Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30084 discussions

Re: [Freesurfer] RE: fdr thresholds in tksurfer compared to Nichol's function
by jorge luis 25 Jun '09

25 Jun '09

Use the fast_fdrthresh matlab function provided in the fsfast/toolbox directory in freesurfer. It gives the same results as tksurfer. Cheers Jorge Luis Bernal Rusiel Phd Student Laboratory of Functional Neuroscience. University of Pablo de Olavide. Seville. Spain --- El jue, 25/6/09, Lars M. Rimol <larilin(a)gmail.com> escribió: > De: Lars M. Rimol <larilin(a)gmail.com> > Asunto: [Freesurfer] RE: fdr thresholds in tksurfer compared to Nichol's function > Para: "FS maling list" <freesurfer(a)nmr.mgh.harvard.edu> > Fecha: jueves, 25 junio, 2009 4:18 > > > > #yiv1972015953 .hmmessage P > { > margin:0px;padding:0px;} > #yiv1972015953 { > font-size:10pt;font-family:Verdana;} > > > > > > > #yiv1972015953 .ExternalClass .EC_hmmessage P > {padding:0px;} > #yiv1972015953 .ExternalClass body.EC_hmmessage > {font-size:10pt;font-family:Verdana;} > > Hi, > > Please disregard my previous mail. I was a > little too trigger happy..., the 1.928 threshold set by > tksurfer is too high for any vertex to survive so the > two methods DO concur. I should actually look at > the maps and not just the output... > > > The reason I asked is that I'm combining images to > obtain an overall FDR, either for both hemispheres or for > several comparisons. I don't see how this can be done in > tksurfer so I'm using Nichols' function, which > works just fine. I just don't know how to get > an FDR threshold when no vertex has a p-value that > survives - but tksurfer obviously produces such a > threshold. How do I obtain that threshold? > > (Or is it simply set just higher than the highest > -log(p-value) in the image, for display purposes? It seems > always to be just above.) > > > > thanks (and apologies for the confusion), > LMR > > > > > From: larilin(a)gmail.com > To: freesurfer(a)nmr.mgh.harvard.edu > Subject: fdr thresholds in tksurfer compared to > Nichol's function > Date: Thu, 25 Jun 2009 14:07:08 +0200 > > > > #yiv1972015953 .ExternalClass .EC_hmmessage P > {padding:0px;} > #yiv1972015953 .ExternalClass body.EC_hmmessage > {font-size:10pt;font-family:Verdana;} > > > Hi, > > I've used the fdr function in tksurfer and compared the > results to Tom Nichol's matlab function (http://www.sph.umich.edu/~nichols/FDR/) > I use p = 10.^-abs(pfile), where "pfile" is > 'sig.mgh'. > > I find that the p-threshold (pID, assuming positive > dependence) is usually exactly the same as the one in > tksurfer (probably because you use the same algorithm..?). > > But in some cases where pID is empty, which > should mean that there is no suprathreshold vertex, I do get > a threshold in tksurfer. Here's an example: > > For one contrast where pID was returned empty in > Nichol's matlab function, I got a threshold of > 1.927741 in tksurfer. > > Is this supposed to happen? > > > The output is: > > > MRISfdr2vwth(rate=0.05000, sign = 0, 1, only marked = 0) = > 1.927741 > > surfer: MRISfdr2vwth with rate 0.05 and sign 0 > returned threshold 1.927741 > > > > > Thank you! > > yours, > LMR > > > > > > > > > > > -----Adjunto en línea a continuación----- > > _______________________________________________ > Freesurfer mailing list > Freesurfer(a)nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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fdr thresholds in tksurfer compared to Nichol's function
by Lars M. Rimol 25 Jun '09

25 Jun '09

Hi, I've used the fdr function in tksurfer and compared the results to Tom Nichol's matlab function (http://www.sph.umich.edu/~nichols/FDR/) I use p = 10.^-abs(pfile), where "pfile" is 'sig.mgh'. I find that the p-threshold (pID, assuming positive dependence) is usually exactly the same as the one in tksurfer (probably because you use the same algorithm..?). But in some cases where pID is empty, which should mean that there is no suprathreshold vertex, I do get a threshold in tksurfer. Here's an example: For one contrast where pID was returned empty in Nichol's matlab function, I got a threshold of 1.927741 in tksurfer. Is this supposed to happen? The output is: MRISfdr2vwth(rate=0.05000, sign = 0, 1, only marked = 0) = 1.927741 surfer: MRISfdr2vwth with rate 0.05 and sign 0 returned threshold 1.927741 Thank you! yours, LMR

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File problem
by Vina Goghari 25 Jun '09

