cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr38401.v1
title: Survey of Consumer Attitudes and Behavior, September 2019
title: Version 1

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2019 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables. Also explored in this survey, were respondents' types of savings and financial investments, loan use, family income, and retirement planning. Other topics explored in this survey were respondents' confidence in institutions, political affiliation and opinion about the Trump administration. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT</b> (Household weight (WT_HH renamed)), <b>WT_HH</b> (Household Weight), and <b>WT_AD</b> (Adult Weight) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: DS0: Study-Level Files DS1: Public-Use Data DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Survey of Consumers Web site.
DOI: 10.3886/icpsr38401
title: Survey of Consumer Attitudes and Behavior, September 2019
title: Archival Version

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2019 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables. Also explored in this survey, were respondents' types of savings and financial investments, loan use, family income, and retirement planning. Other topics explored in this survey were respondents' confidence in institutions, political affiliation and opinion about the Trump administration. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT</b> (Household weight (WT_HH renamed)), <b>WT_HH</b> (Household Weight), and <b>WT_AD</b> (Adult Weight) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: DS0: Study-Level Files DS1: Public-Use Data DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Survey of Consumers Web site.
DOI: 10.34740/kaggle/dsv/6192929
title: COVID Vaccination in World (updated daily)
DOI: 10.6084/m9.figshare.23744586
title: Ethnography and Conservation Data-Sets

description: This package contains csv files which contain further information on studies for reviewers if required.
DOI: 10.6084/m9.figshare.23744586.v1
title: Ethnography and Conservation Data-Sets

description: This package contains csv files which contain further information on studies for reviewers if required.
DOI: 10.18738/t8/7e0s4k
title: Video test files

description: Video test files
DOI: 10.5281/zenodo.8182284
title: H2020 Enodise: Analytical dataset configuration B2 ECL

description: This dataset considers analytical data for configuration B2 as defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise). The results were calculated using the half-plane Green's function for the convected Helmholtz equation for predicting the sound scattering by trailing edges in the presence of a uniform flow. For mimicking the Distributed Electric Propulsion (DEP) configuration model which includes a wing and two side-by-side propellers measured during the wind tunnel tests, the formalism of source-modes is introduced, from which the sound field could be expressed uniformly in the whole space. The wing was approximated by a thin plate with zero-thickness. The aerodynamic performance of the propeller was calculated by using a BEMT method.
DOI: 10.5281/zenodo.8182283
title: H2020 Enodise: Analytical dataset configuration B2 ECL

description: This dataset considers analytical data for configuration B2 as defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise). The results were calculated using the half-plane Green's function for the convected Helmholtz equation for predicting the sound scattering by trailing edges in the presence of a uniform flow. For mimicking the Distributed Electric Propulsion (DEP) configuration model which includes a wing and two side-by-side propellers measured during the wind tunnel tests, the formalism of source-modes is introduced, from which the sound field could be expressed uniformly in the whole space. The wing was approximated by a thin plate with zero-thickness. The aerodynamic performance of the propeller was calculated by using a BEMT method.
DOI: 10.26050/wdcc/ar6.c6cmccce
title: IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 CMIP

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.CMIP.CCCma.CanESM5' 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 CanESM5 climate model, released in 2019, includes the following components: aerosol: interactive, atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa), atmosChem: specified oxidants for aerosols, land: CLASS3.6/CTEM1.2, landIce: specified ice sheets, ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m), ocnBgchem: Canadian Model of Ocean Carbon (CMOC); NPZD ecosystem with OMIP prescribed carbonate chemistry, seaIce: LIM2. The model was run by the Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada (CCCma) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, atmosChem: 500 km, land: 500 km, landIce: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6cmccces
title: IPCC DDC: CCCma CanESM5-CanOE model output prepared for CMIP6 CMIP

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.CMIP.CCCma.CanESM5-CanOE' 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 CanESM5-CanOE climate model, released in 2019, includes the following components: aerosol: interactive, atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa), atmosChem: specified oxidants for aerosols, land: CLASS3.6/CTEM1.2, landIce: specified ice sheets, ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m), ocnBgchem: Canadian Ocean Ecosystem (CanOE) with OMIP prescribed carbon chemistry, seaIce: LIM2. The model was run by the Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada (CCCma) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, atmosChem: 500 km, land: 500 km, landIce: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.6084/m9.figshare.23744628
title: <strong>Table_S1: The role of thermal tolerance in determining elevational distributions of four arthropod taxa in mountainranges of southern Asia</strong>

description: Physiological thermal tolerances, geographical range limits information at species level at two trasects.
DOI: 10.6084/m9.figshare.23739792.v1
title: Getting the most out of the API and the Reporting Database materials

description: Materials for the "Getting the most out of the API and the Reporting Database" webinar with Symplectic Elements, 20230724
DOI: 10.5517/ccdc.csd.cc201r50
title: CCDC 1848721: Experimental Crystal Structure Determination

