SPATZ/conversion.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/simulations/raw/40km.txt', sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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",
       "1718                                 2.44784090479522E+00\n",
       "1719                                 2.17155207218444E+00\n",
       "1720                                 1.89344494094220E+00\n",
       "1721                                 1.61375233123499E+00\n",
       "1722                                 1.61375233123499E+00\n",
       "Name: acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket, Length: 1723, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['acceleration_without_gravity_x~STAHR_Rocket#B~STAHR_Rocket@STAHR_Rocket']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df['Time'], df['u_x~STAHR_Rocket#L~STAHR_Rocket:Earth'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.71343179099667"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(df['mach~STAHR_Rocket'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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",
       "1718    68.176453\n",
       "1719    68.176453\n",
       "1720    68.176453\n",
       "1721    68.176453\n",
       "1722    68.176453\n",
       "Name: latitude~STAHR_Rocket#PCPF~Earth@Earth, Length: 1721, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['latitude~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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",
       "1718    68.043314\n",
       "1719    68.043314\n",
       "1720    68.043314\n",
       "1721    68.043314\n",
       "1722    68.043314\n",
       "Name: declination~STAHR_Rocket#PCPF~Earth@Earth, Length: 1721, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['declination~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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",
       "1718    21.081902\n",
       "1719    21.081902\n",
       "1720    21.081902\n",
       "1721    21.081902\n",
       "1722    21.081902\n",
       "Name: longitude~STAHR_Rocket#PCPF~Earth@Earth, Length: 1721, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['longitude~STAHR_Rocket#PCPF~Earth@Earth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1ca72ac1e50>]"
      ]
     },
     "execution_count": 11,
     "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": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "318.99999999906896"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[2, 'altitude~STAHR_Rocket@Earth'] * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uuooHHngAgFGjRvHqq68ye/ZsWrVqRWxsLAC1a9cut1LDmDFj+Mc//sH1118PeK4orVu3jvfee4/Bgwfz+eefY7PZ+OCDDwgODqZt27bs3r2be+89/h+7zz//PJdffrn3dUxMDJ06Hf39/9e//pVvv/2W77//ngcffJCYmBgcDgcRERHlaho7diyDBg3yXgVr0aIFb7zxBr1792bcuHGkpaUxdepUFi9eTPfu3QH417/+RZs2lTM/nUKRnLGwVM+/QjIaDaBtZQeS8Lq4W/TDvnEKF+dNZemOAXRvHFO5NYiIVLKOHTt6n9tsNuLj40969SQ/P58tW7Zw9913lws5paWlREVFAZ5VJDp27FhuCHuPHj1OuL9u3bqVe52Xl8dzzz3H5MmT2bt3L6WlpRQUFHivFP2elStXsmrVqnK3xIwxuN1utm3bxsaNGwkICKBr167e7a1btz5u8XhfUSiSM5K1K5VmxRtwGRuNe99mSQ0BXQfDxilc55jPP5ZuVygSkdMXGOq5YmPVsc/2o4HlJ6y12Wy43e7fbZ+XlwfABx98QM+ePcttczgcZ3z8sLDyV7gef/xxZsyYwSuvvELz5s0JCQnhhhtuoLi4+KT7ycvL4/777+fhhx8+blvDhg3ZuNHaNS4ViuSMbJ/7CZ2Blc7OdGls0QSKzftSHFyb2oUHOLT6Rwqv6URw4Jn/Ty4iNZDNdta3sKoqp9MJgMvl8r4XFxdHQkICW7duZdCgQSf8XKtWrfj0008pKiryLp21ZMmS0zrmL7/8wp133sl1110HeMLO9u3bj6vr2JoAunTpwrp162jevPkJ99u6dWtKS0tJSUnx3j5LTU09bvF4X1FHazkjtbZNAiCn2R+sK8IRQGAHzz3yy90/M31tunW1iIhYrG7duoSEhDBt2jQyMjLIzs4G4C9/+Qtjx47ljTfeYOPGjaxevZqPP/6Yf/7TszzTrbfeitvt5r777mP9+vVMnz6dV155BeCUfTVbtGjBN998w4oVK1i5cqV3X8dq3Lgx8+bNY/fu3ezf75lbbtSoUSxYsIAHH3yQFStWsGnTJv73v/95O1q3atWKK664gvvvv59FixaRkpLCPffcQ0hISIX+nf0ehSI5bdm7UmlUup1SY6fFxTdbWout400A9LMvZfrybZbWIiJipYCAAN544w3ee+89EhISuOaaawC45557+PDDD/n444/p0KEDvXv3Zvz48d4h/JGRkfzwww+sWLGCzp078+c//5nRo0cDnHJJlH/+85/UqlWLCy64gAEDBpCcnEyXLuVXNnj++efZvn07zZo183YG79ixI3PnzmXjxo306tWL8847j9GjR5OQcLTz+8cff0xCQgK9e/fm+uuv57777qNu3boV9vd1Mlr77DRp7TNY9dX/0XHdy6wI6EjnZ362thhjKP5nB5y5O3mk9BH+75lntUisiBxHa5+dmc8++4whQ4aQnZ1daVdnKoLWPpNKF7J1GgAHE/tZXAlgsxHY6UYArrL9wk/rMywuSESk+vnkk0+YP38+27Zt47vvvmPUqFHcdNNN1SoQVSSFIjkthVnpNC1YA0D98wdaXI2HrcMNAPSxr2DWis0WVyMiUv2kp6dz22230aZNGx599FFuvPHGcrNl1zQafSanZev8/9LWZthga0arlpUzidYpxbWjKLo5QVmbCdjyEzmFFxKpW2giIqftySef5Mknn7S6jCpDV4rk9KR6Rp3tib+0Ss0g7Wzv6VDY17aImbqFJiIi50ChSE7JlBTQNHcpALW6XGttMb9ha3M1AH3sK/lxxXZrixERkWpNoUhOKW35LIIpJsPUol3nJKvLKS/hPErCEwizFWG2zCa3sMTqikSkCtJAa/9WUT9fhSI5pUOrpwKwKaIHzqo2c7TNRkA7z0SSfW2Lmbtxn8UFiUhVUrakxamWn5Dq7fDhw8Dxy6GcKXW0llOK2euZk6i0yaUWV3JitjYDYNG7XGZfxl/X7ubqjhatgC0iVU5AQAChoaHs27ePwMBA7HZdC/AnxhgOHz5MZmYm0dHRZ7Wu27EUiuSkCg6k0bB0O25jo3GPq6wu58QaJlESXJtahQfITZ1LiasrgQ794hMRz3IV9erVY9u2bezYscPqcsRHoqOjiY+PP+f9KBTJSW1fNIk2wHp7C9o2SLS6nBOzO3C06Q/LP6FX6a8s2X6QC5rVsboqEakinE4nLVq00C00PxUYGHjOV4jKKBTJSbk2/gRAet0LaVeFhuL/lr31VbD8Ey51LOdfa9MVikSkHLvdrmU+5JR0j0F+n9tFw6xFAIS1qQJLe5xMk4tx2Z00sO1n87qlGmkiIiJnTKFIflfmpsVEkkeOCaVtj0usLufknGHQuBcAbXN/JTUj1+KCRESkulEokt+VvtJz62xDUEciQ6v+4oCOVlcAcKljOT+t0+zWIiJyZhSK5HcFpP0CQG698y2u5DS19Nzi62rbyK/rtlhcjIiIVDcKRXJirlIa5q0EIKp1H2trOV21GlMS04IAm5vovfM5mK+RJiIicvoUiuSEMjcvIZzDZJswWne+wOpyTltga88ttEvsy/l5k2a3FhGR06dQJCeUcaQ/UWpQe8JDgiyu5gy0SAY8C8TO3aB+RSIicvoUiuSEAnZ6+hPlxPe0uJIz1PB8SgMjqG3L5cDGhbjdGpovIiKnR6FIjucqJTH3SH+iNlVzvbPf5QjE3vwyALoUL2H17myLCxIRkepCoUiOs+9If6IcE0rrTklWl3PG7K08t9Ausa9gdmqmxdWIiEh1oVAkx0lfNROADc72RIRWw2nxm3mubrW3bSdl/WaLixERkepCoUiOY9u1GIDcut0truQsRcRTUqcNdpshOv0XDc0XEZHTolAk5RlDQs4qAMKaV5+h+L8V2LIvAL1sqzU0X0RETotCkZSTn7mVGHOIYuOgSccLrS7n7B25hXaxYxWz12tovoiInJpCkZSze9UcADbZmxFXu5a1xZyLhhfgdgQRbzvErk0rNDRfREROSaFIyincuhCAzOhOFldyjgKDofFFAHQqWsoqDc0XEZFTUCiScqL2L/M8SexhbSEVoGy+oovtq5mbqn5FIiJycgpF4uUuzKVByVYA4tv1triaCnCkX1FP+3oWpu60uBgREanqFIrEa8/aX3Bg2G3q0Lx5C6vLOXexrXGF1yPYVoJz92KyDmtovoiI/D6FIvE6lPozANtC2hPo8IP/NGw2HEduoV1oX8X8zfstLkhERKoyP/jmk4oSuGcJAAXxXS2upAI1PzI0375K/YpEROSkFIrEwxji89cDENXsfIuLqUBN+mCw0ca+kzWpGzFGQ/NFROTEFIoEgLyMrUSbHIqNg6Yd/CgUhdXG1OsMQNvDS9mQnmttPSIiUmUpFAkAu9ctAGCrvRF1oiMtrqZilQ3N7+VYxdyNuoUmIiInplAkABRs9/QnyoxoZ3ElPnBkaH4v+2rmbki3uBgREamqFIoEgJB9nkVgS+M7W1uILyT2wB0YRm1bLofTVpBXVGp1RSIiUgUpFAm43dQvSAWgVvOeFhfjA45A7E09k1FewCoWaGi+iIicgEKRkLN7A+EcpsA4adq2m9Xl+EazY4bmq1+RiIicgEKRsGf9LwBsdjQlKjzE4mp85Ego6mpPZXFqmobmi4jIcRSKhKIdKQDsj2xrcSU+VLsZ7ujGOG0uEnOWsXV/vtUViYhIFePTUDRu3Dg6duxIZGQkkZGRJCUlMXXqVO/2wsJChg8fTu3atQkPD2fgwIFkZGSU20daWhr9+/cnNDSUunXr8sQTT1BaWr6j7Jw5c+jSpQtBQUE0b96c8ePHH1fL22+/TePGjQkODqZnz54sXrzYJ+dcHYUf8HSyNgnnWVyJb9mbHzMKTbNbi4jIb/g0FDVo0IAXX3yRlJQUli5dyqWXXso111zD2rVrAXj00Uf54YcfmDhxInPnzmXPnj1cf/313s+7XC769+9PcXExCxYsYMKECYwfP57Ro0d722zbto3+/ftzySWXsGLFCkaMGME999zD9OnTvW2+/PJLRo4cyZgxY1i2bBmdOnUiOTmZzMxMX55+9eAqpX7hJgBqNU+yuBgfU78iERE5GVPJatWqZT788EOTlZVlAgMDzcSJE73b1q9fbwCzcOFCY4wxU6ZMMXa73aSnp3vbjBs3zkRGRpqioiJjjDFPPvmkadeuXblj3HzzzSY5Odn7ukePHmb48OHe1y6XyyQkJJixY8eedt3Z2dkGMNnZ2Wd2wlXcwa0pxoyJNNmj40zO4UKry/Gtgizjfq6WMWMiTZ8/TzAFxaVWVyQiIj52Jt/fldanyOVy8cUXX5Cfn09SUhIpKSmUlJTQt29fb5vWrVvTsGFDFi5cCMDChQvp0KEDcXFx3jbJycnk5OR4rzYtXLiw3D7K2pTto7i4mJSUlHJt7HY7ffv29bapydI3eG4jbgtoSkRIkMXV+FhwFDToDkBPs5JF2w5aXJCIiFQlPg9Fq1evJjw8nKCgIIYOHcq3335L27ZtSU9Px+l0Eh0dXa59XFwc6emeWYfT09PLBaKy7WXbTtYmJyeHgoIC9u/fj8vlOmGbsn2cSFFRETk5OeUe/qhw5woAsiJbW1tIJbEdWfLjYvsq9SsSEZFyfB6KWrVqxYoVK1i0aBHDhg1j8ODBrFu3zteHPWdjx44lKirK+0hMTLS6JJ8IPbQeAHd8R4srqSRH+hVdaF/Dz6l7LS5GRESqEp+HIqfTSfPmzenatStjx46lU6dOvP7668THx1NcXExWVla59hkZGcTHxwMQHx9/3Gi0stenahMZGUlISAh16tTB4XCcsE3ZPk7k6aefJjs72/vYuXPnWZ1/lWYMCQWeTtbRTbpaXEwlSTgPd3A0UbbDRBxYxc6Dh62uSEREqohKn6fI7XZTVFRE165dCQwMZObMmd5tqamppKWlkZTkGQWVlJTE6tWry40SmzFjBpGRkbRt29bb5th9lLUp24fT6aRr167l2rjdbmbOnOltcyJBQUHeqQTKHv4mf992Isin2Dho2Kqz1eVUDrsDe9M+gGdo/rxNuoUmIiIePg1FTz/9NPPmzWP79u2sXr2ap59+mjlz5jBo0CCioqK4++67GTlyJLNnzyYlJYUhQ4aQlJTE+eefD0C/fv1o27Ytt99+OytXrmT69Ok888wzDB8+nKAgT6fgoUOHsnXrVp588kk2bNjAO++8w1dffcWjjz7qrWPkyJF88MEHTJgwgfXr1zNs2DDy8/MZMmSIL0+/ytu7YREA2+wNqR0VYXE1lehIv6JeDs1XJCIiRwX4cueZmZnccccd7N27l6ioKDp27Mj06dO5/PLLAXj11Vex2+0MHDiQoqIikpOTeeedd7yfdzgcTJo0iWHDhpGUlERYWBiDBw/m+eef97Zp0qQJkydP5tFHH+X111+nQYMGfPjhhyQnJ3vb3Hzzzezbt4/Ro0eTnp5O586dmTZt2nGdr2ua/B3LAcgMbUEri2upVE0vAaCzbTOrt6RRXNoFZ4AmdxcRqelsxmgRqNORk5NDVFQU2dnZfnMrbe0/+9MuZz4zGz/KZXc+Z3U5lcq81R3b/o3cXzyCIfc8zPlNa1tdkoiI+MCZfH/rn8c1WJ28jQCEJvr38h4nYmvmuYXW276KObqFJiIiKBTVWKV5B4lzezqw12vVzeJqLFC25IdjFXNTtdyLiIgoFNVYGZuWALDLxJKYkGBxNRZofCHG4aSBbT+FGRvJyCm0uiIREbGYQlENdXDLMgB2BzXHYbdZXI0FnGHYGnpGOfayr2KeFogVEanxFIpqqvTVAOTVamNxIRY60q+ol301cxWKRERqPIWiGioiOxWAgPo1ZHmPEznSr+gC+1oWbtyLy62BmCIiNZlCUU3kdlGvZAcAdZrWvJFnXnHtMeFxhNmKaF28mmVph6yuSERELKRQVANl7d5IECUUGCeNm7e1uhzr2O3YWvQD4FL7Cn5cm25xQSIiYiWFohooY7Onk/V2R0PCgp0WV2OxllcAcJl9GTPWpqO5TEVEai6FohqoYJenk/XB0GYWV1IFNO2DcThpbM/AfmgLmzPzrK5IREQsolBUAzn2bwCgKKZGrXh2YkHh2BpfBMCl9uX8uC7D4oJERMQqCkU1UK28LQAE129vcSVVhPcW2nJmKBSJiNRYCkU1jCkpJN61C4DaTTtbW0xVcaSzdXf7Brbu3E2mZrcWEamRFIpqmINpawnATbYJpVEj9SkCIKYJ1GlFgM3NxfZV/LRea6GJiNRECkU1zL4tKwDYEdCYYGeAtcVUJS2TAbjEsZwZ6zQ0X0SkJlIoqmEKd68B4FCYrhKVc6Rf0SX2FSzcvI+8olKLCxIRkcqmUFTDBB70LO/hqtPa4kqqmMSemOBoYmx5dHBvYPYG3UITEalpFIpqmNr5npFnIRp5Vp4jANuRq0VXOJYwedVeiwsSEZHKplBUg5iiPOLdnv4ycc06W1tMVdT2DwAkO5YwOzVDt9BERGoYhaIaJHPrKgD2mSgSExtaXE0V1OxSTGAoDWz7aenawsz1mrNIRKQmUSiqQQ5uWwHAroDGBDr0oz9OYAi2FpcDcIVjMZN0C01EpEbRN2MNUrR3HQDZERp59rvaeG6hXWFfwtzUTHILSywuSEREKotCUQ0SeGgzAKZ2S4srqcJa9MM4nDSz76WReyc/6RaaiEiNoVBUg9Q6vAOAsPoajv+7giOxNbsUgCvsi5m0UrfQRERqCoWiGsKUFBDn8nzB12nS0eJqqrg2AwDP0Py5G/dxIK/I4oJERKQyKBTVEAd2bsBhM+SYUOo3aGR1OVVbq6vA5qCdfQcJJp0fVu6xuiIREakECkU1xIFtnuU9djkaEBSoNc9OKjQGmvQC4Gr7r3yzfLfFBYmISGVQKKohCvauB+BQaGNrC6kuOtwIwLWOX1i1K4tNGbkWFyQiIr6mUFRD2A9sAqA4urnFlVQTbQaAI4iW9l20tu3U1SIRkRpAoaiGiMjbCkBgnEaenZbgKGjZD4BrHL/w3fLduNzG4qJERMSXFIpqAreb+JKdAEQ3amtxMdXIkVto1wQsJD37MAu3HLC4IBER8SWFohrg8IGdhFBEiXFQv7FC0Wlr0Q+CIklgP91sG/nPkjSrKxIRER9SKKoBMo4sBLvLFk+tyDCLq6lGAkO8cxZd4/iFH9ems19zFomI+C2Fohogb9daAPYFaX6iM9bhBgCuCVyE3VXE1ym7LC5IRER8RaGoBnDt2wjA4cgmFldSDTXpDZH1iTB5XG5P4T+L03Crw7WIiF9SKKoBQrI9I8+IbWVtIdWR3QGdbwXgj4Hz2HHgMAvU4VpExC8pFNUAdQo9C8GG11cn67PSeRAASbZVJLCfzxfvsLggERHxBYUiP+c6nEVtcxCAuCYdLK6mmoppAo17Yccw0DGPH9dmsDe7wOqqRESkgikU+bn92z2drDNNNAnxcRZXU42ddzsAtwf/jMvt4pOFulokIuJvFIr83IGd6wBID6iPw26zuJpqrM0ACIqkriuDJPs6Pl+UxuHiUqurEhGRCqRQ5OcK0z1rnuWGaTj+OXGGeme4vjdkDtkFJXyzTOuhiYj4E4UiP+fI8ow8K4lqbG0h/qD73QD0di8ijoN89Ms2Dc8XEfEjCkV+LjzfszRFYGwLiyvxA3HtoNGF2I2LO4PmsHVfPnM37rO6KhERqSAKRX4utthziyeifkuLK/ET3e8B4PbAWQRSyri5WywuSEREKopCkR8rztlPJHkAxGsh2IrRZgCExxNeepD+AUtYvO0gS7YftLoqERGpAApFfixzh2c4frqJITamlsXV+AlHIHQbAsCIyDkAvDVrs4UFiYhIRVEo8mM5uzYAkBFYH5tNw/ErTNc7wR5A48Or6WTfytyN+1i9K9vqqkRE5BwpFPmxwkzPFYzc0IYWV+JnIuKh/Q0APFd7JgBvz9bVIhGR6k6hyI8FHNoGQEl0E4sr8UMXPARA57y5NLBlMm1tOhvScywuSkREzoVCkR8Lz/csReGMbW5xJX4ovj00uxSbcfN/decC8Mr0jRYXJSIi50KhyF8ZQ2zJLgAiElpZXIyfuuBhAC7On0aMLZef1meQsuOQxUWJiMjZUijyU8U5+4jgMADxjdtYXI2fatoH4jtgLy1gbOJiAF6evgFjNMu1iEh1pFDkp8qG4+81tYmNiba2GH9ls8EFjwBwec431HIU8evWg8zfvN/iwkRE5GwoFPmp7F2pgIbj+1z766F2c+yFh3il0SIAXp6eqqtFIiLVkE9D0dixY+nevTsRERHUrVuXa6+9ltTU1HJtCgsLGT58OLVr1yY8PJyBAweSkZFRrk1aWhr9+/cnNDSUunXr8sQTT1BaWlquzZw5c+jSpQtBQUE0b96c8ePHH1fP22+/TePGjQkODqZnz54sXry4ws+5qijeVzYcv5HFlfg5uwMufgKASw59RR1nCat2ZfPDqr0WFyYiImfKp6Fo7ty5DB8+nF9//ZUZM2ZQUlJCv379yM/P97Z59NFH+eGHH5g4cSJz585lz549XH/99d7tLpeL/v37U1xczIIFC5gwYQLjx49n9OjR3jbbtm2jf//+XHLJJaxYsYIRI0Zwzz33MH36dG+bL7/8kpEjRzJmzBiWLVtGp06dSE5OJjMz05d/BZYJOLQV0HD8StH+Bohpir3gIK83XQLAi1PWU1DssrgwERE5I6YSZWZmGsDMnTvXGGNMVlaWCQwMNBMnTvS2Wb9+vQHMwoULjTHGTJkyxdjtdpOenu5tM27cOBMZGWmKioqMMcY8+eSTpl27duWOdfPNN5vk5GTv6x49epjhw4d7X7tcLpOQkGDGjh17WrVnZ2cbwGRnZ5/hWVtj6/91MWZMpPn5+/FWl1IzLP/cmDGRxv33Juayv00yjUZNMq/OSLW6KhGRGu9Mvr8rtU9RdrZnKYSYmBgAUlJSKCkpoW/fvt42rVu3pmHDhixcuBCAhQsX0qFDB+Li4rxtkpOTycnJYe3atd42x+6jrE3ZPoqLi0lJSSnXxm6307dvX2+b3yoqKiInJ6fco9owhjolewCIrN/S4mJqiA43QkxTbIcP8GaLFADenbuFPVkFFhcmIiKnq9JCkdvtZsSIEVx44YW0b98egPT0dJxOJ9HR0eXaxsXFkZ6e7m1zbCAq21627WRtcnJyKCgoYP/+/bhcrhO2KdvHb40dO5aoqCjvIzEx8exO3ALFeQePDsdvpDmKKoUjAHo9DkDrLR/Rp6GTwhI3L07dYHFhIiJyuiotFA0fPpw1a9bwxRdfVNYhz8nTTz9Ndna297Fz506rSzptmWmezuz7TDSxMbUsrqYG6Xgz1GmFreAQLyfMxmaD71fuYcn2g1ZXJiIip6FSQtGDDz7IpEmTmD17Ng0aNPC+Hx8fT3FxMVlZWeXaZ2RkEB8f723z29FoZa9P1SYyMpKQkBDq1KmDw+E4YZuyffxWUFAQkZGR5R7VRfaeTQBkBsRrOH5lcgRA3+cAiF3zEfd2Cgbgz9+uprjUbWFhIiJyOnwaiowxPPjgg3z77bfMmjWLJk3Kj4Tq2rUrgYGBzJw50/teamoqaWlpJCUlAZCUlMTq1avLjRKbMWMGkZGRtG3b1tvm2H2UtSnbh9PppGvXruXauN1uZs6c6W3jT4r2eUae5QQ3OEVLqXCtroTE86G0gMec31A7zMnGjDw++Hmr1ZWJiMgp+DQUDR8+nE8//ZTPP/+ciIgI0tPTSU9Pp6DA0/k0KiqKu+++m5EjRzJ79mxSUlIYMmQISUlJnH/++QD069ePtm3bcvvtt7Ny5UqmT5/OM888w/DhwwkKCgJg6NChbN26lSeffJINGzbwzjvv8NVXX/Hoo496axk5ciQffPABEyZMYP369QwbNoz8/HyGDBniy78CaxzyLARbHFF9+kH5DZsNLn8egKDVn/P3iwMBeGPmJnYcyD/ZJ0VExGq+HAYHnPDx8ccfe9sUFBSYBx54wNSqVcuEhoaa6667zuzdu7fcfrZv326uvPJKExISYurUqWMee+wxU1JSUq7N7NmzTefOnY3T6TRNmzYtd4wyb775pmnYsKFxOp2mR48e5tdffz3tc6lOQ/LXvniJMWMizdwvX7W6lJrrP7d6huh/dpO59YOFptGoSea2D381brfb6spERGqUM/n+thmj9QhOR05ODlFRUWRnZ1f5/kV7nm9NgnsvS/t8Src+A6wup2batxHeOR+Mi/QBn3Pxt3aKS928dnNnrj2vvtXViYjUGGfy/a21z/yN20Ws29P/KrpBC4uLqcFiW0LP+wGIXzCGEX08y62M+X4tGTmFVlYmIiK/Q6HIz+Rk7iAQF0UmgHr1tcSHpfo8BWGxcGAT9wf/RIf6UWQXlPDUf1dpwVgRkSpIocjPHNi5EYB0WyxhIUEWV1PDBUfBZWMAcMx7ideurofTYWd26j4mLt1lcXEiIvJbCkV+Ji99MwAHAhMsrkQA6DwIErpAcS7NVv6Dkf08y648P2kdu7UEiIhIlaJQ5GdKDmwDID9UnXmrBLsdrnrZ83zFZ9zb5ABdGkaTV1TKk1+vxO3WbTQRkapCocjPOLI9cxS5ohpaXIl4NejmuWIEOCaN4JXr2xIcaOeXzQf41/xtFhcnIiJlFIr8TFi+p69KQO2mFlci5Vz+VwiJgcy1NN30Mc9e7ZmN/aXpG1i1K8va2kREBFAo8jsxJXsBCI9vZnElUk5YbbhirOf53L9za/NSrmwfT4nL8NB/lpNbWGJtfSIiolDkT9yFecSYLABqJ7aythg5XseboeklUFqIbdKjvHhdB+pHh7DjwGFG/2+t1dWJiNR4CkV+5ODuTQBkmzDi4+IsrkaOY7PB1a9CQAhsm0vUpq95/ZbOOOw2vl2+m69TNExfRMRKCkV+5OAeTyhKt8cR6NCPtkqKaeKZ1BFg+p/oVruEEZd5Zh5/5rvVrNuTY2FxIiI1m745/UhBxhYAsoI0HL9KSxoO8R2h4BD88AgP9GlG75axFJa4GfppCtmH1b9IRMQKCkV+xH1wOwAF4Q2sLUROzhEI170LDidsnIpj1ee8fktnGtQKIe3gYUZ8uVzzF4mIWEChyI84c9IAMNGNLK5ETimuHVzyJ8/zqU8RXZzOu7d1JSjAswzIG7M2WVufiEgNpFDkRyIKdwMQFKs5iqqFCx6GBj2gOBf+N5z29SJ44boOALw+cxOzN2RaXKCISM2iUOQvjCG2NB2AqIQWFhcjp8Xu8NxGCwyFbfNgyQfc0LUBt53fEGPg4f8sZ3NmrtVViojUGApFfqIoJ4MQinAbG3GJza0uR05X7WZw+fOe5zPGwL5URl/djh6NY8gtKuWu8Us5mF9sbY0iIjWEQpGf2L/LM/Isk1rUjoqwuBo5I93uhqZ9oLQAvr4Lpynm3du7khjj6Xg99N8pFJW6rK5SRMTvKRT5iay9mwE4EFAXm81mcTVyRux2uO49CK0DGWtgxrPEhDn5aHB3IoICWLz9IH/+dg3GaESaiIgvKRT5icJ92wHIDa5nbSFydiLiPf2LABa/Dxsm0yIugrcGdcFug69TdvHu3K3W1igi4ucUivxFlmc4fkl4osWFyFlrcTkkPeh5/r/hkL2b3i1jGTOgHQB/n7aB/63YbWGBIiL+TaHITzjzjnxZRisUVWuXjYF6nT2zXX9zL7hdDL6gMXdd2ASAxyeu5OdN+6ytUUTETykU+YmIwr0ABNVpbG0hcm4CnHDDR+AMhx2/wOwXAHimfxuu7liPEpdh6L9TWL0r2+JCRUT8j0KRPzCGOq4MAKLqaeLGaq92Mxjwuuf5z/+ADVOw223846ZOXNi8NvnFLoaMX8yOA/nW1iki4mcUivxAUd5BwikAoE79ZhZXIxWiww3Qc6jn+bdD4cAWggIcvHtbV9rWi2R/XjF3fLSYfblF1tYpIuJHFIr8wIFdR4bjm0hioqOtLUYqzuV/hcSeUJQNX90BxYeJCA5k/F3dSYwJYceBw9zx0WKyDmtyRxGRiqBQ5Aey9nombtzniNMcRf4kwAk3joewWM/8RZNGgDHUjQjmk7t6Uic8iPV7cxj80WJyC0usrlZEpNpTKPIDhfu3A5ATFG9tIVLxIhPgho/B5oBVX8KSDwFoUieMz+7pSa3QQFbuyuau8Us4XFxqcbEiItWbQpEfMIc8cxQVhde3uBLxiSa9oO9znufTnoLt8wFoFR/Bv+/uSURwAEu2H+KeCUspLNFyICIiZ0uhyA8E5u0CwEQ1tLgS8ZkLHoJ214O7FL68HQ5tB6B9/Sgm3NWDMKeDBVsOMOxTrZMmInK2FIr8QHiBZ44iZ+1GFlciPmOzwTVvH5nY8SB8fgsU5gDQpWEt/nVnd4ID7cxO3cfQf6foipGIyFlQKPIDMaWeOYoi4jVHkV9zhsIf/wPh8bBvPXxzH7g94ef8prX58I6jweieCUspKFYwEhE5EwpF1VxpQQ7R5AJQp34Li6sRn4tMgFs+B0cQbJwKs/7q3XRRizqMH9KDUKeD+Zv3M2T8YvKL1PlaROR0KRRVc/t3e4bjZ5swYuvUsbgaqRQNunpupQHMfxVW/Me76fymtfnkrh6EBwXw69aDGq4vInIGFIqquaw9nlCU6aiL3a45imqMjjdCr8c9z79/CLbO9W7q1jiGT+/pSWRwAEt3HOK2fy0m+7CCkYjIqSgUVXMF+7YBkO3UHEU1ziV/hvYDwV0CX94GGWu9mzonRvP5vecTHRrIyp1Z3Pz+QjJyCi0sVkSk6lMoquZcR+YoKgxLsLgSqXR2O1w7DhpdCEU58NmNkL3bu7l9/Si+uO986kYEsSE9l4HjFrBtvxaRFRH5PQpF1VxgjmeOInek5iiqkQKC4JbPoE4ryNkNn98Ehdneza3jI/nvsAtoXDuUXYcKuPHdBazZnX2SHYqI1FwKRdVcWOEeAAI0R1HNFVILBk2E8DjPGmlf3g6lRxeJTYwJZeLQC2iXEMn+vGJuef9XFmzZb2HBIiJVk0JRNVer5MgcRXFNLK5ELFWrEdz6FQSGwba58P2D4HZ7N8dGBPHFfeeT1LQ2eUWl3PnREiav2mthwSIiVY9CUTXmLi6gtjkEQExCc4urEcsldIabJhxdPHb602CMd3NEcCAfD+nOFe3iKXa5Gf75Mt6duwVzTBsRkZpMoagaO7h3KwD5Joi6cfUsrkaqhBaXezpfAyx6F+a+VG5zcKCDtwd14c4LGgPw4tQN/Onb1ZS43IiI1HQKRdXYwSMTN2ba6xIY4LC4GqkyOt0MVx4JQ3P+Br++W26zw27juT+0Y8yAttht8J/FO7lr/BJyNMmjiNRwCkXV2OFMz5WiQ5qjSH6r5/3Q50+e59NGwcovjmsy5MImvH97N0ICHfy8aT83jFvArkOHK7lQEZGqQ6GoGis96Jmj6HCI5iiSE+j9JPQc5nn+3QOwYcpxTfq2jWPi0CTqRgSxMSOPa99eQMqOQ5VcqIhI1aBQVI05csvmKGpgcSVSJdlskPw36HQrGBdMvBM2/3Rcs/b1o/hu+IW0jo9gf14Rf3z/V75asrPy6xURsZhCUTUWetgze7EjprG1hUjVZbfDH96ENgPAVQRfDIKtc45rlhAdwtfDLiC5XRzFLjdP/ncVY/63Rh2wRaRGUSiqxmoVpwMQFtfY2kKkanMEwMCPoOWVUFoIn98C234+rll4UADjBnXl0b4tAZiwcAe3/2sRB/OLj2srIuKPFIqqKVNaTG33AQBq1dMcRXIKAU7PHEYt+kFpgWc5kB0Ljmtmt9t4pG8L3r+9K2FOB79uPciAN+ezdo+WBhER/6dQVE1lZ+zAYTMUmUDiEhKtLkeqg4AguOnf0OxSKDnsWUA2bdEJm/ZrF8+3wy+kce1QdmcVcP07C5i4VP2MRMS/KRRVUwd2bwYg3VaHYGegxdVItREYDLd8Dk16Q3EefDoQdi45YdOWcRH8b/hF9G4ZS1Gpmye+XsWTX6+ksMRVyUWLiFQOhaJqKj9zGwCHAjVHkZyhwBD44xfQuBcU58K/rzvhrTSAqNBAPr6zO49d3hK7Db5auovr3lnAtv35lVy0iIjvKRRVUyUHdgCQrzmK5Gw4Q+HWL48Go08HnnBUGnj6GT10WQv+fXdP6oQ7Wb83hwFvzmfqai0oKyL+RaGomrLnePp3lEbWt7gSqbacYTBoIjTve6SP0U2w8cffbX5h8zpMfrgX3RvXIq+olGGfLeMvP6ylqFS300TEP/g0FM2bN48BAwaQkJCAzWbju+++K7fdGMPo0aOpV68eISEh9O3bl02bNpVrc/DgQQYNGkRkZCTR0dHcfffd5OXllWuzatUqevXqRXBwMImJibz0UvlFMAEmTpxI69atCQ4OpkOHDkyZcvzsvtVJcP6ROYpqNbK4EqnWAkM8fYxa9T8yj9GtsP6H320eFxnM5/eez/0XNwXg41+2M3DcArbuy/vdz4iIVBc+DUX5+fl06tSJt99++4TbX3rpJd544w3effddFi1aRFhYGMnJyRQWFnrbDBo0iLVr1zJjxgwmTZrEvHnzuO+++7zbc3Jy6NevH40aNSIlJYWXX36Z5557jvfff9/bZsGCBfzxj3/k7rvvZvny5Vx77bVce+21rFmzxncn72PRR+YoCo1tYnElUu0FBHmG67e7Htwl8NVgWP317zYPdNh5+qo2fHBHN6JDA1mzO4er35zPxKU7McZUYuEiIhXMVBLAfPvtt97XbrfbxMfHm5dfftn7XlZWlgkKCjL/+c9/jDHGrFu3zgBmyZIl3jZTp041NpvN7N692xhjzDvvvGNq1aplioqKvG1GjRplWrVq5X190003mf79+5erp2fPnub+++8/7fqzs7MNYLKzs0/7Mz7jKjXFY2oZMybSbNm03upqxF+4So35ZqgxYyKNGRNlTMonp/zI3qwCc/N7C0yjUZNMo1GTzIOfLzPZBcW+r1VE5DSdyfe3ZX2Ktm3bRnp6On379vW+FxUVRc+ePVm4cCEACxcuJDo6mm7dunnb9O3bF7vdzqJFi7xtLr74YpxOp7dNcnIyqampHDp0yNvm2OOUtSk7zokUFRWRk5NT7lFV5O7fRSAuSoyDuPqNrS5H/IXdAde8DV2HAAa+fxB+ef2kH4mPCuaze87nieRWOOw2fli5h6te/5llaVpUVkSqH8tCUXq65/ZPXFxcuffj4uK829LT06lbt2657QEBAcTExJRrc6J9HHuM32tTtv1Exo4dS1RUlPeRmFh1Jkgsm6Mo0xZDWEiwxdWIX7Hb4epX4YKHPK9njIYfn4GT3BZz2G0Mv6Q5E4cmkRgTwq5DBdz47kLemrUJl1u300Sk+tDos9/x9NNPk52d7X3s3Fl1ZvPNTffMUXQwIO4ULUXOgs0G/f4PLn/e83rBm/DdA+AqPenHujSsxeSHe/GHTgm43IZXftzILe8vZMcBzWkkItWDZaEoPt4z6WBGRka59zMyMrzb4uPjyczMLLe9tLSUgwcPlmtzon0ce4zfa1O2/USCgoKIjIws96gqig94QlGu5igSX7rwEc/tNJsDVn4OXw6C4sMn/UhkcCCv39KZV27sRHhQAEu2H+LK13/m80Vp6oQtIlWeZaGoSZMmxMfHM3PmTO97OTk5LFq0iKSkJACSkpLIysoiJSXF22bWrFm43W569uzpbTNv3jxKSkq8bWbMmEGrVq2oVauWt82xxylrU3ac6saWfWSOovAGFlcifu+82+DmTyEgGDZOg0+vh4KT9xey2Wzc0LUBUx/pRc8mMRwudvGnb1czZPwSMnIKT/pZEREr+TQU5eXlsWLFClasWAF4OlevWLGCtLQ0bDYbI0aM4P/+7//4/vvvWb16NXfccQcJCQlce+21ALRp04YrrriCe++9l8WLF/PLL7/w4IMPcsstt5CQ4LlKcuutt+J0Orn77rtZu3YtX375Ja+//jojR4701vHII48wbdo0/vGPf7Bhwwaee+45li5dyoMPPujL0/eZoPw9ANhqNbS4EqkRWl8Ft38LQVGQthA+vgqyd5/yY4kxofzn3vN5pn8bnAF25qTuo9+r8/hh5Z5KKFpE5Cz4chjc7NmzDXDcY/DgwcYYz7D8Z5991sTFxZmgoCBz2WWXmdTU1HL7OHDggPnjH/9owsPDTWRkpBkyZIjJzc0t12blypXmoosuMkFBQaZ+/frmxRdfPK6Wr776yrRs2dI4nU7Trl07M3ny5DM6l6o0JH/n822NGRNpFs/6xupSpCbZu9qYl1t6huy/0sqYPStP+6Mb03NM/zfmlRu6fyi/6NQfFBE5R2fy/W0zRjf6T0dOTg5RUVFkZ2db27/IGAr/EkswJWy6ZT4tWnewrhapebLS4LMbYd8GcIZ7Jn1s3vfUnwNKXG7enLWZt2dvxuU21I0I4oXrOnB5Ww0YEBHfOZPvb40+q2byD+4mmBJcxkZcYjOry5GaJroh3DX9yEKyeZ710pZ9clofDXTYGXl5S74ZdgFNY8PIzC3i3k+W8tB/lnMgr8jHhYuInJpCUTWzb6dnbbgMW20iw0ItrkZqpJBouO0b6HgLGBd8/xDM/OtJ5zI6VqfEaKY83IuhvZtht8EPK/dw+avz+H7lHo1QExFLKRRVM7l7twBwIOD3pxMQ8bkAJ1z3Llz8pOf1z6/AN/dC6eld8QkOdPDUla35bviFtI6P4GB+MQ//Zzn3fpKiEWoiYhmFomqmeP9WAPJC6ltcidR4Nhtc+mf4w1tgD4DVE+Hf18Phg6e9i44Novn+wYsY0bcFgQ4bP63PoO8/5/LlEs1rJCKVT6Gomimbo6gkouosOyI1XJfbYdBEcEbAjvnwYV/Yv+m0P+4MsDOib0smPdSLTg2iyC0sZdR/V3P7vxaTduDkk0WKiFQkhaJqJiR/FwC2mMbWFiJyrGaXwt3TIaohHNwCH14GW2ad0S5axUfw32EX8KerWhMUYGf+5v1c/upc3p69meJSt48KFxE5SqGomoku8kx8F1a3icWViPxGXDu4dxYk9oTCbPj0Blj8wRntIsBh576LmzFtxMUkNa1NUambl6en0v+Nn1my/fRvy4mInA2FourE7aKOex8A0fVbWFyMyAmEx8LgH6DTHz0j06Y8DpMfO+Visr/VpE4Yn9/bk3/e1InaYU42ZeZx47sLGfX1Kg7lF/uoeBGp6RSKqpGcfWkE4qLYOIiv39jqckROLCAIrh0HfZ8DbLDkQ/hs4CnXTPstm83G9V0aMPOx3tzS3dOH7sulO7nsn3P5b8oudcQWkQqnUFSNHNi5EYAMWyyhwUEWVyNyEjYbXPQo3PIZBIbB1jmeDtgHtpzxrqJDnbw4sCNfD02iVZxn+P5jE1dy6weL2LIvr+JrF5EaS6GoGslLPzJHUaDmKJJqonV/TwfsyAZwYDN8cAls/umsdtWtcQyTHr6IUVe0JjjQzsKtB7jytZ/5+7QN5Bed2e05EZETUSiqRkoObAcgX3MUSXUS3wHumw0Neng6YH92I8x/9bRnwD5WoMPOsD7NmPFoby5pFUuxy824OVu47B9zNSO2iJwzhaJqxJa9A4DSyIYWVyJyhsLrwp2ToMsdYNzw03Mw8U4oOrvbX4kxoXx0Z3c+uKMbiTEhpOcU8vB/lnPL+7+yfm9OhZYuIjWHQlE1EpaXBkBgbFOLKxE5CwFB8Ic34epXwR4I676Df/WDg9vOanc2m43L28Yx49HejLy8JcGBdhZtO0j/N37mue/Xkn24pGLrFxG/p1BUjcQW7wYgIqGVxZWInINud3muGoXVhcy18H4f2DzzrHcXHOjg4cta8NPI3lzVIR63gfELtnPJP+bwxeI03G7dUhOR06NQVE0U5x2iFtkAxDdpZ3E1Iueo4flw/1yo3w0Ks+CzG2D+a2fVz6hMg1qhvDOoK5/d05PmdcM5mF/MU9+s5rp3fiFlx5lNByAiNZNCUTWRuWMdAPtNFHVq17a4GpEKEJkAQ6bAebcf6Wc0Br4ectb9jMpc2LwOUx/pxTP92xAeFMDKXdkMHLeABz9fxs6DWktNRH6fQlE1kb1rAwDpgfWx2WwWVyNSQcr6GfX/B9gDYO23nnXT9m08p90GOuzc06spsx7vzU3dGmCzwaRVe7nsn3P5+7QN5Baqv5GIHE+hqJoozPCsOp4TqpFn4mdsNuh+DwyeBOHxsG+DZz6jNd+c867rRgTz0g2dmPTQRSQ1rU1xqWcI/yWvzOHzRWmUurTQrIgcpVBUTTgObQWgJEoLwYqfapQE98+Dxr2gOM9zK23qKCg997XO2iVE8fm9Pfnwjm40rRPG/rxi/vTtavq/MZ+fN+2rgOJFxB8oFFUT4fmeOYoCY7UQrPixiDi4/Tu4aKTn9aJ3YfxVkL3rnHdts9no2zaOaSMuZsyAtkSFBJKakcvt/1rMkI8Xsykj95yPISLVm0JRNRFb7PlSiKiv4fji5xwB0HcM/PELCI6CXUvgvYthy6wK2b0zwM6QC5sw94k+3H1REwLsNman7iP5tXmM+noVe7MLKuQ4IlL9KBRVA8W5B4jCMyInrkkbi6sRqSStroT75kK9TnD4APz7epjzd3BXTD+g6FAnz17dlhkje5PcLg63gS+X7qTPy3N4ceoGTf4oUgMpFFUDGdvXev40tYitFWNxNSKVKKYJ3PUjdBkMGJjzN/j8RsjfX2GHaFInjPdu78Z/h11Aj8YxFJW6eXfuFi5+eTbvz9tCYYmrwo4lIlWbQlE1cCjNM0dRhrOBhuNLzRMYDH94A64dBwHBsPknePci2PZzhR6ma6NafHn/+fxrcDdaxUWQXVDC36Zs4NJX5jBx6U5cmhlbxO8pFFUDJemeUJQT3sziSkQs1PlWuHcW1GkJuXvhkz/AnBfBXXFXcmw2G5e1iWPKI7145cZOJEQFsye7kCe+XsWVr8/jp3UZmHOYdVtEqjaFomrAecgzR5GrjjpZSw0X1w7umwOdb/PMgj1nLHxyDeTsrdDDOOw2bujagFmP9+HPV7UhKiSQjRl53PPJUm54dyELtlTc7TsRqToUiqqB2oc9q4iH1W9vcSUiVYAzDK59G657HwLDYPvP8O6FsGlGhR8qONDBvRc3Zd6TlzCsTzOCAuyk7DjErR8s4tYPftWaaiJ+xmZ0Lfi05OTkEBUVRXZ2NpGRkZV2XFfRYWx/S8BuM6TdtYqGDRtV2rFFqrz9m+HrOyF9tef1BQ/DZaPBEeiTw2XkFPLO7M18vjiNEpfnV+clrWJ5rF8r2teP8skxReTcnMn3t64UVXEZ21ZjtxkOmQjq10+0uhyRqqVOc7j7J+hxn+f1gjfgoyvg0HafHC4uMpi/XNOe2Y/34ZbuiTiOzHF09ZvzGfrvFFLTNQGkSHWmUFTFHdzu+RfwrsCGOBz6cYkcJzAYrnoZbv7UM9nj7qXw7sUVsnba72lQK5QXB3Zk5sjeXHdefWw2mLY2nSten8cjXyxn6748nx1bRHxH37JVXNFez8iz7LCmFlciUsW1GQBD50OD7lCU7Vk77dthUOS7qzeN64Tx6s2d+XHExVzVIR5j4H8r9nD5q/N4fOJKdhzI99mxRaTiKRRVcYEHNwLgqq2RZyKnFN0QhkyFi58Amx1Wfu6Z02jnEp8etkVcBO8M6sqkhy7istZ1cbkNX6fs4tJ/zGXkVyt05UikmlAoquJq528BILR+W4srEakmHIFw6TNw52SISvT0L/ooGea+VKFzGp1I+/pR/OvO7nz7wAVc0ioWl9vwzbLd9P3nXB75YjmbM9XnSKQq0+iz02TF6LPi/GycLzcEYPc9q6nfoGGlHFfEbxRkweTHYM3XntcNk+C696BW5YziXLUrizdmbuan9RkA2GzQv0M9Hrq0Ba3iIyqlBpGa7ky+vxWKTpMVoWjbspk0+f56Moih7pitWuJD5Gyt/NITjopzISgS+v8TOt5YaYdfszubt2ZtZtradO97V7aP58FLm9MuQUP5RXxJQ/L9xKEtSwHYFdRCgUjkXHS6GYbNh8SeUJQD39wD/70XCrMr5fDt60fx7u1dmTaiF/071sNmg6lr0un/xnzu/WQpq3dVTh0icnIKRVXZkQnp8mu1sbgQET9QqzHcOQX6/AlsDlj9lacT9vZfKq2E1vGRvH1rF34ccTHXdE7AboMZ6zIY8NZ87vhoMb9uPaC11UQspFBUhUVnrwcgoH4niysR8ROOAOgzCu6aBtGNICsNxveH6X+GksJKK6NFXASv33IeM0b25vrz6uOw25i3cR+3vP8r149bwI9r03G7FY5EKpv6FJ2myu5TZEqLKfm/ejgpZdMt82nRuoPPjylSoxTlwvQ/wbJPPK9jW8N170LCeZVeStqBw3zw81a+XLqT4lI3AC3qhjO0dzP+0DmBQE3cKnLW1NHaByo7FO1Zv4iEL/uRY0IJfmYXzkCHz48pUiNtnA7fPwR5GWAP8Mxx1Osxn62fdjL7cov4+Jdt/HvhDnKLSgGoHx3Cvb2acHP3hoQ49XtA5Eypo7UfyFj3MwBbna0UiER8qWUyPPArtLsO3KUwZyz863LYl1rppcRGBPHkFa355elLGXVFa+qEB7E7q4DnfljHhX+fxZszN5F9uKTS6xKpKXSl6DRV9pWiFa/fROdD05lX7y4uvv9Vnx9PRIDVX3uG7hdmgSMI+o6BnsPAbs2/HwtLXHydsov3520l7eBhAEKdDro2qkXbepE0rxtOi7gImtcNJzwowJIaRao63T7zgUq/ffZ8axLce1l8wQf06HeTz48nIkfk7IXvH4TNP3leN7oIrn2n0iZ8PJFSl5vJq/cybs4WNqSfeFbshKhgmsdF0KJuuOdxJCxFhVT+bUCRqkShyAcqMxTlH9xL2ButAUgflkp8XLxPjyciv2EMpIw/MiotH5zhkPwCdBnsmZbasrIMa/fksGJnFpsyctmUmcemzDz25Rb97mfiIoNoUTfiyFWlcFrU9QSnWmHOSqxcxDoKRT5QmaFo/ez/0GbuULbaEmk6Zo1PjyUiJ3FwG3z3AKQt8Lxu2gcGvGHpVaMTyTpczOYjAWlTRh6bMnPZlJFHes7vTzMQE+akWWwYzeuG0yw2nGZ1w2keG0796BDsdk0WK/7jTL6/dRO6CjqcOguAvVGdaWpxLSI1WkwTuHMSLHoXZv4Vts6Bd5Lg8r9At7st62v0W9GhTro1jqFb45hy7+cUlrA5M4/NZUHpSGjanVXAwfxiDuYXs2T7oXKfCQqw0zQ2vFxgal43nCZ1wgjWoA/xcwpFVVDdfZ5/ldqbXWpxJSKC3QFJw6HlFZ6h+zt+gSmPw9rv4Jo3Iabq/tMlMjiQLg1r0aVhrXLvHy4uZeu+fLbsy2NLZh6b9+WxJTOfbfvzKSp1s35vDuv35pT7jM0GDWqF0Dz2aFAqu7qkW3HiL3T77DRV1u2z7IztRI3rhMvY2P/ABuLUn0ik6nC7YcmH8NNznr5GASFw2Wjoeb8nPFVzpS43uw4VsDkzzxOY9uV5rjRl5pFTWPq7nzv2Vlzj2mHUCnUSGRJARHAgEcEBRB75MyI4EGdA1bi6JjWH+hT5QGWFohXfvUbnFWNYb29Jm9FLfHYcETkHh7Z7rhptm+d5ndgTrnkb6rSwtCxfMcawP6/YG5I8gSmfLZmeW3FnIjjQTkRwIJFHQlJkSFlwOhqeyt6LCDpm+5E/w50B6vMkZ0R9iqoxZ+r3AOxrcBlaBlakiqrVGO743jNC7cdnYeciz+Kyl/wJkh70i6tGx7LZbMRGBBEbEcT5TWuX2/bbW3FpBw+TU1hKTkEJuYWl5BR6/sw7MkN3YYmbwpKik46YO3ktEB50TID6TZA69qpU2dUqbwA70i4owI7NwlGEUnXpStFpqowrRXmH0gl+rQ0BNjebbp5HizZaCFakysvaCT88Altmel7X7wp/eAvi2lpbVxXjchvyjoSksqBUFpxyC0vIKfuzoJTcovLbc45sL1sX7lwFOmzHh6egwBPe8js2bB39TAABWo+u2tCVompq45R36GJzs8HenFatO1pdjoicjuhEuO2/sOJzmPY07E6B9y6Gi0ZAr8chMNjqCqsEh91GVGggUaFnP5lkYYnruBD12/DkDVEFx7fLLSzBbaDEZTiQX8yB/OKzriXU6ThBeDo+UEUeCVGe944GrzCnQ1erqiCFoiqiuCCPxM2fArC/zWBa638WkerDZoPzBkGzSz0j0zZMgnkvw9pvYcDr0Pgiqyv0C8GBDoIDHcRGBJ3V540x5Be7fnOF6miw8gSo0t9cySofuA4XuwA4XOzicLGLjJyzuw1ot+ENUb+9xVf2Xvgxz8v6XR37GQWrilfjbp+9/fbbvPzyy6Snp9OpUyfefPNNevToccrP+fL2WUlxIas+GErXfd+STh0inlhFWFhYhR5DRCrRuu9hyhOQl+553eUOuPx5CKl18s9JlVficpN3THg69qrU8YHKcyvwt1etSlwV87VrP9K/KuKY23onfv6bsBV0zPYg/++4rtFnv+PLL7/kjjvu4N1336Vnz5689tprTJw4kdTUVOrWrXvSz/oqFC2fPoF2C0bitHk6IS46/x16XjGowvYvIhYpzPYM3V/6ked1WF248u/Q7jpLlwoRaxljKCp1e69MHRui8oqOvdV3dNux75U9L3VX3Ff30ZBUPkh5RgD+zvvH3CYMD6rafawUin5Hz5496d69O2+99RYAbrebxMREHnroIZ566qmTftZXoWjjsjm0/P4aDhHBug5PcuHAhyts3yJSBexYCD88DPs3el63vAKuesXTF0nkLBhjKCxxezuk5/6m35QnUJV/zxO4jratyI7r4OljFR7029t9J75qdTRsld/uqzmsFIpOoLi4mNDQUL7++muuvfZa7/uDBw8mKyuL//3vf+XaFxUVUVR09F5xTk4OiYmJFR6KiooKOLBnB/ENW2B3+NcwXhE5orQI5r8K814Bd4lngdlLn4Ue9/rd8H2pPopKXb8bqo57v+jEYauwpOKCVVCAnd4tY3n/jm4Vtk/Q6LMT2r9/Py6Xi7i4uHLvx8XFsWHDhuPajx07lr/85S8+rysoKISEJq19fhwRsVBAEPR5ynPr7PuHYeevMG0UrP7Ks8BsfHurK5QaKCjAQVC4gzrhZ9dxHY7vY3XCgFV04luAZc/zj3ReLyp147b4Ok2NCUVn6umnn2bkyJHe12VXikREzlpsKxgyFVI+9vQ3Khu+f/4wT2gKirC6QpEzEuiwUyvMeU7r3x07h5XVnb6rbs+oClanTh0cDgcZGRnl3s/IyCA+/vj1xYKCgoiMjCz3EBE5Z3Y7dL8bhi+CNgPAuGDhW/BWD1j3P6gZPRpEvMrmsEqMCaV+dIiltdSYUOR0OunatSszZ870vud2u5k5cyZJSUkWViYiNVJkAtz8Kdw6EaIbQe4e+OoO+OxGOLjN6upEaqQaE4oARo4cyQcffMCECRNYv349w4YNIz8/nyFDhlhdmojUVC37ea4aXfwE2ANh8wx453yY+5Kng7aIVJoaM/qszFtvveWdvLFz58688cYb9OzZ85Sfq4y1z0Skhtu/CSaPhG3zPK9rN4f+/4CmfSwtS6Q605B8H1AoEpFKYQys+S9M/xPkHekD2f4GSH4BIo7v/ygiJ3cm39816vaZiEiVZ7NBhxvgwSXQ4z6w2WHN1/BWd1j0HrhdVlco4rcUikREqqLgKLjqZbh3FiScB0U5MPVJGHeh50qS+huJVDjdPjtNun0mIpZxuzxzG8183rOmGnhCU9troeNN0PACz1B/ETmO+hT5gEKRiFiuIAt+HQfLPvEM4S8T2cBzy63jTRDXzrLyRKoihSIfUCgSkSrD7YYd82HVV54JH4tyjm6r29YTkNoPhFqNLStRpKpQKPIBhSIRqZJKCmDjNFj9NWz6EVzFR7c16AEdbvSsuRYea12NIhZSKPIBhSIRqfIKDsH6HzwBads84Mivd5vDM9dRhxuhdX8I1u8wqTkUinxAoUhEqpWcvbD2W1g9EfYsO/p+QDC0TPYEpOaXQ2CwdTWKVAKFIh9QKBKRauvAFs/Vo9UT4cCmo+8HRUHbAZ6A1LgX2B3W1SjiIwpFPqBQJCLVnjGQvsoTjlb/t/wItvA4T+fs9jdA/S6eSSRF/IBCkQ8oFImIX3G7IW2BJyCt/Q4Ks45uq9XEc/Wow40Q29KqCkUqhEKRDygUiYjfKi2GLTM9AWnDFCgtOLotvqMnHLW/HqIaWFejyFlSKPIBhSIRqRGK8iB1qicgbZkJ7tKj2xpd6AlHba7REH+pNhSKfEChSERqnPwDsO47TyfttAVH37fZPR2z210Hbf4AYbUtK1HkVBSKfEChSERqtKydsPYbzzD/PcuPvm9zQNPe0O56zxxIoTHW1ShyAgpFPqBQJCJyxMFtnitIa77xjGYrYw+Appd4brG1ugpCoq2qUMRLocgHFIpERE7gwBbP1aO130LGmqPvO5zQ7DLPLbZWV2oWbbGMQpEPKBSJiJzCvo1HryDtW3/0fYfTs8xImwGeK0hhdayqUGoghSIfUCgSETkDmes98x+t/Qb2bzz6vs3uGcXWZgC0vhqi6ltWotQMCkU+oFAkInKW9qXC+u89i9XuXVl+W/1unoDUZgDUbmZNfeLXFIp8QKFIRKQCHNoBGyZ5AlLar8AxX0F12x0NSHHttNSIVAiFIh9QKBIRqWC5GZA62ROQts0rP1FkrSZHAtIfoH5XsNutq1OqNYUiH1AoEhHxoYJDkDrNE5C2zITSwqPbIhKgzdWekNTwAnAEWFenVDsKRT6gUCQiUkmK8mDzT56AtHE6FOce3RYSA62v8lxBatoHAoIsK1OqB4UiH1AoEhGxQGkRbJ3r6ai9YTIUHDy6zRkBLft5riA1vxyCwq2rU6oshSIfUCgSEbGYqxTSFnquIK3/AXL3HN3mCILml3kCUssrtNyIeCkU+YBCkYhIFeJ2w55lnitI676HQ9uObrMHeBasLZsLKSLOujrFcgpFPqBQJCJSRRkDmeuOXkE6drkRbJDYw7NYbeurNRdSDaRQ5AMKRSIi1cSBLUfnQtq1pPy22NZHAlJ/SOiiuZBqAIUiH1AoEhGphnL2QOoUTyft386FFJFwNCA1vggcgdbVKT6jUOQDCkUiItVcQRZsmuG5irT5JyjOO7otOApaJHsCUvO+GsnmRxSKfEChSETEj5QUeq4cbZjkuZKUv+/oNkcQNLvEE5BaXgnhsdbVKedMocgHFIpERPyU2+Xpe7RhEqyfVH4kGzZoeP7R22wxTS0rU86OQpEPKBSJiNQAxsC+DUcD0t4V5bfXbesZxda6P9TrpI7a1YBCkQ8oFImI1EDZu2DDFE9I2j4fjOvotsgGR68gNbpAHbWrKIUiH1AoEhGp4Q4fhE0/HumoPRNKDh/dFhwNra70BKRml4IzzLIypTyFIh9QKBIREa+SAtg650hH7alw+MDRbQHBnmDUur9nRJs6altKocgHFIpEROSE3C5I+9UzF9KGHyAr7ZiNNkjs6bmK1OoqqNNC/ZAqmUKRDygUiYjIKRkDGWuPDvXfu7L89phmRwNSYk9wBFhTZw2iUOQDCkUiInLGsnfBxmmeztrb5oG75Oi2kBhomewJSc0uhaAI6+r0YwpFPqBQJCIi56QwB7bM8vRB2jQdCg4d3eZwQpOLPQGp5ZUQVd+6Ov2MQpEPKBSJiEiFcZXCzkVH12UrN2EkUK+z5xZbqyshvoP6IZ0DhSIfUCgSERGfMAb2b/QEpNSpsHMxcMxXc2SDI8P9r4JGF0GA07JSqyOFIh9QKBIRkUqRt89ze23DFM/tttKCo9ucEdCir+cqUovLIaSWdXVWEwpFPqBQJCIila6kALbO9VxF2jgN8jKObrM5PDNpl91mi2liXZ1VmEKRDygUiYiIpdxu2LP8yG22KZC5rvz22DZHhvtfCfW7gt1hTZ1VjEKRDygUiYhIlXJwm+fqUeoU2P5L+XXZQutAi36eIf/NLoXgmvu9pVDkAwpFIiJSZRUc8qzHtmGy58+i7KPb7IGe22wtr/CEpNrNrKvTAgpFPqBQJCIi1YKrxLPsyMZpsHE6HNhUfnvtFtDqCk9ISuwJjkBr6qwkCkU+oFAkIiLV0oEtnnC0cRrs+AXcpUe3BUdB876egNS8L4TGWFenjygU+YBCkYiIVHuF2Z5h/hunw6Yf4fCBo9tsdkg833OLreUVENvKLyaNVCjyAYUiERHxK24X7E45epstY0357dGNjvZDanwRBARZU+c5UijyAYUiERHxa1k7PZNGpk7zLF7rKjq6LTAMml3iGe7foh+E17WuzjOkUOQDCkUiIlJjFOd7Jo0su4qUl15+e/2uR68ixXes0rfZzuT72+6rIl544QUuuOACQkNDiY6OPmGbtLQ0+vfvT2hoKHXr1uWJJ56gtLS0XJs5c+bQpUsXgoKCaN68OePHjz9uP2+//TaNGzcmODiYnj17snjx4nLbCwsLGT58OLVr1yY8PJyBAweSkZFx3H5EREQEcIZ51lr7wxvw2Aa4by70+RMkdPFs350Cs1+A9y6Gf7aF7x+G9ZOgKM/aus+Rz0JRcXExN954I8OGDTvhdpfLRf/+/SkuLmbBggVMmDCB8ePHM3r0aG+bbdu20b9/fy655BJWrFjBiBEjuOeee5g+fbq3zZdffsnIkSMZM2YMy5Yto1OnTiQnJ5OZmelt8+ijj/LDDz8wceJE5s6dy549e7j++ut9deoiIiL+w2aDhM7QZxTcNxseS4U/vAmtr/bcVsvdA8smwJeD4KUm8Mk1sPAd2L/Z6srPmM9vn40fP54RI0aQlZVV7v2pU6dy9dVXs2fPHuLi4gB49913GTVqFPv27cPpdDJq1CgmT57MmjVHO3/dcsstZGVlMW3aNAB69uxJ9+7deeuttwBwu90kJiby0EMP8dRTT5GdnU1sbCyff/45N9xwAwAbNmygTZs2LFy4kPPPP/+0zkO3z0RERH6jpBB2zIdNMzy32Q5tK789pqmnD1KLy6HRRRAYXOklVonbZ6eycOFCOnTo4A1EAMnJyeTk5LB27Vpvm759+5b7XHJyMgsXLgQ8V6NSUlLKtbHb7fTt29fbJiUlhZKSknJtWrduTcOGDb1tTqSoqIicnJxyDxERETlGYLBnfqMr/w4PL4cHUyD5b9C0j2cm7YNbYdG78OlAz1Wkz2+BpR95OnVXQQFWHTg9Pb1cIAK8r9PT00/aJicnh4KCAg4dOoTL5Tphmw0bNnj34XQ6j+vXFBcX5z3OiYwdO5a//OUvZ3VuIiIiNY7NBnWaex5Jw6Eo19NZe9OPnitJuXtg41TPA6BuO88VpBb9jsysbVkk8TqjK0VPPfUUNpvtpI+yMFLdPf3002RnZ3sfO3dWzVQrIiJSJQVFQJurPZ21R66DofPh0mc9E0Ta7JC5Fn55DcZfBS81hYl3wqqvLC35jGLZY489xp133nnSNk2bNj2tfcXHxx83SqxsRFh8fLz3z9+OEsvIyCAyMpKQkBAcDgcOh+OEbY7dR3FxMVlZWeWuFh3b5kSCgoIICqqeE1WJiIhUKTYbxHfwPC5+HA4fPDqz9uafoOAgrP0W8jKh402WlXlGoSg2NpbY2NgKOXBSUhIvvPACmZmZ1K3rmQRqxowZREZG0rZtW2+bKVOmlPvcjBkzSEpKAsDpdNK1a1dmzpzJtddeC3g6Ws+cOZMHH3wQgK5duxIYGMjMmTMZOHAgAKmpqaSlpXn3IyIiIpUoNAY63OB5uF2we5ln4sjazS0ty2c38NLS0jh48CBpaWm4XC5WrFgBQPPmzQkPD6dfv360bduW22+/nZdeeon09HSeeeYZhg8f7r1CM3ToUN566y2efPJJ7rrrLmbNmsVXX33F5MmTvccZOXIkgwcPplu3bvTo0YPXXnuN/Px8hgwZAkBUVBR33303I0eOJCYmhsjISB566CGSkpJOe+SZiIiI+IjdAYndPQ+rGR8ZPHiwAY57zJ4929tm+/bt5sorrzQhISGmTp065rHHHjMlJSXl9jN79mzTuXNn43Q6TdOmTc3HH3983LHefPNN07BhQ+N0Ok2PHj3Mr7/+Wm57QUGBeeCBB0ytWrVMaGioue6668zevXvP6Hyys7MNYLKzs8/ocyIiImKdM/n+1jIfp0nzFImIiFQ/1WKeIhEREZGqRKFIREREBIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREQACrC6guihbIi4nJ8fiSkREROR0lX1vn85SrwpFpyk3NxeAxMREiysRERGRM5Wbm0tUVNRJ29jM6UQnwe12s2fPHiIiIrDZbBW675ycHBITE9m5c+cpV/D1BzXpfGvSuYLO19/pfP2XP5+rMYbc3FwSEhKw20/ea0hXik6T3W6nQYMGPj1GZGSk3/3HeDI16Xxr0rmCztff6Xz9l7+e66muEJVRR2sRERERFIpEREREAIWiKiEoKIgxY8YQFBRkdSmVoiadb006V9D5+judr/+qSed6MupoLSIiIoKuFImIiIgACkUiIiIigEKRiIiICKBQJCIiIgIoFFnu7bffpnHjxgQHB9OzZ08WL15sdUlnZd68eQwYMICEhARsNhvfffddue3GGEaPHk29evUICQmhb9++bNq0qVybgwcPMmjQICIjI4mOjubuu+8mLy+vEs/i9IwdO5bu3bsTERFB3bp1ufbaa0lNTS3XprCwkOHDh1O7dm3Cw8MZOHAgGRkZ5dqkpaXRv39/QkNDqVu3Lk888QSlpaWVeSqnZdy4cXTs2NE7qVtSUhJTp071bvencz2RF198EZvNxogRI7zv+dM5P/fcc9hstnKP1q1be7f707kC7N69m9tuu43atWsTEhJChw4dWLp0qXe7P/2uaty48XE/W5vNxvDhwwH/+9lWCCOW+eKLL4zT6TQfffSRWbt2rbn33ntNdHS0ycjIsLq0MzZlyhTz5z//2XzzzTcGMN9++2257S+++KKJiooy3333nVm5cqX5wx/+YJo0aWIKCgq8ba644grTqVMn8+uvv5qff/7ZNG/e3Pzxj3+s5DM5teTkZPPxxx+bNWvWmBUrVpirrrrKNGzY0OTl5XnbDB061CQmJpqZM2eapUuXmvPPP99ccMEF3u2lpaWmffv2pm/fvmb58uVmypQppk6dOubpp5+24pRO6vvvvzeTJ082GzduNKmpqeZPf/qTCQwMNGvWrDHG+Ne5/tbixYtN48aNTceOHc0jjzzifd+fznnMmDGmXbt2Zu/evd7Hvn37vNv96VwPHjxoGjVqZO68806zaNEis3XrVjN9+nSzefNmbxt/+l2VmZlZ7uc6Y8YMA5jZs2cbY/zrZ1tRFIos1KNHDzN8+HDva5fLZRISEszYsWMtrOrc/TYUud1uEx8fb15++WXve1lZWSYoKMj85z//McYYs27dOgOYJUuWeNtMnTrV2Gw2s3v37kqr/WxkZmYawMydO9cY4zm3wMBAM3HiRG+b9evXG8AsXLjQGOMJkXa73aSnp3vbjBs3zkRGRpqioqLKPYGzUKtWLfPhhx/69bnm5uaaFi1amBkzZpjevXt7Q5G/nfOYMWNMp06dTrjN38511KhR5qKLLvrd7f7+u+qRRx4xzZo1M2632+9+thVFt88sUlxcTEpKCn379vW+Z7fb6du3LwsXLrSwsoq3bds20tPTy51rVFQUPXv29J7rwoULiY6Oplu3bt42ffv2xW63s2jRokqv+UxkZ2cDEBMTA0BKSgolJSXlzrd169Y0bNiw3Pl26NCBuLg4b5vk5GRycnJYu3ZtJVZ/ZlwuF1988QX5+fkkJSX59bkOHz6c/v37lzs38M+f76ZNm0hISKBp06YMGjSItLQ0wP/O9fvvv6dbt27ceOON1K1bl/POO48PPvjAu92ff1cVFxfz6aefctddd2Gz2fzuZ1tRFIossn//flwuV7n/2ADi4uJIT0+3qCrfKDufk51reno6devWLbc9ICCAmJiYKv334Xa7GTFiBBdeeCHt27cHPOfidDqJjo4u1/a353uiv4+ybVXN6tWrCQ8PJygoiKFDh/Ltt9/Stm1bvzxXgC+++IJly5YxduzY47b52zn37NmT8ePHM23aNMaNG8e2bdvo1asXubm5fneuW7duZdy4cbRo0YLp06czbNgwHn74YSZMmAD49++q7777jqysLO68807A//47rigBVhcgUp0NHz6cNWvWMH/+fKtL8alWrVqxYsUKsrOz+frrrxk8eDBz5861uiyf2LlzJ4888ggzZswgODjY6nJ87sorr/Q+79ixIz179qRRo0Z89dVXhISEWFhZxXO73XTr1o2//e1vAJx33nmsWbOGd999l8GDB1tcnW/961//4sorryQhIcHqUqo0XSmySJ06dXA4HMf19M/IyCA+Pt6iqnyj7HxOdq7x8fFkZmaW215aWsrBgwer7N/Hgw8+yKRJk5g9ezYNGjTwvh8fH09xcTFZWVnl2v/2fE/091G2rapxOp00b96crl27MnbsWDp16sTrr7/ul+eakpJCZmYmXbp0ISAggICAAObOncsbb7xBQEAAcXFxfnfOx4qOjqZly5Zs3rzZ736+9erVo23btuXea9Omjfd2ob/+rtqxYwc//fQT99xzj/c9f/vZVhSFIos4nU66du3KzJkzve+53W5mzpxJUlKShZVVvCZNmhAfH1/uXHNycli0aJH3XJOSksjKyiIlJcXbZtasWbjdbnr27FnpNZ+MMYYHH3yQb7/9llmzZtGkSZNy27t27UpgYGC5801NTSUtLa3c+a5evbrcL9cZM2YQGRl53C/tqsjtdlNUVOSX53rZZZexevVqVqxY4X1069aNQYMGeZ/72zkfKy8vjy1btlCvXj2/+/leeOGFx02fsXHjRho1agT43++qMh9//DF169alf//+3vf87WdbYazu6V2TffHFFyYoKMiMHz/erFu3ztx3330mOjq6XE//6iI3N9csX77cLF++3ADmn//8p1m+fLnZsWOHMcYzzDU6Otr873//M6tWrTLXXHPNCYe5nnfeeWbRokVm/vz5pkWLFlVymOuwYcNMVFSUmTNnTrnhrocPH/a2GTp0qGnYsKGZNWuWWbp0qUlKSjJJSUne7WVDXfv162dWrFhhpk2bZmJjY6vkUNennnrKzJ0712zbts2sWrXKPPXUU8Zms5kff/zRGONf5/p7jh19Zox/nfNjjz1m5syZY7Zt22Z++eUX07dvX1OnTh2TmZlpjPGvc128eLEJCAgwL7zwgtm0aZP57LPPTGhoqPn000+9bfzpd5UxnlHNDRs2NKNGjTpumz/9bCuKQpHF3nzzTdOwYUPjdDpNjx49zK+//mp1SWdl9uzZBjjuMXjwYGOMZ6jrs88+a+Li4kxQUJC57LLLTGpqarl9HDhwwPzxj3804eHhJjIy0gwZMsTk5uZacDYnd6LzBMzHH3/sbVNQUGAeeOABU6tWLRMaGmquu+46s3fv3nL72b59u7nyyitNSEiIqVOnjnnsscdMSUlJJZ/Nqd11112mUaNGxul0mtjYWHPZZZd5A5Ex/nWuv+e3ocifzvnmm2829erVM06n09SvX9/cfPPN5ebt8adzNcaYH374wbRv394EBQWZ1q1bm/fff7/cdn/6XWWMMdOnTzfAcedgjP/9bCuCzRhjLLlEJSIiIlKFqE+RiIiICApFIiIiIoBCkYiIiAigUCQiIiICKBSJiIiIAApFIiIiIoBCkYiIiAigUCQiIiICKBSJiIiIAApFIiIiIoBCkYiIiAigUCQiIiICwP8DRnA0diBcp5gAAAAASUVORK5CYII=",
      "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "z_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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QtHTpUgwePBhqtRpqtRppaWlYv3699XpzczOysrIQEhICPz8/TJw4ERUVFTavUVZWhszMTPj4+CA8PBwvv/wy2tpsj3LYunUrhg0bBpVKhYSEBCxbtuyqWpYsWYL4+Hh4eXkhNTUVu3fvtkufnc3+cvN8oiExgZDLZRJXc+ss84p2nKiC0cR5RURE1HF2DUXR0dF48803kZ+fj7179+Kee+7Bww8/jMOHDwMAZs+ejW+//RarVq3Ctm3bcO7cOTz66KPW7zcajcjMzITBYMCOHTuwfPlyLFu2DPPmzbO2KS0tRWZmJsaMGYOCggLMmjULzz33HDZu3Ght88UXXyA7Oxvz58/Hvn37kJycjIyMDOh0PEDUOp/IySdZWwzqEQB/LwX0zW0oPFsrdTlERORMRDcLCgoSH330kaipqRGenp5i1apV1mtFRUUCgMjLyxNCCLFu3Tohl8uFVqu1tlm6dKlQq9WipaVFCCHEK6+8IgYMGGDzHpMmTRIZGRnWr0eOHCmysrKsXxuNRhEVFSUWLFjQ4bpra2sFAFFbW9u5Dju4u97aLOLmrBFbS3RSl9Jlnv+/PSJuzhqxePMxqUshIiKJdebzu9vmFBmNRqxYsQINDQ1IS0tDfn4+WltbkZ6ebm2TmJiI2NhY5OXlAQDy8vIwaNAgaDQaa5uMjAzo9Xrr3aa8vDyb17C0sbyGwWBAfn6+TRu5XI709HRrm2tpaWmBXq+3ebiaC/Ut1lVaznYI7I1Y5hX9yHlFRETUCXYPRYWFhfDz84NKpcK0adPw1VdfISkpCVqtFkqlEoGBgTbtNRoNtFotAECr1doEIst1y7UbtdHr9WhqakJVVRWMRuM121he41oWLFiAgIAA6yMmJuam+u/ICsprAAAJ4X4I8PaUtpgudFt7KMovu4jmVqPE1RARkbOweyjq168fCgoKsGvXLkyfPh2TJ0/GkSNH7P22t2zu3Lmora21PsrLy6UuqctZQpEr3SUCgF6hvtCoVTC0mbD31EWpyyEiIidh91CkVCqRkJCAlJQULFiwAMnJyVi0aBEiIiJgMBhQU1Nj076iogIREREAgIiIiKtWo1m+/qk2arUa3t7eCA0NhYeHxzXbWF7jWlQqlXXVnOXhag6eMU9ETo4OkLiSriWTyTC696VVaERERB3R7fsUmUwmtLS0ICUlBZ6ensjNzbVeKykpQVlZGdLS0gAAaWlpKCwstFkllpOTA7VajaSkJGuby1/D0sbyGkqlEikpKTZtTCYTcnNzrW3ckRACh9pXZw3s4VqhCLg0hLadh8MSEVEH2fX0z7lz52L8+PGIjY1FXV0dPvvsM2zduhUbN25EQEAApk6diuzsbAQHB0OtVuPFF19EWloaRo0aBQAYN24ckpKS8NRTT+Gtt96CVqvFa6+9hqysLKhUKgDAtGnTsHjxYrzyyit49tlnsXnzZqxcuRJr16611pGdnY3Jkydj+PDhGDlyJBYuXIiGhgZMmTLFnt13aFp9My40GOAhl1lPl3clt/U2Hw5beKYG+uZWqL1cZ84UERHZh11DkU6nw9NPP43z588jICAAgwcPxsaNG3HvvfcCAN59913I5XJMnDgRLS0tyMjIwPvvv2/9fg8PD6xZswbTp09HWloafH19MXnyZPzxj3+0tunZsyfWrl2L2bNnY9GiRYiOjsZHH32EjIwMa5tJkyahsrIS8+bNg1arxZAhQ7Bhw4arJl+7k8L2obM+4X7w8vSQuJquFxXojZ6hviitasCuk9W4N8l9f9dERNQxMiF4nHhH6PV6BAQEoLa21iXmF/31uxK8t/k4fp4Sjbd/nix1OXbx+68K8emuMjxzWzxef2iA1OUQEZEEOvP5zbPP3JRlt+dBLjbJ+nK3tU+2zuO8IiIi6gCGIjckhEDhWfNmlK44ydoirX1eUUlFHSrrWiSuhoiIHB1DkRuq0Legqr4FHnIZklxwkrVFsK/S2j8uzSciop/CUOSGLENnrjrJ+nKWVWgcQiMiop/CUOSGLKFoQJTrDp1ZjLbuV8Q7RUREdGMMRW7IsmnjoB6uO3RmMaJnMBRyGcqrm1Be3Sh1OURE5MAYityQO6w8s/BTKZDcfrYb5xUREdGNMBS5mcq6FlTWtUAmg0vuZH0to9vnFW0/znlFRER0fQxFbqbovHkpfs8QX/go7bqhucOwnIO248QFcK9SIiK6HoYiN2MJRe5ylwgAhsYGwstTjqr6FhzT1UtdDhEROSiGIjdTrK0DACRG+EtcSfdRKTwwIj4YALD9OOcVERHRtTEUuRl3vFMEXDryg/OKiIjoehiK3IihzYTj7cNHiZHuc6cIuLSJ466TF9BmNElcDREROSKGIjdyXFePNpOA2kuBHoHeUpfTrQb2CIDaS4G6ljYcOqeXuhwiInJADEVuxDJ0lhiphkwmk7ia7uUhl2FUL8vSfM4rIiKiqzEUuZFibft8IjeaZH05noNGREQ3wlDkRorOm1eeudskawvLOWh7TlWjudUocTVERORoGIrchBDCZvjMHSWE+yHMX4WWNhP2lV2UuhwiInIwDEVuorK+BRcaDJDJgH4a9xw+k8lkHEIjIqLrYihyE5ahs54hvvBWekhcjXRGW/cr4mRrIiKyxVDkJorddNPGK92WYL5TdOBMLeqaWyWuhoiIHAlDkZsoqTDfKerrpkNnFtFBPogN9oHRJLDnVLXU5RARkQNhKHITlp2s+2r8JK5EeqMTLPsVcV4RERFdwlDkBkwmgWMV5lDUx83vFAGXn4PGeUVERHQJQ5EbOFvThKZWIzw9ZIgP8ZG6HMmlta9AK9bW4UJ9i8TVEBGRo2AocgPHdOb5RL1C/aDw4K881E+FxPZdvfNOcgiNiIjM+AnpBo5ah844n8jCMoS2g/sVERFRO4YiN3CUK8+uYtnEcQfnFRERUTuGIjdgWXnWJ5x3iixSewXDQy7DqQuNOFvTJHU5RETkABiKXBxXnl2bv5cnBkcHAODdIiIiMmMocnFceXZ91iE0zisiIiIwFLk8rjy7vsvPQRNCSFwNERFJjZ+SLo4rz65vWFwQVAo5dHUt1p8TERG5L4YiF8eVZ9fn5elhHULbXKyTuBoiIpIaQ5GL48qzG7snMRwAsIWhiIjI7TEUuTCTSVwKRbxTdE139zOHovyyi6htbJW4GiIikhJDkQs7r29Go8EIhVyGOK48u6aYYB/0CfeD0STw/bFKqcshIiIJMRS5sJOV5rtEsSE+8OTKs+viEBoREQEMRS7tZGUDAKB3GOcT3YhlCG3r0UqYTFyaT0TkrhiKXJjlTlGvMF+JK3Fsw+OD4K9SoLrBgANnaqQuh4iIJMJQ5MJOWO4UhfJO0Y14eshxR1/zRo4cQiMicl8MRS6Md4o6bkz7ENqWEk62JiJyVwxFLqrR0IZztc0AgF6cU/STLPOKCs/WQqdvlrgaIiKSAkORiyqtMg+dBfp4IthXKXE1ji/MX4XkmEAAQE5RhbTFEBGRJBiKXJRl5VmvUA6dddR9AyIAABsOaSWuhIiIpMBQ5KK4HL/zMgZoAAB5Jy5wd2siIjfEUOSiTlZZJlkzFHVUrzA/9NX4oc0kkFvMITQiIndj11C0YMECjBgxAv7+/ggPD8eECRNQUlJi06a5uRlZWVkICQmBn58fJk6ciIoK2w+ksrIyZGZmwsfHB+Hh4Xj55ZfR1tZm02br1q0YNmwYVCoVEhISsGzZsqvqWbJkCeLj4+Hl5YXU1FTs3r27y/vsKKzDZ1x51imWIbSNhzmERkTkbuwairZt24asrCzs3LkTOTk5aG1txbhx49DQ0GBtM3v2bHz77bdYtWoVtm3bhnPnzuHRRx+1XjcajcjMzITBYMCOHTuwfPlyLFu2DPPmzbO2KS0tRWZmJsaMGYOCggLMmjULzz33HDZu3Ght88UXXyA7Oxvz58/Hvn37kJycjIyMDOh0rrcvjRDCuhy/N0NRp2QMNIeibUcr0Who+4nWRETkUkQ30ul0AoDYtm2bEEKImpoa4enpKVatWmVtU1RUJACIvLw8IYQQ69atE3K5XGi1WmubpUuXCrVaLVpaWoQQQrzyyitiwIABNu81adIkkZGRYf165MiRIisry/q10WgUUVFRYsGCBR2qvba2VgAQtbW1nex19ztf0yTi5qwRveauFS2tRqnLcSomk0mMfjNXxM1ZI9YXnpO6HCIiukWd+fzu1jlFtbW1AIDg4GAAQH5+PlpbW5Genm5tk5iYiNjYWOTl5QEA8vLyMGjQIGg0GmubjIwM6PV6HD582Nrm8tewtLG8hsFgQH5+vk0buVyO9PR0axtXYrlLFBPkDaWC08Y6QyaTWYfQ1nMVGhGRW+m2T0yTyYRZs2Zh9OjRGDhwIABAq9VCqVQiMDDQpq1Go4FWq7W2uTwQWa5brt2ojV6vR1NTE6qqqmA0Gq/ZxvIaV2ppaYFer7d5OIsTVZb5RJxkfTPGDzKHok1HKtBkMEpcDRERdZduC0VZWVk4dOgQVqxY0V1veUsWLFiAgIAA6yMmJkbqkjqslHsU3ZJhsUGIDvJGg8HIVWhERG6kW0LRjBkzsGbNGmzZsgXR0dHW5yMiImAwGFBTU2PTvqKiAhEREdY2V65Gs3z9U23UajW8vb0RGhoKDw+Pa7axvMaV5s6di9raWuujvLy88x2XyOkL5lAUz1B0U2QyGR