Proton Motive Force via DIRK II JRP seq 250-2000


Estimates ESC parameters along series of PAR 250, 500, 1000, 1500, 2000 Estimates the proton motive force through the ATP synthase, thereby estimating ATP production. The proton motive force is measured by measuring the electrochromic shift (ECS), the shift in the absorbance of chlorophyll at ~520nm in the thylakoid membrane due to a shift in the electric field. The electric field is created by the accumulation of hydrogen ions (H+) in the thylakoid, causing an electric field to be produced between the inside and outside of the thylakoid membrane. This measurement applies the ambient light level in the chamber to the sample, then shuts off the light, causing the intensity of the electric field to drop as the H+ ions drain from the thylakoid. This drop in electric field intensity is detected by the measuring light at 520nm. The method is called DIRK - Dark Induced Relaxation Kinetics. The size of the change in the electric field (and therefore 520 signal) is an indicator of the quantity of H+ ions which had accumulated in the thylakoid. The rate at which the electric field changes indicates the capacity of ATP synthase to release H+ from the thylakoid membrane.
// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?

var output = {};
var spad;

var vhplus_250;
var tau_250;
var ECSt_250;
var quality_flag_250 = 0;
var i_250 = 0;
var j_250 = 0;
var h_250 = 0;
var k_250 = 0;

var vhplus_500;
var tau_500;
var ECSt_500;
var quality_flag_500 = 0;
var i_500 = 0;
var j_500 = 0;
var h_500 = 0;
var k_500 = 0;

var vhplus_1000;
var tau_1000;
var ECSt_1000;
var quality_flag_1000 = 0;
var i_1000 = 0;
var j_1000 = 0;
var h_1000 = 0;
var k_1000 = 0;

var vhplus_1500;
var tau_1500;
var ECSt_1500;
var quality_flag_1500 = 0;
var i_1500 = 0;
var j_1500 = 0;
var h_1500 = 0;
var k_1500 = 0;

var vhplus_2000;
var tau_2000;
var ECSt_2000;
var quality_flag_2000 = 0;
var i_2000 = 0;
var j_2000 = 0;
var h_2000 = 0;
var k_2000 = 0;

// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_250 = json.data_raw.slice(300,600);
var smooth1_abs_250 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_250 = MathMEAN(json.data_raw.slice(230,290));
smooth1_250[0] = fixit_250 ;// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_250 = json.data_raw.slice(300,600);
var smooth1_abs_250 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_250 = MathMEAN(json.data_raw.slice(230,290));
smooth1_250[0] = fixit_250;
smooth1_250[1] = fixit_250;

// create an rolling average for every 2 measurements.  Then repeat with ever 3.  Then 4, etc.  Then repeat that process 5 times.

var tbsmooth_250 = 0;

///*
// first just smooth out the big bumps
for (k=0;k<15;k++) {
  for (h=2;h<3;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_250 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_250 += smooth1_250[i+j];  // sum current point + next point
      }
      smooth1_250[j] = MathROUND(tbsmooth_250/h,0);
    }
  }
}

// then roll out the kinks
for (k=0;k<7;k++) {
  for (h=2;h<5;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_250 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_250 += smooth1_250[i-1+j];  // sum previous 1 point + next h-1 point(s)
      }
      smooth1_250[j] = MathROUND(tbsmooth_250/h,0);
    }
  }
}
//*/


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_500 = json.data_raw.slice(1200,1500);
var smooth1_abs_500 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_500 = MathMEAN(json.data_raw.slice(1130,1190));
smooth1_500[0] = fixit_500 ;// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_500 = json.data_raw.slice(1200,1500);
var smooth1_abs_500 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_500 = MathMEAN(json.data_raw.slice(1130,1190));
smooth1_500[0] = fixit_500;
smooth1_500[1] = fixit_500;

// create an rolling average for every 2 measurements.  Then repeat with ever 3.  Then 4, etc.  Then repeat that process 5 times.

var tbsmooth_500 = 0;

///*
// first just smooth out the big bumps
for (k=0;k<15;k++) {
  for (h=2;h<3;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_500 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_500 += smooth1_500[i+j];  // sum current point + next point
      }
      smooth1_500[j] = MathROUND(tbsmooth_500/h,0);
    }
  }
}

