Drosophila 3rd instar larval aCC motoneuron (Gunay et al. 2015)

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Accession:152028
Single compartmental, ball-and-stick models implemented in XPP and full morphological model in Neuron. Paper has been submitted and correlates anatomical properties with electrophysiological recordings from these hard-to-access neurons. For instance we make predictions about location of the spike initiation zone, channel distributions, and synaptic input parameters.
Reference:
1 . Günay C, Sieling FH, Dharmar L, Lin WH, Wolfram V, Marley R, Baines RA, Prinz AA (2015) Distal spike initiation zone location estimation by morphological simulation of ionic current filtering demonstrated in a novel model of an identified Drosophila motoneuron. PLoS Comput Biol 11:e1004189 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Drosophila;
Cell Type(s):
Channel(s): I Na,p; I Na,t; I A; I K;
Gap Junctions:
Receptor(s): Cholinergic Receptors;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; XPP; MATLAB;
Model Concept(s):
Implementer(s): Gunay, Cengiz [cgunay at emory.edu]; Sieling, Fred [fred.sieling at gmail.com]; Prinz, Astrid [astrid.prinz at emory.edu];
Search NeuronDB for information about:  Cholinergic Receptors; I Na,p; I Na,t; I A; I K;
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Gunay_etal_2014
neuron-model
aCC-L3-neuron.hoc
aCC-L3-neuron+electrode.xml
aCC-L3-neuron-swc.hoc
calc-impedance.hoc
chan-DmKA-Marley.hoc
chan-DmKdr-Marley.hoc
chan-DmNaP-DmNav10.hoc
chan-DmNaT-ODowd.hoc
collapse-neuron-tree.hoc
current-inj-50pA-read-mV_dt_0.025ms.bin
data-axon-tail2-axon-50um-vc-noKdr-long-back-85mV-Na_4_lines_dt_0.025000ms.bin
data-axon-tail2-axon-70um-vc-noKdr-long-back-85mV-Na_4_lines_dt_0.025000ms.bin
data-axon-tail2-axon-70um-vc-noKdr-long-back-85mV-Na-5xNaP_4_lines_dt_0.025000ms.bin
data-axon-tail2-axon-70um-vc-noKdr-long-back-85mV-Na-5xNaT_4_lines_dt_0.025000ms.bin
data-axon-tail2-axon-70um-vc-noKdr-long-back-85mV-passive_4_lines_dt_0.025000ms.bin
data-axon-tail2-chans-axon_11_lines_dt_0.025000ms.bin
data-axon-tail2-chans-axon-last_11_lines_dt_0.025000ms.bin
data-axon-tail2-chans-botdend_11_lines_dt_0.025000ms.bin
data-axon-tail2-chans-ext-axon-70um_11_lines_dt_0.025000ms.bin
data-axon-tail2-chans-in-all_11_lines_dt_0.025000ms.bin
data-i-syn-10syns-20-EPSCs-10x-10ms-VC-60mV_6_lines_dt_0.025000ms.bin
data-i-syn-4dends-50-EPSCs-10x-10ms-VC-60mV_5_lines_dt_0.025000ms.bin
data-i-vclamp-syn-dend-513-180-EPSCs-10x-1ms-saturating_2_lines_dt_0.025000ms.bin
data-syn-dend-357_2_lines_dt_0.025000ms.bin
data-syn-dend-513_2_lines_dt_0.025000ms.bin
data-syn-dend-520_2_lines_dt_0.025000ms.bin
data-syn-dend-685_2_lines_dt_0.025000ms.bin
data-v-syn-10dends-20-EPSCs-10x-10ms-noVC_6_lines_dt_0.025000ms.bin
data-v-syn-4dends-50-EPSCs-10x-10ms-noVC_6_lines_dt_0.025000ms.bin
