ME3263-Lab_03.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.fftpack\n",
    "import check_lab03 as p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({'font.size': 22})\n",
    "plt.rcParams['lines.linewidth'] = 3\n",
    "pi=np.pi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ME 3263 Introduction to Sensors and Data Analysis\n",
    "\n",
    "## Lab #3 Measuring Natural Frequencies\n",
    "\n",
    "\n",
    "### What are natural frequencies\n",
    "\n",
    "In free vibration (i.e., no external forcing), structural components\n",
    "oscillate at specified frequencies or combinations of frequencies. Since\n",
    "these vibrations are unforced, the associated frequencies are referred\n",
    "to as natural frequencies; it's how the system vibrates if left to\n",
    "behave on its own. In contrast, driven linear systems vibrate at the\n",
    "driving frequency. An amplification of the response (called resonance)\n",
    "occurs when the driving frequency coincides with one of the natural\n",
    "frequencies. In short, the system is driven at a frequency at which it\n",
    "likes to vibrate. Large amplitude oscillations are the result. So it is\n",
    "important to know what the natural frequencies are *a priori* so you can\n",
    "avoid driving the system into resonance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In lab 2, we used the Euler-Bernoulli beam equation to describe static deflection of a cantilever beam. Here, we will use the Euler-Lagrange dynamic beam equation to account for inertial effects. The Euler-Lagrange beam equation relates bending stiffness and density as such\n",
    "\n",
    "$\\frac{\\partial^2}{\\partial x^2}\\left(EI\\frac{\\partial^2 w}{\\partial\n",
    "x^2}\\right)=-\\mu\\frac{\\partial^2 w}{\\partial^2 t} +q(x)$  (1)\n",
    "\n",
    "where $E$ is the Young's modulus of the beam, $I$ is the second moment of area of the beam's cross-section, $\\mu$ is the mass per unit length of the beam, $q(x)$ is the applied load, and $w=w(x,t)$ is the displacement of the neutral axis that is a function of $x$-distance along beam-and $t$-time. \n",
    "\n",
    "Calculating the natural frequencies ignores the applied load $q(x)$ and if the cross-section is constant, Equation 1 becomes\n",
    "\n",
    "$EI\\frac{\\partial^4 w}{\\partial\n",
    "x^4}=-\\mu\\frac{\\partial^2 w}{\\partial^2 t}$.  (2)\n",
    "\n",
    "The full solution requires evaluation of the partial differential equation. We will use the derived mode shapes and natural frequencies for a cantilever beam [\\[1\\]](https://en.wikipedia.org/wiki/Euler%E2%80%93Bernoulli_beam_theory#Example:_Cantilevered_beam). The solution for $w(x,t)$ is as such\n",
    "\n",
    "$w(x,t)=\\sum_{n=1}^{\\infty}(A_{n}\\cos\\omega_{n}t+B_{n}\\sin\\omega_{n}t)\n",
    "\\left(\\cosh\\beta_n x-\\cos\\beta_n x+\n",
    "\\frac{\\cos\\beta_n L + \\cosh\\beta_n L}{\\sin\\beta_n L+\\sinh\\beta_n L}\n",
    "\\left(\\sin\\beta_n x -\\sinh\\beta_n x\\right)\\right)$   (3)\n",
    "\n",
    "where the formula $\\cosh(\\beta_n L)\\cos(\\beta_n L) +1 =0$ defines the constants $\\beta_n$, $L$ is the length of the beam, and $A_n$ and $B_n$ are constants derived from initial conditions. In the experiment, you will deliver an impulse to the cantilever specimens. An impulse will only require $\\sin(t)$ components, so $A_n$=0 for all n. The beam will vibrate similar to the following video [Beam vibrations](https://photos.app.goo.gl/t5a79MEz7PrM9vhf7). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Measuring natural frequencies\n",
    "\n",
    "In this lab, you will measure the first 3 natural frequencies of a rectangular beam using strain gage data processed with a [fast Fourier transform](https://en.wikipedia.org/wiki/Fast_Fourier_transform). \n",
    "Your goal is \n",
    "to measure the free response time series data using a strain gage. With this data, you will\n",
    "determine the first natural frequency in two ways: (i) by peak counting in the\n",
    "time domain (which gives a very rough estimate of $\\omega_n$); and (ii) by a\n",
    "formal frequency domain analysis (fast Fourier transform or FFT). For the\n",
    "rectangular beam, you have analytical expressions for the natural frequencies\n",
    "and you can confirm that you're doing everything properly by getting the\n",
    "analytical frequencies to agree with the experimental frequencies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measuring vibrational modes has two components, the frequency and the amplitude. The amplitude of vibration can be determined by taking the difference between the maximum and minimum measurements. Measuring the frequency requires more attention. Consider 10 oscillations of a cos-wave of 1-Hz with amplitude of 1 a.u. (aribitrary units). Now, take N measurements over the given timeframe from 0-10 seconds. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'a.u.')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "N=20\n",
    "t_collect=10 # time to collect data\n",
    "t=np.linspace(0,t_collect,1000)\n",
    "y=np.cos(2*pi*t)\n",
    "tsample=np.linspace(0,10,N+1)\n",
    "ysample=np.cos(2*pi*tsample)\n",
    "plt.figure(20)\n",
    "plt.plot(t,y,label='signal')\n",
    "plt.plot(tsample,ysample,'o-',label='measure')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.xlabel('time (s)')\n",
    "plt.ylabel('a.u.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For N=20, it would appear that we can capture a minimal example of our signal (just the peaks occuring at 1 Hz). Collecting data for N=20 over 10 seconds is equivalent to sampling at 20 samples/10 seconds = 2 Hz. This is called the Nyquist rate which is given as such\n",
    "\n",
    "$f_{Nyquist}=2f_{signal}$. (4)\n",
    "\n",
    "In Equation 4, the Nyquist rate (also Shannon Sampling) [\\[2\\]](./jerri_1977-shannon_sampling.pdf)[\\[3\\]](./nyquist.pdf), $f_{Nyquist}$, is the minimum sampling rate necessary to capture the signal at frequency, $f_{signal}$. Try changing N<20 and consider the apparent signal frequencies. \n",
    "\n",
    "If you try N=11 in the Python code below, you will see a phenomenon called \"aliasing\" or the \"wagon-wheel effect\" [\\[3\\]](http://www.onmyphd.com/?p=aliasing). When you look at the measured signal, it appears to have a frequency of 1 cycle/10 seconds = 0.1 Hz. This phenomenon is called the wagon-wheel effect because it is noticeable when recording spinning objects like a wagon wheel [or turbine](https://www.youtube.com/watch?v=vIsS4TP73AU). The wheel spins at a given frequency and the camera records at another frequency. When the ratio of the wheel frequency to camera recording frequency reaches certain values the wheel appears to stop, spin slower, or even backwards. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'a.u.')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "N=11\n",
    "t_collect=10 # time to collect data\n",
    "t=np.linspace(0,t_collect,1000)\n",
    "y=np.cos(2*pi*t)\n",
    "tsample=np.linspace(0,10,N+1)\n",
    "ysample=np.cos(2*pi*tsample)\n",
    "plt.figure(20)\n",
    "plt.plot(t,y,label='signal')\n",
    "plt.plot(tsample,ysample,'o-',label='measure')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.xlabel('time (s)')\n",
    "plt.ylabel('a.u.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Experimentally, we avoid aliasing by sampling above the Nyquist rate from equation 4. This poses a chicken and the egg problem. In order to measure the frequency, we need to  double the measured frequency and measure the frequency. The result is that we cannot trust measured frequencies below half of the sampling frequency. We use a method called the fast Fourier transform to compare amplitudes measured at different frequencies.\n",
    "\n",
    "The fast Fourier transform (FFT) is a numerical implementation of the Fourier transform [\\[4\\]](./cooley_and_tukey-FFT.pdf). A Fourier transform of the function introduced earlier, $\\cos(2\\pi t)$, is two dirac delta functions at 1 Hz and -1 Hz. The FFT, if the sampling is well above the Nyquist rate, will produce two peaks, one at 1 Hz and another at the $f_{sampling} - 1Hz$, where $f_{sampling}$ is the sampling frequency. The signal is produced in the previous example with 1000 data points using `linspace(0,10,1000)`. In the next block of code we can compare different numbers of data points collected and the effect on the FFT results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 5.0)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Y    = 2/1000*np.fft.fft(y)\n",
    "freq = np.linspace(0,1000/t_collect,len(Y))\n",
    "plt.figure()\n",
    "for N in range(20,50,10):\n",
    "    tsample=np.linspace(0,10,N+1)\n",
    "    ysample=np.cos(2*pi*tsample)\n",
    "    Ysample= 2/N*np.fft.fft(ysample)\n",
    "    freqsample = np.linspace(0,N/t_collect,len(Ysample))\n",
    "\n",
    "    plt.plot(freqsample, np.abs(Ysample),'o-',label='N=%i'%N)\n",
    "plt.plot(freq, np.abs(Y) ,label='signal')\n",
    "plt.xlabel('frequency (Hz)')\n",
    "plt.ylabel('Amplitude (a.u.)')\n",
    "plt.title(r'FFT of $\\cos(2\\pi t)$ 10-s collection')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.xlim((0,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the figure plotted above, for N=20, $f_{sampling}=20/10~s=2~Hz$, for N=30, $f_{sampling}=30/10~s=3~Hz$, for N=40, $f_{sampling}=40/10~s=4~Hz$. The Nyquist rate is $2~Hz$. For each sampling rate above the Nyquist rate we see two peaks, $1~Hz$ and $f_{sampling}-1~Hz$. As a rule of thumb, do not trust any peaks you find above $f_{sampling}/2$. The FFT calculation produces the same amplitude in either direction from the point $f_{sampling}/2$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 1\n",
    "\n",
    "Take the Fourier transform of a function $\\sin(2\\pi t)$ recorded for 10 seconds. Plot the results for:\n",
    "\n",
    "a. N=20\n",
    "\n",
    "b. N=30\n",
    "\n",
    "c. N=40\n",
    "\n",
    "*Hint: use the same code from above [click here for answer](https://photos.app.goo.gl/QE2wM6Ur24cCtaiX8)*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 1 - Rectangular beam dynamics\n",
    "\n",
    "Use the physical dimensions of your beam and calculated modulus from Lab #1. Calculate the first\n",
    "three natural frequencies of a cantilever beam using the formula\n",
    "\n",
    "$\\omega_i=\\beta_i^2\\sqrt{\\frac{EI}{\\bar{m}L^4}}$ (5)\n",
    "\n",
    "where the $i^{th}$ natural frequency, $\\omega_i$ is given in\n",
    "rad/s, $\\beta_1=1.875104$, $\\beta_2=4.694091$, $\\beta_3=7.854757$, $\\bar{m}$ is\n",
    "the mass per unit length, $E$ is Young's modulus, and $I$ is the second moment\n",
    "of area of the beam. Ensure that the units of $\\omega_i$ are rad/s e.g. 1/s.\n",
    "\n",
    "As an example, the function `natural_frequency(i,E,I,mbar,L)` returns the $i^{th}$ natural frequency of a cantilever beam given \n",
    "    Youngs modulus, `E`,second moment of area, `I`, mass per unit length, `mbar`=density*(cross-sectional area), and Length, `L`. An example for aluminum is given with a cross-section of $12\\times4$ mm in the cell following the function definition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def natural_frequency(i,E,I,mbar,L):\n",
    "    '''returns the i^th natural frequency of a cantilever beam with \n",
    "    Youngs modulus, E \n",
    "    second moment of area, I\n",
    "    mass per unit length, mbar=density*(cross-sectional area)\n",
    "    Length, L'''\n",
    "    # solutions to cosh(pi*x)*cos(pi*x)+1=0 are saved in beta array below\n",
    "    # first 19 mode shapes are solved\n",
    "    beta=np.array([ 1.87510407,  4.69409113,  7.85475744, 10.99554073,\n",
    "                   14.13716839, 17.27875953, 20.42035225, 23.5619449 ,\n",
    "                   26.70353756, 29.84513021, 32.98672286, 36.12831552,\n",
    "                   39.26990817, 42.41150082, 45.55309348, 48.69468613, \n",
    "                   51.83627878, 54.97787144, 58.11946409])\n",
    "    if i>len(beta):\n",
    "        print('Error: choose a natural frequency less than %i'%(len(beta)))\n",
    "        omega=np.NaN\n",
    "    else:\n",
    "        omega=beta[i-1]**2*np.sqrt(E*I/(mbar*L**4))\n",
    "    return omega\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the 1st natural frequency is 574.665 Hz\n",
      "the 2nd natural frequency is 3601.363 Hz\n",
      "the 3rd natural frequency is 10083.922 Hz\n"
     ]
    }
   ],
   "source": [
    "E=200E9 # 200,000,000 Pa=70 GPa\n",
    "b=4e-3 # width in m\n",
    "h=4e-3 # thickness in m\n",
    "I=b*h**3/12 # second moment of area for rectangular cross-section (m^4)\n",
    "mbar=7500*b*h # 7500 kg/m^3*(cross-section area) -> mbar [kg/m]\n",
    "L=3*25.4e-3 # length in m\n",
    "\n",
    "f1=natural_frequency(1,E,I,mbar,L)\n",
    "f2=natural_frequency(2,E,I,mbar,L)\n",
    "f3=natural_frequency(3,E,I,mbar,L)\n",
    "print('the 1st natural frequency is %1.3f Hz'%(f1/2/np.pi)) \n",
    "print('the 2nd natural frequency is %1.3f Hz'%(f2/2/np.pi)) \n",
    "print('the 3rd natural frequency is %1.3f Hz'%(f3/2/np.pi)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 2\n",
    "\n",
    "What are the first three natural frequencies of a steel beam that is 2 mm x 6 mm x 300 mm (in Hertz)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Whoops, try again\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# your work here\n",
    "\n",
    "p.check_p02(f1/2/pi,f2/2/pi,f3/2/pi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, use the LabView data from the strain gage.  \n",
    "Use a sampling frequency at least twice as large as the highest\n",
    "frequency you're trying to capture (this is the Nyquist limit). You can do this\n",
    "estimation in a trial-and-error fashion as you carry out the analysis that\n",
    "follows.\n",
    "\n",
    "Begin recording data. Make sure that when you apply an impact to your\n",
    "beam that you get a decaying vibration on your LabView time series plot.\n",
    "Measuring the frequency: you'll do this in two ways:\n",
    "\n",
    "1.  Estimate the $1^{st}$ natural frequency from the decaying\n",
    "    oscillation. The time between the peaks is the oscillation period,\n",
    "    relate this to the frequency as \n",
    "\n",
    "    $f=\\frac{1}{T}~Hz$\n",
    "\n",
    "2.  Second, use a frequency domain approach: the\n",
    "    Fast Fourier Transform (FFT).  \n",
    "\n",
    "In the second approach, you need to explore 'windowing' your data. You can change the sampled window by changing the range of time you consider in the FFT. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 1 - Estimate the first natural frequency\n",
    "\n",
    "In this example, we plot the raw strain gage output and look a the decaying first natural frequency. The example steel bar is 3.2-mm thick, 25.5-mm wide, and 16.5\" long. The strain gage data was collected at 700 Hz. First, predict the natural freqencies, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the 1st natural frequency is 15 Hz\n",
      "the 2nd natural frequency is 95 Hz\n",
      "the 3rd natural frequency is 267 Hz\n"
     ]
    }
   ],
   "source": [
    "E=200e9 # 200,000,000 Pa=200 GPa\n",
    "b=25.5e-3\n",
    "h=3.2e-3\n",
    "I=b*h**3/12 # second moment of area for rectangular cross-section (m^4)\n",
    "mbar=7500*b*h # 8000 kg/m^3*(cross-section area) -> mbar [kg/m]\n",
    "L=16.5*25.4e-3 # length in mm\n",
    "\n",
    "f1=natural_frequency(1,E,I,mbar,L)\n",
    "f2=natural_frequency(2,E,I,mbar,L)\n",
    "f3=natural_frequency(3,E,I,mbar,L)\n",
    "print('the 1st natural frequency is %1.0f Hz'%(f1/2/np.pi)) \n",
    "print('the 2nd natural frequency is %1.0f Hz'%(f2/2/np.pi)) \n",
    "print('the 3rd natural frequency is %1.0f Hz'%(f3/2/np.pi)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get interactive graphs, we use the `%matpltlib notebook` tool. Now, we can use zoom, translate, and even get cursor locations in the graphs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we load the data into the notebook and plot the strain gage readings over the course of the experiment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "\n",
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       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
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       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
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       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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ECAgALYH8ggIgPNoaVsZgQULFoRDDjmkez7ZoTdq1KjKzM1ECBAgQIAAAQIECBAgQIAAAQJFC/zsZz975aehr7nmmnDwwQcXPYT+EhUQACda2NSXdfPNN4f999+/e5k33XRTGDNmTOpLtj4CBAgQIECAAAECBAgQIECgwQKykAYXv8WlC4BbBHR5OQIOvXLcjUqAAAECBAgQIECAAAECBAiUIyALKcc9hVEFwClUsYFrcOg1sOiWTIAAAQIECBAgQIAAAQIEGiwgC2lw8VtcugC4RUCXlyPg0CvH3agECBAgQIAAAQIECBAgQIBAOQKykHLcUxhVAJxCFRu4BodeA4tuyQQIECBAgAABAgQIECBAoMECspAGF7/FpQuAWwR0eTkCDr1y3I1KgAABAgQIECBAgAABAgQIlCMgCynHPYVRBcApVLGBa3DoNbDolkyAAAECBAgQIECAAAECBBosIAtpcPFbXLoAuEVAl5cj4NArx92oBAgQIECAAAECBAgQIECAQDkCspBy3FMYVQCcQhUbuAaHXgOLbskECBAgQIAAAQIECBAgQKDBArKQBhe/xaULgFsEdHk5Ag69ctyNSoAAAQIECBAgQIAAAQIECJQjIAspxz2FUQXAKVSxgWtw6DWw6JZMgAABAgQIECBAgAABAgQaLCALaXDxW1y6ALhFQJeXI+DQK8fdqAQIECBAgAABAgQIECBAgEA5ArKQctxTGFUAnEIVG7gGh14Di27JBAgQIECAAAECBAgQIECgwQKykAYXv8WlC4BbBHR5OQIOvXLcjUqAAAECBAgQIECAAAECBAiUIyALKcc9hVEFwClUsYFrcOg1sOiWTIAAAQIECBAgQIAAAQIEGiwgC2lw8VtcugC4RUCXlyPg0CvH3agECBAgQIAAAQIECBAgQIBAOQKykHLcUxhVAJxCFRu4BodeA4tuyQQIECBAgAABAgQIECBAoMECspAGF7/FpQuAWwR0eTkCDr1y3I1KgAABAgQIECBAgAABAgQIlCMgCynHPYVRBcApVLGBa3DoNbDolkyAAAECBAgQIECAAAECBBosIAtpcPFbXLoAuEVAl5cj4NArx92oBAgQIECAAAECBAgQIECAQDkCspBy3FMYVQCcQhUbuAaHXgOLbskECBAgQIAAAQIECBAgQKDBArKQBhe/xaULgFsEdHk5Ag69ctyNSoAAAQIECBAgQIAAAQIECJQjIAspxz2FUQXAKVSxgWtw6DWw6JZMgAABAgQIECBAgAABAgQaLCALaXDxW1y6ALhFQJeXI+DQK8fdqAQIECBAgAABAgQIECBAgEA5ArKQctxTGFUAnEIVG7gGh14Di27JBAgQIECAAAECBAgQIECgwQKykAYXv8WlC4BbBHR5OQIOvXLcjUqAAAECBAgQIECAAAECBAiUIyALKcc9hVEFwClUsYFrcOg1sOiWTIAAAQIECBAgQIAAAQIEGiwgC2lw8VtcugC4RUCXlyPg0CvH3agECBAgQIAAAQIECBAgQIBAOQKykHLcUxhVAJxCFRu4BodeA4tuyQQIECBAgAABAgQIECBAoMECspAGF7/FpQuAWwR0eTkCDr1y3I1KgAABAsULLF++PNzxwJNhwdLHwlPPPhf6b7BOOHjkgLDHkP6hq6ur+AH1SIAAAQIECBAgUEsBWUgty1aJSQuAK1EGk8gr4NDLK6Y9AQIECFRR4JePPB2mzV4SfvHwH14zvVGDNglffOduYcSAflWcujkRIECAAAECBAh0WEAW0mHwhIYTACdUzCYtxaHXpGpbKwECBNIUyMLf486/KTz95xfWuMCN1+sbvjd5/7DjQCFwmrvAqggQIECAAAEC8QKykHgrLVcVEADbEbUUcOjVsmwmTYAAAQJ/Ecge+/DWr9wQ7nrotXf+/jVSdifw5VPHehyE3UOAAAECBAgQaLiALKThG6CF5QuAW8BzaXkCDr3y7I1MgAABAq0L3H7/E+HY82+O7mjOlP3DnttuGt1eQwIECBAgQIAAgfQEZCHp1bRTKxIAd0raOIUKOPQK5dQZAQIECHRY4Jwr7w7nX3dP9KhTJgwPpx+2U3R7DQkQIECAAAECBNITkIWkV9NOrUgA3Clp4xQq4NArlFNnBAgQINBhgRmX3BkuvPXB6FEn7TMknH3MqOj2GhIgQIAAAQIECKQnIAtJr6adWpEAuFPSxilUwKFXKKfOCBAgQKDDAu4A7jC44QgQIECAAAECCQjIQhIoYklLEACXBG/Y1gQceq35uZoAAQIEyhXwDOBy/Y1OgAABAgQIEKijgCykjlWrxpwFwNWog1nkFHDo5QTTnAABAgQqJbB8+fKww8fmhxdeXN7jvHbYcqNw9bRxoaurq8e2GhAgQIAAAQIECKQrIAtJt7btXpkAuN3C+m+LgEOvLaw6JUCAAIEOCWQB8IiPzQ/PC4A7JG4YAgQIECBAgED9BWQh9a9hWSsQAJclb9yWBBx6LfG5mAABAgRKFvAIiJILYHgCBAgQIECAQA0FZCE1LFpFpiwArkghTCOfgEMvn5fWBAgQIFAtAS+Bq1Y9zIYAAQIECBAgUAcBWUgdqlTNOQqAq1kXs+pBwKFnixAgQIBAnQWmz/lpuGjRb6KX8K69B4eZx+4a3V5DAgQIECBAgACB9ARkIenVtFMrEgB3Sto4hQo49Arl1BkBAgQIdFhg2uwlYe7i30aPOnH0oHDu8btHt9eQAAECBAgQIEAgPQFZSHo17dSKBMCdkjZOoQIOvUI5dUaAAAECHRaYNntxmLv4oehRBcDRVBoSIECAAAECBJIVkIUkW9q2L0wA3HZiA7RDwKHXDlV9EiBAgECnBKbPuTNctOjB6OEm7TM4nH2MR0BEg2lIgAABAgQIEEhQQBaSYFE7tCQBcIegDVOsgEOvWE+9ESBAgEBnBWbOXxpmLbw3etDJ44eF6YePjG6vIQECBAgQIECAQHoCspD0atqpFQmAOyVtnEIFHHqFcuqMAAECBDos8J+3LAsfu/Tn0aN+7ug3hvfst210ew0JECBAgAABAgTSE5CFpFfTTq1IANwpaeMUKuDQK5RTZwQIECDQYYH8zwDeOpx7/OgOz9JwBAgQIECAAAECVRKQhVSpGvWaiwC4XvUy278IOPRsBQIECBCos8DhX74+LH346egl7LzVxmHeKQdGt9eQAAECBAgQIEAgPQFZSHo17dSKBMCdkjZOoQIOvUI5dUaAAAECHRbIGwCP3GrjMF8A3OEqGY4AAQIECBAgUC0BWUi16lGn2QiA61Qtc31FwKFnMxAgQIBAnQWmzV4S5i7+bfQSJo4eFM49fvfo9hoSIECAAAECBAikJyALSa+mnVqRALhT0sYpVMChVyinzggQIECgwwK3LXs8HDfrluhRL548Juw1dLPo9hoSIECAAAECBAikJyALSa+mnVqRALhT0sYpVMChVyinzggQIECgwwLLly8PIz42Pzz/4vIeR95hy43C1dPGha6urh7bakCAAAECBAgQIJCugCwk3dq2e2UC4HYL678tAg69trDqlAABAgQ6KDDh89eGZY8/2+OIWfg7YkC/HttpQIAAAQIECBAgkLaALCTt+rZzdQLgdurqu20CDr220eqYAAECBDokcOi514dfPvp0j6Mtm3lkj200IECAAAECBAgQSF9AFpJ+jdu1QgFwu2T121YBh15beXVOgAABAh0QEAB3ANkQBAgQIECAAIGEBGQhCRWzw0sRAHcY3HDFCDj0inHUCwECBAiUJyAALs/eyAQIECBAgACBOgrIQupYtWrMWQBcjTqYRU4Bh15OMM0JECBAoHICh33p+nD3Ix4BUbnCmBABAgQIECBAoKICspCKFqYG0xIA16BIpvhaAYeeXUGAAAECdRdwB3DdK2j+BAgQIECAAIHOCshCOuud0mgC4JSq2aC1OPQaVGxLJUCAQKICAuBEC2tZBAgQIECAAIE2CchC2gTbgG4FwA0ocopLdOilWFVrIkCAQLMEBMDNqrfVEiBAgAABAgRaFZCFtCrY3OsFwM2tfa1X7tCrdflMngABAgRCCAJg24AAAQIECBAgQCCPgCwkj5a2KwsIgO2HWgo49GpZNpMmQIAAgZUEvATOdiBAgAABAgQIEMgjIAvJo6WtANgeqL2AQ6/2JbQAAgQINF5AANz4LQCAAAECBAgQIJBLQBaSi0vjlQTcAWw71FLAoVfLspk0AQIECKwkIAC2HQgQIECAAAECBPIIyELyaGm7soAA2H6opYBDr5ZlM2kCBAgQEADbAwQIECBAgAABAr0UkIX0Es5lQQBsE9RSwKFXy7KZNAECBAgIgO0BAgQIECBAgACBXgrIQnoJ5zIBsD1QTwGHXj3rZtYECBAg8KrAQZ+/Ntz3+LM9klx16riw48B+PbbTgAABAgQIECBAIG0BWUja9W3n6twB3E5dfbdNwKHXNlodEyBAgEAHBJYvXx52+viV4c8vvNTjaKMGbRIunzo2dHV19dhWAwIECBAgQIAAgXQFZCHp1rbdKxMAt1tY/20RcOi1hVWnBAgQINAhgdvvfyIce/7N0aPNmbJ/2HPbTaPba0iAAAECBAgQIJCegCwkvZp2akUC4E5JG6dQAYdeoZw6I0CAAIEOC5xz5d3h/OvuiR51yoTh4fTDdopuryEBAgQIECBAgEB6ArKQ9GraqRUJgDslbZxCBRx6hXLqjAABAgQ6LDDjkjvDhbc+GD3qpH2GhLOPGRXdXkMCBAgQIECAAIH0BGQh6dW0UysSAHdK2jiFCjj0CuXUGQECBAh0WMAdwB0GNxwBAgQIECBAIAEBWUgCRSxpCQLgkuAN25qAQ681P1cTIECAQLkCngFcrr/RCRAgQIAAAQJ1FJCF1LFq1ZizALgadTCLnAIOvZxgmhMgQIBApQSWL18eRn78yvCnF17qcV6jBm0SLp86NnR1dfXYVgMCBAgQIECAAIF0BWQh6da23SsTALdbWP9tEXDotYVVpwQIECDQQYE3feG6cO/vn+lxxKunjQsjBvTrsZ0GBAgQIECAAAECaQvIQtKubztXJwBup66+2ybg0GsbrY4JECBAoEMCR3z5x+EXD/+hx9GWzTyyxzYaECBAgAABAgQIpC8gC0m/xu1aoQC4XbL6bauAQ6+tvDonQIAAgQ4ICIA7gGwIAgQIECBAgEBCArKQhIrZ4aUIgDsMbrhiBBx6xTjqhQABAgTKExAAl2dvZAIECBAgQIBAHQVkIXWsWjXmLACuRh3MIqeAQy8nmOYECBAgUDkBAXDlSmJCBAgQIECAAIFKC8hCKl2eSk9OAFzp8pjcmgQcevYGAQIECNRd4Mh//XH4+UOeAVzHOi5fvjzc8cCTYcHSx8JTzz4X+m+wTjh45ICwx5D+oaurq45LMmcCBAgQIECgBgKykBoUqaJTFABXtDCm9foCDj07hAABAgTqLiAArmcFf/nI0+Gk/7o93PO7Z16zgFGDNglffOduYcSAfvVcnFkTIECAAAEClRaQhVS6PJWenAC40uUxuTUJOPTsDQIECBCou4BHQNSvgln4+7av3hD+/MJLa5z8xuv1Dd+bvH/YcaAQuH4VNmMCBAgQIFBtAVlItetT5dkJgKtcHXNbo4BDz+YgQIAAgboLCIDrVcHssQ8TvnBduP/xZ3uceHYn8OVTx3ocRI9SGhAgQIAAAQJ5BGQhebS0XVlAAGw/1FLAoVfLspk0AQIECKwkIACu13a4/f4nwrHn3xw96TlT9g97brtpdHsNCRAgQIAAAQI9CchCehLy+2sSEADbG7UUcOjVsmwmTYAAAQIrCXgGcL22wzlX3h3Ov+6e6ElPmTA8nH7YTtHtNSRAgEBKAl6WmVI1raVKArKQKlWjXnMRANerXmb7FwGHnq1AgAABAnUXEADXq4IzLrkzXHjrg9GTnrTPkHD2MaOi22tIgACBVASy56WfctHicPcjT79mSV6WmUqVraMsAVlIWfL1H1cAXP8aNnIFDr1Glt2iCRAgkPHNYU8AACAASURBVJTAm794Xbjnd8/0uKarTh3nhWI9KrW/gTuA229sBAIE6i+Qhb9Hn3dj+L/nX1zjYrwss/51toLyBGQh5dnXfWQBcN0r2ND5O/QaWnjLJkCAQCIC2Y/GjvzEleFPz7/U44q8UKxHoo408AzgjjAbhACBGgtk39sOOff68D+P/bHHVfje1iORBgRWKyALsTF6KyAA7q2c60oVcOiVym9wAgQIEGhRQJjYImAJl2fBxnYz5kWNLNiIYtKIAIHEBHxvS6ygllNJAVlIJctSi0kJgGtRJpP8awGHnj1BgAABAnUWOGf+0nD+wnujlzBl/LBw+uEjo9tr2B6BodOv6LHjdfv2Cd//fweEEQP69dhWAwIECKQk4FE5KVXTWqoqIAupamWqPy8BcPVrZIarEXDo2RYECBAgUGeBD16wKCxY+lj0Eg7ZeUD45t/uFd1ew/YIxATA79pncJh5zK7tmYBeCRAgUGEBL8uscHFMLRkBWUgypez4QgTAHSc3YBECDr0iFPVBgAABAmUJTPzajWHxA09FDz96SP8w96Sx0e01bI9ATAB88kHDw0cP3ak9E9ArAQIEKizgDuAKF8fUkhGQhSRTyo4vRADccXIDFiHg0CtCUR8ECBAgUJZA7juARw4I33yfO4DLqteKcQXAZVfA+AQIVFnAM4CrXB1zS0VAFpJKJTu/DgFw582NWICAQ68ARF0QIECgRIHshVp3PPBk92MQnnr2udB/g3XCwSMHhD2G9A9dXV0lzqwzQ8+cvzTMyvEM4Mnjh4XpngHcmeK8zigC4NJLYAIECFRYwMsyK1wcU0tGQBaSTCk7vhABcMfJDViEgEOvCEV9ECBAoByBXz7ydPjI95aEn/32D6+ZwKhBm4QvvnO35F+g5S6pcvZeq6MKgFsVdD0BAqkLxJyTfft0hXmnHJj89/rUa2195QjIQspxT2FUAXAKVWzgGhx6DSy6JRMgkIRAFv6+Y9ZN4Q9/emGN69l4vb7he5P3DzsO7JfEmle3CHdJ1bO0McGGZwDXs7ZmTYBAMQIx5+SBO2wevnvCfsUMqBcCDROQhTSs4AUuVwBcIKauOifg0OuctZEIECBQlEAWer71qzeEu1Zz5+9fj5HdCXz51LFJPw4i5h/JmcvV08a5S6qoTdhiPzE1EwC3iOxyAgRqLRBzTh45aqtw3nv2qPU6TZ5AWQKykLLk6z+uALj+NWzkChx6jSy7RRMgUHMBjz1YtYAx/0jOrrjq1HFJ3w1dp20dUzMBcJ0qaq4ECBQtEHNOCoCLVtdfkwRkIU2qdrFrFQAX66m3Dgk49DoEbRgCBAgUKHDOlXeH86+7J7rHKROGh9MP2ym6fZ0aegREnar16lxjgg0BcD1ra9YECBQjEHNOHjFqYPjae/YsZkC9EGiYgCykYQUvcLkC4AIxddU5AYde56yNRIAAgaIEZlxyZ7jw1geju5u0z5Bw9jGjotvXqaG7oetUrXQD4OyDiDseeDIsWPpYeOrZ50L/DdYJB48cEPYY0j/px6/Uc/eZNYF6CAiA61Ens6yvgCykvrUre+YC4LIrYPxeCTj0esXmIgIECJQq4A7gV/lZlLoVez14TLBRlzuAsxcynnLR4nD3I0+/xiN7BvcX37mbZ0/3eqe4kEBzBWLOSXcAN3d/WHnrArKQ1g2b2oMAuKmVr/m6HXo1L6DpEyDQSAF3vb5adndD1/OPQEywUYcAOAt/jzn/xvDMn19cYyE2Xq9v+N7k/T1/up5b1awJlCYQc056BnBp5TFwAgKykASKWNISBMAlwRu2NQGHXmt+riZAgEAZAtmPm4/7/LXhwSf+r8fht99yw3DNtPHJ/hi6O4B73AKVbBATbFQ9AM7+HB75rzeEXzz8hx6NszuBL586Ntk/hz0CaECAQG6BmHNSAJyb1QUEXhGQhdgMvRUQAPdWznWlCjj0SuU3OAECBHot8G8/vjd85oqlPV6/0bp9w5wp6d59eNuyJ8Jxs27u0WFFgzmTx4Q9h24W3V7D9gjEBBtVD4Ddid+evaFXAgReFog5JwXAdguB3gvIQnpv1/QrBcBN3wE1Xb9Dr6aFM20CBBov8M3r7wmfm3d3lEPKdx/etuzxcNysW6IcskYXTx4T9hIAR3u1q2FMsFH1ANjd5+3aHfolQEAAbA8QaL+ALKT9xqmOIABOtbKJr8uhl3iBLY9ABwWyH4e+44Enw4Klj4Wnnn0u9N9gnXDwyAFhjyH9/dhzwXXIrPc9a0F47OnnonvO7gLec9tNo9vXpaEQri6VWnWeKQTAnj9dz71n1gTqIhBzTroDuC7VNM8qCshCqliVesxJAFyPOpnlXwk49GwJAgSKEMhehPTh/29JuOuh1z4LM7v79Ivv3C2MGNCviKH0EULI+6PnGdqUCcPD6YftlJzf9Dl3hosWPRi9rkn7DA5nH7NrdHsN2yMQE2ycNGF4OK3Ce9aHD+3ZG3olQOBlgZhzctwObwjfOWFfZAQI9EJAFtILNJd0CwiAbYRaCjj0alk2kyZQKYEs/J34tRvDs8+9uMZ5bbxe3/C9yek+h7bTBckbPGXzm7TPkHD2MaM6PdW2jzdt9uIwd/FD0eNMHD0onHv87tHtNWyPQEywUfUAOO8HManehd+eHaJXAgRizsm+fbrCFf94YNhxoA/Z7RgCeQVkIXnFtF8hIAC2F2op4NCrZdlMmkBlBLJHERz6pevDrx79Y49zSvk5tD0uvuAGeX/0PBs+1TuAp81eEuYu/m20sAA4mqqtDWOCjaoHwNn5t92MeVFOO2y5Ubh62jiPw4nS0ogAgTzni79f2S8EeicgC+mdm6vcAWwP1FTAoVfTwpk2gYoIuAOunEL05g7gVO8+nD7np+GiRb+JLsS79h4cZh7rERDRYG1qKABuE6xuCRBIQsDfr5Ioo0VUXEAWUvECVXh67gCucHFMbc0CDj27gwCBVgTyBpGp3oXaimFvrr1t2ePhuFm3RF+6zabrhx+fdlCSdx/ag9HboFINUwiABTSV2lImQyApAd/bkiqnxVRUQBZS0cLUYFoC4BoUyRRfK+DQsysIEGhFIO+jCFJ9Dm0rhr259rZlT4TjZt0cfWnKAbAQLnobVKphCgGwgKZSW8pkCCQl4O9XSZXTYioqIAupaGFqMC0BcA2KZIoCYHuAAIFiBQQgxXrG9pbXPes31UdAeE5i7K6pVrsUAmABTbX2lNkQSEkg7/d5P2GVUvWtpVMCAuBOSac3jgA4vZo2YkUOvUaU2SIJtE3A3Zdto33djvMGT1lnKf/jMCZMzAy+/jd7hkN3GVhO0Yy6ikBMzar+vGYBjU1NgEC7BPz9ql2y+iXwqoAsxG7orYAAuLdyritVwKFXKr/BCdRewN2X5ZQwb/CUzTLVx2/Yg+XswVZHjQmA1+3bJ1w+9YCw48B+rQ7XlusFNG1h1SkBAiEE39tsAwLtF5CFtN841REEwKlWNvF1OfQSL7DlEeiAQEyQs97aLwc5IwZUM8jpAFOhQ+QNnrLBU70DOK9Fqo/CKHSDtbmzVIKNVNbR5nLrngCBXgrE/P0q69pPt/QS2GWNF5CFNH4L9BpAANxrOheWKeDQK1Pf2ATSEIj5B8rJE4aHjx62UxoLrsAq8gRPK6abavCZ927oVIPwCmzL6CmkFNrHnH8ZzNXTxvkALHqHaEiAQJ7v86MGbRIunzo2dHV1gSNAIIeALCQHlqarCAiAbYhaCjj0alk2kyZQKYGYAORTb9slvG//oZWad90nM3zGFeHF5XGrSPkfh9Pn/DRctOg3cRAhhKo/VzZ6ITVuOHP+0jBr4b3RK5g8fliYfvjI6PadbBhz/mXzWTbzyE5Oy1gECNRcIKUPympeCtNPWEAWknBx27w0AXCbgXXfHgGHXntc9UqgSQIxAYgAuPgdscOZ88LzEQnwhuuuFeaeNDbZuw+nzV4S5i7+bTTwxNGDwrnH7x7dXsPiBT54waKwYOlj0R0fMnJA+Ob79opu38mGMeefALiTFTEWgTQEzpm/NJyf44OyKeOHhdMr+kFZGhWxihQFZCEpVrUzaxIAd8bZKAULOPQKBtUdgQYKxAQgAuDiN0ZsAPzVSaPDUbttXfwEKtLjtNmLw9zFD0XPRgAcTdW2hhO/dmNY/MBT0f2PHtK/+0OMKn7FnH8C4CpWzpwIVFsg9wdlOw8I3/zban5QVm1ps2uygCykydVvbe0C4Nb8XF2SgEOvJHjDEkhIICYAEQAXX/Dtz5gXXnip52dAfH/qAWHUNpsUP4GK9Dh9zp3hokUPRs9m0t6Dw9nH7hrdXsPiBVIKNmLOPwFw8XtIjwRSF0jpg7LUa2V99RWQhdS3dmXPXABcdgWM3ysBh16v2FxEgMBKAjEBiAC4+C0T+wxgdwCvau8O4OL3Yt4eU/rR5pjzTwCcd4doT4BA7g/KKvyoHNUkUFUBWUhVK1P9eQmAq18jM1yNgEPPtiBAoFWBmABEANyq8qrX53k7+PZbbBSu+dC4ZN8OfupFi8OlS+IfAXH07luHL71rdLEF0VsugZRebhRz/gmAc20PjQkQCCGk9LJMBSVQVQFZSFUrU/15CYCrXyMzFADbAwQItEEgJgARABcLn1KA1qrMCd++Nfzw7t9Fd3PwTluGb71/7+j2GhYvkOcDjFGDNgmXTx1b2Q8wYs6/TPCqU8eFHQf2Kx5TjwQIJCng+3ySZbWoigkIgCtWkBpNRwBco2KZ6qsCDj27gQCBVgViAhABcKvKq15/zpV3h/Ovuye60ykThofTD9spun2dGnpOYp2q9epcY86NrPXV08aFEQOqGZymFGTXcxeZNYF0BZwv6dbWyqojIAupTi3qNhMBcN0qZr7dAg49G4EAgVYFYoIcAXCryqteP+OSO8OFt+Z48dk+Q8LZx4wqdhIV6S3vcxLHDNs8XPgP+1Vk9s2dRsy5keksm3lkZZHcoVfZ0pgYgSQEYs7Jvn26wrxTDqzsB2VJFMIikhWQhSRb2rYvTADcIvGiRYvCrbfeGrL///nPfx5+97vfhd///vfh+eefD/379w8jR44Mb3rTm8L73//+MGTIkKjRHn744TBr1qzw/e9/Pyxbtiz86U9/CgMHDgwHHnhg+MAHPhDGjx8f1c+KRpdddln47ne/2z3HRx99NGy88cZh+PDhYeLEieHEE08Mm2wS/5b1oueWayErNXbo9VbOdQQIrBCI+QeKALjY/eIO4Fc9875QbNMN1g53fPyQyj5SoNidUt3eYs6NqgfA/hxWd3+ZGYEUBGLOyQN32Dx89wQfaqZQb2vovIAspPPmqYwoAG6xkhtttFF45plneuxl3XXXDZ/85CfDjBkzXrft3Llzu0Pep556ao3t/v7v/z6cf/75Ya211nrdvp5++unw7ne/O/zgBz9YY7ttttkmzJ49O+y///49rqHIufU4WA8NHHqtCrqeAIGYf6B8+u27hL8dMxRWQQLuPHwV8rZlj4fjZt2SS3bO5DFhz6Gb5bpG42IFYs6NbMQqPzvXnfjF7gm9ESCwqkDMOXnkqK3Cee/ZAx0BAr0QkIX0As0l3QIC4BY3QhYAb7jhhmGfffYJu+yyS/edutn/sucfZXfvXnHFFeHGG298ZZRPfepT4ROf+MRqR12wYEE44ogjuu8ezr6OPPLI8La3va27/zvuuCN861vfCn/4wx+6fy8Lgb/xjW+scfYvvPBCd1/XXHNNd5sBAwZ0X7PzzjuHJ554Ilx44YWvzCu7U/mGG27onv+avoqcW4vk3Zc79IpQ1AeBZgvE/ANFAFzsHsnzbMDtt9gwXPOh8cne8XrbsifCcbNuzgU8cfSgcO7xu+e6RuPiBPLs3yq/BM4dwMXtCT0RIPBagZi/XwmA7RwCvReQhfTerulXCoBb3AF33XVXd3Da1dW1xp6+853vdD8CIvuHQ9++fcP9998ftt5661XaZ4952HHHHcMDDzzQ/etf+cpXwtSpU1dp86tf/ar78Q+PPPJI969fffXV4ZBDDlntuNkdwieddFL372Wh749+9KPuEHjlr4985CPhi1/8YvcvjR07tjsEXt1X0XNrkbz7codeEYr6INBsgZh/oAiAi98j259xRXjhpZ77/eqk0eGo3Vb9XtnzVfVpkTeE6/5+vlW/MO+UcfVZZGIzTeUO9lTWkdj2shwCyQjE/P1KAJxMuS2kBAFZSAnoiQwpAO5QIbM7ebNn+mZf//Zv/9b9mIeVv84777xXAt+3vvWt4fLLL1/tzC655JJw7LHHdv/efvvt1x2E/vXXiy++GLJHO6wIim+//fawxx6v/RGbrN1ee+0VlixZ0t3FlVdeGQ499NDX9Ffk3IridugVJakfAs0ViPkHigC4+P2xw5nzwvMvLu+x48unjg27btO/x3Z1bTB9zp3hokXxL8TL1jl08w3CdR89qK5Lrv2884b2UyYMD6cftlPl1p3KncyVgzUhAgS6BWL+fjVuhzeE75ywLzECBHohIAvpBZpLugUEwB3aCNmzf2fOnNk92llnnfWaZwGPGzcu/PjHP+7+/WuvvTZMmDBhtTN76aWXul/glj1eIvu67777wtChqz6fMrvb981vfnP372d3DF933XVrXOV//Md/vBJGv+997wvf/va3X9O2yLkVxe3QK0pSPwSaKxDzDxQBcPH7Y8SZ88NzL/Z8C3DqAfC02YvD3MUP5QLefosNwoIPC4BzoRXYOKVn58acfxnd1dPGhRED+hWoqCsCBFIXiDlf+vbpClf844Fhx4HOl9T3g/UVLyALKd60KT0KgDtU6Xe84x3h4osv7h7t3//938Pf/d3fvTJy9rK27Dm8Wbjbr1+/8OSTT77uC96mTJkSZs2a1X391772tZD998pfp512Wvj85z/f/UvnnHNOyP57TV+PPvpo9zOLs68tt9wyZP+98lfRcyuK26FXlKR+CDRXIOYfKALg4veHAPhl02mzl4S5i3+bC3inARuFK6eNz3WNxsUJpHIHcCYSc/5l7ZbNPLI4QD0RIJC8gJ8wSL7EFlgBAVlIBYpQ0ykIgDtQuEsvvbT7sQ1ZwLv++ut3372bha0rvn7yk590P84h+8rutl24cOHrzioLkE844YTuNtlzfrNHNKz8dfjhh3c/ziH7yu4GPuig179baMiQIeHBB1/+MdTHHnssbLHFFm2bW1HcDr2iJPVDoLkCMQGIALj4/SEAftl0+pyfhosW/SYX8IB+64afnHlwrms0Lk4gpWfnxpx/mZwAuLj9oycCTRBI6ZxsQr2ssZ4CspB61q0KsxYAF1iF66+/PjzxxBPdPT733HPdoepVV10Vrrnmmu5fW3vttbvv/n3ve9+7yqjZS+Kyxy9kX2t6DMPKF2SPiHjTm97U/UvZox4WLFiwSn/Dhg3rfjRE9rW6R0T89ZKzx0Rkc8++ssdQHHDAAa80KXpuRXE79IqS1A+B5grEBCAC4OL3h2cAv2x6zvyl4fyF9+YCHtR//XDj9Je///vqvEBKd7bFnH+ZsAC48/vMiATqLJDST0rUuQ7mnraALCTt+rZzdQLgAnWzu3izu3n/+qurq6v7LtxPf/rTYezYsa/5/X/9138Np5xySvevf/jDHw5f+MIXXndWd955Z9htt9262+y5557htttuW6X9Zptt1v0Yiewre4TDRhtt9Lr9HXPMMWHu3LndbbIX1R111FGvtC96bjHcq3ux3V9f97Of/SyceOKJ3b980003hTFjxsR0rQ0BAgReEYgJQATAxW8YAfDLpv/1k/vDmXPvygU8enD/MPfk1/49IlcnGrckEHNuZANU/dm5sesQALe0XVxMoHECKT0rvXHFs+DaCAiAa1Oqyk1UAFxgSdYUAA8ePLg7rHz/+98fBg0a9JoRs5fCnXnmmd2/nv3/Zz/72ded1a9//eswYsSI7jbZ///yl79cpf0666wTnn/++e5fy/6/b9++r9vfe97znvDf//3f3W2y/580adIr7YueWwx3Fpjn+RIA59HSlgCBFQIxAYgAuPj9MnzGFeHF5T33+9VJo8NRu23dc8Oatpg5f2mYlfMO4LMmjgrv3ndITVecxrRjzo1spVUPTlNZRxq7yioIpCPgDuB0amkl1RUQAFe3NlWfmQC4TRV65plnQhbUXnbZZeGLX/xi95242Z25WcB66KGHrjLqyiHrxz72sfCZz3zmdWdVVgBcxNxiuAXAMUraECDQqkBMACIAblV51evz/Aj99ltsGK750PiQ93tCsTNuX29575LKZnLP5w573ZfEtm+2el4hEHNupBQAX3XquLDjwH42AAECBKIEPAM4ikkjAi0JCIBb4mv0xQLgDpT/nnvuCQceeGB4+OGHQ3Z37q233vrKIxyy4Yt+zIJHQHSgqIYgQKD2AjFBjgC42DL7h+GrnnnvksqunDNl/7DntpsWWxS95RKIOTeqHgDn+SBm1KBNwuVTxyb7QUyu4mtMgECPAs6XHok0INCygAC4ZcLGdiAA7lDpL7jggu5HQGRf73znO8Ps2bNfGbnoF615CVyHimoYAgRqLRAT5AiAiy1x3tBzyoTh4fTDdip2EhXpLW8Ynk07ZY+KlKXHacScG1UPgPPuPR889LgtNCBAYCWBmHOyb5+uMO+UA8OIAX7CwOYhkFdAAJxXTPsVAgLgDu2F3//+92GLLbboHm3LLbcMjz766CsjZy+Oy54fnH2NGzcuLFy48HVn9e///u/hhBNO6G5z0kknhfPOO2+V9ocffni48soru3/tRz/6UfcL6F7va8iQIeHBBx/sbvLYY4+9Ms/sv4ueW1HcDr2iJPVDoLkCMf9AEQAXuz/yPvZg0j5DwtnHjCp2EhXp7aWXXgrDzpifazbv2ntwmHnsrrmu0bhYgZhzIxuxys8A9kFMsXtCbwQIrCoQc04esP3m4T8/+PK/f30RIJBPQBaSz0vrVwUEwB3aDX/+85/Deuut1z1a9hiI7L9XfGXPB+7fv3/I/jHYr1+/8OSTT77uM/6mTJkSZs2a1X351772tZD998pfp512Wvj85z/f/UvnnHNOyP57TV9ZED1w4MDu3/7rYDr7taLnVhS3Q68oSf0QaK5AzD9QBMDF7g/B06uety17PBw365ZcwBNHDwrnHr97rms0LlYg5tzIRqxyAOyDmGL3hN4IEFhVIOacFADbNQR6LyAL6b1d068UAHdoB9x1111h1KiX72IaNGhQ+M1vfrPKyNmdvz/+8Y+7f+26664L48ePX+3MspB4++23D/fdd1/372f/P3To0FXaZnf9vvnNb+7+tQkTJoRrr712jav8j//4j/CBD3yg+/ezR1Rk//3XX0XOrShuh15Rkvoh0FyBmH+gCICL3R9+9PxVz2mzl4S5i3+bC1gAnIurLY1jzo1s4CoHwD6IacvW0CkBAn8RiDkns0dAXPGPB3rJpF1DoBcCspBeoLmkW0AA3KGNMHXq1Fce1fDXzwDOppDdyXvyySd3z+atb31ruPzyy1c7s0suuSQce+yx3b+XPTYi+8P/118vvvhi2GabbcIjjzzS/Vu333572GOPPVbbbq+99gpLlizp/r3ssRGHHnroa9oVObeiuB16RUnqh0BzBWL+gfKZt+8S/mbMqh+yNVes9ZXneTnM9ltsFK750LhkXz51+JevD0sffjoX6qR9Boezj/EIiFxoBTeOOTeyIascAPsgpuBNoTsCBF4RyPN93ksmbRwCvROQhfTOzVUC4Jb2QPYYhh133LH7Ltuurq7V9pWFsdnjGM4444yQfUPMvlZ3h++f/vSn7r4eeOCB7jZf/epXXwmEV3T861//uvsZwSuC3WuuuSYcfPDBqx33/PPP734+cPa1yy67dD8LOHvEw8pfH/3oR8MXvvCF7l8aO3ZsuOGGG1bbV9Fzawn9Lxc79IpQ1AeBZgvEBDlTDxoePnJomi8hK6v6w2dcEV58+dvh6359ddLocNRuW/fUrLa/35sA2Evgyi93zLmRzbLKAbCApvx9ZAYEUhXwAVOqlbWuKgnIQqpUjXrNxR3ALdQre2TCBRdcEAYPHhwOOeSQ7kc8ZCFr9ozfp556KmSPfbjsssvCsmXLXhllxowZ4ayzzlrtqAsWLAhHHHFEeP7557t//6ijjgpve9vbwoYbbhjuuOOO8K1vfSv87//+b/fv/f3f/334xje+scbZv/DCC919ZSFx9pU95ze7Zueddw5PPPFEuPDCC18JfDfZZJNw4403dgfFa/oqcm4tkL9yqUOvCEV9EGi2QEyQs97afcJlJx/gRxQL3CrbnzEvvPBSzwnw5VPHhl236V/gyNXqatrsxWHu4odyTWrOlP3DnttumusajYsViDk3shGrHABn84tdx9XTxoURA/oVi6g3AgSSFfCImWRLa2EVEpCFVKgYNZuKALiFgq0IgGO6yELWs88++zUvbPvra+fOndv9TN4sQF7TVxbkZnf4rrXWWq87dPYCt3e/+93hBz/4wRrbZY+KmD17dth///17XEaRc+txsB4aOPRaFXQ9gWYLuAOuvPoLgF+2v23ZE+G4Wa99jNOaKjN8iw3Dgg+NT/aRGOXtyHwjxwanqQTAVV9HvuppTYBAuwW8ZLLdwvonELofA7oiv7npppvCmDFjsBCIEhAARzGtvtEf//jH7jtnFy5cGG655Zbw0EMPhcceeyxkwWt21+6AAQPCrrvu2v1c3Xe84x0hC4Fjvh5++OHugPf73/9+993D2SMYttpqq3DAAQeEE044YY0viFtT39ldyN/5znfCokWLuufXr1+/MHz48HDMMceEE088MXpeWf9Fzy3GY3VtHHq9lXMdAQKZgB9RLG8fCIBfts/zIUTWftZ79wiHvXGr8gpn5G6BpgXAV506zk9A2PsECEQLuAM4mkpDAr0WkIX0mq7xFwqAG78F6gng0Ktn3cyaQFUE/AOlvEoIgF+1jw0Tsyu8LKe8PbvyPY5H/QAAIABJREFUyLE1q/Kds3k+fLDvqrHvzIJAXQR8wF6XSplnnQVkIXWuXrlzFwCX62/0Xgo49HoJ5zICBLoF/IhieRshNgBO/SVwWQViw8QV1fIM4PL27YqRY2tW5QBYQFP+PjIDAqkK+IAp1cpaV5UEZCFVqka95iIArle9zPYvAg49W4EAgVYE3AHcil5r1w6fcUV4sed3wIX1+vYJl01N+wV8sWHiCvEpE4aH0w/bqbUCuLolgdiaVTkAdv61tAVcTIBADwIx5+RaXSHMP9VLJm0mAr0RkIX0Rs01mYAA2D6opYBDr5ZlM2kClRFwB1w5pchzZ1A2wx223ChcPW1csi8+i/lH8sqVmrTPkHD2MaPKKZ5RuwVia1blANhPQNjMBAi0UyDmnFyrT1eY948HesZ4Owuh72QFZCHJlrbtCxMAt53YAO0QcOi1Q1WfBJojkCeI9AzM4vbFbcseD8fNuiVXh3Mmjwl7Dt0s1zV1aRzzj+SV1+IO4PIrG1uzKgfA7gAufx+ZAYFUBfz9KtXKWleVBGQhVapGveYiAK5Xvcz2LwIOPVuBAIFWBWKCnPXW7hMun3pAGDGgX6vDuT6EMO2ixWHukodyWUwcPSice/zuua6pS+OYPbjyWjwDuPzKxtbsqlPHVfbOttuWPRGOm3VzNGbKH8JEI2hIgECUgJ+wimLSiEBLArKQlvgafbEAuNHlr+/iHXr1rZ2ZE6iKQEyQM/VN24ePvGXHqky59vOY8Plrw7LHn821jp232jjMO+XAXNfUpXHMHlyxFneil1/VVO5sy3sn/sWTx4S9Er0Lv/xdZQYE0hLwEwZp1dNqqikgC6lmXeowKwFwHapkjq8RcOjZFAQItCoQE7595ug3hr/Zb9tWh3L9XwT2/Mw14fFnnsvlMXKrjcN8AXD45FE7h787YLtcdhoXK5DKnW0CmmL3hd4IEHhVwDPG7QYC7ReQhbTfONURBMCpVjbxdTn0Ei+w5RHogIAAuAPIfzVEb+4A9giIlxHXX3ut8PNPvSX06dOn84UzYrfAzPlLw6yF90ZrTB4/LEw/fGR0+041FNB0Sto4BJon4AOm5tXcijsvIAvpvHkqIwqAU6lkw9bh0GtYwS2XQBsEBMBtQO2hy1MvWhwuzfkM4JR//DxmD65MetbEUeHd+w7pfOGM2C3wwQsWhQVLH4vWOGTkgPDN9+0V3b5TDQU0nZI2DoHmCaTykxLNq5wV10lAFlKnalVrrgLgatXDbCIFHHqRUJoRILBGgZjwzSMgit1AeZ89us2m64cfn3ZQ6OrqKnYiFektZg+uPNXdB28SLj35gIrMvnnTmHjejWHxg09FL3z04P5h7sljo9t3qqGAplPSxiHQPIFUnpXevMpZcZ0EZCF1qla15ioArlY9zCZSwKEXCaUZAQItBcCfPfqN4b2eAVzYLnrppZfCsDPmR/d35SkHhJ222iS6fd0a5g2At95kvXDTjDfXbZnJzPe4WTeF25Y9Gb2evYduFr43eUx0+041zBPQ7LDlRuHqaeOS/RCmU+bGIdAkgZjvbX37dHW/4HXEgH5NorFWAoUIyEIKYWxkJwLgRpa9/ot26NW/hlZAoGyBmH+g/L83bR8+/JYdy55qMuO78/DVUuYJ4VZctekGa4fFn3hLMvuhbgtJ5Q7gPHtPAFy3XWq+BMoXiPn71QHbbx7+84P7lT9ZMyBQQwFZSA2LVpEpC4ArUgjTyCfg0MvnpTUBAq8ViPkHynpr9wmXnXxA2HGgO1SK2EOePfqq4m3LngjHzbo5F+vmG64Tbv/4Ibmu0bg4gVSeAeyDmOL2hJ4IEOjd368EwHYOgd4LyEJ6b9f0KwXATd8BNV2/Q6+mhTNtAhURyHMH3KhBm4TLp471I9AF1G7GJXeGC299MLqnSfsMCWcfMyq6fZ0aTpu9OMxd/FCuKW+8Xt9w5z8dmusajYsTmDl/aZi18N7oDiePHxamHz4yun2nGvogplPSxiHQTIGYD9izR0Bc8Y8H+oC9mVvEqlsUkIW0CNjgywXADS5+nZfu0Ktz9cydQPkC7oArpwaCp1fdD//y9WHpw0/nKsSG66wVfv7pw3Jdo3FxAqmcGz6IKW5P6IkAgVUFfMBuRxBov4AspP3GqY4gAE61somvy6GXeIEtj0CbBQSRbQZeQ/epBGhF6B3+pevD0kfyBcD91lsr/OyfBMBF+Pemj1SCDedfb6rvGgIEYgR8n49R0oZAawKykNb8mny1ALjJ1a/x2h16NS6eqROogMD0OXeGixbleRTB4HD2MbtWYOb1nkKeAG37LTYM13xofLKP3vjbf/tJuP7Xv89V0G03Wz8sPO1Nua7RuFiBmB9tzka8etq4yr7dXkBT7J7QGwECrwr4gMluINB+AVlI+41THUEAnGplE1+XQy/xAlsegTYL5H3+6sTRg8K5x+/e5lk1o/vhM64ILy7vea1fnTQ6HLXb1j03rGmLUy68I1z204dzzX7ciDeE73xg31zXaFysQGwAvGzmkcUOXGBveT6I8Qz0AuF1RaABAh4x04AiW2LpArKQ0ktQ2wkIgGtbumZP3KHX7PpbPYFWBabNXhLmLv5tdDcC4GiqHhsOP2NeePGlnhPg7MV7u27Tv8f+6trgg9++NSy4+3e5pn/0bluFL03aI9c1GhcrkEIAnInErqPKdzIXW1m9ESBQhMA585eG83O8LHPK+GHh9Aq+LLMIC30QaJeALKRdsun3KwBOv8ZJrtChl2RZLYpAxwROv3hJmH1bfAB8/F7bhHOO261j80t5oGEzrggR+W9IPQCe+LUbw+IHnspV6oNHbhm+9b69c12jcbECscFple8AzhMAX3XquLDjwH7FIuqNAIFkBf7rJ/eHM+feFb2+syaOCu/ed0h0ew0JEAhBFmIX9FZAANxbOdeVKuDQK5Xf4ARqL3DqRYvDpUseil7H0btvHb70rtHR7TVcs0BsAHzZyWPDboMTvgP4gkVhwdLHcm2V0UP6h7knjc11jcbFCqQQAHsERLF7Qm8ECLwqMHP+0jArxx3Ak8cPC9PdAWwLEcglIAvJxaXxSgICYNuhlgIOvVqWzaQJVEYg7wu4PHu1uNIJgF+2zPtjstk1h4wcEL75vr2KK4aecgukEAB7CVzusruAAIFIAc8AjoTSjEALArKQFvAafqkAuOEboK7Ld+jVtXLmTaAaAod/6fqw9JGnoyczcqt+Yf4p46Lba7hmAc8AftkmbwiXXeNOqfL/ZKUQAJ9z5d3h/OvuicacMmF4OP2wnaLba0iAQHMF3AHc3NpbeecEZCGds05tJAFwahVtyHoceg0ptGUSaJPA4V++Pix9OD4A3nmrjcO8Uw5s02ya1a0A+OV65/kx/BU7ZM6U/cOe227arA1TsdWmEAC7Q69im8p0CCQk4BnACRXTUiorIAupbGkqPzEBcOVLZIKrE3Do2RcECLQiMG324jB3cfwzgCeOHhTOPX73VoZ07V8EBMCvboXYMDG7YoctNwpXTxsXurq67KUSBWJrVuWXwLkDuMQNZGgCiQvkfbzRlPHDwumeAZz4rrC8ogVkIUWLNqc/AXBzap3USh16SZXTYgh0XGDRfY+Hd3z9luhxL568X9hr6ObR7TVcs4AA+GWbvHcAC4Cr8acqhQA47+NH3Hlejb1nFgTqIDB9zp3hokUPRk910j6Dw9nH7BrdXkMCBEKQhdgFvRUQAPdWznWlCjj0SuU3OIHaC9y27PFw3Kw8AfCYsNfQzWq/7iosQAD8chXyhnDZNYK48ndwbAB81anjwo4D+5U/4dXMIM+HD6MGbRIunzrWneeVrKRJEaiegJ+wql5NzCg9AVlIejXt1IoEwJ2SNk6hAg69Qjl1RqBxAjPn/SLMuv6+6HVPHrddmH7EztHtNVyzgAD4ZZu8L8rJrvEyrnL/ZKUUnMYG2dljR0YMqGaQXe5uMDoBAqsTmDZ7SZi7+LfROB6xFU2lIYFXBGQhNkNvBQTAvZVzXakCDr1S+Q1OoPYCx51/U7jt/iej17H30E3D9ybvH91eQwFwT3vggxcsCguWPtZTs1V+f9I+Q8LZx4zKdY3GxQnkvWu7yndsxwbAVb6TubjK6okAgaIEps/5abho0W+iu3vX3oPDzGM9AiIaTEMCwSMgbILeCwiAe2/nyhIFBMAl4huaQAIC+561IDz6hz9Hr2TAxuuGn5xxcHR7DQXAPe2Bo8+7ISx58H97arbK77sDOBdX4Y1TeXlaSncyF15kHRIg0JJAKudkSwguJtBmAVlIm4ET7l4AnHBxU16aQy/l6lobgfYLjJ35w/Dbp/4UPdCg/uuHG6e/Kbq9hgLgnvZA3rvQs/6qfEdpT+tN4fdnXHJnuPDWPC83quYd2yndyZzCvrIGAikJ3LbsiXDcrJujlzRn8piwp3csRHtpSCATkIXYB70VEAD3Vs51pQo49ErlNziB2gtMPO/GsPjBp6LXMXpw/zD35LHR7TVcs8D2Z8wLL7y0vEei7MVTu27Tv8d2dW2Qdw+uv/Za4RefPtTLuEoseCp3tqWyjhK3gqEJEFiDwKL7fh/e8fWfRPt878T9wt7bbR7dXkMCBATA9kDvBQTAvbdzZYkCAuAS8Q1NIAGB/7z5vvCxy34RvZLPvn2X8N4xQ6Pba7hmgWEzrggR+W/4yqTdw1t3G5QsZd5nAI8Ztnm48B/2S9ajDgtL5c7ZVO5krsOeMUcCTRM49aLF4dIlD0Uv++jdtw5fetfo6PYaEiAgALYHei8gAO69nStLFBAAl4hvaAIJCHz35mXh45f9PHoln3v7LuE9AuBorzU1zPPs0cGbrR+u/+hByd7xes78peH8hfdGm75zr23CPx+3W3R7DYsXyLN/Rw3aJGR3sXd1dRU/kRZ7dAdwi4AuJ0BgjQLjzvlheODJ+Edsbbvp+mHh6R6xZUsRyCMgC8mjpe3KAgJg+6GWAg69WpbNpAlURiDvC7h2H7xJuPTkAyoz/7pOxLMBX61c3rtJh2+xYVjwofGVDBTruh97M++h06+Iuuzrf7NnOHSXgVFtO90o797z7OlOV8h4BOorsPMn5odnn3spegEbrNMn/OLTh0e315AAAXcA2wO9FxAA997OlSUKCIBLxDc0gQQEvASunCJOm704zF0c/6OhE0dvHc49Ps0fDc1zN+mKagniytm3K0bNU7Mq3wGcyjrK3Q1GJ0BgdQI7nDEvPB/znKe/XLx2n67w67OOgEmAQA4BWUgOLE1XERAA2xC1FHDo1bJsJk2gMgL7nrUgPPqHP0fPZ8DG64afnHFwdHsNVy8w4fPXhmWPPxvNM3TzDcJ1Hz0oun3dGsbeTbpiXVMmDA+nH7ZT3ZaZzHxTunM2du9dPW1cGDGgXzI1tBACBNorsP2MK8ILPb/n9ZVJ9O0K4X/OPrK9k9I7gcQEZCGJFbSDyxEAdxDbUMUJOPSKs9QTgSYKHDfrpnDbsiejl7730M3C9yaPiW6v4eoF9vjM1eGJZ56P5tlsw3XCHR8/JLp93RrGhnAr1jVpnyHh7GNG1W2Zycw3pWfnxu69ZTMFM8lsYAsh0AGBHT82L/w5RwK8Xt8+4e7PegREB0pjiIQEZCEJFbPDSxEAdxjccMUIOPSKcdQLgaYKnD3vF+Hr198XvfwTx20XZhyxc3R7DVcvkPfO64EbrxtuSfTO6zw/hr9C0x3A5f7JmnHJneHCWx+MnkSVA3sBcHQZNSRAIIfAqH+6Kjz9pxeir+i3Xt/ws386NLq9hgQIeAawPdB7AQFw7+1cWaKAALhEfEMTSEDgv35yfzhz7l3RKzlr4qjw7n2HRLfXcPUCh/zLdeHXjz0TzbPDlhuGaz40Ibp9nRrmfZxAtraLJ48Jew3drE7LTGqu7gBOqpwWQ4BAGwT2+sw14ffPPBfd8xs2Wifc9rF0f9InGkJDAjkEZCE5sDRdRUAAbEPUUsChV8uymTSBygicM39pOH/hvdHzmTJ+WDj98JHR7TVcvcAHL1gUFix9LJrnkJFbhm++b+/o9nVqmDdMzNY2Z/KYsKcAuLQy5w3tq/zSPncAl7aNDEwgaYF9PrcgPPZ0/DsWtuy3brj1TO9YSHpTWFzhArKQwkkb06EAuDGlTmuhDr206mk1BDotkNKPcnfarpXxBO+v6uXdg9mVHgHRyu5r/do8j+0YNWiTcPnUsaGrq6v1gdvQgwC4Dai6JEAgHHbuwnD3o3+MlthpYL9w5anjottrSICAR0DYA70XEAD33s6VJQoIgEvENzSBBARmzl8aZuW4A3jy+GFhujuAW658SndQtorRmzuAq/xM2VY96nJ9bHB69bRxYcSAfpVdVuw6vASusiU0MQKVFDj4i9eG//nds9Fz236LDcKCDx8U3V5DAgQEwPZA7wUEwL23c2WJAgLgEvENTSABAc8ALqeIee6g3H6L7Pm/4yt7B2WrgnnD8Gw8dwC3qt769akEp6mso/WK6oEAgSIFxv/zj8L9T/xfdJfbbrZ+WHjam6Lba0iAgADYHui9gAC493auLFFAAFwivqEJJCDgUQTlFXHYjCvCS8t7Hv8r7xod3rr71j03rGmLPGH4iiVW+ZmyNS1D7mmnEpymso7cBXQBAQJtFRj/z9eG+5+IvwN42803CAs/6g7gthZF58kJyEKSK2nHFiQA7hi1gYoUcOgVqakvAs0TyPv8VT96X9weiQ2ALzt5bNhtcP/iBq5gT7EhXDb1qj9TtoK8bZlSbM2q/uiE2HVcdeq4sOPA6j7Koi1F1ikBAr0WeMu5C8OvcjwDeMSAjcLV08b3ejwXEmiigCykiVUvZs0C4GIc9dJhAYdeh8ENRyAxAXcAl1dQAfCr9rEhXJ+u0P2SnCo/U7a8HdXZkWNrVuUAOM/d5z546Oz+MhqBugt88IJFYcHSx6KXccjILcM337d3dHsNCRDwCAh7oPcCAuDe27myRAEBcIn4hiaQgMB/3rIsfOzSn0ev5HNHvzG8Z79to9truGaB4WfMCy9GPAPCHcCvGm6z6frhhtM9I7EKf65SCIDzPn/ao0eqsPPMgUA9BHzAXo86mWW9BWQh9a5fmbMXAJepb+xeCzj0ek3nQgIEQginXrQ4XLrkoWiLo3ffOnzpXaOj22u4ZoHYO4BTfwZwJhQbJgqAq/MnKrZmVb4D+Jwr7w7nX3dPNKqXD0ZTaUig8QI+YGr8