{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 10 - a - Neptune - Feasibility Charts - Lift"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle\n",
    "\n",
    "import numpy as np\n",
    "from scipy import interpolate\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams\n",
    "from matplotlib.patches import Polygon\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a planet object for Titan\n",
    "planet=Planet(\"NEPTUNE\")\n",
    "planet.h_skip = 1000e3\n",
    "planet.h_trap = 50e3\n",
    "\n",
    "# Load an nominal atmospheric profile with height, temp, pressure, density data\n",
    "planet.loadAtmosphereModel('../atmdata/Neptune/neptune-gram-avg.dat', 0 , 7 , 6, 5, heightInKmFlag=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs('../data/jsr-paper/neptune/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "vinf_kms_array = np.linspace( 0.0,   30.0,  11)\n",
    "LD_array       = np.linspace( 0.0,    1.0 , 11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "runID = 'neptune-lift-'\n",
    "\n",
    "num_total      = len(vinf_kms_array)*len(LD_array)\n",
    "count = 1\n",
    "\n",
    "v0_kms_array    = np.zeros(len(vinf_kms_array))\n",
    "v0_kms_array[:] = np.sqrt(1.0*(vinf_kms_array[:]*1E3)**2.0 +\\\n",
    "                          2*np.ones(len(vinf_kms_array))*\\\n",
    "                          planet.GM/(planet.RP+1000.0*1.0E3))/1.0E3\n",
    "\n",
    "overShootLimit_array  = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "underShootLimit_array = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "exitflag_os_array     = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "exitflag_us_array     = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "TCW_array             = np.zeros((len(v0_kms_array),len(LD_array)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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      "Run #85 of 121: Arrival V_infty: 21.0 km/s, L/D:0.7000000000000001 OSL: -12.899161425015336 USL: -15.648020731576253, TCW: 2.7488593065609166 EFOS: 1.0 EFUS: 1.0\n",
      "Run #86 of 121: Arrival V_infty: 21.0 km/s, L/D:0.8 OSL: -12.843844909708423 USL: -16.086056021609693, TCW: 3.2422111119012698 EFOS: 1.0 EFUS: 1.0\n",
      "Run #87 of 121: Arrival V_infty: 21.0 km/s, L/D:0.9 OSL: -12.794013310864102 USL: -16.55660003745288, TCW: 3.762586726588779 EFOS: 1.0 EFUS: 1.0\n",
      "Run #88 of 121: Arrival V_infty: 21.0 km/s, L/D:1.0 OSL: -12.749012655986007 USL: -17.05963997163417, TCW: 4.310627315648162 EFOS: 1.0 EFUS: 1.0\n",
      "Run #89 of 121: Arrival V_infty: 24.0 km/s, L/D:0.0 OSL: -13.842044990349677 USL: -13.842044990349677, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #90 of 121: Arrival V_infty: 24.0 km/s, L/D:0.1 OSL: -13.660688850450242 USL: -14.063170481473207, TCW: 0.4024816310229653 EFOS: 1.0 EFUS: 1.0\n",
      "Run #91 of 121: Arrival V_infty: 24.0 km/s, L/D:0.2 OSL: -13.511397249985748 USL: -14.330554556217976, TCW: 0.8191573062322277 EFOS: 1.0 EFUS: 1.0\n",
      "Run #92 of 121: Arrival V_infty: 24.0 km/s, L/D:0.30000000000000004 OSL: -13.388332059126697 USL: -14.64895725741735, TCW: 1.2606251982906542 EFOS: 1.0 EFUS: 1.0\n",
      "Run #93 of 121: Arrival V_infty: 24.0 km/s, L/D:0.4 OSL: -13.28650095163539 USL: -15.02103599833572, TCW: 1.73453504670033 EFOS: 1.0 EFUS: 1.0\n",
      "Run #94 of 121: Arrival V_infty: 24.0 km/s, L/D:0.5 OSL: -13.200815481057361 USL: -15.446956083687837, TCW: 2.2461406026304758 EFOS: 1.0 EFUS: 1.0\n",
      "Run #95 of 121: Arrival V_infty: 24.0 km/s, L/D:0.6000000000000001 OSL: -13.127375179246883 USL: -15.923346782466979, TCW: 2.795971603220096 EFOS: 1.0 EFUS: 1.0\n",
      "Run #96 of 121: Arrival V_infty: 24.0 km/s, L/D:0.7000000000000001 OSL: -13.063287791275798 USL: -16.450286682473234, TCW: 3.386998891197436 EFOS: 1.0 EFUS: 1.0\n",
      "Run #97 of 121: Arrival V_infty: 24.0 km/s, L/D:0.8 OSL: -13.006804086395277 USL: -17.02532699241783, TCW: 4.018522906022554 EFOS: 1.0 EFUS: 1.0\n",
      "Run #98 of 121: Arrival V_infty: 24.0 km/s, L/D:0.9 OSL: -12.956187751507969 USL: -17.645112334652367, TCW: 4.688924583144399 EFOS: 1.0 EFUS: 1.0\n",
      "Run #99 of 121: Arrival V_infty: 24.0 km/s, L/D:1.0 OSL: -12.91045819127612 USL: -18.306307808248675, TCW: 5.395849616972555 EFOS: 1.0 EFUS: 1.0\n",
      "Run #100 of 121: Arrival V_infty: 27.0 km/s, L/D:0.0 OSL: -14.03512689389754 USL: -14.03512689389754, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #101 of 121: Arrival V_infty: 27.0 km/s, L/D:0.1 OSL: -13.829980885398982 USL: -14.293864091276191, TCW: 0.46388320587720955 EFOS: 1.0 EFUS: 1.0\n",
      "Run #102 of 121: Arrival V_infty: 27.0 km/s, L/D:0.2 OSL: -13.667218842747388 USL: -14.615816427180107, TCW: 0.9485975844327186 EFOS: 1.0 EFUS: 1.0\n",
      "Run #103 of 121: Arrival V_infty: 27.0 km/s, L/D:0.30000000000000004 OSL: -13.535784719653748 USL: -15.007816391374945, TCW: 1.4720316717211972 EFOS: 1.0 EFUS: 1.0\n",
      "Run #104 of 121: Arrival V_infty: 27.0 km/s, L/D:0.4 OSL: -13.429135452373885 USL: -15.468544454779476, TCW: 2.0394090024055913 EFOS: 1.0 EFUS: 1.0\n",
      "Run #105 of 121: Arrival V_infty: 27.0 km/s, L/D:0.5 OSL: -13.340746507765289 USL: -16.0003409244091, TCW: 2.659594416643813 EFOS: 1.0 EFUS: 1.0\n",
      "Run #106 of 121: Arrival V_infty: 27.0 km/s, L/D:0.6000000000000001 OSL: -13.26567645727846 USL: -16.6015295376601, TCW: 3.3358530803816393 EFOS: 1.0 EFUS: 1.0\n",
      "Run #107 of 121: Arrival V_infty: 27.0 km/s, L/D:0.7000000000000001 OSL: -13.200512942945352 USL: -17.268133343823138, TCW: 4.067620400877786 EFOS: 1.0 EFUS: 1.0\n",
      "Run #108 of 121: Arrival V_infty: 27.0 km/s, L/D:0.8 OSL: -13.143094837727404 USL: -17.995172108931, TCW: 4.852077271203598 EFOS: 1.0 EFUS: 1.0\n",
      "Run #109 of 121: Arrival V_infty: 27.0 km/s, L/D:0.9 OSL: -13.092048304395576 USL: -18.77685321253739, TCW: 5.684804908141814 EFOS: 1.0 EFUS: 1.0\n",
      "Run #110 of 121: Arrival V_infty: 27.0 km/s, L/D:1.0 OSL: -13.045718595341896 USL: -19.608076966527733, TCW: 6.562358371185837 EFOS: 1.0 EFUS: 1.0\n",
      "Run #111 of 121: Arrival V_infty: 30.0 km/s, L/D:0.0 OSL: -14.196883029504534 USL: -14.196883029504534, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run #112 of 121: Arrival V_infty: 30.0 km/s, L/D:0.1 OSL: -13.969076040597429 USL: -14.493690488441644, TCW: 0.5246144478442147 EFOS: 1.0 EFUS: 1.0\n",
      "Run #113 of 121: Arrival V_infty: 30.0 km/s, L/D:0.2 OSL: -13.794088742695749 USL: -14.87319548989035, TCW: 1.0791067471946008 EFOS: 1.0 EFUS: 1.0\n",
      "Run #114 of 121: Arrival V_infty: 30.0 km/s, L/D:0.30000000000000004 OSL: -13.656709264618257 USL: -15.338537567215099, TCW: 1.6818283025968412 EFOS: 1.0 EFUS: 1.0\n",
      "Run #115 of 121: Arrival V_infty: 30.0 km/s, L/D:0.4 OSL: -13.5464152314089 USL: -15.896243807394058, TCW: 2.349828575985157 EFOS: 1.0 EFUS: 1.0\n",
      "Run #116 of 121: Arrival V_infty: 30.0 km/s, L/D:0.5 OSL: -13.45608961196558 USL: -16.545714041629253, TCW: 3.0896244296636723 EFOS: 1.0 EFUS: 1.0\n",
      "Run #117 of 121: Arrival V_infty: 30.0 km/s, L/D:0.6000000000000001 OSL: -13.379855483759457 USL: -17.28186355057187, TCW: 3.9020080668124137 EFOS: 1.0 EFUS: 1.0\n",
      "Run #118 of 121: Arrival V_infty: 30.0 km/s, L/D:0.7000000000000001 OSL: -13.313954329660191 USL: -18.09793901066587, TCW: 4.783984681005677 EFOS: 1.0 EFUS: 1.0\n",
      "Run #119 of 121: Arrival V_infty: 30.0 km/s, L/D:0.8 OSL: -13.255874470098206 USL: -18.98566452389059, TCW: 5.729790053792385 EFOS: 1.0 EFUS: 1.0\n",
      "Run #120 of 121: Arrival V_infty: 30.0 km/s, L/D:0.9 OSL: -13.20426223172035 USL: -19.936720690271613, TCW: 6.732458458551264 EFOS: 1.0 EFUS: 1.0\n",
      "Run #121 of 121: Arrival V_infty: 30.0 km/s, L/D:1.0 OSL: -13.157532973913476 USL: -20.942349761608057, TCW: 7.784816787694581 EFOS: 1.0 EFUS: 1.0\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(LD_array)):\n",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,-4.5,0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "        overShootLimit_array[i,j],  exitflag_os_array[i,j]  = vehicle.findOverShootLimit (2400.0, 1.0, -80.0, -4.0, 1E-10, 400000.0)\n",
    "        underShootLimit_array[i,j], exitflag_us_array[i,j] =  vehicle.findUnderShootLimit(2400.0, 1.0, -80.0, -4.0, 1E-10, 400000.0)\n",
    "\n",
    "        TCW_array[i,j] = overShootLimit_array[i,j] - underShootLimit_array[i,j]\n",
    "\n",
    "        print(\"Run #\"+str(count)+\" of \"+ str(num_total)+\": Arrival V_infty: \"+str(vinf_kms_array[i])+\" km/s\"+\", L/D:\"+str(LD_array[j]) + \" OSL: \"+str(overShootLimit_array[i,j])+\" USL: \"+str(underShootLimit_array[i,j])+\", TCW: \"+str(TCW_array[i,j])+\" EFOS: \"+str(exitflag_os_array[i,j])+ \" EFUS: \"+str(exitflag_us_array[i,j]))\n",
    "        count = count +1\n",
    "\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'vinf_kms_array.txt',vinf_kms_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'v0_kms_array.txt',v0_kms_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'LD_array.txt',LD_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'overShootLimit_array.txt',overShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'exitflag_os_array.txt',exitflag_os_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'undershootLimit_array.txt',underShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'exitflag_us_array.txt',exitflag_us_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'TCW_array.txt',TCW_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 0.0 km/s, L/D: 0.0 G_MAX: 0.47871559417992887 QDOT_MAX: 246.8325066595104 J_MAX: 52072.9323702999 STAG. PRES: 0.00928472517456087\n",
      "V_infty: 0.0 km/s, L/D: 0.1 G_MAX: 0.4871895196029437 QDOT_MAX: 248.24601463676103 J_MAX: 52329.109988743236 STAG. PRES: 0.009166705828225478\n",
      "V_infty: 0.0 km/s, L/D: 0.2 G_MAX: 0.5004171098215326 QDOT_MAX: 249.63898031754633 J_MAX: 52594.59946903137 STAG. PRES: 0.00905238663517709\n",
      "V_infty: 0.0 km/s, L/D: 0.30000000000000004 G_MAX: 0.5188969606485972 QDOT_MAX: 251.08909158349442 J_MAX: 52863.38553341251 STAG. PRES: 0.00894051221680685\n",
      "V_infty: 0.0 km/s, L/D: 0.4 G_MAX: 0.5421983293519989 QDOT_MAX: 252.56443852243828 J_MAX: 53127.53490765327 STAG. PRES: 0.008828197096459878\n",
      "V_infty: 0.0 km/s, L/D: 0.5 G_MAX: 0.5697442643816761 QDOT_MAX: 253.96988510635694 J_MAX: 53399.089179168026 STAG. PRES: 0.008717643336415684\n",
      "V_infty: 0.0 km/s, L/D: 0.6000000000000001 G_MAX: 0.6019838367390808 QDOT_MAX: 255.46637627815892 J_MAX: 53666.16464963904 STAG. PRES: 0.008607320006729504\n",
      "V_infty: 0.0 km/s, L/D: 0.7000000000000001 G_MAX: 0.6381625035273355 QDOT_MAX: 256.95095025873553 J_MAX: 53938.576146710955 STAG. PRES: 0.008499532998534017\n",
      "V_infty: 0.0 km/s, L/D: 0.8 G_MAX: 0.6780657019116583 QDOT_MAX: 258.4447257851316 J_MAX: 54210.09875694123 STAG. PRES: 0.00839195221810565\n",
      "V_infty: 0.0 km/s, L/D: 0.9 G_MAX: 0.7213374353837376 QDOT_MAX: 259.93017211627904 J_MAX: 54480.3787276924 STAG. PRES: 0.008285388977763488\n",
      "V_infty: 0.0 km/s, L/D: 1.0 G_MAX: 0.7682100996825573 QDOT_MAX: 261.4874643592906 J_MAX: 54759.697530381294 STAG. PRES: 0.008182462821872143\n",
      "V_infty: 3.0 km/s, L/D: 0.0 G_MAX: 0.6245574557899737 QDOT_MAX: 282.14304151080853 J_MAX: 58813.10372680668 STAG. PRES: 0.012113023337180517\n",
      "V_infty: 3.0 km/s, L/D: 0.1 G_MAX: 0.637604589963351 QDOT_MAX: 284.17409679146874 J_MAX: 59195.802152155804 STAG. PRES: 0.011920835359139799\n",
