cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e130542
title: National Neighborhood Data Archive (NaNDA): Urbanicity by Census Tract, United States, 2010

description: This dataset contains measures of the urban/rural characteristics of each census tract in the United States. These include proportions of urban and rural population, population density, rural/urban commuting area (RUCA) codes, and RUCA-based four- and seven- category urbanicity scales.
description: All census tracts in the United States, including Puerto Rico. . Smallest Geographic Unit: census tract
DOI: 10.3886/e129361
title: personality characteristics and reckless driving

description: This project analyzes the influence of personality variables on the prediction of risky driving behavior<br>
DOI: 10.3886/e129361v2
title: personality characteristics and reckless driving

description: This project analyzes the influence of personality variables on the prediction of risky driving behavior<br>
DOI: 10.3886/e119446v49
title: COVID-19 US State Policy Database

description: For questions or comments about the database please contact:<br>Alexandra Skinner <br>skinnera@bu.edu <br>Research Fellow & Database Manager<br>Department of Health Law, Policy & Management <br>Boston University School of Public Health<br><br>Database of state policies on closures, shelter-in-place orders, housing protections, changes to Medicaid and SNAP, physical distancing closures, reopening, and more created by researchers at the Boston University School of Public Health. Policies included are state-wide directives or mandates, not guidance or recommendations. In order for a policy to be included, it must apply to the entire state. We are working quickly to go through state government websites to make the policy database as complete and accurate as possible in a rapidly changing policy context. If you use data on a given policy, we encourage you to triangulate based on additional sources of policy data and to review the source documentation to consider the coding decisions that are right for your work. Of course, please email us if you note a discrepancy so we can improve the database for everyone. State policy source documentation can be found at: tinyurl.com/statepolicysources.
description: other; Contributors: Megan Cole Brahim, Noa Krawczyk, Carolyn Hoffman, Claire Corkish, Elizabeth Ferrara, Elizabeth Long, Emily Baroni, Faith Contador, Hannah Simon, Morgan Simko, Rachel Scheckman, Sarah Brewer, Sue Kulkarni, Felicia Heykoop, Manish Patel, Aishwarya Vidyasagaran, Andrew Chiao, Cara Safon, Samantha Burkhart, Harry Jung, Victor Lee, Marina MacKinnon, Aarohi Rede, Marie Vearling, Sophie Li, Christina Wang, Tim Levengood, María Jordán P. Emma Chistolini
description: State policies. Smallest Geographic Unit: State
DOI: 10.4225/08/5799d4a672aff
title: Mean monthly shortwave radiation ratio modelled using the 1" DEM-S - 1" mosaic

description: Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive: • Incoming short-wave radiation on a sloping surface • Short-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface) • Incoming long-wave radiation • Outgoing long-wave radiation • Net long-wave radiation • Net radiation • Sky view factor All radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane. The radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view. The monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9631 . The 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value. The 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18732
DOI: 10.6084/m9.figshare.7763330.v4
title: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS)

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open−access and easy−to−use application that allows a hospital to perform data analysis independently and generate isolate−based and sample−based surveillance reports stratified by infection origin from routinely collected electronic databases. The application was built in R, which is a free software environment. The application has been placed within a user−friendly interface that only requires the user to double−click on the application icon. <br>AMASS performs data analysis and generates reports automatically. The raw data files required are hospital admission and microbiology databases. Firstly, the application cleans the microbiology data file and produces isolate−based and sample−based surveillance reports without stratification by infection origin. Secondly, the application then merges the microbiology and hospital admission data files, analyzes the merged data, and produces an isolated−based and sample−based surveillance reports with stratification by infection origin. Finally, the application then perform a statistical analysis to estimate all−cause mortality of patients with AMR infection and mortality attributable to AMR, which are automatically added into the AMR surveillance report.<br>AMASS aims to support the hospitals even those hospitals having only microbiology results. recorded electronica formats. For example, only isolate−based surveillance report without stratification by infection origin will be generated, if only microbiology data file is available and hospital admission data file is not available in the computer.<br> This is the AMASS.zip containing the AMASS application. Further, details on how to use the application can be found in http://mice.tropmedres.ac/home.aspx.
DOI: 10.6084/m9.figshare.12117408
title: Antimicrobial resistance surveillance report, WHO Test Hospital, World Health Organization, 01 Jan 1995 to 31 Jan 1995