data-v-syn-dend-513-180-EPSCs-10x-1ms-saturating-noVC_5_lines_dt_0.025000ms.bin
data-v-syn-dend-685-AP_3_lines_dt_0.025000ms.bin
exp-axon-tail2.ses
exp-axon-tail2-chans-axon.ses
exp-axon-tail2-chans-axon-last.ses
exp-axon-tail2-chans-botdend.ses
exp-axon-tail2-chans-ext-axon-50um-onlyNa.ses
exp-axon-tail2-chans-ext-axon-70um.ses
exp-axon-tail2-chans-ext-axon-70um-10alphasynapses.ses
exp-axon-tail2-chans-ext-axon-70um-10x-mimic-sustained.ses
exp-axon-tail2-chans-ext-axon-70um-10x-mimic-sustained-random.ses
exp-axon-tail2-chans-ext-axon-70um-mimic-synapses.ses
exp-axon-tail2-chans-ext-axon-70um-mimic-synapses-sustained-currents.ses
exp-axon-tail2-chans-ext-axon-70um-mimic-synapses-v-change.ses
exp-axon-tail2-chans-ext-axon-70um-onlyNa.ses
exp-axon-tail2-chans-ext-axon-70um-tomasz.ses
exp-axon-tail2-chans-in-all.ses
figures.m
fitfuncs.hoc
graph-i-vc-ext-axon.ses
iclamp-50pA.ses
IClamp-steps.ses
inc-first.ses
lincir-vclamp.hoc
lincir-vclamp.ses
NaP_NaT_data.csv
neuron-CB.ses
neuron-CB+electrode.hoc
neuron-CB-act-electrode-embed-IClamp.ses
neuron-CB-ext-axon.ses
neuron-CB-ext-axon-2pieces.ses
neuron-CB-ext-axon-2pieces-chans-axon.ses
neuron-CB-ext-axon-2pieces-chans-axon-last.ses
neuron-CB-ext-axon-2pieces-chans-botdend.ses
neuron-CB-ext-axon-2pieces-chans-ext-axon-50um-onlyNa.ses
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um.ses
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um-10alphasynapses.ses *
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um-10x-mimic-sustained.ses *
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um-mimic-synapses.ses *
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um-mimic-synapses-v-change.ses *
neuron-CB-ext-axon-2pieces-chans-ext-axon-70um-onlyNa.ses
neuron-CB-ext-axon-2pieces-chans-in-all.ses
neuron-CB-pas-electrode-embed.ses
neuron-CB-pas-electrode-embed-fit-pas.ses
neuron-CB-pas-electrode-embed-fit-pas-VClamp.ses
neuron-CB-pas-electrode-embed-IClamp.ses
neuron-CB-pas-electrode-embed-test-axon-hh-chans.ses
neuron-Import3D-CellBuilder.ses
neuron-NL-CellBuilder.ses
neuron-NL-CellBuilder-pas.ses
neuron-NL-CellBuilder-pas-electrode.ses
neuron-NL-CellBuilder-pas-Na.ses
neuron-PointProcessMgr-ext-axon-2pieces-chans-ext-axon-70um-10alphasynapses.ses
nrn-fit-cap-02_dt_0.025000ms_dy_1e-9nA.bin
shape-plot.ses
SkeletonTree_ORR_aCC_48h1_NL.hoc
soma-vclamp-testbed.ses
stats.hoc
vclamp_-85_to_-25mV.ses
vclamp_soma_-60mV.ses
vclamp_soma_-60mV_syn1234.ses
vclamp_soma_-60mV_syni.ses
vclamp-family.ses
v-graph.ses
v-graph-bigger.ses
v-graph-bigger-axon-2pieces.ses
                            
{ ion_register("k", 1) }
objref ks, ksvec, ksgate, ksstates, kstransitions, tobj
{
  ksvec = new Vector()
  ksstates = new List()
  kstransitions = new List()
  ks = new KSChan(0)
}
// DmKA Density Mechanism
