cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2f3d43
title: CCDC 2237584: Experimental Crystal Structure Determination

description: Related Article: Shuang-Long Wang, Wen-Li Yuan, Ying Zhao, Kun-Lun Cheng, Guo-Hong Tao, Ling He|2023|Dalton Trans.|52|8975|doi:10.1039/D3DT00937H
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: 10.5517/ccdc.csd.cc2f3db9
title: CCDC 2237590: Experimental Crystal Structure Determination

description: Related Article: Shuang-Long Wang, Wen-Li Yuan, Ying Zhao, Kun-Lun Cheng, Guo-Hong Tao, Ling He|2023|Dalton Trans.|52|8975|doi:10.1039/D3DT00937H
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: 10.5517/ccdc.csd.cc2g0lx0
title: CCDC 2264702: Experimental Crystal Structure Determination

description: Related Article: Na Li, Bin Li, Fan Yu, Xinying Zhang, Xuesen Fan|2023|J.Org.Chem.|88|8179|doi:10.1021/acs.joc.3c00194
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: 10.5517/ccdc.csd.cc2g0lz2
title: CCDC 2264704: Experimental Crystal Structure Determination

description: Related Article: Na Li, Bin Li, Fan Yu, Xinying Zhang, Xuesen Fan|2023|J.Org.Chem.|88|8179|doi:10.1021/acs.joc.3c00194
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: 10.5517/ccdc.csd.cc2g0tt4
title: CCDC 2264916: Experimental Crystal Structure Determination

description: Related Article: Conrad J. Powell, Eric Bosch, Herman R. Krueger, Ryan H. Groeneman|2023|New J.Chem.|47|13084|doi:10.1039/D3NJ02449K
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: 10.5517/ccdc.csd.cc2g12p9
title: CCDC 2265160: Experimental Crystal Structure Determination

description: Related Article: S. Amanchar, T. Schweitzer, T. Mazet, B. Malaman, L.V.B. Diop, M. Francois|2023|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|79|263|doi:10.1107/S2052520623004602
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: 10.5517/ccdc.csd.cc2g17qh
title: CCDC 2265316: Experimental Crystal Structure Determination

description: Related Article: Zhi-Yuan Chen, Meng-Wei Yang, Zi-Lu Wang, Yun-He Xu|2023|Org.Lett.|25|5242|doi:10.1021/acs.orglett.3c01702
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: 10.5517/ccdc.csd.cc2g1drp
title: CCDC 2265472: Experimental Crystal Structure Determination

description: Related Article: Teresa M. Karl, Samir Bouayad-Gervais, Julian A. Hueffel, Theresa Sperger, Sebastian Wellig, Sherif J. Kaldas, Uladzislava Dabranskaya, Jas S. Ward, Kari Rissanen, Graham J. Tizzard, Franziska Schoenebeck|2023|J.Am.Chem.Soc.|145|15414|doi:10.1021/jacs.3c03403
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: 10.5517/ccdc.csd.cc2g6t9t
title: CCDC 2270666: Experimental Crystal Structure Determination

description: Related Article: Chun Yang, Xinying Zhang, Xuesen Fan|2023|Org.Chem.Front.|10|4282|doi:10.1039/D3QO00939D
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: 10.5519/qd.pvqe2qdv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1900 records)
DOI: 10.5519/qd.iohqruhc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1067 records)
DOI: 10.6084/m9.figshare.23905452
title: Metabolite concentration and annotation in Pearl millet samples

description: This dataframe contains metabolomic analyses on various pearl millet lines.These analyses were done on Shoot, Root and Rhizospheric compartments.
DOI: 10.6084/m9.figshare.23905452.v3
title: Metabolite concentration and annotation in Pearl millet samples

description: This dataframe contains metabolomic analyses on various pearl millet lines.These analyses were done on Shoot, Root and Rhizospheric compartments.
DOI: 10.6084/m9.figshare.23905452.v4
title: Metabolite concentration and annotation in Pearl millet samples

description: This dataframe contains metabolomic analyses on various pearl millet lines.These analyses were done on Shoot, Root and Rhizospheric compartments.
DOI: 10.5281/zenodo.8272853
title: LPJ-GUESS model results for parametrizing the CLASH model

description: Results from the LPJ-GUESS model to parametize the CLASH model, as used in the manuscript 'CLASH - Climate-responsive Land Allocation model with carbon Storage and Harvests' The dataset contains netCDF files for four sets of runs (cropland, pastures, forests and LUH2 land-use). In each of these the LPJ-GUESS model is driven with four different climate scenarios modelled wiht three different Earth-system models (EC-Earth3, CanESM and MPI). This data was used to parametrize the CLASH model (https://doi.org/10.5281/zenodo.8271846).
DOI: 10.5281/zenodo.8272852
title: LPJ-GUESS model results for parametrizing the CLASH model

