cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k6jybymbrj.1
title: Data for: When are women willing to lead? The effect of team gender composition and gendered tasks
DOI: 10.17632/3vmctzkygb.1
title: Semantics of Color, Tableware, and Prepositions (denoting spatial relations). Dataset Belarusian language

description: Semantics of Color, Tableware, and Prepositions (denoting spatial relations). / by method mpi.nl / dialects study task by http://eoss.nl/elicitation/ https://archive.mpi.nl/islandora/object/lat%3A1839_00_0000_0000_0021_209D_0
DOI: 10.5281/zenodo.3341769
title: CMS 2011A Simulation | Pythia 6 QCD 1400-1800 | pT &gt; 375 GeV | MOD HDF5 Format

description: Simulated QCD jets from the Simulated QCD 1400-1800 Dataset of the CMS 2011 Open Data reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. For reference, the other corresponding datasets of simulated jets available on Zenodo are: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV There is an associated dataset of jets recorded by the CMS detector available on Zenodo: CMS 2011A Jets, pT &gt; 375 GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.5281/zenodo.3341770
title: CMS 2011A Simulation | Pythia 6 QCD 1400-1800 | pT &gt; 375 GeV | MOD HDF5 Format

description: Simulated QCD jets from the Simulated QCD 1400-1800 Dataset of the CMS 2011 Open Data reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. For reference, the other corresponding datasets of simulated jets available on Zenodo are: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV There is an associated dataset of jets recorded by the CMS detector available on Zenodo: CMS 2011A Jets, pT &gt; 375 GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.17632/nfkkdz45rt.1
title: Dataset for Localization and Estimation of Bending and Twisting Loads from Depth Images
DOI: 10.17632/pm8z3ppb87.1
title: Prenatal Mercury Exposure and Postnatal Outcome: A Case Series in Bogotá, Colombia

description: We report fourteen cases with high mercury (Hg) levels. The intake of certain river fish species (catfish, tuna and tilapia) could be related with the exposure. We evaluate exposure biomarkers and susceptibility biomarkers; these last ones, are novel and can guide new studies in environmental toxicology. These results are significant because we found some similarities with the literature, among them, the relation of Hg ratio in maternal blood and umbilical cord, a possible exposure factor is fish consumption during pregnancy. High levels of Hg may be related with susceptibility biomarkers such as GSTs gene polymorphisms. This case series highlights the need to develop studies that evaluate the interactions between environmental factors and individual genetic susceptibility. Additionally, the importance of evaluating which Colombian fish species present the highest levels of Hg.
DOI: 10.21227/8ht5-hw76
title: Correlation matrix of the items of the Six Sigma CSF survey in HEIs

description: The correlation matrix and the survey items are provided for the design and validation of an instrument to evaluate the implementation of six sigma critical success factors during the realization of improvement projects in higher education institutions.
DOI: 10.21227/9znz-2j19
title: Correlation matrix of the items of the Six Sigma CSF survey in HEIs

description: The correlation matrix and the survey items are provided for the design and validation of an instrument to evaluate the implementation of six sigma critical success factors during the realization of improvement projects in higher education institutions.
DOI: 10.5281/zenodo.3340204
title: CMS 2011A Open Data | Jet Primary Dataset | pT &gt; 375 GeV | MOD HDF5 Format

description: A dataset of 1,785,625 jets from the Jet Primary Dataset of the CMS 2011A Open Data reprocessed into the MOD HDF5 format. Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor. Particle Flow Candidates (PFCs) for each jet are provided and include information about the PFC kinematics, PDG ID, and vertex. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. There are corresponding datasets of simulated jets organized by hard parton \(\hat p_T\) also available on Zenodo: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.5281/zenodo.3340205
title: CMS 2011A Open Data | Jet Primary Dataset | pT &gt; 375 GeV | MOD HDF5 Format

description: A dataset of 1,785,625 jets from the Jet Primary Dataset of the CMS 2011A Open Data reprocessed into the MOD HDF5 format. Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor. Particle Flow Candidates (PFCs) for each jet are provided and include information about the PFC kinematics, PDG ID, and vertex. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. There are corresponding datasets of simulated jets organized by hard parton \(\hat p_T\) also available on Zenodo: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.17632/np2r2k24rp.1
title: Claustrophobia

description: Claustrophobia VR project raw data
DOI: 10.17632/cm27w42ff3.1
title: Supplementary Appendix - Pharmacokinetics and Safety of Apremilast in Pediatric Patients With Moderate to Severe Plaque Psoriasis: Results From a Phase 2 Open-Label Study
DOI: 10.5066/p9xf3c11
title: Base flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version