// k ohmic ion current
//     ik (mA/cm2) = g_DmKA * (v - ek)
{
  ks.name("DmKA")
  ks.ion("k")
  ks.iv_type(0)
  ks.gmax(0)
  ks.erev(0)
}
// g = gmax * m^4 * (0.95*h)
// m' = (minf - m)/mtau
{
  ksstates.append(ks.add_hhstate("m"))
  ksgate = ksstates.object(0).gate
  ksgate.power(4)
  kstransitions.append(ks.trans(ksstates.object(0), ksstates.object(0)))
}
{
  tobj = kstransitions.object(0)
  tobj.type(1)
  tobj.set_f(0, 4, ksvec.c.append(1, -0.1376, -17.55))
  }
  tobj.set_f(1, 7, ksvec.c.resize(1501), -100, 50)
  for i=0, 1500 {tobj.parm(1).x[i] = fscan()}
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 2.8 2.7927 2.7854 2.7782 2.771 2.7638 2.7567 2.7496 2.7425 2.7355
 2.7285 2.7216 2.7147 2.7078 2.7009 2.6941 2.6874 2.6806 2.6739 2.6673
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 2.5364 2.5306 2.5249 2.5192 2.5135 2.5079 2.5023 2.4967 2.4912 2.4858
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 2.4282 2.4233 2.4183 2.4134 2.4085 2.4037 2.3989 2.3942 2.3895 2.3848
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 2.3359 2.3317 2.3275 2.3234 2.3193 2.3152 2.3112 2.3072 2.3032 2.2993
 2.2954 2.2916 2.2878 2.284 2.2802 2.2765 2.2728 2.2692 2.2656 2.262
 2.2585 2.255 2.2515 2.2481 2.2447 2.2413 2.238 2.2346 2.2314 2.2281
 2.2249 2.2217 2.2186 2.2155 2.2124 2.2093 2.2063 2.2033 2.2003 2.1974
 2.1945 2.1916 2.1888 2.186 2.1832 2.1804 2.1777 2.175 2.1723 2.1696
 2.167 2.1644 2.1619 2.1593 2.1568 2.1543 2.1518 2.1494 2.147 2.1446
 2.1423 2.1399 2.1376 2.1353 2.1331 2.1308 2.1286 2.1264 2.1243 2.1221
 2.12 2.1179 2.1158 2.1138 2.1117 2.1097 2.1077 2.1058 2.1038 2.1019
 2.1 2.0981 2.0963 2.0944 2.0926 2.0908 2.0891 2.0873 2.0856 2.0838
 2.0821 2.0805 2.0788 2.0772 2.0755 2.0739 2.0723 2.0708 2.0692 2.0677
 2.0662 2.0647 2.0632 2.0617 2.0602 2.0588 2.0574 2.056 2.0546 2.0532
 2.0519 2.0505 2.0492 2.0479 2.0466 2.0453 2.0441 2.0428 2.0416 2.0404
 2.0392 2.038 2.0368 2.0356 2.0345 2.0333 2.0322 2.0311 2.03 2.0289
 2.0278 2.0268 2.0257 2.0247 2.0237 2.0227 2.0217 2.0207 2.0197 2.0187
 2.0178 2.0168 2.0159 2.015 2.0141 2.0132 2.0123 2.0114 2.0105 2.0097
 2.0088 2.008 2.0072 2.0064 2.0055 2.0047 2.004 2.0032 2.0024 2.0016
 2.0009 2.0002 1.9994 1.9987 1.998 1.9973 1.9966 1.9959 1.9952 1.9945
 1.9939 1.9932 1.9925 1.9919 1.9913 1.9906 1.99 1.9894 1.9888 1.9882
 1.9876 1.987 1.9864 1.9859 1.9853 1.9848 1.9842 1.9837 1.9831 1.9826
 1.9821 1.9816 1.981 1.9805 1.98 1.9796 1.9791 1.9786 1.9781 1.9776
 1.9772 1.9767 1.9763 1.9758 1.9754 1.9749 1.9745 1.9741 1.9737 1.9733
 1.9728 1.9724 1.972 1.9716 1.9713 1.9709 1.9705 1.9701 1.9697 1.9694
 1.969 1.9686 1.9683 1.9679 1.9676 1.9673 1.9669 1.9666 1.9663 1.9659
 1.9656 1.9653 1.965 1.9647 1.9644 1.9641 1.9638 1.9635 1.9632 1.9629
 1.9626 1.9623 1.9621 1.9618 1.9615 1.9613 1.961 1.9607 1.9605 1.9602
