{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Table of Contents](./table_of_contents.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multivariate Kalman Filters\n",
    "\n",
    "Filtering Multiple Random Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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   "source": [
    "#format the book\n",
    "import book_format\n",
    "book_format.set_style()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are now ready to study and implement the full, multivariate form of the Kalman filter. In the last chapter we learned how multivariate Gaussians express the correlation between multiple random variables, such as the position and velocity of an aircraft. We also learned how correlation between variables drastically improves the posterior. If we only roughly know position and velocity, but they are correlated, then our new estimate can be very accurate.\n",
    "\n",
    "I prefer that you develop an intuition for how these filters work through several worked examples. I'm going to gloss over many issues. Some things I show you will only work for special cases, others will be 'magical' - it will not be clear how I derived a certain result. If I started with rigorous, generalized equations you would be left scratching your head about what all these terms mean and how you might apply them to your problem. In later chapters I will provide a more rigorous mathematical foundation, and at that time I will have to either correct approximations that I made in this chapter or provide additional information that I did not cover here. \n",
    "\n",
    "To make this possible we will restrict ourselves to a subset of problems which we can describe with Newton's equations of motion. These filters are called *discretized continuous-time kinematic filters*. In the **Kalman Filter Math** chapter we will develop the math for non-Newtonian systems. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Newton's Equations of Motion\n",
    "\n",
    "Newton's equations of motion tells us that given a constant velocity $v$ of a system we can compute its position $x$ after time $t$ with:\n",
    "\n",
    "$$x = vt + x_0$$\n",
    "\n",
    "For example, if we start at position 13, our velocity is 10 m/s, and we travel for 12 seconds our final position is 133 ($10\\times 12 + 13$).\n",
    "\n",
    "We can incorporate constant acceleration with this equation\n",
    "\n",
    "$$x = \\frac{1}{2}at^2 + v_0t + x_0$$\n",
    "\n",
    "And if we assume constant jerk we get\n",
    "\n",
    "$$x = \\frac{1}{6}jt^3 +  \\frac{1}{2}a_0 t^2 + v_0 t + x_0$$\n",
    "\n",
    "These equations were generated by integrating a differential equation. Given a constant velocity v we can compute the distance traveled over time with the equation\n",
    "\n",
    "$$x = vt + x_0$$\n",
    "\n",
    "which we can derive with\n",
    "\n",
    "$$\\begin{aligned} v &= \\frac{dx}{dt}\\\\\n",
    "dx &= v\\, dt \\\\\n",
    "\\int_{x_0}^x\\, dx &= \\int_0^t v\\, dt\\\\\n",
    "x - x_0 &= vt - 0\\\\\n",
    "x &= vt + x_0\\end{aligned}$$\n",
    "\n",
    "\n",
    "When you design a Kalman filter you start with a system of differential equations that describe the dynamics of the system. Most systems of differential equations do not easily integrate in this way. We start with Newton's equation because we can integrate and get a closed form solution, which makes the Kalman filter easier to design. An added benefit is that Newton's equations are the right equations to use to track moving objects, one of the main uses of Kalman filters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kalman Filter Algorithm\n",
    "\n",
    "The algorithm is the same Bayesian filter algorithm that we have used in every chapter. The update step is slightly more complicated, but I will explain why when we get to it.\n",
    "\n",
    "**Initialization**\n",
    "\n",
    "    1. Initialize the state of the filter\n",
    "    2. Initialize our belief in the state\n",
    "    \n",
    "**Predict**\n",
    "\n",
    "    1. Use process model to predict state at the next time step\n",
    "    2. Adjust belief to account for the uncertainty in prediction    \n",
    "**Update**\n",
    "\n",
    "    1. Get a measurement and associated belief about its accuracy\n",
    "    2. Compute residual between estimated state and measurement\n",
    "    3. Compute scaling factor based on whether the measurement\n",
    "    or prediction is more accurate\n",
    "    4. set state between the prediction and measurement based \n",
    "    on scaling factor\n",
    "    5. update belief in the state based on how certain we are \n",
    "    in the measurement\n",
    "    \n",
    "As a reminder, here is a graphical depiction of the algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1100x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import kf_book.book_plots as book_plots\n",
    "book_plots.show_residual_chart()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The univariate Kalman filter represented the state with a univariate Gaussian. Naturally the multivariate Kalman filter will use a multivariate Gaussian for the state. We learned in the last chapter that multivariate Gaussians use a vector for the mean and a matrix for the covariances. That means that the Kalman filter needs to use linear algebra to perform the estimations.\n",
    "\n",
    "I don't want you to memorize these equations, but I have listed the univariate and multivariate equations below. They are quite similar.\n",
    "\n",
    "<u>**Predict**</u>\n",
    "\n",
    "$\\begin{array}{|l|l|l|}\n",
    "\\hline\n",
    "\\text{Univariate} & \\text{Univariate} & \\text{Multivariate}\\\\\n",
    "& \\text{(Kalman form)} & \\\\\n",
    "\\hline\n",
    "\\bar \\mu = \\mu + \\mu_{f_x} & \\bar x = x + dx & \\bar{\\mathbf x} = \\mathbf{Fx} + \\mathbf{Bu}\\\\\n",
    "\\bar\\sigma^2 = \\sigma_x^2 + \\sigma_{f_x}^2 & \\bar P = P + Q & \\bar{\\mathbf P} = \\mathbf{FPF}^\\mathsf T + \\mathbf Q \\\\\n",
    "\\hline\n",
    "\\end{array}$\n",
    "\n",
    "Without worrying about the specifics of the linear algebra, we can see that:\n",
    "\n",
    "$\\mathbf x,\\, \\mathbf P$ are the state mean and covariance. They correspond to $x$ and $\\sigma^2$.\n",
    "\n",
    "$\\mathbf F$ is the *state transition function*. When multiplied by $\\bf x$ it computes the prior. \n",
    "\n",
    "$\\mathbf Q$ is the process covariance. It corresponds to $\\sigma^2_{f_x}$.\n",
    "\n",
    "$\\mathbf B$ and $\\mathbf u$ are new to us. They let us model control inputs to the system.\n",
    "\n",
    "<u>**Update**</u>\n",
    "\n",
    "$\\begin{array}{|l|l|l|}\n",
    "\\hline\n",
    "\\text{Univariate} & \\text{Univariate} & \\text{Multivariate}\\\\\n",
    "& \\text{(Kalman form)} & \\\\\n",
    "\\hline\n",
    "& y = z - \\bar x & \\mathbf y = \\mathbf z - \\mathbf{H\\bar x} \\\\\n",
    "& K = \\frac{\\bar P}{\\bar P+R}&\n",
    "\\mathbf K = \\mathbf{\\bar{P}H}^\\mathsf T (\\mathbf{H\\bar{P}H}^\\mathsf T + \\mathbf R)^{-1} \\\\\n",
    "\\mu=\\frac{\\bar\\sigma^2\\, \\mu_z + \\sigma_z^2 \\, \\bar\\mu} {\\bar\\sigma^2 + \\sigma_z^2} & x = \\bar x + Ky & \\mathbf x = \\bar{\\mathbf x} + \\mathbf{Ky} \\\\\n",
    "\\sigma^2 = \\frac{\\sigma_1^2\\sigma_2^2}{\\sigma_1^2+\\sigma_2^2} & P = (1-K)\\bar P &\n",
    "\\mathbf P = (\\mathbf I - \\mathbf{KH})\\mathbf{\\bar{P}} \\\\\n",
    "\\hline\n",
    "\\end{array}$\n",
    "\n",
    "$\\mathbf H$ is the measurement function. We haven't seen this yet in this book and I'll explain it later. If you mentally remove $\\mathbf H$ from the equations, you should be able to see these equations are similar as well.\n",
    "\n",
    "$\\mathbf z,\\, \\mathbf R$ are the measurement mean and noise covariance. They correspond to $z$ and $\\sigma_z^2$ in the univariate filter (I've substituted $\\mu$ with $x$ for the univariate equations to make the notation as similar as possible).\n",
    "\n",
    "$\\mathbf y$ and $\\mathbf K$ are the residual and Kalman gain. \n",
    "\n",
    "The details will be different than the univariate filter because these are vectors and matrices, but the concepts are exactly the same: \n",
    "\n",
    "-  Use a Gaussian to represent our estimate of the state and error\n",
    "-  Use a Gaussian to represent the measurement and its error\n",
    "-  Use a Gaussian to represent the process model\n",
    "-  Use the process model to predict the next state (the prior)\n",
    "-  Form an estimate part way between the measurement and the prior\n",
    "\n",
    "Your job as a designer will be to design the state $\\left(\\mathbf x, \\mathbf P\\right)$, the process $\\left(\\mathbf F, \\mathbf Q\\right)$, the measurement $\\left(\\mathbf z, \\mathbf R\\right)$, and the  measurement function $\\mathbf H$. If the system has control inputs, such as a robot, you will also design $\\mathbf B$ and $\\mathbf u$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have programmed the equations of the Kalman filter into the `predict` and `update` functions in FilterPy. You will import them with:\n",
    "\n",
    "```python\n",
    "from filterpy.kalman import predict, update\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tracking a Dog\n",
    "\n",
    "Let's go back to our tried and true problem of tracking a dog. This time we will include the fundamental insight of the previous chapter and use *hidden variables* to improve our estimates. I could start with the math, but instead let's implement a filter, learning as we go. On the surface the math is different and perhaps more complicated than the previous chapters, but the ideas are all the same - we are just multiplying and adding Gaussians.\n",
    "\n",
    "We start by writing a simulation for the dog. The simulation will run for `count` steps, moving the dog forward approximately 1 meter for each step. At each step the velocity will vary according to the process variance `process_var`. After updating the position we compute a measurement with an assumed sensor variance of `z_var`. The function returns an NumPy array of the positions and another of the measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import numpy as np\n",
    "from numpy.random import randn\n",
    "\n",
    "def compute_dog_data(z_var, process_var, count=1, dt=1.):\n",
    "    \"returns track, measurements 1D ndarrays\"\n",
    "    x, vel = 0., 1.\n",
    "    z_std = math.sqrt(z_var) \n",
    "    p_std = math.sqrt(process_var)\n",
    "    xs, zs = [], []\n",
    "    for _ in range(count):\n",
    "        v = vel + (randn() * p_std)\n",
    "        x += v*dt        \n",
    "        xs.append(x)\n",
    "        zs.append(x + randn() * z_std)        \n",
    "    return np.array(xs), np.array(zs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predict Step\n",
    "\n",
    "For the prediction we need to design the state and covariance, the process model and the process noise, and optionally the control input. We'll take them in order."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design State Variable\n",
    "\n",
    "We previously tracked a dog in one dimension by using a Gaussian. The mean $(\\mu)$ represented the most likely position, and the variance ($\\sigma^2$) represented the probability distribution of the position. The position is the *state* of the system, and we call $\\mu$ the *state variable*. \n",
    "\n",
    "In this problem we will be tracking both the position and velocity of the dog. This requires us to use a multivariate Gaussian represented with the state vector $\\mathbf x$ and its corresponding covariance matrix $\\mathbf P$. \n",
    "\n",
    "State variables can either be *observed variables* - directly measured by a sensor, or *hidden variables* - inferred from the observed variables. For our dog tracking problem the sensor only reads position, so position is observed and velocity is hidden. We will learn how to track hidden variables soon.\n",
    "\n",
    "It is important to understand that tracking position and velocity is a design choice with implications and assumptions that we are not yet prepared to explore. For example, we could also track acceleration, or even jerk. For now, recall that in the last chapter we showed that including velocity in the covariance matrix resulted in much smaller variances in position. We will learn how the Kalman filter computes estimates for hidden variables later in this chapter. \n",
    "\n",
    "In the univariate chapter we represented the dog's position with a scalar value (e.g. $\\mu=3.27$). In the last chapter we learned to use a multivariate Gaussian for multiple variables. For example, if we wanted to specify a position of 10.0 m and a velocity of 4.5 m/s, we would write:\n",
    "\n",
    "$$\\mu = \\begin{bmatrix}10.0\\\\4.5\\end{bmatrix}$$\n",
    "\n",
    "The Kalman filter is implemented using linear algebra. We use an $n\\times 1$ matrix (called a *vector*) to store  $n$ state variables. For the dog tracking problem, we use $x$ to denote position, and the first derivative of $x$, $\\dot x$, for velocity. I use Newton's dot notation for derivatives; $\\dot x$ represents the first derivative of x with respect to t: $\\dot x = \\frac{dx}{dt}$. Kalman filter equations use $\\mathbf x$ for the state, so we define $\\mathbf x$ as:\n",
    "\n",
    "$$\\mathbf x =\\begin{bmatrix}x \\\\ \\dot x\\end{bmatrix}$$\n",
    "\n",
    "We use $\\mathbf x$ instead of $\\mu$, but recognize this is the mean of the multivariate Gaussian.\n",
    "\n",
    "Another way to write this is $\\mathbf x =\\begin{bmatrix}x & \\dot x\\end{bmatrix}^\\mathsf T$ because the transpose of a row vector is a column vector. This notation is easier to use in text because it takes less vertical space.\n",
    "\n",
    "$\\mathbf x$ and the position $x$ coincidentally have the same name. If we were tracking the dog in the y-axis we would write $\\mathbf x =\\begin{bmatrix}y & \\dot y\\end{bmatrix}^\\mathsf T$, not  $\\mathbf y =\\begin{bmatrix}y & \\dot y\\end{bmatrix}^\\mathsf T$. $\\mathbf x$ is the standard name for the state variable used in the Kalman filter literature and we will not vary it to give it a more meaningful name. This consistency in naming allows us to communicate with our peers.\n",
    "\n",
    "Let's code this. Initialization of `x` is as simple as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10. ],\n",
       "       [ 4.5]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([[10.0],\n",
    "              [4.5]])\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I often use the transpose in my code to turn a row matrix into a column vector, as I find it easier to type and read:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10. ],\n",
       "       [ 4.5]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([[10., 4.5]]).T\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, NumPy recognizes 1D arrays as vectors, so I can simplify this line to use a 1D array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10. ,  4.5])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([10.0, 4.5])\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All of the array elements have the same type, typically either `float` or `int`. If the list contains all `int`s then the created array will also have a data type of `int`, otherwise it will be `float`. I will often take advantage of this by only specifying one number as a floating point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array([1., 0, 0, 0, 0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are some examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[19.]\n",
      " [48.]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 2], [3, 4]])\n",
    "x = np.array([[10.0], [4.5]])\n",
    "\n",
    "# matrix multiply\n",
    "print(np.dot(A, x))\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Python 3.5+ we have the matrix multiplier @, where `np.dot(A, B) == A @ B`. It is somewhat less useful then you might realize because it requires both `A` and `B` to be arrays. It is entirely valid in the math in this book for some of these variables to be scalars, therefore the utility of `@` is often lost. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": [
     "raises-exception"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[19.]\n",
      " [48.]]\n",
      "\n",
      "[[19.]\n",
      " [48.]]\n",
      "\n",
      "[19. 48.]\n"
     ]
    }
   ],
   "source": [
    "# alternative matrix multiply)\n",
    "print(A @ x)\n",
    "print()\n",
    "\n",
    "x = np.array([[10.0, 4.5]]).T\n",
    "print(A @ x)\n",
    "print()\n",
    "\n",
    "x = np.array([10.0, 4.5])\n",
    "print(A @ x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last returns a 1D array, but I have written the Kalman filter class to be able to handle this. In retrospect that might lead to confusion, but it does work. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design State Covariance\n",
    "\n",
    "The other half of the state Gaussian is the covariance matrix $\\mathbf P$. In the univariate Kalman filter we specified an initial value for $\\sigma^2$, and then the filter took care of updating its value as measurements were added to the filter. The same thing happens in the multidimensional Kalman filter. We specify an initial value for $\\mathbf P$ and the filter updates it during each epoch.\n",
    "\n",
    "We need to set the variances to reasonable values. For example, we may choose $\\sigma_\\mathtt{pos}^2=500 m^2$ if we are quite uncertain about the initial position. Top speed for a dog is around 21 m/s, so in the absence of any other information about the velocity we can set $3\\sigma_\\mathtt{vel}=21$, or $\\sigma_\\mathtt{vel}^2=7^2=49$. \n",
    "\n",
    "In the last chapter we showed that the position and velocities are correlated. But how correlated are they for a dog? I have no idea. As we will see the filter computes this for us, so I initialize the covariances to zero. Of course, if you know the covariances you should use them.\n",
    "\n",
    "Recall that the diagonals of the covariance matrix contains the variance of each variable, and the off-diagonal elements contains the covariances. Thus we have:\n",
    "\n",
    "$$\n",
    "\\mathbf P = \\begin{bmatrix}500 & 0 \\\\ 0&49\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "We can use `numpy.diag`, which creates a diagonal matrix from the values for the diagonal. Recall from linear algebra that a diagonal matrix is one with zeros in the off-diagonal elements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[500.,   0.],\n",
       "       [  0.,  49.]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.diag([500., 49.])\n",
    "P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I could have written:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[500.,   0.],\n",
       "       [  0.,  49.]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.array([[500., 0.],\n",
    "              [0., 49.]])\n",
    "P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are done. We've expressed the state of the filter as a multivariate Gaussian and implemented it in code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Design the Process Model\n",
    "\n",
    "The next step is designing the *process model*. It is a mathematical model which describes the behavior of the system. The filter uses it to predict the state after a discrete time step. We do this with a set of equations that describe the dynamics of the system.\n",
    "\n",
    "In the univariate chapter we modeled the dog's motion with\n",
    "\n",
    "$$ x = v \\Delta t + x_0$$\n",
    "\n",
    "We implemented this as follows:\n",
    "\n",
    "```python\n",
    "def predict(pos, movement):\n",
    "    return gaussian(pos.mean + movement.mean, \n",
    "                    pos.var + movement.var)\n",
    "```\n",
    "\n",
    "We will do the same thing in this chapter, using multivariate Gaussians instead of univariate Gaussians. You might imagine this sort of implementation:\n",
    "\n",
    "$$ \\mathbf x = \\begin{bmatrix}5.4\\\\4.2\\end{bmatrix}, \\, \\, \n",
    "\\dot{\\mathbf x} =  \\begin{bmatrix}1.1\\\\0.\\end{bmatrix} \\\\\n",
    "\\mathbf x = \\dot{\\mathbf x}t + \\mathbf x$$\n",
    "\n",
    "But we need to generalize this. The Kalman filter equations work with any linear system, not just Newtonian ones. Maybe the system you are filtering is the plumbing system in a chemical plant, and the flow in a given pipe is determined by a linear combination of the settings of different valves. \n",
    "\n",
    "$$\\mathtt{pipe_1} = 0.134(\\mathtt{valve}_1) + 0.41(\\mathtt{valve}_2 - \\mathtt{valve}_3) + 1.34$$\n",
    "$$\\mathtt{pipe_2} = 0.210(\\mathtt{valve}_2) - 0.62(\\mathtt{valve}_1 - \\mathtt{valve}_5) + 1.86$$\n",
    "\n",
    "Linear algebra has a powerful way to express systems of equations. Take this system\n",
    "\n",
    "$$\\begin{cases}\n",
    "2x+3y=8\\\\4x-y=2\n",
    "\\end{cases}$$\n",
    "\n",
    "We can put this in matrix form by writing:\n",
    "\n",
    "$$\\begin{bmatrix}2& 3 \\\\ 4&-1\\end{bmatrix} \\begin{bmatrix}x\\\\y\\end{bmatrix} = \\begin{bmatrix}8\\\\2\\end{bmatrix}$$\n",
    "\n",
    "If you perform the [matrix multiplication](https://en.wikipedia.org/wiki/Matrix_multiplication#General_definition_of_the_matrix_product) in this equation the result will be the two equations above. In linear algebra we would write this as $\\mathbf{Ax}=\\mathbf B$, where\n",
    "\n",
    "$$\\mathbf{A} = \\begin{bmatrix}2& 3 \\\\ 4&-1\\end{bmatrix},\\, \\mathbf x = \\begin{bmatrix}x\\\\y\\end{bmatrix}, \\mathbf B=\\begin{bmatrix}8\\\\2\\end{bmatrix}$$\n",
    "\n",
    "And then we can use the SciPy's `linalg` package to solve for $\\mathbf x$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.],\n",
       "       [2.]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.linalg import solve\n",
    "A = np.array([[2, 3],[4, -1]])\n",
    "b = np.array([[8], [2]])\n",
    "x = solve(A, b)\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use the process model to perform the *innovation*, because the equations tell us what the next state will be given the current state. Kalman filters implement this using this linear equation, where $\\mathbf{\\bar x}$ is the *prior*, or predicted state:\n",
    "\n",
    "$$\\mathbf{\\bar x} = \\mathbf{Fx}$$\n",
    "\n",
    "which we can make explicit as\n",
    "\n",
    "$$\\begin{bmatrix} \\bar x \\\\ \\dot{\\bar x}\\end{bmatrix} = \\begin{bmatrix}? & ? \\\\? & ?\\end{bmatrix}\\begin{bmatrix}x\\\\\\dot x\\end{bmatrix}$$\n",
    "\n",
    "Our job as Kalman filters designers is to specify $\\mathbf F$ such that $\\bar{\\mathbf x}  = \\mathbf{Fx}$ performs the innovation (prediction) for our system. To do this we need one equation for each state variable. In our problem $\\mathbf x = \\begin{bmatrix}x & \\dot x\\end{bmatrix}^\\mathtt{T}$, so we need one equation to compute the position $x$ and another to compute the velocity $\\dot x$ . We already know the equation for the position innovation:\n",
    "\n",
    "$$\\bar x = x + \\dot x \\Delta t$$\n",
    "\n",
    "What is our equation for velocity? We have no predictive model for how our dog's velocity will change over time. In this case we assume that it remains constant between innovations. Of course this is not exactly true, but so long as the velocity doesn't change too much over each innovation you will see that the filter performs very well. So we say\n",
    "\n",
    "$$\\bar{\\dot x} = \\dot x$$\n",
    "\n",
    "This gives us the process model for our system \n",
    "\n",
    "$$\\begin{cases}\n",
    "\\begin{aligned}\n",
    "\\bar x &= x + \\dot x \\Delta t \\\\\n",
    "\\bar{\\dot x} &= \\dot x\n",
    "\\end{aligned}\n",
    "\\end{cases}$$\n",
    "\n",
    "This correctly has one equation for each variable in the state, isolated on the left hand side. We need to express this set of equations in the form $\\bar{\\mathbf x}  = \\mathbf{Fx}$. Rearranging terms makes it easier to see what to do.\n",
    "\n",
    "$$\\begin{cases}\n",
    "\\begin{aligned}\n",
    "\\bar x &= 1x + &\\Delta t\\, \\dot x \\\\\n",
    "\\bar{\\dot x} &=0x + &1\\, \\dot x\n",
    "\\end{aligned}\n",
    "\\end{cases}$$\n",
    "\n",
    "We can rewrite this in matrix form as\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\begin{bmatrix}\\bar x \\\\ \\bar{\\dot x}\\end{bmatrix} &= \\begin{bmatrix}1&\\Delta t  \\\\ 0&1\\end{bmatrix}  \\begin{bmatrix}x \\\\ \\dot x\\end{bmatrix}\\\\\n",
    "\\mathbf{\\bar x} &= \\mathbf{Fx}\n",
    "\\end{aligned}$$\n",
    "\n",
    "$\\mathbf F$ is called the *state transition function* or the *state transition matrix*. In later chapters it will be a true function, not a  matrix, so calling it a function is a bit more general."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1. , 0.1],\n",
       "       [0. , 1. ]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = 0.1\n",
    "F = np.array([[1, dt],\n",
    "              [0, 1]])\n",
    "F"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's test this! FilterPy has a `predict` method that performs the prediction by computing $\\mathbf{\\bar x} = \\mathbf{Fx}$. Let's call it and see what happens. We've set the position to 10.0 and the velocity to  4.5 meter/sec. We've defined `dt = 0.1`, which means the time step is 0.1 seconds, so we expect the new position to be 10.45 meters after the innovation. The velocity should be unchanged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x = [10.45  4.5 ]\n"
     ]
    }
   ],
   "source": [
    "from filterpy.kalman import predict\n",
    "\n",
    "x = np.array([10.0, 4.5])\n",
    "P = np.diag([500, 49])\n",
    "F = np.array([[1, dt], [0, 1]])\n",
    "\n",
    "# Q is the process noise\n",
    "x, P = predict(x=x, P=P, F=F, Q=0)\n",
    "print('x =', x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This worked. If we call `predict()` several times in a row the value will be updated each time. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x = [10.9  4.5]\n",
      "x = [11.35  4.5 ]\n",
      "x = [11.8  4.5]\n",
      "x = [12.25  4.5 ]\n"
     ]
    }
   ],
   "source": [
    "for _ in range(4):\n",
    "    x, P = predict(x=x, P=P, F=F, Q=0)\n",
    "    print('x =', x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`predict()` computes both the mean and covariance of the innovation. This is the value of $\\mathbf P$ after five innovations (predictions), which we denote $\\mathbf{\\bar P}$ in the Kalman filter equations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[512.25  24.5 ]\n",
      " [ 24.5   49.  ]]\n"
     ]
    }
   ],
   "source": [
    "print(P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspecting the diagonals shows us that the position variance got larger. We've performed five prediction steps with no measurements, and our uncertainty grew. The off-diagonal elements became non-zero - the Kalman filter detected a correlation between position and velocity! The variance of the velocity did not change.\n",
    "\n",
    "Here I plot the covariance before and after the prediction. The initial value is in solid red, and the prior (prediction) is in dashed black. I've altered the covariance and time step to better illustrate the change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from filterpy.stats import plot_covariance_ellipse\n",
    "\n",
    "dt = 0.3\n",
    "F = np.array([[1, dt], [0, 1]])\n",
    "x = np.array([10.0, 4.5])\n",
    "P = np.diag([500, 500])\n",
    "plot_covariance_ellipse(x, P, edgecolor='r')\n",
    "x, P = predict(x, P, F, Q=0)\n",
    "plot_covariance_ellipse(x, P, edgecolor='k', ls='dashed')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that the center of the ellipse shifted by a small amount (from 10 to 11.35) because the position changed. The ellipse also elongated, showing the correlation between position and velocity. How does the filter compute new values for $\\mathbf{\\bar P}$, and what is it based on? Note that I set the process noise `Q` to zero each time, so it is not due to me adding noise. It's a little to early to discuss this, but recall that in every filter so far the predict step entailed a loss of information. The same is true here. I will give you the details once we have covered a bit more ground."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design Process Noise\n",
    "\n",
    "A quick review on *process noise*. A car is driving along the road with the cruise control on; it should travel at a constant speed. We model this with $\\bar x_k=\\dot x_k\\Delta t + x_{k-1}$. However, it is affected by a number of unknown factors. The cruise control cannot perfectly maintain a constant velocity. Winds affect the car, as do hills and potholes. Passengers roll down windows, changing the drag profile of the car. \n",
    "\n",
    "We can model this system with the differential equation\n",
    "\n",
    "$$\\dot{\\mathbf x} = f(\\mathbf x) + w$$\n",
    "\n",
    "where $f(\\mathbf x)$ models the state transition and $w$ is *white process noise*.\n",
    "\n",
    "We will learn how to go from a set of differential equations to the Kalman filter matrices in the **Kalman Filter Math** chapter. In this chapter we take advantage of the fact that Newton already derived the equations of motion for us. For now you just need to know that we account for the  noise in the system by adding a process noise covariance matrix $\\mathbf Q$ to the covariance $\\mathbf P$. We do not add anything to $\\mathbf x$ because the noise is *white* - which means that the mean of the noise will be 0. If the mean is 0, $\\mathbf x$ will not change.\n",
    "\n",
    "The univariate Kalman filter used `variance = variance + process_noise` to compute the variance for the variance of the prediction step. The multivariate Kalman filter does the same, essentially `P = P + Q`. I say 'essentially' because there are other terms unrelated to noise in the covariance equation that we will see later.\n",
    "\n",
    "Deriving the process noise matrix can be quite demanding, and we will put it off until the Kalman math chapter. For now know that $\\mathbf Q$ equals the expected value of the white noise $w$, computed as $\\mathbf Q = \\mathbb E[\\mathbf{ww}^\\mathsf T]$. In this chapter we will focus on building an intuitive understanding on how modifying this matrix alters the behavior of the filter.\n",
    "\n",
    "FilterPy provides functions which compute $\\mathbf Q$ for the kinematic problems of this chapter. `Q_discrete_white_noise` takes 3 parameters. `dim`, which specifies the dimension of the matrix, `dt`, which is the time step in seconds, and `var`, the variance in the noise. Briefly, it discretizes the noise over the given time period under assumptions that we will discuss later. This code computes $\\mathbf Q$ for white noise with a variance of 2.35 and a time step of 1 seconds:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.588 1.175]\n",
      " [1.175 2.35 ]]\n"
     ]
    }
   ],
   "source": [
    "from filterpy.common import Q_discrete_white_noise\n",
    "Q = Q_discrete_white_noise(dim=2, dt=1., var=2.35)\n",
    "print(Q)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Control Function\n",
    "\n",
    "The Kalman filter does not just filter data, it allows us to incorporate the control inputs of systems like robots and airplanes. Suppose we are controlling a robot. At each time step we would send steering and velocity signals to the robot based on its current position vs desired position. Kalman filter equations incorporate that knowledge into the filter equations, creating a predicted position based both on current velocity and control inputs to the drive motors. Remember, we *never* throw information away.\n",
    "\n",
    "For a linear system the effect of control inputs can be described as a set of linear equations, which we can express with linear algebra as\n",
    "\n",
    "$$\\Delta\\mathbf x = \\mathbf{Bu}$$\n",
    "\n",
    "Here $\\mathbf u$ is the *control input*, and $\\mathbf B$ is the *control input model* or *control function*. For example, $\\mathbf u$ might be a voltage controlling how fast the wheel's motor turns, and multiplying by $\\mathbf B$ yields $\\Delta[\\begin{smallmatrix}x\\\\\\dot x\\end{smallmatrix}]$. In other words, it must compute how much $\\mathbf x$ changes due to the control input.\n",
    "\n",
    "Therefore the complete Kalman filter equation for the prior mean is\n",
    "\n",
    "$$\\mathbf{\\bar x} = \\mathbf{Fx} + \\mathbf{Bu}$$\n",
    "\n",
    "and this is the equation that is computed when you call `KalmanFilter.predict()`.\n",
    "\n",
    "Your dog may be trained to respond to voice commands. All available evidence suggests that my dog has no control inputs whatsoever, so I set $\\mathbf B$ to zero. In Python we write:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x = [12.7  4.5]\n",
      "P = [[680.587 301.175]\n",
      " [301.175 502.35 ]]\n"
     ]
    }
   ],
   "source": [
    "B = 0.  # my dog doesn't listen to me!\n",
    "u = 0\n",
    "x, P = predict(x, P, F, Q, B, u)\n",
    "print('x =', x)\n",
    "print('P =', P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setting $\\mathbf B$ and $\\mathbf u$ to zero is not necessary since `predict` uses 0 for their default value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict(x, P, F, Q)[0] == predict(x, P, F, Q, B, u)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ True,  True],\n",
       "       [ True,  True]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict(x, P, F, Q)[1] == predict(x, P, F, Q, B, u)[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "#### Prediction: Summary\n",
    "\n",
    "Your job as a designer is to specify the matrices for\n",
    "\n",
    "* $\\mathbf x$, $\\mathbf P$: the state and covariance\n",
    "* $\\mathbf F$,  $\\mathbf Q$: the process model and noise covariance\n",
    "* $\\mathbf{B,u}$: Optionally, the control input and function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Update Step\n",
    "\n",
    "Now we can implement the update step of the filter. You only have to supply two more matrices, and they are easy to understand. \n",
    "\n",
    "### Design the Measurement Function\n",
    "\n",
    "The Kalman filter computes the update step in what we call *measurement space*. We mostly ignored this issue in the univariate chapter because of the complication it adds. We tracked our dog's position using a sensor that reported his position. Computing the *residual* was easy - subtract the filter's predicted position from the measurement:\n",
    "\n",
    "$$ \\mathtt{residual} = \\mathtt{measured\\, \\, position} - \\mathtt{predicted\\, \\, position}$$\n",
    "\n",
    "We need to compute the residual because we scale it by the Kalman gain to get the new estimate.\n",
    "\n",
    "What would happen if we were trying to track temperature using a thermometer that outputs a voltage corresponding to the temperature reading? The equation for the residual computation would be meaningless; you can't subtract a temperature from a voltage.\n",
    "\n",
    "$$ \\mathtt{residual} = \\mathtt{voltage} - \\mathtt{temperature}\\;\\;\\;(NONSENSE!)$$\n",
    "\n",
    "\n",
    "We need to convert the temperature into a voltage so we can perform the subtraction. For the thermometer we might write:\n",
    "\n",
    "```python\n",
    "CELSIUS_TO_VOLTS = 0.21475\n",
    "residual = voltage - (CELSIUS_TO_VOLTS * predicted_temperature)\n",
    "```\n",
    "    \n",
    "The Kalman filter generalizes this problem by having you supply a *measurement function* that converts a state into a measurement. \n",
    "\n",
    "Why are we working in measurement space? Why not work in state space by converting the voltage into a temperature, allowing the residual to be a difference in temperature?\n",
    "\n",
    "We cannot do that because most measurements are not *invertible*. The state for the tracking problem contains the hidden variable $\\dot x$. There is no way to convert a measurement of position into a state containing velocity. On the other hand, it is trivial to convert a state containing position and velocity into a equivalent \"measurement\" containing only position. We have to work in measurement space to make the computation of the residual possible.\n",
    "\n",
    "Both the measurement $\\mathbf z$ and state $\\mathbf x$ are vectors so we need to use a matrix to perform the conversion. The Kalman filter equation that performs this step is:\n",
    "\n",
    "$$\\mathbf y = \\mathbf z - \\mathbf{H \\bar x}$$\n",
    "\n",
    "where $\\mathbf y$ is the residual, $\\mathbf{\\bar x}$ is the prior, $\\mathbf z$ is the measurement, and $\\mathbf H$ is the measurement function. So we take the prior, convert it to a measurement by multiplying it with $\\mathbf H$, and subtract that from the measurement. This gives us the difference between our prediction and measurement in measurement space!\n",
    "<img src=\"./figs/residual_chart_with_h.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to design $\\mathbf H$ so that $\\mathbf{H\\bar x}$ yields a measurement. For this problem we have a sensor that measures position, so $\\mathbf z$ will be a one variable vector:\n",
    "\n",
    "$$\\mathbf z = \\begin{bmatrix}z\\end{bmatrix}$$\n",
    "\n",
    "The residual equation will have the form\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\textbf{y} &= \\mathbf z - \\mathbf{H\\bar x}  \\\\\n",
    "\\begin{bmatrix}y \\end{bmatrix} &= \\begin{bmatrix}z\\end{bmatrix} - \\begin{bmatrix}?&?\\end{bmatrix} \\begin{bmatrix}x \\\\ \\dot x\\end{bmatrix}\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "$\\mathbf H$ has to be a 1x2 matrix for $\\mathbf{Hx}$ to be 1x1. Recall that multiplying matrices $m\\times n$ by $n\\times p$ yields a $m\\times p$ matrix.\n",
    "\n",
    "We will want to multiply the position $x$ by 1 to get the corresponding measurement of the position. We do not need to use velocity to find the corresponding measurement so we multiply  $\\dot x$ by 0.\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\textbf{y} &= \\mathbf z - \\begin{bmatrix}1&0\\end{bmatrix} \\begin{bmatrix}x \\\\ \\dot x\\end{bmatrix} \\\\\n",
    "&= [z] - [x]\n",
    "\\end{aligned}$$\n",
    "\n",
    "And so, for our Kalman filter we set\n",
    "\n",
    "$$\\mathbf H=\\begin{bmatrix}1&0\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "H = np.array([[1., 0.]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have designed the majority of our Kalman filter. All that is left is to model the noise in the sensors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Design the Measurement\n",
    "\n",
    "The measurement is implemented with $\\mathbf z$, the measurement mean, and $\\mathbf R$, the measurement covariance. \n",
    "\n",
    "$\\mathbf z$ is easy. it contains the measurement(s) as a vector. We have only one measurement, so we have:\n",
    "\n",
    "$$\\mathbf z = \\begin{bmatrix}z\\end{bmatrix}$$\n",
    "\n",
    "If we have two sensors or measurements we'd have:\n",
    "\n",
    "$$\\mathbf z = \\begin{bmatrix}z_1 \\\\ z_2\\end{bmatrix}$$\n",
    "\n",
    "\n",
    "The *measurement noise matrix* models the noise in our sensors as a covariance matrix. In practice this can be difficult. A complicated system may have many sensors, the correlation between them might not be clear, and usually their noise is not a pure Gaussian. For example, a sensor might be biased to read high if the temperature is high, and so the noise is not distributed equally on both sides of the mean. We will learn to deal with these problems later.\n",
    "\n",
    "The Kalman filter equations uses a covariance matrix $\\mathbf R$ for the measurement noise. The matrix will have dimension $m{\\times}m$, where $m$ is the number of sensors. It is a covariance matrix to account for correlations between the sensors. We have only 1 sensor so $\\mathbf R$ is:\n",
    "\n",
    "$$\\mathbf R = \\begin{bmatrix}\\sigma^2_z\\end{bmatrix}$$\n",
    "\n",
    "If $\\sigma^2_z$ is 5 meters squared we'd have $\\mathbf R = \\begin{bmatrix}5\\end{bmatrix}$. \n",
    "\n",
    "If we had two position sensors, the first with a variance of 5 m$^2$, the second with a variance of 3 m$^2$, we would write\n",
    "\n",
    "$$\\mathbf R = \\begin{bmatrix}5&0\\\\0&3\\end{bmatrix}$$\n",
    "\n",
    "We put the variances on the diagonal because this is a *covariance* matrix, where the variances lie on the diagonal, and the covariances, if any, lie in the off-diagonal elements. Here we assume there is no correlation in the noise between the two sensors, so the covariances are 0.\n",
    "\n",
    "For our problem we only have one sensor, so we can implement this as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "R = np.array([[5.]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We perform the update by calling `update`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x = [ 1.085 -0.64 ]\n"
     ]
    }
   ],
   "source": [
    "from filterpy.kalman import update\n",
    "z = 1.\n",
    "x, P = update(x, P, z, R, H)\n",
    "print('x =', x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Keeping track of all of these variables is burdensome, so FilterPy also implements the filter with the class `KalmanFilter`. I will use the class in the rest of this book, but I wanted you to see the procedural form of these functions since I know some of you are not fans of object oriented programming."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing the Kalman Filter\n",
    "\n",
    "I've given you all of the code for the filter, but now let's collect it in one place. First we construct a `KalmanFilter` object. We have to specify the number of variables in the state with the `dim_x` parameter, and the number of measurements with `dim_z`. We have two random variables in the state and one measurement, so we write:\n",
    "\n",
    "```python\n",
    "from filterpy.kalman import KalmanFilter\n",
    "dog_filter = KalmanFilter(dim_x=2, dim_z=1)\n",
    "```\n",
    "\n",
    "This creates an object with default values for all the Kalman filter matrices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x =  [[0. 0.]]\n",
      "R =  [[1.]]\n",
      "Q = \n",
      " [[1. 0.]\n",
      " [0. 1.]]\n"
     ]
    }
   ],
   "source": [
    "from filterpy.kalman import KalmanFilter\n",
    "dog_filter = KalmanFilter(dim_x=2, dim_z=1)\n",
    "print('x = ', dog_filter.x.T)\n",
    "print('R = ', dog_filter.R)\n",
    "print('Q = \\n', dog_filter.Q)\n",
    "# etc..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we initialize the filter's matrices and vectors with values valid for our problem. I've put this in a function to allow you to specify different initial values for `R`, `P`, and `Q` and put it in a helper function. We will be creating and running many of these filters, and this saves us a lot of headaches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from filterpy.kalman import KalmanFilter\n",
    "from filterpy.common import Q_discrete_white_noise\n",
    "\n",
    "def pos_vel_filter(x, P, R, Q=0., dt=1.0):\n",
    "    \"\"\" Returns a KalmanFilter which implements a\n",
    "    constant velocity model for a state [x dx].T\n",
    "    \"\"\"\n",
    "    \n",
    "    kf = KalmanFilter(dim_x=2, dim_z=1)\n",
    "    kf.x = np.array([x[0], x[1]]) # location and velocity\n",
    "    kf.F = np.array([[1., dt],\n",
    "                     [0.,  1.]])  # state transition matrix\n",
    "    kf.H = np.array([[1., 0]])    # Measurement function\n",
    "    kf.R *= R                     # measurement uncertainty\n",
    "    if np.isscalar(P):\n",
    "        kf.P *= P                 # covariance matrix \n",
    "    else:\n",
    "        kf.P[:] = P               # [:] makes deep copy\n",
    "    if np.isscalar(Q):\n",
    "        kf.Q = Q_discrete_white_noise(dim=2, dt=dt, var=Q)\n",
    "    else:\n",
    "        kf.Q[:] = Q\n",
    "    return kf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`KalmanFilter` initializes `R`, `P`, and `Q` to the identity matrix, so `kf.P *= P` is one way to quickly assign all of the diagonal elements to the same scalar value. Now we create the filter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = .1\n",
    "x = np.array([0., 0.]) \n",
    "kf = pos_vel_filter(x, P=500, R=5, Q=0.1, dt=dt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can inspect the current values of all attributes of the filter by entering the variable on the command line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KalmanFilter object\n",
       "dim_x = 2\n",
       "dim_z = 1\n",
       "dim_u = 0\n",
       "x = [0. 0.]\n",
       "P = [[500.   0.]\n",
       "     [  0. 500.]]\n",
       "x_prior = [[0. 0.]].T\n",
       "P_prior = [[1. 0.]\n",
       "           [0. 1.]]\n",
       "x_post = [[0. 0.]].T\n",
       "P_post = [[1. 0.]\n",
       "          [0. 1.]]\n",
       "F = [[1.  0.1]\n",
       "     [0.  1. ]]\n",
       "Q = [[0.    0.   ]\n",
       "     [0.    0.001]]\n",
       "R = [[5.]]\n",
       "H = [[1. 0.]]\n",
       "K = [[0. 0.]].T\n",
       "y = [[0.]]\n",
       "S = [[0.]]\n",
       "SI = [[0.]]\n",
       "M = [[0.]]\n",
       "B = None\n",
       "z = [[None]]\n",
       "log-likelihood = -708.3964185322641\n",
       "likelihood = 2.2250738585072014e-308\n",
       "mahalanobis = 0.0\n",
       "alpha = 1.0\n",
       "inv = <function inv at 0x00000268CA22DB80>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All that is left is to write the code to run the Kalman filter. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kf_book.mkf_internal import plot_track\n",
    "\n",
    "def run(x0=(0.,0.), P=500, R=0, Q=0, dt=1.0, \n",
    "        track=None, zs=None,\n",
    "        count=0, do_plot=True, **kwargs):\n",
    "    \"\"\"\n",
    "    track is the actual position of the dog, zs are the \n",
    "    corresponding measurements. \n",
    "    \"\"\"\n",
    "\n",
    "    # Simulate dog if no data provided. \n",
    "    if zs is None:\n",
    "        track, zs = compute_dog_data(R, Q, count)\n",
    "\n",
    "    # create the Kalman filter\n",
    "    kf = pos_vel_filter(x0, R=R, P=P, Q=Q, dt=dt)  \n",
    "\n",
    "    # run the kalman filter and store the results\n",
    "    xs, cov = [], []\n",
    "    for z in zs:\n",
    "        kf.predict()\n",
    "        kf.update(z)\n",
    "        xs.append(kf.x)\n",
    "        cov.append(kf.P)\n",
    "\n",
    "    xs, cov = np.array(xs), np.array(cov)\n",
    "    if do_plot:\n",
    "        plot_track(xs[:, 0], track, zs, cov, **kwargs)\n",
    "    return xs, cov"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the complete code for the filter, and most of it is boilerplate. I've made it flexible enough to support several uses in this chapter, so it is a bit verbose. Let's work through it line by line. \n",
    "\n",
    "The first lines checks to see if you provided it with measurement data in `zs`. If not, it creates the data using the `compute_dog_data` function we wrote earlier.\n",
    "\n",
    "The next lines uses our helper function to create a Kalman filter.\n",
    "\n",
    "```python\n",
    "# create the Kalman filter\n",
    " kf = pos_vel_filter(x0, R=R, P=P, Q=Q, dt=dt)\n",
    "```\n",
    "\n",
    "All we need to do is perform the update and predict steps of the Kalman filter for each measurement. The `KalmanFilter` class provides the two methods `update()` and `predict()` for this purpose. `update()` performs the measurement update step of the Kalman filter, and so it takes a variable containing the sensor measurement. \n",
    "\n",
    "Absent the work of storing the results, the loop reads:\n",
    "\n",
    "```python\n",
    "    for z in zs:\n",
    "        kf.predict()\n",
    "        kf.update(z)\n",
    "```\n",
    "\n",
    "Each call to `predict` and `update` modifies the state variables `x` and `P`. Therefore, after the call to `predict`, `kf.x` contains the prior. After the call to update, `kf.x` contains the posterior. The states and covariances are saved in `xs` and `cov`.\n",
    "\n",
    "It really cannot get much simpler than that. As we tackle more complicated problems this code will remain largely the same; all of the work goes into setting up the `KalmanFilter` matrices; executing the filter is trivial.\n",
    "\n",
    "The rest of the code optionally plots the results and then returns the saved states and covariances.\n",
    "\n",
    "Let's run it. We have 50 measurements with a noise variance of 10 and a process variance of 0.01."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fqvvvGavxv2iva2lCCCGEEOKWcPGms3bt2nh6elZJ02g0NGjQgPT0dBRFoaSkBHd39xtRzT9dRUUFFRUVBAYGkp5+BqMRvLzgjjsa4uV1ltBQE3b7KTQaDQ88MJCvvnqLykoTBQUF6PXOwGvt2l2sWLGVnTtT+O9/38bLy8NVfsOG8a7XGzfuZejQ7q73Go2G9PRleHr+9rk1We3klJjJLTORU2Imp9RMdnElm3Ync/h0BmUm23U8KxJECCGEEEKIKwgNDSUzM5OUlBRyc3OpUaOGK62yspLt27cDoNPp8PPzu1HVvO4qKys5fvw4deokotPZ2bVrFXl5mQwe3IHIyAJq1gSdDs6ePURwsC/Bwb6ufQ8ePEJ+vgl3d/D09HJtnz9/NR9//AMAe/YcoVOnZq60Nm0a0KFDE9q3b0Tv3m0BUBQFkxUKKxwUVegoyjZz4lQ257KL8ImIp6DsJDmlNnJKTeSWOgOG0l8NEjwhKBGD+fq2FkkQIYQQQgghqrn77rt56623sFgsjBw5klmzZhESEkJhYSETJkwgPz8fgDvuuAODwXCDa3vtFEVBpVIBsHPnTry93UlMjMRkOsfu3UsJDc2jRg0fmjb1R60OBEzUqlWT2rUjSMvIYuspK/e9t58MewQncmw4rBZsFg1Kly8xqy0c8fei/wf5GLSQHzqQGgMTUWxm3tyoYW1xCUZnIwXFFQqJ908ntcLBrh0KRetzKKxwYKo0YT53FH1IHBqjJ5acDGwlubjHBQFFV/xMBq2aIG8DQV5Gsk4f48i+ndjLC3CUFxIV6H1dz58EEUIIIYQQoppHHnmETz/9lNLSUlasWEFkZCQJCQmcOHECs9kMOFshnnrqqRtc09+mKArFxcUYjUaMRiOpqUfYuXMzw4f3RaWqxGI5gtVqBMz4+cGoUd1dMyV5erqjKApHzlXy6Y+pnIp4guK4SFRaI2vOAVxoAdDo0bjpAXAAOWbISbdeqIEv7vGtAThUAYe2VVxWNwcqlfNY5nNHURQFY0QdVBodarsZf6OaoCBP3MMaUJRzjsKsFBRzGSE+bvTo0Iq2TeoT5G0kyNuAl0GLSqWipKSE8PCelJWVodfrWbZsGY0bNyYw8Ifrdk4liBBCCCGEENVERUWxZMkS+vfvT2lpKTabjZSUFFe6Xq9n9uzZNG7c+AbW8tedO3eOyspK4uJisdtLmT//C9q3b0hiYgiBgTk0aOCFw5GORqOhXbt6Vfa12x2czyvnYI6ODalmNqaaOVfkAILBMxgVoDIXoM/fiy5/L9qiI+TlqSgp1+Pp48aTkx+iRatWmKwKJpuC2Qomm4LJqlBabsJkduDQGijKzSczZT+de91OsH8NCs9542XQ0axxA3zd9Xjob0elUjF79mzuv/9+TCaTq46HgNUfwIABA5g9ezbuF5s2cK7jcXFNilGjRtGtWzdXy9H1IkGEEEIIIYS4os6dO5OSksKHH37Id999R3Z2Nv7+/gwePJjx48cTHx//24X8iSwWCw6HA6PRSH5+Pps3b6R797a4u8OZM9soLMwmLq4VWi3061cfPz9PwIy/vw/+/j6uchRFodSssGr7GV76ZCt5unAMYQkol01kqteAknucnAObqDy9l2/eu5ulS3/mcJZzYblIfx097urJvfeOpGbNmq79iopKycsrIi4uEjAyZ85qatVKoGXLllRWQmpqbRISEjAajdDg0n4X/fTTT9xzzz0oinLFc7B48WJGjBjBDz/84OqeVVBQ4Er/s4I8CSKEEEIIIcSvioyM5PXXX+f111+/pv0URWHnzp3Mnz+f3NxcAgMDGTp0KC1atHDd7P4as9nMli1bKCgoIDg4mNatW6PVasnNzSU3N5ekpDqAmQULviYuLowWLRIxGPLx8srGbj8KeNC4WRSFlVEkZ1jJL3OQV+ZG/lEzGblFHDtbwLk8E25+gVTYdeSXObDYAdwhuht6QAFqBmroEG+gY7yBljV1rPrpKI5erWnV6kFCQwO5887BFBUVUVlZiZ+fH0ajEbPZwqZN+0hKiicgIJyMjFL27MmiVq2+qFRaunQJwMvLC3DHzQ0aNmz4P8/h5MmTXQHEiBEjeOGFFwgJCWHu3Lk89thjlJaWsmjRInbu3EnLli0BCA4OdpWxceNGHnrooWv67q6GBBFCCCGEEOK6ys7O5q677mL9+vVVts+cOZOOHTsyd+7cKje6F9ntdl577TXef/99cnNzAVCroVatEKZMeZSmTRuSkpJCUpIJUOjQIZIim4HVh7PZd6qY9fsUTv/3MCZtIA6N2/+ooY/zTwE4RzBc2Oqmoih1N+rsI7SL0/HNG49W2at//06u15WVJtzcjPj6+nLkSDpHjxbQuXNXdDojubnpVFbWBCJITIwmKamDa9xDSEjIVZ/Hffv2kZycDEDTpk35+uuvXQHYfffdh91uZ+zYsQD85z//cQUR3bt3x9/fn4KCAr7//nu6detG3759r/q4V0OCCCGEEEIIcd2UlZXRrVs3Dh06dMX0DRs20LVrV7Zv346npyfFxcWcPn2aBg3qM2bMMH74YR4GA8TFgdEIZjMY3bL5vy/epU3mMOq2uZ3H5haSmm3jZK4Dk7USqLxQehRcNlGUYreitZUSG+ZDWIAbgR5qrGWFfP3p99gri+nYsjbTnh9JgKeaAA81bnoVpaWd8PLqU63eeXlFaLUafH29yMgoYvnyHdx99914eYVQo4Y3VqsNCEethkGDhrr202p//+32iRMnXK8HDx5crQVnyJAhriDi8rxGo5EnnniCZ599FkVRuO+++wgKCvrd9bgSCSKEEEIIIcR18/HHH7sCiLCwMF5++WVatmzJxo0bee2111xrT7zxxvO8+uoUiotPcODABk6eXMihQ/OIraVG8YqmdttB2LwTSCtWU6z4gcbA8lJY/nNZleOpHDY0FemoS8+iKU9DW55O6bls0o5loVgqiI0FbXwg782di4+PD2azOx7HPWnWrDktW9YjOFhhzZqVbNy4kYqKCoKCgujduw8REdGcP59HgwaJgAdr1+4iPDyWtm3bERTkoFu3WIzGCEBHXFztP+Vcurldak3JzMysln7u3Lkr5gWYPHkyp06d4osvvgAgJyfnutZNggghhBBCCHHdfPrpp67XP/74I02bNmLTplUEBelZs+ZzBg/ujc0Gu3Z9BwzHK0BDZMv2vPDeDxQ3fR2bT23QGNkHUAqusc12M5ryDEI9TNzduyUfvvEuqbu2Yy/OomEDB2o1dOnSmaeemsq2bYcZNuxZPHzcUKsryc3NY/Hixdx7770YDHreeGMCACkpKTz44GhycnJxOKCszNl96rPPFlG7dlOGDh1NvXr1Uas13HZbMB4eHoAGvZ4qg6f/LG3atMFgMGA2m/nqq6+YOHEitWrVcp4Ou52XXnrJlbdLly5V9lWr1Xz22WcMHDiQDz74gA0bNlBRcf0WnJMgQgghhBBC/GEnTpzAbrdz9uxxfHwgMjKckJASYD916+qpXTuS4OAAElt04GiegTO+dejyZg6n8i6MSfDq6irL26giKVhhxbffYsk5Tas6/mhMOynIz0cxGhn3783s/NLM4ULn03mTCSIi/Hj11VcxGAz07u1PSclGMjIyGDRoMADLli1jxIgR5OcXU6OGH2lpadx550Pk51eiKFBe7vxzcRKks2f3UFFhYNSoB1GrNXh7X5/F2vbt28d7773H6tWrqaiooGbNmowePZqRI0deCFIuCQgIYNiwYcyaNYvS0lIaNWrEiBEjCAkJYcGCBa4WHw8PD0aNGlXtWCqVij59+tCnTx/y8/MJDAy8Lp8BJIgQQgghhBC/Q3Z2NsnJB+jWrQ0qVTknT27CYHBQ78KSCxERGkJDvTiYYWXjcQ17zjrYm5ZDUfDTcGFM9cUAwpqfgbboCJ7mIzSN1vHltBdRqSDwuZ+oLCjmWEUN2rXzoyA/H4vFjKIoTJx4N7ff3oZXXnkWrdY58Pjiytk6nfMWNzo6Gl/fYHJzs0lPzyI728rSpfsZMmQoL7zwNikpzrEUrVu3Ztq0adSpU4eff/6ZJ598ktzcXLZu3crChQu58847r8s5mzFjBpMmTaqyLT8/n127dvF///d/rFy5kqioqCrpb775Jjt27ODw4cOUlZXx8ccfV0nXaDR89dVX+Pv7X5c6Xi0JIoQQQgghxBXZ7XbKy8vx9vZGURR+/HERCQkRJCaGA2ewWo9iNntiNBro0aM+KpWK+LqNOJjjxlHv5jR56RxF5l/cbtpNaIuPE6LN4a5uTXh0xDgclSWEhuowhlo5kaensPARAgICGDduCGq1iuBgHz777E1UKueUsyqVisaNE4mODuL118HhgNOnz6AoCqdPn+PkyfN0796VsjKFvXsLKC2FkBA/goJaMnBgPKDlu+8WAODv78+KFStcLQ0jR44kODiY2267DYDPP//8ugQR8+bNqxJAuLu7ExAQQHp6OgDHjh2jT58+7N27F53u0sJx/v7+bNq0icmTJ/PNN99UWXCuZcuWvP7663Tu3PkP1+9aqX87ixBCCCGE+CcwmUwcOnTowo2qlR071rB8+WzgJCrVIcLDy/H2LgCyCA420rt3W4xGA6fzbPxnczl3vJ/FzvCXKWv0LObwHhSZtajsJipSt1Gw+lMMG57Ef92d+OyZwpM9PLi3exQ6h4mGDeNp2DARALPZwqOPPsq+fft49tnR9OzZgNWr53NxYqL+/fuTnp5FWloW/v4BREfXIT0d1q49wbffbkerrYdOl4jdXpMpU96jqMiK3Q59+vRBq9VSo0YN0tLSsFgsAPTt27daV6UePXoQEBAAwJEjR/7weVUUhZdfftn1/plnniEnJ4e0tDR27drlGudw6NAhFi9eXG1/f39/Pv30UzIzM1m+fDkLFy7k0KFDbN++/YYEECAtEUIIIYQQ/zhWq9X1tHv79u24u2tp0KAWNlsu27cvISCgJaGhfiQl6YmLiwOKAGjWLAkAi01h1xkLa4+aWXfUzKk8+2Wlq/FwFGBP34Qubydlp1PIPWkDwCsMPEOgdetW9O3bF61WS2npRnQ6LdnZ2QwfPpzCwiKOHDnKmDEPOEtTg8UCJSVQs2Y4AwaMZdeuY4CBqKjGDB78LIsWjQBg5MgJtGrVioYNGzJ27FhSU1MvlKFmwoQJrhrq9XrX67y8vGrnp6KigvLycgBXF6k/4sCBA6SkpADOrlOvvfaaK61Zs2Z89NFH9OjRA4Bvv/2WIUOGXLEcPz8/evXq9Yfrcz1IECGEEEIIcQtTFIWCggLc3Nxwd3cnNfUQmzatZfToAajVJrTak6jVWkCFpyeMGdMDtdrZWcXX18tVRurJ83yxKpNDBe6kWQIoMyuuY6gUOxVnD1F5ciffzhhCzza1eOed/7J48WHUHjZiY8HdHTw9tQwcOJCJEye61k+4OH5BUTRMmvQ877wzg1OnssjNdQ5ytligogIiI6P56KMV+Pgk0qVLHVcdhw0bxpYtW/joo48AZ1C0ffv2S3VTqfjoo4+od3GwBlC7dm1CQ0M5f/48K1asYM+ePTRt2tSV/s4777i6DXXs2PEPfweXT8XavXv3auldu14aVH6lqVz/jiSIEEIIIYS4xWRlZVFaWkrt2jVRlDIWL/6KFi0SqF8/gpCQIjp0iERRsgANzZolVtlXURRKS8vx8vJwvV+abGLcp/movSIu5iLQU03nBANdEg0cXreU17/4iE5tGhDm5cBgMDBp0iQefHAsmzZtpLCwED8/P9q0aYuXlxcGg56iolI2btxPp07t8fYOIi0tn9LSEH744STz5//At99+S1lZGaGhodx9993069fP1XpyMYAAZ5DwwQcf0KxZM2bOnOl64g/QqVMnnnnmmWo37lqtloceeogXXngBh8NB+/btGTVqlGtg9bJly1x5x40b94e/Dx8fH9frgwcPVks/fPjwFfP+nUkQIYQQQgjxB+Xk5DBnzhxOnjyJu7s73bt3p0uXLlVudv9MpaWl7Nu3j5YtG+LpCWlpO8jIOEPt2u1Qq2HAgIb4+HgCNry9PfH29qxWxsmTGdx77wvs35/KyJF9+PDDyRxIt/LK0hJ2n7Wi9qqBrSSXsuRVzP+/YXRtXAO12jlQoWtCfx6fUH1FZa1WR926TahVy7ko24IFGwgJiaRdu44YjWo8POw4HLUAX5o1C6dFC+f5uueee7jnnnuu+vOrVCrGjBnD6NGjOXnyJEVFRYSGhhIeHv6r+zz11FP8/PPPbN26lcrKSldLxuWmTp1apYXi92rRogXBwcFkZ2ezePFifvrpJ1e3pLKyMh577DFX3n79+v3h4/0VJIgQQgghhPid7HY7zz77LDNnzsRqtbq2z5gxg6SkJObMmUPDhg2vy7GsViuFhYUEBQUBsHr1CvR6B0ZjATrdWcrKkjGZwNPTl2bNwmjRIsK1b0CAL6WlpcyaNZs5c5Zy7lwhcXF+DBp0G3fccQehoSEEBvqyZcsBAHYdyuTxuUUs3Ofs0uOmU9HCK41w3X7aPdOCtnV8XQEEgF7vbCGw2WwcOHCc6OhQAgMjyMwsZ/PmNKKje6LVGmndOuDCysp+GI1Vu/Fcj4BLpVJdGMPx29zc3Fi5ciVPP/00s2bNorKy0pUWERHBc889x4MPPviH6wTOMRgTJkzgueeeQ1EUevfuTdu2bYmKiuLnn3+moKAAcA6gHjly5HU55p9NpSiK8tvZ/jlKSkrw8fEhLy/PNSpfiCuxWq0sX76c3r17V5mKTYgrketFXC25Vm4uEyZM4P333//VdF9fX7Zv305CQsI1l22320lOTiYyMoLAQC+OHt3Pxo0bGDOmH1qthaNHT6DRqDl37hRt27ZzjS24qKCgGF9fL9RqNcePH2fChAkcPZrH2bPO9LAwCAkBg0HPa6+9RufOnYlLHIqtVlfUdXvjUDuvv8FNjDzV04sQH80V63n48CkKCyto27Y9iuLO3LkraNasLXFxtbHZnAOqL45/+LsqLCxk3bp1lJSUEBERQadOna57nW02G0OHDmXRokVXTPfw8GDp0qV06tTpuh73oouLzRUXF1+XhfNkilchhBBCiN/hwIEDrgBCo9HwxBNPsHnzZubMmUODBg0AKCoqqra42OUURaG4uBiHw7no2p49u1i7djmQh1qdwZEjaygs3AqkEBPj4I47mqPRlAM2EhNjiIkJq1bmu+9+T0LCIAICunL8eBrFxcWMHz+e3Nw8Ll8Q+eKDd7PZwqTJz/DBspMEjnwP6vfHodbRPEbHj+MDeGuoL/5uDioqnK0SBQXFfPvtagoKdEAsanUCanU8UBOVKoS77hpFXFxtwBk8/N0DCHDOejRo0CBGjRpFt27d/pQ6a7Va5s+fz/vvv098fLxru16vZ/jw4ezcufNPCyD+DDdtEPH666+jUqmYOHGia5uiKLz44ouEhYXh5uZGp06dqgyuEUIIIYS4Xj755BPX6zfeeIM333yTtm3bcvfdd7N582ZCQkIA+O9//1tlxp3U1FTOnz8P2MnKOsHcuZ9RVJQMHMbXN5PAwBLgLCpVHsOGdaZ2bWe3JKPRgL+/DyqViuPH05g7dyVvvvlNtXpVVJhITU0DYPv2QyxcuIi8vHwAmjSpw5Qp97Bu3cfs2fMDPXp0x+qTSEHj1/n3Jg+yShTCfdVM76vhhXaFNIjQAQaWLdvHzp3ZQG28vdsSH98ZnS4W8CcxsQGtW7f+E87wrUej0TBu3DiOHj3KmTNnOHLkCHl5eXz77bckJSXd6Opdk79/aHgFu3bt4tNPP3VF+RfNmDGDmTNn8uWXXxIfH8+rr75K9+7dOXbsGF5eXjeotkIIIYS4Fe3bt8/1+pd95w0GA3fddRfvvPMODoeDWbM+5dlnHwMqSElZQ3i4D6GhCdSoYaNPn7p4e5sB+4UByJeYTGby8oqIiAiusn306Jdc4xfmzKna0tGqVT30eh1NmiTi7m5k3rxLMw1NmzaNyMhIAM4V2SlKfIwSxYHisGM+sY2HBjRk8p1NyTiby6ZNp0lIqItOZ6RNmxoYjUbAG63WOVBY/H4qlYro6OgbXY0/5KZriSgrK2P48OF89tln+Pn5ubYrisI777zDs88+y6BBg6hXrx5fffUVFRUVzJkz5wbWWAghhBB/JbPZzKxZs2jbti1+fn4EBwczZMgQ1q9ff12Pc/lMRGfPnuXs2bOAQkVFAV9++QF2ewZxcZCYCP7+RSjKcSCTAQOa06KFc4yEVqslPDyoWvcZk8lMw4Z34+nZgbvvfrZK2tGjR6mszHe9f/756YwZM5qfflqBoii0a9eIkpINbNs2iyFDupGTkwtAWFg4DkXHoQwz//65lFaPrOeHH7eBomA6sprcZe/QNToEo64mNWs2Z9Soh9DpjAAEBwffNFOPir/GTdcSMW7cOPr06UO3bt149dVXXdtPnz5NVlaWa7U/cD4F6NixI1u3bmXs2LFXLM9sNmM2m13vS0pKAOfAtstnWRDily5eH3KdiKsh14u4WnKt/DF5eXn069eP3bt3V9m+YMECFixYwLhx45g5c2a1qUh/yy8XbMvISMfPzwtvb+ciah98MJX+/W8jLKwJOp1C48a+zJmzEm9v0Go1DB7cE5vNXqXM9PRsvvpqKTt3HqRZs9oMG9aD2NhYNBotGo2G4uJS7HY7+/enYjZbUKvVbNq0kWeeeYbSUhuhoc5ju7vD4cNHeO6559i/fz9PPvkEarUaq9VGcspZzJ51KfWPIdkYS+uHf0YT2xKNhy94h9Ei0Z1Ty97l7NZVAMTGxsq1d4u63t/rTRVEfP/99+zZs6faDwM4F1UBZ6R8ueDg4AtPBq7s9ddf56WXXqq2fd26dbi7u//BGot/glWrVt3oKoibiFwv4mrJtXLtFEVh6tSpHDp0yLUtICAAk8lEeXk5AB988AHl5eUMGDDgV8u4GGBkZmZSUVFBfHwUKpWZNWvWkpgYQe3aQZSVFdGqVSCZmaBWw86dS4BznDq1k6KiIjZs2EBpaQmKAhERcbz77rc0bhxHQMClWXE2bdrNyy9/D8COHdtZvvwbfH19aNeuHR06dCAmJgiNRkXt2uGsWbMWs9nE9OlvYLXa8PKC0FBP4uJqkZOTQ2bmeQC+nb+SzcdUhLUYyPFCN47uP4TKfwiG8ERQHGgtlbi5uRPr5aBNvDdZe35m2YUAonbt2uzZs+d6fy3ib6KiouK6lnfTBBHp6ek8+uijrFy58kKfvCv75ZOFy38MrmTKlCk8/vjjrvclJSVERkbSuXNnmeJV/E9Wq5VVq1bRvXt3mYZR/Ca5XsTVkmvl99uyZYsrgAgODmbOnDm0a9cOq9XKZ5995lrQa/ny5bz33nsYDAaKiopQqVT4+PiQm5vF8uWL6d+/C76+OpKTLRQW5tGxYxQAzZsH4eXl4ZpKtVev7vj66vjyy69QqWD79t3s2lX1QWdpqRsLFx4DjvH11y/Tr187ANasWc2SJXNRqUBRwOSc+IiiomKWLl1GUVERy5d/UOUa+Pjjj7BabTgc0K5dO6a9/ionc+y88u+5+CfEcazCFwd6duenYTzjgUqtwVCzBYHuWtL3rsOUcRhTRgoRnmpCO7Tnxx8OVgkapk6dSu/evf+U70bcePn5+b+d6RrcNEHEnj17yMnJqbJqoN1uZ+PGjbz//vscO3YMcLZIhIaGuvLk5ORUa524nMFgwGAwVNuu0+nkx1tcFblWxLWQ60VcLblWrt3cuXNdr2fMmEGXLl0A5xSaEydOZMuWLSxYsICcnBw2bFhLnz6d2bBhCcHBXrRvX5eAgFKaNQvAw6MInc5I06Y1gZquMoODqz9cHD9+PCtWHGTNmn2YzQoNGsDF4Q0NGzagQ4fbGT36NQAOHjzOPff0Jicnh5dffhlFUahVC6KigujevSOZmefYsmUrAJs3b2Hu3O8ZPXo0ZWUVHDlymhWbUij160CJyZOdlc1o/e9Kysx2zJVJaHU10Hj7oFIcOEyl9K8XQNcGMTSN9iPc141ZszK5//5/oygKp3Pg9KmT1T7HiBEjrrmbl7h5XO/fk5smiOjatSsHDx6ssm306NEkJiYyadIkatasSUhICKtWraJx48YAWCwWNmzYwPTp029ElYUQQgjxF7p8GtX27dsDznuB5cv/S7NmSdx+e3O2b18AgMm0AwinW7c43N2NgBmDQU+jRtUXhXM4HDz99LscOnQST083FiyY4UpzzrJTE7N5LwA9evQlKSmGVq1aUadOIllZedxxR1caNYqnW7eWACxcuBCz2QLA0KE9eemll1Cr1ReChRQeHjeOgnIf/v3Nfs4HWdl7ooQd6w9C1BNoanqhN1dwHlCb7Rh1auLia9G9UU22L5vDki/eQTGXM2r8Hpo0CnfVc8yYMcTGxvL6669X6SrXoEEDnnjiCe655x4JIMQ1uWmCCC8vL+rVq1dlm4eHBwEBAa7tEydOZNq0adSuXZvatWszbdo03N3dGTZs2I2oshBCCCH+AlarlezsbNfsQQYDfPfdRzzzzL/Q68vx9y9Ar88gM3MXQUHOfS6u2Ovr65wCvrS0nI0b97F371EaN06gb9/2rvLVajXz5q0iPT0bX1+val2lk5Ji8fb2oG7dWtx+ez86dGjiSgsJCWT+/KoPM7du3erqwjRmzP0UVuqY//MxNm4/iiGpB8Wd5mPKO4fF6Mmnm5xdUDQJncBhw5x5DEvWcaaOu5fbWiYR7Wtg5c8ruK1rLeo9OhfF7Bz7cXmvjIs6d+5M586dyc7OJisrCx8fH6KjoyV4EL/LTRNEXI2nn36ayspKHn74YQoLC2nZsiUrV66UNSKEEEKIW8yxY8fw9PQkPDyQ/PxTLF++hH796nDoENhssHPnAgoLe+Dn50eHDk1ITk7mxx9/RFFAo9FTr16DX5R3lr59JwJwzz29qwQRAElJNUlPz74wS1MxAQG+rrSxYwczbtzQK96Mm0xmjEZnt+nduw9jtmg4XRxElmcMJo2Duz61kKs6j8OsRbHWRn2sEJXWDX2NGCy5Z+gcqaNH80Tqh/vw87xZPPnvJwD4tmAXfb77Dm1ADBUVFUycOJETJ04A0KVLlysGERcFBwf/z67eQlwNlaIoyo2uxN9JSUkJPj4+5OXlycBq8T9ZrVaWL19O7969pd+y+E1yvYirJdfKlaWlpZGaeoRu3doA5SxZspiwMC+aN0/EbrdTWlqBh4eRO+4YQkZGBgBubkZatWpFaWkpu3fvIT8fzp1zBhkLFkxn8OCurvLNZgteXh2wWm0kJdUkJWVeleMfP56Gh4cboaGB//PJ/alTGfj6euHv78vp0/n88ON24tv141A2rNt6gOPZpRAQA4CiOFCp1KhUUDvIk0aRvtQL8+bVxx/k+O4NYLdy+vRpYmKc+YuLi6lbty7nzp1zHS8uLo60tDQsFmf3KJVKxapVq+jatesvqyb+4fLz8wkMDKS4uNjVEvdH3FItEUIIIYS4udlsNrRaLVarlSVLfqBZs0RiYvxRqY6jKCdwOPxRq9X069fMdTOv0Whc3ZJGjfoXTz/9Cnl5JmJiTKxbt95VtkbjDCAA9uw5WiWIMBj0vP76eMLCAmnWLKlavWrXds7Q5HA4KCwswcfHE41GQ0rKSbKzS+jSpROKYmDu0k1UekSR7+bLnpM20s+FoT13FpVaAwRAQABuGgcFqXsxZx7F117Eh69O4rauHcjJyWHy5Mkc37Ea4MI0rzGuOvj4+PDTTz/Rs2dPzp93Tul6sfUBnN2uPvnkEwkgxF9CggghhBBC3DBFRUV4e3ujVqvZsmUteXnn6N+/PTpdGRERJtzdcwE7kZG+REa2cu2nKArnz+cRFlajSnmLF2/lxAnThTwGwLmgbFhYKCNG3MYrryygSZM6xMVFVKvLE0+MqFL+xSAlOfk4np5u1KxZi4KCChYu3MWAAf0JCorCzc0HtNl8s03L7B2nOXIuFpVGCzhv8g1+IcQHe9Ek2o8mUX40jvIlwltHixbPkZycTDHQu/sKvLy8KCsr42IHEbVazQsvvFCtjvXr1+fQoUN89tlnfP3112RkZKDT6Rg0aBCPPvoodevW/b1fhRDXRIIIIYQQ4h8qOTmZHTt24HA4aNSoES1atPjTB9nm5uaiUqkIDAwgLy+NhQvn079/e4KDjdSqZSU83BdwDiZu1ar+Fcu4884prFy5HaNRT2bmiip1btWqPl9/vQyAkSP/xZAhHdFqdQQHB6FSqZg48eFqn9HhcJCfX4yXlztGo4HDh9PYu/cUI0bcBRjJzs7EZgsF6uHnZ6dfvyj8/QM5dK6c2fsrWLK/lApLCgBuRj1tawXSJNqPxpG+NIj0xdNQ/XZr+fLl9OrVyzXzZGlpqStNr9fzxRdfuKao/SV/f38mTZrEpEmTpPubuGEkiBBCCCH+YQ4cOMDDDz/M1q1bq2xv2LAh7777Lh06dLhux8rJySE1NZV27VoAFezYsRyjUaFbt4b4+9vo3TsJ5xBEGyEhga79zp49z6ZN+9DrdQwd2r1KmYWFJRQVOW+609OziYoKcaXddltrPv/8OVq1qk9iYgwajeaK9Tp1KgOr1UZCQm1sNi2LFq2jU6euxMc3IDg4hsaN41GUMFQqFd273+7az2KHTRlWvv1hBwfSi1zb44I8Gd4yikGNI/Bx/+2b+fDwcHbt2sWCBQv48ssvOXPmDJ6entx222089NBDREdH//bJFeIGkiBCCCGE+AfZt28fHTt2rPLk+6IDBw7QrVs3li1bRvfu3a+w95VZrVYqKyvx9vbG4XCwcOE8GjWKJy4uGLP5JLm5e7BYtOj1Orp0icNo1AMO1Go1ERHVZwkqKiolNrYfiqLQpElitSCiVav6JCefoFWrelRUmKqkxcaGc999zvUR7HY7FosVvV5HdnY+mzYdpF+/3uj1vmRm5mI2G0lIaIBeD4MHB+Pr6wtoCAgIqDa5yomcUmbvSOOHPRmUmJwDK3QaFbfVC2V4yyhaxvpfcyuOwWBg+PDhDB8+/Jr2E+LvQIIIIYQQ4h9CURTGjBnjCiDi4+N58MEH0ev1zJo1i3379mG1Whk1ahRnzpz51e4xFRUVnDhxgsTERPR6hW3bVpObe47BgzujVlcQE2PFyysPUIiM9CAy8lLLhnNhN8jKyuObb5azadM+evZszbhxQ115fH29qFevFgcPnmD//lRKS8vx8vJwpT/33H289NLYajft5eWVFBaWXAhMtHz//XriaifRuEkrjMZogoPdsNmi0evdadeu6hSoV5qR0WJz8HNKFrN3nGX7qQLX9kh/N4a1iGZIswgCPQ1Xd/KFuMVIECGEEEL8Q2zbto39+/cDUK9ePXbu3ImbmxsA//rXv+jRowfr1q0jMzOTefPm0b17d4IurM62cuVPBAX50KhRbSyWLHbvXkpISD5BQd40aOCBwxEHlABUmd3Ibrdz/Hg6gYG+BAb6urYXF5fx9NPvXsjjqBJEADzwwADy8orp0KExBoO+Sppe7wxuLBYrhw6dpFatCHx8gjh+PJd9+04yalQXjpy3sL2iPq/9UErFwq2oVWDQajCu24xRp8Go02DQqjHoNBi16gvb1M48OjUqVKw5mk1emXPqVLUKutYJZnjLKDrUroFaLQu0iX82CSKEEEKIf4hNmza5Xj/yyCO4ubm5ZiGy2WzcdtttrF+/Djc3WLt2IRZLFqNH9wMqCQoqxMfHChjw9YXRo3u4WgIuTq/6S/PmreK++16hrKyCJ58cgt2ezbFjqajVKurWrYufnxeFhaWkpqZVWwV6woS7XK8vX9Jq//5jWCzQokUr1GoDhw4lExAQhY9PLDG1okkpr8Wgj/awL63IuYPK2fLhUKDSaqfSagesV33Ogr0N3NU8irtaRBLq43bV+wlxq5MgQgghhPiHsF1cJAHnmgPr1q1EUSrp0qUpWm0pkEbduqDXQ3S0wqBBzbjYutCoUUKVsi7e8K9atZ2lSzezZ88R5s+fTmjopcHRYWE1KCurAGDWrPlcPlY4M/M8AQEwYkQXZs6cViWAsNvt2Gx2DAY958/nsXLlPoYMGYy7ew3UatBqVUBNtFoYOfJBUrNLefHHFBbuvTReQatW0aNuMMNaRFM/wgez1Y7J6sBsc/5tstkx/XKb1bnNbHNgttqpG+5D18QgtBr1dfwWhLg1SBAhhBBC3MLy8vLQ6XT4+HgTFOSNpyf4+8PGjR/w2GOPoVargWy0WrBaM9Ff6DmUkBCHj48nAGfOZHLw4AkyM3MZO3ZwlfJXrdrBu+9+D8CePUfo27e9K61Ro3j8/NxxOCrwdBaFp6cHdrudykoT3t6wZctaPvjgQ+6+ewRBQf6AmgULNhEdHUerVh1xc4vl/Pl9vPLKf3Bzc6NNmzZ06dIFk9XOT4fOM3t7GrvPFrqOGenvxl3NoxjSLIIgL+OlirrJ9KdCXE8SRAghhBC3kIKCArKzs6lTJwEoZ9WqecTEBNK6dTx3392Qb77xpaysiG3bNhIQ4MVdd93FiROVLFq0iO+/X4TDAb6+Bnr16uUqs1+/xzl48ARarYbRo/u5xiQANG1ax/U6NfUscCmIKCkpombNChQFjEYjzz8/lW7dumGz2fjii2/44otPsNkU3n33e9TqeB5++BE0Gk/atAnE09OT2bN/5PHHHycnJ8dVptY/gqjOd+NWpxNlVmc3J41aRbc6QQxrGU37uEAZryDEX0CCCCGEEOImdHEMgcViYevWrdStW5saNdw5f34v+/btJSGhHLVaRe/edfH0dAPseHp6MGXKkzz33HMALF26jKVLl2G1QkoKOBzg7Q2TJz+Et7e361h169bk4MET2Gx2jh9Po27dWq60rl1bsGrVBzRunEBAgG+VOq5YsYKLwxl69x5IcHAMGo0HKpUbRmMidercwezZ8wELKpUPGo1zbEVkZCT/+c9/uO+++1C7+2AIr4MuMAqPpE4Yo+pjB8qsCoFuau5tF8fQ5pEEexsRQvx1JIgQQggh/uYsFgs5OTmEh4ejUqlYv34lFkspPXq0Qqsto6TkABZLJRBEnTo+1K3b1bXvxS5JGRnZLFy4js2b99Oz51A2bFiCyWQGQHvZ3YBe78WIESOqHH/w4C7UrBlOvXq1CAurUSUtMNCXbt1aAmAymbHbHXh4uJGXV8Ty5XvIy4PKSoiJ6Ux+fiBQF7Uahg9/iMDAWGbPno/K4MGxXBOL953jdF45qeeL+HFTGZGPfo/a6Fn1ZCgOKk7spHT/Cny97Yx/fs+fvsq2EKI6CSKEEEKIvwGz2czChQtZv349J0+eZM2aNYwePYrGjeuQnX2cn35azl13dcfbW03Nmlbsdh2QhVoN/fq1c5WjVqspLS3HYNBX6XZ05MhpHn30TQAefngIy5cvZ/ny5Rw6dAiHw4FafQp//wCaNk36ZdW4445u3HFHt2rbCwqKycrKJympJuDGjz9uIywsmnbtGuHpqcbNrTZpaTsAsNsNNG7ViVWHs0nNLuV0Xjmb95uIGP8tGg9f/muG/87d7ypbF3yhtUNRCPdzJzbQg2YxfgxsGEL/7lM5cOoAB4CdO3fSsmXLP3z+hRDXRoIIIYQQ4gZwOBwUFxfj5eXFunXrGDbsbkpK8vH2Bnd3OHp0DWvXfsiECWMYM2YMd97ZGi8vBXAQFRVyxTK///5npk//iuTkE6xa9QFdujR3pbVqVR+1Wo3D4WDfvmP4+Phw9913u9Jff/3K9TSZzFgsVry9PTGbLfz88w6aNWtCWFg0OTkmdu8uJDGxIWq1lk6dAnF3dwc8MRgU+g2/j0UHsjCE1+H5HTaeP7zqF6V7oLmwhpy/m4a4EB9iAzzYtW4Z21f9F1vhOVYv/p4ObVtX2euBBx5g/PjxwPUNIhwOBytXruSLL74gNTUVg8FAly5dGDt2LLGxsdflGELcKiSIEEIIIf4iJ06cQKPREBsbSVlZFvPnf0doqAdTpz5KSIiNwEBnAHGJnU8//Qy73c7DDz8MwOHDp9i2LZn9+1N5++3H0V7WF8lqtbF/fyoAW7YcqBJEeHl58M03L1OnTgz168f9ah0LCoo5evQMrVo1RK12Z+PGFGw2Db1790WvN6LTFfHDDwc4fnwBiqLQrFkzTCYLWr2aDJOOPUdz2H32KHvOFpJXZiGw98Qq5btZi3GrzOXsoV2YctOwFWbSpUV9fvpxkSvPqKUzWXd8mzO/vvqtikajcb2+fA2JP6KkpITBgwezevXqKtt37drFW2+9xbvvvsu//vWv63IsIW4FEkQIIYQQ14miKJSUlGAwGDAajaSlpbFz5xYGDeqBWm3i9OnNGI0QG1sfLy+Fvn3r88QTE9FobGg00K5dc4YPH87p02dIS8vgu+8WYDDArFmzGDhwEKGhIbz88mfMnet8oj927CDq1bsUELRt2xCVSkX9+nH4+3tXq9+wYbcBznUYiovLLoyXUPHdd2upX78e9eo1wmz2JCPjPCZTHdzd3WnePOTCNLA+fP/9d4wbN47CwkLU7j7oQ2rz7YFinl2ThzE8AZtSdWyCXqMmPtDAgTULyT+6C/O5IzhMpVXyJCQk8OVnH1fZ1rhxY7766isAPvnkE5o3vxQMOWd2+sL1vkmTJtf+Rf2CoijceeedVQIIrVbrWlfDZrPx8MMPExQUxODBg3+tGCH+USSIEEIIIa7R5asrnzx5koqKCurXT0BRKpg//z+0bl2funUjcXfPJCysEpvtOHq9ju7d67vKUKlUFBfnkZp6DID4+Nq89957OBwKDzzwFqmp5/Dz8yQ6ugyHQ+HHH5cwduxYGjdOcAURe/cerRJExMaGU1i4zjWY+iKbzUZGRg6hoYEYDG7s2nWK06fzuPvuewB36tfXExwcDNQgNDSEoUMTsNkdpOVXcLbAxtn8ClZuXcuKTYcw9n+JSN8Q1Ab3qsdQwF3joE18KM1i/Gge40e9cB8MWg2Zdyby8ssv8+23KZRfyO/n58fo0aN59tln8ff3r1LWPffcw5QpU6isrOSLL77AZDIxatQoysrKeOedd9i9ezcASUlJtG3b9o9+nWzZsoUVK1YA4O/vz8cff8zAgQPJz8/nlVde4YMPPgBg6tSpDBo0SAZyC4EEEUIIIcRvOnv2LJ6engQEBJCVlc6yZUu4887eeHpqKCzcR0lJAWBBrYbbb6+Hr68nUE5goA+BgQ2rlZebW8i7737Pzz9v5Px5CA2FPn36oNVqsVptaDQaHA4H+fllhIc7Z09KTT0OQK9ebdHptDRpklhljQZwBiYXA4jTp8+hKAo1a9bCbHZj5crN9OhRm5iYRJKSahIXZwE8OV9cSQaBbD1SwtnNWaQVVHA2v4JzRZXYHZd3FdLjntDm0rGAIHcVtqxjpG75CVPGEXzVJj7IyMBgMFSpV1hYGB9//DFvvfUWJ0+eRK1WExcXh9F45WlZ/f39mTFjBhMmTABg9uzZzJ49u0oenU7HBx98cF1u6L/88kvX65kzZzJkyBAAgoODee+999i3bx9bt27lyJEjMpBbiAskiBBCCCF+IT09nXPnMmjVqhFQzvbt/yUmJoiAgHh8fMpp0aIGWm0WYKBZs1jg0qDb4OAAAMxmC4cPn2L//lRatapPnTqX8mg0al591dklx8PDGUSYTCZXelJSFHq9gVq1Qjl6dL1rH4AGDWrToEFtV16bzca2bdvZunU7Z87k0b17Z3r1uoMzZwDcqVmzHh4eMHx4NB4ezlHMHp5e7EnN5dulu1h3LAfHrwwr0GvVRPm7ozMVsWPtMmyF52mSEMXn77xBpL87Bq0GRenFgAHr+TE5gzxg0aJF3HXXXVcsz8PDgwYNGlzVdzB+/Hh0Oh1PP/00JSUlVdIuriPRqVOnqyrrt5w+fdr1un///lXSVCoV/fv3Z+vWra68EkQIIUGEEEKIfzCLxYJer6eyspKffvovrVs3IDTUi8rKw+TnH0NRdKhUKgYObHZhulQ7bm7GKgOTLRYrx46dJTExBp3u0n+rCxasYcSIqQDMmPFIlSDC39+HqKgQ0tKysFhAUWDx4sXcfffd6PUGHn64H23btuW1117j1CnnPvXrN6CiwkRpafmFQEXFtGlfMH/+As6dy6G8HCoq4OOPV+Pr+29mzJjBAw884Dqmh4cHuaVm5u1OZ86ONM4VVbrS6oZ5U7OGJ9H+7kQFuBPt7050gAdBXgbUahVTpkxhxZrPAHj8hSXEBXm59lWpVNx///38+OOPAOzfv/9Xg4hrNXbsWIYPH868efM4ePAgWq2WNm3acPvtt1cZUP5HXQyuAE6dOlVtnMXlQcbleYX4J5MgQgghxD+C1WolOzv7woJtsGrVUuz2cm67rQVGYxmBgcXodOcAX+LjA4mPD3Ttq9frLqyloK5S5pNPvsM773yH3W7n0KG5VVZyrlu3puv1xRmTLvf999MICQlg+vRX2LVrN+fPZzFixAjuuOMOsrKyWLBgAVu2bKeyEry9dfTteyeHD+dx5Ega99zTjs2bd/Pii59htVqrlV1UVMSDDz6IzWbjoYceYvupAr7dcZaVKVlY7c5mBx83HXc0jWBYyyhq1fCsVsblLv/cVzre5dt+eY7+KE9PT8aMGXNdy/ylHj168N///hdwjntYtGgRer0egJSUFL7++msA3NzcaNeu3a+WI8Q/iQQRQgghblnHjjnXQwgJ8ScnJ5Xly5cydGgXfH211K2rA3yBQlQq6NCh+iw/iqIwZszL7NhxCKvVxvHji6qk+/l5YbfbAUhJOVUliEhMjGHEiF40apRA27bVx0W0bu3s1vPkk08xatR9VFaWkZaWzgsvvO1qnSgvh7IymDbtNfz8WpGUVEGdOgqK4sbDD4933by3bduWRx99FE9PT7766ivmzp2L2uDBc1+vYV5pAqcLLrU6NI7yZXjLaPo2CMWo01Sr15Vc3n3n/fffZ8CAAa5pVh0OB++//74rvUWLFldV5t/JyJEjmTp1KkVFRSxfvpyEhAQGDhxIdnY2CxYswGKxAHDvvffi5+d3g2srxN+DBBFCCCFuGWlpaZw+fZKOHZsD5aSkrCEqyo+QkHiCg20MHdoKX18NoBAWVgNwBgrp6dls334QLy93evW6NNuPSqXi0KGTHDni7M5SVlaBp+elWYkaNoynYcN46tatSUhIQJW6GI0GvvnmlWp1dDgcpKScIjQ0kMDAGjgcfvTs+SAbN25g48Y9XLhfBSA8PJwPPvi3a1E49wuLSGzdupWDBw8CzulQ161bh06nQ1EUQuu15mxwe85pQ1DrjJwuqMRdr2FA43CGtYiiXrjPNZ/X3r17ExkZSXp6OuvXr6dTp06MHTsWlUrFxx9/zObNmwGIiIigb9++11z+jebt7c33339Pv379sFgsnDlzhrfffrtKnqZNmzJ9+vQbVEMh/n4kiBBCCHFTURQFs9mM0WjEZDLx448/0Lp1AyIjfbHbj1FZeQyHwxO1Ws2AAc1d3Wu0Wi2+vl7VysvMzCU62nnj27VrC1cQkZOTw6JFiygvz0atVuHv786yZSu5447bXU/h+/ZtT9++7a9Yx9LScjw93VGr1Rw4kEp+fiVdunRGrXYnOfkAOl1dAgPrERVl4sEHG/Dss/9m//79rFu3juTkZAYMGPCrff/37t3ren3n6IfYfLKQw+dLWH7wPCmZJeAWgxqw5JymrqGAhW9Pwcuo+93nXKvV8tlnn9GnTx/sdjubN292BQ4XaTQaPv300+s6VuGv1LNnTzZt2sTUqVNZuXKla7uPjw/33XcfL774Il5e1a8fIf6pbs5/6UIIIf4xTCYT6enp1KpVC7VaYe3a5VRWFtG3bxuMxnKioqy4ueUAFmJj/YmNbe3a92IAceTIad5993u2bz/I2LGDeOihO1x5wsODCA8P4ty5HHbuTMFut7Ny5UpefvllLBYrOh00aABqdTkzZrzKqlVLeeutt/DxqfpE/9ChE3h7exIVFUFOTjlLlmxj8OCBBARE4OHhhd1exsVZnIYPv9+1n9FodE112qRJE+rXr8/y5cvp3bt3lRvyUpOV1OxSjmaVsrowgOBhb6CrEcNH5zz56Mtdrnx6rZpWYTrmTZuA+dxRuo8c+YcCiIt69uzJ8uXLeeihh6oMNAaIjY3l448/pkePHn/4ODdSixYt+Pnnn0lLS+PEiRMYjUYaNWrkagESQlwiQYQQQoi/nZ07dxIY6EfNmiEUF59l3bolBAR0wt/fSP36RhyOIKAIgFatLi3gVlpazs6dKTRpkoifn3eV7R9//AMAW7YcqBJEgHPlZ4vFSqtW9dm2bTvPP/88jgvznmq1oFKBwwFWK+zZs58nn3ySRx55hiNHMhg6dBDgxtmzpwkNrUFUVEMCAmz07h2Ft3cwoCMuLv6qP7vdoZBVAcsPZnE8t4KjWaUczSoho7DyslzeGCPrOV867NQO8aZOqA+NIn0Z0Dicx8c9iPncUQCaNWt21cf+LT169OD48eOsWrWKPXv2AM5uPt27d3e1ztwKoqKiiIqKutHVEOJvTYIIIYQQfzlFUSguLsbd3R29Xs/hwwc5dGgvQ4feBpRTUnIADw8foBY1ajgYNarrhSlWISjI/4plvvPOHJ544h0cDgc//DCDQYO6uNIaNUrAaDRgsVgpLi6rtu/UqZdaBkaNGuUKIJo3b89dd91N+/YdWbZsHWPHTqakpIyDB/fRtauNpKQugPNms0+fS4GJVqslIiLiqs+Hze5g+6kClh86z8+Hssgv18KB5Gr5gr0NJIZ4kxDixbfvvcGJPZuwFqQT1qI5bR55BM8iT8aOepoFCxYAzjEU99xzz1XX42poNBpuu+02brvttutarhDi5iJBhBBCiL/EuXPnsNlsREdHYjLlM2/eV3Tr1oyaNQMJCDhPYqIBRUlHpVLRrdulmZLUajV6vbNb0s8/b+W775Zy5MhZ3nprPK1bt3A9Aa9ZMxyHwwHAtm0HqwQRer2OTZs+IyEhGi+vqvP822w2HA4FvV7Htm17WLXqEBoNREcnMnLkS2i17mg0SfTrl0RJiY/rpvx/Lap2Nax2B9tO5rP84Hl+TsmisOLSNKl6tUKdMF/qhHqTGOJFQojzbz8PvStPJ9+xdOkyF+w2tm3bxrZt26od4+2338bX1/d311EIIX6NBBFCCCH+FHl5eezdu4cuXVqj1Zo5dmwjFksJ0dHNcHOD22+vT2CgG2AmODjAtdIzwPnzeaSlZdGypbPLTmWliffff48331xATo5zStX77ptAXFwI999/PwMHDqBVq/o0ahRP69YN6Nat+jSjzZolAc4ZlkpKyi/MzqRlzpy11K/fkMaNW5ORcZzMTGf+kSMH06ZN5ypl3HXXXa4g4tTFVeCugcXmYMvJPJYnn2fl4WyKKy8FDv4eenrWDaZ7nRoUHd3J7X1botP9+liGNm3asHLlSkaPHl2tLn5+frz55pt/+voKQoh/LgkihBBC/G4Wi4XS0lICApwBwMKF31OzZiiNGtVErT6H1XoMk8kdT093OnasVaXffGho4BXLbNRoGAcOpBIY6EtOzirMZjPjx49n//79GAyX8lVUQFZWFq+++iq5uTk8+OCD7Ns3p1p5ZrOFw4dPERcXhZdXIMeOZZGScpaRIzsDBjp08Lkw978XNWqEuPY7c+YMNruD4zllnC+uxEOvpaQgB413DRzmCtw9/vcCba7j2+xsPp7H8oNZrDqcRYnJ5koL9NTTs24IveuH0jLWH61GjdVqZXn1temuqEOHDhw/fpyVK1eyZcsWbDYb9erVY9CgQbi5uV1dIUII8TtIECGEEOKqmUwmkpOTSUxMwNtbz8GDW0lJOcjIkX2AcuLjVQQEmIAc/P119Olzac2FiwFEUVEpH344n127DpOYGMPrr4+vcoyQkAAOHIC8vCLS07NZuXIp+/fvB6BGDR1t2zamZcv6nDx5mK1bnV14PvnkU9q370CdOokA7N9/DIdDQ5MmzVCp9CQnJxMYGIWXVzR168ZSr54KcEYkMTExgHOcRmjt+tRoehs273DWqhKo+/wKzBdWeL4o4l+zADgL1HvhZ7yMWryNOryM2gt/dK6/s0tMrD6cTan5UuBQw8tAr3oh9KoXSotYfzRq1R/6TtRqtYxREEL85SSIEEKIf7gzZ87w3nvvMX/+fHJzcwkICKBv375MmjSJ2NhY1q1bhU7noF27RqjVRRw/vp6IiEK8vQNJTDRQq1YjoASAevXiXOWaTGb2708lONif2Nhw13adTsvUqR/jcDho1Ci+WhDRqVNTLBYrTZvWweFwuAYJq9Uqvvzyc+rWrQuAxWLl888/54svvsBigUmT3mH+/O8wGPxRFDuKogFqodfDvfeOdZV/cTrV3FIzyRlFHMgo5kB6EckZRRRWWHHvdqk+ZruCxmHBS2WhuLwSm0qL2uCBSuscm1BmtlFmtnG+2PQ/z3GIt5Hb6jlbHJpG+/3hwEEIIW40CSKEEOIf7KeffmLQoEGYTM6bYDc3KCs7x9y5n7B58yw++ugtwsJCL6xXkIFeD8OHd3Xt7+Fx5S4zK1Zs5fbbH8Nms/PCCw/w4otjq+xTr14tkpOPc+ZMJufOZRIeHuZKnzx5FJMnjwLg9Okz5ObmAdCkSXPc3X0v5NIxb9566tfvy9mz35JfZKegtIDzRYGg0WEMScRktbP1ZB5mq4NKqx2T1U7OxcAhvZhzRZdPmXqhVI2KxGBPTu1ez9l9G7CcP4614BwoDlcejUbDN7O/o3uffpSabJSarJRUOv8uNdkoufB3qcmGQaemW50gGkf6oZbAQQhxC5EgQggh/gGsViu5ubkEBwej0WjYsWMLycm7mTZtMiEhJqxWCAjQEB8fxdmzaZjNdjQaC5MmPcHs2XOIja0+Xen69buZO3cVBw4c5733nqJp0zqutISEaGw25wDoXbsOu7YrisKSJUvw9y8lKQkMhjL69etHkyaNGTPmPlq3buXKazKZ2br1ABWVYNEEcLo8gckfHECXWIPTecUU54ViSbbjcd98PFXO2Zs6vb3lqs+JSgW1anjSMMKXhpE+NIzwJTHUC4NWQ0VFM156qZzPPttH4WUBRPv27Xn55Zfp1KkTAIGehl8pXQghbm0SRAghxC1EURRUKucT77179+Ln50tsbAiFhWksXbqEQYM6EhjoRmhoEd9/vwx/f2cLRKdOnXjuuefw8/OlsLCI1157lXXr1lNSYuHZZ2dQr14zpkwZ7SobYMeOg64F3O67bwJNmkTRo0cP+vbtS0xMGO3aNSIuLpIuXZq56vbGG2+wYIFzH6MRFAVsNti7dx97946nX797aNi8Kz41W7DvrIYftxgpbvl/6INrccxuA5UK1YkCZwW0zhWjL3++r1GrcNNpMOo0GHVq12s3nQaDTo2Pm4564T40iPChfrjPr67k7O7uzvTp03nxxRfZs2cPlZWVxMbGEhcXd8X8QgjxTyNBhBBC3KRsNhtnz54lNDQUd3c3Dh7cy8GDexk27Hagkvz8vWi1XkAcAQF2hg5tiY+PFrARGRnM3r1bAXBzM/L440+Rn1+Kn58vfn6+vPjii+zY0YvjxytJSdkJ7GT06H6uGZX27NnDd9/9x1WX7OwiDhwo4sCBZGbN+pJ33/0/Nm36vEp9f/rpJxYs+AGTCTQaaNy4IW7etVix4RgVHvGoAhP56Jg3mkwrOr8LU5Z6N0TvDYrDjjU/HV9HMUO7tqRd/Zoc2L2dN9+YRk7WORSrmW++/A/D766+boOiKKxZs4affvqJ8vJyCqOjiRg+HC/jlWeHupybmxvt2rX7PV+PEELc0iSIEEKIvzGHw0FpaSk+Ps6n7jt37kSjsdO0aRI2WyFr1sylR48WxMQEEBpahFbrB5wDoHv3xq5yNBoNvr5ervcmk4mysnIUBQ4eVIiI6EPTpnXYvfsbADw9PalTpw6pqXspLXXuk5x8nNDQQNLS0pg4cSJQSXy8cxyFr68npaXOlaDz8vIYP34833//PQEBAZw4kc7RU3m8O2cnOd69KHWYiW/dm9TIRmQWlOLoWI6buzeqC12SUBRq1fCgYYQv9SN88HUUM2pAd0oK8jgPvPRV9fPUqlUrht4xuNr2w4cPc+edd3Lo0KEq25977jnGjh3LO++8g16vr7afEEKI/02CCCGE+BtxOBwcO3aM4OBg/P29OHEimfXr1zJ69AB0Oht6/Sk0GhWgx2iEkSM7YTQaAAeBgb4EBvpWK/P06XPMmPE1ycnHGTiwM08+eQ8GgwG9XofFYsVmcy54dujQSWw2G1qtFqvVysmTp/DxAZ1Oxdtvv+4a8/D1119TUVGJRgPdurVk8uQp1KhRg8NHUpn+3uckny4jI1fDna/vxy+uFSlHCsnPycEt+iE0EeCjOMhRqaHYhEqjIzYyjKQQD+Z/8hbl6UcI1FSw5vSJKp8hbPlSBg0aRObFleAu07lzZxYsWFBtYbbTp0/TqVMncnNzr3ieP/roI4qLi/n222+rdNP6oywWCwsXLmTt2rWYzWZq167NyJEjiYqKum7HEEKIG02CCCGEuAFsNhsajQaVSkVKSgqFhbkXplCtYPfuZTRtWgt//ygiIkz07VsfjaYIUNOoUe0q5TgDCEhLy2LLlv2kpJzinnt6k5AQc9mx7K6xCxdXhVar1XTs2JFVq1bj5uagRo0AevbsQHm5CU9PN95//32Kiorw8oKBA7syZEg3AKxWGytWrMCi8sJhjCRp4Cv833Y9G9esJ6tUQR05BaWGA3XWSVLt4ajPlIJbEO7RQViKsrDmp1Mz0J3HxtxFXJAncTW88HF33vyveWUvBeknKPHy4pdatmzJyZMnmTdvHkuXLqWkpISIiAhGjhxJ+/btrxgETJ061RVA1K1bl2effZa4uDiWLl3K9OnTMZvNzJkzhwcffJCOHTv+oe/zovXr1zNs2DDOnz9fZfsLL7zAo48+yr///e8qC+4JIcTNSoIIIYT4C2RnZ1NS4lxLITf3HIsXL2Dw4G74+xvQak+g1RYCzpvn4cM7olY7u/a4uxtxd3eua2C12jh+PI1jx84ycGDnKuUvXLiWxx6bCcD69SsJCAAfH286d+7C7bf3xd3dSEWFiYKCYtc+w4cPZ/Xq1URHA+STkbGV114rJiUlhaysbBwOcKChTe97WLi3gkWLNlCoCyO9ySfYbQ5M6YeY/lMpap0BuyEWlZsWrVqFoyQPW0kOptN7mPV/rxMX5EWwO4QFBWKz2aBGDfrNnFBlReVjx45x4oSz9eHXntgbjUZGjhzJyJEjf/N8FxQUMH/+fAD8/f3ZtGnThVWpoXnz5kRFRXH//fcD8Omnn16XIGLnzp306tXLNV3u5RwOB2+//TYWi4X333//Dx9LCCFuNAkihBDiT3D+/HlOnTpF27bNgAq2bVtGTs5RoA6+vnbat4/A3b0YMJCQEAFcmkJVrVZTUWFyBQ8X9e07kZUrtwOQnb2SoCB/V5qv76WpRo8fz6CyEjIyICXlMF999SWffvo4ffv2wMfH05Wvfv36TJo0iTfemA5ARlYRR3Mz0Ia2wpZYi/IyB4rKyKM/BQAlmDPd0Xhp0XoFoAU8o+vRs1EUiSHeJIZ4UTvYixBPDVER4RQWFuLl5cWAxt+4jjdo0CDmzZtHbm4uw4cP59133yUiIoLk5GRGjRrlync1QcJvOXr0KBaLBYDBgwe7AoiLRowYwcMPP4zFYnGthv1HPfnkk64AolOnTkyZMoWQkBDmzZvH9OnTsdlsfPDBB/zrX/9yLZgnhBA3KwkihBD/OLm5uZw5cwZ3d3cSEhIuLKR27UwmEyaTCV9f3wv94L+nVasGxMQEYjankpd3ALtdh0ajoUePRPbsKQHs6HRaEhNjqpVntdoYPPgpdu8+QmxsGFu2/KdKemJijCuISEk55QoiCgoK+PLLjwgLc06b6u7uHBhdVuYc6FxaWsbHH79Nu3ZNcXc3UlJSRkCAL4qiUOqIoNHAN9iT70WB3YfK0/twi26Cxt0HvbkCRXHgZdCSGOpFndY9SAzx5t2Xn2bnqiUoVhMNkz7g4XseBpyzIL3wwgsUFhYC0KtXryr1nzJlCkuWLMFsNrNo0SIWLVpEYGAgeXl5rjzh4eE88MADv+v7uNzFlhzAFUxczmaz4XA4quX9vY4ePcqmTZsAiI+P5+eff3YN2G7QoAFeXl5MnjwZgM8//5y33377Dx9TCCFuJAkihBD/GHv37uWll15i6dKlrhvIiIgIxo0bx+OPP/6bs/SUlZWRmppKgwb10WptbN26grKyAvr1a4deX0FcnAovr3zATkyMDzExHQDIz8/n/Pnz5OcXUFJSxqZN+9mz5wiNGsUzePCl1Z91Oi2HDp3i/Pk8iovLsNvtVfrPd+zYhOzsfOrWrUVkZLBr+/z58yktLSIkBOrWTWLq1OepXTuO9PQMXnttGuvX78Rmq+Q//5nDbX3vZd6KAxiSerIxtYQzx0FtqIHWJxgNUKtlDxpF+lA/0t/ZwhDqRbivW5UxB27338mg5XMBGDduHLNnz6Zp06Zs2rSpylP9Rx99tMr5a9SoET/88ANDhw6loqICoEoAERERwYoVK6q1GvwedevWxd3dnYqKChYsWMBrr71GeHi4K/2jjz5ydq3COd7ijzp48KDr9bBhw6pdS6NGjXIFEZfnFUKIm5UEEUKIf4Sff/6Z/v37Yzabq2zPyMhgypQprFu3jh9//BGdTkdZWRne3t4ArFy5gvDwAOrWjaGyMp2DB1dSs2YZvr4eNGnih1rtDzif+DdrluQqV1EUli9fw+LFC9i7d7dr+yeffMWaNc5Bt0OHdq8SRAA0bZpIYWEJUVGB3H//Q5SVFeHl5UWnTp3o168fgwZ1qfbZfvzxv1gs4OamZvr06Zw6lce5cyl06tSZadO+oWa9zjhCGvLZyRZ8M8+K1RKHemc2KpUKz7BatKoZQKf4GnRMqEHNQI/fnKlowIABTJw4kXfeeQeArVu3snXr1ip53njjDdq0aVNt3z59+nD8+HE++eQTlixZQlFREaGhoQwfPpx7770XrysMqv49vLy8uOeee/jkk08oLy+nRYsWTJw40TWwetasWa68//rXv/7w8S5vzboYIF2uvLz8inmFEOJmpVIURbnRlbgar7/+OgsXLuTo0aO4ubnRpk0bpk+fTkJCgiuPoii89NJLfPrppxQWFtKyZUs++OCDa+p7WlJSgo+PD3l5eQQEBPwZH0XcIqxWK8uXL6d3797VppYUfy8FBQXExsa6BjaHh4fTu3dv0tPTWbFihSvf889P5vbbe3LkyEHuuacPUMHu3fsIDPQlJibsqo83e/ZP/Otf0ygtrSQmBvwvDV1AUWD/fufftWpFcOLE4ir7HjmSyuTJT5GRca5auR4eHrz55r9p0aIFmzfvJzo6nMjIGCIj61BUBElJSWzfvo/Ne46SklnESbMPG1JzySmtGjjFBnrQ8ULQ0Co2ADf9tc8WpCgKX331Ff/+9785fPiwa3vz5s2ZPHkygwYNuuYyr7ecnBxatWrF6dOnfzXPxIkTr0vXonPnzhEdHY3dbicoKIiUlBQCAy8tZjdu3Dg+/PBDAF566SWef/75Xy1LflvEtZDrRVyt/Px8AgMDKS4udj0o+yNumschGzZsYNy4cTRv3hybzcazzz5Ljx49OHz4MB4eHgDMmDGDmTNn8uWXXxIfH8+rr75K9+7dOXbs2HV7uiXErS4rK4svv/ySAwcOoFaradGiBSNHjrwuXUxulP/85z+uAKJv37488cTjuLtraNGiLps2rWLo0GH4+ips3vwR48d3ISIiHnD267+8deFya9bs5Oeft7F37zEWLpyBt/elAcuKYqO0tBKAigqoVy+UFi1acODAAU6fPkNEBGi18PjjfauUWVZWxtNPP0Fm5nkcDrBYwMtLh9lspaAA0tLKufPOJ1i+fB2lpTWorKzFqdxQKmp0RxMTREZUPRq/vJ6iSuuFEi+sEmczU3HmAJWn9rBj8X9Iigr6w+dUpVIxatQo7r33XlJTUykoKCAoKIhatWr94bKvl6CgIDZt2sSYMWNYuXJllTQvLy8mTZrEM888c12OFR4eTv/+/Vm4cCE5OTk0adKEcePGERoayrx581i2bBkAOp2O++6777ocUwghbqSbJoi4/GkhwKxZswgKCmLPnj106NABRVF45513ePbZZ11PwL766iuCg4OZM2cOY8eOvRHVFuKmoSgKM2bMYOrUqVitVtf2OXPm8Mwzz/Duu+/eNDc/DoeD/fv3ExkZSY0a3ixf/j3e3s4Wgf/7vwcpL89Bo1EDHrRvX5uRI7uwevUaioqKSU8/Q5MmTQAwmy0cPnyKzMw8+vRpV+UYCxasca29sG/fMTp2bOpKO306Ba3WOcC5ZcsGLFz4KYoCW7ZsprLSxHPPPQfAmjU/8dBDY1wDe99551OOHz+P3Q7BwTW57bY+PProE5SWWhj70L/YtO8olR4J3Pf+FiLqtyZl20nKLal49bg09qCo0opWrSI+2Is2tQIoPb6DGU+NBbuV9u3bX5cA4nIqlapKi/DfTXh4OD///DNHjhxhxYoVlJWVER0dzcCBA6/7w6WZM2eybds2zp8/T3p6umsMxC/zXD42QwghblY3TRDxS8XFzrnO/S/0Ezh9+jRZWVn06NHDlcdgMNCxY0e2bt36q0GE2Wyu0kf64tNKq9Va5UZKiF+6eH3cKtfJ22+/fcWbHnD28b7//vvRarUMGzbsL67ZldlsNvLy8ggKCkKtVrNr1zYKCrLp2bMNUMmRI2swGGLx9Y0kOLiM6Gjn0//w8ADUaueNtNXqHFgbHR2NooBK5fwNuLg9KWkIp06dw9vbg5ycVVVm8WnUKN71+sCB47Rp09D1fv/+3dSvD1qtmi++mI6iOOurKAr16zembt16pKQc4vDhs8ycOZdHHhmHSuXBN99sIzUV1O4+TH1vNiaDL+9sKeLw+RLOtX6C8ObOweCZQOaZAgAMWjURnir2r/0RS84pLFknSAz1oWbb1iyfu5dt27a56jV+/Phb5nq9VnFxcYwfP77Ktut9LsLCwli3bh3jxo1jzZo11dJeeeUV7rnnnt887q322yL+XHK9iKt1va+RmzKIUBSFxx9/nHbt2lGvXj3A2QUDIDg4uEre4OBgzp49+6tlvf7667z00kvVtq9btw53d/frWGtxq1q1atWNrsIfVlZWxtSpU13v+/btS7du3bDb7SxdupR169YBzv7jHh4eN6zfbXp6OkajkeBgX0pKcti5cwcdOtTD319PdnYOJpOFLVvSAAgPV5Obe5bc3LMYDDouVvmLL74gKcnZRamoqIw331zA3r1HMBohNta5vsOWLZsBCAnx4dSpc5SUlPPDD/8lLOzSOCl/fy3Tpo0hPj6CgABv1z7OcgtRqcDNzZ21azdjNluJjAzBYjHy5ptzOX/ejUOHwKr2IjnDyOQv9pNj0lLa/CEiekagcffh+fX5QH6Vz6+ymanMTMWSc4q7e7ajXoQPwW6gUcHCI+V8vepnAJKzIXn/3ir79u3bF71ez/Lly6/rdyKqmzBhAgMGDODQoUNYrVZCQ0Np3LgxWq32ms7/rfDbIv46cr2I33KlSR/+iJsyiBg/fjzJycls3ry5WtovZxVRFOV/zjQyZcoUHn/8cdf7kpISIiMj6dy5swysFv+T1Wpl1apVdO/e/aYfzPbxxx+75tK/7777+Oijj1xp48ePZ+DAgSxfvpyioiIcDge9e/f+0+pisVhQq9VotVpOnjzJ0aMH6dOnI1DBsmUZhIToaNo0Ers9jK5d4/Dz8/qf8/ynpWXh7V2LtLRD+PrCsmXLaNKkCU2bNiU/v4Dt21/GbnegKFC7dhx33HEH4PzNuPvubGJiomjYsDYdO7avsrjb5RwOBzabHb1eR15eETabD0VFxWRllVFeXgNf/wh0oa1ZvmE3Sv06pBbuJejBR9B4+LER4MJzDn2EcxIIRXEQ6edOfLAXtYM8qRPqRd0wL+7s040ze/cAMOk/zxEaGuqqQ+/evenbty8zZsxg9+5Ls0HVqVOHxx9/nJEjR/7mrEvi7+FW+m0Rfz65XsTVys/P/+1M1+CmCyImTJjAjz/+yMaNG4mIuLTCa0hICOBskbj8P9acnJxqrROXMxgMGAyGatt1Op38YxRX5Va4Vo4ePep6fe+991b7PKNGjXI9QU1NTb2unzc/Px+LxUJoaCgmUxGzZ8+iW7cW1KxZA2/vNGrUKEGjOYtarWbAgFau/XQ6LSEhzn+7VquNY8fOcPDgCW6/vQOenpdaEY8ePcN77y0BQKOBrKxsxo0bj5eXJxUVFej1DsxmZ1enBx54sMpnGz/+TsaPvxNw/rZ8++23nD+fiUqlIzGxLgMG9EKl0vH992uJjY2jZct2eHo6iKt/B7tzdmGsVZdXdxrBz4hj+z5AA5hQhSZxcT6kCD83Z7AQ7MnG/85l7cJvsRZkcNdjj/LGpDdcN/4LFixg34UAon79+kRGRlYLCoYMGcKQIUM4efIk2dnZ+Pv7k5CQIMHDTepW+G0Rfx25XsRvud7Xx00TRCiKwoQJE1i0aBHr168nNja2SnpsbCwhISGsWrWKxo0bA84nmhs2bGD69Ok3ospC3DQu/2G5ON7ockVFRVfM+3sUFxeTkpJCixZN0GrNHDiw5sKCba0wGu107VoT5zOBUsLCAqp0IQKw2+1YLBZ+/PFHlixZQlpaGqdP28nMdPb13Lz5c9q2beTK36BBnOu1Wu0OOJtzS0udazvExYFeD08//TRdu1Zdg0FRFGw2O9OnT+fbbxeh0ThnTCouhrIyiI//js+/nIcutBPrMm188uUJ9qUVUujZhRr9nWU5ABRQKoowZZ3AknsWa14a9sIM/vvtZ3Tr1N51vF6hA2j8kbN75YwZM1i9ejVdu3blwIEDVWYXevTRR/9nYFCrVq2/1SxJQgghbj03TRAxbtw45syZw5IlS/Dy8nKNgfDx8cHNzbma6sSJE5k2bRq1a9emdu3aTJs2DXd397/NQFAh/q7atWvH//3f/wHw1ltvcdttt7kWxKqsrOS9996rkvdq2Gw2Vxlr1qwmNNSXpKQorNZ00tK2ULeuFR8fT9q0iUCvjwXsgHPthCuZNOldVq/eyfnzubRu7cmZM5fGOl22qDPvvPMpbdp84LrJjogI5tNPn6Vu3ZokJESzc+c2lixZwrlz5zAYDLRs2YohQ+4gLCycc+dyCA93Drpevz4Zq1XNkiU/8vXXiygvB4daj84vDH1wLYyNE8iJSGLwd6dRqap2p9Jr1MQF6Dm8aTm5R3diPncUe+mllZn1ej1fffVVlQACnCs6z5w509XFcu/evezdW3Vsw4gRIxg9evRVfQdCCCHEn+WmCSIu9tHu1KlTle2zZs1i1KhRgPNJYmVlJQ8//LBrsbmVK1fKGhFC/Ib+/fsTFhZGZmYm69evp0WLFowePRqLxcJnn33GsWPHAGjQoMEVVyG22+1kZmYSEBCAu7s7Bw/uYf/+ndxzT1+gHC+vTAyGckBFYCDcddelJ/5Go8FVxsGDJ9iz5wgGg54RI6qOuzhw4Dh79zq7XaWm5qPXO7dHRkagUhVQVlaBmxscOrSTBQsWMGTIEMA5TuqBBwa6yunVqxe9evUCYPfuw4SFBREWFklaWiH/XXaIdrcNptDizr7CSvYeOcWK9Dg8BszExzcYjbvPFc+fwVZGj6bxNI70pXGUL0lh3hi0GsoebMk333zD119/TUaGEZVKxZAhQ5gwYQIxMTFXLOuxxx4jJiaGV199tUoAER0dzaOPPsqjjz76P8eACCGEEH+Fm2bF6r+KrFgtrtattkroqlWr6NOnz69OAefp6cmqVato1co5LiE5ORmHw0qjRglYLMV8+eU3dO7cmNq1gykoKCA/v5hatSJ+9YbXbrejuawJoby8Em/vjjgcDho1imffvjlV8j/33IdMmzYLg0EhOhpq1w5lxox/U6dOIlarjfnz5/HWWzMBCAkJZsmSJahUKnJzCwkI8EWn07J//wnOns2nQ7derDtm4scfV2PzCKXCI5SzeaXkFpag0rv/z65CXkYtSaHeJAW78eHLT5Gfuge1pYzz58//z9+Ma71eFEXh2LFjnD9/Hh8fHxo2bFjlfIlb16322yL+XHK9iKv1j12xWgjx5+revTurV69mwoQJJCcnV0lr3boVzz33FMnJ22jcOAiDwYHVegSHw7nGil4Pw4a1vTCg2Y6/vw/+/tWf2h89eoYXXviE7dsPcv/9A5g69X5XmoeHG0lJsRw6dJJDh05iMpldrRQAjz8+HLM5jbVrVwPw5JNPUqdOIuAcZD1s2DB27NjJqlWbOXMmm717DxMf35gff0ymb9/bcfeNZPs5B8sP2HlixxFsDgWoCSYgvwgAtcEDD72GSH93Ivzc2LB8EdmnDkN5PhuXLyI22Acft0v/SWf+VJNP963GjnNwetu2bf/4F3GBSqUiMTGRxMTE61amEEIIcb1IECHEP5jdbqewsBA/Pz80Gg1+fr7MnPkGPj46Dh/ew/btu+nRozUDBnSioqKSzEw1Gk0uoKVp07gqZV0+I1J6ehbbth2kTZsGRERcmh1Np9Myb55zLvPt2w9Wq8/48UMpL6+kadM61Z66+/v7UFJShKKA3Q516zrXiElNzWDHjmOMGHEX8fHd+PjjzVgscOqUG/F1k9DV0jDlpyK2nDx1IXDwARTqhHrTLNqPCD83V9AQ6eeOr7vO1RLR4K37KD14EI1GQ+0abni4VX3Kd/lCldLFSAghxD+JBBFC/AM4HA7XTe7evXvx9fWhZs1wCgrSWbRoMQMHdqZGDXfc3U/j41NCs2ZJNGvWjWHDOl0YHK3g7m4kLi6ySrlWqw2tVlOl+8/nny/mgQdeBeCzz57j/vsHuNJq1gwnMNCXigoTRqO+Wj3Hjh18xfpnZuZSUWHCy8ubsjLIzYWffz7B8OEdCQyMpWHDWByOcLZtO44VdzzqtmJ2mhdTp63Gar/UYzMxxIu+DULpXT+UmjU8f/O8tWzZkoMHD2K32/nwww956qmnXGnnzp1jwYIFALi7u1O3bt3fLE8IIYS4VUgQIcQtxmq1cvLkSSIjI/HwcCc5eRfJyfsYMeJ2wER+/l40Gk+gCH9/OwMGNMLPzw5UVpsZ6eLsSr80c+a3fPPNcg4fPs3Jk4urtDYkJES7Xl/stnSRSqVi586viIwMvmLZF4OdwsIStm07SKdO7XF3D+DMmRwKCuw0bHgvb721FoC33/4PPXsOJTAwEJ27F69+u5JVplpETpiNSqvjYAGAQkKwF30uBA5xQb8dOFzuoYce4vPPPwdg0qRJHDlyhNtvv52TJ0/y9ttvU15eDsDw4cOvS/9SIYQQ4mYhQYQQNyGLxUJBQYFrkcXNmzei0ym0bFkPh6OYTZt+oEePFnh4BBAeXorRWAM4D0D37o1d5Wg0ml9dhfn7739m796jlJVV8uGHk6ukZWcXsH9/KgDJycerBBENGtSma9cWtG5dn+7dW1YrNzY2HHB2pSouLnONnVi8eCshIRG0atUOnU5BrTZhtdYEfGjVyjlA22Qy8dxzU0nPzOJQtok6gx4hpH47St3DQaPFLa4FAD5UMLpbQ/rUD6V28O+fna1p06Y89thjvP322yiKwqxZs5g1a1aVPDExMbzyyiu/+xhCCCHEzUiCCCFuAjabje3bt1OrVjShoX6cPZvCunXrGT36dnQ6O35+WRfGEJzBYIAxY7pfeK8QEOBLQIBvtTLtdjvHj6dz6NAJ/Py86dq1RZX0V175gsOHT6HX6/i//3sSne7Sz0WDBrVRq9UkJERjsdiq7Ofj48nq1R9WO57D4SAtLYuAAB+8vLw5ciSLHTuOMnr0fajVXtSr54OnpydQA09PuO22Xq59s0rM7E0rZM/ZQuLHfQZ5lajUzvqUXshjzU+n/OgmWoRoWTbn8+s2S8lbb71FYGAgb7zxBqWlpVXSunfvzqxZswgODv6VvYUQQohbkwQRQvyNWCwWdDrnwN59+/aSn59Jt24t0GrLKSjYS0REIRBGVJSDoUNbotVWACrq1q26OvHlg5Iv3rx7e3tUmTEpPT2bOnXuAKBfvw7Vgoh69Wpx+PApLBYrqalnqxxj0KDODB7cxTV7kqIoHDhwgEWLFnPixAm0Wg0NGjSgZcsO+Pr6Ua9eXcCdtWu30qpVe5KSGlKzZjzBwS1QqXwAFXFxzoHaFpuDw+dL2HO2kL1phew9W8j5YlOVuqnUWgwOEyWnDlCedhDTmf3E1XDnufHjeeCBB361G9bvoVKpeOaZZ5gwYQKLFi3i7NmzeHp60rNnT5KSkq7bcYQQQoibiQQRQtxARUVFKIqCn58feXmZLFw4l0GDuhIYqMfHJwO1uhxIB6Bfv0vThxoMegyGqgOTLy75cvkg53fe+ZopUz7GZLLwyiv389xzD7nSoqJC8PR0p6ysgkOHTlar26OP3sW99/ahYcN4wsJquLabbQpFFh35ZQ7yysxkF5n57oefOHo2FxsRVBR4oguuxbr9eipX7iXYz5fWvWuhUZlRVC3Yux80yfvRqFSoVCo06kw0ahWg4mROGQcyijDbHFXqolGrqBPqRdMoP5pE+9E02o9wXzes1tvJysrCaDRSo0aN/7m+wx/l5eXFyJEj/7TyhRBCiJuJBBFC/IUKCwtJS0ujYcP6QAXr1y/G21tLly4N8PWtpFOnaDw9ywADNWuGX1WZ778/l3nzVnPo0ElSUuYRGhrI4cOHmT59Btu2HcJ04SH+u+9+zvHj25k06WmSkpJQq9VMmHAnRqOe+vWrTtdabnZwnDiOmmwsWuMgv6yAgnIH+WUOikvKsJcXofN31q/86GY0noEYYzvisJqxcxhNYG00Rk88wptSBqw6nH1N58nXXecKGJpE+dEw0gd3ffWfK71eT1RU1DWVLYQQQog/ToII8behKAo7duzgp59+ory8nOjoaO666y5q1Kjx2zv/TTkcDjZs2EDt2lFERPhSVHSE5OQt1KljQq/X0qVLLG5uRsCKVqslPj66WhmKorBw4Vq2bk2mvLySjz9+pkr66dOZbNq0D4BDh06Qm5vJv/71MCaTCaPRuRCc0QhubnDo0CEeeOABPvzwQxo2bMi0aeOqlFVqcvD1tgo+31ROQakFlUaHYrdiSjuIvkYsGk8/7GUFWDOPEhYZjbdBwwGHDWtuGvbc0/Tu0p6ug+5G5bCxfPlP/HfZMlQqNV4+Pkyb9joqtQaHomB3KDgUBYcCdoeCoihYbHbCfd1oFhtAzUCPP7VVQQghhBB/jAQR4m/hxIkTjBgxgh07dlTZ/uSTT/LII4/w+uuvX9d+7tdbeXk5bm5uqNVq9u7dRWbmafr2bY9aXY7FchSbrQwIIybGSGxsN9d+3t5Vpxx1OByUlJTj63tpRiGVSsWjj77JuXO56PU6XnhhNKGhoa70evWcYxXCw4MoKirjo49mYLrQ/BAfH8NTT/UHVCxZspjTp89gMpl54YUXWLhwoWvtiMzcct798TTL0wIoMauoPLOfIHcYc3cfani5c2Z/OU0aNyKhZjR+Ri0+7jo0Gg3PP/88a//7JgCvvfYaz0wa5qrXPe0TGJy6iYULF1IG+OUPp3///lU+b0lJCR9++CGff/45J0+eRK1W07ZtW8aNG8eQIUNkATchhBDib+rve1cm/jEyMjLo2LEjmZmZ1dIsFgtvvvkmRUVFfPbZZzegdleWmZmJ3W4HFPLzz/Hjjwvp378DwcFuBAXlYjAAOD9Pz56XBiz/2tP17Ox8Ro16iW3bkunTpx2zZzsXa8vKyuK9996nsjIPAIvFSo8et9O9ewcmTHiE2NgYhgzpxsCBnfH19WL79u2cPZsGQN26SXz++efo9c6xE0OG3MGYMfdz7NhR0tMzeO+9r2jb+TbWnw/k85/TyD2yB4/E9tSOqMHwrr3olhhEVOSFdSNaxV+x3qdPn3a9/mWAADBgwAAWLlwIwKlTp6qkpaen07VrV44fP+7a5nA42LRpE5s2bWLx4sV8++231VauFkIIIcSN97uCiPLyct544w3WrFlDTk4ODkfVQZC/vFkQ4n+ZOnWqK4CIi4tj0qRJ1KpVi2XLlvF///d/2Gw2Pv/8c8aMGUPr1q3/snrZ7XYURUGr1ZKRkUFKykF69uwAVLJ378/o9Q58fErw8wume/c4/PxsgImIiOAq6yZcZLFYmDdvMT/9tBF/fw86dGjGbbfdhpeXF/7+PmzYsIfKSjNbthwAnCsi33fffeTm5hEYCL6+4OEBOh1s2LCRPXv28sknH5OYmOg6xr59+1yvBw8ewrFjacTFReDm5sn+/Zn8f3v3HR5Ftf9x/L1JNpVU0kgjoRNCDyWAlyYdBFHpCKIiIiAgV/T+rgL2BohY0XtBRQEVRaVJrgJSpIXee00oCZBCSN35/RFZWQOYDYEAfl7Ps48758yc/U5yiPPdmXNOuXKN+emn3WThw6wN7kzdn0yehwnD7E39u7szok0VOsSU+32g819zd3e3vj9y5EihVZsPHz5sfe/h4WF9b7FYuPfee60JhMlkol69epw7d87692P27NlUqVKFCRMmFCkWERERuXmKlUQ88sgjLF++nP79+1OuXDk9uyzFdv78eWbPng2At7c3q1evto6BaNmyJVFRUQwbNgyADz/88IYmEadPnyYrK4uIiAjy8jKZMeMT/vGPelSpEoKDw2EcHA6Sl+eHk5MTbdtWx2QysWrVShwcHKwLqF3NypUrGTHi32zalAFAYCCsXv0zb789haFDH6dPnz40bFiDXbsOU69eNbKyspkwYQJnzhTcgQgN9aJ9+/aYzWYWL/6J5ORkMjIyePbZZ/nPf2ZYp27dtes4Z8+CYYCjYwTr1p3B3z8ON7cIqlaNoGJMNkYdJ8rWac9JsysANUK8GN6qMm2jg3AoYvJwSdu2bZk2bRoAL774Ii1atLAmFsePH+e9994DCpKE1q1bW4/7+eefSUhIACAqKooFCxZQvXp1DMPg66+/pk+fPuTn5zNlyhSefvppmwRERERESl+xkohFixaxYMECmjZt+tc7i1zDrl27rM/v33fffYUGUT/88MOMGjWK3Nxc60Xn9bBYLOTn52M2m0lJSWHt2t9o1SoOV1eD3bt/5dy500RENMHJKZ/mzcMJDrYA5wgJ8SYkpLG1HWdnM7m5eYXa3759P3Pn/sKqVVt46aXHadgwhrVr1/LUU0/9/vhTgYyCXIKsrCwmTZqMxWLw/feT8PIqGFC8d+9eEhI2AlCuXDCff/45vr6+5OXl0bhxKyZOfJU9e/aTkHCMl1/+gjfffAMHBw8CAppw+PBPAMya9TMzZ87EZDJx4vxFPlx+gpm7vfBq0A2AUNdcXuwVR8uqgcX+IuCee+6hfPnyHDlyhDVr1lC5cmV69OhBRkYGc+bMsS7O1rlzZypW/GOdiTlz5ljfv/HGG1SvXh0oSDZ69OjBggUL+Oyzz0hNTSU+Pp5u3boVKz4RERG5MYqVRPj6+uLn51fSscjf3KV1Dv5cdqXyojp//jxnz56lQoUKQC5z5nxOpUohNGhQFbP5NE5OR8jN9cLV1YMmTcJxdIwECi72K1e++tShhmFw+HBiodh++20b48cXfDPfpk0jGjSowRtvvEleXj5OTlC1qj+NG9ejYcMapKQcYt68eQC8//57dO7c2Xoxv3btOmubd93Vlp07k2jatBKOju4cOLCN5s2HMXfuSAAyMpwAX8CB0aOfYuLESaRdzGHuiq2kjHqLslViWXs8kzwLYHIk69gOcjf/wE9rF/++QnTxmc1m5syZQ5s2bUhPTycxMZG3337bZp8KFSrw0Ucf2ZSdOXPG+r5JkyaF2m3atCmfffZZoX1FRETk1lCsqU9efPFFnn/+eTIzM0s6HvmbiY6OxtW14LGauXPncuqU7XoCn3zyCXl5Bd/4x8bGXrGN3NxcLl68CEBmZiZLlvxESsoJ4CxHjqxn5cpvgK3AVuLiAqhY0Rk4i5eXE23bNsbTs+BRGScnpyJ9Iz9hwjTKlm1NlSrdSUxMsalr2rS29f327QfYtGmTdVxATEwMO3YsYMaMVxg6tC/PPfdv7r//PgCys3P5/vvvAUhJOc/PP+/g1Ck4eBDc3Wvj7FwNiMRkCqRfv0do2PCPuyIWBzMJR8/zn5WH+Pf8fVQYNoPwkXMI7vMau12jWXW0IIHIOrKFk18+y6kvx/LiE32uO4G4pFGjRvz222906dLF5ufn6urKww8/zOrVq21mkwLw9/e3vv/zjFwAa9assb4vW7ZsicQpIiIiJadYdyImTpzIgQMHCAoKIjIyErPZbFO/cePGEglO7nze3t707t2b6dOnk5aWRlxcHP/85z+pVKkS8+fPtz5TDwVjcaBg7MLevXtp1iwOyGbx4nm4uzvRunVDnJ0zyM3dQ36+A+BHjRpe1KzZEsgFIDIypEhxzZmzhDVrtnH69DnrTEmXODk5cu5cGgDbtx+mR48/6qpVi+TLL18iLq4W5cuXs3ls5557ulhnGrJYLJw7l0a3bt34+uu5nDoF8+dvYeDASnh6momKasqJE/EArFu3ieHDRwNwMSefnUlpvPbtGsp2HIVzcCX+5x1B/Ie/XRahGZMJ8tPOkJ20j+yT+8g6soWcpL04OzszceJEhg4dWqSfQ1HVqFGDH374gRMnTrBr1y6cnJyoU6cOPj4+V9z//vvv57///S8AY8eOpVatWlSsWBHDMPjxxx/5/PPPAfDy8qJt27YlGquIiIhcv2IlEXo+WUrSiy++yJIlSzhx4gSHDh2yucA1mcDFBZo1iyMoyAE4TFbWIU6f3kRenhknJycaNQrAyckRSMHJCTp1+mOszrXWlsjLy2PnzkPk5OQSGxttUzdp0hesW7cDgPfffwZv7z++ta9XrxrBwWWpV68anp5uNsc5ODjQu3d7m20oGOh86tQ50tIy8PLyYv/+ZJYt20p0dAybN18aCB0MeOPsXLA+xtvvf0yWa1m+33OBVv/6FAe/cA6lXCTfAEyVKPP7KtMGEOTlQs1QH2qFeVMzzJuaod7kXzjPjBmnSEgAwmtTv/4gBg4cSFBQ4ZmjSkpoaCihoX+90na7du2oVasWW7duZd++fVSpUoW4uDjOnj3Lrl27rPsNHTq0xO6YiIiISMkpVhIxbty4ko5D7jCGYZCYmEhaWhrBwcH4+voW2icrKwvDMAgNDWXu3G946KF+nDx1kDLRzclz9sdkZONbLpBa0VWoERXKiuPp7LxwHA9nZ4JrNWZ7kgUP5zzcXbxxdjaRk2fg7FS0AcJnz6YSFtaRixezadkyll9++dCmvn796tYkYvv2/TRtWsda1759E5KSfiI3N49Vq1Ze9TPOnDmHu7sf+fkFA6nfeWcedes+QFxcHSIisunatQ4jRozAMMDJO4iQhh2ZtGQPO5PS2JmYhvdDH+H9e1sHLUBywSNb+RfOkZ20j5yT++nYuAZvPz+aQC/XwgGUCWLs2LFF+nncbA4ODsybN4/WrVtz6NAhLBYLq1atstnn3nvv5YUXXiilCEVERORarmuxuYSEBHbt2oXJZCI6Opq6deuWVFxymzIMg88//5zJkyezefNmoOCCsUuXLgwdOpTIyEiqVKkMZPH11zOoXj2c2NjKVKySS6+nxjD/aFlOZ7vj/Ht7GcDqdFi9FdiaB6Re8/PdzQY1QszUDncmwCmN9T8tZNf6dTzYvwOPPXafdT8/P2/8/Lw5ceI0CQm7sFgsNqsjP/ZYd+69twV161bD39/H5jOuNm4iKyubjRt3U6NGFby9QzhxIpWMjHKYzfU5cCABOMngIaPp8eiTnMeTXzbtJcmpHuEj78PBxYPvzgC/7LdpswxZnNqTQO7pQ+ScOkjO6QPkp6f8HuNjvPf62Nt2MbaoqCg2bNjA1KlT+eSTTzh+/DgADRs25IknnqBv37637bmJiIjc6YqVRJw+fZpevXqxbNkyfHx8MAyD1NRUWrZsyezZswtN0ymlLzs7m1WrVnH27FmCgoKIi4u75qM+xWEYBkOGDLGuG3CJ2Wxh5crv2bBhPv369eG110YBFu6+uwJmV3emrzrFtF8vkJQaDkBZDwceiHXD2Qkysw0u5Bhk5hhcyP79vzkGmdkGmTkWMrItZFzMJ5+Ci83MXBPrj+Sx/kge4AQu92CJbcX7u85zdlE6tULN1ApzIszXka5dm5OScp7Y2Ghyc/NwcXG2xly79pVXaL50npcSif37T+Dispe4uGY4Oblx7NgBypePwts7lJo1y+MTlkVflwoc/ehLTP5RpAZV4D/Hf79rEFCbS/cPHE0G1UO8iS7nVfAK8aZaOU+8XM3s3l2DadOmsWbNESz+lahT534GDx5MvXr1SuT3Vpr8/PwYN24czz//POnp6ZjNZtzc3P76QBERESlVxbqKHD58OGlpaezYscM6v/vOnTsZMGAAI0aMYNasWSUapBRffn4+r7/+OlOmTOH06dPW8vDwcMaOHcvQoUOvOSPRnj17+OGHHzh//jwhISHcf//9Ns/Up6enc/z4capXr86MGZ/w2WfT8PEBb2+oV686zs7unD59iNTUsxhGPsuXzyYpqQeefkHM2+PKf1ZmkJxRsOJ5kJcDj/3Dg94N3XFz/iMmwzBISkpm//5j/OMff1w45+fn07p1X7Yu3w8OjpSv6Ip3sD95XhXJ96qMxacq2e7lcXAtQypl+Gj5BeuxPu4matZ7lPphZmJCzZxIc8DbzUIZVxMuf3okKiMjE5PJhIeHG4mJKSxZkkCPHvdjNnuRmRmKg0MVIIqzmVn41WzLrO3n2bJ4LVuPp5J6sWBAt1udTtb2LNkXyDm5n5xTB3HPOcc/H+3F0H73YXa88mRp1apVY9KkSdf4Ld/+TCYTXl5epR2GiIiIFFGxkojFixfzv//9z5pAQMFUne+9997faiaV48ePM3XqVL744gsSExPx8fGha9euPPnkk9SpU6e0w8NisdCvXz/ritCXO3bsGMOGDWPfvn2F5vWHgrn5Bw0axPz5823KR44cSfv27Zk8+VUqVQohOXk3q1YtJSqqLYsWvUalSgWDoV9+eTxdunQGCqZgHT9+PIsX/0SWxZnR/93JzjwHUi8WrLEQ5uvI4y08uL++G2YHo9Cqye3aDSM+vmAa0LS05dYpWWfOnMmxY78//mPJx8vVlTYNo1i/fi0ZSb8A4OngzRsffkayxZetx3PZdiKXXUl5nM80WLEvhxX7cgqdu2NuOq65afiHR1DGxZGzW5cTEBJBxRr1cMGH82ejWPjaUo4fPsi5C1nMOraDnJ/OkZKZX6gtZycHost5USfch5qh3liSD3Jw8w7yAyCm9z106NCh0OxmIiIiIre6YiURFovlihc+ZrMZi8Vy3UHdDlasWEGXLl1ITf3jGf1z584xY8YMPvvsMz766CPrlKSlZebMmdYEwmQycd999xEbG8uvv/7KwoULAZgyZQodO3a0Sf4SExP5xz/+wYEDBzCbsb58fcHNLY/du+fzxhvJfPjhO5Qvb2bQoLYkJiZy4MBBnJ2hZs0YawIBBf1iwOCRfHsgmKywTvyW7g4YVAhw5IkWZbi7Coz952TefGw75csH8/33tt+6ly//xxoDu3cfpkGDGuTm5jFr1izc3SEgAPr0uZdHHulJTEwl0tMzeOqp0QUrPltSOXtwNT0feICeDQrayM4z2HMyryCpOJ7LxkMX2Lt1Oxbf8ji6e3PxfAqppw+R4RaCyZRPvns0Jy64snXTpTUsPAteIQWzEF0EyMwHw6BKkCe1w30KXmE+VA32xNnp8jsMYdDuHyXw2xUREREpPcVKIlq1asWTTz7JrFmzCAkpmHf/xIkTjBo1itatW5dogLeipKQkmwTCbDYTExPD/v37SU9Px2KxMHjwYKpUqcI//lF6F4xTp061vv/666+5776CgcVjx45l4sSJjBkzBoB3332XnJwLhIX5U6dOFf7zn3FcuHCAmBgICvLh3nsfoHz5SA4e3MOsWbPIycklIWENy5f/SsuWLQDIyMiwflbFipWs75NS85n26wVmrcsnK/IBAJwyjvL24Jp0iHHF0cGEYRjMnfsLycnnOXbslM2YA4AmTWpx/PhpoqOj8PHxBGDnzh2cOZOMszP06/cPJk36P+v+np5lGDNmDL179wFg6dKlPPDAA2RkZFKmjDsuTibSj+wmJNuBfvffjcXizoIF+dSp2wCvsoGkZmaTmWshIyuP9Ow80rPyyMjKY92mLXz65VeYnN1xcHHD5OwOlnxyTu4jO3EvOacO0O6hB3lztO3qzCIiIiJ3mmIlEe+++y5du3YlMjKS8PBwTCYTR48epWbNmsycObOkY7zlfPjhh9YEonXr1nzxxRcEBQVx4cIFxo4dy3vvvYdhGLz++uullkSkpaWxYcMGoGCl5Pbt27N06VLq1q2Bj48Ld91Vg8jIMri4ZJCcHE/58n3x9U0nP/8IK1Z8S0gIODo68PHHnxAVFfl7q+2oXr06zzzzLABz535jTSIurUBsmBz4dfsZ3l+azrrDuazen0PO70/5ZCfuJfW32ZQz9tL53f9ZYzWZTDRuXJOFC1cRERFESkqqzYxIDz10Dw89dM+fzi/d+r5KlcKDoCtXrkxubsGjVenp6Rw7lsqiRevo3bsXnp7BBAf7kJ+fD4SQkZFG48ZN8fPzw9HREW+3wnfZDMPghQFtOb9nDwB9+vRhzJgxbN68mVOnfBk3bgFGbg7Tpk1j9OjRVK1atWi/KBEREZHbULGSiPDwcDZu3Eh8fDy7d+/GMAyio6O5++67Szq+W9KlgeMODg7MmDGDwMBAluw4yd3Vg3j77bf58ccfOXr0KIsWLeLcuXNXXCPhRsjJyeHs2bMEBweTlZWFk1PBQm0xMb44Ox8hNXUz2dm5QFlq1fKiXr1ADh/OIDc3m5iYiphMJpKSkkhJOQsUTLX5RwJRoHXr1vj5+XL27Dl27txJXr7B9sRc1hx0Ja/JW5w3R3DW2Z03fvpjEHOtcvnkbJzGT58vACA7tGyh2N9/fyy+vl6UKeNepHO9lLQA1mTp5MlkEhOTqVevJmvWbOXoUcjOhvLlKxAU1Ix27Sri5hYKOBEVFcXnn39Onz59SEhIAApmCho4cCBPPfWU9Q7bJatXr2bP7wlEkyZNmDlzJnl5eRw9epR+/foB8OyzBcnVf//7X15//fUinYeIiIjI7ei65vhs06YNbdq0KalYbhunThU8G1+hQgXCwsKYve4oz3y7jRZVA5jUow5Nmzbl6NGjGIZBcnLyDUsiDMNg8+bNhIaGEBjozbFjO/j55//x4IMdKVs2h/r1PcjIuMCRI2tJSztOt25/3BVJSkri8OGDANa7SZfavORKc/Tn5RukmaM4G9iSzIg61HnhNBnZvx/jUQ0TkJ+VAae34ZOzkyDjGCfiCy7y/fzA09ON8eOHFmo3PDy4SOeckZFJbm4e1apVJTw8goSEoyxZspnJk+fQuvU9HDp0HkdHg4ceeolLw1X69OmHs7Mz5cuXLziHvDz69u3LV199ZdP22bNnmTRpEl988QX/+9//iImJsdZdSiAAevbsWWhGq169elmTiMv3FREREbkTFTmJeOeddxg8eDCurq68884719x3xIgR1x3YrczPz4+0tDSOHDlCcnIyjg4mXJwcWLbnDB2nrCDlUIp13+tNIPLy8jhz5gwBAQE4OTmxaVMCp04do337uzCZMtm//1fc3MIJDCxPeHguPXo0wsUlG5PJxAMP3MOXX84iOzuHJ598kqeeeorq1auzadMm3nrrLetndO3a1fo+MDAQHx8fzp8/z5o1azl27DjpjkGs2JfDmoM5LN+ZhqVWwSrCFwGyDbxcTTSq4ExVnyz+9egIcs8cwc/XQmAknLvsXBo2DODdd9+lYsWKRT7/s2dT2bXrEE2a1MNkcmflyh0YhjMdOjTkvvte4PvvBwIwevSbeHl9RFBQEPv27bMeX7VqVbp3727T5quvvmqTQMTExFCuXDl+/fVXsrOzOXXqFF26dGH37t24uLgAWP8LBTNX/dnlZZfvKyIiInInKnISMXnyZPr27YurqyuTJ0++6n4mk+mOTyK6d+/OpEmTyM3N5YknnmD69OnEhDZl6BcJHErOxLjrCbwsntRxS7Z57OZacnNzrTNerV+/Hl9fbypVCuX8+RP8+ON3dOvWgsBAd3x9E3F0zAIOA/DAA82sbTg7m3F2/uN5/n79+v3+SNV5du3azSOPPFroc0NDQ2wusp2cnHDzrMaWMxYcgxvQcnIaec6XdRNHF/KzMsg+tp2G5eG1pzpRvZyTdYB0nS/G4O/vTnz8YlasWMGFCxcIDAykY8dOdOvWFU9Pzyuef15eHk5OThiGwXff/Uq1atFER9cmO9uDxMRTXLxYFXd3d+Lign//ObnTv/8ADh8+yvPPPw8UjANJS0uztlmxYkUWLlyIs/Mfi8hlZWVZk2AHBwe++eYbunXrZn2Uq1OnTmzatInDhw/z7bff0rt3bwCaNWuGyVRwjh9//DHDhg3Dz88PKFiv4uWXX7Z+RosWLa72axYRERG5I5iMy59fEdLS0vD29iY5OZmyZQs/uw9w6NAhoqOjycrKAgruNjRp0oTtu/dxIfoePKJbAFDD12DmsLb4ejjbHJ+Xl8fx48cJDAzE3d2VLVvWsWXLRh58sCtwkaVLlxMQUIaYmEpYLBZSUzPw9i6Dg8OVFyO7ln379jFy5ChOnjxpLTMMyMkBT89AHn54EI88cj/Hzubxy+5sftmdzfLdF8DhssHF+VmYz27FfHYL+UnbOLn7MFWrlOP9918lNjba7pgA0tMv4ObmgpOTEwkJ+9m37zS9evUGPNm4cQchISEEBxftEac1a9YwdepUlixZwsWLF6lQoQKDBg1i0KBBhRYwi4+Pt05n27Nnz0JraCxdupRWrVoBcN999/HNN99Y67p168b3338PFIzJGDBgAGfOnGHLli1s2bIFAG9vb44dO3bVZEn+vnJzc1m4cCEdO3bU2iByTeorYg/1FymqlJQU/P39SU1NLZEFXos1JuKFF15gzJgxuLvbDoK9ePEib775pvWb4TtVVFQUs2fPpkePHuTk5HDu3DkWLCgYNMyBt8g6uo3A9k+w45wDHd9Zwbt96uKde5a8vDyqVSuPxXKOJUtm0bp1XSpWDCAi4iJlyoRiGEmYTCZatqxj/SwHBwd8fYv/i65cuTJz537DL7/8ws8//0xqaiplynjzzrurcA4JZOLPecxJS2bf6bw/DnIwk5d6iuxDG/DJXIfnxW2YLAWLsplM0OvJzjz77DO4uroWOY7U1Ayys3MIDPTjwgULs2atpm3b9kRGRlO+fHl8fFKBgrs29erVu3Zjf9K4cWMaN25cpH1TUv541Cw2NrZQfYMGDazvz549a1P37rvvsnHjRo4dO0ZycjITJ060qXd0dGTGjBlKIEREROSOV6wkYsKECQwZMqRQEpGZmcmECRPu+CQCCsYRrF+/nrfeeouvvvqK7OxsoGCw+VNPjcK9XCUen/gFifm16PHRb9wXmkiHaBPVql2wrm3g7l5wEe7r63VdicKV7Nt3lIkTZ7Jq1RYGDuzCU0/1o1WbDizclsXPu7OJePIsmN25COw7nYejA9Qvb6ZVNRdq+F4gwjuIiIhB7N7dlOXLl5GenoG/vz/t2rUtNHPRlWRmZnHgwHFq1KiAg0MZ1q/fQ2Ym3HNPSzw8nOjQIZigoCDAGX9//yI/9nW9Lr+7sWLFCutaGZf8+uuv1veBgYE2dWFhYaxevZpRo0bx3Xff/T5FbIG6devy5ptv/i3WSREREREpVhLx58XALtmyZYv1OfG/g8jISF566SU+/vhjzp1L4aeffiQmJor69SuRlnaKN/sG8v0JJxbvga+OhZDi4UKdCxZ8PRysCcT1ys3NY/PmPVSoEErZsj425R999C0Av/66kdY9ejD6q1QOnvn9wtfsjgvZ1ArIpk+LEFpVd8fb/dLjUmWs7VSvXo3q1asVKZZNm3bj4+NNVFQVMjLMrFt3htDQVvj5BRAXF/H72ISCLhceHn69p14sTZs2JSQkhMTERH744Qc+/PBDHn30URwdHdm1axcjR4607turV69Cx4eFhfH1119z4sQJfv31V9avX0+vXr1o0KDBFf9NiIiIiNyJ7HrI3tfXFz8/P0wmE1WqVMHPz8/68vb2pk2bNvTo0eNGxVoqLBaL9S5DZmYmS5b8xNmzicA5Dh5cyy+/zMbFZT/BwSdp2jSI8uUdgXN4eTnToW0DPhgYzCv3euHsBD/vzqbTO8kkHMkpkdg+/3wBPj4taNhwAAsWrLSpq1YtEj8/bxzNLhz3ieO+D85y8Ew+AZ4ODGvpwdzH/dj5SgRfP1WFe+uXuSyB+GuXhtEcPpzIggW/Ab5AOMnJXqSlhQFVCAioycCBj+PnFwCAh4fHLfGsptls5umnn7ZuP/7444SFhVG7dm2io6OtMzvFxMTQuXPnq7YTGhrK/fffT/Pmzalbt64SCBEREflbsetOxNtvv41hGAwaNIgJEybg7e1trXN2diYyMpK4uLgSD7L05LBgwbd4eDjRqlV9nJ0zyMvbQ16eA+BHdLQnNWo0BwoGWFeqVPjbdZPJRJ9G7tQON/PEF+c5nJJPj4/O0qzMFs6smsq5syl4eXnTqlVLevXqZV3L4JL163cQH7+W9et38vHH/7ZZyTksLIjMzILPXrVqCw8++MdFr4ODAzO++4j3N3qx66QFLNCltisvdvXCx46EwWKxcPFiNh4ebuTl5TFnznIaNWpMpUoxODv7UaaMF3l5ETg5OdGmTReb877SOhO3ghEjRrBv3z7ee+89AE6ePGkz8LxixYr8+OOPODld1zIqIiIiIncsu66SBgwYABQMLG7SpMkt8c3yjZKTsxHwIzbWF7PZCTiLkxN07NjUus/l06n+lRohZn4cXpbHPjnM6uPuLE+rjTn4UcokTyYnOZlZs75m5sxvmTz5ZZuVv7/4YjFTphSskD1kyH20axdHcnIy58+fp0KFYCpUCKVRoxhat25oPSbfYvCflZm8taQMOXkWfNxNvNTNi8613P4yzry8PBITkwkJ8cfJyZmVK3eTnHyR7t0fwMmpDDVquODrGw74ERLiR0hIVJF/BrcKk8nE1KlT6dy5M1OnTmXp0qVkZWVRuXJlHn74YR577DGbBFlEREREbBU5iUhLS7NOB1W3bl0uXrzIxYsXr7hvSUwbVdqcnQu+RS9XruQG/GacO82xrwbi4ducC1UHkxvQiAvN3uf8ys9I3r4aU14m//rX/xEWFka1agXjEBo0+GMK1blzF/PNN/9l48ZN1rJWrery4IMduOuugvUijqbkMebrVNYdzgWgZVUXXr/Pi0Cvq98VOHDgOGazExEREaSlObB48S46d76XkJAKxMSUJy8vDyi4qK5Tp06J/TxKk8lkon379rRv3x64+jgfERERESmsyEmEr68vSUlJ1hWNr3TBdelC7PJZa6TgkaAtW/bywgtvc+RwJgEXFlE/0oWD5R7h+Hk/3FuOJPyuoWQeWM/5tOXM+OxLXnulYFXoVq0a8NlnEzhxYh9ffTWTP//YN27cxMaNmxg+fDjO1R/gpQXpZOYYeDib+HdnT3o1cCv0uzp5MpkdOw7RqlVzTKYy7N17AE9PLyIiauLra9CrV0VrIvh3GSivBEJERESk6IqcRPzyyy/WC8qlS5fesIDuRDk5uTRu/BA5Obm4uEBIiBNTxj+Bk5s3M1Zl8t9fTnEODzyqNiWHpszJuUDOnLPcW8+DuApliYkJ4e23x1kTiMjI8sTE1GT79m0cPnwEi4sfL68sS+7ugtWaG0aZmfiAN+F+Bb9ewzD46ac1VKpUlUqVYjAML7KycsjJqYCLiwvt24dZL6JNJtMdcSdJRERERG6cIicRzZs3v+J7KXDyZDLvvvsVK1ZspmXL+owf/5i1ztXVhUaNYlixYhPZ2VCuXHl8fX0BGN66DMNaebAzKY8nJy7gYF4FLG6BfLsph2835eBfxgGftCRyvavilLqHRx4exOOPP47JZMIwDEZM/JH5SdUxzJ44GHn8q7Mvg5q6s3fvEX5cdYouXe7BZPLC0/Mizs7lgXKUKwedOlW2xqdv4UVERETEHnZN8XrJ4sWLWbnyjylF33vvPerUqUOfPn04d+5ciQV3K8rLK1iXITHxTKG6l1/+L7/+upH4+LWF6p544gEqV3alWjU4c+YEmZmZ1jqTyUS1IAdcdn+Mz8qH8d4wlp71nfF1N5GcYWG/Qz3SGk4k7R//JT2qL/tO53HugoVhs1L54UwDDLMnprO7yP/+UVqHOeDgUBFPz1iCgmIxjFDAi6ZN7yIiIuJG/mhERERE5G+iWEnEP//5T9LSCh6d2bZtG6NHj6Zjx44cPHiQ0aNHl2iAt5Iff/wVb+8W1K3bly+/XGxTFxzsT+XKBRfpKSmphcaF9OzZlv792+HuDhcvZjFp0iRycwsGP1ssFqZNm8bJk6cwYdA82pvXH/Bj3f8F8mEfd5yTlkLeRfJcAnl/aQZtJiXT+NXTfLt4CzmHNhB45lcSP3+Go3vO4OgYAfgSGlqehg0b6i6DiIiIiJS4Yk2Ef+jQIaKjC2YNmjt3Ll26dOGVV15h48aNdOzYsUQDLC0DBoxj6tR/EhUVai2LjAyxrsuwdu32QsfMnPkCoaGBhIYGXrHNXr168+OPP5Kfb+G77+axYsVKatWqye7du0lMTLLu17dvXwDMjiZaVnUl6OCHXNj5Ltl+DfAObsBJ3wZkm7yoGBnO0MaBPPpAR3Ky8vH29i61laBFRERE5O+jWHcinJ2drY/j/O9//6Nt27ZAwUw+l+5QlKb333+fqKgoXF1dqV+/PitWrLC7jQULVrJ69VabsujoKGJiKtKzZxs6dWpW6JiGDWOumkAAVK5cieeffx4Hh4K7A8nJyfzyy1KbBOKJJ56gXLlLC8458dNP2wgLa8au7dnsXLISx4Pr+eaRunw6qCGfDmrE51Nfs/4u+vXrpzsPIiIiInLDFetORLNmzRg9ejRNmzZl3bp1zJkzB4C9e/cSFhZWogHaa86cOYwcOZL333+fpk2b8tFHH9GhQwd27txp95iAhIRd9O3bwbrt6OjItm1zriu+zp07ExERwWeffcby5cuxWAyys6Fhw3o88sijhITUYPHidfTp04gyZfyJiwuhfPlGzJ+/Cshg5cqVxNaKJjw8nGPHjmEYBgBlypRh1KhR1xWbiIiIiEhRFOtOxLvvvouTkxPffPMNH3zwAaGhBY/8LFq0yLp4V2mZNGkSDz/8MI888gjVq1fn7bffJjw8nA8++MCudlas+IQ333zyhsRYrlw4Dz74GMuX/8YPP6zkqafeYejQqTRpMoSwsDj69HmMMmUKFrkLCAigdu3a/PDDD9apVw3D4OjRo9YEwsvLi++//56KFSvekHhFRERERC5XrDsRERERzJ8/v1D55MmTrzug65GTk0NCQgLPPPOMTXnbtm1ZvXr1FY/Jzs4mOzvbun3pcazKlcOxWAwslrzrjisvL48tW/YRGRlK2bLhJCVlsG1bFlWr1iEw0IGePetiNputA61dXFys7y9p1qwZ27Zt4+OPP+abb74hOTkZf39/7r//fh599FHKlStX6Bi5sS79vPVzl6JQf5GiUl8Re6i/SFGVdB8xGZe+zrZTfn4+8+bNY9euXZhMJqpXr07Xrl1xdHQs0QDtkZiYSGhoKKtWraJJkybW8ldeeYVPP/2UPXv2FDpm/PjxTJgwoVD5/Pkv4eHheh2xpJCefpGKFauQm+vKsmVbqFChGsHB5awre4uIiIiI3AyZmZn06dOH1NTUEllYuFh3Ivbv30/Hjh05ceIEVatWxTAM9u7dS3h4OAsWLCj1x2r+fIF+rYv2Z5991mZa2rS0NMLDw4mNbYCfn3eRPzMjI5O1a7cTG1sfb+8Qtm49xpkz6TRv3gaAu+/uV4wzkVtZbm4u8fHxtGnTBrPZXNrhyC1O/UWKSn1F7KH+IkWVkpJSou0VK4kYMWIEFStWZM2aNfj5+VkD69evHyNGjGDBggUlGmRR+fv74+joyMmTJ23KT58+TVBQ0BWPcXFxwcXFpVC5k5MTZvO1fzwJCbuwWJxo0KApZcq4kpOTisVSCbM5kPr1I4t9HnJ7MZvN+sMtRab+IkWlviL2UH+Rv1LS/aNYA6uXL1/OG2+8YU0gAMqWLctrr73G8uXLSyw4ezk7O1O/fn3i4+NtyuPj420ebyqu06fP8tVXS8nKKgNEYTZXx2yuBoRjNgdwzz3dCAy8+hSvIiIiIiJ3gmLdiXBxcSE9Pb1QeUZGBs7Oztcd1PUYPXo0/fv3JzY2lri4OKZNm8bRo0cZMmRIsdpbtGgNAQGhxMY2w8MjinLlXMnPDwM8qFXL7y+PFxERERG50xQriejcuTODBw/mP//5Dw0bNgRg7dq1DBkyhHvuuadEA7RXz549SUlJ4YUXXiApKYmYmBgWLlxI+fLl//rgy1gsQUAFIiJc8fT0BPzx8IC77rrrhsQtIiIiInK7KFYS8c477zBgwADi4uKsz1fl5ubStWtXpkyZUqIBFsfQoUMZOnTodbVhsfgDbtSoUaNkghIRERERuUMUK4nw8fHh+++/Z//+/ezcuROA6OhoKlWqVKLBlSYnp2L9aERERERE7njFvlL+z3/+w+TJk9m3bx8AlStXZuTIkTzyyCMlFpyIiIiIiNx6ipVEPPfcc0yePJnhw4cTFxcHwG+//caoUaM4fPgwL730UokGKSIiIiIit45iJREffPABH3/8Mb1797aW3XPPPdSqVYvhw4criRARERERuYMVa52I/Px8YmNjC5XXr1+fvLy86w5KRERERERuXcVKIvr168cHH3xQqHzatGn07dv3uoMSEREREZFb13UNrF6yZAmNGzcGYM2aNRw7dowHH3yQ0aNHW/ebNGnS9UcpIiIiIiK3jGIlEdu3b6devXoAHDhwAICAgAACAgLYvn27dT+TyVQCIYqIiIiIyK2kWEnE0qVLSzoOERERERG5TRRrTISIiIiIiPx9KYkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG7KIkQERERERG73BZJxOHDh3n44YeJiorCzc2NihUrMm7cOHJycmz2O3r0KF26dMHDwwN/f39GjBhRaB8REREREbk+TqUdQFHs3r0bi8XCRx99RKVKldi+fTuPPvooFy5c4K233gIgPz+fTp06ERAQwMqVK0lJSWHAgAEYhsHUqVNL+QxERERERO4ct0US0b59e9q3b2/drlChAnv27OGDDz6wJhFLlixh586dHDt2jJCQEAAmTpzIwIEDefnll/Hy8iqV2EVERERE7jS3RRJxJampqfj5+Vm3f/vtN2JiYqwJBEC7du3Izs4mISGBli1bXrGd7OxssrOzrdtpaWkA5Obmkpube4OilzvBpf6hfiJFof4iRaW+IvZQf5GiKuk+clsmEQcOHGDq1KlMnDjRWnby5EmCgoJs9vP19cXZ2ZmTJ09eta1XX32VCRMmFCpfunQp7u7uJRe03LHi4+NLOwS5jai/SFGpr4g91F/kr2RmZpZoe6WaRIwfP/6KF/CXW79+PbGxsdbtxMRE2rdvzwMPPMAjjzxis6/JZCp0vGEYVyy/5Nlnn2X06NHW7bS0NMLDw2nZsiVly5Yt6qnI31Bubi7x8fG0adMGs9lc2uHILU79RYpKfUXsof4iRZWSklKi7ZVqEjFs2DB69ep1zX0iIyOt7xMTE2nZsiVxcXFMmzbNZr/g4GDWrl1rU3bu3Dlyc3ML3aG4nIuLCy4uLoXKzWaz/jFKkaiviD3UX6So1FfEHuov8ldKun+UahLh7++Pv79/kfY9ceIELVu2pH79+kyfPh0HB9vZaePi4nj55ZdJSkqiXLlyQMFgaxcXF+rXr1/isYuIiIiI/F3dFmMiEhMTadGiBREREbz11lucOXPGWhccHAxA27ZtiY6Opn///rz55pucPXuWMWPG8Oijj2pmJhERERGREnRbJBFLlixh//797N+/n7CwMJs6wzAAcHR0ZMGCBQwdOpSmTZvi5uZGnz59rFPAioiIiIhIybgtkoiBAwcycODAv9wvIiKC+fPn3/iARERERET+xhz+ehcREREREZE/KIkQERERERG7KIkQERERERG73BZjIkRERETuJFlZWTazTRaXxWIhPDycxMTEQtPfy99PQEAArq6uN+WzlESIiIiI3ERZWVmcPn2a0NBQHB0dr6sti8WCt7c3Xl5eSiL+5vLz8zlx4gSBgYE3JZFQbxMRERG5ic6cOVMiCYTI5RwdHQkNDS2RO1xFoSRCRERE5CZTAiE3ws3sV0oiRERERETELkoiRERERETELkoiREREROSWcvjwYUwmE5s3by7tUOQqlESIiIiIyFWZTKZrvgYOHFjaIUop0BSvIiIiInJVSUlJ1vdz5szh+eefZ8+ePdYyNzc3m/1zc3Mxm803LT4pHboTISIiIiJXFRwcbH15e3tjMpms21lZWfj4+PDVV1/RokULXF1dmTlzJikpKfTu3ZuwsDDc3d2pWbMms2bNsmnXYrHw+uuvU6lSJVxcXIiIiODll1++YgwWi4VHH32UKlWqcOTIkZtx2vIXlESIiIiIlLJJkyYRFhZGWFgYy5Yts6k7dOiQtW748OGFju3duzcRERGEhYUVqpsxY4b12G+//fZGhc/YsWMZMWIEu3btol27dmRlZVG/fn3mz5/P9u3bGTx4MP3792ft2rXWY5599llef/11nnvuOXbu3MmXX35JUFBQobZzcnLo0aMHGzZsYOXKlZQvX/6GnYcUnR5nEhERESllaWlpnDhxAoDs7GybuksrEQOcO3eu0LEpKSnW+j+7cOGCtS4zM7MkQ7YxcuRIunfvblM2ZswY6/vhw4ezePFivv76axo1akR6ejpTpkzh3XffZcCAAQBUrFiRZs2a2bSRkZFBp06duHjxIsuWLcPb2/uGnYPYR0mEiIiISCnz8vIiNDQUABcXF5u6SysRA/j6+hY6tmzZstb6P/Pw8LDWubu7l2TINmJjY2228/Pzee2115gzZw4nTpwgOzub7OxsPDw8ANi1axfZ2dm0bt36mu1eeiTq559/vqHxi/2URIiIiIiUstGjRzN69Ogr1kVFRXH8+PGrHjtr1iy8vLxwcCj8lPrAgQNvyuxJl5KDSyZOnMjkyZN5++23qVmzJh4eHowcOZKcnByg8GDsq+nYsSMzZ85kzZo1tGrVqsTjluLTmAgRERERKVErVqyga9eu9OvXj9q1a1OhQgX27dtnra9cuTJubm78/PPP12zn8ccf57XXXuOee+5h+fLlNzpssYPuRIiIiIhIiapUqRJz585l9erV+Pr6MmnSJE6ePEn16tUBcHV1ZezYsTz99NM4OzvTtGlTzpw5w44dO3j44Ydt2ho+fDj5+fl07tyZRYsWFRo3IaVDSYSIiIiIlKjnnnuOQ4cO0a5dO9zd3Rk8eDDdunUjNTXVZh8nJyeef/55EhMTKVeuHEOGDLlieyNHjsRisdCxY0cWL15MkyZNbtapyFWYDMMwSjuIW0laWhre3t4kJydTtmzZ0g5HbmG5ubksXLiQjh07alEd+UvqL1JU6it3vmPHjhEeHl4ibVksFtLS0q46JkL+fq7Wv1JSUvD39yc1NRUvL6/r/hz1NhERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYuSCBEREREpthYtWjBy5EjrdmRkJG+//XapxSM3h5IIEREREflLAwcOxGQyFXq98cYbvPjii1c9zmQyMW/evJsXqNwUTqUdgIiIiIjcHtq3b8/06dNtygICAnB0dLzhn52bm4vZbL7hnyNFozsRIiIiIqXEMAwyc/Ku63UxJ79YxxmGYXe8Li4uBAcH27xat25t8zjT5SIjIwG49957MZlM1m2AH3/8kfr16+Pq6kqFChWYMGECeXl51nqTycSHH35I165d8fDw4KWXXrI7XrlxdCdCREREpJRczM0n+vmfSuWzd77QDnfnG3spuH79egIDA5k+fTrt27e33rH46aef6NevH++88w533XUXBw4cYPDgwQCMGzfOevy4ceN49dVXmTx58k252yFFpyRCRERERIpk/vz5lClTxrrdoUOHa+4fEBAAgI+PD8HBwdbyl19+mWeeeYYBAwYAUKFCBV588UWefvppmySiT58+DBo0qCRPQUqIkggRERGRUuJmdmTnC+2KfbzFYiE9LR1PL08cHOx7St3NbP83+y1btuSDDz6wbnt4eNC7d2+720lISGD9+vW8/PLL1rL8/HyysrLIzMzE3d0dgNjYWLvblptDSYSIiIhIKTGZTNf1SJHFYiHP2RF3Zye7k4ji8PDwoFKlStfdjsViYcKECXTv3r1Qnaurq83nya1JSYSIiIiI3DBms5n8/Hybsnr16rFnz54SSUikdCiJEBEREZEbJjIykp9//pmmTZvi4uKCr68vzz//PJ07dyY8PJwHHngABwcHtm7dyrZt2zQL021CU7yKiIiIyA0zceJE4uPjCQ8Pp27dugC0a9eO+fPnEx8fT4MGDWjcuDGTJk2ifPnypRytFJXuRIiIiIjIX5oxY8YVy5ctW2azffjwYZvtLl260KVLl0LHtWvXjnbtrj6ovDjrWMjNozsRIiIiIiJiFyURIiIiIiJiFyURIiIiIiJil9suicjOzqZOnTqYTCY2b95sU3f06FG6dOmCh4cH/v7+jBgxgpycnNIJVERERETkDnXbDax++umnCQkJYcuWLTbl+fn5dOrUiYCAAFauXElKSgoDBgzAMAymTp1aStGKiIiIiNx5bqs7EYsWLWLJkiW89dZbheqWLFnCzp07mTlzJnXr1uXuu+9m4sSJfPzxx6SlpZVCtCIiIiIid6bb5k7EqVOnePTRR5k3bx7u7u6F6n/77TdiYmIICQmxlrVr147s7GwSEhJo2bLlFdvNzs4mOzvbun0p4cjNzSU3N7eEz0LuJJf6h/qJFIX6ixSV+sqdz2KxYLFYSqStS9OgGoZRYm3K7c1isVzx70dJ/025LZIIwzAYOHAgQ4YMITY2ttD8wwAnT54kKCjIpszX1xdnZ2dOnjx51bZfffVVJkyYUKh86dKlV0xWRP4sPj6+tEOQ24j6ixSV+sqdKzw8HG9v7xJtMz09vUTbk9tXSkpKoXHDAJmZmSX6OaWaRIwfP/6KF/CXW79+PatXryYtLY1nn332mvuaTKZCZYZhXLH8kmeffZbRo0dbt9PS0ggPD6dly5aULVv2L85A/s5yc3OJj4+nTZs2mM3m0g5HbnHqL1JU6it3vsTERLy8vEqkLcMwSE9Px9PT85rXO/L3UbZsWWrWrFmoPCUlpUQ/p1STiGHDhtGrV69r7hMZGclLL73EmjVrcHFxsamLjY2lb9++fPrppwQHB7N27Vqb+nPnzpGbm1voDsXlXFxcCrULYDab9cdbikR9Reyh/iJFpb5y53JwcMDBoWSGpV56hMlkMpVYm3J7c3BwuOLfjpL+e1Kqvc3f359q1apd8+Xq6so777zDli1b2Lx5M5s3b2bhwoUAzJkzh5dffhmAuLg4tm/fTlJSkrX9JUuW4OLiQv369Uvl/ERERERK2tq1a+nTpw/+/v54eHjQuHFj3nzzTc6fP39DP3fgwIGYTCaGDBlSqG7o0KGYTCYGDhx4Q2O405lMJubNm1faYRTJbZGyRkREEBMTY31VqVIFgIoVKxIWFgZA27ZtiY6Opn///mzatImff/6ZMWPG8Oijj5bYLUMRERGR0vTqq6/SuHFjZs2aRUpKCllZWezZs4dnnnmG2rVrs3fv3hv6+eHh4cyePZuLFy9ay7Kyspg1axYRERE39LOvl9YOK1m3RRJRFI6OjixYsABXV1eaNm1Kjx496Nat2xWngxURERG53cyZM4d//etf1m1vb2+qV69u3T569CgdO3a0ucAvafXq1SMiIoJvv/3WWvbtt98SHh5O3bp1rWWGYfDGG29QoUIF3NzcqF27Nt988421Pj8/n4cffpioqCjc3NyoWrUqU6ZMsfmsZcuW0bBhQzw8PPDx8aFp06YcOXIEKLgr0q1bN5v9R44cSYsWLazbLVq0YNiwYYwePRp/f3/atGkDwM6dO+nYsSNlypQhKCiI/v37k5ycbHPc8OHDGTlyJL6+vgQFBTFt2jQuXLjAQw89hKenJxUrVmTRokU2n1+UdkeMGMHTTz+Nn58fwcHBjB8/3lofGRkJwL333ovJZLJub9myhZYtW+Lp6YmXlxf169dnw4YNf/GbuvFuyyQiMjISwzCoU6eOTXlERATz588nMzOTlJQUpk6desXxDiIiIiK3E8MwrI9wA4wbN46TJ0+yfft21q1bR0xMDAAHDhzgq6++uqGxPPTQQ0yfPt26/d///pdBgwbZ7PPvf/+b6dOn88EHH7Bjxw5GjRpFv379WL58OVAwliMsLIyvvvqKnTt38vzzz/Ovf/3LGnteXh7dunWjefPmbN26ld9++43BgwfbPXj8008/xcnJiVWrVvHRRx+RlJRE8+bNqVOnDhs2bGDx4sWcOnWKHj16FDrO39+fdevWMXz4cB5//HEeeOABmjRpwsaNG2nXrh39+/e3znhkT7seHh6sXbuWN954gxdeeME6E9v69esBmD59OklJSdbtvn37EhYWxvr160lISOCZZ565NcZLGWIjNTXVAIzk5OTSDkVucTk5Oca8efOMnJyc0g5FbgPqL1JU6it3vqNHj9p9zPbt2w3AAIzGjRtby/Pz841z584ZK1assNa3bdu2JMO1GjBggNG1a1fjzJkzhouLi3Ho0CHj8OHDhqurq3HmzBmja9euxoABA4yMjAzD1dXVWL16tc3xDz/8sNG7d++rtj906FDjvvvuMwzDMFJSUgzAWLZs2TVjudyTTz5pNG/e3LrdvHlzo06dOjb7PPfcc4V+PseOHTMAY8+ePdbjmjVrZq3Py8szPDw8jP79+1vLkpKSDMD47bffit2uYRhGgwYNjLFjx1q3AeO7776z2cfT09OYMWPGFX8OV3K1/pWcnGwARmpqapHbupbbYp0IERERkb+zyyeOad68eaH6uLg4zGYzubm5NvveCP7+/nTq1IlPP/0UwzDo1KkT/v7+1vqdO3eSlZVlfXzokpycHJtHnj788EM++eQTjhw5wsWLF8nJybE+ZeLn58fAgQNp164dbdq04e6776ZHjx6UK1fOrlhjY2NtthMSEli6dCllypQptO+BAwes425r1aplLXd0dCw0beqlmT9Pnz5d7HYBypUrZ23jakaPHs0jjzzC559/zt13380DDzxAxYoVr3nMzaAkQkREROQW5+vra31/pYXEdu3aZV2R+PJ9b5RBgwYxbNgwAN577z2bukvTzi5YsIDQ0FCbukuPmX/11VeMGjWKiRMnEhcXh6enJ2+++abNdP3Tp09nxIgRLF68mDlz5vDvf/+b+Ph4GjdujIODg3W17kuutCKzh4dHodi6dOnC66+/XmjfyxOUPz8uZDKZbMouPVZ16Vyvp92/Wml8/Pjx9OnThwULFrBo0SLGjRvH7Nmzuffee6953I2mJEJERETkFlenTh3Kly/PkSNH+Omnn5g1a5Z1ra3U1FSefPJJ677du3e/4fG0b9/eOttRu3btbOqio6NxcXHh6NGjV7xrArBixQqaNGnC0KFDrWUHDhwotF/dunWpW7cuzz77LHFxcXz55Zc0btyYgIAAtm/fbrPv5s2b/3KsQL169Zg7dy6RkZE4OZXcZXBJtWs2m8nPzy9UXqVKFapUqcKoUaPo3bs306dPL/Uk4rYcWC0iIiLyd+Lo6MioUaOs23369KFOnTrce++91KxZk19++QUoeAxowIABNyWeXbt2sWvXLhwdHW3qPD09GTNmDKNGjeLTTz/lwIEDbNq0iffee49PP/0UgEqVKrFhwwZ++ukn9u7dy3PPPWcdSAxw6NAhnn32WX777TeOHDnCkiVL2Lt3r3U2qlatWrFhwwY+++wz9u3bx7hx4wolFVfyxBNPcPbsWXr37s26des4ePAgS5YsYdCgQVe8eC+qkmo3MjKSn3/+mZMnT3Lu3DkuXrzIsGHDWLZsGUeOHGHVqlWsX7/eZlau0qIkQkREROQ2MHz4cJvF3LZu3coPP/xAeno6UHDxPm/ePHx8fG5KPF5eXlddi+vFF1/k+eef59VXX6V69eq0a9eOH3/8kaioKACGDBlC9+7d6dmzJ40aNSIlJcXmroS7uzu7d+/mvvvuo0qVKgwePJhhw4bx2GOPAQV3P5577jmefvppGjRoQHp6Og8++OBfxhwSEsKqVavIz8+nXbt2xMTE8OSTT+Lt7X1dK36XVLsTJ04kPj7eOmWuo6MjKSkpPPjgg1SpUoUePXrQoUMHJkyYUOxYS4rJ+PMDZX9zaWlpeHt7k5ycTNmyZUs7HLmF5ebmsnDhQjp27HhrTLUmtzT1Fykq9ZU737FjxwgPDy/WsYZhMHPmTKZMmUJCQgIAbm5u9O7dm7Fjx1oH8Mrf19X6V0pKCv7+/qSmppbIQswaEyEiIiJymzCZTPTv35/+/fuTkpJCeno6bm5uBAQEXNc36SL2UhIhIiIichsqW7Ysvr6+pKWllXYo8jeklFVEREREROyiJEJEREREROyiJEJEREREROyiJEJERETkJrueNQlEruZm9islESIiIiI3UUBAACdOnFAiISUqPz+fEydOEBAQcFM+T7MziYiIiNxErq6uBAYGkpSUxPUu12WxWEhJSaFs2bKa4lUIDAzE1dX1pnyWkggRERGRm8zV1ZWwsLDrbic3N5fNmzdTs2ZNLU4oN5VSVhERERERsYuSCBERERERsYuSCBERERERsYuSCBERERERsYsGVv/JpVkS0tPTNUBJrik3N5fMzEzS0tLUV+Qvqb9IUamviD3UX6So0tPTAa57RrBLlET8SUpKCgBRUVGlHImIiIiISMlKSUnB29v7uttREvEnfn5+ABw9erREfsBy50pLSyM8PJxjx47h5eVV2uHILU79RYpKfUXsof4iRZWamkpERIT1Wvd6KYn4k0sLtXh7e+sfoxSJl5eX+ooUmfqLFJX6ithD/UWKqqQWJdTAahERERERsYuSCBERERERsYuSiD9xcXFh3LhxuLi4lHYocotTXxF7qL9IUamviD3UX6SoSrqvmIySmudJRERERET+FnQnQkRERERE7KIkQkRERERE7KIkQkRERERE7KIkQkRERERE7KIk4jLvv/8+UVFRuLq6Ur9+fVasWFHaIckt4Ndff6VLly6EhIRgMpmYN2+eTb1hGIwfP56QkBDc3Nxo0aIFO3bsKJ1gpVS9+uqrNGjQAE9PTwIDA+nWrRt79uyx2Uf9RQA++OADatWqZV0gLC4ujkWLFlnr1U/kal599VVMJhMjR460lqm/yCXjx4/HZDLZvIKDg631JdlXlET8bs6cOYwcOZL/+7//Y9OmTdx111106NCBo0ePlnZoUsouXLhA7dq1effdd69Y/8YbbzBp0iTeffdd1q9fT3BwMG3atCE9Pf0mRyqlbfny5TzxxBOsWbOG+Ph48vLyaNu2LRcuXLDuo/4iAGFhYbz22mts2LCBDRs20KpVK7p27Wr9n7n6iVzJ+vXrmTZtGrVq1bIpV3+Ry9WoUYOkpCTra9u2bda6Eu0rhhiGYRgNGzY0hgwZYlNWrVo145lnnimliORWBBjfffedddtisRjBwcHGa6+9Zi3LysoyvL29jQ8//LAUIpRbyenTpw3AWL58uWEY6i9ybb6+vsYnn3yifiJXlJ6eblSuXNmIj483mjdvbjz55JOGYejvitgaN26cUbt27SvWlXRf0Z0IICcnh4SEBNq2bWtT3rZtW1avXl1KUcnt4NChQ5w8edKm77i4uNC8eXP1HSE1NRUAPz8/QP1Friw/P5/Zs2dz4cIF4uLi1E/kip544gk6derE3XffbVOu/iJ/tm/fPkJCQoiKiqJXr14cPHgQKPm+4lRiEd/GkpOTyc/PJygoyKY8KCiIkydPllJUcju41D+u1HeOHDlSGiHJLcIwDEaPHk2zZs2IiYkB1F/E1rZt24iLiyMrK4syZcrw3XffER0dbf2fufqJXDJ79mwSEhLYsGFDoTr9XZHLNWrUiM8++4wqVapw6tQpXnrpJZo0acKOHTtKvK8oibiMyWSy2TYMo1CZyJWo78ifDRs2jK1bt7Jy5cpCdeovAlC1alU2b97M+fPnmTt3LgMGDGD58uXWevUTATh27BhPPvkkS5YswdXV9ar7qb8IQIcOHazva9asSVxcHBUrVuTTTz+lcePGQMn1FT3OBPj7++Po6FjorsPp06cLZWsil7s044H6jlxu+PDh/PDDDyxdupSwsDBrufqLXM7Z2ZlKlSoRGxvLq6++Su3atZkyZYr6idhISEjg9OnT1K9fHycnJ5ycnFi+fDnvvPMOTk5O1j6h/iJX4uHhQc2aNdm3b1+J/21REkHBH/L69esTHx9vUx4fH0+TJk1KKSq5HURFRREcHGzTd3Jycli+fLn6zt+QYRgMGzaMb7/9ll9++YWoqCibevUXuRbDMMjOzlY/ERutW7dm27ZtbN682fqKjY2lb9++bN68mQoVKqi/yFVlZ2eza9cuypUrV+J/W/Q40+9Gjx5N//79iY2NJS4ujmnTpnH06FGGDBlS2qFJKcvIyGD//v3W7UOHDrF582b8/PyIiIhg5MiRvPLKK1SuXJnKlSvzyiuv4O7uTp8+fUoxaikNTzzxBF9++SXff/89np6e1m97vL29cXNzs87trv4i//rXv+jQoQPh4eGkp6cze/Zsli1bxuLFi9VPxIanp6d1XNUlHh4elC1b1lqu/iKXjBkzhi5duhAREcHp06d56aWXSEtLY8CAASX/t8Xu+ZzuYO+9955Rvnx5w9nZ2ahXr551Wkb5e1u6dKkBFHoNGDDAMIyCKdPGjRtnBAcHGy4uLsY//vEPY9u2baUbtJSKK/UTwJg+fbp1H/UXMQzDGDRokPX/NwEBAUbr1q2NJUuWWOvVT+RaLp/i1TDUX+QPPXv2NMqVK2eYzWYjJCTE6N69u7Fjxw5rfUn2FZNhGEYJJT8iIiIiIvI3oDERIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiIiIiJiFyURIiJS4pYtW4bJZOL8+fOlHYqIiNwAWrFaRESuW4sWLahTpw5vv/02ADk5OZw9e5agoCBMJlPpBiciIiXOqbQDEBGRO4+zszPBwcGlHYaIiNwgepxJRESuy8CBA1m+fDlTpkzBZDJhMpmYMWOGzeNMM2bMwMfHh/nz51O1alXc3d25//77uXDhAp9++imRkZH4+voyfPhw8vPzrW3n5OTw9NNPExoaioeHB40aNWLZsmWlc6IiImKlOxEiInJdpkyZwt69e4mJieGFF14AYMeOHYX2y8zM5J133mH27Nmkp6fTvXt3unfvjo+PDwsXLuTgwYPcd999NGvWjJ49ewLw0EMPcfjwYWbPnk1ISAjfffcd7du3Z9u2bVSuXPmmnqeIiPxBSYSIiFwXb29vnJ2dcXd3tz7CtHv37kL75ebm8sEHH1CxYkUA7r//fj7//HNOnTpFmTJliI6OpmXLlixdupSePXty4MABZs2axfHjxwkJCQFgzJgxLF68mOnTp/PKK6/cvJMUEREbSiJEROSmcHd3tyYQAEFBQURGRlKmTBmbstOnTwOwceNGDMOgSpUqNu1kZ2dTtmzZmxO0iIhckZIIERG5Kcxms822yWS6YpnFYgHAYrHg6OhIQkICjo6ONvtdnniIiMjNpyRCRESum7Ozs82A6JJQt25d8vPzOX36NHfddVeJti0iItdHszOJiMh1i4yMZO3atRw+fJjk5GTr3YTrUaVKFfr27cuDDz7It99+y6FDh1i/fj2vv/46CxcuLIGoRUSkuJREiIjIdRszZgyOjo5ER0cTEBDA0aNHS6Td6dOn8+CDD/LUU09RtWpV7rnnHtauXUt4eHiJtC8iIsWjFatFRERERMQuuhMhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2URIhIiIiIiJ2+X+vOFjnn5oIcAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1wyAianMnTpxo9QqH/oZtPhEFoua09z5XpJvNZgC1wYeFhbl1rNVqRUZGBlJSUqDX670Rns9grvIJlDwB5nq5srIyJCQkuNq/QNLSNp+vITkxVzkFSq6ebu99rkh3ftwZFhbWoiLdZDIhLCxM6hcBwFxlFCh5Asy1KYE43KOlbT5fQ3JirnIKlFw93d4H1uBHIiIiIiI/4HaRvmnTJkyYMAFxcXFQFAXr16+v97wQAmlpaYiLi0NwcDBGjx6N3bt3eypeIiIiIiLpuV2kV1RUYODAgViyZEmjzy9cuBCLFi3CkiVLkJ2djZiYGCQnJ6O8vLzVwRIRERERBQK3x6SPGzcO48aNa/Q5IQQWL16MefPmYdKkSQCAlStXIjo6GqtXr8bMmTNbFy0RERERUQDw6I2jR48eRUFBAVJSUlzbjEYjRo0ahS1btjRapFssFlgsFtfjsrIyALWD761Wq1vXd+7v7nH+iLnKJ1DyBJhrU/sQERE5ebRILygoAABER0fX2x4dHY28vLxGj0lPT8f8+fMbbM/IyIDJZGpRHJmZmS06zh8xV/kESp4Ac3WqrKxsw0iIiMgfeGUKxsunlRFCNDnVzNy5c5Gamup67Jw/MiUlpUVTMGZmZiI5OVnqKX4A5iqjQMkTYK6Xc36CSERE5OTRIj0mJgZAbY96bGysa3tRUVGD3nUno9EIo9HYYLter2/xm3drjvU3zFU+gZInwFwvfY6IiOhSHp0nPTExETExMfU+1q2pqUFWVhZGjBjhyUsREREREUnL7Z70Cxcu4NChQ67HR48exY4dOxAZGYnOnTtjzpw5WLBgAXr27ImePXtiwYIFMJlMmDJlikcDJyIiIiKSldtFek5ODsaMGeN67BxPPm3aNKxYsQJPP/00qqqqMGvWLBQXF2PYsGHIyMiA2Wz2XNSNOFR0AS98sgvF5zQYP96rlyIiIpW9+uUBfL1Li5AeZzC2X5za4RAReZzbRfro0aMhhGjyeUVRkJaWhrS0tNbE5TadRsH3h8/BoFGuGB8REfm/w2cu4Gi5gqJyy9V3JiLyQx4dk66m2IggAECNQ0FxJeccJiKSmUFb+/ZVY3OoHAkRkXdIU6QbdVp0DDUAAE6XVKscDREReZNRpwUAWFikE5GkpCnSASAuIhgAcLq0SuVIiIjIm4z62rcvFulEJCupivROdUNeTrEnnYhIahzuQkSyk6pId/Wkl7AnnYhIZkYde9KJSG5yFenh7EknIgoELNKJSHZyFel1w13yS1mkExHJTF9XpNfYWaQTkZykKtI71Q13OcXhLkREUmNPOhHJTqoi3TncpbjSisoam8rREBGRtziL9Bori3QikpNURXpYsB5B2trVRnnzKBGRvAwc7kJEkpOqSAeAdsba77x5lIhIXheHu9hVjoSIyDukK9IjjbU96aeK2ZNORCQr54qjnCediGQlXZHezlD7/VRJpbqBEBGR1zgXM+KNo0QkK+mKdPakExHJz6hnkU5EcpOuSHeOST/NMelERNJyze7CIp2IJCVdke7qSefsLkRE0uJwFyKSnXRFurMnvaCsGjZOzUVEJCUDe9KJSHLSFelmPaDXKrA7BArKOOSFiEhGRs6TTkSSk65I1yhAbN3KoxyXTkQkJ4OOw12ISG7SFekAEFdXpHMaRiIiORlZpBOR5OQs0iOCAXAaRiIiWTkXM7I7BO8/IiIpSVmkd4pw9qSzSCcikpFBp7h+5rh0IpKRlEW6qyedY9KJiKTknIIRACxWFulEJB85i3TnmPRijkknIpKRTquBRqldF4M96UQkIymL9E6unvQqCCFUjoaIiLzBOeKFPelEJCMpi/SYup70aqsDxZVWlaMhIvJ/6enpUBQFc+bMcW0TQiAtLQ1xcXEIDg7G6NGjsXv37jaLSV/3Dmax2dvsmkREbcUrRXp5eTnmzJmDLl26IDg4GCNGjEB2drY3LtUoo06DjubapUc5wwsRUetkZ2fj7bffxoABA+ptX7hwIRYtWoQlS5YgOzsbMTExSE5ORnl5eZvE5epJ5zSMRCQhrxTpv/3tb5GZmYn33nsPO3fuREpKCsaOHYtTp05543KNujjkhePSiYha6sKFC5g6dSreeecdtGvXzrVdCIHFixdj3rx5mDRpEvr374+VK1eisrISq1evbpPYdK6edBbpRCQfnadPWFVVhbVr1+KTTz7BzTffDABIS0vD+vXrsXTpUrz00kuevmSjOrULxo4TJTjJnnQiohabPXs2br/9dowdO7Ze+3306FEUFBQgJSXFtc1oNGLUqFHYsmULZs6c2ej5LBYLLBaL63FZWRkAwGq1wmpt/vBEq9XqGu5SWV3j1rH+xpmbzDk6MVc5BUquzcnTnd+Bx4t0m80Gu92OoKCgetuDg4Px3XffNdjfUw228xjn99iw2uEuJ89XSPmiCJQXPBA4uQZKngBzbWofX7NmzRrk5uYiJyenwXMFBQUAgOjo6Hrbo6OjkZeX1+Q509PTMX/+/AbbMzIyYDKZ3IpPp6ld0Oj7H7bh/D75JwnIzMxUO4Q2w1zlFCi5XinPysrmj/DweJFuNpsxfPhw/OlPf0KfPn0QHR2NDz74ANu2bUPPnj0b7O/JBtspMzMTxfkKAC1+2n8Mn+NIi87jDwLlBQ8ETq6BkifAXJ3cabTbyokTJ/DEE08gIyOjQafLpRRFqfdYCNFg26Xmzp2L1NRU1+OysjIkJCQgJSUFYWFhzY7ParXiLzu/AQAMGDQYyX2jmn2sv7FarcjMzERycjL0er3a4XgVc5VToOTanDydndHN4fEiHQDee+89zJgxA506dYJWq8V1112HKVOm4Keffmqwr6cabKD+L8d4uBhrj+2APSgc48cPb3VOviZQXvBA4OQaKHkCzPVy7jTabSU3NxdFRUUYPHiwa5vdbsemTZuwZMkS7N+/H0Btj3psbKxrn6Kioga965cyGo0wGo0Ntuv1erdfC3qNAKDABkX61xHQst+Rv2KucgqUXK+Upzv5e6VI7969O7KyslBRUYGysjLExsbi/vvvR2JiYoN9PdlgX3pslw5mAMDpkmqpXxCB8oIHAifXQMkTYK6XPudrbr31VuzcubPetunTp6N379545pln0K1bN8TExCAzMxODBg0CANTU1CArKwuvvvpqm8TovHG0hjeOEpGEvFKkO4WEhCAkJATFxcX48ssvsXDhQm9erp5O7WpndymutKKyxgaTwaupEhFJxWw2o3///vW2hYSEoH379q7tc+bMwYIFC9CzZ0/07NkTCxYsgMlkwpQpU9okxotTMHKedCKSj1cq1y+//BJCCPTq1QuHDh3Cf//3f6NXr16YPn26Ny7XqLAgPcxGHcotNpwuqUKPKHObXZuIKBA8/fTTqKqqwqxZs1BcXIxhw4YhIyMDZnPbtLeuxYy44igRScgrRXppaSnmzp2LkydPIjIyEnfffTdefvnlNv9It1O7YOwrKMfJYhbpRESttXHjxnqPFUVBWloa0tLSVInHNdzFziKdiOTjlSL9vvvuw3333eeNU7ulU0RtkX6qhHOlExHJRseedCKSmFdWHPUVcXWrjp5mkU5EJB09x6QTkcSkLtKdN4+e4qqjRETS4ewuRCQzuYv0up50DnchIpKPa7gLi3QikpDcRTp70omIpFW7mBGHuxCRnOQu0ut60gvKqmHj3f9ERFJxzpPO4S5EJCOpi/SOoUYYtBo4RG2hTkRE8uBwFyKSmdRFukajIDYiCACHvBARyUbPIp2IJCZ1kQ4AceG8eZSISEYc7kJEMpO+SHfePMq50omI5HJxuAtvHCUi+chfpHMaRiIiKXG4CxHJTP4iva4n/STHpBMRSYXDXYhIZtIX6V0iTQCAg4UXIIRQORoiIvIUnWuedBbpRCQf6Yv0a+LDodMoKCir5pAXIiKJuIa7WDkmnYjkI32RbjLo0C8uDACQc6xY5WiIiMhTXMNduFgdEUlI+iIdAIZ0jQQA5OSdVzkSIiLyFNfsLlYW6UQkn4Ao0od2bQeAPelERDLh7C5EJLOAKNIHd6ntSd9fWI7SSqvK0RARkSc4e9Jr7A5ODEBE0gmIIr2j2YjEDiEQAvjpOHvTiYhkoFcu/szedCKSTUAU6QAwuEvtkJfsYxyXTkQkA90l72As0olINgFTpLvGpeexJ52ISAbaS3rSuaAREckmYIp05wwvP58ogcXGOXWJiPydogDGuu50tutEJJuAKdK7dQhBZIgBFpsDu06VqR0OERF5wMUinT3pRCSXgCnSFUVxjUvP4bh0IiIpGOqKdA53ISLZBEyRDnBcOhGRbNiTTkSyCqgi3bXy6LHznFOXiEgCBi170olITh4v0m02G/7nf/4HiYmJCA4ORrdu3fDiiy/C4VC/Ae0fFw6jToPiSisOn6lQOxwiImol3jhKRLLSefqEr776Kt58802sXLkS/fr1Q05ODqZPn47w8HA88cQTnr6cWww6Da5NiMC2o+eRc+w8ekSFqhoPERG1jkFfV6Rb1e8IIiLyJI/3pP/www+YOHEibr/9dnTt2hX33HMPUlJSkJOT4+lLtcgQjksnIpKGa7iLnUU6EcnF4z3pI0eOxJtvvokDBw4gKSkJP//8M7777jssXry40f0tFgssFovrcVlZ7fSIVqsVVqvVrWs797/ScYPiwwAA2UfPu31+X9KcXGURKLkGSp4Ac21qH3KfUacFwOEuRCQfjxfpzzzzDEpLS9G7d29otVrY7Xa8/PLLmDx5cqP7p6enY/78+Q22Z2RkwGQytSiGzMzMJp+rtAEKtMg7X4k16z9HmKFFl/AZV8pVNoGSa6DkCTBXp8rKyjaMRC6uMekc7kJEkvF4kf7hhx9i1apVWL16Nfr164cdO3Zgzpw5iIuLw7Rp0xrsP3fuXKSmproel5WVISEhASkpKQgLC3Pr2larFZmZmUhOToZer29yv5XHt2Bf4QVE9ByM/9cv2q1r+Irm5iqDQMk1UPIEmOvlnJ8gkvtc86RzuAsRScbjRfp///d/49lnn8Wvf/1rAMA111yDvLw8pKenN1qkG41GGI3GBtv1en2L37yvduyQxEjsK7yA7SfKMOHa+BZdw1e05vfkbwIl10DJE2Culz5HLcOedCKSlcdvHK2srIRGU/+0Wq3WJ6ZgdBpaN196bh5XHiUi8mecgpGIZOXxnvQJEybg5ZdfRufOndGvXz9s374dixYtwowZMzx9qRZzLmq063QZKmtsMBk8/msgIqI24BruwsWMiEgyHq9O//a3v+GPf/wjZs2ahaKiIsTFxWHmzJl4/vnnPX2pFusUEYy48CCcLq3GjuMlGNGjg9ohERFRC1zsSWeRTkRy8XiRbjabsXjx4ianXPQVQ7pG4tOfTyP7WDGLdCIiP2VgkU5EkvL4mHR/MbhL7aJGO05wUSMiIn/lXMyIRToRySZgi/ReMWYAwOEzFSpHQkRELWXU88ZRIpJTwBbp3TqGAABOFlei2srGnYjIH11ccZQ96UQkl4At0juGGmEO0sEhgLxzXO2PiMgfOYe7cHYXIpJNwBbpiqKge8dQAMDhMxdUjoaIiFqCs7sQkawCtkgHcLFIL2KRTkTkjy6uOMphi0Qkl8Au0qNqx6WzJ52IyD+5FjOysyediOQS2EW6a7gLZ3ghIvJHF3vSWaQTkVwCvEiv7Uk/cuYChBAqR0NERO66uJgRh7sQkVwCukjvHBkCrUZBRY0dhWUWtcMhIiI3cbgLEckqoIt0g06DLpEmAByXTkTkjzjchYhkFdBFOgB04zSMRER+i4sZEZGsAr5Id83wwmkYiYj8jkGnAOBiRkQkHxbpnOGFiMhvXexJt3MCACKSCot0DnchIvJbzjHpDgHYHCzSiUgeLNLrpmHML61GhcWmcjRERL5j6dKlGDBgAMLCwhAWFobhw4fjiy++cD0vhEBaWhri4uIQHByM0aNHY/fu3W0ao0F78W2MQ16ISCYBX6RHmAxoH2IAABw9yyEvRERO8fHxeOWVV5CTk4OcnBzccsstmDhxoqsQX7hwIRYtWoQlS5YgOzsbMTExSE5ORnl5eZvF6JyCEeDNo0Qkl4Av0gEOeSEiasyECRMwfvx4JCUlISkpCS+//DJCQ0OxdetWCCGwePFizJs3D5MmTUL//v2xcuVKVFZWYvXq1W0Wo1ajQK+tvXmUCxoRkUx0agfgC7pHheDHY+c5wwsRURPsdjs++ugjVFRUYPjw4Th69CgKCgqQkpLi2sdoNGLUqFHYsmULZs6c2eh5LBYLLJaLi8eVlZUBAKxWK6xWa7Pjce5rtVph0GpgtdtRUV0Dq0m+t7VLc5Udc5VToOTanDzd+R3I15q1AGd4ISJq3M6dOzF8+HBUV1cjNDQU69atQ9++fbFlyxYAQHR0dL39o6OjkZeX1+T50tPTMX/+/AbbMzIyYDKZ3I4vMzMTcGgBKPjqm42Idf8UfiMzM1PtENoMc5VToOR6pTwrKyubfR4W6eBwFyKipvTq1Qs7duxASUkJ1q5di2nTpiErK8v1vKIo9fYXQjTYdqm5c+ciNTXV9bisrAwJCQlISUlBWFhYs+OyWq3IzMxEcnIy0ndvQUWZBcOGj0T/Ts0/h7+4NFe9Xq92OF7FXOUUKLk2J0/np4fNwSIdQLe6GV6Onq2A3SGg1TT9BkNEFEgMBgN69OgBABgyZAiys7Px+uuv45lnngEAFBQUIDY21rV/UVFRg971SxmNRhiNxgbb9Xp9i9689Xo9jPraudIdiiJ1AdDS35E/Yq5yCpRcr5SnO/nzxlEA8e1MMGg1sNgcOF1SpXY4REQ+SwgBi8WCxMRExMTE1PtYt6amBllZWRgxYkSbxuScK91i5ewuRCQP9qSjdnaAxA4h2F9YjkNnLiAhUuJBjUREzfTcc89h3LhxSEhIQHl5OdasWYONGzdiw4YNUBQFc+bMwYIFC9CzZ0/07NkTCxYsgMlkwpQpU9o0Tuc0jJyCkYhkwiK9Tveo2iL9cNEFjOkVpXY4RESqKywsxAMPPID8/HyEh4djwIAB2LBhA5KTkwEATz/9NKqqqjBr1iwUFxdj2LBhyMjIgNlsbtM4jbra4S4s0olIJizS63CGFyKi+pYtW3bF5xVFQVpaGtLS0tomoCa4hrtwnnQikojHx6R37doViqI0+Jo9e7anL+VRnOGFiMg/cbgLEcnI4z3p2dnZsNsv9mbs2rULycnJuPfeez19KY9yzvByhEU6EZFfcfak17BIJyKJeLxI79ixY73Hr7zyCrp3745Ro0Z5+lIe1a2uJ/3shRqUVloRbpJ/iiAiIhlwTDoRycirY9JramqwatUqpKamNrm4haeWiHYec+l3dxg1QHSYEYVlFuwvKMGghAi3z9GWAmWJXSBwcg2UPAHm2tQ+1DIGjkknIgl5tUhfv349SkpK8NBDDzW5j6eXiAZavuxsuKJBITRY//UPyI8SLTpHWwuUJXaBwMk1UPIEmKuTO8tEU0Mc7kJEMvJqkb5s2TKMGzcOcXFxTe7jqSWigdYvO5vt2IsD204gNK47xqckuX18WwqUJXaBwMk1UPIEmOvl3FkmmhricBcikpHXivS8vDx89dVX+Pjjj6+4n6eXiG7NsT2ja/9TcPRcld8UDoGyxC4QOLkGSp4Ac730OWo5A1ccJSIJeXwKRqfly5cjKioKt99+u7cu4XGchpGIyP+4hrvYOSadiOThlSLd4XBg+fLlmDZtGnQ6/1kvyTkN4/FzlbDa2SNDROQPjHr2pBORfLxSpH/11Vc4fvw4ZsyY4Y3Te01MWBBMBi1sDoHj53kjFxGRPzBouZgREcnHK0V6SkoKhBBISvLtmy8vp9Eort70w0Uc8kJE5A+M+tobRzm7CxHJxGtj0v3VxXHpFSpHQkREzWHkPOlEJCEW6ZfpUVekHywsVzkSIiJqjos3jrInnYjkwSL9Mr1izACAfQUs0omI/IGRUzASkYRYpF+mT2ztXOmHii5whhciIj/AxYyISEYs0i/TKSIYoUYdauwOHD3LcelERL7OuZgRbxwlIpmwSL+MRqO4hrzszedS3UREvo43jhKRjFikN6I3x6UTEfkNDnchIhmxSG9E77px6fvYk05E5PM43IWIZMQivRF92JNOROQ3Lg53YZFORPJgkd6IpLoiPb+0GiWVNSpHQ0REV2LUc0w6EcmHRXojwoL0iG8XDIC96UREvs6grX0rs9oFHA6hcjRERJ7BIr0JvWM4Lp2IyB8Y9VrXz1x1lIhkwSK9CX1iOS6diMgfOMekA1x1lIjkwSK9Cc6e9L0s0omIfJpOo0BRan+22DkunYjkwCK9Cb3retIPFJTDzjGOREQ+S1GUizO8sCediCTBIr0JXduHwKjToMpqx/HzlWqHQ0REV8AFjYhINizSm6DVKOjlnC+dN48SEfk0LmhERLJhkX4FfTgunYjIL1xc0Ihj0olIDizSr8A5Lp096UREvo2rjhKRbFikX8HFGV5YpBMR+TJD3Zh0DnchIlmwSL+C3nVj0k+cr0J5tVXlaIiIqCnsSSci2bBIv4J2IQbEhAUBAA4Uclw6EZGvMnBMOhFJhkX6VTjHpe/NZ5FOROSrjJzdhYgkwyL9Kpzj0vdxXDoRkc/iPOlEJBsW6VfRxzXDC3vSiYh81cUVRznchYjkwCL9Ki72pJdDCKFyNERE1BjXcBc7e9KJSA5eKdJPnTqF3/zmN2jfvj1MJhOuvfZa5ObmeuNSXtetYwj0WgUXLDacLK5SOxwiImqEUe/sSWeRTkRy8HiRXlxcjBtvvBF6vR5ffPEF9uzZgz//+c+IiIjw9KXahF6rQY+ouiEvXHmUiMgnGbScgpGI5KLz9AlfffVVJCQkYPny5a5tXbt29fRl2lSfGDP25pdhX34ZkvtGqx0OERFdxqivW8yIw12ISBIeL9I//fRT3Hbbbbj33nuRlZWFTp06YdasWfjd737X6P4WiwUWi8X1uKysdhYVq9UKq9W9BYSc+7t73NX0jAoBAOw5Xerxc7eUt3L1RYGSa6DkCTDXpvahluONo0QkG48X6UeOHMHSpUuRmpqK5557Dj/++CMef/xxGI1GPPjggw32T09Px/z58xtsz8jIgMlkalEMmZmZLTquKWUlCgAtcg8X4PPPT3n03K3l6Vx9WaDkGih5AszVqbKysg0jkROHuxCRbDxepDscDgwZMgQLFiwAAAwaNAi7d+/G0qVLGy3S586di9TUVNfjsrIyJCQkICUlBWFhYW5d22q1IjMzE8nJydDr9a1L5BJDyy1YujcLZy0Kxoy9DcEGrcfO3VLeytUXBUqugZInwFwv5/wEkVrOeeMoFzMiIll4vEiPjY1F3759623r06cP1q5d2+j+RqMRRqOxwXa9Xt/iN+/WHNuY2HY6tA8x4FxFDY4VV2NAfITHzt1ans7VlwVKroGSJ8BcL32OWoeLGRGRbDw+u8uNN96I/fv319t24MABdOnSxdOXajOKoqB33aJGe/PZ40VE5GsMzjHpNo5JJyI5eLxIf/LJJ7F161YsWLAAhw4dwurVq/H2229j9uzZnr5Um+oXFw4A+PlkqcqREBHR5Vw3jrInnYgk4fEifejQoVi3bh0++OAD9O/fH3/605+wePFiTJ061dOXalPXdW4HAPgpr1jlSIiI6HIc7kJEsvH4mHQAuOOOO3DHHXd449Squa5LBABgf2E5yqutMAdxDCkRka8wsCediCTj8Z50WUWZg5AQGQwhgB0nStQOh4iILuEc7sLZXYhIFizS3XBxyEuJuoEQEVE9Rt44SkSSYZHuhsFdaov03OMcl05E5Etcw12s7EknIjmwSHeDsyd9+/FiOBxC5WiIiLwnPT0dQ4cOhdlsRlRUFO68884G0+sKIZCWloa4uDgEBwdj9OjR2L17tyrxOm8crbGzSCciObBId0PvGDOC9VqUV9tw6MwFtcMhIvKarKwszJ49G1u3bkVmZiZsNhtSUlJQUVHh2mfhwoVYtGgRlixZguzsbMTExCA5ORnl5eVtHq9zxVGLlcNdiEgOLNLdoNNqMDChdr50TsVIRDLbsGEDHnroIfTr1w8DBw7E8uXLcfz4ceTm5gKo7UVfvHgx5s2bh0mTJqF///5YuXIlKisrsXr16jaP16Dl7C5EJBevTMEos8Fd2mHrkfPIzSvGr6/vrHY4RERtorS0diG3yMhIAMDRo0dRUFCAlJQU1z5GoxGjRo3Cli1bMHPmzEbPY7FYYLFYXI/LympXcbZarbBarc2Ox7mv87sWtcV5jd2BmpoaKIrS7HP5ustzlRlzlVOg5NqcPN35HbBId5NrhhfePEpEAUIIgdTUVIwcORL9+/cHABQUFAAAoqOj6+0bHR2NvLy8Js+Vnp6O+fPnN9iekZEBk8nkdmyZmZkAgEobAOggBPDZf76ATsLPiZ25BgLmKqdAyfVKeVZWVjb7PCzS3TSorkg/fKYCJZU1iDAZVI6IiMi7Hn30Ufzyyy/47rvvGjx3eY+1EOKKvdhz585Famqq63FZWRkSEhKQkpKCsLCwZsdktVqRmZmJ5ORk6PV6VFvtmJv9NQBgzNgUmIPkeXu7PFeZMVc5BUquzcnT+elhc8jTirWRyBADunUIwZGzFdh+vARjekepHRIRkdc89thj+PTTT7Fp0ybEx8e7tsfExACo7VGPjY11bS8qKmrQu34po9EIo9HYYLter2/Rm7fzOK324tuZUDRSFgIt/R35I+Yqp0DJ9Up5upO/hB8Iet91zvnSefMoEUlKCIFHH30UH3/8Mb755hskJibWez4xMRExMTH1PtatqalBVlYWRowY0dbhQqNRePMoEUmFRXoLcFw6Eclu9uzZWLVqFVavXg2z2YyCggIUFBSgqqoKQO0wlzlz5mDBggVYt24ddu3ahYceeggmkwlTpkxRJWbXgkYs0olIAhzu0gLOlUd3nCiBze6ATsv/6xCRXJYuXQoAGD16dL3ty5cvx0MPPQQAePrpp1FVVYVZs2ahuLgYw4YNQ0ZGBsxmcxtHW8uo0+CCBahhkU5EEmCR3gI9o0JhNupQbrFhf2E5+sWFqx0SEZFHCXH1VZUVRUFaWhrS0tK8H1AzGF096VzQiIj8H7uAW0CjUXBt5wgAXNSIiMhXOIe7sCediGTAIr2FLo5LL1E3ECIiAgAYdVoAHJNORHJgkd5CgznDCxGRTzHqOdyFiOTBIr2Fru0cAUUBjp+vxJlyy9UPICIir3JOwcjhLkQkAxbpLRQWpEdSVO0MBpyKkYhIfRd70lmkE5H/Y5HeCtd1iQDAIp2IyBe4FjOyskgnIv/HIr0VXDePclw6EZHqXDeO2lmkE5H/Y5HeCs6bR385WcoxkEREKnMNd7HyxlEi8n8s0lshsUMI2pn0sNgc2H26VO1wiIgCmmu4CztNiEgCLNJbQVEUDO4SCQD44cg5laMhIgpszp50frJJRDJgkd5Ko5I6AACy9p9RORIiosDGxYyISCYs0ltpVFIUgNpFjcqrrSpHQ0QUuAw6LmZERPLweJGelpYGRVHqfcXExHj6Mj6jc3sTEjuEwOYQ+P4Qh7wQEanFqONwFyKSh1d60vv164f8/HzX186dO71xGZ8xKqkjACDrAIe8EBGphcNdiEgmOq+cVKeTuvf8cqN6dcSKLcew6cAZCCGgKIraIRERBZyLw11YpBOR//NKkX7w4EHExcXBaDRi2LBhWLBgAbp169bovhaLBRaLxfW4rKwMAGC1WmG1ujfG27m/u8e11uD4MBh0GpwqqcK+0yXoERXq9WuqlasaAiXXQMkTYK5N7UOtc3G4C8ekE5H/83iRPmzYMPzzn/9EUlISCgsL8dJLL2HEiBHYvXs32rdv32D/9PR0zJ8/v8H2jIwMmEymFsWQmZnZouNao1uIBvtKNXjr080YEyfa7Lpq5KqWQMk1UPIEmKtTZWVlG0YiLyN70olIIh4v0seNG+f6+ZprrsHw4cPRvXt3rFy5EqmpqQ32nzt3br3tZWVlSEhIQEpKCsLCwty6ttVqRWZmJpKTk6HX61ueRAsURuRhwRf7cUYXhfHjB3v9emrm2tYCJddAyRNgrpdzfoJIreMa7mJlkU5E/s8rw10uFRISgmuuuQYHDx5s9Hmj0Qij0dhgu16vb/Gbd2uObalb+sRgwRf7kX2sGFahwGTw+q8WgDq5qiVQcg2UPAHmeulz1HrOG0dr7CzSicj/eX2edIvFgr179yI2Ntbbl1JV944h6BQRjBq7A9uOnFc7HCKigONccZTzpBORDDxepD/11FPIysrC0aNHsW3bNtxzzz0oKyvDtGnTPH0pn6IoCkb14lSMRERqMWo53IWI5OHxIv3kyZOYPHkyevXqhUmTJsFgMGDr1q3o0qWLpy/lc0bXzZe+cX+RypEQEQUeZ086h7sQkQw8PnB6zZo1nj6l3xjRowN0GgXHzlXi2NkKdO0QonZIREQBw7WYEXvSiUgCXh+THkhCjToM6doOALDpIIe8EBG1pYuLGXFMOhH5PxbpHjYqKQoAkLWfRToRUVu6uJgRe9KJyP+xSPew0XU3j245fI69OUREbcg13IVFOhFJgEW6h/WOMSPKbESV1Y7so8Vqh0NEFDCcw11sDgG7o+1WfiYi8gYW6R6mKApGJTmnYuQsL0REbcU53AXgkBci8n8s0r2A86UTEbW9S4t0DjckIn/HIt0LburRERoFOFB4AadKqtQOh4goIOi0GmiU2p85Lp2I/B2LdC8IN+kxpGskAODzX/JVjoaIKHA4bx7lcBci8ncs0r3kVwPjAACf/HxK5UiIiAKHc9VRDnchIn/HIt1Lxl8TC51Gwa5TZTh85oLa4RARBQSDtvZtrZqrjhKRn2OR7iWRIQbcXDfLy6c7TqscDRFRYHD2pNfYWaQTkX9jke5FE6+tHfLy6c+nIQTn7CUi8jbnmPRqK4e7EJF/Y5HuRWP7RCNIr8HRsxXYeapU7XCIiKQXHqwHAJRUWlWOhIiodVike1GIUYfkvjEAgE845IWIyOuiw4wAgILSapUjISJqHRbpXjaxbpaXz34+zWWqiYi8LDosCABQWM4inYj8G4t0L7s5qSPCg/UoKrdg25FzaodDRCS1GGeRzp50IvJzLNK9zKDTYPw1sQA45IWIyNtiwmuL9IIyFulE5N9YpLcB5ywvn+/K5wIbREReFGWu60kvs6gcCRFR67BIbwPXd41ETFgQyqtt2Lj/jNrhEBFJy9mTXlhWzalvicivsUhvAxqNgl8550znkBciIq9xjkmvrLGj3GJTORoiopZjkd5GflU3y8tXewtRXs35e4mIvCHYoEVYkA4Abx4lIv/GIr2N9IsLQ/eOIbDYHMjYXah2OERE0nJOw8ibR4nIn7FIbyOKomDitZ0AAJ/8zCEvRETecnFcOm8eJSL/xSK9DTmHvHx/6CxXwyMi8hLXgkbsSSciP8YivQ117RCC67tGwu4QWLU1T+1wiIik5Lx5lJ0hROTPWKS3sek3dgUArP7xOKqtnDOdiMjTosOMADgmnYj8m9eL9PT0dCiKgjlz5nj7Un4huW80OkUE43xFDT7l2HQiIo9zDncpYpFORH7Mq0V6dnY23n77bQwYMMCbl/ErOq0GDwzvAgBY/v0xLrZBRORhzhtH2ZNORP7Ma0X6hQsXMHXqVLzzzjto166dty7jl349NAFBeg325pdh29HzaodDRCQV55j0M+UW2OwOlaMhImoZnbdOPHv2bNx+++0YO3YsXnrppSb3s1gssFguTpNVVlYGALBarbBa3Vv0x7m/u8e1tRC9gjuvjcOa7JNYtvkIBieEuX0Of8nVEwIl10DJE2CuTe3jazZt2oTXXnsNubm5yM/Px7p163DnnXe6nhdCYP78+Xj77bdRXFyMYcOG4e9//zv69eunXtAA2ocaodUosDsEzl6ocfWsExH5E68U6WvWrEFubi5ycnKuum96ejrmz5/fYHtGRgZMJlOLrp+Zmdmi49pSYg0A6PDV3kK89/HnaN/C9xB/yNVTAiXXQMkTYK5OlZWVbRhJ81VUVGDgwIGYPn067r777gbPL1y4EIsWLcKKFSuQlJSEl156CcnJydi/fz/MZrMKEdfSahR0DDWioKwahWXVLNKJyC95vEg/ceIEnnjiCWRkZCAo6OoN49y5c5Gamup6XFZWhoSEBKSkpCAszL0eZqvViszMTCQnJ0Ov17sde1vbdCEX3x8+h1Om7njg//Vy61h/y7U1AiXXQMkTYK6Xc36C6GvGjRuHcePGNfqcEAKLFy/GvHnzMGnSJADAypUrER0djdWrV2PmzJltGWoD0eFBKCirRkFZNQaqGgkRUct4vEjPzc1FUVERBg8e7Npmt9uxadMmLFmyBBaLBVqt1vWc0WiE0WhscB69Xt/iN+/WHNuWZoxMxPeHz+Gj3FP4r9t6w2Rw/8/hL7l6QqDkGih5Asz10uf8zdGjR1FQUICUlBTXNqPRiFGjRmHLli1NFumeGuJ4tWFEUaEGAMDp4gqfHU7UXBweJifmKh9PD2/0eJF+6623YufOnfW2TZ8+Hb1798YzzzxTr0APdGN6RaFrexOOnavE2p9O4YEbuqgdEhFRsxQUFAAAoqOj622Pjo5GXl7Ti7V5eohjU8OIqs9rAGjw/fY9iDy3y+3z+iIOD5MTc5WPp4Y3erxIN5vN6N+/f71tISEhaN++fYPtgU6jUTBtRFfM/2wPVnx/FFOv7wyNRlE7LCKiZlOU+m2WEKLBtkt5aojj1YYRHc86gs2Fh2COisf48f793sPhYXJirvLx9PBGr83uQs1zz+B4/DnjAA6fqcDmQ2cxKqmj2iEREV1VTEwMgNoe9djYWNf2oqKiBr3rl/L0EMemjotrFwIAOFNeI01RwOFhcmKu8vHU8EavrzgKABs3bsTixYvb4lJ+xxykx71D4gEAy78/qnI0RETNk5iYiJiYmHof69bU1CArKwsjRoxQMbJaXNCIiPxdmxTpdGUPjegKRQE27j+Dn0+UqB0OERGA2kXpduzYgR07dgCovVl0x44dOH78OBRFwZw5c7BgwQKsW7cOu3btwkMPPQSTyYQpU6aoGziA6LDa3vrCUhbpROSfWKT7gC7tQ3DXoE4AgNe+3K9yNEREtXJycjBo0CAMGjQIAJCamopBgwbh+eefBwA8/fTTmDNnDmbNmoUhQ4bg1KlTyMjIUHWOdKfoulVHyy02VFhsKkdDROQ+Fuk+4smxSdBrFXx36Cy2HDqrdjhERBg9ejSEEA2+VqxYAaD2ptG0tDTk5+ejuroaWVlZPjNBgDlIjxBD7WxihRzyQkR+iEW6j0iINGHK9Z0BAK9+uR9CCJUjIiLyb9Ecl05EfoxFug959JaeMBm0+PlECb7cXah2OEREfi3aXFukF5VZrrInEZHvYZHuQzqajZhxYyIA4M8Z+2F3sDediKilOMMLEfkzFuk+5nc3d0N4sB4Hiy5g3fZTaodDROS3nDePFnCGFyLyQyzSfUx4sB6zRncHAPwl8wAsNrvKERER+SfXNIzsSSciP8Qi3QdNG9EV0WFGnCqpwuptx9UOh4jIL8XU9aSzSCcif8Qi3QcF6bV4/NaeAIAl3xzCBc7xS0TkNufsLoW8cZSI/BCLdB9135AEdG1vwrmKGvzju6Nqh0NE5Hcu7Ul38EZ8IvIzLNJ9lF6rQWpKLwDA0o2HceJ8pcoRERH5l45mIxQFsDkEzlXUqB0OEZFbWKT7sDuuicX1iZGostoxb/0uLnBEROQGvVaD9iG8eZSI/BOLdB+m0Sh4ZdI1MOg02HTgDNbv4JSMRETuiAlnkU5E/olFuo/r1jEUT9TdRPriZ3tw7gJvgCIiai7nuHQuaERE/oZFuh/4/c3d0DvGjOJKK/70f3vUDoeIyG9EOW8e5YJGRORnWKT7Ab1Wg1fvHgCNAqzfcRrf7i9SOyQiIr9wcYYXfgpJRP6FRbqfGJgQgRk3JgIA5n28k3OnExE1A4e7EJG/YpHuR1JTkpAQGYzTpdX4y1eH1A6HiMjnXVzQiEU6EfkXFul+xGTQYcFd1wAA3tt2HMfKVQ6IiMjHRYfVzu7CnnQi8jcs0v3MTT074u7r4iEE8N4hLcqrrWqHRETks5zDXUoqrai22lWOhoio+Vik+6E/3tEHceFBOFut4JmPd3ORIyKiJoQH62HU1b7VFfHmUSLyIyzS/VCEyYC//XogtIpA5t4ivJl1RO2QiIh8kqIoiAnnzaNE5H9YpPupAfHhuCfRAQB47ct92HLorMoRERH5pmgzi3Qi8j8s0v3Y8CiBuwbFwSGAxz7YjgIu1kFE1IBzhpciFulE5EdYpPsxRQHm39EHfWLDcK6iBrPez0WNzaF2WEREPiXGOcMLOzKIyI94vEhfunQpBgwYgLCwMISFhWH48OH44osvPH0ZqhNs0OLN31wHc5AOPx0vwYLP96odEhGRT4nmgkZE5Ic8XqTHx8fjlVdeQU5ODnJycnDLLbdg4sSJ2L17t6cvRXW6tA/BX+67FgCwYssxfPzTSXUDIiLyIc4inbO7EJE/8XiRPmHCBIwfPx5JSUlISkrCyy+/jNDQUGzdutXTl6JLjO0bjdljugMAnv73L/h6b6HKERER+QbO7kJE/kjnzZPb7XZ89NFHqKiowPDhwxvdx2KxwGK52LtRVlYGALBarbBa3Vuox7m/u8f5o8ZyfXx0N5w8X4lPfs7HH97/Cf948DoMS4xUK0SPCZS/a6DkCTDXpvYh74i5ZLiLEAKKoqgcERHR1XmlSN+5cyeGDx+O6upqhIaGYt26dejbt2+j+6anp2P+/PkNtmdkZMBkMrXo+pmZmS06zh9dnuuoYOBIOw12FgMPr8jG7H52dAlVKTgPC5S/a6DkCTBXp8rKyjaMJPBE1d04WmNzoKTSinYhBpUjIiK6Oq8U6b169cKOHTtQUlKCtWvXYtq0acjKymq0UJ87dy5SU1Ndj8vKypCQkICUlBSEhYW5dV2r1YrMzEwkJydDr9e3Og9fdqVcU1Ls+P2q7dhy5Dz+cSgY7z88BEnRZpUibb1A+bsGSp4Ac72c8xNE8g6jTou48CCcLq3Gj8fO47Z+MWqHRER0VV4p0g0GA3r06AEAGDJkCLKzs/H666/jrbfearCv0WiE0WhssF2v17f4zbs1x/qbxnLV6/V4Z9pQTH13G3acKMH0lT/ho0eGo0v7EJWi9IxA+bsGSp4Ac730OfKuCQPj8NamI/h37kkW6UTkF9pknnQhRL1x5+R9IUYdVkwfit4xZhSVWzD13W04XVKldlhERKq4e3A8AODbfUU4e4HvR0Tk+zxepD/33HPYvHkzjh07hp07d2LevHnYuHEjpk6d6ulL0VVEmAz458PXo2t7E04WV2HSG1uwr4AfqxNR4EmKNmNgfDhsDoH120+pHQ4R0VV5vEgvLCzEAw88gF69euHWW2/Ftm3bsGHDBiQnJ3v6UtQMUeYgvP+7G9AjKhQFZdW4d+kP+P7QWbXDIiJqc/fU9ab/O/ckhBAqR0NEdGUeL9KXLVuGY8eOwWKxoKioCF999RULdJV1igjG2kdG4PrESJRbbJj2jx+54BERBZwJA+Ng0Gqwr6Acu0/zU0Ui8m1tMiad1Bdu0uO9h6/HhIFxsDkEUv/1M5Z8c5C9SUQUMCJMBiT3iwZQ25tOROTLWKQHEKNOi9fvvxYzR3UDAPxvxgHM/XgnrHaHypEREbUN55CXT3acQo2NbR8R+S4W6QFGo1Ewd1wfvDixHzQKsCb7BO5ZugXHzlaoHRoRkdfd1KMDosxGFFda8c2+IrXDISJqEov0APXg8K5458EhCA/W4+eTpbj9r5t5MxURSU+n1eCu6zoB4JAXIvJtLNID2K19ovHFEzdhWGIkKmrseOqjn/H4mh0orbKqHRoRkdfcc13dnOn7i3CmnHOmE5FvYpEe4OIigrH6dzfgqZQkaDUKPvv5NMa/vhm5eefVDo2IyCt6RpsxMCECdofAJzs4ZzoR+SYW6QStRsGjt/TER48MR0JkME6VVOHeN3/AvHU7cb6iRu3wiIg8jnOmE5GvY5FOLtd1bofPH78Jk67rBIcA3t92HGP+dyNWbjkGG2eAISKJ/GoA50wnIt/GIp3qMQfpsei+a7Hm9zegT2wYSquseOHT3bj9r99hC1cqJSJJhJv0nDOdiHwai3Rq1A3d2uP/HhuJl+7sjwiTHvsLyzHl3W34/T9zsOtUqdrhERG1mnPIy8c/ncTBwnKVoyEiqo9FOjVJq1Hwmxu6YONTozFteBdoFCBjTyHu+Nt3eGDZNmw5fJZjOYnIb93UowP6dwpDWbUNv357K/bmc9gLEfkOFul0VREmA+ZP7I8Nc27GndfGQatRsPngWUx5ZxvufGMLNuwqgMPBYp2I/ItOq8F7M4ahf6cwnKuoweR3tvKTQiLyGSzSqdmSos1Y/OtB2PjUaDw4vAuMOg1+PlGCR1blYsyfN+KvXx/EifOVaodJRNRs7UIMeP+3N+DahAiUVFox+Z2t2H68WO2wiIhYpJP7EiJNeHFif3z/7C14dEwPhAXpkHeuEosyD+Cmhd/i/rd+wL9yTuCCxaZ2qEREVxUerMd7D1+PoV3bobzaht+8uw0/HuVaEUSkLhbp1GIdQo146rZe2PrcrVh030Dc2KM9FAXYdvQ8nv73LxjyUiZmv/8TPso5gaLyarXDJSJqkjlIj5UzrseI7u1RUWPHtH/8iMw9hbzvhohUo1M7APJ/JoMOk66Lx6Tr4nG6pArrtp/C2p9O4siZCvxnZz7+szMfAHBNp3CM6dURo3pFYWB8OHRa/h+RiHyHyaDDPx4aipnv5SLrwBn87p856B1jxvQbu2LitZ0QpNeqHSIRBRAW6eRRcRHBmD2mB2aN7o5fTpbi631F2Li/CL+cLMXOU7Vff/3mEEwGLQbEh2NQ53YYlBCBQZ3boaPZqHb4RBTggvRavP3gYKR/vg8fZp/AvoJyPLN2J9K/2IfJ13fGb27ogk4RwWqHSUQBgEU6eYWiKBiYEIGBCRFITU7CmXILsg6cwbf7i7D5wBmUVduw9ch5bD1ycdxnfLtg9IkNQ8+oUPSMDkXPKDO6dQyBXlExESIKOEadFmm/6ocnxybhXzknsPKHYzhZXIWlGw/jrazDuK5zOwzqHIFrE2q/x4YHQVHYUBGRZ7FIpzbR0WzEPYPjcc/geDgcAofOXMD248XYfrwE24+X4EBROU4WV+FkcRUy9xTWO7ZTRBCCHRpsrN6FhHYmxEUEo1O7YMSGB6NjqBFhwTq+QRKp6I033sBrr72G/Px89OvXD4sXL8ZNN92kdlitFm7S43c3d8OMkYn4em8hVmw5hi2HzyEnrxg5ecUAjgIAosxGXJsQgcSOIYiva5/iIoLRKSIY5iC9ukkQkd9ikU5tTqNRkBRtRlK0GfcP7QwAKK+2YufJUhwoLMehMxdwsPACDhVdwLmKGpwqqQagwaHtpxs9n06jIDLEgMgQAzqEGtEuxABzkA5mow7mIB1CjTqYg/QIMeoQpNcgWK9FsEGLIL0WwXotjDoN9FoNdFoFeq0GBq0GGg2LfqLm+PDDDzFnzhy88cYbuPHGG/HWW29h3Lhx2LNnDzp37qx2eB6h1ShI6ReDlH4xyDtXgexjxdhxoraTYV9BOYrKLci4rHPByRykQ/sQA8JNBkQE6xFh0iMiWI/wYD1MRh1Mhtp2yGSo+9mghUFX2w4F6TUwaLVQYMcFK1BWZUWwUKDVKNBr2E4RyY5FOvkEc5AeI3p0wIgeHeptP3fBggMFpfh841ZEde2FgvIanCqpwumSKuSXVKPcYoPNIVBUbkFRuQWAZ5b21mpq3wh1GgVaRYFWW/uzRqndrqnruddoAI1S+1gBgLr3TAW1Q35qv188r4KLDy7v/BdCoKxcizeObPHaJwNNnbepq9WLvYk8mty/qScACOFAaYkW/zixrdGYGguz6Rjd+115u6x5ffKggBqzvGjRIjz88MP47W9/CwBYvHgxvvzySyxduhTp6ekqR+d5XdqHoEv7ENwzOB4AUFVjx67Tpfj5RAlOFlfhVEkVThVX4XRpFUoqrSivtqG82gaca+0aEjrMy/m23haNAug0Gmg0gFZRoLmk3XK2Sxql9t+Is61SUPsdSv3H9f+tX2y7FFebVruPcnGni/vj0mMbj765/36FECgu1uKfp36U/hNSIQTOM1e/NrZvNB4Z1d1r52eRTj6tfagRQ7q0Q1FHgfGjukGvr//RscVmx/mKGpy7UINzFTU4X2HB+QorLlTbUF5d+wZ5wWJDWbUVFRYbqq0OVNvsqK6xo9rmQFWNHRabHZcvmGp3CNgdAjVtmGstBfmVF9r8qupQkHdBvtUdLVa72iG0mZqaGuTm5uLZZ5+ttz0lJQVbtmxp9BiLxQKLxeJ6XFZWBgCwWq2wWq3NvrZzX3eO8QadAlzbyYxrO5kbPHfBYkNBaTVKq6woqbKitMqK0iobSiprf6602lFVU/tVabWjssaGqhoHauwOWG0OWGy1P9fYHLA1sqqzQwA1dgcg3UtOwdHyErWDaCPM1Z9172iq1wY1p11yp81ikU5+zajTIja8dnx6a9gdAla7o+5L1L0pOuBwoPa7ELDX/SwE4BACDlHbO+Coe+ycTlkIAQFACKD2pzqN/+his9mwbduPuH7Y9dBpPf9PUzR6VaCpaaBFvX1Eo9ubOuDSazV2fpvdjpzsHAweMrhBro2dv6m5qpuKxXNTW7t/oqiwIE9d3OedPXsWdrsd0dHR9bZHR0ejoKCg0WPS09Mxf/78BtszMjJgMpncjiEzM9PtY9QSVPcVDQDauq9mvlxq2xnAXvfluOS76wuoa59qX7nissfO73A9V9uj6XBuQP3nL91Wrz1A4w+a/PfY1HZOQU9+LtKSh88/z2uw/UrtUmVl8z9VY5FOBOfwFq2q8yBbrVaU7Be4sXv7Bp8YyMZqtaL6sMCtvaOkzzUQNDZkoamPtOfOnYvU1FTX47KyMiQkJCAlJQVhYWHNvqbVakVmZiaSk5Olfw05c70tJXByDaS/K3OVR3PydH562Bws0omIqEU6dOgArVbboNe8qKioQe+6k9FohNHYcE0EvV7fojfvlh7nj5irnJirfK6Upzv5e3zJx/T0dAwdOhRmsxlRUVG48847sX//fk9fhoiIVGYwGDB48OAGH+1mZmZixIgRKkVFRCQHjxfpWVlZmD17NrZu3YrMzEzYbDakpKSgoqLC05ciIiKVpaam4t1338U//vEP7N27F08++SSOHz+ORx55RO3QiIj8mseHu2zYsKHe4+XLlyMqKgq5ubm4+eabPX05IiJS0f33349z587hxRdfRH5+Pvr374/PP/8cXbp0UTs0IiK/5vUx6aWltVOsRUZGNvq8p6bjch5z6XeZMVf5BEqeAHNtah9/NWvWLMyaNUvtMIiIpOLVIl0IgdTUVIwcORL9+/dvdB9PT8cF+NeUXK3FXOUTKHkCzNXJnSm5iIgoMHi1SH/00Ufxyy+/4LvvvmtyH09NxwUEzhQ/AHOVUaDkCTDXy7kzJRcREQUGrxXpjz32GD799FNs2rQJ8fHxTe7n6em4Wnusv2Gu8gmUPAHmeulzREREl/J4kS6EwGOPPYZ169Zh48aNSExM9PQliIiIiIik5vEiffbs2Vi9ejU++eQTmM1m1yIX4eHhCA5u3dLtRERERESBwONF+tKlSwEAo0ePrrd9+fLleOihh656vBACQMvGaFqtVlRWVqKsrEz6j4+Zq3wCJU+AuV7O2d45279A0tI2n68hOTFXOQVKrp5u770y3KU1ysvLAQAJCQmeCIeIyG+Ul5cjPDxc7TDaFNt8IgpEzWnvFeFjXTcOhwOnT5+G2WyGoihuHeucGebEiRNuzwzjb5irfAIlT4C5Xk4IgfLycsTFxUGj8fhC0D6tpW0+X0NyYq5yCpRcPd3ee30xI3dpNJorzgbTHGFhYVK/CC7FXOUTKHkCzPVSgdaD7tTaNp+vITkxVzkFSq6eau8Dq8uGiIiIiMgPsEgnIiIiIvIxUhXpRqMRL7zwQqOLI8mGuconUPIEmCu1XiD9XpmrnJirfDydp8/dOEpEREREFOik6kknIiIiIpIBi3QiIiIiIh/DIp2IiIiIyMewSCciIiIi8jEs0omIiIiIfIw0Rfobb7yBxMREBAUFYfDgwdi8ebPaIbXapk2bMGHCBMTFxUFRFKxfv77e80IIpKWlIS4uDsHBwRg9ejR2796tTrCtlJ6ejqFDh8JsNiMqKgp33nkn9u/fX28fWfJdunQpBgwY4FqRbPjw4fjiiy9cz8uS5+XS09OhKArmzJnj2iZLrmlpaVAUpd5XTEyM63lZ8vQlbPP993XE9p7tvb/n2lZtvhRF+ocffog5c+Zg3rx52L59O2666SaMGzcOx48fVzu0VqmoqMDAgQOxZMmSRp9fuHAhFi1ahCVLliA7OxsxMTFITk5GeXl5G0faellZWZg9eza2bt2KzMxM2Gw2pKSkoKKiwrWPLPnGx8fjlVdeQU5ODnJycnDLLbdg4sSJrn/AsuR5qezsbLz99tsYMGBAve0y5dqvXz/k5+e7vnbu3Ol6TqY8fQHbfP9+HbG9Z3svQ65t0uYLCVx//fXikUceqbetd+/e4tlnn1UpIs8DINatW+d67HA4RExMjHjllVdc26qrq0V4eLh48803VYjQs4qKigQAkZWVJYSQP9927dqJd999V8o8y8vLRc+ePUVmZqYYNWqUeOKJJ4QQcv1NX3jhBTFw4MBGn5MpT1/BNr+WLK8jtvfy5BkI7b0Qbdfm+31Pek1NDXJzc5GSklJve0pKCrZs2aJSVN539OhRFBQU1MvbaDRi1KhRUuRdWloKAIiMjAQgb752ux1r1qxBRUUFhg8fLmWes2fPxu23346xY8fW2y5brgcPHkRcXBwSExPx61//GkeOHAEgX55qY5sv3+uI7b08eQZKew+0TZuv82jEKjh79izsdjuio6PrbY+OjkZBQYFKUXmfM7fG8s7Ly1MjJI8RQiA1NRUjR45E//79AciX786dOzF8+HBUV1cjNDQU69atQ9++fV3/gGXJc82aNcjNzUVOTk6D52T6mw4bNgz//Oc/kZSUhMLCQrz00ksYMWIEdu/eLVWevoBtvlyvI7b38uQZKO090HZtvt8X6U6KotR7LIRosE1GMub96KOP4pdffsF3333X4DlZ8u3Vqxd27NiBkpISrF27FtOmTUNWVpbreRnyPHHiBJ544glkZGQgKCioyf1kyHXcuHGun6+55hoMHz4c3bt3x8qVK3HDDTcAkCNPXxKov0/Z8mZ7L0eegdTeA23X5vv9cJcOHTpAq9U26EEpKipq8L8YmTjvIpYt78ceewyffvopvv32W8THx7u2y5avwWBAjx49MGTIEKSnp2PgwIF4/fXXpcozNzcXRUVFGDx4MHQ6HXQ6HbKysvDXv/4VOp3OlY8MuV4uJCQE11xzDQ4ePCjV39QXsM2XJ2+29/LkGcjtPeC9Nt/vi3SDwYDBgwcjMzOz3vbMzEyMGDFCpai8LzExETExMfXyrqmpQVZWll/mLYTAo48+io8//hjffPMNEhMT6z0vW76XE0LAYrFIleett96KnTt3YseOHa6vIUOGYOrUqdixYwe6desmTa6Xs1gs2Lt3L2JjY6X6m/oCtvn+/zpie8/2HvDfXBvjtTbfrdtMfdSaNWuEXq8Xy5YtE3v27BFz5swRISEh4tixY2qH1irl5eVi+/btYvv27QKAWLRokdi+fbvIy8sTQgjxyiuviPDwcPHxxx+LnTt3ismTJ4vY2FhRVlamcuTu+8Mf/iDCw8PFxo0bRX5+vuursrLStY8s+c6dO1ds2rRJHD16VPzyyy/iueeeExqNRmRkZAgh5MmzMZfe7S+EPLn+13/9l9i4caM4cuSI2Lp1q7jjjjuE2Wx2tUGy5Okr2Ob79+uI7T3be3/Pta3afCmKdCGE+Pvf/y66dOkiDAaDuO6661xTOfmzb7/9VgBo8DVt2jQhRO00Py+88IKIiYkRRqNR3HzzzWLnzp3qBt1CjeUJQCxfvty1jyz5zpgxw/Va7dixo7j11ltdDbYQ8uTZmMsbbVlyvf/++0VsbKzQ6/UiLi5OTJo0Sezevdv1vCx5+hK2+f77OmJ7z/be33NtqzZfEUKIFvbuExERERGRF/j9mHQiIiIiItmwSCciIiIi8jEs0omIiIiIfAyLdCIiIiIiH8MinYiIiIjIx7BIJyIiIiLyMSzSiYiIiIh8DIt0IiIiIiIfwyKdiIiIiMjHsEgnIiIiIvIxLNKJiIiIiHzM/wcAzYEL3SSOfgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P = np.diag([500., 49.])\n",
    "Ms, Ps = run(count=50, R=10, Q=0.01, P=P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is still a lot to learn, but we have implemented a Kalman filter using the same theory and equations as published by Rudolf Kalman! Code very much like this runs inside of your GPS, airliners, robots, and so on. \n",
    "\n",
    "The first plot plots the output of the Kalman filter against the measurements and the actual position of our dog (labelled *Track*). After the initial settling in period the filter should track the dog's position very closely. The yellow shaded portion between the black dotted lines shows 1 standard deviations of the filter's variance, which I explain in the next paragraph.\n",
    "\n",
    "The next two plots show the variance of $x$ and of $\\dot x$. I have plotted the diagonals of $\\mathbf P$ over time. Recall that the diagonal of a covariance matrix contains the variance of each state variable. So $\\mathbf P[0,0]$ is the variance of $x$, and $\\mathbf P[1,1]$ is the variance of $\\dot x$. You can see that we quickly converge to small variances for both. \n",
    "\n",
    "The covariance matrix $\\mathbf P$ tells us the *theoretical* performance of the filter *assuming* everything we tell it is true. Recall that the standard deviation is the square root of the variance, and that approximately 68% of a Gaussian distribution occurs within one standard deviation. If at least 68% of the filter output is within one standard deviation  the filter may be performing well. In the top chart I have displayed the one standard deviation as the yellow shaded area between the two dotted lines. To my eye it looks like perhaps the filter is slightly exceeding that bounds, so the filter probably needs some tuning.\n",
    "\n",
    "In the univariate chapter we filtered very noisy signals with much simpler code than the code above. However, realize that right now we are working with a very simple example - an object moving through 1-D space and one sensor. That is about the limit of what we can compute with the code in the last chapter. In contrast, we can implement very complicated, multidimensional filters with this code merely by altering our assignments to the filter's variables. Perhaps we want to track 100 dimensions in financial models. Or we have an aircraft with a GPS, INS, TACAN, radar altimeter, baro altimeter, and airspeed indicator, and we want to integrate all those sensors into a model that predicts position, velocity, and acceleration in 3D space. We can do that with the code in this chapter.\n",
    "\n",
    "I want you to get a better feel for how the Gaussians change over time, so here is a 3D plot showing the Gaussians every 7th epoch (time step). Every 7th separates them enough so can see each one independently. The first Gaussian at $t=0$ is to the left."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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v4/f7k/1ZTwIxpSIdOXrqyPdiwLQ6Mq2SfD7fqubedKyq1hNQWMazTycsgrKQNraaXpsJYei6zuTkJENDQ2iaRltbGw0NDTk5SRQD6az3OIgplw3YlKM/ePAgaUfU1taWJKZiR1Cp76WiooLu7m7u3btHX18fe/bsobW1dctzSrVKSk35WdHU0wWLoCxsiXTHqqdDULquMzExwdDQEEII2traqK+vz8lJoljYanNLdbTIpXH4caQtN5Kjb9Y4Wwist56iKOzbt2+VVVJ7e3tawpK10ZRlPPt0wSIoCxvCHHmhquqGIy9SsRlB6brO+Pg4Q0NDyLJMW1sbdXV1OW1+siw/ERHUWmLq7u4uSm9WIWDK0U07osrKyrz7GW6GzQixurqa5557bpVUvqGhIaNoyjKefbpgEZSFVVhvSGC6aqj1CErTtCQx2Ww2duzYQV1dXV42h2LKzM31UrG0tITf72dubu6pJ6ZUmHZENTU1XL9+nVAoRDwez4s7+lbYquZlSuXr6uq4efMmk5OTq6ySNoNllfT0wSIoC8DW02vTQSpBaZrG2NgYw8PDOBwOdu/eTU1NTV43hMclM39WiWkt6urqaGhoYG5uLm/u6FvBVN5tBdMq6datW5w9ezbp77cVLOPZpwvWN/MqRz6IyYQsy2iaxtDQEMPDw7hcLvbu3YvP5yvIk2qxU3xCCO7du5e0WnpWiSkVsixTV1eHx+PZVI6eL5iRTTowrZIePnxIf38/9fX17Nu3Ly3CsaKppwMWQb1Ksd702lzqQaqqMjk5SSQSSQ7M83q9BbfJKUaKb3FxMSmDdzqdrwpiMmFGNK2trVRXVyfl6J2dnZSXl+d9vUxFGZIk0dTUhNfrXdV47PV603otwN27d5EkiX379lnNvU8YLIJ6lSHb6bUbIR6PMzIywujoKC6XC0VROHbsWFGeRgud4ltcXMTv9zM/P09TUxN2u53m5uaimtM+bqQ26paUlNDV1cWDBw84d+7cI3L0fCBb1aDb7ebEiRMMDQ1x+fJlWltb2bVrV1rXtilDt4xnnzxYBPUqQa7Ta9ciFosliam8vJyOjg4cDgeXLl0qqjVOIQhqLTHt378fh8NREBPXJx1rnSRS5eg3btzI2B19K+TSGCxJEm1tbauk8ulEepqm4XQ6V43xsIxnnwxYBPWMI9/EFI1GGRkZYWxsjIqKCg4fPpz0SguHw0VV1eW7BpVKTM3NzUliSsXTYK2UT2xkdVRVVcXp06eTcvR0Jd/prJdr35XZeDw4OMi5c+e2tErSNC1JRpbx7JMFi6CeUQghWFhYWOVHlisxDQ0N8fDhQ7xeL0eOHHnkydQkjGI1d5qbSa5+ccFgkEAgwMLCwqqIaaP1Xk3Y7LNNlaOn646+FfJ17ciyzK5du6ipqVnVeFxSUrLumqnRkmU8++TAIqhnDKlDAi9fvpz0M8sWkUiEoaEhxsfHqa6u5tixYxuODjc3lmJt4qkjMLIhqGAwiN/vJxgMbkpMa9crNJ4kEkznszXd0W/evMnZs2fp7OzMWo6e74ebiooKTp8+zd27d+nt7WXv3r20tLSsek+mSGgtUl0odF3HZrNZ0VSRYRHUM4L1ptcqipJ1yi0cDhMIBJicnMTn83H8+PEtjTrNm3ztE2mhkC0hriWmAwcOpNXomc1axUA0GsXj8RRk80yX/J1OJ0ePHt3SHX0rFCL6VhSF/fv3U1tbu8oqybShSk3xrYX53lPl6JbxbPFgEdRTjs3Gqpt9SZkgFAoRCASYmpqitraWEydOrJsWWQ+pBFUMpDZdprMRphJTc3NzRsSUut6TgmAwyODgIPPz89TV1aXtqJAJMolOTXf0XOTohUwPV1dXr7Jx2r9/P42NjWldP2b62jKeLS4sgnpKsd4sprU3jKIoaRPUysoKgUCA6elp6urqOHnyZMYebKm5+2Ig3Sm3CwsL+P1+FhcXsyKm1PWehAhqcXGRwcHBJNHu2LGDkZGRZA9QLindtcgmfZqLHL3Q86fsdjsdHR1MTk5y69Ytpqamkl6TW8Eyni0+LIJ6ypDJWPV0UnypRqf5GD9ezBlNWxHUWmJqb2/P2U/ucRKUqTI0xRwm0cbjcY4cOcLo6ChXr16lpaWFPXv25CUSyZYwTDm6KVKYmpqis7Nzy2urWAIbs25269YtwuEwS0tLaRG7ZTxbXFgE9ZQgE2IysVkEZbojmH5y+ZpZ9DgIau16hSCm1PWKjVTvv43EHJIk0dLSQlVV1arhg+kM+NsMuUY0lZWVGcnRiznew+l0cuTIEb72ta9x//59QqEQe/futaySniBYBPWEIxtiMrFeDcqUVJtNqPm27Sk2QaWm3ebn5wkEAiwuLtLS0pI3YkpFMSOo1MGH6X5XZg+QOeBvPdVaJshHys2Uo9fW1ibl6BulWYs9f8p8b0eOHGFwcJCenh46OzupqqpK+7WW8WzhYH2aTyhShwRCdhNTUyOo1KgiHUl1tngcY9iDwSB37txhaWmpYMRkrlUMRCIRVlZWuHTpUlZu6bIsJ016TbeH9vb2rB5E8lkTqq2t5cyZM9y8eXPDelmxCUoIgaZpeDyepFXSpUuXaG1tZffu3RnVpqxoKv+wCOoJQ7rTa9OBLMssLS1x5cqVgm/eqWsWi6Dm5+cRQnD37l1aWlro6Ogo+MyiQkZQKysr+P1+pqensdvtnDx5Mqe0q6lau3XrVpIQampqMjpGvkULqXL0q1evPiJHz8XqKBuY16pZR0q1SpqZmaGzs3PDvr9UrI2mLKuk/MAiqCcE5sgLTdNyJiYhBHNzc0xMTBCNRmlrayvK5g3FIaj5+Xn8fj/Ly8tIkpS2e3WuKNTGGQqFksRUX1/Prl27mJqayktN0G63c+jQIcbGxrh27RpNTU3s3bs37c2zEKq6zeTo+bA6ygSpBGXCTJOaKkTTKimdz2Gt0s+KpnKD1XH2mKGqKsvLyywvLyfTG7nUC2ZmZrh06RK3b9+mtLSUyspKtm/fXhRygsIRlBCC+fl5rly5wo0bN6iqqqK7u7uoNjT5lpmHQiFu377NhQsXkGWZrq4u9u3bl/dNTZIkmpubOX36NMFgkL6+PpaWltJ67XoE9f73v4+vf/3rOZ+XKUevq6vj3LlzDA4OFp2gzBT42jVNFeKJEycYHR3l/PnzhEKhtI6Z2m5hjrOxkB2sCOoxIJex6hsdb3p6mkAgQCwWo7W1laamJqamphgfH8/jmW+NfBOUSUx+v5+VlZVHUnnF7k3Kx1qpLh21tbVZ9Zxlg/X6k7Zt27YpGa5HUN/65l/y4P4dXvva1+Z8Tqly9OvXrwOGM0Y+osd0sFXGorKykjNnznD37l16enrYt28fzc3NGUVTlvFs9rAIqojI5/Ra83hTU1MEAgHi8Tjbtm2jsbExSXa5WB1li3wR1HrEdOjQoUdUUo9D1p4tHhcxpSJ1XMb169eZmZlZZfuzFmtrQrFYDFVTCQbv5/W8KisrOXnyJP/yL//ChQsXOHDgAI2NjQXf0NNxkTCtkkxT3MnJyU0/s1RYxrO5wSKoIkAIQSgUIhaLJUkpF2LSdT1JTJqmsW3bNhoaGh658LOxOsoVuRJGusRk4mmIoCKRCIFAgImJCWpqajKyjyoUqqqqOHPmDLdv304KKGpra9f921SS+NKXvoTHIwiFF/N+TuY90dHRwe3bt5OTmQuhNjWxkVHsevD5fJw5c4aBgYFVPV3pwDKezQ4WQRUQqWPVb9y4QVlZGW1tbVkfT9d1JiYmGBoaQghBW1sb9fX1G95gmVgd5QvZEtRaYmptbd2UmEwUk6AyXSvVCd7n86VNTMV6P6aA4uHDh/T399PQ0PDI2PO1su+v/MOfEQlLTE0b2YB89v2Y77uuro6qqqpN5ej5wmZGsevBbrfT2dnJxMRE0iop3ZaNtcazVjS1NSyCKgDWGxJot9uzJgtd1xkfH2doaCgpha2rq9vyye9pIChTcej3+wmFQmkTU+p6xR7vsRVSZ2dVV1en5QT/ONHY2EhlZSX9/f309vbS2dmZHEK59rMN+O8w9tD4bvr6+njNa16Tt/Mw04mSJCXl6KZ9U7bu6Omsmc0x6+vrV5GoORcrHciyzNzcHIODg3R1dVlWSZvAIqg8YrPptdmQhaZpSWKy2Wzs2LGDurq6tC/mJ7kGlUpM4XCYlpYWmpubM34iL6Y5LWwe3USjUYaHhxkbG3sqiCkVHo+HkydP4vf7OX/+fNLgNVVVNzY2htsVBwyByuf+8s/zTlCpD12mfZPX683aHX0rZJLiWwuTRE0Jf2NjY9pWSfF4nFgstkqObo3xeBQWQeUBplInGo1uOFbdZrMRDofTOp6maYyNjTE8PIzD4UiqnDJ9yjJrUIV2iF675maEkS9iMlHsFN96iMViDA8PMzo6itfr3XSo45MMWZbZuXNnsj9penp6lUjiL/78f3Ngb5yFRZlIBHp6c5eap2IjFwlTfWiOcN+1a1fafUnprJlLVGZK+L1eLzdu3KC3t5eOjo4trZJUVUVRFGuMxxawCCoHmI7GsVhsQ2IykU4EpapqkphcLlfSribbCza1O79YuW5ZlpP2TKlYS0ymFD7XGsbjrEGZxDQ2NkZlZSVHjx7N69P944Jp8DowMMDc3Byzs7OUl5dz4cKXONqps3unysyExMCgkldros2OZY5wN10epqen03JH3wq5RFCpMCPQQCDApUuX2LZtG7t27drw2JqmJa99yyppY1gElQXWGxK41UVus9nW3bjBIKbR0VGGh4fxeDzs37+f6urqnC/Sx0VQqRGUEILZ2Vn8fj+RSCRvxLTReoWGmcY1I6aKigoOHz6crNk8K7DZbHR0dDA+Ps6DBw9YXl5mYWGa2XmFXdvjSHEbA4Pw+c9/nje+8Y15WTMdmyOTPF9++eVVQwezvVcyFUlsBkmS2L59+yMkul40vXZdy3h2fVifQAbYbHrtVlgvgorH44yMjDA6OkpJSQnt7e1UVVXl7enJJE0zx10MmIRRaGIyUcwIynxPg4ODlJeXP5PEtB6OHj3K/fv3EToEhhVO/XCUu3eM7/G//uffzBtBpesiYbPZOHjwYLIvKRc5eiEe3srKyuju7ub+/fvJlOTagY0bKSCtaGo1LIJKA+ZTTSwWAzIjJhM2my1JULFYLElM5eXlaeWss4EZ2RVTySdJEuFwmEuXLhGJRNi2bRtNTU0Fi+CKQVCqqjIyMsLc3Bwul4tDhw5RWVlZ0DWfFAghcLlchrO3IggM22jfp/I3fy+xsyXO6GT+vtdM04XpuKNvhXyl+NZClmX27NlDbW1tcmBjR0dHsjHbrEGtB8t49hVYBLUJ0hmrni4URSEej3P//n3GxsaoqKgoykZXLKm5GV2MjIwQi8XYuXNnQYnJRCFl5iYxjYyMUFpaSkVFBT6f74kjp0I+YZu11WvXrqHroMiCpkYNVYV9O+IMjuZvC8mmnpWrHL3Q6W8zJbnWKknTtC3Hn1jGsxZBrYtchgSuh2g0ytjYGLFYjJWVFY4cOVK0YnqhpeamQW0gECAajVJZWZn0AywGCiEzT60JpqZeb9269dgVg8WE+V4lSeL69etEY7Bzu4rTIYhrEt4KHSHyd57ZCi5ykaPnswa1EWw2GwcOHKC2tpYbN24wNTUFkJbN1as9mrIIKgX5JqZUJwHzqbuzs7Oom0+hIiiTmPx+/yqD2pmZGUZHR/O+3kbIZ4pP07QkMbndbg4ePIjX601+X8W2VXrcSCWo+/fvEg5LNDVoOBwCVYPKMuP3/f397N+/P+c6Z66zoLKRoxezPuvz+Xjuuee4ffs2ExMTGQ2QfLUaz1oEhXFjhMPhnKbXpiIcDjM0NMTExAQ+n4/jx4/jdDp56aWXiqqog/z78a0lprUGtY9jom6upGH2nQ0NDeFyuThw4MAqYkpd69WEVIKafHgPXZco8+g4HaCqEuWlxu8jkUjSgSKXWmo+JOvrydFTaz/rrVnM+9G0l1pcXGR8fBxN0zhw4EBaJLl2jMerIZp6VRNUPqfXgjHfJxAIMDU19YgpqLlpb1YcLQTyFUFtRUwmik1QuaynaRoPHz5kaGgIp9OZlrz/1RpBLSxMsRKScdjB/Mory43Pva2tjVAoxKVLl2hra2Pnzp1Z3Uv5nAWVKkfv7e3dUI5eKJHEVjAd0icnJzl79mxGAo9Xk/Hsq5Kg8k1MKysrBAIBpqenqaurW3eMgulgXmxvvFxrUGtnTW1ETCaehggqlZgcDkfaDdHF2gTSfT/muJXp6Wn27NmTd1ulVIKKRlcQAiJR4zOQZahIRFB+v5+urq5kDWhmZoZDhw5lPEokn02/8KgcfWpqioMHD66SoxejBrUeNE3D5XKtEnhkMu341WI8+6oiKFVVCYfDnD9/nkOHDuU8FG15eZlAIMDMzAz19fV0dXVt2tmuKMqGzbqFQrakaBKT3+9fd9bUZus9qQSl63qSmGw2G3v27MnYQupJiKDMaHZwcBBVVamsrKSvry+jYXrprgNmu0KcGp/O9Iyc+Bk47MbvTdPT8vJyuru7k020mc50yjdBmdhMjl7sFJ8JM5NiCjxMe6menh46OzvTVoqaKtZ4PI4Q4pmzSnrmCcpsejNHLxtPg9GciGJpaQm/38/c3ByNjY2cOnUqLbJ7HO7ima6ZSkyqqm44a2ojPI4U31bfpekGHwgEsNlsWXsbPm6RhGkXNTg4SDQapa2tjcbGRnRdp7W1NRm9rI0SclkPSEx81mms1ZmdN2uNYE/sHi+//HLyNYqicODAAWpqarhx4wbT09McPHgwrRpLoQgKHpWjm9HK40rxpVodgaHo6+rqwu/3c/HixYxSpevJ0Z8V49lnlqA2m15rs9mSSr1MEAwGCQQCzM/P09TURHd3d0ZKnM3sjgqFdAkqV2Iy8TgiqI3WM+dnBQKBZPG8trY26yfMx/lkahLTysoK27dvX9Vjpus61dXVnDlzJmlY2tnZidfrzWlNk6CMBztBQ63G6ISxpiQJbDbj94HBgUdeW1NT80jUUl1dvel6uar4tsJaOXpvb+9jiaDMvWntupIksWPHDmpqalYJPNIxHjYFFM+a8ewzR1DpjFXPlCgWFhYIBAIEg0GamprSHlC2Fo8rgtrKXdyczmsSU2NjY9ZPYE9Cik/XdSYnJ/H7/cmbPpMxJZuh2BHUwsICg4ODBAIBvvD5P+buvVEuXrq37t86HA6OHj3K8PAwly9fzkmwAK+81wcPHiBJUOvTCYyaBqevRFDTU8Prvt6MWoaHh7ly5Qqtra2GI8UG55NPkcRmSJWj379/n8nJyZxMmTOFeX9sZPuVjlXSRnjWrJKeGYJKJSYzbN/oYk+HoIQQLCws4Pf7WVpaorm5Oefx048jgpJled1oMd/ElLqeEKKg6ZpUpBKUECIZMQFs3749rcGOmaxVLKiqyrVr1wgGg8RiMf7rf/6P/PcPz/MbH6hgYmKC+vr6Dc9x27ZteL1erl+/zuzsLJ2dnRkLFuAVF4k7d+6g6xL1PsNBwlgH7IkIKrgwt+ExUs+nv78/eT7rCTqKdc3AK3J0s4Z84cKFTeXo+YT5kLpZ5GZaJZmp0rVWSZthPePZpzWaeqoTlUIIFhcXiUQiLC8vEwqF0ioU2u32DYnCtOy5cuUKN27coKqqitOnT7Nz586c8/pPQg1KCMHk5CTnz5/n/v37NDc3093dTXNzc142B/MYxYo0TBHIxMQE58+fx+/3s23bNrq6umhoaMj7hlfo97W8vMzo6ChLS0uUlpZy+vRpAoEAFeU6O9s04qrEpUuXtjyO+RReVlZGb28v4+PjGZ+LmYF48OABsTjU+XR0HVR1NUGthKJpn4/X66Wvr4+RkZF1I9/HUTs5fPgwpaWl9Pb2MjY2VhRvx3TVw+b+U1paSk9PD6Ojo2mfX6rSzxRRPG14qiMoVVWpqKjgzp07GW1G69WgTGIKBALJQXqZjB5Pd93HUYMy3cUnJycJBAJomkZbW1tBNnDzeMXI7QshWF5eZn5+nqWlJbZv3059fX3BNrlCPoGurKzg9/uZmZmhoqKCiooKdu3aBcDLd+4A4B9W8LgF169f5Qd+4Ae2PKaiKBw8eBCfz8fNmzeZmZlh//79GV3TkiQxOnyH5RWZOp+GyylYCMpIEthsUFmmk+4lLcsy+/btw+fzJQUU7e3tyQe/x0FQpqhgKzl6vtfMJKIx5fK1tbWrzi+d+vfTbpX0VEdQdrud0tJSgsFgRptHKlGY4oBLly4xMDBAbW0t3d3dtLW15X00xOOIoEx38fPnzzM4OEhLSwvd3d00NTUVzMUZKGgdykxPXrhwgZmZGVwuF93d3XlJUW6GQqj4QqEQt2/f5uLFi9jtdk6dOvVIWnJqcoBQWOLeoI3DHTGG/FtHUKmoq6vjzJkzhMNhent7CQaDab3OrAnNTD1gaUmirkanxCOYW5CRZVBkKC/RkTL8yH0+H2fOnAGgp6eHmZkZoPgEZT64mRt2bW0tzz33HEIIenp6mJ6eLsi6G43a2Aqm8ESWZc6ePcvk5GTarzX3x5WVFR4+fPjURFNPdQQF4PV6mZ+fz+g1NpuNUCiUjCgy6fPJBZmMfc8VZsRk9jHt2bOnIBHTWqTaseQba90s2traAJieni7axpavGzsSieD3+5mcnKSuru6RHrrUB67F4ASlJYI7d2287rURPv6/RjJez+VyceLECQYHB7lw4UJahXfzO5yfn0bTJep8GuWlOnPzMg67IBoDj0tnbjHzz97hcHDkyJGk7LulpSXZBlIsmO8v9Z5PPa9r165l1DybLnJxk3E4HBw+fJjx8XFu3rzJ5ORk2j6IkiSxuLjInTt38Hq9T0U09dQTVFVVVUYEZfruzczMsLCwkLWcOhsUI4LSdT0pftB1nZqamqQsvljIt5IvdVDgWjeL8fHxp8phPBqNEggEGB8fp6amZl3XkbWIREK0tajcG7Txwfct8t/+JJTV2pIksXPnTqqrq7l+/TozMzN0dHRs2MNnRlArKyEcdkFVhaC60iAop8NwlXC7IBqXiMfjGZuumrLvqqoq+vv7CYVCeXfD2Azmvbj24WY9OXpnZ2fehlOu7YHKBg0NDVRVVWUk44fV0dvTYDz71BOU1+tlYWFhy78zpcemas3hcNDV1VXUlEIha1Cp708IQVtbG/X19QSDQebmNlZZFQL5Iqi1U3nXG35Y7ObZbNeKxWIMDQ0xNjZGdXU1x48fT3sztttUaqp1xiZsrIRkZCnzHr5UVFZWcubMGW7dukVvby8dHR3U1NQ88nemik/XNWp9GpIEDXU60zMSTqcgkoig4nGJ4eFhdu7cmdX5lJaWcurUKV566SX8fj8ul4uWlpaCb5obEZSJVDn6+fPn2blzJzt27Mj5vPJlr+RyuTh27BgjIyNcuXIlrVlYqqomCelpMJ59JghqswjKdBEYGhpCkqRkbWlwcLDoBdlCRFAbEZP53h5H3StXgjIdE/x+P+FweNOpvIUcWLgW2ZBhPB5neHiY0dFRKisrOXbsWFqNlyZ0Xcfh1PFVa0Sjdt7165X4hxVmZ2fTemLeCDabjUOHDjE2Nsa1a9fW3dxMghJCp67G+D5rqnXGpxRcLkEkKuNO6AgGBwezJigwvke32019fT2Dg4NJAUUmjfCZwhTybEY4phy9pqZmVdSZixw92xrUepAkidbWVqqrq1c1aW8U7a1d+0k3nn0mCGq9CEHTtCQxKYqyqlkzGAwWXU0Hq8e+54qtiMnE4zCozZaghBDMz88zODhIKBRKEtNmN3Oh6l25wpzGOzw8THl5OYcPH84qRXTnzh0aajV8Xh1ZhuFRBTUhNX/d616X83k2NTVRWVlJf38/586d49ChQ8nIzlRJ2u0adT4NIeCvv+xme6uK2yWIRI1ICkj2nuUCXdcpLy9nx44d3Lp1K5m6Wi+6ywcysTmqqKhIyx093XXzHa2UlJRw8uRJ/H4/58+fZ/v27es2acfj8UfuJ/M9aJr2xBnPPhMEZaqA4FGn6vV81x6H3BvyYxabSkxgjDrYrBk1VWZerCejbAjKJKaVlRVaW1tpbm5O6ymzmCm+dNYyhx4ODQ1RUlKS1Yyk1DX6+/vZvT2Oz6szOy/zYz8Q4i+/VMKN/mt5ISh4JZV17969VaazQgiGh4fxVgrqanT+8ktugkGJhQWZbds0IjGjHwrgc5/7HD/7sz+b03mYfVfmzCQzuiuEUMFcL5Njpsq9zebZbOTohRq5I8syO3fuXGWVtLYp2kzxrYfUaOpJMZ59Jgjq/v37LCwsMD4+npQdbzZCwYxkii1rzSWCSvWVM1OV6bgkKIqCEOKJJaj5+Xn8fj/Ly8tZ9Z4Vm6A2gvlgFAgEcLvdyTHxuX7md1++RVe7akRQEhw/pPLlrwvu3z2f03HXQpbl5D1jms7W19czNjZGaYnA49L5/N+5KfcIVM2InKJRCfNrDi1npqRdD6n3oyRJNDc3JwUUfX19HDp0KKP06FbI1ii2pqaG5557LilQaG9vzyjKy4dIYjOUl5dz+vTp5APH7t272bZtG5IkoarqpmnTJ8149qknKJfLxeTkJO3t7bz97W/nXe9615ZD58yLwxRLFAtmBJUJWawlpkzte8y/K6ZrczoEZdpILS4u0tLSQkdHR1ajt4vt/bee+4FJTA6HI62hh5lgfKyfttdrOB2CGp9OqUcQicDQ8N3k3+TzwSPVdPb27duc7+slGrVx62UbP/cDK3z1shtvucbcvExjmcRKOLG2tpLz2ut58ZnR3YMHDzh37tyqzTZX5NJMbsrRs4nyVFXNedTPVjAfONZaJa2X4luLJ8l49qklqPn5ef7oj/6Ij3zkI1RUVPAnf/In/NAP/VBam7CiKMkxDcUkKPPCSOfGyJWYTJjrmE9DxcBmpBEMBvH7/QSDQZqbm2lvb8/pvB5XBJX6/SiKktVsqXQwO/uQ1iaNuAouh8DjFlSW6szMRpPnkW+YprO3bt0iODfMwR0q8wsye1tVegd0Sl06D8bs7KhVWVhKWFvpW9sdbYWNMhqyLLN79258Ph/Xr19PunznusnnWgsyo7xM5eiFjqBS4fV6OXPmDHfu3KGnpweHw7Ghj+NaPAnGs1k9Un/iE59g+/btSZnjSy+9tOHffutb30oycur/7iTsW7LBxz/+cbZt28a3v/1tfu/3fg+Hw8GP/MiPZLR5Py7bIWDTdc0n8nPnzjE8PMyOHTty8pUzPb+KKZRYj6AWFxe5fv06165dS/qy7dy5M2fSLDZBmcR0/vx5hoaG2LFjBydPnsxpjMdmCIdWqKnWqa7SUVWJEo9OU41GOFzYjUKSJHw+H4oUJRSRWA5LSBjWRkgQGLERCksshRJqUSl3otwq5V5VVcWZM2dwOBz09PRk5KSwHvKVVfB4PJw8eZLGxkbOnz/PgwcPNr0miz3F12az0d7eTmdnJ+FwmOHhYaLR9B4o1srRzQxQsZAxjb/wwgu8+93v5hOf+ARnzpzhf/yP/8HrX/96bt++TWtr64ave/nllykvL0/+Oxdlzt69e/nKV77Cc889R39/P7/zO7+T8TGynQmVCzYb+54qh5dlOa8jInId+54pUglqaWmJwcFB5ufnaW5uznpUyWZrFeOGMRVtc3NzLC0tbaiazBfM793hMPqPXE7QBbjdApDQdJiamkpOhi0EhBDYFFgJy6i6kc6rqhAElyWmpmVCEeMcK0o0yANfplMTNgUUDx8+5MaNG8zMzLB3796sIpJ8+kWaAoXUKG8jF/l8yswzQW1tLQ6HA1mW6enp4eDBg9TV1aX12scVTWX8KX30ox/lbW97G29/+9sB+NjHPsZXv/pVPvnJT/IHf/AHG76utrY27THGW+F7vud7kv9tNupm+lTypCj5Uqe9rpXD5wuPI4IKh8P09/czNzeX0wytrVBomXmqi0UkEsHtdnP8+PGi1PNisRgu5yvXik0xUnyxOOi6xNe+9jXe9KY3FWx9o1YKkSjoOswuyVSV61wdcFJRLghFJBRJUOoCVc9PTSjd676xsZHKykpu3LhBX19fVk4PhYhkUuXoPT097N+/n6amplXvq9gRVCo0TWP//v0sLy8na1PpGgg/DuPZjO6yWCzG5cuXef7551f9/Pnnn6e3t3fT1x45coSGhgZe+9rX8s1vfjPzM90ApoQ3HTeJVGw2cqOQMBtndV1nbGwsOXpg586ddHV1UV9fn/cnk2I26y4vLxMMBhkbG0uauO7evbtgtb5CpfjMZuHLly8zMDBAQ0MD27Ztw+VyFU1scvPmTZobUgjKhkFQqoTLIfjrv36hoOsLIVBkQ0quyDAbVKiq0Flclqgs1YlEJWQZ3A5BPi6vTAcWrk2tDQ4OZnQtFEo4ZMrRDx8+zN27d7l27RqxWCz5+8cVQZkRkN1up7Gxkeeee45IJMLZs2eZnZ1N+zjm/hSPx4nFYgXNYGT0Kc3MzKBp2iNhYV1dHRMTE+u+pqGhgU996lMcO3aMaDTKX/zFX/Da176Wb33rW3zHd3xH9meegMfjweFwMD8/n1Fn/eNI8YFBFpOTk9y+fRubzZbzGPJ01yx0ii91XITb7aaxsZE9e/YUdE0oDEGlSt+3bdtGc3MziqIwOjqa13W2wo0bN9i5/ZVr1G4Hh10QVyUaqlUGH2Rfx00HQghj5pMEmi6YDUqUVUtomkSVRyccM65Zt0MwvZjb9ZvtkMtUf0FTHt/Z2ZmWgKLQI2E2kqM/rgjKfCA3ydHlcnH8+PHkxON0rJJMFCuayorG126mm8mm9+7dy969e5P/7u7uZmRkhI985CN5IShJkrJ2NC9mBGWKH0KhEKqqFoWYTBQyxbeyskIgEGB6epqGhgZOnTrFyEjmbtvZwqxB5aPPKxgMMjg4yOLiIq2trXR2dq5rC1MsfPWrX6a1TkHXQZahslxnclpGF4ZYYXSqsOcihECWQAAeJ8wvy/BQIh6FBq9KKCIhSeBUBNEcn/XMzzXbiKayspLTp08zMDCQrK9spVYrRuvFenL0dKTehcBagoJXJh6b/W99fX10dHSknS5NlaMXwng2o2/H5/OhKMoj0dLU1FTaxTaAU6dOce/evUyW3hTpGsamolgEpes6o6Oj9PX1MTY2RklJCa2trXmvM22GQqT4QqEQt27d4uLFiyiKQldXF3v37k2mwIolyjA/w1yIY2lpKakwNJsct2/fvu4mUkyC0qKz3L+n8Maf8xIKQ61Pwz9iQ5LBV6kT1wp7/SwtLWFTjJRimUdnOSzjH1FAwKltMRw2I/3ntAkiMYmpqams1zKvl1wIw2az0dHRwcGDB7l16xY3btzY9B4vViRjytHPnDnD4uIiuq4TCmXnSJ8LzNTievuO2W/W0NCQnLad7j1sKoXNaCqfe01GV4PD4eDYsWO8+OKLq37+4osvcvr06bSPc/XqVRoaGjJZelNkOnIDCl+DMi1vTGLavXt3crTC4x77ngvMAXsXLlxAlmW6urrYt2/fqllGTwtBmYXiy5cv4/F4tpS+F7sHJBYN8ubXRTh3ycGvvr+Suhqd4TEFRYaGauPzHR4e5vbt2wXZ8EZGRqgo0YnHBW47rEQkRidsOO2CnTUacqI+ZZMAJK5evcrAwEBW15p5veTjM66vr181oHGjh9diTH1Ohcfj4ejRowBcu3ZtSzl6vrFV5GYqEbu6upKtFMvLy2kf3/zuYrFY3kbMZxxnvuc97+Gtb30rx48fp7u7m0996lMMDw/zjne8A4D3vve9jI2N8ZnPfAYwVH5tbW0cPHiQWCzGZz/7Wb7whS/whS98IeeTN5Ftiq8QNSjTpDYQCGC32x/xAsynYWy6yEcNKhwOEwgEmJycpLa2dtM5RsUkKPOJO5ObIRQK4ff7mZ6eprGxke7u7rRds4u5oajxKCCw2eDCZTvhqMTuNpAkQUO1cQ1NTU1RUlJCb28v7e3taTdhpoPR0VF2NmpMLSiUuHWCCwoumyCuQnWJ4Q0oS+BI7CIHDx5kZGTkEdPZdJCPCCoV5oBGv9/PhQsX1h2VUUx3FRPm9XPixAlu3ry5qRw939jMhy8VFRUVdHd3J62S9uzZQ2tra1oPD2bflCkEczgcOT10ZExQb3zjG5mdneWDH/wg4+PjtLe385WvfIVt27YBMD4+zvDwcPLvY7EYv/Zrv8bY2Bhut5uDBw/yD//wD3zf931f1ie9FtXV1Y+9BrXWpHYjZ4HHMf4ilzXD4TBDQ0NMTEykPWDvcURQ6ayXSrL19fWcOnUqIzeCYteg4vE4qi5RVqrzr9sj/P11N+UeI3LxVRrv99ixY4BRP7t58yazs7Ps27cvL5HBvXv3aCzX0TQoKxFEpyUONsa56bfjthsyc1kSOO3GuSwsLKxrOpvOBmV+rvmMUiVJYseOHY8IKMxov9gRFBgkIUkSVVVVW8rRC7F2urUvRVHYt28ftbW19Pf3MzU1RXt7+6pMyWYw30eu7yerSt073/lO3vnOd677u09/+tOr/v0bv/Eb/MZv/EY2y6SNysrKx0ZQa4lpM5Nac91ijX03kY1IIhKJMDQ0lJz8euLECUpKStJe70lK8aW+l62ivycB5ntRZI2HMwpOp0DV4cdOrDAhFGQZykuMvwkGg1RUVFBfX095eXmy0H348OGcp9MOD/mpqwePQ1Du0YmpEoea49wK2LHLEFcl3A6RjKBMT8y1prPpOH6bCr5CbNBmRGCSwYEDB2hsbHwsEVSqzZGiKBw4cICamppkNJWNO3q6yEac4fV6ee6555JWSQcOHKChoSHtaCpXPD6b2jyiurq66H1QmqYxMjJCX18f4+Pj7N27lxMnTmzpx/akR1DRaJSXX36Zc+fOEY/HOXHiBAcPHkybnODJIahYLMbdu3dXvZcDBw5kTU7FjqBsimBkwkirhaIS37k/Tjgko8iGLx+wSmxk9gXV1tYm++tyOd/g7AhLYZkqt2FSG4pIdLbEkSWwyRCLG31QTruxxvT0dPK1pumsruv09vZuOdW50JMFzN6kjo4OBgYG6O/vL9jYi82w3po1NTWcOXMGgJ6enlWfY77XzsZaLNUq6c6dO4/0dW2EfBDUU2sWm4pcVHyZypMzjZg2WreYSIcwotEoQ0NDPHz4MOOR5Nmsly+keoWZiMfjyfHqVVVVGU+x3WytYiEej2NTBOOzCrXlGuGYTE25ztSsgt0mkCWDFG7evMnx48eTr5NlmT179iQNTGdnZzl48GBWG1NoeZ7pBZk2n0qZRxAKSxxsVpEwyFPTDPslj9P47FPnssErprPDw8NcvnyZtra2dYfoQeEJykRdXR0VFRXcuHGDpaWlomczNjKKdTgcHD58uKAzsHJtEK6treW5557j1q1bnD17lvb2dmpra/N2fuvhmYigshVJCCHSjiw0TWN4eDjjiGktnrQIKhaLJWsGkUiEY8eO0dHRkVN6qNgjMFJn2AwODtLb28vy8jJHjhyhs7MzrzOECh1BLS4uMjo6yuzsLC6n4Xt3qDVGJC7hdgriMfB4BOGoceteu3Z13eP4fD7OnDmDqqqbKtk2QywWZmpBYWetQVAApS7D/sgmAwKWQzKehL5kbu5RNwKzz+bUqVNMTk5y4cKFdRWHmdgc5QqzQdVms3H//n3u3btXtOt1M2n7Wjl6b28vwWAwb2vno//KJNJ9+/bR39/PzZs3N3zgtiKoBLIlKNj6qULTNMbGxhgeHsbpdLJv376c5v08Lhf1tQQVi8UYHh5mdHQUr9ebtygDik9QAGNjY0xMTFBaWsqhQ4fy5vuYikJuoCsrKwwODjI7O0tFRQXhcJjqCp2xGTs7anVu+o1+I02VcNgF4USGxX//1obHdDqdHDt2jEAgwMWLF9m1axdtbW0ZzCLTWAxJVJcKcEF1uXENyZJAkQW6gOWQhEMxyGth5uGGxzId7O/cuUNvby8HDx5c1WqSqc1RrjB7d/bt25d0QDl06FDBa5PpRDFmqtYc375z5062b9+e8+ejqmpGqfqNIEkSjY2NVFVVJV0yOjo68Hq9OR97LV61BCVJ0qZkYRLT0NAQLpcrZ2Iy8bgiKJMw4vF4kpgqKys5evToKpf5fKBYBGV+R7qus7CwQHt7e0FuEhOFqEGFw2H8fj9TU1M0NDTQ3d3N9PQ0Fy5cQJIEkSi01mjEVAmnXeCwCRaXZcJRQ0E3P7d5vcKcJVZVVcX169eZnZ2lo6MjLVm90w6RmERElVDDEopkHhPsCqgxiVBcShqZb0ZQYFyHBw8exOfzcfPmTWZmZpJGpcWebg1G1GYS51oBRaEeRtKte6W6o6eOb8+FQPPtAWgaJ5sp3JaWFnbv3p18f1YElUBVVRVzc3MZ15PW64VaS0z5npD6uCIoVVV58OABo6OjVFRUcPjw4Yzdn9NFoQkqdYqt0+nEZrOxZ8+egkRNa5EvgopGowQCgaSysKura5WEd3p6mrmgQjQm0epTiWsSLjtIQrAQlIlEJSpKdMLhrYvV8IoV0K1bt+jp6aGzs3PLUR2yDNE4LEVlossSIvGVyhIosiAaM5p39cRHEgymZzhq1oHMIX+HDh16LARlqvhS1XQ3btxIqukKMeAz02GF6bijp4tCWCyZKdzq6upVzvL5euh9JgjK6/WiqirLy8sZpalSycJ0fhgeHi4IMZkwI6h8eMelg3g8zuTkJCsrK8n8caGIyUShCCp1NInNZksKVLZy0s8X8vF9paZWq6urN5Tvz8xM83BGRga8ZYK4Bg6bQEJidl4mEpMocwumY+kTpjlLaWxsjKtXr9La2sru3bs3JIbFkBG1LUclQppELG72toBdNohKF4YfH8DKSvquA2Yj7eDgIBcuXCiq9Re8Yk6bGs2YarrUtFUmBtTpIBvlYL7k6Nmq+NJBaWkpXV1dDA4Ocu7cOXbu3JkXs+hngqAqKiqQJImFhYWMCSoWizE0NMTw8DBut5sDBw7g9XoLdrOYTzCFHvusqiojIyOMjIzgcrmw2WwcOXKkYOulIt8EJYRgYmICv9+PLMuPGO0WU/6d7Trm9zE8PExlZeWWNb/Q4jgz8wpup47bIYhrEjYFXHbBXFAmHJPwOAVqhn58ZiG+srKSa9euMTc3t27tZWlpiYVlmYoSnaWIxJIwXCOMYxjjN2yy8VnowvhFpoq4VCfyK1euoOs6kUgk51Hu6cC8PteShdPp5OjRo4yMjHDlypUtSTxT5HLfmwRqRsGmO3q6KPSYD/PerKmpob+/H6/Xm7OzyTNBULIsJ/34Wlpa0nqNqqrE43Hu379PSUlJwYnJhHlDFIqgVFVNRoIlJSV0dHRgt9u5cuVK3tfaCPkiKCEEU1NT+P1+dF1n+/bt1NXVPbJZFKvmlc21kRqZezyetAUcoaVp7DaB0y6w20im0VyJ2UuRqIQzQVzZnFdpaekq0cJamyS/34+mS+i6YCEks6TKKAlCkiXTJDbxx4lzi0azS11XVlayc+dOHjx4kDyXQsuXzTrwesQjSRKtra14vd5k3a6zszPnxmdz3VwacXORoxfLRb2iooIzZ87k5UHjmSAoSF8oYW7g5kgIn8/HgQMHipZeMMe+q6qatv9bOkh9Xx6Ph/b2dqqqqpAkiVAoVPSJutnO9wGDmGZmZvD7/cTjcdra2mhoaNjwWE9iBLW2TpbpA1AoFMTlFDx3IAqQFCgoEpSXCsIRKdmsu7y8nNVmYIoWqqurH7FJCgQCAEgCgmGZiPaKSEKWBKpqjNkA0BIfSUzN/iFBlmXKy8tpaGjg+vXrGc0mygYbRVCpMEn87t27GVs3bYR8RDFmFGz2uvX29m45UVjX9eSo9mIgXxHnM0NQWzmap0YWHo+HAwcOJKdIFtulOp9KvtQn9I1SlIqi5EQYmSIbA1fz7+fm5hgcHCQajbJt2zYaGxu33KSKRVDpesqlpiM38mTcCnPBMB6XoKrUnJP0yu9KPIazhMf5ipvEVoKHzVBfX09FRQXXr1+nr6+PQ4cOMTIygt0mKLULQjHD0sh4f4aCL6QavVBOu0BLjHuP5OC9bF6bTU1NScVhNqaz6ULTtGST92Ywpeg+ny8poGhvb886CsrniA+Px5Os+2wlR19vFtTTgKfrbDfBRhHU2pRXamSxuLhY9E5yyI+SLxO1YWpasZgElYkZ5/z8PIODg4RCIbZt20ZTU1ParzUjtkJjMyIUQjA9Pc3g4GAyHVlfX5/1w8/8okadV+C0mWm1V9a1KYJwzKhJATx48IDu7u6s1jHhdrs5efIk9+/f59y5c9y/9zLlHp3aUh0zeyrLENfAbhNE4jKSZKQcVd1Q9cXU7B/0Uh+ezI03G9PZTNbLhCjMxudUAUU2DwX5tlcy63hbydHj8Xiy96tYsGTmKVgbQW1GTCbsdjtLS0tFP9dcIqi1VkvpqA1TCaMYyGS9hYUFBgcHWV5eprW1lUOHDmX8lLfW6qiQWEtQa6O+trY2Ghsbc9oIhBBEohLhiIRNWh1BCQFCN/qTTNHC0NBQ1mulItUm6X9/8r9gV6CtSmVg0UGLN85DWSYal4wIKqFud9gEum4IJvJFUOa5ZGM6my6yiWTM6bijo6NcvXqVlpYW9uzZk9F3Xaja81ZydFPBV6xsUd7acvJylCcAZgQ1NzfH/Px8cnrtesRkolAzobZCNhFUak0jUw9A0yW6WHWo9fzx1mJxcZHBwUGCwSAtLS1JMUe26z2OFN/CwgIPHjzIKupLB6omYUuwkElGmgZohpNEieki/jB/06nBiBbU6BIxFdqqdM6OyTRVabw8aiOqStgVQUSVkv1Qmm6IJiQpe0+9jayOTNPZGzduJGst+WjGzjabIEkSLS0tVFVVJZ3jM0lDFtKgdq0c3RyR4XA4Cq7gKxSevjPeAKWlpVy5coWDBw/ygQ98gB/7sR/bkJhMPI6mWcgsglrb+5NtTaPYDhYbKeuWl5cZHBxkbm6O5uZmDhw4kPNTcTEJSgixilyzjfo2g/m5qZqEJl5RzoEh6a706CyvyJRUGH93+dy387a2ieDiPIshmcZyjXBUoqlSM4gpbkRN4URPlN3shcIgqPHxcZqamjJebzNiy8R0NpP1ciGK0tJSTp06lUxD7t27l5aWli3vy0K3l8BqOfrZs2fp6OgoyrqpsCKoBILBIH/0R3/EH//xH1NfX8//+l//i9e//vVpXbyFHvu+EdIhxlRiUhTlkd6fTJGPqbqZYC1BraysJD3PMp1im+lahUI4HCYWi3HlyhWam5sL5jYwNTUFQCwOkZTmWF2HuAoIQTT6yvUdieT/Gl5ciqJqEvVlBkE1V2nYFZIpvmhcQpIEdkDTDcFEVDUEG9kQ1FZefKZjwVrpd7bWP/kQK6SmIVMFFJtd1/kUSWyGtXL0ioqKpzKCyqli9olPfILt27fjcrk4duwYL730Ulqv6+npwWazcfjw4VyW54/+6I9oa2vjG9/4Br/8y79Mc3Mz3//935/2k9WTGEGZqbxz584xMjLCzp076erqyrnT/nFFUKFQiNu3b3Px4kXsdjunTp1iz549eZXYFzqCCofD3L59m4GBASRJoru7m127dhVMsjs6OgoYEVQ4anznTrtgKQLRmES7T6Xeq6FqIGGIFPKNlYjx/7UlGnHNJCiRIChBWDWipjKbjk0R2BPmsX6/P6v10k0Nmt55ZWVl9Pb2Mj4+ntV6+RQMmWlIRVE2nedkTk8oFlGkuqOHw2GCwWBe3dG3WjsfyPobeuGFF3j3u9/N+973Pq5evcprXvMaXv/6168a974egsEgP/VTP8VrX/vabJdOor6+nr/5m7/hW9/6FmfOnMnK0VzTtKI7b5vrpsKMmM6fP8/Q0BA7duygq6srJyVYKrKZqpsrAoEAFy5cAKCrq4u9e/cWxCWgUARlDm88f/48AO3t7SiKkldyXQ8PHxqmq6VuwcJKQtnmFMwtG82y73nNCtNBhcWwzKGmaE7ihI0QSzy3VbqNe6OxSsNuw6hB2cwICnaWqVR6BDZFAFLWgo1Maldm/1ZHRwe3b9/mxo0bWdV08xnJmDZSe/fu5dq1a9y+ffuR+838d7GHJHo8HhoaGigpKeH8+fPcv3+/6HtetsiaoD760Y/ytre9jbe//e3s37+fj33sY7S0tPDJT35y09f9/M//PD/xEz+RsywW4I1vfCP/6l/9K2DrPqj1kDpyo5gwzVvhlb6Z8+fP4/f7aWtryysxpa5ZDIKKRqPcvXuXaDSKpmnJKbapRqj5Rr5TfLFYjPv379PX10csFku+h2JY8ADcvn0bEPjKNOaXjVvU7TAcHZw2QIJozEj71ZYJogUgKC2hzNOFjNup47KDIyWCiqrG+mUOQXBFwpnYc7ONaLIRV9TV1SWjg0xnJxWi5UKSJJqamjhz5gzBYJC+vj4WFxeTvzfv+WITFBjvt6qqiq6uLsbHxzecy5UvPNYIKhaLcfnyZZ5//vlVP3/++ec3Ne78sz/7Mx48eMBv//ZvZ7Pspshm5IaiKElXh2LCTC2axDQ4OJgc6raZY0IuKHQNKnVTj0ajeDweWlpa8jJ/ZivkK4JSVZXBwUH6+vpYWVlJDm8sKSlhdnaW7zhznGg0mocz3hz+B3cpdQt85TpLYeNaKHEa0ZTbIViKyKiaYeQqSyDIL0FNTk4iAQ0VGssxCU+iSdeREEkYkZSMBFQ6BIshmRJHYqru9GRWa2Y7sNA0nW1qauLChQv4/f60roVC1oLMPq66ujrOnz9PIBBIpvdMJ5liw5SZm3L08vJyenp6GB0dLZoLSzbIKhk6MzODpmnU1dWt+nldXR0TExPrvubevXv85m/+Ji+99FJBcrBer5dQKEQ0Gs0oBVPsOpQQgpWVFebm5lhaWtrSxidfKFSKb+18KdME9fLly0Ud+57LTWa6cQwNDVFSUrKuX94LL7yAEDqf/8v/yfd8z/fkeMabY2pqEpssqCnTGZ4xNtFSl2AxJOF26CxFJRBGT5Q5LDCfMuJz587hsAtaEwTlSDQLO+xGtOZQBKYuo8qlM7Bsw57Y65fmZjY46ubIZWBhquns9evXmZmZoaOjY9OIN98pvrWQZZndu3evaqBta2t7bEKFeDyeNCfeTI6eLzz2GtR6J7HRCAlN0/iJn/gJfud3ficvFuzroaqqCiDj0dbF6oUyjU8vXLjA1NQUDoeD7u5umpqaivJEle8Un6qq+P3+ZBrj8OHDHDp0KHkTFHOqbrZOErquMzo6Sl9fH1NTUxw8eJCjR4+ua+Z67ttfoqZCZ+DWlazGp2eCpZUoJS6Bt0RHS3yEJS6dYEjG7YClqIQkBJEUN4menp68PQlfv34dTZPYUx1nOfqKi7nLkVDx2RJNuRJUOo2IzrzrV5YWslozHzZclZWVnDlzBofDQW9vb1INuR6K5apSVVXF6dOncTqdXL9+veDrbYT1Rm2YcnRJkjh79uyG4o7Hiazo3OfzoSjKI9HS1NTUI1EVGNb9ly5d4urVq7zrXe8CjAtSCIHNZuOf//mf+e7v/u5sTiUJh8NBaWkp8/Pz657DRih0BJVqfBqLxWhra8PpdPLgwYOihvr5Iqi10UZHR0fy4SAVxSSoTJ0kUv3yFEVJq7fs4dgQP9AV4cGwwm/9xs/zJ596IR+nviFKXDq+Uh0tMU6j1CUSBCVYiknoOoRjEvaEV19/fz8ej4fOzs6cRRz37t0jpkkcrFNZjhnRqaqBx2F4ANptEA0b51Xu0FmJSqahOZFImJGRkYytifLlE2mz2ZIzrzYznS10BJUKu91OZ2cnd+7cIRAIcPPmTfbt21fUaGqjCNuUoz98+JDr16/T0NDA3r17nxhJelZn4XA4OHbsGC+++CJveMMbkj9/8cUX+eEf/uFH/r68vJwbN26s+tknPvEJvvGNb/D//t//Y/v27dmcxiPIpg5VqF4oIQSzs7P4/f5HjE+DweBjHfueDUyLpUAggNvt5uDBg5u6cxeboNKJHrL1y1teXmZkCi7eddBcqXLn/iVmZmZyMmjdCi47VHt0VM1I5ZV6dB5OKbgdOitRGTUuEYoYc5nAqMXY7fak20Iug/bGRw0l7u4aFZsELlkQDBvmtOGY0agb0oyoyakAAvREDKXrKvfv32d2djajPrF8GxlvZTqraVrRnL1NVFRUUFZWxsrKSnKScKGHh5rYbNSGKe6oqqpKOnbkem6PvVH3Pe95D29961s5fvw43d3dfOpTn2J4eJh3vOMdALz3ve9lbGyMz3zmM8iyTHt7+6rX19bW4nK5Hvl5LshWyZfPFF+qN1skElnXAidVxVcsyLKc1ftMbRi22+1pTxp+kiKotX5527dvz6ju95nPfAaAqXkZNIWdtXG+9rWv8aY3vSkv578WHodOXJPwlerIsuESXuYSLEckqksFKzEJmwQrYQkSxHD35Zf5mZ/5GcbGxrhy5Qrbt29n586dWW0U4UUj1bOjSqO6RMfrNqI3j0MnHJNxOwXzicvXrghkIC6MnixJCE6fPr1qo0tn/lUhnPY3M50tVsNsKlRVxeFwcPz48aQD+a5du9i+fXvBPfLSmabr8Xg4efIkfr+f8+fPs2PHDnbs2PFYRB0msiaoN77xjczOzvLBD36Q8fFx2tvb+cpXvsK2bdsAQ266VU9UvpEtQeWDLMxN0O/3Ew6HaW1tpbm5ed2boNhj3801I5FI2n+v6zoTExMEAoFkwTcTi6Vi16A2It98+OV95v/8MSUunVKXYGZJobNF5dKlCwUjKJddEItLVJfquO2C4IqMxykIRSRaqjVCKzJ2RbC8rCRrVKND91FV9ZFpuZ2dnRnL47XoMqDg9RgHL3EIgmGZEqdgdsWYshvTjD4okyLVhJuEkIyptMeOHSMQCHDx4sXkGIjNrp1C3Qsbmc4WM8VnwmzSTRV1mOfU0dFRsFYMIUTaIhpJktixY0fy3Kanp9eduJzOcfKBnKjxne98J4FAgGg0yuXLl/mO7/iO5O8+/elP861vfWvD137gAx/g2rVruSz/CLJJ8eVKUCYxXblyhVu3buHz+eju7mbbtm0b3gCpY9+LhXRTfKl9WakNw5naLD3uFN/i4iLXrl3j+vXreL1euru7aW1tzXhTCoVCzC/p/Mrrl3DbdWaWZJp9KkN3C1fwtisQjoGvVMdtT4gjnIJIXMLjEqzEwWkzRBJq4hKan36YJGqPx8Pp06dxuVz09vYyM5OZsi6e+NrMr7vcqRMMSZQmUnxOmyCWmAclEAhhTPx12kRy8q8kSWzfvp2TJ08yMjLCpUuXNpXoF3pWmen2oOs6vb29RCKRokcGa41iKysrOX36NG63m97e3g0V0LnCfBjOpK5kytErKiro6elhZGQkbRFOPh80noxKWJ6QbQ0q25lQ8/Pz+P3+jEdFFHrs+0ZrbkaIZn3G7/ejqmqyPpPtTfy4CGplZYXBwUFmZ2fz4pf3/vf9GgA//Z0hvjXgZDls9CDNzW2sEMsWy8vLvPzyyygyhKIy3lKNEqcgGDJ6kaIxiRKHMUDQrhgpNXOa7fJyMPldmcP4Dh48yPj4OFevXmXbtm3s2rUrre8zFJd4y+GV5L8rXTqffqmEuRWZg01xHDaIqRJKwt7ILgs0IeNUBHF99eZkjv825yh1dnauW7srxjDNVNPZgYEBpqeni6aihfXvd5vNRkdHBxMTE9y6dYvp6Wn279+f130h22GFa+XouQ5rzAbPFEFVV1cnp+Smi2xqUKkzjFpaWujs7Mzoyy/U2Pet1lyPoEwxx+DgYFJlmOs8I3O9YtXZzLVu377N1NQUDQ0NeTOj/fY3X2SbT8PtNAQJVaUa9ydsyCL9dOlWCIfDDA4OMj09ja7rOGyCuZBMlUdQ7tYJrsg0eDUiqoTbYdgNOWyGFVJcM49hRCfmtaVpGqqq0tjYmJyWOz8/T2dn55appIgqsbfmle/OYxME7sqUuQVjs4rhJKEZEZSmS9hlw3nCLgui2vpjbUxl3dWrV2ltbWX37t2rrrFiTXs2TWeHh4dZXFzkwoULOZnOZoLN6l719fVUVlauGuGeTu0uHZiRW7af71p39Pb2dmprazf8+3xGUI+v+lUAeL3erPqg0t1Ig8EgV69e5fr161RWVtLd3c327duzetoptnnr2vXM1OTly5cZGBigvr6e7u5umpub87JRFCuCikajTE9PJx9MTM+/fBH/YkTiuX3GdL5IXKLKozM6J6Nqes7vL9XrT5Ikurq6UBQFhyIodRoCCW+J4cHndhhNss5Es6xTEbidAlUYjbOqtvpczA0pHo/jcrno7u6mpKRky/4gMGpKvpJXjndx1MnOMpVSh0BLWBzpmmF5pAPoIABFMohqvc/FNC7t7u5menqa8+fPr7LaKRZBpWL//v2Ul5fnZDqbCbaqA5muGM3NzVy4cIEHDx7kpbdtMwVfujDl6Hv37qW/v59bt24V5QH0mYqgClWDCgaD+P1+gsEgzc3NtLe35yxRLbaDRWoNam1qsrm5Oe+pxkITVCwWSzpYeDweKioqOHDgQN7XEUJiYcV4IozGJb57V4Sv3XejahK3b9/OSoWa6r7h9Xo5ceIEbrcbXde5fv06kgS+MuOzqynTmQ4aBBVTDVfzmGYIKRw2gcD4b2WdvT11srEQggMHDiTHVWw0DVbXdQQSfUMOfuRgBFWH6ZBMtVtCkY161L1xW1IUoQuYD0vownjajesSCwsLGw4VLC0tpbu7m5dffpne3l7a29upr68vqmDIfJ92u50DBw5QXV3NzZs3mZmZyXt6LRXpKAfXihRMAUUuEV46Cr50sJ4cfb1Iz4qgNkA2Kr7N+qAWFxe5fv06165dS95YO3fuzMuX/TgiqHg8ztWrV+nv7092uBfKfqVQBLWeX16+J9maMKPxqWDi2AJ+7bXLCF0gyyRdztOFpmkMDQ3R19dHMBjk8OHDdHR04HQ6k84GV69eZTlqKPgA6ip0phIEFU+JoFw2gU0yakCybAgV1oMsy8nvNx6PU19fz+nTp5mdnX0kioFXnNSvPjSu8duTNkokQUwzJHuTizLnHzhQNSNy04XEwyUFoUvIgKpLyWNsBLO20dHRwa1bt7h582bRnB1MpJJFLqazmSATO6qKigq6u7spLS2lt7d3y880X+umA1OObkZ6hXRHf6YIKpcUX2oovbS0RH9/P1euXKGkpCQ5/yefxcFiRlBLS0vcv3+feDxOeXk5p0+fzjo1mS7yTVDm5t7b28vCwgKHDh1KWisVigxNa5qlSMI1wS0IRg27Ibsi+PY3/iGt4+i6ztjYWNJSqb29nSNHjlBaWko8HkeSJBwOB3a7nYD/ATEVKhIS74YKjbklQ8UX0xIRlC7htgtsQEyXEALi2ua9YKkpP4fDwalTp5LprcnJVwxeHzx4kHjPMnENvn7fyYmKGDHdkJVPLylcC9iNCEoxCFKRDJm5QzbuoXTVaHV1dZw+fZrl5WV0Xc9arJQN1hJitqazma6ZyYOUzWZLjhUZGBjg+vXrWfUy5iPFtxZmpHfq1KnkmKCVlZXk7/KFZ46gsknxmU7Dy8vL3Lhxg8uXL+N2uwtCTCaKEUGtrKwk34+ZIshXBLgV8kUa6/nlHTlyZFVaoVDzoK5evQqAphkkUF2mMTRnI64am/OtW7c3fb0QgsnJSc6fP8/IyAh79uzh+PHjVFZWJr97h8OBw+FIbpZLi3No+isOEU1elYUVY8yGqku4bCRTfDZheOLZJAjFJObm5jY9H1NAoes6qqqyf/9+Dh48yI0bN7h9+za6rid7Fz2Kzu1JO98adPLGlhCqgLmITDwhioiniCMcsmGFZEucszlwMR243W5OnDiR/LyHh4eL4q69Xh+U2Z904sQJhoeHuXTpUka9g1sh20jGjPBisRg9PT0Z73H5jqBSYT7wVlZW0tvbm5EcPR08czWohYWFjJ5UzC/u1q1bzM/P530c+WbrFiqCCoVC+P1+pqenk4o2MJqni1WMzpWg1vrlmc2W6z2dFYqg7g4YBOVxCiaCMrXlOiNzCrIES2GZpfD6a5oClAcPHhCPx5OSfTA2CzPttt41GonEETaJSOJBubHC6IOSJCNScdoFqibhsQtsGkQ1CZsiEEj4/f4t7ZdSVX7xeJy6ujoqKiq4du0a586d49atWwBsd6t8a9DB7IpMs1snpkvcnLZT59KoSUzZddgEOhKKJFA1OemsbsyzyhydnZ0MDAwwOzublzrvRjBrchvdB6bp7K1bt5J1ss1Ua+kiF/cKl8vF8ePHGRoa4tKlS7S1tbFz58607uV81aA2gqIo7N+/n5qaGm7cuIHD4aC1tTUvx37mCEoIQTAY3LBIm4qVlZXkiGpFUYpCTCYKEUGFw2ECgQCTk5PU1dXR1dWVlBSbqYEnnaDW+uXt2LFjy3H32bqZb4WpUSPd1VhlSMsbqjTG5hU0DRZC63+G6zlXpFox2e32TTepuAaVbsHsonF8px0iMeO9S7KZ4gO3XeBRdIJRBWeCGIaHh5PRyFYwRTOxWAy73U5XVxd3797lyrmXsMmC7toYn7pWSp1Dx5WQlWtCwoFgtxxnTLPhUITRACpJqDp4bMZ7vPvynbTOwYT53fl8vqRNUk9PD4cPH86b1DoV5nex2feQrulsJsg1kpEkiba2tlVjRdJxeShEim89+Hw+zpw5k1dHjGcqxefxeHA4HFuGwCsrK9y6dYuLFy9is9lwOp00NTUVjZwgvxFUqlxZ13VOnjzJ/v37V10oqc3BxUCmBGX2Y128eJG7d+/S0tLCqVOn0jJzzdTNPF3MJq6jjhaV60N2Gqt0JhdlFInkmHVTsr28vMz169e5fv06VVVVScm+EAJd17HZbFuSk4lqj0ge/8qQnflliQcTRuSWjKAcgoqEu7gzsff845e/nNH7k2UZRVGSVjh79+5lfn4GhyLwOgXLMYkzlRGcsiCqS7SWqDgV+P6aKIokcCigCskYmiigJPGQPj6S2dh387uTJClpk7Rt2zYuXrzI4OBgQWpBkN5kW3NC7sLCAufOnWN5eTmndfMh5ikrK6O7u5vKysq0hg4WOoJKRWq6Oh94pghKkqRN61ChUIjbt29z8eJFZFmmq6uLffv2FczRfDPkI4KKxWJJI8x4PM6JEyc4ePDguk9UsiwnTTKLgUwIan5+nitXrnD79u1kP1YmHf6FSvFFY3Faq1W6d0W5MWynqkRnISxTndIj9KEPfYhbt25x6dIlPB4P3d3dtLW1Aa8U4k1iSvvGlV6Jmj76T6WsLMPvvVBmuIfbjd4nj12nwqETjknJCGq89yV+9W1vy2jqr0lSkiQRj8dZCsWIaxIrmpG6e319BEei1nTGF0MC9peqROJGSi+uGQQlS0ZDL8D8UmabuHmdmJ9PpjZJmcK8B9It5pumsz6fj76+vqzqLLqu59X/z0yrHT58mLt3724qoChkDWo9WCKJTbCe1DwcDnP79m0uXLiQbIhMjTCK3ZOU65rxeDw5Xj0cDnPs2DHa29u3HK9e6LHvqUiHoEy/vP7+/pz88gpFULouaG+Oc6wtztCMgrdUZzEiUVumIUmCCpfGN77+teTDjukebhKTqczL9IlS1YwN//6kwt0JG00encCYjWDYEEmoGpQ4oMwuiKskp9ku2FX45jd5xw/+ICMjIxmtaRJoVDUEEEuaTJlTUG43GnOdCvzm3iWQoEQRrEQlHApEtYSLOSSJMq5mdo2Z497XbmymTZLD4aCnpydjT8HN1jNJOV2YprNHjx7l/v37XLt2jVgslvbrTVLMN1GYLg+aptHT07Ouk06xUnyFwDNJUKbUPBwOMzAwkOxXWS/1BYWbCbUZsomgzB6g3t5elpeXOXLkCJ2dnckptluhUGPfN1prI4Iy1ZJXrlyhtLQ0Z9l7IWTms7OzhGIS7S0qNpsR0XhLdZZjMr5SQblbsMcXR9Ej7N27F7vdnkzhZEtMZpQQUSWaPCrv/2I5ihDYZPiV7UtMBRVkGZDA7RBoSDSW60nFX0yX+Jm5OZYfPOBnnn+er/7t32a0fur5LqsSui6xnEg1ShLUOI2pT07ZMK6VE2o+M8VniiR8tszupc3qojabjc7OTvbs2cPVq1d5+eWXc/6uc+m5Wms6u5Vy0oS5vxSiX8/pdHL06FF27NjBlStXHvmMipniAyuC2hRer5fh4WHe+c538tJLLyVrMgcOHNiwmFisse9r10yXFFVVJRAIrOoBOnz4MOXl5RmtWczm4PVIw4xkL126lBx5v2vXrpxvnkJEUNeuXSMal2hvjhOYVoiqEjbZkHN7S3RD5q1IuO3kHDFpmsb//pM/4V8fOQKAqkkcrVe5Pmxnd4WGLMEPtUQpd+lE44mIxpYQLuhgS/QfldgE76iq4kgoxNeGh/nDX/s1fuktb8k4PdboUZmOGtHUsppIuyV+J2PIyoWAmRWJWCLa8zo0zLdty3BX2Uq4k2qTNDMzs26DcSbItRZkms5u376dy5cvc+/evS1J01yzUG4ZkiTR2tqa/IxS62XFTPHl+/09UwQ1OjqK3+/nD/7gD5iYmGDv3r0b1mRS8ThSfOmQhaZpDA8P09fXx8zMTLLBM1tl0+NK8aWKOCD/fnmFIKjbCbn1n/xzCW/9RBWoghsjNgRQXaIhI1AFKApJAUSmxCSE4HN/8Re8obub0o98hNcnNhSPXdDVFGOnT8VjE4YoQ4dqp8aDSdsrBKVLxDSjaRdAFfDP09P8k8tFd10d/yYc5oe/8Q1+8vnnH5lovR7Me2B3ucp0RCYchSUzgkr8jSwJnDLEYhIPFxVimowMlNggFJcT55HZJpWuzVFpaSmnTp2ioqIiJ/+8fNSCTNPZU6dOMTk5yYULFzYlzWINSDQdb7xeb7JeFovFXt0pvk984hNs374dl8vFsWPHeOmllzb827Nnz3LmzBmqq6txu93s27ePP/zDP8xp/YcPH/KLv/iL7N69m1gsxpve9Ca++MUvJocnboUnrQaV2pw6MTHB/v37OXbs2KYj1tNBsVN8Qgju3r27SsRx4MCBvA9mK4TMPHDPcJEITClsr9I43hDnq9dc2GTwlQqEDhHV2JwvXbqU8fG//Hd/x1te+1oWP/hBdkxP83lZ5u8SDeElDsHDJZnGSo0Gl4bHpjMXlVE0GBg1CMplg2hitIX5zqOaxOvq6vh+XectsRh/5XTysZIS6kZG+OhP/zT/9KUvrXsuZoPu17/+dQAOVqpMhRRKZViOryYoKSGIiKswMm8jLgzSsiOSf5vpnZRJ60OqTdLt27eTNkmZIJ+2SqaibivT2WJGMbIss2/fPo4cOZK0ISpG8zM8gRHUCy+8wLvf/W7e9773cfXqVV7zmtfw+te/fsNpuiUlJbzrXe/i29/+NgMDA/zWb/0Wv/Vbv8WnPvWprM/hDW94Aw8fPuT8+fP81E/9VMbpuielBqXrOg8fPqSvr4+xsTH27t3LiRMnNmxQzceahYCqqskifSgUSlvEkS3yKTMXQjAzM8PwoBFxuBLRye5qlYuDDmyKoMylIwlj9LoswT/8Q3qWR2A8oP3cD/0QN/7jfyQWCOCPRBhTFBRdZymxiVQ4da5MOLAr0ODW8dgEc1EZr13nVsBuyM0TEZQsjJoVGFHWMU3jms3GWZeLWk0joml8TzBIxews/+XXfo0P/vIvJ1N+ZjN0b29v0nQXYG+5ynRYZn9JnPlEVCRLIvH/xvtwyoKxoEJMM0jLJgQrifPYyNF8I2TTm5dqk9TX18fS0lLar813NLOWNG/cuPHIfvI4Rsz7fD66uroA4yEqXyKTYiJngvroRz/K2972Nt7+9rezf/9+Pvaxj9HS0sInP/nJdf/+yJEjvPnNb+bgwYO0tbXxkz/5k7zuda/bNOraCt/85jf5whe+QGdnZ9Z+fI+jBmVOuhRCJP2shoeH2bVrFydPnsxoxHo6KDRBpfrlmYabBw8eTFvEkS3yleJbWFjgypUrDAwM8HBiATDculUNakp0FkISupAocwjKHLAUNUZOXOjr2fLYt27d4tff+lb+9h3vYOjWLVqnp3FLEpdtNsK6zv+ZmTGaXmVBtUfnzowNTYdGl0aJTTAfk/E5de5PvJLii+kgdIMoq50qmpAIyTKLus6krvPB+XlOqCr/rbycAHB2fJzlL36Rf3vmDDdu3OD8+fPcvXuX7du3Jx3GAbaXqSzGZLqqYswn5O7mRqFg+O55ZMFiRCKuS4ZwQoKlxN+qYmvD2FRk2zzudrs5efIkdXV1nDt3Lm2bpEKNe9/MdLbYUu+12L17N1evXuXOnTsFTfM/URFULBbj8uXLPP/886t+/vzzz9Pb25vWMa5evUpvby/f+Z3fmfV5pNaYUlV86eJx1aCA5Hh1v99PW1tb8oYrRDG1UAS1kV+e+btCwySobEkqtcnWlLu7ZeNzkmUJlyKodOtoKkwEZVZiRt0nHDNcxacmNpZ0T0xM8DvvehcfeeMbudbXx78fGaFZ1/nTsjKEpvGtqSm8us7ramrQJHDZBNVunWBUZmZZodGjUWoXLMQNYoxGJSREgqAkdA1CCfKKaBK3gS9OTfGdkQg/4/UyrCj0TE3RqOucqK0loij84b17/M5b3sLZb3yDM2fOJN0uLl68iISg1qWj69Ds0lhIRlDG+3HIgqXEuPdyl0hGUGWKcc5VioYupKTpbDrIxd1ElmV2797N0aNHefDgAdeuXdvyYbOQzukbmc4+jggKXlHwtbS0cPr0aebm5jKOOB8ncvqWZmZm0DSNurq6VT+vq6vb0tG4ubkZp9PJ8ePH+YVf+AXe/va353IqSRRqJlQ+IYRInuODBw+SrgkNDQ0FtSHKtxxb13XGx8c5d+5cMiV5/Phxqqurk43BxSAo8zPLlKBCodAjTbZm3dI862hcQpYElS5BmSKYWVKYC0nEdSO68thF0tcuFUtLS3z0//v/+NnXvpaL//iPfNzvpy0e5x1eLxWqyoWpKSKSxMnaWg5pGn81N4cmG2PUq1w6MU1ielmm0WNEUMGYTKlNGK4OqpQkKIcMyzHDMBYk9sTjfE9tLSMOB1+ZmUFIEqfr6hCKwu8uLXFLlvk1rxdpZYXFz3yG3//VX00aot4ZGECSoNSmUe3UqXHoLMSMz9YuQ0gFlyJYTggjyh2GR58EVNgFS3EJuySICTLKiORjFlSq/HsrQ9VCRVAmNjKdfRwRVGrkVlJSwqlTp6ipqeHcuXMMDQ3lvTb1REVQJtaeVDoX3EsvvcSlS5f40z/9Uz72sY/xuc99Lh+ngtfrTbs3wUSxalCmnc+lS5e4e/cukiRx6NChjFwTckG+IighBFNTU8knxB07dqybkizWVF1zzXRvNlNVeOHCBWRZ5tSpU0njTfPpWpbAY9cJxyWicYlyp47Po2GTBQthJSlQcNsEobjE+fPnWVpaIhqN8r8/9jF+tKuLa5/9LC8GAtSoKq+rrWWbpvG16WkGbDaO1dVxTNf58PIyf+908vaaGjRhRCpCFzhknaWITK1Lp9yhsxiXKLHp1Ls1xucVnIqRaiuz66zEDGdxgFGbjf8zP8+UovCG2lpkSeLfRyLckyT+uqQEF+AQgjZVpS4Y5Nt///f8zOtex/DwMNPTU+hCYiJiwy4JahwawUQE5VIEwbiMSxGsaDKKJHBLAlUHJKiyaSzHZEOCjsS//Mu/pP395csf0pR/t7W1cenSpQ1tkoo1e8o0nXU6nQQCgaKXEeDRJl1ZltmzZw/Hjh3D7/dz5cqVvLp05Bs5UbrP50NRlEeipampqUeiqrXYvn07AB0dHUxOTvKBD3yAN7/5zbmcDvBKBJXJU5lZDyqkker8/DyDg4OEQqHkFNu+vr6iqWvAIKhciHitS3dbW9umUd+TRlDmJNuRkRGqq6s5ceIEJSUlqKqaTMEoisLCwgKyDDu9Krem7IRiEhVOY2ifr0xjasnolrVLAl0IQKKuro4/+vCH+dbf/A2HV1b4l5kZfqi2lmO1tfywpvGBuTl+2ufja3V1dOk6u2MxXnC5uFpRQbOuExUCkXiqNyMiCWNSbpldML0s43XqaA6d5aiMXTEsj3wOjdC8hL0kMYtJlniv14sCHI3HuW+zMS5JSEIwKMu8JRSiTFX5o7Iy+lwuPj89ze2FBd7y3d9NHOO93F+0USrr1Dn1pMzcIwsW4zIuWbCsGbOhyoSOKgyFn9dmRJTORGAyMRIgFoulNaomn/edaahaVVXF9evXmZ2dpbOzc1VLQzHTbWaj8aVLl5idnWVgYCBn09lMsFGTrtfrTTq29/T00NHRQU1NTc7rPVERlMPh4NixY7z44ourfv7iiy9y+vTptI8jhMgbi3u9XuLxeHJ4VjownzAKEUUFg0GuXr3KjRs3kvWNbdu2JTfDYqYWc5GZr/XLO3Xq1JaRX7EIaqsUn6ZpBAIB+vr6WFxc5OjRo8lJtmsHBsqyzP3791mOSjSUquhCIqpJRpOsJuFz6kwEZRRZsKNSRRXG2j//hjegfPaz/P3wMDdlmRN1dRwWgt9dXuYrDgf/oaaG3UJwVNMYk2UuOByU6DoLus6PB4N0Jq4DVZOYWFIoc+iJ92Sk0pZUiTK7wOsyfh7XjL6nKocx1daeaNZ12gSyrrMzHudAJMIC8DWHg9+bn+e9wSD/0+3mD8vK+NuZGf7T8jJvqK7mP5eX82fT00kpef+8nV0elXIbRBKRossmWIxLuBSjN0qRoEZoxDRjFEiJTafELrAn1H7RaJze3t600u2FeDCsqKjg9OnTSZuk6enpVesVux7kdrtpbm7Oi+lsJthMnGG32zl06BB79+7l2rVr3L59u6hTvtNBzknR97znPbz1rW/l+PHjdHd386lPfYrh4WHe8Y53APDe976XsbExPvOZzwDw8Y9/nNbWVvbt2wcYstuPfOQj/OIv/mKupwIYF6YkSczPz1NaWprWa8x6iaqqeRtOuLi4iN/vZ2FhgZaWlnXn25iRW7GQTYpvcXGRwcFBgsEgra2tHDp0KO1cerEjqLVrmbL9QCCA0+mkvb0dr9ebHNgnSdK6Dba3b99mPiyzv1bjnx8YzuWlDqPm85qaKDNRGUWGKqfORMT4LH58aoq/Livjn+vqOKqqtKkqf+92c6uigsZEhLRdVZmXZaZ0nZgk8eezs3zR4+G/lpdTlngP4bjEyKINn1PDLgvCmuEQEdIkSm2CJd2Y5huOG4rCUoegxKFjPrg6ELxtcZEPVVRwrqSEz83MMKIo/EplJXbgC7Oz/GNZGf+6pgavJPGRhQU+WV7Oe7xe3DadFVXh1ryNH6kyptuqCYIqUXSCcQm3ohPSjPHuz5XEuGO38RCFElngUAxbJhlBHCmZatu5cyfbt2/f8Om6UJkLM3oZGxvj2rVrtLa2snv3bjRNK8gQ0s2gqiqlpaXs378/afC8b98+mpubC+YuAVv78EmSRFNTUzLi7Ovro7OzM2OXmkIhZ4J64xvfyOzsLB/84AcZHx+nvb2dr3zlK8li8/j4+KqeKF3Xee9734vf78dms7Fz504+/OEP8/M///O5ngpgbIqVlZVJYkgH5kaVj2hmeXkZv9/P7Owszc3N7N+/f8ObodgRVCYEtfZ9HDx4MGNLoseV4jMn2fr9fiRJYs+ePdTU1CTHSmxETCZu376NLiTaa2OUOnSj30gy1Grf3RLlc6MeZElQ59IZXDTW/j/lpRzWdOxCMK8oLEsSTk1jWpL4jwsLXPJ4+Ee7HUWS+OrkJH9aWspPer3UC8E3pqd5X3U1d2UZVUgJ2biEAqzEZaPOpUq4FcGtGQduu+EJKCFwKwKXTWCaNywh8buVlXxpepprTif/trqaUknif87P87mKCn68pgYP8CsrK3ympITPuVzMKAq7YjFGMaKKqYjCsYrE/LBEUOpRYEkzUnwhTUYCdjs1vr7iwpYgJ1kyUpIlimBJM6x3qqqquHbtGnNzc3R2dq57L5hmsYWAaZNUWVnJ9evXmZubw+l05r1ZfCtomobNZkuazvp8Pvr7+5mZmeHgwYMFI8x0ffhMx/YHDx5w/vx5du/ezbZt2zL+XvL9PeZFVvLOd76Td77znev+7tOf/vSqf//iL/5i3qKljZCtki+XIqY5/HBmZibtqbxPYgSVOo031+nCxSQoUzE4MzPD4ODgI5NsU92kt0rvjATuASBLEo0VGrqW6AWSYHu5xvCCgiJDU5nGypgECBwOnc6FGGN2Oy8LgSrLvDA9zedKSvidigoqgW9PTfHhykq+q7aWXcD/m53l130+vqe2lpbEjW2TBZoOYVVC0g1lnMcmiOiG3P3GlB2nJAglmoRdisCugEi8fkWT+ZVohB+sqaFCkvj9xUU+XVbG+ysrWVIUXh+J8A2XiwVdR5ckRhwOGnWdXwkG6fFUU+XQWIpLNDmNz8skqFKbzlJcwq3AigZ2WVCh6EwvypQ7DTdz838eRbCkGU/vJSUlnD59mps3b9LT08OhQ4ceGSa62XTbfMG0SXr55ZcZGRkpuqJOVdVV152pOrxx4wa9vb3JHs5CrJvu/WtK9k3ynJ6epqOjA5fLlffzShfPlBefifVGbmyFbKXmpgGqOfzw1KlT7NmzJ62L4nFEUBsRxlplW1dXV9rvYyMUi6BM3Lp1i4GBgeSY+/r6+uQcHnMwZTq1h+mHAUodOitxmYYyPWnGKktQ7tQJxYyBgT63RijRC6VKEn/tdHJRUfja1BRvWFnh3/p8nHe5+Nr0NLs0jdN1dQw4nfzRwgIzsszba2pYliR+OBZjSpLY7Y1R6dapsOuEVQmbECyrCYJSJdw2gapK7HarxBJzmErsAkkSCbsjgU2Cv3K7eUc4jAz8k8PBjCxTLQRO4MzKCjYh+MuSEroiET47M8Mo8BOJzVETEIwaRGT+GwzSWVYlXIpOWJNwyQIVg0htcsJuSTc2FLsssEkG6ZjXd2dnJzt37uTy5cs8ePBgVb2wWFOeTceH0tJSJiYmsrJJyhZmBJWKbExnM0U2ozaqqqo4ffo0TqeTnp4eJicn037tEyWSeFJRjF6oSCTCnTt3Vhmg7tu3L6OnjWJHUOuJJNYberjeSJJs1ys0QS0tLXH9+nWEEJSXlyeHHaYOiEt3kq2JheASJXZjomxDmZYkKJssKHcY025dNkOcICWaa0OaxLenpviOeJwztbVc93j4y7k5kGVeX1vLhM3Gu5eXGZVlPllejg40aBqVQEU8zrKuU+4QlNoF2zwaYVVK9BbJuBXD1sitGH1QFZLg/rRiKOlserJpq8QmsCsCHZBVFSSJ2w4HTZrGB2Zn0XSd/1RZyY8vLfG16Wm+4XDwupoa/uPSEj+5soImoMmuUuZIIQ8hIQSU2gUrqoxLgZAuY5eMEfAxXUJgRFq6DrokkiM5zHHyZs2vubmZrq4uxsbGVg0hLBZBmbDb7ezevZuVlZWiNa1upBzM1HQ2U2Q7asNut9PZ2cn+/fu5ceMGN2/e3HJ/LESa1iKoBNKtQUWjUe7evcu5c+dQVTUnA9THWYMyZ0v19fUVzC+vkARlNtlevnwZj8eDoiir0nnmJFsz758JlqOGU/l8RKKhVMNlg4hqDOSLqoAOyzHZqAvZDVKIaRJn6urw2+38l2CQMVnml6urCUsS3x2PsyzLvGy3I+k6DyWJ741EeMPSEoNC8GmPh+fCYWbDCstxiaPeOOG4oRhcTqT4TIJySIIGl8btCcOTr8wh0DSDoxyyQMbwxfufpaWcDoX44tQUI5LEv/X5+IWlJb4yM8OnSkv5ztpafiUc5ndWVnh/RQWfKi8nrMmU2w2XCDPAsUmCsCbhUQQrmpFmjOhGlBTH+Lu5SMKDTzNsjnQdHJJIusmY30E8Hsfj8axS183OzhadoDRNw+12c+LEiYxtkrLFVlZH6ZrO5nvdrdDY2MiZM2dYWVl5xL6pGHg6Pdi3QCFqULFYjOHhYUZHR6murub48eNpqwQ3gqIoGU3lzBUmQQ0NDTE0NERpaSmHDh3KenzHVigEQUWjUQKBAOPj49TV1XHq1CkcDgcTExPEYjHKysoyG6+eAlVV+eL//b+oukQ4Bg+XFA7Xx/F5NAbnbFS4BGMrCnEVgmGJiGaMWxfCkHy/JRzmiyUl/FVZGTLg1nWqJYnWaJRv2e18zeHg/QsLlArBeyorEU4nfzMzg99m4ycrK3GvgM+jE1IlVB3q3TqLMUMkEdPBrQjiQqLZqfHijAtZErhtgGY4myuSQRCvW1riF0Ihvqu2ln9wOvmtlRV2x2L8lNeLo7ycfxeLsSxJ/GlJCXagW1X5J5uMXZJY1mXQYS4uUe0QCWsjKdmQ7FYMwiqRBZqASFxCRQEkHBJENMkYQyLBl770Jb77u78beKUVwKzFtLe3Mz4+zpUrVygpKSlI/WUjJJuxEzUXr9dLf38/s7Oz66pt87XmVlG8mYKsrq7m5s2bzMzMsH///pwIJh/TdE3Pw8HBQc6fP8+uXbvWVWUWIoJ6Jgmqurp6Qzf1jbARQZnNnaOjo1RWVnL06NG8STCLabGk6zpTU1OoqsrU1BTt7e1UVVUVVOKaT4KKx+MMDQ0lHxDWNtk2NDQwMDBAR0cHPp8vo2MLIfjnL3+Z//7+9+NJpHsEMBpU+L5dURrKNAbnFLxunYcrCnYZ5kIyobiR4jMHUvQkIqSXZZm3rKzQGIvxe5WVXCkp4f/OzjIjSbyrqgqbJPHCzAzn3G5+0OejUjLqTWWykR6bjspUOARep2AhZkQvakIkoQqDOOaXDNcGM6oKq4ZHX1ST+LPSUl4oKeFd0Silus6Hy8pwA6+PxxmWZS7bbCwoCjWaxoQk8f2Li/yzrxIJQ31nE4LJmEK1Q8UlGQTlkgUrGjhlCGsSTlkQ1mXQYEaV0TF6oKKaBAKEBFfWjCExSUFVVXRdp7GxkYqKCs6fP08sFqOtra0oBfm1fVCpggVTyFFVVZXXNTOJZOrq6qioqKC/v5/e3l4OHTpERUVF1uvmg3BN+6bq6uqk+rCjo6PgashnkqCqqqro7+/P6DU2m41wOJz8tzkyYmRkhLKyMg4fPpz1RbIRijH+Qtf1VZJrgGPHjhUlpZIPgtI0jZGREYaHhykrK0s+IJj+d2Yqb+/evZSVldHf309bW9umfTep6Ovp4cPvfjeN8/P8/cQE7/D5wGZjW7nGSFChoUyjsUxnKGij2q0zGVLw2HQeBu1EVAlVI2kzdNmm8Lm5OWKSxHsqK5E8Hr40Pc0Np5Mf93qTcu8vlpfz5poa3MAvrazwVx4PuixR44qzqMvMRhWq7DrVTo3JmIJDMcQKbpsgrhuKupWYhNstcNuEIf2Oy7gT57FN1zkmBH/ldiMBnarKkCxTE40y5vEwIgRxXecvZ2b4w8pKfruiItGQa9TSdigaU1GZA6WGOMKoPRmE5EjUw6rsOku6hFvWmVEVhDDcL5YTAoqwLrE0PbXuZ26z2dB1nXg8jtvtxufzsbKyQk9PD52dnXlxNNgM61kdmYKFoaEhLl26xI4dO9ixY0deHuDMeUyZ1EFN09nBwUEuXLjArl27aGtry/h88u2iXllZyenTpxkYGKC3t5eDBw8mU+tWBJUmcqlBaZrG6Ogow8PDeDweOjo68v40ZaKQEZQQgunpaQYHB9F1nR07duD1ejl79mzRcv65EFRqk63L5Vq3ydbhcKx6H42NjZSVlXH9+nWCweCm6ZqbN2/y2+94B3tnZvjkw4e80+fju+rq2JGoQ5yoi/PlgIvGco2Gco0LI3ZaK3SmVgyhgMMmWIxJROMgDKdWyhXBO6uqcEkSL8zO8k9lZfxATQ1VksTvLS7yZ2VlfLCykqCi8K+jUb7ldBLVNFRJQsNI6U0HFWajMr9/OMjdRRt3l41bVALsRnCCWzE88EKqEVW5ZcGCKlFlMx52hhSJcsmGU9OYk2XetrDAX1ZU8FduN+VC8LWpKX6zspJ/4/OxX9d5aXqaXfX1+GwaYU1mh1tlNGpspqVKIoJSDCWhQxbEhSFvD6sS7oQlk8AYxSEJgUvWiesyktj4u09N+ZkRsNPpXNVQW6hrdCMnibU2SWbvVq6Tn817PFOiSI1arl+/noxa0o0yTfu2fEvqbTYbHR0dTExMcOvWLaanp9m/f39B3DkskUQCsiwnVT1TU1McOHCAo0ePFoycoDARlDlw7+LFi9y7dy/plF5fX5+8UB/H2Pd0YQ7RO3fuHKOjo+zdu5djx45RWVmJqqoIIbDb7Y+Qk4mysrLkkDbTwDUVgUCAn3jd6/jrN7+ZXxkY4IKq8h9qanBJEt8ZjzOROOauSpUqp06ZQ1BTojO5olBTojMTlnHZBFVunWBcxqnASlxiT1kcmwM+HgxySAh+xufj804nPxeJIIB/sdmYk2VKhMANPL+0hEMIPl1ayplwGJAotxuTeqM67C7XqHW94iYuSa/8zy0LdA2mVxQUcwS7Bq7ExxGRZCZ0nT+fmuJ0JMIvV1UxLkmcm5piv6bRVVtL0G7nC7OzLCgK/6q2FoB9Cfl6pyeOP2RcK6WK0f/kko3IySkbdkweGVYSUvdSm6EcFBJU2gTuhMjCs8UDdSgU4ubNm8zNzVFSUpJsD5ienubChQurMhr5xFZmsZvZJGW7HpA14aaazvb29jI1tX5kuhYmMRaipgZQX1+/av5VpmOO0sGrnqB0XWdsbIx79+4Ri8VWjYwoZH0G8h9BmX55AwMD6/rlmQ2txRz7ni5BpRLrgwcP2L59O11dXVRXV696EtyImFJht9s5fPgwjY2NXLx4kYcPHzI6Osq7fvIn+ZMf/VH+1a1bnA+H+fPycjy6jlPX2R+P49M0ZhLnu71Co8QuGFuS8Xl0FsIylW6d+ahMucOo/SzHJUrsRiThVAQaEn9cWsqAonA84fFXGY0iSRLnXS72xuN8eHaWqK7zK1VV/LvFRb4+Pc1XE0/EcsJsNZ6wF6pxaQRjq+cxyRhpNzUOCxEJLVHvcUgCh9m7BJyKRnldbS2zNhtfm57GKUmcrKtjWVH4b8EgdxWFn/X50CWJf52ove50qtgkQbtLZSRiHKzSbpjEuhWIi4R8nITlkTBc30sUHS1hGhvVTaNbsEti3bE70WiU27dvc/78edxuN88991zSQ9PlctHd3U1ZWVlGm3G6EEKk5cVn2iTt2bOHa9eu5TTozxSG5LKfmOezb98+rl+/zsDAwJb3saqqybpfoWCmIltaWpJjW/KJV22KL7U2I8syLS0tDA8PFzz/nYp8RVDp+uVJkpSTYWymSJegFhYWePDgAaFQiLa2NpqamgCSqbx03B/WQpIkduzYQTwe5/d/4zeI3ryJPRhkSZIYlmXQdQaB9y4sMGGz8T9LShA2G0ejUb7udlFforG9XGVgys7hhjhLMWPkxlJcotyh40QmpMqU2AznB4dkpMCWZZlaIfjJYJCr1dX8YXk5b11c5KdWVvi+ujre4PPxu8Egh+Nxvs/n42NlZfxyJMJ/8niod2qUKDrRxNdT5zLWgxSCkgyCcklGj5KqS2hCosohcNuMz7rephF0OPjM3Bzv9vn4vro6GoGfD4X485ISPl1WhgJU6jqlskxFNApOJ5oOlTadvc44EzPGplZl15mPGTUooRtS9phunMOsbvjuuSTJsIPC+PdyYkaUDPzVX/0V7373u5Pfp6kgra6u5tSpU4+0NZjRzf79+5PquqamJvbu3ZuXjda8HtO5ntbaJJ0/f55Dhw6tGpCaDtZr0s0WjY2NyfM5d+4chw4d2lBNnA8FXzqQJInt27cXZK1nlqBWVlbWtfs3fdoCgQBCiKQdTiQSSU6/LHTkZCJ17Hs2a6b65bW0tKTll7eZm0S+sRVBLS0tMTg4yMLCQpJYU19j9s9kszEtLy/zfz/5Sfo+/3mmZ2Z408oK04rC3zud3LHZ+H/T03zb6eQDFRW4JYmvTk3x+dJSfr/Ug00Gn1unuyHGhVE7370jSlSVqHQZnnjbSjVcus6yqlAmG0IFu2z0CX1idpY319Tws14vv7OwQFcsxvO1tXy6tJT3Ly9TqWm8O7HmT8ViPFQU/jKhhHIqUGnXmdMUwhq4bRBLRFNK4vKQEgTlTjQPx3WJuDBMXZ2Jj0mW4Lai8F6vFwk4EY/zwOFgSpKQdJ1BWebfhELsjUb57cpKziVIYkpVaLZrlNkgpL1CUGMxBadsKAiNGpShLAwnpO0uzZjmK0sgaRAUMo6Equ/v/voFfumXfomHDx/y4MED3G43R48eXbe1wfyuTQFMXV0d5eXlyc348OHDGZPDWmSTbku1STKFAQ0NDWm/fq3NUa4wffO2Mp3Nl4IvXVgiiTRh1o0WFhaoTeTXTdGA3+9HVdUkMZkXqs1mS45mLpZPl3nRZrpmLn55T0IElXr+TU1NyV4PXddXzWXKtpfpC5/9LH/z8Y8zOTfH/56Z4RsuF5/yeHAC35ie5rMeDz/i81EjSfztzAwf9Xr5nro6ajE295gOXpfO4Zo4H/96Ka/bHUWRDZujsCbhdenUOATjYZnaMtWwIBKGE933+Xz898VFalSVn6iuxiUEvxSJMCvL/OeyMlySxPfG4wwoCpOA32ZD0TRQFO4t2yizw4wKs1GZZo8xbwmMyARAkQQeWaCQaJbVjdSiDZEcoqgLsAujkbZDVTkSDnPBZuNvnU7+6/w8HiF4R1UVwuXiizMz/EZ5Ob2KwnhM5ojHSPeZ6/rsOl+ddzEWVojrBonGBLhlYxSHDWiT4ngUYRCUgHlNpgaNFSGxPDXJN7/5TVwuF/v27aO2tnbLjcx8iIrH4zidTk6dOsWdO3fo7e2lvb09qRrLBua1nylhrO1Rmp2dTVsYUIg9JR3T2Xwr+B4Hnu6z3wAOh4OSkhLm5+epqalhdnYWv99PNBqlra2NxsbGRza/1JlQxfpSzXXSvYCj0Sh+v5+JiQnq6uro6urKuA+hGNJ2E2sJaqMm23wQkxCCf/q7v+NTv/u7LC8s8NXxcf5PaSn/zuulRghenJ7mv1VVcaamhlbgkwsL/F5VFf/e5wNJ4q3hMP/P4yGW2JgdCnxjxEkkDL/65QpmojIVTkFYlal26/gcOqFFqHDq2GXTCw++Q1X5tUSE9OZolH5F4UW7nTm7nV2qSkBReG5picnKSl6y2fDoOr89N8dP1NQwGlaod2mGO0OCoDRhmsgaE3SVRASlAqUOnYgmG05HAlYSwwUjQuI/BIPs0DR+o7KSb5SW8vmZGeZkmbdXVWGXJP5idpYrJSX8cE0NQUmgSAIViV+rM+aoqbqELuDaop3+WRu/damckPxKBOWQBWEhUSrr7JE1BpZtSAiqZcF9TUJHsCAUdOAjv/7r/If3v58zZ85kdO3AK0q0ffv24fV6k+Swb9++rKISU8Ga7dO+GdWZPUqHDx+mrKxs09cUckDiZqazxUrxmbCsjjJAVVUVL774Ij/90z/NwMAAdXV1dHd309zcvO4GKElS0a2HzJrQVmum+uWZ9krZ+uU9DoKKx+Pcv3+fvr4+YrFY8vzNFKcsy6sGBmaK3pde4kdOnuTPfvVX+ZuBAV4bifAddXWc9Xj4q7k5yhJ+eFcdDn59ZYVZWeYTZWUEgW2ahkeSqIrFkNZY3fzDoJtyu+Cb3TOU2IzakKqD12VIrXVdotShoyTk3wAvOu2cUVVsuk5JNEpMUZiSZcJC8OHZWfapKr9XUUFc0zg3NcWueJyfSWwoIU0iniCkmYRIwXQTdymCuZghSjD7rlyy4XYuS4a9kTn9NqpL/JeyMn61qooXZmf5/eVlfsTn45eqq/no0hLfqev8nM/HpzwefjoSQWCILeJCwpeoY7kknUBY4ctTbrwI/qF8lrgqcXXejiqMRt2IMBwlfJLOyyE7SBLNioaEoEQW6Al/833z85z/rd/i/3vXuzLyvZNlObnBxuNxamtrOX36NIuLi5w7dy6joaQm8jHu3bRJqq+vT8smqdAPvRuZzhY7xVcIPJME9dJLLxGJRPjQhz5Ec3MzJ0+epLW1dcunmHzNhMoEmxnGFsIvr5gEBUY6zzTkNCfZulyudSfZZoqbN27wY2fO8Lm3v52/vHOHck3jNfX1vOxw8AfBIOOyzHu8XuYkie+Kx4lIEkOKggQMKwrfGY3y1sVFpnWdPy4r43fn5ihNbNATKzJRFVwKyDK4gZcCTmMEu0MnqMlUuzTqXDqKLtAFOCQdXYJ/Pz9PkxB8tqQEXdd5cWqK3fE4P+LzUSoEZ6emiMsyR+vqKFUUGhPfR0xPWBYBU5FEBJFiBDsfNcbMh1QjFekSghXVECdUKoJgTKZWiaMKiVpd5y2qyr/1+fhQeTm/Hg5TLQR/5vFw2WbjcOI63xYOoyWIxJbyAFwh67zvbjk/poTQzFEgccHH75aiJtR8Ud2I7CQZFlSjG6pG0SlTBBUIpARtf02WuRqJMPyP/8h/+IEf4O7duxl9z2ZUHY/HsdvtSXVnb28vDx8+zOhY+YpmTJuko0eP8uDBA65du7ahVVoxRsyvZzobDoetCCoVn/jEJ9i+fTsul4tjx47x0ksvbfi3X/ziF/ne7/1eampqki7UX/3qV3Na/8KFC7zuda/j+7//+yktLeV3f/d3+b3f+7206zO5zoTKButFbaZfntlbcPjwYQ4dOrRlKiHd9QotktB1ndHRUe7du0c8Hqe9vZ0jR45QWlqafK8OhyMtyfh68Pv9/MTzz/PZN7+Z37l1i0FV5cdqa1mSZd4SDvNQlvlySQkSRurvoKbRHg4T1nW+6HLxvvl5/nB+nn9wOPiVqir+bGaG/zU3xy9WVuKxG5vqF++5OFERSzqZ1zs1vvyyC0UWlNsNxwUFY3O2Y4gVXDZBRMj8fHU11fE4F6amsAvB8dpaGjDmP1232fjO+nq8ksSvhEKcs9kYcdjxOQyaWIhL1Dk0HoYSY+wxSKo0oabz2ARBVUaRYJts1L9kSVBt11mMy7gkiCExZlf4ksPBD8XjIEksaBpRWWZWUXAJwa/PzVGlaXwo4Y6iIPAprzy4+Gw6d1ds/HLJCkqCaNwyaFHD1cIpG+uUyYbE3BBrSFQpOi7Z6M2qkIzrTEUQ1nWEqhIdG+Ud3/d9fH7NnLitYAoozMhgz549HDp0iIGBgYzGZuR73LuZYtN1nZ6ennXVw8UsG6Sazo6MjBRE+r0eCiUsyxtBvfDCC7z73e/mfe97H1evXuU1r3kNr3/96zf0xPv2t7/N937v9/KVr3yFy5cv813f9V384A/+IFevXs1q/Wg0ypve9CaOHj2K3+/n6NGjGTf6FdMbL3VN8+YyN3azWdjc2PNpsVRIkURqk+3Y2BjNzc24XC4qKyuJx+NbNtluhbGxMd7xxjfy8R/9UX70xg0uRiL816oqbECTplEpBKoQaLrORUXhXQsL/PLiIn2SxH8rK+MzMzP86fw8/7Gigrd7vfz53By/GQ7z4z4f76yu5v2hkGmsx9/c9/CuXUu4FcF8DJrdOgMztoSDuJ4kqGBMpiIRdTkSr/3n6WluOxwcq6+nDfjQ8jJfczj4udpaqoEziYbgS04nDl0HSVDj1HBJgpAqs82lMR42NlG7ZNSWSm2C+ZhMiSKYj8vIwAGnytCiDUmCOrtGXCep7otiCBj+9dISZULwFyUlbIvF+NLUFHZd59/4fHxHJMLZRJ9Ro0Oj2f7KdVGj6JyUYsjyK4VqBcFvKkssqTJOWYBINA1jpD7HYwo+RUdGICMokQQ2BE4JHgpBrdBZ0AVfmprkxQ/9Pj/34z+e0QPh2pSfz+fj9OnTLC8v09fXx/Ly8pbHyEeKby3MFJs54n7tvKt8q/i2ginoqKysZG5ujhs3bhR9X8sX8kbrH/3oR3nb297G29/+dgA+9rGP8dWvfpVPfvKT/MEf/MEjf/+xj31s1b8/9KEP8bd/+7f8/d//PUeOHMl4fafTycsvv5zMuXq93ow7mx8HQSmKQjweT9r6KIqSVOcU4qmkUO4Vs7OzPHjwAFVV2bFjB/X19czNzfHw4UNUVcXhcGR9k05NTfGJD32IqZ4eKqanGbHZuOZwYNd1HgL/bnkZh67z8dJSbrtc/NXMDGOKwrsrK7FJEl+YmeGqy8WP+nxUSBIfCwb5Umkp70wIJH46HObvXC4uSBI2SdBapjIbltheKvA5dQZXbPgcGrEFBzFNosxuTLh1CsFcVKbcrjOrK9hkQ2zww/X17NF1vica5Z9dLibKyqjQdWQhaFdVPJrGOZuNSUXhT+fm+GFfNV6HQNF17kUU9pXE+daS0bzrkI1BgWV2QTBu9F0FVQmbLNjpUPnneTeyBF67TpndaCA2IFGiafxCVRVvWFnhN5eWeF1tLadqa/nZaJTvW17mTTU1vJCQbYc1mNVe2bgvhxx8h2zMazIVhDYJXqPEcKuGqW1MSJTJhoowrMGSkCmXdHRdwu5Q0KNQKenMCAW7pHPWZqMEwQ9W+9ihanzv2bP8wo/+KB/+8z/PyM08VeVns9k4efJkssa5f/9+mpqaNrx38h1BmVjPJslMZ2ualrNdUjaw2+3s2LGDubm5nE1nt0KhIqi8EFQsFuPy5cv85m/+5qqfP//888mZMFtB13WWlpZyst1PLQgWciZUvmDK2h88eIDNZmPHjh3U1dUVtA8r3ym++fl5BgcH122yLSkpwel0cuPG/8/eewbKVVbt3797l+m9niSkEgg1lIRAAiK9N0GkShEQBH1oogIqSJEioPSOiFJFeu81JKElECChhFSSTD/TZ5f7fj/MnDwREZMQ0Mf3v76c5ORkypm999prrWv9rncZO3bsSl8YarUat197LVPuvZdysciurRYd4HUhWKhp/LlQYJZpcm4kgi4Ej+fzvOz1sl8ySVTTuK1Q4O5YjH1TKYJC8LN6ndtCIW7z+5ljGIy1bd41TUa3Wph+P0/7/TTagrhPYrvdnaO0VzK/aZD0SkJSMqtuIlVX0j3c67C0oeEXClt2yeaGUMQdiR8o9VpSHwPnl8vMNwyuDoXAMHgil2Oy18tR8TgSgV9TjAy4vFMXbByxua/QTRxeXVG3NcKmpN8SBA1FxelWUENMyaJa1zwwrkt8usLQIKJLaq5gr1aL7zYa7J5Oc18gwPcch7HtNr+JRPhrIMB6rgtS8plpIhHM63QvB3VXUHY0ckb38xrYwfILRYkuwfz1fpM2gqCuaEhBWNeo9E4dpcBBdG3qNQgpSV3TcKWLo+ncWsjzw2SKD6Vk/gcfcNh223Hx7bez3vrrr/CxMVAFDRhTjh49mng8zrvvvkupVGK99db7wrba11FBLR8DmKT33nuPyZMns+GGG34jM6gvigEY7+qAzv67YrV8UoVCAdd1yWazf/f9bDb7haiTL4pLL72URqPB9773vdXxkla5gvomZlDLY30ajQbRaJTNN9+cvr6+r/3AWV0tvgEn23feeYdEIvEPTraGYSw7OYLBIFOnTl3hGwbHcbjr5ps5ZrvtuPv66zlj9mz2rde5w+vlQa+Xp/J5Tq7XOSiZ5IpIhAeKRfZ0HHZIp7k6GuXCWo2oUvwyHucl02QPy8IVgpqU2EKw0DDISsmppRI+KflNNMqOtRqbdTo0XY1RPodgb51ksN9lYUsn7ZGM8tkoBPl2dyoz1O+Sb+rYdFl4hugu1nZcl9fp8vf+mstxcn8/p8Vi3BwK8WShwHGtFttnMlwRjXJj73fSlrBZxKLhCIb7XazePURA7yr1wj3kUNCQVHszqEgP2CoEJMyuKEETENQkfk1xbTDI7tksWyjFvo7DMx4Pt4TD9EmJz3UZYdvM6x1vmqsQCoqO4IW6h1HCIS+7lwe/UPTL7kxpsdQwpeKhnB+pGcRMqCMIaxq66FZaEU1QcyCiCzpohOi2+pQQxF2XQ+MJUlLyqt/HIf39/PXjjzl5//25+tJLV+oYHGj5CSGwbZtkMsmkSZNot9v/1Cn3m0gWA1iiMWPGMH36dCqVyr8lQQ2o+Aags5ttthnz58/njTfeWO2zqf/4GRT844tcUULCnXfeydlnn83dd9+9bLH2q8Y3Yfu+KvF5Xl5fXx/BYPAbcxT9qi2+AcDngJPtxIkTGT58OPDFTrYD/fBRo0bx1ltvsWDBgn8qyVVK8dgDD7D/Fltw8wUXcOf773NErcYPEgnuDwR4Kp9nD9tm60yGOyIRri+XSQjBEakUz5kmR7fbtEXXl6lf0zCBuFLsXK9jKsUtoRA7Nxrck8uxBNgvleLYWo2n83nuCgZ5wucjoEvyHQ2jd7Ed5Hf5rK0R8yiE0Ih6XRbXdTQBQ3wuTaeL+XFVF++jEHzgMXkun+fYRoOd02luiUa5p1hkU6XYJZ3mrmCQX9VqSCH4Q0/48llLJ6gpDE2RMLv+T9AFsdZsQdjTlZGHzO5XXYDZW87tSPCK7kxI0U2UPqEISskarosDLO597ouU4qRymT2aTR4xTT7SBRqKwZpkXc1mSsPDfWU/P/HWKfUSVEwoFrkGCSFZonRCmmJhxwO6TlC41JSGoUG4dw0O6RptCRFd62KR6FZUplLUdZ0fOzZeXefeYpGrQyF2yGTYutGgdcMN/PqEE1ZaPj6g8rMsC13XGTduHIMGDfpCCfjX1eL7fAghGDJkCBMnTsSyLObOnbtardxXJD4vzlhV6Oy/M1bLVTGVSqHr+j9US7lc7h+qqs/H3XffzVFHHcU999zDDjvssDpeDvCfl6Cq1Spvv/0277777rKKY9iwYd/43GtVE1Sn02HWrFlMmzYNXdfZYostWHPNNZdVZF+2yySEYOjQoYwbN445c+bw/vvv/8NrePWll9hnwgRu/+lPeaC3y7RVNsvzoRB3l0rEgd2yWV71ejmtXqdfCG4Ih8lrGmv2dpmynQ5CKZ71+dix2eR3xSJFpTghHuen5TJP5fPc7fezXSbDTxsNbq5UOCcSYZdslu/1uH/DAi4tpQ1oJUh5JLmOTtSUVFxBRJMsbWloGiS8PUGCFOh0Z0XQ1Vl8K5vl/lCIy/r7EUJwYiLBDF1nb8uiLQTzAUcI8r0LSEsK3qkbDPFJhPhfkoMQilxLJ2h2E1XQUD2RgsQCpIRyR0fRtX7vqO5SlqFBW0k2tCymAW/0TBKPr1b5aSzGPcEgz+TzGEIQEpL1PA57eds82e/j447BRI+N3XsNUU3ymdSIa5KlUiPmMcgKsF1FQChamoGOwtt7744QNBV0lGIILq7oHg8ZTdBUkiu9Pua6Ljun0hxrWWzcM06stlpMe+IJfrj77ittODpwM6SUWjYHHZCAz5gxY9k59nW3+D4foVCIQCBAMBhcrVbuKxJfpB5cFejsvzNWyyfl8XgYN24cTz/99N99/+mnn2bSpEn/9P/deeedHHHEEdxxxx3svvvuq+OlLIv/lBlUvV7nnXfe4a233lomp18erPhle1BfR6zsDGr5Jdvll4RXZck2Foux+eab02g0lrUZ3n3nHb47aRL3H3MMt8+ahem6bNXXxyyPh9/297NYCH4ej5PXNLa2LBwhyAkBSvGJYfDtToej+/spS8kFkQhnlsv8rVDgPp+P76RSXFip8OdymV/E4+yYyXBiu83Rts1vw2FOSSbZ0XEYpBRL6FLBR4ccEF2/JYCEV1KxNWKmpOEKJgQtpOwih+Ke7g91lEBK6Le779+nSY5tNukXgsd9PupCEATiwMRGA00p7giF2LNe56pCAYC2C2/1e1nD1z3+NODKD4K8mffwh3dDKAWNHpy25gpiPfv3li0odjQcJdAkNGTXLl4oKBo6z3i9PJ/LcUyjwc6pFLdHItxfLDJeSrbLZLotOCUZZ1rs4OnwUsNLQg3Iw7sJN6W5LJE6aVNQUDpxDTZv1qjZXSZgWzMwBQxTDrYQ2EqB0phnd5PSfAUpJSkqmChd0ihuKpfYWUqmezwMcV1mCsGLus7duRxHvfMOh2y3HQ//9a8rfJzC/yapgZbfgLmebdtMnjyZ/v7+b6yCWj6klIwYMYINN9yQ999/n5kzZ37tN6VKqS8lSQwePJgtt9ySSqXClClTVkgB+WXxH9/iO+WUU7jpppu45ZZb+OCDDzj55JOZP38+xx13HACnn346hx122LKfv/POOznssMO49NJL2WKLLViyZAlLliyhv79/tbyef/cMqtls8t577/HGG28ssxBYc801/2Gz+5umV6zoDMp1XebOnbtMvrvpppuywQYbfOUlW5/Px/jx46lUKnxvu+2456CD+NUHH/Cu43BQJkNL09i302GppvFMT2HWBMbbNps3m9Sl5PZAgF+XSlxbLPKIYXBsIsENxSJ/KZX4aSzGXuk059XrnGJZnBiP88NUiu9bFqOB5z0eHvH5WNNxcJRi21qNuFK8putIBGv4XTw9z6O6I0h4JA1HEDUlbakxNuTw+lIPhoCooUApLCkwBcuwRGFdEbYsUIpXvF52brU4v1QipxSnxWKcUS7zRD7P7YEAe/bs6SO6Yl5bYw1v97PxCMWdn/j5Q6wf0VZc/E6IpgNBs1upBY0urHWgzefSxQ/VXQ2/gE5PqLC1bbNlNssDoRBXVCp4gB+mUryl6xzY6ar0fJpifcPB0LoMvx2N7nxiGY9Pk+RdnQQuBSVICsl6moOQ3VlXB42opthIWjxlhdAFJHVBB0FK2oSVZG3loCnFC5rBVs06h6fSzDV0ZgJPezw8m8/z83qdnVMpLo7F+GM+z8xf/5qfHH44nd7rXNEYaPkN2E1suummDBkyhGnTplEul7/RCgr+V2aezWaZNGnSMt+5laFqrGwMnONfRpIYgM6mUilee+21L22//7titcnMDzjgAIrFIueccw6LFy9mgw024LHHHls2n1i8ePHfle3XX389juNwwgkncMIJJyz7/uGHH86tK7nE90URj8cpl8sr5R67Otpt7XabuXPnrjAv799RQX3Z833eyXbAUfjLnGxXJubPn8/Fp5+O//332SeX4y6fj1wshgeIuC5DgZDjYEvJy4bBueUyPqU4JRbj6UiEvxUKVIXg+4kEXiG4vlJhjtfLIckkISE4tdXiBa+XG4JBqrrOlpbFdNMk1Wphe73klEIpxRWFAqcnEvw6GmVtKZlSKDBk0CASHonZA7J+1tIZGnBoSUHUUFgKRgcc7l3ix2d0ad2OCx0BWVNCb+3OlYKLIhEuKpcZa9vskU5zr8fDNZUKSddlv1QKr1Kc0m7zkGkyWdfpMyV5W2PPTBulum652+gdEoYkq0satqBhdm0vGq4gbnRbjiGhyNHdQ/IIqLndHaYldrft9ppp8pNGg1tCIe4KBChrGmvaNktNk7WbTfD7kQhG693jPqIkE3Vr2efVUZDRFG+6GhsIm37Nz2jhkkfHVLDA0mkLQZ8uSSuX59safgPW0SWfuoKA4xLUTIqGSVTBJMvmWV+QHa0Okw2Tl3I5bo7FmJTJkBSC8/v7uT4c5qxolKJts/WLL3Lcnntyzs03M3To0BU+zgaOzwGl7MiRI0kkEssq9wEqxTcRy7M2B4RDn3zyCVOmTGHMmDEMHTp0tVcgAzfa/2pBeEWgsysS/9Ey84E4/vjjOf7447/w3z6fdF544YXV+dT/EIlEAqUU/f39K+yK+1USlGVZzJs3j0WLFpFKpZap1/5VfNMV1D9r8Q3YkMyZM+fvdrEGWgUDiqlVbY8sXryYmy+5hM9efBG7WMQDzDUMhFJ8DPy6XKakafwhHOZVv59H8nlm6zonxuN4heCuQoG3AwH2SqWICcEFtRoPBYOcHovR0TT2b7d52utlqeOwOBjEY9ugFP9TLvPLVIprwmHWtW3uLRQ4Mplk53Sa7W2bV0olDkql2KQ3K607Xb6cz6tY1NJZO+ygejMdDUgYPaRQwKElQVOCliMYFLR61ueCloJNLYvTeon3/HqdsmHw43gcvxAc3unwjmHwmNfLW7pGyuMw2HBpuYK1gg4fNgzqrsDUu/OfphJcEOznF3YUv96tmIKGor+j4dXAr0tcugIJRwnimsJVgpSQ9Gs6jpQIpXjP42FD2+bHlQrHJpP8omd5YQAhTdFWUEVjKTrgENCgKDVimqSieYiIFg3NICUbzEVDKMGTjRAdJUho3d2otqtoKsWamoUPD0oThHSdnCvZRrmMstp8Egizf7XG8GCQzbJZYkJwbLPJXYEAM3Sdhq4TUQqPlBxSKnHaJ59w5E47cdpFF7HzXnut8DG3vBTdtm0ikQjpdJpqtcqrr77Kxhtv/IW2H6szBhLk8ufNACZpwO+qWCyywQYbrNaEOTB/WtHEMUDEmDlz5j9AZ/+d8V/J4gMIBoOYprlScyjTNJfRk1c0viov75uuoD7f4huQvE+bNo05c+YwcuRIJkyY8HdOtgP0h1VJTo1Gg+suuohf7LknLz3wAPvMmcOGnQ5vAy/qOn/L5TilWuWMaJSrw2EeLRQ4udlk53Sac5JJbqhUmCAlR6bTXBkKcUKrhQE8Zxh82OPYGcCO9Toh4N5gkEGWxb35PEnX5YBUivU7HabkchSFYNNMhpHAn0slXvV42D6bJaZpHNeT3b5XNQnpijEhh0/r3dND750lhuj6NUkJbUfQdAU+0ZV6p72SkKEYYdq0pMZkv5dT223GK8VVoRA3BQJs5TiYShFst2nrOjlA0uX4jdAd1jBcZtUN7l7sZwQObQVRTdFRguFG113X6qn2QrqiX2poKMK9qkqI7mJszJRoPYpDv3K5KRTigHqdPxUKvKHrHJJIcGalQkK6aChCPfrE27YHQyk+dLv3rQmvSVF2l2/rwiCiKRpoJJRNUTPJCsEbDQNHQUI4SNEVexRdGOW00KVikWbiFbCNULyiGfw5EMJUkmPjcR7y+Tiw08EVgrXabQJC8FAgwHDb5q58noCUHJJMMrHZ5IX587nptNP48cEHr3TLbwCT5DgOUkoGDx7M8OHDef3115d5wH1dIaVEKfWFlcyKYJJWNVYFr+TxeNhkk00YNWrU30FnVyT+42dQ/2khhFhpocTylhv/KlYXL+/fUUENJKjlJe+DBw9miy22IJvNLjuRDcPANM1VSky2bXPHjTfy/W99i7/ecAPXzZrFd+t1zo1Gedrr5bl8niN7iejWngx7EynZLZXij6EQv6zXUcC1wSAzDINNbRsNyHY66EIw1etllONwWamEX0qOj8fZodFgSi7HfE1j80yG7W2bB4pFHvP7mdTXx3rAT1stnjBNfp5MkgbWdl0UMK/3Hhe3dH46qs7GEZtP6t072gHJuaEpooakaQuWtjTqjoapKRwFaVPi11XX2K8HX12gFAt1HV1KbKU4vlxmhJTcEgphuy7P5HLYCHQFY7wu430Wb/ebPF/08pNIk6LUCQmFjSCqKVoWPL/Egy0FEUNSlV2SeVBIaq62TF7effYuM88VgjuKRW4Mhdg7leL8/n6u6e/np7EYC0yTwcJhzV5778m2l201i0/c7vuOKYei1IhqkobSCAtJC0FMKPp1k8G6wg90pCKhLGoIEpqOoyCJZA1D52Op0ZGSHRpVRgrBGClZs2Pxq2aDlhDsU6sRlpLTYzG2aDR4LZdjiaYxqff5PVwo8LjfzxbZLOt2Ouz2/PMcs/vuzJw5c6WOR8dx+OijjygUCgSDQYYPH85mm23GvHnzeOutt7As618/yCrEv/Kf+leYpFWNVbXaEEIwbNiwv4POftPy+OXjvzZBwcor+QZ8Yr4sYaxuXt6/YwblOA7Tp0//wiXbgXbEQGJa2VmTlJJH77uPvTfbjIcuvJBHZs9m11aLHdNppgQCPFEoMFopts5meSoY5Hf9/XSE4LREgpmGwe62jQXklMIRgvmmyWjX5Uf9/QgpOT8a5YD+fp7K5ZitaeyYSnFkvc5jhQK3BwJsns2yq+tydrPJH/1+jshkWEdKNnEc5gvBcz4fQaXoV4r9ajXGtdvMVopHeydzW8ImMZuxEYt5zR4Pr+sQv2w51lCKRXWdQkdDaF2yt1eXCKEwNfAKiY3gYZ8Pj+tyXz7PaNvm0GSSSA8iG5SS8ZkMCoGDYB2vw/ahDg/n/fiVIm249EsNIboMPENAWCmeWezDUoKoqai7XZJ5SEoaPcGEqRRFV8NQAF0Bwz6pFBdUq5zUanFqNMrJ8TiHdjo4CBKaZFOze3F+zfZwol5jkdbFLCXcNgVlEBWKloKIULRkt0qrC51BwmWNdoe6q4jjUNQM/BpERBePVBMaYSH4TAk+1gwaKH5fKvCm30fasghIycHJJHs2mzybz/Oc38/4bJZJUvK7Wo07/X4OzWQYBuxk28zQdV4wTYqffsqF3/8+Tz388Aodj3PnzuXVV1+l3W6zxRZbkEqlsG2bUCjElltuiaZpTJ48ebVWMAMxMLf9svNoAJM0YcIEFi1axOuvv/6VF2m/qtXG8tDZFZHH/78KahViQCixoiGE+KdzqAHxwGuvvcaiRYsYM2YM48ePJ5FIfKUPZ6Ci+SbUM81mk48//hilFMFgkEmTJjF8+PBlffKv4suklOKVF19k7/Hjefm003j044+Jui4Tslk+9Xq5tlwmp2kclE4zV9c5pNWi0EsYHSFwgbWkZOtGA6UUt4ZCHFOpcHuhwHtCcFAiwa8rFR4vFLg6HGbLTIYftdtc1GhwYSTCftks20vJllLyisfDX0Ihhrgu0nWZ1GiQkJKFwLuaxh/zeY6q1fh9TzjwVD7PFr220QBsdVSgu7ALEDEli9tdgULN7bbXOq6gYGl4RbdqsqVASUBAsPcYT+RyGEoxIZNhpFI8WijwvsfDhL4+IprGWT1prysFg0yXtXwu81s6+3hbxDVFvbesq/UOr4AAJbu2HIEeYiioKUaq3l26gKRQLHZ0Ishlx2VCupweiXBtMMjRnQ5JpZjTu6M3gQ1Mh5aCphJkdUWjp0YcrElympeIJmlL1a3mlCIqJA0Ea0iLdZRD25ZEhKKme/AJxYbK5Vk9jItiayEZb1vc7g0gpeS7yQyuUvxPLM5h9Tp3lUrcFgyya18f6ynFIZbFc6bJn8JhIrKLlxrkugy2bWpSMk3XObNc5uRPP+X8k07i9GOO+cKW3wC4eODiOnbsWDbZZJNlS/HLt7rHjh3LyJEjV2sFMxADN3wrco0YwCT5fD4mT55MPp9f5eddHQT1gSX7AXn8P4POfp30m/9KR92BWBWp+ed3oZRS5HK5Zb3qNddcc7Xy8lbWVXdVYnkn3nQ6DbCMx/VVnWwBpr/9NmcdfzzfKpW4cskSfpRKsWNfH8Ol5NhWiz8Hg9wYjSKBpJREhSBm20gpecbr5ZRymfUch6MSCd6Mxbi5WCQlJbun01ymFL+r1dCBE2MxgprGke02CwyDP/v9KCHY2HGYp2kMbrd5x++n33VpC8GdhQJ3hUJcHwwSAl7I5fhTKMQ+qRRZIXg0n+fqeJxtMhlqvc9ziK970dK0LrYIusu6nzYN4qZkYcfAo3Ut4Ut2t63moQtOdV1wzW6CqkvJpGyW/VyX4+p1zozFeCmbJSElW1gWr3u9PNuT0Sd0d9kcKKJJjgg1sRC0Btx0e79nXSg2kjYfKwO/pmhKjbAmWdewebvl7e5x6TZvWiajNYeFUsdAMVc3uKha5dpIhL/5fIgeyxC6ooiIULxpexjt6X5voNk1VHN4QwXwia5xoia6d7QxIWkryLod3jKC+BS843ioazpDlGSDToNbCGFoih2a/czzxxmMYKdqjbtDQS4oVQgJwY8TCeLAICnxuy62ENQBu8cv/Gl/P36lOCsaxQ0EuC+fp6jrHNFzBb67UGD2I4+wz4wZ/OHPf2bMmDEAVCoVPvzwQ1qtFqNHj2bw4MH/cL5+XuU3dOhQYrHYMtDr2LFjVwvgdWUTxcAi7aJFi5g+fTpDhw5l7bXXXulzc3W66WazWaLR6DIX4a8TOvv5+K9PUKtCkxiwhigWi8yZMwfbthkxYgSDBg1a7TsUA73pr8MzxrZt5s2bx8KFC0mlUkyYMAGv18vSpUuxLAu/3/+VEtM777zDZWecwZrz5vH9QoFrg0HeSqUIK0XMdfEKwWJdByl5T9M4rVzGD/w6GuWtUIh78nmamsahySQm8MdikbxpclhPMn5ms8nbHg/nhsMITWM32+ZNoOk4zPH50FyXfk3j56USV8di/NnvJwE8l8txQTjM/qkUo6TkhXye3yQSbJHJMFIIriuVOC+R4LB0GqdHM78k4MMQEDf+dyhsyy74NOOTzGvqxD2Szzo6ulBENbnMl2m0aePveSA13e6FMKiBKSWvmSbzIxFiUmIoxZquS8R1qUnJK73f+4Y+ByGgKbsVTYeufHzgNmmAcacDJ3rqHGEnCOiKOl15d0jC/I6OT1OM1F28AnRN4ZMKISQldM4Ih+lTij2tDk/4/GzYajEjHKbuCo7tjzHe67KzWwMDNAQNJRipuzzaI5wPAGN10TVvdJQig6RkeEm6ir90gqQNwSbKQSDQ0FgkYYxrM1fT+E2lzFWRGHfn8xyQzjBUSiJS0lSK77Ra+F2XK0Mh3jFN7iwUKGoax8bj6ELwYD7PbK+XPdNpAkJwRX8/z/n9HJpMYmga3128mIu//332PPVURq27Lvl8nhEjRjB8+PAvPac+r/Ib6Cosr2RLJpOrdG4MxKqy/4YMGUI0GmXGjBlMmTKFjTfemEDvhmZFYnW76fp8vn8Knf1/FdQqxsq2+KCboKrVKgsXLlxG6B48ePDXtn0+YDW/OudQjuOwcOFC5s+fTyQSYdy4cYTD4WWqvEgkwqxZs9hoo41W6SD+8MMPuemCC1DTpxOsVFgMFH0+fFKSB35WqbDANLktEGCGx8NDuRzvmWZXdi0E9xcKzPB6+U46TVQILu/v54lgkONSKTQh+EGrxeM+H28KwXSPh0GWxULgu+Uy81Mp7vP7GeS6PJLLcVI8zsHJJBu7Lq/lcvwkmWSzTIZNgDtKJU5JJtk1myUGnFivc2M4zJ9CISqaxgjbpt80WbPdRgT9SODj5v+eEl4BJUsw2OfyWUsn5ZF81ukmpSwuNbdrfb6m7rCko2MKRcPpVjUeoVgqdEKuy8dCcF65zALD4JpQCGkYPJLLcV44zP3BIGt5u6loesuDpWCpqxE23WUnZ1AoKhJMoRihu5h2d+7VloKEKXFtaLiCiC4JiC7dwfR4MVynK3xXCgTUlOJvHi9RJbkzGAAUKVz2V21+24pwnqd7rsQ1xUJXZ6TmULC6F5+Bo1+jS3k3gLSQVIVgXc3lVanRdBXD3TYzdY2oJhjsOBwcytCQikGOzQKlODKdIe66zBOCK0ol6kLw01gMrUejf9802TeZJCAEt5TLvBAOs3c2i18pTm42ecjv55ZAgEVeL2M7Hd43DEY0GrxWKHDNGWcwduutOeuKK1ZKrDSQqAba3BtuuCGfffYZb731FiNGjGD06NGrfBH+KjeeoVCIiRMnMnv2bCZPnsx6663H4MGDV/h5V/ee1wB0NplMMmPGDAqFAhtuuOFKJc6Vjf/qGVQymVypBFWtVqnVaixatIhkMsnEiRMZOnTo145GWV1KvgEBx5QpU5YdPBtvvDHBYBDHcVBK4fF4GD9+PH6/n6lTp64UuSOfz3Phz37GpQccwIyXXmKHefNIuy4fANOF4G+5HEdVq/wmGuWvwSBP5/Oc1GiwazrNRfE4fymV2FpK9k2nuTgS4bRGAz9wp8/HFNNkrNPVv23YbGIKwcteL1HH4Y+FAsNcl2OTSYZ0OryeyxHqiQxCmsaDxSLzdZ0ts1mahsEZjQYf6DpnxeO0hGADx0ETgpbqkh+mmyZ7NRqcWqmQk5JfRaO4qktvKFk6AyOImCn5rK0zyN+dQaW9kpylE9S7Sanf0oiakowh+aTRNTO0pMAEBqYYD+TznFStclosxo3hME8UCvxPDyL7aCCAgWKdXoJ6ru4liCLn/r3NRVyTLHQMYppigdRxJXzYk3dHdImtuq67JWmiAKm6O02mEEjRteYwAAdIS5d+oSG0LmV8H9ocSIuUcul1FEk7HRZKnZAGrV5BuayC6r0zXUAKl5pUrOO2WafVJmdL1lA2n3n8DEbyP/V+LAQRKTkolmIdV1LvLUlfUipxTDzOmfE49xSLHNvpsEMmwy/jcX7TaLAm8JtYjAc9HnawLDTAdRxcTeOz3i7fOeUy6zoO50aj4Lq8vGQJgWee4eBtt2XBggUrde4MzKUGWH5DhgxZRrj5KqKFr0pP1zSNddddl7Fjx/LBBx+ssPng6mzxfT6+Sejsf3WCWtEZ1PK8PK/Xy+DBgxkxYsQ3ZtP8VZV8SikWL168zMl2zJgxjBs3jmg0uiwxGYaB1+tdxivbYIMNGDZsGG+88ca/VOg0m02uvfBCfrj99jx/331c+eGHbNNqcW40yvuaxsu5HN9ttdg+nebRSISHCgU2kJLts1luD4U4r1pFCcG5sRjTDIPtLAslBIbj4AjBh6bJGq7LWaUSISn5RSzGVvU6k3M56sCWmQwTbZunCgWmeTyMz2YZJATn1mo8bxj8MJXCJwRbOQ4VTeMdjwdNKZYIwR7NJvvUauSk5KZgkEuLRW4rFvmL38/hySTXFYv8uVRCIjB7Xkof99R7g7wOi5o6Sa+kaGmkfZKllkbCkIz12lguxE2FB1hsdedRA1YX3VafYJt0mpvCYf5WLDLRddkxneYvoRDn12oooYjrkuGe7gVnasPDZnqHz5xeW62XDOK65DNXJ6ZJPpM6mgPPFn1dlJChqNBl8S3sCKTqIpfqriKoCSpSMEq4BFDUNJ2KprGOY2OgCCDZWrN4RfhwhOBd2b3jXlNZzKFLEhjg8ekoZK8FacluReXv6dlH2210rwevUjymhSjpBls5bd40PMSBG4oFBgk4otrPxeUS30mnOSOZ5MpqlQ2V4thUitv8fg7udNCBWUJQ1DRQ3ervmEqF4VJyXSiE13F4Opdjw06HPVIpdKV4NZcjAGySyVA0DH738cf8et99ue2mm1bqPBo4NzRNW+alNHHixGWihUKPm7gysbrcdDOZDFtuuSXNZnOFMElft8388tDZlaXPr0z81yeoL6ugvoiXl0wmV6uh34rEqlZQSiny+TzTpk3j008//cIlW8MwvnDJdkDautFGGzFr1iw+/PDDf1AvDewy7bPZZrx9/fU88cknbNJus30mQ97sWkrEhWCLbJbpfj+XVyqUheC4VIoPdJ19Ox0aQvCBYWAJQUXTGO26HFitoknJpZEIB/b383Auxzwh2DWV4ge1Gk/l89wXCDA+k2FHx+Hiep0/BwLsn80yCtjOtpmlaTwQChGkS83eodVi7XabnJQ8ZppcXShwQbnMn30+To/FuKdQ4PpSiaMTCQ5Mpfh9tcqPLYsfpNMc0xOOWC5sEezwcqF7cV4zKJlVNUh4JDWna+1ecjRSpiSod6kRcU+XKl7v7SEFhEIX0O6VI0nXwScEh/f4d0e3WjSF4HGvF4XAFIphHhepoN8VrGO6zHW6FxavgLqEhCZZ4nZp4ktUV6H3TtVEGh7iuqSCQVTTaEuBRBDUdKou9BndRDJKg4rQ8CpFS8ALmo5PKfxCYx0cHjHCbCU7TDNCAKwvbObgoyoFJctll/5BLOgoLrYSBDTFEjRMukBdAxilXJboBuOE4FnXQ9GVTLCavBUKc0yzygWJFCeXy5wQi3N2PMEv63V8wINeL58YBkNcFwFsV6uRBO4PBAj25PlrWxYHJpPEevL8kFKMy2RwdZ27ikUWmCbbDxpEv65zSrPJbCG4NhRicbnM9Esu4byTT17pHaflF3uVUmywwQasvfbavP3223z44YcrdX1YneKngTlQX1/fF1qJLB9fR4vvi2Lw4MGMGjXqa3v8//oE9UUVVLvdXmYdoWkam2++OWuvvTZer/ffZvu+shVUuVzmzTffZNasWX+3ZDuQmJbfZfqyGBBPFAoF3n77beyeuu6Re+9l9002IX/uuTw9dy4VYJNsFtMwuL5c5j3D4DvZLDVN49BOhwW9hOEAmlKsIyVjm01cpbgnEODHlQo3Fgq8KwRHJBKcWyotk4xvncnwk1aLP9RqXBCNsmdfHztIyU5S8qzXy7XRKGu4LrrrslGrhaEUFaWYIQRXFwr8qFrlTz4ft4RCPJ7LcVGlwvcTCU5NJPhLqcSxlsVeqRQnpVKc0WwyCrg6FOIvPh9bWRaaUphCEtAUB6ZaPFvwoRS8VPTw57kB3u83aDjdZFR1NTIel5yj03YFQVN2aeYK6lLgRVGTXY8lD5KFHpOaEEywbRxN42NNQyjFLNPEobvH5BOKDzsGSSEZbTgsdLqfWUKTzLcNUrokJ3XSmmSp1ImbAl3rtvhCmqSumQR1iOqKBgKPgI6E0ZrEhyLsWMSUZC0kGSHwaII4iqTR9ZV639X5KTUmu93EvKlmM93W2K+ZxZRwbWUp+ymX16s6b7QE77kmMU2xqJeoBuFSVYrtO3U263SoupLT/Ek+kpKX/EGmCMFl8QQ/azSwhUB3XYzesnXEcbi+UGC4bfOjRIJhnU43EUnJhEyGuBA8Uigw1+Nh82wWSwjOqtV4xzQ5Mx6nLQSbWRZNTcNyXYQQzDIMtmy3OfWzz3j54Yc5ZJttVqnlN2DfYds2gwcPZuLEieRyOaZNm0ar1Vqhx1ldFdTyr2uttdZaZiUyffr0L0zAX3cFtXx8nSKJ/+oEFY/HKZVKy/5uWRYfffQRU6ZM+TvriOVhrv+OBLUyz1mr1ZYt2Q7MyZZfsv28YeCKRDAYZMKECQBcd9VV7DZuHMWf/YxrFyzgAdNkh0GDGCQEP+h0mGYYXB6P4wNirstIx0F3XVwpecUwOL1c5oxKhanAr6JRbs7nuatY5PxIhH1SKS7p7+eSep0fJRLslcnwQ8tiRym5ORDg/FiMTRyHgJSk221ymkbTdVkkJRcXCuzSanG738/LHg/P5nKcVK9zYCLBNeEwDxcKHGRZbJvJcH4iwSXVKkOAn8fj3O7zsZ9lIYSg4rqUdZ0moCvFz0olBsvuAlOfx2VMwGVRW+ePCwLoFoSl4qL3wzTc7nJsU0LaI8m7GkJCydJoSIHlwhJLJy4klZ66L0S3/RcUAlsIpJRM83jYpt3ml73ZnyXh6kKQVxoexukW6+oOn/WUcyndZb6jk9YleVeQ0V3yStDn0Rhk2VhuD3Ok6QQExAwoS4FHgyiSmNMmpRxmax7ihk6/UixVYPVUguM0l3lKJ6AJhtH1eoKuKGOhBT+vl9hbd5msednAarCmY3Os2+ZX7RiLHFiAQVAoqnSl9hOtFp/4/Rzj2ExothjtSOptm2sqFSpCsGmrRbpni7Juq8UruRw+Kdkqk2G06/JMPs9HHg/jsllCmsbvqlUmmyZHpVLYwK6WRc4wmGWaoBRlTWOs43Bofz81KbkuHOakSoWHCgWeNk2+m0zym1KJ62bO5Ae77sqt11+/gmdkNz5v3zHQZQmFQis8e/m61keWxyR90ZLx1zmD+ibj//47+JIYaPEVCgVmzJiBYRjEYrFlqrYviq/DE+pfxYpUUM1mkzlz5lAoFFhjjTVYf/31l4FfV8cu04svvMAtF17IZvPm8Z1mkzv8fh5OpxkuJbaUxF2XuYYBUvIR8LtSiQW6zmXhMC/5/Tyay/GpYXBcD+56R7HIR14v+6dShIXg7Hqdl/1+zo7FcIVgL8tiqmnScBxm+3yYrktZ0/hFqcSV8Th39CTjz+ZyXBIKcWAqxTCleC6f55J4nImZDMM1jRuKRS6Mx/l+KoXUNI5ptbgrEGCKYZDTNNJS4gDfqVaZ7PVySyjEpHabS0olDkyn2TOdZkvLwtV9DO1ZXXhRXP9pkBeH5dlhbopHsnl2WpwibEg6UiNpSqa5JlIq5jUNwq5EKIGtBEMNlymWF7/otoH60fhYulR1nU0cB5+SPOnx8EiPFu0Rir9W/KQMxSWBfvo0SVUOGPx1Z0+jTIeS0knoFhXNy1Ahybot3iFMWFO0EGQMSbED/ZqBIWCkDq9KL4MNnU9sSQnFC40Ce4czRJSLqcFWdo1n9BATre48wxCCotK4SCRRSrCdsmh0mrxqePm+XecOX4TvNMu8pXmZreAZI0ifBh9iEkARUd2F3kNqFb6T7OORpUvYLZMlW6+RdR0OSyY5tNXiuGqVfbNZNslm2c11OblS4dREghezWeLAgZ0Oj/h8BHw+hFLoSjEc2KrZ5FmPh3t9Pk6tVPi2ZbFXOs0LiQTXlEqMdF12Saf5rVL8stUi5LqcGo/jE4Lt63UWX345Z7/3Hj+78MKVUp4NnGcD1dB6661HIpFgxowZ/3JPyXXd1bJP9UUxgEmaN28eb7zxBqNGjWLUqFHLaDjfFK39/1VQqxher5chQ4YwduxY/vSnP60QL291ekKtaHxZBbV8O9IwDCZOnLhM9vpV6Q8Ab7zxBj/Zf38mn3gi7pw5VNttpnq9+B2HkpScViqxqWXxgq7zmq7z+NKlnFStcmIsxvWRCI8VCpzYarFTJsOZySTX9PczTil+mEpxYSTCUZ0OXuAtIXjXNEn32HcHViqkleKvfj+66/JQLscmnQ4HJpO0peS1XI7RjsP4bJbZgQC3l0o4msbu2SzTPB5OajYpCMHtgQB5XWeolPiVYt1mE0MpHgkE2KrV4sZ8HkdKDksmOaBa5dVcjrcNg80yGbZzHO4qlXjc5yOsKX7U1yU7DNIdxnssfFoXEJs0uhXCe1WTjoKYoahIjbCm+KRh0C8FYa2bkGJ6VyQRFArR21+qCw1N1/lQ13jR9HB5pcI+PfpBSkiOMet8ZBmMMZzugnBvftVnuCx2ul5LbcNPVJPUNIMMFoYQ+FT3udoIspokbVv0o+ETiq3dDrNcnaqukzZ0QsA2oQxtpQij6BgextHhcfwcqbpD7jWlxW1ugLcdk611xVsYjJY28z1+1lQuRU1nHWmT1zR+Vy/zqO3h6Y5gtjAYJSRvah7WEJKlQmNtJXnY4yXmSg5IJNml3eGeYpH7AwF2GDSIPuCHnQ4vmSY3RCJ4gJTrEleKwe12127F4+GHtRqXlkq8IQS/iEa5vFTi4UKBC6JRdk2nubBa5cpajR8lk+ydzfJ922YvKbkmFOLyaJT1XZeY64Lj0Gg0mPbooxy7xx6r1PIzTXPZzlRfXx+TJk2iWCwyderUf8qr+7pbbV+ESWo2m1/r4v83GV9LgrrmmmsYOXIkPp+PcePG8fLLL//Tn128eDEHH3wwY8aMQdM0TjrppK/8/J1Oh6uuuorNNtuMxYsXc+GFF3Lrrbeu0Pbzf8oMasDJdqAdOWHCBNZZZx10Xf9KhoEDsXDhQs485hhuOeIIZr39NvsuXEifUjxrGOSAx/J59mg2OTYe523T5IVcjr06HbbKZLg7GuX2UomRSrFvOs0fg0FOazRwgbt9Pt7TddZ2HExg02YTjxA85fcz1LK4NZ8n6zgcmUyyTrvNtFwOoRTjMxnimsb9xSKfGAZbZbP0myan1+vM0nXOj8WoC8G6joNXCITrIpTida+XPRoNflkuUwV+Go9zWrnMs7kcT3q9bJPJcEKjwT3FIleEw2zV18eOUnKiZXG7z8dJ6TQOCp+uWNvf/Qw+tcxljroDp7hHKf44N4AuIGZ0Z1F9uqTfEdSURlAovELh0k1WQdFt7/mRIATzXYeypmEIwUmxGH/1dXl343WbvXwWSf738x+wWs/okpw0e7BWeoghjYy0WCoMAgLeaZm0JQzCZm0cZts6GV0Rll3DxKIr2UV12N1qcLLVxEYwSChytssFZprFrmIw3Te7jd3gKjvEldUcGzttXtR9jFQueQQBFBqKOApXKTZzbMJCY892kyv0MK84gr94g4Rsi1MicT5RcH4kypH1Or+v1bglGORnqRQRpRjtODhAS0qklHygaRxWq/HTSoV3lOKycJhrikXuLRT4XTjM/skkV1cqXN/fzw+SSfZMpzmp0+EQx+E3sRhnx2Js6boMkpLFA5QM16UsJUf197NHs8mTpskrmsZ9S5fyg+nTOXjbbXloJR17gWWtc9u28Xq9bLHFFkSjUSZPnsySJUv+4ee/qsx8RWN5TNJrr70GfLlZ4eqM/1MV1N13381JJ53EmWeeydtvv823vvUtdt11178zK1w+Op0O6XSaM888k4022ugrP/8nn3zCmDFjuP7667n++uvx+XxssskmK21a+E06Sy6fFB3H4dNPP2Xy5MnU6/Vl9h0+n+/vDANX1TSwXC5zwWmncdQOOzD32We5/tNPWceyODaRwLRtpuZyrO04bJbJ8JnPx0PFIkoItslmmebzcVatRl4ILoxGmaPrjHMcDCHwOg4IwZteL+Msi7NLJXQpOSkW47vVKpNzOT7VdSZlMuxsWTxcKPCU38+Evj6GA79sNHjaNPlxKoVfCMa7Lp2eBF1TinmaxncbDQ6qVlkqJZeHw1xaLHJPocCdfj/7p1JcVqlwV6nEL2IxtslmOa7T4UTL4qJwmKMzGSYqxdpSslDTeMHrJSwl/VLi1RQeoYgZikUdDUdCridU8GhdtVpcU3xYNZAKokaX6p01XXyaoq0EQV0R6fkyCboWHYaAkFAIFLamU5Pdec2RjTq13jm9uWnzum1iIZYlpgGqREKTVHVPl2SuBDFN0VSQEJKy4SElBA+1IthKkXE7WEKj5ULFUV2IrKZTkrB7p8qMQJjX/QGGoPgAgw2QVBsWllTL0EaObhJCsQ4OG1ot3vMGCQws+gI+1aVbhHsAW01JflOvEtR0zuivMEX3EO64LBU6V+QLXNho8PtolPsDATxSUlCKfRoNDqhW+RC4w+fj+mKRW4tFfh8K8cN4nD+XStxYqXBoKsU+6TRnNxoc5Tj8pCd62dNxGAFMM01eN01irktbSvaoVtm00+FlXec9Ibgnn+fU/n5OicW4KxjkmXyeUxoNvp1Oc1Esxs2FAu+fdRYnHXnkSu84fd6+Y5111mGDDTZg5syZvP/++3+n8vsmxQoD0u8BVd3KKg7/E2O1/+Yuu+wyjjrqKI4++mgA/vCHP/Dkk09y7bXXcsEFF/zDz48YMYLLL78cgFtuueUrP/+IESO47LLL2HvvvdF1nWQyuVI8PtM0UUotU8J9EzEgM1+wYAFz587F7/czduzYv3OyHXhtqzpjajab3Hr55fz11lvZt1rlxWqVPTMZtshkONi2ubBc5oB0mgl9fYyXkvNqNc6LxfhxKkUD2Mq2+aAnCwaYq+vs2G6zS73OSYkEF0UinFMqMcmy2DGT4blUit/VaqzfbrNbOs214TCHWRZDbZuLQiHuDARY23Xx9hLGU37/Msr4DxoNpFJcFwox1+Phjnyehqbxg3gcEQhwb6FAVdP4fiKBD/htvc4Cj4cTevOGAzsdZhgGr+k6OY+HNVyXxUKwe38/z4ZCvKLrCODxpUu53+/nD8nwMsDr0xUvE70d3mx35wYpTTLP0cgYEtNRzOh4iBkSWwoGGRKjpWhrgpGGi9dR2ErQdgVej47huujQs/8DJQRJKbktGMIjFF4h2dzocHErjBfFfFdnTcMl1FvWjeuKutSIaJKO7OKVOlKRMCRVoTNGd3mpLvDokNJcyqYX3Ra83hFMQsMjICMlp/lSLHRcakBLCIJS8stOmf8JZVjPtXhMC7K7bHC9CJDqvda1pc0i0T3+fXQT0wiheFMzWQ/Ji4aXDVBMMTyMch2GuC7fVooJHYu9LYufZDJs22phS8mrus4txSKWEBwdjyOE4MFCgbymcXAyiUcp/tDfz2yfj0N6O21Hdjq8YRjcHwhQ1HVGOg4LdZ3xtRrNcJgpPTXkg4UCD3q9/DIaJSIELy5dyv3BINul06SE4K+FAn+Mx9k+myUA/LJW49ZgkMsiEeZZFpu+8AI/2muvVXLsXT5JZTIZJk2axPTp05kyZQobbbQRwWDwG6uglo9EIoFhGJTL5b97LV9X/J9BHVmWxZtvvskvfvGLv/v+TjvtxOTJk1fnU/3T0HWdfffdd9nfVxZ3NHC3Y9v2N3JgKaVoNBqUy2Xa7TbrrLPOMifbgcT0VZxsbdvmz9ddx5+uuoozKxUeaTbZNZ3mnkCA/WybjdptzolEeMrnIyslG9k2cz0eng4G8UhJv1J8t9Ui4ThMNgzu9Pu5sVAgoBQHJZP8LR7n9mIRUyn2TaXwAqc3mzhCcHo0ij8aZXfbZommMc0weMnrZZDrUhKCXapVZvr9zNA05uo6D+TzTPF4OC8SwSMEj+VyvOnx8N1kkoimcUupxEuhEN/NZAgoxUnNJo/5/dzl87HQ62UTy+J9w2DDRoP3YzFm6Tq66/JwLsel0Si/jEZZA3gll+PKSITtMhlGCIFUiliPwfdI2c/F8QpHLO4mqMGmy0e2SZ/hsqFwmWp58YnuRXyQ4SIc6OiCPlNitgUNYeDTBVUXspqg5HbtNEJIappG0HUIAwINV0FKV7zrmKyHwyeuwZqGS0Lv4o5GmW7XRqN3/g98TfRo4sOUDa6HOoqU2XXPzfSqrIXCIIDi5+0q1/qirKEUthAYSqF0jZiSBJTkwkaJY6IZyrrJeMdG13Se0bzsIjvYvcppmFDMwGB9t8MU3cO4ToNXTB/bteo8FAhxaKPKNdE4vy0VOCiVZYdWi4br8oDHw1O5HB8ZBockEgSE4NZSiTeCwS5XTylOarV4zufjmkiEkq4z3rZ53zDItFoEIhE+6t0s3lwsclswyPnRKHHg5VyOPwWD7JxK0ScEj+XzXJNIMKmvjwRwYX8/10Qi/DyRIGcY7Nrp8LzXS9t1UbrOZ6rr2HtGPs+pwOE77MAvLrmEnfbcc6XOL8Mwls2lPB4PW2yxBbNnz+a1115j/fXX/0YrqIFwHOcfXsvKYJJWJr7O5ASrucVXKBRwXZdszz57ILLZ7Bf2Z7+JWBXLjW/CRHD5Jdt8Po/H4/nCJVuv17tKyUlKyS3XXst3Jk4kdfHFnNHfzznhMPtls3xbSia4LtMNg1vDYVI9pd5utRoJ12Wx6/KqrnNrPs/P+vu52e/n0kiEBwsFriyXOSyR4PBUiuv6+/mxZXFIKsWRmQwndDqMUYr7fT5uDoXYyHFAKTat1UAI5gFLpOSPuRx7NptcHIkwtTffOq5eZ7dUihuiUR4oFtnZddkxm+WCeJzz6nUSSvG7cJj7vF526knGI5ZFR9NYqOsYPSn6GMfh7GgU03F4JZdjvG2zbSZDrrdYnFCKLbJZXvP7+X2lQlUImkqwps/BVbCkozPK02XpAQwxXeZYOkN1l47qmvcVnK5RYNaQJDRJw9UY6hN4HZecqxMzNJouZAzoV91TLIEkpCQFXacjBDqKtTQbR0FdCcbrFtPt7sxgsOaypEeOaMn/RQsNfI0LSVMqhrktBrsONQeSmqSuBGvpkjiKguFhtC7xSUlFCO7rz2FrOlvYLXbH4vf+GAdZdQbRldhfJ32cXy/yrVaNJ73dhd2AUtjA+q7FFN3LulaTD7wB1rM7fOQPsLnd5gOvj62tDh9pOmfGkjRdlye9Hp7N5/lZq8W3MxlOTSY5p9FgjFL8Kh7nNp+PnSwLUwgsx6Gt65QBSyl+WSoxsdPh8nCYxUrxYi7Hd5tNdk+leM3n49l8ni16Ni73hcNcVangBX6QSvGCaXJwu01HCD7SNBqahk0Xbnt0uUzWdbkiEmGIZfFMPs8w22aXdJqM4/D8woU8dNppHH/wwV9psdd1XcaMGcPYsWN5//33abfbX/tF/PMxkBRXFZP0nxRfi0ji8x+IUuob/5AGYlWJ5l/nBzmwZDt79myGDBnCuuuuu0yVtzJLtl8USinuvv12Dt9+e8yLL2ZIsciDhsF14TAbOg5KSjavVnGEYJFSLFSK25YuZe9Gg9+HQjzn9fJcLsfJtRrfSaW4LBbj3mKR/RyHXXqImnPqdQYpxaWhELf5/exo2wgg2m5T03UWC4ErJZfk82zgOFwQjdJ0XV7J5diu1WLHTIb3fD6eyedZSykmZbM8FA5zeaWCEoKfJJM8bxh8t9PBFoIlSlHXNMq6TkIpflIuE5eSiyIR1mu1eCaXI+44bJ/JMMp1eSWfp6zrbJrN0jFNri2XeU/X2T+dZomuc1CnwxJN40WfD0sI2kqwQcBmRsMko3fFCh7R3VFaw3CZZ+sMMSWLXI2RmsMrFS+agIQuiXg9dKQgKzoM0hWWVHg0hSZgbV3iRRFGYgmNutDwqa4svInGth6LD1yDJJItdYtZqiucGKbZLBJ+TMGyWejAkaDTraQEMEi5BEwTQykCQtFSinVkhzGdNu85MMLpMNnwsJey2D+UZAtp8aY/zAHNfl43vOzR6ar3NrY7JF0XH7CZ02GW3q0eRwvJVDysYzV5v6fkW6SbjFIOS6XiPd0k57rslezDVpICMDmXY3vHZZdslitCIQ7t4YvmADlNQ8muBfqxlQpjHIebeu7CT+VybNdssk8qxSJd55VcjrGuy7hMhlcCAW4pl9E0je9mMrximhzbalEVgmc8HsqaRkRKvMCutRoRpbgtGGS0ZfFAPk/Scdg3nWZ9y2JKLkdd09g4kyGm69xeKjHdNNkxm6VsWWzz/PP8cI89+Oijj1bqvPu8yi+VSjFp0iSklMycOZN6z/vrm4jP70B9HpNUrVZX23P9n6qgUqkUuq7/Q7WUy+X+oar6pmJVEtTXtQu1/JJtKpViiy22YPDgwRiGQafToVarrfSS7fLx8ksvcewee/Dx2WezdMEC4tUq/brOEsByXS7P5xnrOFwYjdIvJS/ncuzSbrNTJsNbgQBP5/NsKCVbZrPcFYnwh0oFXQhOSSR43OPhu5aFIwQFpahoGlVNI6oUJ5bLJHvoojV7CWOQ47BDJkPGcXg5l8MWgk2zWYo+H9eVy8zXdQ7MZPhE1zms3aYoBC/6fDSFQCnFMKXYuVbDVIobw2H2qtW4N5ejrhR7plLsX6/zcj7PVI+HTbNZNlWKGysVHvV62bWvj6AQfL/TYaauc1skgi4EASlZ03EY0W7jKsUjPh9HlMsI4NolIU75NMqewS4hYJDh8l7HIGtKlro6Sd0lLzU20G3uzfkxNEHSkLSEhhdFTJeYHoO8IwgK8CsIOG38SIbiUFZd+40+6dLUuiKDTU2bVy0PE7UO6wqHxap7UVlTd1jY4+It84IagLT2vhoC+oRLSWiMEPAnN4oGrOW0UB4vmhL8Ufl52xcgblnM03T60Vjiutxl+Bkku7OuCoIXNS8NYaCAPiWxeklxU7vNS5qHDoK3lM7/+NMssh12CQ+i6Upu8EXY1rKIScWUXK67zJ1K8ZxpMsK20YDdajUyUnJHMEjIcXiwUGAjy+J7qRSalEzN5RjhumyazTLP5+POUommrrNTNsvbpsmpzSY5TeNPgQB5TWOE62IKwQatFj7gsUCA9SyLWwsFgq7L4ckk2zSbTOlZx2+aybC+6/K3YpHJXi9b9fXh1TR+3mzymmFwQTSKIwTrOQ62EAQsi8Vz5nDafvutkGPv52N5ld9Akkgmk8uMTr+J+KIdKJ/Px4QJExg0aBBTp05l3rx536gQbFVjtSYoj8fDuHHjePrpp//u+08//TSTJk1anU+1wrGyRHNY/btQzWaTmTNn8uabbxIKhZg0aRLDhg0DujLUcDjM6NGjmTFjxiq1Qj/66CP+Z//9ufKYY6jPmsUJS5aQlJILIxHGtFo8m8sx2HXZLpMhLSWv5PM4msa4bJbPvF6uKZdZoGkckskwS9c5tNOhIgSveL00RNftdoSU7NJLGDeEw+xVr3NvPk9TSvZIpdivXueVXI63eiSA9aXklnKZp7xedu5dFI7odHhP17k1EkHRtSpfU0qGdjpIpXjY5+P4cpkri0U+Ao5OJPhNscjT+Tx/CgbZKpvlB60WN/b3c3kkwvZ9fYxXikNsmyc8Hi6Ox0koRdx1Geo4uFJiSckbus4vy2V+0d/PVE3j/EiEP+Xz3FMocGE0ikLwl2SJhi3YqEcWH2k6vNcxSeuSiquR0iX9SmN9j8MnbQOvqRMRkrqCtK7IORoNTUcq6EjFmprDJ8qDX4DUdFJIhuhQEhoN1TX9W0t3eNH2sq/ZRtOg09t/WsewWeR0VX2uUlgKdCWxZLd6GoC1ZpA0lGJbZfOnugcJjMRlqWEwQYd9Wg0+dOBN3ccVtTIfoLFHp8M9RpD5SlBE8LtQikNaNVI6vKt1L6gZFPPRWILgLiPIrZ4YFoIbly5lR6U4qlzhhkqZfsPgknIZP4ozIxHm6DpzNY3BvZnRUMviiGSS4ZbF67kcYWB8D5f1ULHIYtNkq2yWBabJr2o1PtJ1LoxEKIiuCaUSgkgv0U3zetnYtvldoYAmJSfG493l61yOT3SdLTIZduh0eLhQ4HG/ny36+hguBGc3Gjzm9XJqMokuBBNtm6KmUeyBaOfqOltbFqf091PqVeU/LZW475NP+N0pp3DioYd+oWPvl8VAy2/gujN69Gg23nhjZs2a9Y202f7Z3EsIwejRoxk3bhxz5szh7bffXul25hc95tcZq73Fd8opp3DTTTdxyy238MEHH3DyySczf/58jjvuOABOP/10DjvssL/7P9OnT2f69OnU63Xy+TzTp0/n/fffXy2v59/Z4lvRJVuPx8Pw4cPZeOONmT17Nh999NEK3d189tlnnHHUURyz666Me+EF7li4kKpS7J5KcWC9ziv5PJN7CWMDpbi+UuEJr5fdslm8QnBIp8NsXef2SAQAj5Ss7zgMb7dxlOIBv5+TymWuKBaZTTdhnNdLGLf1EsbRrRY3Vir8Phxmu0GDmKAUB1sWT3o8nJdIkKLrojvUcWgqhbNcwjilv59pwHmRCH/sJYwLotFlSKSrajVOSCTYpa+PI22bfR2HG4NBfpVIsL7rknBdoo7DAk1DSslc4KxSif1rNZ7Tde72+Xgol+PycplTo1FOTCS4o1Ti/HqdfZJJDs5kGNrbPxtlunQUzOx0T+y1PC6zOgZpw6UuuwmqrjQG6xLL1ci1FWUpusZ9Grxr+6krgUAw34I1pM1MxyCga+SkRljXWKIEJyiLuFB4BAzTXBYrg7W07mswhaAkBUM1yRt12D43iH5bsf3iPhbbgsWyOwNbKDU8QqFU9wTeyGogpGCerRjS4+Lt2qpR8Hg5QjqElKKo6QxDsV+rzlAhOK1e4ZBQhleFwXHtOt+tVrg3GAdgM7vNnv4Mc4SXmNC4K7eEQ22LPwVDnFgucmsszia2zVDX5aJgiIWazlNeH1s3GryYy+FKyeaZDOu6Lo8XCszs2dyj65xbqzHVMDglkaDeI9DXhaC/lzDmGAbjbZuflstYUvKbaJQjKxWez+WYoetsm8lwWKPBY4UCd4TDTOjrY6KUnN9ocHsgwFGZDFG6QOGPdZ13TBNdKfqBibbNAdUqJSm5NRjkjHKZ+/N5HjNNDkgkuLhS4cFikbOiUb6VzXJUs8k+zz7LD3bbjZkzZ67Uef/+++8zffp0Ro4cCfwvmmhFaeRfJf4V5iiRSLDllluilPpCTNJ/Uqx2eckBBxxAsVjknHPOYfHixWywwQY89thjDB8+HOgu5n5+J2qTTTZZ9uc333yTO+64g+HDhzN37tyv/HpWxfb9qyaoL3KyDQQCuK6LbdvL+tWfb+Mlk0kmTJiwLFlvuOGGX3iglUolLv/Vr3juySe5vlDgTNdl+3SaG0IhftFqsYZl8ZN4nKsiESY5DiHX5XmPh7cSCVJKdQnNlkVHKSwpeU3XubJYpCMEp8ZivBCJcH8+jw3sm0phApdXKkhN49hEgpCmcVS7TV7XuSkUQguF2Kin1ItYFh97PAgpWSAE1xSLvO3xcF0ohNB1nszleM8w+HFPEn5nocBHPh/7plJEekikKX4/Z/WQSLvZNm/TddGdGQjgcV0qmsYlpRL3hkI87PHgE4Jnly7lAZ+PY+NxYsBjhQKPh0Jsl8mQFIIrKxXujkT4YSrVddFtt3nM4+EzQ0NHMdfRCQvFtLaHw2gxzHR5pO7tUhyAiKZwNZ205uJHMLctWGR3sUKb6g6vNk1aUjFEh9csgdBUTwUnSOGglEafktys+/AJF0sJzmjGEMsdA1kh+cQ1eElF0CS80FzMT30ZdmmUONcT59JGgrimWCSNrqkgGh5gbeWQ0TWK7gDAFbay21zij3F5YTE7J/p4ORzjgXKOw5NZLqrk2dB1OFsKdnW71cH+doudiPKcJ8C9uo8YguuKOc5KpPiz18/3+ysckO7j1EaNUdLld4EgczSdtwIBfl4us1unw96ZDPf7/WznOPywVuOsWIzXvF40pdip0+GN3hK3phRlIRhv2xzU38+UZJKrw2F+3t/Prq0WO2SzPJ9KcUF/P+Msi93TaS4Ph/mBZTGm0+FX0Sg3hcOMlpIhjsMUj4d+pfBKiVSKsa7L+Hqdl2IxHvJ4uKBUYozjsE86zQPxOLcWiySlZI90GqEUZzWbeKXkxGQSH7CLbeMoxd0+H3GlcObO5XeHH84hZ5/9pSo/13WZN28ec+fOXTaD8vv9y+ZShmGw2Wab8cknnzBlyhTWWWcd1lhjjdVehTiOg6+3CP7P4sswSf9J8bXoH48//niOP/74L/y3W2+99R++93X2Qr/JGdTALtP8+fOJRqPLmH8Du0wDS7ZfNl8aALe+8847vP7662y88cbLYLaNRoOLzziDqc89x8WLFrGNafKDXsI4rt1mtmHwZ7+fTjDIxo7DPE1jRKvFjECAjusyXwhuz+d51u/nhmAQUwieyeV4zTQ5Nh4nJAR3FQq8GQiwZypFVAjOqdd5JhDgnGiUjq4vY+i1bZuZPh8e16UsBKeXy9wcifCQ10tACJ5ZupTbAgGO6VVRT+bz/C0cZptMhozo2q7/KRbj6HQaVwiObrV40OfjXSGYbpokbZvFus7h5TL5ZJK/+XxkpOTxXI7zw2EOSyRYUyleyuX4fTzO5j3J+G3FIpckEuyXyQBwUqPBbcEgj5km7+k6w22buabJtrUar6ZSzNcgJCSvd0wmeizetbq9+yGGS8HVu+6xors86zE0Mpokagj8UvGZo2MIGK1a/M0K49cVa5uKj1xF2/DS6QhqjuIITfFnCZM0cJXL60ojjsvCdjeRDcSaToO7OkGmO15G6BLLhbVdi1mayTGqxXVNPzUh2NKrk8JlLgZ+FHG6O04HSJsD9RRIhY7Ci+JdzaBJ16L9gnCMhJRs6DqcH4qxh3J4wfTS7JEihFL82hPh0cISjkj1sUDTOKJS5oRUlsOXfkafcvltIMSHCN4MBLkunyejFIek01ylFEOkZJLj8FqPoWcqhaMU412XrZtNnvd4uNfv5+xymXG2zR7pNE8lElxfKjF8gKMXDvOzVous4/CLeBwvsKXrEnJdHvH5usu5UqIpxQjHYY1Oh+cMg8m6zkW9WegRiQQPRaP8tVDABPZMpTCU4g/VKm1N44h0Gh9waKdDUdO4LhTCA6zlulSEIOC6OEBdSirAH0olquUyvzrpJF589FHOuuIKPD2WInSvX0uXLuWjjz7CNE023XRTYrHYsn9f3rFXSsmaa65JPB7nnXfeoVQqsf76669WKfqKcvgGMEmJRILp06dTLBYZO3bsv0xun3+MrzP+78Oa/kWsqu37iuL0oSvpXrRo0T9dshVCrNSSrWmabLLJJnz44YdMnTqV9dZbj5uuvJL3nn6aoz79lMWBABdEIlQMgz07HV72eDA6HT71+bBcl7ZSnF8scnE8zi2BAFng+VyOK0IhvpdKMQx4Op/nxnicb2UyZIXg6nKZq2Mxjk8maek6Rzab3O/38xEw2zCI2DaWUhxZLjM3nebuQIBhjsOj+TynxWIclEwyVkpezeX4VTzO5tksY4A7i0XOTiT4TiaDKQSn1evcGApxj8/H+7rOaNtmjmmyRaPBU34/j/r9jLFt/pjPc1QyyaHJJNvYNlPLZY5LpRifybC5UvytWOSkVIod+/qIAb+o1bgqEuG6UIg5us76lsUnHg+j2m2MUIgX/H42tiwuKRb5fibDMYkE3202mRoMMkJzeLHl5YBAi2nV7oWnz3Cpye7J59G6Xw26cu62gowHljgaupIMEi62hA4wWu9g4KMkdLIGVB3YyK7xmB7jDSUoKwFC4ziaPOMJY7uSkhIkhGKcsDilFed5ZwkX+1K8hcmadosHzTAHW1XW8fiZpyRv4qdPlyxQOoM0yWxMPMCBjX6mhdMsUIrDQllKUnFkJMmdxQJp12XHVJqEgld1k2dMH48Xl2CGY9wYjmHSbU8GEMSBoxo1LogmuaacByk5KxRlnoQPfAEeyOVY4PVyYjrNCNclJCWGUox2XUZaFk95PLxgGFxUKjHIdTkkmeTRaJQ7CwWCSrF7Oo2hFBfVamii6x/mA/a3LJpCcGswSEAphrkuLSDuOGhSUutJ5i8tlbBF1ypeGQYP5/NUheB7vUT0x3KZpR4P30mlCGoaJ7VafGwYnBuLIYAJjsN8TaOhFDVNo+O69AvBGeUynxgGfwiHEULwZC7HBz0Asgf4Wz7POw8+yD5vv83vb7uNMWPGUK1WmT17Ns1mk7XWWotBgwZ94UV7YC410EUZaLO98847TJ48mY033phIr9X+VWNld68ikQiTJk3i/fff59VXX2XDDTck07vB+3fHfzUsFr7eGdTyTrafffYZ66677t852S5vGLiyqjxN01h77bV55/XXOX633Ujceiv5QoG5UrJI15F091SO7UFXrw+FGNTp8EQuxzqW9Xduo4OUYlw2y/RgkFtLJSxN43uZDE97PBzXalHvyXUXahoJpQgD2zYaBITgnkCADdpt7sjnSbsuB6RSbNhqMS2XQ1Nd8ziPYXB/schiXefbgwYxx+PhjFqNeT0k0mc9WwRDCAI9juBUn4/NLIsLSiW8rsvx8Th71Gq8lsuRE4LxmQwbS8nDhQJvezxs0deHq+uc2WgwwzA4M5GgvzdM14TAlhKhFNM9HrZvtTi9XMaWkp/G4xxTqfByLsf7hsFWmQz7tNs8WijwaI9ova2/zYe2ybc8FiaQd7oUhgFpd8DQewKF/537rOu0qSqdiKF63xdUHRihOuguFFxYw1BkhOIjZeDTNU606ggggcv+NGm7iglYvKC6r+MDPUgYwRAk60iLN/AwHJcluslI5bBU0zm3WeHJlsHrHY3P0BmmbD7QDNK9PStLwF3lAiU0Li6XSArBAl3joGwflzTqXFgucUIozt7NrmngGbUKN2oeHtc9PJVfQgLJW7rBrq0GM3WD+wMhKkrxmNfHY7kcp3Q6HJ/JcF8ggOG6zAF+Vanws/5+HjUMrgwG+Vs+z23FIifG4xySSnFDpcJFjQbfS6XYP5Ph+HabnVyXi6NRLo5E2NRxiEmJdLuVYNt1WaIUPyuXOaxa5WHD4CGvl4dyOa4slTg+Hudn8Th/LRY5t9Fg53SaI9Npzmk02FkpTkqluCASYTfXJS4l84Rgfm9puy4lP6hU2KnZ5FHT5E0heDCX49eVCj+Kx7kmEuHxQoHTGw2+ncnws2SSq/r7+bbrcmAqxYXBIHt89hkXHXooN199Na+//jrxeJwtt9ySwYMH/8uKYnnHXk3TGD9+PEOGDGHq1KlfakC4MrEqVhvLO+TOmDGDWbNmrRAm6f9VUF8xEokE9Xody7L+riz/svhXCUopRaFQYM6cObiuy6hRo8hms8voD0KIr0R/kFLywtNPc9tFF+HOn09SSraq1XjINPljKMQhtRrH1Ot8N5tl71SKE+t1Dm402CWTYdNslu86DieXShybSrFTXx+DlOK4Vos/B4PcGI1SBwZLialpDOl0EIEAj/n9HFarsV+zyYHpND9IJDirXGbXdptte0ikEzoddqjXOTCV4gG/nwlK8d1mk8vDYT5KpRBCsIlts9Q0mWsYaErxia6zV6vFt5pNTk4k+G00yvmlEpt3OuyUzfJMKsX59TqbtNvslU5zczDIPq7L+u02F4XDPO31EleKdRyHomEws8fmmy8EBzUabNjpcFo8zh/CYa4oFhnjOOyUyXB/KsXl/f2MtG32TqX4XTTK9y2LNWyb34VC/CUYZJSUfCoEu/k7vNT2omkwVHP4wDJIG9YyckPao5hjGyQNxXypYSD5vtbkD+0oI/3QaENI08g7ioRwSZs6cxzFvrqF4Sju1IOEpeQKM0RUKHwoliAYrUmOsKpcZibZRTV52PYS6z3n2laL+8wwx9gNygr6eoq9daVNUujMdTViwsN2ssN7wmADafOS4WU4ElN1FX4BpfhLMcdO8RRbWzbbt5ockslykGXxt0CY/TpNzoinGetILMNAA35aKXNuIs32zTot6XKZL8jDS5dySSrFeYkEWdsmLyVLdJ1n8nlmGwbHxOP4heCeQoH3/H52TqcJC8Fv6nVe9fv5RTKJA+xs27yj6xSEYKGuIxyHmqZxfLnMS34/d/j9GELw1NKlvOL1cmw8TrBHiXglEGDbTIaIEFze38+joRCHpdMIITik3eYFj4dphsH7hkHccViq6+zX348Ih3ncNPEBj+dyPOj3c3xvTvlcPs/DoRDfymZJAH8qlfhLLMZemQy6EPyk2eQ+v597AwHe93oZZVnMAcbXaszSNG6/7DK23m03vnXppSuVEAZuVgdmUyNHjiQejzNjxgyKxSIbbLDBVwK9fhWrjSFDhhCLxZgxY8Y3gkn6V/Ffn6Di8a4yqVKprHDZ+mUzqHK5zCeffEK73WbEiBHL8CEDNPKBPYhVZea99cYbXHXmmcz5+GN+Uy6zlm1zUCrFD+NxbiiVWMtx2DaT4c+BAL9otVir3eboZJIbIhEmOg5DbJuHfD7eTSYJKYVfSoYqRZ3uCTFN1zmrXCYtJcfH4/w6GuVP+TwZKdkpk+GmYJBLajWyts0hySS/BfazLGKuyx/9fu71+xndq1Y6QvCaz4dXSpYoxQnVKi5wZSTCXT4ftxWLSKX4fjLJX3w+7iwWEUqxX6+l87NeG/XsaJRANMrWjkMNmK3rfBQMEpWSOvD9apWqpnFLKMQcj4e783nqQnB4IoEIBLi7UMASggOSSfzAmc0mNV3nZ70Zxk62zVJNY4ZhMM00SbpuV0FWrfJsLIahKdI9u4zNPDZvtky2DljEPDplBwYbkg+trkDiE8fEowlGSZelFqwfkCyWBh4NInrXKqMtBBHVE8SYPmJKYCmoKjAQjDXgTiLs4tTZEIdPXY0btRg7Oi1m6D6KwHAcFusmfru7lCsALxBHoYCbK3kOCyexDYHu0dm3U+UJj5/dWw1uDYU5o1zk1EQaC/hhu8ULHi/bpbJs5Ep+Ximzg8fDbpEUBzgOvywVOSCd5UXTg6EU812X100fT+XzHJnO8LLXy4aNBpeGwoQ1jWfzeZ4KBvlWz/H28kqF+yIRjk6ncYTg4HabZ71eZmoaHxkGQcehoOscWqlwRzTKgx4PwV4L7S6/n2MSCZJ0E8bfwmG2zGZJC8Efi0X+FIuxbyYDQnB8L2E85vXyjmkyzLaZp+tsU68zJx7nGY+HsJQ8ks9zXTDIj+JxBtFFW90aibBlJsPgXiK9JpFgx2y2i+aq17k1FOKacJjZhsHGts27psnIVouo38/rpknAdbmuUOC3kQinxOMMl5LJS5Zw+f33s8/kyVz/wAOrxPIbaPnFYrF/aPmtiPvCF8VXNSsMBoPLMEmTJ09m/fXX/6eYpP9XQX3F8Hq9BIPBlUpQX7QHVa1WmTNnDtVqlWHDhjF06FCE6LqkKqW+smHghx9+yEUnncTHH37Iw0uXdkGaiQReIbi6UqFqGByVSBDsCQoWmiZ/DASQwSAb9WCogzodPvH5UK7LXCG4qVhkumlyRTiM8vt5KpfjY8Pg6J6C7rbeLsqBPQXdL5pNPvJ4ODfaXfrc0baZrWmUpeQtn4+olPQLwZmVCi8GAjzi8aB0nSdyOV72evlNj6H3SD7PO6bJgYkEISG4vlzmbb+fg1IpgkLw41aLVz0eHvD5KOo66zkOn2oaW1SrvBQO855SyN7jPOH18rtwGJ8QPJHLMdXrZZ8em++GcpmXQyEOzmTwAj9qt3ne4+EJj4eFHg9rOQ7zdJ1tazWeCIeZqmkI4LFcjvv9fs4Lh0lpLm9bJpt7umq27X0dzquHgQbDTJcZHQ+DtA5zLYMhpsu8lk5KV7QVtFyY2RAkpY4pIIWigIZCMdaAu2WQjK5zpF1nujL5RPOgkOwm2vxFhDjDqQCQFPCXjpfXrCWcF0jzAj72oE251+0xlUICERRFuk69o6RLBJ2GK/hUKcYLg3mmj582q1wdCaIbcQpSsoVj85NKhY9TaXJCME/XaQG/jCVZz3H4SO9eAn5TKvC9eJI1heCKcpmfJ5J0hODo/gq/ikQZrhQPFwpcnEyySzaLEIITGg3uDgR43jSZZRj02TYLDIPdq1U+SiZ5yOcj5bo8ks9zUTjMUYkEI5Vici7HVdEom2cyDBOCu4tFLonH2SmbxQP8vF7nllCIW4JB3jUM1rNt3jdN1m82ea7nqBxzXW7O5/l1LMYJ8ThjpGRqocBFsRhbZjKMBh4pFDgvlWKrbJaYEJzb389V0SjnRSJ8Yhh8q9PhNa+XkG1jCsEHhkFAKS4uFDgtmeQXsRjrOQ6vFgr8Ohpl60yGDaXk2XyeM5NJNstm6QPO+vRTztpvP3Y98UT2P+SQlTrvB8wQLctC13XGjRvH3LlzmTZtGmuttRbDhw9fqSQw0MX5qlYbA5ikZDLJu+++S7FYZN111/3GuYL/9TMoWPk51PItvkajwcyZM3nrrbcIhUJMnDiRYcOGoZRaLYaBixYt4qg99+SX++zDxa+8wg9aLXZJp/lJKsUFjQbrK8W5kQjnRiLsbdv4AMO2eV/XUa5LQynOKxTY2La50+djNl0X2uOqVQ5PJLg9HOaxQoEftttsk8lwejLJVdUqGyvFj5NJfh2LcYRl4Qc+kZLJHg8px6HTE0QMlpJnPB4KwMO5HPs0GpwcizHN4+H5XI4jm022S6e5Phrlb8Ui2/fUWOf3GHpZ4KJolNsDAXbpdBBK4el0qOg6eaCjFJcWCmzqOFwcjTJfCF7O5fhes8lOqRR/jUR4qFDg267LDpkMF8di/KbRIKYU1wSDPOTxMKm3bDi62UQIwfu6jiUlN+TzfKvd5pfRKAuE4JVcjgObTbbLZHg4EsEUiqwueanlZS9/N0Gt43FYIg0aUrCoA4/UgwzWLBa6JoOExXxXZ7AhmSMNYprOzLbOEmHgQ/E9t8Ff3K753k5OAylhqSvZr1PlaWEQUpI1BEx0GiipSPZ8mDZw2gyTLgawUafBVN2Hl/+dgWWEYh4aawuX1zQv6+PyouFlDSE5r1TAg2CaCLDAcTk8kqHjKppti6m5paAbbJbJEkLxYj7HZh2LzVNZjmw2uKuQR1OKH0eiHJ3MsK3jYgqNLS2Ln1T72SmV5o+RKNdUKjQ0jd+Gw7xlGKznOAhgXKtFFHjC7yfiOPwln2fjdpsfJJMYjsO0XI6Ne9YtH/r9PFgoEBSCrfv6eNLv5+xajboQ/C4U4j1dZ3PLQgpBxrLwCMHbvUR0RaHAWrbNSfE4KcvitVyO9W2bLTMZqqbJ04UCPk1j82yWKV4vv+vvp6RpnBqP846us5tl0RKCBiCFYKFpEleKM0olhjoOZ0WjDGu3eSmXY3Snw7d7Nzwv5vMYwKbZLB96vVxdqfCZYXB4KsV7hsGB7TYVIfhA11lSKvHwOedw3sknrxLLb/lENXz4cMaPH8/cuXNXepl24IZ5dSWSrxOTtCLx/4sEFYvFKJVKK/zzpmniui4ffPABr7/++tfiZFssFjnhkEO4YM89+Z9XXkG125yQSHCn38+hnQ6OEMxXigW92YC/J4jIKMUNoRBp2+bxfJ5NOx32SqWoC8GruRzrSclm2SxPRyLcWirhE4KD0mnu9Pv5catFRwheMAxm6zp9rtvll1WrhIAHAgEylsXd+TzrWhaHJ5P4XZepuRzrOQ4Tslk+8ft5uFAgDGzT18cTwSAXVau0heCniQQvGwb7WhaWEHwqBBVN63oIKcXh1SoRpbgmHGZwT9AxtMf405Xi5VyOODAhm+XNQICrKxVaQvCjZJLJhsF3eo9bc11amsZCwyAhJWcXiwxxXc6IRhnS6fBqLsfats23MhmahsEz+TwhIdgim+XlQIDfVyrUhEBqAq9QfGgZdPjfu9SW0th5YYZA2+XlmslFhQh5ZZLRHAqalyHCYY4yCOmQMaGkeVjDUKSVy0cWtJVijNsho2tUpWIv3yBcICUUXk3jfUzGat0bIAm8iBfVs7ZYR1rMMbtrBQP+S2sJlzeEl/WcNm/pJpt2Grxs+tjBanGXL8h3HJuNmg2OsS3G2TaPFfJM9/u4w+fnXV1nU9flLcPkQa+XR71e9rZt/hIIUgWqQuMVj4+Ty2UuLxUZbttsmcnyx1CYHzWb5HSdkhBITeNtr5eRrsvlhQJ9jsNx8TgbtFpMzeWISMn4TIaApvF4oUDJNNkim+Uj0+S31Sqfahq/iMWYo2lsY1m0hUDJrpnjhx4Pw6Xk7FKJpOPw81iMcY0GL+dyRFyXSZkMa0jJ8/k8RcNgfDZLzjT5Q6XCbF3n6GSSuZrGvp0OpR4Z3+kde31KcWx/PzEpuSQcZrMeiivcYzeuZ9u8kstRMk02yWZxTJMby2XeMwz2TadZoOsc2W6zSNd50TRpC4EHiArB3vU6QaW4JRRiXKvFPQsXMufBB9l/yy1XybHXMAyEENi2vcyAEFipZdqBzs/qrHT+GSZJCPF/jyTxnxgrU0ENLNkCf+dkO9D2+6pOttVqlfN//nN+seuubPTii3xYrfK030+191ijpGSbeh1P78Dfo1rlrnweTUr2SqXYudFgSi7Hgh4MNSoEfymVeNc02aWvjwWGwQnNJnM1jVtDIUpCkHVdUsBa7TYG8FAgwI6NBlcXCpiuy/eTSfap1Ziay7FUCMZlMqwLPFQo8K7Hw8S+PuqGwW+qVd41DH6SSpHXNHbpdKgJwVseD5YQdIBRSrFVo4GmFLcHg+zcaHBDsUhLKQ5OJvlOvc7knnx3fK9lckepxOseDzsMGkRH0/hhq8U8TePuYJAO3T70AJvPkJIrIhH2qtV4LJejqRTbZzJs127zYj7PBz02n1fXuby/nzcNg0PTaZZqGvt1OhR0nde9XjpC0EBjZs8998Z6V0lXlYKGozhLljjNU2O4qfN9t86cFiR1lxIGg2WbBRjENMUwx6GsBMM1hxaCjhJ8aEMRjRZwtVXDp8Gp7SqjUMx3FecQYU7PQPdJPcAoISkLgQJGKYdir7U3TOvaXKxtt3hHMxjttJnjC7K+Y/GRP8BW7QZvhoIcWKvwaDjKUf0VXjcNFmsaIQVXhsOcXipxbe9zPicS5YpCnnPLJeKOzbfTGQ6v13kqn+eKWIwfxRNM0XWGuy5Zpdi70SAgJb+KRtmvWuWVXI4iMDGT4Vu2zZOFAtN8PjbroawurFZ51TT5UTJJRQh2sm0qmsZndL2wFhsG60nJjysVTCk5Pxpl71qN53I5KsC2mQw7ttu8kM/zus/HptksKU3jyv5+XvB4ODCdpqZpHNDpMF/TmOrx4AqBA6yhFPv2UFzXhULsVq/zcD5P03XZPZViz2aTl3M5Zng8bJzNMgK4tVTiWZ+PPfr6aAnBsa0WM3Wdv/n9XXm7lMSEYGKjgaEUfwsG2bbZ5C/5PI7rcmAyyX71Oq/mcswyDDbJZNjQtrl29mzO+M53+OP116/09WFgTGD1iP0bbbQRI0aM4I033mDOnDn/UuXnOM5XGjX8s/g6MEkrEv8vQfVieSfbZrMJwJprrrnMyRb4Sk62rVaLP119NT/eaSem//WvrPvZZ6TabVwpecjr5axikT8Ui7ynFEcnEly0HFJoy0yGQzodbq5UuCYcZttBg1hHCI6wLF72ejkvHsejFEnXZZTj4EgJSvGqx8NJlQpnViosUIpTYjEuyud5Lp/nPr+fbbJZfthsck+xyFWhEBOzWcYrxWntNvd5vfwokyECjHMcmj1BhK4UZWCnVouNWi1aUvI3n4/TSyUuLpd5TylOisW4sFTi4Xyeu/x+dk6l+Gm9zj3FIleGQkzq62NXx+G0Vou/eb38TzpNRinWsW1MYKmmgZRMM02OqlY5t1xmNvDDRILflEo802PzbZ7Nsp9lcVV/P7cEg+zZ10cfsE/PU+j+UAgdcIHNbJtNegZ6d/v9HF8u40WRFS5HeZpMtzzYCv7QTjJYKN4TXoYJl5IUHKU1qTqCh1phqhKyukve8DFCU2zhtMhbkmGyzadCI63rJDSYiUlcKDaxmoySLtf6IsyQgos6VUKajiEMntIDXC0i/KZWICwEc9HxAkbvGjQgNR/hWizwBBipum61a/aS2JrSpV/CECnxKMmbuoFPSg5KJDmxVuP+YpFz43E2y2TY0bK4pVLhhFSanfoGYQqNQxyHG8JhXjFNHOBNw+DH/f3cUijwqRDsmkpxQq3Gk4UCt4fDjO/rY5yUXFivc4ffz2GZDP5eIpqr67zt8SCAqhCMs232r1bpSMk1kQg/qlR4JJfjPSHYI5Xix9Uqz+Tz/DUQYFw2y9auy9X9/dweCrFPNksEOKDT4U3D4DG/H0F3FjdMSr7VaCCl5O5AgEP7+7kzn2cecGAyyU/6+3kxn+dRv5/x2Sy7Og63lUr8ORhkp0GDSAnBce02L5om10ejXUCu6+IHRnU6KCl51ufjO60W1xUKFJTih4kEJ/RWFV70etkik2Efy+KvxSJ3hMNs3dfHEE3jZ80mj3g8nBOLUSmX+fCyyzj/lFNWueU3ME8aNmwYEyZMYMGCBbz55ptf+nhft//UwP4WwOuvv/61A2f/60US8OUJavkl20AgsGzJ9uWXX6bT6eD1er+Sk63rujx8773cedllLC0UuCeX4wPT5MxoFM3j4bF8niWaxiGJBL6eIqpqGMsIET9ot1mo69wZCCADAdZzXXJCMLLdZr7Hg5SSjzSNm4pF5ug650WjvBAM8lguR1HTODCRwBSCG8pl2rrOUckkQSH4UY8g/vtgEE84zHjXpUjXk+dFnw+/lBTp7rh8aprcGgjwiWny13yeBZrGSfE4eL08lM9T1DQOTSQwgZsqFZpCdKXHwC+bTaq6zpnhMMFIhO/YNp8JwVTTZLLHw2DHoSIE32k2WWyaPKlpfODxcEehQEnXOS4WQxOCm8pl2j3UUlDTOLhXvd3r9/O4388gKWkrxdhOB5SiZpq8rOtcVyyiK8UPEgkeicW4N5/HUIpd0mmiKFK4fMu0eEOa/LUV4JmmyW/0IneLKCFRRyqFKSCh6zxe0zE1yGguZaUxiQYVBLaEllR8ZgZJKknSdnnB8LMZNg8ZfoLSQVMGMU1gK8VWyuHkWpHdQhn6NMFQJBt2Gkw1/Ix06sRR5NFYy2ryhBFkH6dNXuik6b5HD90TVwExJbk6GKZfKY6OJ7miv5/5Ph8XRqMMkZKMUviBObpO0+fD6P2edq9W2cC2uTeZ5NxolLvzeVJSsn0mw0XRKD9pt+nreWsFo1HWlpKE6/K2aVL3+/FK2X0vlsWmrRbPxWLc6/NxQanEWMdh91SKpxIJriuVGOW67JxO87twmJPabUZZFqfGYlwKbOC6DLVtnvJ6+TQcxqcUISkZKiVrt9s86PHwtMfDaZUKW1kWe6fTTI3HubpcZn3bZodMhmvDYX7RarFuu80PEwkujsWY4LqM6XS4c0CFpxQp10XXNIK2jVSKt3SdI+p1dmk2OSD1/7H3l/FWlevbN/69Rs3uWAtFBDtQsbEbbMRuEbsVWxE7UbGxsLGwc9ut2wYMVMQW1prdMer6v5hD/vsX9+/e6t77ue/n2ecbPk7mGnOxXOO6xnWex/E90pweizG1XGYDy2LzbJZ7/X7ObTZZvd3mgEyGK4CtHYfVul1uCIV4wecjLCUrOw45XacmJYqU/KAobNtus0ejwcFPPcXs99/n6gcf/N0qv9/WJ8uyFkOmP//8c9555x3WWGMNksnkf/m6P6vg+3vKMAzWXHNNut3uv1V8/4j672LfpZQMDAzw/fffo6rqYsXKb08t0WiUBQsWMGrUqD+0OUkpee2ll5h25pkEq1UeWbSIh4JBdkmnGSIETxQKPBKLMTaTISoEF9brPBgOc3UkQl7X2c40eU/XiXU6vBmP0/XmLncVCtwcjXKf308MeMWLLT8omSQlexHYL4fDbJPJkBCCqbUaT4TDnBGP01FVdu92eUvXKdk274XDxFyXopScWCxybyzGy5qGT/RQRY8GApwVixGlhyp6PRBgXCpFUggeLBZ5PRxme+9zrqzVeCkU4phkElUIjm21eNnv5wGfj6Kus4Vp8qmuY3S7DHgZQFUhuKlc5u5IhNuDQXQheCmX47FAgL1SKYJCcFu5zIuRCEemUviA3U2T9zSNpuMwPxDAcRwWCsE9hQJv+nzcHA6jedf5XNc5OJHoJbkWi8wPBNglnSYiBEtbFnWfQhWFVRSLU40GO5bTnG9UWU5xWEhPBWV4959fSE41y5ymxskqLjUpGS67PK6FCaDwoB0hqCqs7VpkzRY3+8J8KxU0f5RNcdndbCN8Bg+EElxZz5HGxZSwfaeXE7SL1eKOcJK97QYjcXiNXubUB1LnSCPLgGWzvX8IVcdlbHgIg47LJrF+AlJytxHkoXyem5IpnoxEWMI06bguXwN3FYtUhOD4RAJUlZdzOdpCMDaTQZc9gHBF09g7myUA7GhZVITg2UCAgJQkXZcusE6rhe724tsXqiq3lUoYrssBqRQP+3w8WiigATt67MaLGw1U4GjPUrCjZSGBB4JB4h62SkpJv+MQtyxaus4nisIl5TJZx+HgVIrXolEeKBaJS8mYTAYFmFarEXJdjkileinOlkXQdZkeCpEMBllSSjTve267Lq7r8i1wbL3OyqbJ4akUc8Jhbi8UGOY4llKVvAABAABJREFUbJXNclMwyPXVKlnHYd9UCkUI9jFNMo7D1EiERCTCMNcl7rosUFVCioLiuhSkZHynw0btNscmk9weCnFVucwoy2KrTIaHfD5uKJUYnstx4A47sNvRRzPRg2b/vfXb2mPbNoqisPrqq/Prr7/y8ccfM2LECJZddtn/sEn8qxJ8hRAEPaP7P7P+P7FBJZPJxeDZv9dku8Yaa/Dll1/ywQcfMGrUKCKRyN/9eR9/+CEXHHMMa5XLPLpoESel02zU18fSQnBtqcRFySQnJxIM6Dq7dzo87/dTdxzyioImJWEpObVU4ngPkrlWt8sjpRInx+Nsn06znuvyVj7P5FSK9fv6WAa4tVTi4mSSw1Ip6orCoZ0ODweDzBOCrzWNpGVhuy4Hlct85UW+L+s4PJzPc0YsxgGpFKu5Lm/nclyeSLBBNssKQvBYocBlySRjslniQnB5tcoN0SinJBJUNI1DWy0eDQR4VtOYrWmsb5p8ZBjYlkXZ8zKBZId6na9TKZ4JBIi6LvcV8hyfSnFoMslw6fJ2PsdJySSbZrMsCdxYLnN1IsHkeJy2F4nwV8NgnUaDr+JxnvX5iEnJC7kc14bD7JNK0S8lLxYK3BOLsYkHib2iWuWeaJTJ8Thl7+f9jmHwtaExCouG6FEjhqsOceFwgNpCAjW7h4yICZe8ozBElQzHIexKPnF82AiWFA4DisaqQvKRq2AJGGU2eNkIsrSqcEi1zEWhKFu0a0yLJLmnPshfwllWlDYvKj6WQ/KKEeJIs87arsWZXvpu2OpynhplNSFwJNydG+D4VB/HFfJ8GgjzvSI4pF7j0HQfLw8s5IRMhifCEdZqNLgqEkHz+3kll+MLVWWvZJKIEDxUKPBZMMimfX0EpeS0Vou3/X4uSyRoKQqreqzG5Vst5vt8fCQEjhA8lM/zja5zZiyG4nmXflZVDvBO/LeWy/zo87FbJkPAO5l/rWncGIngCsGqjsOAEMQsi6Km0fDYjTcUi5RVlTNjMQgEeDaXo6oo7J5Oo0vJXaUSZU1jT4+bd2yrRU7TOD8exweMchwqQEkIyqoKrssgcFalggacE4vxod/Pw4UCipTs4hnJZxaL2IrC/qkUOjCp08EWgjOSSQLAuo5DV0rm6DpJRcHv9gzSu7TbLGmaXBCP851hcFupRNpx2DmT4S6/n5nFIkEpGZdOowGnttsEXJdJnol5jXqdwWuv5cKvvuK0yy/H5/P93evJb5vUb8rhoUOHEo/HmT17NuVymdVXX33x9f4REvO/t/4VYNn/T82gnn32WV544YXFSbajR48mm83iOA6O46Bp2uIkW1VVGTlyJEsssQQffvgh+Xz+f/s5c+bMYZ8xY3hpwgTOXrCAN6XkgGyWQVVlJ9OkKgQf+Hx0hKCmKIyyLHb2BrvXRKPsWa3ypBdXsE0mw9btNu/mcvziKYw0XWdGucyXmsa4bJavNY1D220GFYVnAwGKikIQGAJs3Gzic13uDYXYpNHgvnyeuOOwWybDBp0OH+RyuMCobBah6zxWLDKoqmzR389sn48p9Tq/KgrnxePMU1XGmiZdIVggBHWlR8yOAau02wgh+NTvZ2nHYUK1iiEl94TDrNjtMrVURHVlz1PSbvN0oYAlJWPTPY7bq4U8g0Jhg0yWjqJyebVKVQguiccpKApLub2k1PG1GhEpOS8WI2ZZfJDLsbQX/T0nGGRmqYRPUdgzk+EJn49DOh1MIfhWiN5MSwg012WXWq03hEYQEZLV1F4//wkZQaDwk1RRBfi8e29ZVfKx1FlOcfgYnaGq4Px6DFXAksKhIhTWsNss3e1SsCUrSYsfDD+7mk3e9Qd4tl7gslCCruNyjhFjJ48efmUoxRX1AkUhqCBQAIngBH+Gl9UgfSg8VBxgTSRfajoH1avcEE+yb73KW4af4Y7D2rbFraEQm9fq3OvzcU8kwrOFAnvYNpv09XFKOs1FzSZDgcmJBNNCIbYxezgn3TRpA4NSUnNdrioU2LfR4NpwmLc8C8F5tRrj0mkujsd5tFjkyG6XLbNZjkmnObfVYqSUXJRIcGM4zGa2jV9KME0aQtBwXUquy+RikT3rdR70+XhN0/hLLsfUcplDk0nOjcd5rFjkvFaLrbNZJmQyXNhsMsZ1OSGd5tx4nDG2TVpKflJVFqgqmm1Tc10mVCrs0GzyhqLwuqrySC7HtaUSZ8VinB2P83ihwA3e979nJsOlzSYHWxYT02mOTSbZybZZUUre9vl4w+cj5jiYrstmjQYbN5t8JSXvqCq3FgpcXypxUyDA5HicWfk895ZK7J9MMi6T4fJ6nbM6HQ7KZNg/m2W847Cx6/JwKMSsUIg+18VwHJbqdlmqVOKNp5/m4LFj/5DKT1XVxSq/YDDIhhtuiGEYvPPOOxQKBeBfd4L6V9X/e/4l/0OVSiW+//57Dj30UKZOnco222zzd5lshRAsu+yyhEIhPvvsM5ZbbrnFQYN/W19++SW3X3op/s8+Y1ilwnxFoRCJ4HddGlKyT6tFzAvVeygQYLpHbtg1k+GtVIrbSiVG2DZbZzLcGolwVLfLip0OJyUS3BMOs7zjsIlt84bPRyWRQKUnQV7dtkl5/fRn/H6mlMusaZrsmclwSDLJdaUSa3n99CcDAU7odNiw2eSAdJoHPYPvDp0Ot4dC/JJKLU4WrWsaCxUFpOR7VWVrD3H0mmFwVzjM8ZUKm3S77J/JcFo8zuRymQ1Mk/GZDAcnk5xbqbCuZTIulWb3VJqz63XWNbvskkrzUibDpFaL0e0Wu6XTPJ/p3dQrdztcEY7wYzxO0HUJuy5RIdiq2eTGaJQTEgkOajQ4pNlkm0yGtfr62FRKLqzVuDge55J4nJIQLGPbFHWd9VstngoEuCscZutWi/OqVfbJZDgklWINs8uPhkYNwZ5ab4N60AyygWIyRxoMp01YSKouLC86zJE6y9stPhYGqysO71qCbxBEAj0D7WpOl7d1P4rrMkcLUpaS7TsN7owNId+uI4GxnRZPGAF+VAUZ1c+S0mEZ12H9bodn/BF27dSxbJsfXclz1QF2TPZTBvZsVLk9muDmUo7zlARBJBu7Nvf5A6zSbHBdKMJKXgtzcirFpHicnwyDbbtd3vT5wLZ7HiAh0KRkSqnEhYkEl8diDHdd3sznmR4OMzadZjjwQqHA9ESCDfr6SArBVZUKt8ZiTEokKOo647pdXjMMqo5DRVVpOQ6Wd+K/JRplRihEkp4X78FgkL1TKTL0WsRPRqNs6F33+kqFB6JRDk6nMRWF/f6GPvG1rhPx6BP7VCo8HQ7zrGFgiB4G6RWfjxPicSLAi/k87wUCbJHNEvNOdC9HIuzu4YoO7nR42zB42u/nV01jKcdhkaKwXqOBPxDgWQ9/9lihwJeaxmnxOLromcLn6zrj02mC9GarnwcC7JLN4heCwzsdPtd1bo1EMBWF5bzZcKbbRVVVPhICWwhuKZWoC8GJiQSSHm6pms+z7zbbcMyZZ7L3QQf9rrXsb8noiqIwcuRIFi1axKeffsrw4cMX8z//FfWvOEEJ+U+UYdx0001MnTqVRYsWseqqq3LNNdewySab/C/f/8YbbzBp0iS++OILllhiCU477bTFQYd/pL7++msmT57MM888w5AhQ3jppZdIp9N/iP5QqVSYM2cOfX19rLDCCiiKQrFYZPqFF/Lr66/zbb3OJaUSL4VCvKTrIAR/GRzkXZ+PybEYPiF4Mp/nJ0Xh4FSKMHB5tcpCn4+pgQBBIdip2+U7VaWiKLQUBb/jUBSCAxsNvjMMXjYMLCm5v1jkF03jlFgMKXrEhZYQ7JJO4wOurlYRwDHRKCFFYbznq3rV5yMABN1erPdqjoMrJW/oOo6UnF+t4gDnxePYUjKzWEQHdkulAHigVCLsuuzgzQNurlSI2za7e22Nq+o14rbNQYkkGnBFvY7mOhwfjaEqgosbDbpIpoQi6MAxZpeGENxhGESFwoqOQxmIAiHH5hNVwwQuqlUZajvs482hxjsOMcdhlt/P8rbNAlVFcV22MU12bjQ4PJWiIyXnVats4z31t4BjTZNx1SrbZLOoqiSGwwOhMh0ER1l9HGMXedcX5RLynEmWzewqfiF5UMY4zK1wjZJivFXjXcfgKdXP275BDnD7eaAzwD7GENa3ujwnNDpCMLc+wE6RPkpS4a5qnrtDUYYgWbfV4KhwgltaZdZzLHIoTIhn0ZFs3G7xQjDCy4WFTI/EqdoOJ7XrjE0N4fXCIiYls2xaq/JXn58XdR8bAzvUalyYSHB4pcLd8TjCcYgJwZ2DgxyeyTBfCDY0Ta6vVJiUSPC6rrOx63Jpscip6TR/VRSGSclplQoXJpP4HIeSprFju81TgQATKxUeSCTwWRYdVeX+wUHOSKeZIwTLuS4PFQpcGInwRCDASq7LbYUCVyaTPKbrLAVcUCpxZTLJINBVFPZpNnk4GGRMo8Fr0SgJy2KRpnFLLse1ySQfC0EKeDaXY3o4zJ3BIEsAs3I5HoxEmObR+a8rFpkRj/O2pqELwcHNJo8EAixrWXzt9zPENPlW0zi/XObxcJiPVRVNCJ4aHOTpQIBrIxEi3j36ht/PadEoUSG4s1DghViMGT4fASk5qtnkhUAAEyirKsNtm29UlQPrdeYEAnyqKFhCcHehwGe6zqXRKKoQvJLLMU9VOdRrhc70OIXnBIMEFYUTWy3mJRK0ttySM6644nfPc35bw6DneWo2m8yZMwfLsshms6y66qq/63p/pP4Mb/TvrX9ai++hhx7ixBNP5Oyzz+bTTz9lk002YbvttvsvYYW/1ffff8/222/PJptswqeffspZZ53F8ccfz6OPPvqHPn/WrFmMGjWKdDrNk08+SbVaJZlM/mGTbTweZ7311qNUKjF79mwsy+KRe+6h8uyz3Dl/Plu2WkyKx5mvabyZy3FQu80W2Sy3xOPMKhbZwnHYKZvllHSayc0maeC+YJBbg0E2sG2klIxqNGgoCr9KScV1uTOXY7tWi+tDId7TdV4dHOTMWo3dUykujMd5uFjk6G6X7Tya87nNJqu7LtMiEaYkEmztugSkJN7tMs8jTxRcl8vyebZqtXheVXlF13lhcJCLKxVOi8W4MB7n0UKBq6tVdk+nOSCT4YZqlZO7XfZKpdgrm+XsVos9bJvjEgkmZrNM6nTYznE4Mxbn+FSK073/Pj0S4ZxEggvaLbZyHM4JhbkyHOWCVoO1pMtNPj8P+/wcZJokpcsvQENVGUDyoaZxebXCTu02Z0VjHJROMaXdYozr8Jqu84rHAPxSCM4ulzm/XGaWYbBfMsm0cpl7ymXOjsfZrL+fHR2Hk7tdbg4E2Ka/n6aUBHBpovIzOveSYA+7zJaiy2d274ZbRbb5yNUZJhwGld6fBRSWkya/GAG2weFEJ00ASZBeOOEO7RrLIYm4LuuF+6lLUJAEXId3NYMjamU+1X1kgPvCPUZkHJec6zKq3ebUZp2g6zKAwk7NGq+HIviApaTLu5qB4thMCcfoFyondjrMU1VGWBZBKbk2EmGnep0Xczmk67JZNsv63S5v5fP87POxVl8fHV3n5nKZzzSNvTIZvlFV9u90KKgqn2gaDXrKwJSU7F2rkZCSGyMRRrbbPJXPs7RlsV0mQ5/j8NdcjjiwpmfevrdUoqGq7NzXxxuGwfGtFmVF4Wmfj18UhSUcBx3YrNUiCTwWDJKwbR7M51m/3eaAVArLdXk/l2NDy2LdbJa3gkEeKxYZAmzV3889oRCTGw2kENwUDvOhprGmafb8Y+02UXpSeek4TC8U2K7Z5PRYjJ8UhXdyOSZ6FJGHolGeKRTYxnHYqK+PS+JxLvSoJ1OSSWb5fGxpmj2Sh+d9zNETXUwpFtm12eSmUIjZqsoruRxTqlX2TKW4NhbjmUKB4zodNspmOSmd5rJGg/Wk5JhslmmRCDs6DhHX5Vsh+LHT4fPnn+eonXf+0y2/QCDA6NGjURSFhQsX/l0jiT9b/1fPoK6++moOOeQQDj30UFZeeWWuueYallpqKaZPn/7fvv/mm29m2LBhXHPNNay88soceuihTJw4kSuvvPIPff5WW23F3LlzmT59OrFYjFKpxBdffPGnTLaBQID11lsP6HkADjjiCFY55hjWW2IJMAyeLRToKgqb9/fzUjDIhbUaZSG4PBbjHV1nU9MEIUiYJl1F6fHLHIcrCgWWsW3OjMfJmCZv5XKM9pAr3/n9vJzPs4KUbNTXx53xONdUqz3IZTzO3YEAu5smLmA6Dgu13hO8KiWTCwVWdBxuDYfpSMkruRx7NJvskU7zViDAK/k8e3S7bNTXx9RkkhnlMqtJyb6ZDJOTSU5pt4lJye2hELcHg4zzfEpfAi8bBqMtC1VKvndd3tV1NjNNVAnPaxpv6zoHdjsEJFwVDjNH0zij2cCP5JJgmJ8VldOadZCSh30+qkKwmttDN40wTaJC4dRYnBeCAR4sl1jVdZkaDPKOptNv2wy6LpeXiuzSbnNGLMakZJJ7SiWO7XQ4IpnkyHSaHR2HpVyXRULwlCcK2dw0sRXBz1IjIeC0bpLHWyoTRJugAg0pkBJWcDss0EIMFQ4VV5L2JN7L4pBHsKNZ5ytL4RsLPveCA1dzLQYUlZnVInHgzcIgU1p1do5lOKLdoAPcH4zwaCXPl4rGfEXjiFiWtWybr/y9J+i9O02uicQY6inQPlZ1Sq7kqHCcvo7F7q7L15rGzrUa0nHYM5Xi5Eql5ykKhVi7r4+1bJvrq1VmhUKM97h5e5sm81SVFwIBbOgF/rkuWzebaK7LXeEwu9brzMrn6TgOu6TT7OKZqud7M9AhQjCzVOIDw2Cb/n4WaRrHt1p8q6rcEwxSUhSGOg5+IVij3cYPPBMMspppckehQNayOCCZZPV2mw9zOWKOw9rZLJau81ShQF3T2Li/n/d9Ps6t1xlUFC4Ph/lKVVnfsnCFIG2a6KKHQUq4LteWSqza6TApkSBs27yTy7GRt0F87e8Bb5cF1u/r46FQiKm1GkIIJiWTvKDr7OThlZpSYioKBSEQUnJGucwG3S7TolFKUvJqLseERoOd02le9Pt5NZ9nD9Nknb4+psbj3FCtspyUHJROc2swyD6miQF8rqr8qqr4bBtbSvapVtnUNHnS52OBlDw2MMBBn3zCvltuyTN/4GH8b6GzUkpCoRB9fX3Mnj2br7/++u+KzPg/uf4pG5Rpmnz88ceMGTPmP7w+ZswY3n333f/2a957773/8v6xY8fy0Ucf/Rdw699TyWSS5ZdfHoBRo0ax//77s/322/PKK6/87mv9bWmaxqhRo0gmk3z44YfsOmECU665hgXpNKdnMrSEYE3bRgMWqioS+ErT2LHV4ohqFeG6nBmPc1ilwmu5HHkh2CibZXPT5NV8ns8Mg3X6+2kbBldXq8zVNA7xnnbHewPor1SVpqJQVRSWsW0OqFaJSMnVkQibNBo8l8uRtW22yWZZ2nF4N5fDpyis1dfHvECAO0slakovE+p5v59jWy3qQvCEFyK4ovf9D2u3sRWFHzWNuJQcXKkQpsdey9g2k8plQsArgQBJ12GrZgMhBB1FQQPmaRq2gO27XaoIroxE6AdOajX4FbgiGGYYkgNbTXIS3tQ0AgLKuk4X2LHdwkWwXzLJoBBMaLdxgdVbLVICjkgkeS0Q4IlSkXUch8PTKe4JhdjaskBKRtfrJICPFYVfXJdtG3VeNQwsIYjgcqKssadVRXUlv5GOQorgV6mwjOIwINXFuVBCgAGEkD0YrGPSp/b+nR/iYznV5RPFIIUk6EqWki6v6gZP+gKsIiU3BiPskshyaqtORErOLRfYPpIm6brcUi1RAGrAjq0GHxh+3tF91FzJkdEkp5crrCN6rc/TiwU+FYJN+/o4ttXimnqdyYkE4/v6WMVx2N6yeMfv5+FIBJ+UqK7LapbFyFaLruvypN/PqZUKdxYKfA4cmExyXqnEa/k8D4XDrNvXxy7dLneXy9weDrPlkCFkhODoTofXdZ0bYjEcYEnHIQQMNU2ElLzm97Njs8m1hQKm63JYMsmBlQrv5nIsUBTWzmZZ33F4ulDgXb+f0f39dDSN8xoNPtI0zonHyQnBhpaFKQSG4yCE4AufjxVsmwuKRZKOw6mJBOs2m7ydy5F2HEZ7RPXX8nlaisI62Sxf+P1cU6mwSFU5KpXiE+/eaQrBoBB0RQ+DFJKS48pllrFtroxESFoWL+VybN5us206TU5VeTuXYy3HYe2+Pp4Mh7m9XCakKOyRyfCQ389hnQ4u8FdN41dVJeq13cbXaqxq2zwcCNB0HB7N55lQqzEhmeSvhsGbuRyHtVqMzma5Oh7nrlyOL6ZM4eRDD6Xb7f6uNem3TcqyLNrtNqlUig022IBCocD777//u8JXf0/9X3uCKhQKOI5DX1/ff3i9r6+PgYGB//ZrBgYG/tv327a9WKHyR8vn83Hvvfdy8803s++++3Lbbbf9qespisJKK63EiBEj+OSTTxi59tocfO21fBsOc2M+z3b1Oj9JyS2hEHfncjxQKHC/38+e6TRXVCo8XixyUTTK6P5+djJNzm23uTUUYi+PhLCJbZNTVZ4Lh1GlpALs0Goxutmk67rcHg5zbrHIg/k8X3uzp0nVKq/n8zwdDLJ2NsvansflSZ+P7fr7sYTgoG6XbzSN+yIRmkDE7UVxjOh2UaTkhUCAnRsNLiqVUN1e2N/+lQov5HK0XZfd0mn2rtd5K5ejoCjsmk6zX73GE8UCeQRnR2OMa9TZo9mgK12+91SFb/r8LCdddja7fC7hsmCYvawua9om813Jbf4Aa9gWaceh5Lp8rapEcHktECQtJdt12vyK4E5/AJ90+UsoSMR2eKmYpwHsmkrzraaxuWUh6C0O/a7LBbEYZdlj/I20bWaEI1TcXrCfDmxGhyf0OBlN4TPZk+Yu53aZK329E5PbW2x8SFwXgkhaQABJHy5dCRc0ytymhBiwXN7SDMbabe4OBDmrWuL0SAJdwsxSnl1aDQYRzPPo4bfFEiRdycrtNgLYv9vmsmiCXxSVkuNyTiTBncUCCQQh6XJdPs/0YJBN+odwSLfLNq7LveEwN0Wj9HmJs2t3uwyxLMquy3uqylWFAleUSjyjqpwdi3FPocBThQJnx2Js47WEb6zXOTmdZmx/P1u6LvtZFg+GQlwajxOXkiGOQ0RKdC+A8yNV5bBqlYuKRb6XktNjMS4tlXg1l+PRQIBNs1mOaLV4tFjklliMDfv7WYWeYXuW38/J6TQIwXq2TUVRqMhe1Py3msZGpskp5TKO63JOPM6BlQqv53IsFIJNs1nGdjq8ks/zUSDA2v39+FSVa6pV3jUMDkylGPBwVoNKL+bD9MQhfcBEj8c3LRJhzU6Hv+RyDLUsxmSzDLVt3svl8AnBWn19fO/3c2epRFFV2SWb5W1d56h2m4qi8IrPR05RSLsuBrBto8ESUvJQKETUs21s0WyyXypFGfhrLsc2psl62SzPRCI8XCwyDNi6v58Z4TCntVoowIxwmLdNE/fVVzlyp51+V8vvb4NTDcMgGo3i9/sZPXo00WiUd999l8HBwT+15v0/Vf9Uucd/3mF/Awz+nvf/d6//0dp3331ZeumlGTduHAsWLODiiy/+U0O+YcOGEQgE+Pzzzxk2bBj3vfQSh48fjzo4yKO5HF/6/eySyRATgkvrdeb4/ZyUSKAKwTjL4gtV5RdF4d1QiLTjUBGC08plZvv9vKcofKdpPDM4yM9eKJzq9/NIoYAFjE+lCAjB5GYTDTgzkSAEbGrbICVvGwZzEgniUiKlZHS3i9+2sXw+XtN1ppVKpKXkgGSSU+Jx7ikUGOo4bJHNMjMY5Ip6nVU6HXbKZLg2GuW4Tod1Wi0OSCa5JhLhqG6H0Y0G+6bSXBkOc2W9TsYymZBIIoCLqxWeicT4xpOJfycU5hk+JrWbPGD4eU7VsQT4JXQVwa/0guxCUuJIyY9ASxVYSL4OBjGRNBBU6ZlnG4rCFqkMY1yXobbNI4EAiU4HdIMTEgnGdLvcX62yaybDutks67suy0qXnxSVADBCV6hZCoZ02deu8rg/xhpugU3cJh/oEbanjY9egm5GkXznKgxXXT6xDJZWJLPRiCDZ3DG5Wqi0EMzSg6wjJHP8gucCEfpch581jb/oPl72BXivkGP/dJZdE1lWcByuKRUZl+lnQrvJZs0GV8fTfBjPcEW5xAWJJCMch+mFPHukMwSFYDdPQec3TaSqslAIXOCxYpFPdZ1zYzFU0TMpL1BVDkomCQjBjFKJH/1+dve8Skd2OvygaVwfjaJAT5wiBCHLoikEpuuyQFGYWi6jSskJiQRvh0I8ks8TAMZ6IpnplQph73dIB/Y2zd4mEA6TDIVYQkqirsugovCdJ2RZCOzVbLJxu82RqRTXRSJcUSqxgWmyRV8fz2YyXFavs1anw67ZLDfEYoy3bTZsNpkcj/OUF2o4zjR5w+fjA0/gYwnB8lKye6PBi55h+4B6neMaDXbKZNg+nebIVosD63X2zmYZ1dfHGMfhnlKJE9NpdujrwxCCo