25 Jun '09

Hello, I used freesurfer table programs to concat files for all my subjects for all the parcellations. For the LH only, for some reason I am seeing one column of values at the very end that are not associated with a label and it is not present for all the subjects. I also saw it for the volume file. Any ideas why just for LH and what it is? Thanks! Vina lh.aparc.a2005s.thickness lh_G_cingulate-Isthmus_thickness lh_G_cingulate-Main_part_thickness lh_G_cuneus_thickness lh_G_frontal_inf-Opercular_part_thickness lh_G_frontal_inf-Orbital_part_thickness lh_G_frontal_inf-Triangular_part_thickness lh_G_frontal_middle_thickness lh_G_frontal_superior_thickness lh_G_frontomarginal_thickness lh_G_insular_long_thickness lh_G_insular_short_thickness lh_G_and_S_occipital_inferior_thickness lh_G_occipital_middle_thickness lh_G_occipital_superior_thickness lh_G_occipit-temp_lat-Or_fusiform_thickness lh_G_occipit-temp_med-Lingual_part_thickness lh_G_occipit-temp_med-Parahippocampal_part_thickness lh_G_orbital_thickness lh_G_paracentral_thickness lh_G_parietal_inferior-Angular_part_thickness lh_G_parietal_inferior-Supramarginal_part_thickness lh_G_parietal_superior_thickness lh_G_postcentral_thickness lh_G_precentral_thickness lh_G_precuneus_thickness lh_G_rectus_thickness lh_G_subcallosal_thickness lh_G_subcentral_thickness lh_G_temporal_inferior_thickness lh_G_temporal_middle_thickness lh_G_temp_sup-G_temp_transv_and_interm_S_thickness lh_G_temp_sup-Lateral_aspect_thickness lh_G_temp_sup-Planum_polare_thickness lh_G_temp_sup-Planum_tempolare_thickness lh_G_and_S_transverse_frontopolar_thickness lh_Lat_Fissure-ant_sgt-ramus_horizontal_thickness lh_Lat_Fissure-ant_sgt-ramus_vertical_thickness lh_Lat_Fissure-post_sgt_thickness lh_Medial_wall_thickness lh_Pole_occipital_thickness lh_Pole_temporal_thickness lh_S_calcarine_thickness lh_S_central_thickness lh_S_central_insula_thickness lh_S_cingulate-Main_part_and_Intracingulate_thickness lh_S_cingulate-Marginalis_part_thickness lh_S_circular_insula_anterior_thickness lh_S_circular_insula_inferior_thickness lh_S_circular_insula_superior_thickness lh_S_collateral_transverse_ant_thickness lh_S_collateral_transverse_post_thickness lh_S_frontal_inferior_thickness lh_S_frontal_middle_thickness lh_S_frontal_superior_thickness lh_S_frontomarginal_thickness lh_S_intermedius_primus-Jensen_thickness lh_S_intraparietal-and_Parietal_transverse_thickness lh_S_occipital_anterior_thickness lh_S_occipital_middle_and_Lunatus_thickness lh_S_occipital_superior_and_transversalis_thickness lh_S_occipito-temporal_lateral_thickness lh_S_occipito-temporal_medial_and_S_Lingual_thickness lh_S_orbital-H_shapped_thickness lh_S_orbital_lateral_thickness lh_S_orbital_medial-Or_olfactory_thickness lh_S_paracentral_thickness lh_S_parieto_occipital_thickness lh_S_pericallosal_thickness lh_S_postcentral_thickness lh_S_precentral-Inferior-part_thickness lh_S_precentral-Superior-part_thickness lh_S_subcentral_post_thickness lh_S_suborbital_thickness lh_S_subparietal_thickness lh_S_temporal_inferior_thickness lh_S_temporal_superior_thickness lh_S_temporal_transverse_thickness MERIT_001 2.617 3.095 1.773 3.009 2.841 3.111 2.935 3.098 2.459 3.402 3.847 2.356 2.166 1.735 2.655 1.83 3.009 2.856 2.637 2.868 3.063 2.313 2.393 3.01 2.765 2.701 2.876 2.91 3.016 3.273 2.492 3.219 3.949 2.813 2.302 2.845 2.569 2.629 1.175 1.62 3.521 1.645 1.816 3.367 2.729 2.164 3.273 2.83 2.778 3.628 1.902 2.453 2.438 2.675 2.184 2.384 2.277 2.464 2.232 2.184 2.743 2.182 2.464 2.624 1.891 2.349 2.242 2.486 2.113 2.399 2.576 2.352 2.722 2.502 2.639 2.706 2.42 MERIT_002 2.339 2.87 1.8 2.76 2.375 2.066 2.325 2.741 2.373 3.37 3.583 2.431 2.629 2.426 2.459 1.963 3.034 2.407 2.159 2.519 2.536 2.313 2.012 2.265 2.622 2.457 3.17 2.752 2.71 2.873 2.496 2.782 3.148 2.509 1.968 2.417 2.11 2.327 1.075 1.953 2.729 1.859 1.779 3.948 2.553 2.141 2.702 2.669 2.669 2.852 1.898 2.042 1.999 2.193 2.091 2.08 2.128 2.248 1.906 2.309 2.421 2.358 2.26 2.022 2.233 2.071 2.179 2.266 2.087 2.21 2.175 2.77 2.136 2.312 2.286 2.384 2.033 MERIT_003 2.845 2.995 1.862 2.62 2.692 2.491 2.481 2.751 3.223 2.825 3.615 2.31 2.749 2.021 2.738 1.997 2.964 2.577 2.284 2.522 2.457 2.186 1.914 2.507 2.267 2.8 3.451 2.667 3.034 3.064 2.224 2.78 3.13 2.315 2.621 2.68 2.401 2.313 0.951 1.769 3.383 1.718 1.868 2.687 2.355 2.127 2.544 2.552 2.372 2.365 1.692 2.055 2.202 2.059 2.018 2.12 1.829 2.101 1.86 1.987 2.458 2.103 2.352 1.866 2.157 1.872 1.773 2.557 1.746 2.228 1.89 2.063 2.081 2.055 2.387 2.154 2.282 MERIT_004 2.485 3.313 1.768 3.212 3.241 2.838 2.88 3.016 3.079 3.229 3.784 2.433 2.626 1.884 3.084 2.273 3.522 3.062 2.509 2.98 2.942 2.551 2.214 2.815 2.722 3.05 3.488 3.015 3.301 3.455 2.935 3.209 3.855 2.893 2.579 2.434 3.361 2.537 1.014 1.829 3.72 1.937 2.097 3.608 2.622 2.339 2.967 3.047 2.741 2.524 2.197 2.399 2.339 2.665 2.4 2.521 2.262 2.44 2.028 2.24 2.615 2.54 2.723 2.302 1.916 2.811 2.431 2.452 2.118 2.587 2.471 2.937 2.727 2.467 2.786 2.556 2.614 MERIT_005 2.989 2.652 1.873 2.654 2.859 2.575 2.457 2.787 2.262 2.953 3.672 2.344 2.319 2.211 2.395 1.973 3.438 2.699 2.069 2.441 2.463 2.243 1.976 2.339 2.2 2.789 2.955 2.431 2.62 2.869 1.992 2.515 3.235 2.158 2.413 2.164 1.966 2.012 1.189 2.298 3.116 1.676 1.526 3.648 2.338 1.792 2.902 2.604 2.378 2.372 1.949 2.203 2.333 2.228 1.872 2.152 1.927 1.973 2.123 2.058 2.192 2.303 2.705 2.26 2.169 2.274 2.003 2.156 1.904 2.319 2.082 2.468 2.471 3.01 2.219 2.355 2.186 1.678 MERIT_006 2.173 2.986 2.128 3.22 3.519 3.077 2.945 3.135 3.067 3.587 3.425 2.893 3.093 2.642 3 2.155 3.126 2.95 2.519 3.252 2.851 2.916 2.188 2.93 2.828 2.593 3.054 3.002 2.988 3.473 3.221 3.416 3.445 2.953 2.786 3.18 2.845 2.516 1.084 1.959 3.583 1.871 1.909 4.077 2.475 1.785 2.744 2.752 2.757 2.655 2.649 2.433 2.501 2.644 2.325 2.416 2.455 2.549 2.313 2.416 2.511 2.63 2.772 2.714 1.711 2.387 2.299 2.582 1.995 2.507 2.307 2.494 2.53 2.49 2.333 2.786 2.644 2.738 MERIT_007 2.525 3.246 2.082 3.185 3.338 3.215 3.186 3.414 2.583 3.684 4.245 2.494 2.329 2.565 3.154 2.4 3.075 2.772 2.505 2.872 3.045 2.811 2.294 3.06 3.002 2.582 3.172 2.769 2.906 3.278 2.463 3.098 3.638 2.818 2.761 2.976 2.698 2.874 1.066 2.024 3.231 2.12 1.893 3.419 2.877 2.64 3.459 2.963 3.037 3.837 2.454 2.413 2.296 2.69 2.339 2.694 2.306 2.44 2.408 2.264 2.757 2.474 2.789 2.384 1.98 1.952 2.573 2.422 2.38 2.646 2.608 2.98 2.438 2.556 2.697 2.755 2.683 2.446 MERIT_008 2.229 3.049 2.167 2.882 3.108 2.968 2.944 3.247 2.871 3.302 3.84 2.79 2.823 2.215 2.973 2.051 3.217 2.93 2.422 3.186 2.989 2.787 2.275 2.986 2.68 2.804 3.771 2.617 3.047 3.308 2.317 3.502 3.738 3.034 3.079 2.372 2.324 2.681 1.11 1.683 2.804 1.959 1.875 3.461 2.82 2.339 3.374 3.016 2.922 2.767 1.892 2.446 2.637 2.544 2.543 2.496 2.404 2.419 2.116 2.379 2.42 2.543 2.758 2.239 2.24 2.835 2.162 2.09 2.238 2.64 2.738 3.025 3.217 2.61 3.018 2.616 2.516 MERIT_009 2.323 3.001 2.066 3.007 3.344 2.893 2.902 3.072 2.913 3.355 3.875 2.404 2.684 2.451 2.791 1.999 2.768 2.841 2.568 2.888 2.849 2.591 2.245 2.78 2.778 3.011 3.382 2.846 2.983 3.221 2.839 3.175 3.337 2.698 2.779 2.286 2.479 2.416 1.158 2.246 3.116 1.862 1.871 3.713 2.692 2.389 3.043 2.784 2.638 2.58 1.825 2.504 2.472 2.59 2.358 2.289 2.206 2.237 2.003 2.31 2.249 2.667 2.481 2.753 2.05 2.521 2.333 2.413 2.189 2.576 2.629 3.413 2.47 2.681 2.779 2.671 2.529 2.659 MERIT_010 2.001 2.852 1.674 2.337 2.559 2.496 2.902 2.938 2.349 3.089 3.736 2.323 2.432 1.967 2.781 2.13 2.998 2.731 2.362 2.758 2.496 2.606 2.139 2.688 2.627 2.845 2.974 2.584 2.814 3.144 2.341 3.069 