 1.96 1.9597 1.9595 1.9592 1.959 1.9588 1.9585 1.9583 1.9581 1.9578
 1.9576 1.9574 1.9572 1.957 1.9568 1.9566 1.9564 1.9562 1.956 1.9558
 1.9556 1.9554 1.9552 1.955 1.9548 1.9546 1.9544 1.9543 1.9541 1.9539
 1.9537
  {}
{ ksstates.remove_all  kstransitions.remove_all }
// h' = (hinf - h)/htau
{
  ksstates.append(ks.add_hhstate("h"))
  ksgate = ksstates.object(0).gate
  ksgate.power(1)
  kstransitions.append(ks.trans(ksstates.object(0), ksstates.object(0)))
}
{
  tobj = kstransitions.object(0)
  tobj.type(1)
  tobj.set_f(0, 4, ksvec.c.append(1, 0.1667, -45))
  }
  tobj.set_f(1, 7, ksvec.c.resize(1501), -100, 50)
  for i=0, 1500 {tobj.parm(1).x[i] = fscan()}
 84.62 84.378 84.136 83.895 83.655 83.415 83.175 82.936 82.698 82.46
 82.223 81.986 81.75 81.515 81.28 81.046 80.812 80.579 80.346 80.114
 79.883 79.652 79.421 79.191 78.962 78.733 78.505 78.278 78.051 77.824
 77.598 77.373 77.148 76.924 76.7 76.477 76.254 76.032 75.811 75.59
 75.37 75.15 74.93 74.712 74.494 74.276 74.059 73.842 73.626 73.411
 73.196 72.981 72.768 72.554 72.342 72.129 71.918 71.706 71.496 71.286
 71.076 70.867 70.659 70.451 70.243 70.037 69.83 69.624 69.419 69.214
 69.01 68.806 68.603 68.4 68.198 67.997 67.796 67.595 67.395 67.195
 66.996 66.798 66.6 66.402 66.206 66.009 65.813 65.618 65.423 65.229
 65.035 64.841 64.648 64.456 64.264 64.073 63.882 63.692 63.502 63.313
 63.124 62.936 62.748 62.56 62.374 62.187 62.002 61.816 61.631 61.447
 61.263 61.08 60.897 60.715 60.533 60.351 60.171 59.99 59.81 59.631
 59.452 59.273 59.095 58.918 58.741 58.564 58.388 58.213 58.038 57.863
 57.689 57.515 57.342 57.169 56.997 56.825 56.654 56.483 56.313 56.143
 55.973 55.805 55.636 55.468 55.3 55.133 54.967 54.8 54.635 54.469
 54.305 54.14 53.976 53.813 53.65 53.487 53.325 53.164 53.003 52.842
 52.682 52.522 52.362 52.203 52.045 51.887 51.729 51.572 51.415 51.259
 51.103 50.948 50.793 50.638 50.484 50.331 50.178 50.025 49.872 49.721
 49.569 49.418 49.267 49.117 48.967 48.818 48.669 48.521 48.373 48.225
 48.078 47.931 47.785 47.639 47.493 47.348 47.203 47.059 46.915 46.772
 46.628 46.486 46.344 46.202 46.06 45.919 45.779 45.639 45.499 45.359
 45.22 45.082 44.944 44.806 44.669 44.532 44.395 44.259 44.123 43.988
 43.853 43.718 43.584 43.45 43.317 43.184 43.051 42.919 42.787 42.655
 42.524 42.393 42.263 42.133 42.004 41.874 41.746 41.617 41.489 41.362
 41.234 41.107 40.981 40.855 40.729 40.603 40.478 40.354 40.229 40.105
 39.982 39.859 39.736 39.613 39.491 39.369 39.248 39.127 39.006 38.886
 38.766 38.647 38.527 38.408 38.29 38.172 38.054 37.936 37.819 37.703
 37.586 37.47 37.354 37.239 37.124 37.009 36.895 36.781 36.667 36.554
 36.441 36.329 36.216 36.104 35.993 35.882 35.771 35.66 35.55 35.44
 35.33 35.221 35.112 35.003 34.895 34.787 34.68 34.572 34.465 34.359
 34.253 34.147 34.041 33.936 33.831 33.726 33.622 33.517 33.414 33.31