5tN7gqHeTIQoKIoLG1ZFFWVTZpNHg8GeTgYZC3T5OZikcOTSfZOpdii22VmpcLJqRRrZ7OsCTxRLHJGKsXm/f34gcm1GjdEo1wfDvOlqrK2aTLbMFi62yUeDvO+YRB1HKYNDnJZu82BW23FmVddxZiddvof16BqtcpXX32FaZqstNJKZLPZ/5C0sPLKK5NMJvnss88olUqsuOKK/3BO3z+z/ikqPtM0CQaDzJo1i/Hjxy9+/YQTTmD27Nm88cYb/+VrNt10U9Zcc02uvfbaxa89/vjj7LnnnrRarX+o+ezbb79lhx12YIUVVuCOO+7404mR9Xqd2bNnE4/HGTFiBJOPOAL3/ff5Bti32eRBT7X0ajRKxrL4WVW5PZ/nqlSK2UAceCGXY3owyIxwmD7g4XyeF4JBLgiHyQJXF4s8E4nwhCe3PaDT4SWfj7Rt84NhkLVtvlMUzqpUeMnLPnKE4Ol8nncMgwuj0cXy2R9UlQOTSYLATZUKJU1jUiRCSAiO6HQoqiqPGwYasIFlUROCn1WVjhCsZNt0gR81lQ6Cbb0h9UO6ThC4rlLmDU3nwWAQRQi2aTd5Mxxht06bBwwfrpRYCHSlt9lo0qWDwELgIEFKFEUQp0fyHqK6tIF1dYsPTB0TBUuCjWBEx+JnXSfibWx1KTmk2WDHToft0hlUYFPpsku1yvHxRI/KLQRLSJvDDZNvpMa6sstuToNttX5eVgaouLCV20dWFRRsF79QqEnJEUoTNB2na6LoBm7LpOAPska9zkOhGJeV8hycyHJEtcLdkShH1KqM73Y5LZHkRVXjqXKBYa7Lkck0bykqz5byDHddro0neUlVqasqG3ZNcrrOjNwgD0Sj3OUP0FUUlrEs5us6jw8OckcoxIOBAH1S8lQ+zxOBABdHIqSF4I5CgaejUW4zDCJCcGKjwZPBIE2gpKqsblnM1TT2qdf5MBRiPtDxFGgfGAbXRiKoQvByLsc3msbBXuDjA8UiPxkGJ0SjBIXgxFaLH3Wd5wwDHVjBtsl78yeA2aqKBUyqVglKybnxOK6U3FcsEvFUoAjB3cUiESnZNZ1GAY7udsnYNpdEIkSApVyXtOMwT9dZrdvlXcPA77qsb9uMaTQ4NR7HAs6q1dim02Hbvj6aUnJZrcaGnnioKQQTLIvN63WOTaVQgSFSslmnw8xgkI3bbd7x+xnmOHRVldOLRU5NpWi6LtuZJpMrFfbIZPhZCA5qtTi20WD/TIZ5QrCD63JUqcQxmQx5IcgAE6pVro7HWb3dZk4gwDreRnR+ocAl6TRNx6EfuD+X49hUio9VlXVsm1tKJc6Nx3naMBgpJdcUClyx1FIMrrsu026//b+kgXe7XebPn8/g4CDDhw9n+PDh/+Fh+zeVn5QSXddpt9vMmTMH6I08/iwF4jdo9j+7/ilbqWEYrL322rz00kv/4fWXXnppMUL+P9cGG2zwX97/4osvss466/zDndHLLbcc7733Ho1Gg7Fjx7Jo0aI/db1IJMJ6661Hu93myy+/5LIZMwhttRWb6jobt1r4hOCxYJDVOx3uzudZxrbZN5Wi3zR5P5djJW9YPCcc5slib8C+XV8ft0YiTKnXsYAZwSDP+/2s7/XmV2s2cRSFuaqK6rrMyOfZpNtlcizGr8CbuRwTm03GpNPcGYvxVKHAbl7EwKR0mkuaTZYRgku8rKmdLIsAULcs3jQM+mwbS0q2r1ZpKQpNz1F/YLlMQ1FQnR6LLdDp8IJhsJfZpQ/JUfEEb4VDPFgpEBXwsT9AW0ru1n34pSStKEQVUFwXV0pqKPSekCSKgKQiF895XKDiChxX8HrXYE2fxcxMCZ+Q+ITLfJ9GwrHoRzLMddjQMpkeCjM2neFQy2R32+J9VeOMZIqdnd4cMy0dQqrCdnaDjzDYyemdQA1FYYFUOUnJ0nHhgfoAh8kuu3QaHNdpMMMJ8aBl8LXiZyWrxTwjwPqdBm/6Q+xktrgjGGFit80nwRAziwWujie5IhJhtm5wUqfDAek+Dk5ne2iiSpmDM33khMJfDB8/C4WrikUuKZdoApeGemF9TSlZzrK4o1BgR+//5Rc+H6/k86wMbNDXx+2xGFNrNfzA6fE4D/r97GRZSCGwHIe6qlIDHCmZXCqxcafDzaEQP9HzKk2q1dg7leKeSIS/FAoc0+mwYTbLSakU0+p1NgSOSKeZEouxq2URk5L5QjBH1wk5Di3X5cBKhS2aTd5VFN5VFB7N5bimWOSCaJQp8TiP5fPcUqmwezrNztkslzSbHN/tcngmw4RslrGOw1quy6s+H08Hg8Q8gcg6rRZrNZsUXJeXdJ0rikVuLxR4Rtc5Nh7ntlKJZwsFLvDCBI9vt7mpVmNKIsH2/f2s4brs3+3yuM/HLbEYBpB1HKJSMrzT6eHIDIP9Gg1uyOfJS8nhiQQnlMu8ncvxrmGwXjbLWMviiWKRJ8NhNhwyBJ+icE6zyeu6znnxOBUhWM+yaAtBwHFQgbmGwcq2zcXe7OykRILRXoRI0rZ7szPglXyethch8oXPx7RKhYWKwlHJJO9YFiu+8QZH/E3Lz3VdfvjhB9555x1c12XDDTdk2WWX/S+doN9Ufr/Npnw+H6NHjyaRSPDuu+/+L0ct/6fVP+2sN2nSJG6//XbuuOMO5s2bx0knncRPP/202Nd05plncuCBBy5+/5FHHsmPP/7IpEmTmDdvHnfccQczZszglFNO+ad8f8lkkhdeeIHVV1+dzTbbjLlz5/6p6/l8PtZee238fj8ffvghZ191Fcueeiq7ZrOcUyrxTi7H+5rGen19rO84PFos8rrfz8ZDhlDVNE5vNvlcVbkoHmeRojDSsvBJSdBxQAg+8PvZsNvlwkKBpONwbCLBJp7KKm3brJfNoqoqL+fzKIrChn19vBgOc3W1Sl0IzojHecYwGGeaWELQcRwKikJDUQgBk8pllnAc7g6FCFsWj+TzbNDtclIiAbbNK5466ohkEt22eSyfY2nXZWYoRFBKUt0uRaFwVLvJALBHIs1KpslSQrA0ki2sTs9L4rq0XElNCCwJPikRAsJCYiBpoGCiEFNhuC45KtbFryscF2vx147B3vkkx8UaTI43eqo7Q+UjJE3gLcNgRqXEdq7DvYaPlwwfyzgOwxyHmaqOpDc/KrhwrJIm6doEve1xC7PGrnaa5U2LbVTJp4rBut0WHwfCjLfbpFWVg5o13nEVnlfD/KoZrO6YfGv42LrT5MNAiD0bVd7XDcoCDOnyoC/A3blB9qrXUF2XuQimlIqsY5ks0+2yTTLNGdUKjxQLnJRKM19RaSgKs4JBDipXeDOXQwrBWtksX/h8XFep8KOmcWQyyUeqyi6mSUsISkBbVSmpKnEpmeQBWqdGIiRNk5dyObZstdg2neZXTePtfJ7RjsM6fX3cE4txa7lMSggO8BRoh3Q6CGCOovCNqhJzXSSwX7XKapbFUz4fA1LyZC7HCdUqRycSPBYM8nI+z+Rmk829h6DbKxV2sW12z2Y5PpXiENNkBPB0IMDTgQBDHQfpuqzfaLC8abJASuYIwS35PJeWStweCHBlNMqT+Tz3FwockkwyLp1mWq3Gxa0WB2UyjO/rYzfHYQfX5Y5QiOtiMbKuS8JxiElJ3LIwXZdPFIUTy2UuLxaZLQRnxWJcUyzycj7P7aEQm2eznNxs8lCpxOWJBJv097OG7JH97wsEONM7fa3lRYhYjoOQkm80jU1Mk8ne7OzseJwDKhXe8KJrNs5m2bLb5ZV8nk+92ZnUNKZVq/xV1zksleLnv5md/agoWIpCTVFIuC6HFArIb75hwjbb8MjMmbz33nssWrSIUaNGsfrqqxMIBP7Hdek3AYVt2ziOw4orrshqq63G559/zhdffIHjnXp/b/0rBBLwLzDqXnHFFSxatIiRI0cybdo0Nt10UwAmTJjADz/8wOuvv774/W+88QYnnXTSYqPu6aef/qeMun9PSSm55JJLuPzyy7nrrrvYdttt//T1FixYwM8//8zqq6/Od/Pnc+Uxx1CtVtnGA1s+5/MRlxJbSnQpGeE49FkWjwcCuFJyerXKCMfhiGQSE5heLrOaZbFZXx+mlJzbbjO62WTXbBYX2MRx2KLZ5OJYT55cE4JRpslnPh/jq1XuicXQHYe1HIdjymUOz2YpuS4TGw2ObLXYI5PheyGY2G5zVL3OXpkMC4RgnOtyfLHIxGyWH4HtHYeTSyUOSKX4VQgONbscWK0yLttrrawuXdqqioZk13qN88NRokAdgYtEF4KWlPgE2EAbr1WAxPbafEnhkjIE2+tNXrKDrKbbhHTB0rLN02aEw8N1TsoFiSg9NFBbQsMVdF3o9z5HUxS275q8aBgMN02+8xkslL3P9CM5WnR4VgRpC8mjbo4huJyoZXjd1pjdWcTjWpB3FR8XmWW2DQ3htdoito4M4eXKIraIDmFDp8vzqsYOiuQlqfJ4Lcc+0SyTa2XOD8WpIbmlWqWlqpwZjaEBk5oNUo7DlGiPMq5LiZAuI02L42pVds9k+Rm4tlZjBdNk72yWoOuiAqNNk9cDAfasVrkvFsPvOCwHnF0oMDGToSgle7fbnFyvs086zXxFYe9ul+OrVQ7JZvlSCNaRkmPKZU5PpVBdl7aisEerxf2hEHtWqzwWi5G1bUqaxoyBAU7PZvlWSpaXkvvzec6NRnnG72dVx2FGscj18Tj3GgZLCcFVxSLXJJN85iGlJjYaPBAKsXq3y5xAgCVNk/maxmXFIg/FYnyoKOhC8OzgIM8FAkz12ssv5HJ8aBgcG4sRFoLbi0XeD4W4zu/HLwQHt9t84vORF4KuopB0HBYJwY7tNhVV5SVdxxaCG0olLOD4RAIXeNITWW2f6bV9b6lUUIDDkkkMKdnTsgg7DjMDAdKeaCPiukhFYd1WiwdDIRTXZc9Oh7HNJhPSabpScnG1yhbdLlv29dGQkvOaTTZqt9kjk6EuBNs6Dls1GkyJx0k7DqaisGG3y6t+P3tWq8yMxYjaNmlF4bJ8noMzGQpSsnOnw7m1GvulUsxTVXY1TU6tVDhmyBBaa6zBDTNn4vf7f9e69J9bfp1Ohzlz5uC6LqNGjfrdYw5FUf4lzL9/6gb1f1M99NBDTJw4kQsvvPAfsikuWrSIL7/8khVWWIFiscgVxx3HKV98wV2xGN8CbSF4MJ/nbb+fa8NhhNf7/1FV2T+ZxBCCO4pFOqrKxHickBAc2unQFYKH/H4CwBIeZiYpBH7X5QNVxZGS4+t1Ep4SypKS20slhjkOY7JZHCm5vlplFctibCaDCxxkWWzQbHJcIoEBLO84bN7pcHM4TFb2IgQ273Z5MBAgBvS7LrvW60yJRpFILmw1GdLpclQigV+CrirUgEtqZS6OJdnFbPOw7mdlu8uXmkELsFyJJgABFoIgkn5NMkJ1KKLyvasyVmvyvBXkwkiFK1oJnkwPckc7whsdP3lb4cZEgWdafmY2gqhA0ZXs2u7yl0CALAJVwPK2xV8VDRfZi6cQcKlVYUYgwZ6dCk8H4+wgW9xNGMeV3NsaoI7CEeF+nm0sZGywn+frAxwS6eP0WpHrI0n2qVa4PZpg2WaT5wJBdEXFkS5SwpRqhTtjcTbstGkpCi8YPkzgplKRvKJwTrxn0H01N4gGbJLJ0hWCk71Tyx3BIKNMk481DcN12do02bzV4qRkElNKLqxW2bzbZWtv3nJxvc7GnQ47ZbPUgN0dh7G1GiclkwSlxC8EW7XbPBoMsl2jwXPhMH1eqN0F+TzHZjKUXZexpsmFlQr7p9N8pSjsZpqcWalwRDrNR6rKaCk5rVjklHSaPD3J/aGNBtMjETZoNnk3HGZly2KernN1Ps/l6TQ/uS5pIXh8cJBLo1Ge8vtZRkoezOe5KxLh+kCAJb0T053JJE9oGkHgxHqdB8JhfLbNr7rOSMtirq5zRLXKm5EI8wBLUZiZy/G+YXBlNIoOvJTLMV/TmPA39Ibv/X5OCYfxC8GxzSY/6Dqv+XzowDCPXLK0Z2h/S9NwpOSkWo0+D/TqSsndpRL9jsM22SyulNxaqdDnOOyWTiO9+2cZ0+SSSIS4lESkZFnbZrZhsFmzyTPBICHHYVUpOaRS4chUipaUHNVoMKHVYvtsljxwUqvF7s0me2az/ALs4DjsXalwQiqFkBKfEOzW6fDiyJGcd9ttLL300r97XfrNL/Vb+++bb77h559/ZtVVV2WJJZb4u6/z7w3q/4F67733GDduHLvvvjuXX375n8Z4lMtl5syZw5AhQ+jr62PCTjux4s8/c20+z63hMLcGgywN3FYo8FAkwi1+PxkhOKta5aFIhJ+BpqqypWnylqaxU7PJO5EITcehrCjcUSjwTDDILL+/t8ENDjLXMDjGIz7PKhYpKAoHJJOEhOCsRoOaqnJDMEgAWN+2aQAlRUEAdXqzis26XZpC8LrPB1JyaLPJQl3nOZ8PVUq2Nk0+9/vRpMvSjsNzmo4B3F/KMzWRoiIlTUVhQEoQAsf7U3rtPAtBWEhKnvloqOIQVRV+dAW27J1C0xrUHcEaPpuPuyoJXTBSN/nVNbg/Ocivlsou+TTL+2BB1yWCw4Cr47iwpmOznHR5zvCDlBjSpYkghORw1eQJNcg17RwrSZsxgX5qEl5tDnBLMEnA7HCE02Kr4BBebS3i+FCWvRpl5hsBfrUlo1yb540Qe7Qb3BGKcWa5yImpDM8OLGJcto/TS2UUJMfFE6SBp3M5vlNV9kinyQIz83k+Dga5OBLBD6xnWXypKGzd6WC4LncHg9j0hAk6MD6dRkrZw0xJyY7pNCpwUqdDv2UxORYjACznOAx1HN4zDEaaJh/rOmHXZWXXZftajXMSCbpSckK9zs7tNuP6+qhIybn1Otu22+yYzVIQgv0ti12qVQ7PZLCAfikZ32xyUyTC+q0WHwSDrGJZ/KDrnF8oMDmVouG6rOa6TC8UmJhK8bmqsrVpcnmlwmmpFC9rGuu6LhcXi5ydTjNbUUgAJ1UqXB2PM7Tb5Vu/n408fuAZpRJ3xuOUXRepqjw+MMANsRhP+HoUjmdzOZ7w+7kwGiUF3F8o8FwkwjS/n6gQnFWr8Ww4zHxFwRSC0abJp5rGpt0u3+k6PwJNT6X4s6pydSQCQvBMLkdFVdkjlUIDZhUKNBWF/VIpDCk5rd2mKwQ3BoOEgBUcB1VKBjWNEabJB5qGLiXbmCajWy3OSCSwpOSiapUNu13G9PXRkZJplQqjLIsdPRHHIabJhs0mJyR7iLA+Kdmk0+HBQIDNWi3eCAZZyrYxVZVzikUmZTLYPh+TLrvsf6vy++/KdV0cx1mMeisUCnz22Wf09fWx8sor/13rnqqq/5pYj39vUP+xvvvuO3bYYQdGjBjBXXfdRTgc/lPXa7VazJ49m0AgwEorrcQlJ5/Mpy+/zFDb5thSibOSScKOQ1nTGNdu81gwyMGVCvcnEoQti7amcd/AAKdmMnwGrOC6PFgocHk4zMPBIMu7LrcXi9wTjXKLz8cQReGSYpG743FmqyqOEOzdbvOsz8fanQ6fBINEbZufVJWpxSKPRaO8q6pIr+Xyl0CAqyM9Vt4ruRxvGwZnxuMYQvDK4CBPBAJc46m9ppcKTE5nWcmyGFQVvqAXvb1zp83DoTBHNipcF4mzQbfNl4aPiqKSdG3mSYElFPpxURRBB7C8zWtLn8PHrsH5viI32wn20Kq8TpRDtBIHVVIM8SncHh/g4Eo/q2kmH3Q1royWObYUp+lCF4HPlejA2q7Dl4pKUwj6kZQVhYPNGu/4wjzQydEGtjf6kELh9dYi5gqNC8MZZjUWsVeon2uaOd7SA8yRGvubTc6JZJhRHmC3+BBeKCxky9QQXsst4qB0H4eXy7jAsfEESwOXFotMSyYpSklR05joqTl3q9V4PRql5Lo0PEHBbF3nrFgMP/B8Ps+3msZBySRBIZhaqbDA72d6IIAP2MY0+cVjNQJUgA6wR6uF5nnkHCm5qVwm5TjskU7jAvd5p4Cts1mElJzZbrNct8uR3mK8puMwsttlZjDIypbFt5rGEo6DVBT2q1S4NJHAcl127XQ4vFZjz74+ClJyQqPBAa0W4zMZfhSC/WybCZUKEzMZBoVgWSmZUK1yUTzOsqbJAp+PzbyN6LRSiWuTSWyPHzhzcJBjk0nmaBpreq3ES6JRHvH7WVVKbioUuDqZ5HFNo08IzimXuT4ep+26lDSNHTod/uLzsWetxsuxGKZtU1FVZuTzPB4O85jPh08IXhoc5B3D4BSvM/FkPs9cn2+xSvHSapVPg0Ee8VSKm5km36oqYXrpzAvpdUAmNBr4XJdro1EcKZlRKhF3XXbJZJDAg4UCUSnZPpMBKTmr02GIZXFKPI5BL6xxhG3znM/HGqbJHF0n7TjEgAOrVc7yNrj9220m1uuMy2YpAafX6+zabrP3kkuSWGcdrrrrrj+kqPstKVzXdUzTXMzyGzVq1P923fv3BvX/YFUqFXbbbTeKxSKzZs1iySWX/FPXsyyLuXPnYpomI0eO5NoLL6T65JMsXavxVDBIxHFYQUoOq1Q4IZ2m4roc3GxyZLPJHpkMPwjBxE6Ho2o19s9m+VoINpKS40olTkqlsACEYN9GgxmRCNvV67wYiTDc6smwb8rlODuT4UfXZQTwYC7HlFiMv/h8rOy63FkocFs4zG3BIMsIwc35PPfFYtxlGAyVkhuKRWZFo9xvGCwL3JrPMT0U5vFAgKWl5PhalcnJFKc1qkwLRmghQSg0pWSoa7NA1YgJMN3e/EmInmrOh0vB7c2SljMkZVR2V6r8oIf42ta4IFDgpFaamdFBTmxlOdJfpSRVzi8HuSTZYCd/iwuaaSxXsqJuM71s0HAFVdkTYKSlxBECQ/Yk60spkkVSEFEEM7t5Lg6kWcns8Lwe5KHmABFgy9AQXm8t4vpAAkyT7dwOp4ayPFJdxFaRIbxeWcR2sX4eLw4wJZFhg3qN+arO/f4gwxWFXRsNbo1EOLdY5JpUCstx0BSFxwYGuDCR4HldZxXX5d5CgUeDQS4Mh3v5V8Uid8Xj/MWDnx7UbvOU388Iy2K+z0fKtvleVZlSLvN6KMRrmgZC8EQ+z+cehVvzbASD3inAB9zo2QjOjkbxw2Kiwl91najsMQSllKziOAztdpkZCuFKyRnVKqvaNvun01hSLp6Dbu7NQae0WqzTbrNPJoMpJRs6Dpu320yNRhnuGc1HWRafGwYHl8vckEigOQ6rui4XFAockM0yAOzVbnNavc6BySSfaRrjLIvTKhWOymT4XAhWBE4olZiSShF0HIqaxvhWi0e9B7kHEwlClkVN05g5OMgFySQfKApLAk/kctwSCnFbKMRQKXmwUOChaJSr/X4ywFWlEvfGYnyoaUgh2KPd5iWfr7dB+3wojsOAojClXGaO388jPh9CCB7P5/lZVTnC8zT+JZ+noCjskUphAFfXalQ0jYvCYXzA1pZFF/hM18k4vXwsTUpGOg5rNptcE4vheLPnjSyLcd7P9PpKhTW91OCWlJze6bCeNwOzhGBN12XLTodHVluNs264gRVWWOF3r02up5j8reX37bff8uOPP7Lyyiuz5JJL/i/FEP8KUCz8e4P6X5Zpmhx55JG88MILi8Gzf6Zs2+aTTz6hWq0SDoeZ/8UX3Dh1Ks8tWoSQknGZDA5wW7nMspbFVtksAjjMNFmn1eLYZJIQsKTrsm63y6OBAOt2u3xoGD3prKIwoVxmcipF03HYp93miHqdfbJZfgWOaLU4vNFg30yGr4Rge9fluFKJozMZFgrBEsCx5TIXJRKkHIe8qrJ/s8ndoRArdrt8Yxgc1mxyRzgMSJaQMK2Y59Bkml+BjW2LsmGQlC4bNuvcHokxut3kr74AIFhJ2HyqGAQEJFyLL9CQQERIsrrKprLOAj3IN67GuUaeq60Ue+lVPiDMgXqZC9ppHo8PsH+tj6WExV9tPy/EF3JhK8ETdYOQptCxHZYUDl84GrYETQICIkJwhVnlEn+cae0SjnQ53JdgGUXweHOQ2wJxFrqSc80q+4X7uLCZpyRUpoXSzGgsYkygn3uaeQ4NpbmgUeKWQAzNleRVjR9cyXgp8ds27/v9zFy0qIemEoL9POHCqckkL2saYxyHyaUSk7zFNwwcV60yLR5n3VaL90MhVjJNPtd1rsvnuTqd5lspiXqn2xvDYe4LBhkCPJbL8WwwyLnhMGkhuK1Q4PlYjDt+o3B7icYtoKKqDLNtFigKezebfOvz8Z6qYnlChLyqcloshgSezefpCsFOmQwacGulgiIlE//GjBtzXe7yBAWalMRcl46isG6zyaxQCFX2kma3bzY5JJ2mLXtk+e26XbbJZikDZzSbbOsJdArAFq7LbvU6ZyQSJF2XlqIwttPhqUCA/TxBQdy20VSVGwcHOSqb5Wcp2cC2uaFU4qR4nDcNgw0dh6uLRc5NpXhOVVleCC4oFrkomWSRRx6f0GhwXyjE5s0mb4VC9Nk2P2oa1xUK3B2P866iEPR+5s/7/VwajRIRgudzOf5qGBzvRX3cUirxbjjMbT4fhhDs1+kwW9epCoGlKBhOL41gZw/RNSsQwAGuKZWIyp7BWdJrxcekZOtMBuhtcEnH4fBkz/Q+xrYZYdvcGQgw3HHIC8FQ26aqaexZrXJdIkEkGOSIiy/+h7T8SqUSc+fOJZ1Os8oqq/y3J6V/b1D/B5SUkssvv5xLLrmEO+64g+233/4PXWNwcJBvv/0WRVGIxWIMDAwwcuRISsUipx9wAFalwnnVKgsNg6u96I1tLIsB0WOGOaIHs+xKye7tNpaUzAyFsL1WTtx12dc7Sd1TKjHCcdjMU/id1m6zTqvF/uk0uhCs7jhs1G4zPRxmBcfhJ0VhZcviZ8Ngl2qVO2Ixgo7DslKyX6XCWek0ruMwynEY02hweTLBcpbNL3pv7rSyY3NSuci4ZBqfBL+qUAXObJSZHkmwTbfN14aPBYpKn9XlQ9UggYsmYHXFYZjq8hG9EMdRssXTVoCgkPhV6DiwWcjhU1PjpmiBgqNwXSfBrNggN7Tj3FbzcVDcZlOlzuRmivMCRY4qx2l7v9FNKQhKSRDQgSEKPNrKMTHch3AdiqrOs/VFlBDsHunn1cYi7vBFeE74cFSNnx2XqKZStx1SiorpurSFYHXL4mNN495CgUc8A/BV+Tzjsll+AiZ1u2xXr7NvJkNDCFaSkj1qNS6Jx1mz3WaOz8coy+Jrn4+LCgUmp9PUHGfxHOeIVIpPVZXNTZOrKhWmJBI8o+usAVxRKHBBKsWHqkoEOLFa5aZYjCGWxbeGwXqmyXuGwWmlEg/G4yyUEkdReDyX44FgkLuCQcL0BAXv/rbYeoKCuYEAZ4dChIRgUrPJXJ+P93QdASxv2yxSFFaybSwh+Mgz455ZqRCUkjMTCRzZM+NmXJdtslkkcGu5TL/jMD6dBuAAy2KlbpfzIxGispcevapt877Px1aNBk+HQkQch2WAY0sljkynqUu52CS7aybDT0JwaLvNofU6B3odhU1cl2PKZU5KpTDpqUP3bzS4LRJh23qdlyIRRlgWP+o603M5zk2n+U5KhgKP5nJcGg7zqNcyn1kocE8kwjWeiGN6ocAdiQR/0XV0KTmm2eSRYJC44/CLYTDMsvhaVTmmUuHjUIh3vNb6zHye7/4mjfjFXI5BpZcabEAPp6RpnBSN4hOCA7pd2orCc4ZB0hMnaVISA1Zvt5kZDKJIyYRWi829e9oErqxU2Mg0Gbvkkiy/3npMveOOf0jLb+7cuXS7XdZYYw2i0eh/eO8fBW7/3vr3BvV31COPPMKECRM499xzOfroo/9uD0CpVGL+/Pl0u12WXXZZhgwZgqIo5PN5PvvsM0aMGIGqqpx72GFsPmcOj0UiDLUsvlFVriwWuTce51MhUEQvt+ZZv58rvD75s7kc81WVgz0BxHWVCgVd56xwmKAQ7NntUlAUPtX1nhHVdelKybqWhSIlz/l8izOgYq7LCckkttdHX9Jz+5uegmkpx2FsNostJXeWS5QVhTMTCfyuZBiwQFU5p1ljvqLygs9PBsnnCFAUhLeoG6JH0A4rgtGyTUnzMw+VuHAp2T2Bhg6coNW4kxgXG0VudpMMd5o86wRZ1Sf4zhbMjOcZqjiMqQ4hJB2297c5IljnuEaWdUWDt5wwX3Ugb0MbgeOCKuCabpmbfTEGpWBvxeaMZol9I30c2yqxoWuxW6iPlJR8JVRqrsvz5TxnJTMcXS1RU1TuCceYXhhkbGYIrw0u4upkioaUnFsqsWkmS1NR2N+yyNg2tweDLOO1h/odBxSFnatVro7FcKVkn3abA+p19uzroyglp9Xr7Nlus4u3+O5n2xxUqTAhnaYoBMPpEQouicdZqdvlK09Q8J7Px+RikampFKY3x3locJCTUik+UFVWdV3uLhS4LhLh7kCA5YBb8nluTSR4QNdJCcHZlQp3RqNU6eUdbdnt8qZhsFu9zruRCEXXpaYo3FYo8LbPx4xQqBf9PjjI996szCcEjxQKFFSVgxIJ/FJyeqtFQ9O4JRAgCKzk9LLHKorCEpbFJ7qOKiU7dLus2W4vnrdcWqkw2jQZ09dHW0qurlZZ2zTZ0dvsD7Astq7VONYTiySBsa0W94ZCbNlo8Go4zNKWRV3XuSSX4yRPpTjacbi2WOSQVIq5qso23S6XVquckUzyoqYxSsqeiCOV4itNIyglx9Vq3BiNsmK3y+d+P6ubJp8YBucVCtyTTLJAysXt20eCQW4Nh4mIXqjiO4bRC1X0Nv/3QyEuCQQICMEJrRYfGAZfqipSUVjatlmoKKztxe68ruvYwJRKhYTrcpwnl7+vWCTrumzlbf63VCqkbZu9PTXh3rbNipbFvSNHcvq117LKKqv87rXub1t+qqqyYMECvv/+e1ZccUWWWmqpxWvfvzeo/8Pq/fffZ+edd2b8+PFcccUV/+OAsF6vM3/+fKrVKsOHD2fYsGH/5Thcr9f59NNPSSaTjBgxgsN33ZV1vvqKMwsFjk8meU/TWM9rX0yLxZjp97OilFxVKHBjMslLmkYIOKFe555wmIRt871h9G4iXWdSucyT8Tjfy16MwOO5HM/5/dwUDqN7kvavNY0JiQRBIbi3UKDmLTBBIbioVkMRgpO8DW9KvU7atjkkHicoJY+XCrxh+Lk+EkYVPYVcGME51RLHJtJcVitwZiTFAe0arwRC1FSNrcwGnxhBfkIh6Zh8hU4Ml7CqcKpS5jqRYEOlTZ8meMkJcIZW4FInzZlagTs6Id53DO5MVri3GyWjSo7WS+xQ6ePKcJHp3Rhz2grbBG3eNH2EXZv5toINGBJSuGzlWqzi2jzkj/BMbRHfCI1jIhk2ci1ekCoJV/JcNceuiX6mVXL8rOpMj8a5tzDIlqkhvJhfxM3xBBVHcnK1woaZPoKKwnamyWeqysqOg99xeMbb/K+sVIi7LhOTSRzg/mKRJV2XzbNZHODCRoOVOx32y2QQwAaOw+hOh+vCYZZ1HBZ6p9vvNY0JlQrXJpPgOIx2HM4qFtm/r48BKdmv2WRSs8kEb/HdybY5tVzmmEyGL4RgGeDEcpnzkknits0iXWfndpsnAwGOKJeZmUig2jZNVWXW4CCXJpO8oar0Ac/kcjzoeZUy9BBcL4fDnB8MEheCS8plXoxEeN07aY0xTT7SNJaxLAY0jSpQFYJTKhWKqsqt4TCOEDzkeZN2S6UQ9NpcPinZ0fMqndFu02dZnBqPEwBWcRyG2zYv+nysbpp8quukHIeMEOxXqXBmMonpuhzQanFIo8H4bJYccGKjwX6tFntlMnwnBLs6DhPLZY7MZCgJQUZKDq7VuDIeZ1SrxaeBAOuaJp/4fFxcKHBZOk3FcUgIwSODg5wTj/OyYbCi63J/ocDt4TA3BoMsJQR35vPclUhwn6YRE4Izq1Xui0ZpSklZVVnX+9ns1mwyNxDgWyFoKwo3FAr8oGlcGo0ivDliSVHYNZVCE4KHCwVqHnpKB45vt3GF4LZAgCjQ5zgEXJeCqrJmt8sLfj/JaJQJF1zwD2n5lctl5s6dSyKRYOTIkWiahmEY//cn6v6/rX744Qd22GEHhg4dyj333EMkEvkPf99ut/n222/J5XIstdRSjBgx4n/0CnS7XWbPno2iKKy22mpcf8EFPP7wwxzY7bJfpcKETIaKojDMdTmoWuWSRIKRnQ5feFSJv/p8nOM9Qbe9m/X+wUFOSKf5QFFYw3G4o1hc/AS9PHBTocDdsRj3GAYpIZhcqXB/NMpP9CTtu3Y6vGIYLGeafB4IsKZpMldVWcWy+MTnY49Oh3m6xvsIhgq4u5jn1FSGipTkVJWaK1nH7jLb8HN+q8yloQQ7mU0+0gN8LxQ06dJAEECyoirZRnS4mxCrqzbrq11utsPcbwxyoJllVnCAPdv9vBgaYIvmEK7x5zm0lSElHJ5L5FAFHF9P8lZb4/xok6+lj1ebChWpoCEpuYKmFChAWIIrBC81c0wNJWk5LoOGj29tl02sLte2KmyVGMLrpUU85Q/xsi/AdZUCWySH8FpxEdfHkpimxdadNgfEUyQUhe07HZ71+bihUOALXWdaJIImemmq3yvK4gTgO0olyrrOcdEoQUVh/06HthA87/MRBvyui5CSLLB0p8PjgQB4Ppm1TJNDkkm6wDXlMutb1mJj6BSv1bN7JkMN2Mx1GVevc1YiwRDHoaIobOktWBMrFWbE44Rtm4iicOPgIId7BuyNLYtry2VOjcV41edjtDfHuSiV4hlNY2nggmKRK5JJckBLVdnXa3ONaTZ5MxwmbNv8qqrcVCjwcDTKi5qG4Z203jUMTovHCQjBc16+1MREggAwrVrlR5+Pa4JBfMBY0ySnKCzUNIKuS5Gecm7zbpelTJMbIxEcT7q9mmWxi3fSn14us5qH8moDp3Y6rN9oMDGTwRGCVVyXrVotbgiHWd00mef5qxYYBqcVClyQTmN6bdZrCwUO9AzP23a7XFKtcnIyyWuaxgauyyWeXP6vikJWCE4rlZiaTBK1LH4xDLbqdnnF5+OocpnHEgmqjkNbUXggl+PhUIgHAgHCnprwLcPgpHicsBA85tEmTgmHCQvBOR5g+i+G0aNY2Da/iF7isOG6zFVVbGBio8FQy+Jsr806vVxmFdtm+2HDOOPGG9lsiy3+0Hr3m2dK1/XFQq92u80aa6xBJpP59wb1f2JVKhX22GMPBgcHeeSRRxg6dCgLFy6kXC4zMDBAf38/yyyzzP8WQfJbOY7D559/Tr1eZ8011+T5Rx/l9auuwqnXGRSCJWwbW1XZol5nRjSKdF12b7fZvdlkQiZDWUpOqdfZu91mV0/qe5BlcUilwoHZHp1gZeDIcplzkkkyts0iTWNHbwB9eLnM3ckkMcui+jcUgR+kJCMEDw4Ocmw2y1dAXFG4spDnuGwfG3Y7vK3ptASMc2x2rVY5LJXm4lqZU8IxVpEuH6EQVRVM10VTBEtJh4WKykbSYmlNMkv6WE+xWF21mOGEmKIUeVBN0CdNRuiSL22VtXSLmNPlBWJc78+xdX0ILVdyTyzPX20fj3UjxBXJDmqN7X0dxlSH8GBokF2qafKuQgCXLp5qSrg9KrkCv7pwbrvKiq7DcbEsfykt5KJYmnS7xYRui7HJIbxRXMSF8TTRdhtdVbnN8LMCgo3bbR4LhXh+0SKe8Pu5IhJhSUVhRj7PY7EY03WdqBCcXK/zdDhMCaiqKqtZFp+rKuNbLeYFAnxBD9Y6vVjkV1XlvL8RKphCLD5N3Fkq4ZeSvZJJNCGYYJr0OQ7TQiGSUhKUkqEeNHijRoMnQiH8rstGjsO+ntm27knC92+12NkTzhzTbrN/vc5+2SwLhGBTKTmsVOLkdBpNSrpCsFerxT1/Q5sYYtvkNI0Zg4NMTqeZBywNPJLLMS0U4v5QiOGyR594OBzmCi+i/YZSiYficZ7TNDTRA6++4PeTdhx+1XVits3PisIxtRrzfT6eNQwcIbi/UKCiKByeSPSsEPk8LrBdJoMqJdPqdfxSclwigUZPMdfvODzs9zPCU8z1uS4oCuM8kCuuy/hOh4NrNfbw/GAn1+vs024vlssfZJocVK0yMZPhF0VhJSk5tFzm3GSSpbxZ1lhv859UKnFzMon0COIPDwxwdirFO6rKslIyK5/ntlCIm0IhlpKSmYUCD8Ri3ODzkRSCi8tlHojF+EpVMYEx3S5v6zrrmiY/GAZFKakKwXlextUN4TBSCB71BC27e7DdxwoFbGD/TIZYPM7Bp5/Oznvs8ac2kv/c8vv+++/57rvv2GqrrX43zeKP1L83qD9QlmVxzDHH8PTTTzNmzBhmzZrFRRddxP777/+HfFNSSr799lt++eUXVl99df76zjtce9ZZPPTjj3zpeWQc4PFCgaCUbOMp/K6pVhluWYxPp9GEYEfbZs12m4ujUYa4LpYQrGpZfGEYbFur8VA0iuEhj44slznSQx4d1GxydLPJPh7i6OBOh2NrNQ72WkYHdLucWK1ycDrNXEXhoHaLbdttDs1kGW12eUPXaUl4oFrkvESa7a0O7+o+1nItntZ8HN2ucHUgxtquxTLC5SHFz6ayTb8meNj1s4es8ooSouQqrKVbvG3pTA2UmWKmeCm8iHGtJZgeGOQXR+V2O8GpepFDmmkiiuSJaI6WFOzR6OP1yCJut+PM7arENMH3bYc5toaCoCIFESSbCpe4lIzrNLg4EOeZ6iD7xfs4vlZimOtwQKKfF4sLOSCWISZdvlY1yo7LWMtmiJS8HQjw8KJFTI3Huc/nYyVgUqnE+akUCdPkR8Ng606Hl/x+TimXuSeZpOE4dL1ZxS2xGI/5fIsJ9q94p4uYEDyQzzM3EOA07wn6jEaDz/x+XtZ1VGCkbfMLsJTj4CoKn3lP0MfVasRclynxOLaU3OGRQ7b2WonTy2WWs212yGSw6QkVRjebnJxIEAFCwMadDk8GAmzXaPBsOEzWtjEUhQvyeY7xfk9+o01M9H4vdjBNzq9UODWV4lVNYw0pOb9YZHIqxY/0hApHeUKFtT2T7/K2zZe6zpWFAnclEswBDCF4enCQZwMBroxECHsz108NgyPjcYJCcGexyBfBIJcEg/g9Gf4CXedLTUMH/I5DExjlOKQsi4c9bNiZ1Sor2zb7p1LY9FSyK1sWW3im2QtbLdby5PIdYFPHYUsPGzbMssirKqNNk7/6/RxZLnN9IoHhOCwB3JDLcXA2y/fA1qbJFZUKJ8fjvG4YbOQ4XFEsMjmZ5GVdZ2ng3FKJS5NJWlJSVVV2b7V4IhBgXL3Oq9Eoqm2TV1VuLhR4KhTiCU8d+MLgIB8ZBid6p9Bnczm+MQwOjcfxA1fWaizw+bgnEGCZaJQhm2/OOmPGkE6nWW211fD5fH9qvfttkxJCoGkalmX9F9HEP6v+vUH9gbIsi9tuu43TTz+dYDDIMccc8w+B2i5cuJB58+ax4oorYts2R+++O4FSiemFAl/6/ZweDhMVghObTb7y+Rb3/VewbQaEYGXHoSYEn6kqlpScXa0igPM95NE9pRJDPGSLLSU3VausYpo9AQQw0TTZsl7nEC9Ubn3HYddajdPjcYQQbG5bHFEus1cqTYselfsXoTA1Fmd8t8OdPh8BBGvYXbqGwSpWl7Kh87Wic0inylRflI3dDhVF5R2pEUVSQaBKlzVUl69djXVo85Xix0ZQlbCGT9KQMCucY9vGElzrz7GiZrNepZ8VdJf7IjkA9q9nmNdViOoKNcsmpKi0JIxQHT4wVQL0UEQaAlVKDjIbvOMPM7FZxZBwaTjB/labK7UAcQF9wK9S8mpukDsTSb5VVK4r5Dk4neELVWUosFWrxUOhEMeUy0yPx9Ech7QQ3J7LcYQXybCRZXF9ucz5sRhP+XysISXXFQpMSyZ5zDOcTimVmB6PU5GSimc4fdHnY5d6nTejUTqOQ9ETKrwSCDAzEEAAL+ZyfKtpTPTQWI97p429Uin8UnJ2q4UjBFeGQgSBVR0Hn+uyQNdZ1qNN+F2XDWybzRsNzvJoE6fXauzQ6bBDNksFFtMmxvf1sRDY07bZu1LhyEwGS0oiQrBvvc6NkQibNZu8EQqxqqcqnJbPMzmTYdBxWEpKHs7nOTsW4wWfb7GIY0Y0yg1+P0uJHvbo7kSCx3SdAL0Z0m/S9UFVZQXL4ktN46B6nc8CAT70pOO3F4sMqiqne6fQ57xT6A7eKXRGuYwCTPgbuXzacbg1GCTrwXCXcBwGdZ0xtRr3RCLorsvmts2hHgKqDhzXaHDQ3xiTD+l2mVircXAmw3whWEtKjiqXOT2ZJOg4VDWNPdptHgwGOcjzbcUti7KmcffgIBcnk3yoKCwBPJnLcVcgwA2RCEOAWbkcz0QiXBAIkFQUrisWeSIW4wVNQxWC3Tsd3jEM+qRkqGEwe9llOeHSS1ljjTWwbZt58+ZRKpUYOXIkqVTqT69Pv7X8LMsikUj8WyTxf2K9/PLLHHXUUWiaxqWXXorjOEyYMIGzzz6b44477k/3ZX/zICyxxBJks1nOmDCB/k8/5T1dZ/tOh+d8Pg6tVnk0Hsfx5gyzcjlmRKM8aRgEgFdzOd75myeuWYUCi1SVgxOJxU/mVVXlJg95tLZtYwO/qio+KXuhgFKyjDcb+VTTiHozkpKiEHVdNuu0meoP9OgHpTynpDIMcWyGdTvcEwyjKb201IiAhQgS0gWhAC4BBMsKh58UnUudApfrKdaUbYZoghdlgLMoMJkM1yuDHGmlqUvY1mfyLQb3BQe5oRNhUPiY72js4W/yoWWw0Fb5wVH4S3CAh9w4H5kqP9mCRa6CK6EhQZEgkexod3lN87O8EHzrSlYEfgWWMU3267S4JJHm1cGFXJRMIx2bsysVts70YSoK/a6Lz3XJAoeVyxyVTNIATqnV2KvTYZzHUTu82+XAWo0Ds1l+EIJRUnJ4qcRZqRQJx6GgquzskUMOq1S41zOcNjWNBwYGOCeV4kNFYRg9GfSdgQA3RiIsISUPFAo8HwpxQShEkp7M+LlIhJc0DSEEO3a7fKTrLGnb5HSdhutSFYITqlXKqsptHm3ivmIRQ8oeU04IHiwUSErJWI98cFqnw/LdLscmkxj00D5rmSYPeB68jw2DpRwHW1U5sVjk9GSSjpSMtSwml8vs6wkT9m63OdXLY3pXVdnEcTinXOZUj/sXA070sEfLdjp8GQiwgWnytmFwTrHI3YkEC6VEKgqPDwzwYDjMHcEgEXpy+b96eK+I1xL8PBDgDE8uf2KrxTeGweu6jk7v9FmllwmVsG1eNQyklBzZaLCyaXJ0KoUtJTeUy6zx20kLmFqrsWa3y66ZDE1gZ8dh63qdM5JJkh4IdqtOh6f8fg6o1bg3FiNl2yiqyk2DgxyZyfAzMNq2ubFU4vRYjJd9PtZzHK4vFrk8mWSWrjMcuKJY5Mpkkm8UBVsIJjSbPBwMsnanw5xAgIRt86OqcmGpRC0Q4KJUipPPP5+dxo//D+uPlJKFCxfy9ddfs/TSS7PMMsv8qfVJSsmsWbM4++yzuemmmxg3btwfvtbfW//eoH5nvfHGG3zzzTccfPDBi5V8H374ITvvvDM77rgjV1111Z9GgDSbTWbPnk0oFGLFFVdk0oEHssKnn3LkokUc2dfHAinZxDS5tlLh7GiUv/j9rOO6TCsUuC6Z5EFdZ6joGRRvSiT4kV4cw+7tNs/5/WzRbPJOOEzAcfhVUbimWOTJSIRXPEf9M/k8bxgGl0WjKN4w9zWfj4tjMRQB9xSLnJdMEZGSoIDXhcJI6XJGtcxRiRT3VfPsl+jjpmqeo2MZLmgWuTqcZGXXYnnhMFMJMLlb5O5AggCS8bLBVBHjQQbYhz4eVnIcJLM8rg4wxh7CX/RFbNjpYz2/w7X+Als3hvBscAANyehalrV9ktv9ee53Ynxk61zhK7BNcwgzjUF2a2UouoIlcMjJHp3Wj2Q4kuWkZFnp8C0qk2ol9klkeSM/wJRkmlTXZN9mna1SWWKKwqqOwzdCcFalwiqe29+WktsqFYbaNuM8vM1uts267TbnxGJkXBcpBOuYJm/7fOxarXJ/LEbYthkqBOcXChyayTAo//8E68OTST7SNLazLM4rlzk9neZVVWUlYEqxyPmpFCUp6agqBzYazAwG2a7Z5NVIhKRt85OmMd0jgbyuqhheu+wtn4+zYrHFQoXvNY0DvNDKqyoVBnw+LguFCABjLIsmME/XSbguOUCVkrUch1X/hnxwRrXKxpbFLuk0bWBqpcImpsm2HpLnKNNkp1qNg7JZmsAyUrJXvc7l0ShrdDp85vezgWnygc/H+YUCF6fTtB2HrBA8MDjIpGSSdzWN1R2HO4tFpv9GOwFuz+e5M5HgHl0nLgRnV6vMjEQoCUFVUdjANPlQ09ix1eLLQIDvgJYQTCuVGFAULonFcIXg6VwOSwh2SqdRhOCBYhEF2DOVQhW9AM+sbXNZJEJCSqKOwzKOw2yfjy0bDZ70fFvLS8nxpRKHptM0gAM939ae3iZ9UKfD0bUah2UyzFYURkvJyaUSp6RSNAFHCA5uNLg9HGbbRoOXolGWNk0WeL6t61MpPgFiQvDU4CAfGAZHZDIcctBBHHbKKf9jG69erzN37lz8fj8jR478Qy2/L774glNOOYWvv/6aK664ggMOOODfIon/m+qnn35ihx12oL+/n3vvvfdP92gty2LOnDnYts0aa6zBvTfdxK0338xFtRrbNhqM7+ujQE+5dZBHPA57jv7dWi1mhkLsW63ycCxGxrapeQKIU7NZvpGSFaTkgXyeS34zKErJ3fk8s0IhrgyFGCYEt+fzvBIKcWkwyDApubNQ4A3D4OJolOWR3FXIs1v/EDbqdpmr6cxHsq3Z4XN/gEM6De4PRNjPbHCDP8olzTynBFNMNKt85g/zndA4wypwqprmUrfA7UaSFZ0WQV3jJ0ewlmax0JYousE+ssIhdpYVNYd3uwoTw10OVyu8b+mc1k7i0xReDC7ClrB1s58bfHnusGN0XYlQdZLdFk87QVx6zD9FCoQAXcK6tslHhp9rKkUeD0VYhCAkBJ8IhYSisFOnzaxAgIcGc1QVhb2SSfzA5fU6vxgG04PBxT6frveUn7Vt3tU0FNmLwRjV6TApmaQrJZdXKmzs+XxqUnJBo8FW7Ta7ZLPkhWAH22avSoXj0mkCsgfZ3dUTKuxWrfJ4LMZQy6Ko69w6MMAp2SzfSckKrssDhQIXRiI8EQiwoutyV6HAfZEI1wYCLCEE1xWLzPRwSiow0XtgyTgOv+g6cU+ocPR/EircVyjQEIJDPfLBk4UCfmArT6hwRaNBn21zqCfi2Ni2WcU0mREMLjaDL2PbFHWdg728Jem6bGpZnFEus182y0Jg/1aLExsNDk+l+EhV2c5xOLNU4sRMhjlCsCRwSrnMJckkCc9cvm2nw/N+P8eUyzycSNC2bVqqygO5HDPDYR7y+wmLHkj5N2NyyFPMfeXzcWw0SshTzC3w+XjY58MHrGbbVETPg5i2bT7UNISU7NrpsGanw8nxOA5wWaXChqbJ1n19tKTk8lqNDbpdxnub9B62zU7VKsek0/hkj0g+vtnkznCYHep1nvMMxIO6zo2Dg5yazfKz67KSlNyTz3NeNMqzfj8jvU363miU68Jh1lt/fU6+4oq/m0D+ty2/1VZbjWQy+Xd9XbVa5eKLL2bGjBkceeSRnHfeecRisd+7nP3h+vcG9Q+sWq3GnnvuyS+//MIjjzzCsGHD/tT1XNdl3rx5FItFRo0axYdvv819kyfTqNVIui7DbJu5hsGanQ6v+3yEnF4y6fhqlZNTPSPpMfU6+7fb7J7J8IsQHOX5RA7MZPhcUdjcdZlUKnFSOk1e9PA7J1QqTI3HyVoWv+g6h9fr3BEOk/R66lcWi9wYj/O+Iji822FMs8nB6SwXVUucF4nTQYLSk5SPtdqUfX4aCLaRbaarYa7p5jnNl2ZHp07D5+dTaXASRc4mzcPKALs6fTyvD7CTPYSHtAHOc5NsqXbYkQbrtPrYOexwgVpgy/YQ7jByXOOmWJsGG2omBzeStKVgdR/M7bgoQkVTYCnh8pGlYOBiSvAD21sdXtf8bIjkDQTrC8GXrmT7dptNLZMzEkmeHVjE84EefTxFLwri3nCYpRyHHw0D6aFnppZKfG4Y3B4K9dRmuRw1jxoggIcKBXzAzp7B9PhOhyU9GnkEWMJ1Wd6yeMvnY8N2m1f8fhKOw1JCcESpxPHpNHXXZf9Wi+MajcWClgM7HY6v1Tg8neZj78n8zFKJU9NpBoVABQ6v17k5EmGDVot3QyFWtKyeLD6f55Zkks8Bn+ihfZ7wYMFRIXh+cJDZhsHh3qJ+e7HI/ECA84JBAkKwf7fLIlXlE10nIHvkA0dKVnQclvK4flL24ivWNU32zWToyh7NewPTZOtslipwaqvF2FaLfTIZqkKwluuyZ63GuYkEw02TX3SdrbtdXvQUc9clk+iOg09RmDkwwEnpNJ8oCiNdl3sKBW6IRLgjEGAZKXubdCzGTT4fKdHzbc2MxZjnkc637XZ5R9dZxzT53jAoyF6Y5jmVCiVF4ZpIpIcpKhTQvJMWUvJwsUgQ2CmVAiE4qdNhadPktHicEDDUdVnNNHne72fTVotXAwH6HAe/onBmocCxmQw112X7bpfzqtXFMSe7dzqcUatxUjrNm6rK2lJyfqHAWek0LU2DpZbi0ClT2GTzzX/3eiKl5Ndff+Xrr79m+PDh/2PLT0rJAw88wNlnn83KK6/MDTfcwMiRI3//IvYn698b1D+4bNvmuOOO4/HHH2fWrFmsvfbaf+p6Ukp+/PFHvvvuO0aOHMlX8+YxbdIkbpw/n9f8fmaEw9hS8lixiC0lu2cyuFIys1Siz1NyKcBR3S5rtVocnUotZvpt1OkwMxhkdLfL+4bBcrZNVdc5tFTismQS1bYZAZxQLnNCJoPhMf+2rde5JxLhuFqNadEoVSm5v1Lk+VCYrw2D0ypFDk2kWdPs8q6q41dVOtJFE4I2oNJ7krSkS0hRabouIVWl4LqsokPHlVyglZlKkpnKIJtbQ3jZt4gr7ShhVeV1x4/r2mzoczlNLVJ2BVs2s4QUhRv1PCdaaZ4wBriFFB3T4h3XR0Uq6AKqjsQBVG+TEsBwIdjO6vKq7uOKYp49UlmmFQtcFYnxtaoyQgj2rNe5IRrl9HKZ+xIJfnBdYkLw3OAgDwUCXOVtYLPyed73+zklGiUmBBd7+JtHDAMN2Myy+EFRCNDz9/wiBCawf7NJ3LaZGostnoEsb9tsn8nQhcU+n7GZDC0hONg0GVOvc7gnMU5Lyc7NJreEw2zRbPJGOMyKlsWvus7UXI7TslmKjsPKUnJHPs+kRIK3dJ21bZubSyVujMWY4fMxQghuzOe5PZnkaU3DD5zk5TP5HYeFmsYKts2XmsbEWo25wSAfeIv9jGIv8+rUeByXnlABIRjrGZFvrlSIuC4Heum04yyL5SyLa0MhlrBtmh5K6VvDYI9KhVtjMQzXZU3H4cxymQMyGXJSsk+rxSmNBocmk3yqaexg25zlMQ7/qigsA5xVKnFhMonjupQ1jd1bLR4NBNi7VuO5WAzdtslrGjNyOR6KRHjaMPB7irkPPQqE35O1f+8Z2v3ApfU6CzWtF1njtW8d4CddZ5ht85k3x13XcdiiXudsz0B8Sq3Gzn8jPDmvVmNsp8Pu2Sw/C8Hets0+HiS3BcSAA2o1ro3F2Kda5e1llmGV7bbjhMmT//QI4X/X8pszZw6TJk3i559/5sorr2Svvfb6lyXo/uf69wb1TygpJdOmTWPKlCncdttt/5BhYi6X4/PPP2fEiBEEg0EO22UXooODzMjl+NTn4/hYjLgQXFou81UwyK1etMAYy+JXIWgLgRSCIr02167tNn7H4dZIBFtKriqXWcpx2DeToSMlt5XLrGpZbOOZQm/xaNbb9mVpSLiyWmGhqjEjGmXXTocZfj8akhdLOcal+7mtkmdSIsMZzTIXB+Nc2CxxSjjFbc0cR4UynNkp83AwzhDbZKgmeVP4ONSqcqmaIIvFHFdhfd1ljf8fe+8Zb0WVpm9fq8LOOZ2DqCgqom3ObQ6omBUUFFFAUVTEhAKKBDOKWUwYMWECMaEIBsxtwoSKARUD5+ycU4X1fjjVvj3/mZ7pHtppZ9r7G4dNVXF+u+qptZ77uW7q5HUfU5UsezR78bSri7YN+zaTzPHn2UIzeajtZWYzxD4uk6tdOR6xg7xqerhMy3JYu5PblAwj23FytmBrYfKJVFD/7OgTELNtcoqKavWkqEaQ5G3JCc0GnbbNjcEgM7I5Lo/F6JKSvR1L8dRolKddLvoBl+RyXBGL8aMQNBWF4bUaj/l87Fur8XoggNcZZJ2VzfJsIMDTLtcvCKsVus6YaBTN6f9VhOCIRAIPcFG1igu4IBT6xdCSsCyWut09KyFNI2pZrCUEg4pFpsZiNG2bkbUao2o1jkylWA2cWa1yfL3OcQ5d4kDb5qx8ntOTSX4SgjAwtljk6kiEPzQafOzzsaPD9bssm+XmaJQuQHF6IHMCAe71+Qg7D/W/NCo8kM3ymdfL+X4/PiEY22jwna7zisNvTFkWDXqMCp2GwbNO7thJ1Srbt9ucGI/TkpJrHcbcAGdWaWqtxj71OkOd7KrdLItjnMypuGVRVFUOccIZTyoWuTcSIWyaNDWN+1evZoKzVbiR7AlNvM0hnfdx5rbmh0LM8HpJCMG1uRzzw2Fe0jQUITi82eQNXaeXkzpcA4pCcHKlgg3cHAhg0TOUHbdtDvmLF8VOy2JgKoUBnNdosHmjwalOke4rJbs3Gtzt97Nzo8FbHg/9HHPLjd3dXL7uutQ22ogr77rrH+LE+7P+vOX3/fffoygKBx54IPl8nksuuYT777+fM844gwsvvHCN44bWVL8XqF9RTz75JMOHD2fSpEmcddZZa/wWUi6X+fDDD4nH46y33npcOGYM5ttv85WUjKrVeMDvZ69qlVdDIToMg5XOZP+ccJg3VBVV9HDCXnca5m5nKyqjKAx2HoizCgVUITgxGsUrBOPqddYyDMaHw+jAxFqVbet1Do0n0IGXsmluC4V5x+VmV7PNHE2nN7Cd1aap6/Rv1PnA56dPq0HdpfOT0NjfrnOHHuL6RpqTPUmeMLoYpHfwlNXFIK2T580u9lZ7caio8aDl4QJvHWlZvKsGmKlkOM1M0Ue2WCy93O7OMKqZ5AlXmkHtFE+5u/AL2KfRwXS1wC12mF2o87oS5BCjxA12AAMFD5KKQ5lYy+6Jqr+ilOeaUJQh1Qp9bJvzQhH2r9VY7PPRkJLx1SqHNBoMTaUoCkEv4KhKhZtDIQ52+gnrmCbdmsa9XV1MSib5HFgfeDSdZpbfz71/8UBcGAgw3ecjqShcn83yfDjMPF1HF4Kjmk3ecazWRUXBtm0KQnB8tUpTCOb4/VhScpuT+3RkIoEJ3J/Ps55lsXcySVsIzms02MkZ6pZCsLFts3+txo3BINu2WnzocrGlYfCly8XUbJapjlFhYymZnclwaizGB5rGHw2DWYUC14ZCPODxsDFwSybDbbEYj2saIdGD9rk/FKIpJRlVZUfD4D1N48hqlU98Pr6gZzB5Vi5Hl6oyzbGEP+OstAYmkwgpubdQIGDbDHGMC8PbbTZst7ksGCRp2yjA5obBO243hzuk86Bpsq4QTMtmOdFZaR3ebDKlXGaMA9c90DGenJ9IsFhV6UcPIeMSh5DRUFVGVqs85PczoFbjtUCAiOOYuz6XY6Hfz0KXC1UInunu5kuXi9P+IuYkq6oMdiI3rimXaSgK00IhXMBupknAtlnqcrGRYbDCebFICMHQYpEpsRiGbTOs0eC0SoXRHR2sSiaZcccdbL7FFmv03PhrklLy8MMPM3bsWA488ECWLl3Ktttuy0033cTGG2/8q5zz79XvBepX1vvvv88hhxzCwIEDue6669Y4JrnZbPLhhx+iaRqbb7450844g/CrrzLqxx85I5VitW2zg2Vxcy7HhEiEl10utnOYfrNDIe7weOgjBNdns9wXjbLQITSfWq3ytNeLJiWrdZ0tHerBXo0G7/j9BCyLtBBs127xttfLAa02CpI5ms76SB7Jpjkm1Yu9jCY5W/KU7mJ9RbASmFvNclIoxcPVbo71J7mpmeMiX4JjmkXe9AVJGU08ukbBlPTWoGkaNFweDjOKTFCSNBVB0bR4zJMjgsWhRidL9C6usiLMa7u4w1dkG6XNfDvIE5aXdVTJS00FJGyu2bzXlmiKRkSRBIEvTfBJmxoKbgG9bJufhYIqJR6hULdtVEWhl7T5ScKdhTw+4Lh4Ap8QRKT85U36tHyeabEYVdtmqBOvMcyJ2zi61eLcUokzEgneUFW2kpIpuRwXJhJ00+PcGl2tcncgwO61Gq8Hg6zTbvOlrnN9JsMDkQhvKwqa0w964y9eLJ5Pp1nt5D55gBuKReqaxkQn92mgYeCybV5wuVjbtskIQcjuiWDfu1zm2kgE27Y5vl7n6GqVo/4CXHt0o8EQB/Uz1DA4pVhkTDLJ9868zhlOLEufVosvPR4GNJss8XiYlM9zpzOYbCoK87q6uCsU4hGPhwg9c1uvO0aFgBA8msnwucfDWcEgfiE4r1Zjla7zhNuN27bpa9s0hUAHehsGr7hcKFJyVKPBzo0GY+Nx2lJySanEgFaL/ZwojynVKgOdF4mfgP1sm+MKBc5KJHDZNm1FYWitxpxAgKGlEvPCYdYyTbo0jXu6u5meSPAJ0At4Ip3mXp+PWwIBetFj+X/J52NiMEhE9JDOXwyFeMDtxgUc1Wjwsa7TVBRsIWjaNjUhGNhskjQMbnVQTVeUSvzhL7KfbnO2cAenUtRCIU4aP54jjj32V581eu+995g8eTIffPABG264IYsWLaKzs/NXPeffo19/0upfXNtuuy1/+tOfeP/99xk0aBDFYnGNjufxeNh+++3RNI333nuPKddey4YTJ3JgZydnFov8KZ1mlaKwTUcHQU3jiVyOVbrOvh0dLPT5uLBaJS8Ed/h8LNF1dmi1EED/ZpO2prFK6XlQX57NsrVh8LjHQ8uymJNOs3uzySLdhbBsjivkedHlZqBlYgrBrskOtjfaHFYuscTt5alSliqCzS2LYf44DdvmcF+S9aTJue4YJ7WLzPbGOL2VZ5EWYLhRZKnqZahZ4kktzPFmgSu0BOMoMdPK0JKCm4hxoZ3gZL2OJsAnLSQClZ53rD52gw9aAl+7yauubnRFYRYZdvCojJUl6pbNTxaso/W4s2xgXdvkJ6HQBKbXyyDg8WKOkIDTSyUurVYYHoszKpFkY8tCs6yenKNike9sm7MiEa7KZnk1k2GB18u2HR3sZFk8mM/zjNfLvp2d/KiqnFGv85Wq8rDXyw+KwtqWhUcIdqrXCQHPeL10Ggb3ZLMMqNUYE4uRB95IpxlTq7FbKsVNkQjzczkGmSb7dXYyOpnk3EaDjaXk9nCY60MhNrMsPLbNWs0m0rZpSskXwKW5HFMLBf4EXBoKcXcmwwuZDHf6/ezV0cGZtRpP5HLcFAqxY0cHHUJwUa3G0x4P58ZiZBSFPdttqkLQlhJbCFbqOn2d/tAGhsHUcJjezSZL0mkOrtXYN5XiY7ebVzIZDjBNtu3o4OJYjJvKZfpLycnJJBeHwww2DMJS8o0QfKppeCyLOnBcqcQR5TIfAwt1nQcyGeZmMtzh8zEqHmd2LseCXI4pkQg7dXZylGFwQ6XC1eEwgzs6cAPDnCj2FzwemkLgkZKklAys1QhKyb2BANs1mzyUybBZs8mgRIKoafJOOs0O7TbbpVI8HwwyL5ejD7BvZyeXh8OcV68TlJK7Q6Ge4E/TREjJRo1Gjz1cSr6VkuuyWa7M53nA7eb6YJAnMhmeyGY5OxLhgESCK8plbi+VGJ9IcHLfvmxz+OE8/MorDD7uuF+1OGUyGcaOHcvAgQPZa6+9WLlyJZtssglbb701r7zyyq923r9Xv6+g/odUqVQ4+uij+fbbb3n88cdZb7311uh4Ukq++uorfv75Z7bYYgu++fJLrh83jmqxyEamyUaGwdMeD5s7UdIdlkVI9JCfp8ViNGybQY0GZ1QqHOfgWo53bL6nx2K8oWkcZFlMyeWYGo+zSNPY07a5IpNhZiTCApeLo9otziyXGNTRi42MNst0F1Ukd5fzPOv1U9U0Dq6UuDoU5cpylrGhBNu16rzi8qIJQRXorQhKUnKGLLHYFea8do4prjgPmd3so/TiJVZzrNLJOLvA/UqY9w1405tGStjH6MUNIsNEEtzhSjO81cGJSoVFIsDDahe3EmW1CcdRZhwdTJAFLraCZGzBjhh8gUZL9qxkNjdNPlFU3PSYFzyKQtOy8SgKw+t1HvT5uDifp6IoTA2FUIXg3lyOkq4zLhLBB+xsmoRtm9dcLvobBh9rGiFnRmZQqcTEeE+hPqlaZZQT1rdKCMbW65xQrXJiMskyx1l5Xi7HOckkq+lx2J1aLjMrFGKHep23/X42Mww+1HVmZrPcFY3yGaApCk93dfG8x8OVoRA+enBKKzWNYY49/s5CgZyuc44TMT+k1UICT7vdJCyLNhCSEq8Q7FqtMjsUQtg2QxoNhtRqDEv2gIEnVCoMbTQ4ynETHmcYjCkWOclZPW5ID0F9WixGzIGoHtJo8JTXy+kOQd02TSqqysPpNPcEgzzhwHMXp9O8peuMi0bxAQuyWb5xuTjZmeOaWq328AC9PYPim1gWONuKG7bbvKHruKVkd8PggEqFM5ye1nnlMoObTQ5OpegGzq3VOKpW49hUiq+FYB/b5tR8vufzgFAURlUq3BoK/ZIptYFh8KWTUn1jPM5H9ARiPt3dzVNeL1cFg4SB59JpPnC5ODkaxQ/clcvxmc/HlX4/LuDoZpMuVeVTXWcPIfigXz9GT5nCTjvttEbPhf9KlmVx1113cfHFF7PLLrtw/fXXs8EGG/zyTLn99ttZvHgx8+bN+1Wv42/V7wXqf1CmaXLWWWfx2GOP8eijj7L99tuv8TF//PFHVqxYQf/+/clkMlx+2mlc8vnnvOzx8JjXiwnMyWbRgWMcHtncfJ51TZM9Ojow6Wnc7l6rcXQyiS0EWzmIo+nRKB2W1dP0d1xs61oWdUUwOZ/nwliMtISLGzV2rVY5vKMX2xttXtVdSGnzSqGbA+O9eKiUZnSkgysrGaaEEkyp57nEF+Oieo7JnhhbmnWeVz0EFYEAJiplvpEqTd3NaUaOw0QnS+hiiojysuXiGK/BSlNhU8VktCxylp3gZUNljqvAlqLNQVYns9Q0ncJmn3YnV5FnGlEuknkuUeJMMAtMJEwBhcG0eEa68AC72CZFVWP3douFLi93Zro5OpFiWLnEn3w+3lNUwsDN+Tz3hcO8p+sgBOuYJt8qCiOrVYqKwlyfD0tK7snnCds2RzhDvQ/8BSOvLSXj2m12qVY5ybGeryUlB9Tr3B4IsHu9zms+X0+YpK5zlePEy1sWm0rJXZkM50ajLNV1tjZNZufz3BkKcYuzhXtrJsND0SgPuVz4pOSsapWnvF5aQF7T6Osk7A6q1/lB03hV17GE4IZ8HlVKTnUiQh7JZuklJbunUlhSck2lQv92m6HJJG1gT8ti31qN6eEw65smXarK7q0Wr3g8jHMs4W7LIiIEd3V3c6pj0tjeNLk9n+eaYJCHvF42lpI7nX7prW43SSG4PJ/noUiET4WgJQQHtFq85fTMftR10lJSEYKJxSItIZgZCmGJnuiYhG0z0CGZ35fLsdZfZJyNabfZoV5nXCyGFwhLyX6NBvf7fBxYrbIwGKSvYVDQda7v7uYsZ+t8S9vmrmyW8x1U09aWxR25HHc4v/d1xP8fbrhQ09CA06pVnvT58ElJWtNImiarFIVjazXWEYIrevXimHHjGD5q1K/ulHvrrbc455xzqFar3HjjjRx00EH/4eeklP80197/qzXzK/6uv0uapjFr1iw22mgjDjroIG677TYGDRq0Rsdce+218fl8fPTRR6y99trMXriQ0YcfjmvVKhan0yzXNIYkEgSBWwoFulwujkn09FKOardpAA/4/Tzp85GQErdt47NtPnW5EFKSB46o14k5Wxg/AQc1Wyx3uWkjONRoc7U/yAx/kKvKJXxmm3djCQ4wDP4Y6WBby2Ch5qGfbVJGEJQ2um3hlhKfbeHCZpxZ5SPdx9xmFwNcKWYoEVq2xRNmlhkiyjFqE2nCq3h4gS4ObXXSlhZXakUQUBAqAvBiIQScrxY40UziFj2cv8kywlqqzRlWBKTkRhGkrwJRo8VzigsJHGM2eEDz4rclK1wesC32iyeJCLgtEGQbw+DpQoGxiSTXhkJ863LhNU2KqspVuRzPuVxc5wx9Lk6nWamqHB2P4wOuLZXI6zojk0m89BC3VWC+18s7LhceKfFLSW/bpqPdRkrJErebMaUSQ+t1BqdSHB+PM75UYpjjxNsmleIQ2+b5bJZxySS7dXYSAi53nHhXBIN85HKxj+PEi7da2H4/q6VEOivhJ30+ZgUCeIEXnXyw4bEYXiF4IJcjresMTqXwCsHJjQZSCC6ORIhJSS8pidg2XYrCSiEQUvKjEBzoENKXulxcFg5zZrHI8Y0GxyQS7J5KMbzdZnaxyGnJJNt2dLAxcGc+z5R4nGMTCbKaxuh6nce8Xj7SNL5WVUKmSVpVGVIqgbPS8tDT0/pY1zklGsXlOCC7VJWjkknczhB0S1EYnUziB7a3LMKWxVNeL98rChrgtSzWtm22q9d5wOtlvs/HqEqFMQ4F4shEgpNqNcZUKpySSLB1Rwe72DZPZ7Ocl0yyV2cnGjDNCTe8KRDgXV1nW8PgY11nnVaLhNvNMlVFsW3uzeXoUhSOSqUYeuSRzJs69W9OPvjvqquri6lTp7JgwQImTZrEueee+5+SyH8rxQl+X0H90/TMM88wbNgwxo8fz7nnnrvGX4parcayZcsIBoNsvPHGXH7OOfy8ZAk/WxanVircGwjQv9XiU5+P9Q2Dz1SV6fk8z4RCvOcANxdkMnyk61wYDiNFT6hhRVE41Jm1eTqTwS17aOoKsCiT5kNdZ2qkJ9tnQ8viU13joVxP1MLnupuQZfKqqrGFAt8IhXtrGc4MprisluVSf4KzmnnudoU4wqzxoaIT1RS2a1U5W4/iUxWaEhaJbh6UXn7WfEy3sowgxeeWYL4ry3e2yrVEuZACF4o4zyqrmSISLGwqzBIF/qCYHEInr1irOUxJcZZVYDJRWihEVUEvaVGwoVsKQDKy2WCR18cx5TKf+vyUFIUZ2QyDkin8Vs9MjWpZ9AYeSKe5IhTiUY+HDYTgRmfw9XlNQxeCE2s1nvZ6e1ZYLhc+y+JnITi7WGSl283jzgr3wWwWARwdj/cMheZyJGybvVMpbOD8RoNt6nVGJBIIIehv2+xbq3FTMMj2zSYfuN1saRh85XJxkRMhX7MsNgLuTqc502HgbeesWm4PBLjN56OvlMx26BL36jpBIZhQqfCk309WCMqKwqZOwvP+zSarNY13NI02cHmhgFdKzohGMekJY1zbstizowNTSq4tl/lDu82RztzW/pbFwEqF86NRejmFfb9mk2ec0MQ7olFCpgmqypyuLs5KpfiUnqDC+3M5bvb7udvvZz3b5v5slgWOJTwmBFfn8zwdCvGiA08+sNVima6TtG2qikJaSupCMLJaJWJZXOmgmmYVCvQzDAZ2dNByjAp/cKjvJSEY3W4z0Jk1A4jy/7s293HSezczDFboOrPSaS5MJvnJtuklesINrw0EeMShsDyeyfCi18v4SIQdt9mG8665hnXWWWeN7vn/SoZhcPvtt3PZZZcxYMAArr32Wvr06fOrnvMfrd8L1D9Ry5Yt4+CDD2bAgAHccMMNuFyuNTpeu93mo48+wrIs1l13Xa6eMgXljTc48+efOTeVIm1Z9AUeTKeZFg7zrNtNf2f6/gmfj0uDQXoDs7NZXvP7ucLrJSwE00slPvN6uc9xKl3gWGgv9vlICJibzfClqnJ2JIpHKAysV3jbH+DxbDeHJntxYbXIgy4Py7UedE4byexmnsm+OPMbXRzo7eTFZhd7eTp5tt3NCG8nFzazvI7OvWqASe4mt9p+HrG70aXNINHJxXaeK9QoVRTuF2n6CIsTSdFlwboaHG+VuFqJMU+uZqqI09tssImwuUWJMMSu8oj08aMNbRQURbC7bfCeVKjKnl5Ow7bprah0WVZP4B1Qsm12Mk0uLBR6ei+KwtZSMsqZidqs2eQjn48t2m0+crm4NZ3m2nicT+npUzzX3c0TXi9XOn2KZzIZPtM0RsViBIAbi0V+drm42FnVHNhu0xaCd52HbRrwScn6ts0u1SpXRyJYts1JtRqDa7V/48Qb6kRIrBA9KbKn5/Oc5nDhksA5xSKXRyKs32rxhdfLnq0WL7vdXJDLcV8sRtq2MRSFeek0T3o83B4I4BaCF7u7+dJZablFD5y1oGmMjkZxA2OaTXQpme3zEQe8tk3Kslit6+z154FfuyeC/dRCgRFOptkJ1Spj63WOj8f5VFU5st3mvGKRc5JJXlcU+gMX5nJMj8ep2jYVRWF4o8EjPh8HV6u8HAziMU1Wqyo3ZbMs8ft53O1GET3D1Ks0jZGxGKroGb6tC8FhiQQacFGtRtCymOSk925iWWxkGDzl8fDHZpM33W56WRaaojAhl+PMRIKabbOfYXBxocCoeJxPVJVDHCrE1GiUZ3SdLYCrs1kui8f5RtdRUil2PvJIDjz00DUGt/5XWrp0Keeeey6WZXHTTTex7777/mrn+jX1u4vvn6itt96ad955h08++YQjjjiCQqGwRsdzuVz069ePdrvN8uXLOfm889h35kyO6OzktGKRt9NppJRsk0ohdJ0XslksRWHPzk7uDYW4qlSiJQSXBYPc4vdzZLuNFILVUvKMx8MfDAOkxDJNZgcD7G+ZaAjOjUSZHo2zIJfllHKJJ7x+JApnRRPsabZZy2jxle7mhWI3LgSDWnVGe6LUbclIV4Jhssl8xcv2wqKBoGbZbIPBM+4Ij1g5bjN9qJZFEpvJWopTlRq7KW2EtFkHgz7CAqAuBattwc1mmj+KFm3bZoWtcopd4F6CtKTka1PSz2qQEQq3GHlcQtJhmbyKRpdQuKpeQhWCmytFctLmoUKeXaTNWrbFjYU8810utu7oYH16HsYrVZVVjqX4fbebrdttbszl6N9qcXw8TswweDudZr9Wix1SKR4PhViQy7GtlOzb0cE5iQST6nV6AfcHAswOBNjcNFFtm01qNXTTpGhZfA5cl81yUT7Py4rCxaEQD2QyLMpkuDkQYM+ODk6v1Xgsl+PGcJide/UiKgRTajWe03XOj0T4SQh2NQxaioJm9wwlr3C5WMc0mZrPs0W7zYWRCAHD4MV0muMqFfZPJFgYCPBCJsOIdpsdOzoYm0hwVbXKTlJyVjLJpFiMAaZJh5T8JASf6Dq6bZOzbYYXixxbKvGDbXO3z8esbJan02mWaBoHJpNMLJdZnMkwLxhk685O1haC2YUCizwejkom+UJVObHZ5AdF4R1dJ6Mo+AGvEAyqVOhrmjzk86FbFo9mMpxSKjE6FuMVxz04rVJhd+ea7yyVOL7V4tBUiuNTKYaaJttLycN+Pw8Fg0RtG5dl0afdZpN6nZZts0TXGV8ocGcmww/AiFiM84pFXk+n+UjX2aajg02k5Klslvc9Hvbs7GSZ2830SoXvFIUHfT4yqRTbDBnCnJdfZuTo0axevZply5bRbrfX8Any7/XTTz8xYsQIhgwZwogRI/j444//1xYn+H0F9ZtQtVpl2LBhfPnll8ybN4/111//7z5Gs9nkm2++oauri969e6NpGqtWrWKzzTYjm8lwyejRNLJZNjBNdmo2ucPvZ+t2m090nY2dyfWzs1mmJxK0LIutbZsZ2SwnpVKsoCeQbUaxyLnRKK/oOrsbBtcWC5yU7EnbDaoqx5SKPBAKMzeb5vJQiJd1F9sL+FpRua6cZYEngK4q7FcrcWkowcxymqGBBH5VoW1L7jNz3OCKMMBu0MdqcY07zkOtbg70rIXbNumv2LxlayyRXTQlHKT0QhVwncjyge3iVcXPBsLGbbc4T1RYJD1MNsP4NQVhWXikTVjAV1LBEAopadGhCPZpVrnbFWRzafEnqeBCIBRBp2XyraKxnhD8bFm0heDCeo23PV4yisKB5TI3OYOplzuzOAcmk3QLwXDL4uhikdGJBC0h8AIjKxVuDIXYr1JhSTDIpobBZ7rO7ek0MxIJvpCSkOhh4s31erkhGCQKPJNO84muc6ITl3JbPs8qt5upgQAeITiy1aIhBK+5XCRsmzI9K62UlOxSqXBjOIyUkuPrdYZUqxydSpEDznVSZIfH43ymqhxpGJxRLHJ6MslnisJaUv4CZ021Wqz0eNi32eQFj4ezCgUei0TI2zZ1J858scfDrYEAurPSWqVpDHGyqh7OZmkoCsPjcXTglGaTmGUxMxAgLiVeKdnINPnI5eKAcpmHg0GClkVfIZiczTIqmSTrEFAmVyqMjUZ5W9fZ1zC4rFDgonicpzSNDYDLnXj674SgpSgcX6sxz+tlByeuwmNZPQnGhQIrXC7u93qxheCxTAZLCI6Mx5GiJ1/LLyUDk0mklJzfbNKv2eS0WAwN2OAvKBC71uu87vXS3zT5Wde5tbubq9ZZh8z663PlPfeQSqV+uVcNw+Czzz6jVCqxxRZbEIlE1vgZ0m63uemmm7jqqqs4+OCDufrqq+ndu/caH/efrd8L1G9ElmVxzjnn8NBDD/HII4/8zXZT0zT57rvv+P7770kmk2y44Yb4fD4Auru7Wb58OX379sU0TaaOHs05y5fzsaLwoEMiuLpQoI9lcUwySUNKbi0U2M4w2M+hMZ/XbHJEpcIQJ+dokGVxRi7HiakUXwNjjDanFgqcFI/zgaJyer2KBjweCDI3m+aIeJK0EJzSbvCI28fzpS4Oiq7FLeU0swIRtrUMUu0ml3vDIFRa0uZ1q5ujXR1MMgr4pM10d4LHW13soneyqWJyh8xyqppiT9lkW6PKCUoKIeAZuxsF2F+kmKEUOZ8Y2Daz7RxRbI7ROnipvZr99E7ubqYZrieQikrRttnENrFUFxtLg7ZhU1EEJRv2NNo86PPzQncXExNJ6ghipskrmkYLWJDLYQNHJpPowO6myUbtNvf7/b9kJvV2coEm5HKcnUxSsqxf0mlPdnhy+7XbXF4sckUkwqNuN/2l5BonPuVVxxF2erXKI34/SdPkO7ebdQyDr1SVU0slPvN4eFHXMYTgbueaRsVi2PREgSf/7MQDLqtW2aLZ5JhkElMItnf6Q5eHQmxqmnyl6+zabvOWs+U3Ix7HtiyioicGY7wTZ/4HZ3v4QZ+PawIBekvJfdkszweDzPD5CAFTymWW+nz8yRlQ38IhpvexLDQp+ZOmYUnJydUq/Q2DM2IxDNkDlN2p3WZfB3P0Z+r7EGf4doBtM9IZvvVYFjVFYVi9zpxAgGGlEo9HInS22/yoadyfTnN1JMJbmkbE2fJb5HYzNRwmKHriRz7TdU6I9vRSbygW+dHtZqbfjwfY0zCwgQ91nfUMgxWqSlBK1pWSwaUSFzi8vZH1OmOqVU5NpVgRj3PZbbexzXbb/Yf3rZSSVatW8fXXX7PRRhuxzjrr/Le3/F588UXGjx+P2+1m1qxZ7LHHHv+t4/wW9XuB+o1p1qxZTJw4kVtuuYWjjjrqr37Otm1++uknvvnmG/x+P/369fsPMfilUokPP/yQZDJJnz59OHXoUIpffMG8ri66FYVBiQRe4LpiEU0ITnVu0gMNg96Gwd0+HykpQUo2Nwzecrvpbxh8oWkMaDZ52uslLiXr2jYX5LIc6SSPLspnuCsU4XtN58p8mj3iHQSBrcw2bl3jvHKOYeEUL1S62D+8FndVurndE+IDRUcKBYRkkdHNYFcHE40Cm8s2A129iArYSzR5RrpZZHahCtiODvZSDGbKPAAniATLLJWFZPgBncv1GAuM1Zypp9i9VcajqjyqBjjGqPKAFmBr22ChrVNHogqVrLQ5plHjaV+Aw6sVPvB6WaWoBIWCYVmoQrAwk2ZhMMhMX09a7WamySoh2MEwSLTbzHEgvjOLRTZvtznEiWO4zolnOCSZpFtRGGaaDPvzSgsICMGocpnrQyH2rFZZGgyyheMIm5VOc1UiwTdS4hc9uJ2HnATWKPBsOs2nTk/LB9yVz/Oz282EYBCvEAxttTCA591ukrZNDQjbNl4h2LtSYVY4jLBtjmg2OaFc5uhUigw9hfGEep0T43E+UFUOMU0mFQqck0jwnqKwlhCcn88zIxrFa1n8rOsMbDZ53u3mhGKRFyIRck7f6O5slvdcLm4IBBBCsCidpix6KOGaEDycy6FJ2UOBF4LRrRYbtVpMCYeJS4lLSrZvt1ni9TK4VGJuKETcNPGKHjrKSckkPwG7t9tcVyhwYSjEcx4P21oWt+RyzI5EuN3lYi0huCGX4+5olNdVFYTg2EaDJU6/Ka3rmJZFXghOqFSQ0EOBAG7N51nHsjjYGR+4O59nI8viqFSKRjDI8WecwVEjR6Kq6n95vxeLRT7++GMikQibbrrp3wWC/f7775k0aRJLly5l+vTpnH766WsMkv2t6fcC9RvUwoULOfroozn77LOZMGHCv0vJTKfTfP311wgh2HDDDUkmk//p21ez2WTZsmW4XC4222wzZl1yCZ89/jg/mSanVqss8Pl6mGMuF2s5Mz2jKhU+83p503Ft3ZDPk1YULotEsKTkrnyegqIwKRoFYHy5xJ/8AX5QVY5o1LnC5ycsbZbk04xOdPBHo83ulTLDI3FiSg8D79x2haJt85ovxMxKmn2DvVhcXc2x/g5+kjBMtFgo3DxndDNBi7GpsDmuXWQ7rYNT1Aan2GXulH4+Vr18LHRmWxnewcUTapCCFDxspUlhc4TWyUVmlp9QmSYiDNZM7jV0LrDL3KqGuKOeYaw/yS3lDCcGkpxTKzPDG2BfJK9IwQDTwA2863azoKuLi+MJXtA0NCHYxDD4RNO4I5tluaZxpRPyuCidpqooHJhI4AIuqVYJO+QJPz3utE3abeZ7vezUbPKW283algWKwnm5HOOTSSqWxQDT5NJ8npPjcZapKvu1WlxeKnFVJMJcl4tN6OlNzYpGeUHTcANnV6s8Egjgs21+1jTWM02+VBRGVKt863LxosuFAdySy+ECTojHsaTkkVyO3pbFHh0dtKXk0lqN7RoNjk6laEjJ9lJyuDMft3GrxUqXi71aLV7yeDg/n+eaWAxhWeiKwmNdXUyNxXhJ01jfcbE96XYzPRwmCTyczfK218v5gQABIbiwUmG5x8MzDvV9E9OkIgSqEPRut1nqcqFJyaGtFvvUapwSj9OUkgvLZQ5rNjnEyZQ6s1ZjWK3GyESCz1SVP0rJOU4wYEtKmorCKAcvdUilwgvhMCnD4Fsn6PHRYJAXHB7iwu5uPnds7LrowUuVFIXDEj0cyisrFVxSMjkSob/PR3yPPTht6lSSyeTfdb+3220++eQTms0mW2yxBcFg8D/9fLPZ5Prrr+eaa67hyCOP5Morr/xN4Yn+kfq9QP1G9dFHH3HwwQez5557ctNNN+FyuVi+fDn1ep16vU7fvn3p3bv334xDMU2TTz75hEajwVZbbcWcW27hswceYMrKlUxMJvnetok4b+W3OZHaKeCpdJp3dZ3TolHCwKPZLDlFYWg8TpieQU5LSg5NJAgIWJpJc204zFsuD2EkXyoKm0qb2fk0+yV6cWmlwNcIbvQF6VQV8hIeq6e51hdlU2kxsFHmeH+KZ2td7OLrZANhcZeZYaDWwRKjm+9QOUNPUhVwr51hpJJkodnNSlTOUBPoAp60unlT9TJHC/FAu4vpapSnLJ1+ukrLNFnHaNGhwDOKl6QCKy1JGIEUkn62BYrGIe0Gj7l8XFbIMCqW4vJ8lovCUQoIEkLQ3zD43OXi6dWruT0QYI7PRwdwVzbL0+Ews91uPKIn7vxd54FXFz30jDowtF4nbBhc78RrXOPQ4g/u6KAmJdcXCuxsGByaTNKlKAw3TY4pFDg5maQKhIRgdKnENeEwu1SrvB4IsK1h8L7LxfXpNNclEnwrJS6HcjDf6+X6YJCg6KGPf6VpHOPMPN2dy1F0iBge4KhWC69t87DHQ28pqQCdlkVdVTmiVOKGSATFttnHMDirUGC4s+12XK3G2bUaZznbkntZFpfkckxPJFiiqnQIwbR8nuujUVq2TVbTGNhq8aLLxRHVKu/5/XTJnjym6/J5VqsqV4RC2MAT2SxeZ8TBpifVucO2OcwZeh5uGOxSrXJONErEthHOYO8jPh/DHaBsL9Okqmnc3dXF2akUK6RkYyl5IJPhVr+fu/x+1pc9IN/n/X4u9PuJCcHNuRwvhkI85HajA0e0WqzQNOpCsKOi8Frfvpw4ZQq77bbbf/t+l1KycuVKvv/+e/r37/9Xgwife+45JkyYQDgcZtasWey8887/7XP+b9DvBcrRFVdcwQUXXMCZZ57J9ddf/8++HAB+/vlnDjnkEPx+P4qi8P7777N48eK/eyvgz5JS8uWXX7J69Wq23HJLvl6xgjNHjuTsQoHjq1XOi8V4UdPYSUouzeW4JB7nLVUlCEwuFrkjHKZu2+Q0jRNrNRZ6veC8pV9QKfO1y81duk5/JPdn0tweDPGs20NNVQjZNntLizGlHAPjvZhX6ObyQIS3VY0tBXwhFJbUuhgV6OD4VoXNjCajAil2t1o8JlyMUVqc1i5yqLuTya08tpScrEWZpDY51ixTBXZWOthVNbnFzCGB/dUOJIKNFJuMLZjQzrM2Fse4O3i5sZqDPJ3cWEsz1Z/k2GqRu709oNXvpKCpqHhsi5rogcauBsY1GmQ0jT+5PTzStZoT4gk+UxS2Bs7M5zk/HqeXYfC1280fHBTRjZkMD4dCLHVWXM93d7Nc1znVeSt/NpOhKQQHOW/lF9dqxEyTs5yt1k0ti83bbR72evljs8nbbjfrmSYNTWNyNsvZTjDlbpbFzFyO02Ix3tE09mq3ubpY5KZwmLvdbjYUPTlPd0ejzHO58P6ZLuHzYQJZVWVd0+Q7ReGwep2CqvK8240pJVcVi3TYNsfHYpj0REpsaprs7USxXNhosFetxjHJJAVgK2B4sciUaJT1222+dbs5oNHgWa+XSfk8N8diYJq0VZV5XV3cGA7zpNtNgh5E0OsuF+McoOz8TIavXS7GhMP4hGBSrUZZVbnd6yUIrGNZBGybVarKjo0Gz/p8+CyLrS2Lk4tFTkwmKcse2v/ptRojEgk+URSOareZWCwyMR5niaaxCXBJNssl8Tg/KAotITixWmWu389OjQYf+HwETZMfVJVphQKqpjG5o4Pjx43j+JNO+odZxrPZLJ9++impVIoNNtjgl6ymb775hgkTJvDOO+9w6aWXcvLJJ/9NW4j/2/W7zRx49913mT17Nlv8Slj7/65cLhc77LADb7zxBoVCgXnz5rHFFlv8t/eZhRBsvPHGbLDBBnzwwQf0Xndd5i5axJP9+3NIr178rOtcUKvxsbNV9b6msYthYAuBbllkFYWmEASl5KBKBSEEaSHwAZs0GjzjdrOfadKlKJwYi/Oa18uCXJoDmg2ywCLNxTGxTiY2KlQEfKq5eK2Y5nsELSm50xMmi2A/o874QIqJzRLnNArowFO4eRkXurTZUbYJI9GF4F215wY+0d2LqaLOV1LnaxRexUVVgi3glmaai9o5pngS9MJme2Fyn+JjWrvAecEOLq9nuToY44Zajh9UjccrWbwCFhQz9BaSs8slLm/WmRsIsEGjwWrbZvtkii1tm0srFVaoKu+4XDQUhS81jbUti5uyWfau1Tg5FqNbUXgjnWZctcquqRRT4nEezOcZYpocmkpxbCrFSMNgcyl5wufjlnCYlG3jsm02azRINpsYts3Lus7UfJ4bsllW2zYjYjHOLxZ5M53mSwcQvJ4QLMxm+cbtZo/OThZ5vVxaLpMVgqsDAZ5zudjDGR9Yq9VCCMH3QN22ucqxad/j9bLQ7WZxdzcP5nKMjUQ4NhZjdqHA7FKJE5JJduvVi4NNk/GtFtcHApyZSKAKwR8ti4yiUOz5wrFK09jaMDizWGQty2JqOMw29TrPZTLs2WiwdyrFD7rOa+k0+5om2zhA2VtLJTaTkhOSSc6PRhlsmiSk5FPnd+23bWq2zeGlEoeVy/wEPO7xcHM2y/xMhld0nUGJBNOKRV7KZFgQCLB1Zyd9gPvyeRZ7PByWSvGhrnN6vc4qRWGR2813qkqnaaID+9RqbGSaLHS7ads2czIZrsvlGBuP88rIkTz19tuMOPnkf+g8UyKRYMcdd+Sll15ixx13ZNmyZVx88cXsuOOOrLPOOqxYsYJTTz31X6I4we8Fimq1yrHHHssdd9xB1Omn/BZ09dVXs8EGG/DDDz+wbNkyBgwYwLBhw3jzzTfX+NjrrLMOW221FStWrMAwDK559FFcffsyrNXCZZogJa+4XIwtFJiSy6HbNuOiUU4uFHg+nSZhGOyXTDKgVuOVdJo/NJsMjic4qlrhynyO9S2bFaqKKuGuQJD33R5ezaXZoN1ilS1pKAqnRDu5ppLjLc2FH3i52M2digfNtnlPaFSAvc0GE/0JzrDqjG6UOFuNMKHdMyt2tjvBPUae76XGOCWGX1ocaVS40swzQulguhpjfjvD2khewM2mmCSkzaVqkB+lwg1qgKl6jB8Ni6GeFE3D4tBAirZlMSicwmtbHBTtwCdhQijCFb4gtmVxeTDEjYU8ZxttXnC7WQ0I2+a2QIATi0WW/sWsWcvl4slcjpqqcmBHB7cHg5xXq2FI2VMA3G42sixsKdm/XGZdw+AT4Bvgwe5uZuTz3OH1MiMcZsGfKdjRKHt1dHBuvc6dpRIXxmLs3asXawnB2GaTZxzkUl4I+pkmuhCsaxjoQvCqx8OmhsHMXI7tmk3GRqN4DIPX0mlOqNfZM5ViTjjMM9kswwyDXXv1YmQyyZRGgx1sm4uiUabGYmxhWSRsG8u2STvopG+AMYUCZ+fzpG2bi8JhLs1mexBKisLOqRQDWy1ecSI2tu/sZIXHw83FIt9qGmPicRa43QxrtWgKQReQVlWkbSOl5ORCgYNqNZ5yufjI2YqencsxORxmQjTK49kscwoFjovH2b2jg1OaTS6p15kYizE0lSImJYPabd7WdV52u2kLgSIlvaXk4FqNiJTcFQiwQ7PJg9ksf6zXOSKRwJaSP6XTDGm12G2ttbh1771ZsHgxk666Cr/fv8b34n8kr9fLiSeeyIYbbsiAAQOYP38+S5cuZfbs2SQcqsW/iv7lC9TYsWM56KCDGDBgwD/7Uv6NhBAsWLCAZ555hi222IJrrrmGSy65hMMOO4yHH354jY8fj8fZfvvt6erqoru7mzufeoonBwzg4liMx9NpFmYyXBEOs09HB2NrNR7P5ZgZifDHXr1YWwhmlUrc6/czoFcvqrrOHYUCD/gD/LGzk61Nkz+l02Db3OX2ck4pz4O+AFlN59VcN9fpXoqWRcKymBKKc0M5yyLNw5bA6HqZE90xjmhXyaHwiVQZ1uppRicEXOyK8SAe1sNiS2lwU72LN6TGec0eB1/INslLmyOMCp3YXNrMcrk7xiRXnFU2PCm8jK/lGKxa7GPWeaiZI6DCkloGv4C7Kzki0mZQvcYOtkHQNLmhUkQC87JpxpltpsQTvKNq1Gybm4NB7shmeTabZVY4zB87OwkJwfhGg7d0nTk+H2lFIWnbRIABjQZxKZnr97Nuq8X9mQxHVKuMiMX4RtN4LZ3mvFqNXVMpzovHuT+f53jH9XdUKsVxhsH2UvK4389NkQhx28ZnWWzYapFqNrGl5CWXi3OLRa7PZqlaFsfH45xeKPBmOk1RCLZJpQirKouyWQq6zu4dHTzi93NFuUxdCGYGg8xzu9mj3QYhSLZaSEUhCxRsmyuyWc4sFpmv6zzs9fJsOs38bJapkQiDEwmuKxZ5sFBgfDzOTp2dbG/bTK3XudPnY1wiQVkIBrTbpBWFMmAKwc+qSh/b5qxikf6GwaXhMIl2m4WZDCMrFQ5JJFji8/FSJsMp9To7dHRwSiLB9ZUKB1gWI1MpxiUSDLBtNpSSD9xu3nS78TiRI/vU6xxaLlO1beb4/UzO53kik6FLSgYmEhxTqfBmOs2Pus7WHR2U3G7m5vP8pGmMTaV4foMNOO/qq5k1f/4aJxH8V1qxYgVDhw7l3XffZcSIEXR1dfH4449jmuavet7fov6le1APP/wwl156Ke+99x4ej4c999yTrbba6jfTg/qPtGjRIoYMGcK4ceM4//zz13h74c94JNu22XLLLZk7ezZv3nYbq9ptjmo2+ULTKDlbe0JKDCnZyjRx2TaL3G7cUrJ/q0XYsrg/EKDTsvArCpqT0TQ+n+e4WBwJvJpL87DPzws+PyeWi5wTDLMdNreXs+wT7cW8UjdvqzoP+MNkhIJh21xg1RjYrrFXoBcP17p5UvczW/XyjJFlLWwGeTrYxmjwrsvL3FY3+7t7MaOZZ5I7xgut1XShMFhPsJG0ub+VZZI/yZaNGkdaDQb6O1lcXc2UQJJ+jTq9BczxhLiymOa4cIpFudUMjXVwdLnMGx4Pb+huIkLgsSzKApak03zg9XJOuCduo69l0XDmY3avVLjCMQOc7zjNDksm+VkIzqzXGV6tcmIiwceqyo5Scl4ux4REgprsWWGOqtWY4/czsFrlxUCAhGnynaZxYzbL805kvBA9icirFYXj4nGEEDyVyeAC9k0mUYAL6nX6N5ucHI/jEoK+ts3e9TqzHWL6qz4fmxkG3+o616bTnJdKkXOQWA+k01wcCvGUx8PGts2D2SxPe71MCQZJAnfncrweCDDT68UrBGPqdVboOh870e4uy8IC1rNtNmk0uDsYBNtmVL3OofU6Q5NJSlJyfrnMkc0mxyUSLFcUjjYMxhUKnJFK8aEQrA2cn89zSTRKwLL4yeXiwD/b2EslFodCZKSkoijcns3yhaZxVSgEzoyTDeyfSoHsIcpHbJtBDp19mGmyU7XKhFiMuG1jCcF+Tmz8hfk89/ftS+cuu3DBVVf90g/6tVStVpkxYwa33XYbJ5xwAhdffDGxWIwvvviCI488knXXXZdnn332NwVz/bX1f8s0/3fohx9+4Mwzz+SFF174T8m+vzXtv//+vP766xx88MGsXLmSm2++eY1uHJfLxbbbbstnn33Gu+++y5GjRuEKBFh8000M6e5mRizGN1KiAou6u3nN7ebCcBgNeLm7m25V5Yh4HE0IXurupiQEg5JJBIInchke9wfoELClabJfshM3kqey3Tzq9bGZECBUdgx1MNpoEJE2V/mjzCun+V6onOqPssjl4xOhsa806CVtVmouegEzvHH2alYIILnQKHOmprOH1sFEq8YudovT7BrHuFNkUbmpmWeip2dodXItyxG+TgbX6mxstdjL10EEhZd0PwFVpWZaDAmlcFsWO0c66I3g2kCQ/S2TE5oNFnp9PJdNc1c4wl6dnfgQbG2aLFcUTi0UaAnBmZEISyIRFmQyeKVkv2SSy8JhTmq32bZe58xYjMf8fjRgVKPB434/i91uMopCp2niEoKDqlWe83h4xOdjU9PkgWyWW/1+xsRirCslr6TTvOr1smcqRUQI7szn+cDvZ5AT1HeUYZARgkf8fmJeL0Epcdk261gWvVotpN/PC24344pFhjQaDE6lODYe58xSiRH1OqclEmybSrGHlLyQzTIpkWC3zk7cwOXlMrcEAlwdCrHc42E3w+BDTSPabGJqGiXLwhCC+3M5yorCmGiUl/x+nk6nCUrJHqkUN/n9zKxU2KTVYlgyydXAjrbNlZUKF0UifBWL8bWicEirxYtuN1Wgrark6MmrOrNQoBqJcEMwyNq2zfOZDItdLobHYkSAZ7NZPvV42DuVwicE02o1VmsaY5JJArbNH2wbr23zjq4j3G6ElDSlZCfTZGS5zPvBILduvz0z77nnrzrq/lGSUvLYY48xefJk1ltvPd5880222mqrX/6+f//+/OlPf+KDDz74lypO8C+8glqwYAFHHHHEv2k2WpaFEAJFUWi1Wr/pRmRXVxeHHnooLpeLuXPnEo/H1+h4Ukq+/fZbvvvuOzbffHOymQxjhwxhv1KJqfk89waD3OT1sr4QzMpmWRgKcYvbTRi4rFjkU6+XO91uvMC1hQI2MDoSobe0WZDNsNTl5tJwBITgoHqVF/wBnsp187TLw93+AHVFIWlbHGKbjKoV2TvaiztLae7wR1gsVBY3MtQQjPKnWFTt4oRAB1/YkoWtLAlsrtTD3KN4uMYscpDd4mXh4jQ9yg3tIvvJFvd6wryvuBjeKHK2O0ZNwjHCZBEql1YLfOPxsVRzc3kpy+BIB8/nVjMummKXep0djBZjowkWdK/mzFjPfE1YCLZqGyxzrOaLPR4uDoUICcGduRxv+/3M8vnwAjsZBgUhaDsF6C1NQ5eSg1otBtRqnBaPU5eSSU6g3pBEgpWKwuhGgzGVCuMSCd5SVbYApmSzTE0kyElJXVUZWa3ysN/PXrUabwYCBByn2ZX5PO95PMz1eLCF4IlMBgMYnEhgC8HjTmbSfqkUhpSc1Wqxc63GCU42VYeUDK5WuTEUYt9qlSWBAFu223zmcnGLQ+7+0baJA0+m08z2+bgzEKDT+fN7LhcnO068e3I5VrrdXOAMDB/damECz7rd9LJtSkDCYQMeUSxydTSKsG32a7c5u1jk2GSSH4Tg2FqN8bUa50ejLNJ1drFtrnRIF8+qKjEhmFYoMDscpgrkVJXdnETd/RsNvne5+FRVaQIXFYv4bZuzYjEsKZmTz9PPNDmosxMrkeDC665jp/8BC/enn37Kueeey5dffsnMmTMZPnz4v1wR+s/0L1ugKpUK33///b/52ahRo+jfvz8TJ05ks802+ydd2d+uer3Occcdx0cffcS8efPYaKON1viYXV1dfPbZZ2y44Ya43W4mHX88rq++olsIRlcq3BQM9jywgkF2brV43e3mAieYbi0nbXRiIc/1sTj7NJu8o+totk1JVZmbSfONqnJKJEo/AdOLOU6JJniqkGaJ5uLyQJhDhA2WhUtRuKCSY2ikFxGzzWpNwxAK0xp5djJbjAh2sMKGS6wqnUaLs70J7q1nGOpLcnUzx0RvnEvreab747xUW00OwV7uFOspcFE9z1m+OPMqaVZqOhf5YzxTWM3h4U4uKOf42e3hQZefkZUiE4IRNkbQZds0pORI20LYNu+6PczvWs0F4QiLXC76CsGEfJ4rYjHWb7f53OslYhisUlVuzGb52O3mNr8f6Ww7WcBAh8/255meQxwywVDTZK9ajbOjUeJSYgjBwfU6D/v9nFAsMicSocM0KWka93d1MSmZZBnQB5iXTvOYk6ibAOZnMnzidnNyOExACGYWCvzkdnONg/HZ2TTRpORDXadfu80yXSdqWawjBMfl84xPJKjbNsc0GpxVqXBcIsHnisKQZpNJ5TLTIhGedLnYQkquzuW4Oh7nNVVFB850imfEsvhB1+ltmqxUFIbXamRVlSc9Hix6hsBTlsVQ5/9/j2Nj3zeVoghMbDbZv1pleDJJXlHoZ9ucWCgwPRajX7PJ514v+zWbLPJ4mJbLcXs8TsmyaCsKj6fTPOH1crvf/0vu1XeqylHxOC7gkVyOuqIwJh4nGY1ywAknMOzkk391IkOxWOTyyy/nrrvu4tRTT2XatGn/IQnmX13/slt8wWDw3xUhv99PPB7/X1GcAHw+H4899hiTJk1i7733Zu7cuey6665rdMzOzk48Hg8fffQRqVSKWfPnc9qQIQxbvpzNWi3coRBP+nwcWq8zuVTipESCC8NhDq3VmF4uMy0UYloozD71OpNKRc6JJ3hHUQgKwQpNZWIswaO5DE8HAgwNx5lRLdGQgutCMRbmu5kcifGeorO4mmWB5kbH5vZqjrG+CG9pLjYz2yxR3NQlLKp2c0CgF2iSOfUsa0uLk8wqY/QoT9YyrC8tdrUNxriiLNc8nNCusUTzs7VtMLld5rRQB4+WV+O2LI70xWgCp/mjxBSVsm1xfSDE6c06c9xens2leTIU5hm3l9sz3bwcd7FNMsVeUnJRtcpV4TBZIbAUhbd0nbVMk4cyGR7xeDgpFqMDWJTJ8J7Xy16pFCEhuKRa5Ttd57REAo+UbGHbCCn5VNexvV4UoC4le7VaDKxWmedgjU4plTipXmdUPM7+ySRHOiGAU+Jxtu3oYEPgYQeYekQySV1VOa1e52mPhxe8Xj7zeultWWSEYNdymbyqsjgYpEtVuT+TIWnbHJBKsTQW465slk0si4OSSe7z+RhpGFxeKDA6meQFnw8/Pby964JBZvt8vK1pbOvEjfRrNAj5fHyqKHhsmxsyGV70eLgoFMILLO7uZrWqcngigRu4tVjEBk50+mUDTJO+hsEtfj+vuly0hWB7w2CVrqPKntTXL1wuNjFNLigU+CEeZ2Ikwh+bTR4vFLgrEGC/RIL1gCWZDAvCYXbo6CAoBFdUKrzq83FOMsk6us5m22zDOTNmsO66667R/fNfybZt5s6dy4UXXsimm27Ke++9xx/+8Idf9Zz/m/UvW6D+r0hRFK666io23HBDjjjiCK6//nqOPfbYNTpmJBJhhx124MMPP6TRaDB7/nyunTqVK+fN44Fcjk3bbQ5IpXiio4NT2m2uyeUYnkqxndfLXrbNC9ks4xIJtk11cJRl8nomzcXhMOPCUS4oFUhYJk+4PZxdq3JlMEITuL5SICxtVqg6x9WqDA71gE0XlNLkgI9dXk5qlBnqT1ESCo9UuwkDa2Hzsy3pJS3awN16kPVsi9cUN+tbdWJGi/mqj7nVDJtLk890D4+qHrZrN/lKC7BjoBfbYPGBqnNPMcuLgRBf2nB5McMhsQ72rdfYwLYYkuxkh2aTnyyLAfEkkxp1iqrG0x4Px7TbeKRkaiTCiEqFcdUq5znFoh89K6RL4nFGJxKkNY3hzSaL3G66bZt3NQ2fbVMRgrGFAj+rKheFw3zmcrEgne4ZcO7o4LFkkluLRfq12wxKpbgtFOIg0+SMQoGz4nHeTSapqCon1+s86Pfztq6zUtNIGAYWcGS5zNeaxkKXi6ht81w6zasuF+dEIgToGZBd7aQvu4GLq1UEcEoySRDob1msbxg843ZTDAZpAms5K90tmk28oRALfD72bDS4ulhkfCTCyHicPxoGbxQK3BsMsksqxTpC8GQ2y6ORCHt2duISgvH1Om+4XFwTCmEqCn2lpAb4TBPNMLCk5ENFYUKhwF6tFoNSKc6MRrk4n+fAVotjnX7ZUNNkZibDGckkO3V2Egeuy+e5KhbjvFiML10uDmm1WOpyYZgmGyoKH3V0MGDaNNweD+VyGcuyfrWt/Y8++oizzz6bH3/8kRtvvJEhQ4b8vp33X+hfdovv/6KWLFnCkUceyamnnsqFF164xl9+0zT5+OOPaTabbL311rywYAHPzphBul6nn2nSYVm85XLR1zRZoar0M026NY3d6nXm+3zs3G7zntvNdu02yzWNiwp5xkdjFIXgumqZ3Rp1Dk110rBtNhCQFwpDWnWGVMscGO8kKyXXNctc6Y9wRr3EgFad/cM9nLjnamkWaF6e8YbYt1nlBa+fulA5ul1jYKPCwcEO9jQbfK66OalV5WZfmKfKq/lCaBzljbOuEIxslrnJG+aV4mrm+YI85fIxJ9/NEdEOBlVLvKl7+JPuIqKo6E7cxvxshutjMVYrKgeUSlwdDtOQklnFIhuaJsekUgjADxxYr/OQ38/Z+Ty3xONopommKDze1cX0SIQXXC7WkZIFmQwvOcUiIgRzMxm+crkY62zLnVGv01AU7vV6CQMh2yZpWfysaexVrfKQw93bxrI4u1BgVCpFt21zVKPBpEqFCeEwS9xudndoEzdHo9zjAFOvzGaZE42yTFUxhODQVou3dZ31TZO8qrJaCOrAiZUKHZbF9EjkF9r49u02Ax3a+BXlMgOaTY5OJvlGCA6wbcYWCoxz4MFSCE51YtH3qtVYGgyyQbvNp5rGtbkcTwYCvKLrSNGT7NylqpwQjYIQPJfJoDqYIykll9VqbNRqMSqRACH4g2UxsFbj2lCIHep13vX52Knd5n2Xi5mZDNMdgnxE9CTdPu/zcUE8zoQLLmDQ8OEoikKz2eSTTz7BNE223HLLXxIB/hHK5XJccsklPPDAA5xxxhlMmTLlV5uh+kfqiiuuYP78+XzxxRd4vV523nlnrrzySjbeeONfPjNy5EjmzJnzb/7djjvuyNtvv/0PuYbfC9T/MS1fvpyDDjqIHXfckVtvvXWNHYq2bfPll1/S1dXFVlttxeuvvca9U6cy+5tveMHjYXYggAU8msnQFoLjEwlMKXk8l8MrJUf+Ocaj2GOcODceZz3TwtJ6mtX7ttucWsxzYCJFFsFzhQy3hCJUVJWJhRz7xlOsLy3mlzM8ont5yhdih3aDV11euhE8Xe4mimTvUAcKkiXVNACn+OK8L1TeqKZxASeHUliGwVe6mz+abQqqxuxympsCUb4TKlPLWQaEUniEioqkbNuc1G4iESz2+JifXs3EeJKKlOgS3nZCCh/PZVnh8XBxMMTatk2BnhTZzW2b0c5WWF5KxlYqnNhoMDYa5U1dZz/LYlo+z7R4nJdVlbgQTC4WuSUcRnHwUTu1Wryr6xxVq7Hc4/mlwT+zUECR8pcG/4P5POubJns5HL8rq1V2aTQYmkrRDewiJSc6c0kx5yViqFM8TykUeDAaxWeapDWNB7u7mRsM8rjbjUsIFnd3852mMcxJo30yk8EWgkMTCRTgnGaTvq0W46NRglISlZI9mk3mer0MqlSYHwrRxzAo6Tq3dXVxZirFt1LS34luv9Xn465AgD5S8kgmw+seD2eEw0SE4LZslo/9fq71+XADB7fb1IXgA12nt2XxnRBEbJukEAwtFpkci2HYNkc2m5xVLnNsMslXQjCs0eDcSoVro1Hm+nzsf8ghjJs+/d9BWf/8XV+9ejWbbbbZ3w19/Y/unTlz5jBt2jS23XZbbrzxxn/zcP+ta+DAgRx99NFsv/32mKbJ5MmT+eSTT/jss89+KbAjR46ku7ube+6555d/53K5iMVi/5Br+L1A/R9Ud3c3hx12GIqiMHfu3DW+0QBWrVrFV199xaabboppmpxyxBHE83nuSKf5StcZFY0SccCabUXhxEjPbNA1pRJrGwaHO1Tvebksccti71QHEsnj+Sz3hiKs1DRGVCucE4oQkzbP5bv5QNOZHI6jCMG+ZpOnNA9PFbsIS8nOkQ58wJJyN0/oHh70hokg2aHdQAp4WffRG5u1zDZnN0ocHUzxpRQ8X03TS0oOD3dyfiVHt6IwzRMmqCgcZTR5WPfwXK6Lt71+bvSHeDazmjOjSZYLgVQ1qqbJurbNfbksM+IJlqsqiiLI25IycE8uR6dlsZ8zZ3NjqcTGhsFRTqHeVkoGVypMj0bZqtnkE4+HPZtNXvF4uCKb5cpEgqoTL76gq4vZgQD3+3xEgUXpNJ/qOsdFo3iF4MFslpKmMSoaxSMEI5tN4pbFDX4/a9k2bSHY1DD41OXiuEKBWU4cRh/g2nSak50wyt0Ng+sLBW4KBLjH52NjKXugt4EAl/p8RIXgikKBpYEAz7tcqMAOhkG3oqACMcviXU1Dk5IDHGfi6Y4zcXy5zNHNJkMTCb5RFE5oNDitUmF8LMbLmsaWwCW5HBfF43yrKLSF4ORajYd9PrZutfjE48FvmvyoqowvFOjSde71+7GAu/7CXNL+SydeKkVeCMa0WhxWLnNyKkVCVbE32YRzZs6kX79+/+l3ffXq1Xz++ef06dPnvx3N/t5773HOOeeQzWa57rrrOPzww//Xb+dlMhlSqRRLly5l9913B3oKVLFYZMGCBb/KOX8vUP9H1Wg0GDFiBO+99x7z5s37h7y5ZbNZPvnkE9Zdd12SySSTRo0i+f77vK1pDKvXWeD1sku9zmt+P/3bbT7XNA6q13kpEGB90yQnBC7ga1VlfK3Kuu0WI8NR1gKeznbzJ93F5EgUDTiiUeVhf4i5+TS9bIsdox2sKyRPlNKcGknR3zJxI3lWdVMWsKDUjVvCHuEUUWBBuSe8cGCoExPBSLNBb7PNHd4Q80td3KP7uMETYGcBgyolLgnFeCm3msVeP7f4QszIZzgpHKcuJH2FQsuy2L3d5pxyiZHJFAHDZJXHQ9U0UZwZsE81jWHxOD4hmFytktY07vd6iVsWNhCWErcQHFYqcWU0imXbDGo2Ob1c5jhna+zPb/sXRyI84XKxrXSCCyMRFrhcBIVgYrnMY4EAVaCgqmxsmnyjKOzTbFITgiVuN5aUXFAqsbFpMjKRoCElNxQK7GoYHOzQx89oNjmmXGZ0KsUKIegHnJfPMyUWI+g47wbV6zzp9TKqWGRhJELdtsk7A7Gf6DrXB4NIIXgmnUYB9kulkMD9uRxr2TYHJ5M0gWGGwf7lMmPjccK2jaGqDKnVuCcQYESpxEPhML1Nk580jQe6u7kyFuNNRSEqehKGX3O5ODcSwe8MJ3erKoMdJ96VlQoKcH44jAfYzLLobxjM83g4tVrl0Q02YJ/jjmPEmDF/c5GoVqt89NFHeL1eNt98c3QncPG/UiaTYfr06TzyyCOce+65nH/++Xi93r/rPvut6s/hip988skvRrKRI0eyYMECXC4XkUiEPfbYg8suu+zfJAiviX4vUP+HZds2kydP5vbbb+fBBx/8hyRtVqtVli1bRiQSoV+/fpx3wgms/c47TPz5Z05PJFjm2IAfzma5MRjkXq+XPsAT6TT3+P3c4vcTUBQWpLs4L5nClpIuRaGvYfCRy8XcbBpdSvaNJ9nGtri7lGNYvJO9jRZpRWGRotNbSB4sdFMDdo10sLW0uaeSYanqYnogSlsoPFdaTQWFIaGeB+ZrpS5UYGQwwVeKSl9gU7PN95rObYU0twWj/EnRidsmSxUNhMKUapn7AkEOr1YY3KgzONlB2DD52eXCtCy2N3tWHrOiUe52uwlIGFGv85jXy0H1Ol/8ee5GCO7K5dCA4xwi+CO5HOtaFvukUtSE4Oxmk/0rFY5LpWgAvaXkhFKJyyIRdqjVeNvvZ5dWi9c9Hq7NZLgxHucHKRGKwlNdXSz2eLgiFMIleuLWs4rCwckkmpTc6cz8DHe25Q4wTbZrNLg8FGIjZ3Wyq3Psic5ckWZZBBWFuV1dTHDiMzZytuEWut1cEA4Tpyd+5VO3m7GhEH4hOL9aJadp3OX1EgJ6WRYRy+I7TWOvWo1HAwGClsUmUjIhn2dUMklaSgY1m0wulzk/HOYFt5tdLItrcznujES4xe1mLSG4LpvlwUiEpbqOpCf24n1NIwSYwI9CYAKHNBocVKtxxrrrssFuuzH92mv/W0XCMAyWL19OpVJhyy23JBQK/dXPWpbFnXfeySWXXMIuu+zC9ddfzwYbbPB3n/O3Kiklhx12GIVCgddee+2Xnz/yyCMEAgH69OnDt99+y5QpUzBNk/fff/8fQt74vUD9C+juu+9m3LhxXHPNNRx//PFrfLxWq8VHH30E0JMtNWsWd91yC+NqNU4olzkrkeA1VWU3Kbksk2FmPM4zisKWAm50snYu9frY17a4Op/jGbebqaEw6wMPZdMc1NGLcbUqS90e3lEUdpA21xUyvK3pnBqMsb4ieKzQxYGxXpxZrzDP4yNmGbytu3m0kGaZx8e1niBNATdW8rzj9fGBqnNYrcQV/iimbTO/lKUXNkdGO9izVuHFQJjvLZvdjRYXVUscE09xXrHAtqbBPvEOQkKgS0ndtjmnUuagZpPjUykyCCwh2K3VYqnHw6Pd3dwYCrHI5SIlJc9kMnyoaYyIxQgKwc2FAhldZ3Io9EuceMS2ed7tZlMn/LC3ZaEqCmfkcpybTFK3LPY2DC4rFDgtGuVdXWePdptrikXuCQa50etlPSG4zbFSz/Z48ErJ6fU67ziEblsI/JZFg54Ij/WbTe5x0EOjazUOaTQ4JpkkJyXnVSoc02gwJh7nXVXlYMvi/FyOC5NJlioKSSGYks9zUzSKbdt0axp7tFq8qescWq+zwuPhc0WhAVxaKOCTkjOjUUzg3nyeTZyojrKUXF6tsmejwbBUilXAzlJyqjN/5TNNcprGsfU69/t8HF8u82Q4jMc0Wa2q3JHN8pLXy31eL0IInuvuRioKe3V0sOmmm3LRzTezzjrrrNF3XUrJd999x8qVK+nfvz+9e/f+d5956623OOecc6jVatxwww0cdNBBa3TO36LGjh3Ls88+y+uvv87aa6/9Vz+3evVq+vTpw8MPP8ygQYPW+Ly/F6h/Eb300ksMHjyY0aNHM23atL856PCvybIsPvroIwqFAkIICuk0z159NaFcjlWKwkGNBo/5fBxRLjM/FGJ/Z5ByZKnEPeEwJ1cr3OUPsEmrxSq3m/syaeaGw9yhuzir1eSESomrwhGe1l0EVZXr82lOiKZ4ON/NY6EoD6gax9kGZ5XyfC8UDg0nGNmqc3azyteKwqBQkp1sk9mVnmyoXUMphBA8UcrwjaZzYTDK7GKa08I9jrfrKkU2t0wOj3XwcL6b1YrKiFCMiKKwk2nwpqpyfzZDRMIRyRR+AaaEiGWxtpRcm80yNhrlHV1nT9PkkkKBS+NxXtI0XPTEps/1++lrGHzlduOzrB4uX6lESVV/MZvcmcuxtmlySCpFHbi1UGA7w+jh+CkKwwyDEcUiJycSlITAKwSnF4tcE4mwk0OT2NJxsM3IZpkXDvOuomApCvPTaVapKqc57riF6TReYA9nW25GtcpmzSbHJpO0hWALy+JIJ0F3q0aDj71eBjSbvOj0y65y+mVCUZjf1cV9Tg8rBCxOp/lSVRkaj+MVgoeyWRqKwvBYDB0Y0W7TxzCYEQzS27apC8EO7Tavud2c6gx+B0wTv6Jwb3c3pycSfKgobG5ZzMnleMTrZUYwSC8peSSb5V2vlwnhMOv06sUpl1zCbnvuuWY3zP+jXC73S+Dn7rvvjt/vp6uriylTpvDkk09y/vnnc+655/7qvL5/hsaNG8eCBQt49dVXWX/99f/Lz2+00UaMHj2aiRMnrvG5f5+D+hfR3nvvzVtvvcWBBx7It99+y+233/7f3htvt9usXLmSQqFAIBCgVquxx4AB9N14YyaMGsVt332H27Z5zOPhAb+fy3I5dm+3eSeV4uZAgEnFIoc1Gzzt8/OOy8UBRpuGgEfdHo5tNrjb6+MLobDK5eLFTDf3hsIMDsW5rZRjbdtmNYKQlLypuRkJDI91cG25wGXBCGtbJtcHozxUyjI9FONh3cNjgQi7WCZvC42mgB2MFlg2g4IJbivnqaoaV0biPJddzeB6lYMiCdZVFMbVazzkC3BJPsu3ms7QZAdRIGXbZGzJlFKJvdst9k2m2DqV4kjT5A5nLmlyOMx7us6OztDqjvU6S3w+lmoaMdtmfjrNSy4XEx0c0HPpNBlFYfBfzCEFbJuzEgn8wIa2zcGtFo95vbSCQXJC0Nc0qeg6m7Tb+IRgsdfLFobBDbkcM4JBzohG6WfbvJJO84rHw37JJDFgbi7HRz4fB3R04BGC41stakJwfSjEWn4/PilZ27KQQiBsG0VKlrlcHNhoMKFYZEUiwRnRKIfVakwtl7kmFGL3VIrNgBczGe4Nh9mus5MgMKNS4Xm/n/HJJE0h2NE06RY9cRqmoqDYNl1SMrpaZUCjwcsOt3BKocARzSbHJxLskkpxTLvNbcUi5yWTbJtKsY6icI8zjHxOMkk9mWTI4Ycz+pxzfhW2ZjweZ6edduLwww9n8uTJDB48mFmzZrHvvvuyfPly+vTp8w8/5z9bUkrGjRvHE088wSuvvPI3FadcLscPP/xAr169/iHX8PsK6l9MmUyGww47DMuyeOSRR/6uZqZt26xatYpvv/2WSCTCRhttRCAQYPXq1Xz22Wf069cPv9/PaUOGkP7uO27NZklZFockkwhgYqPBntUqg1NJqhImNBscVS5zdDLFl0Jwd6nAdu02Y6Jx/qRpTKsU2ckwOCrRwdBGjUe8fnY1WqRVjTvzaWZE4jysqFzbrDGgUeM1Tef0YIyrakX2N1qsEgoHhxMcY7U5v1Lkfd3FmcE4AhhiNnlJc3FiucjBRovhkQTLFZUdgfXbLZa5PTyc7uLRQJCZPj9eBBubBstVjae7uzAVhf0SSVTgMMNAB952uxleKHBTJIJh2wxuNhlfLjMmFuN9TeMQw2BaocA10SgPulysA1yVy3FnNMoHqoopBIe3Wrz1F3NIPwlBCxhRrbK2YTA1GqUtJTOKRXZ3YjjSTu/nyHqdk5NJ3lcUdpGSC7JZJiYS/CQEphCMrVa5NxBg60aDZT4fKdNkpaoysVDgK7ebR73enm24XI6IbXNEIoFBT8BfP9PkwFSKrBCc2moxuFzmhGSSghAkpGRsschlkQjbNBq85/f/gsG6NJvloWiUL+gpSI+l03ylaZwbiSCBFzIZVGAvZxV3Y6lEX8Pg6GSSNrCzbXNYucyUaJT+rRZfuVwMbDZZ6PVyTTbLvHXW4fv11mPGXXf9wxrz/5kWL17MtGnTWL58OZdeeuk/ZJXwW9Vpp53GQw89xJNPPvlvTFbhcBiv10u1WmX69OkMHjyYXr168d1333HBBRewatUqPv/8839n4//v6PcC9S+oZrPJqFGjePvtt3n88cfZZJNN/tPPSylJp9N89dVXqKpKv379/h2ctlgs8uGHH9LZ2cn666/PRaefTq+XXmKpEKxrWVSApG3TUhR+FIK4baMrgrBl86Wmsk+rxQKPl7iUbGCZnFvIMyyRJCdhdrnIdu0Wp0djvKZqPFzKsb5lcWCyF2uZJrqqcEEhy6hoirMrRa4LRZhdSDMmmmJkvco9vgDP51Zzpz/EA7qX9ZA8XkiTFQoHx1J4EWxkmaQRHFOrMLTVYGwsyadCAUWwkWFS0DXmdXfxstfHmYEgfiE4pNXiFZeL4U7xOD8axZCSh3I5+lgWBzgsuSGWxaBSidMSCSKWRUFVGVqv84Dfz+mFAvdEowRMk4ym8Uh3N/c5c0hux/CwUlU5xiHGP5HNIqTsKfqiJ6Rwi3qdMxyKt0dKDqrXmRMIcEypxMPhMOsZBl26/gu372NgLXqgrk+53VwUDhMBnslk+F5VGRKP90B/SyUsITjPGRnY2rLo58TP79Jo8KbHw4amSU5VmZHNcmYySdG22cy2uSub5aJQiCc9Hja1be7LZlns8XBeKERcCO7OZvnA5+Ninw+fs4orKwpLXC46bJui832xFYVjikUui0bBttnTNJmezzMtmeS1eJzLbr+dbbbb7h98h/x7/fjjj0yePJlFixYxZcoUotEoZ511FhdccAGTJk1a4y3z36L+muPxnnvuYeTIkTQaDQ4//HCWLVtGsVikV69e7LXXXlxyySVr3Pv75Rp+L1D/mrJtm6lTpzJr1iweeOAB9t577//wc6VSiRUrVtBoNNhwww1Za621/uoXt16v8+GHH+L1etlss824+Lzz+PG557j/xx95+i9cZi93d/ONpnF8vGc182K6m25F5fhkEktK7ir0zCdNj8bobVmsIyU6ktWKyvhSgTHRBAKY0KhyaLXCabEkbwjBY6U8G1smt/uDzHJ7uadaZDujzTM+P5PdfnYBrsmnOSuWYkOjxZcuN6skVBWFlzNdNITgoHiKBFATPTH3hzaanFKrMCWe4GVVRSDYs9XkZbeH+Zk0H2sa54Yjv8wl/eB2Mz4c/gUPFLMsPnW5GFgu82AwiNe22cqyuDCXY1QqxXfAwc0mF5fLXB0M8pDXy5ZScnM2yxPBIFd6vcSE4JJCgVeCQV7SdQSwtWPbdwMpw+AVl+uXbK5Dq1XGJJNUbJvTKxVGNRqMjsf5QFUZ3G5zfrHIFbEYj+k6fYGrslluicV+WcUd02zyisvF2qZJVtMoAHVgWK1Gb8PgYocmcXmpxO6tFoemUmSAKZUKhzcanJxI8L6qsodtc0Eux8REgpVCIITgzEqFOwMB+rfbLPd6Wbvd5ktV5YxSiW/dbuY7ANlbczk6bZtBzirurkKBzQyDYakUPwcCnHjWWRw1cuSvnjjQbre58cYbmTlzJocccggzZ878xSixbNkyBg0axPTp0xkxYsSveh3/qvq9QP2La86cOZx22mnMnDmTkSNH/vLzRqPB119/TTqdpk+fPqy33np/E+HZMAw+/vhj2u12D3liyRKunjCBdVstrs9keDEQ4HKPh4SicGMuxyq3mwsCAYLALfkcPttmUDxBAMkTuSwx22aXZAcCyevZNEUUDk+lMG3JtaU8CnBeNM4mlolXCA6plLgkHOPQVpOlHi+35boZFu9gHcNA11TuznbznO7mgmCYAabJVaU8c4NhHvF4Sdo23wIVBE/mM4RtyRHJFJptU1MUepsmXkXhzkyG2/x+bvX5WU8ILsnluDYWw2XbdOs6mmXRLQTTikU0KZkUjWJKyYO5HBtaFnunUpSAKY0GA6tVjk2l+BnYBDg9n2dyPM7arRZfezwc2mjwpNfLOfk8j0ajFG2bsqJwXzrNRy4XMxzr8/OZDAqwdzKJBO4qFlnPMBiUSlEBDrYsjiwWOSORIO6s4o6u17nP7+fUQoF7o1GipkmXpvFQdzf3hkI86XLhFoIXurv5XlU52lnFPeWc6yAHNXRms8lW9TqnxeMEgABwaK3GHYEAR5VKzAuH6eeEIs7p6mKas4qLi57o9ufdbqaEwwToAer+rCi/AGSvL5XQgPOiUfr5fCT32INxF130DyMV/GdasmQJ48ePx+PxMGvWrP9wTKNQKBAKhX7T0Tz/m/W7SeJX1t/Cs/pnasSIEfTp04dBgwbxzTffcOaZZ3LRRRex+eabs/POO7PLLrv8XU1nXdfZeuutWbFiBe+88w477L47Vz70ENeMHcszlQr3+P0c3mrxktvNd4rCLcEgOxkGyzWN7xSFu+IJ9nBiGWYHQ7zi9XJcq4WQsG+qF21gZrlIn3aLwxMpNAmP5dL0tm0OiKd4IxBhYTZNStp8o2ocEElwZzHPdu0WY+MpBsQ7CAJzijnGRhN8raj8BPxo29hSsjiX4V23h8HxFBtJG0NCHcHUQpEB7RYjEskeCKyEi8plro5EKAqBIQSfKcovINb3dJ2TolF8QvBwNktO0zg6lcIDHNlq0WFZ3BAI8KzXS10IdjUMvna5aNATgb5S1+lnmpxTLPKDqnJpOMxWhsHcXI6nPR4GJxJ00BPM95FDSPcJwYRajYKicHY8TgRYy7ZJWRaf6zrLXC5MoCx6QhaHlss87/FwTSjEwHqdy0slrgsGOTSRYDMpeTWd5ulgkB07OogJwa2FAq/7fAxNpdCEYG/TpCIlSzweVioKGiBsm80ti12cROD7AgFGlcucXqsxNhrlsGSSAwyDOwoFZkUibJtK0UcI5mWz3BOJsE8yiaKqnNJs8q6u82AoxB9Uld59+zJ0yhR22223f/g98P/q+++/Z9KkSSxdupSLLrqIsWPH/tWXs2g0+qtfz7+yfl9B/cr6W3hWvwUtX76cPffck1arRd++fbnhhhvYfvvt/9vHk1Lyww8/8PXXX7PpppsihGDEQQcx7ocfGFytMj4WY6mmMbDV4vJSibudKIntLYvb8zmec7uZHAqzHjA/m2aex8PVwbDDg+vigWCI591e2gLOKhf5wOfnE00nIiW9bIve7TbzvX42tCx8SM4o5RmR6KBtWZxUrzGyUeNRt5fLAiH2sy0uyuc4LZGkf7vFT7rOMqHQlvBaNk1ZUTgs0fNQXsu26bBM8qrGrO5uTnZ4b38eNL02GuUBl4uEEEwtFLgzHMYG0qpKH9PkW0VhSK1GXQge8fmwpOTKYpFNTJOjkj2sv2uLRfZstxnmZC8dbZqMLRQ4K5nkM0UhDJxfKHBNJEKnafKly8VO7TZv6zonlUp84PPxrqrSFoKb8nk8UjI6HseQkvvyefqbJvulUuSACxoNDqlWGZFM8p0QbAyck88zORYjbpp873JxRL3OAo+Hk0olFoZCFIGionBbNssPqsrFkQi2lCzIZonYNnt1dGBIya2lEn9otznK2QIcaNscXyhweiJBwLIoqiojajXu9vsZUS4zLxwmbBis0jTuzmb5ye1mYjLJKePHc8yoUb86KqjZbHLddddx7bXXctRRR3HllVfS0dHxq57zd/3n+n0F9Svr+eef/zd/vueee0ilUrz//vu/8Kz+mZJS8vzzz3PuuecSCoWIRCIIIda4ySmEYN1118Xr9fLJJ5+w3nrrMf/VVzl/9Giue/ddDmm1WJzNcnIyyS4+HxvYNk9ls5wfj7NnR0dPbHcmw53RGDukOllbShZm0j3suniKPwh4ItNNVQj2SSRZV0qeyHQD8MdEBx63yqJMFx5g/0SKQdEktxdybGwYHJ7o4Dmvj4qicl69yp2BIAqSTVst5rrdbGOavFLI8lgwxMBUBz4hWMuWZKTkpGKBXdpt9k91sEcqxaRGg91rNY5LpfjI5SKtaRzdbPK014vXNGkLwSop8dg2N2YyvOhsZ3mF4IV0moIQHJhMogNXVSqkTJOT43F0epA9k+p1ZgWDlMNhvlRVdmq3+dTlImWaCEVhuaoSt20uzeW42+fjmmCQJD3BfCscc4VX9KTaNtSePp8LOKTdZsN2mxsDARa73RQUhQHtNh848eqGovCzqtLLsjijVKJbCK4LhdhQShZmMix1uTg+FiPiAGS/dbs5MJnEIwRnNBpoUjI+FqNDSgJSsp1psszlYgtNo+Ugr9aTkiGVCi95vdwSCLB9q8Xt+TyL3W4GJZPsveeePHX11UQikTX6Lv4tWrhwIRMmTCASibBkyRL++Mc//urn/F3/tf7vWU9+4yqVSgD/I3vof4tmzZrF8OHDGTNmDJ9//jlvvvkmG2+8MXvttRefffbZGh8/mUyy/fbb89NPP7Fy5UqunjOHfY44grbfz/2BABkh6GcYtITgB0VhlarSYdkgekgES3WdzU2TgqKQVhQujkQ41DL5UVF5XXcxpKMXowwDS1GY7fNzcEcvjrJM1hNwXTjKuHiKmBD0RfKW28O3qkpLCL4VgmmFHMNrVfZpNtkpkaKsaTyfy/KTpnOfx8uTPh/SllQtm4fT3TySzTA+EmWXjk6Ob7U4rd3m7kCAh/x+WkBOUdi71eLsYpG+hsGYeJxNm01eT6c5vNlkx1SKOyMR5udyDLQs9u/o4JiODsa022whJY8EAlwXjRKzbQKWRd9Wi0S7DVKy2OVibKHAzFyOsGkyLB7nwEqFN9Jptmq32a6jg7cCAV7IZtnWttmts5NTk0mm1OtsZNtcG4txcSzGppZFxLbxmSZ120baNp8qCqcXCkzI57FsmzOjUcbm87yYThM3TbZPpVBVldcyGdYGduzs5NJYjOvLZXoDE+JxpkSjDLAsolKSk5IVqopq23RLyahikRMLBUq2zVWhEJfkcjybyVC1bXZJpdi51eLtdBqXqnLA2mszd6+9mPvccxwzdiyffvop1Wp1jb+Hf03ffPMNgwYNYsyYMZx33nm8++67vxen35B+3+L7H9Rf41n9M5XP5xFC/Ju9dCkl06dP54YbbuC+++5jwIABa3yeVqvFhx9+iKIobLnlljxwxx3cdsMNvLx6NUHb/iVX6N58nq1Mk+GJBMsVhSsrZfZrNpkeCvOU2834Wo1j6zXu93i5Lhjk6FaLCZUSS3UXZ4cj7GxZzCrk+FFROCSWYF3giVyaFrBrMoUuBffle6JAhiZT9JY2poSdWi3e8Lh5NN3NGbEE7ykKh7RaTC+XuCcSYbbbjYrgsFaLJS4Xx1cquGyba8NhDCdeZG2HrVcWglNaLQ4ulzkhlUKVElMIRlar3BYMMqJY5NFolKSznTWnu5tHQiGecLlQHVNC2oGhCiFYkM32/I5SKUxgTKvF3tUqo50kXpcQDK9UuCkU4qhSifnhMJsYBst1nbu7u7kpGuVPqorLwQEt13VOjUZRnFWcDeybSoGUXFyvs0mjwchEAiEEfR36+lXhMHtUq7waCLBzq8Vbbjez0mlmJBL8ICX6XzABLw2FfrHIFxSF/ZNJdCm5rVQiapocl0yCEOxhmuxdq3FJOMxRzSav9u3L4aedxuCjj/7le7hy5Uq+//57/vCHP/xDt9vq9TozZ87kpptuYvjw4Vx++eUkEol/2PF/Tf0tfW0pJRdddBGzZ8+mUCiw4447cvPNN/+vS+/9vUD9D+pv5Vn9VvTAAw8wZswYZsyYwYknnrjGx7Msi08//ZRKpcLWW2/NZ598wlVjx1IqlTi1XqeXYXB+OIwf2NY02b9WY2o4TC/bxg2MLRaZGI2yvmlS0lQuz+U4J56g0zBYrevMymW5MBYnbBqscLm5vFTgtmDo/2vvvsOjKLcHjn9ne0+yNaFJV5AOEgVFsFBEITRpShEQEKVIUUSRIiCCikgXEQsqIIIFsV4RrkhTQJooTaRlsy272c3Wmd8frNyfV6+NEoLzeZ78kc1m5mSzT07emfOeQ6VEgm06HY0SCXYqlXQPhdClk0tSknjd66GqKNLN5uA7hcD9sTjtQkF6OJxcX1TEerOZ8skkJ5QKPjidz4Z0BwiLILCioIDDGg1DsrIwcGZ0RYYosl6r5cZwmLUGA5mpFJWAxwsK6OdycUySaBWPMy0QYLbJxFKDgZqSxKJ0leNYoxGrIDAlEOBbg4E3tFo0QO1kEoUkcVylol66dVRGKsVVksT9Ph/3Op14RZG8aJRHg0Eey8jgA62Wa1MpnvN6ectoZIrRiEsQmOP18pnFwqtaLSrgtngcryBwVKEgRxTZr1RiEUUqSxI9AgFG2u2ERZEu0SijgkHus1rZqlLROh5nSiDAkv/XE3B+uifgEp0OLdA/EmGPRsMRpRKddGZarkaSKC+KDAwEeKRSJa644QYemznzN1sFud1u9u7dS7ly5ahateo53YuSJIl33nmHhx9+mJycHObOnUuji7CP6nz6M/e1p0+fzpQpU1i6dCnVq1fniSeeYMOGDRw4cOC8bKC9WOQEdZH81X5Wl4qNGzeSl5fHXXfdxZQpU855Q6IkSRw6dIiffvqJOnXqcOLECZ66/37G7d7Nm2YzX6tUxIGxgQAp4Mn0Bs2xhYVclUzS3+EgKorcFw6TFwnTIzsHt5iiUyzOmMIAgx1OtggCN6eSPO3z8prOwNMmEw3FFIt9Xk4JAq1tDuxIrPB6yVcq6WM7006obiqFK5XkG42WCZ4ChtsdeEWRgUVFDIyEed5iYbFWRxVgks/HdKsVQyrFTxoNtvQAvXHpuCen9wq97vVSJb2yCgATw2FahsP0drk4CtQERvh8PGK1Yk0k+FGrpUNxMe/odPQPBPgoIwOPJFGoUDDP4yFfqeTxzEySksTbXi+uVIqbXC4iwKxAgMaxGN1cLn4CbkxPtR1ms6ETRTxKJb2LinjFaKR7KMQHGRlok0lOKJXM9njYrdGwwGRCFARWFRRgFkVauc5MMH7J5+PKZJKOLhengDuTSXr7/QxyOEgAKeHMxNznLRbahEJ8mpHBFemRKzO9XtYbjbyr0SCmk7pFkmiZk0OVq6/miXnzKFOmzO++b8LhMLt27UKn01GrVi00Gs1ffu8dOHCAUaNG8e233/Lkk0/St2/fy2KD7X/PaZIkiTJlyjB8+PCznS5isRgul4vp06czcODAEo74z5OLJC6wv9PP6lJyww03sHnzZtq2bcuRI0d48cUXz6n6UBAEqlatisFgYOfOnVx55ZXMe/99+rRrh+PHH/k43Tmhs82GWRBY43ajkCRucTpRAUu8Xionk7RxOHjOZGJqKEiLcJgeThcNnS76JRLM8fu4z+GkiTObqpLIJx4Po+x2ulntHFepeLSoiCVGI2t1Or42GMgQRYoEuN/rwSmKtHG6uCvLyhKvh0rJJHc6nbxtMp3p3BAO84rJhCRJJIGdSiWOVIqX3W6+UqsZkpWFOf0HvkCloovDgV4Q6BGLkZ1MMtNiYY3RSKEgcFMiwW6NhiAQVSg4oVJRQRQZFgiQn5XFsxYLV6ZSrPN42KjR0MdqJUsQeLuggOMaDXfY7egFgXujUSypFOOsVsqIIggC7eJxtmi17FYqCSsUCKJIOUmiZ1ERm7VaFplM1IzHec3rZa1WS3+rFTtn9lMd1Gi4zeHAKAg8WlSEKAgMdjjIkiQckkTzeJzPdDqsOh2FCgXZySQKpZIWkQhvmc0sNxqpHY+z2ONhmU7HkKwscoB/ud3s12jIc7m4omxZpk+bxrVNmvyp943RaKRx48bs3buXrVu3Urdu3T+9EgiFQjz55JMsWLCAfv368dZbb11W5eH/fV/7yJEjnD59mpYtW559jlar5cYbb2TTpk2lKkHJK6gL7I/6WZUWXq+Xjh07UlRUxIoVK85LM0i/38+uXbvIycmhUqVKPDFiBN5PPuFwKsVDoRCrjEaKgVMqFTfFYhxWKtFzpsQZScIoiqgEgSvicT7R6aiaShJXKOkd8POo1UbZdDfs2e58+rpc/ChKXJNKMtfn4x2djolmCzUlkZc9Hg6o1XTNsmISBEaFw7jVKt7T6rgmGuVzrRa9KNI6FmNIYSF90+XfvYuLGRoK8aTVygq1mhxBYLzPx7zMTCRJ4rRaTbVEgh8UCrpEIhTD2dLyaYEAdZJJOjscFEoSTwUC3BKPc096plZeKsUon4+xdjvblEpMwCOBAAsyMjClUhzTaLg6HmefUknHSASvUslH6UGF4wsLqZFIcJfDQViSmBkI0CIeP3tf7+54nAcCAUbbbPxbqaSMIDDB5+NZq5WoJFGgVHJTPM5mlYqbolFOqdXsUCpJACMLC6maTDLQZiP2/47dOT1wcXA0Sr9gkFF2O+uVSqoBT3i9TLNaSQoCCYeDpj16cNegQX+r8/fP4y+OHDlCjRo1fvd9KEkSK1eu5JFHHqFy5crMnTuXunXr/r036yXqt+5rb9q0iaZNm3LixIlfrEzvvfdefvzxRz766KOSCvcvk1dQF9j8+fMBaP5f7f9/7mdVWthsNj7++GMGDBhA8+bNeeutt6hdu/Y5HTMrK4vGjRuzY8cOiouLeWzWLGY+9hjm99+naX4+q4xGjgAmUeQhr5eVBgOzTCb0ksS/8vM5qlDQzeFgu1bL+vzTaIEWThcjMrN4x+2mvJiih81OU4eT8UVFdAiHecDh4FpXNhWQWOHxMMpmZ1xmJlv1BlrFY2xWqbkiWowiocKr1vCBRsPH+fkYJInmTievOp0MjMd5PF2ksF2j4UeVijtjMdbp9RhSKeIKBcdFEX0qxayCAj7Vank0IwNDuighKAi0Spd7Tw2FKJtIMMBm4wmgiiQxLhzmObMZwWRip0pFk1iMnVot5RMJlMABhQJjKsV0j4d1Oh2TLRYMwMfpooTW6bL1uYEA9lSKXumOD7mpFNNCISZnZPBjZiY71GraRqOs1+sRgZBCQVEqhVqSGOn1ssJgYK7JhCFd8JCvUHCbw4FGknjZ68UoSXRLd65om0wyNBTikaws/q3R8JNKxd3FxbxtMOATBLLMZjzVqjFj0aJf9XH8KwRBoFKlSphMJvbs2UMwGKRatWq/ulS3Z88eRo4cycGDB5kxYwY9e/Ys9SPXf8v999/Pt99+y7///e9ffe2/f15JkkrdayAnqAvsclqgarVaXn75ZSZPnkzLli15+eWXf3EZ4e8wGAw0btyYb7/9lu3btzNiwgS+bNaMFsOHMyAcZnEgwNyMDK5xOqnDmVY4ay0WGmVnkwks8vnYZzBwc3YOSqBvcTFqSaK304lNFNGKIr0ScRabLRSJEruUKq5KJkim9/hkSBIfarTcGI0y0+/jC7WGfllWyqVb+mwzGGiZnY0BuDGZpBj4SqtFF48jAkeUSu6MRLgvFGKvUkkfm40ekQhvBIPMycjgGpeLysDbHg+vZGXR2uUCQaBfNMoutZpVJhMCYJYklJLElfE45WMxBJOJ9/R67isspE8kwj02G11tNroVF/N6MMjzGRnkOp1UFQTeKyhgWVYWLbKzUQsCw4qL2aFW81xmJirAIUkoRBF9IoFKFFEAWzUaehUVcW9RET8olQzMyqJbOMyYYJDZGRlc73RyJWe6ja/MzOTanBz0ksT4cJjtWi1j05V5lUQRQZLwKBS4ASSJIwoFdxQX80BhIflaLWOrV2faCy9Q5zyuXhwOB7m5uezatYsPPviABg0aUKZMGQKBAFOmTGHJkiXcd999rF279ncn4ZZmDzzwAO+++y4bNmz4RdFVdnY2AKdPn/7FCtPtdpe6jcfyJT7Z3/LGG2/Qv39/pkyZwr333nvOxxNFke+++46CggLq1avHiePHmTZgAOWOH2ePWs3d4TCLTSb6BwIszcykQTzOFo2GuQUFPGuzUSBJBBQKXnO72aTTMSd9s/8dz5lxDh3sDoolibe9HiqKIj3sDvYKAqOjUe4MBhnodHJEIaBBYFQgwIzMTDoVFvJxZiZiKoU73f/Or1Ryn9WKKEm87/GQIYrcmh4u2C8Wo21REf0cDszp/n13FxWxyGxmsN/Pq1lZZCSTnFSpeCM/n9VGI6/p9SgEgU/y8wkpFLR1OIAzI+GdqRS3u1xEJIkeySR5gQADHQ706a7w94RCzLNY6BkIsCori7LxOD+o1Sx2u1ljNrNGowFBYG1BAREgz25HSrcVyhZFWjkchNIl8e2CQfo6HCQBnSAwOBBgZmYmNxcV8S+zmdrxON9oNDzt8fCuxcLn6Sm9ywsKiAkCPWw2ROAtj4eyokgnl4tCs5mBo0eT16PHBStGSCaTPPDAA3z44YcMGjSI+fPnU6tWLebMmUPNmjUvyDlL2n/f165Wrdqvvl6mTBlGjBjBmDFjgDNNb51Op1wkIftn6N69OxUqVCAvL4+DBw8ybdq0c2qYqVAoqFGjBgaDga+//pqrr76aJ1eupF/79kz+8UfqRSKs0euZbTbTJxhkaDjMNLOZe6xWbk4kWOrzsV6rJc9up6IksS5d/t3S7sAsCEwtLEQUBLo7XViAyqkUg+JxlhqNJJNJDiqV5CST6BQKWkSjvJtIsNBsJjcWY4HPxwaNho52O3ZBYFl64F+ey4UeyE0mUUsSX+j1SKkUcUkiClyTSJBXVMS7BgPPWCzcHg4zKRhkoclEe7ud6sC/CgpYbzRynctFpiDwZDDIYa2W/g4HBqB6KkWWKLJFrcao1xMDtJJEzWSS1uEwK00mFlks3FRczEy/n4UGA3fZbFQRRT53u/lKp6O5w0GGIPBcIMBxrZaeTid60lWLySTv6vUERZEwUCaVQqtU0igeJwNYYzBwTTzObK+XBQYDg7OyqCxJrHe72aHV0tZx5vVd6PPhVqvp5XJxpclEvZtvZsj48WRkZJz7m+13qFQqBgwYwKFDh3jiiScYNGgQc+bMKXWXsv6KIUOGnL2vbTabOX36NPCf+9qCIDB8+HCmTp1KtWrVqFatGlOnTsVgMNCjR48Sjv6vkVdQsnNy6NAh2rZtS9WqVVmyZAkmk+mcj+l2u9mzZw+VKlXC6XQysndv9u7cyeOhEDeEw3R3OvELAg1FkeE+H/fbbGSmUuQrlQwPhZhjsdC6qIiPLBbqxuNsV6kY6/ezyWhkg1pNjDPjHCyiyN0OB1FJ4rV0j7oeDgf7BIF+iQT90iuWfCE98C8UYp7ZTJdgkM8tFopFEa9CwUKPB59CwejMTFKcuZxXVhRp4XQS5D9dy3s5nZwUBCpKEiN8PsbbbFSKRtmr19MyFuMTjYYRfj8fZ2RwAIgIAgu9XuKCwP1Wa3rP1pmO6Leme+k9Folwe1ER/ZxODqR76Y31ehlntaJPJjmu1dKxuJi1Oh2diorYbjRyEggBk/1+1JzpFJ6UJF7w+aibTNI6PQTx0aIiOkQi3OdwsE2hoK4k8bjXy3ibjQIgpFTSKxLhHZ2O6+JxDAYDWypXZvCkSTRu3Pic3wd/xOv1MmnSJJYtW8awYcO47rrr6Nu3Lz179uTpp59GrVZf8BhKwh/NaYL/bNRduHDhLzbq1qpV6yJGeu7kBCU7Z36/n44dOxIIBFi5cuUf7mn5M4LBIDt37sRms1G9enWeefRRVGvWUBCNsl+lIieVQisI9AoEGGe1ohRF6oki0z0e7ktPlb0+keB5n493tVomZGRQSZJ4o6CAY0oleXY7JkHgeb8fURAYmpWFCaiWStEgFuNNg4G7AgFeyszElUyiVih4JT+fkenKt1rpIXxfajQMzswkC3jZ6+WYRsOwzEy0kkT7WAyHJPGqXk+deJy9ajU1k0lOqNVMLChglMNBOJWiGrDE7eYps5kVej2VJYkVBQXsUKnoY7ViFgRe9nrxqVQMzspCA7RP99KbZTJxdSLBYZXqTMNYjYbJXi/j7XbEVAqzQsFbp08zIyODt7TaMx3Q3W72qlT0sFrRp7utxwWB7nY7SqBHLEbdaJRxGRlUSqXwKJW0KS5mtcHAQz4fz1itmJJJIioVq06dYr3ZzHirlUeeeIK2HTpc8NWLKIosXbqUxx9/nGuuuYbZs2dTvXp1AA4fPkzHjh3Jy8tjwoQJFzQO2YUnJyjZeRGPxxk4cCCffPIJK1euPC/lvNFolJ07d6JSqahTpw7zn3mGd196iU9PnCAqSbRxOkkAr3u9XJlKkedw8KNCwQOxGHcHAgx2OtmrUFBekpjs9TLBZkOdSnFMraZjNMqHGg3tIhH26nR8rzjT+2+C3085UaSfzUaxJLHI76dRIsFddjt7FAp6JxIM9Pt50Olkj0KBFhhdWMg8i4Wa8Tjf6nQ4kkmOKhQMLywkoFCwyGwmKUnM8/upkUjQ3uXCJ0k8GTzTxmmQ3c4WhYKbpTNj2h9zONiTvmczIhRimclETjLJUY2GzFSK04JA50gEXSrFQosFURR5rLCQG2Kxs53DxwaDdIlGGWO18olKRTNJYorHw9M2G++rVBiAh4NBVptMFAoCIYWCMqkUHqBOKkWFaJQlJhMKSaJXJELXoiJ6ulyclCTuLSpiUCTCAouFFywWuvTowYAxYy7Ktolt27YxcuRIPB4Ps2bNon379r9KiJFIhFQqVao6Jsh+m3wPSnZeaDQalixZwrRp02jVqhVLly6ldevW53RMnU7HNddcw+7du9m2bRv97r+fKlddRftHHyUWiTChqIi4QsE9TidmoFIqxa3pkeQFosgPCgWNEgmOaTToRJGIQoFfkigrigz1+zEZjcwzGikDfJifz/F0kYIRWOjzoQL62u3ogXqpFGOLi5ljMhE3m9mrVFIjkeC4Wk3D4mLsZjOfqNWUT6V4Kd3te0RmJmbOrFiCCgV3OBxoJYmHIhGuiMcZZrXyrCRhliSGRyK8aDLxtl7PbqWSaokEP6rVNI1E+EyvZ7NSSYYossrtZodazaCsrLO99URB4Ba7HYUgMC4SoW4kwj0OB/M5U8E3IRRiRkYGc4xGPlOruSEeZ5tGwxWxGGqjkeOcmeO0zO3msFrNvVlZYDLxoduNAWjucDDPaOTxcJimkQh9HA7+bbNhqFuXN55++qK07XK73UycOJEVK1YwatQoHn744f+ZEA0GwwWPR3ZxyCso2Xm3fPly+vXrx8SJExk8ePA5H0+SJPbu3cupU6dQq9XEYjFenTyZ8Xv28EJmJt8pFGda/fh8SMAIq5V4uvHs1ckk7R0OfhIEJodC3F5czEM2Gx+rVOSmVxVTbDZ2KRTEFQoGhcO8q9dTMZkkX6XCCxQDvYuKuDIeZ2R6M+vUQICW8Ti97HZ2KxT0jcW4v7CQJ2w2VqtUlBMEpnk8LLRaOSQIFAkCLdKX+aonk0jAVyoVgiTRvbiYm8JhBjgcBCWJEaEQdxUXMyIzky80Gm5LJJjo9/NiZiZztFrKCAJPezy8YzazTqNBoVDQIpHAnV4JlUsm+UqtxiyK1Eql6Of3M8jpJCCKdIxGeSQYZLzFwlqdjtxkkud9PtYZDDxsMuEUBOZ5vXxjNDLLYEAL3BKPoxRFvtTpuDsaZVWVKrQfPJjO6aauF1IymWTx4sVMnjyZZs2a8eyzz1K5cuULfl7ZpUFOULIL4quvvqJ9+/Z07tyZ6dOn/+0Kv1gsxsGDBzl9+jRWqxWv10uNGjXQ6/X0uf12rjx5ktkFBexP31MxCwIvezzEFArustvRcOaeSv3iYh7OzKRyKoVHoeD24mJWGAyM9fmYabNhTSQoVKlYfeoUszMyWKXVkpEu//5JoeCO9LHe8PnQiyKdnE4k4LZkkpahEKOtVq6OxzmgVnN7NMo7ej1PeTw8ZbcTSW/efef0aT7Q63nabEad3vxaLAjc7HQiAIsCASolEnR2OAgDzUSRuwIBRthsVIzHOaTV0jUS4Q29njF+Py9nZZEQRXwKBS+nR8BPt1gQBYG1bjcmSeIml4uYdGZ4YN1YjO4uF8eA5qLIAz4fQ+121KKIV6mkbzjMq0YjHUIh1lssCKkUpxUKJvl8OCSJwdnZNGzZkokzZ/6tXnh/1aZNm3jwwQcpLi5m9uzZtGnT5oKfU3ZpKf2dEmWXpOuuu44tW7awfv167rzzTkKh0F/6/lQqxZEjR/jyyy9JpVI0adKE+vXr06BBA77//nu8Xi8r/vUvFDfdxL1lyjDEbmdCOEw2sCAjg4fsduqlZx/pEgkOKBQIksQhYLDfT8/CQgypFOMyMhjs87GyoIAmxcVc73SSr1azwe0mL5Hgmuxs7nY6mR4Oc4MkMdZmY4jLRRVRpIIokpAkTgkCgiSxR6mke1ERwwIBKiQS3J+VRZNwmI/dbnqEw9zodLLKZOJDj4dB0ShNs7O5IzubUdEonVIpHrdaecDhIBOonUrhUyjwKBSIgsARlYprYzEGFRZSK5FgYkYG5WIx3nO7eSQQoLPdziKLhfc9Hp4JBrnV6eTmnByGRKOMicUYY7XS1+VCEgTuSCTYr1LxnUpFkUJBHMiWJO4KhaifSPCS0QjJJG+53Sz2eLjPZmPuHXcw5913adWxI4cPH0YUxfP/pkk7deoU/fv3Jy8vj65du7Jnz55Sk5w2bNjAHXfcQZkyZc6MSlmz5hdf79OnD4Ig/OLj2muvLZlgSwE5QckumEqVKrFp0yYSiQQtW7bkxIkTf/g9kiSRn5/Ppk2byM/Pp379+tSpU+fs/Qar1Urjxo3Jz8/nwIEDTFm0iKzWrcnVamkTDpOdSvG5SgWpFC+63Yz3+Vig1/OSycQH+fm8V1DA45mZ3OJyMSQSYbXXy3OZmTTPzuZ7rZapoRBfq9XMMZlYodVyYyKBJAhULS4GSeKEJOEVRRa43Uz2elmnVDLFYmGF282nBQW8YjCQ63RyUzLJWo+HTw0GbnG5WGM08kQwSIFSyYt6PS/p9TRJJFAA1SMRxGSSgChyCJhVUMBEn4+9ksSYjAzmu91nGq0qlTR0ubhaFFlfUIBPreYGl4vZmZk8U1iIRhB4IiODiVlZ3JRKoZckSCT4iTOVb8c40zn9vkCAYlFkXEYGj6aHB2YlkzR2OrFIEl+53dSSJFqWLcv4xo1Z/OabPPPqq1SvXp3c3Fz8fj/ffPMN8Xj8vL5fEokEzz//PA0aNCCRSLBv3z7GjRv3t3r2lZRwOEzdunWZM2fO/3xO69atOXXq1NmPDz744CJGWLrIRRKyCyozM5N169YxaNAgmjdvzooVK6hfv/5vPjcYDHLgwAEikQhVq1Y9+1/of/u5s/XP7ZEemTGDT997jybjxtE3HGZ2IMDTVisNXS7KCALLPB5ey8ykk8tFXBDoHI9zWKlkncHAxvQ8JL0oUiuRoGo8jlaSWG4w0DsUYmhREeMtFrrZ7TRLJtno8bDWaKSpy4VdEFjs87HDYKCzy4UWuC6ZRCdJvK/X45UkigGHKOISBK6Jx8kCVhiNXB+P85zPx4sGA4OysqiU7i+4V6PhdocDkyDwdCBATBDok/78qlSKO2Ix3tDriZpM/KhUUjOR4Ce1mqvicUzAZrWanFSKZzwe1up0PG6xYElfqgykhwdqgJnBIGUSCfra7UwCqosik4uKmJaRQQWjkf05ObTq3Jl7R4z4xeVZvV5P48aN2bNnD1u2bKFevXrnpVpu/fr1jBo1CkmSWLVq1XkZklkS2rRp84erPa1We7Ydkez3ySso2QWnVqtZvHgxQ4cOpXXr1qxdu/YXX4/FYuzdu5dt27aRmZlJ06ZNKVu27O/up9FoNDRo0ACz2czWrVtp1qoVz7/+OhvLl2dCZiZrNRq6xWIEBYGgILBPrUYtiiBJDPZ6uTUUYhvwhUrF+6dP84bbzVsaDV1sNp70+VhfUMBao5GG2dmEdDpe8/nYo9Fwj83GTIuFQcXFpIQzo+M/0+nITKWIShJ9/X5aBIOcEkVWarW8UlDAyoICvgNa2e3cEwyy2e2mUKWiocvFeqOR5T4fKoWCHg4Hw202BsZiZEoSmzQa3jCZsEkSKVHklmCQeuEwCVFkhV7P414v8z0eMhMJbnc4aBaJsMXtJjeRoIHLxdKMDN72erkhlaJ1djZdXS76x+PUlySWmc3MzsrCKElkiCJlUykaRaNU1ulY37w5sz78kMGjRv3mvUOlUkmdOnUoW7Ys27ZtIz8//2+/N44fP06vXr3o1q0bffv25dtvvy21yenPWr9+PU6nk+rVqzNgwADcbndJh3TJkldQl5l58+YxY8YMTp06xdVXX82sWbO44YYbSjosBEHgoYceomrVqvTu3Zvx48fTp08fpk6dypVXXkm9evVo0qTJX9pLo1AoqFmzJkePHmX79u3UqlWLiW++Sd/27Xnm+HFyo1F2q1Tcl5VFz6IiRoZCvGQycbPTSXVgncfD5yYT12dnoxcERkYi5CuVjLXZcKSn+OYmk+QrlZxWKIgLAseUSuonEgwOBjmkVDIlI4P6iQTLvF7+rdHQw2olizM96U6pVHRItxXqFotRIZFgekYGa4xGTigUtIvF2KjT4RYEvIKAShCwpKfMxsxm3tDrsXKmBP5HhYK8nws1PB70kkQnpxMR6JBIMDIQYLjVyr81Gk6p1QyORHjVaGSXSsXXajWOZBK3SkXHwkLMej0LjEZQKPgoP/9MpV5ODtsaNmTy/PnUqFHjT/0+K1eujMlkYu/evYRCIapUqfKnN+nG43Fmz57NjBkzaNeuHd9999152eB9qWvTpg1dunThiiuu4MiRIzz22GPcdNNNfP3116XqUubFIlfxXUaWL1/O3Xffzbx582jatCkLFy5k8eLF7Nu3jwoVKpR0eGdt3ryZ1q1bo1aryczMZO7cuVx//fXndMz8/Hz27t1L5cqVsVqtjLjrLg7v28c9xcW0DQbp7XSilCSUgsCQdDPYdqEQazMyqBmPs0OlYpbHw0cmEx9otSSBlQUFaIAODgcxSeKVdNl6F4eDQwoFPZJJBvl8DEt/rubMpt35FgtVEgn2a7WUSyY5rFDQq6iImCCw1GhElCQmFxaS+/821j4aDJ4pAc/M5AONhusliSc9HhZYrbypVmMAxoRCfG4wcFipJJVOZmJ6iGDTUIjZmZkoRZHW8TgjAgHucTj4ThC4PRplUjDI6wYDM0wmKgIvpTu1j7dYyHY46Pbgg9zeufPf6gJRVFTEzp07MRqN1K5dG5Xq9//v/fTTTxk5ciR6vZ45c+bQrFmzv3zO0kAQBFavXk1eXt7/fM6pU6e44oorePPNN+nYsePFC66UkBPUZSQ3N5cGDRqcnUEFUKNGDfLy8pg2bVoJRvYfO3bsYPjw4ezbtw+73U758uV55ZVXzstIhMLCQnbu3InD4aBixYpMHTmSCp9+SqqoiDUGA5mpFFdKEg/7fPR3OjkmSdwaizE9EGCJwcAck4kqksQrBQXs12jolZ6O+2RhIQmFgnEWCxaggijSKBplucFAp2CQFRYLVRMJ3Go1S0+d4iGnk2+BbOBdt5uNGg3DMzMxCAIfuN1EBYGWDgdK4NFIhDqRCH3SqyOrJNErFOKpzEw6BIO8Y7HQML2x9gW3m8VZWXylUEB6HIhHEOhpsyEB73g8uESRlk4nAUFgeDRKh2CQfk4n+YJAJjDa52Oa1cp1xcUcz8nB2qwZQx9/nMzMzHN67ROJBLt37yYajVK3bt3fnLp89OhRHn74YTZu3MjEiRO57777/jCZlWZ/JkEBVKtWjf79+58dzy77D/ke1GUiHo/z9ddf/2o+U8uWLdm0aVMJRfVL8+fPp2nTpjRp0oTDhw+zefNmAG699VZ++umncz5+RkYGubm5FBYWsn//fsY/9xzBu+7iVZOJd/PzWV1QwGalklvsdu4NhfgqP59jGg2NXC7Wm8287vORUii4x25nmM1G/1gMM7BXqeQtoxGLKFIsinQOBLg2fS9oqdHIE14vL3k82OJxWjqd1IvF2Op2c30ySQOXi5lWK2/4fNyYStEhO5s7XS46JZPUE0XWabW8aLGgFAR0kkStZJLasRh6UeR1o5HbwmGe9XppW1TEXTYbQUlig9vN5GCQ5g4H9zocLPb7GV9cTCeXi5Y5OTSUJPrG47xmMDDXYsGtUHBlMolKEKiTSHCtSsWWatUYvmoV45999pyTE5y5z1ivXj3sdjtbt27l2LFjZ78WjUaZOnUq11xzDTabje+++46hQ4de1snpz/J6vfz000/nZUL15Uh+h1wmPB4PqVTqVwPJXC7X2Xb8Je22226jVatWv+gEsHbtWu6//36aN2/OypUradCgwTmd47/bI903ejQNcnPp+/DD+IqK6BKLYUmlmG6x8I7BgEehoEU8zn6tliLOTJX1SxI5osjQQICU2cxig4Fs4KP8fA4rFHSw29EJAq94veglia7pqbKtkkkGFhYyxmplj1LJAa2W3pEIqwwGTgsC+9Vq9MkkQaWSe/1+vtRoeNJiAaWST/Lz0UgSN7pcrLHbmRsIUD8ep5vTSUO9nmsliTd9Ph602bjLbueEWs39kQgr9Xo2azRsMhhwpFIUCgKtg0F0ksSbGg1va7XM8XjITSQY4nBwW5UqPPLUU4xu1eqcXuffolAoqF69Onq9nptvvpkePXrQqFEjHn74YbKysvjss88u+z0/RUVFHDx48OznR44cYefOnVitVqxWKxMmTKBTp07k5ORw9OhRHnnkEex2Ox06dCjBqC9dcoK6zFzKY56vuOKKXz2mVqtZsGAB1apVo02bNixevJg77rjjnM6jUqmoV68e33//PVu3bqV+bi6DZ89m/pgx3LZvH//S64mLIt8oFCz2eKiUTJLncjHAamWGz8fNsRgjbDYauFy0EEU+Lyhghs3G9dnZKIFJRUWsNRiYbrUSUiqpmEoRB5SShB/ObNpVqehRVMSgUIidajUPZmWRFw4zPhjkDYOBVnY7FdPDBLcZDDR3uTAIAoOLi0kB46xWyieTJCSJm1Mp9ms05AsCYYWCYkminCgyoLCQfOAFo5EKosj76Y4a3dJdypd7PKSAPg4H9owMrr/zTqaMGHHBb8aXL1+eKVOmMGLECObPn8+UKVMYMmTIOc0LKy22b99OixYtzn7+4IMPAtC7d2/mz5/P7t27eeWVVwgEAuTk5NCiRQuWL18uN7b9H+R7UJeJeHoez8qVK3/x39iwYcPYuXMnX3zxRQlG9+esXr2aXr16MXbsWIYNG3ZeEuvx48c5cOAANWrUQKVS0T8vD/Pp0yx1uylQKOiQbuA6LhKhQjzO/VYrGekGru3DYRaYzfQtLOTljAyuTCT4Qa3mjfx8ns3KYr1SiVYQ+Cg/nxNKJV1tNgDe83jIkiRaORwUCQIDYzE6BoP0sduJASqFghGFhczIyOCmcJj1ZjNV43H2qFQ85vezX6tluV5PEljg9VIpmaSD00kh8GwgwI3xOA/YbHypVNJSFBnv9TLVZuNTpRKdIJztUp4QBMrqdLjr1uW+iRPPjqS4kCKRCE899RRz5syhU6dOHDhwAEmSWL169UVpKiu7vMgrqMuERqOhYcOGfPLJJ79IUJ988gnt27cvwcj+vA4dOvD5559zxx13cPjw4fMydK5cuXLo9Xq+/fZbypcvz5uffsq4e+/l2S+/ZL1SSZf0QMMDSiXbTCa0okhUkugeDtO0uJiXjEbmmUyMCAS4q7iYxywW2trt3JRM8qXbzTtmM9e6XNgEgQV+P7v0erqmN+3WS6XISCZZq9WS0OsJKhRkp1KYJIlri4txWCys0uupG4sx3+vlXa2WhzIysAOfuN3kKxS0dzjQSBITQyHKJZMMttkwAzZR5OGiIp63WFiq17NBraZxPM4ujYZa0Sh+vZ55djtdZs6k+U03nY9fz++SJIk1a9YwduxYypQpw8aNG2nYsCGxWIwhQ4bQqFEjvvjiC6688soLHovs8iGvoC4jP5eZL1iwgOuuu45FixbxwgsvsHfv3t+8vHapOnbsGLfffjsul4tXXnnlvIwN/7kU2mw2U7NmTcYOHoxywwZmnTjB8nQDV4Mg8Gl+PmFBoIXTiRKYFwhQNd3AtVihoFEqxT1+P6NsNq6KRtmt19MxEuFtg4FxPh/LMzM5KUmEBIEXvF6KBIFh/28abrVUinZOJ8eBh4qLuTMU4kGHg38rFFQCnvB6mWm1UgD4lEraxGJ8k+6AnhJFtmg0qCSJvGiUtkVF9Hc4CKRnNA1Mj+yYl5XFgKFD6XHvvRelEOG7775j9OjRfPvtt0yfPp0+ffqgUPyn/kqSJFasWEGHDh0uSpNZ2eVDTlCXmXnz5vHUU09x6tQpatWqxbPPPlsq95kEg0G6du3KsWPHeOutt85Lgo3H4+zatQtRFKlXrx4frFzJ/CeeoFosxlMeD69lZfGmWo1KEOgfifCdRsNBpRKLKJIvCFhFkQxBoLffzxi7nXgqRbNkkmk+H49mZPChVkvdVIoXvV62qVT0s1rJEARe8ngoVKm412pFC7RNJKgTjfKk2UzDWIzdGg03x2J8ptfzjNvNRIeD4lSK1M8d0HU6nrJYUAkCn+fnkxQEbnQ6ESWJBYWFXBWP08vpRKXXU+mGGxg+ZQq29OXGCykUCjFt2jQWLVpE//79mThxIllZWRf8vLJ/DjlByS5ZyWSSoUOHsmrVKlauXEmjRo3O+ZiiKLJv3z78fj/16tVj986dLBo1ij4//MDTNhvl43EOqtW8lp/PKrOZFVotCAIf5OeDINDa6SQhSbzm83FVMsmdTieHBYH2qRRDfT7ut9koEAQSCgXDQiGWmkzUisfZr9OhT6XIFwS6h8M4EgmeysoiKYqMLSzk9liMHg4HBwWBAZEIg4uKWGA2s0Cvpzowx+NhncXCbJ0OLdA3EsGnVrNeo+EOUeSLatXo9dBDtLhIl/NWrFjBuHHjqFKlCnPmzDkvE5Rlsv8mJyjZJU2SJGbNmsVjjz3GokWL/nDT45895pEjRzh69Ci1a9cmHA7Tt107Rp06RZdIhIVGIwuNRmpKEgs9HrbpdDxgsWAWBB4LhYgqFMwwmcgCMkSR+vE4H2q1DAgEmJuVRZlkkmKVijdPneJRm40vlEpcwPtuN/tUKu6yWtEIAu8VFKACWjsciMDAWIxbQyH6ORwYRJGEQsHAYJBZFgs9g0HeysigfCLBAZWK5zweilUqxpUtS94993Dv0KG/uKx2oezevZuRI0dy6NAhZsyYQc+ePS+ZKlHZ5UdOULJS4d1336Vnz5489NBDjBgx4rz8UTx9+jT79u2jatWqWCwWxvTujX/fPiypFCN8Ph5N32faqddzSyzGZxoNw/x+vjKZ2KZSEQOe9vnITqXo5XAQkSRm+f00SyS4z2rlK5WKzokEY/x+5litvKJWYxMEpvj9vG82s02tRgSqpVIkJImUQkHjcJhXTSbMqRS10xV6A5xODgDNEglm+f1s0mjoZ7fT6uabaXL77dSvX5+yZcue8+vxe/x+P1OnTmXJkiUMGTKExx9/XC6Nll1wcicJWanQrl07vvjiC+bPn8+QIUNIJBLnfMzs7GwaNmzIkSNHOHXqFLOXL6dsbi5NlEpsqRRKQWCrRkONRILxPh89gkGeyMjg+/TG2mUeD/dmZdHV4eCZQIA3fT7G2GzckJODoFLxVDDIBzodk8xm3tZqaR+PExUEdMkkJxUKoqkUYUniMY+HgX4/3wKLDAZWuN28X1DADqWS651O2kWjbHK7KVKryStXjgXNmvHmBx8wdcECmjRpwvfff3+2nPt8E0WR1157jfr167N//36+/vprZs6cWaqS0x8NEZQkiQkTJlCmTBn0ej3Nmzdn7969JROs7BfkBCUrNRo0aMCWLVvYuXMnHTp0IBAInPMxMzIyaNy4MYFAgH379vHUkiUk+venbXY2j/p8bHK7kQSB+i4XO0wm1qb73bVxOOjldDIiFqMysNxkYrrVSpYkYUqlqBSLYU0mUUkS6/R6uodCTPD7aVpcTF+bjcxkks/dbiYGAtxqtzPaZuM1r5ep4TDtXS6a5+RwrSgyLBZjodHIO2Yz/rJlue2hh5i/Zg3VqlUDzgxwzM3Nxev1smPHjvOSuH+2Y8cObr75ZiZPnsycOXP47LPPqFmz5nk7/sXyR0MEn3rqKZ555hnmzJnDtm3byM7O5tZbb/3LU6Bl5598iU9W6oRCIbp3786hQ4dYtWoVFStWPOdjJpNJvv32W6LRKPXq1WPT55/z5mOPofH7KVAouCka5V2djsd8PqbZbFiSScIqFW+fOsULFgvLdDr0gsC/8vMJCAK3Op0IwBteL+VSKTo4nfgEgTbJJAP8fgbb7ehTKQrUavoXFfGy0UjHUIgvLBYSqRQeQeCRQIBqySQPVKhAtRtv5PGZM//nOJL/36y1Xr16GAyGv/1aeL1eJk2axLJlyxg+fDjjxo37zeavpdF/N3CVJIkyZcowfPjws81aY7EYLpeL6dOnM3DgwBKMViavoGSljtlsZs2aNdxyyy00b96cLVu2nPMxf1V0ZHAAABHjSURBVG6PZLVa2bp1K42aNqXv7Nl8bzLxXEEB9wQCaEWR0ZmZ3O/3s7qggBuLi7nB6eR7rZYvCgroF41yTU4OHVwuJoXD3JVM8oDDQR+XiwzghmSSAyoV36tUhBUKQgoFVVIpeoZCXBOL8aLRiJRMstrt5lWPhwetVibfeivPffghT86d+7uzsn5u1mqz2di6dSs+n+8vvwapVIolS5ZQr149fvrpJ3bu3MnUqVMvm+T0W44cOcLp06d/0WRZq9Vy4403XjJNlv/J5E4SslJJpVLx/PPPU61aNe644w7mz59Pp06dzumYCoWCq666CqPRyPbt23E6ndw3cSL3zZxJ0O3m0VCImsXF9HY4mMOZ0RhTCwuZmpXFQoOBdw0Gbo7H2aLRUCEaZbtaTUQUCQJvFhSgAzo6HIzJyOClggLqJpP0tdtp6HTSOZXi3243k+x27ihTBm3Zsjw3YQLXN2/+l+K/8sorMZlM7NixgyuvvPJPtxfatm0bDz74ID6fjyVLltCuXbt/RHXez42Uf6vJ8o8//lgSIcn+HzlByUq1oUOHUqVKFbp3787hw4cZNWrUOf9h1el0aDQa8vPzqV69Oi+vW8f4QYPwf/UVL2o0KAGtKFIvkaBOPI5JklhmMtEhHObRYJCFRiP3WK1cJYr8Kz+ffWo1dzgcmASB6YWFKIFBDgcWIEcUGRWJsNBkoqFOx08uFw1btmT4+PF/u+tC2bJlMRgM7Nq1i6KiIqpXr/4/S9DdbjcTJkxg5cqVjB49moceeugvTTW+XFzKTZb/yeRLfLJSr23btmzYsIEXXniBQYMGEY/H/9ZxwuEwO3bsYM+ePVSqVIlrr70Wv9/Pjz/+yMxXXmFz69Zs1On48PRpVrndrNFoaGu3MzYQYGN+Pl/r9VzjcrHZZOJ1n4+IUkl/m42hdjt943EygN0qFW8bjRhEkago0jYY5LaiIsqrVLzUpAlT165lzBNPnHNLoKysLHJzc/H5fL9ZPJFMJpk/fz7169fH7/ezZ88eJkyY8I9LTtnZ2QC/Gknjdrt/taqSXXxygpJdFurVq8eWLVvYu3cveXl5+P3+P/29yWSSH374gc2bN6PT6WjatCnly5fHbDaTm5tLNBplx44dPPHccwx47DF6Va5My5wc+sVi9E0mmZyVxSi7nZAg0CSZJKBQIEkSUYWCH5VKyogiI/x+7gwGWaLX861Sycf5+axxu5memcndDRty37JlLH3vPRwOx3l7TfR6PY0bN0ahUPDss8+ya9cuAL788kuuv/56FixYwOuvv84777xDpUqVztt5S5NKlSqRnZ3NJ598cvaxeDzOF198QZMmTUowMhnICUp2GSlbtiwbNmzAYrFw0003cfjw4d99viRJnDx5ki+//JJAIEDjxo2pUaPGL1YvP3eJ1+v1bN26lVYdO9Jx4kQcmZm0CwaxRKOERJFtCgULCgqY7vUSEkW622yM9Pn4wu2mcnqy7lcmE594PDRLpWifk8PAq69myNixvPHZZzRo2PCCvCY/F3+cPHmSW2+9le7du9OhQwe6devGnj17aNOmzQU576Xk50bBO3fuBP4zRPDYsWMIgsDw4cOZOnUqq1evZs+ePfTp0weDwUCPHj1KNnCZXGYuu/ykUilGjhzJsmXLePPNN7nuuut+9ZzCwkIOHDhALBajWrVquFyu373nIEkShw8f5tixY9SuXZuioiIGd+qE0+9nkdvNCZWKHjYbOuCB4mIqx2KMysqifCpFSKGgczjMSyYT0z0ellesSLRWLR5//vmL0lw1kUgwf/58Xn31VQ4cOMD48eN57LHH/jH3WNavX/+LIYI/6927N0uXLkWSJCZOnMjChQvx+/3k5uYyd+5catWqVQLRyv4/OUHJLltz585lzJgxzJ07lzvvvBM4c5/p6NGjnD59mooVK1KxYsW/NOn11KlT7Nu3j+rVq59pj9SrF9d+/TVv6/XUi8fZq1TSLhJBBN4wGhFEkSGhEB2Lixmbnc1up5MnlyyhRo0aF+in/qX169czcuRIBEHg+eefx2AwkJeXR8eOHZk9e/Y5z9uSyS4kOUHJztnRo0eZPHky//rXvzh9+jRlypThrrvuYty4cSU+/2fdunV07dqVoUOHEo/HeeWVV8627vm7BQGBQICdO3eSnZ1NpUqVeKBnT7J37GDG6dNs1GgYlpmJQRD40O1GAm53udBmZTHg4Ydp26nTRVm5HD9+nLFjx/LJJ58wfvx4hg0bdjYZHTt2jHbt2vHQQw/RvXv3Cx6LTPZ3yQlKds4+/PBDli9fTvfu3alatSp79uxhwIAB3H333cycObOkw2P+/Pk8+OCD2Gw2nnzySTp27HjOxywuLmbHjh3odDpq167Nq3Pm8M7ChZgSCZ7yeFiWmck3ajVOi4UKrVvTf8wYMjMzz/2H+QOxWIzZs2czY8YM8vLyeOqppyhTpsyvnheNRtFqtf+Yy3yy0klOULILYsaMGcyfP/8PCxUupIMHD/Lggw+yceNGRo4cyerVqzEYDLz++uvnZaDfz+2FYrEY9erV48N33mHdjBlM//57Xitbls3lyvH4vHlUr179PPw0f+zjjz9m1KhRGAwG5s6dyw033HBRziuTXShyFZ/sgigsLMRqtZbY+SVJonPnzuTk5PD999/z6KOPsmHDBux2OzfddBMHDx4853P83F4oMzOTrVu30qJ1a4a/8gqjmjXj6ueeY9mnn16U5HT06FG6du1K3759GTZsGN98842cnGSXBXkFJTvvDh06RIMGDXj66afp379/icVRXFz8q/tMoigyZswYXnrpJd58802aNm16zueRJImffvqJgwcPUrNmzbObPy+04uJinn32WZ599lm6du3KtGnT5M2lssuKvIKS/U8TJkxAEITf/di+ffsvvufkyZO0bt2aLl26lGhyAn6zCEKhUDBz5kymTJlCXl4eb7zxxjmfRxAEKlSoQO3atdm3bx+HDx++ILOZfiZJEu+//z6NGjVi3bp1fPbZZyxZsqRUJ6ffeq9drEQvu3TJKyjZ/+TxePB4PL/7nIoVK6LT6YAzyalFixbk5uaydOnSizKC/Fx89NFH3Hnnndx///088sgj56VgIBQKsXPnTrKysqhZs+Z5fw0OHjzI6NGj2b59O1OmTGHAgAF/qUz+UjVhwgTeeustPv3007OPKZXK89pZQ1b6yM1iZf+T3W7Hbrf/qeeeOHGCFi1a0LBhQ1566aVLPjkBtGrVii+//JK2bdty+PBh5s2bh1arPadjms1mGjduzM6dO/n666+pW7fueSm1D4fDzJgxgzlz5tCrVy+WLVv2p383pYVKpZJXTbJfuPT/isgueSdPnqR58+aUL1+emTNnUlBQwOnTp3/VgPNSVKtWLbZs2cKhQ4e4/fbb/3DF+GdotVoaNWqEVqtl69atFBUV/e1jSZLE6tWradCgARs2bGDjxo0sWLDgsktOAD/88ANlypShUqVKdOvWrUQrQGWXBvkSn+ycLV26lL59+/7m10rL2ysSidCrVy927NjBqlWrzkv1nSRJHDp0iJ9++ok6der85dL2/fv3M3r0aPbs2cP06dPp3bt3qViZ/h3r1q0jEolQvXp18vPzeeKJJ/juu+/Yu3fvedkSICud5AQlk6WJosjYsWN54YUXeP3112nWrNl5Oe7JkyfZv3//nx4gGAqFmDp1KosWLWLAgAFMmjTpomzyvZSEw2GqVKnCmDFjePDBB0s6HFkJke9ByWRpCoWC6dOnU7VqVTp16sSsWbPo2bPnOR+3TJky6PV6du3aRTgcpnr16r9ZkCFJEitWrOCRRx6hatWqbNmyhTp16pzz+Usjo9FI7dq1+eGHH0o6FFkJujyvF8hk52DAgAG88847jB49mkmTJiGK4jkfMysri8aNG+P1etm5cyfJZPIXX9+9ezetWrVi3LhxzJw5kw0bNvxjkxOcadm0f/9+cnJySjoUWQmSE5RM9htuueUWNm3axPLly+nbty/RaPScj2kwGLjmmmuIRqN0796dQ4cO4ff7GTVqFM2bN+faa6/lwIED9OzZ8x/XI2/UqFF88cUXHDlyhC1bttC5c2eCwSC9e/cu6dBkJUi+xCeT/Q81a9Zk8+bN5OXlcdttt7F8+fJz3pejVqtp0KABWq2WZs2aodVqufrqq/nmm28u2giOS9Hx48fp3r07Ho8Hh8PBtddey+bNm7niiitKOjRZCZKLJGSyP1BcXEyfPn3YunUrq1at4qqrrjqn4+3YsYMRI0bg8Xg4efIkr776Kl26dDlP0cpklw/5Ep9M9gf0ej1vvPEG3bt35+abb2b9+vV/6zher5ehQ4dy6623csstt7B7925WrFjBPffcw7Rp00pNSb5MdrHICUom+xMUCgVTp07lmWeeoUuXLrz88st/+ntTqRQvvvgi9erV48SJE+zatYupU6diNBpp164dGzduZOXKlbjd7gv4E8hkpY98iU8m+4s+//xzOnbsSL9+/ZgwYcLvbp7dsmULI0eOxO/3M2vWLNq3b/+bz5Mk6R9XGCGT/RF5BSWT/UUtWrTgq6++YvXq1fTu3Zvi4uJfPSc/P5/Bgwdz++230759e/bv3/8/kxMgJyeZ7DfICUom+xuuuuoqNm/ezOnTp2nTpg35+fkAJJNJ5s+fT4MGDSgsLGTPnj08/vjjZzu+y2SyP0++xCeTnYNoNErfvn356quvGDduHLNnzyYajfL888/TunXrkg5PJivV5BWUTHYOdDodr7/+OrfeeisDBw6ka9eu7Nmz57JJTvPmzaNSpUrodDoaNmzIxo0bSzok2T+IvIKSlWqxWIzc3Fx27drFjh07qFevXonFsm/fPmrWrFli5z/fli9fzt133828efNo2rQpCxcuZPHixezbt48KFSqUdHiyfwA5QclKtWHDhvHDDz+wbt26Ek9Ql5vc3FwaNGjA/Pnzzz5Wo0YN8vLymDZtWglGJvunkC/xyUqtdevW8fHHHzNz5sySDuWyE4/H+frrr2nZsuUvHm/ZsiWbNm0qoahk/zRyLz5ZqZSfn8+AAQNYs2YNBoOhpMO57Hg8HlKpFC6X6xePu1yuUjEpWXZ5kFdQslJHkiT69OnDoEGDaNSoUUmHc1n77/1Z8oZi2cUkJyjZJWPChAkIgvC7H9u3b+f5558nGAwyduzYkg75smW321Eqlb9aLbnd7l+tqmSyC0UukpBdMjweDx6P53efU7FiRbp168Z77733i//kU6kUSqWSnj17/qU+ebL/LTc3l4YNGzJv3ryzj9WsWZP27dvLRRKyi0JOULJS59ixYwSDwbOfnzx5klatWvHWW2+Rm5tLuXLlSjC6y8fPZeYLFizguuuuY9GiRbzwwgvs3btXntMkuyjkIglZqfPfe3BMJhMAVapUkZPTedS1a1e8Xi+TJk3i1KlT1KpViw8++EBOTrKLRl5ByUq9o0ePUqlSJXkflEx2mZETlEwmk8kuSXIVn0wmk8kuSXKCkslkMtklSU5QMplMJrskyQlKJpPJZJckOUHJZDKZ7JIkJyiZrJSqWLHir1pBPfzwwyUdlkx23sgbdWWyUmzSpEkMGDDg7Oc/b1qWyS4HcoKSyUoxs9lMdnZ2SYchk10Q8kZdmayUqlixIrFYjHg8Tvny5enSpQujR49Go9GUdGgy2Xkhr6BkslJq2LBhNGjQgKysLLZu3crYsWM5cuQIixcvLunQZLLzQl5ByWSXkAkTJjBx4sTffc62bdt+c1DjqlWr6Ny5Mx6PB5vNdqFClMkuGjlByWSXkD87E0un0/3q8RMnTlCuXDk2b95Mbm7uhQpRJrto5Et8MtklxG63Y7fb/9b37tixA4CcnJzzGZJMVmLkBCWTlUJfffUVmzdvpkWLFmRkZLBt2zZGjBhBu3btfjUvSyYrreRLfDJZKfTNN99w33338d133xGLxbjiiivo1q0bY8aMwWAwlHR4Mtl5IScomUwmk12S5FZHMplMJrskyQlKJpPJZJckOUHJZDKZ7JIkJyiZTCaTXZLkBCWTyWSyS5KcoGQymUx2SZITlEwmk8kuSXKCkslkMtklSU5QMplMJrskyQlKJpPJZJckOUHJZDKZ7JL0f8duSSgAeLGGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kf_book.book_plots import set_figsize, figsize\n",
    "from kf_book.nonlinear_plots import plot_gaussians\n",
    "\n",
    "P = np.diag([3., 1.])\n",
    "np.random.seed(3)\n",
    "Ms, Ps = run(count=25, R=10, Q=0.01, P=P, do_plot=False)\n",
    "with figsize(x=9, y=5):\n",
    "    plot_gaussians(Ms[::7], Ps[::7], (-5,25), (-5, 5), 75)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Saver Class\n",
    "\n",
    "In the `run()` method I wrote boilerplate code to save the results of the filter\n",
    "```python\n",
    "    xs, cov = [], []\n",
    "    for z in zs:\n",
    "        kf.predict()\n",
    "        kf.update(z)\n",
    "        xs.append(kf.x)\n",
    "        cov.append(kf.P)\n",
    "\n",
    "    xs, cov = np.array(xs), np.array(cov)\n",
    "```\n",
    "\n",
    "There's an easy way to avoid this. `filterpy.common` provides the `Saver` class which will save all attributes in the Kalman filter class each time `Saver.save()` is called. Let's see it in action and then we will talk about it more."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from filterpy.common import Saver\n",
    "kf = pos_vel_filter([0, .1], R=R, P=P, Q=Q, dt=1.) \n",
    "s = Saver(kf)\n",
    "for i in range(1, 6):\n",
    "    kf.predict()\n",
    "    kf.update([i])\n",
    "    s.save()  # save the current state"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `Saver` object now contains lists of all the attributes of the KalmanFilter object. `kf.x` is the current state estimate of the filter. Therefore `s.x` contains the saved state estimate that was computed inside the loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([0.531, 0.304]),\n",
       " array([1.555, 0.763]),\n",
       " array([2.784, 1.036]),\n",
       " array([3.944, 1.105]),\n",
       " array([5.015, 1.086])]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see all the available attributes with the `keys` attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['alpha',\n",
       " 'likelihood',\n",
       " 'log_likelihood',\n",
       " 'mahalanobis',\n",
       " 'dim_x',\n",
       " 'dim_z',\n",
       " 'dim_u',\n",
       " 'x',\n",
       " 'P',\n",
       " 'Q',\n",
       " 'B',\n",
       " 'F',\n",
       " 'H',\n",
       " 'R',\n",
       " '_alpha_sq',\n",
       " 'M',\n",
       " 'z',\n",
       " 'K',\n",
       " 'y',\n",
       " 'S',\n",
       " 'SI',\n",
       " '_I',\n",
       " 'x_prior',\n",
       " 'P_prior',\n",
       " 'x_post',\n",
       " 'P_post',\n",
       " '_log_likelihood',\n",
       " '_likelihood',\n",
       " '_mahalanobis',\n",
       " 'inv']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.keys"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are many attributes there that we haven't discussed yet, but many should be familar.\n",
    "\n",
    "At this point you could write code to plot any of these variables. However, it is often more useful to use `np.array` instead of lists. Calling `Saver.to_array()` will convert the lists into `np.array`. There is one caveat: if the shape of any of the attributes changes during the run, the `to_array` will raise an exception since `np.array` requires all of the elements to be of the same type and size. \n",
    "\n",
    "If you look at the keys again you'll see that `z` is one of the choices. This is promising; apparently the measurement `z` is saved for us. Let's plot it against the estimate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "s.to_array()\n",
    "book_plots.plot_measurements(s.z);\n",
    "plt.plot(s.x[:, 0]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While I've demonstrated this with the `KalmanFilter` class, it will work with all filter classes implemented by `FilterPy`. It will probably work with any class you write as well, as it inspects the object to retrieve the attribute names. We will use this class throughout the book to keep the code readable and short. Using the `Saver` will slow down your code because a lot happens behind the scenes, but for learning and exploring the convience cannot be beat."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Kalman Filter Equations\n",
    "\n",
    "We are now ready to learn how `predict()` and `update()` perform their computations. \n",
    "\n",
    "A word about notation. I'm a programmer, and I am used to code that reads\n",
    "\n",
    "```python\n",
    "x = x + 1\n",
    "``` \n",
    "\n",
    "That is not an equation as the sides are not equal, but an *assignment*. If we wanted to write this in mathematical notation we'd write\n",
    "$$x_k = x_{k-1} + 1$$\n",
    "\n",
    "Kalman filter equations are littered with subscripts and superscripts to keep the equations mathematically consistent. I find this makes them extremely hard to read. In most of the book I opt for subscriptless assignments. As a programmer you should understand that I am showing you assignments which implement an algorithm that is to be executed step by step. I'll elaborate on this once we have a concrete example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction Equations\n",
    "\n",
    "The Kalman filter uses these equations to compute the *prior* - the predicted next state of the system. They compute the prior mean ($\\bar{\\mathbf x}$)  and covariance ($\\bar{\\mathbf P}$) of the system.\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf{\\bar x} &= \\mathbf{Fx} + \\mathbf{Bu}\\\\\n",
    "\\mathbf{\\bar P} &= \\mathbf{FPF}^\\mathsf T + \\mathbf Q\n",
    "\\end{aligned}$$\n",
    "\n",
    "$\\underline{\\textbf{Mean}}$\n",
    "\n",
    "$\\mathbf{\\bar x} = \\mathbf{Fx} + \\mathbf{Bu}$\n",
    "\n",
    "As a reminder, the linear equation $\\mathbf{Ax} = \\mathbf b$ represents a system of equations, where $\\mathbf A$ holds the coefficients set of equations, $\\mathbf x$ is the vector of variables. Performing the multiplication $\\mathbf{Ax}$ computes the right hand side values for that set of equations, represented by $\\mathbf b$.\n",
    "\n",
    "If $\\mathbf F$ contains the state transition for a given time step, then the product $\\mathbf{Fx}$ computes the state after that transition. Easy! Likewise, $\\mathbf B$ is the control function, $\\mathbf u$ is the control input, so $\\mathbf{Bu}$ computes the contribution of the controls to the state after the transition. Thus, the prior $\\mathbf{\\bar x}$ is computed as the sum of $\\mathbf{Fx}$ and $\\mathbf{Bu}$.\n",
    "\n",
    "The equivalent univariate equation is\n",
    "\n",
    "$$\\bar\\mu = \\mu + \\mu_{move}$$\n",
    "\n",
    "If you perform the matrix multiplication $\\mathbf{Fx}$ it generates this equation for $x$.\n",
    "\n",
    "Let's make this explicit. Recall the value for $\\mathbf F$ from the last chapter:\n",
    "\n",
    "$$\\mathbf F = \\begin{bmatrix}1&\\Delta t  \\\\ 0&1\\end{bmatrix}$$\n",
    "\n",
    "Thus $\\mathbf{\\bar x} = \\mathbf{Fx}$ corresponds to the set of linear equations:\n",
    "\n",
    "$$\\begin{cases}\n",
    "\\begin{aligned}\n",
    "\\bar x &= 1x + &\\Delta t\\, \\dot x \\\\\n",
    "\\bar{\\dot x} &=0x + &1\\, \\dot x\n",
    "\\end{aligned}\n",
    "\\end{cases}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\underline{\\textbf{Covariance}}$\n",
    "\n",
    "$\\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf T + \\mathbf Q$\n",
    "\n",
    "This equation is not as easy to understand so we will spend more time on it. \n",
    "\n",
    "In univariate version of this equation is:\n",
    "\n",
    "$$\\bar\\sigma^2 = \\sigma^2 + \\sigma^2_{move}$$\n",
    "\n",
    "We add the variance of the movement to the variance of our estimate to reflect the loss of knowlege. We need to do the same thing here, except it isn't quite that easy with multivariate Gaussians. \n",
    "\n",
    "We can't simply write $\\mathbf{\\bar P} = \\mathbf P + \\mathbf Q$. In a multivariate Gaussians the state variables are *correlated*. What does this imply? Our knowledge of the velocity is imperfect, but we are adding it to the position with\n",
    "\n",
    "$$\\bar x = \\dot x\\Delta t + x$$\n",
    "\n",
    "Since we do not have perfect knowledge of the value of $\\dot x$ the sum $\\bar x = \\dot x\\Delta t + x$ gains uncertainty. Because the positions and velocities are correlated we cannot simply add the covariance matrices. For example, if $\\mathbf P$ and $\\mathbf Q$ are diagonal matrices the sum would also be diagonal. But we know position is correlated to velocity so the off-diagonal elements should be non-zero. \n",
    "\n",
    "The correct equation is\n",
    "\n",
    "$$\\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf T + \\mathbf Q$$\n",
    "\n",
    "Expressions in the form $\\mathbf{ABA}^\\mathsf T$ are common in linear algebra. You can think of it as *projecting* the middle term by the outer term. We will be using this many times in the rest of the book. I admit this may be a 'magical' equation to you. Let's explore it.\n",
    "\n",
    "When we initialize $\\mathbf P$ with\n",
    "\n",
    "$$\\mathbf P = \\begin{bmatrix}\\sigma^2_x & 0 \\\\ 0 & \\sigma^2_v\\end{bmatrix}$$\n",
    "\n",
    "\n",
    "the value for $\\mathbf{FPF}^\\mathsf T$ is:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf{FPF}^\\mathsf T &= \\begin{bmatrix}1&\\Delta t\\\\0&1\\end{bmatrix}\n",
    "\\begin{bmatrix}\\sigma^2_x & 0 \\\\  0 & \\sigma^2_{v}\\end{bmatrix}\n",
    "\\begin{bmatrix}1&0\\\\\\Delta t&1\\end{bmatrix} \\\\\n",
    "&= \\begin{bmatrix}\\sigma^2_x&\\sigma_v^2\\Delta t\\\\  0 & \\sigma^2_{v}\\end{bmatrix}\n",
    "\\begin{bmatrix}1&0\\\\\\Delta t&1\\end{bmatrix} \\\\\n",
    "&= \\begin{bmatrix}\\sigma^2_x +  \\sigma_v^2\\Delta t^2  &  \\sigma_v^2\\Delta t \\\\\n",
    "\\sigma_v^2\\Delta t & \\sigma^2_{v}\\end{bmatrix}\n",
    "\\end{aligned}$$\n",
    "\n",
    "The initial value for $\\mathbf P$ had no covariance between the position and velocity.  Position is computed as $\\dot x\\Delta t + x$, so there is a correlation between the position and velocity. The multiplication $\\mathbf{FPF}^\\mathsf T$ computes a covariance of $\\sigma_v^2 \\Delta t$. The exact value is not important; you just need to recognize that $\\mathbf{FPF}^\\mathsf T$ uses the process model to automatically compute the covariance between the position and velocity!\n",
    "\n",
    "Another way to think of this is to reflect on the $\\mathbf{Fx}$ multiplication. That projected $\\mathbf x$ forward in time. $\\mathbf {FP}$ might seem to be the equivalent operation, but $\\mathbf P$ is a matrix while $\\mathbf x$ is a vector. The trailing $\\mathbf F^\\mathsf T$ term ensures that we multiply by both the rows and columns of $\\mathbf F$. In the second line of the computation of $\\mathbf{FPF}^\\mathsf T$ we have the value for $\\mathbf{FP}$. You can see that it is an upper triangular matrix because we haven't fully incorporated $\\mathbf F$ into the multiplication.\n",
    "\n",
    "If you have some experience with linear algebra and statistics, this may help. The covariance due to the prediction can be modeled as the expected value of the error in the prediction step, given by this equation. \n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\bar{\\mathbf P} &= \\mathbb E[(\\mathbf{Fx - F\\bar \\mu})(\\mathbf{Fx - F\\bar\\mu})^\\mathsf T]\\\\\n",
    " &= \\mathbf F\\, \\mathbb E[\\mathbf{(x- \\bar\\mu)(x- \\bar\\mu)}^\\mathsf T]\\, \\mathbf F^\\mathsf T\n",
    "\\end{aligned}$$\n",
    "\n",
    "Of course, $\\mathbb E[\\mathbf{(x- \\bar\\mu)(x- \\bar\\mu)}^\\mathsf T]$ is just $\\mathbf P$, giving us\n",
    "\n",
    "$$\\bar{\\mathbf P} = \\mathbf{FPF}^\\mathsf T$$\n",
    "\n",
    "Let's look at its effect. Here I use $\\mathbf F$ from our filter and project the state forward 6/10ths of a second. I do this five times so you can see how $\\mathbf{\\bar P}$ continues to change. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt = 0.6\n",
    "x = np.array([0., 5.])\n",
    "F = np.array([[1., dt], [0, 1.]])\n",
    "P = np.array([[1.5, 0], [0, 3.]])\n",
    "plot_covariance_ellipse(x, P, edgecolor='r')\n",
    "\n",
    "for _ in range(5):\n",
    "    x = F @ x\n",
    "    P = F @ P @ F.T\n",
    "    plot_covariance_ellipse(x, P, edgecolor='k', ls='dashed')\n",
    "book_plots.set_labels(x='position', y='velocity')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that with a velocity of 5 the position correctly moves 3 units in each 6/10ths of a second step. At each step the width of the ellipse is larger, indicating that we have lost information about the position due to adding $\\dot x\\Delta t$ to x at each step. The height has not changed - our system model says the velocity does not change, so the belief we have about the velocity cannot change. As time continues you can see that the ellipse becomes more and more tilted. Recall that a tilt indicates *correlation*. $\\mathbf F$ linearly correlates $x$ with $\\dot x$ with the expression $\\bar x = \\dot x \\Delta t + x$. The $\\mathbf{FPF}^\\mathsf T$ computation correctly incorporates this correlation into the covariance matrix.\n",
    "\n",
    "Here is an animation of this equation that allows you to change the design of $\\mathbf F$ to see how it affects shape of $\\mathbf P$. The `F00` slider affects the value of F[0, 0]. `covar` sets the intial covariance between the position and velocity($\\sigma_x\\sigma_{\\dot x}$). I recommend answering these questions at a minimum\n",
    "\n",
    "* what if $x$ is not correlated to $\\dot x$? (set F01 to 0, the rest at defaults)\n",
    "* what if $x = 2\\dot x\\Delta t + x_0$? (set F01 to 2, the rest at defaults)\n",
    "* what if $x = \\dot x\\Delta t + 2x_0$? (set F00 to 2, the rest at defaults)\n",
    "* what if $x = \\dot x\\Delta t$?  (set F00 to 0, the rest at defaults)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8baf8dc28f804c13b5ae97e217eb5b71",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=1, continuous_update=False, description='F00', max=2), FloatSlider(value…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipywidgets import interact\n",
    "from kf_book.book_plots import IntSlider, FloatSlider\n",
    "\n",
    "def plot_FPFT(F00, F01, F10, F11, covar):   \n",
    "    plt.figure()\n",
    "    dt = 1.\n",
    "    x = np.array((0, 0.))\n",
    "    P = np.array(((1, covar), (covar, 2)))\n",
    "    F = np.array(((F00, F01), (F10, F11)))\n",
    "    plot_covariance_ellipse(x, P)\n",
    "    plot_covariance_ellipse(x, F @ P @ F.T, ec='r')\n",
    "    plt.gca().set_aspect('equal')\n",
    "    plt.xlim(-4, 4)\n",
    "    plt.ylim(-4, 4)\n",
    "    #plt.title(str(F))\n",
    "    plt.xlabel('position')\n",
    "    plt.ylabel('velocity')\n",
    "    plt.show()\n",
    "                 \n",
    "interact(plot_FPFT, \n",
    "         F00=IntSlider(value=1, min=0, max=2), \n",
    "         F01=FloatSlider(value=1, min=0, max=2, description='F01(dt)'),\n",
    "         F10=FloatSlider(value=0, min=0, max=2),\n",
    "         F11=FloatSlider(value=1, min=0, max=2),\n",
    "         covar=FloatSlider(value=0, min=0, max=1));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(If you are reading this in a static form: instructions to run this online are here: https://git.io/vza7b). Or, go to binder using the link below, and open this notebook from there.\n",
    "\n",
    "http://mybinder.org/repo/rlabbe/Kalman-and-Bayesian-Filters-in-Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Update Equations\n",
    "\n",
    "The update equations look messier than the predict equations, but that is mostly due to the Kalman filter computing the update in measurement space. This is because measurements are not *invertible*. For example, consider a  sensor that gives the range to a target. It is impossible to convert a range into a position - an infinite number of positions in a circle will yield the same range. On the other hand, we can always compute the range (measurement) given a position (state).\n",
    "\n",
    "Before I continue, recall that we are trying to do something very simple: choose a new estimate chosen somewhere between a measurement and a prediction, as in this chart:\n",
    "<img src=\"./figs/residual_chart.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The equations will be complicated because the state has multiple dimensions, but this operations is what we are doing. Don't let the equations distract you from the simplicity of this idea.\n",
    "\n",
    "$\\underline{\\textbf{System Uncertainty}}$\n",
    "\n",
    "$\\textbf{S} = \\mathbf{H\\bar PH}^\\mathsf T + \\mathbf R$\n",
    "\n",
    "To work in measurement space the Kalman filter has to project the covariance matrix into measurement space. The math for this is $\\mathbf{H\\bar PH}^\\mathsf T$, where $\\mathbf{\\bar P}$ is the *prior* covariance and $\\mathbf H$ is the measurement function.\n",
    "\n",
    "\n",
    "You should recognize this $\\mathbf{ABA}^\\mathsf T$ form - the prediction step used $\\mathbf{FPF}^\\mathsf T$ to update $\\mathbf P$ with the state transition function. Here, we use the same form to update it with the measurement function. The linear algebra is changing the coordinate system for us. \n",
    "\n",
    "Once the covariance is in measurement space we need to account for the sensor noise. This is very easy  - we just add matrices. The result is variously called the *system uncertainty* or *innovation covariance*.\n",
    "\n",
    "If you ignore the $\\mathbf H$ term this equation is the equivalent to the denominator in the univariate equation for the Kalman gain:\n",
    "\n",
    "$$K = \\frac {\\bar\\sigma^2} {\\bar\\sigma^2 + \\sigma_z^2}$$\n",
    "\n",
    "Compare the equations for the system uncertainty and the covariance\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf{S} &= \\mathbf{H\\bar PH}^\\mathsf T + \\mathbf R\\\\\n",
    "\\mathbf{\\bar P} &= \\mathbf{FPF}^\\mathsf T + \\mathbf Q\n",
    "\\end{aligned}$$\n",
    "\n",
    "In each equation $\\mathbf P$ is put into a different space with either the function $\\mathbf H$ or $\\mathbf F$. Then we add the noise matrix associated with that space.\n",
    "\n",
    "$\\underline{\\textbf{Kalman Gain}}$\n",
    "\n",
    "$\\mathbf K = \\mathbf{\\bar PH}^\\mathsf T \\mathbf{S}^{-1}$\n",
    "\n",
    "Look back at the residual diagram. Once we have a prediction and a measurement we need to select an estimate somewhere between the two. If we have more certainty about the measurement the estimate will be closer to it. If instead we have more certainty about the prediction then the estimate will be closer to it. \n",
    "\n",
    "In the univariate chapter we scaled the mean using this equation\n",
    "\n",
    "$$\n",
    "\\mu =\\frac{\\bar\\sigma^2 \\mu_z + \\sigma_\\mathtt{z}^2 \\bar\\mu} {\\bar\\sigma^2 + \\sigma_\\mathtt{z}^2}$$\n",
    "\n",
    "which we simplified to\n",
    "\n",
    "$$\\mu = (1-K)\\bar\\mu + K\\mu_\\mathtt{z}$$\n",
    "\n",
    "which gave us\n",
    "\n",
    "$$K = \\frac {\\bar\\sigma^2} {\\bar\\sigma^2 + \\sigma_z^2}$$\n",
    "\n",
    "$K$ is the *Kalman gain*, and it is a real number between 0 and 1. Ensure you understand how it selects a mean somewhere between the prediction and measurement. The Kalman gain is a *percentage* or *ratio* - if K is .9 it takes 90% of the measurement and 10% of the prediction. \n",
    "\n",
    "For the multivariate Kalman filter $\\mathbf K$ is a vector, not a scalar. Here is the equation again: $\\mathbf K = \\mathbf{\\bar PH}^\\mathsf T \\mathbf{S}^{-1}$. Is this a *ratio*? We can think of the inverse of a matrix as linear algebra's way of finding the reciprocal. Division is not defined for matrices, but it is useful to think of it in this way. So we can read the equation for $\\textbf{K}$ as meaning\n",
    "\n",
    "$$\\begin{aligned} \\mathbf K &\\approx \\frac{\\mathbf{\\bar P}\\mathbf H^\\mathsf T}{\\mathbf{S}} \\\\\n",
    "\\mathbf K &\\approx \\frac{\\mathsf{uncertainty}_\\mathsf{prediction}}{\\mathsf{uncertainty}_\\mathsf{measurement}}\\mathbf H^\\mathsf T\n",
    "\\end{aligned}$$\n",
    "\n",
    "The Kalman gain equation computes a ratio based on how much we trust the prediction vs the measurement. We did the same thing in every prior chapter. The equation is complicated because we are doing this in multiple dimensions via matrices, but the concept is simple. The $\\mathbf H^\\mathsf T$ term is less clear, I'll explain it soon. If you ignore that term the equation for the Kalman gain is the same as the univariate case: divide the uncertainty of the prior with the of the sum of the uncertainty of the prior and measurement.\n",
    "\n",
    "$\\underline{\\textbf{Residual}}$\n",
    "\n",
    "$\\mathbf y = \\mathbf z - \\mathbf{H\\bar{x}}$\n",
    "\n",
    "This is an easy one as we've covered this equation while designing the measurement function $\\mathbf H$. Recall that the measurement function converts a state into a measurement. So $\\mathbf{Hx}$ converts $\\mathbf x$ into an equivalent measurement. Once that is done, we can subtract it from the measurement $\\mathbf z$ to get the residual - the difference between the measurement and prediction.\n",
    "\n",
    "The univariate equation is\n",
    "\n",
    "$$y = z - \\bar x$$\n",
    "\n",
    "and clearly computes the same thing, but only in one dimension.\n",
    "\n",
    "$\\underline{\\textbf{State Update}}$\n",
    "\n",
    "$\\mathbf x = \\mathbf{\\bar x} + \\mathbf{Ky}$\n",
    "\n",
    "We select our new state to be along the residual, scaled by the Kalman gain. The scaling is performed by $\\mathbf{Ky}$, which both scales the residual and converts it back into state space with the $\\mathbf H^\\mathsf T$ term which is in $\\mathbf K$. This is added to the prior, yielding the equation: $\\mathbf x =\\mathbf{\\bar x} + \\mathbf{Ky}$. Let me write out $\\mathbf K$ so we can see the entire computation:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf x &= \\mathbf{\\bar x} + \\mathbf{Ky} \\\\\n",
    "&= \\mathbf{\\bar x} + \\mathbf{\\bar PH}^\\mathsf T \\mathbf{S}^{-1}\\mathbf y \\\\\n",
    "&\\approx \\mathbf{\\bar x} + \\frac{\\mathsf{uncertainty}_\\mathsf{prediction}}{\\mathsf{uncertainty}_\\mathsf{measurement}}\\mathbf H^\\mathsf T \\mathbf y\n",
    "\\end{aligned}$$\n",
    "\n",
    "Perhaps a better way to *see* the ratio is to rewrite the estimate equation:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf x &= \\mathbf{\\bar x} + \\mathbf{Ky} \\\\\n",
    "&= \\mathbf{\\bar x} +\\mathbf K(\\mathbf z - \\mathbf{H\\bar x}) \\\\\n",
    "&= (\\mathbf I - \\mathbf{KH})\\mathbf{\\bar x} + \\mathbf{Kz}\n",
    "\\end{aligned}$$\n",
    "\n",
    "The similarity between this and the univariate form should be obvious:\n",
    "$$\\mu = (1-K)\\bar\\mu + K\\mu_\\mathtt{z}$$\n",
    "\n",
    "$\\underline{\\textbf{Covariance Update}}$\n",
    "\n",
    "$\\mathbf P = (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar P}$\n",
    "\n",
    "$\\mathbf{I}$ is the identity matrix, and is the way we represent $1$ in multiple dimensions. $\\mathbf H$ is our measurement function, and is a constant.  We can think of the equation as $\\mathbf P = (1-c\\mathbf K)\\mathbf P$. $\\mathbf K$ is our ratio of how much prediction vs measurement we use. If $\\mathbf K$ is large then $(1-\\mathbf{cK})$ is small, and $\\mathbf P$ will be made smaller than it was. If $\\mathbf K$ is small, then $(1-\\mathbf{cK})$ is large, and $\\mathbf P$ will be relatively larger. This means that we adjust the size of our uncertainty by some factor of the Kalman gain.\n",
    "\n",
    "This equation can be numerically unstable and I don't use it in FilterPy. The subtraction can destroy symmetry and lead to floating point errors over time. Later I'll share more complicated but numerically stable forms of this equation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### An Example not using FilterPy\n",
    "\n",
    "FilterPy hides the details of the implementation from us. Normally you will appreciate this, but let's implement the last filter without FilterPy. To do so we need to define our matrices as variables, and then implement the Kalman filter equations explicitly.\n",
    "\n",
    "Here we initialize our matrices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = 1.\n",
    "R_var = 10\n",
    "Q_var = 0.01\n",
    "x = np.array([[10.0, 4.5]]).T\n",
    "P = np.diag([500, 49])\n",
    "F = np.array([[1, dt],\n",
    "              [0,  1]])\n",
    "H = np.array([[1., 0.]])\n",
    "R = np.array([[R_var]])\n",
    "Q = Q_discrete_white_noise(dim=2, dt=dt, var=Q_var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.linalg import inv\n",
    "\n",
    "count = 50\n",
    "track, zs = compute_dog_data(R_var, Q_var, count)\n",
    "xs, cov = [], []\n",
    "for z in zs:\n",
    "    # predict\n",
    "    x = F @ x\n",
    "    P = F @ P @ F.T + Q\n",
    "    \n",
    "    #update\n",
    "    S = H @ P @ H.T + R\n",
    "    K = P @ H.T @ inv(S)\n",
    "    y = z - H @ x\n",
    "    x += K @ y\n",
    "    P = P - K @ H @ P\n",
    "    \n",
    "    xs.append(x)\n",
    "    cov.append(P)\n",
    "\n",
    "xs, cov = np.array(xs), np.array(cov)\n",
    "plot_track(xs[:, 0], track, zs, cov, plot_P=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results are identical to the FilterPy version. Which you prefer is up to you. I prefer not polluting my namespace with variables such as `x`, `P`, and so on; `dog_filter.x` is, to me, more readable.\n",
    "\n",
    "More importantly, this example requires you to remember and program the equations for the Kalman filter. Sooner or later you will make a mistake. FilterPy's version ensures that your code will be correct. On the other hand, if you make a mistake in your definitions, such as making $\\mathbf H$ a column vector instead of a row vector, FilterPy's error message will be harder to debug than this explicit code. \n",
    "\n",
    "FilterPy's KalmanFilter class provides additional functionality such as smoothing, batch processing, faded memory filtering, computation of the maximum likelihood function, and more. You get all of this functionality without having to explicitly program it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary\n",
    "\n",
    "We have learned the Kalman filter equations. Here they are all together for your review. There was a lot to learn, but I hope that as you went through each you recognized it's kinship with the equations in the univariate filter. In the *Kalman Math* chapter I will show you that if we set the dimension of $\\mathbf x$ to one that these equations revert back to the equations for the univariate filter. This is not \"like\" the univariate filter - it is a multidimensional implementation of it.\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\text{Predict Step}\\\\\n",
    "\\mathbf{\\bar x} &= \\mathbf{F x} + \\mathbf{B u} \\\\\n",
    "\\mathbf{\\bar P} &= \\mathbf{FP{F}}^\\mathsf T + \\mathbf Q \\\\\n",
    "\\\\\n",
    "\\text{Update Step}\\\\\n",
    "\\textbf{S} &= \\mathbf{H\\bar PH}^\\mathsf T + \\mathbf R \\\\\n",
    "\\mathbf K &= \\mathbf{\\bar PH}^\\mathsf T \\mathbf{S}^{-1} \\\\\n",
    "\\textbf{y} &= \\mathbf z - \\mathbf{H \\bar x} \\\\\n",
    "\\mathbf x &=\\mathbf{\\bar x} +\\mathbf{K\\textbf{y}} \\\\\n",
    "\\mathbf P &= (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar P}\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "I want to share a form of the equations that you will see in the literature. There are many different notation systems used, but this gives you an idea of what to expect.\n",
    "\n",
    " $$\n",
    "\\begin{aligned}\n",
    "\\hat{\\mathbf x}_{k\\mid k-1} &= \\mathbf F_k\\hat{\\mathbf x}_{k-1\\mid k-1} + \\mathbf B_k \\mathbf u_k  \\\\\n",
    "\\mathbf P_{k\\mid k-1} &=  \\mathbf F_k \\mathbf P_{k-1\\mid k-1} \\mathbf F_k^\\mathsf T + \\mathbf Q_k \\\\        \t\n",
    "\\tilde{\\mathbf y}_k &= \\mathbf z_k - \\mathbf H_k\\hat{\\mathbf x}_{k\\mid k-1}\\\\\n",
    "\\mathbf{S}_k &= \\mathbf H_k \\mathbf P_{k\\mid k-1} \\mathbf H_k^\\mathsf T + \\mathbf R_k \\\\\n",
    "\\mathbf K_k &= \\mathbf P_{k\\mid k-1}\\mathbf H_k^\\mathsf T \\mathbf{S}_k^{-1}\\\\\n",
    "\\hat{\\mathbf x}_{k\\mid k} &= \\hat{\\mathbf x}_{k\\mid k-1} + \\mathbf K_k\\tilde{\\mathbf y}_k\\\\\n",
    "\\mathbf P_{k|k} &= (I - \\mathbf K_k \\mathbf H_k) \\mathbf P_{k|k-1}\n",
    "\\\\\\end{aligned}\n",
    "$$\n",
    "\n",
    "This notation uses the Bayesian $a\\mid b$ notation, which means $a$ given the evidence of $b$. The hat means estimate. Thus $\\hat{\\mathbf x}_{k\\mid k}$ means the estimate of the state $\\mathbf x$ at step $k$ (the first $k$) given the evidence from step $k$ (the second $k$). The posterior, in other words. $\\hat{\\mathbf x}_{k\\mid k-1}$ means the estimate for the state $\\mathbf x$ at step $k$ given the estimate from step $k - 1$. The prior, in other words. \n",
    "\n",
    "This notation, copied from [Wikipedia](https://en.wikipedia.org/wiki/Kalman_filter#Details) [[1]](#[wiki_article]), allows a mathematician to express himself exactly. In formal publications presenting new results this precision is necessary. As a programmer I find it fairly unreadable. I am used to thinking about variables changing state as a program runs, and do not use a different variable name for each new computation. There is no agreed upon format in the literature, so each author makes different choices. I find it challenging to switch quickly between books and papers, and so have adopted my admittedly less precise notation. Mathematicians may write scathing emails to me, but I hope programmers and students will rejoice at my simplified notation.\n",
    "\n",
    "The **Symbology** Appendix lists the notation used by various authors. This brings up another difficulty. Different authors use different variable names. $\\mathbf x$ is fairly universal, but after that it is anybody's guess. For example, it is common to use $\\mathbf{A}$ for what I call $\\mathbf F$. You must read carefully, and hope that the author defines their variables (they often do not).\n",
    "\n",
    "If you are a programmer trying to understand a paper's equations, I suggest starting by removing all of the superscripts, subscripts, and diacriticals, replacing them with a single letter. If you work with equations like this every day this is superfluous advice, but when I read I am usually trying to understand the flow of computation. To me it is far more understandable to remember that $P$ in this step represents the updated value of $P$ computed in the last step, as opposed to trying to remember what $P_{k-1}(+)$ denotes, and what its relation to $P_k(-)$ is, if any, and how any of that relates to the completely different notation used in the paper I read 5 minutes ago."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: Show Effect of Hidden Variables\n",
    "\n",
    "In our filter velocity is a hidden variable. How would a filter perform if we did not use velocity in the state?\n",
    "\n",
    "Write a Kalman filter that uses the state $\\mathbf x=\\begin{bmatrix}x\\end{bmatrix}$ and compare it against a filter that uses $\\mathbf x=\\begin{bmatrix}x & \\dot x\\end{bmatrix}^\\mathsf T$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution\n",
    "\n",
    "We've already implemented a Kalman filter for position and velocity, so I will provide the code without much comment, and then plot the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from math import sqrt\n",
    "from numpy.random import randn\n",
    "\n",
    "def univariate_filter(x0, P, R, Q):\n",
    "    f = KalmanFilter(dim_x=1, dim_z=1, dim_u=1)\n",
    "    f.x = np.array([[x0]])\n",
    "    f.P *= P\n",
    "    f.H = np.array([[1.]])\n",
    "    f.F = np.array([[1.]])\n",
    "    f.B = np.array([[1.]])\n",
    "    f.Q *= Q\n",
    "    f.R *= R\n",
    "    return f\n",
    "\n",
    "def plot_1d_2d(xs, xs1d, xs2d):\n",
    "    plt.plot(xs1d, label='1D Filter')\n",
    "    plt.scatter(range(len(xs2d)), xs2d, c='r', alpha=0.7, label='2D Filter')\n",
    "    plt.plot(xs, ls='--', color='k', lw=1, label='track')\n",
    "    plt.title('State')\n",
    "    plt.legend(loc=4)\n",
    "    plt.show()\n",
    "    \n",
    "def compare_1D_2D(x0, P, R, Q, vel, u=None):\n",
    "    # storage for filter output\n",
    "    xs, xs1, xs2 = [], [], []\n",
    "\n",
    "    # 1d KalmanFilter\n",
    "    f1D = univariate_filter(x0, P, R, Q)\n",
    "\n",
    "    #2D Kalman filter\n",
    "    f2D = pos_vel_filter(x=(x0, vel), P=P, R=R, Q=0)\n",
    "    if np.isscalar(u):\n",
    "        u = [u]\n",
    "    pos = 0 # true position\n",
    "    for i in range(100):\n",
    "        pos += vel\n",
