SPATZ/tests.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 492,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       21.079909\n",
       "2       21.079909\n",
       "3       21.079909\n",
       "4       21.079909\n",
       "5       21.079909\n",
       "          ...    \n",
       "1362    21.080085\n",
       "1363    21.080085\n",
       "1364    21.080085\n",
       "1365    21.080085\n",
       "1366    21.080085\n",
       "Name: longitude, Length: 1366, dtype: float64"
      ]
     },
     "execution_count": 493,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/simulations/11km.txt', sep='\\t', encoding='latin')\n",
    "df = df.drop([0], axis=0)\n",
    "df = df.astype(float)\n",
    "\n",
    "df['longitude']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 494,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       67.885478\n",
       "2       67.885478\n",
       "3       67.885478\n",
       "4       67.885478\n",
       "5       67.885478\n",
       "          ...    \n",
       "1362    67.959101\n",
       "1363    67.959101\n",
       "1364    67.959101\n",
       "1365    67.959101\n",
       "1366    67.959101\n",
       "Name: latitude, Length: 1366, dtype: float64"
      ]
     },
     "execution_count": 494,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['latitude']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       67.750940\n",
       "2       67.750940\n",
       "3       67.750940\n",
       "4       67.750940\n",
       "5       67.750940\n",
       "          ...    \n",
       "1362    67.824918\n",
       "1363    67.824918\n",
       "1364    67.824918\n",
       "1365    67.824918\n",
       "1366    67.824918\n",
       "Name: declination, Length: 1366, dtype: float64"
      ]
     },
     "execution_count": 495,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['declination']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 496,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8.20214666930979e-13 -1.51393643837011e-12 -2.40063988328838e-12\n"
     ]
    }
   ],
   "source": [
    "print(df.at[2, 'x_FL'], df.at[2, 'y_FL'], df.at[2, 'z_FL'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 497,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/simulations/raw/Resultmin20.txt', sep='\\t')\n",
    "\n",
    "# Result_Exporte -> 19km\n",
    "# Resultadd10 -> 16km\n",
    "# Resultmin10 -> 23km\n",
    "# Resultmin20 ->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       X-Acceleration w/o Gravity of STAHR_Rocket in ...\n",
       "1                                         Meter/Second**2\n",
       "2                                    9.67852498145304E+00\n",
       "3                                    9.67852498145304E+00\n",
       "4                                    9.67852498145304E+00\n",
       "                              ...                        \n",
       "1715                                 9.79985543156082E+00\n",
       "1716                                 9.81624939319664E+00\n",
       "1717                                 9.82432436318236E+00\n",
       "1718                                 9.82407348573446E+00\n",
       "1719                                 9.82407348573446E+00\n",
       "Name: acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket, Length: 1720, dtype: object"
      ]
     },
     "execution_count": 498,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 499,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Phase', nan)\n",
      "('acceleration_without_gravity_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity_radial~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity_y~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity_z~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_without_gravity~STAHR_Rocket', 'Meter/Second**2')\n",
      "('acceleration_x~STAHR_Rocket#J2000@Earth', 'Meter/Second**2')\n",
      "('acceleration_y~STAHR_Rocket#J2000@Earth', 'Meter/Second**2')\n",
      "('acceleration_z~STAHR_Rocket#J2000@Earth', 'Meter/Second**2')\n",
      "('acceleration~STAHR_Rocket#J2000@Earth', 'Meter/Second**2')\n",
      "('acc_aero_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_aero_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_aero_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_aero~STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_normal~STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_thrust_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_thrust_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_thrust_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second**2')\n",
      "('acc_thrust~STAHR_Rocket', 'Meter/Second**2')\n",
      "('aero_area_ref~STAHR_Rocket', 'Meter^2')\n",
      "('aero_bank_angle~STAHR_Rocket', 'Degree')\n",
      "('aero_roll_angle~STAHR_Rocket', 'Degree')\n",
      "('airpath_angle~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('airpath_angle~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('AIRPATH_BANK_ANGLE~Esrange#A~Esrange:Earth', 'Radian')\n",
      "('AIRPATH_BANK_ANGLE~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Radian')\n",
      "('airpath_heading~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('airpath_heading~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('airpath_speed~STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('altitude_apoapsis~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('altitude_periapsis~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('altitude~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('angle1~IB3:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle1~IB3:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle1~STAHR:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle1~STAHR:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle2~IB3:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle2~IB3:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle2~STAHR:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle2~STAHR:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle3~IB3:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle3~IB3:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle3~STAHR:STAHR_Rocket#B~STAHR_Rocket', 'Radian')\n",
      "('angle3~STAHR:STAHR_Rocket#J2000', 'Radian')\n",
      "('angle_body_and_local_vertical~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('angle_of_attack_rate~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('ANGLE_OF_ATTACK~Esrange#A~Esrange:Earth', 'Radian')\n",
      "('angle_of_attack~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree')\n",
      "('angular_velocity~STAHR_Rocket#B~STAHR_Rocket', 'Degree/Second')\n",
      "('arc_length~STAHR_Rocket', 'Kilo-Meter')\n",
      "('ascending_node_rel~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('ascending_node~STAHR_Rocket#J2000', 'Degree')\n",
      "('ascending_node~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('asymptote_decl~STAHR_Rocket#J2000', 'Degree')\n",
      "('asymptote_decl~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('asymptote_right_ascension~STAHR_Rocket#J2000', 'Degree')\n",
      "('asymptote_right_ascension~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('atmos_density~STAHR_Rocket', 'Kilogram/Meter**3')\n",
      "('atmos_pressure~STAHR_Rocket', 'Pascal')\n",
      "('atmos_temperature~STAHR_Rocket', 'Kelvin')\n",
      "('bank_angle_rate~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('bank_angle~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree')\n",
      "('bending_moment~STAHR_Rocket', 'Pascal*Radian')\n",
      "('burn_time~IB3:STAHR_Rocket', 'Second')\n",
      "('cross_range~STAHR_Rocket', 'Kilo-Meter')\n",
      "('declination~STAHR_Rocket#J2000@Earth', 'Degree')\n",
      "('declination~STAHR_Rocket#PCPF~Earth@Earth', 'Degree')\n",
      "('declination~STAHR_Rocket#TOD~Earth@Earth', 'Degree')\n",
      "('DECL~STAHR_Rocket', 'Radian')\n",
      "('dimension_x~STAHR_Rocket', 'Meter')\n",
      "('dimension_y~STAHR_Rocket', 'Meter')\n",
      "('dimension_z~STAHR_Rocket', 'Meter')\n",
      "('down_range~STAHR_Rocket', 'Kilo-Meter')\n",
      "('drag_acc~STAHR_Rocket', 'Meter/Second**2')\n",
      "('drag_coeff~STAHR_Rocket', nan)\n",
      "('drag~STAHR_Rocket', 'Kilo-Newton')\n",
      "('dummy_altitude', 'Meter')\n",
      "('dummy_declination', 'Degree')\n",
      "('dummy_latitude', 'Degree')\n",
      "('dummy_longitude', 'Degree')\n",
      "('dummy_radius', 'Meter')\n",
      "('dynamic_pressure~STAHR_Rocket', 'Pascal')\n",
      "('dyn_viscosity~STAHR_Rocket', 'Pascal*Second')\n",
      "('eccentricity~STAHR_Rocket@Earth', nan)\n",
      "('eccentric_anomaly~STAHR_Rocket@Earth', 'Degree')\n",
      "('energy_total~STAHR_Rocket@Earth', 'Kilo-Joule/Kilogram')\n",
      "('equinoctial_f~STAHR_Rocket#TOD~Earth', nan)\n",
      "('equinoctial_g~STAHR_Rocket#TOD~Earth', nan)\n",
      "('equinoctial_h~STAHR_Rocket#TOD~Earth', nan)\n",
      "('equinoctial_k~STAHR_Rocket#TOD~Earth', nan)\n",
      "('equinoctial_l~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('equinoctial_p~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('excess_velocity~STAHR_Rocket@Earth', 'Kilo-Meter/Second')\n",
      "('flightpath_angle~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('flightpath_angle~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('flightpath_heading~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('flightpath_heading~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('flightpath_speed~STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('flightpath_vertical~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('flight_time', 'Second')\n",
      "('flight_time~STAHR_Rocket', 'Second')\n",
      "('force_aero_axial~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Kilo-Newton')\n",
      "('force_aero_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Newton')\n",
      "('force_aero_lateral~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Kilo-Newton')\n",
      "('force_aero_normal~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Kilo-Newton')\n",
      "('force_aero_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Newton')\n",
      "('force_aero_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Newton')\n",
      "('gps_time', 'Second')\n",
      "('gravity_force_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton')\n",
      "('gravity_force_y~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton')\n",
      "('gravity_force_z~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton')\n",