 33.207 33.104 33.002 32.9 32.798 32.696 32.595 32.494 32.394 32.293
 32.193 32.094 31.994 31.895 31.797 31.698 31.6 31.502 31.405 31.307
 31.21 31.114 31.017 30.921 30.826 30.73 30.635 30.54 30.445 30.351
 30.257 30.163 30.07 29.977 29.884 29.792 29.699 29.607 29.516 29.424
 29.333 29.242 29.152 29.062 28.972 28.882 28.792 28.703 28.614 28.526
 28.437 28.349 28.262 28.174 28.087 28 27.913 27.827 27.741 27.655
 27.569 27.484 27.399 27.314 27.23 27.145 27.062 26.978 26.894 26.811
 26.728 26.646 26.563 26.481 26.399 26.317 26.236 26.155 26.074 25.993
 25.913 25.833 25.753 25.673 25.594 25.515 25.436 25.358 25.279 25.201
 25.123 25.046 24.968 24.891 24.814 24.738 24.661 24.585 24.509 24.434
 24.358 24.283 24.208 24.133 24.059 23.985 23.911 23.837 23.763 23.69
 23.617 23.544 23.472 23.399 23.327 23.255 23.184 23.112 23.041 22.97
 22.899 22.829 22.758 22.688 22.618 22.549 22.479 22.41 22.341 22.273
 22.204 22.136 22.068 22 21.932 21.865 21.798 21.731 21.664 21.597
 21.531 21.465 21.399 21.333 21.268 21.202 21.137 21.072 21.008 20.943
 20.879 20.815 20.751 20.687 20.624 20.561 20.498 20.435 20.372 20.31
 20.248 20.186 20.124 20.062 20.001 19.94 19.879 19.818 19.757 19.697
 19.637 19.577 19.517 19.457 19.398 19.339 19.28 19.221 19.162 19.104
 19.045 18.987 18.929 18.872 18.814 18.757 18.7 18.643 18.586 18.529
 18.473 18.417 18.36 18.305 18.249 18.193 18.138 18.083 18.028 17.973
 17.919 17.864 17.81 17.756 17.702 17.648 17.595 17.541 17.488 17.435
 17.382 17.33 17.277 17.225 17.173 17.121 17.069 17.017 16.966 16.914
 16.863 16.812 16.761 16.711 16.66 16.61 16.56 16.51 16.46 16.41
 16.361 16.312 16.262 16.213 16.165 16.116 16.067 16.019 15.971 15.923
 15.875 15.827 15.78 15.732 15.685 15.638 15.591 15.544 15.498 15.451
 15.405 15.359 15.313 15.267 15.221 15.175 15.13 15.085 15.04 14.995
 14.95 14.905 14.861 14.816 14.772 14.728 14.684 14.64 14.597 14.553
 14.51 14.466 14.423 14.38 14.338 14.295 14.253 14.21 14.168 14.126
 14.084 14.042 14 13.959 13.918 13.876 13.835 13.794 13.753 13.713
 13.672 13.632 13.591 13.551 13.511 13.471 13.431 13.392 13.352 13.313
 13.274 13.235 13.196 13.157 13.118 13.079 13.041 13.003 12.964 12.926
 12.888 12.851 12.813 12.775 12.738 12.701 12.663 12.626 12.589 12.552
 12.516 12.479 12.443 12.406 12.37 12.334 12.298 12.262 12.226 12.191
 12.155 12.12 12.085 12.05 12.015 11.98 11.945 11.91 11.876 11.841
 11.807 11.773 11.739 11.705 11.671 11.637 11.603 11.57 11.536 11.503
 11.47 11.437 11.404 11.371 11.338 11.305 11.273 11.241 11.208 11.176
 11.144 11.112 11.08 11.048 11.017 10.985 10.954 10.922 10.891 10.86
 10.829 10.798 10.767 10.736 10.706 10.675 10.645 10.614 10.584 10.554
 10.524 10.494 10.464 10.435 10.405 10.376 10.346 10.317 10.288 10.258
 10.229 10.201 10.172 10.143 10.114 10.086 10.057 10.029 10.001 9.9727