3.407 2.573 2.875 2.037 2.429 2.2 0.98 1.891 3.424 1.558 1.698 2.556 2.475 2.203 2.487 2.694 2.457 2.389 2.268 2.104 2.415 2.462 2 2.361 1.879 2.101 2.067 2.317 2.276 2.436 2.854 2.347 2.025 2.478 1.921 2.629 2.068 2.387 2.184 2.21 2.539 2.227 2.773 2.296 2.195 MERIT_011 2.925 2.871 1.782 2.624 2.826 2.803 2.823 2.938 2.945 2.973 3.38 2.391 2.869 2.369 2.813 2.021 2.979 2.572 2.249 3.015 2.756 2.729 2.31 2.638 2.583 2.525 3.024 2.772 3.069 3.246 2.609 3.356 3.37 2.66 2.613 1.964 2.023 2.191 0.969 1.97 3.434 1.86 1.644 3.109 2.391 2.335 2.232 2.678 2.488 2.558 2.113 2.389 2.316 2.528 2.089 2.489 2.181 2.409 2.026 2.366 2.418 2.132 2.678 2.247 2.021 1.997 2.205 2.078 2.112 2.422 2.326 1.779 2.339 2.376 2.703 2.607 2.54 2.914 MERIT_012 2.215 3.052 1.741 2.777 3.044 2.946 2.792 2.925 2.652 3.318 3.728 2.591 2.214 1.961 2.801 1.978 3 2.698 2.59 3.027 2.829 2.617 2.399 3.009 2.543 2.599 2.965 2.747 2.999 3.054 2.48 2.952 3.354 2.997 2.534 2.591 2.607 2.487 1.199 1.613 3.5 1.877 2.082 3.841 2.415 2.152 2.953 2.688 2.483 2.656 2.196 2.147 2.202 2.528 1.949 2.396 2.255 2.125 2.116 2.196 2.413 2.375 2.709 2.24 1.854 2.559 2.187 2.581 2.206 2.514 2.596 2.055 2.326 2.387 2.351 2.551 2.477 2.09 MERIT_013 2.755 2.88 1.718 2.984 3.815 2.711 2.739 2.973 2.749 3.052 3.364 2.466 2.363 2.088 2.513 1.867 2.746 2.682 2.419 2.761 2.812 2.407 2.34 2.854 2.497 2.36 3.182 2.83 2.96 3.162 2.362 3.058 3.844 2.821 2.236 2.425 2.14 2.296 0.985 1.89 3.523 1.774 1.784 3.478 2.582 2.098 2.76 2.541 2.568 2.368 2.025 2.147 2.152 2.508 2.089 2.017 1.955 2.214 2.082 2.182 2.282 2.104 2.626 2.496 1.59 2.699 2.126 2.453 2.151 2.396 2.36 3.024 2.17 2.148 2.405 2.834 2.366 1.941 MERIT_014 2.095 2.953 1.829 2.978 3.423 2.981 3.067 3.064 2.954 3.072 3.467 2.558 2.792 2.308 2.939 2.203 3.087 3.034 2.402 2.923 2.946 2.607 2.37 3.04 2.717 2.691 3.217 2.647 3.132 3.297 2.439 3.367 3.31 2.615 2.931 2.569 2.844 2.254 0.988 1.907 3.815 1.703 1.952 3.232 2.594 2.216 2.914 2.552 2.493 2.793 2.147 2.294 2.57 2.51 2.41 2.85 2.333 2.432 2.231 2.182 2.735 2.433 2.811 2.51 2.028 2.739 2.451 2.549 2.232 2.595 2.49 2.399 2.616 2.51 2.446 2.618 2.638 1.933 MERIT_015 2.441 3.037 1.797 2.788 2.956 2.644 2.816 3.074 2.543 3.373 3.845 2.552 2.634 2.212 2.903 2.023 2.796 2.794 2.239 2.622 2.587 2.601 2.083 2.892 2.419 2.572 3.226 2.938 2.952 2.999 2.861 2.949 3.696 2.865 2.335 2.679 2.403 2.316 1.132 1.749 3.388 1.783 1.808 3.32 2.674 2.184 3.045 2.891 2.56 3.319 2.014 2.278 2.367 2.576 2.297 2.324 1.942 2.441 2.313 1.983 2.552 2.426 2.776 2.073 1.758 2.351 2.268 2.59 1.909 2.29 2.403 3.263 3.381 2.142 2.222 2.346 2.402 2.611 MERIT_016 2.511 2.933 1.907 2.836 2.654 2.987 2.803 2.936 2.738 3.146 3.67 2.078 2.509 2.42 2.583 1.959 3.126 2.579 2.571 2.577 2.648 2.607 2.411 2.85 2.566 2.756 3.1 2.566 2.898 3.192 2.226 2.912 3.586 2.717 3.06 2.17 2.054 2.241 1.291 1.651 3.056 1.753 1.756 3.232 2.357 2.147 2.688 2.594 2.638 2.771 2.055 2.235 2.286 2.525 2.437 2.68 2.02 2.302 2.168 2.122 2.44 2.141 2.515 2.081 1.875 2.23 1.971 2.322 2.026 2.338 2.516 2 2.094 2.34 2.447 2.716 2.315 2.317 MERIT_017 2.204 3.05 1.85 2.806 2.377 2.522 2.786 2.973 2.266 3.474 4.007 2.227 2.506 2.11 2.895 2.142 2.63 2.812 2.324 2.911 2.903 2.384 2.307 2.753 2.633 2.732 3.469 2.807 3.027 3.042 2.737 2.992 2.966 2.492 2.593 2.094 2.315 2.434 0.836 1.978 3.549 1.929 1.824 3.759 2.547 2.096 2.662 2.86 2.505 2.21 1.985 2.291 2.465 2.519 2.261 2.679 2.11 2.154 2.251 2.382 2.484 2.777 2.634 2.302 2.219 2.759 2.103 2.784 2.07 2.345 2.581 2.822 2.598 2.105 2.676 2.359 3.144 MERIT_018 2.319 3.342 1.701 2.952 3.181 2.884 3.176 3.293 2.672 3.754 3.744 2.424 2.698 2.02 3.168 2.006 3.425 2.88 2.504 2.955 2.999 2.436 2.288 2.859 2.701 2.988 3.597 2.861 3.111 3.402 2.523 3.267 4.063 2.694 3.079 1.781 2.667 2.426 1.146 1.954 3.946 1.803 1.713 3.076 2.728 2.06 3.147 2.826 2.697 2.859 2.207 2.43 2.526 2.56 2.593 2.556 2.276 2.614 2.18 2.306 2.677 2.408 2.688 2.585 2.304 2.621 2.188 2.703 2.011 2.523 2.498 3.442 2.979 2.882 2.205 2.915 2.717 2.402 MERIT_019 2.942 2.666 2.043 2.754 2.887 2.75 2.959 2.803 2.545 3.086 3.573 2.438 2.524 2.031 2.847 1.869 3.162 2.67 2.469 2.485 2.574 2.552 2.414 2.802 2.623 2.99 3.461 2.85 2.901 3.15 2.414 2.984 3.604 2.476 2.686 2.228 2.273 2.175 0.975 1.799 3.209 1.827 1.712 3.827 2.366 2.101 2.812 2.785 2.326 2.515 1.685 2.251 2.259 2.289 2.201 2.011 1.888 2.079 1.769 1.862 2.474 2.321 2.48 2.474 2.057 1.777 2.205 2.159 1.926 2.268 2.236 2.478 2.543 2.101 2.033 2.574 2.288 1.984 MERIT_020 2.305 3.13 1.879 2.938 3.255 2.756 2.923 2.978 2.771 3.499 3.787 2.282 2.514 2.252 2.871 1.974 3.002 2.981 2.548 2.958 2.88 2.745 2.265 3.121 2.81 2.946 3.323 2.963 3.077 3.127 2.899 3.008 3.765 2.358 2.798 1.929 2.124 2.217 1.004 1.791 3.386 1.725 2.231 3.086 2.536 2.462 3.062 2.885 2.538 2.783 1.784 2.401 2.235 2.645 2.301 3.191 2.394 2.481 1.779 2.075 2.44 2.293 2.561 2.051 2.051 2.733 2.159 2.675 2.195 2.619 2.708 2.57 2.317 2.453 2.447 2.388 2.397 MERIT_021 2.861 3.056 1.698 2.873 3.267 2.848 2.772 3.046 3.287 3.406 3.765 2.387 2.099 1.923 2.704 1.985 3.275 3.017 2.294 2.512 2.561 2.447 2.027 2.701 2.586 2.945 3.524 2.591 3.052 3.022 2.207 3.183 3.775 2.357 2.851 2.794 2.314 2.128 0.992 1.731 3.651 1.706 1.673 2.26 2.669 2.158 2.829 2.59 2.422 2.323 2.024 2.201 2.416 2.424 2.528 2.161 2.017 2.309 2.196 1.969 2.505 2.196 2.677 3.229 2.441 1.985 2.079 2.456 1.735 2.486 2.262 2.341 2.711 2.29 2.53 2.708 2.436 2.048 MERIT_022 2.304 2.928 1.804 2.928 3.071 2.992 2.872 2.946 2.495 3.004 3.605 2.693 2.49 2.131 2.798 2.133 2.985 2.749 2.373 2.887 2.661 2.634 2.051 2.802 2.614 2.457 3.59 2.379 2.93 3.034 2.407 3.139 3.562 2.528 2.595 2.592 2.525 2.389 1.02 2.022 3.361 1.792 1.783 3.644 2.529 2.169 2.871 2.571 2.674 2.84 2.038 2.312 2.344 2.491 2.215 2.532 2.241 2.298 2.101 2.231 2.725 2.568 2.623 2.23 2.032 2.046 2.204 2.552 2.12 2.555 2.31 1.573 2.317 2.59 2.504 2.532 2.493 2.205 MERIT_023 2.596 2.972 1.85 3.075 2.968 2.875 3.071 3.128 2.452 3.015 3.987 2.674 2.863 2.23 2.88 1.932 2.905 2.806 2.526 2.949 2.956 2.686 2.277 2.823 2.732 2.895 2.733 2.773 3.343 3.078 2.769 3.084 3.466 2.741 3.028 2.226 3.367 2.512 0.996 1.943 3.512 1.887 1.766 3.495 2.618 2.245 2.947 2.899 2.635 3.376 2.26 2.513 2.434 2.669 2.64 2.85 2.398 2.401 2.245 2.203 2.583 2.235 2.861 2.513 2.133 2.734 2.31 2.571 2.144 2.69 2.443 2.71 2.606 2.535 3.027 2.526 2.274 MERIT_024 2.462 3.276 1.939 2.832 2.873 2.526 3.001 3.179 2.491 3.854 3.836 2.466 2.825 2.505 2.743 2.126 3.349 2.703 2.581 3.014 2.814 2.613 2.509 2.894 2.662 3.137 3.693 2.782 3.156 3.139 2.815 3.375 3.58 2.54 2.766 2.648 2.239 2.546 1.047 1.947 3.842 1.97 1.961 3.614 2.672 2.087 2.884 2.977 2.678 2.692 2.012 2.257 2.5 2.546 2.377 2.461 2.24 2.263 1.949 2.219 2.667 2.222 2.49 2.158 2.568 1.9 2.265 2.899 2.266 2.538 2.246 2.826 2.457 2.957 2.383 2.612 2.503 2.154 MERIT_025 2.315 2.64 1.487 2.288 1.953 2.214 2.458 2.728 2.674 2.664 3.619 2.012 2.607 2.213 2.193 1.828 2.536 2.719 1.836 2.561 2.629 2.194 2.022 2.48 2.195 2.977 3.203 2.516 2.917 2.692 1.833 2.663 2.825 2.604 2.418 2.169 2.244 2.165 0.985 1.616 3.272 1.789 1.559 3.436 2.494 1.928 2.628 2.57 2.172 3.245 1.743 2.151 1.713 2.082 2.052 2.194 1.978 2.019 1.931 2.106 2.328 2.167 2.653 2.258 2.486 2.246 1.757 2.113 2.096 2.521 1.938 2.442 2.278 2.932 2.165 2.51 2.357 2.547 MERIT_026 2.662 3.049 2.047 3.296 3.545 3.429 3.203 3.372 2.725 3.579 3.671 2.322 2.778 2.208 2.445 1.858 3.12 3.062 2.455 3.093 3.099 2.75 2.221 2.997 2.752 3.176 3.891 2.953 2.979 3.342 3.017 3.258 3.535 2.743 2.946 3.568 2.42 2.345 