description: Results from the LPJ-GUESS model to parametize the CLASH model, as used in the manuscript 'CLASH - Climate-responsive Land Allocation model with carbon Storage and Harvests' The dataset contains netCDF files for four sets of runs (cropland, pastures, forests and LUH2 land-use). In each of these the LPJ-GUESS model is driven with four different climate scenarios modelled wiht three different Earth-system models (EC-Earth3, CanESM and MPI). This data was used to parametrize the CLASH model (https://doi.org/10.5281/zenodo.8271846).
DOI: 10.5519/qd.g9ryxkfv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.23898961
title: Table S1. from Genome-wide association study of aphid abundance highlights a locus affecting plant growth and flowering in <i>Arabidopsis thaliana</i>

description: List of GWAS accessions and phenotypes.
DOI: 10.6084/m9.figshare.23898961.v1
title: Table S1. from Genome-wide association study of aphid abundance highlights a locus affecting plant growth and flowering in <i>Arabidopsis thaliana</i>

description: List of GWAS accessions and phenotypes.
DOI: 10.26050/wdcc/ar6.c6cmgige1
title: IPCC DDC: NASA-GISS GISS-E2-1-G-CC 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.NASA-GISS.GISS-E2-1-G-CC' 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 GISS-E2-1-G-CC climate model, released in 2019, includes the following components: aerosol: varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2 x 2.5 degrees; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, landIce: Fixed, ocean: GISS Ocean (1 deg; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10m), ocnBgchem: NOBM (NASA Ocean Biogeochemistry Model; same grid as ocean), seaIce: GISS SI (same grid as ocean). The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6cmgige1eh
title: IPCC DDC: NASA-GISS GISS-E2-1-G-CC model output prepared for CMIP6 CMIP esm-hist

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.NASA-GISS.GISS-E2-1-G-CC.esm-hist' 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 GISS-E2-1-G-CC climate model, released in 2019, includes the following components: aerosol: varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2 x 2.5 degrees; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: varies with physics-version (p==1 Non-interactive, p&gt;1 GPUCCINI), land: GISS LSM, landIce: Fixed, ocean: GISS Ocean (1 deg; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10m), ocnBgchem: NOBM (NASA Ocean Biogeochemistry Model; same grid as ocean), seaIce: GISS SI (same grid as ocean). The model was run by the Goddard Institute for Space Studies, New York, NY 10025, USA (NASA-GISS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.18112/openneuro.ds004706.v1.0.0
title: Spatial memory and non-invasive closed-loop stimulus timing
DOI: 10.6084/m9.figshare.23925291.v1
title: Dataset A mesocosm experiment to study the warming and temperature-induced body size reductions effects on freshwater communities

description: This file holds the data and scripts used in the article "A mesocosm experiment to study the warming and temperature-induced body size reductions effects on freshwater communities".Data are available in files whose name begins with the prefix "df". The variables names "date" and "date_c" represent the sampling date in discrete or continue value, respectively. "mesocosm_ID" is the identity of the mesocosm. "fish" represent the fish treatment (NF for no fish, CF for cold fish and WF for warm fish). "warming" is the temperature treatment (NW for no warming, W for warming). "tmean15" is the mean temperature of the 15 days prior to the sampling date. "compartment", "class", "order" and "taxa" represent the taxonomy of the organisms. "N_l" is the density per liter. "C_mug_l" is the carbon biomass in microgram per liter. "C_mug" is the individual carbon biomass. "S" and "H" are the species richness and the Shannon diversity index, respectively. "ZP" is the zooplankton:phytoplankton biomass ratio. The variables in df_bss.csv file are described in the main text of the article.Files with a numeric prefix are the scripts used for the statistical analyzes (ecological index, community density and biomass, individual biomass, Predator Prey Biomass Ratio and Biomass Size Spectra).
DOI: 10.25403/upresearchdata.23723442
title: Survival analysis to study recidivism, right-censored lung cancer data

description: Both datasets can be found in the survival R package. They are right-censored. The Rossi dataset contains 432 male inmates from Maryland state prisons (Berk, Lenihan & Rossi, 1980). The prisoners were followed for one year. Those not re-arrested during this follow-up period were censored at week 52. At the end of the study, 318 prisoners were right censored. Thus, the censoring rate for this data is 26.39%. Meanwhile, the veteran dataset consists of death for 137 male patients with advanced lung cancer; 9 individuals were censored. Thus, the censoring rate is 6.57%. <br>
DOI: 10.25403/upresearchdata.23723442.v1
title: Survival analysis and right-censored lung cancer data to study recidivism

description: Both datasets can be found in the survival R package. They are right-censored. The Rossi dataset contains 432 male inmates from Maryland state prisons (Berk, Lenihan & Rossi, 1980). The prisoners were followed for one year. Those not re-arrested during this follow-up period were censored at week 52. At the end of the study, 318 prisoners were right censored. Thus, the censoring rate for this data is 26.39%. Meanwhile, the veteran dataset consists of death for 137 male patients with advanced lung cancer; 9 individuals were censored. Thus, the censoring rate is 6.57%. <br>
DOI: 10.5517/ccdc.csd.cc12zc2h
title: CCDC 1012276: Experimental Crystal Structure Determination

