pnavaro/polyglot-ds-prep.ipynb

## polyglot-ds-prep.ipynb

      
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## polyglot-ds.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Polyglot Data Science with IPython & friends\n",
    "\n",
    "A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.  \n",
    "\n",
    "This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.\n",
    "\n",
    "See the [companion notebook](polyglot-ds-prep.ipynb) for data preparation and setup."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"seaborn\")\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 6)\n",
    "sns.set_context(\"talk\", font_scale=1.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's begin by reading our dataset and having a quick look:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(300, 2)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.094287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.021014</td>\n",
       "      <td>-0.216828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.042028</td>\n",
       "      <td>0.329982</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "0  0.000000  0.094287\n",
       "1  0.021014 -0.216828\n",
       "2  0.042028  0.329982"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data.csv')\n",
    "print(data.shape)\n",
    "data.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah, it looks like we have a quantitative dataset with $(x,y)$ pairs - a scatterplot is a decent starting point to get a feel for these data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot.scatter(x='x', y='y');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mmh, what to do?\n",
    "\n",
    "Let's try to build a simple linear model for these data, with some features we'll extract from the data. There's probably:\n",
    "\n",
    "* a linear dependence\n",
    "* something that looks broadly non-linear, let's say quadratic, to keep things simple\n",
    "* and maybe an oscillatorty term: but it looks a bit like a chirp, not a simple sinusoid. Again, simplest non-linear choice: quadratic frequency dependency.\n",
    "\n",
    "In summary, let's try\n",
    "\n",
    "$$\n",
    "y \\sim \\theta_1 x + \\theta_2 x^2 + \\theta_3 \\sin(x^2)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oh boy! Complicated data, Julia to the rescue...\n",
    "\n",
    "Maybe Julia can help us efficiently compute that nasty non-linear feature, $x^2$?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing Julia interpreter. This may take some time...\n"
     ]
    }
   ],
   "source": [
    "%load_ext julia.magic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "jxsq = %julia xsq(x) = x.^2  # Simplest way to define a function in Julia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've defined the function `xsq` in Julia, and in Python we have it available as `jxsq`, which we can call as a normal Python function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = data['x']\n",
    "f2 = jxsq(x)\n",
    "x.shape == f2.shape  # our feature should have the same shape as our data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# More complicated features, we need performance... \n",
    "## Fortran can help us!\n",
    "\n",
    "Let's use this oldie but goodie to assist in the task of estimating our next non-linear feature, $\\sin(x^2)$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/fperez/.local/lib/python3.6/site-packages/fortranmagic.py:147: UserWarning: get_ipython_cache_dir has moved to the IPython.paths module since IPython 4.0.\n",
      "  self._lib_dir = os.path.join(get_ipython_cache_dir(), 'fortran')\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "$.getScript(\"https://raw.github.com/marijnh/CodeMirror/master/mode/fortran/fortran.js\", function () {\n",
       "IPython.config.cell_magic_highlight['magic_fortran'] = {'reg':[/^%%fortran/]};});\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%load_ext fortranmagic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%fortran\n",
    "subroutine sinx2(x, y, n)\n",
    "    real, intent(in), dimension(n) :: x\n",
    "    real, intent(out), dimension(n) :: y\n",
    "    !intent(hide) :: n\n",
    "    y = sin(x**2)\n",
    "end subroutine sinx2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, `sinx2` can be used as a plain Python function too:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#f3 = sinx2(x)\n",
    "f3 = np.sin(x**2)\n",
    "\n",
    "f3.shape == x.shape  # same sanity check"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistical modeling? Maybe R can do that??\n",
    "\n",
    "We now have our data `y` and our features $x$, $f_2 = x^2$ and $f_3 = \\sin(x^2)$.  This is a classic linear modeling problem, and R is awesome at fitting those!\n",
    "\n",
    "Let's put our features together in a nice design matrix and load up R:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(300, 3)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.column_stack([x, f2, f3])\n",
    "A.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "y = data['y']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In R, this can be written as a linear model `lm(y ~ 0 + A)`.\n",
    "\n",
    "Note that we'll ask for the fit coefficients `fitc` to keep moving forward:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = y ~ 0 + A)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-0.7186 -0.1182  0.0090  0.1275  0.5450 \n",
       "\n",
       "Coefficients:\n",
       "    Estimate Std. Error t value Pr(>|t|)    \n",
       "A1  1.000707   0.012517   79.95   <2e-16 ***\n",
       "A2 -0.199631   0.002566  -77.81   <2e-16 ***\n",
       "A3  1.015147   0.016646   60.98   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.1958 on 297 degrees of freedom\n",
       "Multiple R-squared:  0.9741,\tAdjusted R-squared:  0.9739 \n",
       "F-statistic:  3730 on 3 and 297 DF,  p-value: < 2.2e-16\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -i y,A -o fitc\n",
    "\n",
    "ylm = lm(y ~ 0 + A)\n",
    "fitc = coef(ylm)\n",
    "print(summary(ylm))\n",
    "par(mfrow=c(2,2))\n",
    "plot(ylm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Back to Python to look at the results!\n",
    "\n",
    "R gave us our fit coefficient vector `fitc`, we can now proceed using it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <span>FloatVector with 3 elements.</span>\n",
       "    <table>\n",
       "      <tbody>\n",
       "      <tr>\n",
       "      \n",
       "      <td>\n",
       "        1.000707\n",
       "      </td>\n",
       "      \n",
       "      <td>\n",
       "        -0.199631\n",
       "      </td>\n",
       "      \n",
       "      <td>\n",
       "        1.015147\n",
       "      </td>\n",
       "      \n",
       "      </tr>\n",
       "      </tbody>\n",
       "    </table>\n",
       "    "
      ],
      "text/plain": [
       "R object with classes: ('numeric',) mapped to:\n",
       "<FloatVector - Python:0x1a2e42db08 / R:0x7fd34b3b7498>\n",
       "[1.000707, -0.199631, 1.015147]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fitc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We construct our fitted model and visualize our results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "yfit = A @ fitc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, 'o', label='data')\n",
    "plt.plot(x, yfit, label='fit', color='orange', lw=4)\n",
    "plt.title('Julia, Python and R working in Jupyter')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Polyglot Data Science FTW!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Bonus\n",
    "\n",
    "## Cython, the happy child of C and Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    return x**2-x\n",
    "\n",
    "def integrate_f(a, b, N):\n",
    "    s = 0; dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += f(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "<p><span style=\"border-bottom: solid 1px grey;\">Generated by Cython 0.28.2</span></p>\n",
       "<p>\n",
       "    <span style=\"background-color: #FFFF00\">Yellow lines</span> hint at Python interaction.<br />\n",
       "    Click on a line that starts with a \"<code>+</code>\" to see the C code that Cython generated for it.\n",
       "</p>\n",
       "<div class=\"cython\"><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">01</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">fcy</span><span class=\"p\">(</span><span class=\"n\">double</span> <span class=\"n\">x</span><span class=\"p\">)</span> <span class=\"k\">except</span><span class=\"o\">?</span> <span class=\"o\">-</span><span class=\"mf\">2</span><span class=\"p\">:</span></pre>\n",
       "<pre class='cython code score-0 '>static double __pyx_f_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_fcy(double __pyx_v_x) {\n",
       "  double __pyx_r;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"fcy\", 0);\n",
       "/* … */\n",
       "  /* function exit code */\n",
       "  __pyx_L0:;\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "</pre><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">02</span>:     <span class=\"k\">return</span> <span class=\"n\">x</span><span class=\"o\">**</span><span class=\"mf\">2</span><span class=\"o\">-</span><span class=\"n\">x</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_r = (pow(__pyx_v_x, 2.0) - __pyx_v_x);\n",