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the open-access demonstration file of WHONET. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using microbiology data of Example_Dataset_1_WHONET (which can also be found in the AMASS folder)<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Example_Dataset_1_WHONET (this is generated for the users of WHONET)<br>Please note that the data dictionary for microbiology data file can be re-used with the data files of the hospital, that are currently using WHONET, in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12117408.v2
title: Antimicrobial resistance surveillance report, WHO Test Hospital, World Health Organization, 01 Jan 1995 to 31 Jan 1995

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the open-access demonstration file of WHONET. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using microbiology data of Example_Dataset_1_WHONET (which can also be found in the AMASS folder)<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Example_Dataset_1_WHONET (this is generated for the users of WHONET)<br>Please note that the data dictionary for microbiology data file can be re-used with the data files of the hospital, that are currently using WHONET, in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6084/m9.figshare.12117408.v1
title: Antimicrobial resistance surveillance report, WHO Test Hospital, World Health Organization, 01 Jan 1995 to 31 Jan 1995

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the open-access demonstration file of WHONET. The attached three files are:1) The AMR surveillance report automatically generated from AMASS using microbiology data of Example_Dataset_1_WHONET (which can also be found in the AMASS folder)<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of Example_Dataset_1_WHONET (this is generated for the users of WHONET)<br>Please note that the data dictionary for microbiology data file can be re-used with the data files of the hospital, that are currently using WHONET, in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.6073/pasta/81f980e956de95e603bfc367232d9fcd
title: Shark catches (longline), water temperatures, salinities, and dissolved oxygen levels, and stable isotope values in the Shark River Slough, Everglades National Park (FCE LTER) from May 2005 to Present

description: This dataset provides information on the catches of sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected suggest that distance from the Gulf of Mexico and dissolved have the largest effects on shark catch rates, with most juvenile bull sharks being caught in Tarpon Bay. This dataset includes all sharks caught on longline gear.
DOI: 10.6084/m9.figshare.13557821
title: condensed_species_NCBI v1.2.0

description: The condensed_species.csv dataset is the second data product from the data merger workflow. The trait data are mapped and aggregated to NCBI species level.
DOI: 10.6084/m9.figshare.13557818
title: condensed_traits_GTDB v1.2.0

description: The condensed_traits.csv dataset is the first data product from the data merger workflow. It include species and strains, and the raw are in their clean, but raw, form.
DOI: 10.6084/m9.figshare.13557824
title: condensed_species_GTDB v1.2.0

description: The condensed_species.csv dataset is the second data product from the data merger workflow. The trait data are mapped and aggregated to GTDB species level.
DOI: 10.6084/m9.figshare.13557812
title: references v1.2.0

description: The reference list associated with the trait and species Data Records.
DOI: 10.6084/m9.figshare.13557827
title: condensed_traits_NCBI v1.2.0

description: The condensed_traits.csv dataset is the first data product from the data merger workflow. It include species and strains, and the raw are in their clean, but raw, form.
DOI: 10.6084/m9.figshare.12117348
title: Antimicrobial resistance surveillance report, Hypothetical Hospital, Hypothetical Country, 01 Jan 2016 to 31 Dec 2016

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the example data files. The Example_Dataset_2 is a data set generated for AMASS users. This example data set was created to represent a large data set from a 1000-bed hospital, containing microbiology and hospital admission data. The data files can be found under the "Example_Dataset_2" folder of AMASS. The attached four files here are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Example_Dataset_2<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of the example data files<br>4) Data dictionary for hospital admission data of the example data files<br>
DOI: 10.6084/m9.figshare.12117348.v2
title: Antimicrobial resistance surveillance report, Hypothetical Hospital, Hypothetical Country, 01 Jan 2016 to 31 Dec 2016