description: Related Article: Qian Jiang, Mingguang Zhang, Zhonglong Wang, Jie Song, Yiqin Yang, Wenchao Li, Wen Gu, Xu Xu, Haijun Xu, Shifa Wang|2018|RSC Advances|8|30055|doi:10.1039/C8RA05031G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.14473/csda/wbhw1t/yzz8jx
title: TI_V1810en.pdf

description: Technical information
DOI: 10.14473/csda/wbhw1t/ahxk0x
title: D_V1810en.pdf

description: Questionnaire
DOI: 10.14473/csda/wbhw1t/0lpf0h
title: NS_1810_DataFile-FINAL_ENG.tab

description: Data
DOI: 10.14473/csda/wbhw1t
title: Our Society 2018 - October

description: Research was conducted by the Public Opinion Research Center (CVVM) of the Institute of Sociology of the Czech Academy of Sciences as a part of the research "Our Society 2018". Data collection was secured by the interviewer network of CVVM. Please note that this research is an English version / translation of materials from research "Naše společnost říjen 2018 "
DOI: 10.5281/zenodo.5215791
title: High resolution land cover 2015 Aarhus, Denmark

description: <strong>Description</strong> This dataset provides land-cover and land-use information at a 20cm resolution for the municipality of Aarhus, Denmark. It depicts the status for the year 2015, containing 23 thematic classes. <strong>Spatial reference</strong><br> All data is projected in ETRS 1989 UTM Zone 32N (EPSG:25832) <strong>Related publication</strong><br> J. M. Knopp, G. Levin and E. Banzhaf, "Aerial Data Analysis for Integration Into a Green Cadastre—An Example From Aarhus, Denmark," in <em>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</em>, vol. 16, pp. 6545-6555, 2023, doi: 10.1109/JSTARS.2023.3289218. <strong>Class Codec</strong> <strong>Class</strong> <strong>Vector </strong> <strong>NumCodec</strong> <strong>(16bit)</strong> <strong>Raster</strong> <strong>NumCodec</strong> <strong>(8bit)</strong> Building 100 10 0 Lowest rise building 110 11 1 Low rise building 120 12 2 Mid rise building 130 13 3 High rise building 140 14 4 Highest rise building 150 15 Mineral surface 210 21 Bare soil 220 22 Artificial grass 230 23 Grass 310 31 Shrub round 410 41 Shrub linear 420 42 Evergreen 510 51 Deciduous 520 52 Lake 610 61 River 620 62 Sea 630 63 Undergrowth 710 71 Agriculture, intensive temporary crops 810 81 Agriculture, intensive permanent crops 820 82 Agriculture, extensive 830 83 unclassified 999 99 NonAOI 999 99
description: {"references": ["J. M. Knopp, G. Levin and E. Banzhaf, \"Aerial Data Analysis for Integration Into a Green Cadastre\u2014An Example From Aarhus, Denmark,\" in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 6545-6555, 2023, doi: 10.1109/JSTARS.2023.3289218."]}
DOI: 10.5281/zenodo.5215792
title: High resolution land cover 2015 Aarhus, Denmark

description: <strong>Description</strong> This dataset provides land-cover and land-use information at a 20cm resolution for the municipality of Aarhus, Denmark. It depicts the status for the year 2015, containing 23 thematic classes. <strong>Spatial reference</strong><br> All data is projected in ETRS 1989 UTM Zone 32N (EPSG:25832) <strong>Related publication</strong><br> J. M. Knopp, G. Levin and E. Banzhaf, "Aerial Data Analysis for Integration Into a Green Cadastre—An Example From Aarhus, Denmark," in <em>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</em>, vol. 16, pp. 6545-6555, 2023, doi: 10.1109/JSTARS.2023.3289218. <strong>Class Codec</strong> <strong>Class</strong> <strong>Vector </strong> <strong>NumCodec</strong> <strong>(16bit)</strong> <strong>Raster</strong> <strong>NumCodec</strong> <strong>(8bit)</strong> Building 100 10 0 Lowest rise building 110 11 1 Low rise building 120 12 2 Mid rise building 130 13 3 High rise building 140 14 4 Highest rise building 150 15 Mineral surface 210 21 Bare soil 220 22 Artificial grass 230 23 Grass 310 31 Shrub round 410 41 Shrub linear 420 42 Evergreen 510 51 Deciduous 520 52 Lake 610 61 River 620 62 Sea 630 63 Undergrowth 710 71 Agriculture, intensive temporary crops 810 81 Agriculture, intensive permanent crops 820 82 Agriculture, extensive 830 83 unclassified 999 99 NonAOI 999 99
description: {"references": ["J. M. Knopp, G. Levin and E. Banzhaf, \"Aerial Data Analysis for Integration Into a Green Cadastre\u2014An Example From Aarhus, Denmark,\" in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 6545-6555, 2023, doi: 10.1109/JSTARS.2023.3289218."]}
DOI: 10.18712/nsd-nsd0372-1-v4
title: The Norwegian 1994 EU Referendum Study