    "        xs.append(pos)\n",
    "\n",
    "        # control input u - discussed below\n",
    "        f1D.predict(u=u)\n",
    "        f2D.predict()\n",
    "        \n",
    "        z = pos + randn()*sqrt(R) # measurement\n",
    "        f1D.update(z)\n",
    "        f2D.update(z)\n",
    "        \n",
    "        xs1.append(f1D.x[0])\n",
    "        xs2.append(f2D.x[0])\n",
    "    plt.figure()\n",
    "    plot_1d_2d(xs, xs1, xs2)\n",
    "\n",
    "compare_1D_2D(x0=0, P=50., R=5., Q=.02, vel=1.) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Discussion\n",
    "\n",
    "The filter that incorporates velocity into the state produces much better estimates than the filter that only tracks position. The univariate filter has no way to estimate the velocity or change in position, so it lags the tracked object. \n",
    "\n",
    "In the univarate Kalman filter chapter we had a control input `u` to the predict equation:\n",
    "\n",
    "```python\n",
    "    def predict(self, u=0.0):\n",
    "        self.x += u\n",
    "        self.P += self.Q\n",
    "```\n",
    "\n",
    "Let's try specifying the control input:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_1D_2D(x0=0, P=50., R=5., Q=.02, vel=1., u=1.) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here the performance of the two filters are similar, and perhaps the univariate filter is tracking more closely. But let's see what happens when the actual velocity `vel` is different from the control input `u`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_1D_2D(x0=0, P=50., R=5., Q=.02, vel=-2., u=1.) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we are tracking a robot which we are also controlling the univariate filter can do a very good job because the control input allows the filter to make an accurate prediction. But if we are tracking passively the control input is not much help unless we can make an accurate *apriori* guess as to the velocity. This is rarely possible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How Velocity is Calculated\n",
    "\n",
    "I haven't explained how the filter computes the velocity, or any hidden variable. If we plug in the values we calculated for each of the filter's matrices we can see what happens.\n",
    "\n",
    "First we need to compute the system uncertainty.\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\textbf{S} &= \\mathbf{H\\bar PH}^\\mathsf T + \\mathbf R \\\\\n",
    "&= \\begin{bmatrix} 1 & 0\\end{bmatrix}\n",
    "\\begin{bmatrix}\\sigma^2_x & \\sigma_{xv} \\\\ \\sigma_{xv} & \\sigma^2_v\\end{bmatrix}\n",
    "\\begin{bmatrix} 1 \\\\ 0\\end{bmatrix} + \\begin{bmatrix}\\sigma_z^2\\end{bmatrix}\\\\\n",
    "&= \\begin{bmatrix}\\sigma_x^2 & \\sigma_{xv}\\end{bmatrix}\\begin{bmatrix} 1 \\\\ 0\\end{bmatrix}+ \\begin{bmatrix}\\sigma_z^2\\end{bmatrix} \\\\\n",
    "&= \\begin{bmatrix}\\sigma_x^2 +\\sigma_z^2\\end{bmatrix}\n",
    "\\end{aligned}$$\n",
    "\n",
    "Now that we have $\\mathbf S$ we can find the value for the Kalman gain:\n",
    "$$\\begin{aligned}\n",
    "\\mathbf K &= \\mathbf{\\bar PH}^\\mathsf T \\mathbf{S}^{-1} \\\\\n",
    "&= \\begin{bmatrix}\\sigma^2_x & \\sigma_{xv} \\\\ \\sigma_{xv} & \\sigma^2_v\\end{bmatrix}\n",
    "\\begin{bmatrix} 1 \\\\ 0\\end{bmatrix}\n",
    "\\begin{bmatrix}\\frac{1}{\\sigma_x^2 +\\sigma_z^2}\\end{bmatrix} \\\\\n",
    "&= \\begin{bmatrix}\\sigma^2_x  \\\\ \\sigma_{xv}\\end{bmatrix}\n",
    "\\begin{bmatrix}\\frac{1}{\\sigma_x^2 +\\sigma_z^2}\\end{bmatrix} \\\\\n",
    "&= \\begin{bmatrix}\\sigma^2_x/(\\sigma_x^2 +\\sigma_z^2)  \\\\ \\sigma_{xv}/(\\sigma_x^2 +\\sigma_z^2)\\end{bmatrix}\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "In other words, the Kalman gain for $x$ is \n",
    "\n",
    "$$K_x = \\frac{VAR(x)}{VAR(x)+VAR(z)}$$\n",
    "\n",
    "This should be very familiar to you from the univariate case. \n",
    "\n",
    "The Kalman gain for the velocity $\\dot x$ is\n",
    "$$K_{\\dot x} = \\frac{COV(x, \\dot x)}{VAR(x)+VAR(z)}$$\n",
    "\n",
    "What is the effect of this? Recall that we compute the state as \n",
    "\n",
    "$$\\begin{aligned}\\mathbf x \n",
    "&=\\mathbf{\\bar x}+\\mathbf K(z-\\mathbf{Hx)} \\\\\n",
    "&= \\mathbf{\\bar x}+\\mathbf Ky\\end{aligned}$$\n",
    "\n",
    "Here the residual $y$ is a scalar. Therefore it is multiplied into each element of $\\mathbf K$. Therefore we have\n",
    "\n",
    "$$\\begin{bmatrix}x \\\\ \\dot x\\end{bmatrix}=\\begin{bmatrix}\\bar x \\\\ \\bar{\\dot x}\\end{bmatrix} + \\begin{bmatrix}K_x \\\\ K_{\\dot x}\\end{bmatrix}y$$\n",
    "\n",
    "Which gives this system of equations: \n",
    "\n",
    "$$\\begin{aligned}x& = \\bar x + yK_x\\\\\n",
    "\\dot x &= \\bar{\\dot x} + yK_{\\dot x}\\end{aligned}$$\n",
    "\n",
    "The prediction $\\bar x$ was computed as $x + \\bar x \\Delta t$. If the prediction was perfect then the residual will be $y=0$ (ignoring noise in the measurement) and the velocity estimate will be unchanged. On the other hand, if the velocity estimate was very bad then the prediction will be very bad, and the residual will be large: $y >> 0$. In this case we update the velocity estimate with $yK_{\\dot x}$. $K_{\\dot x}$ is proportional to $COV(x,\\dot x)$. Therefore the velocity is updated by the error in the position times the value proportional to the covariance between the position and velocity. The higher the correlation the larger the correction. \n",
    "\n",
    "To bring this full circle, $COV(x,\\dot x)$ are the off-diagonal elements of $\\mathbf P$. Recall that those values were computed with $\\mathbf{FPF}^\\mathsf T$. So the covariance of position and velocity is computed during the predict step. The Kalman gain for the velocity is proportional to this covariance, and we adjust the velocity estimate based on how inaccurate it was during the last epoch times a value proportional to this covariance. \n",
    "\n",
    "In summary, these linear algebra equations may be unfamiliar to you, but computation is actually very simple. It is essentially the same computation that we performed in the g-h filter. Our constants are different in this chapter because we take the noise in the process model and sensors into account, but the math is the same."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adjusting the Filter\n",
    "\n",
    "Let's start varying our parameters to see the effect of various changes. This is a very normal thing to be doing with Kalman filters. It is difficult, and often impossible to exactly model our sensors. An imperfect model means imperfect output from our filter. Engineers spend a lot of time tuning Kalman filters so that they perform well with real world sensors. We will spend time now to learn the effect of these changes. As you learn the effect of each change you will develop an intuition for how to design a Kalman filter. Designing a Kalman filter is as much art as science. We are modeling a physical system using math, and models are imperfect.\n",
    "\n",
    "Let's look at the effects of the measurement noise $\\mathbf R$ and process noise $\\mathbf Q$. We will want to see the effect of different settings for $\\mathbf R$ and $\\mathbf Q$, so I have given the measurements a variance of 225 meters squared. That is very large, but it magnifies the effects of various design choices on the graphs, making it easier to recognize what is happening. Our first experiment holds $\\mathbf R$ constant while varying $\\mathbf Q$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/j4uLS0megvCY0el0bNmyhZYtW2JlZVXW4QjlnLhehHslrpWK4+mnn2bTpk0ArFu3jsjISIv1ffr0YfPmzQCsX7/ePJpkSXqU18u8efN4/fXXAXBycuKNN96gYcOGHD16lC+//JKkpCQAxo4dy1tvvfXQx3vnnXfMTdXr1avHpEmTqF27Nrt372bs2LGcO3cOgPfee88cV0VUWFjIypUr2bp1K1qtlsqVK9OvXz+CgoIe6XHT09OpVq1ayQ02JFUQ/fr1k5o0aWKxbNSoUVLDhg0lSZIko9EoeXp6SpMnTzavLywslBwdHaUZM2bc83GysrIkQEpNTS2ZwIXHVlFRkbRs2TKpqKiorEMRKgBxvQj3SlwrFcfs2bMlQAKkunXrSgkJCZIkSZLBYJBmzpxpXhcQECDp9fpHEsOjvF4iIyPN57B161aLdWfOnJHkcrkESD4+PpLRaHzo412+fFlycXExH/NuP/7+/lJ6evpDH+tJlJqaKgFSVlZWiZRXYTpWv/766+zdu5cJEyYQGxvLggUL+OGHHxg+fDhgasY0atQoJkyYwNKlSzl58iSDBw/GxsaG/v37l3H0giAIgiA8bvr27Yu/vz8Ahw8fJjAwkCZNmhAYGGgxKuSbb76JQqEoqzAf2LFjxwAIDg6mefPmFutCQkJo2rQpYJrHKzU19aGP5+/vz8aNG/9xbpfg4GA2bdqEs7PzQx9LeHgVpjlT/fr1Wbp0Ke+88w4ff/wxVapU4euvv2bAgAHmbcaMGUNBQQGvvPKKebK5DRs2iDkiBEEQBEEocdbW1qxatYqYmBhSUlLQ6XTs2rXLYpvhw4fzyiuvlFGED+dW59uioqK79jEtKioqtu3Dqlu3LufPn+e3335jyZIlpKen4+7uTr9+/ejVqxdqtbpEjiM8vAqTRAB07tyZzp07/+N6mUzGuHHjGDduXOkFJQiCIAjCE6tWrVocPXqUb7/9lp9//pmUlBTkcjktW7bktddeo0uXLhV2tMcGDRqwY8cOLl++zMqVK+natat53YEDB9izZw8AVatWLdF+pLa2trzwwgu88MILJVamUPIqVBIhCIIgCIJQ3nh6ejJhwgQ+++wzCgoKUKlUKJUV/xZr2LBh5kl++/bty4gRI2jWrBkHDx7k66+/ttiuoiZKwoOr+Fe4IAiCIAhCOSCTybCxsSnrMEpMnz59WLBgAatWrUKr1TJlyhSmTJlisU10dHSFba4lPJwK07FaEARBEARBKD0KhYLFixfzyiuvoFKpLNbJ5XL69+/P+vXrsba2LqMIhbIkaiIEQRAEQRCEu1Kr1UybNo2PPvqIP//8k+vXr+Ps7Ey3bt3MI1MJTyaRRAiCIAiCIAj/yt3dnZdffrmswxDKEdGcSRAEQRAEQRCE+yKSCEEQBEEQBEEQ7otIIgRBEARBEARBuC8iiRAEQRAEQRAE4b6IjtWCIAiCIAjCE+3cuXOsXr2anJwcfH196dmzJ87OzmUdVrkmkghBEARBEAThiZSSksJzzz3HmjVrLJa/+uqrjBw5kk8//RSFQlFG0ZVvIokQBEEQBEEQnjjp6ek0b96cc+fOFVtXUFDApEmTSElJ4aeffkImk5VBhOWb6BMhCIIgCIIgPHEmTJhgTiA8PDyYPHkyK1asYPjw4ebah9mzZ7N169YyjPK2ixcvcuDAPiAX0Jd1OKImQhAEQRAEQXiyFBYW8vPPPwOmWbl3795NYGAgAF26dCE8PJyhQ4cCMGPGDFq2bFmix5ckie0XUtlzMQ2jJGE0SkiAJIHBaEAmk1OYn0vcsb341ayNxk5DyqVz5GbeICAhD29HT55vWg0bVdndyoskQhAEQRAEQXiiXLhwgYyMDAA6d+5sTiBuGTx4MG+88Qa5ubns27evxI4rSRK7L6bx5YZzHL6SCYCxMB+52gaAgvgjyBQKNP7hSEYD2oQ8VAUpKDR2gBvgxp79BUA8a06m8cPAevi52JRYfPdDJBGCIAiCIAjCE0WSJPNrKyurYusVCoW5SZPRaCyRY+6PT+fLDefYdfw8cisN1nYONPfScf3sUeo2i8FKIyejeiAKhQIXD1tkgEzWCBmADGSAXCbDKEn8uq+IM0nZdPnfTv7Xry5Ngt1KJMb7IZIIQRAEQRAE4YlStWpV7OzsyM3NZeXKlSQlJeHl5WVev2jRIrKysgCIiIh4qGOt3XeS71Yf4nSR6UZff/UkXZpV47MXq+KgKuLGjUZ4e9vcTFqq31OZfetX4eX5pzl+NYtBP+/jnQ41eKFplVLtAC46VguCIAiCIAhPFBsbGwYOHAhAXl4eTZs2Zfbs2ezbt4/x48fz/PPPm7e91TfivxQVFZnLW7ZsCduOHWfI7B08/8N2Dp66iFIO/aOs2TW9Cz+MjsDdQYZGo8bPz/O+h5H1dtKwaGhDnqrni1GCz9acYdTCoxQUGe6rnIchaiIEQRAEQRCEJ84HH3zAypUruXr1KhcvXuS5554rtk337t3p0KFDseXZ2dlcunSJ8PBwwMC6dStRKnW0aRPJpcw0Zu2L59iWIhTWDlh7VKZn+xBea22Ln0vJ3XprrBR88VQ4tXwc+XjVaZYfvcaFlFxmllI/CVETIQiCIAiCIDxxvLy82LZtG5GRkcXWyWQy+vfvz5QpU5DJZBiNBhYtms+FC4eBFDIyTnDo0Cq02gPAUWrVUmPjYcPwBXF0+i6Fk1INlDYO9IjQsGm0G1/0dizRBOLOOJ9tFMCvL0ThaqvidFI2Xf+3k92xqSV+rL8TNRGCIJS569evc/78eVQqFbVq1cLa2rqsQxIEQRCeAAEBAezatYsDBw6wcOFCYmPP07RpPQYM6MXly/EcO7aOqlVbIJcXUrUqODqmARL+/mqGDGkHQEK6nqk7VSw/qsUoaQHoFK7h9TZ2BLmXzq12dKArK19twtB5hziRmMUzP+3j3Y41eL7Jo+snIZIIQRDKzKlTp/jggw9YsWIFBoOpHaeTkxPPPfccH330EQ4ODmUcoSAIglCRxMbGsnLlSjIzM/H29qZnz55UqlTJvD4vL4+MjAx8fX0BA4sW/ULVqt40bhxMeHg/Dh06Tv36NbG1lfDw8Eap9ANMiUG9ejXM5chkMiRJ4o+DBYxfmUNekWm0p7ahal6PsaOGV/ERnx41bydr/ni5Ie8uPcGfhxP5dPUZTiZmMbFnONaq++tzcS9EEiEIQpnYvXs37dq1Izc312J5ZmYmU6dOZdOmTWzduhVnZ+cyilAQBEGoKNLS0njxxRdZunSpxfLXXnuNnj178u23X1Opki2xsfs5dOgAQ4Z0RCYrIjq6Eg4OKiATe3sVLVrcbtqkVqv+8XipuQbeXpLNpjOFAERWtuKjLg7U8i395OFOGisFX/auTS0fRz5dfYZlR69x4bqpn0RJ1/GLPhGCIJQ6rVZL7969zQmEp6cnw4YN4+mnn0alMn1pHz9+nFGjRpVhlIIgCEJFkJOTQ4sWLSwSCJUK3NzAw6OI7dt/58MPn0KSzhISYs2AAc2QyUwjKQUEeOPi4nhfx9twSku7r9LYdKYQKwW83cGOhUNdyjyBuEUmkzGkcRXmPx+Fi62KU9ey6fq/XRy4lFGixxE1EYIglLrFixdz7do1AJo2bcq6deuwsTGNJHHu3DkaNGhAdnY2v/32G1988QXu7u5lGa4gCIJQzly/fh21Wo2joyPjx79HXNxJvL3Bz8+Jzp074OfnT1paAosWLUKn07N//062b99O8+bNH/iYuYVGPl6Zw6KDBQCEeCqZ2seRUO/ykTz8XcOqt/pJHORkYjbDFhwt0fJFTYQgCKVu7dq15tcff/yxOYEAqF69Oi+88AIAOp2Ov/76q9TjEwShYjMajaxcuZKuXbsSHBxMzZo1efnllzl+/HhZhyY8oOTkZI4ePQrogSz++msxZ85swGA4zNGjCwgIAC8vGQsW/MD777/Bs8/2ZvTo0YwbN85cxpIlSx74+Pvji+jwTRqLDhYgk8HQZrYsH+FabhOIW3ycrFn8ciN6RPhgMEr/vcN9EDURgiCUury8PPPrqlWrFlsfFBRkfv33PhPCv7t06RKLFi0iJSUFFxcXevbsSY0aNf57R0F4TOTk5NCzZ082bdpksfz06dPMnDmT8ePH8+GHH5ZRdMK/MRqNFBYWYm1tTUFBAZs2radBg3A8PGxJTz9GbOwpatfWI5PJ6NSpJra21ly/fo2MjDQ0GoiKiiIwMNCizJiYGKZMmUJGRiYnT56875gK9RJTN+byw/Y8JAl8nORM7eNEVOA/95d4FIxGI6dOxWFvb0NAgPd97auxUjC1T20C7CVGfV1yMYmaCEEQSl3lypXNr1evXl1s/apVq8yvAwICSiOkCi8vL49nnnmGwMBAxo4dy9SpU3n//fcJDQ2lc+fOpKY++jHDH0dFRUUcPHiQ7du3k5CQUNbhCPdgwIABFgmEra0tSuXtZ6YfffQRP/zwQ1mEJvxNbm4uJ0+eRJIkQMf69X+yffsyIA61+gI2NknIZBeBq4SGuvHUU83Nw5U6ONihUChu7mty5//zLXK5HIXCtNxoNN5XfGeTdXT7Xxozt5kSiN71rFk3yq3UE4idO4/i4tKK8PCnmTnzzwcqQyaT8UyUf4nGJZIIQRBK3bPPPmt+/fbbb7No0SL0ej2ZmZm89957rFmzBgA/Pz9atmxZVmFWGHq9nq5du/Lrr79a/EG9ZfXq1bRp00bU6twHrVbLhx9+iK+vL/Xr16d58+b4+/sTExPD7t27yzo84R8cPHiQlStXAqbhov/880+ysrJIT0/no48+Mm/38ccfo9fryyrMJ86tIbwlSWLjxg3ExZ0B0snIOM2+fSvIz98HHKduXQfq1XMHMpDLdbRu3QB3d5d/Ldvd3R0nJ1PH6L1795r7292yc+dO80OUkJCQe4vXKDFzWx5dv0vjbLIeF1sZMwc68UVvR+w1j+bWOT09ixUrtjFmzDecPh1nsS4oyJesLNP3965dxx7J8R+ESCIEQSh1devWpXv37gBkZWXRt29f7O3tcXV1ZcKECebtPvroo7s+WRIs/frrr2zevBkAe3t7PvnkE7Zu3cqXX35pHh/92LFjfPfdd2UZZoWh1Wrp0KEDn3zyCTdu3LBYt2nTJlq0aMHy5cvLKDrh38ydO9f8etKkSfTo0QOFQoG9vT3jxo2jU6dOACQmJpp/Z4SSl5uba07SDh7cw9Kl84AryGTnUKmuIJfHAvH4+MgYMiQGW1tTvwIPD1fc3Jzu61hKpZJu3boBpgcqL774EkuXLuXEiZP8/PPPvPfee+Zte/bs+Z/lJaTr6fdjOhPX5lBkgDY11Kwf5Ua7mpr7iuvfGAyGYg98fvttPd26vcEXX8xj48Z9Fus8Pd1o1Cicnj1b0rdvTInF8bDEX2dBEMrEvHnz6N27N+vWrQNMN263yGQyPv30U55//vmyCq9CmTFjhvn1kiVLiIkx/ZFp3rw5MTEx1K5dG0mSmDFjBm+//fYjm730cTF+/Hi2bt0KgEKhoGvXrvj7+7Ny5Uri4uLQ6XQMGDCA+Ph4i0mshLJ35coV8+uOHTsWW9+5c2dzE8rLly+XWlyPu6ysLHQ6HW5ubmRnX+f33+fRoUM0fn4O+Pvn4uTkBJgS8ubNI8z7yeUl8yx70KBB/PXXZq5evUpycjKffvpZsW2io6No3br1P5aRmGlg8cECftyRR26hhK1Kxged7elb37rEvjPnzFnJL7+s4uDBM5w48btF34YmTeqYX+/ceZSRI/tZ7Ltr188lEkNJEjURgiCUCTs7O1avXs3atWvp2bMnISEhhIeHM2LECE6ePMm7775b1iFWGIcPHwYgMDCQNm3aWKyrVasWTZo0AUw3WGlpaaUeX0VSUFDAzJkzAdMTzl27dvHnn3/y9ddfc+7cOXr16gWY+qD89NNPZRmqcBd2dnbm17GxscXWnz9/3vza3t6+VGJ6HOXn59/sy2AE8tm7dy179y4FjuHgkEC7dtXx8FAARbi7uxAU5PdI43FycuKHH2ZSp06dYutkMujQoT1TpnyJQmE5a7NWJ7HiWAEDf0qnyeQbfLUpl9xCicjKVqwd6crTDWzuO4HIzMxh06Z9zJxZfCSoS5eusXXrIXJz89m3z7KTd1hYVcaMGcSff37BtGlj7+uYZUXURAiCUGbkcjnt27enffv2ZR3KY+Fu/SH+bblQ3IEDB8jIME3I1Lt3b6KioszrlEolkyZNMg8TuX79et5+++0yifNJIUkSO3bs4Mcff+TkyZMolUoaNmzIyy+/TGhoaLHtO3bsyK+//grA+++/z/r1682JxenTp5k1axYAKpXqX59KCyaSJJlvovft20elSi4EBnqSnR3Hvn2r8fNLx9HRlsaNfVCprDANvwqVK3uVeqweHh789NMsTp48ybZt28jJycHNzY127drj5+drcU4nE/X8caiAZUcKyNbe/n5sGKiiT31rutbWoJD/e/Kg0+nJyMgu1mejRYuhHDt2HrlczjPPdMTW9vY80Q0a1ATAz8+DgoJCi/0UCgWTJ7/2wOdfFkQSIQiCUMHVq1ePPXv2EB8fz4YNG2jXrp153bFjx9i1axdgGhXL1dW1rMKsEO7sfH634YfvHC1MdFR/tAoLC3n22WdZuHChxfKDBw/yv//9j48++ogPP/zQ4klxr169GDNmDImJiezevZvAwEC6d+9Oeno6K1asQKfTAaYRnERTNEsGg4Hr16/j4uKCWq3m+PFDnDlznL592wP55OQcx97eCQjE3d3I4MFtzE/27exs/q3oUhUWFkZYWFix5el5RpYdKWDRwQLOJt/uVO/tKOepSGueqmuNv6vlbbEkSej1Bqysbi8vLCyidu1+XLx4lejoWuzYMctinwYNanLs2HmMRiOHD5+ladPbzbdatozk2rV1eHm5ldTplimRRAiCIFRwL7/8Mnv27AFMN1FvvPEGzZs35+DBg3z++efmmoiXX35Z9If4D3cmCStXruTjjz+2+MzuHJL4zqGKhZL3yiuvWCQQcrncPESnJEmMGzcONzc3hg8fbt5GrVazePFi2rVrR3Z2Njdu3ODHH3+0KDciIoKvvvqqdE6inDtz5gwyGYSEVKGwMJWVK38lJqY+Vaq44umZjlJpB5hGO2rTpq55v5Lqy/Co6Q0SOy4U8cehfDaeLkRnGiQKlRLa19TQO9KaRlVVxWod9u49wWuvfcH581d4++3BvP32YPM6tVpFdnYeer2B8+ev8HedOzdBrbaiQYOahIQEWKyzttZgbf3gHbQlSeLQoUMcOHCQxER7AgJC6dOnDw4ODg9c5sOoGFeBIAiC8I/69+9v7guRl5fHxx9/TOvWrRk7dqy5D0RERASvvvpqWYZZIYSGhhIZGQmYanGGDh1KSkoKRqORNWvWMGzYMPO2gwcPLqMoH38XLlzg559NHUmtra2ZNWsW+fn5ZGRk8MEHH5i3Gz9+PIWFls1CoqOj2bdvH3369LEY3c3FxYWxY8eybds2HB0dS+dEygHT03TTk/dr167xxx8L0OtTgCukpR0mPX0fcAobmxR6925A5cr2gB53dxdCQwP/rehySZIkTl/T8fm6HBpPvsGQORmsOWFKIGr5KPmkmwMH3nVncPVkdi5eQO+nxpCQkGxRhlptxYEDp8nKyuX8+eId8CMiqlO7djVatKiHTmc5VHDXrs357rsxDBzYiUqVnEvsvM6fP8/TT/dj6NCXmTVrFlOnfsWLL76Ij48PX3zxRZk0WxU1EYIgCBWcUqlk+fLlvPLKK8ybN6/YhErdunXj559/xtbWtowirFg+/vhjOnXqhCRJ/Pjjj/z4449oNBqLEcQaNmxIhw4dyjDKx9udQ7V+8MEH5pHa1Go1H3/8MadPn2bJkiXcuHGDtWvXmoeMviUkJISFCxeSlpbGhQsXUKlU1KxZE7VaXZqnUSaKiorIzs7Gzc0NMLJgwWzCwgKoXTsAG5treHsXoNdfRKlU06SJ5bwJzs5l80T7YRXpJfbFF7HpdCGbzmhJzLz9HehkLaOJbwHDO/pQw8vKvHzp0i18+qlpcIQBA9rj5+dpXhcc7I9cLsfPzwMnp+Id8Fev/uYRnk1xcXFxvPjiS3dtQpmbm8uYMWPIzc1l/PjxpRqXSCIEQRAeAzY2NsyZM4dPPvmEP/74g5SUFFxcXOjRowfVqlUr6/AqlA4dOvDTTz8xdOhQcxv6OxOIqKgoli9fXmykF6HkXLp0yfz61hwAd+rWrZu5g3t8fPw/luPq6vrY9wPS6XQkJiaSn5+Po6M1x4/v5PTpYwwa1AHIp0EDF1xdZUAmTk42NG5cp4wjLhmZ+Ua2nitk45lCtp0rJLfw9pN4aysZTYNVXPzrD7YumMNJycDn2duA20lE/fq3O+YfPnyWXr1ud7S3s7MhL28HGk35SDqnTp1qTiCCgoJ45plnsLaO4Lfflptr7D755BOeffZZAgNLr/ZIJBGCIAiPET8/P0aPHl3WYVR4Q4YMoWXLlsycOZMNGzZQUFBAYGAgzz33HF27dhWTID5id9aaxcfHFxuJ6c7E4UmpYbtzpKTjx48jSXpq1w7GaLzOhQu7uX7dD0dHb2rUUBEUFAHkAaan6o+Ly2l6Np4uZNOZQg5cKsJwR6WrRiqgR5QLMaFqGlVVo7GS8dzWJIz6IgCOHTtPw4bh5u0bN67N3LnjiYwMpXr14v2byksCkZiYyJ49ewHw9PRg9uyfsbGxAWrQpk1XPDw8mDhxornmdOLEiaUWm/gWFARBEIS7CAgIYOLEiaX6R1kwadu2rXm+jo8//pgWLVqYk4WEhASmTZsGmCam/PvcKI+L1NRUNBoNdnZ2XLkSx6ZNa3nmmS6oVHqKis4gSYWAhFqtp1OncAIC3AEshhSt6CRJ4vAVHZvOFLLuRD7xaZbt/kM8lRxb8wfpJ7bjZExnwqR1FgMhNGwYzuHD56hfPxR7e8sRpFxdnRg4sFOpnMfDOHv2rPl1p06dbiYQt73yyivm76hDhw6VamwiiRAEQRAEoVzp2rUrlStX5vLly+zfv5+goCD69OlDbm4uCxcuJC/P9JS9S5cupdp841G6evUqaWlp1K4dCuSzZs0CatasTL16gbi4ZFK/vhumkZKsiIwMsthXqXz8mtZdzTAwdkkWu2KLzMtkkpFGwRra1FDTpoYaPxclHdafYV3yBa4DV6+mWPRtePHFHrz4Yo8yiP7JIJIIQRAEQRDKFaVSyaJFi4iJiSE7O5vk5GS+/fZbi22qVq3KjBkzyijCB2c0GpHL5eTm5rJlyyYaN47AxUVFevpRrlyJo3Zt02g/XbuGY2dnDRRhZ2dDrVpB/15wBXbiRCy//baeo0fPMXJkf1KdwpmwOoe8IgmNEtKObyM/dh9Btpn8Ovlni33Hjh3EyJFPU79+KK6uTmVzAo9QSMjtzu+rV69hyJAhWFvfrm2aPn26+XW9evVKNTaRRAiCIAiCUO40aNCAvXv38u6777JixQrzqGM2NjY888wzfPrpp+V+wjij0UhGRoa5c/eGDauwstLTsmUEGk0WGk0ikmQPOBEe7kV4+O2Znu82KlBFVlCg5eTJixw9ep6BAzta9Dk4f/4yEyfORmFficw6NlwzZgNQP8CKL55y5OnOa7FyVdKoUR2LviEALVpElvq5lCYfHx8aNoxmz569XLmSTOfOT/PaayOwtU1m4cJl5lnYZTIZL7zwQqnGJpIIQRAEQRDKpRo1arB06VKSkpI4c+YMSqWSOnXqlNnkWvciLi4OJycnXFwcuXTpJJs2bWDgwA5YW+upVk1CobACUlEqISYmuqzDvW9/v4m/Vy+/PJG5c02TNdarV4O6dW8/Ya9duzp2tdvh3PJ5rhlt0FjBW+3sGdzIBoVcxp49s5+oiTJvfcY6nZ716/fSt+8wNm06xdWrOZw6lcjmze8U2+f999+natWqpRqnmGxOeCQkSeLKlSucOnWK9PT0sg5HEARBqMC8vLxo1aoVzZo1K7ME4lZNSH5+PsePH785yZ3EoUN7WLFiIZAGXGPPnhXEx/8FHMXHJ59u3WqjVhcABgICvC3a7FckWp3EpLU51Pgwhf4/prPkUAH5RZZz0ixatJGhQz+jY8fXiu1fp87toaaPHLndWfhapoGPt9ng2v5V5Gob6lW2Ys1rbjzfxNY8k/TjnkDk5RWYr689e06zevVRwA8rq1rY2YUTFBTD779vJyCgJn+fU87W1pZJkyaV+hwRUIFrIiZOnMi7777LyJEj+frrrwHTjev48eP54YcfyMjIICoqimnTplGzZs2yDfYJIkkSc+bM4auvvuLEiROA6Ze/U6dOvPfee0RHV7ynLoIgCMKT5dq1a6SmphIeXgvQsWjRbwQG+hAZGYpWe52DB9fg45OFWm2Dh0cG1tZy4BIAffo0xMrKdHulVqvw8Kj481QcTSjizT+yiL1uAGD3xSJ2Xyzig+UyOtbS0KuuhqgqKr799nd27ToGQHJyKp6ebuYymjSpw+DBXahTpxpNm0YgSRKLDhbw6aoccgol1EpT7cOQxjbm5OFxdf16OnK5HDc3J27cyGfp0p306NGTSpUC8PPzwM2tADCNttWiRUvAlEifOHGCrVu3smXLFrRaLcHBwfTp06fMZmCvkEnEgQMH+OGHHwgPD7dY/vnnnzN16lTmzJlDtWrV+PTTT4mJieHcuXPY2z9ebQvLI0mSeOmll8zt8+5cvmrVKtatW8eCBQvo3bt3GUUoCIIgCCZpaWnIZDJcXFzIzs5i5co/iYlphLu7HampR4mLiyU8XA9I1K3riIODBCTh4gLPPdfOXI6vr4dFubcSiLsxGCUy8o2k5Zp+UvNuv87WSrQMUdOyevmYnwCgUC/x9aZcZm7LwyiBm50c+4urOXc1D5vQluTjyuJDBSw+VICvswLHJgNQnkqB3BucOBFrkUTUr1+T2bNND3WTsgwMnp3BtvOmkZci/K2Y0tuRqpUq5G3pf7pxI4OLF68SHV0XsGXPnuPY27vRqlULXF1lxMT44ujoA6jw9fX9x3JkMhktW7akZcuWpRb7v6lw/1u5ubkMGDCAH3/8kU8//dS8XJIkvv76a9577z169uwJwC+//IKHhwcLFixg6NChZRXyE+Pnn3+2SCDq169PjRo12Lx5M1evXkWv1zNw4EDq169PQEBA2QUqCIIgPBGMRiOSJKFQKEhMTOTcubO0atUYKGDXrpXY2ipo3bouNjZ5BAfL0WiSATvCwz0JD/cETG1HgoL87vF4EutOFRJ3Q09qrpG0O5KEtDwj6XlGjNI/7z93Tz5da2v4qIsDrnZl0+I8KyuXtWt38dfRGxxTN+Z6oWkkoK61NYzv6kCjyNUknb2EavuvbD6+iZUn9aw+ruVqhoGrhOIzdBZ1/RSkOdqSrTXioLl9HpIk8cehAj5Zaap9UCnhzbb2PN/k8ah9KCrSoVJZYTAYWLNmN7VqhRMQUJ28PCVXr6ai09XAysqKmBgvNBoNIEcuhypVqpR16A+kwiURw4cPp1OnTrRp08YiiYiPjyc5OZm2bdual6nVapo3b87u3btFEvGISZLE1KlTze/nzp3LwIEDAdDpdAwZMoRff/2VwsJCZsyYwaRJk8oqVEEQBOExlZaWRmFhId7e3uh0+cyd+xPNm0cSFOSJ0RhHYeFp9Ho7lEolrVpVRa1WAVqUSgUNGoQ91LEz8oyMWphpfrr+T2QycLaR4WqrwNVOjqudHDdbOVqd6QZ7xTEtO2ML+aiLA11rax5Zf4CCAi0nTsQSEOCNu7uLefnVpHSGTT+HQ1QvZIUK3OzkfNrdgfZhGsDUtyE5OY0mTeoQYJfHpF7ufNTFgQ2ntSw+VMDO2CIOJxg4nJDNRyuyaVdTw1P1rKnqruT9pdlsOVdoKsfPVPsQ5F7hbkUByM/XcvHiVapXr4xKpWbnzlPcuJFPjx49UShscXYuRKWqCngTEOBDQEBt875/nzCuoqpQ/3O///47hw4d4uDBg8XWJScnA+DhYVmt6OHhweXLl/+xzMLCwpudo0yys03Diul0OnQ6XUmE/USIi4vj9OnTAERHR/P0009bfH6TJk3it99+w2g0smzZMj755JOyCrXE3Do/cZ0I90JcL8K9EtfKf7s1ek16ejpHjhyhadMGqFR6jhzZTGbmDbp1awToadDAHWfnAnS663h62uHp2QBJAp1OfzOBML1+WCcSdbz6ew6JmUbUSuhUS427vRwXWzmutjJTsmArx81OjpO1DKXi7olB30gV7yzN5VyKgZG/Z7HsSD7ju9jh5fjPk8np9XqLf+/FrFnLePXVLzAYDPzww3sMHtzFfB5j11jj2LCPacPL+1g9vQMutnLz5/Ttt2/h4GCLXG6qYdDp9Chl0LGmFR1rWpGcbWD50UKWHi3k4g0DK45pWXFMaz62SgkjW9nwXCNrlIqS+fwflaysXDIzc6hc2TT07urVe/D29iMiIoKcnHz27DmIm1s0bm7eVKnijpeXFp3O1D8hKsrUB7Q8/R6XdCwVJolISEhg5MiRbNiw4WYV0N39PWP/r6HIJk6ceNce7Vu2bHlsMsXSEBcXZ35tZ2fHmjVrim3j6OhIRkYGN27cuOv6imrjxo1lHYJQgYjrRbhX4loxKSgoID8//+ZcCxJ7927H29uZatW8KCjI5NSpMxgMh7C11WA06nFxkbNr11bz/mlpVx9ZbJIE2646Mv+0B3pJjrtNESPqJOLvcPPhpATkmn7SMP38l7dqw5p4V1bEurLlnI49san0rX6D5n6Z/FuLn3379lq8j41N5ODB85w6dZmxY/venLjOJD8/A4PB1El67dqtBFR1YXmsK2viXTFKMtRoaWZzlLY9ZZw5uvu+PhOAMAXUrAvx2Rp2JjqyL8mBPJ2CKo4FvFArCR95EX8Lt8xIkoReb8DKSkl+vpbDh+MIDa2GnZ0z588nERd3jZYtW2M0WnH5soy0tEySkk4gSRLu7pXZv/8ocNRc3smTJ8vqVP5Tfn5+iZYnk6S/DxZVPi1btowePXqgUNzOxg0GAzKZDLlczrlz5wgKCuLw4cNERESYt+nWrRtOTk788ssvdy33bjURfn5+JCUlmSeHEf5bSkoKfn6mNqNVqlTh9OnTFv9Xx48fJzLSNCFMZGQku3ff/5dSeaPT6di4cSMxMTFYWVmVdThCOSeuF+FePanXyq2HfgUFBRw8eJBatWrg5KTiyJEDnDhxjEGD2gOFnD0bj7OzfZmPeqTVSXy0Mpc/j5juIVqHqPi8px0O1iXTl+HCdT3vLsvlaILpSX2DACWfdbcnwNWyVkKv17Nhw1+0bdsapfL2s+GRI6cwffpiAFav/oaYmCj0eh1bt25lxYrV/P77Edzd7WjYsQtXfXoTm2q6HewUpuLDzna42JZcn4xCvcSFFAMhnop/rIUpLQUFWpKT06lSxRuQs3r1fmxsnGjZMga9XsWOHfupXbs2Li4u6HQ6ZDKZxedakaWlpeHl5UVWVlaJDJVcYT6V1q1bm4cMvWXIkCGEhIQwduxYAgMD8fT0ZOPGjeYkoqioiG3btjF58uR/LFetVqNWFx8JwcrK6on68n5Yvr6+tG3blg0bNhAfH8+IESP4/PPPcXFx4dSpUxazKA4aNOix+mzFtVKx6PV6Nm/eTFxcHDY2NrRs2dKcAJcGcb0I9+pxvlYKCgpISUm5OciGxIYNq1CpJFq0qAtkk5l5FINBh5WVG+HhDoSHN8XKSg8oqFUrqGyDBy6n6Xl5fhZnkvTIZfBWOzuGNrNFXoKdg0N9lCwZpuaX3fl8sT6X/Zf0dP5fBm+0tee5xjYoFTKGD5/M8uVbycjIJi2tjcXIUI0b1zYnEYcPn6FOnSqMHDmSuLh4AKpUVVIQ2IGtVj0gVcJBbWDSU650rPXPrT0elJUVRASUzbUsSRIHDpzCz88LLy9/EhJ0bN0aj79/SzQaJ+rX9775u+aOlRUWfWsft9+/kj6fCpNE2NvbExZm2enJ1tYWV1dX8/JRo0YxYcIEgoODCQ4OZsKECdjY2NC/f/+yCPmJ895777Fp0yaMRiM//fQTc+fOxcPDg6tXb1cl+/n58eyzz5ZhlMKTbN68ebz33nskJCSYl8nlcnr06MG0adOK9akSBKFkGI1GDh48iL+/L56e9iQlnWHTpk0MGtQRjcZIcLCEUqkAUrCygp49m5v31WjKz5CnAJtOa3l9URY5WglXWznf9XOkUdCjidFoMOCYspe2hiscVNYnUe/GhDU5rDpewORejty4kUFi4g0ATp+Ot5gFulWr+vz44/s0ahSOn18l+g15hSsZ1hh82mKw8UHnFonBrjIAquQd2F2eQ+iQaUDAIzmXR62wsAgrKyVyuZzjx2NJSsqmXbu2yGS2XLt2EUdHf7y8QvD31zNoUKS5abyPj08ZR15xVZgk4l6MGTOGgoICXnnlFfNkcxs2bBBzRJSSZs2aMWfOHJ577jn0ej06na5YArFu3boym21UeLJ98803jBo1qthyo9HIkiVLOHbsGLt376ZSpUqlH5wgPCb0ej1yuRy5XM7JkydJTr5MmzZRyOV5JCbuxcnJF0/Pyvj5SQwc2ByNxtQuv0qV8n8jZzBKTN2Yy7QteQDU9bfi+wFOeP5Lp+d7ZTQaiY1NQKWyIiDA27xcLpcxcOCHFBQUEljVl89/W8Anq3M4flVPl+/SqF2jM/aO+wmu6kFRkY4ivcTlNAMXb+iJS9UQ59iS1Vv1nE3MpCDoi2LHddRIVElbTMKJXygEZs+ew/jx4x76fEpDamomAG5uTqSna1m8eBvdunXFwyMABwdn9PpMwJQkde/e17yfUql8bJonlbUK0yeitGRnZ+Po6EhqaqroE/GALly4wPfff8/KlSvJzs7G19eXQYMGMWTIkDKbVfFR0Ol0rFmzho4dOz52VZ6Pm0uXLhEUFGTuSNi+fXt69OjBlStXmDlzJqmpqQA899xz/PTTT48kBnG9CPeqIl0rWVlZGI1GnJ2dyci4wZIlv9O1azPc3a2JiztPWlo69evXLOsw71lRURFr165l+fLlXLlyBZVKRWRkJO269mX6US92xpqGbx3cyIZ3O9qjUj5886W9e0/QseNIMjKyef31/kydOtpifcOGQ9i719ScOyNjC4VyGz5Yls2G06a+GIFucuxl2WQaHEjI+Pd5KOQF16lT1ZnwANPEbh1raVCTT+fOncnJyUWlsmLz5s1YW1v/cyFlJC0tkwsXEoiOjgBsWbVqNxqNI23adMJolHPx4kX8/Pz+dfCdJ11aWhpubm5PXp8IoeIIDg7mq6++4quvvirrUAQBgB9++MGcQIwcOZKvv/7avG7o0KHUrFmTnJwcFixYwJQpU3B2di6jSAWhdEmSRFpaGkajETc3N/Ownf8kNTWV2NhYoqPrAwVs374Ca2to06YOjo5aGjXyxM4uF9ATGOhFYKBXqZxHSUhLS+PVV1/l3LnzFsuX7YhlfrYRo6YIaysZk3o50K3O/d1kX7mSzMaNe9mz5wTDh/cmIuJ2s6PAQB8yMkzDyx8+fLbYvu+99xx6vYG6dUNwdLRDJpMxc6ATa08W8uHybOJSjYAdYATAViUjsJKCwEpKqlZSElhJwWdjh1KYehFfL1f+/GbF345gR1RUNJs2baKoSEdqamqp9hO7k8FgoKCgEDs7G4xGI6tX76JmzTACA0PIy7PiypVkIiJCUKvVtGx5a8I2BXK56d5DKF0iiRAE4bG3fft28+uxY8darPPz86Nfv3788MMPaLVaDh06RJs2bUo7ROExc+rUKbZs2UJhYSHBwcF06NChXNUqFBQUMG3aNKZPn24eotvb25sXX3yRl156CZVKhZubGwaDnsWLf6Nu3RoEB3uTnx9LQsIB6tYFlcqKZs380WhUQBFyuZzQ0MCyPbEHZDQaeeONNywSCLdKbqTYNSY7cDDIrZDnXeW1hml0q9PuH8sxJWVZuLo6Wgwvv3btLl5+eSIAoaFVLJIIFxcHatYMwNpaSXCwB6mpqbi5uZnXd+7ctNhxZDIZHWtpaBio4o+DeVy9fJGYqGpU8zLNT/H3oe2/M14n1VhIRkYGWq222NP6W3NtAXcdbOZRyc/XEhubQEhIACqVDbt2nePGjTx69XoKudwGF5ci1OoAwAd/f1/8/cPN+9ra2pZanMLdlc2c6oIgCKXozkmY7tak7s6ah/I0MZBQ8cTFxdG6dWvCwsJ49dVXefPNN+nWrRuVK1f+x6HGS1t2djYtWrTgrbfespjjJynpGlOmjKdt2wasXPkzcBaF4gRBQTIcHTOAJPz9benduwUqlSkhcnS0M0/aVpHt27ePEydOIiHH0S+cZ96fT5UBv5EZ9CLIrVCl7MJx3+usXvAdqakZnD9ffBLbceNm4uTUgkqV2nD5cpLFuoYNb9/87t17ex6BZcuW0aVLF9TqSxiNsRw+vJZOnTrxwQcfmCe//TfOtnKGNLKmlX8m0YEqPBwUd50bKzo6CoD8/ALmzJljsW779u3muQ2qVg18JP3Ciopuf69u23aYEycSABeKiipx8GA6WVmVgXBq1epA06bdAGdATePGjUXH53JM1EQIgvDYCw0NZd++fQDMnz+fl156ybyusLCQhQsXmt+HhIQU218Q7sWlS5do3LixxVPdW5KSkhg8eDBZWVm89tprpRLPrS6PMpmMa9eukZqaSnh4LV599SVOnNiPkxPY2UH9+uFkZOSRmXkRuRwMhkS2b1/AkCGtAahXr0apxFvajEaJuFQDJxJ1zFyZRVbkJPT2gaQrbfhmH0AhCjm808Gew79vYZ+hgE2bCqhUKQZPT1eSktZblGdlpSQ729Tpes+e4xYdpGvWDGTKlFFERYWZR1CaPXs2//vftGJx6fUG1qxZy/nzF5g168cSGRymb9++rFq1GoAff5zF/v37qV+/PhcuXGDbtu0W2/3bBL33Kjvb1L9Co1Fz6lQCBw7E8uyzzyKT2WJra0CtdgKq4OQEQ4YEm48pmpJWLCKJEAThsffCCy8we/ZswDQUdHZ2Nj169CAhIYGPP/6YS5cuAdCmTRuqVKlShpEKFdno0aPNCYS/vz+vvvoqnp6eLFq0iJUrVwLwxhtv0KtXr0fydDU2Nha1Wo2fny8ZGSksWfIHXbu2wt3dgdTUo8TFxVGpUgKnTy8iMBAcHGz58cfvqVnT1PH50qVLDBs2jOvXb3D8+DFOnTplXlfR3UoYTibqOJGo48RVHaeu6ckrutULuY7p4Tcg6bQUpsQR4i7j69cbU8dPxbxLUezbuxelEgoLITk5jYICLdbWt5sFBQf7U7WqLwEB3sVqZxQKBW+88Yz5fXx8PNOm3U4gmjRpQtOmTUhMTOTPP5eSm5tLbGwsP/zwA2+88cZDn39oaCgjRgw3Jy3Hjh3n2LHjFtu0adOG7t27P1D5WVm55Obm4+Pjjl5vxaJFe2nUqCmhoeH4+gah0dRCklyRyeRERjaw2LckkhahbIgkQhCEx17Dhg3p27cvCxcupKCggLfeeou33nrLYhuNRsOkSZPKKEKhoktMTGT58uUAuLu7c/jwYfMIf8888wwjRoxg2rRp6PV6Zs2axUcfffRAxzEajUiShEKh4MqVK5w8eYyOHZsDeZw9uwU3Nxv8/Gpgb6+jYUMP7OwyAS3h4d6Eh3uzcOFCjEYJtRqefba/RZIQEBDAiy++yGefTQBg8+YtFT6JOHCpiGlbcjkQr7sjYbhNJTdSy09NZtw+ks9sRZZxkVN7EkAyUr1ZXer4tQQgNvYiALa2EBJSjTp1alBQUGiRRPTpE0OfPjH3FNfixYu5NTbmkCGDGTFihHld9+7defrppykq0rFixUpeeWW4xXEe1JAhQ/D29mbWrFnmCecA3NzcePrpvgwaNAiF4t6Gq9VqCzl37jLVqweg0Thz6lQCCQkZ9O0bg1KppHNnd1xcXAArHB0dH6uRGYXbRBIhCMJjTyaT8csvv6BWq5k7d26x9R4eHvz+++/Uq1evDKITHgf79+/HaDSNjjN48OBiQ4SPHj3a/OR5z54991xuZmYmWq0WT09PdLoC5s79iebN6xIU5IFSeQkbm2vo9WdQKpV06hRx86muhFKppGbNqsXKu7Od/d2a7tWoUeOObbPuOc7y5n8L9jLvqIoU+e0mRdZWMkK9lVjlJLJq3nyKki/yyVvdGTtsICtW6Bm/eTMAHu62NGhQl6ZNIwA4fPgw69atAyAkxJZ163566CFQDx8+DJjmgfj7BKyVK1emVatWrFu33lwjUatW2N2KuW/t2rWjbdu2nD9/ntTUVOzs7AgNrWkx0/WdDAaDObE4ePA0Go0NYWHh6PUyDh06irt7M7y8fKhbN4AGDZTcuq309PQskXiF8k0kEYIgPBHUajW//PILb7/9NnPmzOHixYtYW1vTtm1bevfuLcYWFx7KnZ33bWxsiq2/cySZO7f9u6ysLA4fPoxerwWyOXZsG2lpyfTs2RQrqyIaN/bC3V0HZOLt7YS3d6R533tpFmJ6Omxy+PARmjdvbrH+0KFD5tflfa6k3Nx8jh+/QHZ2Hu3bNwLgXLKOqRtzWX8qAOQgGfR0qgGvdvAg2F2JUiHjyJEbLBy7mSpVfFCrTDfIbdu2Zdq070lNTcXHJ4/s7CNkZFgzdOhQDh68/Zn07NmzROZQuDWAg0KhuGt5d/aD0OtLdrAHmUxG9erVqV69usVyo9HItWs3cHS0w97elgsXktm+/ThDhgxCLrfDYChAr7cDgrGzg8GDA81DAovvzyeTSCIEQXii1KhRg8mTJ5d1GMJjJjz89ug7v/76K++88w4q1e128bf65IDpGrxx44Z5FJwVK5bg6+tG3brBGI1JpKQcwM6uCAigQQMPrKx8ANMkZyEhAQ8VZ8uWLfniiy/Q6fQsWrSQOnXq0KJFc2QyGYcOHbKYbLFdu38eyrS06XR6i6flRqMRL6/25ObmExTkx8Y9f/DVplxWHNMiSSBDIufEZrJ2LaDVrNep4eVr3rdWrSByc3dga3v75l2j0TBlyhRGjBhBbm4uOTm5rF+/wSKG6Ogohg0bViLnExgYSHz8JXQ6PZs3b6Zt27bmdQUFWrZs2QKYair8/f1L5Jh3c/78ZXJyCqhXry4ymYYNG3ZRv35DatWqg4dHHk2aBGE0eiCXK4mKamKx73/NKSI8/sQVIAiCIAgPqXr16jRtahrP/8KFC8TExLBu3TqOHTvGmDFjeP/99wGwtobWreuxevU84BxwlMBAPe7ueUASzs7Qq1dz7Oysb26vQaksued9Li4u9OzZEzANu/nmm2/SuXMXunfvzksvDSU7OweAli1blPkgA7GxCcTEvIKHR1vGjPnGYp1cLqdmzUAU9pVID+pO6y9TWX7UlEB0rKVm1lMGFoysSuL5eTz1lOW8L0ql0iKBuKVWrTDmzZtLly6dLTpG+/h4M2rUKL7++muLxPBh9OjRw/z6s88+Y9GiRSQlJXPgwEFGjBhBamoaAM2aNX/oGiGj0UhhoSkJTU3N5Ndf/yI7Ww1UpqDAm9xcH6AGMlkV+vZ9kbCwBoACBwcHqlevXqLXn/B4EVeGIAiCIJSAzz77jLZt26LVatm+fTv792/H3t6UOLi7g4sLDBrUh7Ztg9Hp9EAuAGFhQaUa56hRo0hKSmL79h0AxYakrV07nHHjxv1rGYmJiZw9a5pdOSQk5IFHmzpzJp5Vq3Zw/PgFRozoS1TU7bb/jo52bNq0H4Bjxy5Y7Hc9x0CldsPwa+6LJFNgkKBViJrRMXaE+VhhGmrJl/vl7+/PuHHjGDNmDCkpKahUKry8vEr8qXt0dDRNmjRm585d5ObmMXny50ye/LnFNjY21gwb9vJ9l63VFpKamomvrwegYOnSPXh4+NKkSSvs7ZUEBdkhlwcAdtSu7Waxr5jATbgfIokQBEEQhAeQkJCAvb09Tk6OXLp0ljNn9rN27Q+MH/8mKSnXAVMCAaBQyOnXrz+vvfbqPY+A86ioVCq+/PJLNm7cyJIlSzh58iRGo5Fq1arRo0dPOnfu9I+za8fFxTF16lT27Nlrsbxhw2hGjx5NYODdZ6xOTc3k4MHTtGvX0KLvxp49xxkz5lsAIiKqWyQRlSo54+npisFgxM3NCYCMPCMztufxy+48tLrKIIOGgSrebGdHvcolN+mdjY3NI62JkclkTJo0iQ8//JDNm7cUW1+pkhuTJ08mKOi/E0yj0Uh8fBI1amTh4eHDpUuZ7NhxjsGDm2Bl5UBUlNvNfjoOqNUQFRX1CM5IeBKJJEIQBKGcSk9PJzk5GScnJ7y9vf97B+GRunLlCikpKdSvXwvIY/v2pVSv7k1kZFU8PQto27Yavr7ubNiwnC1btnDw4EEKC4vw9/ejc+fOeHh4lPUpmMnlctq1a3df/R7Onz/Piy++RG5ubrF1e/bsZciQ55g5c0axUZ+GDBnPnDmmeTLi4pZTpcrtWovw8GDz6+PHY4uVe+bMYhwd7cjWSny1MYefd+aTU2gaGzXC34q32trRKEh9z+dQnlhbW/PFF19w9uxZVq1aRVJSMjY21jRs2JA2bdoUazql1+tRKEwzUp86dZGMjHyaNGmCTKbk1Kl8IiPd8fCoSWBgMH5+0VhZmWoVfH3vv0ZGEO6FSCIEQRDKmV27djFhwgTWrl1rnnU4MjKSN954o8RmlBXuLicnB4PBgJOTEzk52axatZRWraLw8LAnN/ckN25c5FZ3wp49690cv9+IRqO2mKG4bdu2Fp1lKzpJkvjggw/MCYSnpwedOnVCJpOxatVqzpxJJiEhl/btXyY+fovFNVq58u3hPvftO2mRRISFVeWXX8YRHh5MjRrFn/zL1LZ8vSmXn3flk6M1/S6Eeil5s50dLaurH4vfhZCQkLsOt5ucnIpSqcTNzYnr13NYtmwXTz3VAxcXHxQKFUplHhCETKajSZO2hISY5vRQqVQl1ndDEP6NSCIEQRDKkXnz5jF48GDznAO3HDx4kH79+nHgwAGmTJnyWNw8lQepqalcuHCBhg0bAPls27YcjUZGmzZ1sbHJo0oVCbU6GcgjNNSD0NDbtQklMQFYRXHo0CHOX7hIgdwT58AoGg4cwZ7rErYqGS99PIBnYzqTlZEP5LJjx26aNWts3rdJkzo0ahROVFQY1apVtihXo1EzaFDnYsfLyjfy0848Zu+6XfNQzUPJyNZ2dAhTI5c/ftd/YuJ14uISadq0IWDDnj3HcXX1olmz2jg7SzRv7oWNTWVAQ0hILYt9xfeBUBZEEiEIglBOnDt3jueee86cQPj7+9O8eXOOHz/OsWPHAJg6dSpRUVH06dOnLEOtUHQ6Hfn5+Tg6OmI0GvnjjwXUrRtCcLA3+fmxXL16gKIiGSqVFU2a+KJSWQH5KBQyoqNr/Wf5d6M3SOyNKyK3UKJViBqVsmLd5On1Bq5kSJy8puNkoo7Ve6xIa/Y7co0dScCsXYXmbdedApfn5qA4vpnck5tZueoviySiTZso2rS5t3b4mTeThzl3JA/VPZSMbGNH+5qPR/JQWFiEWq2iqEjHypW7iYyMpHLlauh0arKyijAaayCXy2nf3vPm/AsyrKwoNq+DIJQ1kUQIgiCUE9999515IrLnn3+eGTNmoFQqkSSJ77//nhEjRgDw1VdfiSTiX2i1WuLj46latSoqFezZs5EbNxLp1as5cnk+QUHg6JgByPD3t8Xfv4V5Xycn+38s979IksSRBB0rjmpZdVxLaq4pGQxwVfBOR3vahpbP5jcGo0R8qoEVO+KZv+Y0qUZHNJ5BFEl33iJ4INeApNdhSL/CoM5h1PSxIiHdwNIjBaRk22BftzP2dTvzlzKL77fm0jPCGk/He+tEnpF3M3nYnU/uzeQhxNNU89CuAicPer2e5OQ0vL0rIZcr2Lr1JNnZOrp27YlKZYuXlxFr6yDAnYAATwICbncsL4lJ7QThURJJhCAIQjmxYsUKwDS79pQpU8zjs8tkMl555RWmT5/OqVOn2Lt3L9evX8fd3b0swy1Xjhw5gq2thmrVfNFqr7Fz55+4uDTCw8OB8HBbJCmYW0Oq1qtXo0SPfSFFz/KjBaw4puVKusG83MlGhlIu41KagaHzMmlQxYoPOjlQy/fuIx+VhtWrd/Lnn5u5cDGJF95/h1OZjmw6U0hanhGwh0pRyIEiCdRKqOFlRS0fK3TXT/DzlK/RpSVQLyKYj7vONl+fb7Wz45Xxc9hyyZoi94ak48jn63L5Yn0uTYJU9KprTbuaGqxVxROB9Dwjs3bk8cvufPKKbicPo9rY0Ta04iQPRqPRPAzshQtXsLZW4+vrR3q6gTVrTtO9ey/c3SsTGup780GBMwCNGjUqw6gF4eGIJEIQBKGcyMrKAsDPzw8nJyeLdTKZjFq1anHq1Cnztk9aEpGXl4dSqUStVhMXd5GDB3fTu3c7ZLJ8cnKOI5OZmiE5OkoMGdLGfJP7MLUL/+RqhoGVx0yJw5kkvXm5jUpG21A1XetoaBKkpsggMXNbHj9sz2N/vI4u/0ujZ4SGt9rb43WPT+nv1//+t5AjR86RlZXL4sW35x7IKzSyZH8WK29UwzriGT7cpAIKALC2klHdQ86O5ctQ5iTSpq4Hv3z3MkqF6SY+N7c2O+cmUWCvJyPjDDNmzKB3794ALF68mIOrZmMPqO2cGfrpIlafMrL/ko4dF4rYcaEIO3U2HWtp6FXXmgZVrMjIl/hxRx5z70geQr2UvNa6fCYPer0eg8GIWq2isLCIY8fOU716AI6OThw/Hs/Ro7EMGvQ0oOLs2QtUqlQJX99auLkZ6dOnGo6OjoDsifudFR5vIokQBEEoJ3x8fMjOzubixYvExcVZjLlfVFTEtm3bAFAoFOVquNBH5dq1a+Tn5xMUFIjBkMuCBT/RpEk4NWr44OBwjYAAIwZDPEqlkmbNbjcDkclkj2SW3fQ8I6tPaFlxtIADl3Tm5Uo5tKhuShza1FBjo7o9MZlKKeONtvb0a2DDlPU5/HlEy59HtKw5qeWlprYMbW6Lrfr+JjIzGAycO3eZgwdP4+rqRKdOTSzWz5u3hv37TclmUno+u+JlrDupZfuFQor09bANNW1nKy+kZwNn2oepaVBFhZVCRlKvHnh6uhZrdmVnZ8dLL73EN9+Y5nSYPXsOs2fPKRbbS0MG8GxTZ55tCpfT9Px5uIAlh7VczTCw6GABiw4W4OusID3PSP4dycOoNnbElHFzL0mSkCQJuVxOUlIqFy5coVmzBoCK1au34+joQosWLZDJ4OLF8/j6VsXR0RdfXz80mlBuTW7XpcvT5jLlcnmxBwKC8LgQSYQgCEI58cwzz/Dee+8hSRIDBgxg3rx5BAUFkZqayuuvv05SUhIAXbt2xcHBoYyjLRkGgwGDwYBKpSItLY2dO7cTE9MIGxuIj99FRsYNgoKiUSgkOnSojqurBsjDzc0RNzfHUolxd2whP+7IZ8eFQvQ3B82SyaBBgBXd6ljTIUyDs+2/JwLeTgqm9nVicGMdn67KZv8lHd9uzuO3AwW82daOp+pZo7jL03eDwYBOp0ejuT0XQmLiDWrWNPWJadeuYbEkwr96CKd1lbGp1ojGX2RhlG6X6+skI9KjgF5RzjQO8Sj2xN/Ly3IG4zsNHDiQ/Px8Zs2axc2Rh81kMnjhhRd49tlnzcsquyp5Pcaeka3t2H9Jx5JDBaw5YUooAGp6m5KHNjXKJnlITk5Frzfg6+tBURHMn7+BFi2aERgYQmGhhszMAozGWsjlcho0cLo5bKorKhX063f7PF1cXHBxcSn1+AWhrMkk6e9fBU+27OxsHB0dSU1NxdXVtazDEcoxnU7HmjVr6Nix4z/O7ioIt9zL9ZKamkrNmjW5fv26eVnlypVJTEw0d7hWKpXs2rWLBg0alErcJU2r1ZKenn5z8jw9v/8+lypVPIiKCiE3N5X9+49Qv34o9va2Fu3My0JeoZGJa3OYv7fAvCzMR0m32tZ0rq154OZIkiSx/lQhE9fmcDnNdEMd4qnk/U72NAlWo9PpmT59Lr//voNjxy7wxRcjeeWV3hb7u7vHkJqaSSW/AFZu/ZXL6QYupRrYG1fE4Ss6i+OFeCppH6ahfZia6h7Kh75hv3r1KkuXLuPs2TOm8kNq0KNH93ua1Cy/yMi2c0XYa2Q0DlI98uRBqzWNIqXRqElOTmXv3tN06tQWKyt7Nm8+SEGBkU6dugNKTp8+ja+vb4VL0MXfIuFepaWl4ebmRlZWVolc56ImQhAEoZxwc3Nj3bp1dOjQgZSUFAAuX75sXq9SqZg/f36FSiD0ej0XLlzA29sbR0cNsbEH2bdvN0OGdEAuL6JxYw/s7GyATOzslLRqVd+8b1kmEPvji3jzjyxzR+n+UdY819iWIPeH/7Mpk8loH6bBw3CVb9YkszPDj7PJ8MxPGbQKUfNWjDUKhZw9e04AMnYduUzExUIupxm4lGbgcpoevxen4Wi0RY+Svj9kFDtGXX8r2odpaFdTTWXXkv1T7+vry6uvjnigfW1UcjrUenTza6SkpJGZmUP16lUADb//voU6depSp04t1Gp/nJzU6PWBWFlZ06yZt0Wzt9DQ0EcWlyA8jkQSIQiCUI5ERERw6tQpZs2axfz580lKSsLR0ZHu3bszfPhwi34S5VVsbCy5uTnUqVMNuTybvXtX0LhxDRwdfQgKklOlSiPk8iIA/Pw8/6O00qXVSXy5IYdZO/ORJPB2lPNFb0caB6n/e+e7kCSJa9duEBubQPPm9SzWLV60nl8mzEauseeZidPYdd2FzWcL2Xa+kGqOjfF+LgQrZ292KVXs+vHviYKpKZdcBk4qLYbMy2hTY1HmXsKHODpUbcnTEU9jb//4/Zk3Go0UFenQaNRkZ+eydesRmjVrjJOTJ1evZhIfr6V69QhARtu2Tjc7Ndvi7GxPixYtzOU8in4zgvAkEb9BgiAI5Yyrqytjx45l7NixZR3KPyoqKsJgMGBtbU1mZiZbt/5F69ZR2NvLyMk5QWbmdcCIXA6DBrVEoTA1/bmzbX95cyxBx+hFmVy8Yap96BNpzfud7XHQPHiNSIsWQ9m+/TBKpYLc3B2o1Srzujp1TJOHGbU5BGbt5KPXn2PS2hw2nC7kTIY9VpVMo0op5ODnrKCyq4IqbkoquyoIcFXiZW/g24lvs2/PbpSA3c1y04AZM86xdu0aZsyYUeFHBMrKyuXatRvUqFEFsGLFil04O1eiefPWaDRKbG31SFIQ4ExEhA/16t3+/zI1mxME4VEQSYQgCMIjkpeXx7x585g3bx5Xr14FYOfOnQwfPpyAgICyDe4+paamcu3aNcLDawFali//HW9vZxo3DkOtzsDRMRWj8SJgR0SEP+Bv3vdWAlFeFeklvtucy/db8zAYoZK9nMm9HGgV8t/NbrTaQr78cj4HDpzGw8OFmTPfs1jv728aRUuvN3DqVBx164aY1zVpUocZM96hTp3q1KoVhI2Nkh8GObPvYgGrd52jRWQ1qnqo8HZSYKUo3nfg888/Z9+e3eb3wcFB2Nracvz4cYxGicuXrzBmzBhmz55dLie5u5PRaKSwsAhraw16vZ6NG/dTq1ZNfH0DuXFDx549KQQHd0ap1NCggRtqtRpwRqWC1q1bm8spyyZwgvCkEUlEGTEajRw8eJDk5GRcXV1p0KCB6BAlCI+R2NhY2rVrR1xcnMXyKVOm8O233zJ37lz69u1bRtHdXVFREVqtFgcHB7RaLWvWrCAqKhwfH2dSU09y8uQhwsKKkMtlNG3qjbW1BsjC2lpOy5aRZR3+AzmTpGP0oizzXA9da2sY39Wh2GhLeXkFHD58Fmdne8LCgszLVSorPv98LtnZeXh7VypWfvPm9bh+PYOIiOo4OdlZrPPycmPo0F7F9qnrb0VBQiaNg1VYWd39z3RmZibLli0DQK1WMXXqVKKjowG4dOkSI0aMICkpmRMnTnL06FEiIiLu/UMpBXl5BcTFJRIaWgWFQsPWrUfJyzPQpUs3lEprVKocZLLqgA+Bgf5UrRplToRE7YIglA8iZS9lkiQxa9YsqlWrRlRUFN26daNJkyYEBAQwZcoUjEZjWYf4xDh9+jQjRowgNDSUqlWr0r59exYtWmQeBUcQHlRubm6xBMLNzc38lLSoqIgBAwawa9eusgoRgIKCAs6dO4dpkL4iNm9ezs6dy4DzqNVnqVQpG5XqKnCV6tUd6d+/tXlIUE9PNxwd7f6l9PJNb5CYtiWXrv9L40ySHhdbGd8PcOKbpx1xtLbc9tChMzg4NKdZsxf5/vvFFuvkcjmRkaYOubm5+aSnZ1msf+GF7qxf/z8mTXqVwMD/Hr3oXu3atYvCQlO/kp49e5oTCICAgACGDRtmfr9p06YSO+79unMAyB07jnD+fBLgQl6eE/v33yAnJxAIp1atDjRo0BFwAaxp3boNPj4+gOkzLu81KYLwJBJJRCl75513ePHFF7l48aLF8mvXrvHWW28xePBgkUiUgi+//JKwsDCmTZvGmTNniIuLY/369fTt25dmzZqRlpZW1iEKFdi8efPMCURoaCgHDx7k2rVr/Pzzz/Tv3x8wjf//2WeflXpsR44c4cqVS0AuGRnn2bZtMdnZu4ETNGjgSuPGlYEcZDIDTZtGUKmSM8BjdRMXe11PrxnpfLE+F50B2oaqebPmRaaMHEWlSm1Ys8YyuQsO9jN/Lx84cLpYeVOmjOTs2cVkZGzBxaV05q7IzMw0v65ZM6zY+rCwsDu2zSq2/lHJycmjqMg0xOzp05dYuHAH4AUE3fypBlShUqWaPPfccJycTPNSVKpU6YmYQFEQHiciiShFW7ZsYfLkyeb3rVu3Zty4cXTt2tW8bN68eSxYsKAswntiLFiwgDfffNP8hEypVFqMl7xnzx569eqFmEJFeFBz5841v54/fz716plG5XFycmLWrFlUrlwZgHXr1lnMCVFSJEky3/TGxsaydu0KIB1IIClpP5mZ+4BzeHoWMXhwaxwdTW3/XVwcK3Ttwn/ZuesYAz7eStsvkzmWoMNeI2NqH0dmDnQCbTZbthwkLS2L48cvWOzn4GBHly5NefHFHgwf3rtYuRERIVSvHlCq7fHvnNzs2LGjxdYfPXp7mbOz0yOLIyUljYSEZECGVqvgt992k5CgBGpSqVIzwsJikCQvwJGmTVtQrVo1wJSUPk6JqSA8iUSfiFL07bffml9/+eWXjB492vz+999/p1+/fubtnnnmmVKP70lgNBoZN26c+f2YMWN49913cXBwYP369QwePJiUlBS2bdvGli1baNWqVdkFK1RYtzpRu7u7F2uLrlQqiYmJuTnrr8TVq1cfevQcSZLQarVYW1uj1RawaNF8mjWrQ0CACxpNPPb2N5CkOGQyGR073u67IJfLUanK5llSRkYme/fuITs7m0qVKtGoUSM0mpKZPyBfq+PA2VQKlM5cSNETe0PPhRQ9ZxJdkeQeIIO6XnqmDfYyTxhXu3YwAJ6ed59kdMWKr0oktpLSpEkTNBoNWq2WpUuXERUVTYsWzZHJZJw7d47p06ebt23Xrt1DHctoNGI0GlEqlaSmZnLw4BlatWqCSuXImTOXycnR4+dXB41GTseOblSqVAlQU6mS5uZrQRAeRyKJKEW32qVWqlSJV1991WJd3759+fTTTzl16hQHDhwgOzu7ws2aWRHs27ePCxdMTxmbN29uUTPUvn17vvrqK3Nzk19++UUkEcIDsbc3Dc2ZlpZGamoqbm5uFuvPnj1rfv0gv+eSJJGWloaLiwtyuYytW9eSk3ODrl0bodHkUru2HU5OeYAcX18XfH1d/rPM0lJQUMDUqVNZtWqVudkLgIODPQMHDmTw4MH3/ERfq5OIu2FKEmJT9Jy/rmfzgQQKVS7IFEog03IHuRKDNpfMrbPp/FoDvBy7mVeFhASQkrIBd/fy81n9G3t7e5566inmz5+PXq/nzTffxNfXFxsba86fv12TUrduhEXTpnuRnp5FZmbOzT4cSn77bRM1aoRSt24DFAotklRIUVEQKpUdjRr53BwUxFSrcC+zVguC8HgQSUQpys/PB8DT07PYSEwymQw/Pz9OnToFmP7QiiSi5F25csX8umPHjsXW37ksISGhVGISHj+dOnXizJkzGAwG3nrrLX788UfzusWLF7Nz504AqlevTtWqVe+pzBs3biCTyXBzc+XGjUssW7aY7t2b4O6uoWZNK4xGTyAbgNq1q5X4OZWEwsJCRox41dzUxqhywmDrj6TUcEOh4culF9h4eTnNWsZQoJMoKJLM/2p1kF8kkVdoICU1l/Q8A7mSDRJ/axJj7Y4MMBYVUMvfhgBXuHx8K5dPbEOflkBBagq+GiNz5+5GpcphwIAByGQyFApFhUkgbhkxYjhXr15l69atwO0asFuCgoKYNGnSXZsN5eUVIEkSdnY25OUVsH37EaKjI3F29uTSpXROn75OYGBHwIqGDe1xcnICXHB2hg4dfMzlqFSqYmULgvBkEElEKapatSoXLlzg5MmTnD9/3tw2FEw3CNu2bQNMTyZdXe9epS48nFtPiAHOnz9fbP2dy+7cVhDux7Bhw/jmm2/Q6XTMmTOHbdu20bp1a3bv3s3p07c75o4cObLYDZ7RaEQul5OamkpsbCzR0Q2APPbsWY2trYzWrcNxc9PTtWs4bm5KwFghbn61Ookvfl7LnnR/9LXaYnCqjkFTvCPtnkLYsy73P0q73ezJQSOjmoeSIHfTz5ZlK9i7YQONwn14e/BAxo17h6TLV1ABKsDm5keVk5PDV199TUZGJq++OqLEzrM0WVlZ8cUXn7N+/QYWL/7DPD9EQEAAPXp0p127Djg4mDp6X72awoULCbRs2QjQsHHjYZycXGnRojVWVjJkshwMhmDAjfBwP+rUkXOr22RFmCVdEITSJ5KIUjRkyBDeffddJEmiR48e/O9//6N58+YcPHiQkSNHUlBQAMCgQYNQKsV/zaPQtGlT7OzsyM3NZf78+QwdOpT69esDptqfd955x7zt3WoqBOFeBAYGMmfOHAYNGoTBYCA+Pp5Zs2ZZbDNw4EC6dOlCfHw8VapUwWDQMnfubBo3jqBaNV/y8i5y5coB6tY1zUXQunUQ1tZqTLNAy/H0dLv7wUuZwWDg7NmzZGVl4erqan44ciXdwNEEHUeumH5OJ+nQGaKh+u2hSGUyqOKqwMFaTm7mDS7HnUdm0GJnbUPi5VSKCvJo3bw2bVrWwdpKhrVKhrWVjFeHfUry1USUBalcuLbUomZ3SKM+KL409S+bPHkyly+bah9dXJzp06cvfn6+7Nixk3Xr1gEwZ84c2rVra/FQpyKRy+V06NCeDh3ac+LEBYxGidq1w9BqZcydu4o2bVoRGBiE0WiPVgtGY03kcjlNm7rcnLDNDpUK2rfvYC5T/P0RBOFeiG+KUjRs2DBmzpzJ5cuXOX369F3b27u6uvLWW2+VQXRPBnt7e55//nm++eYbCgsLiY6OpmPHjnh5ebFy5UqSk5MB0//DgAEDyjhaoSLr378/vr6+jBs3ji1btpiX+/q68957r/PSSwPZuXMnOTkZVKkSjUJhoEEDVypVKgBSqFzZjsqVW5r3s7W1vstRyo7RaGThwkX8+ut8Em/koHcIRu9YHZVXBAbH6uTqi0+eKSvKRJl1jgC7HDo3DOPIX+s4tOoI3/8xmapVg2jbdhjZ2TkolfZc358DgJVnW14e18SinPShDVGplDRoEFbshvfW7Nj5+fmsWrUKAI1GzS+//GKepKx9+/ZUrRrItGnfA6YmZu+++27JfkCPSE5OHgqFAhsbDQkJKWzdeoKnn34KKytH8vJyADVQC40GOnRwvNmxWYO/vyP+/rcTJVHbLQjCwxJJRClycnJi06ZNdOzY0dy59063bmT9/f3LILonx4QJEzh06BA7d+7EaDSabzRusbGxYfHixdjZPb5DXQqPTlJSEqmpqdSqVYNmzeowZEgP3nlnEO7uVhw7dpCqVcOoV68GcnkyTZoE3uxEbACgZs176x9RlrQ6iVOJRXzx82oOX5bQVxmHMex2Z9oCAD0oMFDLT0O4txw3WToNq2kYOvAZZEB4i+ZknM3jl1mmiduOHDlL9eqVsbGxITs7B5XKSPXqlQkNDaRFi3rFYnj22c7/GefFi3Hk55tqd1u1alVsluO+ffsyY8YMDAYjx44df+DP41FLSUkjIyOHkJAqgA1Llmyldu0IIiIicHQMIjTUA6PRF1ATHd3CYl8/P7+yCFkQhCeESCJKWVBQECdOnODPP//kt99+4/r16zg7O9OrVy/69euHra1tWYf42LOxsWHDhg18/vnnTJ8+nZSUFMD0BLNbt2589NFHhIeHl3GUQnlmNBopKipCo9GQm5vLpk3radKkLm5u1ty4cYSLF89Tq5ZpNuFOnWpiZ2eDTCYjIyOZBg3CsLIyffWW5rwCD0JvkLhwXc/xqzqOJug4flXHuWQ9eiNAI9McYjc5KvKwzr9IdvxelFlnUebEofeMZNKGgxiNEjdubMDezpbc3Dz27t3L66+bhh1VKhVcu5bKoUOHSE42/S4GB1dlx46fHyp2g+H2zPPW1sVrcVQqFXK5HIPBaLFtWTAajeh0etRqFTk5efz110FkMiPgRmJiLnFxhYSERAAyOnZ0uTnohgYHB8xzkAiCIJQ2kUSUAbVaTb9+/czzQgilz9ramo8++oh3332XM2fOoNVqqVKlihjTXLir/Px8kpKSbo6kpGfNmj+xtpbRunVdNJpsHB1TkcvjAUfCwz0ID7/dYfjWDMY6XdneqP6dJEkU6iFbayRHK5GrlcjRGknLM3Liqo5jV3WcTNRToCs+6aKVIQfSz6DMPk+LWv7428lQSYW88dkz/PJLEt9+uwKAhITL5vM+cuQ8nTt35vffF6LVFrJgwQ989dUwOnduyYkTx3n77bfN5ffo0eOhz69y5QCUSgV6vYG//trMa6+9ZlG7uG7denNsQUFBD328+5GTk8e1azeoXj0AULJy5W4cHd1o0aI1arUSlSqHtLR0wJ+IiEDq1r3d+f5h5xQRBEEoKSKJEJ5oVlZWotZBKEaSJA4cOICfnw9eXo6kpJzmr7824e3dFmtrGfXqOd6sTchEqYSWLSP/s8zSlJ5n5Lf9+VzPNpKjNZJTKJFzM0nI0UrkFpr+1Rn+uyw7tYyaXgq81LmEuEu0jnCjb5fOyICAgADW/LSVK1eScXZ24PXX+9O//wDmzp1HZmYmWm0q1ar507hxbZyd7Rk8eDCbNv1Famoqly9fYt686cybN93ieGFhYbRv3/6hPwNnZydatWrFhg0byczMZOjQobzwwovmjtV3dnTv2bPnQx/vbgwGAwqFAoPBwJYtB6lRozo+PlVISSlkx45rBAZ2wMrKhshIt5tDpbqgUkFMTFvWrFkDIGZ1FgSh3BJJhCAIT6yioiKUSiVyuZyTJ0+QmBhPu3aNkMnyuHZtH46OPnh5VcbPT2Lw4FaoVKYbOi+v8jEy0t1cvKFnyOwMrqTfQ4aAaYQkO7UMB40MO7UcB2sZNbysqO1rRW0/K3TpVwmr2Qej0Uj//u3pHf26eWYGLy9PwsOtuHIlmYyMbM6evURoaCDu7pXIzMzE3l7HgQNLLG6EZ86cwZtvvkl8/KVisURHRzFhwoRi8+g8qFdeeYW9e/eSnZ3D2bPnePPNN4tt07p1K/MIbQ9Dr9eTkpKOp6crCoWCnTtPk56upWvXbigUNhgMqTeHUPWnSpXKBAZGm5uz+fj4/HvhgiAI5ZBIIgRBeGJkZmZiNBpxcXEhMzOFRYsW0LVrczw9bbGzu4KraxZwGYDu3RuZ96soQ17ujSti6LwMsgok/FwUdKutwV4jx14jw04jw14jx0Ejw/7mazu1DFuVjK1bD/Lll/PZt+8kP/74Pj263R4VqsjJB7lchtEIx49fwNHREbubfRuOHDnKa6+9T/fuzQkPDyYoyI+EhKvmgSN8fHyLPUkPCAhg4cKF7N69h23btpKTk4ubmxsdOrSnZs2aJfrk3c/PjxkzZjB27FgSEq4WW9+5c2feffedBz7mmTPx2NlZ4+dXmfR0A6tXn6J79164u/tTtao3vr6FgKn5Ubt2t4eMvjWClCAIQkVWMf4yCoIgPIDs7Gzi4+OpXTscyGfXrlUolTratauHg0MhLVpUxslJC0gEBHgSEOBZ1iE/sD8PFzB2SRY6A9T1t+LHQc642t3uuG0wGDh1Ko69204waFAnNJrbT/uzs/NYs2YXAHv3nqBHj9tJhEplRc+erdBoVNStG4JSqaRjx44sWvQHWq2WDRsWM3bsGIKDgzl+/DgTJ05EutmNomvXLneNVaFQ0LRpE5o2bXLX9SWpevXqLFmyhF27drF7924KCgrw9PSiU6eO9zQSnl5v6jehVCqJj0/k9OkrdOrUAbAhLi4Od3cX/PzCcHMz0qdPNRwdHQEZXl5e/1quIAhCRSeSCEEQHiu7d+/G19cDf39XsrLOc+TIXwQH52Jjo6FpUz80GjWgQy6XU61a5bIO96FJksTXm3L55q88ADrV0vBlH0c0VpZP14cOncBPPy0HIDw8mOjoWuZ10dFhALi5Od11xKiFCydavB84cCDr1q0jOzuHo0eP0q9f/5u1Fbc7YXt4uNOrV6+SOcmHpFAoaNasGc2aNfvPbZOTUykq0uPv70lRkZxfftlEy5YtCQqqjlrthr29EwZDAAqFgk6depv3k8vlODk5PcKzEARBKF/K9/iCgiAId2E0GjEajQCcOXOaNWuWAjeAS2RnH0erPQZcxMdHxrPPxmBjowHAwcEOlapk2tuXB4V6idGLsswJRAv3FAo2f0uHti8X2zYysob59b59Jy3WeXq6ERe3nOvXNzJx4oj/PK63tzffffcdLi7O5mV3JhA+Pt5Mm/Z9ub2p1uv1FBXpALhxI4OVK3dQVGQFVOLs2QKOH88H6qBSRdCyZV88PcMBJ7y9K9OsWTPRHEkQ7pEkSWzfvp0RI0bQt29fRowYwfbt25Gk4qO+CRVPhamJmDhxIn/++Sdnz57F2tqaRo0aMXnyZKpXr27eRpIkxo8fzw8//EBGRgZRUVFMmzaNmjVrlmHkgiA8LK1Wi1arxcnJidzcLBYunEe7dg3x9XXAzu4Kbm7ZwBUA2re/3Um2vM/D8KAkSSI+MZO3VxvZH69DIYfPujvw4zvj2bz5AACXLydRufLtJjVNm0bQu3cboqPDaNeuYbEyq1S5v869YWFhLFu2jDVr1rJ5819kZ2fj7OxMu3btiYlpg0ajebiTLEGZmTlkZGTfPEc1v/22hZo1a1G3bhRWVoVYW4NOVxWVypYmTbwt+sCU9vCvgvC4uHbtGr169WLv3r0Wy6dNm0Z0dDSLFy8WgwpUcBUmidi2bRvDhw+nfv366PV63nvvPdq2bcvp06fNE7R9/vnnTJ06lTlz5lCtWjU+/fRTYmJiOHfuHPb29mV8BoIg3Kv8/HwuX75MSEgIMlkRW7euwGDIo1OnKOzsCoiKqoSTUz4Afn6V8PN7Mub30Ov19Ov3HtsPX8Wu49sYbCthr5bx/TNONA1Wc65ZBJs3H0ClsuLUqYsWSUTNmlVZtGhSicZja2tL795P0bv3UyVa7sMqKNBy+PBZwsKq4+joSXx8GidPJlGlSkdASfPmDjf7Ljji5ARt2tye16OidKIXhPIsOzub1q1bc/bs2buu37t3L61bt2b//v03J08UKqIK8225bt06i/ezZ8/G3d2dQ4cO0axZM1O74K+/5r333jOP+f3LL7/g4eHBggULGDp0aFmELQjCv9Dr9eabtiNHjuDq6oy/vxtZWRfZuXMV3t7NcXS0JjraHaVSARQAEBb2+D4dLiwsYu/eE5w/fwVXV0d69mxlXqdUKjmZDKpOH2KwccTLQcac51yo7mlqojVwYEdatKhHgwY1sbYuPzUBJeXSpUssWrSIHTt2kJ+fj4uLG127dqZ79+6cOHEJUNOoUROUShWJiZcIDKyKo6MXYWGVqV27Dbda8N5Lh2pBEB7c999/b04g/P39+eyzz2jYsCF79+7l3Xff5cqVK5w7d45p06bxzjvvlHG0woOqMEnE32VlZQHg4uICQHx8PMnJybRt29a8jVqtpnnz5uzevVskEYJQxrRaLWfPniU4OBhbWw2HDu3h3LlT9O/fBdCSnLwfhcIJf/8gPDyMDBnSxpxgODk9XjWJubn5nD4dx/nzV6hfP/TmzMW317VoYfq+at26gUUSsfJYAYWNXkMhU2Cdn8S0QZ7mBAIgMNCXwEDfUjuP0rRy5So++OBjJMmIUgnZ2XD0aBZbtnzD+PGLmDp1BtWqVQP8sLKCPn0GmPctqXknBEG4N7cmc5TJZKxdu5bQ0FAAqlatSkREBGFhYUiSxI8//iiSiAqsQiYRkiQxevRomjRpQliYaVSR5ORkADw8PCy29fDw4PLly/9YVmFhIYWFheb32dnZAOh0OnQ6XUmHLjxGbl0f4jq5LTc3l+Tk5JvtyCXWrVuJo6OGhg3DKSzM5NChVbi4RKJSOePjk4+dXSV0ugQA2rSpA4BOpzeXd+friig7O4/jxy/QuHFtDAbT5G96vZ5Fizbx/PMfAzBlyiiLG38HBztcXBxIT8/m/PnL6HR6JElixvYCpm7KB5mC1tWtmNonDBuVrMJ/Rn9nNBqRyWTIZDJiYxO4fj0DKysFr746nrQ0Cb0eJMkKd3dP0tNN105aWhLDhw/n6NGjj8Xvo/huEe5HebtetFotFy9eBKBevXoEBwdbxBYcHExkZCQHDhwgPj6e7OxsrK2tyyrcJ0pJXyMVMokYMWIEx48fZ+fOncXW/X3SIEmS/nUioYkTJzJ+/Phiy7ds2YKNjc3DBys89jZu3FjWIZQZg8HAxYsX8fBww9XVmmvX4jlz5jQdO9ZDqTSQmXmDggIrdu0yVWtXrWpNXNwp4uJul5GUFF9G0T9aX3yxiDVr9gOwYME7eHm5ArBv31602gzzdtu376NePcvag759m2NlpcTfvxLbduzkl1Oe7Eh0AqBd5XT6BlznyIHSOY9HLSMjB7lcjqOjLTk5RWzdeooGDSKxt3fj8uU00tKyWbx4CZcvm0ZziYmJ4dlnn8XOzo6rV68ydepU4uLiuHr1Km+//TadO3cu4zMqOU/yd4tw/8rL9XJrbhWApKQkVq9ebXEfJkkSSUlJ5vcbNmwQtYWlJD8/v0TLq3BJxKuvvsqKFSvYvn07vr63//B6epomiUpOTraY5Of69evFaifu9M477zB69Gjz++zsbPz8/GjZsiWurq6P4AyEx4VOp2Pjxo3ExMQ89l+AOp0OpVKJTCbjyJEjZGffoHnzukhSLkuWXKRuXUcCA33Q6/2AZqXWOdVoNJCVlYWVlQo7O7tSOeadPv30Jw4cOEVRkY61a7+zWLd+/UlzEqFQOBAVFc2+fXuJioomNDScI0cSCA72o2HDcIs5GwAaNzZNwpaSbWDMklx2J+qQy+CDTrY8E+UGVCuV83sU0tOziItLJDIyDLBj1ao9aDRONG7cHoNBjq/vGapUqWIeMCM5OZkPPvgQgMDAQFasWGExxGqjRo2oW7cuYOpX8/3335f6OZW0J+m7RXh45fF6adCgAfv37ycxMRGAjh1vz9i+Zs0arl41zSAfGRlJt27dyiTGJ1FaWlqJlldhkghJknj11VdZunQpW7dupUqVKhbrq1SpgqenJxs3biQiIgKAoqIitm3bxuTJk/+xXLVajVqtLrbcysqq3PwyCuXb43itpKamolAocHZ25vr1RJYv/4OnnmqDs7MVzs5JWFnlYmV1DYB+/W632beyKp2vlBs3bjBv3jxWrlxJdnYOACEh1enbty+dOnUqsXH8JUkiLi6RQ4fO4ORkT9u20Rbrly3byvHjF1AoFOj1eovOzI0ahRMVFUZERHWqVLk9bKhSqcTd3YUff3z/H4+bmW9k+rY8ftmdh1YHNioZ/+vvSKuQitdZ2mg0snXrIYKCgvD3D0arVXHpUhIREbXQaDS0a1cZjUaDXC7Hygrz9/ctqamp5tetWrUqNnRsREQEnp6eJCcnk5SU9Fj9Lj6O3y3Co1Oerpfhw4ezf7/pIUqfPn14/vnnzR2rf/rpJ/N2I0aMKDcxPwlK+rOuMEnE8OHDWbBgAcuXL8fe3t7cB8LR0RFra2tkMhmjRo1iwoQJBAcHExwczIQJE7CxsaF///5lHL0glG/Xrl3j0qVLNGpUDyhg+/ZluLnZ0qxZTZydC2ja1A9r62xATXBw2XbcjY2NZdiwYaSnZ1gsP3v2HOPHf8yuXbv47LPP7rs2RJIk9HqDRSJ06dI1goK6A9CxY+NiSURERHWOH7+Avb0Nly8nExISYF7XpUszunS5PUPyvfRdyCs0MntXPjO355GjNTXfqetvxafdHQj1fvR/aHNzc8nOzsbBweG+a3aKinQolQrkcjnHjsVy5UoGXbp0QS63w2hMx2CoClSmcuXKVK58O1H4r2ajpqFYTU6ePFlsfXJyMtevXy+2rSAIZWfAgAEsWbKEFStWoNPpmDFjBjNmzLDYpkuXLjzzzDNlFKFQEirMTEzTp08nKyuLFi1a4OXlZf5ZuHCheZsxY8YwatQoXnnlFSIjI0lMTGTDhg1ijghBwNRU79ZT3cJCLfPn/8SlS0eABLTa06Sm7sdoPA5cJCamGo0aBQI6rKyUhIQEoNEUr7ErbUVFRYwePdqcQKhUVkRHRxMcfHvI102b/uLnn3++5zJ37TpKTMwruLq25uefl1usCwjwxsXFdGN66NDZYrOsfvjhC8THryA9fbNFAnG/CvUSc3bl0fyLVKZsyCVHKxHiqeSnZ51YMszlkScQBw8eZOTIkbRo0YIuXbrSokULRo4cycGDB/9xnytXkrl6NQWQkZ2tZ86cv0hOVgM1cHVtROXKjQAfwJE2bdoVqz2+V1WqVDFPGLp3717mzJljXnfrerg1e7loFiEI5YNCoeCPP/5g9OjRxR4U2NjYMHr0aBYvXixmf6/gKkxNxL1MkS6TyRg3bhzjxo179AEJQjmXlZXF6dOniYqKRC7Xsn//egoKsujSpRFqtZbQUA2OjpmAkcBAZwIDm5r3tbe3LbO4/83mzZtJTDQ1owoJqc4333yDm5sbAFu3buWtt97CaJRYuHAhzz77rLmpYlZWLvv3n2TfvpMMG/YUrq5O5jIlCTZtMlW7HzpkOTGSTCZj+PDeKBRy6tWrUWyghocdTtVglFh6RMtXG3NIzDTdCFd2VTA6xo4u4Rrk8n8eFKKk/PHHH0yaZNnkU5Jg585dbNu2i7feGs2AAf25ciWZw4dj6datAzKZDSdPXsDGxglf3zrY2UGLFs44O/sB1vj62uDr61ci8clkMkaPHs3zzz8PwJAhQ/juu++oUaMGW7Zs4do10/WgVqt5+eWXS+SYgiA8PJVKxZdffsmHH37ImjVruHHjBpUqVaJjx46i1vAxUWGSCEEQ7u7OCds2bdqIr68rISF+FBZe5tKlndSsWYSDgx3R0Z4olT7cmrCtbt2QMoz6wWzevNn8etSo180JBECLFi2IiYlh3boNZGZmcfjwERo2NDU/Gj/+B776agEAEREhdOrUxLxfnTrVkMlkeHi4YGtbvM/Bxx+X/I2pJEmsP1XIlxtyuXDd1MzJ3V7Oa63t6FvfGivFo08eAE6cOGHRZ8zR0Y3AwCASEy9x8WIyqanw6qtTCQrqSJUqdXF1dUCvr4KVlRXt2vU2P0WUy7k5R8OjMWTIEPbv38/MmTMBOHz4MIcPHzavt7Ky4tdff6Vy5cqPLAZBEB6Mo6Mj/fr1K+swhEdAJBGCUIEYjUZSU1NxdHRErVZz9Oh+Tp06woABHYE87OyuoVLlAxLu7jKLTs92dhV/yOKsrGzz69DQGhbrPv/8FxYvPklcHISHQ3Z2lnldVFSY+fW+fSctkgg7OxuSktbh7u7yr8NBl5TdF4uY+lcBxxJM43U7Wst4pYUdgxraYK0qneTBaDQil8uZNWsO6emgUMAzz7xA69Y9yc830rp1e8aMGcPUqVMB+PLLmSxatAh399sj35VmMwSZTMb06dNp1KgRX331FUePHgVALpfTtWtX3nnnHRo0aFBq8QiCIAgiiRCEcu/q1avo9XoCAnwpKkpj2bJfaN26HlWruuHnl4OtrTuSlIJMJiM6Ouy/C6zAbGzsyc4GgwEOHz5C06a3k4EjR85x4YKpaUtBwe3Z7AEaN67NiBF9iIoKo1mzusXK9fB49MM5H7uq4/MDfpxOMyVCNioZzzex4cVmtjhoHl33NL1eT1ZWrrkJ1/Llu/H09KV+/Ub88stusrJMn9Xbb//PYqS6iRMnMnfuXFJTU1m+fLk58SgrMpmMQYMGMXDgQK5du0Z2djZeXl44OTmVWUyCIAhPMpFECEI5k5GRwZEjR2jWrAFKpZbY2J1otVkEBESi0UDPnvVwdrYH9Li6Olm073+cGY1GZs7cTUEBqFTw5ZdT8Pb2omrVquj1etRq04zQKhXY2TlQp87tEYB8fT347rsxpR6zJElsv1D0//buOzyqamvg8G8mbTLpvYckQAIhoUY60jsIovQqKhZQil7L/a5gBRuKWBALRVBABVGqIE2KIL2FFkoCJCEkkF5mMnO+P2KGjAFNGRIC632ePMzZ+5x91sAmyZqzC1/+nsOOOB3ggI0VDG+hZXxHB7ycLP9pvsFg4Pz5RLy93XB2duXkySvs2XOCRx55FLXaifr1nXB0dCQvz5GMjKKnIVFRUaWWura1taVBgwZs27YNnU5HXl6eae+G6qRSqQgICCAgIKC6QxFCiHuaJBFCVJOScxk2bFiPn58r0dG1gEQyMw+Tm2uFs7Mj7dqFmQ0d8fR0rZ6Aq0BSUipvvvk1e/Yco2PHGN57b6KpTq1Wc999Dfj99wPodHDu3CUGDRpMnTq1uX79OleuXCM6GmxsYMqUx6tsz4qb0RUq/HI4ny9/z+HUlaI5D1ZqaOWXzptDQgnxsuxKV/HxSWRn59KgQQNUKi2//76b1q3DcHZuSFhYXXx9m6NSuQAq09wFRVFwdnYmMzOT/fv3k5GRYTbZsbgcwMnJ6V+XYhVCCHFvkSRCiCqSm5uLtbU1tra2HDt2kAMH/mDUqL5ANh4eaTg66gAb3Nygf/8b+wvcbUvgHT0ax7JlGzh/PpHRo/uY7b1gZ2fDZ5/9ANx847rBg7tSt24Ahw7tpLDwGgBxcWcBKN4WYvDgQQwZMuQ2v4uby8gz8t2eXBbsyuVKZtFqSw62KoY0t2dkCzsuHD9JgGudf2nl32VmZrN79zFat26Bo6MvV69mkpqqokGDBqjVMGLEk9ja2gJFyyneLAFQqVQMHTqUuXPnkpOTw5gxY/jiiy/w8vIiNTWVcePGkZ2dDcDQoUOrZL6IEEKImkOSCCFuk5ycHHJycvD29kavz+bbb7+kXbuG1KvnTUBAOra2vhiNyajVapo1q3krJf2TZcs2sGXLPs6fT+T779/GxeXGxmVnziTw1ltF+zjUrx9ilkS4u7tQt24wcXEX0esLSy2p+vTTA4GiTdF++mklK1euJCEhHltbO+67L4bBgwfTsmXLKv+F9+K1QubtzOX7vXnk6IqWo/ZxVvNIGy1Dm2txsVej1xdyoRxtKopCXl4BWm3RilHbth3E3t6V5s1bY2trjU6XgU4XBrgTE2O+1GxxAvFvJk+ezDfffENeXh4rV65kzZo11K1blzNnzqDXFw110mg0TJ48uRyRCyGEuBdIEiGEheh0OuLj46lVqxa2tgoHDmwmKSmeQYPux8ZGT8+eEXh62gM63NyccXNzru6QK0xRFE6evMDBg6fIzy9g7FjzTb42btzD118Xbdx27twlmjS5kSSFhd0Yy37u3OVSbf/880wCArxwdr71jsmOjo6MHDmCkSNHlEo0qtKRS3q++D2HtUfzMf61lU09X2seb+dA30YabK3/OS5FUdDrC7G1tcFgMLB3byxhYQF4e/ty5kwSW7ceYOzYkVhbu+LhYYudnQbwR6OBPn0eqHT8ERERLF++nIceeoi8vDz0ej2xsbGment7e3788Ufq1bu7klwhhBCVJ0mEEJWQnJzMhQsXqFs3iPz8JLZs+YE+fZrj7+9GkyauxMS4A0Wf6AYG+lRvsBVUUKAjJyfPtHNzsVatHiEjI5uAAO9SSUTJROH8+USzJCIiohZr1swiLCyQWrV8S92vfv3y7WxckQTiapaBudtyyMhTcLZX4aRR46RR4aRR4Wx6rTY7Lk4IjEaFLacK+OL3HPac15vabFfXlsfbOdCurm2pmIo3y8zOzmPPnmO0ahWNlZU9mzcfIC/PSJ8+vbCy0nDpUhze3mF4e9cmICCMHj3qoVL5AlZERUWX+32WRc+ePYmNjeWTTz7h+++/N20INWjQIMaPH1/hnaaFEELcGRRFYc+ePaxdu9ai7UoSIUQ5pKSkcOjQQbp0aQ1kcv16LAkJKurWbYazM4wa1QGNpmjSbE3fl+H06XgGD36Z48fP8dhj/fnss5dMdSqVisaNw9m27QCXL6dw9ep1vLzcTPUjRvSiS5fmhIUF4uFhnnzY22vo1ast1WX7mQImL8sgNdtYruvsrMFJo0algqtZRddaq+GBRhoea+dApL8NANnZuWRl5eLn5wmoWLp0Mw0aRFGvXhTp6e6kp6tp3Lg+jo5OREV5YzAYgKIE8+GHh5nu5+DgUGWrIYWEhPD+++/z/vvvV8n9hBBCVI0jR47wyCOPmG3QaSmSRAjxN0Vj0fPQarUoisLKlT8SERFIZGQQkEBh4WkKChyxtramRYsg2rZtZLq2OIGoKbZu3cecOcs5ceI806ePp0+fdqY6Hx8PDh06DRTtwfB3jzzyAN26taRJkwgcHe3N6oKDfQkOLv2UoTrpDQofbMzm8205KAqE+1jTr7GGzHyFrHwjWSX+zMy78bp4jkNBIRT8lXg42akY2tyeR9o64GRVwIEDR8l2jsLR0YPY2ETi4hIZNux+QEN0tB1eXl6AG05OAfTq1Qsbm6KEw8enZj6dEkIIcec7duwY999/PxkZGf9+cgVIEiHueQaDgaSkJLy8vLCzs2Hv3t+JizvBsGHdUalyCAnR4eqaAdji7W1Hr16tAdDrC2vEijWrVv3O9u0HOXHiAj/88LZZonPlyjW+/34jAEeOnDFLIlxcHImIqIW1tRUNG5ZeUWj06D5mx0XzJE4SF3cWa+ui4TdBQYGlrqsOF68V8sySDA79tUv0sBb2vNLbuUw7RBuMCqnp+SQkpaN18yRPpxB/+CC+rp74udQnLw+uXk0kL68Ojo5eREcH0bChCiiaEN2gQQMA00RlIYQQoio888wzpgQiMjKSsWPH8vzzz1us/QolETk5Obz99tts2rSJlJQUjEbzYQHnzp2zSHBC3C4XLlzAaDQSFhZIQUEKa9cupmvXGEJD3albVyEgIAS4DmA2nv9OlZycyuHDZ8jOzuWhhzqb1S1Z8itLlvwKwOnTCTRsWNdUVzz/wNraivT0rFLtHju2zLSXxT85cOAAM2d+wMmTJ83KW7VqyYsvvkhQUFC535OlrDqcx39XZJJVoOCsUfHOQy70jNb84zWFhYUcOHCS0NBAvLz8uZ6SwaFdp3nkkXZYWzvhovfE3t4e8MXeHh56aLDp2qJyIYQQovqcOHGCrVu3AhAWFsaff/5Jfn5+9ScRjz32GNu2bWPkyJH4+fnViE9jxb0tNTWVAwf207lza6ys8jh3bgeQT1hYE7RaGDKk1V+rASl39MpJOp2e3Nx8XF2dTGWKohAe/hBZWTkEB/uWSiIaNaprSiJOnDhfKok4ceJHatcOvOm+DGVJIHbt2sXkyVMoLCwsVffHH7sZM+YR5s37mlq1apX5fVpCnk7htVWZLN2bB0CzWjZ8NMSVQLeifTeMRiPXrmXi7u6MWq1mz55YMjML6dq1C9bWWuLj4/D0DMHLqzahoWEEBrbA2rpoxai6deve8r5CCCFEddu7d6/p9aOPPoqDgwP5+fkWvUeFkoh169axZs0a2rRpY9FghKgsnU5nWiN/7dpVBAd7EhUVjEp1CZ3uJHl5WhwdtXTsWM8s+f2n5UTvBCdPXmDIkP8SG3uOceMe5JNPXjTVqVQqGjasw86dh0lISCY9PcssyRg4sAuNGoUTGRlGYKC3Wbs2NtbUqxdS4bgKCgqYOnWqKYEID69Lr169ycvLZeXKlVy5kkJ6ejrTp09n7ty5Fb5PeZ1M1jPhu3TiUgyoVDC+gwOTujhy7mwCSfkO+Pn5kpycxerV+xk4cCBubv54e7vj5JQHFD01GThwuKk9Ozs77Oxq1nwXIe40RqOR3377jUOHDqFWq2nRogVt27aVDyKFuA1KjhIq695B5VWhJMLNzQ13d3dLxyJEuZXcBfrw4b0cObKXkSN7A9n4+WXi7KwGbPHwsKZPnxsrAt2JP7RiY8+xcuVWDh48xeTJw2jd+saEbW9vNw4fLprkfPjwmVLXDhnSjRYtomjUqC7W1uY7XIeFBRIWdnvmJvz2229cv54OQMuWLfnoo1mmpxdDhw5l2LBhJCYmsW/ffuLi4qhTp/K7Nf8TRVH45o8c3lyTid6gxkWfwiPRWUzq3hPQcvz4SQIDffHza4S3dyH9+tXF2dkTsJKlTIW4jdatW8eECRNKDXdu0KABX3zxBa1bt66myIS4OzVqdON3iIULFzJx4kSL30NdkYveeOMNpk6dSm5urqXjEeIf5ebmkpqaCoBOl8XixZ9z4cJ24CjBwdm0aROAolwF8mnSpN4dt0KQoiicO3eJH3/87a+lPW/YuzeW//u/z/jxx03s2HHIrM7d3YWwsAAaNAijQYOwUu1OmDCYmTMnM2pUnypdWrbkknFjxow2G/7k5OTEwIEDTccHDx68LTFkZmaTmppOeq6Rx+Zd5bk3V5B3LZWOEa5881gLGtWKRlHqAAH07z+c++4r+mXF2toaHx8frKys/vkGQohK+eWXX+jTp89N50seP36czp07s3PnzmqITIi7V5MmTYiJiQGKVmnq3Lkz69evt+g9KvQkYubMmZw9exYfHx9CQkJMyxUWux1r0Yp7k06n4+LFiwQHB2NjY2Tfvk2kpFzk4YfbYWuro2fPCLy8qn4X6IsXL7F//z5OnDiJg4MjMTHNyvR0Y8SIV/juu6L/xCdO/Gg2lKhJkwjT6yNH4kpde+rU8jLNUahKJVcccnV1LVVfssxSqxOlp2cRG3uOFi0aYWXlxJ9/nubw+WyWp4aSmGFEGxDBf/o1ZUL3hkX/JvUjTdfeiU+ghLibFRQU8Pjjj5uGVrRr147HHnsMnU7HnDlzOHDgAPn5+Tz22GPExsbK/1EhLGj27Nl07NiRgoICtm/fzvbt2y3afoV+I+nfv79FgxCipISEBFQqFUFBPuTmXmLTpmX06dMCf39XmjZ1Ra12B3QABAVV7ZOGy5cv884777Bz5y5T2Y8//khISAiTJk2iXbu2fPjht+zYcYiMjBx+++0zs+vr1w8xvT548KRZElG/fiiLF79BkyYRhIcHl7r3nZZAQNEmZcXWr19vNuFYURSzTz1KnvtvjEYj2dm5prkqq1fvIjS0Ng0aNEKnc+LixUtER4eTUWjFnznZfHk6AcWqgBAPLR9PGE50oMu/3EEIURVWrFhBSkoKAD169GDNmjWo1UWDIEaNGkXr1q3Zv38/J0+eZOvWrXTs2LE6wxXirtKqVSvWr1/PyJEjuXTpksXbr9BvJdOmTbN0HOIelpmZyZkzZ2jatCEqVTYnTmzFzq6QoKBGuLrCiBHt0WqLluSszl2gL1++zNixY0lNTaOwEIoXOXB0LFoydvLkSbz11lt8992v7NtX9IlaZma22aTtdu2a0LNna2JiIomONp8fYGNjzfDhPS0as9FoNA3/8vDwsPjQnT59+vD5559jMBj55ptvsLa24YEH+pKbm8fixYvYs+dPAHx9fWnRooXZtYqiYDAYsLa2RqfTc/p0PGFhgWi1juzbF8eZM0kMHz4C0OLnB87O3ugNfpzLvs45p2YM+PIAZ1KyixqzsmFAkwBe7x+Fo92dl2wJca/avXu36fXEiRNNCQQUTfYcP348Y8eONZ0rSYQQltWhQwfOnTvHqlWr2LBhg0UXOanUT9v9+/dz4sQJVCoVkZGRNGnSxFJxibvcsWPHcHV1JjDQjZycOI4f30h4eA5OTg506VLP7Jfd4gSiOuh0evT6Qhwc7Hn33XdNCcSRI0X1YWFeNGzoy5EjR1EUePPNN2nUqCv79sXi4GBPXNwlmja9sc9E+/bNaN++2W2POzs7m8WLF/PTTytNSYSnpycPPtifESNG4OhomdWovL29GTlyJAsWLMRoVPjqq6/46quvAFAUMBhArYZJkyZy5co1zp27TNu2TQFbfvnld9zcPLj//rYYDAb27NmHi8t9aLVh1KsXSq1aeYArV7MKOI8P835P4fczsWTl31hK1kqtolmwG8NbBtOvcYBF3pMQwnJKzv3SaEp/Ly+5r8rf54kJISzDxsaGAQMG0L59++pPIlJSUhgyZAhbt27F1dUVRVHIyMigY8eOLF26FC8vL4sFKO4OKSkpnDt3jpYtGwJZXLiwC39/RwIDI/D1VRg5sotpLOydMNH1998PMH78O5w8eYEZMyYwZEhH08Q/Pz9PUlIUkpPTuHIli88/X8m0adPYuPE3cnPziIry4vjx74mIqFUt7+X69es88cQTnD1rPokxNTWVL7/8ik2bNjF37lyLrLCmKAqjRo3BaDSyaNEisrOhsLAoccjPh/x8a/7v/16ma9enOHfuMteu5aMojVGpVDRp4vTXsqk+2NvDo49OAMBoVDifYWTLqQy2/HCGw5cyzO7p7mBLh3AvOtbz5v66XrhobW4SmRDiTtCwYUPT63nz5tGhQwfTsaIozJs3z3RccjUZIcSdr0JJxDPPPENmZibHjx+nfv36AMTGxjJ69GieffZZlixZYtEgRc1jNBrZvXs3ISH++Ps7kZt7isTEvej1KmxsrOnT58an8dU1kW7Dht2sXLmVI0fOMH/+NOrWvTEPwdFRy7FjZwE4ejSOyEgPFKWo7sEHH6RBg1yys3PRalUUFhoZPXo0Gzf+BkBSUjyRkaVXUDp48CA//PADhw8fwWAopHbtOjz4YH86duxo0WRj2rRppgTCykptWp1h3759GAxGzp07z7Rp0/j444/L3bbBYODYsbMEBnrj4eHFqVOX+f33w4wf/y4PPPACb745k7Nnz+Pu7k6bNm3o3bs3YWFhgC1hYS6Ehd2Y5BwcbD7vY9vpq6w6nMjWU1dJzS4wq4sKcKZThDcd6nnTKNAVK7VMvhSiJhgyZAjPPfcc2dnZLFq0CLVazeOPP45Op+Pjjz9m48aNAAQEBNCzp2WHcwohbq8KJRHr16/nt99+MyUQAJGRkXz66ad069bNYsGJmuXMmTMkJV3k/vuboFZncu3aQby9U4AgQkK0hIS0r4aYEjh06DQJCck899wIs7rdu48yZ86PABw6dNosiahfPwSNxo66dYMIDvY1243ZycmJmTOfQK8vZOfOHdja2uDkdGNzt8JC81WIjEYj7733Ht9//4NZ+dWrqezevZv77oth5syZODg4VPr9njt3zjTp28PDnblzvyA0NASA8+cv8MQT40hLu8auXX9w9uxZateuXaqN/PwCkpPTCAoqWv70zz9PkJGho2vXLlhZ2XP06GHs7Rvh4RFJcHAdevWKRq32JjTUl6+/nl+huOdsPcs760+ajh1srWhX14uO9bzoEOGNj3P1DWkTQlScs7Mz7733Hk899RRQtF79woULzc5RqVR8/PHHd+TiEUKIW6vQ/1ij0VhqWVcoGnNVcoc8cXfLzc1lw4Z1tG7dEG9vDSpVHIpyEShaGadPn5ZVFktmZjbXr2dRq5afWfmwYf8zTXJ+8smHcHC4Mf625MTmCxcSza6zt9eQlbXN9EPt6NGjprr169czZMgQs/PXrVtnev33TcsWLlxolkBotfbY2tqSnl40TGfv3n1MmzaN999/v1zv+Wa2bt1qej1q1ChTAlEUVwijR4/mgw8+pLAQVqxYzX/+U7T5zJo1u6hdO4x69epz/Xo6GzacYdCgxri6+uLp6YajYz5QlGSNGPF4ifeiRaut3GT3kgnEoJhA+jUO4L4Qd2ytK7SNjRDiDvPkk0+iKAr/+c9/yMnJMatzc3Njzpw5PPjgg9UUXc2UmZnJ/PnzWbRoEZcuXUKtVjNw4EAmTJhgtkqeELdThZKITp06MXHiRJYsWYK/vz9QtHLN5MmT6dy5s0UDFNXPaDSaVtTYtWs7eXnX6dy5KRpNBi4uqajVCYArdep4U6eOd5XGdv16Ji1bjuH06QS6d2/F+vXmQ3QaNqzDvn2xKIpCbOw57ruvgamuQ4dmbN/+FVFRtXF1dfp702afikVFRVG7dhhnz57j+PFYXnjhBUaMGEFqaipfffUVCxbc+AS+X7/+ptd5efmmT91UKnj++ecZMGAA1tbW7Ny5k1deeYWsrGy2bNnKmTNx1K1buR2dMzMzTa89PPy4di0Dd3cXrl3L5Lff9uPrW4/UVMjOhj/+uALUB+zw8jKg1foCwXh7Gxg5sr5pwmPRcKTbo2QCMaVrOM92lh9+QtyNnnrqKYYNG8Z3333HoUOHUKvVNG/enMGDB1f6g4h7zcmTJ+nevTsJCQlm5bNnz+azzz5j3rx5jBw5spqiE/eSCiURn3zyCf369SMkJISgoCBUKhUJCQlER0ezePFiS8coqkFhYSHW1takpFxh9erlPPxwJ5ydwdf3+l+bhl1BrYaOHWNueyyXLl3h++83sn//SR544H4GD74xZM7V1Ylr14p+cd6//wSKopjNsXjooU6EhPgTHV3HbLgSgJubM23bNi5TDCqVismTJ/Pss89iNCps2bKVLVu2ljpvyJAhBAUFmo537NhBVlbRMqS9e/c2e4LRrl07nnjiSdMTiHXr1lK37rNligeKkrtr1zJxdnbA1taGM2cSuHw5j6wsKCiAxYt/x9m5EW3aRGFvbyAw0I5Vq1ZR/HOnZcvOQNEP7+bNm5vatbKyMlsx5Xb5fJskEELcS1xcXEzDmkTFZGVl0aNHD7MEIiAggCtXrlBYWEhhYSFjxowhODiY9u2rfgixuLdUKIkICgriwIEDbNy4kZMnT6IoCpGRkXTp0sXS8YkqUlBQ8NdKObB69XJcXKxp1y4SV9frNG3qio1NGqAhLOz2LaNZUKDj4MFTREaGmu2tcPHiFZ57bhYAGo2tWRKhUqlo06YRiYlXadasPvn5Bdjb3xg/36tXW3r1amuR+Fq1asU777zDa6+9Rna2+SN5laoogZg8ebJZeUrKFdPrli1LD+9q1epG2ZUrKaXqFUUhL6/AtMztgQMn0Wg0REbWJyenkBUr9tOzZ0+Cgmpja+tGq1YKH364EoPBwE8/bWbgwMdQFFs0mqLVmWbPng2AWq1m6NChFf/LqKTPt53l7XWSQAghRHksXLiQ+Ph4oGjlq2+//ZaIiAiWLVvGpk2bWLBgAUajkenTp0sSIW67Ss1i6tq1K127drVULKIKFRYWYjAYsLOz49y5U2zatJZRo3phZ1dAVJQtGo0tkImtrRWNG0fc9nhmzfqOF16YjV5fyKpVH9KnTztTXaNG4ajVaoxGI0eOxJW69qef3q+yFZ46depEixYtWLt2Hfv37yM5OZlmzWJ48MH+BAYGljq/5H4M586dK1VfXKYo4OjoQGFhIYcPnyE01B93d09OnLjErl1HGTt2NGq1lvz8bNRqFyASR0eF/v19/1qq1ZpatcKoVSuMMWPG8PXXX5OXl8eDDz6Iv78/KpWKy5cvm+47evRogoKCLP73UxaSQAghRMWUHO3xzTffEBUVhV6vx8nJiTlz5rBt2zbOnz/Phg0bSE5OxtfXtxqjFXe7MicRs2fPZty4cWg0GtOnmbfy7LNlH5IhqobBYCAzMxM3NzfAyLJlC4iI8CMmJhRf3+t06BCClVU6YE1IiP9tiWHHjkNs3ryX/ftP8OOP72Jjc6P7BQR4o9cXrYC0Z88xsyRCq9WwdOl06tYNokGD0qsJVfUSsQ4ODgwc+DD9+/dn584dtGnT1uy9lNSqVSusrNQYDEa+//4Hunfvjq+vPwkJyfj6uvL553NJTS0aftSiRX/U6tqcOhWLu3sw7u51CA4Ow8kpGvAG1LRufeOTJZVKhbd36Tkon3zyCYmJiabJ3omJ5pPGe/bsyaeffmqxv4/ymFsigZjcRRIIIYQoj0uXLgFFG33+fV8NKysrOnfubNrwMzExUZIIcVuVOYn48MMPGT58OBqNhg8//PCW56lUKkki7gAGg4H4+Hi8vb1xdNRw7Nhu9u//kzFjeqFW59KunR8uLo5AHlqtptR8gcrIy8vn4sUrhIfXMiv/7LMfWLLkV6Bo74WSOzm3aBFFvXohtGgRRYsWUaXaHDiwZg2VKyjQkZdXgLe3N926deO779aTnp5N9+7DaNiwNSkpOZw4cYrr13MBqF27Nh06DEOtVjNs2COmdhwdHcu9u7RGo2HVqlUsX76czz//nH379gEQExPDE088wcMPP1wtm+DN3XaWGSUSiIldak4CodPp+PHHH01DCRwcHOjRowdPPPFEqf0uhBDidnFxceHy5cukpqaSkpJS6oOk2NhYs3OFuJ3KnEScP3/+pq/FnePcuXPk5uYQFVUHRclg8+bvadcuiogIP+rUgYCARqhU2YCK4ODb8+lE+/bj2LnzML6+Hly6tNasrkWLKFMSsW9frFkSERzsy4kTP96WmG4n5a8d6LKzczly5AxNmtTH3t6VvXvPkZSUzsCBg3j++QV8/307zpw5Axg5d26HWRve3t6sWrXKtAKWJVhZWTFo0CAGDRpksTYroyYnEImJifTs2ZMjR46YlR84cICZM2cyf/78ap1fIoS4d/Tp04fY2FiMRiOTJ09mwYIFprpvv/2WXbuK9gmKjIy8rSvrCQFQod9aXn/9dXJzc0uV5+Xl8frrr1c6KFE2165d4+effyI3NxlIJDX1AFeu7AJisba+zMiR7YmIKNo3wcHBHk9P10oP/cnKymHu3OWMG/cW7767sFR90dAdA5cvp5CUlGpW17dvOxYvfoO4uJU8/njNWBPcaDSa9j65ciWNo0eL52RYs3LlHxw9mgb4YzTW4tIlO3Jz6wL1adiwO126PAy44Orqw4EDB3jllVfw8fExta3Vann88cfZt2+f2caNd5uSCcSkLnVrVAKh0+no1auXWQJRclPAgoICRowYwZYtW6ojPCHEPeapp54yLYLy3XffERYWxqOPPsp//vMfHnnkxlPsSZMmVflQX3HvqVASUbQ6TXap8tzcXF577bVKByXMldzAb/36NezZswGIR6M5h6NjMoWFp4AkmjcPpXPnG0uu2tnZVuqep05dKJUIKIrCk0/O4Msvf2L58s2lrmvRIoro6Do88khfdDrznZvDwgIZPrwntWsH3lHf3ErGeeLEec6fvwyoycws5OuvN3DligoI5OpVR06c0AONgUY0aNANJ6dwwBdn52AGDRqOh4cnULRLa9H8kyKOjo68/vrrXLx4kZMnT3Ls2DFSUlL44osvqm2Cc1X44nfzBGJSl/Bqjqh8VqxYweHDhwGoVasWmzdvJisri8TEREaNGgUU/V+RD0+EEFUhJCSERYsWmfYxunTpEosWLfrrSXeRRx99lMcee6y6QhT3kAolEX9fi7/Y4cOH/1opRlSGoigUFhZNMj53Lo5vvvmcwsILQCy1auXh56cHUtFqVXTu3NxsOVRL2LBhNx4enalX72EWLlxtVufs7Eh4eNEY8GPHzpriLDZ9+niOHFnKvHnTSu0eXV0MBgP5+QVAUcKwe/dRrl3LAGw4diyRxYt/B/yBEC5dsiUlxQNogoNDDG3aPIizc33Ah6io1gwaNAIomk9Qt27dcvd3GxsbIiIiaNCggdkn2nejL34/y/S1NTeBAEwbBQLMmzePjh07olKp8PPzY968eYSHF72nrVu3cuHChWqKUghxLxk4cCDbt2+nb9++Zr+LRUVF8fXXX/Pll1/eUR/UibtXuZZ4dXNzQ6VSoVKpCA8PN+ukBoOB7OxsnnzySYsHeS/Iy8vD3t4eRTHy3XcLiIoKplGjIDw9rxAT44GiXAGsqV8/1CL3O306ng0bdrNnzzFeffUJate+sTxpcLAv6elZAOzefbTUtR999DyOjloaNw4329UZqn6lpGL5+QVYWVlhY2PNlStpnDoVz/333wfYsW7dDjQaR7p06YJarSY+/gyBgXVwdw8mKKgWWm0DFMUXlUpF164PmNq0srIiMjKyWt5PTVcygZjYuWYmEIApMbC3t6djx45mdVZWVvTq1YvTp08DkJCQQEhISBVHKIS4F7Vs2ZJffvmFtLQ04uPj