// then roll out the kinks
for (k=0;k<7;k++) {
  for (h=2;h<5;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_500 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_500 += smooth1_500[i-1+j];  // sum previous 1 point + next h-1 point(s)
      }
      smooth1_500[j] = MathROUND(tbsmooth_500/h,0);
    }
  }
}
//*/

// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_1000 = json.data_raw.slice(2100,2400);
var smooth1_abs_1000 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_1000 = MathMEAN(json.data_raw.slice(2030,2090));
smooth1_1000[0] = fixit_1000 ;// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_1000 = json.data_raw.slice(2100,2400);
var smooth1_abs_1000 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_1000 = MathMEAN(json.data_raw.slice(2030,2090));
smooth1_1000[0] = fixit_1000;
smooth1_1000[1] = fixit_1000;

// create an rolling average for every 2 measurements.  Then repeat with ever 3.  Then 4, etc.  Then repeat that process 5 times.

var tbsmooth_1000 = 0;

///*
// first just smooth out the big bumps
for (k=0;k<15;k++) {
  for (h=2;h<3;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_1000 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_1000 += smooth1_1000[i+j];  // sum current point + next point
      }
      smooth1_1000[j] = MathROUND(tbsmooth_1000/h,0);
    }
  }
}

// then roll out the kinks
for (k=0;k<7;k++) {
  for (h=2;h<5;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_1000 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_1000 += smooth1_1000[i-1+j];  // sum previous 1 point + next h-1 point(s)
      }
      smooth1_1000[j] = MathROUND(tbsmooth_1000/h,0);
    }
  }
}
//*/

// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_1500 = json.data_raw.slice(3000,3300);
var smooth1_abs_1500 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_1500 = MathMEAN(json.data_raw.slice(2930,2990));
smooth1_1500[0] = fixit_1500 ;// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_1500 = json.data_raw.slice(3000,3300);
var smooth1_abs_1500 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_1500 = MathMEAN(json.data_raw.slice(2930,2990));
smooth1_1500[0] = fixit_1500;
smooth1_1500[1] = fixit_1500;

// create an rolling average for every 2 measurements.  Then repeat with ever 3.  Then 4, etc.  Then repeat that process 5 times.

var tbsmooth_1500 = 0;

///*
// first just smooth out the big bumps
for (k=0;k<15;k++) {
  for (h=2;h<3;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_1500 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_1500 += smooth1_1500[i+j];  // sum current point + next point
      }
      smooth1_1500[j] = MathROUND(tbsmooth_1500/h,0);
    }
  }
}

// then roll out the kinks
for (k=0;k<7;k++) {
  for (h=2;h<5;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_1500 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_1500 += smooth1_1500[i-1+j];  // sum previous 1 point + next h-1 point(s)
      }
      smooth1_1500[j] = MathROUND(tbsmooth_1500/h,0);
    }
  }
}
//*/

// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_2000 = json.data_raw.slice(3900,4200);
var smooth1_abs_2000 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_2000 = MathMEAN(json.data_raw.slice(3830,3890));
smooth1_2000[0] = fixit_2000 ;// The measures DIRK ECS using on-off-on actinic, with actinic pulled from the PAR sensor.  This measurement smooths out the dark period by using a 2 layer smoothing.
// should I calibrate this to a 940 signal, to estimate thickness?


// This is the area which needs to be smoothed out,  the _abs version will be absorbance values
var smooth1_2000 = json.data_raw.slice(3900,4200);
var smooth1_abs_2000 = [];

// points 300 and 301 can be affected by electronic blips, so we set them == to the average of the previous 'on' values
var fixit_2000 = MathMEAN(json.data_raw.slice(3830,3890));
smooth1_2000[0] = fixit_2000;
smooth1_2000[1] = fixit_2000;

// create an rolling average for every 2 measurements.  Then repeat with ever 3.  Then 4, etc.  Then repeat that process 5 times.

var tbsmooth_2000 = 0;

///*
// first just smooth out the big bumps
for (k=0;k<15;k++) {
  for (h=2;h<3;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_2000 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_2000 += smooth1_2000[i+j];  // sum current point + next point
      }
      smooth1_2000[j] = MathROUND(tbsmooth_2000/h,0);
    }
  }
}

// then roll out the kinks
for (k=0;k<7;k++) {
  for (h=2;h<5;h++) {
    for (j=1;j<296;j++) {
      tbsmooth_2000 = 0;
      for (i=0;i<h;i++) {
        tbsmooth_2000 += smooth1_2000[i-1+j];  // sum previous 1 point + next h-1 point(s)
      }
      smooth1_2000[j] = MathROUND(tbsmooth_2000/h,0);
    }
  }
}
//*/











