ydvKXXdSyz6tgJt+gjsNnr7odgrvbOY5RO54KxIM9E6K+SaqJvvNgzf4844yfjqSx54zailrjxTkQJYfx9KmMwrxlTfLiOc9BFUOUmLqAyTExK9SNrW+pIhgeiCOCVaXpNLtbFLXsYmNBVCcaB2eCcnYg5VmOlwNyDwAbkXvjgir0bmtxjdtGXl8pJGVkoMoIcEq0xHXPnINxgG0IEyH93PD8aSfuS2vDQK1quoTYfw1hWkm/i2ouIqKtp8BEXIkab84MoWCrC84SE41VwwIyZQgoC+ONAmuBuuL6NFbIWupaSsazE6XridtJMpvM+V3sZViQGKzeEHbdc07CtOK5wJnRqVuAnRIP7tFv0YkBrM9bWchUsAK8NrTRTHqIA0Q9DOTjvZMpJ4rpSzGqMdCWIvP0lPP3u18SeiVhsc9TogohdTViSL0eCO5o9ozwddUtPRoCT+/baOQ5tK4b9B0GPXZNn7aDY9FlDqwsl6im0+Ae9x4TeML3vzXLz+1Y+mU84c97n1KPAn9v16n7d3Polxx7HvQ4+avfg/xjdf36/3PkVPOhkMj5BISFw33ZU/hi+SD+tfgB7sn3YJWmgYwd2mRcCxk3BFSihmsSlZxFCV9yvE/i6hKy/PPkHG1z0XEukLdX6T7mjEDO8npFJq34O5cXf1dyJwd5gYTEcr0ajeLUnu30XchhLjH5qVSIFDGTtSpoK+cqYXtSjtzYBkExh/0OVrwDHCoN05dUqflpV0LCJIQLjSU7MDnLcptOiAyexMkrZ+03iMr1Lkqxx0DBRcwXF2+D48xpCx4UjZN4s2uTrGriTIndEipZjSmPyN3WTLKqZNkVzu3XhQ5dQ2hqXmhE1bomj3lvghAooETN9SkNQJm6qDlZbCoejcbBL3TRywBTeH8BE2TNC67Umggo9S4NYDJpY+0wBWE6pYi4uYxSplstyKpRxvgAAHTOu204kWlaEb+0Q/qgIAA1cZLYnN8x30OJVzvH6lSU8tIgxOu1P/UkBzFcGgfbAFXNGfLTCmgqYFQRRmubHU3a5NXvcTy/V7JyLnIgz8V7knFdMqNhlmCQqtGpnpW6EXVaEcYTh72rwONT+Nh8njedecibJ9FMXNL9HrvKT90BDEr+3isdclH4GcG7zTNDIOO8V8nJzAZdUEgT+qYVYSJqmvMNHA7sB3aLYXDGc4BXnb/pqv5ISOR8AkCnOH2peBD/WjyAu/MncdDMIWMr5OsVsOHv6q6Os63j2HJMvvF3jS931DKcxp0jklZy9uRrZCENdn3DAhac7AUXucI1Q1sJG6KamV38MU5IWVWjV84O/oUTBvADuMax1aUMZ3wSFhMvK2hNhqpduCaTsgkDoQtqK0PIflbXd1DTLsSlKZBoN84MB7+/nazEZzhwzBkROZMo2xhOiNkbJjpvU8jcqnFB/CIPVWpwTgwBQgOJPUIWC/HJT3wN3Q4iGDGInCPULpCsIZ5HrQu/VBJLjxOGSLwYmVgpriGfOOZcUHZl5K7VLPCRLHeqLmcj6tpkoX+tKGwb3atcEoUKQ+iV7ZhQtUnaAAAbKUlEQVSxFWOgrtkFazJ+vtQoKNTAkHBJUwGTqGxd5Y1I3M05J2st9ZjANFav03w4PCKLt9SsxqsqxH2JgGZKaDpKfBZOPEpMZj1JiOoV7IIu4niygQ9VaL6Dg7jmxfXMZBplg6/RIa4/W595nw2p4nTol8DKYljEJM+ApcUc06lDnjmupzzbRmz7ePlbJ8+Ij8OLsp9MOVTw1Cp84t76C8J0yX89Y6C93ZCo/RLetX+skMh5C0KV8ReKB/CvJSvjNarQQMx5ITI0ACqNFcs/T8YRCXv3dYZ4LrIn13oOMXt3tSpkBNe2k/hzRMheIavfNYpF63ayMtfXkv/BQdSwV8wSG1aFze5b/q4x1VhJKyE7GylMQOZAM9FpxrFBWLOXV+MKi4cYhGxrhzAoqGWtZN5V0uFFFmGd7FhNxzFm/ZzJutZaFX3fse4nhHg1u6jlwSBS5yU0Icx5JQW4aFEFf5i61D1RABDDQ5W8ErTG5ppa64Xg6oZu4KINwMZXzUQdyIANH14UhAkpJguCuvuB3EVNaQh1FdzNGlc1BPSFYbS/q4pjuQD8wG6EuHMDUAbfZlvzfG9Pqo7Vap7r9C2gLA16heFXOUp/Qtyptf6t2wZHRgApqVjAToGpXNVG91xJ3DmKYrbs5l7ui+eCfOTD9683CJWQhJTqWp4u6ct6TKgBHM5MJ31284zJppTM90GPkGdR3+s/UvJsExfHuZU4nSf8WhaRmVaEp9eCWo4RlPN6ZLoxipxd0L0esDAAdqwwieZ+FTNR/JHa93/V8BRrjcBDGCEYz2q8NY3DtGZDaloB25efWX2fCRI5bwFUaPDdbA8+X34ftxQP4v58L0akk5vQVsYxCVeGE7lqVcaZuKs7CjlWwp6Q0SHiLkGDSVjiyd4YELdwcGd3/kp2ti7AAdc+Rwk3VpO6n7xLm/fpnF6/DaxkgEDQ6p5qJWOJQglEDU9K1jk/d9qQLJsJeHVee3UrbjGE6VEAu+50vi9naXP5RghnxoUt8UeCEJchkEyBckKZ1g/I8l5r4pdgGCFxYUb2kmhdpHwHJ0aQkLP2qQTwLGQwclpGNLioUSS3k1W2ELRT13yIW8exSrhA2iTqvRbC94RJXIYThVbZeLAP8V0tJ9c6ET8/tuZVypRMsoiws6wdN3W1w6QBGkve5RoTC7uknXdpApwwqAbB1BCqWow/iMITl3KRAZSHQV19Ikq6tgnkVDcmGCLSxlyInBzBVWxcxMnPPmQStdVpnD7n62cZu26zgSY7gd20es/0p6ZGlxgjGq+t6mBkWMkfsJYwqYBJi9k3Ip/19xFYXWrCWFkwaar3wmdli4t5MMgxnVQtl70+3c5xg5x1XjE7MRo14awSwpxMgf1rTJxV1TUfjgTabT7zfwFvfN0Rv8hcJHI+Dhiiwh3Fo/h0cT/+vXgYj2YHUZGVwReBjNUdXRtWyBUxGcekHB8Tu69t9LmJtnmSV1IGZuLHSsJKzBp7noklmzkEDDgXubpln5N98ORLEWGH6UlKFuo+5cG/TeKAEryqRvLuTQLHQdXdDMvKQjOjWeGGesQDImmsU+6TkUG8kcFOB78McZYytUlC4r+qXtk4CCtDKRE5RPXX8rW/jIGB82qKRM3rday0RV3aPmGMwufoZFEF7TI0w9aTgY7weowQNFFoKyi4SZnEw7BKCCuTuYbEtR2RlPS9k+U3dVnRoBxdiI+LgeCNJ5L6NqyElbBDMhqXkxO7eD2kX9Xgsg2XrYQdE2iZZZxtncEbMrZhQtDzXfSsWBfmMeuc7KIATKmKTLtTn03nCZOn9wW3snPiuYgNF8MeFahqxjyooepadVOi1+zlXJRkWQKm31aRen/19gcFH153qs+mhgyaRgi/gZ9bXteESU1zY+vzkOfOewHWx+z+POeEMjYE2HW+vMD3ocjFCNA4cxZ5VUx4FvWee2NTni9vXMtvw0bPmf79yXMOVecjh0TOxwBP0hq+VDyAT5f/jW/kT2BfNgqqGJgl44kQcJVFZNx1Xc+ZAtUl4a5ydqKYHdrbNOlLCbWJ1bFpk2pMzJ5wo+Od7m+TsydjGZxi5UyeYFR1RwQtJEZ+4JFztd8QJVIJoTeyT2kzKOcwHSeaMezn+WpWs/5r5HoEcWMCfvqVEpgftJy61eU90hTUptYT4IHURirfRiSuZEXSzxQ30xO56DbfZvU2aww0GmDByWZcBaZm7tdIYUgZ7N2PphnF7SP4GLkNHB59iIwm3SJhiFhN+0ERagARUOuLNkwr/mqkQ1oGECEYV/KYwRGcErYnUNdydxsj6jWLySccX1ugmQJVxc+br0NU5zZpSk9KOMKJK7dLkPE/QMk8uIzzIqj7mChiA4oQQiKNDfO247gx1KtBobyc4OPlz2SOsnP6vIZ/MQGqIs7L4MnQawciDPWKbEWAgH7PYDyRNfqjNvoYM0Kfquu8buBj9Wtj+Gl5xxLLi8DP/eyxuVYi5yOMBhbfyn6IG8v7cEvxIP4n24+x0QCtQImsJibaadb+W2VCzCb8VSKuJbta1bI165Az2krZ/4vUss+sjv8BM67qSOW2iNcTs5wH+W6jdjrwFCvEx0RlKqnKdlJyVyKGC3HnOLEK8CRpI4UNRETsFTVvJ8nMzvS64HpYGdC965zCfGIlB0SDVKOqXMpV9y1/1qE1ThqDVyAWEk9GIG99UTwAUAOQ0Xi5nh8IGdJ2dZUjKscPgkK0/onzJBr3ddRXep8M+dibqgkliK5rW8PPoeg4AS6obwPnlbl1bBsa32YHwPisb+0nfeWlidoUx2X1+vD1koFMb5h4PJxl4qw6RKkkpvN0DTkUhYHJY8Mm6hd1ESsxOsBaM7d+rc8x8WrsX8i8aUI7g/eibXTpNk/mQoCqDntFJ5ZP0TMo/aIqkKhzra4aFg9Y04Tv8TNlAFBDXsUfxvso5mIj5ayGQGY6ajjjOPPiICj/VmzcoG3sUDDy1ChEZAj5FAr9oURGq5MfQtxXzgE/9eIfseGHgUTOPyL20gifL76PG8p7cVf+QxwwEzj/iiCBuodrA0wMMDXANJd/SsYREWtSV+tvRMqtNa6VkGk2ftxN8lISnXFVx4Qbq+DoHHRIGVIuXNiOiJiV5PU83Qb4ctU6b23X4d6F7U7VsardiNitHgtq/SVfXtivA7+kRnlFFl3VGwJORkoL+Hr6Ywk+Dh3Ho+P66HQw60KkWDPHQ4KNXpfiIuBIE9WAkPTlvMpQslZlAkTKSxW6tif6HF/EE39kZITMM+lr58K5voNIud+XTf6c9vVcp22kpKOKOlKpoR08tYsIXkFZcU2rcqaIjOK4dbsfQpOMVEMHZ4j739VCugCaynilpg3x2eYmkKB+j1V4aDO1jTj5q6vWKdnOc63OI/awL3qOvVqOSFw/IyJ3hOvFRE8IKlddv0SSdZ+xW957CyI3sPapd9l3eDU2BIA59fF9wc9PnmeYjF2IJ6uLX/7Zmg3FZyD6jyrO/N8OF/3czC/qqCCR82Fgghpfyf8HHy++i9uLR7E3G8Ea2z7IIZDmVIh4HBHxJGcSVpWsbuuu67q1jKZ8j2PFcaa10++YJWcl2Xlx5BYJI5C1k1+guMxa5DoTM5Zj9HtLIRtPor5vHG9XdYvOYOLLUrKVUUWpNAwAvN90BqC2gouIwe/hnRqDdoBPyIptKnXjGkTbVJEpWXoynlXoSuRZpzyti7bXXzIqoxF1rWt5t4iHwnzmNhG1CX4enGsfEBOzn4bl+yOi+uh2xJdy8X7Z0bKTXOtw/uz4thhPGOK5QFvxaLlx+72SbaJHQ70mNOdft4yITD25Szn+1ZRib2qMnl/8Io6r9cgQnfh69FkzyCHLf0aOlVa/dO+Pzj6wCAQPqY+N8h+65N79bGb6JfotW46pA+vFtNdH+ze7/l+9bpwQRoZjxc5poh5AvcgAkh+dXzCF5rUj9KGqY7hguK1bb0QerWjsAIJrXT/HRoV6Fs74seiEo4xEzuvAwuGb2RP4f8W3cUvxIPZkQ9jMzjswxHYnGTDKgEnBnyc5/+26rWvZVlNwVatbWt3WMTHPWdN6NsM6IuKWEo62OzkWiI6FJ8y2KpYnPlbA+vB2lW6LvAFPaf5hp9Zn54k86kNEx8ajf1SOKudYybKqdtDYtD88IuAWWesA7YkjTugK29oqOCJ2gR8I5buSuCY0ITqn5bKM2hW7Myn6x3FnfctUYJRoXPdw0Xdto/PX11hyaIc/xwWi8FO5ovKpc7HA11Efwt+aViw3rpB3HXYQqywfjlBCbNWtTTpx++eRmydOFxLgZuKec4jMWoJtjN8fGx7xvQGJgWGk3ibqgGgw10e6nmMIdck9rlOszmNCypWMJHM8Nj4ACgSFsC/uR70WRdenTl1iwvIhlMj9jejvTH/GfRURp/6WUIuHQi5lp/xyl62KTDwJcSJZZoDh8NjVOZEzACdE/NH8TtxaPoID2RhuHhE7BFU8yYBhBowLYJTzv2nOKnmSReo4+tsYybhWdRzNO54h4oh0W4SMtkJWwo1d0PPixPF3JV1Q+LXEKlfJtku8QChL+yMadHxikIuPjfsvOlcRd3NMzp7IESxdxAM5WsfF8Aq4dSxfXxXRzD6EAUYH5rA2dbvKUZZVUO16WEQKemqXTEJ8OhQZk7CxsupSx3eom1RRx+XHxBvXVwfZLpHF7ukuEXUP5uZGG0kGcWrXQ4qNKhVut98c7dM4KMUHQPIOpGKqHGdINiLN2FhQ8vQ2UtwX8p/rfIYDsszAOts2Ami2X2YMBZqtA3U+a3NIHn9vGPk2A0TUrqsN9bOAf3HJzP2N2xHt02cxPsb3X4v4XStmre50Vfl5gbanRtuv7m0EpavHxP1C3nhp36NeSZhO5d7qMVGX6LOhDfCefQfE0wG740Ps1tfrxl4Hh45CtpGHJDqmEWOi61Z/as9JQs533XUXPvKRj+D6668/mpc5LDg4fIUewoeK2/HtcjeqvGYfW3f0UpJqiOPEwxxYK4HVAhgVTMpDcVGP8lkirkQNaxw5noccv/FJl89sKeDITe2oTcyehKlDwtG+OKu6RcqCrpsagHdla1kx8cXPY3zORsdoWbFjeIao2/0dK01PorrbIdrXGtda1++e1w3/x9vi89su81k+9hsjQoofGR3Q4hJbn9sVDsQh21s2isZE3SzBAGipnm6Z88hqrvqm9nkxYeoBcftcfHBsccyBDq5dKyW2y7pFuM4Oir4zcYQFV+LzZ0hSt8VlzLln3fYbGFnopl0n38cEzDPK/LGuXZfW37gOc+7Bpo6Xv7FB59tsNnF+p82h3tTuVBva3X3u4n6Z9wNZ7/h55+Q5UNdm42t0zomNs5A1HwwKdX+DIoNiToIYr42uUxWdNy7UYwHMJtnp+Wf/xElAztdddx1uuukmDAaDo3WJQ2JkJ3hn8yV8duEHsP2K03TXI2JNtpoaYC0H9veAgyVwsAcMC/43ytllPc5YJcex4ziZy6tiihKyTNv97NVx5E6O1XDslo4zmzVhyydTxfujbdouP8JExwHtMmfc0AgEjeh4oP2jdJ3vSg8z27HB9rDPzXyevaTui0lXP3aJOdSps8WttyfmHvJlx2Tu1+32x4XPOra3piptxGLrHMFrFs8fTFskpP+iEZs6x3ZJcB5hxVBi7fZj3M7WY9EpP7bVKNyY1vivRbjO964BM2MQdEHBC9J9tOKBdSNC