description: Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release and study, we derived alpha from a groundwater flow coefficient (gwflow_coef) defined in the National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS) (Regan et al., 2018). The second parameter, beta, is defined as the maximum value of the base flow index (Eckhardt, 2005). Beta is optimized using specific conductance and mass balance techniques, where a hydrograph is split into quick flow and base flow and specific conductance values are proposed for these streamflow components. OHS uses two model types to estimate base flow specific conductance from stream specific conductance, referred to as 'SCfit' and 'sin-cos' model types. The 'SCfit' model type uses a peak-fitting algorithm to define time periods where the stream is entirely comprised of base flow, whereas the 'sin-cos' model type emulates seasonal variation in streamflow specific conductance with a sine-cosine function to pinpoint when base flow contributes to streamflow. For more information and equations regarding model type and OHS methods, please see the associated publication (Foks et al., 2019). OHS was applied to 1076 stream gages within the conterminous United States (CONUS) where daily streamflow and daily or discrete measurements of specific conductance were collected. Gages were selected for this method if they were of "reference quality" as defined by the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) dataset (Falcone, 2011). Of these 1076 sites, 825 had "successful" OHS models - implying good agreement between observed and simulated stream specific conductance. This data release contains the results of applying OHS to hundreds of stream gages of varying watershed characteristics, summary of watershed and hydro-climatological characteristics for each site (Falcone, 2011; USGS, 2003), and a comparison of OHS-defined base flow to base flow -analogous flow components within the NHM-PRMS (gwres_flow and slow_flow) (Regan et al., 2018; Regan et al., 2019). For this data release and study, comparisons of OHS-defined base flow were made to the "by HRU" calibration of the NHM-PRMS (Hay, 2019).
DOI: 10.17632/ft3ftwzxgw.1
title: Data for: Cognitive Evolutionary Therapy versus Standard Cognitive Therapy for Depression: A Single-Blinded Randomized Clinical Trial

description: Depression is one of the most common mental disorders and the leading cause of disability worldwide. Despite the benefits of the current treatments, continued efforts are needed to improve existing interventions or create new ones. This dataset contains the research data of a randomized controlled clinical trial which compared the efficacy of Cognitive-Evolutionary Therapy for depression to Cognitive Therapy for depression.
DOI: 10.17632/ft3ftwzxgw.2
title: Data for: Cognitive Evolutionary Therapy versus Standard Cognitive Therapy for Depression: A Single-Blinded Randomized Clinical Trial

description: Depression is one of the most common mental disorders and the leading cause of disability worldwide. Despite the benefits of the current treatments, continued efforts are needed to improve existing interventions or create new ones. This dataset contains the research data of a randomized controlled clinical trial which compared the efficacy of Cognitive-Evolutionary Therapy for depression to Cognitive Therapy for depression.
DOI: 10.5066/p9lgxdj8
title: Data sets related to Wetland extent maps for 12 stream reaches covering approximately 750 river miles in Indiana

description: Potential wetland extents were estimated for 12 river reaches covering approximately 750 river miles in Indiana. The study was completed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS). This study follows and adds to the work completed in the pilot study (Kim and others, 2012) and shows that potential wetland extents can be estimated using streamflow statistics, streamgage data, and flood-inundation mapping techniques. The study was designed to assist in the Agricultural Conservation Easement Program (ACEP). The ACEP is a voluntary program administered by the NRCS. It provides technical and financial assistance to private landowners and Tribes to restore, protect, and enhance wetlands in exchange for retiring eligible land from agriculture. For a site to be eligible for wetland restoration, it should be in a zone with sustained or frequent flooding. This study calculated the flows that occurred for a period of seven consecutive days on average at least once every two years (a value termed the 7MQ2) for all the U.S Geological Survey streamgages within the selected river reaches. These 7MQ2 flows were related to the stage-discharge tables for each streamgage and a corresponding water-surface elevation was determined. Maps of estimated wetland extent were prepared using the 7MQ2 inundation elevation data in conjunction with bare-earth land surface elevation data made publicly available through the online geospatial data clearinghouses of Indiana, Illinois, and Ohio. Flood-inundation mapping techniques were applied with the aid of Geographic Information System (GIS) software to generate water-surface planes that represent inundation elevations associated with the 7MQ2 streamflow. Land-surface elevation data from high-resolution digital elevation models (DEMs) were subtracted from the water-surface planes to produce maps of wetland extent. The 12 map products, including data sets and geoprocessing tools, produced from this study will aid the NRCS and its partners with the onsite inundation-zone verification in agricultural land for potential restoration.
DOI: 10.6082/uchicago.1932
title: Geomasking Archaeological Site Points