// now convert smooth1 into absorbance ( abs = log(Is / I0) )
for (var x=0;x<300;x++) {
  smooth1_abs_250[x] = MathLOG(smooth1_250[x]/smooth1_250[0]);
}


// calculate ECSt_250
max_250 = MathMEAN(smooth1_abs_250.sort().slice(10,299));
var min_250 = smooth1_abs_250[0];
ECSt_250 = max_250 - min_250;

// Calculate GH+ by finding the 1/e point in the dark period
var tmpval_250;
var howclose_e_250 = 1;
var tmpslope_250 = 0;
var close_e_250 = [];
var slope_e_250 = [];
for (k=0;k<299;k++) {
  tmpval_250 = (smooth1_abs_250[k]-min_250)/(max_250-min_250);
  howclose_e_250 = (1/Math.E - tmpval_250);
  close_e_250[k] = MathROUND((1/Math.E - tmpval_250),3);
  // if slope is largest, then choose it for vhplus_250 up to tau
  if (((smooth1_abs_250[k+1]-min_250)/(max_250-min_250) - tmpval_250) > tmpslope_250) {
    vhplus_250 = (smooth1_abs_250[k+1]-min_250)/(max_250-min_250) - tmpval_250;
  }
  tmpslope_250 = (smooth1_abs_250[k+1]-min_250)/(max_250-min_250) - tmpval_250;
  slope_e_250[k] = MathROUND((smooth1_abs_250[k+1]-min_250)/(max_250-min_250) - tmpval_250,4);
  // once you hit tau, then stop iterating
  if (howclose_e_250 < 0) {
    tau_250 = (smooth1_abs_250[k]-min_250)/(max_250-min_250);
    break;
  }
}

// Check for quality issues
// issue 1: large standard deviation in the first 'on' period
var st_dev_on_250 = MathSTDEV(json.data_raw.slice(20,290));
if (st_dev_on_250 > 50) {
  quality_flag_250++;
}

if (quality_flag_250 > 0) {
  output ["quality flag_250"] = quality_flag_250;
  output ["st_dev_on_250"] = MathROUND(st_dev_on_250,0);
}

//output ["log out"] = smooth1_abs;
output ["ECSt_250"] = MathROUND(ECSt_250,4);
output ["vhplus_250"] = MathROUND(vhplus_250,4);
output ["ghplus_250"] = 1/MathROUND(tau_250,4);
//output ["close_e"] = close_e;
//output ["slope_e"] = slope_e;
//output ["smooth1"] = smooth1;


// now convert smooth1 into absorbance ( abs = log(Is / I0) )
for (var x=0;x<300;x++) {
  smooth1_abs_500[x] = MathLOG(smooth1_500[x]/smooth1_500[0]);
}


// calculate ECSt_500
max_500 = MathMEAN(smooth1_abs_500.sort().slice(10,299));
var min_500 = smooth1_abs_500[0];
ECSt_500 = max_500 - min_500;

// Calculate GH+ by finding the 1/e point in the dark period
var tmpval_500;
var howclose_e_500 = 1;
var tmpslope_500 = 0;
var close_e_500 = [];
var slope_e_500 = [];
for (k=0;k<299;k++) {
  tmpval_500 = (smooth1_abs_500[k]-min_500)/(max_500-min_500);
  howclose_e_500 = (1/Math.E - tmpval_500);
  close_e_500[k] = MathROUND((1/Math.E - tmpval_500),3);
  // if slope is largest, then choose it for vhplus_500 up to tau
  if (((smooth1_abs_500[k+1]-min_500)/(max_500-min_500) - tmpval_500) > tmpslope_500) {
    vhplus_500 = (smooth1_abs_500[k+1]-min_500)/(max_500-min_500) - tmpval_500;
  }
  tmpslope_500 = (smooth1_abs_500[k+1]-min_500)/(max_500-min_500) - tmpval_500;
  slope_e_500[k] = MathROUND((smooth1_abs_500[k+1]-min_500)/(max_500-min_500) - tmpval_500,4);
  // once you hit tau, then stop iterating
  if (howclose_e_500 < 0) {
    tau_500 = (smooth1_abs_500[k]-min_500)/(max_500-min_500);
    break;
  }
}

