From 62fb035224e9bd64d47862a72564922538156e67 Mon Sep 17 00:00:00 2001
From: Manish <manish@radii.dev>
Date: Thu, 27 Jul 2023 18:19:40 +1000
Subject: [PATCH] Solution

---
 Three Math Games.ipynb | 354 +++++++++++++++++++++++++++++++++++++++++
 hree Math Games.md     | 231 +++++++++++++++++++++++++++
 output_5_0.png         | Bin 0 -> 20041 bytes
 output_9_0.png         | Bin 0 -> 6597 bytes
 4 files changed, 585 insertions(+)
 create mode 100644 Three Math Games.ipynb
 create mode 100644 hree Math Games.md
 create mode 100644 output_5_0.png
 create mode 100644 output_9_0.png

diff --git a/Three Math Games.ipynb b/Three Math Games.ipynb
new file mode 100644
index 0000000..6f03c00
--- /dev/null
+++ b/Three Math Games.ipynb	
@@ -0,0 +1,354 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "e4365f4a-71af-4b54-8000-e549c34df127",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from ipywidgets import interactive, fixed\n",
+    "from IPython import display\n",
+    "from random import randint\n",
+    "from time import sleep\n",
+    "from sympy import symbols, Eq\n",
+    "from sympy.solvers import solve\n",
+    "from sympy.parsing.sympy_parser import parse_expr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23fa0780-17a8-4801-ae5a-f4ee0172ae40",
+   "metadata": {},
+   "source": [
+    "# Projectile game"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0740f36c-6c52-422f-9db0-a6619a9a5ffb",
+   "metadata": {},
+   "source": [
+    "## Easy Mode"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "f39607ff-7776-4d49-8de9-2f79bff89a92",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6016d1e3623c4376bcf7aa7041f2beaf",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(FloatSlider(value=0.0, description='a', max=25.0, min=-25.0), FloatSlider(value=0.0, des…"
+      ]
+     },
+     "execution_count": 116,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xlo = -2\n",
+    "xhi = 20\n",
+    "ylo = -20\n",
+    "yhi = 120\n",
+    "\n",
+    "def graph(a, b, c, height, distance):\n",
+    "    plt.clf()\n",
+    "    fix = plt.subplot()\n",
+    "    plt.axis([xlo, xhi, ylo, yhi])\n",
+    "    plt.plot([0, 0], [ylo, yhi], \"black\")\n",
+    "    plt.plot([xlo, xhi], [0, 0], \"black\")\n",
+    "    wall_height = height\n",
+    "    wall_distance = distance\n",
+    "    plt.plot([wall_distance, wall_distance], [0, wall_height], \"brown\")\n",
+    "    plt.grid()\n",
+    "    plt.title(f\"{a:.1f}*x**2 + {b:.1f}*x + {c:.1f}\")\n",
+    "    \n",
+    "    x = np.linspace(0, xhi, xhi*1000)\n",
+    "    y = a*x**2 + b*x + c\n",
+    "    success = a*wall_distance**2 + b*wall_distance + c > wall_height\n",
+    "    x2 = []\n",
+    "    y2 = []\n",
+    "    for i in range(len(y)):\n",
+    "        if y[i] < 0:\n",
+    "            break\n",
+    "        if not success and x[i] > wall_distance:\n",
+    "            break\n",
+    "        x2.append(x[i])\n",
+    "        y2.append(y[i])\n",
+    "        \n",
+    "    y2[-1] = 0 # finally ball hits the ground (handling imprecisions and ball hitting walls)\n",
+    "    plt.plot([x2[-1]], [y2[-1]], 'ro')\n",
+    "    plt.plot(x2, y2, \"b\")\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "slider_range = (-25, 25, 0.1)\n",
+    "wall_height = randint(2, yhi-20)\n",
+    "wall_distance = randint(2, xhi-2)\n",
+    "interactive_graph = interactive(graph, a=slider_range, b=slider_range, c=slider_range, height=fixed(wall_height), distance=fixed(wall_distance))\n",
+    "interactive_graph"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "810b43cb-8289-4952-8259-648add3bbb0e",
+   "metadata": {},
+   "source": [
+    "## Hard Mode\n",
+    "Now guess projectile paramaters without fiddloing with slider"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "8b65fbea-7647-4e29-902e-ddd80170cdc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xlo = -2\n",
+    "xhi = 20\n",
+    "ylo = -20\n",
+    "yhi = 120\n",
+    "\n",
+    "wall_height = randint(2, yhi-20)\n",
+    "wall_distance = randint(2, xhi-2)\n",
+    "\n",
+    "plt.clf()\n",
+    "fix = plt.subplot()\n",
+    "plt.axis([xlo, xhi, ylo, yhi])\n",
+    "plt.plot([0, 0], [ylo, yhi], \"black\")\n",
+    "plt.plot([xlo, xhi], [0, 0], \"black\")\n",
+    "plt.plot([wall_distance, wall_distance], [0, wall_height], \"brown\")\n",
+    "plt.grid()\n",
+    "display.display(plt.gcf())\n",
+    "\n",
+    "print(\"You're at origin, provide A, B and C values for projectile to get across wall.\")\n",
+    "a = float(input(\"A: \"))\n",
+    "b = float(input(\"B: \"))\n",
+    "c = float(input(\"C: \"))\n",
+    "\n",
+    "x = np.linspace(0, xhi, xhi*1000)\n",
+    "y = a*x**2 + b*x + c\n",
+    "success = a*wall_distance**2 + b*wall_distance + c > wall_height\n",
+    "x2 = []\n",
+    "y2 = []\n",
+    "for i in range(len(y)):\n",
+    "    if y[i] < 0:\n",
+    "        break\n",
+    "    if not success and x[i] > wall_distance:\n",
+    "        break\n",
+    "    x2.append(x[i])\n",
+    "    y2.append(y[i])\n",
+    "\n",
+    "if success:\n",
+    "    plt.title(f\"Awesome, {a:.1f}*x**2 + {b:.1f}*x + {c:.1f} worked!\")\n",
+    "else:\n",
+    "    plt.title(f\"Oops, {a:.1f}*x**2 + {b:.1f}*x + {c:.1f} did not work :(\")\n",
+    "    y2[-1] = 0 # ball hits the ground after hitting wall\n",
+    "\n",
+    "plt.plot([x2[-1]], [y2[-1]], 'ro')\n",
+    "plt.plot(x2, y2, \"b\")\n",
+    "display.clear_output(wait=True)\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ef5840e-9c5a-41b0-8f79-2588f6915f78",
+   "metadata": {},
+   "source": [
+    "# Algebra practice game "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "56df3e31-3cfe-47b8-bde5-2096cff8d941",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Solve for x in following equation:\n",
+      "34 - x / 18 = -49\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "answer:  1494\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Pretty accurate!\n"
+     ]
+    }
+   ],
+   "source": [
+    "def rn(): # random integer\n",
+    "    return randint(-100, 100)\n",
+    "\n",
+    "def rop(): # random operation\n",
+    "    op = randint(1, 4)\n",
+    "    if op == 1:\n",
+    "        return '+'\n",
+    "    elif op == 2:\n",
+    "        return '-'\n",
+    "    elif op == 3:\n",
+    "        return '*'\n",
+    "    elif op == 4:\n",
+    "        return '/'\n",
+    "\n",
+    "def rpm(): # random plus minus\n",
+    "    if randint(0, 1):\n",
+    "        return '-'\n",
+    "    return ''\n",
+    "\n",
+    "x = symbols(\"x\")\n",
+    "\n",
+    "eq = \"\"\n",
+    "if randint(0, 1): # one step problem\n",
+    "    eq = f\"x {rop()} {rn()} = {rn()}\"\n",
+    "else:\n",
+    "    eq = f\"{rn()} {rop()} {rpm()}x {rop()} {rn()} = {rn()}\"\n",
+    "eq = eq.replace('- -', '+ ').replace('+ -', '- ').replace('- +=', '- ')\n",
+    "lhs, rhs = [parse_expr(part) for part in eq.split(' = ')]\n",
+    "sympy_eq = Eq(lhs, rhs)\n",
+    "\n",
+    "solution = round(solve(sympy_eq, x)[0], 2)\n",
+    "\n",
+    "print(\"Solve for x in following equation:\")\n",
+    "print(eq)\n",
+    "ans = [float(num) for num in input(\"answer: \").split('/')]\n",
+    "if len(ans) == 2:\n",
+    "    ans = ans[0]/ans[1]\n",
+    "else:\n",
+    "    ans = ans[0]\n",
+    "\n",
+    "if abs(ans-solution) < 0.01:\n",
+    "    print(\"Pretty accurate!\")\n",
+    "else:\n",
+    "    print(f\"Oops! correct answer was {solution} but your answer was {ans}\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4354b487-229b-40b3-92e9-74610bc74030",
+   "metadata": {},
+   "source": [
+    "# Scatter Plot Game "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "4dac8ed5-b7dd-42d5-a4ed-e51af3324867",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Guess the location of point (x, y) on graph:  -28, 22\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sorry, the correct answer was (-25, 24) but you provided (-28, 22)\n"
+     ]
+    }
+   ],
+   "source": [
+    "plt.clf()\n",
+    "xlo = -50\n",
+    "xhi = 50\n",
+    "ylo = -50\n",
+    "yhi = 50\n",
+    "\n",
+    "x = randint(xlo, xhi)\n",
+    "y = randint(ylo, yhi)\n",
+    "\n",
+    "fig = plt.subplot()\n",
+    "plt.axis([xlo, xhi, ylo, yhi])\n",
+    "plt.plot([x], [y], 'ro')\n",
+    "plt.show()\n",
+    "\n",
+    "gussed_x, gussed_y = [int(round(float(num.strip(' ')), 0)) for num in input(\"Guess the location of point (x, y) on graph: \").split(', ')]\n",
+    "\n",
+    "if gussed_x == x and gussed_y == y:\n",
+    "    print(\"You got it!\")\n",
+    "else:\n",
+    "    print(f\"Sorry, the correct answer was ({x}, {y}) but you provided ({gussed_x}, {gussed_y})\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d9745ef-fe26-477f-a480-e146542b04c1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/hree Math Games.md b/hree Math Games.md
new file mode 100644
index 0000000..079d6d5
--- /dev/null
+++ b/hree Math Games.md	
@@ -0,0 +1,231 @@
+```python
+%matplotlib inline
+import matplotlib.pyplot as plt
+import numpy as np
+from ipywidgets import interactive, fixed
+from IPython import display
+from random import randint
+from time import sleep
+from sympy import symbols, Eq
+from sympy.solvers import solve
+from sympy.parsing.sympy_parser import parse_expr
+```
+
+# Projectile game
+
+## Easy Mode
+
+
+```python
+xlo = -2
+xhi = 20
+ylo = -20
+yhi = 120
+
+def graph(a, b, c, height, distance):
+    plt.clf()
+    fix = plt.subplot()
+    plt.axis([xlo, xhi, ylo, yhi])
+    plt.plot([0, 0], [ylo, yhi], "black")
+    plt.plot([xlo, xhi], [0, 0], "black")
+    wall_height = height
+    wall_distance = distance
+    plt.plot([wall_distance, wall_distance], [0, wall_height], "brown")
+    plt.grid()
+    plt.title(f"{a:.1f}*x**2 + {b:.1f}*x + {c:.1f}")
+    
+    x = np.linspace(0, xhi, xhi*1000)
+    y = a*x**2 + b*x + c
+    success = a*wall_distance**2 + b*wall_distance + c > wall_height
+    x2 = []
+    y2 = []
+    for i in range(len(y)):
+        if y[i] < 0:
+            break
+        if not success and x[i] > wall_distance:
+            break
+        x2.append(x[i])
+        y2.append(y[i])
+        
+    y2[-1] = 0 # finally ball hits the ground (handling imprecisions and ball hitting walls)
+    plt.plot([x2[-1]], [y2[-1]], 'ro')
+    plt.plot(x2, y2, "b")
+    plt.show()
+
+
+slider_range = (-25, 25, 0.1)
+wall_height = randint(2, yhi-20)
+wall_distance = randint(2, xhi-2)
+interactive_graph = interactive(graph, a=slider_range, b=slider_range, c=slider_range, height=fixed(wall_height), distance=fixed(wall_distance))
+interactive_graph
+```
+
+
+
+
+    interactive(children=(FloatSlider(value=0.0, description='a', max=25.0, min=-25.0), FloatSlider(value=0.0, des…
+
+
+
+## Hard Mode
+Now guess projectile paramaters without fiddloing with slider
+
+
+```python
+xlo = -2
+xhi = 20
+ylo = -20
+yhi = 120
+
+wall_height = randint(2, yhi-20)
+wall_distance = randint(2, xhi-2)
+
+plt.clf()
+fix = plt.subplot()
+plt.axis([xlo, xhi, ylo, yhi])
+plt.plot([0, 0], [ylo, yhi], "black")
+plt.plot([xlo, xhi], [0, 0], "black")
+plt.plot([wall_distance, wall_distance], [0, wall_height], "brown")
+plt.grid()
+display.display(plt.gcf())
+
+print("You're at origin, provide A, B and C values for projectile to get across wall.")