0.991 1.88 3.827 1.795 1.628 3.7 2.871 2.133 3.05 3.321 2.528 2.988 1.864 2.596 2.495 2.642 2.485 2.654 2.168 2.614 1.988 2.267 2.735 2.075 2.847 2.611 2.235 2.771 2.213 2.263 2.18 2.568 2.565 2.776 2.366 3.068 2.447 2.672 2.517 3.04 MERIT_027 2.451 3.161 1.73 2.781 2.754 2.519 2.763 3.213 2.782 3.186 3.82 2.397 2.755 2.273 2.857 1.924 3.186 2.7 2.092 2.702 2.994 2.454 2.357 2.508 2.555 2.625 3.198 3.014 3.254 3.122 2.896 3.025 3.441 2.628 2.93 2.567 2.622 2.695 1.054 1.762 3.033 1.826 1.695 2.962 2.639 2.423 2.798 2.943 2.557 2.78 2.034 2.438 2.167 2.657 2.258 2.594 2.226 2.596 2.172 2.463 2.637 2.571 2.649 2.229 2.042 2.319 2.464 2.839 2.252 2.803 2.247 2.914 2.511 2.529 2.788 2.775 2.652 MERIT_028 2.179 3.303 1.869 3.293 3.464 3.038 2.965 3.143 3.177 3.681 3.49 2.452 2.724 2.417 2.976 2.181 3.08 2.955 2.569 3.094 2.93 2.833 2.467 3.033 2.778 2.431 3.285 3.219 3.014 3.338 2.853 3.49 3.544 2.854 2.579 3.034 2.629 2.342 1.049 1.832 3.598 2.102 2.129 4.277 2.826 2.203 2.929 2.981 2.847 3.207 1.879 2.459 2.55 2.782 2.632 2.229 2.289 2.455 2.307 2.426 2.677 2.382 2.681 2.506 2.056 2.672 2.365 2.749 2.285 2.742 2.541 3.019 2.47 2.207 2.644 2.751 2.622 2.283 MERIT_029 2.901 3.249 2.137 3.066 3.076 2.904 3.048 3.303 3.048 3.228 4.054 2.327 2.772 2.295 3.128 2.201 3.221 3.269 2.497 3.306 3.154 2.738 2.331 3.157 2.951 2.828 4.156 3.253 2.822 3.316 2.594 3.359 3.342 2.753 2.739 2.332 2.432 2.522 1.137 1.978 3.443 2.052 2.107 3.341 2.782 2.34 3.174 2.842 2.794 2.545 1.955 2.329 2.269 2.678 2.6 2.888 2.294 2.424 2.468 2.445 2.598 2.689 2.93 2.472 2.375 2.688 2.534 2.168 2.319 2.68 2.522 2.945 3.005 2.462 2.629 2.704 2.565 MERIT_030 2.029 2.834 1.759 2.711 2.841 2.608 2.686 3.11 2.06 3.216 3.405 2.485 2.539 1.98 2.954 2.059 3.015 2.504 2.604 2.663 2.934 2.477 2.253 2.569 2.613 2.437 3.042 2.754 2.881 3.207 2.69 3.137 3.532 2.849 2.467 2.06 2.191 2.627 0.939 1.649 3.199 1.793 1.895 3.701 2.619 2.192 3.23 2.857 2.485 2.872 2.011 2.309 2.087 2.436 1.934 2.379 2.321 2.591 2.175 2.159 2.64 2.625 2.382 2.163 1.823 2.942 2.267 2.192 2.432 2.548 2.496 3.232 2.307 2.571 2.94 2.611 2.844 MERIT_031 2.708 3.011 1.804 2.535 3.067 2.478 2.39 2.808 2.203 3.479 3.824 2.264 2.951 2.097 2.695 1.866 2.646 2.494 2.27 2.665 2.532 2.426 2.088 2.66 2.405 2.507 3.461 2.759 2.951 2.829 2.329 2.738 3.282 2.563 2.405 2.484 1.917 2.208 1.077 2.281 3.305 1.903 1.978 3.683 2.534 2.068 2.593 2.785 2.596 3.017 2.065 1.904 1.99 2.389 2.316 2.262 2.063 1.948 2.346 2.196 2.714 2.118 2.411 2.143 2.456 2.373 1.925 2.821 2.146 2.208 2.408 2.601 2.248 1.801 1.986 2.572 2.226 2.697 MERIT_032 1.989 2.845 1.691 2.755 2.903 2.841 3.02 3.094 2.387 3.633 3.697 2.726 2.737 2.019 2.678 1.896 2.704 2.78 2.037 2.822 3.016 2.241 1.961 2.687 2.479 2.557 3.201 2.837 2.793 3.005 2.729 2.744 2.797 2.73 3.033 2.014 2.73 2.24 1.05 1.775 2.935 1.741 1.724 3.081 2.649 2.518 3.108 2.967 2.661 3.16 1.944 2.304 2.5 2.594 2.878 2.415 1.921 2.116 2.04 2.097 2.805 2.2 2.642 2.57 2.372 2.3 2.067 1.852 1.981 2.63 2.583 2.656 1.875 2.306 2.696 2.456 2.734 MERIT_033 1.605 2.901 1.763 2.089 2.342 2.259 2.578 2.87 2.297 3.178 3.334 2.385 2.542 2.12 2.769 2.043 2.536 2.217 2.276 2.773 2.742 2.474 2.134 2.214 2.76 2.464 3.248 2.402 2.722 2.846 2.379 2.512 2.685 2.71 2.544 1.907 2.983 2.426 0.956 2.131 3.153 1.904 1.7 2.759 2.529 2.14 2.61 2.528 2.584 2.144 2.163 2.216 2.47 2.382 2.83 2.85 2.415 2.387 2.192 2.081 2.542 2.422 2.519 2.736 2.363 2.38 2.056 2.304 2.226 2.328 2.393 3.423 2.722 2.163 2.766 2.683 2.497 2.385 MERIT_034 2.631 2.944 1.877 2.642 3.095 2.612 2.675 2.84 2.789 3.272 3.984 2.184 2.432 2.17 2.821 1.992 3.337 2.869 2.2 2.704 2.533 2.476 2.324 2.968 2.575 3.013 3.493 2.628 2.905 2.886 2.437 3.231 3.318 2.575 2.731 2.509 1.899 2.212 0.966 1.683 3.707 1.794 2.023 3.417 2.474 2.014 3 2.479 2.503 2.25 1.751 2.042 2.28 2.31 1.953 1.947 2.083 2.097 1.868 1.979 2.264 2.438 2.477 2.282 2.273 2.266 2.22 2.319 1.96 2.139 2.167 1.745 2.188 2.437 2.403 2.244 2.129 MERIT_035 2.197 2.871 1.437 2.547 2.646 2.57 2.523 2.634 2.696 3.061 3.769 1.808 2.383 2.049 2.491 1.617 2.875 2.531 1.445 2.272 2.394 2.085 1.619 1.789 2.028 2.427 3.233 2.254 2.428 2.729 2.342 2.537 2.977 1.806 2.654 2.267 2.353 2.106 1.105 1.869 3.534 1.478 1.281 3.226 2.741 1.989 3.083 2.87 2.596 2.735 1.687 2.192 2.34 2.426 2.517 1.816 1.666 1.843 1.803 1.778 2.109 2.13 2.505 2.176 1.783 1.803 1.827 2.507 1.866 2.443 1.747 2.855 2.639 2.483 2.18 2.45 2.248 2.341 MERIT_036 2.546 2.849 1.853 2.78 2.813 2.916 2.817 3.072 3.355 3.163 3.96 2.604 2.466 2.217 2.742 2.188 3.1 3.069 2.526 2.799 2.993 2.556 2.497 2.791 2.508 2.719 3.284 2.851 3.024 3.038 2.46 3.006 3.393 2.408 3.113 2.01 2.426 2.199 1.108 1.988 3.524 1.883 1.815 4.063 2.502 2.159 2.962 2.759 2.58 2.831 2.012 2.24 2.268 2.475 2.537 2.06 2.305 2.522 2.072 2.158 2.447 2.354 2.968 1.913 2.203 2.93 2.282 2.543 2.208 2.5 2.613 3.281 2.7 2.075 2.372 2.463 2.492 MERIT_037 2.514 3.186 1.815 2.667 3.116 2.688 2.847 3.185 3.083 3.169 3.778 2.466 2.203 1.866 2.561 1.918 3.044 2.929 2.37 2.544 2.774 2.29 2.258 2.923 2.58 2.723 3.327 2.644 3.122 3.223 2.793 3.029 3.121 2.785 2.56 2.495 2.133 2.564 1.087 1.54 3.709 1.676 1.895 3.345 2.771 2.101 2.663 2.928 2.517 2.527 2.076 2.222 2.429 2.523 2.288 2.454 2.146 2.481 2.016 2.064 2.374 2.546 2.752 2.389 1.857 3.243 2.286 2.337 1.985 2.487 2.303 2.015 2.773 2.573 2.619 2.505 2.612 MERIT_038 2.219 2.96 1.897 3.018 2.878 2.692 2.921 3.046 3.093 3.65 3.687 2.314 2.496 2.196 2.466 1.921 2.648 2.822 2.466 2.753 2.944 2.425 2.251 2.712 2.584 2.999 3.416 2.944 2.708 3.101 2.525 3.243 3.538 2.759 2.882 2.477 2.269 2.366 0.941 1.806 3.686 1.911 1.924 3.61 2.526 2.342 2.925 2.897 2.641 2.429 1.796 2.365 2.498 2.716 2.371 2.355 2.279 2.246 1.873 2.231 2.702 2.257 2.851 2.514 2.15 2.286 2.004 2.524 2.267 2.522 2.402 2.574 2.789 2.865 2.391 2.506 2.446 2.275 MERIT_039 2.855 3.08 1.59 2.893 3.353 3.029 2.888 3.018 3.015 3.151 3.663 2.078 2.182 1.737 2.62 1.82 2.85 2.721 2.189 2.715 2.838 2.602 2.083 2.768 2.647 2.579 3.167 2.584 2.995 3.095 2.485 3.245 3.353 2.48 2.172 2.555 2.322 2.316 1.067 1.715 3.657 1.695 1.835 3.386 2.66 2.176 3.09 2.665 2.471 2.734 1.661 2.393 2.508 2.58 2.567 2.361 2.095 2.258 1.981 2.022 2.627 2.168 2.701 2.387 2.3 1.868 2.122 2.171 2.006 2.518 2.057 2.672 2.301 2.579 2.193 2.72 2.469 2.019 MERIT_040 2.135 3.073 1.745 3.104 3.131 3.097 3.094 3.01 2.775 2.865 2.477 2.759 2.119 1.779 3.048 1.865 1.994 3.086 2.566 2.885 3.098 2.524 2.729 3.011 2.562 2.621 3.247 3.39 2.962 3.37 2.763 3.254 2.598 2.967 2.965 2.394 2.687 2.629 0.974 1.59 2.259 1.807 2.042 2.833 2.731 2.325 2.994 2.695 2.708 3.046 2.181 2.654 2.547 2.613 2.397 2.46 2.143 2.605 2.229 2.284 2.892 1.868 2.738 2.54 2.126 2.293 2.234 2.209 2.321 2.63 2.405 3.89 2.491 2.36 2.617 2.71 2.773 MERIT_041 2.038 2.831 1.917 3.018 3.178 2.647 2.829 2.991 2.545 3.336 3.914 2.492 2.558 2.137 2.823 2.175 2.998 2.959 2.457 2.957 2.796 2.615 2.267 2.785 2.481 2.99 3.219 2.678 3.062 3.178 2.807 3.305 3.555 2.745 2.757 2.232 3.085 2.451 1.09 1.825 3.614 1.864 1.898 3.927 2.703 2.08 3.461 3.086 2.487 2.75 1.958 2.391 2.197 2.504 2.339 3.472 2.121 2.333 1.967 2.076 2.362 2.132 2.352 2.275 2.264 2.515 2.201 1.985 2.151 2.321 2.483 2.834 2.126 2.417 2.178 2.285 2.398 2.188 MERIT_042 2.611 3.225 1.748 3.256 2.377 2.518 2.544 3.109 2.295 3.951 4.351 2.31 2.532 2.37 2.72 1.996 3.047 2.452 2.345 2.781 2.732 2.38 2.386 2.672 2.485 2.663 3.403 3.222 2.976 3.275 2.921 3.59 3.499 2.713 2.829 2.216 2.849 2.674 1.045 1.938 3.533 1.916 1.807 3.333 2.854 2.007 3.375 2.854 2.807 