// Check for quality issues
// issue 1: large standard deviation in the first 'on' period
var st_dev_on_500 = MathSTDEV(json.data_raw.slice(20,290));
if (st_dev_on_500 > 50) {
  quality_flag_500++;
}

if (quality_flag_500 > 0) {
  output ["quality flag_500"] = quality_flag_500;
  output ["st_dev_on_500"] = MathROUND(st_dev_on_500,0);
}

//output ["log out"] = smooth1_abs;
output ["ECSt_500"] = MathROUND(ECSt_500,4);
output ["vhplus_500"] = MathROUND(vhplus_500,4);
output ["ghplus_500"] = 1/MathROUND(tau_500,4);


// now convert smooth1 into absorbance ( abs = log(Is / I0) )
for (var x=0;x<300;x++) {
  smooth1_abs_1000[x] = MathLOG(smooth1_1000[x]/smooth1_1000[0]);
}


// calculate ECSt_1000
max_1000 = MathMEAN(smooth1_abs_1000.sort().slice(10,299));
var min_1000 = smooth1_abs_1000[0];
ECSt_1000 = max_1000 - min_1000;

// Calculate GH+ by finding the 1/e point in the dark period
var tmpval_1000;
var howclose_e_1000 = 1;
var tmpslope_1000 = 0;
var close_e_1000 = [];
var slope_e_1000 = [];
for (k=0;k<299;k++) {
  tmpval_1000 = (smooth1_abs_1000[k]-min_1000)/(max_1000-min_1000);
  howclose_e_1000 = (1/Math.E - tmpval_1000);
  close_e_1000[k] = MathROUND((1/Math.E - tmpval_1000),3);
  // if slope is largest, then choose it for vhplus_1000 up to tau
  if (((smooth1_abs_1000[k+1]-min_1000)/(max_1000-min_1000) - tmpval_1000) > tmpslope_1000) {
    vhplus_1000 = (smooth1_abs_1000[k+1]-min_1000)/(max_1000-min_1000) - tmpval_1000;
  }
  tmpslope_1000 = (smooth1_abs_1000[k+1]-min_1000)/(max_1000-min_1000) - tmpval_1000;
  slope_e_1000[k] = MathROUND((smooth1_abs_1000[k+1]-min_1000)/(max_1000-min_1000) - tmpval_1000,4);
  // once you hit tau, then stop iterating
  if (howclose_e_1000 < 0) {
    tau_1000 = (smooth1_abs_1000[k]-min_1000)/(max_1000-min_1000);
    break;
  }
}

// Check for quality issues
// issue 1: large standard deviation in the first 'on' period
var st_dev_on_1000 = MathSTDEV(json.data_raw.slice(20,290));
if (st_dev_on_1000 > 50) {
  quality_flag_1000++;
}

if (quality_flag_1000 > 0) {
  output ["quality flag_1000"] = quality_flag_1000;
  output ["st_dev_on_1000"] = MathROUND(st_dev_on_1000,0);
}

//output ["log out"] = smooth1_abs;
output ["ECSt_1000"] = MathROUND(ECSt_1000,4);
output ["vhplus_1000"] = MathROUND(vhplus_1000,4);
output ["ghplus_1000"] = 1/MathROUND(tau_1000,4);





// now convert smooth1 into absorbance ( abs = log(Is / I0) )
for (var x=0;x<300;x++) {
  smooth1_abs_1500[x] = MathLOG(smooth1_1500[x]/smooth1_1500[0]);
}


// calculate ECSt_1500
max_1500 = MathMEAN(smooth1_abs_1500.sort().slice(10,299));
var min_1500 = smooth1_abs_1500[0];
ECSt_1500 = max_1500 - min_1500;

// Calculate GH+ by finding the 1/e point in the dark period
var tmpval_1500;
var howclose_e_1500 = 1;
var tmpslope_1500 = 0;
var close_e_1500 = [];
var slope_e_1500 = [];
for (k=0;k<299;k++) {
  tmpval_1500 = (smooth1_abs_1500[k]-min_1500)/(max_1500-min_1500);
  howclose_e_1500 = (1/Math.E - tmpval_1500);
  close_e_1500[k] = MathROUND((1/Math.E - tmpval_1500),3);
  // if slope is largest, then choose it for vhplus_1500 up to tau
  if (((smooth1_abs_1500[k+1]-min_1500)/(max_1500-min_1500) - tmpval_1500) > tmpslope_1500) {
    vhplus_1500 = (smooth1_abs_1500[k+1]-min_1500)/(max_1500-min_1500) - tmpval_1500;
  }
  tmpslope_1500 = (smooth1_abs_1500[k+1]-min_1500)/(max_1500-min_1500) - tmpval_1500;
  slope_e_1500[k] = MathROUND((smooth1_abs_1500[k+1]-min_1500)/(max_1500-min_1500) - tmpval_1500,4);
  // once you hit tau, then stop iterating
  if (howclose_e_1500 < 0) {
    tau_1500 = (smooth1_abs_1500[k]-min_1500)/(max_1500-min_1500);
    break;
  }
}