description: Related Article: S Jone Kirubavathy, R Velmurugan, R Karvembu, S Chitra|2022|CSD Communication|||
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: 10.5281/zenodo.8272705
title: software

description: software
DOI: 10.34740/kaggle/dsv/6346145
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.8272704
title: software

description: software
DOI: 10.26302/sshade/bandlist_raman_calcite
title: Raman bandlist of natural Calcite

description: MIR-FIR Raman bandlist of natural Calcite at 295K and 80K
DOI: 10.34740/kaggle/dsv/6346160
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.8273000
title: The data for reassessment of the circulation depth

description: Table 1 Main hydrochemical and isotopic data of Xinzhou geothermal field. Table 2 The measured temperatures at typical depth of kilometer borehole in Xinzhou geothermal field. Table 3 The circulation depths of geothermal water in Xinzhou geothermal field estimated with the recharge section (traditional method) and with the discharge section (new method proposed in this paper), respectively.
DOI: 10.5281/zenodo.8272999
title: The data for reassessment of the circulation depth

description: Table 1 Main hydrochemical and isotopic data of Xinzhou geothermal field. Table 2 The measured temperatures at typical depth of kilometer borehole in Xinzhou geothermal field. Table 3 The circulation depths of geothermal water in Xinzhou geothermal field estimated with the recharge section (traditional method) and with the discharge section (new method proposed in this paper), respectively.
DOI: 10.5281/zenodo.7940637
title: Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty

description: We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function.<br> The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the robust knapsack problem. Both problem sets have been described and used for benchmarking in the paper "A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty", published in Mathematical Programming Computation by Christina Büsing, Timo Gersing and Arie Koster.<br> Furthermore, we provide instances for robust weighted matching on bipartite graphs and robust weighted independent set. The latter are based on graphs for the clique problem of the second DIMACS implementation challenge (1993). Both problem sets have been described and used for benchmarking in the paper "Recycling Inequalities for Robust Combinatorial Optimization with Budget Uncertainty", presented at IPCO 2023 by the same authors. Paper "A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty": https://doi.org/10.1007/s12532-022-00232-2<br> Paper "Recycling Inequalities for Robust Combinatorial Optimization with Budget Uncertainty": https://doi.org/10.1007/978-3-031-32726-1_5<br> For algorithms solving these problems see: https://doi.org/10.5281/zenodo.7463371
DOI: 10.34943/3ff1a7f2-2bbc-4f9d-a8c7-82306dcf9104
title: Endeavour South Current Meter Deployed 2023-07-09

description: The Nortek Aquadopp Current Meter A3L9188 AQD14218 was deployed on 2023-07-09 at Endeavour South. This south section of the Endeavour Hydrothermal Vents includes two moorings to monitor the regional circulation. This device is a Current Meter. Acoustic Current Meters (ACM) measure current speed and direction, using the Doppler Effect. Aquadopp current meters have a sensor head that contains 3 acoustic transducers, a tilt sensor, a temperature sensor and a pressure sensor. The instrument transmits a short pulse of sound, and then listens to its echo to measure the change in pitch or frequency. The change in pitch can determine the velocity of the current. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.6084/m9.figshare.24711990
title: Figure 1. Demographic Profile of Respondents.docx

description: Demographic, Social, and Occupational Profiles of the Respondents are displayed as a percentage ratio.
DOI: 10.6084/m9.figshare.24711996
title: Table 4. Summary of (PLS-SEM) path analysis and hypothesis testing.docx

description: Three hypotheses were rejected because their individual t-statistic values were 1.96 or less, as shown by the specific t-statistic values in Table 4. The second, third, and fifth hypotheses are connected to these theories.
DOI: 10.6084/m9.figshare.24711999
title: Table 3. Square root of AVE and Latent Variable Correlation.docx

description: Discriminant Validity examination focuses on the following criteria: ensuring that the square root of AVE exceeds latent variable correlation and identifying a cross-loading value exceeding 0.7 in one variable. As depicted in Table 3, the square root value of AVE surpasses the correlation value of the latent variable in every variable. Consequently, the discriminant validity test of the current study has been successfully confirmed using the correct indicators and variables.
DOI: 10.6084/m9.figshare.24715788
title: Behavior_pattern_journal

description: Behavior_pattern_journal
DOI: 10.6084/m9.figshare.24715788.v1
title: Behavior_pattern_journal

description: Behavior_pattern_journal
DOI: 10.6084/m9.figshare.24712002
title: Table 2. Measurement items, reliability and construct validity.docx

description: This evaluation is predicated on three criteria: AVE and Communality values, both exceeding 0.5, and factor loading values exceeding 0.7, as delineated in Table 2. The results of the examination demonstrate that the Communality and AVE values for every variable exceed 0.5.
DOI: 10.6084/m9.figshare.24712002.v1
title: Table 2. Measurement items, reliability and construct validity.docx

description: This evaluation is predicated on three criteria: AVE and Communality values, both exceeding 0.5, and factor loading values exceeding 0.7, as delineated in Table 2. The results of the examination demonstrate that the Communality and AVE values for every variable exceed 0.5.