+a = float(input("A: "))
+b = float(input("B: "))
+c = float(input("C: "))
+
+x = np.linspace(0, xhi, xhi*1000)
+y = a*x**2 + b*x + c
+success = a*wall_distance**2 + b*wall_distance + c > wall_height
+x2 = []
+y2 = []
+for i in range(len(y)):
+    if y[i] < 0:
+        break
+    if not success and x[i] > wall_distance:
+        break
+    x2.append(x[i])
+    y2.append(y[i])
+
+if success:
+    plt.title(f"Awesome, {a:.1f}*x**2 + {b:.1f}*x + {c:.1f} worked!")
+else:
+    plt.title(f"Oops, {a:.1f}*x**2 + {b:.1f}*x + {c:.1f} did not work :(")
+    y2[-1] = 0 # ball hits the ground after hitting wall
+
+plt.plot([x2[-1]], [y2[-1]], 'ro')
+plt.plot(x2, y2, "b")
+display.clear_output(wait=True)
+plt.show()
+
+```
+
+
+    
+![png](output_5_0.png)
+    
+
+
+# Algebra practice game 
+
+
+```python
+def rn(): # random integer
+    return randint(-100, 100)
+
+def rop(): # random operation
+    op = randint(1, 4)
+    if op == 1:
+        return '+'
+    elif op == 2:
+        return '-'
+    elif op == 3:
+        return '*'
+    elif op == 4:
+        return '/'
+
+def rpm(): # random plus minus
+    if randint(0, 1):
+        return '-'
+    return ''
+
+x = symbols("x")
+
+eq = ""
+if randint(0, 1): # one step problem
+    eq = f"x {rop()} {rn()} = {rn()}"
+else:
+    eq = f"{rn()} {rop()} {rpm()}x {rop()} {rn()} = {rn()}"
+eq = eq.replace('- -', '+ ').replace('+ -', '- ').replace('- +=', '- ')
+lhs, rhs = [parse_expr(part) for part in eq.split(' = ')]
+sympy_eq = Eq(lhs, rhs)
+
+solution = round(solve(sympy_eq, x)[0], 2)
+
+print("Solve for x in following equation:")
+print(eq)
+ans = [float(num) for num in input("answer: ").split('/')]
+if len(ans) == 2:
+    ans = ans[0]/ans[1]
+else:
+    ans = ans[0]
+
+if abs(ans-solution) < 0.01:
+    print("Pretty accurate!")
+else:
+    print(f"Oops! correct answer was {solution} but your answer was {ans}")
+
+```
+
+    Solve for x in following equation:
+    34 - x / 18 = -49
+
+
+    answer:  1494
+
+
+    Pretty accurate!
+
+
+# Scatter Plot Game 
+
+
+```python
+plt.clf()
+xlo = -50
+xhi = 50
+ylo = -50
+yhi = 50
+
+x = randint(xlo, xhi)
+y = randint(ylo, yhi)
+
+fig = plt.subplot()
+plt.axis([xlo, xhi, ylo, yhi])
+plt.plot([x], [y], 'ro')
+plt.show()
+
+gussed_x, gussed_y = [int(round(float(num.strip(' ')), 0)) for num in input("Guess the location of point (x, y) on graph: ").split(', ')]
+
+if gussed_x == x and gussed_y == y:
+    print("You got it!")
+else:
+    print(f"Sorry, the correct answer was ({x}, {y}) but you provided ({gussed_x}, {gussed_y})")
+```
+
+
+    
+![png](output_9_0.png)
+    
+
+
+    Guess the location of point (x, y) on graph:  -28, 22
+
+
+    Sorry, the correct answer was (-25, 24) but you provided (-28, 22)
+
+
+
+```python
+
+```
diff --git a/output_5_0.png b/output_5_0.png
new file mode 100644
index 0000000000000000000000000000000000000000..69679ad11f334775bca434af7a70e7ce29caa5f9
GIT binary patch
literal 20041
zcmeHvbyQY+*X;%b1d$L)DN#X50Z}>>!2(2Dx}-t6OB5*ql@<h~8w8|7q@<)vB&E9>
z?%JO7e)rt(zTX{p-2d(vpW~dtIgbx}?_aGo*PL^0zsE9CXYr}=5d=AV|DMDX1i=(Q
z5R8J;IPeJ*eWf(~;J3Z2Vk>X?%+^82+5nN(v3+i4X=`Sz%V2L{ZDVX{!NYNjgPV=P
z$kz6`jQ}U7`G0(Y!_wN2^P0w#2V4a2`8`z|1R>Hv|HViXO*KXk=`Z&s#1$N4mVP<7
z%5UxCuF96-(iV#0KECREo+QM4FtIT09!ZW08~zK=fsDrnPJ@}}L#|<tw3M)LS43Em
zajG<je-<Z6zzml@Ltd^tBvLK9ZfbV#*8Of8k(GW{&UZFd{7xTZlJ=fkTL(RmI3)pp
z@bz`(F@51r;4AUh@Z)^I|I3ei2{~HTgkcX}y}5A9B(*JupOhsmLw!d%T_KX+CdJBM
z-qRbG=yvjx@zImx;;#{v&&O}??(HSS$JdOtxOZKjjr0qk;MAS%NJvvF<}foiA75H}
z)6wx*y~44xCz<Neqeldifs|gUaqiTFgoH*tX(S`=2j;`&4!OfEB{nmJI7D;=%F4=o
zf`XU$_$aGSj$QmFFWfXU@@)2^6Luck-&(lRK3Za>mrqYwZ1Jl$OSPaQ;SO$3mMUqH
zN$>4oI^jIaQ4#MRMY&An+=k5DDtvl+`ZNU=0(y~(x_ra-81ZWNqp`U;KWbi+c!QR3
zm3&?7^^J{|EtLokjoYJDZgPo|XG=;;$KTu<seys|)4Ck(+ilKvCZ3~Jj4dhQ3#1pN
zixseY5gSXZz@nI*>nC-VUWA4v?7_;!%#2~hr_A&fcxXRDmGty<Uw{AFr2Fr+b-o7A
zHP#z;5SWct(V7nxio+y~I4`ifZVwt#@>^dfq~Y_tX+EUg7(|=G(aFFh9sLq+JrSm?