2.734 2.238 2.304 1.962 2.695 2.377 2.616 2.123 2.245 2.266 2.122 2.845 2.555 2.677 2.256 2.345 2.676 2.247 2.416 2.261 2.5 2.69 3.123 2.524 2.343 2.716 2.625 2.524 MERIT_043 2.456 2.942 1.864 2.672 2.927 2.575 2.536 2.635 2.327 3.102 3.431 2 2.525 2.37 2.907 2.059 2.974 2.601 2.15 2.463 2.552 2.357 2.039 2.552 2.402 2.159 3.392 2.442 2.793 2.903 2.338 2.958 3.422 2.594 2.544 2.405 1.96 2.335 0.932 2.017 3.373 1.975 1.852 2.855 2.396 2.008 2.678 2.875 2.35 3.078 1.734 2.046 1.928 2.18 1.903 1.931 1.985 2.266 1.845 2.015 2.252 2.262 2.336 2.123 2.11 2.167 2.107 2.442 1.906 2.222 2.284 1.949 2.327 2.237 2.346 2.067 2.383 2.257 MERIT_044 2.594 2.783 1.833 2.788 2.883 2.596 2.47 2.914 2.817 2.71 3.865 2.475 2.758 2.245 2.741 2.019 3.144 2.623 2.347 2.849 2.738 2.514 2.183 2.744 2.607 2.212 2.749 2.509 2.726 2.876 2.34 2.881 3.28 2.435 2.599 2.286 2.292 2.294 0.945 2.207 3.197 1.803 1.837 3.044 2.533 2.19 2.523 2.484 2.453 2.317 2.329 1.949 1.95 2.413 1.792 3.714 2.203 2.319 1.949 2.034 2.565 2.192 2.359 1.431 2.226 2.428 2.239 2.12 2.153 2.277 2.384 2.983 2.454 2.21 2.358 2.25 2.334 2.601 MERIT_045 2.464 2.771 2.012 2.628 2.717 2.726 2.676 2.712 2.934 3.459 3.529 2.259 2.657 2.562 2.693 2.143 2.572 2.645 2.198 2.803 2.722 2.531 2.215 2.78 2.736 2.246 3.086 2.54 2.727 2.996 2.735 2.927 3.506 2.4 2.529 2.141 2.273 2.317 0.993 2.121 2.816 2.001 2.024 4.313 2.398 2.163 2.597 2.671 2.222 2.633 1.868 2.154 2.321 2.31 1.958 2.009 2.089 2.193 1.76 2.082 2.383 2.116 2.247 2.1 1.98 2.429 2.21 1.991 2.213 2.245 2.3 2.145 2.182 2.301 2.306 2.35 2.475 MERIT_046 3.066 3.059 1.902 2.826 2.94 2.738 2.715 2.836 2.903 2.931 3.683 2.536 2.675 2.4 2.963 2.26 2.608 2.85 2.476 2.92 2.644 2.569 2.35 2.891 2.629 2.739 3.426 2.555 2.606 3.006 2.628 3.117 3.672 2.549 2.617 2.252 2.075 2.227 0.813 2.123 3.032 1.996 1.978 2.722 2.406 2.183 2.612 2.72 2.342 2.27 1.9 2.093 2.261 2.252 2.011 2.076 2.073 2.372 2.032 1.969 2.232 2.308 2.263 2.281 2.34 1.789 2.249 2.62 2.1 2.164 2.192 2.295 2.13 2.335 2.284 2.183 2.274 2.046 MERIT_047 1.982 2.748 1.887 2.282 2.389 2.255 2.451 2.578 2.45 2.465 3.108 2.399 2.312 2.455 2.841 1.994 2.772 2.355 2.249 2.653 2.408 2.648 2.187 2.424 2.629 2.264 3.742 2.554 2.735 3.095 2.187 2.669 3.243 2.579 2.299 1.835 2.264 2.276 0.877 2.11 2.896 1.837 1.716 2.336 2.167 2.104 2.509 2.311 2.234 2.698 1.894 2.012 2.264 2.298 1.873 1.954 1.969 1.969 1.941 2.278 2.063 2.301 2.214 1.788 1.885 2.187 2.119 2.018 1.99 2.094 2.094 2.536 2.723 2.057 2.239 2.214 2.572 MERIT_048 1.156 3.286 2.015 2.897 3.144 2.766 2.881 3.071 2.462 3.458 3.789 2.671 2.872 2.587 2.901 2.223 3.027 2.778 2.566 2.953 2.989 2.619 2.432 3.065 2.668 2.722 3.463 3.138 3.091 3.263 2.799 3.44 3.664 2.859 2.834 2.115 2.393 2.904 1.133 2.326 2.603 2.006 2.083 3.192 2.672 2.474 3.01 2.971 2.736 2.427 2.265 2.341 2.152 2.592 2.307 2.159 2.323 2.492 2.153 2.499 2.778 2.44 2.611 2.211 2.151 2.729 2.499 2.078 2.356 2.618 2.547 2.224 2.388 2.268 2.543 2.471 2.624 2.436 MERIT_049 2.714 2.952 1.897 2.772 2.902 2.882 2.637 2.893 2.637 2.922 3.774 2.378 2.647 2.436 3.035 2.129 2.877 2.639 2.303 2.808 2.916 2.543 2.422 2.834 2.865 2.349 3.156 2.863 2.842 2.983 2.552 3.291 3.038 2.482 2.577 2.502 2.245 2.355 0.954 2.112 3.554 1.961 1.934 2.941 2.403 2.353 2.727 2.678 2.537 2.759 1.985 2.259 2.142 2.348 1.9 2.273 2.152 2.255 2.067 2.063 2.548 2.477 2.71 2.087 1.91 2.504 2.293 1.856 2.235 2.468 2.244 2.899 2.935 2.524 2.487 2.288 2.317 2.55 MERIT_050 2.896 2.89 2.069 2.831 2.966 2.968 3.018 2.917 2.669 3.064 3.781 2.335 2.813 2.507 3.066 2.184 3.156 2.707 2.475 2.903 2.903 2.732 2.464 3.012 2.793 2.32 3.001 3.078 2.949 3.151 2.307 3.264 3.603 2.713 2.715 1.728 2.374 2.292 0.979 2.295 2.924 2.087 2.018 2.968 2.337 2.14 2.653 2.648 2.411 2.77 2.2 2.13 2.252 2.248 2.319 2.239 2.271 2.159 2.325 2.023 2.429 2.262 2.804 2.415 2.25 2.678 2.232 2.257 2.107 2.415 2.425 2.294 2.418 2.732 2.248 2.34 2.164 MERIT_051 2.022 2.782 1.916 2.456 2.839 2.562 2.575 2.601 2.541 2.891 3.451 2.036 2.423 2.195 2.354 1.886 3.108 2.516 2.409 2.515 2.467 2.366 2.067 2.726 2.517 2.11 2.702 2.711 2.567 2.897 2.446 2.948 3.234 2.365 2.138 2.064 2.16 2.122 0.812 1.903 3.127 1.797 1.909 2.46 2.231 1.823 2.543 2.734 2.17 2.134 1.767 2.062 1.881 2.126 1.793 1.976 1.85 1.745 1.758 2.063 1.732 2.085 2.238 1.91 2.155 1.935 2.125 2.003 1.888 2.314 2.086 2.89 2.192 2.229 2.168 2.039 2.195 2.056 MERIT_052 2.619 2.584 1.904 2.683 2.876 2.6 2.399 2.703 2.923 3.103 3.697 2.011 2.579 2.314 2.608 2.031 2.883 2.68 2.333 2.675 2.603 2.367 1.985 2.602 2.588 2.344 3.044 2.682 2.551 2.961 2.622 3.202 3.178 2.757 2.263 2.151 2.191 2.33 0.671 1.976 3.329 2.003 1.959 3.174 2.289 2.128 2.883 2.531 2.465 2.769 1.973 2.155 2.105 2.228 1.943 1.639 2.012 1.968 1.72 2.023 1.912 2.152 2.453 1.971 2.323 2.222 2.271 1.825 2.074 2.381 2.258 2.365 2.306 2.188 2.156 2.234 2.272 MERIT_053 2.178 2.451 1.796 2.442 2.476 2.285 2.383 2.391 2.283 3.094 3.355 2.15 2.401 2.461 2.754 1.904 3.565 2.555 2.182 2.44 2.394 2.215 1.942 2.528 2.325 2.223 2.89 2.507 3.009 2.954 2.079 3.19 3.293 2.201 2.282 1.743 2.031 1.835 0.927 1.988 3.197 1.747 1.829 3.665 2.064 1.753 2.568 2.375 2.241 2.522 2.333 1.832 1.866 2.027 1.836 2.059 1.788 2.198 1.978 2.201 2.531 2.349 2.523 2.08 1.966 1.846 2.036 2.135 1.712 2.069 2 1.917 2.152 2.015 2.24 2.764 2.379 1.896 MERIT_054 2.162 2.807 1.796 2.575 2.772 2.462 2.494 2.861 2.356 3.028 3.499 2.373 2.625 2.187 2.657 2.036 3.148 2.437 2.347 2.779 2.784 2.408 2.101 2.869 2.316 2.027 3.157 2.601 2.657 2.936 2.247 2.912 3.271 2.546 2.06 2.04 1.974 2.351 0.946 2.192 2.845 1.814 1.93 3.157 2.271 2.182 2.463 2.602 2.307 2.398 1.961 2.042 1.937 2.215 1.665 1.947 2.035 2.491 2.043 1.957 2.443 2.282 2.141 1.737 1.622 3.273 1.973 2.024 2.048 2.109 2.333 3.048 2.534 2.514 2.064 2.295 2.318 2.131 MERIT_055 2.61 2.691 2.037 2.563 2.585 2.221 2.407 2.646 2.442 2.859 3.39 2.087 2.495 2.081 2.701 1.916 2.828 2.295 2.257 2.506 2.59 2.321 1.945 2.531 2.442 2.322 3.233 2.547 2.586 2.9 2.233 2.947 3.316 2.509 2.086 1.802 2.04 2.227 0.904 1.995 2.794 1.797 1.733 2.5 2.112 2.064 2.464 2.506 2.308 1.964 2.05 1.998 2.054 2.217 1.831 2.034 2.007 2.018 1.869 1.891 1.837 2.019 2.098 1.706 2.13 2.261 1.871 2.033 1.924 2.101 2.056 2.508 2.21 2.567 1.989 2.099 2.223 2.157 MERIT_056 2.248 2.78 1.932 2.78 2.66 2.411 2.498 2.714 2.674 3.108 3.337 2.476 2.696 2.2 3.032 2.015 3.315 2.602 2.254 2.751 2.598 2.482 2.196 2.764 2.747 2.369 2.954 2.486 2.877 3.084 2.386 3.198 3.24 2.432 2.437 1.907 2.124 2.119 0.933 2.042 3.551 1.744 1.991 3.342 2.297 2.13 2.807 2.525 2.395 2.811 2.263 2.21 2.167 2.371 1.961 2.45 2.085 2.34 2.066 2.051 2.389 2.513 2.34 2.249 2.332 2.411 2.14 2.134 2.087 2.156 2.329 2.166 2.561 2.18 2.487 2.386 2.075 MERIT_057 3.033 3.042 1.724 2.769 2.86 2.82 2.729 2.879 2.643 3.312 3.502 2.498 2.584 2.225 2.682 2.071 2.906 2.755 2.258 2.801 2.819 2.483 2.284 2.983 2.575 2.387 3.19 2.971 3.124 3.137 2.656 3.338 3.428 2.677 2.502 2.042 1.939 2.339 1.069 1.991 3.053 1.975 2.029 3.036 2.462 2.354 2.506 2.622 2.561 2.972 2.008 2.228 2.093 2.31 1.902 2.294 2.024 2.027 1.855 1.937 2.06 2.272 2.483 2.008 1.97 2.317 2.291 2.018 2.098 2.305 2.351 2.612 2.226 2.096 2.189 2.071 2.432 2.639 MERIT_058 1.999 2.941 1.929 2.881 2.913 2.67 2.75 2.84 2.824 2.819 3.237 2.203 2.575 2.284 2.604 1.965 2.609 2.637 2.319 2.755 2.757 2.596 2.455 2.979 2.555 2.367 2.963 2.853 2.731 2.989 2.401 3.127 3.428 2.4 2.473 2.683 2.692 2.353 0.833 2.088 2.984 1.757 2.019 2.595 2.328 2.112 2.738 2.347 2.308 2.274 1.981 2.35 2.17 2.381 1.935 1.924 2.054 2.047 