 9.9447 9.9167 9.8888 9.8611 9.8334 9.8058 9.7783 9.7509 9.7236 9.6964
 9.6693 9.6423 9.6153 9.5885 9.5617 9.5351 9.5085 9.482 9.4556 9.4293
 9.4031 9.377 9.3509 9.325 9.2991 9.2734 9.2477 9.2221 9.1966 9.1711
 9.1458 9.1205 9.0954 9.0703 9.0453 9.0204 8.9955 8.9708 8.9461 8.9215
 8.897 8.8726 8.8483 8.824 8.7999 8.7758 8.7518 8.7279 8.704 8.6803
 8.6566 8.633 8.6095 8.586 8.5627 8.5394 8.5162 8.493 8.47 8.447
 8.4241 8.4013 8.3786 8.3559 8.3334 8.3109 8.2884 8.2661 8.2438 8.2216
 8.1995 8.1774 8.1555 8.1336 8.1117 8.09 8.0683 8.0467 8.0252 8.0037
 7.9823 7.961 7.9398 7.9186 7.8975 7.8765 7.8556 7.8347 7.8139 7.7931
 7.7725 7.7519 7.7313 7.7109 7.6905 7.6702 7.6499 7.6298 7.6096 7.5896
 7.5696 7.5497 7.5299 7.5101 7.4904 7.4708 7.4512 7.4317 7.4123 7.3929
 7.3736 7.3543 7.3352 7.3161 7.297 7.278 7.2591 7.2403 7.2215 7.2028
 7.1841 7.1655 7.147 7.1285 7.1101 7.0918 7.0735 7.0553 7.0372 7.0191
 7.001 6.9831 6.9652 6.9473 6.9295 6.9118 6.8941 6.8765 6.859 6.8415
 6.8241 6.8067 6.7894 6.7722 6.755 6.7379 6.7208 6.7038 6.6868 6.6699
 6.6531 6.6363 6.6196 6.6029 6.5863 6.5698 6.5533 6.5368 6.5205 6.5041
 6.4879 6.4716 6.4555 6.4394 6.4233 6.4073 6.3914 6.3755 6.3597 6.3439
 6.3282 6.3125 6.2969 6.2813 6.2658 6.2504 6.235 6.2196 6.2043 6.1891
 6.1739 6.1588 6.1437 6.1286 6.1136 6.0987 6.0838 6.069 6.0542 6.0395
 6.0248 6.0102 5.9956 5.9811 5.9666 5.9522 5.9378 5.9234 5.9092 5.8949
 5.8807 5.8666 5.8525 5.8385 5.8245 5.8105 5.7967 5.7828 5.769 5.7553
 5.7415 5.7279 5.7143 5.7007 5.6872 5.6737 5.6603 5.6469 5.6336 5.6203
 5.607 5.5939 5.5807 5.5676 5.5545 5.5415 5.5285 5.5156 5.5027 5.4899
 5.4771 5.4643 5.4516 5.439 5.4264 5.4138 5.4012 5.3888 5.3763 5.3639
 5.3515 5.3392 5.3269 5.3147 5.3025 5.2904 5.2783 5.2662 5.2542 5.2422
 5.2302 5.2183 5.2065 5.1946 5.1829 5.1711 5.1594 5.1478 5.1361 5.1246
 5.113 5.1015 5.0901 5.0786 5.0673 5.0559 5.0446 5.0333 5.0221 5.0109
 4.9998 4.9887 4.9776 4.9666 4.9556 4.9446 4.9337 4.9228 4.912 4.9012
 4.8904 4.8796 4.869 4.8583 4.8477 4.8371 4.8265 4.816 4.8055 4.7951
 4.7847 4.7743 4.764 4.7537 4.7434 4.7332 4.723 4.7128 4.7027 4.6926
 4.6826 4.6726 4.6626 4.6526 4.6427 4.6328 4.623 4.6132 4.6034 4.5936
 4.5839 4.5742 4.5646 4.555 4.5454 4.5359 4.5263 4.5169 4.5074 4.498
 4.4886 4.4793 4.47 4.4607 4.4514 4.4422 4.433 4.4238 4.4147 4.4056
 4.3966 4.3875 4.3785 4.3695 4.3606 4.3517 4.3428 4.334 4.3252 4.3164
 4.3076 4.2989 4.2902 4.2815 4.2729 4.2643 4.2557 4.2472 4.2386 4.2301
 4.2217 4.2133 4.2049 4.1965 4.1881 4.1798 4.1715 4.1633 4.1551 4.1469
 4.1387 4.1305 4.1224 4.1143 4.1063 4.0982 4.0902 4.0823 4.0743 4.0664
 4.0585 4.0506 4.0428 4.035 4.0272 4.0194 4.0117 4.004 3.9963 3.9887
 3.981 3.9734 3.9659 3.9583 3.9508 3.9433 3.9358 3.9284 3.921 3.9136
 3.9062 3.8989 3.8916 3.8843 3.877 3.8698 3.8626 3.8554 3.8482 3.8411