z`PH9{mH6Db7v?{|B-kzV-Me@1>c;Wh+}!M70W%@3z{_CKW6FYOZMCH~GaZ#K4wtW7
zF>YM?Rj#~JwYRrNMo96Rh+fj({>#W_WF+P9sj2blwhtw?bMHnD%N<rGYG0i}JT=Pg
zFS4-U%L;FupKgy0Fz!yd$j*M&ZGZEt&)Ews3c(j8?%vfoIX*HPso>Ab%6dTKFx^UJ
zJKuxXpR3gfgIoR192XChwmarcL`*^=H$6FA<#yp$nccVEOl2;QV^`PBPN{)Pms|Ur
zbKb+l>WG-8CY`RX?&k7`*w{CBUK1)--M{4b=1o0}G$cIS=UH2{q6yWPFJE@oTR81F
z0?669jbi0fW$r2|g^NcR8;yFL2*Y;_=D8m|JKEoBYH9fva`Db14S(*_il)lBnq;`R
zxN935?+<oX7Fu0a$Gl*3`XweNs+ZfhNsv*uC){~`SyWWZk{a1N7(LOPK1%%b>6B-T
zkkb>vrLN?My2i%W<WnAzki0D{yfHUekh(e7Ej2MYnJn&&V|{$+WIS3`NkGLdfsc>h
ztYIl3@e(fo-3tph$z^BRdj0o(r=zX@WSCRygKcv^Kfkv)XQ`WF_-%e~{1A<p>rQQ%
z@6ALn_1U0>oP=a=Dnje`S8rT_mbUhGa#2yybQnOX={1vqJe{semz@W{c3{5`&D3;u
z%E4+VEtbGU!(6?Ab)I{)(wF@Kj!DEGpI&1SnTv}{snw*9{Zm`pLL{WfwBO&iDO;^L
z33ko;{z7ic_xH@n=rfMhU>NshMWL$_HlNG3wzh^T2K(>v_yN<EEB8%IGJJj6o)+Fi
z?zy_Umad4J4P3Xfwar?c3{T06JA2`#!u&C!-w;TJlbtS9TU(nX;31UWYx4d3_qSNM
zgr||c=?|6!WryMHYRzyg&z7|^t8Tenc?%(liboP@8vph>AXba=6kH&Y=V)=TpsUzY
z%gWmNoRpN*TyJJXT|>is;9#DPHxdFn<2#(X`nERdn3$N~a2!KmGtUPK+s%ib!ol$`
zFE1Y$9K8R{=j>E=@d&qB!IkGWHt%62!ufOD4z|0h+*~T>yu7@+AXda03py-^&U|!{
zF*7s!y*CpVaY-u3Xr{id&i6s`JJ|Ab!-m}{(wJf*2a7yQg>mlt_c1Xs>qbU2KRVA}
zL!U=R<$<(x80-vRxGzk4i{MH{B88bhDGA9%q>w&_Y>iJmHLdGKyJ>DEQ+s>6^ViLy
zeoay$qG0X_jZ_(0r>$P)trXFt&F-#p2g{|U!$ViqYWGT^tsZ$@OG{2TZg0;}a2U<x
zYE^3@O=Wfqw&6UMBSIJqa85Z2!avb5&z|4n6KCe+lzsB#3Cm%m$MIe&!G)WTVq#<K
z>+A21xNb=EJ1oa&c0_UM`Dpq!wYP^`O*Y)mep-|y`G$HO&Qc5PhGsHbe9=XSn=Cdn
z?O|{m|LpAS&H3JkIqIdKZn^*bV&0V^eIdV~fYiak0q^YDu%E@23qnN5CdU;jQTGan
zi*pq#wcoyBd$MU&sSC1SyePhM^dU0x>Ltm*5COY+U$|VM+2E6#7Q<-;hqe86pY8_e
z&vhktrO92&&&vyeyOLe7{ajEml^mgY&d|_sZ>^F3q1&>>aLGl8zg<z=2P@TQkV=8H
z_1#`Y-kqi5(N8+xd}fD=O!GI&?G}9C6zJ|O{~9u;;MA1p&(T=xmKD{RsPl`wX-*BN
zv@=nPD2C7Kwk6g0_&5Z*bI;mi{BDi9l76^pUh9d0#lVPoLSVRb{W>ukzJ7mypKm?&
z;H8hx#O~T;gK?Sf=B8~@YHFfV_S57b)~i=*eu$m~+Aj^wwJmfcVC86(`#@A!x^d>r
znOIux0L_)&Oo|b=9SsRd$qCrZh$kGd@yeZ%J7QwUh|^50ZiIY^>|Hr>a&m#u{0Il;
zj+ZY_@$vE1eEpiBKAHIxl2u4_v_F?#!x%)K601p^zARPmrJu!m&7s$lM|Rp{1xq|m
z-2E2jhf8gSexf;Mk9D7>YO7Cewm+Aik&*HFLLWO)^Xd%6b<;k!KpOsYoK?FMlV6@D
zbMx?wFD?>LP*A{{U1Vb;fSh44A}c{mLlekZeRvK|S3O+R3ZfM3qAc~`gYBP|dV`-0
zP7@H+y}&-BZEpT1Len|@b`hsa9wKPJSR+O6_7e907);dZvuAs$3aln23Fw3<!^6XU
z0|V>Q<P!7T4(x5`y09S_Af7O&c-c4+Bz}WT^M0BAl0SNQ7jqqdH<75QsEjqey(G|$
zw2eMOnwp!@ti1}MknzTi^APV}1O%M%A)*hOYKd47Zif}mgEb1I6Q+)HUB??99^P!w
zH!v87?>FS@HKN%bvQc`^%wpTE(Vm0oje&eU1kI+Q&RQ9WJTp6ss<riJBxG!C>`CL+
z%Ba?i#|ah=0r7<k7h-b@mPaaCWn^T!vej-a71pu~K%NbQB(<~&bBd1)7MVu)`YsOS
z-$9zv<x>d;H1=Afc%+bffMU`o>4Y2^5dH1NLFWzFFISM?>r*Z7!o!)+!z|*q-vl@y
zXQQ`wA-6i`NJ~dj(g!{5T@_9?u_p;+M;QjSFY%nUG|oaYIq2<$z*X1Zul(%C$Lyo|
z`GOxJ-Fx#He9AfMB!Ys1PLpqLv24XC)|1CpR0!b_5mA_$nl7D`u(PupY|Zx?aP0J?
z%VUbc+MlU(B4v6+jJ%7DWiPfI4Trt^9nzz1RT+Ss_jsgCMk_WeBf?e?D&Z0D$;bp1
zTKswnp`N8ku`X22mPz&_+j}PIcWA5ttWczOQ@~-F&7`QT=U{obR32#p%uv+5zP_Gh
z+Mi=!(aG;|T!Dl*jJhcsM&(u?JHPred&9Kvk+rpTVRr<l76($OHfC*OlPnV}u)bLE
z;{hab`(gMxGolZ8V91zkZ+`yx=s-Zt<lX!C^|iIPHQlxpW3vNb?yB0u;{c%HA$#+g
zxrKUgmHN?9Et8(Kgd>-yyV1|>?fZVZ#m|z*qKSH>vb-ll@gbZT<(wginK}J4FeTWY
zNy*7!rc??yabiufo_AZRj`sTa_~0X@ZU<ig4*7X|d&3@9u^f)%(yN2JA7DJDw8h`?
zyBZ4XsHCJcl=}^Tw3X*sYX_c0gZ*sB#r)5oS-wO_{i<-1NA4*ogpO1|e#JwU=;Ka~
zRy>BB&QjkXCTV+JOC)+2Z&RHp73}}&)hk;7!vncegmgkzqoSf1Kka!d?k0SJjVqVg
zYYpgfZ>wMHuEd5qg}XMKNh$Z^y&2turlzJ4G-H|cWnFVv9==wv0y)D8@J#!a%a<h}
z)+XJm{Irl$7=MZJv+dlIx&GX^!v(FAKPv~3uCBTHf&Jou+`Kgry-3zk#-to1I8tPN
zCeFkEX?FPRtPx44>%e)R;;bw-e#h1L_M@AYBWy?#1cpyf()9rdPt9|&vrEtL3%G1&
zAtAAX4)c#>Wn?(|*YOpZX3wXtvX-=cxD_E_0oYjAz#w^NyaWypw|D#D-bT?0$<=uX
zu4MQEckhJz8pXBLo?NFDw12dcnRwgX-M#CJx!Tf_|8nBw%nb9zix(LgKfCN$<bV0n
z*LU*Mvf9u0-a=n?vd78s&;gq2Q&Uq%`g339CR<h?DM=jT3)H(QY7HESp6to4?d(tx
z5fPz4s#(Lqsv(G$6_zcyh@h)JHz$LOnVA{s*lSMad$kc86SF$@6-)owvrmxlohPGt
zO?_Uxz+7TFzAYVnqq9^4aKEFIld%W&PXN*c)HhB8uD%WV6AhUFd>ELSQ)`8%rl%Pp
z>CHSD{_&Pmt13`g(+T^B$N}5&-VcxPQgr}f$ki_?wOW#7L32Ngb4Ms2K76<|y?z^}
zuK@y+6(Gb@*w{LCz9a%0=r+}OCI>jrCoGJN`i9Zt#azpZ%F519ch6ML0e(M?hxZi@
zmA}Wy!RYGtHb=Tf_J>=RpWsXjM6j!U8G{QtcY7SJHF8HNYn~xz6H`z)533l6COoJg
zU@`<dk{?pMeD&%gCueTmLAZm4s;cTm1_m+9Kqz0z;Ql=9moJ~<tlT^&^HInTz-5BN
z%E;9GB_Sd88Ge?-GVK~q41sPqB`rllcP@y!3$d}WH6Pv`gVJzpYU&l#P_vIXmsiBB
zc8c=y#3mcwu)2<Zf@orE(GLX~vI@J+gg!NCYJYFfct%+g5_XZ6G%dgNsimQ!JLUFE
zW7E?<0L2)1dC349y>I70ZdnYAK>*rxuhQ84=vGLlr8Rnv-eb7LiqCHT{Pxn%*ASJI
z%ZRvx-g$^VV49hjz~toQJUra^ksNdYz)r5%LIW)wd3d_V?9S5>FF?B5h18bsu%a1A
z$%TogkRW=|oSnv^8&GZC`SDTME~UP)ae?N?bYHd_WWSe?eX5}9G#_Jq^Wnn<C}0DG
zr)9<qCtln!ZsdpD_7wm-1_DF5^X%C(zk}BEL9F+U8xybHFzLDKy7S9npwO7qd23#A
z+7VgZ+>`(~-d=b&fE>0t2Hf4ReG`&Jm}%71+Mr=v0^oh;g(}$TP_EZ(E%dMT$jg$s
zXu+6}t5zChIW3>4Z<?vh+r)&1zU)qw#X{VVwv^AGKOefVdx?};rVc=MQ86hgDVOc+
zV>ZnSm6<)3!;T!2?d|R74i1gqUK2^L?~>^l8>=qb?wz<D1*SiY;Mi>xJ@$e!idHI!
zMjXbG@FX4GCN!`tBO@bM;g6M8<NDQQQQlWCyuI_GQeguOpyj$&uSa{(@aq??latfE
zhYwl%M@3jJ6wfNyKpA$&)m12nPWb8KAuK0aq@w@@iHEKF{P}Y+b@iB$ftCo)Z?(0U
zFv$KW_o-&G*q?w&N*q=`j(pwx=yB}S`r#H)s%%_Ciu8x)YZG_P20tg?J}NZn#qaFw
z6rhlmm0dbaO1cd3fRULQ7l2l;`_*vB7?|u&3p?Bg$m}NS@L&njYCUc|YmM}Raq6s1
z)cXbpqbQHn_QXH(x(?<|vjNZKhY?D%1620*_NPyu?kI&bp8)lwbNAUjo!H1omBnzr
zqNit(WQ)#p;4e&Ieiq9FoYpUYbXhLN?<XZEM<E~z_@FpZ`C_J8y1diM^J7*>3XV7q
zQfU5D$<P^aG^_gii;#TAp+Fad&Hj+KKVBRQSPogs#;J*8!t)NJ5PYB}&92?a_Jtxb
zv}72_g(cVcL%}5q7J}<AXxQ<g+x7s~p95$@S0^YaNMIo!s>c%RDgTkTuOR?s$y+)R
zP+mtC`g0rmwLISB<>le`9;ek}Ni;MziuPHjotF1-kW4-RApNJDahj&un+z7UoxXDA
z%6Fb0LYIJpv4+jMw26U*gQEBLV+=ezyotp{^@P~BXx?FDgapzfSk+n|K!NS)x<8kS
zv%o7XtRY}K%K*s98q)ZaM)IA4R_rt6vr9MJ_SOyZ3kyT<zh_cR3!iKZ4oFT;25!pN
z_nDMj*n{L^OW%v<MMmj84)evsmB|Dzi5@H#OiWLwY(%%Vw7maf{?q^c`}ge&b5JM?