description: A zip folder holding a set of five point shapefiles, including: one sample of observed, non-sensitive archaeological sites in Wyoming; one set of geomasked points produced using a donut method; and three sets of geomasked points derived from a low resolution, georeferenced maps at the scales of 1:100000, 1:5000000, and 1:20000000.
DOI: 10.7910/dvn/ovs1pc/h3oism
title: README.txt

description: :unav
DOI: 10.5281/zenodo.3341771
title: CMS 2011A Simulation | Pythia 6 QCD1800-inf | pT &gt; 375 GeV | MOD HDF5 Format

description: Simulated QCD jets from the Simulated QCD 1800-\(\infty\) Dataset of the CMS 2011 Open Data reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. For reference, the other corresponding datasets of simulated jets available on Zenodo are: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV There is an associated dataset of jets recorded by the CMS detector available on Zenodo: CMS 2011A Jets, pT &gt; 375 GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.5281/zenodo.3341772
title: CMS 2011A Simulation | Pythia 6 QCD1800-inf | pT &gt; 375 GeV | MOD HDF5 Format

description: Simulated QCD jets from the Simulated QCD 1800-\(\infty\) Dataset of the CMS 2011 Open Data reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets). Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have \(p_T^\text{jet}&gt;375\) GeV, where \(p_T^\text{jet}\) includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain truth-level particles with kinematic and PDG ID information, and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files. For additional details about the dataset, please see the accompanying paper, Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have \(|\eta^\text{jet}|&lt;1.9\) to ensure tracking coverage and (in the case of SIM) have "medium" quality to reject fake jets. The supported method for downloading, reading, and using this dataset is through the EnergyFlow Python package, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please submit an issue on GitHub. For reference, the other corresponding datasets of simulated jets available on Zenodo are: SIM/GEN QCD Jets 170-300 GeV SIM/GEN QCD Jets 300-470 GeV SIM/GEN QCD Jets 470-600 GeV SIM/GEN QCD Jets 600-800 GeV SIM/GEN QCD Jets 800-1000 GeV SIM/GEN QCD Jets 1000-1400 GeV SIM/GEN QCD Jets 1400-1800 GeV SIM/GEN QCD Jets 1800-\(\infty\) GeV There is an associated dataset of jets recorded by the CMS detector available on Zenodo: CMS 2011A Jets, pT &gt; 375 GeV
description: {"references": ["P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}
DOI: 10.17632/n5gx5mgfrv.1
title: Data for "I Believe I Can Craft! Introducing Job Crafting Self-efficacy Scale (JCSES)"

description: Job crafting has many positive consequences for employees and organizations. To better predict these behaviors, we introduce the concept of job crafting self-efficacy (JCSE) derived from Theory of Planned Behavior, Social Cognitive Theory, and Job Demands-Resources model. We define JCSE as an individual’s beliefs about their capability to modify demands and resources of their job. This article describes development and validation of a scale to measure JCSE. We conducted a qualitative study to design and four quantitative studies to test the psychometric properties of the JCSE Scale among Polish and American employees in both paper-and-pencil and online versions. Three independent confirmatory (N1 = 364; N2 = 432; N3 = 403) factor analyses demonstrated a good fit to a 3-factor solution comprising JCSE beliefs about increasing (1) structural job resources, (2) social job resources, and (3) challenging job demands. The final, 9-item version of JCSE Scale had good internal consistency, high time stability, and good convergent and criterion validity. It correlated positively with general self-efficacy and relevant job crafting dimensions. In addition, JCSE explained unique variance in job crafting behaviors over and above general self-efficacy. We also found that the JCSE beliefs were more important in predicting job crafting than organizational opportunities to craft. This research demonstrates the role of social cognitions in shaping job redesign behaviors and provides a useful tool to evaluate the effectiveness of interventions dedicated to empower JCSE. Keywords: job crafting, self-efficacy, psychometric validation; Social Cognitive theory, Job Demands-Resources (JD-R) theory
DOI: 10.7910/dvn/rm940e/6mjf76
title: 002_codebook_PROMIS-Mali_FollowupChildMonthPlatform.pdf

description: :unav
DOI: 10.7910/dvn/rm940e/hkcxdm
title: 003_dataset_PROMIS-Mali_FollowupChildMonthPlatform.tab

description: :unav
DOI: 10.7910/dvn/rm940e/asprll
title: 001_questionnaire_PROMIS-Mali_Longitudinal_enrollmentFollow-up.pdf

description: :unav