cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20443584
title: PROMISE data

description: College enrollment data
DOI: 10.6084/m9.figshare.20443584.v1
title: PROMISE data

description: College enrollment data
DOI: 10.5281/zenodo.8262424
title: AMOC Hysteresis

description: These directories contain Python (v3) scripts for plotting/analysing model output. Python scripts can be found in the directory 'Program'. Model output can be found in the directory 'Data'. The processed model output are stored as NETCDF files and using the relevant scripts one can regenerate all the figures. We provided the original model output (native grid) and is only converted to yearly-averaged data (due to storage limitations). Some scripts (e.g., FOV_index.py and AMOC_transport.py) use the original model output and running these script generates in the time series, which are presented in the manuscript.
DOI: 10.5281/zenodo.8262423
title: AMOC Hysteresis

description: These directories contain Python (v3) scripts for plotting/analysing model output. Python scripts can be found in the directory 'Program'. Model output can be found in the directory 'Data'. The processed model output are stored as NETCDF files and using the relevant scripts one can regenerate all the figures. We provided the original model output (native grid) and is only converted to yearly-averaged data (due to storage limitations). Some scripts (e.g., FOV_index.py and AMOC_transport.py) use the original model output and running these script generates in the time series, which are presented in the manuscript.
DOI: 10.5281/zenodo.8263320
title: circaetus_spectabilis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8263319
title: circaetus_spectabilis_spades_01.fasta.gz

description: .
DOI: 10.25403/upresearchdata.23937777
title: Unsupervised machine learning in air pollution epidemiology in South Africa

description: This dataset consist of different scripts and do files, used to achieve objectives to assess the applicability of machine learning in air pollution epidemiology in South Africa. The STATA do files were used to investigate the artificial intelligence (AI) survey distributed among postgraduate diploma students at the School of Health Systems and Public Health. R scripts were used for data imputation i.e., kalman, mice and mtsdi imputation, for the missing air pollution data and meteorological conditions. R scripts were also used for classification and regression trees to investigate joint effects of PM10, PM2.5, NO2, SO2 and O3 on respiratory and cardiovascular hospital admissions. Again presented are the R scripts for the unsupervised machine learning clustering methods i.e., k-means clustering, spectral clustering, dbscan clustering for joint effects for PM10, PM2.5, NO2, SO2 and O3 on respiratory and cardiovascular hospital admissions.
DOI: 10.25403/upresearchdata.23937777.v1
title: Unsupervised machine learning in air pollution epidemiology in South Africa

description: This dataset consist of different scripts and do files, used to achieve objectives to assess the applicability of machine learning in air pollution epidemiology in South Africa. The STATA do files were used to investigate the artificial intelligence (AI) survey distributed among postgraduate diploma students at the School of Health Systems and Public Health. R scripts were used for data imputation i.e., kalman, mice and mtsdi imputation, for the missing air pollution data and meteorological conditions. R scripts were also used for classification and regression trees to investigate joint effects of PM10, PM2.5, NO2, SO2 and O3 on respiratory and cardiovascular hospital admissions. Again presented are the R scripts for the unsupervised machine learning clustering methods i.e., k-means clustering, spectral clustering, dbscan clustering for joint effects for PM10, PM2.5, NO2, SO2 and O3 on respiratory and cardiovascular hospital admissions.
DOI: 10.26050/wdcc/ar6.c6hrinichc1
title: IPCC DDC: INM INM-CM5-H model output prepared for CMIP6 HighResMIP control-1950

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.INM.INM-CM5-H.control-1950' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM5-H climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM5-H (0.67x0.5; 540 x 360 longitude/latitude; 73 levels; top level sigma = 0.0002), land: INM-LND1, ocean: INM-OM5-H (North Pole shifted to 60N, 90E. 0.167x0.125; 2160x1440 longitude/latitude; 40 levels; vertical sigma coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 50 km, atmos: 50 km, land: 50 km, ocean: 10 km, seaIce: 10 km.
DOI: 10.26050/wdcc/ar6.c6hrinich
title: IPCC DDC: INM INM-CM5-H model output prepared for CMIP6 HighResMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.INM.INM-CM5-H' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM5-H climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM5-H (0.67x0.5; 540 x 360 longitude/latitude; 73 levels; top level sigma = 0.0002), land: INM-LND1, ocean: INM-OM5-H (North Pole shifted to 60N, 90E. 0.167x0.125; 2160x1440 longitude/latitude; 40 levels; vertical sigma coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 50 km, atmos: 50 km, land: 50 km, ocean: 10 km, seaIce: 10 km.
DOI: 10.5281/zenodo.8263134
title: Data repository in support of the article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming

description: This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming. The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa. The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).
DOI: 10.5281/zenodo.8263133
title: Data repository in support of the article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming

description: This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming. The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa. The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).
DOI: 10.5281/zenodo.8258861
title: phalcoboenus_megalopterus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8258860
title: phalcoboenus_megalopterus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8263394
title: Data repository supporting the JGR article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming

description: This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming. The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa. The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).
DOI: 10.5281/zenodo.8263393
title: Data repository supporting the JGR article: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming

description: This dataset contains the meteor radar wind measurements and the background atmospheric data fields used to produce the results in the Journal of Geophysical Research - Space Physics article titled: A case study of the solar and lunar semidiurnal tide response to the 2013 sudden stratospheric warming. The nav_2013_ERAn_1dm_grid.dat file contains gridded latitude-longitude-altitude daily mean winds and temperatures for the composite atmosphere described in the article. The full range of dates span from the 1st of December 2012 to the 1st of April 2023. The composite atmosphere is constructed using ERA5 winds and temperatures below 85 hPa, NAVGEM-HA winds and temperatures between 85-0.001 hPa, and HWM14 + MSISE00 winds and temperatures above 0.001 hPa. The meteor_radars.zip file contains a folder containing the hourly meteor radar wind measurements for the Collm (Col), CMOR (CMO), and Kiruna (Kir) radars, as described in the supporting paper. The .hdf5 files contain both the horizontal and meridional wind measurements for December, January, February, and March (winter of 2012/2013).
DOI: 10.6084/m9.figshare.23982912.v1
title: Digital citizen science for ethical surveillance of physical activity among youth: mobile ecological momentary assessments vs. retrospective recall

description: Data for Digital citizen science for ethical surveillance of physical activity among youth: mobile ecological momentary assessments vs. retrospective recall
DOI: 10.5281/zenodo.8263398
title: daptrius_ater_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8263397
title: daptrius_ater_spades_01.fasta.gz

description: .
DOI: 10.25403/upresearchdata.23984184
title: Pasting parameters of Bambara groundnut flours from heat-treated Bambara groundnut seeds

description: This datast shows the summary of statistical analysis of flours from heat-treated Bambara groundnut seeds. The seeds were moisture conditioned to 20% moisture level, soaked to 53 % moisture level before heat treatment. The heating conditions used a combination oven with infrared and microwave. The samples were heat treated to 130° C for 0, 5 or 10 mins. The table shows pasting properties of flours from raw, untreated, and infrared, microwave and combined treated Bambara groundnut seeds from heat treated Bambara groundnut seeds.
DOI: 10.25403/upresearchdata.23984184.v1
title: Pasting parameters of Bambara groundnut flours from heat-treated Bambara groundnut seeds

description: This datast shows the summary of statistical analysis of flours from heat-treated Bambara groundnut seeds. The seeds were moisture conditioned to 20% moisture level, soaked to 53 % moisture level before heat treatment. The heating conditions used a combination oven with infrared and microwave. The samples were heat treated to 130° C for 0, 5 or 10 mins. The table shows pasting properties of flours from raw, untreated, and infrared, microwave and combined treated Bambara groundnut seeds from heat treated Bambara groundnut seeds.
DOI: 10.5281/zenodo.8263236
title: Raman and refractive index of amorphous and crystallized GaS

description: The data presented in this dataset is published in: Gutiérrez, Y., Dicorato, S., Ovvyan, A. P., Brückerhoff-Plückelmann, F., Resl, J., Giangregorio, M. M., Hingerl, K., Cobet, C., Schiek, M., Duwe, M., Thiesen, P. H., Pernice, W. H. P., Losurdo, M., Layered Gallium Monosulfide as Phase-Change Material for Reconfigurable Nanophotonic Components On-Chip. <em>Adv. Optical Mater.</em> 2023, 2301564. https://doi.org/10.1002/adom.202301564 Experimental details on the structural and optical properties available in this respository are described in the Methods section. The files have the following structure: <strong>Refractive index files </strong>- files are structured in columns as: eV nm n k <strong>Raman files</strong> - files are structured in columns as: cm<sup>-1</sup> counts Descriptions in the files: <strong>refractive_index_amorph_GaS.txt</strong> - Refractive index (n,k) of as deposited amorphous GaS. Data shown in Figure 1b of the manuscript. <strong>refractive_index_thermally_crystallized_GaS.txt</strong>- Refractive index (n,k) of thermallycrystallized GaS. Data shown in Figure 3c,d of the manuscript. <strong>refractive_index_laser_crystallized_GaS.txt</strong> - Refractive index (n,k) of laser crystallized GaS. Data shown in Figure 3i of the manuscript. <strong>Raman_amorph_GaS</strong> - Raman spectrum of amorphous GaS. Background substracted. Data shown in Figure 1a. <strong>Raman_cryst_GaS</strong> - Raman spectrum of crystalline GaS. Data shown in Figure 1a.
DOI: 10.5281/zenodo.8263235
title: Raman and refractive index of amorphous and crystallized GaS