5KjgIAfFNwTuJqiIiou9g1FAkhMGPGDHz11VfYvHkzevbsaXM9JSUFnp6eyM3NtT5XUlKCsrIypKWlAQDS0tJQWFhos0osJycHarUaSUlJ1jaXv4aljeU1lEolUlJSbNqYTCbk5uZa21xJpVJBrVbbPJzF6epGAEBciI/ElTivh4f0AABsLankRo5ERG7CrqEoKysLn3zyCT777DP4+/tDq9VCq9WiqakJABAQEICpU6ciOzsbW7ZsQX5+PqZMmYK0tDSMGjUKADBu3DgkJSXhqaeewoEDB7Bx40a89tpryMrKgkqlAgBMmzYNJ0+exCuvvILi4mK8//77WLlyJWbPnm2tJTs7Gx9++CGWL1+OoqIiTJ8+HQ0NDZgyZYo9fwTdzmgSKLtgDkXxIbxTdLP6RfgjMcIfBqMJGw6fl7ocIiLqDvZcBgfgmo+PP/7Y2qapqUn8+te/FkFBQcLHx0c88sgj4vz58zavc+rUKTF+/Hjh7e0tQkNDxUsvvSRaW1tt2mzZskUMGTJEKJVK0atXL5v3sPjb3/4mYmNjhVKpFCNHjhQ7d+7scF+cZUn+mYuNIm7OGpHwu7WitY3L8W/Fki3HRNycNeLxf+RJXQoREd2kznx+y4QQQrpI5jz0ej0CAgJQW1vr0ENpO45X4YmPdqFnqC+2/PZuqctxauXVjbjjrS2QyYCdc8dCo/aSuiQiIuqkznx+cxMbF8P5RF0nJtgHKXFBEAJYvf+s1OUQEZGdMRS5mFOWlWecT9Qlfp5iXi35xd5y8KYqEZFrYyhyMaereKeoKz2QHAUfpQdOVjZg7+mLUpdDRER2xFDkYjh81rX8VApkDooEAHyxx3n2qiIios5jKHIhQgjrxo1xHD7rMo+NNO9mvvbgedQ1c88iIiJXxVDkQirrW9BoMEIuA6KDvKUux2UMiw1C7zBfNLUaseYg9ywiInJVDEUu5HT7po1Rgd5QKTwkrsZ1yGQyTBphvlu0YneZxNUQEZG9MBS5EEso4nyirvfosGgoPeQ4cKYWB8prpC6HiIjsgKHIhXA+kf2E+qnwwGDzhOvlO05JWwwREdkFQ5ELOWU984x3iuxh8m3xAIBvD56Drq5Z2mKIiKjLMRS5EMudothg3imyh+SYQAyNDUSrUeDzXVyeT0TkahiKXIhlTlF8KO8U2csz7XeLPtl1GoY2k7TFEBFRl2IochE1jQbUNpn30IkNZiiyl/EDIxHur0JlXQvWFXJ5PhGRK2EochGW+UQatQo+SoXE1bgupUKOp0bFAQD+/v1JnodGRORCGIpchHXlGecT2d1TaXHwUXqg6LweW49WSl0OERF1EYYiF8E9irpPoI8ST4yMBQAs3XJC4mqIiKirMBS5iFPtd4riQ3mnqDs8d0cveHrIsPtUNfaeqpa6HCIi6gIMRS6Cd4q6V0SAFyYOiwYALN3Ku0VERK6AochFcE5R93vhrt6Qy4DcYh0Ona2VuhwiIrpFDEUuoKGlDVX1BgBALO8UdZueob54KDkKAPDXnKMSV0NERLeKocgFnLnYBABQeykQ4O0pcTXuZWZ6X3jIZdhcrEP+6YtSl0NERLeAocgFlFWb5xPxLlH36xnqi5+1zy36a06JxNUQEdGtYChyAeXtoSgmiKFICi+OTYCnhwzbj1/AjhNVUpdDREQ3iaHIBVjvFPF4D0lEB/ng8fZ9i/6yoQQmE3e5JiJyRgxFLuDMxfY7RQxFkplxTwJ8lB44UF6Dbw+ek7ocIiK6CQxFLsByp4ihSDrh/l749d29AQB/WV+M5lajxBUREVFnMRQ5OSEEyqvNq884fCat5+7ohR6B3jhX24yPfjgpdTlERNRJDEVOrqregKZWI2QyICrQS+py3JqXpwdeua8fAOD9rSegq2uWuCIiIuoMhiInZxk6i1R7QaXwkLgaeig5CkNiAtFoMOJ/N3KJPhGRM2EocnKcZO1YZDIZ/vBAEgBg5d4zyD/Nw2KJiJwFQ5GTK7vAUORoUuKCMGl4DADg918dQqvRJHFFRETUEQxFTo57FDmmV8cnIsjHE8XaOny8vVTqcoiIqAMYipxcuXX4zFviSuhyQb5KzL2/PwDg3ZxjOFvTJHFFRET0UxiKnByX4zuunw2Lxsj4YDS1GjH/60MQgjtdExE5MoYiJ2ZoM+F8rTkU8dwzxyOXy/DGIwPh6SHDpiIdvjnAna6JiBwZQ5ETO1fTBJMAVAo5wvxVUpdD19BX448ZY/oAAOZ9fRg6PfcuIiJyVAxFTswynyg22AcymUziauh6fj2mNwZEqVHb1IrffcVhNCIiR8VQ5MR45plz8PSQ451fJLcPo1VgdcFZqUsiIqJrYChyYlyO7zwSI9T4zT3mYbTXvznCYTQiIgfEUOTEzrSvPIsO4nJ8ZzDt7t4Y2MM8jPbbLw/CZOIwGhGRI2EocmK8U+RcPD3kePcXQ6BSyPH90Ur8i5s6EhE5FIYiJ2adaB3CUOQs+mj8rWej/WVDMQ6drZW4IiIismAoclK1Ta2oaWwFwD2KnM2TqbEYl6RBq1HgN5/vR0NLm9QlERERGIqcVnn70FmIrxK+KoXE1VBnyGQyvPWzwYgM8MLJqgb8z7eHpS6JiIjAUOS0zrQPnUVzPpFTCvRR4t1JQyCTASv3nsF/8s9IXRIRkdtjKHJSnGTt/Eb1CsGssX0BAL/7qhBHzuklroiIyL0xFDkpy0GwMVyO79RevCcBd/cLQ0ubCdM/zUdtU6vUJRERuS2GIifFO0WuQS6X4d1fDEGPQG+cvtCIl1Ye4P5FREQSsWso+v777/Hggw8iKioKMpkMq1evtrkuhMC8efMQGRkJb29vpKen49ixYzZtqqur8eSTT0KtViMwMBBTp05FfX29TZuDBw/ijjvugJeXF2JiYvDWW29dVcuqVauQmJgILy8vDBo0COvWrevy/nany889I+cW5KvEB79MgVIhx6aiCizddkLqkoiI3JJdQ1FDQwOSk5OxZMmSa15/66238N577+GDDz7Arl274Ovri4yMDDQ3XzoC4cknn8Thw4eRk5ODNWvW4Pvvv8fzzz9vva7X6zFu3DjExcUhPz8fb7/9Nl5//XX84x//sLbZsWMHHn/8cUydOhX79+/HhAkTMGHCBBw6dMh+nbcjk0lYd7PmuWeuYVB0AP740AAAwDvflWDb0UqJKyIickOimwAQX331lfVrk8kkIiIixNtvv219rqamRqhUKvH5558LIYQ4cuSIACD27NljbbN+/Xohk8nE2bNnhRBCvP/++yIoKEi0tLRY28yZM0f069fP+vUvfvELkZmZaVNPamqqeOGFFzpcf21trQAgamtrO/w99nKuplHEzVkjes1dK1rbjFKXQ13EZDKJV1YdEHFz1oiB8zeIYxV1UpdEROT0OvP5LdmcotLSUmi1WqSnp1ufCwgIQGpqKvLy8gAAeXl5CAwMxPDhw61t0tPTIZfLsWvXLmubO++8E0ql0tomIyMDJSUluHjxorXN5e9jaWN5H2djmWQdFegFhQenhbkKmUyGP04YgOFxQahrbsNzy/egptEgdVlERG5Dsk9UrVYLANBoNDbPazQa6zWtVovw8HCb6wqFAsHBwTZtrvUal7/H9dpYrl9LS0sL9Hq9zcNRcJK161IpPPDBUynoEeiNUxcakfXZPrQaTVKXRUTkFnib4ToWLFiAgIAA6yMmJkbqkqzKGYpcWqifCh9NHg4fpQe2H7+AN9YckbokIiK3IFkoioiIAABUVFTYPF9RUWG9FhERAZ1OZ3O9ra0N1dXVNm2u9RqXv8f12liuX8vcuXNRW1trfZSXl3e2i3ZjCUXRPPPMZfWPVGNh+47Xy/NOY/mOU1KXRETk8iQLRT179kRERARyc3Otz+n1euzatQtpaWkAgLS0NNTU1CA/P9/aZvPmzTCZTEhNTbW2+f7779HaemnTu5ycHPTr1w9BQUHWNpe/j6WN5X2uRaVSQa1W2zwcBYfP3MO4ARF4OaMfAOD1bw9jw6HrD/cSEdGts2soqq+vR0FBAQoKCgCYJ1cXFBSgrKwMMpkMs2bNwhtvvIFvvvkGhYWFePrppxEVFYUJEyYAAPr374/77rsPv/rVr7B7925s374dM2bMwGOPPYaoqCgAwBNPPAGlUompU6fi8OHD+OKLL7Bo0SJkZ2db65g5cyY2bNiAd955B8XFxXj99dexd+9ezJgxw57dt5vT7aEoLoShyNVNv6s3nkiNhRDAzBX7kX/6otQlERG5Lnsug9uyZYsAcNVj8uTJQgjzEuQ//OEPQqPRCJVKJcaOHStKSkpsXuPChQvi8ccfF35+fkKtVospU6aIujrbpcoHDhwQt99+u1CpVKJHjx7izTffvKqWlStXir59+wqlUikGDBgg1q5d26m+OMqS/IaWVhE3Z42Im7NGXGxo+elvIKfX2mYUz368W8TNWSOG/M9GcULHpfpERB3Vmc9vmRCCZwp0gF6vR0BAAGprayUdSivR1iFj4fdQeylw8PUMyeqg7tVoaMPj/9iJA2dqERPsjf9OH40wf5XUZRERObzOfH5z9ZmTOX2hAQAQF+IrcSXUnXyUCvzzmRGIDfZBeXUTpi7fg/qWNqnLIiJyKQxFToaTrN1XqJ8Ky58diSAfTxw8U4vnlu9Bc6tR6rKIiFwGQ5GTsYYiTrJ2Sz1DfbH82ZHwUymw82Q1ZnBzRyKiLsNQ5GROX2hfecY7RW5rcHQgPpo8HCqFHJuKdHhp5QEYTZwaSER0qxiKnAx3syYAGNUrBB/8MgUKuQzfHDiHeV8fAtdMEBHdGoYiJ2I0CZRf5PAZmY1JDMe77btef7qrDH/ZUCJ1SURETo2hyImcr21Cq1HA00OGyABvqcshB/BgchT+/MggAMAH207g3ZyjEldEROS8GIqcSNllZ555yGUSV0OO4vGRsXgtsz8AYFHuMQYjIqKbxFDkRMoucD4RXdtzd/TC7++/FIwWbmIwIiLqLIYiJ1LavnFjPOcT0TX86s5e+N39iQCAhZuOYdGmYxJXRETkXBiKnMjJSnMo6hXmJ3El5Kiev7O3NRi9u+ko3stlMCIi6iiGIidysrIeANArjEd80PU9f2dvzB1vDkZ/zTmKv35XwuX6REQdwFDkJNqMJutEa94pop/ywl2XgtF7m4/j/60pYjAiIvoJDEVOovyieTm+l6cckWovqcshJ/DCXb3xx4cHAAD+tb0Uc/9byJ2viYhugKHISViGznqG+kHO5fjUQU+nxePtnw2GXAas2FOOWV8U8Kw0IqLrYChyEpcmWXM+EXXOz4fHYPETw+DpIcO3B85h+if5aG41Sl0WEZHDYShyEifa7xT1DmUoos67f1Ak/vHUpUNkn122B/UtbVKXRUTkUBiKnASX49OtGpMYjmVTRsJX6YEdJy7gsX/kQVfXLHVZREQOg6HISZys4nJ8unVpvUPw+fOjEOKrxKGzekxcugOlVQ1Sl0VE5BAYipxAbVMrquoNAICeHD6jWzQ4OhD/mX4bYoN9UF7dhIlLd+BAeY3UZRERSY6hyAkc19UBACLUXvD38pS4GnIF8aG++M/02zCwhxrVDQY89o+d2FKik7osIiJJMRQ5gWKtORT1i/CXuBJyJWH+Kqx4Pg139AlFU6sRzy3fiy/zz0hdFhGRZBiKnMBRhiKyEz+VAv+cPAIThkTBaBL47aoDWLjpKHe/JiK3xFDkBKx3ijQMRdT1lAo5/vqLIXjhrl4AgIWbjmH2FwXcy4iI3A5DkYMTQuBoBe8UkX3J5TLMHd8ff35kEDzkMqwuOIdffrQLF+pbpC6NiKjbMBQ5uMr6FlxsbIVcBiSEc48isq8nUmOxfMpI+HspsPf0RTzy/g4c19VLXRYRUbdgKHJwJe1DZ/EhvvDy9JC4GnIHt/cJxVe/vg0xwd4oq27EI+9vx/bjVVKXRURkdwxFDq6Ek6xJAgnh/lj969FIiQtCXXMbJv9rNz7ZeVrqsoiI7IqhyMFZQlFfTrKmbhbip8Knz6XioeQotJkEXlt9CHP/WwhDm0nq0oiI7IKhyMEVnq0FAAyIUktcCbkjL08PLHpsCF7O6AeZDPh8dxme+HAnKus4AZuIXA9DkQNrbjXiWPsk10HRARJXQ+5KJpMha0wC/jl5OPxV5gnYD/7tRxw8UyN1aUREXYqhyIEVndfDaBII9VMiQu0ldTnk5u5J1GD1jNHoFeYLrb4ZP/sgD//dxx2wich1MBQ5sEPtQ2cDewRAJpNJXA0R0DvMD6uzRmNsYjgMbSZkrzyAN9YcQZuR84yIyPkxFDkwy3yiQT04dEaOQ+3liQ+fHo4ZYxIAAB/9WIqn/7UbVdzokYicHEORAzt45tKdIiJHIpfL8NuMfnj/yWHwUXpgx4kLeOC9H5F/ulrq0oiIbhpDkYNqMlw2yZqhiBzU/YMi8XXWaPRun2c06e878fH2Uh4oS0ROiaHIQRWU18BoEohQeyEygJOsyXH10fjj6xm3I3NwJNpMAv/z7RHM+Hw/6lvapC6NiKhTGIoc1N5T5mGI4fFBnGRNDs9PpcDix4di3gNJUMhlWHvwPB5e/COOtR9mTETkDBiKHNTu9lA0Ij5Y4kqIOkYmk+HZ23viixdGQaNW4URlAx5esh1fF5yVujQiog5hKHJAbUYT9p2+CMB8p4jImaTEBWPtb+7Abb1D0GgwYuaKAsz/+hBa2oxSl0ZEdEMMRQ6o6HwdGgxG+KsUSIzg8R7kfEL9VPj31FRkjekNAFiedxoTl+7AqaoGiSsjIro+hiIH9P2xSgBAaq9geMg5n4ick4dchpczEvGvZ4YjyMcTh87q8cDffuRwGhE5LIYiB7StxByK7uoXLnElRLfunkQN1s28AyPjg1Hf0oaZKwow58uDaDJwOI2IHAtDkYPRN7civ8w8n+juvmESV0PUNSIDvPHZr1Lxm3sSIJMBX+wtx0OLf8RRrk4jIgfCUORgthTrYDQJ9ArzRUywj9TlEHUZhYcc2eP64dOpqQjzV+GYrh4PLf4RK3aXcbNHInIIDEUO5puCcwCABwZFSlwJkX3clhCK9TPvwB19QtHcasKr/y3Eb1YUoK65VerSiMjNMRQ5kKr6Fmw7ap5P9NCQKImrIbKfUD8Vlk8ZiTn3JcJDLsO3B84h870fkd++FQURkRQYihzIv/NOo80kkBwdgIRwf6nLIbIruVyG6Xf3xsoX0tAj0Btl1Y34xd/zsHDTUbQZTVKXR0RuyO1C0ZIlSxAfHw8vLy+kpqZi9+7dUpcEwHyX6OPtpQCAX93ZS+JqiLpPSlwQ1s28Aw8PiYLRJLBw0zH84u95KLvQKHVpRORm3CoUffHFF8jOzsb8+fOxb98+JCcnIyMjAzqdTtK6Cspr8MK/86FvbsOAKDXGD+R8InIvAd6eWPTYUCx6bAj8VQrsK6vB/e/9gP/kn+EkbCLqNjLhRn9xUlNTMWLECCxevBgAYDKZEBMTgxdffBGvvvrqDb9Xr9cjICAAtbW1UKu7bpfpE5X1GPvONgDmQzVXTUtD/0juYk3uq7y6EdkrC7DnlHl+UebgSPx5wiAE+HhKXBkROaPOfH67zZ0ig8GA/Px8pKenW5+Ty+VIT09HXl6eZHVV1DZb//urX9/GQERuLybYByueT8PLGf2gkMuw9uB53Lfoe+SduCB1aUTk4twmFFVVVcFoNEKj0dg8r9FooNVqr2rf0tICvV5v87CHNpP5Rl1SpBp9NJxcTQSYjwjJGpOA/0y/DT1DfXG+thlPfLQTC9YX8WBZIrIbtwlFnbVgwQIEBARYHzExMXZ5nzB/FR4d2gP3JPJID6IrJccEYs2Lt+OxETEQAvj7tpN4ePF2HD5XK3VpROSC3GZOkcFggI+PD7788ktMmDDB+vzkyZNRU1ODr7/+2qZ9S0sLWlparF/r9XrExMR0+ZwiIuqYjYe1+N1/C3GhwQCFXIaZY/tg+t29ofDg/7cjouvjnKJrUCqVSElJQW5urvU5k8mE3NxcpKWlXdVepVJBrVbbPIhIOhkDIrBx9p3IGKBBm0ngnZyjmLh0B47r6qUujYhchNuEIgDIzs7Ghx9+iOXLl6OoqAjTp09HQ0MDpkyZInVpRNQBoX4qfPDLFLw7KRn+XgocOFOLzPd+wEc/nITJ5BY3vYnIjhRSF9CdJk2ahMrKSsybNw9arRZDhgzBhg0brpp8TUSOSyaT4ZGh0RjVKwRz/lOI749W4o21RfjuSAX+92fJiA3hQcpEdHPcZk7RrbLXPkVEdPOEEPh8dzneWHsEjQYjfJQe+H1mfzwxMhYymUzq8ojIAXBOERG5BZlMhidSY7Fh5p0Y2TMYjQYjfv/VITz9r904W9MkdXlE5GQYiojI6cWG+GDFr0bhtcz+UCrk+OFYFcb9dRv+vfM05xoRUYcxFBGRS5DLZXjujl5YP/MOpMQFocFgxB9WH8LjH+7EqaoGqcsjIifAUERELqV3mB9WvpCG+Q8mwdvTA7tKq3Hfou/x0Q8nYeRdIyK6AYYiInI5HnIZpozuiY2z7sTohBA0t5rwxtoiTFy6A8cq6qQuj4gcFEMREbms2BAffDI1FW8+Ogj+KgUKymuQ+d6PWLz5GFqNJqnLIyIHw1BERC5NJpPhsZGx+C77ToxNDIfBaML/fncUDy/ejkNneYYaEV3CUEREbiEywBsfTR6OhZOGINDHE0fO6/Hwku14c30xmgxGqcsjIgfAUEREbkMmk2HC0B7ImX0XMgdFwmgS+GDbCYxbuA3fH62UujwikhhDERG5nTB/FZY8OQwfPT0cUQFeKK9uwtP/2o2ZK/ajqr5F6vKISCIMRUTkttKTNPgu+y5MGR0PuQz4uuAcxr6zDSv3lIMnIBG5H4YiInJrfioF5j84AKuzRiMpUo3apla88p+DePzDnThRWS91eUTUjRiKiIgADI4OxDczRuN39yfC29MDO09WY/zCH7Bo0zG0tHEiNpE7YCgiImqn8JDj+Tt747vZd+KuvmEwGE14d9NR3L/oB+wurZa6PCKyM4YiIqIrxAT7YNmUEXjv8aEI9VPiRGUDfvH3PPx21QFc4ERsIpfFUEREdA0ymQwPJUdhU/ZdeGxEDADgy/wzuOedbfhk52meo0bkgmSCSyw6RK/XIyAgALW1tVCr1VKXQ0TdLP/0Rby2+hCKzusBAMnRAXhjwiAMig6QuDIiupHOfH4zFHUQQxERtRlN+PfO03jnu6Oob2mDTAb8MjUOvx3XDwE+nlKXR0TX0JnPbw6fERF1kMJDjimje2LzS3fh4SFREAL4987TuOedrfhP/hnubUTk5BiKiIg6KVzthUWPDcVnv0pF7zBfXGgw4KVVBzDp7ztRoq2TujwiukkMRUREN+m23qFYP/NOzLnPvLfR7lPVuP+9H/CntUdQ39ImdXlE1EkMRUREt0CpkGP63b2x6aW7kDFAA6NJ4MMfSjHmf7fiv/vOwMRVakROgxOtO4gTrYmoI7YU6/D6t4dx+kIjAGBYbCBef2gABkcHSlsYkZvi6jM7YCgioo5qaTPinz+WYvHm42g0GCGTAZOGx+C3Gf0Q6qeSujwit8JQZAcMRUTUWdraZry5vgirC84BAPy9FJid3hdPpcXB04OzF4i6A0ORHTAUEdHN2nOqGq9/cxiHz5k3fuwT7of5Dw7A7X1CJa6MyPUxFNkBQxER3QqjSWDl3nK8vbEE1Q0GAMB9AyLw+8z+iAn2kbg6ItfFUGQHDEVE1BVqG1vx7qaj+Hf7+WkqhRwv3NkL0+7uDR+lQuryiFwOQ5EdMBQRUVcq0dbh9W8OI+/kBQBAhNoLL2f0wyNDe0Aul0lcHZHrYCiyA4YiIupqQgisP6TFn9cV4czFJgDAwB5q/CEzCam9QiSujsg1MBTZAUMREdlLc6sRy3acwuLNx607Yd83IAKvjk9EfKivxNUROTeGIjtgKCIie6uqb8G7OUfx+e4ymATg6SHD5LR4vDi2DwK8PaUuj8gpMRTZAUMREXWXoxV1eGNtEb4/WgkACPLxxKz0vngiNZb7GxF1EkORHTAUEVF321qiw5/WFuGYrh4A0DvMF7/P7I8x/cIhk3EyNlFHMBTZAUMREUmhzWjC53vK8W7OUev+Rn01fpgwtAceHBzFPY6IfgJDkR0wFBGRlPTNrViy5Tg+3n4KhjaT9fnk6ABkDo7E/YMiER3EgER0JYYiO2AoIiJHUNvUig2HzuPrgnPYefICTJf9BR8SE4gHBkdi/KBI9Aj0lq5IIgfCUGQHDEVE5Ggq61qw4bAWaw+ew67Salz+13xYbCAyB0fh/kERiAxgQCL3xVBkBwxFROTIdHXN2HBIi7UHz2P3KduANDwuCJmDIzF+YCQiArykK5JIAgxFdsBQRETOQqdvxvr2gLTn9KWAJJMBI+KCcf+gCIwfFAmNmgGJXB9DkR0wFBGRM9LWNmP9ofNYe/A89p6+aH1eJgNGxAfjgcGRuG9gBML9GZDINTEU2QFDERE5u/O1TVhXaJ6DtK+sxvq8TAak9gxG5uAo3DcgAmH+KumKJOpiDEV2wFBERK7kbE0T1heex5qD51FQXmN9Xi4DRvUKQebgSNw3IAIhfgxI5NwYiuyAoYiIXNWZi41YX6jFmsLzOHBFQLqtdyjuHxSJcQM0CGVAIifEUGQHDEVE5A7KqxuxrvA81haex8Eztdbn5e1zkO4fFImMARFcxUZOg6HIDhiKiMjdlF1oxNrC81h/yDYgAeZ9kMYPNE/S5lEj5MgYiuyAoYiI3Fl5dSM2HtZi/SEt8i9bxQYAA3uorQGpd5ifRBUSXRtDkR0wFBERmVXom80BqVCLXaW2R4301fhh/MBIjB8UgX4af8hkMukKJULnPr/l9iriT3/6E2677Tb4+PggMDDwmm3KysqQmZkJHx8fhIeH4+WXX0ZbW5tNm61bt2LYsGFQqVRISEjAsmXLrnqdJUuWID4+Hl5eXkhNTcXu3bttrjc3NyMrKwshISHw8/PDxIkTUVFR0VVdJSJyKxq1F55Oi8fnz4/Cnt+nY8Gjg3Bn3zAo5DIcrajHotxjuG/hD7jnnW34y4ZiHDxTA/7/b3IGdgtFBoMBP//5zzF9+vRrXjcajcjMzITBYMCOHTuwfPlyLFu2DPPmzbO2KS0tRWZmJsaMGYOCggLMmjULzz33HDZu3Ght88UXXyA7Oxvz58/Hvn37kJycjIyMDOh0Omub2bNn49tvv8WqVauwbds2nDt3Do8++qi9uk5E5DZC/FR4fGQs/u/Zkch/7V688/NkpPfXQKmQo7SqAUu3nsBDi7cjbcFmvLa6ENuOVsLQZpK6bKJrsvvw2bJlyzBr1izU1NTYPL9+/Xo88MADOHfuHDQaDQDggw8+wJw5c1BZWQmlUok5c+Zg7dq1OHTokPX7HnvsMdTU1GDDhg0AgNTUVIwYMQKLFy8GAJhMJsTExODFF1/Eq6++itraWoSFheGzzz7Dz372MwBAcXEx+vfvj7y8PIwaNapD/eDwGRFRx9W3tGFzsQ4bDp3H1pJKNBqM1mv+KgXu6heGe5M0GJMYDrWXp4SVkqtziOGzn5KXl4dBgwZZAxEAZGRkQK/X4/Dhw9Y26enpNt+XkZGBvLw8AOa7Ufn5+TZt5HI50tPTrW3y8/PR2tpq0yYxMRGxsbHWNkRE1LX8VAo8lByF959Mwb4/3IuPnxmBx0fGINRPhbqWNqw5eB4zVxRg2B9z8NQ/d+H/8k7hXE2T1GWTm1NI9cZardYmEAGwfq3Vam/YRq/Xo6mpCRcvXoTRaLxmm+LiYutrKJXKq+Y1aTQa6/tcS0tLC1paWqxf6/X6znWQiIgAAF6eHhiTGI4xieH40wSBgjM1yDlSge8Oa3GisgE/HKvCD8eqMO/rwxjYQ41xSRG4N0mDxAhO1Kbu1alQ9Oqrr+Ivf/nLDdsUFRUhMTHxlopyBAsWLMD//M//SF0GEZFLkctlGBYbhGGxQZhzXyJOVtYj50gFco5UIL/sIg6d1ePQWT3+mnMU0UHeuDdJg3FJERgRHwSFh2SDG+QmOhWKXnrpJTzzzDM3bNOrV68OvVZERMRVq8QsK8IiIiKs/3vlKrGKigqo1Wp4e3vDw8MDHh4e12xz+WsYDAbU1NTY3C26vM21zJ07F9nZ2dav9Xo9YmJiOtQ3IiLqmF5hfnjhLj+8cFdvVNa1YHOxOSD9cKwKZy424ePtp/Dx9lMI9PHEPf3CcW+SBnf2DYOvSrKBDnJhnfpXFRYWhrCwsC5547S0NPzpT3+CTqdDeHg4ACAnJwdqtRpJSUnWNuvWrbP5vpycHKSlpQEAlEolUlJSkJubiwkTJgAwT7TOzc3FjBkzAAApKSnw9PREbm4uJk6cCAAoKSlBWVmZ9XWuRaVSQaXiOT9ERN0lzF+FSSNiMWlELBoNbfj+aBVyjlRgc3EFLja24r/7z+K/+89CqZDj9oRQ3Jukwdj+4Qj355Ej1DXsFrXLyspQXV2NsrIyGI1GFBQUAAASEhLg5+eHcePGISkpCU899RTeeustaLVavPbaa8jKyrKGkWnTpmHx4sV45ZVX8Oyzz2Lz5s1YuXIl1q5da32f7OxsTJ48GcOHD8fIkSOxcOFCNDQ0YMqUKQCAgIAATJ06FdnZ2QgODoZarcaLL76ItLS0Dq88IyKi7uWjVOC+gRG4b2AE2owm5J++aJ6HdKQCZdWN2Fysw+ZiHWQyYGhMIO5tn4eUEM4dtenm2W1J/jPPPIPly5df9fyWLVtw9913AwBOnz6N6dOnY+vWrfD19cXkyZPx5ptvQqG4lNW2bt2K2bNn48iRI4iOjsYf/vCHq4bwFi9ejLfffhtarRZDhgzBe++9h9TUVOv15uZmvPTSS/j888/R0tKCjIwMvP/++zccPrsSl+QTEUlPCIGjFfXIOaJFzpEKHLjiTLZeob7meUgDNBgSEwQPOSdquzse82EHDEVERI5HW9uMnCLzPKS8E1VoNV76SAv1U2Jsogb3Jmlwe59QeHl6SFgpSYWhyA4YioiIHFtdcyu2Ha3Ed4crsKVEh7rmS8dGeXt64M6+obg3KQJjE8MR5KuUsFLqTgxFdsBQRETkPAxtJuwurbYOs52rbbZek8uA4fHBGNe+3D82xEfCSsneGIrsgKGIiMg5CSFw+Jwe37Xvh1R03nYz3r4aP6T31yA9SYMh0YGQcx6SS2EosgOGIiIi11Be3WjdMHL3qWoYTbbzkO5JDMfY/hrc0ScUPkruh+TsGIrsgKGIiMj11Da2YutRHXKOVGBbSSXqWi7NQ7Lsh5Te37wfkkbN/ZCcEUORHTAUERG5NkObCXtOVSPnSAU2FVXgzEXbA2oHRwdYA1JSpJrnsjkJhiI7YCgiInIflv2QNhWZA1JBeQ0u/7SMCvBCepIGY/trMKpXMFQKLvd3VAxFdsBQRETkvnR1zdhSrMOmIh1+OFaJ5laT9Zqv0gN39QvD2EQNxiSGI5jL/R0KQ5EdMBQREREANLcasf14FTYV6ZBbVAFdXYv1mlwGDI8Lxtj+4UhP0qB3GI8dkRpDkR0wFBER0ZVMJoFD52qx6UgFcop0Vy337xnqi/T+4Ujvr0FKXBAUHnKJKnVfDEV2wFBEREQ/5cxF82G1OUcqsPPkBZtjRwJ9PDGmnzkg3dk3FP5enhJW6j4YiuyAoYiIiDqjrrkVPxyrwqYjFdhcokNNY6v1mqeHDKN6hVhXs0UHcVdte2EosgOGIiIiulltRhP2ldWYV7MdqcDJqgab64kR/ri3fTXb4B4B3FW7CzEU2QFDERERdZUTlfXILarApiId9p6qxmWbaiPMX4WxieG4JzEcoxNC4avirtq3gqHIDhiKiIjIHi42GLClRIfcIh22Ha1E/RW7aqf1CsHY/uEY0y8cMcEcZusshiI7YCgiIiJ7a2kzYtfJamwu1iG3uALl1ba7avfT+GNMYjjG9g/H0JhArmbrAIYiO2AoIiKi7iSEaB9m0yG3WIf80xdtDq8N9PHE3X3DcE9/De7qE4YAH65muxaGIjtgKCIiIinVNBqw7WglNhfrsLWkErVNl1azechlGB4XhLH9w3FPoga9w3x5Nls7hiI7YCgiIiJHYVnNlltcgc1FOhzT1dtcjwvxwT2J4RibqMHInsFQKtx3mI2hyA4YioiIyFGVXWjE5uIK5BbrsOtkNQzGS2ez+akUuKNPKO5JDMeYxHCE+qkkrLT7MRTZAUMRERE5g/qWNvx4rAqbiyuwubgSVfWXzmaTyYDk6EDzkv/+4UiKVLv8MBtDkR0wFBERkbMxmQQKz9Yit1iHzcUVOHTW9my2CLUX7ukfjrGJ4bitdyi8lR4SVWo/DEV2wFBERETOrkLfjC3F5tVsPx6rQlOr0XpNpZBjdIJ5mO2exHBEBXpLWGnXYSiyA4YiIiJyJc2tRuw8ecG8J1KRDmdrbPdESozwt65mGxITCA8nPXqEocgOGIqIiMhVCSFwtKLeupptX9lFm6NHgnw8cVffMIxJDMedfcIQ5KuUrthOYiiyA4YiIiJyF9UNBmw7qsOmIh1+OFoJffOlo0fkMmBobBDuSQzH3f3CHH6yNkORHTAUERGRO7LsiWTeNFKHYm2dzXWNWoUx/czL/UcnhMLPwQ6wZSiyA4YiIiIi4GxNE7aW6LClWIftxy/YTNb29JAhtWcI7u5nHmrrFSr9ztoMRXbAUERERGSrudWIXaXV2FKsw5YSHU5faLS5HhfiY72LlNozGF6e3b/kn6HIDhiKiIiIrk8IgdKqBmwpqcSWYh12lV5Aq/FSxPD29MDohBDc3R6SenTTkn+GIjtgKCIiIuq4+pY2bD9e1T7UVgmtvtnmej+NP8YkhmNMvzCkxAVB4WGf89kYiuyAoYiIiOjmCCFQdL4OW9rnIl255N/fS4E7+4bh3v4aTBjao0vfm6HIDhiKiIiIusbFBgO+P2YeZtt2tBIXG1sBACN7BmPlC2ld+l6d+fx2rHVzRERE5PKCfJV4eEgPPDykB4wmgQNnarClWIeeob6S1sVQRERERJLxkMswLDYIw2KDpC4F9pnVRERERORkGIqIiIiIwFBEREREBIChiIiIiAgAQxERERERAIYiIiIiIgAMRUREREQAGIqIiIiIADAUEREREQFgKCIiIiICwFBEREREBIChiIiIiAgAQxERERERAEAhdQHOQggBANDr9RJXQkRERB1l+dy2fI7fCENRB9XV1QEAYmJiJK6EiIiIOquurg4BAQE3bCMTHYlOBJPJhHPnzsHf3x8ymaxLX1uv1yMmJgbl5eVQq9Vd+tqOyJ366059BdhfV8f+ui5X7qsQAnV1dYiKioJcfuNZQ7xT1EFyuRzR0dF2fQ+1Wu1y/xhvxJ366059BdhfV8f+ui5X7etP3SGy4ERrIiIiIjAUEREREQFgKHIIKpUK8+fPh0qlkrqUbuFO/XWnvgLsr6tjf12XO/X1RjjRmoiIiAi8U0REREQEgKGIiIiICABDEREREREAhiIiIiIiAAxFkluyZAni4+Ph5eWF1NRU7N69W+qSbsr333+PBx98EFFRUZDJZFi9erXNdSEE5s2bh8jISHh7eyM9PR3Hjh2zaVNdXY0nn3wSarUagYGBmDp1Kurr67uxFx2zYMECjBgxAv7+/ggPD8eECRNQUlJi06a5uRlZWVkICQmBn58fJk6ciIqKCps2ZWVlyMzMhI+PD8LDw/Hyyy+jra2tO7vSIUuXLsXgwYOtm7qlpaVh/fr11uuu1NdrefPNNyGTyTBr1izrc67U59dffx0ymczmkZiYaL3uSn0FgLNnz+KXv/wlQkJC4O3tjUGDBmHv3r3W6670tyo+Pv6q361MJkNWVhYA1/vddglBklmxYoVQKpXiX//6lzh8+LD41a9+JQIDA0VFRYXUpXXaunXrxO9//3vx3//+VwAQX331lc31N998UwQEBIjVq1eLAwcOiIceekj07NlTNDU1Wdvcd999Ijk5WezcuVP88MMPIiEhQTz++OPd3JOflpGRIT7++GNx6NAhUVBQIO6//34RGxsr6uvrrW2mTZsmYmJiRG5urti7d68YNWqUuO2226zX29raxMCBA0V6errYv3+/WLdunQgNDRVz586Voks39M0334i1a9eKo0ePipKSEvG73/1OeHp6ikOHDgkhXKuvV9q9e7eIj48XgwcPFjNnzrQ+70p9nj9/vhgwYIA4f/689VFZWWm97kp9ra6uFnFxceKZZ54Ru3btEidPnhQbN24Ux48ft7Zxpb9VOp3O5veak5MjAIgtW7YIIVzrd9tVGIokNHLkSJGVlWX92mg0iqioKLFgwQIJq7p1V4Yik8kkIiIixNtvv219rqamRqhUKvH5558LIYQ4cuSIACD27NljbbN+/Xohk8nE2bNnu632m6HT6QQAsW3bNiGEuW+enp5i1apV1jZFRUUCgMjLyxNCmEOkXC4XWq3W2mbp0qVCrVaLlpaW7u3ATQgKChIfffSRS/e1rq5O9OnTR+Tk5Ii77rrLGopcrc/z588XycnJ17zman2dM2eOuP3226973dX/Vs2cOVP07t1bmEwml/vddhUOn0nEYDAgPz8f6enp1ufkcjnS09ORl5cnYWVdr7S0FFqt1qavAQEBSE1NtfY1Ly8PgYGBGD58uLVNeno65HI5du3a1e01d0ZtbS0AIDg4GACQn5+P1tZWm/4mJiYiNjbWpr+DBg2CRqOxtsnIyIBer8fhw4e7sfrOMRqNWLFiBRoaGpCWlubSfc3KykJmZqZN3wDX/P0eO3YMUVFR6NWrF5588kmUlZUBcL2+fvPNNxg+fDh+/vOfIzw8HEOHDsWHH35ove7Kf6sMBgM++eQTPPvss5DJZC73u+0qDEUSqaqqgtFotPnHBgAajQZarVaiquzD0p8b9VWr1SI8PNzmukKhQHBwsEP/PEwmE2bNmoXRo0dj4MCBAMx9USqVCAwMtGl7ZX+v9fOwXHM0hYWF8PPzg0qlwrRp0/DVV18hKSnJJfsKACtWrMC+ffuwYMGCq665Wp9TU1OxbNkybNiwAUuXLkVpaSnuuOMO1NXVuVxfT548iaVLl6JPnz7YuHEjpk+fjt/85jdYvnw5ANf+W7V69WrU1NTgmWeeAeB6/467ikLqAoicWVZWFg4dOoQff/xR6lLsql+/figoKEBtbS2+/PJLTJ48Gdu2bZO6LLsoLy/HzJkzkZOTAy8vL6nLsbvx48db/3vw4MFITU1FXFwcVq5cCW9vbwkr63omkwnDhw/Hn//8ZwDA0KFDcejQIXzwwQeYPHmyxNXZ1z//+U+MHz8eUVFRUpfi0HinSCKhoaHw8PC4aqZ/RUUFIiIiJKrKPiz9uVFfIyIioNPpbK63tbWhurraYX8eM2bMwJo1a7BlyxZER0dbn4+IiIDBYEBNTY1N+yv7e62fh+Wao1EqlUhISEBKSgoWLFiA5ORkLFq0yCX7mp+fD51Oh2HDhkGhUEChUGDbtm147733oFAooNFoXK7PlwsMDETfvn1x/Phxl/v9RkZGIikpyea5/v37W4cLXfVv1enTp7Fp0yY899xz1udc7XfbVRiKJKJUKpGSkoLc3FzrcyaTCbm5uUhLS5Owsq7Xs2dPRERE2PRVr9dj165d1r6mpaWhpqYG+fn51jabN2+GyWRCampqt9d8I0IIzJgxA1999RU2b96Mnj172lxPSUmBp6enTX9LSkpQVlZm09/CwkKbP645OTlQq9VX/dF2RCaTCS0tLS7Z17Fjx6KwsBAFBQXWx/Dhw/Hkk09a/9vV+ny5+vp6nDhxApGRkS73+x09evRV22ccPXoUcXFxAFzvb5XFxx9/jPDwcGRmZlqfc7XfbZeReqa3O1uxYoVQqVRi2bJl4siRI+L5558XgYGBNjP9nUVdXZ3Yv3+/2L9/vwAg/vrXv4r9+/eL06dPCyHMy1wDAwPF119/LQ4ePCgefvjhay5zHTp0qNi1a5f48ccfRZ8+fRxymev06dNFQECA2Lp1q81y18bGRmubadOmidjYWLF582axd+9ekZaWJtLS0qzXLUtdx40bJwoKCsSGDRtEWFiYQy51ffXVV8W2bdtEaWmpOHjwoHj11VeFTCYT3333nRDCtfp6PZevPhPCtfr80ksvia1bt4rS0lKxfft2kZ6eLkJDQ4VOpxNCuFZfd+/eLRQKhfjTn/4kjh07Jj799FPh4+MjPvnkE2sbV/pbJYR5VXNsbKyYM2fOVddc6XfbVRiKJPa3v/1NxMbGCqVSKUaOHCl27twpdUk3ZcuWLQLAVY/JkycLIcxLXf/whz8IjUYjVCqVGDt2rCgpKbF5jQsXLojHH39c+Pn5CbVaLaZMmSLq6uok6M2NXaufAMTHH39sbdPU1CR+/etfi6CgIOHj4yMeeeQRcf78eZvXOXXqlBg/frzw9vYWoaGh4qWXXhKtra3d3Juf9uyzz4q4uDihVCpFWFiYGDt2rDUQCeFafb2eK0ORK/V50qRJIjIyUiiVStGjRw8xadIkm317XKmvQgjx7bffioEDBwqVSiUSExPFP/7xD5vrrvS3SgghNm7cKABc1QchXO932xVkQgghyS0qIiIiIgfCOUVEREREYCgiIiIiAsBQRERERASAoYiIiIgIAEMREREREQCGIiIiIiIADEVEREREABiKiIiIiAAwFBEREREBYCgiIiIiAsBQRERERASAoYiIiIgIAPD/ATGQwdaLKiHIAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vx_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vy_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vz_FL\n"
     ]
    },
    {
     "data": {
