cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26050/wdcc/ar6.c6spccce
title: IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP

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.ScenarioMIP.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.c6spccces434
title: IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP ssp434

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.ScenarioMIP.CCCma.CanESM5.ssp434' 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.c6spccces460
title: IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP ssp460

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.ScenarioMIP.CCCma.CanESM5.ssp460' 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.c6spccceso
title: IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP ssp534-over

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.ScenarioMIP.CCCma.CanESM5.ssp534-over' 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.c6spccces
title: IPCC DDC: CCCma CanESM5-CanOE model output prepared for CMIP6 ScenarioMIP

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.ScenarioMIP.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: 10.5281/zenodo.8205244
title: BP-tracer: Supplementary Data 2

description: <strong>Supplementary Data 2 of BP-tracer</strong> Including: 1. BP-Tracer analysis results of simulated metagenomes 2. BP-Tracer analysis results of real metagenomes
DOI: 10.5281/zenodo.8205243
title: BP-tracer: Supplementary Data 2

description: <strong>Supplementary Data 2 of BP-tracer</strong> Including: 1. BP-Tracer analysis results of simulated metagenomes 2. BP-Tracer analysis results of real metagenomes
DOI: 10.34740/kaggle/dsv/6231209
title: COVID Vaccination in World (updated daily)
DOI: 10.5519/qd.1lyxn6dt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (16 records)
DOI: 10.25345/c5k931h24
title: MassIVE MSV000092564 - Proteomics of HeLa cells starved and treated with YWF or leptomycin B
title: HeLa cells labeled with SILAC and were amino acids starved and treated with YWF, leptomycin B, MG132 or chloroquine. Cells were lysed with a 8M Urea buffer and proteins were reduced and alkylated. Equal amount of proteins of different labels were mixed and were digested with trypsin and resulting peptides were injected on a Q Exactive plus instrument. Raw data were analysed with MaxQuant with default settings.
DOI: 10.5281/zenodo.8205300
title: DADOS DE ANÁLISE ESTATÍSTICA INTEGRAL DO ESTUDO QUALIDADE DE VIDA DOS ESTUDANTES DO ENSINO MÉDIO INTEGRADO DO CAMPUS SÃO FRANCISCO DO SUL/SANTA CATARINA: UMA ANÁLISE SOBRE O ESTILO DE VIDA DOS ALUNOS.

description: Dados da dissertação: <strong>PERFIL DE ESTILO DE VIDA DOS ESTUDANTES DO ENSINO MÉDIO INTEGRADO: UM ESTUDO NO CAMPUS SÃO FRANCISCO DO SUL, SANTA CATARINA</strong>
DOI: 10.5281/zenodo.8205299
title: DADOS DE ANÁLISE ESTATÍSTICA INTEGRAL DO ESTUDO QUALIDADE DE VIDA DOS ESTUDANTES DO ENSINO MÉDIO INTEGRADO DO CAMPUS SÃO FRANCISCO DO SUL/SANTA CATARINA: UMA ANÁLISE SOBRE O ESTILO DE VIDA DOS ALUNOS.

description: Dados da dissertação: <strong>PERFIL DE ESTILO DE VIDA DOS ESTUDANTES DO ENSINO MÉDIO INTEGRADO: UM ESTUDO NO CAMPUS SÃO FRANCISCO DO SUL, SANTA CATARINA</strong>
DOI: 10.5281/zenodo.8205210
title: Raw data and data accompanying publication: https://doi.org/10.3390/ijms23052452

description: Raw data and data accompanying publication: Szutkowska, B.; Wieczorek, K.; Kierzek, R.; Zmora, P.; Peterson, J.M.; Moss, W.N.; Mathews, D.H.; Kierzek, E. Secondary Structure of Influenza A Virus Genomic Segment 8 RNA Folded in a Cellular Environment. <em>Int. J. Mol. Sci.</em> <strong>2022</strong>, <em>23</em>, 2452. https://doi.org/10.3390/ijms23052452
description: This research was funded by the National Science Centre, Poland grants UMO-2020/01/0/NZ6/00137 to E.K., UMO-2020/39/B/NZ1/03054 to E.K., UMO-2019/33/B/ST4/01422 to R.K., and UMO-2017/25/B/NZ1/02269 to R.K. W.N.M. was supported by NIH/NIGMS grants R00GM112877 and R01GM133810 as well as by startup funds from the Roy J. Carver Charitable Trust. D.H.M. was supported by NIH grant R01GM076485.
DOI: 10.5281/zenodo.8205209
title: Raw data and data accompanying publication: https://doi.org/10.3390/ijms23052452