z<jRt~br^AyT3lM1f^$D)e6YPlicAe9l%`o$?Lj>WoPmVIWypu{jVl}+Ik#I#(#vAs
z(!0rg{`}crI8<!BeGp0*&aE{%L&M*-aq*(d?M=aS52rizcF!*d4u3Xy_`SWoFX-U-
zU}ei*^5YHTclKJ@>ltdrIXBFQ6ckv(wpS^cWnzdC=hy7Sd!~lJAs#;!l+IRqI0IzK
zFDfSp)&|>E08lX);5@P^x78ofLSTEEe{kx_6xVE|7bHc$qM{<$X5Rsk7yvQCZ9a5k
zZF`#>5GZ7g<3yh02rYLKsDNR^<-jSB{q*Tm62xL%Q&ZN)VEX<bRssRo<RMUgG&hH_
zUV-2YVK@nP_|WqLNd3lLNq&!F_~iO>G+2Rp3x@;bUr<nR2xA(WB0GMN^jT0F2N(AY
zLdB)~(iKvrK!lXTbN1zae4wb%@))3P5Sx0*<8TfQ7C4?1mX?;4S`R~+SXm!N-!x}|
zggvD7`uFeO_co^6>H(y7b$7G&YFPn-;Xr@^VsaMtfUCX>33)tjAR^PTx8iZaYBSyX
zmfvRD7sv_}VY(au;nx*(08s9f=M9Tt6&RyFP(BkYE1ZZvKuduZvyON#`_z@&w=74_
zL-lDqT#}!ql7D;pM;s@wX<sNg`_oz1)8SXRxa3TFGp-1`Z1+@Yp6pH%t*x#Sdw6(M
z(n`0iLxs%GuX>=qwe(XNX?jiXeieO=FjnRHK(|ePzu;gBpcbhF?X%GGH5~9M)Jva`
zkSe!>@Ifhe_bS`vVO5yh-@hD2!(>H|6d;aYflSNRZ)NL4K*fk$zHvhV#rnW?^o;aB
z7MFtkzz@JC6oBgY&};H_U%!e&z)mAI!FTxN4ygS%Fpw-ZhGrzvHSC8jO82sr0)UG`
zLZWyK=L3JVwuVCJK?xn#-SO9-VHYiphQX!gw&Xs>Us~@c{0%eCS};9v9OP$oe2GiH
zDTI4PcIsQa9ut5>Ln>~4U)WcFwwJSWGm7&GKPvSM78qW+di5T}!i#Xay9x|t`Rx}Y
z+asljC{+rcNvF#t`as1yPqPN4O98ij6ESc=Bx-7E=r-6~=$Ez3Y>5~5hHz1J`{WF3
z2E-d@Ts+nap?z`HE_z?JVvFyi$J@88?CrxL|K9^T)nC|1)wm&;o)c<8YY4-!a}dYL
zSy@?Orp;ctu-+ekEptDj*>wyy$F(_a^I&&vKVP`F)Pc=YI0VL>pI!ltD`^>3k4;M=
z%|Jvza2`lJD?7Wej*bp|+;XUm(4e4R?XF?C52xV4A(^Hz%7}~<3+0YV#l06jIh6My
zq-6mTGZgA;G>+Y{98rg@qqVHnf`+;amK6!Y+GFrTZW#;bnSsG~AR0KAmzO7IXI0X%
zaKf2qeSOV-l_@?gwqOVH5sgR=HDV-feQ7%*F0zmY*ija|x`st4ur6`sho>ik;V&w2
zS6BB_1(f3gx#Lm`*+v~CBvE`;x}{$nBQ_n(zQ4Qj1VH6duE5+{nnZ@SELTQ25F@_D
zBhF`1Wnx*j$IQv5#>c$?u62*iOkZSlewUP#gmS4WCC@KP2GJPLTes3VNHTesIIb~5
zK)Y_-by+^*wuFA4y1M#xs|g8|sIxRQ&fvqL<@SXDd5M>|s8ybqm_%+6IOL?GWHw<s
z5pRgTNh)E40#JcBv~X4v!0`q`d=bhyLD_62y{@GDMxCFqX=rItrXIzPfB}0|8vs0z
zP*dXrNmEi*ru)0;?UaBQEmgzn__vFUID?`fFr*1&*mitxY7)y-%FZ+CWvO(6@`lf4
zn++n6Pl4eNT?p5{0ReY_J+^Cj1tiNveSmLJPy^I|ui@%?P&tIL`vLN~_gdWDF8N7%
zo?as%WV84>E|{O&uL)_NPd1$0-Q7j$5y$B$LtFPXxGY`8?nFQdkPW5n8+TxE3ehZr
z{fZAB;483@scUFpAo=<E&+Y7b_l7PrFd#s_@L5fq(sY^%(~W>#lxV|U1F2WYb(a{H
zpG?Gzj|5iD$Cm+EZ-76NzvjvwypXZCzlpN&7w`Dg3=UEuAt522P;$+Z>lt9*x^)XO
zPH0J1Q`5cHXx^5zt#d$o_m<c#kVDQgES$O^Je$^Qf^s8_FMtCV-Cj?56!pT__w>?I
zXy|zu4ugou2wVGR^xL-y!m7hS)s9U}=uY?(z-mm^cwwR3epYt2v__EJ)k>*t!{gAA
zO9wn2kcR7k?K0o|VUdUvTN`2nbF(;FtyRv8iwFq|Tb&%c#jXJ~bKG4`Xdld?H!w9l
z1E;!j&ceb%pd~kFadEM*|JU$vq1Mzjzo*$g-riWlzkZP&;3zr=Fa9{Z2DeJ3X&70m
zGt%-W^NC?q&e4V{5MX3~)XK_A@bBOHz++1an!{=WL=*$`{6-NtY!YE{mdd-#!oswG
zWqU`00C4SX%#2S@<DkHN$<pH+#G^F`s272CFCYDbsm;tfvQ&9Cmwr+tO1`OuN-SO}
zlZ1{gC?tgVc)}kx1i_~+@fl#=VJcF$?Z@4Dfad)M)XUoF$uR}8I&AY}Zg>Tqs?J1Q
zL>nsG(?mp4D<hRUIyznuuXG@@{JpcJlD%bsUV1!q(XrXakq#Em6&U(3b}zU~nu1V2
z8I0f>xi{f||M;(`Kq=X~9hmzyAd$cQ{CR;T3?Jz9o+wVnND()Iii!$tOUqygi0Y-*
zcMV(rx3F<fRyNn{KAckt0Tx<YZf@?53`N$gr$re9dq8>D0fftY)<zAiEhgaG)A;ze
zL9eoZWMp)eL$ksccnY+p;&a`-E*VUxG58La&DT~%aXW~!Vii-<ar~9;jNfUH8+;&p
zF@j)-tkzR#)qMMg1&=6k@7`$+jk1@36~+L28TIGTBHB~UVUBC{6#0&8x{fX`6y=LC
zF*JZ}j4V@AQZSJo6W$&ZJA<F;+;>fHL`1V@<S}2_R=PJQ{8@A(b(3x|ZZ9)q1cvc|
zl%75q*j)Hylv-L+5)Tp#V4b^gM_oO=@%j0Tv-}7#F);#EF*>x|iuDKiEkQt(LZ;hH
zIa&Qi1clLcR~{TC+kie`z;qza)|v#e3J47KT%nBZa?$sgmi=?vu&5~2E5Ul9@$W-I
z5M*_AwIgbId^{mG;(v`vOOX?gqPVeP9}oQmT$iR*ErN-K1thRp8hIeorAv2QD&c@a
zT;$c@lKcecjh6NeP=GZ<Lqk1Nl&}7A!-&vOg+Djcdjy#<uc)Z^gN3=dIXS1#C*J6X
zZDGlq$H>%9({XFupI^$%*ynEk(IPA?jDdjSCD0A!Xwk;MBGTU95y_qao~(27`h$+O
zt*uw7smve&7Ir_8m$w4IuzPTTg&ZCoy^V<p<S}eFYJ|8(kByBzJCL8q)eJoMC+0`V
z)nyN4Wg8)&78OrUPFjH$2h{f0#ztJA9lil?)|qslba#JWcc{=9$dU%&z!0P@n)eO_
zF)k?0Vcu~}il{*s09xhR8ig{tBgy3E;%)XfjW-tu<z333<Bo&apaa*7<g;RgoqFAQ
z)95lYb0R?Pfda$e_S`_=m0zx|KHpsabpa9!<qacZr7V>-$|X=fNsf}c#8ah$>4@K+
zo5@sQY5gdC0kRc`RUps^Rmb}a&EaBjO9hsX3uuV@e-r2bzx}<I<{oU~w~%H<S<fKa
z#+F234-C*y-%4LRORPw`r>Z*8S0((V$TIh=kc7mhBc(0O(Y^eC`y-Ir7T9bqD5GG#
zYez=tfR1W_<ix-@#KrgmRMu}TEoXoNf%?7%uz#THpEPw5ehsRQJm)PFw2DR5A@qO2
zzL2F}`b6;Ac<n3H41h{7P|1PhN+K>U4m#S+XU4E>o2RbNTiF7m<})^?U9s8q5b;E{
zD8T1@Kn@^neKCOBbwG$XO-P7?09Qf*C$$FnXp(d1bX(Wa!HmNL0El=Ani5U*(e{Op
z?)%1vo87W}&YM@m*;FwRAS<M9-v;Fovv9}C%1RtkEXjonYGxh4I*9{Szin?~!h(op
zE8WRfx==vtef4Q#X^*<xE8%PT#kU(~xi~pja;Ijd#2@V*UUQ>msT394L*tgRVkH&t
z?4yrDR1g<dH#WSJldquj2l^t^0hq|SbLS9*j*d=XX9I#uyNiOp{$(gjl5ZVB0p$tg
zpO@hEicebKm*7wWYr>S(Q1U4;QCj0gC)H=E?`^%BqvZ~q3O8@!sM#C*^S*xvuAcY;
z^Pe}(h6?etJdSvyZ&?Oy%>2*;Mh`uuc{<-%idsQeVqj#v?IH*~AQYfd+S&}DYo1js
z>(tlRH_F|a?>&=~las>Qa1Y`$+`BVXmR?0o?L!$&BBTW;*gIS{ObEl(tEZK=w{cW0
z46goT_<x79o_HRe+EXwKst05WpfaJ*5@;M<klKN!JB3_kVybOvdFWDIS0^E~Gi+1O
z(cRZa4gt`)8_J2ciTcNdk~Zn3pF>CJwFl@F@7|nzs;2rigIdVpf!6B>D@2do0Y$kg
zDr!j{^(sDl#>B>EOJCd7bq>N9f@o=JIXXKtGBHUCiozIyQShv;uI74p2@P$Ya>cV1
zhwCkow=C&^JM934C`QnM@L@RHS6`A#2m<-`zYKAKs?-p9gfU=iDdnj90kb_0P^<pv
zU<U>BAi`;*G7A@MXc#LFq|i5j<4}>#WqVO>Q>F|JNWAdNAhG9}4RW)oeaWihf*V5M
zYJdvujVeBRc`wHtR*1q+*l=k7`^W!b3KDUF1YFhzxd&kL>&i;ur-epdK--$m1e{Kh
zjUxm^Jn-}9C8$b3*yFNS{VT4RbnJmUq_fn<5cc#Wkp1*1$?LlQojFalAjQ5FB)5Fs
zdVDm2p&KVL@zRSIFG6Bt&0D)5tjywR8??TXx_dXl{b(OHv$uV8Zf@>&nXfjexsd{P
zEWqJnpzJNSkdRQG&5X>;moF&`gwS>5gF52mc&8dbS1s@q{-FINSo|t;1i*!6OhgPw
zT?h^UW8y1=ffg6AU-TUq7|`_w-j5KK_=@G_<uMS*swPE4kxP^koz!i~)BY@r_x&o#
zxZz+rIeD;)auVs*&dAO!Jf1tkXkK}H6jhxu-<Bpmvoq?^2n7@DFE7-^1QlN`)Z|1!
