41J Blog

Turbo side remote connector:

Connects here on the instrument:

Connection (Turbo side to JEB17):

Pin 1 to pin 1 (should be +24v)

Pin 2 to 5 (venting signal)

Pin 3 to 2 (motor signal)

Pin 4 to 1 (pumping station)

Pin 5 to 3 (heating)

Pin 6 nc 

Pin 7 nc

Pin 8 to 4 (output rotation switch point)

Pin 9 to 5 (output collective malfunction)

Pin 10 to 7 (mass ground)

Pin 11 nc

Pin 12 nc

Pin 13 nc

Pin 14 nc

Pin 15 nc

Measurements on my (broken) system:

Pin 1 21.9 V

Pin 2 low

Pin 3 high when external pump on only (motor signal)

Pin 4 tied high?

Pin 5 low

Pin 8 low

Pin 9 low (output collective malfunction)

Pin 10 low

More turbo pics:

Here’s the modeling code from the substack post.

from math import comb
from math import log10
import sys


def tprb(n, k, t):

        totalp = 1

        for i in range(0,k,1):
                p = 1 - (t / (n - i))
                totalp = totalp * p

        return 1-totalp

ctoffset = 45
ctslope  = -3.36

def predictCT(fragments,ampregion,fragmentsize,genomesize):
	totalfragments    = genomesize-fragmentsize
	ontargetfragments = fragmentsize-ampregion
	targetfragments = fragments*(ontargetfragments/totalfragments)
	ct = ctoffset+log10(targetfragments)*ctslope
	return ct

genomesize      = 30000
totalng         = 10
qpcrampregion   = 90
basesperng      = 1771000000000 
rrnafraction    = 0.6
fragmentsize    = 1000
starttargetfraction  = 0.000000001
targetfraction  = starttargetfraction


totalfragments  = (basesperng*totalng)/fragmentsize
reads           = 100000
targetfragments = totalfragments*targetfraction

totalfragments_norRNA = ((totalfragments-targetfragments)*(1-rrnafraction)) + targetfragments

# Vary reads count
#print ("total fragments, reads, target fragments, probability of >1 read, probability of >1 read (no rRNA), predicted CT")
#for creads in range(reads,100000000,1000000):
#	print (totalfragments, " ", creads, " ", targetfragments, " ", tprb(totalfragments,creads,targetfragments), " ", tprb(totalfragments_norRNA,creads,targetfragments),predictCT(targetfragments,qpcrampregion,fragmentsize,genomesize))

# Vary target fraction
#print ("target fraction, total fragments, reads, target fragments, probability of >1 read, probability of >1 read (no rRNA), predicted CT")
#while targetfraction < 1:
#	targetfragments = totalfragments*targetfraction
#	print (targetfraction, " ", totalfragments, " ", reads, " ", targetfragments, " ", tprb(totalfragments,reads,targetfragments), " ", tprb(totalfragments_norRNA,reads,targetfragments),predictCT(targetfragments,qpcrampregion,fragmentsize,genomesize))
#	targetfraction *= 10

# Vary both
#print(", ", end='')
#while targetfraction < 1:
#	targetfragments = totalfragments*targetfraction
#	print(targetfraction, ", ", end='')
#	targetfraction *= 2
#print()

#for creads in range(reads,5000000,100000):
#	print(creads, ", ", end='')
#	targetfraction  = starttargetfraction
#	while targetfraction < 1:
#		targetfragments = totalfragments*targetfraction
#		print (tprb(totalfragments,creads,targetfragments), ", ", end='')
#		
#		targetfraction *= 2
#	print()

# Vary both - CT
print(", ", end='')
while targetfraction < 1:
	targetfragments = totalfragments*targetfraction
	print("{:.2f}".format(predictCT(targetfragments,qpcrampregion,fragmentsize,genomesize)), ", ", end='')
	targetfraction *= 2
print()

for creads in range(reads,5000000,100000):
	print(creads, ", ", end='')
	targetfraction  = starttargetfraction
	while targetfraction < 1:
		targetfragments = totalfragments*targetfraction
		print (tprb(totalfragments,creads,targetfragments), ", ", end='')
		
		targetfraction *= 2
	print()