       "  goto __pyx_L0;\n",
       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">03</span>: </pre>\n",
       "<pre class=\"cython line score-71\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">04</span>: <span class=\"k\">def</span> <span class=\"nf\">integrate_fcy</span><span class=\"p\">(</span><span class=\"n\">double</span> <span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">double</span> <span class=\"n\">b</span><span class=\"p\">,</span> <span class=\"nb\">int</span> <span class=\"n\">N</span><span class=\"p\">):</span></pre>\n",
       "<pre class='cython code score-71 '>/* Python wrapper */\n",
       "static PyObject *__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/\n",
       "static PyMethodDef __pyx_mdef_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy = {\"integrate_fcy\", (PyCFunction)__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy, METH_VARARGS|METH_KEYWORDS, 0};\n",
       "static PyObject *__pyx_pw_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n",
       "  double __pyx_v_a;\n",
       "  double __pyx_v_b;\n",
       "  int __pyx_v_N;\n",
       "  PyObject *__pyx_r = 0;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"integrate_fcy (wrapper)\", 0);\n",
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       "    static PyObject **__pyx_pyargnames[] = {&amp;__pyx_n_s_a,&amp;__pyx_n_s_b,&amp;__pyx_n_s_N,0};\n",
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       "    if (unlikely(__pyx_kwds)) {\n",
       "      Py_ssize_t kw_args;\n",
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       "      switch (pos_args) {\n",
       "        case  3: values[2] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 2);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  0: break;\n",
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       "      kw_args = <span class='py_c_api'>PyDict_Size</span>(__pyx_kwds);\n",
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       "        if (likely((values[0] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_a)) != 0)) kw_args--;\n",
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       "        if (likely((values[1] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_b)) != 0)) kw_args--;\n",
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       "        }\n",
       "        CYTHON_FALLTHROUGH;\n",
       "        case  2:\n",
       "        if (likely((values[2] = <span class='pyx_c_api'>__Pyx_PyDict_GetItemStr</span>(__pyx_kwds, __pyx_n_s_N)) != 0)) kw_args--;\n",
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       "      values[2] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 2);\n",
       "    }\n",
       "    __pyx_v_a = __pyx_<span class='py_c_api'>PyFloat_AsDouble</span>(values[0]); if (unlikely((__pyx_v_a == (double)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "    __pyx_v_b = __pyx_<span class='py_c_api'>PyFloat_AsDouble</span>(values[1]); if (unlikely((__pyx_v_b == (double)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "    __pyx_v_N = <span class='pyx_c_api'>__Pyx_PyInt_As_int</span>(values[2]); if (unlikely((__pyx_v_N == (int)-1) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "  }\n",
       "  goto __pyx_L4_argument_unpacking_done;\n",
       "  __pyx_L5_argtuple_error:;\n",
       "  <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"integrate_fcy\", 1, 3, 3, <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args)); <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L3_error)</span>\n",
       "  __pyx_L3_error:;\n",
       "  <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_e533f0119deb0c87f04cae3c0c2176c0.integrate_fcy\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return NULL;\n",
       "  __pyx_L4_argument_unpacking_done:;\n",
       "  __pyx_r = __pyx_pf_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_integrate_fcy(__pyx_self, __pyx_v_a, __pyx_v_b, __pyx_v_N);\n",
       "\n",
       "  /* function exit code */\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "\n",
       "static PyObject *__pyx_pf_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_integrate_fcy(CYTHON_UNUSED PyObject *__pyx_self, double __pyx_v_a, double __pyx_v_b, int __pyx_v_N) {\n",
       "  int __pyx_v_i;\n",
       "  double __pyx_v_s;\n",
       "  double __pyx_v_dx;\n",
       "  PyObject *__pyx_r = NULL;\n",
       "  <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
       "  <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"integrate_fcy\", 0);\n",
       "/* … */\n",
       "  /* function exit code */\n",
       "  __pyx_L1_error:;\n",
       "  <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_t_5);\n",
       "  <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_e533f0119deb0c87f04cae3c0c2176c0.integrate_fcy\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n",
       "  __pyx_r = NULL;\n",
       "  __pyx_L0:;\n",
       "  <span class='refnanny'>__Pyx_XGIVEREF</span>(__pyx_r);\n",
       "  <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
       "  return __pyx_r;\n",
       "}\n",
       "/* … */\n",
       "  __pyx_tuple_ = <span class='py_c_api'>PyTuple_Pack</span>(6, __pyx_n_s_a, __pyx_n_s_b, __pyx_n_s_N, __pyx_n_s_i, __pyx_n_s_s, __pyx_n_s_dx);<span class='error_goto'> if (unlikely(!__pyx_tuple_)) __PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_tuple_);\n",
       "  <span class='refnanny'>__Pyx_GIVEREF</span>(__pyx_tuple_);\n",
       "/* … */\n",
       "  __pyx_t_1 = PyCFunction_NewEx(&amp;__pyx_mdef_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_1integrate_fcy, NULL, __pyx_n_s_cython_magic_e533f0119deb0c87f0);<span class='error_goto'> if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n",
       "  if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_integrate_fcy, __pyx_t_1) &lt; 0) <span class='error_goto'>__PYX_ERR(0, 4, __pyx_L1_error)</span>\n",
       "  <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n",
       "</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">05</span>:     <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span></pre>\n",
       "<pre class=\"cython line score-0\">&#xA0;<span class=\"\">06</span>:     <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">s</span><span class=\"p\">,</span> <span class=\"nf\">dx</span></pre>\n",
       "<pre class=\"cython line score-5\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">07</span>:     <span class=\"n\">s</span> <span class=\"o\">=</span> <span class=\"mf\">0</span><span class=\"p\">;</span> <span class=\"n\">dx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">b</span><span class=\"o\">-</span><span class=\"n\">a</span><span class=\"p\">)</span><span class=\"o\">/</span><span class=\"n\">N</span></pre>\n",
       "<pre class='cython code score-5 '>  __pyx_v_s = 0.0;\n",
       "  __pyx_t_1 = (__pyx_v_b - __pyx_v_a);\n",
       "  if (unlikely(__pyx_v_N == 0)) {\n",
       "    <span class='py_c_api'>PyErr_SetString</span>(PyExc_ZeroDivisionError, \"float division\");\n",
       "    <span class='error_goto'>__PYX_ERR(0, 7, __pyx_L1_error)</span>\n",
       "  }\n",
       "  __pyx_v_dx = (__pyx_t_1 / ((double)__pyx_v_N));\n",
       "</pre><pre class=\"cython line score-0\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">08</span>:     <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">N</span><span class=\"p\">):</span></pre>\n",
       "<pre class='cython code score-0 '>  __pyx_t_2 = __pyx_v_N;\n",
       "  __pyx_t_3 = __pyx_t_2;\n",
       "  for (__pyx_t_4 = 0; __pyx_t_4 &lt; __pyx_t_3; __pyx_t_4+=1) {\n",
       "    __pyx_v_i = __pyx_t_4;\n",
       "</pre><pre class=\"cython line score-5\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">09</span>:         <span class=\"n\">s</span> <span class=\"o\">+=</span> <span class=\"n\">fcy</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"o\">+</span><span class=\"n\">i</span><span class=\"o\">*</span><span class=\"n\">dx</span><span class=\"p\">)</span></pre>\n",
       "<pre class='cython code score-5 '>    __pyx_t_1 = __pyx_f_46_cython_magic_e533f0119deb0c87f04cae3c0c2176c0_fcy((__pyx_v_a + (__pyx_v_i * __pyx_v_dx))); if (unlikely(__pyx_t_1 == ((double)-2.0) &amp;&amp; <span class='py_c_api'>PyErr_Occurred</span>())) <span class='error_goto'>__PYX_ERR(0, 9, __pyx_L1_error)</span>\n",
       "    __pyx_v_s = (__pyx_v_s + __pyx_t_1);\n",
       "  }\n",
       "</pre><pre class=\"cython line score-6\" onclick=\"(function(s){s.display=s.display==='block'?'none':'block'})(this.nextElementSibling.style)\">+<span class=\"\">10</span>:     <span class=\"k\">return</span> <span class=\"n\">s</span> <span class=\"o\">*</span> <span class=\"n\">dx</span></pre>\n",
       "<pre class='cython code score-6 '>  <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_r);\n",
       "  __pyx_t_5 = <span class='py_c_api'>PyFloat_FromDouble</span>((__pyx_v_s * __pyx_v_dx));<span class='error_goto'> if (unlikely(!__pyx_t_5)) __PYX_ERR(0, 10, __pyx_L1_error)</span>\n",
       "  <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_5);\n",
       "  __pyx_r = __pyx_t_5;\n",
       "  __pyx_t_5 = 0;\n",
       "  goto __pyx_L0;\n",