      "image/png": 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UrJ4ZSRpImAEA4KQIMxZp9BmqqGmQFJww07pnhmUNAABoQZixSEVNvfl1MMJM3+xUxdltOnqsnmUNAABohTBjEW91U69MUkKcHPHt/zEnJsSpT/OyBgw1AQDQgjBjkWDWy/j5h5o+I8wAAGAizFjEyjBDzwwAAC0IMxaxJsywRhMAAMcjzFgkmHPM+Pkfz959qEo19SxrAACARJixjBU9M13TnOqc4pDPkLYxEzAAAJIIM5axIszYbDbqZgAAOA5hxiLeGv8wU3xQz0vdDAAAgQgzFvH6a2YSg9czI7V+oolhJgAAJMKMZfxLGaQlBrdnpn9Oc5hxs6wBAAASYcYy/uUM0oLcM3N+VqoS4myqqGnQvqPVQT03AADRiDBjEX/PjCvIPTOOeLv6ZjXVzWw+QN0MAACEGYu0DDMFt2dGkgblNS9rcMAT9HMDABBtCDMWaRlmCm7PjNQSZuiZAQCAMGOJhkafquqaZugN5gzAfoO6pUsizAAAIBFmLFFZ22B+bUXPzIBcl2w2ye2t0aHK2qCfHwCAaEKYsYC/XiYxwa6EuOD/iFOd8erdOUUSvTMAABBmLOC16LHs1gaadTMUAQMAOjbCjAWsmjCvtUF51M0AACARZixh5WPZfoO7NffM7KdnBgDQsRFmLNCyLpP1PTN7Dh8zHwMHAKAjIsxYwB8ugr3IZGuZKQ7lpidKYtFJAEDHRpixQChqZqTWk+cx1AQA6LgIMxaoqA1NmBnYPNS0aT9FwACAjoswYwGrVsw+3mB6ZgAAIMxYwVsdomGm5mUNdpZVqrah0dJrAQAQqQgzFgjFpHmSlJeeqIzkBDX4DG13V1p6LQAAIhVhxgL+AmArH82WJJvNZhYBb2KoCQDQQRFmLBCqmhlJGmzOBEyYAQB0TIQZC4Tq0Wyp9RpNPNEEAOiYCDMWaBlmsr5nxj8T8NYvK9ToMyy/HgAAkYYwE2T1jT5V1zc9WRSKnpneXVKUlBCn6vpG7T5EETAAoOMhzASZv1dGklJDEGbi7DYNyE2TxOR5AICOiTATZP7i36SEOCXEhebHO7gbRcAAgI6LMBNkZr1MkvW9Mn6DKAIGAHRghJkgC9WEea0NMh/P9sowKAIGAHQshJkgq2zumUl1hq5npm92quLtNnmq67XvaHXIrgsAQCQgzARZVV3ow4wzPk4XZDcVATPUBADoaAgzQVZZ2/RYdoozLqTXHcQK2gCADoowE2RVtU09MymO0PXMSK2faKJnBgDQsRBmgswMMyEcZpKkwd2aemY27qdnBgDQsYQszDz88MOy2Wy64447zG01NTUqKipS586dlZqaqkmTJqm0tDTgfXv37tWECROUnJysrKws3X333WpoaFCkqjKHmUIbZgbkumS3SQcralXqrQnptQEACKeQhJlVq1bpz3/+s4YOHRqw/Wc/+5neeOMNvfrqq1q6dKkOHDigb3/72+b+xsZGTZgwQXV1dVq2bJleeOEFPf/885o5c2Yomn1O/D0zqSGumUl2xOu8rqmSpE30zgAAOhDLw0xlZaUmT56sv/zlL+rUqZO53ePx6Nlnn9Xjjz+ur33taxo5cqSee+45LVu2TMuXL5ckvfvuu/rss8/04osvavjw4br66qv10EMP6emnn1ZdXZ3VTT8nlXXhGWaSpCHNdTMMNQEAOhLLw0xRUZEmTJigwsLCgO1r1qxRfX19wPb+/furR48eKi4uliQVFxdryJAhys7ONo8ZP368vF6vNm/efMpr1tbWyuv1BrxCJVw1M1JLETBrNAEAOhJLP3HnzZuntWvXatWqVSfsc7vdcjgcysjICNienZ0tt9ttHtM6yPj3+/edyqxZs/SrX/2qna0/Ny3DTOEMM/TMAAA6Dst6ZkpKSnT77bfrpZdeUmJiolWXOakZM2bI4/GYr5KSkpBduzJMBcCSNDDPJZtNcntrdLCiNuTXBwAgHCwLM2vWrFFZWZkuvPBCxcfHKz4+XkuXLtWTTz6p+Ph4ZWdnq66uTuXl5QHvKy0tVU5OjiQpJyfnhKeb/N/7jzkZp9Mpl8sV8AqVlnlmQlsALDX1BvXukiJJ2sTkeQCADsKyMDN27Fht3LhR69evN1+jRo3S5MmTza8TEhK0ZMkS8z3btm3T3r17VVBQIEkqKCjQxo0bVVZWZh6zePFiuVwuDRw40Kqmt0s4a2akliLgTfsIMwCAjsGyT9y0tDQNHjw4YFtKSoo6d+5sbp8yZYruvPNOZWZmyuVy6Sc/+YkKCgo0ZswYSdK4ceM0cOBAfe9739Mjjzwit9ut++67T0VFRXI6nVY1vV3CsTZTa0O6petf6w/QMwMA6DDC84nb7IknnpDdbtekSZNUW1ur8ePH609/+pO5Py4uTgsXLtRtt92mgoICpaSk6KabbtKDDz4YxlafWkOjTzX1Pknh65kZlMcTTQCAjiWkn7gffvhhwPeJiYl6+umn9fTTT5/yPT179tRbb71lccuCo6qu0fw61AtN+g1qXtZgf3m1jlTVKTPFEZZ2AAAQKqzNFET+epmEOJuc8eEJM67EBPXqnCyJR7QBAB0DYSaIwl386zeYmYABAB0IYSaIKs3HssMbZvxPNG2mCBgA0AEQZoKoZcXs8Awx+dEzAwDoSAgzQVQZKcNMzU80lRypludYfVjbAgCA1QgzQXQszHPM+KUnJyg/M0kSMwEDAGIfYSaIqiKkZkZqqZthqAkAEOsIM0EUzkUmj8cK2gCAjoIwE0T+npnUMBcASy11M4QZAECsI8wEUaQUAEstw0x7Dh+Tt4YiYABA7CLMBFGkTJonSZ1SHOqW0VQEvJl1mgAAMYwwE0T+FbNTHOEfZpKkwc3rNDHUBACIZYSZIKqKoAJgqWWoicezAQCxjDATRC0FwJERZgbxeDYAoAMgzARRJBUASy09M7sPVZltAwAg1hBmgsismYmQMNMl1anc9EQZhvTZAYqAAQCxiTATRP6amUgZZpKkQXkMNQEAYhthJohahpki42kmqWWoaTNhBgAQowgzQVLf6FNdg09SZPXM+B/PpmcGABCrCDNBUtWqwDY5Ahaa9PP3zHx+sNJc1RsAgFhCmAmSqrqmehlHnF2O+Mj5sWa5EpWV5pTPkLZ8SREwACD2RM6nbpSrisB6GT//Ctob9zHUBACIPYSZIDnW3DMTSUNMfoPNmYDpmQEAxB7CTJD461GSImRdptYG57FGEwAgdhFmgqTa7JmJvDAzpHtTz8yOskrV1DeGuTUAAAQXYSZIqptDQlJC5IWZHFeiuqQ61OgzKAIGAMQcwkyQ+GtmInGYyWazmTMBUzcDAIg1hJkg8Q/fROIwk9Qy38wmnmgCAMQYwkyQ+HtmEiNwmEliJmAAQOwizATJsQguAJZaHs/eXlqh2gaKgAEAsYMwEyQtw0yRN8+MJHXLSFKn5AQ1+Axtc1eEuzkAAAQNYSZI/PPMROowk81ma5k8bz9FwACA2EGYCZLquqYVsyN1mElqtawBdTMAgBhCmAmS6vrmGYAjtGdGkgb7H88mzAAAYghhJkgieZ4ZP//j2dvcFapr8IW5NQAABAdhJkgieTkDv/zMJLkS41XX6NP2UoqAAQCxgTATJJG8nIFf6yLgzQcYagIAxAbCTJBUR8Ewk9Qy1EQRMAAgVhBmgsSsmYngnhmp9RNNPJ4NAIgNhJkgqY7wSfP8/D0zW770qr6RImAAQPQjzARJNBQAS1LPzslKS4xXXQNFwACA2ECYCQKfzzB7ZiJ1BmA/m83GfDMAgJhCmAmC2lZztkR6z4wkDelOETAAIHYQZoLAvy6TFPk9M1LrJ5ooAgYARD/CTBD4n2RyxtsVZ7eFuTVnRhEwACCWEGaCoKY+Oop//SgCBgDEEsJMEETLHDN+FAEDAGKJpWFm1qxZuuiii5SWlqasrCxNnDhR27ZtCzimpqZGRUVF6ty5s1JTUzVp0iSVlpYGHLN3715NmDBBycnJysrK0t13362GhgZFCnMpgyjpmZEoAgYAxA5Lw8zSpUtVVFSk5cuXa/Hixaqvr9e4ceNUVVVlHvOzn/1Mb7zxhl599VUtXbpUBw4c0Le//W1zf2NjoyZMmKC6ujotW7ZML7zwgp5//nnNnDnTyqa3SbQsZdAaRcAAgFhh6XS1ixYtCvj++eefV1ZWltasWaMrrrhCHo9Hzz77rObOnauvfe1rkqTnnntOAwYM0PLlyzVmzBi9++67+uyzz/Tee+8pOztbw4cP10MPPaSf//zneuCBB+RwOKy8hbPiH2ZKTojs2X9bO74IOCGOEUcAQHQK6SeYx9M0pJGZmSlJWrNmjerr61VYWGge079/f/Xo0UPFxcWSpOLiYg0ZMkTZ2dnmMePHj5fX69XmzZtPep3a2lp5vd6Al5WicZiJImAAQKwIWZjx+Xy64447dOmll2rw4MGSJLfbLYfDoYyMjIBjs7Oz5Xa7zWNaBxn/fv++k5k1a5bS09PNV35+fpDvJlB18zwz0VIALFEEDACIHSELM0VFRdq0aZPmzZtn+bVmzJghj8djvkpKSiy9XnWUPZrtRxEwACAWhKTIY9q0aVq4cKE++ugjde/e3dyek5Ojuro6lZeXB/TOlJaWKicnxzxm5cqVAefzP+3kP+Z4TqdTTqczyHdxav6amcRoCzMUAQMAYoClPTOGYWjatGmaP3++3n//ffXu3Ttg/8iRI5WQkKAlS5aY27Zt26a9e/eqoKBAklRQUKCNGzeqrKzMPGbx4sVyuVwaOHCglc0/a2bPTBQNM0nMBAwAiA2W9swUFRVp7ty5+te//qW0tDSzxiU9PV1JSUlKT0/XlClTdOeddyozM1Mul0s/+clPVFBQoDFjxkiSxo0bp4EDB+p73/ueHnnkEbndbt13330qKioKae/L6fgfzY62YSZ/EXBFTYO2l1ZoUHMNDQAA0cTSnpnZs2fL4/HoyiuvVG5urvl6+eWXzWOeeOIJXXvttZo0aZKuuOIK5eTk6J///Ke5Py4uTgsXLlRcXJwKCgr03e9+V9///vf14IMPWtn0NonWYSaKgAEAscDSnhnDMM54TGJiop5++mk9/fTTpzymZ8+eeuutt4LZtKCK1mEmqakIuHjXYW3c79H1F4W7NQAAtB0zpQVBNM4A7EcRMAAg2hFmgqAlzETPDMB+FAEDAKIdYSYIjkXxMBMzAQMAoh1hJgjMGYCjcJiJImAAQLQjzARBNK7N1BozAQMAohlhJgjMmpkoHGaSKAIGAEQ3wkwQROukeX4UAQMAohlhpp0MwzALgKN1mIkiYABANCPMtFNtg0/+uQGjdZiJImAAQDQjzLSTf4hJit4wI1EEDACIXoSZdvIPMTni7IqPi94f52CKgAEAUSp6P30jRDQvZdDaUIqAAQBRijDTTtH+WLYfRcAAgGhFmGknc8XsKO+ZoQgYABCtCDPtdKx5KYPEKO+ZkSgCBgBEJ8JMO9XESM+MRBEwACA6EWba6ViMFABLFAEDAKITYaadjsVIAbBEETAAIDoRZtoploaZKAIGAEQjwkw7xdIwk0QRMAAg+hBm2sn/aHZSQnyYWxIcFAEDAKINYaadWmYAjo0fJUXAAIBoExufwGHkDzPJjtjomaEIGAAQbQgz7eRfaDIWJs2TKAIGAEQfwkw7tfTMxEaYkSgCBgBEF8JMO1XXNy1nEAvzzPhRBAwAiCaEmXaqjrFHsyWKgAEA0YUw006xNAOwH0XAAIBoQphpp1iaAdiPImAAQDQhzLRTrM0A7EcRMAAgWhBm2qk6BoeZJIqAAQDRgzDTTtX1sTVpnh9FwACAaEGYaYe6Bp8afIak2OuZoQgYABAtCDPt4O+VkWKvZoYiYABAtCDMtIO/XibOblNCnC3MrQk+ioABANGAMNMOZr1MQpxsttgLMxQBAwCiAWGmHY7VNS1lkBhjQ0x+FAEDAKIBYaYdYnHCvNYoAgYARAPCTDvE4lIGrVEEDACIBoSZdojFRSaPRxEwACDSEWbaoTrGh5kkioABAJGPMNMOsT7MJElDKAIGAEQ4wkw7tAwzxdZSBq31zKQIGAAQ2Qgz7eAfZkpKiN0fo91OETAAILLF7qdwCFTVNs0zE2uLTB6PImAAQCQjzLSDP8ykOmM7zFAEDACIZISZdqisbRpmSonxMEMRMAAgkkVNmHn66afVq1cvJSYmavTo0Vq5cmW4m2QuZ5DijN2nmSSKgAEAkS0qwszLL7+sO++8U/fff7/Wrl2rYcOGafz48SorKwtruyqbh5lSYrxmhiJgAEAki4ow8/jjj+uWW27RD37wAw0cOFBz5sxRcnKy/vrXv4a1Xf6amVgfZpIoAgYARK6IDzN1dXVas2aNCgsLzW12u12FhYUqLi4OY8uktXvLJcV+AbBEETAAIHJF/KfwoUOH1NjYqOzs7IDt2dnZ2rp160nfU1tbq9raWvN7r9faD+DMFIel548ExxcBJ8RFfA4GAHQQMfmJNGvWLKWnp5uv/Px8S67z06+dr4e+OUgDctMsOX8koQgYABCpIj7MdOnSRXFxcSotLQ3YXlpaqpycnJO+Z8aMGfJ4POarpKTEkrbdOa6fvlfQSzabzZLzRxKKgAEAkSriw4zD4dDIkSO1ZMkSc5vP59OSJUtUUFBw0vc4nU65XK6AF9qPImAAQCSK+JoZSbrzzjt10003adSoUbr44ov1hz/8QVVVVfrBD34Q7qZ1KBQBAwAiUVSEmeuvv14HDx7UzJkz5Xa7NXz4cC1atOiEomBYiyJgAEAkioowI0nTpk3TtGnTwt2MDs1fBFxR06DtpRUa1FxDAwBAOPF/rXHWKAIGAESiqOmZQWQY0j1dxbsOa+N+j66/KNytARAMhmFoq7tCR4/VyeeTfIYho3m7+a8hGUbrfa33H/ceQzJkNG8/yXnUfHzz1y3nN5qOb96m447zfy1JPt+J15b5/lbXVtObT3meVu31Nd+jZMjnazmP/z06Sdtbtge+x9d8nuN/Zr7mCxvGiddWQDtO83M+/ud2mveYx5/y9xX4+znjtZtuK+D37Wv+Wa66t1Bd05zB/E/zrBFm0CYUAQPnbn95tT7aflDlx+pV1+BTo2E0fxg0fSD4P3h8vpbvfa32G4Zhhg3/940B7z1xv88w1NjqazOstDr/nsPHdKSqLtw/HkS55qgTFoQZtAlFwMC5WV9SrhueKVZNvS/cTTml3l1S5Iizy2aTbDabbJLsdskmW8A2m02yt/r6hO22E99jDzjOf0yr44/bb2/ebzvufPbjz338eY57j731uU93nlPd1/HnOdV9ndXP53Tnad3+c3lPq5+F/TTXNs/R+mdxivOc8Ls8/Xk6JYdvNnzCDNqEImDg3DyxeLtq6n06PytVw7pnyJlgV5zNpjh7yweK3fxgafnabn6ANG+z2447VgH7jn+v3f9e++nPPSA3Td07JYf7xwScE8IM2sRfBFy867A27fcQZoCz0OgztGrPEUnSUzeO0IBcJvIEgokxArQZMwEDbXOwolbH6hoVZ7fpguzYX8sNCDXCDNqMImCgbY4eayqu7ZScoDh77K/lBoQaYQZtdnwRMIDT84eZjDAWSAKxjJoZtBlFwOgIGn2GKmsbVFXboGN1DaqsbVRVbYO5raqu6ftTb2s03+utaZDU1DMDIPgIM2iz1kXAG/dRBIzI09DoU2VtgypqGuStqVdFTUPzqz7gX+9Jtvm/rqprDHq7rujbNejnBECYwTkamt8UZj7d59ENF4e7NYhFhtHUM+Kprlf5sXrz3/Lqulbf1zVvq5eneV9FTYOOBTGIxNttSnHGK9UZrxRnnPl1siOu1fZTbWv6PsURL1digtLpmQEsQZjBORnePUOStGFfeVjbgehR1+DTkao6Haqs1eGqOh2pqtXhyjodqmz5ury6XkeP1cnTHFYafO2bUdQZb1daYoJcifFKS4xXWmJC87+tv27613WSbanOeDnj7bLZKNoFIhlhBudkaH6GJGmru0I19Y1KTIgLb4MQFg2NPh2uqlOpt0al3lqVemtU5q3Rwco6HTZDS1OAqWiuG2krR7xdGUkJykhOUEaSQ+nJCS3fJzuU3npfUmBYccTzjAPQERBmcE7y0hPVJdWpQ5W12nzAo5E9M8PdJATZsboG7T9arX3l1Sr1NIeViqaw4g8uhypr1ZbOkzi7TZkpDnVOcahzqkOdU5zN/zqUmeJUZoqjOaQkNIWUJIcSE+gZAXB6hBmcE5vNpuH56XpvS5k+LSHMRKOq2gbtPlSlfUertb+8WvuPVmt/+THz66PH6s/qPHF2m7qmOpXtcirLlaisNKey0hKVmepQlxSHOqc2hZQuqQ65EhNkZ54VAEFGmME5G9o9oynMUDcT0Y5W1WnTAY+2fOnV7kNV2nWwSrsPVamsovaM701LjFe3jCTlpicqJz1RWWmJynYlKtvlVLYrUVkupzqnOJkIDkBYEWZwzoY11818WlIe1nagxcGKWm064NHm/R5t3O/Rpv1e7S+vPuXxmSkO5XdKUrdOSeqW0fTq3im56ftOSXIl8vQNgMhHmME5G9a8RtOew8dUfqyO2U1DrNFnaKvbqzVfHNWaL45q9Z6jpwwuvbukaGCeS+d1TVWfLinq1SVFvTun8KgwgJhAmME5y0h2qGfnZH1x+Jg27PPoiguYEMxKDY0+fbrPo092HtKqPUe0bm+5KmsDnxCy2aQ+XVI0uFu6hnRL16C8dA3q5qKHBUBMI8ygXYZ1z2gOM+WEmSAzDEOfH6zSxzsO6uOdh7Vi12FVHBdeUp3xGtEjQyN7dtKonpka3iNDqU7+Zw2gY+GvHtplWH6GXv/0gNaXeMLdlJhQ3+jTqt1H9O5npXpvS6n2HQ0cNkpPStCl53fWmD6dNapnpvrlpFF8C6DDI8ygXfx1M5/uK5dhGMwHcg5q6hv1wdYyLdrs1gdby8xFCaWmCeMu7pWpS8/vosvO76KBeS7CCwAchzCDdhmUl644u00HK2rl9tYoNz0p3E2KCo0+Q8t3HdaCdfu1aJM7YPioc4pDYwdkqXBAti7v21VJDmZXBoDTIcygXZIccbogO01bvvTq05JywswZlBw5pnmr9urV1fsC5nnJTU/U14fladzAbI3o0YneFwBoA8IM2m14fnpTmNnn0VWDc8PdnIjT6DP04bYyvbRirz7YViajefr/9KQEXTMkVxOH5+miXpnMjAsA54gwg3Yb1j1Df19ZwuR5x6ltaNT8tfv15492afehKnP7ped31uTRPVU4IJuFEAEgCAgzaLeh3TMkSRv3eeTzGR2+h6G6rlEvLv9Cf/n3LnMoyZUYr/8cla/vjO6hPl1Tw9xCAIgthBm02wXZqUpMsKuitkG7DlXp/KyO+WHd0OjTq2v26Q/vbVeptynE5LgS9V+X99aNF/dQCvO/AIAl+OuKdouPs2tIt3St2nNUn5aUd8gws3T7Qf3qjc3adbBpOKlbRpJuH9tXE0d0YygJACxGmEFQDO2eoVV7jmrDvnJNGtk93M0JGbenRg8t/ExvbvxSUtPCjdO+er4mj+khZzyPVANAKBBmEBT+FbTX7+sYMwEbhqGXV5Xo129uUWVtg+w26QeX9tYdhX2VxjpIABBShBkExfDmIuAtB7yqbWiM6V6JI1V1mv6PDXr3s1JJ0vD8DP164mAN7pYe5pYBQMdEmEFQ5GcmKTPFoSNVdfrsgFcjenQKd5MssXbvUd324hqVemuVEGfTf4/rp/+6vA+T3AFAGFGZiKCw2Wwa0TzUtHZveVjbYpVXVpfohj8vV6m3Vud1TdH8H1+qH33lPIIMAIQZYQZBc2HPpt6YdXuPhrklwWUYhma9tUX3vLZBdY0+jRuYrX9Nu4xhJQCIEAwzIWj8PTPrYqhnptFn6L4FG/X3lSWSpNvH9tXtY/t2+IkBASCSEGYQNEPzM2S3SfvLq1XqrVG2KzHcTWqXhkaf7nzlU73+6QHZbdLD3x6q/7woP9zNAgAch2EmBE2qM14XZKdJiv6hJp/P0M//sVGvf3pA8XabnrxxBEEGACIUYQZB1VI3Ux7ehrSDYRia9fYW/WPtPsXZbfrT5At17dC8cDcLAHAKhBkEVcsTTdHbM/O35V/oL//eLUn63aShGjcoJ8wtAgCcDmEGQeXvmdmwz6P6Rl+YW9N2K3Yd1oNvfCZJuueqfvp/HWhpBgCIVoQZBFXvzilKT0pQbYNPW770hrs5beL21Kho7lo1+Ax9fViebvvKeeFuEgDgLBBmEFR2u00jemRIiq66GZ/P0J2vrNehyjr1z0nT7yYNkc3G49cAEA0IMwi6EflNQ03RVDfz1092a9nnh5WUEKc/Tb5QyQ5mLQCAaEGYQdBd2DNDUvT0zGwvrdAj72yTJN07YYD6dE0Nc4sAAG1BmEHQDcvPkM0m7T1yTIcqa8PdnNPy+QxN/8cG1TX49NV+XTV5dI9wNwkA0EaEGQSdKzFBfbOaejfWfhHZQ02vrC7R2r3lSnHE6bffpk4GAKKRJWFmz