description: Raw data and data accompanying publication: Szutkowska, B.; Wieczorek, K.; Kierzek, R.; Zmora, P.; Peterson, J.M.; Moss, W.N.; Mathews, D.H.; Kierzek, E. Secondary Structure of Influenza A Virus Genomic Segment 8 RNA Folded in a Cellular Environment. <em>Int. J. Mol. Sci.</em> <strong>2022</strong>, <em>23</em>, 2452. https://doi.org/10.3390/ijms23052452
description: This research was funded by the National Science Centre, Poland grants UMO-2020/01/0/NZ6/00137 to E.K., UMO-2020/39/B/NZ1/03054 to E.K., UMO-2019/33/B/ST4/01422 to R.K., and UMO-2017/25/B/NZ1/02269 to R.K. W.N.M. was supported by NIH/NIGMS grants R00GM112877 and R01GM133810 as well as by startup funds from the Roy J. Carver Charitable Trust. D.H.M. was supported by NIH grant R01GM076485.
DOI: 10.7284/138685
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AR41 using a SeaBird SBE-911+ instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149580
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AT45 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149608
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AT47 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.3886/e113758v1-140566
title: Replication data for: Freedom Fries

description: Do firms always choose the cheapest suitable inputs, or can group attitudes affect their choices? To investigate this question, we examine the deterioration of relations between the United States and France from 2002-2003, when France's favorability rating in the US fell by 48 percentage points. We estimate that the worsening attitudes reduced bilateral trade by about 9 percent and that trade in inputs probably declined similarly, by about 8 percent. We use these estimates to calculate the average decrease in firms' willingness to pay for French (or US) commodities when attitudes worsened. (JEL D24, F13, F14, L14, L21)
DOI: 10.5281/zenodo.8205348
title: Test Dataset for MapSeq Data Manager Galaxy Wrapper

description: Test Dataset used to test the Data Manager for the MapSeq Galaxy Wrapper
DOI: 10.5281/zenodo.8205347
title: Test Dataset for MapSeq Data Manager Galaxy Wrapper

description: Test Dataset used to test the Data Manager for the MapSeq Galaxy Wrapper
DOI: 10.6084/m9.figshare.23816127
title: Dataset.xlsx

description: In this study, a rich data survey of 3,500 Greek SMEs is used at the peak of the sovereign debt economic crisis of the year 2012 in order to explore if and how ICT and innovation efforts of SMEs influence their growth performance in a time of crisis. In this study, the effects on firm growth of employee risk taking, firm size, and age are also analyzed. The moderating role of firm location in the relation between ICT/innovation efforts and SME growth is also examined in the context of the externalities that the knowledge spillovers may create for firms located in metropolitan areas.
DOI: 10.6084/m9.figshare.23816127.v1
title: Dataset.xlsx

description: In this study, a rich data survey of 3,500 Greek SMEs is used at the peak of the sovereign debt economic crisis of the year 2012 in order to explore if and how ICT and innovation efforts of SMEs influence their growth performance in a time of crisis. In this study, the effects on firm growth of employee risk taking, firm size, and age are also analyzed. The moderating role of firm location in the relation between ICT/innovation efforts and SME growth is also examined in the context of the externalities that the knowledge spillovers may create for firms located in metropolitan areas.
DOI: 10.5281/zenodo.8197843
title: Deep and fast label-free Dynamic Organellar Mapping - Imaging data

description: Imaging data from the article "Deep and fast label-free Dynamic Organellar Mapping", published in Nature Communications by Schessner et al., from Fig. 6, 7 and Supp. Fig. 6c. Widefield images were captured on a Leica DMi8 inverted microscope equipped with an iTK LMT200 motorised stage, a 63x/1.47 oil objective (HC PL APO 63x/1.47 OIL) and a Leica DFC9000 GTC Camera, and controlled with LAS X (Leica Application Software X). Fig6_GLG1_TGOLN2_GALNT2_SuppFig6c_LC3B: Widefield imaging of wild-type HeLa cells cultured for 1h in either: 1) full growth medium (Control); 2) EBSS to starve the cells (Starve); 3) full growth medium plus 100 nM BafA (Control + BafA); or 4) EBSS plus 100 nM BafA (Starve + BafA). Cells were labelled with anti-GALNT2 (Alexa Fluor 488), in combination with either anti-GLG1 (Alexa Fluor 568) or anti-TGOLN2 (Alexa Fluor 680), as shown in Fig. 6, or were labelled with anti-LC3B (Alexa Fluor 488), as shown in Supp. Fig. 6c. In all images, cells were stained with DAPI to label nuclei. Fig7_GALNT2_GLG1_TM9SF2_TGOLN2_GOLIM4_SDF4: Widefield imaging of HeLa cells left untreated in full growth medium (0h) or cultured in the presence of 100 nM BafA for 0.5, 1, 2, 4, 6 or 8 hours, before fixation. Cells were labelled with anti-GALNT2 (Alexa Fluor 647) in combination with either anti-GLG1, anti-TM9SF2, anti-TGOLN2, anti-GOLIM4 or anti-SDF4 (Alexa Fluor 555). In all images, cells were stained with DAPI and phalloidin-488 to label nuclei and cytoplasm, respectively.
description: This study was supported by The Max-Planck Society for Advancement of Science. AD received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 896725 and a Humboldt Research Fellowship from the Alexander von Humboldt Foundation.