       "</pre></div></body></html>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%cython -a\n",
    "cdef double fcy(double x) except? -2:\n",
    "    return x**2-x\n",
    "\n",
    "def integrate_fcy(double a, double b, int N):\n",
    "    cdef int i\n",
    "    cdef double s, dx\n",
    "    s = 0; dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += fcy(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "22.3 µs ± 2.54 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
      "202 ns ± 3.58 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "tpy = %timeit -o -n 1000 integrate_f(0, 1, 100)\n",
    "tcy = %timeit -o -n 1000 integrate_fcy(0, 1, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101.84337702512775"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpy.best/tcy.best"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Julia interoperability is pretty neat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "%julia @pyimport numpy as np\n",
    "%julia @pyimport matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a32003518>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%julia\n",
    "# Note how we mix numpy and julia:\n",
    "t = linspace(0,2*pi,1000); # use the julia linspace\n",
    "s = sin(3*t + 4*np.cos(2*t)); # use the numpy cosine and julia sine\n",
    "fig = plt.gcf()\n",
    "plt.plot(t, s, color=\"red\", linewidth=2.0, linestyle=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IIYSwIEnShBBCCCEsSJI0IYQQQggLkiRNCCGEEMKCJEkTQgghhLAgSdKEEEIIISxIkjQhhBBCCAuSJE0IIYQQwoIkSRNCCCGEsCBJ0oQQQgghLEiSNCGEEEIIC5IkTQghhBDCgiRJE0IIIYSwIEnShBBCCCEsSJI0IYQQQggLkiRNCCGEEMKC7GYHYLR9+0rjfg1FUcjNTaegoBxd1+N+vWQj9y92cg9jJ/cwdnIPYyP3L3bJcA+bNMms8zkZSYuCqgZ+MFS5e1GR+xc7uYexk3sYO7mHsZH7F7tkv4dJ+mUJIYQQQtRvkqQJIYQQQliQJGlCCCGEEBYkSZoQQgghhAVJkiaEEEIIYUGSpAkhhBBCWFDck7T777+fSy+9NKzXVlVV8a9//YvTTjuN3r17M3bsWBYvXhznCIUQQgghrCeuSdrMmTN55513wn79X/7yF1588UXOOecc7rrrLtxuN9dccw0rVqyIY5RCCCGEENYTl44Dfr+f5557jqlTp4Z9zKJFi/jiiy+47777uPzyywEYNWoU559/PlOmTOGtt96KR6hCCCGEEJZk+Eia2+1m9OjRPPPMM4wePZpmzZqFddyHH36Iw+Hgj3/8Y+ix9PR0xowZw8qVK9m5c6fRoQohhBBCWFZckrSKigqeeeYZJk+ejN0e3mDdr7/+SufOnUlJSTns8R49egCwatUqo0MVQgghhLAsw6c7MzIy+OSTT8JOzoL27NlDnz59ajzetGlTgLBH0hLRw0tVlcP+Lepm++VnnO+8iVJZRdXNt6K1a98g75/tpx9xvfk6elYWVdfdgJ6bF9P5rHYPlcID6I1zzA4jIla7h/WR3MPYyP2rm/3773B88jHec8/Dd+JJdb4u2e+h4UmaqqqoUWRJ5eXlpKam1njc5XIBUFlZGdZ5cnPTUZTEfLOys9MTcp1664UX4PrrQdOgfXtS/vMMHDJS2mDu35w58Ic/gM8HQOq+3fDSS4ac2hL3cN8+GDoYPv4YTjjB7GgiZol7WM/JPYyN4ffv88/hjDPAZjP2vIni8cC9k+CXX0h9fhosXAgDBhz1kGT9GYzLxoFo1ZZcBR8LN/EqKChPyEhadnY6RUXlaJoe34vVU45P55F57bUAVI27Gvfl4/BX+KCirEHdP2X3brKuHIfq8+Ee+ye03Fwq77kfDpTFdF4r3cOUp6aStmsX7kceo3zadFNjiYSV7mF9JfcwNvG4f7ZlP5A17Bx8fftT8tmXUFEBaWmQoMELw8ybT+bFo3F8vxDvnXdR+v6cWl+WDD+DOTkZdT5nmSQtLS2t1tGyqqoqIDCNGg5d1/H7DQ2tTpqm4/fXzx+KeFIOFJB+600AlN/7ABUT/xp4wq9DZSVpj/wDThqMdt7opL9/mfffi1pUiPuscyj5v+cOvlEa9HWb+TPonP8Z/uYtqbrgQtIeeQjHZ5/gd3shwqUOZpPf49jJPYyNkfcvZdb7AHgGDibl/r+R+vIMCj/8FH/PXoacP2GcKRS//Ca5vbvh+OYr9I2b0Nq1r/PlyfozaJmOAy1btmTfvn01Ht+7dy9A2LtEhfnSpv4f6v79eIacTMWtdxz2nOuzeaT89z9w220oRYUmRZgY6qaNuGa/h+5wUDblycM+ySoHCrAvXmRidLHLuOuv5Jw+BMor8HXoiFpchP2nlWaHJUSD5vzycwA8556HUlyEUlGO89tvTI4qfOrOHSjFRQDoWdm4h48AwPVR7SNpyc4ySVr37t3ZsGEDHo/nsMd//fVX4OAuT2FxmoZj0XcAlP/9YY6ce3ZfMBrvyadAYSEpTz1hRoQJo+7bh79DR6r+OBbtuNYHH/99C7k9u5B11Z/A6zUxwugpJcXYtm5Bd7nwdzse76ATAXCsWGZyZEI0XMqBAuzr16GnpODtNwDvkJMBQu/J9UH65IfJzW+H691AbVTP2cMAcCxcYGZYprFMkjZ8+HCqqqqYOXNm6LHy8nLef/99+vXrR/PmzU2MToRNVSma+wVFsz/G16dfzecVhYoHHwYg5X/TUQoPJDjAxPENGkzhdz9Q/vDkwx7X2rTF36EjakEBzm++NCm62NhXB0ri+LoeD3Z76HttX7HczLCEaNCCH5K8J/QFpxNfv/4A2H/60cywwqfrOBZ8jaJp+I4PDMwEE021pAT05JvOPBZTkrT9+/fzwQcfsHLlwamRoUOHMnToUB555BGmTJnCm2++yWWXXca+ffuYNGmSGWGKaKlq6BerNv4+fWH4cJSKClJefSlxcZlBVdEzGx3+mKLgPv9CABxffmFCULGzrQqMcPuO7x74d/fAG6ptw3rTYhKiobMFPzz16g2Av31HtPQMbLt3oVQvHbIydevv2HbtRMvJwd/teAC0Fi3Zv24LRXM/r3+bHwxgSpK2ceNGJk2axNtvv33Y4//3f//H2LFjmT17NlOmTCElJYUZM2ZwQj3c1t8QqTu2h/9GMHEiAKn/e77eTvkdjXPOLNRNG+t83nvKaYHXfVc/h/DtqwNJmr86OfN37kLVqDG4zx9lZlhCNGj23zYA4M/vFnhAVUO/o/Y11i8IHxqh79n7sKUy9a0Go5Hivg3ryy9rTucMGjSIdevW1Xg8PT2d++67j/vuuy/eYYk4SHvycVJefZGyfz1F1RVXHf3F55yDv0s+tvXrcH46D8/ICxITZAIoJcU0uvEa8PspWLOp1jcYb9/+6Glp2NeuQdmzB72ebYyxr/oFAF/3ngDo2Y0pnf6SiREJIUqfnEr5HZPQs7JCj/k6dsKxdDG2zZvwnnq6idEdWzCR9HXrXvsLguVEGhDLrEkT9Zzfj+vjOSi6jre2tWhHUhTKp/ybwjmf4jnv/PjHl0DOL79A8XrxDjqx7k+ATmdosb2zHi6ItW39HQBfl64mRyKECLHZ0Nq1P+x9xz36IkonP473pKEmBhYe25rVwMFlFKHHN24gp2cXGp97hhlhmap+FTQSluVYuhh1/3587Tvg79EzrGN8Q09Jyro2znkfAeAZft5RX+cddCLOr+Zj27I5EWEZquCXDai7d6HnHWxvpRQUYF+zCq1JU/z5krwJYQXe087Ae1r9SG6CI2nB9WhB/hatUPfthYL94HZDdSeihkBG0oQhHF/NB8BzzvDoFnceUXql3vJ4cH4RqFMUrO9Tl8qrr2X/xu1U3FEPN8bYbGitjjvse53y2ktkjxlJymsvmxiYEA2T4+svyR52GqnPPm12KFErfnsWxW+8iy+4pi4oLQ1/h44oPh/29WvNCc4kkqQJQwRLSUS65kHduYOsP44i+9wz4xFWwjmWLEItLcHXtRta+w5Hfa2e3bjmzs96zN+xMwC2Tb+ZHImFaBrq5k2hXXdCxIt9/VocK1dg+/2IkXldx/X+u6Q9/igJa8cTJa3VcXjOGnZYj+eg4PrX4M7yhkKSNBEz5UAB9h9XojsceE6su/RGbbTcPOwrV+D45aek+OPuXPA1AJ7Tz4rsQE0zPpg4cb35GtnDTqtRPkVrHSjYa9u504SorEXdvo30B+4l9/gO5A46gfQpjxx8UtdxvfcOVLe8E8II6rZtAPjbtDv8CUUh4/57SJ/yCOqu+vu76a9ep2avXrfWUEiSJmJm//knUBS8AwdDenpkB7tcoYrSzo/nxiG6BHO70dPS8Z5yalgvT336SXJ65Yeqa9cH9jWrcaxcgVJ4eFsvf4tWAKi7dpgRljXoOin/+y85Jw8kbdpU1AMH8DdrfthCaMdXX9DoxmvIOWUQ9qVLTAxWJBPbtq0A+Nu0qfGcv3pU38rrX50fzibzpmtxfjqv1ud9HTsBYNtcd2mjZCRJmoiZ97QzKFi7mbLHn4rqePeIkQC4Pv7QyLBMUf7QI+zfsBXPKeFN+ypeD7bdu7CvXRPnyIwT/GMQHDkL0vPy0B0O1AMHAlvlGxqfj4zbbybznjtRKspxjxxF4Wdfc+CX9VRMuvfg65wufF27YduymewLhpHy8gzzYhZJQw3+Xh7XusZz/lbBD1DWHUlzLFlEysy36yyI7e9QnaRtrP8zLpGQJE0YQs9uHFqTFCnP6Wehu1w4li1F3bPb4MhM4HAE/glDsISFrR4thlW3V0+rtD7iE7uqorVoCYBtt3X/GMSLbd1aUt5/Fz01leL/vULJjFfxndC3xuu8J59C4ecLqJhwG4qmkXnnxHq92FtYg21boCyOv3XbGs9pzQO/l1ZO0my/bwHA37Zm/AD+Dh0pfWQKZY/8K4FRmU+SNBEbTYu9n1pGBp7qLeLOTz42IChzqFs2B7aHRyBYqsJeS3Fnq7LtCCRptX1iDyZp6o6GN+Xp796DkhdepmjmHDzVbb/q5HJR/veHKX3s3+iKQsY/7sP1wfuJCVQkHaW0BLWoCD019bCyOEFay+oPT1ZO0qprL2pt29X+grQ0qq65wfIFeY0mSZqIifOLT8np3ZW0QxdGR8E9IlDQtj5PeWZdfgl5XdpEtJPP374Dut2Ouu13KC+PY3QG8XpRCgrQVRWtSdMaT5f8Zzr712zGe/IpJgRnkkM+pHjOORffgEFhH1p11TWU/+P/AZD26D+TskWaSACfj4rrJ1D1p8trLYHkD354suqmHl0/ZCStnamhWI0UsxUxsS/7IdC8N8IRpCN5zjmX0sf/D/ewo9cWsyp1z27s69aip6Xh7xTBtK/Dgb9jJ+zr1mLfuAFfL2v3qVUL9qPoOlpeE7DZajyvHTkFmuSUslKyLjyPyhsm4P7DxVHVCKy8fgJ4fbgvHhv2NLkQh9Ib51D+8OQ6n9eat0S3cAFYZd8+lIoKtKxs9KzsOl9n/3EFzvmf4+3bH+/pyVG26VhkJE3ExPFDYHeat//AmM6j5+ZSdcVV9a6HZZDj+++AQBcBnM6IjvV3zgfAVg82D+g2e+AT+yV/MjsUS0ib/DCOn38kddqz0degUhQqb5mI1qy5scEJUc3XfwD7t+6l5OU3zA6lVrad24Hal1AcyrHwO9If+384P/8kEWFZgoykiej5fDhWLgdiT9LqO8fSxQB4Bw+J+Niqiy/F228Avt59jA7LcHqTJkf9xG775WfSH/sn/vYdKH/40QRGlnjqpo2kzpiOrqqUPjkV7Aa8nbrdpM6YjnvYuWgdOsZ+PtEg2NauQSktwd+pc+39glVrj8fodgfuc4Yfc6ozWF7EVr15qSGQJE1Ezb5mFUpFBf627dCbNIn5fEppCemPPIRtwwaKZ35gQISJE6x35R04OOJjPcdoH1WfKFWVuD77BG/ffmaHEnfpjz+K4vdTeell+Hv2MuacjzxE2nPPYF/+A6UvSHstEZ7U554h9c3XKH3iaaouH2d2OBHz9+hJyWvvHPN1wZE227aGk6RZO70WlmZfuQIAb7/+hpxPT0vH9f67OBd8hbqp/hQsVMpKsa/6Bd1mw1tLyYVkYtuwHvviRSj799f6fHAzgbpvXyLDSjjb+nW43nsH3eGg4i93GXbeyutvQk9NJWXOLOzLlhp2XpHcbLt3AaAdZblI5g1Xk9u1HfblPyQqLMMFy4uoDWgkTZI0ETX7Lz8D4Otp0GJ3mw1P9fZq51dfGHPOBLCvXIGiafh69oq84wKA34/zozmkTn/O+OAMljrjeRpfMIyU92v/1KvlBUZU1X17Yy/NYmGp//0Piq5T9acr0NrUXtcpGlrLVlRedxMAaU89bth5RXJT9+wBQGveos7XKGVlqAcOoO7dm6iwwqbu2I6yb98x2+PpubnoqamoxUUoJcUJis5ckqSJqFX96TLKHngYj4G7bDxnnA2A88v6k6R5Tz6FA4tXUPboE9GdQFVpNOFaMv52l+XfeIJv8FrTOj6xZ2Sgp6WhVFWhlJclMLIE8vtxLF4IQOV1Nxp++orrJ6CnpuL67BNsDaxPoYiOuicwkuZvVneSFvoAtd96o9yZt00gr3vHY384VxT81VOeagOZ8pQkTUTN16cflTffFmp8a4Tgtmrnwm8jLgxrGkXB36ETvr5RTvsqSmjBrJV76wGoe6s/sdeVpHHwj4FiwU/shrDZKPxmMUUfzMPfuYvhp9fz8qi69DIA0v4jnQjEMbjdqAUF6DZbrYVsg3QLJ2lqdYeSYP/fo/F36oKvYyeUinpQV9IAkqQJS9GaNcfXvSdKRQWOJYurhVdwAAAgAElEQVTMDidh/O3aA9VdCyxMCSdJaxKc8rTeHwPD2O14TzwpbqevuOFmdFXF9f67gWkgIepw2AenWmoXBmnVCZxixSStusiu1qLukcCgkpffoHDRioiKRtdnkqSJqNgXLyLtyX9h/2ml4ecOTp/WhylP26pfyT7jZNL+PSWm8/jbBpI025YtBkQVP2r1hgHtKJ/YPaefRdVFl6BnZiYqrIRR9uxBKTwQ9+to7dpTMfEvlD71bFLeR2EcNYxNA2Dd6U6lrBS1rBQ9JQU9u7HZ4ViOlOAQUXF9MjcwFePzGV7fy33e+eD3h1pFWZlj8fc4fv051IMzWtpxxwEHizpakseDWloSmFY5SlXwikn3JjCoxEp75t+kvvgCZY8+EfdSBxV33x/X84vk4OvTj4IVq1DcVUd93cEkrfad2WZRd+8GArMoEXXscLvBwl0UjCJJmojKwZ2dvQ0/t6/fAHz9Bhh+3nhw/FBdxDaK+miH8reqXgy7w7pJmlo9gqQ3zomq/VG95/fjmv0+iteLr0dPs6MRIsBuP2alfgB/p86U3/5X/F1i+0BptODI3tGWUBzK9usvZI85D3+79hR99k08Q7MESdJEVOxrAk3Efd17mByJuRwxFLE9lNaqFbqqxtwDNZ60vCYUrFyNUnaMXZuVldh2bEe32dDad0hMcAngWPgttr178Ldrjy9B9fDUTRtJe/Zp9Kwsyh94KCHXFMlJO641Ffc8YHYYNQTXXAZH+o5Fz8tDLSqCBlIrTZI0ETGloAB1/z609IywPsFFew3XnFmgaVSNvy4u14iVunMHtu3b0DIb4e/aLaZz+XqdwP5t+6zdYNtmQ2t13DFf5vr0YxpddxXukaMomfFqAgJLDNfHHwJQdeEfEjaSqHg8pL76IlrjxpTfc7+1fz6EKVL/+yyOJYupHH8d3pOGmh1OxLwnnUzR+x+hh1ljUmvaDN3pDEzbVlRAZhS1KesR2TggImZfvxYAf35+3P5YqTt3kHnXHaQ986Rli6IGm8v7+g846q6qsNhsSfMHWMu17i6yqOk6zi8+A8BzzvCEXdbftRu+/K6ohYU4vv06YdcV9Ydj6RJcH30QKCB9rNcu/BbXu2/BsUbDE0jPycV78in4+oTZSk5VQ0V7g5smkpkkaSJitrVrAOK6tsHfvQdaXh62nTuw/bYhbteJhX2pMevR6gvnvLk0GvfnwJv8UWjVDZ7VosJEhJUQtvXrsG39HS03N/w/JgZxjxoDQMrs9xN6XVE/KAXVO65z695xHZRx1x00mnBdvW9QHkzSbJKkCVELVcXfth2+bsYVsa3tGp5TTgPA8c2X8btODDzDz6Pi+pvwnHGWIefLuOsOcnp3xbHga0POZzT76l9xffwhtg3rj/o6PSeQpCmFyZOk2VcuB8Bz5jmxj5pGKJikOT/+CDyehF5bWF9o4X0Ya7oOa9tmESkzppP+0AMRfRj3t2gJgLprZ7zCsgxJ0kTEqq68mgM//EzlDRPieh3PqWcA4Pzmq7heJ1reoadS/vCjho2sKGVl2HbttOynXOVAAXAwCatLaCSt8IBlp6oj5R77Z/b/soHyO+9J+LX9nbvg69oNtaS4QRV4FuEJJWlhjKTp1b+bioVGuV1zZpE29amIpi615s2Bg0Vwk5lsHBDRi/PiaW91s3XHwu/A602aNVt18VcvyrdqGQ61IJCkaTm5R39haip6aipKZWVgYW80TectSG/WDLNSTs9Zw7CvXYPz80/xDj3VpCiE5fh8KIWF6IpyzA9PAFrjQLFY1UKj3JGMBAa5R16Iv