 3.8339 3.8269 3.8198 3.8127 3.8057 3.7987 3.7918 3.7848 3.7779 3.771
 3.7641 3.7573 3.7505 3.7436 3.7369 3.7301 3.7234 3.7167 3.71 3.7033
 3.6967 3.6901 3.6835 3.6769 3.6704 3.6638 3.6573 3.6508 3.6444 3.638
 3.6315 3.6251 3.6188 3.6124 3.6061 3.5998 3.5935 3.5873 3.581 3.5748
 3.5686 3.5624 3.5563 3.5502 3.544 3.538 3.5319 3.5258 3.5198 3.5138
 3.5078 3.5019 3.4959 3.49 3.4841 3.4782 3.4723 3.4665 3.4607 3.4549
 3.4491 3.4433 3.4376 3.4319 3.4262 3.4205 3.4148 3.4092 3.4036 3.398
 3.3924 3.3868 3.3813 3.3758 3.3703 3.3648 3.3593 3.3538 3.3484 3.343
 3.3376 3.3322 3.3269 3.3215 3.3162 3.3109 3.3056 3.3004 3.2951 3.2899
 3.2847 3.2795 3.2743 3.2692 3.264 3.2589 3.2538 3.2487 3.2437 3.2386
 3.2336 3.2286 3.2236 3.2186 3.2136 3.2087 3.2038 3.1989 3.194 3.1891
 3.1842 3.1794 3.1746 3.1697 3.1649 3.1602 3.1554 3.1507 3.1459 3.1412
 3.1365 3.1319 3.1272 3.1226 3.1179 3.1133 3.1087 3.1041 3.0996 3.095
 3.0905 3.086 3.0815 3.077 3.0725 3.068 3.0636 3.0592 3.0548 3.0504
 3.046 3.0416 3.0373 3.0329 3.0286 3.0243 3.02 3.0158 3.0115 3.0073
 3.003 2.9988 2.9946 2.9904 2.9863 2.9821 2.978 2.9738 2.9697 2.9656
 2.9615 2.9575 2.9534 2.9494 2.9453 2.9413 2.9373 2.9333 2.9294 2.9254
 2.9214 2.9175 2.9136 2.9097 2.9058 2.9019 2.8981 2.8942 2.8904 2.8865
 2.8827 2.8789 2.8751 2.8714 2.8676 2.8639 2.8601 2.8564 2.8527 2.849
 2.8453 2.8417 2.838 2.8344 2.8307 2.8271 2.8235 2.8199 2.8163 2.8128
 2.8092 2.8057 2.8021 2.7986 2.7951 2.7916 2.7881 2.7847 2.7812 2.7778
 2.7743 2.7709 2.7675 2.7641 2.7607 2.7573 2.754 2.7506 2.7473 2.744
 2.7406 2.7373 2.734 2.7308 2.7275 2.7242 2.721 2.7178 2.7145 2.7113
 2.7081 2.7049 2.7017 2.6986 2.6954 2.6923 2.6891 2.686 2.6829 2.6798
 2.6767 2.6736 2.6705 2.6675 2.6644 2.6614 2.6583 2.6553 2.6523 2.6493
 2.6463 2.6433 2.6404 2.6374 2.6345 2.6315 2.6286 2.6257 2.6228 2.6199
 2.617 2.6141 2.6113 2.6084 2.6056 2.6027 2.5999 2.5971 2.5943 2.5915
 2.5887 2.5859 2.5831 2.5804 2.5776 2.5749 2.5722 2.5695 2.5667 2.564
 2.5613 2.5587 2.556 2.5533 2.5507 2.548 2.5454 2.5428 2.5401 2.5375
 2.5349 2.5323 2.5298 2.5272 2.5246 2.5221 2.5195 2.517 2.5145 2.5119
 2.5094 2.5069 2.5044 2.5019 2.4995 2.497 2.4945 2.4921 2.4897 2.4872
 2.4848 2.4824 2.48 2.4776 2.4752 2.4728 2.4704 2.4681 2.4657 2.4633
 2.461 2.4587 2.4563 2.454 2.4517 2.4494 2.4471 2.4448 2.4426 2.4403
 2.438 2.4358 2.4335 2.4313 2.429 2.4268 2.4246 2.4224 2.4202 2.418
 2.4158 2.4136 2.4115 2.4093 2.4072 2.405 2.4029 2.4007 2.3986 2.3965
 2.3944 2.3923 2.3902 2.3881 2.386 2.384 2.3819 2.3798 2.3778 2.3757
 2.3737 2.3717 2.3696 2.3676 2.3656 2.3636 2.3616 2.3596 2.3576 2.3557
 2.3537 2.3517 2.3498 2.3478 2.3459 2.344 2.342 2.3401 2.3382 2.3363
 2.3344 2.3325 2.3306 2.3287 2.3269 2.325 2.3231 2.3213 2.3194 2.3176
 2.3157
  {}
{ ksstates.remove_all  kstransitions.remove_all }
{objref ks, ksvec, ksgate, ksstates, kstransitions, tobj}