z2!J9@03;-s>4=D851bqwjb?;dxVg`PAk+2X_#2TZ2<Tr|r72Z9bANBIj1qxDN~)x%
z4wPvM$Jbec!NlLwCb=uW$|+bbT<~Tu{~TIH7&by5e~7}j=GNA%ca3s>zLcipH*elV
zF(Cx?l-O-x%O(LN0*I>zS-AsNW4O|VLQ_+7hzqn7p9jgcpbu<?s}7UL0=*3!>aiz~
zZ23>QA_D^nmP8)xtc<?S%*-@C!;M+=^bO!vC|_{<`ub8h8m|U+>S-#G+wTI((e!)s
zDy*_nJY0?HA93RlIEt^3w60ydCV6ytbDo?Qwu;b3D~~`os#BdD&WIuiP~eCd5DqdO
z_a8l~v-u&cyvPl>OvltT^VTnbacr6de}UGAFw;Iua*FyqIYnV)Ss7n#QaA0={)O6<
z6}Jp}v^4CNhp8aR2z0w2EZw?c)PZ<DYt)BZ)Ya7)%>Wh#Qw8bj$;rteRJSCG;Si(#
zcD~huz{lmdstuN@b8#NW{30iZHi#$84;UD(J1nc;Fzz~4RaJ#LGC<7Y(yl@D!X;s+
z%ObGdK*0f|OdH8<fDcmlS%`}eatIO<68<k@6cVph?GCzvmfwaV3mN?S8>lQVl%I#K
z>|DF5jsm(Q6#{|({_)ooD5Y?Crm^@T9)}pim1l$;<4Zrj!~8vig^eA($7_PLw|fSh
z8JohsVRo8NAiB(&kuie+hxSQU49(b~(^wte*rxH=y1`g883TXmL`#Oo1*5K0M!%?y
zx^avKpO6MZ_3W(Iaj~8lgG2Mw@s6nW54y2gIfh%x9x)HFd(so}IEze-zYMFWVuXiB
z?-?6MXA6D*UK1-Ay+A}~!~uRaj(Tbt8BPX<nsaXZ$k9H=)`GHJB4i^AMRHpZoIFvl
zi8ql*4LIcxWN>hB7fL2ni-KAWP4sbY+f)$HGBVhncxriI-!#X(X^As2X*W|^jzueI
z!omL3=u7hr3xa{45gvQrzei7LmYs?b&Mb`)VZZmV;A;?V4g6ESg84&~sA4~3y0+tv
zgo3cb{SJPR8G%R-fRb|l5j`lL_A4WAKy1L_;NSp~p%F-jH8}iAcUAQpxVdkPL+Ls;
zTw0y-a}Yz=8R4uzPGMunie?YK*x*yw;MGzsvN&6DT=wkgvuAWlIe}neG+g{?=%?4{
zIoZe?fk%2HSk(E(>O??v_FV}HeQL>*UPWhTf!lZPtOa`<Vgc{nBO`nN{#S5n<>`Mv
z2TrXspeNJ=@_fEHz(phKK0ILXHmb~>c6aqoyr!^rE2VT({%1^0cdCKUcMELRPL6Ra
zPDDBi=O$mryi-xba(DNbSn=Sj=}fFy`dQN)Cf1)5?dD*=g7d<gSCE@iGiy%(RyN~f
z=SeOVC|%$H!o$G8h!k|lvEK*E8l`C<8N^P{%;18p7TkIhpt*9|JMr`LH+}!!IU*x1
zjg0{L1^-;K)8YG%8v4#QIX#iYUDb&IPKBnH?xcu@H`pr`@}3EI&WtT<Zmyl(&b#7V
z*f><g`_;6Sa;$jNb8CSeDtYn}8>v@#q@H^l*m{lR3_=x1kqKFKD{v0g;c*eTT;rzS
zC>Qbs<eWV`*U^eOH^Z67qyrM)nf8yu0pJ>)YkPR_p68o4XMq^BOL1{@WVm=Sq0T@O
zfFA&TP|tVAae*-wvTth$kB!Z)1S!@XY=u#I)RX=}LGFtNm#+-!Y&;VMgCzalUi8@z
zb~O>PljHu56lq2_wj0$M++pvW7yHhx?iAOIf7=2JlzfRzBi_c0n(kZ|CIO8j+0lWP
zceZ&|yIWGz$8L}<Uo|&0q!mTHzSyT@m+~Jm8KmSep`gwe?O?oF{fbM^06aiE{WLgH
z#ld6x2l&tT=LXl*h=IC&VbLn^%D*alXK`7){{<B*n@~kX)x5hxu2M0885I@H&gZs&
zUVFX=bN8Se)5x^s1#3cuFb*!(84ApD`>BiEUFSrP^xsH-h#s%O5PcN)F<9rD#DQsU
zMHbs)BtI!aeE$5YO#ekLb8R1$*S%3)2Uww_C>?qK{(Z%DKFKoz;Hmx!c(W6XgG+_r
zQK1oWr344%we96!0br$q`gy^1fEmzrcXvVE6y&MezCI<(GSI|SD=7W@j5v6el??Vt
zF+k8Opl@IL8EqUZh!sF?{3S%8*xM;0Rm#+Ktf>D+b;HnS?A?P=uZ4a^#~E7IEVb0Z
zgfi(1V*fMEnR@5S{ms&3WK;!ir+0$aQoZCk#>|hneogQYz6Kxqk{x)b&?L7)N<r}&
z{1mmLqoXPYa=i8jH#@4Una&SaoxNd%nEk@1;m5o>enm$oVXwDuss&~=I*~I@0K3qV
z$aNKC^`!g*n1nH?%maenzbF0Zwyhd#3<MU+m&(wCryH^oxEpYQ)~NsmVRdJR(@IMJ
zNy-aM?WL#MU6<Q(-)Cj>stGemcO9y$8=IMXtxbA`5Hm2|E(kNM$JcJO7kv42H}UQp
z75RvJ5=oRy!nKXSg8xl$&e2>C`ACC@SCgkxLnLZs0sP6yA@gc0PfB(si=&e<p*5fG
zsnvGDnw4rbZH!~Tn&=PLug1M*XJ+Jn$#SITygDWx`x9z86*x|yXDNmmJm$@JxwYD-
z7A?;@@Du9{IijQE5$ivGzcZC+b>l}(U2xB?*&AN>U7quzT1~ePWKwbheVYyybA<)x
z{6aot4l*ZeiApya_u})}NZN!{Gqe9bZ*6-j+~bp^xoI2SK&i<k+PM$_tKYIG6_U@L
z^Q=BPdsV2VvBXMDKZ$#%KAnck4nso1zc&7k;`FYSb_c`QvPK)#x9a@|1&SawG^y<N
zk}3MxE!>bgQ{|#ukhqpEPrwf$)0IF#Ux6_?&cFKT%QTIG$H9l`(6iFfk!9R~3eH`h
z4e9*-8@club7RKT;zuNg*-xCFG@YR`z|G&ky4f~e?dr~6>v|Z@=SrFP8S{9JNPG9W
zyfVaMS!&Q!O6nxw;Ix;x|H71!sR5~$UkPX|IYmf(-eqnVW`F&}@6Ro->6Xtk493rX
z8db&uH+{l28}jw=Sg@nKc)E4C$i#q=se$^3P-1Jr@;Q>XPGjv&`ovaN(Q(1hWg)Z`
zs(pNzcxV7LbQFy@q3{>eeoxIxPeBLI={B#(NTHte_XhKy0p?TM&aMqtq~q~BteD(x
z_ri)Uum<n3A})b|g7Ke^+CJ2D%VHgDV-%TwK%e7N_4V1u$&mI3*LH_^Yx*gC{V;@t
zr8VGAZ#i&iGx9cV$LcA(S|Yrhw>*yycuxT5Dc*w1T{PicozJY9>-H=!pI*rDIV-IZ
zw(c8QhRMiipxu#RO^PA;26KB6V{ysrSGiY;^q))0eW$cd8%~kNI^N=}>3U*g-5x|M
ztpUhUZVvuJUF3u&@|LWPTN`z}mS}e$s5T08aH|w7T+h7gZCg}4p2ed#&4nMNU^=v4
zWaPe#L(9_Jn^_YtE~ZI$UEh~!7WlQOGw`Y01N@F^QScRs9c<T>*?B%Nm<PkUZ*#Et
zYyYq~qL(j`2o4Op1&D0M?#5_Jm4Vx<yk|by;#t=ycRYrP;g%&3NSYZv!6E1DQy(oM
zG5Xn;GzHgJr1mD9^9{fnaeipyR(nc&Rr}9_Zt_vu-eVP}rR00OVOeZZbGVn1gO*)u
z*Jp{5wmDkKU>x@&#RAdxzHHC1u=Gq6jS3M6oI+HJ@CPdPa=Qf`oukX((@%|!@pt%K
z$bEe~)U^sv&vw-pZozG-@V(nfIfONA>hy}JPZQ!ayy3Bf2bb{q7QgZGU<?bA;SF5u
z-*1C6iN>$xf;93%d<O4}9c!L@CDX9$7TMUc#rz-1Bmh1qqtD$7BSTydxjGVG-){k9
z9XCEsEc0VcI$~=4q!i5KW1&m@Ab3!~J+HFh`@X@BiS^2@#>oP;2^Q<E)%95+o%T3f
zD74g1Hs#}W?#L^_V(F_B2*`#2GHkoWD|*FaicEX<u{?^m|N0Bn0?#uPo==NBc};ia
z0Z2X(fqT}iO-8%fAQ0{1WoTh0>-DxTGjg-R--tb9x^71K_;LJRnaP;gpX>bLAQ&%Q
z>IBz5A3uKr*hML?Ya<gA6SfWdhK85Gzzkv?c#LttD)SN;8oltXx+nofn@v4SOYM4m