1OXBrHURJI0ERmPB6Wy4qjFTI2itWyFr3MX7BvWY1++DN/gE+N+zXA5P52Hun8fnjPPDq2PiJXWMtC3Tt25w5DzGU0NjqTlHiNJA7TsxtgqK1ELD6DV9yTNAh8Q3KNGg82G+/xRpsYhrEU5cABF19Fyc8F+7D/nwYr+VhpJiyZJ8w0ajG9QIEFL7OKDxJPpThERx4pl5HVuQ6NL/5CQ63mGnxdoE6Va60c1dcbzZN5+s6HTT1qrQJJms+hImnIgUMz2mCNpQMkLL1P4xQK0Jk3jHVbcpU95hJx+PXDNfs+0GHy9+1D+t7/j63WCaTEI61F0DffIUXhOD29drFadpKkH4t/aLCw+H+qBA+iqit5YWkLVRkbSRERs6wLlN/QIPvXEovz+fyTkOhHx+7H/sBQwdmen1bsOBEfSwknSkqn5sWPht9i2bUXPyDA7FCEOozVrHlEtwmAiZJWRNKUguM41N7INOZWVpMyaiVJWiufG+K6NNpskaSIitnWB8hs+i7UWSSTbmtWoZaX427RFq95lZISDI2k7AgvuLdZ6yTt4CP7du8Ka7kwaZWXYf1yBrqp4B5k73a4UFJDyzpso5WVU/PVuU2MR9VPVmD/ivuBC9MxGZocCHDrVeexND0fKnDgB3W7Hc/2NRodlKZKkiYjY160DwN81gUma14tj+Q9ojXNibmRuhOAUp9fg0SK9URYVE24LrM3QtISXejiW0v9MD/u1zrkf4vzyC9wjL8B7+plxjCq+HD8sQfH58J7Qx/Q/bIrHTcbf70VLz6Ditr+Yvk5OmE/Zvx+lqjLwnpGScuwD0tNN2/xSG8Xvw9ujF/6OnSI7MDUVrXFj1MLCwGhcnjWSzniw1kIfYXm2DYEkzdc5P2HXTHvmSbIvGE7qjOcTds2jCTVVN3pkRVEo//vDVE641XIJWqQcK5eT+uqLOH5cYXYoMXEs+R4A74knmxwJaC1a4uvUGbU8MLonROoL08jt2520p/9tdihR8fU6gaIvv6N0+ksRH6s1bxi10iRJE+ErK8O2exe604nWuk3CLuupLjngsEi9NMeSOCVpVuZ2o27bilJWGtbLg7XSFKssUI6SY/kyALz9B5ocSYD35FMAcH63wORIhBWEyuKEUSMNQCk8QNZFo8i6ZHQ8w0qIUK00SdKECLBt3gSAv137hI70+Pr0Q2uUhX3TRtRtWxN23VqVl+Nv1x5/8xZxmXq1rVuLc84sbJt+M/zcsbCv+oXcfj3IGj0yrNcHFyjX69ZQmoZ9ZWDEytevv8nBBIQ+sEiSJjhkTVeT8DZy6a4UnAu+wvH9d9YoNO12Rx3Hwa4Dyd0aSpI0ETatfXuK3nqP8gceSuyF7Xa8Jw0FLNB9ID2d4llzOfDjmriUBUl9cTpZ11wZauZtFUpREUDY9fFCI2mF9XgkTdcp+d8rlP3jkVANO7N5hwR+DxxLF0NVlcnRCLMF+3aGvds+NRXd5UJxu6GyMo6RhSfj7r+Q1yoX1ztvRnxsqMm6jKQJEaBnZOI942w855yb8Gt7gt0HzE7SguJUt01r2ixw+r3W6a0HoBYHkjQtO7wkLTSSVp+nO202vKeeTuWNN5sdSYiem4uvW3cUtxv7jyvNDkeYLJKWUAAoysFaaRYY5VYL9qP4fOhpkRe81pq3QE9LCxSbTmKyu1PUC97TAkma89uvAzsfTSpua1uzGn/nLmFV946G1qx6ncXePXE5f7SU4mIA9KyssF6vWbBHYLJwDzs3sOTAKbs7Gzq1eiQt7CSN6g9Qe3ajFBaCySPEwfZU4bS0OlLVFVdRNW48NptCqtGBWYgkaSJsaY8/CopC5ZXj0aOoaxMLf/uO+Fu3CVSo3rkD7bjWCb0+gFJSTOPTTkTPyqJg1ca4lEDQmgYq9Kt7dht+7lgoxRFOd+YERnz87drHM6y4Sn/oAbTGOVRdMS4hbdDCVXHvA2aHIKxA0w4uQwhzhBsOfoBSiwrxxyWw8AU/xAVH9yJisS408SJJmghb6oznUffvp+pPlye+1o6iUPjJV4Hk0KQir/ZlP6DoOr6OneNWo+rgSJrFpjuLIpzubNKEwm+Ma5mVcB4Pqf99Fnw+qsZdbXY0QtSqaM6nqCVFEY3sh/p3WqDJejAGaQlVN0nSRFiU4iLU/fvR09IMaygeKT3MHUzx4lhaXcQ2jqU3Dq5Js9p0Z2QjafWdbd1aFK8XX8dOphexrY1SVop9+TJ83bqjN63//VFFFFQ11GQ8Ep6hp6BnZYVKWJhG10Pr4qIaSfN6aXzGSaiFByCJd3hKkibCYtu0EQB/uw6mtytSCgoCfRRdroReN1QfzcB+nUfS8pqgKwrKgQLw+y1T1LbyxlvwDB+Br+vx4R+k61BREfg+xWkNX7zYV/0CgK97T5MjqV3mbRNwfTib0qeepepPl5sdjqhHqq65AUvsCy4vR/F40FNTITWKVWUOB+quXaglxVBYCEpi/x4kSsOY1BUxs20M1O2KuH2HwTJvvp7c4zvgWPhtYi/sduNYUV3YNI5JGnY7B35ex/6tey2ToAH4O3fBc865aG3ahn1M9oizaNK+BfZffopjZPERTNL83XuYHEntvAMCxXXty5aaHIkwi23Vr6TfdxeumW+bHUp07HZKpv6Xsn8+FvUpgmt42W2tNbxGkiRNhCU0ktaho6lxaM1boOh6wuulOVYsQ6msxNe1W9w3TWjNmidFX0Y9PQOwxtqXSNlX/QqAr4c1R9K8fQLFdaUMR8NlX7uatOefw/nZvMgOLCvDtma1+QWzU1JwX3wpVZePi/oUweUhkqSJBi/4C+0zOUkL1ktLdJJm/2FJ4PrVbXkamrQnHiPtX5NRSorDPiZYrkON4BhL0HXsv/4MWHe609ejJ7qqYl+72hJFSUXiBXdG6hGu53J++Tk5pw4m/Z//iEdYCSUjaUJU05o2x9exE/5OnU2NwztwMHpqKvbVv6IkcAdk5S23c2DBEiqvvTHu10p5YRrZ556Bc86suF8rXKn/fZb0f00Gry/sY7TqJE0pKYlXWPFRUYF38El4e/RCq249Yznp6fjzu6L4fNhX/2p2NMIEwRpjWoQ1xkK7O02uYWhbu4bU6c/hWLQw6nPISJoQ1cofeoTCRSvwDRhkbiAuF97BQwBwLkjgaJqi4O/aDa19h7hfyrZrF47ly7BvtEj/Tk2LuJgtgN6oOkkrrmcjaenplLzyJkVffmf6Jpmj8fXuA8iUZ0MV7UhasKaaavIyBMfSxWT87S5c774V9TkkSRPCgjynngEkcMozwY2Iteo+fEp1yxezKWWlKLqOlp4RWT2m+jrdWU94q5M009cWCVOERtIiTNK04IenUnNHuIN9fSNNMg/lHXwSlX+9C4YNMyosy6lf++KFOSoqUDzumH6ZjBTq4/ndgkACFefRjrTHH8X5xadU/OWuhPQt1XJzgYMtX8wWTVVzOOSPQXWNtfrCtuk3tJxcy/y818X9hz/iGXlBqACyaFhCSU6k052NAnX/zB7hjjbJPJRv4CAqTxxMak4GHCgzKjRLkZE0cUzO+Z+R16UtmdeNMzsUAPzHd6f4xdcpTNB0lPObr3CsXEGi2iwER9LU/QWJueAxHJzqjCxJ855yGiVPP0fVpZfFI6y4aTT+SvK6tMW+crnZoRyVnt1YErQGTGvWHH+79qH3i3Dph46kaVo8QgtLaLpWug0clYykiWOybdkCHDL/bzZFwXPe+Ym5VGkJ9hXL0FUV7+D4dRo4VLDEh1VG0tTqkTAtgvVoEKit5u/cJR4hxY/fj+239YH/NLkmYEQSMKIsrKXsyanRHWi3o6elo1SUo5SXmdZRw4iRNHw+HF9/Dd5KGH6BMYFZjIykiWOybf0dAK1tO3MDMYFjwTcoPh++/gMT1hJJyw0kaYpFkjQAX/sOaK3bmB1G3Klbf0dxu/G3aBkacbCylFdfovGJfUn533/NDkXUI0UzP+DAV9+jp6aZFoMhI2mKQsbYi+Cyy8DrNSgya5GRNHFMtt83A+C3UpLm9ZJ5+83Yl/9A4TeLwemMy2WcX34OgOfMs+Ny/tpouXlUjbkIrZk5PVKP5D35FAqX/BjxcUpJMa533wabjapx4+MQmfHsG9YB4O+cb3IkYfL7sW/8DcfKFdZo9SMSQ9cDbeOibLfm6z/Q4IAip/j96KqK1jiyNXWHsdnQmzRB2bMHZd8+sMh7ppEkSRPHpFaPpPnbtDM3kEM5HNh//jHwB+r77/Cedobx19B1nPMTn6SRkkLptBmJu16cKGVlZN7zV/zNW9SbJM22LpCk+fLrR5Lmq25bZV+9yuRIRCIpJcXkdW6Dv9VxHFi52uxwolL00WeGrInTmjZD3bMHde+epEzSZLpTHJ3fj23b1sB/RtC3MRHc554HgGvuh3E5v23dWmw7d6A1aYqvR6+4XCOZBXd31qcSHPVtJM3fLdDw3rZhXdJO94iaQq3Wouzvm/LqS2TcdhP2n0yusaeqgX9iEFwrre7dY0REliNJmjgqdddOFK8Xf9NmkGbe+oXaeEaOAsD18YeBoX+DaccdR8n0lyi/94GY30gipW7fhn3pEpQD5u/wTH/wPnI7HkfKS/+L8MB0dJsNpaICPJ74BGcw2/q1APjzu5ocSXj0jEz8bdqheDzYrFL8WMSdWhTbonvHd9+Q+uZr2DasNzIsU+jVraEUSdJEQ6Tl5FL0zmzKHvu32aHU4OvRC3+bdqj79uKo7q1pJD0jE/eoMVT9+QrDz30sGXfdQeORZ+NYsjjh1z6SUlKMWloSeaKqKKGCtvWlNVTJi69T9PYsfD3rz8ip7/juANjXyJRnQxEcSYu2lp+eae7vpbp7Fzn9e5I1dkzM5wqNpO1JXJvARIpLkrZz504mTpzI4MGD6devH7fccgs7duw45nHTpk0jPz+/1n/Ky8vjEao4lrQ0vKedkbCSFxFRFNwjA9uunR99YHIwxtKrd3iqFug6oJSVAqBnZER8rB6a8qwfBW21Fi3xnn4mekam2aGEzXd8YMpT1qU1HGp1IVstyp2RoQ9PJnUdUAoKsG39HXXnsfOCYwk2WVf3JWeSZvjGgaKiIq644goqKiq48sorsdvtvPjii/z5z39m9uzZZB+lavmGDRto2rQpf/3rX2s853K5jA5VJAH3yAtI+8/TuOZ+SPnDjxpWK8r54Qe45n1E5ZXj8Q0abMg5IxEqaGuBMhxKaXWSlhl54qI1ysKG+dXNk5nnjHPAZg+1SxPJL9aRNK2664Bq1khaSXQFsmvjvuxK0ifcQIVPBfNq88aN4UnaSy+9xI4dO5g1axZduwbWdQwdOpTRo0fz4osvcvvtt9d57Pr16zn++OMZNWqU0WGJKKW8+ALqnt1UXXwpWoeOZodTg69vf8rvvs/w3Zcp776F65O5ePsNMCdJs1CtNLUs0G4lmtElPbsxWlY2itttdFiGc37yMa7ZM3GPvBDPyPpTGNM3cBC+gYPMDkMkUGhNWk60053mtoYKXjeYLMYkIwOygm2hEttnOREMn+786KOP6Nu3byhBA+jatSsDBgxg7ty5dR7n8/nYvHkzHTp0MDokEYOUd98i/d9TsO3eZXYotVNVKu6YhK93H+MqrpeV4fx6PoBp07yh/p37zU/SlFCSFvl0Z/G7synYsBXv4CFGh2U4xw9LSHl/Jva19bOkgWg4PGcPo/Sxf+M5e3hUxx+c7jQrSavuB1wPCkabzdAkrbi4mG3bttGjR48az3Xv3p1t27ZRXEfmvmXLFrxeL506BVqxVFZWopnYV0wE2H7fAliskO3R6LF/knLN/wylqgrvgEFozc2pu2Ol1lDB6U4tmnVa9ahVkW3TRgD8FhwxPhb7jytIff4/2H7bYHYoIgF8vU6g6qproi5KqzVvgbd3H7TW5pRVCq6F0yNsNVer0lI4+2wyRw6L/VwWZOh05549gS2wzZvXbPrbrFlgB8auXbvIquUbs359YCvw0qVLefbZZ9mxYwdpaWlceOGFTJo0idTU1LBiUBQl7tUSVFU57N9Jq7wcdd9edKcTpVVLbDZjvt543D/HnA9InfoUlTdPxHtBbNPlKe+9DYDnwtGGfc0Ra1K9Ju1AQa0xJPJnsPKvd6Lu3YvSrKl59yMOjryHts2BJE3v1KnefZ1pL72A643XKJ/ixJ2fuH6pDea9ME7Mun/aKadQ+uUCAKKrtBYbW3DDQlZWzL9rakY6fPklDk3DpkffhcGqDP1qgjswU1JSajwXXPhfUVFR67EbNgQ+Af7000/ccMMNZGVlsWDBAt544w02b97Miy++iBLGp/Lc3PSwXmeE7Oz0hFzHNLsCnQaUtm3JaWL8sLSh969wLyxfRuZ7b8G4P0d/nj174PPPwG4n/ZqrSM+JfIrPEEMGwLJl2Js3J+coMSTkZ/CWmwCIqkre9Onw2GMwfjzcc4+hYRklOzs9UPl88yYAsvr1gmyTvu/R6t8X3niN9N/WmvIzm/TvhXEW8f174w2oqoJRo6B6aUS9cvop4PkLqWedSaoRP695ebB3LzlaFeTUHCSqzwxN0vTqqabakqTgY3UlUAMHDkTXdcaPH09m9S6yYcOG0bhxY6ZPn878+fM566yzjhlDQUF5QkbSsrPTKSoqR9OSb6FikOOnVWQCntZtKTtQZth543H/lBEXkn333TB3LsU/rkKLsjtCyvQZpPn9eIaPoMyeVr0Y1STtq6ve1xJDffkZdBUUk75xI1Ubt1Bh5r2sxaH3UN++g8aVlWi5uRRpdnO/71Gwt+lII8D78y+UJjD2+vJzaFXR3r+svz+I7bcNFHXthdY1ysoHmgbl5RDFru2Y9Tsx8A/E/LumqgrZTZvC3r0Ur9+M31nPPmDBUT+IG5qkpVVXpK+qqtnqN/hYRh2Lj0888UROPPHEGo+PHTuW6dOns3jx4rCSNF3X41F8vlaapuP3J+8bk3PLFgD8rdvG5es09P7l5OEeNYaUd9/C+b8XKH/goahOUzl8JHpRMd5BJ9aL723cfwYrKnB98D56Ti6eYedGfLi/ehcZRUWWvZ+apqP+FqjW72/f0bJxHo3eKTDFaduw3pT4k/29MN4ivX9K9e5OX6Ns9Cjuu1JWSm7H4yA1jf1bLLopLBLVtdL0PXvxd0uun0NDx5xatWoFwN69NYvKBderNa2+meHKrR7KrWuaVMSPnpKKr2s3/F0St8YlFpVXXwtAyusvQ2VlVOfQ2raj4q6/xadhe4TS/98/aDT+CpQ95rU7UfftpdFtN5FxT83aheEI1kFSLN6/U09JwT38PDxDTzE7lKhoLVqipWegFhSgFJjfSkzEka6jFFXvjjxK3dGjniItHRQFpaIcfD4jowuLfekSHAu/Na6YbrCgrQWKfxvN0CQtMzOTNm3asHp1zS3sq1atok2bNrVuGgC4+eabGTt2bI3HN20KrBM57rjjjAxVhKHq8nEULlhC5bU3mh1KWHx9++M9oQ9qYSEpb7wS+QkM2BlqJOfnn+L6cDa2vbtNiyGW8htwcPeWavFitr5+Ayh55U0q7nnA7FCioyj4O3cGDjaJF0mqogLF50NPTYVoi7yr6sFaaSZ0Hci4bxLZo8/Dtt6gn1VJ0sI3fPhwli5dGtqtCbB27Vp++OEHzjvvvDqPy8nJYeXKlSxZcrAHo6ZpPPfcc9hsNkaMGGF0qCLZKAoVtwVGfFLefiOipMv22wYaD+5DyqsvxSm4yGk5OQAoBw6YFoMSQyFbAM3EPwQNjb9zPlqTptLdIckFq/VrMdYY0xuZV9A22DPUiI4DAJx0ElWXXYGvS9djv7aeMXyv6vjx45k9ezZXXXUVV199NbquM2PGDFq2bMm4ceMA2L9/PwsXLqRNmzb06dMHgFtvvZX58+dz0003cdlll9GkSRM+/fRTli5dysSJE2nXrp3RoYpjUIoKA79E9ajWlefc8yh5+jnco8ZEFHfaU49j37wJ+48r4PJx8QswAsGWL8Hq4mZQy6rfTKMdSatelBystWZVtjWr0XLz0Js0qVc/74cqfepZcDjMDkPEWTCpirXGWHAkTS0tSXg3JaMSzZCLL6birBFJuS7S8CQtOzub119/ncmTJzN16lScTieDBg1i0qRJob6dGzduZNKkSYwePTqUpOXl5fHGG2/wxBNP8Oabb1JZWUmnTp147LHHuPDCC40OUxxLVRV5XdqiZWVTsG4Lcd8yaxRVxT02shIcttWrcL37FrrDQcXNE+MUWOS0xhYaScuMrn2LlpNLxfUT0Jo2MzIsw2WPOQ+1oICCX9ajNaunW/glQWsQlPIydIcj5mr9WrDrQKL7d+r6wUTTiLZQSS4uVd/atGnDc889V+fzgwYNYt26mnPRbdu25emnn45HSCJCtp3bgepfovqSoB1BKSrE+cnHR0/aNI2Mu/+CoutUXHk1WnvrtCXTG5s/khZM0rQoR9LIyKD84ckGRhQHZWWoBQXoLhdak8g2NlmSxwNOp9lRiDjx9RvA/u37weuN6TymTXdWVaF4veguF9RSUzUqHg+2Vb+iVFTi69vfmHNaRHKV5hWGUbcHkjT/ca1NjiRKbjeNzxyKbdtWirMb4xle+5rG1OnP4Vz8PVqTplTcaa1iq5YYSSuPbeNAfWDbthWo/lmvpx9IANA0Gp86GNvG39i/YRukS4HZpKUoMSfildfeiHvUGHy9TzAoqPAEpzoN7du5fTtZp5yIv3UbDiz/1bjzWkA9fkcS8WTbvg0ArVU93VXrclF5VaAkR+ZN12L/aWWNlzi+W0D6g/cBUDrlSfTqpMgq/O074DnxJLQ2bUyLofLaG9n3+x7K//Zg1OewL1uK89N5YNEyOurWQGeNaAsgW4aqBqaSfD7sm34zOxphcd5TTsN90SUJf48PjtxpRvTtDDp0d6fFdunHSpI0USu1OkmrtyNpQOWEW6m6cAxqWSlZo0fieuv1w6YI/B06orVoScUtt+M573wTI62dZ8RIij+YZ24JFEWB1FRIi6opFACZt9xA1uWXYNu5w8DAjKP+HkjS/CY1mzaSv3OgS4VhpQ2E5aS8MI3Gpw4m5eUZZocSFX+HjhT8tJbiN2Yad9L0dPTUVJTKykAXhSQiSZqolbojMN2p1eMkDUWhdOrzVI3+A2pZKY1uvZG8zq1xfvgBAFrLVhTNm0/53/5ucndvDgMAACAASURBVKDJLbTD06IFbdVt1UlafR9JA3ydg50HJElLVrZt27CvWR3zjmnbLz+TOm0qjgVfGxNYuOz2QPHldu2NO6eioOU1AZKvVpokaaJWttBIWj2d7gxyOimdNoOSp5/D17kLSkUFcHA4XGvW3LrrkHQ9ULjSxI4D6f98kOzzh+H4bkHU5zhYNNOaZThsvwenO82bVjaKvzpJsx9Sp1Ikl+CHnVhLcDiWfE/GA/fi+vhDI8IynZ6kSZpsHBC1Kr/rPtx/uBhfj95mhxI7RcE99s+4L/lToPZbavRTd4mk7NtHXo9OaLm5FKzZbEoMtrWrcSxZFNrlGY1gIVyrJmnljz5OxbU34queKqzP/J0CXQdsmzaaHImIF7W6JVSsa7rM+r10fjqPlNdfxn3uSNyXXmbYebWmwSRtv2HntAJJ0kStfAMH4Rs4yOwwjKUoltsccDTBvnxKYSFomikjfsE38OCUZTRC051l1kzS9JYt8TVrYXYYhvB36AiAbcumwEhsPS3MK+p2cCQttmr9ZiVptnVrcX3yMf6OnXEbeN7QSNq+mr3D6zNJ0oSwKqcz0DS7vAyltMS4FioRiLV3J4DW6GBlcxFfelY2Zf94JLBMwe8Hu7zFJxvjOg5UJ2nl0Y+SR+NgCQ5jC9lW3nEn5Tfcgr++ViSog/wGixrUzZtIees1fL36WHLXY0Oi5+RAeRlKYaFJSVr1SFoMSdrBjQMWTNI2bCB90t14+w2g8voJZkdjiMobbzY7BBFHanH1dGesvTurf6cT3VdXMbolVDWtXfukbAtl0RXTwkz2X38m/cnHA03KhamCBW3VQnMK2qoxNlgHqLxuAgUrV1Nx4y1GhWWc1atxzX4fx9dfmh2JEGGpuvQyKq8cj56XF9N5zNrQo8RpJC1ZyUiaqMEW7DbQuh6X30gSwSbrSqE5raGCI2laDEmanpuLZT/fbtkCJEEh20PYNv2G87NP8LduKyPhSajijkmGnEfPyEB3OhPe8zU4oh7rdO2R1E0bSXt8Clqz5pTf96Ch5zaTjKSJGtTtgTY5WitJ0sym5VT37zRjJE3XqfrjpVSN+WNMxWwtrTpJS4ZCtkH2X34m44F7SXnnTbNDERamtWjJ/u37KVywJKHXVYMdBxoZu3xDqawk5e03cH42z9Dzmk1G0kQNoZG0+l4jLQlUXnMj7gsvwtenb+IvriiUPf5UzKex/fIz6Y8/ir9LvvUKB2+t/kCSRD/roR2em6UMR9IpL8exbClaXhP83XvEdi6Tdv56+w9ET09Hq27lZJRkLWYrSZqoISm6DSSJZCiDopaV4pr3Ed4DBWaHUtO26qLNLZMoSWvfAQDb5k2mlW4R8WHbspnsP47C17VbwkfAjFL+j/8Xl/PqubnoioJSUBDY2WyzxeU6iSa/vaIGW/V0p1+mOxu2sjLsP65A/X1LTKfRgguUrbi7szpJ01q1MjkQ4+gZmfibNkNxu0MfuERyOFi+wpj1XFl/uICcvt1Rd+005HymstvRc3JQdD2QqCUJSdLE4TwetGYt0PKaoDdpYnY0DZ7ttw2k/XsKrplvJ/za9jWraHzOaTS64eqYzmPZYra6DkOG4Duhb6A9WBIJTXlK54GkEqyRpmUbs55L3b0T2/ZtifsApWmov29BKYrPRqhknPKUJE0czumk8JtFFKzeKNMkFmDb9Bvpj/6TFBOStFAh2/Tod3bCIUma1YrZKgq89x4l879JuqKvkqQlJ6W6RppRI2mJrpWmFBWSO6AXOQPj024wGZO05HpnEiLJBOukxeuT59EY0W0gcPwh7WekVVFC+Dt0wt+8BWh+s0MRBlINaq4epGdUL0WIoTdvJELlNwwuZBvk6zcAnE701NS4nN8MkqSJw3m9gVEF+UNqCXpOdTHbA4kvwWFEtwEg8KaZkoJSVQWVlZYp56EUHgB3KTjSgeT6ea+8ZSKVt95udhjCYKHpTsOStOBIWmKWIqhx6jYQlEz10YJkPkscJu3xyeS1b0Hq9OfMDkUAWrZ5I2lqWezN1YM8Zw/HPXIUis8b87mM4nrtFWjZkrT77zU7FOPJh6ykFOrbaVCNsUSvFw0mg0a8pzQUMpImDmPbvh2logI9PcbRE2EIPTs7sK28uDjh28pDb6gxdBsIKvnfKzGfw2jqzsCONq1lS5MjiSO3G5xOSdqSRMWdd1M17mq0rMaGnC+YLKmJTtLi1RJK0wLr9jxe9GbN4nONBJORNHEYdXt13ahWyVM3ql6z2dAbZQW2lVcvGk6U4DoVLdbpTosK1QNM0p/17DOHktemKerePWaHIgyiN8rC37FzzH07gzynnE7FzRPx9jzBkPMdS3CDghEf/GrjnDeXvPx2ZN55W1zObwYZSROHsYUK2SbnH676yN+mLXpxNkplZUJ7YFZefxPukRegNW8R87mU0hKUwkK0nFywSNKX9CNpdhuKrqNu2ZJ0JUaEMTznnofn3PMSdr14T3dqTQJdDNR9e+NyfjPISJo4yO9H3bkj8J9JVIG9viua/y0Hlv2c8BEfrVlzfH37o7WMvdBr5oTrye3fE+c3XxkQmTHUnck9kuZv2w4A2++bzQ1EGCbjnr+SecP4eluk2DPsXIrfnEnlFbHVXqyLVj3CqO7bH5fzm0FG0kSIumc3is8XqDWTRFuYhfksVyvN40HZuxdUNWlHmbS27QGwxdgxQliH8/NPsW39nfK77zPkfEpBAfZVv6A3aoTvhPj3B9ZaHYcnjh+KggXYk6lOmoykiRA12Fi9tbSDEpD6f0+QceftqAYURLVa1wF19y4UXYcWLZKukG2Qv50kackmtLvToBIcjqWLyb7oAtKeeMyQ85lNz8hEd7lQKsqhvNzscAwhSZoI8bdtR8nTz1F5061mhyIOkf7PB8nNb0vK64ndIemaO4fUl/+HakD5D726f6eaoHpMx6I1aUrJR5/A//5ndihxc3C6c4upcQiDaBpKsJhtpjG7Iw+OcCfm99L17lukPfowtjWr43MBRTm4Li1JRtOS8yOkiIrerBnusX82OwxxJJ8PtbAQJcEFbQ8u8o39D0KoybpFkjRSU/GdeBLkZMCBxFRbT7RgkqZKkpYUlNISFF1Hy8g0bPQ3VMw2QR0HXB/NwTXvI3w9T8Df7fi4XEPLy8O2fRvq/n1o1b8D9ZkkaUJYXHBqQzWpBEfMHQdI/Cd2AVrLVpQ98DD+9h3MDkUYIDTVaVBzdUj8WlHFwALZdSl/4GHw+fB37hK3aySSJGkixPX2GyhVVbjPHYnetKnZ4YhqWlbgTVkpSoYkzRobB1xvvY5j3Wq4ehy0S4438xpsNipvTp56UQ3dwW4DxrVU0jISuwwhVCctjkma9+RT4nZuM0iSJkLSnpuKffWv+Pr0xSdJmmUEPzkrJQlM0jQNtbw6STOg+4T3pKEUv/Eu/uPaxHwuI7g+nYdr7hw4eUjyJmkiubhcuM86B621cb9DoenO8gQ1WDdwCUVDIUmaCDnYbUB2d1pJaLozgSNpwTft/8/eeYdJUWVt/K2qzj15BgaYYcg5Z5Aki4tExbCGFUXAsGYRdw0f65pzXuPqgoIJ3TWBiCKGNYOKSpRBwiQYJofu6e7qqvr+6K4awoQOdSt039/z7LM+M933Hsue6lPnnPu+ojsFYOM/XyR27oJAZ+OIxrLlh0P/kBe/BpyRsWz7Bdb/fYHg8BHgJ07WOxxKHAh9+6H+tf+ou6jLBYllwTQ1ATwPWK3qrn8cWnh3Wrb9Atva9yAMGAj/GWcT20cr6OlOCgCAqa8DW18HyemElJWldziUo1DanVrOpPE8+NFjERxBXjtJDxSrpM7xuykYGesXnyPljuWwbfhA71AoRoRhUPPND6jatkcTKRrZI1QkZAsFANxvu+F+/GHYPlxHbA8toZU0CgCALQ07DeR3pWbMBkMo6A7PTf8HoaCbZntKWdmoXf+Jausx9XVwPvsUwHHw3nizauvGhCSBPXwo9M+dOwN+Lc22tIXKcCQOinF4ejpgs6m2rtCzt2prtYkoQuiSB8bjAVwuctsoEhyJ4TpAK2kUAABXUgQgcS1yzIzUsSO8y26C/0/n6R1K7AR4uB95AM4XntU7EjC1NWACgZAsiNutdzhEEbt3B0CTtETA+fwzyBnUC67HHtI7lNhgWdR88yOqf9lNtBAg5oRdBxLEv5MmaRQAR7kN5NN5NApC8yl+v2rLHSPBIelbuWLLQ61OKTdX1zi04JhKms7XnRIfipCtSm4DMq4H70XagnPICcxqTKKJ2dIkjQIAYAJ+iOkZEGmSZkhsmz6G/Y1XVU2c2tzv4w3o0LUD0i5WSdzYbg/ZtQSDgM+nzpqxEgyCHz4CwcFD9I1DA6S0dIiZmWC8XjAVifGllaywYQkOeUZVLaw/bIb94w1gD5Wpuq5eSFlZkBgmJP4dDOodTtzQJI0CAGi6/CpUFRbBe90yvUOhtEDK0muQdu0Vmj0dKnpGKs6OGEXQVhg8BLUffwHPv1/WNQ6tEAq6AwC4A/v1DYQSFyR00oCQ3yUAsIQ1DC2bv0dO985IW3AO0X1gsUDKzgYjSWCqqsjupQE0SaMcC8fpHQGlBRStNI1kOGQJDjWEbGWUL4NGYwjaJgtCz54Q8ruGTKcppoVUu1MrayimsR6M1wMmECC6DwAE+/ZHcMBAME1e4nuRhp7upISQJHqq08DIT89sfR0EDfZT3AZUFJ0UU9PAQf9KGjwewOlMmgeShudW0L/tBEDWSVQ7SROVJI3s3yWroZBt3bvrie+hFbSSRgF4Htk985A5cTQginpHQ2kBUeNKGquiJZSMWNANwV69df+MpV53JXLysmFd976ucWgGTdASArmSJhJqdxKvpIWTNJGgkG0iQitpFLCHysB6GiE1NqqiLk9RH0ljQVtlJk3FJK1+5SuqrRUPXPlhMIIAKTPJRJsFIWmqh4lIw1PPg6mqhJjbSdV1tU7SSLoNHIMkhT7zGoj0koR+I1PAlYbkN+jJTuMiytZQWiVp4Ru2mIAee7KQrZgEEhwAwO7fh6yh/ZA5dbzeoVDigD9pEgLz5gMOh6rrCr37wD/9jxB69lJ13eNpfvAjn6Q5XnwOOd1y4b7vLuJ7kcbcKSZFFRTPznwqZGtUmitpdZrs13ThIvATJiI4dpwm+2mGJCmWUGpXJIyKlJMD7vAhSHW1dPaUcgKB2XMRmD2X+D5KJU2DJA0OJxifLyEEbWkljQIunKSJ1FjdsHivug4V+8rg/estmuwXHDcevgsuUtUyxvX4w8jumQfnk4+qtma0MPV1YJqaQsbxSTIbI6WmQczIANPUBCZBrHKSDaayEu67b4fj5RV6hxIzgZmz0fj3O8GfNJH4XrKgLZMAgra0kkahbgNmQMXZML2QGAZsYwPYev0kOGS3gWRpdcoI+QVga2vBlRQh2KGD3uFQooQrK4HryUfBDx4K38LF6i4eDIKprgYjChA7dVZ37aPgJ04GP3EysfWPRszJAQCwCSDgTCtpFHCl4UoabXdSwjheeRmOFS8oJ8rUQNFjIiya2RZs+WEAIPplZETErgUAALa4SOdIKLGgCNmqLL8BAJZff0bO4N5Iu9DE3sDHkUjWULSSRkHTxZeAHzMOwYGD9Q6F0grc7l1IuXkZxIJuaHiSvEm566H7wB0qQ+DUWaopnCunyHTUSQv27Y/65/6t3QkzgyB0DVXJueJinSOhxAIptwGgWbeM9MOTbcN6MH4fAlOnQcrIJLrXMSbrJp/DpEkaBYGZsxGYOVvvMChtIQiwffMVgtXa2JwwBHTSlC8DwqKZbcaQmwv/mX8CACSTGIVcSeOKD+ocCSUWWEJuA4B2jgPu++6EZddOVH/2DQTCSRpcLojuFLCeRjAN9USSW62gSRqFYgI0tYWSJCWRktxqJmn6V9KSlcCkqWi86z7wI0frHQolBhjFXJ1cksYmmE6a5x93QbLbIVmsmuxHCpqkJTlsWSlsH30IYcBA8ONP0jscSivIT9CsijNireLxgJGkkLm6ikKQRkjS7P9ZA7aqEv7Z84Du3XSLQ2uEQYPRNIiOM5gVWcSahKWS/CDGeD0hNxBCguZaJ2m+i5dosg9paJKW5Fh+3orUm26A/5QZNEkzMJI7BRLHgfF6gUAAcNqJ7cXK5uoqVtGA0AnDxuV3QMzLU3XdaHCsfgm2b79GcOBgiEmUpFFMjsMBoUsexI4ETiWzbHNr0NNIxltTkjQVs00kaJKW5DSf7KTyG4aGYSBlZICpqgq1PJ3kJCTkVqeosuyHlJODpmuXqrpmtDS7DSSHkO3R2NavA7e3EL5FSzQxuaaoh/f6G+G9/kZi60spKYCnEUwjoSTN6wUjipCcTsCqTfvR8uvPsPz4A4LDRyA4YpQme5KASnAkOVQjzTzIxsrEW54+P8SUVFMP27aIJIGTddI6JV+S5n7gbqTc/Q9wB/brHQrFYDQ88Qxq17wDkdBAP0tgxrU9bOvXIfWmG2Db+JFme5KAVtKSHFb27cyjGmlGJzD3dPA11ZAcDpA8UC4MGoyqfaWho+sqY1v3Ptj6OvjOOV9z42OmsQGM1wPJ6UzKSpKQ3xWWXTvBFhUBQ4bpHQ7FQPB/OIXo+vI8mqih9I3YQZbhMLdWGk3SkhyuJCRuKeQX6BwJpT08f79D+WdN5CMIaAul3nA12Npa+GfNgZSZpfr6baG4DXTMNbVuUqwoMhwlVNDWbGT8cSq4slLUvrseQp++eocTNULvPqgoqQTja9Jsz0QRtKXtziRHbndStwGKFjQLZ2p/wlMxVicxfG0C5Acx6jpgPtgj5WArjoRmughgW/se3PfcAW7HdiLrhzaxaTpCIR0taGtiaJKWzPA8GCEIieOSzibHjDBVVbBs+wXsoTKi+9jffB2ZE0bC9fjDqq+tq+uA3w+hYy6Ezl2039sACAXhSloRTdLMBkvQFgoA7OvXwvXEI7Ds2EZkfT1IFJN1mqQlM1YrqnbtR+XeEoBLJv11c+J65klkTp8Mx5rXiO7DlpfD8vteIsK5zf6d2idp/LTpqN5eiIYXXtJ8byMgn+BmS6g1lKng+dAsJcsSk69QHp4ICdraPvoQGbNPgfOfjxNZvyUSxWSdSJJWVlaG66+/HuPHj8eoUaNwzTXXoLS0tN33+Xw+PPTQQzj55JMxbNgwnHfeefjuu+9IhEg5Grdb7wgoESCma+M6wDTKekbqn8SShSzZRv1M1pNxHg0AhK7dQlp7BA6EUMjB1If/HtPTiX12SVtDsSVFsP6wWdN5SCkjE5LVGhLnDQQ021dtVD84UFtbi4suugherxcLFy6ExWLBypUrccEFF+Ddd99FRtjepiWWLVuGzz77DAsWLED37t3x1ltv4ZJLLsGqVaswcuRItUOlUEyFYg1VRzpJC4vZEjiJJeo4k5bsSDk5qCyu0PxULSU+FLcBgvNcSpLmIfN3ySpuAxqeqmYYVO4/BNhs2u1JANUraS+99BJKS0uxYsUKXHHFFbj00kuxYsUKlJeXY+XKla2+79tvv8Unn3yCW265Bbfeeiv+/Oc/45VXXkHHjh3x4IMPqh0mBYDr8YeROW44HK+t1jsUSgQ0W0ORrUIpN1QCrRU9raFSL1mIrGH9Yf3yC833NgQMQxM0EyLrIsqVdBKQrqTpIcEBwPQJGkAgSVu3bh1GjhyJ/v37Kz/r378/xowZgw8++KDV961duxZWqxV/+tOflJ+53W6ceeaZ2Lp1K8rKyA5LJyPc73th2b8PEAS9Q6FEgCxmS77dGa6kEWh3Nt51PyqKK+C7aJHqa7cHV1oM7lAZJBs5Sy3TQFuepkHs1BmNd9yLpiWXEdtDfiBjCT08UUuo2FE1Saurq0NxcTEGDz7RyHfQoEEoLi5GXV3Launbt29Hnz594HA4jvm5vNaOHTvUDJWC5gFi6jZgDpR2J2HHAcUWisRTr9sN2PVJkuQBYlnkMhlxPvEIsgf1hmPli3qHQokQsVNnNF1xNfznLyC3R1Z2yBs0jUw7UjFXJ/Dg1xauRx5A1thhsL/9lqb7qomqte/ysFhkpxYsV3JzQ9pEhw4dQnoLx4jLy8sxYsSIE37esWPoGC2tpKkPVxz27exKhWzNgNLuJDyT5p83H8G+/SB270F0H02RJEUvSQrfU5IRJnwdOKqVRjmKwKw5qJ41h9j68oOf1k4fTH09uAP7FT1QM6JqkubxeADghGoYANjDT89er7fV9zpbEOqT39fUFJlSMcMwYAkLi7Asc8z/mxJBAFsW/uAWdAXHaffvkhDXTw8KClD/4UaIWdlEryF/8SLw4X9WW5jF+ukncDx0P4JTp6Hp5v9TefU2aGgE09QEyekEm5YKMExSfg4lWSuttFiVv/lkvIZqEsn14379Bdye3xAcMhRiv/6tvs7IBKdMBdLSgR7dVf+uafMa5oYeyCxVRzT9jlMTVZM0KTznwLRwTFj+WUu/O/410b7vaLKz3RG/Nl4yMkwsXVFSAgSDQMeOyMrTp/1j6uunCylA52M99kx3DcUAsPl7WAu6wpmlYeuj+jAAgMnNRVb2sW1c013DeBgYshSyHyqFXcXrn1TXkABtXr+N64F77wXuuguYMFq7oNTk1psAACQHHVq8hj1CDyWO+lo4tLzfqIiqSZrL5QIQ0js7HvlnKa30pF0uV4vVsvbedzxVVR5NKmkZGW7U1nogiuYcwLVs24U0AMEu+aivJnOipzUS4frpDclraPlsE+B0IjhmnOoix1bGilQAfFUNGjT83FkK94c+79k5yuc9GT+HbHoOMgCIBw6iVoXrn4zXUE0iuX6uwxVwAPBYnfAT+pthSkuRPn0ypIxM1H33I5E9SNHWNbS60kL3m+JSTe830ZLVRgKpapKWl5cHADhy5ESvLHlerWMr8yBdunRBRQvKwPJa8kxbe0iSpNlhRVGUIAjmvDFJHTrBc8vfIWZm6fbvYObrpxeuB+4BV3QQTXffC2T0UP8aShIyzz0LjCCgoqQSsKn7xMO4wlWs+npN/9tLnfLQeNtdELOzT9g3mT6HQodOkDgObPlhCF6faoc4kukakqDN6xc+zS2kphG7xozVDraiAmIwSGQPyy9bITldEHr1JuZu0+I1zA5bQx0pN+3nU9U7cGpqKgoKCrBz584Tfrdjxw4UFBS0eGgACJ3+LCwsROA4ZeDt20OGry2dGKXEjtitO7xL/wrfxUv0DoUSBfZ178Hx1htgW3gQUgWfD4wgQLLbiWgMKTppjdrqpIn5XdF09XVET8iZAosFYti7lC017zB1MqGI2RLy7QSOs2sjIM+SMe9UZE0aA/j9qq/dFmJu6BAjW35Y033VRPXG4MyZM7F582bs2bNH+dnu3buxZcsWzJnT+umRmTNnwufz4T//+Y/yM4/Hg7fffhujRo1q8cQohZJsSOlkXQdIaqQB+orZUkJ4r7oWjfc8QFTBnqIesrm6mJ5JbhO7HZLVCiYYVD+R4nkwPh8kjgNaOBxIEik7G01LLkPTFdeYVhtQdfnpJUuW4N1338WiRYuwePFiSJKEFStWoEuXLrj44osBAJWVlfj6669RUFCgyG5MnjwZkydPxr333ouSkhJ07doVb775JioqKvDoo4+qHWbSY/voQwAAP+EkerM2EWL4aZppRW8wXkiLTuqVpFm//hJsZQX4seOVSlKy4ltyud4hUKJA1kUkWUkDQg9mTE0NmMZGSC0oNMRKs/xGqva+uSyLxvse1nZPlVG9kpaRkYFXX30VQ4cOxVNPPYUXXngBo0ePxssvv6z4dv7+++/429/+hjVr1hzz3ieeeALnnXce3n33XTz44INwOBxYsWIFhg8frnaYSY/77n8g/cJzwR48qHcolCiQE2pSSRrrkStphJK0lFT4zvwT/GefQ2T91nC+8BzSLr0Yli3fa7ovhRIvxxisE0TWMFN7FIEhaDOXDBAxcisoKMCzzz7b6u/HjRuH33777YSfu91uLF++HMuXLycRFkVGko4SsqVuA2ZCvlGTsoYi7rHHcWh47t9k1m4DRci2Q/IK2cow5eWwff0/SGlpCJxyqt7hUNqheutOMI0NxIVgJfdRc2kqoiRpWvt2huH2FoIr3IPgoMEQC7rpEkM8EBaroBgRprYGjNcDMSVVmXGimAORsDWU0prQ2L6FNHKSJtIkDZYd25D2lyVwPvuU3qFQIoHjQvdpwtpSTZf+BY3/uBtix8iUFCJF70qa8+knkL7wfNg+26TL/vFCpJJGMTZc2LNTzM/XfkaAEhdCtx7gR40mVhEKTJmGqh+2Ef1CYA8eAFtdhWCffoBGySBDfTsVZBs42buXQgEA34KFRNZlG8PtWp0qaWJYvsusJzxpkpaEsMXUWN2s+M9fAP/5C8BxDIhovDscxFsCaZddDOvWn1Dz4SYER40huhcAwOsF62mEZLPRQzIAhC4hPUuutAQQReIVGkrssAcPIO2yixHsPxCNTzyjdzgxwY+bgJqNX0Cyq3cYIRrEDnKSVq7L/vFCk7QkhCsJmSuLNEmj6ICUEh5Q1uiE5zGtTlo5BtxuiNnZYKuqwFYcUbSkKMaDrayAdetPmuzFbd8Gy57dCA4ZBqFPX9XWlVLTEBw2QrX1okXRSqswZ5JGH6GSEKaqEgAg5BfoHAklJoJBIHziS23sa15D2uILYVu/jsj6gPYyHGxNNSSGoa3OoxDyQg9otOVpbORT3FpUgB1vvIK0vyyB7ZOPie+lJWZvd9IkLQnx3nIbKvYfgm/xJXqHQokSy7Zf0KFLFtJOm0Vm/e2/wr7uPXAH9hNZH9DedSA4fCQqS6tQ99Z7muxnBuQqOkeTNEPD1stCtuQPeCmuAyr/XdrWvouUZdfB+vmnqq4bKfJBCGIuLYShSVqy4nZT3RoTIspaRqTEbGXHAYJDvvKXAdtAphrYIhYLPcl8FELXrpAsFjA1NXqHQmkDpZJGWCMNACS3/PCkrhG5B90jQAAAIABJREFUdfN3cK5eCcvuE+0itaA5SSs3pesAnUmjUEyEVjppJCU4lESTWkPphueW2+C5/R5iZtcUddCy3dlcSVM3SWvWSSOr89YqTieqfthm2plUWklLNrxeZI0dhvRzzzDlU0WyozgONNSHTuapDKuBTppcwVX7y6A1XA/dh4yZ02DbsF6T/UyBy0UTNBPAamCuLqOMIXjUfXhiNXjwaw+xoJvmvqFqQStpSQZXUtw8b2TCp4qkh+MgpqaFWoX19VD7T7i53Unuqdd/9jngJ0+BGJaCII1l9y5Yf/oRTJNXk/0oFLXghw2H79w/IzhkKPG9SD08yX7AxFxMEhxaSUsy5NNcVCPNvChP1QRanvINWnQTbHd2yUNwxCjNpB8Y6jZwIo2NyJgxFZnj9ZNGoLRP4LQz0PDP5xCYPoP4XsTbnW79kjTnC88i/fRZpqym0yQtyWh2G6BJmllR5lMIDH3zo8ciMHkqpOxs1dfWC2oJ1QJuNyy/7YZl3+9KpYOS3PBjx6Nyz0HU/ed9VddVrObSdJpJA8AWFcH27dfgCvfoFkOs0HZnkkEraebHc/NycAEfUgrU17lrfPhx1dc8HvbAfrieegJip07w3ngz+f2oJdSJMAyEvHxY9haCLSmBMGCg3hFRWoDbvg3gOAg9ewF2O9nNbDZINpvqywp9+gEWK6QM/U5XK4K2R8wnaEsraUkGV3QQACB0pUK2ZiUwczYCZ5wFmLTaxTbUw7lqBewfrCW/mc8Htr4OksUCKSOT/H4molkrrUjnSCitkXbpQmRNHa/ct81I/YrVqPnsa4idu+gWg9gxVEVnj5hP0JYmaUmG/MdO2p+RYkJEEWxZKfH2l5iineMAWxmuouV0oB6VxyFX02UvX4rxYMMSHKIWnrN+P9LPOg3pp5MRytaT5kqa+QRtabszyfCdfS6CAwZB6N1H71AoMWL5YTPsW74Dpp8MDBim2rpMTQ2yhw+AmJmJqt/IPbnLJ0eZRvKzUJLVBu/lVwI6mTsbGeo6YHAkCUy9dmK2sNlg/eoLMJIECII6Ei2iCPj9gMOhq5qAkqSZ0BqKJmlJhm/xpXqHQIkT22eb4HroPiD4d3WTtHAFjbQTRbMtFHmdNCk3F5677ie+jxlRKmmlNEkzJD4fmEAAkt0eSnJIwzCQ3ClgGhvAeBpVEdBlyw8je1h/CHn5qN6qj+MAcHS7k1bSKBQKYUhJcCgaaaTtwux2SDYbmEAg9JRNeiCa0iLBYSPgvfJa8KPG6B0KpQVk304t3AZkpJQUoLEBTKM6SZoiv6GzkKyUmQX/3NMh5uSEqnsmGn2gSVoSwR48AMvOHQj2HwCxR0+9w6HEiEhIgqM5SSOvDC6lpoKpqgLT0BCqFBCC27cXTEUlhJ69INHTnccg9OsPz+136x0GpRVkSyhRi1ZnGLW10pTqvN5CtgyD+hWr9Y0hRsyTTlLixvbJx0hfeD5cTz2hdyiUOFCMwlWupLEe7exb+OEjwY8dD0YIEt3H8dIKZM6bAcea14juQ6GoDaOhJZSMkqSpdHio2QtYP400s0MraUmEIr/RjZ7sNDOK3pDa7U7lhkr+qbf+9f8S3wM4+nRnjib7mQ3L1h/B/b4Xgel/hJSZpXc4lKMIDhqC6s++0XTgXm1rqGZzdf0toZjqKnAHD0Ds1FlXOZBooZW0JII7eAAAld8wO0q7k9BMWiJ57MlJGm11tkzK329B2pWXwrJzh96hUI7H5YIwaDCEgYM02zJw8h/gO+d8iNnqPNQobgMGuKe4H7oPmadOg/29t/UOJSpoJS2JYOVKGk3STI2Ung7J6QSjsjp4YNp01K1eA7GTBp6akhQ6NMCyAAGVcxmmshJAWCeNcgJCfldYN38HtpgK2lKApmtvUHU91kDm6kK4esYeOqRzJNFBK2lJhNLuLOiubyCUuBDzu6Km5Ajw44/qrpuXj8CpsxAcRt50O/Wqy9ChoCPs779DdJ9jxGwpJyCGnUeoVprxsK19DynXXwXbxg16hxIzgZOno/7JZ+E/42y9Q1FanOzhMp0jiQ5aSUsSmNqakD2Oy51Q5tkUcyK53AAIa6VJUnOSplL7JtEQ8vIBAGxpic6RUI7H+uMWOF9bHfLt/ONMTfZkaqrBHj4MKTMTYqfOca8n9O0HoW8/FSKLH5FW0ihGhi0J3YSFbt10VX6mGBfb2nfheug+cDu2E99LEbQlaA3F1NWCCQYhpqZpIwZqQsSuYdcBag1lOJTTnRp6zjpXvoisqePhWPGCZntqhdg5lHRyZbSSRjEgwuAhqDhYDrZWXW0tij6knHMmsHM72LUbIBT0UGVN+7r34HjnvxB69oIwaLAqa7ZGs+sAOWsoKS0dVVt3KnpTlBMR8kPtTuo6YDzYsA6imKldktask6bOw5Ptww/AlpUicMoMiN26q7JmrAidwpW08kOhmViTFCtoJS2ZcDpNdfSY0jpsZQVw6BAYFQVtNXMcgDaVNLAsxLx8TU/HmQ2l3VlREfriohgGJvxArWUlTf7bZ1X6u3SsXonUW26EZc9uVdaLC7cbYnoGGL8fTHW13tFEDK2kUSgmRBa0VbNK1KyTRl7MVgybrKv1ZUCJkZQUVG4rDEmUmKSykCywYYkdUcMkTVTZV5dVdNKMIWZb99a7EDMym7UmTQCtpCUJqddegfT5s8Ft+1XvUCgqIKuQM/UqJmla2kKlkK+k2davQ9qiBbD/901ieyQCUm6uqbwMkwWlkqZlu9OtbruTqQ9LcGhQnY+E4PCRELv3ADhO71AihlbSkgTLD5th2Vtoqg8npXVkPz+2Tj1BW1ZD4cngsOFoePxpCAQ9ZC3bf4X9g/cR7Nef2B4UCimCg4dAzM7RtJKmuuNAo3bV+USFPj4lA6J4lEYaFbJNBJRKmprtzvANVXSTT9LErgXw/flC8BMmEttDkd+gbgNt4nh1FTJOmQLHS//WOxTKUdS/8iZqN30JaJjgKAcHPGobrBuj3Wn99BOkXr4IjtfMY7ZOK2lJAFt+GEwgEPIvpE80CYGUpv5MmpidA0hSwjz1srLbQIeOOkdibJi6Olh//Rn8nnF6h0LRGaF7D9S+9yFENXxcJUnTOddI4EqK4Xjnv5CcLuDPF+odTkTQJC0J4A7sBwAIOh+BpqhHcMJJwK23gh+p3hdrzZebVVurXZqa4Hj9FUAU4LvkL0S2YCuOAAAk6jbQJoKslVZCBW0NA8+DafKGKlBaHuhwudSrbvt8ofYpHwDsdnXWjBNFK+2QebTSaJKWBHD7fgcACD166RwJRS2CEycB82YiWN0ICOaTTmCEIFJvXgbJ5SaWpDHUEioiRFmGg1pDGQbLjz8g87RTwY+bgNq1H+kdTmw4nagqLDKUtIuilWaiJI3OpCUB3P59AEB0SJtCiQbJ5YbEMGC8HkAQiOyhtDtzqCVUW8iCtlwJNVk3CrLouJim/SyX+87bkLL0asDvV2dBA0m7iF3yAJjLGoomaUkAP3Ycmi5eAn78SXqHQlGLhgbgo49g+fwzVZbjdu5Adp8CpJ8zX5X12oVljzpJRkCGQxQRmDoNgYmTNRUDNSNSTg4kux1sbS2Z/xaUqNFDyFbG8fpqOF9dpchnJBJSVlbos15XC3g8eocTETRJSwICM2ah8cHHwE+eqncoFJXgSkuAmTPhvvlGVdZj6uvB1tWC8XpVWS8SiLoOsCwaXnwZde98QDXA2oNlm50H6FyaIdDDEkpGcqvz8GT57ltkjR2GlBuuUSMsdWAYiLnhubTD5mh50pk0CsWEiGnqitmyDaF1RA000mQkldXNKbHjP/fPCDQ0GOYUXrLD1OlXSWv274zv75KtrgJ3YD/Y/gPUCEs1AlNPDtmgGagN2xY0SUtwmIZ6WD//FEKffhAM9sdCiR3Z1kQtCQ7lqLyWSZr8ZdCgfluFqa8DU1sbkt9wOlVfP9HwLv2r3iFQjkKppOlgXyT/XbKNDYhnWlTRSDOI24BM4yNP6h1CVNA+QIJj2bEd6UsuQur1V+odCkVNnE7AagXj8wE+X9zLMTp47Elp6RBTUsGoNaB8FLYN65E9eghSl16t+toUCmn0nElrrqTF1+5kNHQwSWRoJS3BYeWTnd3pyc6EgmGAjAygogJMXR0khyO+5XRI0ureeJtYy6FZyJbKb0QC01APy7ZfAZalB4wMQNNlVyIwfQb4seM131tUyRrKaObqCqIY0lD0+SCaQDuUVtISHEV+oyfVSEs4wq0QVoW5NCY8k6bpUy/BmRCWaqRFheXXX5Axfzbcd9+udygUAMFRY+A/53yIOtj4CT17gR8yDJLLHdc68oOflnOukWD77BNkD+mL1GXX6R1KRNBKWoLTLGRLK2kJR/jkF6OCyTp/8nR4nC4ExpPz0tQSOUmjbgORIeSHXAfYUnq6M9nx3nobvLfeFvc6Rp1Jk3UBWZPoAtIkLcGhQrYJzDvvoMYTQDA1/uFifsJEombnLeFY/RKcTz0O3wUL0XTtUlXXpm4D0SF27gKJYUJK7DwPWK16h5TUOJ98FHA40HTxJYDNpnc4MRGYMg2Sw4ng0GF6h3IM8gMJV1oCiKLhJXpokpbISBJtdyYyXbpAMqktFAAwviZY9u8Dd6hU9bWb253UbSAibDaInTqDO1QG9lCZLm02ShhRhPueO8BIEpoWX6ZPDJIEBINxJeuBuachMPc0FYNSCbcbYlYW2OpqMBUVkHJz9Y6oTYydQlLigqmuBuP1QEzPgJSZpXc4FANj/WwTbB+sBVNdpdmeitabSjIiR9N8cKCj6msnKrKHJ0dbnrrC1NeBkaTQ34dF+zqK49VVyOmUgZSbl2m+t1YIeXI1zfh+tTRJS2Ck7GxUFh1BzadfmUa4jxIFr7+OlHPOhH3Na3Ev5b7/LqQvukCpvGqBlB7WelNJkPdo6l98GXWr3oCY20n1tRMVoWt4Lq3YHLM6iQpTG5ox1cvOTLLbwUhS3BIc1m+/hvXbrwENXUwiRZRnMEuMn6TRdmeiY7NB7FqgdxQUEhw8CNumjQgOGIR4lcZknz4pXN3SAilsHk3CIzA4crTqayY6omy0TitpuqKYq+sgZAs0S2bEK8GRet2V4A7sR/V3P0Ho2VuN0FRDfiDhimmSRqFQSKG4DsR/ulMPxwG53ckSaHdSosd7xTXwXn4VJKotpytMjX5CtoB6tlByJU5MMZhOGgDfRYsRmHs6gn366R1Ku9B2ZwKTcvMyZMw7FZbvv9M7FAoJFAmO+JMcVrmhamgLla6u/6gMt7cQ7lv/Cvsbr6q6bqIj5eRA6tiRjkbojFJJ08FcHTjari1OxwH5wS/NeEma0Lcf+PEnQcrO1juUdqFJWgJj2fw9rN9/C1g4vUOhkEAWs423ksbzYLxeSAwDuOMTsIwGMSsb3suuQNOiS1Rdl/ttN1wvPg/7+rWqrkuhaIIgQMzO1i2BONq7M2b8fjB+PySrFbDbVYosOaHtzkRFFGH5vRAAIPTuo3MwFCJkqDN43+yxl6ZtFcXthufuB1RfVpHfyKbyG1ERCCDtkoVgK8pRu36T+StqkgT7++/A8dpqsAf2w3v9jfCfv0DvqNrFf/a58J99rm77y+3JeNqd8nul1FRjfo78frjvuwtsVSUa/vmc3tG0CU3SEhS2tARMUxOEjrnKKTpKgiEnabXxVdKM3JaIBeo2ECM2G6zffAW2vg5MVRUkE2vMMQ31SL3iEtg/3qD8jM7aRYaUkYGG+x6GFEe7tdltwKD3FJsNzpUvgGlqQuO9DxrPX/QoaJKWoHCFvwEAhD59dY6EQowOHRA4dSaELvlxLSN2LUDFgcNgmppUCixyLD//BPZIOfiTJqlmH0OFbGNHzO8KdmcduJIiBM16/TwepJ93FqxbvoeYngHPzcvBT5oCQRbolSQ4n34SvnPOD83gUY7FbodvSXwiunocRIoKhoGQlw/L3kKwxcUQBg7SO6JWoTNpCYqlcA8AQOhNk7SEJSsLja+9hcYHHo1vHYYBXC5dZmBSbrgW6QvOVTxm1YCRhWxpJS1qmrXSjC9N0CKShNS/LYV1y/cQ8vJRs/EL+JZcBqFff8DpBAC4Hn0QKXf+HemLFwCCoHPAJ5J6yUJkjRoM6zdf6R1KzAj9B6Dqpx2oW/mK3qG0iqyVxhncw5MmaQkKVxieR+tD59EoxkU54amiDAdLfTtjptl1wJxJGltSDNunGyG5XKh7/b8Qu/c44TVNFy6C0KkzrJu/g/PpJ3WIsm24kiJwxUWhoXudsL/3Npz/eiZ2eR+rFWJ+1xavv1EQuoVi4w7s1zmStqFJWoIS+MMpaFp8Kfix4/UOhUIQpqICXOEewB+7nK31041IP20mnE8+pmJkkaEIZ6ooaCt26oxgj57UbSAGhLCgrRmU2FtC7FqA6m9+RN3r/4XQf0CLr5E6dkTjY/8EALgfuR9smfresfHAVlcDAKQs/az8XA/ei5TlN4M9dEi3GEgj9OgJAGBpkkbRg8DsuWi8/xEEh4/UOxQKQVJPn42siaPjahdyxcWwffcNuIPa36xIaKU1PPsiar7/udUvaUrriLISe4l5XQekzCzwEya2+ZrA9Bnwzz0dTFMT3PfdpVFkkcGEkzQxSz8Nr2ZB29hkOGwffoC0hX9WxbKOFEJ3WkmjUCiEUaNd2Dzkq/0JJzFddh2I3zWBEj/BfgPgO/NsBCZP1TuUqGAPH4Lz+aej8olsvO1OSBYL7G+9AfbgAXLBRQPPg62vg8Syup7Klw/xxCrDYdm9E/YP18Gyt1DNsFRF6N0H/NDhEHoZeyRI9dOdmzZtwtNPP419+/YhKysLZ599Ni677DJYLO1vdeqpp+LAgQMt/vzJJ403O2BU2OIiWH/YjOCQYVQjLcGRkzS2PvYkh2kIJXh6nMSSvUJVm0kThND/bDZ11ksyhP4D0PDcCr3DiBrn00/C9fzTsOzYjoYnn43oPWL3HvCfcTYcb70B5+qX4Fl+O9kgI4A5utXJ6ldDkdzxWUPJf8+igaUthL79UPvJ//QOo11UTdI2btyIa665BmPGjMFf//pX7Nq1C0888QQqKirwj3/8o833+v1+FBUVYc6cOZg69dinuLy8PDXDTHhsX36B1Ouvgu/MP6HhuX/rHQ6FIPLTdjxaaXoel1e73cn9thtZJ08AP2o0aj/8VJU1KcaGqayEc1UosfReekVU7/VetwyBKSfDf+afSIQWNWx1FQB9W51A870g1nanopMW/vumxI5qSZogCLjvvvswdOhQrFy5Uqmcpaam4qWXXsKCBQvQq1evVt+/d+9eiKKIGTNmYObMmWqFlZRwsvwG1UhLeJQkLY4khw0naXo89frO/TP8c06DmKnOkLQiZOtwqrJeMsKWFIM7sB/BwUN0M/mOBufL/wbT1AT/H0+FMGRoVO8V+vaD0Nc4JttSVhYal98OSUN7thbjkGfSPPFV0gwvkC2KYA8fguR2G1b0XbV66tatW1FaWopzzjnnmNbmRRddBFEUsWHDhjbeDRSGJSPaSuQokSEL2QZpkpbwKO1ONWbSNDRXl5EyMkN6RSp9KVH5jfhJve5KZJw5F5afftQ7lPYJBuFYtRIA0HTZlXEtxTQ2AJKkRlQxI+Z2QtO1N8C35HJd45DS0iFZLGD8gZjez4YfGkWDV9JSll2L7OEDYH/vHb1DaRXVkrTt27cDAAYPHnzMzzt37ozMzEzl962xZ88eWCwWdOvWDZIkwRvFACjlWCy7dwEAhH70dFuio8bBAX78BPjmnwmxe3eVotIPJUmjFkAxIygin8aX4bB9vAHcoTIEe/YCH8dhB/fdtyN7cF9Yv/9WveBMjOfm5agsrULTldfE9H65sm9kuyUgJNkCGPuEp2rtzvLycgBAp04nahN17NgRh9rRWyksLERaWhqWL1+OjRs3wuv1oqCgAEuXLsXs2bMjjoNhGOLzlizLHPP/hqKhAVzRQUg2G9CnNzjOeDEa+vqZBPnaBeefgfqhwyF27x7zf+vAVddAfl7mVIovUtjSErhuvQliZia