      "('gravity_potential~Esrange', 'Kilo-Joule/Kilogram')\n",
      "('gravity_potential~STAHR_Rocket@Earth', 'Kilo-Joule/Kilogram')\n",
      "('gravity~STAHR_Rocket', 'Meter/Second**2')\n",
      "('great_circle_distance~STAHR_Rocket', 'Kilo-Meter')\n",
      "('heat_flux_density~STAHR_Rocket', 'Kilo-Watt/Meter**2')\n",
      "('hload_lift~STAHR_Rocket', nan)\n",
      "('inclination~STAHR_Rocket#J2000', 'Degree')\n",
      "('inclination~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('inertial_flightpath_vertical~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('inertial_flightpath~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('inertial_heading~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('inertial_speed~STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('inertia_xx~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('inertia_xy~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('inertia_xz~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('inertia_yy~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('inertia_yz~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('inertia_zz~STAHR_Rocket', 'Kilogram*Meter**2')\n",
      "('isp_vacuum~IB3:STAHR_Rocket', 'Second')\n",
      "('isp~IB3:STAHR_Rocket', 'Second')\n",
      "('julian_date_tt', 'Day')\n",
      "('julian_date_utc', 'Day')\n",
      "('knudsen_number~STAHR_Rocket', nan)\n",
      "('latitude~STAHR_Rocket#PCPF~Earth@Earth', 'Degree')\n",
      "('lift_acc~STAHR_Rocket', 'Meter/Second**2')\n",
      "('lift_coeff~STAHR_Rocket', nan)\n",
      "('lift_drag_ratio~STAHR_Rocket', nan)\n",
      "('lift~STAHR_Rocket', 'Kilo-Newton')\n",
      "('load_factor_axial~STAHR_Rocket', nan)\n",
      "('load_factor_cross~STAHR_Rocket', nan)\n",
      "('load_factor_normal~STAHR_Rocket', nan)\n",
      "('load_factor~STAHR_Rocket', nan)\n",
      "('local_central_body_radius~STAHR_Rocket', 'Kilo-Meter')\n",
      "('longitude~STAHR_Rocket#PCPF~Earth@Earth', 'Degree')\n",
      "('LONG~STAHR_Rocket', 'Radian')\n",
      "('mach~STAHR_Rocket', nan)\n",
      "('magnetic_flux_density_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density_radial~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density_y~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density_z~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Nano-Tesla')\n",
      "('magnetic_flux_density~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Nano-Tesla')\n",
      "('mass_flow~IB3:STAHR_Rocket', 'Kilogram/Second')\n",
      "('mass_total~STAHR_Rocket', 'Mega-Gram')\n",
      "('mean_anomaly~STAHR_Rocket@Earth', 'Degree')\n",
      "('mean_local_time_of_the_ascending_node~STAHR_Rocket', 'Hour')\n",
      "('mean_motion~STAHR_Rocket@Earth', 'Radian/Second')\n",
      "('mission_time', 'Second')\n",
      "('moment_aero_x~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('moment_aero_y~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('moment_aero_z~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('Norm_Indep_Var', nan)\n",
      "('nozzle_area~IB3:STAHR_Rocket', 'Meter^2')\n",
      "('OMEGA_X~STAHR_Rocket', 'Radian/Second')\n",
      "('omega_x~STAHR_Rocket#B~STAHR_Rocket', 'Degree/Second')\n",
      "('OMEGA_Y~STAHR_Rocket', 'Radian/Second')\n",
      "('omega_y~STAHR_Rocket#B~STAHR_Rocket', 'Degree/Second')\n",
      "('OMEGA_Z~STAHR_Rocket', 'Radian/Second')\n",
      "('omega_z~STAHR_Rocket#B~STAHR_Rocket', 'Degree/Second')\n",
      "('orbital_period~STAHR_Rocket@Earth', 'Second')\n",
      "('periapsis_argument~STAHR_Rocket#J2000', 'Degree')\n",
      "('periapsis_argument~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('pitch_rate~STAHR_Rocket#J2000', 'Degree/Second')\n",
      "('pitch_rate~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('pitch_rate~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('PITCH~Esrange#L~Esrange:Earth', 'Radian')\n",
      "('PITCH~STAHR_Rocket', 'Radian')\n",
      "('pitch~STAHR_Rocket#J2000', 'Degree')\n",
      "('pitch~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('pitch~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree')\n",
      "('pitch~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('pitch~STAHR_Rocket#N~STAHR_Rocket', 'Degree')\n",
      "('pitch~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('PROP_MASS~STAHR:STAHR_Rocket', 'Kilogram')\n",
      "('quaternion_w~Earth#J2000', nan)\n",
      "('quaternion_w~IB3:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_w~STAHR:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_w~STAHR_Rocket#J2000', nan)\n",
      "('quaternion_w~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('quaternion_x~Earth#J2000', nan)\n",
      "('quaternion_x~IB3:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_x~STAHR:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_x~STAHR_Rocket#J2000', nan)\n",
      "('quaternion_x~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('quaternion_y~Earth#J2000', nan)\n",
      "('quaternion_y~IB3:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_y~STAHR:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_y~STAHR_Rocket#J2000', nan)\n",
      "('quaternion_y~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('quaternion_z~Earth#J2000', nan)\n",
      "('quaternion_z~IB3:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_z~STAHR:STAHR_Rocket#B~STAHR_Rocket', nan)\n",
      "('quaternion_z~STAHR_Rocket#J2000', nan)\n",
      "('quaternion_z~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('radius_apoapsis~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('radius_periapsis~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('radius~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('reynolds_number~STAHR_Rocket', nan)\n",
      "('right_ascension~STAHR_Rocket#J2000@Earth', 'Degree')\n",
      "('right_ascension~STAHR_Rocket#TOD~Earth@Earth', 'Degree')\n",
      "('roll_rate~STAHR_Rocket#J2000', 'Degree/Second')\n",
      "('roll_rate~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('roll_rate~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('ROLL~Esrange#L~Esrange:Earth', 'Radian')\n",
      "('ROLL~STAHR_Rocket', 'Radian')\n",
      "('roll~STAHR_Rocket#J2000', 'Degree')\n",
      "('roll~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('roll~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree')\n",
      "('roll~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('roll~STAHR_Rocket#N~STAHR_Rocket', 'Degree')\n",
      "('roll~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('R~STAHR_Rocket', 'Meter')\n",
      "('semimajor~STAHR_Rocket@Earth', 'Kilo-Meter')\n",
      "('sideslip_rate~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('sideslip~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree')\n",
      "('side_force~STAHR_Rocket', 'Kilo-Newton')\n",
      "('SIDE_SLIP_ANGLE~Esrange#A~Esrange:Earth', 'Radian')\n",
      "('SIDE_SLIP_ANGLE~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Radian')\n",
      "('solar_beta_angle~STAHR_Rocket#PF~STAHR_Rocket:Earth', 'Degree')\n",
      "('sonic_velocity~STAHR_Rocket', 'Meter/Second')\n",
      "('static_stability_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Meter')\n",
      "('thrust_to_ew~STAHR_Rocket', nan)\n",
      "('thrust_vacuum~IB3:STAHR_Rocket', 'Kilo-Newton')\n",
      "('thrust_x~STAHR_Rocket#J2000', 'Kilo-Newton')\n",
      "('thrust_y~STAHR_Rocket#J2000', 'Kilo-Newton')\n",
      "('thrust_z~STAHR_Rocket#J2000', 'Kilo-Newton')\n",
      "('thrust~IB3:STAHR_Rocket', 'Kilo-Newton')\n",
      "('thrust~STAHR_Rocket', 'Kilo-Newton')\n",
      "('Time', 'Second')\n",
      "('torque_x~IB3:STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton*Meter')\n",
      "('torque_x~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('torque_y~IB3:STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton*Meter')\n",
      "('torque_y~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('torque_z~IB3:STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket', 'Newton*Meter')\n",
      "('torque_z~STAHR_Rocket#B~STAHR_Rocket', 'Newton*Meter')\n",
      "('total_angle_of_attack_slope_normal_coefficient~STAHR_Rocket#TA~STAHR_Rocket@STAHR_Rocket', 'None/Degree')\n",
      "('total_angle_of_attack~STAHR_Rocket#A~STAHR_Rocket:Earth', 'Degree')\n",
      "('total_lift~STAHR_Rocket', 'Kilo-Newton')\n",
      "('total_solar_irradiance_at_earth~STAHR_Rocket', 'Watt/Meter**2')\n",
      "('TRAJ_SMOOTHNESS~STAHR_Rocket', 'Radian^2/Second')\n",
      "('true_anomaly~STAHR_Rocket@Earth', 'Degree')\n",
      "('u_length~STAHR_Rocket#LO~STAHR_Rocket:Earth', nan)\n",
      "('u_length~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('u_n~STAHR_Rocket#LO~STAHR_Rocket:Earth', nan)\n",
      "('u_r~STAHR_Rocket#LO~STAHR_Rocket:Earth', nan)\n",
      "('u_t~STAHR_Rocket#LO~STAHR_Rocket:Earth', nan)\n",
      "('u_x~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('u_y~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('u_z~STAHR_Rocket#L~STAHR_Rocket:Earth', nan)\n",
      "('velocity_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('velocity_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('velocity_rel_apoapsis~STAHR_Rocket@Earth', 'Kilo-Meter/Second')\n",
      "('velocity_rel_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('velocity_rel_periapsis~STAHR_Rocket@Earth', 'Kilo-Meter/Second')\n",
      "('velocity_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter/Second')\n",
      "('VI_EAST~STAHR_Rocket', 'Meter/Second')\n",
      "('VI_NORTH~STAHR_Rocket', 'Meter/Second')\n",
      "('VI_RADIAL~STAHR_Rocket', 'Meter/Second')\n",
      "('vload_lift~STAHR_Rocket', nan)\n",
      "('vx~STAHR_Rocket#J2000@Earth', 'Kilo-Meter/Second')\n",
      "('vx~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter/Second')\n",
      "('vy~STAHR_Rocket#J2000@Earth', 'Kilo-Meter/Second')\n",
      "('vy~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter/Second')\n",
      "('vz~STAHR_Rocket#J2000@Earth', 'Kilo-Meter/Second')\n",
      "('vz~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter/Second')\n",
      "('wind_gust_p~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Degree/Second')\n",
      "('wind_gust_q~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Degree/Second')\n",
      "('wind_gust_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Degree/Second')\n",
      "('wind_velocity_east~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second')\n",