2.119 2.056 1.874 2.211 2.311 1.941 1.908 2.335 2.258 2.374 2.09 2.354 2.35 3.137 2.352 2.552 2.229 2.068 2.326 2.461 MERIT_059 2.606 3.451 1.861 3.073 3.082 2.994 2.803 2.998 3.289 3.389 3.848 2.696 2.898 2.658 2.976 1.915 3.063 2.982 2.415 3.112 2.887 2.554 2.219 2.863 2.873 2.839 3.407 3.161 3.302 3.485 2.548 3.542 4.077 2.866 2.751 2.198 2.965 2.351 1.003 2.188 3.678 1.964 2.086 3.682 2.663 2.121 2.891 3.341 2.642 3.065 2.059 2.256 2.257 2.53 2.285 2.291 2.178 1.931 2.148 2.015 2.479 2.579 2.833 2.178 2.613 2.276 2.241 2.525 2.131 2.556 2.201 2.345 2.42 2.473 2.708 2.698 2.456 MERIT_060 2.1 2.698 1.757 2.674 2.626 2.464 2.574 2.672 2.563 2.419 3.019 2.087 2.462 2.166 2.664 2.091 2.59 2.47 2.306 2.617 2.28 2.397 2.034 2.406 2.463 2.813 3.199 2.469 2.461 2.791 2.16 2.669 2.938 2.135 2.409 1.994 1.811 2.069 0.769 2.12 3.101 1.968 1.885 3.027 2.361 2.099 2.146 2.424 2.235 1.968 1.786 1.924 2.167 2.381 2 2.313 2.013 1.846 1.581 1.835 1.933 1.812 2.505 2.081 2.127 2.075 1.758 2.01 2.032 2.178 2.056 3.14 1.754 2.279 2.121 2.01 2.043 2.149 MERIT_061 1.987 2.958 1.921 2.56 2.395 2.583 2.526 2.717 2.815 2.847 3.137 2.435 2.867 2.415 2.692 2.24 3.109 2.714 2.366 2.808 2.718 2.483 2.246 2.81 2.583 2.257 2.843 2.439 3.041 3.03 2.37 3.035 3.457 2.568 2.638 2.069 2.198 2.623 0.953 2.073 3.549 1.854 2.015 2.607 2.423 2.158 3.33 2.733 2.449 2.475 2.083 2.307 1.915 2.132 2.318 2.28 2.19 2.437 2.326 2.255 2.484 2.494 2.471 1.695 2.497 2.143 2.249 2.507 2.236 2.169 2.288 2.283 2.324 2.359 2.605 2.472 1.931 MERIT_062 2.753 3.112 2.294 3.149 2.927 2.872 2.64 3.063 2.466 3.108 3.944 2.564 3.017 2.564 3.094 2.306 3.266 2.913 2.694 2.991 2.77 2.709 2.344 3.131 2.835 2.246 3.155 2.845 3.146 3.298 2.667 3.58 3.666 2.849 2.832 1.902 2.334 2.296 1.054 2.444 3.546 2.008 2.128 3.834 2.703 2.494 2.997 2.844 2.522 2.876 2.013 2.222 2.242 2.289 2.083 2.17 2.151 2.295 2.09 2.06 2.441 2.77 2.792 2.172 2.284 2.425 2.245 2.172 2.234 2.327 2.497 2.366 2.424 2.464 2.505 2.482 2.664 MERIT_063 2.412 2.997 2.042 2.783 2.52 2.852 2.724 2.916 2.689 3.133 3.228 2.209 2.628 1.93 2.502 2.213 3.129 2.775 2.196 2.666 2.575 2.468 2.384 2.51 2.576 2.629 3.226 2.694 2.483 2.622 2.428 3.065 3.841 2.406 2.458 1.886 2.027 2.282 0.946 1.97 3.177 2.039 1.879 3.286 2.565 2.047 2.509 2.788 2.57 2.162 1.879 2.254 2.371 2.571 1.963 2.457 2.112 1.974 1.516 1.857 1.897 2.238 2.98 2.326 2.347 2.194 2.22 2.201 2.315 2.296 2.396 2.324 2.429 2.415 2.246 1.835 2.237 2.55 MERIT_064 2.232 2.723 2 2.586 2.555 2.639 2.461 2.732 3.049 2.499 3.44 2.237 2.536 2.026 2.446 2.255 2.875 2.656 2.241 2.877 2.406 2.248 2.053 2.338 2.201 2.367 3.186 2.435 2.37 2.87 2.158 2.789 3.204 2.306 2.814 2.088 2.155 2.17 0.965 2.384 2.898 2.093 1.841 3.247 2.296 2.014 2.396 2.673 2.287 2.259 2.31 2.195 2.666 2.323 2.011 2.73 1.862 2.101 1.816 1.93 2.11 2.238 2.406 2.222 1.915 2.746 1.979 2.825 1.775 2.206 2.268 2.287 2.14 1.974 1.82 2.288 2.133 MERIT_065 2.493 2.964 2.034 2.561 2.566 2.602 2.655 2.822 2.786 2.951 3.65 2.258 2.645 2.174 2.823 2.142 3.051 2.512 2.417 2.795 2.807 2.536 2.336 2.612 2.622 2.459 3.131 2.826 2.503 2.815 2.882 3.021 3.248 2.486 2.489 1.847 2.237 2.334 1.012 2.171 3.339 2.076 1.797 2.94 2.539 2.049 2.665 2.643 2.575 2.692 1.813 1.955 2.062 2.26 1.964 1.91 2.019 2.273 1.884 1.933 2.406 2.2 2.307 1.861 1.806 2.256 2.209 1.92 2.134 2.327 2.156 3.637 2.569 2.042 2.278 2.284 2.266 2.867 MERIT_066 1.938 2.833 1.699 2.661 2.715 2.432 2.51 2.708 2.573 2.912 3.354 2.432 2.667 2.239 2.946 1.875 3.347 2.566 2.25 2.663 2.564 2.307 2.33 2.685 2.481 2.225 2.532 2.498 2.901 2.957 2.621 3.094 3.598 2.466 2.637 2.15 2.075 2.201 0.985 2.096 3.322 1.813 1.897 2.883 2.391 2.16 2.501 2.6 2.439 2.472 2.494 1.99 1.983 2.335 1.874 1.975 2.07 2.057 2.072 2.113 2.316 2.442 2.713 1.849 2.328 2.481 2.265 1.906 1.878 2.413 2.149 2.115 2.182 2.227 2.196 2.259 2.152 MERIT_067 2.375 2.905 1.904 2.71 2.974 2.596 2.719 2.698 2.617 2.823 3.358 2.401 2.554 2.366 2.757 2.076 3.181 2.732 2.441 2.775 2.683 2.372 2.252 2.77 2.54 2.444 3.223 2.7 2.881 3.223 2.523 3.12 3.535 2.491 2.481 2.357 2.278 2.125 1.125 2.271 3.232 2.109 1.933 2.866 2.45 2.24 3.422 2.666 2.403 2.39 2.007 2.113 2.188 2.276 2.228 2.107 2.102 2.158 2.084 2.196 2.179 2.456 2.719 2.181 1.948 2.012 2.213 2.163 2.031 2.355 2.147 2.774 2.345 2.379 2.461 2.477 2.799 MERIT_068 2.533 3.107 1.816 2.73 3.035 2.63 2.78 3.003 2.886 3.306 3.408 2.481 2.899 2.263 3.096 1.835 2.76 2.769 2.566 2.777 2.673 2.566 2.435 3.025 2.72 2.091 2.578 2.754 3.08 3.012 2.5 3.157 3.633 2.579 2.537 1.733 2.262 2.171 0.939 2.191 3.22 1.799 2.05 2.82 2.456 2.339 2.684 2.723 2.356 3.141 2.141 2.154 2.137 2.302 1.871 2.633 2.049 2.335 2.077 2.132 2.533 2.251 2.612 2.201 2.038 2.769 2.121 2.894 1.988 2.315 2.454 2.278 2.374 2.373 2.295 2.37 2.632 MERIT_069 2.01 2.702 1.789 2.462 2.727 2.448 2.452 2.613 2.276 2.747 3.318 2.056 2.311 2.411 2.59 1.929 2.806 2.286 2.133 2.486 2.331 2.458 1.884 2.508 2.558 2.471 2.169 2.313 2.52 2.641 2.425 2.804 2.97 2.295 2.324 2.141 2.307 2.057 0.814 2.007 2.939 1.768 1.887 2.757 2.314 2.303 2.699 2.61 2.225 2.593 1.699 2.156 2.13 2.22 2.041 2.012 2.137 2.104 1.755 1.882 2.207 2.143 2.272 2.049 2.105 2.149 1.973 2.483 2.057 2.35 2.483 1.888 2.272 2.375 2.15 2.276 2.257 2.07 MERIT_070 2.733 2.849 1.941 2.73 2.887 2.824 2.693 2.837 2.9 3.35 3.71 2.313 3.03 2.645 2.719 1.879 2.999 2.847 2.578 2.846 2.825 2.631 2.392 2.88 2.874 2.401 3.025 2.695 2.857 3.08 2.434 3.146 3.461 2.555 2.609 2.262 2.251 2.389 0.818 2.182 3.438 1.988 1.949 3.187 2.326 2.527 2.789 2.994 2.606 2.72 1.904 2.196 2.133 2.384 2.308 2.082 2.139 2.055 2.132 2.348 2.725 2.422 2.503 2.091 2.269 2.276 2.317 2.325 2.208 2.373 2.241 2.353 2.763 2.376 2.58 2.385 2.354 2.338 MERIT_071 2.239 2.892 1.868 2.686 2.828 2.579 2.485 2.651 2.796 3.074 3.501 2.288 2.642 2.254 2.726 1.853 2.847 2.559 2.386 2.575 2.634 2.37 2.217 2.868 2.416 2.396 3.012 2.63 2.923 3.028 2.591 2.919 2.999 2.226 2.384 2.159 2.15 2.19 1.069 2.154 3.059 1.677 2.041 3.154 2.25 1.988 2.696 2.574 2.391 2.686 1.814 2.067 2.089 2.231 2.093 2.067 1.866 2.295 2.095 1.937 2.373 2.142 2.372 2.024 1.942 2.269 2.042 2.456 2.087 2.313 2.172 2.253 1.926 2.045 2.314 2.331 2.314 MERIT_072 2.538 3.057 2.126 2.586 2.308 2.497 2.479 2.99 2.814 3.442 4.026 2.148 2.815 2.783 2.94 2.2 2.928 2.721 2.59 2.763 2.84 2.654 2.401 2.572 2.78 2.48 2.993 2.818 2.862 3.076 2.072 2.953 2.907 2.809 2.635 2.17 2.167 2.503 0.98 2.386 3.274 1.991 1.999 3.669 2.569 2.181 2.734 3.044 2.519 2.083 2.038 2.137 2.267 2.486 2.126 2.038 2.307 1.928 2.221 1.981 2.305 2.098 2.445 2.103 2.363 2.833 2.272 2.183 2.222 2.445 2.365 2.46 2.597 2.43 2.253 2.477 2.401 MERIT_073 2.199 3.044 1.759 2.793 2.7 2.628 2.717 2.733 2.566 3.262 3.647 2.564 2.842 2.371 2.81 2.094 3.19 2.593 2.367 2.732 2.759 2.543 2.128 2.894 2.581 2.649 2.684 2.831 2.88 3.134 2.681 3.25 3.702 2.697 2.336 2.091 2.059 2.341 1.074 2.209 3.446 1.965 1.893 3.499 2.386 2.156 2.628 2.545 2.351 2.767 2.103 2.204 1.966 2.333 1.782 2.107 2.128 2.255 2.024 2.196 2.499 2.37 2.554 2.072 1.922 2.044 2.059 2.163 2.11 2.361 2.582 2.665 2.101 2.374 2.371 2.468 2.479 2.759 MERIT_074 2.925 3.129 1.89 3.034 3.452 2.85 2.842 2.802 2.761 3.185 3.713 2.218 2.779 2.193 2.931 2.21 3.19 2.85 2.595 2.784 2.679 2.45 2.25 2.809 2.559 2.453 2.951 2.836 3.059 2.978 2.578 3.391 3.286 2.344 2.36 2.331 2.502 2.202 1.005 2.111 3.603 2.151 1.966 3.269 2.424 2.186 2.736 2.827 2.56 2.538 2.21 2.214 2.267 2.436 1.867 2.011 1.982 1.916 1.823 1.968 2.144 2.368 2.891 1.992 2.083 1.994 2.134 2.772 1.959 2.344 2.168 