8jz8V93pcOElDh47tXg/6OWwZqSD0xWUpLTb8NZRn0fyLLwFnjf3Ty7AMGK8HztdWQZzYtnyHmhx//bhffwF78ACEIUP1FYLl4ksNhNFjgZRUMJ1yiX8HxfMZlHqGtNIsB/YZ8rsSUDFJ83g8AACn88RZEIfDgbp2nvQLCwtRXV2NYDCIhx56CDU1NVi9ejWWLl2KQCCA+fPnRxRHdrYbDKPNxc7I0HduoEV+2wYAYAYMQFausedJDHn9TEba0IHA0IF6hxE79Q5g3ftAQQEcWSnxr9cQOkDh6p4PV4Tr0c/hcfTrDQBwVhyG0+jX8KIFgIWF+4rL4I7n83PVX4DHH4F97Xuwr3hRsZDSCuX6vf9f4LHHgIcfBpYt0zQGVXn+GQCAllNeMX0Gh4c6f7big8hS4/5DgHaTtH792h6qPPfcc3HnnXdCCvfyW0qQIkmaFi5ciJSUFPzpT82nbObNm4c5c+bggQcewNy5cyOS8aiq8mhSScvIcKO21gNR1HeG4Xisu/cixWpFoO8AeKpjG/okjZGvn1lQ8xpyO7ZDcjohdusOcNrW0hiRQyYAsaYWtSp8XlNKy2AD0OBMBd/OevRz2DKWzI5IA8D/vg8NRr+G884K/Q8A4vn8ZHVC2vCRsPz8Exreegf83NPUia8djr9+7tLDsANodKQgoOP9m/thC9w3XAth8BB4nvmXbnFEQjyfQSYrF5kApL2/o6aqIeRjrANtJYjtZj1XX311m7+XZ9BcLhcAoKmpCbbjNIqampqQktJ2lrpo0aITfuZwODB//nw89dRT2LNnDwYObL9iIEmSZp65oihBEIx1cxfmzofvwBwwjQ2QDBbb8Rjx+pkN6dBhOJ7+J6SUFHiX3RTTGpkzp4PxelGxrwxo5+9UdVzNR/0FXohbG8p72VXwT/sjAoOHQYzws0U/h8cidQ5JHrElJRFfl0S4hr5585Hy80+wvvcOfLPmabq3cv2qKgEAQmaWrteTCQqw7NgOyeGIPg5RBFtSDCk9XdMTkzF9BtMyIaZngK2rhXj4CKSOHckEFwftJmnXXBPZ4GCXLl0AABUVFUg/7kTHkSNHMHJkbPZEWWH/MnqQIAqsVkgqSRpQjA3j9cD19BMQCrrHlqTxPBivFxLDqHbCMio4DmJqGtiGejAN9XHf1PlJU8BPmqJScMmJbLLOlpUCwSAQQQdDa7h9e+H817PwnXM+giNHq7Km/7T5SLnrNtg+2gA0NWne8gQMpJMWh8g0U1WF7NFDIGZno2qXcQfyZYQePcD+vDUkO2PAJE21xuCgQYMAADt27Djm52VlZaipqTnh1OfRFBYWYtasWVi5cuUJv9u/P/QfOT8/X61QExdJ0v0IOUVbmsVgYxOzlcUqpdQ03Ur9apxQpaiI3Y7qTV+haluh5u3vSLG/tQbOFS/A+ZJ6Yt1it+7gh40A62mE7Wt9lOjZKv19O4Gj7yv1Ub9Xdj8x+slOGc+d96Fm3UYEB7Weo+iJaknayJEjkZubi9dffx3CUf3G1atXg2XZNk9oduvWDeXl5VizZg38fr/y87KyMrz99tsYPXp0i6dGKcfCHilHdp8CpC04R+9QKBpxzBOvKEb9fkV0Ukc9I9WsoTweOJ98FPb/vqlCVMmNMGQopJwc3RL3NpEk2N/5DwDAd5a697rGBx5B9Tc/IjB9hqrrRgoTrqRJ2fomabKwNdsQfZImJ3aiQcVhj4cffxKCY8fp00mIANXq2CzL4qabbsINN9yAJUuWYM6cOfj111/x5ptv4sILL0T3ozSYtm7diqKiIkycOBE5OTmw2WxYvnw5brnlFpx//vk444wzUF9fj1dffRUcx+H2229XK8yEhtu5A2x9XUxPPxSTYrFATEkF29gQmkNMiy7Zko3N9byhBiZPgdC9B+BwxLUOd6gMKXffDqF7D/hV/vKmGAfut92w7PsdYna26q1ttVqnMREIgG1sgGSx6F+FcrkgcRyYpiYgEIjKC9c0bgMmQdVhgzlz5kCSJDz//PO48847kZubi6VLl+LSSy895nVr1qzBO++8g1WrViEnJwcAcOaZZ8LhcODFF1/Egw8+CIfDgXHjxuGGG25Az7CWCaVtLLt2AgCEASaWZKBEjZSeDjQ2gKmrizpJM0IlzXPX/aqswx4JaTWKHXNVWS+Zsa1fB8drqxCYOQe+BQv1DucY7B+uAwD4Z8wi246VJG0riTYbKoorQj68elcwGQZSejqY6mow9fWhqmqkb5V9O6O8F+kFU18H12MPg6mvR+MjT+gdzgmoPhE6d+5czJ07t83X3H///bj//hNvzLNnz45KuJZyLJZdoXnA4IBBOkdC0RIpLR0oLQFbW6MoaEcKE66kGdW3LhrYiiMAaJKmBuyRctg/3gAxOwcwWJJm2/ABACAwq+3vmZjXX78OrkcegP+0+Wi6TmOtMrsdUq4xPr9NFy0Gw/OAJbpEWLaoE01SSZNsdjif/SfAMGi890HAbtc7pGMw3rEdSsxYtoeEbGmSllwE+/ULSVfEcGiEn3Iyaj7cBMml4zyGzwe2sgKSwxnVE/vxKJU0agkVN0KPUPeC279P50iOhT1UBuvWnyA5nQhMOZnMJpIE67ZfAKdT+yTNQHhvvS2m98njNmappMHhgFjQDdyB/eD274PQ31h2ioRlXyma4fOB+20XJJZFcPAQvaOhaEjDv15CzWdfIzh0eNTvldIzEBw1RtcWueufjyF75CA4X3gmrnXYI7SSphZC2JLIcJ6GogjvpX+B7/wFQFibU234KVMhWa2w/LAZTE01kT1awrZ+HTLm/BHO55/WbE8S+OedjrrX3gr9NzIJwT59AQBc4R6dIzkRmqQlCJad28EEgxD69DXsKRUKpSXEsBYiW1MT1zoMnUlTDTEvH5LVCu7wIcBAGpViXj489zyIxvsfIbaHlJrdbbr4AAAgAElEQVQGfvxJYEQRts82EdvneLh9v8O65XuwJSWa7dkW7P59sH75BdjDbftuH4/YtQCBU06FMNA8HR2hT8hZyVL4m86RnAhN0hIEIb8ADQ8/Ae+V1+odCkUPJAng+ajfZn/9FaTcdAMsP2wmEFRkyMLLTLxJmiRBsttpkqYGFguE8Hwjd/CAvrHoQGDaKQAA65dfaLYnW1kBABA7GENQ1f3YQ8g4ax5sn36idyjEEWgljUIaqWNH+C5aBL+JSswUdXCseAE5+Tlw3xn9DInt801wrnxR17aWmJEJAGCr42stNTz5LCqLjiDwx1PVCCvpUebSDNLytGz7BY5XV4WcEAjDTw5Je9i+1E7UVjn4YpCZSnnwP1r9Qsfql+B64B6wBptnbItguJJGkzQKhaI6ktMJhufBxjA/I5/EkjL0O90phdudTG18lbTQIkzc/p+UEPzJf4Dv7HNDJzwNgP2tNUhdejWcK18kvldw8FCI6Rngig6ALTpIfD+guZImGSRJU0Sm66NL0uz/WQP3Iw+A0yCZVguhXz/wg4ciOGKU3qGcAD3dmQj4fHA/cA/4ESMROO0MvaOhaExzuzD6JE2W4BDT9EvSxEx5Jk27IW1K+zRdfpXeIRyD7X+fAwACU6eR34zj4Fl+O8SsbM0smpgKY7U7ZTHaaJO0ZgkOk5zuROgAVe2nX+kdRovQJC0BsOzaAdfTTyDYtx9N0pIQJcmJoV3IGKGSlhl/u5OprkLWpDEQevVB7dqP1AqNYhCYI0dg2bkdktMJfsw4Tfb0LVysyT4ySrszx1iVNDZKBxtFe9EkOmlGhyZpCYDll58BICYJBor5UdqFsbQ7a2UxWx29O1PTULfqjVCyGaPKO3vkCNjKSiVhpaiAKII9eADc4UPgJ0zUNRTbl58DCPksGk1sVC38888Ce/iQYZI0MS02k3X5lLZ8XzINkgS2uAiM368cJDACNElLACy/hpO0YTRJS0aUSlq0M12SpLQydDVDZhgEZsbnNEItoQjA88gaPwJgWVQWHQGsVt1CsX3xGQAgMEWDVufR+659D/aP1sNzw98g9uxFdC/PXfcRXT9aYmp3+v1gvB5IHAcpJZVQZGSwrXsP6Usugn/GTNS/8qbe4SjQJC0BsPy8FQAQHDZC50goeiC3KpnaWkAUIx+c53kEhw4H4/XGbW6uN81JmjHmeRICux1iXj64kmKwxUXEk5RWkSRY5Xk0Ui4DrWBf+w4c774NfvRY+PT699cJfuRoVH+1JarqNCNX5jMz9fcfjRIh7NRj2bFd50iOhR6DMjlMY0NoVsNiAU/bncmJxYKG+x5Cw+NPh5K0SLHZULv+E9R8/g252CLE/sarcC+/KeYj8IrbgEGGrhOFZhkO/eQUmIZ6CL16Q8jLhzBosKZ78xMmAQCs331NdB+mqhKWH7dELRxLlJQUCH37RXXalPE1IdirN4TuPQkGRgahR09IDge40hJ1TpqrBE3STI5l609gRDFkBUXIJoVifHxLLof/vAsAizmL4/b1a+H617Pg9sSm+E3N1cmg2EPt108rTUpLR91/16J6y6+ay6vw408CAFi//47oPtYv/4fMWdORcuvfiO5DGrFbd9R8+xNq15tQAJfjEAz7dlp27dQ5mGZokmZymIAf/OCh4MedpHcoFLPB80AgoHcUAOKYqwvTbK5OK2lqIldE9KykKejwACL06w8xIwNcaQnYkmJi+zBHjCVkCwCQJKRefTnSFpwTXYXexAQHhXyvLdt+0TmSZmiSZnIC02eg9tOv4LnzXr1DoeiI9esv4XjxOXC/F0b8Httnn6BDfg7SLjqfYGSRIYVdB5gYZTj8c0+H5/ob6QlnldHdaD0YDFmWBYP67M+y4MeOBwBYvyM3FmA0+Q0AAMPA9uEHsH+8IfLDA5JENibCBIePBBDqUBkFmqQlCiYb0qSoi+OVl5F6699g+WFLxO9RNNIM0CZvNlmPLUkLzJoD7623aT6zlOgoM2k6WfxYtv6IzNmnIGPWdF32BwB+7AQAZFuejMF8O2UUoewIH56czz2N7J55cD1ozqJBcEQ4SQsrJhgBcw6wUACEdLGYmhqIPXrSJC3JiSXJUUQndRSylVEqaQYa2KWEjKdrNn6hVNS0RnYZkL889YCfOAmBiZMRHDiI2B7ygQExtxOxPWJBzMwMWWPV1iCShidTWw22scG01mzBAYNQs25jaMbbIJjzSlIAAPb330X2+BFIWXq13qFQdCYWayjFvkVHIVsZJcmMpd0ZCMC+5jVYv9LODDtpsNsRHDYCkk46elZZH23qH3TZHwCCo8ag7p0P4Ft0CbE92EPhJK1zZ2J7xILiBhLhfUUWshXD7zMdViuCY8cZ6hAeraSZGOvXoS8lqo9GabaGirwSpWgapet/QxU75ELo3iOmmRz2UBnSrvkLhLx8VG81zqksSpw0NsL6w2ZILAt+4iS9oyEKe6gMACB27qJzJMciJ1tMTWT3FbkSLlfGKfFDkzSzIkmwfR0yhOUnTdE5GIrexGINxdbpbwklExw/AdWbYztRxR4+DAAQOxmrVZQo2Na+B+erL8N3+pnwn79Au32/+xpMMAh+5Cj9v/SDQVi2/wr4/AiOn6D68vWb/geppNRYBwfQXKFPmkoaAG7HdqTcdRuETp3R+PjTeodD251mhdvzG9iKIxA65kLo3UfvcCg6I2ZlAwDY6qqI38OEXyu/16xwh8NViE7GqkIkCmz5Idg+/QTWHzZrum9zq1NbK6iWsH3xKTJnnIyUu24jsr6Y3xXBMeMAjiOyfqwEBw5GYNp0CBH+bSnVeb2T6niw22H79BPYPvnYEKdVaSXNpMjzN/ykyfTQAAViTgdIDAOG5yN+T9MV1yAwYxaCQ4cRjCxKeD6khxXFZ1oZuqaVNCIIvUNm07G6QcSKZfs2AACvsV9nS/Cjx0JiGFh+/gloagKcTr1D0gTfRYvgu2hRxK9XKmkmTtKEXr0hZmeDO1IO9sD+0ME8HaGVNJNi+/pLAAA/kbY6KYAwYCAqS6tQu/ajiN/DT5wM30WLIOblE4wscrJGD0WHvOyoT3jK7U6hk7GGrhMFoW8/AIBlr7ZJWt3b61D9+bfgx4zTdN+WkNIzIPQfCIbnYf1lq7qLf/453IsvguO11equqwOeG29C4//9w9zOHwyjiMOT1MaLFJqkmRFJgiV8owjQeTQKEDryblJLKBnJEmr1sJWVUb1PGbo2mHxBoiB27gLJ5QZbWam0yDWBYSAMHATYbNrt2QayqK1ls8p6ab/8Avt77yj3dEMhimCqqpS/sfbwn3cBmq5bBqSkEA6MLPyEUJJm+5asZ2sk0CTNjDAMqr/9CTXvf6R7KZZiUgQBzicegeOVl/WOREEKD03L6uuRIid1Iq2kkYFhEOwjtzwjd7SIC4PYlR0NPzZU0bOqnaSVyTOVxvv8Wn76ATkDeiDt4j/rHYqm8BMmAgCsNEmjxIzNRuSUEcW8pF6+CFmjh4Dbvavd1zK1tUi55w647/y7BpFFhqy2Hm2SVvfWu6jcvV8xw6aoj3w4SZOWpyQha/wIZMz6A5goq6ok4ceFnQe2fK+ul2VpKQBAMJj8BnC0Tlr7IwhMdRUcr7wM62ebSIdFnOCgIRBT08AdPAC2rFTXWMzdH0lWAgHDtAAoxoE9cgRc0UGwR8oh9B/Q9mvlk53hI/ZGQDaXZqJM0sAwkEx+QtXoBKZOA6xWCN26E9+LK9wDrqQYjM8HKds4/13FrgUQOnUG42sCe/gQxC556ixs4EqaqIhkt5+kcft+R+oN14AfOQq10/Sz8VIFjoP32qWQUlIg6XxIhCZpJoMtP4ysccPhP+VUNLzwEj3ZSVGQNZbYsA9gW8hefEZKbmKtpFHI4z/vAvjPu0CTvaz/C0tvTDnZWPc3hkHtx5+HhuLVtD0KV9KMmKRJ6RmQGCakqSgIbUqEsAkmZNt03TK9QwBA250xwe7fB2zcqMveto0fgfF6wTR5jXUDo+iOlJMDILIkTRanlO2YjICSpEXR4uL27UXmtIlIueEaUmFRNEb26wycrJ8VVGuInTqr70spV9IMZgkFAOA4Rexa1kBrDfnBTzSAF3AiQStpUcIV7kHGxNFAbi6wfQ8AbRMl+/vvAAACs+dpui/F+MhJTiRzPHK700iVNH7CRDTc/wiCg4dG/B62tBSWHdsgpqURjIwCAGzRQVh2bEdg2nTA4SCzCc/D+lVYXmjyVDJ7qIHPp8414Hng1FPBHy6HlKa/80dLSBmZQG0t2NpqCG20n9mq8AhFdo5WoSUFtJIWJULvPhC6FgDl5eB++lHTvZnqKli//AISx8E/c46me1OMjxjF6UjlqddASZrQrz98iy8NGRxHiDzUS4VsyZN+/llIX3g+LHt2E9vDsvUnsI0NCPbuYxj9vmOQJKSfNQ85vfLAVLRfsW4XqxX4z3/Q8P6Hhu2MROrfyVaFHg4lg1lbmR2apEULw4A/dRYAwPbRh5pubd+wHowggJ80xVADtRRjEM1MGoQgRHeKodqdscCVlgAAxPwCnSNJfIIDBwMAuJ07iO1h++JTAABvACuoFmEYQJJCorZbvtc7Gk3w3HYXate8AyEsw9IaTPi+YzT/UbNDk7QYCMwMJWnWDes13Vdudfrnzdd0X4o5EPr1g/fyqyL6fDRdtwxV+8vQdO0NGkQWIaII+xuvwvn0kxG/hQ0naYIRqy4JhjBwEADAQjBJa1p0KeqfXwGfhkbu0aKmXhpTXg4UFYWG8g0KP3Ey+GnTIaW3PWvGNjQAoO1OtaEzaTEQPGkSkJoKy84dYA8egKjBsXSmtibU6rRY4KfzaJQWEHr1geeu+6J7k5FaLAyD1L8tBePzoWnh4ohUy7niIgCA2LUr6eiSHrmSRjJJk3Jy4D/jbGLrq4HsPKBGkuZ47mngycfguGU5PEv/Fvd6elL/71UhX1ODmcSbHVpJiwW7HZg7FwDgePstTbaUMjJR/f3PaHjmBeUUH4WSUDBM1DIcSiWNtjuJExwwEABg2bld50j0JThqTMhs/defQwcI4oAtKQYQ0mAzKpYft8B9zx2wfbC2/Rc7nVTDU2VokhYrCxZAcjjANDZqtqWY3xX++Wdpth/FfFi2fA/buvcBv7/N12X8YRIyJ40BW35Yo8giQxa0jWiuDoD/rHPgO/tcWknTALFrAcSUVLCVFWCOqK9l53r8YaQsvZrozJsahMzWB4AJBGD5OT6/TdYElWDLtl/heuIR2DZ9rHcoSQltd8bKjBmo2fU7BHcq8a2Y2hpIqWm0jExpl7TLF4MrKUbVll9bb8NLEix7doMJBCCmkP/8RkNzJS2yJM17g7lbRKYibHjObPkeln17wXfsqOry9jdfh2VvIXznaiOaGw/8mPGw7NoJ6+bv4rLn44rCSVpBN7VCU52IqttNTcicPgli5zzU/fd9jSJLDmiSFisWC5CWBggS8a1S/roUll9/RsNTzyM4JnJ5AkryIebkgCspBltxpNUkjamvCyVo7hTA7dY2wHaIRkaEoj31z74Ykm1R+XPDFhfBsrcQYmoagqNGq7o2CXznXwB+wkngJ06OfRG/P1TJ5jhDug3IRJKksVWVsOwthODxaBVW0kCTtHjhedjXvQf/H2dGNOgcLWzRQdjXvguwrDF1gyiGQswN6YWxh1tvY8pVKqmD8Y7Ki+HqTCRtWLa4CNz+fRB691HPR5HSJqRmp2xhU25+8tSQdpjBCY4ag+CoMXGtwZWG5tGQnx966NfggT8WlBGENqrbLJXfIAadSYuTtEsvRtrli+F483Ui6ztfeBaMKMI//yz6RURpF7FTFwAAe7is1dfIT8TyE7KREDvnQbLbwbQzUwcA9vVrkXH2aXA98YgGkVFIYvs8pI8WMLsxdxRw+/eF/qFXL30DaYdjKmlSy4mkImRL9TtVhyZpceI7M3Rc3PnCs4Aoqro2c+QInKtfBgB4r6DehJT2kf3/uEOHWn0NY+AkzXfBRagsOgLP3+9o97VsCT3ZqTmShLRFC5A9qDeY+jp11gwGYTWwX2drWL/5CinLroNt/bqY3h8YdxLqNmwC7r1X5chUJiUFkssFxucD09jQ4ktk9wWqkaY+NEmLk8DseRDy8mH5fW9kR5SjwP3oA2C8HvhnzoYwJHI/Q0ryInQOV9IOtVFJO1IOoLm1aCis1oi12zhZviCfjgFoBsOALSsBW3EEll9+VmVJy08/gq2vQ7BnL000J9XCsu0XOFevhO2jGEXNU1IgjBkLjDP+nHGw/wAEBwxqVc1AHk8w8mydWaFJWrxYLPBesxQA4L7vTiAYVGVZdv8+OFathMSy8Nz6D1XWpCQ+8k2SPdx6JS04YhQ8y25C4JQZWoVFBDY80yPkG1e+IBEJDh8JIOSzqQZibi48S2+Eb+ESVdbTCjVFbY1O7YbPUPPFtxDDD4HHw4XvN9RDV33owQEV8F14MVzPPQXL3kI4XlsN30WL4l6TraqE2DEX/JSTIfQfoEKUlGSAHzcBVVt3QuyY2+pr1Bh6JknG3Bngfi9E9fc/Q0pLb/V1XNFBAMYWAk1E+OEj4QRg/WUrAiqsJ3brDu8tt6mwkrYEBw+F5HLB8vteMJWVUYuMpyy7Dkh1A/fcBbN/FQdOmgQIAvjho/QOJeGglTQ1sFrhuTV0k3HfczuY6qq4lwyOHouaL79H4+13x70WJYlwuUKngE1wQq41mKpKsFVVYNuaq6utAVtdDcnlUk60UrRBqaT9rE4lzbRYreBHhJKSqM3WeR6O11bB8ezTgMNBIDgCSFKrnaLAvPlofPAxBMeN1zioxIcmaSrhP/1M+E47A4133AspMyv2hY7SmZFS0yBl0dMyFHWxrX0X1k8/idvShhTyKWbZ8qkluIMHAABC957G8h9NAoS+/SC53OCKi+J2HrB++gmcz/xTUd43G4rZ+vffRvU+rvggGEEIPVCZIElzPvNP5BR0hOvh+/UOJemgSZpaMAwaXnwZ/vMuiP1Lo7ERmbOnw33brarNtlGSD/fym5Axazq4fXtb/H3q9Vcj47wzwRhUeFKee+HaOPwQHDYClXsOom7Faq3CoshwHPhwu9zyXXTJyfE4V61Eyu3/B9vHG9SITHP4CZMAANav/hfV+7jffgMQSnjNgJSSAsbvb/lAkijC9vGHIS9TiurQJI0Qll+2wrYxihtPYyPSF5wDy66dsG36GEyTl1xwlITGsmsnrD9uAXvgwAm/YxrqwTbUQ3I4IGXFUfEliBA+rdledUXKyITY09gaU4lK08JFaLzzXgjDh8exSBNsn4dEbAMzZ6sTmMbw4yaAHzMOgVP+2KqGWEtYdu8EAAgDzDFvLP9NcqWlJ/yOqaxE+oJzkX7OfK3DSgrMPa1oULjCPcg4fRYQCKDhkSfhP39Bm69nS0uQdslCWH/cAiG3E+pXvxHy6qRQYkAI+wByRQfBH/c7NnyTFfLyDdsmFLr3BABwB/brHAmlNQKnnQEA4LjYP0O2Lz8H4/WCHzbCvG4qTidqP9gY9ds4OUnrP1DtiIggdgk/OMkuCUfBhYWzZSFtirrQShoBhN590LT4MjDBINKuuxKpl17cclXA74djxQvInHZSKEHLy0fde+sh9OytfdCUhEHWmpLnto6GLQvNeck3XSPSnKTta/U1qX9ZjLQL/gR2f+uvoRgb24aQvphZq2jxYNklV9JMkqTlheZEubLSEyqG8gEfKr9BBpqkkYBh4LntTjQ88iQklwuO995G1ughSJ8/G87nnlJeZl+/Fqk3LwNbWwv/KTNQs/F/NEGjxI1SSWshSZPbFfJN14gIffvCe/X1aFpyecsvkCTYPtsE+8aPTDF0nahYtv4I5713AV9/Hf2bBQH2cJLmnzVX5cg0RpLA7doJx6qVEb+eHzMO/PAR5plJS02DmJoGpqkJTHX1Mb9jy8LV+VY01CjxQdudBPFdeDEC06bDfc8dsK99F7ZvvjpG5T0wZRr4wUPhXXojAnNPN2z7iWIuhHAljW2pkhY+MSkY2AdWysqG57Y7W/09e6QcbE0NxPQMqnCuI7aP1sP56EOAyAPLh0X1Xuvm78BWVkAo6G6aalKriCIyTp8JtrYWgSknQ+zeo+3XMwwaH3kSQHztYq0R8/PB7toJrqwEwaM8OuWxBDO5RZgJWkkjjJjfFQ3Pvoiq7YWoW/kqfIsvU34nZWej9tOvEJg3nyZoFNUQuoW+JLgD+09sTdSEnoJNOwMEgJNbRf0H0L8bHeGnTAv9wwcfRP1eyemEf9Zc+M45z/z/DTkO/KSpAABb2IM0EfFefyPq//kchONGJeQkTWgvOaXEBK2kaYSUkYnAnHl6h0FJAqTsbPjmnwmxc15IyuUoYdvGBx6F5+blgMXYf/rcnt9g+ekHBAcPhTB4yDG/k0/GBU0ydJ2o8GPHQ8zIBLtnD9jCPRB69on4vcHhI1H/8msEo9OWwJSTYV/3HmybNrbrOGP5+SeIWdlhpwzzJKj+M85u8eey8wdN0shAK2kUSqLBMGj410vw3HFPi84DUmaW4U8PO9a8hrRrr4B9/doTfsft3gUgZPpM0RGLBXzY/9X20Yc6B6MvgRkzAQC2zzcdI0jeEqlLr/n/9u49Luo63+P4ay4MdzBvkKjbmm2uSq6Ia2B2ATQ2A8JWlBBI7Gh6vGSGaW7bxe14tFzzlhUpZm62XoLj1i7Wbq5Lj9IsObpiBllHBXsActeRmWGY8wcMLQvpEAO/+Y2f5+PBQ/l9fwNvvgzwme/v+/t+6RMeiv6zTu5S4KKq8z6i6pMvaPz5CKWjuCUp0oQQLqexZZ6SvvBku7bWNaaGyx8FpVl+1XxnpkfLTQCO8H5tMx4H/+ZWC3Y3DQjBMiYczZUrGA7+7YdPvHwZ3ZeF2HQ6GkNv67mATqCprMRr+1a8tm9t2+DpiXXoLeDpqUwwNydFmhDuyGhEf/QI+n/ZU1B/5DA33D4a32d/o2AwxzSGNk9E15880a6tYVoKDfGJMpLmAixR0eDhgf7IYTQXL17zfO35c/g+s4LAGUloKru+x7ErMd0XD4Dn+/t/8ByPY5+jaWqicfhI8PHpqWhOoa2uwn/pYnw2vax0lOuKFGlCuCHDoYPcMHkivmv+q/WYvug0+m/OoL1YoWAyx1iH3oLN27t5f8jqtrf8N8x8hPo33uzaHrnCKWwBgZCUhCltJhqL+Zrne2/fiqapCVN8IragoB5I2HPMk++nydcP21WKL/som+XOu3solfNYb/opNg+P5jloLZd0De/tJzA+tv3omnAaKdKEcEONI0YCbS8X6oqLmttu+ZkimTpFp6Ox5XKm/uQ/FQ4jrmrnToxrX27dc/UHXbmC187tzf+dNfvq56qQdchQKk9/27q8RkcMH/0VAPM90T0Vy3n0eqw3N6/jqf+6+XeJxxdHMRz+BG1FuZLJ3Fq3FWl1dXVERkayZ88ehx9TVFTEI488Qnh4OOPGjWP58uVUV1d3V0Qh3FbToME0+QegvViBprz5F6i9YLPeoo4FNBtHtlzyPHG89Zhn7j48PvoQjLK3rdp4b9+Ktroay+gwGls2aHc7V5mXpf3uAvpTJ7H5+GAZF9GDoZyn8WfDANB9dRr4fjpC40h1za9Tk24p0sxmM4sWLaKyE3MOzp8/T2pqKmfPnmXevHmkpqaSl5dHRkYGZvO1h9GFEP9Co2mdWO9xogCsVvQFXwDQGDZGyWQOs4wJx+bjg8bYcreczYbvb5bRa/qD6K6x+broYY2NeO55B9+nMjts1tTX4bNhLQDGJ5apf220qzGZ8Pyfd9G2LE1hZy/QzHdHq3aSvX2HBP2pQrDZvi/SWkbuhfM5fbGksrIyFi1aREFBQacet2HDBsxmMzt37iSoZa7CiBEjePTRR8nNzSUpKcnZUYVwa5ZxEXgc+RSPj/OxBg9Ae6kea8hA1azSb3rgQUxTpoLBAID+eAG68jKsNw5QzXY61wtNbQ3+mY+hMRoxT47HMn5Cm3bvjS+jrazEMnYc5ph7FUrZM/yeeQrvbVlcSZ7BpfWvtB43R0+i8p9FaFR8dcgS3jwC6nHkU3RFX6GtrMTaP6hlzTfRHZw6kvbxxx8TGxtLUVERaWlpDj/OYrFw4MABJk6c2FqgAdxzzz0MGjSI93/EitZCXO/ME1pWQf/rATz/eqD52F33KBmpc7y8Wgs0AM99zVMnzLH3ufdIjArZ+vTFuGAxAP6L56OprWnTblz4OMbZc6lfs87tv3fGOf+JTafDa/cu9Cf+t02bzT+Appa9ddWocew4bN7eWAcNwvCPgwBYIse7/fdUSU4t0s6cOUNkZCT79+8nJibG4ccVFxdjMpkYObL9kOnw4cMpLCx0ZkwhrguWyDto6tsXm7cPDQlTMC58HFN8otKxOq+hAZ+XX8J7x7bmdx9KVTiQ6IhxwWIafz4C3f99S2DSA83LcrTMh8TPj8u/W431Orgs1vTTIVzJ+A80VisBs9Lw+OhDfP77d+AG03Zs/gFcLDxD/evb8cx9FwDzvfcpnMq9OfVyZ3JyMunp6QCUlpY6/LiysjIAgoOD27X179+f+vp66uvr8ff3v+bH0mg0aLv5nlWtVtPmX9E50n9d51Af6gxcemsXjWHhaPR6Gp55rvlwTwR0FpuNgLh70R9vnj5hnjgJW1iYU74GeR52XZs+9Pbk0q7d+Mf9Co+CY9wQN4nG0Nuo++BgmxHR60HDsysxHPkU/Ynj9Jr+IAC62hqMa9a2OU+Vz8HA5r/DxrUv4/PUUhrvj1N0o3hV9mEnOLVIM/zIH8TLLWuueHl5tWuzHzMajQ4VaX36+KLpoaHXXr18e+TzuCvpv667Zh/GOj6i7bJefxUyM2HAAAwbNtC7t59TP7w8D7uutQ97D4fPj8KqVfCXv6APDKD3xQvQwVUS9+YHH/0Nli6FTz+F8ePxemkNXoEdP3dV+RyccDvk/wHEwc0AAAsYSURBVANXWa1QlX3ogGsWabfeevUJutOmTeP555/vUgibzQbQYXFlP+Zo4VVZeblHRtJ69fKlpuYyTU227v1kbkj6r+uuqz4cOhxy/mVeatUlp3zY66oPu0mHfaj3gadXNr/ZOel7pioaT3hx/ffvW2nXD/Ic7Dp36MOrvfC8ZpE2f/78q7Z3NI+ss3xaVmhuaGho13blyhUA/Pwce/Vss9mwWrscySFNTTasVnU+KVyB9F/XSR92nfRh10kfdo30X9e5ax9es0hbsGBBt4cICQkBoLy8/arF5eXl+Pv7txZyQgghhBDXA5fYFmrIkCF4e3tz6tSpdm2FhYVOGa0TQgghhFATlyjSDAYDUVFR5OXlUVHx/ebPBw8epKSkhMmTJyuYTgghhBCi5zl9xwFHFBQUcO7cOcaPH0/fvn0BWLhwIX//+99JSUkhLS2Nmpoatm7dSmhoKAkJCUrEFEIIIYRQjCIjaX/84x9ZunQpZ86caT120003sWPHDoKDg3nxxRfZtWsX9913H6+//vqPXtpDCCGEEEKtNDb7+hduoqKivts/h06noXdvP6qqLrnl3STdTfqv66QPu076sOukD7tG+q/r3KEP+/X74TVgXWJOmhBCCCGEaEuKNCGEEEIIFyRFmhBCCCGEC5IiTQghhBDCBUmRJoQQQgjhgqRIE0IIIYRwQW63BIcQQgghhDuQkTQhhBBCCBckRZoQQgghhAuSIk0IIYQQwgVJkSaEEEII4YKkSBNCCCGEcEFSpAkhhBBCuCAp0oQQQgghXJAUaUIIIYQQLkiKNCGEEEIIFyRFWidcuHCBxx57jNtvv50xY8awYMECSktLlY6lWk8//TTJyclKx1Cdzz//nPT0dEaPHs2oUaOYPn06hw4dUjqWqpw4cYKHH36Y8PBwIiIiWLFiBVVVVUrHUqXTp08zcuRI1q1bp3QUVcnIyODWW29t9zZlyhSlo6lGdXU1zzzzDHfccQejR49m6tSp5OfnKx3LqfRKB1CLmpoa0tLSMBqNpKeno9fryc7OJiUlhdzcXHr16qV0RFXZu3cvu3fvJiwsTOkoqnLy5EnS09MJCQlh3rx5eHh4sG/fPubMmcOGDRuYNGmS0hFd3qlTp0hJSWHQoEEsXLiQuro63nzzTb744gveffddfHx8lI6oGo2NjSxfvhyLxaJ0FNUpKioiIiKCxMTENsflb4ljjEYjqamplJSUkJaWRr9+/di7dy+zZ89m27ZtREREKB3RKaRIc9D27dspLS0lJyeHYcOGATBhwgQSExPJzs5m8eLFCidUB6vVypYtW9i0aZPSUVRp1apVBAQEsHfvXgICAgCYNm0acXFxrF69Woo0B7z00kv4+vryhz/8gRtuuAGA0NBQZs+eTU5ODikpKQonVI/XXnuN4uJipWOoTk1NDRUVFcycOZOEhASl46jSG2+8QXFxMVlZWdx5550ATJkyhYkTJ7J582a3KdLkcqeD3nvvPcLCwloLNIBhw4YxduxY3n//fQWTqYfJZCIxMZGNGzeSmJhIUFCQ0pFUpaGhgePHjxMdHd1aoAF4e3sTFRVFSUkJ5eXlCiZ0fU1NTXh5eZGYmNhaoAGMHTsWaL50Jxzz1VdfsWXLFubNm6d0FNWxF7Y333yzwknUKycnh8jIyNYCDcDX15dly5YRFRWlYDLnkpE0B9TW1nL+/Hmio6PbtY0YMYIjR45QW1tLYGCgAunUw2QyYTQa2bhxI5MmTXKrH6SeYDAY+POf/4yHh0e7turqagD0evmRvhqtVssrr7zS7viXX34JQHBwcE9HUiX7Zc7IyEji4+NZv3690pFUpaioCPi+SLt8+TK+vr5KRlKV0tJSLly4wIwZM1qP2fswPj5ewWTOJyNpDigrKwM6/gVuHw367rvvejSTGvn5+ZGXlyeX5H4krVbL4MGDufHGG9scLy8v58MPP2TIkCH07t1boXTqVFZWRl5eHpmZmfTr14+kpCSlI6lCVlYWZ8+e5fnnn1c6iioVFxej1WrJzs4mPDycsLAwJkyYwM6dO5WOpgrffvstAP3792fdunX88pe/JCwsjLvuuoucnByF0zmXvOx2wOXLlwHw8vJq1+bp6Qk0T2IUV6fVatFq5XWBM1ksFjIzM7ly5Qpz585VOo6q2Gw2YmJiMJvN6HQ61qxZQ79+/ZSO5fKKi4vZvHkzv/3tbwkODqakpETpSKpTXFxMU1MTZ8+eZeXKlZhMJvbt28fKlSupqalh/vz5Skd0aXV1dQBs2rQJq9XKE088gbe3N2+99RbLli0DaHdDhlpJkeYAm80GgEajaddmP9ZRmxDdyWKxsGTJEg4fPkxCQoLbDfN3N4vFwgsvvIBWq2X37t0sWbKEixcv8vDDDysdzWVZrVaWL1/OmDFjZNSxCxITE4mKimLWrFmtx+Lj43nooYd49dVXSU5Opk+fPgomdG1msxmAqqoq8vLyWvvq3nvvJTY2lrVr15KQkOAWgwLq/wp6gP2W/IaGhnZt9mN+fn49mklc34xGI3PnzuXAgQPcfffdvPDCC0pHUh2DwUB8fDz3338/2dnZhIaGsn79ei5duqR0NJe1detWTp8+zZIlS6iqqqKqqqp1VMNkMlFVVSXLcTjg17/+dZsCDZqvNCQlJWGxWDh27JhCydTB29sbgJiYmDbFrMFgIC4ujoqKCs6cOaNUPKeSIs0BISEhAB3eOWefr9a/f/8ezSSuX3V1dWRkZJCfn090dDQbN27s8GYC4TidTkdsbCxGo7F1votoLz8/H4vFwtSpU4mIiGizzld2djYRERFSYHSBveCwT7ERHbPPy+3bt2+7Nvsxd+lDudzpAH9/fwYPHsypU6fatRUWFjJ48GC5s1P0CJPJxJw5cygoKCA+Pp5Vq1bJHZ2dUFZWRkpKCg888EC7eT/2eaUdzT0VzZ588snWkTO7ixcvkpmZSVxcHFOmTGmzTJFor7a2lhkzZhAREcFTTz3Vpu2bb74BYODAgUpEU42hQ4diMBj4+uuv27XZ50j++w1WaiUjaQ6KjY3ls88+a711GprXVDp69CiTJ09WMJm4nqxZs4Zjx44RHx/P6tWrpUDrpKCgIBobG9m7d2+by5q1tbXs27ePgQMHMnToUAUTuraRI0cSGRnZ5s2+a0hISAiRkZHygvUaAgMDMZvN7N+/v81WZPX19ezYsYOBAwcyevRoBRO6Ph8fH2JiYsjPz2+ztmF1dTW5ubmMGjXKbdbhlN/wDpo1axa5ubnMnDmTjIwMbDYb27ZtY8CAATLRWPSI8+fPs2vXLjw9PRk7dix/+tOf2p0TExMj6y1dw3PPPcecOXNITk5m6tSpNDQ08M4771BZWUlWVpbcBCS63bPPPktGRgbTp08nOTkZi8XCnj17qKioICsrC51Op3REl5eZmcnRo0dJT08nNTUVPz8/3n77bYxGIytWrFA6ntNobPZbF8U1nTt3jlWrVnH48GEMBgPjxo1j6dKlMjT9I0VFRREUFMSuXbuUjqIKubm5PPnkk1c954MPPuAnP/lJDyVSr0OHDrFlyxYKCwvx8PBgzJgxLFy4kNDQUKWjqU5JSQnR0dE8+uijsj1eJ3zyySds3ryZkydPotPp+MUvfsGiRYsYNWqU0tFUo7S0lN///vetcyVvu+02Hn/8cbfqQynShBBCCCFckMxJE0IIIYRwQVKkCSGEEEK4ICnShBBCCCFckBRpQgghhBAuSIo0IYQQQggXJEWaEEIIIYQLkiJNCCGEEMIFSZEmhBBCCOGCpEgTQgghhHBB/w+mlPs2VdVx0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = %julia fig\n",
    "fig.suptitle(\"Adding a title!\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## And you can really use Fortran as an interactive language"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%fortran\n",
    "subroutine f1(x, y, n)\n",
    "    real, intent(in), dimension(n) :: x\n",
    "    real, intent(out), dimension(n) :: y\n",
    "    !intent(hide) :: n\n",
    "    y = sin(xx**2) - cos(x)\n",
    "end subroutine f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = np.linspace(0,2* np.pi, 1000)\n",
    "plt.plot(f1(t));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Bash, Perl, Ruby, etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/fperez\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "echo $HOME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feb"
     ]
    }
   ],
   "source": [
    "%%perl\n",
    "@months = (\"Jan\", \"Feb\", \"Mar\");\n",
    "print($months[1])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}