FgDQAQFZSAeQEx1CAJxoYVNflkMv9QpbH4H2Chz2pYXh7kf+GD3ITgP7df8Ivq/WBbabfkWIeAdcWH/ttcKlJ49N9vmjeX4Mf52+fcIvP3NY6Orqar0AemhJIIUA2DPQW9oCLiZA4HUE8nxvG7JZ9gK4Cb632VEEcgrIQnKCaf6KgADYZqilgEOvlmUzaQKVERj/+WvD/Y/Hv6V66OYbhOu8pbrl+uX5h2E22KhBG4fLpx6Q5D8O3SXV8nYqpYMUAmB3AJeydQxKoBECL730Uhh2xvyota69Vlf3h5t9+vSJaq8RAQIvC8hC7ITeCgiAeyvnulIFHHql8hucQO0FvKW6nBLmDT2zWab6/NGZ85eGWQvvjS7E5PHDwvTDR0a317A9AikEwHn/HKb6Z7A9O0SvBJot4B0Lza6/1XdGQBbSGecURxEAp1jVBqzJodeAIlsigTYKeEt1G3Ffp+u8L4fJukr1+aP59+CA8M337VVO4Yz6ikBsAHzVqeMq+/iSPHfijxq0Sbh86tgk78K3rQkQKF7gkH9ZGH79WPwjtkZsuVG4+kPji5+IHgkkLCALSbi4bV6aALjNwLpvj4BDrz2ueiXQFIG8QeSU8cPC6e6+bHl75A09swEn7TMknH3MqJbHrloHE792Y1j8wFPR0xo9pH+Ye9LY6PYaFi+QUnAaG2RfPW1cGDGgX/GYeiRAIEmBXT4xPzzz3EvRa9twnbXCzz99WHR7DQkQ8AgIe6D3AgLg3tu5skQBAXCJ+IYmkICAH4Eup4h5Q89slu4AfrlWh+w8IHzzb90BXM7OfXnUlM6N2AB42cwjyyQ3NgECNRMYcea88NyLMa96fXlh66zVFX71uSNqtkrTJVCugCykXP86jy4ArnP1Gjx3h16Di2/pBAoQSOlOvgI4OtZFb+4ATvX5o+5C79i2K2yglF6eFhsAV/lRFoUVVkcECBQmsNPH5oc/vRB/B/B6ffuEuz97eGHj64hAEwRkIU2ocnvWKABuj6te2yzg0GszsO4JNEAgNgDxI9DFbYa8Lz7bYqN1wq1nHpzk80dvW/ZEOG7WzdG4cyaPCXsO3Sy6vYbFC8y45M5w4a0PRndc1ceX5PkAbMhm64eFHz0oyT+D0YXUkACBaIGdPz4/PPt8fAC8wTp9wi8+LQCOBtaQQPAICJug9wIC4N7bubJEAQFwifiGJpCIQGwA7Eegiyt43h+hP/f43cPE0YOKm0CFerpt2ePhuFm3RM/o4sljwl4C4GivdjTM+wHG5PHDwvQKPjs875/D0w4dEU46aId2kOqTAIHEBEZ+fF74v+fjHwGx/tpdYelnPAIisW1gOW0WkIW0GTjh7gXACRc35aU59FKurrUR6IyAALgzziuPkufOw8Gbrh+uPy3dOw/zPk7g0F0GhK//jWcAd37Xvjrif/3k/nDm3Luip3DWxFHh3fsOiW7fqYZ5917fPl3hV589LPTp06dTUzQOAQI1FRhx5hXhuRfjJ7/OWiH86nOeNR4vpiUBdwDbA70XEAD33s6VJQoIgEvENzSBRAQEwOUUcrvpV4SYe4O+8q7R4a27b13OJDswat7HCfTpCuF/Pne4EK4DtVnTEKk8tznv3ss8qhpml7gdDE2AwGoEYr/Hr7i0K4Rwn5dN2ksEcgnIQnJxabySgADYdqilgEOvlmUzaQKVEhAAl1OOYTOuCC9FJMCXnTw27Da4fzmT7MCoee/C7A7hjn5jePd+23ZgdoZYnUDe4LSqzwDuzd4bPaR/mHvSWBuDAAECrysQ+3erlTvxqC2bikA+AVlIPi+tXxUQANsNtRRw6NWybCZNoFICsf9IuerUcWHHgf0qNfc6T0YA/HL18j6HNbtmhy03Ctd8aHydy1/ruecNTqdMGB5OP2ynyq25N3tv2Bs2DD/6yITKrcWECBColkDs360EwNWqm9nUS0AWUq96VWm2AuAqVcNcogUcetFUGhIgsBqBPM+iHTVok3D51LGhqyv7QUVfrQoIgF8WzLMHV5ivv85aYemnD2u1BK7vpUDe4HTOlP3Dnttu2svR2nfZSy+9FIadMT/XACMGbBSunubDh1xoGhNooIBHQDSw6JbccQFZSMfJkxlQAJxMKZu1EIdes+pttQSKFkglyCnapRP9CYBfVc57p1T2HOB7z/aynE7s09WNkSe0H7LZ+mHhR6v5EsO8519mMX6HN4QLTti3LHrjEiBQE4E3fvLK8Mc/x78FbqN11wp3fcoHmzUpr2lWREAWUpFC1HAaAuAaFs2UvfnSHiBAoDWBVH6UuzWFcq4efsa88GLEQ4BTfwZwpp83AF6rTwj3nCUALmfnhpDnztl1+/YJSz99aCVf2pf3/Mu8Dx65ZfjW+/Yui964BAjUROAf//v2cPmdj0TP9u27bRW+PGmP6PYaEiAgC7EHei8gAO69nStLFPCpV4n4hiaQgEAqL3OqYyncAfxq1fIGwN6WXu6O/6+f3B/OnHtX9CTOmjgqvHvfIdHtO9Vw+pyfhosW/SbXcF4Cl4tLYwKNFTh73i/C16+/L3r9J47bLsw4Yufo9hoSICAAtgd6LyAA7r2dK0sUEACXiG9oAgkI5L0Drqovc6pjKQTAvQ+A11mrK/zqc0fUsexJzPno824ISx783+i17D54k3DpyQdEt+9Uw2mzl4S5i3+ba7g377RF+Lf375PrGo0JEGiegA/Ym1dzK+68gCyk8+apjCgATqWSDVuHQ69hBbdcAgUL3LbsiXDcrJuje50zeUzYc+hm0e01XLNA7Ativvyu3cPbdx+UNGXeO4DX6xvC3Z/1CIiyNsXYmT8Mv33qT9HDD+q/frhx+pui23eq4akX3REuXfJwruEO3GHz8N0T9st1jcYECDRPwAfszau5FXdeQBbSefNURhQAp1LJhq3DodewglsugYIFFt33eHjH12+J7vXiE/cLe223eXR7DVcvkOclWoM3XT9cf1o1X6JVVH3zBsAD+60bbjnz4KKG109OgX3PWhAe/cOfo68asPG64SdnVK9eH/z2orDg7sei15E1HDFgo3D1tPG5rtGYAIHmCeR9yeScKfuHPbfdtHlQVkygBQFZSAt4Db9UANzwDVDX5Tv06lo58yZQDYFpsxeHuYsfip7MxNGDwrnH7x7dXsPVC7jzelWXvAHwlv3WDbcKgEv743Xs124Itz8Q/wiIPYf0D3NOGlvafNc08MTzbgyLH3wq17yGvWGD8KOPHJTrGo0JEGieQJ6XZa6/9lrh5596SyVfltm8yllxnQRkIXWqVrXmKgCuVj3MJlLAoRcJpRkBAqsVOOxLC8Pdj/wxWmfkwH5h/qnjottruHqB/MH71uHc40cny5k3AH7DhuuE2z5+SLIeVV/Y277y43Dnb/8QPc3dBm0cLvt/B0a371TDY8+/Mdx+f74A2B3AnaqOcQjUW8AdwPWun9nXQ0AWUo86VXGWAuAqVsWcehRw6PVIpAEBAq8jMP7z14b7H3822mjbzTcICz/q7rdosDU0nPD5a8OyHO5DN98gXJewe94AuP/6fcOSTx7aahlc30uBUZ+8Mjz95xejr+637lrhZ586LLp9pxoe8i8Lw68fi/8ALJvXuB3eEL5zwr6dmqJxCBCoqYBnANe0cKZdKwFZSK3KVanJCoArVQ6TiRVw6MVKaUeAwOoE3nLuwvCrR+MDEHe/FbOP9vzMNeHxZ56L7mzzDdcJtyd8x2veAHizDdYJd3zCHcDRG6jghiPOnBeee3F5dK92aZHiAAAgAElEQVTrrNUVfvW5I6Lbd6ph3g9isnkdMnLL8M337d2pKRqHAIGaCsy45M5w4a0PRs9+0j5DwtnHjIpuryEBAiHIQuyC3goIgHsr57pSBRx6pfIbnEDtBT54waKwYGn8S5CEH8WU3J3XqzrmDYBTD8SL2WXt62Xkx+eH/3v+pegB1l+7T1j6mcOj23eq4eFfvj4sffjpXMONHtI/zK3g84xzLUJjAgTaLuAO4LYTG4CAANge6LWAALjXdC4sU0AAXKa+sQnUX+Cc+UvD+QvvjV7IlPHDwumHj4xur+HqBU658I5w2U8fjuZ5+25bhS9P2iO6fd0a5g2AU38kRtXrd/RXbwhLfhP/ErjdB/cPl55cvZfA5X0Wd1aXQ3YeEL75t3tVvUTmR4BAyQJe9lpyAQzfCAFZSCPK3JZFCoDbwqrTdgs49NotrH8CaQt4SUk59f3Pm+8LH7vsF9GDf/btu4T3jhka3b5uDfMGwEfvvlX40rvSDcSrXr/v3nRf+PjlefbvzuG9Y7ar3LIW3fd4eMfXb8k1Lx+C5eLSmEBjBfKeLxefuF/Ya7vNG+tl4QR6IyAL6Y2aazIBAbB9UEsBh14ty2bSBCojsHz58rDdjHlR8xk1aJNw+dSxoaurK6q9RmsWyHvn4cTRW4dzjx+dLGneAPiso98Y3r3ftsl6VH1hM+f9Isy6/r7oaU4et12YfsTO0e071TBvQJPN6+LJ+4W9hgppOlUj4xCoq0D+7/ODwrnH717X5Zo3gVIEZCGlsCcxqAA4iTI2bxEOvebV3IoJFC0QG75dPW1cGDGgX9HDN7K/vM8e3XmrjcO8Uw5M1ip2D64AcBdmuVvhhG/fGn549++iJ3HwTluEb71/n+j2nWp46kV3hEuXxD+KJZvX545+Y3iPDx86VSLjEKitgO/ztS2diddIQBZSo2JVbKoC4IoVxHTiBBx6cU5aESCwZoHY8G3ZzCMxFiSQ9x+GI7faOMxPNADOcxf6Cv5Jew8OZx+7a0HV0E1egQPO+VH4zZP/F33ZNpuuH244/U3R7TvVMO/LGLN5eQlcp6pjHAL1FvB9vt71M/t6CMhC6lGnKs5SAFzFqphTjwIOvR6JNCBAoAcBAXDnt8i02UvC3MW/jR544uh0fzQ073OoM7RxO7whfOeEfaP9NCxWYOdPXBmefe7F6E43XGet8PNPHxbdvlMN9/jM1eGJZ57PNdzwLTYKP/zw+FzXaEyAQPMEfJ9vXs2tuPMCspDOm6cyogA4lUo2bB0OvYYV3HIJtEEgNgC+6tRxYceBHgFRRAluW/Z4OG5W/MunLp48Juw1dLMihq5cH+dceXc4/7p7cs1r8Kbrhx9X8I7SXIuoceMRZ84Lz724PHoF6/btE3752cOj23eq4X5nLQiP/OHPuYZzB3AuLo0JNFbA9/nGlt7COyggC+kgdmJDCYATK2hTluPQa0qlrZNAewTy/Pi9l8AVV4M87lnYef1pByX78r0Zl9wZLrz1wVy4/ddfOyz55FtyXaNxcQK7fOLK8EyeO4DXXSv8/FPVuwP4kH9ZGH792B9zwXz2bTuH9+6/Xa5rNCZAoHkCeb7Pb7/lhuGaaeOT/T7fvOpbcacEZCGdkk5vHAFwejVtxIoceo0os0USaJtA3h+/nzNl/7Dntpu2bT5N6jj2zusZh+8YThy/fbI0vbkDePON1gm3f+yQZE2qvrADZv4w/OapP0VPc5v+64Ubpr85un2nGh53/k3htvufzDXc3x8wNJx51C65rtGYAIFmCsR+n7/ylAPDTltt3EwkqybQgoAspAW8hl8qAG74Bqjr8h16da2ceROohkDe8G3KhOHh9MN2qsbkazyLPHcGpX4HcN4PIbKyjx+xRbjgA/vUeAfUe+rHfu3GcPsDT0UvYq9t+4eLp4yNbt+phkefd0P4/9k7D+iqqqyP/9N7I0BCD0FKAkgCCZ2A0tERAiigY4PxIygzgI7SOwkwjgYclWpDHWAAgzok9BJAE1pCkYRelSJNevdb5zHBlPfIPeeWd8t+a31rPmGfffb+7ZND3v+eu0/uid+4pgvx9UDOGDp9zgWNjImARQlIFYDT/9YK0RVJALboMqG0ZRAgLUQGPIsPJQHY4gvAqOnTpmfUylHcREAfBHhfv+/TuComd6+vj+ANHMW2oxfQc+aPkjNYktQMjUzaA5hHDC8AtjipKeIiQiXzI0NlCbR/fz0OnL0m2WnN8v5Y9ab+Lk77yxdbsTrvrOQ8mKGnuyv267CfMVcSZEwEiIDqBHj+batXKRDfD2xJLSBUrwpNYDYCpIWYraLa5UMCsHasaSYFCdCmpyBMckUELEiATgA7p+hDFuYgLecXyZMnxlZCaq8YyfZGM5R6SorlFerngW2j2tMXZScWufW763Ds/HXJEUSE+mL9209IttfKcEpGHmZuOMw1nbeHK/In6u9CO64kyJgIEAHVCfC+3UIttlQvCU1gQgKkhZiwqBqlRAKwRqBpGmUJ0KanLE/yRgSsRoC+oDin4p2nZyLv1BXJk0dXCET6oFaS7Y1myCMAe7i5YN/ETnB1dTVamqaJt80/1uLohRuS89GrAMy7/7GEY6oEYekbLSXnToZEgAhYk8DUjDzM4HjANKB1JIZ2jrImLMqaCAgSIC1EEBwNAwnAtAgMSYA2PUOWjYImArohwPOKYv1KQfhuYAs6ealA9XgF4KgKgcgwqQDMswYL0Cd3q4cXmlZToBLkQoRA+9QNOHDmquShtcL8sXKI/lpA3L9/H5EjMiTnwQwX/V8TxEeW5RpDxkSACFiPAG+LmfbRYZjzUpz1QFHGREAGAdJCZMCz+FASgC2+AIyaPm16Rq0cxU0E9ENA6unLWS82Qse64foJ3MCRDF6Qg6W50ltAdIupiGm9Yw2csePQRU5h6lVQNGWB7CTV7/MtWJP/q+R020WVx9yX4yXba2XIu/ao/YhWlaF5iIDxCSR+vBk5HJdlxlYNRtrr+rss0/iVoAzMTIC0EDNXV93cSABWly95V4kAbXoqgSW3RMAiBHhOX7KLnFYOSaATwAqsjS9/PILR3+6V7GlS17r4c7MIyfZGMuTtQ81yC/b1QO6YDkZK01SxmuXVZt6117FuGGa9SCf0TLWYKRkioBIB7hPAUWGY8zLtLyqVg9yalABpISYtrAZpkQCsAWSaQnkCtOkpz5Q8EgErEdh29Dx6zsySnPLipGaIiygj2Z4M7RMYsiAHaRwngBNjKiLVpCeAh3+zC/O3nOBaKqF+ntg+uj3XGDJWjsC2oxfQc+aPkh0uSWqGRjrcN3jXXhlftu7a0UMwyZUnQyJgXQJT0vdiZuYRyQCSEqpjWJdoyfZkSASIAEBaCK0CUQIkAIuSo3FOJUCbnlPx0+REwPAEhizMRVrOz5LzSIythNReMZLtydA+AeoB/AcX3lOYbGRCrbKY17cJLS8nETDLgyPek8wM95IBzdGoWoiTyNO0RIAIGIXAlz8exehvf5IcbnLXunjBpG/6SIZAhkSAkwBpIZzAyPwhARKAaTEYkgBteoYsGwVNBHRDgIRI55SCl3t0hUCkm/QSON4+rKxii/s3RVz1UOcUj2bFlIw8zOS43T6pdSSG6fB2+6+zj2Fk2h6uig5oUwNDO9XhGkPGRIAIWI/Ai59kYeOB85ITT6hZFvP60YNNycDIkAiATgDTIhAnQAKwODsa6UQCJAA7ET5NTQRMQICESOcUccjCHKTlSL8Erm2d8vjkFf1doqUEPZ4+1Gy+KiE+yHznCXoNXwn4gj7M0ttycvpezOJ4RZvh6tO4KiZ3ry9IjoYRASJgFQKNJq7C+Wu3JadLrY0koyJDIvCQAGkhtBhECZAALEqOxjmVAG16TsVPkxMBwxPgFSITYysitVes4fN2dgK8PVRrlPPD6jdbm1b0jBi2THJJUns1QGJsZcn2ZKg8AbPcbs8rZDOS1KdT+fVEHomAGQnUG7scV2/dk5yav5c79ozvKNmeDIkAEaATwLQGxAmQACzOjkY6kQAJwE6ET1MTARMQ+CrrGEYtlf4KdEq3eni+aTUTZO7cFO7fv4/IERlcQZi59yiPAMzaYSz7W0vTiuFci8JJxrzCafuo8pjzsv5OsPMK2Q8E4EgM6xLlJPI0LREgAkYhEDthJS5evyM53EBvd+waRwKwZGBkSASoBQStARkESACWAY+GOo8ACcDOY08zEwEzEDBLL0+j1UKk7+2A1pEYqsM+qkqw5xGA2XxmFsOV4Km2D7O8OdD3s2ys3XeOC1dslWCkvdGCawwZEwEiYD0CPT7ehO3Hf5OcuLe7K/ImdqKHm5KJkSERoBPAtAbECZAALM6ORjqRAAnAToRPUxMBExAY/s0uzN9yQnIm1P9SMqpHGk5dno8Z6w9xOWsfHYY5L8VxjTGKMa8ATBdxObeyQxbkIC1Xeg/rxJiKSO2tv9YxL87NwsaD0i9pYtRrlPPHmrdaO7cANDsRIAK6J/C3f2/Hd7tOc8W5OKkZ4iLKcI0hYyJgZQKkhVi5+vJyJwFYHj8a7SQCtOk5CTxNSwRMQoBXiCThTZnC8wrvbNbYqsFIe92cJw95BeA+jatgcvfHlSkGeeEm0O/zLViT/6vkce3qlMPcVxpLttfKsNXUtThx8QbXdHQCmAsXGRMByxJ46ZNsZB7ge8NArw/LLFtESlz3BEgL0X2JdBsgCcC6LQ0F9igCtOnR+iACREAOgW1Hz6PnzCzJLuh0imRUjzTkFd6Zs/ZRYZjzMp0AZizoMkJl1qGolw6pG7D/zFXJw2uF+WPlEP2dmo0ZvxKXbkjv0ckSph7AkstOhkTA0gQ6T8tE3ukrXAwiQn2x/u0nuMaQMRGwMgHSQqxcfXm5kwAsjx+NdhIB2vScBJ6mJQImIbDl8Dk8NztbcjaL+jdBfPWyku3J0D4BkR7ASa0jMYx6ANuAJtQqi3l9m9DychKBVlPX4MTFm5Jnrxrig8yhT0q218qw0cRVOH/tNtd0XRtUwPQ+DbnGkDERIALWI9B5eibyTvEJwGX8PLBjdAfrwaKMiYAgAdJCBMHRMJAATIvAkARo0zNk2ShoIqAbAi99mo3M/dJfUWxdqxy+6Ku/V7l1A1RiIL///juix6zAjTv3JI4w98VnvC0g6oQHYPngBMnsyFBZAk2SV+HMFenCaViAJ7JHtlc2CAW8ibyiHV0hEOmDWikwO7kgAkTAzAR4L8tkLPS6V5q5TpSbsQmQFmLs+jkzehKAnUmf5hYmQJueMDoaSASIAADeE3Ch/p7YPkp/Qo4Ri9njo43YfuKypNBdXICDkzrBzc1Nkr3RjHgFYBLhnFvh+uNW4MrNu5KDCPB2x+5xHSXba2W49ch5PDtLegscFldUhUBkkACsVYloHiJgWALbjl5Az5k/csVfzt8DW0fRCWAuaGRsaQKkhVi6/LKSJwFYFj4a7CwCtOk5izzNSwTMQYC3B2awjwdyx9KXEyWq3zE1E/vOSH89NCWxPp5vUlWJqXXng1cAToythNReMbrLwyoB1Ru7HFdvST+97u/ljj3j9ScAs5P41Yenc5WN1h4XLjImApYlcP/+fUSOyODK38/TDT9N6MQ1hoyJgJUJkBZi5erLy50EYHn8aLSTCNCm5yTwNC0RMAmBdu+vx8Gz1yRnU7O8H1a92UayPRk6JlB/7HJc4RDRYqoEYekbLU2JlFcAXpzUFHERoaZkYYSkGk5ciQvXpF+eFurnge067WvJv/aaIS6ijBHKRDESASLgRAIivf493VywP7mLE6OmqYmAsQiQFmKseukpWhKA9VQNikUyAdr0JKMiQyJABOwQSFm2F7M3HpHMpn9CJIZ3iZJsT4aOCdQakY7b93+XjKhikDd+GN5Wsr2RDEmEM1K1gHbvrcPBX69LDrpmOT+sekufD4541l7N8v5YOSQBLqwnC32IABEgAo8gMHV5PmasP8TFiE4Ac+EiYyIA0kJoEYgSIAFYlByNcyoB2vScip8mJwKGJzAlfS9mZkoXgJMSqmNYl2jD562HBB4bsQx370uPJMTXAzljzNl+g0eEY8QGtKmBoZ3qSIdHlooSaDF5NX7+7ZZkn5WCvLB5eDvJ9loa8qw9Jv7WCgvQMjyaiwgQAYMSGP7NLszfcoIr+srB3tg0zJwPerlAkDERkEiAtBCJoMisBAESgGlRGJIAbXqGLBsFTQR0Q6Df51uwJv9XyfG0iyqPuS/HS7YnQ8cEao/KwC0OBTg8yBtZdALYBrRP46qY3L0+LS8nETBT73AeAfjolKecRJymJQJEwGgERE4Ax1ULweIBzY2WKsVLBJxGgLQQp6E3/MQkABu+hNZMgDY989SdXUaz4/hFrM47i0vXbyPY1xPtosLQsGowvW5qnjLrLpP272/AgbNXJcdVi70C/WZryfZk6JhA3THLce229Iu0oioEIGNQgimR8ohwDEBS60gM60ytSJy1GBqMW4Hfbt6VPH2Qtzt2jtPfJXAsAZ61t2JwAmqH0wlgyYUnQyJgYQIiPYDpngULLxhKXYgAaSFC2GgQABKAaRkYkgBteoYsW4mg952+gr8vysXuny+X+Lv6lYLw3nMN6LVTc5Rad1k0TVmD05dvSo7LzKdQJUNQyJCXfWJsJaT2ilFodn254RHhWOTJ3erhhabV9JWEhaJpNXUtTly8ITnjKiE+2Dj0Scn2WhryrD3qAaxlZWguImBsAuxgR/Xh6VxJhAd6IWuEPtvlcCVCxkRAIwKkhWgE2oTTkABswqJaISXa9IxfZSb+PjvzB1x+xGmqQG93LEpqTiePjF9u3WXQcMIKXLgu/SRfGV8P7DBpH1qti5P40SbknPhN8rSLk5oiLiJUsr2RDHlEOJZXYmxFpPaKNVKKpoq172fZWLvvnOSc2tYpi09eaSLZXktD3rW3OKkZ4iLKaBkizUUEiIBBCfDuL6F+ntg+ur1Bs6WwiYD2BEgL0Z65WWYkAdgslbRYHrTpGbvg7HTAnz7chD12Tv4Wz4ydBP5uYAtqB2Hskusu+oYTVuHC9duS4yrj54kd9OVEMq9HGXb/aDN2nLgk2ZeZhSfeL8nRFQKRPqiVZHZkqCyBv/17G77bdUay02ceD8cHzzeSbK+lIe/aM/NJfC2501xEwAoEePeXamV8sOEdfb4tYYV6UY7GI0BaiPFqppeISQDWSyUoDi4CtOlx4dKdMW9/sCUDmqNRtRDd5UEBGZdA7PiVuHjjjuQEQnw8kDO2g2R7MnRMoPU/1uHYheuSEQ1oUwNDO9WRbG8kQ94vyVHhAcgYbM5+yEaoW9cPN2HnSemn12MqB2HpwJa6TI177VUIRAY9fNBlLSkoIqAnAvfv30fkiAyukBJqlcW8vvp8W4IrETImAhoRIC1EI9AmnIYEYBMW1Qop0aZn7Crz3hBsZgHI2JU0bvRxE1fh3DXpJ4DL+nti2yh6PVGJiscnr8avV25JdtWncVVM7l5fsr2RDHlFOPqS7NzqWvUSOEa9Trg/lg+mizCduwJpdiKgfwJfZR3FqKU/cQXaLaYCpvVuyDWGjImAlQmQFmLl6svLnQRgefxotJMI0KbnJPAKTTv8m12Yv+WEZG9mFoAkQyBDRQk0Tl6NsxwiZPkAL2wZSReUyC0Ca/9Sa2QG7tz/XbKrAa0jMbRzlGR7IxnyCsDdYipiWm/qAeysGtcelYFbd+9Lnt7DzQUHkrtIttfSkHftxVQJxtI3WmgZIs1FBIiAAQl0SN2A/WeuckXePqo85rwczzWGjImAlQmQFmLl6svLnQRgefxotJMI0KbnJPAKTUsngBUCSW6ECfSc8QO2HbsoeXx8tRAsGtBcsj0Z2ifA2/6FeUnpVg/PN61mSqS8IlyfxlUwufvjpmRhhKR4TwC7uQAHU7rosoc979qrVd4fK9+kE8BGWKcUIxFwJoGY8StxiaPFFou1Vpg/Vg6h/cWZdaO5jUWAtBBj1UtP0ZIArKdqUCySCdCmJxmVLg15RSDqAazLMho6qMnpezEr84jkHPonVMfwLtGS7cnQPgHehz/MS9cGFTC9jzlfDeUV4cx8GtoIPzMvzs3CxoPnuULV679fvGuvRjk/rHmrDVfuZEwEiID1CDScsBIXrku/Y4ERokvgrLdOKGN5BEgLkcfPyqNJALZy9Q2cO216fMVjr13vOH4Rq/PO4tL12wj29US7qDA0rBrslJNJLJ46o5dLepW2fqUgfDewhVPi5KNM1kYiQA8hnFMt3vYvLMqIUF+sf/sJ5wSs8qy8Ilxyt3p4waSnoVVGrYj7eT8cwZjv9nL50msPe961F1MlCEvf0OeFdlwFIWMiQARUJcB7WeYDAdgXG94x57/zqsIm55YlQFqIZUsvO3ESgGUjJAfOIECbnnTq+05fweAF25F3+lqJQVHhfpjepxFqhQVId6iQZcI/1uL4hRulels5JMEp8ZUaGBkYmgB7CFF9eLqkHOghhCRMkoxETgCH+nli+2hzXsDHK8JRD2BJy0w1o8ELdmBp7iku/73jq2BKD/217eBde0kJkRjWxZy9uLkKSsZEgAg8ksDgBTlYmvsLFyVqAcGFi4yJAEgLoUUgSoAEYFFyNM6pBGjTk4afib9PfZCJR91Z4+4KLPtbAmqHaysCS70k4uiUp6QlS1ZEgJOAVAFk1ouN0LFuOKd3MrdHgPfkNfNh1hPAPA8hClhGVQhExqBWtLicRKDNu+tw9Px1rtkTYyoiVYcX90nd/wqSpYcPXGUnYyJgWQLDluzCgq3SL3pmoOgSOMsuF0pckABpIYLgaBhIAKZFYEgCtOmVXjYmLsRMWInfbtwt1TjIxx25Yzpo2maBBOBSy0IGKhLgEd9qssuPhiRo+vOhYupOdX3//n1EjsjgiiExtiJSe8VyjTGCsYgYHl0hEOkkADutvCK9LVvXKocv+jZ2WsyOJuYVgGnt6a6EFBAR0CUBkTd9qL+9LktJQemYAGkhOi6OzkMjAVjnBaLw7BOgTa/0lZF18Cx6z91auuH/LBa+Fo8mNcpLtpdr2P79DThw9mqpbugEcKmIyECAwLaj59FzZpbkkYuTmiEuooxkezK0T0BE9FyS1AyNTMhe5Ety2zrl8ckr8bS8nESgScpqnLl8i2v2qAoByBiUwDVGC2NeAbhOeACWD9ZfHlqwojmIABGQToD+nZfOiiyJgCgB0kJEydE4EoBpDRiSAG16pZctZlw6Lt38vXTD/1mE+bkie3RnyfZyDaX2AF4xWPv2FHJzo/H6JzBkYS7Scn6WHGhibCWk9oqRbE+G9gmIiJ6HkjvBzc3NdEhFLsSLLOuHNW+1ptPoTloN7d9fjwNnS/bTf1Q4em3bwSsAJ9Qqi3l9mziJPE1LBIiAUQjwvGFVkBM9ZDdKdSlOvRAgLUQvlTBeHCQAG69mFDFAjc9LWQUiv3wxl1qdtmXx1RqVgTv3Sheo6fV7+pFXg0Dn6ZnIO3VFsmu9ijiSE9CJoYjomdytHl5oWk0nGSgXhogYzmZfMqA5GlULUS4Q8iSZwF++2IrVeWcl2zNDvfbO5RWAzdqKhauYZEwEiIAkArz7y4A2NTC0Ux1JvsmICBAB0kJoDYgTIAFYnB2NdCIBeur1aPjZh86i1xzp7R8KvGklANPr90784aGpbQT4BWB9vsZttHKKiJ41y/th1ZttjJZqqfGKvCbLnNIX5VLRqmYwNSMPMzYc5vKv1wcYvAJN7/jKmNKjAVfuZEwEiIA1CfDvL1Uwpcfj1oRFWRMBAQKkhQhAoyE2AiQA00IwJAHa9B5dtiaTVuDM1dIvfyvuRSsBmF6/N+SPnamCfunTbGTuPyc5J71e5CQ5AZ0Yioie/p5u2DOhk04yUC4M0Tc1+jSuisnd6ysXCHmSTEBk/er1ciNegSYxpiJSe5vvMkbJxSdDIkAEJBPg3l+ozZZktmRIBBgB0kJoHYgSIAFYlByNcyoB2vQejZ/3F68Cb1oJwPynLwORQTffO/VnzmyTD1mQg7TcXySnReKHZFSPNBQRPb09XJE/Ubv+5MpkKs2LyF5NJ4ClsVXDSmT99mlcBZO76+9kG+/ao4dgaqwo8kkEzEmAd3+hexbMuQ4oK/UIkBaiHluzeyYB2OwVNml+tOmpIwBrddkSvwD8x+v37Av4juMXbX0YL12/jWBfT7SLCkPDqsF0MZJJf97VSGvYkp1YsPWkZNe94+n1RMmwSjF8bMQy3L0v3Vt4oBeyRrSTPsAgliJiIkuNLstxboF5hQ2z9ACOqkBtcJy78mh2ImAcArz7pF4flBmHOEVqNQKkhVit4srlSwKwcizJk4YEaNNTRwD+v5YRGPF0XdUrKfr6/b7TV/D3RTux++ffSsRYv1IQ3nuuAWqFBageP01gfAK8vWjp1KVyNY8ZvwKXbkhvUdOqZii+7NdUuQB04mnb0QvoOfNH7mgW92+KuOqh3ONogDIEeIWNhFplMa9vE2UmV9ALbx51wv2xfHBrBSMgV0SACJiVAO/+Qr9jmXUlUF5qESAtRC2y5vdLArD5a2zKDGnTU0cA9nUH9k56SvU1I/L6fVKbx/DszB9w+aZj4SjQ2x2LkpqjdjiJwKoX0eATbD1yDs/OypacxaL+TRFPoptkXo8yjJ2wEhev35HsS68CmuQEHBgOWZiDtBzpbUgK3Oj1RKlcHkYZzytsRIUHIGNwgu7S480jpkoQlr7RUnd5UEBEgAjojwDv/kJvtuivhhSRvgmQFqLv+ug5OhKA9Vwdis0hAdr01BGAmVct+gDzvn7fK64yfvrlMvb8crnUnwp2Evi7gS2oHUSppKxt8FXWMYxaukcyhJRu9fB802qS7cnQMYG6Y5fj2q17khGZ9dVz3lY4BcCqhfpiw9tPSOZHhsoS4BU2oisEIl2HPex586gc4o1NQ9sqC5O8EQEiYDoCIu2NliQ1Q6OIMqZjQQkRAbUIkBaiFlnz+yUB2Pw1NjxlDBEAACAASURBVGWGtOkZWwDmff0+oWZZZB44J3ktLxnQHI2qhUi2J0PrEej24SbknizZSsQRiZjKQVg6kE6/KbFSokYvx4070gVgvQpoclmICsBB3u7YOa6j3OlpvCABXuFUrye2efMI9vFA7tgOgtRoGBEgAlYhsP3YBfSYwdfeaEDrSAztHGUVRJQnEZBNgLQQ2Qgt64AEYMuW3tiJ06ZnbAFYtPel1FVLvcSkkrKuXdykVTh39bZkAGX9PbFtVHvJ9mRonwA7GVRzZAbu3v9dMiKz3g4+ZGEu0nJ+lsyhwDDQ2w27xnXiHkcDlCHAK5wmd6uLF5pGKDO5Ql5ETuiF+nli+2jaAxUqAbkhAqYlwHvIg4FoHx2GOS/FmZYJJUYElCZAWojSRK3jjwRg69TaVJnSpmd0Afg8es7MUm1N9mlcFZO711fNPzk2PoHoMctx/bb0U6i+nm7YO4FEN7mVFzkZtDipKeIizHfp2bajYvtgeKAnskaQECd3LYqMFxFOE2MrIrVXrMh0qo0R+Tk0ay9u1SCTYyJgUQLDv9mF+VtOcGUfWzUYaa+34BpDxkTAygRIC7Fy9eXlTgKwPH402kkEaNMztgAscjqAZ6nRCWAeWta0bTB+BX674fhCweJU6PVnZdaJyM++WS/gExETWRUqB3tj0zDqxarMiuTzIiKc6rGFicjP4cRnovFi8+p8wMiaCBAByxEQ2V/aR4Vhzst0Athyi4USFiZAWogwOssPJAHY8kvAmABo0zO2ACxyOoBnpVIPYB5a1rStP3Y5rnBcRBbg5Ybd4+kEsNzVIvKzr9ceqnJZsPG87QTYmPAAL2SNbKfE9OSDk4CIsKHHSwxFfg67NqiA6X0achIjcyJABKxGQKTNW1LrSAyjHsBWWyqUrwwCpIXIgGfxoSQAW3wBGDV92vSMLQCLfImWulbrVwrCdwNbwMXFReoQy9mxk4c7jl/E6ryzuHT9NoJ9PdEuKgwNqwZbhludURm4efe+5Np7u7sif1JnyfZkaJ+AyM9+RKgv1r/9hCmRigjAgV5u2EUPI5yyHkSE01Y1Q/Flv6ZOidfRpCI/h1XL+CDznSd1lQcFQwSIgP4IbD1yDs/OyuYKjA5ucOEiYyIA0kJoEYgSIAFYlByNcyoB2vSMLQCLvEYrZcG5ubogY1Ar1AoLkGJuSZt9p6/g74tysfvnyyXyZ+L5e881sAS/miOW4Y50/RcersCBlKcsuWaUTFrkZz/U3xPbTXoBn4gATA8jlFyRfL6mZuRhxobDXIMSapbFvH5NuMaobSzSf5reglC7KuSfCJiDAO8FpwFe7tg1roNlDiCYo8qUhbMJkBbi7AoYd34SgI1bO0tHTpuesQXge/fuocbI5Yqv4ZgqQVj6RkvF/ZrFIRN/n535Ay7fdNz7NtDbHYuSmqN2uLlF9MfHrXgkh+I1Z1x2jetolqXgtDzY6fOaI9PBcfgadAK4aLk83VywP7mL02po5Ym/zj6GkWl7uBBEhQcgY3AC1xi1jUVe0fbzdMNPdBGm2qUh/0TA8AQ6T89E3qkrkvPwdHfFvomdSACWTIwMiQDoBDAtAmECJAALo3sw8MqVK1i5ciXWrVuHHTt24MCBA7h06RJ8fHxQsWJFNG7cGM8//zw6duz4yH/Y1q9fjyeekP6K68svv4zPP/9cUvTffvstvvzyS2zduhVnzpxBYGAgatSogcTERPTv3x9BQUGS/DCjU6dOYebMmfj+++9x9OhR3Lx5E+Hh4WjVqhX69u2L1q1bS/Ylx5AEYGMLwCJfoqWsl+Y1QvHv1/T1qq2UuLWwYcLbnz7chD12Tv4Wn98KbTSe+ddG7JLAooBNg8qB+HZgKy1KZfo5un64CTtP/iY5z8SYikjtHSvZ3kiGIieA/b3csWc8PYxwRp2nZORhJucJYF1eAidwkpkEYGesOJqTCBiPAK8AzDKkFhDGqzNF7FwCpIU4l7+RZycBWEb13n//fYwcOdImgpb2YQLpV199hapVq9o1VUMAZuI0E5//+9//OgyvcuXKWLhwIZo3b15aCkhLS7OJvEzgdvR57bXXMGPGDLi5uZXqT44BbXrqCMBanSxL/Hgzco47Xkeia4NOADsmx/vqvdl/GR/07+34dtdpyUut6+PhmP58I8n2ZOiYwOwNB5GSsU8yosVJzRAXUUayvZEMRQTgx8r5YvVb0h8YG4mH3mMV6QGcGFsJqb1idJXaX77YausBz/OhFhA8tMiWCFiXwJCFOUjL+YULwIDWkRhKl8BxMSNjaxMgLcTa9ZeTPQnAMuglJSVh1qxZNg9MSG3bti3i4uJQrlw53LhxA9nZ2TbR9+rVqzab6tWrIysrC+XLly8xa2EBuFevXujdu/cjI2NCcsOGjm9jvnv3Lrp06YJVq1bZ/ISFhYGJs9HR0bhw4QLmz5+PzZs32/4uODgYmzZtQt26dR3OuXr1apu/O3fu2GyeeuopPPPMM/Dz87OdfJ47dy4uX37QU5TNM3v2bBlkSx9Km55jRvfv30fkiIzSIdqxCPJ2w85xnYTG8gxq+956HPr1Gs8QSbasB3D631qZvn2BJBjFjHgv/RnQpgaGdqojMpUhxvT7fAvW5P8qOdZ2UeUx9+V4yfZk6JjA2rzT6PvFdkmIvNxdkTehI1xdXSXZG81IRADuFlMR00x6Ilrv9ePdR1k+S5KaoZHOHmCIPIQND/RC1oh2ei8RxUcEiICTCYi0mGkfHYY5L8U5OXKanggYhwBpIcapld4iJQFYRkUGDBiAw4cP4+9//7tN/LX3BfXYsWO29g/79j047fTqq6/i008/LTFrYQF47NixGDdunIzIYDuF+/rrr9t8MNF37dq1NhG48IfF/d5779n+qEWLFjYR2N6HnXCuXbs2jh8/bvvrf/3rXxg4cGAR0/3799vaP5w+/eBEHWuL0b59e1k5PGowbXqO6cxeuxcpK48Isa9Wxhcb3lH/ZJnIl0+pCVmhfYFUFoXthi3ZiQVbT0oe2ju+Cqb0eFyyvdEMeddgbNVgpL3ewmhp6jLeOZmHkJyeLzk2M59GFxGAqR2J5KWjuCHvmxQebi623pZ6e4DB+wCMgaxZ3h+r3tSmzZfihSOHRIAIaEaAtRyrPjydaz76HYsLFxkTAeoBTGtAmAAJwMLoYDtJW6ZM6a+l7ty5EzExD17/8/X1xa+//mr738IfJQVgdsEWO5FcIMZu377d7mlhZsdOLOfm5tpCWb58uU2sLv756KOPHgq+f/rTn/Ddd9/ZpfbNN9+gR48etr9r2rSpbWNS60MCsGOyIoJCgbfy/p7YMko94b5gHrV6ABf4N7NgJPozxXsrsx5fWxbN3d44XgGkafUyWNC/mZIhWNbX619vR/pu6e03zPxqqMh+XTHIGz8Mb2vZ9ePMxEWEDT3+ezR4QQ6W5vK9ot0+qjzm0FsQzlx+NDcRMAwB3n/b2keFYc7LdALYMAWmQJ1OgLQQp5fAsAGQAKxR6aKiopCf/+DEExOEH3+86Mk6JQVgdtqXnUhmH3Yql/l29Pnss89sfX3Zx9HFcgkJCdi4caPNhl1216ZNG7vuWOsBdrkcuxyOfY4cOYKIiAhVCNOm5xgr7y9dhT2F+nlg++gOqtSssFM5bSqkBGf29gVSGBS34e3JZnYBmFcA8fVww08THn2Zp0hdrDim20ebkHtC+iVwZhaeRPbrEF8P5IxRf5+24tqUkjNvzZJaR2KYznpb8v57wLgkJVTHsC7RUhCRDREgAhYmIPKgTI/7pIVLSKkbgABpIQYokk5DJAFYo8I0btwYW7dutc3G+gA3adKkyMxKCsDvvPMO3n33XZv/qVOngv23o8+ZM2cQHh5u+2vWm5j9d+EPu0iO9Qhmgl1AQAAuXrz4yAveWFuMmTNn2lx8/PHHYP+txoc2PcdUeb+cFvYU7OOO3LHa3C4vJ87S1lSfxlUxuXv90sws9ffDluzCgq0nJOfcJ74KJpu4BYSIALK4f1PEVQ+VzJAM7RNomrIKpy/flozHzJeeieyD4UHeyKITwJLXj9KGvDXT48k23n8PGMOUxPp4von9i4yVZkz+iAARMC4B3lY5LFM9vilh3ApQ5FYgQFqIFaqsTo4kAKvDtYjXW7du2frv/vbbgxNPp06deii6FhgWFoDr1atnE1lZf+Hbt2/b2kywP2M9dfv161dq24nOnTvb2jmwDzsN/MQTj+7pyi6UO3HigTB09uxZ2yV2BR92kR1r58A+7CTwhg0bHkmM9TdmMbIP60HM2keo8aFNzzFV3i+nhT1pebJMTpylrSk6AVySEK/gmRhbEam9YktDbdi/FxFAEmqVxby+RR/eGRaAEwOvOyYD127flxxBiK87csZo82BKclAKGYrsg9XK+GDDO08qFAG54SXAWzM99myempGHGRsOc6VOJ/S4cJExEbAsAZHLMpcPaoU6FQIty4wSJwK8BEgL4SVG9gUESADWYC18/vnntsvf2Kdhw4ZgPXmLfwoLwI8Kyd/fH9OnT3/YtsGebWRkpK39AvtIacPA2kRkZmba7Fmrh5YtWz50O2/ePFtrCPZx1CKicAysRcSTTz74YsraUKxevVoVwrTpOcbK++W0sCc/Dxf8NLGLKjUr7lROnKUFqMdb10uLWe2/f/GTbGw8cE7yNAk1y2JeP/OKnSICSKCXG3aN7ySZIRnaJ1Bj+DLc+106HQ9X4EDKU9IHGMhSZB+sEuKDjUNJAHZWmXlrVifcH8sH6+vyNJE+/O2jwzDnJerR6ax1R/MSAaMQ4L10mOXFLplcOSQBLi4uRkmT4iQCTiVAWohT8Rt6chKAVS4fu/Ctbt26tovf2IddlJaYmFhiViYAM+GUCcSsxy7rGRwUFISrV69i9+7d+M9//oOTJ08+HDd58mQMGzbMbvTsxDBr1cA+rIUDE40f9enevTvS0tJsJt9//z2efvrph+YffPABBg0aZPvvt956C//85z8f6WvXrl1o0KCBzaZRo0bYtm0bN2Epl8cxJv3797f5/uGHH9CsGV3OVACa98tp4QJ5urlgf7LxBeBF/Zsinl7VL/Kz1/ofa3Hswg3JP49mP2UoIoC4uwIHTSpESl4YChhWH7YMHPovXF2Aw5NJAH64x4f6Yv3bj36zR4EykQs7BER6W2rZWklq0aZk5GEm5wng2KrBSHu9hdQpyI4IEAGLEuC9dLgA0+KkZoiLKP1ydYtipbSJQBECJADTghAlQAKwKDkJ41j7hnbt2j28QK1bt24Phdbiw1lbCCbW1qpVy67nO3fuYMSIEQ8FWPaElAmfBe0Zioh4np5g9uzD/tfd3f2R0b7wwgv497//bbNh/9unT5+H9ikpKRg5cqTtv9n/Tpo06ZG+Dhw48DAHlsu+ffskkCpqwvv0lwTgovzkCMCuAA5P0UZokRNnaYuKvar/xauN6SRBIVCNJq7C+WvS+66G+nti+6j2paE27N9PSd+LmZkP3pSQ+jGzECmVgRJ2NUYswz3pHSDg4eaCAxo9mFIiPx4fIvtgVIUAZAxK4JmGbBUiINLb0sfDDXkT9fXmwPBvdmH+Fuk94Rm+dnXKYe4rjRUiSW6IABEwKwHelmMFHLo1qIBpfRqaFQvlRQQUJUACsKI4LeWMBGCVys0uTXvppZfw9ddf22aoUaOG7RK4kJAQWTP27dsXn332mc1Hly5dsGzZshL+PFUSgEeNGoWJEyc+Mn4SgGWVV5HBIoJCwcRmEYBZPnUrBCC1dyxqhQUowtXoTtq8uw5Hz1+XnEaEyU8Z9vt8C9bkP3gzQ+rHx8MVeRM7SzUnOwcE4iauxLlrDx5SSvlUDvHGpqFtpZgazkZkvzZ7f249F1Gkt6W3hyvydbZviORh9rZAel53FBsRMBIBkTsWWH7hgV7IGtHOSKlSrETAaQRIAHYaesNPTAKwCiVkrwiy9gRz5syxeWeXrLHL0yIiImTP9vPPP6NKlSpgc3h5edlaPfj4+BTxSy0gZGM2tAMRQaEgYbO0gCjIx8fdFUsHtkTt8EeLwOyBzfytJ7B4+0lcvnEHgT4eeLZRFfSOrwxXVyaLG//z0ifZyOTpAWzyC8/ap27AgTNXuQpbs5wfVr3VhmsMGZck8OyMTdh67MGlqFI+f3o8HP96vpEUU8PZiOzXk7rWxZ+byf99wnCwdBCwyMnZUD9PbB+tr7cpRE4y12I9Ot/UVy9jHSwJCoEIEIFiBEQeMDEXenxYRsUlAnolQAKwXiuj/7hIAFa4RkyYff311zFz5kyb58qVK4P192UngJX61K5dG/v377e5++mnnxAdHV3ENV0CpxRpY/oRERQKMg3xcUfO2I6aJC4nTp4Aq5bxwYa3n3DYDmLFntP464Ic3L5b8p109uru9N4x6FA3nGdKXdoOXpCDpbm/SI6tW0xFTOsdK9neaIa8PZFZfv/XqjpGPFV0vzVa3nqIt1nKapy6fEtyKI+V88NqkwrvIvtg15gKmN6bXpOVvIAUNBTpnftYOV+sfktfPZtFehlXCvbG5mHmPImv4BIhV0TA8gS2Hb2AnjN/5OZAAjA3MhpgYQIkAFu4+DJTJwFYJsDCw9kv1G+88QZmzJhh++NKlSrZxN/HHntMwVmAFi1a2Pr/ss/mzZvRvHnzIv47d+6M5cuX2/5s7dq1eOKJR3/xYCeUT5x40Avu7NmzKFeu3EN/2dnZD/sMJyQk2E4yP+rz6aefol+/fjYTJoR/9NFHiuZe4Iw2PcdYRQSFAm9h/p7I1qjvq5w4eReVo0vhmPjb/6vtpbqb9edG6FjP2CIw763MveOrYEqPx0tlY1QDEQGYhDdlql13zHJcu31PsrNgXw/kjukg2d5IhiL7oNnbs+i5fiKXR8ZVC8HiAUV/T9NDjrxrLyzQC9n0erYeSkcxEAFdE9h65ByenZXNHWOAlxt2j9dXv3TuJGgAEdCIAGkhGoE24TQkACtU1OLib8WKFW3ib82aNRWa4Q837HI11muXfeydAH7nnXfw7rvv2v5+6tSpYP/t6HPmzBmEhz8QtsqXLw/234U/7GK64OBgsFfkAwICbC0n3NzcHPobMGDAw9PPH3/8Mdh/q/GhTc8xVd4vdYU9+Xu6Ys8EbXqcyomTd02xS+Hm9W1SZBhb01FjVuCWnZO/xf2zk8A/je9g6HYQvK/kDWhTA0M71eFFbRj7VlPX4sTFG1zx0uVbXLgcGtcbuxxXb0kXgP083fDTBHN+KRTZB81+QaMyq0wdL1Mz8jBjw2Eu5zGVg2ytiPT24V17jaoGY8nrLfSWBsVDBIiAzggMWZiLtJyfuaOiHsDcyGiAhQmQFmLh4stMnQRgmQDZ8OLib4UKFWziLxNqlf6cPHnS1lO4oAfwhQsX4OvrW2Qaduq3bdsHr+m1adMG69atcxgGu1COXSzHPq+88srDC+YKD2Anfzdu3Gj7I5ZX69b2e8AxQY2ddj5y5IjNlv2vEn2P7QVPm57jlcX7pa6wJy0vuZITJ+/Plb0ejLwnuVIS6+P5JlV5p9aNPW/PxyUDmqNRNXmXVuomeTuBtH53HY5xXIrHXNDJS2UqynsJHJv1cEpnQz+AcUROZB+sxtravPOkMsUgL1wERHoAx0eEYFGS8U8AN6wShG/e0J+QzVVAMiYCREB1Ap2nZyLv1BXueaqG+CBzKP3bxg2OBliSAGkhliy7IkmTAKwARtb2gZ12ZR92mpaJpKxPrxqfV199FZ9//rnNdadOnZCRkVFimnv37tl6D58+fdr2d9u3b0fDhiX7BTK7uLg45Obm2uxY24iOHUv2f2W5sRzZ509/+hO+++47u6l988036NGjh+3vmjZtCrYxqfWhTc8xWRFBocCbpxuwP/kptcr20K9I/0E5Qdl7hbzbR5uQe0L6RVQxVYKw1MBfftkDmsgRJfcLe1zNcOK5tPXSadoG5J/muwSuVpg/Vg6hS5BKY1va39cdk4Frt0v23H7UuORudfFCU/NdfCayXyfULIt5/Yq+0VAac/p7ZQjwvknBZo2tEoy0N/R3cpZ37bFLYvdN6uywn74yhMkLESACRicgKgBXCfHBRhKAjV5+il8jAqSFaATahNOQACyzqH/961/x4Ycf2rww8Zedtq1Th++16YMHD4KJp0lJSQgMDLQb0Z07dzBixAj885//fPj39vr/Fvwl60PMevCyT926dW29gFmLh8Kft99++6E/1ld406ZNdue+efOmTdA+fvy47e9ZvgWCcMEA1pKCnRQuEJ1XrVqFdu3ayaTreDhteo7ZRI9Kx/W7vwux16r/lugFEUJJAbAn3DWfsga/XLop2aXRL8ChE8BFS817KR4b3bZOWXzyCglvkn9oHBjWHpWOW5x7VJUQb2wcar4LqHhFOIY0MaYiUk18QaPc9aXm+G1Hz6PnzCyuKdpHh2HOS3FcY7QwFll7S5KaoVFEGS3CozmIABEwKIEhC3OQliP90uGCNCNCfbD+bToBbNCyU9gaEyAtRGPgJpqOBGAZxRw1ahSSk5NtHlxcXJCSkiJJ/GWncVkbh4IPO4EbGxsLLy8vPPnkk4iPj0f16tVtPXevXr2K3bt34z//+c/Di9rYODYvE4Qdfe7evYsuXbqACbHsw8Tp1157DdHR0WBtI+bPn/9Q8A0KCrJdJseEYkef1atX2/wxIZp9nn76aTzzzDPw8/PDjh07MHfuXPz224PTlGye2bNnyyBb+lDa9BwzqjNyGW5Kb69ZxJFWPYAHL9iBpbmnSi+0QhYp3erh+abViniLnbASF68/WM9SPiG+Hsgx8EVUvL0rzd4D+Ksfj2DUt3ullP6hDZ285MJl15id/q8xIh33OZ9RubkAhyar/3aC/Az5PIiIcO2jymPOy/F8E5G1IgREHl72T6iO4V2iFZlfSSciay8xtiJSe8UqGQb5IgJEwGQERPZJhoDaG5lsIVA6qhIgLURVvKZ2TgKwjPKy/robNmzg9sD67rJ+uwWfAgFYiiN2Qjg1NfVh395HjWEXuD3//PP473//69CMtYpYuHAhmjcvvT9dWlqabd5Lly459MfEX3b6+FEXxUnJszQb2vQcE6oxYhnu8b1d/dCZt7sL8id1KQ2/7L9P+MdaHL/AdwGX6KSuLsDB5JL9Q5skr8KZK7clu2Wno3eONeZFcPtOX0GvWT/i0g3pgnefxlUxuXt9yXyMZihyQqVWeX+sfJNaQMipNe9J9MJzHZ1CAjDjEVs1GGl0GZecZSg8VqQFRFJCJIZ1iRKeU62BIgIw9UFXqxrklwiYhwBPy7HCWVMLCPOsAcpEfQKkhajP2KwzkAAso7JKCcC3bt2y9Q3OyspCdnY2jh49ivPnz+PixYu2U8Fly5ZFgwYN0L59e7z44osO20Q4SuXbb7/FvHnzsHXrVpw9e9Z2srhGjRro3r07+vfvD3YCWOrn1KlTNoH3+++/t8XJ2kOwS+9atmyJfv36ObwgTqp/qXa06TkmJfKlrsAb6/G3P1l9ATh6TAauc/YAlbo2itsF+bgjd0yHEn0Lm0xaiTNXpQuizC/rjTu9dww61A0XDUfzcUz87T5jM67d4jsWbvYTwCI96ozeBkTzxWdnQhEBrcANCcAPSLSrUx5zX6ETwM5Yz8OW7MKCrSe4pq4T5o/lOuwdLvK7QhlfD+ww8JswXIUjYyJABIQIiD7opQdMQrhpkEUJkBZi0cIrkDYJwApAJBfaE6BNTx0B2NfTFXsndFa9oDVHpuPOPc53wGVEZa9voRwRetafG6FjPf2LwOx1+y4fbBS6jXnJgOZoVC1EBnV9DxURgMMCvJA9Ur3e5vompkx0w7/Zhflb+AQ0EoCLsu8WUxHTqAewMguS04vImwPuri44kKy/y9NIAOYsPpkTASIgiYDog96oCgHIGJQgaQ4yIgJWJ0BaiNVXgHj+JACLs6ORTiRAm546AnBYgCeyR7ZXvbJaC8CJsZWQ2iumSF5yYmAngX8ar/92EKKnMOpXCsJ3A1uY+rb3wfN3YOlOvj7UUeEByBhMX07kbBCiXwzZnHQC+AF56sMqZwXKGztkYS7Scn7mdqK3y9PYw8Hqw9O58zB6L3zuhGkAESAC3AREH/TSv23cqGmAhQmQFmLh4stMnQRgmQBpuHMI0KanjgBcOdgbm4a1Vb2o0WOW4/ptvpYEcoKKrhCI9EGtirioPSoDt+4KNksGkJJYH883+eMyRznxqTVWVGyb9WIjdDRQmwsRfsn/3Ys5m45wDX28UgC++ysJwFzQihmLPpRwdwUOplAPYIaTLoGTswLljR22ZCcWbD3J7aRbTAVM692Qe5xaA0QvaaI2OGpVhPwSAfMQEP3dM7lbPbxQ7MJm81ChTIiAsgRIC1GWp5W8kQBspWqbKFfa9NQRgLU6ARw3cQXOXbur2Yq0d3Kz1dS1OHFR/CI6I1zEJHoKwwongLt9uAm5J3/jWoPx1UKwaEDpF2ZyObWYMTt52GD8Sly+yffzb1bhSeQ1/NgqwUh7o4XFVo4+0hUVNsIDvZA1Qj/tY0RaWbAKxFQOxNKBRR+m6qMyFAURIAJ6IbDt6Hn0nJnFHU7/hOoY3iWaexwNIAJWJEBaiBWrrkzOJAArw5G8aEyANj11BOBAb3fsGtdR9Wo2SV6FM1duqz5PwQQJtcpiXt8mReabt/kwxnyfJxxDjXL+WPNWa+HxWgwUFStYbGbvAfzke+tx+NdrXGWIrRKEtDdaco0h45IEes74AduOXeRCk1CzLOb1K/ozzOVAp8YiAjA9iHBeMbceOY9nZ/ELG94ersifqH5/falkRHqgM9/Uf1oqYbIjAtYlIPqGQfuoMMx5Oc664ChzIsBBgLQQDlhkWoQACcC0IAxJgDY9dQTgIG937NRAAG44cSUuXLuj2dqz9/rtlz8ewehv9wrHYIQTwKKnMBiUAW1qYGinOsJ89D6wQ+oG7D9zlSvM+IgyWJTUjGsMGZck8PrXl2cerAAAIABJREFU25G++zQXmnZR5TH35XiuMUYwFhGAG1QOxLd0CtMp5f0q6yhGLf2Je25/L3fsGa/+w1WpgYkKwDFVgrCUHoJJxUx2RMCSBEQPH9DbLZZcLpS0IAHSQgTB0TCQAEyLwJAEaNNTRwCuVsYHG955UvU10ebddTh6/rrq8xRMYK9nZuLHm5Fz/JJwDEboVSZ6CoNB6RVXCVN7Fr04TxiWDge+ODcLGw+e54qMvpxw4XJoPDvzEFLS87mcGeGBC1dC/zMWEYDjI0KwKIlakYjwljtG9N+NSsFe2DxMTy0gxC6zq1HOD2veaiMXI40nAkTAxARE24/FVQvBYmqzZeKVQakpSYC0ECVpWssXCcDWqrdpsqVNz3Epqw9bht8FK22vVYKgq0cOG7wgB0tzf1HDtV2f9sSjtu+txyHOFgCFnf/n/5qgcWRZzXIQmUj0FAaby+wnvV79NAvr9vMJwPR6osgqLDlmbf4Z9P18G5ezdnXKY+4rdAKYQaMHEVxLR1FjkdYxtv20chCWDtRP+xjRt0Nqhflj5RB9tz5StODkjAgQAW4Cor971iznh1X0gImbNw2wJgHSQqxZdyWyJgFYCYrkQ3MCtOk5Ri5yoqzAm1Y3lYu+Riu60OwJd6InuQpiaF2rHL7o21g0JE3GiZ7CYMGF+HogZ0wHTeJ0xiTt31+PA2f5egD3bxWB4U/VdUa4pppTRAA2a+9Rkf3a3hsNplogOk6m/fsbcOAsX+sYlk5UuD8yButHOGWXMVYfns5NulXNUHzZryn3OBpABIiAdQhsP3YBPWb8yJ2w3i7L5E6ABhABDQmQFqIhbJNNRQKwyQpqlXRo03NcaTkngLUSFqZk5GHmhsOaLdek1pEY1jmqyHxfZx/DyLQ9wjGE+nti+6j2wuO1GDg1Iw8zBDlrdSGgFhzszdE0ZTVOX77FNX1SQiSGdSm6jrgckLGNwMz1BzBl+X4uGomxlZDay3wtSUQE4MTYikjtFcvFj4yVIdD1o03YeeI3bmcRob5Y//YT3OPUHCCy9trWKYdPXtH3g081mZFvIkAESicg+oAp1M8T20fr+/fq0rMnCyKgDQHSQrThbMZZSAA2Y1UtkBNteo6LLPKlrsCbVq/9yzmZKrK8lwxojkbVQooMvX//PiJHZIi4s40J9vFA7lh9n5CVI3KXD/DElpHm/UX88XErcPnmXa7606v3XLgcGj/9QSb2/HKFy1mf+CqY3ONxrjFGMBbZr80qhhuhXp2mbUD+af4TwDXL+2HVm/rqnSuy9szai9sIa49iJAJGIiCyv9AJYCNVmGJ1NgHSQpxdAePOTwKwcWtn6chp03NcfjkngOOqBWPxgBaqry0tTwB7urli36ROcHFxKZGXyC+oBU6M0AtxcvpezMo8IlRPvfWsFEriEYPqjlmOa7fvcbkNC/RC9gj9XOTEFbyOjOuPW4ErnOK7WUVPkT2od3wVTDGhGK6jJeowlM7TM5F3iu/hBXOm1b+tPAxF1p5Wbwnx5EG2RIAI6I+AyP5SOcQHm4aqfxG1/mhRRESAnwBpIfzMaMQDAoYWgNkJvkOHDuHixYu4efOmpJomJCRIsiMjfROgTc9xfWoMWwY+WesPX7XK+2Plm+r3KdSyB/CTtcvh01dLvrIq+opaAa3krnXxQrMIXf+g/OWLrVidd1YoxnJ+Htg6Wt8nnIUS+9+g+mMzcOXWfW4Xh1M6w9XVlXscDfiDgIj4TgLwH/wGtKmBoZ3q0JJyAoEhC3ORlvMz98w1y/tjlQb/tvIEJiLQaHVPAE8eZEsEiID+CIjsL3pslaM/shQREXhAgLQQWgmiBAwpAG/atAnvvvsuVq9eLVn4ZYDYCcC7d/le+RUFS+PUJUCbnmO+tUem49a934UKUK2MDza8o/7T98ELdmBp7imhGHkHLU5qhriIMiWGiV5SUeBoUf+miK8eyhuOpvZyLrrz9XTD3gmdNI1Xy8maTFqFM1dvc0+Z3K0eXmhajXscDfiDQPMpa/DLJWkPbQtGmfXUq8iX5EX9myC+ellaUk4gsO3oefScmcU9sx6FDZG1l1CrLOb1bcKdPw0gAkTAWgRE9peo8ABkDKaDWtZaKZStKAHSQkTJ0TjDCcD/+Mc/MGLECLDTe+z/eD5MAL53T/RsJM9MZKs2Adr0HBOOGpWOG3f5fjYKvGn1JTXhH2tx/MINtZcJWB9b9sq+vfYPU5fnY8b6Q8IxsBOJ7z/XwK5vYacKD5RzAtjb3RX5kzorHJF+3LWcsgYnOUVIFr1Wp+T1Q0r5SMZ8uxvzfjzO5djeRY5cDnRqLPIluX9CJIbTZYROqajomyN6FDZE1p4e83DKQqBJiQAReCQBkf0loWZZzOtHD5hoaREBKQRIC5FCiWzsETCUAJyZmYk2bdrYBBf2S3jlypXxxBNPoFKlSvDy8pJU4bFjx0qyIyN9E6BNz3F9okdn4Pod/lfbmUetLqoRuYBLZEVWCva29ROzJwArcRFd/UpBeO+5BqgVFiASnupjpqTvxUzBHsAhvh7IGWPeFhBNU1bj9OVb3DUwuzDODURgwJq80+j3xXaukSmJ9fF8k6pcY4xgLPIlmXpRO7eyIjVrVTMUX/Zr6tzAi80ukkd0hQCkD6ITeroqJAVDBHRGQPRBGQnAOiskhaNrAqSF6Lo8ug7OUAJwjx49kJaWZhNzpk6dirfeekvXp+90XXmDB0ebnuMC1h+7HFduiZ10j68WgkUDmqu+OkR6gIoGtWRAczSqFlJi+NSMPMzYcFjU7cNxgd7uWJTUHLXD9ScCf5V1DKOW7hHKMYydnh7ZXmisEQY1mrgK56/xt4BwcwEOTX7KCCnqNsZ1+87i1c+2csXXv1UEhj9Vl2uMEYxFRDi25+wa19EI6ZkyRpGaJTwWinl/Mb4A3LpWOXzRt2RPfVMWmpIiAkRAiIBoizV6w0AINw2yKAHSQixaeAXSNpQAXLFiRZw5cwbdu3fHokWLFEifXBiVAG16jisXO34lLt64I1TamMpBWDqwpdBYnkFaCsCOLkz6OvsYRqaJiaPFc2Ungb8b2EJ3D6SGLMxBWs4vPKV5aBvg7Y7dJhaZRE8Au7sCB1NIABZaVP8bJCIAx1UNxuLXW8iZVpdjRcREOgHsvFKKnmzTqr0SDxmRtdctpiKm9Y7lmYZsiQARsBgB0bfPtLqHxGLloHRNSoC0EJMWVoO0DCUAe3t7486dO/jkk0/wyiuvaICHptArAdr0HFcmanQGbgi2gIiPCLGdZlX7o1ULCJZHp7phmPliXImUpmTkYaYCJ4ALHDs6aaw2y0f57zw9E3mnrgiF4OPhhryJ5r0Ert0/1+HguevcbLzdXZA/qQv3OBrwBwERAdisLUlERDjqAey8nybRk22hfp7YPlpfb1SIrL1ecZUwtWeM8wpAMxMBIqB7Aj1n/IBtxy5yx1klxAcbh6p/ETV3YDSACOiQAGkhOiyKQUIylADMev6eOnUKCxYswLPPPmsQxBSmGgRo03NMNXL4MtwXuwMOsVWCkfaG+qfsEqauwfGLN9VYGiV8Bnix16U7lDidq0QP4MKTOTpprEmSDiZp8+46HD3PL3Iyd94ersifaN5L4Dq+vwH7zl7lLo8bgENT6AQwN7hCA9bmn0Hfz7dxufB0c8H+ZPMJ7yIi3KL/a4L4yLJc/MhYGQKil4fq8dS2yNpLqFUW8/rSJU3KrCbyQgTMSaBJymqcEbhjQY9vSpizQpSVGQiQFmKGKjonB0MJwE8//TQyMjKQnJyMYcOGOYcYzaoLArTpOS6DyJe6Am/tospj7svxqtf4xblZ2HjwvOrzFEywOKkZ4iLKFJlP9Iu8o6D7NK6Kyd3ra5aTlInap27AgTP8IifzHR7giSwT9wCOn7QKv17l7wHM2BwlAVjK8nNoMzvzEFLS87l8uAA4YkLuIvu1Hh82cRXTwMaiDw4rh7ALSdvqKnORtVcrzB8rh7TWVR4UDBEgAvoi0GLKGvx8if+QB/UA1lcdKRp9EyAtRN/10XN0hhKA2QVw7CK4+vXrY+fOnXrmSrGpTIA2PXUE4MSYikjVoL/f4AU7sDT3lMqr5A/3ibGVkNqr6GurWw6fw3OzsxWLIal1JIZ1jlLMnxKO+n2+BWvyfxVy1eqxUHyps0uLhBJxMKjRhJU4f12sVzYJwPIq0Wf2j/jx8AVuJ2bkLiLC9Y6vgik9HufmRwPkExBtHVQtxBsbTCAAR5b1xdq/PyEfJHkgAkTAtAQSP9qMnBOXuPNLqFkW8/rRGwbc4GiAJQmQFmLJsiuStKEEYJYxa/2wZMkSvPXWW3j33XcVgUBOjEeANj2VBGA7Qqkaq0OOMCkST1SFAGQMSigyNGXZXszeeETEnd0xSQmRGNZFXwLw1Iw8zBDsc5wYWxGpvcx72U/shJW4SAKwYuufx1HLKWtwUuB0EAnADyhr9aCOp6ZWsf0q6xhGLeW/PDQ80AtZI9rpCpPIwwfq0amrElIwRECXBEQvWSYBWJflpKB0SoC0EJ0WxgBhGU4AvnXrFvr164f58+ejdevWGDx4MJo3b46yZakfngHWm2Ih0qanjgDcO74ypvRooFidHDnqkLoB+wVbE4gEZ6+vmBwB0F4Mj5Xzxeq39HUySvTCIpZfn8ZVMLm7eU8ZNk1Zg9OX+V9R9HJ3wT66BE7kx/DhGNH2GyQAP0DYulY5fNG3sawa0GAxAkMW5iAt5xfuwQHe7tg9riP3ODUHiAjA5fw9sXWUvi6zU5MR+SYCRICfwP379xE5IoN7ILWA4EZGAyxMgLQQCxdfZuqGEoDd3Nj1Ow8+v//+e4lLnUpj4eLigrt375ZmRn9vAAK06TkuksiXugJv3WIqYpoGLSDkXE4msjzt9S2sOTIdd+4J3pZnJwh/LzfsGd9JJDzVxrB9svrwdCH/Zu8z2mlaJvJPX+FmE1spAGl/LXqanNuJxQfUG7scV2/d46Lg5gIcmmy+y/dE9mt7bzRwwSRjYQKdp2ci7xT/vuHj4Yo8nV2qKbL2fNxdkTfJvJeDCi8MGkgEiEARAiL7S3SFQKQPakUkiQARkECAtBAJkMjELgFDCcCurq6yysgE4Hv3+L50ypqQBqtGgDY9dQRgrW747jwtE3kC4pvogrJ3uV2tkem4raAA7O3hinydfcFnvER+CWfjlgxojkbVQkSR637c4AU5WJrLf5Kva4NwTO/TSPf56TnAx0Ysw937fBF6ublgX3IXvkEGsBb5+aRTUs4rrKgA7OkK7E/R1wMMkbXn6gIcNuGDGOetKJqZCJiTgMj+YvbWY+asNGXlLAKkhTiLvPHnNZQA3KZNG+5Tv8VLtG7dOuNXjTIAbXqOF0H1Ycsgeq5Vq5NlQxbmIi3nZ81Wcv+E6hjeJbrIfI2TV+HslduKxRAe5I2s4fq65V1UAPZip7wmdITch26KwVXBUfahc+g1h/8SQHr9Xn4xRARgPZ6glE9C7AGNVg/qlMjPbD5E/+3y9XDFXp09IBQRaDzdXLDfhA9izLZOKR8i4EwCom+fTepaF39uFuHM0GluImAYAqSFGKZUugvUUAKw7uhRQE4jQJueY/Q1hi+D6MHWSkHe2KyBiLn1yHk8OytLs/Vj75fK7h9two4TvykWQ7eYCpjWu6Fi/pRyJPIln829JKkZGkWUUSoM3fnZcvg8npvNvwa1ekiiO2AKBlR3zHJcu833No6fpxt+mqCvFitKIBH5+ezaoAKm99HfXqMED7372Hb0PHrO5N839Ng7XGTt+Xu6Ys8EagGh93VK8REBZxIQvX9CqzZ0zmRDcxMBpQiQFqIUSev5IQHYejU3Rca06TkuY/ToDFy/w/l+dSF3h1M6q37yU/RLtOjitXezcLv31uHgr9dFXZYYl9y1Ll7Q4ckFkS/5LLnE2EpI7RWjGB+9OZqSkYeZGw5zhxVVIRAZ1KOOm1vhAZ2nb0DeqatcPvT4Cj1XAg6MRX4+20eVx5yX45WYnnxwEhA92abHE+wia6+Mryd2jKFL4DiXDZkTAUsRmLo8HzPWH+LOmX6/4kZGAyxMgLQQCxdfZuokAMsESMOdQ4A2PcfcG4xbjt9u8p2uK+xtwp/q4KUWNVQtrKj4JhpUkI87do4tegN77ISVuHj9jqjLEuP0eCpPVKxgyZm9z+jQxbuwcNsJ7vrTCRVuZCUGtPnHWhy9cIPLEbsB4PAUffVQ5UpAQQE4tmow0l5vocT05IOTALtI+LFRKzhHASG+HsgZ04F7nJoDxARgD+zQWR5qMiLfRIAI8BMY/s0uzN/C//sVXQLHz5pGWJcAaSHWrb3czEkAlkuQxjuFAG16jrFHjUrHjbuiXYABLV7x/MsXW7E676xma4f1tN1X7Oby2qPScUsGp+LBVwv1xYa3n9AsJykTyTlprdeexlLylmIjegmcXk96S8lZLzZNU1bj9OVb3OEcJQHYxqxaqA82vP0kNz8aIJ/A3+bn4Lud/JdHxlQOwtKBLeUHoKAHEQE4PNALWSPaKRgFuSICRMBsBERPAJv9zTOz1ZnycS4B0kKcy9/Is5MAbOTqWTh22vQcF7/myGW4I34A2OZYbaEl8ePNyDl+SbMVHOjjjl3FTgDXG7scV2/JBFUog1A/T2wfra9XY0UvLGJp6fHEmpILRlQApluq5Veh+ZQ1+OXSTW5Hau9L3AEpMEBEhGPTHpzUEe7u7gpEQC54CNQZlY6bAg8O46qFYPGA5jxTqW4rsvZqlffHyjdbqx4bTUAEiIBxCYj2AF6c1BRxEaHGTZwiJwIaEiAtREPYJptKlwJw3759bZhdXFzwySefPERe8OeiNSjuT9QPjXM+Adr0HNfgsRHLcFe8BbDNsdpCi9YngO31AG7//nocOHtNscUcEeqL9To7Adx5eibyTl0RyjHI2x07xxVtmyHkSKeDhi7eiYXbTnJHV7u8H1a82YZ7HA34g8DTH2zEnl8ucyM5MrmL7fcCM31ERDiWvx5bzpipLo5yiRy2DCL/vJYP8MSWkfp6QCiy9uIjQrAoSV9CthXWHeVIBIxEQLT92MLXGqNJjXJGSpViJQJOI0BaiNPQG35iXQrArq6uD7/k3bv3xwm9wn8uSr6wP1EfNM75BGjTc1wDJVobqC0AT83IwwyBC7hEV569UwUpy/IweyP/JWCOYtDjK76dpm1A/mm+y7YK8vP1dMVeE9/2Pjl9L2ZlHuFeUiG+7sgZY15hnBuIwICXPslG5oFz3CMX92+KuOrmOh0kIsIxcB6uwIEU8/VE5l4UGg+oPmwZRBoshfp6YLvOeueKrL3aYf5YMYROAGu87Gg6ImA4AiL7S4PKgfh2YCvD5UoBEwFnECAtxBnUzTGnbgVghped9CkuAMvBXtyfHF801rkEaNNzzL/emAxcvS1yRukPn2oLwNuOXkDPmT9qsojcXV1wILlziZODSl9EVznEG5uGttUkJ6mTdP3XRuz8mf+kJfNf1t8T20bp68Sa1Lyl2M374SjGfPeTFNMiNm4uwKHJJLxxgys04PWvtyN992luF61qhuLLfk25x+l5gMiX5IJ81N6n9czNWbHVHJmOO/f4JWA/D1f8NLGzs8K2O6/I2mP99PMndjLdSXxdFYaCIQImICCyv7i7AAfp9ysTVJ9S0IIAaSFaUDbnHLoUgI8dO/aQdrVq1R7+/4X/XLQchf2J+qBxzidAm57jGtQfm4Ert8QFYFcX4LDKv4BtPXIOz87K1mQhubOTcsklXx0XvaXYUdCBXm7YNb6TJjlJnSRm/EpcunFHqnkRO7OfxBg0PwffClzmxCCR8Ca0pB4Omp15CCnp+dxOArzcsFtnP2PcSRQbIPIlucAFrUO59PnHPz5uBS7fvMs9UI8PjkTXHvXp5C4/DSACliMgur/Qv2uWWyqUsCAB0kIEwdEw6FIAproQgdII0KbnmFDU6AzcuCMuAHu6uWB/cpfSSiDr7+VcTiYy8ZKkZmgUUabIUKVPANu7aE4kViXHiL6uzGJISayP55tUVTIcXfnqPC0TeafF+iPTFxR5pVybdwZ9v9jG7USLh1PcQckYINonkQRgGdBlDm05dS1OXrwh5EVv+4aoQGOvp74QEBpEBIiAaQmI7i962ydNWyBKzPAESAsxfAmdlgAJwE5DTxPLIUCbnmN60WMycF1GCwgtTtnJEd9E1k1ibCWk9oopMnTSf/dg7qY/3jYQ8Vt4TJUQH2wc+qRcN4qOF/0FnAVxcFJHuLu7KxqPnpzJuSCPvqDIq+S6/LN49fOtQk7MxF70pnQGjnoACy0f2YP6fpqFtfvPC/nR29oV/fdBjw87hQpCg4gAEVCNgOj+ord9UjVA5JgIyCRAWohMgBYeTgKwhYtv5NRp03NcPdFfugo8hgV4IXtkO1WXR+t/rMWxC2KnqEQCi64QiPRBRS+WiJ+0Cr9evS3izu6Y9lHlMefleMX8KeFIzlpI7lYPLzT9owWPEvHoycfgBTlYmvuLUEj0BUUI28NBogKwHl+jl0Ni6vJ8zFh/SMiFHnvKCiVisEFm2jdE/33Q4i0hgy0LCpcIEIFiBET3F/r9ipYSEZBGgLQQaZzIqiQBEoBpVRiSAG169ssm95Vi5rVaGR9seEfdk6yNk1fj7JVbmq29qAqByCgmANcYvgwCd/k4jDmpdSSGdY7SLCcpE4n+As581wrzx0oT3/aefegces0R60NNX1CkrD7HNqICsNkuiJHTh5xEOHlrUHT0kIU5SMsxx4Mj0X8ffD1csVdnF9qJ1pPGEQEioA4Bkf3FFcDhKXTJrjoVIa9mI0BaiNkqql0+hheAL168iJMnT+Ly5cu4d+9eqeQSEhJKtSED/ROgTc9+jbYeOY9nZ2XJKqAWrQxEL9IRTaxbTEVM6x1bZHjk8GW4z3+Zu8MQ9Ngzt/bIdNwSVLl9Pdywd6K+LrUTrb+9cVsOn8dzs8V+VkgAllcJUQHYy80F+1TuTy4vM77Rck4Ae7oB+5PpizIfcfnWw5bswoKtJ4Qc6W3fEBFoWOLlAzyxZWR7IQY0iAgQAWsQEN1f9LZPWqNalKURCZAWYsSq6SNmQwrAV69exQcffIAvvvgCBw8elEzSxcUFd+/y394seQIy1IwAbXr2Ub84NwsbD4r1JyzwqMUJ4AbjVuA3gZvURRfYhD9F4aUWkUWGy+2VXDyW/gnVMbxLtGiIqoyLGb8Cl26I73mHUzrD1ZWdyTDfR84lgGbvj6x2tUUFYB8PV+SZ6OShnB7A7q7AwRQSgNVeq8X9i4r2emxfIirQaPE7gtZ1pfmIABFQjsD9+/cROSJDyCEJwELYaJAFCZAWYsGiK5Sy4QRgJvh26dIFhw4dAnvdnefDBGApp4R5fJKtcwjQpmefe53RGbh5576sooT6uGL72M6yfJQ2uEPqBuw/c7U0M8X+vmZ5P6x6s00Rf10/3ISdJ39TbI52UeUxV2c9gDu8vx77z14TzjGlWz08b9I+wEOX7MJCwZN8zzwejg+ebyTM1eoDRQVgs7U9kNOyx2ztMIzyMyEq2nu4uuBAShddpUkCsK7KQcEQAdMQ+Dr7GEam7RHKhwRgIWw0yIIESAuxYNEVStlQAvCdO3fQoEED5Ofn29Jv1aoVWrRogSlTpoCJu8899xyqVKmCI0eOYN26dbhw4YLtz3v06IG6devaxowdO1YhdOTGmQRo07NPX/QLXWFvWpxU+irrKEYt/UmzJWSvr9g7i3Lxn+0/KxaDHnvmtn9vPQ78Ki4A6zEnpQom5wQwnb6UVwVRAZjNemRyF9u/62b5iO7ZZhPDjVJP0ZNtWvy7ystQdO1VCvLC5uHqXhTLmwvZEwEioB8CiR9vRs7xS0IBkQAshI0GWZAAaSEWLLpCKRtKAP7ss8/Qr18/25e/lJQUDB061IaBvaLM/iwtLQ3PPPOM7c9u3bqF1NRUm+Dr7e2NxYsXo3176lmm0Lpxuhva9NQTgJlntX8BYyfxa4xcruk6Kp7TS59kI/PAOcViiAj1xfq3n1DMnxKO2ry7DkfPXxd2FeTjjp1jOwqP1/PA7MPn0Gu22CVwWvyM6Jmd3NjkCMAL/xKPJo+VlxuCbsaLinAkADunhMIngN2AAzrr2Sy69sr4emDHmA7OKQDNSgSIgO4JtH1vPQ4JHD7wcAUOUGsj3deXAtQHAdJC9FEHI0ZhKAG4a9eu+P77722ngHNych7yticAF/zl/Pnz8cILL6Bs2bLYtWsXwsPDjVgnirkYAdr0jC0Abzt6Hj1nil3AJfrDUFwAbjl1LU5evCHqrsS4qAoByBikr0smE6auwfGLN4VzDPByw+7x5rwIbt4PRzHmO/FT6Go/JBEumgEGrs07g75fbBOKtHKINzYNbSs0Vo+DREU4b3cX5E/SV0sBPfJVOibRHsBe7i7Yp7N6ia49PeaidJ3JHxEgAuIERE8A+3q6Yu8EdVvQiWdFI4mAvgiQFqKvehgpGkMJwKy9wy+//IJx48Zh9OjRJQTgJUuWoFu3biX4t2vXztYSYsyYMdQCwkir8xGx0qZnbAF48IIcLM39RdPVWFywqzsmA9duy+uXXDiBbjEVMa13rKY5lTZZ7ISVuHj9TmlmDv/ezLe9J360GTknxF5RZMBIABZeVpideQgp6Q9aOYl8zMReVISjL8oiK0f+mOHf7ML8LSe4HelRNBVdez4ebsibaM4Hg9yFpQFEgAiUICDaA9jH3RV5k0gApiVFBKQQIC1ECiWysUfAUAKwr6+vrbXDV199hT59+jzMx93d3XYh3Ndff43evXuXyPPDDz/E3/72N8TGxmL79u20EkxAgDY9+0UU/UJX3JvaAkvrd9fhmIzWBCJLuHhOtUYuw+17Ip7sj0nuWhcvNItQzqECnmqNTMfte3yXZRaeNjzQG1kjzHPasnBuT763HocFXlEs8GG2XrQKLDfJLl7/ejvSd5+WbK/1/iQcmMBA0T3b38u3iAcqAAAgAElEQVQNe0x6Ol8Ao2ZDRE8AswAPTuoI9vuqXj6iay/Yxx25Jm0NpJfaUBxEwMgE7t69i8dGreBOgXX3P2yyPv/cEGgAEZBIgLQQiaDIrAQBQwnAPj4+uH37NhYtWoTu3bs/TCYkJASXL1/G+++/j0GDBpVIktn36tULoaGh+PXXX2kZmIAAbXr2iyj6hU5rgaXRxFU4f+22piuxuABcf+xyXLmlnAKcGFsRqb30dQL4sRHLcFfGIWcz93qUewJ4cVIzxEWU0XQNm2Uyuf231X5ApSVn0T3bzP25teTPO5doD2A2T9cGFTC9T0PeKVWzF117tcv7YcWbbVSLixwTASJgbAJyLnpe1L8J4quXNTYAip4IaECAtBANIJt0CkMJwAUtID755BO88sorD0tSt25d5Ofn47XXXsPMmTNLlGratGl488034enpiZs3xfthmnQNGDIt2vSMLQDLvZxMZNEWF41ixq/ApRt3RVzZHRNdIRDpg1op5k8JR3JF7jJ+ntgx2pyXZ3754zGM/naPMGY9tvwQTkbjgX1m/4gfD18QmpWdEDoy5SmhsXocJCrC+Xq6Ye8Eeg1f65qyt82qD08XmlZvFxyJrr1KQV7YPLydEAMaRASIgPkJdEjdgP1nrgol2qBSIL79q75+lxZKhAYRAZUJkBaiMmATuzeUANyhQwesWbMGw4cPx6RJkx6WhV3yxi57q1SpEo4cOVLiFbuWLVvihx9+ABOQjx07ZuJyWic12vSMLQAPWZiDtBzn9gBuNHElzl8T749bvAJRFQKRoTMBuOuHm7Dz5G/CG0OIrwdyTHrb+52791Bz1HJhNlXL+CDznSeFx1t5oBwBmHGjE8BAWT8PbBvdwcrLyGm5iwqnelu7onl4u7sin/p0Om390cREQO8EYsavxKUbYr9fu7kAhyab5yGv3mtF8RmXAGkhxq2dsyM3lAA8duxYTJw4EW3btsWqVasesito8eDi4oI///nP+OCDDxAUFISrV69i5MiR+Ne//gX2d0wonjdvnrOZ0/wKEKBNT10BWO3+pluPnMezs7IUWAnSXRTPKXrMclxXsAlwYkxFpOrsErieMzZj2zHxi84qBXtj8zBz9gCWKwAHertj17iO0hcgWT4kQC0g/lgMoiJc5RBvbBpqzp9Nvf+oiNbMLAKw3vLQ+3qh+IiA1QjIbfNmpoe8Vqs95asdAdJCtGNttpkMJQCzU7zsNK+XlxdOnz5tE3nZ5969e3j88cdtbSDYh12ywfr9nj171nY5HPs/Dw8PZGdnIyYmxmw1tGQ+tOmpKwAvfK0xmtQop9ra2nrkHJ6dla2af3uO//N/jdE48o+cao5Ix5374hekFZ9j0jPR+HPz6prmVNpkTVJW48zlW6WZOfz7mMqBWDrQnK/ibTl8Hs/NFn8IEejlhl10CZfQ2qJL4B5gk9NOoHKwNzaZ9OGM0KLScBAJwOY6ha/h0qGpiIAlCMh9yKv2IRRLFIGSND0B0kJMX2LVEjSUAMwo9O3bFzdu3MAbb7xhE4MLPvv27cOTTz6JU6dOlYDFBOFZs2bh1VdfVQ0kOdaWAG166grANcv5YdVb6l3yMmRhLtJyftZ00dQI9cGat/94Zb/myHTcuaecANzqsVB8+ZemmuZU2mQtpqzBz5fE+56buc/t5PQ8zMo8XBpCh38fHuiFrBHUB1ME4OzMQ0hJf/DAVuRjltNBci4UqxjkjR+G0wlgkfUjZ8z9+/cROSJD2IWe1q4cIftwSme4uroKc6CBRIAImJfAlsPn8Nxs8UMei/s3RVz1UPMCosyIgAIESAtRAKJFXRhOAH5UnS5fvmxr98DaQ7ATwn5+foiPj8fAgQNRr149i5bYnGnTpqeuAMy8q/lFtfP0TOSduqL54iycU+yElbh4XaxHmb3Ag7zdsVNnLQG6fbQJuSfEewDHVAnC0jf+eNCmecFUnHDo4p1YuO2k8Ay1wvyxckhr4fFWHrgm7zT6fbFdGIGae5NwUAIDpy7Px4z1hwRGAj7ursijPqxC7OQM+jr7GEamiV8eqaeTbXIE4ORudfFC0wg5KGksESACJiWw7egF9Jz5o3B2rWqG4st++jpQIZwMDSQCKhEgLUQlsBZwayoB2AL1ohT/R4A2PRKARX4YCgtHycv2Ys7GIyJu7I7xcnfFPp0JMnLFihrl/LHmLXOKnIMX5GBprvhFhG1rl8UnrzZRbP1YydHa/DPo+/k24ZTNIgAP/2YX5m85IcwhKSESw7pECY+ngfwEEj/ajJwT4n3VlwxojkbVQvgnVmGEHAG4cpAXNg2nNyBUKAu5JAKGJyDn4SZLPsDLDbupxZbh1wEloC4B0kLU5Wtm74YSgI8fP26rBesBHBYWZua6UG6lEKBNz9gC8JCFOUjLERffRH9ACgtHd+7cQc3RK0VdlRinx0vB5L6uHFslGGlvtFCMkZ4cDZqfg293iq/B5hFB+HeSOU9Hq10nOgH8gLDcL8nMx8FJHW33HtBHGwJy2+r0T6iO4V2itQm2lFnkCMCs+cPhKU/pIg8KgggQAX0RkPtw090VOJhC+4u+qkrR6I0AaSF6q4hx4jGUAMz6jbm4uGDAgAH48MMPjUOZIlWcAG16xhaA5b4eJrqgCgvAck/HFo8hMtQHawv1GBaNUelxcr7kP9uwEt59zpwXZ76zaCf+s128BYS3G5CfTF9QRNYr9QB+QE1OD+AC7s80qIAP+jQUKQONESAg92LNuKrBWPy6Ph6qyfm3gaEzy0l8gWVAQ4gAEXgEAbkPN+kBEy0vIlA6AdJCSmdEFvYJGEoA9vb2Bju199lnn+Gll16imlqYAG16xhaAf//9d1Qfnq75Ci78hVXuq7zFg/fzdMVPEzprnlNpE8r5ku/PXsMb19H24M1sH7mXwJEAIr4iXv96O9J3nxZ2YBbhSYl90A3AITqJKbyWeAf2nPEDth27yDvsoX2IrwdyxnQQHq/kQDn/NtD+p2QlyBcRMBcBJR5umuXfeXNVlrLREwHSQvRUDWPFYigBOCIiAidOnMDXX3+N3r17G4s0RasoAdr0jC0As+jlfvkUWVCFf6FsPnk1fvntlogbh2P0+AurXM5LkpqhUUQZRTnpwdmWw+fx3OwsWaHosd6yEtJo8EufZiNz/znh2Q6ndAZ7I8gMH7k/nyTEabsKpqTvxcxM8d7xfp5u+GlCJ22DdjCb3LVH+58uykhBEAHdEVDi4SbtL7orKwWkMwKkheisIAYKx1ACcI8ePbB06VKMHj0a48aNMxBmClVpArTpqS8Aq31budwvnyJrqvAvlLETVuLi9TsibgwjACvxS3jXx8Px/+ydB3QV1dbH/7klvRBKEiBAEiCEIr2EXqSjNAHLp6CAFEUFC9KRDvKwooBdRAGpFqpBQgClBxAIvQSQ0CEhIZ1vncGE9Ew5c+/M3D1rvfXeI/ucs/dvn3vunf+c2efj5xpw5aSFztLSM1B1wkZFrtANijx8SncAT+teHS80C5E3uMZa8VgHaR7aLqlKd7Z5OptwRCNviiidezTvbDfvaCQioDcCtL7oLWPkr94IkBait4xpx19dCcBM/O3duzeCg4MRExMDZ2dn7ZAkT2xKgBY99QVgtU8rV/rjUM6Ey3nDWn/aH7iVmCqnG90IwPvO30Sfhcp2uXo6m3FEIzvWeCYrPSMTVcZvUNQlCSDy8CmtAeztYsLhKdortyKHBo91kOahHPLy2ih9qObtYsZhjZxur3Tu0byTN4eoFRFwBAK0vjhClilGexIgLcSe9PU9tq4EYIa6T58+WL16tSAEL168GO7u7vrOAHkviwAteuoLwGqeVq70JlrWpAGQc1dz/ambcYvjDmAtCqUjl0Vj7cF/5eLKbmfEG30SgBVPC9kdbImJw6Dv98tuzxoaYU7yWgeNwELRZLBh48zMTISMk//gSEs1m0mgseHEoaGIgIMRoPXFwRJO4dqcAGkhNkdumAF1JQDHxsYiJSUFI0eOxIYNGxAYGIiBAweiZcuWwv92c3MrNjEVK1Ys1oYMtE+AFj31BeCKvm6IeredKpNB6Wu0cp1aOSwcDYNKCc3rT/0Dt5L47QCuXc4Lv77eSq5rqrRrPXcrLtxMUty3EQUmEoAVTwvZHfx5/CoGfrdPdnujCMC81kEjfj4VTQ4VG/+4+wLGrzmiaASt5IsEGkVppMZEgAgUQUDp+qJ2GTpKHhHQOwHSQvSeQfv5rysBmB36kvM0erZ7Rsrp9Mw2PT3dfrRpZG4EaNFTXwBWU2SZs/E4FkSe4TYfxHbUorIvlrzcTDDnXQM4wMsZu8Z3EOuKTex47XLWimDBExoPAfjUtI6wWq083XKIvmgH8MM081oHjfj51OoHodfnOxEde0eRe1rJl1KBRitxKEoGNSYCREAVAkrXl5XDmqKhAQ8gVgU2deqQBEgLcci0cwladwKwkqiZAJyRkaGkC2qrEQK06OlbAB67+jCW7rlo89nkxMpAzO4mjNtg2mbcTOR3CJzVBJya+bBvrVzhMyMQF5+i2B0j3ujzEIBbVi2FHwaFK+braB0s2nYaszacUBS2EeYkr3XQCCwUTQYbNn58XiTOXE9UNKIWdrbxKD+ihTgUJYIaEwEioAoBHutL9zoB+ORZ4x1ArApw6tQhCZAW4pBp5xK0rgTgl156SXHQ3377reI+qAP7E6BFzzYC8NmZXcB23vO+eO18k+NXlljSZEYEriYoF0ezfDA7AWdmaUsA7vDBNpy6dk8OplxtjCgw8RCAGSQjslE8YYrp4Nkv/sbfZ28pGsYI4hOvdZDmoKKpJKkxjx3AywY3QngVP0nj8jbmUX5kxdAmaBRcmrdr1B8RIAI6J8BjffF0NuHIVGMc9qrzdJL7GiVAWohGE6MDt3QlAOuAJ7loIwK06NlGAH6vWyhebFmVe1b3nb+FPgv/5t6vmA6zXtvvs+Av7LtwW0wTUTZaFIB5xWhEgYkEYFHTWhWjFrO34NKdZEV9rxreDA0q+Srqw96Nedwk00MI22aRRw3g8j4u2Dm2vW0dzzMaj4cPtcp64vc3Wts1DhqcCBAB7RHgsb7Qd5v28koeaYsAaSHayoeevCEBWE/ZIl+zCdCiZxsB2OIEnFZhV+u+8zfRZ+Euu8zorNf2Z60/hkVR57j5YDE54fTMrtz649FRz/k7cPDSXcVdGVEATsvIRNXxG4iNYgLSO6g3ZTNu31dWfmVY6xCM6VJd+uAaasHjNVm6SbZtQjMzMxEyTv/rBo/yIzlLKtk2CzQaESACWiYwZtUhLNt7SbGLRvztqRgKdUAE/iNAWghNBbkESACWS47a2ZUALXr58fMSE/L2rMYPMF67A+ROQhYTr913WT5osQYwrx3Ap6d3gsVikYtbk+1IALZfWsImrEdy+gNFDrQKKYHFQ5or6kMLjZUelEMCsO2zaISc8foOVuP3ge0zSiMSASLAk8Co5QexJvqy4i5pfVGMkDowMAHSQgycXJVD05UAHBISAnaQ26JFi9C+vfjX56KiovDiiy8Kbc+cOaMyUureFgRo0ctPefeZ63j6yz3c8avxA4zH7iMlgbKYeAvmbhYnxEzX1g7gXp/tRPRFZSfWM87dapXBZ883VoJcc21T0zMQOmGjYr/U+HwodkrjHVQZtw7pmcqc1OIDFzkRGUFMlBO3ntsYIWe8HoDS+qfnmUy+EwF1CIxaHo010f8q7pzWF8UIqQMDEyAtxMDJVTk0XQnA7DAqJuKuWbMG3bt3F41m06ZN6NKli9A2IyNDdDsy1C4BWvTy56b9vEicVng6eUEZV2P35+wNMVi47azdJljWj0oeN/JZQZTysGD/xE52i6mggQd/vxcRMde4+GS0H+K7z97E018oL0OyaWQrVAvw4sLYUToJHrMOyvb/PiRlhDnJYw0yAgc9zX0j5IzXA1Cae3qaueQrEbANgTGrDmPZ3ouKB6P1RTFC6sDABEgLMXByVQ6NBGCVAVP36hCgRS8/15Ax66BwU12ByepeOwCfPNeAayKX7DqPCWuPcu1TSmdZojaPG/mscb1czPhnSmcpbqhuy1NoN9oP8VnrY7AoSvlDiNIeVuyd0EF4wEiXOAJVx61HWqZyCdgIc5LHGnRyagc4OzuLg09WignwyJkW5q5R4lCcUOqACBABrgSoxAxXnNQZESiQAGkhNDHkEnAIAfjXX39Fz5494eLigvv378tlRe00RIAWvfzJ4HEzV1CKTQDOzu7GNfsjlx7A2kNXuPYppbMedQLw8bMNwJOZFg/E4Sm0n5vV1VAi57srD2P5PuU7VNi8+3lIYzQOKSNlCjq0bc3JG5GYovxtHCPMSR5rUO1yXvj19VYOPadsGTyPnGlh7vKIY8PrLVC9nI8t8dNYRIAIaJzAvvO30Gfh34q91MKDMsVBUAdEQCUCpIWoBNYBunUIAXjatGmYPHkyypcvj4sX+dzwO8Dc0HSItOjZTgBmI/H+ERY+awvi7ibbbY6ZnYAzs7pxFYBZMFq4qc8JdeSyaKw9qLwOG+tz2eBGCK/iZ7ec8R6Y1w5g5lfl0u7Y8nZb3i4atr/msyNw+U6K4viWv9wITSrre07yEOHUWKMVJ8fAHfDI2YqhTdAouLRdKfGIo4ynM/aMb2+oh4N2TQoNTgQMQGDf+Zvos1B5ia2zM7uAlX+kiwgQgfwESAuhWSGXgGYF4NjYWJw/fz5XXG3atBF+ZDJBt0WLFkXGzOqbJSYm4sCBA3j//feF/921a1f89ttvcllROw0RoEVP3wJw9YkbcD9NjYIV4icpE7V53ADnHHHlsHA0DCol3gmVLbt8HIWYKwlcRinj5Yy94ztw6UsLnfCqAZwVC++HJFpgpJYPbeb+ifM3lb+N4+tmRvRkbZVdkcqM1xpE808qefn2PHJW2tOKfRM6yneCQ0secTA3Vg1rigZBJTl4RF0QASJgBAK8SkDUDfTG2hEtjYCEYiAC3AmQFsIdqcN0qFkBeMqUKZg6dWquRDBRl11Say2ydqzNihUr0Lt3b4dJrpEDpUUvf3Z53cwVNG94HwSnBQGY7dYNHrue68ekVdXSWDyoCdc+lXTGUwBmfuhRZGLr/4HY28JheHeSUlHC3Rntq/ujZllPhE3arARvrraOvlOlMM71K5bI953d47MdOHTxLhf2i55vgE61Arj0ZY9OeK3bevxs2oM3jzF55Yz396rU2HjF0b22Pz55rqHU4cmeCBABgxIYu/owlu7h88btqWkdYbVaDUqKwiIC8gmQFiKfnaO31LQAzERgHhc7HGX06NH5BGUefVMf9iFAi55tBeC6ZT2w9o023JJdb+om3E5K59afnI5WDmvKpUZZzrG1dhDcqOXRWBPNpwQEi1NvIueJuASMWnYAx+Lu5ZsiQSXdcP6W8l2oWR1Pe7I6XmgeImcq6r4N4/zWzwdx5N/4fLHUKueND56ui1B/r+y/DV+yDxuOXOUSNyvncmqGfl8T5SXCkQDMZTqJ6oRXzjysTjg6rauoMdUw4hWHqwk4PpPvOQFqxEt9EgEiYBsCvHYAM29bVC6JJS83tY3jNAoR0BEB0kJ0lCyNuapZAXjbtm2IjIzMhYsJwmwnb79+/RAWFlYkSlYzyNPTE8HBwWjVqhVKlqTX0zQ29xS5Q4tefny8buYKS8ykJ8IwsEVlRXnLavzU5zuxP/YOl77kdlKrnBeO/MunPEKWDxYTcFpDN8K8DuLIim9a9+p4oZk+RE4mSvacvwP3021TaqSEmxkHdV6OQM5niXHu9flOJKUWfqibh7MZq19pjmoBD0XgL6LOYOb643KGK7DN1CfD0L85n7WJm1MiO+K1bpMALBI4BzNeOWOujOsciiFtqnLwSnoXPOOg+SedP7UgAkYlsP/CLTy1QPkhcFl8aH0x6kyhuJQQIC1ECT3HbqtZAbigtDBRlwnAa9asQffu3R07cw4ePS16+ScAz5u5wqbXpCdqYGCLYMWzb/b6Y1gYdU5xP1rsQEs/VNlr+TzLXPi4mnHoPe3XXGVxt5q7FRc57vAVM9e0lHsx/iq1YZzbf7ANZ64nFttVVT9PbB7VSvgO3xITh0Hf7y+2jVgDFzNwYoY+dyDyWrcdbe6JnRtq2PHKWZZvZ2Z0htlsVsPVQvvk/d2gtQNQbQqTBiMCdiQgpfySrdzkvb7Q95utMkfj6IkAaSF6ypa2fNWVAJxVEuLZZ59FaGiotkiSNzYlQIuefQRgNiqPm1XeuwNsOvmKGUxrZRJ4ixV6+CG+99wN9F202+bTQg9seEKRetI3K7vSMKgk/jx+FQO/28fTFehVgOL1+XS0ucd18kjsjFfOsoYd0jII47rVlOiFMnPe38E/D2mCxiGllTlFrYkAEZBEgL2B8+byaBwt4LDfmmW98OEz9XKVX5LUuUJjnuskfb8pTAY1NyQB0kIMmVabBKUrAdgmRGgQXRCgRc9+AnB4cAksG9pc0TzJyMhA5fEbFfWh1cZaK5PA80c4Y/50w/KY06euVvELfj3/1S7sOH3T5j6+0iYEoztXt/m49hpw1PKDWBN9WfTwveqVx4dP18WWmKsY9D1fAXjZoIYIr+ov2hetGPL6fNINsu0yyitnWR47m4GTNt7BzrNGJ4ujSmk3RLzdznZJoJGIgIMTYOJvj/k7kFxEmSs3iwlrR7TILr9kS2Q810keG09sGTuNRQRsQYC0EFtQNuYYhhWA4+PjkZ6eTrV/jTlvQYue/QRgNrLSH2M/7r6A8WuOGHJ2elqBI9O08Tp6ZmYmQsZt4M65Uw1/LOqv3VPfq0/cgPtptqn9mxfusFYhGNPVMUTgLh9HIaaAnUeFTbjqZb2x4Y2WqgjAeqzBzPPzWSfQC7+MaMX9s04d2ua71tY72MeuPoyley5yTa+tY+DqPHVGBHREgJVYCJ+1BVfjU4r1umJJN2x7p61QfsmWF08BeHDzipjw5GO2dJ/GIgKaJ0BaiOZTpFkHdSUAp6Wl4Z9//hFgVqpUCaVKlcoH9s8//8SoUaNw5MhDcSkwMBDjx4/HkCFDNJsEckw6AVr0bHNTWlhmBjYNxKQedaQn7r8W7NCoaDsfAifbeRENtbIbT02hfd2IpqgZqM3DNXneeIhIdz6T09M7wWKxyGmqqzZdPopCTJz4gxSrB3hhw8hWqgjADJxWPndik8j78zn/mTp4om6g2OHJTiYBNdaXpYMaoGnVAJkeSW/Gewcw8+DJWn749PlG0p2hFkSACEgisHJfLN5e+fB+WMy1Ymg4GgXnv2cW01auDe91Um/f73K5UTsiIJYAaSFiSZFdXgK6EoA3bdqELl26CE8xjx49irCwsFzx7NmzBy1bthR2/rKno1kXs58xYwbGjBlDM8AgBGjRy59I3j+2ipsqSn6MtZsXibMiDo4qzget/l0rO6F6frYDBy/eVQWTie0En9XV5rtKxARj689CXp+eqOWH+Q4ghLSfF4nTEj7HVf088MebbUgA/m/CqPEgTGs1yMV8XvVmo8b64uNmxqHJtjtgk3cN4KwcOtIbEHqbt+SvMQiw+9sa7C2n9Ef3ucVF1qJKSSwZ3LQ4M65/571O0ncb1/RQZwYgQFqIAZJopxB0JQC/9dZb+PDDD1G3bl0cOHAgHzIm/u7cuVP49zJlyqB8+fI4fPgw2GuWzs7OgmhcuXJlO6GmYXkSoEXP/gKwkh9jHT/chpNX7/GcEprqa9nghgivYv96pM1mReDfu8W/IigX3qi2QXijk20PLxLjK+8bDzFj5rRhL1qem62NMiBSfZdi/9jkjUhIyRDdxMvFjH+mdEbEsTgMXrxfdDuxhsNah2BMF/2U33h8XiTOSBDQxXDoW9cfc59RpzwL+y21dO9FrNx/CfH30+DtZkXfBhXwTKNAmEzskZBjXGqtL0oeqkolz0Sk4LHrpTYTZe8ob0CIgkFGRIAzATkPb9ydzTg21XYPmFjIvNfJV1sH450uNTjTpO6IgH4JkBai39zZ23NdCcDNmzfHrl27MHLkSMybNy8Xu5MnTwo7gtlu3z59+uDHH38UXsHdvn072rdvL+wKfvfddzFz5kx7M6fxORCgRS8/RN4/tsSkaeH/1UPnx8qJMc1l0//r3Yg6dUNyO700YFJIj3rl8XyTiqhfydduu2Qfe28TEpLTVcXWuaY/Fr6gjuAk13F7fBby+mpLMUcuJ6XtQsasg9RKy4zLom1nMGvDcaXDF9h+/evNUaNcCVX65t2pGjuAmY9KHs4VFuOmI3F4fVk0Ugo4cMjNasLHz9RDx5q2K2HAOxdi+1NTOJX7fSrW97x2aq2TbUJL4buB4XLdonZEgAgUQWDOhhgs2HZWEiN7PJRWY33Rytt1kuCTMRFQiQBpISqBdYBudSUAV6lSBefOncOiRYswePDgXOn55JNPBGGY7UI5f/68UPs363rqqaewZs0ahIeH46+//nKAtBo/RFr08udYjR9bYmZS9bJeaFPND+2r+6N+xRKixM53Vx7E8n2XxXSve5vKpd2x4IWGCPX3snksNSdtRGKq+B2ach0c0ioY47pqZ2eGvT4LOfm90Lg8pvaqI+rzIJe7vdvJ4dy8cin4uFmx/kicKu6bnYDTM7VZmiRvwLxrAGf1P6RZIMZ1l1+jPa+fTPwduqT4HduLnm+ATrWMLQLL2X0nZaJvfKMlwsp6S2kiy1ZNIZs5REKNrLRQIwMQYJ+tA7G3ERFzDXeSUlHC3Tnf72O2KemVH/Zi84lb+SJ+8rEAfPh0nULPERj03R5sOX5dMilbPpRWa3356aX6aFatrOTYqQERMCIB0kKMmFXbxKQrAdjHxwf37t3Dzz//DCbq5rzYrt/Vq1ejYcOGYLWAc17z58/H66+/Lhwad/269C9N26SCRpFCgBa9/LTkiDFSmIuxrVXeGx/0q1us2KnGATRi/LOXjcUE/P6abW7sc8ZY571NuKvyDuCc41Up44GZvWoJhya6CYwAACAASURBVI3Y+sTpnH5o4bPA/GG7bvo1qoB+DSuIfjhirzkqZ1y5nH3cLLh7X72d6c0r+wr1Du05B8XwZCUVQsZtEGMq2SbUzx2b32wruV3eBszHsImbkJpR/F5vF4sJMVM7GbochNrfXVYzcHI6vwcYGRkZmL3xhFC2IzElHWaTE8ICvPFU/XKY8MsxxfOjsA5WDGmCRiGlVeufOiYCWiRwIi4Bb/18EEf+jc/nXq1y3vjg6br4ec8FfLXzQrHuD2sVhDFd85fY6vDBNpy6Jr2EWrtqZfD1i41s8r247/xN9Fm4q9gYpRqwt+vOOkB5LalcyN4xCZAW4ph55xG1rgRgFxcXoZTDt99+i/79++eKPyAgQBB333zzTcydOzfX35hg/Mwzz8BqtSIlRb16mDwSQn2II0CLXn5OcsUYccTFWzHRq1NNfwSX8Sx0V7Dau6jEe2s7S8Zl3WvNUKO8r80GbT57Cy7fSbbZeFkDeTo7YdUrLVAtQP2dbAUFp5XPQk7fzCZgzdDGqF2pjM3zodaAWuScM9aKvq4IDfBGVT9PtK8RoEkRXk2GQaXcEPlOO0XpX7LrAiasPSK6j5k9a+G58Eqi7fVmOHb1YSzdc1FVt9tULYnX2ocpnq/f7DiHqb+rJ/IWBaGGnyvWv/m4qpyocyKgJQJM/H3y0+1IzRB/OFtx/revVhpfvdQkl1mTGRG4miDvXpbV4V8+pInqv0NHLT+INdHqvOV3alpH4X6eLiLg6ARIC3H0GSA/fl0JwFki7/Tp0zF27NjsqGNiYlCzZk3hqeaKFSvQu3fvXER++uknPP/883Bzc0NiYqJ8WtRSMwSMsOhlvSb2x7GriLl8G/svxuNejgOVWF3Fav5e6NeoIvo1KIef9sTi061ncCMhFeznpckJ8HK1IqikK4JKe+GXQ/9qJj95HXExm+DuYkaVMp5oEOSLx8P80HcR/90BmgWQwzG2G5htpmM5ZKJwnUAf/DyksXBQJe+rx/ztOHQp/04U3uMU1l+FEi4ILuOF6+xmxQnCzrOsusiszZ6z1zF+7TGcu5mIBw8AixNQ1c8Dl+NTcCfp0Q5RdoCJq9UMdvNSqZQHSnpYEZ+UhpPXExGflIrMB4DVYsqeXwsl1sezFQ82TjV/D2wa1caWQ6o2lpripRpOl3CzoFOtsqrsyBbz2m/emNR6TTbnOP/rEYo+TavKxtnhg0icuib+d1P5Ei7Y8e7jNtllJjsoBQ3V3gGc0zVfd6tQV1nOGwRfbz+LaetiFESqvCmVgVDOkHrQBwG2ltef9gduJ6Vxd7hv/XKY269edr81Jm1EksLSXk83CsScp/iVCcobdJePohATl8CdRVaHX7zQwCFqzqsGkDo2BAEjaCGGSIQOg9CVANyuXTtERkbmK/MwefJkTJs2TbjhiIuLQ5kyuXdYvf/++xgzZgwqVqwo1AemS/8E9L7osZ0Cw77biXN31K/Pqv9sUwSFEWD1Tl3MQHIGBBGULn0R8HWz4q2OVfFck0qFvjYvRVgUayvWrjiaehOA88bjajGhpIcz/L1d0bdhBTzTKFBW+QK2nr+5/ACOXsn/Wi57yNM2rAzm96uFfl/uw5Erj26KrWYnpHHcLVZYvpqF+OKnIc2KS2eBf686bh3Siq/+kK+tq9WEtlV8cfL6fZy5kZT996plPPDbq+E4ejVJqJF5OzEFKekPwObkveR03ExKRSkPF+FBUHG7tguax+zhIru2HC+8/qYsEP81stfbK+zhxeQna6JnvfLFiuvHLt9B1093KgmTW9unDVwChxsk6kj3BFbui8XbK/9RLY4J3cIwuGVlof/Q8eu57DIe2ioYY1U6u6HN3K04f/PRuq8GmIX/Vx+dH6N6wGqwpT71QUDvWog+KBvTS10JwPPmzcM777wj/Ph9++238dJLL2H//v0YNmwYkpKS0Lx5c0RFReXLFCv/wMpAdOjQAZs2bTJmJh0sKj0vekws6PRR/nnqYCmkcIkAESACuiXAahHK0EXtGq+bxQkpGQ+ENw/YrnpfDxcwobZiSfdCy2RoQeRn/rLatc0ql8JXL9TDP1fuYfnei/jtwCXcF5kEXzczJnd/DD3qlitWQC0qSbbYtV3U+K4WJ8zqXbtQIZj9vuj8UZTwhomWLnerCSuGNkHNwJK53OL1MEpLsZIv+iJQ3By8f/8+Wv5vB24kpmYHVsbTGVFvtRDeLGXtmSgr50GZFFJnZnSG2WxG2IT1SE7n8wk/Pb1ToYfNsfrhE1cdwE8HruVyk208+H5AXTSvVvhaKrdOsRQezLZdWBm82qYK6lfyVbSuSx2X7ImAFgjoWQvRAj9H9kFXAnBCQgJCQ0Nx7VruLyP25ctE4d9++w1du3bNlc+0tDT4+fkhPj4e7733HiZOnOjI+TZM7Hpd9NhcDRm7XnM3Z4aZGBQIESACRIAIEIEiCDibnfBis0p4p2OoUFppzobjyFFxJrull7MZPu4WpGVkIv5+Ou5zEl14JcfLxYSy3m5ISEnD9YRUaMw9xWG6W83IyMwUfi95uFjwdMMKeKdTqCCC5bxyCnhZO8rZ39mhhL4ezsJZBHUDvbF070V8//cFXLubLPTp42ZFtQCvXA8/WDu2y/vH3RcRc+Uu7qdlgs0Xb1cr7t5PQ0JymvD6fUbmw13r7HEKOyjRZHKClZW6crbA1dksjJ3zwUq9Cj6IvngHm45cwdaYazh7K0koBcUebrg5m/F8kwp4t3NYdmw5Y7p1LxlX7qYgLj4Z6ZkPBL/7Nnj0xgKzLcrneynpwpsGni5mwSd2v5RVlomVGWsUVBIXbyXi9PVE3LiXAvZw68rd+4iLf1huLOfl7AQ4OQEpOR68sDcp+jetiNGdquHgpbtYsisWe8/dwFU2Jwt4QMNiZpezwMgNLzULBitJwPgw7sfj4gWmrlYL7qdl5IuZ+Z8VL7NlV6ifJ/y93bD77A1cvJ2E+OR0oawU+w9708LH3fowN1YTSns4IyElA5du30dqeiYSUgo+kJTNsuLe0QsL8MT0no+hz8K/Fc/34jrwcTELPFJFPvQqrj/2d28XExqHlEHl0m7IhBO2Hr+GuLvJwjhiXk5hB8uZ2Hy6l4zk1Excu5cizLX7qemi2ovxUYwNm7OVy7gh9ub9XHOTtWWCdVkfF3R9rJzwOWWf4xLuzkIpOnaxt0XYupGclolbiam4Fp+MpLQMYe6wB4/s85mzfFnW4bLFPTgozO+sdpuPxmH/hTvCfLWYTPDzckGfBoEI9ffEnyeu405Saj4/s/6NrWn1K5YoVPQW+3YMy9+Jq/ew6sAlxN9Pg3eetYXFUJC/ZicnYU0u6+MKZ7MJNxJThBjYuljK0wVVyrijQikPXLqVhDv/8c5ah5ftu4QV+y4Ka1BKGjuY1Jz9GfRysaBn3XKCsL9s32VhLWDj+3m5opSnM1ws7MH1wzW9sPhzrody2ouZb1qx0asWohV+juyHrgRg4YfZ/v3o2bMnLl9+VFyeLcYTJkzAlClT8uVy5cqV6Nevn7BIbtu2DS1atHDkfBsmdr0uepFHYvHiEvVeEzNMgikQIkAEiAARIAJEgAgQASJABIgAESACKhFgD6UW96+DFtWLL7GkkguyutWrFiIrWGrElYDuBGAWPXsdZ/369Th9+jQ8PDzQvn17hIWFFQjm008/xYEDB4S6fosWLSr0VReuVKkz1QnoddHTwuu0qieHBiACRIAIEAEiQASIABEgAkSACBABIqATAptHtUKov5cuvNWrFqILuAZ3UpcCsMFzQuGJIKDXRY8EYBHJJRMiQASIABEgAkSACBABIkAEiAARIAI2JLBpZCuhPJDWL71qIVrn6gj+kQDsCFk2YIx6XfRIADbgZKSQiAARIAJEgAgQASJABIgAESACREDXBHxczTg4uZPmDxbUqxai68lhEOcNIwDfu3cP7JA4Ly8veHp6GiQ9FEZhBPS66JEATHOaCBABIkAEiAARIAJEgAgQASJABIiA9ggsf7kRmlR+eFCgVi+9aiFa5elIfulWAE5OTsb333+PVatWYffu3WACcNbFBOAmTZqgb9++eOGFF+Dq6upIOXWIWPW66JEA7BDTk4IkAkSACBABIkAEiAARIAJEgAgQAZ0RKO/jgp1j22vaa71qIZqG6iDO6VIA3rZtG55//nn8+++/QpoePHiQL11OTuxMRyAwMBBLlixBy5YtHSSljhGmXhc9EoAdY35SlESACBABIkAEiAARIAJEgAgQASKgPwLnZ3fTtNN61UI0DdVBnNOdAPznn3+ia9euSEtLyxZ+3dzcEBISIpR+YDuBz549i/v372en0NnZGRs2bEDbtm0dJK3GD1Ovix4JwMafmxQhESACRIAIEAEiQASIABEgAkSACOiTAAnA+swbeV08AV0JwEzcrVy5Mq5fvy5E1q5dO4wbNw6tW7eG2WzOjjYzMxORkZGYNWsWtmzZIvy7n58fzpw5Aw8Pj+KpkIXmCZAArPkUkYNEgAgQASJABIgAESACRIAIEAEiQAR0RYAEYF2li5yVQEBXAvC8efPwzjvvCKcyjh49WhB4i7uYQDx79myhzdy5c/Hmm28W14T+rgMCJADrIEnkIhEgAkSACBABIkAEiAARIAJEgAgQAR0RIAFYR8kiVyUR0JUAzEo4sPq/DRs2xJ49e0QH2rhxY+zfvx+tWrXC1q1bRbcjQ+0S0KsAvO3oRQz44bB2wZJnRIAIEAEiQASIABEgAkSACBABIkAEHJCA1QycmkE1gB0w9Q4Rsq4E4LJly+LatWv43//+h1GjRolO0EcffSTs/GVlIOLi4kS3I0PtEtCrAMwOLAwZux75jy3ULmvyjAgQASJABIgAESACRIAIEAEiQASIgNEJvNyiEsY/UUvTYepVC9E0VAdxTlcCsIuLC9LT07F8+XL06dNHdIpWrFiBp59+GuwwuOTkZNHtyFC7BPS86J28moCOH0ZpFy55RgSIABEgAkSACBABIkAEiAARIAJEwMEInJnROdf5UloMX89aiBZ5OpJPuhKA2Q7emzdv4pNPPsGrr74qOk+ff/45RowYgdKlSws7iOnSPwG9L3on4hIwcul+xFxN1H8yKAIiQASIABEgAkSACBABIkAEiAARIAI6JvBsfX/M6tdQ8xHoXQvRPGADO6grAbhp06ZC7V9WCzgiIkJ0Wjp06IAtW7agSZMmYB8WuvRPwAiLHisHcSD2DiJiruJOUhpKuFvRoYY/6lUoIRxayC5ms+/8LXy69TSOXo5HxoMH8PNywUvNgvB0owowmUy5ksnsdxz/F4OWHEJqBhWa0P9Md6wI2KxnU9oJTgj0dUOnmv7oVKus8JlgV97PS/vqfniQ+QDf7TyLjUeuId2xcFG0RIAIEAEiQASIABEgAkSACHAicG5W1+z7cE5dqtKNEbQQVcBQp8US0JUAPHnyZEybNk34UC5atAiDBw8uNsCvv/4aL7/8stBm0qRJYH3QpX8CtOiJy+Hg7/Yg4vh1ccacrVwtJoSU8UCrqqXRsVZZ1A30QfTFu4LgferqPeG/HfVyNjshI/OBsC55uVrwdMNAPF7dD3+euFHow4AsVsU9OMj593WH/kXs7ft2wczE3Cp+HhjYPLjAhxVqOjVnQwwWbDur5hDUNxEgAkSACBABIkAEJBOY1asmnm5UEREx1zDkh/2S21MDIkAE1CGweVQrhPp7qdM5515JC+EM1IG605UAzMo3VKlSBYmJiYJwMnToULz77ruoWLFivpTFxsZizpw5glCcmZkJT09PnDlzBmXKlHGg9Bo3VFr0xOV25LJorD34rzhjDlZsF/PSwY1RvdzDHZuFXUykDB67nsOI+upi3YimqBlY0mZOz1h3DF9uP2ez8dhALmYnrHmlKWqU97XpuDkH23/hFp5aoP23PZzNJvh7u+CVNiHCzWDWjn72+dh/4TZ+3B2L43EJYGJ6NX9PNA4uidhbSbhzPz3fGwMFPRhgO6TZiZMRx6/le7DAeBX3BkJxCawzcR3uphVnlfvvlUq64eLt+8i00wsK7s4mVPP3Qt+GFRDq74ktx68X+9BFTIRZOVuy6wKiL97BveR04eFO/Yol8Hx4JdSr+PDzkJO5t6sZi6Js+/kUEwvZEAEiQASIwCMC7k5AEqfvrNGdquGVtlWyO990JA7Dluynw6FpwhEBOxIo7WbCT8Na6Eb8ZahIC7HjhNH50LoSgBnrxYsX48UXX8zems+E4NDQUOE/Hh4egjh88uRJ4T/shoz9h9l89913eOGFF3SeLnI/iwAteuLmwqjl0VgTrb4A3LteuWyRI6t8RXEeBo1ZV5yJof4+6YkwDGxR2aYx9fxsBw5evKv6mCYnoE6gD8Z3rY4GQSXt/uqUVh8wsJ3fveqVx9ONK+Yq9aJ6glQaoNdnOwWxU8rF3giIOnVDShMutq+3q4yR7UPzlc3h0rnMTrTwoII9XLCaAU8XqyBAuFqcYDGbhYicLSZBxD51NQGJqZmiotw0siWqBXgXa5uWloZnvtyD/bGFzx9fFxOWDmuGsLI++fr7evtZTFsXU+Q4JdwsmPxkDVQs6SE8BDl88Q52nrlZrG8hJZ0x9+mGwlsqtxNTkZKeiQeZmbh8Jxn7Y2/b7eFFQY7XLucFbzcrTl67h7v305GRkQlXqwmZcEJqWgbSOYlWxULjZMDmY8WSrqhb0RdODyAwj72dBLOTEzxdLChbwg3lfFzh425FpVIeiL2ZiNtJaUhOy8CtxBScvHoP1xJSCsyR2QTUr+iLdzuFwsnJhD9iruLklXgcuRKPO4mpyHRygsXJKfvNJTaPP444gfO38h8ezR7elPZyhYvZBD9vF5TycIaL1YwS7s5CKa+sN57+OBaHM9cScSMxBa4WM05djceNxPxPzdh3qJeLBcFlPBFUyk14gMTe3klNz4S7sxmhfp4I8HHD7nO3EC88XDKjcZAvjv0bjwMX7yIpNSNfBli8LB6rxYyyPi54PMwfaelp+P3wVVy9l5rLPquYGGtjNZuEeyf2llJ6pvAMUbhcLCaU8rDC280ZNxKSkZr5AGkZD+BmMcHN2YzktHQkpmQiJSNTyB0r55SzPfv+y1majMXM/q1iKQ/ULOsNF6sJKekPhAee7H/7uD3M8YUb93DmepLA0NfNgpv3UnH2RiLup2YIvlnMJlhYAA8eCOs7Y/bAyQnuVhNaVSklcDx+9Z4wJzyczcIbVyv2X8LNAvJQ0DTe+EaLXGtQVmm2yb8exbErCZJmfoC3C/4e+3i+30hso9KyvZfw875YXItPwf20DLhazWDzjP03i5mVikvNyICFidEy6125WyDM7xNxiUgrYG1gffu4O6OUpzMCS7jgVmI6LtxKEuaCsxkILOmBSzcTcSc5XcgtyyGbF9UCvPBU3XL44/h1HP334ecp/4yUhEoVYz8PC24nZwjztrCLTSVWhY/FVdXfU+BxLT5ZmG+MQ1pGJu6nsQ/GA2Hem50gfCbvifyOzDluOU8TUjJMuHlfWkKZj6U9rEhKy8B94fsJgh+uzmZh/rPPmZyl32oCKpV0xfV7qYhPzszuQyjP9rAyofD5ZJ8lcb8IclN2NQHJhTR0tzrBw8UifDZS0x8gMzNdSATzQ+zF1gH2W4Z9bjydnXD6+n3kTct/YQhdWi0mYe0Z3zVME/cuYuPMsiMtRCoxss8ioDsBmDnOxNzXXntNEHuFxei/eqk508q+oNnFROH58+djwIABlHUDEaBFT1wyx6w6jGV7L4ozlmHFvkg3yXxdxpEEYLbDc3Tn6jIIK2vy+LxInLmu7kGDT9UNwLxnGihzVIXWP/11GuN+PaFCz9K7rFvBBxM0Io5L977wFj/uvoDxa45I6rJXvXI2eSiV5VSNAE989Gx9Te7qmL3+GBbaaAdwx+p+GNa2iqwHDyevJqDbx1Fg97yFXUwyXi9S/M37Wy3vbvewAC88H15R2DVd1APFjIwMzN10EqujL+FeykO5IagUKztUSig7lLOeftaYTGj5OvIEZmzOXyKmjKcVUW+1hJubW6Fxtp67FRduJkma82oYh5R2x4LnG4gS2wt7O8CWb0nM6RmGfk1CbPJwsLgySVLywbMvNi7v/qTEQraPCLA17YlPthd5VgYTk9a9XvQDLbZ7d/iS/aLEMCZIrx3BZ4eh3N/PZ2d2sclD0Nbv/4kLt9QvP2Y1OaFb7QD0bxqEuhVKZJeZK+xcFXt9Bor73Bf3dzl+q9GnHD/UaGPk2KTwIi1ECi2yzUlAlwIwC+DixYv45JNPsHr1apw7l/8VyuDgYPTp00cQigMDAynrBiNAi564hKq5A7iEqwk/D5f/Y1buD1hxkWvDqqS7FT+KKImhlrdydmhK8cXDAhyd3k1KE5vZsh+IVcevF3ap2PPSUz0xqZyYmFZ90kZh15aYq6qfJxpU8lX1oRTzg+1UGdq6cr5DNcX4aEubPgv+wr4Lt1UfcnTnanilzaNXjuUMeCIuASOX7kfM1fwPlKr7e+Dj5xpoUmSXE2tRbTp8sA2nrt3j3W2h/Xm6mNGhuh/8vV1xNzmjwMNi5Thjy93ni56vLxzmSRcR0BIBtqaNWn4Ax67k/zzXKOuJj54R9+Awa/fud3+dFXYqs12iea/HyntjXr+63NbIKmPXSd7dP7pjKF5pV9UmKag9ZRPiJe5qlepYx+ql8cWAJlKbkT0RMAwB0kIMk0qbB6JbATgnqevXr+PKlStISEiAl5cXypYtS7V+bT6VbDsgLXrieI9afhBroi+LM5ZodXp6J1gsFomtHppr9RV9WcEU0CiohDM+eK6hrN12vHxg/cxcH4MvotQ7DO3UtI6wWq08XebaF9vl0/HDKK59iu0sqKQrvhjQmNsNn9hxbW23+WicqENs2Gvpv45oIaxHCyLPqOqm1udlVvBNZkbganyKqiwCvJzx97j2XHZe0q4bwFai/e+vhqNWhVKqzY05G4+r/jlkzn/xQgN0rBmgWhzUMRFQQoD3msa7v8JiqzdlE25LFFjPzerK5XtADO86723C3WRpZQ3E9JtlM6xVEMZ0rSmlCdkSAcMRIC3EcCm1WUC6EoAHDhwogKlTpw7eeOMNm0GigbRHgBY9cTl5d+VBLN/HXwCe1C0MA1vKr2dry91H4kjxtVIijvP0RM1XzOtX8MHqV1vwdFeVvtgunxE/7MKpm7lrHqoyWI5ObfWqpdpxiOmfvQb7+rJooVZqQVfFku74akBDQQxX+7P/TKNAzH6qjhi37W7TfPYWocapmlfe+pVqjuUIfav9VgVjeGZGZ5j/q8OsFtOxqw9j6R71ykN1f8xfKL2SdbClWnFQv0TAEQn0/2Y3ok6Kr6XfsJIvVg5vZjNUapbKCa/khWXDW9ksFhqICGiVAGkhWs2M9v3SlQDMfkiyenDz5s3DyJEjtU+XPFSNAC164tCqsQPY1QIcV/jav612H4mjxN/q/GxtlEVQ8yZfTwJnYbtyen/+F//k/9ejVuaAagHm6Zi9BssEpe//Pi8cYmM2O6FWOR+ww9fqV3p0MCDLRcjY9bIOKCkuljahpfDdwPDizDTzd7XFxPeerIEXmwdrJl4jODL4+72IiLmmWihlPMzYO7Gzav1ndTxr/TEsUrH+tJ6+H1SHTQMQAc4E9p67ib6LdonudeWwcDQMUu+NgryOjFx2AGsPXhHtnxTDlUPD0TDYdrFI8Y1siYAtCZAWYkvaxhpLVwJw6dKlcfv2bSxfvlyo70uX4xKgRU9c7tWoAXxiSnu4uLiIc6AQKzWFSUWOcWjMDvxaq5GdsbM3xGDhNv4lIBY+Xw+da5XjQMu+XahVh7pOeW/88lpL+wan4dErj12HIg7hlu25LV9xle1kjoZyDtETM67VDMx/luquimEl1UatNTXLj5k9a+G58EpS3ZJsr2Z5oL51/TH3mYaSfaIGRIAIiCPAHqS2nhuJ2FvFH0hZqaQ7It9pY7PyDyyCfedvoc/Cv8UFI8Gqgq8boka3tWksEtwjUyJgUwKkhdgUt6EG05UAXL9+fRw6dAgLFizAkCFDDJUICkYaAVr0xPEas+ow1wOXmoeUxI9DmoobvAgrI+8AXjGkCRqFlFbMiEcHS3adx4S1R3l0ld3HK21CMLpzda592qsztQTgFUOboFGwNuaAvdgWNW7o+PVFnr4ux+eqpdzwxzvt5DS1Wxu2azpk3Aau4zuxEgI2Oumdq+M66UzNEiYWkxNOTu9sk7IJau4+p92/OpnM5KauCbAzDnp+thNJqRmFxuHubMbaV5vb/CwCtc75MPKhurqejOS8XQiQFmIX7IYYVFcC8KRJkzB9+nT07dtX2AVMl+MSoEVPXO557gA2M2GBU2kDNW+ixZFRz0pLuxB55p8Re7xaKXz9kn5esS8uy2oIwAHervh7bDvaoVIE/HpTN+N2Ulpx6ZH0d72K7rzn4LFJbeHu7i6JHRmLJ6CWsME8sOWbFY/Pi8SZ64niAxdpOf+Zx/BE3YoircmMCBABJQTYGQdvrTiII5fj83VTq7w3PuhX1+bib5YjvL/bhjQPxLgn9VHfX0lOqS0REEuAtBCxpMguLwFdCcBXrlxBrVq1cPfuXURERKBNmzaUUQclQIueuMTzrAH885DGaBxSRtzAxVipeRPNxUGZnXhYnXB0WleZrfk36/JxFGKuJHDreNXwZmhQyZdbf/bsSI05aDEB699oZbcbLnvylDJ2qzkRiL2dIqVJsbZaevBSrLP/GfCeg8Gl3LBVZ7ugxbLSkh1vYYPFNrxNCN614ZsVauwADirpisjRj2spVeQLETA8gcLOOKhXoYRdH0TzXifpzQLDT2UKUCIB0kIkAiPzbAK6EoCZ10z4ZfV/2auTM2bMwKBBg2i3iwNOaFr0xCX93ZUHsXzfZXHGxVjxFlh4/ziUGqTZCdzrkHq5mPDPlC5SXVHNvvX7f+LCrfvc+uc9B7g5JqMjxch3yAAAIABJREFUNXahbxrZEtUCvGV441hNmsz4A1cTUrkFzfPtBG5OieiI9xx0tIMHRSBWxUSN7y5b527muhh8sZ1vfXhbx6BKcqlTIkAEuBDguU66mIATM7VxuDIXONQJEeBAgLQQDhAdtAtdCcADBw4U0nTq1Cns3LlTeLLp5uaGevXqITAwUPjfRV3M/uuvv3bQVBsrbFr0xOWT5w5gnjd3vHe+iaOR28rX3cr9NfRSHs7YP7GDHHdUadNizp+4dJufAMxzDqgSsIROedehfqVVEEZ3rSnBA8c1rTlpIxKLqFsolcyUJ0IxoEVVqc3sbs9zDtYKcMfvI9vaPSajO6DWd5et19Y3lu7HL4fiuKbL1jFwdZ46IwJEgCsBngLw1Cero3/zEK7+UWdEQO8ESAvRewbt57+uBGCTyZTvdRb2Y5wJu2KvjIzCi+WL7YPs7E+AFj1xOeBVA7ZqGQ/88Ra/kiv7zt9En4W7xAWhkpWnixn3UviuB62qlsbiQU1U8lh6t63mbEHs7WTpDQtpYaQb/LGrD2Ppnovc2NDrieJQsu/skLHr8UCcuSgrvbLnOQdPTu0AZ2dnUbzISD4BNU63r1LaHRFv21a8D58Zgbh4vmVYjPT9IH+GUEsiQAQYAZ4CsF6/42kmEAE1CZAWoiZdY/etOwFYSTqYUEwCsBKC2mlLi564XAz+fi8iYq6JMy7Cimf9XzYMz53JcoNju3VvJvJ7DZ35MbRlMMZ2qyHXJe7teJaA8HQ24chU7ZS3UAqL5+5L5guJH+IywrvswTMNAjC7bwNxg2vMiuccpPlnm+Tyeqia01ve369iSFQbvx4pGfwew7D656fpFW0x6MmGCDgEAZ4CMH2/OcSUoSAlEiAtRCIwMs8moCsB+MKFC4pTV6lSJcV9UAf2J0CLnrgc8DrohXftV96Hk4mjkduqTqAPDl26K6dpoW3qBvpg7YgWXPtU0lnLOX/iIqcSEEsHNkDT0AAl7miqLU8h0gLg9GyqTycmwTxFTzaenncG8ZyDdIMsZvYpt+H93WUCcGZWV0lvsimPAqg6fj3SOArAg5tXxIQnH+PhGvVBBIiAAQjwEoBdnIATs+j3lQGmBIXAmQBpIZyBOlB3uhKAHSgvFGoxBGjREzdF+iz4C/su3BZnXIQVb3GB9020nABbVC6JHWduyWlaaJtyJVzx1xjtnILe+v2tuHAriUuMvB8CcHFKQSc8a3lO714dzzej+nRi0sGz7MFnz9RGt7oVxAyrSRuec5D3Gq1JYBpwivd31/+eqoU+jWy/MaH25I2I51gC6cyMzjCb2XGMdBEBIkAE+JWAGNIyGOM09GYd5ZYIaIUAaSFayYT+/CABWH85I48B0KInbhr0nL8DBxXucm0W7IOfhvLd1arGa7TiiDy08vNyhpvFhAsc6+Oyfr1cLfjnvU5SXFHVtvWcLdxiNKLAxGuHip53oao6AQvonOcOYCPMSR5z0NfVhOj3jFOexdZzUsp4PMsXOZuBE9Ntv/uXxdv/692IOnVDSuhF2hrhs8gNBnVEBBycAM+Hm/RwycEnE4VfKAHSQmhyyCVAArBcctTOrgRo0ROHv8/Cv7DvvLIdwKemdYTVahU3oEgrNQ7SETm0YLZscEMMXXIQd5PTpTQr1tbD2YyjUzsXa2crg+azI3D5jvKDflj2TxmwxAEP8c3Pw4I9E7Uj+ttqbskdh8oe5CbHYw42reSNpcNbyk0JtZNAgOcBphteb47q5UpIGJ2f6d5zN9B30W4uHbqbgWMz6BVtLjCpEyJgAAL0PW+AJFIImidAWojmU6RZB3UnAG/fvh3Ck8XgYFSoUPyrn7GxsTh//jxMJhNatOC7i1GzWXUAx2jRE5dkpTWAq/m5YdOb7cQNJsGK5+4ACcNmm7JyBrUmb0Jiaoac5oW28XG14JCGdgDXmrwB91IyFcfYoIIPVr1qvPWTh/h2Ykp7uLi4KGbsKB2wz37YxI1ISVc+L42w65DHHHS3mnBsGu0AtsVniOd3lz3nL884pnWvjheoBI4tph+NQQR0QYDe9NFFmshJnRMgLUTnCbSj+7oSgCMjI9GuXTvhsIx9+/ahXr16xaKLjo5GgwYNhDZMPG7WrFmxbchA+wRo0ROXo8Hf70VEzDVxxgVYqfXqVWZmJkLGbZDtl5KGr7UNwVudqqPGpI1I4iwAh/p7YvOo1krc49o2eMw68DjnfWirYIztWoOrb1rojIf4Zk8RRwsM5fjQb+Ff2KPwzQQ2rt7Z8xTh9M5CzjyyVxse64bZiR3+Zt9ds7ziODWji7DJgi4iQASIACPAq9Z/rQAP/D6yDUElAkSgAAKkhdC0kEtAVwLwG2+8gU8//RR16tQBE3bFXvXr18ehQ4fA2n/wwQdim5GdhgnQoicuOTPXHcUX28+LMy7ASi1R4cfdFzB+zRHZfilpmFWvtdbEDbiXpnwXYk5fZvSshf8Lt/2BPoXx4HGDz/peNbwZGlTyVYJdk22V8inpbsaBSdop+aFJyAU49fbPB7HywGXF7qq1Pil2TGQH9JqsSFAaM1O6brBwnqwdgE+fa2DXyHjE8cULDdCxZoBd46DBiQAR0BYBXjuAVwxtgkbBpbUVHHlDBDRCgLQQjSRCh27oSgBu1KgRDhw4gLfffhtz5swRjXvs2LGCfePGjbFr1y7R7chQuwRo0ROXm5nrY/BF1FlxxgVYqSWw9Pp8J6Jj78j2S0nDrJhqTdqAe6l8BWCtHQbGawcwK5nB3qIw0sVj9yWrJR1exd9IWGwSyzsrDmHF/kuKxmpZpRR+GByuqA97N+Z1k8ziUGuttjcjrY3PY91gMZ2e3gkWi8Wu4fEQgGne2TWFNDgR0CQBXg83jfjbU5MJI6d0SYC0EF2mTRNO60oALlmyJO7evYtvvvkGAwYMEA3w+++/x0svvQTW/sYNfqcei3aADLkToEVPHFKlNYDVurl7fF4kzlxPFBcEZ6usmMImbEAyhzqkOd1Ti5dcBFXHrQOPTc5ai0suj5zteNyg0M2JvEzw2AGsxuGU8qKR34rXa7LlS7hi55jH5TtCLUUT4LFuaEWwJwFYdNrJkAgQAQkEeD0oM+JvTwkYyZQIFEmAtBCaIHIJ6EoAdnZ2RkZGBlasWIHevXuLjnnVqlXo27evsNsiNTVVdDsy1C4BWvTE5Uap0KrWjy8t7ACuMXEjktL4HQLnbHbCyRldxSXGRlY8bvC1GBcPfDx2X6r1+eARn5b7eOnbPdh64roiF43AnsccZBCXv9wITSr7KeJJjcUR4JEzV4sTjk+3/3cFj+8HI3wOxWWerIgAEZBCQOn6ooU66VLiJVsiYGsCpIXYmrhxxtOVAFy6dGncvn0bCxcuxMsvvyw6C19++SWGDh0Kb29v3Lljn9fORTtLhqII0KInChO0ugPYnjWAs25Y603djNtJaeJAirCqUsYDEW9p67AKpT/AWdh1Ar3xy4iWIgjoy4TH7ksSP+TlvPNHUTgelyCv8X+tjMCe125S2omuaCpJasxj3RjSMgjjutWUNK4axjy+H4zwOVSDLfVJBBydgNL1ZVDTCpjYo7ajY6T4iUChBEgLockhl4CuBGB2+NuRI0eE8g+sDITYi5V/YGUgwsLCcOzYMbHNyE7DBGjRE5ecmeuO4Yvt58QZF2Cl1s1dZmYmQsZtkO2XkoZZMbWftxWnrycp6SpX25aVS+KHl5ty649HR0p/gDMfVgxpgkYhxjuEg8dOPrU+Hzxyr+U+2v4vEuduKCsBYwT2PF6TZZW5z83upuV0G8o3HuvGmRmdYTab7c6Fx/eDET6Hdk8EOUAEDEhA6fqilXXSgKmhkAxCgLQQgyTSDmHoSgB+7bXX8Nlnn8Hd3R2nT59GQEDxJw//+++/qFq1KpKTkzF48GAsWrTIDphpSN4EaNETR3TksgNYe/CKOGMbCsA8hA85QVnNwKkZD8WSOu9twN1kfofAhQV4YePIVnLcUq2N0h/g7BW80zONdwAcA85j9yWJH/KmbqcPt+HE1XvyGv/XyijslX5GSQBWNI0kNzbKusHrO9gon0PJE4EaEAEiUCQBpd9ttLbQBCMCRRMgLYRmiFwCuhKAd+/ejaZNmwqn0Tdu3Bjr16+Hr69vobGzcg9dunQBa8fabN26Fa1aaUugkZs4R29Hi564GdDl4yjEXJH3qnWzEF/8NKSZuIEkWu09dxN9F+2S2Eq5ec5yBiFj1oGf/AvUKOuN9W9oq1RC6Ph1SFVQ5tjT2YQjU7soB6/BHngIIHSDIi+xPT6NwqHL8talrBGNwl7pTTLjYRQW8maTbVvxeHtFC/niIWTT3LPt3KPRiICeCCj9btPCOqkn3uSr4xEgLcTxcs4rYl0JwCzonj174tdffxUE3XLlymHMmDHo0aMHAgMDs5lcunQJa9euxfvvv4/Lly8L/965c2esW7eOFzfqx84EaNETl4A2c7fi/E15ZQ5OTesIq9UqbiCJVi98vQvbT92U2Eq5ec5yBkp/nOb1ple98vjw6brKneTYQ70pm3D7frrsHt2sZsRM6yy7vdYbKp0DdIMiL8M86m8bhb3SOUginLw5KLcVD+FUC3OXRykLN6sJMdOM+YBQ7vygdkSACDwkoPS7TQvrJOWSCGiZAGkhWs6Otn3TnQB89+5dhIeH48SJE4IInHV5eHjA09MT9+7dQ2Lio9qCbJdXaGgo2IekqN3C2k4TeZeXAC164uZEhw+34ZTMV63V/PFV+71NiE+WL0yKiz6/Vc7DkpT+OM3b+8ph4WgYVEqua6q0azBtM24myj/ozsXshBMz7H9avSpwFN6g0Kv38rMSPGYdHshvLrRUc31S6Jqk5jzWIaOwkATOTsY8hFMt5GvMqsNYtveiIoovtwjC+Cfsf5idoiCoMREgAqoQUPrdpoV1UhUw1CkR4ESAtBBOIB2wG90JwCxHTAR+8cUX8csvv+RKGROEmeCb82K7g9mBcWqJvwkJCdi8ebNQXuLAgQM4deoUWOkJNzc3YYcyK1Xx3HPPoVOnTrkE66Lm2pUrV7Bw4UL89ttvOH/+vFC/mNU7btmyJQYOHIjWrVtLmqqM0w8//IC9e/fi6tWr8Pb2RuXKldGrVy8MHToUPj4+ovvj7ZvogfMY0qInjtyg7/Zgy/Hr4ozzWKn546vq+PVIy1AqAUkPK2dMvEtArBzWFA2DSkp3SsUWbd7fivO35O0AZ25ZTKwGsHEPmFJyg8KOcDpDh2/Jmr1KuGcNqOb6JCsomY2IhUxwdmo2dvVhLN2jTDjVwtwdtTwaa6L/VUSRDmlShI8aEwFDE1D63aaFddLQCaLgdE+AtBDdp9BuAehSAM6itW/fPixevBjbt2/HxYsXER8fL4ibrBwEq/Xbv39/NGzYUDW4H3zwAcaPHy8ItMVdTLxdsmQJKlasWKTpmjVrBJGXiciFXS+//DIWLFhQ7CnSTJxm4vPvv/9eaF+M1fLly9GsWfG1Xnn6Vhyv4v5Oi15xhB7+ffaGGCzcdlaccR4rNX98VRu/Hik2FoBdLE44Mf3RbtYq49YhnWMR4OFtKuPdzmGyWKvViEepDTXngVpxi+2XblDEkuJrp5Q788Yo85JY8J1bavdmlB3AI5dFY+1BZQKwUT6Das8Z6p8IOCIBpd9ttL444qyhmKUQIC1ECi2yzUlA1wKwvVM5bNgwLFq0SHCDCamPP/64IDiXKVMG9+/fFw6fY6IvK0vBruDgYOzatQt+fn4Fuh4REYGuXbsiLe3hK9vdunVD9+7dwcpbsN3FX331lSBys4uJwF988UWhCNLT04W+/vjjD8HG399faFOjRg3cunULS5cuxc6dO4W/lShRAjt27EDNmoW/ysfTNx55o0VPHMUlu85jwtqj4oxzWHk4m3BUxcO/msz8A1fjUyX7paRB7fJe+PW1R4dAVh67Djw16GcbV8Ss3o8pcZF7W7rJLxwpHQLHfbqJ7lDpjaGn1YQjBqk9qpSFm8UJMTkebIlOAhnKImCUGsCDv9uDCJlvB2WBI4FG1hSiRkTAIQgo/W6j9cUhpgkFqYAAaSEK4Dl4UxKAFUyA4cOH4+zZs3j77bcF8ddkMuXr7cKFC0L5B1azmF0vvfSSUJIi78V2EVerVg2xsbHCnz799FOMGDEil9nJkyeF8g9xcXHCv7PSEx06dCgwArZD+JVXXhH+xkTfP//8UxCBc17M73nz5gn/1Lx5c0EELuji7ZsC5NlNadETR1GuABhUwhmRYwqeW+JGLtrqha92Yftp2x4C16N2AD5+rkG2YzzqkOaMUos7gMesOoRley8pSplRf4TvO38LfRb+TWwUEZDXWOlnb1r3MLzQrLK8wTXWSulN8pAWQRhHdVhtllWjPDjq9flORMcW/qaZGKBG/W4QEzvZEAEiUDQBpd9ttL7QDCMCRRMgLYRmiFwCJADLJQcIO2lLliy+5uehQ4dQt25dYSR3d3dcv35d+O+c12effZYt+D755JP49ddfC/Rs9erVeOqpp4S/scPw2Ic/75WRkSHsSM4Sivfv34/69esXaMd2LB88eFD428aNGwWxOu/F0zcFuHM1pUVPHMkuH0ch5kqCOOMcVqU9rNg3saPkdmIbvLH0AH45dEWsORe79tX98NWARtl98d4BvGp4MzSo5MvFV16dzNkQgwUyS4Bk+WDUH+Ejlx3A2oPK5qBR2fCaf4X1U2PSRiSlZsge5uzMLgU+cJXdoR0bKr1Jpjqstk+ekpyV8bRi7wT1vlvF0hj8/V5ExFwTa16gHa1/ivBRYyJgaAJK1kkGhtYXQ08PCo4DAdJCOEB00C5IALZR4qtXr47jx48LozFBuHbt2rlGZjWLWS1jdrED5dq0aVOgZ5mZmcIBbuxwOHadO3cOQUFBuWzZbl+2I5ldbMdwZGRkoVF+++23Qs1hdg0YMADfffddPluevvHCTYueOJJyBWBXiwnHp3cRN4gMKx6vn0odtl7FEljzSvPsZtXGr0OKfA0q1/CPlffBryOaiz7oUarvcu3llgDJOZ5Rf4SHz4xAXHyKXLRCO6OyUQRFROMe87fj0KWH5YzkXEbiruQmuZS7Bfsn5X9oK4cptRFPQEnOpveogeebBosfTCVLejioEljqlggQAYGAknWSfl/RJCICxRMgLaR4RmRRMAFNCsBTp07N9nbSpEnZ/zvnv8tNaM7+5PYhp13jxo2xd+9eoSmrA9ykSZPsbthhbawOLxN3vby8cPv27SIPeGOlJxYuXCi0//zzz8H+f85r9OjRmDt3rvBPc+bMAfv/hV1Xr15FQECA8GdWm5j9/5wXb9/ksCuoDS164kj2/3o3ok7dEGecw8rNakKMijU2ebx+KjWoDtX98eWAR4dCPjZ5IxI4KMDerhasHN4Mof5eUl1S3V5uCZCcjhlJbMsZV9jEDUhOk38KoK+bBdGTSXyTM4nfXB6N1dHyDqByYg8+Z3eTM6wm2yi5ST4xpT1cXFw0GZdRnVJaAkIru9eV1jK2mIDTM43zOTTqfKW4iIC9CCj5bmM+G/W3p73yQeMajwBpIcbLqa0i0qQAzGrpOjmx2zyAlTPIunL+u1xAOfuT24fUdikpKUL93bt37wpNr1y5ki26sv/PDotj5RzYxXbbbtu2rcghWA3hQYMGCTaszi8r0ZDz6tKli1DOgV1sN3Dbtm2L7K9ixYq4ePGiYHPt2jXhELusi7dvUtkVZk+LnjiScgVgtcUtHq+fiiPwyGpY6xCM6VI9+x/qT92MW0kPD1yUe7Gdv/P61dGk+Mti6vJRFGLipJcAycnDqD/Ca03aiHsKyhAMbRmMsd1qyJ06Dt3u7RWHsHK//NrURpqTSm6SjcRBLx8IpcKpVnKmVMgu6W7BAdp9rpdpS34SAZsTUPLdVsbTGXsnqHcOic1h0IBEQAUCpIWoANVButSsAMz4MxE4rwCsJC95+1PSl5S2rKwCO/yNXawWL6vJm/NavHixUH6BXYWVYchpz0pEtGvXTvgnVuohIiIiV38hISFCaQh2FVQiIq/vrExEVFSU8M+sDEWLFi2yTXj7JoZbQXWN87b7559/MHToUOGf//rrLzRt2lRM1w5n0/mjbTged09y3K1CS2PxwEe71CV3UEwDHq+fSvUpb41epQKws9kJJ6Z30VzZh5xc2szdivM3k6SiyrY32m7LnCA6fBCJU9cSZbOh2quy0YEE4Efs5N4ksyNnzxpoJ7T82WTblnM2HseCyDOyB9WKAMwCkDv3WNs6gd74ZURL2RyoIREgAsYmoGR90UqpHGNniKLTOwESgPWeQfv5r0kBOOcOWCZOZl3F7YwVgzFnf2LsldqwA99q1qwpHPzGLnaIW69evXJ1+8knn+CNN94Q/u2tt97C//73vyKHPXz4MOrUqSPYNGjQAPv27ctlzw6mY2Uk2MVKOHh6ehbZX+/evbFmzRrB5rfffsMTTzyRbc/bNzE8s3Z/i7FlNiQAF05Kbg3gFUPD0Si4lNgUSLZTuotK8oDsYcisrrnEWqXiqMkJODtL26/AKhU5a5f3wq+vtZKDW/Ntluy6gAlrj8j2U0tCjuwg7NSQBOBH4JXcJNMctP0EHrPqEJbtNcbudSVzb2avx/Bck4q2TwCNSASIgOYJKH3DQCulcjQPmhx0aAIkADt0+hUFr0kBWFFEGmqcmpqK9u3bZx/u1rNnz2yhNaebM2fOxPjx44V/Yv89ffr0IqM4deoUQkNDBRv23ydOnMhl7+zsjLS0h6+2s/+2WCxF9vd///d/+OmnnwQb9t/PPvtstj1v38SkhwRgMZTE2YxafhBroi+LM85hlVcsldxBMQ1YveuQcRt4d1tkf3nFEkeoj9vpg0icULDL9eXmFTH+ycdsmidbDZaeno4qEzbJHo7EN9noaAdwDnRKRDiag/LnoNyWcr9Ts8bTSs5IoJE7A6gdESACxRFQuslDK+tkcXHS34mAPQmQAGxP+voemwRglfLHBK7+/fvjxx9/FEaoXLmycAicr69vvhFziqwTJkzAtGnTivTKXgIwD9/E4KYSEGIoibPZc/Y6+n2xR5zxf1auFhOOT+8iqY1UY6U/DqWOF+Bpwa4JuQ/sUroD1GwCzmj8EJw6723E3eRHddSlcnumUQXMfqq21Ga6sP9x9wWMX0M7gO2RrLd+PohVB6Q/mGK+Bvq6Yse7j9vDbVXGlCsAUwkIVdJRbKejlkdjjcwDDF1MwAmNfGco/Q4mgabYqUIGRMBhCczeEIOF287Kjp/WF9noqKEDESAB2IGSzTlUEoA5A2XdsZ0VrD7tl19+KfTODllj5SuCgoIKHI13mQW9l4AQkxJa9MRQAuSInK4WJxyf3lXcADKtlP44lDpsvUBPrBnxqJwMaz97/TEsjHpYK1vOVd7HBTvHtpfT1GZtqk/cgPtpmbLH61G3LD5+pr7s9lpu2OvznYiOvSPbRbpBkY0OL367B5EnHpZFknotH9wITar4SW2mWXu5AnAlXzdse/fhWQB02Y7AmFWHsWzvw0NzpV6lPazYN7Gj1Gaq2BuplrEqgKhTIkAEZBNQetAz/b6SjZ4aOhAB0kIcKNmcQ9W1AMx22Z45c0aod5ucnCwKTatW6tazZOLvK6+8goULFwr+BAYGIjIyUtgBXNjF+6A1vR8CJyaRtOiJoQT0+mwnoi9KE7nY4WYnZ6grACv9cSgu+kdWvm5WRE/OfeOt1IfpPWri+aYFP9SR6p9a9mETNyBZgQBcr0IJrHm1uVru2bXfdvMicfa6/EPg6AZFfvo6fRSFE3EJsjpQuzyNLKcUNJIrAA9tGYSx3WoqGJmayiGgRDgt4WbGwcmd5QzLvc3Y1YexdI88IZt2n3NPB3VIBAxFgB6wGyqdFIxGCZAWotHE6MAtXQrAUVFRwkFpERERSElJEY2Z1ZZldR/Vupj4++qrr2LBggXCEOXLlxfE3ypVqhQ55O7duxEeHi7YMIG6uMPuvvnmGwwaNEiwZ2LzZ599lqv/Ll26YOPGjcK//fnnn2jbtm2R47MdyhcvPrwRuHbtGsqUKZNtz9s3Xuxp0RNHsvnsLbh8R9zDkawebSEAK/1xKC76R1ZWkxNOzcwtaivxwWp2wolpnWEysVth7V7hMyMQFy9+jcwbSSkPZ+yf2EG7ASrwTOkBeSQAy4ff9n+ROHdDuvhudgLOaPzgRalU5ArAq4Y3Q4NK+UtKSR2f7KUR2Hf+Jvos3CWt0X/WFhNwWiMlIJQI2Ub8HMpKKDUiAkSgQAKDvtuDLcflveXjxA5tnq3tA5Yp7URACwRIC9FCFvTpg+4E4Pfeey+7Ri4TXKVcTADOyJBfD7OosfKKv+XKlRPE36pVqxbrYkJCAkqUKAG2o9nLy0vY0Ww2mwttN3z48Owdxp9//jnY/895jR49GnPnzhX+ac6cOWD/v7Dr6tWrCAgIEP7s5+cH9v9zXrx9KxaGSANa9MSBajIjAlcTpAmAFifgtMoii9Ldt+Kiz22VV7Ab/N1eRBy/JqcrfPFCA3Ss+fBzo+Wr/9e7EXXqhmwXPV0sODIld+1k2Z1prGGP+Ttw6NJd2V6RACwbHeTuADbizkM5ArCJCeEzu0LqganyM0YtswjsPXcTfRfJE4C1NH+V1ADWUhw0M4kAEdAegVHLorHm4L+yHaPfV7LRUUMHIkBaiAMlm3OouhKAf/vtN/To0SMbASur0LJlS0HAdHFxEYVm8uTJouykGOUVf8uWLSuIv6GhoaK7YTt/t2/fLtiztq1b565XmtURE4nZjuJz5x7WLmX/nbe2MNv1+/jjDw/JadOmDbZu3VqoH99++y0GDhwo/P3FF18E+/95L56+iQZSjCEteuJIdv4oCsclvmpti5u7ORtisEDBARHios9tlfcH5chlB7D24BVJXbmYnfDpc/V1If6ywEYui8ZaBT/Cfd2tiJ6kjZqVkhIlwrjzh5E4flX6LtSsrukGRQRq/RS2AAAgAElEQVTkQkyU1AA2Gnc5ArCH1YSj09Q9qFN+do3dUskhcFraOct+twaPXS8rWVYTcEojO5llBUCNiAARUJWAknWSOWa073lVYVPnDkuAtBCHTb3iwHUlAHfo0AFbtmyBxWLBokWL8NJLLykGwKMDVvaB7cRlFxOjmYBbrVo1SV2z9qwfdj355JP49ddfC2y/evVqPPXUU8LfWNkI9uHPe7Fdzqz2cFxcnPCn/fv3o379/Ac5MbuGDRvi4MGDgh0rG9GpU/7dfjx9kwSlCGNa9MSR7Dl/Ow5eihdnnMNK7R9fSnYfSQ7mvwZ5Yxq1/CDWRF8W3R2rh7tqeFPNl33IGdCYVYewbO8l0THmNQzz98TGUQU/jJLdqUYatpm7FedvJsn2Ru3PiGzHdNDwrZ8PYtUB8Z+9nCEZjbscATiolDsi3ym6tJMOpoEuXezycRRirsirX6014VTO3GNJ8/N0xp4JxiwNpMtJSU4TAY0RUHJYJgvFaN/zGksPuWMQAqSFGCSRdghDVwJwqVKlcOfOHWHH6pdffmkHXPmHfO211zB//nzhD0z8Zbttw8LCJPvGDrFjonFsbKzQlvWZJQhndXbq1CmhRnCWsPvHH3+gffv2BY7F6hCz+sDsqlmzplALmJV4yHm98847Qi1ldjVv3hw7duwosC/evkmGU0ADWvTEUeyz4C/su3BbnHEOK7V/fCnZfSQ5mP8a5I1Jqjj6TKMKmP1UbbnD26WdkjqPzOE6gd74ZURLu/iu9qAdP9yGk1fvyRpGSzv5ZAVg50ZvrziElfvlPZhQe22yNRo5IlzPuuXw0TP1bO0qjQdAiQDsbAJOamjnrJy5xybBsFYhGNO1Os0HIkAEiECBBJT89nS3mnCM3nChmUUEiiVAWkixiMigEAK6EoA9PDzAxMglS5bg2WeftXtSJ0yYgBkzZgh+sFp8M2fOFCX+st247OC1vBc71K5r165IS0sT/vTEE0+ge/fuYHEfOHAAX331Fe7efViz8uWXX8YXX3xRKAN22B3ri4nE7GLiNGtTo0YN3Lp1C0uXLs0WfH18fLBz505BKC7s4ukbj8TRoieOYo/523FIgzuAmfdybz7FRZ7bqqCD7aT+QB3epjLe7Sz94Y4cf3m1UbrTukN1f3w5oCEvdzTVj5Ia0C1CfLFkSDNNxaMnZ0gAfpQtOevgzJ618Fx4JT2l3DC+Sn1zJGfgni5mHJnSWTMs5Mw95vyZGZ2LPKdCMwGSI0SACNiFgJLfnkNaBGHcE4Xfj9olIBqUCGiQAGkhGkyKTlzSlQBcvXp1nDx5Ej/88AOee+45uyNm9XW3bdsm2Q9WZ5fV2y3oWrNmjbDDme10LuxiQi7b4VvUQXGsLTvAjXH6/fffC+2LlYpYvnw5mjUrXszg6ZtkaHka0KInjqCcGsC22t0o9+ZTXOS5rVwsTjgxvWuuf5T6A3XV8GZoUMlXzvB2a8N2Wj85fweOXJZeBoQ5Pax1CMZ0MeZOr9kbYrBQZh3qlcPC0TColN3yqveBSQB+mEG5b0IMbRWMsV1r6H0a6NL/fedvos9CeYfAVfXzwB9vttFM3HK/g422C18zCSFHiIBBCMj9bmPh0wMmg0wCCkN1AqSFqI7YsAPoSgBmJQ1Y7d+33noL77//vt2TooYAzIK6cuWKIPCyQ+/Onz8v7HpmB8u1aNECgwYNKvSAuMKA/PLLL1i8eDH27t2La9euwcvLC+wAvd69e2Po0KFgO4DFXrx9EztuXjta9MSRazIjAlcTUsQZ/2fVPLgEfhzaXFIbqcZKfhxKHYvZ+7hZcGhy7vrWUsTRx8r74NcRzYWd/nq7Tl5NACsFEp+cLtn1lcOaomFQScnt9NBA6gOArJisZiecnN5Fl3NBK3khAfhhJuTOQSPvzNfKHC3MDyXfXVrbuS1HALbVA2KtzwPyjwgQgaIJyFlfQv09sHmUdh6SUY6JgJYJkBai5exo2zddCcDHjx9H3bp14enpiRMnToDVBKbLMQnQoicu781mb8G/d5LFGf9nZYvdjXKFD0mB5DBuVbU0Fg9qkq+5GHHU29WClcObIdTfS+7wdm93Ii4BTHT75/LDEjJir1XDmqKBQQVguUKOr5sF0XkeJojlSXYPCZAA/JCD1DI0WfOnXsUSWPOKug/paK4WTkCOsMF6Ozuzi6YOEZUTh9YOsqN5SgSIgDYJyFlfetQpi4+fzX9ouTYjJK+IgH0JkBZiX/56Hl1XAjAD/c0332Dw4MFgdXRXrlyJoKAgPfMn32USoEVPHLj28yJx+nqiOGMAFpMTTs1Qf3ejXOFDdCB5DIsStYsSR9nO33n96uha/M1CwQTPN38+hDXRl0Vj1GPdY7HByRWAS3s6Y9+EDmKHIbsCCLz180GsOiB+HmZ14WY1IcZAh8OMXX0YS/dclDxH2lf3w1cDGkluRw34EJAjbGhROJUTR0H19PlQpV6IABEwEgE560thmzWMxIViIQK8CJAWwouk4/WjOwGYpYjVomV1cO/duycclBYeHo7SpUuL2lnRv39/x8uyASOmRU9cUnvM34FDl8Tv+qwW4IlNI1uL61yBlVzhQ86QbAfvockdi3xln4mBB2LvICLmKu4kpaGEuxUdavijXoUShnrVf8yqw1i2V7zg9GzjCpjVu7Yc7JpvI3cXuq+bFdGTO2o+Pi07+OI3uxF58oZkF71dTDg8pYvkdlptIPdBWKuqpbB4ULhWwzK8X3KEDVY86NzsbppiIycOV4sTjuepp6+poMgZIkAE7E5A7gP2SiXdsG10O7v7Tw4QAT0QIC1ED1nSpo+6FIB/+uknTJo0CWfPnpUkzrD6nenp0utgajN1ju0VLXri8t/pw0icuCp+B3CYvwc22qD+llzhQ1zUua261grA5883kNPUcG1GLY/Gmuh/RcfVq155fPh0XdH2ejKUOwd93a2InkQCsJJct5rzJ2Jv35fcRTkfF/w1tr3kdlptIPchhJ+XM/aMp13o9sqrHOHUxEpAGEAA9nIx4R8DPYSx1xyicYmAkQnI/W7zcDbj6NTORkZDsREBbgRIC+GG0uE60p0APGLECOGANHaxJ4xSLiYAZ2RkSGlCtholQIueuMSEz4xAXLz4Q+ACvF2wa5z6AovcH4fios5tZeQyBlJ5jFp+UFIJCCMLwFJ3Q2exdjYDJ2doayef1Hlgb/s6Uzbj7v00yW6U93HBTgMJwHJ3SdFr+JKnDtcGjiwA+7pbED0p94GqXOFSZ0SACOiegNwH7BYTcHom/b7S/QSgAGxCgLQQm2A25CC6EoBXr16NPn36CIlgYm67du3QsmVLBAQEwMXFRVSCBgwYIMqOjLRNgBY9cfl57L2NSEgW/9DDy9WMf95T/+m7XOFDXNS5rVYNb4YGlXzlNDVcmzGrDmHZ3kui43qmUQXMfsqYJSCk7obOCe28xnbyiU6oRgzrvLcZd5OlC8BGPIBPjpjoYnbCiRldNZJNx3NDTs60uLNNThzeLmYcnqL+bwTHm1UUMREwDgG5Zd60+KaEcbJCkRiNAGkhRsuo7eLRlQDctm1bbNu2DW5ubvjtt98EAZguxyRAi564vIdNWI/kdPE75W1Z30/Ozae4qB9ZuVnNODqlo6j64FL71qO91F0ZRt49PXJZNNYeFF8OgwRgfjO+1ZytiL2dJLlDsxNwZpaxdgfJWQfLeDpjLx1EKHn+8GogJ2da3DkrJw5PZzOO0CvavKYS9UMEDElA6m/NLAhG/I43ZIIpKE0QIC1EE2nQpRO6EoD9/f1x48YNvP766/jwww91CZyc5kOAFj1xHEPGrEOmOFPBygzgjA12N9IOYAlJ4WgqtfSGkXdPD/puD7Ycvy6LLu0AloUtu9GAr3dj2ynph8Bp8SAtZSQAOSJcnfLe+OW1lkqHpvYyCcjJWWkPK/ZN1FbtcDlxuFlNiJlmnIMYZU4BakYEiEARBKT+1szqypabUCiBREDvBEgL0XsG7ee/rgRgLy8vJCUl/T97ZwJfVXXt/5WBmSTMAYFAQhkCRkBmkAREhmAHpipo1VbbR6K8ClpLGEqdmJ71Yf9PBbWTvvYhFQyllSCiEhRlDqA2AgoRQcUKRXEG8f850SBIQvbe99x79jnnez+ffvoR1l57re9a2eH+7r7ryOLFi+Wyyy7zjho7e06AQ0+tBCZv8GIhbpn+41At6zOtgnyLVZeHI7x/797n5eWDH1S7NKtliqyYNEDrQZvVOrXIYPT966Vk/1GjiGLxM2IUmE8W3bRkuzxeclA72oR4kdcDNh/Q5IzObJ4kRZOztfmxwB0CJjVrVr+mbLLo1rbph7C1E+Pl1TsRgN3pJLxAIJgETM+XpvVqyGbLPigLZoXIKggE0EKCUEVvcvCVANy5c2fZtWuXPPzww/KjH/3IG2LsagUBDj21Mpi8UY2FuGX69TC1rM+0mtA7TeaOyTJZGsg1uw8dk3ELX5APPj1RZX7JtRNlaX5/6ZCaFEgGTlI/fXizrCl9Vzu/IN5C1YYQ4QJTAbhVg9ryfMGQCHe3a7nJGd22cV1Ze8tguxIJUTQmNWvTqK4U/9Kempl+CMsDCEPU6KQKgQgImJyTTevXkM0z7fqmRAQIWAqBqBJAC4kq3kA795UAfPPNN5ePfsjPz5f77rsv0IUhuXMT4NBT6xCTf4DFQgA2fUCEWtZnWnED+Gxqu945Jr94bIe8dPD9s/7Sufl792VdAy3+OknPLyqVhcV7tVuqW6tkWT6Jr99rgzttwY//sEnW7tYfv3HnD7rIj/q1jWRrq9aa3pJq3bCOPDeVZyB4VUyT36u2zW02/RDWxofZedUH7AsBCFRNwOScTKmdIDti8CBq6gaBIBBACwlCFb3JwVcCcFlZmXTt2lW++OIL2bFjh7Rr184bauzqOQEOPbUSmPwDLBYCsOmbT7Wsz7QK8hxbEx4Vaxzxadv+o7Km9JAc/fi4NKhbQ4Z2TpXurRsEduzD6by2lB2WcYs2aCN87D/6SK+MJtrrWPANgeEL1smuQ8e0keydkxuoBzqa3sK07TapdiF9vsDk96ptArDph7AtG9SS9QWX+LyChA8BCESbgMk56Xz7bOetw6MdGv4hEAgCaCGBKKMnSfhKAHYI/eMf/5DLL79cmjVrJo888ogMHMhNLE86x+NNOfTUCnDh7U/KkY+r/qr/t700rpcoW38V/X98bSk7IuMWvaiWRARWQZ9jGwGa0C/dtPc9uezBjVocnCdUvzZnZCgEci0wmsaD7lorZYc/0lqV2by+FE3O0Vpju7HpB2FtGtWR4l9yA9ir+poIG82SasmmGfYIp6a91ym1vqyaEqyfQ6/6iH0hEGQCJudk06SasnnG0CBjITcIuEYALcQ1lKFz5CsB+Pbbby8v0LZt22TFihXlb8K7desm/fr1kyZNmijdDJo1a1boihzEhDn01Kr64p53ZMLvt6oZi8ji63pKv/apyvamhqa3L3X2C8McWx0e2J5J4Orfb5R1e97TwtIsqaZs4s2JFrPKjE1uALdrUlee/oU9M1QjhiAiprcwGQHhBn1zHybChm0P7jO9fW6bkG1eRVZCAALRJGByTqYm1ZSN/BsrmmXBd4AIoIUEqJgxTsVXAnB8fPwZN6+crzA7IrDOyxkfwcv/BDj01Gro/Ixk3fqkfPhZ9X1fv1aCvHTrcO2fKbVIzrQyvX307b2SaiXKsc/OvuEcljm2JuxZ8xWBHnc8JYc/+lwLR8O6NaRkFg8o0YJWibHJDOA6NeKl9I7cSLe2ar3pOdiobg3ZRh96UkvTuc1dWybL3/7Tnm+smebRpH5N2TKTG3qeNB+bQsBHBEwE4JTaibKDERA+qjKhekkALcRL+v7e23cCcCS4HbEYATgSgvas5dBTr8XuQ8ckd8E6OZcEnCAiRVOyY/bgL9Obb9/OelCHJvKfQzqEdo6tehdg+W0C3W5bLUc/Oa4FpnlSTdnA7RQtZpUZ37RkuzxeclDbTyzmk2sHFcEC01uYNRJE9sy+NIKdWWpKwLRmtt0AdvI3EWiSajsfFI8wxcc6CEAgJARMzhdmAIekOUjTFQJoIa5gDKUTXwnAxcXFERcpJ4fZZRFDtMABh55eEXa9c0x+/pfNsutfn5y1sGPTOvI/P+oVM/HXCcD05tu3gx/csan88Se99WBgDQERGbagWHYf+lCLReuGteW5qUO01mB8NoGb/7pDlm07oI0maAKw6S3MGvEie+YgAGs3kAsLTH932fjtAROBpnZinLx650gXSOICAhAIMgGT8yU1uZZsnG7PrPQg14fc/E8ALcT/NfQqA18JwF5BYl/7CHDo6dfEERu27T9qxW1Z01tUCMD6dWdF5QT+vKFMZi5/RQtPy5Rasn4ab060oFVizA3gb6CYvEmuWyNe/hmwcRiR9lSs1pt+e8UZsfTybfbcnDX98CEx3nkQJh8+xKrf2AcCfiVg8rutQ7N6svqmQX5NmbghEFMCaCExxR2ozRCAA1XO8CTDoefvWjtvPp0bmHve/SiiRLgBHBG+UC92xgG1m7FKi0GjuomybdZwrTUYn03gmt9vlGLNB/DVSoiTXbODd/PQ5E1ys/o1ZRNzWD350TK9AWzb3GbTD2FrJcbJLm4Ae9J7bAoBPxEw+d3Ws00DWZo/wE9pEisEPCOAFuIZet9vjADs+xKGMwEOPf/X/Xfr9sqdK0sjSgQBOCJ8oV68peyIjFv0ohaDmglxsjuAIqQWBBeMB857Rt48evY4mnO5bl4/UTbMDJ74bvImmVnULjShoQtT4TS7QxN55No+hru6v8xUyG6eXEs28BVt9wuCRwgEiIDpNwzaN6snT3EDOECdQCrRJIAWEk26wfaNABzs+gY2Ow49/5d2RuFL8peN+yNKpHfbhvLXvP4R+WBxOAlMfnSbLN/+tlby8XEie+fy9WctaJUYd5m1Sj76/FyPpTx7UVqjOrLulxdHurV1600E4KRaCfKSReMErIMaxYBMhY2lE/tKz/TGUYxMz7XpKIsfdG0hv51wod5mWEMAAqEiYPpBGR8whapNSDZCAmghEQIM8XIE4BAX38+pc+j5uXpfxT516U5ZsuXNiBJJjI+TJ34+UDo2T4rID4vDRyDnrmfljcMfaycetAeRaQNwYUHHmUXy2YmTWp7aNKojxQjA5czq1UqQVxCAtfrHTWMT0X7f3JESFxfnZhgR+TK9ATx71PlyZd82Ee3NYghAINgETM+XhnUTpYQxW8FuDrJzjQBaiGsoQ+cIATh0JQ9Gwhx6/q+j6T8Qv515VssUWTFpgFVvrv1fneBn0OOOp+TwR59rJ4oArI3srAUmN4A7NKsvq2/KiXxzyzyYiInJtRNl563BG4dhWWmqDMekZradG6Y39PJyMqQgN9MvpSJOCEDAAwKm3zCwbVa6B+jYEgLKBNBClFFh+C0CCMC0hC8JcOj5smxnBG36BrSyzJfl95cebRr6HwoZxIzAoLuelTJuAMeM9+kbDZz/jLz5b70ZwD3bNJSl+cEb92IiJqYm15KNzGH1pHedTU1qZpsAbDrKYkLvNJk7Jssz9mwMAQjYT8D0gkfdmgnyz9tH2J8gEULAAgJoIRYUwachIAD7tHBhD5tDz/8d4LwB/d69z8vLBz+IOJn8Qe1k6ohOEfvBQXgImMwATogTeZ0ZwBE3yah7n5ftB97X8tO9dYoU3nCR1ho/GJuIie2b1pOnbh7kh/QCGaNJzWwTgE2F7PycDJnKDeBA9jVJQcAtAqYXPGrEi+yZw3MW3KoDfoJNAC0k2PWNZnYIwNGki++oEeDQixramDrefeiYjFv4gnzw6YmI9uVWUkT4Qrn4zxvekJnLX9bKvVZCnOyaPVJrDcZnExj238Wy+90PtdBwA/gbXD3SGsiy6wdo8cPYHQKmN2eDIgDPGXW+XMEMYHeaCS8QCCgB03OyVmK87LozN6BUSAsC7hJAC3GXZ5i8IQCHqdoBypVDLzjF3PXOMfnFYzvkpYN6NwJPJ8AN4OD0Q6wymVdUKouK92ptFx8nspcbwFrMKjMedNdaKTv8kZaf7zStJ2sCeOvV5Dbpd5rVkzU3cQNYq4FcMja92RYUAXhUtxZyz/gLXaKJGwhAIIgETAXg1g3ryHNTLw4iEnKCgOsE0EJcRxoahwjAoSl1sBLl0AtWPZ1/LG7bf1TWlB6Sox8fl0+PfyGFJQeVk2QGsDIqDL8mYPqQEhuFHL8V1eQGcPPk2rJh+hC/pVptvCYCcON6NWXrr4ZW6xsD9wmYzra08dww6b22jevK2lsGuw8WjxCAQGAImH5QNvsHXeTKfm0Dw4FEIBBNAmgh0aQbbN8IwMGub2Cz49ALbGnLE9OZD5zVMkVWTBogcXFxwYZCdq4SCJKQ4yqYGDgzmQGcUjtRdtw6PAbRxXYLExGuZkKc7GYUSWwLFcEHR85vpn3z7JtradJ7ybUTZWcAfw49aSY2hUBACZj++2rvnFyJj48PKBXSgoC7BNBC3OUZJm8IwGGqdoBy5dALUDGrSEVlPrDzZnRpfn/pkJoUfCBk6CoB0xsqNt7kcxVMDJwNnP+MvPnvT7R2Sq6TKDt/jQDsQONhhFqt46qxibBh65PtEYBdbQ2cQQACEXxQ1rheomz9VfB+x9MUEIgWAbSQaJENvl8E4ODXOJAZcugFsqxnJXWu+cDOzd+7L+uK+BuOVnA9S9MZdQjAkZfigluf1H7wY5tGdaT4l8GbDWgiwjkVoA8j70MTD1vKjsi4RS9qLW3ZoLasL7BvfIlJ76Um1ZSNMxg/otUAGEMgZARMPigL6rd8QlZ60o0hAbSQGMIO2FYIwAEraFjS4dALS6W/Ggdx+nzgBnVryNDOqdK9dQPGPoSnDVzPFAHYdaTKDrvMWiUfff6Fsr1jOLrbebJgfHetNX4wNhHhbB0p4Afekca4peywjFu0QctNt1YpsnzSRVprYmFs0nutGtSW5y0Us2PBiz0gAAE1AibfsHL+bb991jC1DbCCAAQELYQmMCWAAGxKjnWeEuDQ8xQ/m0PA9wRM3qA4SXPzMvLSZ936pBz79ISWo6V5/aRn20Zaa/xgbCLC0YfeVXZ+UaksLN6rFUBedoYUjMzUWhMLY5Pea1S3pmybxQ3gWNSHPSDgVwImH7C3b1Zfnropx68pEzcEYk4ALSTmyAOzIQJwYEoZrkQ49MJVb7KFgNsETL6iiPDmThX6zlkj73zwmbIzZ4bqK7cND+SNfxMRjhvAyq3juuFPH94sa0rf1fKbl50uBSM7a62JhbFJ79VOjJNX7xwZi/DYAwIQ8DEB3fPF1g/KfFwCQg84AbSQgBc4iukhAEcRLq6jR4BDL3ps8QyBMBCY9vhOWbzpTa1UEd60cFVpPGxBsew+9KGys8t7tpL547oq2/vJUPdNspNbYrzIa3Mu9VOagYl19P3rpWT/Ua18JvROk7ljsrTWxMLYpPfq1EiQ0jtGxCI89oAABHxMQPd8sfWDMh+XgNADTgAtJOAFjmJ6CMBRhIvr6BHg0IseWzxDIAwETG4A10iIkz2zuf0WaX9c9fsN8tyew8pulub1lZ5tGyvb+8lQ902ykxtzWL2rsNEN4JwMKcgNxgiIhnVrSAlzOr1rQHaGgE8I6P5us/WDMp/gJswQEkALCWHRXUoZAdglkLiJLQEOvdjyZjcIBI2AyQxghDd3uuAH9z4nOw58oOxs9qjz5cq+bZTt/WSo+ybZyW32qC5yZd+2fkozMLHOKyqVRZozgGf/oItc2c+uepnM6HSK2Cm1vqyawpzOwDQ0iUAgSgR0f7dxAzhKhcBtYAmghQS2tFFPDAE46ojZIBoEOPSiQRWfEAgPgZMnT0rG9CKthG0UcrQSsMS4++2r5d8fH1eOpntaAym8foCyvZ8Mdd8kO7m9dudwSUxM9FOagYnV5IOj7PZN5JHr+ljFwCQPJ4GurZLlb5MGWpULwUAAAvYR0P3dxgxg+2pIRHYTQAuxuz42R4cAbHN1iK1KAhx6NAcEIBAJAV0BJCE+TvbcOULi4+Mj2Za1ItL5V0Xy8fGTyizSG9eRZ2+5WNneT4a6b5Kd3OaMzpIr+qT5Kc3AxGpyc7Zx/ZqydeZQqxiYjMBxEhjaOVUeurqnVbkQDAQgYB8B3d9t3VunSOENF9mXCBFBwFICaCGWFsYHYSEA+6BIhHg2AQ49ugICEIiEgK4AklwrUXbcOkzi4pxHwfGKhMB3pj0hJ75U95BSO0F23BrMB0/pvkl2qAX5RrR6V3hnqVuzBnVqyPZfD/Mu4Ep2NnkIpuMmz9J5xlbBJRgIQEB0z8mWDerI+oJgftBLO0AgGgTQQqJBNRw+EYDDUefAZcmhF7iSkhAEYkrARABZlt9ferRpGNM4g7iZ7hvDhDiR1+deGkQU2m+SHQjtmtaXp29mDqtXDaHbv60b1pHnptolbOh+AFbBOsjzuL3qJ/aFQBAJ6J6TzZJqyaYZlwQRBTlBICoE0EKigjUUThGAQ1Hm4CXJoRe8mpIRBGJJwEQAyc/JkKm5mbEMM5B76b4xdCCUzUMArmgGbgB792NhMgJiYPvG8r/X9fUu6Ep21h2BU+FiVLfz5J7x3a3KhWAgAAG7CJick5nNk6RocrZdiRANBCwmgBZicXEsDw0B2PICEV7lBDj06AwIQCASAiYCCPMvIyH+zVoE4MhYMAPYnT408WJybvzwwvPkrsvsEk1NBBqHV2aLZCm6kYfAmfQOayAQFgIm52TXlsnyt//kbAlLj5Bn5ATQQiJnGFYPCMBhrbzP8+bQ83kBCR8CHhMwEUC4eelO0dILnhCNEcBSK0Fk12xuADv0E+LiZM9sHkboTifqezH55kB2hybyyLV99DeL8gqTD2I6t0iWlQjAUa4M7iHgbwIm52Svtg3lsbz+/k6c6CEQQwJoITGEHbCtEIADVtCwpMOhF5ZKkycEokdAVwAZmpkqD13TMyzHZFcAACAASURBVHoBhcTzd6Y/ISdOqiebmlRTNs4Yqr7AR5a6PZiaVEs2MifRswpPXbpDlmw5oLV/h9T6snqKfTObdXvPSXp095ay4PJuWvljDAEIhIuAyTMWurduIIU3DAgXKLKFQAQE0EIigBfypQjAIW8Av6bPoefXyhE3BOwhoCuATMxOl2kjO9uTgA8jMbl5XadGvJTekevDbKsPWbcHazssbh8hcXFx1TvHwnUCV/1+gzy357CW33ZN68nTNw/SWhMLY93ec2JamtdXerZtHIvw2AMCEPApAZMbwIzY8mmxCdszAmghnqH3/cYIwL4vYTgT4NALZ93JGgJuETARIpm9Gjl9k9mAtRPj5dU7EYAr6C/L7y892jSMvBh40CbQe/YaeffYZ1rrbB0dYyIAPzaxr/RKRwDWagCMIRAyAia/5/Oy06WAD9hD1imkGwkBtJBI6IV7LQJwuOvv2+w59HxbOgKHgBUETATg/JwMmZqbaUX8fg3C5GYQAvCZ1c4f1E6mjujk1xbwddwdZqyUz7/QmWAtMnvU+XJl3zbW5W0iADMCwroyEhAErCNg8u+ridkZMm0k/76yrpgEZC0BtBBrS2N9YAjA1peIACsjwKFHX0AAApEQOHnypGRML9JyMaF3mswdk6W1BuMzCZjMBkyqnSgv3To8kChNRLjxvVrLvLEXBJKH7Um1n75Sjp/UE4Af+48+0iujiXWpmfReZotkKeIhcNbVkoAgYBsB3fOlfbN68tRN9o3KsY0r8UCgggBaCL1gSgAB2JQc6zwlwKHnKX42h4DvCWwpOyLjFr2olQc3L7VwVWpscgM4qVaCvHTbiMg3t9CD7ptkJwVuYXpXyKxfr5Jjn32hFYCt9TLpvc4tkmUlArBW/TGGQBgJ6J4vDerUkO2/HhZGVOQMASMCaCFG2FgkIgjAtIEvCXDo+bJsBA0BawjMLyqVhcV7teJh9qoWrkqNTWYD1quZIK/cjgBcAdRWQTHy7rDfw9j718vW/Ue1ArXx1qzJNyD48EGr7BhDILQETEZANK5fU7bOHBpaZiQOAV0CaCG6xLCvIIAATC/4kgCHni/LRtAQsIbA1KU7ZMmWA8rxNKxbQ7b9aqjExcUpr8HwbAImbwy5AXwmxwm9W8vcMYyA8OLna/KjJbJ8+1taW2e2SJKiG7O11kTb+C8b35AZhS9rb7M0r6/0bMtD4LTBsQACISJg8kFvdvsm8sh1fUJEiVQhEBkBtJDI+IV5NQJwmKvv49w59HxcPEKHgAUEJi/eJst3vK0cSe+2DeWvef2V7TGsmkD76U/I8ZPqhFLr15CNM4P31VDTW5g8jFC9d9y2nLJkuxSWHNRym9OhqTx8bW+tNdE2Hn3/einRvMnsxLQ0r5/0bNso2uHhHwIQ8DEBk1FP/zGwrUy/tIuPsyZ0CMSWAFpIbHkHaTcE4CBVM0S5cOiFqNikCoEoELj69xtl3Z73lD3Xr+U8iGwYN4CViVVt2HlWkXz8uboC3LphHXlu6sUu7GyXC9NbmHNGZ8kVfdLsSiYk0RQs2yGPblb/5oCDZVS38+Se8d2tIjTk7rXy+r8+0o4pLydDCnIztdexAAIQCA8Bk4e98hC48PQHmbpDAC3EHY5h9IIAHMaqByBnDr0AFJEUIOAhgdzfrpPSt49pRcAMYC1cVRp3mlkkn55QF4CbJ9eWDdOHuLO5RV5Mb2EiwnlXRJObbZd0aiq/+3EwbgAPzUyVh67p6V0B2BkCELCegMk56XzI/vJtw63PjQAhYAsBtBBbKuG/OBCA/VczIhYRDj3aAAIQiIRA7j3rpPQdPQEY4S0S4t+sbT99pRw/+aWys+TaibLz1uC9MTS9hTmhd5rMHZOlzA9D9wiYzLa08Qa76e3z7mkNpPD6Ae4BxRMEIBA4AibnZK2EONk1e2TgWJAQBKJFAC0kWmSD7xcBOPg1DmSGHHqBLCtJQSBmBKY8WiKFmg9z4vabO+XJmPaEaOi/Uq9mvLxye647m1vkxfQGcP6gdjJ1RCeLMglPKCZzm238AMMkD6fKQzunykNXcwM4PB1PphDQJ2DysNdaifGy687g/Z7Xp8cKCKgRQAtR44TV2QQQgOkKXxLg0PNl2QgaAtYQ2LzvsPzwgQ1a8XD7TQtXpcYmbwzrJMZJ6Z3BuxlkeguTB3FF3oemHkxuttWrmSCv3D7CdMuorWtb8IS2b74FoY2MBRAIJQHd86V+zXh5OYAf9Iay+CQdEwJoITHBHMhNEIADWdbgJ8WhF/wakyEEoknA5AYct98ir4iJgBZUAdikB50KLMvrJz3aNoq8GHjQJmAy27Jh3RpSMmuY9l7RXGDyQYwTz+xR58uVfdtEMzR8QwACASCgKwC3aVRHin8ZvIe9BqCUpGApAbQQSwvjg7AQgH1QJEI8mwCHHl0BAQhEQsBEAMnPyZCpuZmRbBv6tSYCWs2EONkd0NmAum+SnQZiBIR3P0YmT7fv1aahPJbf37ugK9nZ5IMYx82obufJPeO7W5ULwUAAAvYR0P3dNrrbebKAs8W+QhKRtQTQQqwtjfWBIQBbXyICrIwAhx59AQEIRELARABelt9ferRpGMm2oV9rIqDFx4nsnXtpINnpvkl2IPAQOO9aweQDjInZ6TJtZGfvgq5kZ5M8HDeZLZKl6MaBVuVCMBCAgH0EdH+3zRl1vlzBtwvsKyQRWUsALcTa0lgfGAKw9SUiQARgegACEHCbgK4AnNUyRVZMGiBxcXFuhxIqfybCk0N83zwE4IpG4Sa6dz8yJjdn54zOkiv6pHkXdCU7m3wQ47jp3CJZViIAW1VLgoGAjQR0BeC87HQpsOyDMhu5EhMEKgggANMLpgQQgE3Jsc5TAhx6nuJncwj4noCOAFwjIU6e+PlA6ZCa5Pu8vU7AREBzYi5DAD5VOhsFRa/7Klb765wbFTHZ+OC0eUWlsqh4rzY2RkBoI2MBBEJJQFcA5hkLoWwTko6AAFpIBPBCvhQBOOQN4Nf0OfT8WjnihoAdBHSEnMR4kSd+ni0dmyMAR1o9He4Ve3ED+EzqNgqKkfaFn9brChs2juz484Y3ZObyl7WxTxyYLtMutWuchXYSLIAABKJOQPec7N46RQpvuCjqcbEBBIJCAC0kKJWMfR4IwLFnzo4uEODQcwEiLiAQYgK6QmT7ZvVl9ZRsRkC40DMZ056Qk1+qO0qIE3mdGcCngNkoKKpX0/+WusKGjQ/tm7KkRApL3tIuRvtm9eSpmwZpr2MBBCAQLgK652Rm8yQpmpwdLkhkC4EICKCFRAAv5EsRgEPeAH5Nn0PPr5UjbgjYQUBXAHaiXpbXT3q0bWRHAj6O4sI7npIjH32unEGjejVl26+GKtv7yVD3TbKTm42Cop+YRxqrbs2W5vWTnpadG7m/XSelbx/TRtGgbg3ZPmuY9joWQAAC4SKge042S6opm2YE8/d8uCpPtrEigBYSK9LB2wcBOHg1DUVGHHqhKDNJQiBqBE6ePCkZ04u0/I/u3lIWXN5Naw3GZxO4cfE2+duOt5XR/KBrC/nthAuV7f1kqPsm2cnNRkHRT8wjjVW3Zo9N7CO90ptEuq2r63P+6xl548gn2j4b16spWwP6YYw2DBZAAAJVEtA9J1s2qCPrCy6GKAQgoEgALUQRFGZnEUAApil8SYBDz5dlI2gIWENgS9kRGbfoRa14OrdIlpU3DtRag/HZBLaUHZZxizYoowmy4Kn7JtmBxk105daJiqFuzbI7NJFHru0TlVhMnV40/xk58G99AdjGXEwZsA4CEIgeAd1zslurFFk+iRnA0asInoNGAC0kaBWNXT4IwLFjzU4uEuDQcxEmriAQQgLzi0plYfFercwzWyRLEQKwFrPKjHXGbwR99rLum2SHJyMgIm7BiBzo1szGW7OmN4CXTuwrPdMbR8SPxRCAQLAJ6PyOryAxqtt5cs/47sEGQ3YQcJEAWoiLMEPmCgE4ZAUPSrocekGpJHlAwBsCBct2yqOb39TanBEQWrjOaawiosWJyJNTsqVDapJ7G1vmSYXDt0PmIXDeFdFE2Eipkyg7fj3cu6Ar2dlkBnBaozpSfMtgHoRpVSUJBgL2Edj6xhEZu1DvG1bcALavjkRkNwG0ELvrY3N0CMA2V4fYqiTAoUdzQAACkRCYu/Kf8sC6fVougjyKQAuEC8YqwmdGk3ryzC8GubCbvS5UOHw7+vycDJmam2lvUgGOzETYaN2wjjw31a7ZllOWlEhhyVvKlUqIEymaHOwPY5RhYAgBCJyTwPxVr8rCta9rUWrXtL48fXOO1hqMIRBmAmghYa5+ZLkjAEfGj9UeEeDQ8wg820IgIAT+/OIbMvNvLytn0yyplmycPoTbb8rEzm2oInwiAFfOcM7oLLmiT5pLlcCNDgETYSO7fRN55Dq7ZgD/ecMbMnO5+vl348XfkSnDOuqgwhYCEAgpgWmP75TFm/S+YdWtdYosv4EZwCFtGdI2IIAWYgCNJeUEEIBpBF8S4NDzZdkIGgLWEJi3slQWrVOfAdy/XWP5v5/1tSZ+vweiIgDHO7cOb8yWjs0ZAXF6vfNyMqSAG8Ce/AiYCBsTerWWuWMv8CTeqjadV1QqizRmoA/vkioPXNXTqhwIBgIQsJOAyQdlzAC2s5ZEZS8BtBB7a2N7ZAjAtleI+ColwKFHY0AAApEQ0J0BnBAfJ3vuHCHx8fGRbMtaEdGZo5rVMkVWTBoQ2JvXKkL4t5tmfK/WMs8yQTEsjW0ibNg4skNXyOb8C0uHkycEIidgMiqnfbN68tRNwR75FDlZPEDgGwJoIXSDKQEEYFNyrPOUAIeep/jZHAK+J6B7A85JmK/eu1N23TeHy/L7S482Dd3Z3DIvJgIwDyP0rohbyo7IuEV6Dzey8dzg/POuh9gZAkEnoPMhbwWLBnVryPZZw4KOhvwg4BoBtBDXUIbOEQJw6EoejIQ59IJRR7KAgFcENu09LJc9uEFr++5pDaTw+gFaazA+m4DuLcr8Qe1k6ohOgUSJAOyvsm4pOyzjFumdGxOz02XayM5WJTpnZak8qDECxwme88+qEhIMBKwmoPu7rVG9mrLtV0OtzongIGATAbQQm6rhr1gQgP1VL6L9mgCHHq0AAQhEQsBEAG7XtJ48fTNfUYyEu7NW9+vnE3qnydwxWZFua+V63TfJThITereWuWPsmilrJdwoBKX74YUTwtDMVHnoGrvm546673nZ/ub7WoTaNa0vT9+co7UGYwhAIJwEdH+3dWuVIssn8RC4cHYLWZsQQAsxocYahwACMH3gSwIcer4sG0FDwBoCc554RR58rkwrnvbN6stTNyGAaEGrxHh+Uaks1HgAlY0zVCNlULFe902ysy7IPNziGi0/uh9eOHHYeHN2yN1r5fV/faSFycY8tBLAGAIQiBkB3d9tA7/TWP73pzxoN2YFYiPfE0AL8X0JPUsAAdgz9GwcCQEOvUjosRYCEBixYJ28euiYFohurRvI8hsYAaEFrRLjv2x8Q2YUvqzsxsYZqsrBV2Oo+ybZcRdkHm5xjZYfkxvAl2Q2k99d0ytaIRn5HX3/einZf1Rr7exR58uVfdtorcEYAhAIJwHd322ZzZOkaHJ2OGGRNQQMCKCFGEBjSTkBBGAawZcEOPR8WTaChoA1BDrPWiUff/6FVjyZzetL0WRuAGtBq8RY9wFUeTkZUpCbGem2Vq7XfZPsJJGXnS4Fls2UtRJuFILSfYChE8LobufJgvHdoxCNuUvdD2GcnZZO7Cs90xubb8pKCEAgFARMHgLXPKW2bJg2JBR8SBICbhBAC3GDYjh9IACHs+6+z5pDz/clJAEIeEqg48wi+ezESa0YMlskS9GNA7XWYHw2Ad2v0TMD+EyGQzunykNX2zVTNix9biJsjO7eUhZc3s0qRCdPnpSM6UVaMQX5YYxaIDCGAATOScDkg7KGdWtIyaxhkIUABBQJoIUogsLsLAIIwDSFLwlw6PmybAQNAWsIdJ5VJB9/ricA2yjkWANUIxDdr9EHWXgyuQHcvXUDKWQUiUbHuWuqW7PxvVrJvLFd3Q3CBW+6efDwQReg4wICISCg+zveQXJeSm15gRvAIegOUnSLAFqIWyTD5wcBOHw1D0TGHHqBKCNJQMAzAiPuWSevvqM3A3hpXj/p2baRZzEHZWPd20HL8vtLjzYNg5L+GXnoinDO4l5tGspj+f0DycP2pExuzuZ0aCoPX9vbutR0e29Ut/PkHstGWVgHlYAgAAHR/ZaPg4wPNmkcCOgRQAvR44X1NwQQgOkGXxLg0PNl2QgaAtYQmLvyn/LAun3K8TSok1j+9cS4uDjlNRhWTkDna/RZLVNkxaQBgeWuK8I5RLu1SpHlky6ivTwgYDI7t0NqfVk9xb7Z4bq9l92hiTxybR8PqLMlBCDgJwImN4B5uKmfKkysNhBAC7GhCv6MAQHYn3ULfdQceqFvAQBAICICurdQnRmezggIXu4QUBWfHriqhwzv0tydTS30osrh9NB7tW0kj+X1szCb4Ic0+v71UrL/qFai6Y3ryrO3DNZaEwtj3d7LbJ4kRZOzYxEae0AAAj4moPvvq1qJ8VJ6+3CJj4/3cdaEDoHYEkALiS3vIO2GABykaoYoFw69EBWbVCEQBQI6X+WukRAnu+4YwZsTl+qgcwM4rVFdKb5lEDeAT2PPV2VdakQDNxffvVb2/usjrZVBuQHcKbW+rLLwJrNWMTCGAASiTkDnd7wTzANXXSjDu7SIelxsAIEgEUALCVI1Y5sLAnBsebObSwQ49FwCiRsIhJTAlrLDMm7RBuXsmf+rjKpaw837DssPH9Bh31d6tm1crV8/GujewnRyHJqZKg9d09OP6fo+5qH/vVb2vKsnAGe3byKPXGff6ATd3uvWOkWW38DoEd83MQlAIAYEVM+X/u0ay//9rG8MImILCASLAFpIsOoZy2wQgGNJm71cI8Ch5xpKHEEglASmLNkuhSUHlXN3xj84YyB4RU7g6j9slHW731N2ZOtDtJQTOIeh6pvk011MzE6XaSM7u7E9PjQJ/ODe52XHgfe1Vg3NbCYPXdNLa00sjHV7z9abzLFgxR4QgIAeAdXzZWJOhkzLzdRzjjUEICBoITSBKQEEYFNyrPOUAIeep/jZHAK+J5B7zzopfeeYch6ZLZKk6EbmXyoDO4dhjzueksMffa7sqnH9mrJ15lBlez8Zqr5JPj2nvOwMKRjJG2Yv6jxiQbG8euhDra1tHdmh23stG9SW9QVDtHLHGAIQCCcB1fMlL6edFOR2CicksoZABATQQiKAF/KlCMAhbwC/ps+h59fKETcE7CCQc9cz8sbhT5SDadu4rqy18EFOyglYZNjtttVy9JPjyhE1qFNDtv96mLK9nwxV3ySfnlO3VimyfBJfxfeizrm/XSelb6t/cOTEaOtD+3R7LzW5lmycfokX2NkTAhDwGQHV8wUB2GeFJVxrCKCFWFMK3wWCAOy7khGwQ4BDjz6AAAQiIXDRvKflwNFPlV20alhbnp/K7TdlYOcwHLqgWPZo3KIM8lfPVd8kn46zZYM6sr7gYjdKgQ9NAlOWlEhhyVtaq4JyA7hXm4byWH5/rdwxhgAEwklA9XfbZT1by3+NuyCckMgaAhEQQAuJAF7IlyIAh7wB/Jo+h55fK0fcELCDQJ/ZT8mhY+pjCJon1ZINM7j95kb1/ryhTGYuf0XZ1exR58uVfdso2/vFUPdJ6RV5cRPTuwpvKTsi4xa9qBWArQ/tUxVoKpJl9rRW2TGGQKgJqJ4vNRLi5B//OVA6Nk8KNS+Sh4AuAbQQXWLYVxBAAKYXfEmAQ8+XZSNoCFhDIGtWkRz7/KRyPEk14+Wl23OV7TGsmsDJkyclY3qREqJaifFSevtwiY+PV7L3k9HWN47I2IV6YqKTHzcxvauyiWifl5MhBRY+5EhVoKmgvSy/v/Ro09A7+OwMAQj4goDuOZnVMllWTLpI4uLifJEfQULABgJoITZUwZ8xIAD7s26hj5pDL/QtAAAIRESgy6xV8tHnXyj7qFczQV65fYSyPYbnJqAqPuVnZ8jUgD7wbP6qV2Xh2te1W2VUtxZyz/gLtdexwB0Cqr1ru3Cqk0daozpSfMtgBBp3WggvEAg0AZMPN/mAKdAtQXJRIIAWEgWoIXGJABySQgctTQ69oFWUfCAQWwJdb31S3v/0hPKmKbUTZcetw5XtMayagM4N4Do1EuSV24YF8gbwtMd3yuJNb2q3yujuLWXB5d2017HAHQI6wmlWyxRZMWmAlcKpTh6J8SK778wN5M+hO12BFwhAoIKAyYebtn5TgqpCwFYCaCG2Vsb+uBCA7a8REVZCgEOPtoAABCIhkHPXs/LG4Y+VXbRtXFfW3jJY2R7Dqgn8ZeMbMqPwZWVEc0ZnyRV90pTt/WJo8ibZyW18r1Yyb2xXv6QZuDhVhdOazmzLnw+UDqn2zbbU+RCmooCzf9BFruzXNnD1JCEIQMBdAiYfbto6K91dMniDgHsE0ELcYxk2TwjAYat4QPLl0AtIIUkDAh4RmPxoiSzf/pby7qO7nScLxndXtsewagKj718vJfuPKiPqntZACq8foGzvF0OTr8k6uXED2NsKqwrAzq3ZJ36ebeXDjf684Q2ZuVz9QxiHeOuGdeS5qRd7C5/dIQAB6wnMLyqVhcV7teIM6u95LQgYQ0CDAFqIBixMzyCAAExD+JIAh54vy0bQELCGwJ83lMnM5a8oxzN71PlyZd82yvYYVk1gyN1r5fV/faSMqF3T+vL0zTnK9n4x1H1QTkVeo7qdJ/fwYYRnZVYVgJ0A2zerL6unZFs3AmLYgmLZfehDLYbOAxl33cmDMLWgYQyBEBLQ/ZaPg2ho51R56OqeIaRFyhAwI4AWYsaNVSIIwHSBLwlw6PmybAQNAWsIzCsqlUUaN1SYT+de6bgB/A1LHTGxYtUlnZrJ737cy72C4EmLgG7NluX1kx5tG2ntEW3jC25dJR98qv4QTCceBOBoVwX/EAgGAd1/XzlZ5+dkyNTczGAAIAsIxIAAWkgMIAd0CwTggBY26Glx6AW9wuQHgegS0J1RN6F3mswdkxXdoELiXfd2UFBnADvl1hUTnTV8VdbbHxTdmtk4sqPzrFXy8ed6AnCrhrXl+alDvIXP7hCAgPUEdP995SS0LL+/9GjT0PrcCBACthBAC7GlEv6LAwHYfzUjYhHh0KMNIACBSAjoPoArf1A7mTqiUyRbsvZrAjoPoKpTI0FeuW2YxMfHB5KfrpjoQOCrst62gm7NOrdIlpU3DvQ26G/tnnXrk3Ls0xNaMf3HwHSZfmlnrTUYQwAC4SOg+++rpvVryaYZQ6wblRO+ypGxnwighfipWnbFigBsVz2IRpEAh54iKMwgAIFKCeg+gIvbKe42kqqI9uBVPWRYl+bubm6RN1UOp4fMOBJvC6hbs8wWyVJkmQDcf+7T8tb7n2qBzMtOl4KRCMBa0DCGQAgJ6P77asHl3cofbsoLAhBQJ4AWos4KyzMJIADTEb4kwKHny7IRNASsIaDzAK6slimyYtIAbqe4WD0VEa1lSm1ZPy3YXzlX4fBt7HNGnS9X8EBCF7tR3ZXOuVHh1cYREKPvWy8lbx5VT1xExvdqLfPGXqC1BmMIQCB8BHS+5RMfJ/La7NzAfssnfNUn41gRQAuJFeng7YMAHLyahiIjDr1QlJkkIRBVAqri2wNX9ZDhAb6FGlXIVThXYZ/euK48e8tgL8KL2Z4qHL4dzKhu58k947vHLEY2+oaA7s02Z+XSvH7S07KHwP15Q5nMXP6KVmltFLK1EsAYAhCICYEtZUdk3KIXlfey8UGZysFjCAGPCKCFeAQ+ANsiAAegiGFMgUMvjFUnZwi4R0DnJh83gN3jXuFJRfh0bgYV3ZgtHZsnuR+AJR5VOHw71MzmSVI0OduSDMIVhu5sy4Z1asi2WUOt+/bA5n2H5YcPbNAqHgKwFi6MIRBaAlOWlEhhyVvK+XO2KKPCEAKnCKCF0AymBBCATcmxzlMCHHqe4mdzCPiegO5NPmYAu1dyxPdvWJoIwM2Ta8uG6cEejeFet7nraerS7bJky0FlpyO6pMqiq3oq28fKUFfIduKa0Lu1zB3DCIhY1Yh9IOBXArm/XSelbx9TDt/GB2UqB48hBDwigBbiEfgAbIsAHIAihjEFDr0wVp2cIeAeAV0BJH9QO5k6opN7AYTYE+J7ZAJww7o1pGTWsBB3kHepX/37jbJuz3vKAWR3aCKPXNtH2T5WhtMe3ymLN72ptV1+ToZMzc3UWoMxBCAQPgK596yT0nfUBeAwjHsKXxeQcbQJoIVEm3Bw/SMAB7e2gc6MQy/Q5SU5CESdgK4AMqF3mswdkxX1uMKwAeJ7ZAJwk3o1ZMuvEIC9+FkZtqBYdh/6UHnrNo3rSPEtFyvbx8pwXlGpLCreq7XdnNFZckWfNK01GEMAAuEjoPtBWf1aifLSrcOsG5UTvsqRsZ8IoIX4qVp2xYoAbFc9iEaRAIeeIijMIACBSgnMLyqVhRoCCLff3GskxPfIBODUpFqyccYl7hUET8oEBv/mWdn33sfK9jUT42XXHSOsEzb+svENmVH4snIejmFeToYUcANYixnGEAgjgcmPbpPl29/WSp0xW1q4MIaAoIXQBKYEEIBNybHOUwIcep7iZ3MI+J6ArgDC7Tf3So74HpkA3KttQ3ksr797BcGTMoGhC4plj8YNYMexjcKG7s+gk8f4Xq1l3lhmACs3C4YQCCmBgmU75dHNmiNmGLMV0m4hbVMCaCGm5FiHAEwP+JIAh54vy0bQELCGwNyV/5QH1u1TjmdidrpMG9lZ2R7DqgkgvkcmAOdlp0sBvejJj9jVf9go63arzwB2grRxfrjuLXwnj9HdW8qCy7t5wp1NIQAB/xCYsqRECkve0gqYMVtauDCGADeA6QFjAgjAapeaUwAAIABJREFUxuhY6CUBBGAv6bM3BPxP4KcPb5Y1pe8qJzI0M1Ueuqansj2GVRPQnT8a5K+ety14QrtVbLxRqp2ETxeY3Gyz8eas7hxuBGCfNixhQ8ADAlOWbJfCkoNaOwf597wWCIwhoEgALUQRFGZnEUAApil8SYBDz5dlI2gIWENg9P3rpWT/UeV4uqc1kMLrByjbY1g1Ad3bh0G+GaQrAGe1TJEVkwZYN1M2LP0eFOF06xtHZOzCF7XKNqF3a5k7hhEQWtAwhkAICRQs2yGPbj6glXledoYUjMzUWoMxBMJMAC0kzNWPLHcE4Mj4sdojAhx6HoFnWwgEhID2DeDOqfLQ1dwAdqP8uiKajV+hd4OD40NHAE6unShL8/tLh9Qkt7bHjyYBE+HUxtEJX375paRPW6mVfZB/DrVAYAwBCJyTgO7veMdZt1YpsnzSRZCFAAQUCaCFKILC7CwCCMA0hS8JcOj5smwEDQFrCOg+BCk/J0Om5nI7xY0C6opoQR55oCMAr56SjfjrRgNG4MNEOLX15qxO7znIluX1kx5tG0VAj6UQgEAYCGza+55c9uBGrVTPS6ktL0wborUGYwiEmQBaSJirH1nuCMCR8WO1RwQ49DwCz7YQCAgBREjvCqkjogV95IGOCFc271LvisbOpwjo1MxZZOvNWd08lub1k54IwPwkQAAC1RCY88Q/5cHn1B+y67hrWLeGlMwaBlsIQECRAFqIIijMziKAAExT+JIAh54vy0bQELCGACKkt6VQEZ/i40RWTQ72rVcVDhWVQgD2tmcrdtepmbPG1puzunnYKmTb0RVEAQEIVBDoM2eNHPrgMy0gzVNqywZuAGsxwzjcBNBCwl3/SLJHAI6EHms9I8Ch5xl6NoZAYAioCiB89d79kquwT29cV569ZbD7m1vkUYUDArBFBdOc2+xE/tjEvtIrvbFdSRjkEeSHMVpXHAKCgI8JZN36pBz79IRWBh2b1ZMnbxqktQZjCISZAFpImKsfWe4IwJHxY7VHBDj0PALPthAIEAFV8Y2bl+4XXYU9AvCZ3OlD9/vQxKNK757u18aHwDnx6eaRl5MhBcxBN2kZ1kAgVARMbgC3b1ZfnropJ1ScSBYCkRBAC4mEXrjXIgCHu/6+zZ5Dz7elI3AIWENAVQBBeHO/ZCrsnREQRTdmS8fmSe4HYIlHFQ4VodKHdhRNp2ZOxJktkqXoxoF2BH9aFLp5zBmdJVf0SbMuDwKCAATsIjBnZak8uG6vVlDMANbChTEEBC2EJjAlgABsSo51nhLg0PMUP5tDIBAEVAUQhDd3y8385W94qvags4I+dLcPTb3p1MzZo3OLZFkZAAE4PydDpnID2LRtWAeB0BD44osvpN2MVVr5JtdOlJ23DtdagzEEwkwALSTM1Y8sdwTgyPix2iMCHHoegWdbCASIgKqQg/DmbtG3vnFExi58Udnpsvz+0qNNQ2V7Pxmq9iACsB1V1fnwoiLioIyAmNC7tcwdc4EdhSAKCEDAagI6v9ucRLgBbHU5Cc5CAmghFhbFJyEhAPukUIR5JgEOPToCAhCIlIDqG5QnJwd7DEGkHHXXz1/1qixc+7rysvxB7WTqiE7K9n4yVO1BBGA7qqr74YUT9bK8ftKjbSM7EjgtCp3ec5bZKmRbB5aAIAAB7Rnj7ZvVk6d4CBydAwFlAmghyqgw/BYBBGBawpcEOPR8WTaChoA1BHRu8mW1TJEVkwZIXFycNfH7OZBpj++UxZveVE5hQu80mTsmS9neT4Y6Ihw30b2v7LyiUllUrD7b0rnVtu1XQ608O3R6DwHY+94jAgj4iYDu+dIptb6smsJD4PxUY2L1lgBaiLf8/bw7ArCfqxfi2Dn0Qlx8UoeACwR0b/IFeQyBCzi1XOiKaHk5GVIQ0NmjOm+SEYC12iwqxtf9aZM8/eq/lH33TW8kj07sp2wfS0Od3nPiGt+rtcwbywiIWNaIvSDgVwK654uts9L9yp+4g08ALST4NY5WhgjA0SKL36gS4NCLKl6cQyDwBBhD4F2J/7zhDZm5/GXlAOaMOl+u6NtG2d5PhjpvkhlF4n1lhy4olj2HPlQOpENqfVlt6a02nd5zEg7yKBblgmIIAQhUS0DnG1YVzhgxUy1WDCBwBgG0EBrClAACsCk51nlKgEPPU/xsDgHfE2AMgXclnLKkRApL3lIOYHT382TB5d2V7f1kqCPCMYrE+8oOuutZKTv8sXIgbRvXlbW3DFa2j6WhTu85cfEtiFhWh70g4F8Cut+wcjJ9bGIf6ZXexL9JEzkEYkwALSTGwAO0HQJwgIoZplQ49MJUbXKFgPsEuAHsPlNVj7m/XSelbx9TNZcgfzUUEU65Daww1O/dJFl5Y7YVsX87CJ3e48MHK0tIUBCwkoDuv6+cJO78QWf5Ub90K/MhKAjYSAAtxMaq+CMmBGB/1Ikov0WAQ4+WgAAEIiGge0OF22+R0D5zra6IltkiWYpuHOheABZ50hHhnLD5Gr63xdO/vd5SFlzezdugq9hdtffq1kyQ5TcMkA6pSVbmQVAQgIBdBHS/YeVE36phbXl+6hC7EiEaCFhMAC3E4uJYHhoCsOUFIrzKCXDo0RkQgEAkBJwZdd+793l5+eAH1brh9lu1iLQMpizZLoUlB5XXBHk2oKoIVwFrQu/WMncMD+JSbh6XDbeUHZFxi15U9rosr5/0aNtI2T5WhidPnpSM6UVK29VIiJNdd4yQ+Ph4JXuMIACBcBMwuQHsnDN7Zo8MNziyh4AGAbQQDViYnkEAAZiG8CUBDj1flo2gIWAVgd2Hjsm4hS/IB5+eqDKu5NqJsjS/P7ffXKzclrLDMm7RBmWPS/P6SU8LRTTlBM5hqCsAB3keshs8o+1D5+FG7Zs5D4DLlri4uGiHpe3/zxvKZObyV5TXzR51vlwZ0AcxKkPAEAIQUCKg+w0rx2lCnMjrcy9V8o8RBCAgghZCF5gSQAA2Jcc6Twlw6HmKn80hEBgCu945Jr94bIe8dPD9s3Jybv7efVlXxF+Xq+2IaEMXFMtr735UrWebRbRqg1cw0BWAszs0kUeu7aPgGZNoEVCtmSP+2jo2YdiCYtl96ENlRB1SHTE7R9keQwhAILwEdD4oq6BUMyFOdnMDOLxNQ+baBNBCtJGx4GsCCMC0gi8JcOj5smwEDQErCThvVrbtPyprSg/J0Y+PS4O6NWRo51Tp3rqBlbf3rISoGZRz+3r0fevlo8+/qHJlvZoJUhjw2aOqYmIFpMzmSVI02c6Himm2gG/NVWtWNs/e22zdblstRz85rlwD50zcPmuYsj2GEIBAuAmonpMVlOrXipeXb8sNNzSyh4AGAbQQDViYnkEAAZiG8CUBDj1flo2gIQABCJwi4Ny+vvmv2+Xlt86ew3z+ecny35d3s/YGpVtl1H2THOQH4rnFNNp+VGtmswB84e2r5cjH6gJwo7o1ZBsCcLRbC/8QCAQBkxvA56XUkhemXRKI/EkCArEggBYSC8rB3AMBOJh1DXxWHHqBLzEJQgACISAQ9tvXqmJiRSsE+YF4fml31ZrZLAD/4N7nZceBs8feVFWDbq1TZPkNF/mlRMQJAQh4SMBkBjBnjIcFY2tfEkAL8WXZrAgaAdiKMhCELgEOPV1i2EMAAhCAgG0EVMXEiriD/EA822pTVTyqNbNZAJ78aIks3/6WMvLR3c6TBeO7K9tjCAEIhJfAvKJSWVS8VwvAnNFZckWfNK01GEMgzATQQsJc/chyRwCOjB+rPSLAoecReLaFAAQgAAHXCKiKic6GQX8gnmtQo+xItWZPTs6Wjs2TohyNmfuCZTvl0c1vKi+e0Lu1zB1zgbI9hhCAQHgJ/PThzbKm9F1lAPFxIq/NzpX4+HjlNRhCIOwE0ELC3gHm+SMAm7NjpYcEOPQ8hM/WEIAABCDgCgFVMdHZbPWU7MDPRHYFahSd6My2zGqZIismDbDyQZLzV70qC9e+rkwqf1A7mTqik7I9hhCAQHgJjL5/vZTsP6oMIL1xXXn2lsHK9hhCAAIiaCF0gSkBBGBTcqzzlACHnqf42RwCEIAABFwgoCMA2zxSwAUUvnChO9tyWX5/6dGmoXW5BSUP68ASEAQgILo3gId2TpWHru4JOQhAQIMAWogGLEzPIIAATEP4kgCHni/LRtAQgAAEIHAaAQRgf7VDUG7OBuUms7+6h2ghEA4CujOA83IypCA3MxxwyBICLhFAC3EJZAjdIABHWPQvvvhCSktLZcuWLbJ169by/9+xY4d88skn5Z6vueYa+dOf/lTtLmvXrpXBg9W//qLq19n4b3/7m/zv//6vbN68WQ4dOiTJycnSrl07GT16tEycOFFSUlKqja/C4O2335ZFixbJ3//+dykrK5NPP/1UmjdvLgMHDpRrr71WcnJylH1FYsihFwk91kIAAhCAgA0EEIBtqIJ6DNMe3ymLN+nMzk2TuWOy1DeIoaVq7zF6JIZFYSsIBIDAXza+ITMKX1bOhAfAKaPCEAKnCKCF0AymBBCATcl9vW7s2LHy+OOPV+lFVaiNhgB87NgxueKKK+Qf//hHlfG1atVKlixZIv3796+WRGFhYbnIe/Ro1XOdfvazn8nChQslISGhWn+RGHDoRUKPtRCAAAQgYAMBVRHOiZUREN5XLCg3gB2Sqr1H33nfd0QAAT8RmLvyn/LAun3KIU/MTpdpIzsr22MIAQgwA5geMCeAAGzOrnzlqFGjym/YVrwaNWokjRs3lj179pT/kYkAfPnll8v48ePPGVlaWppceOGFVdqcOHFCRo4cKU899VS5TWpqqjjibOfOneXIkSOyePFiWb9+ffnfNWjQQJ5//nnp0qVLlf7WrFlT7u/48ePlNpdeeql8//vfl3r16sm2bdvkd7/7nXzwwQflf+fs8+CDD0ZI9tzLEYCjihfnEIAABCAQAwKqIpwTypOTs6Vj86QYRMUWVREI0uxc1d5DAObnAQIQ0CGgPQM4M1UeuoYZwDqMsYUAWgg9YEoAAdiU3Nfr5syZI85N2x49epT/Lz09vXzkw09+8pNyCxMB+Ne//rXceuutEUXm3MK9/vrry304ou8zzzxTLgKf/vrFL34hd999d/kfDRgwoFwEruzljHno2LGj7N+/v/yv/+d//kcmTZp0hunu3bvLxz+888475X++evVqGTp0aEQ5nGsxh17U0OIYAhCAAARiREBVhHPCyWqZIismDZC4uLgYRcc23yYQpNm5qr2HAMzPAQQgoENg9P3rpWR/1d8W/bav7mkNpPD6ATpbYAuB0BNACwl9CxgDQAA2Rlf1Qq8FYGcusTPaoUKMdWYTV3Zb2LHr2bOnbN++vTyZVatWyfDhw89K7L777jsl+H7ve9+TFStWVJq8MwrDGYnhvPr27SvOwRStF4detMjiFwIQgAAEYkVAVYSriGdZfn/p0aZhrMJjn0oIqNbsgat6yPAuza1lqJrHrO92lmsvSrc2DwKDAATsInDdnzbL06++qxzU0Mxm8tA1vZTtMYQABBgBQQ+YE0AANmdX5UqvBWDntu+QIUPK43Nu5Trzhat6/fGPfyyf6+u8qrqtnJ2dLc8991y5zbPPPiuDBg2q1N3JkyfLHy7nPBzOee3bt0/atm0bBcIcelGBilMIQAACEIgpAVURriIonpYe0/KctVlQbgA7FwDazVilBNO5cP7anSOi/mwHpWAwggAErCdw9e83yro97ynHmd2+iTxyXR9lewwhAAG0EHrAnAACsDm7Kld6LQD/8pe/lLvuuqs8vvnz54vz31W9Dh06JM2bf3VDpVmzZuL89+kvZ7yFMyPYEXeTkpLk3//+9znfBOTn58uiRYvKXdx///3i/Hc0XtwAjgZVfEIAAhCAQCwJ6ArAl2Q2k99xUyqWJTpjr6DMAJ6zslQeXLdXmWNedoYUjMxUtscQAhAIL4GhC4plz6EPlQF0SK0vq6fkKNtjCAEIIADTA+YEEIDN2VW5MlIB+Pzzzy8XWffu3Suff/65OA+Wc/7Mmal73XXXlf/3uV65ubnl4xycl3MbePDgwee0dx4o9+abb5bbvPvuu9K0adNT9hs3biwf5+C8nJvAxcXF5/T1hz/8oTxG5+XMIHbGR0TjhQAcDar4hAAEIACBWBLQFYB5oxzL6py91/xVr8rCta8rB5E/qJ1MHdFJ2T5Whn3mrJFDH3ymvF1qci3ZOP0SZXsMIQCB8BIYfNczsu/wJ8oA0hvXlWdvOfd7VWVnGEIgJATQQkJS6CikiQAcBaiRCsDnCql+/fry29/+9tTYhspsMzIyyscvOC+VMQzOmIh169aV2zujHi666KJTbh955JHy0RDOS+WBds6IiIsvvrjc3hlDsWbNGm3CKrODX3rpJZk4cWK57xdeeEH69eunvQ8LIAABCEAAAl4S0BWA2zauK2t5o+xZyaY9vlMWb/rqA3OV14TeaTJ3TJaKaUxtsm59Uo59ekJ5z+TaibLz1rOfEaHsAEMIQCA0BLgBHJpSk6iHBBCAPYTv860RgKNQQFMB2BFOnYe1OTN2MzMzJSUlRT788ENxxM6//vWvcuDAgVPRzp07VwoKCiqN3rkh7IxqcF7OCAdHND7Xa8yYMVJYWFhu8ve//12++93vnjL/f//v/8mNN95Y/t8333yz/OY3vzmnr507d0rXrl3LbXr06CFbtmzRJqz7hHMEYG3ELIAABCAAAY8J6MyTrQg1s0WSFN2Y7XHk4d2eG8DhrT2ZQwACagSu/sNGWbdbfQZwToem8vC1vdWcYwUBCJQTQACmEUwJIACbkjvHOhMB+O233y4Xazt06FCp5+PHj8v06dNPCbCOSOoInxXjGU5fVLNmTXHsnZfz/4mJiefM8sorr5T/+7//K7dx/n/ChAmn7OfMmSMzZswo/2/n/++8885z+tqzZ8+pHJxcdu3apU0YAVgbGQsgAAEIQMBnBHTnyTrpje7eUhZc3s1nmQYnXN2aLcvvLz3aNLQOADOArSsJAUEgMAQKlu2URzdrfFOiV2uZO/aCwORPIhCIBQEE4FhQDuYeCMBRqKuJAKwaxrXXXit//OMfy81HjhwpTzzxxFlLoyUAz5w5U+64446oC8CMgFDtBuwgAAEIQMCvBHRvkzp5/vVnvaV3u2/m9Ps1d7/GrXNrO6tliqyYNEB0P9SOBZsTJ07Id2Y+qbzVa3cOr/YygbIzDCEAgUATmF9UKguL1R8ymZ+TIVNzechkoJuC5FwngADsOtLQOEQAjkKpoykAHzx4UFq3bi3Om5BatWqVj3qoU6fOGVn4fQSESkk49FQoYQMBCEAAArYS0J0n6+QxcWC6TLu0s60phSIu1bnND1zVQ4Z3aW4lk6DcZLYSLkFBIOQE/rLxDZlR+LIyhTmjs+SKPmnK9hhCAAKMgKAHzAkgAJuzq3JlNAVgZ9OOHTvK7t27y/d/5ZVXpHPnM98M+v0hcColQQBWoYQNBCAAAQjYSsDkBnDDujWkZNYwW1MKfFxBuQGs23v5g9rJ1BGdAl9fEoQABCInMK+oVBZp3ADOy8mQAm4ARw4eD6EigBYSqnK7miwCsKs4v3IWbQF4wIAB5fN/ndf69eulf//+Z2SRm5srq1atKv+zZ555RgYPHnzOLNPS0uTNN7+a1fTuu+9K06bffL1048aNp+YMZ2dnS3Fx8Tl9/eEPf5Drrruu3Ob666+X++67LwqE+dQrKlBxCgEIQAACMSOwpeywjFu0QWu/xPg4eW3OSK01GLtHICg3Z3Vvn0/onSZzx2S5BxJPEIBAYAlozwDu3VrmjmEGcGAbgsSiQgABOCpYQ+EUATgKZY62AOw8XM152JrzquwG8C9/+Uu56667yv9+/vz54vx3Va9Dhw5J8+ZffUWxWbNm4vz36S/nwXQNGjSQkydPSlJSUvnIiYSEhCr95efny6JFi8r//v777xfnv6Px4tCLBlV8QgACEIBArAhsKTsi4xa9qLVdnIjsm3ep1hqM3SMQlJuzQcnDvcriCQIQcIvAlCUlUljylrI7Hm6qjApDCJwigBZCM5gSQAA2JXeOddEUgA8cOCDOjd2KGcBHjhyRunXrnhGNc+t3yJAh5X82aNAgefbZZ6uM1nmgnPNgOef14x//+NQD5k5f4Nz8fe6558r/aO3atZKTk1OpP0ck/s53viP79u0r/3vn/9u2bRsFwtwAjgpUnEIAAhCAQMwI6IpwTmA1E+Jk92xuAMesSN/aKCg3Z4Nyk9mrPmBfCECgagJTlmyXwpKDyogQgJVRYQiBUwQQgGkGUwIIwKbkzrEumgLwT37yk/IRE85rxIgRUlRUdFYkX3zxhbRq1Ureeeed8r/bunWrXHjhhZXa9ezZU7Zv317+d87YiOHDh59l59zkveGGG8r//Hvf+56sWLGi0uwff/xxGTt2bPnf9e3bV5yDKVovDr1okcUvBCAAAQjEgoCumOjEVLdmvPzz9txYhMcelRDQFe1tnZ2rM8s4rVEdKb5lsMTFOffPeUEAAhA4N4GCZTvk0c0HlDGN79Va5o1lBIQyMAwhIFyGownMCSAAm7OrcqWuAPzaa6+JI57m5eVJcnJypX6PHz8u06dPl9/85jen/r6y+b8Vf7lw4cLyGbzOq0uXLuWzgJ0RD6e/brnlllP+nLnCzz//fKV7f/rpp+UPntu/f3/53997772nBOGKBc5ICuemcIXo/NRTT8kll1wSBbpfuUQAjhpaHEMAAhCAQAwI6IqJTkgptRNlx61nf1Abg3DZQkR0x3Ysy+snPdo2so6d842tjOlnXyCoLNBaifFSevtwiY+Pty4PAoIABOwjwEPg7KsJEQWPAFpI8Goaq4wQgCMk7Yw5+P3vf3+Gl507d8rf//738j+74IILym/Nnv5ybuOOGTPm1B85N3C7d+8utWrVkosvvlh69eol6enp5TN3P/zwQ3nppZfkr3/966kHtTkLZ8+eXS4IV/U6ceKEjBw5Uhwh1nk5c35/9rOfSefOncUZG7F48eJTgm9KSkr5w+Qcobiq15o1a8r9OUK08/rud78r3//+96VevXqybds2+d3vfifvv/9++d85+zz44IMRkj33cg69qOLFOQQgAAEIRJmA7tfwnXDaOLcxf3lxlCPDfVUEdB/ctzSvn/S0UAD+y8Y3ZEbhy8qFnjM6S67ok6ZsjyEEIBBeApwv4a09mceOAFpI7FgHbScE4Agr6szEHTx4sJaXa6655tQYB2dhhQCs4sS5IbxgwYJTc3vPtcZ5gNsVV1wh//jHP6o0c0ZFLFmyRPr371/t9oWFheX7Hj16tEpbR/x1bh+f60Fx1W6kYMChpwAJEwhAAAIQsJaA8zX8TjOL5LMvvlSOMbt9E3nkuj7K9hi6S0D31ratIyBG379eSvZX/W+5b1PrntZACq8f4C5MvEEAAoEkML+oVBYW71XOLT8nQ6bmZirbYwgBCPBtaHrAnAACsDm78pVuCMCfffZZuZ8NGzbIxo0bpaysTA4fPiz//ve/y28FN2nSRLp27SpDhw6Vq666qsoxEVWl8re//U0eeeQR2bx5s7z77rvlN4vbtWtXfgt54sSJ4twAVn29/fbb5QKvc8PZidMZD9GiRQu56KKL5LrrrqvyAXGq/lXtEIBVSWEHAQhAAAK2Ehh13/Oy/c2vvj2j8hrV7Ty5Z3x3FVNsokCgYNlOeXTzm8qeJ/RuLXPH2Dfbcsjda+X1f32knEe7pvXl6ZsrfwCwshMMIQCBUBDQnW8/oXeazB2TFQo2JAkBtwighbhFMnx+EIDDV/NAZMyhF4gykgQEIACBUBP48R82ytrd7ykzGN+rlcwb21XZHkN3CUxZUiKFJW8pO7X16fbcAFYuIYYQgIAmgaB8U0IzbcwhEFMCaCExxR2ozRCAA1XO8CTDoReeWpMpBCAAgaASuOLBF+WFvUeU0xvVtYXcM+FCZXsM3SUwZcl2KSw5qOzUVgGYGZ3KJcQQAhDQJKA7335Zfn/p0aah5i6YQyDcBNBCwl3/SLJHAI6EHms9I8Ch5xl6NoYABCAAAZcIDPnNWnn9PfWv4ndr3UCW38AsVpfwa7spWLZDHt18QHnd+F6tZd5Y+0ZAnDx5UtrPKBKV8dO1EuOl9PbhEh8fr5w3hhCAQHgJOPPt06etVAKQ1TJFVkwaIHFxcUr2GEEAAl8RQAuhE0wJIACbkmOdpwQ49DzFz+YQgAAEIOACgS6zVslHn3+h7KlxvZqy9VdDle0xdJfAvKJSWaTxcKO8nAwpsPDhRo5A0+321fL+JyeqBdSmUV1Ze8sgBJpqSWEAAQhUEGhb8IQSjAeu6iHDuzRXssUIAhD4hgBaCN1gSgAB2JQc6zwlwKHnKX42hwAEIACBCAk4IlzGtJXypYafBnVqyPZfD9NYgambBIIyOoGvaLvZFfiCAAROJ6BzAzitUV0p5gMmGggC2gTQQrSRseBrAgjAtIIvCXDo+bJsBA0BCEAAAl8T0BXhnGXNkmrJphmXwNAjAvNW/lMWrdunvHtedroUjOysbB8rQx7SFCvS7AOB8BHYvO+w/PCBDcqJL83rKz3bNla2xxACEGAEBD1gTgAB2JwdKz0kgADsIXy2hgAEIACBiAnoinDOhi0b1JL1BQjAEcM3dPDThzfLmtJ3lVcPzUyVh67pqWwfK8Npj++UxZveVN5uQu80mTsmS9keQwhAILwErv7DRlm3+z1lADkdmsrD1/ZWtscQAhBAAKYHzAkgAJuzY6WHBBCAPYTP1hCAAAQgEDEBXRHO2fC8lFrywjQE4IjhGzoYff96Kdl/VHl197QGUni9fQ/t0/3wIX9QO5k6opNy3hhCAALhJdDjjqfk8EefKwNoXL+mbJ3JbHtlYBhCgIfA0QMREEAAjgAeS70jgADsHXt2hgAEIACByAnoinDOjqlJtWQjIyAih2/oQfsGcOdUeehq+24A647CEA3MAAAgAElEQVQfWZbfX3q0aWhIjWUQgECYCHS7bbUc/eS4csrMtldGhSEEThFAC6EZTAkgAJuSY52nBDj0PMXP5hCAAAQgECEBXRHO2S6zeZIUTc6OcGeWmxKYX1QqC4v3Ki/Pz8mQqbmZyvaxMnQe0tR37tNy6IPPqt0yq2WKrJg0QOLi4qq1xQACEIDA0AXFsufQh8ogOqTWl9VTcpTtMYQABBgBQQ+YE0AANmfHSg8JIAB7CJ+tIQABCEAgYgKOCNdhxko5flLdVddWyfK3SQPVF2DpKgFd0d7mm7O3/f0V+eP6smr5rJ6SLR1Sk6q1wwACEICAQ+DPG8pk5vJXlGHMHnW+XNm3jbI9hhCAAAIwPWBOAAHYnB0rPSSAAOwhfLaGAAQgAAFXCPSZ/ZQcOqY+K7FT8/qyajI3pVyBb+Dk5MmTkjG9SGllnRoJ8sptwyQ+Pl7JPtZG9699Tf5r1a5qty2bd2m1NhhAAAIQqCCgc07WSoyX0tuHW3tOUlUI2EoALcTWytgfFwKw/TUiwkoIcOjRFhCAAAQg4HcC588qkg8/V78C3KBOomz/9XC/p+3b+IN0AxgB2LdtSOAQsJ5A24InlGJ88KoeMqxLcyVbjCAAgW8IoIXQDaYEEIBNybHOUwIcep7iZ3MIQAACEHCBQLvpK+WLk18qe3JuS+26M1fZHkN3Ceg+uC9/UDuZOqKTu0G45G3h2tfFyae6FzeAqyPE30MAAt8moCoAc77QOxAwI4AWYsaNVSIIwHSBLwlw6PmybAQNAQhAAAJfE3BmAKdPW6nFIyFe5PU5fCVfC5qLxtMe3ymLN72p7HFC7zSZOyZL2T6WhgjAsaTNXhAIFwEE4HDVm2xjTwAtJPbMg7IjAnBQKhmyPDj0QlZw0oUABCAQMAK64wSc9J25sqV3jAgYCf+kE6QbwIuKX5d5RdwA9k/3ESkE/EMAAdg/tSJSfxJAC/Fn3WyIGgHYhioQgzYBDj1tZCyAAAQgAAGLCMwvKpWFxXu1ImrftJ48dfMgrTUYu0dgS9lhGbdog7LDpXn9pGfbRsr2sTREAI4lbfaCQLgIIACHq95kG3sCaCGxZx6UHRGAg1LJkOXBoReygpMuBCAAgYAR+OnDm2VN6btaWc0edb5c2beN1hqM3SOwpeyIjFv0orLDZXn9pAcCsDIvDCEAgWAQQAAORh3Jwl4CaCH21sb2yBCAba8Q8VVKgEOPxoAABCAAAT8TGH3/einZf1Q5hThx5v/mSnx8vPIaDN0lwAgId3niDQIQCCYBBOBg1pWs7CGAFmJPLfwWCQKw3ypGvOUEOPRoBAhAAAIQ8DOBn/5pk6x59V/KKdROjC+f/xsX50jBvLwgEKSHwN35j3/K757fVy3GJydnS8fmSdXaYQABCECgggACML0AgegSQAuJLt8ge0cADnJ1A5wbh16Ai0tqEIAABEJAYPKjJbJ8+1tamS7L7y892jTUWoOxewSCcgP4yy+/lH5zn5Z3PvisWjhZLVNkxaQBfPBQLSkMIAABBGB6AAKxIYAWEhvOQdwFATiIVQ1BThx6ISgyKUIAAhAIMIEpS0qksERPAM4f1E6mjugUYCp2p7b1jSMydqHGDGBLBfug5GF3txAdBMJLgBvA4a09mceGAFpIbDgHcRcE4CBWNQQ5ceiFoMikCAEIQCDABAqW7ZRHN7+pleGE3mkyd0yW1hqM3SPg3JxNn7ZSyaHNN2eDcpNZqRAYQQACMSeAABxz5GwYMgJoISEruIvpIgC7CBNXsSPAoRc71uwEAQhAAALuE9AV4ZwIuAHsfh10PaoKG6unZEuHVDtn5xYs2yGPbj6gnPr4Xq1l3tgLlO0xhAAEwk1A9Zwsm3dpuEGRPQQMCaCFGIJjmSAA0wS+JMCh58uyETQEIAABCHxNQPdr+M4yZgB73z7p056QL7+sPg6bhY0pS7ZLYcnB6pP42mJ095ay4PJuyvYYQgAC4SaAABzu+pN99AmghUSfcVB3QAAOamUDnheHXsALTHoQgAAEAk7AGScw+Ddrpezwx0qZZrVMlhWTLuJhXEq0omcUDAFYb/40AnD0+gnPEAgiAQTgIFaVnGwigBZiUzX8FQsCsL/qRbRfE+DQoxUgAAEIQMDvBJZtPSA3P7aj2jTq1UyQwhsGWDtSoNoEAmQQBAF46tIdsmSLzgiIVjJvbNcAVZFUIACBaBJQFYCfnJwtHZvbOSonmnzwDYFICaCFREowvOsRgMNbe19nzqHn6/IRPAQgAAEIiMimfUfksgderJbFo//RV/pmNK7WDoPoEwiCsMEIiOj3CTtAIKwEgvKwzLDWj7z9QQAtxB91sjFKBGAbq0JM1RLg0KsWEQYQgAAEIGA5gaVbD8gvFG4AL/5ZX+nXDgHY63IGRdiYsoQREF73EvtDIKgEdOfbM9s+qJ1AXtEkgBYSTbrB9o0AHOz6BjY7Dr3AlpbEIAABCISCgCMmXnx3sex776Nq881sniQrbxzI/N9qSUXXICjCRsGynfLo5jeVYU3o3VrmjrlA2R5DCEAgvATmr3pVFq59XRlA/qB2MnVEJ2V7DCEAARG0ELrAlAACsCk51nlKgEPPU/xsDgEIQAACERIIipgYIQZfLQ+KsBGUPHzVPAQLgZAQ4AOmkBSaND0lgBbiKX5fb44A7OvyhTd4Dr3w1p7MIQABCASBACKc/6o47fGdsniTzs3ZNJk7Jsu6RPnwwbqSEBAEAkOAETOBKSWJWEwALcTi4lgeGgKw5QUivMoJcOjRGRCAAAQg4GcCQRET/VwD3diDIto740f6z3tG3n7/02oRZLVMkRWTBjB+pFpSGEAAAg4BHjJJH0Ag+gTQQqLPOKg7IAAHtbIBz4tDL+AFJj0IQAACAScwv6hUFhbvVc4yPydDpuZmKttj6D6BIN2cnVdUKosU+m/1lGzpkJrkPkw8QgACgSRQsGyHPLr5gHJu43u1lnljmTGuDAxDCAgzgGkCcwIIwObsWOkhAQRgD+GzNQQgAAEIREzgLxvfkBmFLyv7mTM6S67ok6Zsj6H7BJybs9+793l5+eAH1Tq3/eas6gcQT07Olo7NEYCrLTgGEIBAOYGgfFOCckLAZgJoITZXx+7YEIDtrg/RVUGAQ4/WgAAEIAABPxNQvYFZkWNeToYUcAPY85LvPnRMxi18QT749ESVsSTXTpSl+f2tvTnLCAjP24gAIBBYAkH6pkRgi0RivieAFuL7EnqWAAKwZ+jZOBICHHqR0GMtBCAAAQh4TYAZwF5XwHz/Xe8ck188tkNeOvj+WU6cm793X9bVWvHXCRiBxrz2rIQABM5N4OTJk5IxvUgJU50aCfLKbcMkPj5eyR4jCEDgKwJoIXSCKQEEYFNyrPOUAIeep/jZHAIQgAAEIiTA12QjBOjxcucW7bb9R2VN6SE5+vFxaVC3hgztnCrdWzew/oFp9J7HzcP2EAgwAT5gCnBxSc0aAmgh1pTCd4EgAPuuZATMp170AAQgAAEI+J0Ab5L9XkH/xs/tc//WjsghYDsBPmCyvULEFwQCCMBBqKI3OSAAe8OdXSMkwKEXIUCWQwACEICApwScG6RD7i6Wve99VG0cnZonSdGNA62/WVptIhhYQQCBxooyEAQEAkmAD5gCWVaSsowAWohlBfFROAjAPioWoX5DgEOPboAABCAAAb8TKNx2QKb8dUe1aSz+WR/p165JtXYYQECFALfPVShhAwEImBDgAyYTaqyBgB4BtBA9Xlh/QwABmG7wJQEOPV+WjaAhAAEIQOA0Ao9vOyA3qQjAP+0j/b6DAEzzuEPAuX3+vXufl5cPflCtQ+ehdismDeD2ebWkMIAABBwCfMBEH0Ag+gTQQqLPOKg7IAAHtbIBz4tDL+AFJj0IQAACASfgiHAD/+tZOfDvT6rNNL1JPXnm5hxEuGpJYaBKYPehYzJu4QvywacnqlySXDtRlub3lw6pSapusYMABEJOwPndlj5tpRIFPmBSwoQRBM4igBZCU5gSQAA2Jcc6Twlw6HmKn80hAAEIQCBCAlvKjsi4RS8qe1mW1096tG2kbI8hBKojsOudY/KLx3bISwffP8vUEWbuvqwr4m91EPl7CEDgLAJtC55QorJ6SjZnjBIpjCBwJgG0EDrClAACsCk51nlKgEPPU/xsDgEIQAACERKYsqRECkveUvYyuntLWXB5N2V7DCGgQsC5rbdt/1FZU3pIjn58XBrUrSFDO6dK99YNuHGuAhAbCEDAWAAum3cp9CAAAQMCaCEG0FhSTgABmEbwJQEOPV+WjaAhAAEIQOBrArm/XSelbx9T5tG5RbKsvHGgsj2GEIAABCAAAS8IqN4ARgD2ojrsGQQCaCFBqKI3OSAAe8OdXSMkwKEXIUCWQwACEICApwR0BeDMFslShADsac3YHAIQgAAEqieAAFw9IywgEAkBtJBI6IV7LQJwuOvv2+w59HxbOgKHAAQgAAERmbJkuxSWHFRmwQgIZVQYQgACEICAhwQQgD2Ez9ahIIAWEooyRyVJBOCoYMVptAlw6EWbMP4hAAEIQCCaBDbve09++MBG5S0em9hXeqU3VrbHEAIQgAAEIOAFAQRgL6izZ5gIoIWEqdru5ooA7C5PvMWIAIdejECzDQQgAAEIRIXAlrIjMm7Ri8q+l+X1kx5tGynbYwgBCEAAAhDwggACsBfU2TNMBNBCwlRtd3NFAHaXJ95iRIBDL0ag2QYCEIAABKJCYH5RqSws3qvsOz8nQ6bmZirbYwgBCEAAAhDwggACsBfU2TNMBNBCwlRtd3NFAHaXJ95iRIBDL0ag2QYCEIAABKJC4KcPb5Y1pe8q+x7aOVUeurqnsj2GEIAABCAAAS8IqArAT07Olo7Nk7wIkT0h4GsCaCG+Lp+nwSMAe4qfzU0JcOiZkmMdBCAAAQjYQGD0/eulZP9R5VC6pzWQwusHKNtjCAEIQAACEIg1gS+//FLSp61U2rZ9s/qyekq2xMXFKdljBAEIfEUALYROMCWAAGxKjnWeEuDQ8xQ/m0MAAhCAQIQEtG8AZ6bKQ9dwAzhC7CyHAAQgAIEoEmC+fRTh4hoCXxNAC6EVTAkgAJuSY52nBDj0PMXP5hCAAAQgECGBeUWlskhjBnBeToYUMAM4QuoshwAEIACBaBKYsqRECkveUt5idPeWsuDybsr2GEIAAtwApgfMCSAAm7NjpYcEEIA9hM/WEIAABCAQMYGtbxyRsQtfVPaz4LKuMvrCVsr2GEIAAhCAAARiTSD3t+uk9O1jytt2bpEsK28cqGyPIQQggABMD5gTQAA2Z8dKDwkgAHsIn60hAAEIQCBiAs6cxIvmPyMHj36q5CurZbKsmHQRsxKVaGEEAQhAAAJeENAVgDNbJEsRArAXpWJPHxNAC/Fx8TwOHQHY4wKwvRkBDj0zbqyCAAQgAAE7CDgCcO85a+Rfxz5XDmhZfn/p0aahsj2GEIAABCAAgVgSmLJkuxSWHFTekhEQyqgwhMApAmghNIMpAQRgU3Ks85QAh56n+NkcAhCAAAQiJKA7AsLZLn9QO5k6olOEO7McAhCAAAQgEB0Cm/e9Jz98YKOy88cm9pVe6Y2V7TGEAAQYAUEPmBNAADZnx0oPCSAAewifrSEAAQhAIGIC81e9KgvXvq7lZ0LvNJk7JktrDcYQgAAEIACBWBHYUnZExi1Sn2+/LK+f9GjbKFbhsQ8EAkEALSQQZfQkCQRgT7CzaaQEOPQiJch6CEAAAhDwksC0x3fK4k1vaoXADWAtXBhDAAIQgECMCeh+uMnvtRgXiO0CQQAtJBBl9CQJBGBPsLNppAQ49CIlyHoIQAACEPCSgO6bZCdWZgB7WTH2hgAEIACB6gjofrjJN1uqI8rfQ+BsAmghdIUpAQRgU3Ks85QAh56n+NkcAhCAAAQiJKA7A7hd03qy5qYciYuLi3BnlkMAAhCAAASiQ0D3w01uAEenDngNNgG0kGDXN5rZIQBHky6+o0aAQy9qaHEMAQhAAAIxIPDll1/KkP8ulr3/+qja3eLjRIpuHCgdmydXa4sBBCAAAQhAwCsCuh9u8s0WryrFvn4mgBbi5+p5GzsCsLf82d2QAIeeITiWQQACEICANQRWbH9Lfv5oSbXxzBl9vlzRp021dhhAAAIQgAAEvCTgfLj5vXufl5cPflBtGFktU2TFpAF8s6VaUhhA4EwCaCF0hCkBBOD/3959QFdR5Q8c/wVpghCKQOggCggCCshK6AoCikhZUfAoCosxin+XVbHgWlZXlxVcG0VEKboUl6KAioLSLUuRKk0BAZfiLgQiiNL+53d3X04S3kvmvcyb9r73HA+Sd+eWz29mEn65cydWOY5zVYCbnqv8dI4AAgggYIPA2j0Z0mPUinxbWv5wB6lWtkS+9aiAAAIIIICA2wLbDmTKb8d8LkdPnIo4lNLFC8uM9FSpW6mU28OlfwR8J0AuxHch88yASQB7JhQMJBoBbnrRaFEXAQQQQMCLAuv2ZMiNJIC9GBrGhAACCCBQAIGt+zPlwX+skw0/HDmnFV35O7JPE5K/BfDl0MQWIBeS2PEvyOxJABdEj2NdE+Cm5xo9HSOAAAII2CRAAtgmSJpBAAEEEPCcgG4HsWZ3hizcfEAyjp+UMiWKSKcGleSK6mXY9sFz0WJAfhIgF+KnaHlrrCSAvRUPRmNRgJueRSiqIYAAAgh4VoAEsGdDw8AQQAABBBBAAAFPCpAL8WRYfDEoEsC+CBODzC3ATY9zAgEEEEDA7wIkgP0eQcaPAAIIIIAAAgg4K0AuxFnvIPVGAjhI0UyguXDTS6BgM1UEEEAgoAIkgAMaWKaFAAIIIIAAAgjESYBcSJxgE6BZEsAJEOQgTpGbXhCjypwQQACBxBKwmgBeNrSDVC9XIrFwmC0CCCCAAAIIIIDAOQLkQjgpYhUgARyrHMe5KsBNz1V+OkcAAQQQsEGABLANiDSBAAIIIIAAAggkkAC5kAQKts1TJQFsMyjNOSPATc8ZZ3pBAAEEEIifwPq9GdL9tRX5djB5QAtpW7dCvvWogAACCCCAAAIIIBBsAXIhwY5vPGdHAjieurQdNwFuenGjpWEEEEAAAYcErCaALyhWWGamp0q9lFIOjYxuEEAAAQQQQAABBLwoQC7Ei1Hxx5hIAPsjTowylwA3PU4JBBBAAAG/C6zbc1huHPW5pWk0qposcwa3kqSkJEv1qYQAAggggAACCCAQPAFyIcGLqVMzIgHslDT92CrATc9WThpDAAEEEHBB4N2Ve2TozPWWe9ZVwM1qlrVcn4oIIIAAAggggAACwRIgFxKseDo5GxLATmrTl20C3PRso6QhBBBAAAGXBB58d53MWLPXcu/p7evIw13qW65PRQQQQAABBBBAAIFgCZALCVY8nZwNCWAntenLNgFuerZR0hACCCCAgEsCaZNXycffHLDce98WNeT5Xo0s16ciAggggAACCCCAQLAEyIUEK55OzoYEsJPa9GWbADc92yhpCAEEEEDAJQFWALsET7cIIIAAAggggIBPBciF+DRwHhg2CWAPBIEhRC/ATS96M45AAAEEEPCWAHsAeysejAYBBBBAAAEEEPC6ALkQr0fIu+MjAezd2DCyPAS46XF6IIAAAgj4XWD9ngzpPmqFpWk0qposcwa3kqSkJEv1qYQAAggggAACCCAQPAFyIcGLqVMzIgHslDT92CrATc9WThpDAAEEEHBBYOMPR6Tbq8vz7fmCYoVl1j2pUrdSqXzrUgEBBBBAAAEEEEAguALkQoIb23jPjARwvIVpPy4C3PTiwkqjCCCAAAIOClhNAE+6s4W0q1fBwZHRFQIIIIAAAggggIAXBciFeDEq/hgTCWB/xIlR5hLgpscpgQACCCDgdwGrCeClD3WQGuVL+H26jB8BBBBAAAEEEECggALkQgoImMCHkwBO4OD7eerc9PwcPcaOAAIIIKACVhPASx5qLzXLlwQNAQQQQAABBBBAIMEFyIUk+AlQgOmTAC4AHoe6J8BNzz17ekYAAQQQsEeABLA9jrSCAAIIIIAAAggkigC5kESJtP3zJAFsvyktOiDATc8BZLpAAAEEEIirAAnguPLSOAIIIIAAAgggEDgBciGBC6ljEyIB7Bg1HdkpwE3PTk3aQgABBBBwQ4AEsBvq9IkAAggggAACCPhXgFyIf2Pn9shJALsdAfqPSYCbXkxsHIQAAggg4CEBEsAeCgZDQQABBBBAAAEEfCBALsQHQfLoEEkAezQwDCtvAW56nCEIIIAAAn4XsJoAXvxge6l1IS+B83u8GT8CCCCAAAIIIFBQAXIhBRVM3ONJACdu7H09c256vg4fg0cAAQQQEJFN/zoi17+yPF8LEsD5ElEBAQQQQAABBBBICAFyIQkR5rhMkgRwXFhpNN4C3PTiLUz7CCCAAALxFiABHG9h2kcAAQQQQAABBIIlQC4kWPF0cjYkgJ3Upi/bBLjp2UZJQwgggAACLgl8sOFfcu/fv86397f6N5erL62Ubz0qIIAAAggggAACCARbgFxIsOMbz9mRAI6nLm3HTYCbXtxoaRgBBBBAwAGBs2fPSscXl8h3Px7Lt7e6lS6Qj3/fVpKSkvKtSwUEEEAAAQQQQACB4AqQCwlubOM9MxLA8Ram/bgIcNOLCyuNIoAAAgg4JLD6+0PSe8wXlnubmZ4qzWqWtVyfiggggAACCCCAAALBEyAXEryYOjUjEsBOSdOPrQLc9GzlpDEEEEAAAYcFhs/fImMWf2e51/T2deThLvUt16ciAggggAACCCCAQPAEyIUEL6ZOzYgEsFPS9GOrADc9WzlpDAEEEEDAYYFHZ62Xqf/cY7nXvi1qyPO9GlmuT0UEEEAAAQQQQACB4AmQCwleTJ2aEQlgp6Tpx1YBbnq2ctIYAggggIDDAqwAdhic7hBAAAEEEEAAgQAIkAsJQBBdmgIJYJfg6bZgAtz0CubH0QgggAAC7gpEuwfw3/o0kZ5Nq7k7aHpHAAEEEEAAAQQQcFWAXIir/L7unASwr8OXuIPnppe4sWfmCCCAQBAEzp49Kx1fXCLf/XjM0nQaVS0tcwa3lqSkJEv1qYQAAggggAACCCAQPAFyIcGLqVMzIgHslDT92CrATc9WThpDAAEEEHBBYNSi7fLCx9ss9zwzPVWa1SxruT4VEUAAAQQQQAABBIIlQC4kWPF0cjYkgJ3Upi/bBLjp2UZJQwgggAACLgkMnbFO3l2113Lv6e3ryMNd6luuT0UEEEAAAQQQQACBYAmQCwlWPJ2cDQlgJ7XpyzYBbnq2UdIQAggggIBLAne/s1rmb9xvufe+LWrI870aWa5PRQQQQAABBBBAAIFgCZALCVY8nZwNCWAntenLNgFuerZR0hACCCCAgEsCrAB2CZ5uEUAAAQQQQAABnwqQC/Fp4DwwbBLAHggCQ4hegJte9GYcgQACCCDgLYGZq/fKA/9YZ3lQ7AFsmYqKCCCAAAIIIIBAIAXIhQQyrI5MigSwI8x0YrcANz27RWkPAQQQQMBpgW/+dUSue2W5pW4bVU2WOYNbSVJSkqX6VEIAAQQQQAABBBAIngC5kODF1KkZkQB2Spp+bBXgpmcrJ40hgAACCLggsGX/Ueny0rJ8e76gWGGZdU+q1K1UKt+6VEAAAQQQQAABBBAIrgC5kODGNt4zIwEcb2Haj4sAN724sNIoAggggICDAlYTwONvby4dG1RycGR0hQACCCCAAAIIIOBFAXIhXoyKP8ZEAtgfcWKUuQS46XFKIIAAAgj4XcBqAnjhH9rJxRUv8Pt0GT8CCCCAAAIIIIBAAQXIhRQQMIEPJwGcwMH389S56fk5eowdAQQQQEAFtu7PlM4vLc0XgxXA+RJRAQEEEEAAAQQQSAgBciEJEea4TJIEcFxYaTTeAtz04i1M+wgggAAC8RawmgDWPYBnpqdKvRT2AI53TGgfAQQQQAABBBDwsgC5EC9Hx9tjIwHs7fgwuggC3PQ4NRBAAAEE/C6wZd9R6fJy/i+B03k2qposcwa3kqSkJL9Pm/EjgAACCCCAAAIIxChALiRGOA4TEsCcBL4U4Kbny7AxaAQQQACBbAKz1uyVP7y7zrKJrgJuVrOs5fpURAABBBBAAAEEEAiWALmQYMXTydmQAHZSm75sE+CmZxslDSGAAAIIuCTw8Iz1Mn3VHsu9p7evIw93qW+5PhURQAABBBBAAAEEgiVALiRY8XRyNiSAndSmL9sEuOnZRklDCCCAAAIuCdz99iqZv+mA5d5vubK6/KV3Y8v1qYgAAggggAACCCAQLAFyIcGKp5OzIQHspDZ92SbATc82ShpCAAEEEHBJYODElfLploOWe+95RVX5282XW65PRQQQQAABBBBAAIFgCZALCVY8nZwNCWAntenLNgFuerZR0hACCCCAgEsCAyetlE83kwB2iZ9uEUAAAQQQQAAB3wmQC/FdyDwzYBLAngkFA4lGgJteNFrURQABBBDwokD6O6vlo437LQ+tb4vq8nwvtoCwDEZFBBBAAAEEEEAgYALkQgIWUAenQwLYQWy6sk+Am559lrSEAAIIIOCOwCMz18u0lbwEzh19ekUAAQQQQAABBPwnQC7EfzHzyohJAHslEowjKgFuelFxURkBBBBAwIMC7329V34/fZ3lkc1MT5VmNctark9FBBBAAAEEEEAAgWAJkAsJVjydnA0JYCe16cs2AW56tlHSEAIIIICASwLb9h+Va19aZqn3RlWTZc7gVpKUlGSpPpUQQAABBBBAAAEEgidALiR4MXVqRiSAnZKmH1sFuOnZykljCCCAAAIuCGw/kCmd/rY0354vKFZYZt2TKnUrlcq3LhUQQAABBBBAAAEEgitALiS4sY33zEgAx1uY9uMiwE0vLqw0igACCCDgoIDVBPAbtzWTTg1THBwZXSGAAAIIIIAAAgh4UYBciBej4o8xkQD2R3G+J+QAACAASURBVJwYZS4BbnqcEggggAACfhewmgBeMKStXMLqX7+Hm/EjgAACCCCAAAIFFiAXUmDChG2ABHDCht7fE+em5+/4MXoEEEAAARESwJwFCCCAAAIIIIAAAtEIkAuJRou62QVIAHM++FKAm54vw8agEUAAAQSyCVhNAH8ypC37/3LmIIAAAggggAACCAi5EE6CWAVIAMcqx3GuCnDTc5WfzhFAAAEEbBD49mCmdHwx/5fAvX5bM+nMHsA2iNMEAggggAACCCDgbwFyIf6On5ujJwHspj59xyzATS9mOg5EAAEEEPCIwLcHf5KOLy7JdzQXFCssM9NTpV5KqXzrUgEBBBBAAAEEEEAguALkQoIb23jPjARwvIVpPy4C3PTiwkqjCCCAAAIOCljdAkKH1KhqsswZ3EqSkpIcHCFdIYAAAggggAACCHhJgFyIl6Lhr7GQAPZXvBjt/wS46XEqIIAAAgj4XeD9tT/I/dPWWp6GrgJuVrOs5fpURAABBBBAAAEEEAiWALmQYMXTydmQAHZSm75sE+CmZxslDSGAAAIIuCTwyMz1Mm3lHsu9p7evIw93qW+5PhURQAABBBBAAAEEgiVALiRY8XRyNiSAndSmL9sEuOnZRklDCCCAAAIuCdzz9zXy4YZ9lnvv26KGPN+rkeX6VEQAAQQQQAABBBAIlgC5kGDF08nZkAB2Upu+bBPgpmcbJQ0hgAACCLgkwApgl+DpFgEEEEAAAQQQ8KkAuRCfBs4DwyYB7IEgMIToBbjpRW/GEQgggAAC3hJ47+u98vvp6ywPaubdLaVZrXKW61MRAQQQQAABBBBAIFgC5EKCFU8nZ0MC2Elt+rJNgJuebZQ0hAACCCDgkkC0CeAZd7eU5iSAXYoW3SKAAAIIIIAAAu4LkAtxPwZ+HQEJYL9GLsHHzU0vwU8Apo8AAggEQOCxWRtkyj93W54JL4GzTEVFBBBAAAEEEEAgkALkQgIZVkcmRQLYEWY6sVuAm57dorSHAAIIIOC0QLR7APMSOKcjRH8IIIAAAggggIC3BMiFeCsefhoNCWA/RYuxZglw0+NkQAABBBDwu8Dw+VtkzOLvLE+DFcCWqaiIAAIIIIAAAggEUoBcSCDD6sikSAA7wkwndgtw07NblPYQQAABBJwWWP39Iek95gvL3c5MT5VmNctark9FBBBAAAEEEEAAgWAJkAsJVjydnA0J4AJqnz59WjZv3iyrVq2S1atXmz/XrVsnP//8s2m5f//+MnHixKh62bdvn4wdO1bmzp0ru3btkhMnTkhKSoq0adNGBgwYIO3atYuqvffff1/efvttWblypRw4cEBKly4tderUkZ49e0paWpokJydbbs/usVnuOFdFbnqxynEcAggggIBXBM6ePSs3vLZcNv5wNN8hNaqaLHMGt5KkpKR861IBAQQQQAABBBBAIJgC5EKCGVcnZkUCuIDKvXv3llmzZkVsJdoE8OzZs02SNyMjI2KbgwYNkjFjxsh5552X5+gzMzOlX79+Mm/evIj1qlWrJtOnT5fU1NR8JewcW76d5VOBm15BBTkeAQQQQMALAtsOZMpvx3wuR0+cijic0sULy4z0VKlbqZQXhswYEEAAAQQQQAABBFwSIBfiEnwAuiUBXMAg9ujRQ3SFbaiUK1dOypcvL9u3bzdfiiYBvHDhQrnuuuvk5MmT5tjrr79eunfvLiVLlpQ1a9bI+PHj5ejR/64S0iTwuHHjIo7+1KlTpq0FCxaYOpUqVTLHNGjQQA4dOiRTp06VFStWmM/KlCkjy5cvl4YNG0Zsz86xFZDcHM5Nzw5F2kAAAQQQ8ILA1v2Z8uA/1smGH46cMxxd+TuyTxOSv14IFGNAAAEEEEAAAQRcFiAX4nIAfNw9CeACBu+5554TXWnbrFkz81/t2rXNlg933nmnadlqAli3eahXr57s3r3bHPfqq6/K4MGDc4xu27ZtZvuH/fv3m69/8skn0qlTp7Az0BXC99xzj/lMk76fffaZSQJnLw8++KCMHDnSfKlVq1YmCRyu2D22ApKbw7np2aFIGwgggAACXhHQ7SDW7M6QhZsPSMbxk1KmRBHp1KCSXFG9DNs+eCVIjAMBBBBAAAEEEHBZgFyIywHwcfckgOMQvFgSwKNGjcpK+N5www0yZ86csCPT7SZ02wktV111lUmE5i66L7Fu7RBKFOvexE2bNg1br3nz5rJ27Vrz2fz586Vz587n1LNzbHZxc9OzS5J2EEAAAQQQQAABBBBAAAEEEEDADwLkQvwQJW+OkQRwHOISSwK4bdu2smzZMjOaRYsWSfv27cOO7MyZM+YFbvpyOC07d+6UWrVq5airq32vueYa8zVdMbx48eKIs5wwYYLZc1hLpNXKdo7NLm5uenZJ0g4CCCCAAAIIIIAAAggggAACCPhBgFyIH6LkzTGSAI5DXKJNAOsWEroPryZ3S5UqJYcPH87zBW/p6ekyduxYM/LRo0eL/j17GTp0qLzwwgvmS8OHDxf9e6Ry4MABSUlJMR9XrFhR9O/Zi91js4ubm55dkrSDAAIIIIAAAggggAACCCCAAAJ+ECAX4ocoeXOMJIDjEJdoE8BfffWV2c5Bi662XbJkSZ6jeuutt2TgwIGmju7zq1s0ZC9du3Y12zlo0dXAHTp0yLO9GjVqyJ49e0ydgwcPSoUKFbLq2z02u7i56dklSTsIIIAAAggggAACCCCAAAIIIOAHAXIhfoiSN8dIAjgOcYk2ATx58mSz/YIWKy+N0y0irr76alNft3pYuHBhjllcdNFFZmsILeG2iMg9Zd0mYunSpebLug1F69ats6rYPTYr3OH2Nc593IYNGyQtLc18+fPPP5eWLVtaaZo6CCCAAAIIIIAAAggggAACCCCAgC8FSAD7MmyeGDQJ4DiEIdoE8CuvvCL333+/GckDDzwgI0aMyHNU69evlyZNmpg6zZo1k1WrVuWoX65cObONhBbdwuGCCy7Is71evXrJ7NmzTZ25c+dKt27dsurbPTYr3ElJSVaqZdUhARwVF5URQAABBBBAAAEEEEAAAQQQQMCHAiSAfRg0jwyZBHAcAhFtAvi5556TYcOGmZHon88++2yeo9q+fbvUrVvX1NE/t27dmqN+0aJF5eTJk+Zr+mfhwoXzbO/WW2+VKVOmmDr6Z9++fbPq2z02K9wkgK0oUQcBBBBAAAEEEEAAAQQQQAABBBJJgARwIkXb3rmSALbX07RWkATw448/Ls8880yeo3IrAWzH2KxwswWEFSXqIIAAAggggAACCCCAAAIIIIBAIgmQAE6kaNs7VxLA9nrGlAC2e5sFv28BYSUk3PSsKFEHAQQQQAABBBBAAAEEEEAAAQSCIkAuJCiRdH4eJIDjYB7tCmC7X7Tm95fAWQkJNz0rStRBAAEEEEAAAQQQQAABBBBAAIGgCJALCUoknZ8HCeA4mEebAP7qq6/kqquuMiNp27atLFmyJM9RvfXWWzJw4EBT55577pFRo0blqN+1a1eZP3+++dpnn30mHTp0yLO9GjVqyJ49e0ydgwcPSoUKFbLq2z02u7i56dklSTsIIIAAAggggAACCCCAAAIIIOAHAXIhfoiSN8dIAjgOcYk2AZyZmSllypSRM2fOSKlSpeTw4cNy3nnnRRxZenq6jB071nw+evRo0b9nL0OHDpUXXnjBfGn48OGif49UDhw4ICkpKebjihUriv49e7F7bHZxc9OzS5J2EEAAAQQQQAABBBBAAAEEEEDADwLkQvwQJW+OkQRwHOISbQJYh6Arf5ctW2ZGs3jxYmnXrl3YkWmS+OKLL5adO3eaz/XPWrVq5airq36vueYa87X27dvLokWLIs5ywoQJMmDAAPP5HXfcIfr33MXOsdnFzU3PLknaQQABBBBAAAEEEEAAAQQQQAABPwiQC/FDlLw5RhLAcYhLLAlgXcl77733mtHccMMNMmfOnLAjmzVrlvTu3dt8pttG6MWfu5w+fVqqVasm+/fvNx+tXr1amjZtGrZe8+bNZe3ateYz3Taic+fO59Szc2x2cXPTs0uSdhBAAAEEEEAAAQQQQAABBBBAwA8C5EL8ECVvjpEEcBziEksC+MSJE1KvXj3ZvXu3GdFrr72WlRAODXH79u1mpXAosbtgwQLp2LFj2BmMGTPG7A+spWHDhmYvYN3iIXt56KGHZMSIEeZLrVq1kuXLl4dty+6x2UHOTc8ORdpAAAEEEEAAAQQQQAABBBBAAAG/CJAL8UukvDdOEsAFjIluwfDmm2/maGX9+vUyd+5c87XGjRubFb3Zi67G7dWr1zk9L1y4UK677jo5efKk+axbt27SvXt3KVmypKxZs0bGjx8vR44cMZ8NGjRIxo0bF3H0p06dMm1pkliL7vOrxzRo0EAOHTokU6dOzUr4Jicny4oVK0yiOFKxc2wFJDeHc9OzQ5E2EEAAAQQQQAABBBBAAAEEEEDALwLkQvwSKe+NkwRwAWOi+/V26NAhqlb69+8vuko4XJk9e7bZkzcjIyNim5rI1RW+eb0oTg/WF7j169dP5s2bF7Et3Spi+vTpkpqamu8c7Bxbvp3lU4GbXkEFOR4BBBBAAAEEEEAAAQQQQAABBPwkQC7ET9Hy1lhJABcwHnYngHU4+/btMwleXUW8a9cu0S0YKleuLK1bt5aBAwdGfEFcpKm8//77MnnyZFm5cqUcPHhQSpUqJXXq1DGrkNPS0kRXAFstdo/Nar+563HTi1WO4xBAAAEEEEAAAQQQQAABBBBAwI8C5EL8GDVvjJkEsDfiwCiiFOCmFyUY1RFAAAEEEEAAAQQQQAABBBBAwNcC5EJ8HT5XB08C2FV+Oo9VgJterHIchwACCCCAAAIIIIAAAggggAACfhQgF+LHqHljzCSAvREHRhGlADe9KMGojgACCCCAAAIIIIAAAggggAACvhYgF+Lr8Lk6eBLArvLTeawC3PRileM4BBBAAAEEEEAAAQQQQAABBBDwowC5ED9GzRtjJgHsjTgwiigFuOlFCUZ1BBBAAAEEEEAAAQQQQAABBBDwtQC5EF+Hz9XBkwB2lZ/OYxXgpherHMchgAACCCCAAAIIIIAAAggggIAfBciF+DFq3hgzCWBvxIFRRCnATS9KMKojgAACCCCAAAIIIIAAAggggICvBciF+Dp8rg6eBLCr/HQeqwA3vVjlOA4BBBBAAAEEEEAAAQQQQAABBPwoQC7Ej1HzxphJAHsjDowiSgFuelGCUR0BBBBAAAEEEEAAAQQQQAABBHwtQC7E1+FzdfAkgF3lp/NYBbjpxSrHcQgggAACCCCAAAIIIIAAAggg4EcBciF+jJo3xkwC2BtxYBRRCixcuFA6depkjnr99delUaNGUbZAdQQQQAABBBBAAAEEEEAAAQQQQMA/Ahs2bJC0tDQz4AULFkjHjh39M3hG6qoACWBX+ek8VoFx48Zl3fRibYPjEEAAAQQQQAABBBBAAAEEEEAAAT8K6GK4u+66y49DZ8wuCJAAdgGdLgsuQAK44Ia0gAACCCCAAAIIIIAAAggggAAC/hQgAezPuLk1ahLAbsnTb4EE/vWvf8m8efNMGxdddJGULFmyQO25dXD2xzfYysKtKNAvAjkFuC45IxDwpgDXpjfjwqgQ4NrkHEDAmwJcm96MS0FHdezYMdmxY4dpplu3blKlSpWCNsnxCSJAAjhBAs00vSnABu7ejAujSmwBrsvEjj+z964A16Z3Y8PIEluAazOx48/svSvAtend2DAyBNwQIAHshjp9IvA/Ab4pcyog4D0BrkvvxYQRIaACXJucBwh4U4Br05txYVQIcG1yDiCAQHYBEsCcDwi4KMA3ZRfx6RqBCAJcl5waCHhTgGvTm3FhVAhwbXIOIOBNAa5Nb8aFUSHglgAJYLfk6RcBVjNxDiDgSQF+WPZkWBgUAqwA5hxAwKMCfN/0aGAYVsILcG0m/CkAAAI5BEgAc0Ig4KIA35RdxKdrBCIIcF1yaiDgTQGuTW/GhVEhwLXJOYCANwW4Nr0ZF0aFgFsCJIDdkqdfBFgBzDmAgCcF+GHZk2FhUAiwAphzAAGPCvB906OBYVgJL8C1mfCnAAAI5BAgAcwJgYCLAnxTdhGfrhGIIMB1yamBgDcFuDa9GRdGhQDXJucAAt4U4Nr0ZlwYFQJuCZAAdkuefhFgBTDnAAKeFOCHZU+GhUEhwApgzgEEPCrA902PBoZhJbwA12bCnwIAIJBDgAQwJwQCLgrwTdlFfLpGIIIA1yWnBgLeFODa9GZcGBUCXJucAwh4U4Br05txYVQIuCVAAtgtefpFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiLEACOM7ANI8AAggggAACCCCAAAIIIIAAAggggAACCLglQALYLXn6RQABBBBAAAEEEEAAAQQQQAABBBBAAAEE4ixAAjjOwDSPAAIIIIAAAggggAACCCCAAAIIIIAAAgi4JUAC2C15+kUAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIsQAI4zsA0jwACCCCAAAIIIIAAAggggAACCCCAAAIIuCVAAtgtefpFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiLEACOM7ANI8AAggggAACCCCAAAIIIIAAAggggAACCLglQALYLXn6RQABBBBAAAEEEEAAAQQQQAABBBBAAAEE4ixAAjjOwDSPAAIIIIAAAggggAACCCCAAAIIIIAAAgi4JUAC2C15+kUAAQQQQAABBBBAAAEEEEAAAQQQQAABBOIsQAI4zsA0j0A4gffff1/efvttWblypRw4cEBKly4tderUkZ49e0paWpokJycDhwACBRTIzMyUTz75RBYtWiRr1qyR7du3S0ZGhpx//vlSpUoVadGihfTr1086d+4sSUlJlnrbt2+fjB07VubOnSu7du2SEydOSEpKirRp00YGDBgg7dq1s9QOlRBAILxA//79ZfLkyVkfPvnkk/LUU0/ly8W1mS8RFRCIWuDrr7+WKVOmyMKFC2Xv3r1y9OhRufDCC6Vy5cpy1VVXSfv27c3Pruedd17Etrk2o2bnAAQiCujPnm+++ab52XbLli1y5MgRKVasmFSsWFEuv/xy6dWrl9x8881SpEiRfBW5NvMlogICgRMgARy4kDIhLwtoQkoTTvPmzYs4zGrVqsn06dMlNTXVy1NhbAh4WuDFF1+UYcOGmQRtfkWTt++8847UqFEjz6qzZ882SV5NIkcqgwYNkjFjxuT5j+H8xsPnCCSqwPz586Vr1645pm8lAcy1mahnDPOOl4Ameu+//36ZNGmSnD17Ns9uDh8+LGXKlAlbh2szXhGi3UQU0J9tH3vsMfnll1/ynH69evVkxowZctlll0Wsx7WZiGcQc0ZAhAQwZwECDgmcOnVKrrvuOlmwYIHpsVKlSqLJogYNGsihQ4dk6tSpsmLFCvOZ/iC9fPlyadiwoUOjoxsEgiVw9913y+uvv24mpb9Uueaaa6R58+ZSoUIF+fnnn+Wrr74ySd+ffvrJ1Kldu7Z8+eWXZgVFuKKrn/T6PXnypPn4+uuvl+7du0vJkiXN6uLx48eblVFa9LoeN25csECZDQJxFtDrR/+xumfPHnNdHTt2zPSYXwKYazPOgaH5hBPQn0n1yZhVq1aZuev3xd69e0vTpk3NE2v65JquBl68eLF5kk3rh0sAc20m3KnDhOMo8Nprr8l9992X1UOrVq3khhtukOrVq5ufPzdt2mR+YaOLjbToSv0NGzaYp9RyF67NOAaKphHwuAAJYI8HiOEFR0BXBd5zzz1mQpr0/eyzz0wSOHt58MEHZeTIkeZL+o1dk8AUBBCIXiA9PV127Nghek1p8rdQoULnNPL999+bf+Ru3brVfHbnnXfKW2+9dU49XUWsqyl2795tPnv11Vdl8ODBOept27bNbP+wf/9+83XdeqJTp07RD5wjEEhQAd3+SH9xor+w6dOnj+hKJy15JYC5NhP0ZGHacRXo0qWLfPzxx6aP3/3ud/K3v/1NLrjggrB96iPk+ovVwoUL5/icazOuIaLxBBPQhQv6b8ZQcle/V+pig9zlxx9/lKuvvlo2btxoPhoyZEjW99JQXa7NBDt5mC4CuQRIAHNKIOCAwOnTp80/akPJodWrV5uVFLmL1tNVimvXrjUf6eOwmqCiIIBAdAK6IqlcuXL5HrRu3TqzZ5qWEiVKiP7wrH9mL6NGjcpK+Opqizlz5oRtd9asWWaVlBbdG/GLL77It38qIICAmL0M9Rc1+qi57q+tKw+ffvppQ5NXAphrk7MHAXsFJk6caH4ZquWmm26Sd999N6YOuDZjYuMgBMIK6Ird0KIC/XeirryPVHSbQf1ZVUuzZs2yVvKH6nNtcpIhkNgCJIATO/7M3iEBXe2r/7jVoqsE9bG5SGXChAlmn1Et+jIc/WGcggAC8RO49NJLzYs0tGhCuHHjxjk6a9u2rSxbtsx8TRNV+tKbcOXMmTPmZY76gg4tO3fulFq1asVv4LSMQAAEjh8/Lo0aNTIr9vXFNdOmTTMvfbOSAObaDMAJwBQ8JaBPqG3evNm8QEqfktGXvcVSuDZjUeMYBMIL6IsYb731VvOhvkvm73//e0QqfSJNn1rTon+Gfr4NHcC1yVmGQGILkABO7Pgze4cEhg4dKi+88ILpbfjw4aJ/j1R0b7XQfk2675r+nYIAAvETaNGiRdZqCt0H+De/+U1WZ/q4ne5tqMndUqVKib7sJq+3nevWE2PHjjXHjx49WvTvFAQQiCygL5p65ZVXpGzZsibxpI+5WkkAc21yViFgr4C+h6J169am0Z49e4o+1RJL4dqMRY1jEIgs8Omnn0rHjh1NhSuvvFL++c9/Rqz8wQcfSLdu3czn+lSavgwuVLg2OcsQQIAEMOcAAg4I6FvNdTsHLboauEOHDnn2WqNGDfMiHC0HDx40+6tREEDAfgF9k7ImnI4cOWIa1/0Ms78wQ18Wp9s5aNFVE0uWLMlzELqH8MCBA00d3fNbH7WjIIBAeIHPP/9c2rRpY37BotdO6NFzKwlgrk3OKgTsFXjuuedk2LBhplF94ZR+D9OVh/pkmr5MSr9Pli9f3jxWrvt09+3bN+wvRLk27Y0LrSGg+/bqvw11mzItek3ecccd58D85z//MU+c6tNs+u4LfXotNTU1qx7XJucSAgiQAOYcQMABgYsuusg8Dq7FymPhuk3E0qVLTX395h1akeHAUOkCgYQSyL7foe7LrftzZy+TJ082W7FosbIli24RoS/g0KI/hOu+bRQEEDhXQP9Bq/tv60sYc18rVhLAXJucVQjYK9CrVy+ZPXu2afS9996Tl19+2Wx7FKno90ytV716db5v2hsKWkPgHAG9NnWbpJMnT5rP9JenutevvmNGV/Zu2rTJbBt49OhR89LG8ePHm/r8TMvJhAAC2QVIAHM+IOCAgL6MSh8d16LfpCO9TTk0lOw/hOsLcUKP8jgwVLpAIGEEdCVFw4YNs1ZU6OOu+thr9qKPpusj6loeeOABGTFiRJ4+69evlyZNmpg64V6+kTC4TBSBfARCWyOdf/75ZnWh7p8dKlYSwFybnGII2CvQsmVL0W2QtFxyySWyfft2KVasmNx+++1mIULhwoXNykJNLOmLVrVcfPHF5iVTycnJWYPh2rQ3LrSGQEhg+fLlcu+994r+rBmu6N7d+r01LS3tnF/MaH2uTc4lBBAgAcw5gIADAkWLFs36ja3+5lZ/iM6r6Eb/+tidFv1TH7OjIICAfQK//vqr2U8t9HK3Hj16ZK18yt5L9kdi9dHYZ599Ns9B6D+Y69ata+ron7q6kYIAAjkFNGGkW6ucPn1a/vrXv8pDDz2Uo4KVBDDXJmcVAvYK1K9fP8f3LN3uQfceDf1SM9Tb/v37zfdPXXGoRRNSumVEqHBt2hsXWkMgJHD27FnzhOiDDz5ofvESruh7K3R7CL0O9Res/EzL+YMAAtkFSABzPiDggAAJYAeQ6QIBiwK636iuaAq9RVlXHq5cudK8hCp3yf4P2ccff1yeeeaZPHshAWwxCFRLWAH95Yuujt+4caNcccUV5trL/WLFaBPAXJsJezoxcRsF9JeW+j0sVHSbldtuuy1sD7oSWK9fTUgVL17cvK9CX5Sqhe+bNgaFphD4n4Du76t7b+u7ZPTn1T/+8Y9y4403mpW+x48fN1uYjRw5Uj788ENzhL7gWP9ff5ETKlybnE4IIEACmHMAAQcE2ALCAWS6QMCCgP5jVR+Ne+ONN0xtfamGvtitVq1aYY/mcTkLqFRBIAqBJ554wvwiRZO++iZz3Uc0d7GSAObajAKdqghYENBfzKxZs8bU1C0d/v3vf+f5xJq+XOqLL74w9T/66CPp0qWL+X+uTQvYVEEgCgFN8Or1uWXLFpP81Ze56TYt4crgwYOzXkCsT5CGnijl2owCnKoIBFiABHCAg8vUvCPAS+C8EwtGkrgCmvzVt5qPHTvWIOiLMxYvXpxj79HcOrxoKnHPF2Zuv4CuGrzyyivNlki67YNu/xCuWEkAc23aHx9aTGwB3dZBt3zQoi+YCr2MOJLKfffdl7X1w6uvviqaeNLCtZnY5xGzt19A3z8R2ipJV/E++uijETvRZHHVqlUlIyNDChUqJHv37pXKlStzbdofFlpEwJcCJIB9GTYG7TeBrl27yvz5882w9dGdDh065DkFXZW4Z88eU0cfq6tQoYLfpsx4EfCUgCZ/dZ/CMWPGmHHpD8ea/NUX2ORVdJWF7lWqpW3btma1cF7lrbfekoEDB5oqmmweNWqUpxwYDAJuCgwZMkReeukl84/SRx555Jz9CUNj0++TixYtMn/V75dXX321+f969erJTTfdZP6fa9PNSNJ3EAWyrxy8/vrrZd68eXlOU7de+fOf/2zq6J+PPfYY12YQTwzm5LpAu3btsn4ho3v/6mrgvIpev6GtbEh4BwAAGFJJREFUIObMmSM33HAD16brUWQACHhDgASwN+LAKAIuEHrbuU5z+PDh5g2tkcqBAwckJSXFfFyxYkXRv1MQQCB2gdzJ3ypVqpjkb6TH57L3lJmZKfpCDd03WPc3PHz48Dn7lWavn56enrXCePTo0aJ/pyCAwH8Ffv/738vLL78cM4fud/jee++Z47k2Y2bkQATCCujWSHfddZf5rHXr1lkvSY3ElT1hrC+B01+ycm1yciFgv4D+vPrtt9+ahrdt25bvz6+RXibO9037Y0OLCPhNgASw3yLGeH0poKuZrrnmGjP29u3bZ61sCjeZCRMmyIABA8xH+hZX/TsFAQRiE8id/NXH4DT5qy+7sVp05e+yZctMdT1WV2KEK5ok1hXFO3fuNB/rn5H2FrbaN/UQCJKAnQlgdeHaDNLZwVzcFtBHxfUJNP2+Wbp0abMHcJEiRSIOq2XLlvLll1+azxcsWCC6hUSocG26HU36D5JA9v25Fy5cmPVvykhz1F/grFixwnz88ccfy7XXXsu1GaQTgrkgUAABEsAFwONQBKwKnD592uw3un//fnOIvqk13ItvtF7z5s1l7dq1pp5uG9G5c2er3VAPAQRyCeiKJF2Jq0VX1msCVx8jj6bo8aGVTfoYnT5OF67MmjVLevfubT7SbSNCL8eJpi/qIoCAiJU9gNWJa5OzBQF7BXTLFf0+qWXSpEly++23h+1Af0694oorzGf6dIw+rXb++edn1eXatDcutJbYArogSK9HLbpI6M0334wIoiuFL730Ujl16pTZbkm3EixfvjzXZmKfQswegSwBEsCcDAg4JKB7j+qeoFoaNmxo9gLWLR6yF93gXzf619KqVStZvny5Q6OjGwSCJ5D9BTWa/NU9RevXrx/1RE+cOGGSxrt37zbHZn/UNdTY9u3bzWrE0C95cq+GirpTDkAggQWsJoC5NhP4JGHqcRHQX1ympqaatjVppD+rNm7cOEdfmuzVp9o2bdpkvj5s2DB59tlnc9Th2oxLeGg0QQU++eSTrAVBSUlJotu1hN43kZ1Er01978zXX39tvhxu0QLXZoKeREwbgf8JkADmVEDAIQH9Tex1111nHpPTogmpQYMGSYMGDeTQoUMyderUrIRvcnKyeXRHE8UUBBCIXiD7y2n0h2V9a7KV5K+uzNdHYHMXfeROr9+TJ0+aj7p16ybdu3eXkiVLypo1a2T8+PFy5MgR85le1+PGjYt+0ByBAAJGwGoCWOtybXLSIGCvgL6gUd9XoaVYsWLSv39/sydw4cKFzRNq+v1Of27Voo+m62KF4sWL833T3jDQGgI5BPQFqDNmzMj6mm5Hpvvi6xOmP//8s+jL4d5++23JyMgwdcqWLWtelhrufRd83+TkQiBxBUgAJ27smbkLArr5fr9+/fJ8s7J+I58+fXrWCgwXhkmXCPheQPfaXrJkSdTz0D239VG7cGX27Nnm0bvQD9fh6mjyV1f7n3feeVH3zQEIIPBfgWgSwFqfa5MzBwF7BXRVryaBdWuySEW3KNPFC5poilS4Nu2NC60lrsAvv/xitiPLa/uHkI4mfadNmxZ2u8FQHa7NxD2XmHliC5AATuz4M3uXBN5//32ZPHmyrFy50uzNpPun1alTR3r16iVpaWmiK4ApCCAQu0A8EsA6mn379pkE79y5c2XXrl2ij9Lpi+V0dZQ+jhfpBXGxz4QjEUg8gWgTwFybiXeOMOP4C6xbt84km/TJtR9++ME8AaNbl+kWEbo3sD5qbqXwfdOKEnUQsCagq/AnTpxonhTdsWOHHD16VIoWLWquTX2KrUePHtKnTx+zej+/wrWZnxCfIxA8ARLAwYspM0IAAQQQQAABBBBAAAEEEEAAAQQQQAABBIwACWBOBAQQQAABBBBAAAEEEEAAAQQQQAABBBBAIKACJIADGlimhQACCCCAAAIIIIAAAggggAACCCCAAAIIkADmHEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBAIqQAI4oIFlWggggAACCCCAAAIIIIAAAggggAACCCCAAAlgzgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCgAiSAAxpYpoUAAggggAACCCCAAAIIIIAAAggggAACCJAA5hxAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQCKkACOKCBZVoIIIAAAggggAACCCCAAAIIIIAAAggggAAJYM4BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgoAIkgAMaWKaFAAIIIIAAAggggAACCCCAAAIIIIAAAgiQAOYcQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEAipAAjiggWVaCCCAAAIIIIAAAggggAACCCCAAAIIIIAACWDOAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIKACJIADGlimhQACCCCAAAIIIIAAAggggAACCCCAAAIIkADmHEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBAIqQAI4oIFlWggggAACCCCAAAIIIIAAAggggAACCCCAAAlgzgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCCgAiSAAxpYpoUAAggggAACCPhFYNeuXVK7dm0z3P79+8vEiRP9MvS4j3PKlCly6623SsmSJeXbb7+VlJQUW/u86aabZMaMGdK+fXtZtGiRrW3TGAIIIIAAAggggIA3BEgAeyMOjAIBBBBAAAEEEAiMQEZGhrz00ktmPpdffrn06NEjz7mRAA7Pk5mZKfXq1ZN9+/bJE088IU8//bTt58j27dulQYMGcurUKdFkc9++fW3vgwYRQAABBBBAAAEE3BUgAeyuP70jgAACCCCAAAKBE4g2oRtt/cCBRZjQk08+KX/605+kVKlS8v3330vZsmXjMvXbbrtN3nnnHbMKe8uWLVK0aNG49EOjCCCAAAIIIIAAAu4IkAB2x51eEUAAAQQQQACBwAqQ0C14aA8dOiS1atUSXQX8wAMPyIgRIwreaIQWNm7cKI0aNTKfjhkzRu6+++649UXDCCCAAAIIIIAAAs4LkAB23pweEUAAAQQQQACBQAuQAC54eJ999ln54x//KElJSbJ161a55JJLCt5oHi20atVKPv/8c9OPrgIuVKhQXPujcQQQQAABBBBAAAHnBEgAO2dNTwgggAACCCCAQEIIkAAuWJjPnDkjNWrUkB9++EE0Mbt8+fKCNWjh6HHjxklaWpqp+dFHH0mXLl0sHEUVBBBAAAEEEEAAAT8IkAD2Q5QYIwIIIIAAAggg4AOB7Inf/Ia7aNEiad++valmJWGsdZcsWWLqnz171vw3depUmThxougWBocPHzZJ086dO8vDDz8sVatWzRrCr7/+al5wpnV1Na3WrVatmnTv3l2GDRsm5cuXz2+45vOlS5eavXKXLVtmXsx24sQJqVChgrRo0UL69esnvXr1Mit2C1o+/vjjrATsiy++KEOGDMmzyaNHj8obb7wh8+bNk2+++cbMr3jx4mZslSpVkquuukquvfZaufrqqyPu7/vjjz9KSkqKaPL5lltuMbYUBBBAAAEEEEAAgWAIkAAORhyZBQIIIIAAAggg4LqAUwngY8eOSZ8+feSDDz4IO2dNfH722Wdy2WWXycGDB6Vnz55me4NwpXr16iaxq/vtRioZGRly++23y9y5c/M0btu2rcycOVMuvPDCAsVCV+Lqilwtq1evlqZNm0ZsTz/v1q2b7N+/P98+V65cKc2bN49Yr3HjxrJhwwbz0rn//Oc/UqRIkXzbpAICCCCAAAIIIICA9wVIAHs/RowQAQQQQAABBBDwhcDx48flk08+MUnX0HYCHTp0kP/7v/87Z/ytW7fOSpRGuwL45ptvlunTp5vEaN++fc3KX+1z0qRJsmrVKtNX3bp1Zd26ddKmTRvzNR1Hjx49pHLlyrJnzx6TYNXVwFp0dbGuSA5XdHVty5YtzcpaLZoo1v4bNmwoxYoVM6uXdbXs2rVrzedNmjSRL7/80qzAjbXUrl3btHv++eeL9l+4cOGwTal3vXr1ZO/evebzZs2amWS3rn4uWbKkWQm8efNmMze1yC8BfNddd5mVxFqyr9COdR4chwACCCCAAAIIIOANARLA3ogDo0AAAQQQQAABBAIjYCWhm32yVupn3wJCj33kkUfkueeey7HlwqlTp8wWELr6V4uudtXk79ixY7MS0qF+MzMzzdYIocRupOSoJpinTZtmDvvDH/4gf/nLX85ZGavbUTz66KMyfPhwU0+3ldCXuMVSNJGt2zZo0SS5bjcRqcyYMUNuuukm8/EDDzwgI0aMiFhX56kro/W/SGXChAkyYMAA8/Hzzz9vjCkIIIAAAggggAAC/hcgAez/GDIDBBBAAAEEEEDAUwJWErrZB2ylfvYEcF4rdvWFabrqN1Q0ofnmm2+G9dH9fG+77Tbz2TPPPCOPP/54jnrr1683K3q16MraWbNm5ems/Wr/ycnJcuDAAbNCONqycOFC6dSpkzls0KBBWVtBhGtHk9GaeNayadMmadCgQbTd5aivK5d1tbMWTXzrvskUBBBAAAEEEEAAAf8LkAD2fwyZAQIIIIAAAggg4CkBKwnd7AO2Uj97Avi9996TG2+8MeycT548abY/0D+16NYHurdtuPL9999n7f0b7sVnuqpWX8KmRZOjv/nNb/J01m0lQltf6AvrdE/gaMv48eNN4leLvsxOk7yRyquvvpq1vcbkyZOzktnR9hmqv337drN1hhZNBEfaNznW9jkOAQQQQAABBBBAwB0BEsDuuNMrAggggAACCCAQWAErCd3sk7dSP3sCWFfXVqxYMaKf7vOrL0UrUaKE/PTTTzm2ich+0C+//JK1V69uHTF//vwcbV555ZVmC4mkpCR59913I+7FGzro66+/lj/96U/mr2PGjJG777476hj/9a9/NYlfLbqlxNChQyO2ofv76l7EugWFJr11iwpNZMe6Elhf/BZ6gZ3uLbxly5aox88BCCCAAAIIIIAAAt4TIAHsvZgwIgQQQAABBBBAwNcCVhK6BUkAnz59WgoVKhTRSF/Upqt7q1evLrt3787TUpO7Wtq1ayeLFy/OUVf3y/33v/8dUyz+/Oc/y2OPPRb1sboVxRNPPGGOs5JE1rp6TPaiyXHdP1hXIHfp0sW8KM5K0VXTRYsWNVX1xXpqSEEAAQQQQAABBBDwvwAJYP/HkBkggAACCCCAAAKeEoh3AlhXvOZVQgngmjVrio4lr5JXArhIkSKiL5aLpTz55JPy1FNPRX1oNCuAQ43PmzfPbBWxYsWKsP21atVKRo4cme8WFqwAjjpcHIAAAggggAACCPhCgASwL8LEIBFAAAEEEEAAAf8IBCUBXLZsWcnIyJAyZcrI4cOHHQmAvrDud7/7nekrvz2Acw9It8ZYtmyZfPHFF6J7EK9Zs8ZsD6FFk9kffvihdOzYMeI82APYkRDTCQIIIIAAAggg4LgACWDHyekQAQQQQAABBBAItkBQEsCNGjWSjRs3mmDt3btXqlatGvfAffrpp1lJWn0ZnL5YLtai21/oi+xmzJhhmrjssstkw4YNEZvTF93py9+09O3bV6ZMmRJr1xyHAAIIIIAAAggg4CEBEsAeCgZDQQABBBBAAAEEgiCgiUfdfkHL7bffLpMmTcpzWlYSxtlfAufUFhD33XefvPbaa2bsr7zyiujf411+/PHHrBfctWnTRpYuXVqgLnVfX01ca7tadCWzrmgOVyZMmCADBgwwH+mWEqGX0RVoAByMAAIIIIAAAggg4LoACWDXQ8AAEEAAAQQQQACBYAkcOnRIypcvbybVu3fvrBWokWbp1QTwqlWr5MorrzTDrlKliqxbt04uvPDCuAerTp06smPHDilRooQcOXJEChcuXKA+r7jiClm7dq1pQxPBkeaQlpaWteJYX4inL8ajIIAAAggggAACCPhfgASw/2PIDBBAAAEEEEAAAc8J6CpTTV5qMlP3lg29bC3cQL2aANax6lYI06ZNM8Nu2rSpSWbXrl07orduozBz5kx54YUXYo7JvffeK6NHjzbH6z6+msANV3RVcuXKleXGG2+UokWLhq2jewLr6ukzZ85ItWrVZM+ePRHH1bhxY7NFRKlSpURfCKf7BlMQQAABBBBAAAEE/C9AAtj/MWQGCCCAAAIIIICA5wR05e+sWbPMuH77299Kr169zNYDoURwixYtpFy5cuZzLyeAf/rpJ7MSVhOxWjQpqglX3Z4hJSVFTp8+LQcPHjSJU92/V+eiSe9vv/025phk3wd4xIgRZh/fcOWOO+4w22skJydL586dTYJak7y6YljHtGjRIpk3b57oNhBaNKmcnp4eti1N+FaqVMnM55ZbbpGpU6fGPH4ORAABBBBAAAEEEPCWAAlgb8WD0SCAAAIIIIAAAoEQWL9+vXmh2PHjx8POR5OTujLV6wlgHd+xY8dk8ODBJtma3/7DWl8TxrqFQqxFV+vWqlXLrNZt0qRJ1vYNudvT/Xp13978iiatn3zySRk2bFjEquPHjxd96ZyWjz76SLp06ZJfs3yOAAIIIIAAAggg4BMBEsA+CRTDRAABBBBAAAEE/Cawbds2efHFF82LzPTFcJoMDiVQ/ZQADrlv3rxZJk6caJK7O3fuNC9U060XKlSoIPXq1ZPU1FTp2rWr6Ormgpbnn39eHnvsMdOM7j2s2zPkLr/++qvolhNquXz5ctm6davZ4/fUqVNSunRpueSSS0ySfeDAgeb/8yq6olnbuPjii007hQoVKugUOB4BBBBAAAEEEEDAIwIkgD0SCIaBAAIIIIAAAggggEBIQJPLNWvWlMzMTBkyZIhJpMerfPPNN9KwYUPTfF7bRMSrf9pFAAEEEEAAAQQQiK8ACeD4+tI6AggggAACCCCAAAIxCTz99NPy1FNPScmSJWXHjh1SsWLFmNrJ76D+/fvL5MmTzbYTuvo30gvl8muHzxFAAAEEEEAAAQS8KUAC2JtxYVQIIIAAAggggAACCS6gq391a4l9+/bFbRXwd999J/Xr1zfbRkyZMkX69u2b4OpMHwEEEEAAAQQQCJ4ACeDgxZQZIYAAAggggAACCAREYOrUqdKvXz8pXry4aLK2SpUqts6sT58+8o9//KPAL66zdVA0hgACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCJAA9k4sGAkCCCCAAAIIIIAAAggggAACCCCAAAIIIGCrAAlgWzlpDAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ8I4ACWDvxIKRIIAAAggggAACCCCAAAIIIIAAAggggAACtgqQALaVk8YQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHvCPw/EmaV0kxh1YkAAAAASUVORK5CYII=\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'microstrain')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=np.loadtxt('./steel_700Hz.lvm',delimiter='\\t')\n",
    "t=data[:,0]\n",
    "y=data[:,1]\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(t,y,'.-')\n",
    "plt.xlabel('time (s)')\n",
    "plt.ylabel('microstrain')"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the graph above, I zoomed into the region around t=34s. The first natural frequency has the largest amplitude, so you can count the cycles and divide by the time, \n",
    "\n",
    "$f_1 = \\frac{\\#~cycles}{\\Delta t}$\n",
    "\n",
    "\n",
    "![image-2.png](attachment:image-2.png)\n",
    "\n",
    "I used the cursor to find peaks at t = 33.99 s, 34.04 s, and 34.10 s. This is two cycles over the course of $\\Delta t = 34.1 - 33.99~s.$\n",
    "\n",
    "The first natural frequency here is $f_1 = \\frac{2}{34.1-33.9}=18.2~Hz.$ This is only 3 Hz off from our Euler-Lagrange dynamic beam theory. \n",
    "\n",
    "# Part 2 - Using FFT to find natural frequencies\n",
    "\n",
    "We have already loaded the data as variables, `t` and `y`. Now, we are going to transform the time-axis to a _frequency_ axis and the y-axis will be _amplitude_. If the FFT shows a spike, we know that there is signal in the experiment that is oscillating at that frequency. The first thing to do is remove the __systematic error__ from the strain gage results. We do this by subtracting the average strain measurement from `y`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=y-np.mean(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the average is not 0, then our FFT will have a large spike at $f=0~Hz,$ but it might make our other signals harder to see. Now, we can use our FFT to transform the data, as such"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    " def FFT(i1, i2, t=t, y=y):  \n",
    "    '''use the NumPy fft to transform a data set from time-signal -> freq-amplitude\n",
    "    arguments:\n",
    "    ----------\n",
    "    i1: first index in the window\n",
    "    i2: last index in the window\n",
    "    t: time values, default is t\n",
    "    y: signal values, default is y\n",
    "    output:\n",
    "    -------\n",
    "    f: frequency (x-axis in FFT)\n",
    "    Y: amplitude (y-axis in FFT)\n",
    "    '''\n",
    "    ts=t[i1:i2];ys=y[i1:i2]                                                                                        \n",
    "    Y=2/len(ts)*np.fft.fft(ys)                                                                                     \n",
    "    f= np.linspace(0,len(ts)/(max(ts)-min(ts)),len(Y))                                                             \n",
    "    return f,Y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the data again, but don't include the time in the x-values, i.e.\n",
    "\n",
    "```python\n",
    "plt.figure()\n",
    "plt.plot(y)\n",
    "```\n",
    "\n",
    "The result, is that `y` is plotted vs the index of the values. For this example, I am choosing a _window_ from i=54300-54500. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "i1=54300\n",
    "i2=54500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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kFTP7tWdoZUrV5YcOXKE9ObBO3GvdABcqlQpWbdunTOfIkWKyMaNG0Oam1txzOuoWLFizk5Z9UjIWLx4seMZSkgd3+cEHwGhAXCvXr3k3nvvdV5SpkwZWbVqles0g89ofuqpp+T8+fNRx3QkJADWnce6Tj0GQx/Gpw+l07nptaM/DAh1aAivx3RoUK27qHW3twb2eiyK7lzW0DuhQ993zZo1zo5nfV/tq+5Yz507t+i1pYG4F4fuSp8/f77zsD/d9a1/N9u2bRvvVPVYGb12da16hrW+pnjx4s7xJVfyPG4vejEnBBBAAAEEEEi4AAFwwu14JQIIIIAAAggksQABcMKANRgaMGCAc0yBnmUb29DjEHTXbZ06dWL9/s6dO50AzXTUqFHDOZIhISP4eIn77rvPOdLhSg0NHjVU1hBch4aXK1eudIJBr4yYAbCG4XretR49oWPDhg2ioXVcQ4+L0OMsNKzVoev7+OOPExQAT5o0Sd58803nPWIbehzF888/Ly+88IJcd9118RJqCK27rrWfM2bMiFpPbC/ScFl3grdu3do4yNTjP/r27RvV29jeV0NRtevQoYNoMB5zxDwSRq8Xk6FH0eh53Tpef/116dmzZ6wvC64LHAOzd+9eee6550R3up89ezba62L7fP3aF1984RxBEriOY36Y9l93pmuAfO2115osgRoEEEAAAQQQ8JEAAbCPms1SEUAAAQQQiDQBAuDQO7Zr1y6pW7eubNmyxejFzzzzjLz33nuXhW5XMwDWIPHcuXPOfHVXrQZjV2roUQqNGzeOersmTZqIhpxeGjEDYA359HgJPWtZh4atAwcOjHPKGrI2bdrU+b6GnRoYP/HEEyEFwGfOnJEHH3zQ+KFzuuN02rRpzkPz4ho///yzszs1lHH//ffL559/Hm+4rDvbNejU+4Pp0PnGFmpf7QBY+6rXo+4gj23EDID1hwB6nMfChQuNlqoPTdQHB4bysEyjN6YIAQQQQAABBCJagAA4otvH5BFAAAEEELBbgAA4tP7qbl/d2fv7779HvVB3BmqoVqBAATl16pQsWbJEfvjhB9HzbAOjc+fOTggcPPTX0nVXb2Dor54Hhv7afrp06aLVV6hQQb7++uvQJvxfte521V2ROjRQ1BBbz/S9EiM4SNX307VroOalEVsArGHl7bff7kwza9assnv3bkmePHms077nnnvk+++/d76nQbEGxqEEwLoLVX9ooMcRBIbuylan0qVLO0c16OdrsLh+/fqoGv3e0qVL4wxrgwNgfQ89d1mvT12P9lev1+XLlzuBfPD1qLtj9azluMaQIUOinYusx1PoXDX8zpgxo2iYffDgQWeuGvDq//ZCAKwhvc5J/35qQKt/rlSpkvN3SY/c0B98rF69OmrZekRElSpVnKMzAiNbtmzOD0l0V7sedaF/L7/77jvnn4GhAXPweddeutaZCwIIIIAAAgiER4AAODzufCoCCCCAAAIIGAgQABsgBZVo0Dt27Nior7Rr1845BiLmWbcazGlgtn379qja6dOnOyFgXCMpzwBu3ry5E8wGRosWLZzdnXE91C0UlZIlS0YLLXVHpYabXhqxBcA6P909q73SoYFe8E7mwPz/+usv57gIDXE1INbzdfVc2FAC4ODzg/V9H374YefhcxkyZIjGpLtTNZjV+sBOVT22oU+fPrFy6tz1mnzllVdEexxXqK8/bGjVqlVUAK3Xmu5iDjzULuab6/nVGkjr0DBUf/AQ13vrbuFZs2bJzJkzpX///pfN82ruAA58uAbnGti7HbGi50BruBsYXbt2lTfeeOOyv8+6e/6ll15yHkwYGCNGjJDHH3/cS5c5c0EAAQQQQACBMAoQAIcRn49GAAEEEEAAgfgFCIDNrxDdOai7HAOjWbNmTqga14Ohtm7d6uzu1Idm6dCgdO3atXF+YFIGwBMnTrxsV67uBNbzYHWXpO4uTpMmjTnGf5W6E1RfpyGgDn3Q2LZt20J+n6R+QVwBsO7m1bBVh+7yDQ4DA3PSgF+P8dARfLyFaQCsu0s1aA0Eug899JDo2brxje7duztn7+rQHy7o7tXYQvVAKG1yJu3ff//tXL+Bo0t057auLebQna758uVzvqyBt557HN8xFG69u9oBsO6e14cc6lnK8Q09XkOPcwiMHj16OA8HjG/oER6jR492SvSHArrTOK5d424ufB8BBBBAAAEE7BIgALarn6wGAQQQQAABqwRiBsCmi4svzIwZ+Ji+p+6GPHr0qGm5UxccmgYeABXSG4RQ3L59e+fBXzr0TF0NeHWnZHxDH/alD7AKjMWLFzu/kh7bSMoAWD9Pd/3qEQOxDX1wm4aUeiSC/kq8Hk2RJ08eVx3dDXvbbbdF1dWuXdvZDeq1EVcAvH//fufhbvowtZQpUzrHZMQMWjU0DRwb8L///c9x1GEaAAfX6Xvr2c/p06ePl0iPa1BXPVpBhx4foseIJHbo2b9qoSN//vyxnmOt16heAzo0TFWjxIyrHQDruc4dO3Z0nbKGvxoC69DjW3755RfnAYbxDbXQvgTO0/bicSeuC6cAAQQQQAABBJJEgAA4SVh5UwQQQAABBBC4EgIEwOaKt956q7MTU4ce7xB8pEJc76K7JzVgvHDhglMS3y7DpA6Adbfuk08+afxgLz1LVus1MIxrh6met6o/DAgMPYYgrpDZXPrKV8YVAOsn6a7eH3/80fnQmOGhHpNQokQJ53u6C1b7r+G/DpMAWHf96uv0rFkdbmfvBq/8qaeekg8//ND50pV6sF5wYK/Xm84r5jEUuktdd64Hhu4INvlhQFxdu5oBsAa4Gpq7HUGi69a+BHZlv//++1G7vN2uPj0mRB98qCOuXdRu78H3EUAAAQQQQMA+AQJg+3rKihBAAAEEELBGIGYArL/WbPJ0e31Akh4rENuIGfjE9kCz2F6nuyKDH9Bkgny1dgBr8KcBcGAMGzbMCQBNhu6q1QeO6ahXr17UrsOYr03qADjweQsWLJC33nrLmUcgmI5vHaVKlXLOU40tBFy0aJHz4LHAMDneQGtNf/CwY8cOyZUrlwlzvDXxBcC6q7dly5bO68uXLy/Lli2Leq/nn38+6tzXmGGfSQCsRxHog9MCY+rUqVK/fn2j9QTv1r0SO3H1Q3Wnc4oUKaI+X4+nKFSoULT56A8KNEDVf+rQc5J1LsGhsNEC/iu6mgGw7mIPnOkc3xw18NdQPTA2b94sBQsWNFqWnhHcs2fPWK8XozegCAEEEEAAAQSsFCAAtrKtLAoBBBBAAAE7BDgD2KyPMUOshQsXRv2avNs7tG3bVj799FOnTB9KFfxguODXXq0AOPCZBw4cEH0w3fz582X58uXOuakaEMY2MmfOLCtWrJCcOXNG+/a6detEA+LAMN0B7KUAWM/R1R986MPedOhRAIULF3YsNPRXJx2rVq2SMmXKRK3VJAAeM2aM8/C1wNAzY92ODQnUaljcsGHDqNfqPIPD25h90h7qGcY6Tz3n99ixY87504FdrrH1denSpc75zzGHPtxs5MiR0b6sa9fdrzVr1pSKFSvG+VC4mO91NQNgPZd7woQJbn8lpV+/fqIP19OhpqdPn3Y9/iHwpsOHD3d2xuvQ60YfsMdAAAEEEEAAAQQIgLkGEEAAAQQQQMCzAgTAZq0ZP3683H333VHFGrDpGaom45VXXnF23OrImDFj1HEAMV97tQPgmJ+v585qiDhlyhRnx2fguItAXbVq1ZywOHjs3r07WqBpegawHhPRtWvXy/gOHz4czedq7ADWSTz99NMyZMgQZz46r/79+ztB4l133eV8TXfB6nEXwcMkANb31Pe+EkODaA3iYw69FvV86nnz5oX8MRrO6nnPMYeGx7Vq1ZI1a9bE+p56DIaGwBr464PRYptX4IVXMwA23YHepUsXeeedd0L2ivmC1KlTRz3kMdFvxhsggAACCCCAQEQLEABHdPuYPAIIIIAAAnYLEACb9ferr76S1q1bRxXrWarBR0LE9y59+vRxzv7VkTx58qgHSMV8TbgD4OD56K//65xjhmQxdz7rzsk0adJE7TLNly+f83C8hA791Xr9FfvAuFoBsO6a1TOPdeiuzl27dsk999wTdc6zOuhxEMHDJAAO7n1CTQKv04fHxdyBrbuVNcA9dOjQZW+v4aSe75sqVapoZzjrmb6BMWfOHGdHb2zj1KlT0rdvXycY10A4rqH9f+mll6R79+6xnhV9NQNg0wdBxrbDOaH9iW+HdULfk9chgAACCCCAQOQJEABHXs+YMQIIIIAAAr4RIAA2a7U+8E13OwaGhpwadpoM/VVz/ZVzHV7eARzbWnRH5ddffx31LQ35evfuHa1Ud8cGzl3VEFt38eo6EzLCFQDrXPVhb/rQNx1ffPGF6NEd586dc0J7/TV/PYc3eJgEwIMGDYoKjtUmMQ9T0x2+wT900OBRd+Hqrm0d+v76Qwo9ckLDbH3IWcyhrwl+oF98AXDgtRry63EUM2bMED0/Wo8KiS30fOCBB2T06NGXfaYXA+DOnTvLBx984MxVdzPfdtttCblcndds27Ytwa/lhQgggAACCCBgjwABsD29ZCUIIIAAAghYJ0AAbNZSDd+Cd0rqw88qV65s9OJ27drJJ5984tR66Qxgk8nrQ/nKli0bVdqiRQvRh6YFj6eeeko+/PDDqC/p0Ql6FmtCRjgDYN3lq0cD6EiXLp2cOHHC+d9NmzaN9YGHJgGwBsm6K1WHBq+6qzZlypQJobnsNUuWLIl2Deo5023atIn3vY8cOSI33nhjVI1JABzzDQ8ePOg8QFB3xes/g4f+oOTOO++M9rWYf3dMd8zq2cSBcPv111+PevBazPno38vA8RemO4DffPNN0ffUwTm+V+Ry5E0QQAABBBDwvQABsO8vAQAQQAABBBDwrgABsFlv9Dzc4N2X+iCoDh06GL24fPnyzgPUdNSrV++y0CzwJl46AiIwJz0K4vrrr49aZ926dZ0HxwWPyZMnOyFpYJg+iCs2vHAGwPv375fs2bNf9iC877//Ptr5z4F5mwTAGmAGP2RNzxHWHdNXYgQfL1GoUCHZtGmT69vGDPQTEgAHf4gGvvpDgYsXLzpfvvfee2Xs2LHR5qHXvv4dCAx9MJ0eT+E2cuXKJfrQPB1XOgD+9ttv5b777nPeW//eaTCux2UwEEAAAQQQQACBhAoQACdUjtchgAACCCCAQJILEACbE2s4qEcB6NCHg+mD4dyGPrhLdxheuHDBKX311VdFdx/GNrwYAOvZr8HHOWho9s0330SbvoZ/hQsXFn0YmY5kyZKJBo16pEKoI5wBsM5Vg2wNtANDj1HQ8F+PCYg5TAJg7fsNN9wQtZtYjwJ5+eWXQ2WJtT5453VsfYntRcG7nPX7iQ2AA38XdNe3jtgelqfHpRQoUCBqOibHp+zbt0+yZcsW9ZorHQBr2J81a9ao9x8zZozcf//9V6QvvAkCCCCAAAII+FOAANiffWfVCCCAAAIIRIQAAbB5m3TH74gRI5wX6K/xa5DldnZozIeALV26NNqO0OBP92IA/NNPP0njxo2jpqnnGeuaYg494kKPugiMkiVLyrJly0I+7iDcAbCuV9cYGLq7VUP72IZJAKyv02MJ9CgIHfrDAD0zNnhXtfkVGL2yY8eOMmzYMOeLeuyC7saNb5w/f16KFCkS7SF9VyIA1gfAvf32285H6w8C9MF0wUPPUU6bNq2cPXvW+bIeHfHggw/GO9f+/ftHC8qvdACsH64Pz5s/f74zjzJlysjKlSud3cAMBBBAAAEEEEAgIQIEwAlR4zUIIIAAAgggcFUECIDNmWP++rw+FE6PB4grNPrtt9+kVKlS8vfffzsfov97zZo1cX5gUgbAGhZqgK3BrOn4559/pGrVqk4wFhgLFy6UKlWqXPYWeq6rBsVTpkyJ+p6ezaqhZCi/Wh/uANjURutMA2ANRIsVKxb14DR9UNvnn38eUtioR3GkSpUq2vR0N3EgrNZzffW4BG/XEZEAACAASURBVA1a4xr6AL++fftG+3ZsAbDuvtX3i23Xc2zvrX3X4FxHgwYNol0DgXp9WJ3+QEBH7dq1ZdasWXHOU9eh16nuPg+MpAiA9Vpt1KhR1Gf06NFDevXqZXwJ6DWv4bapk/EbU4gAAggggAACESlAAByRbWPSCCCAAAII+EOAADi0PuuviQefcaoh4HvvvXfZTlcN/XRXpu72DAw9O1fP0I1rJGUArMdX6FEGGnjpg8L0qIP4givd3aw7egM7JHXO+tA7DYDjCrz/+usvKVeunOzcuTNqiTly5JDXXnvN2QWbPHnyONeuYZqGgi+88ILoObmBsWPHDtGzYBM7Hn30USd01VGwYEHZvHlzYt/SOADWDwreJat/btKkiQwdOlTUJ66hAejEiRNl8ODB8vzzz192RIEG87fffnvUy1u2bOnsNI4ZFGuQr8eOaPirD6ILnNerL4wtANZ7gobFzzzzjLNTV6+duIY+/E+PoggM/fOTTz55Wbn+HXnuueeivj5gwICoB+4FF69bt070Byvad73OAg+MS4oAWD9Xj87Q84ADo23btqLBeubMmeNcsx7rog9C/OCDD0StNNxmIIAAAggggAACBMBcAwgggAACCCDgWQEC4NBac+jQISfkDDycSl+tIZ4GSfnz55fTp0/LkiVLnPOBNXgLjM6dOztBcXwjqQPgwPnFOgfdKaoPJ9O16Fmoek6t7jLdtWuXLF682Al+g4NC3RGqXytatGi8a9CQWc9HDjz0LlCcPn160R3BpUuXFj1XV/+sVuqpYawGkfra4JElSxbZuHGjZMqUKbQmxVId7gBYzwLW0D14h7QG4nfccYcTrGsPUqRIIUePHnUCdN0prjtmA8cmxHVGrb5+9uzZUSvWa1F/SKFn7uruVLUdN26c7N6926nRIFgD+cCIKwDWHxLo0GtSj0fQkDNv3rzOdaJz2r59u7Prd8OGDVHvpcc/6Lz1eJSY48SJE87xEMHXoO4k1x+SaH/1OtDrS99Trzv9QYleH/oDBx1JFQDr7nw9CkJ39weGHs+hD2vUvx8aBKuB9kV/mKN1GrwH/m7o33UC4ET/9eQNEEAAAQQQsEKAANiKNrIIBBBAAAEE7BQgAA69rxqSakAVeOiZ2zt06tTJ2S3odr5oUgbAGgjqrt6EDN0xqw9+0yMsTIYGd3o0wfDhw51QOdSROnVqefrpp51dqOnSpQv15bHWhzsA1knpGbzPPvuss/M31KG7VHWHb8yhgWqlSpWiAt743ld3YY8aNcrZBRwYbgGw6Tz1+poxY0a8O5r1s/S4CL0+4hu6q3natGnOTuB58+Y5pUkVAOt7nzx5Uh5++GEnKA91LF++PNou7FBfTz0CCCCAAAII2CNAAGxPL1kJAggggAAC1gkQACespRpi6YOvhgwZ4uxejG2ULVvW+bV73U1oMpIyANZdmxrQTZgwQebOnWsUBuv8NTht3759gs451R29gwYNksmTJ7seuaChb/ny5aVVq1bObmrdIXwlhxcC4MB6dHe0njWrR4IE7xKPuV7dzatn6uoxDNWrV4+TQ48k0MBcjyUI3rUdeEG+fPlEz7fVAFhH8HUWWwC8d+9e52iDH3/80dnJHdiFHNsE9KF2erb0iy++aPRgO30/PTIi5g5xfW/tuR6pojZ6PInuGL8aAXBgXTNnznQecLhgwQLRHdtxDf2BSMOGDUXPctbd0QwEEEAAAQQQQMD5/7EuBQ6vwgMBBBBAAAEEEEDAKgENipYuXeoEnAcPHnR+/V1/nV9/rT9nzpyeXauG1ps2bRJ9UN3hw4fl1KlTToCnIVzu3Lmd3b5X4uiFAICGwfrr8/q5+n96PEHGjBmdh41poKYPSYvvjGDPQiZiYmq+aNEi5zgRPT9Z/5NB/fXMYz1qI9TrR401MN2zZ48zq2zZsjnHLmiQn9ChO7j1XF49/kAfDqc/+NDrRI9G0Ae1ad+SJUsW8tvr0R56fIL+ndE161r14XD6g4BwDz17WY+e0N3V2hfdMa3Xap48eZz1qisDAQQQQAABBBCIKUAAzDWBAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljWRYCCCCAAAIIIIAAAggggAACCCCAAAIIIEAAzDWAAAIIIIAAAggggAACCCCAAAIIIIAAAghYKkAAbGljbV/Wn3/+KZMnT3aWmSdPHkmTJo3tS2Z9CCCAAAIIIIAAAggggAACCCDgY4GTJ0/K9u3bHYEmTZrILbfc4mMNlh6KAAFwKFrUekZgxIgR0qFDB8/Mh4kggAACCCCAAAIIIIAAAggggAACV0vgo48+kvbt21+tj+NzIlyAADjCG+jX6RMA+7XzrBsBBBBAAAEEEEAAAQQQQAABBAiAuQZCESAADkWLWs8IzJw5U+rWrevMR296xYsX98zcmAgCCCCAAAIIIIAAAggggAACCCBwpQU2bNgQ9dvQM2bMkDp16lzpj+D9LBUgALa0sbYva8mSJVK5cmVnmYsXL5ZKlSrZvmTWhwACCCCAAAIIIIAAAggggAACPhYgC/Fx8xO5dALgRALy8vAIcNMLjzufigACCCCAAAIIIIAAAggggAAC4REgCwmPuw2fSgBsQxd9uAZuej5sOktGAAEEEEAAAQQQQAABBBBAwMcCZCE+bn4il04AnEhAXh4eAW564XHnUxFAAAEEEEAAAQQQQAABBBBAIDwCZCHhcbfhUwmAbeiiD9fATc+HTWfJCCCAAAIIIIAAAggggAACCPhYgCzEx81P5NIJgBMJyMvDI8BNLzzufCoCCCCAAAIIIIAAAggggAACCIRHgCwkPO42fCoBsA1d9OEauOn5sOksGQEEEEAAAQQQQAABBBBAAAEfC5CF+Lj5iVw6AXAiAXl5eAS46YXHnU9FAAEEEEAAAQQQQAABBBBAAIHwCJCFhMfdhk8lALahiz5cAzc9HzadJSOAAAIIIIAAAggggAACCCDgYwGyEB83P5FLJwBOJCAvD48AN73wuPOpCCCAAAIIIIAAAggggAACCCAQHgGykPC42/CpBMA2dNGHa+Cm58Oms2QEEEAAAQQQQAABBBBAAAEEfCxAFuLj5idy6QTAiQTk5eER4KYXHnc+FQEEEEAAAQQQQAABBBBAAAEEwiNAFhIedxs+lQDYhi76cA3c9HzYdJaMAAIIIIAAAggggAACCCCAgI8FyEJ83PxELp0AOJGAvDw8Atz0wuPOpyKAAAIIIIAAAggggAACCCCAQHgEyELC427DpxIA29BFH66Bm54Pm86SEUAAAQQQQAABBBBAAAEEEPCxAFmIj5ufyKUTACcSkJeHR4CbXnjc+VQEEEAAAQQQQAABBBBAAAEEEAiPAFlIeNxt+FQCYBu66MM1cNPzYdNZMgIIIIAAAggggAACCCCAAAI+FiAL8XHzE7l0AuBEAvLy8Ahw0wuPO5+KAAIIIIAAAggggAACCCCAAALhESALCY+7DZ9KAGxDF324Bm56Pmw6S0YAAQQQQAABBBBAAAEEEEDAxwJkIT5ufiKXTgCcSEBeHh4BbnrhcedTEUAAAQQQQAABBBBAAAEEEEAgPAJkIeFxt+FTCYBt6KIP18BNz4dNZ8kIIIAAAggggAACCCCAAAII+FiALMTHzU/k0gmAEwnIy8MjwE0vPO58KgIIIIAAAggggAACCCCAAAIIhEeALCQ87jZ8KgGwDV304Rq46fmw6SwZAQQQQAABBBBAAAEEEEAAAR8LkIX4uPmJXDoBcCIBeXl4BLjphcedT0UAAQQQQAABBBBAAAEEEEAAgfAIkIWEx92GTyUAtqGLPlwDNz0fNp0lI4AAAggggAACCCCAAAIIIOBjAbIQHzc/kUsnAE4kIC8PjwA3vfC486kIIIAAAggggAACCCCAAAIIIBAeAbKQ8Ljb8KkEwDZ00Ydr4Kbnw6azZAQQQAABBBBAAAEEEEAAAQR8LEAW4uPmJ3LpBMCJBOTl4RHgphcedz4VAQQQQAABBBBAAAEEEEAAAQTCI0AWEh53Gz6VANiGLvpwDdz0fNh0lowAAggggAACCCCAAAIIIICAjwXIQnzc/EQunQA4kYC8PDwC3PTC486nIoAAAggggAACCCCAAAIIIIBAeATIQsLjbsOnEgDb0EUfrsEvN71Lly7J3F8PyqjFO+XoqbOSKkUyaVU+hzQpkU2SJ7vWh51nyQgggAACCCCAAAIIIIAAAgjELqD/Db1w2yH5dOEO+evkWUmVPJm0LJdd7ip9q6Sw4L+h/ZKFcH1feQEC4CtvyjteBQE/3PT0X1wvf79Bxq7cfZlo1XyZ5LM2txMCX4VrjY9AAAEEEEAAAQQQQAABBBCIDIE3J/0iny7acdlky+a8QUY/XkFSJk8WGQuJY5Z+yEIiukEenjwBsIebw9TiFvDDTW/sil3y0vcb4kToWDOvdG1QiMsEAQQQQAABBBBAAAEEEEAAAd8LTFr3pzw9Zk2cDo9WziU9mxWNaCc/ZCER3SAPT54A2MPNYWr+DoDvH7FElm4/HCfCLRlSyaKXa8s111zDpYIAAggggAACCCCAAAIIIICArwUe+2yFzN58IE6DjKlTyOoedeXaayP3v6EJgH19iSdq8QTAieLjxeESsP2md/HiJcnT7SdX3lkv1JC8mdO61lGAAAIIIIAAAggggAACCCCAgM0CuV7+0XV5kzpVleLZM7jWebXA9izEq+42zIsA2IYu+nANtt/0zp6/KAV6THHt7Eety0r9olld6yhAAAEEEEAAAQQQQAABBBBAwGYBkwC4f4vict/tOSKWwfYsJGIbEwETJwCOgCYxxcsFbL/p/XP+ghTsMdW19cMeLCMNi2dzraMAAQQQQAABBBBAAAEEEEAAAVsFTH+L9u17Ssi95W6LWAbbs5CIbUwETJwAOAKaxBT9FwCfOXdBCr3qHgAPbVVGGpcgAObvCAIIIIAAAggggAACCCCAgH8FTH+L9p2WJaVF2ewRC0UAHLGtC/vECYDD3gImkBAB2296p86elyKvTXOl+eCB0tKs5C2udRQggAACCCCAAAIIIIAAAgggYKuA6X9DD7qvpDQvTQBs63XAuuIWIADm6ohIAdsD4BNnzknxntNde/P+/aXkzlK3utZRgAACCCCAAAIIIIAAAggggICtAsfPnJMSPvhvaNuzEFuvTy+siwDYC11gDiEL2H7TO3b6nJR8wz0AfvfeknJ3mcj96WXIjecFCCCAAAIIIIAAAggggAACCMQQOHzyrJTpNcPVZfADpaVpBP8Wre1ZiGsDKUiwAAFwgul4YTgFbL/pHT11Vkq96f4vr4EtS8o9EXx+UTivIT4bAQQQQAABBBBAAAEEEEDADoEDx89I+b6zXBcT6c/RsT0LcW0gBQkWIABOMB0vDKeA7Tc9059eRvoTTMN5DfHZCCCAAAIIIIAAAggggAACdgj8efS0VH5rtutihj9URhoUi9wHqduehbg2kIIECxAAJ5iOF4ZTwPab3qG//5FyvWe6Er91d3G5v3wO1zoKEEAAAQQQQAABBBBAAAEEELBVYNdfp6T6gDmuy/uodVmpXzSra51XC2zPQrzqbsO8CIBt6KIP12D7Te/AiTNSvo/7r6/0bV5cWlUgAPbhXwGWjAACCCCAAAIIIIAAAggg8J/A9oN/S+135rl6jHy4nNQpcrNrnVcLbM9CvOpuw7wIgG3oog/XYPtNb//xM1LB4PyiXncVk9YVc/rwCmDJCCCAAAIIIIAAAggggAACCPwrsGX/Cak3aL4rx6ePlpPahQiAXaEosE6AANi6lvpjQbYHwHuPnZZK/dzPL3qjWVF5pHIufzSdVSKAAAIIIIAAAggggAACCCAQi8DGP49J4w8WutoQALsSUWCpAAGwhxu7Zs0aGT16tMycOVP27Nkjx48fl0yZMkm2bNmkYsWKUrNmTWnevLkkS5YszlXs3btXhg8fLpMmTZKdO3fKmTNnJGvWrFKtWjV57LHHpEaNGiEJTJgwQb788ktZsWKF7N+/X9KnTy958+Z15tGhQwfJkCFDSO+X0GLbA+A/jp6WKgYH2L/etIi0qZI7oYy8DgEEEEAAAQQQQAABBBBAAIGIF1i/56g0G7LIdR0cAeFKRIGlAgTAHmysBr2dO3eWzz//XC5duhTvDI8cOSIZM2aMtWb8+PFOyHv06NE43+Pxxx+XYcOGxRsi64tPnDghrVq1ksmTJ8f5XtmzZ5exY8dK5cqVk1zV9gB49+FTUu1t9wPsezQuLO2q5Ulybz4AAQQQQAABBBBAAAEEEEAAAa8KrPr9iLQYtth1eiNal5V6PATO1YkC+wQIgD3W08OHD0v9+vVl5cqVzsyyZMkiLVq0kDJlyji7bXXXre4Gnjt3rrMLV+tjC4B113CjRo3k3Llzzvs0btxYmjVrJmnSpJHVq1fLyJEjnR3FOjQEHjFiRJwS58+fd95rxowZTs3NN9/svKZIkSLO548ZM0YWLfr3J206l4ULF0rRokWTVNb2ANj0CabdGxWWx6sTACfpxcabI4AAAggggAACCCCAAAIIeFpg+Y7Dcu9HS1znOPyhstKgWFbXOq8W2J6FeNXdhnkRAHusiw0aNJBp06Y5s2rXrp0MGjRI0qZNG+ss9XiHzJkzS/LkyaN9X495KFiwoOzatcv5+uDBg6VTp07RarZs2eIc/7Bv3z7n69OnT5e6devG+jm6Q7hjx47O9zT0nT17thMCB48uXbrIO++843ypSpUqTgiclMP2m97OQyel5sC5roQvNywkT9TI61pHAQIIIIAAAggggAACCCCAAAK2CizedkhajVzmurxhD5aRhsWzudZ5tcD2LMSr7jbMiwDYQ1387LPPpE2bNs6MWrZsKd9++22CZjd06NCowLdp06YyceLEWN9n3Lhxzu5iHXqmsN5IYo4LFy6IHu0QCIpXrVrl7EaOra5cuXKydu1a51tTp051djIn1bD9prf94N9S+515rnwv1i8oT9XK51pHAQIIIIAAAggggAACCCCAAAK2CszbclAe+XS56/KGtiojjUsQALtCUWCdAAGwh1qqu2s3bdokKVKkkN9//9152FtCRvXq1WXBggXOS+fMmeM8LC62cfHiRecBbvpwOB07duyQXLlyRSvV3b533HGH8zXdMaxHT8Q1Ro0a5Zw5rOORRx4RDbSTatgeAG878LfUedc9AO5Sr4B0qp0/qZh5XwQQQAABBBBAAAEEEEAAAQQ8LzB783557LN/j9KMbwx+oLQ0LXmLW5lnv297FuJZeAsmRgDskSbqGbpVq1Z1ZtO8eXPR3bkJGfqwNj2HV8PddOnSiT4kLlmyZHG+1ZNPPinDhw93vv/hhx+K/jl4dO3aVQYMGOB8qX///qJ/jmvo+cRZs/57lo6eXax/Tqph+01v6/4TUnfQfFe+5+oUkM51CIBdoShAAAEEEEAAAQQQQAABBBCwVmDaxn3S4ctVrut7//5ScmepW13rvFpgexbiVXcb5kUA7JEu9u3bV7p37+7MZsiQIc6Zu6NHjxbdVbthwwY5duyY3HTTTVK2bFm599575YEHHog12F22bJlznIMO3Qk8b178u0g//fRTadu2rVOvn6nHRwSPhg0bOsc56NDdwLVq1YpXLEeOHLJ7926n5sCBA84ZxUkxbL/pbd53XBq89+8u7vjGM7XzyfP1CrqV8X0EEEAAAQQQQAABBBBAAAEErBX4acNe6fj1atf1DbqvpDQvnd21zqsFtmchXnW3YV4EwB7p4t133y3jx493ZvPDDz/I+++/7xzfENfQc3i17rbbbotW8sUXXzjHL+gwOYZBP6N27dpOvR71MHPmzGjvlydPHudoCB2xHRERc356TMT8+f/uXNVjKAK7mkNhju0s4piv11C8Q4cOzpcXL14slSpVCuUjPF/7y5/HpdEH7gHwkzXzyksNCnl+PUwQAQQQQAABBBBAAAEEEEAAgaQSmLD2D+n8zb/PJIpvvNOypLQoSwDs5sT37RMgAPZITzXAXLp0qTOb/Pnzy9atWyVlypTy8MMPOyFq8uTJZd26dTJy5Eg5fPiwU5cvXz5ZuXKlZMiQIWoVH3zwgXTu3Nn58wsvvCADBw6Md4Xr16+XkiVLOjW6u1jfL3jceOONzjESOvR4ibRp08b7fsFB9qRJk6RJkyYhC19zzTUhvcbGAPjnP45Jk8ELXR0er5Zbujcu4lpHAQIIIIAAAggggAACCCCAAAK2Cny/ao+88N061+UNuKeEtCwXfSOd64s8VMAOYA81I8KmQgDskYYVKlRIfv3116jZ6HEPs2bNigpnA9/Yt2+f1KlTRzZu3Oh86amnnnKOjAiM4KMk9EiJ3r17x7tCDZoLFCjg1Og/g+egX7vuuuvk3Llzzvf1nxpExzcefPBB5+gKHfpPPaoi1EEALLJhzzFpOsQ9AG5TJZe83rRoqMTUI4AAAggggAACCCCAAAIIIGCNwLcrdkvX79e7ruftFiXk3tsJgF2hKLBOgADYIy3V8FXD2MDQoxxat24d6+x0J3Dp0qXl0qVLkipVKuesXX3gm47gALhHjx7Sq1eveFfoxQCYIyBE1u0+KncOXeR6dbaumFN63VXMtY4CBBBAAAEEEEAAAQQQQAABBGwV+HrZ79J9/M+uy3vr7uJyf/kcrnVeLWAHsFc74/15EQB7pEd6/MLq1f8eWK5HOhw6dCje3baVK1eWQFA6ZcoUadCggfNaG46AMGmJ7Te9NbuOSPMPF7tSPFA+h/S7u7hrHQUIIIAAAggggAACCCCAAAII2CrwxZKd8tqEf39TOr7Rt3lxaVWBANjNie/bJ0AA7JGe6rEOeuSDjmrVqkU9SC2u6T399NNRRz8MHjxYOnXq5JTa8BA4k5bYHgCv+v2ItBjmHgC3LJtdBrT89wxnBgIIIIAAAggggAACCCCAAAJ+FPhk4Q7pNfkX16X3vquYPFQxp2udVwtsz0K86m7DvAiAPdJFDXCHDh3qzKZx48YyefLkeGemxzv06dPHqdF/duvWzfnfy5Ytk4oVKzr/u3r16jJv3rx43+fTTz+Vtm3bOjUdO3aMmkPgRQ0bNpSpU6c6f5w9e7bUqlUr3vfLkSOH7N6926nRoykyZ86cJMK23/RW7jws9wxf4mrXvPStMui+Uq51FCCAAAIIIIAAAggggAACCCBgq8BH836TflM2uy6v151FpXWlXK51Xi2wPQvxqrsN8yIA9kgXP/74Y2nfvr0zm6pVq8qCBQvinVlwYKwPgdOHwek4ceKEZMyYUS5evOicC3zkyBFJlixZnO/15JNPyvDhw53vf/jhh6J/Dh5du3aVAQMGOF/q37+/6J/jGvv375esWbM6386SJYvon5Nq2H7TW77jsNz7kXsA3LTkLTL4gdJJxcz7IoAAAggggAACCCCAAAIIIOB5gaFztsmAab+6zvONZkXlkcoEwK5QFFgnQADskZbu2bNHdPesPtgtffr0zhnAKVKkiHN2lSpVkqVLlzrfnzFjhugREoGhO38DAfLcuXOlRo0asb6PhsT58uWTHTt2ON/Xf+bKFf1GqLt+77jjDuf7NWvWlDlz5sQ5p1GjRsljjz3mfP/RRx8V/XNSDdsD4KXb/5L7R/zb3/hGw2JZZdhDZd3K+D4CCCCAAAIIIIAAAggggAAC1gq8P3OrDJq5xXV9rzctIm2q5Hat82qB7VmIV91tmBcBsIe6qMcraGCr4/PPP5eHH3441tmtXbtWSpf+d9en7vLVnbbXX399VK3u5A3sCG7atKlMnDgx1vcZN26ctGjRwvmeHhsReKhccPGFCxcke/bssm/fPufLq1atkjJlylz2flpXrlw50bnp0GMj6tevn2S6tt/0Fv92SFp9vMzVr26Rm+Xjh8u51lGAAAIIIIAAAggggAACCCCAgK0C707/VT6Yvc11ea82KSJtqxIAu0JRYJ0AAbCHWhocat50003OmbslSpSINkMNe3VH7saN/z7dsnv37tK7d+9oNWfOnJGCBQvKrl27nK8HHxERKNy6datzRnAg2I25izj4DYcNG+acD6yjaNGizrz0iIfg8eKLL8rAgQOdL1WpUkUWLlyYpLK2B8CLth2SB0e6B8C1CmaWUW3KJ6k1b44AAggggAACCCCAAAIIIICAlwX6T90sw+b+5jrFHo0LS7tqeVzrvFpgexbiVXcb5kUA7LEuvvzyy85ZuzpSpkwpjzzyiHMmcPLkyZ3dtSNHjpTDhw873y9btqwTtKZKleqyVcycOVMaNWok586dc77XpEkTadasmaRJk0ZWr17tvM+xY8ec7z3++OMyYsSIOCXOnz/vvJeGxDr0nF99TZEiRZy5jBkzJirwzZAhgyxatMgJipNy2H7TW7D1oLT+ZLkrYbX8meTLthVc6yhAAAEEEEAAAQQQQAABBBBAwFaBPj/+Ih8v+Pd4y/hGt0aFpH31vG5lnv2+7VmIZ+EtmBgBkclK5gAAIABJREFUsAebqLt6NQTWYxXiGnq8ggavN9xwQ5w148ePd87kPXr0aJw1GuTqDt/4HhSnL9aHy7Vq1UomT54c53vpURFjx46VypUrJ7mq7Te9eVsOyiOfugfAlfLcJGPaV0xybz4AAQQQQAABBBBAAAEEEEAAAa8KvDFpo4xatNN1ei83LCRP1CAAdoWiwDoBAmCPtnTdunXyySefOLtu//jjD2cnrx67oOGqng3csGFDo5nv3bvXCXgnTZokO3fuFD0eIlu2bM6u4rZt28b5gLi43nzChAnyxRdfyIoVK+TAgQPOGcR58+aVu+++Wzp06CC6A/hqDNsD4Dm/HpA2o1a4Ut6e6wb57omkD9xdJ0IBAggggAACCCCAAAIIIIAAAmESePWHn+XLpb+7fnrXBgWlY818rnVeLbA9C/Gquw3zIgC2oYs+XIPtN71Zm/ZL289Xuna2dI6MMr5jFdc6ChBAAAEEEEAAAQQQQAABBBCwVeCVcRtkzPJ/n4MU33ixfkF5qhYBsJsT37dPgADYvp76YkW2B8Azftkvj3/hHgAXvzWDTHq6qi96ziIRQAABBBBAAAEEEEAAAQQQiE3gxe/WyXer9rjiPF+3gDxzR37XOq8W2J6FeNXdhnkRANvQRR+uwfab3rSN+6TDl6tcO1soazqZ+mx11zoKEEAAAQQQQAABBBBAAAEEELBV4Lmxa2X8mj9cl/dsnfzybJ0CrnVeLbA9C/Gquw3zIgC2oYs+XIPtN72pP++VJ75a7drZ/FnSyozna7jWUYAAAggggAACCCCAAAIIIICArQJPj1kjk9b96bo83f2ru4AjddiehURqXyJh3gTAkdAl5niZgO03vZ827JWOX7sHwLkzpZE5XWpyhSCAAAIIIIAAAggggAACCCDgW4Env1olU37e57r+p2vnkxfqFXSt82qB7VmIV91tmBcBsA1d9OEabL/pTV7/p3Qavca1s7fdeL0s6FrbtY4CBBBAAAEEEEAAAQQQQAABBGwV0Gfo6LN03MZTtfLKi/ULuZV59vu2ZyGehbdgYgTAFjTRj0uw/aY3cd2f8swY9wA4W4ZUsuSVO/x4CbBmBBBAAAEEEEAAAQQQQAABBByBNqOWy5xfD7pqPFkzr7zUgADYFYoC6wQIgK1rqT8WZHsAPGHtH9L5m7WuzcyUNqWs7FHHtY4CBBBAAAEEEEAAAQQQQAABBGwVaP3JMlmw9ZDr8jrUyCOvNCzsWufVAtuzEK+62zAvAmAbuujDNdh+0xu/Zo88N3ada2dvSJ1C1rxWz7WOAgQQQAABBBBAAAEEEEAAAQRsFXhgxFJZsv0v1+W1r55HujUiAHaFosA6AQJg61rqjwXZHgB/v2qPvPCdewCcLmVy2fBGfX80nVUigAACCCCAAAIIIIAAAgggEItAy+GLZcXOI6427armlh5NirjWebXA9izEq+42zIsA2IYu+nANtt/0vlu5W17833rXzl6fIpls6tXAtY4CBBBAAAEEEEAAAQQQQAABBGwVaP7hIlmz66jr8h6rkltea0oA7ApFgXUCBMDWtdQfC7I9AP52xW7p+r17AJwi2TWytU8jfzSdVSKAAAIIIIAAAggggAACCCAQi0DTwQtlwx/HXG0erZxLejYr6lrn1QLbsxCvutswLwJgG7rowzXYftP7ZvkueXncBqPO7ujXSK655hqjWooQQAABBBBAAAEEEEAAAQQQsE2gwXvzZfO+E67LeqRSTnnjzmKudV4tsD0L8aq7DfMiALahiz5cg+03vdHLdkm38WYB8G99G0myawmAffjXgCUjgAACCCCAAAIIIIAAAgiISN1358nWA3+7WrSumFN63UUA7ApFgXUCBMDWtdQfC7I9AP5q6e/S44efjZq5uVcDSZUimVEtRQgggAACCCCAAAIIIIAAAgjYJlBr4FzZceik67IerJBD+jQv7lrn1QLbsxCvutswLwJgG7rowzXYftP7YslOeW3CRqPObnyjvqRJmdyoliIEEEAAAQQQQAABBBBAAAEEbBOo9vZs2X34tOuyHiifQ/rdTQDsCkWBdQIEwNa11B8Lsj0A/mzRDuk56RejZq57rZ5kSJ3CqJYiBBBAAAEEEEAAAQQQQAABBGwTqNRvluw9dsZ1WfeVu03631PCtc6rBbZnIV51t2FeBMA2dNGHa7D9pvfpwh3y5mSzAHhljzqSKW1KH14FLBkBBBBAAAEEEEAAAQQQQAABkXK9Z8qhv/9xpWhZNrsMaFnStc6rBbZnIV51t2FeBMA2dNGHa7D9pjdywXbp/eMmo84u63aH3Jw+lVEtRQgggAACCCCAAAIIIIAAAgjYJlD6zely5NQ512W1KJNd3rmXANgVigLrBAiArWupPxZkewD88fzt0ucnswB44Uu1JPsNqf3ReFaJAAIIIIAAAggggAACCCCAQAyB4q9PkxP/nHd1ubv0rfLufaVc67xaYHsW4lV3G+ZFAGxDF324Bttveh/N+036Tdls1Nm5XWpKrkxpjGopQgABBBBAAAEEEEAAAQQQQMA2gUKvTpEz5y66LuuuUrfIe/eXdq3zaoHtWYhX3W2YFwGwDV304Rpsv+kNm/ub9J9qFgDPfL6G5MuS1odXAUtGAAEEEEAAAQQQQAABBBBAQCR/95/k3IVLrhTNSt4iHzxAAOwKRYF1AgTA1rXUHwuyPQAeOmebDJj2q1Ezpz5bTQplTW9USxECCCCAAAIIIIAAAggggAACNglcunRJcr/yk9GSmpTIJkNalTGq9WKR7VmIF81tmRMBsC2d9Nk6bL/pDZm9VQZO32LU1clPV5Vit2YwqqUIAQQQQAABBBBAAAEEEEAAAZsELly8JHm7mQXAjYtnk6EPEgDb1H/WYiZAAGzmRJXHBGwPgD+YtVXenWEWAP/wVBUpdVtGj3WI6SCAAAIIIIAAAggggAACCCCQ9AJnzl2QQq9ONfqghsWyyrCHyhrVerHI9izEi+a2zIkA2JZO+mwdtt/03pu5Rd6budWoq/97opKUy3WjUS1FCCCAAAIIIIAAAggggAACCNgk8Pc/56XY69OMllS/6M3yUetyRrVeLLI9C/GiuS1zIgC2pZM+W4ftNz3d/au7gE3GN+0rSsU8N5mUUoMAAggggAACCCCAAAIIIICAVQLHTp2Tkm9ON1pT3SI3y8cPEwAbYVFklQABsFXt9M9ibA+A35n+qwyevc2ooV+1rSBV82cyqqUIAQQQQAABBBBAAAEEEEAAAZsEDv39j5TrPdNoSXUKZ5GRj9xuVOvFItuzEC+a2zInAmBbOumzddh+0xswbbMMnfObUVc/a3O71CyYxaiWIgQQQAABBBBAAAEEEEAAAQRsEth//IxU6DvLaEm1C2WRTx8lADbCosgqAQJgq9rpn8XYHgD3n7pZhs01C4BHPlxO6hS52T/NZ6UIIIAAAggggAACCCCAAAII/Cew58gpqdp/jpFHzYKZ5bM25Y1qvVhkexbiRXNb5kQAbEsnfbYO2296/X7aJB/N327U1eEPlZEGxbIZ1VKEAAIIIIAAAggggAACCCCAgE0COw+dlJoD5xotqXqBzPLFYwTARlgUWSVAAGxVO/2zGNsD4D4//iIfL9hh1NAhrUpLkxK3GNVShAACCCCAAAIIIIAAAggggIBNAtsO/C113p1ntKSq+TLJV+0qGNV6scj2LMSL5rbMiQDYlk76bB223/R6Tf5FPlloFgC/d18puav0rT67AlguAggggAACCCCAAAIIIIAAAiKb9x2XBu8tMKKonPcmGf14RaNaLxbZnoV40dyWOREA29JJn63D9pveG5M2yqhFO426OrBlSbmnbHajWooQQAABBBBAAAEEEEAAAQQQsEng5z+OSZPBC42WVDHPjfJN+0pGtV4ssj0L8aK5LXMiALalkz5bh+03vZ4TN8pni80C4LfuLi73l8/hsyuA5SKAAAIIIIAAAggggAACCCAgsnb3Ublr6CIjivK5b5RvOxAAG2FRZJUAAbBV7fTPYmwPgF+b8LN8seR3o4b2uquYtK6Y06iWIgQQQAABBBBAAAEEEEAAAQRsEli587DcM3yJ0ZJuz3WDfPdEZaNaLxbZnoV40dyWOREA29JJn63D9ptejx82yFdLdxl1tWfTIvJoldxGtRQhgAACCCCAAAIIIIAAAgggYJPA0u1/yf0jlhotqWzOG+T7JwmAjbAoskqAANiqdvpnMbYHwN3Gb5DRy8wC4B6NC0u7ann803xWigACCCCAAAIIIIAAAggggMB/Agu3HpKHPllm5FE6R0YZ37GKUa0Xi2zPQrxobsucCIBt6aTP1mH7Te+VcetlzPLdRl19uWEheaJGXqNaihBAAAEEEEAAAQQQQAABBBCwSWDurwfk0VErjJZU8raMMuEpAmAjLIqsEiAAtqqd/lmM7QHwS/9bL2NXmgXAXeoVkE618/un+awUAQQQQAABBBBAAAEEEEAAgf8EZv6yX9p9sdLIo0T2DDKxU1WjWi8W2Z6FeNHcljkRANvSSZ+tw/ab3ovfrZPvVu0x6mrnO/LLc3ULGNVShAACCCCAAAIIIIAAAggggIBNAlN/3itPfLXaaEnFbk0vk5+uZlTrxSLbsxAvmtsyJwJgWzrps3XYftN74dt18v1qswC4U6180qV+QZ9dASwXAQQQQAABBBBAAAEEEEAAAZHJ6/+UTqPXGFEUyZZefupMAGyERZFVAgTAVrXTP4uxPQB+fuxaGbfmD6OGdqiRR15pWNioliIEEEAAAQQQQAABBBBAAAEEbBL4Yc0f8uzYtUZLKpQ1nUx9trpRrReLbM9CvGhuy5wIgG3ppM/WYftN79lv1sgPa/806mq7qrmlR5MiRrUUIYAAAggggAACCCCAAAIIIGCTwP9W7ZEu360zWlLBm9PJtOcIgI2wKLJKgADYqnb6ZzG2B8DPjFkjE9eZBcCPVs4lPZsV9U/zWSkCCCCAAAIIIIAAAggggAAC/wl8s3yXvDxug5FH/ixpZcbzNYxqvVhkexbiRXNb5kQAbEsnfbYO2296nUavlsnr9xp19cEKOaRP8+JGtRQhgAACCCCAAAIIIIAAAgggYJPAl0t/l1d/+NloSXkzp5FZL9Q0qvVike1ZiBfNbZkTAbAtnfTZOmy/6XX8epX8tGGfUVfvv/02eatFCaNaihBAAAEEEEAAAQQQQAABBBCwSeCzRTuk56RfjJaUJ1Mamd2FANgIiyKrBAiArWqnfxZjewD8xJerZOpGswC4RZns8s69Jf3TfFaKAAIIIIAAAggggAACCCCAwH8CIxdsl94/bjLyyHlTapn3Yi2jWi8W2Z6FeNHcljkRANvSSZ+tw/abXvsvVsr0X/YbdfWuUrfIe/eXNqqlCAEEEEAAAQQQQAABBBBAAAGbBIbP+03emrLZaEm33Xi9LOha26jWi0W2ZyFeNLdlTgTAtnTSZ+uw/abX7vOVMnOTWQDcuEQ2GdqqjM+uAJaLAAIIIIAAAggggAACCCCAgMiQ2Vtl4PQtRhS3ZrxeFr1MAGyERZFVAgTAVrXTP4uxPQBu+9kKmbX5gFFD6xe9WT5qXc6oliIEEEAAAQQQQAABBBBAAAEEbBIYNGOLvD9rq9GSbsmQSha/codRrReLbM9CvGhuy5wIgG3ppM/WYftNr82o5TLn14NGXa1TOIuMfOR2o1qKEEAAAQQQQAABBBBAAAEEELBJYOC0X2XInG1GS8qaPpUs7UYAbIRFkVUCBMBWtdM/i7E9AH7k0+Uyb4tZAFyjQGb5/LHy/mk+K0UAAQQQQAABBBBAAAEEEEDgP4F+UzbJR/O2G3lkSZdSlnevY1TrxSLbsxAvmtsyJwJgWzrps3XYftNr/ckyWbD1kFFXq+bLJF+1q2BUSxECCCCAAAIIIIAAAggggAACNgn0nvyLjFy4w2hJmdKmlJU9CICNsCiySoAA2Kp2+mcxtgfAD41cJgu3mQXAFXLfKGM7VPJP81kpAggggAACCCCAAAIIIIAAAv8J9Jy4UT5bvNPI46Y018mqV+sa1XqxyPYsxIvmtsyJANiWTvpsHbbf9Fp9vFQW//aXUVfL5rxBvn+yslEtRQgggAACCCCAAAIIIIAAAgjYJNB9/Ab5etkuoyXdkDqFrHmtnlGtF4tsz0K8aG7LnAiAbemkz9Zh+03v/hFLZOn2w0ZdLXlbRpnwVBWjWooQQAABBBBAAAEEEEAAAQQQsEng5e/XyzcrdhstKcP1KWTd6wTARlgUWSVAAGxVO/2zGNsD4Hs/WiLLd5gFwEVvSS8/PlPNP81npQgggAACCCCAAAIIIIAAAgj8J/DCt+vk+9V7jDzSpUouG3rWN6r1YpHtWYgXzW2ZEwGwLZ302Tpsv+m1HL5YVuw8YtTVQlnTydRnqxvVUoQAAggggAACCCCAAAIIIICATQLPfrNGflj7p9GS0qZMLj+/QQBshEWRVQIEwFa10z+LsT0AbjFssaz63SwAzps5jcx6oaZ/ms9KEUAAAQQQQAABBBBAAAEEEPhP4KnRq+XH9XuNPFJfl0x+ebOBUa0Xi2zPQrxobsucCIBt6aTP1mH7Ta/5h4tkza6jRl3NeVNqmfdiLaNaihBAAAEEEEAAAQQQQAABBBCwSaDDlytl2sb9RktKleJa2dyroVGtF4tsz0K8aG7LnAiAbemkz9Zh+03vziELZd2eY0ZdvTXj9bLo5dpGtRQhgAACCCCAAAIIIIAAAgggYJNAu89XyMxNB4yWdF3ya2VLbwJgIyyKrBIgALaqnf5ZjO0BcNPBC2XDH2YB8M3pU8qybnX803xWigACCCCAAAIIIIAAAggggMB/Ao98ulzmbTlo5JH82mtkW99GRrVeLLI9C/GiuS1zIgC2pZM+W4ftN73GHyyQjX8eN+pqprTXycoedY1qKUIAAQQQQAABBBBAAAEEEEDAJoGHRi6ThdsOGS3p2mtEtvdrbFTrxSLbsxAvmtsyJwJgWzrps3XYftNr+P4C2bTXLADOcH0KWfd6PZ9dASwXAQQQQAABBBBAAAEEEEAAAZH7Ploiy3YcNqbY+RYBsDEWhdYIEABb00p/LcT2ALjBe/Nl874TRk1Nc10y2RjBTzE1WiRFCCCAAAIIIIAAAggggAACCMQi0GLYYln1+xFjmx39Gsk111xjXO+lQtuzEC9Z2zYXAmDbOuqT9dh+06s3aJ5s2f+3UTdTJr9Wfo3gQ+yNFkkRAggggAACCCCAAAIIIIAAArEI3Dl0kazbfdTY5re+jSSZngURgcP2LCQCWxIxUyYAjphWMdFgAdtvenXenSfbDpgFwPovLv0XGAMBBBBAAAEEEEAAAQQQQAABvwmE8gwdtdnap6GkSHZtRDLZnoVEZFMiZNIEwBHSKKYZXcD2m17td+bK9oMnjdseyb/CYrxIChFAAAEEEEAAAQQQQAABBBCIIRDKEYr60l97N5CUyZNFpKPtWUhENiVCJk0AHCGNYpr+CoBrDZwrOw6ZB8CR/BNMrm0EEEAAAQQQQAABBBBAAAEEEipwxztz5bcQNlBt7tVAUqUgAE6oN6+LTAEC4Mjsm+9nbftPvWoMmCO//3XKuM+b3mwg118Xmf8CM14khQgggAACCCCAAAIIIIAAAgjEEAj1v59/ebO+pL4ueUQ62p6FRGRTImTSBMAR0iimGV3A9ptetbdny+7Dp43bvqFnPUmXKoVxPYUIIIAAAggggAACCCCAAAII2CBQ5a3Z8sdR8/9+/vmN+pI2JQGwDb1nDeYCBMDmVlR6SMD2ADjUf4GtebWu3JDmOg91iKkggAACCCCAAAIIIIAAAgggkPQCFfrOlP3H/zH+oPU960n6CN1AZXsWYtxECkMWIAAOmYwXeEHA9pte5X6z5M9jZ4ypV3SvI5nTpTSupxABBBBAAAEEEEAAAQQQQAABGwTK9Z4hh/4+a7yUda/VkwypI/M3aG3PQoybSGHIAgTAIZPxAi8I2H7Tq9h3luw7bh4AL3mltmTLcL0XWsMcEEAAAQQQQAABBBBAAAEEELhqAiXfmC7HTp8z/rxI/g1a27MQ4yZSGLIAAXDIZLzACwK23/TK95kpB06Y/wrLgq615LYbU3uhNcwBAQQQQAABBBBAAAEEEEAAgasmUPS1qXLy7AXjz1vVo47clDYyf4PW9izEuIkUhixAABwyGS/wgoDtN71Qf4VlTpeakjtTGi+0hjkggAACCCCAAAIIIIAAAgggcNUECvaYIv+cv2j8eZF8hKLtWYhxEykMWYAAOGQyXuAFAdtvemV6zZDDJ83PMJrxXHXJf3M6L7SGOSCAAAIIIIAAAggggAACCCBw1QTydvtJLly8ZPx5y7vdIVnSpzKu91Kh7VmIl6xtmwsBsG0d9cl6bL/plXpzuhw9ZX6G0ZTO1aRwtvQ+6T7LRAABBBBAAAEEEEAAAQQQQEDk0qVLkvuVn0KiiORn6NiehYTUSIpDEiAADomLYq8I2H7TK9Fzmhw/c96Ye1KnqlI8ewbjegoRQAABBBBAAAEEEEAAAQQQiHSBcxcuSv7uU0JaxqKXa8utGSPzIeq2ZyEhNZLikAQIgEPiotgrArbf9Iq/Pk1O/GMeAI/rWFnK5LjBK+1hHggggAACCCCAAAIIIIAAAggkucDpsxek8GtTQ/qcSH6Iuu1ZSEiNpDgkAQLgkLgo9oqA7Te9UJ9i+t0TleT2XDd6pT3MAwEEEEAAAQQQQAABBBBAAIEkFzhx5pwU7zk9pM+Z/2ItyXFT6pBe45Vi27MQrzjbOA8CYBu76oM12X7TK/zqVDl97oJxJ0c/XkEq581kXE8hAggggAACCCCAAAIIIIAAApEucOTkWSnda0ZIy5jbpabkypQmpNd4pdj2LMQrzjbOgwDYxq76YE223/QK9pgi/5y/aNzJL9uWl2r5MxvXU4gAAggggAACCCCAAAIIIIBApAscPPGP3N5nZkjLmP1CDcmTOW1Ir/FKse1ZiFecbZwHAbCNXfXBmmy/6RXoPkXOXjAPgEc9ervUKpTFB51niQgggAACCCCAAAIIIIAAAgj8K7D32Gmp1G92SBwzn68h+bIQAIeERnHECxAAR3wL/bkA2wPgfN1+kvMXLxk3d0TrslKvaFbjegoRQAABBBBAAAEEEEAAAQQQiHSB3YdPSbW354S0jBnPVZf8N6cL6TVeKbY9C/GKs43zIAC2sas+WJPtN708r/woIeS/MuzBMtKweDYfdJ4lIoAAAggggAACCCCAAAIIIPCvwI5DJ6XWwLkhcUx7troUzEoAHBIaxREvQAAc8S305wJsD4BzvfxjSI394IHS0qzkLSG9hmIEEEAAAQQQQAABBBBAAAEEIllg6/4TUnfQ/JCWMKVzNSmcLX1Ir/FKse1ZiFecbZwHAbCNXfXBmmy+6V26dElyv/JTSF0cdF9JaV46e0ivoRgBBBBAAAEEEEAAAQQQQACBSBbYtPe4NHx/QUhL+PGZqlL0lgwhvcYrxTZnIV4xtnUeBMC2dtbyddl807tw8ZLk7RZaAPz2PSXk3nK3Wd51locAAggggAACCCCAAAIIIIDA/wts2HNMmg5ZGBLJ5KerSrFbCYBDQqM44gUIgCO+hf5cgM0B8LkLFyV/9ykhNbZv8+LSqkKOkF5DMQIIIIAAAggggAACCCCAAAKRLLB61xG5+8PFIS1hYqcqUiJ7xpBe45Vim7MQrxjbOg8CYFs7a/m6bL7pnTl3QQq9OjWkDva6s6i0rpQrpNdQjAACCCCAAAIIIIAAAggggEAkC6zYeVhaDl8S0hJ+eKqKlLqNADgkNIojXoAAOOJb6M8F2BwAnz57QQq/FloA/FqTIvJY1dz+vBhYNQIIIIAAAggggAACCCCAgC8FFv92SFp9vCyktY/rWFnK5LghpNd4pdjmLMQrxrbOgwDY1s5avi6bb3on/zkvRV+fFlIHuzUqJO2r5w3pNRQjgAACCCCAAAIIIIAAAgggEMkC87cclIc/XR7SEv73RCUpl+vGkF7jlWKbsxCvGNs6DwJgWztr+bpsvumdOHNOivecHlIHuzYoKB1r5gvpNRQjgAACCCCAAAIIIIAAAgggEMkCczYfkDafrQhpCd92qCTlcxMAh4RGccQLEABHfAv9uQCbA+Bjp89JyTdCC4Cfr1tAnrkjvz8vBlaNAAIIIIAAAggggAACCCDgS4HpG/dJ+y9XhbT2b9pXlIp5bgrpNV4ptjkL8YqxrfMgALa1s5avy+ab3tFTZ6XUmzNC6qCGvxoCMxBAAAEEEEAAAQQQQAABBBDwi8CUDXvlya9Xh7Tc0Y9XkMp5M4X0Gq8U25yFeMXY1nkQANvaWcvXZfNN7/DJs1KmV2gBcMeaeaVrg0KWd53lIYAAAggggAACCCCAAAIIIPD/AhPX/SnPjFkTEsnX7SpIlXwEwCGhURzxAgTAHmphzZo1Zd68ecYz2rFjh+TKlSve+r1798rw4cNl0qRJsnPnTjlz5oxkzZpVqlWrJo899pjUqFHD+PO0cMKECfLll1/KihUrZP/+/ZI+fXrJmzevNG/eXDp06CAZMmQI6f0SWmxzAHzo73+kXO+ZIdG0r55HujUqHNJrKEYAAQQQQAABBBBAAAEEEEAgkgXGrd4jz3+7LqQlfNm2vFTLnzmk13il2OYsxCvGts6DANhDnb3SAfD48eOdkPfo0aNxrvLxxx+XYcOGSbJkyeKVOHHihLRq1UomT54cZ1327Nll7NixUrly5SRXtfmmd+DEGSnfZ1ZIho9VyS2vNS0S0msoRgABBBBAAAEEEEAAAQQQQCCSBb5duVu6/m99SEv4/LHyUqMAAXBIaBRHvAABsIdaGBwAa3jrNurVqyepU6eOtWzmzJnSqFEjOXfunPP9xo0bS7NmzSRNmjSyevVqGTlypBw/ftz5nobAI0aMiPPjzp8/77zXjBn/Hktw8803O68I5EwbAAAgAElEQVQpUqSIHD58WMaMGSOLFi1yvpcxY0ZZuHChFC1a1G36ifq+zQHw/uNnpELf0ALghyvllDfvLJYoU16MAAIIIIAAAggggAACCCCAQCQJjF62S7qN3xDSlEe1uV1qFcwS0mu8UmxzFuIVY1vnQQDsoc4GB8CXLl1K8Mz0mIeCBQvKrl27nPcYPHiwdOrUKdr7bdmyxTn+Yd++fc7Xp0+fLnXr1o31M3WHcMeOHZ3vaeg7e/ZsJwQOHl26dJF33nnH+VKVKlWcEDgph803vb3HTkulfrND4mtVIYf0bV48pNdQjAACCCCAAAIIIIAAAgj8H3v3AV1FtbZx/KXXANJ7lxY6oYbeuwiignJpIoIFFUEpUgRBBL0IAhEREEXEAtJbqKF3CCX0Ji30Kp27ZlggesMhM0M4s/f8Z61vcZPMu2fv3zvfsPJ42IMAAioL/LDqoHw8bbulJYxtFSRV8/0z07A0gB9P1jkL8SOrJy5NAOyiNj+pAHjEiBEPAt8GDRrI9OnTo1zllClTpEmTJubPypQpI8aD5N/H7du3xdja4X5QvGHDBilevHiU5wUFBcnmzZvNn82dO1dq1aoVY7o6P/SOnv9Lgj+zFgC/GJRZPn+hSIx5MzACCCCAAAIIIIAAAggggAACbhMYu/yAfDJzh6VpjflPkFQvQABsCY2TlRcgAHZRC59UAFyxYkUJCwszV7Z48WIxxo3quHPnjvkCN+PlcMYR1UvljE/7VqtWzfy58YnhJUuWPFJs3Lhx5p7DxtGyZUsZP358jOnqHAAfOXtVKny+2JJd42KZ5MuXilqq4WQEEEAAAQQQQAABBBBAAAEEVBYYvWyfDJgdYWkJo1uUkJqB6S3VuOVknbMQtxjrOg8CYBd19kkEwMbL2ox9eI1wNyAgQM6dO+fzBW8dOnSQkJAQU2HkyJFifP3w0bVrVxk8eLD5rUGDBonx9aOOkydPSvr09x6iadOmFePrmDp0fugdPnNVKg62FgA3LJJRhjUrFlPcjIsAAggggAACCCCAAAIIIICA6wRGLtkrn8/dZWleIa+WkNoFCYAtoXGy8gIEwC5q4cMBsPHStk2bNsmpU6fMF7dlzJhRypUrJ82bN5cqVao8ctZr1qwxt3MwDuOTwEuXLvW5wrFjx0rbtm3Nc4x9fo3tIx4+6tSpY27nYBzGp4F9Xds4J2vWrHLkyBHz/MjISEmTJmberKlzAHzw9BWpPOTRn7SOqqF1C6WXka+UcNHdzFQQQAABBBBAAAEEEEAAAQQQiFmBYQv3yJcLdlu6yKhXikudQhks1bjlZJ2zELcY6zoPAmAXdfbhANjXtKpWrSo//vijZMjw/w+sCRMmmNsvGEd0tmEwtogwxjMOY6uH0NDQf1w6Z86c5tYQxhHVFhH/nqexTcSyZcvMbxvbUJQvX96ycFR7Ef97kPDwcGnfvr357ZUrV0rZsmUtX8etBftPXZaqX/gO7v8995oF0sno/wS5dUnMCwEEEEAAAQQQQAABBBBAAIEnLmCEv0YIbOUY0by41CtMAGzFjHPVFyAAdlEPjQB469atUqNGDTFeqJYpUyZz+4ajR4+an76dM2eOubWDcWTLlk1Wr179YMuF+8sYNmyYdOrUyfyyc+fOMmTIEJ8rNK5XpMi9l4eVKFFC1q9f/4/zU6ZMaW4jYRzG9hJJkyb1OV7jxo1l6tSp5jkzZsyQ+vXrWxaOFSuWpRrdAuC9kZek+pf3QvToHlXzpZWxrUpG93TOQwABBBBAAAEEEEAAAQQQQEB5gc/nRsjIJfssrWN4s2LSoEhGSzVuOZlPALulE+rNgwDYRT0z/h/ZCGHjx48f5aw2btwoTZo0efDSNmN7htmzZ//j3AEDBkiPHj3M7xl/9u/f3+cK9+zZI3ny5DHPMf7cteufe+cYc7l586b5c+PPuHHj+hzvlVdekZ9++sk8x/izWbNmloW9HgDvPnlJav7XWgBc4dnU8kPb0patKUAAAQQQQAABBBBAAAEEEEBAVYEBs3fK6GX7LU3/q5eLynNFM1mqccvJBMBu6YR68yAAVqxnu3fvlsKFC8v169fNma9du1ZKlvz7k58PB8A9e/aUfv36+VyhGwNgr28BEXHiotQeGmbpziyXK5X81O7e3s8cCCCAAAIIIIAAAggggAACCHhB4JMZO2TsinvbVkb3+O9LReT5Ypmje7qrziMAdlU7lJoMAbBS7bo32ddff12+/fZb83/36tVL+vbt+2AVOmwBEZ2W6PzQ23HsotQdZi0ALpU9pfzyhj77IEfnHuAcBBBAAAEEEEAAAQQQQAABbwv0mrZNJqw6ZAnhi6ZFpEkJAmBLaJysvAABsIItnDRpkjRv3tycedOmTeWXX355sAodXgIXnZboHABvO3pB6g9fHh2GB+cUz5pCpnQMtlTDyQgggAACCCCAAAIIIIAAAgioLNB9arj8tOawpSUMfqGwNA3KYqnGLSfrnIW4xVjXeRAAK9jZBQsWSM2aNc2ZGy+Mmz9//oNVrFmzRsqUubcVQMWKFWXp0qU+Vzh27Fhp27ateU7Hjh1lxIgR/zjf2Gd47ty55veMF9FVqVLF53hZs2aVI0eOmOdERkZKmjRpYkRY54de+J8XpMHX1gLgwpmTy/S3yseINYMigAACCCCAAAIIIIAAAggg4EaBrr9tkV/W/2lpap83KSwvliQAtoTGycoLEAAr2ELj5WrGy9aM49+fAL506ZKkSJFC7ty5IwEBAXLu3DmJEyfOI1fZoUMHCQkJMX8+cuRIMb5++OjatasMHjzY/NagQYPE+PpRx8mTJyV9+vTmj9OmTSvG1zF16BwAbzlyXp4bscISXf4MyWROpwqWajgZAQQQQAABBBBAAAEEEEAAAZUF3p+8WaZsOmppCZ81LiQvl8pqqcYtJ+uchbjFWNd5EAAr2Nl27drJmDFjzJlH9aI345O/YWH39pBdsmSJVKpUKcpVGiFx7ty55cCBexumG39mz579H+can/qtVq2a+b3KlSvL4sWLHyk2btw4adOmjfnzVq1aifF1TB06P/Q2HT4nz49caYkuT7qkMv+9qPtsaSBORgABBBBAAAEEEEAAAQQQQEARgXcmbZLpW45Zmu2A5wtJ89IEwJbQOFl5AQJgxVq4a9cuKVKkiFy/ft2c+erVq6V06dL/WIXxSd4333zT/F6DBg1k+vTpUa5yypQp0qRJE/NnxrYRRqj67+P27duSOXNmOXHihPmjDRs2SPHixaM8LygoSDZv3mz+zNg2olatWjGmq3MAvOHQOWkyyloAnDN1Eln0QeUY82ZgBBBAAAEEEEAAAQQQQAABBNwm0HHiBpkdfi+viO7Rv1FBebVMtuie7qrzdM5CXAWt4WQIgF3S1GHDhokRoJYrV+6RM9q0aZM0btxYDh48aJ5j7AM8b968/zv/2rVrkjdvXjl8+N5G6F9//fWDQPj+yXv27DH3CL4f7Br7ClevXj3Ka48aNcrcH9g4AgMDzb2AjS0eHj66dOkiQ4YMMb8VHBwsy5db28PWaht0fuitP3hWXgj5/zDel1HWlIllWVff+zNbNeZ8BBBAAAEEEEAAAQQQQAABBNws8PqE9TJ/h7XtJ/s9Fygtyv7zXz+7eY0Pz03nLESVHqg6TwJgl3SuUaNGMm3aNMmVK5cZxBYsWFBSpUpl7t977NgxWbhwocyePdvc29c4smXLJitXrpSMGTNGuYLQ0FCpW7eu3Lx50/x5/fr1pWHDhpIkSRLZuHGjuYXEhQsXzJ8ZW0qMHj36kRK3bt0yxzJCYuMw9vk1agoUKCBnz56VSZMmPQh8kydPLitWrDCD4pg8dH7orT1wVl78xloAnDF5QlnZ7d5WHRwIIIAAAggggAACCCCAAAIIeEGgzfh1sigi0tJS+zYMlJblCIAtoXGy8gIEwC5p4f0AODrTMbZWGDt27CPD3/tjTJ061dyT9/z5848c1ghyjU/4+npRnFFsvFyuefPmMnPmzEeOZWwVMXnyZJ+fYo7O+qJzjs4B8Or9Z+Tl0aujw/DgnDQBCWRdj6g/wW1pIE5GAAEEEEAAAQQQQAABBBBAQBGBFt+tkbA9py3NtneDAtI6OIelGrecrHMW4hZjXedBAOySzu7bt898YZuxp++WLVvk1KlTcvr0aXOvX+NTtcbL2cqWLWuGsMZ+vdE9jh8/bga8M2bMMLeOMLaHyJAhg5QvX17atm37yBfEPWp841PKEyZMkHXr1klkZKQEBASYn1o2tqZo3769Odencej80Fu577Q0/3aNJcaUSeLLxo9rWKrhZAQQQAABBBBAAAEEEEAAAQRUFmj+7WpZue+MpSV8XL+AtC1PAGwJjZOVFyAAVr6F3lyAzgHwir2n5ZUx1gLggIRxJbxPzL10z5t3GatGAAEEEEAAAQQQQAABBBBws8CLIatk7cGzlqbYs15+ea1CTks1bjlZ5yzELca6zoMAWNfOar4unR96YXtOSYvv1lrqYOL4cWTHJ7Ut1XAyAggggAACCCCAAAIIIIAAAioLNB65QjYefvS2l1GtrXvdfPJ6xVxKLlvnLETJhig0aQJghZrFVP8W0Pmht2RXpLQat85Su+PHiS27P61jqYaTEUAAAQQQQAABBBBAAAEEEFBZoOHXy2Xrn/decB/d46M6+eSNSgTA0fXiPD0ECID16KPnVqFzALw4IlJaj7cWAMeKJXJgYD3P3QcsGAEEEEAAAQQQQAABBBBAwLsCdb4Kk53HL1oC6Fo7r3SsnNtSjVtO1jkLcYuxrvMgANa1s5qvS+eH3sKdJ6Xt9+std3D/gLoSO3Ysy3UUIIAAAggggAACCCCAAAIIIKCiQM3/LpXdJy9bmvoHNfPIW1WftVTjlpN1zkLcYqzrPAiAde2s5uvS+aG3YMdJaTfBegC8q39tSRA3juadZ3kIIIAAAggggAACCCCAAAII3BOoOmSJ7D99xRLH+zXyyDvVCIAtoXGy8gIEwMq30JsL0DkAnrf9hLT/YYPlxu74pJYkjh/Xch0FCCCAAAIIIIAAAggggAACCKgoUPHzxXL47FVLU3+3+rPybvU8lmrccrLOWYhbjHWdBwGwrp3VfF06P/Tmbjsub/y40XIHt/SuKckTxbNcRwECCCCAAAIIIIAAAggggAACKgqUG7hQjl24Zmnqxqd/jU8Bq3jonIWo2A+V5kwArFK3mOsDAZ0ferPDj0vHidYD4A09q0uqpAm4SxBAAAEEEEAAAQQQQAABBBDwhEDJT0Pl1KXrltb6dtXc0rlmXks1bjlZ5yzELca6zoMAWNfOar4unR96M7cek7d+2mS5g2u7V5O0yRJarqMAAQQQQAABBBBAAAEEEEAAARUFivdbIGev3LA09Ter5JIutfJZqnHLyTpnIW4x1nUeBMC6dlbzden80Ju+5Zi8M8l6ALzio6qSKUUizTvP8hBAAAEEEEAAAQQQQAABBBC4J1Cozzy5dO2WJY4OlXPJh7UJgC2hcbLyAgTAyrfQmwvQOQCetvmodPp5s+XGLutSRbKmSmy5jgIEEEAAAQQQQAABBBBAAAEEVBQo0GuuXL1x29LU21fKKd3q5LdU45aTdc5C3GKs6zwIgHXtrObr0vmhN3XTn/Le5C2WO7iwcyXJlSap5ToKEEAAAQQQQAABBBBAAAEEEFBRIE+POXLj9h1LU3+9Yk7pXpcA2BIaJysvQACsfAu9uQCdA+DfN/wpnX+1HgDPe7ei5E0f4M0bglUjgAACCCCAAAIIIIAAAgh4TiBHt1ly9661Zb9WPof0rF/AWpFLztY5C3EJsbbTIADWtrV6L0znh96v649Il9+2Wm7grHfKS2DG5JbrKEAAAQQQQAABBBBAAAEEEEBANYE7d+5Kzu6zLU+7TXAO6dWAANgyHAVKCxAAK90+705e5wD4l3VHpOvv1gPgaW8GS5EsKbx7U7ByBBBAAAEEEEAAAQQQQAABzwhcv3Vb8vaca3m9rcpllz4NAy3XuaFA5yzEDb46z4EAWOfuarw2nR96P689LB9NCbfcvd87lJMS2Z6xXEcBAggggAACCCCAAAIIIIAAAqoJXL1xSwr0mmd52i3LZpO+zxW0XOeGAp2zEDf46jwHAmCdu6vx2nR+6E1cc0h6TN1muXuTXy8jpXOmslxHAQIIIIAAAggggAACCCCAAAKqCVz466YU6Tvf8rRblMkm/RoRAFuGo0BpAQJgpdvn3cnrHAD/sPqQfPyH9QB44mulJTh3au/eFKwcAQQQQAABBBBAAAEEEEDAMwJnLl+XEv1DLa/3ldJZ5dPnC1muc0OBzlmIG3x1ngMBsM7d1XhtOj/0Jqw6KL2mbbfcve/blJJKedJYrqMAAQQQQAABBBBAAAEEEEAAAdUEIi9ek1IDFlqedrNSWWVgYwJgy3AUKC1AAKx0+7w7eZ0D4PErDkifGTssN/e7lkFSLX86y3UUIIAAAggggAACCCCAAAIIIKCawNHzf0nwZ4ssT/uloCwy6IXCluvcUKBzFuIGX53nQACsc3c1XpvOD72xyw/IJzOtB8DftCghtQLTa9x1loYAAggggAACCCCAAAIIIIDAPYHDZ65KxcGLLXM0LZFZBjctYrnODQU6ZyFu8NV5DgTAOndX47Xp/NAbE7Zf+s/aabl7I5oXl3qFM1iuowABBBBAAAEEEEAAAQQQQAAB1QT2nbos1b5YannaTYpnli9eJAC2DEeB0gIEwEq3z7uT1zkA/nbZfvl0tvUA+KuXi8pzRTN596Zg5QgggAACCCCAAAIIIIAAAp4R2HXiktQauszyehsXyyRfvlTUcp0bCnTOQtzgq/McCIB17q7Ga9P5offN0n0ycE6E5e590bSINCmR2XIdBQgggAACCCCAAAIIIIAAAgioJrD92AWpN2y55Wk3KppRhr5czHKdGwp0zkLc4KvzHAiAde6uxmvT+aE3ask+GTTXegA8qEkhealkVo27ztIQQAABBBBAAAEEEEAAAQQQuCew5ch5eW7ECsscDYtklGHNCIAtw1GgtAABsNLt8+7kdQ6ARyzeK4Pn7bLc3E+fLyivlM5muY4CBBBAAAEEEEAAAQQQQAABBFQT2HDonDQZtdLytOsXziBfNy9uuc4NBTpnIW7w1XkOBMA6d1fjten80Pt60R4ZMn+35e71bRgoLctlt1xHAQIIIIAAAggggAACCCCAAAKqCazZf0ZeGr3a8rTrFcogI14hALYMR4HSAgTASrfPu5PXOQAetnCPfLnAegDcs15+ea1CTu/eFKwcAQQQQAABBBBAAAEEEEDAMwIr9p6WV8assbzeOgXTy6hXS1iuc0OBzlmIG3x1ngMBsM7d1XhtOj/0hobulqGheyx3r1udfNK+Ui7LdRQggAACCCCAAAIIIIAAAgggoJrA0t2npOXYtZanXSswnXzTIshynRsKdM5C3OCr8xwIgHXursZr0/mhZ3z61/gUsNWjS6288maV3FbLOB8BBBBAAAEEEEAAAQQQQAAB5QQW7jwpbb9fb3neNQqkk2//QwBsGY4CpQUIgJVun3cnr3MA/MX8XTJ80V7LzX2veh7pVP1Zy3UUIIAAAggggAACCCCAAAIIIKCawLztJ6T9DxssT7t6/rQypmVJy3VuKNA5C3GDr85zIADWubsar03nh97ncyNk5JJ9lrv3dtXc0rlmXst1FCCAAAIIIIAAAggggAACCCCgmsCsrcflzZ82Wp521XxpZWwrAmDLcBQoLUAArHT7vDt5nQPgz+ZESMhS6wHwG5VyyUd18nn3pmDlCCCAAAIIIIAAAggggAACnhGYtvmodPp5s+X1Vs6bRsa3LmW5zg0FOmchbvDVeQ4EwDp3V+O16fzQGzh7p3yzbL/l7rWrkEN61CtguY4CBBBAAAEEEEAAAQQQQAABBFQT+H3Dn9L51y2Wp10xTxqZ0IYA2DIcBUoLEAAr3T7vTl7nAPjTWTvk27ADlpvbqlx26dMw0HIdBQgggAACCCCAAAIIIIAAAgioJjB53WH58Pdwy9Munzu1/Phaact1bijQOQtxg6/OcyAA1rm7Gq9N54dev5k75Lvl1gPgFmWySb9GBTXuOktDAAEEEEAAAQQQQAABBBBA4J7AxDWHpMfUbZY5yuVKJT+1K2O5zg0FOmchbvDVeQ4EwDp3V+O16fzQ6ztju4xbcdBy95qVyiIDGxe2XEcBAggggAACCCCAAAIIIIAAAqoJfL/yoPSevt3ytMvkTCk/v17Wcp0bCnTOQtzgq/McCIB17q7Ga9P5oddn+nYZv9J6APxCicwypGkRjbvO0hBAAAEEEEAAAQQQQAABBBC4JzAmbL/0n7XTMkepHCnll/YEwJbhKFBagABY6fZ5d/I6B8C9pm2TCasOWW7u88UyyX9fKmq5jgIEEEAAAQQQQAABBBBAAAEEVBP4Zuk+GTgnwvK0S2Z/Rn59o5zlOjcU6JyFuMFX5zkQAOvcXY3XpvNDr+cf4fLj6sOWu1e/cAb5unlxy3UUIIAAAggggAACCCCAAAIIIKCawIjFe2XwvF2Wp10i2zPyewcCYMtwFCgtQACsdPu8O3mdA+DuU8PlpzXWA+DageklpEUJ794UrBwBBBBAAAEEEEAAAQQQQMAzAkNDd8vQ0D2W11ssawqZ2jHYcp0bCnTOQtzgq/McCIB17q7Ga9P5oddtylaZtPaI5e5Vz59OxrQMslxHAQIIIIAAAggggAACCCCAAAKqCXwxf5cMX7TX8rSLZEkh094kALYMR4HSAgTASrfPu5PXOQD+8LetMnm99QC4ct40Mr51Ke/eFKwcAQQQQAABBBBAAAEEEEDAMwKfzYmQkKX7LK+3cObkMv2t8pbr3FCgcxbiBl+d50AArHN3NV6bzg+9Lr9ukV83/Gm5exWeTS0/tC1tuY4CBBBAAAEEEEAAAQQQQAABBFQT+HTWDvk27IDlaRfMlExmvl3Bcp0bCnTOQtzgq/McCIB17q7Ga9P5odf5ly3y+0brAXCZnCnl59fLatx1loYAAggggAACCCCAAAIIIIDAPYE+07fL+JUHLXMUyJBMZnciALYMR4HSAgTASrfPu5PXOQB+f/JmmbLpqOXmBmV7Rn5T9E2mlhdLAQIIIIAAAggggAACCCCAgKcFev4RLj+utv4C9XzpA2TuuxWVtNM5C1GyIQpNmgBYoWYx1b8FdH7odfp5k0zbfMxyu4tmSSF/KLqRveXFUoAAAggggAACCCCAAAIIIOBpAbsvUM+bLkDmvUcA7Ombx4OLJwD2YNN1WLLOAfDbkzbJjC3WA2CV9zHS4Z5kDQgggAACCCCAAAIIIIAAAk9P4INft8hvNt6f82zapLLg/UpPb6JP8Eo6ZyFPkImhohAgAOa2UFJA54femz9tlFlbj1vui8r/jMXyYilAAAEEEEAAAQQQQAABBBDwtMB7kzfLVBvbJ+ZKk0QWdq6spJ3OWYiSDVFo0gTACjWLqf4toPNDr+PEDTI7/ITldudOm1RCFf2vmJYXSwECCCCAAAIIIIAAAggggICnBd76aaPMtPHhqZypk8iiDwiAPX3zeHDxBMAebLoOS9Y5AH7jhw0yd7v1ADh7qsSypEsVHdrLGhBAAAEEEEAAAQQQQAABBBDwKWD3d+dsqRLLUkV/d9Y5C+F2j1kBAuCY9WX0GBLQ+aH3+oT1Mn/HSctymZ9JJMs/rGq5jgIEEEAAAQQQQAABBBBAAAEEVBN47fv1ErrT+u/OWVImkrCuav7urHMWotr9p9p8CYBV6xjzNQV0fujZ/UssfbKEsrp7Ne4QBBBAAAEEEEAAAQQQQAABBLQXaDVurSzZdcryOjOlSCQrPiIAtgxHgdICBMBKt8+7k9c5AG47fp0sjIi03NzUSRPI+p7VLddRgAACCCCAAAIIIIAAAggggIBqAi2+WyNhe05bnnbG5AllZTc1PzylcxZiuZEUWBIgALbExcluEdD5odd63FpZbOO/YqZIHE8296rplhYxDwQQQAABBBBAAAEEEEAAAQRiTODl0atk9f6zlsdX+V/P6pyFWG4kBZYECIAtcXGyWwR0fui1HLtWlu62/s9YkiaIK9v61nJLi5gHAggggAACCCCAAAIIIIAAAjEm8MKolbL+0DnL46cNSCBre6j5r2d1zkIsN5ICSwIEwJa4ONktAjo/9Oz+M5aE8WJLRL86bmkR80AAAQQQQAABBBBAAAEEEEAgxgQajVghm4+ctzy+ytsn6pyFWG4kBZYECIAtcXGyWwR0fui9OmaNLN9rfR+juLFjyd4Bdd3SIuaBAAIIIIAAAggggAACCCCAQIwJ1B8eJtuOXrQ8fqok8WXDxzUs17mhQOcsxA2+Os+BAFjn7mq8Np0fes2/XS0r952x1b0DA+tKrFixbNVShAACCCCAAAIIIIAAAggggIAqArWHLpOIE5csT/eZxPFkk6Lvz9E5C7HcSAosCRAAW+LiZLcI6PzQs7uRvdGbvZ/WkbhxYrulTcwDAQQQQAABBBBAAAEEEEAAgRgRqP7lUtkbedny2MkTxZMtvdV8gbrOWYjlRlJgSYAA2BIXJ7tFQOeH3ovfrJK1B6y/ydToTUS/2pIwXhy3tIl5IIAAAggggAACCCCAAAIIIBAjApUHL5aDZ65aHjsgYVwJ76PmC9R1zkIsN5ICSwIEwJa4ONktAjo/9JqGrJR1B62/ydTozba+tSRpgrhuaRPzQAABBBBAAAEEEEAAAQQQQCBGBMoPWiR/nvvL8tjG78zG784qHjpnISr2Q6U5EwCr1C3m+kBA54de45ErZONh628yNXA296ohKRLH505BAAEEEEAAAQQQQAABBBBAQGuBMgMWyomL1yyvMXH8OLLjk9qW69xQoHMW4gZfnedAAKxzdzVem84PvUYjVsjmI/YC4PU9q0vqpAk07jxLQwABBBBAAAEEEEAAAQQQQEAkqJdhf0wAACAASURBVH+onL583TJFwnixJaJfHct1bijQOQtxg6/OcyAA1rm7Gq9N54fec18vly1/XrDVvdXdqkn65Alt1VKEAAIIIIAAAggggAACCCCAgCoCRT+ZL+ev3rQ83fhxY8vu/gTAluEoUFqAAFjp9nl38joHwA2GL5fwo/YC4LCuVSRLysTevTFYOQIIIIAAAggggAACCCCAgCcECvaeJ5ev37K81rixY8neAXUt17mhQOcsxA2+Os+BAFjn7mq8Np0fevWGhcn2YxdtdW/JB5Ule+oktmopQgABBBBAAAEEEEAAAQQQQEAVgXwfz5FrN+9Ynm7sWCL7B9azXOeGAp2zEDf46jwHAmCdu6vx2nR+6NX5Kkx2HrcXAIe+X1Fypw3QuPMsDQEEEEAAAQQQQAABBBBAAAGR3N1ny607d21RHPyMANgWHEXKChAAK9s6b09c5wC49tBlEnHikq0Gz323guRLn8xWLUUIIIAAAggggAACCCCAAAIIqCBw9+5dydFttu2pHhhYV2LFimW73l+FOmch/jL1ynUJgL3Sac3WqfNDr+Z/l8ruk5dtdWzm2+WlYKbktmopQgABBBBAAAEEEEAAAQQQQEAFgVu370juHnNsT3XfgLoSx9gLQrFD5yxEsVYoN10CYOVaxoQNAZ0fetW/XCp7I+0FwFM7lpNiWZ/hJkEAAQQQQAABBBBAAAEEEEBAW4FrN29Lvo/n2l7fnk/rSLw4sW3X+6tQ5yzEX6ZeuS4BsFc6rdk6dX7oVf1iiew/dcVWx357o6wEZU9pq5YiBBBAAAEEEEAAAQQQQAABBFQQuHz9lhTsPc/2VHf1ry0J4saxXe+vQp2zEH+ZeuW6BMBe6bRm69T5oVdlyBI5cNpeADypXRkpmyuVZt1mOQgggAACCCCAAAIIIIAAAgj8LXD+6g0p+skC2yQR/WpLwngEwLYBKVROgABYuZYxYUNA5wC40uDFcujMVVuN/rFtaSn/bGpbtRQhgAACCCCAAAIIIIAAAgggoILA6cvXJah/qO2p7vikliSOH9d2vb8Kdc5C/GXqlesSAHul05qtU+eHXoXPF8mRs3/Z6ti41iWlSt60tmopQgABBBBAAAEEEEAAAQQQQEAFgRMXrkmZgQttT3Vb31qSNAEBsG1ACpUTIABWrmVM2BDQOQAO/myRHD1vLwD+9j9BUqNAOm4SBBBAAAEEEEAAAQQQQAABBLQVOHL2qlT4fLHt9W3tU1OSJYxnu95fhTpnIf4y9cp1CYC90mnN1qnzQ6/cwIVy7MI1Wx0LebW41C6YwVYtRQgggAACCCCAAAIIIIAAAgioIHDw9BWpPGSJ7alu6VVTkicmALYNSKFyAgTAyrWMCRsCOgfApQeEysmL1201enizYtKgSEZbtRQhgAACCCCAAAIIIIAAAgggoILA3shLUv3LZbanuunjGvJMkvi26/1VqHMW4i9Tr1yXANgrndZsnTo/9Ep+GiqnLtkLgIe+VFQaFcukWbdZDgIIIIAAAggggAACCCCAAAJ/C0ScuCi1h4bZJtnQs7qkSprAdr2/CnXOQvxl6pXrEgB7pdOarVPnh15Q/wVy+vINWx0b/EJhaRqUxVYtRQgggAACCCCAAAIIIIAAAgioILDt6AWpP3y57amu61Fd0gQQANsGpFA5AQJg5VrGhA0BnQPg4v0WyNkr9gLggY0LSbNSWblJEEAAAQQQQAABBBBAAAEEENBWYNPhc/L8yJW217e2ezVJmyyh7Xp/FeqchfjL1CvXJQD2Sqc1W6fOD72in8yX81dv2upYv0YFpUWZbLZqKUIAAQQQQAABBBBAAAEEEEBABYH1B8/KCyGrbE91VbeqkiF5Itv1/irUOQvxl6lXrksA7JVOa7ZOnR96hfvMk4vXbtnqWO8GBaR1cA5btRQhgAACCCCAAAIIIIAAAgggoILAqn1npNm3q21PdcVHVSVTCgJg24AUKidAAKxcy5iwIaBzAFyo9zy5dN1eANyzXn55rUJObhIEEEAAAQQQQAABBBBAAAEEtBVYvue0vPrdGtvrC+taRbKkTGy73l+FOmch/jL1ynUJgL3Sac3WqfNDL7DXXLly47atjn1YO590qJzLVi1FCCCAAAIIIIAAAggggAACCKggsHhXpLQet872VJd1qSJZUxEA2wakUDkBAmDlWsaEDQGdA+D8H8+Vv27aC4A718gjb1d7lpsEAQQQQAABBBBAAAEEEEAAAW0FFuw4Ke0mrLe9viUfVJbsqZPYrvdXoc5ZiL9MvXJdAmCvdFqzder80Mvbc45cv3XHVsc6VXtW3quRx1YtRQgggAACCCCAAAIIIIAAAgioIDB323F548eNtqe6qHMlyZkmqe16fxXqnIX4y9Qr1yUA9kqnNVunzg+9PD3myI3b9gLgN6vkki618mnWbZaDAAIIIIAAAggggAACCCCAwN8CM7Yck7cnbbJNEvp+JcmdlgDYNiCFygkQACvXMiZsCOgcAOfuPltu3blrq9HtK+WUbnXy26qlCAEEEEAAAQQQQAABBBBAAAEVBP7YdFTenbzZ9lQXvFdRnk0XYLveX4U6ZyH+MvXKdQmAvdJpzdap80MvZ7dZYjP/lbblc8jH9Qto1m2WgwACCCCAAAIIIIAAAggggMDfAr+uPyJdfttqm2TeuxUlb3oCYNuAFConQACsXMuYsCGgcwCc/aNZtpvcsmw26ftcQdv1FCKAAAIIIIAAAggggAACCCDgdoFJaw9Ltynhtqc5p1MFyZ8hme16fxXqnIX4y9Qr1yUA9kqnNVunrg+9u3fvSo5us21365XSWeXT5wvZrqcQAQQQQAABBBBAAAEEEEAAAbcL/LD6kHz8xzbb05z1TnkJzJjcdr2/CnXNQvzl6aXrEgB7qdsarVXXh96t23ckd485tjv1UlAWGfRCYdv1FCKAAAIIIIAAAggggAACCCDgdoFxKw5I3xk7bE9z5tvlpWAmAmDbgBQqJ0AArFzLmLAhoGsAfOPWHcnT034A3KR4ZvnixSLcJAgggAACCCCAAAIIIIAAAghoKzAmbL/0n7XT9vqmvxUshTOnsF3vr0JdsxB/eXrpugTAXuq2RmvV9aF37eZtyffxXNudeq5oRvnq5WK26ylEAAEEEEAAAQQQQAABBBBAwO0Co5bsk0FzI2xP8483g6VoFgJg24AUKidAAKxcy5iwIaBrAPzXjduSv5f9ALheoQwy4pXi3CQIIIAAAggggAACCCCAAAIIaCswfOEe+WLBbtvrm9KxnBTP+ozten8V6pqF+MvTS9clAPZStzVaq64PvSvXb0lg73m2O1UrMJ180yLIdj2FCCCAAAIIIIAAAggggAACCLhd4L8LdstXC/fYnuZvb5SVoOwpbdf7q1DXLMRfnl66LgGwQt1u2bKlTJgw4cGMe/fuLX369HnsCo4fPy4hISEyY8YMOXjwoFy7dk3Sp08vFSpUkDZt2kilSpUeO8bDJ0ybNk1++OEHWbdunZw8eVKSJUsmuXLlkueff17at28vyZPH/Ebquj70Ll27KYX6zLfUj4dPrpYvrXzXqqTtegoRQAABBBBAAAEEEEAAAQQQcLvA4HkRMmLxPtvT/KV9WSmVgwDYNiCFygkQACvSsrlz50qdOnX+MdvoBMBTp041Q97z588/cqXt2rWTUaNGSZw4cXxqXLp0SZo3by4zZ8585HmZM2eWyZMnS7ly5WJUVtcA+MJfN6VIX/sBcKU8aeT7NqVi1J7BEUAAAQQQQAABBBBAAAEEEPCnwMA5O+WbpfttT+Hn18tImZypbNf7q1DXLMRfnl66LgGwAt2+ePGiFCxYUI4cOSJJkiSRK1eumLN+XAAcGhoqdevWlZs3b5rn16tXTxo2bGiOsXHjRhkzZowYYxuHEQKPHj36kRq3bt0yx1qwYIF5Trp06cyaAgUKyNmzZ2XSpEmyYsUK82cpUqSQ5cuXS2BgYIzp6vrQO3/1hhT95J6xnSM4dyqZ+FoZO6XUIIAAAggggAACCCCAAAIIIKCEQL+ZO+S75Qdsz/WndqWlXK7Utuv9VahrFuIvTy9dlwBYgW4b2yoY4azx6doXX3xRvvzyS3PWvgJgY5uHvHnzyuHDh81zhw8fLm+99dY/Vrt7925z+4cTJ06Y358/f77UqFEjShHjE8IdO3Y0f2aEvosWLTJD4IePDz74QL744gvzW8HBwWYIHFOHrg+9s1duSPF+9gNg45+wGP+UhQMBBBBAAAEEEEAAAQQQQAABXQV6T9sm3686ZHt5E18rLcG5CYBtA1KonAABsMtbtnjxYqlWrZrcvXvX3MN3/fr10rdvX3PWvgLgESNGPAh8GzRoINOnT49ypVOmTJEmTZqYPytTpowYweq/j9u3b5vh8/2geMOGDVK8ePEozwsKCpLNmzebPzO2rahVq1aMCOsaAJ++fF2C+ofaNiuR7Rn5vUPMbr9he3IUIoAAAggggAACCCCAAAIIIPAEBHpMDZeJa+594M3O8UPbUlLh2TR2Sv1ao2sW4ldUj1ycANjFjb569aoUKlRI9u/fLy+99JL8/PPP5kvfohMAV6xYUcLCwszVGSFy5cqVo1zpnTt3zBe4GS+HM44DBw5I9uzZ/3Gu8WlfI4Q2DuMTw0uWLHmk2rhx48w9h43DeGnd+PHjY0RY14de5KVrUurThbbNimROLtPeKm+7nkIEEEAAAQQQQAABBBBAAAEE3C7w4W9bZfL6I7anabw7x3iHjmqHrlmIan1Qcb4EwC7uWqdOnWTYsGHyzDPPyM6dO80tF6ITABsvazP24TXC3YCAADl37pzPF7x16NBBQkJCTImRI0eK8fXDR9euXWXw4MHmtwYNGiTG1486Tp48KenTpzd/nDZtWjG+jolD14feyYvXpPQA+wFwYMZkMuudCjFBzpgIIIAAAggggAACCCCAAAIIuEKg8y9b5PeNf9qey7jWJaVK3rS26/1VqGsW4i9PL12XANil3V65cqVUqFDBDHHHjh0rrVu3NmcanQB4zZo15nYOxmF8Enjp0qU+V2mM37ZtW/McY59fY/uIh486deqY2zkYh/Fp4CpVqvgcL2vWrOYL64wjMjJS0qR58v9VTdeH3vELf0nZgYts35V50wXIvPcq2q6nEAEEEEAAAQQQQAABBBBAAAG3C3T6eZNM23zM9jTHtgqSqvn++V4j24M9xUJds5CnSOjZSxEAu7D1xgvcihYtKrt27TK3XggN/XtP2OgEwBMmTDC3XzCO6GzDYGwRUbVqVfP8f1/P+F7OnDnNrSGMI6otIv5NaGwTsWzZMvPbxjYU5ctb25Igqn2I/32N8PBwMV6OZxxGWF62rB4vPjt6/i8J/sx+AJwzTRJZ1Dnq7T5ceKszJQQQQAABBBBAAAEEEEAAAQQsC7w5caPMCj9uue5+wZj/BEn1AgTAtgEpVE6AANiFLbu/5UKiRInECDqNPXrvH9EJgI1tI4ztI4yjc+fOMmTIEJ+r3Lp1qxQpUsQ8p0SJEuaL5h4+UqZMaW4jYRzG9hJJkyb1OV7jxo1l6tSp5jnGi+vq169vSTlWrFiWztcpAD5y9qpU+HyxpfU/fHK2VIllaRffn9C2PTiFCCCAAAIIIIAAAggggAACCLhAoP0P62XedvtbTo5uUUJqBt7bvlKlg08Aq9Qtd82VANhd/TDDV2P7htu3b8vnn38uXbp0+ccMoxMADxgwQHr06GHWGX/279/f5yr37NkjefLkMc8x/jQ+efzwET9+fLl586b5LePPuHHj+hzvlVdekZ9++sk8x/izWbNmlpS9HAAfOnNFKg1+9Ev2HgeZKUUiWfHRvU9zcyCAAAIIIIAAAggggAACCCCgo0Db8etkYUSk7aWFvFpCahckALYNSKFyAgTALmrZjRs3zE/gbtu2TYoVKybr1q37v5e3WQ2Ae/bsKf369fO5SrcFwF7eAuLA6StSZYj9ADhdsgSypnt1F93VTAUBBBBAAAEEEEAAAQQQQACBJyvQcuxaWbr7lO1BR71SXOoUymC73l+FfALYX/LqX5cA2EU97NWrlxnWxokTR9auXSvFixf/v9lFJwBWfQuI6LRE14fevlOXpdoXvl/a58snVZL4suHjGtEh5BwEEEAAAQQQQAABBBBAAAEElBR4ZcxqWbH3jO25j2heXOoVJgC2DUihcgIEwC5p2ZYtW6RkyZLmFgvGtg/G9g9RHdEJgFV/CVx0WqJrALw38pJU//LeC/TsHMkSxpWtfWrZKaUGAQQQQAABBBBAAAEEEEAAASUEXvxmlaw9cNb2XIc3KyYNimS0Xe+vQl2zEH95eum6BMAu6fZ7770nQ4cOldixY8tHH30kxgvgojoWLVokixffe0lYlSpVpGrVe/u95s2bV5o2bWr+7zVr1pj7CBtHxYoVZelS358oHTt2rLRt29Y8v2PHjjJixIh/XLpOnToyd+5c83vG9Y3r+jqyZs0qR44cMU+JjIyUNGnSPHFlXR96u09ekpr/tR8AJ4kfR7Z/UvuJezMgAggggAACCCCAAAIIIIAAAm4RaDJqpWw4dO9l9XaOr14uKs8VzWSn1K81umYhfkX1yMUJgF3S6HfffVe++uor27N57rnn5I8//jDrL126JClSpJA7d+5IQECAnDt37v/2En74Qh06dJCQkBDzWyNHjhTj64ePrl27yuDBg81vDRo0SIyvH3WcPHlS0qe/t5F62rRpxfg6Jg5dH3oRJy5K7aFhtsnix40tu/vXsV1PIQIIIIAAAggggAACCCCAAAJuF3ju6+Wy5c8Ltqf535eKyPPFMtuu91ehrlmIvzy9dF0CYJd0+0kGwMaSjE/+hoXdCxKXLFkilSpVinKlRkicO3duOXDggPlz48/s2bP/41zjU7/VqlUzv1e5cuUHn0COasBx48ZJmzZtzB+1atVKjK9j4tD1obfj2EWpO8x+ABw7lsj+gfVigpwxEUAAAQQQQAABBBBAAAEEEHCFQN2vwmTH8Yu25/JF0yLSpAQBsG1ACpUTIABWrGXR2QPYWJLxSd4333zTXF2DBg1k+vTpUa50ypQp0qRJE/NnxrYRRrD67+P27duSOXNmOXHihPmjDRs2RPmCOuO8oKAg2bx5s3mesW1ErVoxsx+trgHwtqMXpP7w5Y7uyv0D6kpsIwnmQAABBBBAAAEEEEAAAQQQQEBDgVr/XSa7Tl6yvbLBLxSWpkFZbNf7q1DXLMRfnl66LgGwYt2ObgB87do1c1/gw4cPmyv8+uuvHwTC95e8Z88e85PC94PdBQsWSPXq1aMUGTVqlLk/sHEEBgaaewEbWzw8fBgvrxsyZIj5reDgYFm+3FmQ6as1uj70wv+8IA2+duZmbAFhbAXBgQACCCCAAAIIIIAAAggggICOAlW/WCL7T12xvbTPmxSWF0sSANsGpFA5AQJgxVoW3QDYWFZoaKjUrVtXbt68aa6yfv360rBhQ0mSJIls3LhRxowZIxcu3Nszp127djJ69OhHaty6dcscywiJjcPY59eoKVCggJw9e1YmTZr0IPBNnjy5rFixwgyKY+rQNQDecuS8PDdihSO2nZ/UlkTx4zgag2IEEEAAAQQQQAABBBBAAAEE3CpQafBiOXTmqu3pfda4kLxcKqvten8V6pqF+MvTS9clAFas21YCYGNpU6dONffkPX/+/CNXagS5xid848TxHRoaL5dr3ry5zJw585FjGVtFTJ48WcqVKxejsro+9DYdPifPj1zpyG5rn5qSLGE8R2NQjAACCCCAAAIIIIAAAggggIBbBYI/WyRHz/9le3oDni8kzUsTANsGpFA5AQJgxVpmNQA2lnf8+HEz4J0xY4YcPHhQjO0hMmTIIOXLl5e2bds+8gVxj6KZNm2aTJgwQdatWyeRkZESEBAguXLlksaNG0v79u3F+ARwTB+6BsAbDp2TJqOcBcAbP64hKZPEj+kWMD4CCCCAAAIIIIAAAggggAACfhEo9WmoRF66bvva/RsVlFfLZLNd769CXbMQf3l66boEwF7qtkZr1fWht/7gWXkh5P9fxGeldWt7VJO0AQmtlHAuAggggAACCCCAAAIIIIAAAsoIlOi3QM5cuWF7vv2eC5QWZbPbrvdXoa5ZiL88vXRdAmAvdVujter60Ft74Ky8+I2zAHjlR1UlY4pEGnWbpSCAAAIIIIAAAggggAACCCDwt0DhPvPk4rVbtkn6NgyUluUIgG0DUqicAAGwci1jwoaArgHw6v1n5OXRqx01eVmXKpI1VWJHY1CMAAIIIIAAAggggAACCCCAgFsFAnvNlSs3btueXu8GBaR1cA7b9f4q1DUL8Zenl65LAOylbmu0Vl0feiv3nZbm365x1KlFnStJzjRJHY1BMQIIIIAAAggggAACCCCAAAJuFcjTc47cuHXH9vQ+rl9A2pYnALYNSKFyAgTAyrWMCRsCugbAy/eclle/cxYAz3+vouRJF8CNggACCCCAAAIIIIAAAggggICWAjm7zZI7d+0vrWe9/PJahZz2B/BTpa5ZiJ84PXVZAmBPtVufxer60Fu2+5T8Z+xaR42a9U55CcyY3NEYFCOAAAIIIIAAAggggAACCCDgRoE7d+5Kzu6zHU2te9188nrFXI7G8EexrlmIPyy9dk0CYK91XJP16vrQW7IrUlqNW+eoS9PeDJYiWVI4GoNiBBBAAAEEEEAAAQQQQAABBNwocP3Wbcnbc66jqX1UJ5+8UYkA2BEixUoJEAAr1S4me19A1wB4cUSktB7vLAD+vUNZKZEtJTcLAggggAACCCCAAAIIIIAAAtoJXLl+SwJ7z3O0rq6180rHyrkdjeGPYl2zEH9Yeu2aBMBe67gm69X1obdw50lp+/16R12a/HoZKZ0zlaMxKEYAAQQQQAABBBBAAAEEEEDAjQIX/ropRfrOdzS1D2rmkbeqPutoDH8U65qF+MPSa9ckAPZaxzVZr64PvQU7Tkq7Cc4C4ImvlZbg3Kk16TTLQAABBBBAAAEEEEAAAQQQQOBvgTOXr0uJ/qGOSN6vkUfeqUYA7AiRYqUECICVaheTvS+gawA8b/sJaf/DBkeNHt+6pFTOm9bRGBQjgAACCCCAAAIIIIAAAggg4EaBkxevSekBCx1N7d3qz8q71fM4GsMfxbpmIf6w9No1CYC91nFN1qvrQ2/utuPyxo8bHXVpzH+CpHqBdI7GoBgBBBBAAAEEEEAAAQQQQAABNwr8ee6qlB+02NHUjE//Gp8CVu3QNQtRrQ8qzpcAWMWuMWfR9aE3O/y4dJzoLAAOebW41C6YgbsEAQQQQAABBBBAAAEEEEAAAe0EDp6+IpWHLHG0rrer5pbONfM6GsMfxbpmIf6w9No1CYC91nFN1qvrQ2/m1mPy1k+bHHVpeLNi0qBIRkdjUIwAAggggAACCCCAAAIIIICAGwX2Rl6W6l8udTS1N6vkki618jkawx/FumYh/rD02jUJgL3WcU3Wq+tDb/qWY/LOJGcB8NCXikqjYpk06TTLQAABBBBAAAEEEEAAAQQQQOBvgYgTF6X20DBHJB0q55IPaxMAO0KkWCkBAmCl2sVk7wvoGgBP23xUOv282VGjB79QWJoGZXE0BsUIIIAAAggggAACCCCAAAIIuFFg29ELUn/4ckdTa18pp3Srk9/RGP4o1jUL8Yel165JAOy1jmuyXl0felM3/SnvTd7iqEsDGxeSZqWyOhqDYgQQQAABBBBAAAEEEEAAAQTcKLDp8Dl5fuRKR1N7vWJO6V6XANgRIsVKCRAAK9UuJntfQNcA+PcNf0rnX50FwP2eC5QWZbNzsyCAAAIIIIAAAggggAACCCCgncC6g2elacgqR+t6rXwO6Vm/gKMx/FGsaxbiD0uvXZMA2Gsd12S9uj70fl1/RLr8ttVRl3rVLyBtyudwNAbFCCCAAAIIIIAAAggggAACCLhRYOW+09L82zWOptYmOIf0akAA7AiRYqUECICVaheTvS+gawA8ed1h+fD3cEeN7lE3v7SrmNPRGBQjgAACCCCAAAIIIIAAAggg4EaBsD2npMV3ax1NrVW57NKnYaCjMfxRrGsW4g9Lr12TANhrHddkvbo+9CatPSzdpjgLgLvWzisdK+fWpNMsAwEEEEAAAQQQQAABBBBAAIG/BRZHRErr8esckbQsm036PlfQ0Rj+KNY1C/GHpdeuSQDstY5rsl5dH3oT1xySHlO3OerS+zXyyDvVnnU0BsUIIIAAAggggAACCCCAAAIIuFFg/vYT8voPGxxNrUWZbNKvEQGwI0SKlRIgAFaqXUz2voCuAfAPqw/Jx384C4DfqZpb3q+Zl5sFAQQQQAABBBBAAAEEEEAAAe0EZocfl44TNzpa1yuls8qnzxdyNIY/inXNQvxh6bVrEgB7reOarFfXh96EVQel17TtjrrUoXIu+bB2PkdjUIwAAggggAACCCCAAAIIIICAGwWmbT4qnX7e7GhqzUplkYGNCzsawx/FumYh/rD02jUJgL3WcU3Wq+tDb/yKA9Jnxg5HXWpXIYf0qKfe20wdLZpiBBBAAAEEEEAAAQQQQAABTwj8vuFP6fzrFkdrfSkoiwx6gQDYESLFSgkQACvVLiZ7X0DXAHjs8gPyyUxnAXDr4OzSu4F6bzPl7kYAAQQQQAABBBBAAAEEEEDgcQK/rDsiXX/f+rjTfP68aYnMMrhpEUdj+KNY1yzEH5ZeuyYBsNc6rsl6dX3ojQnbL/1n7XTUJVU3s3e0aIoRQAABBBBAAAEEEEAAAQQ8IfAkXp7epHhm+eJFAmBP3DAs0hQgAOZGUFJA1wD422X75dPZzgJgVfcyUvJGZNIIIIAAAggggAACCCCAAAJPVeD7lQel93Rn785pXCyTfPlS0ac67ydxMV2zkCdhwxi+BQiAuUOUFND1offN0n0ycE6Eo568UCKzDFHwn7I4WjTFCCCA3XF3egAAIABJREFUAAIIIIAAAggggAACnhB4Ev9ytlHRjDL05WLKeemahSjXCAUnTACsYNOYsoiuD71RS/bJoLnOAmBV/yLjvkYAAQQQQAABBBBAAAEEEEDgcQIhS/fJZw4/ONWwSEYZ1owA+HHW/FwfAQJgfXrpqZXoGgCPWLxXBs/b5aiX9QpnkBHNizsag2IEEEAAAQQQQAABBBBAAAEE3Cjw9aI9MmT+bkdTq184g3yt4O/NumYhjppJcbQECICjxcRJbhPQ9aH3JP4iqx2YXkJalHBby5gPAggggAACCCCAAAIIIIAAAo4FhobulqGhexyNU69QBhnxinofnNI1C3HUTIqjJUAAHC0mTnKbgK4PvWEL98iXC5z9l8zq+dPKmJYl3dYy5oMAAggggAACCCCAAAIIIICAY4Eh83bJ14v3OhqnTsH0MupV9T44pWsW4qiZFEdLgAA4Wkyc5DYBXR96T+K/ZFbKk0a+b1PKbS1jPggggAACCCCAAAIIIIAAAgg4Fhg4Z6d8s3S/o3FqBaaTb1oEORrDH8W6ZiH+sPTaNQmAvdZxTdar60Pvy/m7ZNgiZ/8lMzh3Kpn4WhlNOs0yEEAAAQQQQAABBBBAAAEEEPhboN/MHfLd8gOOSGoUSCff/ocA2BEixUoJEAAr1S4me19A1wD4SfxTllI5Usov7ctysyCAAAIIIIAAAggggAACCCCgnUDvadvk+1WHHK1L1a0Tdc1CHDWT4mgJEABHi4mT3Cag60Pv87kRMnLJPkfcxbOmkCkdgx2NQTECCCCAAAIIIIAAAggggAACbhToMTVcJq457GhqVfOllbGt1Ht3jq5ZiKNmUhwtAQLgaDFxktsEdH3ofTYnQkKWOguAi2ROLtPeKu+2ljEfBBBAAAEEEEAAAQQQQAABBBwLfPjbVpm8/oijcSrnTSPjW6v37hxdsxBHzaQ4WgIEwNFi4iS3Cej60Bs4e6d8s8zZZvYFMiST2Z0quK1lzAcBBBBAAAEEEEAAAQQQQAABxwLv/7JZpmw86micinnSyAQFX56uaxbiqJkUR0uAADhaTJzkNgFdH3qfztoh34Y528w+T7qkMv+9Sm5rGfNBAAEEEEAAAQQQQAABBBBAwLHAO5M2yfQtxxyNUz53avnxtdKOxvBHsa5ZiD8svXZNAmCvdVyT9er60HsSbzPNmTqJLPqgsiadZhkIIIAAAggggAACCCCAAAII/C3QceIGmR1+whFJuVyp5Kd2ZRyN4Y9iXbMQf1h67ZoEwF7ruCbr1fWh13fGdhm34qCjLmVJmUjCulZ1NAbFCCCAAAIIIIAAAggggAACCLhRoN2E9bJgx0lHUyuTM6X8/HpZR2P4o1jXLMQfll67JgGw1zquyXp1fej1mb5dxq90FgBnSJ5QVnWrpkmnWQYCCCCAAAIIIIAAAggggAACfwu0Gb9OFkVEOiIplSOl/NKeANgRIsVKCRAAK9UuJntfQNcAuNe0bTJh1SFHjU4TkEDW9ajuaAyKEUAAAQQQQAABBBBAAAEEEHCjQIvv1kjYntOOplYy+zPy6xvlHI3hj2JdsxB/WHrtmgTAXuu4JuvV9aHX849w+XH1YUddeiZxPNnUq6ajMShGAAEEEEAAAQQQQAABBBBAwI0CzUavllX7zziaWolsz8jvHQiAHSFSrJQAAbBS7WKy9wV0DYC7Tw2Xn9Y4C4ADEsSV8L61uFkQQAABBBBAAAEEEEAAAQQQ0E6gachKWXfwnKN1FcuaQqZ2DHY0hj+Kdc1C/GHptWsSAHut45qsV9eHXrcpW2XS2iOOupQwXmyJ6FfH0RgUI4AAAggggAACCCCAAAIIIOBGgUYjVsjmI+cdTa1IlhQy7U0CYEeIFCslQACsVLuY7H0BXQPgD3/bKpPXOwuA48aOJXsH1OVmQQABBBBAAAEEEEAAAQQQQEA7gfrDw2Tb0YuO1lU4c3KZ/lZ5R2P4o1jXLMQfll67JgGw1zquyXp1feh1+XWL/LrhT8ddOjCwrsSKFcvxOAyAAAIIIIAAAggggAACCCCAgJsEag9dJhEnLjmaUsFMyWTm2xUcjeGPYl2zEH9Yeu2aBMBe67gm69X1off+L5tlysajjru099M6EjdObMfjMAACCCCAAAIIIIAAAggggAACbhKo/uVS2Rt52dGUCmRIJrM7EQA7QqRYKQECYKXaxWTvC+gaAL83ebNM3eQ8AI7oV1sSxovDDYMAAggggAACCCCAAAIIIICAVgKVBy+Wg2euOlpTvvQBMvfdio7G8EexrlmIPyy9dk0CYK91XJP16vrQ6/TzJpm2+ZjjLoX3qSkBCeM5HocBEEAAAQQQQAABBBBAAAEEEHCTQPBni+To+b8cTSlvugCZ9x4BsCNEipUSIABWql1M9r6ArgHw25M2yYwtzgPgTR/XkGeSxOeGQQABBBBAAAEEEEAAAQQQQEArgdIDQuXkxeuO1vRs2qSy4P1KjsbwR7GuWYg/LL12TQJgr3Vck/Xq+tB786eNMmvrccddWtujmqQNSOh4HAZAAAEEEEAAAQQQQAABBBBAwE0CJfotkDNXbjiaUq40SWRh58qOxvBHsa5ZiD8svXZNAmCvdVyT9er60Os4cYPMDj/huEsrP6oqGVMkcjwOAyCAAAIIIIAAAggggAACCCDgJoEifefLhb9uOppSjtRJZPEHBMCOEClWSoAAWKl2Mdn7AroGwG/8sEHmbnceAId1rSJZUibmhkEAAQQQQAABBBBAAAEEEEBAK4HAXnPlyo3bjtaULVViWdqliqMx/FGsaxbiD0uvXZMA2Gsd12S9uj70Xp+wXubvOOm4S4s6V5KcaZI6HocBEEAAAQQQQAABBBBAAAEEEHCTQJ6ec+TGrTuOppQlZSIJ61rV0Rj+KNY1C/GHpdeuSQDstY5rsl5dH3qvfb9eQnc6D4Dnv1dR8qQL0KTbLAMBBBBAAAEEEEAAAQQQQACBewI5u82SO3edaWRKkUhWfEQA7EyRapUECIBV6hZzfSCgawDcdvw6WRgR6bjTs94pL4EZkzsehwEQQAABBBBAAAEEEEAAAQQQcIvAnTt3JWf32Y6nkzF5QlnZrZrjcZ72ALpmIU/b0YvXIwD2Ytc1WLOuD73W49bK4l2nHHdo2pvBUiRLCsfjMAACCCCAAAIIIIAAAggggAACbhG4fuu25O051/F00idLKKu7EwA7hmQAZQQIgJVpFRN9WEDXALjl2LWydLfzAPj3DmWlRLaU3DQIIIAAAggggAACCCCAAAIIaCNw9cYtKdBrnuP1pA1IIGt7VHc8ztMeQNcs5Gk7evF6BMBe7LoGa9b1odfiuzUStue04w5Nfr2MlM6ZyvE4DIAAAggggAACCCCAAAIIIICAWwQu/HVTivSd73g6qZMmkPU9CYAdQzKAMgIEwMq0iok+LKBrAPzqmDWyfK/zAHjia6UlOHdqbhoEEEAAAQQQQAABBBBAAAEEtBE4c/m6lOgf6ng9qZLElw0f13A8ztMeQNcs5Gk7evF6BMBe7LoGa9b1odf829Wyct8Zxx0a37qkVM6b1vE4DIAAAggggAACCCCAAAIIIICAWwROXrwmpQcsdDydZxLHk029ajoe52kPoGsW8rQdvXg9AmAvdl2DNev60Ht59CpZvf+s4w6N+U+QVC+QzvE4DIAAAggggAACCCCAAAIIIICAWwT+PHdVyg9a7Hg6yRPFky29CYAdQzKAMgIEwMq0iok+LKBrAPxiyCpZe9B5ABzyanGpXTADNw0CCCCAAAIIIIAAAggggAAC2ggcOnNFKg1e4ng9AQnjSnifWo7HedoD6JqFPG1HL16PANiLXddgzbo+9F4YtVLWHzrnuEPDmxWTBkUyOh6HARBAAAEEEEAAAQQQQAABBBBwi8DeyMtS/culjqeTNEFc2daXANgxJAMoI0AArEyrmOjDAroGwI1HrpCNh887bvbQl4pKo2KZHI/DAAgggAACCCCAAAIIIIAAAgi4RSDixEWpPTTM8XQSx48jOz6p7Xicpz2ArlnI03b04vUIgL3YdQ3WrOtDr9GIFbL5iPMAePALhaVpUBYNOs0SEEAAAQQQQAABBBBAAAEEELgnsO3oBak/fLljjoTxYktEvzqOx3naA+iahTxtRy9ejwDYi13XYM26PvSe+3q5bPnzguMODWxcSJqVyup4HAZAAAEEEEAAAQQQQAABBBBAwC0Cmw6fk+dHrnQ8nfhxY8vu/gTAjiEZQBkBAmBlWsVEHxbQNQBuMHy5hB91HgD3ey5QWpTNzk2DAAIIIIAAAggggAACCCCAgDYC6w6elaYhqxyvJ27sWLJ3QF3H4zztAXTNQp62oxevRwDsxa5rsGZdH3r1hoXJ9mMXHXeoV/0C0qZ8DsfjMAACCCCAAAIIIIAAAggggAACbhFYte+MNPt2tePpxI4lsn9gPcfjPO0BdM1CnrajF69HAOzFrmuwZl0fenW+CpOdx50HwN3r5pPXK+bSoNMsAQEEEEAAAQQQQAABBBBAAIF7AmF7TkmL79Y+EY6DnxEAPxFIBlFCgABYiTYxyX8L6BoA1x66TCJOXHLc8K6180rHyrkdj8MACCCAAAIIIIAAAggggAACCLhFYHFEpLQev+6JTOfAwLoSK1asJzLW0xpE1yzkafl5+ToEwF7uvsJr1/WhV/O/S2X3ycuOO/N+jTzyTrVnHY/DAAgggAACCCCAAAIIIIAAAgi4RWD+9hPy+g8bnsh09g2oK3GMvSAUOnTNQhRqgbJTJQBWtnXenriuD73qXy6VvZG+A2DjP1Deveu7/+9UzS3v18zr7ZuE1SOAAAIIIIAAAggggAACCGglMDv8uHScuNHnmqLzO7MxwJ5P60i8OLGV8tE1C1GqCYpOlgBY0cZ5fdq6PvSqfrFE9p+64rO9CeLGluu37vg8p0PlXPJh7Xxev01YPwIIIIAAAggggAACCCCAgEYC0zYflU4/b3b8O7MxwK7+tSVB3DhK6eiahSjVBEUnSwCsaOO8Pm1dH3pVhiyRA6d9B8ABCePKpWu3fN4C7SrkkB71Cnj9NmH9CCCAAAIIIIAAAggggAACGglM2finvP/LFp8ris7vzMYAEf1qS8J4BMAa3R4sxYcAATC3h5ICugbAlQYvlkNnrvrsSeqk8eX05Rs+z2lVLrv0aRioZG+ZNAIIIIAAAggggAACCCCAAAJRCfyy7oh0/X2r49+ZjQF2fFJLEsePqxS0rlmIUk1QdLIEwIo2zuvT1vWhV+HzRXLk7F8+25sxeUI5duGaz3NalMkm/RoV9PptwvoRQAABBBBAAAEEEEAAAQQ0Epi45pD0mLrN8e/MxgDb+taSpAkIgDW6PViKDwECYG4PJQV0DYCDP1skR8/7DoCzpUr82E8JNyuVRQY2Lqxkb5k0AggggAACCCCAAAIIIIAAAlEJfL/yoPSevt0nTvZUieXgY/5lrTHA1j41JVnCeEpB65qFKNUERSdLAKxo47w+bV0femUHLpTjj/l077Npk8qeyMs+b4EXSmSWIU2LeP02Yf0IIIAAAggggAACCCCAAAIaCYwJ2y/9Z+30uaI86ZLK7pO+f2c2BtjSq6YkT0wArNHtwVJ8CBAAc3soKaBrAFx6QKicvHjdZ08CMyaT7ccu+jynUdGMMvTlYkr2lkkjgAACCCCAAAIIIIAAAgggEJVAyNJ98tmcCJ84BTMlk21Hff/ObAyw6eMa8kyS+EpB65qFKNUERSdLAKxo47w+bV0feiU/DZVTl3wHwMWyppBNh8/7vAXqFc4gI5oX9/ptwvoRQAABBBBAAAEEEEAAAQQ0EhixeK8MnrfL54qKZ00hGx/zO7MxwIae1SVV0gRK6eiahSjVBEUnSwCsaOO8Pm1dH3pB/RfI6cs3fLa3dI6UsubAWZ/n1A5MLyEtSnj9NmH9CCCAAAIIIIAAAggggAACGgkMDd0tQ0P3OP6d2RhgXY/qkiaAAFij24Ol+BAgAOb2UFJA1wC4eL8FcvaK7wC4wrOpJWzPaZ99q54/rYxpWVLJ3jJpBBBAAAEEEEAAAQQQQAABBKISGDJvl3y9eK9PnOj8zmwMsKZ7NUmXLKFS0LpmIUo1QdHJEgAr2jivT1vXh17RT+bL+as3Hxvuhu6M9HlOpTxp5Ps2pbx+m7B+BBBAAAEEEEAAAQQQQAABjQQGztkp3yzd7/h3ZmOAVd2qSobkiZTS0TULUaoJik6WAFjRxnl92ro+9Ar3mScXr93y2d66hdLL7PATPs8Jzp1KJr5Wxuu3CetHAAEEEEAAAQQQQAABBBDQSKDfzB3y3fIDjn9nNgZY8VFVyZSCAFij24Ol+BAgAOb2UFJA1wC4UO95cum67wC4UdGM8sfmYz77VipHSvmlfVkle8ukEUAAAQQQQAABBBBAAAEEEIhKoM/07TJ+5UGfONH5ndkYIKxrFcmSMrFS0LpmIUo1QdHJEgAr2jivT1vXh15gr7ly5cZtn+19MSiz/LL+T5/nGG89ndIx2Ou3CetHAAEEEEAAAQQQQAABBBDQSKDH1HCZuOaw49+ZjQGWdakiWVMRAGt0e7AUHwIEwNweSgroGgDn/3iu/HXTdwD8apms8uNq33/hFcmcXKa9VV7J3jJpBBBAAAEEEEAAAQQQQAABBKIS+PC3rTJ5/RGfOK+UzvrYkNgYYMkHlSV76iRKQeuahSjVBEUnSwCsaOO8Pm1dH3p5e86R67fu+Gxvm+AcMnaF7z2PCmRIJrM7VfD6bcL6EUAAAQQQQAABBBBAAAEENBJ4/5fNMmXjUZ8rah2cXcat8L1NhDHAos6VJGeapErp6JqFKNUERSdLAKxo47w+bV0fenl6zJEbt30HwO0r5XzsW0/zpEsq89+r5PXbhPUjgAACCCCAAAIIIIAAAghoJPDOpE0yfYvvd+JE53dmgyT0/UqSOy0BsEa3B0vxIUAAzO2hpICuAXDu7rPl1p27PnvyTtXcMmzRXp/n5EydRBZ9UFnJ3jJpBBBAAAEEEEAAAQQQQAABBKIS6Dhxg8wOP+H4d2ZjgAXvVZRn0wUoBa1rFqJUExSdLAGwoo3z+rR1fejl7DZLHpP/ygc188iQ+bt93gJZUiaSsK5VvX6bsH4EEEAAAQQQQAABBBBAAAGNBF6fsF7m7zjpc0Wda+SRLxb4/p3ZGGDeuxUlb3oCYI1uD5biQ4AAmNtDSQEdA+C7d+9Kjm6zH9uP7nXzyYDZET7Py5A8oazqVu2xY3ECAggggAACCCCAAAIIIIAAAqoItBm/ThZFRPqc7oe188mQ+bvk9mM+XTWnUwXJnyGZKks356ljFqJUAxSeLAGwws3z8tR1fOjduXNXcnZ/fADcp0EB6TNjh8/2pwlIIOt6VPfyLcLaEUAAAQQQQAABBBBAAAEENBNo8d0aCdtz2ueqetTNL5/Pi5Cbt31vrzjrnfISmDG5UkI6ZiFKNUDhyRIAK9w8L09dx4ferdt3JHePOY9t64DnC0n3qeE+z3smcTzZ1KvmY8fiBAQQQAABBBBAAAEEEEAAAQRUEWg2erWs2n/G53R7NyggA+dEyI1bvl+wPvPt8lIwEwGwKr1nns4ECICd+T3R6nXr1snatWvF+HP79u1y6tQpOX36tNy8eVNSpEgh+fPnl6pVq0qrVq0ka9as0br28ePHJSQkRGbMmCEHDx6Ua9euSfr06aVChQrSpk0bqVSpUrTGuX/StGnT5IcffjDnePLkSUmWLJnkypVLnn/+eWnfvr0kT/50Hp46BsDGX055ej4+AB78QmHp8ttWn30LSBBXwvvWstRbTkYAAQQQQAABBBBAAAEEEEDAzQJNQ1bKuoPnfE6xX6OC8umsHXLtpu8AePpbwVI4cwo3L/f/5qZjFqJUAxSeLAGwi5qXNGlSuXLlymNnlCBBAundu7d069bN57lTp041Q97z588/8rx27drJqFGjJE6cOD7HunTpkjRv3lxmzpz5yPMyZ84skydPlnLlyj12DU5P0PGhd+3mbcn38dzH0nz1clHp9PNmn+cljBdbIvrVeexYnIAAAggggAACCCCAAAIIIICAKgKNRqyQzUcenXEY6/iscSH5ZOYOuXrjts9l/fFmsBTNQgCsSu+ZpzMBAmBnfk+02giAkyRJIqVKlZLAwEDzk7rG/xkvBzM+vTtr1ixZsWLFg2v27dtXevXqFeUcQkNDpW7duuanh42jXr160rBhQ3P8jRs3ypgxY+TixYvmz4wQePTo0Y9cy61bt8yxFixYYJ6TLl06s6ZAgQJy9uxZmTRp0oN5GZ9UXr58uTn/mDx0DID/unFb8vd6fAAc8moJeePHDT5548aOJXsH1I3JFjA2AggggAACCCCAAAIIIIAAAk9VoMHw5RJ+9ILPaw5pWkT6TN8ul6/f8nnelI7lpHjWZ57q/J1eTMcsxKkJ9dETIACOntNTOWvbtm1mcBorVqxHXm/ChAnmFhBGKBw3blw5dOiQZMyY8R/nG9s85M2bVw4fPmx+f/jw4fLWW2/945zdu3eb2z+cOHHC/P78+fOlRo0aUV7X+IRwx44dzZ8Zoe+iRYvMEPjh44MPPpAvvvjC/FZwcLAZAsfkoeND78r1WxLYe95j2ca1Kimtx6977HkHBtb1eS89dgBOQAABBBBAAAEEEEAAAQQQQMBFArWHLpOIE5d8zsj4V7M9/9gml675DoB/e6OsBGVP6aLVPX4qOmYhj181ZzwJAQLgJ6H4lMcwPslr7OlrHN999525zcPDx4gRIx4Evg0aNJDp06dHOcMpU6ZIkyZNzJ+VKVNGjAfJv4/bt2+LsbXD/aB4w4YNUrx48SjPCwoKks2b721NMHfuXKlVK+b2oNXxoXfp2k0p1Gf+Y++mia+VllfGrHnseXs/rSNx48R+7HmcgAACCCCAAAIIIIAAAggggIAKAtW/XCp7Iy/7nOrXzYtJj6nb5MJf9/5F9KOOX9qXlVI5CIBV6DtzdC5AAOzc8KmPYOz9+9lnn5nXHTBgwP/tBVyxYkUJCwszf7548WKpXLlylHO8c+eO+QI3Y3sJ4zhw4IBkz579H+can/atVq2a+T3jE8NLlix55HrHjRv3IIxu2bKljB8/PsZsdAyAjb+civR9fAD86xtlpWnI/4f1/8aO6FdbEsbzvbdzjDWIgRFAAAEEEEAAAQQQQAABBBB4wgKVBy+Wg2eu+hzV2Dax25Stcu6q7wD459fLSJmcqZ7wDGN2OB2zkJgVY/T7AgTACt4LTZs2ld9++82c+dixY6V169YPVmG8rM3Yh9cIdwMCAuTcuXM+X/DWoUMHCQkJMetHjhwpxtcPH127dpXBgweb3xo0aJAYXz/qOHnypLlnsXGkTZtWjK9j6tDxoXf+6g0p+sm9fZZ9HcZG9cbG9487wvvUlICE8R53Gj9HAAEEEEAAAQQQQAABBBBAQAmB4M8WydHzf/mc63ctg6Trb1vlzJUbPs/7qV1pKZcrtRLrvj9JHbMQpRqg8GQJgBVr3h9//GFu22AEvIkSJTI/vWuErfePNWvWmNs5GIfxSeClS5f6XKERILdt29Y8x9jn19g+4uGjTp065nYOxmF8GrhKlSo+x8uaNascOXLEPCcyMlLSpEkTI8I6PvTOXrkhxfs9PgCe/U4FqTvs3ie8fR2bPq4hzySJ/7jT+DkCCCCAAAIIIIAAAggggAACSgiUHhAqJy9e9znX79uUks6/bJHTl32fZ2yvGJybAFiJxjNJxwIEwI4JY2aAZcuWydmzZ83Bb9y4YYaq8+bNkwUL7gWE8eLFMz/9++qrr/5jAsZL4oztF4wjOtswGFtEVK1a1Tzf2OohNDT0H+PlzJnT3BrCOKLaIuLfqze2iTDmbhzGNhTly5e3DBTVXsT/HiQ8PFzat29vfnvlypVStmxZy9dxW4Hxl1NQ/3/6RzXH0PcribHv0eOOtT2qSdqAhI87jZ8jgAACCCCAAAIIIIAAAgj8j707j6/h6v8A/ol9i33fBUFCgkSEhARBEkutVVqtXS2lVdXaaZCqpVpLQ2Mtil9R+xaxJYJEEmIJQWINse87v9dMnqpbcuamhDtnPvNPH8l35p7z/p5n7iuf3JyhgC4EnMdswZU7Gp/s7VYTXy6NRtJtcQD8e1cX1CmfNh9aSytMGT8Ml1ZWvK6pAANgC10Ryqd4lU/z/vuwsrJSP4X7/fffw83N7ZXv//LLL+jfv7/69a+//hoTJ04UzvDgwYNwdHRUa5ycnBAREWFSnzdvXnUbCeVQtpfIkSOH8HqtWrXCypUr1RrlQXVNmzZNtbAyx9QcsgTASbcfwGXsVs2p7xpUD3V+3KZZt/u7+iiaO6tmHQsoQAEKUIACFKAABShAAQpQgAJ6EFCem6P1cLelPVzRf0k0Lt56IJyS8klhD1sGwHroO8f45gIMgN/cME2ukFIAXKJECfWTr506dUKxYsVeeW3loXBDhw5Vv678d8yYMcLxxcXFwdbWVq1R/nvs2DGT+kyZMuHx4+SN05X/ZsiQQXi9jz/+GIsXL1ZrlP+2b98+1T5GDYAv3XqAmuO0A+C9QxqYVacExSXyZku1P0+gAAUoQAEKUIACFKAABShAAQpYooD9iI24++ipcGjLe9XGF4sjceGmOACe27kG6lX4Z0tNS5zvv8fETwDroUuWOUYGwJbZF5NR3b17F0pQu2rVKkyaNEn9JK7yyVwlYG3cuLFJ7csB8LBhw+Dn5yecoSUGwEbdAiLx5n3U8g/WXJHK3r7VzNgrOPhrD9gUEH9iW/PFWEABClCAAhSgAAUoQAEKUIACFLAQAdthG/DoyTPhaFb3dUOvhZGaD4ub08kZ9SsWspCZmTcMBsDmObHqVQEGwDpbFSdPnkSdOnWQmJgI5dO5+/bte7GFgzIVGbaAMKclMt70zl2/B/fx2ls7HBrdGJVHbtJk2vxVXdgWstasYwEFKEDAzNYbAAAgAElEQVQBClCAAhSgAAUoQAEKUEAPAjaD1+HZc/FIlQenf75wP85cuycsDPzUGV52DID10HeO8c0FGAC/ueE7v8L8+fPVLSCU48MPP8TSpUtfjEGGh8CZAypjAHz22j2z9vY9+r03Ko/ahKca73rr+rnDvmguczhZQwEKUIACFKAABShAAQpQgAIUsGiBZ8+ew2bIes0xbvmqLroviEDCVXEAPKujExrZF9a8niUVyJiFWJKvzGNhAKzD7l65cgUFCiRvVF6wYEFcunTpxSyUB8cp+wcrR926dbFjxw7hDOfMmYOuXbuqNb1798b06dNN6n18fLBx40b1a8HBweoD6ERHyZIlcfbsWbUkKSnpxTjfNrOMN73TV+/CY8J2TapYP28oG98/1Pizl1V93OBYIrfm9VhAAQpQgAIUoAAFKEABClCAAhSwdAFl6wdlCwitY9tAT3SdF45TV+4KSwM+cYJ3ZQbAWp78vhwCDIB12MeHDx8iS5Ys6siVbSCUf/99KPsD586dG8+ePYO1tTWuX7+O9OnTpzjLXr16ISAgQP3+jBkzoPz75WPQoEGYMGGC+qXx48dD+XdKhxJEFy6cfPP8dzD9tpllDIDjr9xFvYnaAfDxMT6o7rcFdx4+EbIu71ULTqXyvm16Xo8CFKAABShAAQpQgAIUoAAFKPDOBe49egK7EdrbISoPRO80dx9OXhYHwL9+XB0+VYq883m8yQvKmIW8iQfPNV+AAbD5VhZTeejQIVSpUkUdT7FixXDu3DmTsSmf/N21a5f6te3bt8PDw+O1Y1dC4nLlyiE+Pl79vvLf0qVLm9Qqn/pt0KCB+jVPT09s25byHrVz585Fly5d1Fpliwrl32l1yHjTO3n5DhpMEn9iW/E8MdYHzmODcOPeYyHv0h6uqGmTL61awOtSgAIUoAAFKEABClCAAhSgAAXemcDN+4/Vv4bVOsIG18ens/chLumOsHR6h+po4sAAWMuT35dDgAGwDvvYt2/fF1s1/HsPYGU6yid5+/Tpo86sWbNmWL169WtnuWLFCrRu3Vr9nrJthBKq/vt4+vQpihcvjosXL6rf2r9/P6pXr/7aOmdnZ0RHR6vfU7aNaNy4cZrpyhgAn0i6Da/JOzXNTo3zhcu4IFy580hYu6hbTbiVy695PRZQgAIUoAAFKEABClCAAhSgAAUsXeDqnYdwGhOkOczwoV74JHAvjl26Layd2r4amjkW1byeJRXImIVYkq/MY2EAbCHdVbZhqFChgvopWysrq9eOSgljle0YhgwZgufPkx97+bpP+D548EC91pkzZ9SaadOmvQiE/75wXFycukfw38Huli1b4OXl9drX/fXXX9X9gZXD3t5e3QtY2eLh5eObb77BxIkT1S+5ubkhJCQkTWVlvOkdv3QbjX7SDoDj/X1Ryz8YF289EBrP61wDnhVM+5SmTeHFKUABClCAAhSgAAUoQAEKUIACaSRw6dYD1By3VfPq0SMa4qNZexB7URwA//xRVXxQtZjm9SypQMYsxJJ8ZR4LA2AL6a6yZcL8+fNRokQJNGzYUN3iQQlZlT1+b9y4AWXbh1WrViEhIeHFiAcPHoxx48a9dgZBQUHw9fXF48fJ2wQ0bdoUzZs3R/bs2REZGYnAwEDcvHlT/V737t0xa9asFCWePHmiXksJiZVD2edXOcfOzg7Xrl3DH3/88SLwzZUrF0JDQ9WgOC0PGW96sRdvwXtK8tYdKR3prIBT/k3gPj4Y567fF9YGfuoML7tCadkGXpsCFKAABShAAQpQgAIUoAAFKPBOBM7fuA+3H4I1X+vQ6Mb4MCAMRxJvCWt/aueIltWKa17PkgpkzEIsyVfmsTAAtpDu/h0AmzMcJWT19/d/5YFt/z535cqV6p68SoCc0qEEuconfEUPilPOVR4u16FDB6xduzbFaylbRSxduhS1a9c2ZxpvVCPjTe/IhVvw/UUcAGdIZ4UT43zVh8UpD40THQGfVId3ZX3tZ/RGi4InU4ACFKAABShAAQpQgAIUoIC0Aqev3oXHBO0Hp8f6eaNNwG4cOi8OgCe1dURrJwbA0i4YTsxEgAGwhSyIO3fuqJ+c3bFjB/bs2YMLFy4gKSlJDV6VT+0WKlQIDg4O6r66bdu2hRICm3MkJiaqAe+aNWvUTw8r20MUKVIE7u7u6Nq1a4oPiEvp2sqnkBcsWIDw8HB1fNbW1ihbtixatWqFnj17mj0uc8YuqpExAD50/iaaThVvnZEpfTocH+uDhpN3aG5or8f9jN50XfB8ClCAAhSgAAUoQAEKUIACFJBT4ETSHXhNNu/B6a1+3Y2D55L/6jmlY0IbB7R1LqErLBmzEF01QMeDZQCs4+YZeegy3vRizt1Es2niADhzhnQ4NsYHPj/vwlGNP2eZ0q4qWlTT135GRl7TnDsFKEABClCAAhSgAAUoQAEKpCxgzraJytnKc3NazNiNA2dT/mtope7H1g74sAYDYK45YwgwADZGn6WbpYwBsPLm9MH0UGGvsmZMj6N+3mg2NQQx5+X7baZ0C5UTogAFKEABClCAAhSgAAUoQIG3ImDOX81mTG+FuLG+aDkjFFFnxAHwD62q4COXkm9lbO/qIjJmIe/KzuivwwDY6CtAp/OX8aYXdeY6Ws7YLexI9kzpcfh7b7PezPxbVUF7nb2Z6XQ5ctgUoAAFKEABClCAAhSgAAUokMYC5vzM/PeHplr/uhv7T18XjmhcyyroUJMBcBq3jZe3EAEGwBbSCA4jdQIyBsDKm5PyJiU6rDNnQMz/nmi6L+GasNbvA3t0rFU6dbCspgAFKEABClCAAhSgAAUoQAEKWKBARMI1tAkIE//MnCUDYkY1RtuA3QhPEAfAY1pUxieupSxwpikPScYsRFcN0PFgGQDruHlGHrqMNz1z3sxyZsmAg6Mao8Nve7D75FXhEhjR1A5d3MsYeZlw7hSgAAUoQAEKUIACFKAABSggiUDYyato/9se4WzyZMuIqBGN8OHMMOyLl+9DUzJmIZIsT4ufBgNgi28RB/g6ARlventPXUW7WeI3s9zZMiJ6RCN8Omcfdh6/LFwcQ3wrokfdslxAFKAABShAAQpQgAIUoAAFKEAB3QvsiruMjrP3CedRwDozwod6of2sPQg7Jf7Q1Ojm9vistr7+albGLET3C1MnE2AArJNGcZimAjLe9Mz5bWbe7JkQObwhus4Lx9bYJOGyGORdAb09y3HpUIACFKAABShAAQpQgAIUoAAFdC+wLTYJneeFC+dRNFcW7B7cAB8H7kHoCXEAPLKZHTq76euvZmXMQnS/MHUyAQbAOmkUhyl/ALz7xBV0CNwrbHX+HJkQMawheiyIwOYjl4S1Axraol+D8lw6FKAABShAAQpQgAIUoAAFKEAB3QtsPnwRPX7fL5xHybzZsHNQPXScvRe74q4Ia4c3tUNXnW2byABY98v4vU2AAfB7o+cLv4mAjDe9kLgr+GS2OAD++89Z+iyKxLqYRCFhv/rlMKBRhTdh5rkUoAAFKEABClCAAhSgAAUoQAGLEFgfk4jeiyKFY7EpkB3BX3uatW3isCaV0K2OjUXMzdxByJiFmDt31r2ZAAPgN/Pj2e9JQMabnrKnr7K3r+golDMz9g7xQv8lUVgVfUFY28uzLL71rvieOsSXpQAFKEABClCAAhSgAAUoQAEKvD2B1QcuoN8fUcILVihkjU1f1UWnufuw/Zh8z82RMQt5eyuEVxIJMADm+tClgIw3ve3HktBprng/oyK5siBscAN8vewAlkeeE/aue50yGNrETpf95aApQAEKUIACFKAABShAAQpQgAIvC6yIPIcByw4IUeyK5MT6/nXQZV44gjWem/OdT0V87qGvB6fLmIVwlb8bAQbA78aZr/KWBWS86ZmzoX2x3FkR+l19fLf8IJaEnxWqdqpdGqOa279leV6OAhSgAAUoQAEKUIACFKAABSjw7gWWhZ/FoOUHhS/sWDwXVvV1R7f54Qg6Kt+D02XMQt79SjLmKzIANmbfdT9rGW96W49eQtf5EcLelMibFbsG1cewv2KwcM8ZYW1H11Lwa1FZ973mBChAAQpQgAIUoAAFKEABClCAAov2nsbQlYeEEE6l8mB5r9roviACWzQenD6wkS361tfXg9NlzEK4st+NAAPgd+PMV3nLAjLe9JQ3J+VNSnSUypcNO76ph1GrD2Pe7gRhbXuXEvBv5fCW5Xk5ClCAAhSgAAUoQAEKUIACFKDAuxeYvzsBI1cfFr5wzTJ5sbRnLfT8PQKbDl8S1g5oaIt+DRgAv/tO8hXfhwAD4Pehztd8YwEZA+BNhy+i5+/7hTZl8mfHtoGeGLP2CAJD4oW1bZyKY2Jbxze25gUoQAEKUIACFKAABShAAQpQgALvWyBw1ymMWXdUOAz3cvmxsFtN9Fq4HxsOXRTWfulVHl962b7vaaXq9WXMQlIFwOL/LMAA+D/T8cT3KSDjTW/joUR8vjBSyGpTIDuCv/bEDxtiEbDjpLC2RdWimPJRtffZJr42BShAAQpQgAIUoAAFKEABClDgrQjM3HES/htihdfyrFAA8zq7oM+iSKyLSRTWKp/+VT4FrKdDxixET/56HisDYD13z8Bjl/Gmtz4mEb0XiQPgcgVzIGiAByZtPoapwSeEK6CJQxFM71DdwKuEU6cABShAAQpQgAIUoAAFKEABWQSmbzuBCZuOCafjVakgAj+rgb6LI7H2oDgA/qJ+OXzdqIKueGTMQnTVAB0PlgGwjptn5KHLeNNbe/AC+i6OErbVtlAObP7KAz8HxeGnoOPC2sb2hTCzo7ORlwnnTgEKUIACFKAABShAAQpQgAKSCEwJOo4pQXHC2XjbF0ZARyf0+yMKqw9cENb2qVcW3zSuqCsdGbMQXTVAx4NlAKzj5hl56DLe9JQ3J+VNSnRULGyNjV/WRWp+82nkdcK5U4ACFKAABShAAQpQgAIUoIAcAhM3HcO0beK/hG3qUATTOlTHl0ui8Fe0OADu5VkW33ozAJZjdXAWWgIMgLWE+H2LFJAxAF4VfR79l0QLvSsVyYkN/evAnL2PPGwLYH4XF4vsHwdFAQpQgAIUoAAFKEABClCAAhRIjYD/hqOYueOU8JSW1Yrhp3ZVMWBpNFZEnRfW9vSwwWCfSqkZwnuvlTELee+oBhkAA2CDNFq2acp401sZdQ5fLT0gbJV90ZxY168OZofEw2/tEWGtW7l8WNTNVbbWcz4UoAAFKEABClCAAhSgAAUoYECBMWuPIDAkXjjztk7FMaGtIwb+3wH8uf+csLZHXRsM8WUAbMClZMgpMwA2ZNv1P2kZA2DlzUl5kxIdVYrlwpov3LEgLAEjVh0W1rqUyYtlPWvpv9mcAQUoQAEKUIACFKAABShAAQoYXmDU6sOYtztB6NDepST8W1XBoD8PYFmEOADu5l4Gw5ra6cpVxixEVw3Q8WAZAOu4eUYeuow3vWURZzHoz4PCtjoWz4VVfd2xeO8ZDFkZI6ytXjI3VvR2M/Iy4dwpQAEKUIACFKAABShAAQpQQBKBoStjsGjvGeFsOrqWgl+Lyvhu+UEsCT8rrO3iVgYjmjEAlmR5cBoaAgyAuUR0KSBjALw0/Ay+XS4OdauWyI2/+rjBnLDYoXgurO7rrsv+ctAUoAAFKEABClCAAhSgAAUoQIGXBb798yCWRohD3c5upTGymT0Gr4jBH/vEYXGn2qUxqrm9rpBlzEJ01QAdD5YBsI6bZ+Shy3jTU96clDcp0fH3p3rN2S/YrkhOrO9fx8jLhHOnAAUoQAEKUIACFKAABShAAUkEBiyLxopI8YPd/t7X15xPC39WqxRGf1BZVzoyZiG6aoCOB8sAWMfNM/LQZbzpLdp7GkNXHhK21blUHvzZqzZWH7iAfn9ECWttC+XA5q88jLxMOHcKUIACFKAABShAAQpQgAIUkERA+RlY+VlYdPT2LItB3hUx/K9D+H3PaWHt39tF6IlHxixET/56HisDYD13z8Bjl/Gmp7w5KW9SosOldF4s+7wWNsQkoteiSGGtTf7sCB7oaeBVwqlTgAIUoAAFKEABClCAAhSggCwCfRZFYl1MonA6/RqUx4CGthi56hDmh4kD4I9rlsTYllV0xSNjFqKrBuh4sAyAddw8Iw9dxpvegrAEjFh1WNhWV5u8WNKjFrYcuYTuCyKEtSXyZsWuQfWNvEw4dwpQgAIUoAAFKEABClCAAhSQRKDHgghsPnJJOBsl/FVC4FGrD2Pe7gRhbXuXEvBv5aArHRmzEF01QMeDZQCs4+YZeegy3vTmhcZj1JojwrbWLpsPi7u7YtuxJHSeGy6sLZIrC8IGNzDyMuHcKUABClCAAhSgAAUoQAEKUEASgS7zwhEcmySczSDvCujtWQ7frzmCOaHxwtp2ziUwvg0DYEmWB6ehIcAAmEtElwIyBsBzQuLx/VpxAOxeLj8WdquJkLgr+GT2XmHvClhnRvhQL132l4OmAAUoQAEKUIACFKAABShAAQq8LNBx9l7sirsiRBnqWwnd69pgzNojCAwRB8BtnYpjQltHXSHLmIXoqgE6HiwDYB03z8hDl/GmF7jrFMasOypsa53y+fF715rYc+oqPpq1R1ibJ1tGRI1oZORlwrlTgAIUoAAFKEABClCAAhSggCQC7WftQdipq8LZjGxmh85uZTBu/VHM2nlKWNu6enFM+pABsCTLg9PQEGAAzCWiSwEZA+Dfdp7C2PXiANjDtgDmd3FBRMI1tAkIE/bOOnMGxIxurMv+ctAUoAAFKEABClCAAhSgAAUoQIGXBdoG7EZ4wnUhil+LyujoWgr+G45i5g5xANyqWjFMbldVV8gyZiG6aoCOB8sAWMfNM/LQZbzpzdxxEv4bYoVtrVehAOZ2dkH02RtoMT1UWJslYzrE+vkYeZlw7hSgAAUoQAEKUIACFKAABSggiUDLGaGIOnNDOJsfWlXBRy4lMX5jLH7dflJY26JqUUz5qJqudGTMQnTVAB0PlgGwjptn5KHLeNNT3pyUNynR0aBiQczuVAOHzt9E06khwtoM6axwYpyvkZcJ504BClCAAhSgAAUoQAEKUIACkgg0mxqCmPM3hbOZ0MYBbZ1LYMKmWEzfJg6AmzsWxS/tGQBLsjw4DQ0BBsBcIroUkDEAnr7tBCZsOibsh1elQgj8zBnHLt5G4yk7NXsX7+8LKysrzToWUIACFKAABShAAQpQgAIUoAAFLFnAe8pOxF68LRzilHZV0aJaMUzafAxTg08Ia5s6FMG0DtUtecqvjE3GLERXDdDxYBkA67h5Rh66jDe9acFxmLj5uLCtjewKYdanzjh5+Q4aTNqhuQROjPVBhvTpNOtYQAEKUIACFKAABShAAQpQgAIUsGQBr8k7cCLpjnCI0zpUQ1OHovhpy3H8vDVOWNukShFM/5gBsCX3nGN7ewIMgN+eJa/0DgVkDIB/DorDT0HiANjbvjACOjrhzNV7qDthm6Z4rJ83smRMr1nHAgpQgAIUoAAFKEABClCAAhSggCULeE7YhoSr94RDDPjECd6VC8Ocn699KhfGr584WfKUXxmbjFmIrhqg48EyANZx84w8dBlveub8htK3SmHM+NgJ52/ch9sPwZpLIGZUI1hnyahZxwIKUIACFKAABShAAQpQgAIUoIAlCyg/Ays/C4uO2Z85o0GlQpi6NQ6Ttog/YNXYvhBmdnS25CkzANZVdyx7sAyALbs/HF0KAjIGwJM3H8MvGnsUNXEogukdqiPp1gO4jNuquT6ihjdEnuyZNOtYQAEKUIACFKAABShAAQpQgAIUsGQB13FbcfHWA+EQ53dxgYdtAZjzjJ2GdoXw26cMgC255xzb2xNgAPz2LHmldyggYwA8cdMxTNsm3qS+mWNRTG1fDdfuPkJ1vy2a4vuGNkBB6yyadSygAAUoQAEKUIACFKAABShAAQpYsoDzmC24cueRcIiLutWEW7n8mLH9BH7cqPWQ9YII/KyGJU/5lbHJmIXoqgE6HiwDYB03z8hDl/Gm9+PGWMzYflLY1g+qFsXPH1XDrQeP4TBqs+YS2P1dfRTNnVWzjgUUoAAFKEABClCAAhSgAAUoQAFLFnAcvRk37z8WDnFpD1fUtMmHgB0n8cOGWGFt/YoFMacTA2BL7jnH9vYEGAC/PUte6R0KyBgAK29OypuU6GhZrRh+alcV9x89RaURGzXFdw2qhxJ5s2nWsYACFKAABShAAQpQgAIUoAAFKGDJAvYjNuLuo6fCIS7vVRtOpfJg1s6TGLdeHAB7ViiAeZ1dLHnKr4xNxixEVw3Q8WAZAOu4eUYeuow3Pf/1RzFz5ylhW1tVL4bJH1bFoyfPYDtsg+YSCP7aAzYFcmjWsYACFKAABShAAQpQgAIUoAAFKGDJAsrPwMrPwqJjdV83OBTPjcBdpzBm3VFhbV3bAljQhQGwJfecY3t7AgyA354lr/QOBWQMgMeuO4LfdsULFds6FceEto54/vw5ygxerym++au6sC1krVnHAgpQgAIUoAAFKEABClCAAhSggCUL2Axeh2fPxSNc368O7IrmxOyQePitPSIsdi+XHwu71bTkKb8yNhmzEF01QMeDZQCs4+YZeegy3vSUNyflTUp0tHMugfFtHNSSskPW46nGu9+6fu6wL5rLyEuFc6cABShAAQpQgAIUoAAFKEABnQs8e/YcNkO0PwS15au6KF/IGnND4zF6jTgArl02HxZ3d9WVjIxZiK4aoOPBMgDWcfOMPHQZb3qj1xzG3NAEYVvbu5SAf6vkALjCsA14qPHnL6v6uMGxRG4jLxXOnQIUoAAFKEABClCAAhSgAAV0LpDabRDn707AyNWHhbN2tcmLJT1q6UpGxixEVw3Q8WAZAOu4eUYeuow3vVGrD2PebnEA3KFmSYxrWUVtfeWRm3Dn4RPhMljeqxacSuU18lLh3ClAAQpQgAIUoAAFKEABClBA5wL3Hj2B3YhNmrP4+0Hov4clYPgqcQDsUiYvlvVkAKyJygIpBBgAS9FG401CxgB4xKpDWBB2WtjMT1xLYkyL5AC46vebcePeY2H90h6uqGmTz3gLhDOmAAUoQAEKUIACFKAABShAAWkEbt5/DMfRmzXnEza4PorkyoqFe05j2F+HhPU1SufB/31eW/OallQgYxZiSb4yj4UBsMzdlXhuMt70hv0Vg4V7zgi79mmtUvj+g8pqjfOYLbhy55GwflG3mnArl1/ilcCpUYACFKAABShAAQpQgAIUoIDsAlfvPITTmCDNaYYP9UIB68xYvPcMhqyMEdY7lcqD5b0YAGuiskAKAQbAUrTReJOQMQBW3pyUNynR0al2aYxqbq+WuI7biou3Hgjr53WuAc8KBY23QDhjClCAAhSgAAUoQAEKUIACFJBGIOnWA7iM26o5n+gRDZE7WyYs2XcG360QB8DVSubGyt5umte0pAIZsxBL8pV5LAyAZe6uxHOT8aY3eMVB/LHvrLBrnd1KY2Sz5ADYfXwwzl2/L6wP/NQZXnaFJF4JnBoFKEABClCAAhSgAAUoQAEKyC5w/sZ9uP0QrDnNmFGNYJ0lI5ZFnMWgPw8K65UHpisPTtfTIWMWoid/PY+VAbCeu2fgsct40xv05wEsizgn7GpX9zIY3tROrak3cTvir9wV1gd8Uh3elYsYeKVw6hSgAAUoQAEKUIACFKAABSigd4HTV+/CY8J2zWnE+nkjS8b0+HP/OQz8vwPCeofiubC6r7vmNS2pQMYsxJJ8ZR4LA2CZuyvx3GS86SlvTsqblOjoXqcMhjZJDoAbTt6BuKQ7wvqp7auhmWNRiVcCp0YBClCAAhSgAAUoQAEKUIACsgucSLoDr8k7NKd5YqwPMqRPhxWR5zBgmTgArlwsJ9Z+UUfzmpZUIGMWYkm+Mo+FAbDM3ZV4bjLe9AYsi8aKyPPCrvWsa4PBvpXUGp+fd+Fo4i1h/ZR2VdGiWjGJVwKnRgEKUIACFKAABShAAQpQgAKyC8RevAXvKbs0pxnv7wsrKyv8FXUeXy6NFtbbFcmJ9f0ZAGuiskAKAQbAUrTReJOQMQD+amk0VkaJA+DPPcriO5+KasObTQ1BzPmbwuZPaOOAts4ljLdAOGMKUIACFKAABShAAQpQgAIUkEbg0PmbaDo1RDifjOmtEDfWV61ZFX0e/ZeIA+CKha2x8cu6ujKSMQvRVQN0PFgGwDpunpGHLuNNr/+SKKyKviBsa2/PshjknRwAt5wRiqgzN4T1/q2qoL1LSSMvFc6dAhSgAAUoQAEKUIACFKAABXQuEH32BlpMDxXOImvG9Djq563WrDlwAV/8ESWsr1DIGpu+YgCs86XB4ZspwADYTCiWWZaAjAGw8uakvEmJjr71ymFg4wpqyYcBYdiXcE1Y7/eBPTrWKm1ZzeNoKEABClCAAhSgAAUoQAEKUIACqRCISLiGNgFhwjOsM2dAzOjGas26g4noszhSWF++YA5sGeCRilG8/1IZs5D3r2qMETAANkafpZuljDc95c1JeZMSHf3ql8OARskBcIff9mD3yavC+hFN7dDFvYx0/eeEKEABClCAAhSgAAUoQAEKUMA4AmEnr6L9b3uEE86TLSOiRjRSazbEJKLXInEAXLZAdmz92lNXiDJmIbpqgI4HywBYx80z8tBlvOn1XrQf62MuCtv6pVd5fOllq9Z8Omcfdh6/LKwf4lsRPeqWNfJS4dwpQAEKUIACFKAABShAAQpQQOcCu+Iuo+PsfcJZFLDOjPChXmrNxkMX8fnC/cL6MvmzY9tABsA6XxocvpkCDIDNhGKZZQnIGAB//vt+bDwsDoAHNLRFvwbl1WZ0nReOrbFJwsYM8q6A3p7lLKt5HA0FKEABClCAAhSgAAUoQAEKUCAVAttik9B5XrjwjKK5smD34AZqzebDF9Hjd3EAXCpfNuz4pl4qRvH+S2XMQt6/qsPdUS4AACAASURBVDFGwADYGH2WbpYy3vR6LIjA5iOXhL0a2MgWfesnB8Dm1L8cGEu3CDghClCAAhSgAAUoQAEKUIACFDCEgDmBbsm82bBzUHKgG3TkErotiBDalMibFbsG1deVn4xZiK4aoOPBMgDWcfOMPHQZb3rd5kcg6Kg4AP6mcQX0qZf8id4+iyKxLsb8PYONvF44dwpQgAIUoAAFKEABClCAAhTQr4A5e/raFMiO4P/t6Rscewld5okD4GK5syL0OwbA+l0VHHlqBBgAp0aLtRYjIGMAbM6WDt96V0Qvz+Q9ffsvicKq6AvCnii1yjk8KEABClCAAhSgAAUoQAEKUIACehVYfeAC+v0RJRy+baEc2PyVh1qz7VgSOs81f8sIvbjImIXoxV7v42QArPcOGnT8Mt70Os/dh23HxA91G+xTET09kgPgr5cdwPLIc8IV0L1OGQxtYmfQVcJpU4ACFKAABShAAQpQgAIUoIAMAisiz2HAsgPCqdgVyYn1/euoNTuOX8Znc8QPjSucMwv2DEneM1gvh4xZiF7s9T5OBsB676BBxy/jTU95c1LepETHUN9K6F7XRi35bvlBLAk/K6zvVLs0RjW3N+gq4bQpQAEKUIACFKAABShAAQpQQAaBZeFnMWj5QeFUHIvnwqq+7mrNrrjL6DhbHAAXtM6MfUO9dMUjYxaiqwboeLAMgHXcPCMPXcabXsfZe7Er7oqwrcOaVEK3OskB8LC/YrBwzxlhfUfXUvBrUdnIS4VzpwAFKEABClCAAhSgAAUoQAGdCyzaexpDVx4SzsKpVB4s71VbrQk9cQUfB+4V1ufPkRkRwxgA63xpcPhmCjAANhOKZZYlIGMA/HHgHoSeuCqEHtHUDl3cy6g1o1YfxrzdCcL69i4l4N/KwbKax9FQgAIUoAAFKEABClCAAhSgAAVSITB/dwJGrj4sPKNmmbxY2rOWWhN28ira/7ZHWJ8veybsH94wFaN4/6UyZiHvX9UYI2AAbIw+SzdLGW967WftQdgpcQA8qpkdOrklB8Bj1h5BYEi8sLdtnIpjYltH6frPCVGAAhSgAAUoQAEKUIACFKCAcQRmh8TDb+0R4YTdy+XHwm411Zq9p66i3SxxAJwnW0ZEjWikK0QZsxBdNUDHg2UArOPmGXnoMt702s0Mw974a8K2fv+BPT6tVVqt+WFDLAJ2nBTWt6haFFM+qmbkpcK5U4ACFKAABShAAQpQgAIUoIDOBWbuOAn/DbHCWXjYFsD8Li5qTXjCNbQNCBPW58qaEQdGMgDW+dLg8M0UYABsJhTLLEtAxgD4w4Aw7EsQB8DKfr7Kvr7KMWnzMUwNPiFsTBOHIpjeobplNY+joQAFKEABClCAAhSgAAUoQAEKpEJg+rYTmLDpmPAMr0oFEfhZDbVm/+lraP2rOAC2zpIBMaMap2IU779Uxizk/asaYwQMgI3RZ+lmKeNNr82vuxFx+rqwV2NbVsbHNZMD4J+D4vBT0HFhfWP7QpjZ0Vm6/nNCFKAABShAAQpQgAIUoAAFKGAcgSlBxzElKE44YW/7wgjo6KTWRJ65jlYzdgvrc2TOgEOjGQAbZxUZe6YMgI3df93OXsYAuNWMUESeuSHsiX+rKmjvUlKtSe1vQHXbbA6cAhSgAAUoQAEKUIACFKAABQwtMHHTMUzbJv4L2KYORTDtf38BG332BlpMDxWaZcuUHke+99aVq4xZiK4aoOPBMgDWcfOMPHQZb3rKm5PyJiU6xreugnY1kgPg1O6BZOT1wrlTgAIUoAAFKEABClCAAhSggH4FzHkGTstqxfBTu6rqJA+eu4Hm08QBcJaM6RDr56MrFBmzEF01QMeDZQCs4+YZeegy3vQ+mBaCA+duCtv6YxsHfOhcQq0x5ymobuXyYVE3VyMvFc6dAhSgAAUoQAEKUIACFKAABXQuMGbtEQSGxAtn0capOCa2dVRrDp2/iaZTQ4T1mTKkw/ExDIB1vjQ4fDMFGACbCcUyyxKQMQBuNjUEMefFAfCkto5o7VRcbcaCsASMWHVY2BiXMnmxrGcty2oeR0MBClCAAhSgAAUoQAEKUIACFEiFwKjVhzFvd4LwjPYuJeDfykGtOXzhJpr8Ig6AM6SzwolxvqkYxfsvlTELef+qxhgBA2Bj9Fm6Wcp402vyyy4cvnBL2Kuf2jmiZbXkAHjx3jMYsjJGWF+9ZG6s6O0mXf85IQpQgAIUoAAFKEABClCAAhQwjsDQlTFYtPeMcMIdXUvBr0VlteZo4i34/LxLWJ/OCjjl30RXiDJmIbpqgI4HywBYx80z8tBlvOkpb07Km5To+PmjqvigajG1ZFnEWQz686Cw3qF4Lqzu627kpcK5U4ACFKAABShAAQpQgAIUoIDOBb798yCWRpwVzqKzW2mMbGav1hy7eBuNp+zUnHXCDwyANZFYIIUAA2Ap2mi8ScgYAHtP2YnYi7eFzfylfTU0dyyq1qyMOoevlh4Q1tsVyYn1/esYb4FwxhSgAAUoQAEKUIACFKAABSggjcCAZdFYEXleOJ8edW0wxLeSWhN36TYa/qQdAMf7+8LKyko3TjJmIbrB1/lAGQDrvIFGHb6MN71GP+3A8Ut3hC2d1qEamjokB8CrD1xAvz+ihPW2hXJg81ceRl0mnDcFKEABClCAAhSgAAUoQAEKSCDQf0kUVkVfEM6kt2dZDPKuqNacSLoDr8k7NGd+cpwv0it7QejkkDEL0Qm97ofJAFj3LTTmBGS86SlvTsqblOiY8XF1+FYpopZsiElEr0WRwnqb/NkRPNDTmIuEs6YABShAAQpQgAIUoAAFKEABKQT6LIrEuphE4Vz61S+HAY0qqDWnLt9B/UnaAXDcWB9kTJ9ON0YyZiG6wdf5QBkA67yBRh2+jDe9+pO249Tlu8KWBnxSHd6VkwPgLUcuofuCCGF9ibxZsWtQfaMuE86bAhSgAAUoQAEKUIACFKAABSQQ6LEgApuPXBLOZEBDW/RrUF6tSbhyF54Tt2vO/NgYb2TOkF6zzlIKZMxCLMVW9nEwAJa9w5LOT8abXr2J2xF/RRwAz+zohMb2hdWubjuWhM5zw4UdLpIrC8IGN5B0FXBaFKAABShAAQpQgAIUoAAFKGAEgS7zwhEcmySc6iDvCujtWU6tOXvtHur8uE2TJtbPG1kyMgDWhGKB7gUYAOu+hcacgIwBcN0ft+HMtXvChv72qTMa2hVSa0LiruCT2XuF9flzZEbEMC9jLhLOmgIUoAAFKEABClCAAhSgAAWkEOg4ey92xV0RzmWobyV0r2uj1py7fg/u47UD4CPfN0a2TBl0YyRjFqIbfJ0PlAGwzhto1OHLeNNzHx+Mc9fvC1s6+zNnNKiUHADvOXUVH83aI6zPky0jokY0Muoy4bwpQAEKUIACFKAABShAAQpQQAKB9rP2IOzUVeFMRjazQ2e3MmrNhRv3UfuHYM2ZHxrdGDkyMwDWhGKB7gUYAOu+hcacgIwBsNsPwTh/QxwAz+1UA/UqFlSbHpFwDW0CwoQLwDpzBsSMbmzMRcJZU4ACFKAABShAAQpQgAIUoIAUAh8GhGFfwjXhXPxaVEZH11JqzcWbD+Dqv1Vz7gdHNULOLBk16yylQMYsxFJsZR8HA2DZOyzp/GS86dXy34rEmw+EHZvXuQY8KyQHwNFnb6DF9FBhfZaM6RDr5yPpKuC0KEABClCAAhSgAAUoQAEKUMAIAi1nhCLqzA3hVP1bVUF7l5JqTdKtB3AZpx0AHxjRCLmyMQA2whoy+hwZABt9Beh0/jIGwDXHBeHSrYfCjizo4oK6tgXUmkPnb6Lp1BBhfYZ0VjgxzlenXeawKUABClCAAhSgAAUoQAEKUIACQLOpIYg5f1NIMaGNA9o6l1BrLt9+iBpjgzTpooY3RJ7smTTrLKVAxizEUmxlHwcDYNk7LOn8ZLzpKW9OypuU6FjYtSbcy+dXS45dvI3GU3Zqdjje3xdWVlaadSygAAUoQAEKUIACFKAABShAAQpYooD3lJ2IvXhbOLQp7aqiRbVias3VOw/hNEY7AN4/zAv5cmS2xCm/dkwyZiG6wdf5QBkA67yBRh2+jDc95zFbcOXOI2FLF3eridrlkgPgk5fvoMGkHZpLIG6sDzKmT6dZxwIKUIACFKAABShAAQpQgAIUoIAlCnhN3oETSXeEQ5vWoRqaOhRVa67ffYRqfls0pxI+1AsFrBkAa0KxQPcCDIB130JjTkDGALi63xZcuysOgJf0cIWrTT616aev3oXHhO2aCyDWzxtZMqbXrGMBBShAAQpQgAIUoAAFKEABClDAEgU8J2xDwtV7wqEFfOIE78qF1Zqb9x7D8fvNmlPZO6QBCuXMollnKQUyZiGWYiv7OBgAy95hSecn402v6vebcePeY2HHlvWsBZcyedWa8zfuw+2HYM0Ox4xqBGsdPdVUc0IsoAAFKEABClCAAhSgAAUoQAFDCbiPD8a56/eFc579mTMaVCqk1tx68BgOo7QD4LDB9VEkV1bdWMqYhegGX+cDZQCs8wYadfgy3vQcRm3CrQdPhC398/NacC6dHACb+1RTvW1qb9Q1zXlTgAIUoAAFKEABClCAAhSgwOsFXMdtxcVbD4Q88zrXgGeFgmrNnYdPUHnkJk3O0O/qo1huBsCaUCzQvQADYN230JgTkDEArjJyE24/FAfAy3vVhlOpPGrTle0ilG0jtI59QxugoLV+/qRFaz78PgUoQAEKUIACFKAABShAAQoYS8CcZ+Ys6lYTbv97Zs69R09gN0I7AN41qB5K5M2mG0wZsxDd4Ot8oAyAdd5Aow5fxpue/YiNuPvoqbClK3vXRrWSyQGwuX/Ssvu7+iiqo99oGnVNc94UoAAFKEABClCAAhSgAAUo8HoBx9GbcfO+eMvEpT1cUfN/z8x58PgpKg7fqMm585t6KJmPAbAmFAt0L8AAWPctNOYEZAyAKw3fiPuPxQHwqj5ucCyRW236/UdPUWmE9hua3n6jacwVzVlTgAIUoAAFKEABClCAAhSgQEoC5nxg6uW/mH345CkqDNP+eXn7QE+Uzp9dN/AyZiG6wdf5QBkA67yBRh2+jDe9CsM24OGTZ8KWrunrjirFc6k1j548g+2wDZpLIPhrD9gUyKFZxwIKUIACFKAABShAAQpQgAIUoIAlCig/+yo/A4uO1X3d4FA8+QNTj58+Q/mh8v28LGMWYonrTcYxMQCWsasGmJOMNz3boRvw6Kn4DW3tF+6oXCw5AH7+/DnKDF6v2e3NX9WFbSFrzToWUIACFKAABShAAQpQgAIUoAAFLFGg7JD1ePrsuXBo6/q5w75o8s/Lz549h80Q7Z+XgwZ4oFxB/XxgSsYsxBLXm4xjYgBsQV29ffs2Nm/ejG3btiEyMhJxcXG4ceMGsmbNiqJFi8LFxQUdOnRA48aNYWVlZdbIExMTERAQgDVr1iAhIQEPHjxA4cKFUadOHXTp0gUeHh5mXefvolWrVuH3339HeHg4Ll26hJw5c6Js2bJo2bIlevbsiVy5km+2aX3IeNMz5w1tfb86sCua8wWvOee8/CaY1n3h9SlAAQpQgAIUoAAFKEABClCAAm9T4L98+Mncc7Z8VRfldfSBKRmzkLe5VnitlAUYAFvI6pg8eTKGDh2qBrRahxLeLly4ECVLlhSWrly5Ug15lRA5paN79+749ddfkT59euG1lHBaCZ/Xrl2bYl3x4sWxdOlS1K5dW2sKb/x9GW96ZQavw3PxLzSx8cs6qFj4nwDYnG0jXt43+I3heQEKUIACFKAABShAAQpQgAIUoMA7FPiv2x+a8zP2pi/rokJh/fzFrIxZyDtcSoZ+KQbAFtL+zz//HDNnzlRHowSpDRo0gLOzMwoUKID79+9j7969auh7584dtaZMmTLYs2cPChYs+NoZBAUFwdfXF48fJz8ls0mTJmjevDmyZ8+ufro4MDAQt27dUr+nhMCzZs1KUeLJkyfqtbZs2aLWFCpUSD3Hzs4O165dwx9//IHQ0FD1e7lz50ZISAjs7e3TVFa2m565v53893YOlUduwp2HT4TWy3vVglOpvGnaD16cAhSgAAUoQAEKUIACFKAABSiQFgL3Hj2B3YhNmpf+9wPQzfmL2Q3966BSkX8+ZKX5Iu+5QLYs5D1zGurlGQBbSLt79eqFU6dOYeDAgWr4my5duldGdvr0aXX7h2PHjqnf69y5M+bMmfNKnfIp4goVKuDMmTPq96ZOnYq+ffua1B0/flzd/uHixYvq15WtJxo2bPhaDeUTwr1791a/p4S+wcHBagj88qGMe9KkSeqX3Nzc1BA4LQ/Zbnrm709UF+UK/vPbyarfb8aNe8khf0rH0h6uqGmTLy3bwWtTgAIUoAAFKEABClCAAhSgAAXSRODm/cdwHL1Z89phg+ujSK6sL+rKD12Px0/N3zdY8wUsoEC2LMQCSA0zBAbAFtJq5ZO0efNqf0rzwIEDqFq1qjrqbNmy4fLly+p/Xz6mT5/+IvBt1qwZVq9e/dpZrlixAq1bt1a/5+rqCuVG8u/j6dOn6ieS/w6K9+/fj+rVq7+2TvnEcnR0tPq9jRs3qmF1Wh2y3fSePH2GcmY8oXTr1x4oW+CfDeqdx2zBlTuPhMyLutWEW7n8adUKXpcCFKAABShAAQpQgAIUoAAFKJBmAtfuPkJ1v+S/SBYd4UO9UMA684sS22EboGwfITpeftC61vUt4fuyZSGWYGqUMTAA1mGnK1WqhNjYWHXkSiDs4OBgMou6deti165d6teUB8p5enq+dpbPnj1TH+CmPBxOOeLj41G6dGmTWuXTvsonkpVD+cTw9u3bUxSbO3euuuewcnz22WeYN29emunKdtMzd0+jbQM9USZ/9heuruO24uIt8b7R8zrXgGeF128VkmYN4oUpQAEKUIACFKAABShAAQpQgAJvQSDp1gO4jNuqeaWo4Q2RJ3umF3UVh2/Ag8fiAHh1Xzc4FM+teW1LKZAtC7EUVyOMgwGwDrvs4uKC8PBwdeTKPsA1a9Z8MQvlYW3KPrxKuGttbY3r168LH/CmbD0REBCgnj9jxgwo/375GDRoECZMmKB+afz48VD+ndJx6dIlFC5cWP22sjex8u+0OmS76T14/BQVh2/U5NrxjSdK5fsnAHYfH4xz1+8Lzwv81BledqZbdmi+EAsoQAEKUIACFKAABShAAQpQgAIWIHD+xn24/RCsOZKYUY1gnSXjizq7ERtx79FT4Xl/9XFD1RIMgDVxWaB7AQbAOmvhw4cP1f13b968qY48MTHxReiq/Ft5WJyynYNyKJ8E3rFjh3CGyh7CXbt2VWuUfX6V7SNePnx8fNTtHJRD+TRwvXr1hNcrWbIkzp49q9YkJSWpD7FLi0O2APj+o6eoNEI7AP73pvb1Jm5H/JW7QuKAT6rDu3KRtGgDr0kBClCAAhSgAAUoQAEKUIACFEhTgdNX78JjQsp/jfz3i8f6eSNLxvQvxmLOQ9NX9K6N6iXzpOn43+bFZctC3qYNryUWYACssxWibKugPPxNOZS9eJU9eV8+FixYoG6/oBzmbMOgbBFRv359tV7Z6iEoKMjkejY2NurWEMrxui0i/s2nbBOxc+dO9cvKNhTu7u5pIizbTe/uwyewH6n9VNPQ7+qjWO5/NrVvOHkH4pLuCI2ntq+GZo5F06QPvCgFKEABClCAAhSgAAUoQAEKUCAtBU4k3YHXZPGH25TXPzHWBxnSp3sxlCqjNuH2gyfCof35eS04l9Z+HlNazi8115YtC0nN3Fn7ZgIMgN/M752erTzwzd7eXn3wm3IoD3Fr2bKlyRh++eUX9O/fX/3a119/jYkTJwrHePDgQTg6Oqo1Tk5OiIiIMKlXHkynbCOhHMr2Ejly/PMAstdduFWrVli5cqX6rTVr1qBp06apNnrdw+j+fZGYmBj07NlT/fLu3btRq1atVL+OJZ1w+8FjVBmV+qea+vy8C0cTbwmnMqVdVbSoVsySpsuxUIACFKAABShAAQpQgAIUoAAFzBKIvXgL3lOSn3MkOuL9fWFlZfWixHH0Zty8/1h4zrKeteBShgGwli2/r38BBsA66eGjR4/g5eX14uFuLVq0eBG0vjyFcePGYejQoeqXlP+OGTNGOMO4uDjY2tqqNcp/jx07ZlKfKVMmPH6cfMNU/pshQwbh9T7++GMsXrxYrVH+2759+1QLv3zDNudkGQJg5U1JeXPSOvYOaYBCObO8KGs2NQQx55O3A0npmNDGAW2dS2hdmt+nAAUoQAEKUIACFKAABShAAQpYnMCh8zfRdGqIcFwZ01shbqyvSU217zfj+j1xALykhytcbfJZ3JxTGhA/AaybVlncQBkAW1xLXh2Q8kC3Tz/9FIsWLVK/WbZsWfUhcHnyvLpPzcsB8LBhw+Dn5yecIQNgy1gAN+49QtXvt2gOZt/QBiho/U8A3HJGKKLO3BCe59+qCtq7lNS8NgsoQAEKUIACFKAABShAAQpQgAKWJhB99gZaTA8VDitLxnSI9fMxqXHy24Krdx8Jz1vcvSZql81vaVNOcTwMgHXTKosbKANgi2uJ6YCeP3+ubnXw22+/qd9QHrKmPNitdOnSrx05t4Cw8IamMLxrdx+hup92ABwxzAv5c2R+cZUPA8KwL+GacNJ+H9ijY63Xrxd9anHUFKAABShAAQpQgAIUoAAFKGAUgYiEa2gTECacrnXmDIgZ3dikxnlMEK7ceSg8b1G3mnArxwDYKGvJyPNkAGzB3VfC3969eyMgIEAdZfHixbF9+3b1E8ApHXwInAU3VDA05U1JeXPSOiKHN0Te7JlelHX4bQ92n7wqPG1EUzt0cS+jdWl+nwIUoAAFKEABClCAAhSgAAUoYHECYSevov1ve4TjypMtI6JGNDKpcRkbhKTb4gD4964uqFO+gMXNOaUB8RPAummVxQ2UAbDFtSR5QEr426dPH/z666/qv4sVK6aGv+XKlROOeO/evXB1dVVr6tatq35aWHTMmTMHXbt2VUuUsHn69Okm5T4+Pti4caP6teDgYNSrV094PeUTymfPnlVrkpKSUKBA2txIZbvpJd1+AJexWzVXY/SIhsid7Z8A+NM5+7DzePJDAVM6hvhWRI+6Kf/SQPNFWUABClCAAhSgAAUoQAEKUIACFHhPArviLqPj7H3CVy9gnRnhQ71Mamr5b0XizQfC8+Z3cYGHbdrkFmnBJVsWkhZGvObrBRgAW+DK+Hf4W7RoUTX8LV++vOZob9++jdy5c0PZN9ja2hrXr19H+vTpUzyvV69eLz5hPGPGDCj/fvkYNGgQJkyYoH5p/PjxUP6d0nHp0iUULlxY/XbBggWh/DutDtluehdvPoCrv3YAfGBkI+TKmvEFa9d54dgamyRkHuRdAb09xb84SKs+8boUoAAFKEABClCAAhSgAAUoQIE3EdgWm4TO88KFlyiaKwt2D25gUuP2QzDO37gvPG9u5xqoV6HgmwzvnZ4rWxbyTvEM/mIMgC1sAfw7/C1SpIga/tra2po9UuWTv7t27VLrlXM9PDxee64SEiufKI6Pj1e/r/z333sLK5/6bdAg+Sbq6emJbdu2pTiOuXPnokuXLur3O3XqBOXfaXXIdtO7cOM+av8QrMkVM6oRrLP8EwD3WBCBzUfEQfuAhrbo10D7lweaL84CClCAAhSgAAUoQAEKUIACFKDAOxbYcuQSui+IEL5qybzZsHOQ6V8su48Pxrnr4gB4Tidn1K9Y6B3P6L+/nGxZyH+X4JmpFWAAnFqxNK5Xtn1QPomrHMqnaZUAt0KFCql6VeV85TrK0axZM6xevfq1569YsQKtW7dWv6dsG6HcSP59PH36VN17+OLFi+q39u/fj+rVq7+2ztnZGdHR0er3lG0jGjc23YA9VZPQKJbtpnfu+j24j085XP+b4/DoxsieOcMLnT6LIrEuJlGo1a9+OQxolLo19DZ7xWtRgAIUoAAFKEABClCAAhSgAAX+q8CGmET0WhQpPN0mf3YED/Q0qan74zacuXZPeF7gp87wsmMA/F97w/P0I8AA2IJ69cUXX2DatGnqiJTwV/m0bcWKFVM9wgcPHqih8ZkzZ9RzlWv+HQj/fbG4uDh1j+C/g90tW7bAy8t0v5y/a5V9iJX9gZXD3t5e3QtY2eLh5eObb77BxIkT1S+5ubkhJCQk1eNOzQmyBcBnr91DnR+1A+Cj33sja6Z/tvTovyQKq6IvCOl6eZbFt96pX0ep6QdrKUABClCAAhSgAAUoQAEKUIACaSGw+sAF9PsjSnhp20I5sPkr079+9pywDQlXxQHwrI5OaGSfvJWlHg7ZshA9mMsyRgbAFtLJYcOGYezYseporKysMG7cOLPCX+XTuMqD1/59BAUFwdfXF48fP1a/1bRpUzRv3hzZs2dHZGQkAgMDcfPmTfV73bt3x6xZs1KUePLkiXotJSRWDiWcVs6xs7PDtWvX8Mcff7wIfHPlyoXQ0FA1KE7LQ7ab3umrd+ExYbsmWayfN7Jk/CcA/nrZASyPPCc8r3udMhjaxE7z2iygAAUoQAEKUIACFKAABShAAQpYmsCKyHMYsOyAcFh2RXJiff86JjX1J27HqSt3hecFfOIE78oMgC2t5xzP2xdgAPz2Tf/TFZX9dXfs2JHqc5V9dpX9dl93rFy5Ut2T98aNGyleVwlylU/4ih4Up5ysPFyuQ4cOWLt2bYrXUraKWLp0KWrXrp3qeaT2BNkC4Pgrd1FvonYAfHyMDzJlSPeC67vlB7Ek/KyQr1Pt0hjVPG0D+dT2j/UUoAAFKEABClCAAhSgAAUoQAFzBJaFn8Wg5QeFpY7Fc2FVX3eTmgaTtuPkZXEA/OvH1eFTpYg5w7CIGtmyEItANcggGABbSKPTIgBWppaYmKgGvGvWrEFCQgKU7SGUB8u5u7uja9euKT4gLiWWVatWYcGCBQgP5aFfLwAAIABJREFUD0dSUhKsra1RtmxZtGrVCj179oTyCeB3cch20zt5+Q4aTNL+BcCJsT7IkP6fAHjYXzFYuCd5q4+Ujo6upeDXovK7aAtfgwIUoAAFKEABClCAAhSgAAUo8FYFFu09jaErDwmv6VQqD5b3Mv0wWsPJOxCXdEd43vQO1dHEgQHwW20YL2aRAgyALbItHJSWgGwB8Imk2/CavFNr2jg1zhfp0lm9qBu1+jDm7U4QntfepQT8WzloXpsFFKAABShAAQpQgAIUoAAFKEABSxNYEJaAEasOC4flUiYvlvWsZVLT+KedOHbptvC8qe2roZljUUubcorjkS0L0Q28BANlACxBE404Bdluescv3Uajn7QD4IQfmpi0e8zaIwgMiRcugTZOxTGxraMRlwnnTAEKUIACFKAABShAAQpQgAI6F5gdEg+/tUeEs3Arlw+Lurma1HhP2YnYi+IA+OePquKDqsV0IyRbFqIbeAkGygBYgiYacQqy3fRiL96C95RdwlYqH/w95W8aAP+wIRYBO04Kz2tRtSimfFTNiMuEc6YABShAAQpQgAIUoAAFKEABnQvM3HES/htihbPwsC2A+V1cTGp8f96FI4m3hOf91M4RLasV142QbFmIbuAlGCgDYAmaaMQpyHbTO3LhFnx/EQfAGdJZ4cQ4X5N2T9p8DFODTwiXgLKfkbKvEQ8KUIACFKAABShAAQpQgAIUoIDeBKZvO4EJm44Jh+1VqSACP6thUtN06i4cOi8OgCe1dURrJwbAelsTHG/qBRgAp96MZ1iAgGwB8KHzN9F0aohQNlP6dDg+1sek5uegOPwUdFx4XmP7QpjZ0dkCusYhUIACFKAABShAAQpQgAIUoAAFUicwJeg4pgTFCU/yti+MgI5OJjXNp4Xg4LmbwvMmtHFAW+cSqRvQe6yWLQt5j5SGe2kGwIZruRwTlu2mF3PuJppNEwfAmTOkw7ExpgHwf/1NqByrgLOgAAUoQAEKUIACFKAABShAAdkFzPnL16YORTDtX3/5+sH0UBw4e0PI82NrB3xYgwGw7GuI8wMYAHMV6FJAtgBYeVNS3pxER9aM6XHUz9uk5L/uhaTLpnPQFKAABShAAQpQgAIUoAAFKGA4gf/67JuWM0IRdUYcAP/Qqgo+cimpG1PZshDdwEswUAbAEjTRiFOQ7aYXdeY6Ws7YLWxl9kzpcfh70wD4vz4N1YhrhnOmAAUoQAEKUIACFKAABShAAf0JjFl7BIEh8cKBt3EqjoltHU1q2vy6GxGnrwvPG9eyCjrUZACsv1XBEadWgAFwasVYbxECsgXA+09fQ+tfw4S21pkzIGZ0Y5OaBWEJGLHqsPA8lzJ5saxnLYvoGwdBAQpQgAIUoAAFKEABClCAAhRIjcCo1Ycxb3eC8JT2LiXg38rBpObDgDDsS7gmPG9Mi8r4xLVUaobzXmtly0LeK6bBXpwBsMEaLst0ZbvphSdcQ9sAcQCcM0sGHBxlGgAv3nsGQ1bGCNtavWRurOjtJkvrOQ8KUIACFKAABShAAQpQgAIUMJDA0JUxWLT3jHDGHV1Lwa9FZZOadjPDsDdeHAD7fWCPjrVK60ZTtixEN/ASDJQBsARNNOIUZLvp7T11Fe1m7RG2Mne2jIge0cikZlnEWQz686DwPIfiubC6r7sRlwnnTAEKUIACFKAABShAAQpQgAI6F/j2z4NYGnFWOIvObqUxspm9SU37WXsQduqq8LzRze3xWW0GwDpfIhy+GQIMgM1AYonlCcgWAIedvIr2v4kD4LzZMyFyeEOTZqyMOoevlh4QNsiuSE6s71/H8prIEVGAAhSgAAUoQAEKUIACFKAABTQEvl52AMsjzwmretS1wRDfSiY1HwfuQegJcQA8spkdOruV0U0PZMtCdAMvwUAZAEvQRCNOQbab3u4TV9AhcK+wlflzZELEMNMAePWBC+j3R5TwPNtCObD5Kw8jLhPOmQIUoAAFKEABClCAAhSgAAV0LtB/SRRWRV8QzqKXZ1l8613RpKbj7L3YFXdFeN7wpnbo6s4AWOdLhMM3Q4ABsBlILLE8AdkC4JC4K/hktjgALmCdGeFDvUyasSEmEb0WRQobZJM/O4IHelpeEzkiClCAAhSgAAUoQAEKUIACFKCAhkCfRZFYF5MorOpXvxwGNKpgUvPpnH3Yefyy8LxhTSqhWx0b3fRAtixEN/ASDJQBsARNNOIUZLvpKW9KypuT6CiUMzP2DjENgLccuYTuCyKE55XImxW7BtU34jLhnClAAQpQgAIUoAAFKEABClBA5wI9FkRg85FLwlkMaGiLfg3Km9R0mrsP24+JA+AhvhXRo25Z3QjJloXoBl6CgTIAlqCJRpyCbDe97ceS0GluuLCVRXJlQdjgBiY1244lofN/OM+Ia4ZzpgAFKEABClCAAhSgAAUoQAH9CXSZF47g2CThwAd5V0Bvz3ImNeac951PRXzuwQBYf6uCI06tAAPg1Iqx3iIEZAuAt8UmofM8cQBcLHdWhH5n+klec7aOyJ8jMyKGmX5y2CKayEFQgAIUoAAFKEABClCAAhSgAAU0BMzZy3eobyV0r2u6lUO3+eEIOioOjr9pXAF96pkGx5bcENmyEEu2lm1sDIBl66hB5iPbTW/r0UvoOj/1WzmEnbyK9r/tEXY9T7aMiBrRyCArg9OkAAUoQAEKUIACFKAABShAAZkEOvy2B7tPXhVOaWQzO3R2M32Ym7JdorJtougY2MgWfeubbh1hyXayZSGWbC3b2BgAy9ZRg8xHtpueOXv5lsqXDTu+qWfS4YiEa2gTECbsunXmDIgZ3dggK4PTpAAFKEABClCAAhSgAAUoQAGZBD4MCMO+hGvCKfl9YI+OtUqb1PT8PQKbDqd+72BLtpMtC7Fka9nGxgBYto4aZD6y3fQ2Hb6Inr/vF3avTP7s2DbQ06Qm+uwNtJgeKjwvS8Z0iPXzMcjK4DQpQAEKUIACFKAABShAAQpQQCaBljNCEXXmhnBK/q2qoL1LSZOaXgv3Y8Ohi8LzvvQqjy+9bHXDJVsWoht4CQbKAFiCJhpxCrLd9DYeSsTnCyOFrbQpkB3BX5sGwIfO30TTqSHC8zKks8KJcb5GXCacMwUoQAEKUIACFKAABShAAQroXKDZ1BDEnL8pnMWENg5o61zCpKbPokisi0kUntevQXkMaMgAWOdLhMM3Q4ABsBlILLE8AdkC4PUxiei9SBwAlyuYA0EDPEyacezibTSeslOzQfH+vrCystKsYwEFKEABClCAAhSgAAUoQAEKUMCSBLyn7ETsxdvCIU1pVxUtqhUzqem7OBJrD4oD4C/ql8PXjSpY0nSFY5EtC9ENvAQDZQAsQRONOAXZbnprD15A38VRwlbaFsqBzV+ZBsAnL99Bg0k7NJdA3FgfZEyfTrOOBRSgAAUoQAEKUIACFKAABShAAUsS8Jq8AyeS7giHNK1DNTR1KGpS039JFFZFXxCe16deWXzTuKIlTZcBsG66oa+BMgDWV7842v8JyBYAr4o+j/5LooX9rVjYGhu/rGtSc/rqXXhM2K65LmL9vJElY3rNOhZQgAIUoAAFKEABClCAAhSgAAUsSaDexO2Iv3JXOKSAT6rDu3IRk5qvlkZjZdR54Xm9PMviW28GwJbUb44lbQQYAKeNK6+axgKyBcB/RZ3Hl0vFAXClIjmxoX8dE9nzN+7D7YdgTe2YUY1gnSWjZh0LKEABClCAAhSgAAUoQAEKUIACliTgPj4Y567fFw4p8FNneNkVMqkZsCwaKyLFAXBPDxsM9qlkSdMVjkW2LEQ38BIMlAGwBE004hRku+mtiDyHAcsOCFtpXzQn1vUzDYCTbj2Ay7itmksganhD5MmeSbOOBRSgAAUoQAEKUIACFKAABShAAUsScB23FRdvPRAOaV7nGvCsUNCkZuD/HcCf+88Jz+tR1wZDfBkAW1K/OZa0EWAAnDauvGoaC8gWACtvSsqbk+ioUiwX1nzhblJy7e4jVPfboqm9b2gDFLTOolnHAgpQgAIUoAAFKEABClCAAhSggCUJOI/Zgit3HgmHtKhbTbiVy29SM+jPA1gWIQ6Au7mXwbCmdpY0XeFYZMtCdAMvwUAZAEvQRCNOQbab3rKIsxj050FhKx2L58KqvqYB8K0Hj+EwarPmEtj9XX0UzZ1Vs44FFKAABShAAQpQgAIUoAAFKEABSxJwHL0ZN+8/Fg5paQ9X1LTJZ1Lz3fKDWBJ+VnheF7cyGNGMAbAl9ZtjSRsBBsBp48qrprGAbAHw0vAz+HZ5jFCtaonc+KuPm0nNg8dPUXH4Rk3toAF1Ua6gtWYdCyhAAQpQgAIUoAAFKEABClCAApYi8Pz5c9gO24DHT58Lh7Syd21UK5nHpGbwihj8se+M8LxOtUtjVHN7S5mu5jhky0I0J8yCtybAAPitUfJC71JAtpue8qakvDmJjuolc2NFb9MAWKmvNHwj7j9+Kjx3Wc9acCmT9122iK9FAQpQgAIUoAAFKEABClCAAhR4I4HbDx6jihl/9bp9oCdK589u8lpDV8Zg0V5xAPxZrVIY/UHlNxrjuzxZtizkXdoZ/bUYABt9Beh0/rLd9BbtPY2hKw8Ju+FcKg/+7FX7lZra/ltx4aZ4Q/yZHZ3Q2L6wTrvNYVOAAhSgAAUoQAEKUIACFKCAEQXOXruHOj9u05z6gRGNkCtbRpO64X8dwu97TgvP7ehaCn4tGABrArNA9wIMgHXfQmNOQLYAWHlTUt6cRIfyCV7lk7z/Pnx/3oUjibeE545vXQXtapQ05mLhrClAAQpQgAIUoAAFKEABClBAlwIHz91A82mhwrGnT2eFuDE+SJfOyqRu5KpDmB8mDoA/rlkSY1tW0Y2NbFmIbuAlGCgDYAmaaMQpyHbTWxCWgBGrDgtb6WqTF0t6vBoAfxK4FyEnrgjP/da7Inp5ljXiUuGcKUABClCAAhSgAAUoQAEKUECnAtuPJaHT3HDh6PNlz4T9wxu+UjNq9WHM250gPLe9Swn4t3LQjY5sWYhu4CUYKANgCZpoxCnIdtObFxqPUWuOCFtZu2w+LO7u+kpN38WRWHswUXhuz7o2GOxbyYhLhXOmAAUoQAEKUIACFKAABShAAZ0K/BV1Hl8ujRaOvmyB7Nj6tecrNd+vOYI5ofHCc9s5l8D4NgyAdbo8OOxUCDAATgUWSy1HQLYAeE5IPL5fKw6A3cvlx8JuNV9pwohVh7BA489a2joVx4S2jpbTQI6EAhSgAAUoQAEKUIACFKAABSigIWDOz8o1SufB/33+6vNyxqw9gsAQcQCst5+VZctC+H+AdyfAAPjdWfOV3qKAbDe9wF2nMGbdUaFQnfL58XvXVwPgyVuO45etccJzvSoVQuBnzm+xA7wUBShAAQpQgAIUoAAFKEABClAgbQUmbz6GX4JPCF+koV0h/Pbpqz/vjlt/FLN2nhKe27p6cUz6UD8flpItC0nb1cOrvyzAAJjrQZcCst30ftt5CmPXiwNgD9sCmN/F5ZV+zQ2Nx2iN7SOcS+XBn71e/Y2oLpvPQVOAAhSgAAUoQAEKUIACFKCAIQSUh6UrD00XHR86F8ePbV4Ncf03HMXMHeIAuFW1YpjcrqpuLGXLQnQDL8FAGQBL0EQjTkG2m97MHSfhvyFW2Mp6FQpgbudXA+BV0efRf4l4TySbAtkR/Jo9kYy4djhnClCAAhSgAAUoQAEKUIACFNCHQJ/FkVin9cwbDxsM9nn1mTc/bozFjO0nhRNtUbUopnxUTR8YAGTLQnQDL8FAGQBL0EQjTkG2m96v209i/EZxANygYkHM7lTjlXbvOH4Zn83ZJ1wGebNnQuRrnopqxLXDOVOAAhSgAAUoQAEKUIACFKCAPgQ+DtyD0BNXhYP9zqciPvco+0rNxE3HMG2bePuI5o5F8Ut7BsD6WA0c5ZsIMAB+Ez2e+94EZAuAp287gQmbjgk9U9rH9+C5G2g+LVR4bjor4MRYX6RT/gcPClCAAhSgAAUoQAEKUIACFKCADgR8ft6Fo4m3hCP9sbUDPqxR4pUac/YPbupQBNM6VNeBRPIQZctCdAMvwUAZAEvQRCNOQbab3tStcZi05biwlY3sCmHWaza2P3vtHur8uE1zGUSPaIjc2TJp1rGAAhSgAAUoQAEKUIACFKAABShgCQK1/Lci8eYD4VBmdXRCI/vCr9T8tOU4ftZ4YHqTKkUw/WMGwJbQa44hbQUYAKetL6+eRgKyBcA/B8XhpyBxAOxtXxgBHZ1eEb3z8Akqj9ykKb1toCfK5M+uWccCClCAAhSgAAUoQAEKUIACFKCAJQhUHL4BDx4/Ew7l/z6vhRql875SY87P2T6VC+PXT179OdsS5v66MciWhViqs4zjYgAsY1cNMCfZbnrm/GbSt0phzPj41Tem58+fo8KwjXj0VPymuLxXbTiVymOA1cEpUoACFKAABShAAQpQgAIUoIDeBe4/eopKIzZqTiNogAfKFczxSp05f2nb2L4QZnZ01nwNSymQLQuxFFcjjIMBsBG6LOEcZbvpmbM3UROHIpiewt5ELmODkHT7obDTsz9zRoNKhSRcDZwSBShAAQpQgAIUoAAFKEABCsgmcOHGfdT+IVhzWvuHeSFfjsyv1JnzrJ2GdoXw22u2WtR80fdUIFsW8p4YDfmyDIAN2Xb9T1q2m545Tydt5lgUU1N4Omnjn3bi2KXbwsZObOuINk7F9d98zoACFKAABShAAQpQgAIUoAAFpBc4fOEmmvwSIpynlRUQN8YHGdKne6VuxvYT+HGj1sPWCyLwsxq6sZQtC9ENvAQDZQAsQRONOAXZbno/bozFjO0nha38oGpR/PxRtdfWfDQrDHtOXROeP9S3ErrXtTHicuGcKUABClCAAhSgAAUoQAEKUEBnAiFxV/DJ7L3CUefKmhEHRjZ6bU3AjpP4YUOs8Pz6FQtiTicGwDpbGhzufxBgAPwf0HjK+xeQLQBW3pSUNyfR0bJaMfzUruprS3ot3I8Nhy4Kz+/tWRaDvCu+/+ZxBBSgAAUoQAEKUIACFKAABShAAQ2BNQcu4Is/ooRVpfNlw/Zv6r22ZtbOkxi3XhwAe1YogHmdXXTTC9myEN3ASzBQBsASNNGIU5Dtpue//ihm7jwlbGXr6sUx6UPH19YMWRmDxXvPCM9v71IC/q0cjLhcOGcKUIACFKAABShAAQpQgAIU0JnAgrAEjFh1WDjqaiVzY2Vvt9fWBO46hTHrjgrPr1M+P37vWlM3MrJlIbqBl2CgDIAlaKIRpyDbTW/suiP4bVe8sJVtnYpjQtvXB8ATNsVi+jbxJ4i97QsjoKOTEZcL50wBClCAAhSgAAUoQAEKUIACOhP4OSgOPwUdF45atIXD7JB4+K09IjzfvVx+LOzGAFhnS4PD/Q8CDID/AxpPef8CsgXAypuS8uYkOto5l8D4Nq//BK85v9msWSYvlvas9f6bxxFQgAIUoAAFKEABClCAAhSgAAU0BEatPox5uxOEVaK/lJ0bGo/Ra8QBcO2y+bC4u6tueiFbFqIbeAkGygBYgiYacQqy3fRGrzmMuaHiNzbRFg7L95/D/7N3H+A1nv//wN+ZIsQIIogYCTFiJjYhVmxKtaUtSlXRgZZvaxelrQ6jVquqFKWtUWrvLcSKvcWMEZJIZOd/Pae/9k+b3M/Z5zz3eT/X5XJVPvd6fU6fJJ/znPv+4NcTwpdCxeL5sXloU0d8uXDNFKAABShAAQpQgAIUoAAFKKAxgfd/OYY1x28LZ/1m43IY3aFKjjE/7b+GcX+It5CoX94bv7ylnQelZKuFaOwlqenpsgCs6fQ57uRlu+np885mz3r+mPxCtRyTvv1cLPouPCJ8QRTzyoPDo1o67ouGK6cABShAAQpQgAIUoAAFKEABzQj0WhCJ3RfuC+c7PCIIg8MDc4xZfOAaxqjsIVy3nDdWaOiTsrLVQjTzYpRgoiwAS5BER1yCbDe9sWtOYdGB68JUvlbfH5O65FwAPhrzCF1n7xe2d3V2wsVP28LJyckRXzJcMwUoQAEKUIACFKAABShAAQpoSKDjzL2IvhUvnLHykJTysFRO15JD1zFq1Slh+zplC+PXtxtqRkW2Wohm4CWYKAvAEiTREZcg201v9Opo/HwwRpjKXg3KYELn4Bxjrj1IQrMvd6q+FKLHt4aXh5tqHAMoQAEKUIACFKAABShAAQpQgAK2FGj8+XbcfPRUOIU5r9ZG22olcoxZFhmDj1dGC9uHlCmM3weyAGzLPHNs6wiwAGwdZ45iZgHZCsDKNyXlm5Po6tOwLMZ3qppjSHxyOmpM2KyqvGdEOEp7e6rGMYACFKAABShAAQpQgAIUoAAFKGBLgeBxm/AkNUM4hV/eqo/65YvkGLP8cAz+97u4AFzLvxBWDWpky2UaNLZstRCDFs9gkwRYADaJj41tJSDbTe+j30/il8M3hJxvNCqLcR1zLgBnZWWjwugNyMzKFvaxZnAj1ChdyFZp47gUoAAFKEABClCAAhSgAAUoQAFVgbSMLFQcvUE1btOQMAT5euUYt+LIDYz47aSwD+X3Y+X3ZK1cstVCtOIuwzxZAJYhiw64BtlueiN+O4EVR24KM9mvcTmMyeV0U6VhyMQteJiUJuxj4Rt10CzIxwFfMVwyBShAAQpQgAIUoAAFKEABCmhF4F5CCupO3qY63ciRLeBTwCPHuN+ibuLDX08I+6juVxB/vNNYdRx7CZCtFmIvro4wDxaAHSHLEq5Rtpue8k1J+eYkuvo3KYdR7avkGtLiq524fD9J2Mc3L9fAC7X8JHxFcEkUoAAFKEABClCAAhSgAAUoIIvAubsJaDNtj+pyLkxqC3dX5xzjVh69iWErxAXg4FIFsO7dJqrj2EuAbLUQe3F1hHmwAOwIWZZwjbLd9IatOI6VR28JMzUgrDw+blc515juc/fj8LVHwj7GdqiCvo3LSfiK4JIoQAEKUIACFKAABShAAQpQQBaBA5cfosf3B4XLyZ/HFac+icg1ZvWxWxiy/LiwjyolCmD9+ywAy/K64TpyF2ABmK8OTQrIVgAeuvw4Vh0TF4DfbhqAj9pWyjVf/RcdwZYzscJ8vtc8EMNaB2ky55w0BShAAQpQgAIUoAAFKEABCjiGwIboOxi45KhwsaW982LPiOa5xqw5fgvv/yIuAFfy9cLGIWGaQZWtFqIZeAkmygKwBEl0xCXIdtN7/5djWHP8tjCVg5oFYESb3AvA+uwj/Fp9f0zqUs0RXzJcMwUoQAEKUIACFKAABShAAQpoRGDJoesYteqUcLZq+/euPXEb7y47JuwjqLgXNg1lAVgjLwtO0wQBFoBNwGNT2wnIVgBWvikp35xE1zvhgfgwIvend6dsOIt5u64I+2hfvQRm9axtu8RxZApQgAIUoAAFKEABClCAAhSggIrArB2XMHXTeWFUWMViWNS3bq4xf568g8FLxU8RV/DJjy3DmmomH7LVQjQDL8FEWQCWIImOuATZbnrKNyXlm5Poeq9FBQxrVTHXkLm7LuOzDeeEfTQKLIIlb9Z3xJcM10wBClCAAhSgAAUoQAEKUIACGhGYtO4M5u+9Kpxtl5olMe2VWrnG6LONRECxfNj2QTONqACy1UI0Ay/BRFkAliCJjrgE2W56g5ZEYX30XWEqh7SsgCEtcy8Arzh8AyN+Pynso3KJAtigoQ3uHfG1zTVTgAIUoAAFKEABClCAAhRwdAF9Dkrv07AsxneqmivVxlN38fbPUULKckXzYceHLAA7+uvNEdbPArAjZFnCNcpWAH57cRQ2nhYXgJWnf5WngHO7Np++i7cWi7+5lSjogQMft5DwFcElUYACFKAABShAAQpQgAIUoIAsAn0XHsb2c/eEyzHH78hlinhi1/BwzbDJVgvRDLwEE2UBWIIkOuISZLvpvbXoCDafiRWm8sPWFfFO89wLwIevxaH73APCPvK4OuP8pLaO+JLhmilAAQpQgAIUoAAFKEABClBAIwJdZu3D8RuPhbOd2LkqXm9QNteYrWdi8eaiI8I+SnvnxZ4RzTWiwi0gNJMoO5woC8B2mBROSV1AtgLwmz8dwdaz4gLw8IggDA4PzBXn0r0naPn1LlW8sxPaIK+7i2ocAyhAAQpQgAIUoAAFKEABClCAArYQaDZ1B649TBYOPbNHLXSsUTLXmO3nYtF3obgAXKpQXuz7iAVgW+SYY1pXgAVg63pzNDMJyFYA7rfwMLapfLzlf20qYWCzgFwFHz5JRcikrarC+z9qjpKF8qrGMYACFKAABShAAQpQgAIUoAAFKGALgRqfbEb803Th0EverIdGgUVzjdl5/h76/HhY2EfJgh7Yr6FtEmWrhdjiteWoY7IA7KiZ1/i6ZbvpvfFjJHacvy/MysdtK2FA09wLwBmZWQgctUE1s+vebYzgUgVV4xhAAQpQgAIUoAAFKEABClCAAhSwtoC+v9v++V5jVC2Z+++2uy/cR68FkcLp+xbwwMGR2jknR7ZaiLVfW448HgvAjpx9Da9dtpue8k1J+eYkuka1q4z+YeWFMfq8S/pzv3poXCH3d0k1/LLg1ClAAQpQgAIUoAAFKEABClBA4wLm+nTr3osP8NoPh4QaPl55EDmqpWbEZKuFaAZegomyACxBEh1xCbLd9F7/4RD2XHwgTOXo9pXxZhNxAViffZJm9KiFToJ9khzx9cQ1U4ACFKAABShAAQpQgAIUoIB9CFy6l4iWX+9WnYza+Tb7Lz1Az/niAnDR/HlwZDQLwKrYDNC8AAvAmk+hYy5AtgLwq/MPYt+lh8Jkju1QBX0blxPGvDB7H47FiE9KndC5KnoJTkp1zFcUV00BClCAAhSgAAUoQAEKUIAC9iBw+Focus89IJyKh5szzk1sK4w5cPkhenx/UBhTJJ87osa0sodl6zUH2Wohei2aQWYRYAHYLIzsxNoCst1Mr0AhAAAgAElEQVT0enx3EAeuiAvA4ztWQZ9G4gJw34WHsV3lMLmhLSvi/ZYVrJ0yjkcBClCAAhSgAAUoQAEKUIACFFAV2Hz6Lt5aHCWM0+fwtkNXHuLl78QF4MKebjg2trXqnOwlQLZaiL24OsI8WAB2hCxLuEbZbnovzzuAQ1fjhJnS58ndYSuOY+XRW8J++jQsi/Gdqkr4quCSKEABClCAAhSgAAUoQAEKUEDrAssPx+B/v0cLl1GlRAGsf7+JMEafJ4kL5nXDiXEsAGv9NcP5qwuwAKxuxAg7FJCtAPzS3AOIvCYuAE/sEozX65cRZmPSujOYv/eqMKZzzZKY/kotO8wqp0QBClCAAhSgAAUoQAEKUIACji4wd9dlfLbhnJChUWARLHmzvjAm6nocus0RbyXh5eGK6PERmiGXrRaiGXgJJsoCsARJdMQlyHbTe3HOfhy5/kiYyk9fCMar9cQF4Fk7LmHqpvPCfppUKIrF/eo54suGa6YABShAAQpQgAIUoAAFKEABOxeYsv4s5u2+Ipxlh+ol8G3P2sKYozGP0HX2fmFM/jyuOPUJC8B2/pLg9MwgwAKwGRDZhfUFZCsAd529D0dVDm+b0rUaetT1F2IvPRSDkavEH5WpVqog1r7b2PpJ44gUoAAFKEABClCAAhSgAAUoQAEVgRG/ncCKIzeFUcqnY5VPyYqu4zceo8usfcIYT3cXnJnQRjM5ka0Wohl4CSbKArAESXTEJch201O+KSnfnETXF92q46U6pYUxG6LvYOCSo8IYv8J5sfd/zR3xZcM1U4ACFKAABShAAQpQgAIUoICdC/RfdARbzsQKZ/leiwoY1qqiMObkzcfo9K24AOzh5oxzE9vaucj/n55stRDNwEswURaAJUiiIy5Btpte52/34sTNeGEqp75YHd1DxQXgA5cfosf34lNO87m74LSG3uF0xNc310wBClCAAhSgAAUoQAEKUMBRBfTZInFcxyp4o1E5IdGpW/HoMHOvMMbdxRkXPmUB2FFfa460bhaAHSnbEq1VtgJwx5l7EX1LXAD+qnsNdAvxE2bx/N1EREzbrZrpC5Pawt3VWTWOARSgAAUoQAEKUIACFKAABShAAWsKtPhqJy7fTxIOOe3lmuhSq5Qw5vTteLSfIS4Auzo74dLkdtZcnkljyVYLMQmDjQ0SYAHYIC4G24uAbDe99jP24PTtBCHvNy/XwAu1xAXgewkpqDt5m2qaIke2gE8BD9U4BlCAAhSgAAUoQAEKUIACFKAABawpEDJxCx4mpQmH/KlvXTStWEwYc/ZOAtpO3yOMcXYCrkxpb83lmTSWbLUQkzDY2CABFoAN4mKwvQjIdtNTvikp35xE1/RXaqJzTfE7nGkZWag4eoNqmjYOaYJKvgVU4xhAAQpQgAIUoAAFKEABClCAAhSwlkBWVjYCR61HVrZ4xD/eaYTqfoWEQfp+QvbaZywAWyu/HMd2AiwA286eI5sgIFsBuM203Th3N1EoMqNHLXSqUVJVLXjcJjxJzRDGLetfHw0Ciqj2xQAKUIACFKAABShAAQpQgAIUoIC1BOKT01FjwmbV4faMCEdpb09h3KV7iWj5tfoWiVentIOTk5PqmPYQIFstxB5MHWUOLAA7SqYlW6dsN73W3+zChdgnwix927MWOlRXLwA3/nw7bj56Kuxr9qu10a5aCcleFVwOBShAAQpQgAIUoAAFKEABCmhZ4OqDJIR/uVN1Cac+iUD+PK7CuMv3n6DFV7tU+7o8uR1clL0gNHDJVgvRALk0U2QBWJpUOtZCZLvp6bPJvb5F207f7sXJm+ID5T59IRiv1ivjWC8arpYCFKAABShAAQpQgAIUoAAF7FrgaMwjdJ29XzhHNxcnKAebqz21q28x+eKnbeHmoo1D0mWrhdj1i1GyybEALFlCHWU5st30mn+5E1ceiE85nftabbQJVn9qt9eCSOy+cF/4UhgeEYTB4YGO8nLhOilAAQpQgAIUoAAFKEABClBAAwLbz8Wi78Ijwpn6eOVB5KiWqqu5/jAJTaeqP018flIb5HF1Ue3PHgJkq4XYg6mjzIEFYEfJtGTrlO2m12zqDlx7mCzM0rzXQxBR1Vc1k+//cgxrjt8WxvVrXA5jOlRR7YsBFKAABShAAQpQgAIUoAAFKEABawn8FnUTH/56QjhcUHEvbBoapjqlG3HJaPLFDtW4cxPbwMONBWBVKAZoWoAFYE2nz3EnL1sBOOyLHYiJExeAv+8VilZViqsmffwfp7Fw/zVhXNfapfD1SzVV+2IABShAAQpQgAIUoAAFKEABClDAWgLz91zBpD/PCoerX94bv7zVQHVKNx8lo/Hn6gXgMxMi4Oku3k9YdTArBchWC7ESG4cBwAIwXwaaFJDtpqfPwW0/9A5Fi8rqBeDpWy/im60XhHkNDyqGH9+oq8ncc9IUoAAFKEABClCAAhSgAAUoIKfAFxvPYfbOy8LFtQ32xZzXQlQBbj9+ioafbVeN0+dAOdVOrBQgWy3ESmwchgVgvga0KiDbTa/RZ9tx6/FTYTp+7FMH4ZV8VFO26MA1jF1zWhhXs3QhrB7cSLUvBlCAAhSgAAUoQAEKUIACFKAABawl8PHKaCyLjBEO16OuP6Z0raY6pbvxKag/ZZtq3MnxrVHAw001zh4CZKuF2IOpo8yBTwA7SqYlW6dsN70GU7bhTnyKMEsL36iDZkHqBeC1J27j3WXHhH2VLeKJncPDJXtVcDkUoAAFKEABClCAAhSgAAUooGWBgT9HYcOpu8IlDA4PwPCISqrLvJeQgrqT1QvAJ8a2RkFPFoBVQRmgaQEWgDWdPsedvGwF4HqTtyI2IVWY0EV96yKsYjHVpO+9+ACv/XBIGFfAwxUnx0eo9sUAClCAAhSgAAUoQAEKUIACFKCAtQRenncAh67GCYcb3b4y3mxSXnVK9xNTUefTrapxx8a0QuF87qpx9hAgWy3EHkwdZQ4sADtKpiVbp2w3PeWbkvLNSXT93K8eGlcoqprJ07fj0X7GXtW4S5+2hauLs2ocAyhAAQpQgAIUoAAFKEABClCAAtYQiPhmN87HJgqH+qp7DXQL8VOdzsMnqQiZpF4AjhrdEkXy51Htzx4CZKuF2IOpo8yBBWBHybRk65Ttphc6aQsePEkTZmlp/3poGKBeANZ3o/vIkS3gU8BDslcGl0MBClCAAhSgAAUoQAEKUIACWhUImbgFD5PEvxsv6BOK5pXUD0h/lJSGWhO3qFIcHtUSxbxYAFaFYoCmBVgA1nT6HHfyshWAa0/cgjiVb3K/vFUf9csXUU16SnomKo3ZqBq3rH99NAhQ70+1IwZQgAIUoAAFKEABClCAAhSgAAVMFIhPTkeNCZtVe1EONFcONle79O3v0MgWKK6Rh6Nkq4Wo5ZBfN58AC8Dms2RPVhSQ7aZXc8JmPE5OFwquGNAAdct566Xc6LPtuPX4qTB2YpdgvF6/jF79MYgCFKAABShAAQpQgAIUoAAFKGBJgajrceg254DqECfGtUbBvOqHtiWkpKP6ePWC8oGPm6NEwbyq49pDgGy1EHswdZQ5sADsKJmWbJ2y3fSqj9+EhJQMYZZ+e7sBQsvqVwDutSASuy/cF/bXp2FZjO9UVbJXBpdDAQpQgAIUoAAFKEABClCAAloUWH44Bv/7PVo4dR+vPIgc1VKv5T1JzUDwuE2qsfs+ao5ShVgAVoVigKYFWADWdPocd/KyFYCrjduExFRxAfj3gQ0RUqawXkmfsPYMFuy7KoxtFFgES96sr1d/DKIABShAAQpQgAIUoAAFKEABClhSYNK6M5i/V/x7bMOAIljaX7/fY5+mZaLyWPXtEfeMCEdpb09LLs1sfctWCzEbDDtSFWABWJXIegGZmZk4e/Ysjhw5gqioKN3fJ06cwNOnf32Uv3fv3li4cKFBE7pz5w7mzp2LtWvX4tq1a0hJSYGvry+aNGmCvn37omnTpgb1t2bNGixevBiHDx9GbGwsChQogICAALzwwgsYMGAAChYsaFB/xgbLdtOrOnYjktIyhRyrBjVELX/9CsDLImPw8UrxO6fFC+TBoZH6vXNqbJ7YjgIUoAAFKEABClCAAhSgAAUooI9Anx8jsfO8+JOsvRuUwSedg/XpDvqej7N7eDj8i7AArBcqgzQrwAKwHaWuW7duWLlyZa4zMrQAvGrVKl2R9/Hjx7n22b9/f8yZMwcuLi5CicTERPTs2RPr1q3LNc7Pzw/Lly9Hw4YNLa4qWwG48piNeJouLgCvGdwINfTY6F7BP3wtDt3nqu+ddHJ8axTwUN87yeIJ5QAUoAAFKEABClCAAhSgAAUo4NACjT/fjpuPVM6y6VwVrzcoq5dTWkYWKo7eoBq788NmKFs0n2qcPQTIVguxB1NHmQMLwHaU6S5dukB5wvbvy9vbG0WKFMHFixd1/2RIAXjr1q1o164d0tP/Olisffv26NSpE/Lly4ejR49i/vz5SEhI0H1NKQJ/9913uUpkZGTo+tqyZYsupnjx4ro2VapUQVxcHJYtW4Z9+/bpvlaoUCHs3bsXVatadm9Z2W56yjcl5ZuT6Fr7TmNU89PvCetHSWmoNfGvfIkuQ54qVuuLX6cABShAAQpQgAIUoAAFKEABChgjkJyWgSpj1ffrXdq/HhoGFNVriIzMLASOUi8Ab/+gKcoXy69Xn7YOkq0WYmtPRxqfBWA7yvbkyZOhPGkbEhKi+1OuXDndlg9vvPGGbpb6FoCVbR6CgoIQExOjazdz5ky88847z630woULuu0f7t69q/v3zZs3o1WrVjlqKE8IDxo0SPc1pei7fft2XRH42evDDz/EV199pfunRo0a6YrAlrxku+lVGLUe6ZnZQrJ17zZGcCn9CsBKR6GTtuDBkzRhn1+8WB0vhZa2ZKrYNwUoQAEKUIACFKAABShAAQpQQChw6lY8OsxUryNEjmoBHy8PvTSzsrJRfuR61ditw5oi0IcFYFUoBmhagAVgO0+fMQXgWbNm/VPw7dixI/74448cV6lsN6FsO6Fc9evXh1JU/fel7EusbO3wd6FY2Zu4du3aOcaFhobi+PHjuq9t3LgRERERFtOVrQAcMHI9MrPEBeD17zVBlZIF9DZ9ed4BHLoaJ4wfEFYeH7errHefDKQABShAAQpQgAIUoAAFKEABCphbYPWxWxiy/K96Qm5XwbxuOD62FZycnPQaPjs7G+U+Vi8AbxkahgrFvfTq09ZBstVCbO3pSOOzAGzn2TamABwWFoY9e/boVrZjxw40a9Ysx1VmZWXpDnBTDodTrqtXr6Js2ef30lGe9m3RooXu68oTwzt37sxV7Mcff9TtOaxc+j6tbCy/bDe9ch//iWxx/RcbhzRBJV/9C8CjVkVjyaG/ngLP7WpRyQc/9KljbBrYjgIUoAAFKEABClCAAhSgAAUoYLLA1E3nMGvHZWE/IWUK4/eBhp05pM/v2puGhCHIlwVgk5PIDuxagAVgu04PDN4CQtlCQtmHVynuenl54dGjR8ID3gYOHIi5c+fqFGbPng3lv5+9RowYgalTp+r+6fPPP4fy37ldsbGx8PX11X3Zx8cHyn9b6pKpAKzvx1I2Dw1DRQPelVy47yrGrz0jTIG/tyd2jwi3VJrYLwUoQAEKUIACFKAABShAAQpQQFVgwOIj2HRaXEN4ObQ0Pn+xumpfzwbo82nbDe83QeUS+j9sZdAEzBwsUy3EzDTsTkWABWA7f4kY+gTwoUOHdNs5KJfyJPCuXbuEK1ywYAH69euni1H2+VW2j3j2atu2rW47B+VSngYODxcXC/39/XHjxg1d/L1791CsWDGLCMt003uSmoHgceqb3e8ZEY7S3p56e+69+ACv/XBIGK98cubshDbwcHPRu18GUoACFKAABShAAQpQgAIUoAAFzCnQ4quduHw/Sdjl6PaV8WaT8gYNq895O3++1xhVS+p/3o5BEzBzsEy1EDPTsDsVARaA7fwlYmgBeNGiRbrtF5RLn20YlC0imjdvrotXtnrYunXrcyLly5fXbQ2hXDltEfFvPmWbiN27d+v+WdmGonHjxhYRlummdy8xBXU/3abqdGR0SxTNn0c17u+Au/EpqD9FvV9D9xbWewIMpAAFKEABClCAAhSgAAUoQAEKqAikZWSh8tiNqufi/PhGHYQH+RjkWXH0Bij9iy5DD1w3aAJmDpapFmJmGnanIsACsJ2/RAwtAM+YMQPvv/++blUffPABvvzyS+EKT548iRo1auhiQkJCcOTIkefivb29ddtIKJeyvUT+/OKTMbt27YpVq1bp4teuXYsOHToYLJzTYXT/7iQ6OhoDBgzQ/fP+/fvRoEEDg8exlwbXHyah6dTc91b+e55nJkTA091V72krG95XH78ZiakZwjbTX6mJzjVL6d0vAylAAQpQgAIUoAAFKEABClCAAuYSuBibiFbf/PUgmegy9FOxSl+VxmxASrq4APzHO41Q3a+Q2vB28XUWgO0iDZqcBAvAdp42QwvAkydPxqhRo3SrUv6eNGmScIUXL15ExYoVdTHK3+fPn38u3t3dHenp6bp/U/52dRUXIF999VUsXbpUF6/83aNHD4OF9T3R8++OtV4APnsnAW2n/3VoX26XslXD5U/bwdlZv9NO/+6ny6x9OH7jsbDv95oHYljrIIPzxAYUoAAFKEABClCAAhSgAAUoQAFTBTZE38HAJUeF3eR1c8HpTyIM/p24ytiNSE7LFPa9enAj1CzNArCpeWR7+xZgAdi+82PwIXDPFoBHjx6NiRMnClfIArDtXwBR1x+h25z9wol4urvgzIQ2Bk/2w19P4Leom8J27ar5YvarIQb3zQYUoAAFKEABClCAAhSgAAUoQAFTBWZsu4ivt1wQdhNcqgDWvdvE4KHuJ6ZCeaDKxckJzk5OcHKG7m/l2SrdfzsBbs7OBheWDZ6ImRrwCWAzQTpgNywA23nSDX0CmFtA2HlCc5iePoe1Fc3vjiOjWxm8uHm7LmPKhnPCdhV88mPLsKYG980GFKAABShAAQpQgAIUoAAFKEABUwXeW3YMf5y4LeymS82SmPZKLVOH0nx7FoA1n0KbLYAFYJvR6zewoQVgHgKnn6s9RW06fRcDFkcJp1TaOy/2jPjrsD5Drm1nY9Hvp+f3df53ezcXJ5yd0AauLs6GdM1YClCAAhSgAAUoQAEKUIACFKCAyQLtpu/BmTsJwn6GRwRhcHigyWNpvQMWgLWeQdvNnwVg29nrNbKhBeBDhw6hfv36ur7DwsKwa9cu4TgLFixAv379dDGDBg3CrFmznotv27YtNm7cqPu37du3Izw8XNifv78/bty4oYu5d+8eihUrptc6DQ2S6aa3+tgtDFl+XEgQVNwLm4aGGcoEfQ+Y2/ZBUwQUEx/wZ/DgbEABClCAAhSgAAUoQAEKUIACFBAIZGZlQ9mnNzVDfFDb3NdC0CbY1+EtZaqFOHwyrQzAArCVwQ0dztACcGJiIgoVKoSsrCx4eXnh0aNHcHFxyXXYgQMHYu7cubqvz549G8p/P3uNGDECU6dO1f3T559/DuW/c7tiY2Ph6/vXDdnHxwfKf1vqkummt/RQDEauihZSKRvSKxvTG3rp+8103ushiKjKb6aG+jKeAhSgAAUoQAEKUIACFKAABYwXiHmYjLCpO1Q72DqsKQJ9+NCSTLUQ1aQzwKwCLACbldP8nRlaAFZmoDz5u2fPHt1kdu7ciaZNc97fVSkSBwYG4urVq7pY5e+yZcs+twjlqd8WLVro/q1Zs2bYsSP3G/OPP/6Ivn376mL79OkD5b8tdcl005u/5wom/XlWSNUosAiWvPnXk92GXm2n78FZfpzGUDbGU4ACFKAABShAAQpQgAIUoICFBbafi0XfheJtC12dnXB2Yhu4cdtCyFQLsfBLi93/S4AFYDt/SRhTAFae5B08eLBuZR07dsQff/yR4ypXrlyJbt266b6mbBuh3Ej+fWVmZsLPzw93797VfSkqKgq1a9fOMS40NBTHj/+1lYGybURERITFdGW66c3cdhFfqZx42rJycczvHWqU57vLjmGtyob6L9QqhW9ermlU/2xEAQpQgAIUoAAFKEABClCAAhQwRoAHlxumJlMtxLCVM9pUARaATRW0cHtjCsApKSkICgpCTEyMbnbffvvtPwXhv6d78eJF3ZPCfxd2t2zZgpYtW+a4mjlz5uj2B1auqlWr6vYCVrZ4ePYaPnw4vvzyS90/NWrUCHv37rWojEw3vc83nsOcnZeFXp1qlMSMHsadeDpj20V8rVJgrlaqINa+29iiOWPnFKAABShAAQpQgAIUoAAFKECB52oJv57Ar1E3hShtg30x57UQwgF8ApivAqMFWAA2ms78DZUtGH744YfnOj558iTWrl2r+7fq1avrnuh99lKexu3atet/JrN161a0a9cO6enpuq916NABnTp1Qr58+XD06FHMnz8f8fHxuq/1798f3333Xa4LysjI0PWlFImVS9nnV2lTpUoVxMXFYdmyZf8UfAsWLIh9+/bpCsWWvGQqAI9bcwo/Hbgu5HqlTml81q26UaTro+9g0JKjwrZ53Vxw+pMIODs7GTUGG1GAAhSgAAUoQAEKUIACFKAABQwVeGH2PhyLeSxs9m7zQHzQOsjQrqWMl6kWImWC7HhRLADbUXKU/XrDw8MNmlHv3r2hPCWc07Vq1SrdnryPH+d+M1UKucoTvqKD4pS+lcPlevbsiXXr1uU6P2WriOXLl6Nhw4YGrcGYYJluesP1eMfzjUZlMa6jcUX1C7GJaP3NblXmvf8Lh19hT9U4BlCAAhSgAAUoQAEKUIACFKAABUwVyM7ORvXxm5GYmiHsavorNdG5ZilTh5OivUy1ECkSoqFFsABsR8kydwFYWdqdO3d0BV7lKeJr165B2R6iRIkSaNy4Mfr165frAXG5saxZswaLFi3C4cOHce/ePXh5eSEgIED3FPKAAQOgPAFsjUumm97gpUfx58k7QrbB4QEYHlHJKNq0jCxUHrsRmVnZwvYL36iDZkHPb+1h1IBsRAEKUIACFKAABShAAQpQgAIUUBGITUhBvcnbVJ3+fK8xqpa0Tq1BdTI2DpCpFmJjSocbngVgh0u5HAuW6abXd+FhbD93T5iY4RFBGBweaHTymn+1E1fuJwnbj25fGW82KW/0GGxIAQpQgAIUoAAFKEABClCAAhTQV2DfpQd4df4hYbiTE3B2Qht4uLno263UcTLVQqROlB0ujgVgO0wKp6QuINNN75XvDuDglTjhosd1rII3GpVTh8kl4q1FR7D5TKywvSn7DBs9MTakAAUoQAEKUIACFKAABShAAYcUWLjvKsavPSNcu7+3J3aPMGyrTJkxZaqFyJwne1wbC8D2mBXOSVVAppte52/34sTNvw7ky+36vFs1vFzHX9Ult4Cpm85h1o7LwvahZQrjt4GW37/Z6EWwIQUoQAEKUIACFKAABShAAQpIIzB6dTR+PhgjXE/zSj5Y0KeONGs2dSEy1UJMtWB7wwRYADbMi9F2IiDTTa/l17tw6d4ToeyMHrXQqUZJo/VXHbuJoctPCNsXzOuG42NbwUn5jA0vClCAAhSgAAUoQAEKUIACFKCABQX0+TTsW2HlMbJdZQvOQltdy1QL0Za89mfLArD2c+iQK5Dpptfos+249fipMI/ze4WiZZXiRuc6+mY8On67V7X97uHh8C/iqRrHAApQgAIUoAAFKEABClCAAhSggLECGZlZqDVhCxJTM4RdfNGtOl6qU9rYYaRrJ1MtRLrk2PmCWAC28wRxejkLyHTTqzVhMx4lpwtTvfTNemgYWNTol0NyWgaqjtuE7GxxF/zmajQxG1KAAhSgAAUoQAEKUIACFKCAngInbz5Gp2/3qUavHNQQtf0Lq8Y5SoBMtRBHyZm9rJMFYHvJBOdhkIBMN72g0RuQmpElXP+qQQ1Ry8Rvem2m7ca5u4nCcbrWLoWvX6ppUC4YTAEKUIACFKAABShAAQpQgAIUMETg+91X8On6s8Im7q7OODmuNTzcXAzpWupYmWohUifKDhfHArAdJoVTUheQ5aaXmZWNgJHrVRe8eWgYKhb3Uo0TBYz/4zQW7r8m7KNUobzY91Fzk8ZhYwpQgAIUoAAFKEABClCAAhSggEjgzZ8OY+vZe0KkeuW8sXxAA0I+IyBLLYRJtb4AC8DWN+eIZhCQ5ab3JDUDweM2qYrsGRGO0t6m7c278dQdvP3zUdWx9v4vHH6FTRtLdRAGUIACFKAABShAAQpQgAIUoIBDCigPQilbISakiPf/fa9FBQxrVdEhjXJbtCy1ECbV+gIsAFvfnCOaQUCWm969hBTUnbxNVSRqdEsUyZ9HNU4UEJeUhtoTt6j28VX3GugW4qcaxwAKUIACFKAABShAAQpQgAIUoIChAqdvx6P9DPVDyk09C8fQeWkhXpZaiBasZZsjC8CyZdRB1iPLTe/agyQ0+3KnatbOTmiDvO6m73vU+ptduBD7RDhe9xA/TO1eQ3VO1gxIzcjErvP38TQ9Ez5eHqhf3htOTk7WnALHogAFKEABClCAAhSgAAUooAkBpcB65X6Sbq5hFYuhYF43u5r3D3uvYuK6M8I5ubk44eS4CLP8HmxXizdxMrLUQkxkYHMjBFgANgKNTWwvIMtN78ztBLSbsUcIqtQ5r0xuZ5aC55jVp7D44HXheP7entg9Itz2Sf6/Gaw5fgufrD0D5Qnmv69Kvl74snsNBJcqaDfz5EQoQAEKUIACFKAABShAAQrYUuBeYgqGLj+OfZce/jONvG4ueLtpAN5rEWiW3ynNsb63Fh3B5jOxwq5CyxTGbwMbmmM4qfqQpRYiVVI0shgWgDWSKE7zeQFZbnpR1+PQbc4BYXo93V1wZkIbs7wE1p28jXeWHlPt68DHzVGiYF7VOEsHbDkTiwGLjyAr+78jFc2fB1q9dQcAACAASURBVKsHN+R+xZZOAvunAAUoQAEKUIACFKAABexeIDktAy/NO4BTtxJynOvwiCAMDg+0+TqysrJRe9IWPE5OF87lnfBAfBgRZPP52tsEZKmF2JurI8yHBWBHyLKEa5Tlprfn4n28/kOkMENKofPI6JZmyeL9xFTU+XSral/TXq6JLrVKqcZZOqDd9D04cyfnH2CUsfs2KoexHatYehrsnwIUoAAFKEABClCAAhSggF0LrDhyAyN+O5nrHPO5u+Dw6JbwdHe16TrO3U1Am2niT8EqE1zcry6aVChm07na4+Cy1ELs0Vb2ObEALHuGJV2fLDe9TafvYsDiKGGWzL0lQ4uvduLy/+0HldvAPeqWxpSu1W366rn6IAnhKvsjl/bOiz0jmtt0nhycAhSgAAUoQAEKUIACFKCArQX02VZh9qu10a5aCZtO9af91zDuj9PCObg6O+Hk+NY2L1bbFCqXwWWphdijrexzYgFY9gxLuj5Zbnqrjt3E0OUnhFlS9rvdOCTMbJkcuSoaSw/FCPsrVzQfdnzYzGxjGtPR8sMx+N/v0apNL0xqC3dXZ9U4BlCAAhSgAAUoQAEKUIACFJBVoOKoDUjLzBIur0vNkpj2Si2bEgz8OQobTt0VzqGWfyGsGtTIpvO018FlqYXYq6/M82IBWObsSrw2WW56Sw5dx6hVp6z6zU85VO39X46rvjoiR7aATwEP1ThLBYz/4zQW7r+m2v3+j5qjZCHb71esOlEGUIACFKAABShAAQpQgAIUsJBA2Y/+VO25YF43nBjXWjXOUgHZ2dkInbQVD5854DunsQY2C8D/2lSy1DQ03a8stRBNJ0Gjk2cBWKOJc/Rpy3LTm7/nCib9eVaYzkaBRbDkzfpmS3lsQgrqTd6m2t+MHrXQqUZJ1ThLBQxbfhwrj91S7X7VoIao5V9YNY4BFKAABShAAQpQgAIUoAAFZBR4mpaJymM3qi5N2Vrh0uR2qnGWCrgYm4hW3+xW7X7hG3XQLMhHNc4RA2SphThi7my9ZhaAbZ0Bjm+UgCw3vRnbLuLrLReEBi0rF8f83qFGOeXWqNnUHbj2MFnY56v1/PHpC9XMOq4hnXWbsx9R1x+pNpn7WgjaBPuqxjGAAhSgAAUoQAEKUIACFKCAjALXHyah6dSdei3t6pR2cHJy0ivW3EGLD17HmNXiT8C6ODvpnlLOn8e2h9WZe+3m6k+WWoi5PNiP/gIsAOtvxUg7EpDlpvfZhnOYu+uyULZzzZKYbuZ9mj76/SR+OXxDOG6gT35sHdbUZlmvNWEzHiWnq44/sXNVvN6grGocAyhAAQpQgAIUoAAFKEABCsgocPhaHLrPPaDX0g6NbIHiNtrq752lR7Hu5B3hPGv4FcSadxrrtRZHDJKlFuKIubP1mlkAtnUGOL5RArLc9MatOYWfDlwXGvSoWxpTulY3yim3RvocPqe0PTyqJYp55THr2Pp09igpDbUmbtEnFO+EB+LDiCC9YhlEAQpQgAIUoAAFKEABClBANoF1J2/jnaXH9FrWsv710SCgiF6x5gxS9v+t8+k2PHiSKuz2rbDyGNmusjmHlqovWWohUiVFI4thAVgjieI0nxeQ5ab34a8n8FvUTWF6+zYqh7Edq5j1JXD78VM0/Gy7ap+zetZG++olVOPMHaBs/aBsAaHP9VKoH754sYY+oYyhAAUoQAEKUIACFKAABSggncCCvVcxYd0Zvdb16QvBeLVeGb1izRl0+f4TtPhql2qXC/qEonml4qpxjhogSy3EUfNny3WzAGxLfY5ttIAsN73BS47iz2jxR2As9YRrky+240bcU2EOejUogwmdg43Ok7ENlaK4UhzX52pasRh+6ltXn1DGUIACFKAABShAAQpQgAIUkE5gyoazmLfril7rerNxOYzuYN4HjPQZeOmhGIxcFS0MdXYCjo9rjQIebvp06ZAxstRCHDJ5Nl40C8A2TgCHN05AlpveGz9GYsf5+0KE4RFBGBweaByUoJU+Tx8HFMun2wfY2ocETN10DrN2iPdG/ntplXy9sHFImNl92CEFKEABClCAAhSgAAUoQAEtCAxdfhyrjt3Sa6otKvnghz519Io1Z9DgpUfxp8r+v8GlCmDdu03MOax0fclSC5EuMRpYEAvAGkgSp/hfAVluei/PO4BDV+OEKR7XsQreaFTO7C+DX4/cwPDfTqr2u2JAA9Qt560aZ86AgT9HYcOpu3p1WSSfO6LGtNIrlkEUoAAFKEABClCAAhSgAAVkE3h1/kHsu/RQr2WVK5oPOz5splesuYLuJ6ai0WfbkZaZJeyyX+NyGGODp5PNtU5r9CNLLcQaVhzjeQEWgPmK0KSALDe9Tt/uxcmb8cIcfN6tGl6u42/2PN2IS0aTL3ao9ts22BdzXgtRjTNnQJtpu3HubqLeXV6Y1Bburs56xzOQAhSgAAUoQAEKUIACFKCALAItv96FS/ee6LUcF2cnnJvYBm4u1vv9afrWi/hm6wXV+X3fKxStqnD/XxGULLUQ1RcDA8wuwAKw2UnZoTUEZLnp6fONemaPWuhYo6RFWJt/tRNX7icJ+1b2Ydo9Ihx+hT0tMod/d5qVlY3KYzciNUP87vCz7fZ91BylCuW1yvw4CAUoQAEKUIACFKAABShAAXsSqDZ+ExJTMvSe0rYPmiKgWH69400JTMvIQqPPt0N5Clh0ubs448iYltz/VwVbllqIKa8ptjVOgAVg49zYysYCstz0Gk7ZhtvxKULNH3qHokVly7wL+t3uy5i8/pxqNgeElcfH7Sqrxpkj4OajZDT+XP3J5GfHWjWoIWr5FzbH8OyDAhSgAAUoQAEKUIACFKCAZgSepmXqHqAx5JrfKxQtrfSk7apjNzF0ufoB311rlcLXL9c0ZBkOGStLLcQhk2fjRbMAbOMEcHjjBGS56dWcsBmPk9OFCEv710PDgKLGQam0ik9OR/0p2/A0PVMYWcDDFQdHtoCnu6tF5vFsp7sv3EevBZEGjTP3tRC0CfY1qA2DKUABClCAAhSgAAUoQAEKaF3g+sMkNJ2606BljGxXCW+FBRjUxpjg7OxsdJ61T3XbQ6Xvte80RjW/gsYM41BtZKmFOFTS7GSxLADbSSI4DcMEZLnpVRy9AcpHYkTX6sGNULN0IcOADIgevToaPx+MUW0xqUswXqtfRjXO1ICf9l/DuD9OG9TNhM5V0atBWYPaMJgCFKAABShAAQpQgAIUoIDWBSKvxuGleQcMWkaPuqUxpWt1g9oYExx1/RG6zdmv2jS0TGH8NrChahwDAFlqIcyl9QVYALa+OUc0g4AMN73MrGwEjFyvqrF5aBgqFvdSjTM2QDksQNmLWO0K9MmPLUPD4OTkpBZq0tfHrTmFnw5cN6iPd8ID8WFEkEFtGEwBClCAAhSgAAUoQAEKUEDrAutO3sY7S48ZtIy65byxYkADg9oYE/zO0qNYd/KOatNZPWujffUSqnEMYAGYrwHjBVgANt6OLW0oIEMBODElHdXGb1ZV3DMiHKW9LXsAm7LlgrL1gtq1qG9dhFUsphZm0tdf/+EQ9lx8YFAf3UP8MLV7DYPaMJgCFKAABShAAQpQgAIUoIDWBX7YexUT150xaBnFvPLg8KiWBrUxNPhO/FPd2S7Kg0+iq0RBDyi/87q6OBs6hEPGy1ALccjE2cGiWQC2gyRwCoYLyHDTu5eQgrqTt6ku/uiYVvDO564aZ0rAjnP38MbCw6pdhAcVw49v1FWNMyWg8efbcfPRU4O6aFqxGH7qa9l5GTQhBlOAAhSgAAUoQAEKUIACFLCCwJQNZzFv1xWDR4oe3xpeHm4Gt9O3wRcbz2H2zsuq4SPaBGFQs0DVOAb8JSBDLYS5tI0AC8C2ceeoJgrIcNO7+iAJ4V+qb9Z/bmIbeLi5mCgmbp6Vla3bBuLKgyTVcbZ/0BTli+VXjTMmICX9rxNss8VvEv+n60q+Xtg4JMyYIdmGAhSgAAUoQAEKUIACFKCAZgWGLj+OVcduGTz/P95phOp+ljlrRvm9rsGUbXikcuC5h5szDnzUAoUt/MCTwTh23ECGWogd80o9NRaApU6vvIuT4aZ3+nY82s/YK0ySst3ulcntLL7vrjIJfQ9fe62+PyZ1qWaRF9f5u4mImLbb4L6VJ6SVJ6V5UYACFKAABShAAQpQgAIUcCSBnt8fxP7LDw1e8vRXaqJzzVIGt9OnwdJDMRi5Klo11FqH0alOREMBMtRCNMQt1VRZAJYqnY6zGBluekeuxeHFueLTWvO5u+D0hDZWSeyT1Aw0mLwNiakZwvFcnZ2wZVhTlCuaz+zz2hB9BwOXHDWq3wuT2sLdlftGGYXHRhSgAAUoQAEKUIACFKCAJgWUT3IqB3sber3XogKGtapoaDPV+OS0DN0nXWMTUlVjNw0JQ5Cv5Q48V52ABgNkqIVokF2KKbMALEUaHW8RMtz0lEPXlMPXRFfR/HlwZLRlN+d/dnzl8ADlEAG1q22wL+a8FqIWZvDXZ+24hKmbzhvcTmmw76PmKFUor1Ft2YgCFKAABShAAQpQgAIUoIAWBaqN34TEFPFDPDmtq2ONkpjZo5bZlzxj20V8veWCar+NAotgyZv1VeMY8LyADLUQ5tQ2AiwA28ado5ooIMNNb+Opu3j75yihhL+3J3aPCDdRS//mMQ+T0fTLHXrtwfvb2w0QWtZb/871iPxgxQn8fvSmHpH/DVk5qCFq+xc2qi0bUYACFKAABShAAQpQgAIU0JrA07S/zlAx5qpasgD+fK+JMU1zbXMvMQXNpu5Eclqmar/ze4WiZZXiqnEMeF5AhloIc2obARaAbePOUU0UkOGmt+rYTQxdfkIoYYvDzd5eHIWNp++qZqhm6UJYNaihWfcn7jp7H47GPFYdO6eAua+FoE2wr1Ft2YgCFKAABShAAQpQgAIUoIDWBK4/TELTqeoHi+e0Lk9lu8FPIsz6+9zHK6OxLDJGlVHZTnDrsKZwcXZSjWUAC8B8DZhHgAVg8ziyFysLyFAA/vngdYxefUooV9u/EFYOamRV3Uv3lIPY9iAzK1t13G971kKH6iVV4/QNqDlhMx6rnBSbW18TOldFrwZl9R2KcRSgAAUoQAEKUIACFKAABTQtEHk1Di/NE58rI1rgwY9bwLegh1kMLsQmos203dDj10jMfrU22lUrYZZxHa0TGWohjpYze1kvC8D2kgnOwyABGW563+++gk/XnxWuu3FgUfz8Zj2DbMwRPGpVNJYcUn/ntrR3Xt07t3lcXUwe9lFSGmpN3GJ0P4PDAzA8opLR7dmQAhSgAAUoQAEKUIACFKCAlgTWnriNd5cdM3rKS/vXQ8OAoka3f7bhGz9GYsf5+6p9KQ85/T7QvJ8kVR1UogAZaiESpUNTS2EBWFPp4mT/FpDhpjd960V8s1W8OX6rKsXxfa9Qqyf+fmIqmk3dgSQ99m4a3b4y3mxS3uQ5Rl2PQ7c5xr973T3ED1O71zB5HuyAAhSgAAUoQAEKUIACFKCAFgSUA7yVg7yNvSZ1CcZr9csY2/yfdnsvPsBrPxzSqx+l+BtShme36IWVQ5AMtRBj1852pgmwAGyaH1vbSECGm96UDWcxb9cVoWDnmiUx/RXzn8yqT9q+3X4RX25WP721gIer7qC6Qp7u+nSba8yvR25g+G8nje4jrGIxLOpb1+j2bEgBClCAAhSgAAUoQAEKUEBLAlPWn8W83eLfKUXr6de4HMZ0qGLSkpWtAzvM3IuzdxJU+2lfrQRmvVpbNY4BuQvIUAthfm0jwAKwbdw5qokCMtz0xq45hUUHrgsletQtjSldq5uoZVxz5UTZ8C934m5CimoHPev5Y/IL1VTjRAFfbDyH2TsvG92HLQ7MM3qybEgBClCAAhSgAAUoQAEKUMBEgSG/HMPq47eN7qV5JR8s6FPH6PZKw8UHrmHMmtOqfbi5OOm2DyxTJJ9qLANyF5ChFsL82kaABWDbuHNUEwVkuOl9+OsJ/BZ1UyhhjndkTaE25Kncxf3qokmFYkYP9/biKGw8fdfo9t753HF0TCuj27MhBShAAQpQgAIUoAAFKEABLQn0/P4g9l9+aPSUyxbxxM7h4Ua3vxGXjIhpu5Gsx9aBtv7d1uhF2llDGWohdkbqMNNhAdhhUi3XQmW46Q1aEoX10eKC57vNA/FB6yCbJc+Qj/OULOiBTUPD4OXhZvB8s7Ky0fKbXbhyP8ngts82uDCpLdxdnU3qg40pQAEKUIACFKAABShAAQpoQaDFVztx2YTfoVycnXByXGvky+Nq8HKV3+F6zj+Ig1fiVNuaa9tA1YEcIECGWogDpMkul8gCsF2mhZNSE5Dhptfnx0jsVDkldUSbIAxqFqjGYdGvG7Kh/yt1SuOzboZtWfHwSSqGLD+OPRcfmLyOfR81R6lCeU3uhx1QgAIUoAAFKEABClCAAhSwd4Fq4zchMSXDpGlWLJ4fs1+tjUAfL4P6+Wn/NYz7Q33rB6VTcx0cbtAEJQ2WoRYiaWrsflksANt9ijjBnARkuOm9NO8AIq+K3y0d37EK+jQqZ/MXgT7F6r8n+VPfumhaUb+tIJT1v7vsKGITUs2yxpWDGqK2P0+UNQsmO6EABShAAQpQgAIUoAAF7FYgOS0DVcZuMsv8PN1d8OkLwXihlp9e/V17kIS20/fgaXqmanxp77y6vX/zuLqoxjJAXUCGWoj6KhlhCQEWgC2hyj4tLiDDTa/jzL2IvhUvtPqiW3W8VKe0xT3VBjDkG7xvgb+2giiYN+etIO7Gp2B99B38GX0HUdcfqQ1t0NfnvlYbbYJLGNSGwRSgAAUoQAEKUIACFKAABbQmoPyO1uzLnWaddgWf/OhQvSTaVy+BQJ/8OfatbP3wyncHEXlNfesHpQNDHhAy62Ik7UyGWoikqbH7ZbEAbPcp4gRzEpDhpqfPfk0ze9RCxxol7eJFsHDfVYxfe0avuXQP8cPU7jX+ic3Ozsam03exYO81HL4eh+xsvboxOGhC56ro1aCswe3YgAIUoAAFKEABClCAAhSggJYElE9TKp8qtdRVydcLPev5o0ddf7i5/P9zVhbsvYoJ6/T7vdCYLQIttR5Z+pWhFiJLLrS2DhaAtZYxzlcnIMNNr+GUbbgdnyLM6A+9Q9GicnG7yLryTm+P7w/ikMq2FX9P9u99nh4lpeG9X46ZZY9fNYjB4QEYHlFJLYxfpwAFKEABClCAAhSgAAUooGmBtSdu491lx1TX4OwEZJnwAI7yVPC810NQvlh+7Dh/DwMWRSEtM0t1XFMOCVft3IEDZKiFOHD6bLp0FoBtys/BjRWQ4aZX45PNiH+aLiRY1r8+GgQUMZbJ7O1iHiajzfTdSE5T3+tJGXxA0/LYeOourj9MNmkur9bz1/3QsiwyRtjPiyF++PKZJ49NGpSNKUABClCAAhSgAAUoQAEK2KnA/D1XMOnPs8LZ1fYvhK61/TB69SmTVlHAwxX9m5THzO2X9Cr+KoP93K8eGlcoatK4bPxfARlqIcyrbQRYALaNO0c1UUCGm17FURtUv3muGdwINUoXMlHLvM0XH7yOMSb+AKHvjJR3q4e1qohBzQIxY/tFTNt6Udg0rGIxLOpbV9/uGUcBClCAAhSgAAUoQAEKUECTAlPWn8W83VeEc29T1RdzXw/BHydu4+PfTyJJzwd5TAVRHuD59IVqpnbD9jkIyFALYWJtI8ACsG3cOaqJAlq/6WVkZiFw1AZVhS1Dw1ChuJdqnDUDlK0gXl9wCPsuPbTosMW88mDGK7X+eQJaefr345XRwjGVfao2Dgmz6LzYOQUoQAEKUIACFKAABShAAVsLDPnlGFYfvy2cRu8GZfBJ52BdzJX7TzBoyVGcu5to0an7Fc6r+50sfx5Xi47jqJ1rvRbiqHmzh3WzAGwPWeAcDBbQ+k0vISUd1cdvVl333v+Fw6+wp2qctQNuPkpGxDe7LfYOcqPAIpj2ci0oReC/r+3nYtF34RHhUgt7uuHY2NbW5uB4FKAABShAAQpQgAIUoAAFrCrQ47uDOHBF/FDO8IggDA4P/GdeKemZ+GTtaSyLvGGxuS7tXw8NA7j1g6WAtV4LsZQL+1UXYAFY3YgRdiig9ZtebEIK6k3epip7dEwreOdzV42zRcCKwzcw4veTZh3azcVJ9wPKu80rwEXZ/+GZ69SteHSYuVd1vPOT2iCPq4tqHAMoQAEKUIACFKAABShAAQpoVaDFVztx+X6ScPpTX6yO7qGl/xOz+tgtjFlzCokpGWZdfp+GZTG+U1Wz9snOnhfQei2E+bSdAAvAtrPnyCYIaP2md/VBEsK/3KkqcG5iG3i42W8x8/ON5zBn52XVdagF+BbwQPvqJaD8wFDaO+cnnu8lpqDup+pFc3t9alrNgF+nAAUoQAEKUIACFKAABSigr0C1cZuQmCou4CrnoyjnpOR0xSenY9GBa7r9gS/ee6LvsLnGtazsgzmvhcDNxdnkvthB7gJar4Uwt7YTYAHYdvYc2QQBrd/09HmaVXkA9vLkdnByev5JWBPYzN40OzsbUzedx2wjisDKdg2da5ZCh+olUNu/MJz/9cTvvyebmZWNiqM3QPlbdP0+sCFCyhQ2+1rZIQUoQAEKUIACFKAABShAAXsQSE7LQJWxm1SnsmlIGIJ81c+UuRCbiHUnbmPlsVu4+eipar//DmhVpThm9awNd1cWfw3GM7CB1mshBi6X4WYUYAHYjJjsynoCWr/pHb4Wh+5zDwjBlE3zT30SYT1UI0dSisBfb7mAmdsv6d1DcKkCmN+rDnwLeujdRgmsN3krYhNShW3mvlYbbYJLGNQvgylAAQpQgAIUoAAFKEABCmhF4NqDJDTT4xOlx8a0QmEDthRMSs3A0OXHsflMrN4UEVWLY2YPFn/1BjMxUOu1EBOXz+YmCLAAbAIem9pOQOs3vV0X7qP3gkghoHIA2uFRLW2HbMDIShF42taLmL7tomqrdtV88WX3GvB0N/xU2E7f7sXJm/HCMT7pVBW9G5ZVnQcDKEABClCAAhSgAAUoQAEKaFHg0JWHePm7g8Kpu7s4QzkfxdBPlGZlZePLzfp9ylP53W76K7W47YMVX0Rar4VYkYpD/UuABWC+JDQpoPWb3sZTd/D2z0eF9mWKeGLX8HBN5Wf61ov4ZuuFXOf8XvNADGlZUXW7h9w6ePOnI9h6Vvxu9ODwAAyPqKQpN06WAhSgAAUoQAEKUIACFKCAvgJrT9zGu8uOCcP9CufF3v8117fL/8StPHoTH/0ejbTMrBz7UM5wmfZyTRZ/jRY2rqHWayHGrZqtzCHAArA5FNmH1QW0ftNTvpkOW3FC6FbJ1wsbh4RZ3dbUAVccvoFP1p5GUlrmP135eOXBuI5VdQe9mXKNXBWNpYdihF28GOKne8KYFwUoQAEKUIACFKAABShAARkF5u+5gkl/nhUurbZ/Iawc1Mik5R+NeYSPfj+JC7H//5A4F2cnDGwagCEtK8CVB76Z5GtMY63XQoxZM9uYR4AFYPM4shcrC2j9pvfzwesYvfqUxb9hWzkt/wx3PzEVB648xM1HyfD39kR4kA/y5TF8y4d/z1/tCWMlvkmFoljcr56tls5xKUABClCAAhSgAAUoQAEKWFRg8vqz+G73FeEYbYN9Mee1EJPnkZGZhd0X7+PSvScomNcNDcoXhX8RT5P7ZQfGCWi9FmLcqtnKHAIsAJtDkX1YXUDrN73vdl/G5PXnhG4sZP6XZ1lkDD5eGS100+qT01b/n4gDUoACFKAABShAAQpQgAKaFBjyyzGsPn5bOPfeDcrgk87BmlwfJ527gNZrIcyt7QRYALadPUc2QUDrN71pWy/oDk0TXa2rFMd3vUJNUJKv6fZzsei78IhwYV4erjg5rrXBhx3Ip8UVUYACFKAABShAAQpQgAIyCrw07wAir8YJlzY8IgiDwwNlXL5Dr0nrtRCHTp6NF88CsI0TwOGNE9D6TW/K+rOYp/KRnS41S2LaK7WMA5K01ZnbCWg3Y4/q6o6Mbomi+fOoxjGAAhSgAAUoQAEKUIACFKCA1gRCJ23Fgyepwml/1b0GuoX4aW1pnK+KgNZrIUyw7QRYALadPUc2QUDrN70xq09h8cHrQoEedf0xpWs1E5Tka5qcloEqYzepLmzFgAaoW85bNY4BFKAABShAAQpQgAIUoAAFtCSQkJKO6uM3q0555aCGqO1fWDWOAdoS0HotRFvacs2WBWC58ukwq9H6Te+DFSfw+9Gbwnz1a1wOYzpUcZic6rvQBlO24U58ijD8s67V8Epdf327ZBwFKEABClCAAhSgAAUoQAFNCBy/8RhdZu1TneuJsa1R0NNNNY4B2hLQei1EW9pyzZYFYLny6TCr0fpNb9CSKKyPvivM17vNA/FB6yCHyam+C311/kHsu/RQGP5WWHmMbFdZ3y4ZRwEKUIACFKAABShAAQpQQBMCK4/exLAVJ4RzLZLPHVFjWmliPZykYQJar4UYtlpGm1OABWBzarIvqwlo/abXe0Ekdl24L/Qa0SYIg5px0/5/I41dcwqLDoi3z2hRyQc/9KljtdcjB6IABShAAQpQgAIUoAAFKGANgambzmHWjsvCoeqW9caKtxtYYzocw8oCWq+FWJmLwz0jwAIwXw6aFND6Te+luQcQeU18ausnnaqid8OymsyPJSe9cN9VjF97RjhEuaL5sOPDZpacBvumAAUoQAEKUIACFKAABShgdYGBP0dhwynxp0lfqVMan3WrbvW5cUDLC2i9FmJ5IY6QmwALwHxtaFJA6ze9DjP34NStBKH9Fy9Wx0uhpTWZH0tOeveF++i1IFI4hIuzE85OaAN3V2dLToV9U4ACFKAABShAAQpQgAIUsKpAxDe7cT42UTjmyHaV8FZYgFXnxcGsI6D1Woh1lDhKTgIsAPN1oUkBrd/0mn+1E1fuJwntv+1ZCx2ql9RkLdeP9QAAIABJREFUfiw56ZuPktH48x2qQ2wd1hSBPvlV4xhAAQpQgAIUoAAFKEABClBACwKZWdmoPHYj0jKyhNOd3ysULasU18KSOEcDBbReCzFwuQw3owALwGbEZFfWE9D6Ta/BlG24E58iBFvQJxTNK/Gb9r+RsrKyUWXcRqSki3/omfd6CCKq+lrvRcmRKEABClCAAhSgAAUoQAEKWFDgRlwymnyh/jCMsh2esi0eL/kEtF4LkS8j2lkRC8DayRVn+oyA1m96NT7ZjPin6cKcLutfHw0CijDvOQi0nb4HZ++It9D4X5tKGNiMH3viC4gCFKAABShAAQpQgAIUkENgx/l7eOPHw8LFuLn8tR2eqwu3w5Mj68+vQuu1EBlzopU1sQCslUxxns8JaP2mV2HUeqRnZguzumZwI9QoXYiZz0Fg8NKj+PPkHaFN9xA/TO1eg34UoAAFKEABClCAAhSgAAWkEPhh71VMXCc+EDugWD5s+4AHYkuR8BwWofVaiKx50cK6WADWQpY4x/8IaPmml56ZhQqjNqhmdeuwMAT6eKnGOWLA15vPY8b2S8Klh5QpjN8HNnREHq6ZAhSgAAUoQAEKUIACFJBQYNSqaCw5FCNcWasqxfF9r1AJV88lKQJaroUwg7YVYAHYtv4c3UgBLd/0lK0flC0g1K59HzVHqUJ51cIc8utrjt/C+78cF669kKcbjo9tbRWfozGPsOv8fSSnZaBs0Xx4oVYpeLq7WmVsDkIBClCAAhSgAAUoQAEKWE8gIzML60/d1W1Jp5xPUj+gCMIqFIOLs5PFJ9Hju4M4cOWhcJy3mwbgo7aVLD4XDmAbAS3XQmwjxlH/FmABmK8FTQpo+aZ3Nz4F9adsU3U/NqYVCudzV41zxIDom/Ho+O1e1aUfHdMK3iYaXr7/BMpT2z5eHv/pKyU9E+PWnMbyIzeem0vR/O6Y1CUYbYJLqM7x6oMknLjxGA+epKKWfyFUK1UI7q7cr0sVjgEUoAAFKEABClCAAhQwUkAp3J67m4gj1+Pg7uKM4FIFUbVkATg5iYu4ys/tw1Ycx+X7Sc+N3CiwCKa9XAvFvPI89+9PUjNw5/FT3fZ/lXy94Gxikbjup1txLzFVuOovXqyOl0JLGynDZvYuoOVaiL3byj4/FoBlz7Ck69PyTe/K/Sdo/tUu1cycm9gGHm4uqnGOGKD8IBU8bpPq0n97uwFCy3qrxuUUsPfiA0z684zuB0PlcnV2QvdQPwxtVVFXDE7LyMKAxUew4/z9XPtX3n3/sHXF/xzAoBSUN52+i0X7ryPyWtxz7X0LeKB/WHn0qFuaTxEblTk2ogAFKEABClCAAhSgQM4CytO7f0bfwewdl3E+9q+f8/++An3yo3eDMuha2w/58vz303y/RMZg7JrTSMvMyrHzCj75sWJAA91DPE/TMjFn5yUs2HcNyu8uyqV8uvO9FoF4uY6/UelJTElHtfHqnyT9fWADhJQx7ncgoybGRlYV0HItxKpQHOw/AiwA80WhSQEt3/RO3YpHh5nip1eVN4YvT26n+g60JpNnpknXm7wVsQkq7353q46X6hj+7veOc/cwYHFUjj/cFS+QB7NfrY0f913DOpWD6JSlKk8DzOxRW/eRsJiHydh5/p5u3667CSlCicKebnijUTn0blAWBT3dzKTGbihAAQpQgAIUoAAFKOB4Ason936Luonvdl9BTFyyEMArjyteDPVD+2oldNu75c/jik/WnsayyOc/9ZdTJ9X9CkJ5AnfY8hM4cychx3FGt6+MN5uUNzgJJ28+Rqdv96m24ydJVYk0HaDlWoim4SWYPAvAEiTREZeg5Zte5NU4vDTvgDBtyg8Zpz6JcMTU6r3mnt8fxP7L4v2vBoSVx8ftKuvdpxKobNHR+ptdSEj56516c1zK08MZWdlGdZXP3QV9G5fDoGaByOvOJ8KNQmQjClCAAhSgAAUoQAGHFMjMysayyBhM33YR91W2TsgNyJSf5XPqU9ll4tcBhn9ScfWxWxiyXHwOirL9nbINHi95BbRcC5E3K9pYGQvA2sgTZ/kvAS3f9JQnQPv8eFiYUx+vPIgc1ZJ5FwiMXh2Nnw+KT8BtWbk45vfW/wTc7Oxs9FoQiT0XH9idvV/hvJjYORjhlXzsbm6cEAUoQAEKUIACFKAABexNQPnk5ajVp3TnbdjbVaaIJ9a/1yTHrSZym+vXm89jxvZLwqWElimM3wY2tLflcj5mFNByLcSMDOzKCAEWgI1AYxPbC2j5prch+g4GLjkqRCxbxBM7h4fbHtqOZ7Bg71VMWHdGOMPyxfJh+wfN9F7F4oPXMWb1Kb3jbRHYNtgXYztWQYmCeW0xPMekAAUoQAEKUIACFKCAXQsoe+V+s+UiFu6/CiM/hGeV9b1azx+fvlBN77EGLzmq279YdL0U6ocvXqyhd58M1J6Almsh2tOWa8YsAMuVT4dZjZZver9H3cQHv54Q5qpyiQLY8H4Th8mnMQvV50lq5eNaZye2gZuL83NDKIcyKHtyxT9Ng793PgQUy4drD5PRbvoePE3PNGY6Vm+j7Cns4eqsOygwv4cr/L09EVAsv24tyt/KIRbKKcRqJxlbfeIckAIUoAAFKEABClCAAkYKPE5Ow+X7T3D5XhIu6f5+gqsPk5DwNAOp6ZlIychEeqZxW68ZOSWTmv34Rh2EB/ng1uOnuHTvCdxdnFG5hBcKebr/p98203b/c0B1boN+1LYSlIOoeckroOVaiLxZ0cbKWADWRp44y38JaPmmp89TpiFlCuN3fnRH+Lq/EZeMJl/sUP1/Y9sHTXUn7kZdf4SDVx7iwOWHOHHz8XM/GCp7ZcUlpan2pbUApQBcv3wR1C/vrfu7fNF8LAhrLYmcLwUoQAEKUIACFHBggTvxT3U/wx+6Eqf7W3loQ7argIfrc+ePKHsEV/YtoPv5vUFAEdQt6w0vD1dUGbcRKelZwuV/3ysUraoUl42I63lGQMu1ECbStgIsANvWn6MbKaDlm953uy9j8vpzwpU3qVAUi/vVM1LHMZplZWWj8tiNSM0Q/xBU2NMNSWmZSFOJcwQ1pSBcwSc/fAt4oHhBD93fJQp6IMjXS/cEsSxPC998lIyDV+Lg6e6CaqUKorS3pyOkl2ukAAUoQAEKUEBigUdJaTh0NQ4JT9NRvXRBBBX3kuZnt3sJKTh9JwG3Hz9FbHwK7iYof1Jx9cET3Ih7KnFW9VuaUhBW8n3ubqJqA+XhF+XTgLzkFdByLUTerGhjZSwAayNPnOW/BLR80/tmywXdKbSiq3WV4viul/6HlznqC0Sfj0E5qo2h6y6a3x21/Aujtn9h1PIvBOUgQmVrCa88bvBwc7b5LxjKAX3Kyc33ElN1T0D4eHkgr7vLc8s8FvMIUzedx/7LD//5d2WrjJfrlMYnnar+ZysQQ40YTwEKUIACFKAABWwhMHfXZczcdlH3UMPfV8Xi+fFB6yAovzc8+yZ+emYWYhNS8Dg5HQXzuuk+Cefs7GSLaT83ZmpGJp6kZOBJagYeJqXh5I3HOBqj/HmEm49Y5DVHgnLb/s4cfbMP+xHQci3EfhQdcyYsADtm3jW/ai3f9CavP4vvdl8R5qBLzZKY9kotzefJ0gsYtCQK66PvWnoYvfsfHhGEXefvI/JanN5tlGJr7wZldT+gz9l52aC2eg9iYqDyw6RSdC2aP49uX2Hdn/x54J3fHXndXP764+6i249Yeeq2gIebbj0FlD8ernD91x7MSjFXuXJ74lh5WvvI9Tgci3ms29dN2eftyv0kJKZm/LMSZX+0+gFF0KKSD6qULID5e65g0+nYXFf6Yogfpr5Y3eaFbBNTweYUoAAFKEABCjiYwA97r2Ki4ODj2v6F8H7LiniQmIrt5+5h94X7z/3MlMfVGeWK/nVGhHJWRHW/QrptBfLlcc1VUvlZ7d8/pymfvktMyUBCSjrin6brnkRWirkpGVlIScvUnaOh/HmUnKZ70/7vPw+epOli0zLFn9qzRVoVj4HNAnU/2y7afw3bz9/D//2YqjqdMkU80b9JeUxYe8Zu1qZs97b9Q/0PwFZdJAPsUkDLtRC7BHWgSbEA7EDJlmmpWr7pjV4djZ8PxgjT0bOePyYbcCKsTLk1ZC1fbT6PmdsvGdLEYrFK8XdweCCUpy5mbLuI+Xuu5nignLLfsLLdQmiZwuhYoyRqlC703JwOX4vDlPVndU9EyHIpxdpsZOtOYc7Kztb9YK0UjcsXy4fgkgURXKoAlIMPlT3dtp+LxZ4LD577xcVcDvNeD0FEVV9zdcd+KEABClCAAhSggEUFlDfBlU+8mftQs7/fSG8eVAzV/Arp3mw/fSsep24n4EJsoq7Qq1zKg8POTk66P+lZWXoXRy2KYobOlZ/FP25bSfdz4bNPR19/mISVR2/h0NWHuPYgWbcVxb8vxaRrbT+M6VBF98DDptN3MWjJUWQqP+ja+GpZuTjm9+anSG2cBosPr+VaiMVxOIBQgAVgvkA0KaDlm96wFcd1P1iIrjcbl8PoDlU0mRtrTnrVsZsYuvyExYdU3uH/snsNKLn79z5kyp5cw1pWxDvNA597UuLhk1TdVgTKUxLKD4dli+SDfxFP3dOxapfyhMUvh2/gsw1nnzsQQq0dvy4WUD4CuXVY0/9sHUE3CjiSgPLUlnKgTlJqJpLTMnR/P03/6xd93wJ5UbVUAb3uU45kxrVaRiAlPRNn7iRAOdRVKW7lc3eBZx5X3SdJlD/FC3igSD53fnLDMvzsVQMCylO4vRZEYs/FBxqYrTam6ObihLebBuge2lA+uaZ2PU3LRExcMq49TMKDJ6nIn8cVNfwKoWzRfM81/fPkHQz/7QSSn9miQwlQPkH39Us1oRwCrjyZbelrQFh5fNyusqWHYf82FtByLcTGdA4/PAvADv8S0CaAlm96A3+OwoZT4m0L3mseiGGtg7SZHCvO+sSNx+g8a59FR1QKvL8OaIDQst5QflldfOA6dl64hweJaajmVxAvhZZG3XLeFpmD8oPm5D/PYuUx8RsGFhlc0k7fbR6o2y+PFwUcRSAjM0v3iQLlY8E7zt3D+Vj1A2SUjworBygqfxoFFtVts8KLAqYKKAd07jh/H9E3H+PkzXhcvPdE9Yk55Y278ErF0LySDxqUL8o38ExNAttrSmB99B3dk6W8zCNQv7w3JnWphkAfyxyQpjxFrWwjcfjaI12huFaZQhgQFgDl039341PQ+ptdFn+w4/Nu1fByHX/zgLEXuxXQci3EblEdZGIsADtIomVbppZver0XRGKXyjvA/2tTCQObBciWNrOvJzElHdXGbzZ7v892qDwl8FHbShYdQ63z/ZcfYPrWi1C2h7CDT5epTdeuv6585HHz0LD/PLmhTFoplG0+E4vTt+N1a2gYUBT1yxeBcpCcsZfypoHydJvylIm9HMJi7FrYTjsCylY0287GYt3JO7onjhL+76O8xq4gpExhTH+lJvwKexrbBds5sEBSaobuyTjlzW9999bMiUvZx1TZt7RtsC86VC8p3L/Ugbm5dDMLKE/hKgfQKvvaKt/HvfT4JFduU1D6ir4VrzsvQjnMrWwRT3SqWRKe7v/di1f5hEaLr3bhTvx/tyAw8xKl766Sr5fu96pONUra9BMFa47fwvu/HLeo969vN0CdspZ5MMWiE2fnBglouRZi0EIZbHYBFoDNTsoOrSGg5Zte97n7de8Mi65POlVF74ZlrUGp+THqfLpVd8iEJa6Wlf9fe+cBZkV1vvEPWJbeYUVERBAbsQYboKKoiGLDGjRqTBQl/jU2TNRYEk3EGlNs0WCLgBqViAWwI2AXBUUFAQGR3uuyC//nPctsLsveunPn3rnzO8+z3Mu9Z075vTNzZ9455zsl9o+z97d6RcmniGWj/qplykzUqOD1Gze50chaTVlTzbRyshZLm76oYsE0/b8mN9lB9CWXdfTarY0NPf+ArW4Cxk1bZNe/MMVN84tNujkbeHhn67//Dm4/kEn82ZzlzlTTaA7x36FFA7eoihZXUUw5jWp7f8YS9zdpzvLKuH3NG9a1Qzq1su6dW9khnVu7beIthJeMj7RfsrrU7Q961Y2pjGqFGGnaoGjLa11r0bDYiotqJyuO7wuEgFZ9H/bhbPe3YKW/50UZH88P6u6m5ZMgkCoBnavOeeSDpNc9qZbn5WtSr8hO/Wl7O+fgDrZLSZN0Nyd/SAkoxurSNaUuvJYWFdPDLbe4WNkmt/Bsq8bFbpFaLVqrxWkzTQqTM2H6EhfKa+J3i23eFhNWs8L23L6pezisv73bN7OFKze4a6/pC1fb90vXmkIMqH793uuBhR4AK7TX61MX2APvfOcWuI1NChN2/XF72Ond2m91TTDkta/d4sCk+AS2a1pvy8J2FYvb7dS6kRt5W79IixPXdtdtLRoVu8/yIekBwO2vfW0PvZN4MfCatPWTG46yVo3r1aQItg0BgTB7ISHAW9BNxAAuaHkLt3NhPukd/9dx9uW8lQnFueO0vV1oAVJyAmc9PNHen7E0ecYtObT42FXH7OouymVofDhzqbvAHz99sTPulEqa1HP8Lz+qi9WtEz7zTDE+P5611BmQH8xcalN+WMHI4Sp7iLcgnFjd9vJX9szHcxPuQ9onunVs4faV5Ws3pry/JcrYunGxtWvewN0o6r1eNU1QNyqN6xe5V+2vGv0zY/Eam+n+VtvsJWtTHtEpU1g3Rbph7dqumZvKv1vbJtXG1dSNtUYr6yZ23op1tmHjJivbpMX7NltZ+WYr37zZ6tauZfXqVtxUaTSe3jdvUGzbN69v2zdrYE3rF211A6ubnVUbyioXk6mjhWRqm+m1qHbF9ionUyPc46t6tLq4RnjXtCxfxPWpEJkGMveXa6X19YrXW+ZWXF9TWub+v3pDeeVn3vT6bC5Cc/iubeyxX2z98MSnrlJMgRL486tTs2p2CJvCMGmEXyOdO7f8VbyvY43r1bVG7rXIxePXObYohL/r8XYP79xXt3btrRayynR3kpG6bmO5C82hP53/vVcx1OjXqrNiNFJ13vL1Lra4zFn9dqwvK3evegBQWr7ZLSRWVLuW1ald24Rf11Z6mKSp+FojoeqDSvVL5u70havsq3kr3XWz/hTCRm1MJSmOdPsWDUwhbXZu3dg6tW5k7Vs2cP3R+VO/TXpdvrbUFq0uNa3doIeqenj2w/J1qVSRNE/9urWtR+fW7uGyd40Zb6NDu7R2C0Dv2LKhM5SzsfBb0gbneQZdz8h4P0gG/M4trSSEDyS1bz/1wWx7bPxM+27RGke8XbP61n2X1tZzl9ZukIAGF+gaXgtdp7MvaqDBZ78/uqCug/J8l8xZ88LsheQMGhU7AhjA7AihJBDmk96Rd73tzJxE6R8D9rfj994+lNoE3ejrXphsT38wO+Vq7zh1bzvjgOrNdU2b1s2AFmwopBtEjZSZMneFu4jUCEGtaDx/xQaTYaSVnqMaVuL4vbZ3YTU0tTNqSUZpmyb1rKRpPWvZsNjtGzovpXpjHY+XFnFq26y+u8GWua4b+GSGpMyEhnW1+FMda1Rc5EZt6VX/1w28Rk85U6K0YsT72o3ltq60zJkU3md6r1HvMhlkUGgUdJN6dZ2RbpvNNpRvso1lm0zHuP7cBVCtWqbRXArwodXNVZe21fHvGR0tG2lEWT1nmOtVBpJMWBmyMg30MECGrMqRqa2+VKyWbs48V9/1qjr1XgtdaRS5PivbtMkZ6/qsfNMm26jPymW+bLLFqzbYotUbnJmSjF/Q++5tp/zEzj5op6Crpb4QEtD59YyHJubVjBQdq5oZ4T1007EuM7KoTsVDKZmUeq/PdDy798601Gf6/5Y8tWvp1FJplOoBmc5BemgnE6bir9jNxtA5Y8kamYsyGUtt6ZoN7qGY+3MPyDa6PDrWVab+kfGqpHqLi+pYcR29VrRDCzdqG2/0q84nSjIbFUpAbdB5VOc0va9YVK/IPXDTuVTnUdXnzqelFa/6v86jOh8lSuKn0dfNGtZ1Zev3s6YPRdUnLbYrI1jXYAtWrXfXKprtFLUkrY79Sduki0UXMhftCzLt2zat7x4S6Jpi+2b13QPskiaFMwNFRrCOHV3rxJtp+Mn3y9w5NNXrgP07NLfnB/Uo5N2Dvm0hEGYvBBFzSwADOLf8qT1DAmE+6R38pzecAZcoaXr6EbuXZEgnWps9Mm6G3fry1JQ6LcPv7wP248l4DC2ZV1pM79Pvl9mns5e5ETYynbwbypTAkgkCEIgMAZk+r15+aLVxtCMDgY4mJaDflr73vWtzlvozkjJphWSAAARCRUAPSvWQpEtJY9t/pxb20w4tbL8OzQlfUEXFv70xze4e+21K2p720/Z21+n7pJSXTOEmEGYvJNzkw996DODwaxjJHoT5pLf3zaOTTt8eftHBbooTKTkBrWr/i8c+SppR4R5euexQN2qFlJiARiVsKNvkRifpJl4jjWQKK9ayRiW611Ub3HeKRawRixvca7kbvaORn34YyBrtpBh6WoBK8XU7tWnkpkZ+MXe5vTF1oVvkataS/8Xs1citvntt7+pXjF4SBCCQHQI6Jp8ZeEiNFkjMTssoNV8I/O75yS4WNQkCEMgOAYXPUFgezYLT9ZeXFE6q9+4l1nuPEju4cys3o0ShBmYsWm1fzF1h705bVBmWqSYtk4GruMuaNeNGndetY/W2vGoks9qhmUbuTzNpGhdXzNDRLJst2xRSyKaasEy0rUb//uyf77uQdcnS4GN3s0G9dkmWje8LgECYvZACwB/qLmAAh1q+3DR+5MiR9uSTT9pHH31kCxYssKZNm1rnzp3tlFNOsYEDB1qzZs2y3rAwn/S6XP9K0il2/720h+3dvnnWORZCBcvWlJoWgktkOOoidfhFh7g4gaTsE5CBrCmlCj3hzODyzVum2lfEf9XF7IxFa2zKvBX25Q8r3as3hVTT/HrtVuJuXrrv0qralbFjezBr8Rq36IoMaMWE0xT9FWs32hF3v+1MaxIEIJAdAud372iX9e7ipsjrxj+IeOmKiazwGzq2FRtZD6Eqwmh44T22fa+wGopBqjx6rynueu/OUesqzlEV4Uo2uin8ihGruJKK+y3jQlP49aCr4mFXRdgRvcb+X2UpKVyJN/1er+7/xbUrzZH6xXVsfWm5mzavPz1IU8xR/X7JRNH5S3+qUwaJYm6La92i2pXvFYJAoQj0gEwhC/Te5dnyuV5Vr/qhvxYN6wYS0kjndYUTkB5jv1pgg//zRXZ2PEqFAATcw7dR/9fT9ti+qTsXab0Hnd+0rsBu2zVJGA9a5z+FFnjz64XuT3H/lWTaar2An+xQsV6A4morNIHCkehP50eFAHHnqAZ1rXFxkS9xp5EzOYF5y9e5mNAK+5IoPXvxIXZAR+51khMNf44weyHhpx/uHmAAh1u/QFu/atUqGzBggI0aNSpuve3bt7cRI0ZY9+7ds9q2sJ70FHtt1xteTcrm9SsPY1XrpJT+l+GiJz62MV8tiLuFTIorj941jRLJGiQBLw6aIg/KsPAjPfPxHBv8HAaEHywpozAJyKDUQllaIEvvZapmGg9bJqRMg6P22M7OOWinGs+0kKEx9ceVNvmHFfb5nBX21Y8rXUxQxV2OaszymuyFGnEnM3v3tk1t7/bN3APmvdo3c7Gua5Kk0wuf/WCjvphnn81e7kz1TJLat0OLhs7I8mLTytwnQQAC1RP4RY+OdtMJXX3Bo4dfWrBP119VF/jzpQIK8YXAq5N/tEv+/WncshQ7+e2rexHmzhfa+V9IWL2Q/Cdb+C3EAC58jX3pYVlZmR133HE2duxYV952221nF154oe255562dOlSGzZsmI0fP95917x5c3vvvfesa1d/Lkyq60BYT3oambjPH8Yk1WT8b480hSwgpUZAo6hOe3CCfR8TDsDbsv9+O9gdp+0dyAio1FpLriAIaKTgqQ9OcKYECQIQMNPCfwd1aulG2B+5e4lbZKdqksmq0Zs3vDglY2QaRfazAzvYL3vu7EajVU164LNkTanNXLzGZi5aYwtXrXf/lwHthZr5btHqpDNlMm4gGzoCGsm3c6tGbpGllo2L3UKHMoBkFGsxLm8RptqaQlMlacT0vz/43oaOn+VGMWeaLjx0Zzvn4J2sQ8uG25gW2hff+WaRG6H43vTFbrQ3CQIQMBda4c2rD3czBUjRIvDA29/ZkNe+3qbTWphx+MCDrWu77M/CjRbx/O1tWL2Q/CUanZZhAEdH6xr19IEHHrBBgwa5MmT6vvnmm84Ejk1XX3213X333e6jHj16OBM4WymsJ70fV6yzQ/78ZlIsk2482i2MQEqdgG5CH31vpo2c9IO7UdST8DO77ehWq6/uBjb1kskZVgJTflhhJ/1jfMqrJ4e1n7QbAokIKF7vOQd3sGP2bOtG/KaS/Ijfqpjc3Tq2sOKiOiYLUYajQvbMWLzGl/iTqfSDPDUjUL9ubWcGyyRW0iwNGfh6sFZTQzadONKaPTV++mJnOr/x9UI3FZ0EgagSuPfMfeyU/dpHtfuR7/eYL+fbExO/t0lzlrtwP0fs1sYu7tXZrZVBig6BsHoh0VEof3uKAZy/2uRNy8rLy02hHebPn+/a9Mknn9j++++/TfuUr1u3bjZp0iT33WuvvWZ9+vTJSj/CetLTqKbed7+TlMk3tx7r4m6RIACBmhHQA4HfjJiUlmHQc5fWdvJ+O9jjE2a5KejVJZlbGk0pc2TWkjX23cI1Nn/l+sqsipGnmNNazPGgnVu6EY4TvltsE79b4sr0y8CQqdayYbFbXEVT4xXTVNM512/cVDNwbB1qAhqFq31Y4RgUyzHdpGn4fe8bZ7OX/m+RxXTLID8E4hHQ/vnq5YfaTq22HYWejNrcZWvd4nLDP5zjzquk6BJQ6BkvZrZiYmsGgfYJxaP2K3Vu08i6d25t3Tu3sp3bNLJJs5dB9GjSAAAgAElEQVTb+zOW2MQZS2zByv+Nfm/esK7t0qaxM+GWryu1cdMWxw2J0r5FA7vw0E721byVNuLjOWk1dVCvzjb42N3T2obMEIBA4REIqxdSeEqEr0cYwOHTLPAWa7Rv7969Xb2HH364vf3223HbMHToULvgggvc9+edd5499thjWWlvWE96WjxG5o8WStF7xctbu7Hc1m4oc++9BWb+cFJXYjhlZc+h0CgSeG/aYntswix765uFCW8MtQjT74/f007v1t4dfxrpNn76Ejeq/JPZy1y8zC4lTdzK2j27tN5m+uWq9RWLUzXQ6teN6sUdea7p09MXrrKFKysWgFq0utS9Llm9wY2MlPm2akOZrV5fcV6QWaIR7ZqSvXPrxu5VU6Y1VTveAk8byspd+Yqd+uW8le5G86t5K2zeiv+Z1PH2Bd1Uqw6N+pPRXae2FpvSay0rLd9kG8o2uUX31pdtcm1dsGK9ay8puwSki/ZBjeKNfa14XxHPV1OCFYtXDydqOj34o1lL7YyHJvr2sCK7dCg9TARuO+UnbnZOTZLOcR/NXGafz13uRpavKS2rPH+u2VDuRijrT+coveq8RcougXpFtV3YF8V01iCGenVru9fiIv2emlvsUOasXpeu2eAenOq6N1lSaJKu7Zq6Bcr0QEvv27doaKpPv9WxSeGf9Bur39S5y9a5GQczF692IWdmLV7rvtPIdp03tdCie61XZK0a1bPWTYpdeAXvr3NJIytpUjH6vWrS9YF+773f6FaN622VRfvnBzOW2htTF7jrfuVV2/t0bWvH77V9ZViycdMW2W//M9l+WL4uIYZuO7Wwsw/uYCfvuwP3B8l2GL6HQAQIhNULiYA0ed9FDOC8lyj3DRw8eLDdeeedriFDhgwx/T9eWrBggbVt29Z9XVJSYvp/NhInvWxQpUwIFDYBLTCkm0CteO3+Fq22hSvXW906ta3HLq3trAN2tKo3cYVGRAwUW1Mjlype17tRww2Ki6xTm0a2S0ljZy6LSTpJ5vePK9abVqrWja5GY2lkVvMGxVtWDC9yBvKmTWblmytMAP3p5t9b9EkPxnQzrf9XfK6HZBUPy1SejHC1UwuWVbyveHXv6xY5s2HthnJTW7RStkZCq6yiOrWtuE4t1yeVU1Tb61vFquYaKyZDwhnv6zc6E0l/Mgo0mkzG/JLVGlm2wcWlVT+aN6jrFjpr0bDYmR0yIdQfrZTuvaqeojq1nHm+1fs6tU1mrsrR5xXvK169fCq3deNia92knrXZYkiov0GnP7861R56Z0bQ1VJfARM4fNc29tgvDgjcxJIhp3PT4lUVD9wUNkrH98byTVZWvsk2bjknVfy/wqTU53rVZzqudfyXbfLeb7LatSqOY+9VsunBnUaALlu70S1aqG0URrmlDEbFWm6sWMv13DlEDx2b1Pdei9w5yguXYu6duXpLy8ttY5leN7m26BzYNGZ7GZhqlxtI4A0u2HLu1LnU+1znf50nGxYXufNmI73W886jRZX/V/k6d9Xx+le7wsDV+VHnRfe3dqM7T6v92zer74xfPZCsasgm2pVl1sr41G/xdwtXu98iPcjSw8eSpvXcq/5qulhhvh9O0uzFST/Yq1Pm27rSMmvWoNj9Fnt/GoUsziQIQAACHgG8EPaFTAlgAGdKLkLb9e3b14VzUNJo4COOOCJh7zt06GBz5lRMaVq4cKG1adPGd1qc9HxHSoEQgAAEIJCAgEZ8aRRhdaPOChWcTLOT/j7evp6/qlC7SL8CJKCHQmOuOKwypnCAVeekKu+cIWNXRjEJAhCAAAQg4AcBvBA/KEazDAzgaOqeVq87depkM2fOdNvotWPHjgm3V5iId9991+UZN26c9ezZM636UsnMSS8VSuSBAAQgAAEI1IzA90vW2OkPTrSFq/4X77JmJbJ1FAnowcnQXxzg4qmSIAABCEAAAhDInABeSObsor4lBnDU94AU+t+yZUtbtmyZy7lq1Spr3DjxKqP9+/e3F154weV/6aWXrF+/finU8r8sOqElS5MnT7aBAwe6bBMmTLBDDjkk2SZ8DwEIQAACEIBABgTmr1hv973xrb359cKtFj7KoCjfNpGhqIWXFNbDhfdwoTUqwm54//feK7yGPqv4+9/3mkbvFpFqUOReFaJk0eoNLn72wlXrXZgATbvXlHj91XfhRrb8FddxK7C7/xdr6n4t0xR7F8tfMbK9uP76f+kmW7exIpyJRoIqxqhieJcoxEeT+m5afsUCjmXuVVPsFWe7tLwi/IALUVBeEQLAe6/PK/4q8sS+VxlrSpPHVvVNjAQFiasWwrzymF1t97bpL0gYRBupAwIQgAAEIBAmAhjAYVIrv9qKAZxfeuRla4qLi23jxo2ubXotKipK2M6zzz7bnn76aZdHrz/72c/S6lc68cMwgNNCS2YIQAACEIBAjQgoLISLhVq+yRmSMxatsUfGzbDXpy6sUbnVbawYqXvt0Mz2bt/cve7YsoFpQSj9yXhN93rB9wbmcYEyo5etLXVxb2XgT/lhpX0xd7l9PneFi4Hrd9p3x+Z28eGdbP8OLbYy4qMUMsVvppQHAQhAAAIQqI4ABjD7RaYEMIAzJReh7TCAIyQ2XYUABCAAAQhkQODbBavs4Xdn2Iuf/eAWzkoltWtW3zq2buRiwnrGbqtGWiirnmnho46tGlltYqemgjLlPIpLO3/lehfXefGqDc4g1p8WRNOIZ4X8mLNsnVt8LJV0xG5t7OLDO9uBO7fEkE8FGHkgAAEIQAACNSSAAVxDgBHeHAM4wuKn2nVCQKRKinwQgAAEIACBaBNYuX6jfT5nuU1bsNo2bd5smzebbbbNJj+xqHYta9e8ge3cusLcbVBcJ9qw8rT3pWWbbM6ytTZzkczgtW7xQy1hVrtWLau1ZS2zHVs2tP06NLeSJvXztBc0CwIQgAAEIFCYBDCAC1PXIHqFARwE5ZDXwSJwIReQ5kMAAhCAAAQgAAEIQAACEIAABCAQegIYwKGXMGcdwADOGfrwVNy3b1977bXXXIPffPNNO+KIIxI2vkOHDjZnzhyXZ+HChdamTRvfO8tJz3ekFAgBCEAAAhCAAAQgAAEIQAACEIBAHhPAC8ljcfK8aRjAeS5QPjRv8ODBduedd7qmDBkyxPT/eGnBggXWtm1b93VJSYnp/9lInPSyQZUyIQABCEAAAhCAAAQgAAEIQAACEMhXAngh+apM/rcLAzj/Ncp5CzXqt3fv3q4dvXr1srfeeitum4YOHWoXXHCB+/788883/T8biZNeNqhSJgQgAAEIQAACEIAABCAAAQhAAAL5SgAvJF+Vyf92YQDnv0Y5b2F5ebm1b9/e5s+f79ryySef2P77779Nu5SvW7duNmnSJPedwkb06dMnK+3npJcVrBQKAQhAAAIQgAAEIAABCEAAAhCAQJ4SwAvJU2FC0CwM4BCIlA9NfOCBB2zQoEGuKV27dnWxgBXiITZdc801dtddd7mPevToYe+9917Wms5JL2toKRgCEIAABCAAAQhAAAIQgAAEIACBPCSAF5KHooSkSRjAIREq180sKyuz4447zsaOHeuaoji/F154oe255562dOlSGzZsWKXh26xZMxs/frwzirOVOOlliyzlQgACEIAABCAAAQhAAAIQgAAEIJCPBPBC8lGVcLQJAzgcOuVFK1etWmUDBgywUaNGxW2PQkWMGDHCunfvntU2c9LLKl4KhwAEIAABCEAAAhCAAAQgAAEIQCDPCOCF5JkgIWoOBnCIxMqXpo4cOdKeeOIJ++ijj2zhwoXWpEkT69y5s/Xv398GDhxoGgGc7cRJL9uEKR8CEIAABCAAAQhAAAIQgAAEIACBfCKAF5JPaoSrLRjA4dKL1m4hwEmPXQECEIAABCAAAQhAAAIQgAAEIACBKBHAC4mS2v72FQPYX56UFhABTnoBgaYaCEAAAhCAAAQgAAEIQAACEIAABPKCAF5IXsgQykZgAIdSNhrNSY99AAIQgAAEIAABCEAAAhCAAAQgAIEoEcALiZLa/vYVA9hfnpQWEAFOegGBphoIQAACEIAABCAAAQhAAAIQgAAE8oIAXkheyBDKRmAAh1I2Gs1Jj30AAhCAAAQgAAEIQAACEIAABCAAgSgRwAuJktr+9hUD2F+elBYQAU56AYGmGghAAAIQgAAEIAABCEAAAhCAAATyggBeSF7IEMpGYACHUjYazUmPfQACEIAABCAAAQhAAAIQgAAEIACBKBHAC4mS2v72FQPYX56UFhABTnoBgaYaCEAAAhCAAAQgAAEIQAACEIAABPKCAF5IXsgQykZgAIdSNhrNSY99AAIQgAAEIAABCEAAAhCAAAQgAIEoEcALiZLa/vYVA9hfnpQWEAFOegGBphoIQAACEIAABCAAAQhAAAIQgAAE8oIAXkheyBDKRmAAh1I2Gs1Jj30AAhCAAAQgAAEIQAACEIAABCAAgSgRwAuJktr+9hUD2F+elBYQAU56AYGmGghAAAIQgAAEIAABCEAAAhCAAATyggBeSF7IEMpGYACHUjYazUmPfQACEIAABCAAAQhAAAIQgAAEIACBKBHAC4mS2v72FQPYX56UFhABTnoBgaYaCEAAAhCAAAQgAAEIQAACEIAABPKCAF5IXsgQykZgAIdSNhrNSY99AAIQgAAEIAABCEAAAhCAAAQgAIEoEcALiZLa/vYVA9hfnpQWEAFOegGBphoIQAACEIAABCAAAQhAAAIQgAAE8oIAXkheyBDKRmAAh1I2Gs1Jj30AAhCAAAQgAAEIQAACEIAABCAAgSgRwAuJktr+9hUD2F+elBYQAU56AYGmGghAAAIQgAAEIAABCEAAAhCAAATyggBeSF7IEMpGYACHUjYazUmPfQACEIAABCAAAQhAAAIQgAAEIACBKBHAC4mS2v72FQPYX56UFhABTnoBgaYaCEAAAhCAAAQgAAEIQAACEIAABPKCAF5IXsgQykZgAIdSNhrNSY99AAIQgAAEIAABCEAAAhCAAAQgAIEoEcALiZLa/vYVA9hfnpQWEIHXX3/djj76aFfbQw89ZHvttVdANVMNBCAAAQhAAAIQgAAEIAABCEAAAhAInsDkyZNt4MCBruKxY8faUUcdFXwjqDGUBDCAQykbjX744YcrT3rQgAAEIAABCEAAAhCAAAQgAAEIQAACUSKgwXAXXXRRlLpMX2tAAAO4BvDYNHcEMIBzx56aIQABCEAAAhCAAAQgAAEIQAACEMgtAQzg3PIPW+0YwGFTjPY6AvPmzbNRo0a59506dbJGjRqFkkzs9A1CWYRSwpQajc4pYQp9JnQOvYQpdwCtU0YV6ozoHGr50mo8WqeFK7SZ0Tm00qXVcHROC1eoM0dV6zVr1tiMGTOcdv369bN27dqFWkcaHxwBDODgWFMTBLYhQAD3aOwU6IzO0SAQnV5yTEdDa3SOhs7qJVpHQ2t0RudoEIhOLzmmo6M1PfWHAAawPxwpBQIZEeBHKyNsodsInUMnWUYNRueMsIVyI7QOpWxpNxqd00YW2g3QOrTSpdVwdE4LV2gzo3NopUu74WidNjI2iDgBDOCI7wB0P7cE+NHKLf+gakfnoEjnth50zi3/IGtH6yBp564udM4d+6BrRuugieemPnTODfega0XnoInnrj60zh17ag4nAQzgcOpGqwuEAD9aBSJkkm6gMzpHg0B0eskxHQ2t0TkaOquXaB0NrdEZnaNBIDq95JiOjtb01B8CGMD+cKQUCGREgB+tjLCFbiN0Dp1kGTUYnTPCFsqN0DqUsqXdaHROG1loN0Dr0EqXVsPROS1coc2MzqGVLu2Go3XayNgg4gQwgCO+A9D93BLgRyu3/IOqHZ2DIp3betA5t/yDrB2tg6Sdu7rQOXfsg64ZrYMmnpv60Dk33IOuFZ2DJp67+tA6d+ypOZwEMIDDqRutLhAC/GgViJBJuoHO6BwNAtHpJcd0NLRG52jorF6idTS0Rmd0jgaB6PSSYzo6WtNTfwhgAPvDkVIgkBEBfrQywha6jdA5dJJl1GB0zghbKDdC61DKlnaj0TltZKHdAK1DK11aDUfntHCFNjM6h1a6tBuO1mkjY4OIE8AAjvgOQPdzS4AfrdzyD6p2dA6KdG7rQefc8g+ydrQOknbu6kLn3LEPuma0Dpp4bupD59xwD7pWdA6aeO7qQ+vcsafmcBLAAA6nbrQaAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEBSAhjASRGRAQIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAOAlgAIdTN1oNAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCApAQzgpIjIAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgnAQwgMOpG62GAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIJCUAAZwUkRkgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAQTgIYwOHUjVZDAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEEhKAAM4KSIyQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhAIJwEM4HDqRqshAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCCQlgAGcFBEZIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQiEkwAGcDh1o9UQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABJISwABOiogMEPCfwMiRI+3JJ5+0jz76yBYsWGBNmza1zp072ymnnGIDBw60Zs2a+V8pJcYlsGrVKhszZoy99dZb9umnn9q0adNs+fLl1qBBA2vXrp0deOCBNmDAAOvTp4/VqlUrJZI//vijPfjgg/bSSy/ZrFmzbP369da2bVs79NBD7YILLrDDDz88pXK8TOwzaeHKKPN5551nTzzxROW2N910k918881Jy0LrpIhynuGzzz6zp59+2l5//XWbO3eurVy50lq3bm3bb7+9HXzwwdarVy93/q1Tp07ctqJzzmWM2wCdYx999FF3Dv/6669txYoVVq9ePSspKbF9993X+vfvb2eeeabVrVs3aSfQOSkiXzOUl5fb1KlT7eOPP7ZPPvnEvX7++ee2bt06V4/Oy4899lhadeazhn63LS0wOczsp85ffPGFu2YbP368TZkyxebNm2cbN260Fi1a2J577mlHHXWUu87S+T2d5Od1VlR1Fm8/tY6nn87zOrdv2LChMsvmzZtTlhutU0YVN2O2dNa5X9dr0mjy5MnuPlm/3dttt5116dLFjjjiCDvppJPc+2QJnZMR4vsoEsAAjqLq9DlnBGQ0ykgcNWpU3Da0b9/eRowYYd27d89ZO6NU8T333GPXX3+9M2iTJZm3Tz31lHXo0CFh1hdeeMHdfMhEjpcuvPBCe+CBBxIaTtqWfSaZKv58/9prr1nfvn23KiwVAxit/eGfrVJk9F5++eX2+OOPW7Kbw2XLllnz5s2rbQo6Z0uhmperc/h11123lRFQXam77babPffcc/aTn/wkbqXoXHM90i3h1FNPteeffz7uZukawPmsoZ9tS5dzrvP7obOuqfRAXg/pk6WGDRvaHXfcYb/+9a+TZfX9OivKOgu2H1onEm3Tpk1uMMWECRO2ypbsNz4b19RR1jobOr/88ss2aNAgmz17dsLjVtd1f/nLX+Lm8fveKco6Jz2BkiF0BDCAQycZDQ4rgbKyMjvuuONs7Nixrgt6kikTUKMVli5dasOGDXOjGZRkQrz33nvWtWvXsHY3NO2++OKL7aGHHnLtlfneu3dv69atm7Vp08aNQPrggw+c6bt69WqXZ+edd7b333/fjSyrLmmEoXTWaBSl448/3k488URr1KiRG138yCOPuNGHStL/4YcfjsuKfSaY3Uh6yBSaM2eO02nNmjWu4mQGMFoHo0+mtei8qlH7GlGopGNWNyz777+/m3WhUSUaDfz222+72RjKX50BjM6ZKpD97f7+97/b//3f/1VW1KNHDzvhhBNsxx13dOfZL7/80pn/uhlU0qhvjSjSbIyqCZ2zr1d1NZx88slupJeXWrZsaa1atao0+dIxgPNZQz/blhulalarHzrPnz+/clSvZmvIBNRfp06dTIbv999/7x7yfPjhh5WNvfPOO+3qq68O7Dor6joLtB9aJ9rb7r33Xrvyyiu3ul5T/mQGsN/X1FHX2m+dhw4dar/61a9MBr+SRvrqGk6/57qn0vWaRn6/+uqrds4558Q1gNG5Zudqti58AhjAha8xPcwTAhrtqaeaSjJ933zzTWcCxyZdpN59993uI93IygQmZZfAJZdcYjNmzHA3CDJ/a9euvU2FuqnQRcg333zjvvvFL35h//rXv7bJp1HEGmXmPbn+29/+ZpdeeulW+b799lsX/kE3Mkqaxnj00UdX20n2mexq75WusCsy4vUA4IwzzjCNKFRKZACjdTDa1KSWY4891kaPHu2K0E2FbhobN25cbZGarquHPkVFRVt9j841USC72+oBnX5DPXNXx7AeqlVNixYtsiOPPNJNFVe64oorKo9xLy86Z1erRKX/6U9/chr+9Kc/dX96yKqQD/qdVUrVAM5nDf1uW+7UyrxmP3TWdZMe1uoYThTiYciQIfbb3/7WNba4uNg9CNpll12yfp2FzhWI/dA63p723Xff2d57721r1651v+naF7yUzAD285oarf3VWQOgDjvsMGf+6mG9HuTo4U51SaEnFi5cGDfECzpnfp5my2gQwACOhs70MscE9GMlc8kz/RTnTqPQqibl0+jTSZMmua80LV3GIyl7BDTqTyOOkiXFJFS8MSWNNJGpoNfY9I9//KPS8NUotP/+97/VFqvprhqJqKT4oxMnTqx2X2CfSaZKzb9XzFAZ/7pxULxmjRa95ZZbXMGJDGC0rjn7bJYQayCdfvrp9swzz2RUHTpnhC2QjTT6ynt4pt9NjeKOlxR2SedkJZmM3qhwLz86ByJZypVkYgDns4Z+ti1liCHImK7OGgWomK/xHuTFdllxvzVtO9Fvud/X5ugcf6dLV+vqStJ1mh7madaOQoHo2jk2bn8iAxitgzkhZKKzjmsNjJo+fbqL9auZl/vtt19GDUbnjLCxUcQIYABHTHC6mxsCGu0rk0lJoz918RIvaQqMRjYopTryJTe9il6te+yxh5t+pCRDWKMQYpOeXo8bN859JGNRC0tVl/SEW4v+aeEipZkzZ1rHjh23yso+k/39SyNI9tprLzcCXAtEDR8+3C36looBjNbZ16cmNehmQgtL6WZCI/jTXQzIqxuda6JCdrfVIjFnn322q0Sx9f/973/HrVAzLzQ7Q0mv3nkcnbOrUaalZ2Ii5POx6mfbMmWaj9tlonOq/dBaGmeddZbLrgU+q4sz7fd1FjrHV8cPrb2Rnfpd10AaXb/FLsycyABG61SPnJrly0RnXXv/7Gc/cxVr1qRmT2aa0DlTcmwXJQIYwFFSm77mjMDgwYNNcciUNDVN/4+XFJfSi0+oaTD6Pyk/CGjEgTfKTHGADzrooMqGaQqr4ofK3G3SpIlpQanYkQlVe6DQEw8++KD7+P777zf9Pzaxz2Rfcy0i8de//tWtHC6zUNPJUzGA0Tr72tSkBk0l7NmzZ8Ib/1TKR+dUKOUuzxtvvGFHHXWUa8ABBxywVdzPqq3SwjL9+vVzH2v2haaXegmdc6dhvJrTNRHyWUO/25Z/amXeonR1TqemV155xa3BoKRwQIobWjX5eZ2FzonVqanWCq2m8B/irEU/b7vtNldhqgYwWqdz9GSeNxOdNZNHM3qUqhtck05r0DkdWuSNKgEM4KgqT78DJdC3b18XzkFJTycV2D5R6tChg1uQSklxjhSbkpRbApp2KINwxYoVriGKGRq7kJCmLCmcg5JGgbzzzjsJG6wYwr/85S9dHsWG1tTB2MQ+k129tXq04ovJsJcWXrzJVAxgtM6uNjUtXfEHr7/+eleMFgnT8aXRoppdoQXAdAxrkSmFAlDMZ408qe5hDTrXVInsbq8YjPqtVDgeJel7/vnnb1PpkiVL3Awc3VgqxrtmaXTv3r0yHzpnV6dMSk/XRMhnDf1uWyY883WbdHVOpx+xcYAV59974J6t6yx0TqxOTbX2Yvrvuuuu7lxev359V2GqBrCf19RoHV/rdHXWgm3NmjVzMZ11r6t7Xs2K1OAMPbjVvXC9evVsp512cr/jWvRVceLjJXRO5yxJ3qgSwACOqvL0O1ACWqFYP2hK1U33r9oYhYl499133ce6WfVGswXaaCrbikDsRY3iN2v6WWx64oknXMgOpVRCdyhEhGKZKemixnv67ZXJPpO9HVDGkeI5a1G/quxTMYDROnva+FFybOzHF1980e677z4XkiVe0vGsfFppmmPaDwWCK0MxPhW+RTEElfRQR7F+FT9dI8W0+JPO3StXrnRxQx955BGXH52D0yiTmtI1EfL5nOx32zLhma/bpKtzqv3Q+aBr1642bdo0t4nWY/BigMeW4ed1FjonVqcmWnuh8WT2KoSeBll4KVUDGK1TPXpqli9dnb/44gvbZ599XKW697344ovdor1r1qyptiEK/6EZtZrBV11C55rpx9bRIIABHA2d6WWOCWiRMYUEUNJNabIFLGINDC1M5U1dzXE3Ilu9RpjpZsIbaaZYcoopF5v0tNq7ILnqqqvsrrvuSsgr9qKnukWJ2Geyt7t5U8QaNGjgRoQqHrOXUjGA0Tp72vhR8iGHHGIK0aLUpUsXZwJoBMm5557rHqYVFRW5EUQyA7UIpJJWiNfCYBqJ4iV09kON7Jfx3nvv2a9//WvTObW6pBtGHfMaBVjV5Fd+dM6+RunWkK6JkM8a+t22dFnmc/50dU61L7G/43rYqwf2Gv1fNfl5nYXOidXJVGvNtlNM/+XLl9tFF11kDz300FYVpWoAo3WqR0/N8qWr8+jRo12IFiWN7NWIX7ird68AACAASURBVI0Klil8zjnnVM7y0cNehX3ykmZ36XefY7pmerF1NAlgAEdTd3odMIHi4uLKEUoamSADIlHSwjaasqykVy84fsDNpjozKy0tdXEmvcXdTj755MqVpWMBxU471/TzW2+9NSE/mVKayqakV41GjU3sM9nZ/WTyKVSHVgq+44477JprrtmqolQMYLTOjjZ+lbr77rtvdTwp3INuHLxRJl498+fPd8e2Rokq6WZCNxVeQme/FMluOVr4RzNmrr76amfiV5cUn13hIaSpHvxw7s6uJjUtPV0TIZ+PVb/bVlO2+bR9ujqn0nZNGz/xxBNdeCc9/FFMeMUIry75eZ2FzonVyVTrk046yY3g1kKuWqsh9iGtakzVAEbrVI6emudJV+fYBeC82mX0a8G/qg9ttDjcZZdd5rLpof53331nO+ywQ9bunTima74/UEJ+EsAAzk9daFWBEfDzwqPA0OR1d3QDoVGD3uryGimqReC0aFjVFHuhcMMNN9gf//jHhH3DAA5eepn5Gm09ZcoU22+//ZyWVWO/pmsAo3XwOiarUQ9UvKm/yqupuT//+c+r3UwjgbUvyERUTEHFn9Mijkoc08lI5/57xfdVHGfF1td5+fe//73JMNBIX8UU1Mi/u+++27QglJIW8tR7PRTwEjrnXseqLUjXRMhnDf1uW/6plXmL0tU5WU16AKTQWpppp6RRuYoZGi/5eW2OzonVyURrDYDRgBil6mbe6fNcG8B+XAMm26/D9H26OsdqrH7utttubmaeHt5Ul2JnyFY32IZjOkx7C23NFQEM4FyRp95IEfBz6lGkwOWwszKENGX4n//8p2uFFhvSwm4dO3astlV+T/9jn/Ff/BtvvNEZ8zJ9P/zwQ1Ps16opFQMYrf3Xxs8SZfJ/+umnrkiNFlq8eHHCWRdaEGzixIkuv1aK96YjorOfqvhflgxeaf31118781cL8yjkR3Xp0ksvrVxoUzNqvBk2yovO/mtT0xLTNRHyWUO/21ZTtvm0fbo6J2q7QsBogWUvrI8eBv3hD39I2F0/r7PQOfGela7WCrmm0A/6/VbINRnA1aVUDWC0DubIT1dnhTnUiH0vVTczL7blY8aMsT59+riPDjrooMpwX14edA5GZ2oJNwEM4HDrR+tDQsDPoPQh6XKomynzd9CgQZWrRmtBIS08ERsrtmoH/V4AhH3G311IIz01DVQhWBT2QReZ1aVUDGC09lcbv0tTWAcvVpwWBfMW1IxXj0aIeaEfNMVQZqESOvutjL/lKc66F8JFo+9+97vfxa1AZrGmiiqOpKaVzp07100pRmd/NfGrtHRNhHw+Vv1um1+M86GcdHWO12aNGNTIX5mFSjoX6JyQLPl5nYXOiWmnq7Vmdjz77LPuIe5XX31l7dq1q7aCVA1gtE52NPjzfbo6K4a/rtO8pGs3b4Hs6lqkWT+tW7d2X2kmj3fMe3nR2R8dKaWwCWAAF7a+9C5PCPTt29dee+011xpNVdUohURJo00VCF9JU5LbtGmTJz0p/GbI/FUsUMWfUpJpIPNXi0QlShp9ptiySlqhWKOFE6V//etf9stf/tJlkdn8j3/8Y6vs7DP+7mtXXHGF/eUvf3Hmz29/+9tt4oB6ten4fOutt9x/dZx6F6Kalnb66ae7z9HaX238Li12tOfxxx9vo0aNSliFpnDedtttLo9er7vuOnT2W5QslKcVwz1zX1O/NRo4UdK+4IWCUEzJE044AZ2zoIsfRaZrIuTzOdnvtvnBN1/KSFfn6tqtkE76nfYW6dWCj0OGDEmpi35eZ6FzYuTpaL1ixQpT3HYlzdCRTvGSRnp7KTb02oUXXmjbbbdd5XdondIhUeNM6eisymTgxt7jKjRbt27d4rZDC8R54SH0qtBusQmdaywhBUSAAAZwBESmi7knoAvSO++80zVEF6b6f7y0YMECa9u2rfu6pKTE9H9SMASqmr8acSDzN9604thWKeacLlgVN1gxRJctW7ZNfNnY/JdccknlCOP777/f9P/YxD7jr+a/+c1v7L777su4UMUVffHFF932aJ0xxkA2VNgWLSKi1LNnz8oFHONVHmsYx64sjc6ByJVxJTovT58+3W3/7bffJj1Px1tcFZ0zliBrG6ZrIuSzhn63LWvQc1BwujpXbaJG/vbu3bvS/NVCkN61dird8fM6C50TE09Ha83UqG6tjVQ09fJ89tlntu+++1Zugtbp0Ms8bzo6e7VooM28efPcf19//XV3TMdLsYaxRgJ7D368/OicuXZsGR0CGMDR0Zqe5pCARhV6P2i9evWqHGFYXZOGDh1qF1xwgftKq5br/6TsE6hq/mp6sMxfLSiVatLI33Hjxrns2lYj1KpLMok1onjmzJnua71WjS3MPpMq9dTy+WkAq0a0To17LnJper9mUeiYbtq0qRthEm9BEbXvkEMOqYwjN3bsWFMICS+hcy4UTK3O2FjPyW4aVaIeBowfP94VPnr0aDvmmGPQOTXUgefKxETI52PVz7YFLkYWK8xEZ685GvmrWTreFPArr7zSLfiYTvL7Ogud49NPR+tsGMBonc6RkXnedHT2atFo7UceecT99/bbb7drr702bgP02+2t09CjRw9TCInYhM6Za8eW0SGAARwdrelpDgmUl5eb4sjOnz/ftUIrk1e3AJXyaerLpEmTXD6FjfCC3eew+ZGoWmEfNBJXSSOwZeBq2n86SdurHCVNL9Y04+qSFrM49dRT3VcKG+EtQBWbl30mHfL+5U0lBrBqQ2v/mGejJBkDOoaVHn/8cTv33HOrrUbn2v322899p5H7mnHRoEGDyrzonA11/ClTD0ilrZIemj766KNxC9ZI4T322MM0fVRhYBRaSfEDvYTO/mjiVymZmAj5rKGfbfOLcT6Uk4nOaveXX37pzF9v9J9CPN1zzz1pd8nv6yx0ji9BplonEzXVGMBonYykP99norNC5mlwlJIG3ejhTryH9loQ0JuNd+utt9r111+/VcPR2R8dKaWwCWAAF7a+9C6PCCimrGK9KnXt2tXFAlaIh9ikBW20sI1SdU8286g7BdWU2EWgZP4qBuzuu++edh/Xr1/vTOPZs2e7bWOnk3uFTZs2zY0e9R4GVB1xGFsp+0zaEtR4g1QNYLSuMeqsFqCHKoodqCSjT+fbvffee6s6ZfZqZobMBCXdSOiGIjahc1ZlqlHhsauBywRQ6A8vrnpswdJZcQE1JVipuodz6FwjKXzfOBMTIZ819LttvgPPUYGZ6KwFwWT+6iGOkmb33HvvvRn3wM/rLHSOL0MmWqciaqoGsMpC61SI1ixPpjprsJN+05UUwkta6WFtbNI9le7XlPTAXrMnYx/kennRuWYasnXhE8AALnyN6WGeENDIo+OOO85k+CnJaNS0lz333NOWLl1qw4YNq5zKolVvNVVVRjEpuwRiF4DShaRWjk7F/NUIbk0zr5o0FVk6b9y40X3Vr18/O/HEE61Ro0b26aefumlOWuBCSfo//PDDcTvIPpNd7asrPVUDWNuidfD6pFOjFvvzFgOqV6+enXfeeS4MQFFRkZtloWNR514lhRPQVML69etzTKcDOcd5tTDjc889V9kKhd1RvG7NuFm3bp1pcbgnn3zSNKVYSXEltVhTdXHdOZ5zI6Zu4quO3v7iiy/spZdecg3SgxtvwT6vhfr97d+/f6iOVT/3r9woVbNa/dBZ4X00S85bG0OzN2688cakDWvYsOFWIV9iN/D7OivqOoutH1onFXVLhnQMYLROlWpq+fzUWWXpob03OGafffaxn//85+4+S2FeNHNSx5aXnnnmmcqFmau2Fp1T049c0SWAARxd7el5DghokYgBAwYkXJVeN64jRoyoHL2Wg2ZGqkpNO9L0o3STYjNrCnJ16YUXXnBTkj3Tobo8Mn/1lLpOnToJq2afSVeZmuVPxwBWTWhdM97Z3lqjemUCa1pgvKSRJ3oAl2jRGXTOtlKZlb9hwwYXdidR+AevZJm+w4cPrzb8kpcHnTPToSZbKVSLRnSmk/QwRyPNwvb76+f+lQ6vfMjrh86ZlKG+77TTTjZr1qy4GPy+zoqyzoKciU6JjulE+286BrDKQWv/zgZ+66zQD2eccYZNnTo1biMbN27sfu+VL1FCZ/90pqTCI4ABXHia0qMQEBg5cqQ98cQT9tFHH7lpbJrK0rlzZzeiZeDAgaYRwKRgCGTDAFbLf/zxR2fwahSTbjw0NVALy2kEoqYpx1sgLl6v2WeC2R/SNYDROhhdalLL559/7m4YNPvihx9+cKPzFX5Ho00UG1jhAVJJHNOpUMpNHo3oliGomTMzZsywlStXWnFxsdNZo0VPPvlkd8OokeDJEjonI+Tv936bCPl+TvZ7//JXjeyV5ofOmZShHiUzgL1e+3mdFVWdxTITnYIygNHav2M8GzqXlpa63/Jnn33WFO5Fcb5l+io2sK7VFEqxTZs2KXeCYzplVGSMEAEM4AiJTVchAAEIQAACEIAABCAAAQhAAAIQgAAEIACBaBHAAI6W3vQWAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiBABDOAIiU1XIQABCEAAAhCAAAQgAAEIQAACEIAABCAAgWgRwACOlt70FgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIgQAQzgCIlNVyEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIFoEcAAjpbe9BYCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCIEAEM4AiJTVchAAEIQAACEIAABCAAAQhAAAIQgAAEIACBaBHAAI6W3vQWAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiBABDOAIiU1XIQABCEAAAhCAAAQgAAEIQAACEIAABCAAgWgRwACOlt70FgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIgQAQzgCIlNVyEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIFoEcAAjpbe9BYCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCIEAEM4AiJTVchAAEIQAACEIAABCAAAQhAAAIQgAAEIACBaBHAAI6W3vQWAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiBABDOAIiU1XIQABCEAAAhCAAAQgAAEIQAACEIAABCAAgWgRwACOlt70FgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIgQAQzgCIlNVyEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIFoEcAAjpbe9BYCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCIEAEM4AiJTVchAAEIQAACEIAABCAAAQhAAAIQgAAEIACBaBHAAI6W3vQWAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiBABDOAIiU1XIQABCEAAAhCAQCEQKC0ttUcffdSef/55mzJlii1dutT0mdINN9xgf/zjH1Pu5oQJE6xnz55Wq1Yt+/TTT22fffZJedtcZ3z55ZetX79+VlxcbJMnT7Zdd901102ifghAAAIQgAAEIACBPCSAAZyHotAkCEAAAhCAAAQgAIHqCaxYscKOOuoo+/jjj6vN8Nxzz9mpp56aEr7y8nL76U9/ap9//rmde+659vjjj8fdbvPmzdaiRQtT/UoLFiywkpKSpPWojiZNmti6deucybxs2TJr1qxZ0u1SzdCrVy9755137JhjjrHRo0enuhn5IAABCEAAAhCAAAQiRAADOEJi01UIQAACEIAABCAQdgKXXHKJPfjgg64b3bp1s5///OfWrl07Kyoqcp/JEG3evHlK3Rw6dKhdcMEFVrt2bZs6dWrCEbTTp0+3Ll26uHJ32GEHmzt3bkp1aITyXnvt5fLusssuNm3atJS2SzXTG2+84QxxpbFjx1a+T3V78kEAAhCAAAQgAAEIFD4BDODC15geQgACEIAABCAAgYIgsHjxYmvfvr1t2LDBdt99d/vss8+sfv36GfWtrKzMGbLff/+9GzGskcOJ0jPPPGNnnnmmy3LCCSfYf//735TqfeKJJ+y8885zec844wwbMWJEStulk0lG+CeffGIHHXSQvf/+++lsSl4IQAACEIAABCAAgQgQwACOgMh0EQIQgAAEIAABCBQCgX//+992zjnnuK7cdddddtVVV2XcraeeesqNHlZ6/fXXrXfv3gnLuvbaa+2OO+5weW666Sa7+eabU6r7N7/5jd13330u75AhQ2zw4MEpbZdOpn/+85920UUXuU3effddO/TQQ9PZnLwQgAAEIAABCEAAAgVOAAO4wAWmexCAAAQgAAEIQKBQCAwaNMgeeOAB1x0t2Lbffvtl3LVDDjnEjZbViOLZs2e7+LyJ0tFHH+2MYiWN/tUo4FTSYYcdZuPGjXNZsxWiYdWqVdamTRs3MlqjlIcPH55K08gDAQhAAAIQgAAEIBARAhjAERGabkIAAhCAAAQgAIEwEnj44Ydt4MCBSZt+44032i233JI0nzJ88803LoSE0mWXXVY5QjfRxq1bt7YlS5a4LIr/qzjAyZIWjtOCbzJolbR9y5Ytt9rs6quvtrvvvjtZUVt9r36qv7HpxBNPtJdeesmFxJg/f76vC82l1TgyQwACEIAABCAAAQjkHQEM4LyThAZBAAIQgAAEIAABCHgELr/8cvvrX/+aFMizzz5rp512WtJ8yvDnP//ZrrvuOpf3P//5j/Xv3z/hdrNmzbKdd97Z5SkpKbEFCxakVE+s0dyxY0ebOXPmNtsdc8wxbmRwOklGb79+/bba5J577qkMiTFs2DA766yz0imSvBCAAAQgAAEIQAACBUwAA7iAxaVrEIAABCAAAQhAIOwEPvzwQ5s3b579+OOPphAQSgrH4L33+nf44YdbixYtUuruEUccYW+//bbL+8MPP1i7du0Sbvf888+7heKUjj32WHv11VdTqkdG7IABA1zeeAvNvfHGG5UjhOMV+tZbb1Wa4OqjjGWFfIhNEyZMsB49eriPtOjcY489llIbyQQBCEAAAhCAAAQgUPgEMIALX2N6CAEIQAACEIAABEJPYOTIkXbyySe7ftx7772mxdUySZs2bbKmTZvamjVrXPzfOXPmJC3mhhtusNtuu83l08hh732yDa+55hq3WJ2StvFGHSfbLvb70aNH2ymnnGLr1q0zhaHQaOF99913myIU/1f9Ki0ttd12282+/vrrdKohLwQgAAEIQAACEIBAARPAAC5gcekaBCAAAQhAAAIQKBQCN910k/3hD39w3dHoXY34zSRNnz7dunTp4jbVSOIxY8YkLaZv37722muvJc2XKIO279OnT1plaLG5M844wy3u1rZtW9No4T333DNuGYprrNHBWtBu7dq1Lh4wCQIQgAAEIAABCEAAAhjA7AMQgAAEIAABCEAAAnlPwFvkTObm8uXL3WjXTNLrr7/ujF+lM88804YPH560GJmvqcb9jVfYwoULtwnbkKhixTQ+++yzbePGjW6k8ptvvllpXMfbTiEgFApCSUbwrrvumrRvZIAABCAAAQhAAAIQKHwCGMCFrzE9hAAEIAABCEAAAqEnIBNU8Xo7d+5sGsWbaXrmmWec8at0ySWX2P3335+wqLlz59qOO+7o8jRr1swuvfTSlKqWYfzII4+4vNp+9uzZKW2nTE899ZSdf/75Vl5e7haf08hfbxG6RIWccMIJNmrUKJdl4sSJdvDBB6dcJxkhAAEIQAACEIAABAqXAAZw4WpLzyAAAQhAAAIQgEBBEFi0aJGVlJS4vpx++ukmEzfT9OSTT9q5557rNr/22mvt9ttvT1iUwjCcdNJJLs8xxxxjismbSoo1mhW7+IUXXkhlM2caDxw40BSrWCN4Zf7K/E4lacTw008/7bJqxLAWuyNBAAIQgAAEIAABCEAAA5h9AAIQgAAEIAABCEAgrwnIdD322GNdG//0pz/Z7373u4zbm+4I4JtvvtluueUWV5/qVf2pJJnLd9xxh8uq2MW///3vk27297//3S677DLbvHmzde3a1RSuQuEnUk2MAE6VFPkgAAEIQAACEIBAtAhgAEdLb3oLAQhAAAIQgAAEQkfgz3/+s1133XWu3ZksphbbYY2oPeqoo9xHqcQAjjVVFZf3tNNOS4mf6lBdSi+//LIdd9xxCbe766677JprrnF59t13Xxs7dqy1bt06pbq8TMQATgsXmSEAAQhAAAIQgEBkCGAAR0ZqOgoBCEAAAhCAAATCSeCMM84wma9K6S6mVrXH3333ne2yyy7uYy0GN2bMmIRQdthhB5s3b57LM2PGjJRi8Spvq1atbOnSpW67H3/8MeFI3ltvvbVyhPCBBx7oTO4WLVqkLdbuu+/uFn/TQnnr1q2zevXqpV0GG0AAAhCAAAQgAAEIFB4BDODC05QeQQACEIAABCAAgYIiIMNWxq3MWC3KVpOk2LrNmze3VatWJV2cTQu5eSEYZMh6hm6y+mfOnGmdOnVy2dq1a+cWr4uXrr/++sqwEj179nSjhZs2bZqsim2+37Bhg9uutLTUZARPnTo17TLYAAIQgAAEIAABCECgMAlgABemrvQKAhCAAAQgAAEIFASBlStXOsNWcXEVjkGLstU09e7d2y2SpiRzViZtdemVV16x448/3n2lkA4Ky5BKeu6559xidUr9+vWzl156qdrNrrzySrv33nvdd0ceeaTrW6NGjVKpYps8EydOtO7du7vPzz//fBs6dGhG5bARBCAAAQhAAAIQgEDhEcAALjxN6REEIAABCEAAAhAoGALvvPOO9erVy/XnxhtvrFyQrSYdvPPOO23w4MGuiOeff95OOeWUaouLDc2g/EOGDEmpWi0Wd/vtt7u8N910k2khudgkM/vSSy+1+++/333ct29f14769eunVH51me655x676qqr3FfDhg2zs846K+Oy2BACEIAABCAAAQhAoLAIYAAXlp70BgIQgAAEIAABCBQUgb/85S92xRVXuD69+OKLdtJJJ9W4f9OnT7cuXbq4cmTE/u1vf6u2zP79+9sLL7zgvhsxYoQpFnEqqU+fPpWxhUeOHGknnnjiVpvJyP7jH//oPmvfvr3dfffdVlxcnLDohg0b2jHHHBM3z8knn2yqSyby/PnzrVmzZqk0lTwQgAAEIAABCEAAAhEggAEcAZHpIgQgAAEIQAACEAgrgXPPPdeefPJJ1/zvv//eOnTo4EtXFG93/Pjx1qZNGxcGom7dutuUu9NOO9ns2bPd5zKNO3funFLdKnPx4sUur2IWK3ZxbOrWrZt98sknKZXlZTr88MPt7bffrnab1atXu36sX7/ezjzzTBs+fHhaZZMZAhCAAAQgAAEIQKCwCWAAF7a+9A4CEIAABCAAAQiEmsBee+1lU6ZMsVatWlWaqn50SGESBgwY4IqqbpTukiVLrHXr1u57jaZdtmyZ1apVK2nVMqk7duzo8pWUlJgWkotNGzdutMaNG7vF2tJJl19+uWk0dHXp0UcftV/96lfuK4XMOOyww9IpmrwQgAAEIAABCEAAAgVOAAO4wAWmexCAAAQgAAEIQAAC2xIoKytzYSBmzZrlYgArBm9Y04EHHmgfffSR6fWDDz4IazdoNwQgAAEIQAACEIBAlghgAGcJLMVCAAIQgAAEIAABCOQ3gccff9zOP/98N7L3888/N402Dlt666237Mgjj3TNHjNmjB199NFh6wLthQAEIAABCEAAAhDIMgEM4CwDpngIQAACEIAABCAAgfwksGnTJtt///2d+RvWUcAyf2UCa4G40aNH5ydoWgUBCEAAAhCAAAQgkFMCGMA5xU/lEIAABCAAAQhAAAK5JDBhwgTTgnCbN292C7PJEA5LeuWVV+z444+34uJimzx5su26665haTrthAAEIAABCEAAAhAIkAAGcICwqQoCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQJAEMICDpE1dEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQCJIABHCBsqoIABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgECQBDOAgaVMXBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIEACWAABwibqiAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIBEkAAzhI2tQFAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCBAAhjAAcKmKghAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACQRLAAA6SNnVBAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEAiQAAZwgLCpCgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAkAQwgIOkTV0QgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABAIkgAEcIGyqggAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAQJAEM4CBpUxcEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgQAJYAAHCJuqIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQgESQADOEja1AUBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIEACGMABwqYqCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAJBEsAADpI2dUEAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQCJAABnCAsKkKAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgECQBDCAg6RNXRCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEAiSAARwgbKqCAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIBAkAQzgIGlTFwQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBAAlgAAcIm6ogAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCARJAAM4SNrUBQEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgQAIYwAHCpioIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAkESwAAOkjZ1QQACpFfYjAAAAEJJREFUEIAABCAAAQhAAAIQgAAEIAABCEAAAhAIkAAGcICwqQoCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQJAE/h+7U0O0P+bF/AAAAABJRU5ErkJggg==\" 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      ],
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    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, '$f~(Hz)$')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f,Y = FFT(i1, i2)\n",
    "plt.figure()\n",
    "plt.plot(f,abs(Y))\n",
    "plt.title('FFT of SG Measure')\n",
    "plt.xlabel(r'$f~(Hz)$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Measuring the natural frequencies\n",
    "\n",
    "What you see above is the amplitude as a function of the frequency. There are spikes at \n",
    "\n",
    "* $f_1 = 15.8~Hz,$ $A = 624~microstrain$\n",
    "* $f_2 = 123.7~Hz,$ $A = 83~microstrain$\n",
    "* $f_3 = 350~Hz,$ $A = 15~microstrain$\n",
    "\n",
    "The last natural frequency has the largest error, so it may be a problem with the window or sampling rate. You'll have to play with both to get better measurements of natural frequencies. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# References\n",
    "\n",
    "1. [https://en.wikipedia.org/wiki/Euler-Bernoulli_beam_theory](https://en.wikipedia.org/wiki/Euler%E2%80%93Bernoulli_beam_theory#Example:_Cantilevered_beam)\n",
    "\n",
    "2. Jerri, A. J. (1977). The Shannon sampling theorem—Its various extensions and applications: A tutorial review. Proceedings of the IEEE, 65(11), 1565-1596.\n",
    "\n",
    "3. Nyquist, H. (1928). Certain topics in telegraph transmission theory. Transactions of the American Institute of Electrical Engineers, 47(2), 617-644.\n",
    "\n",
    "4. [http://www.onmyphd.com/?p=aliasing](http://www.onmyphd.com/?p=aliasing)\n",
    "\n",
    "5. Cooley, J. W., & Tukey, J. W. (1965). An algorithm for the machine calculation of complex Fourier series. Mathematics of computation, 19(90), 297-301.\n",
    "\n",
    "6. Harris, F. J. (1978). On the use of windows for harmonic analysis with the discrete Fourier transform. Proceedings of the IEEE, 66(1), 51-83."
   ]
  }
 ],
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