zd1Z7<*#VJ(HpS%ST?c4H1NGqJ%wDi`0rlZy-wIB!HL$@<e6Xzg3QZu-ca}8>ely{E
z^E;hWsZzH&iaR-F(s#pL7>1?zy*cvCD9ZRQ0k!xEo`%n6ngBqU4+wZ!YQ=;olLg)Y
zYy=8!EVM!cqst^fp<B<K{8N>%z^B-+ti)NN{byw|!sWc%6T!BRARxsdp1^PehX*Wx
zm|(+?A4DP|B2aX)-<(B}Ei<#!9~KM&sFk3U`9`%${Csxj057MCw$~X7w((^SU;pMi
zio(LLgrmOgr?Kg6Mn*)WR(_0&v+VlMMRs=c3mI{7jD|NCUIPy~33fAV1eD8~h6Ws9
z(**Q{g@i!Ye7tB46VH{o>g#a#@NZed@t4m((Gb;?)$*`aT?{`k{FW6~<f$^hZZ=Pb
zG6@KjHPaVl{9ysHJ4le{hjms-`bihe20<hEN5T0A+{lDs$HKw@&&3IZ=d2#PA(-6Z
zAa$Ui@h(`%NGK^!8ye0uvUkt=FUR#{Dsxtb7@o$)7SoQu(qnSw6b?B9OU4z2jBp%}
zn0Ej$C8VSh!C{`KG`n}@uL9dsAF0`(jgy*LzWMJ-K=~`;%tAsmqi#F2g!CeTu!6>^
zF2Kv(x<vsLs{s8j=odf+ve~QtZ^8$4<}?6uNE6SWBYinV04a@w7_~VTep^v~mQsA%
zRs!CK-icEAeF24kfl*W#nP-moWq@0v4th{|#upYcd8z@z=Y9Di`RGxg{Zn;y8jFz%
zJTS26g{P=MMt_MHy|6L8rmi&opst6EnB<x_l-^+B90wnH1DGGie*aGTwbD>ukByrA
ztgOC*l^%{R1}K{V4JV=dz`MFy)Wb^gJ}EQiwQFMK_BAdmQDxK+fx5X(I#es2d69Tf
zDFnK2ff){DJuC!#Klq?ip`KR&@+cc*80Yq^_4E0KRh_XGPTrZk{Y9RduC5+bERBNQ
z92BZ|P!0}KfDW$|GnJ?c&ezLldZCfLGtp~%Nm`8v0>532jmEXQ=CB&hYGir&Pu%oD
zt48e(InQzjFDjlJ{fVDEPeke9@jFR_#icMr4vFu{;(qj?b6jBm>qNUjJ7MY3ffu_P
z2x;2AEN#_jb^kT^E>Cy_R5n%9`vdu6A8w{(qi%#UoenO&I1fVginKvy!*-g#E^!2x
zNEbahl_J}(9w&SuO||<^*j1Dw5O`+NPQ!2w&vBXx3McqBPU1u<Jw#YP@kWB9?GMu>
z{79ZYp0=XFOguA0Qcn1d*~H)*f{fL>jKt^l=S^VyW^m%r@{rP=bv?+Q7E+3H)&1+!
zTkz?-2wVvXqny{TFx=h$enPztu1gF3rtOA`1=Cuou0VQ!dIu&kzd!=*=|^o_bKOoN
ztjVOuyZ*jS43xI5b?Z|#l`dl6e4-N>Alu6g!e=$~9!BjC2$79xj4xmQT((IahUn$A
z;n|}wRyyMuLi}go`XZFJ8Kt|9ZK~ff+LUNN#>T)D9q#6<wn@hkru9OH3NfY8pNDNd
z<1NE$e=L+|{C;}>1vV4=E5KW9T(b&#@0m^ApV6GdEHpR$>zhRIO}kZwJO@r~^Xx&Y
zD3}12An{b{a~LVo-Rktb_(nZVf2KEz6&&|h1*rL)6>KVEf<<rI@xsbY2Z*OeUn}D^
zTvUm-(D;*H_1obwqX0;}XU4$AZEJ6WuPHbY2=w~;qVrEoN9gDn`GpR4uT5jT{F}uA
zj2J;&K7I^R=IAnNZfr8gAxJoPbUV_S);CUuqIoQ6AR%^H!-Jjof}0I|Ia}gL^4t!a
zk@1nn*{JB}-v~+GieH~qz}nlZ$x@A8pm$Hh6NGzi?!t3;Wvh9W@YS@P-5taFGl@ww
z1OiM-k5~Jz!4ts3!y>%Zf!Q7a@*uYwlY=8VE)@N296k#<ecd5vdjDX>v=)`psR+G;
z@Roj=zS@}aqUJ5JgwNh`!Ph#N;|4I05x0oOHZ(os;LyIu1F)r(SKNP?1Z(6=5G>xP
z4^lJ$i}@Zdt84IZ`1SF6=QJ>EU%z>yU3*Ht|27-~NXbkIgVCha(E(+4((3q%P@m?p
zT}6<z_PBl;?hn4cbg-^uf_BZAVhjjx!<!Z^JAMTXvr)p9XKiC45x7WR%qmGo-o-q(
za^nSf5}RJeS&-%N!R!7K&NfQ+zGs$=F1wt#w!w;AC#iX|yL&#ej3$HdizO}?z{c8X
zf6X~88>R3p5|b!KhozqxD6>Ol0#weoT^t~331`3a_%Sgg@yDr{E_2WH^&y6I`G!&Z
zyt<3yc^B~v41A2LIA0hpL7oPs4XSb<#se&Z0X=t-#ZeD>7Lqi&SY}MQbOw4?&n!<Q
z9$#zppQNdQzP>^mmY<*9Y==1XA{G{JY;4s3{HX@{EPyr+I$(fK9YWjQP606!Ih8EP
z@Z@*bDJx808gawexnG&$*%hm`XE+;5z;;E+YZ$qinF$3e2#GjAdJGwZzzYhZ7_<!L
z@Aw4<f-yW``w7_HGFT#-#wrMeg20Io1-~PDybHT&?_bJ1Kx$43m$?6=X*Hsjc@X1!
zoX=jobO{T(cCe7T#>Q{Gy}gClR9;WB8z4P&Lei_Zu;x_=R+0+F<gCuB6eiDH!!=2u
zvsef`Xe=JpwTs{gbC2<V@{csL0x{eO%#xk-jlU0O6+*MK*}=5Fl~P_-7Jawl+WreW
zJ3B?Q4ruE027X$1G#+PR?G=Tm^VSVPx&UpV@VR#7bojr=ldmW;T<K}A<laf%!M$3I
z8jsd9XNjqqj^;BU(B~BvN&xxXz6t0Hw5;efmQO7D#&~R6Ii)$y`VPNqf3}1x8aG{J
zd~)tR4lS_wV1*{<;^G=I1_jL5&(8}4FFe*u8Mm=;F;9+fZ3fY)=6-y(U*naM9^iWq
z<I!=iqJ+dLV77d~G!FQT5X{w7pus~;Y8h2_<5LFDa|U7>0w~Id%W)l@Ff_`o9}<#u
z>Tx@DI4u?RqrDxE;zVdcH*j1ooyh~6SS4+!-}xV1=Vm*<^(aCj_5bcoh`fCL8oC>X
zdkg@2zpYgWkQamhAfdwgZwJu7H9>{Ty=VtTmdpD0y?<!!(99e1;X@|RGW2(#O&wrf
zc@3h79!Tg7SJ5{Qe0;3bpfU>$d~%N;dxF7jB0cqEE%Y6}0COX{{lTV;gCwP-FhV0H
zoHekep5;(4@g%t<S<~A~25nO}CI5(HFS#CcKpzd~{`OL4<u7O=t*fusfwMCdUtrwL
z^m}?*7l314e!e*9@Ten%P4)B3KkqyssJ$wl$_M8knu5DWg20&rK6-6Ey~J4Z^XFft
zrCmJ)v<~vxv;3C7#r1Y;j4?P#5Q!u+MxMjQE9|EiarFg4i&ROE1~e}4Hr{*i;05qj
z=`CFN$^X*;gC0NxA>o>z1pc_xd5Z;<*z{k~SP1OJ)vc{wsu|R-qx_@;g2-R?AJH;4
zn+`Bu%SV7CME?m;X#nK7hSpinqYZe0X=!Os8r92e@lfaWPcY$&gNJ1etkb$ZX>wti
zpMC!oTgv0(5wHcmEH4*SVCmK4tY(2Z{RBE7YDNSF9V~=jul>sg@Rxn*;r;tw!NI}p
z#lj7b6XG|<U(@UEu8t=M8TX{U-QNFI?$8N-VYIy;q@B`sJ`jXJ7@vQ{TCp@Yr#i9z
zx8B6l*4tY|)2l2Bt<L^#7+B4J>)(G|goej#Y=JIGAMmkbfpbfQ<2*&}GSf~ACL7Yf
z+3QVeXxwT9GoJ$h`K6s;DAkO>x8tX!28WSE@ui$@4=AY}(9H{WNp0xka9kb304Wmc
zm3Z0>XlMThMGSPB)In21zTJWnYUiFYg<b`yvUNgZ--5^53c4E9E1k(;w{%A-mpBxG
zfawlwFF@%8c#1T|OmdK9k0lNZhe78@Tl^02Wv+p`|CdfE|Hl-ms2I$`wY>s#k+1Kg
zmosP?&seY90g3y+{K54O5OD(di1G>w?ts(<EnnZCG<s~b-9oJwkXTVo7;SI#XUUEP
z3u&R{C>`jjY4WLrI0TfQB_$<KR?yyBu;|7H#KvlnDXLpR#n_WsJZmiNug9@KgrE-d
z{<sIpx1p0Zf3i*Ih!!YUI9=SJw?Q)xD)Pqe{Tm}pv%1CI(Z+@+Pd#8eLzC5QutAK?