description: The aim of "The Norwegian 1994 EU Referendum Study" was to study the Norwegian public EU opinion in a broad sense, i.e. to study electoral motives as well as elite participation through organizations such as "Nei til EU", "Europabevegelsen" and "Sosialdemokrater mot EU", as well as the media coverage of the EU issue. In addition, there was a goal to further develop research on referendums. Studies of the 1972 referendum indicated that social position (gender, age, place of residence, education, occupational affiliation and income) was of major importance for voters' views. In addition to the importance of social position, an emphasis was placed on cultural, ideological and political ties and loyalties in the study of the 1994 referendum. The main material for the project was interview data with about 3600 Norwegians. Each respondent was interviewed in advance of the election campaign, during the election campaign and after the vote. The survey was conducted on behalf of the Norwegian University of Science and Technology at the Department of Sociology and Political Science, and coordinated with the Nordic project "Referendum i Europas utkant".
DOI: 10.25934/pr00009073
title: Projecting the Development of Antimicrobial Resistance to Beta-lactam Antibiotics in Africa: A Mathematical Modelling Approach

description: Background: 
Despite significant advances in antibiotic and anti-infective therapy development, the global threat posed by AMR is undeniable, with millions of deaths attributed to bacterial AMR in recent years. The emergence and spread of resistance genes threaten the therapeutic effectiveness of beta-lactam antibiotics, which are widely used worldwide. The World Health Organization recommends the use of alternative antimicrobial treatment as empirical treatment when ≥25% of organisms are resistant. Susceptibility to beta-lactam antibiotics, one of the commonest treatment options has been decreasing in many countries. It is impossible to completely prevent the development and spread of resistance because the ability to adapt to changing environmental conditions is a fundamental property of all living things. Mathematical modeling is a powerful tool to investigate the dynamics of AMR; however, the extent of its use to predict population-level development of resistance to beta-lactam antibiotics is currently unclear. 
Aim: To use antimicrobial resistance surveillance data and develop a mathematical model to project the time to reach the 25% threshold for resistance to beta-lactam antibiotics. 
Model development and analysis: We shall use data from Antimicrobial Testing Leadership and Surveillance) Program ATLAS in Africa from 2004–2020 about minimum inhibitory concentrations (MIC) for penicillins, cephalosporins, and carbapenems. The data will be analyzed to assess the current prevalence and trends in beta-lactam resistance. Descriptive statistics and trend analysis will be employed to identify patterns and changes over time. We shall develop two susceptible-infected-susceptible models to fit the data and produce projections of the proportion of resistance until 2035. The single-step model will represent the situation in which a single mutation results in antimicrobial resistance. In the multi-step model, the sequential accumulation of resistance mutations will be reflected by changes in the MIC distribution.
DOI: 10.5281/zenodo.7348779
title: SAXS data - FAD-dependent monooxygenase from Stenotrophomonas maltophilia

description: Raw SAXS data for FAD-dependent monooxygenase from <em>Stenotrophomonas maltophilia</em> (<em>Sm</em>TetX) in h5z format. Detailed description is available in the manuscript "Tetracycline-modifying enzyme <em>Sm</em>TetX from <em>Stenotrophomonas maltophilia</em>". Processed data were deposited in the SASBDB database under the accession codes SASDPV7 and SASDPW7 for sample without and with reducing agent (30 mM DTT), respectively. https://www.sasbdb.org/data/SASDPV7<br> https://www.sasbdb.org/data/SASDPW7
DOI: 10.5281/zenodo.7348780
title: SAXS data - FAD-dependent monooxygenase from Stenotrophomonas maltophilia

description: Raw SAXS data for FAD-dependent monooxygenase from <em>Stenotrophomonas maltophilia</em> (<em>Sm</em>TetX) in h5z format. Detailed description is available in the manuscript "Tetracycline-modifying enzyme <em>Sm</em>TetX from <em>Stenotrophomonas maltophilia</em>". Processed data were deposited in the SASBDB database under the accession codes SASDPV7 and SASDPW7 for sample without and with reducing agent (30 mM DTT), respectively. https://www.sasbdb.org/data/SASDPV7<br> https://www.sasbdb.org/data/SASDPW7
DOI: 10.5281/zenodo.8165363
title: NIHAO-SKIRT-Catalog

description: Data product containing resolved photometry and spatially integrated spectra for a sample of 65 NIHAO galaxies, each from 10 different viewing angles. The two python analysis files demonstrate how to access and use the data files. README.md contains further information about the data file contents.
DOI: 10.5281/zenodo.7848163
title: Images for PDB entry 8OSP

description: Images used to calculate the structure for PDB entry 8OSP