      "V_infty: 3.0 km/s, L/D: 0.2 G_MAX: 0.6574069080513625 QDOT_MAX: 286.24802897035033 J_MAX: 59584.62878306936 STAG. PRES: 0.011733011390986718\n",
      "V_infty: 3.0 km/s, L/D: 0.30000000000000004 G_MAX: 0.6838940306655849 QDOT_MAX: 288.34584308846223 J_MAX: 59973.116293241896 STAG. PRES: 0.011546342634051765\n",
      "V_infty: 3.0 km/s, L/D: 0.4 G_MAX: 0.7167648473986982 QDOT_MAX: 290.43506810804655 J_MAX: 60364.069595909605 STAG. PRES: 0.011360614690972186\n",
      "V_infty: 3.0 km/s, L/D: 0.5 G_MAX: 0.755964719701413 QDOT_MAX: 292.5463443137264 J_MAX: 60759.597829058046 STAG. PRES: 0.011179376067981743\n",
      "V_infty: 3.0 km/s, L/D: 0.6000000000000001 G_MAX: 0.8010881971393146 QDOT_MAX: 294.66640983811806 J_MAX: 61154.577114205065 STAG. PRES: 0.01099671495289936\n",
      "V_infty: 3.0 km/s, L/D: 0.7000000000000001 G_MAX: 0.8519279134636645 QDOT_MAX: 296.8132060022469 J_MAX: 61551.98367843734 STAG. PRES: 0.010814607334096778\n",
      "V_infty: 3.0 km/s, L/D: 0.8 G_MAX: 0.9081530734052529 QDOT_MAX: 298.9864704597454 J_MAX: 61946.863116432614 STAG. PRES: 0.010633851350641136\n",
      "V_infty: 3.0 km/s, L/D: 0.9 G_MAX: 0.9689663889547996 QDOT_MAX: 301.1099765572125 J_MAX: 62355.40465127094 STAG. PRES: 0.010458967505444462\n",
      "V_infty: 3.0 km/s, L/D: 1.0 G_MAX: 1.0345524299862494 QDOT_MAX: 303.26394265410596 J_MAX: 62749.106118955744 STAG. PRES: 0.010281988695609425\n",
      "V_infty: 6.0 km/s, L/D: 0.0 G_MAX: 1.0620884986308312 QDOT_MAX: 373.8037469962948 J_MAX: 75787.82198343273 STAG. PRES: 0.02059739107960851\n",
      "V_infty: 6.0 km/s, L/D: 0.1 G_MAX: 1.0958561692299345 QDOT_MAX: 378.3048191488036 J_MAX: 76601.57579148708 STAG. PRES: 0.020059519217791467\n",
      "V_infty: 6.0 km/s, L/D: 0.2 G_MAX: 1.1417511559877425 QDOT_MAX: 382.86995736840834 J_MAX: 77420.08767032408 STAG. PRES: 0.019534069569764778\n",
      "V_infty: 6.0 km/s, L/D: 0.30000000000000004 G_MAX: 1.1998236510740257 QDOT_MAX: 387.4569775536947 J_MAX: 78253.1011435564 STAG. PRES: 0.019025144619702252\n",
      "V_infty: 6.0 km/s, L/D: 0.4 G_MAX: 1.2703152775409716 QDOT_MAX: 392.07219104265096 J_MAX: 79085.86532565 STAG. PRES: 0.018524319557613134\n",
      "V_infty: 6.0 km/s, L/D: 0.5 G_MAX: 1.3531423894713026 QDOT_MAX: 396.718035834868 J_MAX: 79921.58408491754 STAG. PRES: 0.018034765735226176\n",
      "V_infty: 6.0 km/s, L/D: 0.6000000000000001 G_MAX: 1.4478925747055083 QDOT_MAX: 401.3684191941307 J_MAX: 80774.1674643795 STAG. PRES: 0.017562078974601873\n",
      "V_infty: 6.0 km/s, L/D: 0.7000000000000001 G_MAX: 1.554300531973695 QDOT_MAX: 406.0140538835244 J_MAX: 81626.61459429305 STAG. PRES: 0.017099845655690393\n",
      "V_infty: 6.0 km/s, L/D: 0.8 G_MAX: 1.672848562690645 QDOT_MAX: 410.7573596937624 J_MAX: 82479.93615682157 STAG. PRES: 0.016649021169742824\n",
      "V_infty: 6.0 km/s, L/D: 0.9 G_MAX: 1.8022673292699531 QDOT_MAX: 415.4775986208275 J_MAX: 83337.19076588505 STAG. PRES: 0.016210801410488494\n",
      "V_infty: 6.0 km/s, L/D: 1.0 G_MAX: 1.9431642889866498 QDOT_MAX: 420.2645482735575 J_MAX: 84209.66249157111 STAG. PRES: 0.01578741193339843\n",
      "V_infty: 9.0 km/s, L/D: 0.0 G_MAX: 1.8128728790395785 QDOT_MAX: 513.4121320029931 J_MAX: 99433.2746423425 STAG. PRES: 0.035154303828134545\n",
      "V_infty: 9.0 km/s, L/D: 0.1 G_MAX: 1.9010526736999616 QDOT_MAX: 523.2877458596511 J_MAX: 101143.80417401232 STAG. PRES: 0.033681628197202\n",
      "V_infty: 9.0 km/s, L/D: 0.2 G_MAX: 2.01224789651522 QDOT_MAX: 533.3274054931317 J_MAX: 102885.02688159519 STAG. PRES: 0.032273101575213944\n",
      "V_infty: 9.0 km/s, L/D: 0.30000000000000004 G_MAX: 2.148174048162481 QDOT_MAX: 543.5138504243904 J_MAX: 104645.51508676168 STAG. PRES: 0.030913859967534027\n",
      "V_infty: 9.0 km/s, L/D: 0.4 G_MAX: 2.3097439900217465 QDOT_MAX: 553.7621518813072 J_MAX: 106428.14178864246 STAG. PRES: 0.02959749794727878\n",
      "V_infty: 9.0 km/s, L/D: 0.5 G_MAX: 2.497881959665464 QDOT_MAX: 564.0934911005671 J_MAX: 108228.69095541674 STAG. PRES: 0.028330551369066464\n",
      "V_infty: 9.0 km/s, L/D: 0.6000000000000001 G_MAX: 2.7136516107948805 QDOT_MAX: 574.5626973618512 J_MAX: 110042.14457471207 STAG. PRES: 0.027126923717495872\n",
      "V_infty: 9.0 km/s, L/D: 0.7000000000000001 G_MAX: 2.9563646733858944 QDOT_MAX: 585.1283383311818 J_MAX: 111867.54834667564 STAG. PRES: 0.02599524177640001\n",
      "V_infty: 9.0 km/s, L/D: 0.8 G_MAX: 3.2260547170085694 QDOT_MAX: 595.7001761590928 J_MAX: 113705.43258188816 STAG. PRES: 0.02492490469131047\n",
      "V_infty: 9.0 km/s, L/D: 0.9 G_MAX: 3.5238989071582547 QDOT_MAX: 606.3090881663003 J_MAX: 115540.92181277375 STAG. PRES: 0.02390173417926408\n",
      "V_infty: 9.0 km/s, L/D: 1.0 G_MAX: 3.8503521276943893 QDOT_MAX: 616.9523003158836 J_MAX: 117393.85067445015 STAG. PRES: 0.0229253224414261\n",
      "V_infty: 12.0 km/s, L/D: 0.0 G_MAX: 2.8908316286180638 QDOT_MAX: 720.5333943051703 J_MAX: 130604.36231785928 STAG. PRES: 0.056051104983572596\n",
      "V_infty: 12.0 km/s, L/D: 0.1 G_MAX: 3.096223426257536 QDOT_MAX: 740.2271074906057 J_MAX: 133918.10970073045 STAG. PRES: 0.052606723814010596\n",
      "V_infty: 12.0 km/s, L/D: 0.2 G_MAX: 3.3484721657998837 QDOT_MAX: 760.5481989762153 J_MAX: 137296.3762419572 STAG. PRES: 0.04939376104806347\n",
      "V_infty: 12.0 km/s, L/D: 0.30000000000000004 G_MAX: 3.650856287727598 QDOT_MAX: 781.6893572966582 J_MAX: 140725.42305256563 STAG. PRES: 0.04636131078773272\n",
      "V_infty: 12.0 km/s, L/D: 0.4 G_MAX: 4.006349232576758 QDOT_MAX: 803.4271388347598 J_MAX: 144200.37139291532 STAG. PRES: 0.04352158500278056\n",
      "V_infty: 12.0 km/s, L/D: 0.5 G_MAX: 4.418380088168293 QDOT_MAX: 825.5517951157982 J_MAX: 147713.67035237935 STAG. PRES: 0.04087387163274198\n",
      "V_infty: 12.0 km/s, L/D: 0.6000000000000001 G_MAX: 4.890770876207847 QDOT_MAX: 847.9144247871607 J_MAX: 151256.7640648889 STAG. PRES: 0.0384078884466757\n",
      "V_infty: 12.0 km/s, L/D: 0.7000000000000001 G_MAX: 5.422695261293328 QDOT_MAX: 870.2116887525549 J_MAX: 154821.41894122103 STAG. PRES: 0.03612234110967443\n",
      "V_infty: 12.0 km/s, L/D: 0.8 G_MAX: 6.01902331146344 QDOT_MAX: 892.6787932647692 J_MAX: 158396.25244191734 STAG. PRES: 0.03400827768020122\n",
      "V_infty: 12.0 km/s, L/D: 0.9 G_MAX: 6.68123477206884 QDOT_MAX: 915.2050539119596 J_MAX: 161970.2698447688 STAG. PRES: 0.03204259577244489\n",
      "V_infty: 12.0 km/s, L/D: 1.0 G_MAX: 7.411377995719377 QDOT_MAX: 937.6770551196159 J_MAX: 165541.12910488964 STAG. PRES: 0.030210483754972626\n",
      "V_infty: 15.0 km/s, L/D: 0.0 G_MAX: 4.346921747902556 QDOT_MAX: 1074.4209641387738 J_MAX: 175885.09160163265 STAG. PRES: 0.0842722141780341\n",
      "V_infty: 15.0 km/s, L/D: 0.1 G_MAX: 4.766028210045917 QDOT_MAX: 1113.910955596647 J_MAX: 181947.38921017348 STAG. PRES: 0.07718278411257636\n",
      "V_infty: 15.0 km/s, L/D: 0.2 G_MAX: 5.26759567967169 QDOT_MAX: 1155.0710064984823 J_MAX: 188146.40376133015 STAG. PRES: 0.07065970810487888\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 15.0 km/s, L/D: 0.30000000000000004 G_MAX: 5.8671462900497575 QDOT_MAX: 1197.4490942917055 J_MAX: 194441.98413274015 STAG. PRES: 0.06470103693882039\n",
      "V_infty: 15.0 km/s, L/D: 0.4 G_MAX: 6.563358994794188 QDOT_MAX: 1240.642817517898 J_MAX: 200785.81417588636 STAG. PRES: 0.059336092830578654\n",
      "V_infty: 15.0 km/s, L/D: 0.5 G_MAX: 7.373172736970291 QDOT_MAX: 1284.397269964909 J_MAX: 207175.8629321341 STAG. PRES: 0.05457114929282812\n",
      "V_infty: 15.0 km/s, L/D: 0.6000000000000001 G_MAX: 8.353082551932902 QDOT_MAX: 1328.3858745943464 J_MAX: 213601.38825112395 STAG. PRES: 0.050289879460405584\n",
      "V_infty: 15.0 km/s, L/D: 0.7000000000000001 G_MAX: 9.485177406404558 QDOT_MAX: 1372.765761241155 J_MAX: 220025.69249007825 STAG. PRES: 0.04644501237075259\n",
      "V_infty: 15.0 km/s, L/D: 0.8 G_MAX: 10.741319214400628 QDOT_MAX: 1416.321183823561 J_MAX: 226419.17693117177 STAG. PRES: 0.04300596068551931\n",
      "V_infty: 15.0 km/s, L/D: 0.9 G_MAX: 12.139099667336504 QDOT_MAX: 1459.9892434536619 J_MAX: 232775.1305361177 STAG. PRES: 0.0399357105324578\n",
      "V_infty: 15.0 km/s, L/D: 1.0 G_MAX: 13.6865265357726 QDOT_MAX: 1508.5633648389878 J_MAX: 239076.54124960536 STAG. PRES: 0.03720389050512151\n",
      "V_infty: 18.0 km/s, L/D: 0.0 G_MAX: 6.174761739486084 QDOT_MAX: 1818.0048214770013 J_MAX: 253411.23063450717 STAG. PRES: 0.11969175627714063\n",
      "V_infty: 18.0 km/s, L/D: 0.1 G_MAX: 6.92499745473957 QDOT_MAX: 1898.3202101830739 J_MAX: 264306.44125130837 STAG. PRES: 0.10695452368292667\n",
      "V_infty: 18.0 km/s, L/D: 0.2 G_MAX: 7.8799317805323685 QDOT_MAX: 1982.4490097750663 J_MAX: 275443.207879964 STAG. PRES: 0.09561146243762211\n",
      "V_infty: 18.0 km/s, L/D: 0.30000000000000004 G_MAX: 9.046791095721932 QDOT_MAX: 2069.4256737839687 J_MAX: 286719.43682038516 STAG. PRES: 0.08555602390986167\n",
      "V_infty: 18.0 km/s, L/D: 0.4 G_MAX: 10.401043233417608 QDOT_MAX: 2158.622183493972 J_MAX: 298088.4464439831 STAG. PRES: 0.0767377507022008\n",
      "V_infty: 18.0 km/s, L/D: 0.5 G_MAX: 11.9727810528169 QDOT_MAX: 2249.865494244237 J_MAX: 309450.342670017 STAG. PRES: 0.06907124154569623\n",
      "V_infty: 18.0 km/s, L/D: 0.6000000000000001 G_MAX: 13.780259822078806 QDOT_MAX: 2341.8168601530147 J_MAX: 320734.0354194679 STAG. PRES: 0.06252820653052431\n",
      "V_infty: 18.0 km/s, L/D: 0.7000000000000001 G_MAX: 15.841045613556439 QDOT_MAX: 2433.640534266721 J_MAX: 331908.3215525538 STAG. PRES: 0.056928719396274946\n",
      "V_infty: 18.0 km/s, L/D: 0.8 G_MAX: 18.151587453036758 QDOT_MAX: 2537.253658995046 J_MAX: 342977.40958762274 STAG. PRES: 0.05209538185795924\n",
      "V_infty: 18.0 km/s, L/D: 0.9 G_MAX: 20.734437948336197 QDOT_MAX: 2638.9579941404577 J_MAX: 353853.0944243188 STAG. PRES: 0.04792361339496824\n",
      "V_infty: 18.0 km/s, L/D: 1.0 G_MAX: 23.59811059945316 QDOT_MAX: 2737.574068848594 J_MAX: 364566.93550278636 STAG. PRES: 0.044318511241187915\n",
      "V_infty: 21.0 km/s, L/D: 0.0 G_MAX: 8.42422420800874 QDOT_MAX: 3620.464063103271 J_MAX: 408118.7760350698 STAG. PRES: 0.16327542873633602\n",
      "V_infty: 21.0 km/s, L/D: 0.1 G_MAX: 9.794969640014452 QDOT_MAX: 3801.275068317137 J_MAX: 428452.7472886194 STAG. PRES: 0.1417048579243079\n",
      "V_infty: 21.0 km/s, L/D: 0.2 G_MAX: 11.429054280634112 QDOT_MAX: 3995.4887700339486 J_MAX: 449184.52972661424 STAG. PRES: 0.12373665702854006\n",
      "V_infty: 21.0 km/s, L/D: 0.30000000000000004 G_MAX: 13.3782007882473 QDOT_MAX: 4199.845090919123 J_MAX: 470040.7452717676 STAG. PRES: 0.10832386211560585\n",
      "V_infty: 21.0 km/s, L/D: 0.4 G_MAX: 15.668956207789446 QDOT_MAX: 4410.657906153966 J_MAX: 490861.1710438749 STAG. PRES: 0.09532165277708327\n",
      "V_infty: 21.0 km/s, L/D: 0.5 G_MAX: 18.330500848032333 QDOT_MAX: 4628.2327863455785 J_MAX: 511431.84565060126 STAG. PRES: 0.08443532350482626\n",
      "V_infty: 21.0 km/s, L/D: 0.6000000000000001 G_MAX: 21.40641208159135 QDOT_MAX: 4845.067172315869 J_MAX: 531660.9160212668 STAG. PRES: 0.07539683355334507\n",
      "V_infty: 21.0 km/s, L/D: 0.7000000000000001 G_MAX: 24.81787520260359 QDOT_MAX: 5084.129301172992 J_MAX: 551473.8547841142 STAG. PRES: 0.0679865633772947\n",
      "V_infty: 21.0 km/s, L/D: 0.8 G_MAX: 28.973716918685227 QDOT_MAX: 5323.58251534389 J_MAX: 570882.9701880673 STAG. PRES: 0.061799990897376866\n",