z&YlKCa0N8(mp~6*dP`R8!mvv7QxEX*^=B4Yj#e3P6qjX*#xK$ZxX5NGuz=?{t<FFx
z)lTK(4<ATqFrQzcCy3Xi2k08_&GwMhwB{;@0NoC*7m#^jqA+1@Ye1>%1lu3<zKuhk
zs}B;jU!(*_{foDkq$a?-g%<nh=(XJUlKojZe?t5x2K@o5>PrFwpe|EGBfo&50cTJ_
z0nhTU^3+POk0koD<ivpKd7;MzjKt>}qr3O9JW<Mjlbn|JEaC_q_YW&%?X*0osHlv3
zGyd?Li-*wHs|)T>G~&p_@L@pL1w7M5LBVnu)25r*qvWlKs3<?wybSvh^)f@3LlAW4
zY_5z}w@xYjwzGI-kS&VLLUW%C+KtCy7u9Qggki9wQdkV^z7E8r$LR`S411j3lFhM@
zClq%UMgghYJpfgaz|&j{hm7m_Sk03NwWysOx{Kb>TJ8<AXlyw%GZRo;Tnuytxu82F
zwDqosoO6#Bzyt>Yw;|1rx)ykLY)={i+q60^cqa-m1w}*#>pWLmB-fp%MJ9^NYtt3S
z5)vYSUeWFeXcIdxI6B-%j|}GPz23GL7x#k1-3%@Hh23bkEzt1LEvP<W&9X0&!xFr$
z90Pa{dShYp`RTFj3*@rYZ$XWC9gmPOr^7m9VW0Hcr~m;WVYp_cbC^I%S<W4jqaQxt
zCxOPzaI_ysa2gnDOffJ(253kcjFtyakkewdw6)cPbcC7+VxNIM7mT8y8<D%j4GgHn
zuA%aR!o==8ywCz0X%;##1N93!Aw40Rps#;{F8?h5b(SS)djYqQB)El%sj2;8+Qa$!
zV*0f#EI6w6=ULIlK5*yPSxtXA_V@o|qI%ITVEvba>Y=(+m=nD+GvoqT7=w?iC5*W?
z@`8@53}Dvs2B*3%^mjvGXR*pE%|*>WizAg6AhfXAnAvH(4tBqZ;z5(5r-rfcrVp?i
zrq<a#iQ2KSqO>JgM4P+Z-9<o$v_-Y0*_egQG_Y6Tzsco*_k&!w80Le95-R8qHS?Q<
zP8xs6q<WApcOjHNhQtWG(l`j>iYn%Nc7T^J+_I?qDC~k7)BqVKLW4EhWoKVenj?w~
zl-e-EnsK@AuAXa*{JHO<Fz%ezB#_a1P*MiSxdGa6u0waolON6+o&BZPp#OyewS0id
zl9-I_6`-l{R}`A?tnLsmoQ^PRs)45kqAhH%NCrk(?{@PqVn~wHHDYT}g)gOI=UR|l
zyWL$`pT9X919#@dl@%i3DVCPtxf39Ds+8NaPq#+tEpoFi!qq!8EeAheLCXf<=(M2)
zZfc)CoL{xrf);GL*x<E|;A<G}8-4!>dJbT76O&|VR+jbTPj3nk;o)^^T0#%P(=TRz
zKvzwUef6IGRbGt8$`b@rcIn2A!q(X1%mo3q6~jA<<FKhRA$qg1vu|x*mVNZ-WooKn
z{?6LwW>&}UJW96w;df~G;vFXXK0|?#2rb$r&RZF8GkDmb{YMC1!f~a~GzbDIymrD1
z-W4(qv|vuhQLFh8S<Y+!ti<MuVCn4Zzahq8L1Id_XuBq(n!7QN_GCfYQ1UB^p4?}(
zg{C|}BZ|9jcnZOGDqV)&U}}XXb?~re@l<8~XsG3ys+2{yNh{<k$T)ZZ@I64t!J^n6
zE31bBAZ~XQv%%SY*YM%pe`1N$#tnYY%uIsyXLWs@`}QlJh>stGU`K?h<nm`%e?t2h
z!Adv=Z_&v3^Wb}6gzWB?H>6Ge%eiqS=g%n8um1*DHa7HOc$b&Eyo!+PTc{9#=J%WL
z-o1N})jQm$B?q0>cVMv~I%ndK_J=OyW&QAhF1*^IA=vUTK=hSCS90DrS2#Rm2_i6q
zq7Lm#gS{FGB&Z@d%GiNSgx)XUGAt|Bd{Bd(;Bh0p$9d@gQLS*y2OM)B8Zs|}6~=nJ
z7F)jP@h9-t_(L&8Bjot_PcVm`Y?DTzp;2%+>4S;idTEFkTE_z6B>Be1#-cBdI?o<D
z2fm+BaN<00b*(tuoeTzB5(B*P=^ebzBf!@wxB51eVDJWzOOV&PJ{Sfqa6<Ds(4NfD
zr$>r>2JswyJ<7JS6!b|G!!AHy?SQropQE8+1Gmb%u&`te$z07!eej15{WPcy&V1-m
zT3Xsw?co70<@p#R>Y+K~7WMwUysn2qWjp+(v9a-brxg8tGqWr>tu4?(mL&b*CN$HK
zLPsG-e)W9eu|%``8-HIYE`7bdz0uu1V4yJbCvT!njbQcDhh7S3pfpCi*x_WwPN7YQ
zkZ^J;H9qcGs8ZSnqK|`)3am<9@R}=r_rnr<O?Ux{0T9mulf~vgnV?Or5KLKUZ=M1C
z1)zmJ<m&ckoo_fxkx~b+PBGi1P@0B7JdguXTy3j9q8oil4LF-1P+x+x5!SEiBAugI
znGtK*zL487Qt5*22@5~h#?!dvFjnKGs}=Fe4RT3Sp>cQJw{Lf#x=e-^A?M0lMjc|X
zv<W=f;8#^-$*u;lc5XBRmyo7|W3uzO**R7@xof`#y4*mwPS+^^0*CRTH_lmofU(YA
z$pX2eZ$E1#GBU!xMqgiaAKortPu1&08$MHT5qb~NH>;$B0}k~0Cf3{vMi^bUnoQ?G
z=uD*=dG85lB!IGeRwcpzb>qUnEouHwANHMK2<@E`eZ4&A3$JxU?%$P>$hock;(q{|
C%pLdu

literal 0
HcmV?d00001

diff --git a/output_9_0.png b/output_9_0.png
new file mode 100644
index 0000000000000000000000000000000000000000..48ff6dbba914b968e2292b845feac5f9b8d4e601
GIT binary patch
literal 6597
zcmdT}XIN8N-oNOMj0F$@K`C)Sl#YOO2#RRHh6)Iwh!6ph66rOB84ICCML?wqND~PX
zTIf0gks2vd189&A0i@ULxjXaD&hE}T^St|hnB5O~^5j0}-gE9b|NpNg^wLEX$F76B
zAPC|x(AT>HLEEGth%NEk9pH)<zu6G@QujP<=4phr_w=!Gw}UR&c;0r#dOADW9`d$x
z_i)6zD#@wJDastW>FIgfLqlHP<(C0+Sa%0`NvmNzc*xG%`e+Xb;<AB1Y*{*)ju3P}
z(LnE{v2Vh3Ki=77vH#7S;cBbsoohk8oRVQWqJ0quPZnx)C)|CuLLItpAMSb}>bYwz
z;ekYADCLF$$H7EJ{3pey3L4+GxU@D&exECc4kb11bbbAx8J#8j?0scKb8PGUh7E<L
z@#d{q$#UOUfAOO|n@R2OLPVNyGfVWoFquX&1nGZx;LZg>w~y<71L?<JVuK!u8$-c2
zcJe`o(EoUeLwXrPm}0S5PfyR9vDUP-)YMcu*dXemMsjxv*82Rj<C6FHsIN^P*^V^U
z(9lRFkw|n51hKfLr>7PCzJ5t#B4$$*{TIdvE3@+ER#sLcj!-b>vIH+Yaz!iXIJl2<
zlag6hW}XGTf#wHY`)(`ALJwq8wn2x_WkFE=J}Kw~`R=Yi<I=03-7x{o(xXyRQnvMv
z#A}PVkSm7{3JPL2R^}9Lb!0u!!3TMIc`bJ7Lnjz(;>Onkri;uf{k;<KTdTNEZ25Gt
z@7C%lW^-+^wXJQRu&}TKcA#QQU?(I1ofVP7v(^WP)+Y0ah>cI|3f@!Q41Z)Y5wSHJ
z;>Oxsrt(+K-g|<?`M*LJ90^+Q8>|~?jz6cpA36p-)-nc*7@Ek*i&FO(SwLf*oWi%W
zb1tBhRb0%^KUEYrx3KtW<R0na`Yw`{phdBBXct)BYg}St;$<}Y0H!Wtyx^LV5fAu{
z(suCi@$vNW;YaZAy2qm;4?T!|RGHc~Fd$Mg;P0fhxzMg)TSMUS9vB%Jc|Yu4n@b`w
z?<NXD`seC(({poWm!^7n_^muI?-5jyxz8cEUshIj?!zgr+SfMkQZq7+`1||Y&J0xI
zsz^CG(zl$Pi2ef^85!?K=WBB-D=Urh-$2is&Mu`TOXpQ67Q6QMI!xaebR{^pXVeP&
z(7C<5yc7agX1ghFn5JYM9Z^xRQQX+-P4AAbF2rJmiHXT&@Ohcf7JT=yjPV(wi128l
z&$Z+t!$1a)LeRzvW9`R#yD{T!=?boNN*0L}W#L*XJ~25t)OJo@_M;i7xhrk)j;wfg
z5#K}i_Z-+aKT0DqnarCvZxT=<elHTl*r1)+@5wUK%X<;1luHClIsVl^<jb6#Mr}^$
z_MWK4)xMdv-|3*=XsZ9lOP#L)Vo;|(y(J889APB-h$2_(3FrdR`<$}N#?a#jmu#;4
zGD`^-*vRgpNml0(!zka`w*<fW233AYd>EzkVy1Ldv}z%}>ft`_{D9?<Nt(84QYj>%
zo}$~!DY7ve^H@eRa4@Av{2Wq?Gx#Jb>p}70#>lMcl`X5-(}g8?Um@sD)TQrSW-2^v
ziQBKA;FfwZ9i6O|Ph~sy{9C>@6{pUS8D@5t+SjeHFhW@w7Z~#ajBy$Jz%}@Tkelx-
zA^(lanN=;m;FD*w9#r|wizeYz7=`U?B*UbQ&t<gBYyyRWp9HtRtMKDy&Fdha?*DXH