9J8zgrWmXZfO55l9Ui+vgttV8/ew1ReuU05koCn3t22ETsEulL0eWvukfDfnvPXaNvcZ6T4vG5D+TN/Oux4ZnplwqOvNuV8AWp2kOQhAcAQeLXzj64Q3v2l66AOPAI4aOZ911lm49tpr8Yd/+IdH6xLr4nTzUWBbxUTcRYuIM2B/AezuA3sXgP194EAPWOsxQY9FIU+iRK4uCfss6ihhy3WIeCYeDLRivLEahn5Hh2TnJVd1jm+NnNT9lXfIOTo2JuxuX80j2fi89QaJjfatp6YPhe7A3alve3CmmW3d49Yjp+55MQHNdGnne4tHDsHLFNWzvYNH0RZ50frtmVfuZg44tNmwiXLnVf+ZlrnBiYdV5jyrZhPnzHt77gzxzKnMhgQ+c+Ahtm3ymJkWbmLbesbeRtu69dqwrofRvjwz8p71zdV9vW2t+s8xILr12ciQWPeYqJClxZNAOV900UV45JFHNn38jh0LyPWFqJvARu/BxKQOabxKnKMMeLIP3LcNeGQbsGcR2L8AHCiBYY9V8TgDqpzJuBYiVnWr5Bu7nUES7wV8RjSoQ6RynE+W0m1oEyx4oPbfoqSnGP49SDR/f/fh1O8G0bSb6MB51mk38YbLCVmxfjNxPTZ6mFvnxNu616UW7YfrUpvAWjG+7jlzts3L3iQzS4mH+tFuqA5mPqwzYB3GoL5uGfJhvfu8qe+YbU9326ZIaTPHRNtmPrcO2uT+zvb1zplpH228/5kQesKPihMv5ems5+U47bT+MbnWlumdffuGmz72tNOWsXv3wXX333z/G/CWr/0Qb60vwE+dvYxTT82xvGDQ6wPFuUD2Uo55aAwins8HhM/ztj0zdK2tY2d9HQkcqr8TjixSfx97pD4/tjiR+3v37iNX1kYic8uQ85HEy190Hr79ovOOdzUSEhISEhKeEcyhD0lISEhISEg4ljiq5HzmmWfiE5/4xNG8REJCQkJCwkmHpJwTEhISEhK2GBI5JyQkJCQkbDEkck5ISEhISNhiSOSckJCQkJCwxZDIOSEhISEhYYshkXNCQkJCQsIWQyLnhISEhISELYZEzgkJCQkJCVsMiZwTEhISEhK2GMjNe09aQkJCQkJCwnFDUs4JCQkJCQlbDImcExISEhISthgSOSckJCQkJGwxJHJOSEhISEjYYkjknJCQkJCQsMWQyDkhISEhIWGLIT/eFTgcWGtxxRVX4N5770VZlrjqqqvw4z/+48e7Wicl7rrrLnzkIx/B9ddfj4ceegh/9Ed/BCLCi170Ivzpn/4pjEl23ZFAVVX4kz/5Ezz66KOYTqd4xzvegRe+8IWpv48SmqbBrl278MADDyDLMlx99dVwzqX+Psp46qmn8OY3vxl/8zd/gzzPU39vAidUj3zxi1/EdDrFP/7jP+I973kPPvShDx3vKp2UuO6667Br1y5MJhMAwNVXX413v/vd+NjHPgbnHG655ZbjXMOTBzfddBO2b9+Oj33sY7juuutw5ZVXpv4+ivjyl78MAPj4xz+Od73rXbj66qtTfx9lVFWFyy+/HP1+H0AaTzaLE4qc77zzTrzmNa8BAFxwwQW4++67j3ONTk6cddZZuPbaa/3373znO7jwwgsBAK997Wtx2223Ha+qnXT4xV/8Rfze7/2e/55lWervo4g3vOENuPLKKwEAjz32GE499dTU30cZ11xzDX7jN34Dp59+OoA0nmwWJxQ5r66uYmlpyX/Psgx1XR/HGp2cuOiii5DnIeLhnAMRAQAWFxdx8ODB41W1kw6Li4tYWlrC6uoq3vWud+Hd73536u+jjDzP8b73vQ9XXnklLrrootTfRxE33HADTjnlFC+qgDSebBYnFDkvLS1hbW3Nf7fWtkgk4eggjgetra1hZWXlONbm5MPjjz+Ot7zlLbjkkktw8cUXp/4+Brjmmmtw880347LLLvPhGyD195HGP/3TP+G2227Dzp07cc899+B973sf9u7d6/en/l4fJxQ5v+IVr8Ctt94KAPjmN7+Jc8455zjX6NmBl770pfja174GALj11lvxMz/zM8e5RicP9uzZg9/+7d/GH/zBH+BXf/VXAaT+Ppq48cYb8dd//dcAgMFgACLCeeedl/r7KOEf/uEf8Pd///e4/vrr8ZKXvATXXHMNXvva16b+3gROqBdfaLb2fffdB+ccPvjBD+IFL3jB8a7WSYlHHnkEv//7v49PfOITeOCBB3DZZZehqiqcffbZuOqqq5Bl2fGu4kmBq666Cp/73Odw9tln+23vf//7cdVVV6X+PgoYDof44z/+Y+zZswd1XeNtb3sbXvCCF6Tn+xhg586duOKKK2CMSf29CZxQ5JyQkJCQkPBswAnl1k5ISEhISHg2IJFzQkJCQkLCFkMi54SEhISEhC2GRM4JCQkJCQlbDImcExISEhISthgSOScknKB45JFHcN555+GSSy7BpZdeil/6pV/Cb/3Wb+GJJ57YdBmXXHLJYV1z586dfo5qQkLC0UMi54SEExinn346PvWpT+HGG2/EZz7zGZx77rn48Ic/vOnzP/WpTx3F2iUkJDxTpLUvExJOIrzyla/En//5n+Nb3/oWrr76aozHY+zYsQN/9md/huc973nYuXMntm3bhvvvvx9/8Rd/gUsvvRT33nsvRqMRdu3ahXvvvRdEhLe+9a249NJLMZ1O8f73vx933303nvvc52Lfvn0AgCeeeALvfe97MRwOYYzBrl27cMEFFxzn1icknDxI5JyQcJKgqircfPPNOO+887Br1y781V/9Fc444wx89atfxWWXXYa/+7u/AwCce+65+OhHP9o699prr8WOHTvwL//yL9i7dy9+7dd+DS9+8YvxH//xHwCAz33uc3jwwQfxpje9CQDwyU9+Eq9//evxO7/zO7j11ltx5513JnJOSDiCSOSckHAC48knn/Rx4+l0ivPPPx+/8iu/gs9//vN4xzve4Y9bXV31n88///yZcm6//XZ88IMfBACccsop+IVf+AXccccduOOOO/Drv/7rAIDnP//5ePnLXw4AePWrX43f/d3fxT333IPXve51+M3f/M2j1saEhGcjEjknJJzA0JhzjO9973s488wz/famabBnzx6/X196H6O7iq9zDk3TgIha+/QtcD/90z+Nz3zmM/i3f/s3fPazn8U///M/42//9m+PWLsSEp7tSAlhCQknGc4++2zs378fX//61wHwa/ve+973bnjOq171Knzyk58EAOzduxe33HILLrzwQrz61a/Gpz/9aVhr8eijj+Ib3/gGAODDH/4wbrrpJvzyL/8yLr/8cnz3u989uo1KSHiWISnnhISTDGVZ4i//8i/xgQ98AJPJBEtLS7jmmms2POed73wnrrjiClx88cVomgZvf/vb8bKXvQznnHMO7r//frzxjW/Ec5/7XP+a1p07d+I973kPbrjhBmRZdsjyExISDg/prVQJCQkJCQlbDMmtnZCQkJCQsMWQyDkhISEhIWGLIZFzQkJCQkLCFkMi54SEhISEhC2GRM4JCQkJCQlbDImcExISEhISthgSOSckJCQkJGwxJHJOSEhISEjYYvj/Ikez13hjRsUAAAAASUVORK5CYII=\n",
"text/plain": [
"