      "V_infty: 21.0 km/s, L/D: 0.9 G_MAX: 33.922851824885996 QDOT_MAX: 5560.251916879797 J_MAX: 589780.5581191398 STAG. PRES: 0.05659249060904906\n",
      "V_infty: 21.0 km/s, L/D: 1.0 G_MAX: 39.37393337663778 QDOT_MAX: 5790.675690004041 J_MAX: 608264.4402619004 STAG. PRES: 0.05217455617103135\n",
      "V_infty: 24.0 km/s, L/D: 0.0 G_MAX: 11.182614590144794 QDOT_MAX: 8248.036217995841 J_MAX: 748680.2376610563 STAG. PRES: 0.21670828369789094\n",
      "V_infty: 24.0 km/s, L/D: 0.1 G_MAX: 13.299782310010826 QDOT_MAX: 8710.290700588193 J_MAX: 789882.0352528467 STAG. PRES: 0.18248597335428227\n",
      "V_infty: 24.0 km/s, L/D: 0.2 G_MAX: 15.877814894148809 QDOT_MAX: 9216.786789727099 J_MAX: 831307.3977832511 STAG. PRES: 0.15493772994463587\n",
      "V_infty: 24.0 km/s, L/D: 0.30000000000000004 G_MAX: 18.957461866291617 QDOT_MAX: 9759.709642147032 J_MAX: 872501.9242971297 STAG. PRES: 0.1329660460516487\n",
      "V_infty: 24.0 km/s, L/D: 0.4 G_MAX: 22.58142722397484 QDOT_MAX: 10322.198163230449 J_MAX: 913005.1757574958 STAG. PRES: 0.1151718628674372\n",
      "V_infty: 24.0 km/s, L/D: 0.5 G_MAX: 26.911390112195324 QDOT_MAX: 10897.396210342911 J_MAX: 952459.8157620035 STAG. PRES: 0.10083984102705652\n",
      "V_infty: 24.0 km/s, L/D: 0.6000000000000001 G_MAX: 32.466978271312755 QDOT_MAX: 11498.287324935909 J_MAX: 990772.4460970437 STAG. PRES: 0.08929581344058474\n",
      "V_infty: 24.0 km/s, L/D: 0.7000000000000001 G_MAX: 38.70820507433439 QDOT_MAX: 12131.60079403634 J_MAX: 1027862.9949657086 STAG. PRES: 0.08005271024910952\n",
      "V_infty: 24.0 km/s, L/D: 0.8 G_MAX: 45.71026094880105 QDOT_MAX: 12749.713571453853 J_MAX: 1063968.0893497155 STAG. PRES: 0.0725486293138238\n",
      "V_infty: 24.0 km/s, L/D: 0.9 G_MAX: 53.585236372939576 QDOT_MAX: 13357.369566930854 J_MAX: 1098863.211108142 STAG. PRES: 0.06630198777031747\n",
      "V_infty: 24.0 km/s, L/D: 1.0 G_MAX: 62.26071611264381 QDOT_MAX: 13953.367365448154 J_MAX: 1132774.5768809386 STAG. PRES: 0.06105653087706181\n",
      "V_infty: 27.0 km/s, L/D: 0.0 G_MAX: 14.363615735279323 QDOT_MAX: 20272.79844339766 J_MAX: 1531993.9939355 STAG. PRES: 0.2783203830485\n",
      "V_infty: 27.0 km/s, L/D: 0.1 G_MAX: 17.492858082192523 QDOT_MAX: 21540.635095592057 J_MAX: 1622252.7195364458 STAG. PRES: 0.22916355811503927\n",
      "V_infty: 27.0 km/s, L/D: 0.2 G_MAX: 21.353627683576416 QDOT_MAX: 22958.188133863572 J_MAX: 1711407.7596616955 STAG. PRES: 0.18906341370922544\n",
      "V_infty: 27.0 km/s, L/D: 0.30000000000000004 G_MAX: 25.931079239810643 QDOT_MAX: 24465.673522600104 J_MAX: 1798935.374272588 STAG. PRES: 0.1596591016620036\n",
      "V_infty: 27.0 km/s, L/D: 0.4 G_MAX: 32.1112007603324 QDOT_MAX: 26040.163026410533 J_MAX: 1883371.416883715 STAG. PRES: 0.13655554476909207\n",
      "V_infty: 27.0 km/s, L/D: 0.5 G_MAX: 39.36127628933757 QDOT_MAX: 27632.437146365406 J_MAX: 1964544.871717222 STAG. PRES: 0.11860836607958714\n",
      "V_infty: 27.0 km/s, L/D: 0.6000000000000001 G_MAX: 47.69819055476627 QDOT_MAX: 29405.476681165506 J_MAX: 2042308.6295229446 STAG. PRES: 0.10452719407866698\n",
      "V_infty: 27.0 km/s, L/D: 0.7000000000000001 G_MAX: 57.15726958677382 QDOT_MAX: 31133.652962213335 J_MAX: 2116948.444353941 STAG. PRES: 0.09341302282088658\n",
      "V_infty: 27.0 km/s, L/D: 0.8 G_MAX: 67.78192725215459 QDOT_MAX: 32847.008695694785 J_MAX: 2189040.7944109114 STAG. PRES: 0.08453432673507223\n",
      "V_infty: 27.0 km/s, L/D: 0.9 G_MAX: 79.34356975133963 QDOT_MAX: 34506.66320084381 J_MAX: 2258792.860557631 STAG. PRES: 0.07718468123623182\n",
      "V_infty: 27.0 km/s, L/D: 1.0 G_MAX: 91.93706339660054 QDOT_MAX: 36085.51363393946 J_MAX: 2325955.2492424552 STAG. PRES: 0.071041316343463\n",
      "V_infty: 30.0 km/s, L/D: 0.0 G_MAX: 17.994963856761558 QDOT_MAX: 51165.606228469434 J_MAX: 3346374.7450613542 STAG. PRES: 0.3486465087744134\n",
      "V_infty: 30.0 km/s, L/D: 0.1 G_MAX: 22.42610762220299 QDOT_MAX: 54698.17043949227 J_MAX: 3555113.7303039636 STAG. PRES: 0.28060723638252283\n",
      "V_infty: 30.0 km/s, L/D: 0.2 G_MAX: 27.888370518023525 QDOT_MAX: 58687.918112634456 J_MAX: 3757956.8061894733 STAG. PRES: 0.22729036308494915\n",
      "V_infty: 30.0 km/s, L/D: 0.30000000000000004 G_MAX: 35.50159724837316 QDOT_MAX: 62925.45741920919 J_MAX: 3952684.9818899683 STAG. PRES: 0.1885077114450837\n",
      "V_infty: 30.0 km/s, L/D: 0.4 G_MAX: 44.48682978043672 QDOT_MAX: 67312.05752136097 J_MAX: 4138378.769145138 STAG. PRES: 0.15969259301004665\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 30.0 km/s, L/D: 0.5 G_MAX: 55.000631123206965 QDOT_MAX: 72106.50330381742 J_MAX: 4314455.590514551 STAG. PRES: 0.1379807957528202\n",
      "V_infty: 30.0 km/s, L/D: 0.6000000000000001 G_MAX: 67.02330887208193 QDOT_MAX: 77061.07551218665 J_MAX: 4481490.306523125 STAG. PRES: 0.12127442764138617\n",
      "V_infty: 30.0 km/s, L/D: 0.7000000000000001 G_MAX: 80.26995057882559 QDOT_MAX: 81860.37647943423 J_MAX: 4640755.994720861 STAG. PRES: 0.10819125188886036\n",
      "V_infty: 30.0 km/s, L/D: 0.8 G_MAX: 95.01109394221965 QDOT_MAX: 86503.29609315004 J_MAX: 4793843.852989098 STAG. PRES: 0.09782508059879762\n",
      "V_infty: 30.0 km/s, L/D: 0.9 G_MAX: 111.07655399612644 QDOT_MAX: 91066.80850778254 J_MAX: 4939316.509102341 STAG. PRES: 0.08928173014236097\n",
      "V_infty: 30.0 km/s, L/D: 1.0 G_MAX: 128.65172002104336 QDOT_MAX: 95149.99581716067 J_MAX: 5083954.181157044 STAG. PRES: 0.08214512172126848\n"
     ]
    }
   ],
   "source": [
    "acc_net_g_max_array       = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "stag_pres_atm_max_array   = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "q_stag_total_max_array    = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "heatload_max_array        = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "\n",
    "\n",
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(LD_array)):\n",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,overShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "        vehicle.propogateEntry (2400.0, 1.0, 180.0)\n",
    "\n",
    "        # Extract and save variables to plot\n",
    "        t_min_os         = vehicle.t_minc\n",
    "        h_km_os          = vehicle.h_kmc\n",
    "        acc_net_g_os     = vehicle.acc_net_g\n",
    "        q_stag_con_os    = vehicle.q_stag_con\n",
    "        q_stag_rad_os    = vehicle.q_stag_rad\n",
    "        rc_os            = vehicle.rc\n",
    "        vc_os            = vehicle.vc\n",
    "        stag_pres_atm_os = vehicle.computeStagPres(rc_os,vc_os)/(1.01325E5)\n",
    "        heatload_os      = vehicle.heatload\n",
    "\n",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,underShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "        vehicle.propogateEntry (2400.0, 1.0, 0.0)\n",
    "\n",
    "        # Extract and save variable to plot\n",
    "        t_min_us         = vehicle.t_minc\n",
    "        h_km_us          = vehicle.h_kmc\n",
    "        acc_net_g_us     = vehicle.acc_net_g\n",
    "        q_stag_con_us    = vehicle.q_stag_con\n",
    "        q_stag_rad_us    = vehicle.q_stag_rad\n",
    "        rc_us            = vehicle.rc\n",
    "        vc_us            = vehicle.vc\n",
    "        stag_pres_atm_us = vehicle.computeStagPres(rc_us,vc_us)/(1.01325E5)\n",
    "        heatload_us      = vehicle.heatload\n",
    "\n",
    "        q_stag_total_os  = q_stag_con_os + q_stag_rad_os\n",
    "        q_stag_total_us  = q_stag_con_us + q_stag_rad_us\n",
    "\n",
    "        acc_net_g_max_array[i,j]      = max(max(acc_net_g_os),max(acc_net_g_us))\n",
    "        stag_pres_atm_max_array[i,j]  = max(max(stag_pres_atm_os),max(stag_pres_atm_os))\n",
    "        q_stag_total_max_array[i,j]   = max(max(q_stag_total_os),max(q_stag_total_us))\n",
    "        heatload_max_array[i,j]       = max(max(heatload_os),max(heatload_os))\n",
    "\n",
    "        print(\"V_infty: \"+str(vinf_kms_array[i])+\" km/s\"+\", L/D: \"+str(LD_array[j])+\" G_MAX: \"+str(acc_net_g_max_array[i,j])+\" QDOT_MAX: \"+str(q_stag_total_max_array[i,j])+\" J_MAX: \"+str(heatload_max_array[i,j])+\" STAG. PRES: \"+str(stag_pres_atm_max_array[i,j]))\n",
    "\n",
    "\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'acc_net_g_max_array.txt',acc_net_g_max_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'stag_pres_atm_max_array.txt',stag_pres_atm_max_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'q_stag_total_max_array.txt',q_stag_total_max_array)\n",
    "np.savetxt('../data/jsr-paper/neptune/'+runID+'heatload_max_array.txt',heatload_max_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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kzp2bmjVrssTMK5H9Nn8KH3UbwMnjULasdYlSfLykqC/I3IL7ezMZ2x2TQcbaEpHzMoGtHrF3TkKa7vh4iI5WxtD0wT8oC2gdUcTJJ2F/HGCr9Ih++03Z6teH4sWVgrh79yrZjxwcoFQpaNZMWYemoSCEOCal9NPFhjZ8ZwYIIQgMDGTfvn1mn66mXv12AGx/S4JoS8bGRtCzB1wJlnBWC3hIRNjF4XywDjY/f/zfzipV3r5YSFeeoXSHMqP0ko4BW4EHgC0gIWdOZQTxwgWoXVvJ2/jll3DypKKXp04pgvXxx29rRCOjaD0lM+Gnn36iX79+XL16lQIFChjbHZ0oXdqL7NkfsXO7dfWUAO7fl+TJBwX+Z8udKc7GdsekcMCBy1wmK1mVpKwuLtC+vbqN3EGJutuPkpjVASXdkBuQC2UNk+9/p1+5AgMGKFHqtWtDuXKQL58ShxEeDt7e8OjRf3NP1o7WU7IiAhMmfc19vRJA/Xo12bcPwsMt9wfR28iWTQl4uLsgDhlpfe//Xbwc+SUffnFbefHRR+oL0gvgU+AyMAs4A4Sg1FcajzKUN+i/0+PjYeFCJQLviy+gXTsoUkQRJIDQUChaFM6fV9dNa0cTJTOhVKlSuLu7E2wB6YsbNPiQ6GhlfN4a6dsHnj8GNy3DQzJeXs3Jltl5iYkBYmKUuGtVGwD+BLYD/kAWlECHzAmvZ6FkdkjAxgY2bID+/ZXKtK9y754ynBcUpJ/K7daMJkpmgq2tLdWrV7cIUaoRVBdnZxu2bTe2J8YhKEiZOHeYpYnSq9i1XUdMmBvbd8fAp58q3RI1cUXpDf0DRLx27DpKYtbKyXc3aKAkl9i/H168UBbWNmumZHWIiIC+fdV1UUMLCTcrAgMD2bRpE/fv3ydbtmzGdifDODk5EVSjKFu2XmCqsZ0xAkII+vaRfNpfkuVoLHF+2p8hgG2DnQjXF8xZ9Zwm77UFtZc/OKIkXW2PUlfJG6X3dB9lrukWijC9wuefK8N3gwYpeWJz5YKWLZV0Q2ovo9JQ0HpKZkSNGjUAy5hXatiwFZcuSa5csc55lfe7KvP42WdoGR4SEU4vsWu2hZ2r3YgNqgP/+5/6jXwC9EJZOLsIJd3QBZSQ8Okow3iv4O4OP/6olLOIjVWi7b7//j9BsuA4MaOhiZIZUbFiRZydnS1iCK9Row8A2LrNyI4YiSxZBF06w7Vl8cgw7c6WiG2XZTg12cWzh9FKKu7YWHUbCAEGAh2BI8BRYAMwDigNvOW/olEjqFZNCQN/tSCusL4AUr2jiZIZ4eDgQLVq1SxClIoULYqPjytbtxrbE+Px8f/gZRRkm/fS2K6YDHaNt8NvH+KwdY6yWOjGDXUbSFzo+hSIR1ksG5fwXKIEPryFDz+Ec+e0ekr6RhMlM6NGjRqcPHmSJ2pHJhkYIQSNGwXy5y54+dI6ewplyghq1IDwmbHIOOv8DFLCQTqyyiMzcdNnKuNnapIoSuEodz/bhM2GdwoSKBHqTk5Kb0lDf2iiZGbUqFEDKaVFlEhv3Lg7ERHWGxoO8Mn/4H4ouGxUeZjKjHmypRoftviA3b59IWtWdY0nitLz9F+aJQt06AAvtY6tXtFEycyoUqUK9vb2FjGEV7NWI5ycBFuseAivZUvInQcyT9cCHhKxrRWMnctTts+/ocRhq4kjShaHDIgSwK+/wty5ajqk8TqaKJkZLi4uVK5cmb0W0L1wcXGhVk1fNm223tlie3vBx33hyp8STmv58ACEcxTFa/3Od0vyEbtmg/oNuKHkv8sAiYENiSUsNNRHEyUzJCgoiKNHj/JC7V+RRqBx43ZcuiS5eNF651R69lDmKnJO03pLiTzqfIge/MJfsZVTPzm9ZCbDogTwyy9KCQu1YzA0FDRRMkOCgoKIi4vjr7/+MrYrOtOk6YcAbN5iXD+MiZeXoHMnuLEoDvnIesX5VZ622s7vmTux6GAh9Y3r0FMCqFNHyYu3YIFqHmm8giZKZoi/vz+2trYWMYTn4+NDiRIebNxkbE+My2f9ISoSss/WZtFBWUhbYn5jJg27pb5xNzI8pwRKiqFatZT5pfh41bzSSEATJTPE1dUVPz8/9uzZY2xXVKFpk/rs3QtPn1pvL6FUKUGdOvB0Riwy2no/h1fZ1y2YyOmD1Tf8BTBcNxPduillLSzgd6HJoYmSmVKzZk2OHDlCeHi4sV3RmaZNexEbC9utNEFrIoMGwKPbkOUPLVErwOBf3Jjl2IgxY1Q23BCor5uJ1q2VEHFtzZL6aKJkptSsWZOYmBiLmFeq5h+Ih4c9GzYa2xPj0qAB+BYH2x9jzL7CsBqsfs+OHQ8q8/33EBWlouFQYJ9uJlxcYM0amDxZDYc0XkUTJTMlICDAYuaV7OzsaNSoIpu3COKsOLOBjY1g0Gdw46TEYZcWHp79+ktqVd/G8+eom45qBtBAdzO1aoGHh+52NJKjiZKZkjivtHv37tRPNgOaN+vGo0cSC+j46USXLpAtG3h8r4WHT+sRSa/Z3+HtDUuXqmi4J7BZHVPr10P37urY0lDQRMmMqVWrFocPH7aI9UoNG7XH3l5Y/RCek5Og3ycQsjUem3+su7f03VcOLJ9YnrZtYeNGUG36tChQUx1T168rUXgnTqhjT0MTJbOmVq1axMbGWkQePDc3N2rVLMK69dab3SGR//VV5ixy/GDd4eF/BdpyqKYTnTop9Yvu31fJ8HVgCTqtVUqkc2dwdNRSD6mJJkpmTPXq1bG3t7ecIbzmHbl4UXL+vPXOKwF4eAh69oArS+KR16y3t5T9Tjw5/75OQIAyp+Tjo5Lhv4HOKOKkI1mzQtu2sGiRUh5dQ3c0UTJjMmXKROXKlS1HlFoog/Pr1hvZERNgwGfKY67J1ju31OPnGKZWO5K0QvXOHZXys7olPOqwgPZVevWCZ89gxQp17Fk7miiZObVq1eLYsWM8e6bCWISRyZs3LxUr5tCG8ID8+QUdO8DNudabemh5Z3t6b84DKMX1cudW6cafKEoq/ckEBkK7dloknlpoomTm1KpVi7i4OIsoZQHQskVLDh6U3LljnTfiVxk6BCLDIds065xbulTMhu0NbcDGBl9fZfhOlSi8RFF6qoItlMzhy5dDs2bq2LN2DC5KQoi8QoiVQoinQohnQojVQoh8abw2nxDidyHEdSFEpBDiohBinBAik779NlWqVauGo6Mjf/75p7FdUYWWLf8HwLp1RnbEBChZUtCsGTycHot8YX0i7f5YUjb4KTx/jhBKgb0//4R793Q0rEOhv3fx5Ans03FRroaBRUkI4QLsAnyBD4CuQBFgd2rCknB8J1AD+ApoDMwFBgG/6tFtk8bZ2Znq1atbzLxSyVKlKFTIjTVrje2JafDlcHj+GLxmWV9vqdKhONYHPSX+7GkAOnZUppd0HsJTefgukX79oHlziIxU1661YeieUk+gINBSSrlWSrkOaA7kB3qncm11FAHrLaX8XUq5W0r5HTAVaJMgeFZJ7dq1OXXqFA8ePDC2KzojhKB1q4bs2g1Pnlhf7+B1qlRRErU+/yEWGWVdn8exyra03OlKuG9eAEqVUrZly3Q0nNhTUlmUunVTektawINuGFqUmgOHpJSXE3dIKa8CB4AWqVzrkPD4+lfpCcr7sNrZ8Tp16gBYTNbw1q37ERsLm6y8nEUiI76AsLvgOde6IvHCPAV/1XHmWZb//rTnzYM//tDRsC2QCdWH72rWhKJFYfZsde1aG4YWpZLA6RT2nwFKpHLtTuASMFEIUUII4SqEqA30B2ZJKc0/XXYG8fPzw83NzWLmlSpX8Sd3bmdWrTa2J6ZBUBD4V4fI72KsqqyFfbQk6M9YIkPPJe2rXFmJwtMZN1QLdEhECOjdG/76C/79V13b1oShRckDeJzC/jAg67sulFJGAQEoPp9B+Z3zJ7AR+CSlax48eICfn1/SNmfOHF18N1ns7OwICgpi586dxnZFFWxsbGjVsjZbt0F4uPXchN+GEIKRX8KDG5D1N+spa+ESASvqPsZ+9YZk+7duhU9S/ItPByuBITraSIEPPlAyPOzYob5tU2XOnDlJ91jAS1d7ZhMSLoRwAv4AsqEESAQBnwPtUfL+voG3tzdHjx5N2nr16mUwfw1NnTp1CAkJITQ01NiuqEKbNp8SGQlbrLhM+qvUrw+VKkP0N9HIGOsQ6mdu0HqvJ6EdqyXbf+ECzJgB58/rYNwfZYZaZTw94epVGDhQfdumSq9evZLuscBDXe0ZWpQek3KP6G09qFfpjpJGsbGUcpGUMlhK+T1K9F0fIURZVT01M+rWrQtgMUN4gTXq4O3twIqVxvbENBBCMPoruB8KWayktyRtBIdqOPAop0Oy/e3aKUNlOq1Z2gtsSPWsDJEzp/IYZ70ZonTC0KJ0BmVe6XVKAGdTubY08FhKGfLa/sMJj8V19M2sKVGiBDly5GCHhYwb2Nra0rpVLTZthogI6+gZpEajRuBXCWInRFvN3FKVPZHYHzmZbF+uXEpQwdKlkOFaiFNRyqLriREjwN9fB/+sGEOL0nqgqhCiYOIOIUQBlHDv1DKe3QWyCiEKv7a/SsLjLbWcNEeEENStW5ddu3YRn5ArzNxp27Yf4eEqF3gzY4QQfD1S6S15WElvaWLfZxSb9GaXpmNHuHQJjh/PoOHpgB6/V3nywOHD8Pff+mvDUjG0KP2CUox4nRCihRCiObAOuAEkBVIKIfILIWKFECNfufY3lOCGzUKID4QQtYQQnwPfA8dQwsqtmnr16vHgwQP+tZDQn5q1GuDlpQ3hvUqjRlC5CkSNj0a+tPyf4e//4cjW72q9sb9tW6hYEZ5mNIIud8KmJzp3hsyZlbkvjfRhUFFKCNuuDVwEFgKLgatAbSnlq/l/BcpqAptXrg0FqgIngXEotSN7AnOAelJKy+ge6EDieiVLGcKzs7OjVcsgNmyEyEjLvwGnBSEEY0fDg+vgYQXrls6UsSWkwJuTM1mzwtGjULt2Bg0fRLmL6OlrlTkzvP++khPPAta0GxSDR99JKa9LKdtIKd2klJmllC0TBOfVc0KllEJKOfq1/WellO9JKfNKKZ2llEWllIOllKkFSVgFuXPnpkSJEhYjSgDvvdef8HAtCu9V6tVTMlOHj49BWvh8W/mjceTbcOqtxyMiMlj8bz9KsjI9rm783/8gOlqpTKuRdswmJFwjbdSrV4/g4GAiLSQBV81aDfD2duCP5cb2xHQQQjBuDITdAc8Zlp0Tr+fMGN7/X8oTM7GxSubwUaMyYFhP+e9epUQJmDUL2rfXXxuWiCZKFkb9+vWJiopi//79xnZFFezs7GjbphYbNsILK8yU/TZq1BDUqwdPJ8Yin1nu5zL+awf67U4pYBfs7KBOHSXXXEx64z4MIEqgZHgoUEC/bVgamihZGEFBQdjb27N9+3Zju6IaHToMIjISNm40tiemxYRx8PQRZP/BcntLt/LacK7w2xWnY0d49CgDGRRUrqn0LvbsUULENdKGJkoWRqZMmQgICLAoUQoIrEOuXM4s1TU7tIXh5ydo0xru/hiLvG+ZcT6FLsXT4Lc7EBWV4vEGDZSghyVL0mk4S8KjyklZU+LgQRg/Xqmeq5E6mihZIPXr1+eff/7hzp07xnZFFWxsbGj/XiO2bIXHjy13qCojjBsLURGQa7xl9pYC9sbx3UcP3hrC5uCghIevXasEPaQZAw3fAfTooeTDmz5d/21ZApooWSANGjQALCc0HKBjx8HExMBqLXN4Mnx9Bd0+gtCf4+CK5eW1WdvWjrJXMv+XuycFBg+G/fvB2Tkdhg04fOftrQwzLlig1FvSeDeaKFkgZcuWJVu2bGzbts3YrqiGX6WqFC7sxtI/rLZs1lsZPUqZ9M8xwvJ6S0/dBaE+gmi7tw9PFi0K5cop+fDSTKIoGWD4DuDTTyE8XAsPTwuaKFkgNjY21K9fn+3bt1tMyiEhBJ06tmPXLsmdO9oQ3qvkzi34rD9cXhqP7bFYY7ujKh6PJB/NjeP51X/eed65c0rl18dpXbGop+qzb6N8eejQAdzcUj/X2tFEyUJp2LAhDx8+5NixY8Z2RTU6dRqMlGgBDykwdAh4eYHH5y+RFpQF1PueZErPcGL/fncWsYgImD8fVqY1JZU9EIJSItRALF2qzC9pvBtNlCyU+vXrI4SwqCG8Yr6+VKyYg8VLtCG818mSRTBqJFzdLcm00XJ6SyFFBJWuZ+duq2rvPK9CBWUYL11ReAX5r8dkIKKjtQTDqaGJkoXi7e2Nn58fWy3sL6BL5w85flxy9qzl9AbUoncvKFwE7IZGI2Mt4/OJtRfczmvLU8eUQ8ITEQI6dYK9e+FWWusFzAUM3OuePVtJqnvihGHbNSc0UbJgGjZsyMGDB3mc5oF206dDx/7Y2MCixcb2xPSwtxdM+hZun5N4zLacZK1dZodjF/xXqud17KjUL1qWVqGZg5IW2oB07QqurjB5smHbNSc0UbJgGjVqRHx8vEUtpM2RIwcN6vuyeIkgPt4yegNq0qKFUgDv2agY5BPL+HyGD3uG54rdqZ5XtCg0bapEIqaJfYCBs4S4u8NHHynCefu2Yds2FzRRsmAqV65M1qxZ2WJhKba7du3P9euS4GBje2J6CCGY/AM8C4PsYywjRLzKRXeCJzVN07kbNkD/tAYvOKIUyTEw/fsryWS1Wkspo4mSBWNra0v9+vXZunWrxYSGA7Ro+T6ZM9vy+wJje2KalCunLKi98VMsXDD/BbV3veN44vTuOaVXiY+H69fTcOJSYHCG3cowhQpBy5bKgl8LCpRUDU2ULJwmTZpw7949TljQzKqLiwvt2gaxchWEh2t/1Skxfhw4OUG2gebfW2q6Kpr8C/am+fzOnZXif6ne8A+h1MI2AvPnK4la07Xg10rQRMnCadiwIUIINm3aZGxXVOXDD7/gxQst7dDbyJ5d8NUIuLI5HpdN6a3rYFp0nR9D1SmH0nx+/foQEgKHD6dyYhaUjA5GGETIkkURpGfPIM78O7OqoomShePt7U2lSpXYvHmzsV1RlYDA2hQsmJnfFmg/Nd9G/0+VEHGbAdHIaPPtUX64zInP/66R5vNbt1YSoC5OLUIzC0o5dAOlGnqdf/+FvHlh3TrjtG+qaKJkBTRp0oTDhw/z4C2Zls0RIQQfvN+RXbskoaHme8PVJw4OgmmT4e4liddk8x3GC3cVPLJPez6gLFmgWTP44w8loODtJyY8GijV0OuUKKFk4Zg0SZtbehVNlKyAJk2aIKW0uCi8Dz4YjhBoAQ/voFEjQbNmcH9sLPE3zXOcyH9fHO1Hn0vXnbtzZ7h/H3bufMdJiaJkgEzhKWFrCwMHwqFDcODdWZSsCk2UrIDy5cuTM2dONlpY6db8BQpQu3ZhfvtdW7P0LqZOBhkHOcw06KHa/ji6j7n91kJ/KdGoEWzapJRLfysGLF/xNj76CDw94bvvjOeDqaGJkhVgY2NDkyZN2LZtG9HRlrPSH6B7t4GEhkp27TK2J6aLj49g+DC4siIe5x3mlxdv6mB7fGLzpKtgkqMjNG4M9vbvOMnIw3cALi7wySfK+qrQUOP5YUpoomQlNG3alGfPnrF//35ju6IqrVp/RNasdszT6tS8kyGfQ8FCYPfJS+RL8+pVxtoLImzS3ktKJCICvvxSueGniAGrz76Lfv3gyBEoUMC4fpgKmihZCXXr1sXR0ZENb/0LNU+cnJzo0rkxq9fAo0fmdbM1JE5OgpnT4c5FSbaJ5jWM5xMSz9AvnhEfeiVd1zk5waJF78ickNhTCtfJPZ3x9AQ/P+W5FvCgiZLVkClTJmrXrs2GDRssqt4OQI8eo4mO1pK0pkaDBoL32sGtCbFwyXyCHnLelvSfFE1k6Ll0XWdjA126wI4dcO9eCifkAuKAbmp4qRtSQs+eMGyYsT0xPpooWRHNmjUjJCSE8+fPG9sVVSlTtjyVK+fil7nC4gRXbaZMBidH8OobZTaf1V8BNuSO9uJJzXLpvrZLFyXt0NKlKRwUmMwdUAh4+VLp1T16ZGxvjIuJ/JdoGIKmTZWkluvXrzeyJ+rTs0d/zpyRHDxobE9Mm5w5BRPGQ+ifkiyLzCTTgxDYCXueZWDyp3hxqFgRFr6tRMUg4HedvFONIUMgPBx++snYnhgXTZSsiLx581K+fHmLFKUOHf+Hq6stc4yUy8yc6NMbqlSFiIHRyAemn6jXPloyYsgzZRwuA/TsCUWKvCWifC9wRif3VKNUKaX0yLRp8OKFsb0xHpooWRnNmzfn4MGD3EtxkN18cXV1pUvnuvyxHB4/No9hKWNhayv4ZRa8eAI5BqY/qs3QxNrBhzMisDv+T4au791bqV/k5JTCwaOACa0RGj4cwsKUCrXWiiZKVkaLFi2QUlpcglaA3r3HEhUFCwxcTdQcKV1aMHQIhCyKx2WraQ/jSRtB4fAc/DO0kU52Llww/eSnVarAlCnQtq2xPTEemihZGeXKlSNfvnysXbvW2K6oTrnylahSJRezZmsBD2lhxJdQzBfo8xL53LQ/r1hiMzSnlMi2beDrq5SLSMY4oLcunqlP//6QP7+xvTAemihZGUIIWrZsyY4dOwgPN/ICDT3Qt8/nnD8v37z5aLyBk5Ng3hx4cB2yDzftYbw+37/AZ3rG02QFBSmJWn9/PajhLPCnTq7phWPH4IMPIMa0O7F6QRMlK6RFixZERUWxI4MTx6bMe+174+Fhz8yfje2JeVC9uuDTfnBlRhxOe003BVH13dFkC874UgYnJ2jfHlatguevlqrIglFz372Nu3dhwQJl8a+1oYmSFRIYGEjWrFlZs2aNsV1RHWdnZz76sCVr1sKtW6Y9JGUqjB8HBQuCXfcopIlW8m27yZnZK+rqZOODD5TUQ6tWvbIzUZRM7G03bgzlysE335j+PJjaaKJkhdjb29OsWTM2bNhAjAWOD/TtO4H4ePhlrrE9MQ8yZRL8OhfuhkAOEx7Ge4Ruq0qrVVNCw5cseWVnFiAGMLG3LQSMGAGXLsHy5cb2xrBoomSltGrVisePHxMcHGxsV1SnUOHCNG5UitlzBNFmXHHVkAQFCfp9AiHT43DabXrDeC1XxNKpj27fVSGUG/yKFa/sNHJNpXfRqhWULAnjxilZKawFTZSslPr16+Pi4sLq1auN7Ype+OSTr7l7V7JypbE9MR++maCUTxcfRSGfmZaYF7ocT+ldD3TOWFqunBLwkIQJi5KNjSJInTtbV8CDJkpWiouLCw0bNmTNmjXEW+DPsPoNWlKkiBvTZwhju2I2ZMokWDAfHt2AHANMazzrh+EONL1YVOnu6MimTUrmhPh4TFqUAFq2hC++UOpDWQuaKFkxbdq04c6dOxy0wIRxNjY29PukH4cOSQ4fNq1f/aZMtWoJi2p/jcN1nWkVhIxGHX9evID161EKQ5q4KIEinsuWpVLa3YLQRMmKadKkCQ4ODhY7hPfhR0Nxc7Nl6jRje2JejB4FZctBVM9o4u+aRi+63LE4fuhwC65d09lWixaQNSvMmwd4AgUwuei7V4mPh5EjYfBg66i3pImSFZMlSxbq1avHqlWrLDIDQubMmenerQXLV2jh4enBwUGweAFEPoPsPUyjxIXrc0nxEy/hqe5dGicnZZ5mzRoIywFcBerrbFZv2NnBV1/BqVOwbp2xvdE/mihZOW3btuXatWscO3bM2K7ohX79JhEfDzNmGtsT86JkScF3E+Hqpng8Zhp/GG9/TTsaXygIZcqoYq9HD6V+kbksTu3YUQln//pry+8taaJk5TRv3hw7OztWJIuTtRx8ChakZcsKzJ4DEREW/tesMv0+gQYN4P7gGGxOW9YKzrJlFWEqkB9oAJh4yZPE3tLJk0oPz5LRRMnK8fDwoE6dOqxYscIkhmn0wcABkwgLSyHvmcY7EULw26/glhkyd4pCRhnv+5H5mWRK21uwYYNqNn/5BZq3AGJRyqKbOB07QpMmlh+Jp4mSBu+99x5Xr17l+PHjxnZFL/hXr0XlyrmYPFUQH2+ZwqsvcuQQ/D4fbv0ryT7IeGHiMfZQ6NxLePxYVbuPHsH2oUAfVc3qBTs72LhRESZLRhMlDVq2bImdnR3LLTSfiRCCQQNHc+mSxAKL7uqdRo0EAwfAlZlxuK4xzvxSlLOg2ZmC8P77qtr94gslc4IK8RMGIzxcKQJoqTnxNFHSwMPDg7p167J8+XKLHcJr3eYjfHxcmfSDtpg2I3wzASpWhPBu0RBqOXfDnj1hZgTcq2NsT9LO5s3Qp4/l5sTTREkDgPbt2xMaGsqRI0eM7YpesLOzY+CAAfz1l2T/fssUXn3i4CD4YymIePDoEIU0Qk7Brz6+C2PHqmrTzw8KuUHMWfOJamvTBkqXhtGjIdb00hTqjCZKGoAyhOfg4MAff/xhbFf0xkfdhuLpac93k4ztiXlSqJBg7hy4/rck+7CXBm8/85P414ohqUMOX3CMhL/+Ut20XrCxgTFj4OJF8wlpTw+aKGkA4O7uToMGDVi+fLlF5sIDyJQpE598/CEbNsKZM2bys9jEaNdO8PH/4MrkWFxXG3Z+acjiXPDdd6rbzV8a3AWYU8L8Fi2U4dSvv4Zo4y8jUxVNlDSS6NChAzdv3uTAgQPGdkVv9Pv0G1xcbJio/r3Navjhe/CrBC8+ioZL5j+/ZO8NnnYwfJixPUk7QigZxPPmhQcPjO2NumiipJFE8+bNcXZ2ZunSpcZ2RW94enrSq2dLliyF0FCtt5QRHB0FK/8ABztwbxuFNNCi5K5Tw5QugtpkAZFQ6C/KtJKjv5MGDWDvXsid29ieqIsmShpJuLq60qxZM1asWGGRFWkTGTRoCjY2MOl7Y3tivuTPL1i8MGH9Uu9Iw0Vt6mNo2V15mPo1lChhPsEDQijb7dsJGc8tBE2UNJLRqVMnHj58yE4LzpOfJ29ePvygLvN+hTt3tN5SRmnYUDB6FFxZFI/nT/qf2FjY30PVjA5JJJSvKJUXrl41v6SnvXtD+/bw7JmxPVEHTZQ0ktGoUSOyZs3K4sWLje2KXhk6dCYxMfD9D8b2xLwZ8SU0bQq3B8bguNdMuhivkyBKNctBgQIwzcxKnYwcCQ8fwuTJxvZEHQwuSkKIvEKIlUKIp0KIZ0KI1UKIfOm4vrgQYoUQ4qEQIlIIcUEI0V+fPlsTDg4OtG3blrVr1xIeHm5sd/RGocJF6NQpgFmz4cEDrbeUUWxsBIsWgE9BiH8vCq7rL/DBf0c4VKkCN26oazg3UBtsXeDjj5UovJMn1W1Cn1SqBK1bww8/KOJk7hhUlIQQLsAuwBf4AOgKFAF2CyEypeF6P+BvwBHoATQGfgBs9eWzNdKlSxfCw8NZZ27jGOnkyy9mERkJP/xobE/MmyxZBOtWQ2wkZG0dhYzUj8hHOwqlOp/a+XXKAn8C5aF7d3BxMb/e0pgxSvqhb781tie6IwyZViahR/MjUExKeTlhnw9wCRgipXzr7UEIYQOcBi5IKVulpT0/Pz959OhR3R23MuLj4ylQoAClSpVi8+bNxnZHr3Ts6M+GDQcJvQJeXloKIl3YsEHSohUUaG/D/SXOCKHu55mHPJzjnKo2U2L9emUNkLlFtXXrBra2MGeOEgBhDIQQx6SUfrrYMPTwXXPgUKIgAUgprwIHgNRiPWsCxVFETUOP2NjY0LlzZ7Zt28a9e/eM7Y5e+WrEbCIitN6SGjRrJhg/Dq4ui8drvOEzPmSYKJTxmhnKy+bNzU+QAObOVcpxGEuQ1MLQolQSpbfzOmeAEqlcG5Dw6CSEOCSEiBFC3BdCTBNCOKvqpQZdu3YlPj7eotcsAZQoWZr27asy/SdtbkkNhg2Fzp3g2lexuK5SNyLP+3YMVKigfpU7R6AKkOe/XYcPKznmIiPVbUqf2CTczU+ehJAQo7qiE4YWJQ8gpYIoYUDWVK7NlfD4B7AdqAd8hzK3tCSlCx48eICfn1/SNmfOnIx5bYWUKFECPz8/FixYYGxX9M6okb8QGamtW1IDIQRzf4HKVeBJ12jsj6oXkRflYqN0YVxcVLMJgAAWkWysJjISVq+GhQvVbUrfvHgBQUEwZIjh2pwzZ07SPRbw0tmglNJgGxANfJvC/nFAbCrXzgEkMO21/UMT9hd//ZqKFStKjYwzbdo0Cch//vnH2K7onS5dAqSzM/LOLaSME9qm43bnFjJfPqRnLqTrdWfpqsI/X+mr3y9B/CtP46X085OyaFEp4+L026zajBkjJUh58KDh2waOSh11wtA9pcek3CN6Ww/qVR4lPO54bf/2hMfyOvilkQIdO3bE3t6e362gjviokfOIjoZvLCB6yRTIkUOwaQNEPwf3ZlHI5yY+NBqIMuOdgBAweLCSidvcCkMOGADZsim9JXMpx/EqhhalMyjzSq9TAjibhmvfhWWmtjYiXl5eNG3alEWLFll02iGAwkWK8tGH9Zk1G65fN8O/ZBOkVCnByuVw57TEq10kMlaFz7VOHRg+XHc7r+MAPEm+q00b8PGBiRPN6+bu6gqjRsG+fbBpk7G9ST+GFqX1QFUhRMHEHUKIAkD1hGPvYgvwEmjw2v6GCY9a7Lce+PDDD7l37x5bt241tit6Z+TIXxBC8PUYY3tiOdSvL/h5BlzbFk+2PlG658grXlxJja02WXhjrMbOTqkp2K6dflLu6ZOePaFcObh1y9iepB9Dr1PKBJwCIoERKHNBY4HMQBkp5YuE8/IDIcAYKeWYV64fBXyFEuCwC/ADRgF/SCk/fL09bZ2S7sTExJAnTx6qV6/O6tWrje2O3hnwWVumTV/F6X+geHEzj601Ib4cIZnwDRT42o6HI50yZEOv65S6oUwMqJwswpjExSnrlgyJ2a1TklKGA7WBi8BCYDFwFaidKEgJCJQsDa/7NwYYArwHbAb6ApOAnvr13Hqxt7fn/fffZ8OGDdy/f9/Y7uidL778mUyZbPlyhLE9sSzGjYX3u0LoqFjc55lgVTp33hi+SyQ6Gn77Dc6kNoFgYtjaKsOOGzdCRISxvUk7Bs99J6W8LqVsI6V0k1JmllK2lFKGvnZOqJRSSClHv7ZfSil/lFIWllI6SCnzSylHSikte8LDyHz00UfExsayyBJrL7+Gt7c3nw/uwZq1cOiQGU0kmDiJoeL168Od3tFkWp9BYfrsMyXmWW3cgRdAChHs4eHQr59SVM/cOHkSmjWDH81ocbiWJVwjVUqUKEHVqlWZN2+e4ermGJEBA78ne3ZHhgwTVvF+DYW9vWDVCihfAZ60j8ZxfwbWMBUvriRlVZuETOGkUP4ha1bo2xeWL4fLl988bsqULw8tWyrBGuaSnEUTJY000b17d86ePcuhQ4eM7YrecXV1ZfSoEezbJ80uHNjUcXUVbN4A+fJBdLMo7E6lM7lq797wnR5q2bsnPD5J+fCAAWBvr9zczY2JE5WKuqNHG9uTtKGJkkaaaN++PZkyZWLu3LnGdsUgdO8xlGLF3Bk6XBATo/WW1MTbW7BjK7hlApuGkXBJf+Uu0ox7wuOTlA/nzKkkPP39d/UrZ+ibokWhTx8lL945/eez1RlNlDTSRObMmenYsSPLli3jmaWUuHwH9vb2fDdxBhcuSOb8YmxvLI/8+QU7toGIAZf6kcgbaRSm+fPB2xsep7bWPp0UBroDbm8/ZehQKFMGzDHeZ9Qo8PU1jxBxTZQ00kyvXr2IiIhgyZIUUw1aHM2ad6RWrUKMGg1Pnmi9JbUpXlywbQtEPgK3elHE30vDYqBChZSFQ2qnwi4JzEURp7eQPz8cPaqUtTA3vLzg33+hbl1je5I6mihppBk/Pz/KlSvHrFmzrCIAQAjBjz8sISwMxo03tjeWScWKSjqiJ9clHvUjkY9SEaYaNWDmTHB3V98ZSYrRd6/z9Cn8+af6zesbIZTw9l9/Vb9OoppooqSRZoQQ9O7dm1OnTnH48GFju2MQypWvTLeP6jBtOly6ZPlCbAwCAwXr1sD98xKPhpHIp0b4nJ8BdkAaKs4OGqTUXHrwQN9Oqc/WrUp13XnzjO3J29FESSNddO7cGVdXV37++Wdju2Iwxo1biJOTLYMGG9sTy6VePSVc/O4piWfDCOSztwjTyZNKL0ntisiuwHCgcuqnDhqklLaYPFldFwxBs2YQGAgjRig9PlNEEyWNdJE5c2Y6d+7MH3/8QVhYmLHdMQg5cuZkxJf92bARtm7Vekv6omlTwR9L4fZRiWejiJQzi2fPDh98oH5pWBuUAjoBqZ2oLJVq1w6mTwdz+xMQQhHThw9hvIkOSWuipJFu+vbtS1RUlFWUtEik/2cTKFIkC/0HCKKjNWHSF61aCZYtgVt/S7wapyBMOXPC1KlQtqz6jT8C0hhZ99VXSkG9KVPUd0PfVKyo6PqUKXDpkrG9eRNNlDTSTdmyZfH392fmzJnEm1v65Azi6OjI1Cm/cPGiZMpUY3tj2bRpI1i6GG4eTOgxpTSUp49Am7oodazTQKlSSmmLCxfUd8MQTJgA/v6mmRNPEyWNDPHxxx9z+fJldux4veai5dKocTuaNyvLmLFw86bWW9In7dolDOX9LfGsH4F8nPDjR0ol788IPWTMdeeti2dTYvFi+OMP9d0wBDlzwp49+ulw6oomShoZom3btmTLlo2ffvrJ2K4YlClTVhEXJxg4yNieWD5t2ghW/AF3jks86kUS9zBWmRT55BMISMPkT3pxJ/X616/g6Kg8hoaabtBAaoSFKQtro00ocbsmShoZwsHBgd69e7Np0yZCQkKM7Y7B8ClYiC+/6MuKlbBtm9Zb0jctWwrWrob7pyWRta9y7949pfJeo0bqN+YOpFNcbt+GYsXMc24J4NAhGDNGmaYzFTRR0sgwffr0wdbWlhkzZhjbFYPy+ZAfKVrUnf99IoiM1IRJ3zRurCywDQuJo0aNGty4cQNiM5BhPDXcSdfwHUCuXNC4sRLR9iSd15oCjRtD06aKMN2+bWxvFDRR0sgwuXLlom3btsybN4/nz58b2x2D4ejoyMwZC7hyRTJ+grG9sQ7q1BFs2+LM3bu3uV6kCBH+/uo34g48J01ZHV5l1Chl+M6UehvpYcoUiImBwSayDk8TJQ2d+Oyzz3j27JlVhYcD1KnbjK5da/DdJDh7VustGYKAABt27/qUpfb2fHH+PCdPnlS3gawJj+nMN1yuHLRoodzczbG3VKiQkmx26VIl+MHYpEuUhBC1hBAjhBAzhBA/CSG+FELooQykhrlQpUoVqlatytSpU60mPDyRH75fQebMdvTsLYiP14RJ/0RQofxFPjlyhNXu7gQFBREcHKyeefeExwwkIB81SqlQu2+feu4YkmHDoFcvKFDA2J6kUZSEEIWFECeAncAYoC/wP2AssEsIcUQIUVB/bmqYMp999hmXL19m48aNxnbFoHhny8aPP0zkr78kP88ytjfWwgF8ixXjr+3byZUrF/Xr12ft2rXqmHZPeMyAKJUvDzdvKml8zBFnZ5g920xESQjhCmwHcgMDgKKAE+Cc8HwQUADYJoTIpDdPNUyWNm3akC9fPn744Qdju2Jw3v9gAPXrFWfYcLh2Test6Z8w+HIgeUqXZl9wMOXKlaNNmzb88osKRa9KoaQaypGxy7NlUx7Npex4Sly7Bq1bK4/GIi09pe6AJ1BNSjlNSnlZShktpXyZ8HwK4A9kA7rp0VcNE8XOzo7+/fsTHBzM0aNHje2OQRFCMHv2RqS0oXcfrKKkh3FxgobZYMIEvDw8+PPPP2nQoAG9evVi1KhRun3+BYEvgTwZNzF+vDK/lJIbjx4p+WRNGSFg2zbo108/STPShJTynRvKkN2PaTjvR2BnaucZcqtYsaLUMAxPnz6VmTNnlh06dDC2K0Zh2tQREpC/zkXKOKFtettspYwbnOyzj46Olt26dZOA/OCDD+TLly8z9p8YJ6UMlVI+yvj34OFDKWNj39wfGyvl+vVSVqiQcduGYtIkKUHKVavSfy1wVOp4305LT6kkkJbZxL0J52pYIW5ubvTu3ZsVK1Zw9epVY7tjcD7+5GsCAwswYJCWgki/xEPcDiUVQUwMoJSunzt3LqNHj+b333+nSZMmPM1IioUIlIkIHWoNeXqCrW3yfdHRiqvNmkGWLMqaIFOmf38l/dCnn8KzdEYiqkFaRCkracud+4D/gio1rJD+/fsjhGCyORaa0REbGxvm/7qNmBgbevTUhvH0yrYzyt3/+PGkXUIIRo0axfz589mzZw/Vq1cnNDQ0fXYzoZRE1zFZxOXLSXoJwPLlSnQbwLffKpVfTRl7e5gzR1lM+803hm8/LaLkQNqWk8UB9rq5o2HO5MmTh86dOzNv3jwePnxobHcMTqHCRflu4lds2w5qzLtrvIVSTvDjAMjz5uTPhx9+yLZt27h16xZVqlTh0KFDabcrUGbQS2XctZUr4YsvlIQTiUknmjaFadPg7Fml11S+vOkHQ1SurIjp8OGGb1uk9otOCBEPjAdSG5MpCAyXUtqmcp7B8PPzk9Y28W5szp49S8mSJRk5ciRff/21sd0xOPHx8TSoX4KDhy5w6gQUKiSM7ZIF4gTiWxCfvvWM8+fP07RpU27evMn8+fPp2LFj2kz/k/BYJmOeXbkClSopomNn99/+gAAICVEq1n76qekP4b1KYrJWB4fUzxVCHJNS+unSXlpFKa1ITZQ0WrZsSXBwMNevX8fV1dXY7hicG9evU7pMQUqUiCd4j8TOThMmVYmX8LAuuKwCN7e3nvbw4UNat27Nvn37+PLLLxkzZgw2NqkMDlVGmYTYlnH3WrSAfPmUyrSPHyuZEiIjwddX6T01apS2G7wp8Py5UnepdWtIy29MNUQpLcN3PunYtAW0GgwbNozHjx8ze/ZsY7tiFPLmy8fMGZM5eFDyzbfG9sYCeQ7k3JnqGKmXlxc7d+6ke/fujB8/ntatW6eeozEr6U7K+jpTpsCJE1C6NHz4IfzzDzRvDj4+cPEifPkl1KsHK1bo1o4hyJxZCXqYMEF5H4YgLT2lXFJKE8kfmz60npLxqFOnDufOnePKlSs4OTkZ2x2DI6Wkc+dAli8/wIF9UKWK1ltSjXgJs+whYCOUq5/q6VJKpk+fzsCBA/H19WXt2rUULlw45ZPbAycBHSvKXr4MW7ZAXJySfujxY0WQXFyUzl2OHMrxRo1Mfyjv0SMoXlzp/R06lHxY8nXU6CmlZZ1SPHAY+AIooWsMuiE3bZ2S8di1a5cE5IwZM4ztitF4/PixzJ8/kyxYUMinj7X1S+puWaSMX5eu/4+dO3dKDw8P6e7uLjdv3pzySb2llNl0/q9PIi5OymHDpGzfXsqZM6W8ePG/Y/v3S5kvn3pt6ZMVK5S1S+PHv/s8DLROyR/4E+gKnBZCXBBCfCeEqKaTGmpYNDVr1sTf359vv/2WaFMqa2lA3N3dWbxoLaGhkv99rIWJq8q9GLhzJV2X1KlTh6NHj5I/f36aNGnC2LFj30wi7I6S+06l/6pRo2DJEhgyBPr2hSJF/jt24wZUrarMN5n6V6NtW2XbuFHp/emV9CgY4AsMAw6ihIDfAeagRPY76KqQam9aT8m4bNmyRQJyzpw5xnbFqIz5uq+W7UHtrbSQsmXpDP1/hIeHy86dO0tANm3aVIaFhf138Fup3D3Cdf9/f/lSyhYtpNy69c1jK1ZI6ekp5ddf696OoXjyRMro6Hefgwo9pYxfqKQt7ANsAaJQCgkvBzrq6pRamyZKxiU+Pl5WqlRJFihQQEan9m22YGJjY2XNmoWkiwvyzL+aMKmyrUbKnV0z/H8SHx8vp0+fLu3t7aWPj488duyYcmC2VO4eN1X5r5ctWkjZs6eUcXHK6/XrpWzTRkk3NGmSOm0YmrAwKdeuTfmYGqKU4SJ/Usq7UspZUspGgDfwCdAKmJlRmxqWhRCC0aNHExoaanVFAF/F1taWJYuDcXV1oF17QXi4iY/VmAMtBNTK+HIDIQSffPIJwcHBxMTEUK1aNWbNmoXMkvB/k4HyFSkxZQocO6ZE2+XKpWR2yJdPyZTQr59yjjSzr8NXXylDea8k1FAVIVX6RIQQbVB6So5SynQWFNYPWvSd8ZFSUrVqVe7du8fFixdxMJcFGnpgx/Y1NGjYmi6d4ffflBujRgZ5IOFhfSipw4KiBB4+fEjXrl3ZunUr44LG8eXeL5Vsn4G6uwlKmr6//lIW1q5fDzNnQtGi6tg2BmFhUKoUeHjA0aPwanCtodYppQtTESQN00AIwddff821a9f41dSTfumZevVbMfKrXixcpKUh0pkxQI1dqpjy8vJi06ZNTJgwgZ/2/cRn2T7jVNQpVWyDcvNu2hTq1oVdu0w/911qeHjAvHlw5ozSa1IdXcf/EjegDRCnlj01Nm1OyTSIj4+X/v7+Mnfu3DIyMtLY7hiV2NhY2aB+CenggDx8SJtfyvB2GClXFlD9/2ffvn0yb9680t7eXn7//fcyLnEySAXi46Xs2FFKFxcp791TzazR6NNHSiGk3L37v30Yc05JQyOtCCEYN24ct27d4ueffza2O0bF1taWxYv3kjOnC23aCR48MLMJBVOhooBW6g9/BlQL4PRPp+leszuDBw+mUaNG3LlzRxXbQsDo0RAVpWQLN3e+/x569FB/KDLVOSUhRFpTBzUCpkkt953GW6hXrx4nT57kypUrZM6c2djuGJXjx/6iekAA1arB9q1afrx081TCZXcofSf5pIauxAF2IEdKZueczcCBA8mUKRNz586lRYsWqjTx0UewbJmSoDVXLlVMGp34eLCxMdyc0mXgUhq26bo4omH5jB8/nocPH1plvaXXqVDRn9mzfmD3bsngz43tjRmyDaj8RMnnoya2wB4QPQR9+vTh2LFj5M2bl5YtW9KjR4/Uc+elgZEjlbmYd+SSNSvCwpT5siVL1LGXlp7SB+kxKKU0mdhfradkerRp04YdO3YQEhKCt7e3sd0xOp/1b8fUaSuZPw8+/FDrLaWZ2xKOCqj5CNz1W1s0OjqaUaNGMXHiRAoUKMDvv/9OYKBKoXkWQGwsBAXB6dPw7JkBct+Z86YFOpge586dkzY2NvLTTz81tismQUxMjKxTp6h0cEDuD9YCH9K3OUoZ/0T9/5RtUspNb+7et2+fLFiwoBRCyEGDBsmIiAidmlm5UspRo3QyYTJcuSJliRJaoIOGGeLr60v37t35+eefCQkJMbY7RsfOzo7lf/xFvnxutGoDoaFa4EOaiJbwtw3cuai+7YkoZU1fIyAggFOnTtGrVy9++OEHypcvz8GDBzPczIEDMHYsnDuXcVdNBR8f+PdfdWxpoqRhcEaPHo29vT1ffPGFsV0xCTw8Pdm44S9iYmxp1kLw7JkmTKnyGPCPhNWr1bedlbdmdHB1dWXWrFns2LGDyMhIAgICGDRoEBEREeluZvhwpZTFiBG6uWsqpFY/Mc121DGjoZF2cuXKxaBBg1i+fDmHDh0ytjsmQTHfkqxcsYrz5yXvtYeYGE2Y3oknsCETNK+gvm13Ui30V7duXf7991969erFjz/+SJkyZdi9e3e6mvH2hsGDFV09ciSjzloemihpGIUhQ4aQPXt2Bg0alLj42uqpU7cFP8+cwLbt8PEnWqmLd2InoLEd5NVD2qp39JRexc3NjZ9//pldu5TMErVr16ZHjx48fpz2xHkDByriNGyY+eXA0xeaKGkYBVdXV8aNG8dff/3FCnOoC20gevQczvBh7/PLXLRS6qlxOAb+UWki41WyotQ9iEzb6bVq1eKff/7h888/57fffqN48eIsW7YsTT8qMmeGH3+E7t118tiiSDUk3JzRQsJNm7i4OCpUqMDTp085d+4czs7OxnbJJJBS0rVrLRYv3svv8+H997VQ8RQpCZQpC3+cUNfuLKAvcAtI5+LWEydO0KtXL44ePUrDhg356aefKFSokLr+mTAmmZBVQyOt2NraMmXKFK5du8aPP/5obHdMBiEEv/66nTp1itG9J2zdark/HHViPjBaD+uFEpc9ZaB8Rfny5Tl06BBTpkxh//79lCpVirFjxxIVFfXO62Ji4LvvQBs00ERJw8jUqlWL1q1bM2HCBG7evGlsd0wGBwcHVq8+TKlS2WjTDv7+WxOmN6gMFItP9bR0o4MogfJjq3///pw/f55mzZoxcuRISpcuzbZtby+zYWsLy5fDoEFKeXRrRhMlDaPzww8/EB8fz+efa/l2XsXNzY0tm0+SM2dmGjeFs2c1YUrGWQk79DSnBDoX+sudOzfLly9n27ZtCCFo2LAhrVu3JjQ09I1zbWxg0iS4cQOmTtWtXXNHEyUNo1OgQAGGDh3KsmXL2LNnj7HdMSly5MzJ9m3HcHBwpF4DwdWrmjAlMR14P+OLV99KCeAQUEMdc/Xr1+fff/9lwoQJbNu2jeLFizNq1CjCw8OTnVerFjRrBhMmwP376rRtjmiBDhomQWRkJCVKlCBTpkycOHECe3t7Y7tkUvz7z3GCalYha9Y49u2V5MqlBT8QIuGFL5Q3n5QIN2/e5PPPP2fZsmXkyZOH7777jg4dOiRVIb5wQanq2r07zJplZGczgBbooGExODs7M3XqVM6cOcNUax+/SIHSZSqwdctO7t8X1K2v1WECoJCAsjH6sf0b8Jf6ZvPkycPSpUsJDg7G29ubTp06Ub16df7++28AihVTQsQ/SFcabMtCEyUNk6F58+Y0a9aM0aNHc+PGDWO7Y3JUrhLExg3rCQ2FuvUFjx5ZuTDdlLDiAbx4ob7tAcAy9c0mEhgYyJEjR5g7dy5XrlyhatWqdOrUidDQUPr1g2rVUr7ustqlOkwQg4uSECKvEGKlEOKpEOKZEGK1ECJfBuwME0JIIcR+ffipYRymTZtGfHw8n376qbFdMUmCajZh3dqVXLgA9RsKHj+2YmE6AHR4Btevq2/7X+Ab9c2+iq2tLd27d+fSpUt8+eWXrFmzBl9fX4YMGcLNm0/o2xfWrfvv/Bs3bjBo0CBKlSrF+PEpZIy1FHRNM56eDXBBKQh4GmgJtED57w8BMqXDTkHgBXAP2P+287TSFebJt99+KwG5du1aY7tismzauEQ6OCArVhQy7KGVlrx4iJQnbaSMjDT2f4cq3LhxQ37wwQdSCCFr1aonS5aU0sdHysQKGbdv35Z79uyRBw4ckP7+/rJ169Y6l89QG1QoXWHQQAchRH/gR6CYlPJywj6fBKEaIqVM0wpKIcQ2IBQoBthJKQNSOk8LdDBPYmJiqFixImFhYZw9exY3SynRqTIbNyyiTduulC4t2L5V4uFhjcEP9iAegsisrtllwAOgn7pm08KpU6eIiYnh+XM/ateGr79WqtW+SmxsLJUrV2batGkEBKR4+zMK5hjo0Bw4lChIAFLKqygd8RZpMSCE6ARUAIbrxUMNo2Nvb88vv/zC7du3GT5c+29+G02bdWH1qsX8+y/UqSd4+NDKhvLCJSwVcPG4+rbXAD+pbzYtlC1bFj8/P2rVgnbt4JtvIDRUqYCbyJ07d3j06BEuLi7GcVKPGFqUSqIM3b3OGZTVAe9ECJEVmIzSqwpT2TcNE6JKlSr069ePmTNnsm/fPmO7Y7I0adqJdWv/4Nw5qFVHcO+eFQlTONDlJezcrr5tD8AE7jA//qhkexg6VMnyAXD48GHef/99KlasiJeXV4rXpSdTualhaFHyIOV10mH8t476XUwCLqIEbKbKgwcP8PPzS9rmzJmTZkc1jM/48eMpUKAAPXr0INLac6+8g4aN2rF50xquXIEaNQU3bliJMHkCZzJDV5VWub5KYvkKI3+UefLAokXw8cchzJ49m2bNmtGtWzcKFSrEnDlzyJdPiRGLi4sDlHve5MmT6dSpE/ny5WPatGl693HOnDlJ91ggZZVMB3a6u2QYhBCBwPtABZnGiTBvb2+0OSXzxdXVlV9++YV69eoxatQovvvuO2O7ZLLUrtOC7du20bhJIwJqxLNzu6RIEQufY7IV4GsDIjr1c9OLBxAHPAeMOKV56tQpli37hrCwMBwcHGjYsAkNGtSlSJEiAMTHxyOEwNbWFoChQ4dy5coVevTogY+PD3369KFAgQI0b95cbz726tWLXr16ASCEeKirPUP3lB6Tco/obT2oV5kNzANuCiHchRDuKKJqm/DaUVVPNUyCunXr0rNnT3744QcOHtRDShkLonpAPXbv2kdEhB0BNeDkSSvoMa16Cbv0sMrVI+HRyKNg27ZtY/ny5URERBIbu5EbN/pSpEiRpFpNNjY2xMcrSWlnzZrFhQsXGDVqFF26dKF69epUrFiREyeU0h6GDGrTBUOL0hmUeaXXKQGcTeXa4kAflK9J4lYdqJrwvK96bmqYEt9//z158uThgw8+ICIiwtjumDQVKlZjX/AxHB2dCaoFe/eax40ow4x8CXPenn07wyT+dDbyvNKQIUO4fPky7u5Z2LPHi0mT+nL8eFxSWqKYmJikXtKsWbNo06YNVapUSbre09OTCxcuACRdY+oYWpTWA1WFEAUTdwghCqCIy/pUrq2VwnYKJXCiFrBSD/5qmABubm7Mnz+fS5cuadF4acC3eGkO7D9HrlzuNGgEa9ZYsDBtA2Y1VN+uifSUAAoWLMjGjRv588892Nvfpl27ZYSHRxEXF5eUI3L58uW4ublRp06dZBF5v/32Gy1btgRI6lGZOoYWpV9Q1hetE0K0EEI0B9YBN1CG5wAQQuQXQsQKIZKi86WUe17fgCfA04TXWjEeC6Z27dr069ePadOmsWPHDmO7Y/LkzZef/fsuUb58Xtq+BzN/tlBhygNk0UOaoURReqS+6YxSvXopfvttHVeutOfTT7dRrFixpDDx58+fkydPHnLl+q9U7vTp03F2dqZ48eJERUVhY2MeWeUM6qWUMhyojRJBtxBYDFwFakspX/1mCcDW0P5pmDYTJ07E19eXDz/8kLAwE4jXNXE8vbz488/zNGlcjo8/gaHDJPHxFiZOeyT8+rf6dlWqqaQ2HTpA48Z27N/fgn37DiaFiTs7O3P27Fm8vb0BZR3TqFGjGDVqFK1atSJ//vyMHz/ePP5udE0JYcqblmbI8jh27Ji0t7eXbdu2lfHx8cZ2xyyIiYmRffs0lYB8rx0yMtyC0hL1QspsDup/aLFSyvtSyhj1TevKnTtSPnmSfN+5c+dk2bJl5ahRo+Ts2bNlnTp1ZIMGDWR8fLzctWuXbNiwoQSki4uL/OSTT+Tly5f14hsqpBkyunDoc9NEyTJJzI03d+5cY7tiNsTHx8vvJg6UgKxWTch7dyxEmB4hZVg5Y3+8RuHlSymPHfvv9YkTJ2SDBg1kkyZN5Pz58+WNGzeklFLGxcVJKaX8559/5Icffijt7e2ljY2NbN26tdy3b5+qP+40UdJEySqJi4uTderUkS4uLvLs2bPGdsesWLniF+nsLGT+/EL+c9JChCmuiH4+rElSykX6Ma0GvXpJ6eYmZYL2JBEeHv7O627duiWHDx8uPTw8JCArVqwof//9dxkVFaWzT2qIklDsWCZpScj67Nkz7t+/T0yMnoqFaeiFuLg4bt++ja2tLTlz5tQ53NXOzg4nJye8vb1xcnJSyUvT5OiRfTRvUY/nz1+yZBE0a2YeocIpck7CRlfocxOyZFHXdhmgHLBAXbNqceUKlC4NNWrA5s2Q3j+BiIgIFixYwNSpUzl//jzZs2enV69e9O7dm9y5c2fIJzUSshq9N6PPLbWe0tOnT+XFixdleHi4Nj9hhjx58kQeOXJEhoaG6mQnPj5eRkdHy7CwMHnhwgX55PUBewvk5o0b0s8vpxQCOX4cMj7WTHtNS5ASpDxzRv0PyQxuCdOnK29fl5HsuLg4uW3bNtm0aVMphJB2dnayXbt2cs+ePem+L6L1lN5Naj2ly5cvkytXLovMtGst3Lx5k7t37+Lj44Onp6fO9iIiIrh79y4FCxZM/WQzJzIyku7d67N06X7atYVf54Grq5n1ml5KiLWBTDFgJiHPahIfD7Vrw/Hj8O+/kD+/bvZCQkL4+eef+fXXX3n8+DElS5akT58+dOnSBXd391SvN8fSFSZFTEwMzs7OxnZDQwdy5cqFq6sr165dUyVpq7OzMy9fvlTBM9PH2dmZxYuDmfjtZ6xaDdWqCy5dMrMfqY4CMtmC0EOmj9+BXuqbVRMbG5g/H8qUATWSnRQqVIjvv/+emzdvMm/ePJydnenXrx+5cuWiW7duHDp0CH13ZKxalMB8Um9opIyNjQ0FCxbExsaGkJCQpGzJGcXavg9CCIYMnczWLau4c8cWv8qwbp0ZCdNTCROA43oob/IvsEh9s2rj4wP790Px4urZdHFxoVu3bhw5coSjR4/SpUsXVqxYQbVq1ShTpgzTpk3T25onqxclDfPHwcGBggULEhUVRWhoqN5/yVki9eq35tjRixQpkoOWrZWFtrGxZvA5vgS+ioHDekjW6wlEAlHqm9YHz55B796QkOpONSpWrMicOXO4ffs2c+bMwdnZmf79+5MzZ046dOjA9u3bdf4x+CqaKGlYBG5ubuTJk4fHjx9z9+5dY7tjluQv4MP+/Vfp3asx301SigbevGniwuQNRGSBPg3Ut52YasgMkiAAhIfDypXQpQvoI5g4c+bM9OzZk8OHD3Py5El69+7Njh07aNCgAQUKFOCLL75QpR1NlDQshuzZs5M1a1Zu3brF06dPje2OWeLk5MSs2ZtYvGgaJ04IylWAzZtNWJiEUOaVeKK+bTMTpZw5Yc4cOHoUxo3Tb1tly5Zl2rRp3L59m+XLl1O6dGl+++03VWxroqRhMQghKFCgAC4uLly5coWoKDMZdzFBOnXux7Gjp8iTx5smzWDQYMnLlyYqTlMi4Y+t6ts10fx376JNG+jaFcaPh7/1kBLwdRwdHWnXrh2bN2/m8uXLqtjURMmCEEKkuhUoUCDp/IMHD/Lee++RK1cuHBwc8PT0pF69evz+++/ExcWxdOlShBAEBwcna+fevXsIIciePfsbPsyYMQMhBKdPn9bpvdSsWZOaNWum+zpbW1sKFSqEEIJLly4RGxurkx/WTDHfUhw6dJ2P/9ecHycr0Xnnz5ugMM2Nho16uAObWU8pkenTlTLqn3wChpxeVWtpjdmUQ9dIndcrs7Zq1YqyZcsyevTopH2OjkqB3ilTpjBw4EBq167NxIkTyZ8/P48fP2b79u307dsXd3d3atSoAUBwcHDS88TXLi4u3L9/n/Pnz+Pr65vsmKenJyVLplTL0TA4OjpSqFAhLl68SEhICEWKFDGbtP2mhpOTEz/NWEe9egvo3qMHFfxi+GGSpE8fE4pU/EeAbQv17Zpg+Yq0kCULrFoF3t7pz/JgCmiiZEFUrVo12WtHR0e8vLze2B8cHMzAgQP55JNPmDZtWrJjLVq0YODAgYSHh5M7d24KFSr0Rk8pODiY2rVrc+7cOYKDg5OJ0r59+wgICDD6DStz5szkz5+f0NBQrl+/Tv78+Y3ukznTouX7VK5clw8/rMv/PjnHho0wb64kZ04T+ExtJMiHSsEbNUlci21mPSWAihWVRynh6lUwp7Xg2s9HK2TixIl4eHjw3XffpXi8UKFClClTBoAaNWpw8ODBZMNgwcHBBAYGEhAQkEywLl26xJ07dwgKCkqXP8uWLcPX1xdHR0dKlizJmjVr3nruqVOnaN68OVmzZsXZ2Znq1auzb1/yNSpLly7F19eXPHny0KVLF1atWkX16tUzNByo8R85c+Vi67YzTJ/2FXv2CkqWhmXLpPFD8FdIGPOn+nZdAXfAjNNiDh4MlSvD7dvG9iTtaKJkZcTFxbF7927q16+fpsSjNWrU4MWLFxw/fhyAJ0+ecPr0aQIDAwkMDEwmCIkC9epQX2rs3LmTTp06UaRIEVavXs3nn39O//79uZDCYovjx4/j7+9PWFgYv/zyC6tWrcLT05O6dety7NgxAHbs2EHnzp3x9fVl9erVDBs2jKlTp3Lp0iUt6a4KCCH4pN8YThz/l6JFc9OxM7R7D+7fN6IwBQNLQtS3K1CCHIarb9pQ9OoFkZHwwQdKSiJzQBu+ewvG/lW9Z88evdh9+PAhkZGR5E9jkqzEXk9wcDCVK1dm3759ODo6UrFiRTw9Pbl+/TqhoaEUKFCA4OBg3NzcKFeuXJr9GTVqFL6+vqxbty5p3sfX15dq1apRrFixZOd+/vnn5MuXj127diVV3GzQoAGlSpVi7NixrF27llGjRlGiRAnWrFmTNFxXsmRJKleuTL58+Xj27Blubm5p9k8jZYr5lmT//lB++H4wI0dNY89eydTJkk6djDDXNF0AxpvDNGWKFYMpUxRxmjIFBg40tkepo/WUNN6Jj48PefLkSeoFBQcHU6VKFRwcHChatCjZsmVLdqx69erY2tqmyXZcXBxHjhyhbdu2yQIRqlatmixKEJTkoXv37qVdu3bY2NgQGxtLbGwsUkrq1q1LcHAwcXFxHD16lDZt2iS7MVaqVAkfHx9sbGy4fPky4eHhOn4qGqCU+xg6bAonjp+gcOHcdHkfmjWH69eN0Wt6ph+zY4Fh+jFtKHr0gBYtYNgwOHHC2N6kjtZTegv66qkYG09PT5ydnbl27Vqar6lRowZbtmxBSklwcDANGvy3ej5xXql27dqEhobSu3fvNNt9+PAhMTExKYaWv74vLCyMuLg4xo4dy9ixY99pL1u2bCnac3BwwM7OjkuXLuHr62vxdZMMRYmSZTlw4BrTp33JlyMmUbJ0POPHST7+H9jaGqDXdFjC/Dsw4RGokCk+GbeA5+qaNDRCwNy50LixkvXB1NF6SlaGnZ0dNWvWZMeOHWnOhh0UFMTjx485dOgQx48fJzAwMOlYYGAgwcHB7N27F0jffJKXlxf29vbcu3fvjWOv73N3d8fGxoZ+/fpx5MiRFLdEe/fv30/RnhCCokWLAnDx4kWryQZuCGxtbflswLec/vciAdWL0/8zqOovOH7cAL2mG8DacNBHgtBZwGL1zRoaLy9lMW1AgLE9SR1NlKyQYcOG8ejRI4YMGZLi8atXr/LPP/8kvU4Umm+//RYpJdWqVUs6FhAQwKVLl1i+fDkuLi5UqlQpzX7Y2tpSqVIlVq5cSfwrs7B///03oaGhyc7NlCkTgYGBnDp1igoVKuDn5/fGZmtri5+fH6tWrUoWEXbs2DGuXr0KKOtuihYtSlxcHBcvXtSCH1TGp2AhNm85w9IlM7hxw4FKVaDfp5InT/QoTm0E3PGBIkX014YFIISSE+/LL2HtWmN78w50rRJoyltqlWfPnj37zuPmTv78+WXnzp1TPDZ58mQphJB169aVixYtksHBwXLdunXy008/lS4uLnLt2rXJzs+WLZsUQkg/P79k+2NjY6Wrq6sUQsjatWu/0c7Vq1clIEeNGpWiHzt27JBCCNmsWTO5ceNGOX/+fJkvXz6ZI0cOGRQUlOzcY8eOyUyZMsm6devKpUuXyj179siVK1fKL774Qg4dOlRKKeX27dslIFu0aCE3bdokf//9d+nj4yNz5Mgha9WqlWTr+fPn8tixY/L06dMyOjo6WTuW/r0wFI8fP5Yf/6+ZtLFBZs8u5O/zkXEx+qpwW1g/b2KxlLK8lDJCP+YNzcuXUlasKGXWrFLeuKG+fVSoPGt04dDnponS20VJSikPHDgg27ZtK3PkyCHt7Oxk1qxZZb169eTChQtlXFxcsnPbtm0rATlgwIA37NSrV08CcvTo0W8cO336tATkzz///FY/lixZIosWLSodHBxkiRIl5OrVq2VQUNAboiSl8n/Wvn176e3tLR0cHGTu3Llls2bN5KZNm5LOWbx48Rv2ypUrJ1u2bJnM1tOnT+XRo0fl6dOnZUxMTLI2NNTj6JH9skqV3BKQ1aoJeeRvlYXpHlJ+lFnKvXvVd36WVO4mN9U3bSwuXpQyUyYpa9WSMjZWXduaKGmiZPLMnj1benl5yfDwcKP5cOPGDeno6CjHjBnzxrFEYTpz5kySMGnfC/WJi4uTv877TmbL5iCFQHb7CHnnlkridA8pc9lKuXCh+o6vkMrd5JT6po3JvHnK3f+bb9S1q4YoaXNKGnpl7969DBgwQLVkjakRGRlJ3759WbVqFXv37mX+/PnUq1cPFxcXevTo8cb5bm5uFC5cmMjISC5cuKDNMekJGxsbPur2ORcv3mfggHYsXARFisH4CZLISB3nm7wE3PBRCgmpjRmnGnoXH30E772nlLh4+NDY3iRHEyUNvbJ48WLVin+lBVtbW+7evcsnn3xCvXr1GDhwIEWKFCE4OJicOXOmeE2WLFkoXLgwUVFRXLx4UdUqmhrJyZIlC9//sJwzp89Rt045RnwFxYoLFiyQxMebYAZyM03KmhpCwOzZsG+fEplnSmiipGFRODg4sGbNGu7cuUN0dDSPHz9m/fr1lCpV6p3XZcmShSJFivDy5Uvu3r3L9evXDeSxdVKkqC9r1p5g966NZMuWnQ8+ggp+gm3bEuYV0svgh0rNBrUx0/IVacHdHcqXV54bovZSWtFESUMjATc3t6Rw8YCAAC5evGhslyyemrWacPjwLRYtnM7Tpy40bAx16wv+/judwnT6pZIOW20Sh+8srKf0Khs3QtWqsGCBsT1R0ERJQ+MVXF1dyZEjB1FRUQQEBCQlotXQHzY2NnTu8gnnzz9i6pQv+Pdfe6r6Q6vWEiV4Mw1szQ0//qi+cy6AExYtSo0aQVAQfPwxqFQ8Vic0UdLQeA0HBwf279+Pi4sLQUFB7Ny509guWQWOjo582n88ISEPGfN1b3bttqVMOejYSRq34q0nFi1KtrawcCHY20PHjhAdbVx/NFHS0EiBokWLcuDAAXx8fGjcuDGLF1tArhkzIXPmzHw1chZXr95n2NAubNhoQ8nS0KXrO8Tp56fQrZt+HKoKpBwjYzHkzQu//gpHjyqJW42JJkoaGm8hd+7cSZnPu3Tpwvjx4zM2Ca+RITw8PJjwzUKuXr3L4EEdWLPWhhKllJ7TmTOv/T88ioPXUlOpxkpgvH5MmxItW8LQoVChgnH90ERJQ+MduLu7s3XrVrp06cKIESPo3r070cYe37AyvL29mfjdUkJD7zLk845s3GRDqTLQuo3kyJEEcRrhAbt2GddRC+Dbb/9b7mWs31+aKGlopIKjoyMLFixg5MiRzJ8/n/r16/PokQVPMpgo3t7efDtxCaGh9/lqxIfs3mNH5apQr77kzz8j9NeL/Q6orh/Tpsr8+dCwIcTGGr5tTZQ0NNKAEIKvv/6aRYsWcejQIapUqcKZM2eM7ZZV4unpyZix87l27RETv/2M02ccGVv/Nn9nycK6n38mVu07qRdQQF2Tpo69PWzfDqNGGb5tTZQ0NNJB586d2bNnDy9evKBq1aqsW7fO2C5ZLW5ubgwZOpmrV5/w+Wef4RQTw8D//Y8iRYowdepUnj9XqTpfNyyiplJ66NIFuneHb76BbdsM27YmShoa6aRq1aocPXqU4sWL07JlS0aOHJmsHpSGYXFycqLJ5MmUCQ/nhzVryJ07N5999hl58+Zl8ODBb9Tm0kgb06ZBqVLQuTPcuGG4djVR0tDIAHny5CE4OJgPP/yQsWPH0qRJE22eycjY2NjQsmVL9u/fz99//02jRo2YMmUKhQoVonXr1uzduzdj8067AHfgiMoOmzguLrBypVIYcPNmw7WriZJGEqNHj0YIYfB2a9asSc2aNQ3erq44OTnx66+/MmvWLHbt2kWFChU4fPiwsd2yTh48gNq1IWE4tXLlyixdupSrV68yZMgQgoODqVmzJmXKlGH27Nm8ePEi7badgaeAiWXTNgRFi8LFi9C7t+Ha1ERJQ0MHhBD07t2bAwcOYGNjQ0BAAFOmTNHWMxkaJyflJ/1rn3vevHn55ptvuHHjBvPmzcPOzo4+ffqQO3du+vXrl7ZgFSvIf/cusmdXHg8cUHpO+kYTJQ0NFfDz8+P48eM0btyYAQMG0KJFCx6aWqEaSyZzZqUOQ8uWKR52dnamW7duHD9+nAMHDtC8eXPmzJlDqVKlCAwMZNGiRURGRqZs28pFCRStHz0aunaFEyf025YmShbI0qVL8fX1xcnJidKlS7N+/Xqdhsi2bt1KtWrVcHZ2JkuWLLRs2ZILFy4kO+fy5ct07doVHx8fnJ2dKViwIH379uXx48fJzlu2bBm+vr44OjpSsmRJ1qxZk9G3aXJkzZqVNWvWMGXKFLZt20bZsmX5888/je2WxisIIfD392fhwoXcunWL7777jrt379K1a1dy587Np59+yj///JP8IndAYNWiJAQsXqzUXmrdWs+FAXUtXWvKmzWWQ9++fbsUQsgWLVrITZs2yd9++036+PjInDlzyqCgoHdeO2rUKKl8Jf5jy5Yt0sbGRtatW1euW7dOLl68WBYqVEh6eXnJmzdvJp23d+9eOXz4cLl27Vq5d+9eOX/+fFmkSBFZtWrVpHN27NghhRCyadOmcuPGjXL+/Pkyb968MkeOHKn6ZkjU+F4cP35cFitWTAoh5ODBg2VUVJQKnmm8k44dpRw2LN2XxcXFyT///FO2b99eOjg4SEBWqlRJzpw5Uz5+/Fg5yUNK+T9VvTVLDh+W0tFRylq1pIyOfvM4KpRDN7pw6HPTRZSCgt7cZsxQjoWHp3x8/nzl+IMHKR9ftkw5fv16ysfXr1eOnz//TrffSbVq1WTJkiVlfHx80r6jR49KIEOiVLFiRVm4cGEZExOTtO/KlSvSzs5ODhgw4K22YmJi5L59+yQgjx8/LqWU0t/fXxYvXlzGxcUlnXfw4ME0+WZI1PqxEh4eLvv27SsBWbp0aXny5ElV7Gq8hd69pRw7VicTDx48kFOmTJGlS5eWgHR0dJTt27eXL3K9kHHt4lI3YAUsWKAox+zZbx5TQ5S04TsLIi4ujqNHj9KmTZtkUXQVK1bEx8cn6bWUktjY2GRbSoSHh3P8+HHat2+PnZ1d0n4fHx+qV6/O3r17k/ZFR0czYcIEfH19cXZ2xt7ensDAQAAuXLhAXFwcR44coW3bttjY/Pe1q1q1KgUKFFDrIzApXFxcmDlzJps2beLBgwdUqlSJ8ePHq59xQENh1iwYMUInE15eXvTv359Tp05x7NgxevbsyY4dOzh1+xT71+1n0KBBnDx5UvlFb6V07QpbtkCPHvqxb5f6KdbJnj1vP+bi8u7jXl7vPp4377uPFyv2bt/exsOHD4mJiSFbtmxvHMueGEID7N27l1q1aiU7ntIf2ePHj5FSkjPnm3n7c+TIwbVr15JeDx8+nOnTpzNy5Ej8/f3JnDkzN2/epHXr1kRFRSX59qofKflmiTRu3JjTp0/z8ccfM2LECNauXcv8+fNTLdGuYTyEEFSoUIEKFSrw/fffE1Y9jMjLkUyfPp0ff/yRkiVL0qVLFzp06GCxP6reRcOGyuP160rB36Ag9WxrPSULwsvLC3t7e+7fv//GsXv37iU9r1ixIkeOHEm2pUTWrFkRQnD37t03jt29excPD4+k18uWLeP9999nxIgR1K5dm0qVKuHu7v6Gb6/6kZJvloqnpyfLli1j+fLlXLt2jQoVKjB69GhevnxpbNcsh2+/hYTeuZo4OjqSs2tOCvYsyJ07d5gxYwZZsmRh+PDh+Pj44O/vz7Rp01L8O7F0eveGZs3g9dgQXdBEyYKwtbXFz8+PVatWJev5HDt2jKtXrya9zpw5M35+fsm2lMiUKRMVK1ZkxYoVxMXFJe2/du0af/31V7JovoiICOzt7ZNdP3/+/GS+VapUiZUrVyZLyfP3339bVRqYdu3acfbsWdq1a8fXX39NhQoVOHDggLHdsgy8vCB/fv3Y7g9MUn5c/O9//+PAgQNcvXqVb775hhcvXtC/f39y585N7dq1mTVrVoo/DC2RX35RovGbNIFbt1QyquuklClv1hp9ByRF3/3+++/Sx8dH5siRQ9aqVeud174r+q5hw4Zy/fr1csmSJbJIkSLSy8tL3rp1K+m8Dh06SGdnZzljxgy5bds22bt3b1moUCEJyPkJESCJ0XfNmjVLir7Lly+fRUbfpYVNmzbJvHnzSkD26tVLhoWFGaRdjQwSn7ClwJkzZ+RXX30lixYtKgFpY2Mja9WqJWfMmCFv375tUDcNzYkTUrq6SlmmjDqBDkYXDn1u1ihKUkq5ePFiWbRoUeng4CBLlCghV69eLcuVKydbtmz5zutSEiUpFWGqWrWqdHJykm5ubrJ58+by/Gshgg8ePJDt27eX7u7u0t3dXXbq1EkePnw4mShJKeWSJUve8C0oKMgqRUlKKZ8/fy4HDBggbWxspLe3t/ztt9+SRU5qmAgLpJT2Usob7z4tPj5enjp1So4YMUIWK1ZMAlIIIf39/eX3338vQ0JCDOGtwdm+XUpvb02UNFFKIzdu3JCOjo5yzJgxxnbFLDDG9+LEiROyatWqEpDVq1eXJ06cMLgPZs+2bVIWLizlhQvq2z4mpRwmpbyf9kvi4+Pl6dOn5ZgxY2S5cuUkIAFZpkwZ+dVXX8mjR49a1A+Q58/VESVtTsnCiIyMpG/fvqxatYq9e/cyf/586tWrh4uLCz30FcOpoTPlypXjwIEDzJ07lwsXLlCxYkX69u2rpSpKD56eUKkS2OkhqLgC8A3gnfZLhBCULFmSr776ihMnThASEsIPP/xAlixZGD9+PH5+fuTNm5e+ffuyefPmt6c5MhNcXVUypKuqmfJmjT2lly9fypYtW8ocOXJIe3t76e7uLps1ayb//fdfY7tmNhj7exEWFib79esnbW1tpbu7u5w8ebJ8+fKlUX2yeuKllGFSyufqmHvw4IH87bffZKtWrWSmTJkkIJ2dnWXTpk3lzz//LK9du6ZOQwYGFXpKQrFjmfj5+cmjR4++9fi5c+coXry4AT3SMAdM5Xtx5swZBg4cyPbt2ylSpAgTJ06kZcuWRikvYvXcA3IA04FP1DUdFRXFnj172LRpE5s2bUqKlC1ZsiSNGjWiUaNGVK9eHUdHR3Ub1gNCiGNSypTDedOINnynoWGilCxZkq1bt7Jp0ybs7Oxo3bo1gYGBHDx40NiuWR96zBTu5OREw4YNmT59OiEhIZw9e5bvv/+eHDlyMHXqVOrUqYOnpyfNmjXjp59+4sKFC6S3M3Hu3Dn++OMPjh8/rv4bUBmDi5IQIq8QYqUQ4qkQ4pkQYrUQIl8arvMTQswRQpwXQkQIIa4LIRYLIXxSu1ZDw1wRQtC4cWP++ecfZs2aRUhICP7+/rRs2ZKzZ88a2z3rwQ7Igt4zhQshKF68OIMGDWLnzp2EhYWxbt06PvjgA86dO0e/fv3w9fWlQIEC9OjRgz/++IMHDx6kanffvn0sWbIEPz8/2rdvT1RUlH7fiA4YdPhOCOECnAJeAiNQolHGAS5AGSll+Duu/R6oBiwGzgC5ga+AbEA5KeUbVeS14TuNjGDK34sXL14wZcoUJk2axPPnz+nSpQujRo2iUKFCxnbN+Fy9Cg4OkDu38josDA4fhps34dkziI6GwYMzHghRGKgMLFHL4fQTEhLCjh072LFjB7t27eLJkycAlC1bljp16lCnTh0CAwPJnDlzsusePXrE/fv3+emnn3BwcGDy5MlvbSMuLg5bW9sM+afG8J1BAw9Q1kXHAYVf2ecDxAIDU7nWO4V9+YF4YExK11hjoIOG7pjD9+Lhw4dy8ODB0snJSdrZ2ckePXrIq1evGtst41KxopR//PHf6ytXpPT1lbJBAym7dZPSwUHKu3czbr+ylLK+zl6qRkxMjDx06JAcP368rF27tnR0dJSAtLW1lX369Hnj/NOnT8v27dvLn3/+WUopk2XrT+TKlSvy008/lfny5ZNt2rRJd2Z7zDAkvDlwSEp5OXGHlPIqcABo8a4LpZRv9FGllNeAByi9Jg0Nq8HT05NJkyZx5coV+vbty4IFCyhSpAg9e/bkypUrxnbPONy7B6VLK8+jo8HHRymZ2rcvzJsH7u6gS/ofL8CEIvTt7OyoUqUKX3zxBX/++SePHz9m586dDB06lEqVKiWdJxNGwy5cuEBUVBQlS5YESAqYSUz7df78eQYPHkxISAhbtmzB3d2dadOmJbNhCAwtSiWB0ynsPwOUSK8xIURxlOG7czr6paFhluTMmZNp06YREhJCnz59WLhwIUWLFuX999/n3Dkr+7Nwd4fbt5XnDg7Ko7095MihPM+WDR7pMClkYqL0Os7OztSpU4fx48fTrVu3pP2J4hMaGoq9vT3FEsoQJO5PFJx58+aRKVMmJk6cSIkSJejbty+nT59m165dBo34NLQoeQCPU9gfBmRNjyEhhB0wC6WnNC+lcx48eJAs6eicOXPS66+GhlmQJ08epk+fzpUrV/j0009ZtWoVJUqUoFWrVhw6dMjY7hmGOnVg4ULYtw+uXFHmj3x8wM1NOe7goHtPyUxLoj99+pTr16/j7e39RmmbxPmjXbt2Ua1aNYoWLQpAhQoVuHPnTqqCNGfOnFcTO3vp7Kyu43/p2YBo4NsU9o8DYtNpaxYQA9R/2znanJJGRrCE78WDBw/kV199JbNmzSoBGRgYKNetW5fiPILFEBYmZYsWSmbQ9u2lrFlTyr17/zu+f7+UN29m3P54qdxZInT00wg8efJEduvWTf74449SSiljY2OllDIpzdHNmzdl4cKF5cGDB5OuefHihbSxsZE30/GZYYZzSo9JuUf0th5UigghvgV6Ad2klNtV8k1Dw2Lw8vJizJgxXL9+ncmTJ3Pt2jVatGiBr68vM2fO5MWLF8Z2UX2yZoW1a2HmTChVSin2ExOjlEm9eROqV/8vMi8j1ATGoIRWmQn//PMPTZs2pXXr1pw6dYqCBQsC//WOEntBp0+fJk+ePGTKlCnp2v3795M1a1Zy5MhBdHQ0FStWpFevXsybN4/Tp08nK2ejJoYWpTMo80qvUwJI06ILIcSXwFDgUynlQhV909CwOFxdXfnss88ICQlh6dKlZM2alY8//pg8efIwaNAgywuKCAmB3bvh7FlYsAAmTVLKpH/wAYwfDxERGbftj7IIJVNqJ5oOxYoVo3PnzuTJk4eoqChatWrFxx9/zPPnz9m7dy/R0dEASQU7Hz/+r2+wfPlygoKCsLW15dGjR3h7e7Ny5Up69OhB6dKlyZo1K7Vr12bYsGGsXr2aGzfeWJWTMXTtaqVnAz5DCf8u+Mq+AijDcIPScP2nKGubvkhLe9rwndJNT+yqa6QNS/5exMfHy7/++ku2b99e2tnZSSGEbNy4sdywYYP5f09u3JCyUSMpK1WS8tdfpdyzR8ojR5Rhux9+kLJuXSknT864/RiplK54ppK/RiAiIkJeuHBBPnv2TJYvX14eOXJESqnkzAwKCpIzZsyQUkr5008/ybJly8pt27ZJKf8b5ouPj5fnz5+Xv//+u/zf//4n/fz8pL29vQQSH82rdAXKb4zLwL8oIeDNURbTXgFcXzkvf4J4jXxlXweUjvMWoOprW4mU2tNESZpcrSJDEBYWJps0aSKLFCkiy5QpI+vVqycvXbqU5uut4XshpZS3bt2SI0eOlDly5JCAzJcvnxw7dmyy4o1mxW+/SVmjxtuPz5kjpS5/C2elcmdZmnETpsy2bdtk3rx5ZbZs2aS/v79cvny5jImJSfW6yMhIeejQIbl06VLzEyWpiEs+YBXwDHgOrAUKvHZOgYQe0ehX9v2WsC+lbU9KbWmiJOX58+ffKMhn6Tx+/Fju2LEj6fXUqVPTJczW8L14lejoaLlixQpZp06dpKqpzZo1k2vXrpXR0dHGdi/trFolZfnyKR8LD5eyRw8pu3TJuP3nUsrZUsrLGTdhDly+fDnD9wyzFCVDbpoo6caSJUskIPe+GsEkpbx7964EZLZs2d645qeffpLAG6Uybt++LYUQct++fXr1OSWOHDki8+fPn+bzrfl7cfnyZTls2LCk3lO2bNnkgAED0r2y3yhcvSpl06ZSduyoZHZYsULpHQ0fLmWdOkpknj4KAFooGSlAqIYoaVnCNd5KjRo1AAgODk62Pzg4GBcXF+7fv8/58+ffOObp6Zm0ajyRdevW4e3tjb+/v36dToEpU6bQosU7E4ZoJFCoUCG++eYbbty4wYYNGwgICOCnn36iXLlylC1blkmTJnHz5k1ju5kyBQrA3LnKgtlhw2DsWFi8GE6cgPLl4auvIGENTob5Fzif6lkWgbFKpOihRKOGpZA7d24KFSqUoijVrl2bc+fOERwcjK+vb9Kxffv2ERAQ8MYXeu3atTRr1gwbG8P+Dvr666+5cuWKtnA6ndjZ2dG0aVOaNm3Kw4cP+eOPP1i4cCFDhgxh6NCh1KhRg44dO9KmTRu8vHRfL6ka2bPD778rz8PDlWg771fKxcbHgy7fwXZAWeAPXZzUeBdaT8kCWbZsGb6+vjg6OlKyZEnWrFlDzZo1qVmzZrpt1ahRg4MHDxIbG5u0Lzg4mMDAQAICApIJ1qVLl7hz5w5BQUHJbDx79ozdu3fTsmXLpH2nTp2iVatWeHp64uzsTLFixfjmm2+Sjo8ePRohBOfPn6dBgwZkypSJfPnyMX/+fAAWLlyIr68vrq6u1KpVi5CQkDd8HzduHJs3b2bLli24uLik+71rKHh5efHxxx9z6NAhLl68yKhRo7h79y59+vQhR44cNGjQgLlz55pO6fYbN2DVKiUcfOxY6NIFPvpIEStdfxSZeKohS0ATJQtj586ddOrUiSJFirB69Wo+//xz+vfvz4ULFzJkr0aNGrx48SKpONiTJ084ffo0gYGBBAYGsm/fvqRzEwUqcdgvkc2bN+Pg4EDdunUBOHz4MNWqVSMkJITJkyezadMmBg4cmOKwULt27WjSpAlr166lYsWKdOvWjS+++IKff/6Zb7/9lvnz53PhwgU6deqU7Lqvv/6aDRs2sH37drJkyZKh967xJkWKFGHUqFGcO3eOEydO8Pnnn3P58mV69uxJjhw5qFu3LjNnzuR2Yg46Q3P9OvToAQMHwp498PQpuLhAXJyyXumbb5QkrRnFEyWxmYb+0HVSypQ3nQIdgoKknD9feR4drbxeuFB5HR6uvF62THn95InyetUq5fWDB8rr9euV13fuKK+3bFFeX7+uvE6MEAsJUV7v2aO81iFazt/fXxYvXjxZOpmDBw9KIEOh4VeuXJGAnDRpkpRSyvXr10tnZ2f58uVLeeHCBQkklUx4//33pZub2xvrXdq3by/btGmT9DowMFDmyZNHhoeHv7XdUaNGSUD+/vvvSfvCwsKkra2t9PDwkE+fPk3aP3XqVAnI0NBQKaWSoh+QhQoVkmXLlpVly5aVqX0XXsWaAx0yQnx8vDx+/LgcPny4LFq0aFJUbJUqVeSECRPkmTNnMjRpniEaN5byf/+T8sWLN4/9/beU2bNL+fBhxu13k1Lmyvjllg5aoIPGq8TFxXHkyBHatm2bbO6matWqFChQIEM2fXx8yJMnT1IvKDg4mCpVquDg4EDRokXJli1bsmPVq1dPViAsOjqaLVu2JA3dRUREcODAATp37pymIbVGjRolPc+aNSvZsmWjatWquCUm2YSkOa3EFeUlS5ZESsnly5c5efIkJ0+e5F3FHjV0QwhB+fLlmTBhAufPn+fMmTOMGzeOuLg4vvjiC0qWLEmRIkX47LPP2LFjBy9fvtSfM3//DZ9/DplSSLtQubIyp6RLpnBvlOE7w1VysDq0QIe3sWfPf8/t7ZO/dnFJ/jpLluSvvbySv86RI/nrvHmTvy5YMPnrhNTy6eXhw4fExMSQPXv2N46ltC+t1KhRgy1btiClJDg4mAYNGiQdS5xXql27NqGhofTu3TvZtbt27SIiIoKmTZsCShqT+Ph48uTJk6a2s2ZNnirRwcEhxX2ASZd4thaEEJQoUYISJUrw5ZdfcuvWLTZs2MCGDRuYPXs2U6dOJVOmTNStW5dGjRrRsGFD8ufPr54Dfn4wZw506ACeniAEvHgB167B9OlQq5ayP6N4oaSVfg64pXKuRobQRMmC8PLywt7ennv37r1x7N69exn+4w8KCmLJkiUcOnSI48ePM27cuKRjgYGBzJw5k7179wJvzietXbuWoKAg3N3dAUVkbGxsuHXrVoZ80TAvcufOTZ8+fejTpw8RERHs2rWLTZs2sWXLFtatWwco+dkaNGhA/fr1CQoKwtXVNeMNTp+uzCnt2vVf+HdEBLx8qdRb+vxz3UUJlN6SJkp6QRu+syBsbW2pVKkSK1euTKomCfD3338TGhqaYbuJQvPtt98ipaRatWpJxwICArh06RLLly/HxcXljYqX69evTxZ15+LiQkBAAIsWLSIyMjLDPmmYHy4uLjRt2pSff/6Zq1evcvbsWX788UcKFCjAnDlzaNq0KR4eHgQFBTF27Fj++usvYmJi0tdIkSKwdy9MnKj0mvz8oHVrZd3S3LlQpoxub+JVUdLQC5ooWRhff/0158+fp2XLlmzatInffvuN9957jxyJ1TcTCA0NRQjB6NGjU7Xp6+tLtmzZ2LBhA+XLl0/2Szbx9YYNG6hatSr29vZJx/7++2/u3LmTTJQAvv/+ex49ekS1atVYuHAhu3fvZt68efTr10+n965hPgghKF68OAMGDGDr1q2EhYWxY8cOBgwYwPPnzxk1ahTVq1fHw8ODxo0bM2nSJI4ePZpsacI7qV4dWrWCGjWUchWxsfDsme6OJy550kRJb2jDdxZG3bp1Wbx4MaNHj6Z169YULlyYKVOmMHXq1GTnhYeHA7whVm+jRo0arFy5ksDAwGT7bW1tqVatGjt27Ehx6K5ixYpvzB9VqlSJAwcOMHLkSPr168fLly/Jnz8/H330UXrfroaF4OzsTN26dalbty4TJ07k0aNH7N69m927d7Nr1y62bNkCQObMmQkICKBGjRrUqFEDPz+/pDnFJM6dg/nz4fRpiI5W5oTt7CAsDBo1UirSOjllzNGiwEKUBbQaekFIXWL2TRw/Pz/5rqirc+fOUbx4cQN6ZDwSF87uSQiomDNnDl9++SXXrl3T28JSX19funTpwogRI/RiX19Y0/fCXLh79y579uxh79697N27l3PnzgHg5ORElSpVCAgIoHr16lTPlQu3QYOU4n59+0L+/ODsrMwpHTkC69dDkybQv7+R35FlIoQ4JqX008WG1lOyUvbu3cuAAQP0mung9bx4GhoZJUeOHHTo0IEOHToA8ODBA/bt28e+ffvYv38/3377LXFxcfQGPsiUifmdOlEtMpKq7u4UK1ZMWSJRpYpibMMG3UTpIEqQQ0rlSjV0RhMlK2Xx4sXGdkFDI8N4e3vTunVrWrduDcCLFy84fPgwT2fNwmP7dlasWMEvv/wCgLu7O5UrV6ZG2bJ8cPQonrly4axL422ARsA8Xd+FRkpoomQl7Hl1HZSGhoXh6upK7dq1lUzh0dGEOThwp0IFLl++zJ2zZ4k+fhyf7ds5CAwGxP79VKpUiUqVKuHn50eFChWSli2kyiogm97eitWjiZKGhoblULAgTJmC+OQTcs2fT67MmZX1SYGBvCxdmn8KFeLTBw84fPgwR44cYeXKlUmXFipUiAoVKlCxYkXKly9PhQoVUs6AXu3NXRrqoYmShoaGZSElbNqkROC9954SDu7mhiNQKWFL5NGjRxw9epRjx45x7Ngxjhw5wooVK5KO58mTh3LlylG+fHnKli1L2bJlKfiwIDZXbaCjod+YdaCJkoaGhmWRKxfs3AklSyopwRKRUkk79Aqenp40aNAgWeqssLAwTp48yYkTJ5K2LVu2EBcXB8DPdj/TSXZiyN4hlC5dmjJlylCqVKk30l9pZAwtJFwL/dV4De17ofE6kZGRnDlzhlOnTpFzTk4aH25MNvdsPHjyXx2L3LlzU6pUKUqVKkXJkiWTcgBmzpzZiJ4bFi0kXENDQyMl9u5VEiWXK6eKOWdnZ/z8/PDz84OXwGG4d/Yet+Ju8e+//yZtZ86cYcaMGcmSA+fLly9JoIoXL560eXh4qOJbWpBSGq28eXrRRElDQ8Py+OADJcXQggXq206IfRCPBHlK5SFPnjzJSqzExcVx5coVzp49y5kzZzhz5gxnz55lz549ycQqW7ZsFCtWDF9fX4oVK5a0+fj4YGen7q1ZCMGCBQs4fPgwRYsWpVOnTqZVxv4VNFHS0NCwPFavBn31RBLz372lAq2trS1FihShSJEitGjRIml/XFwc165d49y5c5w7d47z589z4cIFVq9ezaNXajzZ2dlRqFAhihYtmmSnaNGiFC5cmDx58iSrlZZWxo0bx9atWylXrhwbNmzg4sWL/Pjjj2+kaAoODubEiRNkz56dYsWKkT9/foP26EATJQ0NDUukQgX92U5FlN6Gra0tBQsWpGDBgjRp0iTZsUePHnHhwgUuXLjAxYsXk7YdO3Yk6105OjpSqFAhChcuTOHChSlUqFDSlj9//mQJkRO5ffs233//PStXrqRu3brcunWLMmXK0KtXL8q8ljV9/fr1zJ07l2LFinH37l2ePHnCsWPHKFy4cPrerA5ooqShoWF5HD8Od+4oee7UJoOi9C48PT3x9/fH398/2f74+Hhu3brFpUuXuHTpEpcvX+by5ctcunSJHTt2JCv/YmNjQ968eSlUqBC9e/fmvffeA2DHjh24u7tTt25dQElq27x5czZs2ECZMmWS5psiIiKwtbXliy++YMiQIeq9uXSiiZKGhoblMWMGbNsGN2+qbzuxRqCKovQ2EoUmb968SsaKV5BScufOHUJCQrhy5QohISFJzyMiIpLOuXDhAqVLl0667uXLlzg7O/PkyRNAGVa0s7Pj+fPnXLlyhb1791KuXDl8fHwoXLiwwQMkNFHS0NCwPEaOhKFD9WPbDsiKQUTpXQghyJUrF7ly5XqjpMyr51y/fp3cuXMn7YuMjOT58+dJJWUSRUcIQUBAAAcOHGD06NE4ODjw1VdfUadOHaSUPH/+nMyZM+tdpDRR0tDQsDzy59ev/R1A2kqRGZ2nT58mE6WbN2/y7NkziiaUi08UGQ8PDz7++GP6J2RQHzp0KGPGjKFEiRLkzJmTQoUKER4eTp48ecidO3fS46ubGmiipGFxPH78mK5du3Lx4kWcnZ3Jnj07M2fONOhkrYaRuXoV9u2DNm0gUyb17VdU36S+KFmyJP/88w8vX77E0dGRhQsX4ubmRsWKyd9EYhh6REQELi4udOjQgXPnznH69Gly5MjBl19+yc2bN7lx4wY3b95k37593L59O6lkvVplcDRR0rA4hBB89tlnSRO706ZNo0ePHlqmdGvi4EFlrVKVKlCsmPr29wJXgQ/VN602Q4cOpVu3bjRr1gwfHx8OHjzIDz/8gI+PD0BSiPmVK1coWLBgkrj8888/xMTE4OnpmfQ39Trx8fE8fPiQW7du8eTJkzfmvTJC+gPeNcyC7du306hRIzw9PXFycqJYsWIMGzYsaXIzvYwePRohBLGxsRk6786dO9jY2LB///4MtZ8eXo00AvD39yc0NFTv7WqYEE2awOXLStZwfbAE0NOUldpkzZqVb7/9loYNG5IpUybmzZtHvXr1uHDhAm5ubty6dQuAmTNn0r17d3766ScWLVrEhAkTCAgIoESJEm+1bWNjQ7Zs2Shfvjy1atVSxV+tp2SBTJgwgS+//JKWLVsyd+5cPDw8OHbsGBMnTmT16tXs3r1btfHftLJu3Tq8vb3fCHk1BFOmTEm2iFHDCsiSRdn0xTfARP2ZV5vEbBGv73v8+DG2trYANG3alM2bNyclnx0xYgRdunTRou80dGP37t2MGDGCzz77jMmTJyftDwoKolWrVlSsWJGPPvqI7du3G9SvtWvX0qxZswytRteFr7/+mitXrjBnzhyDtqthZJ4/hxUrwN8ffH3Vt2/YJAd6I1GQAGrWrEnNmjWN50wC2vCdhfHdd9/h4eHBN99888YxHx8fhg0bxo4dOzh+/LjObW3duhVXV1c++eQT4uPj33res2fP2L17Ny1btky2/9SpU7Rq1QpPT0+cnZ0pVqxYkt+Jw4Dnz5+nQYMGZMqUiXz58jF//nwAFi5ciK+vL66urtSqVYuQkJA32h03blzSLz+1JmE1zIQXL6B7dyUxqz44BwwDbuvHvDWjiZIFERsby969e6lXrx5OTk4pntO8eXMAdu7cqVNbCxYsoHnz5gwbNoyffvrpnT2gzZs3/7+9c4+Tqrjy+PcHiMoqAXkE4woYoogQH0GNZF0hkkgQY9BFk6hA8EN280ICkTVBP2ZQE0k0IZtdwwejRgUEI9ERQohEgVkkPNSYxKCg8nQUVkGQxyCCc/aPug09Tc9Mz/S7+3w/n/vp7rpVdevc212nq+qcU7Ru3brOOs+qVavo168f69atY8qUKcyfP5/x48dTneDseNVVVzFkyBAqKyvp27cv119/PRMnTmTq1KlMnjyZ3/zmN6xdu5ZrrrmmTrlJkyYxb948Fi5cyEeyOY3jFCadO8PGjTBiRHbqf4MwfXfkfyEnTXz6rj4GpJDnMuDGuPxfi45twLAUyifm/x7wRWAt0AyDoe3bt7Nv3z66d+9eb57YuU2bNjX9AhE//elPufnmm5k6dSqjR49uNH9lZSWDBg2qoyhvvPFGOnTowIoVKw6NYpJZ7kyYMIERUcdy7rnnMm/ePKZNm8aGDRto27YtEIwoxo4dy6ZNm+jWrRurV6+moqKCHj160L9/fyCYuza0t5ZTYrRsmV1fpViooW3Zu0S54kqpTGnu2s64ceO47777mDNnTkrGAx988AELFizgnnvuOZRWU1PDsmXLmDBhQqPTavFbArRv3/6QpU9MIQGcHq0ZvPHGG3Tr1o3evXtTyptXOikycyZ07Ahxu8pmjJhSejvzVZc7rpTqY0ka+Ts2sXxi/ma6VcTWZhoyf46da6713axZs+jTp0+dqbiGWLRoETU1NVx22WWH0nbs2EFtbe2hMCcNkbjFdOvWrZOmAXWiKTsOt98OZ52VXaWU51BDpYivKZUQrVq14qKLLjoi3H08c+fOBTg0rdVUnnnmGTZv3szgwYPZs2dPo/krKyvp378/7dq1O5TWvn17WrRoccg/wnGywtKl8OCD2an7aKAtrpSygCulEmPChAls376diRMnHnFuw4YN/OQnP+Hss8+mX79+zaq/d+/eLFmyhNdee61RxWRmzJ079wiruzZt2nDhhRcyY8aMOqH3HSejdOoExx6bvfo740opC7hSKjEGDhzIpEmTmDJlCldeeSWVlZVUVVUxZcoULrjgAmpra5k9e/ah/Bs3bkQSFRUVKV+jV69eLFmyhHXr1jFo0CB27959RB5JrFy5ki1bthyhlADuvvtutm/fTr9+/Zg+fTqLFy/m/vvvZ8yYMc0R23GOZOFC+NWvsld/J1wpZQFXSiXIrbfeyoIFC9i7dy+jRo1iwIABjB8/nq5du/LSSy/V8ezeu3cvAF26NC3kcc+ePamqqmLTpk1ccskl7Nq1Cwhh8Vu2bEnLli0PmXEnWzs677zzWLZsGSeffDJjxozh0ksv5a677kppnclxUuKJJ+CHP8xe/Z1wQ4dsYGYle/Tt29ca4uWXX27wfClx7bXXWps2bWz58uV10qdNm2YdO3a0vXv3ZuQ6V1xxhfXo0cPMzHr27Gm33357RurNJeX0vShp9uwxe//97NU/2sy6ZK/6YgR43tLst936rkx44IEHqK6uZsiQITz77LP06tULgKqqKsaNG5d2xIPnn3+epUuXHnKCBVizZk3a7XacZpONLSvi+TlwT6O5nCbiSqlMaN26ddKtG2bOnJmR+q+++mpqa2sZO3YskyZNykidjpMW//gHzJkDN9wAJ2QhWN3xma/ScaXkZIj169fnuwmOU5dXXoFJk2DYsOwopZeAewkx8HIbdL+kcUMHx3FKkyuugAMHoE+f7NS/FZgBbMlO9eWKj5QcxylNWmW5e/s8sCO7lyhHfKTkOE5psnMn3HILrFqV75Y4TcCVkuM4pcnBg3DnnfDii9mpvxb4MmEKz8kYZT99Z2Y53+7XKVzMo4uXDh06BMWUrd93C+ApoAtwXXYuUY6U9UjpqKOO8thrTh327dvH0Ucfne9mOJlAyp5CitEZ+L/sXqLcKGul1LlzZ958801qamr8H3IZY2YcOHCAd999l+rqajp06JDvJjmZYvJkePjh7NXv8e8yTllP38U2invrrbc4cOBAnlvj5JNWrVpxzDHH0LVr13q3kneKkMcegzPPzN626J3xLdEzTFkrJQiKKX4XU8dxSogXXshu/Z2AP2f3EuVGWU/fOY7jpEVnYBvBEs/JCDlXSpJOljRH0nuSdkl6XFLXFMseI+kuSVsk7ZO0XNJF2W6z4zhFyiOPwE03Za/+jxIU0vbsXaLcyKlSktQGWAScDowEhgOnAoslpRLS937g68CtwGWEAB9PSTo7Kw12HKe4efFFmD8/e/V3il7d2CFj5Hqk9HXg48BQM6s0syeBy4FuwH80VFDSWcA1wDgz+7WZPQNcDWwGbktW5p13yuObcu+99+a7CTmhXOSE8pE163LedVeIFp4tTiQEY61pOFu5PE+gY7oV5FopXQ6sMLPXYwlmtgFYBnwphbIHgEfjyh4EZgODJB3hXLJt27ZMtLngKZcvfLnICeUja9HL2R+oBs5tOFvRy5k6nRrP0jC5Vkq9gWR/W1YDZ6RQdoOZJf4nWQ20Bj6RfvMcxykpVqyAUaOgTGZNSoFcm4SfQPK4uu8C7dMoGztfh5qamv2SPoxLeodgK1NqdJRUinIlUi5yQvnImhs5H3ww65dohFJ+nh05PEJqmW5lJe2nZGbuBek4jlNE5Hr6bgfJR0T1jYJSLQuHR0yO4zhOkZJrpbSasDaUyBnAyymUPSUyK08s+wHw+pFFHMdxnGIi10ppLnCBpI/HEiR1B/4lOtcQ84CjgKviyrYi7Giy0Mz2R2nNds4tJiQNkGRJjp35bltzkfTPkv47coquieTpniRfUTtRN0HOZM/XisUvT9IwSb+TtCl6Tmsl3Snp+IR87SXdJ2mbpL2Snpb0yXy1u6mkIqek7g08z3Z5bH7KSBokaZGkrZL2S6qW9FtJZyTkS6sPVi6jY0cOsn8D9gG3AAbcDhwPnGlme6J83QhhDm8zs9viys8GBgETgA3ANwlOtJ8xs79Eo6i/Afvj6r8DaBPVvzcXcuYCSQOAxcANwHNxpw6a2fP5aFO6RDI9CrxAWDC9BDjFzDYm5JsJDCF8D9YD3wYGA/3M7K85a3AzaYKcBjwITEuo4u9JrFALDkkrCH6ETxIMp88BKoA1hN9srcJmZkuB7oTnuQP4AWFG5Wwzq859y5tGinJ2J/RZd3LkH/DnzOxDChxJXwU+BawkGI11Bb4PnAx80sw2ZaQPNrOcHpEgvwN2AbuBSqB7Qp7ukTAVCenHAj8HtgLvRzdnQNz5scCHwCfi0k4BDgLjcy1rlu/jgOgefS7fbcmgTC3i3o+O5Ev8bpwVpY+KS2sFrAXm5luGTMkZnTPgjny3Nw05OyVJGxHJdXH0+UvR58/G5fkIYY34l/mWIYNyxvq00flub4Zl7xnJ9b3oc9p9cM5j35nZZjP7NzNra2bHm9lQS/iHaGYbzUxmVpGQvs/MxptZFzM7xsw+bWZL4rKk45zr5BkzSyWsZZOdqAuNFOUseswsmXNQbFR/UvR6OfCWmS2OK/ceYbq+KH6zKcpZqsSi/h2MXtPug0stSng6zrnFykxJH0raLumRUlw/S6DcnKi/Gc3f10Tz+f+a7walSf/o9ZXotaHfbFdJx+WkVZknUc4Yd0o6GK23zC2mtbMYklpKai3pVMLU8lZgVnQ67T641PyU0nHOLTbeA34GVBGmQs8BJgLLJZ1jZm/ns3FZpMlO1EXMDOD3wFuE+JATgEWSPp8wQ1AUSDqJEKfyaTu87nkCsDFJ9tjzbA/syX7rMkc9cu4ndOALCesxpxN+r3+WdL6ZJSqvQmYl0Dd6/zphijLW36TdB5eaUiobzOxF4MW4pCpJ/wusIhg/3JKXhjkZw8yGx31cKulJwr/QO4AL89Oq5hGNeJ4kTPOMynNzskZ9cprZFuAbcVmXSvojYQRxM3BdLtuZJsOBtoTg2jcCf5J0YeIyTHMptem7dJxzix4z+wvwKnBevtuSRcrWidrMdgPzKbLnK+lYwhrRx4FBVteirrHnWTS/20bkPAIzewN4liJ7nmb2ipmtNLNZwEDgOIIVHmSgDy41pZSOc24pkTs7/9zjTtRF9HwlHQXMIcTRvtTMXkrI0tBvdrNFbiKFTgpyNkTRPM9EzGwn4TcXW8tNuw8uNaWUjnNu0SPpXIKJ5qp8tyWLpOREXYpIakvwyyuK5yupBTATuJiwh9qKJNnmAidJ6h9Xri3wRYrkN5uinMnKdSVMwxbF80yGpI8S1sfWRUlp98E5dZ7NNqk655YCkQPpBuAvwE6CocMPCNuNfcrMijIisaRh0duBhDn4bxEWht8xs6ooT4NO1DlvdDNoTE5JNxL+YCzmsKFDLG2gmS3NfaubhqSpBNl+RDDYiKfazKqjDv1ZggNmvPPsmcBZ0RRXQZOinD8jDAKWE55zT4KcHwE+bWZrc9jkZiHpCUJ/83eCcdVpwDigC3C+mb2akT44385XmT5IwTm3FA7CF/rvBCu8A8AbwL3AifluW5pyWT3Hkrg8DTpRF8PRmJyEkcIywlYrBwj+IHOjH3/e25+ijBsbkLMiLt8JwAOE9cAa4BmCQsq7DJmSE7ie4Lu0I3qeW4FHgJ75bn8T5LyJEIVkZ/Sc1hIsCrsn5EurDy6pkZLjOI5T3JTampLjOI5TxLhSchzHcQoGV0qO4zhOweBKyXEcxykYXCk5juM4BYMrJcdxHKdgcKXkOI7jFAyulBzHcZyCwZWSUxRI+rUkkzQlg3VWSMqK93gqdUuqlLSjvt1yJR0vaa+kB7PZxih2YFaRdKKkWklFteWGk3tcKTkFT7QlwNXRx2sy2IneB/TLUF3N4SGgHSFuXzKGAW2ifMXOlwgx3/6c74Y4hY0rJacYGErYVOwPQGfgC40VqG/0EX/OzKotxYjOWWI+IabdiHrOjwA2A0ty1aAsMhSYZ2a1+W6IU9i4UnKKgZGEQJZfI0QfHhl/Mm4aqo+kpyTtAX6b6rno/VVRvjMTLy7pD5L+Fvf5E5KmS9ogaZ+k9ZKmSkppu+cYZvYBMAsYLKlDwjW7Av2B6ZbDAJWSviBpj6T/kdQi7v6dHt2/vZI2SxoV5R8uaU1UZrGkHknqbAt8lhCYE0mnSXpC0tuS3o/qeywX04hO4eNKySloJH0M+BzwqJm9Q+jYvliPAngSqAIuBxLXnho6B2GfpvdI2JY62i/mEuDhuOSPEaKyf5ewhcZthC0o/pC6ZId4iLA/1FcS0q8DlHDdrCJpBCES+WQz+07CqOYxwshuKCFS9AOSfkzYNuT7hK2/exIiXydyKWEDxqejz/OBk6Kyg6Ly+/H+yIHS27rCj9I6gP8kbAHQL/o8KPr8jbg8FVHa2CTlGz0X9/nXQDXQIi7tu8BBGtgSBGhF2KzNgHOS1d2IjKuBlQlprwDLs3xvY/emVXSfDwCj68kzIi6tfXRPtgNt49JviPJ2S6hjNjAnet8xynN5vr9bfhTm4f9MnEJnJPCamS2PPj9N2PRuZJK8TzRQT0PnYjxM+Ad/cVzacOAZM9sSS5DUWtLEaNpqH6Ezj2261zOF6yTyEHC+pNOi+s8n7OaZKwOHKcAkYJiZ3VdPngWxN2a2A3gbWGFmu+LyrIleT44lSGoNDCaauiMosvXAZElfl3RqRiRwSgZXSk7BEm3vfgbwuKR2ktoRdrB8nLDl8mkJRbZQPw2di/EsYcO24dH1ewGf4sgptDsJI4gZwBDgfODK6NwxKVwnkRlALYcNHkYQprMebUZdzeGrwD84PL2WjB0Jnz+oJw3q3oOLCRaEv4do6AifB54n3MdXozW5bzav6U6p4UrJKWRio6GbCB1g7PhOlJ5otdaQQUCjxgJRhzkDuFJSG4Jy2sORo6yvAA+b2R1mtsjMniPsxtkszOwt4E/AddHI4ssES7U6nb6kzpJmS5omqY2kb0VGGJc099oRAwm7hS6QdFyadSUyFKgys52xBDNbb2YjgE7AOcAi4FeSBmf42k4R4krJKUiizvmrhK3OP5vk+CswXJIyfOnpwHGEkc+1wONmVpOQpw1hyi6eUWle9yGgG2H00JHkU3c3AbcCiwkjj/MJ9+ja6H41l9XAAOBUMqiYomdzOYen7upggb8C46OkPpm4rlPcuAmmU6gMAToA3zOzJYknJU0DphI604xhZq9KWglMJqwvJbN++yMwUtJLwOsEBfaZNC9dCewCxhHWa/6YJE8LM3uVMOX1XYKV3HuSngO6EHyakNQd2ABMMrOKVC5uZq9IGkBQeE9J+oKZ7U5DHoBPAycSp5Qik/v/IkxNvg60JJj6HySMmJwyx0dKTqEyEthNMEVOxiyS+CxliOkEhfQmoZNOZAzBdPpHhM71eMKIpdmY2T6C/5SAR8zsYLJsknpEymM/UBFFuzgX2BqX75+i1600ATNbS/CN6gYsjPyL0mEo8IKZVcelbSUoz/GEeziLYGJ/mZm9kOb1nBJAYRrdcZxCR1IX4BfAh8C3CaGXrgZ+aWZz4/L9O0Fhdksy9ZgzJK0BZpjZHflqg1N8uFJynBJD0kxgtZn9ON9tcZym4krJcRzHKRh8TclxHMcpGFwpOY7jOAWDKyXHcRynYHCl5DiO4xQMrpQcx3GcgsGVkuM4jlMwuFJyHMdxCob/B5fByOBKAQDRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/neptune/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/neptune/'+runID+'LD_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'stag_pres_atm_max_array.txt')\n",