z%veC}K4;|0#%QDVH_+yLV$iQa@~Xk9^wLswxvCY0fVRJ9g8xLeTeEUkO_Z?an$Y}P
zc7z@VgNZ=sAkRb|<b$gU0N$0TZ=gMU#W`YPV`FbRJ4ZCft5QM7Fy4H>UBQP*@2<w<
z=brSrmdhpq1Tm`)!W9-4>Y-4mrg?88=#Z!sc}l-Jw)pq}Zn<A=vBM}WJzd<MmLv=c
z^2o&m0h-qQ`M~jW)?oy~bYBTI6S<gu)5Rt7oP6a%byC442|c;E@IWNu<HwKbThb78
z^i4hzzdWfe1#TA=t&0@o=jL{CadG?f=KCi~4j1R1z%BS#(kQj4s7MF39opA{O-^g;
z>k~W|D-+r%U#-=mIa5I(j7?2NG&D2_DA}J+#yH)&m0D0RPZ%9%GNV8nF@|(gE|H(I
z1%I6=F@;eJ(^u@0?>*g1^h){_n*8O$x6q3WYhAlJM(x~>yX9;0f);b0X!*IjRTdYk
z{11Rc%}h*$_4f9PCFNviOMYDqbaTRD<%h?h69;0B8<S<iYs2}ehWNGi?m|bS^NAWo
zw5{>>OzQ0CcbK8N$l4-dP4AjMY_;&>;v!1R0icGlsp)bL6#O>(#d6kh6_q+Anih`^
zYn6ss7;CLvzvy0Snc&_a`LJ==_VbVT@;%4f1XNuu!A(@z68b*y6zW100=j-%db}@M
zT1qO4Qf1%#%<T2`lX`(G-(wqNWy2Ay6>4jLzc2>}$J~1{qR=8rhgIJf&365hdgtg&
z(56t#mAz8XvDw3`>Og`}PyNY!_a8yJf4qoC-^PR>g49~nh9U$MZ1pVN>&52)8O8=2
zh7PgWam9E|cGk9~pTpFK@#Wh!#!^20usby+<vT!AM$A?ySW!A4i;ib)=HF~hrF_0G
z$Y@XA^3+=D#wfUddGE^zJ=&ms5V~Y<#}Sj1lynntD<E0kE|?oUMw&u9J3GaKE&#&h
z-E|Ks2pv<4Q8pe3n5k6roxR@C(XoKe%gzpMX=wq2JUl$UxR)}nnwoYY(zZc%mzEHl
zLV3U9J~|*5am7~&_?5dmd2Gi%q_l$Gbg2B9CRdbyBDar-AvVbFYNx5Ol(aNvZDBm$
zZK#f64n&zVouUA!tWoU%^xy|_RVsj1P^2qsUDYB=_DzJRN)C0)Rm+tytk7@2;}{m<
zfFugYAq{cW8^gZK{XRpaa%LD<D`ob_-9zw28`bV@(9vXACAxFXxq(*%eE*O(npRd;
z_BYx0$t<~=on8)rFgoP-bmM;`#r>`j{<mK!=CJXA|75Ni<+crgB;||h!;jS_UlrJb
z;%seiZy%+o4)}@z+~5;C69I^;%&gSiPO^>-+L2|Gt~S0j-IrEUqIxy&ny^DM&fB@K
zSa!dxIq&-N3~`-VE-xy&>z-~?qNeId(^DRz_L7-%f0=UCTqL&Ui2{aECy14)g%ys`
zLpyXQ0{@|Mc|eeeT)Vk3ERPQ*5Ksu*ac0GQ%g+c-AedDJ`fW@(=!66MK+OB?zNZW7
z7YMb>K({~YVGHJ&1joNVEfND*1R$z3(iPB4Pk{r!n7An1VX!otsb+0mrnLjmyQiB%
z+X3ylxVcYC(}x*hl5@58f@;69<s=}CXV0D?slxvBo*usr4`o$Vlw6#&E0B8W2M$6K
z<wLt-h8yEhr%%_STv@A_`2KPqs)?x;ACRyvGUkP27%qB82k&ZN6{V=81V81m4RX{V
z#XH8yTI}DwUuNY!rbTPMiNRuyjS-|t6j8bIDYEaz9CcmD)WSj#ybG?AQ=62Vt39!r
z^YUft%a;?rbvwX@gK0x~j@H$L@({<n;W_zCExFq>4T;K5oiz`>!&z5k=j9Or=_zpv
zsqK9i!bKzyI0RK{N=K6fG1MsSq<kp&<jcd$SyKa*nn=JSRKT8$s&!_#&mc}!LsN5|
z9^l^Z)pgp=&Q8XXa%>=QzS*qA)k<sS(;c{RuSEO>+H*pDRVW62YD=OfX0#;{Hc`lR
z&PqXzxW-z*x<ZkWkqWrAg(t^sbm?AQR>)J|KoS!rw9Arw$pB=w8@j_^w=4b}$MnbG
z{hzh2oG&SDpj7#<`Pvv88`n(cRS!4}3Suj`3+$W2xW&%sfogeWSxW8zo_D)`{i)%l
zJ}l87`iOAxH3?o@CcV^cZ9EfYVPQcB6yOFRl{!S!xi;|-3TCr4lQi67gv-~#ho-Yy
zZ^)?Sx1K7P8P80P0>lCnO)8nJh@5{)gXa}l9t0@uI~18Nv>OsQbapB1tf{FfsCJ1Y
zpezN{-M`qZgLyE3#ejiBTRH)Q0t=e;nQDB;ytj`JFehULY|tGe16}b(GAu*rpuQA<
z(-RYE@98<9tgH;zJ#%VGYoathK3*)Yk*@>*4v(rD^x*NYTduDJON6_%3b&q`ojrc{
z*WH#ptFs-_f9KYpMt1IjXL*Yf@fdmPP?vEb9tcI{moHzgO~or<&RF6%7w5i28=e7@
z686YF_%SyZm+8wiYZDW%Za=o*x8oFDJ4Q{Yf*YfT<xfAwrOi9I$@B>)YJwO6fJtYr
z1%I5SyMdk_aC+24pMeAHoI-@p??O;|HLzx;d(a~DF;o#6K)6FDk9;<P^G&A>T~0f5
zTCWD}kjNK()G&%bm?V|URm~^P)Bqbe6s5@|xbzj*-r+(DaB0n+kUX;u+VT8RmG){H
zKsw*m;kdN?e1#0dWD%Yt=LzM^vPO$&w&2v?=fh1B;$L!;f157;e>c8s(0)UWu|w<W
z0qRyX+y)8doTBxGBvFa>Z$cWtd5Vg{xl2<t5SvbeRX8ARqspp9*Rhh(l!1YPF#wpY
zX(#}^r%S1;cuC$}mrYIiL6QR#0MqTFKMAE_8SY8hKQ18CCHjvEP@=^4ExwrVPTjBh
zQXk!@UAGh5qy3!K%AxZ2oAz`u(yke(*EARY66rh&1{GtLZ+qI<#3Uww_s2#3P^X8S
zU82HA`-%i+Rok~gcj8QcE1cQ~>*_!3Tdh-^?%2x3t1#SVTueNenc#jl!K)LU5BPU%
ze0<y^VX{?6BxvO`(2`0Z<luIz7musS$*VGFKHO0W913NH5f0k{w~6e`I^`})9!>A5
zF^?v8MBrW+h(W+0pnS_1P9{JrH5{L-A4&>fhK7ZOnUQZ8xJ}<E-LEUoT{0LH0Ftut
z*NeI-dp$;5BHImhw1JUf0O1%}K2xPBg5Q`^Jg-i18LZOw4+y|4PJEmjiO1G$=hE5>
z(|RDtf8<1l{1=G7t8I4_{a<}$ylP&A5m!)N<&ycUYn2);I;;)k<k9A$_Y&pS8w~!Q
zLdSNp>R_N!IALnJnuT*46eDUqiWJsVnPf8MNd0b9;U2(#7WWMdk<zB5Ca}fkfm2|a
zKziDP{i&t0bBQz^x$x{U;P^PVm(jE&?Eo_2y}7wL8EDMPfMt6?qqNREYiq3$;M|P%
zbEBP{oJ#A2I)L(tOY~?_?*Y9|rs0?#J-H<V&+K~Yy<{s=uh@fvg!Q{GI2PM4?;nOt
zV}Ft&D8Q|5xqsIpLHH>DD-EObaQef*bfql-Gnoo9D<GJRECm&B=r=u8Ituc#Mzx;$
zqscUs9xqD}*8FguR;tpTaUopND1)LR-qzhMU}}x?N}lnn0ZX`h_JAE478`_kY?Zow
z(-XHE3?TS4Ans|sDO8ZEi6_t9C<bS3R&>jR?%95!RvAqGvr+iOT}`W^Ze{{y7b}C_
z7iS&hm*6wt$36GCdhQo1Z57{UR_^TrP*(g|d^}g5kD}G?lq=gB<K&5;yomH-?4U@_
z)!Z=L`qF75BcoE3NJrG7|3>*giKVRb(Wh2nb6f1vXFJ_nG%PawqT`>UJ$ItfRTw(1
z7ycHeFTNh^ItFNjvb8oj1U4xGRPH+_1GzvcE?&CZqHQKTxv2IcElrF>VT4hp$c>!k
z2Azu%l{<Nk)O<)eMO?uxX)_Vw{PIztUBA2LHyraX&VDPo!pVaHa)w$^AB@y+IVqB`
zmhUlm?8?@1H3B3UZS@|q4Y=s0`Y9}a-J%%u0b>b7cy`<mwb!Q#&;bDfv34w<d3!@c
z!?{TyFX<I%(Q@zUh8FeFgeht3)w4@^_|3`Jn<NzLiMoe<vF{v%F?5HW%RV#F`&qo>
zxmVyYoSdEiR;-(=G(6Iol_IE?j9cnq^nzMsALd9HzAC}HrlkXGY?$GeKIR1}_mz1~
z8o>3Sy9L{>B~mh6)PQSyx~i6nfL?d$=`C_9cqoRl&oRxD8+?AJgJe}sE}$Vb%fB{A
z7g&{h+s#zWUv$%~SsX(+b&;9@9+DB8W2hcDJeUF+zNs$aK(v>)cWgl6$?5pP4g1)}
zVX`%AtqZrc$r?hiBt$&sn^hf*GS1hlxb!{-99rE7Tw%f5+M41;+}D+5pUoRRVE4cp
zqj;szv3B^CcL*{qXsG}V45oLlW2W6Q-NVpthtQYKSLo=|HQXimQP9Ic0@%S11+KFI
z?&o+_tlYBxoq^V^%{+8LhHn!bl}uR-u3c3D!rvKmVGn=xN-a{saD2ldD?z3!6;Q;h
sLHxj9Ku%gQ$^Hj_HT-YP$J#y2zBjI0NoWE5r2-k8zNkmiz5c^r0pn=hc>n+a

literal 0
HcmV?d00001