2.182 2.604 2.376 2.284 2.362 2.45 2.517 MERIT_075 2.103 2.788 1.679 2.693 3.083 2.536 2.722 2.784 2.447 3.454 3.582 2.299 2.555 2.284 2.651 2.135 2.808 2.607 2.135 2.679 2.672 2.525 2.234 2.783 2.521 2.256 2.802 2.733 2.899 3.002 2.469 3.125 3.401 2.692 2.431 1.89 2.029 2.232 0.808 2.01 3.023 2.014 1.859 3.88 2.274 2.054 2.407 2.516 2.331 2.853 2.191 2.162 2.074 2.465 1.807 2.089 2.066 2.253 2.204 1.915 2.348 2.341 2.438 2.178 1.938 2.271 2.09 2.391 2.114 2.374 2.168 2.654 2.527 2.343 2.289 2.452 2.263 MERIT_076 2.578 2.93 1.821 2.843 2.919 2.725 2.819 2.891 2.703 3.215 3.538 2.336 2.632 2.062 2.983 1.927 3.282 2.824 2.478 2.851 2.709 2.533 2.277 3.182 2.824 2.369 3.166 2.997 3.065 3.261 2.738 3.281 3.486 2.579 2.382 2.204 2.06 2.349 0.977 1.911 3.008 1.858 2.055 2.752 2.422 2.212 3.062 2.699 2.537 2.237 1.884 2.254 2.256 2.448 1.904 2.07 2.021 2.248 2.08 2.184 2.311 2.362 2.859 2.058 2.196 2.801 2.079 2.512 2.162 2.581 2.506 2.621 2.456 2.479 2.33 2.456 2.982 MERIT_077 2.479 2.904 2.082 2.849 2.93 2.942 2.636 2.722 2.999 2.823 3.14 2.318 2.711 2.367 2.879 2.147 2.768 2.949 2.28 2.806 2.705 2.626 2.431 2.623 2.531 2.346 2.777 2.741 2.771 2.86 2.169 3.075 3.038 2.619 2.524 2.262 2.426 2.319 0.952 2.108 2.575 2.051 2.06 3.144 2.349 2.035 2.636 2.777 2.484 2.198 2.088 2.139 2.161 2.345 2.035 2.541 2.09 2.143 1.861 2.052 2.261 2.331 2.381 2.022 1.872 2.13 2.346 2.585 2.189 2.252 2.266 2.951 2.314 1.975 2.206 2.365 2.305 2.098 MERIT_078 2.175 2.854 1.893 2.583 3.067 2.285 2.541 2.764 2.77 3.482 3.428 2.268 2.709 2.351 2.673 1.955 3.44 2.863 2.325 2.633 2.726 2.381 2.241 2.813 2.503 2.823 3.431 2.527 2.851 3.107 2.15 2.994 3.599 2.63 2.203 2.252 2.219 2.251 1.165 1.999 3.76 2.079 1.838 3.001 2.489 2.162 2.539 2.753 2.556 2.431 2.208 1.93 1.777 2.138 1.97 1.975 2.019 2.191 2.012 2.04 2.297 2.477 2.655 1.848 2.292 2.469 2.006 2.446 2.073 2.539 2.202 2.728 2.54 2.568 2.481 2.321 2.327 1.914 MERIT_079 2.557 2.929 2.02 2.702 2.566 2.713 2.678 2.862 2.562 3.182 3.657 2.484 2.766 2.39 2.851 1.977 2.925 2.55 2.559 2.689 2.739 2.393 2.263 3.016 2.553 2.362 2.73 2.61 2.683 2.966 2.389 3.077 3.213 2.543 2.469 2.054 2.23 2.188 0.971 2.201 3.073 1.979 2.163 3.918 2.401 2.089 2.708 2.595 2.345 2.169 2.253 2.126 2.184 2.329 1.745 2.159 2.002 2.203 1.854 2.058 2.29 2.165 2.522 2.045 1.988 2.57 2.12 2.13 2.204 2.293 2.266 1.797 2.235 2.309 2.181 1.982 2.283 2.148 MERIT_080 1.467 2.594 1.668 2.53 2.442 2.249 2.472 2.57 2.606 2.914 3.206 2.334 2.64 2.156 2.792 1.911 3.406 2.565 2.209 2.556 2.699 2.297 2.058 2.628 2.433 2.262 2.599 2.665 2.933 3.098 2.035 2.914 3.51 2.4 2.2 1.523 2.226 2.11 0.799 2.144 3.33 1.836 1.753 2.324 2.202 2.148 2.328 2.507 2.277 2.729 1.871 1.966 1.928 2.211 2.032 2.181 2.013 2.325 2.203 1.899 2.323 2.137 2.65 2.059 2.101 1.996 2.116 1.954 1.995 2.297 2.394 2.336 1.987 2.049 2.253 2.459 2.237 2.281 MERIT_081 2.611 3.087 1.772 2.731 2.668 2.58 2.587 2.695 2.685 3.157 3.634 2.502 2.627 2.37 2.823 1.982 3.453 2.678 2.356 2.615 2.671 2.44 2.263 2.852 2.555 2.087 2.646 2.762 2.79 3.08 2.562 2.875 3.355 2.554 2.213 2.026 2.235 2.403 0.899 2.207 3.211 1.872 1.948 3.29 2.476 2.152 2.869 2.485 2.37 2.486 1.835 2.094 1.96 2.256 1.694 2.009 2.079 2.462 2.161 2.231 2.314 2.296 2.539 2.068 2.204 2.502 2.229 2.683 2.107 2.302 2.307 2.739 2.174 2.366 2.116 2.303 3.09 MERIT_082 2.254 2.764 1.578 2.449 2.744 2.307 2.397 2.633 2.449 2.578 3.23 2.171 2.337 2.008 2.75 1.805 3.208 2.629 1.846 2.421 2.315 2.245 1.932 2.316 2.242 2.276 3.184 2.432 2.817 3.035 1.909 2.815 3.481 2.068 2.235 1.797 2.749 2.075 0.926 2.081 3.35 1.629 1.796 2.463 2.19 1.69 2.745 2.704 2.269 2.305 1.735 1.959 2.075 2.103 1.861 1.814 1.999 2.091 1.723 1.987 2.353 2.116 2.077 2.018 1.852 2.321 2.03 1.851 1.898 2.019 2.227 2.897 2.279 1.807 2.219 2.233 1.871 MERIT_083 3.088 3.075 1.737 2.774 2.835 2.357 2.71 2.896 2.735 2.903 3.923 2.201 2.653 2.164 2.673 1.921 3.053 2.484 2.479 3.043 2.677 2.508 2.327 2.896 2.585 2.456 3.348 2.343 2.97 3.138 2.1 2.989 3.747 2.383 2.669 2.778 2.597 2.114 0.998 1.977 3.294 1.732 1.911 3.5 2.426 1.879 2.782 2.756 2.501 2.591 1.805 2.262 2.252 2.451 2.14 2.203 1.938 1.895 1.697 2.067 2.273 2.432 2.604 2.143 2.379 2.561 2.059 2.428 1.986 2.336 2.328 2.24 2.471 2.808 2.117 2.482 2.355 2.638 MERIT_084 2.224 2.795 1.87 2.78 2.368 2.734 2.698 2.682 2.941 2.956 3.948 2.19 2.463 2.264 2.71 2.026 3.294 2.722 2.317 2.777 2.769 2.418 2.229 2.801 2.605 2.592 3.361 2.824 2.806 2.913 2.362 3.141 3.38 2.382 2.429 1.856 2.316 2.387 1.037 1.991 3.506 1.917 1.748 2.774 2.343 2.094 2.717 2.792 2.503 2.626 2.042 2.096 1.988 2.297 1.979 2.317 2.05 2.194 1.755 1.919 2.507 2.529 2.788 1.735 2.44 2.301 2.128 2.164 2.103 2.38 2.249 2.585 2.464 2.509 2.159 2.13 2.382 2.538 MERIT_085 2.306 2.763 1.875 2.587 2.692 2.56 2.685 2.725 2.633 3.072 3.331 2.393 2.748 2.21 2.83 2.067 3.029 2.634 2.406 2.664 2.734 2.563 2.381 2.817 2.53 2.064 2.744 2.519 2.836 2.96 2.217 3.018 3.115 2.653 2.447 1.781 2.176 2.312 1.04 2.152 3.531 1.913 1.97 3.27 2.336 2.125 2.603 2.628 2.357 2.309 1.776 2.168 2.225 2.396 2.087 1.767 2.081 2.054 2.017 2.118 2.187 2.35 2.194 2.18 2.058 2.523 2.02 1.846 2.228 2.204 2.177 1.943 2.444 2.394 2.341 2.425 2.384 2.244 MERIT_086 2.25 2.888 1.781 2.586 2.816 2.544 2.44 2.533 2.525 3.025 3.591 2.109 2.388 2.085 2.527 1.856 2.911 2.69 2.093 2.374 2.414 2.164 1.985 2.401 2.524 2.355 3.381 2.471 2.605 2.813 2.391 2.921 3.28 2.383 2.106 1.933 2.099 2.107 0.842 1.906 3.324 1.63 1.896 2.034 2.2 2.046 2.637 2.571 2.37 2.344 1.722 1.947 1.792 2.258 1.838 1.841 1.892 1.922 1.679 1.77 1.989 2.331 2.406 1.715 2.275 2.348 1.961 2.141 1.884 2.177 2.111 2.095 2.295 2.066 2.188 2.04 2.174 2.379 MERIT_087 2.614 2.879 1.729 2.629 2.321 2.696 2.512 2.621 2.654 2.974 3.697 2.384 2.482 1.936 2.525 1.811 3.066 2.616 2.252 2.631 2.593 2.39 2.023 2.6 2.409 2.31 2.895 2.597 2.701 2.9 2.408 2.926 3.328 2.419 2.241 2.066 1.885 2.099 0.959 1.932 3.122 1.668 1.879 3.547 2.301 1.966 2.315 2.913 2.249 2.142 1.649 2.067 2.002 2.265 1.896 2.203 1.986 2.018 1.717 2.026 2.026 1.943 2.298 1.973 2.026 1.977 2.224 2.324 1.944 2.259 2.077 2.046 2.389 2.283 2.128 2.209 2.281 2.251 MERIT_088 2.453 2.936 1.719 2.696 2.602 2.781 2.634 2.785 2.783 3.022 3.518 2.185 2.61 2.152 2.574 1.842 2.855 2.759 2.231 2.851 2.717 2.524 2.342 2.767 2.62 2.768 3.465 2.802 2.661 3.253 2.145 3.139 3.545 2.213 2.636 2.411 2.244 2.157 0.926 2.27 3.675 1.823 1.875 2.803 2.373 2.073 2.647 2.39 2.377 2.353 2.053 2.082 2.145 2.224 1.918 2.18 2.005 2.042 2.034 1.937 2.132 2.296 2.228 2.174 2.272 2.068 2.169 2.324 2.108 2.446 2.298 2.04 2.09 2.558 2.648 2.09 2.428 1.933 MERIT_089 2.557 3.209 1.89 2.757 3.011 2.829 2.74 3.066 2.736 3.053 3.922 2.468 2.67 2.229 2.914 2.06 3.264 2.914 2.448 2.754 2.789 2.507 2.231 2.969 2.766 2.444 2.894 2.689 2.971 3.048 2.182 2.892 3.322 2.617 2.455 1.937 2.014 2.218 0.949 2.203 3.262 1.914 1.955 3.903 2.423 2.206 3.051 2.804 2.458 2.737 2.334 2.151 2.058 2.498 2.022 2.41 2.059 2.2 2.041 2.041 2.404 2.751 2.432 1.493 2.243 2.235 2.128 2.559 2.171 2.366 2.435 1.825 2.179 2.136 2.458 2.311 2.517 1.975 MERIT_090 2.367 2.945 1.758 2.733 2.784 2.722 2.602 2.821 2.685 2.961 3.568 2.313 2.547 2.242 2.834 1.992 2.846 2.671 2.284 2.616 2.546 2.433 2.274 2.9 2.624 2.544 3.093 2.774 2.954 3.088 2.56 3.151 3.487 2.4 2.507 2.253 2.395 2.359 0.988 2.06 3.425 1.799 1.925 3.469 2.383 2.095 2.503 2.694 2.561 2.467 2.09 2.246 2.189 2.358 2.053 2.144 1.936 2.114 1.546 1.8 2.089 2.246 2.404 2.052 2.1 1.985 2.067 2.374 1.964 2.292 2.32 2.294 2.611 1.892 2.196 2.476 2.284 2.95