549mjJlinr37q2kpCSdd955uv/++1VXVxdw3IYNG3T55ZcrMTFR+fn5euSRR04416uvvqr+/fsrMTFRQ4YM0VtvvWVFkxFkLXUz5eFtyGkcqarTw4u2SpJ+9h8XKDc9KcwtAgCcC0vCzNatW+Xz+fTnP/9Zmzdv1hNPPKE5c+boF7/4hXmM1+vVuHHj1LNnT61Zs0aPPvqoHnjgAT3zzDPmMcuWLdONN96oKVOmaN26dZo4caImTpyoTZs2WdFsBNHI5vlmIrln5vfvblP5sXr1z0nTTZf0CndzAADnyGYYhhGKCz366KOaPXu2du3aJUmaPXu27r33XrndbjkcDknS9OnTtWDBAm3d2vT/lq+//npVVVVp4cKF5nnGjBmj4cOHa86cOWd9ba/Xq/T0dHk8HrlcriDeFU5l18FKfe33S+WIt2vjA+PkjI8Ld5MC7DpYqf944iM1+gzNmzpGY/p0DneTAADHOdvP75DVzHg8HmVmZprfFxcX64orrjCDjCSNHz9e27Zt09GjR81jCgsLA84zfvx4FRcXn/ZatbW18nq9AS+EVu8uKeqS6lBdg08b93nC3ZwTPPbuNjX6DI3tn0WQAYAoF5Iws3PnTj311FP60Y9+ZG5zu93Kzs4OOM7/vdvtPu0x/v2nMmvWLKWnp5uv/HxWOw41m82mUT2bwuuqPZE11LRu71G9tdEtm026+6p+4W4OAKCd2hRmpk+fLpvNdtqXf4jIb//+/brqqqt03XXX6ZZbbglq409lxowZ8ng85qukpCQk10WgUb2a6mZW7zkS5pYEeuK9HZKkb4/orv45DDsCQLRr0zSnd911l26++ebTHtOnTx/z6wMHDuirX/2qLrnkkoDCXknKyclRaWlpwDb/9zk5Oac9xr//VJxOp5xO52mPgfUu7t3UM7P6i6Py+QzZ7eF/7HnjPo8+2n5QcXabbh/bN9zNAQAEQZvCTNeuXdW1a9ezOnb//v366le/qpEjR+q5556T3R7YCVRQUKB7771X9fX1SkhIkCQtXrxY/fr1U6dOncxjlixZojvuuMN83+LFi1VQUNCWZiNMBua6lOyIk6e6XjvKKtUvJy3cTdKfPtwpSfrGsDz16Jwc5tYAAILBkpqZ/fv368orr1SPHj302GOP6eDBg3K73QG1Lt/5znfkcDg0ZcoUbd68WS+//LL++Mc/6s477zSPuf3227Vo0SL9/ve/19atW/XAAw9o9erVmjZtmhXNRpDFx9l1YY+mYLoyAoaadpZVaNHmpv8Gb7uSFbEBIFZYEmYWL16snTt3asmSJerevbtyc3PNl196erreffdd7d69WyNHjtRdd92lmTNnaurUqeYxl1xyiebOnatnnnlGw4YN02uvvaYFCxZo8ODBVjQbFoikupk5S3fJMKTxg7J1QXb4e4kAAMERsnlmwol5ZsJn2c5D+s7/rlBeeqKWzRgbtnYcrqxVwcPvq67Bp3/++BKzxwgAELkibp4ZdEzDe2Qo3m7TAU+N9pdXh60d81aVqK7Bp2Hd0wkyABBjCDOwVLIjXoO6pUsK31BTQ6NPLy3/QpL0/YJeYWkDAMA6hBlY7qLmdZpW7g5PmHlvS6kOeGrUOcWhCUNzz/wGAEBUIczAchc1zzezfNfhsFz/+WV7JEk3XJyvxITIWiMKANB+hBlYbkzvzrLZpM8PVqnMWxPSa28vrdDyXUcUZ7dp8uieIb02ACA0CDOwXHpyggbnNdXNFIe4d+aVVU1LWYztn6W8jKSQXhsAEBqEGYTEJec1rUy9bGfowkx9o08L1h+QJF03isVGASBWEWYQEgX+MLPrUMiu+dH2gzpUWavOKQ5d2e/sluEAAEQfwgxC4qJemYq321RypFolR46F5Jr/WLtPkvTN4d2UEMd/6gAQq/gLj5BIccZreH6GJGnZ59b3zpQfq9N7n5VJkiaN7Gb59QAA4UOYQciYdTOfW18388anB1TX6FP/nDQNai4+BgDEJsIMQqbgvC6SmsKM1UuCvbamaYjp/43sbul1AADhR5hByIzokSFnvF0HK2r1+cFKy66zo7RCn+7zKM5u0zeHM8QEALGOMIOQSUyI06heTUsbfLTdurqZ15oLf7/ar6u6pjktuw4AIDIQZhBSV16QJUn6cPtBS87f6DO0YN1+SdKkCxliAoCOgDCDkPLP97J812FV1zUG/fz/3nFQpd5aZSQn6GsDsoJ+fgBA5CHMIKTOz0pVt4wk1TX4VGzBBHr/WNvUK/ONYXlyxrOoJAB0BIQZhJTNZjN7Zz7YGtyhJk91vd7Z7JbEU0wA0JEQZhByX+3XNPzzwbayoD6i/eaGL1XX4FPfrFQN6cbcMgDQURBmEHKXnN9Zjji79h2t1ucHq4J23tfWNK2Q/f9GdpfNZgvaeQEAkY0wg5BLdsRrdJ9MSdKSLaVBOefnByu1dm+57DZp4gjmlgGAjoQwg7AYNzBbkrSoucalvV5d3TS3zJX9spTtSgzKOQEA0YEwg7AYPyhHNpu0bm+5vvRUt+tcDY0+/bN5orzrKPwFgA6HMIOwyHIlamSPptmA39nUvt6Zj3YcVFlFrTJTHBo7IDsYzQMARBHCDMLmqsE5kqS32xlm/ENME4d3kyOe/6QBoKPhLz/Cxh9mVu45cs5DTUeq6vRecxHxdaMYYgKAjogwg7Dp3ilZF/fOlGFI85vXU2qr+ev2q77R0JBu6RqQ6wpyCwEA0YAwg7CadGHTY9T/XLu/zRPo+XyGXlr+hSTpPy/KD3rbAADRgTCDsLpmSK4SE+zaWVapDfs8bXrvRzsOatehKqU54/Vt5pYBgA6LMIOwSktM0PhBTbUzc1fsbdN7n1+2R1JTr0yKMz7YTQMARAnCDMLue2N6SpLmr9+vQ5W1Z/We7aUV+nDbQdls0vcLelrZPABAhCPMIOxG9uykYfkZqmvw6cXmGpgz+eN7OyRJVw3KUc/OKVY2DwAQ4QgzCDubzaYpl/WWJP2t+Asdq2s47fFb3V69ufFLSdLthX0tbx8AILIRZhARrh6co/zMJB2uqtNfP9592mMfXbRNkjRhSK765/A4NgB0dIQZRISEOLv+e1w/SdLsDz/XgfKTT6L37ma3lmwtU0KcTT/7jwtC2UQAQIQizCBifH1oni7skaGqukbd89oGNfoC55350lOt6f/cKEm65fI+Oj8rNRzNBABEGMIMIobdbtNj1w1TYoJdH+88pPsWbFRDo0+SVOqt0U1/XakjVXUalOfST8dSKwMAaMLkHIgofbqm6vH/HK6iuWv195UlWr3nqPrnuvTh1jJV1DYo2+XUnO+OVGJCXLibCgCIEPTMIOJcMyRXT3/nQqUnJWhHWaXe+PSAKmobNLibS6/deonyM5PD3UQAQAShZwYR6ZohuRrTp7Pe21KqgxW1GpCbpisvyJLdbgt30wAAEYYwg4iVmeLQf45iAUkAwOkxzAQAAKIaYQYAAEQ1wgwAAIhqhBkAABDVCDMAACCqEWYAAEBUszzM1NbWavjw4bLZbFq/fn3Avg0bNujyyy9XYmKi8vPz9cgjj5zw/ldffVX9+/dXYmKihgwZorfeesvqJgMAgChieZi55557lJeXd8J2r9ercePGqWfPnlqzZo0effRRPfDAA3rmmWfMY5YtW6Ybb7xRU6ZM0bp16zRx4kRNnDhRmzZtsrrZAAAgStgMwzDOfNi5efvtt3XnnXfqH//4hwYNGqR169Zp+PDhkqTZs2fr3nvvldvtlsPhkCRNnz5dCxYs0NatWyVJ119/vaqqqrRw4ULznGPGjNHw4cM1Z86cs26H1+tVenq6PB6PXC5X8G4QAABY5mw/vy3rmSktLdUtt9yiv/3tb0pOPnEtneLiYl1xxRVmkJGk8ePHa9u2bTp69Kh5TGFhYcD7xo8fr+Li4tNeu7a2Vl6vN+AFAABikyVhxjAM3Xzzzbr11ls1atSokx7jdruVnZ0dsM3/vdvtPu0x/v2nMmvWLKWnp5uv/HymxAcAIFa1KcxMnz5dNpvttK+tW7fqqaeeUkVFhWbMmGFVu09rxowZ8ng85qukpCQs7QAAANZr00KTd911l26++ebTHtOnTx+9//77Ki4ultPpDNg3atQoTZ48WS+88IJycnJUWloasN//fU5OjvnvyY7x7z8Vp9N5wrUBAEBsalOY6dq1q7p27XrG45588kn9+te/Nr8/cOCAxo8fr5dfflmjR4+WJBUUFOjee+9VfX29EhISJEmLFy9Wv3791KlTJ/OYJUuW6I477jDPtXjxYhUUFLSl2fLXOFM7AwBA9PB/bp/xWSUjBHbv3m1IMtatW2duKy8vN7Kzs43vfe97xqZNm4x58+YZycnJxp///GfzmE8++cSIj483HnvsMWPLli3G/fffbyQkJBgbN25s0/VLSkoMSbx48eLFixevKHyVlJSc9nO+TT0zwZSenq53331XRUVFGjlypLp06aKZM2dq6tSp5jGXXHKJ5s6dq/vuu0+/+MUv1LdvXy1YsECDBw9u07Xy8vJUUlKitLQ02Wy2oN2D1+tVfn6+SkpKOsQj39xvbOtI99uR7lXifmNdLN+vYRiqqKg46Xx1rVk6z0ys62jz13C/sa0j3W9HuleJ+411He1+T4a1mQAAQFQjzAAAgKhGmGkHp9Op+++/v8M8Bs79xraOdL8d6V4l7jfWdbT7PRlqZgAAQFSjZwYAAEQ1wgwAAIhqhBkAABDVCDMAACCqEWba4emnn1avXr2UmJio0aNHa+XKleFuUpt99NFH+vrXv668vDzZbDYtWLAgYL9hGJo5c6Zyc3OVlJSkwsJC7dixI+CYI0eOaPLkyXK5XMrIyNCUKVNUWVkZwrs4e7NmzdJFF12ktLQ0ZWVlaeLEidq2bVvAMTU1NSoqKlLnzp2VmpqqSZMmnbDg6d69ezVhwgQlJycrKytLd999txoaGkJ5K2c0e/ZsDR06VC6XSy6XSwUFBXr77bfN/bFyn6fy8MMPy2azBaztFkv3/MADD8hmswW8+vfvb+6PpXv1279/v7773e+qc+fOSkpK0pAhQ7R69Wpzfyz9verVq9cJv1+bzaaioiJJsfn7bZc2LXIE07x58wyHw2H89a9/NTZv3mzccsstRkZGhlFaWhruprXJW2+9Zdx7773GP//5T0OSMX/+/ID9Dz/8sJGenm4sWLDA+PTTT41vfOMbRu/evY3q6mrzmKuuusoYNmyYsXz5cuPf//63cf755xs33nhjiO/k7IwfP9547rnnjE2bNhnr1683rrnmGqNHjx5GZWWlecytt95q5OfnG0uWLDFWr15tjBkzxrjkkkvM/Q0NDcbgwYONwsJCY926dcZbb71ldOnSxZgxY0Y4bumUXn/9dePNN980tm/fbmzbts34xS9+YSQkJBibNm0yDCN27vNkVq5cafTq1csYOnSocfvtt5vbY+me77//fmPQoEHGl19+ab4OHjxo7o+lezUMwzhy5IjRs2dP4+abbzZWrFhh7Nq1y3jnnXeMnTt3msfE0t+rsrKygN/t4sWLDUnGBx98YBhG7P1+24swc44uvvhio6ioyPy+sbHRyMvLM2bNmhXGVrXP8WHG5/MZOTk5xqOPPmpuKy8vN5xOp/H3v//dMAzD+OyzzwxJxqpVq8xj3n77bcNmsxn79+8PWdvPVVlZmSHJWLp0qWEYTfeXkJBgvPrqq+YxW7ZsMSQZxcXFhmE0BUC73W643W7zmNmzZxsul8uora0N7Q20UadOnYz//d//jen7rKioMPr27WssXrzY+MpXvmKGmVi75/vvv98YNmzYSffF2r0ahmH8/Oc/Ny677LJT7o/1v1e33367cd555xk+ny8mf7/txTDTOairq9OaNWtUWFhobrPb7SosLFRxcXEYWxZcu3fvltvtDrjP9PR0jR492rzP4uJiZWRkaNSoUeYxhYWFstvtWrFiRcjb3FYej0eSlJmZKUlas2aN6uvrA+65f//+6tGjR8A9DxkyRNnZ2eYx48ePl9fr1ebNm0PY+rPX2NioefPmqaqqSgUFBTF7n5JUVFSkCRMmBNybFJu/2x07digvL099+vTR5MmTtXfvXkmxea+vv/66Ro0apeuuu05ZWVkaMWKE/vKXv5j7Y/nvVV1dnV588UX98Ic/lM1mi8nfb3sRZs7BoUOH1NjYGPAfiSRlZ2fL7XaHqVXB57+X092n2+1WVlZWwP74+HhlZmZG/M/C5/Ppjjvu0KWXXmquxO52u+VwOJSRkRFw7PH3fLKfiX9fJNm4caNSU1PldDp16623av78+Ro4cGDM3affvHnztHbtWs2aNeuEfbF2z6NHj9bzzz+vRYsWafbs2dq9e7cuv/xyVVRUxNy9StKuXbs0e/Zs9e3bV++8845uu+02/fSnP9ULL7wgKbb/Xi1YsEDl5eW6+eabJcXef8vBEB/uBgDhUlRUpE2bNunjjz8Od1Ms069fP61fv14ej0evvfaabrrpJi1dujTczbJESUmJbr/9di1evFiJiYnhbo7lrr76avProUOHavTo0erZs6deeeUVJSUlhbFl1vD5fBo1apR++9vfSpJGjBihTZs2ac6cObrpppvC3DprPfvss7r66quVl5cX7qZELHpmzkGXLl0UFxd3QuV4aWmpcnJywtSq4PPfy+nuMycnR2VlZQH7GxoadOTIkYj+WUybNk0LFy7UBx98oO7du5vbc3JyVFdXp/Ly8oDjj7/nk/1M/PsiicPh0Pnnn6+RI0dq1qxZGjZsmP74xz/G3H1KTUMrZWVluvDCCxUfH6/4+HgtXbpUTz75pOLj45WdnR1z99xaRkaGLrjgAu3cuTMmf7+5ubkaOHBgwLYBAwaYQ2ux+vfqiy++0Hvvvaf/+q//MrfF4u+3vQgz58DhcGjkyJFasmSJuc3n82nJkiUqKCgIY8uCq3fv3srJyQm4T6/XqxUrVpj3WVBQoPLycq1Zs8Y85v3335fP59Po0aND3uYzMQxD06ZN0/z58/X++++rd+/eAftHjhyphISEgHvetm2b9u7dG3DPGzduDPijuHjxYrlcrhP+2EYan8+n2tramLzPsWPHauPGjVq/fr35GjVqlCZPnmx+HWv33FplZaU+//xz5ebmxuTv99JLLz1hGoXt27erZ8+ekmLz75UkPffcc8rKytKECRPMbbH4+223cFcgR6t58+YZTqfTeP75543PPvvMmDp1qpGRkRFQOR4NKioqjHXr1hnr1q0zJBmPP/64sW7dOuOLL74wDKPpUceMjAzjX//6l7Fhwwbjm9/85kkfdRwxYoSxYsUK4+OPPzb69u0bkY86GoZh3HbbbUZ6errx4YcfBjz2eOzYMfOYW2+91ejRo4fx/vvvG6tXrzYKCgqMgoICc7//kcdx48YZ69evNxYtWmR07do14h55nD59urF06VJj9+7dxoYNG4zp06cbNpvNePfddw3DiJ37PJ3WTzMZRmzd81133WV8+OGHxu7du41PPvnEKCwsNLp06WKUlZUZhhFb92oYTY/bx8fHG7/5zW+MHTt2GC+99JKRnJxsvPjii+Yxsfb3qrGx0ejRo4fx85///IR9sfb7bS/CTDs89dRTRo8ePQyHw2FcfPHFxvLly8PdpDb74IMPDEknvG666SbDMJoed/zlL39pZGdnG06n0xg7dqyxbdu2gHMcPnzYuPHGG43U1FTD5XIZP/jBD4yKioow3M2ZnexeJRnPPfeceUx1dbXx4x//2OjUqZORnJxsfOtb3zK+/PLLgPPs2bPHuPrqq42kpCSjS5cuxl133WXU19eH+G5O74c//KHRs2dPw+FwGF27djXGjh1rBhnDiJ37PJ3jw0ws3fP1119v5ObmGg6Hw+jWrZtx/fXXB8y5Ekv36vfGG28YgwcPNpxOp9G/f3/jmWeeCdgfa3+v3nnnHUPSCfdgGLH5+20Pm2EYRli6hAAAAIKAmhkAABDVCDMAACCqEWYAAEBUI8wAAICoRpgBAABRjTADAACiGmEGAABENcIMAACIaoQZAAAQ1QgzAAAgqhFmAABAVCPMAACAqPb/AVOhlq/DIdtsAAAAAElFTkSuQmCC",
      "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",
    "print('x_FL')\n",
    "plt.plot(df['Time'], x_FL)\n",
    "plt.show()\n",
    "\n",
    "print('y_FL')\n",
    "plt.plot(df['Time'], y_FL)\n",
    "plt.show()\n",
    "\n",
    "print('z_FL')\n",
    "plt.plot(df['Time'], z_FL)\n",
    "plt.show()\n",
    "\n",
    "print('vx_FL')\n",
    "plt.plot(df['Time'], vx_FL)\n",
    "plt.show()\n",
    "\n",
    "print('vy_FL')\n",
    "plt.plot(df['Time'], vy_FL)\n",
    "plt.show()\n",
    "\n",
    "print('vz_FL')\n",
    "plt.plot(df['Time'], vz_FL)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.748061737030652"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(np.array(acc_total) / g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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",
       "1718      9.595482\n",
       "1719      6.396103\n",
       "1720      3.197213\n",
       "1721     -0.001187\n",
       "1722     -0.001187\n",
       "Name: altitude, Length: 1721, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['altitude'] * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41435.2573895818"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(df['altitude'] * 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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",
       "1718    752.238883\n",
       "1719    752.842354\n",
       "1720    753.445825\n",
       "1721    754.049295\n",
       "1722    754.049295\n",
       "Name: Time, Length: 1721, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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/40km.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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