description: The data presented in this dataset is published in: Gutiérrez, Y., Dicorato, S., Ovvyan, A. P., Brückerhoff-Plückelmann, F., Resl, J., Giangregorio, M. M., Hingerl, K., Cobet, C., Schiek, M., Duwe, M., Thiesen, P. H., Pernice, W. H. P., Losurdo, M., Layered Gallium Monosulfide as Phase-Change Material for Reconfigurable Nanophotonic Components On-Chip. <em>Adv. Optical Mater.</em> 2023, 2301564. https://doi.org/10.1002/adom.202301564 Experimental details on the structural and optical properties available in this respository are described in the Methods section. The files have the following structure: <strong>Refractive index files </strong>- files are structured in columns as: eV nm n k <strong>Raman files</strong> - files are structured in columns as: cm<sup>-1</sup> counts Descriptions in the files: <strong>refractive_index_amorph_GaS.txt</strong> - Refractive index (n,k) of as deposited amorphous GaS. Data shown in Figure 1b of the manuscript. <strong>refractive_index_thermally_crystallized_GaS.txt</strong>- Refractive index (n,k) of thermallycrystallized GaS. Data shown in Figure 3c,d of the manuscript. <strong>refractive_index_laser_crystallized_GaS.txt</strong> - Refractive index (n,k) of laser crystallized GaS. Data shown in Figure 3i of the manuscript. <strong>Raman_amorph_GaS</strong> - Raman spectrum of amorphous GaS. Background substracted. Data shown in Figure 1a. <strong>Raman_cryst_GaS</strong> - Raman spectrum of crystalline GaS. Data shown in Figure 1a.
DOI: 10.5281/zenodo.8239530
title: The Anatomy of Conspirators: Unveiling Traits using a Comprehensive Twitter Dataset

description: This repository contains the Twitter dataset used to investigate the traits of 7,394 conspiracy users and 7,394 random users. Both the profile's info and the most recent 3,200 tweets (until Jun 13th, 2022) are provided.
DOI: 10.5281/zenodo.8239529
title: The Anatomy of Conspirators: Unveiling Traits using a Comprehensive Twitter Dataset

description: This repository contains the Twitter dataset used to investigate the traits of 7,394 conspiracy users and 7,394 random users. Both the profile's info and the most recent 3,200 tweets (until Jun 13th, 2022) are provided.
DOI: 10.3886/e193383
title: Air Pollution and Suicide in Rural and Urban America: Evidence from Wildfire Smoke

description: <b>This repository contains replication code and publicly-available data accompanying the article "Air Pollution and Suicide in Rural and Urban America: Evidence from Wildfire Smoke".<br></b><br>Reproducing the results of the study requires the restricted-access Detailed Mortality Files (2007-2019) from the National Center for Health Statistics (NCHS), which is not provided as part of this repository. Instructions for requesting the data can be found in the accompanying article. This repository contains all code and cleaned publicly-available data, allowing users with access to the NCHS data to replicate all results of the study.<br><br>Article Abstract:<br><br>Air pollution poses well-established risks to physical health, but little is known about its effects on mental health. We study the relationship between wildfire smoke exposure and suicide risk in the United States in 2007 to 2019 using data on all deaths by suicide and satellite-based measures of wildfire smoke and ambient fine particulate matter (PM2.5) concentrations. We identify the causal effects of wildfire smoke pollution on suicide by relating year-over-year fluctuations in county-level monthly smoke exposure to fluctuations in suicide rates and compare the effects across local areas and demographic groups that differ considerably in their baseline suicide risk. In rural counties, an additional day of smoke increases monthly mean PM2.5 by 0.41 μg/m3 and suicide deaths by 0.11 per million residents, such that a 1-μg/m3 (13%) increase in monthly wildfire-derived fine particulate matter leads to 0.27 additional suicide deaths per million residents (a 2.0% increase). These effects are concentrated among demographic groups with both high baseline suicide risk and high exposure to outdoor air: men, working-age adults, non-Hispanic Whites, and adults with no college education. By contrast, we find no evidence that smoke pollution increases suicide risk among any urban demographic group. This study provides large-scale evidence that air pollution elevates the risk of suicide, disproportionately so among rural populations.
description: All suicide deaths in the US, 2007-2019.