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the example data files. The Example_Dataset_2 is a data set generated for AMASS users. This example data set was created to represent a large data set from a 1000-bed hospital, containing microbiology and hospital admission data. The data files can be found under the "Example_Dataset_2" folder of AMASS. The attached four files here are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Example_Dataset_2<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of the example data files<br>4) Data dictionary for hospital admission data of the example data files<br>
DOI: 10.6084/m9.figshare.12117348.v1
title: Antimicrobial resistance surveillance report, Hypothetical Hospital, Hypothetical Country, 01 Jan 2016 to 31 Dec 2016

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website<br>This is a repository of the files for the example data files. The Example_Dataset_2 is a data set generated for AMASS users. This example data set was created to represent a large data set from a 1000-bed hospital, containing microbiology and hospital admission data. The data files can be found under the "Example_Dataset_2" folder of AMASS. The attached four files here are:1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Example_Dataset_2<br>2) Aggregated summary data in .csv format automatically generated from AMASS3) Data dictionary for microbiology data file of the example data files<br>4) Data dictionary for hospital admission data of the example data files<br>
DOI: 10.6084/m9.figshare.12000240
title: Antimicrobial resistance surveillance report, Sunpasitthiprasong Hospital, Thailand, 01 Jan 2015 to 31 Dec 2015

description: AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) was developed as an offline, open-access and easy-to-use application that allows a hospital to perform data analysis independently and generate isolate-based and sample-based surveillance reports stratified by infection origin from routinely collected electronic databases. AMASS performs data analysis and generates reports automatically. The application can be downloaded from https://www.amass.website.<br><br>This is a repository of the files for Sunpasitthiprasong Hospital. The attached four files are:<br>1) The AMR surveillance report automatically generated from AMASS using hospital admission and microbiology data of Sunpasitthiprasong Hospital in Thailand<br>2) Aggregated summary data in .csv format automatically generated from AMASS<br>3) Data dictionary for microbiology data file of Sunpasitthiprasong Hospital (configured by the hospital to be used with the AMASS application)<br>4) Data dictionary for hospital admission data of Sunpasitthiprasong Hospital (configured by the hospital to be used with the AMASS application)<br><br>Please note that the two data dictionary files can be re-used with the data files of the hospital in the future in cases when variables names and values in the raw data remained unchanged.
DOI: 10.34721/k2fk-qf20
title: Scientifically framed gene drive communications - data
DOI: 10.25345/c5sz1p
title: MassIVE MSV000086686 - Cardiac proteome of Western painted turtle
title: Western painted turtles (Chrysemys picta bellii) are the most anoxia-tolerant tetrapod. Survival time improves at low temperature and during ontogeny, such that adults acclimated to 3oC survive far longer without oxygen than either warm-acclimated adults or cold-acclimated hatchlings. Since protein synthesis is rapidly suppressed to save energy at the onset of anoxia exposure, this study tested the hypothesis that cold-acclimation would evoke preparatory changes in protein expression that would support enhanced anoxia survival in adult but not hatchling turtles. The relative abundances of 1316 identified proteins were compared between temperatures and developmental stages.
DOI: 10.21227/gbwy-cc19
title: Google.com Ping

description: Ping reponse times from google.com
DOI: 10.21227/q4n1-x098
title: Google.com Ping

description: Ping reponse times from google.com
DOI: 10.21227/y4b1-q467
title: Google.com Ping

description: Ping reponse times from google.com
DOI: 10.21227/qjkw-2478
title: Google.com Ping

description: Ping reponse times from google.com
DOI: 10.21227/jfph-p623
title: Ping Response Times from google.com

description: Ping reponse times from google.com
DOI: 10.5281/zenodo.4433177
title: Release Dataset

description: Dataset
DOI: 10.5281/zenodo.4433180
title: Specular Meteor Radar wind estimates from Tirupati, used in "Validation of ICON-MIGHTI thermospheric wind observations: 2. Greenline comparisons to specular meteor radars" by Harding et al. (2021)"

