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Here is a combined dataset of genetic data on 2,643 individuals from 163 worldwide human populations. These genotypes were all generated on Illumina chips (550, 610, 660) for multiple different studies. The two main papers that this dataset was compiled for are: Hellenthal, et al 2014 A Genetic Atlas of Human Admixture History, Science; and Busby, et al 2015 The role of recent admixture in forming the contemporary West Eurasian genomic landscape, Current Biology. The data are in PLINK format and the BusbyWorldwidePopulations.csv file outlines where the different datasets come from. Note that because these two datasets were combined together, not all populations are typed on the same set of SNPs. We have included genotype data on 523,443 SNPs, of which 441,038 are genotyped on at least 97.5% of individuals. Therefore, additional QC steps are required to filter this set down to high quality calls, depending on the subset of samples that are required. Complete information about the populations used is available in the various publications that are outlined in the associated paper. Note that these same populations are available elsewhere and this dataset represents that compiled for the above mentioned papers. UPDATE 11/11/2019 Thanks to some heroic work by Kristján Helgi Swerford Moore at DECODE, I have now updated the population and sample information to more accurately and verbosely label the individuals.
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Files for Hardware design for build a Step Width System Capture
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This dataset contains the raw NMR data from the paper "15N Stable Isotope Labeling and Comparative Metabolomics Facilitates Genome Mining in Cultured Cyanobacteria" for the compounds aeruginosin 865, anabaenopeptin UIC827, and Nostopyrrolidonamide. The compounds were all identified using a stable isotope labeling-comparative metabolomics approach. The following dataset contains: 1H NMR spectrum (800 MHz, MeOH-d4) of aeruginosin 865 1H NMR spectrum (800 MHz, MeOH-d4) of anabaenopeptin UIC827 1H NMR spectrum (900 MHz, MeOH-d4) of Nostopyrrolidonamide DEPTQ spectrum (226 MHz, DMSO-d4) of Nostopyrrolidonamide COSY spectrum (800 MHz, MeOH-d4) of Nostopyrrolidonamide HSQC spectrum (800 MHz, MeOH-d4) of Nostopyrrolidonamide HMBC spectrum (800 MHz, MeOH-d4) of Nostopyrrolidonamide ROESY spectrum (800 MHz, MeOH-d4) of Nostopyrrolidonamide 15NHSQC spectrum (900 MHz, MeOH-d3) of Nostopyrrolidonamide 15NHMBC spectrum (900 MHz, MeOH-d3) of Nostopyrrolidonamide
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Behavioral output from subjective ratings and memory response times during fMRI task. Output from a spatiotemporal and hippocampal-seed PLS analysis. Preprocessed fMRI contributing to the neuroimaging analysis.
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In this article, we present a load cell dataset of torques and force during a tele-operated robotic Gas Tungsten Arc Welding in presence of collisions. The dataset comprises raw data of 15 tests with four columns sorted as in Table 1. First column Second column Third column Fourth column Torque on x-axis Torque on y-axis Force on x-axis Collisions Table 1 Description of the raw data columns Torques are numerical values expressed in [Nm] while force values are expressed in [N]. Collisions column, instead, are zeros/ones values indicating whether a collision is verified (i.e., ones values) or not (i.e., zeros values). In addition, tests data are provided in .mat files for eventual processing in Matlab software.
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This dataset contains supporting documentation explaining the use of time-dependent concrete material models TDConcrete, TDConcreteEXP, TDConcreteMC, and TDConcreteMC10NL in OpenSees. The dataset contains a manual explaining the use and features of the models, an Excel table for calculating model input parameters and example files using the material model TDConcreteMC10NL on a specific example.
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Matlab code to implement the fill factor estimation including raw data
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A study of anisotropic characteristics based on shear wave splitting parameters (fast shear wave polarization and delay time) was carried out from microearthquakes recorded from a network of fifteen seismic stations temporarily installed in Los Humeros Volcanic Complex, Puebla, Mexico from 2011 to 2016. This analysis determined the effects on seismic activity caused by fluid injection, as well as possible variations of the tectonic stress regime by changes in both parameter, where most of the fast shear wave polarization results correlate with the orientation of the main geological structures that tend mainly NW – SE and follow the inferred Malpais, Antigua, Iman and Nueva faults with some secondary polarizations E – W and WNW - ESE related to minor local faults (employing the values of azimuths) in the tectonic ambient and effects generated by variations in pore pressure of fluid injection. On the other hand, the annual tendency for both parameters shows a significant change from September 2014 to June 2016, based on statistical tests that indicates that possible changes in the stress level are due to an increase in fluid injection. Graphs of the annual averages from 2014 to 2016, also indicate a change in the stress level (decrement), similar to our results of fast shear-wave polarizations, also confirmed by a t-test. The delays results have allowed characterizing the main routes of permeability in the geothermal field, indicating the Los Humeros Fault, and the inferred Antigua and Malpaís faults as the main routes from internal heat sources. The database, consisting of the results of both parameters (fast shear wave polarization and delay time), allows interpreting them in a general analysis for the period studied, by years, months or by areas, since all have been referred to a seismic station, which also allows a local analysis. Likewise, raw data related to the hypocentral parameters of the seismic events employed are also available, allowing to know more about the characteristics of the phenomenon. For example, the raw data of Figure 4 are represented by columns of years, latitudes, longitudes, depths, and magnitudes, which can show the locations of the seismic events registered from 2011 to 2016; the filtered and analyzed data of Figure 6 are represented by columns with the number of azimuths (left) and the value of azimuth (right) of each seismic station, which can be represented by rose diagrams for the studied period 2011 –2016; the filtered and analyzed data of Figure 8 are represented by a columns of time (left), and values of the azimuth parameter (right), which can be depicted by graphs of individual values and annual averages of the azimuth parameter; or the analyzed data in Table 6 are represented by a column with the values of the delay time parameter of each station, which allow to calculate the mean delay time and the standard deviations.
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Accompanying data for article 'Co-speech movement in conversational turn-taking,' submitted to the journal Speech Communication
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This Mendeley Data repository "EOCG Model" contains R code to run Empirical Orthogonal Constraint Generation (EOCG), a model aimed at learning a reduced set of dimensions to solve a Multidimensional Knapsack Problem (MKP). The R code also runs the two models ORIGINAL and HYP. The code has been used in the following research article: T. Setzer and S. M. Blanc, Corrigendum to “Empirical Orthogonal Constraint Generation for Multi-Dimensional 0/1 Knapsack Problems” [European Journal of Operational Research, 282, 1 (2020), 58–70], https://doi.org/10.1016/j.ejor.2019.12.029. Corresponding author: Thomas Setzer, E-mail address: thomas.setzer@ku.de. (DOI of original article: https://doi.org/10.1016/j.ejor.2019.09.016). Computational results presented in the referenced manuscript are available in folder R/Results. Guidance on how to read result files is provided in R/Results/readresults.txt.
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