      "('wind_velocity_north~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second')\n",
      "('wind_velocity_r~STAHR_Rocket#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Meter/Second')\n",
      "('x_offset_CoM~Esrange', 'Meter')\n",
      "('x_offset_CoM~Main_Stage:STAHR_Rocket', 'Meter')\n",
      "('x_offset_CoM~STAHR_Rocket', 'Meter')\n",
      "('x_offset_CoP~STAHR_Rocket', 'Meter')\n",
      "('x_offset~IB3:STAHR_Rocket', 'Meter')\n",
      "('x_offset~STAHR:STAHR_Rocket', 'Meter')\n",
      "('x~Earth#J2000@SSB', 'Kilo-Meter')\n",
      "('x~STAHR_Rocket#J2000@Earth', 'Kilo-Meter')\n",
      "('x~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter')\n",
      "('x~Sun#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter')\n",
      "('yaw_rate~STAHR_Rocket#J2000', 'Degree/Second')\n",
      "('yaw_rate~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('yaw_rate~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree/Second')\n",
      "('YAW~Esrange#L~Esrange:Earth', 'Radian')\n",
      "('YAW~STAHR_Rocket', 'Radian')\n",
      "('yaw~STAHR_Rocket#J2000', 'Degree')\n",
      "('yaw~STAHR_Rocket#LD~STAHR_Rocket:Earth', 'Degree')\n",
      "('yaw~STAHR_Rocket#LO~STAHR_Rocket:Earth', 'Degree')\n",
      "('yaw~STAHR_Rocket#L~STAHR_Rocket:Earth', 'Degree')\n",
      "('yaw~STAHR_Rocket#N~STAHR_Rocket', 'Degree')\n",
      "('yaw~STAHR_Rocket#TOD~Earth', 'Degree')\n",
      "('y_offset_CoM~Esrange', 'Meter')\n",
      "('y_offset_CoM~Main_Stage:STAHR_Rocket', 'Meter')\n",
      "('y_offset_CoM~STAHR_Rocket', 'Meter')\n",
      "('y_offset_CoP~STAHR_Rocket', 'Meter')\n",
      "('y_offset~IB3:STAHR_Rocket', 'Meter')\n",
      "('y_offset~STAHR:STAHR_Rocket', 'Meter')\n",
      "('y~Earth#J2000@SSB', 'Kilo-Meter')\n",
      "('y~STAHR_Rocket#J2000@Earth', 'Kilo-Meter')\n",
      "('y~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter')\n",
      "('y~Sun#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter')\n",
      "('z_offset_CoM~Esrange', 'Meter')\n",
      "('z_offset_CoM~Main_Stage:STAHR_Rocket', 'Meter')\n",
      "('z_offset_CoM~STAHR_Rocket', 'Meter')\n",
      "('z_offset_CoP~STAHR_Rocket', 'Meter')\n",
      "('z_offset~IB3:STAHR_Rocket', 'Meter')\n",
      "('z_offset~STAHR:STAHR_Rocket', 'Meter')\n",
      "('z~Earth#J2000@SSB', 'Kilo-Meter')\n",
      "('z~STAHR_Rocket#J2000@Earth', 'Kilo-Meter')\n",
      "('z~STAHR_Rocket#TOD~Earth@Earth', 'Kilo-Meter')\n",
      "('z~Sun#L~STAHR_Rocket:Earth@STAHR_Rocket', 'Kilo-Meter')\n",
      "('z~Sun#L~STAHR_Rocket:Earth@STAHR_Rocket.1', 'Kilo-Meter')\n"
     ]
    }
   ],
   "source": [
    "print('\\n'.join(map(str, zip(df.columns.values, df.loc[1]))))\n",
    "\n",
    "df = df.drop([0, 1], axis=0)\n",
    "df = df.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.16807271758589"
      ]
     },
     "execution_count": 500,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(df['mach~STAHR_Rocket'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 501,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2       67.885478\n",
       "3       67.885478\n",
       "4       67.885478\n",
       "5       67.885478\n",
       "6       67.885478\n",
       "          ...    \n",
       "1715    68.072499\n",
       "1716    68.072499\n",
       "1717    68.072499\n",
       "1718    68.072499\n",
       "1719    68.072499\n",
       "Name: latitude~STAHR_Rocket#PCPF~Earth@Earth, Length: 1718, dtype: float64"
      ]
     },
     "execution_count": 501,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['latitude~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 502,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2       67.750938\n",
       "3       67.750938\n",
       "4       67.750938\n",
       "5       67.750938\n",
       "6       67.750938\n",
       "          ...    \n",
       "1715    67.938856\n",
       "1716    67.938856\n",
       "1717    67.938856\n",
       "1718    67.938856\n",
       "1719    67.938856\n",
       "Name: declination~STAHR_Rocket#PCPF~Earth@Earth, Length: 1718, dtype: float64"
      ]
     },
     "execution_count": 502,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['declination~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 503,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2       21.079909\n",
       "3       21.079909\n",
       "4       21.079909\n",
       "5       21.079909\n",
       "6       21.079909\n",
       "          ...    \n",
       "1715    21.080786\n",
       "1716    21.080786\n",
       "1717    21.080786\n",
       "1718    21.080786\n",
       "1719    21.080786\n",
       "Name: longitude~STAHR_Rocket#PCPF~Earth@Earth, Length: 1718, dtype: float64"
      ]
     },
     "execution_count": 503,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['longitude~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 504,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a034d71a90>]"
      ]
     },
     "execution_count": 504,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['altitude~STAHR_Rocket@Earth'] * 1000\n",
    "\n",
    "plt.plot(df['Time'], df['altitude~STAHR_Rocket@Earth'] * 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 505,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "318.99999999906896"
      ]
     },
     "execution_count": 505,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[2, 'altitude~STAHR_Rocket@Earth'] * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 506,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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O+v7PPvssr732Glu3bqVTp04UFRVx3XXXsWDBAtatW8eAAQMYPHiwY7X0H374gSZNmvDyyy9z6NAhDh06BMCuXbsYMGAAt9xyCxs2bGDatGksW7aMMWPGON7rvvvuY9++fSxatIjvvvuOjz76iNzc3Es6f9XhVefvINyDrQK1eRYG4Ed7b8Z3b1Lnbxkd6Ms1bSOZlnElzxu/hrX/hcT76vx9hRAepKIEXo3R573/dhDMjS765ddddx2PPvooAM888wzvvPMOixYtok2bNoSHhwMQGhpKVNSpq+oTJ07krbfe4uabbwa0Kz5btmzhk08+Yfjw4XzzzTcYDAY+++wzfHx8SEhI4MCBAzz00ENnvP/LL7/Mtdde63geEhJC586dHc9feeUVZs6cyU8//cSYMWMICQnBZDIREBDgVNOkSZMYNmyY4ypVq1ateP/99+nbty+TJ08mKyuLX375hdWrV9OjRw8A/v3vf9OuXbuLPnfVJSFHaPb+gaH0GEeUlUPBPejYOLBe3vae5KaM3XI5z3h9i/eBNMjZDJEXt0aWEEK4k06dOjl+NhgMREVFnffqRnFxMbt27WLEiBFOoaWyspLAQO13dkZGBp06dcLHx8exv2fPnmc9Xvfu3Z2eFxUV8dJLLzFnzhwOHTpEZWUlpaWljis557J+/Xo2bNjgdAtKKYXdbiczM5Pt27fj5eVFYmKiY3/btm0JCgo673Frg4Qcodk2F4AFtm4M7NTE6V5rXerdIoyA0GhSCxK5zrQa1n4JA1+rl/cWQngAbz/tiope730pL/f2dnpuMBiwn2dy1KKiIgA+++wzkpKSnPaZTDXvXtCokfNVqKeeeorU1FTefPNNWrZsia+vL7feeivl5eXnPU5RURGPPPIIjz322Bn74uLi2L59e41rqy0ScgQohX3bHIxAqj2RJztF19tbG40G7u7VlOm/XMl1ptWoDd9iuPbv4FV7ExAKITyYwXBJt4xcldmsLaVjs9kc2yIjI4mJiWH37t0MGzbsrK9r06YNX331FWVlZVgs2u/RP//8s1rv+ccff3Dfffdx0003AVp42bNnzxl1nV4TQLdu3diyZQstW7Y863Hbtm1LZWUlaWlpjttVGRkZ5OXlVauuSyEdjwXkbMJYsJ9SZeZASBJt62BunPO5NbEJq4xdOKhCMJQeh5OrnwshREMVERGBr68v8+bNIycnh/z8fAD+/ve/M2nSJN5//322b9/Oxo0b+eKLL3j77bcBuOuuu7Db7Tz88MNs3bqV+fPn8+abbwJc8Ap9q1at+OGHH0hPT2f9+vWOY52uWbNmLF26lAMHDnDkyBFA60+0fPlyxowZQ3p6Ojt27ODHH390dDxu06YNAwYM4JFHHmHVqlWkpaXx4IMP4uvrW6vn7Gwk5AjHrapl9o5c26lZvd2qqhLkZ+ba9jHMsPXVNqz/X72+vxBCuBovLy/ef/99PvnkE2JiYrjxxhsBePDBB/n888/54osv6NixI3379mXKlCmOIedWq5Wff/6Z9PR0unTpwnPPPceLL74I4NRP52zefvttgoODueyyyxg8eDApKSl069bNqc3LL7/Mnj17aNGihaNzdKdOnViyZAnbt2+nT58+dO3alRdffJGYmFMdwr/44gtiYmLo27cvN998Mw8//DARERG1dr7OxaDUJY6Bc2MFBQUEBgaSn5+P1WrVuxzd2D++AmP2ep6ueJgHxrxAu+j6PxdLtx/mxS9+ZLHlSZTBiOHJDPCv+/8BhBDu5cSJE2RmZhIfH3/BL22h+frrr7n//vvJz8+vl6snteV8f9bV/f6WKzkNXWE2xuz12JWBLf7J9X6rqkrvlmGcCIgn3d4Cg7LDJpkzRwghLsZ///tfli1bRmZmJrNmzeKZZ57h9ttvd6uAU1sk5DR0uxcDsEk1o1u71vV+q6qKyWjg5m6NmWm7XNuwYZoudQghhLvLzs7m7rvvpl27djzxxBPcdtttTrMpNyQScho4tWsBAL/bO3J1O31vD92S2ITZtl5UKiMcXCuLdgohxEUYP348e/bscdzueeedd/Dzu7Th7u5KQk5DZrdj27EIgFWGLiQ3D9W1nBbh/jSNa8pS+8kJsjZM17UeIYQQ7k1CTkOWuxmv0sMUKwt+LZLrfK2q6rglsQmzbL21JxunX/LaMEIIIRouCTkN2S7tKs5KewJXtKv7taqq47oO0SyiO8XKAsf3wP7qTWIlhGhYGvDA4AajNv6MJeQ0YJU7TvXH6dsmXOdqNMGNzHRv1YR5dm1WTLllJYQ4XdVSCCUlJTpXIupa1Z/xX5e/qAlZ1qGhqijFkLUcgN2BSTQOcp2hhTd0ieHHHZdxi2kZautPGAb+E4z630oTQujPZDIRFBTkWMjSz89Pt1Ghom4opSgpKSE3N5egoKCLWperioSchmr/n5js5WSrYGJbdrpw+3p0bUIULxg7kacaEVSUA3uXQ3wfvcsSQriIqKgogPOu2C3cX1BQkOPP+mJJyGmo9mpXcVbZ23F5K9e4VVXF3+JF33aNmb+1B3d4LYbNMyXkCCEcDAYD0dHRREREUFFRoXc5og54e3tf0hWcKjXqkzNp0iR69OhBQEAAERERDBkyhIyMDKc2V155JQaDwekxcuRIpzZZWVkMGjQIPz8/IiIiePrpp6msrHRqs3jxYrp164bFYqFly5ZMmTLljHo+/PBDmjVrho+PD0lJSaxevbomH6dBK9+1FNBCTnILfYeOn83gztHMsScBoLb+BLbKC7xCCNHQmEwmfHx85OGBj9oIOFDDkLNkyRJGjx7NypUrSU1NpaKigv79+1NcXOzU7qGHHuLQoUOOx+uvv+7YZ7PZGDRoEOXl5SxfvpypU6cyZcoUxwJiAJmZmQwaNIirrrqK9PR0xo4dy4MPPsj8+fMdbaZNm8a4ceOYOHEia9eupXPnzqSkpMjly+qoLMd0YA0Ax8O6E+Rn1rmgM13ZJoKN3p05rvwxFB+GvX/oXZIQQgh3oy5Bbm6uAtSSJUsc2/r27asef/zxc75m7ty5ymg0quzsbMe2yZMnK6vVqsrKypRSSo0fP161b9/e6XV33HGHSklJcTzv2bOnGj16tOO5zWZTMTExatKkSdWuPz8/XwEqPz+/2q/xCHtXKjXRqo682Fi9Omez3tWc07hp6eqb525UaqJVqZ8e07scIYQQLqK639+XNIQ8Pz8fgJCQEKftX3/9NWFhYXTo0IEJEyY4DfVbsWIFHTt2JDIy0rEtJSWFgoICNm/e7GjTr18/p2OmpKSwYsUKAMrLy0lLS3NqYzQa6devn6PN2ZSVlVFQUOD0aJD2LgNgtb0tvVu6Vn+c093QJYbZ9l4AqC1yy0oIIUTNXHTIsdvtjB07lt69e9OhQwfH9rvuuouvvvqKRYsWMWHCBL788kvuvvtux/7s7GyngAM4nmdnZ5+3TUFBAaWlpRw5cgSbzXbWNlXHOJtJkyYRGBjoeMTGxl7ch3dzJ3b+DsCfKoHuzYJ1rubcercIZbtPF46qAAylx2DPUr1LEkII4UYuenTV6NGj2bRpE8uWLXPa/vDDDzt+7tixI9HR0VxzzTXs2rWLFi1aXHyltWDChAmMGzfO8bygoKDhBR1bJV4HVgFwLCwRP7PrDrDzMhnp1yGGeWt7MsxrgTbKqsXVepclhBDCTVzUlZwxY8Ywe/ZsFi1aRJMm518OIClJGyGzc+dOQJvfICcnx6lN1fOq8fDnamO1WvH19SUsLAyTyXTWNucbU2+xWLBarU6PBidnI16VJRQoP8JbdNO7mgu6rmP0qVtWW38GmwwXFUIIUT01CjlKKcaMGcPMmTNZuHAh8fHxF3xNeno6ANHR0QAkJyezceNGp1FQqampWK1WEhISHG0WLFjgdJzU1FSSk5MBMJvNJCYmOrWx2+0sWLDA0Uacwz5tLai19lYkxrtuf5wqvZqHst3SkcPKiqH0OOxeondJQggh3ESNQs7o0aP56quv+OabbwgICCA7O5vs7GxKS0sB2LVrF6+88gppaWns2bOHn376iXvvvZcrrriCTp20WXX79+9PQkIC99xzD+vXr2f+/Pk8//zzjB49GovFAsDIkSPZvXs348ePZ9u2bXz00UdMnz6dJ554wlHLuHHj+Oyzz5g6dSpbt25l1KhRFBcXc//999fWufFI5Xu1W1Xr7C3p4cL9cap4m4z0a9+Yebae2obNM/UtSAghhPuoyZAt4KyPL774QimlVFZWlrriiitUSEiIslgsqmXLlurpp58+Y4jXnj171MCBA5Wvr68KCwtTTz75pKqoqHBqs2jRItWlSxdlNptV8+bNHe9xug8++EDFxcUps9msevbsqVauXFmTj9Mgh5AXv9FRqYlW9fRrb+ldSrUt2pajbn/2DaUmWpV9UqxSFWV6lySEEEJH1f3+NijVcNerLygoIDAwkPz8/IbRP6f4KLzRHICX2s3lpTt661xQ9VTY7PR8ZT7z1UgiDHlw1wxo3V/vsoQQQuikut/flzRPjnAzJ2c53mmPoUPLpjoXU33eJiPXtI/hF1sPbYPcshJCCFENEnIakMqsU/1xujd1/f44pxvUMZo5tpOjrLbNhspynSsSQgjh6iTkNCAlu7WQs927LU1D/XSupmZ6twwjw9KeHBWEoawAdi/SuyQhhBAuTkJOQ2G34ZOzDoDy6EQMBoPOBdWM2cvINQnRzLVp8y7JLSshhBAXIiGnoTiyHbOtmGJlITS+s97VXBTtlpUWctS2OVBZpnNFQgghXJmEnIZivzYJ4AZ7Czo3DdO5mItzeaswtpsTyFbB2i2rXQv1LkkIIYQLk5DTQJTt1UJOumpB5yaBOldzcSxepr/cspqlaz1CCCFcm4ScBqJsn9YfJ8e/HUF+Zp2ruXgDO0SdumWVMRcqTuhckRBCCFclIachqCzH7/g2AEwxXfSt5RJd0TqcDO+2HFIhcstKCCHEeUnIaQgOb8NLVZCv/Iht3k7vai6Jj7eJq9vJKCshhBAXJiGnAVAHtVtVm+zxdI5zr0kAz+a600dZZcyFilKdKxJCCOGKJOQ0AEV70gDYQjwJMe6/RteVbcLJ8G7DARWKobwIdi7QuyQhhBAuSEJOA1C5X7uSkxeUgMXLpHM1l87H28RVbaNO3bLaMkvXeoQQQrgmCTmezlaJf14GAMbGXXUupvZc3+lUvxyV8YvcshJCCHEGCTme7kgG3qqMQuVLVDP37nR8uivbRLDduw37VdjJW1a/6V2SEEIIFyMhx8NVdTrerJrRobH7dzqu4uNtol9ClIyyEkIIcU4Scjxcyd61AGxW8bSJCtC5mtrltJZVxjy5ZSWEEMKJhBwPV3Gy0/Fh/3b4eLt/p+PTXdE6nN3mk7esKophR6reJQkhhHAhEnI8md2O73Gt07EhuqPOxdQ+H28T1yZEMdvWS9sgt6yEEEKcRkKOJ8vPwmIrpkx5Ed6svd7V1IlBp4+y2j4Pykt0rkgIIYSrkJDjyXI2A7BTNSahSajOxdSNy1uFkWlpzT57OIaKEtjxq94lCSGEcBEScjxY6b4NAGxTcR4x0/HZWLxMpLSPZo5dblkJIYRwJiHHgxXvWw9Atm8LrD7eOldTdwZ1ima245bVfCgr1LkiIYQQrkBCjgfzOrIVAHuY50wCeDa9W4Sxz9KaXfZoDJWlsHW23iUJIYRwARJyPFV5CdaSLAAaxXXWuZi6ZfYyMqBDNLNsvbUNG6frW5AQQgiXICHHUx3ehhE7R5SVuNh4vaupc4M6RfOjXQs5avdiKMzRtyAhhBC6k5DjoSqzNwGwzR5Lm2jP7HR8uuQWoRT6NiHN3gqDssOm7/UuSQghhM4k5Hiowj3pAOwyNqNJsK++xdQDb9NfblltmKZvQUIIIXQnIcdD2Q5pV3IKrK0wGAw6V1M/buramDm2XlQoExxKh8Pb9S5JCCGEjiTkeCKl8Mvbpv0c2UHfWupR96bB+AZFstTeSdsgHZCFEKJBk5DjiYpy8KvMx6YMBMU1nJBjNBq4sUvMabespoNS+hYlhBBCNxJyPFGOdqtqj4qiZeMInYupX0O6NibVnkiR8oG8vbBvtd4lCSGE0ImEHA9UdkibBDBDxdImKkDnaupX68gAmkeHM9/eQ9sgt6yEEKLBkpDjgQr3aVdyDnrHEdLIrHM19W9I1xhm2i7Xnmz8DirL9C1ICCGELiTkeCB1OAOAsqBWOleijxs6N2aFas9BFQIn8iBjrt4lCSGE0IGEHE+jFP4FOwHwjvLsNavOJSrQh6Tm4Xxvu0LbsO4rfQsSQgihCwk5nqYoF19bITZlILRpgt7V6GZI18Z8dzLkqF0LIf+AzhUJIYSobxJyPM0R7VbVPhVBq8bhOhejnwEdosg2xbDK3lZb5mH9//QuSQghRD2TkONhivZrnY53qsa0imhYI6tOZ/Xxpl9CJNMrr9Q2pH8tc+YIIUQDIyHHwxTt3wJAjqUZvmaTztXo67bEJsy196QYHzi2G7JW6F2SEEKIeiQhx9Mc1pZzKA1qqXMh+uvTKpxAaxA/V/bSNkgHZCGEaFBqFHImTZpEjx49CAgIICIigiFDhpCRkeHU5sSJE4wePZrQ0FD8/f255ZZbyMnJcWqTlZXFoEGD8PPzIyIigqeffprKykqnNosXL6Zbt25YLBZatmzJlClTzqjnww8/pFmzZvj4+JCUlMTq1TK7rX/BLgCM4W10rkR/JqOBWxObMMPWV9uweRaUFepakxBCiPpTo5CzZMkSRo8ezcqVK0lNTaWiooL+/ftTXFzsaPPEE0/w888/M2PGDJYsWcLBgwe5+eabHfttNhuDBg2ivLyc5cuXM3XqVKZMmcKLL77oaJOZmcmgQYO46qqrSE9PZ+zYsTz44IPMnz/f0WbatGmMGzeOiRMnsnbtWjp37kxKSgq5ubmXcj7cW8kx/CuPARAY117nYlzDrYlNSFOt2W2Phopi2PS93iUJIYSoL+oS5ObmKkAtWbJEKaVUXl6e8vb2VjNmzHC02bp1qwLUihUrlFJKzZ07VxmNRpWdne1oM3nyZGW1WlVZWZlSSqnx48er9u3bO73XHXfcoVJSUhzPe/bsqUaPHu14brPZVExMjJo0aVK168/Pz1eAys/Pr8GndmF7Vyg10ar2vxiv1uw5qnc1LuO2j5erV/42SqmJVqU+7qOU3a53SUIIIS5Bdb+/L6lPTn5+PgAhISEApKWlUVFRQb9+/Rxt2rZtS1xcHCtWaJ0+V6xYQceOHYmMjHS0SUlJoaCggM2bNzvanH6MqjZVxygvLyctLc2pjdFopF+/fo42Z1NWVkZBQYHTw5OcOLlm1U57Y1qGN9yRVX91e/dYvrf1oQxvOLQeDq7VuyQhhBD14KJDjt1uZ+zYsfTu3ZsOHToAkJ2djdlsJigoyKltZGQk2dnZjjanB5yq/VX7ztemoKCA0tJSjhw5gs1mO2ubqmOczaRJkwgMDHQ8YmNja/7BXVjhvo0AHPCKI9DPW+dqXMd1HaMoNwczx5akbVjzH30LEkIIUS8uOuSMHj2aTZs28e2339ZmPXVqwoQJ5OfnOx779u3Tu6RaZc/RRlYVWlvoXIlr8TN7MbhzDF9XXqNt2Pg9lObpWpMQQoi6d1EhZ8yYMcyePZtFixbRpEkTx/aoqCjKy8vJy8tzap+Tk0NUVJSjzV9HW1U9v1Abq9WKr68vYWFhmEyms7apOsbZWCwWrFar08OTWAp2A2AIa61zJa7ntu6xpKnWZKg4qCyF9e4TzoUQQlycGoUcpRRjxoxh5syZLFy4kPj4eKf9iYmJeHt7s2DBAse2jIwMsrKySE5OBiA5OZmNGzc6jYJKTU3FarWSkJDgaHP6MaraVB3DbDaTmJjo1MZut7NgwQJHmwan4gTWMu1WXUCThrkw5/l0iwuibZSVL6uu5qz5j8yALIQQHq5GIWf06NF89dVXfPPNNwQEBJCdnU12djalpaUABAYGMmLECMaNG8eiRYtIS0vj/vvvJzk5mV69tAnZ+vfvT0JCAvfccw/r169n/vz5PP/884wePRqLxQLAyJEj2b17N+PHj2fbtm189NFHTJ8+nSeeeMJRy7hx4/jss8+YOnUqW7duZdSoURQXF3P//ffX1rlxL8czMaIoUH40aexZfY1qg8Fg4O5eTZll600pPtoaX3uX612WEEKIulSTIVvAWR9ffPGFo01paal69NFHVXBwsPLz81M33XSTOnTokNNx9uzZowYOHKh8fX1VWFiYevLJJ1VFRYVTm0WLFqkuXboos9msmjdv7vQeVT744AMVFxenzGaz6tmzp1q5cmVNPo5HDSGv2PSjUhOtat0LXdTBvBK9y3FJhScqVMILv6ivn7tRG04+/T69SxJCCHERqvv9bVCq4V6zLygoIDAwkPz8fLfvn3Nk3iTCVr7Gz+pyrn9pNgaDQe+SXNJzMzeSvnopcyx/A6MXjN0I1hi9yxJCCFED1f3+lrWrPMSJ7O0AFDRqKgHnPIYlNWWzasZqe1uwV8Kfn+tdkhBCiDoiIcdDGI9pa1bZgmT4+PkkxFjpFhfEvysHaBvWfAEVpfoWJYQQok5IyPEQAcV7AbBEycKcF3J3r6ak2rtz0BABpcdgw3S9SxJCCFEHJOR4gtLjBNjyAAiKbatvLW7guo7RWP0s/Kf8Wm3Dqo9lOLkQQnggCTme4Kg2CWC2CiY2MkLnYlyfj7eJO3vEMd12JScMPpC7BTKX6F2WEEKIWiYhxwMUH9KWc8i0R9MszE/natzDvclNKTb6M62ij7Zh5cf6FiSEEKLWScjxAAUHtJCT7d0YP7OXztW4h5ggXwZ2iGKqLUXbsH0eHN2lb1FCCCFqlYQcD2A7vAOAIv9m+hbiZh64PJ7dKoaF9m6AguXv612SEEKIWiQhxwN452l9cuwhMny8JrrFBdMlNojJFddrG9L/B4U553+REEIItyEhx90pRVDJyeHjkbL6eE09cHk8f6o2rKcN2Mpg1WS9SxJCCFFLJOS4u8JsLOoElcpIaJNWelfjdgZ2iCLK6su/ygdpG/78D5wo0LcoIYQQtUJCjptTR7TlHPapcJpFBOtcjfvxNhm597Km/Gbvxl5jLJTlQ9oXepclhBCiFkjIcXNFh7ROx3tUFLEhMnz8Ygzr2RQ/szf/KhuobVjxEVSW6VuUEEKISyYhx81VhZyj5sb4eJt0rsY9Bfp5M7RnHLNsl3PMGApF2bBhmt5lCSGEuEQSctxc5dFMAMoCYnWuxL2N6BMPJm8+Kju5cOfvb4OtUt+ihBBCXBIJOW7Ou2CP9kNwvK51uLvoQF+GdGnMN7ZrKDQGwvFM2DhD77KEEEJcAgk57kwprKX7AfCJbKlzMe7vkb7NKcGHj6r65ix9Q67mCCGEG5OQ485Kj+NnLwYgtInMkXOpWkYE0D8hkv/arqXYZIVju2DT93qXJYQQ4iJJyHFj9tNWH28aFaZzNZ5h5JUtKMaXj0+/mmO36VuUEEKIiyIhx40VHtLmyMlSkTQJ9tW5Gs/QLS6YXs1D+KLyWkpMAXB0B2yeqXdZQgghLoKEHDdWeHL4+BHvGLxN8kdZWx6/pjVF+PFJ+cmRVktel6s5QgjhhuSb0Y1VHtFuVxU3kuHjtSm5RSi9mofwn4oUSk3+cCRDruYIIYQbkpDjxrzytYU5bYHN9C3EAz1+TWsK8ePTqqs5iyfJSCshhHAzEnLcmH+JNnzcO7yFzpV4nqqrOZ9VDKDYFARHd0L613qXJYQQogYk5LirilKCKg8DEBAtq4/Xhaq+Oe+WD9Y2LPknVJTqW5QQQohqk5Djro5rt6oKlC/RUTE6F+OZqq7m/LfiGvK8I6DgAPz5ud5lCSGEqCYJOW6q7PBOQBs+HhfWSOdqPNfj17SmDDP/LB2ibfj9LTiRr2tNQgghqkdCjpvKP6ANHz9ojCLQ11vnajxXcotQLmsRyvTKPuSY46D0OCz/l95lCSGEqAYJOW7qRK52JafAp4nOlXi+Zwa0xYaJicU3axtWfAhFufoWJYQQ4oIk5Lgpw/E9AJRZm+pbSAPQOTaIgR2imGfrQaa5DVQUa52QhRBCuDQJOW7Kp2gfAMaQeJ0raRieSmmDyWhkQtFt2oY1X8DhDH2LEkIIcV4SctyRUljLswFoFNVc52Iahhbh/tzevQkr7QmstiSDssGvL+hdlhBCiPOQkOOOio9gUWXYlIGwaLmSU18ev6Y1Fi8jzxTcit3gBTvmw66FepclhBDiHCTkuCH7yTlysgkhNjxI32IakKhAH+7vHU+miuZH7+u0jfOfl8U7hRDCRUnIcUMFh3YBcECFEx3oo3M1Dcuovi0I9PXmpYLrKfO2Qu5mWPeV3mUJIYQ4Cwk5bqggWws5x81ReJnkj7A+Bfp58/g1rcjHn3/ZTg4pX/h/UFaob2FCCCHOIN+Qbqj86B4ASv1kOQc93JPclOZhjfi45GqOWZpAcS4sfVPvsoQQQvyFhBw3ZMrXho/brHE6V9IweZuM/O26dlTgxd+K79Q2rvgQjuzQtzAhhBBOJOS4Id+SAwB4hcpEgHq5pl0El7cMY15lVzb59QR7BfwyHpTSuzQhhBAnSchxN0oRXDVHToTMkaMXg8HA89e3w2gwMPr4ndiNZm04+daf9S5NCCHESRJy3E3xESyUYVcGQmSOHF21jbJyZ8849qoopltu0jbO/xuUl+hbmBBCCOAiQs7SpUsZPHgwMTExGAwGZs2a5bT/vvvuw2AwOD0GDBjg1ObYsWMMGzYMq9VKUFAQI0aMoKioyKnNhg0b6NOnDz4+PsTGxvL666+fUcuMGTNo27YtPj4+dOzYkblz59b047idymN7AMgmmMZhgfoWIxh3bWsCLF68dHwART4xkL8Pfn9L77KEEEJwESGnuLiYzp078+GHH56zzYABAzh06JDj8b///c9p/7Bhw9i8eTOpqanMnj2bpUuX8vDDDzv2FxQU0L9/f5o2bUpaWhpvvPEGL730Ep9++qmjzfLlyxk6dCgjRoxg3bp1DBkyhCFDhrBp06aafiS3kn9yjpyDKpxwf4vO1YgwfwtP9m/NCSy8cOIubePy9+HoLn0LE0IIgUGpi+8paTAYmDlzJkOGDHFsu++++8jLyzvjCk+VrVu3kpCQwJ9//kn37t0BmDdvHtdddx379+8nJiaGyZMn89xzz5GdnY3ZbAbg2WefZdasWWzbtg2AO+64g+LiYmbPnu04dq9evejSpQsff/xxteovKCggMDCQ/Px8rFbrRZyB+rf3p1dpuvaf/GrqS/8XftK7HAFU2uzc8K8/2HIon/lh79GmaDW07AfDvgODQe/yhBDC41T3+7tO+uQsXryYiIgI2rRpw6hRozh69Khj34oVKwgKCnIEHIB+/fphNBpZtWqVo80VV1zhCDgAKSkpZGRkcPz4cUebfv36Ob1vSkoKK1asOGddZWVlFBQUOD3cTeXJOXKK/RrrW4hw8DIZeWVIB8DAyKN3aJ2Qd/4Gm2fqXZoQQjRotR5yBgwYwH//+18WLFjAP//5T5YsWcLAgQOx2bT1fbKzs4mIiHB6jZeXFyEhIWRnZzvaREZGOrWpen6hNlX7z2bSpEkEBgY6HrGxsZf2YXVgKtDmyKkMaKJzJeJ0iU2Dub17EzJVNF+bb9M2/vIMlB7XtzAhhGjAaj3k3Hnnndxwww107NiRIUOGMHv2bP78808WL15c229VYxMmTCA/P9/x2Ldvn94l1VjVHDmmkGb6FiLO8MyAtgT6evNKXn/yGjXXZkJOfVHvsoQQosGq8yHkzZs3JywsjJ07dwIQFRVFbm6uU5vKykqOHTtGVFSUo01OTo5Tm6rnF2pTtf9sLBYLVqvV6eFWlCLo5Bw5vhEyfNzVhPpbGD+gDeV481jRfdrGtf+FPct0rUsIIRqqOg85+/fv5+jRo0RHRwOQnJxMXl4eaWlpjjYLFy7EbreTlJTkaLN06VIqKiocbVJTU2nTpg3BwcGONgsWLHB6r9TUVJKTk+v6I+mn5CgWpc2RExwlIccV3dkjjs5NAlla1pLfAwdrG38eCxUndK1LCCEaohqHnKKiItLT00lPTwcgMzOT9PR0srKyKCoq4umnn2blypXs2bOHBQsWcOONN9KyZUtSUlIAaNeuHQMGDOChhx5i9erV/PHHH4wZM4Y777yTmBhtwcm77roLs9nMiBEj2Lx5M9OmTeO9995j3Lhxjjoef/xx5s2bx1tvvcW2bdt46aWXWLNmDWPGjKmF0+Ka7Mf2ApAjc+S4LJPRwD9u6ojJaGB0zg2U+YTD0R2w7G29SxNCiIZH1dCiRYsUcMZj+PDhqqSkRPXv31+Fh4crb29v1bRpU/XQQw+p7Oxsp2McPXpUDR06VPn7+yur1aruv/9+VVhY6NRm/fr16vLLL1cWi0U1btxYvfbaa2fUMn36dNW6dWtlNptV+/bt1Zw5c2r0WfLz8xWg8vPza3oadJH35zSlJlrVny90V+WVNr3LEecxae5W1fSZ2erZV15WaqJVqb+HKpWzRe+yhBDCI1T3+/uS5slxd+42T87+Of+kyZ+vMt/Yh5QXZ1/4BUI3JypspLy7lL1Hi/kl4iPaFfwBMV1hxG9g8tK7PCGEcGu6zpMj6kb5MW00WKnvuTtXC9fg421i0s0dAQP35Q6l0myFg+vgj3f1Lk0IIRoMCTnuJH8/AJX+MToXIqrjshZh3NkjlhxCeMP4gLZx8WuQs1nfwoQQooGQkONGzCXa8HFjkEwE6C4mDGxHeICFT/J6sDO4D9grYNYosFVc+MVCCCEuiYQcN+Jfps0L5Bsap3MloroC/bx5+Yb2gIG7c4ZSaQmEQ+th2bt6lyaEEB5PQo67qCzHatOWCAiKaqZvLaJGBnaMZlCnaLLtQbxuHKFtXPJPyN6ob2FCCOHhJOS4CVV4ECOKMuVNRJQszulu/u/GDoT5W/j0eCIZQVecum1VWa53aUII4bEk5LiJolxtIsBDKoTGwX46VyNqKriRmddOjra6O2coFZZg7UrOktf0Lk0IITyWhBw3kZe9B4AjpjB8vE36FiMuSr+ESG5LbMJhFcjL6iFt4+9vw54/9C1MCCE8lIQcN1FyWLuSU2iO1LkScSleHJxA4yBfvizoQlrwdYCCmY9AaZ7epQkhhMeRkOMmKvMOAFDmJxMBurMAH29ev7UTAPceuoVS/1jI3wdzn9K5MiGE8DwSctyEqfCg9oNVOh27u94twxie3JRifBld+ijKYIKNM2DDdL1LE0IIjyIhx034lh4CwDskVudKRG14dmA7WoQ3YmFxU34MvFvbOOdJOL5X38KEEMKDSMhxE9aKwwA0CpOJAD2Br9nE+0O7YjYZeTK7H7lBXaCsQOufY7fpXZ4QQngECTnuoLKMYJUHQHB0c31rEbWmfUwgzwxsiw0TQ4/cj83bH7JWaBMFCiGEuGQSctxAWdXq48pMZKR0PPYkD/RuxpVtwtlVGc7rXo9oG5e8DrsX61qXEEJ4Agk5buDYoT0A5BBKoJ9Z32JErTIYDLx5W2fC/C18cjyRNaGDAQXfPwSFOXqXJ4QQbk1CjhsozNkDwDGvcAwGg77FiFoX5m/hrds7AzDswC0UBraB4lz44UHpnyOEEJdAQo4bKDuWBUCxRSYC9FR9W4fz4OXxlGHm7vxR2L39IHMpLH1T79KEEMJtSchxAypfmyOnvJH0x/Fk4we0pXNsEOtPRPCeZZS2cfEkLewIIYSoMQk5bsCrSAs5ytpE50pEXTJ7Gfnwrq4E+nrz3pFE1oZcj9Y/50EoytW7PCGEcDsSctxAoxPZAJhDJOR4uibBfrxzh9Y/566Dt1AQ0BKKcuC7B8BWqXN1QgjhXiTkuIHAypMTAYY31bkSUR+ubhvJo1e24AQWhuWPwu7lB3t+hwUv6V2aEEK4FQk5rq6ilCBVAEBwVLzOxYj6Mu7a1iTFh7CxPJp/mB/TNi7/ADbP1LcwIYRwIxJyXFzRYW0to2JlISpSRlc1FF4mIx8M7UqYv4V/H+vEwtCh2o5ZoyF3q77FCSGEm5CQ4+KqJgLMNYTiZ/HWtxhRryKsPnwwtCsmo4GHDlzHwZAkqCiGb4fBiXy9yxNCCJcnIcfFVV3JOe4VoXMlQg/JLUJ57rp22DBxY/YDlPlFw7FdMHMk2O16lyeEEC5NQo6LqziqrVtV4iO3qhqq+3s34+ZujTlsD+CB0sdRJgtkzIXfZaJAIYQ4Hwk5Lk4VHACgolG0zpUIvRgMBl69qSMdGwfyR2kc71pOLuS56FXYNlff4oQQwoVJyHFx3sWHtB8CG+tbiNCVj7eJT+5JJLSRmfeO9eL3oCE4JgrM3qR3eUII4ZIk5Lg4f8dEgLE6VyL0FhPky0fDuuFlNHB/9s0cCO6hdUT+31AoOqx3eUII4XIk5Li4oMojAPjLRIACSGoeysTBCVTixfXZD1Hi3xTys2D6PVBZpnd5QgjhUiTkuDBVXkwghQCExjTXuRrhKu7u1ZShPWM5rvy5veBxbGYrZK2A2eNAKb3LE0IIlyEhx4XlZe8BoFD5EhEuQ8iFxmAw8PKNHbisRSibyqN4Sj2GMhgh/StY8aHe5QkhhMuQkOPCjp+cCPCwIRSzl/xRiVO8TUYmD0ukeVgjZhYm8Lnfg9qO1Bdg+6/6FieEEC5CvjldWPERbSLAfG+5iiPOFOjnzX/u60GQnzf/ONqXZdZBoOzaiuUy4koIISTkuLKKY9pEgMU+UTpXIlxVs7BGfHJ3It4mI/fn3kGWNRHKC+Hr26DgoN7lCSGEriTkuDDDyS+pSn8JOeLckpqHMunmTlTgxfW5j1Dg3xwKD8LXt0NZod7lCSGEbiTkuDBziTYRoDGoic6VCFd3a2ITHr2yBQX4c/2xsZT7hEHORphxH9gq9C5PCCF0ISHHhfmX5QBgCYnTuRLhDp7q34YhXWLIsocxrGQcdi9f2PkbzHlShpYLIRokCTkuLLhSm8U2IEImAhQXZjQaeP3WzvRuGcqf5c14yn5yaPnaqbDsbb3LE0KIeichx0XZThRipRiQiQBF9Zm9jHx8dyLtoq38UNKZ971PDi1f8DJs/E7f4oQQop7VOOQsXbqUwYMHExMTg8FgYNasWU77lVK8+OKLREdH4+vrS79+/dixY4dTm2PHjjFs2DCsVitBQUGMGDGCoqIipzYbNmygT58++Pj4EBsby+uvv35GLTNmzKBt27b4+PjQsWNH5s71nBWZjx3cDUCB8iMsNFTnaoQ7CfDxZsr9PWgc5Ms7BVfyo+8QbcesUbBnma61CSFEfapxyCkuLqZz5858+OHZZ1Z9/fXXef/99/n4449ZtWoVjRo1IiUlhRMnTjjaDBs2jM2bN5Oamsrs2bNZunQpDz/8sGN/QUEB/fv3p2nTpqSlpfHGG2/w0ksv8emnnzraLF++nKFDhzJixAjWrVvHkCFDGDJkCJs2ecb8IMeztTlyjhhDMRkNOlcj3E2k1YepD/Qg0NebscdvJc3vcrCVa4t5Zm/UuzwhhKgf6hIAaubMmY7ndrtdRUVFqTfeeMOxLS8vT1ksFvW///1PKaXUli1bFKD+/PNPR5tffvlFGQwGdeDAAaWUUh999JEKDg5WZWVljjbPPPOMatOmjeP57bffrgYNGuRUT1JSknrkkUeqXX9+fr4CVH5+frVfU1/Sf3xfqYlWtfYfV+tdinBjf2YeVa2fm6taP/OD2v16H6UmWpV6o5VSxzL1Lk0IIS5adb+/a7VPTmZmJtnZ2fTr18+xLTAwkKSkJFasWAHAihUrCAoKonv37o42/fr1w2g0smrVKkebK664ArPZ7GiTkpJCRkYGx48fd7Q5/X2q2lS9z9mUlZVRUFDg9HBVFce1iQBLfGWOHHHxujcL4b07u1JuMHPj0THk+rWEohz48iYoOqx3eUIIUadqNeRkZ2cDEBkZ6bQ9MjLSsS87O5uICOdlCry8vAgJCXFqc7ZjnP4e52pTtf9sJk2aRGBgoOMRGxtb049Yb4yF2kSANv9onSsR7m5AhyhevakjBTTi+mNPUOgTDcd2wze3yWSBQgiP1qBGV02YMIH8/HzHY9++fXqXdE6WEi2sGQMb61yJ8ARDe8bx7MC25BLMDflPccIcDAfXwbS7obJc7/KEEKJO1GrIiYrSbq3k5OQ4bc/JyXHsi4qKIjc312l/ZWUlx44dc2pztmOc/h7nalO1/2wsFgtWq9Xp4aoCqiYCDJWJAEXtGNm3BSP7tiBTRXNH0TgqTX6wezHMGgl2u97lCSFEravVkBMfH09UVBQLFixwbCsoKGDVqlUkJycDkJycTF5eHmlpaY42CxcuxG63k5SU5GizdOlSKipOTUefmppKmzZtCA4OdrQ5/X2q2lS9j7sLsR0BZCJAUbueGdCGoT3jWG9vwUNlj2M3eMGm72H+BJkVWQjhcWoccoqKikhPTyc9PR3QOhunp6eTlZWFwWBg7Nix/N///R8//fQTGzdu5N577yUmJoYhQ4YA0K5dOwYMGMBDDz3E6tWr+eOPPxgzZgx33nknMTExANx1112YzWZGjBjB5s2bmTZtGu+99x7jxo1z1PH4448zb9483nrrLbZt28ZLL73EmjVrGDNmzKWfFZ1VluThTwkAodHxOlcjPInBYOD/hnTg+k7RLKrsyHjbSG3Hqo9hyZlzUQkhhFur6bCtRYsWKeCMx/Dhw5VS2jDyF154QUVGRiqLxaKuueYalZGR4XSMo0ePqqFDhyp/f39ltVrV/fffrwoLC53arF+/Xl1++eXKYrGoxo0bq9dee+2MWqZPn65at26tzGazat++vZozZ06NPourDiE/vHOdUhOtKu/FaFVps+tdjvBAZRU2de+/V6mmz8xWkyY+pg0tn2hVavmHepcmhBAXVN3vb4NSDfcadUFBAYGBgeTn57tU/5ydy2fR8tfh7DQ0peXEDXqXIzxUabmNe/69ijV7j/OM74+MUtO0HYPfh8Th+hYnhBDnUd3v7wY1uspdlB7JAiDfO+ICLYW4eL5mE/++rwftY6z8s/QGvjTeoO34+XGtn44QQrg5CTkuqPLkRIClPpEXaCnEpQn09ebLEUm0jbLyQskd/GBMART88DBkzNO7PCGEuCQSclyQofAQABX+MTpXIhqCkEZmvnowiZYRATxZcg/zjVeAvRKm3wu7l+hdnhBCXDQJOS7IUqKFHGOQTAQo6keYv4VvHkyiWVgAo0se5HdTT7CVaQt67vtT7/KEEOKiSMhxQVUTAZpDXHfZCeF5Iqw+fPNQEtEhAYwoHs0aUxeoKIavb4FD0gFeCOF+JOS4GqUIsWkLJ8pEgKK+RQf68s2DvQgPsnJP8WNsNrWFE/nw5RDI2aJ3eUIIUSMSclyMvTQPP04AECITAQodxIb48c1DSQRagxha/CQZppZQchSmDobcbXqXJ4QQ1SYhx8Xk5+wB4LjyJzwkWN9iRIPVNLQRXz+UhE9ACLcVj2e7sQWUHNGCzuHtepcnhBDVIiHHxeTn7AXgsCEMb5P88Qj9tAj3Z9ojyfhZw7it5Bl2GOOhOBemXg9HduhdnhBCXJB8i7qYksNayMmTiQCFC4gPa8S0R3rRKDCM20ueYZexKRTlaFd0ju7SuzwhhDgvCTkupmoiwBKZCFC4iKahjbQrOkGR3FYygd2GOCg8BFOuh2O79S5PCCHOSUKOizEUHgSg0j9a50qEOCU2xE+7ohMSyW2lE8g0xELhQZgyGI7v0bs8IYQ4Kwk5LsZSnA2AIbCJzpUI4axJsB/THk7GPzSa20snsMfQGAr2nww6e/UuTwghziAhx8X4l2sTAVpkIkDhgmKCfLWgE9aY20r/xl5DDORnwZRBcutKCOFyJOS4EqUIrtQmAmwkEwEKFxUV6MO0h3thDW/C7aV/Yy8xkL8Pvhgko66EEC5FQo4LUaXH8aUMgJDoZvoWI8R5RFh9mPZIMqHRzbj1xPPspMnJPjqDZMJAIYTLkJDjQopytX4NR1UAkSFB+hYjxAWE+Vv438O9iGsaz+0nnmebitOGl08ZBNmb9C5PCCEk5LiSvJOzHecawvDxNulbjBDVEOjrzZcjetK+VXPuLHuOTSr+5MzI18PBdL3LE0I0cBJyXIhMBCjckZ/Zi8+Hd6dnQkvuKvsb6+wtofQ4/PcG2J+md3lCiAZMQo4LqTy+H4BSmQhQuBmLl4mPhnWjX9fW3FP+LH/a22irl//3RshaqXd5QogGSkKOKynQJgIsbyQTAQr342Uy8uZtnbmpVzuGlz/DclsClBfClzdD5lK9yxNCNEASclyIpUQLOTIRoHBXRqOBl29sz/Ar2/NAxdMstXWEimLUV7dCxi96lyeEaGAk5LgQ/zJtIkBziIQc4b4MBgPPDGjL2IGdeajiSX61JWKwlaG+HQYbputdnhCiAZGQ4yqUIuTkRID+EfE6FyPEpRvZtwX/uK0HY2xP8L2tDwZlQ/3wMKz+TO/ShBANhJfeBYiTio9gpgK7MhAcJbMdC89wa2ITQhuZGf21iYJKP+73mg9zn4KyArh8HBgMepcohPBgciXHRRQfzgQglyCiQqw6VyNE7bmqbQRfPZTMe94jeK/yJm3jgpch9UVQSt/ihBAeTUKOi8g7pIWcHEMY/ha5wCY8S7e4YL4b1Zvp/vfySsUwbePy9+Hnx8Fu07c4IYTHkpDjIkoO7wGgwFvmyBGeqWWEP9+PuoxlYXfydMXD2DDA2qnw/YNQWa53eUIIDyQhx0VUnJwIsMRX5sgRnisq0IfpjySzN/ZmxpQ/RrkyweYf4NuhUF6sd3lCCA8jIcdFGAu0kGMLaKxzJULUrUA/b/47oieq3Y08WPEUJcoCO39DTR0MxUf0Lk8I4UEk5LgIn5JDAJhCYnWuRIi65+Nt4sNh3Wh12RCGlf+NY8ofw4E01L/7w/E9epcnhPAQEnJcRGB5NgC+YTJ8XDQMJqOBF65P4Mbrb+S2ipfYr8IwHNuF/fP+kL1R7/KEEB5AQo4rqCwj2H4cgMDo5joXI0T9uq93PM/efQN32V9mqz0WY3EO9v8MlPWuhBCXTEKOC6jMOwDACeVNdGSMztUIUf+uTYjkg4cHMcr7H6y0t8NYXoj9y1tg0w96lyaEcGMSclzA8UO7AThIGGEBPjpXI4Q+OscG8eXoa/l74CvMtfXEaC9HffcArPpE79KEEG5KQo4LKMjRJgI8ZorAaJRp7kXDFRvix7ejruTLJhOZWnktBhT8Mh5++7vMjiyEqDEJOS6g7EgWAIU+UTpXIoT+Av28mTIimfQOz/F6xe3axmVvY585UiYNFELUiIQcF6DytTlyyhtJfxwhACxeJt6+owuN+j3D0xUPU6mMGDd8S+WXN0Npnt7lCSHchIQcF+BVpHU8JrCJvoUI4UIMBgOjr2rJNUPH8ah9PEXKB6+9v1P+2bVwfK/e5Qkh3ICEHBcQUHoQAEuoTAQoxF8N6BDNYyMfZaT3PzikQjAf2075J1fDgbV6lyaEcHEScvRmtxNamQNAo8iWOhcjhGvq0DiQtx+7m+dC32WrPQ7ziSNU/uc6yPhF79KEEC6s1kPOSy+9hMFgcHq0bdvWsf/EiROMHj2a0NBQ/P39ueWWW8jJyXE6RlZWFoMGDcLPz4+IiAiefvppKisrndosXryYbt26YbFYaNmyJVOmTKntj1IvVFE2FsqpVEZCY2QiQCHOJcLqw0ejruc/rSezxNYJL1sp9v/dhX2lDDEXQpxdnVzJad++PYcOHXI8li1b5tj3xBNP8PPPPzNjxgyWLFnCwYMHufnmmx37bTYbgwYNory8nOXLlzN16lSmTJnCiy++6GiTmZnJoEGDuOqqq0hPT2fs2LE8+OCDzJ8/vy4+Tp0qOLQTgEOE0jjMqnM1Qrg2H28Trw/rzcYrPuWbyqswYsc4bzxls58Bu03v8oQQLqZOQo6XlxdRUVGOR1hYGAD5+fn8+9//5u233+bqq68mMTGRL774guXLl7Ny5UoAfv31V7Zs2cJXX31Fly5dGDhwIK+88goffvgh5eXa8NGPP/6Y+Ph43nrrLdq1a8eYMWO49dZbeeedd+ri49Sp4wd2AJBrjMTiZdK5GiFcn8FgYMy17Qi87SPetA8FwLLmY4q+vAvKS3SuTgjhSuok5OzYsYOYmBiaN2/OsGHDyMrS5oFJS0ujoqKCfv36Odq2bduWuLg4VqxYAcCKFSvo2LEjkZGRjjYpKSkUFBSwefNmR5vTj1HVpuoY51JWVkZBQYHTQ2+ludpsx/k+jXWuRAj3MqhzDAMe+ScveI2jTHnhnzmP/MnXQsEhvUsTQriIWg85SUlJTJkyhXnz5jF58mQyMzPp06cPhYWFZGdnYzabCQoKcnpNZGQk2dnaKtzZ2dlOAadqf9W+87UpKCigtLT0nLVNmjSJwMBAxyM2Vv/RTOrkUNiyAP1rEcLddGgcyONjn+UfYa9xTPkTeHwTRf/qg33/Or1LE0K4gFoPOQMHDuS2226jU6dOpKSkMHfuXPLy8pg+fXptv1WNTZgwgfz8fMdj3759epeEpVC7ymUIbqZvIUK4qTB/Cy88OoIvO3zBdntj/MsPU/HvFErTv9e7NCGEzup8CHlQUBCtW7dm586dREVFUV5eTl5enlObnJwcoqK0JQ2ioqLOGG1V9fxCbaxWK76+vuesxWKxYLVanR56CzyhzZHjF9lC50qEcF/eJiOP39afLdf9wBJ7FyyqDN9ZD3Bs7iuy5pUQDVidh5yioiJ27dpFdHQ0iYmJeHt7s2DBAsf+jIwMsrKySE5OBiA5OZmNGzeSm5vraJOamorVaiUhIcHR5vRjVLWpOobbqCwjxH4EgKDGMkeOEJdqSK+2BI34gW9N1wMQsvpNsv8zDCrOfRtbCOG5aj3kPPXUUyxZsoQ9e/awfPlybrrpJkwmE0OHDiUwMJARI0Ywbtw4Fi1aRFpaGvfffz/Jycn06tULgP79+5OQkMA999zD+vXrmT9/Ps8//zyjR4/GYrEAMHLkSHbv3s348ePZtm0bH330EdOnT+eJJ56o7Y9Tp8qP7cWIokRZiImJ07scITxC56ahXDP2P3xifZwKZSJq3xyy378Ge750SBaioan1kLN//36GDh1KmzZtuP322wkNDWXlypWEh4cD8M4773D99ddzyy23cMUVVxAVFcUPP/zgeL3JZGL27NmYTCaSk5O5++67uffee3n55ZcdbeLj45kzZw6pqal07tyZt956i88//5yUlJTa/jh16ug+bfj4AcIJ9bfoXI0QniM8wML9j73El63e5bjyJ6pwM3nv96FwT5repQkh6pFBqYZ7w7qgoIDAwEDy8/N16Z+zffa7tF4zkZVePen1fGq9v78QDcHcxX/QZtGDtDAcpBQLh699n7jed+pdlhDiElT3+1vWrtJR+ZFMAIr8ZI4cIerKdVf25sS981ll7IIvZcSlPsLmr58Bu13v0oQQdUxCjo688rSQYwtspm8hQni49i3iaDPuF1IDtCVk2u/4mC3vDOZE0XGdKxNC1CUJOToKKNbmyDGFt9K5EiE8X5C/H9c88R9+az2RMuVNQuEyDr99OQd3btS7NCFEHZGQoxe7nbCKAwD4N26jczFCNAxGo4F+d41jy4BvySGEWPt+Ar66lvQF3+pdmhCiDkjI0Yktfz8WyilXJho3ba13OUI0KF2T+6EeWsxW7wQCKKXT0pEs/fez2GzST0cITyIhRydH924BYB+RxIQE6FyNEA1PVOOmtHhqEX+G3YTRoLhi32TWvHEDh48e1bs0IUQtkZCjk7z9WwHI9W6CyWjQuRohGiazxYceY6awvsvfqVAmkk78Tv4HV7JmrcynI4QnkJCjk/IcbSLAokZNda5ECNF5yFhybv6eY4ZgWpJFyx8H8930qVTK7Ssh3JqEHJ145+8GwBbSXOdKhBAATTpfhd+Y39nn244gQzE3b36cGe+M5VBesd6lCSEukoQcnQSW7AXAEikjq4RwFT6hscSOW8zeprdgNCiGFk1l+7uD+X3DDr1LE0JcBAk5erBVEFaZDUBoXDudixFCOPH2oen9/+Hw1W9Sjjd9SaPpdwP5z4xZVMjtKyHcioQcHZTm7sILOyXKQpO4FnqXI4Q4i/ArHoIRv3LcHE2c8TB3bXqQj9/9O/uPl+hdmhCimiTk6OBwpjbDapYhmhBZfVwIl2WO7Ubw2OXkRvXFx1DB/yt8l5Xv3U3qhr16lyaEqAYJOToo2b8JgBxLvM6VCCEuyC+EiIdnkd9rPHYM3MoCIr+7kTem/UppuU3v6oQQ5yEhRwcqV5sjpyRI1qwSwi0YjQQOeA7b0O8o8QqkkzGTh7bcx8vvvMfmg/l6VyeEOAcJOTrwL9gJgClSOh0L4U682/TDb8wfFIZ2IshQzD9KXmbR5Cf499Id2O1K7/KEEH8hIae+2W1Elmurjwc366RzMUKIGguKJWDUb5zocj9Gg2KM6XsSUu9l7Oe/kFt4Qu/qhBCnkZBTz8pyd2KmglJlpmnLBL3LEUJcDC8LPkPeRd38GRUmP5JNW3jxwCO8/M4HLNyWo3d1QoiTJOTUs+yd6QBkGhoTHuCrbzFCiEti6HQ73qN+50RYe8IMBfzL/n9s++opXv5xPScqpFOyEHqTkFPPivZrw8eP+DbHYJCFOYVwe2Et8XlkIZWJIwB41Osnrkt7kAffn0VGdqHOxQnRsEnIqWeGw9sAOBHcWudKhBC1xtsHr8Fvw21TqfT2p7txOx8UPMZbH7zLA1P+5L8r9rAztwilpHOyEPXJS+8CGpqgfC3keEV30LkSIUStaz8Er+jOVEy7j+CcdD71fpOFu37j2+1X8Yq9K4H+jejVPIRezUPp1TyUFuGN5IquEHVIQk59KisiqnI/AKGteuhcjBCiToTE4/1QKvw2EVZ+xNWmdK42pZOnGjH3RBI/buzNCxvaoDAS5m8h6WToSW4eQotwfwk9QtQig2rA108LCgoIDAwkPz8fq9Va5+93bOtSQqYNJlsFE/jcLnzNpjp/TyGEjo7ugrQvYMMMKMp2bD5iCueHil78UNGbbSrOsT3M30zSyas8EnqEOLfqfn9LyKnHkLPtxzdpu+4VVnr1oNfzv9X5+wkhXITdBnt+18LO1p+grMCx64hfC1K9+vLpsa5kVoY6vSzM30xSfCi9moeQ1DyUVhESeoSA6n9/y+2qelR5IB2AgqD2+hYihKhfRhM0v1J7DHoTts+HjTNgx6+ElexiKLsY6gWFMd1ZE3AN04q7sWi/4khROXM2HmLOxkMAhDQy06NZMD3jQ0mKD6FdtBWTUUKPEOciIaceWY9vAcCrSRd9CxFC6MfbF9oP0R6lx2HLT1rg2bOMgNw1XJW7hqsMJuytr2BP9HWk2ruzJKuctVnHOVZczvzNOczfrE04GGDxIrFZMD3jQ0iKD6Fj4yDMXjJoVogqcruqnm5XqfJibK/G4oWNDbctp1N7uZojhDhN/gHY/ANs+h4Orju13WSGVv2pbHcTG/wvY9W+UlZnHmXNnuMUllU6HcLiZaRb3KnQ0zUuWPr+CY8kfXKqoT5DzuGNvxH+/S0cUiEE/W0Hvha5iCaEOIeju7Sws/E7OJJxart3I2h7HXS4BVvzq9l2+ASrM485HkeLy50O42U00KlJoOP2VmKzYKw+3vX8YYSofRJyqqE+Q86Wb58nYdsH/G65gj4Tfq7T9xJCeAilIGezFng2fQd5Waf2+QRBwg3Q4RZo1gdlMLLrcPHJwHOUVZnHOJTvvGCowQAJ0VbHlZ4ezUII9bfU72cSohZIyKmG+gw5GW/1p03hKubHjSPlgYl1+l5CCA+kFOxfowWezT9A0WkLgTaKgPY3QcdboUkPMBhQSrH/eOmpKz17jpF5pPiMw7aM8KdVhD/hARbC/S3afwMshPmf+q/08xGuRkJONdRbyLHbKXq5Cf4Us/LamfTqfXXdvZcQwvPZbbBnmRZ4tvwIJ/JO7QuMgw43a4EnsoN2+eak3IITrN5z6vbWtmqurRXk5024/6ngc2YQMhPubyGkkRkvkwQiUfck5FRDfYWcvJ2rCPqqP4XKl8qndhMc4Fdn7yWEaGAqy2H3Iq3/zrY5UHHa1Zqw1tDhVu2WVljLM156vFgbtbX/eCmHC8s4UlTG4cIyDlf9t7CMSnv1vyIMBgjxMxPmbyEswOwIRmEnrxKFVQWiAAshfhKIxMWTkFMN9RVyNn/7PO23fcBy715c9tz8OnsfIUQDV14CO+ZrgWdHKtjKTu2L7AAJN0LCEAiv3gLBdrsiv7TirOHn9OdHiso5VlxGDfKQIxBVXRGqCj9hZwQjM6GNLDIfkHAikwG6EJ89iwAoiu2rcyVCCI9m9tP65rS/CU7ka1d2Nn4HuxdDzibtsegfEN5OCzzth0B4W6dbWqczGg0ENzIT3MhMq8iA8761za44VlzOkaJTV4S0n8s5co5AdLS4/OSIsPPfNjMYILSR2RGAqm6Rnd5vqOrnkEZmCUTCQa7k1PGVnIrCwxjfaoUJxcbbltGxfcc6eR8hhDinkmNa4NnyoxZ47BWn9oW11q7uJNwIke3PGXhq0+mB6FQYOhWCTt9+tLicmnxLGQ3azNCnB6DTQ9Hp2yUQuS+5XVUN9RFyMn5+hzZpL7GV5rR+ca38DyWE0Ffpccj4RQs8uxaC7bS5dUKaQ+sB0DoF4i4DL7N+dZ5UabNzrKScI4Vnv0p0eki6uEB06lbZX/sNnR6Kgv0kELkSCTnVUB8hZ/drl9H8xGZ+bTKG/g/+o07eQwghLsqJfMiYpwWenb859+ExB0CLq7TQ06o/+IfrV2c1nR6IDheVcaTwLLfOTj4/VnJxgej00WSn9xs6/QqRBKK6JyGnGuo65ORu/YOIaddRrkzsHraCtq3b1Pp7CCFErSgr1K7sbJ8PO36F4sOn7TRA40TtCk/rFIjqVC+3tepSVSBy3CI72W/IEYyKyhxXjy4mEIX6O3eoDve3EHraLbNQGXZ/SSTkVEOdhhyl2PHGVbQqWccSv2vpO/672j2+EELUFbtdWz9r+zxttNah9c77A6K1qzutB0DzvmBupE+d9aTSZudYcblT5+kjJwPR4ZO3yqquHh2vYSACCPbzdgo/VVeFqjpbn77Nx1vWIgMJOdVSVyFnzY8fYtk9n475SyhVZnbemkrHjl1q7fhCCFGvCg5qV3e2/6rNyVNRcmqfyQLxfU7d1gpuql+dLqAqEOWepd/Q0dNumV3MsHuARmbTyX5DJ0PQaUPw/xqUrD5eGNz8itu5NJiQ8+GHH/LGG2+QnZ1N586d+eCDD+jZs2e1XltXIefwS80I5zgAqa0ncu1d42rt2EIIoauKE7B3mXZba/s85/W0QBue3jpFCz1NeoBJZio5F5tdkVdSflrwORWCjjr9rF0lKq+01+j4ZpPREXhOv1V2tkDkbiPNGkTImTZtGvfeey8ff/wxSUlJvPvuu8yYMYOMjAwiIiIu+Pq6Cjmr3x2K3WDCK3EY3S8fWGvHFUIIl6IUHN52MvDMh30rQZ32RewbDC37aYGnxdXgF6JfrW5OKUVhWSVHT7tVdqRY60t0tPhU/6GjJ7cVllXW6Ph/na06tJFz3yHHtpO30fS+bdYgQk5SUhI9evTgX//6FwB2u53Y2Fj+3//7fzz77LMXfH19LtAphBAer+TYyc7L87QZl09fU8tggtikU1d5wtu4fedlV3aiwuYIPKdfDar6+chpP9e0YzVAgMXLMdxeCz9VV4wshPuf+jnM34y/pfZvm3l8yCkvL8fPz4/vvvuOIUOGOLYPHz6cvLw8fvzxxzNeU1ZWRlnZqSGSBQUFxMbGSsgRQojaZquE/X+eDDy/Qu4W5/1BcSf78aRAs8vB20efOgWVNjvHSyqcgk/VCLO/BqIjRWVU2GoWG5Y8fSVNQ2u3c7rHL+tw5MgRbDYbkZGRTtsjIyPZtm3bWV8zadIk/v73v9dHeUII0bCZvKBpsva49u9wfO/JzsvzIXOp1pdn9afaw8sX4q+AVtdqj+BmelffoHiZjI6V5S9EKUVBaSVHistO3io78/bZ6bfNistthPlf+Lh1xW1DzsWYMGEC48ad6gRcdSVHCCFEHQtuCj0f0h7lxbB7iTY8ffuvUHhQ+3nHyQWMw1pDy5OBp+ll4KXfl6RwZjAYCPTzJtDPmxbh/hdsX1puw9esX/8dtw05YWFhmEwmcnJynLbn5OQQFRV11tdYLBYsFvmfRQghdGVuBG2v0x5KQc5m2Jmq9ePJWglHtmuPlR+CdyNtLp5W12rBJ0j+YepO9Aw44MYhx2w2k5iYyIIFCxx9cux2OwsWLGDMmDH6FieEEKJ6DAaI6qA9Ln8CSvO0RUR3pGrBpygHMuZqD9CGqLfqp83JE9vLJdbXEq7LbTsegzaEfPjw4XzyySf07NmTd999l+nTp7Nt27Yz+uqcjYyuEkIIF2a3Q85GLfDsSIX9q52HqJsDTl7l6a9d6bHG6FerqFceP7qqyr/+9S/HZIBdunTh/fffJykpqVqvlZAjhBBupOSYNuPyjlRtQVGn9bWAyA7avDyt+kNsTzB561OnqHMNJuRcCgk5Qgjhpux2OJSuhZ0dv8L+NcBpX2eWQGhxpRZ4WvaDgLP31RTuSUJONUjIEUIID1F8VJuIcOfJqzwlR533R3U6OUS9PzTuLstNuDkJOdUgIUcIITyQ3aator4jVbvKc3Ct836fQGh+JbS4BlpeA4FNdClTXDwJOdUgIUcIIRqAosOwa4EWeHYucF5uAiC8rXZLq8XV0LS3zL7sBiTkVIOEHCGEaGDsNjiwVgs9O3+DA2nOI7a8fLRlJlpcowWfsFayxpYLkpBTDRJyhBCigSs5BplLtMCzc6E2+/LpAmO1W1otrtGGq/sE6lOncCIhpxok5AghhHBQCnK3nrzKswD2LgfbqUWdtZXUe57qyxPdBYxG3cptyCTkVIOEHCGEEOdUXgJ7/zh5lWcBHN3hvN8vFJpfdao/T8CFJ6EVtUNCTjVIyBFCCFFtx/eeusqTuRTKCpz3R3U8dZVHlpyoUxJyqkFCjhBCiItiq4D9f2qBZ+dv2sSEpzP7Q7M+J/vzXA0hzaUDcy2SkFMNEnKEEELUiuIjsGuRFnh2LYTiXOf9QXHara0WV0F8X/AL0adODyEhpxok5AghhKh1VQuL7lygBZ6slWCvOK2BAWK6aoGn+VUQmyS3tmpIQk41SMgRQghR58qKtJFauxdpV3sOb3Xe7+2nzc1TdaUnvK3c2roACTnVICFHCCFEvSs4CLsXa4Fn96IzV1MPiD657MTV2n/9I3Qo0rVJyKkGCTlCCCF0ZbdD7uZTgWfvcqg84dwmssOp0NP0MvD21aVUVyIhpxok5AghhHApFScga8WpW1vZG5z3mywQ1+tUf56oTg1yQkIJOdUgIUcIIYRLKzqsLTtRdaWn4IDzfr9Q7SpPVX+eBrKiuoScapCQI4QQwm0oBUd2aCO2di+CPcugvMi5TWhLbYh6877aPD0eOlRdQk41SMgRQgjhtirLtQkJq25tHVzrvKI6BojudCr0xF0GZj/dyq1NEnKqQUKOEEIIj1Gap13dyVwCu5fAkQzn/UZvbYHRqtDTOBFM3rqUeqkk5FSDhBwhhBAeq+CQtsZWVegp2O+83+wPTXtrgSe+L0QkuE0nZgk51SAhRwghRIOgFBzbrc3Pk7kEMn+H0mPObfzCIP6KU6EnJF6XUqtDQk41SMgRQgjRIFUtPbF7iRZ69i6HihLnNkFxJ29tXamFHxealFBCTjVIyBFCCCHQOjEfWHMq9Oz/E+yVzm0iEk7152naG3z0+96UkFMNEnKEEEKIsygrOjkp4WIt9GRvdN5vMGqLjDbro13liesF5kb1Vp6EnGqQkCOEEEJUQ/FR2LP01JWeY7ud9xu9oUn3k6GnDzTpCd4+dVaOhJxqkJAjhBBCXIT8/Vrn5T2/ayO48vc57zdZTg1X73YvBETW6ttLyKkGCTlCCCHEJVIKju/Rwk5V6CnKObV/7EatE3Mtqu73t1etvqsQQgghGhaDQRtuHhIPicNPLT+xZynkbK71gFMTEnKEEEIIUXsMBghvrT105h5TGwohhBBC1JCEHCGEEEJ4JAk5QgghhPBIEnKEEEII4ZEk5AghhBDCI0nIEUIIIYRHkpAjhBBCCI8kIUcIIYQQHklCjhBCCCE8koQcIYQQQngkCTlCCCGE8EgScoQQQgjhkSTkCCGEEMIjNehVyJVSABQUFOhciRBCCCGqq+p7u+p7/FwadMgpLCwEIDY2VudKhBBCCFFThYWFBAYGnnO/QV0oBnkwu93OwYMHCQgIwGAw1NpxCwoKiI2NZd++fVit1lo7rieQc3N2cl7OTc7N2cl5OTc5N2fnSedFKUVhYSExMTEYjefuedOgr+QYjUaaNGlSZ8e3Wq1u/xeprsi5OTs5L+cm5+bs5Lycm5ybs/OU83K+KzhVpOOxEEIIITyShBwhhBBCeCQJOXXAYrEwceJELBaL3qW4HDk3Zyfn5dzk3JydnJdzk3Nzdg3xvDTojsdCCCGE8FxyJUcIIYQQHklCjhBCCCE8koQcIYQQQngkCTlCCCGE8EgScurAhx9+SLNmzfDx8SEpKYnVq1frXVKdWrp0KYMHDyYmJgaDwcCsWbOc9iulePHFF4mOjsbX15d+/fqxY8cOpzbHjh1j2LBhWK1WgoKCGDFiBEVFRfX4KWrfpEmT6NGjBwEBAURERDBkyBAyMjKc2pw4cYLRo0cTGhqKv78/t9xyCzk5OU5tsrKyGDRoEH5+fkRERPD0009TWVlZnx+l1k2ePJlOnTo5JiVLTk7ml19+cexvqOflr1577TUMBgNjx451bGuo5+all17CYDA4Pdq2bevY31DPC8CBAwe4++67CQ0NxdfXl44dO7JmzRrH/ob6OxgAJWrVt99+q8xms/rPf/6jNm/erB566CEVFBSkcnJy9C6tzsydO1c999xz6ocfflCAmjlzptP+1157TQUGBqpZs2ap9evXqxtuuEHFx8er0tJSR5sBAwaozp07q5UrV6rff/9dtWzZUg0dOrSeP0ntSklJUV988YXatGmTSk9PV9ddd52Ki4tTRUVFjjYjR45UsbGxasGCBWrNmjWqV69e6rLLLnPsr6ysVB06dFD9+vVT69atU3PnzlVhYWFqwoQJenykWvPTTz+pOXPmqO3bt6uMjAz1t7/9TXl7e6tNmzYppRrueTnd6tWrVbNmzVSnTp3U448/7tjeUM/NxIkTVfv27dWhQ4ccj8OHDzv2N9TzcuzYMdW0aVN13333qVWrVqndu3er+fPnq507dzraNNTfwUopJSGnlvXs2VONHj3a8dxms6mYmBg1adIkHauqP38NOXa7XUVFRak33njDsS0vL09ZLBb1v//9Tyml1JYtWxSg/vzzT0ebX375RRkMBnXgwIF6q72u5ebmKkAtWbJEKaWdB29vbzVjxgxHm61btypArVixQimlBUij0aiys7MdbSZPnqysVqsqKyur3w9Qx4KDg9Xnn38u50UpVVhYqFq1aqVSU1NV3759HSGnIZ+biRMnqs6dO591X0M+L88884y6/PLLz7m/of8OlttVtai8vJy0tDT69evn2GY0GunXrx8rVqzQsTL9ZGZmkp2d7XROAgMDSUpKcpyTFStWEBQURPfu3R1t+vXrh9FoZNWqVfVec13Jz88HICQkBIC0tDQqKiqczk3btm2Ji4tzOjcdO3YkMjLS0SYlJYWCggI2b95cj9XXHZvNxrfffktxcTHJyclyXoDRo0czaNAgp3MA8ndmx44dxMTE0Lx5c4YNG0ZWVhbQsM/LTz/9RPfu3bntttuIiIiga9eufPbZZ479Df13sIScWnTkyBFsNpvT/0QAkZGRZGdn61SVvqo+9/nOSXZ2NhEREU77vby8CAkJ8ZjzZrfbGTt2LL1796ZDhw6A9rnNZjNBQUFObf96bs527qr2ubONGzfi7++PxWJh5MiRzJw5k4SEhAZ/Xr799lvWrl3LpEmTztjXkM9NUlISU6ZMYd68eUyePJnMzEz69OlDYWFhgz4vu3fvZvLkybRq1Yr58+czatQoHnvsMaZOnQrI7+AGvQq5EPVl9OjRbNq0iWXLluldisto06YN6enp5Ofn89133zF8+HCWLFmid1m62rdvH48//jipqan4+PjoXY5LGThwoOPnTp06kZSURNOmTZk+fTq+vr46VqYvu91O9+7defXVVwHo2rUrmzZt4uOPP2b48OE6V6c/uZJTi8LCwjCZTGf06M/JySEqKkqnqvRV9bnPd06ioqLIzc112l9ZWcmxY8c84ryNGTOG2bNns2jRIpo0aeLYHhUVRXl5OXl5eU7t/3puznbuqva5M7PZTMuWLUlMTGTSpEl07tyZ9957r0Gfl7S0NHJzc+nWrRteXl54eXmxZMkS3n//fby8vIiMjGyw5+avgoKCaN26NTt37mzQf2eio6NJSEhw2tauXTvHrbyG/jtYQk4tMpvNJCYmsmDBAsc2u93OggULSE5O1rEy/cTHxxMVFeV0TgoKCli1apXjnCQnJ5OXl0daWpqjzcKFC7Hb7SQlJdV7zbVFKcWYMWOYOXMmCxcuJD4+3ml/YmIi3t7eTucmIyODrKwsp3OzceNGp19AqampWK3WM36xuTu73U5ZWVmDPi/XXHMNGzduJD093fHo3r07w4YNc/zcUM/NXxUVFbFr1y6io6Mb9N+Z3r17nzE1xfbt22natCnQsH8HAzKEvLZ9++23ymKxqClTpqgtW7aohx9+WAUFBTn16Pc0hYWFat26dWrdunUKUG+//bZat26d2rt3r1JKG74YFBSkfvzxR7VhwwZ14403nnX4YteuXdWqVavUsmXLVKtWrdx++OKoUaNUYGCgWrx4sdOw15KSEkebkSNHqri4OLVw4UK1Zs0alZycrJKTkx37q4a99u/fX6Wnp6t58+ap8PBwtx/2+uyzz6olS5aozMxMtWHDBvXss88qg8Ggfv31V6VUwz0vZ3P66CqlGu65efLJJ9XixYtVZmam+uOPP1S/fv1UWFiYys3NVUo13POyevVq5eXlpf7xj3+oHTt2qK+//lr5+fmpr776ytGmof4OVkqGkNeJDz74QMXFxSmz2ax69uypVq5cqXdJdWrRokUKOOMxfPhwpZQ2hPGFF15QkZGRymKxqGuuuUZlZGQ4HePo0aNq6NChyt/fX1mtVnX//ferwsJCHT5N7TnbOQHUF1984WhTWlqqHn30URUcHKz8/PzUTTfdpA4dOuR0nD179qiBAwcqX19fFRYWpp588klVUVFRz5+mdj3wwAOqadOmymw2q/DwcHXNNdc4Ao5SDfe8nM1fQ05DPTd33HGHio6OVmazWTVu3FjdcccdTnPBNNTzopRSP//8s+rQoYOyWCyqbdu26tNPP3Xa31B/ByullEEppfS5hiSEEEIIUXekT44QQgghPJKEHCGEEEJ4JAk5QgghhPBIEnKEEEII4ZEk5AghhBDCI0nIEUIIIYRHkpAjhBBCCI8kIUcIIYQQHklCjhBCCCE8koQcIYQQQngkCTlCCCGE8EgScoQQQgjhkf4/vDgwmY2T6WIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ndNlll2nGjBlasmSJ3n//fX3wwQeSpLffflvbt2/Xr3/9a02bNk1XXXWVfvrTn2rRokXq7Ow0u/RBCU3LTvKY9hkJLqdG5aZIYiVgAED8Mj3MlJeXa968eSorK+v3/Pr169XV1dXv+ZKSEo0YMUKrV6+WJK1evVpTpkxRQUFB6Jy5c+eqsbFR27ZtO+1ndnR0qLGxsd8j0noH/7pN/Zy+i+cBABCPTL3TLl26VBs2bNC6detOOVZVVSWPx6PMzMx+zxcUFKiqqip0Tt8gEzwePHY6Cxcu1L/+678OsvrBCY6ZSU80r5tJksbmp0mqYvdsAEDcMq1lprKyUnfffbdeeuklJSYmmvUxA3rggQfU0NAQelRWVkb08yWpqT0wSDkt0dyWmfHBtWZq6GYCAMQn08LM+vXrVVNTowsuuEBut1tut1urVq3S008/LbfbrYKCAnV2dqq+vr7f66qrq1VYWChJKiwsPGV2U/D74DkD8Xq9Sk9P7/eItKaebqY0k1tmgmvN7KluZkYTACAumRZmLr/8cm3ZskWbNm0KPWbOnKn58+eHvk5ISNDKlStDr9m5c6cqKipUWloqSSotLdWWLVtUU1MTOmfFihVKT0/XpEmTzCo9LBoj1DIzMjdZLqdDTR3dqm7sMPWzAACIRqbdadPS0jR58uR+z6WkpCgnJyf0/K233qp7771X2dnZSk9P11133aXS0lJddNFFkqQrrrhCkyZN0te+9jU99thjqqqq0oMPPqjy8nJ5vV6zSg+L3m4mc1tmvG6XinOSte9Yi3bXNKkwI7JdegAAWM3SFYCffPJJXXPNNbruuut06aWXqrCwUH/4wx9Cx10ul5YtWyaXy6XS0lLddNNN+vrXv66f/OQnFlZ9Zpo7At1MqSa3zEjS+J6upl0MAgYAxCHz77R9vPvuu/2+T0xM1KJFi7Ro0aLTvqa4uFhvvvmmyZWFX7BlJj0CYWZcQaqWb5P2MAgYABCH2JvJJJGazSRJY3u2NWB6NgAgHhFmTBKp2UxS/92zmdEEAIg3hBmTRLJlZnReipyOwBYKx5qY0QQAiC+EGZNEajaTJCUmuFScE9ijiUHAAIB4Q5gxQXuXT50+v6TItMxIfVYCZsNJAECcIcyYINgq43BIqZ7IhJkJBcHp2YQZAEB8IcyYIDj4N9XjltPpiMhnji8MhJmdhBkAQJwhzJggkoN/g0ItM1VNzGgCAMQVwowJgmEmEqv/Bo3MTVGCy6GWTp8O17dF7HMBALAaYcYEkVxjJijB5dSYPAYBAwDiD2HGBFZ0M0nS+J6upp1VTM8GAMQPwowJGi1omZGkCYXMaAIAxB/CjAmaO6xumSHMAADiB2HGBFZ1MwVnNO051qzunkX7AACIdYQZEwQHAKdHuJtpeFaSkhJc6uz262Bda0Q/GwAAqxBmTGBVy4zT6ejd1oCuJgBAnCDMmMCqMCP1jpv5mDADAIgThBkThNaZ8Ua2m0liRhMAIP4QZkxgxQrAQRPYowkAEGcIMyZosmhqttQ7o+nA8Ra1d/ki/vkAAEQaYcYEzcGWGW/kw0xemleZyQnyG9LeY6wEDACIfYSZMPP5DbX1tIikWBBmHA5HaBAw42YAAPGAMBNmLZ3doa+taJmRerua2KMJABAPCDNh1tIzXsbldMjrtubyjmdGEwAgjhBmwiwYZlI8LjkcDktqmMAeTQCAOEKYCbPmjsB4Gau6mCSFVgE+XN8WWvMGAIBYRZgJs1DLjIVhJjPZo4J0ryRpdw3jZgAAsY0wE2bREGak3m0N2KMJABDrCDNhFpzNZGU3k9Rn3AyDgAEAMY4wE2bBMTMpXpeldTCjCQAQLwgzYRYt3UysNQMAiBeEmTALhhmru5nGFaTK4ZCON3eotrnD0loAADATYSbMmqOkZSbZ49aI7GRJ0q5qWmcAALGLMBNm0dIyI4k9mgAAcYEwE2YtwQHAHmsHAEvMaAIAxAfCTJhFSzeT1GdGE2vNAABiGGEmzKKpm6lvy4xhGBZXAwCAOQgzYRZNLTOjclPkdjrU1N6tIw3tVpcDAIApCDNhFlwBOBrCjMft1Oi8FEl0NQEAYhdhJsxaomDX7L4mFKZLkj4mzAAAYhRhJsx6u5msn80kSSWFwZWAGy2uBAAAcxBmwqjL51dnt19S9LTMBMMMLTMAgFhFmAmj4EwmKTrGzEjShJ4ws/dYs7p8fourAQAg/AgzYRTsYvK4nUpwRcelHZaZpDSvW10+Q/uOtVhdDgAAYRcdd9wYEW2DfyXJ4XCEWmc+ZtwMACAGEWbCKNoG/wZNYNwMACCGEWbCKDhmJsUTPS0zklQyJDA9eydhBgAQgwgzYRRNWxn0FZrRdJRuJgBA7CHMhFGwmyk5ysLM+J49mo40tKuhrcviagAACC/CTBj1tsxE15iZjKQEDctMkiTtqqarCQAQWwgzYdTSGZjNFG1jZqQ+g4DpagIAxBjCTBhF047ZJ2NGEwAgVhFmwihaBwBLffdoIswAAGILYSaMgovmRWPLTElh7/RswzAsrgYAgPAhzIRRW1d0LponSaPzUpTgcqipo1uH69usLgcAgLAhzIRRsGUmKSH6wkyCy6kxeamS6GoCAMQWwkwYtfXMZkqOwtlMUp/F8wgzAIAYQpgJo9au4KJ50dcyI0kTesbNEGYAALGEMBNGrT3dTMlR2M0k9Z3RxFozAIDYQZgJo9Zo72YaEggze4+1qKPbZ3E1AACEB2EmjFo7o7ubqTA9UemJbvn8hvbWtFhdDgAAYUGYCaPelpnoDDMOh6N3vZlqupoAALGBMBMmnd1+dfsDi9ElJ0RnN5PU29X08VEGAQMAYgNhJkyC07IlKSlKW2Yk9mgCAMQewkyYtPSMl0lwOeRxR+9lZY8mAECsid67rs0Ex8tE4+q/fY0vCISZqsZ21bd2WlwNAACDR5gJk2hf/TcoLTFBw7OSJNHVBACIDaaGmYULF2rWrFlKS0tTfn6+rr32Wu3cubPfOe3t7SovL1dOTo5SU1N13XXXqbq6ut85FRUVmjdvnpKTk5Wfn6/vf//76u7uNrP0s9YS5dOy+6KrCQAQS0wNM6tWrVJ5ebk++OADrVixQl1dXbriiivU0tK7xsl3v/tdvfHGG3rllVe0atUqHTlyRF/5yldCx30+n+bNm6fOzk69//77evHFF/XCCy/ooYceMrP0s9YW5dOy+yoJbWvA9GwAgP2Z2ieyfPnyft+/8MILys/P1/r163XppZeqoaFBv/zlL/Xyyy/rsssukyQtWbJEEydO1AcffKCLLrpIb7/9trZv366//OUvKigo0LRp0/TTn/5U9913n3784x/L4/GY+SOcsdAaM1E8LTuIGU0AgFgS0TEzDQ0NkqTs7GxJ0vr169XV1aWysrLQOSUlJRoxYoRWr14tSVq9erWmTJmigoKC0Dlz585VY2Ojtm3bNuDndHR0qLGxsd/DbHbtZvL3rI0DAIBdRSzM+P1+3XPPPZozZ44mT54sSaqqqpLH41FmZma/cwsKClRVVRU6p2+QCR4PHhvIwoULlZGREXoUFRWF+ac5lZ26mUblpsjjcqq106dDJ9qsLgcAgEGJWJgpLy/X1q1btXTpUtM/64EHHlBDQ0PoUVlZafpn9k7Njv5uJrfLqbH5qZIYNwMAsL+IhJkFCxZo2bJl+utf/6rhw4eHni8sLFRnZ6fq6+v7nV9dXa3CwsLQOSfPbgp+HzznZF6vV+np6f0eZgtuMplig24mqberiXEzAAC7MzXMGIahBQsW6NVXX9U777yjUaNG9Ts+Y8YMJSQkaOXKlaHndu7cqYqKCpWWlkqSSktLtWXLFtXU1ITOWbFihdLT0zVp0iQzyz8roZYZG3QzSb17NDE9GwBgd6b2iZSXl+vll1/WH//4R6WlpYXGuGRkZCgpKUkZGRm69dZbde+99yo7O1vp6em66667VFpaqosuukiSdMUVV2jSpEn62te+pscee0xVVVV68MEHVV5eLq/Xa2b5Z8VOs5kkaQLTswEAMcLUO+/ixYslSZ/73Of6Pb9kyRJ94xvfkCQ9+eSTcjqduu6669TR0aG5c+fq5z//eehcl8ulZcuW6c4771RpaalSUlJ088036yc/+YmZpZ81u3Yz7T/eovYunxKjfBsGAABOx9QwYxifPu03MTFRixYt0qJFi057TnFxsd58881wlhZ2dutmyk/zKis5QSdau7SnplmTh2VYXRIAAOeEvZnCxE5TsyXJ4XCweB4AICYQZsIktGhelG802VdoW4OjjJsBANgXYSZM7NYyI/VZCbialhkAgH0RZsKk1YZhhm4mAEAsIMyESasNu5nGFwTCzLGmDtU2d1hcDQAA54YwEyZ2bJlJ8bpVnJMsicXzAAD2RZgJA7/fUFuXvaZmB00ooKsJAGBvhJkwaO/2KbikToqNupmkvns0MaMJAGBPhJkwCHYxSVKSzVbSLRkSmJ5NNxMAwK4IM2EQnJadmOCU0+mwuJqz03d6ts//6Ss2AwAQbQgzYRBcMM9uXUySVJyTosQEp9q7/DpY22J1OQAAnDXCTBjYbV+mvlxOB4OAAQC2RpgJAzuu/tsX2xoAAOyMMBMGLR32WzCvr5IhgZaZHbTMAABsiDATBsE1ZmzfMsP0bACADRFmwsCOq//2FZzRVFnXpqb2LourAQDg7BBmwqA3zNizmykrxaPC9ERJ0i520AYA2AxhJgxaQ2Nm7NkyI0kTe8bNbD9KmAEA2AthJgxabbovU1/BlYCZ0QQAsBvCTBgEp2bbcdG8oN49mmiZAQDYC2EmDIJTs+3cMjOxzx5NfrY1AADYCGEmDFptPjVbkkblpsjjcqq5o1uH69usLgcAgDNGmAkDu68ALEkJLqfG5qdKknYwbgYAYCOEmTCw+wrAQcGVgBk3AwCwE8JMGATXmUnx2rdlRpImshIwAMCGCDNh0NoZYy0zrDUDALARwkwY2H07g6DgjKb9tS2hgAYAQLQjzISB3bczCMpN9So31SvDkHZVN1tdDgAAZ4QwEwa93Uz2bpmRerc1YCVgAIBdEGYGqbPbry5fYJE5O68AHMRKwAAAuyHMDFJwjRnJ3isAB5X0zGhirRkAgF0QZgaptSvQxZTgcsjjtv/l7LvWjGGwrQEAIPrZ/+5rsZaOnh2zE+zfKiNJY/NT5XI61NDWparGdqvLAQDgUxFmBik4+DfFa//xMpLkdbs0Ji9FEuvNAADsgTAzSLGyxkxfwXEz2xk3AwCwAcLMIMXK6r99BRfPY0YTAMAOCDODFJMtM6w1AwCwEcLMILV2xF6YCW44ue94i9q7fJ9yNgAA1iLMDFKomylGBgBLUkG6V5nJCfL5De2pYVsDAEB0I8wMUkuwmylGpmZLksPhYCVgAIBtEGYGKdamZgcFZzQxbgYAEO0IM4MUiwOApT4bTtIyAwCIcoSZQYrFAcBSn5aZKlpmAADRjTAzSK1dwTATW91M4wvS5HRIx5s7VdPEtgYAgOhFmBmk1o7gonmx1TKT5HFpZC7bGgAAoh9hZpBCY2ZibACw1LveDF1NAIBoRpgZpNA6MzE0NTsoND2blhkAQBQjzAxSb8tMDIaZnj2adjCjCQAQxQgzg9Q7NTv2upmCLTN7aprU5fNbXA0AAAMjzAxSS3DRvBgbACxJw7OSlOp1q8tnaN+xFqvLAQBgQISZQYrlAcD9tzVgEDAAIDoRZgah2+dXZ3eg+yUWBwBLUknPSsA7GAQMAIhShJlBCC6YJ8XmAGBJmhgcBMweTQCAKEWYGYTgVgYup0MeV2xeSrY1AABEu9i8A0dIaI0Zj0sOh8PiaswxoWfMTHVjh+paOi2uBgCAUxFmBiFWd8zuK9Xr1ojsZEm0zgAAohNhZhBaOoLTsmNvJlNfrAQMAIhmhJlBCO2YHaODf4OCKwHTMgMAiEaEmUEIDgBOTojtlpmJobVmaJkBAEQfwswghAYAx0nLzM6qJvn8hsXVAADQH2FmEOJhALAkjchOVlKCSx3dfu0/zrYGAIDoQpgZhFjeZLIvl9MRmqLNuBkAQLQhzAxC33VmYt3EIcxoAgBEJ8LMIMRLy4zESsAAgOhFmBmEeGqZCa41w4aTAIBoQ5gZhJaO+BgALPW2zByub1Nje5fF1QAA0Ms2YWbRokUaOXKkEhMTNXv2bK1du9bqkkLdTCne2O9mykhO0NCMREmBKdoAAEQLW4SZ3/72t7r33nv18MMPa8OGDZo6darmzp2rmpoaS+uKp24mqc9KwEcZNwMAiB62CDNPPPGEbrvtNt1yyy2aNGmSnn32WSUnJ+tXv/qVpXXF0wBgqc+4GVpmAABRJOrDTGdnp9avX6+ysrLQc06nU2VlZVq9evWAr+no6FBjY2O/hxk2VdZLir+WmR20zAAAokjUh5njx4/L5/OpoKCg3/MFBQWqqqoa8DULFy5URkZG6FFUVGRKbV534PIVpCea8v7RZlLPWjM7q5rkZ1sDAECUiPowcy4eeOABNTQ0hB6VlZWmfM6Prpmk578+U2PzU015/2gzMidFHrdTrZ0+VZ5otbocAAAkSVE/2CM3N1cul0vV1dX9nq+urlZhYeGAr/F6vfJ6vabXdtNFxaZ/RjRxu5waX5CqrYcbteNok4pzUqwuCQCA6G+Z8Xg8mjFjhlauXBl6zu/3a+XKlSotLbWwsvjESsAAgGgT9S0zknTvvffq5ptv1syZM3XhhRfqqaeeUktLi2655RarS4s7wRlN7NEEAIgWtggzN9xwg44dO6aHHnpIVVVVmjZtmpYvX37KoGCYb+IQWmYAANHFFmFGkhYsWKAFCxZYXUbcC7bMHKxrVUtHd1ysfgwgfhiGIb8h+Q1DfsOQYUhGn+/9xqnnyNApr/H3OccIPfdJ5wz82X3P0QDv6+/znHGaz+57jgZ4zcl1+P39X+8b4Liv32cFjj9wVYnSEhMs+e/GnQhnJSfVq7w0r441dWhXdZOmj8iyuiQAZ2DH0Ua9t+e4Orr9/W9WOvWGdupN8+Sb+WluggPeVAcKAJ9+zqk393Opc+DQ0Pccnfw9ztk9ZeMIM7CPksI0HWvq0I6jhBngZIZhqL3Lr26/X36/5DMM+fyBm2W33wj8q7bnX7Y+f+/Df9L3PsMIvd7vD7y273nBP0PvafR9b4Ve4zcM7TjaqGWbj1p9aWKSwyE5HQ45HZKj58/A947QsU87xzHAa5yh1wZf1//7k9/PIYeczjM7x9HzWc6T6nOo5zXOgV7f85yz/2v7HrdyNXzCDM7apCHp+vvu44ybAXq0dfr078s/1ltbj+pYU0fU/gs/N9WjsokFcoRuYAPceNVz43SefMPrc0PsOT7QjTdwQwweH/im55A+8cbbe1P9lBuvc4CbbTAg9Lm5n/acAd73lADwKecgOhBmcNZKelYCZlsDIOBf39impes+eXFOtzPwL16XwyFXz03Y7XLK6XDI5ZRcPf8iPvW8nj+dDrkcktvplNOpfseCrw2+JvgIvbfToVSvW9/67Bjlppq/BhcQaYQZnLWJoT2aAtsaOJ386wTxq6m9S7/fcEiS9MQ/T9VnxuUq2eOW29k/aAAwD2EGZ21sXqoSE5xq7ujWgdoWjc6Lj+0cgIGsO1CnLp+hkTnJ+vL0YXQ9ABaI+hWAEX3cLmeodWbL4QaLqwGste9YiyTpvGEZBBnAIoQZnJPJQzMkSVsJM4hzFXWBTVeLs5MtrgSIX4QZnJMpw4JhhkHAiG8nWrskiYG1gIUIMzgn5w0LdDNtPdIgw4jSeahABDS1B8JMaiJDEAGrEGZwTsYXpMnjdqqpvVsHa1utLgewTFN7tyQpnTADWIYwg3OS4HJqYs8+TVuPMG4G8au5J8ykeq1Zxh0AU7MxCOcNy9BHhxq05XCDrjl/qNXlAGHj8xtqaOvSidZO1bd26kRLl+rbugJft3bqRGvg6/rWLu2vDcxmSqNlBrAM//fhnPUOAqZlBtGr2+dXXWunapsDj7rWTjX0BJITPYHk5IDS2N6lsxkK5nE7NYLZTIBlCDM4Z73TsxtlGAZrbCAi/D2tJrUtHTre3Km6lk7VNge+rm3pUF1LZ+Dr5g7VtgTCyblKS3QrMzlBWckeZSZ7lNXzdUZSQuDrlMDXEwrTlJXiCeNPCeBsEGZwzsYXpirB5VBDW5cOnWhTEf8yxSB0dPt0rKlD1Y0dOtbUrpqmDtU0dqi6sefrpg4da+rQidZO+c5yJ0enQ8pO8YQemUkeZaUkhAJKZrJHmUmBcBL8PiMpQQkuhhUCdkCYwTnzul2aUJimrYcbteVwA2EGAzIMQ7UtnTpa364jDW06Wt+mqsYO1TS161gwsDS1n3ULSkZSgnJSPMpJ9Sgnxdvzp0c5qd7Qc7mpPeEl2SMX+yMBMYswg0GZPDRDWw83auvhBl09ZYjV5cACTe1dOtrQrsP1bTpa366jDW06Ut+uI/VtOtrQpqMN7ero9p/Re3lcTuWleZWf7lVBWqLy073KT/Mqv+fr3FSv8tK8ykr2yOOm1QRAAGEGgzJ5WIa0rpI9mmJYl8+vo/XtqqhrVUVdqw7Wtaiy5+uK2lY19kxN/jR5aV4NzUzS0IxEFaQnnhRYEpWf5lVmcgJjrwCcNcIMBuX84YFBwJsPNTAI2Ma6fH5V1LVq37EW7T3WrIO1LaHwcqS+/VPHqKQnugNBJTNJQzISe75O1JCMJA3LTFJBeiItKQBMQ5jBoJQUpsvjdqqhrUv7j7dodF6q1SXhE5xo6dS+483aW9OivT1/7jverIraVnV/QmDxup0qyk7WiJ5H36+HZSUp1cuvEgDW4TcQBsXjdmry0HRtqKjXpsp6wkyUaO/yaU9Nsz6uatLHRxu1s7pJO4426Xhzx2lfk5Tg0ui8FI3JS9XI3BQVZydrRE4gsOSleuVkAC2AKEWYwaBNK8oKhZmvXDDc6nLiTlN7l7YcatBHhxq09UiDPj7aqP3HW3S6hpahGYkak5+q0bkpPX+manReigrTEwksAGyJMINBmzYiU3pP2lRZb3UpMc8wDO073qL399Zq48ET+uhQvfYdbxlwtdrM5ASVFKappDA98OeQdI3LT1UKXUIAYgy/1TBo04syJUk7jjaqvcunxASXtQXFmNrmDq3adUzv7anV+3uP62hD+ynnDMtM0tSiDE0ZlqlJQwPhJT/Ny4BsAHGBMINBG56VpJwUj2pbOrXtSKNmFGdZXZLt7TvWrBXbq/WXHdVaf/BEvy4jj8upC4ozdeGoHE0rytD5wzOVm+q1rlgAsBhhBoPmcDg0rShTKz+u0abKesLMOTAMQ1sPN2rZliNasb1a+4619Ds+aUi6Lh2fpzljczSzOFtJHlq/ACCIMIOwCIaZjxg3c1b21DTp9Y+O6o2Pjmj/8d4A43Y6VDomR1+YVKDLJxZoWGaShVUCQHQjzCAspo3IlMQg4DNR29yhVzce1u83HNaOo42h571upy6fmK+rJg/RZyfkKT0xwcIqAcA+CDMIi/OHZ0qSKupaVdvcoRzGcPTj9xt6f2+tfrOuQm9vq1KXLzAIxu106NLxefqnqUNVNqmAxecA4BzwmxNhkZGUoLH5qdpT06wNFfX6wqQCq0uKCg2tXfrNugq9tOagKuvaQs+fPzxD/zyzSPOmDFFWisfCCgHA/ggzCJuZxVnaU9OsDw/WxX2Y2X+8RUve269XPjykti6fJCkt0a0vTx+mG2YV6byhGRZXCACxgzCDsJk5MltL11XqwwMnrC7FMlsONeiZd3ZrxY7q0EJ2JYVp+uZnRumL5w9lFhIAmIAwg7CZNTIwJXvzofq4Wzxvy6EG/dfKXfrLjprQc5+fkKf/75LRunhMDovXAYCJCDMImxHZycpL8+pYU4c2H2rQhaOyrS7JdHtqmvToWzv1lx3VkiSnQ/rStGEq//wYjc1Ps7g6AIgPhBmEjcPh0IUjs/WnLUe17kBdTIeZupZOPfWXXXppTYV8fiMUYhZcNlZj2DkcACKKMIOwmjkyKxRmYlGXz68X3jugp9/Zrab2bknSFyYV6L4rSzQ2nxADAFYgzCCsZo0MtMasP3hCPr8hlzN2xopsPlSv+36/JbTQ3aQh6Xrwmom6eEyuxZUBQHwjzCCsSgrTlOJxqam9W7uqmzRxSLrVJQ1aa2e3/vPtXVry3n75DSkzOUEPXFWi/zOjKKbCGgDYFWEGYeV2OXVBcZb+vvu4PjxQZ/sws+VQg+5eulH7evZN+tK0ofrRNZPYpRoAoojT6gIQe2YWB7qa1tp4vRm/39AvVu3VVxa/p33HW1SYnqglt8zSf311OkEGAKIMLTMIu9mjA2Fm9d5aGYZhuzVW6lo6dffSjfr77uOSpCvPK9TCr0xh2wEAiFKEGYTd9BGZSkxw6nhzh3bXNGt8gX3WW9l+pFG3/78PdehEm5ISXHroi5P01VlFtgtkABBP6GZC2HndrtCspvf2HLe4mjO3bPMRfWXxezp0ok0jspP1Wvkc3XjhCIIMAEQ5wgxMEZyu/N6eWosrOTPP/22fFry8Ue1dfl0yLlevL5ijCYX2aVECgHhGNxNMMWdsjiRpzb5adfv8cruiMzf7/YZ+9uYO/fIf+yVJt8wZqQfnTWLKNQDYSHTeYWB75w3NUHqiW00d3dp6pNHqcgbU7fPr3t9tCgWZH1xdooeuIcgAgN0QZmAKl9Ohi0YHWmeicdxMt8+ve367Sa9tOiK306Gnbpim2y8dw/gYALAhwgxMM2dsYNzM33cfs7iS/oJBZtnmo0pwOfTz+Rfo2unDrC4LAHCOCDMwzecm5EmSPjxwQo3tXRZXE+D3G7r3dx+Fgsyi/3uBrjiv0OqyAACDQJiBaYpzUjQ6L0XdfkN/32V9V5NhGPrJsu16/aMjBBkAiCGEGZjqsgn5kqR3Pq6xuBLp5+/u1QvvH5Ak/ec/TyPIAECMIMzAVJdNDISZd3fWyO83LKvjdx9W6vE/75QkPXTNJP3T1KGW1QIACC/CDEw1a2S20rxu1bZ06qND9ZbUsKHihH746hZJ0h2fHaNvfmaUJXUAAMxBmIGpElxOXTI+MKvprxZ0NR1v7tC3f71BXT5DV00u1H1XToh4DQAAcxFmYLrLSwokSW9trYro53b7/Lrr5Y2qamzXmLwUPX79VNaRAYAYRJiB6b5wXoE8Lqd21zRrZ1VTxD738bd3avW+WqV4XPrF12Yo1cvuHQAQiwgzMF16YoIuHR9Yc+aNj45E5DPf2nJUv1i1T5L02P+ZqrH5bBoJALGKMIOI+OLUIZKkZZuPyDDMndW0p6ZZ3//fzZKk2y8drXnnDzH18wAA1iLMICLKJhYoMcGpA7Wt2mbixpMtHd2649fr1dzRrYtGZ+tf5jLgFwBiHWEGEZHideuyksCaM6+b1NVkGIb+5febtaemWQXpXj1z4wVyu/grDgCxjt/0iJgvTQts5viHDYfU2e0P+/v/8h/79afQ5pEzlJfmDftnAACiD2EGEXNZSb7y07w63typFdurw/reH+yr1cK3PpYk/eiaSZpRnBXW9wcARC/CDCImweXUP88skiT9Zm1F2N63qqFdC17eIJ/f0JenD9PXLioO23sDAKIfYQYRdcOsIjkc0j/2HNfu6sGvOdPZ7Vf5yxt0vLlTJYVpeuTLU1gYDwDiDGEGEVWUnawrJgVWBF68au+g3+9nf9qu9QdPKC3RrWdvmqEkj2vQ7wkAsBfCDCLu258bK0n646YjqqxrPef3+e26Cr24+qAk6cl/nqaRuSlhqQ8AYC+mhJkDBw7o1ltv1ahRo5SUlKQxY8bo4YcfVmdnZ7/zNm/erEsuuUSJiYkqKirSY489dsp7vfLKKyopKVFiYqKmTJmiN99804ySEUFTizJ1ybhc+fyGnnln9zm9x/qDdXrwta2SpHu/MF5lPa09AID4Y0qY+fjjj+X3+/WLX/xC27Zt05NPPqlnn31WP/jBD0LnNDY26oorrlBxcbHWr1+vxx9/XD/+8Y/13HPPhc55//33deONN+rWW2/Vxo0bde211+raa6/V1q1bzSgbEfTdL4yXJL2y/pA+qqw/q9dW1rXqW/+vdyfsBZ8fa0KFAAC7cBhmry3f4/HHH9fixYu1b19gv5zFixfrhz/8oaqqquTxeCRJ999/v1577TV9/HFgiu0NN9yglpYWLVu2LPQ+F110kaZNm6Znn332jD+7sbFRGRkZamhoUHp6ehh/KgzGvb/bpD9sOKypwzP0+zsvPqMF7mqa2nX9s6t1sLZVJYVp+v2dFyuFDSQBICad6f07YmNmGhoalJ2dHfp+9erVuvTSS0NBRpLmzp2rnTt36sSJE6FzysrK+r3P3LlztXr16k/8rI6ODjU2NvZ7IPrcf1WJ0rxufXSoQU+/s+dTzz/W1KGv/3KtDta2akR2sl785oUEGQBAZMLMnj179Mwzz+hb3/pW6LmqqioVFPQf5xD8vqqq6hPPCR4/nYULFyojIyP0KCoqCsePgTDLT0vUv315siTp6ZW79drGw6c9d09Ns65b/L4+rmpSfppXv751tgrSEyNVKgAgip1VmLn//vvlcDg+8RHsIgo6fPiwrrzySl1//fW67bbbwlr86TzwwANqaGgIPSorKyPyuTh7X5o2TLfMGSkp0O3083f3qMvXu9VBZ7dfS97br2ue+bsq6gItMr/9VqlG5CRbVDEAINqcVRv99773PX3jG9/4xHNGjx4d+vrIkSP6/Oc/r4svvrjfwF5JKiwsVHV1/yXtg98XFhZ+4jnB46fj9Xrl9bIvj138aN4kdXT79fKaCj22fKde+qBCpWNy1OXz6/29tTrW1CFJmjM2R0/dMJ09lwAA/ZxVmMnLy1NeXt4ZnXv48GF9/vOf14wZM7RkyRI5nf0bgUpLS/XDH/5QXV1dSkhIkCStWLFCEyZMUFZWVuiclStX6p577gm9bsWKFSotLT2bshHlnE6HfnbtZE0dnqF/X75Th+vb9L/rD4WO56V59Z3Lx2n+hSPkdLK6LwCgP1NmMx0+fFif+9znVFxcrBdffFEuV++qrMFWlYaGBk2YMEFXXHGF7rvvPm3dulXf/OY39eSTT+r222+XFJia/dnPflaPPvqo5s2bp6VLl+qRRx7Rhg0bNHny5DOuh9lM9tHe5dOqXce0u7pJLqdTE4ekqXRMjrxuVvYFgHhzpvdvU8LMCy+8oFtuuWXAY30/bvPmzSovL9e6deuUm5uru+66S/fdd1+/81955RU9+OCDOnDggMaNG6fHHntMV1999VnVQ5gBAMB+LA0z0YYwAwCA/UTdOjMAAABmIMwAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbI8wAAABbc1tdQCQE99JsbGy0uBIAAHCmgvftT9sTOy7CTFNTkySpqKjI4koAAMDZampqUkZGxmmPO4xPizsxwO/368iRI0pLS5PD4Qjb+zY2NqqoqEiVlZWfuDV5POLaDIzrcnpcm4FxXU6PazOwWLouhmGoqalJQ4cOldN5+pExcdEy43Q6NXz4cNPePz093fZ/YczCtRkY1+X0uDYD47qcHtdmYLFyXT6pRSaIAcAAAMDWCDMAAMDWCDOD4PV69fDDD8vr9VpdStTh2gyM63J6XJuBcV1Oj2szsHi8LnExABgAAMQuWmYAAICtEWYAAICtEWYAAICtEWYAAICtEWYGYdGiRRo5cqQSExM1e/ZsrV271uqSTPW3v/1NX/ziFzV06FA5HA699tpr/Y4bhqGHHnpIQ4YMUVJSksrKyrR79+5+59TV1Wn+/PlKT09XZmambr31VjU3N0fwpwi/hQsXatasWUpLS1N+fr6uvfZa7dy5s9857e3tKi8vV05OjlJTU3Xdddepurq63zkVFRWaN2+ekpOTlZ+fr+9///vq7u6O5I8SdosXL9b5558fWryrtLRUb731Vuh4vF6Xkz366KNyOBy65557Qs/F67X58Y9/LIfD0e9RUlISOh6v10WSDh8+rJtuukk5OTlKSkrSlClT9OGHH4aOx+vvYEmSgXOydOlSw+PxGL/61a+Mbdu2GbfddpuRmZlpVFdXW12aad58803jhz/8ofGHP/zBkGS8+uqr/Y4/+uijRkZGhvHaa68ZH330kfFP//RPxqhRo4y2trbQOVdeeaUxdepU44MPPjD+/ve/G2PHjjVuvPHGCP8k4TV37lxjyZIlxtatW41NmzYZV199tTFixAijubk5dM4dd9xhFBUVGStXrjQ+/PBD46KLLjIuvvji0PHu7m5j8uTJRllZmbFx40bjzTffNHJzc40HHnjAih8pbF5//XXjT3/6k7Fr1y5j586dxg9+8AMjISHB2Lp1q2EY8Xtd+lq7dq0xcuRI4/zzzzfuvvvu0PPxem0efvhh47zzzjOOHj0aehw7dix0PF6vS11dnVFcXGx84xvfMNasWWPs27fP+POf/2zs2bMndE68/g42DMMgzJyjCy+80CgvLw997/P5jKFDhxoLFy60sKrIOTnM+P1+o7Cw0Hj88cdDz9XX1xter9f4zW9+YxiGYWzfvt2QZKxbty50zltvvWU4HA7j8OHDEavdbDU1NYYkY9WqVYZhBK5DQkKC8corr4TO2bFjhyHJWL16tWEYgaDodDqNqqqq0DmLFy820tPTjY6Ojsj+ACbLysoy/vu//5vrYhhGU1OTMW7cOGPFihXGZz/72VCYiedr8/DDDxtTp04d8Fg8X5f77rvP+MxnPnPa4/H+O5hupnPQ2dmp9evXq6ysLPSc0+lUWVmZVq9ebWFl1tm/f7+qqqr6XZOMjAzNnj07dE1Wr16tzMxMzZw5M3ROWVmZnE6n1qxZE/GazdLQ0CBJys7OliStX79eXV1d/a5NSUmJRowY0e/aTJkyRQUFBaFz5s6dq8bGRm3bti2C1ZvH5/Np6dKlamlpUWlpKddFUnl5uebNm9fvGkj8ndm9e7eGDh2q0aNHa/78+aqoqJAU39fl9ddf18yZM3X99dcrPz9f06dP1/PPPx86Hu+/gwkz5+D48ePy+Xz9/meRpIKCAlVVVVlUlbWCP/cnXZOqqirl5+f3O+52u5WdnR0z183v9+uee+7RnDlzNHnyZEmBn9vj8SgzM7PfuSdfm4GuXfCYnW3ZskWpqanyer2644479Oqrr2rSpElxf12WLl2qDRs2aOHChacci+drM3v2bL3wwgtavny5Fi9erP379+uSSy5RU1NTXF+Xffv2afHixRo3bpz+/Oc/684779R3vvMdvfjii5L4HRwXu2YDkVJeXq6tW7fqH//4h9WlRI0JEyZo06ZNamho0P/+7//q5ptv1qpVq6wuy1KVlZW6++67tWLFCiUmJlpdTlS56qqrQl+ff/75mj17toqLi/W73/1OSUlJFlZmLb/fr5kzZ+qRRx6RJE2fPl1bt27Vs88+q5tvvtni6qxHy8w5yM3NlcvlOmUEfXV1tQoLCy2qylrBn/uTrklhYaFqamr6He/u7lZdXV1MXLcFCxZo2bJl+utf/6rhw4eHni8sLFRnZ6fq6+v7nX/ytRno2gWP2ZnH49HYsWM1Y8YMLVy4UFOnTtV//dd/xfV1Wb9+vWpqanTBBRfI7XbL7XZr1apVevrpp+V2u1VQUBC31+ZkmZmZGj9+vPbs2RPXf2eGDBmiSZMm9Xtu4sSJoS64eP8dTJg5Bx6PRzNmzNDKlStDz/n9fq1cuVKlpaUWVmadUaNGqbCwsN81aWxs1Jo1a0LXpLS0VPX19Vq/fn3onHfeeUd+v1+zZ8+OeM3hYhiGFixYoFdffVXvvPOORo0a1e/4jBkzlJCQ0O/a7Ny5UxUVFf2uzZYtW/r9olmxYoXS09NP+QVmd36/Xx0dHXF9XS6//HJt2bJFmzZtCj1mzpyp+fPnh76O12tzsubmZu3du1dDhgyJ678zc+bMOWXJh127dqm4uFhSfP8OlsTU7HO1dOlSw+v1Gi+88IKxfft24/bbbzcyMzP7jaCPNU1NTcbGjRuNjRs3GpKMJ554wti4caNx8OBBwzAC0wIzMzONP/7xj8bmzZuNL33pSwNOC5w+fbqxZs0a4x//+Icxbtw4208LvPPOO42MjAzj3Xff7TedtLW1NXTOHXfcYYwYMcJ45513jA8//NAoLS01SktLQ8eD00mvuOIKY9OmTcby5cuNvLw8208nvf/++41Vq1YZ+/fvNzZv3mzcf//9hsPhMN5++23DMOL3ugyk72wmw4jfa/O9733PePfdd439+/cb7733nlFWVmbk5uYaNTU1hmHE73VZu3at4Xa7jZ/97GfG7t27jZdeeslITk42fv3rX4fOidffwYbB1OxBeeaZZ4wRI0YYHo/HuPDCC40PPvjA6pJM9de//tWQdMrj5ptvNgwjMDXwRz/6kVFQUGB4vV7j8ssvN3bu3NnvPWpra40bb7zRSE1NNdLT041bbrnFaGpqsuCnCZ+BrokkY8mSJaFz2trajG9/+9tGVlaWkZycbHz5y182jh492u99Dhw4YFx11VVGUlKSkZuba3zve98zurq6IvzThNc3v/lNo7i42PB4PEZeXp5x+eWXh4KMYcTvdRnIyWEmXq/NDTfcYAwZMsTweDzGsGHDjBtuuKHfWirxel0MwzDeeOMNY/LkyYbX6zVKSkqM5557rt/xeP0dbBiG4TAMw7CmTQgAAGDwGDMDAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABsjTADAABs7f8HngnUAsWgDR0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "from spatz.dataset import T1, T2, T3\n",