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apply inverse transform
by Martin Chadwick 24 Jun '09

24 Jun '09

Dear freesurfers, I'm new to freesurfer and have a problem using --apply_inverse_transform with the .m3z warp. Any help would be greatly appreciated: I've been running a multivariate fmri decoding study, and have used freesurfer to generate anatomical masks which I've used as ROIs for the multivariate analysis in the native space of each subject. I then took the pattern of informative voxels from each subject as a binary mask, and warped it into standard space using the freesurfer high-dimensional warp (I am looking at subcortical structures, so this level of registration accuracy is quite important) with the following command: mri_convert -ot nifti1 ~/inputimage --apply_transform ~/transforms/talairach.m3z ~/outputimage.img Which seems to have worked fine. I've then performed some overlap analyses on these warped binary images, and created a new binary image representing the between-subject overlap. What I really want to do next is to warp this back into the native space for each subject and use as an ROI for further multivariate analyses. To do this I tried the following command: mri_convert -it nifti1 -ot nifti1 ~/inputimage.img --apply_inverse_transform ~/transforms/talairach/m3z ~/outputimage.img which gave me the following error message: mriBuildVoronoiDiagramFloat: incorrect input type(s) Any ideas on what I'm doing wrong here? Many thanks, Martin

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make_average_subject error about limit
by Feng-Xian 24 Jun '09

24 Jun '09

Hi, I have a problem with make_average_subject. After running all commands about running QDEC, I found that QDEC could not analysis my group. Because the group I want to analysis have 1 factor and three levels, QDEC can't run. So, I want to change the method of analysis from QDEC to FSGD. But, I have a problem about FSGD. When I type: make_average_subject --subects <subjid1> <subjid2> ... the terminal show that: limit: descriptors: Can't remove limit (此項操作並不被允許) What's wrong about the command I type? And, how to solve the problem? Thank you in advance! Feng-Xian ------------------------------------------------- Chang Gung University Mail Server Web Mail system By Chang-Gung University Information Center (http://www.cgu.edu.tw/ic/)

1 0

volume group analysis
by Anita di Iasio 23 Jun '09

23 Jun '09

Hi all, I follow the tutorial on group analysis. But the example is surface-based. I looked for something similar in freesurfer archive, but I can't find anything. Can someody helps me to do a volume-based group-analysis? which flag do I use with mris_preproc and mri_glmfit? for example I need to compare white matter volume....I think should be similar with other volumes, don't I? In the end....to visualize the results, what shall I use? perhaps the tkmedit command? Thanks, Anita

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R: Re: R: Re: [Freesurfer] Qdec
by free_surfer＠virgilio.it 23 Jun '09

23 Jun '09

Dear Nick, we were able to use Qdec upon your suggestions. Many thanks. Since we are going to download the last version of FS (with a newer Qdec) on another workstation, would you suggest to use the new Qdec for our data processed by FS 4.0.2. If yes, can you briefly tell us which are the main differences and advantages of the newer Qdec? Many thanks, Antonio >----Messaggio originale---- >Da: nicks(a)nmr.mgh.harvard.edu >Data: 22-giu-2009 12.49 >A: "free_surfer(a)virgilio.it"<free_surfer(a)virgilio.it> >Cc: "Freesurfer Mailing List"<freesurfer(a)nmr.mgh.harvard.edu>, "Allison Stevens"<astevens(a)nmr.mgh. harvard.edu> >Ogg: Re: R: Re: [Freesurfer] Qdec > >Antonio, > >The Generate Stats Data Table feature was added in the v4.3.0 release of >freesurfer. Its not necessary to perform an analysis, only to aid in >the import of the morphometric measures from the recon-all stream (like >hippocampal volume). > >You should be able to goto to the Design tab and conduct and analysis >with your age and white covariates. > >Nick > > >On Mon, 2009-06-22 at 10:03 +0200, free_surfer(a)virgilio.it wrote: >> Hi Allison, >> I send you the snapshot of qdec. >> Thanks, >> Antonio >> >> Antonio, >> Can you >> describe what qdec is showing that's wrong or send a screenshot >> of >> it? >> Thanks, >> >> Allison >> >> -- >> >> On Thu, 18 Jun 2009, free_surfer(a)virgilio.it wrote: >> >> > Dear >> Freesurfer users, >> > We are experiencing a problem using Qdec (FS version >> > >> 4.2.0; Qdec 1.0) for group data analysis. >> > Indeed, the qdec display [after >> > >> creating the qdec.table.dat and the <factor>.levels files] >> doesn't visualize >> > >> properly (as in the tutorial) the Data Table View and other >> window-options that >> >> > should allow us to select "Generate Stats Data Table" and >> proceed with the >> > >> group analysis. >> > >> > Any suggestion would be greatly appreciated. >> > >> > Many >> Thanks in >> > advance for your help, >> > >> > Antonio Gallo, MD, PhD >> > Department of >> Neuroscience >> > >> > Second University of Naples >> > Ph: +39-081-5665090 >> > >> > >> > >> _______________________________________________ >> > Freesurfer mailing list >> > >> Freesurfer(a)nmr.mgh.harvard.edu >> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>>> > >> > >> >> _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > >_______________________________________________ >Freesurfer mailing list >Freesurfer(a)nmr.mgh.harvard.edu >https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>

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Re: [Freesurfer] concerning my posting: curvature file'lh.area.mid' has wrong magic number - add logfile
by Oliver Grimm 23 Jun '09

23 Jun '09

Hi! Thanks for the replies! 1. I think, I need some help with the stats output of mris_calc: e. g. mris_calc lh.area stats gives me mris_calc lh.area stats mris_calc: Insufficient number of arguments. You should specify '<curvFile1> <ACTION> <curvFile2>' Use a '-u' for full usage instructions. which is a quite humiliating error message, isn't it ... 2. A look into the /surf/ directory shows that lh.area.mid has a size of zero byte. That does not look very sensible. 3. Disk-Space: I am running my experiments on a NAS with >300 MB free diskspace. Even my local computer has some GB's left and I don't see anything written locally. Memory and processor speed should be enough (4 MB quad-core). 2009/6/23 Grimm, Oliver <Oliver.Grimm(a)zi-mannheim.de> > > ------------------------------------------- > *Von:* freesurfer-bounces(a)nmr.mgh.harvard.edu im Auftrag von Nick > Schmansky[SMTP:NICKS@NMR.MGH.HARVARD.EDU<SMTP%3ANICKS(a)NMR.MGH.HARVARD.EDU>] > > *Gesendet:* Dienstag, 23. Juni 2009 01:04:35 > *An:* Grimm, Oliver > *Cc:* Freesurfer Mailing List > *Betreff:* Re: [Freesurfer] concerning my posting: curvature > file'lh.area.mid' has wrong magic number - add logfile > *Diese Nachricht wurde automatisch von einer Regel weitergeleitet.* > > Oliver, > > That's a strange error. Did you run out of disk space? I can only > think of that as a reason for a corrupted curvature file. > > Nick > > On Mon, 2009-06-22 at 14:00 +0200, Oliver Grimm wrote: > > Hi! > > > > I just mentiones my error > > > > curvature file 'lh.area.mid' has wrong magic number > > > > on a openSUSE 11.1 system: > > > > /data/MOODS2/freesurfer/1005/surf > > > > mris_calc -o lh.area.mid lh.area add lh.area.pial > > > > > > mris_calc -o lh.area.mid lh.area.mid div 2 > > > > > > mris_calc -o lh.volume lh.area.mid mul lh.thickness > > > > > > mris_calc: curvature file 'lh.area.mid' has wrong magic number. > > > > Linux impsy-pc4 2.6.27.19-3.2-default #1 SMP 2009-02-25 15:40:44 +0100 > > x86_64 x8 > > 6_64 x86_64 GNU/Linux > > > > recon-all exited with ERRORS at Sat Jun 20 00:17:58 CEST 2009 > > > > > > I forgot to attach the recon-all.log for further details. I attached > > it. > > > > Thank you for your held, > > > > Oliver Grimm > > > > > > > > -- > > Dr. med. Oliver Grimm > > Zentralinstitut für Seelische Gesundheit > > Institut für Neuropsychologie und Klinische Psychologie & > > AG Imaging in der Psychiatrie > > J5 > > 68159 Mannheim > > > > Tel: +49-621-1703-6341 > > Fax: +49-621-1703-6305 > > email oliver.grimm(a)zi-mannheim.de > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer(a)nmr.mgh.harvard.edu > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > _______________________________________________ > Freesurfer mailing list > Freesurfer(a)nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > -- Dr. med. Oliver Grimm Zentralinstitut für Seelische Gesundheit Institut für Neuropsychologie und Klinische Psychologie & AG Imaging in der Psychiatrie J5 68159 Mannheim Tel: +49-621-1703-6341 Fax: +49-621-1703-6305 email oliver.grimm(a)zi-mannheim.de

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How to rerun recon-all after modifying talairach registration manually?
by Zhen Zonglei 22 Jun '09

22 Jun '09

Hi all: After autorecon1 was done, I corrected the talairach registration manually. Next, I rerun autorecon1 on the data, but tal_check still gave the same talAviQA and z-score as non-corrected. What's the problem? Is it necessary to rerun autorecon1? Can we skip autorecon1 and do autorecon2 directly? My version is FreeSurfer4.3. Thanks. Zonglei Zhen -- Zonglei Zhen, PhD Assistant Professor of Cognitive Neuroscience BNU Imaging Center for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, P.R. China

2 2

concerning my posting: curvature file 'lh.area.mid' has wrong magic number - add logfile
by Oliver Grimm 22 Jun '09

22 Jun '09

Hi! I just mentiones my error curvature file 'lh.area.mid' has wrong magic number on a openSUSE 11.1 system: /data/MOODS2/freesurfer/1005/surf mris_calc -o lh.area.mid lh.area add lh.area.pial mris_calc -o lh.area.mid lh.area.mid div 2 mris_calc -o lh.volume lh.area.mid mul lh.thickness mris_calc: curvature file 'lh.area.mid' has wrong magic number. Linux impsy-pc4 2.6.27.19-3.2-default #1 SMP 2009-02-25 15:40:44 +0100 x86_64 x8 6_64 x86_64 GNU/Linux recon-all exited with ERRORS at Sat Jun 20 00:17:58 CEST 2009 I forgot to attach the recon-all.log for further details. I attached it. Thank you for your held, Oliver Grimm -- Dr. med. Oliver Grimm Zentralinstitut für Seelische Gesundheit Institut für Neuropsychologie und Klinische Psychologie & AG Imaging in der Psychiatrie J5 68159 Mannheim Tel: +49-621-1703-6341 Fax: +49-621-1703-6305 email oliver.grimm(a)zi-mannheim.de

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