description: <pre>This dataset was used to generate the figures in the paper mentioned above and is being made available for the sake of reproducibility and future analysis. The primary variables are u0, v0 (the zonal and meridional wind profiles observed by the meteor radar). Dimensions are "time" and "alt" (in km). Velocity units are m/s, and lat/lon are in degrees. More information can be found in the paper. Please contact and get permission from the data providers (M. Venkat Ratnam and S. Vijaya Bhaskara Rao) before using the data in any publications or presentations.</pre>
DOI: 10.5281/zenodo.4433179
title: Specular Meteor Radar wind estimates from Tirupati, used in "Validation of ICON-MIGHTI thermospheric wind observations: 2. Greenline comparisons to specular meteor radars" by Harding et al. (2021)"

description: <pre>This dataset was used to generate the figures in the paper mentioned above and is being made available for the sake of reproducibility and future analysis. The primary variables are u0, v0 (the zonal and meridional wind profiles observed by the meteor radar). Dimensions are "time" and "alt" (in km). Velocity units are m/s, and lat/lon are in degrees. More information can be found in the paper. Please contact and get permission from the data providers (M. Venkat Ratnam and S. Vijaya Bhaskara Rao) before using the data in any publications or presentations.</pre>
DOI: 10.5281/zenodo.4431059
title: Dataset - Assessing the Students' Understanding and their Mistakes in Code Review Checklists -An Experience Report of 1,791 Code Review Checklists Questions from 394 Students

description: This is the assignment specification and artifacts related to the paper "Assessing the Students' Understanding and their Mistakes in Code Review Checklists -An Experience Report of 1,791 Code Review Checklists Questions from 394 Students", ICSE-JSEET 2021.
DOI: 10.5281/zenodo.4431058
title: Dataset - Assessing the Students' Understanding and their Mistakes in Code Review Checklists -An Experience Report of 1,791 Code Review Checklists Questions from 394 Students

description: This is the assignment specification and artifacts related to the paper "Assessing the Students' Understanding and their Mistakes in Code Review Checklists -An Experience Report of 1,791 Code Review Checklists Questions from 394 Students", ICSE-JSEET 2021.
DOI: 10.17632/g46b3fjdx9.1
title: Data for: Quantifying temporal variability and spatial heterogeneity in rainfall recharge thresholds in a montane karst environment

description: 15-minute drip data (sum of drips) for 9 sites at South Glory Cave 2013-2019. Missing data infilled using QuickSampling
DOI: 10.17632/b9trv5djj5.1
title: Data for: Evolution behavior of liquid film in the heat-affected zone of laser cladding non-weldable nickel-based superalloy

description: Phase composition in K447A superalloy obtained via EPMA and the friction of solid in the grain boundary of K447A superalloy obtained via JMatPro software are listed.
DOI: 10.5281/zenodo.4433187
title: WLutz Demo Files - with iCom

description: WLutz Demo Files - with iCom
DOI: 10.5281/zenodo.4422174
title: WLutz Demo Files - with iCom

description: WLutz Demo Files - with iCom
DOI: 10.17632/8my28rx6c3.1
title: Data for: Operating scenario of 3GWthClass FFHR power plant with bypass controlled supercritical CO2 gas turbine power generation system

description: Abstract: In order to achieve high power generation efficiency, facility compactness, high safety, and high coexistence with fuel tritium in the 3GWth class FFHR power plant, optimization, performance and operation scenario of the power generation system of the power plant model using the axial flow type uniaxial supercritical CO2 gas turbine power generation system were examined. As a result, the following conclusions were obtained. The most efficient and compact axial flow uniaxial design supercritical CO2 gas turbine power generation system suitable for 3GWthFFHR power plant has a maximum heat capacity of 1.5MWth×2, and the power generation efficiency at that time was evaluated as 46.2%. Therefore, split connection with two power generation systems is optimal for a 3GWth class FFHR power plant. Here, the operating speed of the turbo equipment was set to 3600 rpm in order to adapt this plant model to the power supply system in Japan.