    "\n",
    "\n",
    "f1 = interpolate.interp2d(x, y, np.transpose(Z1), kind='cubic')\n",
    "g1 = interpolate.interp2d(x, y, np.transpose(G1), kind='cubic')\n",
    "q1 = interpolate.interp2d(x, y, np.transpose(Q1), kind='cubic')\n",
    "h1 = interpolate.interp2d(x, y, np.transpose(H1), kind='cubic')\n",
    "#s1 = interpolate.interp2d(x, y, transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   30,  310)\n",
    "y_new =  np.linspace( 0.0,   1.0 ,110)\n",
    "z_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "z1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "g1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "q1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "h1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "#s1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "for i in range(0,len(x_new)):\n",
    "    for j in range(0,len(y_new)):\n",
    "\n",
    "        z1_new[i,j] = f1(x_new[i],y_new[j])\n",
    "        g1_new[i,j] = g1(x_new[i],y_new[j])\n",
    "        q1_new[i,j] = q1(x_new[i],y_new[j])\n",
    "        h1_new[i,j] = h1(x_new[i],y_new[j])\n",
    "        #s1_new[i,j] = s1(x_new[i],y_new[j])\n",
    "\n",
    "\n",
    "Z1 = z1_new\n",
    "G1 = g1_new\n",
    "Q1 = q1_new\n",
    "#S1 = s1_new\n",
    "H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "\n",
    "\n",
    "Zlevels = np.array([0.5,1.0, 2.0])\n",
    "\n",
    "Glevels = np.array([30, 50])\n",
    "Qlevels = np.array([5000])\n",
    "Hlevels = np.array([800])\n",
    "#Slevels = np.array([0.8])\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "#plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "#plt.xlim([0.0,30.0])\n",
    "#plt.ylim([0.0,0.4])\n",
    "#plt.tight_layout()\n",
    "#plt.contourf(X, Y, Z, levels=levels)\n",
    "\n",
    "\n",
    "#plt.axvline(x=25.0,linewidth=3, linestyle='dotted' ,color='red',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(LV$'+r' '+r'$C3$'+r' '+r'$limit)$')\n",
    "#plt.axvline(x=13.1,linewidth=1, linestyle='dotted' ,color='cyan',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(Chem. OI)$')\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([6.25,6.25])\n",
    "rcParams['font.family'] = 'sans-serif'\n",
    "rcParams['font.sans-serif'] = ['DejaVu Sans']\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=12, colors='black',fmt='%.1f',inline_spacing=1)\n",
    "ZCS1.collections[0].set_linewidths(1.5)\n",
    "ZCS1.collections[1].set_linewidths(1.5)\n",
    "ZCS1.collections[2].set_linewidths(1.5)\n",
    "ZCS1.collections[0].set_label(r'$TCW, deg$')\n",
    "\n",
    "\n",
    "GCS1 = plt.contour(X, Y, np.transpose(G1), levels=Glevels, colors='blue',linestyles='dashed')\n",
    "\n",
    "plt.clabel(GCS1, inline=1, fontsize=12, colors='blue',fmt='%d',inline_spacing=0)\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "GCS1.collections[1].set_linewidths(1.5)\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted')\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=12, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='magenta',linestyles='dashdot')\n",
    "\n",
    "plt.clabel(HCS1, inline=1, fontsize=12, colors='magenta',fmt='%d',inline_spacing=0)\n",
    "HCS1.collections[0].set_linewidths(1.5)\n",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "\n",
    "\n",
    "#SCS1 = plt.contour(X, Y, transpose(S1), levels=Slevels, colors='cyan')\n",
    "\n",
    "#plt.clabel(SCS1, inline=1, fontsize=12, colors='cyan',fmt='%.1f',inline_spacing=1)\n",
    "#SCS1.collections[0].set_linewidths(3.0)\n",
    "#SCS1.collections[0].set_label(r'$Peak$'+r' '+r'$stag. pressure,atm$')\n",
    "\n",
    "#plt.axhline(y=0.36,linewidth=1, linestyle='dotted' ,color='white',label=r'$Apollo$'+' '+r'$CM$'+' '+r'$L/D$')\n",
    "\n",
    "\n",
    "\n",
    "#matplotlib.rcParams['text.usetex'] = True\n",
    "#plt.rc('text', usetex=True)\n",
    "\n",
    "\n",
    "# circles for b=50 plot\n",
    "#plt.plot(7.5,0.20,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "#plt.plot(4.95,0.30,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "\n",
    "#plt.plot(7.5,0.211,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "#plt.plot(4.95,0.315,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "\n",
    "\n",
    "#plt.grid(True,linestyle='dotted', linewidth=0.1)\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(\"L/D\",fontsize=16)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=16)\n",
    "plt.xticks( fontsize=16)\n",
    "plt.yticks(fontsize=16)\n",
    "ax = plt.gca()\n",
    "ax.tick_params(direction='in')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "ax.xaxis.set_ticks_position('both')\n",
    "plt.legend(loc='lower left', fontsize=16)\n",
    "\n",
    "dat0 = ZCS1.allsegs[2][0]\n",
    "x1,y1=dat0[:,0],dat0[:,1]\n",
    "F1 = interpolate.interp1d(x1, y1, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "dat1 = GCS1.allsegs[0][0]\n",
    "x2,y2=dat1[:,0],dat1[:,1]\n",
    "F2 = interpolate.interp1d(x2, y2, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "dat2 = QCS1.allsegs[0][0]\n",
    "x3,y3= dat2[:,0],dat2[:,1]\n",
    "F3 = interpolate.interp1d(x3, y3, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "dat0a = ZCS1.allsegs[1][0]\n",
    "x1a,y1a=dat0a[:,0],dat0a[:,1]\n",
    "F1a = interpolate.interp1d(x1a, y1a, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "\n",
    "x4 = np.linspace(0,30,101)\n",
    "y4 = F1(x4)\n",
    "y4a =F1a(x4)\n",
    "y5 = F2(x4)\n",
    "y6 = F3(x4)\n",
    "\n",
    "y7 = np.minimum(y5,y6)\n",
    "y8 = np.minimum(y4,y6)\n",
    "\n",
    "plt.fill_between(x4, y4, y7, where=y4<=y7,color='xkcd:neon green')\n",
    "\n",
    "plt.fill_between(x4, y4a, y8, where=y4a<=y8,color='xkcd:bright yellow')\n",
    "\n",
    "\n",
    "plt.xlim([0.0,30.0])\n",
    "plt.ylim([0.0,1])\n",
    "\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-small.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-small.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-small.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 468x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/neptune/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/neptune/'+runID+'LD_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/neptune/'+runID+'stag_pres_atm_max_array.txt')\n",
    "\n",
    "\n",
    "\n",
    "f1 = interpolate.interp2d(x, y, np.transpose(Z1), kind='cubic')\n",
    "g1 = interpolate.interp2d(x, y, np.transpose(G1), kind='cubic')\n",
    "q1 = interpolate.interp2d(x, y, np.transpose(Q1), kind='cubic')\n",
    "h1 = interpolate.interp2d(x, y, np.transpose(H1), kind='cubic')\n",
    "#s1 = interpolate.interp2d(x, y, transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   30,  310)\n",
    "y_new =  np.linspace( 0.0,   1.0 ,110)\n",
    "z_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "z1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "g1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "q1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "h1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "#s1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "for i in range(0,len(x_new)):\n",
    "    for j in range(0,len(y_new)):\n",
    "\n",
    "        z1_new[i,j] = f1(x_new[i],y_new[j])\n",
    "        g1_new[i,j] = g1(x_new[i],y_new[j])\n",
    "        q1_new[i,j] = q1(x_new[i],y_new[j])\n",
    "        h1_new[i,j] = h1(x_new[i],y_new[j])\n",
    "        #s1_new[i,j] = s1(x_new[i],y_new[j])\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "Z1 = z1_new\n",
    "\n",
    "G1 = g1_new\n",
    "\n",
    "Q1 = q1_new\n",
    "\n",
    "#S1 = s1_new\n",
    "\n",
    "H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "#X, Y = meshgrid(x, y)\n",
    "\n",
    "\n",
    "Zlevels = np.array([0.5,1.0,2.0,3.0])\n",
    "\n",
    "Glevels = np.array([5.0, 10.0, 20.0, 30.0, 50.0])\n",
    "Qlevels = np.array([600.0, 1000.0, 2000.0, 4000.0, 8000.0])\n",
    "Hlevels = np.array([125.0, 225.0, 400.0, 600.0, 1200.0])\n",
    "#Slevels = np.array([0.8])\n",
    "\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([6.5,6.5])\n",
    "rcParams['font.family'] = 'sans-serif'\n",
    "rcParams['font.sans-serif'] = ['DejaVu Sans']\n",
    "#plt.xlim([0.0,30.0])\n",
    "#plt.ylim([0.0,0.4])\n",
    "#plt.tight_layout()\n",
    "#plt.contourf(X, Y, Z, levels=levels)\n",
    "\n",
    "\n",
    "#plt.axvline(x=25.0,linewidth=3, linestyle='dotted' ,color='red',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(LV$'+r' '+r'$C3$'+r' '+r'$limit)$')\n",
    "#plt.axvline(x=13.1,linewidth=1, linestyle='dotted' ,color='cyan',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(Chem. OI)$')\n",
    "\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black',zorder=0)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=10, colors='black',fmt='%.1f',inline_spacing=1,zorder=0)\n",
    "ZCS1.collections[0].set_linewidths(1.5)\n",
    "ZCS1.collections[1].set_linewidths(1.5)\n",
    "ZCS1.collections[2].set_linewidths(1.5)\n",
    "ZCS1.collections[3].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "\n",
    "ZCS1.collections[0].set_label(r'$TCW, deg$')\n",
    "\n",
    "\n",
    "GCS1 = plt.contour(X, Y, np.transpose(G1), levels=Glevels, colors='blue',linestyles='dashed',zorder=1)\n",
    "\n",
    "plt.clabel(GCS1, inline=1, fontsize=10, colors='blue',fmt='%d',inline_spacing=0,zorder=1)\n",
    "\n",
    "\n",
    "\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "GCS1.collections[1].set_linewidths(1.5)\n",
    "GCS1.collections[2].set_linewidths(1.5)\n",
    "GCS1.collections[3].set_linewidths(1.5)\n",
    "GCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted',zorder=13)\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=10, colors='red',fmt='%d',inline_spacing=0,zorder=13)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\n",
    "QCS1.collections[2].set_linewidths(1.5)\n",
    "QCS1.collections[3].set_linewidths(1.5)\n",
    "QCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='xkcd:brown',linestyles='dashdot',zorder=14)\n",
    "\n",
    "plt.clabel(HCS1, inline=1, fontsize=10, colors='xkcd:brown',fmt='%d',inline_spacing=0,zorder=14)\n",
    "HCS1.collections[0].set_linewidths(1.75)\n",
    "HCS1.collections[1].set_linewidths(1.75)\n",
    "HCS1.collections[2].set_linewidths(1.75)\n",
    "HCS1.collections[3].set_linewidths(1.75)\n",
    "HCS1.collections[4].set_linewidths(1.75)\n",
    "\n",
    "\n",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(\"L/D\",fontsize=12)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=12)\n",
    "plt.xticks(np.array([ 0.0, 5, 10, 15, 20, 25, 30]),fontsize=12)\n",
    "plt.yticks(np.array([ 0.0, 0.2, 0.4, 0.6, 0.8, 1.0]),fontsize=12)\n",
    "ax = plt.gca()\n",
    "ax.tick_params(direction='in')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "ax.xaxis.set_ticks_position('both')\n",
    "plt.legend(loc='lower left', fontsize=12)\n",
    "\n",
    "\n",
    "\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-large.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-large.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/neptune/neptune-lift-large.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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