// Check for quality issues
// issue 1: large standard deviation in the first 'on' period
var st_dev_on_1500 = MathSTDEV(json.data_raw.slice(20,290));
if (st_dev_on_1500 > 50) {
  quality_flag_1500++;
}

if (quality_flag_1500 > 0) {
  output ["quality flag_1500"] = quality_flag_1500;
  output ["st_dev_on_1500"] = MathROUND(st_dev_on_1500,0);
}

//output ["log out"] = smooth1_abs;
output ["ECSt_1500"] = MathROUND(ECSt_1500,4);
output ["vhplus_1500"] = MathROUND(vhplus_1500,4);
output ["ghplus_1500"] = 1/MathROUND(tau_1500,4);



// now convert smooth1 into absorbance ( abs = log(Is / I0) )
for (var x=0;x<300;x++) {
  smooth1_abs_2000[x] = MathLOG(smooth1_2000[x]/smooth1_2000[0]);
}


// calculate ECSt_2000
max_2000 = MathMEAN(smooth1_abs_2000.sort().slice(10,299));
var min_2000 = smooth1_abs_2000[0];
ECSt_2000 = max_2000 - min_2000;

// Calculate GH+ by finding the 1/e point in the dark period
var tmpval_2000;
var howclose_e_2000 = 1;
var tmpslope_2000 = 0;
var close_e_2000 = [];
var slope_e_2000 = [];
for (k=0;k<299;k++) {
  tmpval_2000 = (smooth1_abs_2000[k]-min_2000)/(max_2000-min_2000);
  howclose_e_2000 = (1/Math.E - tmpval_2000);
  close_e_2000[k] = MathROUND((1/Math.E - tmpval_2000),3);
  // if slope is largest, then choose it for vhplus_2000 up to tau
  if (((smooth1_abs_2000[k+1]-min_2000)/(max_2000-min_2000) - tmpval_2000) > tmpslope_2000) {
    vhplus_2000 = (smooth1_abs_2000[k+1]-min_2000)/(max_2000-min_2000) - tmpval_2000;
  }
  tmpslope_2000 = (smooth1_abs_2000[k+1]-min_2000)/(max_2000-min_2000) - tmpval_2000;
  slope_e_2000[k] = MathROUND((smooth1_abs_2000[k+1]-min_2000)/(max_2000-min_2000) - tmpval_2000,4);
  // once you hit tau, then stop iterating
  if (howclose_e_2000 < 0) {
    tau_2000 = (smooth1_abs_2000[k]-min_2000)/(max_2000-min_2000);
    break;
  }
}

// Check for quality issues
// issue 1: large standard deviation in the first 'on' period
var st_dev_on_2000 = MathSTDEV(json.data_raw.slice(20,290));
if (st_dev_on_2000 > 50) {
  quality_flag_2000++;
}

if (quality_flag_2000 > 0) {
  output ["quality flag_2000"] = quality_flag_2000;
  output ["st_dev_on_2000"] = MathROUND(st_dev_on_2000,0);
}

//output ["log out"] = smooth1_abs;
output ["ECSt_2000"] = MathROUND(ECSt_2000,4);
output ["vhplus_2000"] = MathROUND(vhplus_2000,4);
output ["ghplus_2000"] = 1/MathROUND(tau_2000,4);















return output;


{
  "time_offset": 240,
  "time": 1499442600912,
  "device_name": "MultispeQ",
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  "app_os": "mac",
  "app_name": "PhotosynQ",
  "app_version": "0.3.8",
  "app_device": "x86-64",
  "location": [
    "43.0092882",
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  ],
  "ConsoleMacro": "209"
}
Default avatar
Created by

Jonathan R Pleban


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Latest Update:
Jul 2017