    "from math import pi\n",
    "\n",
    "# Rename the columns\n",
    "df = df.rename({\n",
    "    'acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket': 'ax_B',\n",
    "    'acceleration_without_gravity_y~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket': 'ay_B',\n",
    "    'acceleration_without_gravity_z~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket': 'az_B',\n",
    "    'latitude~STAHR_Rocket#PCPF~Earth@Earth': 'latitude',\n",
    "    'longitude~STAHR_Rocket#PCPF~Earth@Earth': 'longitude',\n",
    "    'declination~STAHR_Rocket#PCPF~Earth@Earth': 'declination',\n",
    "    'altitude~STAHR_Rocket@Earth': 'altitude',\n",
    "    'pitch~STAHR_Rocket#L~STAHR_Rocket:Earth': 'pitch_l',\n",
    "    'yaw~STAHR_Rocket#L~STAHR_Rocket:Earth': 'yaw_l',\n",
    "    'roll~STAHR_Rocket#L~STAHR_Rocket:Earth': 'roll_l',\n",
    "    'atmos_pressure~STAHR_Rocket': 'atmos_pressure',\n",
    "    'atmos_temperature~STAHR_Rocket': 'atmos_temperature',\n",
    "    'sonic_velocity~STAHR_Rocket': 'sonic_velocity',\n",
    "    'OMEGA_X~STAHR_Rocket': 'OMEGA_X',\n",
    "    'OMEGA_Y~STAHR_Rocket': 'OMEGA_Y',\n",
    "    'OMEGA_Z~STAHR_Rocket': 'OMEGA_Z',\n",
    "    'drag~STAHR_Rocket': 'drag',\n",
    "    'flightpath_speed~STAHR_Rocket': 'flightpath_speed',\n",
    "    'mass_total~STAHR_Rocket': 'mass_total',\n",
    "    'mach~STAHR_Rocket': 'mach'\n",
    "}, axis=1)\n",
    "\n",
    "g = 9.81\n",
    "t0 = df.at[2, 'Time']\n",
    "\n",
    "vel = np.array([0, 0, 0], dtype='float64')\n",
    "pos = np.array([318.99999999906896, 0, 0], dtype='float64')\n",
    "time = t0\n",
    "\n",
    "init_latitude = df.at[2, 'latitude']\n",
    "init_longitude = df.at[2, 'longitude']\n",
    "\n",
    "t0 = df.at[2, 'Time']\n",
    "omega_E = (2*pi) / (24*60*60)\n",
    "\n",
    "altitudes = [318.99999999906896]\n",
    "velocities = [0]\n",
    "acc_total = [0]\n",
    "\n",
    "pitch, yaw, roll = df.at[2, 'pitch_l'] * pi / 180, df.at[2, 'yaw_l'] * pi / 180, df.at[2, 'roll_l'] * pi / 180\n",
    "decl = df.at[2, 'declination']\n",
    "\n",
    "B_to_L = T1(yaw) @ T2(pi / 2 - pitch) @ T1(-roll)\n",
    "L_to_G = np.linalg.inv(T2(-decl) @ T3(init_longitude + omega_E * t0))\n",
    "G_to_LF = T2(-pi/2 - init_latitude) @ T3(init_longitude)\n",
    "L_to_LF = G_to_LF @ L_to_G\n",
    "\n",
    "x_FL, y_FL, z_FL = [8.20214666930979e-13], [-1.51393643837011e-12], [-2.40063988328838e-12]\n",
    "vx_FL, vy_FL, vz_FL = [0], [0], [0]\n",
    "\n",
    "for i in range(3, len(df)+2):\n",
    "    dt = df.at[i, 'Time'] - df.at[i-1, 'Time']\n",
    "\n",
    "    # Fetch values for the current time step.\n",
    "    acc = np.array([df.at[i, 'ax_B'], df.at[i, 'ay_B'], df.at[i, 'az_B']])\n",
    "    pitch, yaw, roll = df.at[i, 'pitch_l'] * pi / 180, df.at[i, 'yaw_l'] * pi / 180, df.at[i, 'roll_l'] * pi / 180\n",
    "    decl = df.at[i, 'declination']\n",
    "    long = df.at[i, 'longitude']\n",
    "\n",
    "    B_to_L = T1(yaw) @ T2(pi / 2 - pitch) @ T1(-roll)\n",
    "    L_to_G = np.linalg.inv(T2(-decl) @ T3(long + omega_E * t0))\n",
    "    G_to_LF = T2(-pi/2 - init_latitude) @ T3(init_longitude)\n",
    "    L_to_LF = G_to_LF @ L_to_G\n",
    "\n",
    "    acc_L = B_to_L @ acc + np.array([-g, 0, 0])\n",
    "    pos += dt * vel + 1/2*dt**2 * acc_L\n",
    "    vel += dt * acc_L\n",
    "\n",
    "    pos_LF = -(L_to_LF @ pos)\n",
    "    vel_LF = -(L_to_LF @ vel)\n",
    "\n",
    "    x_FL.append(pos_LF[0])\n",
    "    y_FL.append(pos_LF[1])\n",
    "    z_FL.append(pos_LF[2])\n",
    "\n",
    "    vx_FL.append(vel_LF[0])\n",
    "    vy_FL.append(vel_LF[1])\n",
    "    vz_FL.append(vel_LF[2])\n",
    "\n",
    "    altitudes.append(pos[0])\n",
    "    velocities.append(np.sqrt(vel[0]**2 + vel[1]**2 + vel[2]**2))\n",
    "    acc_total.append(np.sqrt(acc[0]**2 + acc[1]**2 + acc[2]**2))\n",
    "\n",
    "plt.plot(df['Time'], df['altitude'] * 1000, label='true')\n",
    "\n",
    "plt.plot(df['Time'], altitudes, label='integrated')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], velocities, label='velocity')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], np.array(velocities) / 340, label='mach')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], x_FL)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], y_FL)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], z_FL)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], vx_FL)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], vy_FL)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(df['Time'], vz_FL)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 507,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.766996294563251"
      ]
     },
     "execution_count": 507,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(np.array(acc_total) / g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 508,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2       319.000000\n",
       "3       319.000000\n",
       "4       319.000000\n",
       "5       319.000000\n",
       "6       319.000000\n",
       "           ...    \n",
       "1715      9.558576\n",
       "1716      6.360338\n",
       "1717      3.162590\n",
       "1718     -0.034668\n",
       "1719     -0.034668\n",
       "Name: altitude, Length: 1718, dtype: float64"
      ]
     },
     "execution_count": 508,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['altitude'] * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 509,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28850.044718887697"
      ]
     },
     "execution_count": 509,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(df['altitude'] * 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 510,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2         0.000000\n",
       "3         0.025000\n",
       "4         0.050000\n",
       "5         0.050000\n",
       "6         0.050000\n",
       "           ...    \n",
       "1715    637.534465\n",
       "1716    638.073041\n",
       "1717    638.611618\n",
       "1718    639.150194\n",
       "1719    639.150194\n",
       "Name: Time, Length: 1718, dtype: float64"
      ]
     },
     "execution_count": 510,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 511,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.insert(0, 'x_FL', np.array(x_FL) / 1000)\n",
    "df.insert(0, 'y_FL', np.array(y_FL) / 1000)\n",
    "df.insert(0, 'z_FL', np.array(z_FL) / 1000)\n",
    "\n",
    "df.insert(0, 'vx_FL', np.array(vx_FL) / 1000)\n",
    "df.insert(0, 'vy_FL', np.array(vy_FL) / 1000)\n",
    "df.insert(0, 'vz_FL', np.array(vz_FL) / 1000)\n",
    "\n",
    "df.insert(0, 'acc_total', np.array(acc_total))\n",
    "\n",
    "df_new = df[[\n",
    "    'Time',\n",
    "    'Phase',\n",
    "    'declination',\n",
    "    'longitude',\n",
    "    'latitude',\n",
    "    'altitude',\n",
    "    'x_FL',\n",
    "    'y_FL',\n",
    "    'z_FL',\n",
    "    'vx_FL',\n",
    "    'vy_FL',\n",
    "    'vz_FL',\n",
    "    'pitch_l',\n",
    "    'yaw_l',\n",
    "    'roll_l',\n",
    "    'atmos_pressure',\n",
    "    'atmos_temperature',\n",
    "    'sonic_velocity',\n",
    "    'mach',\n",
    "    'OMEGA_X',\n",
    "    'OMEGA_Y',\n",
    "    'OMEGA_Z',\n",
    "    'mass_total',\n",
    "    'flightpath_speed', \n",
    "    'acc_total', \n",
    "    'drag'\n",
    "]]\n",
    "\n",
    "descriptions = pd.DataFrame.from_dict({\n",
    "    'Time': ['Second'],\n",
    "    'Phase': [None],\n",
    "    'declination': ['Degree'],\n",
    "    'longitude': ['Degree'],\n",
    "    'latitude': ['Degree'],\n",
    "    'altitude': ['Kilo-Meter'],\n",
    "    'x_FL': ['Kilo-Meter'],\n",
    "    'y_FL': ['Kilo-Meter'],\n",
    "    'z_FL': ['Kilo-Meter'],\n",
    "    'vx_FL': ['Kilo-Meter / Second'],\n",
    "    'vy_FL': ['Kilo-Meter / Second'],\n",
    "    'vz_FL': ['Kilo-Meter / Second'],\n",
    "    'pitch_l': ['Degree'],\n",
    "    'yaw_l': ['Degree'],\n",
    "    'roll_l': ['Degree'],\n",
    "    'atmos_pressure': ['Pascal'],\n",
    "    'atmos_temperature': ['Kelvin'],\n",
    "    'sonic_velocity': ['Meter / Second'],\n",
    "    'mach': [None],\n",
    "    'OMEGA_X': ['Radian / Second'],\n",
    "    'OMEGA_Y': ['Radian / Second'],\n",
    "    'OMEGA_Z': ['Radian / Second'],\n",
    "    'mass_total': ['Mega-Gram'],\n",
    "    'flightpath_speed': ['Kilo-Meter / Second'], \n",
    "    'acc_total': ['Meter/Second**2'], \n",
    "    'drag': ['Kilo-Newton']\n",
    "}, dtype=str)\n",
    "\n",
    "df_new = pd.concat([descriptions, df_new], axis=0)\n",
    "df_new.to_csv('data/simulations/28km.txt', sep='\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'Time', yes\n",
    "\n",
    "'Phase', yes\n",
    "\n",
    "'declination', yes\n",
    "\n",
    "'longitude', yes\n",
    "\n",
    "'latitude', yes\n",
    "\n",
    "'altitude', yes\n",
    "\n",
    "'mach', yes\n",
    "\n",
    "'sonic_velocity', yes\n",
    "\n",
    "'x_FL', yes\n",
    "\n",
    "'y_FL', yes\n",
    "\n",
    "'z_FL', yes\n",
    "\n",
    "'vx_FL', yes\n",
    "\n",
    "'vy_FL', yes\n",
    "\n",
    "'vz_FL', yes\n",
    "\n",
    "'OMEGA_X', yes\n",
    "\n",
    "'OMEGA_Y', yes\n",
    "\n",
    "'OMEGA_Z', yes\n",
    "\n",
    "'pitch_l', yes\n",
    "\n",
    "'yaw_l', yes\n",
    "\n",
    "'roll_l', yes\n",
    "\n",
    "'flightpath_speed', yes\n",
    "\n",
    "'acc_total',\n",
    "\n",
    "'atmos_pressure', yes\n",
    "\n",
    "'atmos_temperature', yes\n",
    "\n",
    "'drag', yes\n",
    "\n",
    "'mass_total', yes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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