2b9/P6NHj8bWtuIjEIQor3IlEbNmzUJRFMaOHctrr71mNvPf1taWkJAQWrVqZfEg7zZGo5HU1FScnZ3RaDQcPLibo0f3MXJkd1SqHJo3d8PDQw1k4+zsQFRUnQrfKy0tnRMnLpTamXn58s38979Fy3x26dLCLIkIDw8mIqIW4eHBdO3aolSbPXq0rnA8lVG8izZAXNxFdDo9kZF1KSy05ptvfqVDh/sJDw9Hp3Pk+vVs9PoG2NjYEBPj9td1nlhbw+DBI01turi4yAoWFmI0KpxPy+Hng5eZvblo7sjEznWZ3LVmJhBwY5+PvLw8EhMTCQgw32wxLi6u1LlCCFFVPDw8cHZ25uLFi/L0QVS5ciURo0ePBiA0NJTWrVtjY2NzW4K6G509WzT0JyIilMLCdFauXEDHjk2pW9eb0NB8PDxCgQxAVaHlVvX6wlJ7FQwc+CI//rgJgCtXNuDtfWPoTcuW0abXf/55nNGj+5iO1Wo1J08uL3cMlnbsWBze3u54e3sSH5/Gr7/uYdSoIWg0rly9mk5BAURGNsbaGrp1c8TLywtwICjIjaCgGxvk3cvrZCuKwtWsAgyKgreTBiu15X7IJGfkc+hiOkcupXP4UjpHLmWQlX9jeFtNTyCgaE+N4iVyX3rpJRYsWGBaHnfLli2sWbMGAH9/f6Kjo2/ZjhBCCHG3KXMSkZmZibOzMwBNmjQhLy+PvLy8m55bfN69RqfTYTQa0Wg0JCcn8/vvm+jfvwu2toUkJ+9Fp8smIiIbW1t46KFmuLo6AXpcXZ3+el0+BoOBfv2e4+jROPz8PNm9e4FZfUDAjfWjjx8/Z5ZE3HdfJLNnP0/LltE0alQ9v+jpdHoSE68SGOiNtbU1+/ad5sqVLHr37gFoOHr0MNHR4Xh7N8HTM4f27YOwsgoGbGjVqrNZWzVpGEm+3kCezoCzvY1FfqlXFIWUrAIupOZwIS2HC2m5XEjN4XxqDvFpueTpDQBYq1X4OGsIcLMnwNUef1cNAa7av/60x9/VHge7m39LSM/VceRSBkcupXPoYtGfKVkFpc6zs1bTwN+ZAU0DGdGy1k1aqlnGjRvHu+++S0FBAYsXL2b37t306tWLs2fPsnbtWtMSv08//bR8qCKEEOKeUuYkws3NjaSkJLy9vXF1vflSocUTrg0Gg0WDvFNdvXqVa9euERERDhSwbNl8IiNr0axZHbTaFAIC8iksjMPWVkObNubLWnp4uJbpHllZOWzZso89e47RrFl9BgzoZKqzsrLixInzJCQkk5aWgdFoNNtroEWLBnTo0IyoqNp4eprfz9FRyzPPDKnoWy8zo9FITk4eTk5Fk4i3bz+Il5c39erVJzMzjw0bztC/fxTe3kH4+Hij1WYBRU9ihg4da2rHwcGBiIiIm93ijpNTUMjl9DwuXc/l8vU8LhV/pedx+Xouqdk607lOdtY429vgUuLLVVv059/LXextyNcbiE/L5Xxazl9JQy7xaTnk6m79f06tArVKRaFR4XJ6HpfTb578A7hqbfB3sTclGtdydBy5lM6FtNJLOlupVdT1dqRxkCsNA11pFORCuI8TNlaW2++iugUGBrJw4UKGDx+OwWAgLi6O2bNnm53Tq1cvXnjhhWqKUAghhKgeZU4iNm/ebFqJ5l5aE72wsBC9Xo+9vT3Z2dls3vwbbdo0wcPDnsuX93Hy5AkiIjoBRjp1CsHZ2QHIwtnZnjZtGpfrXnl5+ahUKjQaO1PZ2bOX6NfvOQAGD+5qlkQAREXVJjU1naio2qSnZ+HufmN8/9ChPRg6tEdF33qZFa0mZcDGxpr8/AIOHjxFZGQYLi6eHDoUx7FjFxg1agSgwcoqF5XKG6iLu7uRESPqoNVqAWrMUqcFhQYuXsvjXEomvyepOLzuFEmZBX8lC7lcz9X/eyN/ySooJOuvpKMy1CoIdNNSy0NLqKcDtTwcCPXUEuLhQKCbFiu1ipSsfBLT87icns/l63kkpuf9dVz0lZVfSHqunvRcPbFJmaXuUctDS6NAVxoGutA4yJUG/i7Y21b9ztdVbfDgwfj5+fHaa6+xefONZY39/f2ZMGECzz//vDyFEEIIcc8pcxLRvn37m76+uxWwdu1yHB2t6dSpGRpNJg4OSYAT4ErDhl40buwDFO3jUHL4UHmsWbODqVM/58iRMyxe/AaDB3cz1UVF1Uar1ZCbm8+ePcdLXfvtt2/i4GBfJROqip80paamk5CQ/NeO07asWrUDZ2d3OnToiFqtIiHhHCEhdXFx8adOnSD8/XMBDwBat25nak+tVpsSiDtNTkEh8Wm5JFwr/rS/6BP/+LRcEjPy+GsUC2AFF+JLXe+ssSbQTUugW9Gn+sWvA93sCXTV4mBnRWZ+Iem5OjLy9KavzLyiX+JLlpX8srZSEeLhUPTlWZQo1PJwIMhNi631Pz8B8HOxx8/Fnma3GGWUma8vkVgUJRxaGysaBRUlDq7ae3fVj/vvv59NmzaRkJBAfHw8jo6OREdHl1qdTAghhLhXVOgn4Pr163F0dKRt27YAfPrpp3z55ZdERkby6aefmm2yVVPpdPsBD1q08MTW1gZIx9oaOndubjqn5NChf7NixWbWrdvF6dMJLF06HT8/zxLtqDhwoGg5zN27j5olEdbW1rz33kR8fNxp0SKqVLuOjrfnl/Dk5FQKCw0EBvqg0xn57rvfuP/+NoSFhZOeDidPXqRhw2isrW1p2tTtr09ivbG1hcGDR5jacXZ2vqPnyOgNRv48f40D8ddNQ4Pir+Vy9Sbj/UtysLUiyF2LrS6DmHqhBP31iX9x0uCs+fdPpt0dbHF3uHN+MXfW2ODsa0M93zv336u6BQcHExxc/oUPhCiLHTt28Omnn7Jt2zays7Np2LAh48aNY8iQIbJ0pxDijlOhJOI///kP77zzDgBHjx5lypQpPPfcc2zevJkpU6Ywf/58iwZZHWxti/5qfHw8/vVcvV5PRkYGy5ZtJi7uIoWFBj7+2HyM9PbtB/nqq5UAnDx5wSyJaN68AWq1mvr1Q256v6efHliJd3Jr6elZ2NraoNVqSE5OZdeu4zzwQA+srR2JjY0nN7eQwMCu2Nra0LSpHe7uwYArder4UqdOM1M7gYGBt77JHShfb2DHmVTWH0/mtxNXSL/F8CM3rQ3BHg6EeGip5V70iX+Ip5Zgdwc8HW0pLCxk7dq19OoZIcNZhBAVpigKzz//PB988IFZ+c6dO9m5cyeffvopa9euxcPj338eCSFEValQEnH+/HnTJlzLly+nb9++TJ8+nQMHDtCrVy+LBngnSU1N5/vvNxIXd5HGjcNp1SqCb775ht9++w2dTs/x41BQABqNLbNn/8dsiFFExI0xJBcuJJq16+HhSkbGVos/VTAYDKSnZ+Hq6oSVlRVnz14iIyObpk0bAhpWrtxG48ZNaNy4EXZ2wXh62lNYGIa1tYZ27fz+GqpR9B4aNmxo0diqWla+ni2nrvLrsWS2nEoxm4js7mBL+3AvansVzSWo5aGllrsDLlpJDIQQt99HH31klkA4OTlhbW3N9evXAfjzzz8ZOHAgmzZtkr0AhBB3jAolEba2tuTmFq3W8ttvvzFq1CgA3N3dycwsPSGzqn322We89957JCUl0aBBA2bNmkW7du3+/cISXnppNhMnDjXb6C0jI5vx44uewLRv35DPPotFr7+xLr6dXVESkZ+v4733PuKFFyaZ6vr370BMTCR16wbj4lJ6U6qKJhDp6VlkZ+cSGOgDwKZNewkM9CciIoLU1Ex+/nk/Dz/8IO7uPuTmKn/9UCpaz75375E4OTkBGtzcHLn/fi9Tu5b4ZD0jT09cSjYu9ta4O9jhYqElTcvqWo6O32KvsP54MjvOpKIzGE11/i4aujXwpUeUL/eFuFdpXEIIUUyn0zFjxgzT8QcffMDjjz/Ob7/9hqOjI8OHDyclJYUtW7awa9cu2rRpU43RCiHEDRVKItq2bcuUKVNo06YNf/75J8uWLQPg9OnT1T60ZdmyZUyaNInPPvuMNm3aMHfuXHr27ElsbGy5xjJ/9dXPtGnT2CyJqFXLF2trKwoLDezde5R69Ypm17q4OBMd3RCNJparV69hZwdLly6mVatmpuTF19cTX1/Pm97r31y7loFarcbV1Ynr1zPZuHE/3bp1wtXVk9OnU4iLu8SwYfcDdtjb52Nj4weE4eFRSP/+tXB2dgesiY6OMWu3aHM2y1EUhbiUbDafTGHzyRT2xV/HYDTNQEatAletLW5aGzwc7HBzsMHdwQ4PB1vcHGzN/nTW2GBlpcJKpUKtBiuVCiu1CrVahVpVurz407mkjDx+PZbMr8evsOd8GiVuT5inAz2iihKH6AAX+URPCFHtNm3aREpKCgAPPfQQkydPRq/Xo1KpaN++Pe+++y5jxowBYPHixZJECCHuGBVKIj755BOefvppfvzxR+bMmUNAQAAA69ato0eP27+k6D/54IMPePTRR3nssccAmDVrFr/++itz5swx+7SnLOLiLpodW1tbs2jR62zfvpXff98IQNeuXZg27VXs7TUYjUa+/noen3/+OVD0Db84iTAaFTLyFNJyjKRlG4v+zDGSkWvESg3WGLC3VWNvZ01m2hWuJSfTvFVz7Kw1bN8Qi6+PH23aRqEYVDh7qCkoDEVRXGnc2JemTdUU/1O2bt3GLF5v74qtGFVW+XoDf5xNY/PJFLacSuHSdfOlSn2c7cjTGcjML8SoFD0duJaj4+zVHIvGofprL4SSSQtAA39nevz1xKGOt6MkDkKIO8rly5dNr7t06VKqvmRZyXOFEKK6VSiJCA4OZvXq1aXKP/zww0oHVBk6nY79+/fz0ksvmZV369aNXbt2lautNWtm3XQ1pCFDuvPtt59ga1v0S/qLL77E1VxrYs/mk5ZjJDd0MOoYBzIKrNhkdKHL+1dIz1dxLUuHPj8PK/uinan1aZdApcLGPQCjPp+c41uxD22KtYs3+vR0CtNS0Ry/gkqlwljgjSrOCtXuPTcC2bgLWys1Llob3LQ2uGptcbW3wU1ri+tfx0Xlxa+Ly22ws67c2v6Xruey5WQKW05dZdfZVPL1N4YJ2VqraRXmQad63nSM8CbYo2iYlt5g5HpuUQJxLVvHteLXf32l5ei4XuI4M1+P0QgGRSmVGNyMohSdi6LgoWTQPyaEMV2aEOR+Zy4hK4QQAC4uN/b2OXbsWKn6kmWurq5VEZIQQpRJhRc5NxgMrFy5khMnTqBSqahfvz79+vXDyqr6Np9KTU3FYDDg4+NjVu7j40NycvJNrykoKKCg4MZynsVzOpo1q4+zs6PZnIe/n+Pn54utrR2/7M7l/Y25FGZeBcDarSOKoZC8c/s4ee4q1s6e6K8lkX/xOAEteuLhaIexQIezgx31GvljVCDZT4WNsydGK1vy9W4UFEZQoDdQUGikoFBDfmHRa12hEb2h6JdqncHI1ayCf12O9O/srNU4a6xx0ljjpLHBWWONs8YGR431X6+tcbK3+Ws35aK6gkID28+ksfX0Vc6kmD9F8HW2o0OEFx3CPWkV5o7W9ka30utvrHzkprHCTWNPbQ/7csULRU9yDIqCUSnx2qjw+/btPPHU06Rdu4ZKZYVRn098QQ4HgNghQ/jiiy/QaDTlvl9ZFL+3ku9RiFuR/iJupn379tjb25OXl8e8efMYOnQoTZo0ASA5OZmXX37ZdG6vXr2k/4hS5HuLKCtL95EKJRFxcXH06tWLy5cvExERgaIonD59mqCgINasWUPt2rUtGmR5/X3ISvEmaTczY8YMXnvttVLl+/btxcFBw/XrWSiKgru7MwaDgYMHzwJ25OfncOTIJSZP/oBabfsT5uxMbtoF7NUKZ4/uJv1KIvrUBCaMf5rQgEJsFXesdDG4uelQqfQQXjw/I6Hoj7pWwPUyvT+DAnoj5BYWfeXoVUV//vWVW6gqeq0vep1rKgcFFQWFRq5m67iarSvj36g5FQqhThDpZqSBq4KfthCVKoeCcxfYeq5CTVZIXFwc//3vf9Hpbv4+li5dSnx8PC+88MJtHca0cePG29a2uPtIfxF/16FDB9atW0deXh7t2rUjOjoaR0dHDh48SF5e0RBRHx8fbGxsWLt2bTVHK+5U8r1F/JviRZEsRaUoyr+PFfmbXr16oSgK3377Le7u7gCkpaUxYsQI1Go1a9assWiQZaXT6dBqtfzwww88+OCDpvKJEydy6NAhtm3bVuqamz2JCAoKIjFxD56ePmzcuIvCQujZsyeKYs2vv25m48bf+PjjjwFo3bo1S5Yswc/Pj6ysLP73v/8xZ84coOian3/++Ta/67IzGhWyCgrJyi8kM19PVv6N15l/vb5ZXVZ+IYUGhZhabnSI8KRdHU9c74DlT3v27MmmTZsA6Ny5M//73/8IDAzk559/Ztq0aeTkFD0x2bJly22ZjKjX69m4cSNdu3aVfSLEv5L+Im4lNzeXvn37sn379pvWe3p6sn79+hq/1La4PeR7iyirtLQ0/Pz8yMjIsMxGwEoFaLVa5ciRI6XKDx06pDg4OFSkSYtp3ry58tRTT5mV1a9fX3nppZfKdH1GRoYCKFeuXFEURVEKCgoUg8Fgdk5iYqLi4uKiAAqg2NjYKE2aNFGcnJxMZSqVStm6datl3pQo5fz586a/69DQUKWgoMCs/quvvjLVjxo16rbEoNPplJUrVyo6ne62tC/uLtJfxD/Jy8tT3n77bSU4ONj0vUur1Srjxo1Tzp8/X93hiTuYfG8RZZWamqoASkZGhkXaU1ck8bCzsyMrK6tUeXZ2Nra2thVKZixlypQpfPXVV8ybN48TJ04wefJkEhISePLJJ8vVTvHcDltbW9Rq878mPz8/Vq1aZZoQp9frOXjwoOnvRK1W88UXX9C+fXsLvCNxMydOnDC9HjhwYKl+N3z48JueK4QQdyKNRsOLL77I+fPnOXXqFJ9++imJiYnMnTuXkJCQ6g5PCCFKqVAS0adPH8aNG8eePXtQFAVFUdi9ezdPPvkkDzzwgKVjLJfBgwcza9YsXn/9dRo3bszvv//O2rVrqVWr1r9fXA7t2rXj6NGjvPjiiwQEBKBSqXBzc+ORRx5h//79piVmxe1RMmko3tW1pPT09JueWxPt27ePRx99lKioKCIjIxk6dChbt25FKf9IRCHEHU6tVhMaGkpAQABarawuJ4S4c1VoYvXs2bMZPXo0rVq1Mo2/0+v19OvXj48++siiAVbE008/zdNPP33b7xMUFMTbb7/N22+//Y+Tt4XlxcTEmFY0WbJkCf/973/NPq0ruSfI/fffXw0RVp7RaGTKlCml/k+dOHGCpUuXMnToUBYsWFDjkyQhhBBC1DwVSiJcXV35+eefiYuLIzY2FoDIyEjq1KnzL1fevSSBqFouLi6MGDGCL7/8kuzsbJo1a8bjjz9OcHAwK1asME24trKyYty4cdUcbcVMnz7dLIGwsbFBpVKZVqNasmQJrq6ufPbZZ9UVohBCCCHuURUazgTw9ddf079/fwYOHMjAgQPp378/X331lSVjE+IfzZgxg/DwcACuXbvGO++8w/jx400JBBTtYF4TxxNnZWXxzjvvAEUJ6vvvv096ejpZWVl8/fXX2NnZATB37lwuXrz4T02VW3x8PK+88gp9+/alX79+TJ8+/Zb7rAghhBDi3lShJOKVV15h4sSJ9O3blx9++IEffviBvn37MnnyZP73v/9ZOkYhbsrDw4MdO3YwZMiQUpschoSE8O233/Lss89WU3SV89NPP5GdnQ3A2LFjee6559Bqtdja2jJ27FheeOEFoGjI0+LFiy1yT0VRmDp1KmFhYbz55pusXr2aX375hf/7v/8jODiY2bNnW+Q+QgghhKj5KjScac6cOXz55ZcMHTrUVPbAAw/QsGFDnnnmGd58802LBSjEP/Hy8mLJkiW8//77bN26lby8PMLCwmjfvn217p5eWfHx8abXffr0KVXfp08f3njjjVLnVsZbb71lavPv9Ho9EydORKvVyqIBQgghhKjYkwiDwUBMTEyp8mbNmlFYWFjpoIQor4CAAIYPH85jjz1Gp06danQCAeDo6Gh6HRcXV6q+ZFnJcysqLS3NlPyrVCpefvllzp07x8mTJ80WKXj55ZfNNmcUQgghxL2pQknEiBEjTLsyl/TFF1+Yrc8vhKiYHj16mF5/+OGHXLp0yXR87do13nrrLdNxz549K32/b7/91pQcPP3000yfPp3Q0FAiIiL49NNPGTBgAACpqan88ssvlb6fEEIIIWq2Cg1ngqKJ1Rs2bKBly5YA7N69m4sXLzJq1CimTJliOu+DDz6ofJRC3GPq169Pt27d2LBhA4mJidSrV48BAwZgZ2fH8uXLTXtjREdH06lTp0rf7+TJk6bXJYcplixbsWJFqXOFEEIIcW+qUBJx7NgxmjZtCsDZs2eBorHpXl5eHDt2zHSeLHsqRMXNmzePdu3acf78eXJycli0aJFZvZeXF8uWLbPI/7Pi1Z6g6GnD35UsK3muEEIIIe5NFUoitmzZYuk4hBB/ExAQwO7du5k2bRqLFi0iJycHKNqBe9CgQbzxxhsWW762ffv2zJo1C4D33nuPnj17mjaxy87ONtuvon379ha5pxBCCCFqrgoPZxJC3H7e3t7MmTOH9957j+PHj2M0GqlXrx5ubm4WvU+fPn2oVasW8fHx7Ny5k0aNGjF69Gh0Oh3z5s0zrQAVExND8+bNLXpvIYQQQtQ8kkQIUQM4OjrSokWL29a+tbU1ixYtolu3buTn53Py5Elefvlls3NcXV2ZP3++DFMUQgghRMV3rBZC3F3atWvHtm3baNWqVam6Ll26sGvXLqKioqohMiGEEELcaeRJhBDCpHnz5uzatYtjx45x6NAh1Go19913H3Xr1q3u0IQQQghxB5EkQghRSlRUlDx1EEIIIcQtSRIhbkmv17Ny5Up+/vln0tPT8ff3Z9iwYbRv317GxQshhBBC3MMkiRA3dezYMfr168e5c+fMyr/88kvatWvH8uXL8fLyqqbohBBCCCFEdZKJ1TVQWloap0+fJi0t7ba0f/HiRTp16lQqgSi2fft2evToQX5+/m25vxBCCCGEuLNJElGDbNy4kS5duuDp6UlERASenp506dKFDRs2WPQ+M2bM4OrVqwA0btyYX3/9laSkJBYvXoyfnx8ABw4c4Ntvv7XofdPT05k9ezY9e/bk/vvvZ+TIkfz2228YjUaL3kcIIYQQQlSOJBE1xKxZs+jWrRubNm0yK9+0aRPdu3fnww8/tMh9CgoKWLRoEQAODg5s2LCBbt264evry/Dhw/nhhx9M53711VcWuSfAr7/+SkhICBMnTmT9+vVs376dxYsX07VrVzp16sS1a9csdi8hhBBCCFE5kkTUALt27WLy5Mmm49q1azNs2DDCwsJMZVOmTGHHjh2Vvtfly5fJzs4GoGvXrqXmPbRp04bg4GAATpw4Uen7Aezbt49+/fqRkZFx0/pt27bRr18/DAaDRe4nhBBCCCEqR5KIGqDkU4YXX3yR06dP8+2333LmzBlefPFFU92sWbMqfS9bW1vT65t9+q/T6cjMzCx1bmVMnTqVgoICAHr37s2RI0fIyclh2bJleHt7A7Bjxw5WrVplkfsJIYQQQojKkSTiDmc0Gvnll18A8PLy4vXXX0etLvpnU6vVvPHGG6ZftH/55ZdKf1ofEBBgesLx+++/l3q6MXfuXNLT0wFo3759pe4FkJiYyPr16wEIDg5mxYoVREdHo9VqGTRokNmQqa+//rrS9xNCCCGEEJUnScQdLi8vD51OB0C9evVKffpvY2NDvXr1gKJ9HSq7YpJKpWL8+PGm4y5duvDkk0/y2Wef8dBDD/Hss8+a6kqeV1Fnz55FURQAHnjggVLvr3fv3tjb2wMQFxdX6fsJIYQQQojKk30i7nBarRYXFxcyMjLYv38/6enpuLq6murT09PZv38/AM7Ozmi12krfc8KECaxdu5ZNmzZRUFDA3LlzS53z7LPP0qFDh0rfqzhBAEhKSipVf+3aNVNipNFoKn0/IYQQQghRefIk4g6nUqkYPnw4ALm5uYwcOZLk5GQAkpOTGTlyJDk5OQAMHz7cIjtJ29rasnr1aiZOnIiDg4NZnY+PDx988IFF5l8AREdH4+npCcDPP/9sSogAFEXhtddeMz2p6Ny5s0XuKYQQQgghKkeeRNQAkydPZsGCBeTm5rJ69WoCAwMJDQ3l/PnzpjkQWq2WSZMmWeyeGo2GWbNm8dprr7Fp0ybS09Px8/Ojc+fOFptQDWBnZ8cTTzzBW2+9RWFhIW3atGHo0KHUrl2b1atXs2fPHgCsrKx46qmnLHZfIYQQQghRcZJE1AB16tRh5cqVDBgwgOzsbAwGg9n8AEdHR1asWEF4eLjF7+3i4sKAAQMs3m5J//d//8fWrVvZuXMnBQUFLFiwoNQ5H3/8MbVr176tcQghhBBCiLKR4Uw1RNeuXTlx4gQvv/wytWvXxtnZmdq1a/Pyyy8TGxtL165dqzvECrO3t+fXX39l0qRJODk5mdVFRUWxfPlyeQohhBBCCHEHkScRNUhgYCDTp09n+vTp1R2KxTk4OPDhhx/yxhtvsGvXLrKzs6lVqxZNmza1yDwPIYQQQghhOZJEiDuKo6Mj3bp1q+4whBBCCCHEP5Ak4h6hKArx8fGkpaXh4+NDYGBgdYckhBBCCCFqKJkTcZdTFIUlS5YQExNDaGgoMTExBAUF0a5dO9auXVvd4QkhhBBCiBpIkoi73Msvv8ywYcM4cOCAWfmOHTvo3bu3xfZ7EEIIIYQQ9w5JIu5iq1at4p133jEdN2vWjHHjxlG/fn1T2eTJk017MQghhBBCCFEWkkTcxT788EPT6w8++IB9+/Yxd+5cjh8/zosvvmiqmz17dnWEJ4QQQgghaihJIu5SOTk5bNmyBYDatWszceJEU51KpeLVV1/F1dUVgDVr1lRHiEIIIYQQooaSJOIulZ2dbXodHh6OWm3+T63RaAgNDQUgMzMTRVGqND4hhBBCCFFzSRJxl3J3d0er1QKwc+dOsrKyzOovXbrEkSNHgKJN7GRDNyGEEEIIUVaSRNylbGxsGDJkCFD0pGHIkCEkJCQAcPr0aYYMGYLBYABg1KhR1RanEEIIIYSoeSSJuIv95z//MT2NWLt2LbVq1cLX15eIiAh27twJgIeHB+PHj6/OMIUQQgghRA0jScRdrF69evz88884OTmZyq5cuWJ67eXlxfr16/Hz86uO8IQQQgghRA1lXd0BiNurS5cunD59mi+++ILly5dz7do1vL29GTp0KGPHjsXd3b26QxRCCCGEEDWMJBH3AF9fX6ZOncrUqVOrOxQhhBBCCHEXkOFMQgghhBBCiHKRJEIIIYQQQghRLjUiibhw4QKPPvoooaGh2NvbU7t2baZNm4ZOpzM7LyEhgb59++Lg4ICnpyfPPvtsqXOEEEIIIYQQlVMj5kScPHkSo9HI3LlzqVOnDseOHePxxx8nJyeH999/HwCDwUDv3r3x8vJix44dpKWlMXr0aBRF4eOPP67mdyCEEEIIIcTdo0YkET169KBHjx6m47CwME6dOsWcOXNMScSGDRuIjY3l4sWL+Pv7AzBz5kzGjBnDW2+9hbOzc7XELoQQQgghxN2mRgxnupmMjAyz5Un/+OMPoqKiTAkEQPfu3SkoKGD//v3VEaIQQgghhBB3pRrxJOLvzp49y8cff8zMmTNNZcnJyfj4+Jid5+bmhq2tLcnJybdsq6CggIKCAtNxZmYmAHq9Hr1eb+HIxd2kuH9IPxFlIf1FlJX0FVEe0l9EWVm6j1RrEvHqq6/y2muv/eM5e/fuJSYmxnScmJhIjx49GDhwII899pjZuSqVqtT1iqLctLzYjBkzbhrDli1b0Gq1//YWhGDjxo3VHYKoQaS/iLKSviLKQ/qL+De5ubkWbU+lKIpi0RbLITU1ldTU1H88JyQkBI1GAxQlEB07dqRFixYsWLAAtfrGaKypU6fy888/c/jwYVPZ9evXcXd3Z/PmzXTs2PGm7d/sSURQUBBJSUl4eHhU5u2Ju5xer2fjxo107doVGxub6g5H3OGkv4iykr4iykP6iyirtLQ0/Pz8yMjIsMhc4Wp9EuHp6Ymnp2eZzr18+TIdO3akWbNmzJ8/3yyBAGjVqhVvvfUWSUlJ+Pn5AUWTre3s7GjWrNkt27Wzs8POzq5UuY2NjfxnFGUifUWUh/QXUVbSV0R5SH8R/8bS/aNGzIlITEykQ4cOBAcH8/7773P16lVTna+vLwDdunUjMjKSkSNH8t5773Ht2jWef/55Hn/8cVmZSQghhBBCCAuqEUnEhg0biIuLIy4ujsDAQLO64tFYVlZWrFmzhqeffpo2bdpgb2/PsGHDTEvACiGEEEIIISyjRiQRY8aMYcyYMf96XnBwMKtXr779AQkhhBBCCHEPq7H7RAghhBBCCCGqhyQRQgghhBBCiHKRJEIIIYQQQghRLpJECCGEEEIIIcqlRkysFkIIIYS4m+Tn55stWV9RRqORoKAgEhMTS+2hJe49Xl5epk2abzdJIoQQQgghqlB+fj4pKSkEBARgZWVVqbaMRiMuLi44OztLEnGPMxgMXL58GW9v7ypJJKS3CSGEEEJUoatXr1okgRCiJCsrKwICAizyhKssJIkQQgghhKhikkCI26Eq+5UkEUIIIYQQQohykSRCCCGEEELcUS5cuIBKpeLQoUPVHYq4BUkihBBCCCHELalUqn/8GjNmTHWHKKqBrM4khBBCCCFuKSkpyfR62bJlTJ06lVOnTpnK7O3tzc7X6/XY2NhUWXyiesiTCCGEEEIIcUu+vr6mLxcXF1Qqlek4Pz8fV1dXvv/+ezp06IBGo2Hx4sWkpaUxdOhQAgMD0Wq1REdHs2TJErN2jUYj77zzDnXq1MHOzo7g4GDeeuutm8ZgNBp5/PHHCQ8PJz4+viretvgX8iRCCCGEEEJUyosvvsjMmTOZP38+dnZ25Ofn06xZM1588UWcnZ1Zs2YNI0eOJCwsjBYtWgDw8ssv8+WXX/Lhhx/Stm1bkpKSOHnyZKm2dTodw4YN4+zZs+zYsQNvb++qfnviJuRJhBBCCCFENfvggw8IDAwkMDCQrVu3mtWdP3/eVPfMM8+Uunbo0KEEBwcTGBhYqm7BggWma1esWHG7wmfSpEkMGDCA0NBQ/P39CQgI4Pnnn6dx48aEhYXxzDPP0L17d3744QcAsrKy+Oijj3j33XcZPXo0tWvXpm3btjz22GNm7WZnZ9O7d2+Sk5PZunWrJBB3EHkSIYQQQghRzTIzM7l8+TIABQUFZnXFOxEDXL9+vdS1aWlppvq/y8nJMdXl5uZaMmQzMTExZscGg4G3336bZcuWcfnyZQoKCigoKMDBwQGAEydOUFBQQOfOnf+x3eIhUZs2bUKr1d62+EX5SRIhhBBCCFHNnJ2dCQgIAMDOzs6srngnYgA3N7dS13p4eJjq/87BwcFUdzt/CS9ODorNnDmTDz/8kFmzZhEdHY2DgwOTJk1Cp9MBpSdj30qvXr1YvHgxu3fvplOnThaPW1ScJBFCCCGEENVsypQpTJky5aZ1oaGhXLp06ZbXLlmyBGdnZ9Tq0qPUx4wZUy1LsG7fvp1+/foxYsQIoGhi9JkzZ6hfvz4AdevWxd7enk2bNpUawlTSU089RVRUFA888ABr1qyhffv2VRK/+HeSRAghhBBCCIuqU6cOy5cvZ9euXbi5ufHBBx+QnJxsSiI0Gg0vvvgiL7zwAra2trRp04arV69y/PhxHn30UbO2nnnmGQwGA3369GHdunW0bdu2Ot6S+BtJIoQQQgghhEW98sornD9/nu7du6PVahk3bhz9+/cnIyPD7Bxra2umTp1KYmIifn5+PPnkkzdtb9KkSRiNRnr16sX69etp3bp1Vb0VcQsqRVGU6g7iTpKZmYmLiwupqal4eHhUdzjiDqbX61m7di29evWSTXXEv5L+IspK+srd7+LFiwQFBVmkLaPRSGZm5i2HM4l7z636V1paGp6enmRkZODs7Fzp+0hvE0IIIYQQQpSLJBFCCCGEEEKIcpEkQgghhBBCCFEukkQIIYQQQgghykWSCCGEEEIIIUS5SBIhhBBCCCGEKBdJIoQQQgghhBDlIkmEEEIIIYQQolwkiRBCCCGEEEKUiyQRQgghhBCiwjp06MCkSZNMxyEhIcyaNava4hFVQ5IIIYQQQgjxr8aMGYNKpSr19e677/LGG2/c8jqVSsXKlSurLlBRJayrOwAhhBBCCFEz9OjRg/nz55uVeXl5YWVlddvvrdfrsbGxue33EWUjTyKEEEIIIUSZ2NnZ4evra/bVuXNns+FMJYWEhADw4IMPolKpTMcAq1atolmzZmg0GsLCwnjttdcoLCw01atUKj7//HP69euHg4MDb7755m18Z6K85EmEEEIIIUQ1URSFPL2hwtcbjUbydAasdYWo1eX7bNjexgqVSlXhe5fF3r178fb2Zv78+fTo0cP0xOLXX39lxIgRzJ49m3bt2nH27FnGjRsHwLRp00zXT5s2jRkzZvDhhx9WydMOUXaSRAghhBBCVJM8vYHIqb9Wy71jX++O1rZ8vwquXr0aR0dH03HPnj3/8XwvLy8AXF1d8fX1NZW/9dZbvPTSS4wePRqAsLAw3njjDV544QWzJGLYsGGMHTu2XDGKqiFJhBBCCCGEKJOOHTsyZ84c07GDgwNDhw4tdzv79+9n7969vPXWW6Yyg8FAfn4+ubm5aLVaAGJiYioftLgtJIkQQgghhKgm9jZWxL7evcLXG41GsjKzcHJ2qtBwpvJycHCgTp065b7u74xGI6+99hoDBgwoVafRaMzuJ+5MkkQIIYQQQlQTlUpV7iFFJRmNRgptrdDaWpc7iagqNjY2GAzm8z6aNm3KqVOnLJKQiOohSYQQQgghhLhtQkJC2LRpE23atMHOzg43NzemTp1Knz59CAoKYuDAgajVao4cOcLRo0dlFaYa4s5MWYUQQgghxF1h5syZbNy4kaCgIJo0aQJA9+7dWb16NRs3buS+++6jZcuWfPDBB9SqVauaoxVlJU8ihBBCCCHEv1qwYMFNy7du3Wp2fOHCBbPjvn370rdv31LXde/ene7dbz0fRFGU8oYoqpA8iRBCCCGEEEKUiyQRQgghhBBCiHKRJEIIIYQQQghRLjUuiSgoKKBx48aoVCoOHTpkVpeQkEDfvn1xcHDA09OTZ599Fp1OVz2BCiGEEEIIcZeqcROrX3jhBfz9/Tl8+LBZucFgoHfv3nh5ebFjxw7S0tIYPXo0iqLw8ccfV1O0QgghhBBC3H1q1JOIdevWsWHDBt5///1SdRs2bCA2NpbFixfTpEkTunTpwsyZM/nyyy/JzMyshmiFEEIIIYS4O9WYJOLKlSs8/vjjLFq0CK1WW6r+jz/+ICoqCn9/f1NZ9+7dKSgoYP/+/VUZqhBCCCGEEHe1GjGcSVEUxowZw5NPPklMTEyp9YcBkpOT8fHxMStzc3PD1taW5OTkW7ZdUFBAQUGB6bj4qYVer0ev11vmDYi7UnH/kH4iykL6iygr6St3P6PRiNFotEhbxXspKIpisTZFzWY0Gm/6/cPS31OqNYl49dVXee211/7xnL1797Jr1y4yMzN5+eWX//FclUpVqkxRlJuWF5sxY8ZNY9iyZctNn3gI8XcbN26s7hBEDSL9RZSV9JW7V1BQEC4uLhZtMysry6LtiZorLS2t1OJDALm5uRa9j0qpxu0AU1NTSU1N/cdzQkJCGDJkCKtWrTJLBgwGA1ZWVgwfPpyFCxcydepUfv75Z7MJ19evX8fd3Z3NmzfTsWPHm7Z/sycRQUFBJCUl4eHhUcl3KO5mer2ejRs30rVrV2xsbKo7HHGHk/4iykr6yt0vMTGRoKAgi7SlKApZWVk4OTn944em4t5x8eJFs+H9xdLS0vDz8yMjIwNnZ+dK36dan0R4enri6en5r+fNnj2bN99803ScmJhI9+7dWbZsGS1atACgVatWvPXWWyQlJeHn5wcUTba2s7OjWbNmt2zbzs4OOzu7UuU2NjbyzVuUifQVUR7SX0RZSV+5e6nVatRqy0xLLR7CpFKpLNbmrYwZM4aFCxfyxBNP8Pnnn5vVPf3008yZM4fRo0ezYMGC2xrH3UylUvHTTz/Rv3//CrehVqtv+r3D0t9PasTE6uDgYKKiokxf4eHhANSuXZvAwEAAunXrRmRkJCNHjuTgwYNs2rSJ559/nscff9wi2ZYQQgghxJ1gz549DBs2DE9PTxwcHGjZsiXvvfce6enpt/3eQUFBLF26lLy8PFNZfn4+S5YsITg4+LbfvzJk7zDLqhFJRFlYWVmxZs0aNBoNbdq0YdCgQfTv3/+my8EKIYQQQtREM2bMoGXLlixZsoS0tDTy8/M5deoUL730Eo0aNeL06dO39f5NmzYlODiYFStWmMpWrFhBUFAQTZo0MZUpisK7775LWFgY9vb2NGrUiB9//NFUbzAYePTRRwkNDcXe3p6IiAg++ugjs3tt3bqV5s2b4+DggKurK23atCE+Ph4oeiry90/rJ02aRIcOHUzHHTp0YMKECUyZMgVPT0+6du0KQGxsLL169cLR0REfHx9GjhxpNry+Q4cOPPPMM0yaNAk3Nzd8fHz44osvyMnJ4ZFHHsHJyYnatWuzbt06s/uXpd1nn32WF154AXd3d3x9fXn11VdN9SEhIQA8+OCDqFQq0/Hhw4fp2LEjTk5OODs706xZM/bt2/cv/1K3X41MIkJCQlAUhcaNG5uVBwcHs3r1anJzc0lLS+Pjjz++6VAlIYQQQoiaZtmyZfz3v/81Hbu4uFC/fn3TcUJCAr169TJ7SnA7PPLII8yfP990PG/ePMaOHWt2zv/+9z/mz5/PnDlzOH78OJMnT2bEiBFs27YNKBqGFRgYyPfff09sbCxTp07lv//9L99//z0AhYWF9O/fn/bt23PkyBH++OMPxo0bV+55HwsXLsTa2pqdO3cyd+5ckpKSaN++PY0bN2bfvn2sX7+eK1euMGjQoFLXeXp68ueff/LMM8/w1FNPMXDgQFq3bs2BAwfo3r07I0eONE1WLk+7Dg4O7Nmzh3fffZfXX3/dtIjC3r17AZg/fz5JSUmm4+HDhxMYGMjevXvZv38/L7300p0x1FERZjIyMhRASU1Nre5QxB1Op9MpK1euVHQ6XXWHImoA6S+irKSv3P0SEhLKfY3RaFSio6MVQAGUadOmKXl5eYrBYFD+/PNPJSoqylS3YMGC2xC1oowePVrp16+fcvXqVcXOzk45f/68cuHCBUWj0ShXr15V+vXrp4wePVrJzs5WNBqNsmvXLrPrH330UWXo0KG3bP/pp59WHnroIUVRFCUtLU0BlK1bt/5jLCVNnDhRad++vem4ffv2SuPGjc3OeeWVV5Ru3bqZlV28eFEBlFOnTpmua9u2ram+sLBQcXBwUEaOHGkqS0pKUgDljz/+qHC7iqIo9913n/Liiy+ajgHlp59+MjvHycmpXP+mt+pfqampCqBkZGSUua1/UiP2iRBCCCGEuJfFxsZy9OhRAFq2bGkaBmM0Gqlbty5z5syhXbt2AHz33XeMHj36tsXi6elJ7969WbhwIYqi0Lt3b7OFcmJjY8nPzzcNHyqm0+nMhjx9/vnnfPXVV8THx5OXl4dOpzONMnF3d2fMmDF0796drl270qVLFwYNGmRaPKesYmJizI7379/Pli1bcHR0LHXu2bNnTfNuGzZsaCq3srLCw8OD6OhoU1nx3mQpKSkVbhfAz8/P1MatTJkyhccee4xFixbRpUsXBg4cSO3atf/xmqogSYQQQgghxB0uKSnJ9Lp9+/al6lu1aoWNjQ16vd7s3Ntl7NixTJgwAYBPP/3UrK54xag1a9YQEBBgVlc8zPz7779n8uTJzJw5k1atWuHk5MR7773Hnj17TOfOnz+fZ599lvXr17Ns2TL+97//sXHjRlq2bIlarTZttFfsZpupOTg4lIqtb9++vPPOO6XOLZmg/H24kEqlMisrHlZV/F4r0+6/bRL46quvMmzYMNasWcO6deuYNm0aS5cu5cEHH/zH6243SSKEEEIIIe5wbm5uptc320jsxIkTpl+iS557u/To0cO02lH37t3N6iIjI7GzsyMhIeGmCQ/A9u3bad26NU8//bSp7OzZs6XOa9KkCU2aNOHll1+mVatWfPfdd7Rs2RIvLy+OHTtmdu6hQ4f+da5A06ZNWb58OSEhIVhbW+7XYEu1a2Njg8FgKFUeHh5OeHg4kydPZujQocyfP7/ak4gaObFaCCGEEOJe0rhxY2rVqgXAr7/+ypIlS0yfxGdkZDBx4kTTuQMGDLjt8VhZWXHixAlOnDiBlZWVWZ2TkxPPP/88kydPZuHChZw9e5aDBw/y6aefsnDhQgDq1KnDvn37+PXXXzl9+jSvvPKKaSIxwPnz53n55Zf5448/iI+PZ8OGDZw+fdo0kbxTp07s27ePb775hjNnzjBt2rRSScXNjB8/nmvXrjF06FD+/PNPzp07x4YNGxg7duxNf3kvK0u1GxISwqZNm0hOTub69evk5eUxYcIEtm7dSnx8PDt37mTv3r1mE+qriyQRQgghhBB3OCsrKyZPnmw6HjZsGI0bN+bBBx8kOjqazZs3A0VzCW7nfIiSnJ2db7kX1xtvvMHUqVOZMWMG9evXp3v37qxatYrQ0FAAnnzySQYMGMDgwYNp0aIFaWlpZk8ltFotJ0+e5KGHHiI8PJxx48YxYcIEnnjiCaDo6ccrr7zCCy+8wH333UdWVhajRo3615j9/f3ZuXMnBoOB7t27ExUVxcSJE3FxcanUZn2WanfmzJls3LjRtGSulZUVaWlpjBo1ivDwcAYNGkTPnj157bXXKhyrpaiUvw8ou8dlZmbi4uJCamoqHh4e1R2OuIPp9XrWrl1Lr1697oyl1sQdTfqLKCvpK3e/ixcvEhQUVO7rjEYjjz766C13hHZycmLNmjWmCdbi3nSr/pWWloanpycZGRkW2YhZnkQIIYQQQtQAarWaefPm8c0339CsWTNTub29PWPHjmXfvn2SQIgqIxOrhRBCCCFqCJVKxciRIxk5ciRpaWlkZWVhb2+Pl5dXpYbjCFFekkQIIYQQQtRAHh4euLm5kZmZWd2hiHuQpKxCCCGEEEKIcpEkQgghhBBCCFEukkQIIYQQQgghykWSCCGEEEKIKlaZjc2EuJWq7FeSRAghhBBCVCEvLy8uX74siYSwKIPBwOXLl/Hy8qqS+8nqTEIIIYQQVUij0eDt7U1SUhKV3fPXaDSSlpaGh4eHLPEq8Pb2RqPRVMm9JIkQQgghhKhiGo2GwMDASrej1+s5dOgQ0dHRssO5qFKSsgohhBBCCCHKRZIIIYQQQgghRLlIEiGEEEIIIYQoF0kihBBCCCGEEOUiE6v/pniVhKysLJmgJP6RXq8nNzeXzMxM6SviX0l/EWUlfUWUh/QXUVZZWVkAlV4RrJgkEX+TlpYGQGhoaDVHIoQQQgghhGWlpaXh4uJS6XYkifgbd3d3ABISEizyFyzuXpmZmQQFBXHx4kWcnZ2rOxxxh5P+IspK+oooD+kvoqwyMjIIDg42/a5bWZJE/E3xRi0uLi7yn1GUibOzs/QVUWbSX0RZSV8R5SH9RZSVpTYllInVQgghhBBCiHKRJEIIIYQQQghRLpJE/I2dnR3Tpk3Dzs6uukMRdzjpK6I8pL+IspK+IspD+osoK0v3FZViqXWehBBCCCGEEPcEeRIhhBBCCCGEKBdJIoQQQgghhBDlIkmEEEIIIYQQolwkiRBCCCGEEEKUiyQRJXz22WeEhoai0Who1qwZ27dvr+6QxB3g999/p2/fvvj7+6NSqVi5cqVZvaIovPrqq/j7+2Nvb0+HDh04fvx49QQrqtWMGTO47777cHJywtvbm/79+3Pq1Cmzc6S/CIA5c+bQsGFD0wZhrVq1Yt26daZ66SfiVmbMmIFKpWLSpEmmMukvotirr76KSqUy+/L19TXVW7KvSBLxl2XLljFp0iT+7//+j4MHD9KuXTt69uxJQkJCdYcmqllOTg6NGjXik08+uWn9u+++ywcffMAnn3zC3r178fX1pWvXrmRlZVVxpKK6bdu2jfHjx7N79242btxIYWEh3bp1Iycnx3SO9BcBEBgYyNtvv82+ffvYt28fnTp1ol+/fqYf5tJPxM3s3buXL774goYNG5qVS38RJTVo0ICkpCTT19GjR011Fu0rilAURVGaN2+uPPnkk2Zl9erVU1566aVqikjciQDlp59+Mh0bjUbF19dXefvtt01l+fn5iouLi/L5559XQ4TiTpKSkqIAyrZt2xRFkf4i/pmbm5vy1VdfST8RN5WVlaXUrVtX2bhxo9K+fXtl4sSJiqLI9xVhbtq0aUqjRo1uWmfpviJPIgCdTsf+/fvp1q2bWXm3bt3YtWtXNUUlaoLz58+TnJxs1nfs7Oxo37699B1BRkYGAO7u7oD0F3FzBoOBpUuXkpOTQ6tWraSfiJsaP348vXv3pkuXLmbl0l/E3505cwZ/f39CQ0MZMmQI586dAyzfV6wtFnENlpqaisFgwMfHx6zcx8eH5OTkaopK1ATF/eNmfSc+Pr46QhJ3CEVRmDJlCm3btiUqKgqQ/iLMHT16lFatWpGfn4+joyM//fQTkZGRph/m0k9EsaVLl7J//3727dtXqk6+r4iSWrRowTfffEN4eDhXrlzhzTffpHXr1hw/ftzifUWSiBJUKpXZsaIopcqEuBnpO+LvJkyYwJEjR9ixY0epOukvAiAiIoJDhw6Rnp7O8uXLGT16NNu2bTPVSz8RABcvXmTixIls2LABjUZzy/OkvwiAnj17ml5HR0fTqlUrateuzcKFC2nZsiVgub4iw5kAT09PrKysSj11SElJKZWtCVFS8YoH0ndESc888wy//PILW7ZsITAw0FQu/UWUZGtrS506dYiJiWHGjBk0atSIjz76SPqJMLN//35SUlJo1qwZ1tbWWFtbs23bNmbPno21tbWpT0h/ETfj4OBAdHQ0Z86csfj3FkkiKPpG3qxZMzZu3GhWvnHjRlq3bl1NUYmaIDQ0FF9fX7O+o9Pp2LZtm/Sde5CiKEyYMIEVK1awefNmQkNDzeqlv4h/oigKBQUF0k+Emc6dO3P06FEOHTpk+oqJiWH48OEcOnSIsLAw6S/ilgoKCjhx4gR+fn4W/94iw5n+MmXKFEaOHElMTAytWrXiiy++ICEhgSeffLK6QxPVLDs7m7i4ONPx+fPnOXToEO7u7gQHBzNp0iSmT59O3bp1qVu3LtOnT0er1TJs2LBqjFpUh/Hjx/Pdd9/x888/4+TkZPq0x8XFBXt7e9Pa7tJfxH//+1969uxJUFAQWVlZLF26lK1bt7J+/XrpJ8KMk5OTaV5VMQcHBzw8PEzl0l9Eseeff56+ffsSHBxMSkoKb775JpmZmYwePdry31vKvZ7TXezTTz9VatWqpdja2ipNmzY1Lcso7m1btmxRgFJfo0ePVhSlaMm0adOmKb6+voqdnZ1y//33K0ePHq3eoEW1uFk/AZT58+ebzpH+IhRFUcaOHWv6eePl5aV07txZ2bBhg6le+on4JyWXeFUU6S/ihsGDByt+fn6KjY2N4u/vrwwYMEA5fvy4qd6SfUWlKIpioeRHCCGEEEIIcQ+QORFCCCGEEEKIcpEkQgghhBBCCFEukkQIIYQQQgghykWSCCGEEEIIIUS5SBIhhBBCCCGEKBdJIoQQQgghhBDlIkmEEEIIIYQQolwkiRBCCGFxW7duRaVSkZ6eXt2hCCGEuA1kszkhhBCV1qFDBxo3bsysWbMA0Ol0XLt2DR8fH1QqVfUGJ4QQwuKsqzsAIYQQdx9bW1t8fX2rOwwhhBC3iQxnEkIIUSljxoxh27ZtfPTRR6hUKlQqFQsWLDAbzrRgwQJcXV1ZvXo1ERERaLVaHn74YXJycli4cCEhISG4ubnxzDPPYDAYTG3rdDpeeOEFAgICcHBwoEWLFmzdurV63qgQQggTeRIhhBCiUj766CNOnz5NVFQUr7/+OgDHjx8vdV5ubi6zZ89m6dKlZGVlMWDAAAYMGICrqytr167l3LlzPPTQQ7Rt25bBgwcD8Mgjj3DhwgWWLl2Kv78/P/30Ez169ODo0aPUrVu3St+nEEKIGySJEEIIUSkuLi7Y2tqi1WpNQ5hOnjxZ6jy9Xs+cOXOoXbs2AA8//DCLFi3iypUrODo6EhkZSceOHdmyZQuDBw/m7NmzLFmyhEuXLuHv7w/A888/z/r165k/fz7Tp0+vujcphBDCjCQRQgghqoRWqzUlEAA+Pj6EhITg6OhoVpaSkgLAgQMHUBSF8PBws3YKCgrw8PComqCFEELclCQRQgghqoSNjY3ZsUqlummZ0WgEwGg0YmVlxf79+7GysjI7r2TiIYQQoupJEiGEEKLSbG1tzSZEW0KTJk0wGAykpKTQrl07i7YthBCicmR1JiGEEJUWEhLCnj17uHDhAqmpqaanCZURHh7O8OHDGTVqFCtWrOD8+fPs3buXd955h7Vr11ogaiGEEBUlSYQQQohKe/7557GysiIyMhIvLy8SEhIs0u78+fMZNWoUzz33HBERETzwwAPs2bOHoKAgi7QvhBCiYmTHaiGEEEIIIUS5yJMIIYQQQgghRLlIEiGEEEIIIYQoF0kihBBCCCGEEOUiSYQQQgghhBCiXCSJEEIIIYQQQpSLJBFCCCGEEEKIcpEkQgghhBBCCFEukkQIIYQQQgghykWSCCGEEEIIIUS5SBIhhBBCCCGEKBdJIoQQQgghhBDlIkmEEEIIIYQQolz+H4QfRi9DgmwwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy.random import seed\n",
    "seed(2)\n",
    "trk, zs = compute_dog_data(z_var=225, process_var=.02, count=50)\n",
    "\n",
    "run(track=trk, zs=zs, R=225, Q=200, P=P, plot_P=False, \n",
    "    title='R_var = 225 $m^2$, Q_var = 20 $m^2$')\n",
    "run(track=trk, zs=zs, R=225, Q=.02, P=P, plot_P=False, \n",
    "    title='R_var = 225 $m^2$, Q_var = 0.02 $m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The filter in the first plot should follow the noisy measurement closely. In the second plot the filter should vary from the measurement quite a bit, and be much closer to a straight line than in the first graph. Why does ${\\mathbf Q}$ affect the plots this way?\n",
    "\n",
    "Let's remind ourselves of what the term *process uncertainty* means. Consider the problem of tracking a ball. We can accurately model its behavior in a vacuum with math, but with wind, varying air density, temperature, and a spinning ball with an imperfect surface our model will diverge from reality. \n",
    "\n",
    "In the first case we set `Q_var=20 m^2`, which is quite large. In physical terms this is telling the filter \"I don't trust my motion prediction step\" as we are saying that the variance in the velocity is 20. Strictly speaking, we are telling the filter there is a lot of external noise that we are not modeling with $\\small{\\mathbf F}$, but the upshot of that is to not trust the motion prediction step. The filter will be computing velocity ($\\dot x$), but then mostly ignoring it because we are telling the filter that the computation is extremely suspect. Therefore the filter has nothing to trust but the measurements, and thus it follows the measurements closely. \n",
    "\n",
    "In the second case we set `Q_var=0.02 m^2`, which is quite small. In physical terms we are telling the filter \"trust the prediction, it is really good!\". More strictly this actually says there is very small amounts of process noise (variance 0.02 $m^2$), so the process model is very accurate. So the filter ends up ignoring some of the measurement as it jumps up and down, because the variation in the measurement does not match our trustworthy velocity prediction.\n",
    "\n",
    "Now let's set `Q_var` to $0.2\\, m^2$, and bump `R_var` up to $10,000\\, m^2$. This is telling the filter that the measurement noise is very large. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run(track=trk, zs=zs, R=10000, Q=.2, P=P, plot_P=False, \n",
    "    title='R=$10,000\\, m^2$, Q=$.2\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The effect of this can be subtle. We have created an suboptimal filter because the actual measurement noise variance is 225 $m^2$, not 10,000 $m^2$. By setting the filter's noise variance so high we force the filter to favor the prediction over the measurement. This can lead to apparently very smooth and good looking results. In the chart above the track may look extremely good to you since it follows the ideal path very closely. But, the 'great' behavior at the start should give you pause - the filter has not converged yet ($\\mathbf P$ is still large) so it should not be able to be so close to the actual position. We can see that $\\mathbf P$ has not converged because the entire chart is colored with the yellow background denoting the size of $\\mathbf P$. Let's see the result of a bad initial guess for the position by guessing the initial position to be 50 m and the initial velocity to be 1 m/s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run(track=trk, zs=zs, R=10000, Q=.2, P=P, plot_P=False,\n",
    "    x0=np.array([50., 1.]), \n",
    "    title='R=$10,000\\, m^2$, Q=$.2\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can see that the filter cannot acquire the track. This happens because even though the filter is getting reasonably good measurements it assumes that the measurements are bad, and eventually predicts forward from a bad position at each step. If you think that perhaps that bad initial position would give similar results for a smaller measurement noise, let's set it back to the correct value of 225 $m^2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run(track=trk, zs=zs, R=225, Q=.2, P=P, plot_P=False, \n",
    "    x0=np.array([20., 1.]),\n",
    "    title='R=$225\\, m^2$, Q=$.2\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we see that the filter initially struggles for several iterations to acquire the track, but then it accurately tracks our dog. In fact, this is nearly optimum - we have not designed $\\mathbf Q$ optimally, but $\\mathbf R$ is optimal. A rule of thumb for $\\mathbf Q$ is to set it between $\\frac{1}{2}\\Delta a$ to $\\Delta a$, where $\\Delta a$ is the maximum amount that the acceleration will change between sample periods. This only applies for the assumption we are making in this chapter - that acceleration is constant and uncorrelated between each time period. In the Kalman Math chapter we will discuss several different ways of designing $\\mathbf Q$.\n",
    "\n",
    "To some extent you can get similar looking output by varying either ${\\mathbf R}$ or ${\\mathbf Q}$, but I urge you to not 'magically' alter these until you get output that you like. Always think about the physical implications of these assignments, and vary ${\\mathbf R}$ and/or ${\\mathbf Q}$ based on your knowledge of the system you are filtering. Back that up with extensive simulations and/or trial runs of real data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A Detailed Examination of the Covariance Matrix\n",
    "\n",
    "Let's start by revisiting plotting a track. I've hard coded the data and noise in `zs_var_275` to avoid being at the mercy of the random number generator, which might generate data that does not illustrate what I want to talk about. I will start with `P=500`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import kf_book.mkf_internal as mkf_internal\n",
    "\n",
    "var = 27.5\n",
    "data = mkf_internal.zs_var_275()\n",
    "run(track=trk, zs=zs, R=var, Q=.02, P=500., plot_P=True, \n",
    "    title='$P=500\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the output we see a very large spike in the filter output at the beginning. We set $\\text{P}=500\\, \\mathbf{I}_2$ (this is shorthand notation for a 2x2 diagonal matrix with 500 in the diagonal). We now have enough information to understand what this means, and how the Kalman filter treats it. The 500 in the upper left hand corner corresponds to $\\sigma^2_x$; therefore we are saying the standard deviation of `x` is $\\sqrt{500}$, or roughly 22.36 m. Roughly 99% of the samples occur withing $3\\sigma$, therefore $\\sigma^2_x=500$ is telling the Kalman filter that the prediction (the prior) could be up to 67 meters off. That is a large error, so when the measurement spikes the Kalman filter distrusts its own estimate and jumps wildly to try to incorporate the measurement. Then, as the filter evolves $\\mathbf P$ quickly converges to a more realistic value.\n",
    "\n",
    "Let's look at the math behind this. The equation for the Kalman gain is\n",
    "\n",
    "$$\\mathbf K = \\mathbf{\\bar P} \\mathbf H^\\mathsf T\\mathbf{S}^{-1} \\approx \\frac{\\mathbf{\\bar P}\\mathbf H^\\mathsf T}{\\mathbf{S}} \n",
    "\\approx \\frac{\\mathsf{uncertainty}_\\mathsf{prediction}}{\\mathsf{uncertainty}_\\mathsf{measurement}}\\mathbf H^\\mathsf T\n",
    "$$\n",
    "\n",
    "It is a ratio of the uncertainty of the prediction vs measurement. Here the uncertainty in the prediction is large, so $\\mathbf K$ is large (near 1 if this was a scalar). $\\mathbf K$ is multiplied by the residual $\\textbf{y} = \\mathbf z - \\mathbf{H \\bar x}$, which is the measurement minus the prediction, so a large $\\mathbf K$ favors the measurement. Therefore if $\\mathbf P$ is large relative to the sensor uncertainty $\\mathbf R$ the filter will form most of the estimate from the measurement. \n",
    "\n",
    "\n",
    "Now let us see the effect of a smaller initial value of $\\mathbf P = 1.0\\, \\mathbf{I}_2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run(track=trk, zs=zs, R=var, Q=.02, P=1., plot_P=True, \n",
    "    title='$P=1\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This *looks* good at first blush. The plot does not have the spike that the former plot did; the filter starts tracking the measurements and doesn't take any time to settle to the signal. However, if we look at the plots for P you can see that there is an initial spike for the variance in position, and that it never really converges. Poor design leads to a long convergence time, and suboptimal results. \n",
    "\n",
    "So despite the filter tracking very close to the actual signal we cannot conclude that the 'magic' is to use a small $\\mathbf P$. Yes, this will avoid having the Kalman filter take time to accurately track the signal, but if we are truly uncertain about the initial measurements this can cause the filter to generate very bad results. If we are tracking a living object we are probably very uncertain about where it is before we start tracking it. On the other hand, if we are filtering the output of a thermometer, we are as certain about the first measurement as the 1000th. For your Kalman filter to perform well you must set $\\mathbf P$ to a value that truly reflects your knowledge about the data. \n",
    "\n",
    "Let's see the result of a bad initial estimate coupled with a very small $\\mathbf P$. We will set our initial estimate at x = 100 m (whereas the dog actually starts at 0m), but set `P=1` m$^2$. This is clearly an incorrect value for $\\mathbf P$ as the estimate is off by 100 m but we tell the filter that it the $3\\sigma$ error is 3 m."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([100., 0.])\n",
    "run(track=trk, zs=zs, R=var, Q=.02, P=1., x0=x,\n",
    "    plot_P=False, title='$P=1\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the initial estimates are terrible and that it takes the filter a long time to start converging onto the signal . This is because we told the Kalman filter that we strongly believe in our initial estimate of 100 m and were incorrect in that belief.\n",
    "\n",
    "Now, let's provide a more reasonable value for `P` and see the difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([100., 0.])\n",
    "run(track=trk, zs=zs, R=var, Q=.02, P=500., x0=x,\n",
    "   plot_P=False, title='$P=500\\, m^2$');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case the Kalman filter is very uncertain about the initial state, so it converges onto the signal much faster. It is producing good output after only 5 to 6 epochs. With the theory we have developed so far this is about as good as we can do. However, this scenario is a bit artificial; if we do not know where the object is when we start tracking we do not initialize the filter to some arbitrary value, such as 0 m or 100 m. I address this in the **Filter Initialization** section below.\n",
    "\n",
    "Let's do another Kalman filter for our dog, and this time plot the covariance ellipses on the same plot as the position."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kf_book.mkf_internal import plot_track_ellipses\n",
    "\n",
    "def plot_covariances(count, R, Q=0, P=20., title=''):    \n",
    "    track, zs = compute_dog_data(R, Q, count)\n",
    "    f = pos_vel_filter(x=(0., 0.), R=R, Q=Q, P=P)\n",
    "\n",
    "    xs, cov = [], []\n",
    "    for z in zs:\n",
    "        f.predict()\n",
    "        f.update(z)\n",
    "\n",
    "        xs.append(f.x[0])\n",
    "        cov.append(f.P)\n",
    "    plot_track_ellipses(count, zs, xs, cov, title)\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.subplot(121)\n",
    "plot_covariances(R=5, Q=.02, count=20, title='$R = 5\\, m^2$')\n",
    "plt.subplot(122)\n",
    "plot_covariances(R=.5, Q=.02, count=20, title='$R = 0.5\\, m^2$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you are viewing this in Jupyter Notebook or on the web, here is an animation of the filter filtering the data. I've tuned the filter parameters such that it is easy to see a change in $\\mathbf P$ as the filter progresses.\n",
    "<img src='animations/multivariate_track1.gif'>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output on these is a bit messy, but you should be able to see what is happening. In both plots we are drawing the covariance matrix for each point. We start with the covariance $\\mathbf P=(\\begin{smallmatrix}20&0\\\\0&20\\end{smallmatrix})$, which signifies a lot of uncertainty about our initial belief. After we receive the first measurement the Kalman filter updates this belief, and so the variance is no longer as large. In the top plot the first ellipse (the one on the far left) should be a slightly squashed ellipse. As the filter continues processing the measurements the covariance ellipse quickly shifts shape until it settles down to being a long, narrow ellipse tilted in the direction of movement.\n",
    "\n",
    "Think about what this means physically. The x-axis of the ellipse denotes our uncertainty in position, and the y-axis our uncertainty in velocity. So, an ellipse that is taller than it is wide signifies that we are more uncertain about the velocity than the position. Conversely, a wide, narrow ellipse shows high uncertainty in position and low uncertainty in velocity. Finally, the amount of tilt shows the amount of correlation between the two variables. \n",
    "\n",
    "The first plot, with `R=5` $m^2$, finishes up with an ellipse that is wider than it is tall. If that is not clear I have printed out the variances for the last ellipse in the lower right hand corner.\n",
    "\n",
    "In contrast, the second plot, with `R=0.5` $m^2$, has a final ellipse that is taller than wide. The ellipses in the second plot are all much smaller than the ellipses in the first plot. This stands to reason because a small $\\small\\mathbf R$ implies a small amount of noise in our measurements. Small noise means accurate predictions, and thus a strong belief in our position. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question: Explain Ellipse Differences\n",
    "\n",
    "Why are the ellipses for $\\mathbf R=5 m^2$ more tilted towards the horizontal than the ellipses for $\\mathbf R=0.5 m^2$. Hint: think about this in the context of what these ellipses mean physically, not in terms of the math. If you aren't sure about the answer,change $\\mathbf R$ to truly large and small numbers such as 100 $m^2$ and 0.1 $m^2$, observe the changes, and think about what this means. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution\n",
    "\n",
    "The x-axis is for position, and y-axis is velocity. An ellipse that is vertical, or nearly so, says there is no correlation between position and velocity, and an ellipse that is diagonal says that there is a lot of correlation. Phrased that way, the results sound unlikely. The tilt of the ellipse changes, but the correlation shouldn't be changing over time. But this is a measure of the *output of the filter*, not a description of the actual, physical world. When $\\mathbf R$ is very large we are telling the filter that there is a lot of noise in the measurements. In that case the Kalman gain $\\mathbf K$ is set to favor the prediction over the measurement, and the prediction comes from the velocity state variable. Thus there is a large correlation between $x$ and $\\dot x$. Conversely, if $\\mathbf R$ is small, we are telling the filter that the measurement is very trustworthy, and $\\mathbf K$ is set to favor the measurement over the prediction. Why would the filter want to use the prediction if the measurement is nearly perfect? If the filter is not using much from the prediction there will be very little correlation reported. \n",
    "\n",
    "**This is a critical point to understand!**. The Kalman filter is a mathematical model for a real world system. A report of little correlation *does not mean* there is no correlation in the physical system, just that there was no *linear* correlation in the mathematical model. It's a report of how much measurement vs prediction was incorporated into the model.  \n",
    "\n",
    "Let's bring that point home with a truly large measurement error. We will set $\\mathbf R=200\\, m^2$. Think about what the plot will look like before looking at it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_covariances(R=200., Q=.2, count=5, title='$R = 200\\, m^2$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I hope the result was what you were expecting. The ellipse quickly became very wide and not very tall. It did this because the Kalman filter mostly used the prediction vs the measurement to produce the filtered result. We can also see how the filter output is slow to acquire the track. The Kalman filter assumes that the measurements are extremely noisy, and so it is very slow to update its estimate for $\\dot x$. \n",
    "\n",
    "Keep looking at these plots until you grasp how to interpret the covariance matrix $\\mathbf P$. When you work with a $9{\\times}9$ matrix it may seem overwhelming - there are 81 numbers to interpret. Just break it down - the diagonal contains the variance for each state variable, and all off diagonal elements are the product of two variances and a scaling factor $p$. You cannot plot a $9{\\times}9$ matrix on the screen so you have to develop your intuition and understanding in this simple, 2-D case. \n",
    "\n",
    ">When plotting covariance ellipses, make sure to always use ax.set_aspect('equal') or plt.axis('equal') in your code (the former lets you set the xlim and ylim values). If the axis use different scales the ellipses will be drawn distorted. For example, the ellipse may be drawn as being taller than it is wide, but it may actually be wider than tall."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter Initialization\n",
    "\n",
    "\n",
    "There are many schemes for initializing the filter. The following approach performs well in most situations. In this scheme you do not initialize the filter until you get the first measurement, $\\mathbf z_0$. From this you can compute the initial value for $\\mathbf x$ with $\\mathbf x_0 = \\mathbf z_0$. If  $\\mathbf z$ is not of the same size, type, and units as $\\mathbf x$, which is usually the case, we can use our measurement function as follow.\n",
    "\n",
    "We know\n",
    "\n",
    "$$\\mathbf z = \\mathbf{Hx}$$\n",
    "\n",
    "Hence,\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf H^{-1}\\mathbf{Hx} &= \\mathbf H^{-1}\\mathbf z \\\\\n",
    "\\mathbf x &= \\mathbf H^{-1}\\mathbf z\\end{aligned}$$\n",
    "\n",
    "Matrix inversion requires a square matrix, but $\\mathbf H$ is rarely square. SciPy will compute the Moore-Penrose pseudo-inverse of a matrix with `scipy.linalg.pinv`, so your code might look like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3.2]\n",
      " [0. ]]\n"
     ]
    }
   ],
   "source": [
    "from scipy.linalg import pinv\n",
    "\n",
    "H = np.array([[1, 0.]]) \n",
    "z0 = 3.2\n",
    "x = np.dot(pinv(H), z0)\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specialized knowledge of your problem domain may lead you to a different computation, but this is one way to do it. For example, if the state includes velocity you might take the first two measurements of position, compute the difference, and use that as the initial velocity.\n",
    "\n",
    "Now we need to compute a value for $\\mathbf P$. This will vary by problem, but in general you will use the measurement error $\\mathbf R$ for identical terms, and maximum values for the rest of the terms. Maybe that isn't clear. In this chapter we have been tracking and object using position and velocity as the state, and the measurements have been positions. In that case we would initialize $\\mathbf P$ with\n",
    "\n",
    "$$\\mathbf P = \\begin{bmatrix}\\mathbf R_0 & 0 \\\\0 & vel_{max}^2\\end{bmatrix}$$\n",
    "\n",
    "The diagonal of $\\mathbf P$ contains the variance of each state variable, so we populate it with reasonable values. $\\mathbf R_0$ is a reasonable variance for the position, and the maximum velocity squared is a reasonable variance for the velocity. It is squared because variance is squared: $\\sigma^2$.\n",
    "\n",
    "You really need to understand the domain in which you are working and initialize your filter on the best available information. For example, suppose we were trying to track horses in a horse race. The initial measurements might be very bad, and provide you with a position far from the starting gate. We know that the horse must start at the starting gate; initializing the filter to the initial measurement would lead to suboptimal results. In this scenario we would want to always initialize the Kalman filter with the starting gate position of the horse."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Batch Processing\n",
    "\n",
    "The Kalman filter is designed as a recursive algorithm - as new measurements come in we immediately create a new estimate. But it is very common to have a set of data that have been already collected which we want to filter. Kalman filters can be run in a batch mode, where all of the measurements are filtered at once. We have implemented this in `KalmanFilter.batch_filter()`. Internally, all the function does is loop over the measurements and collect the resulting state and covariance estimates in arrays. It simplifies your logic and conveniently gathers all of the outputs into arrays. I often use this function, but waited until the end of the chapter so you would become very familiar with the predict/update cyle that you must run.\n",
    "\n",
    "First collect your measurements into an array or list. Maybe it is in a CSV file:\n",
    "\n",
    "```python\n",
    "zs = read_altitude_from_csv('altitude_data.csv')\n",
    "```\n",
    "\n",
    "Or maybe you will generate it using a generator:\n",
    "\n",
    "```python\n",
    "zs = [some_func(i) for i in range(1000)]\n",
    "```\n",
    "\n",
    "Then call the `batch_filter()` method.\n",
    "\n",
    "```python\n",
    "Xs, Ps, Xs_prior, Ps_prior = kfilter.batch_filter(zs)\n",
    "```\n",
    "\n",
    "The function takes the list of measurements, filters it, and returns an  NumPy array of state estimates (Xs), covariance matrices (Ps), and the priors for the same (Xs_prior, Ps_prior).\n",
    "\n",
    "Here is a complete example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "count = 50\n",
    "track, zs = compute_dog_data(10, .2, count)\n",
    "P = np.diag([500., 49.])\n",
    "f = pos_vel_filter(x=(0., 0.), R=3., Q=.02, P=P)\n",
    "xs, _, _, _ = f.batch_filter(zs)\n",
    "\n",
    "book_plots.plot_measurements(range(1, count + 1), zs)\n",
    "book_plots.plot_filter(range(1, count + 1), xs[:, 0])\n",
    "plt.legend(loc='best');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The batch filter takes an optional `filterpy.common.Saver` object. If provided, all of the filter's attributes will be saved as well. This is useful if you want to inspect values other than the state and covariance. Here I plot the residual to see if it appears like noise centered around 0. This is a quick visual inspection to see if the filter is well designed. If if drifts from zero, or doesn't look like noise, the filter is poorly designed and/or the processes are not Gaussian. We will discuss this in detail in later chapters. For now consider this a demonstration of the `Saver` class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "track, zs = compute_dog_data(10, .2, 200)\n",
    "P = np.diag([500., 49.])\n",
    "f = pos_vel_filter(x=(0., 0.), R=3., Q=.02, P=P)\n",
    "s = Saver(f)\n",
    "xs, _, _, _ = f.batch_filter(zs, saver=s)\n",
    "s.to_array()\n",
    "plt.plot(s.y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Smoothing the Results\n",
    "\n",
    "This book includes a chapter on smoothing the results; I will not repeat the information here. However, it is so easy to use, and offers such a profoundly improved output that I will tease you with a few examples. The smoothing chapter is not especially difficult; you are sufficiently prepared to read it now.\n",
    "\n",
    "Let's assume that we are tracking a car that has been traveling in a straight line. We get a measurement that implies that the car is starting to turn to the left. The Kalman filter moves the state estimate somewhat towards the measurement, but it cannot judge whether this is a particularly noisy measurement or the true start of a turn. \n",
    "\n",
    "However, if we have future measurements we can decide if a turn was made. Suppose the subsequent measurements all continue turning left. We can then be sure that that a turn was initiated. On the other hand, if the subsequent measurements continued on in a straight line we would know that the measurement was noisy and should be mostly ignored. Instead of making an estimate part way between the measurement and prediction the estimate will either fully incorporate the measurement or ignore it, depending on what the future measurements imply about the object's movement.\n",
    "\n",
    "`KalmanFilter` implements a form of this algorithm which is called an *RTS smoother*, named after the inventors of the algorithm: Rauch, Tung, and Striebel. The method is `rts_smoother()`. To use it pass in the means and covariances computed from the `batch_filter` step, and receive back the smoothed means, covariances, and Kalman gain. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy.random import seed\n",
    "count = 50\n",
    "seed(8923)\n",
    "\n",
    "P = np.diag([500., 49.])\n",
    "f = pos_vel_filter(x=(0., 0.), R=3., Q=.02, P=P)\n",
    "track, zs = compute_dog_data(3., .02, count)\n",
    "Xs, Covs, _, _ = f.batch_filter(zs)\n",
    "Ms, Ps, _, _ = f.rts_smoother(Xs, Covs)\n",
    "\n",
    "book_plots.plot_measurements(zs)\n",
    "plt.plot(Xs[:, 0], ls='--', label='Kalman Position')\n",
    "plt.plot(Ms[:, 0], label='RTS Position')\n",
    "plt.legend(loc=4);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This output is fantastic! Two things are very apparent to me in this chart. First, the RTS smoother's output is much smoother than the KF output. Second, it is almost always more accurate than the KF output (we will examine this claim in detail in the **Smoothing** chapter). The improvement in the velocity, which is a hidden variable, is even more dramatic:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Xs[:, 1], ls='--', label='Kalman Velocity')\n",
    "plt.plot(Ms[:, 1], label='RTS Velocity')\n",
    "plt.legend(loc=4)\n",
    "plt.gca().axhline(1, lw=1, c='k');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will explore why this is so in the next exercise."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise: Compare Velocities\n",
    "\n",
    "Since we are plotting velocities let's look at what the 'raw' velocity is, which we can compute by subtracting subsequent measurements. i.e the velocity at time 1 can be approximated by `xs[1] - xs[0]`. Plot the raw value against the values estimated by the Kalman filter and by the RTS filter. Discuss what you see."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
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   ],
   "source": [
    "dx = np.diff(Xs[:, 0], axis=0)\n",
    "plt.scatter(range(1, len(dx) + 1), dx, facecolor='none', \n",
    "            edgecolor='k', lw=2, label='Raw velocity')\n",
    "plt.plot(Xs[:, 1], ls='--', label='Filter')\n",
    "plt.plot(Ms[:, 1], label='RTS')\n",
    "plt.legend(loc=4);"
   ]
  },
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   "source": [
    "We see that the noise swamps the signal, causing the raw values to be essentially worthless. The filter is maintaining a separate estimate for velocity. The Kalman gain $\\mathbf K$ is multidimensional. For example, it might have the value  $\\mathbf K = [0.1274, 0.843]^\\mathsf T$. the first value is used to scale the residual of the position, and the second value will scale the residual of the velocity. The covariance matrix tells the filter how correlated the position and velocity are, and each will be optimally filtered. \n",
    "\n",
    "I show this to reiterate the importance of using Kalman filters to compute velocities, accelerations, and even higher order values. I use a Kalman filter even when my measurements are so accurate that I am willing to use them unfiltered because it allows me accurate estimates for velocities and accelerations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion and Summary\n",
    "\n",
    "Multivariate Gaussians allow us to simultaneously handle multiple dimensions, both spacial and others (velocity, etc). We made a key insight: hidden variables have the ability to significantly increase the accuracy of the filter. This is possible because the hidden variables are correlated with the observed variables. \n",
    "\n",
    "I gave an intuitive definition of *observability*. Observability was invented by Dr. Kalman for linear systems, and there is a fair amount of theory behind it. It answers the question of whether a system state can be determined by observing the system's output. For our problems this has been easy to determine, but more complicated systems may require rigorous analysis. Wikipedia's [Observability](https://en.wikipedia.org/wiki/Observability) article has an overview; if you need to learn the topic [[2]](#References) is a good source. \n",
    "\n",
    "There is one important caveat about hidden variables. It is easy to construct a filter that produces estimates for hidden variables. I could write a filter that estimates the color of a tracked car. But there is no way to compute car color from positions, so the estimate for the color will be nonsense. The designer must verify that these variables are being estimated correctly. If you do not have a velocity sensor and yet are estimating velocity, you will need to test that the velocity estimates are correct.; do not trust that they are. For example, suppose the velocity has a periodic component to it - it looks like a sine wave. If your sample time is less than 2 times the frequency you will not be able to accurately estimate the velocity (due to Nyquist's Theorem). Imagine that the sample period is equal to the frequency of the velocity. The filter will report that the velocity is constant because it samples the system at the same point on the sin wave. \n",
    "\n",
    "Initialization poses a particularly difficult problem for hidden variables. If you start with a bad initialization the filter can usually recover the observed variables, but may struggle and fail with the hidden one. Estimating hidden variables is a powerful tool, but a dangerous one. \n",
    "\n",
    "I established a series of steps for designing a Kalman filter. These are not a usual part of the Kalman filter literature, and are only meant as a guide, not a prescription. Designing for a hard problem is an iterative process. You make a guess at the state vector, work out what your measurement and state models are, run some tests, and then alter the design as necessary. \n",
    "\n",
    "The design of $\\mathbf R$ and $\\mathbf Q$ is often quite challenging. I've made it appear to be quite scientific. Your sensor has Gaussian noise of $\\mathcal{N}(0, \\sigma^2)$, so set $\\mathbf R=\\sigma^2$. Easy! This is a dirty lie. Sensors are not Gaussian. We started the book with a bathroom scale. Suppose $\\sigma=1$ kg, and you try to weigh something that weighs 0.5 kg. Theory tells us we will get negative measurements, but of course the scale will never report weights less than zero. Real world sensors typically have *fat tails* (known as *kurtosis*) and *skew*. In some cases, such as with the scale, one or both tails are truncated.\n",
    "\n",
    "The case with $\\mathbf Q$ is more dire. I hope you were skeptical when I blithely assigned a noise matrix to my prediction about the movements of a dog. Who can say what a dog will do next? The Kalman filter in my GPS doesn't know about hills, the outside winds, or my terrible driving skills. Yet the filter requires a precise number to encapsulate all of that information, and it needs to work while I drive off-road in the desert, and when a Formula One champion drives on a track.\n",
    "\n",
    "These problems led some researchers and engineers to derogatorily call the Kalman filter a 'ball of mud'. In other words, it doesn't always hold together so well. Another term to know - Kalman filters can become *smug*. Their estimates are based solely on what you tell it the noises are. Those values can lead to overly confident estimates. $\\mathbf P$ gets smaller and smaller while the filter is actually becoming more and more inaccurate! In the worst case the filter diverges. We will see a lot of that when we start studying nonlinear filters. \n",
    "\n",
    "The Kalman filter is a mathematical model of the world. The output is only as accurate as that model. To make the math tractable we had to make some assumptions. We assume that the sensors and motion model have Gaussian noise. We assume that everything is linear. If that is true, the Kalman filter is *optimal* in a least squares sense. This means that there is no way to make a better estimate than what the filter gives us. However, these assumption are almost never true, and hence the model is necessarily limited, and a working filter is rarely optimal.\n",
    "\n",
    "In later chapters we will deal with the problem of nonlinearity. For now I want you to understand that designing the matrices of a linear filter is an experimental procedure more than a mathematical one. Use math to establish the initial values, but then you need to experiment. If there is a lot of unaccounted noise in the world (wind, etc.) you may have to make $\\mathbf Q$ larger. If you make it too large the filter fails to respond quickly to changes. In the **Adaptive Filters** chapter you will learn some alternative techniques that allow you to change the filter design in real time in response to the inputs and performance, but for now you need to find one set of values that works for the conditions your filter will encounter. Noise matrices for an acrobatic plane might be different if the pilot is a student than if the pilot is an expert as the dynamics will be quite different."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- <A name=\"[wiki_article]\">[1]</A> 'Kalman Filters'. Wikipedia\n",
    "https://en.wikipedia.org/wiki/Kalman_filter#Details\n",
    "\n",
    "- [2] Grewal, Mohinder S., Andrews, Angus P. *Kalman Filtering: Theory and Practice Using MATLAB*. Third Edition. John Wiley & Sons. 2008."
   ]
  }
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